From beebc433d07cf4078c7c30635b7e890a05659af6 Mon Sep 17 00:00:00 2001
From: Magnus Pedersen <magnus@hvass-labs.org>
Date: Fri, 9 Dec 2016 12:09:18 +0100
Subject: [PATCH 01/61] Added Tutorial #15

---
 .gitignore                             |    1 +
 15_Style_Transfer.ipynb                | 1111 +++
 README.md                              |    2 +
 images/15_style_transfer_flowchart.png |  Bin 0 -> 797339 bytes
 images/15_style_transfer_flowchart.svg | 8993 ++++++++++++++++++++++++
 images/style1.jpg                      |  Bin 0 -> 21516 bytes
 images/style2.jpg                      |  Bin 0 -> 110449 bytes
 images/style3.jpg                      |  Bin 0 -> 145653 bytes
 images/style4.jpg                      |  Bin 0 -> 71557 bytes
 images/style5.jpg                      |  Bin 0 -> 79913 bytes
 images/style6.jpg                      |  Bin 0 -> 39338 bytes
 images/style7.jpg                      |  Bin 0 -> 93471 bytes
 images/style8.jpg                      |  Bin 0 -> 69146 bytes
 images/style9.jpg                      |  Bin 0 -> 129584 bytes
 vgg16.py                               |  186 +
 15 files changed, 10293 insertions(+)
 create mode 100644 15_Style_Transfer.ipynb
 create mode 100644 images/15_style_transfer_flowchart.png
 create mode 100644 images/15_style_transfer_flowchart.svg
 create mode 100644 images/style1.jpg
 create mode 100644 images/style2.jpg
 create mode 100644 images/style3.jpg
 create mode 100644 images/style4.jpg
 create mode 100644 images/style5.jpg
 create mode 100644 images/style6.jpg
 create mode 100644 images/style7.jpg
 create mode 100644 images/style8.jpg
 create mode 100644 images/style9.jpg
 create mode 100644 vgg16.py

diff --git a/.gitignore b/.gitignore
index 6b5cc2f..fc3ae95 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,6 +4,7 @@ sandbox*.py
 # Data for TensorFlow
 data/
 inception/
+vgg16/
 checkpoints/
 checkpoints*
 logs/
diff --git a/15_Style_Transfer.ipynb b/15_Style_Transfer.ipynb
new file mode 100644
index 0000000..0a0d57d
--- /dev/null
+++ b/15_Style_Transfer.ipynb
@@ -0,0 +1,1111 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #15\n",
+    "# Style Transfer\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "We saw in the previous Tutorial #14 how to maximize the feature activations inside a neural network so as to amplify patterns in the input image. This was called DeepDreaming.\n",
+    "\n",
+    "This tutorial uses a similar idea but takes two images as input: A content-image and a style-image. We then wish to create a mixed-image which has the contours of the content-image and the colours and texture of the style-image.\n",
+    "\n",
+    "This builds on the previous tutorials. You should be familiar with neural networks in general (e.g. Tutorial #01 and #02) and it may also be helpful to be familiar with Tutorial #14 on DeepDream."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "This flowchart shows roughly the idea of the Style Transfer algorithm, although we use the VGG-16 model which has many more layers than shown here.\n",
+    "\n",
+    "Two images are input to the neural network: A content-image and a style-image. We wish to generate the mixed-image which has the contours of the content-image and the colours and texture of the style-image.\n",
+    "We do this by creating several loss-functions that can be optimized.\n",
+    "\n",
+    "The loss-function for the content-image tries to minimize the difference between the features that are activated for the content-image and for the mixed-image, at one or more layers in the network. This causes the contours of the mixed-image to resemble those of the content-image.\n",
+    "\n",
+    "The loss-function for the style-image is slightly more complicated, because it instead tries to minimize the difference between the so-called Gram-matrices for the style-image and the mixed-image. This is done at one or more layers in the network. The Gram-matrix measures which features are activated simultaneously in a given layer. Changing the mixed-image so that it mimics the activation patterns of the style-image causes the colour and texture to be transferred.\n",
+    "\n",
+    "We use TensorFlow to automatically derive the gradient for these loss-functions. The gradient is then used to update the mixed-image. This procedure is repeated a number of times until we are satisfied with the resulting image.\n",
+    "\n",
+    "There are some details of the Style Transfer algorithm not shown in this flowchart, e.g. regarding calculation of the Gram-matrices, calculation and storage of intermediate values for efficiency, a loss-function for denoising the mixed-image, and normalization of the loss-functions so they are easier to scale relative to each other."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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enjE38pzYng+BZMQiI+jeiT1r8jiCjrnol2O3jayamIhVrRCtZl567zw/P/Hp820HVVY1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53TTOMk90/ZbpOOPE0Q8RVeHtN+8IoUdLZplrQOHle88xJ7hgDLuevW6hrNzd1dfgdr8hho6X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88gg/+MEPZmy/6qqrOOqoo3a4v6mcd95523W4+ad/+qddKjJ6oe6fz5XLLruMd7zjHaRp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\nDpqmNcu1m4PkMCGal+SwxhPv/AWSw5rSli1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bb721Wa67bt06XnzxRRYuXMi2bduOe6yi\nKNGt7q699lp+/OMf1+kaUmjRdBr6b2uaJr/61a+YOXMmx7v1LoUW9bN582ZOPfVUAPr378/mzZvj\nHFGM8bKihRBCCNEGmKbJZZddFlNk8cc//lGKLBrRsmXLmDBhwlH3JdZ1nZ/+9KdSwd+EHA4H55xz\nDuecc06zXnfWrFkxX45Gjx7dZJP7UPPlKicnp8nGb4kGDhzIwIED4x1Gm7R69WrGjRsXvUE5YMAA\n8vLyyMvL47zzzsPtdsc5wvZDcpgQ9Sc5rGWIV/4CyWGidTu8Xcjh1Qw6duxIbm4ueXl5ZGdnt9kb\nsy1Ne8lh7SF/ud1uhgwZwpAhQ+IdSruwYMECLr/8cgzDQFVVhg8fHs1hZ555pqwedgwbNmzgrrvu\n4r333qvzObZts2nTpuh2d2eccQYPP/xwmy1CbMt+9atf8fjjj8c7DNHMpNBCCCGEaOVs2+aGG27g\nzTffjPb9+te/5je/+U0co2pbVq9ezYUXXhhTZJGQkEBWVhbjx49nwoQJdOvWLY4RiqYQCARqrXJw\n++23xykaIepn2bJlXHXVVeTn55Ofn89Pf/pTMjIy4h2WaEaSw0RrJjlMSA4Trdm+ffvIy8ujR48e\n3HTTTWRlZbX4lXdE45IcJlqzOXPmcO+993LdddcxceJExowZ02jbdrVlM2fO5O677z7hFjcnsnr1\nasaMGcNFF10UM9crWrZvvvmGmTNnxvSNGDGCKVOm0KNHj5jtmrp06dLc4YkmJIUWQgghRCs3ffp0\nXnzxxWj7F7/4BQ8++GD8AmpjvvrqK3JycigvL6dPnz5MmDCBCRMm8JOf/ESepGzj/vKXv3Dw4MFo\nu3fv3lxwwQVxjEiIuvP5fGzZsgWXyxXvUEScSA4TrZnkMCE5TLRm5eXlfPTRR6SlpcU7FBEnksNE\naxUOhxk0aBCFhYWyakUd2bbNLbfcwjPPPFPrtcOrgeTk5HDmmWeSkZFBRkYGlmVRWlrK5s2b+eyz\nz3jnnXfYvXt3zLkLFy5srh9BNILZs2fHrGI0adIk3nzzzRa9NZhoHFJoIYQQQrRiDzzwQHR/boDr\nr78+uoe9OHnffvstf/vb33jooYfIycmhV69e8Q5JNJM1a9bwwAMPxPT9+te/li9IotUYMWJEvEMQ\ncSQ5TLR2ksPaN8lhorU77bTT4h2CiCPJYaI1czqdDB8+PN5htCq//OUvj1pkMWHCBB566CF+9KMf\nHfPcs846i6uuuoqnn36a999/nz/+8Y98+umnTRmuqIMlS5bErEySnJx8wnM+/vjjmPavfvWrOuf9\n7777Dsuyom1Z8aJ1kUILIYQQopX63//9X+69995oe8qUKcyaNQtFUeIYVdsyYMAAnn322XiHIZrY\nxo0bKSgoAGr2Uv7qq6949dVXY75UDRgwgOuuuy5eIQohxDFJDhNCtGaSw4QQrZnkMCHat1dffZXH\nH388pk/XdZ599lmuueaaOo+jKAq5ubnk5uYyb948br31Vg4dOtTI0Yq6qkthxZFs22bDhg0xfUOH\nDq3z+V27dq3X9UTLIoUWQgghRCv07LPPcvfdd0fbeXl5zJ07V5b1a2Ty79k+vPfee/ziF7845uu6\nrvPCCy+g6/LRWQjR8kgOE0K0ZpLDhBCtmeQwIdqv4uJibrvttpg+VVV58803Of/88xs87mWXXca5\n557L5MmTTzZE0Uz8fj+GYUTbDocDj8cTx4hEc5L1qoQQQohWZv78+dx8883Rfd9GjRrFG2+8gdPp\njHNkQrQ9brebl19+mbPPPjveoQghRL1JDhNCtGaSw4QQrZnkMCHatj/96U+UlZXF9N11110nVWRx\nWI8ePVi2bNlJjyOaRyAQiGnLVlHti5RSCiGEEK3IkiVLuPrqqzFNE4Dhw4ezePFivF5vnCMTou3w\ner1kZmaSlZXF7bffTr9+/eIdkhBC1JnkMCFEayY5TAjRmkkOE6J9qKioYPbs2TF9vXv35g9/+EOj\nXaOp53pDoRCbNm1i06ZNFBUVUVlZidPpJDU1la5du3L22WeTmpraaNfbsWMH69atY/fu3Rw6dAjT\nNPF6vSQnJ9OrVy/69+9Pz549W9zYdXH4YciW4Ntvv2XDhg0cOHCAsrIykpOTycjIYMSIEfTp06fJ\nrrtx40bWrl3Lnj17qK6uJjk5mbFjxzJw4MAmu2ZLIYUWQgghRCuxbNkypkyZEt3rc+DAgbz33nsk\nJSXFOTIhWrfp06czffr0eIchhBANIjlMCNGaSQ4TQrRmksOEaJ/mz59PdXV1TN9NN92Ey+WKU0R1\nU1hYyGuvvcYHH3zAF198QSgUOuaxiqIwZMgQ7rjjDq644gocDke9rxcIBHjiiSd48cUX2bx58wmP\n79SpE6NHj2bq1KlccMEFcRv73HPPZcWKFdH2u+++S25ubswxbrf7mP9+oVAIRVFOGNOxbNu2jczM\nzDofv2fPHh566CHeeust9uzZc8zj+vXrx80338ytt95ar/dq586d2b9/f7S9YcMGBgwYgGmazJo1\ni5kzZ/L999/XOu+BBx6QQgshhBBCtAyrV6/m/PPPj36I7927Nx988AEdOnSIc2RCCCGEEEIIIYQQ\nQgjRPixatCim7XA4uPbaa+MUTd08/vjj3HXXXXU+3rZt1qxZw7XXXstjjz3G22+/Xa8VEb788ksu\nvPBCdu3aVedz9u/fz/z581m6dOlxiyGacuzWxLIsfv/73/PII48QDAZPePyWLVv45S9/yRNPPME/\n/vEPhg8f3uBrFxcXM2nSJD7//PNjHtOSVvpoSrJRjBBCCNHCrV27lnHjxlFZWQlA165dWbp0Kd26\ndYtzZEIIIYQQQgghhBBCCNE+2LbN8uXLY/oGDx5MRkZGnCKqm4qKimO+5vF4SE9PP+YqB9988w1n\nnHEG27Ztq9O1Nm/ezJgxY45aCKFpGp07dyYzM5OMjAycTmfdfoBmGLs1qaqq4qKLLuKBBx44apGF\nruukpaUddSWSnTt38pOf/IQPPvigQdeurKwkKyvruEUW0H4KLWRFCyGEEKIF27RpEzk5OZSXlwM1\ny5z9+9//pm/fvnGOTAghhBBCCCGEEEIIIdqP77//Pvow3GFnnnlmnKKpv5SUFPLy8sjNzWXw4MEM\nGDAgpsCiqKiIFStW8Nxzz/Hee+9F+0tLS5kyZQorV65E07TjXuO2227j0KFD0bbb7eaOO+5g6tSp\nnH766ej6/92atm2bbdu2sWbNGt59910WLVqEZVlxGbs+CgsLo4UEBw4cYNiwYdHXXC4XW7ZsqfNY\ngwYNivmZ6uLqq69m4cKFtca5/fbbycrKit47sG2bDRs2MH/+fGbOnBl971ZVVTF16lTWrFlDr169\n6nXtGTNm8M033wCQnJzMjTfeSE5ODr169cLj8bB3716WL19Ox44d6zVuayWFFkIIIUQLtWPHDrKz\nsykuLgYgNTWV999/n1NOOSXOkQkhhBBCCCGEEEIIIUT7UlhYWKtvyJAhcYikfvr168dzzz3HlVde\necyVKwA6d+7M5MmTmTx5MgsWLOCqq64iFAoBNVt2vPHGG1x66aXHPH/Pnj18+OGH0bbD4eCjjz7i\nnHPOOerxiqLQp08f+vTpw+TJkwmFQixZsqTZx66vI1eaPrK447Du3bvXeSxFUep17ZkzZ/KPf/wj\npu++++7jd7/7Xa0iGEVRGDhwIPfffz8/+9nPGD9+PJs3bwagrKyMG264gaVLl9br+p988gkAWVlZ\nzJs3r9bW5t27d29VxUcnS7YOEUIIIVqgoqIisrOzo8ugJSQksGTJEgYPHhznyIQQQgghhBBCCCGE\nEKL92bt3b62+9PT0OERSP1deeSXXX3/9cYssfmjKlCk8+eSTMX1/+ctfjnvOmjVrYraMyM/PP2Yh\nxNG4XC4uuuiiZh+7taioqOC+++6L6bv//vv5/e9/f8KVRvr27cuSJUtISkqK9n344YcUFBTUO44z\nzjiDJUuW1CqyaI+k0EIIIYRoYUpLS8nJyeH7778Haj4Evv322/X64CiEEEIIIYQQQgghhBCi8fj9\n/lp9ycnJcYikedx4440xqzOsXLmSQCBwzONLS0tj2vXdluJ4mnLs1uLpp5+O2WZkyJAh/Pa3v63z\n+f369eOuu+6K6fvb3/5W7zieffZZnE5nvc9ri6TQQgghhGhB/H4/48eP5+uvvwZqlh6bP38+WVlZ\ncY5MCCGEEEIIIYQQQggh2q/D22gcyefzxSGS5qEoCqNGjYq2DcM47goIKSkpMe0vvvii0WJpyrFb\ni1deeSWmPX36dFS1frf6r7322pj2xx9/XK/zzzvvPFl1+whSaCGEEEK0EMFgkAsuuICVK1cCoKoq\nzz//PJMmTYpzZEIIIYQQQgghhBBCCNG+HW3rjaqqqjhE0njC4TAHDx5k+/btbNmypdZ/P1y5YOfO\nnccc64wzzohpf/7559xxxx1HXQmkvppy7NbgwIEDfPfddzF9+fn59R6nZ8+eMauUFBYWcuDAgTqf\nn5OTU+9rtmV6vAMQQgghBEQiES699FI++uijaN+TTz7JVVddFceohBBCCCGEEEIIIYQQQsDRV68o\nLy+PQyQNt2XLFl5//XU++eQT1q9fz549e+p1fllZ2TFf69KlC+effz6LFi2K9v3lL3/hpZdeYvLk\nyYwfP57zzjuPTp061Tvuphy7NVi5ciW2bUfbHTt2JBAIHHcrl2NJT09n9+7d0fa+ffvIyMio07lD\nhw6t9/XaMim0EEIIIeLMsiyuvfbamA+Jf/jDH7j11lvjGJUQQgghhBBCCCGEEEKIw7p06VKr7+DB\ng3GIpP62b9/OjBkzePPNN09qnMrKyuO+/vTTT7NmzRp27doV7Tt06BAvvPACL7zwAgB9+/blnHPO\n4Sc/+QlZWVlkZmbW6dpNOXZLV1RUFNMuLi6mR48ejTJ2aWlpnY+ta0FGe9HiCi0Mw6CiooLvv/+e\npKQk3G53vfeXEUKI5mYYBn6/H6fTSWZmJl6vN94hiVbCtm1uuOGGmP3V7rnnHn7729/GMSohhBBC\nCCGEEEIIIYQQR+rbt2+tvrVr18Yhkvr54osvGD9+/HFXo6gry7KO+3q3bt1YtWoV06ZNi3mw8EiF\nhYUUFhYyd+5cAM4880xuvfVWrrjiCjRNi8vYLV1TFvTUZ/ubo63q0p61uEKLyspK1q5dyyuvvILb\n7cblckmhhRCixTNNk6qqKjIzM5k0aRKnnXaa5C5RJ7/4xS+i1bYAN998Mw8++GAcIxJCCCGEEEII\nIYQQQgjxQ/3798fn8+H3+6N9q1evjmNEJ1ZcXFyryEJVVXJychg3bhxDhw6le/fuZGRk4HK5cLlc\nMefPmDGDRx99tF7X7Ny5MwsXLuSrr77ixRdfZPHixWzfvv2Yx69atYpVq1bx2GOPMX/+fAYMGBCX\nsVuycDjcZGMfuSXJiSiK0mRxtEYtrtCiqqqKjRs3Mn/+fDRDx6U7URUVGwvLAJkUPwAAIABJREFU\ntrBRURUnKhr8p2pKUWsqkGxsbFsBxQaFmuPtmvMs2wIUUBQURUEBTNPAsq2aN4UCtmWjoaDZCpqi\noCgqtqqiqjqa5kBBQUPBgYYdNnG6XJi2SXUkSDASIkIEVAtFq7kGtoKChcNt4k42cCYYWCroDg2w\nsSwNbBVFsYAQqurGtlSMiEG4OoxZ7caq9mIbCpZlYBgRLExARVedaKoDUNA0DVWt+dls28YyDWxA\nVWr6bcvGMiPY//lZbSxQLBRFBVuJVp/ZChz+W9J0FYdLw5mg4E4yUZyV2IoBmNFjbNuuuZ5tw39+\nL7rqoOZvzMLCwLYjmJaFbdWMbdk1vzbzPwVvqqKgqgqqomJaJqZpY1RD2K8SqXKg215UVUVTNVRN\nQ1FUFE3DtjUUam5iK9TEobg1dIcTTQNFDaMqYJlhjIiFYakoigOHw4Om2+jOEKoeRlEMbMUG1UZR\n//Musk0MI4RDd2CYYUJBk0i1jh1xEQmqhCMBTLMa0NAUJ7ZlY1s2DocDtzsRzdJxOXUUu+Y9qeka\ntqVjqpW4fBW4E6pRNRvb9v7nfWvWvFcUJ2AANigmkbBJVaXKoQMe3O5kLBNMI4yuGjh0C7cvgisR\nNJcNilHzN4KCZWqYBpjhCEYwghVxEgo5CIU0IoaCriioSjUOh4WuKVimiWVHcCV4cCaY6O4ImsNC\n0Wp+Z7atYYZdBP0uqv0ubMOFZZootoGmWITDYYJWBFXRcegOXC6F5I4qbm81ihb6z+/dAVgoSs17\npeY9YgMuwkGV6koXIb+OZRhoqOiahjshgjspgua2idgG4ZBCdaVCKOBEsbwo2GAbqLaKomoouoHu\nCeHyBVGdQRTVxLZUqiodEPFCxIkZVohEQFF1gqEqsMJoKIBW8z5VTRRNQ9UcaKoTO2LjdOho6uG8\nUfP+cyeYOLwhFFcQkxD+KhP/QReVldWcddYZnHnmma32f9aief3hD3/giSeeiLavu+46nnrqKfmw\nIprcwYMHKSgoiHcYQsTVjh074h2CaKDdu3dLDhPtXnFxcbxDEA30/fffk5aWFu8whIirEy05Llqu\ndevWxezpLkR7ZJpmvEMQcaSqKueeey7vvfdetG/t2rWUlJTQoUOHOEZ2bPfee29MkUW3bt1YuHAh\nw4cPr9P5RxaV1NewYcMYNmwYTz75JLt27WLFihV89tlnfPrpp6xdu7bWDf5169YxevRoVq1adcJt\nMZpy7JYoPT09pj1y5EhWrFgRp2jEYS2u0MLtdpORkYGiKPRPPZUeSd3wOBxErBBBM4yJB6+zIy58\n2MFQTSGDKxFTVTAsC9NWUXQTW7MJmyFCkSChcJigEagpmtA0dF1HVRQChw4RMkOoTg1UMKsNfDjw\nmCpJmhOH04XhcuNxp+NJTEVXdBJtBxmWF/NAgM7dunAoUsXWAzvZXr6bA1YxlieEw62hOxxggWYG\nSe8TpO95JXQ4vQLTY5OUnoCNRSSUgG240ZVqLGUPbldPrLCH8uIKigqLqfy+N1VbTsEs1wkFyqnw\nlxEy/Ji4SEnogs/VAcXWSUry4HDqqJqOYRgEgpWYpoXX5cPlcGIZIQKHSjGMajRNx1KrsXUDTXOj\nGDrBQBBbMbE1hYitYJqQ3MFLWnc33U/X6XWGH6VTAbZ+EJPqmuIVE8JGBMuyCRkmluXEpXciNaED\nTgVsQoSpIGiWUF0dJByyiBgQNhSCIYWqINgouHQVr9OBQ3cSCPqpqjIp3QJFX7o4+G0GiZEBJHi8\nJCT48HgS0J1ONG8KluVBtd1oioaCiWmFcPVIIqljRxISFXR3EV6XRbCiiINl1RwKOFG1dDqmn0pi\naoSkTnvxpu1F1SsxtAg4I2guC0UzMCJ+KiuLSE1KpvxQCbt3HKJ0ayrB4m6U7Uxgf/EmDlVtR7M9\neLVuhAIRbDNEWmpH+vYahiecSI+OaWiGjW1buJNdGOEOBFyr6TZ4BT0HbcabbGPap6BiY5iVYOvo\naidsuwJFN4FKSg4E+Hq1m8/f7Etm91FU+22qyotIdleSkRqg5+AD9Bhuk9LLwNTKMQkQtHWqA8lU\nlapU7jtIxa4yAgc7UrQ7lR27Eygpc5LqcODQNpORHiLJoxKuqiZol9FzUCYdBwZI7bMfX8dqnF6V\niGFimj4qizuza113Nq3pSaSsG8GKKjSjjAS9mqL9xewOluN0ppCRmE73HhqjprroNeB7HL69hCwI\nG2moBNBUGzQXiqKiEsGiO0W73GxZ1Z3da5MIHazEi4tUn4/MH5fS66wSkvoZHAyXsn+PzqYvVfZ+\n1xklMAiHEgGzHJflw+Xw4Eg9RGK/nXQbvhVvp11orkNYIRffFXTGLOqPVdIJ/34XpcUWmjuJHXu+\nhdABElQVxU6iotqP5Qqi+7wkJHXC58zALLPpmJ5MoteBQ9dQVDcOn5vM0wKkDdiNs9tWqtjLmu+q\n+HJRF9as3IrH46FDhw5yo1yc0KOPPsrvfve7aHvKlCnMnj1b3juiWfzzn//kn//8Z7zDEEKIBnni\niSdiChWFEKI1ue222+IdghBCNFhubm68QxBCiLg7//zzYwotIpEIL7zwAr/61a/iGNXRGYbBggUL\nYvpeeOGFOhdZABw4cKBRYunRowdTp05l6tSpQE3x+FtvvcWTTz7Jd999Fz2uqKiI//7v/45u/RHv\nsVuKjIyMmHZhYWGcIhFHanGFFqqq4nA4ANBtG82yMCMRwpEILocXhyuN5IQueLUkLHcQVbFweVJB\ndWChoaguXB6FqqAfiwi2ahOKhKkMFBGKGCiajqo5sCIqYcXEqbtQNRWDIJGUKhLcbpxmIrrhxWm7\nSXB5SU5Kw1RV0tPTSXd5cZRVoXkMUrzJVAWqSEhNJd3XlR2h7RwM70Fxm2gujbAZRKs2SHMkkqgH\nSE4pwdWrDJfDRHd5ceouFMtFMBSgqtqPohaiOZw4UjWssJfg9wm4LZ3qkInT0uiY1IGyKgeW7SLR\nkU6KqyNO3Y3X7cLl1tBUFcs0CGseQqFDpKa6cTvdGBGdKmcIW/dgWjYhMwND8aDqDnRsqqsqsO0w\n6CqmrmPjonPvFPoMs+k+vJTE/vuJJAZADWGZIWzbQFFsQhGbiAmhENi2SoIL0nx+sIIYhAjZAYJG\nkFAAzJCDiGETDFoc8ttolTaq6sTttHE7Izh08EZMEgMqxgEoVTWclodERwrpvgRSU5JwOxNQcOH2\n9UR1e1AcLpxuB26vio2NLy2F5IxUvBmH0DNKSexczaGwRkVphMqDfszqalJ8XjI6ukjv5ichpQpL\nqSas6EQUgzBBDIIohNAsB0GrmDTbJLWPk51d/JTt8JPWvQ/9wt2prqiieAdoRleqKyvx6DqdOqTT\nNS0Dd0klqbabBF8CVXaAIv8BUlMysSLdqd7ZAyu9kr6nhtGTHQSsClBsdDQUs4qIXYymR9BVhfRU\njUCxSVGvHfRM60Kl00ulmoQXi6o9W4j0rCRZqaRHRiVKSglBy8ZfohKwOuN390dzeEEPkpqailId\nxjJMOqT68B+CUJWH0pIyDJdOamIaCSkqYcsG/QDpnVPpOsAPbqgOH8RSq+jUbzddMv107m+y4TMo\n3uqhsjTIvso9BHU3aR26kZaYQYbHS2dfJd08AfqkhXF30Qi7FSIEsRU/immhqGFsRccAFA6QkpGK\ncaiaQzsTOLDfh4KLSGWASKkbn9WHAX1MKp0hdnXfiubykOBKpWx7AC3SEawUErUOpCYk4utUQfJA\nldRB+/B28uByKCgRN2lJvVn3noNQVSq6J5kqilHCKh0TulKturGscM0WH+EqXO40EhM60SGxBx18\nnUjo4MKZHCLztDQyevgIq1VYnoN07AgJXUJoqSFsVaXLqS5Kt+5nw4YKVFXF6XTGN5GKFu+5556L\n+eCdl5fH3LlzW/UecaLlKy0tjXcIQgghhBBCCCGEEEK0alOnTuWuu+4iGAxG+5555hnuvPPOFndv\nYPPmzTFzgl27diU7O7teYzTVipIdO3Zk2rRp3HDDDVx55ZXMnz8/+tqbb77Js88+i8fjaXFjx8vQ\noUNj2vv372fjxo2yunqctbhCC+U/W3sAVAUPcUjz4tQ9WLaGpnlwaUl4HIm4XYkoXi9oETQlAafb\ni9PlwrYVqqrKSEn0YtoRQpEQGjbOxI5Uh0I4nE50hwvTUIiEwaHqYNWsiGDZPhyaA7crFYftw4EH\nr8NJotNF2LbRgmCaNi7VgytZJVAexKO66ZXaE0coESuo4w6pVJolBI0qNAwU08D2J0EgHcWoQKUc\n2zYIBcvAFUFVXYStAIoGllpF2AoQUXy4vRm4tWSqgiG8Pg+m4uVAcSmq5sWlJ5KR1omM5C7YJkQi\nAbAMjIiJYkZwKwa6aqHZJrYZxFZCqAkGttvC4Xbh0nXQdXSXmwR3EmV7nYT8Foqm40rSSO3kpEt/\ng64/3oevXyHhxEIiShm6atRs3YGGopiotg2WE011g+nBMi0C4f3YdhgDk5BtEghbGEEFOwyWUbPF\nhsuhkZzkxam60PUAthrCNEF12Oi2ghJWwHTiciST4Egj0evE6/Ti1hNwaD58KW4caSpKQgBnsk1i\nmpOgFcGhH8SbmI6vUwh3t/34MsIo7EfNKMVbEcT0u9CxScxIxZtWhebxY9shNDUCZgiHbYNiYSom\ntmLVbEth2bgjQRK6lGMZXpK6lKEF3ejBLmgDz2TLRgMMP17Lix4Cq6wYrxIm3evFVlT8hgdnSjq+\nXlX4VA9KZAhUpRMq34orzcLtOoSmWKh2AMMKoKsaIdPECLkp32ew7ZtSHFY3ktPLSEhz4zyYRHVZ\nCDPoo+xQAjs3VGKZIZwdDCqDDuxDSbjdaaSmpNNhoI9IZggsN+nbQji/DrJrUwi/EQDVRHe48aUm\n0bVXTzr18eHqVknaKRppPQxst0nA2o+pRUAz0TSDxM5BMu0Q/uJi/Ac9HCq30D3puO0eJPsySE5w\n41GDBAM2m5bvxqh002lQOol9QugdwmhOHdsExXRgGV4U04OiKbjVDvg8HhJ8CpUeN27NjVWtEAkp\nhKsUgpV+zA4GCekW/UeAwl6K9u1BDZ6NS+2Irh/CnRAkpaOfjEw/zvQQrgQVXXNi6woeXxWWGqay\nuhJ/lYY/UonDaYNuYuoKkbCGbrtITOmGN9FJkttHCgqpiknnXpB+WhU9h1SQ0s0gaFVgO/yglaB7\nD6C7KsAKk+AyyOjiJiFJj8lhQhzNa6+9xk033RRduuy8887jjTfeaHEfwkXbsmbNGubOnVuvanUh\n2pPMzMx4hyBOoEePHpLDWgDTNFm7di0AmqYxZMiQOEckADp16hTvEMQJnHLKKVL02gL4/X42bdoE\ngM/n49RTT41zRAIgKSkp3iGIExgyZAglJSXxDqPdO3DgADt37gRqnmru2bNnnCMSALre4m6xiWaQ\nmprKDTfcwF//+tdo39atW7n33nt56KGHGuUagUAAr9d70uPs378/pt2rV696nf/1119Hc09T0TSN\nJ554gtdeey06Zx4MBtmyZQunn356ix27ufXr14/MzEy2b98e7Xvttde477774heUaHmFFkeqDoXx\nawY+jxOPJwWXJw2vNw3N4QJdQ3U7QNOxIgpoNqrDQlEs7EPVOBxuVMvGMG0caPh8HXA6gyiaisPp\nRlUcYGsoio1phjAjQaywiW65cSseNMOJrjrweTykel1UR0IYRpiQqaBpLpxOlbBtoBkqHt1HJ19n\nArpJ2KrEsIKEDT9WJIjLVgn5bSr3OUjcm4yrUxp2skXErkSzTHS82JaBbWtEIhHCloERCmNFQujY\nqGoY0IhYBkErjO7woWg6FjVL/mAClo1iWZjhAIoZwOGMoOtVNVtQeJ04EizcSSqqT8GbruJMMFAc\nAQCc+MDjxr/fi654SOsWJnNQFUk9t+HttQEreSthtRTTDKLabrBUTMPCMm1My4FqJ+BSvViWjhms\nxh8OYWtBLA1CQHVYxTJUVMuBZZlEjAjhMJiGgu2wsbXDeyRZqIAZVIj4FaygE4eWhEv3oduAAZpT\nJTnVTXovG2fXAHbyIRyp1SSkKRyKVGGY5SjuNLQ0HS1tN6bbj6rsx6VXoHnC2CEnZrgCJTGDiNPC\nJIiFiW2H0QAFsC0bCxtLC2Pah4hYBrYSwuuNkNwhE5+RjiuchjN4CmZ5f/ZqW0jydSfBTCdc4qfC\nfwCn10K1/VSbBn7DIuKqpMfQClyeciJlSdjBPhTvtgmppaR0j6B7irCVCgzFwh9yUVQYIXIQdqwL\nsXO9SY+MTHr1r8SZ2IGSEi/7doE7PYNwKMjWTQYleyJ4U3QCIYV0Vwe6n5JBag8nyb0qgCIMW0fz\neSg7YLNt7SEiARMcNopDxZ1sktHPT9+zg/i6l+HKKEfxBghEKqmsLkNxWGi6hUMFh9sgIbkaX8oO\nbNuFYnalU9opBF0d6JCchjfBAtuJVQW7txykrCRAZkk1/cwqOvlUcHgI+C0q9luEy73odEJzWBiB\nDMKlSWiGA1110a17F3Zs+Z5gxIW/3MOeTUF8WjqO9HKSOlgkd6/AlV5BsHQQGN1AsdEsPy7nIVyp\nASy9GoMQYGHYFqHIPnQ9lWCklNIqi0NGEDsYxulRcCT40N0amqWR4EnB5XDhClfhsstJ7RCm98BO\ndDnDT3LvXaiJ+9GtAA4F/GY5lhLAJIhphQiF3WhaEqraolOqaAGWLFnCVVddFd3Lcfjw4SxevLhR\nPjQLcSwffPABkydP5o477uCPf/xjvMMRQogGufPOO7nzzjvjHUa7V1FRQUpKCgAJCQlN9mSTEG3N\nkZPwIn6WL1/OqFGjgJobx8uXL49zREK0Dkcujy/i56mnnopuPzVlyhSeeuqpOEckRPv2//7f/2Pu\n3LmUl5dH+x555BFGjRrF+PHjT2rsXbt2MXnyZFatWnWyYdZ6KPTQoUP1Ov/Pf/7zScdQFx07diQ5\nOTnm37OqqqrFj93cLrnkkpjfyeOPP85tt91Genp6HKNq31r0XUFLdYCWhMvdieTkdDwuH15vIoqi\nElFMFM2JpqlYRphw2EBBRdcsNDuIFTExIxaKAS6nB6/Hh+JwEDEtdN1DQkIybocTE4Ow6ScU0rEC\nJk4rBRdgh0BHxePT8SZ5UKtVQiEDywRLUzA0Fe3/s3evsbZddeH3v2OMeZ/rvvbt7H3up3daKAIi\nRPznjyAtICkkiNcaTQxGMXJTIgmSIEIwfQEYIiZUXwghXp5HqShaJH+IiPahQAttT3t6eu5n39d9\nrXkfYzwvjk8jj4qAwillft6tMeb4zd9ayR57r8zf/o1mQDbJsfmcRtxhVfWZJn2yckRmFGlaIb2Y\nJCnYPZ/jP+rRXO/hNHbBM1gqhKlwFBgDVjsIK6CsKBdzKHKUEkynU5IiRyqDFhUaw2yeYLMxnlJE\nvoNSAjAYm2LtAuFMCPuCeMMjPiiJNgxeyyHqpbhxjqEiTzyKUUFOH+WHKOOwdHzM2jMfQ/buRzee\nIJMjSiNwVBNHtDHaQVdgSoXvNHB9HyEUZVaQ5ClJIlChgMCCECBAOAohFcZa8lQwXxiSeUIcSaIG\n+IFEKY2rBYvcUswlOnVRuEgsorRYleG0PdrrhrUbc5yjI6rWEOIZQSunKqYU1QzP20GFPsafkTCg\nsgOEM8dtlNhIIYoR2p1TqAhHAKIEa5HSp9IJpc2pUGhGJHaPzJRU1iNgjYZ+NmJyAJlsUE4PMdlx\nyMdTlLuKK5fADYniVdzAsjPeIUUxDUqMt83xZ1a40TaL4TH2zh5i++IK4/0K3y1QazvgLdBWsDUu\nePQLJaMnXLbPCmb7McdedIDjt6Q0WhOmU4eVIw7bWyucORkyPBuxd7GPlAukWhBeG+CGHo2lKVHv\nPJpTOCii4Qpu2CAvM3TRxYiAqkxAjYhW9unevCBeGoNbUpQ5Nh9iqhwjwFQShMTYHPJ9ksWYdNaF\nYp1u3MXGlkOHSxp9gRYe890+e49fy4Wzmxg5oLWm6R4WuLbN8ELJma/mzC936QXX4EcKazosdgJk\nLogjSavTQouSeRKwe6FBVlYcUms0b5wgG1PiANaPrLB1PkQumpRakc0SyklGVWqqssJWBdoa0gSS\n2YLQD5AMKYqKyiom+3MOHz1Ap3MAR8ZQGSJ/jSqDan4OW40IXMvSRkr3QI6KZpTsIdQCF3ApyW1O\nZVNKW1ClDarcw5qn9JZau8o+97nP8drXvpayLAG46aab+NSnPkW73b7KmdWezv70T/+UO++8k6Io\nuP322692OrVarVar1Wq1Wq1Wq9Vqtdr3vNXVVT7wgQ/w8z//80+OGWO44447uPvuu/m5n/u5byvu\nxz/+cd7whjcwmUz+R/JcX1//utePPPII58+f/6Y6W/zVX/0VH/vYx76l+1lrv62O33t7e//uPR84\ncOC7Fvt7xVvf+lY+9KEPPVkoMplMeN3rXsenPvUpXNf9tmJ+u59r7Yqn9FPBMO7R7R9kuX2QZhji\n2gJpMrSwCFyQ6kqbfkp0lZBXJdYBXSRYGZBXJUa4tJshlcmRUqBQuI5HI2rTDGOSdIowGUhF6bo4\nqkXQdFDKQSDR0jI0BVErxMs0FBZXKqxwMU2DZoHOpogsYbm7SpFvUGW7LDKFV0UsTITWCcV2hX8y\no7NcsNQfkMaa1Ba4IsHxJEo6eG6IKCtMKVCLEDNrMBvnTGYplSiQQlCUKb7TRzgBwvEwQlPZDKMF\nLqAF5NUcEYzoHdvg8AuadG6coFY3CcImFVtkekiaJYi5QnjXsuL8EE44IUv2ketPUK19DhnvUsmK\nohQUhSJQyyjVxREufuDgxiGxr9AsqOyIhRiQzEdki4TYBSXAOKAs5JkhzQqy1JLMBfOpZDGpAIHn\nR/iexBELQiuQmYVMYUqJNBlWjFAywHUMQSxoHYhoXZ8gj1wi9fepRIL0KwIyGlbgMkUiMVgqY8lx\nENLDEQIlLaUzJTceSsQo5QELCgG5rqjEHqU7osQyLccYV1Bogam6mMnNPPbFkrgI2D09xcwvc+TQ\nMZQQBG0BjgHXJWwsI0TCw/90lkLktK9VbBwtafQfQHhjcuNQhW32JgIzXhC3E7pVQbgCMnBJpyl7\nZy1n7uuzs9nAbc/o33SZaKXCMWOWljscuOYIjz8eMk7XKIqD7JdTdjcvELc30Ss7OCc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fl8yHg4ZXt3h8ZoQbMFaSYY7glmSUamC5Qb0O8GrC73iUSXxWif049kREcdVq71QWQgCiQg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\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33gTFgBBCDkWJdcw5FdOb3b/7bVe/Zj9H+3R1sSF3pWJF3q2Mz93/Zs4fTPgzGPM3nqFa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m5BNNplsN4wPOZpbE2TX6aZ7VJPFebyKtJ4dNlg5h6aBC8ccajohMuknRWiqEsny+jHIdIadD0F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\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eRjd36Z+ss+WAaVmkwqUwM4RskmeSPEvRRA6GIEhhpo2IvBxjwcMLTnF+6++o/UOL5VGK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HOFjMVhg/pLcdUrJi7/JFdGdKXw8Z+A2GMiPWDbUcUEaKcjplshhzZrch2V/QTSXDrkD7OUWz\nZCvdptbrXHPMI6Y5pyaG7nDC/vkFgfDE8YL+0ZOs3VCR3VhgrWE1LTk4mFDpEQerC2SJwQnDaHfM\n4lzAeO8QWgzxzvHs1x29//0mZBNRnD+Ny2eEYotz5wTJVzYZDPoMD8X0ri+59UdfSmf7FI/9zYiT\n/3nEM095nt6r+cmf+J+xu1/n5Ogx5ueu5e//z5pBuImzF6j9ZeJuwrnJGUJ5QLJZkoYa6wsCIa80\nSexbqkkBtcIZTeTdlY1zW7MqPb5JUToCYahXIbPdDDtPWV2IqVaWqhAEwRr9/gbYEBWWJP0AZQfM\nxVmGg32wE6TM6XZ38StNlu2wKlPMIsf5kk44ZDGdUzcFUhoiZenHKSEBdtlQVTOach/iOSIeoOMM\nLWOkLAhiQ6J7pBsBenNIrYYU+WUm9ddokkt0jyT0xfWsmgbZRERmDVNLDsZLku4ewoekiWGoQ7r9\niK7fYa15MaWtWTaGRIzpb3UxOiQLIiIvkEXOcC3AzueELLDjJWefrOlcN6S7c5QmXFLZGVKWRDJE\nuwAhDEbOaLzF2Jqm8Sjp0QR408NV67hCUk1jqlGP6qDCjJdUs9MoJXHBOXzvK9zyQ4beRp+1TUnc\nsaxcwXxVEgQlmYyoVp4z52ZceNIwPiHQxRaHNg7RLDKKZokKJEpYFObKBAtb0hOKrixRxlMtHSJQ\nSJ0gCAl1itQZZe2otaGxDUoFhKliUU9IAgikAW+xdkG5mBOriCyOUUFE40OytZDLM0Oowqu9bLb+\njT3yyCN8+tOf/ub1gw8+SLfbvYqJWq1Wq9VqtVqtHxybm5u8//3v553vfCd/8id/wgMPPMAzzzwD\nwHK55A/+4A/49Kc/zc/8zM/w3ve+l5e//OVXOXHre217e5vbbruNRx999Dt+j/bYkB8cf//3f89v\n//Zv81d/9Vc4576lduzYMd7+9rfzy7/8y+1zfqvVarVarVbrX/ScbrTYPtJD6BEHkz3C2NFfj0kH\ngtmFPqOTEdPzkq3LGRcuFOxfWjDflRzsjZktcvpZj0GyybEjh7npxuuZXR4RBUuirCBOG/wAzl4c\n0802CeVxenqdZhIzvvwPVPEZ0jQlTQZYFgTBFF87JDGBDFEuQYVrBO4Qym+yWiou7I5ZlB02gl2E\nSogHivXtbfJZRbAyrK9v4/0tjGZnkD1HGinCeIzOFkSDPXR3Qe4rbFNjKoPJaxAGfIRtFKYWCKGI\n0pBwq4TkEmozRwcdZn+/YBhbjl4bctMRTSozzpytWKxicqswzjM6kZOfjdAqont0RdwtiHSBaXKQ\nJzl8VNNRDVW55PzuIdKLKavLSy5dtsxnfW7YvEg6sMjAU5UV0XjKqtqDxuOWHqUbgkChwyGqO0at\nnWFY38Rx8z9x4okVm7EmFV2GR/uk2RHOXXBUyxGrfahn+1T1k8ig4vj2BmfSJYPwRra3f4Gvnv0y\nj/0niQ6uY7RX8Lf/29dp6j7n3VmkKEi7hjp8mvUjFiMLCCU6FWilSAOBqQ2RCqh1RDlz5OVlpDZI\n4fFG4CqNVzHdbp80vRlJxKUTU1x9wKHhiiztozR4cpw0VHZGlniy9ZTeegJZzXAYUs4NWhrSOGHZ\nGGaTKWVjUULQSxOK+YSX/fcvZLkqOH3qFPPxiI3+NoPOGtPphNHBHkU1YnMtRQV9IpmhBWCXVHlM\n95Z1Nm8JSbYbimbM8NAKFY+JkLhJzN5X55gwI+p0UPRwTcCyWnHx4Osc3b4FHVqktKRhTDSImM+H\nZNH1ZGHDYvksysKqnhOFEZ0sQQvBslwhG0va7WKV49zlA9ZGA4IyQXccoa5QsibwnjC4MlHFUyFY\nEoUFQszRCuJAE7JAJJIk6VO4dYrZLZTVzRi3jS1HTKtH6R79Bre+3LBxfU4QerxwLP/LRJlhZ5NV\nUzHasywuC+Z7PexsnWKyoNxbInPBoHuMzs0D5rNdrFsRxzX9gaE3GOLNjGp1QD2HYLlO3czQKiB0\ngrIuaKqQXn8Lo0vm+ZjG1zQqQXa7NN5QmwKBIAwihNYsmxWrfEEgNaEKiHXEMAxJdDvR4gdJ0zTc\ndddd3/yn1M/+7M/y8z//81c5VavVarVarVar9YMnyzJ+9Vd/lTe/+c188Ytf5L777uPv/u7vAHDO\n8fDDD/Pwww/zile8gnvvvZdXvepV7cSC57E777zzO260CIKAn/zJn/wuJ2o9l3jvefjhh7n//vt5\n5JFH/ln9ZS97Ge9617v4uZ/7OYKg/Z2n1Wq1Wq1Wq/X/7TndaLG3d47JaEUygNpEZD5ltTzA2z62\nGDA6WzLZhclsQL5KyAtDYx2dXkCv02UQbxCrkGa5RPma4THJ8LAg6QuSOmXCApMrmmqDYhVy8Rtj\ntnoeOUxQwTZeJSzyk0RBTlUJmjrENhJsg1ASa8FZidYhSS8k6C4p/TnCMMGnCaWMEXGPzroiygK6\nG5skI8nZ0xexVjCejDiYHHDMl+TFBBGDx185hsN46kaQlwa8xBqJc4pOv0/hC2bliuUkYH83JZ+G\nHDmecuTmhBv/h5hOr8Pa+XVO/eecvTMJ82mHxYUxX//SRV5gUtK4hMBBoGg4wMuC2kn8QHLtSzwn\nz005dcLCWFMuO1x82nH8h2fEwYqo16DThm64pBrvUdQN9UQRhhalPFbV7NyYsh+W7E/22VtYirHh\nmuv77Ox0Ge7kRIMR7msps33LwZ7i4hMDDvmjrFwDK5CTFxDWQ06f/AZJdphT3ziBUFOKfMzsoEaq\nS0BNGElUUBP0FqieQHmDUBKHQgcSowwiApmATx3eOZK+pzOUhKFBeIczkny2oNPZYZjdjDTbTPZ2\nme2fRzQB3uUQlMh0TryR0uuu2NhWDNZLpHYQVIigRxilKClZTQzCpBhbAwVIRVkX5NWYIL2RwHu8\n8FgL1sJytaBu5gRRg4wTAtEjpE9gA0JV00ugnw3o3BSgj87xUYkwIfFGjlorCU3ItJAsliVr0Q51\nA1UFLgmRXc18fA4rjuN9Q11WFMsGHQQMh2tYvyJv9pnWKbbJcQ5MU1PUK7wFJwzKeEQJUglslFAv\nA5qFhkRgAhBaYrTFIZBENF7S+CUG8LLGywpEgCDF2QbpQXqJbQR5aXFFzqq8TNKbsXnEka57jCpB\nFnihcMLhfcUi95TLhNnljL0ziktnG2YXHNOLBbJQdGVGFMWkOkTHDp3G9LcXbB6fsX3c4WTC/KDP\n+LRjejomHGesZg0+L3HSonyHpshpghXO51hvWRWAC4mCGK1CnGkoGwM4+sMurqlwZYVUAhAo7ZDy\nOx9N2vr+88ADD/DEE08A0Ol0+PjHP36VE7VarVar1Wq1Wj/YpJS8+tWv5tWvfjVf+tKXuP/++/ni\nF7/4zeboRx55hNe85jXceuut/Nqv/Rq/8Au/QBzHVzl167vtzjvv5L777vuO7r399tvp9Xrf5USt\n54KyLPnsZz/LQw89xOOPP/4tNSEEr3zlK7n33nu54447rlLCVqvVarVardb3m+d0o8VqWjHfjell\nm5SNYdXA9GDMMtfMVlPO700x+zHGSZyNcMREsSBOU7LOAGkjfG1Q1hAmORs3JRx6oSbswXwqyUaS\nZhpQTzVVI5js5azNUqJ4QJ0H1E3JMl9SiBp8QjGVLHc1xTzAOoH1JciaMA7JeoaoO8L6KYaSRp2h\n0gWdrRcSKZBY5nOLOyU5e66gqSIm45zRXsVqHhFMBfGgxlBTeUctFcvCU+WeOBIEylNVDWXTUMwT\nLp/0XHoqZn4mQjagqEn7NYPjOelWRXxYM1vmlD7FR+swyzj5+C5pN0VlJWu6JFlvULrEiYLGAkqj\nB4K16xbEmymrvQFF0eH803DyHxK6yzFr187obTdEmaXXl+zvWcrGYWuQgaf0K+Khwu1LCp9gOYR0\nml7fcfhmy/YtOdFwRBl2uXQSRJ4xv9iBfMh4Nadc9FjM16nmKVUzxTWeg4MTWDfB+xp8SdOscL5G\nhSFRXKM6lkYIAg1IARKkkqhQIxHYjkA6Q9gRxKmiv+FIUohCiJTELfooDhHYQ9jFYaSNqedLjJnh\n5JT+hmdwVLB+tCEe1nTXLVFy5XgMKTsYpQiSHmknQgqLlhHGG4xf0VhB01iCMODpZ57GOUHT5CBA\nqJDalpRmgZMNQZwiXIdEdQmEIlGWTjeitxGQXlfiN8bU2iHoEHYaYllhxpJyWVNMFJgIY0sq4agU\nWB1AErAq5oRuijIpS/ZIsnWyLKasEpJIk4aaaV6jIo21jqIsEWiktMRKUSDQNkI1G6wupxQXQ4JI\novuGRtbkvqQGAi/xVtJYibUhSg3x1YpiAcZ08fU6ik1EsY1v1qgbRaADimbJWiLob3QJshwjHUJU\nWAzGG4TzVFWH2eWIybmQyZmI8emKxcjRLKAnNVksiWOHjB1xR5Ntw/DagrUb9lk/MkbpAcN5Su9I\nyOVeyP6jPZr5ZapmimgkQmTUKFZmQiMKkB7TNGAjkjDAOjDOgvRYV1E6iRIeGSq8uFJrpMWKttHi\nB8XJkyf54Ac/+M3r97///Rw7duwqJmq1Wq1Wq9VqtVr/b3fccQd33HEHjz/+OA899BCf/exnKcsS\ngMcff5y77rqL973vfdx1113cc889DIfDq5y49d1y++23s7a2xng8/rbvbY8Nef6ZTCZ87GMf41Of\n+hSXL1/+lprWmje84Q28/e1v54d/+IevUsJWq9VqtVqt1ver53Sjhct7FJe2mJFT1LvUVcFyAtPZ\nHrvTEZdyi5PrxFEPpUNiHdNLOzQ0oGJMDaapCHVNspkzvClg+EKLSAzleUeyCcJ7wtphvcMbBdU6\ntnAs50tsOKNqSprSQN5ldi7h8pNdxud6rFYepMOqCkJIehMILuCcoWlqrN4j3lzQ3+7TzXIEjoO9\ngoPVEh3PsUVEUcB4P2F0voPvDenYC/ikxCiND2KK3DK+rEhkSBZJrDUcFHPMYpuLX4k58zUNZUQn\nyrBmTFmNqWxJFC2Q62fJrk85JK8nHfTgpOb8UwNOfy2nUZYjzrJ9o4SewscVXjusdZSVozNM6Kx3\nmWQZxUozvqQ59eXDZNMD6mqMjkvSyBHHCUo4lsua3EGQZBgBu6Oc2byLtx0UA5QsCcOK3uGCtZun\nhMNLHI0S9DBieSrA7A6ZPL3D3u6MSSFZOIWMQzqbMZene9TNLs4vUVqgdcFqscC4nKgboVOHSgW1\nBaklSoPQHiEhjEIQYDAEgSPSkjizRH1Dklq6HcWwE9H3N1ItrmV2OWFeeYK4g4oEtt4l7NWsH0vY\nuWVAb8sjOw4RlFhRI7xHa0Eta8JEkQ17dLs5zUgiXYW1JbURWB+QxV2efuI0cSTpdTokWYSKIspy\nSeUqDBCoCIcmkpBIiGNFshbSvXFJtFNAZ4HVoII+PigIZEVdS8qFoikiSgfWWRpXYZRDZ30CUbJc\nzAnNHlEW0agYvKTT2ybQEEhIZMBoXoKS1GWNEZowDimFIIgFVodIlaKaHgcnBGknICQmPQY2mlMn\nBsIEVyqqaU6+bAh0RJpm5PMVi/0Ct0yJ3A467BGqLZr5NmaVEgU9qlpSNwHepQgsQno8MwqTUxqH\ntD1YVYwvlozPlizOB9R7AbaoyGRMR8UkSpBkK/S6pXPdlM41e3SOXiTduojNzqDEDmm2QxCvgXXs\nPzVGuQmqmSNqiRUTyCRNU2BlgxYSSYOzBudSKmMxtiGKNNiG2bIm0iGJ1ngB3lkKazDe/VfXtdbz\nw1vf+laKogDgJS95Cffcc89VTtRqtVqtVqvVarX+Jbfeeiuf+tSn+OAHP8gnPvEJHnzwQSaTCQCX\nL1/mAx/4AB/96Ed505vexDve8Y62gfp5QCnFj/3Yj/EXf/EX3/a9baPF88e5c+f43d/9XT7zmc+w\nWCy+pdbv97n77ru5++67ufbaa69OwFar1Wq1Wq3W973ndKPFai9gceYG7G7N2bMjuoc2UTajWYxY\nLXKc7BPGh1jvHiEUkjSQ9JKM3b0JC5sz0D28c4zmz/Lif5/SPT7H9cdYsSBKOmS9TUanxpgqo5P2\nyBTYWUKjCqRYQaeh8ZbVXHH+Hz2TpwImJ/rsnR6wOz7P1uENCttQMqe/PacwZ1FNF+kDwsxw5Jaa\nVJ+mkyjKwlJoz8ZIs7YmKIwlXwXMRppTTybU4Tb95T6dIyXRRkAoIkReMj4RsbrQIXYxWd9xECwZ\nn9ji0pPrrHYbQl1yqPtiEF9lNF6xO5qSXLegCZ5leN21XHP0RvaeaTh99hnWh4cZnc5ZzQVmHpMW\nEf7ai0RbK0y4pLYCYyKU2yEOd1CJx0egXZ9qfpz5E5eJB4bOzi55eIYoyxBKMroEi3HE0ePHyNYy\nvvy3K3rcTmp3OHPiMY5IxWq+jZVg0ylz9RV6/12GVR3KZcliN0JVx5le7HG2cUQ7kqhruFRcRnZK\n9HyKCiuiOMPPFOcuXSbMPC5MIFboWKN0jY8kVjq0cggtQUi8AKsdTnl0BjJp8KlFJIowTUm7G/SD\nLepgh2oZsQgcMkjI1gM2O5rh0RXdnRKflTTBOmmsETrBuwTpNXHUYW4mONFDygwhcuqqQ1U2VyYg\nIHFYDsY5G8MdpM9JQs1g7TDjhWFvfhGFI80GaC1REkyzh44j0o4mPlyz8aMrguEeKlSIuI9zSyar\nXToywYuEILGorKKpoRMGzPI5Yaw4evwmvvpkiVntU5oplnXiWLGaH6D1FioIUCIlYoCsFbPZDFtJ\ntDXEKibr9snVHC9ShBgQ4BmdmjDfH1Pud9i8QVOEmnR7wPqhw8zOF5z9yh7752YcObrGIlEc7Dt2\nz60oxhWDABp1QO/QHmnnEFURsZAHrCY1UQLTC4LOhkRtSFbBBVb1hKJQuNxQ79UcnFtjfKFgOdrA\n5B0atWIY9/GFpqwK0qxh+wWStZedJjp8ApnMkYTAGgYHag/RrwmuG+Ku+Sr+YkIyz5B1iHcTpNBk\nUUDjEpyT4EBJR1XXSB0QhCGNbdBKEYYR3kPlPMKCqWvyssQ05iqvmq1/C3/+53/OX//1XwNXfsD7\n1Kc+hdbP6a/TVqvVarVarVbrB97W1hbvf//7efvb384f/uEf8sADD3Du3DkAFosFDz74IJ/4xCd4\n/etfzzvf+U5uvfXWq5y49d/izjvv/LYbLY4cOcIP/dAPfY8Stf6tPP7443zkIx/hC1/4Ak3TfEvt\nyJEjvPOd7+RNb3pTe0RMq9VqtVqtVuu/2XN6ZygJhlw6U1LlC4zZJIkGPHv2WebzBC+GbHSG6KBH\nL8yIdYAyHjP3bGQdZrYhn+ZMO4ajRy0b1yuq8GsocYAmxtaHaaYx/ewGqBJGBxe5dOEst+TrDG86\nxlqnSzgMEcZQLW7GHcSYUQ+/SAhcidYhdROR6i7eaSYHMzZmfbobPaSSIBwihShdsrIHuDQk2xiw\ndSij16uwsxrb9HBVxO5Zx+EXXINfTHHTS1RySSUmdCKJbBLqg00Wu+ucWQXksebkqccoZk9wdONF\nvPTFP8EgPsTTJ86z+w3J2a9C2oO16yqitEaJpwm3ItaPT7HLNZTr45qE5cmCi1HJjq9YXNL0d/oI\nGXL2RIVc9AjFGr5ZUZcl0Zqhs96wdewmdCqYL+dsBT10oLHC0ZRd9p7tcemfhmxuHMNcWsN0bmZx\nMKOux6wdvpHx3iVG55esjZawtk4n0yyNQMyX5JMZdVnib96lmw8JkyGLYsSJM/9I3B/jsz3y2jI5\niCjzAK8lSV+SDRuirCaUkhqPFhCGkiiGMPHo0FGVHi8cUnu0hkA7kkCw1huy3t0kFEM0m0zykrpU\nJGGHeD1kVY9JN6b0rynZOB7R3YxRYQwuQtsuXiTURiBESuT3KGcF00sVTaXw0tDNusQGVo1haUoW\nZooQOcoKkmCbRB/CN+fQssI7R9VonEg5lG0i612EzokGgu7himjzLC5eUNQB0lqCYAMpMsJoE9Hv\nMrxGsvMiT35yH1OkZJ11miakKD1eGw7KETVLonRAZheEYZ8qX5GmA4bb17FfzOi4ozgbUQUlVkqM\nrahNhWkaKlFSyiUJII3GrBLGTyUUly3785okaTjNaeoFLCdQFn3qp6A7SKjyAObrdOkTJseZzC6y\nvDRHZ6doxC6VsVTmgHw0opqUrPYV6zcNMd2K3IYsl4bVRFCPQkYnPLOLM0Tl6KWSrDdgqNch8Ai5\nQKYFan2FSy/i9QiBQXhFwDqeFY0w2KAi2cx54X+MeHx3yXwWooymZ6YUsxIr+1iVYnQHr7rU1Rzt\nS4adkCgMWS4sznvyxRLpFUmQEAcRhAF1OUP49uiQ57vpdPot0yvuuusufuRHfuQqJmq1Wq1Wq9Vq\ntVrfjm63yz333MNb3/pW/vIv/5IPf/jDfPnLXwagaRo+97nP8bnPfY5XvOIV3HvvvbzqVa9CCHGV\nU7e+XXfeeSdCCPy38Zz+0z/90+1n/X3Ke8/DDz/M/fffzyOPPPLP6i960Yu49957ef3rX08Yhlch\nYavVarVarVbr+eg53WhRlAtWjLC2xDvDxYsHlGVIlh4ljrooFTHsbaAsZFFCJENMbhBixWKyR5YM\nGB7qQO880+ZJaPZRlcKhqZoanWoaJ1gsS+aLHGkd82lJz0iiOKbT66CrAUF6lIvGEDYZopaUxYRO\nvyYvzrF96CX0onVOPHpAtjYgiGesHa2JuxLnQwrrscbSFJZq0dBUlm42xHUHCBcwzxv2LpfsX4xZ\nzCSHREo3EZhgRreXsixWEA0QyREunDzDUl4gKtfohF2213bYPGzx1UUGaxrfJBycMVw8pNlfHHD0\nxgoXNJiwx6Frh8wvLFnPXsB8nDOenmLx6Jy9iaDW17G1s4OQKc+evEBPH2F8USCqkG5iSXp7xBtL\nesclyeEGmQrG05I11cGZmIN9WE6u5frhq1hdmjE7e44pXyOvDP045fLoDGnWYExOVZTIYsjsRJ+L\n/7hi8vVt5hdSJsV50usPM9s/jyouYd0CJWZIFlS2pKgbyqah8RFeQ9JXhL0GEV6ZGhEKCYCQgBR4\nwHhP1VypR4EkDj2x9qSBphMkBD6mKQRlXOA9eOdo6gBT1hiTk25AthkQdANEEGKMRdiCUHTAJTTT\nAFN3WC0lxf6UybMV83FEk89J4x7egqtK6noBFFinSMIhUiRMRyu8adDK4aUgChOybB3vE7ROsKrE\nhAbdl/hQkiRrIBOsz/BOEwQZyBQZK3rHNNfR4SAacvFJi9AdTOHZPzjLoqqxCiItWfiK/cWI4711\nFtMV2foGvcEmncEOJsop9hbk5ZKGGqE9zdKQpQqlweApjaATCbRzVIslrqzx+ZBS1FQ1eBvQ2ARr\nUsrC0TQKa0JcozAixsqK0jRYplhbsio9XgiqpkSMV8ynNeOR5tCZDtHGYSoGzOYLFlNDZLew8w6+\nCAllRq+zge5uUi8apDfEsSbIBJ3NAwhLrEjQokYwweNorMbJFCcbmnBK/+g6R34kQjQ10ydL3Mii\njWC9kxFrz1J5XOgg7TKZXMbVEqkzMCVxkBCFCukV0ntEWeGcw9UN3rVHhzzfvfe97/3mma5Hjhzh\nd37nd65yolar1Wq1Wq1Wq/WdCIKA1772tbz2ta/lS1/6Evfffz9f/OIXv7kx/8gjj/Ca17yG2267\njd/4jd/gjW98YzvJ7vvI9vY2t912G48++ui/+p722JDvP8YYPv/5z/N7v/d7PPbYY/+s/uM//uO8\n7W1vaxumWq1Wq9VqtVrfE8/pJ8SmzrHBEqEs3num0xVRktHJhsRBRkDIIMjQCrIwQouAOjA4XyO9\nJuv0CeKIy6Mp66N9wnVH1t1AMKAsLKt6SlHNWK08TWnoZUOiJEBFK3wwQQWGDjssVxK7UNRzS105\nZBTgvERKi2mm1HkM5hrOPmpIO44gHINYEWZLhK6wlcXWIWVpWBbQHxxBFus4v6D0FbWLGF/qUhpP\nrUOu2+jT2d4gn45I18CVNcv5koKGqjZsqE22N4fccEuH7ZtWLMYF0Uwi/RHKseeJv3mW619+DfPe\nkt6GJ+xINq/1NKtTJPMbOH8i4WDZY35QUFQC60PyUwOCKMPUfXbzECsjmvoyghnRwJOry2x2dwgy\nSyOgWATk04CO/GFCG+GqTab7IeVUkSpN46agBEc3DzHaO0FullSNp8g9lXF0loe59NiM8ekNptOE\ny8sphzYD6rLGMQIxIQhWmKaiNlBXkrrxOGdIO4psCEHm8frKxIpIK5wGKT3OQ9V4rHBUjSeMFUkk\nCXVNqAVpGKIQeONw1mEpUSpAyQrcCtdItMxQugbZgE8RNqNagjQCiaSeCi6dNCz2Z1TzHLey1GNP\nNa7BS4qyxjuBcwZsQ6QFeJAovL3SXGCxCO9xzuG9QUiDdRYZa3Q3Il6L6W/3iKOQSIOTGmyAR6NV\nAD5EaEky1MRBStQcZra3pBhL6jJnlRuc7OKjDRo0uZPETU1R5cgwxdYNSmkG/U28WjIeX2JRTnBV\nAaHFmJI46uF1g/EN3imcrBBqSW0cthH4OqNuEurKIoIUrxSlWKG9QxrwToKUKCUxVHilEcKBq3DO\nU/uSZVFiTcFsUbI/8eyNBDvXHEUEm6zKnLI0CHmYQadPdxChiUjCDFSPvNkloEFIgTUa72qkjRBG\n4OUKJ+c4LAYPfon3OV4oZLfH2osddVXR2Iap00jTEMoCYxTWAsrReE9ic9zcUhUFonboWCCbGokA\npzCNw1hPU+dXPu/W89bf/u3f8olPfOKb1w888EA7arTVarVarVar1XoeuOOOO7jjjjt47LHH+OhH\nP8qf/umfYsyV57vHHnuMX/zFX+R973sfd999Gi1cngAAIABJREFUN3fffTf9fv8qJ279a9x5553/\n6kaLIAj4iZ/4ie9xotZ3y2w245Of/CSf/OQnOX369LfUtNa84Q1v4Nd//dd56UtfenUCtlqtVqvV\narV+IDynGy20d2jvEULhVISSNVmSEqqAUAR0gozICXpRSBJLpGyoZU1lDVk3RWnFclmxNIZrRhvU\nhwVutYN1Gcv9CdO9fYrZCNl0SIMO3SwizBYESUXt9qjrhsRew4VTF1iM1lnNobYSlaaUy5AoyFjN\nl1RByfGdW5iPLLPzgnhQQ1jQCytE0NBUDuUlQq9wQc1g5widaAtCQykLVquE/XMBRRMT90N2XnCM\n9SMppy7+L/S3Mub7+4wXJUG4RiKuIdYJx18QcMvLBRs3FHQO4PQpjy/65BPNpacv8oKbt2imzyI3\nDNmaJ4gmpJ0Ri2f+CbV7DWHUpeuvRaoFjSlZHCxJUsP6oR1OXBoRDAW1b2hcQa0FC1OyWDrqaYVv\nHF6vcfFkyrH+S0ibDVQz45kTT9ELFddemxF3K4qi5uBSQl4lzMucyTime8mxaOZszWMm5wKmecZS\nxixcD7+7jxAKS0XFBBstWeYrjFGYUuMaiZKSwaaiMzQECVcaLbRFaYUMHFILENBYcBaMEMRaoAOJ\nkgIpJVIqLJaGGh1EeOfwxoFpwFR4m6IZ0ixrysmKMpCIUrA8MMhmwGKRMj3jOP3ElN0LUwJj6egO\nARLXlETBgDzP8QicUCgVEktwViOcBucQWJqywQuBNYbKLwgiTRAn2NAT9DI6m316a5v0k+up7d6V\nBiKpQCgUFukDlNSoMIBOSGdrnbgvMH5MWS9RQUAYrOFNgCtLKqdoZMXe+BzHt2JMHmF1xLCzRtOs\n6ASHWOkZjurKlAllsVWBIQKhwQc0piDSJcZ5jA2ojcbYiJWTKNHBKcHKeALnCLUCpRFAoA1aetAJ\ngQMtAkysKMtLOAV102BNgcBT7xYMuxlJtkYqFZ00RNkeG4OQQAf4RuCdJa8siBKlDcIHNKuMxaU+\n/V4J0QSnLE4EOJEBBd4twXm0TDDBkuSIYsNJZCiJulA8aaj2Z6h5TeIq8DnerNiUEbaw2FVFIiOU\n9VAsEd6ClOAExoJzJfh2osXzVdM03H333bj/MrXkVa96Fa973euucqpWq9VqtVqtVqv13XTbbbfx\n2c9+lg9+8IPf3MSdzWYAnD59mne/+93cd999/NIv/RLvete7OHLkyFVO3Pr/c+edd3Lffff9q157\n++23t4303wcuXLjAhz/8Yf7oj/6I+Xz+LbU0TXnzm9/MPffcw/XXX3+VErZarVar1Wq1fpA8pxst\nQg8dlSFUQGVy1noGpEELQaxTsqBDL9J0UxgMIRsYXLBkspgz35WcP7NLXXi2t65FNjmYOa5KWU0l\noxMNwWKNeq+mK3r0ttYJOgX706+ypXOcMeSLJc6f4/TpU+TL/5Eg6kNtmCxnhB1YTAq2BjdxZOvF\nDPodjh/xjN0zLBY1vSbDu5jVXCKMQ8gCnawYXLMgCMcMro9QTzv2l2POnN9jcmnI8Wt2iO06drbD\n+Lzj7GmP80vOn8oZnQkIbQre0Rsobrh1nRtuCyjjPeL+GsGg5BvPPorPI7a2Usa7+1z77xxBcgEX\nreh0hpg8Y9o8zkH+DEbcyPbOHaxtbuG8YTKe0PiCZGBIBpc4fXCRMD1O1n0Bp3dPcPN1h3n6mYsk\nB3P62w6lBywubfLoEweYcYQuY7bXM2qzgN6IzZvmWGOZLsfkJifyx7hwNsUEHq9yLnxll9nsCHnQ\nocoSogwuX/oGnYElV1MKNUMFNWVdIkyGNwHaJKTdkI1DS5KugVBgpURoCxKUdqhQI5RCIhEowqjB\nS4Physa/94bc1AQ06NBivWU5q1kd5ExHnsW4weSC+dITj2K0WFGOxzimFJOEuDnE4nLM3rkVe6ML\n5KsZ6/E2DQqnNE73kCak8ZbGNXhAyATlA4IoI4m7KAJWyyXlqkSnIdJ7cB7wGCkovaQmpqoHLKcb\nHPE7lHUD4RIdaJzzYAqioIOUMYIQzxq5jZnMl8xWB5TNAV6skLrP8NA6zXJOMx8xL8Y0i5h+GEJm\nSXpbRNk6RVwTuHWG8ZJAWy5VF8iyDrY0GFcRRAatJNprqGO80hgvWViL7HYpvMJFEQ2OpdJoaRC1\nQSuNlAJsRV9LlAzAKwQaj8V6Q5olOAqki+iv9ZEMCVVMFq4RpRtkaR9hE4S6TJzWaO0oVhXlfEYQ\nLVFGIH1MUPeZnWqIhjkyOw3JZZBgaBACRB0jrEaoCJ1M0N2c5AUx29d08C/TnP0/4Mx/WlGes/iF\nxdSKjX6AazyCFOdiytpS1jWShqZeUTuDUBJrBWGcoLW6yqtm63vl4x//OF/96lcByLKMhx566Con\narVarVar1Wq1Wt8r1157LR/60Id4z3vew2c+8xk+8pGPcOHCBQDm8zkPPvggn/zkJ3nd617Hu9/9\nbl70ohdd5cStf8ntt9/O2toa4/H4v/ra9tiQ57Ynn3ySD33oQ/zZn/0ZdV1/S21nZ4d77rmHX/mV\nX2FjY+MqJWy1Wq1Wq9Vq/SB6TjdadHTKmtrASsFELjAmp1xV+FAT+E0qNC51BOuO7gsqhteUiKhE\njnc5/48VyfQoarWBrxdgD8iiHvkCds/nTCd91vo30H3hNqt5h3leM1rMKYuKps4wjafOpwTeE/cq\n5GbGtHCwWNHxkot7nu0jh7FiRBX8I7f+x5uQw8scCo5Riy5NtWQ5npGbZ0gjBbEljgSDnRjVWyDN\nEwyCmMOLGaOLNarcYeUDducr6q8/SvPUmKj7ozz+T1MuPr7A7QsGakEvyFB0mR/sMttbkFxjyPMl\nWSfg0KGjLC4pRhcnpD3NNx6rWKst6bYlSg5YTveZLUKUOMbGMODI8Tmb15/CByvC0UmKckUnO8LC\nL1g8lWDLDKW3KV3M33zpaX705a9gNfoGZ0+cRPkuF75Rsd4TyOYiG72KW14cMQsvEW+fo7sjyKcJ\nfi3jh17xH/i//6+vsVGuIVYDLj31BPbSkiLMObN6hvjQFre+9OX8rxcfx7OLT/ZRQYH0DUkIde7w\nXmGVx4RLgq5DhFcmWigdIIUmTAXoBpRFB54skNR5SRgKdCiJpSeSjrgDUjQ0VU7RaGQtsJN9Vgd9\nZhNNsRAIV+GMYvesYf+CRQgDxqNMB+oF+bxhNa9xlUe7gFVTYKUkdiHKQ6MMhc1RWhGFMdpLvHUk\nskuoBlgdgy+Q9YrG5DjtkbGk9FDMxngy/EjgzyiyrR0OHTtMfCjHiTHWFCi1QAdjhNcIF4CLqYsu\nq5Uk7R+lsykwBsI6YeC6hFFC4RxVM0eYJaVb4vQML9coyhxEyrB7iCM7xxnNHa4UdJXCuxlIgRYS\nnMNS4Y3EWYcLBY3UFFISZB0aD7VTGNMglAa/JAr6aB3TuIo8b/C5JXURVmmcrlm5hlXhkbLANpYg\nSkiiAd6G7O/uM9039Hs1O0cUnUGB7J1k7fqcje2IpkqIngqYXBzglz1snbAYz7C9fYZmTm2XGJej\nUVgrrzR3aE8QVGhVAQ0Cj9YFYeZR4Rr+ZwfsN6cx/zBH7CbEKqW7mTGZ7FKWIabsUy9SytojlcJG\nKXVjcMD6Zp9RWSGv9qLZ+p44ffo0v/Vbv/XN69/8zd/k+PHjVzFRq9VqtVqtVqvV+rfQ6/W45557\neMtb3sIXvvAF7r//fp588kkA6rrmc5/7HH/8x3/MK1/5Su655x7+H/buNNbes67//fsa7nGNe96/\nof11BAr+i5IcOEDDUUSl1PqAB45NqxAcGFoECZNGGkOxGpDWAgrqAwhGRQ2Gto9ITI40iJiCoJbS\nub9xT2uv6R6v6Tz4eRo5+P97zpH2V/B+JTs79/1d2ddnr71y7az7/q7retWrXnWBE3f+PaUUP/zD\nP8xnPvOZ//SxXaPFs9PnP/957rjjDu655x5CCN9Se97znse73/1ufuqnfookSS5Qwk6n0+l0Op3O\nf2fP6kYLFRdkSY33GYtGIV3ANAGhwKiATwNi7OldOmfwnAXxkSW1qVAeRmsjzjw6o64bhmbE7ADq\ncoIwLZoVLjl+Oa6IiYYRTlgmpaGqHLI/xDea0Ca0lce6gtWjK8ymC5YHDUls6cUJA9OnnpeMj6wT\npSln9h/m0hOHrK80VGFOYfZYmn1U0kIicSrDhj5SxhCfpGweJR6tMjwC5BUkJVWbY6pjLHY2OXXa\nMxjETB6ZsZIq1q8akqmYnh3jQ0mzbJjvNehxiaJhbb1PuS5pFzEupFiT8NiD55Cj4+RDR9mcpiyn\nzJcZXieMjjpWrjxFeuwbGL1LPjpAFgrVAIzZ3TlgtRezOthiMrH02g1Of61iWlusWmN97XJ8NWFl\new0V5vSyffLeLoPje5hsD+97NFUfKUYIGRMlCaa0NPuG2AxZqhrX84jQYpkyLx9mtF2wZAcVF+jI\n40pHJBVBxjTBI0RFnFqEdngsgYAUAi0FcSQJKhCUR6mAkoEsEjgCSeSJI4GQHuFBCk2oI2qjqKct\n08fOUe5p2umQmIjhMCMER1WPaRqNcCMkHmsjfDunMTOckKAUSiocLY0XBGHRAYINOGEIRCgnkfSI\nxJAsWyXujWkFCOuIRwMa77FSgRIIpdBRTJz0cE7SlANMtcn+Ez029DH0Csj0NKgGREwIAkWAoMHl\nJGLI1uaYcHFEJCXF4pBc9jG2RgiJCjlOOqp6wYIKYSckMqEfjUmziNXBJsEHjFDMXcWs3CfODYIG\nSBEhQSmF94HKVdS+xcmEONbgHMIEVADpBREC7QFr8K7G+4bGWmzbIJGgI7xURFGEiAQ67aFkwBQN\nGEOeJbhml1IucLJgeNGY0SVLxsf3yMZzIuvYSsao4RA/uQIz6zNbWmbNjLXKoluNagRGlHjhUSJB\nC4kXHusdWmtCEBiR4MUAnfTRawMufflF1JsVbuIRImV9Y42dHZgdWJYHjvk5R3tK4dsR2AhhPMEH\n5GDAaATp8rELOmd2nh5vetObKMsSgBe+8IW84x3vuMCJOp1Op9PpdDqdzjMpjmNuvPFGbrjhBu65\n5x7uvPNOPv/5zwMQQuDuu+/m7rvv5kUvehG33HILP/dzP4dS3YqHzwbXXnvtf9pocezYMa6++upn\nKFHnP+Oc49Of/jR33HEH999//7fVX/ayl/Gud72L6667Dim7j7x0Op1Op9PpdC6cZ3WjhU4a4mQJ\nrScVjjbE2DYQZxodC2TqIF+gN07D+i6mV9DMA63J0HKAUHOsbKn8KuVyncNzp8hTh15CUkrqhcXL\nGa4C30hCE0E0YLFfIUcSYSFQko/HhKNnqA9TXDEkkSMOq4ayXWLdKsvK8PjZRzmRHdJbV4R2Sjk/\nwNsCgcAKT6xTvBhSGE9RR7Rmjnce+n1WLumzs9twsF/jH0kZjlapi3Umj55kpSc4cbnm2GWKtKfh\n0FGcTTHGsL/vGZwIpP0lx69QBNvinMCfyVhWGWFyDMoE6glLc5Lg+6T9PvoixXjlgOTis7B6kqbd\nRevzWyOcOj3D8XzqZpdoaNkeCUY+4mBHsThds6w9bRyw5ZxiVhER8I2jahrM3EBRkCYaXyqKaaAu\nHcI0RElMWzQszi2wpcJna7hEkiEwGE6f/hoi3wE/J0QGtEIojfPgvUKqgEoM+dCgc4GI4fxd/YDQ\nIGRAKQhaIFVACE+UaPCWLFPEPYEPEFqPcxpMji16zM8JDh9qaaYJic7JVlKyXkxINtHVNnVZE0xF\nogKR0JimRsklhAoTLIoIEwzeh3/bokLjgSBBCE8QoHVOxipJuoHSKW1bIltHrhIi3aMVAY9HE5HE\nA7QaEMUZWo4oZg0HZwrSXso4XiVOKoIo8aJACMP5lRkMkWqI9IK0F7N+PCXrbZzftqaC+aQArwh2\nQGlS1Chmt5piLKzqhNit0BQpK/kYnKf2BTM75vDAE6KA15YgPSqKQIJIJMY1VNZQE3CLBQZBFGXo\nKMI4hfAK09ZYB22ocbbF+QZnLKDQPiHRKVke0/J/n5NIo/ClQYoGJVv6WcFoQzG6aEl+0TnU9mlC\nfw9CzSjfxmcrtLuCdrIkLEuWYk4rSkzrwARC1CAiCAiCVDgCPgQE+nzDDTGgIHi8LFm/LEKsB1xt\nMDjSZMnWXDOYaOanI9RDMRVDlodDtOuR6Zw4ypEaYtkSn80v5JTZeRp89rOf5d577wVACMFdd92F\n1s/qf52dTqfT6XQ6nU7naSKl5Prrr+f666/n/vvv58Mf/jB/+qd/inMOgPvvv5+bbrqJW2+9lZtv\nvpk3vOEN5Hn3PvFCuvbaaxFCfNtqCP/eq1/9aoQQz2Cqzn+kLEs+8YlPcOedd/Loo49+S00pxWtf\n+1puvvlmrrnmmguUsNPpdDqdTqfT+VbP6rtFUQ+ivCEIR9JWSKuRzqKDIpECrVpksosaPEnIz2FU\njQsphFWgIIklUZzQGkm7HLL36DZreU1aapq9GZEf0PgdTB0RNWMSn9JWCecenzD3LdG6IMkhkZZs\n9Sz9zQFulqGcxjoPkadsCg6nDXm9wMX72EjiTEGgRYqYpnR4WmKlQAXmVUFVaIJzVE3JMqTEq+uQ\nrLBcPsnh/jcYr6ywttpn79Q+V19zEVf9D8f6CyrSVWj3Fywe3uTMmZbDVnAskmSjGRujALGj9oZ5\nFXH28YzhkRcQiwGuKakqQ5YOWD0uifWCeDDF9GfYKFA3I6rqOGdPRfzLP03YTi4iSR+nlzas5nOi\nAHIHglDUMqMpl5yZnaSpanZ2TuKWJZFpWE1S+m6DtRay/gBlFctliWsWOG/xVlAsGhbTGn10yLIt\ncUEQfMlsdpKmdxadNxAFQpCgEurWY4xARJCPobfmiAcxIVFILRAqILQnCA9SojSgQQiJFhFSBLK+\nJO1pXKMpZwoz72OqFdpZzvKco9kbINp1snGPPNVIbUiiFeJolUhZgm3pJ4p+nGNay+H0HILT1P6Q\nlBwXLLWpcQ4ineCVwosGJSGOUrKkT+aHKJFjGkuzLPBlSZIJtBAkQuMEBBn/2yoQ0B8N6CUZy8ND\nsryhnOYM1hP0eAwsMEwRIuCDQ4olkT6DylvkIGElG7JxUUxb9FmcLvDG4RqFaQaUGqKxZnbyUYT3\nJEkfOe+hVMzmYBuX5CyzPpusszNJ8G2LVS1KGoQGGwI6ifHG0piW0jTI6SFCKvJRRJpkeBlhPJS2\nxjQBFwwei/MNFouWGq0kUijiRGJai7eAi4lshLMN1AW9Fc+R4xHHr6gYHF3S9h6lzfYQ/TmBFpUo\nBqqiGhTEWyv0fJ9lXaHziqA8QmikiFCRQnoB4t9eJ0Fgg0eG6N+2+mghCIJq0bkgyhxBWKQING1J\nPOojhylO5OSHQ+LRBrIOaJGzMjzOeHiEoi6ZN4dIlV64CbPzHbdYLLj55pufOn7961/fXdDpdDqd\nTqfT6XQ6ALzoRS/ik5/8JO973/u44447+KM/+qOnVsJ79NFHeetb38r73/9+3vjGN/LmN7+Z9fX1\nC5z4v6ft7W2+//u/n6985Sv/08d024ZcWPv7+9x111189KMfZW9v71tqWZbxhje8gbe85S1cccUV\nFyhhp9PpdDqdTqfzH3tWN1ok64p4HDDTFt9WuNqSJoLIBULt0Kslw/EBw5UFgxUwcURpYHy8x3K/\nYdCPqM5FiHnFgTugx+UIrcjrkrx0xBqqckqcH2c1XUXQUkjFqYdK2idbsvWUrWMDRqsJkdrHqUCr\nPHvLKVYpfFDgIJUZ4/QYpjI8fvIkOmoRQVJXnqZMME1ANi1CTVi2U4JXtA0gcmaLjK/9k2Rr7UVU\nw4ql36VdnuHxxQIRVukPjnHskoqVKx6n1LusHr+IaHiK5TDHqAFlsk/WP4fnLHILBhdnpE8OOPjX\nPU6obXwYIcwKqRxgXUkyXtJfEYjMMy0blpOcPLyEk/865v7/c8KpRxRu7FEmJ0Vi5xXNQcs4v4gZ\nE3qyh8wGZN7z+MkH+No3/omVPCMPMcU/wDXDH2bv4JAXvOgKLtmAL4e/5dSZ0xRFyfb2EQIRu+d2\nWJN9dvdPYuyE/qimv11gRUU8DLggaAtB22jqyuCdJMocyTDQW1OQekQcgQwEYRECCB4hBFKD0BBQ\n+KDRsUPGBqUcMEDXF9Puj2lmCcWsYjaZsVBjBskKXkhMXRGVU9LIsgwVIumT9nr0egMyHZGpBTa3\ntDgiEnLTQzpBJRqMC2idUSsBGESwRMQorxABXFNRLicU1S5W1TiVULU1cSTpyRjtA86fQ4iCOEno\nZWOk0gTfoHSNE1NqM0VFDSo6DsEhaIElXu6Qrj7BRm8NyRrarRHKPlk/YbIPSSEZ+BinFVUbyNZW\nMLMlh7NddK/H9spxzLJAyoiVwTYkhtOTDc7MzqJjTyQlVZOdX9UijqhCRBssCMhiia1KbDmlDR7r\nPAtjcBHgQbSe4MEFhVeSKIrI4phUKWxbEAuFkDG0gqqeE6kZ+VrO6sWajas8Gy9YILdqfDKFKOBC\nhsPg5YxsuyEe70PTQ8ttWpOyXCZE6Zgk0yD6BC/Q0uEwWBwQaKwAaxEiQakesZD4oPDCUYoWR0CF\nPpkesiwE033JYneEKY6wOBBIURNphQgprs0QNkOHCEUPaC/cpNn5jvrN3/xNTp48CcDm5ia33377\nBU7U6XQ6nU6n0+l0nm0uu+wy7rjjDn7913+dj3zkI3zkIx9hf38fgL29PW699VZ++7d/m5/8yZ/k\nve99L8997nMvcOL/fq699tr/aaNFFEX8yI/8yDOcqAPw4IMP8v73v5+/+Iu/oGmab6mtrq7ylre8\nhTe+8Y1sbm5eoISdTqfT6XQ6nc7/2rO60WL98pa1rcdZnLFkYYyuBjjmeJEQZUOGmwXjExPi1QKS\ngIwDWX+K8SXp+vexeTlUiwMe+9oClmM2r7qKdllw7vA0K9JT1nB2kqFXNVmqIY/pEZGqVYr6ORSP\n7XDyiSn7mxFOPEHkh1SzITvFjNKXjHoDzLLAzRI2o4s5ePgs1YrCxy1pHsh7ETtnFqxlF3Ow2+Jd\nQ6+3yROndxivH2W6N+TcA+tk7QmWs0MSDsl7fdowZt8/Ru/okG/unWH4jSnPH+/TP2II/a/jj89Y\njdehHiD9nKZq6A1SFt5BknLiec/h5ElDYJNTTx6y9CfJ1iKcOcboEo/EYpoaGQqqQnLywZrZE89h\nXY1Qw3+lPniIrWQDcxjx+GyKDJqqtrQyxQdxfhsIZ1GxQOYpNte0XkOd8MAj5xj3Ig7+9lHUWsbW\niat44OEvEyXw5MHjKKHJt0YsFzsoNSHpTVD9JdNQ0vYFxgeklYRW40pFjKK2oJAkiSJOWywWrEIJ\nUMoTKUekBIkEqQJEAe89tjZkqUGIQNtK6rklNJbFYc3ByRazlOTpFqOtNcLCIsUMlbasHN0gXY1Y\nVwolBcK1BLuPCIHNo2NWlkOS3owDYUnnEtsYpALvIkKI0NrQtAZ8IBICaT1SeBq7oPUTZDwjSmDm\nHb3BgIGEUeTo5REm2mC8uUEy9iTr/0L/yC7J2sNwdAc33MDFz0PKSwk4vAwEZ1A0xJEljVuqrMSy\nQxCrCHecLNpk8OSIYl7ha5CxRihPSBLaUKItBBGBkDRNgcwylNC0TcTa+BJ2Fo9RtxNEW5Mrh0wG\nlE2gNprgYkRwNG1L6Qrmsxq5rFFRDnHCbLmPqWbE0jPIhwwHFxO8Im4tkTE4ZyE6v52LFpokEaR5\nxMb2kIuvzrjohQPGz2lh+zSlqrFiirIxqpXoJFCLPRoscSqIkwGaBhH6hJ7C4XEYlA+M5Sqlb7Gh\nxvsaGzyRzhBS4YInhCVCKhYBZKWIXYqzMWUdo5Y9mqVifjpj9kSf2ZMSU1gG2TZ5tIr0UJSnUekS\nogOI9oDRhZ46O98B999/P3feeedTxx/84AdZXV29gIk6nU6n0+l0Op3Os9nGxgbve9/7ePe7382f\n//mfc9ttt/Hggw8C0DQNn/rUp/j0pz/Na17zGt7znvfw0pe+9ILk/Lu/+zuOHz/OpZdeekHGvxCu\nvfZabrvttv+w9tKXvpThcPgMJ7qwHnjgAba2ti7Ye9wvfvGL3Hbbbdx7771477+lduLECX71V3+V\n17/+9fT7/QuSr9PpdDqdTqfT+X/rWd1o0SSncZueJM7ptyv4c4HKNaRxQjxcJR446NW0UY1valxj\n8NYRpTHJ9kn8OUGVSFy2yiDb5mByQLAFUepI45z90zsE3SPtD+mNPSE+IMkNzWxMttwmL4ZM5wec\neWAP2buUfJBTVjWzumG0MkQ1MT0d4eqWf/7qaYZmQHxsld6Kxg8qqmSJKRSPP5Kw3M/BBfqDDCtX\nmE2P8cBX5px7XHBkZUQ7+hI/cGWGneScebKlmY9oyTiYSR79piHtNxyjZpQWJJFFjkpCpFEiIdRD\n9quK1oPMHQs3I+tfweQQ0vGc1Ezx5RIphhStQ1cNzsFytsbJBw55+B8t9ZknUfMcVTSMI0nkFlgT\nMVdDXJIwVyXeKoTwGBqadkaUKIg1S+eogmFloJG9lN3JFGaBNAyR9NCRxgfD4XxGvz/gssuPsHPu\nCZaTCSockicOlQakkVgHrtKEhYTCIeuUVCqy1BBHArxCuhYnwAvOfw+SSAiUDOggkV6CgJC2ZLkn\nEgJTSpppRLsL9dShTEysRuRyhdh6CnGKeK1k5Yo+W8/LGKxtIrQkuCVNPaGqStJohbXjmpFTJJtj\nRusp7aOB6jFJW3mME7TGImOJswHvBMpHRDrFB0vTzvE0hETiEkfqHGNvGOuY9ZU+65fktP0IlXl8\nekCycYbVy6eMji3ojyKidIbSDyNw4NcQCKSokKI8v32JjLGyON+IwgypKlhr6Z3YRp1ThIWjlwwQ\nTYXJlpRpS+1qpvVpirCOdzEJQ3yQKOcZRtusppdw6BS0ApEZmqaidZLGBFonsMFS+xZDA0EijMCb\nGlvMsaYlUpDqiFjGxCFByhhwGF9hQiAG87NZAAAgAElEQVS1koHyxELRH0nWL0sZXzHh6P8WkR1d\n0g5LXF7QuAVCtQjf4mwAZcEMIBYEPMYLrCgQMsdZcMEAFu8NlTjAEuMRWBvRWo+MInwZY40DHK0X\nLEtL7MY0zTr1ckgxSxBLTbUIzHdgfkbTTiLG2TYXXXQp1iqKskQkS/rbU5R6lOifJ3SNFt/9nHP8\n0i/90lP7LL/qVa/ihhtuuMCpOp1Op9PpdDqdzneDJEm48cYbueGGG7jnnnv4wAc+wBe/+EUAvPfc\nfffd3H333bz85S/nlltu4bWvfS1KqWcs3wtf+EKe//zn86lPfYof+qEfesbGvZBe8pKXMBqNmM1m\n31b7sR/7sQuQ6ML53Oc+x4c+9CH+9m//9hkd1znHX//1X3PHHXdw3333fVv9JS95Ce9973u57rrr\nkFI+o9k6nU6n0+l0Op3/v57djRZqih0EhASXL6i9wwZP4zyVaahNhcNRewtlg7MOiSJKBE7vEFLw\ncUzjLanZZrbYZW0tMF5t0a3BH+wjRE40VPQ3IvLVgqTvmZ81LPZjgpBUbUzxZMEw20RFPQx7LCvP\nxsYqy8IhRyPqVPGNcwdsZVvIswu2jiUM1wtqaUizderZZTzywBRFzIteeDUPPHA/uR6x+4ilOmxh\nuMOlV+3wvCuPMX2soigbpm3KTmtpTcJ8P2F/J2ZwSUNaSTIdIaIal0iEy1kcCIzXIKFpBUVtWRSG\nGEuSDEiSdVp7yObWxRTNSaqZoZ5ssDh7gof+6V849U1ws4fou8CaGjHo92kqT+ugDo6SikpaBr0U\nU7csqiWFWVCaiqw3IAhB4w1zvyQkkp3DA3qjHrZp2H14l6IokMGAkAgpKJsZJ/cfx+oSlQlCJME7\nVCuxjcAWCr+U+Crg2wilBVK0uMZTTSSiFZAGSAUOaKWg8eCDR4QIFSRSOuLMkcaBYKCZCordFLu3\ngl1khEZBiBBJIMoPGK4fMDzWsvYcyerlLVm/wguLMbvQ7hB5Sz9TRKN9EhmhhilJ1OfkwTkidb7Z\no3UG17aIpIcWDhcUMmhkiLDO0LQzfFTjZaAl0I8kvdDQTwWjzT6rJwbMhcSTY/ScqBfob1j6mw1Z\nNETIAsQuhAgPSBRKtBAaLA6HwgmPoyUEAwRCFjM6cpzhlqKZOrQbIeaKtreCGxQ0puSwPsvObEgS\n1hiLCCVTIikYR6tsDC6jmdUU9QE2KlkuDUHn2KAJIhAIWGcxoSV4C74ioHChJo1H9KIRidIoGRGh\n0FJglKURLc61BCBVkiRpGW3B8R9w5M+ZkT2nwaUSIyxBNHjlQCSARzoDVuFtihWSID0a0CJFuBjf\nQDBDgo2p2wOWnEHnA4TOsT7CtArTpLhFH1sq6mXDYrJkeWDIlUaZnLZYoZxntEsPHspZg1lKetGI\nIxuXYl1EPuiRr+SUvmF0UUkU75COluD/V7Na57vBxz72Mf7xH/8RgDRN+ehHP3qBE3U6nU6n0+l0\nOp3vNlJKrr/+eq6//nq+8IUvcPvtt3PPPfcQQgDgvvvu47777uOKK67gzW9+M7/4i79IlmVPe67h\ncMgP/uAP8upXv5o//MM/5Od//uef9jEvtCiK+NEf/VE+85nPfFvtuuuuuwCJLow777yTt73tbXz4\nwx9+xsasqoqPf/zj3HXXXTz88MPfUhNCcN111/HOd76Ta6655hnL1Ol0Op1Op9PpfKc8qxstggr4\nSOGVpxGHGN8QqT7BG8p6j7LawzpLYywhCFyrUUJA0zA/rHANyBBoq4rGL/BizvCIYLwypT7Yp8cC\nT062eYrB8YjNi/sIqfHikMZBG3r05Yje2YI8MWhZE1yDNRCToJXC6BE+0hRGMD3Xp14cYvca5lsp\njTJsHL+EyD2X6eSbKBHTy1/IV7/8ZTaHgThEjPoL8uxxnvc/BKtHDqhbS/qkID7IUQuLChGxHqFT\njxUFxkkyL3C2xoUIRZ9Tj5+k3x8gVU5TrOHtUfYOppzYzEmjdYLx1O2UOD7OzmTCzsmEw8cu4fCx\nKzhzquFwf59UzCDyOGmIeiPmVUqNpnA1s/qQuJ+zstHn3LkpB+UBxlUsmwWRjYjjCOcN82rKwfKA\nhV2i0NSLCY8+/ghtW5PGEZGUmKbgoYe+wtm9b3L8ipTeMAZpsE0LVYBS48sIW0XYVuJcTKQNqrUU\nE4cpFLofk448ahgIg0ArQMQQI1BSoGVASkscgwqSai5ZnotZnOkjFhv4WuP9HJ9MUaOC4WWH9LYa\n8s2G4bEZ8doOlpqgwMeH6HxBkiQMMocNM1AZuR7hZhmlmeOMpm48ZdPQNgYdReANUoAIEu80TVPQ\n+iUhtHgv8VaQZxGpbMk3PMlRie1piklKcDlBj0jtCBkfEvQC5BApJIEWKLEsiKQkEAjB4IJFogEF\nJDgM1pcoNSHOFvT7MVUGlIFCeJIsoR1kNKVisZzw5P6jHBlKem4FrVN6SQ8Rx6z3L2Ky3KWoDmma\nEmc8IjWIKCcoiQCEk9jaYE2BEJDEOVkakSUrZGqEChLvDUKI87+/qBGqJnItWgV0lJGtNIwuK1h7\nfgXHJjSJJaiEQExwEqliQtAEJC7UuHZ+fiULZ1EC0DFKJDgbCDZBVJuYecxk/3FmzSnGRzxRJgku\nwzR9qr0ezWGPdpJweGbJqcdq6omipwyZapC+oW0VZW0ZDjKCj0hUynh1jdXVbR4+9TC9DcHWxX0O\nGxhdskTJOXG/wc4v5KzZ+a86ffo0733ve586fte73sWVV155ARN1Op1Op9PpdDqd73bXXHMN11xz\nDQ899BB33XUXH//4x6nrGoCHH36Yt771rdx22238yq/8CjfffPPTvqXDTTfdxKc//Wl+4Rd+ga98\n5Sv83u/93vf8KgLXXnvttzVaHDt2jKuvvvoCJXrmWGt505vexMc//nGSJOFnf/Znn/YxJ5MJd955\nJx/72MfY3d39llqaptx444286U1v+m/x/Hc6nU6n0+l0vnc9qxstJAm27uNtTJpb0mxBiFcZDjUr\nay1pf4FQBa0tCR6EkeBbzh7UlHuS/ZOB+W5Cpi5jc2ubEC/ww130iSfQm6cYXyrYWr0KmTSk45rh\n9jp1PSBqJ/SlYrhxHF2MMUvNmSfPcLBXUdQlQyURpubY6jEW84pmWrMxGtCelgyS51Oc3mO6c5qQ\nepZnY3pZS49tTOu47wv/TDEdIHsDdLTL1tEZL/rf1+mN5zRJTVhTqPUUo1oiUmKfsLH5PDYvHuP0\nvzCrZsTRFsu5A7PJMHoJD/3zA1x0PGNr7YWk5rlQx3j7rzQLwanHluzN59ikYTY7yaSEcm/A3iMN\npx9+kPXRGsvl1xiOh8R6hdN7Uy597hEO907RygVONrR1QeaOkeeC2i/YK86h00Ay0DT1HFMBSiGT\njEfOPMzaxoBJscfk7ITW1JhgUEZRNzVtO4O45Iorc9I1j5E1wXtSLZnPW0STo5oUayK8jWlEjBAN\nTW2wVUC7hDzPUasF0VqDMA4pBeQxUjqUBiUDhEBwirZSFOdyitOrtAfruMIj9TmGxw5YOVazdjxj\n/fIxKqvQfY8eNtTRDqZZkOcDtAoIH6OlROeA9WgNSkmU9hRVia9jitJQWwNCUxRLdFojpSQIhZMx\ni2KBywxetQSviEVGz0vixLFxWY/eZQPOzBuWs5S2PEecNySVwrQCQYqSOYoYH2JskDhKRAgEoUAE\nAhbHHNw6yBhocMJg7IR69k1mk4jlQUJYNLTGYV1D0IEQSxpt2VvsMh5uMFvsIWzM+voR6nqfUbLN\nOL2IwhxQhV0aU2BFg6RG6RQkIARCeJSCJEoY9MYMhwOwPUIIiGDQImCtpalLnPdEMmaQCXq5J88z\nVi43rF89Jb7kCaZMcWVMnA6JIoW3AUFMCDFBKhrX0tY1aaJAB7yQFNYyd1NiHKZdIaq3KA62Of1g\nykFxBuVHCBVRLRJ8vYKdbHHm0YrlacPsjGL3bIorJKkSJHpBmnqSPMNqRyLXGY/WGAzW0NEQYxWr\nR1Lk8CR+3HJ0y5AdX9AeFhCZCztpdv7L3vrWtzKfn++Wueqqq3j3u999gRN1Op1Op9PpdDqd7xVX\nXnkld9xxB+95z3v42Mc+xu///u8zmUwA2N3d5dZbb+WDH/wgr3vd63jb297GiRMnnpYcr3zlKzl6\n9ChnzpzhzjvvZDqd8olPfII4jp+W8Z4Nrr322n/7AEh46tyrX/1qhBAXMNXTryxLbrzxRv7qr/4K\nOP88PJ2NPE888QQf+tCH+JM/+ROWy+W31MbjMbfccgu//Mu/zPb29tOWodPpdDqdTqfTeaY8qxst\nFucE0WVrJDJjf3GGtjAEE6PlmOAEi+khserT1Ad40aJdwBrJ/GCL4vSAcw9OmJxM8HbAVx/c4ZVX\nXA3xjCqecewF+vzqFOXjyMQTeoZJcshofDmrvQPEeEG19wT24F9YuWTAdHGU6dmAaTxKDlCyTxQs\nl66mqKBYFAVtrOmtrFAGybKVmGWPxx/c53lXOnp1YGfvgG988zSJMVh3itXL5mw/t6DIppj5If1B\nhokU2VqPYxcf4clHJlz5vKvoD1Y5mO5RFoZsksL6OpPJjHqRkfsRj3z1Ik7+s+aS4yMEEd98aJ+j\nGyd4/BtfY3KwwnhzDZKEy6/8AR68/+vYMsKVgcX0CbTd50i+RSYlQg3ZPvZ8pq1mtzokaEuvl5Hn\nA7xd8LWvf4md6TnasKQoGxKh2RiuIhEYb/BOEGUZk2KXxXTOYjGntRVCGdIsIUkd+ciSrQqG2y2h\n50kTTXCKelaTpVDXluAk3ka0BggBqSCJNVHQ0OZ4kyKWHh070lyQG0kuUnJdEguDwOOBaqFwiwFm\nsUVs18l0QpPukK49wcaVC7au0Aw3RohxSpIG4iwiSjRCeWRsIAi0HyBCQHiLsA2+rXC2pZoGdp7Q\nmKUgIiKKwShwXmO8xTpBFMUkvRwdpcx2S/IsJQRwbSD1iigKWFMicoUYr1JOM5qyj3YLmuUh84Oa\ndrGObw9A5SAdHjAYDPtYBDr00WQgIyDgnSeEGK1iYilphWF6OGW571nsRZhJSxPHuCjG+YDXGpml\n0DYs2wNkE5HQB7eBaRyDdI2ja1fSqhmn5guUaDC2xApH05Y0jcULz3CYMxpfSiJWMC24qsbZBUpF\nZElK1ksQUjA/aKjrlshLMpkhZYnoa+SawQz2WcgzZIMN6sbTmjmmLdCih5AK03ridIRUQ4ItcDpB\nGQ02g6qPm/Q5exqafUW1u09zKGiXRzGz/4NvnpoidSDWfbQYcPrBOfs7S5ppjatqcJo61DShQYWG\nyE7ptTFHR8cZrYxY3zxK1lvD2Jh5W6F7MNowrJw4idx4jHy9oTlc0jrL9/ZngL63fe5zn+Mv//Iv\ngfNLmP7BH/zB9/SFxk6n0+l0Op1Op3NhbG1t8b73vY9f+7Vf44//+I/50Ic+xJNPPgnAcrnkzjvv\n5K677uI1r3kNv/Ebv8GLX/zi7+j4SiluuukmPvCBDwDwyU9+kgcffJC/+Zu/YWtr6zs61rPF9vY2\nV1xxBQ899NBT56699toLmOjpd+7cOX7iJ36CL3/5y0+du+mmm56Wsf7hH/6B3/qt3+Lee+/F+2/d\nU/Wiiy7i7W9/O6973esYDAZPy/idTqfT6XQ6nc6F8KxrtPDeY60FYP9kjzPfTLG146t/30JzAmSP\nWVHBTLI26DPfrzF+g8YeUi9KbBWhuALbaJTMULHBOcOll7+AycRRPWTYlCnpSOKoaQqD0iBTh9Q1\nq8OWnZML6kVFPRNMTtUUk8CTyxHnyjm1q+jlMU1rkGOJ6kt8kDgdM0iHqKQlDSWmqnCzhqOba5h2\nj7KY07aHON8glKdqMvYnDepsTKP7NLbHaO8YbRVxeMYxmTpUr8+54oD5A1M4PUP1j7O6MqJZ3WBv\nf4eD/RZlHmRxcAKBpJoV4B9hMW8pp4JZOaVsPQeLFhtKDna/yqmzT+CtRYsIHTukSpAhYBEsfYtv\nz7LzxElqKrJ4CDLHUVFUExbFPrPyEOcqpAoEISjaEu/Bh4ByNdXpOc57vPE47xAiILzHuQodB3Tu\n0X2FUYHWeoK1BAvBnL+x2QZL6yzWGrxzgEUGTxRpssQjaVG6IU1L0pEl6wfSNBDrCmUFvlRYD60L\nNA2Yw4gws3h7gFUtor9Ejw8hb2mIWTYR7f4BeSaQyiGEJIosUjm0TpDBERzI0DJN59RtQ6pXMRPP\nyYcU86ml5wOt8tS+oTQVVnlM7chVQIaSsj1NHVX4xiOkg+AoXUthY0Sz5Oz+AemZM0wOU+rZCv1Y\nUphDmv0zbOxMMUnNNJ0hpMOFChMajKgJxGgCGo8iAgTBTwkiRokUHRKq2vDI1yt2H/OUBzGuaLFK\n4+OUyjmKtqAODUpX7JVnaZUj1BK73yCJifsaG7WYEGhbT+lrSrEgxBKpUoSI0ErivKVpGpwvMY0n\nhJZAwFhDa1qq2hNH0LRTnG0QqUQOIhp1yHhDEq1E1M0qi2+uoZIeVhR4ZwgthMYhnSRWQ4RWEDlk\nNEBEEusMzaKg3Yf2bMT+I55iv8KWeyh3gGSTsmkxyqFiiJIKKRzl3HLu3A6uapDB07jzf7faNKRR\nTKY03nqCzkH3KY2kWixprKE1ZxgOHeHcaZqVR8nlGQ7rmr1zc+rSkv67Oazz3WO5XPLmN7/5qeMb\nb7yRV7ziFRcwUafT6XQ6nU6n0/le1+/3ueWWW3jjG9/IZz/7WX73d3/3qZvi3nvuvvtu7r77bl7+\n8pfzzne+kx//8R//jq3AcMMNNzzVaAHwpS99iVe84hXcfffd37PbJ774xS9+qtFCCMErX/nKC5zo\n6fP1r3+d66+/nieeeOKpcxsbG1x33XXfsTFCCNx9993cfvvt3Hfffd9W/77v+z7e8Y538NM//dPd\nhxg6nU6n0+l0Ot+TRPj3a+Y9C5w9e5Z7772Xt7zlLWyuR2xtD2lry8lHp/Tj4wiXIWVG2peM1kpW\njiwJeUFrF9RVjWs1efYcTBEoJxWLSYtpUzaPP5diMUPGZxhtH7Jy1OHFHGdiECC0QyhBnqwx2Tsk\nWIdrYTYBW/aZH4xZLCsCLb10RF+MGQ8GpKnE4WhayJMRgQonStq2oCkq0miIMSV1VVI3DQ0e4xxx\nmhJnlnwUGKykNG0g7a0TnKBeVJSThrLUKBRIh4gscR7o532yLGFRzFgsCnAJzgxBCLxvCd4hgsRZ\nQ+tLhIjBRxjXEsfQmiUBi5IRic5IdUKwDUhFkBrrLa0x6CQhTQZoGWHbmqaZ09RLalvjgkVqiRAS\nKTTeByAgpcCYFiEEQigkAkRABItSniiBKAPdE6j0/GYXzgMeZADZCOpS4poUZxTOOwiSJJWkqSeO\nPVIJpDJE2pEkniQHnYPOA0ppQghY77E+YFuJrXqINiJYj3ctQhmSoSEdBuKeQscxNiiSSBFwhCDQ\nOkGpGKEy8Pr8tjTBobXDWkuse7hiwORJwexUS9KmeG+pXUPTOoIEayFJ+8RJjvOBolgihEdKEHhk\nsIwihZA1veND9PqQotLYSY80jqntIbo3YfvSmniwJIoSwOOx57+EIYQISYokRqIRCAIB0AgiZIgw\nrWPvUUexE/BLTbAJHvAqwoaAMS3WVEhrUAYy1SOLhiS6R6x7xFmfZVtyMD/HrDxL7ea0ogQlUCpG\nqQghFUKBFhnCxwQHceIBQQgSH0AKS6TB25rgLEkiyfsSQ8F4e43+hkJkCyp3AFISVE0IlmAFvo0Q\ndkAc9QkigDLoxBNkwFpDW1jMLMLNcpZ70JQV+ICWCVL2cEHgJEgNUgkCAikU+/t7BOuQAoxvQUua\ntiVJYuJIo4Jga+Uiev11pE7Ov7bC+caRPFVkqxPyzT2ylYKgGw4PC77+pZpLtl/Brbfeyste9jKU\nUhdyOu38f/DOd76T3/md3wHOX3x64IEHWFtbu8CpOp1Op9PpdDqdzn83X/jCF7j99tu55557+H9e\nsrv66qt5+9vfzs/8zM8QRdF/eayXvvSl/P3f//23nBsMBvzZn/0Zr3nNa/7LP//Z5nOf+xw/8RP/\nF3t3HlZ1mfj//3XgIAiKaOBuuS9lKpUz6DB1VWSW5JKN+1hqI7hT4xqaRo1boQQmUpZaSeo05d6Y\nZvkxpsbUNBOVMbVcMkEFRZDtnO8f/nz/PKHIcuDN8nxcF9d17vdyv19oo+Phde67p6Rrv5b79+83\nOVHpWLt2rYYMGaIrV644HH/xxRcVGRlZ4vlzcnL00UcfKTIyUj/88EO+88HBwZoyZYoCAwNL/CwA\nAACgHHuyXBYttm3bpgULFki6tpxhZd8vEUDFZ7PZlJOTow4dOigkJISiRQWyb98+de7c2ViJ5N13\n39Xw4cNNTgUAAACgKtu/f78iIyO1atUq5eTkOJyrX7++QkJCFBYWJh8fn2I/Y8mSJRo1alS+41ar\nVVFRURozZkyx5y6P8vLyVLduXV24cEFz5szR1KlTzY7kdLNmzVJERES+ko50bZWL9u3bF3vu1NRU\nRUVFKS4uTmfPnnU4Z7VaNXDgQL344ovq1KlTsZ8BAAAAVCDlr2iRnZ2tc+fOadeuXfL19ZWXl5es\n1nK3wwkAOMjOztaFCxfk6empDh06qFatWmZHQiHYbDZ16dJFu3btkiQ98sgj2rZtGwU/AAAAAOXC\nr7/+qri4OL355ptKTU11OFezZk0NGzZMkyZNUuPGjYs89/nz59WoUSNlZWXlO2exWDR9+nS98sor\nlerfR/3799eaNWu0b98+dezY0ew4TpOXl6eJEycqKirqpudLsoLHqVOn9Prrr2vZsmW6fPmywzkv\nLy+NGDFCL7zwgpo2bVqs+QEAAIAKqvwVLSQpNzdXV69elaurq1xcXMyOAwC3ZbfblZeXJxcXF7m7\nu/NnVwURFxen0NBQSZK7u7t++OEHtW7d2uRUAAAAAODo0qVLWrZsmd544w2dOnXK4Vy1atXUv39/\nTZ48ucgrFlwvHtxKnz599OGHH8rT07NYucub5cuXa/r06Tp58mSlKZCkpaXpmWee0bZt2255zZtv\nvqnx48cXad4ff/xR8+fP1+rVq5Wdne1wrlGjRpo0aZKGDRsmb2/vYuUGAAAAKrjyWbQAAKC0nTlz\nRnfffbfS0tIkSeHh4XrttddMTgUAAAAAt5adna1Vq1Zp/vz5OnjwYL7zf/rTnzRlyhQ99dRThZpv\n8+bN6tGjR4HXdOzYURs3bizWqhnlzdmzZzVjxgy98847ZkdxihMnTig4OPim/y1c5+7urtOnT+uO\nO+4o1JwbNmzQvHnzlJCQkO9cu3btNHXqVA0YMEDVqlUrdm4AAACgEqBoAQComgYPHqz4+HhJUosW\nLXTgwAFVr17d5FQAAAAAcHt2u11ffPGF3nzzTW3cuDHfeX9/f4WFhWnQoEEFbsmbl5enJk2a6Ndf\nfy3weY0aNdL69et13333lTi7mVJTU3Xo0CH5+/vLw8PD7Dgl8vXXX6tPnz5KSUkp8Lo+ffrok08+\nKfCa3NxcxcfHa+HChdq3b1++80FBQRo/frx69OjBCp4AAADANRQtAABVz9atW9WtWzdjvGXLFocx\nAAAAAFQUe/fuVVRUlD766CPl5uY6nGvatKnCwsL0/PPPy8vL66b3T548Wa+//vptn1OjRg3Fx8cX\nerUMM50+fVpffPGFvvrqKx0+fFhHjx5VcnKywzXVqlVT06ZN1bJlSz3wwAMKCgpSQECA3NzcTEpd\nePHx8Ro+fLiysrJue+3atWvVq1evm567cuWKli5dqqioKJ04ccLhnKurqwYNGqQJEybo/vvvd0Zs\nAAAAoDKhaAEAqFoyMzPVoUMHHT16VJI0cOBAY2ULAAAAAKiojh8/rqioKC1dulQZGRkO52rVqqVn\nn31WU6ZMUcOGDR3OJSYm6p577inUM1xdXbVgwQKNHz/eabmdJT09XfHx8frggw+UkJCg4rzlWadO\nHQ0YMEDDhw8vt+WCWbNmKSIiolDfX7169XTq1Kl8q5qcOXNG8+bN04oVK4ztNK/z9PTU888/rwkT\nJqh58+ZOzQ4AAABUIhQtAABVy4wZM/Taa69JkmrXrq1Dhw6pXr16JqcCAAAAAOdISUnRu+++qzff\nfDPfliDu7u7q16+fpk2bpnbt2hnHO3furN27dxf6GSNHjtRbb71V4LYkZSU9PV1vvvmmoqKibruN\nhre3t1xdXZWenq6cnJwCr33sscf08ssvKzAw0Jlxiy07O1uhoaFatmxZoe8JCwvTwoULjfGhQ4c0\nZ84crVmzJt9qGL6+vhozZozGjBkjPz8/p+UGAAAAKimKFgCAqiMxMVH+/v7Kzs6WJMXGxio0NNTk\nVAAAAADgfFlZWVq9erXmzJmjw4cPO5xzcXHRk08+qalTp+pPf/qTFi1apHHjxhVp/scff1xr1qyR\nt7e3M2MXyaeffqoJEybo5MmTDserVaumhx56SEFBQfrjH/+oZs2aqXHjxnJxcTGuuXz5so4fP64j\nR47oiy++0JYtW/Jtn2GxWDRkyBC98cYbqlu3bll8Szd18eJFPfPMM9q+fXuR7vv+++/VqVMnJSQk\naO7cudq8ebNsNpvDNW3atNFLL72k/v37y93d3ZmxAQAAgMqMogUAoGqw2+166KGHtHPnTklS165d\ntXPnToc32gAAAACgsrHZbNq0aZPmzp2r//znP/nO33///RoxYoReeOGFfKsc3M69996rjRs36s47\n73RW3EK5fPmyRo8erQ8//NDheLt27TR+/Hj169dPderUKdKcdrtd3377rZYtW6YVK1YYBX1J8vPz\n04oVK/TEE084JX9RJCUlqUePHsb2l4XVsWNHvfjii4qOjtaePXvyne/SpYumTZumHj168O9iAAAA\noOgoWgAAqoZly5Zp+PDhkiQ3Nzft3btX7du3NzkVAAAAAJSdr7/+WtHR0frkk0+Ul5fncM7Ly0tX\nrlwp8pwNGjTQ+vXr9cADDzgrZhs0YnkAACAASURBVIF++uknPfnkk0pKSjKONW7cWJGRkXrmmWec\nUho4deqUZsyYoRUrVuj6W6cWi0UzZszQK6+8UuL5C+v//u//9PTTT+v8+fNFvtfX1zffVioWi0U9\nevTQlClTys2WKAAAAEAFRdECAFD5JScnq23btrpw4YIkadKkSZo/f77JqQAAAADAHEePHlVMTIze\neecdZWZmlng+b29vrVmzRo8//rgT0t3avn379MQTT+js2bPGsZEjR+qNN95QzZo1nf68L7/8UkOH\nDtWpU6ccnhcbG1vqq0B88skn+utf/6qMjIwSz+Xh4aGRI0dq7NixatWqlRPSAQAAAFUeRQsAQOU3\nbNgwLV++XJLUvHlzHThwQJ6enuaGAgAAAACTnTt3ThEREXr33Xd19erVEs1ltVoVExOj0NBQJ6Vz\ndOTIEf35z39WcnKyJKl69epaunSpBg0aVCrPuy4lJUWDBg3S1q1bjWOjRo3S4sWLS+2Zr7/+uqZO\nnSqbzVaieby9vRUWFqbRo0erXr16TkoHAAAAQNKTrrNmzZpldgoAAErL9u3b9fe//90Yx8fHq127\ndiYmAgAAAABzpaamavny5Zo6dao+/fRT5ebmlnhOm82mTZs26fLly3rsscdksVickPSac+fO6aGH\nHtKZM2ckST4+Ptq8ebOCg4Od9oxb8fT01IABA3T8+HH98MMPkqTdu3fLzc1NDz74oFOflZOTo1Gj\nRmnevHlyxmfjsrKydObMGeXm5qpp06by8fFxQkoAAAAAklayogUAoNK6evWqOnbsaOzd27dvX338\n8ccmpwIAAACAspedna1169bp7bff1pdffqm8vLxSe9Zjjz2mf/7zn6pVq1aJ58rNzVVQUJB27Ngh\n6VrJ4quvvlLHjh1LPHdR2O12Pf/883rvvfckSRaLRWvXrlXPnj2dMn9ycrJ69+6t//znP06Z72bu\nv/9+/fWvf9XgwYPl6+tbas8BAAAAqgC2DgEAVF6vvvqqXn75ZUnX3oxLTExUgwYNTE4FAAAAAGXn\n66+/1gcffKB//vOfunjxYpk9t3379tqwYYOaNm1aonnmz5+vKVOmSJJcXFy0fv169ejRo8jzWK1W\n43WPHj20bt26Is+RnZ2tbt26GaWP+vXrKzExUbVr1y7yXDc6fPiwgoOD9dNPP5VonsJyd3fXY489\npqFDh6p3795yc3Mrk+cCAAAAlQhFCwBA5XT48GF16tRJWVlZkqTo6GiNGzfO5FQAAAAAUPp+++03\nLV++XO+//74SExNNy1G/fn2tW7dOf/jDH4p1/88//6x77rlHV65ckSTNmjVLM2fOLNZcN25l0qNH\nD23cuLFY8/z222+67777jG1MQkNDFRsbW6y5JOnLL79U3759y7QEc6MGDRr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bTs2zVvyxOn1FH2DW7WkhJDFJNFCictNjg6V9G4Duk1IbH4yCBswFYb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\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m8T4wvT0jF8Pzj1+wW1mk7Xj9nefruaI/Wh5ew+5JROiAajKSyPzwluNdYnlokPWa23+z\nYvPpiv585vx6ZrqH6ANGG1S1xsdMzpGmUsgwokQCEil6huSYGdB1YBk94v2C2nhmBoYxsfQgXYuO\nidPxjvl0wfkNXtdE46GChGIxmdl7xHni2ScN1acvOewabtZP+M1vf4b7+wtvF8vqLy3Nn2nceeIf\n/5e/5f/539/y+KYn0SCaFj0euGn2uPpjsvk5682ec7rw7vxP9PMZgG69BRe4WW8hzbRPDC/+bct/\n/F+/4PH8HlV7KnFLywPj6QNfPQxYmWjXW1SzoZ+/Y/Iz+w4MkuVRMh5n2gZaaajajrxsOb6WzENC\nJIlpKnaqZuwtl7uZYQzEXKPsBgj4rAje47Jn9oLLMLE5dDRtxqgaqdaEvODHhBQNpt6hVzs4GUKy\n1HpLrTaMfqbxPUoGlAkkFvqrJLeWdvOEtb5lV3ccnkXWHz3S5Ak3zQQfsFGiugpSJHvLEOExjixI\nDkGjri0qV7SbxKQCgogPgqH/4exQZQO7/07y4rMGaSo+OgnsFze0H3rePUwMy8Q8L9RtQruMdRGd\nM7nX/KyWhNqQ2kBbzT/mbBZFURRFURRFURRFURRFURRFURRF8Sf2kw4tGr0lzxUf3i6Mi+dwo6m6\nFiMPaPkUpbbgBSpkMjNVPfNkL9ltOoTZE2PLeK4438G8OHRS5JBZnMRPgqu3pOYWdCAKz7J4FpfZ\nbSyxMqA1MiakBR0V2jYYq8hZMLvIdOyJKVOphnW1RimNqDNX0TOoE3IdOXw+cPNfaz79ZGFbnZku\nZ+7/cKb/OjFvDeu94Poc1laxrQSDShxuEtV/JalUw7uvRrxrsd2e9fPPON2/Z3XKpIeMkhIn6OkA\nACAASURBVGBlJlugkriwcO0nrlfP4fbAk2dPmYPi/XeB8/eeOC5Ml5m2Cegqg8oIAaLSyK0hNC3S\ndQgH2QXm68L8zxFHbRv0qzWVtJz+2HP3xwtGCBqrmO2GYSOJ7RWeOiKZSEYk8EmTUmY6JhYBoQ7Q\nJOJUoXymWWXkRxltroT8huw6hBqQpmdKA8NY453AD4FsRqTqgUxz25HbTDCOed2TQkRUnsNn4NaC\nx68zVBIfYHaZREQSqXJCspCUQ4qM0JIkHNVB09QC4zMigJeSHDIiaeIouNxfOb8HP+3Bd0ihsKIh\npUyK0E8zr09vqd8qftU+Y/3Lp/y8+QR1e2I8fsGXX77ny3/I/PZvLwzpAxf1ni/HE8/Nr/lo/ZJm\nPlCHBlu1ZKtpN1vqZsWiZ97dfUcQC9t2zae3r/j0+Wf4IRGD5508sqSF/vd3PFUVizE4DFMvmb6P\nuASKNcFook6I3HP/PkFKdMHgesO0RDh5XKsQOjKz4JaRcbBcjxk/KogKQcS4RAx7VBTklMgiEuMC\nCCQSkw0bY9m86rjZZpq1w+4E+pnBdQGlJXqWtKqiDSvmD57tqma32WCrFQ+XQDtUDBeHQfHi6ZaD\nkJzURJ4j30/v0LajcR4xDaxrhdIKI6DOCj9EnE/MInExgtNKIVNmjok0X3BBUFnJVC0sZ4iPGzhW\ncK3Z/MLSfDRgP3lEdj3bMPDntzPL3wju7xOxD3SHms+7FQd5xlwDKTvinGhWhjGc8cGTzY+7m0VR\nFEVRFEVRFEVRFEVRFEVRFEVR/Gn9pEMLkysqYdHJEQbPSUT2doU0G/K4Ix5bwjiRDhHVzLR2QVeK\nechMoyTMGT86lhGiTEhjmX3Au4xH4Y0gGUPSmogiZoELHh0C/bknpQVjWzZPNuxki59Gltnjk0Iq\ngVYteA1ekqVGKINREb3JNOvE/heZTz8f+flnC7/eBm6FZ8TwxWrP1+d7Hn4PqZfcNIG/fGXojOC5\nyNgqcKln0nliuIfrPYxe4mgY45rV5hm7aqKRPXbtOfkLg52Zs2OuEnpvaHVN09VUaJZ+YXq/MPcf\nGLzDGAftghcT2gqydChtEFohokUsiezAjQupdaTuh5cbBuUZ48AyV7jJIuuWlFryYolngz8Kqu1E\nNhGtA9l5Ln2GbNBujQoV493M8Xwi54CUgjppzEGgmke8u7CcNXJvqA+B+C4zDZHxlKkfHJ32VHvI\nVUTdRNQmMatAMAFnAo2JmCxQSbC5Jo7fSvrriRAV0kiSzCThUDagqwgm/3B6QnoWMiZE5JyRxjAB\n/UWynAT+Aeb7zDxDDJomrdnbT3m2/oSuW+PDlfvxe/74/R2XeeaT//bnNC9XEA21WdjaDTJf6E8z\n4yRYkiXoAy9sy8E8oZIbar1mp9d06w3ZZtCKkGauw4QUmp1t2FVrCPDmzXech4EUJJubDXu1Yv5w\nRfqFfjzjGGAXyYeaaBtqW3EOieVhxMfAPEpu6wMiVCxvE0M/IOsGtZaItSIqzXzVzL1hvghyqpCy\nIiXN5MAtjkq3tKYhycB4dfgUSRFIgrptePXZC7r6nnYjqG4F4lYQmopma1ipNYdqj8lbVj9bmAaB\n698znd+iUuDnvzT46YC7CPrLxOPsaBvBsAT6eOZu7GnfLDwdHTcrRZ08+EgKguslUdWCYCUXKThW\nESEDavAcNCidcWTGJTDdVUxvK9yHDtkLNtay7iba7SNic49OA8sc6FYBW0WsVnTSsJZrNtLRVI4s\nJEvMyDFhtMQqjbb5x57OoiiKoiiKoiiKoiiKoiiKoiiKoij+hH7SoYVG0VWG3dai2gVHYhgVl5NB\nvrM0V0vVQd4BZiLbnlRDiIbpPnH+3jE+SkTSUCe8CniVCAqyVAQEjoyPiaQEorJQSUZtmcdEdJ6N\nyDxpNU83FecPM29OF65TwAmwpsJiMEFSW4FaB3LbU+2vrD6eefXrxKcfLfxqM/MKySZrRrvi21aj\nhGd5E7gbMn985vj0UKN3nq1KtNLzXp45bv/I6maDuu8Yz5qLjyyiYr1/waY9Y6xDbxxxurKYkSEl\nUm2odi3SSUKKIBTWQttF/NLzODogovTE6Easy5AiCjBCosUaoqJ/35OrEfUiI9YRJxYmJpLwWJmp\nhcR7T5IbjNrTmD0y1Yj+xCIDUnlyDIRZYNIalo506QgfGtx9xrQZ0XhoM9FEgnpArj0uQxYN6qEG\nIZknxfkuUW0izY2krlckMRJjRuaIVgEnAlkmqhSQAbIRmK2ge65wOSImSUqJFDxBe4LKaJPAQIwC\nYTPL4hAxEwPkQXHvJZerYDqCe9TEa4thQ91s2dQ3vHryCZ9//K/ZtTecTh9wX868P93h7JHv7u55\ntzySLoHp9UKeB1o9keoFqTMdFVJKTHXA6hoXDDknIg6frggfyUmyOJjOnvVqxVq1NMIwXWcezz33\nvkebls+aBqMqxjGwjAPX+cISJ/jgYWORT1pSMAzzzGWIOJdRbsOu3TL1LYGMdwPXfEfdZlYvanJb\nsdwr5seGcNEI3RCVYpoWjscFqQKHrcUozTwtuMUTc4ak0MZgu45212CNpD1kmn0i1pFcCbbVisau\nqSqN0I7bV4K+73m8eyDcD2yulqZfk45b+ncGETTDYlnSD8FEso4Bx/1porkLnA6enAPdIsAl8gh0\nkqmKnKqJs07kS8CeJ9ZGEDvJVQUug6J/DIwPgTQkOi15etOw3p6ou4lcTWQ3IoKHEDBVpFlpKmVI\nY42JNVKPhGpGkdBDpFOKSoGQ4ccdzqIoiqIoiqIoiqIoiqIoiqIoiqIo/qR+0qGFlJK6NaxvK9Q2\nMHvH928kx/+UUV/Bi87w4q86Fv0N3swspmd0jmk5MD0K+teaeNa0+4pkZ8YQf/hgqyy1qPEhEELC\nCRBKU7c1tpJoVSNMIE4eqSRuGDA2YHxP8veM0wWvDXW7o7UNrTGsdgn1ZGawb6mfXVm/CjzZZvZC\n8lxoVrnBJcNJat6bCvnyOfaPI9PDxLv/IPndrYG/CthNxBAxKTKZO+zuYzp7QC0Ni1csRHzKxCiR\nOZPswCxGgnFEL0hYEIKUM4ubSMGTUqTdRuZB8HCemY+RqvE476imhFoSrayxqqZOT4iy4/LmNXLT\ns7pVaJEJOaCtpNpamkMNR8G3jw4XI1JsaNoapSVj/0fO05ElRkwlWHcaITcMZ014K0mnlq0wrExF\nFBeC75mHI1M80T4TsIWcPbl2CNMRveX8oFi/NAhp0UaRZcDJgMDT6ERLQAvIOeCIuJyJlWT/r2qq\nZ5bL/cRw3+NPE0FmpiwwQqK0IiuJbmGePH6EfpGMM9wthsXbH06czB2d3NHs1zy9ueHFiw2f/dzw\n0WcByxX/9UT3AJtTQyLwn/+3v8a7gTCOmCRo65ZGe/ReE3wkeAc4hE00ukIPkslnxjgyTz0pBVRt\nEcKSnKapa8Qi8UvEx4T3BqVXyLblMmb8MuK1w80TUTl89vhjIn6lEM7gE7gIMSlIFumfcOprolmx\nWnfoOvLd7wfWUpCnHXqj6d9c8bHBiBU5VYzec3kYeLwf2b3Y4oHjeOX4/oFNrVFIlBKYyqAawxIW\nlIpkgJRhTiihEEiWBZZhRNRX1jeKen9iu7ln9emAvWr8NwZX7anljo1qGK3heh3RrSIkTyQTpCa9\nqTgeJkItiJNCLoLGQLJwNTN9HpiukH5bMy2R8akkrgWPKvNwMRwvmmlQKBS7p5Znn9XofSBKT1gy\ny6CIfUK4TKUzVS2IEe7eeFZvFXYXEU8cTSPRKmAcyAwhlhctiqIoiqIoiqIoiqIoiqIoiqIoiuJf\nsp90aLEk8FqxaMm4zDyeMg/fOvyHzGpQxCxxWuJx5EZCqxmPV16/uZLeLIi+RY8VcRGIoIl1YOoj\nSki65xXZaSqf2VQr9usDt6sNtYZgI8N+5DSeOR6PPLw/MrzvqWvP/qVit93hyczHK75/wImJXM+8\n+JVCbB+JlUcby35c0cmGQYMWivsk+GvpuX/SUv+PO9Yu8/A/X/iH/3MkXSoOHwlSO2OUp14p1IuI\n/vae3brl2XbF+SHzjc98+dUb8pg5fBzJ48jETEgZ7TQEAYsgx8Q8j0SvyFliNopQwdl5rl8Gujlz\n+LhBXz3+9UQ/KsSmoX7R4uaK0dXs7Z5NCz47ooBmXaFjTfIWmzXHCdy0cP/+gWZTsbUDyypxvXi+\nexMwpuIv/rJl/2THd28yswOjBV1lIMyonMlRIYImo8lCAKBtRbtuWO0tTkKQDVWjaJvIMjsSC85H\nRAxUQlJL6BCkWnJBsOhEfYjIzZXmRUSeF5q3C/595PwIPkekUejKoIQhOujnK9d3geu95DI0zHWF\n0Xu28hmf3r7i1798jnx+4faVZvtiod3/jrH6PbOrWIKmejmy+VZwfdNw2c1Ut5DXI2P/yHB0+Oip\nV0/QjUGsNNa0uGvmcrrQHwect+hVRV3XpAkSCRBgDFFlgnKIGJnnwLB4rNKolFnkGR8SYglAgDoT\noyAFSzp13L37QK8SVRfZrDRttYbF8x7HfbuwaxraUPGBHVq0XM41/m7hwzeCwyeGX/zsM+Ra8XA9\n0YjMZt3SHraEDHenB/rhyue/eMkyLoQY8fnK+SFxu++oN5Fwhigs5pAxK4sQFUIItI3UXWCtT4zD\nA1bO+ByIYsT9ObTrI2K341rvyFODmX440TOlRBCCA7CbDqx/f0+zHcja07uAvE3MF0ecFPVFI7+U\nTH+f0Z+uSJVl6hKDHrhcak4PFcNRIYNAbWG58Xy4HtHLBYJnGRTXD5anXc2H5szD+zPfP5zp/9Bz\nv8BncuFFI5FGM2ePmAxhBhnFj7iaRVEURVEURVEURVEURVEURVEURVH8qf2kQ4uxX/jwuke2M3Ij\nYdFU/gm2XiPXgaN9wAKMCt5ZXDa44wZ53hBzQ1oZkoJxWHhzd0Eayf5frdj9bI304L5+QE4VW9Pw\nURbcLJLgBPMSGcNCdgMNM7LOiJhJNpKqjBSJ8fqAsIH1U8+qcmwPns0W1C6RlUQEiXUgfGIMAmcm\nTiKhaKn3BlrH5/+T5uWnLW//3cJXv535h/+741MhaD6+kvNImhXVL+AmCLw3HAfJcbFM48zDKZJr\nQVVZdFsTsiceJekIy5QIwSENiKww2lI3mqpZUwXLeTkzfjsQ3ktqFE1cYdgwXDXhu5mwBJKQjGPm\n8YNHVgLTSMiRZD2p8jgy0SdySPSnyJs/aI6XkfwyI2rYGBAZzt/A+PZCntbozlJ1iqryZCNIJD58\nGDgNI9VWkx8rhAjgOlRa09SSumrQRnH3uDD854HNs4mbT2aiFUgUMcK8wLveo1eJLDRJKlDgfOaa\nryTpES3QCvIi8JeMGxNLmCFPDI8wTRGEpF7V0OzY7A7c7n7Np+uXfHaz4elHBvtiYHV7JTcPBHWP\nVwO67rimjHrxgsNfPEf+3rA8WJa7C14EBJq6qlFRsFwVy3Umeo9UZ+ZREMQaeELVHbDrFqlgd+jQ\n1MRRk2fF4dBwOl04Ph5xi6dpWqq1xnuPGASCTFAzj4ycgwfT8KR+wWfbDdWf/QWxSrw+/oFvvvsd\n/fsTT7d7ds9rRgOX6Hh7PjFIME86qk2FioZOCxYS35y/w0yCnAJtk1hvNqy3a5CaQyu57Bba9YRK\nI8tsSUGSo+bx4Y6nm1tEyAznCSUEYX1G245GtayyQPUj9TSzomGUgpOIXFSkRlB9HKnbgVVd8VHX\n8fXfW754D3OfCUmx5IrrvWU5PmCfzdSvPPVTjbu1CJWRE4gHQ/rjmlXa8+G1Z4yaNlnES4M5t1SX\nSC0g1orBL7z5cOTVdmJnPdokZGsI25rH+8S0RIIUqK1GJsukBFfvGf3CuvHcNJExCGbvuU7+xx3O\noiiKoiiKoiiKovgX7nq9slqt/n/zu0VRFEVRFEVR/PT8pEMLkmT5IDlnhegMuqmplg1BaVLniLXg\n+gibeoWJt2QnUA8j6/SMc65ZhCAoT5COTqxRtxq1USx6IXElbkae3MDBLnR6osYQpowSniEP2DiQ\n80RSEyEvuLigloS10FYgZMaKBVvN1I1gtQFTaZLX+MHgB8nDHHknJzgobN3w/7F3J7+6JgeB5p8Y\n3/EbzrnnnnOHvJlpp0lsKKoNbSxK6lYjkNukQcKwMBghluwA773nDzDDoiXLbPEC9qgXvaAphLpo\nGjC2wXZOdzzDd77pnWLsRXahroaukiiDk6z3t4xXiohVSN85jyJOgVVK2GpCvNqzrY/oNPFXX5N8\n7X+tkPEer/w42A8/Z7kMSC3JDxJ3biQPrhp2RHQhGdPAbpcpkqQ8bYhHRxoUTCXEClVWKC0pF5Jq\nITFGMB4kYipwrsF3mWnvSNIidEEuFsRsGceR2Blyhjho/HVFs1xj7wS8mPB5wmVJT8PqTkF/Azk5\nht7BzqNPDDJbdBCoaPEvSq73CWMTVo6UylFVPeZ0Ah3p6OjHiKEB2yKVwPWG8VpjlOL0YoUuDYfj\nDdvnI37qSNZRnRfoMhNURApN1pLJZAoj0Rm89yQyiAgyEQX4rBAyoXQk5swUMuOY6I8gJdQLiakr\nUHdQ6wesygUP7zY8uG9pzwfE2RZVPSOIZ0R/QxgnUA1Ii70Dpsv4Z0umFw0pSETRkKWg844sNMEL\nsqqwusLojCwEUS/Q6g7WnqNrS6kL0ILpmGjWCx5dPOTgezYpoQ0URaSyiuBHog+kKeIIOOPIKKq8\nJo41tWp5uFjQPrDsQ8d+Mtw/aylOS0qhka3hZhzpugmCpyot1/7I5mpLYSWrk5r+OHE77VARtMhY\nBMtGM7odOYIKEyeVQscDuhTIDD46+gHe+U7k9YcvMU0NzhcsFHThSLOOTLpDTCN27Ikj6MIiNIhs\nkLHCi56xyJSnHUslidTkQ4MqSvLjkuebyHQUXF/CenkHMUVk3sLCMRUJnQNyJxieKtzlEjGe46Kj\nT+/dXjF8x7H7lmd8GiArkgrcdke+9c6O5fkVlb3Fq4kuSS5TzYvBECUsFw1GNNhQYlYSudJQZ6KZ\n8FbgrSIYSVbhe3xwzmaz2Ww2m81ms9ls9sH2R3/0R0zTxOc///l/sTW/9KUv8WM/9mN88pOf/Bdb\nczabzWaz2Ww2m71/ve9Di+wqlCup6kBlLLpuGUtLf5Q4D8/e7NldjdQLibINOpec2pdxauIYNhy6\nPUyZO/dOqR8a5NIRco/LR9bNwNk6sG4CVXHEqho6iJOjPHa0xw45ODwRUkIIEDqhVaYpC3LOyCzR\nGoQSLJYtcVSMtxp/o5l6wXEz0Jee5crxSCYeRYmaAi0jqTry9H7Hs0942u83PPmzwFk64V5zQnNW\nUt2/xLsDod6iFi2rtuVOKghGk8m4sUTGU3SwDJsjMRuEqhAYTFXRrCXrR5HmbkYQGW7g+EIydJaS\niqQtttLYUiFNQQqRaX8g3BZokfAxM968F7hQT0xmwk+JYR8YXKCoaiYTCVMiZYG0CmNbpPIUhSN3\nlvHKsN8I0BNSeKztWJwcqaoJuza40jFlSXdV04YFGcHQZ8Y9yKQpSkNVW/qDxO0CKjvCABKJkJmU\nMuiMLBNJS6jfu+EhHSPZJXQUTL3A7TLukBBBIKUgIyBnssnUq0yzhMYXmLACzpDNCaWSLNae+gLs\n2RZvr+jHJ6SwIQRHcKBMZlEU2BPH1N8g7gZEp4lbjZYV1hiU9Ni6oT9G3JiQOVMoQWU1UbWUxR3q\n+i62qtCxYNNtyCZzdrri1dfOePx2z9hmFuWSLB0u7IhjjxEQLUSZiVpQ6zsIdwZBc2cRWT/cY5fX\nuPHI2XrPYgnLtsT1gQhwlUkDLLRhEpK96zgcOowQ5BBQSaJLiZIKEkxTYBhGCJLsEiYnKiuJB48p\nCqQQSJEBz7Prjk0/UUVD6GpMCcdaYa1AnYxEe8CHkUPQdD4DBitb2lxxtenRC2iXmfbUMY4di1XN\ng6EiuVN0SDy+3PC1N3e8+sjwsF6iN55xFQg+oGKE54rxSjF0FWJqCQE8Cn9M7MYjh8c9auqIGVwq\ngJIYMn7aMk4bYjFxKwRv+j03Y0sUJ5w3Z9yp79EuTqg+eqB9ENDlDpUm4gAiQVUaqtJ8L0/N2Ww2\nm81ms9lsNpvNPvB+4id+gnv37iGE4Bd/8Rf/2df70pe+xG/+5m/y9OnTf/a1ZrPZbDabzWaz2b8O\n7+vQQiioTivOXyu59zBhaoGqLMfJcvVC8+RbnsfvbJgOR9pl5OIlyfnDBVW5RIsN49Cx3W3RseC8\nDZzWinaRSTYw7CeyPNBET1VkinsScaJRQhBve4p9ZnWrkDeSGBeMXiGVoqgEVZmotGTqHTEZsinA\nKhYnj7h+HDlcRfpnEj/BMTjkPcmD6LkfPReDQ+US40GqhGsSi3uRVz4j+LO/mHj8l5GHpw3ta/eZ\nlnt8vGXkkk5GvKkpi7t4Y/DeQlph5Ippd0l/gCAN0lQIpdChoj7PLF8eaM4cUiWauxZQHHeCajRU\nbcPqooRFZMqebnMg94JMCV4RUqA/ZsLTjAWCziQU06gYp4jyHp8iIQhMNpi6oGwEtowYMdE7uL5O\nTJMg5JGURmzdI+oJP/VUsiFWkigM+xtL6wuk80wBYpQIIRn3IzpF0hBIToDLlFJQIdA5kjOklPFx\nIhvDlMHnTMwQjpk4wngjGS8T6QBSGUSySC0oiky5CLQ2sYwCczwhHe4y+RXJatoyYxc9YpXhZEfs\n90xDT5okwi+QoQJrWbVLOh3Yr48sXlMUZ+d034a8kVSUtPUC0zRgPHk7kYeIEIoiW8gVq6LhZLWm\nqJd0N4HRbanalgcnawoiD9d3WbeG3eHA1e2Gyz5ATkgtoNAoI9Giojb3UbuGdj1x/2Nb6n/7Nizf\n5sR7zMmeKR+QJhKwEFowAasgRsPmmNFZUhYlY+fYvdjzYH1K3RgKVZAidG4i7hXGvhcZiRwRUTMN\nBURNzAqtDU2j6cSed/dXnNkC7S3x7YFxU9BMivr7BcVdgagUNyTi6FnkktOixWq4evGCNRlVG2xt\nGe+MhOIKJTWPThZECt7aB7799JpDLkgu88hXmCES65GUJ9KtZDpoxiwpECi1REwW42EV1yixw4mR\nzbSjCxOLUnJx9xSrE47AKBK3SfDubmToSk6nikflfT52//s4//g9br/vG3SLt5BxwA49OoHGsjKG\nxsrv9dE5m81ms9lsNpvNZrPZB9p6veZHf/RH+eVf/mWAf9bY4ktf+hJf+MIX+KVf+iWknH/zz2az\n2Ww2m81ms/e8r0OL5Uuah/+94qXXM4s6YuoEJz3uqPCpo//WSLkSLFYnLNaCxUUmrRKbq2c8fb7h\nuD+iERirGG+3uDZhGkdb9yTX4YYjhR0RQXAEju3Iep0oHo2YqcZclfCWgEPN7nai0oL7Z4YHdw0q\nRp68m3m+SQypQK3vIO68Brsj3h04PJ04bjzOC/RHR/ZZspWSJo/UXUFQirptOPHwekhc/zT8b/9L\nzzdfPGP1uGX5pyuK1wqCCHjb0a0C10rgUkHyGlJESkUWmT5KpF0hsyFETUJh2jXF6haEZxonVAnB\nJspXCuo9xCBpT+DeS5KwcOxcR7QDwmhYSMSzghQVorKYUlLEmm6fEDpjbQmtJY2JHCD7TI6QpMIU\n+b3nFFJkJLIfFdNUohtLU0mqFkwb0LLEDSUyltS2xNmK26PAOMg5gkgYJZG9I+KpRIAKMonbd6Au\nexYXhqoyJJU5OMu09VxeBtw+YUm4K0seJKHPiGSwZQ1ZIIXCKI2tDWWjaRBIp6FYkvyKSEYbRbNI\nIAcOzuNyT9YJu1iAjEhZoqsV1mo613G5u2TnBqp7ifuvSNLDNTff6HjxtUve/JtLvrF9zv3lAz58\n8RoPLu5jhWHzYkcBNG2miZ682SOeHXjZFNRFjZgim3d7Xnn9AecLwze/tmV8+xoxjoQ+cVQ9fR7I\noqItXkJdai4cLF99weKH/pL00a8h5DP0IaC7jnHq8SpTXjSksUEHEN6Sb0/QCJaF4LSuaB6dsVw0\ntE3LixdXDMeE9JpWL1mcLokKpsmTfSBkUFaSlUaRaYyh1pa1PnB99Q7qpKUKme1Nz53NEi0yjck0\n1jOuI9uyQ4oC4TzKOZJQ7EdJleDSZ7ZhxNUO/XokurfZvrPB6xWvf6wiXZzz5OuXxG95/FTwoXhO\n1I7jtGX0iThppAgYBet2SW1KCgNaC8Z6yc1eIbpnTMOBwUSijkRbE3VLNx549rzn8t9rVsMJD/wj\nPmYf8v3Llng34F/a4/yBdDPhfaSpSippMD2klL7XR+dsNpvNZrPZbDabzWYfeG+88QZ//Md/zK/8\nyq9QFAU/93M/911f47d+67f4whe+QM6ZN95447s+/2w2m81ms9lsNvvX630dWqgFlHc01WmByaDi\nyH64YjNcsh0MKdacPzgnC4Gue5w90u8cx6uGrhvJSVM2hsWypVwpyrzF7A9YP2FFItYFtga19tgT\nT1vBSpc4l+kLON73lCZx8/iS/Y3n5E7Jw4+VnJ5KQsrYdYfuBrRS+NWRb95+E6FafJ3xZLptIkWN\nOZaYFDA2oBUE05OoGMdMTNDGCi0y3/9DJd/ZZp7e9mz/umHxDcOwiPSLzG12XMvn9Psa4RdURUvR\nVqAyITvkWmAt1FVBu15ydr9ANQOIEZE8aXLE6FCNQFaRED27mwxTj3nZEcoeXUXMKxXcPzDdGZmu\nBaGTpKTRaE5OX0EXkiwTw+C5uuyIyROlYvSBq6cb/GKgOt1jJWRvqKzmuPUoU2DXNe1pTbVaYorE\nfjMyvhBMG4uSBqstpgApQNuEbSOOkbjMpLwnj0dySAQkYpSIgyB2mXHI3O7g+nmiv4U4GfpkSYOm\nXtYYrRBGoZRFmYKqbikXNbYoUAmy+3+iAS9IuaCoa+q2pFpKZOmYpp7+8Y4UDyyrRFMaimWFEgXb\nmyP7Y4cATpYFKXlu3/4rxpsV01hilnByr+BhXPLwwy3LRSSzxztDpKM4sah2R8Ah7hSkogAAIABJ\nREFUoqKtNToX+KEnK4NeLXhnc+T5mzv2V1siB2LquZ5ecGWOuFiw8mvOiyVnytB8+Ib0+l8y3vtT\n6uYpp0YgC4koPaFLjEmStEesO+wUKI4Ctxs4RoMwhpwkPjoCI7fdc1QLd08rrLQ4r+mTY3Ve056s\nSCFz9e6G/RNBqQzKGnRhEVry6NU7HHa3XHWXNBYqIwit4jhqpsslpVYMpYNTSV5mfJEZVQQVaVea\nQoFiiQwFMvTE0wn7fZFVoRBPC8JzS7mNWAlTSFxfRhqnqFYrXG7pR8c0JQrgpYeRi3sT6wea8q5B\nAtffSNz8tWK4EfTHiIoaMSw5PL7LWBbsh47xnYHqdkE9PqIJ9zCLFlc6er3lVvwVLr1DM07orWW4\niVAoUlQo4b7HJ+dsNpvNZrPZbDabzWYffJ/+9Kf54he/iPeez3/+8/zBH/wBn/nMZ75r83/5y1/+\n+8hCSsmnPvWp79rcs9lsNpvNZrPZ7F+/93VokTS4LJh6gZwSRgrGacL5QEqaLAXKOpIUZDvhcs/h\n0PP4qud4iGQydVEiraJuC7QsCGPHlCWyrJBtgS+PDPoGrRzawCOpScJiSUQT2baJ564nfwhWjzLr\niwlbRgIZ3QSWPrHICisTgQ26DRQXFeWFRD1XjLcaMZVMceBGgbAlZQIdR6ocURmCFdRa8+iT5zx+\ne827f274xtc86//LsPwfl+h1wglHcy8xPZkQoSINA2MagIgyA+ZEoZeCagXLtaQqAlopSBZCgc6K\nnCPTGIkpknIkDzBlxfQsINeg1xKz9KQ6MI0RkUqKtqWyhlJZCllhjYIcUDIzngr6veDYJcbsmQ4j\n5srjjh5NRvQGIxqaokALQzhmjjkRjxZTZtxOIo+K0hdYW9CsFPUdQbGAyjpqnRAFHKuJazfgdg62\ngmELf/em58kLMAp8p3HjgvG2Ik8alUpUqrCypJYVeimgSUgrqEqLFiVGlljRoFOFdxPeTUSfiFkh\npYYckQQ0geRG/LTFWg9R4mNkHI4Mw4GhG0BKEAKRBHiHyj3TITPuasJgMVbyg//2AXZZoJMjT1uS\nFlR3E/pUM9qREBXGWqrlghQbbGnRi5JcCW6OBzbPe6bjgPc9QzpwsB3izLLkAfX4Ej4ZFqtE/PDX\nUN/3VxSvPGd5kamzJvQjhfUsKoEeNFE7pJlom0xaaFRjcZ1hJOODJ0mPrDxi7VmdahoTMMlDqAlY\nnIw4v8d7aNaG0qxwgyLl9wIkdxw5r2vUMDL6jiFEPInD7Z5zX4Ew7HcSVktqbVFnA6kd6XJPGgKl\nDZSiRrkGRI1Rmklfo+9F4njAHBXrruW14oSt3nJwjsveQ4L1sELriihaamO4d2fBy/dbVnehONvA\neiCJyOK1hvpKUe4b9DAydonnfzcR7tQIIpvbyItnkjyuSP2SrFuiqBi056gumcQNIXdMZA5KkpWg\nbyauB8Eh++/10TmbzWaz2Ww2m81ms9kH3g//8A9zcXHBixcvmKaJn//5n/+uxRZf/vKX+dVf/dW/\nv7XyR37kRzg/P/+vnnc2m81ms9lsNpt9cLyvQ4uQEuMQ6fceOU3kmPAlYDTWFpQLTeon3JBJ40jE\nM/aZbnJMPoEAlRJjzjhliGqBMIJkPL0smLRGVgVx6SiWgWWhkbLEovFpQglP0JmbdmJxYTCnDlkm\npMgooFkIZALtoQ0RHydCFQmveOSmZvc2bK4j6aCIo+IgEs4KdPaUIbGSiVpmkJIPScv+o6d8+/yM\n26nk767h4v+Q/HefPKVSnmUp4X5DvGNxSeJ2jim89w9zs5qoVlDcjVQLTVMpcIkcIylksjQIJDF1\nTGNCSImtC4LLTL0iBE3hJUpEknbIJoMeUAuFzWBMxnqBDgk8pBAgTlQnkRXgLwP9jSM7TzoIUl+S\npULEBpUajNQQFf4YCMdEuJaQAzobtLTUVcl6XbF8TWBejph1pGSkGhyrRvPUdgx+pHuROe4lx8vI\nOAqElpAVrtdU9g42KxpdUNuKVlU0VUV5VyDue+KpgzKyaAxysKjBoIYSDi2uz4QJgsvELBFSIEMm\nTSNBj+R8QNojVR2BzDDCYfBsbnuUFCzbE4wx+CkydIFxHJmcIGKQ2qKM4fRiiUuBPHmyGhEiUqwE\nLDyT0GRZ0BYrbHov2rGVRZqJ0Y2Eo0RFxXh07MYjnRxQNdxb3WOVP0ar77M0PQ9/5BnPP/JN9Ife\n4uRuz93FgnKo2FY9KE+hBdZqog5kDUUSVHcF1R5UKLjsI13KiDqQ257moefsgWRRSypZYlmSRcnV\nC3j61oE4CNaLexSrJdtnE8MgGWPGe0+lNG1ZkUiMyeNcohsGnPfsDoGTa8n5gwXN+RK650zVgSQ7\nUogoXaKlQGExuUaiiOzR7QjrTFxl8sFwoRbUwrKZEtswkXyg30cqu2a1vsvZ3Qe8/so556cTsh5I\n+kjIG0IK5OqUXBmEkshkSG7k2Zs73KVCesnxaOm9QrUlstCwkrh1YCs6+nyNDwMqJZSQRCUIQjHJ\nwIGMy/F7e3DOZrPZbDabzWaz2Wz23wApJZ/5zGf4yle+AsA0TXz2s5/lq1/9Kp/97Gf/yfP+9m//\nNr/+679Ozvnvx37mZ37mv3q/s9lsNpvNZrPZ7IPlfR1a5CnhjxPTYqLIHfmoQBRYXbJoWsy9mv0z\nwe5qjxs9UiukbakKyDaTgoRYMqSCTVKcVjX2rKVqBYfR85ieypYUdxbUZ4ITZUFm1GDQZLRIWAOL\n1x3LRqBkIuSMSJoqKU402BQxU+Kuc1iR6MqJ/kGAo+fFX1jEk4C/iXAjYcwc6Dj4SOMktyFyhuBl\nW/HQacJdybvrmhtTc+mO/MU3HPdfLGjbnuQ0a33OtjXcbgAJZCAnpPLYZcAuHNp6ZBhJUyZKg1AC\nqUCkRJ8cIWrKRY26V9HlzOFdTxoVMmdUmsAlqvug/IhUGSECLvVYMjpn4iTw08ikOlgGFmfQ68Th\nAGGUqNFSmIbS1iBKjlngQ0SkDFKg0OQp43YRtVRoA8uF4tUHJevXEv3LE7E6IIY9ae+wqsSUe6ra\nIfeSzU4Qn2q0qkHVTMHST4bUnCGbkqItubOqOG8sJ42EBwP+pYg7BVFkFmVGDaD2mvxC0R8ScfD4\nIZGQKKUwSVIg8ccON27Qp1uqOwNqmfBHz9AnjsdA301oaTEiIBeWjKTvB662R1yK2KqkLBVWVAxO\nQFZIQKmIVgFKjywjqihYtAV3Ty0iOkwTCWKPmyRx11JsTii1ZdcNPO62qLPMqih5wAPuhEfcXz3g\n1Y/tqf7nv2FYvotqbznVkpOosH5Br3fklBFEFpUEkUm2gMYwKY3xGilKdpcdToCoPa7c0Cw8q1Xi\n/NywbhoKkXDBUupE6o5sRaIuAiavWLcaETTRG5I1DGFCKEVZtRgEMWmk6LjpDzw5dpxYhVQVdx/X\nCFUQOkhtQCbee87HZGwhKJWGkPGyQPiJ0hTIumUUljgkjCooREnwHs/Efgr0OtGu7nKyusPF6gIr\nNkxuwI2JIAXRCfpdT9cLup1n2kdQns1+g3tR0Ywl2qxpzxP6XsHpKrI8PyLvRVy9JecdZoo0SbNU\n78VCLkr6PlC7TDOHFrPZbDabzWaz2Ww2m/2LeOONN/4+tADw3vO5z33unxxb/GORxX9cZzabzWaz\n2Ww2m83+397XoYV1Ao4dUz/hSk82a4qLOyyLM2p/Sqbh8muJJ5uvMx7Ee8+DnCqyGrH1CnFYIccS\n4QJJ7hHrgHlNYU4E4moibjou3Q2V27P2CTsJ3Jkj95BSpiRxYeB/uLtkpVfUY48dekxQ4EFrSZEk\nhVMoZ5HCsfICX0zIheD8dUOWDc+ev2D/bcXyfgnLkfBOZvc0kBrF3Zck6/ORatK8Wt/y2sOCr59q\nnrx5xXfkgSf7B6y/eZ9w6yio6F4k3BCQWlFIgwJMG2lag1SOfDzgjyO2KJFVQU4SHzJJJazSWF1g\n9BJRrhlrzeNtJqdA7CeC69CxIg8B4zMUCppAVgGHh3CLzJJgMrGcEAuFloKmVCyrgr5rEJ1kJOOs\ngkLhpEG1GRkyIo0YE6nvSBbnFkaQQVA0gtWpwuYD3XiJCAd0ygitue0EopYUWVKMkWYQVPIVVLug\nWDeoRctkWna7hCkUy7OCs3uG+2cJUw+4u1tkOyGtR0hHhaEzgTHXxH5Nv69BZ7RVFEZjrcFKMCpw\n+fySIJ6xakeaU8kgBgYiQxB4ISlazbRPXD3fst86lCwYh4TWiklFeteTU0OxXlMUFQSN7hNlcBg1\nkWzP4qSmWpYURYnIA106QBSEBCItqIu7FOKcF8ee67HjWm1ZtwZb3GOKFjv13P1Yx8kvS3L316jy\nbao8UPWnZN3ixAlV3tNWAmc8KnvGLZzKGrtccCgLOqU4EUvqHOmOBzwDXvbcqSVNk1kjODlKYgiY\ndWBxobFN5DtPDmy+s6FUS17/2Ou8+W3HzTcG+s7ihUXXK+6ePeDu3QvKquLx0+f87//nf+DFi1tu\nuoxqBOnPAy9ft9QXa+w6UJxmqo8XtAmM7YgZxilAhO07A/UoCNvE88c9T6ZAeVbyoZMLOCwYDgdS\nTmRdoE8lgYnj8yNUhr417IZElyaS9+SgyU4R+sxx75naPdKMSHGPpbzHSbOieDSx+pFbXvvIgQdn\nPeumoK4ModZYzhDCEmtPKGAlocwl7XXiz5mfDpnNZrPZbDabzWaz2exfwqc+9Sm01oQQ/n7snxpb\n/P9FFufn53ziE5/4ru15NpvNZrPZbDabfTC8r0MLfIKcEKVEntcgS/pTgY8V/qbh8DV482uBY4Ly\nXotcVmzjke1tQHrDR1jyqF0g702Il59z53yPXQdUkynShOQp5x8eefBg4lUraEOk7RRKZUphsFJg\nrCP0Ae8PHJPD58iUFAGYvCLHjEQSSkmKEH1k12V2/UTPDXpVcVHVGFFw9ReJw3Zg/8Tzyh2oXgkE\nD8+8olWBm/CY4iNXPPyfah5rzcb1vPWngfvrlkLATmSubw70fcCKTLSWtrjD6vQuVZnI+ZYwHAiH\nSBgnQvaoE4HVApsFOXtqqSl1hpyY+szJomC3tYxDIAWBmAr0WmOKe5ACIXq8crjk2CdPiB5hBWVb\nkIFSVqioYIJpzNx4qGpLbSqkLogukfoelQNVE1ncgeVpomgVficYDnCII9/+1iUPtIdVJFeOMUTc\nqDgeemyRENHwsr7gQz/4KrduwYvjQEQgZKYqRlgkqhJO2oGyTPhqIj+IdPKG6EdkCBQqU4oaX0/0\npiAWI/psTWlb6hWYKmANEDzPv/MuO/0MUxyZsuPqxYRoDFNM+AS+V/i9wkQNQRF7SARiTJRLjXMR\nJSIiRLo0otOaOhYUEsrG0KwKzN2W+x9esjytUULTdxPP9z2344EUDGETePHWAfH0yNvPt4w5YIsG\nv1E860YGuefBh24oH3kKNnwr/glFDXVuSDHTuw5bP0X7kZOsiEHgY8TjuR4P+OzJ5hS7POfZwZMc\n5AGklqxFTbrNqIeGSZbss0GpjOwC22PHwXjUhxLFg0hi4PL51ynOWj786orNc/jmWwe220i7uMvp\nScvJ3YLpEFgQWGmL0gLnJ/7ynT03O8vdp3B+UfHgNUf6AdjVPWhPird4Is2kaHLNtKl5/k7kyWZP\nXJ0hREZHgY4SMcA+JOqLgsjI9f6Sd4+ClhJfJabzRDoL2LVDFnvMtubVV9aU5ZJvbSRP5beRKnGx\nsrQXDc0Dz+LD79B8/zVNVdOk+xTiDO88bd/gs8chkIWkjyPbGLicIv2YvscH52w2m81ms9lsNpvN\nZv9tWK/XfPKTn+RP/uRP/pNx7z2f//zn+cM//EN+6qd+6r84z1e+8hV+4zd+4x9EFgA/+ZM/iZTy\nu7bn2Ww2m81ms9ls9sHwvg4thkNkGiCh8UpwjD3OGdJtJL2pmb5tOW4zclmzuF+RreH6OwcmZ7m3\nKvlIU/JvLizmoxP5Bw54+y6j6uliRK4cP/jgyOlasq4EKwytyJRoJj0RfSCnSPYZPSQSEakSWYEj\n0+dASIqcM1EkEBJKwT5KrsfEIWbkOlE5Ry0axslw/S3PzWNFOioOnWSxzISXE53O3I6RoBwnH5l4\n8Mme5WPN8O0C9wz8UECh6NVIoEQqjQuBNIKuahaLV/C7W4JL5CGg3AgyoYwhZc80jiQrMCjkKPEH\nj98NpE6gTUlba4xY4QdNGHd0lyP1iUFETQ4KWRh8dPQuMuaAViBzAR3InUJuCkokxiSSzASlGTxk\nFwghYTNY5bGqx1QBc99QnlWIo6B7y3N8GnHXguImU609efleDOB8xklF4VsKV2L9KUqsuIzgM6SU\n0NlRmsCillQ2sjjxyPXAWB+hCCQxoUJGxfeeT3EycZx6xlgjy4Li3KHvecpzgbKROHr66wNd+ZSp\nPVCtEvUdiUDgDokYIA2KNEjcPuGHSPYJqSJCS4SBermgWUvkssDEEusKPrRuMYPEJo2UmSAdOQbe\n+tsjLm05DI6rXUc/ObZXATHViF4z3gpkFFyFjrGaMLpAOM2UMlN9w2a15y0R6B8/py82FHmilYEq\nGwyZMe4wfkJphVYKIws6erAQZGZwnv1+xztPRsiWxih8tkx7z74YWCdDkIYQBMpHVIpMwhNFQkqF\nrMCIhLhwlPUR2UamWLMaSsJB0u03vPmtv+b6MtEfN7xyLyNixfWtZ78bGEaP95kp1tTFCjVG5LBF\nrDq8cvTJ0avMeMhUuwXDteRwK0hZkpUnZYdSiUIXNPaU9VJBVQEa7z2dGhh3EdEKcmWRJxpdj+Ry\nRJmSVaVx2lIeVzjTIHWLaVuKRU1dd6wfBRarjkpB4SZ09MQskLKEbAluIsZENJJRwtEl+uEf/lFm\nNpvNZrPZbDabzWaz2T+Pn/7pn/4HoQXAOI787M/+LL//+7//n73Z4nd+53f4tV/7tX80sviP889m\ns9lsNpvNZrPZ/9f7OrTwDo63ic2LiJORMU6kPYSnB/zXe46PBbf+AFXGtBYfLNPeUjhLrTynj255\n9EMHlj+0J93bcdvf8NZVz2GfqO54PvIwcCZqmiRQIROjYCcjLnmi9zgSHZk0WlQtQCucEEwkxikg\nlEchEAg2wbMfYJ8inQcxSRaNQJ9mskvcXk+8eDty89zS6JKby0R55dDbkeNJZOMzH20y988Tt/8m\n8ehvPd1jCUMiWUWUhjF7kimQSRBCYoqJbspsnmiysEi1wKhAJpMmj81ATu/FIDGTesVxn2HvScNE\nzgZReNpKscgl/TZz/e6RsRckCyoJdLTIrBDewQg5JvzoOXYJEyR5m5GjohAGqxNDjvioIAtUBhUz\nVTlimp7Fec/i1UD5qkIvAmmSlC4yHRPDHnbbhOoEqq7IxoASFNSoQ4Mel+T9gt21YNNPTEDOYHKk\nKiLtUlBbh1kNxGaPswdyjpRCo4RBZwVRcBCBfQjEGKnriFpMSBMozg0pOrrxwHbaE6o99sxjlwLd\nSLTUjHuPO2pCp4hHRT5APApiTAgbUG1GN5JUOwpTY1JBkyrWueFBbTk+P+J8ZoyZITrGGHnzOxv2\n+8BxiNweHCGU7G4NcczkfMCrPZN+h3pZc6c5YynvIDFMzZ763o7xzPGd3RXP/sO3eenDkbN7ieUq\ns0IihCbJDksi54QErNSMQiKUZJsDt9OB4AL3LypKrdhtE1cbSX+Q7GrJbYio7BBCYGXAu0DUkJGU\nQWIoUdaTGgmlR2VHdes4NxeM33Jsbp6wuZlYLjwnZ5mz0xKZS0RSPHmRiCSuhoCwiovxhOgs4iCQ\n5yPJTDiVGA34nPHHzPEGhoPG6gpiRqmMGwKFt5zZc9YXK7bZs/UjR9fxLAfUvmBVnFH4BdI5YoKu\nPyKyQOdM5TPtoFDR4JuOIe1xoUV6i+hbhq6k14Iihvee2UmSPmWckEQM0iekzHiV6HximOYbLWaz\n2Ww2m81ms9lsNvuX8sYbb/DFL37xH/3mnOMXfuEX+OpXv8qP//iP/4Pv/6XIQinFpz/96e/mdmez\n2Ww2m81ms9kHxPs6tJC2oO8yz986Uh5GpPbIXNE/3rJ/s2a36Xmen7AykXGqSXtL0VUUKWLSFnn/\nBcXHPYsfmIjuQMgREQX9QSGNIPuMtIYyJYRP3ITELncQPNElvEq81wxUZBuJStPFzD4GUidp6kCp\nDCIqDhO8+W7Ey0DOhhqN0oL6RLN7Z2R7Gbl8ITkcWmhPuDw40rtbto0DFwgPEz9cZU4sDI/gh/6d\n5PG/H8luRGpB1dT4QrLzHcFNIEEAwzTw9T97h5Mzy+lFg15AEg4XD8S+p6wyRitihOOTxPbWU8SE\n0SCLQLucKFtQUhGLCblNoCV77zEiUQlDkS3KG0pvyINmGA4cvKO2mSwjloTMAislxzEQXKBqNauF\nxtpMdbdDnu44ey2zehli41DZY7xECY3Kkv3fJIZDIosKU9bIKkHMsCkIzwtS3+COFdcvEscsScbi\nk6fMkbaVLM8idRXxVU9fHHFigpiwUUGW5KiIDvY5MAqDzu+FAak4kKYON0jGfcfuxYHDdkJbRb0U\naA0uCnAK33nGG8O4laSjRowWNUmU9UjtkHVAnEaGdsCkFWa0mGCok+H2asfzd67YbHtGEciNYETx\n9FlP2teosKR2ln5sIWeG3DHmHb255Sa+zaviQ7ysz3ioTihFQXilp/jYhG4Tw/OR229ecppBvaao\nzgSVUUSXWdiEcIqJQI4OmaHNmilkjowMcuLlE81HfuIhaXR8/W8H9oPnuIW9Uzw99ISVQBeSxoLv\nI4oCIyU1lkWuuNEdsctM2UEdaF+V+Grg7bcm9ocR7ycQieVdidSJ84s1Ulb4oeDd45Fj13Pj4HrS\ndEPL4nhBcFfEMiJNQMVMqg2HIXPYS0IoWZQLHJGj9FxdTSgnWZ1ecH52httv2NxObI47ruNEIQpi\n0DRdQ3m7xhSCmz6j91C5gZQ9lR6pZKSLb7PpFLvbmpMXC7q/uUfkQKx7YnY0ckIqxWBHogkYNJVQ\nhBDIKhGIRObQYjabzWaz2Ww2m81ms38pH//4x3nw4AFPnz79R7875/jc5z7H7/3e7/0n47/7u7/7\nn40sAD7xiU9wdnb23dzubDabzWaz2Ww2+4B4X4cWZV3RrAxRD9xcHqmkZa1PkBtL2B/xeSBVHp00\n+3cH/ItEuU0068RrH888+Hcd+pUtbpzwfcY5jTcRXyS8E4StIZ0agpfgQAqopGATEv0UgEQpM8t2\nz0Fb/m/27mT31vO68/v3ad9ud//+tOQhKVKybNkql1WyKwEyCEQVoUwzDXwBvgL7YnQRuYAgUWwk\nrhayJIukxOb0/3a3b/e0GRzUIIDjFGzCIqT3M9vA3gtrtCbPb6+V0JggqPYC11qOCwFB0DlBGgz5\nNsBYgFDIRYE9LxBp5MXnr1lfSmReIUzNIRuGruD2F4HiRc/FleP7//NIWWh0EFyUmT/4fc9f3wO9\nu+X0/nu88+QRY5H42dOnvB4HsvIYLVDAdnuHKY4pa4vRgqqy1LMKRIsmk0bB4S6xeQ1hB6UW1LWg\nqmHxjiCIDc4nlEmczBz6OvHikwMpGApRIjAYa7EArcQNAR0ESilS1zHmhCzg+KhkaOHu+oAUcPG2\n4v6/ihz9gWVYZpR35C7Q+8isXDLWA7kJVEmTbmoOL2FwCpMUQmREgu4lxGtBezNw2IOLJbZYElSk\n294RisjydM63/ztJSi2v2h27Q8CNCdHz5pxHNrhRsut7buiZ2QYjNRmHjz3ebdl9HuhvA6GFUhow\nmaaW+BQZ+sTQCg47CcKSYkW7NcStodaZ0grsLKOOA3keGaQmpxol5uz6gtunW774ycdoK8EKfCVw\nyiBlQZgrxq3CrQ0hryj1fWIY0aqlyRI57tGzCsZItz3g9B1ns5p3vqc5/nclwta8/NvAry8fojZf\nEi8Dm+OMW4zYGIidoHeJmDNpTATfIfPIwcBpU/PQFJzkhFQvoB84soEjCS//Gra3A92XA/M6oVcg\nB4VNNYsyM2pN9AYxZMa9p0klyhbII4GrBf5wYLY65ui0omsjUnsGLVjajvm8oa7myK5k/XlDiC1Z\nWg7R4lLNXNZ08iW2HJkxsHeZZ0px+3pEBcHZxYKL2TE3NyO3m4EkCuq3znj4p0+IvSd9nBFRUskK\nOdeMuuOX1x8TnxkW8xnnj+a0fUW7uwO3g8HQ1tAUhpAFMkfcbaBtDasn76O34IZnrP3AqPeUc83y\nOBBdT9d5kBXaCk4KOK8l82a62zqZTCaTyWQymUwmk8m/FCEEP/zhD/nxj3/8//kd5xx//ud//v/6\n/Bd/8Rf/aMgC3mzLmEwmk8lkMplMJpN/yNc6aGEKyepkjjkSbHpFe53otjDuBIWuODmveLU94PaG\nft0Rhy3zdxTL7ww8+B9eYx7eMSRHo0pkVYGokeeS0AVuPxG0VUeYj/QanIaNELRFQc4lBQmdHEYO\nWAuVyKzvRvY3idwrCmXQXeKwT6w3ka4fGV4IQrckREteaGon0DKx7yydAxchikQXHcIbTmzJWw+O\n+PYfaY70gEgS7Q0LImezlnf/rWXzn3oe3kv84Xs1QSsSp8x0ZLvtcWNAycT9kxMEkrE/cDUeqGct\nJzZggiQOApcU7V7jsYzBIrLBSqB0RDzb62uySGhdQKOoTWK2k7QvMrfPRw5G8eCsIsiIy5ksJFZr\nYtdTnifqc0N1ERGLxOZzwe7TyNlb8N53E/MPduR6gx0k9HPSoDE+I1yiKgRSO9RSoh5qbr9I9K8j\nQib0XKBRhHWg349cXjraNnB8b8777zykPWx5Nu7BD7S7gf3G4lLLEEZEBBEFjZRYYQkpM2oHczjR\nDTNKTNSInPExcLsNDNsEPQiXETGBkKQoEBpEBB8St7eBdtuyvcq0NwWiH1mazJMniaOLRHOmGRcl\nr69XbJ5VXP0sE391IPQD5UlB+ZZFrgyDgX4Yefb0mtqecfLuPU4fP8b1FabyGs6kAAAgAElEQVRa\n0V/e0A4RlU84kRY9P2N3CLQpsZYbHpeOqnLMpOD44h73//QtznnI1ac/4eWvOp67Le5hT9uAbiys\nJYsmcNQkajQVBcZFllbSSBA5IHC0eSCUETlXlLMC5RrmcY5HsJ1pLpaGs0NkIDMg0bpgUdRkJRhv\nD3S7TGgs/UJRnliaWWZmBQw1VkFpE2I1IOs1dSP4lr3P8fmK/+vvDC+3PdvbO376qw35LPPWe3Dm\nVjB0xHbPMiXE9zO1VKxIyLs9hZDUrebhyRHn9xaEVcdQHyg/iNw7m7F7bbl+tmafE7NFgZ0X5B6u\nPxnIZoWo58SyZ8wdY+yJAQ4d1GZE1JnV4ph4CLRfXqDvGfRxR1EFlO0Y3B5dCwpbonuD0IJhP+L3\nEeGmjRaTyWQymUwmk8lkMpn8S/rwww//0aAFvAlX/FfDMPw3151MJpPJZDKZTCaTf8jXOmihpKQq\nKprSYLNG3K/Zbyo2ocZR0MfEeuh52DymOZGIZsvs3R2nf9yiz27xYkcYJSpqRpkZBQwqM5CJO9j8\nUrGZCcK5IpYZZyJ7AaNMKJ2YR7DZcL3NtGvF/k7ge4FRGirJ81cDwUmCN+QBdLYMXQ15htCK7tLh\n3UjfanzMxJTJ2TF60EKxPFny6HHN+THMEcRWEnSBMAkdM0++Jfn8eaI+6Vgcd8g4553astMWbyIZ\n6MOITAMWjZASqQuiMOxbiZIC0WtGr9ltJPFgEKMhK4UcBXVMjDceNUay8OQUkNJirKauFH0WDD3E\nlHm9HfEi4PuESIrKCpRKNMtAdX7A3k/IZeRxrSlCphF7xt2BqtuRyx4dNcFJYrCorEnDgJD5TYoh\nC4SWyBKefwFNG5mfZEqVSF6CkAgpAAExUKpIZuR8BdlK8AMvP92SdEuqAqaUaGuorSaOiTEODHiS\nTJTKIlsHY6QfE+vesesFIQlykqiUKeSbG5x9SLgx48eEbzPjaHFjSYwVqBIWUJxFyvMDdjWiikwa\nCvZruP1lx/oXPe4FzKTmvfMS/VZGvpNYnhiOigb788TdzwbcvuXkFN69N0PNNIu7is02414VxM/m\n3O4s7bAjAsq2NGNH+StHuCgIbY0JFiFrdHMfly7YXDluwoHdvcyythQ2E00k6whCIpPGIsBndqNj\n3Y3IBhCZIAWzheL81HLzScbsNG6bWZ/BzUmi9IEYCjqX2LqWLw4tfudpwkBRC5QwtA4GF1FaUhuL\nF5k4ekIbkI8E+sxjzRZ5LLiojvgugtNnls26Zb/dcLn2zLcjuknYmDC54HxmWcwlSgdUf0tix/xi\nxjel5bAvSNKx2bxANI7iKGOKEjk2jM8lIlbIMKCVRssGyZIin5MzeD3Q25ZWHSjjBVV1hbGCG7Ph\n4/gJp+uao2NN0a04FIac9zQ2EFOAHIkxstkP2EKybwPDQZDi13qsTiaTyWQymUwmk8lk8lvnww8/\nRClFjPErq3lycsK/+Tf/5iurN5lMJpPJZDKZTH67fK1fBEXWaOYUWSFSRWErAoZoZgxOcr2+wQcQ\noWB1OqN6S2LfP1Af35HMgBaSKlvwGqEy0oAsJEoLiJnumcHfF7gm46rEQWUGlehjRLQRHSXzsqDd\ne26fC/a3ghwV5dxSYOkOnpgE2SvcTjAONSHUWNUQXWL9qqPdO/brhBsVMQliiLghcHRUcH6x4PTC\nUdcb5qJCeUlKNSKDTLA87lhcBORsTTRXNIXkvIncs4rRKIYsCRH2bYvZS7TO6HnAC8EoFbmTIBQp\nFIRRQ2dpdIWMIHWmchl/22GqADqQgiBkSRwlaS+II/gELib26w6pJSa+2YgghaOcK6pmpJqPqCYR\nNeisWVURvfX0N55i1yHqROZN7SAkEkFMEUUiBYFyGo2lXsEXnwf2XcZ3sJhnrJKEkFDGUJYCUs/u\n5iWMBxZzj1mCFCN3V2tkmdBHEWPBaMghMQ4DTmS8jpATla3Ru4zfwX6juGkle6URRUaoiFKRnBNK\nZxzQjdDvwO/enIcJvkCqimJRY2rJ7HEgz/cc1MC+jdxeJZ7/rGf380j7yqMGQV0ds1g0zL4RKL8J\ns9NMUyXOli1/1wXWP3tKtjWP/7BBru64p3pevxq4+lvN/umSw/4YlQVBHDikAy/dQPkrj9Mz1k81\nUox064g7ZHIxw8eacjZSao8JkboAK9+Ed7RMCA1kwy5ENgfH3d5hhaGaSbTNzGaCoxnc7RJqkyl7\niYnQpcjr5NBecgiCnQscxhFzkIhC4rWgFdD6xDiMhHHE9ZLhIMlKU1EyW8HswUBRO8JwRX2x5+23\na4pfSF5/MjDEFj339H5k02dKNCUFtaowKjGEAy61qFmJfTByUZ1TXUXuti393lGWiaIoSEFgdEFt\nC5QuCaZFG01dLFjMjlkWZ4QqEErP6GYczJLt1cA1NQe75iAP+HxgvJnj9RKTZ9SqwBeadkgkRorQ\nEwfYXjtmdYELgugt6f9n7ehkMplMJpPJZDKZTCaTr9bx8THf//73+Zu/+ZuvrOZ/DW9MJpPJZDKZ\nTCaTyT/kax20yEmT/JzkKrw3hM6RhKEqlrB1vL49MDut6VzHfpSQA1EOFMMN1gpO6opVqhC+olCJ\nWSFY2My8EPQ+EvYKeZcQbYtbDeykYjdmuBWUd2+CHmNTEXeSYe84bBNu1BSdpjxYTLViCIHdXaC7\nhP6g0dkiCkkIjnbXM+w8bQvBaUgGGRU2WS6WM84WlrIaEWXGKIFCkZJFeIM2CSP2LM8iIV6xH59y\nfL9gtkq8tdAcWst6CCgUfgi0r3tyCqijQHkvU+uC4BShV6hUU+gZ6QBFUxO6Hp8HZEhE26F0izSJ\nEC1uD+2zwOGppN8pRjIhBlwvmFc1VhsKDbYaqE4KVHFAEsgjtDt48fNENcyovCCOicElchZkJEIq\nooY+eqLxGBUpo6LyFjAsV4bMnv1aYZAUCpIWHHYjQinqFSjR8frlZyxmiqNTTX2UCcoTiEgLFIKs\nBCFF8s4RhowoNdJIhMyUssSPkcOdZXdrGLzFNYYgPFr0aOXxLhKDICaJGwVuUKSxIHtFzgZTlRS6\nQRWSlDuud5mbIdLvI5efe17+xxb5asQOkSNRcl5JFu9E3n7fcfJYsBAZ6/ecnT7D/cGCn7/aEoLD\nrhSzty5ZnPVUpyNsjtAvv4l8sSJ1kXVsyXKHZ896C+Unlv3zHT07Nl2H33fUS8n976x471xwfn/P\nXeewZEQHRkgW9ZuzLA7L7d5xeZ0ZeljUGTkTKJuwhaexChkz4iCo2oJmL8k5sh0T0ncI2bBQDauF\nZVYptnhuVGBDIsSMcI5hu+f2ZmS9qVgtj7g4Oub0omJxvkGVW0Z6hN1B1qxWGXUiIRqKexFdZpxL\nyJSwQErpzQaXtmMInrKaYU4FcZjhTSDrjMyZ7B1SgxsdY1CIZY1MhrIqKGzJwlhOqsTpWU9aOLwa\n8KPHXcHlTyOsG8a45yA8SmbaoeX6Y828W3JczElLQ+s7WuMxZY+Mgn6ISFFirEFITWY6HTKZTCaT\nyWQymUwmk8m/tB/96EdfadDiRz/60VdWazKZTCaTyWQymfz2+VoHLVJS7HaRiMdYQ7UU1KcV1zcj\nL+5uuB3ueHJ6is6Ru/2Gl393Qz285n/6X455p+44VYYiN4hUkktPli1Nl9F78FtBN5a8eu05uxBU\nx4njmPlP/2ePWmu+dW4o55rXTwPPbga80KArlDFsXgdevrziW999gJ0riJ5xyGy3oEVmdIHSSsri\nmHI1Q9CxTwkRNXZW8vjdBxxbDaFn7A+0bsewvGIpGsqDxwxz0Jp70pKOBXcvbvhsrbl4MidVBegC\nFRWq16QR9uFA81BT25qiNJSLxOwkwJjZvsq4XYHSM9rNwJEoGTYDjCOpg+IDi110DL2nvwJ3V7D9\nhaC9UQxa4hcSYQ16BOUMRZGZXwgWjyyLGfgusX7RcfP3metrQ/Y187OSwY9cbjrmN576MYTUYopE\npGD00JQaDagA9IG0HyhLhUAQk2HoFZvLQFlLuh6OHxQszip22wPP//MN8wc16qSGpXxzaiWXyNOI\nWWmSErStRzhLGDuUEJSFwGjF5YuBL//zQPuqQWSLPlpwdvSAL/fP2LcDTRbMrSC0kX4/EHqBDCWN\nLajuNZTlPYp4wbiveH134Iu/3zEMknaU9GMkjIl9GKgbQaUzM61IjwPqW1esFmsuBstRXFBbyzkK\n+70t8TW8/kXL9foZj7/pmfk9yyeK89U5n150/Op/e4/qP2R8eyCIA4Q9mBpFwWHjuA5bdrLlsB2p\nu4on//pd3n+r5+L8OYe7a/yXnuF5wAuPek8gSoM7VNx9qnj6SabtJW8LR+w88hQaZiyWK47Oenxs\n+fW/3/L8154nH0QeLSqkkDSrJcvlnFp7wiyT7jzb0iMMyBsN1zBsBPuQ8YWmmS9YzOc0S01DQnQD\nWfTkS0vxjufhv86o3xeMfeTzzzq8hEAgyYjJBUYJbGyoiLi4pe8HZJgztCOHITFkiVQSf4h0hwOH\nu5ExCYq3F/R9frP9xRTMjxoWjxvs40viwjP4O3w7YB7POF8taf76gld/f83T3ZbVCh59/4TZvqBf\nOz79mxvksy3f+L0l+vERtnSUlefoosDKGf0+k+4SIUxBi8lkMplMJpPJZDKZTP6l/fCHP+Sv/uqv\nvpJaUkp+8IMffCW1JpPJZDKZTCaTyW+nr3XQIsaILCK5cezTHb0e2MXI51eC243mraNzlqlBjopa\nlLz7eMF7f3rG2/c+4bS+pBgFoZsRxBGF71A60CRYoDk0kjFXbNOAHTy0CZEHziporyS3rwXZKYrF\nDOMNNzc9u9uRNGZULFDljM2VwNxkXKdJrUWMgiQNY8gwJrAZEQSlsVQnBciakC1CC3II7Dcdt5db\n8oXDCktzbBAqo5VHS8EqK8Yzx+3a8XT9muUXf8+753+IXWhmhWSFZHSZqDzaJ3Rp0TOLqAMxtuiY\neftiyeLRKSrNuH3ZkqTn0Dpa0XGTJXoYWS0LkjW4oGlfV5hdyYmeI6vM1goEFh0TTxaZh79fMPuO\nxh+PuG5NeOnJ1zCvKhbvn3M8e0K7gXG/RpUeGQ4M657UZHxUDIfIfufJ92dkHzEtFE4jZyX9c8Hx\nvKFCknyku43s1z3VkQIbSapHG8/Rkwwne7rZgbC02FlFoSwUmRgd3T6zXwsqLKWsqbRFeUV3F/j8\nkwP7G4s7GISDcsws72XqzhL2kIIHkxFdog4KmSxFrZmdeB40JYKK/Z3k6eXI6y9bDncS5CkyLihT\nQhrDyeMlVgFtQOw8N3LPB/ccxaxHyyO8v2DXBQJHlM0Vj55o8qjfbEe5luRTj9E9wvas3rvj4ZDQ\n/THPPu652zukTehakpfQmDnOCfb7nqKUaAm3V5nPPrFEc0JGcrm/Y9sfKOqSR8Wcwi65e565+SLg\n7iSFKBg/1Zx9+5hiYegHx+Vdi68dUUSs0TRHhuI0YwswsmA3HPhit6XLAW2gqCXOCapQsLhqCJ3l\nF2s4dJmysZxfnPDw7BhRX5KqjMyCMpWIUsAwkMNA9CNBCuxRJuYK4QIJGGUm6Y6DH/AkvNXsYmL7\n0tG9HPF3ijRKkBEpPfNjzfE3Z6iZYAgth5cbJAopDXFV4d6uOHwrUtSGgh4delR7wFY9659GHs6W\nBL7JS17y8csXnNqKe9UD5uUS6Qq+/OVAvc3M38noFbhRMKtaigx+SMTggOY3PD0nk8lkMplMJpPJ\nZDL53fLHf/zHPHjwgJcvX/6za33ve9/j/Pz8K+hqMplMJpPJZDKZ/Lb6WgctggtEEi4P3OxvKNXI\nbRfx9ZLZeUOyhvauZxwjF0cz3r9/zPtP5lTic5QAoT3CHBBJk3MmJbBZUQkQEryBoVQMosJ2ieA8\nViRiJRh6uLx1mH5LREGKDNuRbuepjWB1siIPmt3GMx4gZUhOIstMzDDGBDFTGYs2GiELsrTkrEkp\nIpVACEEcDO6ygNizTQOUkmzAIpAHRQ6AFHQh8vKu5ckDRUskacmstATfYE2iHwaGkIgHz8JIjCh4\nWAtOFiX1zIASFCeafT9wkxyd9wzRMj537O4UYRSES4G8VWhlMZVmUQvKJlNWirMHJQ/fObB4Z0u6\nN7Art4i5RxclWij6ywKh5iyXx8g4EkNHSAJ/FzFfCIqLAilL3EaQ1hJCw5De9DxEhRgT22uHCRVZ\nKpLUZGvwQlJXChEy7jAihGf1tkCfe8Iiv9mgQIEZSuLa4fpEHCQ6VOiypmgKci/pt9DuE/ubyNiW\nhMGivUEpw/jcoUaP6SMiJ7AC40pitjRlw+npjLO3Ziz1KYe95upZYHMb8S5Rqjmz+h6LpmRWWLSE\ntdjR4vF1JpUjLt3y8osNH7yTCXWPTzsQBsycWY6cXURu7iKvvuhQo+HRk5KjiwG7iJycJuSjPeKD\nim4XGYKgi5Gb6y2YiocPZhyvjmllz7DdkXpYfxr5vBA4XzPIjt22Yew1JsL6UwW/9uyeFxyuTsk7\niQ+J271n3AjqlaYsS0S0yNjRjS9Q845cBPoqcJslZvSMEVqZ2IlI9pLieSSNFWlXkl5qNi8Et1cO\nN4AtE8PQcfVcUVxs0XKPWgwokTBZo3uJcBKfIqKAUgnabYQOUAK5CCSrOIiWUEiGJOk2wAbGg0SN\nmjIXKCMRViDmHnG/x1w4tGm5eLLl7jLjWk2qSnQ940ytIEOOFSEoHCOu3CLPDLPjFY3ThK5k2HkO\nJrErPUZlmtAwbjtKVXMQhrwayXUk+Yhwgs3zyHDpfsOTczKZTCaTyWQymUwmk989Qgh++MMf8uMf\n//ifXeujjz76CjqaTCaTyWQymUwmv82+1kGL9jayuw6UVjBGGA8D271H1EfMzksObaDfjhQjyNoR\n9ltePb/Clre0suNIBuY5UpqMyyU+eqRI1I1mcV/TDhKxFIxothtN7yT7DeSciSR8NxL3A1qUhANI\nlxAuEvyAL0f8kBn3gjAqlNJoJEZLssjkKIkRxiywpUUqTczgUyTFTAbKQhHDDL+O1EaS5z2+kjid\nEWNCRyhyoigFY858/kXPe/cj69GRK8X8yCKyQVORYqQfB4a9QzrB8bLifKVZ1gqallT3NItAHHY0\nrsfdeg4d3N0GBJI4CFQnmHvJ8iRTH0WOVoJyFVmsRs6ONfbsEjMbcSriokMXkFcFubH4ZHBdJjQO\nJRJCJbyPjIdAVSiMtcSgibcSeTBIOSNGS1TgksDdZfouk7xCJIk2GlsYsjZY42HwJBLlTKBWCuaC\nZMA5SG0ibwRpIyAYrJboIiOSwsU3fXRtpt0L0lCBLxBOI71CkGi/6Mm2R8VATplRS0rTMJ9fsDg5\nY3E6QyvN9mnBqxctr75wtIeAXWaOjo54tHrIo8UZp+UMlTNPb57x68Mlr+KeUGZ0tcIfdmy6A6fV\nnqqwGDUjZknoS3Thqe8FijvF1RcaE2YI5zh+IKjnC1yRKU9G6nuZZrDEQ8Xh4LnarMnaMmtmkCLK\nCsSYGO8yl7+UdEmx04JgKqSusUZwvc6MGw9tiehX5LEhuoyXgtQnQmnxdYU0ms2rDW12VOyoXEcX\nO2RpUK7HJcEuSLZD4HAHxQuJ3M5I+yPcRvByM7JzAgqFMJpu6Lm5gfrXO+qiAz3SJo/ZWY6JlEki\nhKEUgrmWRBHxB0noBYcuwVkm1JFoE66T9IeMOERSl5B9QpIpLFSnGh6MmHs95VmH1i162dFUkuu7\nkZRGokrYOCPvLXIsSLkk546cblh+MCKjp1WGy2czNpctV3aHWhqOF0tOVseErSDcFPRewpgo7kU6\nBHEvGG8yYp9/06NzMplMJpPJZDKZTCaT30kfffTRFLSYTCaTyWQymUwm/yK+1kGL/UvJ5ceCWdak\noxVdO4LTGGUYRWDvWpKBKhncYeDTj1/Shp9yXt5yXkfOpeAhmfsrA1Eggkdmz+y44MEfNRy8gjEQ\nfWZ9nbi5SdxsE9YKjBTkkHF9xN0OJG+QWVAbQRgil8+vsPkIo+aYskJLi4kSazTITEqaDCQf0KZE\nKIH3iRAi3gcOIaJMTe3nmEPJ0WyF6G5JswGXM6LNLMTIvAjMVhn3InL58Y7PzgeEbygWksoCLhG8\nQBzePDaHIXB743nLN5i3KqQYieyIekSaiCn2NBcH9s5xczdwe5UolUFHSyUNZmlZPI4cvdNxct9z\ndDIym40U1rPrLzFJU8SGHBUHJei9IntJHiVh5xn1HiqBFJ4sImNMSKlIo6JfQ38FyVtCVZBjRTYa\n76C9cUQBMUHKAqsNpizRuiC7HTlnjJXURhFSIOeCOCZcq3FbhbpSqK7G1qBXkaA8+3Cg7UbGPtLu\n4bCXRD8juIzwAjGAHxzO75GrgSQiKUqirqlOzrm/+jbF6j5DgC8/WbP93wMvX1i8iJgTyfk9w+Pq\nnG+cv8Wj+pyVmSGyYunmuIPmuvuMvQ3Y03NWjWA7fspeOk6aDpMT7BVtN+CUZPVgTlHOePW/wvZZ\nwnhF4UvUSUW7PdCnjnykqJ1GblYYI9iElqefXaLEK8pjgRICU1nUqDhsYPuLwLaRYEuK0jIrS2a2\nQOwjsdcIV0OwSBSmWLIq5syKGteNPL98xctnGbk8ZplmFLOOcrmnvJ8Jg+V27Xh91XN76bl5lplt\nZoi2ebMhQmauomM0JeViRrNcgC1IwuBfZ8SJZKwyT92esKl5zwhOjKLUlkJnhIS4TLTXit2NZvcq\nYraR5TctqsjkEAhdJg8BuhH2EoWnKDT1WUQ/7CkuPEUZkF2gcPD43FA3mcttYptaXgw3rNw9ilCA\nkkhl0EXk6LsD1WwkZMtuX/Hy08BufklhAtLc4/SsYPfKc7dRZA32JJOdwEkQg8KETIH8TY/OyWQy\nmUwmk8lkMplMfif94Ac/QGtNCOGfXOP8/Jw/+ZM/+Qq7mkwmk8lkMplMJr+NvtZBC+nP2H0+4+rV\nwFjBvSdnfPvR+7id57+8+BU///IzTh8/5N3lA8yo6WMkFoGuzNyoAiMTqxBxhxGzGChHjYoeU0fO\nFzWP64ZxZ7l71rN5OfLy04DvBWOpKUqNVRkVIHSOtM/EJEEpSi0RqiAHyThGhmGg0pmmbFBRoLXG\nVJaqqjk+niMUXF7esl+vGcYIGnzIuKQZ4xyzl7zu1xy+uKR5uGNxz1MJyX0d8EcCpQTLElppGV9r\nTlYLrBCk6GhOIzpJXt4GQjviW8d4AH+kidKQtQM7IMsbDC0qOqTyDGPg9iYSXAF2jtUrVo3l0b3A\no3+1Qb37muZii7Ge2IPKmrqyhH0gHjoKOWeoMsVo2YaEcwKZDVpKikqA1QxRcrf11DIj7RFZVMik\nyFvLbiNRq5qowYVM8gW+HUhBIIQkYci5gF4hXECXCltHdPIoLxj3EjyIvUXtG/R4ipFgCoesB2g6\nhEgoJ3F9TzcO+GToWuh3Bj3MkLnGSkUMknbrSCkwaxruP/gGHzz8U8Zwws0niVevdly90LjnNbNm\nzkmpWZnEmZbcjyes6jnFPYFb9GQivt2xGgrO5DEOzdBLtj89ZrE853ByzavFC+TgOS1PwSyoKN5s\n+9CZtx/N+dl/7HE3NbJd0T3WfPb6jtuxpS8sfmkIrUE2S95vvkl7N3J9/Yzd66f4maMqGmrAOk3e\nOgavUKEgDDXoGfXpktX5MbPzgsM+slk7ksvMzAL2ieA1KWtkWjEMLSKXhLUg/Eoh/zYTVq8RRx2X\n60teXXq2fc3VIfN0Z7jd33HnrxhMJjaZd06W/MGD+9y//5AyGFwbmIuK4tATbjtiD50ObFpJVRdI\nrUm5pxMDyUqSKug6y83lwKy1qABi4RGy5NwsWVeGgAQiuobmfESeDKRiR0oeXEYHwWpZkWPN2yea\nSji++MWe3dNrvvutt/CFpos9WXTo+yPevOL6xTVXfkXyF6zyElNcYISi3R/YXO7wBszxEc2TFcW9\njj46lBboUuGjI/T+Nz06J5PJZDKZTCaTyWQy+Z20Wq34sz/7M37yk5/8k2t8+OGHSDn9iWIymUwm\nk8lkMpn8477WQYt40Eg9xxYNHsjtyMtfDpgsqKuGB+/NybJAtJaFbDh99z7F/7jh7uGOWAl8n3Ah\nE6zHCkOwCeE1KoOzG4Jr6bYd7cbDAAuzQtoaFyWpd0QRkAqCa/ERfBDkoFGhAFORRYUqLNYWVNZi\nCgEecnhzBsE2BfcfH7O+3qGcp0oeYzPdGJHS0raeL4Y9jap4WJfI+pix6+n6gFko7tIADqRSzLTC\n6MgvP77m+99fUVpPiLeoxUjeVWgGVE5IrWEuGXXkddsx9h22apGupa4Vh3Wku5HkdQV7ybiz1POS\nB9844fd/r+adD9YsPrgkzT3JR7iG2Bs+s4GYBTpErJFgwHceNga5ldALvIMxDgz7RJ8HxhCIZPZR\nEW4gdZqwq6AzRC/BZYYsCEKhtEKMGpEVSE0OBck31IVheVJTLTy6cYhiICpP6gNCaZhVZFui64ox\ntQzWsc97bvpLunjAjgrXj0Qi2moiHiMrvJDchBEReqQKaD/n5OyE737/A/7s3/73/Pz/jlz+e8ez\nX7bs+8js4ojm92fU1JQi0djEQmmOCoVcrSke9JSnHUl1mPtrdr90nH3iWX/qufkMHp2cUF9/h/z0\nNbf9c1q55mURqaxjJjVnWnJ2IeF7jqt14NnHW/7D325JP83oM1AnhiRBzeH4gxI1NsSrkeQiZVxR\nNQVjc8c2HtiLnkIqTFbM8xkqN/gDeAfb5Fk04LRjjC2HsGHrDxzUjIvZClU09KPnwDVpccAHwTgW\n+L5gPFjKu4c47bjd1lzfzdgMPU6MzI5KvvPdRywuTjhoz+giKkbOzk/44L23+c5b94ibG4pmxC9a\ngvGc5cSRzZgxcxg9h01gMCP2CBq7QJVLZF0gRGL9YqS/ShRNZHleszw9Yze0+BTAZIpzweqPLPmt\nHd6MhBxwo3izWaabYRZHkObMGjj/1pov/ssVn17eMpsPVAtJNfd0uydVVMoAACAASURBVJ6tywyi\nQJgCguR89YCrkxavDzx/cYW7gZPqEe/9yQPm93fE4x3JjKA3pJuMPTEUxxUcftPTczKZTCaTyWQy\nmUwmk99NH3300T8raDGdDZlMJpPJZDKZTCb/Lb7eQYuc0MlgsyLEDtd5nt/eEnPHuNrTnBZU6ZT3\nzNu8f2RY/V6P+Ibj3syQpIE+owN0rmS3jhA8noSvBcFK+n5k7AdGnzGy4Kie0R8qRLZEIfAxcHAj\nvVfEJAgRYhYoDPVihhHFm7MLUr95xNcJ20BTCZpKUjeCjgP74QphDsyWgTEEpARlZnTKsg+Z6/5A\nvxk5XwiWswLd92xypDeJpjAYK1nKijlLvvyipfv2QKFHgtyS5IEhG5S12KKkUgYrJLKU7O5aoryl\nkndURUtWBdurjLupKXYNxwfDUVpSmBmlUig5okyPljuUiqTBEJwgRUl75+iyQNSCsg6UciAeBPEm\n060lXS8IZK52PeVSEXUmSYNUDW4sCKMEr8EbRDRYaYlBkJIghUyKAzYrzMxQLRpmpzMWFxWzylJX\nHdL0QEJkS1nUiARJaZywOG/IPQydpxc7dnbHXjn2Q8RsA/QexkzeBdxrSxwrumQIBspiTr4ryG1P\nuaj4cu1Z/+Tv+Oz/GJHPT2nCivceHHHyezXxKCATyDEg+4HgE/1Rwhxv4eQVrrlCji35uKf5QPMg\nLthfNax/rXi1PfDwcMHseQFXlo14hahHlo9HzGJLUezQ1iDul1RvFcQbzXqEMWSK0VC0I2WtqRso\nip6CLaquWNQr+lcn9FcjfVpScIWb92QtEMEi4xztKlCRaCNORP7++jNU75Ey4pWnM44hdXT7NWVb\noJUiVh5vt6y7DplqSj2nTSVlKDh0juFQMI7HKEbeflhz8e6Md95+xPnZMamIZJ+5vL1l7/fcXr1k\nfyx4/EgzPz3Cze5DGuh3ju4Q3gSihgGZJbIw+FaydYl+G+i6Eh9KQqgYR4lyAmFqpJlz+/mO2EcW\nSwUXivZYMNQOC2hZILDkYEl5RRcqIooxJ4QpOX13xXjnGa62mG2m2kbqhWb/0tNeAalg3hwhZguu\ng2UYMvsQ0DohLDSvb8kP9yybxNESciqxcsXN2kA9pSwmk8lkMplMJpPJZDL5Tfnoo4/4y7/8y3/S\nb5VSfPjhh19xR5PJZDKZTCaTyeS30dc6aGEWicWpxM5Kci4YQmLfH+jZkvNIUTXMx5pVOeP0XHD8\nIGMWAWtrxhb2XtP3ius7SxsDMoBtFPokE/VIOxzwPjG4TBawWBUUZkbbGYZeM7rM6AaSnTMGjw8R\nKSVFUVCUNVZqdMpolTE1xHlgeWpYNplZAVZldu1r9v4K0Thm80ThE/0anBuJLjI6aPtAu+mpksXc\nGlKhMNXIUGZkVJimoYgrKnFM3MDuZqCqHBjHmHYELHZxRk2J8iUqaUybGYYB6JH/D3t3tiNddp53\n/r+GPceYGTl8md9YA4ujSEllQZS7YQKCiq6DvoO+Et0Mr6D7BtoHDdBw25BlSSyRrGIN35xzZETs\n2POa+qB86rbUgFQFcv+O1wJebGA/Rw/WOw/ELmG7EQxlhurnHIoVj4oliVpQFh10Jbt1SbndwP2e\nVAciG6FkRBwLloOl76AsHVUVmLoe3RbYtaZrI4ag8Cj6LiCnAoICrxE+wZuvSxXSCYRXBCnRWuOc\nQxCQwUEwpIkiXwnmDyUHjyMOHyVkUUTb3eHZI7FEDqZxjEDTCYmxMDQDRnS09pa9u2UfSkxwGAth\nCMRGoPYC+1rBqzmdmbGXkiENNKlG7eA0LZgkmrLpeH35BtXmHC6WPFkkPHxaMH1PsptsMaLBtA22\n7DGt5X7aopI7Uq5YhB3LAF4Ejo5i5F7TPEq4v1BcVXue3xQYEyOHGbt9Q35sScWa/lFNIzqUkpBo\nzGyGX+REZEyXGdlcgamJQkesDDruySYd08OI9OkUe3XI9teKcj0j6zRDXiIWgljlSFug64R+OVDb\nllr27OweZRyR9IgAISgG7yk3O7QXxDomaNg3Fb3riZSnU44QIgZVsA8DSZJwoA+IIs/Td5asnqYc\nHxasppLpTCC85mSx5NM3FdfXF/yd3RKSFQ8PHVFcEMsVhTPY7RqGDtEaohAQNqZsI8pbw34/sK89\nXa2wfYQPCUWUQpuwfWW5flGTzCE6ithrsAa0ipDG44XCoLFDwIiArQ1eBjweqSzLM02pB8o3hvqt\nY/8SJplkf5cQdlOiMCOepFhh6PoeIywuLghRgXM5681rpkPNUeY4mIuvv7Oa0ywUIh++6egcjUaj\n0Wg0Go1Go9HoD9aPf/xjzs7OuLi4+Gff/fDDD1mtVv8CU41Go9FoNBqNRqPfN9/qosX0gePknUAx\nUSR1zG0XaGowPsZlkqAjaB2Nb2g16GRgGTS5m3DbtFRDTlXGXH7ZM5iCSTJhfpiRuoGhvSbkDSCw\neJzyFAvB7DBHXAqc1USDIpYTQp5Q9jtsZJikMdPphAhHhCRR9usXHo4d8pHj5DQml4F4sIi+Y1fd\nI/OWSAbSVBK8IFjP/Zt71veBfa9BRKRa4aRkf69pnWayBJ1oZKlQhwukP0WnBdL13F+1TA4C2QEM\nvUVHMdkiZdAxotJEe414UyMLgZynCCewvWezadEqZ7E44CB5wLl6TCRSvqhfcNvUlHe37G43DDPD\nNNfMtCKVGi0lD+YZxle0N4FqrfC1RhFjy4TOpHgd4a1ECY8bAlhD6AUYgVTgnQfnCCGAFljlAY+S\nnjTzZLkiyzzRQ0N63qBOwaWGwXnq/jnJxJAWKdrEyCjgiegDlK3jvnEMYs+QXlA397SDxQuF7ixy\nEMi9RFxpeFEQXp2wtwsGHeNjjUlSjg6XfP/BU2YnW4b5S5ZpzvmDFbOQsow9xXKHOGyw6SWNusHk\nDS4DaTS7UOHNDaumJ4szVnJON2imuUesNM0HnnYQ3P/K8frtFfuyQA9QvZHMTyXLLGEaadABgsV7\ny30Dg5CsHk55508XzI8kw52hvSzpNhVWCiZFynzZM8kV8knOZHXKzd8rwuuOXiomseDk6JDpYkEk\nI6q+42a/527fMm+PEJ2iL1vapmLwHYN0mK7EW8feeHZtg7GSYrJAKoHzAAEbBlSkWBZTTtM5s0Sw\nOhAkUY8YLgmDp1ARQac8eHZESGds/vaeT377lkbs+cDOmCwtMstR+eOvX+vwG6SoUcFijcN1imEf\nsbkQbLcB4wQOSLXioMgxneT26p5yXzNdKnrpaZxHGMWJPkA1O5y1GN9T7xvixKJDSiJzskwhihbr\nGyaPA2awmGtP+1xx9aUjmq3IsxXWJmzElmvb0SUlqjDIRKJkTB7mpIs56TxjUsQslSCLU9ohJ514\n4um4x3U0Go1Go9FoNBqNRqNvihCCn//85/ziF7/4Z98d14aMRqPRaDQajUajf6pvddEifVhz+J2S\nh6uIx1rxslMM/1XTvEroGo1uFOkkIisy1LSlNw11vyfvNTbOaE3CXSP53ctAcw1PTlPqO0V46fEr\nwYMfSaa5JHso6ApBt2m4r6+wcsHxgwccDUsu30oudhbfJUxmMccHMYXsKNd3xJFEJZIsjlksPflj\ny6OVQveO/dWWcu3IYk36sCBgsWagry1Se0JkUVqiOoFFcPz0ECVhsI6uyml6RTQxVEnAaslimpDP\n5zTmLRdvDJMHEWermCyfECLN1liaumdX1YSXDSel4uj0FC0T6rsrblyFGxqOTwpOnmYcTWKmWY/Q\niuTvLMlLi2s7rl/UPDrWSJshYo2Vgbbt2DcbEqN5NJmzrSdcPVe8ujI4EegQBCVIY/Be0u17RDAQ\nAqlUKAvG9DhTg49RMkFKwWSakOQtiyPLg0cR6B6bQudK7l62/ONVTfnmnnc+6Hn/j46I1SFt1ZKp\nnM4HSjuw6zyNk4ikROaWOIaikYghoSr33L8KrL+A/sWE7npC4yNee8XZyWM+fPhD/uzkR/zszz7g\ni+of+Nz/B7bXa+xQs1Uls8UhyWFMuhpgsWHgOZ49ddMz1AnUC4QIzCYxh8mE2C+43iypSst0VRNN\nDSfvOoJz3NzC5UsIgyXJY8TplK9+8zkJFpkGVjEMscFLwasvN0RuyjtPpnzvOzlCV+jjBnfSU162\n3G0qhJQcHB5RLDTWB+zUks4m6F9G7F9ImuuAmEScfS9l/iTCpzG2P8DfT7j8tWD9257aBfrY0sQN\n90PFG3mBTzwmMThxj20Gpjqhb1rsYMmKCVorZssZR3nBcZKyjAB5Cf4raC9BDUg/JZ4fcnKeYmTB\nm+dLvvpty/WnBfomodtakmXKD/7yjGlxhp69wc/eMrgtvXWExFNwjntpufyyoxeao6dLXJLQ64g2\nOHrvUDOPFwPpLOb86YLTd+ZMteQu9Ai7RwtHnFrypIa4JzM9E58Q+0Cf7+n3kJ0KfC3ofxdoSpin\nB1zuHK/uvuSmapkuD0kjgRIRzjoa2ZKfpDx+75zzpyXzzJOtBdN8ycSl3KUVOpNA+KbjczQajUaj\n0Wg0Go1Goz9YH3/88Vi0GI1Go9FoNBqNRv+ivtVFi/MfSd77Yc+5u6at7ugXN/g/W3Iyeczli5ir\n65LXak/kf00hJ6yiFDObcsM9d2HgZt/T2hnnxTlBLXj5RcllvSFdGf74LyY8mEFQtzQMSALxfCDx\nU6RIEJXF33Y8i6e8q48IQtLj2LYV603DZDXBtB1WWpx0ID3HE8mw7bGdRwwBKSEoi48iTO9pKkO5\naejXAi01syJils2Ipwc4PbC5L9HCkSUZOAGdIBDYbwxtc0NT3xNOd6RPJrgMOieYTWd47xmE5Wa9\n5e6qZyI9T84fIKYzhI6YpZIHp0eIbMPkKGKxbCny10jxGqUjsssSf3tNud/ies9DGWGdoHcWrRxy\nbtF5hL/Nqe8S1lea7S7BhILBKESUkOqYTEIUHKHrCV6AlAgtUNqTphBSkDIQRSBTmC4GZgeOYtYT\n4nu8VrgQMzQ9u7d7br9oeXJWcFxI4tYy3O1xfUpfLGmbHl9Z0qbFmY5dtqUKDV1lMVee5rrj9hO4\nudLY+ynUZzj1Hj58wE//3RFPPlzxvXeO+eEctubvCZ//jpndo7IUJSSUDV5usXGM1RYzlCgZEdqA\naiSyDnR3LX6IOZrluGvNnbA4WxJ0xN3VLVHbQCQxacrT7654eJSjIxA6sLvxvH3e8urVHv1JoI0k\nyZGi3AC3BSeLFY/EkmUtkUc9Q3tFG/dEJxGLWYQyjkm0ZSVisnxKnV2ghOLNlxHVFw7zKmbfDtQP\ndqQPDPmpJ1MRQRcU/QHTncJMUog0LROubxMeJQVta6l6y04PDEvJbJKSxYrISxgEnRywWNKkZ6p6\nMtNi9xuiVcn08cBk1SGLDjHrudgEun7Gu08mpP5H+LsDRDPl9vaK7m7D1WLCBz+L8X7AZSU+bYFA\nsgdtU04fTjCt5GZnWN/fkQwl0+IUqWI2bYURJZmWLA4XnD5IOMhiutsWuXG4MCCmHcmhI480ggSJ\nwjmPx+NFYJpHhNBhtWZ5cER4Z86Li4bLbUfnPKtkQX77iOAz/KSFqSLNYw6iBbOhJfMCpUu6qKJt\nOnwPJpckSwuobzg9R6PRaDQajUaj0Wg0+sP1V3/1V2itsdb+k+8cHx/z4Ycf/gtONRqNRqPRaDQa\njX6ffKuLFlnhyRY9ieqRiwseTG/InjSczI9YFUckbzL2uocS1veGqy8Dq/dyOLumFI7aDQw7ibua\nEy47bqs9b2zFIteYOse82iJmDhU5kgJkEkC0yLSm37Uw2XL4ZMVMtEQxNMpyWe/pL+6pX0rszoKT\nqEQRJxIGTV+BrT2m87RCE3TMYAW2U7Q7xeYCXAXpJEWLiL732KHEhECSxaQqJtOWWAnyAqQyGNdT\ndR0u8Xz/3wtOZ5ph6Ck7SZQkVPeK/cvA8NYgq0A2m6DOpjQS8iEh75bM7EC+MkyWA0XeEUcWIouI\nLdl5iXq7x913OCEIRmFbRy8tgzQYb+gGR+xTXJ8ztIohSGSSEUlJQBB6gx8sQoIwFnwgRBBii0wN\neSZJ1YJYHRAlh8gZJPOWoO9pwtXXq0YcYCbYSjBNJN///pwHD1Jm05RYSbxNsDamrCz9zqDqjklX\n4W3LHRXNXlA+D7SfKZrnM15dTmjFFOwxM/2MZ0cf8O6PHvP+X6VMftITzW7Z3jyn/3JLEA2yaVCb\ngBKBqIjouo51ZRmmgVgJzKBAzJnGEhVrNjbQ7x39K023EeS5IJsrZAQigLcWowwy6ZifxSQnA+m0\nwwmHfr3h3bLh9ecdrzeB7qVg3sP+1nP7OuLERYR1oH3eMNElRjV4PFpEZFqRxTETLcmcIh4kXgaO\n84H5O46730ja14aL7T3552vkw5bk3JEWCp/l+MMl0aMYaWfoPCMOnv7VnmmraW4d9S5wIAtCnjA7\nnDFfzMjiFHrHvr5nXe1o+oGh7thXFfNDzcGDGcUzQ3xgUbpDRHv2ZYlOH/Dkve/x9OEZ/eVTzF3K\nq2TCm7sLmtuay1/D9FwjT3IGmdDXFbYU9NcV8TBhmWVUleftjSXqInoZ0EkAEZHPIpZLkKLm/uYt\nTXXH0PVE0UAUGUTvCbWmjC06jtDBYwfP0A90TU+nHLtW0AwxPovJVwc0F1c0rsEYiR4Cy2jOfJni\nZg2lbDGdw2ze4m4rTN3Q6x49g6kdaMuBtnLs+xaYfdPxORqNRqPRaDQajUaj0R+sxWLBT3/6U375\ny1/+k+989NFHSDmuAx2NRqPRaDQajUb/NN/qokWwhs6t2SclcnLDfLpFRC1iv2L7Kid+FWHtQEXg\n1U2D+nWNOVPkiaZLLL5x+NrQbwa26zu2bkc3sdgsoms0l7/rSE4N6ZFHHQhE6kFV+EyA8uhCkqiS\nyaCIY0ecelo/kB809EIQrRPUNkYmGTotGHoYrKZzgR6B0RrvFe3aY/aCbhNj6gxrDZMoQcYRDkfb\ntSiVksQpmZJkciBVllk6EHzLEPWYwiJmgcPHkoWD3dZyt5Z8+YXm5vMEs84omojlZMbiwRJ5kLK9\n3SNNxmE9Re8HIrMlES2JN+jB4kNP0C3FwY70uEXderCKemuI5gKlLChDN1ic1VRbT11ajAGVKrR1\naAU4UM4TB4tWAhECKlXIaYKcBOJiYBonJMzRbg7MaIaB3c0WIzdQ3JMsA8KBsgrhU+bzlMlxSpyB\nEwmNAG8Fgwu4qsR1LcqWuNAyYNnvDdvniu2vNPtP51Trp9yHU5L4MY+m7/Ldw8d89+GC7/6JZvrB\nJc3RCzb2Letmhy8DiYmxmx6z9hjpUWcaWyjq2iIayGNNtXNflw6iFBVrXBIoZUd14/AbC0eOYu5R\n0cA8lnSJwmGROpAWllhvSBYBJwcyX/LkzwJD4bnbOK72sENSXTn297DJAuU6MF8oQgdqGhEJCF5j\ng0CKDBsUXRcRBPjIk2HIDnr0ImHQgru6Zv58YP6eIXtY44WFIcWpDf4kw5HhU40PAa17dJVBJlGb\nGO/nBA3xpEZoR1Ax2VSRZx5ZCN7c9dysd4SqYn5WMDvOyVcJYgbIHabvUElLorfM0jWpuEU9OKa/\nhmiZIV7N+eptxd//x7ccPF0zf6dFTyz9viWYCLez6A6iQRD2gbiNKeKMcKfoItBZxGxWMJ9Zhq7l\n7Ys9QglE4Th8kDOJAspLfKkYEoVKv37TwvuAMdDUsPYDjS1wNkekMdEkIc4y0tSiBERCMpkrlgea\n6CBl4aB802Pv3yA6STAGJwUuj0hs+Pq1jE2PrTrGosVoNBqNRqPRaDQajUbfrI8//vifVbQY14aM\nRqPRaDQajUajf45vddGiLSvqylCkJYloyQjY0HLHS6ohor87Y23ugIHaWswLT/hPnhM5xS8Mbh/j\nu5g6WC7cnj60pLMYXcSsNwH2loV1HMcwm2tQAmKH8XtUpkgSD+09WoIMnjgE0hSSE89k8MT5lKAj\nUunR0xwigcgihFYwOHwDzcYwvNW0O8kQYvJMU/UlgxPEiSQqFJkOJGmGthGpkGSK/76KQ6GFJZp2\n6LMARwIXauTQs5ilbLaKTz65Zf1pwYNC8HB6zOpoRXI2ZQiWfb9h4iVqOETWCcM6op06tPD4ILCt\nIJKQR4HpyrM99PhLye6uJzvUJIVHRp5gJJqU9XXDdt1jQ0ZSCHzvEF6RypRUxkTERIkEAfEhpMeK\nNJcgHKqL6Xcp242j3O55dVUz7C6YH+85+q4jXQ1EMkEJgRQxUkf0wrEdWoggGIfsIfaK0Du8aOhl\nTSUda6N5e+HZfu6pP1uwv36HbfIDJvl3eBx9wL9793v82Y+nHL9/ySS74j58wvbyN/TtBnOfou0S\nuxfYncOUgUE5zEUgfajRVmA7S1dbyn1PMZmgfIzvY7TSyKhgv9tQYXFTS64rksSSFoFIpsg6wnVA\nrXHpliHe41KHmkpmTw1Pp5r4teT6ynNXOtbXAXrHq7uG1WXPwaOCeSjI9JzB9fRC0ilB7SIGFxMG\nQR4aBBtCcEipEJFkQDPsA9WdZv8yZf1woFU18dCjzYCcTPF+wyAGvPTII48vEnSWoRZzfA19NdDW\nW64vW1znWGQpT86PyTK+/g+bEmcsT9oF3s+RQSF9D9JhnGU2nRHrQBCvaUXF/GCL1wcsDuc8OIQX\nG8tn/+kN8uWak5cdq5OeRAryJEGqAtcq2ntHfyc4zlbMZIZoE0zr0eRkekUcKvrdPV3VQS6ICkiz\ngE9BWoHoIHIZbkjxUYRXHuuhbxPKvcFHCVoUeB2xtx2zyQRcivGGKJKo5Q0yb1meR5yKiDaSdGGH\nymIUAXyE1YbOWmwaSBHkvfimo3M0Go1Go9FoNBqNRqM/eB9//DF//dd//U86q5Tio48++heeaDQa\njUaj0Wg0Gv0++VYXLS4+vUT/6WPeffIAugrsPQfHWxI9IaofctA+453dGb+uP6G633F/5fjyq4jq\nd3PUexZ15tjuHb/bXrJ3kvlBwfHhisHH/PY396y84X2tmJ1KZjIhn8QkWnJ1v8YlgiTSCBxJEGx7\nx6ACIYYj7UknjrZfs1zNWT2Yk64SkmSKjCdUteH+psFUHcPGoG1GJBQqTkjzhKbuuVnXJAUkSUrw\nkImEg8kErEDQkxeCdO45SBz5yuMPG7rUE8cCKzxtAw6JmcLqyYxpl6Kdx2xqXBzITgpyGYiHgDDg\ndYSSGdVmwHWWLM6I4oSp9cTBU6SByTSiu4sRQhGEwXlLVzk2t5D6HtEHsixGJQMGj5h4oiRDa0Os\ncvJoxmRRkCwgXgh0EuE7RXk/UN1bfve85R8+WfO7zzfcrEt+cF7wk4ngNASkDySRgiCJioygFfth\nw72r6GLwxpEZmCFpbwzqULHzntd7y4trz91/drhP59A8wUZ/StH+r/zM/pSP/3LFo/9FED26QvCa\n4vw5u+oKv20YLh3tK8OsV4RbCDX0xrEu9wy3gTNRkCwSvA2U9zXtYNltOpRTtHeB/QWYTlC3kmKZ\nQ+FpaImkBLlAypjQO+qXDZtPeh78UUSUSVQxoAtBh2P6QPD+UjJdCv72b2C/ha4KvHj+gi9f3VHx\nkJ9NA6vvZjTSsHEDpUz5Qgf+dDLjsPeYfcm2rJkv5qyWS6bTlK+iwFtqsnbG4sWM7AcSrSwyusY0\nHWkK4HGhx0uwGmTaoTNDUBI7RAgZ0zeBrhRs3la8uX2D/IsBdyJY397TlpCxZPPZlIvzQC0Ek2eS\n+WFgvliQuYSAg8Shpjuc/q9YJL4/heqceJ5z+uCcu8Gy2UlUUnByGtMOirqEq892bN7ERPGC45On\nNI2hrXuiGKaLI/LyBNl9RZgOqOVAnFiyxRQ9n1D7irbsYKuYqYJJVkBc0LmO9b6i6h3eZaSLBZ6c\n+7LmzafXnM7Pebya0APb4Zp68nd856/OODo/QtxPiBaC5NywvrpAl/ckjcHnEp9YROSI80CcfMPB\nORqNRqPRaDQajUaj0Ygf//jHnJ2dcXFx8T89++GHH7Jarf4VphqNRqPRaDQajUa/L77VRQutJfva\ncL2rybOeKDtCDkfM1DOeLU7JJxPaNzW5tuyjkkoNCHPA9h8zElswjQKNaNgMG9qh57ASzFuPPpvz\n6N8c8/jJ+xw9uCFO7thfluxuO1plMIUgPvV0yUAcK2yWMdnn1EawrwZ60ZGKjsWJYx5rUD3Xb18j\n4hzTQdfBsFf0V5rNFz3BSKxXpPOcNM9I54fctBuKdMXp0TF6sMj9QDaNkYUgKA+pps4TfJGRT2Yo\nLTDdnmgDEYLjySGcH/DqycB6o2m6gZny6CxC5QK/r6nXJbZ1dMaTasG5Gnj0x0uitMEOAeUVw16i\nswmzqWI69zQIbIBd1WNyi4yAPGDbnkEKBnqM3BMKhTwIqNmCeTTjkMBMQDxxdBHYVNEPku4q5f5v\nUr76dM9X+w219zx7+JR/+70HPFlJTr57xeTsc6LwlkxOCWKOHyTYnlwbKmnYK89gBKIPpHvL8Crm\n/ncNX+16Xt16dtcR5uoI1x8wif6cHx78b/zls+/zk784YPadivT8C5j9lkG85c62XF8G9ndLwt0B\n+jam3Hqq2z0DlmHqEXlC2kjuLgIqExzFOWK+JN4Zbi8N3ncMnaa5T5A+JpsdkawMdr5jw4CTMXUv\ncRvJ/iJhd53z3359y8M64fv6kMOsw/kdGQmhCbS7gNp6Dp3nIoUAPHzvnHefrcgeBp6XLdF1jIxi\nYiGYpTncNHxy85rdpOPsxKDnEbdhxuZSENWHnDGHOuW1ahGflJinkvd/MGX6rKQ097y92GGdIk5T\nkiTHBMFiPkW5lGZQ1Ndg14rm2lBtDM5K8rMF5WC4/t2O/V5xWDzjKDljXqXUX70kWhnSY0s/dUzy\nDOsVfeswjUE2Ha25RilIixsOji3v/9GfkC+f8R/+rz3l3qPWGmkOOZqcI53GqA2l2IARFKJm9u4h\ns3yFUAkpKXHfMtxmyPqYOKqQJy1ds0Pva6qhZygdE5OxvY5Z/KbhRwAAIABJREFUPj0g1TlVXVFd\n7NiXGdlyhnUa03WIwXJylHI06Yl1jYg7zuYDnFiK45eI7DXqJGc+P2I2PKJ+HRFLQfD265VBS00I\nEWJuUMXwTUfnaDQajUaj0Wg0Go1Gf/CEEPz85z/nF7/4xf/07Lg2ZDQajUaj0Wg0Gv1zfauLFu/8\n4JAnT5fMMoGKE2IOiGJP7TOyJOLscMEu1tzLSzb+LVduQykEcRmYGc32umNnGnbG8iSd8U44YVGv\nkHaKPopZveuZrwzBQn3jKV/t2dQtyUwgQ0AViqyIqGXAWknTajorQQlSKSkSSyw1PZYhdEQJWNOD\nCAQTM+wLvIuwQRLimDYI+nUP0QGTLGM1OWE1WeKbPa6/wbod8Uyhj0GcgJrGuDxjEyy+G5B9j957\nVjJiUkzx2YwDteHzuqEQikYYKtOS1o5caiKhifIYNYuRuaLvDXcXNcm8JsslIre0uqOPHHiBSkAo\nS1+Bqixy5UkmgigH0Ug0Fms9zeAR6UC8guXScSAF80GQGUsIPa7v2e5h+yZj/188zX/LsPuUxeqQ\n+YFgwQGP5ivmU0c+r4nmU1RYIEKGMxFdGwhhQMcDrjXYhcC3kuYWmguB/a3kxQt4sQ3cthFDt8J3\nZ8xOf8r3Tz/iZ8++z5/+JGH2bz5HnXxKmH7FoNbUjaHcCZrdAe72EPN6YPt8x67egAQ1iSDTaKdw\nnafta55/teX1biA6rCkyCF7SW48xnpiY8+WK7MiTHG3Qs69fb6j3DW0HzctA9SZity7Ydj3uSnPw\nUhLnJZ3ekM8U/spx92ng8iXUpSZSOfnZnJP3Mg6eePTckKwCV5sdibLEUYTbaZbrgrdfrrlrS56f\nBB7/aMn5O2d0uznRUDCLFXdRRWN2NP2S7duI2y8Fep7jk8DbzY7Nc8Mi0bz33ROSRKKqKeEuxr+M\ncS9Sbl4ObF1PFQJ6npOfJdjIopqMZT5jkT/l8exdHiQT/Kyhzr6gLvf4WU9SKIatxTQBpELZGNdH\n6MIQXI/UOyZHFav0KY9enPHVJ9DfAuaUJHmX7WZPXXZ0pkJIS1m2ZAeO2cMCvTjA7RcM14ooe48k\n3RDCFUN9gbl6jUwqMqFRzR5bKa4+6VglMaLLKTeG+jbF2sDgI+xdj/aeY6E4ONNkcUVHQxs1iIXB\nzQw+McRSMlEeVwSa5cB8ppj2A5nTaK8Ja49NwAqLiew3HZ2j0Wg0Go1Go9FoNBqN+LpAMRYtRqPR\naDQajUaj0b+Eb3XR4uQs4+QkZ5FHBBTSS6RqQPUY1eO0J4snHKoVCRmdt3jdsiwKbCQptw2btkHL\nmLPZKQ+jM+bZHHKJP6pJFg160hDMgE4dwnrcxuFqjZtKKCTyoaJNAm3aY3zAWQCBDhqNwhhoQo+J\nLSKRBNsjBgguYEyCmsxwQwZRRpAaYyTz+SGh65glBakEk/QkD1u6dIs9NPBQoB9IpI7o4552cJhS\noUyGVp6kjmj2BhkG5mjwHqSmdYa67VDV16sgYhkRxRIZe4QXdFXP7ralUD0614TU0cctHR1OQBop\nZomirhy2UtgG9MKjExg8lAJKG0AmrBYz5kvN4WRO0RfoPqIrLbuhYm8bdh00b2f425zcpkwXMavV\nFD8RFH3OAYoYh/DgXQRuincJfaOpK0NwllhbbDXQbWKavaC9UOy+iqi/EtxfpGzaFCdnZOkzouUP\n+fGjj/nZ4x/y46cR8clrmsP/QpZ/gdMb6h6q7YRqm2G3C+wttDf37MuWcqhIZjlJqohyTewU9brB\nRYGyaem6hqjqmB9qlA4YB0oFJgcZj58dwaSE+QafDvSypq96dOfxrcT3AUJEVMyJpwtsH2hvFD5f\n45ynfFFx8Qm8fCHpIk2yXDJdzEhjgbcVXhkWq4yb5xWd1aQyZ+gl03BAaiQvXmmuXwuG9pSkf5fh\n7ZRhp2j8hjq6wIiSmsD+ZsL2HyVCzhF5wd0byd1vWvow4zgcsDqfMhDRX0bUXyr2rzyvL+4pixI/\niZjHC6ROUCLm7LAgyibkecEyc+T6juUzyy4TXCrHdjfQNYHIFmhShIrAOhJavBroVKBzLZYdQ99z\ntnzAJhbc1nvqILmTLbf3e1wXOJjNSKeSXEmEC4ggyPIJ6fSc+HDOVCkGU7Ltv6K/t4iyAhmTxhCH\nFNN6VNXy8tc7kswgcUhfkOmY0PTYoWc68bz/LOZ8KRDCshl6rruWjRkYGoGqAoWUHCAJYmDLmqLQ\nzGLJtE2I+4LK79kPjqqxlJ37pqNzNBqNRqPRaDQajUajEfDRRx8RRRHGmP/hmePjYz788MN/xalG\no9FoNBqNRqPR74NvddFCuAolpmiVgE0JakNl7tl3jvt6xnZXsA1TBmcIXoLQyEQzmSqU7xFtRyoV\nBwdzJnJJPMuJDxzy4Rb/aI1clJioR4iO6KBn8VRhQoSrFP4tNEGwM4H0mcYpg8w9kRX0g8V3Amsl\nQ2eo1IDJwXiLdw7fKPpaYYMjOcyxZcowxGhyFtOc+TQnHixR2uLTkujghuTRFnl4hyk2yNyQ5AlU\nU4KxJAmkS4knwVnD2wtFv7kj1wNxOOHxakW1bRkax+AseDCtQyuJcz31boM1CrGsKQ4k0gu8sxgf\naG2LHVqCTSjIkUlCVxn8PtBftQQcYuLZ7ANXLyW20pwuDzhP32Pap1DDsLFUt4bdtuOGNT42KCVZ\nFgmLHyvShxNcknHveqqqRwWP8wOOjqG1uHuBcjGRzKm3gbr1OOeQ3tA2jru3lpsbxeYi4u51xm7v\nOJAFaTJhnhxxePQuy/f/go+OfshPjmdM51fs5KcQ/Qrj9nSVoylThpuYoZxh1jHtuqFvW0RiiCOF\nFxCUR2Ugg6RJeqIkUISIRKSEWGKdpWp6Aopi4olSwfRIYaVj0APG1/T9PYMdyDJFepqSRoHoTvOo\nXnD+eMqi6BDGoYdTursd24uB+7Vns5d0WrNaTohdRrizdF1HQ4M/T/BB0NuYwaS0bcJ8ckgeLUhc\nyfo68Hp9DF9Mye2C8rbitrtmF93Qi5LrbmC2OWH+myP6zYQ+Mdy/7hleTWi6KW+riPyPVwyDp11L\n9m89V+uSV+GCjg2pLEispFknZFHM0XlOfiZhtsa4t1zcf0mRSQ6PDcalXN1Jvvii4b3vnLJczvFe\nM+wNQa2xTmFcS2dbmu2e7WfXJPePmLJiLQ035Zbr+x1BBIoi4+j4kNXpHIVlkAGspjAF752fsnrn\nkEkycH2b8vnvSvZfxkCKo0GnEdNsRqQj3GHL33/yFhcE52dLnjxeAh2D7PF54PCh4r0/jjmaBaQS\nLOoYdaVoXynqK0ESB7LjmGJSUEQRy2BpXYc3AmsSpEiQBztE7ek66DrxTUfnaDQajUaj0Wg0Go1G\nI2A+n/Pnf/7n/PKXv/wfnvnoo4+QUv4rTjUajUaj0Wg0Go1+H3y7ixbiGh3HWAm7fsfRImPd7vjk\n09dc/3ZNUimCOeLT559xX92jdUSfadTgiRvDgyInPTli9ugQtYF6ViMPa5KTK6KjC3y6pwWiJCI9\nTsg/iBCLhPXfCsxOsvss0Lz0nP85qA88au4I3hPj8DJjfd1ivUWeK4rTmLbv6TcWW1pMpZCR4OB0\nju089cYQQk8cx7j6mtUJJEc96WlNdrSmmn7G8tCTBUgHR2Y6bCgJTChCQp5qhmPPV8Lyf/+flv/4\nq4Ekqnj3acSf/NG/5T//P7+isQ020jhpyYopWZB0+xY5BBZ5zjxK0GbP7qZi11ZMe0Ebbci0JbIa\neRchmhTXpZjWUZoBmoBXnk//zpN4zeHyAUI+4vKTgi+vHPUXlm5f08sSP21Zfl9y+qOM45VkEQVS\nv6HaSyp1iN1Y+hct/kWgA6TpkNs9OgQSpTBY1rcVjeswtHTtwP1txPMXHRevBXd3GU2XchJOeSaf\ncawzJouExXunrD6IyLaWoRwQBx2z05adEny23bKvA2qrSK4d4W1Pe2mwbYeOHZmPCG5BXfVECLLU\n48Oe+GRPnoOKJISYwXh6p7i/HzAW2q7lq9dvWE0cs1UgZDe00S1dYkgKELMKNYmYTuas5ilPlytE\n4WltT9UE2ipQtQ4VZqyOPFvv2JaK3ijMzkGrsFvB+r7m131KcVwQp3MCS1ybcrP23Fwqyu2Mdqcw\nlynbz0oezRN04VAThdaabj3QFS0XQwtfNMRfOAYb2JWQiimpXLItU26dZ2ccxnq2TcMXwyVX+i2z\nPEan4EzH9u0a2wTc/cBRrslPA8Rb5g9K1v2OtrSQC1KO+OQfvuDpuzOyySEgkLLj5qInOVR0FvrK\nEt6UDP+4Z7+5gdZRJB7bVez2FYeHC6JE4lyNaDQHZ3OCmDNwQLY9Jr9b8vCHEdMHgWKlsSGmv0u5\n3ShsHVgmOQ+mCVGkePXpC5q9QWcREaCantrcICc9J+97zn+YIA49zjjiVLGMCmQWCIsdr/+PmrY/\nwGxXhNUUv3K02QuGvKc0grswUIgOKk/uPOdHigcPIn71zUbnaDQajUaj0Wg0Go1Go//u448//v8s\nWoxrQ0aj0Wg0Go1Go9H/H9/qosXeGSoxoCRsupjm5o4XN1uWi5zZT3I++5sLfvvJc8yq5+h8iS4z\nLr+siPeW/FCRHEXoaYTrDe4woVyW9M/uSL93x+Rhi+wdeRAkiSfKPE479AcS/VbT3Eu6UhJ6Sfdp\n4PRUszqAODKYXcPwxtA2A2oWkJGgLS3bm4HhrYG1QzpNFkFoSmZxQrFMiBPITzeEk5bwoKJP70mT\nHctZz9FB4Ew78tYTnMcrEFYhiEgGifeOe295Env+zf/uePrKYS+m6O2K/j6QhQKvDcZ17EqI+wgh\nBmzTIY2kcp6mbohsyeSdiDgp2Dc1zkvyaImqFpirgvVdyuvbjqqNaboJVaOoGot0U374w4dk/pjy\n7YztPsbfCaaR4vyxYPlOT/H+luxJxWTRkPoB3UKwe5rZPf8ve3eyLNt5nvn9/zWrXyu73Z59Ohwc\nEAB7ikJJcoUmjhDJYvBqNNVQN6LQJdizinCNSi7ZIamohiQgkMDB6XabO/vVfp0HUJRLLjnCYTsM\nUF6/WeY3eXLyjp5837r9jF1vOWTgk5ycCUqBpAb2KA60jaDuPMt9YLlybC4d7RvNF6uYbTMjjd/l\nuxcf8KF4ylmqqVJHfhSTnZS06zta849cNorD1YbitubgFyThBL/SHF4Ybj/eUV9eYuodKjPEpUJn\nCVUZU2gFyRIf1kg1cPEg4AgUiwSdK9o2YDtPpWG7hl1r6Nodn3zWk19Z4rIhnmqKhaQ6kpSlQsqe\nkN/iKsm+WBGJBJkF8tQjgoStoDhOKScpURZhbzyfv96y36WIRUU8m6It3P1mx/JakFWBrIgIImH/\nyqGbI+bWQz0wrD027tnvliQhkMxjHh0/x5Fzsxy4vw/QDxyJjEZ6dD5FJTGH0LCyG9q7hml+SmsC\nd12H8TEn7kOSHqR0DDJggqHIEo4fKJ68F6Pe2fPm8IIVO44TTZRK0DEn85w/+IP3KHON7y1xUBSD\nJ1YVL359z6bv6FeG8Mlb9GcFq66nVREqc4gjz/LqCqd2PCmecXb8mIePT6l3lthlfPv8ER++84iz\nJwZzdEWvromnWz743QNPn2e8uC3Yrkqc2OCGHfZloLlc8/zREZNFybyKybTlqNJMfrchejygpj2t\nbcnbmMzOCVIzEBhkT3kBd7+Zkt4/RZ2fUu4NKg34/AVZUpN2HVln8aEghJZkkKTGftWjczQajUaj\n0Wg0Go1Go9E/+elPf8qf/Mmf/ItvSil+/OMf/3+caDQajUaj0Wg0Gv1r8LUuWkhlObQbulazvqlQ\nZkOiIqIscHfYcLMU5EenFIuK6/sV9fWBnIQkScjKgK4EVBofwUE3uLihmNcki440DeRWMq0F2gp6\nCX0V6CaOPhd0QnFoFYORBKdYXfZ4a0llwG0jhtuIobdI2+O7Hh8MUQCLxwmQkSSJPMGtKbIEVSlU\nNRDODvjHA+rYM889FwjOrCSYE2bWknUWhYfUYoMnaMAYTO/IA/jjGJV00AnCvcRbiegSKj0lqAZv\nG7zxWDVgXY+zFikUQQwI5ZCtp106ZO+wUpDPFhiXEG40h7eO5cpyV8OuB+9jIp1x9qDgyYOHzKcT\nICb4mKwomX9QMCk001NL/mBLdFyTFIJEK1wtcYPBhx6frnACBm1pnMQPExgUbmfIXIeQHTapuasD\ntxvB5YuI61ea9V1GU0uyYcH3jr7Hu0++x/nJGbkTlJEFe8C6hs1Ny9LsGfKOjUoo9j3lyxZzExGF\niuZKsX/d4HYd5xeaNhha53DCY7XBxztmDyTJpMe7HWa3JU4inBiQU0U810QBhNEUZaC88cgby+Xa\ns+o828EgtgPFveC8Kbg4F/hMQumhrAnVLTrdIZoUoSRR1aOnA0dKI596molAh5j7TvCr3zTscsfr\nfc2hiziZ5Ty/OGV102AOU/qsoGvAbiS5cwyHlm6/5dBaCANVesLRYsbsYo6NNLaXxD0MTpKrjDwU\nlIUgP444xDvu+1va3R19m3IinqBtRqEjzi8WzNIFjbPc91vWhxX3XcN0Cl4nKD2lLDNOqzXbxuOS\nllZadFCUueS7H57hsEjXEaEIvuHRoxlfrNeslo79pUB+4TjeRSADe3Hgymw4sOH5yVOOJhVxtODN\n254Xb16xKBa8/zjldBFx8mSNfv4Wpv+ADXtkH4h6QRT3PHjWcvQkZU9Ef3+gX3Uob5hViiA9h11L\nmgeefCOhfBzwxxYhAokNdNbwdu8IicYUlrKM+PCHGZf7ko//oefnv7hmcSZ4X014fHTMIknIEhiC\nI/SCoCWDcAzef9WjczQajUaj0Wg0Go1Go9E/+f73v8/FxQWXl5f/zdtHH33E8fHxV5BqNBqNRqPR\naDQa/bb7Whct1sZy3x/IvaTZO0Loyc5Stu3A9VWNb2csjhZcDnfcLtfU247jdEGclaiJw+oei0Pl\nkGSW8qFgehYxL2PmwqEdlIPCC4mLBTpXCOkIqcepgHHgpETHGXan2fc9dTdg7wV2KwlJinKC0PXg\nLSpERJlGVhFqSEBYgt0yPS7RRY+dHwjnHdF8YBaVnGQppyFlto+xzQNEtmcve2AgpmMQhhiPwGGF\nxQhBXWQ0+w7rFX7QhMaRCkWEIpEKrzWxVnjhac0AUqISxZA6dCWQQtKsPH4T8CJit8mgF+idhkZD\nrnh8EuOrhCQVZFlElqcsigpzkEAgK2C2ECzOLWluiYoamd2D2OLsHmthGALGBXywbLY9dpDYrae/\n9wx3A33dYLyhxFMrz9Z33O4Et680qxcpu+ucvj+iiGd86+gp33/3+zx5+gydSup6y2Bqdu2a3X7D\nMARsBJFfYcqE3gX6tccBqjaYO0foBIuzirN3FdvGsNo6mq7Ha8uQrKEMJEcHlOwx6cAwGHRukBOH\nKARpEqN9QZYq4gLIPS5W7I2gbTR967FtTiEL3K3ERxahOnxkCGpHMekRtEgrECGg8BS5QpaWpmtp\nN4qL24JJnHAYBu5CS2MH+pBTFhGHVYYUET0Nq8OGh+kxuhxo7Y6du6fVlrwEUcxwwtMeLNZ7Jrrg\n6NGM8CBCDJqCnMlJxHSe8cXhC3ZvXrDf3zPoiH0IPFyc8+zijKePc1KZc3llkPeWxrastw333jJE\nRwR3AluQ1uB6Tze/xkQNhRRMIkVWxKybHVhLQCDpSBPD2aOEgwqopsAuHuL3ORvRcRcdWOsaKeDB\n8bvk6stTKV0k2Yia4mhBMi0Y5JadfE02+5xK/wrcgBg0wy7BOsHkOFCXgUEFvDDYpzWz04ibpmd5\n3eJ7jz2L+WGaUMUeIQPCSaIeDruB/jAQVzFlIpnlEbNHnvtJy00juLmKOPYZ1ZuceT3jPNVEUUvb\n9Ry2gWrqCXbADOarHZyj0Wg0Go1Go9FoNBqN/gshBD/60Y/48z//8//m7Sc/+clXkGg0Go1Go9Fo\nNBr9a/C1Llp8trE83TseRw7nvjz/0SSSt5eGzW3EIilo6pZPP/2U+/WGiZwyyQriaIGqLFZucX6H\nznounkY8/lbE7CInTwZSHzg4sFEK0qMlVEbjIkddQjvz+H2AWBBZgWhzTBvT3Xfs39ZgApMnOYIY\nbxQ+tDgjIcnQk4zQJbTOEWnL9HmKzhpcVZNfaAobeFTHJA6EdFibsu81W+m5cgMNLRPVEenAAysp\nNVgV2HjLJs3w956sjwkmZbCSJAmIMKCEIEpiVKwwwdFbT5TFiCymiwZUHIilQBmJCBFCx9RLgQaK\nPOP4UcH0QcTZ45TJU41KA309sL1r2F6/Io4TJvMJi+OSvDII1XxZRoi+PP0hjOG+7Qg+oh8kxoI3\nkuV1gjtozCtP+zk0n2tc00MpaZKIuot4tZIcNor9VY4+HJFzysnkhO9W7/LNx+ecXcyQuWFXHzAr\nw+3mhtvuktrXxDLlND9De4ESDqUDCIkIsFnWhF4yO044fl4QUou9l1ArVBDIxOJLg4m2GFkTZT1Z\nEtHdGdJFTFIa4tSTRaDRmBDQGWRzzXwRc7lU3LxVrFyK7QOHnabfplRFj8o3OLnGhJqqVMRaEAWN\nNBLWCrEP6Dmo44b8Pc/5m4inRxGfXPW4KfhcsOla/uo3nzFpSmRjWA89a7VkdjajSAbq0NLoDplp\nykclyscsVx3dqxqC5MkHM955mpNOY0IckaQTFicVc3VE8uuB9eUXtIeM6UlMUVje/Z7khz+IOD9v\n6A4tw28c20vBSijW+4SVg0ZPqLdT2r/zvHkz4RAtKN7rKM+gmAuySLHuGtADxg1I54mF47Be8vBx\nTDSZcqtO2Zv3ub6Dt/2etbKkecE0KTGHiq6d8s7jRzz73QXyXQtDQXsHS3NDWL3mtLkljQNaWUpl\nsSrQmBxVKy77NbVuCGogvNNz+rzg47/oePmqhwBaws2VZvaBp8wAB7532JWgEpKJk1RGI43gWtxj\n+jvi5IzZyYTquEJ3Kd1uYFcZFAd8X1PfS6aJR7UG+rFoMRqNRqPRaDQajUaj0dfJz372s3+xaPGz\nn/3sK0gzGo1Go9FoNBqN/jX4WhctmuvA538laSLJaak4++A5v3h1xRe/CIiXE/Kg+fzvf4WXNefz\nknk1IxcRJSXlO4L4qCRUCWLxkncuOh6nnhPriDpJrTL8NAOrMW7ACoOwDrQlO4WHP9To5wJTG37x\nd28YXivEkBCHjDSegwp4LejCgeAkMkogFti9AqfxWmLzQPYo0J2smMQ1x5HlSa9AxUx8QATFOhb8\no9rz75d3XP0SVkNAHcHT92LeLQ2uGZiXEi1B7h0ha9FvNfu/j3EvYzJVUOQZUaqhETjr8d7i8KA1\nRBp0hE401jeE4IljSTlNmZxXlOcpZ8eB6UKQZRKtBPGRJrgd2+0V+3aF9YHoJEHFBUm1RJUaGUfg\nFKge4RqwhmHQ9FtB0wu295Zua9EB0iJl9Tpl9UnP3S8t3W9iohChnmSsPpPcHGLe1hm7vqOMZzwr\n3udZ8R7n0yM+OJ+jkw6r9tT7LW+vrzm8bNkPW3xmmEwUVR6RRhEFkkQqoih8+dOjmFXb0TYdahYz\nFSVyCIQDpE0KwVDLFnHuKWeBLA9AwDiHSL88/xJlmizz5CFCoVFFQKeKJE64eKfg+HXMb1yM6Q1X\n9cB9r+nsBfgBmhhCh5dbjGvB9eBzIpGBkYRGIXyDzQbkhWHxb3u+8eYBra9ovSBFIiPD7dsNqlMo\nI5mqKc+LJ5RZxusvllxtljjhuJickBVTmlqTzGKm04S0j3l4mpPrA1kF1aOcxUlM0k1gq6naM87b\n53RhIMkdzz9K+OYf5Jw8bAnDHdWzmuO54+bvc8RdRq8E253n1QvH9nJNt2453B3oEiifJ3zjvys5\n+oHhkNYcwgFfxviuo296pAwIZRBeMOx2DNuICIkMFad6jgv3dM0a0cVIofnD97/Ht36/ZPL9mmE+\nMNiIu3lgODhulOGLz7Y8fr7iaSk51QVprvBhx75bswsrRKXJywwZw/QiZzGd0C4CMgqUleOTX2w5\n/7ZAZ44hdDQWXFVRHmUEVVKLCCs6dm3geKGYTi3ruzWHVcs8+wHnh4J6f88uvmeRB+JHEfvMs60D\nfSy+6tE5Go1Go9FoNBqNRqPR6L/y4x//mCiKMOZ//3PE6ekpH3300VeYajQajUaj0Wg0Gv02+1oX\nLRJ7SuISpIho24zldYRup8x1xWof+Pg3b9kPe+JIMAkVBSUYy7a549VfbyhOLA+/0/Hu85pvnEqS\nzJEEkMbhnGXfOLq0J1OSUiTEUlNYxclZhDxXDIPj7qrnZDdw/VlKvbf4YEnLkqAdairIH+aoVGE7\nQ7vqkX1MsDlCR8gsoBeePq45iic8QRO1Fld4VIjpI7gtWl6JNe94+LCKsFvNrgncftzyn4OkvzCc\nDoYq8uTBs/qLntVfwPKvFOZKMpko5LcGVC5JXc5gIjo3YK0k1xGZqohCgYggfpDwg3+reXTWEclA\nayR905FFHqV6vDYMqaSTK+r7W9r9HodDTBRaSXR0QEUgAG8UtkmJKolKBYMXrOqWoY9pdxG2q+h6\nwWo9sLzvwEbs1hmHxnErOrzsibeSe+G5HwTSHPG+fJ/v6qc8eTynejdCTixCWGwf2A8d982Gu3pL\nFHu0MuhYkImM1MyY7Oe8e/4u2YnHPtwyzBq2/ZrZ056LRUpxkaOUwm4sURejdpY0zpiezBkWAZHd\noyaGiEC7kpRZhbQCrEQQQFoiGaMjhRcDQg0UiwwtU5afRyQEsJ46RPzyakCmEVNTIfIjkqljepIQ\nlS0Ch+8HzEHBEEGXkiuBTgPJmeLkwwO/Vz7m6pVieVfTGoNcCKgDvvPYMHxZ7llbkj7h9578Gx48\nekBeZbwZtqySA83geTA95b9/5xtMC08bPsbNrtETj0wPxElJf7shtJYyPubpgw8w5zUPPpTk8xjh\nNKmM8O2BNHPM5p7To5jtUcHtqubjm1+i4wFhFAwFcT1px3JFAAAgAElEQVRjOsnJDltwN2y4p05W\ndLUlsoIiivB5BEKyW/W4JmCahqsXn+Lqp5xlH1CFKRuzoubA4Gui4nOihaE4W3N0Ebi/fkRoFyy7\nnt3O0vYJbxePUaUklhFzPIgdJ2XCXEou1ZLL3Y7tpWF4UfLN977D7/3OM7xKWG+v2dz+DS+/iLDT\nmPQxtImn31rqnSWv76iCoZxIZieWD78zod9I6p3n8rbmP/zHv2X3uuLZ7ydMvnnEqrhjdS7ZWcln\nneCLvfuqR+doNBqNRqPRaDQajUaj/8p0OuWjjz7iL//yL//Ldz/+8Y+RUn6FqUaj0Wg0Go1Go9Fv\ns6910WIm3uNB/JBKS9qm5eXfdLQ2Zv0bz+p1R10P2Mwxm1RUaUGkwMQ9cZxzlsyZnyrOjldMsmuE\n7pAiwnqN8YGtd7zZOYpIEGmFkQKEQ0WB2DqC7mldxzJ0RHOLEJKhCRibUKYxT5/PSB/viE4O4CR9\no1B9RrOLGfqYkCmYO0SuUDoiMTmxKUFFTOOKy2LPW33PtbIoF/EtDSd5Tixj6tTxYlvzH3594LNf\nwsumIG0VUevZLD27lyndqkK5hLm1ROs9AU2qMmKniaMIPS1Jkpipr5joKeV5zMkPdxQPf4mI9jjv\niWKBiA7EacDHB/owUB9y/C6l2wlMG+E8oIDSo2LPoTbUrSGPNKmOaPcWao81gbbRuCHm+s6yvvNs\nljnrm5R2ExNswvbGsawb9qVHJSlb5QjdjAfhlPPkjG8vPuDxwymzhwnRscDFlnY/YBpNW4MyMWfz\nIxp3/+X5DQ/SRmRxxSSv8MkOf1YTvbclKluq0HP8jRP0NGbrW96+WuKk5+iiROgYq2rEY0t46BGP\nIK4g7KFfB1RI8bsUoRLIJaJy9M1A8JagDd4bAg4TPN7mRE5SRTEmTrjdOT75bKDQLZOZ4OJ5xf2x\nRWlHlDiCNthEkYaEJBHEOsH2hq7pSd/xpMaibqfIoeSmSdBlgy80SazJrSQNDq0s1WnB0emU+XRO\nEmU8TFKyuGS13hGHhGk24+lTyeevDc2wA+Nwg8ZnB1rz5UKSeJIQqwl9IZgsYtJCg9OowTOs12hl\nmWcVZ5M5d1nGkoFVt8KEG/CBNFzwzeQ9vvX+A87P32JVz9ZecbmqOWx7josMMVeYMNA7uFka1teB\n1U3Dob5lcfEuuhbIGnofIPFMVI9rX1KHG8r0mlwrkqRHVQbRetwB6vuYy/8kEd+tSB9pQnlApit8\naKjljt2wZX3fsn8JyhuKyY7Tsz1pqThpY14UKYdux+VrR6QCwznYxOF8z1R4jHB0xpJZSzxdc/yu\n4fgq480KrlYDyyTiyfUU+Wigm96hCsl6b7hzltr6r3p0jkaj0Wg0Go1Go9FoNPo/+NGPfvTPihY/\n/elPv8I0o9FoNBqNRqPR6Lfd17poITanuJtnNBpW7ZKX67cMvWf/1tB1FjFVyDyCSCMk6ASiMqGw\nGcUkZTqXFGmDko572zANCV4mDEg2CF72lne8IvEOGQQSTfCBwQ50oeW27Vi2njS26NijtML0MV2n\nmS1mJOWAShp8B9JKZKcwu5h+rzCpp88MwxvLxZkn9orIZtiyZCNSPk8yrlWJ9BdcNIqTtuYBUJQG\nU7QkSvGxU/z855r15xPMOqHrLL3SDF2MDjHTOEUlirbpKZOEPImRwlILw0HGdF5SEJEnMYtCU2rD\nbndH528QDpJIoaKOkEOgZxg0w7qku0/omwLnWkTSISuPbyytFTR3Hb62TOcpaSawXmAHiTMKMyT0\n65S7y4Hrt4r1bUy3zTGrlCEE9uuGphNQFsi4oiRnUTziYnbBxWTKO49mlA80SRoRkeD7gN1t8dsB\n0TiqLGZ2UvH5bo13ESCRSuMjCGVNe/Ga+PmG4nlNGTvO4pJCx2y1ZVPvoT9go47s6ITsXY8XG/zJ\nBvHogD8ykDqM98SJxtcx6lAiZY6axMiJZwg7BrNFBMugOrxr6A410eyMi8dzsiJl12uujeOz1xtS\n3/Dk3HO0SFm+7lDzhKBrguqIEs1JrggqRgqFsAFhe06eGMy6xuVzNiJHmpI0meLCQCIEhfRkDCQT\nz/GDiLzYE8QW6SRHSlPpCdNcowfN6y/uiDPPYd9ihMBvBdI7VKrxwjKIgU419GKg3QZimxGHBGxg\n6Hq6LsfFlpwZi2zONFbg7vCJx8QdIRgi25C6iCwtCLKkH2Y0zRmXnx24f7XHzHOSpwXJ3NNaR31n\nadeeEBTFCSh/QLy5RFtF5lo0A6prWd/tWNbXJP7tP22gmaMITNOEoRhYbhxvfyVYm4LNUFA+i9GT\nLUOIqTtBs1I0LyOGV4KTeUE1rSmmb8nLDWnl6OPA7b1jfWtwg8duBFQOsQ8oINIBh8P3Bpv3sLAk\nxw0i0nT7CmNi5OEIvQ8okzDpBVMLcyEotGD1Fc/O0Wg0Go1Go9FoNBqNRv/cH/3RH/Gnf/qn/+zz\naDQajUaj0Wg0Gv3f9bUuWmxfSV7tDT527GLLtZS4bYN0Bj3zyDzC5YphAz5AHufkSYUIOcEJdpsa\nkpr4kaBzAiVAa0cP7B3U0mCcxxhHCmgX4XtJHXt2feDQCtARLnKkRUQ+Kdj1GfttoN47ooMgzkGG\nQIwEIxG9xOwC9cZTG4vZbfn2H0ZkVUuSHOhSz8fDireHb2KbD5ntKpJ1zN4sWSxWxPM7hvQOG2nK\n4oJMpmzbCc0+ZSs8RT5FRwOph0kKi+NAXCoWUcoREcrAph3Ytz2NFCTasY22hFXD5c8/Qzy7RZY1\nCon2kjgCFxRCl7j2CHn3iOE1dLuAVQeik44iDwz7DYfasL+DEGJkNGHZCLA5dqcxB4VpNfvXMbsu\nZXXl2W9jIjmj3nQ0yZ7BSzQ5ETmpOOHd9DEPj8+Yn+YU00B2ZIklZENO1icwBCKbsPcHQqiJI89R\nVfFWgxMxKo5RRYQpDzTnK/LvXZO8v2F21nEeNA+Sh9xtXrM0NXWimDwv6R4c0HZHHjm06jD2gMt7\nOl9jup7gNLEqaPqYyKboOkOsNCGyoEucrXEOgnOYMNC2O2bvlsyOp+zfKq5eQndnuKprOul46BN0\nE9O+jFA7TWMdPnLMH2l8mWBChCQQKc+iSoinA7uLluZih7gC2wWicoI+HMhcIPeGLG2ZLQSL04FE\nQzQoUiNRteY4KjifTtl1A29uXrBr10xODDrL8RuH6hOS+ZQ0DRg2HLpbhsHhltC+8ZjcI2VL067o\nvaE7WEzrEE5QBcVEJph8hsy3WN8QBc3m8pZ//LznrGzJZYrJn3D4RHH/yxVZETO/LigvwIYa2WtS\nYUlOEsRpwe72DcLsSfKKqk3ot5799sBlooiuQC41Q24o9jVJe0UkFNkEip1AdhXdp4EulAxDiTsP\nhCJC3Du4TBk+29FctsTfyamOApPFEp3c4LqB6XHLvnH0O0936RguFeSeWAbayJEkDl2CzT1WaQ4Y\nhrgHHWF7TWsShmaCrA1pX5KbA8+sRCJ4LR2vv+rhORqNRqPRaDQajUaj0eif+cM//EMuLi64vLzk\n93//9zk9Pf2qI41Go9FoNBqNRqPfYl/rooXYCSQGlx6os3tMfodMA5GSqEEwOIGMC949e8gsFCS9\nRhmNLWLiWUY/BPb3Ej5XnP+O5iiq0Dg2TU24t/ywSJjFjiKRRMHizI4h00QOMhMzU4L0yFL3KTIt\nWduY/d4R2oHrqx3Jg55QHCDaI/KUaFog76FxsGskQafkR57FzJIc31PbK26Z4IYfYP9qwpv/IeFv\n/1OPqGt+92lJ9GFC+R3B7hsdbytD8Au+990P+KY4w/5qgtyUVGqKOTqQPhtIn+4IkzcItybbe1Tt\nSEh5GC94/sEZ+XszNttrrj//lPvbt/Tdbzh5pEnUhFh7YjRCaPpdwrBPcKsFcnWCutZE1tFF0A4N\nQz+QnyYMa8dQZ3idsN1P2IVAf5ey+dzR33oyD/1+4HJ74K7t0FLwIH1GFqfYLuCkxRWOspjy3fe/\ny4ffOqeaxXg7YHcdcjcwBEPqJLGUVGnCw2cpr24HmlVNp2q2tuXiOKGPwHiFnyj0M0f2wzXi2SVu\nskb1gcJWuNDgzYZKQiDCSsvpfEGSrHHDFX27xglHaz1D3LO7t9SvA9yCMClKplgjaK8G+rVFnYND\n0luBUIIkj5BagFgRKigeWx6qCW9vDyTSk04S4tkcohLbr+luLCorqeYZlVO0tSI+qghqQMgDIghM\nbYiPW2a/YziOArd/I9ndJ8yHOWfOc8KWUt9x/GBAlB1CSSJZoLqcyZCwyBPCieX41KLTjPq6JSjF\ngMT0Az0J5l6SFROyyQ1J1pEIjdvXfPwfe7omcPxsj5cr9Knm6qphvbylfbvBLp/yb46e8yav+LV3\nvG0+536zpWt+ga4f077V5HtDEBpzdY5sCoRNMJ9mHD4NhMzgZgVqtiI+MZSnktNziX3oePnLA5uX\nBlVU5NWc1gk+/puGdVHyu//unGo1ocjBx2us32MKRYifsN7ccPlxQd4ec/z8ASp/QHqZky9via+u\n6a4+53NVM9OBouqYFi1xZbGbgSRVFIMnuIDbe5odSKFpCRAsQwxBBty5Z9MFWgnRJKBl4KofeHE4\nkHcDM52Qq1v8znG6DRy14+mQ0Wg0Go1Go9FoNBqNvm6EEPzkJz/hz/7sz8azIaPRaDQajUaj0ej/\nsa910aK7vseYhHBsIekRKFKdUaqMRGm8d/TpwK7eMZvHPHqyYHE6Y2csn71uWV7tkbIhuQCVpqx1\nTRwsurCcRgEtDYaeWCQkUUSPRXkQWpPGAe8DpBL5xJJcJdTrnM29YnkLv/75muk7lsWTgVC1WDra\npGWjZhx8Rn1IUD7jRJzRpUsuJx59EKw+j3j171v++n+8oq0L8pNT0qniLjrhP39yy+zGUrxxZL8z\n49tnz+gpqJ8r7NGXmwwenEjU1OLjGqO3DHGP0w7VWgqbUIWULFJEF7AWbygma95/B1I941C/RyOW\ndLYhWIEgxQ8aazTanpLpCwITNtuO7fYeMwWVZrjBE3aW/ZuO1cEyJDGqCwz+BH89IVxJhpc73l5f\nsRcHFrOK75w/I8lP2deKkMaELiNPzplVR3zj6Nt89IMPGYYeO2zwdkPaxhRDSqChWjiy+T3EW3qx\npHiwY7K7YX9zxcvtnmcfXlCKKUlWIiqPOTpQ/KDjdDplUgkit+Xm/pa6vkIIzZxHzCjZKYc8BLbq\nHhHtkcKjvAAs9bWlvw34Q4Q1Ka4G4x2zLKIsU3Tuqestg/QYJUEq6DxSK0QKcVkTqiW9NWRZTRwG\nXB2wvSNLCp5MTyCuUWVDKA+YdIf1cKjBxIqpzjmZacrOcJ9u2PcNi/ce8c3qO0z/NsV8LCjqlvIo\ncPytlvTpFSGFbrvBrHJEU6Fsz/HMkD+rEc82yImh2il2VyDbmIQSzZzVpiWdTti3O5r2hgflgsnF\nCa6sWa4vqcsrysc7lLG0uidkBRQ9IRHE/YQTPcNH30cnM95Ur/De8pu7Szb7gomMcCbQ7hX65IJ8\n/pgyPSNtQKy3dPknDIlDTu6Iyz0yMsyPjjl6+JjlFye8+DvF64Oh23ckb4/Z/XXFp3S4d1rss4Yw\nWbLO9/S2IH1yxvrne9rGUe9y9MuSJM7YvnDsrirqu4ih6VHVmp6GXebo84HWGq6HgJSSKPYcS8fp\nVFHvE66/kBzWAhE0+dRx+NizfNlznzgOjUAnAS8c/caxeuG5PgsM3w5scwcJ3DlYt+GrHp2j0Wg0\nGo1Go9FoNBqN/gU//elPx6LFaDQajUaj0Wg0+n/F17poUZWWSdKAHpBTy8W7FTo6pXkjOLzpsUNP\nUJ7iCE6/6Tn/VkN1FEi6Cf/wYs9h01HkCkWFVitu44FgPakRlEGQehAhxgdJIx2NtrjOo4CA+3Lr\nQ6IYJgF7GtHOU24zWMqBvnas72r8fQ2ywzrwBewjy95aDm1CFkqK6IKhfsjt5ZL+Hw/c/E85L//n\nI8L+nHRawXGgy1rurGN7H9P4ObOlI/kEjh4JCiyTqUctatTRQHbcImSLCx3C10CNShQ+hySuiITC\n9R1OX+P8Fhk3qKgD0SLSlgSNlAUmgOslphcEYqyVdF1L01kaGbg2G0TfkXcOfRio7cBnL2uaISDL\nhKgRZLKgeZnQXTvaHXg089mU6VFBXEU4MTCEHX1Wkoljjqojnp8+5sOT9zhOKvZ9A32EPhTI1YFi\nBvf5Bn+xxT46IMp7kmSLMHv03ZI0vyfsejgSJHnL+ckRi+MCWQnkcUKeCYwfaHZ72i10iaZMC9Kk\nII9TCB1db5ED9NrQ09BJgdlBu4q4fyPYXClcB0XimBQWXw24yoKGrm9oEoPLINIajGDYW4IXWHXA\nqgNtuiVZKCZVRNMp1puazy93TB/mLDKJSiN8leFKSS8c265h6B19LOkiQW88QngePDEsjnpWnw2c\nbs/pTEnetpQz0KdrokWCV5pEnXO4P+PurSSae8zRluS9Fek7a6w1OFkwCQl5LxmcoOng8s0tzX3N\nq9eXdPWOaFqRnSfsI4M4LYnPJ0RVg3VrdObQR4bUKTI1J3q5J+0mZIeSuJ2C1xi5pTtsqPcJkYgJ\nQhCc5qL0NGfHNDmk+zn6OgP5lqAgyjqqI4uOHUps6WSJrqZUk4ecJAnX11eYbs99CAxDYP4sMPgG\nFTUMqcPuwfoDh73hxi3R+og5MxCS5W7GdhPYLDuW2yuKYeDqXCBygdxLNu2G3SvDVHpO0sDJRFKU\nEV1ZkrU5207gt5Zu09PpgW0O7dThgkYQE+uYthlYNy03dUe7NcgipdM9S+FZjgstRqPRaDQajUaj\n0Wg0+lr6yU9+wsOHD/noo4++6iij0Wg0Go1Go9Hot9zXumgRJmuyR4LZO4GLdx3dqcXRcOdKunWG\n7QNh33L0PcHR9xryDxt0IoiHC9A7JJ5I5IjaUn+xZDc1+CRQoZBWIXVAigSnPF1kOQSBtZYkKGQA\nKQQyBIQJhDAgvEGi8NqzawzLK0t4CzoITPD4xrDatKy3gmafoJ0m7RbIlyeslltu/pc1t/+r4vYq\nIntQEU0MYtrD3DPsVqhYMZDSiIL2zQ5We44XGUWhiCcDXm5waokNBxwG4wc6a4h1iVIpMrN42dCZ\nBttvCarBhRYzDOyNY98NZFmCUhFCwRAMjbUM1tDWhnq/pzExJk1YFQ3G1UTrmsgeUFPHbWswvUb1\ninAF88ixu+xpmx6XdURTzeQkpu+g3e6RwaDcjFmuOc6mnOdzHsYxZdgh647TKicKJQiN71r0YkP7\ncANP7wjHS5y+I5sEhm5LEW04ygacFQixI5lDPof5bKAsEwZvaPqB3cqxu45x2zmiiJGPM1wqsXqP\nHnpEcAhnsQHqAXYHyfBpTH2XcVgmNLsMHzJE5MjLGjM90KaeYBx93GIzQx8bhmCwQ2BYBxIX8MFg\nE4NVjmiSUpaCrjfcLve0bSAzjvffhWpiUMohY4/vDDSWvnNsg2eIBdEkI0oC0wLIOrLDPZN3zqkB\n0QRk7AkTQVZWOJEj1GOsesDVxqEeJqiHa+SZh3QgbAOul0QaUu0ZsPR6oKs8n31yy/X1DXlvEEGR\nLFJMIokexOTHChV2SCTZTNPmlr7c489uqacvULcXyE/B33YMVuBah1ICJwyd6uhjQ0KOjWM2+pJX\nKrBjR2JSlDVkWUR5mnJ01hO8w4aOur2jp0TIc2bxhFbvaemxvWVzI/jss5pUdlRKkJUZ3mbY3mK9\nZLm/p19eMS8CQlsOoWXlOm76nrs+oFYzdr9eoDuH0XvWuy1RI4gXDe5iTUgPkDpmhSYSM6Yyp74G\n4zvs5MDsJEOWFjqJ2WiqVBFqR/CWoffsNo5+rrjsYNcHNn7caDEajUaj0Wj0/zfee5bL5VcdYzQa\njUb/F/zxH//xOLNHo9Hot0CWZVRV9VXHGI1Go9Ho/9TXumjRTN+iv9ty8Xs56VPPF3XDvrlC7J8T\nrx8QTERoEqZnkD7eEM4anPeYoSGrUqpKkoiU4bbj7i897rEneeRwc2iVhNSTBSDyWAkuRPS9QwWJ\nCBJrwRiD2TuG6y37jcKZnKA913cdszeKYlFSDILBtTRtYPW6o7nXcAAdNPGNJvvVI27/bs6Ln6cc\nOoPPBgwHImPIWkGsU4Z6w/x4Suo9bi8Ih5TVTUO8jdGzCDtX+EEheo1NYryU9FZRD5qoiZjmBYEE\nIwOd6TCqRckWM9QYY3FB0zSGAGjtGLxjZzq2Xc/+ENgdEuqmpB9yOh8TcsV23dLs1sS1YSI8fSwZ\nhghzL+nvoFEHBpthsx5dGVQu2UUtm6tAZCWLXHOcpzwUJWdTTTU9oLIVe+ko9Jyzi3eIyxl9b2nW\nNR2/JnrnDvVwj47XiGZNHiJ83DBUDqkELgRqAumZw/st9VAjbULb99zvLfevAu1lhuoL0iyimws2\nxZperPnf2LuPZuvS87zv/yetuPPJb+i3A4AGCIAUk0VaocpDfwsWPwM/jzH2zOWhVVa57HLJIkVK\nIkEAje5Gv/Hks9PK60keYOwyJ3C35PUb78Fda3CNrv1cBkvUgpEe2yvc3Yrxi5zD32TU4woxW7Gc\nZ7hshMUtbnOgm3c43+F6i8oKkAZnA11tiU+OsFUkA4hOIucJKjEkRqKVx7uRYw3VMfJl4khPNVfO\nMsOifcA2ETOm+BrqRtCrlDOpSRNPaHsCFcn6mtnVkqE50Ny3ILcUpSNJSoJaEYYl+BIpNaY4IVlm\njG5Hv91BKxHNDNv3FPlIkg2k6cD8QtK2e9qmIZUB5yCqiE5SojUMhx6tFqyXK2bLiLUNdTlSXd5Q\nzXvkXY2uU+RNh+sFoc3YnC6ZzTVD2vIYDxRjQeY11W7L9riDfY65PedHs8jp8pSzF5HlZs9w3EIa\n6VyLXNzjs1tkWbLYSBJvaBM4MvD3/2bH2SFwVS85PZmRDnN0r5BKcggdx+MN+8fIfN5T2wN37o7r\n8I7K9JxvLugf1zxcC9rtSLsPrJcLuot7Ds2XiPJrmmcVLzaBohQkumCxyvHCwSYjvprxaBw3T5HU\nC/RXhrgvWPuMvA+EShIOnl0H+wra4dtOzslkMplMJpPJ/9fu7++5urr6ts+YTCaTyT/RX/3VX33b\nJ0wmk8nk/8Vf/MVf8LOf/ezbPmMymUwmk/9H3+mixdkfR87/pCc97xnpef79yG+e4OE3ng/bJ/Rx\nSa41uV9h3EAIPRBo2lvK1SlhleOOgfoQ8W8NJ88KShXIJeRpwJeSw1ghhoisDbpOSY8L8Al91zDY\nkdEGrr/0ZMHS9w6hIsVccV8ljDvB8EuDuU4IOsMpT+nmiLxAj6eccYF6SEjGkqbvebfs6LIjn4qC\n07UnbXvGX7Y0zrN+8RnnlzOaXc3xrkKR4YeA2s8JYsECg2zPeXz7HmRFutCoQhEZCAEoZozGEKip\nZcW4keiZwEdJ9AlaZszzAqE9h2PF/e7Arm0ZOk+SnCLijPFouH03cDzUZGpJ12n6kKF84LGr8QLG\nQ4s8KGZxTTSWbL0kGI1AIruB3fWB2eyC84sV50XJuk65oGO1+orN9xz59zr8RU8MGTfV3/D86nNO\nnv8IY+dU72+4fviK9MHx0WXG5foU3+7p956xDgwddAFYaZyX9J1lbysqN1L5hvox5/CuxH3IWeo5\nm7M1w9dP7OtHmrN35KVEaY2jwN+UuL+dYf/zCfrhBTpdEU2CK2q8+cDFH4AsLa7fUt9WNLcpm3WG\nspIiWaGaGbvrlr6G+7cNaimZnwpmiSKXBtuCHaDIc07OL3jxA8lQ3DPOj6QnA6WSpOaEcSipMs1h\nC8dHx+tfHMk+TVleCpLM0rs7utazG5f0UpMoT+Y87UFiZpqqGji2NZich69bin8UFF6jZoIswlJo\nqsoR1ECWSyQFKTlaAErQh4Ft+57xXU3lDEenmZ/n/PjPPufkR4aueYsYI0ujma8i+Ud3vH3bwnZO\nPuYsnhSPXySszUd8+uI5+cKwvdlz375nbVPq+p4H9UQdc4xL+NezP+ayPCUTljhWLMSaSMux6Ck/\nqhH+iUOT4wdoH/ZUh0cONEQUZnZCejghXV2Spqekd1vG+x113eLEEbvN8RcSxxbf7rGhprY192JO\ne0zBSnAaE1e83gue754zGIH4PpSzN8SXCewbRCeQMUUpx+rTnuUVXOaC5VnG+3HJ6t+d4IaURZaR\nxTvGKFkmht73/Moqul59u8E5mUwmk8lkMplMJpPJZDKZTCaTyWQymUx+p77TRYv0uWP5IuF0fYbX\nCbG/oVq1fPr5gvnTM/phxeOXD3S/GBh/6rCfDYxyz6G1BCmBNWGUOCLDMUEPlsIMpLkjRk9VwfhG\nIXYK06UYt2B2eoLKUoTf025vONxu8cNv//FfLFJSuSGbG95Wd/y6rrFZyifZhgxBPOxJbU6xKTl9\ndcZHs5eofcJ9bTngaRYVt90XLKuUop9R+hIpNMex5fbtDb3doqPEyBSzLNkNEQdsjz1pC8tkhuIz\nVDLCMSCVJaieNMtpjzBYi1wm8LEmLTOO4xtaXzGMHdbt0caAEnRDT2cDkpRmH3jaOdrjwDCk6Dgn\nmJbr2y3ROYqZIRXniG6JdBVJD6mYkyU5nTOUxRzVGpKdYy3h5MUrvv/fXJEsNM2hpbs/osWW8OMH\nkj96Yv68ITrNqfk9wiAp8zfE+IAJ8KOPzjDLA+8f77h9V6MWKQkJJafU9Yi9aQm+wxSGWEt0rpnN\nEhLlkCIySxYUYc2RJcM7wy/+Q4u9eODqXzk2nxTsgmUvB7ZvQLwtUc0JQb3E9QWxk6yfZ5z8JEF9\n2tKIb+jtlnbX0e0itvfs3iTcXA8cdj1DFYlDZLVIsc6iK8kwQF0IdDVw9zQysmZ9suT8asE4brl4\nKSkuLN5UdFGigyGi8S6hbwTVAYad5uRZgfUCFUDpQLLyxMzTVdC0nq6JnLYKp2C3f6SPPScvnzM8\nHnj4VeCjq5LZ5YKhfWJbvWYsRsxKE3OFrj3+9VFF2IcAACAASURBVECsLNJEOut5/XhkESzl7ILD\nY8c4dKg/vOL0YsXuccsgOqzsGExDcq75ael5mXi6es9f/w8tf/Dpn/OvfvzfsVzOGX3DxXLkYnOK\ntQfKmGBiyhMdi/kaUyfIwyXaVkSzh74nj4KX5W8nOZ5me963hnJ5iv5ygXgXkIfIQ9fw9X/c8vBL\nOJ+XnKzmxGRJ1W25aQ8MQXBhEuITuHDE2RHlIyJGpFNE5xlliy0smIrH0bCQn2CTK5LEc7LI8N07\nTOwwC0+eSLRybJKOYvQoCo6suF5ECBm20SQnCRfPZshPZnThluV15KQOLFRk/22H52QymUwmk8nk\nWyOl5OTk5Ns+YzKZTCaTyWQy+S9O3/dUVfVtnzGZTCaTyT/Jd7poMTuJFCtBqlOEX6B9zatSIS8W\nyJOS143kYAfChxLxkOBbwagGhJLoecugJJ1NKHLJ+fMTFgtJkjgEI8FBoiLHO8Hx5zDeSZIk5aM/\nPafcGFxl8TuNFprVs8BqoShdQXiYY36jOT21bJ8Exy5w+xRZ5RojSy4vEpbPDOuTkZV5wrSnHD90\n6DeGzG/wyYK2tLz1DVXnSb2iKwTCBOp6hx4FhSrJoqPuLKEYEUaSGA+JIO0L2l2P9w35PHJyVRJF\nye1thRgCpTPMlmuE8VTjI5WrGBiwMmLyiNKaupY0lWLsNMf7gKw2UM0IdUI/BFxikViyxJCHgviQ\nkLTniKGnEJIiLUhnM9KLNUW+QUcoouPFOfzoX6Rc/iiBRHP9zvN1MyKKI1w+oC63zE8jeb8mtxUD\nFrCIWFLkM5SUnJ0sOB5a7l8fePdLuLjacPHiilg90d5cI0xOemNZnGQUWUD6njj2oAJpISlWhkMu\n+HBs+OYfHrhIWhI70EfHk4y0vefwNDDeHGH7SKIL1j8q2FzlzJ+Dmz3xdPMV3fEak42EUSFDTlKs\nybKPuQhzcq0ZMoFGkKWOZjxg9Y6+2nO4PxKryLEJBCOJqN/+LinI0wEpJCEIUBKhPL1rqO1IP2jC\naNg9WsxTwCw8RIcmElSFmeeoNqdvDMOdoP51JCsDMZPkypMXNdv9E/Zryez7NcmrgDeBIezpxcjD\ntUV1A8XDmuN/KkiOivmioA6W45MlcYL1vMQcA6mAZabxciAWFh0jiRWUFpJjT9Qj4VnF9/6l4b9v\nZhSdZfV8R7mWyEQjxozVteDdbyJ91TLPVqwv1pT5CU3reXyTYr53yslHF+TJkSyz5FhyOTI/7Uj+\nxR2PZxHnUoZWEM2chw8t74ca0cFdVXC6yyiynKofqf1AEwO5rUnHgigkwWtkTEn1AukNMhq0cgyq\nohUHZHZKWmiK9TNmSclcJczLBtPf47MBmwhwHhEicvCkcWBmPIuzlPp7GdWXkkq1lDwxiz2JDPww\nV4jc8Fb7qWgxmUwmk8lk8v9jZ2dn3N7efttnTCaTyWQymUwm/8X52c9+xl/+5V9+22dMJpPJZPJP\n8p0uWgTlUIkjNwHdSVJKUuHotOBaBTwOM1MMIbJ9Z0m/HNBXnjSdk6zAJj0DgU1Zcv5qRrmpkakg\naAFOoyyMR83uDg4fEnReIm8SFj34BvpaEueC2UvJfBmYtSNjN5IIzfl8xdhZ+q7moRpxLnK11CyX\ncPlqZPXskUQ7MjHi1yXP4gV1/z36J01lr3mKT+wczAIorUh0ZPQB4QLVcMTYBiE0acxQyuMZCW4g\nsznH4YFmeCJPJSI55ThWPIrmt1MeFtIPEdN0dCJhlDNCCmQJrXWYNKE6eKongW1S2l0kHeeEocB1\njr7pYDOSF4KSjNyWhD4j6daIY2Se5CzKgvlFwvnnS9IMMj9Sqp7NxcCnf5iTL0DLDb5OuI4QrSZP\nCpQeESqSJzNCY0nIsLYnhkBpFFEeKLThbLamdobrL1rssaBcvqSxCYe6RrgjSnvEZ4JQeIYwYKJD\nabCipx2P7OqR2+PIdXPLQgsq39O2ln2i6baK+hho+4ZoHpk/M6w+zpGrnjoOVPsbjnc3pE5gVgtQ\nACk6vyDPXzLPTplrRT+LaBXx8kjsoHOWvmrZP0X6A4wuQSSawQW61kKeMtxr+lQjhEauBI0c6JTC\nqggCVJTY3hM7iJ0gJgABHwOztSSMBfKQMkTNuBeYsKFMC4wWjK6jrXeIQrN/6tA3HckJBAmd9zzc\nj7S/aSi/qsjvz5llc8ZFYAiRwfZcff6K07MzemfRoSWIgSYMhMKjVCRrFWknyY8jdTki0oar35/z\n8dkl7S9blPwFZnmBSVfIdsY8K+n7kuZNxmHc4/qawdzTSM9wt0S/1mx+ek6RZyhlCbYl50iS97jF\nliAtvlsQRUH3pcDfKTqp6MaO1t9T96B7idIWJQKJlEgtQAl0nuNdpNSCjBXLeUkqUrxJkWLEjR0m\n8QhdY8SStF3C/Zz5yQIfromyBxQuCPpeooMkAHmiOF8U3P5U0f29Z5Rbor/hvD9QAufGcKoVhRi/\nvdCcTCaTyWQymUwmk8lkMplMJpPJZDKZTCa/c9/pokVdeWwYSPKWnIQ0RLwacEOFY0b+fMVlPuNe\n1+x+/cgyrXjxLxXr84wQJaMIOO1RuSdfRlRpCWnAG4H1im4rGbsEpw1hsWJMN7y/GckfBlLhUIlE\nLiLFTNCbjjjcY2uNHS/ImBEi9NHhvIMhcCFKhA8Y0ZPOjmTLPcSaeZmwKC44Nd9n9h9e8O/v/hGy\nD/ikp3EDsatRvSVLE6T0ODfStR1pmmCHligsPgYGD+NYMOoDvXliEB5hW5qqJ2wAGRlHR//oKI+K\n2UyhsxnaaWQYODZ7VAp9rej2At8ljI1hdALvekY9IuaWdC5RsSTrcnKRk81LkhUkZcI8W3D6yYKz\n34fNq4by4sBiWWHSI0HV2LREyJI85qRqwWKc0z+UzO9nyPstjanQWqAGmM003dhjuwatWsqlRccN\np+UZzWrONzzw8y9G1AvHMeQcZc7w9ECSOZ7eOUbdUS5HlBLIAqp9xe1tz/2tph0880tLMh8IY4/Y\ngtGK43WCq0Z0FtDLgWS9Z7z8Nff3nvZpwB0juc2Z5RsyleDlSACknBFDiq16xmPADpaYD7j0iPO3\nBN0QB4sXisYGhMlRJmH0jodDS0lK9A7bC9ZKE2aWJnRIk5GUCl8oRgJGQ4EiiwrjJCKAj5EsV8Qs\nQ+QL3KpE6xlFtibNM9zYUA/vUaUjP/FYW/P4oSEZAkWZ0ruI7XIO1yk3f9fwchYwn85JMoEaLflJ\nxg//2++hR0XT3nLcVry986i6Jd9EVBJB/HaCwwWNDBIpR/IVPFsG8lVD13/FIB8Y3YawO0HL73NZ\nGfbbhNff9Pz68TWmfGAxf0E3XHFyPYfDCfpKE12N8xYfBd5FhOiYrzvMn1rIHO93gnRhWPRrHB3O\nD/TmgdH1bNIZ82BYyJLVfEmWFaSrlFSUzMZAHjOKTUKiFFbVlE6TtooaS1/dMR4S3IeM9heOdiEZ\nkkiMATsq2lbgHag8QeoM7TPWOkG+hOFji6trtDiQDy0xQNIqukEQ/bednJPJZDKZTCaTyWQymUwm\nk8lkMplMJpPJ5HfpO120kMcZbQX72Q1C3ZEWgfss8kENdIuUzfeX9AfJ3/31LenxwI9XGS8+GPpO\n8Ou/23F7I8jJaaOjR4LuaNxA1Y64fqQ/jPTDKeX8nKJ4xhhWbG+ODGPNaulZvMqQpxn10FD1I/nu\ngDkWhG5JVTuGZqSvB2ToScsUnZ+QaAlNS3u/px13zJd70lJQ/OglL17+mJ/88Wf8wf+x5s39Ne/v\nH7jxt2yrD9ixgiJDC48WDm08NvQ0T4FyISnnCXkq6foe6QNlVkARcU4gpCRZRYIJCKdJV3NmYkZf\n76kOA6KN5KWi6xKsHwkDDEdJc7AgElDgGME4Cp3iouJKnSFDZHQtYvNI8pOUjy8vuDwTnH/sOPth\nj0p/TmYeUf0B0TukLQjthnEZ6esH+layiaccPozY/ymnf50T//SR7tU1y3LgaJ8QfULiloxOY5xH\nBQ+jpZgvePb5Jf/23/wtvN0wXyaEUtDPwEnJ05sKuenJTgZ621PdDtxeCx6uNU0LRluuPkpY5D2m\nd/hbxTgG3F5gokCVEm1GYn/L9a8smc9Q7ZJsXFHEOZoURU45B6lgqCT1b24Ydp4wSqSJWNHSyy1h\nUREHh+oEs7Ik7gNjmuFTSes66t2Ar3KafYtQknyd/HYaZC4xUmFKDaWgY0SEgfYQyOoekVsQkcFa\nbm/f0d14xE6TMSe/PCMYw2EY6JuamIx8/KcGG/YEeaRpKh7cSEwMoZeIao0bC+6k4+7hhpcvn6Oj\nwEiDSRy62qFkJNVHmuMD/+H/aqgvGz7657DedIg0kC5y2qPEtII8JAQfGPUtaXHHaVFQ9XPq4YK4\nVuzbOw7NEeqWj5NTTq5WvPVb3o9b1i4h1wvOkzV2f4tKHnGMPB09u+3I/LkkuhZl7ikvGy4/WWHF\nGv2fV8yipJcBEz1FGdEpWKuQcs5qs2A1v6KYFQQUQx/w1rNelsznM4JrqKslpS+5G94gZc/Q7Khv\nCo4bT/rCEJ/PIB04tj23HyTrXHBSnlKKGbVNaf1IMkQunhe0TwVxNOzvBfqZYTuMPFpNHcW3HZ2T\nyWQymUwmk8lkMplMJpPJZDKZTCaTyeR36DtdtLj925H2U8lso5nPIl8DP1eOp1LiVc3x8ZZqhFqM\n6CTBjym7N4rjg6Q0kmfPJWIQODNyfIyMzzpc4YlB4jtFuJH4NiClJU1GVnrg5aqgrwa8tHjj6EcL\nPSgEqYfISAw1da+IqUA7A/1A3w/86tcf8HbOGD0bN1AMI+vEslYfyPT/ili8J/zgU37v00s+HSLX\n3yje/EPG/a9nxCrF3Suqw0DvR5QR+ETz6fefEbxk/1jzdGiJbUN5Zrgsr8jLgi70HMQB23U4N0AG\n5twgrcM7DyisM4yV4Oz0E969ecvQ9AgrMFJRztY0WJwdEYDRBuNSlklKflKjz7aUf7wj+3PL2ew1\nV2nOqZHk2pJrgW48IRpcFLjR4pd7joNgf3vP8Cgw6hRVCgKK/S8VZbri+fcWqMUDdrxDlR3O92wt\ntFWCCEfGwdET8IkgKQ1Ns8eYlPa45/qba2btjM3ZgpnK0OGIVY4wBpQuSXJFMRsRvUN5R7N19N4T\ni0jvIqE2OBvoXGTwgd5ZpBRcGItyBwIeW0IlYect7W3P2I7o0VCkJWmWIlON95au39HLb2ARCFIh\ndcZmueA0v8DGnKhKTD4jy3NM36P9e6J7pN17kk6SZAFpEkyiiakgaAijww+OwY2EYLERbp8iu7uK\n/vUW/bhgaTZkauQXX73B0nH+LOH592eM2zvCrsePnngUhEzgM03YpyQfFiRvSjLf4y7hcXgi2xn6\noeE43PCb7cD3LxUffXJEFQOvbw68+1WFfAVJCstME7JAKhN6PyCFoAyGxCqksGRKIRNNDIK963jq\nvySYgo8/u2Qccr50j3iveHzjSMUMIxb0+0iy7BDZkaap2W4H6kPA6JRje8+YetwQODnLaEbHy2bO\nantK1+fYYMmWFrwl8SWL5IT16pS0mNH4gXG0zDSUZc75Zk2xmtMNc568JrYeG3us2LMbHvnidqBJ\nRuL3Eoxe83hs2R8tRak5v9QIPRJDxMSUOSXfF694dZrx5HPu7YH9w3veO6g7x2MDxzF+y8k5mUwm\nk8lkMplMJpPJZDKZTCaTyWQymUx+l77TRYtifUVSKmoqKtdSJQnSwHKekM1THILD/RM+OJyQNI1i\n/yFFJBHbexS/fbABCU3V0b+2hJ3DCfC1RLeaVEpIPGXaczpPONloYoCQKro85ZCXcGLQxmPShHBM\nkWXKZ6czZpWnzSTBGyQBLSP1YPnwocX6jo9yUCMIf0TL12h9RJRfk6tPidFwtsr5wSeR+rHj67/v\nefd/jkSv0F1KajLmr1Z8/sMr0jRhe1fx/je37LYdJofEaJJR0+8hF4Ykd7/9Dn7EN0cGr6gfG/ZV\nT+8dSSF58ckZOu8YhiMiBFQCQVh8GJGpYi5nXPoVKSkb11J8dsP8z2+4/DPL+UqyKCVFtBgbEA5o\n5/SDIwqHQVOkJQBOlmiZUQlBJQfUVcS1ULeWcqeYXWdY22LykUJ5lBPYQeC9xTlLsCndqHC14vPL\nnPZQ81gf2FUHdn3kw03ke5+XiCbBVg1DNrLvPCQjMvdEPeKdo90LAh7RCKwRVJWnOwIh4ILEmgCl\nR6eKeR5R80BgpOr2bL9+gJiSSY3xAtd53o932EQjpMEIgU4HxFlABxh7R2gtOVBkBkVGXs5ZrJfM\nlgXC9ox9gwstXd1hv/Jk5571hSdKi4sSskDTDOTek6gRm4y0UdKrQBsj+31FuN4yZmtSPePh+IgT\nA+W4RKc5g4h4aeiahKZxdEVElQnZsCA+pfQPlo6KUDSI7IKhV4x7T4wtD9vf8MlHmvXakV9aLj7L\neHxqUbUn7Bxh7giJx8iSVCpMTLFW0MSWSva0R4ceIlWV8ptbyVc/d3y++SMuuWR/A6p5wmlHLxwm\nzSnUCt937Gc7huEr2mEkqJximZCXKVYtMNrhhMbNR5LTiuw44qTC1CukLclmA2PXIXpFoWZsFinL\ns0jtLH4cEWNAC8vZIqc4SQhRs0pnzDmH1zX72BJ0S288T0Nk/kZS9BsO/QGrOhaXhrLU5GmKFpre\nJoT9iuX9Bd17CE8DKn9Fud5y5x/YN4/sHy39fipaTCaTyWQymUwmk8lkMplMJpPJZDKZTCb/NftO\nFy2y8zWcCPp0QNCROcOZC/RJTrtY0OUzXPuIVglaGYLN6Q8GIR0+jiSZoJwnZGVGsAP9e4G9Ay8C\njJ5Cabz1CFlhVnDyvZ6TjQAxEjOHTTyrWKAyQ1QjUQj6g0A9SH5vvaJ4O/DUBlrnGMeREBztYDFx\nRJwIlmXJcibJMo/ggBBHUnmLjgdSnbBabmCZ0j+rSNYRl/WEv1+y/ULTPloulyseD08kRhAJzE8E\nNjFEbXG6out7hkNPNA4/tJi1I00iLlqcjgwqEk1CplOS3OCcpCxXRKuwoiNai4seJRRpmrBUMzZD\nSYnk/PzA8o8bln/Wc/Zcc15LMp9DDETnwCncYAAPmt++zECGO1hir6DVtK3ntj9AJghCoWYavTA8\n3Q9sjztW5wPLQpB4iR8g1x4XA0N3z3FfI9qCP3l5yfuHwOuHHVXdU6eG2x52R8PyFlKl8BeBzkeU\nGRDJQBSOqlE8PUHtJf4AfQgcnwKhD6gxopJIegrzEnSpkCcJ1ki6xnK0FlkYdFMgyAlSMwTLrq3w\nXhCJBBvwLjDcCLQRzMvAahaRORg1kkrLycKzOXPkqxahHaNTtH1K0xiGfU+QUOYgEk+MAVlCHwb2\nXUANjsQHaiJOBIRUhCDo2pHDcGC1mZPNwZMgUYwNNI3hcFC0R80oCwglxITjvaa9bqnqkXHdoecS\nJSX+oNFtyuVHJenFe8LKITeRVWo4J+Nim1GZkcQFxt7SjQFyjRIFOkh8DAQxEqRkLwLjoePm60e+\n+KrG12ckz8Aea7aHjuPugUN+BBkYx8D+3vL0bmDMe7bjA8GNSLFEqoI8Dcg0IxUR4UHogZDUiMWO\nLJ6TLUpm4Rnj0HAcH+hiSzAV6Zll9nwkEw226bC1Q3hFcXIkP1+hs4zyFJJywDqNvld0TiKMxivF\n/t1vi0uuWDN/EdnMJYSWMViCtrQDHK8N/qsM9zYhDXC+blhd1PRDQNk9fjfg9xGm9ZDJZDKZTCaT\nyWQymUwmk8lkMplMJpPJ5L9a3+mixWA8Q5mQznLOrWNocvJuYI/BJyk6L5gvNoRSc1rmrHOBiB3C\nOspUM58pTp7NWFxmbO8G6oeaauiJKpAYgR8FdduTbDo25xXpT1NEEehbj0MiZcYslGRe4wbwmUO/\nGKFrSXvPvgrU1lGNPVVX0x1bEqlYXyhOlwueX8xYLgIyGRj9ljG0GF8yKkNGAtYytIIuPvHpj2a0\nzz3hTLM75Dy8jZwPkX/4z19RHZ84med8+uoKUXh8UtG5I2qQhBSCFPS2ItGKxVmKnKUQBSeLkuAM\niAQXBI91w9wYRJlzDJ5eOBJS5iolNYZSaaIckHrk7E8sl39mWLwoyBqFHx2VUyil0EEge4n3kSQ1\nWKPptaCxDbfbEVWXNHc92wfHN7uO1qSkacLHL87JnqU07onH+5pmsLQLyTwRpDJgiKAiVbXlsIVU\nnPKDk2dcrZd4b3m9P2CLlL3QvHmMGC1YR4nOBVLCEDx2DHQN3O0EN0fJ7ZjROMvQWcZKsZaSZNQs\nVoqZlGRJJE8F0Wc8HS1Pjy3CC/7gx5+RtVe0bULTQVbC5tSh8BChrkY+vHvi/dsR7y0ff2RZfxZR\nc4fJGtIEirUgP+lQC0+YDyTGIroRHjXiMcGP4DoIdiRaCKlELQeqLiKfInkuGaXAHhVmLMj1Ap+k\nhDCg88DZrMQ5iXSap1tLV8847AbCYEjzhMRpmu3Ahy8OHB9GYgLZSqFnknD06FqzzNe8/D3P5k/u\nkGVNyAJRBryLrE8VpdK0aaATgsFJegGFtRDAy0hqFCUl1Srl9n3k62+OXL/u+cPf/xHV+IGb4x3v\nm46HfksrEsqY0Ox6vmyu0UnPYp1ymKd42WHbI03TciYScpOSqQTfCzrn8VYish3rcuQyz1gx481X\nA8exwfo7/HpAvxKYF3sy09FuK8LOoWJJPD/BnWWIMkEERXESebaJiC8anp4sfRtg0ByvJb0QLF5t\nWH40IxcDrn/HfjxCrqgHy25r2X8D6aFktTHMz2r05YryZs1JsuHgD8ihg+zbTs/JZDKZTCaTyWQy\nmUwmk8lkMplMJpPJZPK78p0uWqilp5gZcjWDPrBRjnU6Ym3HN76hUTNefvKMny5fcVIk0N/zdPsl\nITacXygWG0F5MZBfSeTpnOv/TbJ7iBhjKE8K+qNhfzeyLEAWnqD31HgIBULmRFKsz8lt5FyXeGWp\nn0fMZuD133zNGAUER55C0CnXN9eoHp7PTjFxiRrmPH39jrAcMQvI0hnWLdFdwm4MCNsgjUQtQDzu\nOF0qfiEcTTBs1n9INr7g1eWcD8mvSNOR1dmar95+xbG6I00j6/WCxYsVroH1WY5ZRcgtUXuQMMsS\nkiBQwuOsJ9lFnvYCayI6FwSpUFmOcYYkaqQKhFlH8rJm+KzGJkfSZmQT5uwHRacjMiaIKOl9x30/\nUkZo6o7tYaC6i9ibhJ88e8FC50g6but73neGzXLByWWB044gKyKW/a5hqD1qk3D+UY5QI7snwfEg\nQEA566m6b1DpS9ZFwsn8jJtuBgS++saTOI+aB8x1jTkVOGm5eQ+//IXkzdtANZ6yFzltCLjg0EYw\nK0pePF/z8vmC+YmgVjUfvnngHx4qqroh15GX5yvem4xPrz6hyNfIBMIyYLqWr7/6gsVJysX3z7h4\nfs4/+6Mf83T/c+rjG/b7CmEs6cyyuuiRqy02G2HR4p9VoBOGrWY8KmwvaCqLtTWj9HgCRgWWPxxp\n95r2UdLXYJTC1SvS8SP0GJDSUs4yFmcl27qher+n2QZUVvKjz59RfvqCUs7RXrI7PHD9879FBsHZ\nq0viUrJLPnDY3rGwks+fnfHx8zPyZ55lmYCKmFyRiUj7WNPUAjYKO0uwWYEPhtvZwMdbRzZ6pJYo\nAwfbsdWe1huKNOXF5Yz5VeDrL76gr6HJDEMdUOEZmRMY5anska/fHXj1TUr2JxvGoefxtmH72LC/\nnZPGltVyQZrk1I3HKI1SI6dXlo+uOuRww5und/j4FSxeo64OqBeS+U86UmNZ1JbxkNB1S47+ER87\nchsxych42hA/K5n9QYb9zYL+P+Y8/i34D4EXqyXp5RLTjNj7I4sfrEmyI1sneBwCrdTsfUJT7zlJ\nLSdjjeDIcr3kJ+F7xNN73uUfGKb1kMlkMplMJpPJZDKZTCaTyWQymUwmk8nkv1rf6aJF2taMXWDr\nHVF4GisYOs+b45aHSqCKJR+vnvNsc0JabAn6gec/PuDtgJSSfJ1jrjz2tEaOkc/yC5K/Lvj1v9vz\nv/9Nw1ysyC9WnGpB1CPbxFP0GXIswSdEmaHIoe6ZK4nPIqNuGJylV5E+GMJoyFROuSjRn/+A3b5h\nMIpvbkbKX3ZcPk8pTiR5klCSYewpmZ4jRMA6hbUCN3b09Vu+sjc8HnMWi4/Z/N7H2CNok0JjqLY9\njzNHomaszgZk0uCo2duO01crZiczvIkMwuGUx2QRl3XgR2SwhDGQSkXSawqfoZRhWaYMXqNGz0wF\nFrknXw/MX1n0eiTkgl0UbA89mRWkfkWKIciekUjhO7IkY/SSWZIxuyz5cB35u7+5JlQV3VDy7HTG\n9r5lf3/Ltoy0sxxzek0zVNTdyKNT1EPPUDaUSOpDxHqDShM6O7CX96gusFm84J9/+pzNU+Bv/tMt\n1fbIcTUy2Ih2CeMY+fK94psvHE+PEqlKMmXIas+LixOurjYkRuLanvP1DO8i3/yq52kHVTjl+r3i\n9MVLfvTjT3mx2fA//y//I3+dH7j66I9ITj9iy8DF6Yy3xwNm27C9W3KaLnh+uWH+kw35SU+5SDHG\nMx46slQhEolMHEnpOAw9x94xDIbgNCIkLNKEuTHYsiXMPGamSM8E5ouUpzeC9l1CFk5wTwsaqzhs\nHc5DSALffP2Ot6+vuTi7YP1sxtsPr/m3//4fmWUzzjYnnCyWKBdQOH7405eUy5dEn9LUl3zz+CuU\nzLB9x5sPb4nxN/zwU8ti4xlkQAWBrSNDqrCJohIOayO5S1DGclTQmfDbGRkrqdMBZMn62YLyn+U0\nN5oP2/9EWNaUmyXi/oR0u8LYZ9iqoh5rPqg9x6aGN44snRPMin4rUHcjSibI2YbG5uwZqOsjSnt+\n8GLJ5Yt75suv8WHJq39tcV91bO8qiuUDWTmwjpZUaroiYqUmLOA8X0Ol2YTfvtBh9UicBz5kLWFs\n2b+XJFlKXxQUxYbEpYRDZDhI9ocaMxzZqiBH0wAAIABJREFUj5Z3b+758u9+xbFJKctzytmc0Qf6\nXY9JwYQVl1cpl68cu9f1tx2fk8lkMplMJpPJZDKZTCaTyWQymUwmk8nkd+Q7XbTIB4sZjkjnUF4T\ng2UbYO88gx/woaXbv2PHlvOzA2ef3TCbPXF0Fa5PUKqFUkEiSaXBvpSUbzVZXhDQ9G7N5XLBPHcw\nPNLvKrJUY6VFeIOJhkTl5ELj44D0oGKgbVsOhwE9T1hfLQk2x/rI6XxJkpe4duTN+57DY83v/17k\nqhgZTeSoLL4NlL7FBwtRIqVAhhH0kerGUqhzxFnJ8PWB40OP9j3LImcwmvvHjjFE1itDPjdEORDS\nDvMywyQK4cE6i5aBYiZJ1xKCpe/2dMeGTgjk2Zq8VCRNiqgS0pgwWwvSmUduWsKFRZ7WHMct9n1D\nJh1GjFwtU3JT09pA50a8j2AjvgHfCaINJNpx8UnK3ngevjzSHRw6zpDeEcaBpw83XGs4GbeMsWdo\nI1FBlwket5E6WPZ3HukESRQcx5GZDCwSODu9YB1KUiM4rj2V0mT5lt4J1Jgy7ise3sD+Hrw1LNOC\ndT5jiIHTsmQ9zxmV5egCMwNtl5B1S87FGq8yzl9UUHQcqzMG8YJ2v4L5GW3YsNtnvAsdqzLl6uUF\n4ekt/njPvd3SH3Z89i87so2lOHfMTwbMkFB4RRIlxjiE8DglwAhsqsEvUNUCg2C9kIyzHW25xyaW\n0AdWq4T+TU5zm3M4zqkPKS5x9L4niJFh12G3IyJK3GagdTCGBt/ucSpwbCOBllxoghoxM/1/s3df\nubakeXren8+FX3b7s49JU2nKNqurRVAiCUEQKECAKN3oSkPQlcajAWgCupMAEYQc1WxbXV2dpjLz\n5LHbLL9W2M/ponoKhUo04jeEAOK9iQfxR+SO6ARlnvJi8oxT19A8bNnVLWpz5NXf1Tz9TFJqg04V\nvfZsouXQCgbjUJklqMjEgO0dQ4h0vaCVEVlGsijRCrIqIGYDaXhkcqnxrkHEJTcf3PDu19A2R9J0\nwMwF6VzStiXu4ZrjEfr3CVUrSBYX9I2hXQ+EIjK5rnj2ceTicmB29paksAy2oqp6npk1zz5oKZPA\nbFKTS0/SZWhliIUmINEzxzxJmTclmfUEMRAHyZEtJhvQc0mxzJH9hK5p2L4LCAP5pSImAmcG3Eky\nbH9/fmi/vqMVkYX1pDrgJlMmt54sL5gte6rpChhDi9FoNBqNRqPRaDQajUaj0Wg0Go1Go9Hon6of\ndGgR9j1xH/C1p/EZMSpaCSLRaKFp9yd2dye8i8x/eSS7PZDrms72JK4k9h3BBlSdUJASy5RyDtO5\nIZ1o1neWiyHiW43cJaiNJCwjKEfUjsG2eLsh94bG9ah+4DRY1ltLOnU8+alGngT1veLue6gPHqsF\nUhqCiHROUi4qormnizWd67HdgLQRl/SIyqKTgB88b/cnhsc5aX9D6zT7zWsGH+jrBpkbpNQcDgNp\nPsPIQJFZdKHwZSQmJ1yIyGjIBUgRKaQnzQUuOhp/4qC2uEIzO58Tdorhe4ncwsWgeHKj0S8s3fNI\nf+6IqmW/ati/7cik4Pp5AlWGMpah64nCYxJFDAolFYKAwKMTS3khsNGxfQR752m3EX+0RGe5Xx+J\nruNy6Iilp3cKXQhAMvRQzjVDJ1ExQUbwoacvLWdPBuZnDZk74EPC55uUx33JIA+cusiwUtSdo3kt\niUeNCZppIvh4ppG6oZpsMGlDYxw6dEi143r5GT++/jmp+YT//a8Gsps1D+4Nj1Zw1hjObv8T0o+W\nxPSK+pgiW8nPph/y4mPJ/q7nmy9/w5s3HffrA+a7AWcsycRyfQZFpjCtJG8VqUuRKpIqQZ4oapFj\n0xmIKSoE6CEmNT4TWAKmlMwWing2wRYz7h9T1lbS6BMi7RG+Z3+wpC1cXiyIytH0FqNhPj+D3BB0\n5OQ7vEhI5wWdd9jhiEg1xTLh9uw5718/sFm/4zjUzKJh+16wOEs5LiJeO6wO2KLj7gFCbZmdOYqp\nJacgekfTwb6TtAmUQiOHiPQeKTqi7MiLI2mV0DWBJLFMqhLTKXCWPXckQXBV3NA2mrtvPesVmOOU\norigT+YcO4+vaqY3miefpzz7uGZSOLTaEUONFgnzqWWmA0Z4tIjgFTJKQg/BAEIiRcTLli5R9EGg\nkNCniNPv46tzY/E3nuNnlp2MDN807DcWGz12uuX20yP52UB0Bmrw28Dp+EiR5fT9hAED8zP8dEfM\nC0QaEUb9sadzNBqNRqPRaDQajUaj0Wg0Go1Go9FoNBr9Af2gQ4v9XUd9LzjdwEE6knSCly1FoslC\nwv1dzfHBcPZMomctrthzOg70J4NKFLL3yC5gtKUS0FWKMoGs8ITE826/Qr8+MSkmXJ0F8uc5CEda\nCVwcaPo1tncYW+FbhfeWh7pjf/K8+KWmTDPCNmP9Rc5xlfCbv6/pleX6vOLm5oyby4zP/9Ml3bIn\nJg2qA20KpmlJnGm6ckcrOupN5OV3mrPmA9o3l+xeetpmRTIx1P6IPUpsn0PMuXz6lEJHCtlTZD0h\n9xzqhtYKyqRgkiWkWqC9Iw6WITa0Q8O+b5gvZpx9mtO9MuzeeSSBtJdMM0v2rMd/1hAmA50L9OuE\n09FjjcLoKU7lNL4joDGpIMkEShtIFDiPtxIHHI4N99uWgxX0PqfeBGL3+z9t7PuG901NsfecLzQm\nieSFxmQJUkcW84pJWWCdwNoeUZ6oPh5YvIhMyg2qlSxFxXM5xb21PKwcp1OEjeL0aKBOyGxCVJpS\nBSZJS75YkU571ESQVgp95ujCwOfPPueXn/yCRP2ML9+943fnoLQjhp5eWp5d/AuOs0jtNFko+WU8\n499+8jmffVzx/f63VAuH/7Xl7o3g278/EDvD0+uCSWqglHRIpNUUMaXSBQk93hmawdBvEoYHgdtH\n9tIxnFvsU4d5ElncGArnyV8oTFcx+IJ3u8i+WZOoSIFGCbi8mjMpE4gBMQTmumQxu+RIS60HPIro\nKy4uLyBEguzIFgmTJyUXNxecHiL4Iy52KJMSw5zhcGKzOXDUA0khmFw5mi96bBsoa0f+LFCScTp6\nmoOg8ZGYgO9yXB1xrUMODut3aN3Q1EdsO6U/NBzeH9H9DWUoeHfY0nLiSVnR1Jav1+/oYst1taQ3\nS+5OHp+XnF/m3P405+ZHe3TeM80kw7HneNgh8VxcZchM0eLopUPHDEtEKMeht6wPcHKSIhhOcmDQ\nG2aZQdsS0ydkLPggE1w8O7GWgXeq4d1BsH/ZsXm35869Y7hdc/MpxFASOo07SE5smVZPKWxOOeSE\nVU37eIc6VzSuxsXujz2do9FoNBqNRqPRaDQajUaj0Wg0Go1Go9HoD+gHHVpst4J9YzhXIIpAarZ0\nR4c9SYZ9xnFf4Ug4P7+irGAQDYNM2fcJh0ExaQxL45AXPfu2Y72v2T8KojWcXaXc7nKss3zzcs10\nanj+cU4x7OgfPZ6eRWW4OUvwqwGkYq8jeiK5qkBfRIIQ5MWM63BDf6/4u79+RxSSyhTMdEE4DfyH\n/+0bPvo3O8onNUVZcJ6ds+scjoFvXzZ8992W/p3mTPwLzObHNF8Y9q8afOxwTYPIBcFFoo9UVUKq\nNKbTiC5HREuWWpou0HQdWaIpyoxZlmCKwMFv6H0gDILuIClvc8q54fi65eAt2UQzqCNb01HJhkJ1\nTLQjdYF1knB7mzDJU1KV8fbrHZtdjRs8VQmX15LZoiAMjrfvG16/bhFSEtqMd68DxzcWt4+EiSbP\nCx53lm03cDwM2HcwV57pBM4mJZdnl5xfLOlWgrbT2L1H647lzzKKi3ecWNPimZeSaZrw/Max/a3l\n9FXA7Q3uTUW6kagyRxcJWkmutKM57pjOenTuGVJPm/dML+HZLXz+qebJdULfBP7l/7hk9/91DKFC\nZzuwK64rg9Az8u0Nn/kP+Le3T/jxvCZZvuXy2T0/u+2x15bj/5pgDxNKu6DoZuhGIJcC7zStdsTO\nYkPAKYUXhiyW+Gjojj3vf2sR2YAUkD7R6HxATzx6XpNeHzkPC5psQbNLaf7DGW6z48LAB9MJeTmh\nOTScHk4YNJeza/RQISpPLAd8X7DYPuOji0t89Qr75A35pw1XH5cYOfAm0SwWZwgZsH4Np5zVw54u\ng+lUcv7MQ6qoZKDeeGgE0hrilSWcIqKDRIIOAnkyeBvZrA64Y0uaepZXBS/fNLx5bbn7YsX2b75F\nPUwQc8NldoUfBK+/fMBRkmrJ+fkFqU756u1rrEn44NOnVJeaogJ/apFTS+gNnfd0uichEg+K1XCk\nT1PSSUpaBhoxULaK9mXk7Ree9w8102dP+flPBUO15jE5cHblEasF6phjhhSf74nPWxZmwrt3ju27\nnvpUUzWRN38N9SEwvTYIPWG+mDNpBrIsYV7MeZKd4cuer1aPnLL39M2A6/Z/7OkcjUaj0Wg0Go1G\no9FoNBqNRqPRaDQajUZ/QD/o0KLXBb97aVlNOqafGj67yZiUgcKVHCnxUSDTGdP8jFJJhO/owiMH\nFXCtQg+KtIHkFFE64UWhSaeC48wRXnWoxCNcxAlBPUjqnUb2CfWxJ5pAeeFQWSQWYFWCMIpMa4Qs\n6XYDdQfdMKD2LTrN+OBFxuNW8exixvOnJZvjI//Xv/+W46zj+SdwnkuG2HI6DrSmYb9LGL75kONv\nrli9uURKxWyy5Meff0hWRt58/x0rv0GWA9NFzsUyQ+HwzYCeS8o0QyYprm4xmUQVEZ9YOunoREcb\njgzWEk+S5FFTfFaiT57lVJD8WKFPkBwGwqynMzXhcKRtOzYbT2ivWZbnlEnGad8TbCQVKV3X8nbV\n8/plxKQdzjq6OhJCSVIkxJgS/UBw0PeRuj1xVAqkppo8Jc81WMiDJqoTdSfZ3ivyHjIBstYoW6LN\nAnnXUB56qg+3GJWCiyhTMxEpV594jr1geKuxNkMagVIpNlMkqeIsL3nyec7seUG86OmLSKckQ+GZ\nnOdMloY0PUDU/OrHktffarKvIrs7T51Y+mGNSc75TM35588rPrhu6K//HTr/a3z6Cs4aqg8nlGcF\n9l3kRl3wpF+g744c5InBKIIyhHmGSCSDPREcqBCZphJxnrGbRg7eQ6/JfcWkyJiZgWQB1nbE8Egh\nJU+GOfZC8dga/NCxkgeKqNAzyWJ5xkItmMortl1A54E8idRbzem9YvGThLN/niA/HrDTe6xdUW9e\ncTarWM0j28YhtWZRnFMlAlO/ge/W2KNg7wPF2wlFN4ETfP32xPtLiTQSOfeYpUSLnOa9xbiMEEuS\nRcVkAd7X9DWELkOVFfpDSV++pZV39KzAtxytpUxSZucFs7Oc6OEQBhw10SRICrAn+sOWnX8kvaxw\nxmOjoBGCY+g56QGrJERF7AKhbsl+J2lfSeqXkv1rePj6QPnScP0rxeyTDEEA2zH4jkwNmEJhVCBK\nS/VEUz1XxCLFmIDrJPZ1SXda0rdTXJ2QGEWZzpEhx/uIsJ5USTbHO7aPR7aHAzD7Y8/naDQajUaj\n0Wg0Go1Go9FoNBqNRqPRaDT6A/lBhxaL6ycsrxymWtGojpftQHEc6H7nef2F5dDMmM4Vd4+e6qWi\nTA3HxHOIljSx2JhTW0kjI5aOvo3UVhGigODx3UCIEqs1zuf4/pzHdUvbWbJlJAc2SqDPBUfrsURs\nJ+keJL7JUHJC3YLb7LFty4srw48/OefiskIox7o+EWPLfmU5nXlUcWLdvUcoODSWzeuc5uUZfvUh\nqztBm/Y8yVqUl2w2DQ/7DR0tMtEINTD4HYU/4/LZFXq6Z396Rx32eOPJzjUh8zR0EDU29HgDtpeI\nLqNoNdk+o6whzzzZ0tIHj48Bnzs666k3lt52vH3tcOstV4Xi6nyByQz2JNnuOrangbqPdDYwdAMh\nBBKdkOUprleELrB/E/GNJstyoiloVEZaGFybQZdhhhR9ktjhgA4KHxQPW0ueW3TdYWJJ4SZUmwL7\nKNnuI9NFQ0mFcRlJIplngbPbgPxEEbcl9aFiS0AUGYXJqKTm6UcZV7+MnIqa96eOehuxbzzHtxn/\n8MXA68VvMdcJk2rJz65Slvszfnfv+cruoAvMupJrXXA2a0mevSe7+BJpHrGx5eQCWxvpneP67JJP\nzq/4eDKjLBIe04EtjiOB2ge6JiCspUBjSNB5RD6RTB8Md696xBBZhpJCCPSpwUQHecDMjijrKecH\nqoViu+pppMXOU2weyDJDqg2p0WSF4UzkuDRyv7P0AhZPNVf/laT8+BX66nusWLF/dNiT4fbTz5jd\nXHP5XcVv/6blzXdrri1c6SXBR95+s0I6yWR2xfzqBW0vePMPr/j28R3n15Lbi4TZeYLtJN99caB7\ndCxuFzz/kwvKJxNO6w2pSNDeoJiipwnt0NC5A/ge5QJWWdqsJa8q0szgu4Ek6VneplydB1y7Zv12\nxfnNjmkVqO2efQwcAIwg9h5FwMaOYbD4TmDWMDxEhpWk3UsOB2i85U1jSaeQXEfk04FFMsE/BmoZ\nObrIMQpi7AkK0mlGYEISCmZFQdFpdt8kvNtueDgeCR/muNhw6g6sXItnxW6y565fsW8bjr1lDC1G\no9FoNBqNRqPRaDQajUaj0Wg0Go1Go3+6ftChRV4mTJcZZt5wSizb3nNYRdrvLNuHhCBTuuD47tUO\nlbZcHwfsUw8XHSrVDEqxtxkRw5EWexiIMcFkKUWqsV2H0AojS3Rc0B9nHLYJooio0rHOPCsPiQXv\nBlQtiXea7pVB2JwoFZ4eGR3lLOPyfMrZ0qGKLQdbM1EHXpwEUnisc5A7YuEQqaHfKoa2wq7P6dYz\n+nhiyB27sMWt17hjzdDVCAFEgVUNtQicpUuySUUnOzYnyynWXHxQIucBLyy9gxgCXQjIJMFLiQwJ\neQ9ylVE8ATnpkeU/fuwuDN5L+lZy2MJm67l/F+nuarZacbyRXN1MGXpB/ehp+kAvFaiU1BRkWUZV\n5aSJJNgBqSTiaYofBF1jeNhJlBTkbopQM5yYokJFUkZcuyaVEeE9jV0TQyCVji6CDYpin/P4D5Lq\nhaKZeGzekwWHQnAuIV55Fj+zNINm/eWE7X7AqZRsesbzy3Oubw3VVU8jTtidZXiVIb/OGA6C11jc\nxT35x79hWi44c0+YB8XSd1w0kvYI59Fx/bxm+uQBd/2XmPJL7GmDI9KdEjaPIINkPpmyKAsqpUlR\nTIylHg6E0NE7j+oEiZcQNUJ5pPboRUJyHXF3llCDfcwQ7zOc0KTFgKEjzQfyxZrueo1+n6C3CeJk\n6FNFWnn0WSRfWKaXDTdPGqpkwmoXOf7G0TvH4rZF/vJ7QvEVZG9gaJE4zi9yjLnnQifoRcb9quPh\n7ZHHexBIUplweJBUpkKLKWY65eQMtWvZtDVlcIRKwFwSTpH0iYEkQV8b/FzTJBqfTlmcT+nWhn5X\n4kXFyXuyeEYqp2hjac0JLxS2jchSkmhFkTsubzLKvCO4I+3hxDAdsLWnDR2HFI5G4gSQRi60JDcB\nVwcOL6H/OiJXhnCSnJxhUIGhtdw/RBavJNN7T7xyONnSJ+DDwOAifS+wDzWuA20K8rIk8YJSlagH\nOL3veTwcOSSSPETauubQNiQ+wauekx/Yx4FNsNTB/5GXczQajUaj0Wg0Go1Go9FoNBqNRqPRaDQa\n/SH9oEML507EaDAyUghJ6yL6mCD7BJsssbM5m1PH8NAy7Fv239dc/RSq/wISE7GJYxAB7VNaBsJg\nyFRCNc2YLRRRDQiVURYX5PKCehOJakp5bQnXHauqYTe0xLeCST9Q3CnkK4W916SmYts1pBeCsxcJ\nsyeCp5c9od1iZYPJLRcfRcS5YPUlCARmCvPzQBMEppuQcUt9vGR3F/HTwHQpQRyo9w26dZS5IgaF\ncx7XB3yiiHpgsxuwSY9PBFmZUywyarkFIQlA03usUIioiCSEEJEd2I1CN6ALR1ZYzMTQOc3xTnC6\nT3l4l3L3JqGpIRwLvMjoB8d2dyRPNTpW5MqiMkM2nXB+vqQoK6ZVhrQ9h8ctWVpy+yKw2Trefm8x\nHdxOKmT/lMA1fT2ne0whrZHNBOUGvO3oOoNgixIDrfM0Q8+mFci/yLj6ScHpynIqHFW2wQ0VSykp\ny8jmRcM7F9i+STlu4aEJLK8LPv7Zj7i86tnymlOA4TRFfPmE4u+usOuOUN4z7GvccceqX7Et3+Os\nIHaKD0NO00uu0iO3T18y+fw1w/z/prevaA97vFKIeopbS3KVI4yiVZ6d7ZCHE8Owxdo13rdEL0jI\nMQhiFwm6JqgGbwq6XCDLQLdW1N+k2HJOPq+QFy0yP1IlO8SyofMH0neRM3tJcbjE9hlSKEgHig/h\nyZ8GfvyZYRYTvnopOGpL9WFg8fHAKvmCM/c9nFpsLQhNyuWzc2r/SB1qxHLC7c8kscv49tsT371s\nUO6EiZpsvmC18byu19QhxTrDZPaCbLaG/EiX9oQ88pP/dkJi5zQ2oXY9q26gTErOn13CqcRuE9yD\nIVkFrs9fMC0ShrDnofme+lgTB0e21FRLGASYtKHta/IkYkyC7Q2P9w2UEV9KvIIDnuypQFeSKjf4\ng+DV3/e8/H9qUjUhqzRWpYTU0u87Nr3ksJc0bwV97vherukLSFNFYQXqJOlfdQhXYbRCJhLjBXbb\n0L0xdNtIRCKzlNALrJUMzuBUjjAlShcgE1o66gjJH3s8R6PRaDQajUaj0Wg0Go1Go9FoNBqNRqPR\nH8wPOrRYLHKuLhRlEWnagWGwyKCwPkPHijpRvOoszkceHmvu7ho+d/D5MkP8POInPaGwqCKFV5Zh\n1xI2HbZT5MU5l+eGx5NCZWek+YwgeuZXt3C7oz1bEytPoi08GNb/ETbfCLLakJuKrFyQqYT5haO6\n7ui5RwTHtHQ0xYnWtDgfyD9T3NY59tTz+H3H3SoyZAX93Rz7akn3TrMfVpjSMikhB+zRc9qfaEJg\nWp2jlCbkkawSnIY1zb2mWCjmz67RZ3B4fEOX1eQJGOFIREFiJmw7S1sHuj7Su0jeGlxMMMqiEwca\nhtgi5Iz+OKF+kPjTBDU4FhfXmDxlu93zxV/ekXrFP/+TGZc/qkhvcvJ5RqZS7u9WdBuPaB37hz2x\nM/y/f7/l7XbLfH7Dv/r5f8d//5//15jmhlVj+f7+wMuvDnyx+1vmVzfczAuqTHFsGr7+6q85vDsR\n+oY+WI5qwN1rfvPvFUo7ij8TmAUse48LHhklmZFwXrNxD5zsJbU07B1sD46Pfjmn91vyoSezivZe\nEH4Dx/2B/fUjXFomixzXpnz39jXT3PLh0zkfPf+Aq7NP8dOEY/EVu+4vyXavOQ6OIXqiKciVoXKR\n77ueWQ71uWJ/m5FdlrSJQzCQ+4AcBLQ1fgCBRhuFjD1DU7Opt3RiSWdnNIcCX19y8XFJUZ0QZk1Q\nmkJaVouWyZnjOql4kvyU1P2UP//bl6y/f0k3q0k+/seTOv17bpdnvPhvpvgkYeOOfL/9Ar/bE4cc\nEWYkpsJuSk62pp48IhZHnnx+wdVsiZnn/O1fvOXV2540ixjpiXXNetezbxWVTPjlLxcsykCSOEgt\nInFYFLbZ4QZNIhRZpkiNR8kZ1YcV2b3g8H868jcp/+Y/+9fMbgq+efMl3d8e6N86bj7I+OC8IL9u\ncARs09BaSbQSnQvSpCIWho4jp1c97aNHhMiTnwiKa0M2TzD3nmHt6AZJrxNQFUEbjs6yd56YSboy\n4X478Ph/1HSF5PpHmmQZcFFg1xH7oCiKghg07bEj1B2b9ZbBphwyQ20Eh9xi5p6zJqNszqh0gahW\niOUU7Qw+CHz4Yy/naDQajUaj0Wg0Go1Go9FoNBqNRqPRaDT6Q/pBhxbB14SdAQGJTkmVZPakYHn9\nIZuX1xz+vIV3LUPbYeQEPT0npDn3v3lkMhyRz/eo8wFlHPnOk8Q5rVOsHwTvv3Ncf/ojfj55TkUg\njVucqSk+qUkuD5xPAoMq2A8KJwQxpKw7yf2Dpq17lvOOTz6dMl96FjcKZQaaZg+nFFyBmSXIpCe8\nFaweBOs7x7YT1F6SSk23USSvLdF3pEmgSCHtQfcO0UfKsiDmkJUlsoiEzKJST4wDQUYGC4U3FOmU\n/ftIMUvIYkdiapIMBmGIURClIRiFTRxNjDS9R3YOLywoDcJDH6m3gf1O43wBScqhl7g2giz59J99\nxCdP5sh+g0kFiRK4fqAXgdBbuk2DaCBlianm/OJXv+Dj+AwVntCcJP/T//y/8MR9wq9+9Sf82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GEMgDIiKIMEgx9wI2BF0hCCHhnzhOiB3PPufsc/Y5e1xjz9VVdR98rwX/v53YGWwD/Xmr1VX9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\nukL6NU5Mcf0SNfJwgYO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SEzWDVKK8mjbL0NZQND7J+pjVm1fwtluEstigRteaWrRYqSlM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6UKoajS9BV6nRxKWKIkDaFFFfyWSWdGpTNj4NQNYsciiyzSUAM0Ql/BsWU8RyWNLZLEIvJ0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\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EB0POq2bHr8drvrR3HJiUk2TO2F8hvGOUmttx5PHiZxTWYHRL6y/J2NCzwncZmZ5QkQP2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\n+f8Dw3IVkGLgh2EAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from IPython.display import Image, display\n",
+    "Image('images/15_style_transfer_flowchart.png')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "xu2SVpFJjmJr"
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import PIL.Image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.11.0rc0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## VGG-16 Model\n",
+    "\n",
+    "After having spent 2 days trying to get the style-transfer algorithm to work with the Inception 5h model that we used for DeepDreaming in Tutorial #14, I could not produce images that looked any good. This seems strange because the images that were produced in Tutorial #14 looked quite nice. But recall that we also used a few tricks to achieve that quality, such as smoothing the gradient and recursively downscaling and processing the image.\n",
+    "\n",
+    "The [original paper](https://arxiv.org/abs/1508.06576) on style transfer used the VGG-19 convolutional neural network. But the pre-trained VGG-19 models for TensorFlow did not seem suitable for this tutorial for different reasons. Instead we will use the VGG-16 model, which someone else has made available and which can easily be loaded in TensorFlow. We have wrapped it in a class for convenience."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import vgg16"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The VGG-16 model is downloaded from the internet. This is the default directory where you want to save the data-files. The directory will be created if it does not exist."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# vgg16.data_dir = 'vgg16/'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download the data for the VGG-16 model if it doesn't already exist in the directory.\n",
+    "\n",
+    "**WARNING: It is 550 MB!**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading VGG16 Model ...\n",
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "vgg16.maybe_download()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "Nv2JqNLBhy1j"
+   },
+   "source": [
+    "## Helper-functions for image manipulation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function loads an image and returns it as a numpy array of floating-points. The image can be automatically resized so the largest of the height or width equals `max_size`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def load_image(filename, max_size=None):\n",
+    "    image = PIL.Image.open(filename)\n",
+    "\n",
+    "    if max_size is not None:\n",
+    "        # Calculate the appropriate rescale-factor for\n",
+    "        # ensuring a max height and width, while keeping\n",
+    "        # the proportion between them.\n",
+    "        factor = max_size / np.max(image.size)\n",
+    "    \n",
+    "        # Scale the image's height and width.\n",
+    "        size = np.array(image.size) * factor\n",
+    "\n",
+    "        # The size is now floating-point because it was scaled.\n",
+    "        # But PIL requires the size to be integers.\n",
+    "        size = size.astype(int)\n",
+    "\n",
+    "        # Resize the image.\n",
+    "        image = image.resize(size, PIL.Image.LANCZOS)\n",
+    "\n",
+    "    # Convert to numpy floating-point array.\n",
+    "    return np.float32(image)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Save an image as a jpeg-file. The image is given as a numpy array with pixel-values between 0 and 255."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def save_image(image, filename):\n",
+    "    # Ensure the pixel-values are between 0 and 255.\n",
+    "    image = np.clip(image, 0.0, 255.0)\n",
+    "    \n",
+    "    # Convert to bytes.\n",
+    "    image = image.astype(np.uint8)\n",
+    "    \n",
+    "    # Write the image-file in jpeg-format.\n",
+    "    with open(filename, 'wb') as file:\n",
+    "        PIL.Image.fromarray(image).save(file, 'jpeg')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function plots a large image. The image is given as a numpy array with pixel-values between 0 and 255."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_image_big(image):\n",
+    "    # Ensure the pixel-values are between 0 and 255.\n",
+    "    image = np.clip(image, 0.0, 255.0)\n",
+    "\n",
+    "    # Convert pixels to bytes.\n",
+    "    image = image.astype(np.uint8)\n",
+    "\n",
+    "    # Convert to a PIL-image and display it.\n",
+    "    display(PIL.Image.fromarray(image))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function plots the content-, mixed- and style-images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(content_image, style_image, mixed_image):\n",
+    "    # Create figure with sub-plots.\n",
+    "    fig, axes = plt.subplots(1, 3, figsize=(10, 10))\n",
+    "\n",
+    "    # Adjust vertical spacing.\n",
+    "    fig.subplots_adjust(hspace=0.1, wspace=0.1)\n",
+    "\n",
+    "    # Use interpolation to smooth pixels?\n",
+    "    smooth = True\n",
+    "    \n",
+    "    # Interpolation type.\n",
+    "    if smooth:\n",
+    "        interpolation = 'sinc'\n",
+    "    else:\n",
+    "        interpolation = 'nearest'\n",
+    "\n",
+    "    # Plot the content-image.\n",
+    "    # Note that the pixel-values are normalized to\n",
+    "    # the [0.0, 1.0] range by dividing with 255.\n",
+    "    ax = axes.flat[0]\n",
+    "    ax.imshow(content_image / 255.0, interpolation=interpolation)\n",
+    "    ax.set_xlabel(\"Content\")\n",
+    "\n",
+    "    # Plot the mixed-image.\n",
+    "    ax = axes.flat[1]\n",
+    "    ax.imshow(mixed_image / 255.0, interpolation=interpolation)\n",
+    "    ax.set_xlabel(\"Mixed\")\n",
+    "\n",
+    "    # Plot the style-image\n",
+    "    ax = axes.flat[2]\n",
+    "    ax.imshow(style_image / 255.0, interpolation=interpolation)\n",
+    "    ax.set_xlabel(\"Style\")\n",
+    "\n",
+    "    # Remove ticks from all the plots.\n",
+    "    for ax in axes.flat:\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Loss Functions\n",
+    "\n",
+    "These helper-functions create the loss-functions that are used in optimization with TensorFlow.\n",
+    "\n",
+    "This function creates a TensorFlow operation for calculating the Mean Squared Error between the two input tensors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def mean_squared_error(a, b):\n",
+    "    return tf.reduce_mean(tf.square(a - b))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function creates the loss-function for the content-image. It is the Mean Squared Error of the feature activations in the given layers in the model, between the content-image and the mixed-image. When this content-loss is minimized, it therefore means that the mixed-image has feature activations in the given layers that are very similar to the activations of the content-image. Depending on which layers you select, this should transfer the contours from the content-image to the mixed-image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def create_content_loss(session, model, content_image, layer_ids):\n",
+    "    \"\"\"\n",
+    "    Create the loss-function for the content-image.\n",
+    "    \n",
+    "    Parameters:\n",
+    "    session: An open TensorFlow session for running the model's graph.\n",
+    "    model: The model, e.g. an instance of the VGG16-class.\n",
+    "    content_image: Numpy float array with the content-image.\n",
+    "    layer_ids: List of integer id's for the layers to use in the model.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Create a feed-dict with the content-image.\n",
+    "    feed_dict = model.create_feed_dict(image=content_image)\n",
+    "\n",
+    "    # Get references to the tensors for the given layers.\n",
+    "    layers = model.get_layer_tensors(layer_ids)\n",
+    "\n",
+    "    # Calculate the output values of those layers when\n",
+    "    # feeding the content-image to the model.\n",
+    "    values = session.run(layers, feed_dict=feed_dict)\n",
+    "\n",
+    "    # Set the model's graph as the default so we can add\n",
+    "    # computational nodes to it. It is not always clear\n",
+    "    # when this is necessary in TensorFlow, but if you\n",
+    "    # want to re-use this code then it may be necessary.\n",
+    "    with model.graph.as_default():\n",
+    "        # Initialize an empty list of loss-functions.\n",
+    "        layer_losses = []\n",
+    "    \n",
+    "        # For each layer and its corresponding values\n",
+    "        # for the content-image.\n",
+    "        for value, layer in zip(values, layers):\n",
+    "            # These are the values that are calculated\n",
+    "            # for this layer in the model when inputting\n",
+    "            # the content-image. Wrap it to ensure it\n",
+    "            # is a const - although this may be done\n",
+    "            # automatically by TensorFlow.\n",
+    "            value_const = tf.constant(value)\n",
+    "\n",
+    "            # The loss-function for this layer is the\n",
+    "            # Mean Squared Error between the layer-values\n",
+    "            # when inputting the content- and mixed-images.\n",
+    "            # Note that the mixed-image is not calculated\n",
+    "            # yet, we are merely creating the operations\n",
+    "            # for calculating the MSE between those two.\n",
+    "            loss = mean_squared_error(layer, value_const)\n",
+    "\n",
+    "            # Add the loss-function for this layer to the\n",
+    "            # list of loss-functions.\n",
+    "            layer_losses.append(loss)\n",
+    "\n",
+    "        # The combined loss for all layers is just the average.\n",
+    "        # The loss-functions could be weighted differently for\n",
+    "        # each layer. You can try it and see what happens.\n",
+    "        total_loss = tf.reduce_mean(layer_losses)\n",
+    "        \n",
+    "    return total_loss"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will do something similar for the style-layers, but now we want to measure which features in the style-layers activate simultaneously for the style-image, and then copy this activation-pattern to the mixed-image.\n",
+    "\n",
+    "One way of doing this, is to calculate the so-called Gram-matrix for the tensors output by the style-layers. The Gram-matrix is essentially just a matrix of dot-products for the vectors of the feature activations of a style-layer.\n",
+    "\n",
+    "If an entry in the Gram-matrix has a value close to zero then it means the two features in the given layer do not activate simultaneously for the given style-image. And vice versa, if an entry in the Gram-matrix has a large value, then it means the two features do activate simultaneously for the given style-image. We will then try and create a mixed-image that replicates this activation pattern of the style-image.\n",
+    "\n",
+    "This is the helper-function for calculating the Gram-matrix of a tensor output by a convolutional layer in the neural network. The actual loss-function is created further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def gram_matrix(tensor):\n",
+    "    shape = tensor.get_shape()\n",
+    "    \n",
+    "    # Get the number of feature channels for the input tensor,\n",
+    "    # which is assumed to be from a convolutional layer with 4-dim.\n",
+    "    num_channels = int(shape[3])\n",
+    "\n",
+    "    # Reshape the tensor so it is a 2-dim matrix. This essentially\n",
+    "    # flattens the contents of each feature-channel.\n",
+    "    matrix = tf.reshape(tensor, shape=[-1, num_channels])\n",
+    "    \n",
+    "    # Calculate the Gram-matrix as the matrix-product of\n",
+    "    # the 2-dim matrix with itself. This calculates the\n",
+    "    # dot-products of all combinations of the feature-channels.\n",
+    "    gram = tf.matmul(tf.transpose(matrix), matrix)\n",
+    "\n",
+    "    return gram                            "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The next function creates the loss-function for the style-image. It is quite similar to `create_content_loss()` above, except that we calculate the Mean Squared Error for the Gram-matrices instead of the raw tensor-outputs from the layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def create_style_loss(session, model, style_image, layer_ids):\n",
+    "    \"\"\"\n",
+    "    Create the loss-function for the style-image.\n",
+    "    \n",
+    "    Parameters:\n",
+    "    session: An open TensorFlow session for running the model's graph.\n",
+    "    model: The model, e.g. an instance of the VGG16-class.\n",
+    "    style_image: Numpy float array with the style-image.\n",
+    "    layer_ids: List of integer id's for the layers to use in the model.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Create a feed-dict with the style-image.\n",
+    "    feed_dict = model.create_feed_dict(image=style_image)\n",
+    "\n",
+    "    # Get references to the tensors for the given layers.\n",
+    "    layers = model.get_layer_tensors(layer_ids)\n",
+    "\n",
+    "    # Set the model's graph as the default so we can add\n",
+    "    # computational nodes to it. It is not always clear\n",
+    "    # when this is necessary in TensorFlow, but if you\n",
+    "    # want to re-use this code then it may be necessary.\n",
+    "    with model.graph.as_default():\n",
+    "        # Construct the TensorFlow-operations for calculating\n",
+    "        # the Gram-matrices for each of the layers.\n",
+    "        gram_layers = [gram_matrix(layer) for layer in layers]\n",
+    "\n",
+    "        # Calculate the values of those Gram-matrices when\n",
+    "        # feeding the style-image to the model.\n",
+    "        values = session.run(gram_layers, feed_dict=feed_dict)\n",
+    "\n",
+    "        # Initialize an empty list of loss-functions.\n",
+    "        layer_losses = []\n",
+    "    \n",
+    "        # For each Gram-matrix layer and its corresponding values.\n",
+    "        for value, gram_layer in zip(values, gram_layers):\n",
+    "            # These are the Gram-matrix values that are calculated\n",
+    "            # for this layer in the model when inputting the\n",
+    "            # style-image. Wrap it to ensure it is a const,\n",
+    "            # although this may be done automatically by TensorFlow.\n",
+    "            value_const = tf.constant(value)\n",
+    "\n",
+    "            # The loss-function for this layer is the\n",
+    "            # Mean Squared Error between the Gram-matrix values\n",
+    "            # for the content- and mixed-images.\n",
+    "            # Note that the mixed-image is not calculated\n",
+    "            # yet, we are merely creating the operations\n",
+    "            # for calculating the MSE between those two.\n",
+    "            loss = mean_squared_error(gram_layer, value_const)\n",
+    "\n",
+    "            # Add the loss-function for this layer to the\n",
+    "            # list of loss-functions.\n",
+    "            layer_losses.append(loss)\n",
+    "\n",
+    "        # The combined loss for all layers is just the average.\n",
+    "        # The loss-functions could be weighted differently for\n",
+    "        # each layer. You can try it and see what happens.\n",
+    "        total_loss = tf.reduce_mean(layer_losses)\n",
+    "        \n",
+    "    return total_loss"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This creates the loss-function for denoising the mixed-image. The algorithm is called [Total Variation Denoising](https://en.wikipedia.org/wiki/Total_variation_denoising) and essentially just shifts the image one pixel in the x- and y-axis, calculates the difference from the original image, takes the absolute value to ensure the difference is a positive number, and sums over all the pixels in the image. This creates a loss-function that can be minimized so as to suppress some of the noise in the image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def create_denoise_loss(model):\n",
+    "    loss = tf.reduce_sum(tf.abs(model.input[:,1:,:,:] - model.input[:,:-1,:,:])) + \\\n",
+    "           tf.reduce_sum(tf.abs(model.input[:,:,1:,:] - model.input[:,:,:-1,:]))\n",
+    "\n",
+    "    return loss"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Style-Transfer Algorithm\n",
+    "\n",
+    "This is the main optimization algorithm for the Style-Transfer algorithm. It is basically just gradient descent on the loss-functions defined above.\n",
+    "\n",
+    "This algorithm also uses normalization of the loss-functions. This appears to be a novel idea not previously published. In each iteration of the optimization, the loss-values are adjusted so each of them equals one. This allows the user to set the loss-weights independently of the chosen style- and content-layers. It also adapts the weighting during optimization to ensure the desired ratio between style, content and denoising is preserved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def style_transfer(content_image, style_image,\n",
+    "                   content_layer_ids, style_layer_ids,\n",
+    "                   weight_content=1.5, weight_style=10.0,\n",
+    "                   weight_denoise=0.3,\n",
+    "                   num_iterations=120, step_size=10.0):\n",
+    "    \"\"\"\n",
+    "    Use gradient descent to find an image that minimizes the\n",
+    "    loss-functions of the content-layers and style-layers. This\n",
+    "    should result in a mixed-image that resembles the contours\n",
+    "    of the content-image, and resembles the colours and textures\n",
+    "    of the style-image.\n",
+    "    \n",
+    "    Parameters:\n",
+    "    content_image: Numpy 3-dim float-array with the content-image.\n",
+    "    style_image: Numpy 3-dim float-array with the style-image.\n",
+    "    content_layer_ids: List of integers identifying the content-layers.\n",
+    "    style_layer_ids: List of integers identifying the style-layers.\n",
+    "    weight_content: Weight for the content-loss-function.\n",
+    "    weight_style: Weight for the style-loss-function.\n",
+    "    weight_denoise: Weight for the denoising-loss-function.\n",
+    "    num_iterations: Number of optimization iterations to perform.\n",
+    "    step_size: Step-size for the gradient in each iteration.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Create an instance of the VGG16-model. This is done\n",
+    "    # in each call of this function, because we will add\n",
+    "    # operations to the graph so it can grow very large\n",
+    "    # and run out of RAM if we keep using the same instance.\n",
+    "    model = vgg16.VGG16()\n",
+    "\n",
+    "    # Create a TensorFlow-session.\n",
+    "    session = tf.InteractiveSession(graph=model.graph)\n",
+    "\n",
+    "    # Print the names of the content-layers.\n",
+    "    print(\"Content layers:\")\n",
+    "    print(model.get_layer_names(content_layer_ids))\n",
+    "    print()\n",
+    "\n",
+    "    # Print the names of the style-layers.\n",
+    "    print(\"Style layers:\")\n",
+    "    print(model.get_layer_names(style_layer_ids))\n",
+    "    print()\n",
+    "\n",
+    "    # Create the loss-function for the content-layers and -image.\n",
+    "    loss_content = create_content_loss(session=session,\n",
+    "                                       model=model,\n",
+    "                                       content_image=content_image,\n",
+    "                                       layer_ids=content_layer_ids)\n",
+    "\n",
+    "    # Create the loss-function for the style-layers and -image.\n",
+    "    loss_style = create_style_loss(session=session,\n",
+    "                                   model=model,\n",
+    "                                   style_image=style_image,\n",
+    "                                   layer_ids=style_layer_ids)    \n",
+    "\n",
+    "    # Create the loss-function for the denoising of the mixed-image.\n",
+    "    loss_denoise = create_denoise_loss(model)\n",
+    "\n",
+    "    # Create TensorFlow variables for adjusting the values of\n",
+    "    # the loss-functions. This is explained below.\n",
+    "    adj_content = tf.Variable(1e-10, name='adj_content')\n",
+    "    adj_style = tf.Variable(1e-10, name='adj_style')\n",
+    "    adj_denoise = tf.Variable(1e-10, name='adj_denoise')\n",
+    "\n",
+    "    # Initialize the adjustment values for the loss-functions.\n",
+    "    session.run([adj_content.initializer,\n",
+    "                 adj_style.initializer,\n",
+    "                 adj_denoise.initializer])\n",
+    "\n",
+    "    # Create TensorFlow operations for updating the adjustment values.\n",
+    "    # These are basically just the reciprocal values of the\n",
+    "    # loss-functions, with a small value 1e-10 added to avoid the\n",
+    "    # possibility of division by zero.\n",
+    "    update_adj_content = adj_content.assign(1.0 / (loss_content + 1e-10))\n",
+    "    update_adj_style = adj_style.assign(1.0 / (loss_style + 1e-10))\n",
+    "    update_adj_denoise = adj_denoise.assign(1.0 / (loss_denoise + 1e-10))\n",
+    "\n",
+    "    # This is the weighted loss-function that we will minimize\n",
+    "    # below in order to generate the mixed-image.\n",
+    "    # Because we multiply the loss-values with their reciprocal\n",
+    "    # adjustment values, we can use relative weights for the\n",
+    "    # loss-functions that are easier to select, as they are\n",
+    "    # independent of the exact choice of style- and content-layers.\n",
+    "    loss_combined = weight_content * adj_content * loss_content + \\\n",
+    "                    weight_style * adj_style * loss_style + \\\n",
+    "                    weight_denoise * adj_denoise * loss_denoise\n",
+    "\n",
+    "    # Use TensorFlow to get the mathematical function for the\n",
+    "    # gradient of the combined loss-function with regard to\n",
+    "    # the input image.\n",
+    "    gradient = tf.gradients(loss_combined, model.input)\n",
+    "\n",
+    "    # List of tensors that we will run in each optimization iteration.\n",
+    "    run_list = [gradient, update_adj_content, update_adj_style, \\\n",
+    "                update_adj_denoise]\n",
+    "\n",
+    "    # The mixed-image is initialized with random noise.\n",
+    "    # It is the same size as the content-image.\n",
+    "    mixed_image = np.random.rand(*content_image.shape) + 128\n",
+    "\n",
+    "    for i in range(num_iterations):\n",
+    "        # Create a feed-dict with the mixed-image.\n",
+    "        feed_dict = model.create_feed_dict(image=mixed_image)\n",
+    "\n",
+    "        # Use TensorFlow to calculate the value of the\n",
+    "        # gradient, as well as updating the adjustment values.\n",
+    "        grad, adj_content_val, adj_style_val, adj_denoise_val \\\n",
+    "        = session.run(run_list, feed_dict=feed_dict)\n",
+    "\n",
+    "        # Reduce the dimensionality of the gradient.\n",
+    "        grad = np.squeeze(grad)\n",
+    "\n",
+    "        # Scale the step-size according to the gradient-values.\n",
+    "        step_size_scaled = step_size / (np.std(grad) + 1e-8)\n",
+    "\n",
+    "        # Update the image by following the gradient.\n",
+    "        mixed_image -= grad * step_size_scaled\n",
+    "\n",
+    "        # Ensure the image has valid pixel-values between 0 and 255.\n",
+    "        mixed_image = np.clip(mixed_image, 0.0, 255.0)\n",
+    "\n",
+    "        # Print a little progress-indicator.\n",
+    "        print(\". \", end=\"\")\n",
+    "\n",
+    "        # Display status once every 10 iterations, and the last.\n",
+    "        if (i % 10 == 0) or (i == num_iterations - 1):\n",
+    "            print()\n",
+    "            print(\"Iteration:\", i)\n",
+    "\n",
+    "            # Print adjustment weights for loss-functions.\n",
+    "            msg = \"Weight Adj. for Content: {0:.2e}, Style: {1:.2e}, Denoise: {2:.2e}\"\n",
+    "            print(msg.format(adj_content_val, adj_style_val, adj_denoise_val))\n",
+    "\n",
+    "            # Plot the content-, style- and mixed-images.\n",
+    "            plot_images(content_image=content_image,\n",
+    "                        style_image=style_image,\n",
+    "                        mixed_image=mixed_image)\n",
+    "            \n",
+    "    print()\n",
+    "    print(\"Final image:\")\n",
+    "    plot_image_big(mixed_image)\n",
+    "\n",
+    "    # Close the TensorFlow session to release its resources.\n",
+    "    session.close()\n",
+    "    \n",
+    "    # Return the mixed-image.\n",
+    "    return mixed_image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example\n",
+    "\n",
+    "This example shows how to transfer the style of various images onto a portrait.\n",
+    "\n",
+    "First we load the content-image which has the overall contours that we want in the mixed-image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "content_filename = 'images/willy_wonka_old.jpg'\n",
+    "content_image = load_image(content_filename, max_size=None)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we load the style-image which has the colours and textures we want in the mixed-image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "style_filename = 'images/style7.jpg'\n",
+    "style_image = load_image(style_filename, max_size=300)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we define a list of integers which identify the layers in the neural network that we want to use for matching the content-image. These are indices into the layers in the neural network. For the VGG16 model, the 5th layer (index 4) seems to work well as the sole content-layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "content_layer_ids = [4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we define another list of integers for the style-layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# The VGG16-model has 13 convolutional layers.\n",
+    "# This selects all those layers as the style-layers.\n",
+    "# This is somewhat slow to optimize.\n",
+    "style_layer_ids = list(range(13))\n",
+    "\n",
+    "# You can also select a sub-set of the layers, e.g. like this:\n",
+    "# style_layer_ids = [1, 2, 3, 4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now perform the style-transfer. This automatically creates the appropriate loss-functions for the style- and content-layers, and then performs a number of optimization iterations. This will gradually create a mixed-image which has similar contours as the content-image, with the colours and textures being similar to the style-image.\n",
+    "\n",
+    "This can be very slow on a CPU!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Content layers:\n",
+      "['conv3_1/conv3_1']\n",
+      "\n",
+      "Style layers:\n",
+      "['conv1_1/conv1_1', 'conv1_2/conv1_2', 'conv2_1/conv2_1', 'conv2_2/conv2_2', 'conv3_1/conv3_1', 'conv3_2/conv3_2', 'conv3_3/conv3_3', 'conv4_1/conv4_1', 'conv4_2/conv4_2', 'conv4_3/conv4_3', 'conv5_1/conv5_1', 'conv5_2/conv5_2', 'conv5_3/conv5_3']\n",
+      "\n",
+      ". \n",
+      "Iteration: 0\n",
+      "Weight Adj. for Content: 5.18e-11, Style: 2.14e-29, Denoise: 5.61e-06\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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QMUNYxn6IEjOutmjMqCp7zYLl6oKqsaQyIKMqQAsUa3AVY9VEM5Vv6LolYLC2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hORyw4wqk2ObRJ0f4oWfzuifZHnPIKQz3yLY2UNtLdt56BnOnzwuvGfL1E0Kasujvk5yuKBbX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m6ppmdYWnrGo0OLygKtFwhlcW1JP+/TBM9Zdca4GjKvLFq1CBomi3263RMauwCnMOmQ8fQA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\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DZ+kR1tffZHrOURzGVH4O73uUeYUpPNnAQymJEs2FZyx7D1rcvjZk42pOEmu8y2kfn0Li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vGLf/8f0fjEAxZabW5v/zmDeJN7Ly1wsL/NV/5A8+G7PR77Dw555auGR164RHU2p5HcYJAGBLIk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76IAxBqWcD0jYPD1c383ncGh4gXT3ChKTGHTimqIwLKC1+9yluutfclkfvvSIbHKvuQyK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kWqIUFGYGY0cRZUSFZ4anIzzTWoOtiWBlLub6/oS15TomVyzOdZnOcqwIxnCkJNV1TJVYewTW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kmceVN3kKOLg3icZlSVx0AiJfe2hhijUaUyNomJKMyMQr9vwnu/2Hs/MnT//wEfp2Ehj1O0\n0pRKZdr1KUZ7uxyaXeTu5CLcWODZ5ecYpV3S/h2ChRkGq9uopWleunyNpfoJxmTcm5bUt3fJyhW0\nc7gCZ+olFz7jwArzQ9NqXYSOeYm9PZDLHCQ/O8tBFkJRmNr9TJDiTc4z3gv5glTgNMZkGA7eUQi0\nZhJPaDU0edxjuinIs10qkWJl5U3qlWkazTnOnlkky1KiSshoPKE5PcWoY6lWK+ztdqg3GqR5Trlc\nZrzYo9ffpV5r8MYbb3DiyFlW7t1ipjlNeWqTCzOHeeLxJ7l5ZZ1mM2R5eYYrq3/Kv/w/rrNcXeC5\nZz9L0Krz6PnP4Mav8s/+x/+WvcE9zpx/hFOnHyUTiqh2iEA5WvWQJM1QIqQ9W8HanGq9wb21y6zd\nGfKp5z7B9195gbtrV4izjCgM2dndY319nen2LMloQq0acef2Bhu9Xc48/DHevXGPwbDEf/XffIw/\n+OLvsFh/iJWdN6iUpg42BqLIW5Hc3xKYwtugtUeVGuvRpPevOXfw+b9PkHIejeSnyvvXoNjXuN9v\nJt7fdPrvd9+7sd/I3JdTeY2JlPe/B7zPCH3w7yikVzlah+QmL9CoYPOceljnxMI8TRHyWjygOvU4\nP39ojj965/eozS1hSH0hKlyxEfCgAiV8UvAHcfMktAAVOkTuqUrGZETVyEuolJcjYiGNU1QQFD4C\nfYCktcbL1mxeeFYE6FJQ5FA4wOKM8gW/VDjnCTtaaaz2CdYUU2+bp2ih/fezhVZEegmJw4BUaF2k\nWUuLLML4nMEPUoAs93r3IAhxeBS3Na6QSkmswONMtcJY0EgkssDxFsjRYkthKWhH+z404w0cUitC\n4bGoYDFZTi4EWgbkMi/SqKV/8zD+8RMCgkCSpjnWSMIii+XgDFPKP3ahIk9y/5rRAptaYpMWl606\nIFEZY3zuRNEUWiCMAtLUp1kL5yVOMvBvHZ4Y5s/NbD8NWwh0GGBMThSFZKnPH8oT45uTAKT2adgu\nL0zL1lOtcH7bZLGkaVogoX3ats0dOlSEUVhI5ixWWaIgQBRSMqRDh0EBUvCvsSzLfbOhPQo5niRY\nIwhCRaj9RilNE6QOfHqFlEjtmyZj/MZChP4x1FJgrKePWeudJqIYKFhjCZT0mTXWFVAwn33hyP35\nkxVnlKAAAWjyLCOMQtI09l9v8Y+p8fTFUAUoLVDanzFJ6reiUqhiQGX91aa8/DjL/JDESTA2J41T\n0sRvWFxBdQsLaILWXmqWJ57spqQiSQxJ8sEQ6s4+tMCdu1+h3s6YXapQmbZsvXuSt27d4uhKg8uX\n+oy2M9bWdtjeHfz/vL1plCXpXd75e5eIuHvue9a+dFVXV6vVm1rdWlusAoEMwgaBsDGDwZsGm7Hm\neGy2sQcwtvAMiwFbHhg8IIQAC4SW0d4ttXrvru7a96yq3PebebeIeBd/eCOzqmV/kM4cdL/UOZV5\nb2bGjYj7X57n+bF/6ghD5XHe/NjrWbh4g6SySnkw4tCI4uyFJUaHD1LiYdzaJIs3/oBO+Rr7Rk7Q\ns1uUkiXMRkwSJ2hTRZdGEek+yAe5fOMWD3f7Ga9eRtYPMnHgENtrbeJyzrHDj3J97iWGBh3Vcoqq\nXKUysoDub7LRSyGzZK0eYEBUyNoRudRUGiWSg2vUpnK6F1ZZ+dw2B0Y8j7ypxkR9lDOnO2xu1miN\nlJg9Pc+RKxW0LOGPblNNWuRZCxE/z2OP9mF7N7k6u4/6WD+XZ66wND/Nie+6Tm3IkWjQh9ZZWVvA\ndyrY1S5xDFFpFD18CSeGePiRv8upp25ysH+QA2PTTO45zMUrjpWbC6RLCd3uk6hSj4eO383/1/40\n7zj+BT536lN87A8uM6z+Pr/5ix8hjse5kv0uY2PDtNQLTB7y9GwXXakitaaeCLJGRsXX6SxLmu0b\n6CRHWk/ajXC6wujwIfoqdzN7/jrXOvMcmOpQrSVY38SqnO1sgb0jVQYnJ/DVlInxGldvbNFXa7Ce\n5izNL5D2KoyN9rOxvMx7f+jbeeqrL3P94hn2jB1kZGCcM+eeZXXtBvuO9yP1ECVZRrqbdLdrjL95\nD9MPRqy3Fhnfs03SP89EYy9nPrmCKQ1SG6zjxCjJyBpXF57j5NG34nybSlymNFxheXmEkf7HWLn1\nBMpa1tvzjA2NUR/WbLa3UBb6RvZw6sZXGFsc5mjeRxx10bJD7B2lpEzuBIglyqU2Uq5SKTUoy00a\nVUm1OkqrfZzW9Tdh/CSL2xe4tvlh3vm3y4zctYWSgo38eXLZZbT/AGudLhcvCVYW+rDrk2ytLLG+\ndJO+yh7e8MAwiwtX0HHK8EiH0clR0s48GyvXKcXHSXtLJFEZ2+vQWt9iaOwQPd2k2b1FV2TogUG6\nNiXvpVTjEjKKWO2usbm2RiUqUU2qjFeqX9d1/g01GloqQAejG5IsC6ClTAdPheqmSOnotDN0EjM/\n38T5GOcFOIMUMdYIvCoAXNJ/TbH2WjlLMNuGgj4zWYilROG7GSvNWxw9epyNxXlsNsqByQFe2jjL\ndDKCGx7GbK4xk3XZPn2OwVqFrVITLCSrEtU3RdZbAx3hbdBMi8Is6gtD4s7EeqcQdc4RKV0YJnc2\nMEVErbw9pVZKFelCRQHrwsbHuZ1tR0F+RRdFSohaDNKQUAC3NhVvf9M7uPvYw5x/5UWiuFTg4mF7\nfo5yOWGrtUUcR3R7Hfo3GihhWFjMUUrTbAlKpQre1+llOX0D/XS2OzzyyBtZXFrgkUce5dOf+RT9\npePc//r7WJyb49jRQ5w7d4HPfOozxDri3T/wONX+Q9TjKklnk2ef/N/57JPP85ZveQ/fdujvUqvU\nSbsr5HmLhkrYbLVoO4NWEciw/UniKjpKSEoHaXcdT37xi/z9v/eT/It/+QH275tiZXGRS1eWePiR\nN9NttSiVygipOXvuee49cS/Xz59jsyX4nQ/9Pv/sZ/8hplJjPvsqiRonULsD7TnExQaFXuABuNcU\n8wCI2+fWzqTvzn93v+2OhnfntLTO7pyIxXvv+e+ldfI1r7Hj0QkGZlWcT+wa018jm0LgfWC0hCep\nYsDtMHkOUZhseyuoqyqnm7f4ob7HaKzA1LFtvnz5Re7Z/zBXbl2hVdkiEoocg1bxbiPjsYUk66//\nkXZzfGZDII8r3hsviHSEweF9jkWgY4U1ECrmsMHRscajMG5nESWCOo5QJCaRCluJTgYiGG9xOxDE\ngowdhZQqpUNktrWePLeU4xhTNPZCaqzwOBEyyKMoeJ987vHKogqTsFYSrRVSKTIbNrjBlGzxXuCK\nJhcp8Fqi4gib5xhjg0mcIHmRIngarAtQN6TApJBnWfAXCIHzlrgUaPUUWxPnQzCGjhROhO0LdzAf\ndBzgfcaG6b11hVwNhy5pdhLN4lKEtR6TFX4yFbYjTgfp0g4sUhRhBVIFloTNslBsm7AhwBusCbA4\nZGhY8twET0Ac4QsPlCTwQZSWOC+xTgXTOB5nwrYoKSfFViIi7aZ47wM9e5fhIIIULApckjRNkYqw\nYbR5kSLlyFODKraDQoDQMjBO8iA9kzIwJnIbzN+4wL2wVqAVYUDhwOdFypsOMj2Ka1UXFHdvDKpa\nCjyWSIUBhysM4MKTxEWimHW7wQ54QZZmCFzgZ3iBlB6TW7y3yEgHaWAkEC5sTKz1CKlwLqRP6bhg\neeyA+kRIKAvNjCpOiUKa5sO9RypVkMTD/ykZQhPAk/YMuQ0wQu1AxzG5y5BehmuLnKj6zYm3ff65\nL7DvpObcTJUhXWd97Sz16l4uXNhg4YZgu7MHk1tSs8G+A4P0V2sMx8MsXrmJ9F32PxrRvy9lNB5i\niWW6a4p8+yhnnp3hrr4aycQ0euh+Vpc/QTlJ6aWCrA0uz0EO00tbCDfO+J4hqiOrbHTOUR7WrKZf\nhspBxg9GjO4tMXDw9Tz75VN0WnD27GnuekeVzfUlyo06rWybtvN0OpK1jS46jmhv5YxMTbPWXmLz\nRouFU1N0V/oYOzbBiXf2M3q0wuStIzz9/86yWLqHhfkpnvjIszz+QyOsDl1HNhr0xC28bnNmfYmT\nb0s4c3mVF58x1BuHufx0zJEHe1Ret0KtbmmM9mj5eTY2DZ1mnfqgJ9dN7v+W/Tz/hWVe+cwz0Kyw\n5779TB0dZPj4KfIvDnHz8gqvPnmEk+pxlntbmJWc10/+Yz7+Zx9k+t7HePa5jzFU74Etk2VX0UqS\nG6iM9VANQc1CL8solxRdUnQiMWVLt5bTNxYzvi9GyQ5axKzPNxkYeB1TtW9l+eY881dPoyx4PY9s\nLFLfV2ffdIeDdym6vZcRKqabTTI8PMjzM20qdoCubVEqSza22mz35jB6k8x3cV7RSy2zczNESYvR\nfUNoN0jJDyI6PYb7YGxoitqj0KmcQbX6iCa6jE17os2E5YUtDleO0c56bGtPMlxj/eZlnEjJej3W\nl1qUa5JDhw8grjXpa9bpdTcQLqHd26Lb8QwmHplJri63iGvD2K0S+Zqgm1hcIonKhsxLhO+j6zbJ\nncKSkvtZyn6EXs8ic41Nc9bby9gtw3rnPK9/8yDxQM5mLyVOeqAlSqwwvwrZ+hhLM+NcOLPB2rU2\nzYUNxisxOpIkSZ3Jw5MM7W8yfV+Hg/e2cfEwc2cirnxVUbt5kuUbS+S9dfor/WxvLJMm60RRl43m\nPNo3aNQHKcUNtpubeJFz8OgBVmZniSRY14PYfl3X+TfUaCBBOIkxitR7ZDsNK3ytcaQopYkjSct3\nSTLLyloTZAnY4V4UtY7UYO+c/O4UakGji7BFkVawKXxYN1eqNUy7w30nTrKyvMD66iqZ9uytDbKx\n1aWu+zi1Nc9Yp0Uncuh0m/JIhTSVqHZCnES4WkqvtQhRjMTjpQqygWLi7JxDqQjn8l14myrMdLaI\nL/Xe7UYYho2FKhqF8MFgd8zqzu3KrSg+BKUoDrlXxHGC9xZMyDmX2hPpErpiOXXmKX7mn19marQf\nJWMGx8boqw8y0OgjM4r+/gHAMDQ4GEx+WUKtkbDZ3CKKIxJZp7sFCMP61nX6+0e5NXOZe1/3OhYX\n5xgarPHo/W/g4qVzVGoxf/ThD1Etl/nBH/g+jpw4xnPPvkhr8zwfe/b/4Ymnl5lfNvz2z72f0uAk\nSmyxsrpIt92lVqlya+siU9P72Fhv0z/Zh3TQ7XaJSjHedKk1psn9AkeOHyRPPf/rP/1Zfus/fpAD\n+yc59dIqm5sb9PdVabc7tFpdpqYHOXf5PK2tN/Hw4zGrnef4rd/+VdbTV/nTP7rI0LDBuyDnwAe6\nNkW61E4T+Jom447HTpG/kxy2K5X6Gr+FKDTdrkiBQt6WWIWI0dvfe/u1g6xEquK18Lsyjh251m1p\nVAEIlGp3u2d9HoIUivQfa1NQFiEVNhckMmajvcwje97Jq61PcODAd3B5/hXeeeLH+Y8v/RuOTLyB\n6yunadRrtDtbJFFfmIKrCJP3iu3ZX/+jWk7AWaz3lFQZlwW+hMtNYLLkge2Bc0RxKOhjHSbDTgRj\nuDNgCdISax3GGrzxKKuQPvgWtNRImYcUKOORsaQAMYQUoCAWItKSXpohfYwUgtx60DJsSwhyHGvC\nhkBKiTcFqM6HCNrQR4RGwLswXU9kiH/tpnmQd0WKKJKgCMVlZpCOsDUxAqcoJvY2vKbSOG/wOUUB\nGSb6sojIzbMsSIh8YRSWCmdz8tyhowiwRWBAOLV0BIKQ3mVzAsBQB49AaovVhyREmVqHimQwCsti\nu+QDP0QWEaqIojmF3cYG70giicHvskdy5Ul0TGGqCYW+Dz4CIXdgmZYk1kG+s7vZFSSxJDfFkCpS\nmMzirQsskjiAN20BO4RgbhZCEEchrlUoMHnwGSitEDrCOhNkSS5QwUtxCZRHeIUzWWj9VBSM3plF\n7cT4FlJd70ApjRC+OD4CpWOk9OR5OAdAhM2Z9bvyRwWgQGtJai1xHIXXI2x/lBBYY7GZxUfhuERx\nkMfZPMjQfPFZE45RON7W5jgbB5+HDrC+nvMIH34/b8N7tBOLG9gsIqRTRQprHN2eIc8yojhGCEmU\nxAhCA5alefDy9HKcjJDWY7Slm35zyOBxupelMwPoUoubq2usr6/Q3fgc59Y2yRhBJxWkLzM8eABZ\n8lT6p1i6Nsd9B4+zreeYfuMEo69LWJpvUT4nqA3U2Lq8QqezhcgG8Lnn5sJLdLtttjcz6tEk86dK\nrF4dIDMRVjaJqoa4vE5cm8Fnio5ZIS19gX33Jgz05+C2SZ/ZxMgFfJqwOKdYn5tAjQ7hxALbucGU\nazSXOjTXNAf3xWg6XDg7i+od5qk/8tCp0lfeYnv7HFpVyJNXqRy4SvkeSX9yN43RAzzxzFle+WJE\nuzTC2D2z+Komy0FVIq6vtBg55BjYd4Dt0wPcvNzjmY9OM3xrnrvftsTQwSpjw5NsLC5jIsPaimLb\nbJPr08yvjTI1/j/T3tpiYGyJ/W9rMnX3Iu1yk8qpSeTiHm596QBLqytstiLmNnucfOBhLsxdotOa\nQeYaKbfp9Xo00w0OHBtB9zs2O4pGWRFHCiE9tXoNCLDkwVFBpeGpjqZUK47hwZQHzcO0No6yMdOl\nUh/EYVnaeJrjxxNOvGWKwX1lfHWDXnwTV24T6SnaKIanxxib7GBbDuNS1nqL9LKIsdEj/Oq//g3u\nOXEcoXLK9X6ytMPayjqNoTrWlBkZ6Mf2WtT6Bqnu61A+ukFL3SQqTVHry4mwzJ5ep7vo2QZa7W3S\nKGKzI6iN7uXGtQtMjxxha+MM3h1ldGoMQZf+kuT6RpPaWI3t7TZJeZCW6zI8mGBijTYHWDxdZmxP\nnYkHB9hWL7HpNuggaLgM03O4rEZ/3/2s3ViltV1FZ0cplyco27dgMs3g8F4uXHsGXRmm1GiRVeaJ\nabKUzRCpMpHby9WznuYlSfdyH66ZMaQaTCZ9lBoZtpYydLDL8IkVBu4+TzZ4mrI4ycGBw1TLCc9/\nSJFsr9FsXSOjjq0L1rYXSMqCRGeYXhvVV2J+aYmB/hpZ1uXcpSYj9Qa5Cj69Nn8NjUZgYYRJpbeC\nTicHp9EqB69Jox5dnYGVmDxnYcNRIiczGs9OlKPE2xQXmKtBB1sU9MUwLaTtFFNO6wzOGro+Q2yu\ncHD0COtzW6Rdga14ak6xmi8wWBmBvMK4HGG2tYyILa4SIdsepTJElBGCWDRR3EdON8Q48lr5i5C3\nmyLgNUWpKLT+kU5wxfZBSYKG24Tnw21TsSoiKXe2IDvT9yDDEndM4x1eWPIs+D3SXoyTjtVtwbnL\nF5jeM03n1C2qFc/MzBzTe/ppdTaYHpnG2pxOZ5vacA2hHIcPHKKzleF9Rjmu01cbxpkOCE+p1Mdz\nz3+GA4emuHjxOi+eep7pAxP4mWUatRSTlPi3/+EDLMx00bVRBsp388DRX+NH3/0Sv/+Hv4qfOsgD\n43dz/tZplFPUB4fodNYZHd/D+sYmkayj8iprWRetI2ZvtpANS383YaivivGWRA0weeww7/quH+CT\nn/8oswuL9LIWW1spjarnTz/2KVw2yM/8q1/jpZf/hNnlAW5dHOTgkQYlYHS0ijX9aB1kDcF2SzH+\nDoWdkEXDsbt58rvbiP9Rk/FaQviOYRtswbHYfW0Rsv2l/B8HGoR0qp3zgN3fKzTNavf7bv/MMIFG\n+KKQKzwbwoRhrgJJhW57mziWtHLB66YeoNM+w6vtBX7QL7Mqu/zui7/C1MgRllrnkcX5612hTy+8\nLKH4+OZwNEyeIUUJSfAA5DZHyFDA6jhMxctJTK+bomS4DiTcNssW75+zDiMCUE1FKkhaEBjjCvmh\nDZNsY/FSYtMA7ZMi0KyFpKBUO6yxdDsZKhLgg+FbJYosD+wFYzw2t0RReA+iSCOUxOQZzgaiebTr\n3bJhcyIgjiSpywl/hi6YDVGY+isVoHs4Yh2HGG+ti4SfMPH3hMSlTi/EjOZkCCRRHBeesWB+twX7\nAy/JehlRHGjrFI2IJxiuw1Q9+B+cdmHD4PJiCx14Eju+sszYopnwCELDm8QR7ayHKrZoOtGAw2We\nPO1QqZSJlCQveA5SeqIkCVsU6zC929sR74OnLyolBUcjHHfrPL12SlyKEITCxKPQkQj3VR+kaRSb\nGZuF50VRFOKPCUZvpSQ2C5Iymzt0RQeJlg3eF23CRijPLXGiiMolbG7wzobELlFsDwkT//A5FKRu\nJsuCUT6KEAUMUUqLN8W5YovTQCnwDhFprDX0MocrtnSmSKzSrohldkUQgAG832WrSCl3GwyldSHV\nM2il0HEcorEJvqGoFJFnGSFLGJwtGFZJCMGQhGhdqaJg1vey8AuFGErninhjwPsAjPTeB/Aigm6r\ng6p/Y/PH/z+PlYsl2uPfygvP/j79U1PUbR9z8zdI6adUmWZ64CAub7F3ZIybs8vMmUUOD+zn8rWn\nefhHa9QPrdNMLpFUK/SPTHLh4gy1qM5I7QB2vUpPPov262Q6ZXsNXvhcxtbZYW6c3sPNpascOHKS\nmeWrPPw9PbbTc9TyEbzpcfhBTT06S3/9IktLXSbXY8bGNBk5G90+zjyTsF/tZXBjlsYhRbVWY7mZ\nMvNMhRsfH2B83LMYN1l55SSb50t4f53pgW8ls09w/soc99/TpKcvcOiRk0y/+Tv50Ac/y9TYMU59\nfoO11S5vedch/NEZKntfYKPdBRSJP0iluo9mfZW4NUF7+S4WP32FyUMVOuUXKTcaJOUSX/30Jide\ndzf9ozU++qF13n7iZ/jghz7NfiFprh6kPKGZN19k5M0NXGmA85+Q9JvXs3xxmAvGsvd+xeXtG0RD\nKdHaEkP7RiltVXn51XNUBgSmJCjXSqiohylpJF0SXQxqJWQlQ1KPUbUetmLRFU2tf5yheC/V0mE2\nl9p4OUHfZIm9/THjx5rYRkovGqPeSLBOo2w/lVIfq9llongvWm/S7vTR6nWxhZZ+YWGOk3c9gu3M\ncvzY3axsptxYPMvI8AQ6DkENvc5FRmr9JOMpU9+7hlC3KNcG8LU2i1s36Fd14hLoeossk4wlFV48\nP8PDb30DX33+GSpbS2x3lpnee5Tm2jwHju/Fo6mKcUTnGsuLc8hahcpIQqNviKZepeoP0V9VzL6y\nzPrsDd60OMWm0tT3jXFw792c/cIlzj27wKHD42xWNJfOdFi7scpwcoQ0usK+u07Q2ZymrZZIt2H1\numTsoEaOwUp0hs3tDejupzeXsXxtnPUbKdnGMD3dZLR/mI3VjNHReQ48oBl9/BRy6CxaNPCM0aNF\nKT5D6cRxskOfhRsDjPYmWO4tI2VEf20QZzW+54m0Z6u9Tb3RoJsHv2dfuUzXGDIjyLtdWp3W13Wd\nf0N3FOsyYiWxVmGsJ7WabifHZIbBsT686OC9IYskJam4ue6pqZSui1FxtJvYY7M0wIx8Ef8JRbEl\noNCWI0RIS3E5nbzFxMA+OtuO+e46b61O8JnNeQ4MHoGlDkm1yysr1zAKurmlXKkQyZg860Ds8S4K\nUhQEXjky10Ygd2VMO7p57wmTKueJ4xjYkcHs5OOHwk2IpDCzh/xzfNCQK1losV0oGkHgZUgGCRpt\nv2vHlTr8fOtTkAYoIH8oYh02O+cuXiZp1Dh19gJH9xzk+rXrfOS/XOe9//hhvucdP8/vfeQX+e63\nfgujcUZUv4sXnnuFF5+/xF13DVPS/QwMSG7cmmd4YIjMrJKoiF7WZGHhKkcOv4Vbz3+cLz81w30D\nCjFylMd//Fuw8iG++1v2kS+O8h3Hj9KJ2nzoP/8hP/Q3/ial1Vv860/8BtMjE6RNwWjfPlKzzRk+\nT5JFVMoRr+ga9x7ZQ9t5xk8cIN4YIG/EXF+6ylZrlQfvfgPNuQX69CqDQvO3f+SfMjQS89xLn+I/\n/vFX+Xc//9O852/9MnPLT/GB9/8JH/yNHyDzl/mj//RVfuSnHqWiT7DfKxWJAAAgAElEQVTSOke1\nMhjYKjJMZfEOpZKCWVFsEfxOw0EhRbqdhX+7ybjdWNwOAKA4D9lNEQv/HzT5u8lUdxLiBQgZSNLu\nazxGOzI8W5g+d38QBO12OCPC5egcXnqUMpisjKSNrjiq+RhtdZWD9X6enb3Bu0f/Fi9u3ODwxEO0\nmnV69UXUdpgupalDyog8z1AqwjiPUiXMNykbXwmJJkxls9zgi+2fJ0DDvHUI7bDGkBaSEorr0VqD\ndY5SOQEhyTOLxGG9RMYU8kIb7g1Fcyd1oCUb67CpJU4SvEsRhWFaIEmSpDA4B4aDzRxRSaMVBHlT\nVhDlg5REyLCZ1AWM1Nhg4PVeoRQYlyNF0fAIQITtZc9YIhljyML9LlIFOyIUp8aGpK2dglorEZqY\nPPxsm/lCz+9RcUIcCWwnxaQpxrqwkXAGmwusdBRWFJwXWG/IjUD60MiazCG0D4biwj+ihIQkRkUS\nS2A7WFOwT9wOgNCii82Q0sFIHmKJAyNkB3CnVDBC7/iIhNrxvoQiWKkA8fPGY4qEKudAR6Fhs9YR\nlSNk5slzE6CIPiRxaSXJMosSCovDG49IwpReRQXwFYlH7XoXfO6QEQgbOBjhmBcx0shgykYE7wsF\nm0NkCCsId+7bEtgoUnR6WcgKKCKApdZAhBBBqpWTBz+SVkRxgnV5YOIoBTY0YUJqnIHcF++VFDhf\neEJSUUAlgxdJKU2kI/LUgBNYPEKGQZXSKhxDU0BgtS5CMBymawjtLOgkJpySktyE2HChVdFPCUya\n4z1UqmVAEMURrY1thLEkpThEGusoNEPfhEdfeZrP/eU5snScanmUp15+Gvw0E4MTRHGDvqRCXKrS\nWTZM9fWznM1z9coKj77LMHm3ZtV+lkGd0cvuIl2tMjX+MHPzmzzxyVd5uLWf8fvvZXjvKi25Rnfj\njZi5GLM0QmLaRHGJVrtCvdpgaeESE+tDDE0P03UdRFVSbmyy0pshHptm794RBga6rG32aPijXDuf\nc+C+u3BrS9i+FZrbiwxUY9x2H72Zwzz31TKdaomXT/8JNdnH33zXv2SwPMqXvvIyF56qMzAhmb6v\nR2W4iY8+zsSJGczWKImfIr/Rz9UnOxxwXc5fhnsfPMSzT80RtwcYqE1wfmWJ0khO/3jK/uNv49b8\nF7nrniGiWJF5Q745zWf/0wB7Jo5RW5xmrT7N9vZNxo8+xKWzr/DAXAc3MsngfsV612CXFphbPYF/\n4CajzWnKyRhPPfdX1EYWqUyuMrOwRtbpg1jTPxpRHV4nUSVS74kklCuaUs2iE0t72yFj0JEhjhy1\nRLJv8iiRrxExyez6MsoNMjFRZ6u3SH3/GmPHYHjfICqqYDslauVJtnKLEDWqXjJ7/hJpO8KrnLGB\nUVody6bpspnPI+Q2sitpxAdZSs9SinukWZeerzA1PIVtXULX1xk46ChNnCfV22QbHerVBCn6KVf3\nIidKHHlUsHZqFtr9TI+fYHvb46OcG1szuEizkq5RK42wtbrOwbseYHF7k/6xw7h8liwx5HmXnunS\n6+V09Ba9NmgTk2/WufVklYu3MqqlHmeyU7Q3LJ32KOdedgyNNujOH2ZQDZBUjzC7cI7O7BWyaJlO\nlmF9i+fX5+gsl5l+YJy0r0ez3WB9WZAuJiycyWkuzjA1KGkMTzCkx2nlTUS1gx5fJi9fpiy38Dai\nxCROrrItQPdv8NB7Knz+4jKiPcyQvsX2ahujR9mMqlCeot1eJfFtDhycYnU5RLhvrK5R1VVq1T4q\nSUJ7e/nrus6/oUYj1hFxReMU2J5HZdBzjm5qkesZ5a5AWvClsLHotlt4mSCJgbyY5EmipIQtUmC8\nt0UpEEzVkYLcBmNiZnO8sFTLdVY687x+6i7amxmfWV3izZP3c3llBteXs7rZI1Ya76CkZNARe4v1\nBkxRxglBwXBGCr1b6+38u6PJD6RgtSuPgbCZUFpj8zQUbnmGEKqYInqU1Di3swnxdxSxkh2mwp0m\nYmstwvli+ux3jYNKSTwW6wVYw3D/EFZ4VLVMK++ElXlplqmRKf7WD/4Itariwx/5P5gY3UejcZ73\n/9R7OHL4J/j1X/8DljdmuHp2iZLo45mXXmZosJ+15ikmBvupJJbZmc/xUz/9Z7zzBx7nC098iaVn\nbjF85QAPRy8SNUfY+8hxhDNcm4VcL/Pnn3qZ1sbfYKT87TzzxAssrb9Ate8p1hYVU3sOE1daVEUV\n323z9NM30SyT5IKJYweo6jo//tP/iLlLN7m0cJlHjryVr5w/x7vf9aNcnPkMH/3jz7CxsI9f/2cf\n541veJRXzr7EoUPH+erTn+fn/9VP8ND9gu97z3twFup9irllT61CIV9ThWfCI3f9NL7YbOxsl9xr\nPBOws4kIW4XbIQS3C42wXfvv/UN3yp5eu+0SWBcYAULKIH8oZHYU552Sstg2hEZaShWkJbDbnAQZ\nh0GIMpZ1avIulu2rDMQG31Ss95q8ceQNvNR6GhVlNFWPOfkyI+sPsO5OU3VlPDsm+FBkeu8CyNB+\nc6RTLs2wWUqpVCXLi3QwrfEmJzOhaMsdqFJcgDjD9RMnMc46ut0uuSngapFGOEen20OKGKE9SaKL\npZErEuEcirDxEFIGk3EBw4vjOCRr52EjK4RCBPMDzoQVqlDBP4EqJD9GECeq4Pm53XtA8AEV54cD\nGcswLPECm1lIwmQ8+BuCJAYCVdv6MFyQPsh0sm6PSEtkFDYz5UqJtBcgbx5RDEYKRoQAkCgJUgep\nT57nIcpRBk1+CDsITZF1AY5njcF2HVEUYZxBCkXugl8EAwqJFwovDFKCycFgiCMdqNPSB4mVMQil\nUZEOk3DjERowFi00JrWQSLQqZDlekvXScE93Ie5cS4lTETY3xCpQsHNjUQUQUNkAo7MmRO4qq1FS\n4M1tv5tzIf0txD4EWJ7S4T0PjBVDIhUqCswL4UWAusYRWS/DKoGONMiwERE6yN1MZrA+NBuuAC+q\nwqPi8eSZQ0QK7wWSYCx3XuALL4SwPiRsiSCXpPCieASRkqRphlWEpliqcK8iQBxRwfDtvSmkdQQ5\nE2EwoaMiVcuG7ZQx4dpWkcY6g9zZVFqPMabY74YodmeDAT5Skqy4z4UYBYsp5L0lLUlKCSbtBrmj\ncfg0bPm+GY/ltevoMmiVcv7iRarVcfZMHKbbydg7vpe02WZqdJxeYnF2lZmlc5y89xH00MvMrP0Z\nE+M55fZe2p0u5ZEKCzdT5hYWiOMyW60mk7GlbyQmdkNUhvdwKV2nKqtcWJ1jcF+HhbmneOd7/wVf\n+dQ8tf5RdPk8e45rnI3Z6FiEqbGyYuktdxhs7EUNDbG41mZ2bpXrlwYQ13IeHJsgJWNsuI8bSzd4\n8L4f49T5z7Ox/iwnB95FkvQxum+d7fUZDt01xPpszuyZMteWr/Lod44xs7LGgRMnWbm4zl0T38FL\nZz7H80/PcPWWw8rHka+8kxdeeIKxvnHm5teZ7J+iNjBPaWqOvmMl6hNlZubW2CNGEKaP51/o8Hfe\n8UtceeUlbp79FIvXXuHo2CFevfAMb39rQmd7k3i4n7lnpnjlw0v0rryJ80tPs+eRb+XS5b9i71SF\nvkqXUuTYaBk6eY4TGiLom1BQDulp5VgFOa4EYwXCejpdS7mRUC9bypGnLylREWW2NjxbjRWSuE6W\n5vS2avS6XUYOVogGPFaU6LZ6aNemrzxJtlqls9nP5tJhNm9cY3W2n6x5k8G+mKzTotVeQ+ku1hkm\nx+7m+uU5fGxIksCBGRnbT9qJ6a8NsGlusWdwCKNqjPRNk5o6vUxRLtUxPkYP5Jz8jgnmqwd44a/W\nqJYmePXsk6y7FFWvYmplri1d56HpvczfWOHgfccZGN0PtTar52/SSTeRKqO73mV0pIHUgk5HMdJn\nKdkuq7Mz1HrT+E6PrW6KKA1CaRsTWeaWc7wcpOckrWyFLElxXGd5oYWMYtrtDLXUY2lpk6kLE/RP\nn2Szvc78/BKDyWFi20fZa4b6J4n6plicWaCRKJJqiYHpObpekbCfWF7Fco12NkScjNH0N6lP7uP1\nP7jOmT+5xPa5hMhlHBxUzBpJXu4wNjDKhYsvIfcMYjpN6tUBBvoreBdhW1tkxpJnva/rOv+GGg2p\nBFEssNKjrQxmOmKy3LG1mZN2JAkKU3K0TJN2z6BUjM+LNBhvcM6gdBLMci4wCqQM0YZCSDxhi4EK\nciIlFRbDeGkSbzXr0Rb3DJR59tbLvPngPfzXS68y0T9AM+1SjWNSk6EgrMjvKO530qBuE6Bv30jv\npD1LESISjb2DgeAJemihiKKIzGdBP2zCTV2rYKATFLrrIhUnVEPqdsKQv51w5H2AT+3IxUK8okVJ\niRGSso4QzpKZnDiOWVlf5p6TJ/mFX/on/E/v+zna2cu89fHvQcdNbl6+ys35V/mZn/0dDk2Osrm9\ngVR1kFXa+So/9r4P8Kd/+fv8k3/4B0wODdBIRnn84QfRBxb4rV/+Tb506vP84rv+DX11yTPX7uGN\n9+xnK3qZRn4fmxuf513v/ihv8Z9nq7vKL/3uP+OLT77AjeWMc2cWefzNj/L3fvxbWJ3JWNpY5Yd/\n+Md4/onfBVOmhefI1Srn577CZ558CiqKqlnnxCMPsX90mF/50hnOnb3BO7/9J/l3v/DbfOaLf4RL\nzvLd3/4YWdrl5Reu8v6f+jecPvsSf/8fvY++KqytzlOr1QlRmRE7KWDBQ+ODQm3X+3Pb/yPETmN3\nO9VsJ2jgtQEEX+u7uN1Y/I+kViFRCHY8GMWTdjdkO5HGO1ReiuABvAtCu6LwUGrnNT1KVMBlJGqU\nTnoO4gGUqvCtR04QdSv8xdoz/Pzh9/MLM/8Xi6cv09eYYM5eYaQySCfrEKsIvStngV6vRxRF3OZ6\n/PU+ytVKKJBkcOh7CBIeEUy4Koow1hDFEYYggQs+B4pkpgglZGAaEIq6KIqCqd4HU7JzYUqe56bQ\nmpvgQYjiMDVXitwY8m7gJESlCGNCkR+M4ppIyZCeRxgKoATS5pg8RyF2pUpK7URuW5xXQZuPDAUo\nopjQe2wWJFs2y4kiFeB3PmzUvN1pJMNAwcjCm+El3hhkFIzAWZYHhkQcqM+ZDUW+xmMcIELykicU\nqxKJcUVMti8abOWDwVmJwBQhFOyZDE2Gx5IZQ6Q0OFMUycE4jYAojrF5J0Q8e0JMrBegw3uZ5xmx\njApPFOAdLreYwlcglUTFGq0UWS/DS0OURMTKku5wU3zwpJgsJGnhfdiUKECqECLg1S4o1RGObZYZ\ncmML4GGAPe5E9hqR4qwnilWgawuN0gE26FJfbBt0uGaFQKqwXcmNxWUWGRVBHjhMAZoUhSHdFqon\nZIyQIUkHXxhkim1VkKRJlAr+Lm8zhJBFMxC2WoFbEhdSKhAyRM56Jwo+RjDZh3jn0HB6QoRy6GHc\n7p0tSzOiJArbKOtDE+tsiBQ2RXNG4NJEQiEpli3ZbQhmmlpkJElEGR17nMygpFDxN0dmqa3BeUMU\nlcjTLpN7xjFpznClH93JGWn0E5se1jhyoFwaod4Y5qtfuU7fwUEGx8uo2n2kW8vM3HiVPBvHtDbp\nbxxiYo9Glp9jrXuKPX2P8NTZZdqLCbeu32L04CQXFppMjo/w6U9+iLfc/92c/dyXGZvsQ4hT9O9d\nR5Y2aG8bKtUGs80hRqfvpeQmaIknOVA/xMatIW4utmkcGOOx7/9+zjz/Sd76vXdx+kt/hm4MU+89\njO4pHv3OHsffmrJyC658RPPo/e/jI7/2H/jJn/sxbrzyFY7ff5hNlfK2H/si6ZkpLs4eoNGt0V2d\nJ8vaPHH1CY7e9wDnTjfZf2yaD3/1d3jj/ZPcXF9mf/I4y+vPkwxM8MynS7zxyM/z0LEFPvzHH2ai\nVuFtj72B9fYFupsHuJpscnn2Au/w+zj76hmOmUe58XKZqJozvzEFM0sMNSbY6pxHldZY29wmNWXy\nbggvGJtIqI9YXOxxOgvpb0kYSLS6jgjoWhhtVJCySaw11VKFVmcbFdeItCfWkkpsyJSnv3aA9uYN\nqk3PUHWc1loHk5VZuhRz5rMtrl+YQaZbjJQnsVszVGtjrKytUyrXiKKIui6Tp5LWVoe+kqLbMzgL\n7ayJKl1nqLwXGp6RQ3s4eO9B6vXD2HwT4zxxnKClx2aCSlKCyDB98gBzZ+tcfWqJpDRENarRbZVZ\nb0lq9QZzSzc4su8kyzPzjA2OYu0GQ9V9tLc2IeuQpx1sQ5OZJj6v0k6bRMkG7TQiNxXSdpVWp0Yt\nHmfdSJKep1JOyDJBueQwOEp6hFIOrn+Mle4tWqYLeZOl1iarLc9D/nGMmWA0vhtthzl21zCdZkLk\nDb1U42mRlMpsb5Rozic0Bsagm5HFVbwYQsgmmX2VkuojLW3Q92CJA13PRWmw5zztrXnYrlIfSVlb\nPMehSoW5l18ijhv4zJE21ymVy1gDuYU0bX991/k3clOwJiNzEkkxtVMORBT0wwY6bcOKz0kq4HOH\n8Q4l40KPHOG8wOQO6WwhTyHcp3d16yEi0EuHdwatwodvySfMdua5vzLM1e0UMb6HfeM15lbWqAxJ\ner0cLUQxBQ2mbUkxnf4ao+9OoQmvLTJ3vm6dw7hs9+uInTz58LsaY3e3H6KQ0UgpkU4Gs+iOjEbs\nTLSD5vfO6N6d4tR7h3BRWGtzm9yqlaSbZkRKhshFAY1qhYvn5th/V4v7Th7m3/7f389f/vlF/vCj\n/xuvO/Z2nnzpAm988HF6WYphha3WAt45Wm3J7/yXX+V7vu1HQLzA/on38vjbHmR9dp6ttQk+8E/e\nz8AnD3Lfo8e49LkbHBiA577yCt/1v7yel/7yHHmU8Jb3wu995Cz3vfkt/PKh59jc9IyVHb/9sd/D\nbc7yW7/xJM9++Ss8eNcQJ/aP86n9383K2gW++uSfcWNtkx89+UZeuHaLs0s3WOnASxvPYlqa3/33\nf8H5K9f5td/4Bzz7zBf5vh9+nK3mMq3mBer9h3ng9ffwhS9+nj/+ww9zdfYWA33jbGxmVGpxYTIN\nJ1FgF0S72wV2IX3idiNXHO87o23D+7/TjNy5zfCvOUe+9lzZIYfDnU2KuFMRdQdfI8hPfB62d4Iw\nfQ0Ca89ulC6FT4MwYfZe42WLevUgreYlhmr72FrtcnTPFG9PVvn3l3+F9598N//2xT/iyMQ+mhdf\npVNSiJCgifau2LCp3b/hDmvJX+sjtwarYvAmBEX0PJEQOBmaeKkkeQrah4jOzAT4osuCVCmJdWEm\nDpT3AGMrCmkPeWqDzl5JdBQF2ZQJ/gPjQ4OvlIbUk+ORzlOOw3UkZJD4GGtRriBSE0B6UorwPGvJ\n83Cdh+hViGKFieIwGBEKrYPnxPpwr/EyDDeE1wHEFxewOhkKSGtc8TcFYnQSh+fn3TQkbdmwCYtj\nhUdQSiIckGYpwktc4Q9yxXQ9ikMsqhcB4CcQ5JnDCYdQkrisUEhsbnHWolTwjwgtEKIwRqtQGJfL\nIS0qgAgtShbpT7ZIvJLBZO12Ni1KFbRr0DJ4DbI0RSqNLkm8F0VRHgrjGI23IbZWFBNQTDBdp2kP\noeLdY28zG3wZ1uFFaJRkFLwszkmkCNwPk4dUNSkFaZoTJfGurNHmDmcFOpLkNvxdwlvyPCRHWcRu\nlK5xLsiUrEcph4oVumiEBYXssdgamNyiSz40CFqgvSzu52FznaUZaM1OpLW1gigK55wuPEM5IjS0\nFI2rC9dpaLDDnSlJFFGiSXsZxoRzORj/FUoGU7kmhAs4CzoSCOtI4uB/wQUITVIOW01c+FxEalQk\nidGBpaEUvTSjpCMsGZ1eRlLTaCkCWPKb8Kh4T1Ieo5d2GB8xYHtU4kEaST+DpZj+qmdkQqIqqyw3\nN1jvq/Hy2c+y/55j0OvgzQp2u8KNF9skG8MsXVrn7r2vo96vuLn8Cfb0WbaXUzrxDGdOnyPrfR/9\nI3XOLK9TGRLcmlvne976g1TiMd70ljdx/eavU95fZkgqmusxIjW4pMnw0RmS5A+4+56fZOvTKS++\n9ALLp4Y4ec+bSbqH2Ly5j/Pn/pw4WeLsU4qyOYxng9E9im/7oXvZqp1jenAM/mqT//qx3+Tg/jEW\nZm7w9m9PaPlPM3x4gtVzDa60PsbiZpk9U+9ldOIhcpsxe2OexqimMniNZ89/njc99m5euPhlHvrO\nI3zqE08wfbJHdWuQ7dkp/uL50+RLezkwMUyabeIGb3L/2zZ54TNd1s9vMth4hC9/SqFGBvjCU9ew\n8WG2qn3UT0iuz55ncAxm8wXKQymtpQ4q74NuQqPUx+TeTUr1bXo+gSgNQ4/EkZRKwWcnNKVqSidv\n0SjHWJexmXaI6/1oaWmupzTnt1mdTzGtOutNaMw3WMvnWb3yCq3lKrX8jcye09y4eZXtrVWmaodo\np46sPIpKy+TC0O2kIKtELqJa66ev2k97a43WZptSXwNjekgcuVa0nGI0GmZtaYg99+zlVusLVPrL\nGCfxWYdGMoxDo2SdpikzuzjHZmcF45cQ0RAHjh5ifWGGzc5Z8maVwVKJcjLOyN5DdNp7kd2LHJk6\nzvnNV+kfGqK1vk1/vUGsYyIf4Tt1fFJlo9dFDgyw1S/p1kusNmMiZaDbpVQZwKRrDFUUUpeIwtWN\ndTnDo0MsLKwzuWcvklFKqky9Pk1f3zDkVfJshuEJR3erx3Jzg1rfNi711MU0q6dPUhp8DvafQipH\nRoayQGsIIfuIaitEo1s0vmuEe9+UcOmjjssfX6ORQK/ZZWQwxqUCXdlDu2fodHtomdPaWEPFIaig\nVvv6eDvf2EZDC4SXCBURRSFNpLWdkmaeSGgyk9NuQ8dITFbF+q1iDBQKhh3AnbUhacQX8iEhbktM\nrDPhw8NY4kTiepZcKR4ZOcEL2SZ7dYnN3hrbS0u0qyVUJyKpaNLs9sRrp7gM6oodnsUdhGhuT6r/\n+wJSFs1JMf31hGmSMZTiMtZlqOJ3Dh8w+ram3+5o/W+zE4zJCL4Nt9voBIlH2LAgJYqdKMEwHVNe\noCKNF5bMprhexuGxCaqTw2y1PFevf5nD49/JS6de5b/+xScZ/O46H/rVT7O1nXF97jpCL/Oxv/p9\nXjr3BWLt+Y5HPsCPfO/38ug9j7I6v8z6FbBacaTP8uJzV3jHY8f5y3MfJ+0tsMec5OTDx/jcB1/g\nyIFJjk7t4Vd/4hf4zaf/M2849nHe/4/fR1kc5dG3v4fhicd4w4k3IWee4bHpCs7HPP/sIm95wzF8\n9G289+/8NJOv97zvocc4PbfEmoXv+4f/lJc+8ocMTU0xJOf52f/zH5Dnhsun63zb4338u1//OX7l\n0C/y3h//53zwN3+IRmOEg0eOcHHuE3j3eqRcDVPgHcmT3fFHFB6cosEI3ovXNgy+MGvcuaW482t3\nbi3gdvO58wjN4x3Rm9w+b+58CMHutFdKj7M7UiuFEC6ckyHzDCnkrndDcBvgJ4RCK8Hy5iYDQ/3E\nnQoH7zrA5TNPsTGccP/wA3z28nlq8RjN+Q4kHo3A+BChnKZF9LJgd5vxzRFOgRGSuFIOf02myNI2\nWulC8CIQLtC1u52UUhwVx2wnNSxA4ig2VUKzyynIsnyXkAy2kJ8Fynie94Bg5vXWoUVRgDlFLzfk\nWYCqOZejkxhR+BO8s0Q6wokAUJNRIU9yLvAIZGiMrPcIBS7Nw/BBKnIkURS8DcIFb4q3wWRsjSVO\nIkzucZkljhUCj450gBMKgZaa3BhMDsqHCblUgcSd9jJUokKKWSTxeSB4mzxHGBc2NFkGInA4bF6w\nFLQqAgDCfcurHfp3BWGKZKNYIWXEDqtDxTHOWXLn6fVShKyE6FgfPAimSBCTeIzzJKUSAkFq88JL\n50M0rnJIoZAyRK3uxBvbPDRZSUkHz4tzpFkW/G0GbLbjh4mQWqF8IK9HSYR3GqkFzoRjqyMV+CkE\n8CPW43MH2hWvHZgnNnPB2G8deWZQWpCICJM6XB5iuJ23SO+JSwpvw/nhnSe3IcmM4GlHiTAUMLkN\n8EKliLSka3cGZmGYYDoWZSXGhcQvhCM3BqXDe6ELaZXzLmxJ/A7csSB7i8DKwVtEUoD/rC9+l9Bo\nxklMnhvyQoacphlCJiEwQSmU8HgpUQRmCdKTZQRgpQqhCwgPxTkocoOMFEprunkaZJyZwfW+OY3G\nUNxPTe5nXp8hz1o024voxjgdl/DfeHvzKMvOut778wx77zPXqXnoquopPWSeGgJJCCAQpiAgyHUA\nURREvHAVl7LUV5fX4ep7l75XvYpXFBQQrzJE5hlCEshAhk66k07S89xdc52qM+29n+H949nV3cH7\nB6y75KyVdKdOV2r33s/znN/39/sOzZqhPGsZv3WdpNlHzp3i6c/3GRx9Mb63hjCPM1yb5uDBc5w5\nXWdm9GrGbpvm9GnHidYq3W4f7Ai93hLZco3KcJ/y9BhHnz7EiI45dNpxzbVXs//wnfzuH74cP3SS\n6fhWWt1l1ubXWMvvZ7BWRkUpo9NN9OAyLr+LnWmfE0fOoUc3c7arGD5/lL0f/AzjM6/n8584Rffk\nGmPxPMPJME42OfHENxm72dFabzE6MUi5M8OZIyeo74959FvrNHZHrI4vsLZ0htW1CqON57Hlsi6b\nrnkKG62RPX03m6b2sOraLD8wTCmq0Gu+mE9/9tu89Sd/kbu+9ufU4lGO7u+ybSaiu3IXr33lFAvl\nIyTTBxmenaRd6/KCO97IRz7waX7kdW9l31e+hjkzR7fZ4b6HP8N//rXf54N/9wBCniYeXkeQUytB\nd83hRIk0XiYZBK9zmrUErCJpgFcpTvQZbiT0W11KVUVJQ0nkVAfA+z6d1ioq95i5s7TmR1ha9JRk\nB5tHHHosBRzkKbEbwPXmWF06Q55ZIp+wmC6TCkdiHVmU0c7WaTQHSHyMN466HETH4/hGiuqv0+2t\nQV3QlxGdxTnk2DAHnulSnZ5l046tjMzuoZetE+tVongOZxO0HIV3zQUAACAASURBVKXfG2J9XTI6\nfQ3txX1EHcWIGSCqVMkai0jfort8FpJVjBtg/vwy48Mz7LjsCubXE4Yih3VniSKJchJjOngZYXOH\nTSLawpAMDJBZRzcTCJ2Aa1EtT6FiRWs9x7d7DPgytqxZF+usdzw6XUPJiGp5HG9iDj59iES12LX7\negYn28jhx9hxa4JWTcoPlDl3aAolNrN6fhk7eIYJ3yLP10iQWCMxROhyRiVawvsMKQSl8hyV0hT+\nHRMcaz2C+u469YkBhqYHOH3mML1slHR5mF4KKk7I/SD9LGNq0xgnW63va5//QPPRJI5QOkGShM6f\nS9GxoFSK8MKglCP3km4PTpxYRWhBnufBLcQH6pHWwVrPuY0PfnPhH+vSkHAbRVjv0GgwnrHKIFlJ\ncEN1kpaI2FOdRk3NstTt0EgSTK+HMEEDIlVBlVLqWV3q4AKlnk2l+h5Kk/eB52qtLcBQ+OCP4xil\niy6mC5aYWZaTZSEIKU17SBVG7hudbkH4YIzj+ELRK6UkiiKiKNhsGpMVxa9EECFJECRETqJkRO4F\nSa1OrVxD9B2PPfkAN7/oCipRzDW7b+bP/tu/sH32et7xtvfxl3/zAtaXv8pNV+xiz647eN1r3ob3\nnspghCo/xXh1iOXTT3D1laN01k8yNTJMb8ozOLWTGb+NbqvOwtk1RLzKt+//BosjGUfm5mhECXJT\n+NB58Omn+elf/m3ue/w8zhqa1ZMM1QewZoaJ6W1ctWWa6y8foxLXSc0R1pKHeMlrtvOxfffTFimz\nAw3evefF/Mkf3MkTB/ez5ZYXMaQFnR685R3Xsmju5+//6YOUp4Z457vezD9+6Is8eN/X2f/YGbBj\nGL2IKrVRKrrwvFxhH+sdWJshhEPKjZDEUMBuTJg21sH3JnRfKur+XnBy6bQN/IWMlUunY5dmrVz8\nvkI0bimoNgVVC1noJjZ+TghVszYntz2cywrhusP6BBllTMQT7Jye4GsPf4nrrngJm02D/UtHeczu\npZZYrFsislvpVHKkCF1xZzdctwJwyvO8mJj8x7/W1zu01nrkzuGFp1xJQsXmJJiQGB0nEaq4nqBd\nIVBDnCfLUuJSTFyOiXV0waFJIpFSh0PLC7wBrULXVhcFoFJR0DlsNDEu5C4EoGVcKC61ChMOrSMi\nLVAihLQpJUF5oiQuXLpC00GI0GhRkQYfxMv4Ikncg4oDTUfKwJL3xhXgSgbhtJT0u31MXthlh1xv\npFahA19MTxHh75pmBpOGzAlhQQpFKY6IlMJnOTbLAvXJU5hNbEx8CkAtFLmzRHFMSBwP7l3hzA32\nqCAoV5NCf+LABk3MBn8/4IdQ7HrjQUoiGRTd1pgg6hcBcEsd9kXez/CWwlFw4zwMKnu3oRESkERx\nwSwN+wRXXLcnhAx6X1xD2GtJHITP3hZTYgp9m/V4KYItrY5wJuSPRMVEBhEmANgwDTG5C5a6zmGy\n/IIFbZREaK0wuSXPinwWCTpRF8BnVKS4+yJjQ2lNpIO7mzEmTMxUMHhwXEwmV0XwnzEGb32YfOGJ\ntCA3Yc8mpZhYaWwR5GiNLbJIFM7k6EgXFL5AwfJFa0Lr4I4mnxU865AqxubhWqUQIZHcBzCmkMGp\nLbMILCbP8DYnFhJvLVES4X5I4Z6qeo6Bcoc4iwkN3oRUg6tb1KRjZM9ZaledYH34EL5cYnrTTs4v\nfA7tLWdPadbbT9JZOc4LnnMztaalOeUR8QqdTk5ZTZGul4hMg5Nz88zs2owePkC5uk69ZJkYGOHI\nUwe54YaXcfe396IqhxifPcfwzNMsZ/dTanpErU/uJ+lnMxgPC0sPMrktw9TbpMky62t9kvQODt3/\nXB7/fBd75kluv32MG2+vctWecaocZ/FslfaZdcpqia2XraDrz9CYqODFDA99S9P0d9BfGqXbgcWV\nJslEhfE9h1Fbv4WZ+RTDN8zhmwfpd2rs3XuQbVNXUlmTXJZcxlc/9F2OP1Sj4p5PJZph95YZpsbL\nWHeA7TtO0Sgvcv5UTuJn6ax1GJ0Y4cy+QwxFI4iBCRjtMTpRY//Tn2Pm8g4tjlOuSkxqiWVESVew\n+Qq1Wh/kOsY5TN5FiZREGRLlSWIPLqVaUpSEY6BiQRlc6lCmhGnVWDjp2X/fMZ66P6W7UGKw3mRw\nsI4UM7jscrS4GusGyTgB5TOIkkAnCuN6dH2LjmjTTpcg7tFLW6S5IxJj1Aa3UBsYR6Aoj46gJkfJ\nmxWkEDSGB6jWB8m6DbSY5fSTJdK5HUgjQKzgRAMPlIRA2Ap1PcrOXbvZcfnVDE5tYnrHFKWkx0Cz\nRHlsAj80zLl0ibn+ceJ6TqmimGhsYbJ5HfXSOO3VHsL38HId6SPiWJMpw1JnDiszVKwQwhILS8lC\nxWt0lpF21pC+T+o7zLXnObU0T289p1qtUGqWGZuaoLvSorewwHgtott6nL64m7GrjnDNHZBs34ff\n+gmmX/Q1Zm4+wMy1HjlqWeit0F5XkDZor7fpZKvkrgvK081SvCxjfEyLrSyJYVzS4MU/ews3vW87\n1713lJvfs50b3zHDztfHbHoxxFtjGJ1Bj29FjmzDNSaZvvya72uf/0ATDaU0USRwPgMp8XmM945c\n5AhVImuv0mjELPdSlnKDNxYRReADFSnwqk1R5IeOmveFQLawuRDakvVySlFMO+8QJRpjJcfOHec4\niuFqhS+e3U+mVxgUQ3R9GL077AXXFCkL4ae8WFBeGsq28bqUyhSsd0WgaxUegN6ZoLsgBBT20/Uw\n/i9AS/i+wK/N+h6lQmKtMSF8rVQqkZsNP/KLxejGz9U6Kb5mQ4GJCD7sxNQjcH1Lr+cYrDXJ1y0v\n23M726dv4+HHD3JqqUPPpTxn163c+Q//ixuTm5l/ch/PHP0ub33vb/OxP/tdAH7jbX/Ejde/nu1X\nj6G7ZU6cbpE6aLs+HKqxdYen08oYL5f4yN6vc9O25zM47tk8OkCsR/mHJ/6CBx94mP/86v/Cjlf/\nGF/+l3/ivofu4dfkL5OzjaXWAtLlmH6Nf/zfn0agmL5+mFv3vJgHvrDCj7/of/LKW/p0jre5+ZY7\nGJ+O2dnskzDGB/723VxRvoPt21us+FfzTx//PRojTV5x3Uu47aU3cPOtL+Kebx9mdDrhdKsNpo7J\nHMqHlFspFHHksU7hyVEkF+hRwU0s0JXC8whg6dJU7wAmLaFIu7gufEHnM8YWdDZ7yfSLIDC+xCL3\n4v4o8lYKb3vvC7tkH9KwhZQoIRAyDu9Zj/E5ue0QR2Wc0yGZOUkwWRb0TqbFYHQTz7Sf4PbL38a/\nHn0/m+uvZcvkOr0TDaKmYqndpZQ46n1J6jzCbax9eQFMKRVh7A+HO5VEpVA4RZq0b4mjiF47K/IJ\ngohV4IlLURBYF8xEoYMewrlAv/HWhea8DXoXVXRevXeBs21yylKHzAwXdFRSgBWFKNza0MkuR+Q2\nPG8sWOlRhX5l45ywPoiSPQKMw6twHkgRMjaUCIJuJQSW4EQmC92PMR5nwbpgtasiSZ7lZP2QRq+F\nLdQUGukDf94RqC+a8LNVVOSIFC5G9PsXNRcSyHLwCokIIAeB0LLQGijIDcY6omIqZHKLzS9xQCso\nejqOcNYAAdzqJEZ4G4TJeKIkUGHDvQ40pEBNDc8tKcVAAGZW2iIoUaCFRCaq0OE4lA+uT1Gii0C7\ni3sLW9gHE6iowkOkFTY1CCUwuS8cmCRKx9g0D7wiE8TpQihyZUNRHoVGlzEejULIABaSWOHwlCol\nrDEYB5EEFWm0C5oHgUCJQuehQvGdpQLpJdaAxxGX4wvFuxCFBXNu6dvweRiMPSQOQ5zEeJsjVGG9\nLcI0zjqPFkE3EikVAIcMoNYaQIa8FiGDqYDQCpPaoMJRstCNEKZXPpxX1jiMD0DS2g3abTj3Qrq7\nQNhwBkRaF2eALhLgCcBfeiIdo5TApimlakLuM6wQ1JrfX+Lv/+2rVHNoM0ej1KLfaZK3WwxUYkoR\nGHUS29zLMqcx/Qqd5UGydo3a6AALCOrplRx5yDAiPCePPIPOx2iLp0kXHHG6nf5yheMHzlPaqRDJ\nGrq8xvT1e+nODbOpsZPjDx0hqmUcOnacpjvIbc0zNGcGOb3vPJVqjd56ipcZE0MjLK72WFupInSX\nfScOcMMrnsvH/6flyMEnOX16nj03XMu++x/hDXc8h5lbV5i8cpjWkbOsPX4D+w7ey+QtdarD89z0\nijq6cp69d5/k9OlBLp98HdqucXb+LIPVTey8sU61soDbtBc7mLM87xgcfiWf/sj9TFbeTGP4II3y\nEW7fU2bvPYvM+y3UTMw3vvYZpFX0r7ycA/edZffgJCv5ObZft4P5BZibP0MiZtFJxNLJJdLFDD89\nQc94JkfrHHriYfLBpykPOFLRIWlUWVt29PuO+nBMY2KV8nAJm1hUHKaXTpoApmMLEhJdoux7DI3X\nsHlOe7VHt10i6o3QOq2wzwyh00lmdiZEtZxS7XI2N8dZmjtLI7EMlBv02o4z5w7RWjpGWQ+Sui6d\nbg8RhymroYvUmkZtmLqbQMfj9Dsd3NI6gxXBoK7QcymprpD4Jq7fZNvsOGdOHEJHgzQGm2xuXgtS\n0+MhpOrTczWqyQL9ZD9dL9l10whbupO0jq4i8gzSBmdXh0jGKjz+9F6u33YDK6snyJc9l01upXdy\nmenBcc4tAVlE6i3NWkIuLNWBCu32Gq1ul5Wjx9FJiS2btrNiU6xRLLQWyJ3EyRTn2qQuoxSV0Rk0\nJxssrC2jfcKoHCHrr9M5s8TMGFxxZU5zy2FWon0Mjp4BuU69YcmjdTpnOmy7bJSlzhI9t0CU9RHV\njKSsEMZgZQpKYLBoWSdilcgYMr1GeUIxPGFZ033mu2cZnxljaLGCv7fEWncr544ImgOTXDO1m7XO\nCkvdue9rn/9gQEMXmoRCIBeoSZ4IRVYE3fVzR6dr6abZhc6zFBJPOHijQsh50aFpI4F5o3Mogj+8\nCA4uGo3Vhj2DN3Jk7jEuq17HkHiGk6ubOFXez2R+GX25UNArAp3JFxz4SzvTzw5ju+gaBDwLhDj8\nBdH4xbwEcck1+gtFqS0E7V4E3rEtCjwdh65mlve4mBh9sTu+cQ2XdsCV0sGGsQjhane7qEgRKUWv\n22WoPEAnneeB/X/Fpz/9ED//5j9m7sQZnv/i3fzGL/wSX/76Xfzhu17P9PQQP/fyk6zXlvnnv/0y\nDzz4Ob5x/5d5/OmMX3v7r5KOCpr9zSydSinN5gwOxBw+u5+nThxjMJNc98rn8KlfeCfN//Tz/O8v\nvI+869n3sX34Qxb5Es973nobr3/T67jnwa/yO7/5Zr7z1S/zUz//Mzz02afYNn0FU1tH+fyj/4uv\nfO1T/OlvfZCV8iLnDh1h+LW72Tk5TL+7wG///h+z5s/wW6/7Lu3vtLjyPZfjvee2l36c6YUJnvOO\nO3jOc5/P0Ow4q4t7abdXwNTI5DqlpBY6dhR0IBfWUNCBWy5qJ0JGSwB0+sJ0awPsbYCBDXBwUcfx\nbBrdBTrdxlMU4sL3Xvrnvxd0XBCQF2GCG1MQxIZWJ9iQhnyLmA2HKiUluekT6ZhVm7FjejdXxhX+\n6eRJtuYHqcbPYyY/y2dPnWR2bIjTi2cZHGzS7vYQWiL8RQAkhSjYXaHI/GG9IiXwuQGtcblFkwQu\nuZYgPcIFXr0MSleEL3IEVATCIoUgy7JiKqGIdCkIZb3Gm0D30eXAhTc27D3hg0OUkjJQG4E0c2hs\nsPwsaC4egXAiWO6qMLGQSiNsKFylBIEiUpoUE4o8GzQWwodzJM8dyoHJPEQOoRReOKJIkvvw53CQ\n9jPKlVJwgyrSy/PU4EQ4S43ziA3dkCfow4wj1sF2NGgEijWkCtcjqdBahKlKaonLyQWTjigKYXyh\nYIVIJ6TdDpGOClep4DzlCXqQtO/xwhST2xgJwYlLeKQorFlzg5I6mGDkedAyhPoVXAATWkuy3CJ9\ncDjq5xabW3QUBOFGBuGxLeyDVRQ0B1JFxQQyrNM0DbRUS2hKRSVJHGk6/RScukBJQ4CW4XMiNBMC\nGDQqnKdaCvIsOCuVKhEyCh1aZ4PAO8KT21AkmcwhbaHpsUEzhBDF1D1QzYSW4DWZ6aO8CrSn3IRn\n54KA2xuHTiLcBeAbLJQRxXuRvOBeJUUQbRsXKFyhqRG0gEIqrC0c6awLQZZCFHkw4bza0JfYzKFk\n4aYoCG5ZIVkUm4d9hrfkWaBnSsLkF6ELOmAIhizJMlnukZlDlhVpmpHZH46/bWVLhF5zuLxN3stp\n1iRuxSHKbYZGzjE8vk51rMLJ3DG+Y4jWmSWG1ADxWs7ZE2epmVvJbIvqSk4SOdbWTzM98SK0M7Sk\n4sFvnMM9atm6a5ThsTKxOks8NMXJk2cxUQlrMpTzTNYvI+tZHnr8CIPlhIXljLRbJUsNSbrMQvc0\nwsd0O9AYGeXDH2qzY+ub6J3+BMa2eXTvnQg3xqbJ67j+RY+xoI6ydXYnZ4ce5/z+HbTKBygPHcfY\n4wxfJRk4OszefWe4qjaL7W2hEY2TuRVqM0uMzETMt9c5f67OoPoZPvuhFg/fO82V4zAQNymZHgvH\nOkwNXsnq2lnG9E4aY2WeOvgI//bVTzDVGOLOO0/yoz/xsxz+0mne+HOv5957/4ZnDh0kTdcYu3Y3\n9xz5LhNb6xw+9ggl3WNyZ4cF0aE8Ar0O9HsR7XaG94pKPWVwWkPFIZMKDoOQOT6My9CxIBg3RERJ\njorXkK5K1Lme9OQw3XXN4rnjLOspRvQk/d4K8eoi1Shn2a1TGqjSaE5Qi2PK44usqTbCl6hlDZQb\nYNmvU4rqdJVExim4HO0ihBfk7VUWzx8ml6us6wprvXWGajUaqcZEh3EsMzAwhJdD2MwRl5Zpp8fR\nWYsovhzvcpRIyf1+KhOH2NKcJJFTyN4wi80K588aBhplUpHQSS0DUxOcXTzNeLXM5Og07bkVmrVN\nRAOKEwuTnFp8iNFto3S6dVQUIZIyHdfFYhkoKdL1ZXrrDZyDlTTF1TWqHYyBMitwUUK1lFCPE9Le\nKvW4jEyrrK0uE8klmlMDjO72zN68hprtYctLOD+AcX36cpGhK3pUxk9Sii5jLK2yulqh0dwMsh5i\nG7Sl51OU8nQzIO8hozHKQuG9xqucBbGG9gMMlIdYWYCFIwrX3cHKOUmpvE4ky5h+DZHXifn+GhI/\nENDQOnTxrQ0ixCiKSHs5wgdKRHDQiejZlJ73SMKHo8Wy4Q4k5cWx76Wcec+GE1QoBFUhOEQJSlGZ\n8+kcY9NbeeLEV5mcfCHn3ecY81tx5RSfOpAa4TaK+QCCQreNf1cAbvx6aaG/8XslZSA+XeJC5Yqi\nFdzF7yd8PXDfnw1cZKFFMcagtSy63/JZxev3akOUCm3djUA/FYV0WiwgJK3OKpsbN/KZz3yal7/g\nDm66fTsraxn/9vEvUOut8a7ffx8ldyef/NffZenEw/zsaz+KB3ZdexXves87md20nXe+/b3MnY3Z\nvgmOJfsZ7O/i7s98i3+98y6aszFqssLoaMwffPVDjD7V4ebdf4Vb7PGMOs6O4a08/ZFHETOXc9vN\nL+WFz3s5f/Xf/5WZSoWjj52mvR4xsqnBP3zqbzjfyfnNX/sdzpyb4+ic5fzdsPNlm9jxClg+1uav\nP/p+/vxv/pJ7/vHTvOTXXslf/tbf85qrX8qxQ3PM/s4Er3nRZj7yz5/ktltuw0qNdJLNM6OcOdEj\nrhu6fUAGC9MQdBeoJaYo4DfC8DburysS3WFjoiGJIlnQrvJiXaoL719ov16yNgIV6tl6jkvX08bv\nv5d+VTBNinVYUGQ8QRQsQvKzKzr2AolSmsy2iG2M7c0zZG7gSXeGt1z58xxbOcs2f569Z1YYHCpj\ngTgp0c76CCz9wsp0AyQX0ttL/j4/HOqUVgKXGUShG8F5IiFxeaBSJZUYAeRZGrrCzpOleUi3LvZC\nFGvSLMViEBGFOHXj2chA81E6iLYtaB3jfciuSOIkNDakRkgdAIoNjm7WhWBMmwc6ivNBiIsPaeQI\nT6SK5+sdUmi8gKwXQhSjKAoZHtaH/epcmMKkwX3FG48VIY3dFfkItijwJQJvBShQIqKf9YqCOzgC\nBb2WK+yZZRAIC0mWGyIlQ7r6xmQGhbMGkxmiSBfORoJeGlyajLHESoMNltnOhADE1GcBWEkVpktW\ngA17KSpFZM6ihCftGzQGRYQwQZ8ikCEYT0eowhnJOY9yAl2cm8ExymKsx5ocWSujVESUxJgs0OJC\nMJ4PORE+JJkrJUi0DpauQmKKgDqsRzhPbm24d5FAeYHxOZFSoYPvgsmAy2yR+aGR3oNzaCnJc0ue\nWlRJB5MRHQetjtCkaY5XAi9NsCz2hEmXdYF+lYXrVAK0iIq8C4H3EuFDdpJWMcb0sbkPwAJX5Nek\n4WwXEu+CJkcRGhVxEpNnhizPieMkTO+ER/nC+coUGTxZMLoIE7sAtExugq7IhUTxKA52bZGKinUW\nHLZ0pFAyCoYCSpMbkL4IupRR0XQJ91/rMqnJKYswVYxU/EM5K7bd3CM7dxc1sZmo0yS18wg9xuCk\nY2T3HHKgg9V1GgPn6bu9NGZews7nLfKdT64jV6e5/MW3ce9XvsmmsqXdhcNnq0yNgKvVGGAzdbWZ\npfPP48jRY5yfTkj9fgb1FZxonaHjWkw2Jzh36Civuu1Wzjx2gs64YJ4Wm7fVOH18hc3N63l83yG2\nzm5j3zNHmLnsKh68t0TTXMPKuXM0K4sM6hfwTP9uBrcO8dXH9tJ45AgTOy1+83ewVy5y5cB1KLdC\nr91n03CDZ9bW2b3nWg4fzuisj/DgAw8ytkOQp9vZeZ2hu5YSKU1nDZ74Tota7+e5buoulk89zBXD\ne9j30GnKSY31ThsXD2HtKlknIypLRL1Cr+YRvQG++/gJJgYq/L9/cCc7Xngbjz7xWRoNzWce/ALT\nO3azunSccmWR4ZEWc3aVfChMoJM8Il9TlKmwnjlKcUyl2if1PUQaIaQjTgyJklQk+NjhvCBvZ9Tr\nGdZp1hYNIs1YPNvh3OGckeYsl82OkS+2MBxhZHYL1cmETVoSC0HaOQ/OsX33NKWxEY76HuUlRdrt\nMaIivEmI45R2Jw3rPHdIYWmni7joPJUazFvL6OgUTdtmbEKQxrsY3zyNqx9haNc3KY09RL7pOKby\nIpR8QaCFSshNm4p2NJst1swyRh5Fql3U4m0MHpjg3L4eKkkQ2uJKZdqLLUZrMUhJu7VIfdMoc/OC\nqbErOL64j1a3TZ0MVW6y3DIYU0aT0k17rLlVVo4fJi6Poyplzp0/gciXGW2MMjm+G2sUtXabtJci\nkhK276iWYkrDmtntQ+x6cY2dLxilN7mXdd/FsUremSKpazryDF2fUh6OKXmLaAww0CyT+wyRZYzJ\naZZNB+E7dEyfUlJHWEXqWkRas+xArUVUmeR8W6FW6vTXNAuHmiw/pcnXM8aGLqcUDdJqnSCqLyOS\nc9/XPv+BI0CVCt2XDQ50pBPQAhNlSJXQ7cNaOyM3Hi3D+FfJDQqHwLo8FG1IvLABFRMWqsAXNrIX\nwYA1hsQn7Ft8lNvKL4TSZo6tfQ3FAN562tlxEj0C3iBEkWJb2EBeSpO5FExcCgouLQrDf1MI1C99\nv7AhLQS1BfsdCni0YWW7UVBeFBNfqgUInOjvFaVLeZHegg+c8SztI+JAy5IISnFMP2tz/94vU08q\nXLZrFz/64t/j3i+9mzf9xE9z83Nexde+8CD/+PmP8i/fuJ+3vOzH+ck3vZz9x0/yvl/9KaZGr+cX\nfuY3+NePfZHR0R4P3O958JEjrIh/4ciJ00zWI059K+ID7/8gK19aYfS5A5xamkMuCZaiLtNrl9Fv\npux+w7UcPLiXo99+BoAjx0/w0h/7RcZnB+jrz3HyuONVb3sVnXWYmJ0lzVd49ctn4F1bWDsiWPEn\nUdds5ede8gb+y43v5t7oYVYetUxcezsPnljhJ154E+f+ep4HDj1Ot6157ZvfyGff+AdUGm36c+Mk\n5adIexWESou7D/giZ6AArRsF/QYlTUp5wfHr4kRpgzYlLwEjF9/fEH1vaCjC47mYXL+xji7V+Hyv\nuPyiAQHP+hp4nPAogsuUQoKMg05JWJxP8RkYvcaWseupROdpZKN86dCnqNV2MySHkY0OSljOL5yj\n1qjS63ZoNJrkfYMVgZrnvP8eAZYv1ul//EsQciiyrI/NJcIWRZyCNDfoXIFwQUCtJSiHiKILYC50\ni8N9V0IFGy1TPFtM6DAX00NnHVk/J9IKpSUuM+QiTFHxYFOLzz3CWqQOYFRLicmyYK+aOxQ2aBBM\nEORmeY5AoYRCF4DNmuJccTmKUExrdCgQpQxCb6kCcHGOpFQmL2xycxMoXJFWWO9CHkQBfBCQpxmp\nc4F6U2SCgCRPUyIdMifsRtPEiUChUuB9oBNZn+OtDaDKOVTQ0pP3DaKgNjnvSVTIKzHG4EyYFpWi\niF7WL8ITbZg6lyJ8bjG5D+L7zCDiONiGW0/aT1ECfBjj4qXHC4EzHmsznHFI78PAgxCaR88EB6zM\nkLui1aQ0WqgQNJgaoijYLhVEIZwBKzxRVMGanKwfAid9tBGvV+x1VzR3nCfWAjZcnGxwT3I2mC04\nY8lzQxx7Ih2uXfogWPcuAFcnPMI5+mmKEBodhZyM3AgEDuFD1kcUacBj+hlGBgMSpwRxOcYah3UG\nJUJauMFDAaYEAu8kzniUVOTOgfW43EEBJHSi8c6GaYU1SGSwqXWEMEbnwAYAm3sbzCUKDYzQHmxY\nqyGssKAdAnma4wv9mvMW4QOtKs8NkRKYfoatROT9DNPPfihnxZx8iOFdKcP5Vg4eMbTSNZLRaUoD\nq5ikR1v1SM/O4x00KpOUd9zNub1ghyYYre/kwUfuJ2ksMDm6gwN79zM4NsPoeJ08eYr6cMba6S3U\nm1sYmG/w4MNPUJ18HozHnF95iunZWdJzlh3T43zuc/cwZvEYBQAAIABJREFUuTzK4M5ZNk2kHFo7\nhuuWuOsuSW9pJ6caVZqTs5yZ28qdf/FlXn37q+nO/AM/9hO38NgXl2kdHWOxW8b1Yx78iuUq0WGq\n1GGkUaPXbKHzBnTG2X9+nvEtdfZ+6wkq1Zfz1MFFXnh5i5X1eeJokHNrHVDLZIuX8cS9x3jkKznV\n7geprkXMTgyQd58hcxO06yMsuHXoWCplx/rCGZJKjIs0x5fWGB+s0Zwe4am9T1KfHiI9Ok+lUiHt\nr3NqboHb73g9Tzz5MOeOn8COahpNTbetSA10lxJo9RGdAZqliHp9FZvFaJOSRjlCCnKvqAuJkJZS\nWgYFYqBPvQ70IF8u0z4uyFs5kwNj1OLNqPVV1uWDbLq+xMytNUbGt4BK6feeYmHpJAPVbQxvr3H1\n9hqDm3fSerBL6z5BXtOst3qIJCbuO8gUlUYTY1J63Tl0tUynlNI0jrHuKiPNAXbtGaE/bMlYJi09\nxejlbSZ3NagkN2HEkWBqZLejPMS6Re4yVnwDEy1jfIb3HexYj5FrbuLIwSM061Podoe01qZdTzm7\n9gSbRobouxLDCJRrM6hmmWneyPL6CaLBjPW1FTIX08sEmTdkeRunDVqndLvn6a7ME6uYgcYAJV1F\np4KSTOgbR8fnNPISmyohc23HiwYZuHEf0y+bZa7/NJT6pPkyOhLkvZPIzEC6CVmJMVmPFdEhVqP0\n1lKUzvDWseQOgxrGOE3aTdCpJl2qYp0kd5LWQp+G3syZpRla83V8y7G2krN4IqW/AJtGr+baG27g\nqQPHKVdbjO5aZ0nt/b72+Q8GNC6IYi8t0D0WC4RiwvqItB94pqIo+C91dwpUksL73Ib3XRFvK4jC\nr1IGK86io3e6fZI3b/05vrbwKZ5f2sOhZBDXOclKtETDb8OyBF7jfIb34kLHTFwKGC4BMBsTk39X\nIBaiTcFFPv4GJLhQyxKqzQ0ev5AF7xhxIWHc2uBWo3X0LFrWpQBj4xo2Xhuc3kCvobD0VGgUJjck\ntTKnz+dMT2zibz70P3jnL7+DD/z9b/Hhf/hn7nr6Ae75kuSz3/wIP3LTaxi7Yg/HskV+749ez76v\nLvH+T/wWk6PX8+EP/wlv/snX4s0MHQ7TsJP8/jt+C+Or7Nv/BRr5AOnVKfOP5TBd47vnj3D91jHq\nyyUQjntOf553vPf/4/rbRvnuowc4f3qOex++k/LjC3zsEx/kY3fex+ve+DZuvvYG3vC621nu1SHp\nQTtn4UyL7bfN8PafeTU/9sZfx21LuTm9kZMn53mNH8W/d5a1tAW3RNz9vsf56N9+hIfv2cv0zDAr\n7dOsRitkRiN0hvShqxIoeGHd4UXBpSZoIhBFhsWz6VDuknWw8UQDsLiU/uQuAMmwdvyFSdOzgCE8\na23/u+1S/EsSbFel38hyCTvG22JKJvWFdeZ8cLCJnOTqsQYLB85zfluXt079Bn9y7DeY6m5iIclo\nakm5nGDSjFJUot/uhfsQXxS9h4UpubiKfzivfqeL8mWSJKKfBaegLO1SqtRC/oC0OBf4+I5gBCE3\nwgyLqWewjPYkJYk1NhSKPkerUKyjJVJ5pIKyioINq5LIJNiaWu8R1iCFDqJzrQFDJATKG7AgRbAE\nVYnAdixRKUIJ6PcNQhg8Oa7Q72gtggOU9EGQLXKytIcXiogIX+hMUATb2aC+QAmFUh4hg8BYUrhX\n2QCUolijhMG7ENYXQIEh0hKtBJCjpcRLHz5UvEcrcLnBWRNsXQuRunUO6RwIgxIOIkEkAtA2uUNI\nTyQFGBBakGYpxga+dTkOmjmBIdIB0OQ2iPaljNFJ8E1WUoSpkxBILchzoNDHKSWLSVpYcTazeCxK\nBU1LjCAqaGShEO4h42AKICQofZEGJIp77Z0jNV3iJEbqAFZ1HD47BOGeehumFMYbIh1jbI724T56\nGwJctZLoKFAVZRT0GmkvhBNuhD6KWOCdpVSKEURo7RFxIYpXtghjhKzbR8g4BAqqkC3iHHhBeI4i\nTFYipXAOKklEbi1SKGyehdwQFxoOOiY8l1LIfun3HUms6Pd6ISfIebSGNMtR0oMTJDq411WrEV6E\n96WKyLs5UrpAbbMGGUUI5dDaoURoQkhh0SqIzPM0I4pjTLcfcndiRVyShWD8h+M6ZZM+NAXL5hRr\n3QFKusnps8coN1cYywXtniNtl/BekdRyVpYXmZio8cjKEezKCGPTTS5/ToX07GPUZxdYz87j60+w\n89oBopLgtOxw5mCKrU9iozkmpmeJBxWL645dapi5fofssus5diyBk03233+C216+nbn+Cpt3XcPs\n1Mv4nQ/8MV++8wu86z3vZtvYJLtmtnL6+Bf4ifcMMLH5FJUnVhlcGWRhZYVIjpPmY2R+Duc9kcjo\n6JPIaDNHD61SKY9wcrGD8FMcPHaIa3fsYOvkyzm4uML117+Cvcc/zdknr6R/5Kd45Lufob3SwfIE\nE4OXEdem6CyM0xNVzp0/iRrQ7No1wyN7HyBzXeaWzrJ55zaGGzVOL5zgiu27OHzmGK+45Uo+/81v\n0O91qVdK7Niyg0cfvpd7H/0G1988THVIst5aJDYRvTVBvqYxXYfLE2Jt6LVTlo5o1ICgPKigCd1K\n0ColJRhUCi27DNQ8JSlYmjfMH45Ry7vx7QpLrXPYoQWmrjjM1VsdA1sWGd5+Hq8suUvpy0OMjUY0\nqxnr/jClsQqz+Ra+ffd38Tah3e6wtrpKOR5Fk4Ko4lKNsR3a2TyVWkK3n7Gp2qDsesSbNJXNsywt\nllBiE8YuUxk4ion249mJEB0Ei2S+SUlLvM/JXRetEyDUOu18lSiaZ3pLwrnNDZL+AGfynMGREVx/\ngdbJwxw4/hiTjctJ4i1EImJ8cJiZ7jXMHztBJ2nh0zVUbQQZl4iQGBPR7i5h83kiXaZUUjQbWxiQ\nTVLTIdaKKM7oZQvI9T7Oe1RSQY8usvnmhNLVK7RL58hEFZ9LpC5jTCPoEs0K1lvW+m1KsaAZT+H6\nJVRfofo7WFk+wcn0G9SnHEkyismHOHWoDGvjpEslDux9ivY5RzNqU5aOTkvRWnMMNWssL/TYNjPJ\njm1X8JWv38tP/9xr2ffMIwxctoouLXxf+/wHzNHIMVajIoFHkecGLwje9ZELabIiIUsLjYQI7iWh\ncxlTkI0vdpILMWHgBAcxJKLgtxadf+sdW2qb+eSpj/GO2V/iQ8v/zJXzm9mvF6gzTpotIROB9AYX\navRQpAtVJPleDOS7tCB8dsEZnE6+l8UeUpyD7z1FkemsK+xIRSgiN6hQbGTBiosVpr+02+0u0Wv8\newqVkEH7Yl1Izk1dHyV0oH9Zj00iUI5Of5FSMsAjD93NlunLecGtd/D8F97I3/3VLp5/7S28+NZX\n8ua3vIXUW77z+FP80d/+Kr/49l/hzDHLjstupTnWZG0l5dTphHe/+1U8+liH5988w9e/+nXe84a3\ncO5cmykhqW6f4qXUqO0us//v7uOat9zCC7e9jit2TfD1jx7gv/7CAlqtc9Vtr+bWW27hw3/7K7zr\nl36TO15zB9V2hwfu+g7XvfRWPvNvX+K6517LCXOej/76x/nnT36HPSOX063cgN4as+lyQ75Z4j/X\nZb2jefU7ryTtdlhePs9Nz/8RWktf58EnvkhZPhenFkn0VrJ8nVDZXYSBoYMfChMIxcFG8voGTe9S\nF6mL6dwbhfn3WNmGL154Rpeulf/T1GtjPW38/zbW3EY4pPcGJ/UFsC1l6PjiII7AITHW4KTHdnIa\nM5OIc3Xk9oSbtOcPD7yXX7nq7fzFIx/lis1XceDQo9QqAyHILNJkBI64tWnhr78hSL+o2QjZx//x\nr8FmBURObh1OQVwqIboetMGLcH1aamyehyJcC5IkwvRtoCE6g1AmXLu2SGFxGKQTJOWE1GbBGSVz\nIFOk1ORZRqJLYB0qsmgdrF699XiXBWcr4UgiiU0dpUTh8hQRSSINWRyKMecFuuQRiaFckuhIk/b6\naB2T9XOEAKk9SoMTHqk8kQrNEiU9KEFclpQSST91CA2RUGgZ3JGsscgkJjfBjlZIgzOGUhLE0chw\nTijlKUmJcwatIDUWZIYuy+C4pASR18hIkNs0mGt4S1KWyDhoUZzzZM4gtEL5cK1KOZy06EQgY0ES\nQ7cNQlq8M4BHaIP0Hm8NTgXQZfHocuHKlGbIRAWNhbEILYMVuQ2Be9ZlxJFGadDK4SOJMQaUQ6ki\nNTyOiCKJjoM4HgJtTkvC54GH3ATnlV7fEyeCzIJWHk8WCnTvSWJNt2MQ0qGcQ5ccMgOvQOQSVfJE\nBDcnyFCRR2qHBaRyxCVN2g/NoKgUqJg6sVibYayhrMtYBF4FXUUcB3pjGL54stwEgyolUVLhlSVJ\nNCYzYdrjTaAP+yAWt1iSUhRE5NITSRWcp7zAY5DagshR2pNUJP1+hk4EXjpUpHC5IY5F0AlpSe5y\niESYhKoQBuisxQlPVFIgwjONlUQKi8eFYNg4AunQ2oepUdlj+ynWZOiES0xM/mNfkajTWq5THbBU\n6yvI1m6mp3PqwysgW/SydUy/Tkl2OPJMh85ZzcmnupT8Hrbt2MqaPUh550mysf2M7JTsmXo+XbmX\nsSum6XQGiNvnmCgPM+y2YtsxJw48RjdeYSy2kLa5dtt2jt/zCFtnRugfVIxXXs6+bxwkL83SPl2i\nWlrnph0v5+Mf/xqd5THi8WFy+U1+9A2XUx8+Sys+TXV3mfa+HhVZQ6Ux1z7/Dlz1z1nuLlJKNjN3\nqsVVM29i731/wrVXDzJc/0+sZxPk6QP0VyT3f+c0vSSjtb6fhXaVztFhHrv3LqZGtvDU+X/i1Xtu\nZ98jj/CaH30hJ04eoDHep9M+w4i9jJGJMicWjxBVHbXhhJWFM0jvqVar7D34CFv3bOXrd3+RNO2E\nor7XZXlumf7JRW68sUF5sM9ap8tANWL5aI8oG8P0I1ye0BUlhFxmbTGjc7pMvT6OmlgjnsiQE+Ar\nJYQ2RJEL1v5W0V1SLD3VpH9mM3bNouJDzN50lsktZSavHkFV5okGPd3kFFl/hcZgk3KtTOQdUR18\nBklVo2uCVruF7NZY7rVQOmZ1ZZW42kcYj49qLC+fQtRyujYn9lUGbACjV75iM4fX1mktxaTrTzAw\nldDrORqyglZ1PJMYF2Npk3mLFhGeDMMS3kwhdISRHbLsLL25+1lbbKGWDWlqyEUfWY7IEs+p1eOM\njmzixJHDbN1yFd3eWUYruxgqPUHPn6KbtjCyR1waCvlFMkRCaO0ZGhhkaGgIl1VwvksM9LOU1ZV1\nvCozWIZG3VGpNZi5bZH6DQ+z4OdxSxXqjVIRxFoBX8ZFsLhykkq5AbEjQ3O6e56S7JOaCQbymzny\n2Bhzaye4/uZNnJt32N4odmGWI0+s0z9hOXqojF2TVCNLOTpDdaBNpjPKYopNE7OUyiOkuWbbNXXO\nZf/G9tsSqttbHD2//n3t8x8IaIRmu0CiQQpi7fCJx/qIXtcgI0h7OWlucRK0kmFERfB639BpuELA\n6UMNWBR1hT2skBjfRziNIDi7LKXzXD10E//j6T/jx3e9ie8OPsHYmTFyv4JJgp2l8T5wsG0xrSio\nGuFAl88Sw6rCChCK4rNwUQmtuHBBG8Ju58Lf2bq8sF10KKlDR9IXri+iCKkCHDaIWgsqld8AVyhC\nXkjISAg3018Qb8riRngvcSI4otg8RxKFZFclSKImy+1VsD3+4L//KYcOH+RLn7ib237kBkZqI7z9\nne/hda/8cQ4+fYid06MIIfjIR7/KNdfvZmE+5b/+6Vt5cu+jnF1QjA7GvGTXTbRP7mXzYJNjZx7n\nSwcO0u7vZVhu4VVHNnFw+RSbDm/jmp+6hW98636uuvIKnnzmAO968zs4fw7e/4Hf5jOf/ghSHubL\nn/w4L3jVj/G617ye++76MIeOH+BXb30/W7ZK/tv/89eMzGrSbIgrhhT/9R//nhVd413Dv07jeVMs\nfv04U6/cQjXx3PS1l/HUR/6erdu2ce7QKa577jiPPtMkc0tIhulnyyhRw/s+guD1L4RGFWFXCImz\n9hIgF4r9OIpDoCNccAUzxqAuCP4vUtqkVMUErJiOyABU5AZglBfBS5h+FLkY/uKkL4jGN+w9Qfog\n1tiYjHhv8V4iJeR5mAvqKML4HtsGd7CyusC2q5rcc98X6Qzu4baxa/i3/V9msFRiYXWepFzF+hAo\n1017SDS5C95Gznqk1BccgTayRdz/YeryH/FK0wxrBbXhKq21Hn1toQJO5USJIHcZQhfi36SEMXmY\nJKiCKuTD/XBekKmQQxBXJP1ejolzeutthK/ipSFpxFjj0VEosKXxGJ8CAXzJ2FMqJaTdFGMdyAgT\nWaIoomdzSiVJlx66IRBCk7VTiCR9maIALxMoe0RkyXo9KpUghpSxIstTao06WS8jSy2lSOEjg4qg\nT4+OTylHFbwMdtiJ1GQ+pRxrsrxPFCdEUmJSR6w9xmYY79AlSTfPiBMF1mBljkwUHdOhFJdDLoSC\nSEsynyFKGovHW0/fZESFLsxLhS8Dsca0PU4ZSo0yabtPjz5ROSL1BhJF5jxxSSJEcBF0kSeKFBkZ\ncRTT7/cZqNfIWxl4j4gloujGO2GxHlCGcrVCLj3G5OiSQihPbrNg+CotA40qeVuEDBOZo2JPP0uR\nURRE/pEmVhLhLDbvQZIEKqkAEk9cVjiX4iz0Oin8/+3debRdVZ3g8e/vzOdO773MCQkQxjApyKg4\ngIKWM2WrBdIOZVGrtaqrtIvSriqXrdWtq1vbsq1Wm7YLpBoLtaoWJZTKoEIaQQkBggwhYQiZSF7y\n8oY73zPv/mOfF5+BQICXkOD+rPVWwtnnnnPvW9yd/Tv7t3/btohVTuDZ5JZCBULu5mR5TkaGLZ4O\nNFSC5bq4rs4jUkrIRZFKivIKkjjB923SPEGcArtuo1KFVbUYdCNsz0PlQkyMZUNKoUsH23omWxTE\ncaTXDamEOI3wXAfLt/ACizyG3M2I4j6+a5OqjKxI9HqlXG9sm6eFfjjn6D1XcisjsWKwMuyagJXj\neHpGCpReu5SBU3N0sOJAnkdYjoOKc6J8gBs4FFgMsgjxBE/KvZ0CHZznKJ1j72Z4rosbWFihENaD\nA9JX7HxUOOfsk3hg6iHiToRkDcJgIbt2rOJkd4Sp5nbcNCFRBVOjR9F+fA7r73qAir2Y2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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb75c641d30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . . \n",
+      "Iteration: 10\n",
+      "Weight Adj. for Content: 2.79e-11, Style: 4.13e-28, Denoise: 1.25e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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VqCBiMl3gvGaRe4rcYV2AqSoaY/FCUNUZo27I22HDydkuh00Hs9CMVU7sGw4byVAramdw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xvH/vlGp2pDXgrywjSG71SxWCqWuWIxzVktEqqsQiuFY9mvULbNuIYxTbC7WU2oXFiSBhzVdDCM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wVp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DrzGaclre6cKj1i7yWoJw77dw1g/jd+VozPFZz3PKgEqZ+zecPE3GwhtRlxWeKaCp6tokYW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\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yMUsLVSJjSLfkcNormAZlwEPONeSKjK4ItjbHXLi+wWDYpyRUJL3P868sIM2W2H96QGYq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Ojy3+XRo7tYekLvQEV2oJfewcgjxqnLyqJOYk9wCi5OCN5gSmcPLGdAOm5xeD9mPwww1RorV2JU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ZvZ9xtBjQ3WyxcXGTRtOENKN33qPIYmRcsf94yN55l6LMSMWEQLl4z6aY0wquRXSaOjGHNHoF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f+TJe8QNqKwcUyytEypvUC5sohs3DOyPGnotbe44//t4esXMdo+yx1nqCxcV5/iJ/k/vb\nbfTCGc6cP8f8pQ2m3KdgVRFygN++yut//DE7N5e4eDVg80rGd759QjrMeHR8RKFaYJCc8Mm1U2jh\nr5Ku3iApnLB5waKbdiivtVCqRyjlHLNgoxgaR8MhitTZ66TUGgJjCiU3Rhpj5i5KjMIxiTrh2dcE\n1dIUUxToyZAMD5lF6Mo266UiQ32eE7+N4+QIHgElNEdl8+kFWu8dctSpsb9vc+NaTGoFOO0Aceo6\n9pxL9WKdc1kJmbc4fOeXePP3/xFPf1ln/rkGiTIg6anYhZjqmYRBojPqh6R3XkEeQzN6F32xS/+o\nQH/6V0tJ/FQHjVxCkmSAAmSEUYoqc6SYyczy/DOuv6oiVYgSFT/OMbwM1zbJlQRTkyioOKZFksQz\nClWWo2kgpILQDWRuzArnigAJucxRFRNV1ZFpMCNSCRVNVcilRBcqqvqZcwMJMkNkApmlaFISydmX\noSgzdKmqKshMzkrAmkKepYRhiJLmqELORHxahqqJWWxGBsRhQqNhQ2ZRLlhkaUa308YumKhCo1qq\n06wpKEpOu+Pj2jZf+spZFhdKvP/pHp/cO+bGpzkfA5MAWq1FfvO3nkOLQl7/vfcpVk8xnnbQpAG2\nSpJIIkOghCnbu7usaxolJ0IoGlnWwKQxy5knQ6DHE2ur7J5bxu8d4yZT5gtLdCYxhlHi/KWnqDhF\niqZNMJlQcy2yfEwt3SSbBuwf3iD0x5QVg3QwJUoC7JrDoHtAoWzTD0fEesZkNCU1M0zDIooCzDjA\n1CBH4fiow/zCApPhBFPTKLouvV4bp2gDRUbTCYpmgmbgui5JPiOqeIFPnOWoWoFGqU7keSiWTnc6\n4Zkz55imEa5mIYUkS1JUfeZvEWRce3OMNO6jsUHDLZCLmFxI/DgilwJNhNiqDopHng5QRZ001UFk\nHCYf0Bu/z6O3HVq1pzm7+Z+xcObPKVQeEqcSTT/EEFUyYtI0BwEaCrqYkdA0VfvM8WJAliMSfUaa\nYgZNUBSFLJTEeYY0BaZtkiQJqqqQxym5ohCnAYZhkUuVXOYIBbJIoMicNEiAnMgLKTgm43GI6xQY\njcYUHJcwjFGZkbIUVEKRoiuCXFXRDYtMVSDTMEyFKAFdlWjiZ4O3LToK09BnKFJazQJ2VMVWC0ir\njKoYHPfH9EYjKs0ioTihd5yh5gqtWp3B1gh3VQfDIDVzrIrFYGqiH6pEqYntNFGNMuWSiiZUVFlj\neKzQH4DpWEhDJSVkehxjNxOcTOCUBGvzDSqlOgdjk0KhiPAUBg+gP57ijwLshqR1SrB+2qK1JBju\n2+zfEhzfmbC330PKMhfO1lGWDC5VUxZwSMh5tH/E3T87YjAJ2ajPU68rRGkHtdtHb4157d88y7mV\nEaroIqXJlZbLYTbCcdtc/lpE0cmoOEVOPk0xC6v0hm3Yj5iWRhymbaxKlWB4wCSaMO6DqRo0T5UJ\nxBQ5mrKglJgeWzz6uItT7rOwMkdzvsrS0jLthwG3PgpZzR3SYYBrjXHnS3xueZX1tVXu/Wmfm28e\n0jseIno1NC3h6rNnWJmro3ZS9Cwi1XbRH4TE8w/RihnDskFsqHS2MybDBD0tM9kNGexlBDsx/n5E\nsOcxyD2WvlbEUSVJPGF/eMxc2cKLckZdD1OvUV1WSaycajlkeDKhEx6TJCq2W0eqkma1ga7Co/0R\nwSDCLTeIgllMt2hYLLCAflIi+iDjcBiy9pRG3J2QFXzcLOPXf6mB6PSoaC2mRZdqcYlA3sNQpiyd\n0ejYHfQwJvE85s6eJ103CN6dQ6qnGJqSXAsZ3brJ7vEW08Rm1B4zuAFvyttcOF3jtX/3cwjxmJYb\nENkxNVUwER5jPO7JAaMYVLuKobVQJgFWJFkRJaRSZSGsYukGnZ4gn2rMVy1IQ3q7PpoTYV/OGFcy\nHKkhBByHEao6oneYIvwOWSxxV6rkWo4+12Vt2aKghnhHDs6CoPMo4e6dHpnW5eqrJUZyn01jSLM8\nxWNKcMHAnVbRKhrlksr9u/ucHzjUl+sUcGk4//87NAA01UCML3P4oMO+3GFpeR9by1AsiR9P2T8M\nEY6gZArMPYt3fydmYy1jsWhzR3OZX5lnfwjF7BSd2x526QB7RcVWenhpF70EuDphmpAlLmp8ltXG\nJTp3/wK5lFIrxwy9mPNftBHDIXtvXGfRqvNWd8riV7+IOsq494M3UOc9PAGWa3PxpYh/u7XBH/5P\nMY3yBW7v3UPNNA4fCL72ty+wqz3EMhQ0mVEywNvzuXw+w/Ju07k/xj8p8PBdj4r1PNXyBUZCwbJ0\nzi+dZb78BPlBgDh8m4YVsjBXJ4pszpxdJKwesvmViIlzk4VNFWl6CDXh4/d3adbOc2f8R9zYf4Nz\njfPkpsFG4wn63jZbg2NaTp2V9Zxz55s0Tz9BN/pjKuUOq6cFR597k3t/bOC4p1hfWqHafIkPs++z\ns/c+8/MGG0tL1Bs2Bd3H3mtTmQO92qeiLZGMbS5dPk+lmJEEPYbTXZziMiE+J0cTaq0FbLfAZDJG\nFweEYwvklDgEJS+iqi7V1hJZZjMatTGNgErhCSaJR+gNmUYdSHwKVkZzsYyjb9PeGbO2/hTJyzmt\n0jpb3Y8IRlMmiYV82KYwP2R+9YhJeMCTLxY4e3aTH31H4e23vscv/8YVNi9L5lbX6NyWXHu7yM4D\nC8tcI0tVzPTrhJlgGt/DcmBvq0fn5pc4d/oOX/7WQ5rrNf7kj6YEwyUS7zGff1KirSncP/wx99tv\nE+5/kab77zD0dplGP2C+scT8+haaonD8yKO8NMOj56kxgxaFRfSGRSp7xPExSuWYwqpDHrdQbElf\ndjBFl1GQUzBKOJqKgoqhuVRKEZ2pxtCb4Bg5Mm6hmApq9YAzL0Z4ss+D989x7cfHnGyrnP7CPkZ1\niKkNMJ2E+qZN8sYIzfoWN358nubiLmrLpXZ2E3VhwsZrCeNnbvOj1+HOnRMa7teoV0LOr2+wdt5h\n0ttH/yu2wX+6MniaEiUpUioz8zaSPM9QZAbazIUhZq1r1FyiJCZJKknShMD3KX7WzciynCyfOSMU\nRZDEKWkqkFIgc4GQLooxQCY6ipKhkCJzd1aiVf7FkmfmY1XVyPMETddIU4kCs0ODyMizdPajVKbk\nADJFKCCFQDccJGKGVJQSTdPJsphUyYinHpoqMAyDMIxxHYt+7LOyUOCk08dxdKBAuWoznowRGDgF\ng8mkg24UmG+cIggmCGXKqYs1Nk9XeXHvDJ/unrB71OZqq8Uvf+N5BLs0FxucPLvAR288Ym1+nTg7\nIc9M0jwjG4fomsCyFTrtA9y1i/QnkoIzQtXAMivoqYJhLBMOj3nh5S9w/fqHxMGUqYRqs0qupqDt\nEKdFpDFPwdQJxiNK5QpFO2AwOaRolNAyyWTs43ldKgWdwcEhiqlxb2+Pk9hDtXT0WGLqDsvzS6AI\nwrCPFCa6UcR1q+QypeAUMDSN6WhMtV5jMpmSScHET6jWa/SnU3TLxh/3gXzWaTAsLK3MQmWBgqEw\nHR0zf+YiMDtMSgCpgJLPplJCkKNRrs2xuPAUBw9vsFy8SpRPQJgoWo5UFMIkQKYpmBZSsfFTj1zz\nydIuGiZJvIJhhlzfe5+7h++xduvzXH32FKcu3EPTRuhM0A0b1JycFFN3ybIIIQyiIMVRHXQxozbk\neYZh2pCliFwli3M0XUeRGlk4I9YGXozILNJcQVMgiiSKI2fQgjRHNTXiIEJTDdJIkguBRCPP1Zmk\nEh1FGCiKjqLMvDKKopDJDEUIdGUWR4wANVdhxnHD0DIyU8UxzZ/mdf9//dSXSixfOU8nnNIbaxjS\noejOEfcMpsOAm9d2UPU6lcUCad5g594dkkcjEsWibJVQCwaObmIYgmLJoLOT0RurEDt4FYO5zQJR\nMGbqx4TjhMP7ESKrUi5aBN0EEhW9oFG2HaqVjIIB42xAtzNl2Ckw3KvCuIolKiiWSTxK8Qd9CrqF\nYk6YeB69Scj+ocXBfkrFbKBTob3jE6VbrH1Bx5QKmeaBEqC4FvO6y/H+gKHiEU016gsJjhtgWYco\nSRepH7HTjdjzfLKSzl7kYQYqi08UaazUubNaYfeTlG//44f87V/4EYtX4dxrcPbzS5hWA3W1xeDD\nDqmWsyAjTMshmE65+fYx80/p0NNxalVsy6Z33CeIY9xGCa/nsXU/RbZzFp/WWVipIMshrlBpntG4\nIk4TDVXGg5jeYw9tfhUlqdPd3SXNJfXuFC0bYxYlNHRC32N0kBB+bJDt9smHKTt3Qk56krLm4lgO\nk6kg1RNUR6E/7hF2QNHGlEsmJwchW7d7LMxrRPoQrewhVQ+9GPHEq1WObwdMjseEowSZFimWmzQL\nBrFuU9Bd9rb6vPbVr1HsrLH7gyFGPya/ZbH6+TLrZ5tkzVuoMmA3GyG9Kk89e5bpRKEY2KzUlrHP\n7DDo9zms3KaXdCgv6YSDMdPiiGJ5gcoVG6/vkR0JOMq4uPE59DNn8JQhnfiE0ZMeRze2ePvWO/yN\n3/jHvPbX4erXVMQatIRKlgMeBEgmgcBmwqK1SLDdQ5nmLDhNbKvM/sMOQxETjBVctUZZrRMnI+wo\nJjnKefyjY5xzOXke0C7mBCPBXFXDHyukRyGyD1ZtzHjvhOpaRLGsYVqCcJyQxibTQKH7UY+VC42Z\naybfxzMC3FSQaZJwPMKPBph6hbPPNIn9hzy6PaCTH6GuaWjaz0buKWWXo8eC+nZGtVbgRPeZq9n4\nocJkkFMKS1TmJUeHPrc+eMC9Dx3yk3XkZJVlUWBgDugYfYYjwQ/+wOOyb2Fujrk8MqnOm6S+x+Rg\nxHDSY8GpsrioUat38aM1Pvo/D6g3bVqXNTaeqpJEj7l7/0OGwZfYP/A4tz+HPhxTWR7TellSaGns\nPswxDMGpqwf8a3+zwj/4ezdJwwXa+20q05jD+xPMdZvhtktl2efxB0Mme0ucvVon8muodg2haZii\nRUU9RyEs4hQWqVYsCnNjhGyjex5qRTCZSOxqi3y1gn1+wn7nTzm7HvDCM1NufXzE3R8rbGr/Hj/6\np29QnT/i7NVXqF1Z5/WfvIfhtEkGGmnUp2WfJkjXGMc9Hn3S57H/kCd+9TmkUaRi38ea+3Pc0y47\nB0ecrv06WRYxnPRYWb+Eree89MI3uLD8Eu/8+Xc4f24FJVkn8zR8fYDrLqJRZDIK6Rym2EqdXruN\nn0+pLSzTaHwepxqSmj+ht/+Qer2EltUoFFaxrR67QZc0GyFUlVpLYmofEATb1BZeJPQ1/H2bYqmB\nYY8Yja4jOrdRVI2D7fvY9peYW1ujF+6wdt7B1EyysUWlNqZY7FGsKkRpAJWfQFPypb+2yoXLi/ji\nT/H6HX7ynsfPfeMS/+D2MY2awvH9MbXG8wTu71LMIB7VuPPJHk6lxuUXd7GLJkm+iVObI3Xm0KYD\nao0+l/6azyVNUFHO8O3feZ/cO+bxJwX6w6c5deZFPt7foTjfQbd8prGB6QRkmcaD+x6rp2w0Y8p8\nSaPfUzHciLlVkx/8XyP63VOU5psYMkIRPoOhTlSMmKQ+ZVPiyxOKTpnBGGwzoG6P0WUFjwNOvxTg\nLueY9jJv/pOAvTtlnn65gaXtoIgOXthHihH1hW9xUn6H+fkL7D04YunlKWMvpLTko0UlFHNKbV6y\nOv8Ku7ev4c7HzC+meN5DnIogffxXu7z86SYamSRNcvIM0jRGCtAE6JoGWU6WSRQlQ2SgWip5mpCk\nEnIDUBGKQAgVRSjEkY+q8tltsYqU6uxGNxUIzSeNiggtIEtAU0rkwkfTHALPp2QU8YIAXdVmICpV\noGkzElUURSjImdAvl8RZQhSnKLoGSUqaZcRxCJlJGqkkcUipXEQzwNQsZJoQ8pn1XEokCrmAaq2I\nPxqxsFQlmMakmaRULqEZs2lLv9enOVeh350ikxQkFAtl1IJATSMaC01e+coFvNDDiKdoapvW8hmG\n/QG/9huvcNz/59z/tMOphSJ5rmK7Od4oIpMBWeYw6LexHJWN1Qu4pTqKtEGqqHrGNDgmTyXCcHjm\n5a+iiIzuwS66ItjdusPOo0dY6DjnBY5eQDVtvKTPw6ND8jBmeuIgM43WyhKpGrLX2aLnDRiPPSJd\nQy06GJmCommYhsl0OgUJTsFBMSAKfIRpkaeSNItRFLBdi36vg8gTJl6A4xTJFROnqDAcdnCKJbyT\nDqEqsQ2XSAoqjkWuJBxuHfDzv/UfkCUJpqbNitFSoCg6aQ6qCrmUXLps8Qu/8O/zO//dfwxqgIpN\nlqfomoEkI81zNCFIcoCETCTEWYLMywRphGkcEI0tKuUqYTjl+tHv8fj7Zzl//yo/9zWLU5uPMTUP\nR6+hqhAlQ0TawFBDck0n02KSRMdGIfdN8jibrTFLyeMctBRUhSQNUB0HPXXIA5NMhqSqQMk0kjwh\nJ5vZvBOBzFWyNEXDIEwjTM3C92J0RSWKEhzHJghihKKQ58z+slm3QwhJmqWzyWCekec5qiowNGVm\nCpc/m+jU+KjHaBASxyqDrYjeI4mTRsiRZO9eByFimueK5KbHZNyjPZngR1N6P+xwqWYQuilpqOD1\nisjcxRtk3L55wHMvP4HZmlIoaUxiIDXJAxXLLlJQyiiJjWVr5JlKooagqkwGgv29EanSx7FcZKhj\nmUWadYPMNhkex8S+5O7jfS4VFtGrAU5dcmq+gqG0GB9P6NzV2fl0iDWdsLaQoY6PuHN3D2tZYGkN\nLn5zCQ4X2PvEY/RgShx5lBsNFC1ia3cbyx6h6RNGmY6s1uiPp3hTBVePsYIBhjVg+fwKtmHyH5a+\nzPbdaxSXpzz99TlOP99kpNt4/QoXniiz/8Mpf/Q/v0Oh4/CVbz7HYbfP1scei2fAKAoK9ZDOQcL6\nhoscKHQ8k0xLibQi+VAlHEh8GZNEBmlB0JsERF2NuljgaGvCjlNmclBD8xRyOeCj4YDTRxnynkR/\nMmdsucRDgffxgM6NPTLPIa+6LKzUGY0Cet02Yzth+Zl1ahsptXMei2dNImnheyZeT2DrJnFqcLjf\nJjd6eOGQAJhbukBlaBD0AvrtkJ0HY2rLTTTToVa0aR/5dPYEG1+5hDcqsf3GMaOgwzvyPv+68zSh\nUNijxo6YomrzGHqZNd3ht//W+9w6t8Xf+68u8R99++v8Wz/39xlfKaHGCXNrTWQElt3B0BRKpmTy\nSQyhwlF3TPqoRkmxyKoJpQsFamctlr9Q4Nwdh7vv3uHbf3eX/1xf4clfeRanfMSq8hjLDXCRHBVz\nVNPGOOnTfpxy2txkrlTFsOfwhxrecEIuwJIljttj8n5CZamGopUJuxW85ITKWovmfIavpEx3XKL7\nOdpQw4gymnEFu6xx+pxCzfJI6HNfzPaBkl5h7CeMH6vsXjdpbK7gNQoMCvdQUEjTOu12iqoKVi/U\nefzh+3zw3gOWQ8F85JCkjZ/JXqGYJ2jx8xxvHSDmhtSrkqGfo2Qm0xOVOz8es7gas7BskBQzVr4q\n2XlHw4rPcspUGNk2k+kW0i3Sn7T48HttLl9aRmt69MWQ3tCEwgpaDFGk0tmLkfe3UZMq7Xc2OZJj\nFD3EXuyz9HmNq/+qzTv/612W555FXvuEsrZGPj/CmxsyTga0ahqjvqDkFrEu+qw8rbHVd0FKUiVg\n+6OYRm+N937Y5kFxnf6OQrevMLhRwzHqnJFXEPUiZdMh8HScgqBSaFIu2UhtSm2xwEHio4o1qmWN\n6fQxcf87zDdW0JwK3Zs6+0qR5fVlRmmbhz96RGP1Ijd3/hQ3FgzkAoris7f7kGo1Y/m8y6DTRVcV\ndvYVBt0GizULXewRZcdE+oClCxpaatJvR7SHt9h6cMTpzfM0GmvsbN/n8f/N25vFWpad932/tfa8\n95nvPXesW3VvTV1VXV09sdlks9ktigNISRZkS1AiS0qEKEH8kjgw8mYjphLAiRwDhhAEQaTASiTZ\nsmxZUhxIokRSpLrVTbLJnrvm6d6687lnPnvee+2Vh1NU8iYLsLmB87ZxHs5Za2H9v+/7/3979/jM\nyy/x3Msef/D7A05FNmfWQxx7QpEk9GcPadbamEGCZSrcuiIZCaTZoJAneJ2K8Sxj/VzOtPc+45Oz\n2GKVRFdI2cXxDIR7g4VWE5mmjIZ36N+zyZIVVpfOMhlLtNMlnO1SCw4ZTbqUM4dT3ZKi/hbXnrtI\nbSWlZMhku0Uv+i5+cUiqJFo9i7Afcu3FBh99K+adm/83i87HeOfgTS5c2SAwTtPsHLC//2eEpYvp\nPsXWi/8x08N/jnJCjg8zNs7eYuG0Ymnx0xxPUzYvh9y46dDeDDj9zANq6zZBw6XY7/LkKx/SqTrY\nhctrfwyPboQsrb7E4PoSK1fe4CT6iM3NS8zGCYcPU9KTVda/cJ/jmYPnrXK4cw9PdnDlkLBvYrVz\nMndKISwm2QhtmljKQmcltbaP2WyQ5AbbhxnV6jGe0GCZuFbO0qZBa/MOfjfg8KMm+/eWqL45ovv0\nFHtB0vIX8HyHxbVFMK9xcDTk3p17XFw/JJoJzi4vcGe4TVr47GzfJqPkOLtN78Rk4YImyiRxPi/4\n/1XPX9OjoSgLPb/oKY0QmsoUZGWJaQrKIse1DQqpCYwA29NY0kIKMe8YlIpKmZjSQGiNRFKU4Noe\nQuo5oE+lWLJGwRTPapFWKYoKw3IpqwS/5lMqhW/788u1VBQGyGJuoi1KBcJAqRIMA6nmlV/DMMG0\nqJRGC4VKSgzPghIqXZBmGZ4VYLs2fuCQpDnhLMHxLNI0ArPCqQVYhsV4FuE6LrpKsc35+Eqt5pCm\nGY4jUbLE8SxUBZbSmLaH1iV51MNQJW6jgeVbnIwjaqbHNDzh7/39v80//G9/g5OTGfV6m8HwmMBZ\nxvNMJkOF43W4c/shRtUkjUJcz8YSNo5bh8Kk0CUimWGphKooaTkmd27dYTycUhQ5kzIjfPddmo0W\nC40GjU6HRhZzZuM0u4+uU4iKb7/2h0zyHFFzmVQFqysbmFpgta1a8AAAIABJREFUawOZKWrtBlKW\naJVTD9ogbCzLR1jz5DDTrBPHQ2zHoshSXNciGkcUZUZVlVROQKnnlf48VhTSwjcsMlWyde48s3RM\nNj5i7doLaMtFiu/nhQGGQOsKDEFeVThCoIXgb/7sl/j1X//vsQxnLiJVSa5jEGBUPqUhyYoMwyjQ\nFVRlhWFqpCXIdIVpJ6SqoKhKnNomoRrxjZv/kruDp3nxyvN87hWLVuc1Gq2KlvckaTZDqwaqKDBj\nsFOPgghNHVsUqEQg8gJRlpRao5l7MVSmsd06ZVEisVF5OQ8vQCEsE62g0CVaQqmrucnbEOR5jlUJ\n0qRAUlGWBQKFYVjIUqLKfL4XUQgU1WPCuZSaQhWUVYVQFaZhY1o/mCqlbbjUElhdXOU4NQmSDd7+\nNwn6JOFoN2Nxa5VTT0jGmaYwoL3WILzdw/EdLlw4y8JqTi4TRoMZ0YEkkHW2lnxWV9YpzBPikwnj\nLMKuNPFM4YpFSifDLCuEZdPsBBTaxxAF8UySZR4La2fw2w4idBGxDb7JrFfgmjHNtsmDQUZJSm4K\nqkCTRhNCx8JoekyGBe2gxupik41AsOrlbH28hrYqphxzW5zw+q0eyV6AK5pUtstglmA5inJaY/tB\ngluvUeo6yaxGNWySGjO6Z1xqi5rtu1PybI9EBqxccrhy7RKtlR66OeT40R0ioSiX2zSf7uBe7PCl\nUzX+6FfuwtYzfPK5F/jGv32dBx9MMIIGySzDkilnL7Q4+8k2pZDc3O8RCUWqc6Z7BaNejshtUsPl\n3PMruMNlDt+HyaHi1t2Ky2eXcc4scjC+R5zt8r3tEaU/JPnqkMgZkeoMvzRYlB5bz15E1EpUuyJ7\nVHFs5JDnRLWKYxWTZmNOdlJqhmS2H+CLM6wtmRwcnVBmgs2zp+mYNUpKTnqK5W4LebZOFY0JpxNm\nuYHKIzavXCOZjPCnEXvvwYe/fpNhXNDwbb5w6lXOf6nLdHiLRLmYzSYN36LjLpCVQ159dZXhzgAp\ndjh99jxLXxhgPLFDDQtllZSTnF6RE9hHiKt16o0AsS9YywPCZMpgckAWRtSXTTYur1J6BdHAxWov\n0Htzxnf+9xWcIwf3vMWZn1nDEiPOcYvVsiKxK/bKE4wUbBHS394mZsBUa4yahfD1HF46iAnMJmYs\nMfuSPBWok4LRUQ/x0KHAwtBt4hMFjwRGZaG7C0RqRv/mjCP/EUKP2btvUU1X8Nwa6806WVzRf6hx\n5CJ7lUGvCZXIGOwtsPsgZsGycOslFz61RWZOWLocs3VxlW/d/8GMWVaNlIOHFvt3Ehrnm6yYcDSM\n6TiaMnS5/U1NdtZAPNvGtQ12bw9Q/RrSl6QMmE41rrXErIyocPGLTUY3Ura/Oqbz9HniUGFNlwmM\nIe4sp7/tcu2LX+C9b3+dWWKhRQNbLGFY24TGiHMf73J0r+TBH32bM3INv/Ee8vIETvUZRBUrZHiB\nySia4rkpn/ubq/yTb7xPf7ZEPWqRv9Hg9rdMklmLD49LfvTT/xW3s1uovmAcWqxurmAKnzy3WFmx\nSKOYNHxA3K8QzTFrqy0+9qUlDvYq3n/7I27ce5ulocU3f29GrbZEWhxQqyqUJwkLmw+iNzh38fO8\n8sNNKvcu6wsX+d6tryITC1e70PdpVwGf/eQneHj7NTYvlXzqP7pIvjAkFyPC2RjDvIi7OmXxiSlH\n7wSgcqIwYxqHLC4v016q89u//5t89Oaf0T98xI/95EssdXfYPq7Ru5/wsZe3aK4G1DoW0XQbt16j\n665h+pBbrxMWCsdqMHpwhXzWpbvSQDp3KeJtLD6GmD2BFzzA9h4RhgaGHdD0psTeCGH36NivMpsE\npNkWhw9vYK4KloTBv/qfv8o47PJ3/ukuzvIOdvXzfPje13GDQxyRUF9epN5MyHWNs5tX2b1eEu+9\nyuu33uWJ51osLnT4xlc+5Gd/8Sf5tf/lV7DVp4h7OSe3z5G4L7J3/EeEU48rL5msnNtA1iZMD/Z4\n6imbB3/Sw6yHdJ/USGuK49aQ7fs8/5Lm2c3n+eh7I3Y/DDjqw/m24J2vzKjfbJIKE/3iWVpL25jj\nguvfTji9qWmvSMyqz8nQJhxYxIcRN7875FonxVqRVOUa2t5lHEF8GGOqHdY3HdqLIU49IRpBf2bS\nNVKkZVB4MbpcYe2soN1eIWlf5WSnyd0PD/ixrsHCSsJK8zzZ5pSWeRYZ5bjbDcazVcY9xZmFGbuD\nuwijRcM8jW2GxPE5etsZ/Zs5I+eE7gUbHWf8excaVTUflZp/8RzaJ0oJaKpCogVoLUGUVJRYho3r\nSixLMzdam1iOjWW5WIaFaUks28AwAap50o4AIQosy8G0BE4pqCpBVZZ4tkeW5biOR1lWWOacrCxV\nTqEihKowtKYoy7n5u9SkaQGVJkmnODogNQwsyyG2ErzCw8YgSxR+w8GUFo5no5XC9QSGYZCmCbZZ\nI88yhG9T5Iog8KESJFGJaRnkucI0TbROQUsMQ5DnCikFcZbjCgvDAMfzMaTAtAQiz2k26yRZTjNY\nYnxwj3/8P/0i/+C/+99Qo4yySimrksE0pdZq0xuOcKXL/YfbpGqZMxurSMskShJqbpMSicTl4OSY\nVj3AkhZrWxuM44Qwl/iByWAy4Wi0Q71Zp7hzg6g0Md+7DpaFYZsICSvdVdY2VuhoRZGDgcBzXGqO\nSzNooFSG0qAFJHlB4CriosR1HMbjMUvLSwxOTnAck+lkQp4V+F5AUYr5GjAMZmlGmsRU9TrFbIYf\n+HjCwZYZeR6y9uLnAf4/kcHj5SYEZVmAkAhpUgIbKx1Ob5wi3e8DLmiNQD4OByhQOkNjYkkHjcYw\nBUpVlKrAsgwqJcmrEiklJSGGZSJNn6P+Lb765j6PHj3HD33qJ3niap+Bf522bFCUsG6tEKc5eeEQ\nVBbjNKP0FPbMoaw0lRIYANLAwCCPSio7Q1gmSJNCaqQswbCoKCkrSSU0WlRzSEcFpWmgck1VgaFc\nqkrN91uZISyNKDSyYk691xJdCaQAQ8/BlUJUSClQpgGlRpU/mNQpMheZaYzYRucVTbtOy7e4dT+D\n3GRxxScUx5R+yspVm7WlNk9eu0SRh4wO+gxHQwxdUuU1Vk8tMbUdhBKYqUPgN7CbOafcFrGZE0cF\nprBQScLwKKEsJHnkUijFaX8Jd2EFrQXxcMK4FyHtFNeOcSyTyq5htgWBt0RpwmEvhfsl4yLF922o\nLGqLLounBGlZMhqnoNpESZ/94ABL75HmmrvVmNbZM9SsLvrAobZoMBnOOHkw5K03Mp55conagiBo\ntEknFclYM05txrspgZ8Sjm1qnkGW5vSHPXbSAy5aHlaW0NyyWFg1wA0RGnrukJd/eovu+Rd4+NUZ\nrUyzUr/K5OSQh9+dYC4nrJyxcNwxNTki6DpcPp8RWjZRbjGclJwMco76Q2Tlk2iBCBOOTiyUNPlT\n3uP3Htzi4w8u022nPPHMKizN11JMhOH7XHiyxdNXa9SWPJy6y/FQc/hwwn4/JFkpaLUCnA2NaCgM\nXaOaWORBmzTK8KRJNC6IDhTtF5bJwx7Xoz3EIOGk16STS4YDAyEdSjOgFjRQBtgyYDVoUus47P/x\nlDd6t3n59DmCJ0Oq8yWPnBGqUrTdDp5l0hv0yL2IvJnww39rlZv/espu71/TWf4cP/6PuqQPc07e\nHXN8OKFm1Gm2A5qrNlEYUuU9hC1Z8JagH6OimFwnuAUURxPq55cxznv0d9qceAW/9faAN97ucHl9\ng8+MA174OzlFvwXODraY0Fwxsa+1yGce2cihYRg0L7TJPcHO/SHTW2NiM8fMJE4SYBy52GsNzq0t\nE3mr6DRjOj3ieHvE4YMYM6xx9epFpNHCND26izW8jkkhjpGhoGme4/BDhwejlHgwZeuVZ6lZEaNH\nmkmZkooadU7hWxEq9plEMUGj5JkXT7PSLRgh6PWHP5CjouYv0te7RP2K7bs+/kKFuRCiVwTxRBP1\nbQ5HK5hlg+WgTrV9iqZ1hjuH7zPWA1qLV+l0n2aw+y7JZMIsq2NvPcnR/Yy9D06oe5KNdotF3+HD\n3h1O3klY+KaFrnmc/uEQrR1GqsdS7CJ8j81ry4SHCfdvPKKc2Sw8HVJ7USM3U3pHFVXDwwkEgx60\n1jSVOOTyM5J3+gmDwRnc/Sa1xQaWTLh40eWd977FpYsvUqYFp7eWiCcZzW6dcXiTs+fWSXZ2oDTZ\njnZoTev823/xT9l65mWe/MLnCL09Pirvs+TXOT9dY7Fq8VTnM0xufI2P/42MUV5xYbPBxlMf8tTn\n3mAwbRHfv4T/ThPP/TROksPEItDH5DsDtHECF79Jb/EthBZo1aBMhyyeCmmtx3TbT/I1dcwoTHjn\nrRsstDZIJmcwimV2b03wrQ3OXnmSP3vtI8wlm53+ERvLTzMLNeP7GYVqIOUGwlwljtp01OdZWy5J\ns98h5y3sVo9ED9jZM2kvbaJUgW0baPMWjpVh2ApEnfZKTlnuYOsJtr1Cr2cyfPQKebmI4X6aJ871\n+No/+wo33/S5/NQyRnyDfHSbMPwT3v3wq7z8Q0+xfvHzVBwyjV7n4YfrFPFDksY7XL34n9Hv+4jk\nFf7w33yFtXNtXvnsPv/iX95kcv80VvsihDZHt9cJyx/m+WcUQeNtslyyc3ADmW1x8GEbURj49jqT\nYwNd7fBEY4PQvc25pTqmmHukquFZzp+1OHPtIZPgiBsfBmw/PEdwsoEKpmBYLHhnyGYF+/YRF05d\nIuvdpLB2WVlv8eafBjTOdFnQuzSbFabpkIYZhtGls5hguQbCSPHcFGFIhL3OSXSMncywU01V5Ozd\nCcj1JrXFOgfHM1SRsrHapdZ6FzewWH36kMHiCZ5/Br0bc/2tyxxed1g9dZvCjwkTA9NvsHSmznRk\nkOx3eff1Ec/6V0m9Q9IEIPkr97nx5S9/+a986Zd+6ZdWgf/SdTykNOdeCv39i6Ccjxc99kzYtoll\nzmNOa76gHljUfYHnGgSui+8GBF6AbbmPKeMCaUik1Ni2Ra4UhhBUukRoTaVKDDEfhSpViWW6lKXC\ntW2+D1YwLYnKCqgqNMwR76pAa4M0KdF6TqE2TBvDsHFsDyklQb1GRYEb+GitCXx/LpYeF361LlBK\n4VgmuhLYtkle5DiOQ5akmJaJqkpMaZBlJZ7nkeUJjuXMvR21GkWh8DwHDZhybkQ3LBMDA60VbsdD\nlzkrbYNplHJn1+b6jUcIxyOJEmp+kzAZ4fseWpvkWU6chZgWOI6JIa25OdkJ5lG/SjEcDEnSGMfx\naS/4lNWUMJ7NzfyVpCxNTLvN+lqT7qlVTp/foLXUpuY6uFJgYuFYAb7t0fDq6HIeJ2yaJrVGgBAm\ntlfDcl2k6eD5NaIoxPNciixFVxW6KFFaURQFSalwvYAwycjLnLxMSNISUShCy+LcwhYLiw3Cnds0\nn3iSjZde4f/vxJn/z/PAAaTAEBLJXHjkCn73d36L2Ukfw/QplHpsrNYY0sQ0LISeG0jFXBMjhECp\nEiEEhpQopTBtg6zMMUwDy7GoBFTmiP3hu3xw6w4fvbeAOXuaKq3TbESoqsKVFWpazOF9aQM7NshT\njcwE5EAhoACRAYWmiApEITGUSZVrqhh0Pv+Qyzlls4Sq1BgIVK4pc0VVzgML0MZ8zLCaj0iVSlGo\n73dOBEoYlGUOWqDKeXevKDR5WVFhEKZwd28I8Ktf/vKXD//Kjf/XfL5/Tjz77CJS9rh3f5vJQUF/\n4DK57xENGpzdWifYsrAXMzpbFUtrFuVsxFLHYHFNIY2QIpqBp6j7beKhZOf9Y0KtkNkU24EnXlhg\ncctGixjbzDl1yce1NMrOMSqLsiyYjGLCJObM5QUank+YFPTHGVbNwHZzyuIQx7YQros2a7z553vg\n+Cx2F8GxKCcG/ahk9FCQDg2iMOPkaEoqobZuEKmQvhoyCQRNcwmTJp6zgAaEzlCqILA8qqkJiU/c\n84knC/S3XfbuafKRRxoZWKJBrdElCk0e7Q+YJTFbl7dYOecj6zmLqzn1IKYldjlNTIcIQypUscCf\n/UGPg6+XdMoVzGSV0USTzAT+qk0mYsJ4QjrZZuVCiWlOiJwBKiuJy4ynn1rnmY8tY7kpu/2QNJNs\nPnGe5eMViplFZozR8YSyPSa0DgiuwVNfXOPpn+5y9UsSXTsgbg3J3ILDNGWm4PgopbTmk7L2ool7\nCprNBoZZwyraJFMXR7XpPwwpUk2nU+dk55CkN8OTDUgCsqhGv5+QFx6G10RYdbygw/SeoPeaontw\nhsGHE0bc4sVPL2J8oo9xTaA2MpwlSRJNcQObQkR4LUGzabLVdLn93R7CinGvxKz6dUI1JZ1JkmOF\nKg1m4zGTJGIw6VPVcs5dbdC55IKYIpyIWi1BeCnxcB8t52WdltflzOZ5Gg82GSQ26XSZna+FHMQG\ncTDGExt47iLN6ixZt8OkAGuhgbhgsnhJ4Fpjat2C9bMeT509j2UbRMc5N793n4Zdo9YwWFltceFS\nGzswqfk1/HqbJy5cxW01+fD2EdJO2diyoR7i1nLOrK1j2AucbCu2b4zwPJuLT6xCFrK9F3H4IKOa\nrbDgb1LMfMJhRDEIWToPq1uaYfKI8TDlO7dCvvv/pP/Bz4p26OGpRXRcI+nNMEsTkQqinsPhPZsH\nH8TY5RWyE4/RcUIeSu7vbTNz+iReyfF0yMn0kIo+th/R8BqMjkJMR2NWijKDcFawc5wyKgOGowHD\no0PWrwguveqxuuWQWweoKiMPYXRySDHzufXRhDyuuPpqgDw3JDM06cCn2ZzHLDtSMxlVBJ6gODpF\ndtihmnpsLG/QXmqyvLTK+uIX+PgnPkaoB5y/1MKtBZxM7zMYvcfy4hFPXQxpezdoL0WkkY00Mixx\nltx2ub1zhFu7Qnf5Ivcf7DMb3CZwK0zD4NTlHPNUjzuHdzn7sRG1pYSg9kOUIiapfZOWd4Wj3YKU\nOzRWJ1Sd9+jzEXnzgMtfDNm40MASHqa8gJLHtLwA6exi1sYM+prjB12eWP485WhKHvaYTo9pNhs8\nceUldvdPGI23OXduk/MXLyFsmyhP2Lwksd2YtVMzDC+mEiXaPIHgT5HW+/iGRRm32Lk3ohGs0+wu\nkqsBWXiBxbUKbRxRFpCkMVpnhMlDpI6YziJMI6fRbqCqKVFW0Ozsc+OD19nbeZu1cwpvrSRor/DN\nr5zQbHV55TM/waP+19BGwt3vbvLhax2WNgue+9iP0l1ZYTB4jevvn6CUybnnjtk96nP9gynh0Rqq\nMrhwZYvGoqa7ssX25P/iwhWBH3RBdBHVebbvpayvfpL9u00O+u9z4RmF9DJKK6IZdCgm6+x85xmm\nRz6nnvken/65CHPpFmeearB0vkcYjvnWX3xAy30aGZ/n5p0bnFpfY3/vBJWlTPdqvPf6gEtbf5cw\nrti4dIeSKWXWJcpm9A4kdpBSqIrJNKZRP8vJScpgPKZet2nWHWzd5GC7IB6v0vE/QVbucf/ht7ny\njMe1Tw/JREjZHCLMkMx6iNk+RBHy3tembN9IcP0CN8iJppqTgxRXLNPrhcT5ENMwGPUmeE2TvLJ5\n7c9mf+U58dcD9mlBWc4lhZTMad1SUJQKKediQ2NhWSaO4+HbJYHn4nsK17GwbRvLcDGwMKREGmCa\nBtLQCGGArPAcFykFaJuyyP4ywSfNMpqtNpPxlGajSRRHOLZNkaWYGFRaUaYZGuaXsCqnKAWlhqKE\nNBNoUSAthZXkWI5JkuR4UlLm80jcOImwKwcnsNFGhSkM7MrAlCayLLEtEzu3MA2LIneoco1tO8zG\nGWU5B6aVZYXUJVpX5HmGkPLxjwdFUWDZ4LouNadNUcWUekrNs0gzwXs3Rvz273yP1a0llruXeHTn\ndZqdEoFEqJiqslCmS284JAhGNBpNXEcQRlOEqlhbXmF9bQPXtomjGVmRo8uK8xtn6dfHxHEC0kQh\nSJMEf6HOve37rNinkaaJ69sYWtNutDByB8OEJEzoLDYR0iI3TNIcDMuiAHQFRRxRNwQaTVXOI2jT\nKMa05xHCtm0R54qyglIppKkpSkVlGAiVYxsBotZGn2yTWw6nP/M3cP5yvT0WB49FhmYuPCol0KJE\nSBPXhooM2zXQWiKkQCuohAStqCgQSEzDpdLVX5LlTaUQWlBUOapSuIaDQFBpTV7mlBSYLCLlOpUX\n8Sj8I37va++yZjwD3essd+v87EvneKLW4URMEVFFEIJn2xR5AkWJUjlKa1SZz8VLnlK4AmFXKDHn\nfQj7sbCRCi0qcp1TicfvS0FVzONqVaVQVYlh2kgchOIv5T0SyseeorJ8HP+sNQYGwhToSlNkFXn5\ng/FoFF7FwpUOeTohcBb4+u/ucbxT0PQbNFYtUiZExT4r3Qw3WERb+2TKwE5yNrYcaqdauM06u8eS\nD3ZGKEMR4BLPMvKZYDaeG7HTeIYyEqL8ANtWLKx4OGhKx0WHinv3H9L8yOLCxRZxatJsuVRFn7RI\n0aZEVwlRFBAPwW9scPhAsXLaZRkP2YxQs4L2eoAIAwyrIE4UD+9HBO8ZnH3+DEG7xjDeoxusou2C\nRAxZuNhmpb1AtBMhUp+jDzUHt0omiUf8fkUaWQTLG3htSXq8j9twsXyTg9094tKmtdFi5sF3Dw5Y\naU3I0x41C2qFhtGUhU4Xu19nYB5y/S9OSO6UXFn5aWZkeHKN2ca75HFOL86wA5vpcMR5Y8rqooUj\nEga1hNZii0YrpG5P2LpcY+OyxcN3HPY/GCJXfE7t1tn7XkZqKRbP1ln79CbtJ2PSYJfDdEQ4G1Jr\nFJzkBWkS0gvrPHjYo5AedqOJshVWx8UsDQ5vKOJYYagSx68hK5tJ36TTWsaMm2xuXEY1zuCWFSOZ\nMy09ZFUR5gLLcpAqYKlYRxw2GXynYi8a0Rc3+YmLp/j4L2rezMbMlmccjUYstDwCnRKmiqPwhMpS\n1Kp5t/ro/ZQkK7j64zM2zU2ON3YZ7UnGdkU+1Xhei85yC2XPcJsZK+cV4eg+9Sc0ZSdidpKjwhjb\nB61OKGcpTk2wuNrl/JfO8u5vp4yU4P2s4Pd++TWWfvmEV//uGZaervHJcxcoOjlhFTE92WVLC+Lm\ngHY9xwzHpG6f2oZF7UDhrQianosZg5NaqGnG0TChzGK65+qsPdvCnnR5+H6P3bv7DMYJxYZJ46TH\nxeckxmDGg1uPMKwulz5h4SmXg4cf4NQ8gsxhli3iW+uEOxazXZvdexkHwZhrn2kS9YeE+hhzvMJK\nvQaM/oOfFdOswzSJ6HRWyCuHu28PWN45yzCJKIkpDIfQhHA6xYwyqkJTX+oyVSHDaIypClqWjWnW\nmKYhvWxAx19gdxpSxSmnV9cZD4YoQ7HaOsWe3WRy2OL4egpnbrJ2OiCtCvY+qggadTorKbad0uy0\nufFewu6kj38iwHKY7bYR8Zhm12ZvryAareB6Jf2PLnNafpyLZ9do1dqYrqQdLOM24dInLS6tJfSH\n7yJ0l/fDIxaiM1TjDvHda+z0V0nkmNVz8M7DklbbRUcR0d2HvPDjP0vo7aI6d8kMh164i9U+YdP/\nOO3gs6wsn3D1qTNk+huMou/RbppMspLV7iWefVmycVHj1Q9pdtchrdPvfURi5uwcpLhNRc18jrq1\nQpnkVLJFnIw4c2mDu0sFhw/epd0YkSQKy91isbtOjs3C8gpF3mPYs7n8TIu3rt/mpU+/TDTeIZvl\nMPVQpSCJlmmuefj1JtOTkqPdEcpUPP38ObToYzUOiaoxqtAY1TXwhhjObSxAFyZWvECZa2reCYZ7\ng1pzmWq2SBZpyqP/nNXOIssbv8vy1hepdUquv/eAPE5RssfrX99m9eIZ7t//FsUQvvjzgpWNijg+\n5sGNHrbVZnUrxMjPsXt7ibv34PY7p1j3zvLzP/fjJLLP19+5Tyju8ewnV2m3AybpPoHzIp1Vk6c/\npzh+cIPxmyGnGmtY/ge4tZSscGn6m/T2bOKJgW2XWN1vESxdY83Z5mwj5uxYM7ufM50FpLs1jFof\nK3+Wcvsc98e/iideYOf9gHYz4ptv/AEvNW2OH9ZYOpcwTTLGkSZJFPdvw+nTLl6giEOJtE36ezPy\nXsmkqajXYxZOrXDmoqa/+x5GPeHtd3KUavLa1x9w5dUWqRNhGAVlaZGpIVJWrJza5MEHOQ/f2qQV\nSEb5LjWzhrHgUahHVJ7LKI3YXL7K3oNjenH/32mf/zWFRoWu5q2MqpJorTEtkNJEINAoVKkpyzkT\nQGuNZQocyyRw3Dl7wW8/jqVNcR0PYcw5CaXK58k6VY4QEiHAcTy0VWLZNhWCNIkfQ9ESPMfEkHOk\nd/bYiJ5XoFRJUSmyoqTINUoI0qQiTiRZoRBWgWmGyFBjWAbIBl5REDQctBKIxyk+piGwTAvLMijz\nEsu1KJXCsgVlUWA7JnEeY0iBNKDdbjIYDHFdhzIrsSyDPE/RlYFhuNi2RRDMWSGV0ozDPvWayYJf\nwzA8tgc2f/9/+B9xaxfRjskv/+Pf4j/5mSeI0hnkFlUFmBUaB8Ouc9iP0cUjzmwUrK92sUzF0eEj\nFtpdDCSddofB4Jh6e408KmgENq6bgBEzC2csLgUUM4cvvfQ5xrMUYULdCYhnEaIw510dIVhaXKQU\nGtvzsVwHx3SoNdtozbxSnhfkSYaBxrJsiizGdhzSJEJIieFYuLZPlpVI06IiIclS8tIkzDOe7S7h\nugZ6nGJdvkx3dQ1VRhhGAKJC6+9T3eddjaoqsQwDKSwAwrDg8PAAGWfUvNbjdShRZUalQFFi4BAY\nATAXP7qSmKY9h+pZBnEaQ1yBFlgYuIaFNmtQKQrzmGgqsQwXWTdQxgFZeJWqH/EPbr6Fsyb5e594\nnpdX1jlM72EflxQ6QpcVokwxDYmtNJWVYZcaYczAssEA09BoU5LLFCk12pUYhkIaEssTVFJjlJpK\nasxqLsa1UWEyD09QlYVUGlFpUClFUVHNpxTRGGDOOTcod6exAAAgAElEQVRaVZRSUxg/GDL4qa0W\nG1ckZR4S9ky2zi9wXj7N8W2LpIgwfcnCusvSYoAtCrJohFcaGI0U1zHw2iaOl+N7LkvnbPzSI+or\n8mGOkD6DRzHbe2PMIAO3wgwKGksWpptT6RI3V6xv1CjJqIqcD96+T1FMePazS3jNBYoqJpxN2d+v\nGD6cET0aYCdNpJBMbzikB1MaGxkrVy3qq5K6XWFWCr0N0ahidMfj3hRaj5ZxT7XobyREJzF+V9Jw\nUwIvZ9g84OjDKSf9JuNiBbNa4WCvQM5s1lpLzA6mlMJmONDE+0N6s5TGoo+/4JHaEUsbTS5vebSc\nGYEQdIwUcUahdMBh/XX+118TbBQvsa/PkR6tc8IMjzZx7RYn4zkz43gyo+kWtG5pXnjpmKRIUZnP\nrC853D6mvZJRrNj0DySsbOJMTuGKJql0sPMhHh6JOeT4OKcnJ1itCN0cU8tinG7B7MiEmcNg16CW\n1wm6HYbTjDwX6InJ2bNPkLgZu3eOGe8XNNYCLNtlsbOMYwge3RryaHtKe1EQjkdkkWY0A8dsI8lp\nu03MwSLWnRr9r+XUwhoHbFPyEZf/iyvw9Aw1vUdWaNQgxlGCIhlj6ARpD6mEIDEz9FGN994XXLrn\n0v85G3tzxDvDR4y322i9gF/zEE6NaQbpbEYgMo5GM/Joxvr5RVYv1dGZz3QYMRxkzMKUcDxB59uU\n2uZwHHH+E+cIeyucnX2B0HuWgbvNjV/7iP8j/hC/dY8f+dEv8Z/+wssMb7xOuHpCp0zxl/s4jQJd\nCXRVsLZp0xYdFgaLpPcMwu/O8D0L/4KmvmpzNBmh8oLxOCZRcOX5C9QCcDlG+AVTa4a3brDqSoLz\nEt3ziQ6n3LpxwLgvkNYKgbVOzakzOUyY7EXkA5MLGys0PBerdFi/sEJ87NKJ3B/IWTGqFP56g9LI\nKZOKImvSuwXCWSGWR0inYmRGxHrEgl8jThL2RvsYhg+mgVAl0+EY2wrQ1jqWX3E4O8K2TPwg4M5s\nyCSacnatxfU77+OeqmHkXcpjgb0/oj+IiBPFcOhgbAZMjSlSj6h3bKaRzf7dJqdkga5HvPEH+1y+\n3MIJFDJ5joZzmd5hk3X5WbobDnXHYf94iFVMON69TdO6hVidsvjpdznjZ8xwqX1skzd/402O31zh\n4VQxa8cc7JpEu3AwmvDTP/NTDI6/Q/KNN7h793fpP/oOz15extxyyeQGt/a/xWs3Uw6LKUO5zfOv\n1CA9zVbzgNujOyyI5yj924j6IcH6A+zWMY3VBg2WuXzF43iYg57g6HWEOgblsL+jMd2L3N19i/Fk\nl6vPPcXHNs5zcPMmpfK5vzPiUe9DXn36SYbjipWNNYrEZHqi+MQnP0n3lGYyddDBLkFjiUkvRVVj\nKjniYLsg7C1Ts+tsXjvFyfYfs3u4T1V0maYJS4tHTJx/yKJ/gapawHRiZtOCbJZx5vQZcnXE0eF9\n3vr6HVT8U3jBF3n74C2EWuRv/cKPsfrsn5O70Mg6fOqV87zznYCa8ymGd3y+960lXnhBY8lHpNOr\nhIMTvvut7/Hxl36EJ1884M//cI8177/mV/7PX+XShZ/CCj1UVrK83mD9gsG714fEacQ0kpiLEZ32\nCXF8SK11xI1BycXT/w01MSLs36WzkmC7FXUJNycfQnkGtz7iyrUGVQkLQRdhVJi1BcYKqrjLYvMy\njXM3GUUfkGQp179ylWvXvkB/5w0m8Qlf/LGfZv/BHf7iT67zzOcMKjG3IxzerrFzI+Hlz0jOPiXo\nGbfA8EmGDQ5uhLz62VW6T45J1IxxeUK5+g6br65z5s1V7t0K+OC2z9bzJmoqSfMKXbQo5QS/ivFq\nIXmmuPlOm2df+hTf+9Y/wpYzDm4rknATB4s4Udx/pJlWLQZp9u+0z/9aQkMIiWGaCG0AGiEkVTUn\ne5uGg1IghIWUFQID17awTAcpS6Qh552B7/sVTJf5dUhSPiYlaylwDMlkFiFkBSh838cw51RvS0qk\nZSGEREpBVZWUKqUoJIZpQAZZnqOUIi0ywjiiKh2Gk4w8FVQiQZhQVCG26ZIkGbYbUeYeo8GEzkJA\nnlXU3TqonIQC17apDHACnzKOkNqmKnNUWeL6DtPRGITBbBriug7TaUhRZghpYRkGnh1QVTmWZYKW\nWKaJ7zngzUeyAmUxjRT/7De/xuFYsNQ9YXhSEY40n/3hz/P1P/lNVtsvEJZHSAWG0AhlYGrBeDwj\n8E2ScMjy6gatxgKD4ZBmrQO6ou43mM1GmGZFvRUwCSsM6WF3O/T7A4Ig4/q9t9nY2GA6yVBVDgbY\n7RbSqxNYBnka45gWWilUUZLgILKcJE1ZXloijqc0gga9QUipStIkQWrwPJc4jciylFmVQ2WSlTl5\nlaEkGJ7BorNK5Vq0ox5HnsuP/OQvMAUapv94BEXMx6UemzW0BlNalIXAEgXCtIiiiCefvMTNb393\nLh7iCI0AIahkhUlFpebJZqZtkkX5Yw6HgRSCRI0xLBPTsqCsKIsCUUqcWkGex3iig+tWCNMmjTMG\n/jYLacJwpY03amMNJf/k97/Cu8vX+YlTW9SsNioyKbMBRaIo9Fw4Y1SYlomuJAUpOCWGa2J4LkpK\n0jJFuhJsqKyKYpJhBC5FNof8SWmgpaDSBloyT9aqkjlQjnQeC11VZNKEeeYWeaEolUFeKQqtUfqv\nNm39+3jSXsytr42pVJ/JLKaardJp1TnKQ05GKafOtiDzKEKoRIrWJYUR4Tsl3XM1ti4ExBS4pyS1\nVZPeqYDdbxecUJLGE2ZDn8goKXILr56RHyishoNlQmVLpCFAKzbXWqxvLLC7HxMeTjncsTh3OSDO\nHAxxiqqsqJldChwalo1OTHo3ewSrFa31gKW6RdMpuPBJn1tlhVI5/Rsx8aGFa3foz0rqY0jv97Cf\nyGk2wZgNGDsT2s0Z8idqNN9b5qM/dwkPodVpIYTP/oMR/eSIJz5ew6gUk/E+VgB+M8X1K1prI1Yv\nDGmYY9rE1LQBlsHdqKLtH/AbXwVuBTx55XNMH7i8rRWv8AkWTk95eOomUW2CWqxhlCmlc5r7DwZY\ngcnLz7V5sFswOITeUUESlbS7YJgJtWJAXLOxLlQMzYCaTvCsnA8+6NGOQfQUgVKoqUM2AeHWMIRH\n3FcEchW/5qNKid/o0Gk1cS2T+988IDpRTMKIOKmwtUOCmrOTrIqa36AiY6EeIOIE0zBQKqKz5KOn\nDaqdgHTHpvc10D2JQcplAV/4V3+bhZ/a473oz5nEE7RhowzoH/ZYc1K6G5rz7VXa+JQ6px+XeEaP\n6MEyrYcvUW0oLlg+2ysFJ4cVUWIy62eoNKTeLJC1ElFJajWN4Y2Z6QmNoI1tllhJRXg0xHW7mLpC\nOEcsXbTwwxjD7VEaNg1bU0uXcPzn8XbW+cbJd/jtf/42nXtnWDY30CeaJ19eovaJ5/CvJGDFHB3t\nEt0p2Xs7J3trgXaxhlWOsRolmZiQrWckxgSrnaJmKW06lMMcLzNp0qTbCCiyPVwnJspSxOoIYyXk\n0kseSy82uPPhkDtv3OLo6JjWKCHsmWSRz8VzF1jeUByebDNUOQ1Tk7c0h8c/mKLEE0tX8V0X25HM\nVMSMgqIds3Z6k7xYJY9mVHFG01mlTgWyh1krsKWHQwPpZlRlgee2sZwO0izZnwzRyuJof4Df8InL\nmL0TA7Hgk04i6jWffGZx+AdtTKtLwZj9/Sm77v/L25vG2nrd532/9c7vfve899lnvme6584TJ3OW\nRImUZUtMrEiRYkce2rRuUdttCgRI0DiBizb9ECRAg8aoU0e26kixAcWSLdoiaZkSSXG8vJeXl3ce\nzzztc/a833lY/bBpN0VRxCoSrW/nfNxYa+F91v95nl9G7XCeo49NkQt6zDam+KOvf8Av/NIEWlHB\nu6tz6VaJWnWGiniYuFSjNjmHk40RendwxgVZNUG3iqy+8jqLpZCi02TWVtmSLQxRYGr5HT7+izP8\nWStP14vZuutRW9wnv7TK56qfZDO4xUP/mcGV0j798312tfvMT5ic/FiLQ0ee4PROgTTt89ab30fV\nTP7w9z/gyefGifUa9fIKt++/hmH9LXJ6g3Tfpuw4tG8ecCDbTFcfwyhex7IjFK6hcY1uqKNqZwh9\nlZxRZ6CHaI7KIHyV8U++D1rIEWOZOxeX8PxdkqTKscOHqFiC91/7kNOOwMwLylMNfH8HP7JJlAak\nh+gNX6E2NUGhOIeZJLRXM8LOGUrqGaoTDYzKgL21GazBGbxkBcNpkbePY85eZdW9gFKb5vqfFHnz\npeOcOz7G1CkXYd8i3q+QuhlTx4Y0Do2RaTcRUqV5e5sHHlyk6b3CZGmetc4m29vrVG80OHT0Tf7d\n/3mBL33lZxhbtpFUmJ5c4jf/8QvMjT8NGaRmyktv/Rblo1cJRA5dm8e0t3H9DYxBgZ6xihnPsvbW\nDFdfDjle+xhXL/8uteMmTl6l0Biyrq5RaUwwvqDQbF9lelklEbcQcRlTGyLTabq7PkVFJWe8yfNf\n6jP/4AO89tpbpGMJL3/jDzi9/BnidJoL519BJCVE7+do3n8fe+oD6vWY04sP8sJr72GqHUrVArIT\noTVsVi722Xgt5VSjwPHHcmzt7qOpFn4akbOGmNU2ux0V353mYNUidJucPDfFzm7IYBgSyoiN3duc\nPPc8X/tXKxTGBO+88wznjh7h/ofvMbusk/kpwi4y6Gb4sUqG8lc65z+i0EjJ0hAUnUxoKCJDUx0U\nAVEaY1k2SSwBAyRoWgFDA13PsCwLVXcwcyaKpiJTHztvkyQBtm4QxRFxFIMGpm2SxSlOwcb3XVRd\nUq2Xcfs+WRxBmqGIUbjX0AtI2WfQjwiTlEwR9N0Q342Jpc0wihlGEUPPIA504ixlQtVH+HYMVE1g\nDTqUyjrDvkMBhcjogGpg5mwSMjRNRyjgSVBNFTVT0BJB5IZowkAoGbYl6HVdsiRFIpBpimKoqOnI\nHhMlLo5ZRggDlDxG0KZgKWx7Ob76by/xrRduYag5dA06gxDXvcXyzBJrk0u0env4HtRqMTIAaen0\nvQzDKLOyssexE9OkSYfhIKRcaDDsN7HMHPliBUW38MMINwyw7RJJGEEqqOUncUXCkSNnEDLD0WM0\nTcV0KvTbB0xaKm43pVaaIsnALpoUSjYyHWU1dGlCYlAsTtL3M/LFGsN+G820yKKY0I+QmUaqWTBI\nCbMIkaUE/QGkgkhRseoG0wXB/lrAyc//NTIhsOD/zv981DolP/qHEAJkhK6qIDQkMGzvs3a9T2oa\nZImHoadoQmPgJiiqTpSl6ELiBT2UUMPQtI9yGozyOYpFiEcaR6iqIElShCbQYhVdyZMJgaJokEoU\nPUNi4OVD4kGXXK5MGico4RTfb/u8Gb/OT8c5nqqehShBySzKqYsv8sRsIgdjqOpNMiqESg1h9MgY\nIhQVTUuxyjlcJSSzdPS8Tey52IYg8ANUwwRVQWg+Oile6uFJSaooCMUizXw8EtJUJ5aSOBWkikGq\nqYR+gpeqxML4ET8D/v8tfz9lsKaQWQ5aXGRsaoGyV2Y1Z9K8u451XXB89jD3Xr9N0lxDzescPZZn\n5oyGPd7jTvcKwaCPSEzCWp3q4cPkSxOMX7dZeb9D6kKhWifOF6hPZjj1kHTYZ/X2AWuX+8Q9B0cp\nMjNXY27GoWTXuaP16e/3uBnGaKaBG8NwU0cNVUxpUzFHQFBLlsgUl0o+T04fMF2J0LVtjp6V2FWN\nLK0QHsDgvsAs1jhoHsC0ztmzU1SVgIWSQg2Fg2JGSErTGZJUdO6+u4a6W6KuzVDUCszNVFk8VKSl\nrFKqS+rlDC86QI19ZqcT5sIdxiKFRC+wr5nkaLEZwr/4A4h3SsiNj1HczCOo8If8MV9WTrO0pHH8\nJ46wMr7BTeUWIvEI44S9dY3BnkrrrsbxxQV2t7ps34nIvDHGbIlTCcgVdPSGz52NVZpuRP7IJHm9\nwulGnWuXV5F9HTNXIq/XKGgafqdPb9vFKhqUcjliP0WRklrBYWFygqX6PB94N9gddFiYWaJULTMI\n+nTbXXQBaTgkS0I6bRevs88g6VIsFjDGVTRdQVEKxAc1gvdytJs+BgEaTZzpTezHS2z4N7jtr9MW\nXYJuhRNz8xQVm5wZonNAmLo01QF6WGS2tshv/N3n+OZ/exXj+klefe81hscDIiXDDxJiL0Q1Cui6\nheeGtC/tU3VKHD9jYZd81MQlDAbEWQ5hOZQbDnmjyPa9NoN9j7puEpshQ1sjZ9VG9kxV5dh8mROf\nWuTEZZMXXr7F6nst+mmDvF3j/h/s8ZWvTlP5/CLVuQHu8DxTMofTcqgUD9O6HKPp0H77PtGuzsHc\nOvmzNQY7A2qaQSks0762yXDoYwmDbt9gtxZhTvVQ8JnRQYljLDNGnUk5NeMwe6TGxT9RaW0NySsV\navUK5VoBqfVY2xzib7soux7KhMrGrv5juSsOTZzGEjVULaKg79MbNKlYEaHqMeMsUK/ajNkpWlxk\nY/s+raxAV4Y4RoVqbgopXAaJS5pJ/CBETSRHx4/QHrRpTNt0/RHgtOc1SVGpaTlC4bO/Br5eJ8DE\n9U36gwpFexwZNtGaeQbDw7SaWyxMnmL1hoXCFvnkKHlRo5YexTQdCtlxvHaTvdb3OL60z8lPpkxW\nN7m6plPuaKyvuBxc/hLV2jZq7fuojbtoImby8Aqf/OUJmh/6TD9zi+d/9lM0ydHu/D63t/J8sJXH\nqJm0tlOSdJmr17a4uvcWFC/wN77wBHZ5g0983qMyVWR7xeCtaz9gfKJBIXecM4sqffE6B51x3n3N\nJftzl/Fanac/MU+5cZlhtoPCNIIYny5Cj6lMd9jddjh55LPk9t6lK1ZQCy3mF89RqMf0Du6gKYu8\n8a1b/Nqv/TPOv/4NPrh6kc6uz6UbQ778sz9J6cg9lp+a4mBtB62Q4iTnyFfPUHSGuH2fzWYbW9sl\nNXwqFeh5HdSwiqXVaDc1Zo+CZmn4w9uEyh3q01NcP79Cb5DyM1+uMXPOxU0vMohu0/R/grTzFIM2\nyBsJHb+Ik/fQ1T5In5mFxxBC5StfmeP1P7nAzuVDvPrtdQrViPrYGV75o5f41M88y0H7Nk5JkA5D\nFg+fxTZm6akJ++l32d1NSbrQ25xE10JMfYBhKnTWb3Dxz49wcvYZZs++zN0f7LF/5adIhuc59tQA\nY34Hw+lSPaeS7Gxy4IaUSwOUpEgSF7l7M8fbL3sUkuMU81cp2ttQdPnk5+cYnxe01n20DUHeHGNh\nwaHl7nDj0nucyD/F2tsOG9oWveU8aXCWdJBx/tVtTj2Sx/djtGQef6/HKy+scuLTj9LZXSfKEpKB\nih0fQe3WOHDvUc01+ObXtnn+vzjK9ffvE2YmfRc0KcnXGrz+6iXOPPgkt25dBLHN+lqPomJitYuc\nevwE1apHsWrx2qtXuHrnr3bOf7R62yxD0RSQoKojHgZIZKqgaRqKUFBVbVRLqiko2gh6IFQdgT5i\nXpCSJCnlYhnPH1AsFghCl5yVw818dB0Gww4FJ0/gBx+15yj0+31UNBRFjKjMSOI4JopHsDRN14kz\nie8GhGGIVFS8XkarGxDHBv1BRq8T4oYZUi2gmBloOTQNTK2EKgV6rUcQmmhhHtVQyFLlL8PDSEne\ncQgDnywbZTpUWyEOPeI4I4lH/v4sA5nKEVQuScEy8bwOE9OTDDoexZKKyj7V8TLN/Tzf+PobfPuP\n3sZybGTgI9MiNl1eeO37fOGnvsAPf/ANZqMKm9EN9oIJEJLpKEPXFAYiRbcLrN/oEC/4NOrjJLJF\nqTCGl0bEwx5JkqIJhVyxQBxFGKZNpVJnb69JKZcnDFrUq2U0SkSBgm0bFCYa5E2Hcs3A1B1UzRg1\nHyk6gYzw/Qgr5xBFIaqiohkKnVaPSq2A6/rYlkF/6JJqAjKJagqSIMMVGb04JvI8ZufHOVJssL26\nQ+XBM8w9/AgS0KUEmSHFv/fbi1EGZDTeMBCKIJURXjDkg/O3mB2b49Ltt9HKh4j93si2J1SkGOUT\nhKGiKwYKI6p3nMUji5WUGIaNZWmkSUKaxijCGIWtGZG0k0wipMJHTjLiLMJPwCUCRSOnmiRqSixT\nxIHNV22Pwp7PgrXFlDZP3NulXaljuRGJjFFCE0GATJvEeoCiWqRSkBDhewqJpqDYJprrIPMGUs9Q\nNBCpRCgZmUiRaoah2hQ18EkJ4wBdSbCkRaSAiJJREDxVCVNBkmnEElJ+PJWVUtGJ4pHNLsGiUKwx\n7PoopoqqFuhvJaQ7VVYvtIm9Pp/50hSVpZBANul0t7CqHrMzDsYoxcJOoU+olEiGedwfdLny5han\nP3GY8bEGthWQuQNuXlujs+8T9lVKhTzT4w0sXbBxb51a2eTUmSkGfpXbdzcJeyphnGKKKulAQRE6\nh2bHwBU0lYztZpetCwOqOY/yY0MKWZfZszUKFQc1qHLth5LbF0ICr4Wekzz6d5aYnoEe77PLHgE7\ndFopbk3HMCwcy6AwJmjkZ1CGDnErIPY9Mh9ChlQqgiNPTZA6GcV6i0Ol+4xFMYqpY8hF7vj3+PCD\nBm+9apHuNUj2lwjfNimdfpi/s/YIr3X/CW7mcWzKIfeJY5yauk49NVn1TLpti9VrQ0KvyI3LLrff\n2UWm4A0rHGwM8DyFh58bYywniNwBhuNTPaQwNVfAbcfElsEZ+zjtjYAwTkk6JnZxAuH3GJ+RTDdK\nDIYHxGFGnKnYOtx68waXB5exZIHSeIOiVWHYCdjZbuKjsDBTQRYNbNujPqaxu7PO9MQs08tjdPHo\n31Xpvq8xeDkg3iijYjEnXKaqLsd+fZxg6jJNdgiUPskmSDekoNmUyzo1S2E/jOmHB3SShOPKDIFV\nZOe65JvyOv/g5v/Mk49o9JRN3osuIhIwTQNNM5ERJKlOqThOqVjBHWygddroVsigP6Q/dOh3x8ii\nImnfw29LKvUaZUMndYeYlkCzfXRNI0KhNBmx35c8/IUqP/Hp55F3jrP54oCttRZb3OJFUeYL357D\nOFtlsZcQlhX2bw3BL7PFGo2wSm9bUNhpcO/6TR6ylrix/T4TJ6aYKFSx7q6Tix2Sa7DvB6THKhRq\nZUS9Q2IlWHWJr/UYkzGiHRJVA8YXSyiFlKhjYqgWtmrgRpJOd8hBBmErZHigsHXjx3NXTDklHHOS\ndnuPvGJTKRdZdbvUchM8OjHPZKmFUtondlpMAntrYxxs9DHNo8xMTlGuK+zvdLlz6zrz8ydIg3Gc\nUkyzeZOQHe7sNBlEIVpSIl+coePdI40d1sMuWqiTEYAVotXyuElEEob4dxWkXiAyNQoDCHYKTJqf\nZ+JUg3nrELutFv38n5GaLQz/QQrGJfzuLq2NImeebXHoY0PuPNTn+vfmeOv9HhudIWf+poczXqBK\nhpskTJ1Zxant0u0s0Wz2SPIbaLU9tIM73Lv1MO6NZba9b9B2h/zCf/c8C48d5o3X3+HCu5fYvKfx\na3//Z1F4iaNnAyrd07SbBnvr+8w2xhiGKY3Fu1TvfIKp2R4zS1eZXnifVpiSF8fIJ0ukkUm+IEij\n66z51xivPUneKJLLrxFM3ELb/mX6e0/R3P8jQnkRo/4ejdO7ZLVXOf3wLOfffYHi1E8wlB2+8c9/\nl1/9zWWCziqzeZuD4A6XVl6k0f4sx07b+G4TlQExJSw9T5Z6VCsae507DA9sKg0TqUo6nRV0LUfe\nrJAKn8BdZ2p+npkjh+htXmKQCNTcAfXCeS6t5rn0UkJtPuLTXx5nZvkU2SBg655L6713yaxbFCdz\nHD27TOFZn+KLOq3dL/LN336X8eoMtI/Rv7VBb3udmnOIlRvvM3O2SJT9NIl7j+sXfo+lqoGmXiJV\n8ji6w8G6wfZ1jVNnTY6duYdY+pBzuXm2Xq3TOh9x7PQC/d4K5bGQ+vwaVkXBqXlAgiasUa1xu0Mu\nncdyBI98dpzCiYvEqscwSpgu/wxa8BIbq3f4G78U8/DjASvuIs3/dYfOvT20ZByZS7l9Z4vCRI7L\n5xPGV+e4+NoFHv3UcW5fiFDNRTa27vKtr+6x9NQ099bWidcNdi9toMeLmEmdWNh47WVe++Z1nv7c\np3j3wm3mp57g9q113KHK3p7CYOcytVIeQ8Y4RZifmuLhpTpLz4K0V0nCBT6WK+L+WYG3N//D5/xH\nEhpIhSwbVZRKCVIRCKmOrCpSIBRjlONAIBEjfoLUUKSCplkYpoFpaqOGnyAmn8/huxGWYxEEPkjo\nD3pUKxUGgy75nEWYZKgIJsbruIOQKPRIo2jkv89SVNUilR5BFDD0XZJUIjHo9XzaXcnANfF8Sd+D\nYaTg9xIC6ZGaeRAuhirQpYKuquhGNvK1Cw3LsTGMDEVTUXQAQZwE6IZJFie4QUgQhAhFQAZRHCKk\nhmUahDIiDCPCNEFVA3JWntCPKBVNKpUKWbzPjRse/8fv/JC3L67T7pmYeXAcE98PEFKwsn0TX/w0\nzz37j/jjP/hFpsvTmFmMn9r0EhdFNYj7ISXbxlVha7dLGCroBiwtKNhmiUGQUc1XcLsdHMdGmBaW\nUyCKE0rVcXJaTGbOE3ZdhBVSK+WxcxXiQUI4bEEqCVIXyy6CMMlZBqZtU3Iset32qG3JHInAUj6H\n1xugaBqt5j7FfJFB5JIIgRf0GSaSju9z0Ony6KnT2KpG0hkizAJP/M2fx5MZDupIUEQJwjJHkwwY\nVdZ+lNGIZIAiTIJIJ29WePbjZ1isVfj5X34FTTcYDgOcgjnK70hAAZklRGmAInQ0VUORAiFA0zSS\naBQzT+IUoSgYhjFqbcoSYpl8NBpMR1wLMaqTTVUdkYX0wgNcTUUxNIJQMjTznDRP8qve7/Lr8T/m\nqPMtntJn6GxuoNkpYWKSGAI9ctHiiChMkXqOLE1QBCRuhq5rpAOdrOMhylWEoYyyRGZGpksULSZR\nYiLVQC2M9qquZGiagalmpKFHHKe4foSbafgJ+NZHg6QAACAASURBVLFCKhRSVfx/nez/qGt764CD\n3X2OPlTk0KEHUXMaB60hOEUOzdXZ2+oy3PTIyzEqy2VKNUkarTN9poxlGHRFi0B28fCwSSig4qs+\nYSRw6mUykXDv9gDRKNL2PHxvlUJZ8MAjC3R6GsLLM14uokrJ9tYBGAMsJSRfyzG9UCL0qmytxPT2\nXVQPFmcKPPPkIttXhzRbe0SR4P7NDpgpsZ1SnA+Yb/RoRftY9SXmFooYrRo3b/RIEg+lFxNeF+w1\nXNxam1oQ4zUlQ5nR2j5AGEWcCUHr5i79tYSCKLCwnCOJ+3j9Jv3eDnF9H/twl8l5hWNUUMw8+zJm\n4/4mv/87ea7+cJF0OEOnZZBPdcJthf/yS+OcnMvxU7+1wDXe4LUXHB4ut0me2ePxLxQ4LBPutHcp\nCY12M+Fg06A7yOjsKajSJPVM5oMxzHR8NIFL71HUVcrHNYqNhPsuFAs55mYXGI6lXHpng3arz6C5\nja1IjMkyXaVNsZAy/8A4diqQmUWrXEQGFTbWWgR+xt7KJp2ei11LKdYVdvt3MDWBH6UIYgpTVcLU\nY323RXW8QbidI7rt0N4o4JKRFz2OPlDl8f9lFn7yaa6Ev8Er7fsM7vZR+1WctML6jS5bapd6MWLy\njM+5XANParQJeXv7PvdfT+mIKf7p1/6Uc508E59IWD45hkbK3gYMhx5KaqLLHNV8gX4nQbXLBJs7\npOqAbuCTL4xTKk+xuubR3+tSzTWwzBxu3CGJI/JjFlId0JgxGTvkUJgS7CcBe5tN9jdKvPenVwjS\nBmPKceayR1Hx+Q6Xmbo8YElYWGsGsbSwhc1hWSGHg8IEJgX8To677wUc7Cvs7KecWiyj7Vv0pEr+\nsklzJ0DpFZgYdyiaY6TrHfZospFsMFPNqLYj0pLCYJAQeTYYZQq1jLAfcXf1LmnaxlqApbkZkmqe\nqBUD/9HLpv5fq5LGWMMVSoUIz5Ws9iU1I0eu71M/2uSB5yW50xZisonXs7n06n02v3WXUing0ecW\nqI2rKMoir7y0ze1L95koWyydFJycsFANh9dfjtm9HeIwhUgPoWYRrtbmIJZESYiV90jlHpZqg6eS\n08Akoq6MM6+eoTHeJZecI0tMJNtsRXdZ+sk2tTP3WCjV+MHvf5+bLw/RgiPcelNSOTKg9PgWDz46\nxCxu8OY3/wUbnaMc2/ocy0c9FLGBrRXo8w7aoRVC3eb+1g9Ru1XGlx7k+MnX+O6rbV76NzUmq/MI\n7Rr56U1k6UM++4t1Bl6DV79j8i9/6wU+87kppuYEcXiS48fyfCi+w72dXayyTWzvkZbew1VD0tTC\nJSChjNc6xLU3OwzuFYm9RSoPB9SO96kvbaOhMavVUIbLvL97Cav+IpV6yGTVQc80soe3eH/nf+LN\nP21iTTyCUZilc8vj5774cYraPTpr17n7zmn0qSFz+f+GicYR+r0/RLWa6HZAZWwCpzzN+tW73Li5\nQamkUi0cIRc/xM761yhOBOQLx4iSG2ytJOjJY0yPPUq7f5XN3ZDFuWUSutxeew+UmIn6P6Jh30bp\nXuf++Q3Wd24xPT/D4pmzNHdCZg9ZmEUgCjh2us67rau0N84gXJf/4StfI+rMUJCH0URIvm7iuS20\nxjX89iaaIhhbgk5rlkCLUIw9yFwWzggm6nlqjYyN7YjV8wH+PsxO/G0M5wUGQwtpQqkcs7PXZSzK\noRsCp+gjZMTM3AyVakiru0blsIFvJ2RCI/On6HVuoee6GCLDKCbkJg2c7k1++is5OlciLl/o0d1T\nyPYkjWqdrWGTXuhjl5/g7X9nI0od6gsNrry2g/3nMdvbGWvNEt1NjXTXQk22SfApZ+O0dwP6gwlu\n3z8g7xznh9/Y5+yRj3H55nlml6uUqh0aesaJM+eYmThJHBqo41sMWSfwW7T8ayw+PEtp1YPv/YfP\n+Y8mNAQj4vZf1v+oo9dmKRGKSpZmCFUlkxDFo1fpTAoSqRBHKZGekKUpWaJhOipRpKHaEVE0ylhE\naUKxUKXbawMJfuBhmyZISafTwdRNNF1H13XSJCP0IiQpQZhi6DqappGFKdFHH1d+Ihj6GYNhSJAo\nJGpGEGa4Bx6J4qDgYigxggSlqyOtPFJN0dQERQmJdIFmKGiqQSbANkyCMCTNMnTdJLMEaRSQIdE0\ng0D4RGFMlKYfgekMvLCFIsYx4hRhx2zvbOD2K/zr332Ld69ukomIYsUGZfRyr+pdvDCHrQd4rYj5\nB85y5P4vcuX1rzNjjaMVJTc6Gf0IHMvBDwNwEjLfAHx0GZE395ieMXGsEmnkUcw7pMnI2pYmMflC\nhd5gSLWwQK+/il3XMdQaamYjwwgnr+L5OpZpEEXgWAZSGKhSkEQJg2GHYqEwIoJnCTkdup0DTFNH\nkSm1ykjM+GFEOw4JXJdY6Igo49jhw2RhhG5pNMOIz/zKr5LKlBwaWSqJSNA18f90/n1UYyyFRGCT\nAQUTWlvb3Lu0S6cdYqqj9jOhqghFRVEUUiQkEtSMTKaoqgoCUilH8D6ZgAppGpMqKYoCQRJ+hIgZ\nCZCMjEzKkT1QJog0JcxAkQluEqOnOrpqkaoKuSjPn/Z/wC9Vf4Gvhf8759pnUaOMibE8sttEM/ZJ\nE0D4pEZIgo7EI838Ub4kTVETHRHGxEqAmplITQHNRrENdFNFMRVUw4JCghKVSbU2WWqhZANioaBn\nKkGaIlOFOFNJUMk0DUWomMaPxzp1aDnHz37lYZqdAdc/uMPKrR204VFMO4/RKLBxsM+HG6ukSkwR\nle2NDrlogL3UozQOq0GfYZxiSJ1Zy8brJPT6kv1uQml8ktNPTjP0E4K+hUFMdWqCmYUAYYT4scfO\n9pDI62MWDIoTOfRKgkZIqiaYTsCwfcDwYEDsFTh8cprlxQp+MuDqnZv0wgFmuUjoZ9y80qIfJzz8\nfJ3OlIZTU1g4XCKaqdNaUHH+BG7f6nPxO9fopAr2oyr5p6bQCwGHliS+oqKeLtMSGjOtHHt9BTNy\nmB0vQr6NMeGzfMjAVUwOpEsvNUl9wXq+Ts1PEZbFt/9pi4OriwSXZhhrnGYmnyD0LkeeKzH3sRQZ\nN3nuW2Oc37/EK31B/w9yPLas4G+njE0d0HVamA8IVu5qFKolpDJP3DbobaS09npsr/v82TdXOXzI\nxsgicnM6y0+OEXYjJhSdRLO5fWGT6MDiSH0ae+YoWaqyu7ILSUqUCvSxjFTtstLcQxU2QjUpzBro\nrYDSbIFGrUz7wAM75MiZQ9y5J9na7LLXbLO5uscznz2FsCa4e2MXdaWIfXue+v5ZYqnhcZdAHOA9\n2oaPFZDyPDf1EKU3R07N8FwdN5KQS5mazVE/ajCfM5mWMCRhwi3Q6eVoPP0MEzc/z3bWZP+ex9gX\nVbIgQTVjMjMjdlWiMCbuJ3QPAm7dH7J81mD5wWXq5WPUSyHp0GL7QBCEOUSqgZKn0w9JQoltaKgy\nI6FN5egYTnmDlvcBfhwSVEtoapXST5ZQDzfxrwYkboN5ucDGhxbflVeYQOVROc1CZRx1KFkWc7Si\nmDo2PhmGyHDUAovlBdqXQlxMSs4i6+4dGuES0ZpLo1Kn92KAtaizG3ZhoQKNY6i2wJ51QPFZXhYE\n94q0myrbF3a4t+myq7Z4+m/P03igxdS0SjzQ6A5+PBkNrb7JpF2j29tif3sdxTNRwxOUT0cs/qJk\n7MkS+3xAVfYJa33OffFDpo6e5uLbPyB9sEh5rkAoMp5e1mn96wGzkw4nP2Vgz7zGnrzCY6dKvPhv\nmjy2PsvOzYhCFnO/00IWJc0wIYgjjGwWLakjoxaN2jhxK6PESZanHkbRD0h3LUL7CsvP7nD4iR8y\n/2iffhYwYQ4YS1qcm3uW3df2CaXHI0UHrd4kIGThWJeZvzfGe9/XefviHiX9kwyiEoPcLYrLE+TH\nhixN3mEzbNLf/xLN7Qq1w68Se7s8OP+rtAY3KI3d5ObumyzPdHBKSySayme+vEF9YZ3v//EKuWiK\n8uHf4XPHJphcaLFz4BIGeYRYolQN2bmvsHnVZNo0ad3o0to4T3CvxELuIfzeYdaaOmfUJscPW3Sz\nW1j6LmPTCmfOnWNtO0WP6ni7Biu3OzzycYOLV7/P0z+3QPOySWd1lhOH6txf+ZDj7Vm+/s0LfPrZ\nv8XRh/O0995ic1OldiSiWGtRVmdBOmzdf5fv/smbPPXko4wt2tT0mPfO/zaTCz7l4gTNnasM+332\nt1OEa9BxtykfUjj55DGC1R4vfus7VLWHefrcc3znO7/Hze8d496mx4Of3uPsY0fIT/bYWn2JTnjA\nQv4xBp0Cexs51q6HVMYfZWxWY31vgy3KPP7x59E1l5f+9DfRthucKDzKjdd6HJ76ebYnN5g6e4dA\nGyIUKOQKzEwWqUy36AWrHHQnWLm4zP0LPY4fPUDLL3Ll/lUOO0U6vT7xWIRjlJBSRzN8JD79HlRL\nB/T3r3PyxEnqJWDgEG49xGCtSDyIcTvvMzX+GO3Bb+PHnyJNrnL0tEarpJOvL7F5vsHmzR2W5xcY\ny+/Sbu/RFG0OejtkWoNr9+9Sma5w92aHVrtMOyrhJQLLKeB195ivGahal7FqAcU+wv3NLYoTQxqa\nS3f7CtUi3F+5w7hjUrAm0Hsei5/cZcu8hzm/xyDrUSs08LYB/S7zh+p/tXP+o14MUqYfYQ2yka1J\nAVUoyCwjVeQIUoZGmgmSWCfJIEsTsixBSkmWamCkBL6FbvrEfg7N8sjSEUgvCDw07S9elWNcd0ip\nVMA2bSBlVEIkR6/dqkDGGao+4kskcUycpARRhh9rDHyfQRCPXnVDnziLSeIEVTXY2XXRVQ2kTjQF\nmWaidEx01cDQI0QGqpZhZCqKNhJNUlGQacZf8KoVBFIBRVERSvKRzUeOpjoyJZMKmYxHlOYkptNN\n6PkOv/kvX+Lu/WRERa7btNo9KsUJ2p0upZLNMPWpqku4vR2kbfPET/33+F2f9t2XMLoqR4tjbPqS\nNb+PY6rogYtiNYjlCDy3udEkjTMajTHKlRpppuGUCqPJQ6lC7A6wEewe3KNSmiHwPIaDJrVqgTR1\nyNIc+XwMUsMwFLKUvySfFyydg+GQYddH1zUUAWkUoIqMTCb0ul2SMCJBIVBV+nGMoijsrm9wdGkZ\nQp+xyTkOukOOfubTFKYmIQPCDGErhEmKrun/3hTjL/bdqHxAFZACa6sbbN64wXRjAUu3SYRKmoxG\nGKqmk2URMs2QakYiU5QsRJHKSCgLlUyO9pBGRpKGCDH6O0lTBCNyPQikoow6dj8ikQPEIkSRGZKY\nMIxRlBBFtxgQcKSe4w/Dd3mSs9xKNL5XfojPbH8NLbdIXt5ByhJJFpGqGUkqQfrILCbKUjI5skgp\nCuioZH4foZtIFESSQyQqIs2hiJDUzZPFLVS9iKZ1kOigRKiKRIlHjWxSiFEBgaGSCfERGPM//ZpY\nMKjUAmqzPfoDwS3XJ4lTTEUhTSXFyQp7nSaKkKxf3UM3Ys7M2Ui3x6Ddhb6DdxBjVsaJKlUCV6Xd\njen2IpKeRUKBZJjR9l20WoAzK0jjmNDfpZgvMvfMGKt3h+xs7+ImGVMzeUwrIQ48pNtHDW1MxSDN\nMsbGCwSxy6U7HdbafULTIssiNFEip+YIOgG712x6bofFh1SksopIV0kMB2NGZxzY/rCDv15l6cE5\n6p2UtLaBNBIyhgw6Pbb2YuKsil2rYGYKfXeLLPI5UtNwqiG+sGk1U9JWhY1bGtlDZ3n72mWu/auA\n3e865PUzLORnmRgbR1HWUcoe49Me+7nvUDn8CCf/bsIb/3CNbaq81T7A+6rLXz9Wh6mAZTnkbrlD\nvRDTabYRQkXL1yhN5Oh1M3bXh6yu7LB6MUdxWuULcyfw7vu4fhdDs1DTFsNbHfx0kqJWoDZRxj8Q\nVPUAtZChFneJJKysb2PbCRgJ+SmV9Ru36MkM20qYPDxJcUyys7HKres3yUSNLMqoqBluKWFi1iQU\nKtWtOt13FOIXHfb3Erbx+aQ4zrH/eorWZ17h22sfMBwbsLth4m1biNCgEJgM4jZ6zSI/Jon0PbaS\nPXKBRXvYRzsoU7szRWsF9LRKxoBUqJRnBL7YIm8kOD0VoSiIUgl70sIfuAyGbVr7Ht7FmOmZFBkF\nmKZCcy8j9jTqc3VkAturHcJBRM7RKZU0Dp+uEdgeYdwiNPZxpm2mnS6r60MmPzFL87RBemKP4faA\na7v7WNWUx+QJtm/c5j33Q4LSPEbap6Qdx25rmBRxcis8uTiLe0xgrjl40iLYljxTe5xgCNPFOs3O\nAeU7Bfx3tykdX2RPqFjnDLJHWoSVkDW/gzvsYHgqs2mdXNfixpse2ztNZn9hGmNqSGi18NcGDPcz\nBr3yj+WumP1sl1PLHvfeHWLPjHH7dp+b2+/x1KM/xdzJjJSXqcs6GWMk4g0iaVM4coexKCHW32A3\nrVNVZzHqu3zyP7+LrV9GrSzhSRWH0ywsNXnur+2x8/U6jeUJNlZ9SrkKK8NddKFhFodkvkLZnEXY\nJ9AjhdkjNcZrY3hum63+JmNEGMZ7nH18h8UnWzSTDNtYIEju8fxzJ3k13sJb09i/08aq7mIaxzGk\njy62kHaZc5+9x4vBOn/2xgQiHnLymXXGlE1yWYSqKIzPthDFP6e9dZrhpb/OtTdepuLtM0he57/6\n+yWmHlmjWjiJJmIU9SYRu5x6sE5ZnOP3fvdlvvj8J2joNRIZYozfQFHa9L0dzi3+Q/7J7/xzCmmD\nic/FGB/rsWg45I0eB2v/Fq37HIVIUKpNI+USjmIQE5CKHZS8xqA1ybXz+0iucnjqCV79IwV1bI7z\n51eY0jc5e7jM/d2YLif4e//gt/jkp36JRnwcvZsyOdVnxV3FtMoY5iSZUubS995mZ2OCx87+CtMz\nO+QKefZWL5M3C9y+cZ9DR56gf7DHzLEJFo4c4s2X3yAQE+TLT9LdcvnuH16knHuYBx85h2K8TZSt\nUSg+Rm//MKrm4aXfx+rPs3K+wdWXBTe//wG77fs08o8wUz3LI5/NME5c41FRIF8V7Fz5Nj/5M1+i\nV3yIb/7eebL9DzFLFju9NcYnM5xDLo6mo6YphbIgV4qRqoah2azu7HLvSkwtP8PTn17gvQ9WiG8/\nC/5FcmWHG696fPoLProZoSVH8WUTX/boHHgYjCOSMlnkog4rXHnlOsNNhcXj55g4dIjNHZeDPYVY\nNFk/XyZXfJj62Wuk632s3AznHjd46JmIy1c0Vs5Pk986jK2/A8KkEAvKhkFYmSByM8Ydh2bUJ2eY\njE1VWXAWSMKQ+vQMm/shx6ZSnFRy6sQpesOEjoxwkjV6B+t4kUU/8NkevsXEQ0N6pbsUDIiy+9RM\nndQzGG7/pxAaMkUoKgiJUEa2FkVCJlMyASLLQBikqGQJuMOUqKSS2BFSZGQZKMLCdxOswgB3oGM7\nAcO+xLIzEClIE0SG73mUSxZZHJGEGYajg5BkaYoUyqhWVknIkAhFIQpDoiiETJJkgqEb0XNT/CjD\njzKCKBzRwqUyIuIGLda3CvhRBrqNUNtYpo6qxqhKDiEzTCOHKkDao+CxVBP4KCuQpemIC6GoIGLi\nJEERow9ZTVMJfEmceBiqiaq5qMLm/qrJV7/+Pa5vtrGdIpZqMxx4lMtlev09TEshCgpYmUciTUIi\nwq7B9LjFZ7/yG7z47ZitK+cZA6a0CKNkc7/bo5OvQBRQUDUqQsNQBQPPo6J4SKWMlSsTRhGOZRD0\nOkxOzJHGMRQOMQy2UUxJ0ZpAylFDWC6fkfYNojjGNBwGrouu63T7TfyBRrFQpNvrEfgZfhCgaQJN\nVxgM+2iaCrogjjNafRdfERx0+jSmprCziKKToz3oUFo6xQMf+wSplKhxgrQ1/CShoBrEaYKhqh+J\nC/GR6BhtQZUMFQVVUchCj3s7F9ho+iRZRopEU3WSVJLEMaqqjrIyMiXJYmQ8Yk0YqoFQVRSREccJ\nQugkyUhsaJo5alNLY1Qkmfgo0yEEqqYgE0iIUCSjSYuQJGmASEJkPmSz6TBpTfChscUX7RN8a/i/\n0V3+dT7XuoUhhlQ6B+zJDFfE5DOJGQ+Reg4/G4XX4yzCQgUpidM+QnHIUgNdEUhVQ4gUBQst6hGr\nJXTHIxElFLVPLtcgSNdQP+JoaKpOAEiRoKkGOevHU1npxR6uu8Nw5wB7wiG6UiNfgXGzSH9owEEH\nkQiSQcrK5jblZYeqPkbN1PF9Gy1UGay5xF2F4Z5Pb5jhD1MUo0Z+zEQxSxgDlbtvrzP5SIEwEgzi\nAyYnS0xXilimSnPFJVcImHu8gWV5BMM26kBSHjOZLEyiBykX7nTZWxmSZDG9jkSrWuixjirqKG6I\n343pd9psJxbWnscg6DNzuMvJSYvDz1SpLZS4/IMe6y2HNFMQbp7BhoscpqRs0vMGFMZmee4LRzlY\nsdn8MOPm9h6looZeUCmMayRRgKMqFJUKB71D5Ad53rhk8Xu/vIZE5wH1CX76+WfpdAVqJSMrKVB1\nKc2uUX+wTKW6xIO/EvDQjQk2XkgJejkuXN8l/h8HfFnJkzw7SbYNbitCTSWGk4Dap1LRsSsa0xMN\n3jnfZ7s5wParDDugm4KphQb5XJ7WjmTpVJH9Wxr71/fp3ktQvDLVxUkKRsr6VhuraGNN5snSPmni\nEyQqzpjGI08/wOr1Vf78lR8wUeuTEJBkPlKz0KXALlvMmkXW1m7RDyzS9SWcvWWGzQY7YoArW9zj\nGs60jzzlktY19td8Wnc0/A1JQVcZH3Oo100wu+ztt1CsFpkrCZeqSFEiuupw65+EtK+FNMUut9nB\n3hC4gU43GtD1uiRSUp8cx7FtBnvguRGabaFaBnlDJRmkKGqe/WaPoZ+gazkiPyKToOVNElUjM1T0\nikZswr2dVar1iNqyhaGBEB5KJUMZamRphHfIYy8OgRymZvLxJ57E7Np8+H/x9p7Bll3nmd6z1s77\n5HDPzbfv7RzQjUYDaAQikABFgEEiRWpGsi1ZNRrXSHJNucblUmnKUpUp2TXj8gSVambssaQZBVLB\nokxZEhNIIpEE0QC6gUY3Oocb+saT8857+cdp6u+Iskfr3626dWrX2Wet+r71ve/7vNSnpd8lI7L0\nVy+TTM2TKXUZNbfILvbZ7A9wYpuF3BTObh+rFnLKmSNScDidIdpNsdQyyftVMiRkA51dPYSpPJ3B\nADc7hWtGFISNXJeM3h6StbLsc2coZHcoV/LMl006Sx7l2P07OSvS5a+SnCqyMHOYuZZN72sXqb9i\n4rdvcufGNrOn1zDMazSCHTTTQqo8sQcLswWG3RyxvsU97SaWmZKVJ/HDAt3WCM3YI5Ms0L7mc/Pl\nHKLZIh4kxHEfSRFNM6jkY4Zei/nSY8xNn8bJDTA0KB07T7a4Ttg6zY23PqDYXeRwZoV48zhsuOiZ\nv2C2atALYa11k+rBGQ6c3SOMNbY3j1OZc9gYROjmYVZW5lgKWjy87PP+N99j8WiJx55+EiFuUeci\nZnAE02oh7FskYZ9kd4Ggm0eTJaJAsX6jzEg8wNz8GdzSXWZrB0FVGeuXWDjzEh+N8ty4kSOOq5jZ\n8zi5PobhYFpdVqPf4JM/+ShLhTPMHHgJs5CSc0J0EgxiVPp1Nhp5Ll/poy4foVo9QXU2wyjzNspe\nBVHizLFPIYtdvOFVzEyd4Vhw5LAk2w8hus0//e8/ya//q9dYWHqaN753HUa7ZL9/g6d/dB8qXaW/\npyhNZdi4+QqJ53L67D2qlWkajS7razuMmxbvvrNDpfwU964ELBwUWPo01y7uYokjmOkhNq51eOPl\nv2Ru0eDDH5/iwptv8ZUvQin+NJ3uOUqlp/nq77X5yGemuXHldcrZwxw8+yDVms2LRz7H97/dp9Fv\ncWkjy6HaMr65zmbjNQ4dOsl8cYePZs6wWTJZ7zZI5XHMqTucOHGacdgg8gRG1KdgK7ZoUEUg00P0\nNxO8XoGHntQpL1/jSMbi3NccWlc/QZIqFs+8h+3solsdBl4LP+3RH6Q4WbCnBuQODWlmb4G5y/4P\nl5H3TtHYOUBsrNN3ruEYLmlkkEscwrakkKnS3m6TBgcIrQ7mUpsjeQ9NDNl9J0/QXkLqBgvaAne2\nNwnzfWa0Aocsl9CtAguYboRpZpgqlShMFYlbdSLhU6l1Of2oIs5Jru/A628EzC0scm+9jagbZC8Z\n+FmD0gMSNe2QjgNEkkGzHEay/zfa5z+kdErjB/XV/etXEpJJIhA6aSqIk4gkUsS2QRinhLEiDhV+\nNMbSbYZ9HzcLXl+RycGgk2BnII4gTkNEKoiCiEzGxfPGqCTC0E2iKEEz1aR41DSCKEQzNOIgQcUK\nqdnoZkIY+vhhTKIkKhV4YYTnqUn0rhRIoYhiD01PGQzGhKHCdX1cWyfrdkHGWKaJZYPnxOiWRRSF\nGLqL1CQijkDESF3DdgySZEiKJOM4NMM6pplnMBxgWRookIlHOHa4uePzv//7V2n7JtliiSQdIgQY\nusVw0Mc0JGkqAQ0VGYSijpv9LN3hBu1WnZX9+3jhs/+Mr/PrbFz+K6aFzXSiI4vT3PT6iNAH3UGk\nGtLWiftD9Lsh4UxKZQoK2TzNRgtT6ET+iDiIsfM9ysVZxn6Iric4RsKwMUYTGpZtk0Y6OSeHLhIC\nb4CtGyThmN2dPq6Toz/yyeQdhuGQRE1+G61+Dz+KCIVGomnUt3coVSvMF8uYjDF1E+IcL/5XP02o\nFAaAbRCkySQRKkowTQuSFLSJJ0hMIqJAKBIhkUrRfu8yf/IHf87G+j1e/LHnGaVDCvGk8UvCCa1b\nKSCVpKlC04z7f8coMZFQkWgoFU+eCZ0kSQBJmgqUEihdkab3YYH3k9UUCUkU3bdVTxoZKSZxzwQW\nsZNwx9yi0Df5M/kei/yXjOrf4p51ln7QYYUc2WiHipajE3Zo6wlxMiArNbJSoFKNSKUEqQAtgSjF\nVil6khLGEZEORmpgBwsIo0nquSRygCkFUEKixgAAIABJREFUUgSYUkcTCs1RWFISJxDpEqlrmKb2\nQ233v/WyHbIzDosLWXSV8nA6z523PK7fukmzG7OXjjj62BymY+O+N83WvTXe/Z7AcRbpjAWrm236\nkU1Oz2CULGoZQZALiMeCUI4ZD2L6Q8XeRpckG7PyRBlDRphOFxzJvTt36A7rLJ2oceSghqM01nd8\n+v2EZjtLf9cjGk1huybDlkNzEGLYBmGoM/RSchmLXM4h7oW0twLe+O4ODzxfo3agxvziAfK1LkKN\nCefvoKqK408WuH21z4Uv32DpYYtTP14lN+VzzCojqLGrGoxmYTkuEw8UcmgwHI7wxpKMU6CxFZJu\n7Gc29zhf/9e73Fi9QiiO8lH1MMcfmaHTuEtLDnHigLLbJDJuk8new1AmcZhD5Kuc/JU81pKB9laV\n7msm333zDXZ/rsUL/2AGccZF7gWsaCbDZESSi7HcPqokqZ4skTk4w8aNIo33h7x3vc4DVonsnCII\ne+w1h+yr7kfsGjTW2/j9mM6dHezEppqfxtsKqFsS2UyYKWYplvL0tkO8XszQHZGOBOO6SV0VsCxJ\npEn6Q4/Yh2I2onbIoBuOGDZCstiYe1kajLFUlxdFlrO/dhzrn6zyXmaNft2ncUcn2nZgoNPzQ7T+\ngLn9CSsHK6gpjQPFg+SIiVVI/WWf0hcP81HvaV4JJC+J6+QRGBnB2pUWg3zCMAlQQhEETQQRYWoQ\nWyGhSvD7AeXKMpapoxKPMA6IgjZOJsRyurSjCGE4EMbEqUUoNLzQICdrKKPP+nadodaiWe8RjBxC\nz8DKlukN6kTBkHEqmN1XIN73AVNn8hTKPt3rPdzDR8le6CLyFuRsKrdirptjDs4YsC5ZdsG61GR3\nb5fFJ6bIPjzDo2IfwTdytG55jJSPKXLYazqbubu0D/ps210eeMRlulCgNqpQdfbxQGYKMe4yeitg\nsL9LO9yiu9Bl1If+7t/NUTHyxwy6IVFLITounrdLIM5w93YO9V2drT1Ffn+AnTMxnRTH8rEKeZzC\ngIG5y8adgOaqh+sqZg6/RhhBMphlqvoYqnWYD/5olejyAaLoANudde62NvDEDZq9LgcOHCIRS1iu\noFTrsHDcYe6pv2Dl6DrlmZjbGy5XB5sEPYtu60U2vtpi/ZqO+fQW+uM2RXeafW6TcLpBed89IusA\nV849wHhtTL3+EPPVNmsdReaQiwpWaY9hphtx51wLuWJSmNnHSB9i4JNzFdWHB3z7/95jp65RnQrJ\nlrPstTYJdraZW4FEdRnHARKBlNPU9BpPPOnxtS9/m3e+sMzP/qJFTq8wpg4CVvbPs3axy1r67yho\nfYSt0VU9bJnHCKeRssnSzIBaaR/f+saXUNozGNMp3kAHYZCZWyUOvoUVghnozHvPs6e/TVz0ScQ9\nguHb/MU3rrF9+xZ+3+PQvk9w69Yaj37IYaEyxd3WHep3n2DYduiOpnFll4WVgPF4zL5TZ4g/uM2w\nGfLxTz/MsF+m21sj017Gzp7AcL9D5GxgWDUuvn6RR+c/zKEXj+InV9mLL1GdG/GZzzR4681X+N5f\n6jQax7n5ncv8vZ/8LB/7sYTMQ1mUPscH373MiSOSnY0eh/bnKVRS8sIh3DrO9e3TXPz9D6jvRUyv\nnECOKxw9+SC312OufvBl5qoGzXaLlaJFEEU4aYl7Gz3maw1at4s0NkYsfDYgyY3IjI9Qzpa5cj4g\nP3WJB08PiHtdBglIw8dLEqRhMFZjZk70OPPRE2jlEKUtEo/L+FHCqH+VsD/NPv2T9Lb/hP56TOHo\nXexcF2m3kKU6hZWD5Kur5GaHxHMRK0Gfzq0iRf8FDBXhyJTVpIs+9BE5SfUwWJ5Gcq+LbQWExZgT\nZ4uYVcHt7l2219oUHY/ygz7VI3mm93IkYYvLFzzWlaDIQb7x8nv8/ZklTLVFtaKxJ4dEocdiZoaj\nD//N5Ng/HLCPCZwPJhAwKUFpEZq0EEjSFNI4ZOwHaLZDmCqCyCZMLMIoJjYCknRA4FlILabXDNAN\nSTAW6FpCEIboAiBlNBrjmAonm0EKQRgmmJoGCKSKybgOnU6XWKRY0mKoYmIkYQKRgihMGPshYZyQ\npAm6bpEkHolKkHJMkuoYJnjekM0NcC2JaSmkLsmNQ0Z+ijaMsFyDdOCRy9r3gX0WpimJwiExilSB\n5RoMwoRsNk+n6ZNx8njDFkIfkyqNa7dSfuv3zzGSLlomRKoYgzxCJESRP4lrvV8EI4ckliBJEwpu\nET/sEaQjeu0R5XmXT/0Xn+f72TzXz32BkjHFlDPGliZ7tkmvF7IXRFjZiRG22/VxjB6FrE1sa2iu\npNcf0xsP8IdDiiRY5QhL6FhaDlOYTFUN0BVCGpimTn1vEynHjMYDTL1ILHrowiFVEaZhMBx7SFcQ\nxyHjOCAxbHb7Q4Rp0+u0ma3WWK5U0OKIhdoib97c5Gd/+VdIlcAQk6mYUgpL3HdlGNr9DmFyK58K\nQSoEcZpg3W8ydq9vE74f8fwjn+UXXvsZLv/bV8nljxInEYbpEEc+lmYRqQRdWiDF/WnahK4tkZhS\nR8USIQPiNAUmkqWUBJVO/CBRHIGa+D0iFaOEIBYJ1uQ+aCLjUxIpdQwlSIWBLjXscYadYhc17PHM\nAvxm/SpDFZDJ/H1WsoKk/zLV4D0eybhU/TKOiGnFPu04RKUSRwoK0mJoTpoKqRmkBugI7NBGpOBZ\nfVSoiLwRUlhYpg9BgMxIpBVh6TrCNBARhKaLtATJePjDbPe/9YqGOlfW13AKfZq9GMNYQvkRrd0G\n/RE8eHaWo5+qEPhDls4e5/v/ocn33toi8S1qywUkNoszOex8i+UVk2oZJLB9T1HP6NxrxvT9EYGS\nKN9EhAV0LJr1DqN2n91Gm+yC5OgZg2nVxaFHPCvxUsHeTY/Gmol3awTRFKksUq1Y7Oy16G93yFg5\nLB0008JKUxYrKyRbJsEHBv0VwXrRY/ehJgWtjlYbUTk1R2JL0g/GfO/713jMXmbfAxWQA7KVPmm0\nh+2aTOUi1OIy2jjL7j3B7uU9bg9neX7pIOmmzc1XS1w5b3C+Y3GQZ3moWObwsRRR6eEsDFjMJJAd\nkisHqIJElVO2M30cc5VBMmS7qOEeOYbtS+ZmHsD8U7i8+X1u/M9bPHx2mYdenKEf7mHpNtvT20SV\nXcJCl2NOjcNPlZldMvnLWx22W2Pm+i6Fjk7Wisk6GSxdEaQDio5FszNCJjaDbo+oa5N4FtLXiKIC\niaPjdSK8EMa7Kd+5dgfLKiHjHH5X0fR9rLJJKgUyE2KWFJmiAX6OxMqRvu9y471dlMrxqMjz8D+M\nmf3VMQEeQdSl0ewTtDSioUZez6PMCIOIuDum3Y2o1QwawqM1CvDe0Rn94gJfbY14JvIwmOVH1FG0\nlS533HcJbzcx5odotiS2EzBCHDfEMWPK0waRn+HujS5rl1YxpUTLRBRn4PSTS5SnIGuWSKOIjdWY\nq7d79PZCuh3BcNDGKHbI7Pbw7B7VWolhW+JG0yjPwY4lJiEL8yZqyac6FaAKqxTyCzz2uSp3b2/x\nu7//ezzjHmK/0SMYJKQLQ4Q5QK+Y9Or3UOUxpQcr5FA4Zw04W0KZNaztRWZuF2iLlBUFvfH7dINp\nknCHuGYxGPfpE9HZqTCdlHHGOm3qRC95qNkxM2WXzH6fYCEguvWfnwoOoHem6f4/Fmvbq6y3aniN\nTzNdOESz0cW6aZM6efadMijMZGj36oThPkzRZExIWZpkXYfXvijxGyVqM1VEIWD+kIYqDbl25w1E\n+xSRf5CLe19np9+kHXWoLS2TpDbdzjTHDzzK1LTLgUe+zaM/81dUagltAhIlOLQvoDrXxy+fZXN9\njHVrP9277/OLP3+WKHsFnzqWgpCEkilZecDhG29ewawfouJp+JezdAazGJe6jKZyLB1XrO98wMLd\nE+ybG6ClTXztGkK5GKJCO2ox/cA8Dz63yJ3XL/PoUzU+85NnMJe/hGbewFQasQhIVYoUJVpBmYy5\nxZFTBmuXfZR3CJXdIG9OE4sOe+P3UdYUV983CFqPUFq4zhPPjXFwyZtFYI9QpSSBy+Mfv4iWgiX3\nk7Ur6PocTWfA3ds+aSfLnSurpFGHo4+sEIoOy/NFouFb3L2zzsqjWfzeJzC6ZZLtlL07Gr/1m++y\ncMLl6U+MGQ1T9jY0Ko+vIbMHkEhWr60SjEYcPGkwfUSxcfN1bpwvM1f6GOevfglr8fs8+cyPoNQe\n776zgVZYYfPGHqFy2bo25rkXHmL+qVmeyX6I9vYa77xU5ODyJ/n+175LriQ4JndY3bzNW6/c5dD0\nKfK5lPUrt9i9/B5mbj+Wscz6dpdb6ymV+X242XlyeZOf+2+P87/+i4uUK0/wrTe/yNFTWer1EXEi\niMKIREsIRgOaLcWjj69w8IDP0NOolVzylS384TEOPbAfK3ONegOKIo/Mptg5m+21DNFgyPyywMq/\njaGXGLQy3H1NY3RNI1s8RbhxGeHFbF5YovNwjH3oPfadbLKz7fEjHz/KuZcvsXjYxcgNUbSw5ndx\n9lUpJvdgaFLLzVDeKdFImqgoRYkBx57sEiceqSjTkxvYZ1aJMMjeGXAgc5CQmEbQYKqyS63kcuTx\nLrpVA6dG1tzPzsU9/vzLHWbmM/yom2UQ9dn3mGIrvMFI/5uxubTPf/7z/8l/+rVf+7VZ4OdN00aI\n+ymjQsB9y24qUgSSJE1I0/sSKKEwhcIwNGxDoWuATJGkaLogTtSE0qwgUTF+4CMExEmAJhW6LoGJ\nH0KXGoVSFk2XJElEFIWMhx6O6+B7IVEcEUQBiVL4QcJwLOj0IgajEC+ISePJ48bx5EYaoSHSieZf\noBNHkzQr27HIug6artCEjkBiGtZkkiFBaqBrGqlKECiiMJ544tMAlI030ND0lDTtk6QmSoy4fL3E\n733xG0SiQJxEOI4OSTIxIt//GiffQ4KUEqUmbOtqZYZnn/kMo3CIpmnEYYrSFGbWZG7mNGhV7u2e\nQ0tNrDQlMk0c10azbXb2GkjTxC2W8HstCiToWZN+2CdTzLKxukouk0d6Q2KVYAiBF/qkaUCsFEHo\nEyU+ntfHdQ10U5AIRSZnT4pXXaM/6iO1lMAfYqOz227SS1K63ghhGjQbe9SqU9RyGUp2CcMKWb3R\n5JP/3S9hzmcwhc5fk/h+sO7rowQTOCRxClLikxJJDV0I7n7tIqs336eS2480W/zHl/+UWnaZ7rBO\nzqoQRRNAXqruv3QUQpMIBHEaI1KF1LQJZRsBUhHHMXESoYS4/w5SYjWR5SkUQgk0KRAKJClCU0gh\nAIEmuc/4UCgJ9tjAtof4nmJKHOBS+2vsy36IjIw5LFy+PfwW0+rT3Kw+xB90y1zJ7/CdWBJbecpm\nmYqVQ9MsmhpUxi5CZDC0PImZBWliJgZpGuPLBISFIQsoJL7yCNQQT8SkjgWuhbBMDNtCz9jYtkM6\nlly8eBfgtz7/+c///x4p84Nz4uhxgyi+h5IhcaQz3shx+Y0B9IoU8kWOPb5IcSnBKbcxNZ9hs4Ma\nS67c3CMe5nArJdKhjzvl4xZ3ae9dmcQjugGOlkP6eXbXfHQtS2Uhx7C7xd7OJp3+AF/3UHbMzLxG\nktkjx5Dx8B69eERjqIh2p2lsZxmt20g9h5vJEYmEdquLTAWVYok0GOMQUCvnmZ+aYnapzObVbZpr\nHTKuTeaARnHBgYyBXYb12y3GnYSMmWN20eXAmSJHD07jphFSHxLEIwItxk6yZKwq436AWczTqndY\n34j53m9vcf51n02vyoLYz4PmSaoLEXq5TZKvI+abpMsDGmzQTrbwnR4DZ8i2do/hSNALBM1QYnXz\naLGNFg+ZPlZjvrTIaENndXOL7nckhXGecKDAgkzZonrWoLA4YMbYwzR8xs0midTpjT12mrtYtsby\nsTx6GuJ1R6R6xNgf41Ylqezh0aI/2iRRA+KgS5oq+vUBhrRwjCpe18IcZdDTMtEABn6CF0VEyYjE\nCnHnBJDS3dWRVxZY+0Mb38+yIhYYTt2l/fwV8h/eYYTHptZksA5a36QgpqmUCuTyFuWSSZj06Ma7\ndMc+UayT25xHfvMQw68e5LX0JjUOccJapvSszmj6HqNSh71kh0HsoWUMyqUsmYINiYdh+TgFj+q8\nTcnNUd8NkKnO4sECy8dzFBZieuNtxl6DYTBCR9JtRzS2R4RhzMgbUalmyJQMsoU8U7PLKK+ALaeJ\n+ga97THjboepOYfZEwVKizpeZo/rhcucsqbYP5Ol3mpTXZjn6rUN/uyb5zh38xbJkk1pNs/crE1o\n9ljvX+dde4M3/HVubazhv76LeL1JGhQYUUZHUKjlWPlwF/3IPbTZDpmFITYZnPES2/+X4N2dBhY5\nspmI3OkNDj3rk11ocUpUaXXLfP23Gv/Zz4rP/GyRkb+PQafKocqTZLMu0/uqNBsbGM4OhUoTc+oO\nI9FC6Rr5mqLRrhOFfaKtLDuXFti78BH8+jHu3tLobRzAbp7AuwXdtT02dlvcam5xced9nHKRWFqI\nsEDN+hBPHTuC6g/52E+f48Tf+xL5WoiPYJplJljVIVKf4/0PJJpXRIoxj7y4yfzT9/DtMY5wETgo\noSEF2IbO+VcaRLdfIDs2qVTPok0dxrZt8tq7nHjGwou62JlDFI5o2LkWHe8GkReCFtLxFbvhiNWb\nY3Lxx7lx748J6LC9Czs7A1RYYmFqP4aYISUgFJdJcSmVXFqNLu+8MubDzz1JM/wmOX2Gjj9Ehctc\nv2AzfWCTh5+2ydoOiiYxW4CLEnlS/TZSxGRNHdJtpLGOZmqU3KNkxUNsrjb55OdOMLe8j0jdwsm0\n2W5u0Bht4pXqRKMW8VaPZ4/+N0gnoJI7yOVzI9ZXdxHdj/HNL79OxZpm+eDjqFCy3dwhUFc5/tAy\nZm7I7SuX2Vy1GTcrrK3eYtQPeOrJR4jNa+xtQWe8x+knHkGz25x/4y3W3rf42As/ha/uYE17VI/u\ncOGtXbbqPTzL542La1x45S65UsKLP/oEG9s7tNqKk4+vYJV0VHKEb/+ZgZv+CK3+mHt758jKFCcJ\nMO0O3zn3m1y7e56Dp+bwI49cNotKR8QB+JFJv+Vw706Pj74gqS00sOVhMJvEnk7a+jH6HZMB5zlx\nVqMx6KMZeRoNj9ZOzO5qyFRpCafcxY/a2IlO/4Myt1+borGe8O6lOoPhkDC7QfXMbY6/sEjDvEFl\ndgGFg53XWVj2UXILma2RNQ6TeBV21yVZTWfcbyL0HI1uC0dXjL3LnHq+i3nyOtmTIcbMGun8BoHc\nw2/l2HlfYlKmutwgu+8WZLeYWg5YOVSi1xnx3tVVYik5dPAR7t4cMlj3SBo2oRygT9ukXp6v/6n3\nnzwnfjjpVJoiUg0hFKmKJgZpQBPGxJyt5IRxEKZEUjCUAqMzQpMSTZpoIsXQUjRNTqYgQpCmEUJO\nDNSpkggREUcCQYJpTjgKsYqp1+tk8+4kWSrVcAtZ+r0Rpmkw8sZ/DXaTcsLa0KRDqgJU6iPuJ2Ol\naYrQJoMDQ5eEYYQUOrqcROBubke4uSGWlSB1E0WCaZqk6JPmQ3NJZIoSoGsWhpFOiszQQTcjnExI\nMDYQtk4qdS6/m+MLf/4msSwTpYpSpUi7vUfGyUCqSNNo8kxS3L85hyAI0E2dnZ11xl4fKQROtkTi\nJXTbQ5ysSa5icPbFn6BU28+7r/4GYafFgazJbreHbTmY0zVCP2SjPaZquVzd6TFjmFTKeQZpAysr\n2RluU04lVjQEsYhpuXjBGNOwJ2R3XWLqBsNBD01LkELQaNYnHpzUR+qC/n1mRavRoh8l+LZNZ9Bl\n7AfMVqrMVcrUMjlUmDIeSg59+lPUVhZIhSBIIqxUB2NCAEfw13G2CiYcizRFKI1UShKVMt5rk9b7\n1FKHeJzwv/zOr1I1Fmi2OjglB4VC03TiJEIISZJMAggkgpQUKcQksEClKG3SDCdJPOFLCAEqJUmi\nyWSOFOSEwwGg0gltWiqNRIX335e6Ty9XJAiSNMB3JZ1gj6q1QCPwWbVH/La9n19vvs50aZ1HM09y\nN3qPmY7OJ8orDOJTtPIxL8V3+FK8SZGE026FFW2apBCTTS1KAgwByJBUD1CJQI/zCN1HSZ8UD1SI\nlAoCcDFJpAlSYFoWhiUQhoOf+VtUBH+LVTJdHji9zFQtor6jsbYnKOhTBGIK1VG073TRsz5qpkO3\n0cCxElYeKJDJFtGUxmjbo2s0yRyJQG8zPTdiJSMZiYiGPU+8m7I4b2P6BmESEkqJholrF3GIkLbE\nmYGs6ZNnhJm3yKPTsSpEc9PoF4ZoKuXogQpxGNL2xkxVNEr7iwTdiN5eE2XkMBxJFEmMjMXJ08tc\nvHydV37nOh+ZncErOmT1AcNuG8/p4867nJyeg1Rx93IXT+kYMzG5uTxumsOOTYa9Aio0GGcTZvdP\n4W2abP9lG6HVeKx4im5vGp0cmdKAynRCMj+gEd1hNNihHOdx5kLckk6gQgauxbmXI/7BLyyxpO0n\nCSTedMSou4dvargI9j+a58AnHmP7a/N84eUv8tZ7ksfUfg4Upxna9whmPURmi5P5MQenCogXDd65\nHPDu99bpXxuS1UI+9MQ+0hmfqUcijJaOu2xAILGEpN/rk4sUoWgRGgl+vMOwH9EdOpQrh9HVFIOm\nThxCIDI0hE0y7uBOJcxOxRSMlHAkcHpF2ldyaP0aVWa4o67TU5f4hX98CpIxO9omN97pou25FLMz\nZKw8wTBEGiBdj+nDFvrUHP1IIYYzJDcOoL92AEPN8j+In+LxI8vwfWh95X1e/ouLjOMhqa5j2TlE\nlNLvhURBQqoNmJ0DR7cQoo9wbAwtJVEBlUKF6WmLkbqL6QbEQYClJ4SBTaHg4BYUcSJxdUU0jgnb\nKaZ0uHfJo7enE/ZG9HsD8mWY3VdgbsWhEddpbHbpj3vMHMnhyBFeQeOxT63gbSaMdgxOLjxDLxzT\n6/V48/xNHntkgf3PVnGfKxIPm9x+e4f3L4248o7BqW6ZY2KXQHnMc4KomGCeXODAEZ39D+fo6Anb\nPcH4Lpzf26HGIkfzBfqnR+hTJovTkljYFPARhH8nZ4VWVlQPphx5/CwVDXyvzs7GLerdHudf36TR\nCZk9dpDW4DYy79PptlBjRWfDJHr7IGsXFqiII4Sl68hwSHtcZ7u7RDuGwKvSJ2YviChML9HqQl5O\nc3b/Y+RGizidBkeWZqjf/ApPFD/GjnqLlIShqpCIIprqkPEd0paPKUt0jHXSY32iTIXc/YsmD53U\ny3Dp7S36e9uIVJBxtpFylshV1LsNVmyNvthGq21TZJc772Qp7DeYne5hmhb9bsD6eobIGeAYGqbm\ncfC5y/yj559ja2/A229fYPtWzNNP7GNKz1EsWWjOSUzzdSK5iytzPPqMYmva4INbX6c8V2Jk5shk\nW4RxnYWFAzz2nE9qbpKqOURqomlVSE7TG97EyZmUtcNsbPYolhWp1Ij1DaxSi9xUSHVhmnfO10mV\nRKOMZhnknJi+1yBsQdhX5DMm7ei7/KNf+jn+z1/5NzSH5yhkY1595evkbZutGzs4Xy1y4iOKlRM2\nRqmIF53HEY8w6nVxnYgHf3wDgwq3ryVcurDGg0/9GLcu/zGPPP6jyOwunfodsm6GqWlFPfo6rtpg\nJn8KccfEFor5hxYQmsul7+9jduESP/2PNRJzjYXjH+cL/8drpKWEowcO8s6l7zAIdGruR/nQh57m\ng60L1IN/yVsfGKxZRxi7DRrNHcSVgMKMQaSDVQIrA4NhiN/OUclpaNkBHpKRdxtf90jkEQLrVbrd\nHXZeznP2qeOst17DcDqEwyofnB/zyKMOZskjVIeBmyjRJK5I2L/J3pWPc/LhI3T6R1hcfIzZxX+G\n6+5iWSbBaJVuf5XK4ixJP4cxLGCbBsLq4C7uYC56TOePYzGFuBZydVMRpgHDnsmgu0RaaaLlNslZ\nNmaUo7MFomdhqiJFYRB3xrhxhtToMZQ3SUtdnvmRT7J+Z5fWrqDdabHR8Cm5EcXsAsJr4ER5dnf8\nv9E+/+HI4FJOUpUEE9G6iFGpRiISpJgkUimlo1RKksZ4gUT0J8ZZx5JYpsQ2A0TaQRMupq2jaaBp\nEsPQJ0FWWoyGnEwelE6aTtKcMlkHXZekaUKapLQHbUzDwhuH6IaBCiJUOolfjaOEIA5RCiQ66n4S\nlNBSBNp9ZY5ApclEmiMVfqBo1Me4WUE+J7CsAZZUZEwLTbewXIGmJZNiU1foUqBpYpL2g0+pmCMa\n98lUTLq9Im+9V+f3/+gSnpQkaUyp7NBpNXGdLHE4mfokatLoCDSUmKj+hWDiT4hDVOxhmAaaZiGt\nBIOEyOsxEC6FYpYTTz1HwZ3l1e/9T3Sv3KY2bTAYNsmaNYZanvqgz16oEearDLdG9DoB++aKZIoO\n2/UdxrFJppDHbyhK2TKOZRON+9iOM+GgoHCdHHEsidOYMAooZi06/YAwjPD0hFavxygISDBpt5rY\ntsWBxSWqmRyzhRz97Tq2nWeYX+IjH31hYuyOEpQGSo+QmJMmg0lTmTKZk0Wk6D8IfCKmIHTeev1d\nKm6G7mrCyrxDw/L5p5/9dc7t/glfeeVNCpUUlEDTNJIknUwn0pQoiScwQENDJBCkMXGUIsVk0pGK\n+xMKMWGzTLw8gkQlkwcAlPoBwEqRphIpmMixJMRpQqpSklRiSEGg8mwlXVS8zqIzz79a+x1+avmT\nnG9dxFgy2bft0s8e4096v8bT1qdwrTKHnCnSsEAnqvNO3OIb/nVqch/ZVDGPzaJhsWLlOaAXmTJN\nstIjiIYQjokihZImcZIhKraJDJvItNEsg1QXaKYk1COUMf5htvvfelWm8xxYyLNx7wO2bmi0drO4\n2hxBOw/jhNatgNgYMGX5JF6T0x+qoakst94R3HinSy5nUyyWqBZjalMpmtamRYdGErL2Tp+oHRNF\nGczEJQkFZanIui75TIKb9YlkSL/bAT8cAAAgAElEQVTdIzZ9MmpIBsWmhOFOkc07e7R2Ug4cnOHh\np7PsrtdJ6m22NmN24y7pWFKchsOHLEIR0V1dJ4g1yvuWOCmWefetgFtfTbHKNdRjkt1eExuXY59c\nxPFKrJ9bZa8+wLuV4vY8CgMDfyQpiGksd4ZE6UxNlRiJiHtXVtlsdvnxj59l5sg+3n05pd9sYBQF\ncq6Du79HYUZHTRfJzCZka3kyNZ3+WND3Rrz80jXeeX2b9EyF9tUQx5OE5hD7kE0wHRCXc8jNhKNH\n8vzS4k/z7p/c5WX/EvU/Uhz/2SrWrE7tOYlp7CLpcvqgS+lQgl2scuddi9EY/vJL7zA3k6UyI0iq\nUJnPMd5tIkKbAw/ZHDlWI2O5BHRQqkS7GfPBXY3tSxp+CGFfp7MdsrHZppftMfuUYv+BHKfO2Li5\nIZ3VHNfPw42/SkiVTio8Th1ZovhPTGrlDK+It2kMO9BO0QeCwOsSjQcYGYNiTVKe16meytEKhoh1\nne0LBW78pqR5PsNQeJxVfR4fATFUfqZC6YqB2kqIXZti0cCyE4TWR1opU4UsmjVizBhSRX+sE+oR\nOpLxQCHihDTxMU0I4j7ScEmJiDxBKZvBtC3KRY3KjM8w6RHEkmHDYLQXkoYJM7UZDh0vYNZGZBcE\nhiywdU8SGIKSKNDLtok8i5nyEu+du8NLF9ehX2SudognnnuSlRWHW7e+w1p9g7mTBoWnZtl3tMTo\nWz47WwHt+lVuKJ0QC0vEPDBThuoY9ZSLUFXKicduu8X2lV3ijMWBBx+gZzcY1+7gHF1F6Vts7cGV\nAC7f+zs5KvDHHZYeOEDBqTPiNvp4j7lKiVY/4fqlFuurOn/wb1o8+GSJxdMe450Q1dRonz9F++2T\nlAoWlgFpEBGHfQZBjyt7I0xVIpNVRGpAZ9RluXCC0nSF6dIiG1sbLGb7JFHEYiyw65/jxlcTTnzm\nCertPyOwBIOwRRiM2dm+x/FjP073ehZpajxweoa84ePFU1idz3Br5w9xZ95j5lDC/FGX6uICr/zu\nq7i9Z4nvvcH+mWMMB6skUyHM+bjVdxlfkNRvHaZ/zEYvVZmZbXHlWoJUNq0tg2RvisrpdwhyMQ8f\n38fjH1ni0psxl87t8m//eZ2Dx3Mcf/oSxx6eoqTNMQh85mbuIc0NgnTM0K8xlTFRQYFKZcAfv/s2\nH/rYCebKn+bmxgUOHVwgFg+SutfJ5XXiYJlAzVDfsMhrB3CrA0K+g631GesvUZp/FCHOIJI+d1Y3\n8KMuhhBous2MOcul/ipnnniMi7d+h/7vfJt3r/eRRZfq9GfR4wUM/Rp9/w5kbiD0PHqxQL/tky8+\ny60Lm2xcr/Pj//BFRv5FEtlhrK3RuvUxLr/9Js9/7gSFkk67e4dxBH6kePCxp1k5ntDYMHn1P6Z0\nt+d46IkbvPi5Kf7dv3iDpdmnuHLudV79wxHPfvYZrl69x/HDRxisjek5EU7/DGm/Q2oOydZKFK0q\nYZRSyqXsqkvkizbz1hSjjRpuvkhjcx1lu+gZEHHCrQttDiwa+GnAjc2Q8tSIRNkcODHP9796kztr\nQ546/Vle+uIlikdm2X9oni/8+/d54uwS+5clKyfqbO/u0W8oypkQY2WAN99nsZpw7OgJ9jr3+PZX\nLjB9d57u3Q2EqcgVKtAPaTd05NYM733rfZ7/xQcxKxtY1W3OvFAgY7VxtAyb3S4z+6boNus47iO8\n9XKXbNPjgedcxqbFoDfE70V0+ls0/RxoEsvvMwz72HGIbQr0MgTWmLnCDOZwSHcYMjdbpD7eZVZN\nE8dZojWX8W4B6P4n9/kPmTo16eIRPyjYE5Ti/q3uDyRVk6IsTRRRrOH5ioFu0O0lOHqEriUIpWGa\nY7TYJFWgEg2VhAipoych0jQxdB3ExPxt2cYEWia4TwHXKRZs+oNJ4RQmkMSCOBUoJUEkaHLCU9A0\nSZJMNPjcjzdNxcT4a1oWaZqQxBGxUgxGKY2Gzm4lS9YOMUVAxvLRLB3LiVFhTJoTmKYkkSClCYRk\ncyaEklrtEHt7u1y/7fG7X3gfT2go5VMuF+i2G+SzhcnNmUjRpIBYoH5QWgtBkkzkPjIFqUO7V6dQ\nm0UlCVLXSBOBNA1E4tFpGkzXysyczvPc1L/kkvYbXLn8JgslF1uPsYRPZbHMWqtLbxShEkXomtxY\nbzIblcm4RbbWdykkgmZzQK04pFauoEuJGMhJxKqlMwpGKGEjdEEvGNAcj/CTiFhqNIcdRp7Pxt4G\ntumyr7bE8twCBSNDRjcYbNSpzMxwZbfDT/zyz08aCCEwhIaZSAI9wVFM5EkAQkxiZYVAxhHoE6OR\nhiTyIt66cJViMUfchrt7W3htjZ98+if48j//36iVq4RhiCYtoihCkU6aBpg0lJLJ7+P++07u/46l\nNNGlhtAN0ngi/ZNyMgoXUvvrSUaaCtDuNxeajvgBtTxNSdXksw0zYRjfJWtMo3kBfUPDU9Pcs0KO\nizt0yPCJ7gL/2vsP/PL0PJvBx6j3d8i5PRL9EHl9FkfPU02yIDV8zactIm7EHYzQoBb1mB8NOWlO\nc9ouYTgWJSvGCIeIpE0aDXCLMyRZHVk08bSUxDDRTB1NCET6N9NT/n9dka/YudXCkzC3MkO5sML4\n6j52vjck6MbMNPLklCTd8dl/eI7lgzaeN6K1GjKINtm7vsvCShH3bpagMCQxRhTmEmiB6TgEckxq\nKHL7LCrSJXVMvLhJc7NH4JsUVxxMYZNJFAXHYqwaRKFJd6PAcChxijaZ6RbF+Q1y8zEzYZZz3/Np\n7Ib0vIDq0ix6NSDwBzgHDGaPLaM1LQrVCs3OkM3VXdZe7lPVDEbpFLPPWoylRtfbRpsP+NCz08xW\nIV+ostH2eP+aT5zYVGolQsMhnO/y+uuvkn/E4X/82Ecp1/N8980bjJsJs6eOUjyu0ck36cW3qJoB\nRSfBNWLq26sMtob0/BG18gK1fombv93m8V+qUh4HZGt5DKOPPpPQ0e9xS0ZUjxYwvTK1I/BjL5xG\n/1XJd+6ucvGLYx6pLHP3Kx7q+QGzuRZzYZfUUtSWIsYNm95ayp0rQ9Zue5w4m8GcM5BGE98WSMcm\nV8swMPZQ8RaD8RahZbLnZclUT2EXLTbfT1h7a5edO5tssstjz0/z6HPzrCyNKZpjgm2d/lsRZnuF\ncexwjzF5FI/81w/TPj3km80LdM0Q0dSZqRVwsxqjbojl+xRmXcx8SPaEwU5nFy+2aO/V6N0uce66\n4Co3eUp9mKxYhBrwjTGc+n95e69g2a7zzu+3dt67c5/uPvnce87NAemCAAMAgoIo5iSRSiON0pRq\nVJwpSROqpsqyx2WXyyVXuTSjqRnLomRqlCmZlBgAUiRIEAQBIl3cANwcTs6d485r+aEPINkvHMol\n7Zd+69X77LW/s77vn3q8+KcvcvRdi5RqHqgYIWKyGUE2b6A7Kcq2CWwdf5gw6CcIDJy8y/5ei+JK\nFnPCINZjEpml3m7S2Qnpdoq4rkGsNDJ5i1LRJGdWaLZiuqFg2FCYhkE+79AbdUh397g12CZ1DIZD\nDa2dZ9DW2O6Y5Kc0Lu/dJHs0w4/96mNc/HKPV76+wcZqyL/5Dz9NOjlPYqRs6oCZYh31KA8Fw65g\n1xnC9TrtNvyh+ktOnPc55S9zaHud2V+aR2QzZG8liOs5Hpo7w7EjZ9nX7hI8vs70T92L48fMmz6d\n3oD6ZAb4h9d0xf6QVrjBWucmudweWQuEPiBOU6ycDusV6leyvNG2GW3ukIQb2O17aN24jyiV7I0u\n0Rq+yHq9hZbT0bMWvd4QYegMY4FIUyanFnAtl2DkkqQCaQ8Is12GPQ3NfZDRXoZX/jigdUNjZW2S\nhz+5w8wTAZ4okP14ji82b7J1Y8BZ7zjB9XNs9G6zs12nvrHB6VMB0ydLBGYPlzql2nXWI527fxAx\n0ztB7Lt09SYn73HoJTcwcpLSkR2ub3vcJ2cpiVn21DZThwye+SMduVYjl+ljuE3m5iTdeIuSAafe\nUWBqvsz3slnu3lnHXY84dvZRNMMlZykG3KZWthipElJI9kabeMa9jAbPc3ja4/JTEReais2NI5Sm\nNGSseO+HPkInucg95yawyya1GRcnX2cU32Y4GtCUglJliqyns5+7DUmHybMxrZbLyvUuYWue+naG\nnDzE69d+m95A8fyd60zkH4WeA7VVOo0tgvaQx9/xQZ5+9utI4zDqlT4rq1OE7T1MPNzpOS6/cIl7\n370EfIW3P1rhcy9fZ78+pKz/InH41xSLecrFc1y7+GfUqi+QmpMkoc5fPflH/Pqv/c9Uzlpky+ts\n+5fYXA+Y5WH+069/jb1bezz+T06zNO3yja9cZPHe01x+YZVRH9blFRaMQxjxIv3Gcfq921TnBTk3\nZL3p0NoY0tsyWHponrxbIfL73L3aJvU1Tp6Yw8isoWs6vu/RjfvsBV+EQoZud0i/MaLAu2heephv\n/skbTC9GLB5f4fiZGfxEYbtNwh2NzZ5AaRbOYcXHP9xi8+6fcwyNP37yJfzhb3Lh5d/lbU9E3Ly7\nR9Ir8PJf7/L46ROYZsre5hrTXkgvFZSXYqqliGS4wtveP8H63bs0NivkykvUt7/B4kOziGGTO7tt\nTh7J4A805o963Dgv6Q9dsDUa/U0mJ03UIKWx3+LW1Uscnf0gC4US9cE+l27dZWJiBjKzNNbOcfW7\nd6jvm/9N7/kPptGwXYRQ6Lo2TnBGQwgNDRNNaHCQCa5UimHqRHGEYZgIobBNgaZiTD3BECmR75Oq\nBMsykCohlQmWYeA4AplKEpniWA6u56BpAqUSZJIerCHwRz5hkGDoBlECcTz+zuEoou9L6t2AgR+T\nJJAmKUpJNE2i6wZK6YRxiGnpKCnRdA3TNImjIaNIYFsZPCvBNTQcI49Mx2Fthi5BaugaDPwRqUpJ\nZIqOhWHEdFt9rl1I+I//8avs9FuonMBRGZI4xNVtkkCi6YJUREiCg2ZtLFQWYtyqmaZOGkRMV8rM\nT99LbbpGioFjaEgjReoFNJHiGD5J0ENRpThRwF08i1tQrNx5hYpt4tlZhsMGtaxJCYPA0FjvDrAz\nHnIUYA4iqpOzbK1vYnsuo2hAOxwwkD4jFeKHAzpBnUAq2iOfxqBJo79FK+qjex5Xbi9z484aO/U9\narUKR48sMjc7S0lzKVlZzO4IrVCkvbPBuV/+NSbKZVLAEIJYdBAYmNJA/N206r+Tm2EwbjgkYCL4\n8pPf4U69xa3VDerSpzZn8P77fxqnK3nxyjPsDuuYembcXAhx8FVijF5p4wwMAaRpOkZJdEGqkjHi\nxQG6oY+1O4pxQJ/2pt0UAoXGuF2VCIzx3ocx/CLGlr6Wsgk0jxGKNExRGZPKKAY7ot0YEBc0ajT5\nePUT/P7W7/Kxwgd4MnidUdAj0eoImpRsG9PN4UVVQvpkpIWjEiDF12PqWo/VtMmdZMB+4hAkEyiV\nQdgJKjMkW83gmyaRnUfP5LFsG8MBzdIYDANefOEK/APzrh959yzluZBsSUPkSjjOAp2NMluXB+Rc\nm1SP0Io6o7SDqPQxC0OSbJvcTA5LOPT2QuJAx9QyZL0ytlFl0MgQh1OgZti6LOh0AiqFLBMTDgun\nHBZOuaBCzr98A6E0Ds9M0mp3kPqIvWZCr12guzlN4GeIg5TpmZAjjxjYmTZDLSLydba2e6RByskH\nplB2H9MZIvUOidFjc6fOcJDgahnq7Q7+fkAhUyBXziNDk7XVdfSSzyMP6ByfHlGze1ipARmfje0+\nrU2BNprg9rW7PPdnT/O2Dxf414c+weTsDLdWVlm9pUhw8Y2Y3BEHv9yhIdfp+E22t9dANvCjPZQV\nk+ox2sjj6t/s073icLp8jIpTxDYMwqDDXqfFULVwamDnI7w8WGWJNS1Zetssu892udJdJb4q0cwc\n+bkaqiBxvZSMCCiVMmTdAt0tm51t6PYMug0b6ebxBzD0BeEwwSlJhN3FEHsIP2KoYu7spWyuZ2jt\nlGm/YbB5o011MsvP/OrbefQnSpRrfaw0gL2E3e8I9i/kef3zLpoq8fjEB1k6mmVv8nW2jds0B7uE\no5B8kqVc9piY0Jg/LHCcFsWFDqG1QtTdw2xJhJhia8Wg++wc65dcHuWH+DCP0RVrTDkFbLPPU//h\nKZ5dvsS73nM/w3yASgPMbEK5YmJWwMhqDOWITn9EsxWwvxISpFkqXhVD19HiFGXqWLkyXrbK9rJP\nrwUZu0gUxvQ7Q4ZBnyQJGMYJUWSzv6dobUjcgs2xEwVsN8SZaGPmYwrlPFbi0N402buRUm8OaNW7\nBOke773/fkqVDJEvyOpVvvonL6EB+cUsqacoTGsURpKprmKqkOP4vTUW3zfB7IcLpIdT4kmf66Nl\n7uxucGdjm9a1hOUvxWz9zgLR946gbZxmcNtC1w0mH21SPikRrOOaA0xbcqWe5anPfH/u9f/fWvHe\nj+noXhtTH9LeNbhyPmXQjhi0E9avH0UNjhG3bfY3fezQZuuCQg8yrOzdQjkGF2+uMEx9yGgkhkaz\n3SNOdVJpYukWtmnj2R5hX8Mx55ienkOQ0A973HfmHmhb5I2UmcIJbjy3zT2FT7DVb3H03DFS51l0\nu0UodTavpbSueGy9kWH9jS4nFqE2f5tys8r3vqIR+0eY1j3ccgszZ7C5I0iTExx7uIp33/fIv7NO\nPzvE31vg9it3EVpCeVLgVZZp1QcM7s6y+sISt14okz+xyXv/qUbBDqjoVTRRpRt3yBV7HHmwwYOP\nu0Qqz9oyJDo4no8hbBA+kYpJtCbIBBnMsnKzzcWvPsSVF3c5dqRIYXGD0nyIU+zQbCjuXM1x+7rP\njY3neP3i6wTDgJnaYba3JI53GMM8TH/Yphe+hnB26AZdBlGAaeZBs2g3Gyitj2XMUD5kEVghWxsG\n3X4bUx7h7NEPM1m5h+XlFq5Z5fqlDS6/3KC1cgbSJ+hv5vDbOo+9613kKus0duuYaYVr3xvRufko\nF19apd24xcmz72fjesBfffEpHvuhn8bWazz75BaPvu1XWLmxzn1ve4K15zq8/rTF1oqgcOR9hKPD\n7N4e8DfPfo6XvnyJ5Vttrq9scPnqNv7+AkFPI44CqqV3Mj3xUVZ2djHzW7h5l42NLpYJ68sNyqUF\ndF0RJA0GzQJJpFNa8rELPXIFQa8X0W1YBN083/1Kj0lvCU3bYmreYL8RUnBO0qhf5BM/W6JlXCNU\nIVoiiP0SvgoolGyWjlUYyAtkiz7ffuYm/tq/4Pq1Ze45+QSvfUfjwrM9mndr3H0p4MTiKXJnL9PW\nO6SOTycVVObAsU1c18d0fTZWOuzfmabdDgm1DRYXF1g6eoxGSzJKQoJ+lksvLFPRf5Jbr+9RnY44\ndLRKu9WiVChRLsyxt9FnYdZh6nADs7QynvuaC7z04quE4SJb6xpRL8fmYOX71okfUAyeQwgTJUHX\ndBTJQZaZGiMbYixm1nUdJcE44N0LzQRhITAQwiWVLhigiYhEBqhUwzAMdCsl8McWpRnHIZUJuqGP\noR0vT5xqmKZFEEUooZMAcarhD4f4gSIUFiMl6AUxg6GB7yuiJEHKdEzNkdo480NFOJZHmo4n1FIp\npEzHVKhYoFLQXYfEUkh9iGVqWNImTTLotsKPe7hmARnoFDyPYW9AY8/mlUsBv/V7X2Wt1SeXKyKS\nBFOXY4RHSNAVqRoL51E6MHbu0nQJQqEJnTiJKbpFbrf3qCyVOL3wfjzNp0eKFB6eUHjZIkp3CWIN\niFAJFBzFscUPkys/yJWVG/T9u8xlc+h6ntCQVLWI+WKeVscntbLs+SMGvRDLzeMPItJEo77XotX2\n6bbqKGAY2DR7Ixq9OjutHlFU4Pm7DV594w7La9u4psEjDz7EqSPHKYoMM1qWYdjB0GJ8zyKuJ9Se\neD8nHn74wAZ23EjowkETOkoXJFIiRIJQKWMP27EFqxBj69hIJshE47m/eZ4zteP090McLyAX3Ifd\nWyU/c5qnbz7FfmsXU8tg6NaY9pVGRGlCKtT4byvl2BZQCDQMdGGia9ZY5I+BlIo0lig0NCHG6x9k\nxozzVyRCglAmhiHRxLihllIiOAjYUxJDgCcM0DTsxKCrK6asCZalz69PPMFT3bt8b//rvHfx47zq\n3+TTEx/ie/HrdEeKgbHPbrzP5EgQZRSObhByQE8EhEwQMiRMA3pqRFsbsSq7XIsky+k0y/Fp9lQZ\nPVeiWA3B6JLYGgPpgmbRazf43veuf9+i8Pe93qwTH/34CU4eVTi5kG6aEsksV15u0t1WFGcLwIDU\nlqhCQnHBIXfIpOwGGBlJaiUYYY6dOwPioUESWqRhhqhfIhnVuHk1ZWcrxDFdlJESG31qRwWzJz2G\nqse182uoVBtLbuIUXUos4RD2phh1CuxtRHT3eiy93eCdp1P8zAaNVshIZrh2voHpZZhbcIn1XXLF\nFkKMEGaCUg62k2c4TBHSoN3uQmhiuR71zQF6pHH6dAmvUicIriHsDlmtRZYSs4tTjDomL3/9Jp/5\nzWv8+L+q8en3fZSws87l6BvcfSXAdeZwnRKtcMDmcJMk6zN5Is/U9AReRjEzVyRfhuJ8gdJUGVdU\n2f1OilWvsaAtUbXmEI5B5MbkZzzKMx4TE1nyeopJSEgbNxOROTzigfsn8VcMrty+y/kLu0yJKSh7\naGaMzI5Y3+vT6qX0Ni2GfRM/8Oh1DQY9RTKw6TQko56GXdNwCi6jTEBLpmwPYHNjku6qy8p5yZf+\n9CLTMyVOva/Eocd87Kk6jhlgNnXSi4L4epE7X7S5G4UcMY7xzo/NkT0Zsu+9Qf6oRmR1iYOQRIQM\nW3XCqEllMsaeazCZCVjM69SER6l8jE4icPqnufynHb63u8a/1n6Ms9kSW+Em5zvLaOcdLjXuMptZ\n4KGfOUWjv4+VScGJcQqQm3DITrvkMiZOzqBcKWA6EzDMMhwk9LoJ7d6QejNgFEn6vka7FZLPFclP\nuFiWhdIVw35IrFKQFgwKNFZDIt/k0NwE1aUsWqaNyPaIHB9pWUCeaN9jd8PH740QZosTx02mqjss\n396iu6MzWZxhd2VIvTli5vAkS8eLpL06QWaNTCGkLAISt0u/tEE0MSCu+ARTPtq0QVzO4GVnWb+Y\n4/I3Ldzeu+mos4ScZRhVqGwdwvS3Ee8LaWUrWKpIkIQsL9t88b92/8FrxaFCAS9xGXag083R3rVp\nbtns3DHI2g+yeKxMJFdgVGZr12eYTBMZKZqKWB10cYsWga4Ik5RYKkzDJu9WOHX4AWpuhQk7T9od\n4ORc0ARuwWMYDyjVaphCY7o6j55R+EmX+46/i5W151h4JGDuHTo98TJClRl0TL731X1mpn6JqWwT\nqzTkiR+bZXvrFa4+eZz8zkdpXNbZuRUw/9gILz9EszXOP2NSmSlgVX28k01OTx6mNDlg4UibpFXi\n/DWbJNrk7pM1vv2ZEcdnP0hoFXjs53aYOdonCHRM3UMkHpZWQ2ld4tjAMEMqkz7d3oAv/MFNzp15\nP926huPauKbCpYOp2zR6bW5ek4j4Cd7zoxof/IWEcz/U4sw5k1MPzLB07y6i9CzlisP9p09yzz1T\nqMRle3/ElctFTp/4EKL0It3hHv3td1CzfwkVlGl37yK0IVamS3ZSQ+gTZNw8Q3+Lucl5nEyWTneX\nfuc2D95n8clPvJ8nHruHmxf2uXDpObK1Pucee4TdYRfTbTCRt3j+W8/iaYf409/ZYv/acVauhvT2\nbILGBH6/ysZV2N1oo/xJqvk8K+vf4G3vmmPpoQe4cP7zPPkHX+LKMzWWbwiOnzhCKLcoL3gEiaTe\nnIXGcQ7N3keYWlgFG5GcIY16bO28iqlLZmdPUanNM9BeItDqTE4KJmoa0gwQySLXX1/j2KGjDPqC\nTMlh8WQJK9MmXxGsLuvYYZlXvqxRv52llFvigfeucubRPlPzRS6+dgVb5Rn4TY7cWyKlTdivMOgp\nKjM+S4cKtBodTB3qjR7FYoWseZJvfP2bvP30L/PqtyQP3/MBnvmLgLOL7+LV87c5cvIcfdlCtyp4\nKOamU9JYIcwBa1sNbIr0OhOs72kUS0vcuizw9+aYnF5g4aik0b5FZ22JfsvByVa5dH6VKecBVm/s\n0ehsYWRh7kiRzHQbJlawPBg05nn55QG6XiKWFrpj4U0UWN25+n3rxA/YaGTRNIHQxvQoJdQBX+r/\nTcl4y0mJlFSNswg0IREqRaURYeiTRgFCS7B1fUxFObC11QyJqYsD9EFDaBKhYpRSpKlEJhFJGIAa\nh8IlqUSlEMYJYSoZjHxa3ZB2N2Y4Okgjl2O6lqYLUAKhQxKPhdy6Np5+a5qGVBKUQRikhIFPNuuR\ncT2UFoHwkUKipQ7hKCabNRgEfdCzwBz/9Q+/ye9+5v+m2Y7IZHIE0QDXsjgAYRDopOmBbevB4Vcp\neUCdGrsdpUpiaBrteMC8meFUbYGjx97FwAwoe0UcDDRLJ4wCdA2ESNCFjUpDsD3CtMP84hyLh86y\nvxdwffU6erjJpGuzr1wSw2RmwsMiROlZ/LTHKA4ZqZhQ1xgZJiKfo61gdxCzPUxYabVY6/bY6vS5\ntr2LPmiiRxHHZ2t86L1PUC3lyJg60/kyAz0iYzvEqWS2Z9O69wiPfeqnD+5ZHGyVt0h2b3lOCaGh\naeMUeV0bayJSOUIIE0MIbly8xfbNXWxZYH5+knaywVx1AjHSGYWSb174a1IJUo2ZgGkSo8SBJ5oQ\nY2qfGNtDvSU4H7sHoKR865co1FtbWSn1t85TBzQqhIZu6qRSkspx+J9k3DwmcmyjLJUY7yMEuq6R\nESahiHBjl2/73+Qx/Qiz0x+k27iC1zf5WnSJj7ufZEvbZNRrMzBmWU83CA0gjpCpQmoHTSoSJRMi\nmTKSKUmSEEcBSgTEskMv2SRuSu4u66ytztOP5jBMl5wdY7sRjdGQF577/kXh73u9WSfe+fgkc6ea\nDDM7DJRifSOkv+9w7NA8+U3jT6IAACAASURBVKJJp9dlZWWTdtLHrSUEYpeuscFevUkQCfLBFFHX\nJNix8LcsRj2XVsdlt2OwtjlChjqWo5PJuhxa0Jk8pIjSFneubKFjI1WGoBXjkMHEppA5RLdns3dH\nsLcekDET5k8MQVyn1dylJSW7dxRrdyT33jPD5LyHZTZxMx2GcovUSmjpQ/y2IGgZWLpNpTZJc7/F\nyht7iIFOueyQmxih5euYlTZHVAlwgBYhPTY3O+xc7vGpj1X4lV/7SWJRIPb/mvOvDdGSCvvrFnGg\n45WzxG6KtCO0fIQUCRE+SkRs7u6w0+izsjZk705M97rJnDhDZn2CXDLBzeUd4imTuCQZhT7txi7D\ncA+7EGAQkxFDJAHmRMJjjx3njLXI3VdHfPm11yhEefLTZfJ5xZFpF68IQezhtw3EoEZOzxCMFFEf\nBqHE0FxUYiCx6bQEe22DdqPK1rrJ/l2Xbz55h06rzyc+fR+nfyjPzIN9cuUedHukVy2GFy3q3/Y4\n32pxTJvhn/2Pn6CVuUPP26Snr4Ho4E6mFGey2MUQ3Q6Io31E2ccTDey4hTBGNPsRVjCDPTxM/7rG\n8jdCfmT4dk4kRXaj2+TI02SfdVZ5WpxnPi5x/IdnGOh72DUN3U5QrkLPCgadNt3+DhlrRLU2QTZb\nRc9U2bvRJfVTcl4ewzHpt1N6DZ9spsTS2Vkm5wvkMzr5go4KU5JUEbWhtSepb0XMTFVJrBGWnaA5\nTULZJwokUc8ibGXQBlm6LYnlwZn7y7znoTwT+CjdxGWCSeswrY0OcSeB+ogzxytMHXGwox52bpc4\nN6BnrSJEjzbbhEaAJiSGaZDPVsnOHEK1DrF2x6KiHmdHzHAeuEwDV+mMbg7J7FxFPnATrdjGMrJs\nNl3+4jO7/+C1Ih8s4u/nSQIfJX3CzhCnv4DNPNVpjWP3DEnSdXbWPAxtisQbotx5tnYDMjM6zV4b\nN+sRBmM690xlhpnMDJ7KULbzqOGIgpPHy5THw6dwhJBijGOHNhOVCUgKLM6d4uWXvow5e4mHfqHI\nsPQapkiI42nWX9AY7DxOt3kC1VQcPzPJxEKOdl2DwQLtWx0KZo5WssXkuSZWqcdIxQx3yiQbs8Qd\nl/t+WMNR+1j6DhT6zB7Kc/16TPvSY6w/c4a0meXudhNtcp93fuA21aLEM6fBUPiawpJFzHgO23+A\nkvMAw4aGiAvceiNk99YC12+8zKkT9+DldAK1M3ZTtPq43gRxKjj59mtMTd8kSEMsUSUS18iYeaZn\nS0wdukOt0iVXuE5pcovq9AmyZQfHOIYpzpDGOp3OgJ2tNhdefZ1oZDC7YGLakjhVjDpd2jsjDN1H\nxQELcyfY3wuoZScxMUjiLs+98ke8dOE/YxVX6Q00DKdMZfrMuJHyU7IT83zha/sERoGLL0fUsk8w\nigZMTx1F6x9m42qbUX8STzxOsy8wjD3uefgso60bvPjcXT71k7/Bt7+1SUbOMZXb45Mfm2Fv2KMf\n9nAyj7PWeYp/+i8jHvtxn8c/foah0njxxeeo5Q7T2q4Q+i6Rc43czCpR0qZQkGh2zKBrcetyn6Pz\nJ9lf26WUOUZ32KI8u4dldzHMDN2eQdle4pt/2SRjHmGinOX0E7eoHm3iTdSxzJj+2ju47/jPc2v3\nO4SyRzAKSeOY6qSDRhvLdtna1Ekjl6P3Bth2RNid4s//+HO4Zkx3u8vJ47NMVOHI0Udo3/ph6ttb\nFB3F5KE+ht1HSIPRIMQycmzc8Bm25shkD9Nptrn3yAk21r7DQ++zoHgew5YMtqeRUZbljU3mSw+z\nd6tHNqewaiGBGDK9CM3oNtIIiOWQtP7DbF8vYiiLYXfAyG+y2bjKIOh93zrxg4nBheBNf1sh3jyc\nJQccewOlDIQYf0qpMCydOFGQpoxCiY4kSQ0ypkKmGpY9zrLQjBRdP6DKqPFh00jAsQ1UFKFpNmEQ\noKSBJlKSWGHoCqQi9CMSpYhkQpRIglQQj0+GCCFI1dgxSKrx5FkdUK/Gh/8xLeYtREaNUZo4Seh0\nXG7d7BMGksOHHVIV48camrKZKpXYXunSCxNeeu1Zbt0ccvWNLQbxBMIURKlP3ssh4xiZKjRNjCk7\nb1KD1JhmxoEAXCmFTBXokMQpZtamRoE526a1v413ooI/8HE0Cwwx1g8IgabryCTAsU1GQUypmsP3\nFXrhJB/8yX/HaxcXePmpzzJaa1I7bKMbEc1mh7nZw1jtHrFXQqWCME6IE9CShLDjoxsmcSLotLtI\nKUmIScIQUp1qweTIkSM8dN99yCgkq5lY6NT7LSq2R3s4YDr0uFDQ+dmf/fm3QvmkUhzcNW8e7AWK\nOAhwPI9RqnA1jSRJMQwdQ8/w9Ne+zvLViwS9HaZreTKZW/iJzdLcDNW8ZGVZUpx3aQ/qmCJPdOC4\nnLy5iqahK0ki/9aOloOoPdQY5Rojcwe/R4JmaHDgJIUcN9RCjM0JNKGj5NgOV9MEUqkDIfv43tAY\nU660g2DLFFIjRUUaeSdARg/yQrjOD+suX+ws84tHH4Ooikif4ZRxiOeim8jCdWaHGlFrgobVP2hy\nNHRhoKRESoHQDHRdEEifGB9f+XRSD5EKWhZktA3s7i22nvFIni/h1iaYPl4lce0f5HX/e19+z6e5\nq6CVonmSwwWL6lmPtDciWA8pzEJLQb1Tp7NbQCvqGLkKBS+DH9kk2QwpOnFTIVMPEVnIoqKXGTEY\n6gwzEUaUUnMlhWM2mVmd1noDFWm890PvQNMnePE71+n1+nTbITdurrK7OSIdlNANh5nFOaZrQ5YW\nQakEbVRi/ZrJ/KECWc8lTBMKbhZDH1H1JhjYOvlyjY5j03U9kk0Pf2iS6ZSo14cMd0E2PIZbguI9\nFQassOm3KcawN3SZyDzM9OlrHD+XZW5qnp2NCzhal+v7gvaKQX8/IN4LsVSI0jtYrobmmQTdiFGQ\nkgKjoaI3tMnNVPF7IbLpMjFzmKnkEBde7HH72j61R2fJyAKb+9eJhcS2JHNajuF6TH9qSDv0yWc1\nFvJ5RtMJJ3/xKL969CP89n9n8vTnriJkleEdxf5DBrHVx0FnKudi5UKGPROhJ9ieRS9UqFHC6msx\no/0sQWKSyCJharJ3p8uVi+vkch6/+Jsf4OwHHCyrh9R3CPdS5L5F+6LO1WcG3NjYZjY7z2889VPw\nsMXW19bZunyBYs1EWvukXUk9bSMXfeZmXWbyNfJYlMngkCCEYuW1lN0bG1z5+jJ3Xwl49MEP8N4f\nd5nY2qJ5JaVf7/JIOsnVnRYfMY8R5XoM/XUKFYGouPR9h8QyGI5C8uU8M3mLPAPMMKSx36J5ewDK\nJzuRwSvqICy0oWQQhJBCPPKJNB1/1CMOYG4+Q2+o2Fr2iX2NSn4KYbgMmgNW7RbmsMfMYQPdzhBF\nGZKBw3Cko5sO01Nl7MyQW/s3GIV7iKFDxi/w6sVvkfYFxyfm8DsRFz9/i48tnSY04PqNLtaUT+iO\ncHMKLdHQwpSB3yW2ptFcHdGzKJ8ucGbvMKVtk/7egFkxTYyNUgY9YXD51SKDX2lT+vQdrAdNXvha\n+o9SK9bqBukgT+NmhWTUI1PsM7Mwz+TxEbmpW2SXUg5FMcsXe7TuzGNkY65sraKcFdSojNAcBj2B\nUHkczaXoTGGOLBzDo5ApICONQ/NHmFo4xdPP/RWGblDMlImjkIpVYrR7g5LzMN3VZ9GSNWYWLWTx\nFogpdFqoxKQX3Gbryins9ALlQ8dp718hjQ5z6okaN70WkdgkUSln3lklKPSppyPCbJnA3mXU3eWx\nn5vDds2D9KUBgRKIwjpT3gK3r5+iG1zmyvoGh46fo9NYpb/uIPLTpJmEoBCRtY4jRY+Nzdvs3LnI\nxqUFHjr1yzzz/OeoVMu84xGX1XbC7dWrHPfmsAvTDNkjCg1ymTlydoHN2xHnjp7DVDkyQgeVoLGE\nKRroxg4mZUKpgZbFMEOOHG2j+AKhGhHVY6LWOerrNq21eeYOOTQ3L2LnI+QgoZid5u7WAH+oceiY\nQ8e8zOSCT9o3yRzZ5jsbnyZrLXDqEz6XXt2mtdpkv7+E7R1BT1L2GreoOPeTW9A5vHiUL734b5mv\nZMjMnWHkFtGVRzjKMlr/Aj/zz99NL1U8/2KPz/3Wt7G7i1T6P462ey/tjS9yrOpRrXR48F+8jezy\nt/jD//QVNi/mKCcf4Omvv8BPHNXJHLrMJ37xES6/VmbluwKSHTpBl/R2lXuXPkwnuYJjVxk26yRd\nl8NLOnrmJqbhc+dOkWrtKHGvR99RjPwYzVAMkg2OPWjx2rduMrFgEiQlhlGLXGWbybPbrN1OQP8h\nnvmLBT79b3+Or3/1f+dtj/fx+xqOUaQbtXHzJpZWQKmA7OwFJo/lKFdqGOECxUMXeOJTd/EmTmMX\nXqZfv4AubJKMT6Y4Sa87wnJiug1FzrOYms3QXE9otm6z39rllfZr/PynHeLs87ieRzzscN/ju7zx\nN4Jjx4+w/fo+S/MRS+cEtYemacsu9fYGtuOCBo1uzLOvPU3sP0w15zFbnGB1exldT9nl+ztH/GCB\nfUq9NYVWajzRBRDIA0K7HGsphEIInSQZNwNpkpDGGiO08aFOCSxf0R1pGLbCMKPxJFszMC0TKTXi\nVIAyxwJxwwUZk2gKUkkcxiRCkaYHeg0/IEwi4lSRJAqhLNBCpMZYA/Gmu5CU4wOv1BCaesv2Vikx\nPkhqOkL5GBooZdPYHxD4Poks44eCyYkA1D7Dfpcjhx/gymvLfPYPn2cUjTUe+WweRYJteERBgFAW\n+kFo9LjHeBP5UW81N29O2TV9jAJZlkWz3SSamGSn1+CQGRN2fWzPISTGTA0MyyRNIwzDIJYKTdOx\nDEGv00YTAtPzEKnNfQ//KJXJe3n1m1/g9uWvcmjaZXFugV6vTcGEyMmDTFGeIg4iTMMmiULSFLp9\nn0Jm/Lz6nQjTM5iZnebUyZNMVadIZYKwMpiaQ5qmLBSnWNnZYMGsctOI+dn/4X9BCQ1T/W1r8Xdx\nLyEESkps10UphavB0A/IuA7LN1/n83/2f5Bzckxkc0ydeYB+L6AzAtsNCIc7qKmYxXvu48vf+DJ9\nf0jZKiENUGmKFKAfLKjUePH0QLgttLdwFMYmthragd4IY+wqNt4XgD42EJAHX5TKBCESYhQ6GrrQ\nQFMHwnBQ6VjBoVKJlApT0yEVxDKiRcogvstx9xRP79zh03Of5EvrT3KycpKn1vf41LmPsCaabIyu\ncjErORK1kUphCAuZCkw9RdcEmm6hHyCJ4oDmpSkTiEmFhUhXacZZlG5hlPrknS5Ra5fV7+oM9NYP\n8rr/va9koNFcS8CDUdBgYW6KiYxicjpDvywYDHMcDwvcWPHoRW30bpV4O6ajOQxbOu0bOsONEiry\nKKsa+bxN5A1o9C5gZWJy0y7ziy5YEcurXYbDBAINv6/YWumSK3hMlKcp1A6Rxj7b+5sIkSJHNr02\ndFsx9VWH2zMTRHLI2lpKuxXjlaZZ32pQ7WlEC0AkMQsauhCEcYPduo8/iIhlkeFAkFvwuHfxCPWV\nXV745nWMS7s8kXU5/v4sqjtg1oUpJ0OjcIMv/N4G6tY0XljmjeWQZMYiiTJYThEvk2Xg5Bg0Jaat\niA8oo6NBTKIPsPOC0sIkqptSdEsMhz2UKtB6w2L/uiQRVW7Q40ONhzGVjRUFRJagvxGzvdencsYh\nSiS6HhMTozshGbtOLuORv1fw+K8/xP7v1Nm8baCPMszPTtEPe6gooSomyWd1GtEQZ1LHchMiy2aj\n4aNiwfKFFqGf0GoFJIlFKVPg0TPHePsjixy7P4dMdhHhCGNXodVTmq8qdjeH7BNhnjB44L8cpvvY\nXV7vXMY94TJZssmmMYUjZfS0x13LpjyTp6TbTMYlWkbA1VsStWfx3B9vsHfRx28UyGey/MhHT/Dw\nYzls/RLeOzIM77fYfbnHnTs69UGDj/+z97NdaTNw1mgFDZz9mCEhqa+zE/aZOiwQaYeEPobu4A8U\naWwyd6JGxrJRcYSdUximSdfPs7/V4PULDSpVB9NNmCxlqU2X0OsJq7d6hKlPtjCJaZhMz88jcn0G\nSZf9nZRRr4WjmyRJTJha5LMFApmy04hJSwWmlgxmqDA0bLJui3d+9ATdKyZ3XgpZ/26b60frVD5S\nRRv1qe9tIoSiXwmwRgZq4JPpZen2+1hWDqvi00vX0T+oM1uaZeZlm+CSz7Cpk9cDeuUO0WxAf9bm\n5t8ktK/F7C//o5QKnMTHly7tpkEu6xE2TVTfIRYt9BkDe77PxqDD1JSO02ry0u1rjNKIbCFHvyup\nFmfRZI5Spjr+PyhzIAVC9zALVc6cOscwtFnZW8PKR9Trywi9ws7adQ6d+yd0uy4nC+9kv/MM9sl1\nvIUnaN6IsRYU2VqNsjeHXvxdvNM7RDffxr55iHPv0dGOrRFPXub0JxaxFs6j6w061Ei0DnrDRSQh\noqMIBit47iEiqehqEYKQRLigNOo399laeYMbu/v0cjr2YgvLd/js7zT5hU+9j53B03zwFxYxjRZN\ncZXCTIG5+RmKps2XP/tdRsMan/zREfe8/fPMssPd1RWu3L6CWS5yZGkGmba5emGdjRsa1co5rlx0\nMdICtakJvGqCbecZBYKc/U4QO1hinkTr0WMLS9YwOcwgeYFsscmJUw9RyJZZOnmLdvQsw7bFcO8s\n6+tdaiWNdnuLdzxympFxFbcCZb3G6xf7+CtrGIZOzr5LpwML77JIc3WuXP4id26vcu74E7zn3R/h\nnnct8uraCk/9xZ9hdbJYcQ2lleg6VZaOnabevIm9+yDf+L9K+KHB8soHCDsRpfkSZk6y/8cvcmLp\ng+x3L5K1ykTNZ4mrv8+P/tI9/Msf/0t+4if/V/7w936fY8c+yTlthT3/NjOFxwjmddZ2zrO2rrGw\nWGTzepf/83ev8e5PneFwtcru7Zjy7DYzZwR7LcWhaszq63XEK7Oc+7BBq7NCPJK4mR6hLagePsTJ\n02Wc8vNka4JRohCuxROf8tCGX0Y8c41n/+r99FofIb3vOmm/ycZwjen5ElvrHY4edtHSECkSzjxw\nnFuv7bPywnXuz1mQuUju9BtEhsXMmTLt7j66OMZ+q8uw46DbLaaKR5mq5qjMbDO3JPjiH21z96qD\nUlVa8TYWdVY2oVzIo+I6c0tZbl2/TaZwApm/xdKDATf6t7nvkRzPfxkmMjU8Z4Yrz5WZKDzGpZ2/\nZn42g5kkWKaPme79N73nP5jrFAdZB0q9pdsVB8jBmHWSHAhlxzx7xbgZ0Rk7P0WMhde6BsMQjFGC\nbevYdkTWc9DQcd0shtCxTEiVQNMEQTzWWUglcS0HxxYkEoaBz3A4IpY6cRwTRZDEOlHMgQWphm4Y\npFIiSRGJGguwkQfIizxoNMbhfVKO4eYkiUjiEbqRZdhPWb3TYNRPUIsgQwizNp//rc+xuRXiOJMY\nzhBNSOI0QAeigyZMoKNkfCCUP1iLN9dLEZqGkmNulZQCKVMwTUqWx+ypM3zmS39F+dSPcDz7ILGd\nkil6RKMIoY9dkHRdR+o6QRCMtQbKwfEMorhPEIfoosT84oNM/Ow8t87ex6tPfpbma68xXZskrC2i\nLBDCRGgK00pxrLH9q4ZONqsRhDppBIfnJ5mZrjFZzSH1CQbDAaVSFUNoxMFY77K6vMnR+aPcCkN+\n6t//T0g/QXPMgz0ypk2J/88+EppGEofoho0Qiowp+Oxv/2/0+10WJ46hVIqIUlrtBiExhekig26H\nUm4KZQjcSsLcySl6XxmwdDTHbruL0jXSOEEZ4q3nKw+crTQxdiRTCqQcN5oyTRnn9qUI5IGQfGzj\nPJ7pybHbl3ZAiVKgaQKNMXVQU2KMkSXjLI7xs30TO5MoKTANEzkS5ApF9gfbmGGJ13IXmHMX6Y6a\nvOfoe7jReYkzPQO38nZubr+GrfVp2zYOAk03iWWC0nRSGSEUmGLssmYInTBJCaSBrQk2dY+JjMJN\nAtKOomekBNYmdsZEBv84iIZKoVIok6na9IZ9htshbeq4ixW6gSTsJgjb5MyxIi9f73DrlRb5GY/8\nhKKzIvC3LXY3JNQtko4k6A/wjg24/8ES1tGEkT5ERQm2rtFqD+nvRXimgyYn2LwzIEnWyOQKRGqE\n6UKpNkFt1iFu6txsbdFYHrFZyZPWctT7Axr7MWlUwLEUnc6ANHKYKBbJVBeI+rv4/SZRNGSqOMFA\nmYwyAt2R2KZBmkhENscoU8MPIsIVEy/OIuc3CIRkyBzfqm/TbiwSbmd5Y8tiIjdJtJKi8gFG3sFv\nKUaBhaGb+ImFP+yiBxq5+SxW2UBz22gqRQ4CukEdNYBut8/WtmDQifj3H/l3/Jcn/5JhmGX7giRa\nytH2Iyw82sLHc/KIaYfJ40tYuSHDsMloELHR22IQa3C0wI/8q/fy4p+f5wtP3uW5b+zxG//9p3Cz\nJvEA7G5IiQbTUzGy0EIUFF7NIvULrN1VxKFFeztESKjMTJKxM7hJSrLRZMIDO8xgrEr6mwGDWyGR\nJph+u87bPj7LxLvhLtdYTzdIohS3pgjDAcVJk1ziMSknaA66GHUHw/BoX6rSfmOea8/ss/pGyOLM\nEkbN58yHl5iYHGFO7pBmG1gnqmQmXdyMYpQP4NSQ1rtf4ey5EneXt7n7rTfYJ4e0M1jFPJbnIGRK\npxMjcopg2KLeUSRGCTerMHQfoQV4mRQrL1FpyigUrC/3UWlAddbDLaT0ZB9lSOZOlihWi3R3NUIZ\nEYcwOe3geEtY3g5BLkPQj2i3UrrNAabtQQKJraGXbNAjtrubpBv71M5O8f4HTtB4I8fzToOn/+RV\n7rzewTtRhlwR1Y0xioqCPaYZx8OEgZTYaBRLksRvMdD+H97eNEi28z7v+73v2U/v20zPfufuGy4u\nLi72hRAJi6REUVsiSrYpWZJjpxRbscuVKBVXKVWJS0mlIpcjxVYpcml1iZYoStzETSRAgMQOXAB3\nx91mn56l9+3s582HHkD5SMolnQ/zaarrdPd7Tr//8zzP7xliT9lYj7iE8ynNwzGHy4+TBgbJ7gBt\nxmDxwhKP3JfBixv85ZfHwM7f+r0iZ+fwZUgrURBmCMRkH1HZWeTeVwL8hk92IaWx5bG7/R5OzeGw\nX2e736IyM4+dFMjKDPlUB6WTc/Jk6tMcOXsfiQJPN1HZIumgT2NjhQsP/RBv3XqFBx58lldef52f\n//GfZRj+AfVnL/PkL1S5fustGjuK/ssX6Rx+iuqS4mjpDK9pG4xDwZH7/4xjT59BlJq0ui3ypXWc\nBzbobGmsv7tC902Jt+ejqxo7OzmM8gle+5bH8biHdqREqLvEDLGDGoNBQqp6OPYhyvdd59xPrPDh\nJxfZXDvC2isd1m9N8/XfjsksrvLoT3o4VoxKFjn7TIlh0ODOm4LZ4iHgdSzlcvxQwJqV0gv2aPey\nOO6Qzn5Ib+siK2+mXHnjG8xOzZCt1zhz3zGOVo/w2rU/5WMfPYKdPYyv2WjaPirVMGWZcTjAMTv0\nrYC11W387iFq8+fIuU30U226w0vYhSW2rtW5cOrnWD68h1H2uLfTJHH3qJQsNm93CPE5+6CJa4Y0\nmiFGRic/v41oZbi7mVDKd9Czc4TDPjt33kIVOrxx9Us8Vf9p8vUqd/aeI5Iheyoi3Ozj6hXa4xvE\napP2bYOnLj6OEIvolQor+5fJxCcwVJ0F5xl2CzOUy3f5+rc+y/T0w3z5K5d59Z0+Tz17ip/4kUf4\n82CHkrvIlXd2CY2QsFPmt//PJocKF1m/co/p2S7l2jzZ7ACt1iPxr2BtOcwWf4nnP/sZ5pYexMkp\nRG2H4cij365OiGlRAT32CAcRs4sWwfAGg+09pgtl9leucmjpR1l9+Vmma5/hRmcNU3PoNwa0rAHJ\n9BClK0T2CrnZCJxlBvERdvsNnF5EKDaw3RZxqFDxFuPOgKWFKqbt0d0dEwrwkl3GSqEVbXZ9m4Xs\neb79/D1OdkqEkUH9aIcHHzzNrcEQZZtEms3GdszdOzGZxTzX3xyj/Apf/twej9z/CzRu67x1/W0K\nVYEWRQRJxH4w+J7bdr7PQUN9oGooDmwjiglSlkn/AEJBmk7cQZGGJuWkMC2OJrmKUBBIgZQxVmDj\nJQmhmvjcFRqeP8DSTGzLQckIO5NFGAJTcxj3B3hBwHjkTdCjCjRTIx5LojjBjxLGvk4QasRKIKRE\noNAOBp9EgFARUtNIoklHglLvvy9x0BatI4QBhGjSJ44TWq2YMIohjOFonS998XX29ro4rkscpZjW\npMPc0m3SNMELxmiaQNNiRDKpc0Mw+XzSlCgK0XQBB03qSZKAgjgOkELgdz2maovML9fZ73c4JnXG\nrR4y8TCsHGkQY9s2gZeiayZxECCsAE1lCDxJHJtYlkmSxAhSTCvDA098kkNHTvLSl36Pq69+lSNK\nY7ZeRzM1TMsl0LLolkEY+Kg4QqiEcrFAIT9DIT+NJgSJGGDrFlPzJbqdHo6VRTd0hJ+wuHyI1ZbH\nJ/63/xE/0sk4GqEfoFkCDfODQsX37WNpmqJpGppuce/GZbZuX+PPPvPHPPLYI7ilAp32JsVyGena\nlCpVthpbdBq7ZCyTVq+DUZ5Dt/Zx8jqak6fXaiM0A00JEn1CMosP1ihCgYpJhUAlk5FHpRMdQx1k\nRlKRonGQIyGe8NPUJJw+yQcdSCSamggdCDShI5VAIhFSJ1YpSqRITUNKiVAphmEQJ4qsZRMPLfTc\nPnt06XX7HDGO8VD5Av/+2h/yby7+G/5i+ss8MJrlujammc5DMiRQAkOmSKURpBFJmkwACWikJKQT\nGgMCgS8NskoyHriMDI0kO8ARY8TYIRpDN9z6/i73v+HhFlzqyyYyqyg7OVav6fQ3UxprHZqbPirU\nyBQy1GpVqk4VNerjb8dEnQS/a+BoVbKujW9k6Ccu01IwNS059xEd5/gOG9saNy7voWSRvFsgiXx6\nnQjlhxgii4x0zDQhWNHPOwAAIABJREFUbuv0wxEyk1Bb1EgjQbVaobkB97ZAbs/QjkycfEq5UGKw\nH5HJZ3CzDlo2h2lBEI0gGJHqCd3OHv5wCHoVrWxjGGAkBgmCueUKe1shb331Mnf3Yp75uVm691vc\nbRfYfFOje8+lGE+hG8cYt1MCRxAGfYYbPfSMjmvYpIaN6CfYdh4I6W82CXY30Qu7DP0RXqCwNJep\nxQUKpSlEpcKfr1/DzgWcOjHF5fdu8aG792PZsxTEiKLrEcsd9J7Ecz32NxTjzQGVSglDxHTClIiA\nMJfgHC7z+C9+Evt3j/Odyy/ws7/6bT418/f42LnT5Mqgl+9gRvukVhdRbFNxI9ptxfReDk/qOEUd\nR3coZ0uoWEM2A4ppmfwgJm2Oab8WsNnp0RBjomMxJ35mnos/scx1dYdA+LjVMelIEGtd4lzAG50+\nJbPKvH2cijzMwNP5dz/3XdbfThFMMcUU55Z/gFPnq7hlD+nuYmbajM01onQT1cyxP7Tp6VO0i2PS\nmuS2O+LC0nlyakAxA0aaMkyAJKGQy5DNKqanBfV5RavdQ5h5BoZD6EWEo5BsNkW4CUrGDLsNylNV\nhFbA6yTkCyZDP0SFA/rtlKFfmNBoAgtTFMgIm71Gm3w5pDZd4PjxGp3ugPZOwv7Qot+K6Q8D/E7C\nYNPGtRTG0KA6q3N6cZp3Nq7Tu5th+eQFZk4tsf1GF5ntMPXUPJGpGOx32bN6VLNZEjS8bR+7KDCc\nAE10cOspM9MCMbdBaIaMBmO82SmarYhoLmL5XETpsMSyxiwOp1k9F/J3MWiUMlmCaIhZCRj5PqMo\npJzLsdc3KAXH6bzWZvW5WyTBFH6cod3uIaXNhfufJe1GpGGfnOtjyIQ0mWG+Okt1uo5INDrNNmHk\ncfx0gev796g5h0mCiLyTZWvvLvUjfb51+be477EWD368ilmExYe+RNBV3BMNLPshrr9yCF17kEJQ\npHpkg4UpwcaVbTpeRLZ8Duu+XdqjLqOWxEoD0o5NtTSFU6zjTE2x+q7N3asGbiXLiaM5pDnLxu4t\n/BWNvTWdgadRKxV46kNnuPDEnzO9eIv6guLCA3Ve/LrO2y/oLCSPYUZvMor6ZC1JpDpkFwNKoyLZ\nRZdhNEVen2Y/usfMzIB8kmd3s4k3jBiNJZXiQ9x3cZMHP3yGStlhv7PKuGlw6bUM7db9tLaP4y5e\noZDXSIOz3H5LkCtIZpaHhEZMrwtWvo8RmWytx5RPdNGMECcnOPpwH83tEHfKpOIiMpPDzj5PGA0o\nzffYuDtm1q2j743QcjZ5x0avCWYqMW+/0mT/tkexA6NbV7DHBYbDfZqyRcQee9uvUlNt3GKNptGB\nhVkG7jRG8T729++w17nLtG7y+b/s8uxH7ie0mziVKm/dCAl/5S7LT81QXuhjSQ9pTZMtXWS7cYnG\nzhucffg9SvXnqU31SDYv8MTDH+G1zVfITwVc/m6TMD2Dra/y1A9n2VhNCSIdzRAUCwnvRX1efuGb\n9JqHePLsP+Lbb/wRx89nGG71WJhaprW+zp1cRKQU5cUyaTCivRlx55U2nVWTSqFDtvoCflTg8nOn\n6WvbXPO22dwyyNl5iqUsK3d3yWUUtguZjODOlTHZ8hl63R0KM3scrs8z9LtIpejthkTzfZIkojwr\neOu7a9SL83R3bWrpAxytJChV5tqbZzm98AwvffPrPPGDEd/dtdncNsjmHqLZDiBZJPASbr+5jV3M\nsrXZpjL3Cb7x9Tbv3bnCkeWErc0+Zy8+zerWbQw1Zjj+3vC23/egIcRf26fEB2VmEim1gwD45P8k\nAiUniYg0nZCXhJo0c2uRQJcmYRITJ3LS/jx5RRzHwdBMbDczKYmLJxtfZTqkQqJpYNjWJPwbhwy9\nMUpZJKkgSgzCeJLzkEhSJUlU/EEkgmRiM1JxCkI7UBPefx8KVEocTCxcUsYkaUKchEih0+8NWR0l\nvP32t6iUp9EshyAeY9sOKplkMELfw7YslFLohkUYhpi6SRLHk4ksTUAX2K6BF3gYk/kH13YxTI0o\ntokigbQ17tzZ4PbKDrW3nudDT/4w/fEA21HEGOSyDlKmJCoCCVZWEoQCL/bQNQupm8RJjGlIhBK4\nVoYoTtCLJ3jiU/8zc0dPcv07f8q1117lzNnTJMkAp2CjySpSKxGOB9SrFdI0IWvm8DsehVKBOMoT\nhm12+j2WZo8R0MOJ87T9uyjtOD/6a784aQXRIFQpwhBoKv1AykgSRaISLENH0zR297b55uc/y9V3\n38GR8OyzH6bT7hGkIzK5RZIUZOLQ6YyxjSymLhBpRD5vkMtkkOjUZuaQqYeVcwlHAdIwUH5AItLJ\nZ35APlNJfDBYTux2Sk1yI6auT9QkNRkWxUE4/33VC0C+r1TIiT1KGtqkGPBg/Qs1UfUOeFlIoRPF\nEVKT+FGK0GNUoEF5l26zzEyuxUDdT9DZ4V39Nv/94j/g/773f/BD5ofYswacKn2UN4ZfJBuUEVaC\nTB3SZHJelu0wDnwwDghmyQH5TUqkiAiVgynbmKGOntj4UiO1PaRpEQ3LMFj5/i75v8ERmz5eMiAZ\n7VDKlJg+MkOrr7O+6jHcV+TtHHkxxd5mRGvVI79QpCg0cGw6IQybKaN2xN5KBzOOCTwTpx6Rr3VJ\n3VVqReiXoLndZ+hJTKlhGzqSGKkFiNik19knViZ+HCOHEcnYRyZZCqrGodk8zUHA1W9GoGlU7suS\nygR/FGJaNqZwGTV1gvaYoR9iuxpHz8wSThtsbIZoqSSMTfwgIAhDshmNciZPDY0VRyF8DxqH0cwS\nX/zDt7h7VSPTsjl25hj0UxpjHzkKSIwEeWANTdME4ccUcjm0cYxpprTCAeWpgA/9V0dI3V3C3jXe\n3N+m1d5mPJgld/FJti59l29c+QMyuRxN3uPSd2KOpovEdhGVy7C9tkN80aG7k5I7rrPb0dkpx5ix\notUao6VtMrqDCgRRz+exf/g497/wBJdeXOHLO5tc29nif3rwB5m5uEDQeBVtqgvuBouHber7Bis7\nCe3QZ3qugteNiQZDtCBH3LNp3zXorsZUjDqb7w24LFJ6tRGP//IRnn72KLkk5rq2z2iYkI5iIg2c\nqoFLjsPpCa42xjy3M0Z/x2XvGwlO8yGeqi4zGjocXygy97CPZrTRCn2sYoRTBmYDVBjSTZpEcYmR\n9LHzGpFu0sptkVX3Ieo72E6ALBRxRjkiO08QCDo7bcw4JB74dHdCQgRxIBlueWQtndmjZRLRpdcb\n4uoG5VmLynSB1XfaRAOLYRhiZU0Mx6OAhxZKQi+mtd8nUA5ONiap6sTDiPZGE6NgUDnsog9NDFun\nMLaJxorubpvb+33sTMz8YzX2/AbdocabN0ecry4wfajMxu0229/Y46Pz5wiNLL4b4Q8iVMnAHwWY\nZYt6pYRjM/kdkil6f0Dj9YAhPoZR5tKt12jtGMwsOcwVDAbGNhnh4/ghelf7W79PADjmLqVogY4G\nQazQnDFNf50dL6FiOsSrPRwji58x2AlHZIrzzFbmcNMqcdzCcKbRZMLc0hyjgYZdLtNXDiIJmZ2R\nNDdusHPzVZSXkkYbbG6PqE4vY9nrHD8TkIg3OPW0w9SpIWMuk6FEtjRg6hO3SMUt0to0777gobt/\nn/KsQTv0ENYacf4aMp2js9YgycxwbOE45dMruJ+YJxU3aYTXUeYWX/8TWPmL85w+Ooduvc1IjqhW\nDX7nf98laj5ArAdUagn5fJ/VKwGlwjFmixt42Zd4+Mc0hsNHWXupzHtvCU5eWEBLltC0Gp72HY49\nbhPZHbR0inEyQDf6+ACyR2TGDLafYW99iPIu8fEffoPC9A56fIx6fgvn0BZHjgZ87T/1efWlOxSu\n3o9R2CJpFrj33sM8/iO7lJ19tvx5pip9bGudfePrVPOnKdQFQnPIWD6jQZf5EwIVvYkWVGluHcb0\nBnitV5B2Hz1nEQwu8F7jPUpT2wyGMQsnUoxMgJu18PVDfPm5d4j8HZ6YexxUGU8fM4x8Xr58ift9\nHacUMz9/AjWGwuwMC4fPcumaojlOGCUD0PtEtXuMw2M45gl2wm8StGeILv00d959gTPTA3RH550b\nN1g+lmF37UE+99tf4Hh5i/2VEbVaxJ3dVzj30BOs33yHTKFJPX0Wu/hNtExMdrZPlB1Sr7jces0j\n6SyR+D0yepXP/O6/pbSgyHf/JUX/ZTTzCmeOXODdlQ1KdY/E2KZUUmxct7nz8jFKwuboIYvTZx1u\nbV/m3uUFnNynaXg73L77AkI2sQs5uu0endaA6tQyvn6L4biN6H+K9b96i+Vn79EdGuwNXayCQxo3\nME1JJKHZ3qK9o/PCb+TIm9Pst8Amx/r4TUrVhwnbOtPWHK/82T0++Yvn+f0//AP+3a/9Kr/13K/z\nwLlHeP3bW5iFx0jjWUZDl5t314i9a2RlF39HY3npJJfufBvTMvEDgTK/t66d7y+jkSYgJ30DcZIg\n3o9TC4EUEqnrxHE62fRMGs8mpCgl0DUdSABJqsREkRAKTQoMy8KQOqYhiSOBaRgoTGzbwhAJpm1P\nqEEqJY0VMknxo/CA3iQJgz5+KBiHGqMwYhhEeOOEKIpRmjjo+lCkycTXnsYpQtNI1KR1/P38Bio5\nKGpTxLGYkKqEQJPaRJXBolgyGPstNE1DYBMFCqGB0CSGBokKsS2HKIgxdIMgCCblgYBpOXh+h9Fw\nSL5gk7Fc/ACGgyF74xAhBLppYIiEfMnlX/+r/4GN9TtosWIUCPxWm2pJEms6hnDQZZYkjhGajlR9\nXFdjHI5I4whL0/DHEZrSCLSQ1PBZXKrR3VMUHvn71OY+wpXXfo/nv/pHPDBT5ch9j5G4OtVSkcjK\nUJ0qMR4PkFKRtQE1RFguVT3LWGXBEqimw358D23hGZ7+p58mUQpNTHpQdFKkZk7UAKWI4hDHsNCU\n4NaVd3jx+W+xuXKDDBHHlxYRQuP2yib1mRqGcJAqJAxDDCsmk83T3O+QKp18Pk+32SENPXxlkcuW\nqFcd2v0hQlOksSJRIemkavxg3aYHPRoH4fsJS+qvs+FqUhT4/rqdkKg0UBoKNclEiIlCBhoqnrSI\nT6xT7w+pYOgGRiIwhUkqTUwhEHaKHgv23ZhM9xha/jbmcBol3majUqAYRhwyCyRujrYzpKhcskaG\nTu8sQ7dLo7dHKSPImxlUBMOhh26bRHGAlBpRkiKURBOQSoGZjkk0k6GMEdpokuGIbFQQQDz4fi73\nv/Exv+QwvSjRsxl6ITS2d9neyGF1p8i5FfJ2CcPLs7O9hx6ZlJwKuq4Ym4KkopP4gsoRGzMxGaz4\nRFM+ab7HZm8TJ7uPEZocWrS5d9MjHBVwXEl1SrFwuIxl6Wyv+UTbCY6IqbpZHL3EbrNDNLDYC8fE\noxJmt0DYHODMVRmvdSEXkCnlcKRJ0A7ZbLRJwhFOVTA9M4Xfj+j1+1jCIIh9fK8/Qd0qh4yTJWOW\ncY0ivSCisd3j6/92l1huIGSFZ+dOoFdtZAqtUYe5QwVChti5GBwHlUQEw4hh5LO11mPj0ns88bFD\n5GcjPvRj05x/eB5wAZPHWGc/2eePv9uC0k1+9u55pg7vczJ3mO7A5+X33ka+BmkH5JEF3OoyaTOg\nWMwj90OOlR7EtCdlhEbeJ2NlSEKDTuCRK5lIr42zmOXkA6fQXj3M89Ft/sObl3l2LY9zv+BEZpHp\nIwNKWsQgB8IcMTfnku73ce0M+DbBsES4YzHYzZCPLG4Hba5rkH1qmgv/8iQPPp2nxw77WotRFDFY\nT0kDiZvVuF8u0/T6rLUihtsO3ecN3v7tXbZaCSfFaeZOuMwtujj1AUGug2c2cDM+qt9iN7lH0epR\nPhSScfKI2OTujQ7tjkFsWjS37zFq7+F11tnwR0xlHAqlw3jCQdcdeuMBjbt7tIwWIo7QLIdhU7G/\nHjM2TAqWiXQ9NMejvlwiSUKsRCFCQafdwymZ2DmN+qxNNZ8haGuMlyzefatHf9SlupjHckeMozFp\n2sPzQ5SRIY7rWGYJY6yRydjkrArSMXEzY7xgRBD2KS6VeeKjD9B928fvKiq1KfLuEQrMs7W3S1DQ\n8bGI+iBllrKZgxiS4ZCsnjJV0ci4Lt2ez24rwkg0BttDvF2dxE6YsatU7Rw1M6Ltb7DtfW9PKv9L\nD1evMJVfwlJjErlDYx8iZZNm2qxFQ5xcGTXSiVWAmsqSN8oMvBFnFuoMbZs4sYilQUSOwyerNLse\n5XqFaL/NkcoU4xuSUr7E9ugqhlPhiWd+irXuF/n0L3ewl99Ed3N0oy02uE0ZGzc9iikBRuxzj8Xz\nPi+93cKIt2mtKT766XvMndkF+gjRJqDDljeiaIegGvS8K4QywrZs2mqDmUMurwZfpLX705T8CCc7\nZBAllKsWl3Z7RKZNvb5OYNxkrljC829jKotY5HCkx/ID61x5vssLf3GcjHmEUhW2thrMHTfQS1dI\nhYk/WqDsFonjLKbWYoiNmYu5/N6IsP0Ajz8DOStPWfRRhk6UFJEyz97wGsnhmAdOHaI6t8K7770K\nxhGMtTy9XQ0hQhJ9FcMAzZ8i1K+QLzxMnn+El34F3S8SNrdxc4pesk9//A2a45Sot0TZvEDPepnq\nkslge4ulkwmFgoHXs4nGHq1GRDLMInM+dX2e1K+y1e8xjgIS5ePaBmujPTor36G+M8eh9iZnajP8\nwA/P46u3Cbx30aXOPh69oMOffuf3eeTsT5Izl0l1h7sNhTfaYH+4wcLxU/zQM/8E2fsSd/svomfq\nxL0f5M/+U5dyPodTi3n03KPcHmawTI2phSqbm1fZb3yczPpfUpwJAUFnQ7B1SyHRyOVcVGbA3Gyf\n0xcFw91fZ3n+WfzB01SmxyxWWhjFMZ2ewutmuPqKgZNeRBr3mDm+w+xpn7azyqnHYl57aYt3vpWh\nmH+Ie6/c5HD5IXbaa/S9y1jxMQpGhsD0udN4h8Vza0ydc3nr9ntMl6bZvN7DsGB/y0Q3HKQY4bd1\njj35o1x6MUu1HDG+/RJPVx+nVMixttKkIqdxqwk3X0r4hx/+x3z5j/4ztaxNRri8+e2YJ5/4ON98\n8ascPX6ezZsebrFJwcwzXz9HJxkijJO0+w0M2UOF8nu6zr8/RUPoCKkzeWprHGQz3t+8TTbsmpQI\noYGSJGk8URCUQKkEw9CRYoKz1XQdXdPQNO3A756gUOhSQ5cSKRWaJiYUIBRCKXRNTJ7MC9AkJEJD\nlwLTyqAH4ST0q7QJchQQIkUyQY9qQsPQDyw8KQfB3kleZIIinZwnB2kCwzDwPA/DtLBMhzCMgJQo\nitF1nYl57IBWhZygUpl4+eMk+QDxa0qdVIAXBCQyIvRH/Mq/+O9YmpmmlC9jOwWSNKE/GvL2O+9w\n8+YqjbUNho0Wzok5irkSO3sr1GcX2dzaZNATJImH7eoIK8E2DEI1QvMmKF8Li1SaoFKk1Emlh9TH\nEFo07nUp5isE9oC5I1mk8/McOvYob3z1N4hvvMiHnvgkqTQQsy4jLwTDIEpSNF3h+R70u9zxJbXp\nOtdu9DhegB1xkk//008z9PpknfykGFGb9KmEB+lvyeR7+Mwf/A67K6tY8Zi8Y3C8PkU3VSSpQNcF\nlVIeQ5PEcYTUTQxTR0pJFEZomgYIQj/C0F3CUIEEx9U4cvh+rrx9GyksEpWg5MQElabpgRIwIX/B\nBA4gpTwACUCcJEhpIOUkta+UOLBbpcRpiADkgbKhEtCEnLTTC4nUDHR90jaPUpiaSaxSojgGKeip\nkGSUEmketcimpV6h4J2h7zToJ/NkwxR9aPG8/iL//Mgv8etXfp1PH/ol3hp8jQtLD/PZd77AQm2J\nfW+feBzjmhZONocConAyHMuDfhKlFFEQEEuJLkIMqaMLHZVAmngTcpX2d7N5yOV1KoywsxZypLOb\nL+J3e9y71uXoVAlpRwyDHqmvMX/oJI6pEeoelh4zzgSo7IDcyYTasTpvfWWDcMGCGcDJMF9bZmZO\n0h7b5N+5x+66hlA6blHHzmtkS3D/Uob5PZut1SH9tsfIG1K0syjd4N5rXUZDk7V3fd7bCnn0o1Xs\nikVhOqDZ22XtzgZCCGbNMk6+wNIhi2IlptPepLHVwXGzZAoWpekCnVZId2+MbbmMgl1CzwaZMmVP\nkex3cfQsc/U84a5PnAbEWkx9xsEphYz8AcqOKGRd3KLNcD9FNz3ube1y4ceW+OhPneZzX36Dz3/1\nDneIue9hOKzboHTycpp/8qEKl4/k+PFzJxjdLhJvN7j/kQqF8n10tyKeb97Ga+zzQyfOs9m8Sfte\nj1Fuj/kzU7THHTKuAbpFoiuUkTAYdHBLY5TTJj1koZI85+pLLLxxP2+t3ORqc0zmxZCVnS0Wt0N+\n4X+9SLYc0Jy+g+j4bI17hH2dZADDrQzsmIw3Y240u0RTW4zPD5n6WUX96ZR+2kDIEB8DQ3dwlEMa\nZsh3Xa6OQm691KGxErP5PKStHA/OnebDxypYbpFUekwd6+O4Izr2NhQTmvTJZDzqS1PMHi9zeOEI\nlpDs6ya9ecnWRh8Rp+REBadscip/kdvnX6B5VbGzukFCHaMAspwl69QxDY28lSLsGnHPoVqNiIYp\n25tDMpWQ7IJBrxuRpDHFTBZpJAwHIakFtcggo3wMr8NoFGO5BepnE3rXB1i2jVAhIg7xUg+v54Nt\nEquAdOARdhSuoRMLhetmURLCToJbkozaBrVClm++dpXWRoajy0fJCpe0HTO3ME3eheZoQCAEhVIJ\nO2NDnJDJKip5i0IFVCRpdAM0IfE9hS0LmJk80k9QmwnNdMA4u8PmTpvVO38ntwpsauRNg1jZ1FSR\noLxNczQGz0YkGVrRmGJuiqo5jVHMU96fIruok9gx/Z2YBx5+jO4oolxw2V1fRUUhC1ZEtl5g++ol\nZqbKNFpN+oFJmoUt/y/5yX++zukHGuwMwRqdImt+iCB6h1SuIEWbXgJZTUMjRqgS/fU2O9tXeebj\nNarzHkEyBbIDfgw2mCohCpvkzDq642MLj04yJCMltYrNVK3Ol/7yVR6Z0pk5NcQUZcK4ixRZnOoG\nH/tnU9z/oKImFJ4AL9EYhCMsW2P5yD4/9a/GjLsGe2s7XH2+SGtnhn/xa3kwdunGu8TOBl2xjO8X\ncMwukS6JPZuzF28SrZzh2ktvUxGHWK/vcuHJMnmzAukylfkb/Mh8B5s10mSfp+/rMbjva2TVj9BY\nOc76qkRUHkakDp3WC0SjGfRsAVed4c3vXma2mkevOPQGK0RCEGt7lEoaYXyavXsP44os0yJld3uF\nKLuFNp1SMHzCUUplCby4x/UrXbSbSxDl8W2PQNdIQ4d+MsbOZQkDn3Z3HU16eN1V+PouSmRp77xH\nYtik/ZSKW+He1hWOzxwjN7OAma3QljrD0XUGfQPZHNHYusd8sUwrvo9BtkexVOfVl7Z48txhkmzE\nd778XTKnF7Ax6LYHmKLM8swSz33+y1x8pIbp9DG0Mn5nxNT8DoViSrfVxx9n+NR//cv44Q3+w2/8\nDrXqT/EnL3yOj/28ojgXUtcEO9dtlo8cxjddvKjF4kMNolqLmYJAGrcob0oKs4LrL5zik3/vU3zj\nd+9iGAuEacTy8jz5dEh57j4GgwRjfIqokdD1/oTO3j3OPlDl2usaw0vzlCoRhVqPXFWju3GLnjek\n2UiRfkjOBL03YC6jE1gxmeJZVrc32d3bZr6sUTp0mJvr36JSnuX1l77B3GzKXvcNTp2axU9KDLxt\n3mo8h6Pn6AU+Dja2yhDS+Z6u8+8Tbzv5URdiggVFHASYSSe0nVT9/1QOdRCcnWw6BQpd19F1HSmZ\nIEwNiS4VQptsBKU+eaI8CeSmaFJH0yCVKRqTVuk01pAiQVcQqcmGL4xikiQmDAVhFBOFKVECqToI\nkXCQKZGTLgXExNYCkKoDapaadCNIORkmTNNC00x0YRLHKUoJkg+C2weWK/n++U7Cxe8TrCaZAIUS\nAi1JicQEv5tzXKzUomRp7KzewSuWGHoJ1UoNy7Z49ulHeebRp4jFLpY+xdb2Coess+w3dyFfQgXQ\nT3x0M0OzM6Tm5JGGCcogo5uMxyGpSomShFQlqMQHzQTfxbYiHDMEbYBME1KrwMmlChtTOf7Zxy/h\nr69y+Wu/ycmKSdYqMlQRpuHQ7fdJFJjSws2aUArwBxEnshFf2xzzq7/3m/SCkIKTJzlAPMmDLIYJ\ntLtt/uoPfpcr169z7uxZSjkLqZm0envowiGfrQCTnpXQD4gDnziK0bMalmWgaZI4jjEMYyJQCA1N\n10giyORNMhmL40fP8e6lGySpRNOTA4rYZLCQB4HvZDIGIuVkyWuagUAiZMwEcSw/AAOk6SToLeSk\n/wTed2EJkgRMzZxYpbRJxieOYwSCXjwilClSQBjG2FmTYdDFcXI0Iw/TuUDDv47TrTCttxmrlFtZ\nwQwJd5prVAunGZhvkUnr7G/d4cLJB7h19xZuKQ9hTCaXZ6e5Rz5bII2Tg2zGX7O80mSSjUpjRSIS\nTG0CYpC6RCYpo+h7jW79lx2NzSGvvLpGxm3TEBKRP878sSXscYa0BSiDwSBi5IWY2xFDP8Z3+gSa\nz+5on0zBZP50DUYhlVaEPhXTS1Ps1oDd9g65usW+Z5ACg36XyMwxDhya/j6Bv0/GiklKRXKRRqw7\n7Nz0sITAUVnmZmsE6SKDHcFsP8WKKviNPbbTLv3Iw7ELVPM5kpFHEAncokuUtglMSW7KwjYltbqJ\nk7HRNI+sKxAiorvWJZEl5k5M40TT1Kc9wl44+U7CkFzWwcoqjCzEokt5xmIU+ATpGG+vi+9JfBWz\nNbzHk/c/xJ61AtMpdi5LdSZLTd9iFPhYpkQTI/pJicaNVSpyiXzeZ/NuH3Oxzclqhe4tSTGq097v\nYzhtxG6fcfMOrdvbVByDY4vTVIuH0KICK/f2CdwetdmU4mEPLTtkmLRYfNzFHXlsHwrZ+v0hb+1d\n43ToUuhJ3v5TU13bAAAgAElEQVRaxK+8/QWe+dGjPPrUIqG5Qc6FccNh71pMGms0NiL8fYEvR/j5\nPtMfD7nvkxkWGTGSTbZosT0Cbh3FW8/RuRxzc6fPaG3E9laMVBaqaVOOs9g5E8eNKNQCvGST2AwY\n53x8OcByXMyMhZlx0XMJw/6AO6s9rDSmt1dEhTlGu5PPuTo+RIyPY5xm8fy3Gd7K4CkTS7PRlIOK\nIEgChJUnNF0GTR1/lBJjIWRKIGBpdgqZGaDJiDiI6bQUWTfLnh7jeQovDthXLRQBgaUzHsf4sYOm\nKcaRwHAdhLAZDxSDaIAuLKJBhB6mJB1IHB09dCGn0+2mdPUIUQyZr+SZW3BZmq9x7vBhkqHgu1+8\nxPrn1viF33yKn/lvP8zNIM/rz62yt+rRDyYdTZFUOBWNbC5GRhH1kzrJqsbGIEYkLmEvxogTonaG\nfLVEv7tFb2wgDQP421dAN1pDtvTLRHGEH0Cqj0kGI0pTRzl24mEKepa91TV6/oiSUcI+4mK5NmFv\njC4t2o1dWv3bLBTOU7Wmqc5kSPY7DEcbeKNLDAYmlUyFSibDIOfSvmrito5w/a96vP65+zG9k7jF\nLg9/6iHMh8qMjHfJyjmGaUyqLfD21XVCL0u5nII2orVToLoUYzl1QrtHoFJ0o0+gxYyTfRyyaHoG\nIW1agcfXvtBG6FN4vqJzo4MV6KztpNx4RRBZksc/Jjh/cReZbNEOFYZtYmFQsSWj2KPgGlTva5Gq\nlLVOh9VOyrz9A0RhFakOkXNOEI9WCNIOwWCGwChgVNvI0OTFL1TJDy/QuPd5to92qNS69IImiQgw\nxC2yUnDjcpHc/jPMVGaIDv0JfqqI3VcZDIp85yshyw/Oc/h8SGFaMh4n7Nx5Cm/tCJe/uMnZf1wk\nTHtkFq/j+QXasc7esIkqXEHOXMeOHuLWTkDGKbM48wTN0UsoX2DlSkR6Cz0fsTyb48pVm1QzSImx\nE40kbWFhIBCEmmKgAvS0T6vVwL/qM+oP6Y8UhqsQuoYmFBU9R7vTRXduMBQJWTcPZpU0LZA6U7y7\n3iErI3RVwxAK0yly+vEFrt95kd5wjXpumvFdiB0DuzBPEOdwbcWFo/+Al7/yWZ5++knuNXYpZKZR\nXGHuRIPh7YTtdw7xO//xs9RPXOXE4zYvf/3POX/0R3jv9Tc48VAXP93jyCkfOW6yJ9ZJ+3cIhE1/\nW6NQq9La30VzaowGLeaqPs3WH/PYI6dZWd2mP/A4ejJky9RRAxtlrBFvZrn3Zp2O/Ti+rrOzvkvN\neYjrb2Qo5WcI4hoPnb/Im9farKxuk5U6J6bnubl/l/m5eRrrK+TyBZo7PmbWwI4kgSwwGGiYSZ1O\np8/h44us7N/BKlYYjvsgFJ12nyDsERZ9pLLxgwQnUyJNvrcR4vtUNCTqA1RszORJsXYQop6EndVB\nWRlKHagSBjAZGixLQzc1NE1hGhLHAFNX6CJBHZStyQNkJ4DUFJY9ySMIJYijmFRPSUwDPYoRcYpE\nQykfDQ0h1QdKSqwUqUoPWp4PNoXJxIUvdI00UbwvYKRqgiid/JGToYTJRleg4/veZIM6McN/0MmB\nkCgpDzC/k6ZvDvIek6ZxSZwkODmLIA3Z29vlzOI83VaL+lSZbLVEIdVZX19j7A05e+5n2N7cJYmW\naA0GzM4eQsghmtjDG69RdDzaPZ9+VGTcLBG0pnGcGmg6G6HEtGzK5RLFQp6xFxEZEKuQOBmQ4tBq\njtD7isXj82TKJpWqzYPZwwCEF0/zwE/8Fi/+X/+e1Te/yvLhQxB1KVk2fRSRDv44xuuuk3WK/OmN\nq/zrz7wEQMEy6XkBhYOehtGgy8qtG1x+7SVe/O4LXDh+gscfeoDtnX1iodA0nVy+jq5JRqMhqBih\nBGkcoOfy6Jp20C2SkMlk0DWNbq8zUdB0SJOA0A/I52PiuM/C3Gn8cIBjThHEIUKak1C2YJKzUBCn\n4UFJ4oENSk2oUOIDVUpMBhFtQlRLRTLJFUkJyWSwfr/jBTVZ10kckqBI4hQv9snYLp3xPhU7RxD0\nyad5DJWSGfncGTZYLveR+w5bs22m9/OEeYNHU5fmyCGemqEcXeZw+hgvt3+HT039NzyfvIqOxTgc\nE3k+UgiKhQKBF6FLSZxMVLkJtlciNEn8vsKoJEoFmFJDKIGuGej83fiuPSFIChpy3mTWmSdgGqM3\nz6y5zPCdmMZKHxE4WALa2wFZqaMLyZA2tuNRfUCRZDYYGyay3qcfpWw2OhRLirKtYaFBICiWc3S7\nHUx8ul1B5UhCvSpZrhj06LBfdWm3hxhlm2Bnn6JT4NR9h7j0tiT22mS1HIPGiKyuEWc08rMlLE2j\nkCvhyTG68tjYaONUe0RRB10bYWYtpA4bm21GbajWCkThHrbbx3QThFCMNrtkpvMEw4Cw51OemWK6\nbBKlAcqM6cVjUgtkbgwhjAYe3XGEF6WY5TEnf6JOxDZHwilanZTNu2NmZxfJ0KctIjo9m1Ls8upv\nX+UbN+/w8ONnOXLuOGY9ixx2iAMPGZlUBx12d/c5/1CVH3/wWbZ2N3ntlbu8+e1t4v51hqsuy9PH\nmD/vYNQiknidpNJj8USOnL5BMG6xMF/kp56c5uaf60zlXNypBGmd5a9efY4//fxdpqs5lpcchNMm\nsmO8fozV0rADkxiTnmozLlzlkU8kPKotQE9nVFjDHuXI3a6w97JD570sL39ji/31HvW5aaazMxRz\nDrm8TtYskMqYJBPgVNpIMyaweySkpJZGszcgmzexCzbt3g6NzbtoYkx9qkhem2K+PM9Dh6f4i2+9\nzJGGzWduX+FHM2M669BsdRBhBidrE49N+nsxwjCxSiWG3ZDtRgdD5slnMpDR2O2HGHs+2dBCDRIc\nU0fqJprUMd0qiTkmECHSzpBkDUTOItg18bqSRHdobQbkcjZDZTAKsqgox5iEcCdED0aYXYWedcln\nSmTjLL5vIfQcpqfY74xYf/5tdtdDPvTgHDNHpqln7uO553voZpM42UCGDWqLQ66/24WggBQGo3BE\nSsLOsI3uD1CJhp3MUq8V2Nmz6XsJLQV3bw2xozVie4i7OM/MvAlc/1u/V2z4l5CyjO/pCBKMsoNT\nm2HGXUL0JY2wQcvb58HDj9Lb6VHPL7G5vU6qpRRrAhHv8gMXPgKhSWBtQTBEGw/p9lbB9rEzMWur\nNpvNMfWFAocz07z1Z026dz7MgniQQ1WD4eoOr/4/73HmF+Y59mwFITrkRZHG+F2uvxYSNc5RKtfI\nzURkpx00q8cwHIFIUdLEMmCQjAkx0DWLsdoliFKiccz5x0r4c1W++Vev0Vw7Qhp1+cIfB2jDT1Ao\nvsLRRY39nQGlmkbFcVHY+PEIW0swdRsdnXECruxTK/V57KM6/+//8odE1Z/hhz/+CLpsYGbeoKBO\ncb3///H2nkG3pWd55vW+K6+dw5fzyaFP6NPdR50ktVACgZAIAgwYgcciGOOibPBMGZVBw4ApMJiZ\nKYtCBYUxSbIksBBCQkJqqVtSx9N9Tp8cv/PltHNYea13fuxPzcwvoDzW+rlrV+3atdd69vs8z33f\n1yVuXAiYnTyDJorQrTGMWrzjJ0t833vH0cjTV0NSsYKmygTk0f1JXnkmI+vqPPVP/jXT5+/zpZ1f\nY+r8q5w6+hRbOy0ufN1m8cTjzM4q/vwz/wWn+R7OH3+MT/3eZ3nTDy1hGt9CJ/kqjis4dhxEOmCj\nHONtLfPt730Xyzdjnn76i+hGheNHHVrba1Tn8piey0pD0hwqUD7YKaZpY2s2kZeQZBFKChItZRgF\nxGHI6tY2MstIhMTY/x/PgECl3Lp/nY4P5dokQkiOHz2FJ1usD7qsbd9jrGozMXaUN1hw5/4Wm1jI\nwzWurN+jkfSp2luMj5/AyOWRKiVOU8q1E9j507x6KWbQHTI753J44Tjt3VXmxmt0JhWHzxzn8u1L\nVKtQqS7R2i1yb+08U5WEZvI1pqoxWW6XpvpbtDxYbp2tVhfDAYJ5GLj02wrXqDF7coLTTyzQe/qz\nnJs9wOyBDfY6d8jEMsceHmd9d8jNyxt0YsXtdZN3fMeP8NKNbR459y7+6i8/zdve9u38hw/9MQ+f\ne4i8lWIaLit7uywtHeSFtQ2a3QEPzi9y+cplJqdrFGcKbLRXSHcF09NzOK7k5bVbGI7LlFtAVwPW\n125TyAlMNHKxhSDBF30yAnJuHZp//3P+j2o0MpUwUt+P/BcjGbzc50T8HWV5FIQjR1sPFJomMU2J\nZesYpsSyFHlL4doajplhaBJTl2i6hmVYGLpE08T+dDkCKfc3IToiSzGUJI5N9PgbsawhQZxiGwrd\nyEaNSZaNJtYCDEPb5w6MIG0yMxBKEKbZiDyeSpRUI1OvZES9zQSGYRHH8YhsLrPXZTdiX/8/mpur\n12NrM5WhI0dbEjmK15WmTqfTw845EJvUqmVSYGVrl0KYMjU+y4HDx3jmK1/hU5/5K44cOMHph6dB\n5VlbW6XkjuGYNbxBht/dY34mpTsYkKqQtHsHFd4jDIa0NNjd2CSIbUq5WRYXH2Zu7hzFXJF22sRx\nBIeenGF6roxpjEB0CEWsFMb+9kGmHt/6cz/N3ece5y8//EFOTs+TttfRSxaxKmHKNrgHeGn583z7\nL/53KgXn9SSpom1y99pVLl54kbXlO4TDDromefsbn6CbBKx19khkTDVfHjWMwxA/TRD6SNpkGBqx\nGkURRyloxJTL+ZEHJ04wDId+v0uSgmGOEq0EGYHf58DiQUzTQjc0BoOQXN4mTtJ9Cd9+DPD/61ZX\nWbZP71bE8ciPIcUIzKfrcgTeywxikaElCcIwyLIYUzpEMkaPDQZRj1homAo6aYfJ/DSbg2WOMM59\nf5eqMc7dwT3mZ05zp7POu+bfzFdaa+RmQn4y/xR/OnyadxUe4IK/zLsOneKra5/lyPhJfvnmb3P4\n0KP8YfOvODI2A1ZGwczhq9HGJRgGSE0fGcGl3PcWgUQgtVHSlcpGGw2QBEk6kooBcfrN2WgkqYaz\nMENWcfG6EV7fI2r3mcrpiIrB3u0BkchINR3pBAyUIh30iaopS2fHKC9kZEmCtCSzRws0132a620a\nEzp3L29wS3UYJCVijjI+VcdUJmCi6zFuLQbVA7FFw3PoCwdsm/yYi/Ak7WaL1TsD8vUiE/MWfhjT\nGDTQB0NcL8OLfHRs0iik4ECzEeAID7diUajqOJpkZ2tAd0ehWS67nSZJ2OXI2THKFZugk7JR2EUk\nAW5BonyH2OvQCJvEcYZd0NBKCmkLgiiiUDRYOjbJYA9Wru3Rm7Xwgl1is4FbT4iUzWtP32f5VY1K\nyaBWGEcXBR47/RA/8ANzbN9qMzWj40yAMTWkvdPg6IlxBmsRSVvj3t1LbOby7N55iaUzJ3h8epHx\nS7u8+vku9+IV2hsDzPwUlaUu8zOKuYd0HpKHCCKfy5VN2vV1xFyBUwcrGN0YI3TRJbxp/CQv/lWL\nF65tcOqhMzi5AeurTcqaTif00QcFegwIuM/C+QLvOTIHOFB6hecu3GXnsxPsvQSdyxntvSa1owc5\n9q5HyOkJJBGO3ifvaOQtRaJJejKhY3aItYBIxeiahmFbqGFKf6/PsWMTVHMFTDmDU+gRJgF6P6XT\nWmOyegh7R6e1kjC5W8d7PE9ZP4U95jNoCxIvojFs41omUrMxYkGUBGhZitI0ul6IJhT5skEul8MQ\nMPBSzExiagZhNvLXhUFMc6DQeya7gxg9kww6kt6upLedYYYm8YaOFDqBsqGgMfD6pIHDUqHGbHmK\nEmW66wlrt3pEuMSWoCc20QoD/GGXabdERBMRa4SixcwJA6uouLT+Chv+bWqTk8weKbF9R9HZSSiY\nGkbJppTLmJzLoyURWuzQ3MzRr0DO1FnbbJB+fcC8YfCd3/44zgGH9csr35Ra0YotpJVguC1I85jh\nJNX8OA1vSKw1mCrUmamX0ZMhCwcOoSyXSXOerLsGDYtCfkB+o0tnuEK13qHT8/CJyAo5Hn7yJDve\nM9xrLbMbFDiaO0fFdqkaBynUBtQLKTu7PXTZod/Wad8/gogzEuMqBiXKboXuLpjRPMUJk3NvLpEr\nD4nEHtIIEFkRIXwSpdOLfDJDIBF4oYEmhkhsHnxco3/+Jnu64PInN/G+MMbtC3BgwaTXc7j25Tae\n0eOht0lEKaSgZTjGEmnqoVIdYbhUZERASFf08DsZheEBXvgjD3d9m+/48TcidY+BdoPJsZOoE3fp\nXOnxmY9fon39KXT9GqfPpfSCCN+KcIWDRQVLHMBihxMPWdjqVRovfSfPf0XwjiM6iwfnePD0JGQX\nodrAuPleujtlPH2buTl4+gufQDs4xfe++wyv3mhRGb6b8sJBvPQP2NqFrKdhmjGmsUcn+BNi9RYm\nFnQq1jjLd66QLxfwtg6xsZuweT+lVp1nMGzTj3ZJkowo8NF0kyRT2I5DHASEaYSmWbT6A3RNYJgm\nQRJi6iaaDqmdEoUR3c49SBoU4iEraxXMygK7e0OKZZfOsMPc/DRDf5zp2RMEGxfRpcSaOktnZ5sk\nvs2icYR8EtOQfSamZthr+px95CFefukrjE8dwHEEzz17hUeffBCtFDM22eC3fuv3ectj383qXUHi\nebx2+RInHniEP/jNy3zH930PX//Cx5lfOMjWhs+ZB3OEWY9Uwtr2zsjP6T+ESH0efMMBpg+sQe5j\nPPq9DRqNa/hjOuGMx4lHUuq1bfSGQWdbo3W1yIn84zzziR5T05P8+ac+xnC4x/MvKUxD4+bVi0xN\nznD91l3+1U/9LL/6n36d8088yeKhBV546Rkmpgosb32NBWuauYU5Lr54l53ebSYORtQPK84+9Db+\n5vOfZWwyYmHCp5wvs73WwdsIkFmVin2QNBMESfIPes7/UY2GlBJNk/se25H0SPKNg/foPUKMJFKK\nDNPUUYpRc2EKDFNhuwauBa6h41gKx9CxDYGuSzQx0pBrctSpIlJ03cVyLBCKLAwxDB0ygWYoNDND\nhBGOIfFNgWlkGFqGoWdYdkYSjqB+8hvE6DRBEyNNvTB1lFDEUYQS+5sOTZAlCbpugYAwCgnC4PVU\nqiTJ0PVvyGjU/nZj5OqQQo42OqPQVJTKiJMY0gTTskbQrzBmcekwgzDg8IGjQB5dFBBK53u+5wcI\ng5CtzQZf++xrlOoOhWIZvVLBj/tMHJxgdztHFAdUxjXiMCTwuxi6RPg9Hq+dYFm/Rqe/jjR6eP3n\nuXv9Ik79MO/83u+lVrIBSIkBAxhR03URj26DCHTTJVUxBx87xb+Y+xh/+qGfZ3FslkHQpVjJCMMF\nbt//NE/9xEd46uHDo0ZQCF5+7qt8/I9+jwldoOVyTE5MI6pldE3SGQyx0DGFySBJQCU0GqvYeR2p\nG2jKIY4DsnSkedYzG103sO08SZQSkaDpGUIobMtE6tpI7iQUYTRA0w2mp07j5ExGLpqMOBk1Edk+\nETxN1OuJU1mWvh5pm2YZOTs3kkcpQRTHxHGKaekoLcVQGqluk8UpumYyTAfooSS1wDIdColiN2lR\nFFXutW8xYc3xmtxi3pih4e/yz87+IF+7+AzvP/gW7nRu8YPzx2jt9Xm2cYUfmHsLF9dv8m0Lb+X5\ne6+wNH6Um7tf471H30uns8Jj9af4+OaXqBar3GqtUnAKCCUxNI0szUhktt/I/x1IUymF3N90qHQE\n0ZRSIjWB0hRx/A8rCv+jV2fb4+rntygvhbh2ES1zsROXtRu79JYlQeYzlAl9o091wsXICUxXxx23\nQUV0u0OKmotAQwwVw2Yf261SMMHORRw/exwRO2yGE+ystGhtRty6sYdRkniqTzm3jHJSbm+bpFoV\nyyyhezV6ns7N27vsJT61mSphuIcq2FTzGVER9HKGkUpSPSCNY3yl0E2daqGGRkSv4dHueAx2M9xy\nDt9XSDtm6dwUhWpGZ3cVP9SwFlyUn6AVi8QeiI6LFuoMvAjf6KObkgzI9Ix+FCC9GN8XhEnIeNml\n099iZj5ibkJDj6Y5PlPj9pWMlSt99pqCLNC4+blrLM5OcebsYZzJJu5iSHk6wZgdEGoa5mGTvG3y\npHuWXK7EneVVBq27eAOT099dZfqRCc4/v8TnPnINpxJw6nSdiWKPk9o03f4tnk8vY5cUh8QCnWKb\nzpJH2soolGoILeTUo5JBweXZ3/kapnGPH/m3b8d7yKF0J6O0UKB7O2DPu4OsS777X54AqsBf8OHf\nu8trfwGN5SHWXpep2YOce/wY4ydnaUYe4W4Xwga2oyP0iIFokZk6ngwQpkK3FZouqYzl2WoNyQZD\n0mBAZ91k6bxOzlaERheBjukEWF6Z9jDCiCWdOwnj82fZlQK/MI47PmDnXkbJNRmzHWw7RxQO8HoD\nGq0WdtnGMHRypoZZNqmOu0hDEMRDIGKwm9FLPIZCMQihH/SpWg6yUsTRi9ipgdETFAYaIsmwEoc7\n1xuIUOAsOjjCYGyqyFSujpFpaLuwevkuw4bF5mqHZjrAGDMYO+xw7oklgmiLx08sYPcsGGjE3Rip\n22S2xu4tn6xkYlQMbF3D1iUqCykVpxgvauRNh4wGhpGiRARWSr5icyfy8dseC49NU65k3F9vY8k2\nmR9/U2qFEDn0JCKvHSZnT1KtKuRAcHziBEO/hwh8DDfH9PgE83lJq32HpGrg1fI0GyFK5Lm0foX5\nh1c58FREiKDflmzenGKnU+H6bZ9WT3HygSPYaY1Oo0en75K3CzSGdxAyR9F2sSYSwiClu+xiLTkM\nBlusNzfwfdAdhaWDUm2gR5J6GNIEqRFmPrHQUSImGBoIM0CzM/otsAyLlCF96bF0Ls+nf7fL2ouH\nWFp8gFxRo5w8DNGznH9wkbH6fTIkIhuSZCGkCbbhAvooyVHYbF/o8/VPDpiyzpObXuDWldt85Nde\n5rt+fBp78Sau2WNuapKdjW3GFp9g5+oEvV2Pv/0zA9MccuLNGaoKfZHR4QqGNompwdJDC7iVTyL2\nNDa9iLFpicU4mahTky/TGP8YzTsL6PqbuH2pxOHpN9DduM3nPvoZ/skHF/n0879JduV3mD5mk8Yt\nQv8uvnaVSGtipN9GZDzD2ORJLJqcGJvCdD2W7wi2Vi2GOyaO8DBVjK00wiQgjBW2IXGMPJZm44kM\nRYxpW6RhitAlcZYgAV2OJPtKk2i6YOi1if0WhmHQ3nTIZwmGUpQLRVotn1ubl7DydVwEpoiYMBaY\nsGdZH1bYajzLs899jcOLDzB14BwqcnBzdWwn5ujhJV584RUmJksUCwtceKGPlW9RnbGoyzNc/GIX\nE4Wdb1J0FHdXvoCtV3j52VXmDz6GaM7gqiG3r73I/KEyRj6HZdZYuzsg3SkxN77ItRfa7NwMeert\nx8BooZk6q/ca5NIeIrHo74a4ssTilMGUWePanTWmHYOdey2GcpNID7h67TpT1Qmy2Kc79KlWSvz+\n7/0GEyWfjdUvsVc0mT6iqE8GFOdjdP0e6XiXwqkmx04tsrJ3EV3XuN/9DIceTDHcHsqASDWojOWp\nn1J4rRZxa4i/bSD6tX/Qc/6PBvZl2QhqhshGk+F9yYbYP9RJMTqwSwSm4YAI0PUM29LJF1xsK8PQ\nUhwnxnA0MiMk0/IYhoFhZSRSkekS3bExLQkyReEjhMR2NYZJiOFIzBisUIDtEAQRpu5hm0OqxZQo\nVMS+IJGAECM9vpJkStsH2yWY6ER+B70IKhB4SYibFUilwJAGw0EXS9dxNB2ETpSlmDqkZCgNFNq+\nUVi8nlykSQ0yOeIoaBqGqRP5AbEWkEQ648UJakUQmWI4DHALCkyLRGX0ghDbMJg9MkvmSzrdNkES\ns7e1RRTHEMUkvkepnCdKY4K4T2WsRq/ZpdsKaRZ3mD4yg7Wd49KlCywt1omVJNi+wp/9+qs41RqL\nx07wxFNvRbr75mYSQCdJUjRDJ40VGCOzvz6l8WMf+R3+26/8PEFjh4nZt/Pq1/6Qd/zK5zl9bvz1\nTciv/a8/znB7g6WZ4zi1EoYm0SwNKTXSBHRpE6Qetm3SazYJ0g65YpUsk2RJiqZnZJqOYRUoFuqY\njk2+YJEF0O7vYVkOShrkDJvd5i3GajmiUBIGCQeXJrm3ssqpcz1mp45zd/0WxGDYGUkmRjKWsIdj\nO2T7hnKltP1mQ6BrAj9MgARNgpT7BvEsRgtdwrwB7TWsWpVuv0FZztJ2mjhJjt7eVWpjjyAHfYxy\nh5+d/ef89t3/zB8+8Iv8+80/4xcWfox/d+u3+fDx/8CHgz/gzdZbuDq4zHa6wWHzAF/cfZEZu87v\nrv8J7yh+C/f9O7x1+r38Zfvz5AcFruXvsu63OVSvYCsDCx2hS7wwwDItDIyRGVzKfc5HSpqm6Pqo\nGRG6vh8rPZKGpUnGfujW//RrxqoyTUz/bpueBtVCkeFdDdVyGQY+YQFiOmjlGGfRwq1lmDmNjq/Y\n2N3B7ml0kxSVKHqrGoWgwPRinbybkKiExl4Pq6DorW+TRQmasGi0Ira2LBYfWUDO5ekEIZXAoRXk\n6LVdhqsJWT/lfq9P6dgE5GN6mx2kkTJ7soYz79IbtAmbIYN+E92yiFVGLjPZ3jRw9DKZZ+F646RJ\nzKCVkF8SHDieR1ba7LU22dkbMFZ38eM+lqEj8ilRHBAQInDIjetUp+uEWcrmXpO4lzK2MIE/kOzc\n84g7kuJYnmzDY1fdoXDSoGyOE08UyN8xmZqewxMaQcekt9FjM0sZqwXMTIIedWlsrpMvmuh2Ey8X\ns95X3F4dMlebQjNg5kENJwtpZk3Sap3a7CE2BiYXPvMlrv92wKHHNK58i8ncEwVyRcnR3RJiYo9G\nBCXbo1/3KVh75FMTIUx+6LuOsHAg5Pc+eIG9n/ko7/3Bb+X4k2e41OqyVVxjfbjBj/y7N3Lk6FtZ\nWf9zfusX7uHv2Bw//CZOHi8xWZnHzVWICooem6hmA602wKSHbkuKeY1+rEiFhW5JVJaAkZF6QxIy\npibh5ID1V+0AACAASURBVHc9SNAPuPzyFbY2JCeOTNEYtlC6z05rCykVqRDMnC7zlWeWOffVQ+Te\nXac2XOQl6zJdL8SMOrhmiokgijxSlVAulyhVTMyihiUFoeEx6OwRZQF5aVKtGXhphNIl1WqORIdu\nS+P+rRb9Sx5OzkUkMQ4CO5ScOjyPLVyOl8d4wxvPYDqKF29fQVgWh5YOc/WlGzTTHsV5l1PvPECg\nZezu9VGmon5UcPrRElcvNphdyuFoYzRfimlHAcqw6N1X7GQB4w+UWEtj/KZJ5CVYsoAKYe1KF9v1\niLUBY6UUUciTehqdfsJuo8ORx45y8JExrHqEH9xi+3ITf1j8ptQKlfYp63MslE5j6RZYferFPHOF\nCDGV0og9KvUFHM2jZ3+Vx97nUJir8ur1NuqCIOmeJT8X8/A/TRl7aAtNldlYdbmz8hovPWcw6Na5\nvz7g5OkqDBNcx6dvriDHZ8i1qwijxUZni0K5xG6zx/p1H6cRMAw2eP5CTLx3Csc4SK1QY/PuFcbM\nDplWQzkBadYj1XxUJtGw6OymkFOYpYg0temlA7YHgkYXnEhw6MhZZrRHyUqXyDkN8lkJPR8StQVx\nCI7lIlWKpXXxoz6pDAjCDMPVMLMJcuI4K5c2eOfbKpz9gZco1wp89uOf4JMfq3H+qXmOPbqHp++w\n+GjErZt50okaE4d0dvZ8/vrPenzxEyFPvO1tVJY0yose9YMjOVWgX2Zs4c0MtAEaPdycSTd7HlMG\nZESM1xaJtRVaqy+weO4BNr/sMW0/gRFOs3zzwzz6qODrz32A3t6P0Vx7B69e/3Xe9ORP0Oy/yMLC\nY0xPmmy1H6XVeZpSdUg/3sayBbpZwCQhCVqgC5CCRItwiwU0TSdnFNCUBCKiTJESYFnaKMhFCAwx\nGqppCiw5Gg6njo6SCXe27lBut6n096hPH2R3Yw9ZLnJ9+Ss8eu4MpsrRLgpMZwlDalQnp7BL38ba\n2h1St4hjlsn0CnEfgqjLoaU30Gn53LjzIkePL9Hvtol1G29V4PX7lPMh7d0tinoRTVhoagLdatPc\nu0olf5Z7Vy8wPbNEufAtbF2U9AwH5XiU7CVk4QCvXHmOYwsn2NzW2bh7kuee/zMqU3NstSvY9jjJ\nzAyFnM1Ou0cWODi2xvR0AbsZMTOusekJ1jrbVKsm6TAAAxJiBlGbRDXQtQGJBL3sEOc1OpZOZPgY\nmmDXv0vxqGQ1uoReNogjST/pYudAaWBZJrYuEFqMpQviik8yKeg6JVZfc/9Bz/k/bqMhdDTNGKXs\nAEIfGXVJQUgdqY2MuqZtYFkWihjHymHbGboUGFqCbRrYVkbeymOafQzNBUKS2CDwPcyCQxIlJEmM\naZmjzxMSoWUkSUIunycMYhzHJPQThmmI4zhEaUrJhiiX4QUpQRyTDGKCSCFkisoUUh+lT6VaMoqt\nKoyiPyMtwPFsUsMnL3OEhChDEMiYNFVoI7HYCOSXKUgAkZGpETTN1i1MwxxNj6UkTfZ5ImmGYVpk\nKkMJqNdqZEpQq5WpVOukmSKJwLZ1dATeYIAYQrfVA1ICkdFOM4qlEr1BSrfTI0PHMCS12gy9bhuk\nJFcocOP6Zd7xtnfTbW4wPlbl6vVXqY2XiIWNZQn6W1us3nqOv/iT/4vvev8HOPvEm6nlp0fkdm3E\nkkBGaColTk10zSYg4fs++Bt85Od+mf/7v/wsP/0bz3LqwTwwIlP/xv/+C3RbOximhZf6uFmRSm2C\nMMxApHhBh2HQQ09NWv0OBi6akERRSJKGFEvjGHoZXcWUKnUOHTrG6sYa07PTrN2+RhaFdFu79Pse\nD58/z1HrMI3m1qhIGRpxPKRQzJFlDnPzJ3jx6ovUa5Ps7e1SrYyj0hFJPo4i5D75Xe2HA0gp9n+v\nEVQyTZLXfTcGNsNyk6JfpFtdwtvpYdqzrOg3edfwcZ4t3uCD5z7ECzv/jejoQ7wv9yb+zYv/G7/1\n+K/z/q/+Wz506t/zC43f5FfHfpWf3/o/OCNm+bL+WU7nH2TXu09L7vD24vdxzXuafzr2Af58+Xd5\n08R7+D/v/xH/cv5HeNW6QDf2KOdL9MI+utD2mwh9ZIoH0iQZ3WP7sbxCjBLfFGoUyiAgTUcJYCN5\nlRrxXL4JlyU0ZmcWyMw6l19osnNf0r+bwDBDWRJVSMlN61QeN5k74tBptfGbPUTaxU0UQQNaqz2E\nMnCyMo4wCXZSbqysMHV+gB6FJPTY2bUZXzpAeaxMJ+qSK5ep14+QN/oUzQ6bg5Td/pDdrQQ3clhZ\na5MpSW22jhdlTBzPs3p/mbFjYxx6pMjObh89tem2BK0Nn4EviJuStKcRNTSMtExnL8DSJEKXOBUT\nr6ETD8FLJVgFmoGk1/OxZIT02iRtm7hlksYhaQciXMy8iS01Ymky2A2AIjmrillwMbMma9eWWagN\nmbfGsCiQ1AR+pLh2aQPRnwI0zNwY04cLtOJdvDt9qkaLw+chZZ0aBgPRYlixCfsGNzaG2HpClB9S\n6EF9vkpu4Sg7RXj4/S612nGuXriG39f49H+8jfNRQXna4Px3ljh5dga3khDQxjCboHZIWwrMCpE5\nyZEj43zwj97CL7/vy1gfvcPykkMvAu1tDu85fZwz338QT+3wKx96kVc+bvHwQ2+ifvA4hqURWx7b\nRothNkRISWkuwbVBUz4qTkn8AIWFNFxEJEAPqY851IsuMoupTtoUSz22+j36ewGf/PB9zP/lEfKz\nR6kshZTLA6K+wzDNmD8xxonVkHuf71Kfr/C+Jx/n+nyXzfwyhi0xVIZmM2I4SQOzZCBJSFQXTXgY\npkfZNdCKDjoJne02hutTnq0yeahIEOv0WgW0QYW7lwek6zpZGLEwkePE2TnOHh/n8tVNjCyhPF9n\nb3uLmiqyvtHgyy88jVsQHDg2w5XlVbrOFg2vj7loUShJ2uzw1Vd6dNbbtNZ2cKISd54e4PUsager\nrF7vkkxpzJgHWNtq4zd99MBmspDHzXTCToQmdOIydJUkbZoEe4KV1S6qYjCxUCXOPCZqFrpbIN5u\ns/blrW9KrRgvHmamdoasfYPx3AI58ygzSxlPvrfIXnCb5z+XYScZw/xXOfz9DZLHVzH0HE+cLVEq\nuuzenUSMr1A/u0egOhhiyPR8geOPSF697TPszVGbqCLUKH2nP4gZe6BKXrdxrA12BxvEpR61w+9k\np73OV1/8BLnkOpHWpbN3msNz70VPxomzDVqDBKNjk6+ALjM6sY/QPPxIJw5T9tYFxqRLZxghNAsv\nTUhSkzSQ3LjWZ3sHzpyrMf/EVQ4ebbPywgm+8MmMv/lEi+8sVtHncwg3wFIZtiygSRtLz4hJaYkd\n1uUtnvrRh3nD45fQp64SKZN3/lDEtRemWF1tcUC5bLZb6ELn/rXL5CoWb3tfwgOnj3L/3hbXL6bc\nvuZz77/qlEo2P/pzDtojW3i9OqvLtxi0cpx5Q5281SaTN5CYbLUihNunVM2YqO7SC+/TvDzLzWd6\n6N4FiovHMEtdHn7LV9lZeYZ+vMMDbpGk+CmKlR499yVs3sj8zHGS6BWK7gS+3GRjy0ZPLCxNoByd\nVOpEwQAvjXFNBwOTLJGIJBlJ8pMM3R4pZDIZITO1n4KaIYEsipHSIiMliCOMnAXpAL9/n501j/LY\nAjXXIVEZmTnGpct30XSThx6aIfQHFN0chIeoOhO0+3tsbN/Ero5hlaq4TNPeW6NcrZNqik6vRRJF\n7IUxiAhT92kODcyCSy8QlIpl8k6OdBhjOimbu6/Rb0fEfsSOWSbqH+fa3QpveOtbuLLxMvOLRTq+\nzkqjwXT1MOSneXWlyAe+8wN87WOf5ImzJ7m1fIe020ezXJRl4pZN/N49js4corGxyVRlmt1hgO+1\ncV2dbnePvOkyjNoIPSI3KanPGijdR3c0/CRD2AIlMxzdQpcCWwqyKMOQEUlekVoCG5uiq9BENDpv\nhECoYxs57OoUe+4/TI6t/dIv/dLf+6YPfehDU8BPmGYJKU1GBDzBKOZW24dOWRimheO6FPbputWy\nQ7FkUioaFPMGpYJBzk3RVYYUTSytgG50cY0CjgW2ZWDbOXQdLMvCMnVMU9ufNu+nUQHeMECpjCQd\nWbCHUUIWx2RxCECqFJFKULqJ9o2EIF2iaTqaMUrLClVMIiOMYQ5PdjhoHCEx29TSMfYGO6P0KMNA\nSTHaXWQSoVmvm4Z1YWBpFnnLwTbsESUaicrYTzaS6FInCBN006HbanPy2BzzU2XGx8YZDlJM3SLn\nOpBldNoNhoMuSeyRpD79YZtWa5vGzjpp4mHKjJmpRUI/Ic2G7GzfwzINJBaV0gzSSHnl0ld44Pjj\nNFqrZCohTnUM1SMdZIxVZmnsKR488xbW726xfuseKQnTs/MAZGIkWSOTaLoc+RWEZBi2eexdb+VW\nZ4r3ff+7EbqFEII//5M/5a8/+jvUSyVmF48wOTOPZeVQSuB5PoNBnywbTQejoIlhGCilATZT0weY\nnT9MlAhqU5PU61NMTU0x8PrYjsalSxdJghZ37tyi2dyl3WvR7HY4cuIkw4FPr9MhUxlu3sEwHZJM\nQFrkL//mYxi6hWEZ6IZJGAbs98SvE8lHBPi/ey2Ow9eZGJlSWKaN1EEF4zTCbaoDhTMr2Wjc4l+c\n/ABOscgb1FE+u/ppnpH3+CnrZ/np+/+Knzn8U/zy5of5N1O/yH/c/U98V7LIxewG7z76dm5srjJh\nVmkPYvS8yc2Gy0PTDn+x+SWOVWvsNlLK9h6PTr6Rj9z6Y1a6Pe73GxTzebJYoTFqJpSANEtJ983f\nat8rpMTou2QopPhGsprYN66P/FJytMpjGPQAPvJLv/RL/7+fJL5RJ5568gDTcxmWo7Ozrli7kbJ3\nq0w4LNHpB3TVgIm36Cy8Q0N3PPJ6k6LTpVAVGLbOjFUn8026N2O2VgKGezGmbjG5MMXS8TpuXSGS\njFzOJj9VJkoEm90WlorwvC2wO4Ren06nR/tujN9UiMRi5eYWc9OzVCZ1dlv3KdQ1RNamXIlYOm5g\nGh3MXJ/aXIo+nSAjh8GWQA5KqIFOQeVp3h1SSiskWoCtNFr9XeJ+jCxbaI5DhEFvDaIuyIGDntqY\nSkcTAteFYdgn8jyK80VqE0UGoUZjJYR+Dm2oocUp7b09jjwWsDglGHQbrO3EOOkMwplhrHqAQm0M\nt1hAah47O6vc31zj7sUVAkMnGffpWzFDUtqxoLOqs3c3pmI5LBwuMVEekBcprtBoxgP8dgCOJI5C\nCpU680dOIJhn42LCC//VY/sVh1xtmtyUS2r1qAsT3x1Qs2fw9DKRWcbPxlhaPEi0Uefpj11j7MkZ\nJp4SfOsPv51u6PGH//1lrn2mj+pNcubRByiNS6y6h17tUZzqYNsNCqUBE7MetdmIwvgQuxDRU3vU\nj5TIzTgY5ZgDRys8dr7KzFzG9FhAxR7Slmv0EoOtmzbPfWyP6093OXL6CAPLo1jNGHMMrIrO7fs+\n68/1oWFQDQqoo4JLV+/g98BEkYUBkTckTTzCJCJJIQn7pFkLt6ih2x7VMRPb8dDzYOVjxg8VKE9D\nKCM8r086EPjLBr3nQ2atSd5x6kEeP3eCs+enieKQ5fvLBD7kvIinf+cC1cI0i2NLdDY6zM/NoizB\nmreMPzYgdyymON6nPh3xhrPT7MbrDHYiZuYWUHEJpzjBiVNnWVne4erlZcqTDvqEzsrqDrvbXXqt\nFEMXjNXz1CaLBGmA1xowbGp0dmD7tZjNewHHDh1getpC5lrYzgbhcJ2aGdHuOXzhc93/6bXiaPk4\nbm6co7bLseoBHnhijNPf/9ccedcqXgw7d22uX1qn9MAN3vLDm5hGk5RdTGuX+SPjBE4bNXUXfaaB\nJRJMHBw0uoHkytf32F0vYlfqnDm5hLa1RSk3QU7XKcchyeoG/f5FxheqOCWdpdPXOPHYdSaOShYP\nPcjE3BzrKwPy7hpvfF+DAw8OKRQjpNnCi7aQGuhajzTN47gOF18O6bTKGLbOMGgz6Em8bsL9S4rm\npQXuXAw599SXeM/35VkYK5PV9tDjMq89q+guHyDSd5g+4gFDcvoSQRSR0x06YUQmEwxtguOnEiaq\nJhoTKNHEyHK4U5t0Bhr3bvdYnDrBVmOFxo0pKrWbfPv7FWbtAkcXC5x51GTyUIOdVgEreSsX/2ZA\nOtDZuFbm6x9dYHHM5PiDOroIsGSNWA1QZkwvGBLHOWxlYdZWePpvYUZ7gLjtsLPsMbPwOPXFGZyF\nZ5H2gIMTP8+hByo4Ey/ilHso5WE6bZq3Zrn48ja9nYjd+wZ+G0RiUKxOst3p0+htUaxXMHQbkUHo\n+2QqxNBTTMcmTkfx9hIw9BSpGSgysjRBKR2payDV6MwXKwxdEvgDuoM2woROr8/SwiGWl++hjIip\niUV2N3vUKosYjkUnXEfpebbbt/C7PTK5QXN7m6I9iyDHTL1GbPTZWr2ErTISzUMTLWIZkpAR6z3i\ndJcoHBLHrREklxqZWSBK9yjXXfo9n15zDzODreUdIi/PtWuv4eSGDLoegR+yun6bVO0RJW3SuIHQ\n2nj+LgeOL3Lh1gsUa5OY7mHurV7F7/VIk4iV9h5TC/MooVBySK/bI059Mq2DVU7JlxRmLiHLQaIp\nNMdAN2ykoUjseKQsSWI0K8NyJWZOYJuCvGNjGDFSQXM3I94TJINpvKZDd6VKXs1xb/fO31sn/nEb\nDc1CaiN9P2oUGCqy0dTUMA3snI3jGlTKDropmarbZIS4RoSuZ5gCVKYwZIIpF1DsIdMyaTrA912k\nCLEtH1PPQQZJnBKF+56IFAxr1DTkcw5RqEgdQRj6uK6NSBNUymgKJTOkLXD7kl5PYzj0CGKIkUh0\nMhVjmha+51N3a8RZh1l3imbvDnOVKTw9YBgmBCoZ6fhNGwuBBwg1igwVgCH/DlaoMrk/Lc9QKh3F\n2yqFkhm6ZqGIqFRcNN0iy3Q0XVCpFInigGF/ACIlSwJafY/hsEEun6PRWKOx1+DzX/wMhXyFU2cW\nOH3mBAXnJCX7OPEwZq9zC8O5wnjtAEcPPMkrrz7DsSPnMPU7bDbv4GSHmZyuc795HVFocHf7C1jY\nbNzpoPwW1y+8yHt++EfJFSukaGjaiH6dqQFhZuKaZUDwgZ/5CaQNL11oEnb3+P3//GscmCqwNHMa\nqziFMAxKdpF2f5M47dLs7OBYLkEE5WIJlemUChUsp0yQxJRNm3IlRxY06fVha/0qe3trOLbJcBhz\nr7GFYxbw/QF+6HH3dptDBw+ztHiU1cyk1d6m220xOZOj1d5kbi6PUopCIc/Gzja6bmO7+5KpfbbJ\n6BpR3IXcT2vS5Ij7kQkSYoIoQpOCLGwyP71I1Ozh7XV55/g7WUtXufHa13hk7ClOzB3irP8tNKwX\n+En9/XiDmHeph/mc/2v864n3ciHsE4XXeeaVZfoTPuPpFNOlOq90vso/n34nf/PqF5lzj3N57SV2\nxJD1HYO48bfMV09iyJCilbLWTYjjEE23MMRIaibU6DsoQO3DBQWCVGUgBGn6/9VHCSFQ6Sh+Ovom\nbTRCzaMTK7zdHcaPnCBfrfHKnsHO3Q6abTJ1rsT8Q5CXO9iygywOGRvX8bI8918c4BEzM55n4U1j\nrN6Iee3VTZYv7qC0KrKiUfR0XNdgfMpEqCZLJ8dwchWWr6/R3ukwc7KAk1ccKbjU4iKtus2Vv+0w\nPi44/2SVCA9EjN+9Samg4++t0rrVpPaASRD2kXkXp5BQDG06VwyCOKaSs9GSkFMPFjmwVGWYmLx2\n6xbenRa5KYOy65L5Or1uhN/UcDKLQJOYpoaFwC265MccZCVEK6QMs5hISvKTGn7HZdhKGG7FqDTC\nquegN0Zzq4svDByVo5/oOOh0RMiQmDAKabU3iFKfIDVYXxX0/rjNY/4Uqp5g5yTDSJJ1XVQrY60f\nETQjBr7g6PkIp30PZm2q04vYeODnaaxmbNxPSAY2evYAO3urfP2vGrSjOf7Z0nG2gi7eIY/Ekawl\nfYyghmwVicbzpMNxvv6pp/nCrds8Zr8B76SP7PeQvs4rn7pDPpqiNuNQnXQZyG2E1aIwtk5hrk1d\nppiOxYQ1AY5Je5AQ9zVSx2VsxmbQD+ntZrQGW1zYuMdYrU99ZohtZIzlKkR2imXVmDUOcv3SfV77\nYg9jfZ3g7SF2mFE5PsO5N1VZ/niRzed0Xm21ODDzIDOVoyy92WDj7m0iP0Rr+RiOgyE0zLzA0nOE\n8QDdzkh1nShNESpDU0PkuE5+MiBODMKdPo5eI1e0SVybph6Ra+scyOcJtu7zbG+N9dYuWeIyX55B\ns6boZrts3szobWRY/UmSnsNr1y4jjuoo2WLueJmJqsFge4NW1sMQGZEyaPdMUmUTFxwu7Wyw0usy\n9sA8YydyeL7HxKzFxIEy6Z5g0EkpFhJmZm1qQZleX+PipSZqIEmaisNj08wU84SDATLbYi9rY5d9\nvKJCGt+chDpdahwtFph2q4wdC3jox1rkj97Ao0MvPMPuZgEnPsHMeJ373css1Q9QRuLTxDNDio88\nQzU5jyZvkEXzBIBnbtLcsAkGklqtglaHUF4kECGFsEc+PUp/JSLKBiwce5SwusmxJ1/gwEPrpIZP\noMbIyw0awfPs+iHe3UWad45hujZ6tUPMLsJqkWUCSQ5hCuK0T+wnXL7Q4s3vrtGOmkSRS9iweeUz\nDVirMWcEuM023VeeRDsGh2aexvi2FldflLz6isDLeZx4ZAw5vsMuAWXGUVoN02wjtHvk83lywxrb\nzx1Hn77G+OFpdlWG1A2Onu+weS/m5a9NcPmSywufvMX3f/cxotWQhcMnGQofpVaZPOTxph/dI91Z\n4sufWubyq0t0l49ycG6cEyf20AqvEasVUuEQRRPoRkochrQ3xtnrJqhikdlqDWtwk8p4idoh6IcN\n/h/e3ivYsuy+z/vWznufHG+O3bdz90xPT8YAGEQCMCkCNAWLkINkmaZcMi0VqSrywZRd5bIolSQb\nlk1VkaaYRYgACBCEMIAwBAYzAAZhUofpfLv75nRy2Hnvtf1wGjD9ZOKB2C/n4dyHE2qvu/5n/X7f\nt/81OPGuNYzyW7SSXyHYe4xy/oOI7DOo5R63Op+lvvw/cSZ5nCtvrpMMfFRRRs1nVJtzbLQPqdcX\nkdkQIX3icYhtaigIklghCiUSjyRN0TSdTFpkBKQyA9VAUwWKrk2IqEmKphkMwhG6Y0KmsbOzxeKM\nxf7mA2Zn15CKSq+zTb3SxDT7dMYjrHyecSdhafoM+3uvcbCxT7UyxeDwCmZxCseucLJxCXtxxDC6\nSxzdpVlScOxp+l2VIJRkWp40BqEndPtdmvVp9g/2qFVmOOwdUJ8rMOi2MNUcBVGgfXCX+myNntdm\ndqmEG1wmtSXTSy47g3Wk6TCMVjkaZ6QHPYzcNO3gCN/x8c0Ofr6BnS8S9Y44cm/T6u4xHg1BKmRR\nhOkYiFjB9z3MQEExQTElkhhTy9BNhaqioxg6mZOCyHAUgaEnKIYkUQLGcYxt25TrguFhDrfdQPg1\n7LjO0Pur/Qbxo3k0FAVFMZBZQpZNTN2qomLoOrmcRbHskC8YVEoqtqVQsjN0Q2CaOlkcImSMpkKa\nmmTpISItgjICUUEREYZpEfgeuq4ShRqKaqDpMDkrAE0ok0K2rhFFEYoqMC2DVIJwbJJEEgtBWUvJ\nspicZjAyFLqWwTgUuIEgigRWphO6UNOr2FLFHhhIO0HzbA6iDnahRJr4aA/JUrqqItIUXUSTUUXT\nUCeUVDIkaTohbglVQRUKaTbpsCRJhq5DFMQ4toqlpySRJAxT8gUbzx8wGo0mhfQsQWYJqqZhOUW6\n3R6FcpW5hRU2tvawnALfevUOm1t9FubXWV1eoladYqY+SxDV2N3qo5q7LM5d5P6Dm1QrdfqDBTy5\nzevbV1koLZIkdaqlBmpO57uXv8TU4SaWV+PffvKT/Ff/3T+iUK1M6FsqiMigvX+NL79yk0sXnuDS\nhRPc74/w90LG4Qae22F69jlUq0CtWiGIxgxGbXq9FkO3OzFqqyblYg7LKFMqFckVbDa371KfLnL3\n3rdwx13czohe1yOX10jlmCCMKDgNdNvBcQpoukZBWGzv7HH71m2a9WPkynUyVeD5PQaDDo5VwLF0\nPvTeD/DSN75JtdnE8zx0TSdLYgzDeNhnmPCMxQ+cfAKQyg+/P+WhyT5JIBUDRnsOPa3HTx77Cbp7\nr2IeLVBeO0XNnuGFwz/gfenTvCpVdsR30TK4qH0EM7jIdtLlbnKZ53PvpnbG4LdefxV/fgw3xwwK\n5/jn3mfJ1xaxnBauV6dm55BmhjlyOYq2URKD+wOVmmmSZQJdU0jjFEUINHUipJQPdS0/JE89vBQe\n4pqZvMG/HBVTf3C889d8WVWNwDzALEBOdLGtMs++7zgvbHUQquDkhRoF+wAr76L1xrDl0hYKdsGk\nlC+gDSJEziEhoVCxWVqosHPgMuzEHNxX0BtVUhnjbhwyNZdRckJSOURoh8yetGnMBdSViIZQyJ1O\ncIcaXbdHebZAyg5Fp8vcvOT+wRH3diXeGLZu9TGO59BCSZrTYSipKgYbvTHj7T7l+TlCNeDxZxuc\neNwi7xRo3pbcuObQanc42OjjKgG5ss7i3ByplxIcxnidhOZijdrcFJnTw9VdVIaM4gBFFAgDB0M0\nsBp14jBh2FERYsh+K6Zy3EFmCt1tnwfXN5DJGtKzid0Ud9TDDbvMLkDTKtHf1/n0pwZsPdjl0Q+c\nwimZSMVEpBNR26Dt0bvVJ1dukDttk9Z7rDQbaFkOdapErSL5jj/kzlffpmhfYO70WfL1RVY2fZK2\nxzf/7wHv+OijtG/exiqUGc7oNNVVtjKby/9kF+WOwXjf4qeefSfNJwyauTxH4w5Dq8jNF3d4vDDL\nI0/MkLM9zFKX8vQGZy6OyYdDnEKeQOrEMuHe9QO6bY8odgg9yfobm7gDnXgk0DWdci0m9GKGwzbm\nBwF4kAAAIABJREFUUoBhhnT264SDmHqzjri3hxPlufCu08yv7OLQws36zJ0/wd/5H5/ld37uNtf7\nLa780YCFf1ihUTcQTpPW7U0ikZHFAYZlY1kphvIwJStA0SwGYYipJPQ8DydU2Dgco4gIR9XQ3JD8\nGHoHHQqRgSJ96k+ewVqbY6Ufc/1IY3fH56uv3mOrb5KrGAzTlPVrt0hkjB4H3Nh/i5/9+FM0TtW5\ncev7xJUIJTE5urNJlC2hqTnu3DoiCPOEoUHkKeRXqzTWdIx6il1NKNby2HGGedLCbaUMu32OjnrY\nuTwNp8yzp2ts3ZFkyoCGUcLfHeDMhsi8zngUEmgJ3Vaf9W3jx7JWzEzNMKUYzDRKVE/skl97kZgK\nKjNU8hluSyNvxwzaKgVxAYUuMmlgqKvE2QhLCbAUCzWtoBhdepFP7AqOtg0279lMV1U++p+cQzP2\nuTXcIx6VmX38OPev98g5M4TFmPqFlNVnLhOwTZKsYoqMkXyLnDnDMLjB7dsKaljjyN/l0gdWJz8u\nKirj5AGGbgIqcZawtDTF+usKW7e3cKo2N6+OWX+lRDG6QL1ynmB4j+/+hxyBu8VHfrEATpnZlWO8\n7xMtrrxgMbh9kdufcVj+cEZxdYRuTuMmZRT1EIUmwg+5/EJMcnuDsWXwno+fQJ58CbIymgKLx2Ou\nvLbOYPs4VS3Pne+mPPPeKqPjV9CEhS0WiFzJ0ydU+mtfZvGRM/zmr3qcvPgJdre/SD8uYge1yf9/\n/RCpb+DjU6vX2bi/y/ZulTn/XYSuRevtQ37+Yx8g98FvEtjfYW8v5vbV+yhGhaP9Okr/EWr6FJvx\np7jw2IdpOvcYVR+gFSRrx87RL/bZ2thgHJS4sX6Ncq1Cqx1DmoM4QBcGSRoipSCNJ8oDQ3NQRYxm\n2iRRiiITNJhAW9IUiDAUDT1VSTNBoVTCiyOih73Go6MNKiWfG702p89cot8foakh6WbEYW/IydPH\nsawGRDoXn/kQn/v3v0EUbyOFjqGGaErE4tJZEn/AYyeOsZFp0NvjaH2MmhSxZB7VzGEWikShSj+8\nQZLcRsGlVn2adD9Pf0/gVE/RH+6gVyMKKylq+YCqkeGlu2TVmEjP8A2Jbus4mQfhOov1OTbuf416\ns8qg3+J9z/8tvvxlE6deZ/Nwg93+Dlk3xhYGvh9Rn84RBimGUkYGYFlF4uEQVQHbSHDyKpo26aWm\nBEg1BUtF1TLkJKCPISRZDkypQhCTZCkiqxIHJlZmo1oj4uDeX+k+/9HK4NmEvjSJY0xQTpquYFoG\nlmXgOAaFvE65lFG0NXIiQ7cFpibJbA0ZZwihoSgeJDOEcYc0qBLHIzypoXohBUclimJ0PUaNBab8\ngeVanYjzpCTNYlRNoMYZTs5EyyAwNDKhoUYhdizJ6waeH5DTQjQjI5+atMcp/ZEkkRIrmaa7vQ2l\nkOXCLL1xiwtLT3Hn8AF9d4Ce6ZjKBLcqs5QoCRGqipJlqMnDEq6QyIexFpmm8LAcj8iQWUJChsgC\n4lDBUCGVPrqu47kB+byFpppUyzXGrk8cS7zARQgFoarMLU4ThT5jL+Di48/zhS98ibmZGXa3urQP\n29y9eYu1Y6vMzC0y21yiOTNDljTZOXiLY4uPMBwPOHl6gY1thVe/9xKHuXsULAtyZzi9+jQ/+ZFf\n4MHtP2exVkFEI1oPbmNbJzEKFb73+n/kxc9+mze++Xmefv9PcuJjHyYdB9x44VN0tyJ+57P/EjcC\nu7ZAdcqkdbBBJlJG7j6eKygXligUSxSKJlEcYMiE9uENdjb6RInP229u4HsBGZLeYIxtVlm/f8Dq\n6hQoGpqax8wVMPQclWKZ9fW3yJKIY4ur1KdqtPot8oVZWvspRzsHzC3ahGGX3/zXv8FH/9OfZafV\nxjAMyMCybQLfh4elaSHEQ1P9hEolpUYcxSiaiq4KMhIUTaCrZYSSYI/hxu41NNvkUmGJsBvwO3d/\ni5+99A/43Y1/x4fTZ8iKT3Eifppr3m/SUaGVO8HO/ohPjz6Hu6HQXJjFHReZn89I4+tMD8oE2QbD\ncYCrBaiZT95rsCtSavYSUXLIY5rOgwx0VSVMJaqUZIpCkqSgCpJU/gD0RirTSTRKTGJ+4uEz4qFD\nJns4iMjsx9MGD50h8884zBQVSCq89dUBmw82uXX/gMffcYpSRaWkRmQbQ9xWm96tED9U0fOCen2a\n6UYJv6fgZiFOWWXuRJ3OSDLoj5mSRQZ7Y6SSYdZi1k7aaPEeJx+tsXhijtiR7KfrtAYxTnaEDDJo\nLFNbEqhCJcodcfycoDEdU4wt7NseN77f4d41F3+5yML8AuCjlaqk+wLpKjTKVQxdZ/ZMSvOpmK5+\nhUBaWPMO6t0AoyQ5d3yRcrOIZkjiICE8yLh31CGKQqJMoNqCVC9i13xUM0YfuZCkyBgcPYcwbHRd\ncjjuMM5SjgmH2Lbw+jphkuKPoHVrh0zp0lhYQqkpPP7cMqeeyTAtnyc+JphZu81LX9xl61bK6sl5\nIkNheDTkzo1N9u/u0yyp/MRPneT2a2NqS3nKBR2tMCQYtFFVi/lTkr//a2fRs1W+9/mYpJdx/vQK\njpT89v/+vzHcXuPm7uvMnGrw7Iffy7c3PT73T6+QH5V5/+lT/Lf/YI3ln1aIj+9Q0DSuJ1d449+k\ntIZdqoUCa6tFssUjKo/5zJyOWDFjQmOMK2B/HLL1nSGdns3e1ohh+4jeQBIPcpjmFOMDBXc4QC/H\nlGb3OPGuiLkCqCOfzmaL9o7JKFW5sHACocdcXMzRletIKWjpHom3x+IzH+KDP1Wn+7tv8/3L93nz\nNzo89YvzVFcyzLJFGvmkmWQ8GtEfTGh3xZwERSMD2sMAwhhhCUSi4XkG4xGcPtZkrl7A6JQ4VPeQ\nJShZOjLYJHEP0Zc0HnnuPOm3HiC+t8fljVs0K8uIOCSciZhesqmvaGSDFdSypNAwyNZdbr51SDFf\nQ/g2jqVRKZcYdyWBAgiJllcxLIHHiMjrodKhLCSzjoGa5JGKSZT5xJGC62XYIqagNRm1h2RkLJ2u\nM+iPGXpjlHGEPZPRnC2zuryMJ3zg6l/7WuEGY3L5MlrOxZnt4EZdHBPGgYqSzrOwUsb0awh/FXZX\nGWsvUy9V8JA4skwozyKThKK9SE9uYuoOUReuvHKPkvZRYnq4vML5px9QX5uiEP8cYbbOpWeavPmV\nu2TWq1x8pkgSbWPpVdLskEyGWEaRcZpx+sxT3Hv9+3z3+3/BO6Y+xObBOpWFPlE2JlMlh4MEoSd4\nQ5WEiK2tPo7W5NtfGNHaKpEXK1SXDjn34ReoF1Y5vDbP/Xu73H0r5ZEPRYS8zXMfmMI76nL9aJ5v\nf2HMUK/y7k8IvJxKlnmAw9gNyFsXyNd87LWzDBWwCh28eIpY25moBjKd1UdS7nzpHdSnr/KR/zph\n7dk2EQN05sikSqymJLjoosHmN11y2Rg//hRTzSJ/8Nu/wxMbDT76d09z6G1QsI8xcA8J0hFPPa0Q\npBbdG2dpP9AI+pvc3Pi3rHU2ya3G6LV1njk5y+atDGl+m6pyEm8nzyPmH+I4b3Lr/neYbla59s0W\njz4+z9XXrlAbLBF2KkwtlthtH/Dkk4/z4le+RL1cIJYJQegjFJssi6k3VaTwUeyUseujjkuIrAh+\n8DAanEKSougauq7hJwn+KMIwdQzLQSYpcZIjyLqoWkK7D72xIFc5xrifYJt5bl5/ien6SZaXT3Dt\nxg4Lxx6h075HkLnIoENWK3H1xrcgvsflrTc5/nSN29ePGO+W0bICQhUE4Rg/iVFxaNTmSEOPfM7g\nwc43GQUuiwsrOLUhffU25gKM/SFawSSUk9iS5WiEboJiOqgig0TBd136rS6ZrzEIPGzH5IUX/h1J\n3OS7b76MreeQKViqQpKMsYoRXhpSqGTY6gFqkkfNpkn6RfxknVLFwtQTNHOybzVzCrEiUXSBrk3w\nuJqukcQRapwihjZJ10YJDFK3gBrnSCKBy4BcvfBXus9/RGHfJCYlhCSVEkVJydBASVF10DUF2wnI\naQVMIySvT56b8MlBcSziyANZJFVdMlkhtMYoaR7diCa+gyRBagmB52Jb2mSwiBWEkiGyCE3TMFQd\nmSrIREGRTNwGpNg5lRQVkQp0w0QzBEoElVyVgzgDK6aRL3Crt4s99nDKNVJ/QKZYuP6QA9ehGw8w\nbBUZpyQSZJpMRG6GmPD6RYJARRIjE4HMBJnIUDWNBAlZiiQhySZm1iRJGfl96lWDLNEp5Oq4QczY\nA1NRsRyV5ZVFdF0jlkyGLHSSLCYMPXTLxLKKnDr5JL/3x7/L3mCbeqmGaVX4+ktvsLS0wdrpGjOz\nj9Bo1JmpX+DqjbcoFBySdkajPs3f+/i/QNFUBp6HKlJGbheiHsKqoGo2Xq/PF//sM1S/kUc1Vdav\n32X5+BlW/s7HGe+mfPKXf5nl1UsMBuvUGzn2drf4W3/7v0RNp9ANE8XocP3mNaZrKyzNnWR2ukkU\n+vT7B7R61znqdbi3fo/9gyOGPR/HsrGMHGkWo6iC2DHIF0octsYsLh1DNQvMNZbpdtt4nse1aze5\ncPEJnHwJzx+TygiZGhhOiaZlMxgOeO4d7+Tzf/YFTp1Y5fKda8zPrOG6LqkiEcrE+6IokxML+RAD\nm5GhaSpZlqKICe5Wykn8DWnQS9fR1VU2o+v8+sl/ya++/nv8o4vnGeQ/yqvX/5DzMyXueg+42b7J\njv19XKVC3LX4anibObOIajhMGxG90QZ6lnJz16FoZLSFh67VyKcadengaxGGHZOLy7jDDZxCgzdd\nn5oikIqKzgQjnDHxn2QPAVKKIiZG+of9DCEEiZw4XQSgMnm/PyBT/ZBB/dd8jdQeie/Tu9ZBPX3E\n/Ikn6ZwxaE4VUIIu3/r0TU71h8yfGNGoVDjwO2w+8Kk0dU6fneLEsQpXvn2PYbeN0ZhBL+tU9gU3\nv36AY2noOxG5RcmJmRrt8SFlo825soUsWVwOPLqthCdmBVVRooqgG5k011SGHUlSGLJypojGTZxM\npTClUJ+e4f7tmN4NhZ3IptCZZvC2grFjcPDSkEtnG4jQozGtsh+vo6YeaaqSdops7W1h1UuUpk38\neESwPyZLBKbtUF8oMSBhFEnWdwdo5RQpfXLFkM4gQw48goGD1U2Ij3zinmDnQR+3NsKsOwxHA/bu\njWndTxineXYOUkRUpNBokJ/JOPWeInV9gwKHHDshePJfPUnx1B1e+KNdKsUTvO9n3kNqwsl3PuDB\nlTu8/fV1vvDpOyxf1Fg6aXPg5yjUYjQtYqYYsbyaZ7og2LrWwbIVTp09RbPQ4PD+Ns+feZR3v/sR\npjZsbt7o8vLndmndCrBHVWaTVQ43PPqdDodeAq0Og2WLza8PufHVQ57JnebcOyrMHjeYfn+J4qJN\nksHlwT4P7mTsX5Ncea2NEUKiVJBBl1IlR7NWwJlaIXGbqMU83XaAKIxYOLfEyec9ZLpHx/Xp3xuh\nIVg4UcevCmJtE4Vpyp0IxS6iKQaRnUcb+lwdvk6pIqhWA4JSyNuvvEZtt8DUVAlNbRAmAbEXE6UZ\n+apC6hj4Ska/O8RTUgoFByefI/ESBr0c/rjPgy2BWQkwowE4XeqP1SlYPt/beZVsEFJt+9Tbh7z4\npcvULi7RaUXsHq0zTBKmlouMF4okto+0Jd969RqbowqKMo9SKOHFKgYqvSDG7XYYSQV0k0q5Sprp\nBHEEaki1qFOZL2NZEVri049c4ixFKRYJOwlprJCS0B0csn6wz1T9JNqUzsLsDLsbXYwpi/NPzjI7\nnSHaOm/k2z+WtWIw6pPYgoQ+pSmBJvIkxOh6iWGYYDeP07ldov3aEbUZixMffJZxcRtFPKAtPDyl\nSai9TInnsJRp+gRs3Nygdd8gHQgqDY9TlwRLqybqaolW8kfMqgX8nRZy6jqNBY8kJ3GMGglDMtUi\nEi5x1sFWFczqA0ytyHDYpT2+gVWoMvT6pCJinAhc3yBxI1LfQjU1ylWTr/6xx1xjBbOfx5y5zf/w\nz6D5aIDKJl//Y5/b9/vsvjnNM4++A3vhiEF2RHFuyOyju4QbF7nx8nU++IE1XGfElO5yFCe8+VqR\nhanznHl2EUO9ztbgFcT0HHkxTzc7IlV0DGyMchtPvsjJiwuceuR5Bt4mothlmKkUlBq22cbI8uzt\nP8ubN77FpSdXWXvmOiJt8Gd/eJYXP9djeskjMiTt9AZnHikgFI2BG0E74Oor9zGSZ5H6bb764uuM\nRY6Zp+Y4/zfmublxixPPnGQu7hGlv0936ypvfLOIujmiNDfk1u1PU115Am3+KtO9MhvX3qJZ+C/o\nHLbRjAzdTOil28waZxgEY2IZkbPzWFpCsRLRWPZRnITtnYTOAwfhVwnJME1lQhVNI6SAOJ0wQc1M\nQUk0VMsgFoLY6DAOM9SogO2GLJ322OtfZmPdZq1+kiySzJSP8eB+C8dKadYW0fUARY3YvHefarnA\naBRQ1mcIegUWao/x+t461VKd/jDGNB3CSJCmOYrNKm5/gIxiSlWLUi4hn0QEyjZxNGR1zWEw9LFt\nA1ULcYyMYhmEEqPmFbIgQmYJvgA7r+K3JTLOkUXTGEqMm2wRSIt6dZH+4QhFVZFRl0oT7LqGNS0p\n5i3oZ0TtHMPDBBWVslXAVGNUESPJMGwFVIEO6FmKlglEmhAbkiyXIjqC8T0LWqfQ4ya2ZxN7Coo5\nJMx20Ivdv9J9/iMNGgkJShKjIsmyZEIAED6K2kRXUzRzhK3WMOwOhsij6QkyVdEfyut0A8hsNCHx\n/RRND0kxkJmPIlVkGIGjIOOEQrFI7IeEqsA2i0RxjJMzieIIRRj4oY+mm2RRRm3WwR0KzEjimBHj\ncR9Kku5AUp86wb07NzhWs5Gpy5uX+yy772Fr+Fka1SX29ru49TqWY3K1d4eq0EmjDIFCIh8WpAE9\nEwhFR2YQJiFZJlGEiq5apMSkiiSTCX7iA5I4jhAKZFmC6owxnAK1RgOZuFRqZdJshNQi4qSJplbJ\npIIifHIFQOap5lQ0XWU4GhKGIc+/82mef8+H+OyX/pzPfPr/4ur9tzl7+iK77Tab32hxfOkFFhfW\nmJq6S7NxmtCVqKqFO5bE2V3iqEO96uCHYBk18vYJVD3PysoqjrVFLpdjf2+XvGqxdvYCo/GIsJXQ\nPDbPmaeeZNjtMrP6KNcvX+fkmROEwYiZ423evnqf3f0pnnz2J3DULgE3+carX2TncIe7d+/hDfPc\n2exiGILlxTWOnV3DNgWFnEkmI0xVxQvGaLpBLpenkK8yMzNLPA4p5QQvv/IyQrM5feop5lYWaXUO\nqdfn8L2IXFFDiIjzF8/y6T/9E/7Xf/bruD40y9PEUfowCpWiGSZRGE824EJMBsA0mXQz0hihTIaP\njAyhqEhsbG1MLjpNVh+Qay/wS9/9x3zmnf8LH/vGr/FLJ3+BN2f+c17e+DcomcbM8hK7mw6F0iZ6\ncYamGuIfSXx7Cy82KOtFEiVHoyiJpUYNgZpmREpIXwknJC4fUFOs/DRpHDJj6ARSoihMcqji4YmE\n8oPTiknf6Qejww9ACamYDE+CyRCCAtnDP3rIQvtrv0oVixOzNguzOTpYbDkBhVmN889WUaKYxPSp\nZD6NQsrUjMo1K6G2nMfIW7TcFu2re3TGLeyKhmEXaG/EnHxkjnCsc+fNPRaP55i9uEjJioj9EKc6\nJuWQQRITDBV2bsJMPaNIj7EC+/ciNG2FWAQEaYtb+0MKUrJWEsgATi2l1Jtr7F6bp33TZrBXxr2e\nsP6GxNyskdXzZEqPOAuJZBvDEXh9jf2thMSw0HQdb+STqR6aGuPGITICo1pnSptm0JN09vqEA0mh\nFJNMK2SRgtszsEIbJRRooUHe1ulu9qgvJRw/Z7CbbuGctWgYGlVLRTufp9fX6I23KFVKuJ0QfWqD\npgxAzVAzg1/4+RNYdo3f+6cv8+DuPu/62QucfqbJ6TOPc/6ZKb735cvc/v4bhCOdcUfl7KNLzJ8p\nEkUB+x2NnZtHPLjcIwnqVJZUdIbE+Q5PfmQBfR4+8NgzPPp8xNf/9ACrUmHpdImSaDK91sVaOiJO\n9ui2fLKWQfuawXgn4bHzCxQrGb34Pjl3QH+9z612l5f+OOPu5YzeaMC5Y1WOv3OGmakyK+d15mol\nhMjhHc2wfUVw8y0fx/IoLjRYejTCUQ+R5hBUBb8OtRNVtP06rhGQlSBIAtyqTU2bpj0KsUKTT/72\n7/EXr7/FJ37pAxy7VMDON9jey3F/fcTOjQhT1SADTTFwSjrFeh7Vjuh3OoShwMjnUGKL2MvR348Y\ndzQSqRMXdAZuREmMed/PnKVWcPji5+7QGtrMFCocHSo8uN+j3qyj1C3igkf5gkHegBiXcdCiO5Jk\nqso4EcR3fcoVG0s3kJmk648o5FJkXWFhMU8qNYZ9l/37e6iKjpa5JIlGMB6hpiZ9YZG0DHTdRs0s\nonCEbhv0+j7DToha0SkvG3TGfQ5CSar4VBoKBUsSDffwxyntwejHslZITPycIAzbOHXo6CUawiIa\nnWDcylO3Z0lLJZq1IVE2oGEvkbWLKHmdqrBweynd0Ke87GBkCboc09rS6dwrszxTZ/ncfZZPx7jc\nwc9aqFoHP7XRF2ZoXtrn9Kk6ZjEBSsRJCGpKlnpEWoeW9JH9gGJxBtNe4mh/l72NFC9/iFLy6R6Z\n2HaK6ymErobrtRgrECbnEekCp2t9zj16hnJ+h0O3RSXvU3uiQ/ktFfdAZ+NreYrv65NbCHnymQHz\nl7b51u8PGXxV43t/cp1H/rP3cCPa4v4bKne/l8N59g7r6jWKK4cUi0cM6TBkRFNUuNY+wClKOvfL\nWPoaG9/a5ZM3P8PpJ2wuvPMpmu9UiXgVlR79eJmx3uGjf/ODLCz1SMWXEQT85N9r8PVPneHzfyBx\nxPNceP5JDgyfw/ZXmG0o1IwCZW0bdZwQ15dRzA/yF1/4LrM3LILwCo3zOte/PkDYi9RWDxHmZQql\n59AG/4RcJyQ8+APWVn4anT9BkV0K9jLd/buEpNh1+MznfovHls9x9cFdmrUyWaJRyHS0dIQUHkbD\nIi57rDoKWgLtTQs1jhgkA0xdxdQNQjfGVs0JPl84BGGCbSpIQlRVJ4498nqdob/HyamA+VMVjKRL\n2PHQZJkobdE+PKI2PQ2yyVRpkf2jB5CMeLBxC3coaCcq5akpOm89YL44T6cPolxkMPSwsiqZlqDI\nLk4toDLtMb2qo2glIpHQmG5y794dUDwaWp7haIyeGvhS4ORVbM1BjkyCOCYIEipmmf1egpHkydSM\nzA4YpxphUkLIDGmaqGEXRRuRa4Q01ySl+Qi9kmHbE7F1d6+NWc4oGzn0QoSoSUTJJCXCMAV5KyPn\nmGQinvSKNUjVlFgDu56RTMWMWxrxeIYoCsnVxshwzNKcRjzj/5Xu8x+tDC4nNeiMhzENITA0C03z\nyLBRpIGqHpIFBYySB1kRy5yYlw0tAwk5SycIA3RVAdVCKDGh1EjThDQTjF1Js1ljNIpwHAvfT1C1\ngHzZJgkTNMUiQ0fXVECgmxGBr4DeQ1clqm6RUUPKjKYyYjDepDZb4o1vB2y/PYXf7dDJf5a7/SGN\nWkytvsBGPOIoCnBUCxELUkVFUyYuCIVJ2TaTCWkakakSTVVJJi5wIsUniuPJ608SwshH0R5uBhFk\nqQqJzurcMU6srOIPewReB8PI4Q1VTHvE3sF1ao0ZHKeCQoEsl9Ibe1RrFYTQ0BRJ62gLVdvnp99z\nifc/81t86lNf4NOf/zOmp6YozGSEgxXuRlu0Orcplbc4tnQaNdVo9Xw006DoTNE6EgR+wLGTDlfe\nfokPvu8TtFoHlKpNUpkwt3yMVEaMBwGnTj6CYmVEYUToDYliF9/3cKMxMigj0jzt3RpTtQJnnzzg\nha/8H9y80mJ7O8ILYrzYoVRcoDnv8A9//meo1muUKxVmZufotrrkLIeh2wM9JYoihJSMxi6RH+L5\nASJps7mxw+5+m0uX3svC8gKh71Mul/B9F03RcH2PkyeXuPb22/zKr/7POOUZUCPQVFIZougCkanE\nUTKhMqUp4iG9DECmk+8WIQFlMlRmKooS4SZFzNIW+sEyXdHm7Nx5Pvbar/GvL/5j/rT7HfK0+fsn\n/3sGkeQz93+XWlPhcOSTy4YkQlJ2HFLVwMg5mF6GbsbIRENRJDITyIelbiV9SIhSJ68piQOEEPhS\n/rBTIR5SpbLs/7XQ87CfIeD/09EQWYZM5Q+RvYZhkCTJQ4fIj2fQKGpV0qzLUXjE/Thl66rGg9tl\ndu5pXDo9xcpTazzxE0OmV3eJlJh3v2eKEQX6RxoHnX2icMTCSoFiqYjsJRwcBHgdg7mlOomvMez0\neHDNY3/XZeECzK2ZqLmQGc0mqRTozvRJhypKQ2CjU0hLJLpJbEtmF4vMTatM0UVkVRxniBqk2CUb\n93pG75U64dtV+usQBS7ThoPSViidaFCreASVBcZhj844ozfOEEYRf6wyHiVkRkgU+rhBTBapOEad\nqm4QBwGxq6GpLq6SESspml5AT1RkKIiGAZaa0N316KU7/Dd/9wyP1QPOopNFOp2Sy87xIsWiyuGu\nQesoQQYBR3eGxPEIZjrkGFDIOgRilQ/87VMYg3k+88nvs/HVG8zPJIhZndUn65x57gnSZIXX/vwl\ntq70ePk/Xqf+dpGT5+eYbkzRO0zZvDvGymz2x0c4ekRaC8jNaYzyQwb+ESLVqJwySFJJVvGQHFD7\nkMbMOZ2h7pP2hrS6Bv5+nVxaYKHaRJEBN27e4QtX3kKth1SaFvXlGS48NsvsyiLN6TpOSbBQLxPK\ndW5u7HF4x6W9cZ/xQYle22Jrs0PRdygtVxB6iD1lYlgKjdkSvpujdWXAxkYXbzDk9U2D/OIqQ7VI\nsin45it3+NqfvcEvf+YCP/nEHCoHbHY7HPYDcjmHsGuSuTY6AmElWKZJ4oX0u/3JyauioiQrcXtW\nAAAgAElEQVQp3YMx7tjD9zVQLEqVMoZMCMYjppckpUWfUgXGeo+NgyMOHyQsNadQHYOZhSaduE+t\nZpCficjNSdyhS27f59BMCX0dkxxJatA5AKkkFMoKqSoZ4mFaBk7Fws4XEHpI0VcwUXBKFpVqhmYo\nuEOPXitDDCS6ZkI4wgsi8lWIY9ALCosnCuh2yuHuIaErmJrSyWspR9uHRMYOcc6gaNo/lrWiXp1n\nb3yHxy/lkaaPNpjljZcESjBFSb+IadkcmN/gXZ/IUV7ZwhAdXvr0K2j9Nc49+wjS6LN5WUOezKgc\nv8/Y8/E6BvX6k2T5iDNP55DamEGi42gxCg2SVEeoAXNnHqDmDxlJE1WUyTBIpQKqRoRO78Bj/2oO\nK1yhPquzfWedy18zUWc07CVBJAL8gYGhq/jtMf3NBtGGwoXjJyknFu+a+3mU4IDv/OlX+NCvFEmy\ny1yYdxiefIQrL2a8dG2DZy/lmV5YQ7dymNYW4Xsd7r55j7vXH4XP94jCVbq7AZcuecyduIdTPcJ3\nI3aVPTQ9ZdY6RygFzVqLw4M8euu97DzoU/RrOPYc+9+6wMF3Yx69GXDqMZVe8YCeKimUrrK43GPk\nPiCXO4k/GLOwdoXcqQNm0o9y/vgZ3v9zVYbZZb7yQo0//+wWhfFTtG83OLcSceapDvvy/+TJ976D\n117Oc+tbl3j581UahQqrT3eploqMo7ssrCp881PfY+/wJT7+M7/Il/7Dd7hxZ5eCMs9hy6FYLpL5\nA+5tb7C6sMaVjRssNlYJogBNUQlGEboTgZIRZz45vYjbCRkceMgoJEtjDN1CkJIlAksz0eXEfYNm\nEBkauqHgRSmJJ0njCm42pl6sMtzskPZ8VponWe96aJbkoHeNVidFdcaMvSNsp4ydt1hcOs7h3gYF\nB3rjHsPePtXl57h89TZmKc/+notKShj71GZzhFmHldNdSot7TC+sYBhN+qMSg7HL1MoJTCvFG+yQ\nAsHhIoX0PHn3AN9NSUIbt60Seimhmifqdkj8PnlHQzVaxKEAfxpP2Ua3tsgv+pQbJsW6ZOaESaGq\nMs48VMtH0T2aDRDnBLocY/omoyxE6lCoKRTzGqgZSqYghYYQGaoKhpZNPtOahqKNkMoGh1cs6BSw\nDAXb0pldLRA3NeD/X+75o5XBAVDIshSVCalHURNkmkNkKaoSoWUlFGVCk0KLcaw8qkjRBHi+i5Ob\nuBTQNEjlxHFhKKTpZCOlmyad9hGNWo0gdHH0PKDiex6lvDlxH2SCTBEgQlI1wTElMi5iGQXGA49C\nQ8V1e/hZie27db744m3euLbJe86dYbi1i1Y6xtqxIW4qGIUeaZJgGiZk2cSqrKgP0aEZIlMmcZVM\nkAk5IU5pQCaJk5AwDIniEMREjKboYhLHkRlh7GMbVcgi3v/u53HHQwJ/DAqopMSZRBV1RjG4w3XM\nvMpUs4jBPKqYDCmqkgNdJ0xDMi/g6OAQNxrykb/xBB/8qXfw+7//R1x56w572Qt4PUGtUmFlWSNN\nN1lbPYapTJEzmyhZQM4yODraJ+cUKReW0AyLbn/MuQvnuHz5LSqNOrpiMpWvoKlwcNhmenYGmaYU\nRY0wMMnb0yytaDSbCu3os2y9abP7aUliX2DXfRMKY86dWuGxiydYmi1Tr8zSOuogRcDu3g06vfsE\nbkS10sA0HESqMhoMqVaq5CwoOBadTpfu4B6X37rG8spZjq+dotZs0BsOMDODar3J3vYOzWad8XjI\nr/+zf0GpWmUYmdi5PHESIpTkYVtBRdP0CQJPTDbmk37NRHInswRVqKiqQAiFVKYkkQAtgN4caf0+\nqrfGle1r/MKj7+Nf3fgM7zj9JJv3Sqzr/573a+/jsbVLbOx4ONo9UqlStKfwhimqZZBEHooDSWwy\nEczrZKQPsbuT+JZMsx/2KuCh4fsvFbl/8PiDgSIDhCp+aAP/y0PID5waaZqi6zpRNIkbJj8m4hTA\nznrI9290yJkeclhEuHXi3QRbA91OIfToH+yDdpeoPGB26ThHBCiLAflgTNhKKRRUDu8NuHV1l+6e\nRU4WKVRtllcr7Gkavc4ucajizuZ48J0+8kKCnnNJlRhF19h9O8atmFipgnuksr0VMR5HNBdVwHg4\nvIUEmYNr++ys99l4K8/omyW83QoFtUmzmFGreUT6IUMPrl8L0ROJJywGRxm9YYapTHjvo3aKVlQx\nrDI5RzCMNLoHPm9ffxtL2hQLOaSU2GgYhQpZ6DH2JGYiUdUMkYbsbd1iadbgne84jievoosikRZT\nUAQrsyr2kw652wWk8Bn2XdrbEil1LL9CNmXRCQOiOCQ8GPHYmTOI5x1uXbtPcEcggxgqLbLZHpds\nwdmfXuTgAw6vfq3P7XWTcDDPrU2FcFxAz+Yp5EpEicIoGtI47jB/0cIuRyiqQfdgxIxuYDZTxsMh\n7dYG0bTJ0tMFGtE895JDrnxD5VbXZ7jjUnre4dSzNeZnFPzLQzwZ8N73nWF5dYFhOyKKFTwUtvYH\nfPv6ZfzhLkXLpqDZzJxqkEzb1GcNanOCTr/L0XYLQ/EZDKFYskmGU+TNKq/fe8DlNzc4+zenif15\nursleocJnZbPt//0Bu/8+BQfOJ+jG30D27jKXqgi9UvQ1xDDHIpnoecVFDtFU1SGh30SM6ZSNLCK\nCjoaPT/Cc0OKjs3YF7TWx3glF2U5Qug67c4+UObR5xrEw4jWd0I23x5y7Pwc7jDBy0u8uZD8TMK0\n8EjCPvcrR5QUB79cxd30kK6GauTJUPHkBO2c2RKnYqLkUgK/S66gc+JMDiNfQEl9VOljWwWMAKxG\nETfN6B/F7O93cDSJY9jkopRUB6kUicKQfgscq0Ctkac72GRnf0x5XpBrKIy6P54TjemKRX93QECI\noeps31DY+l4TTVHQzW2Co5hu9iL6/BrV+S6Dwwir3EHRTBTnAqOjiP2rPfybq8yf+VlitcX6qy+B\n4VFuWFSr07x96/vEis/UvErZGSEoMY5DNEvHDTUsvYAkISVBUS2ibEh/kHD3Khjt52hOT3HiuTxf\n/LzCd17a4PgTDhVVpTBbYBQNGN3XGe2qrH8/wRr8FJ2dFhfOXyCNXsO2i9SmBfGghiZO073iwAOH\naWeFvfV7jF9tMKqUyM1rjNN9Lpy9z52fENz/0h6tBwuMw30e+dCQd37MQAoH5AyB2Ge7Xefyyw7G\n+SKJ8z20apGvfdFF306oVXp89Bc0+gf7hK0cgWdy+9sZt766QGSc4tGPRvw/vL1pkGXpWef3e89+\nz92XvLkvVZW1r91dXeq9W621LYEsIcEAA4zBnggGiIGZwPbgwBHjD8SAHWaGxfZgTDAYCQYhgSW0\ndUutbvW+1dpVlUvlUrnn3dezn/P6Q1a3sL8wRAw6nzJuRuan+554nve//E5/5iw9vo2ZUokDQToz\nRiy3uPjBFJf9W6zuO/SCMeLUd3nsyXGWL/fYXrEolMYZxqtMjv4wo3MdookXac9arL/0qxTtCvPV\nc/R7v8mVlxcYHftvuH5rn8cePcbV743z2pv/jov3PYnTOsfdzTozx09x5fKbnDp3lNadBnv1HUbz\nYwxdD0WCKhMyGZNA87ErJl7s4OxL/N2IpG+hJAl2OkssIgbDLqaqYasaieehqyaKgMgPiOIAVYkp\naCkiK8VQ2SIKxtm4PkPWHKBrMTPlWRrOLnoCmnKwBJQmD9MZ7KHGOtKJGSnkcQe3OHHYYLm7j2e1\nUacVmjc7lIqHUaVPOlVBNeuYU20On7SYO/M5sulz1Dv7SKVBcbLGwJMYSgUlex97g4id0MIMJkh2\njtKt7VBv9nEHW9gpEz3VR1cU7MwIqvBRgip+30dJrTM7Z1Ccc0kVVYRwsfMamuWRWAkFM4NUBWHo\nkLIltqbhewEyHVHQTZIkJJ1PKBZiBkFEGEsM5WDRUITE1hUszWSoRWTGJXqyi7s9SaeRBpkiDECI\ngET3/5PO+d8zowGQ3FM1QNESZGShWSHIFEKaCNVBjUsgQ4SMSRIfRRMoqoqVMpAyAQGapty7vT3w\nxyMEEQk6IZqpMhj2yeUyhKHDoJ9QKKcJoxBL14niAMtSUXQdRagYyjie20FX+4hcE6c/ysbiHEvX\nHf7gS1+gOD7HuZkj7G5tYcxMEgwT+t0WjUigWCYpoZEkKkKTeLYBcUISRYRRQCIEqqqgqTpCi/CC\ngMDxcUMPKWKkiED5fvBWEQecDT90EQjcZJcHz59AyBbLy1dJREgiJaEfkjFtgsRlfLTK1OQx0toc\nnR0F1AV0w6ZXrzE2NUexOorjBwh8MsUMSTjP1tY2STTgH336M/zKz4/x3Buvsbq4yde//m0WXl1g\nJCu5dGmPD1y6SNqAVtsnjEew7TL1ehtVBYSg2WwRJzEj1SqV6hiImK2NFdKlDLt7W0RxyJnTZ+l1\nejT3IkJ6jJVO8PxzL7K0ssdIZZbf/J9/jmzuELXaT1Hb6dJq7tLu1KjvhiwvfZdy8TDdXp1coUjg\nR4yMTjBSLGNZFr7nkkQRtmlR39/DTgk6jW1W1pdIZ4qcPP0A88dP0mq3yeby9AYDnMGAdMbGGfa4\nu7HHcy+/zVixiqbrJPG9235AHggVKOIA9KMgURSBRBx8D+V7TqSEOOGAPIwCmsCUZYb5GnQy5PUN\nJqoP8we3rvDY9BTttVscnjhHNX6GP938GuN2lV9+4Ef4vbWvETXv4rV84lxEouXQRYqeZ2CpHkiB\nUBKE1JAyQggVku+rLFIISA5qat9TKt5XX+79nNyrk/7beYv3COGK8n0ooZQc1Pi+9zfv/f8fwONt\npwjrsyj5CZKeRWupgGgXOXlymlwpBvrsbtUI9RbSGFLM1an7C+QsybyVITszwgt3lnjtjTaBO8Kh\nU4+gtzLcfXeHQUeHjEq/JtFiSUY5SuxZrL/rM3KfQ66cZbRQ5KW3Frj2zpCRySKjYxYiq5C0BCvX\nhoxMuozMw7t7WdJjHRaXYPP5iJ1X04RbIRmRxYoNxu08lWMRw4Jko13HWY4ZdhISQyeQCXpsomo6\nvhuw3z9oINJykkgYBL7K/lYfIzSwSzb5UpFstQJpl6HfwJEaUkCggWY6DHp9WtoGY+dDBu4Otugz\npMsgcsjqGTw/wQ4yjOQKyJEC690OUc+nEQc4PUjfhd2NADl0EUEXq7OH6Zcw4pjVqzFjwibK+FRk\nxJ2jO9jGXYycwD7dx78e89LbK8wZHyDrzmHoJg1tiDruEOVcprIKnWCHTqtHoaSgZ0OqZYuJ82l8\nV7Cx0aPh7RIF42hGkWN6nuhRm43vRLTzCqURi8lDWeyLhxhODXjuS9f4vd9/npPVGY4dO4ZuZugF\nB+UZNTeNEBVkxqWdtCiUXLKZCSbL45THC6SXBHvLDTwlTdovESgZ/MEoi8+3ePaVGzxx/0N89MlL\npGWL5s0aw67LOy/dJoqyPPNjx0iZA2yxQRtoxSb9hoLn6iiBhnR0UjkD24Bes01rb5/MuE56NE0u\nA7m0Rj6vgIB2PUaEOdLZGDObIpd3kHqCV+izFu6iFSpc+OgZHCXPtb/aZf3FAdZcQvqwzuH5CuNl\nD9V0KU0VsBWFraHC9o6GP2ITGGna3RgpVIRU0CxB4Pfp9gOE4xG6MaZlkWgahnSIw5hg6OE1fex0\njtgN8YROtxtQnshz9HiJmRmBpXs4Qcid2zG3rzbY2zEp5g06dQuFgKQo6fcSfOEzUhoHOv/wLwsn\nxdjoNKLwAt7+FLtXjqI7p9jbX0Gxh9i6xpGzeQ4darM4+Dqjo2c4+qFpcuZJsmmF1rt7jIyNUb+m\n0txcZL/j4/j3MX/4ITZrL7F5M0RuWGQmC8zP3YcfXqZiZIiCDq47xM6quMkOKBJNzRHJkKHXJpaC\nXOosc2cfpTC3gTb7XZ7U0nz+3wX0901SIy5HL0RcviK4cznhxosJWu0RKkaJmYmInb19rIJLduRp\n5qYex4jWqa0f5/XPO7CVYm2tRvbwDNeeFTgrGmd+us/4qftwcfjUj2X4Zv0wnRsFcrM3OPlRA0kL\nH4coisgZISNWRMGMee7LEefuf4LSmU0yRpfnXv8WP/ljOk/+6INoquDdG29R3w84LD7Czed90v4p\nuK4QXNxiu1pnxhRk8UmUDRo0yVkX6Tc6dGsGr37L49AJhfXFd5nNP0bfnqCcmiJXCPnOK5cpNSb5\n+M8dJXr8D+k1/pS15z9L39pi9j6DN27qfO1L/5EL53+Cl5/bYNhKePJjn6Xh/O+kjUkePfcM12+3\nEFrE9cW3aLQapFIC3x+SS1Xxwz6K3iW2uxQmFbSxGKlJhCYojGVo7gdYQUISaASqhqkdzIdaysRS\nLdyBS8ZKoasKQRyArqOJNC4GXlKBJItUI2SiIgINkbicmB0nMQ3cwTrtlo8f3SFXmCAMBCW7iq5H\n3H/fPH1vmZmZk1BoMnYGbJEmE+WxyOE6JYbhGsfvc0hPb5GqTBKSxWntMD03z/rGCjMT09AdJ3am\nyBbmCcw3Ue0+24sG23f3cIIahILQ8xg1KxiGjdv3CVFw/StkcylUq8jImE9hPCE15WOYEMkAqUh0\nNY2ZUpHSwx/GZHTIaAqxqtM3Q/BVpJ5gZw+I6yDRNdBNiSoESI0k1nCSCE3LULB84rTAtTXqgO8m\nxF7AsOdiTWeB7t95zP+eikaMTGIQycGqkSQgPaLIIol9wigh8HIkeYdQprA0SRjHaIpAMTTSlo0f\nxGhJhExAU/QDhLx60AAk0QhCCGMPI53GdV2SxMQyckS+wEk8hKqiGRJDr6CSIg4NfH0bIxUx6OTZ\nuP0Ur73c4dbCIs+/+0VmJkvoXhtHy0LaIhUI9s0eIhJ4oY+SSHQsAkJ0XyXSPLQQTEsFoSIVCHwf\nN3DxhgOQ4sDPLyRCHAx4iTwIEot7ADWhSpCCtJ2m0YdMegIRFYjiMl13yI1rNwmGLrlClmq1zO72\nDm++vcj4eJmJyRLT4xeYmDRIEpdW8y61/S1cP2RsbJoEBVOLOX/+GCox+7sNdleaPHzfB7jv9CGe\n+eSDbK70ePbZl3nppdf41rf/kh/+2DxPPv5BJqdTZK0xJiaPcfvdLXb3V7AzKk6/i6lDc3+V6sgk\nKUMhSSRxFLKxsUKlkiL0AkxNZbRS5NXbtzGNMrmyy8LmbZ765L/kZz55kTNHp8mVRpibPsy5Cw9i\n2GkazQ9iC4c40cmXcgfZHCMh9CSu38IumJRGxmnUGxTzRRrNTZZXbjD0FC5e/ADT0/OUR0eJEp/h\nIMA0LFRFxQt95o8c4hf/+S+hAGaqRCBDZByjoKAKEz8JDvgkyXu0bPG+9ShJYt6ruk2S+P1BXlEU\nNHT6xg7pII9CTKTYbHWuUUpNstho0I8Mfoq7tNoNfuup3+DLV/+Q53Yuc945SXTuflp3btCwVtne\naaCmDRKrQOj5CNMkHVsEIkYkOokckqCjJRFC11FjiVQUZJx8P1dxT8VQ/j+tWRww+fi+ovG3lxJ5\nL+z+nnXK9310Xf9bLJF/2EeTKv6GzUrYxApM9rZC4kEKqzKHr2+SWDp2sUycr4Ots+532JdDCgjy\nIkRKl/K8x9OcwOcw7oZNfd9DGDGpjEq2UsIuqWwsbPLWt3d4MMxQOXOS8piNKnw6sYuSH0OPNE4+\nfpq8nUY9kqG11Mdf6ePf7OGNSs6PWry7dJu3/zTke79VYyw8xoQiOTxlc+bsJC11l63BCpqhEikQ\nxjmUvk5+wmDg9ek6PULPYawgyeRtMlkVNZUCTafb1ynnIaNXyOg2nhcSxiHxwEXqOokKoRqBjAhK\nIfnUgDPjKYb1IV/9y9eZOBPSrAk2FnyMnkU1LRmZFAeyeZTHHo6Q0SS6PiDY3iHMhaQSDydUiYd5\nmrshw5UAbzNHsxmheUX8nRbpTgEzH1AdlVjS4akL45gJ1H9zwH/44kvoYo1P5J7i4Y+MYIzHxEcl\nSb6BmQrJZUPGSjqhcMnYCZbwiHEpjG9x6+oatbhJThZxhEpve5rx0Sr5ksXt1X38lx22F9fRJ0JE\nVSHfyvPat5e4+nydan6cVLmKh2D+2DTjDx1GaHXKR7tMpXWypkpAiNMx0ZU8d15qstvWmDo7hh7l\nWbvc5Tufv0nOHOXxT15gcryM2UgI6n06awMW393m0Y8dAV3Bcx36Ro+rW7DyWpbeHcGgAZojsBQN\nYoiBfEZn5OI8iTJkOOzj97oMcwEz02OcP11mZTFhazWhH0HWtGg1B2jqkJ3eHhoeSl9B67WZmznB\nqbOjrN/YImuD2+1SW+wTRQGZKUn+Uh6cABoBUeBTypTY70X0+wOEphNi4LoSQzXxfA+Rlog4JqV4\nlCsphOUThiquIxm0XLxMir1GC1MroqUsJo7kSOUl9U4bO90lM5Ji9vw47XbI6mWHbh3W113OXSow\ne/EEhXSX/V6dpSs/GEVj4kSX+Q8sUTzhsl6v0RkojKbnGTt9gtX9OhlTJUFnY/8uMu2w679GpjKF\no7aJeJVkrM3sh6bY3iqyfiUkXcxy5IxOurpPcvsId99WKFWfRo3/nM3OVxgbybLnBUTbR7j+zhjn\nHjaJUgsoaR1faCSKIBiaaIbJkfsqjIZ38EtXQNykcMwgdyhNvT8g17JZfTXk1vcka5fzmIOzPHb/\nR1HMZ0llfWKvQNK5QFO7wkCZJNv4CKs3XuHOTY1xtUS61KBBwM5yB22vyYai87lf1FCmTHRaGIfb\nGHeqdOpL7N8uUrhoYOMRGD6NSMHMprj0SJVbr21x7W+OciYok+7Pc3JmgnPn9oiMNpoMOXIhxQPy\nAdae66G5Nt3dHeo16Os7nPnpI8i5dWQskGISiw6ra/tc/67JeOUon//dL/Hg/P3I3oe5tbDL6fsm\nSJfylEfLPPpUntff/R1uXm0xesrmxIe/is1xvv7vv8tDiY5gnicuPEj1UEzuyLMMdz/Ly3+dYvbw\nD1O78wV64hRqmCDVGq1+n2LJptdtUs2O4Q2HCCvEznsURwXZQyphyackdPpmwEheMBhI2gtdtGQM\nJZUC3WTY7TAMfcyUjTIUhEFA4kWomkroRCgpA0QX/BQOCaHWJYgzjNoZIs1ASRXp9QcIw0YXPv3a\nHkYQ4/oxmWkYOF36aoPyURV7KoNfrJEOVhkvxOR6VZJhhe27kwRej8rsAK0c0HLWUY0AIzWGpczj\n7zvYxjG2lpsIN42peuiuzV6/w/L2ItLoYIWSRAE7NUKn5VEadZg4UkfVBty+0UbXDpM1HsRStpme\ntrBmdojVAYEMORhrhpi6ThLF2BaYpoZpJGhmCqWn4SPRjBDVOLho11wTQ4+J5QChmBjqCJAlUfdJ\n2Vn8RophuE+s64xXNVJqGuka2JaCIlL8Z180DoDDB8yBmAhTUUlkiBCSKFZxHB+vkBDGBl4wRDgK\n2DGmadPt97DTKfwgxNRN4gBUzQWhICMVoavomkoUJijSwPcUVEshChWGQw+pgioV0kI7aHsKPPrD\nAKfXZ6d2mt1Vn3ev11m5+xe03S12OzUUO8XGnscnTl6k3+jTjIbcFS16rSZhNsWIlSIQGv0opJtS\nGB0GpLBItATHGRBFPlES3rsBV0CPkFI9qFOTB6Rm4oPlS9M1lHuVv4oE1+uRMgziuMcHn36cH/no\nR+kOPk5z6JFJ5Xn39jLf/NbXWV68ShR0GCmX2dmJcAeCpaUX8PwBlaLG3Owk1VKVqeok3d06qp1H\nWmPc3LlLrASMT0wxdvwwWRU63SxzI0XmJwdc+sB9tLs/yxuv3uLt19/kj//DtygVFGZnKjz00JOU\ny6P4XplipkyzWcMduEipsLn6OmfPn6LR6HDm+Hm+9o2v8FJvj5FKCRnCRn0bQ/WYms7wqZ/61/y3\nv/7PmctVubG4RaM9oFTZZXT0LpoCI6VxyqUSQekQU5OzDF1JoVQgjkNyJUkYmnR6A6JEI1+doec5\nrL67Q33g8sTFJzl98iLV6iTKPeXFMg/scXbGpra7w+LSAq9fW+H08aNs7XikbBeR6MgIYqGhKgax\njEhkgoLy/rAexfH37UjyQE3TtAPVI0ki3CQmFWjolstA1TBUFZkqIsyAoCPRsw1e2CgRj1i88O1/\ngVQSHh5/im/3/5J/fPcQTzz0M/zONz/PqbMfY+vdF5HCO6COe5Kh5WFEBqEIEVEWXYuIVQ3ph0hD\nRRcCqavEYXSgjokDA1icJO9nNRKZkETy/dzFe8tGHMfvqxqJTNDVA8vUezkNTf3BQLgEkl5rj6Gz\nh6vr+L0su3sDSkVJefYQQ9GiH1QJGiGddo29vR2yD6p0J2w2en32+yGWJshPh2wu11m6tYXrpLGL\nRZSxCK/XR9OhOgHrCz2WroeElkH8rAezfbJGFtPPMnJ2BCMl0HMxZilkqjuHu2DT+LrP9/6qRXFG\ncOVNk7VXXIxAcObMRQ6fGCGbdVDHljlzNM3qi1vcbbTxRIht5fCDgI4TYGR7FLMRR89XGK2a6KKD\naWroOZPO0EDZh1h6JKIDVkyn02Aw9IlkRD6n0ZcJvaHL/sClYnnc/8lxHnwgw8rKHr//a2tsfEly\nerYM7WN4azbLTpqcaVIybCqVKrkxk249JD9RQiko6KaHJpqoOjT6A7bWGrgbJoOajSsTwp0+46fy\niK5CYydg6v6A6smAqUmDhx44zrE/usinzpX48u8vsrfX5I3nNzmRN3jgx8vopTSm2qC/28fvG/Q8\nB0dsMjZnMhaCTO+wMCpZeLXJ+DkblDLRTprEEfhS5Y1vLlA5/BC6nyd3HJ752AjhU0P2Lta5/fKQ\nQQPSapasZxDfMeklBoc+Ms3MdJnRaEBRD/BJ6GYUGtdUNDOLKtK01iwuf/caK1tdiocNPvWZJ0jP\n+Fh+ncbuGt3rm7z91htYXp/pS6fwwjY79gheK6B9Uyc1mCYUVYxynvRIGbfrMQx7+H2XnB1w6NAE\nSspka88j9lSypRQyJwm8gPworC4M6O8OsI1xzJ5AGcliUCV0hnRqCa0766zVVczaKHoKuEIAACAA\nSURBVM1hj0OT8ygZm5srNdbe2eHM4zp9kaN6apotb50HSuPsBhGb17cYMQUDP0F3Yux0moyZQo8k\npZSGHzUwY4ekHeGLIV6/iDtU0YwShfIoQRzSqIe4YZ9uS8NQE0w1RBPQ3glJFJ9EUzlzYYblyx02\n111+6CdOkKnGpMyErDsk0n8grwpOfbLO+U/qNDt5snmPDx/ZoH7lzxmsnGbltV3MbIaZrMXOxgzp\nWQ2R3aXteshUA8IuoW+TqWxxN6zhVo7yX/3ySc49tUvD/Wu+9cc52PpxXnk2YD6qcuJTGXxfZfVV\nj+61c+zdznOk6pJ9IEditVETCwvIFbaJkahqj1B8g4QmLqDmIu5/OuG5v/B459t5othif9/gWOmz\nHDo8xdHzNzj3YR9hCHbXNZbfukYx+xjrt1pYqRa7d2wOT88yodmYkcFge5+huMNicpijdw+zdWeP\n85Ob9MUi9z9ZYSm+ysaf2bz5HzVwmxRPWWjFWVJqGxWBl9ni8Y/2+Orv7qB950muLu+Q9mNuXDEI\njCrnL1j4NOis7fLyv4dj5X/GvnA5Wgm5/fU6x86MocyBo93GIUVv32Thmyaz6VN8/GdOMv3Oz/Gt\nP3wWQ91lJHOWfGqam6+1mTtr0JiDj396ntXoC1iZMqeyFSzt91i++nOI+FOs3f0rnnrsGEfPbTDz\n5B5f/cqv8/TnvkRvZZpR+xphENKNuwy6ffJpGHRD8pkJhk4b1Ughsh3KR2FkSoW8IDEldi7B1kFV\nYqbvN9CDkOFdj2CYwvd9UAPaXkIUh+TSOZIowLZ0VKnjSIdIuGTNFIai0Bj20YpF7FQBNZUnMz7H\nRr1Js94ipeUZyYNV0dndXSdJXDr7glCtoWuTFKfByS+Ducf8vIC+h+ws0F05TKi1sUugGgP0qICt\nHEEJz1O7a/Ly7Q2W33RZ1VcRQUgka2h2iOMpTI6dQ53T2drtExd8SBTKFRstVWD6hEf5cB0/thnq\nZ6j4l8hnD2FPJZTKCloBBoM9bC1BKhHDKMGKK2iaRWLXiLQWfqQjZExG07CNHIlRINJ3yWQgUSrE\nkYOp64QkGGYCUUgcp4kGEiPW0d1j6LKMaqbQIh1dn8LSVKJwG9j7O8/532vRSOIYqYYk0kchIU4E\nqjRxvAihJmStNEFP4mtDcmWFJNYQiUbQH4KICByJ0HSiwCWJYgy9gi8b6FpIHMZIVwHFIpT7JFJi\nRBUUYRLIiIzUMGKd9i7E0malk+bOcszetsHS0jcZOC6o0A2HtIcukaWB6/PYkfv51tYVPp47zHrk\n0uh0KNhpvNDBjRX6apOyGCdwm/hhkUjrgJMQKSExEaGSoJsWnh+iBDG6oR5UocqYODoY7BTVQCDv\nVaPGxFKSzxcYuh7FTI4/+aP/jR/94Y/Qb4b0e0PatX1mqhq/8os/Sb//Y2zc7XPt2k1efedZOoNF\nYsdkanqarbbHyk6NfmcBTVfJpRVSlsf0zBi2bXNk5hjtnQWQEdlsGitlsbetUq0eIW0XsUyVH/+h\nh/nMM49SHZlm4AWoQnDlymvIOMFKeey113D3NULPZ2f/RaqFU9y+1mBu/kFCAScvHOOvvvT7PPrA\nOW7c2OPJ8xf43eevMTMZ8pGkzX/3T/8H/vX/+lskSY7RiTybG21qux1GR0vs7fdJpbJMT7QYtjtM\nT0/Rb0eoqRipZgklmFaFw1NF3n79ezQ2llm+coPHH3uQuVOPMn5ojlwhQ7/vUijm8BwNVQ9YvLbA\n+ESBX/+ffoO0laLWirD0GKRxwDbRQBEHzBUVSIQgEQc8FBkfDO5CESSJgiIiFEW7p3CAqqooSkIk\nJcQKCiGxn2ArBmokUDNpItmnZ62Qadv87KXPIhsRFTPP/dO/yJeD6/zR136Nf3LhR0nqOidOfIDX\nundodpZJCkW0WgBpgeKb6Kk9nCSHOexjZkroXsIw8Q4yJUikqiKTg3YsRZEkCQd2L1UHeRDAUu5l\nMg64IN+3UME9NUQIoiQGRRAEP5icxqkHsnz6s+M019Z45w1BZ9ujG3S5dmOFkeOHUc00e3sa7qZC\nvakQGyOMzlexRjW25HWcdJ+ZYh6FESbOlPCHu+wvDJg5UqacS+jsRtTuDti/49Ld87BTWY4VzqH1\nJNWWSr1bY2RfZWrU5FI0Tt7PIetZFjYl9dcnuPNNjZutDiMImlQZyDaX0hPc98gc9rSLX15COwTR\noTTNWwv4kUrgCUQQk3gaStmjlE0zcUhgploIvUeq4JKe9Gi0bVo1jVpPZ5jETM2MoyYB+nCAkCEq\nCkk+gxkmGFGMGvlUx3SY2qdKntH5/5JHv5iwvnaZq9/VqaQe46UvbrP4vTZ3t12uiS1Y61ARs1w8\nMkf6ko0dauTyA6ZP5zGmFBJDJ/EFdjvN3tsuq6/7vPhX29y8ssjWzZDKpZCd7ZDiSsDoOQ9tuIW3\nmwbtBP/05x4hK1Ostd+kM7aE5vVQZI1evEuj3WflRZ+eP+Tc03MUCfCMDiNS49go3Lgt+eaftShZ\nRYYdlZUbA8yczv56n6/+8RVOf6hKWIo5frJIYSpg1lI5NF3i6vMOdxf2aW+UibJlBt2A6lyR1nSI\nPasjZJdEBCxt7PLVr+yBP8EgNFm6tkig9Dl/yeaZz5xn/LyKW++gKF3sdp+1nauMT8JP/o8fYvL+\nLM9dvsvSawGtbR21M0E0zIGn02u3ibIKqioplhJUM0FLHVTBZqSGlooxsgpqNcCjhes3iQybdEHQ\n7gSo+GStNEooiDs+hqVQnrGpTE+x+WrC7aU1utLj4anjfPjjH8b5Ukzn1Q4jnOfyF3ZQrR5D32bi\nvz7EZNzi1ESInjLZ2e9Q3wlIOgG+qeLGMaZvkWAjMwKrokKQEPrZg0KBlMWgZZB4kmFrSCptYBsa\ncRDhDGOchkO+WqDTbkG/wsh0gYI5ydtvXWbQc7AIiBUXX4nRlR9Qpmv0Wwz0aewKpCsBpcE4t1em\nuPzNDknQZW9Ho/liwuFLMxy9UKQvE5qNNsM9CLsavbsai28KhgP47M+XOfexHWLlbSbsKT7w+GH+\n6De/QmX8KRqbEf7yJ+iHHVZfadK/nef4yeOUx26Ryjh0RYKqDklknSBxkUlIu78DWkSiJiReFiUJ\nGR3VsS2o92xa6xrTpQ8Q1Hvoo2/xwU/qjF26S5CkUTJ90pWA3loewodYX0rxQx/7Ma5878tYqk+5\nLZmLWwSegWnFSLdO6LYQoo8gy2gmRXvOoDJaob5a4Y2/yTC9W2LknCQ7tkopdwhXvIM5E+EVOnz3\nhQYT1WO4bovn/u2Q5BOnSJwWFx5+iFs3bpBXivhuSBK7qDjo2pD95j4TcYdEFagiZPGtMXZr43z8\nc49y7ImbpC/9Nlr+LM9/4RFWa3Xc619mYuQ0idanvnGW+K2jTDzwo/T9LxKEp6lMXeOX/81Fmkuz\nlN8o0Y/+gnTpCE6/yKGzi3z5dz7HtP8LGFqFzc0tqJiMHT7DwuY1zHSOut8nnU4RuyGThRRWwSdM\nJei6cgCnjS0yqQDDsrDHY5JjPnXHpT3MIMKIbCFNlIKw5yBUSFs2RqIgIwUij4xIIQMQYUxKKoSe\nR2y4BGaGgefhxyCFfnDOhEa+WKZ4PEerto2lZzEKecYnqyT2NcJ0DXtUQzgqYTdHs2YThxUKoy4i\n6xE6Fv2Nizj1k6wvruM1XPyOTjldwR8MafVbuFEPoUfYRpkk1yAZ7pA2+lTHy0SKoDyhIwuLzF+s\nMDr7BJvrHSbrbVbffpnKVIXDJ+ZQDI2wo5OKx0lRYejs0t+MkVYJw+pRnEkRoBAoPpEISNQcuikw\nlTESKbEHKWKpEEuFEBVLs9AjG+maRGEVpzdEGej07lbZXnSgP4pulQicEMUy8NsJcPXvPOZ/v9Yp\nFUhiFA7sQ0kUo+sahqEikLieR7cHKUNF02Kytk0vHmBqKpoicIMI07SwUmlCVIJokyTIYxo5bMtD\n2nX8YAjRJEnsEeEiEpB+nk4/wXVs9jYN7q7EbGwt0u5t4kWb5M1TxFLFcRyaw10i1SeOFTQ7zfqw\nwUNGldu6h9kV3JedZTlp0OumyNgWqhQMwha+8Klkhmy6Hex8hV7Lw1ZNtDhEBC4FE4aqipCS9wwo\nmnaAvJckcO+G/P2a0TjGskykFrO+uc2//e3f5hd+6VfIZHMYmk59d5tb794mk9UplSz+0eee4qf/\n8Q+xcXeD1a1lVu6s0kk18T2XuekKMgnY2KyxV1dZ39yiP+wR+a9jpSzSWQNT5EilNUxTYqcNEgJm\nZkcZH51EEVmqlQnavR7Hjk3zvVee44EHj3Cy/PMkZcGVnWep5i+yuuJyffhVCtlJPuD1OXnycYzA\n5KHTH2Hhyg3MjMJf/D+vkIiAy2+1aX5ij0NH5vhffuNf8S/+5X/P6lrE6ZOHSYIBe7VtDNVANWs4\n/Sb77XUGw0cYm85gOYcw0rsYokSzdpuoM8rC4k2++8Y3ePqHn+HI4Y8zO22RzmTxeh6dwS7pYIyI\nBin9OKqhUqs32NjYIGVaCOQ9XsSBRSpOJImQB/W29zJB7936H9iLDqB9qqoQJypSKkgOBnNVVQEF\nTQhQJIrUDoLjMjpQ3ghR5Dn6kct+uM/vvfInoIM0JKMZ+LT9GGPHP8FfL7zEWNVFbsd8sPAQ8dHH\neefaF1maMBgZBgxTQ7rOcfJWnaA8j2x3qGc08pFB34ghkmRQiYUEKQ/O2z371wHg/KC+VlG+b5eS\nUhJF0fvWqfcWkPcWD1X7wSgaA63HysYq2aJP9UKVuWGGxTcEcb3PneUtpk5rCLK43QqNbQe7UiBY\nq7JJnXJ2luJ4BxmZxGoXNxZMzDu0vDr24R6xkIxXBZWjecYmNEIp2bnSpnc7YqI4TuctwWt/eZ20\nHTH9aRsx7dJ1XaJWgzf/IMdgYZ6t1lH2ZUILl3HhMCLajE8V6AdNQu8Os8f6nHu6yFsr19DH+oyO\nFBjWY5yWRxRASk2Ry5loRoRlO2hGk9zYHq3uADdVZSAz1DoKgRuSCyRaFOMpAiVnkMQGQ8fB9WDY\n9UlHCt5Q4jAgiHex9AX8UGdy7iSt4z55y+SjP/sAj/wXZfavRWzd6HH1pV3WZJs/WXmVyp2E09MK\nj3zMZly3KKpdlOqQ4iGw5gwO3WeReziFNV/lna8ZvPraTZZf6TIzVNBWI+zXfXxvB6fepzTcYL64\nzcRYjoa1SjLYY7sLHzqZ5+pqj/r+gG98YZ/125Kf61VJF2ZpZGuYlkPHt5HtIuvXNHZEmaJq024O\nmDl+iBPzp3jxK6/T2RxiLnssfHOPk4+GVA8FFCp5lEKF7IslXuo0WbpWQ8dAGcQ4bYnyWYfBZMDO\n3U2uPNskM1ZhZHqWm9/ZJS54PPmJWZ78mSrjYw69zjp+qNLZGBJYMer0gNMP5jh/MWFAhDtUuXVF\nIrdGyGljmEYKTTXRNBXHDzh6MsvoRJooTugHA8KBz8CW+FEfxXbI5XSQAWYevOUhh+8vcvLcSTZX\nWgwaQ4b9BFX3Kc7qFIom/WEfdbzIoY+OIV14N1zn8v+1wMIrC9w/P8vh/AlsbRTNGqUe3GXliz1c\nw+PQo9M88tg8i1sb3HxtnY2tAe39BDQTaabQCypRKHFCnXanRxAruF0Vaak4tguaTko3yJgWoZNg\nBeAOTEaKFQabAfVmn0xunHLBpNXzyWQSVm8vU5oPcUSLONtANX8wkkakaZgcwxD7GGKBzr7F+rtr\nGPEDKJpO4NVJ6xVK+SxCu4IIt1Bci4WX6gS1NJs3BZdfzPDMTz7AIx+20ZXLuDQocj+VUZ/pWY/V\nl9+lt7vO9e9CMVvFXT6KEgaMnL5NfqpNIlxU2UJigjBQVImf+HhJH29YJDY1wo5g2IzYuuOxfs0m\n4z7NkXOzOE6P0NklOxfhVmtssowlDMbOHGHqTIhfe4WFFwTtoU1HLvHkL2zRCSJuflXj5pUrGOpJ\nArfFvtfHTBSgjyln8Nlh2LfwI4PEf4TmSgsje4f7H34cvXCdkGWa9QypimDqYoHlt5YY0c+jzpW4\nWTd5828W2VtMKP6zSaJwnDg9z7Deouu+iyM9SrMeE6c9av0aGQO0dANpZTn10TRHH13A5TrV1BHG\njjXY1/+cB87+Maa7xCd+pMzAcnnnu/83x5SP06zBhU+do6d38TTB9eHPow3+DU9/+Dw9f5Uw/VUi\nJ0eldJTTj4Tc+UpIL0lhlj08w2B+7D563Q69QYe0YSH9GEvYKLJHHOsMwyFFoZHRNAzdhyRiMIgh\nSghVnVDTSBllFLtEpAYEio6vQuwFxFISxgoiTmHrRYzwvebFAF1oOGFANOiio9LtSfAU0oqBVIFM\nikjRUCKJIjMUU1UUt87d11aYyklSxXG8/R5akqfZMyEdkS+tYog0ne4xVt+aorufJaxFDPfzlM0i\nitcmkF12+g20jInjhWSNDClhcnvhDUYmEh56+BD5sTyipFIeLZGbrZKYPaRSIB+YPFE+z8TIHfKF\nACObo9/P0W9kibpVsnadlHqSaBH6ikLAPpZXQ6nqaCMOobaLJEFJJ4jAIBpM4TlFIidFfkxF1WoH\nNPZOAr6BcI4S7Lqovkr39iy12ytYyi5h2sFxfMxuTNf7T8tx/b0WjTgMEKoBIkZTDxpz4sAnRKKm\nFQISXEVj6B4M3wo+rhSkNIGuHVDEQSMRbVA7WMyg2h66qpHEgjgpkFJsPOMOgeMh4hkSv8JOvcLa\nis365jbt3jKu30LTbQx1BE15kHrnLnbOoBPs4kv3ACKIBlKw095lZuI0TqPPVDrL0OuR001Ozoyy\nsHWLij3DDpIRdYzbgx2q2gytrVukzNyBh81UcNwEPxEYqvb+UnHQRHVgvVGEAnzfIw8HtpYkjolj\nnZ4ref3NNzj5ra9z36VH2djrcGT2DKX8LAN3k1Zrk+tXXyCTziNQOHd6kocfPE2CjtOPqTfbhEGC\noul0B20GwzbNZouNzS2Wlm6zs7+CrSoM4ghdxPjbMZcuPMpI/ijT1Vkq5UlyxSKTU/OEYQ8ZlHjx\nxW8wN/MS3/j2n/A3X36Hh596k6c+8hH++ktvs7rmEMQvUWttkNY0dnfqNDpd2nXJMG6SqkyQ7Ad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ZC0pRFtrxA2HY5uKbQ2O+CXKbmz1NvrSDMgVkOOun3Gq3OosYEcQcF0kcGQs6eXEKSUJ8Y4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\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IcB9tgSNtCWiKxTg7xMgvsNm9gWFNUZ7x2BqM6XV7VKaKWNKYZLXoGjITaIZGlogJJewn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\nkwQ45gRjgcbxbzFxI+DJA+S5BFgKXKmqf1DVh4kb/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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb754607588>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . . \n",
+      "Iteration: 20\n",
+      "Weight Adj. for Content: 2.63e-11, Style: 1.09e-27, Denoise: 1.30e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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gbEb0nTo/+oNjTNpDBRO6C3Uuv7DKtVc7JNdP6D41IpNTemc38TzHNLfUYsfW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HKeJRQmx/dHFMdj8qMZ83enqC64CooMdBFRTHoE7lW2V2+xsvFNeus3SfLHDIcFV14JWb9+wNnR\nCU8+e8Ro9iZPn+9z97Pv81/8l5vszv57fvc/fQ0xg3f/ouLTd0/4rf/gkI7/Id3hN1mUz9D8HU0h\nuX57ip//Nt7wCs8+/gYPf/gmT9Q9rLPBMt2FYUVzuY45yHj7tRTWzliWGVFD8s1/4wYd3+XP//iM\nhx9e5bOf/pT2YIW1/g3C6Cqrl7/OynDO6heOWF2mfP+7Y27e/H0efPR9Wt//Ka/2ApLGAUVpWN/o\ncW6arG60OPYhdCL8eETUXOP1N3+Le3d9Dsb/Gxv353jNmMYll0h1GZ2fcHVli4bToNq7zcHzNyme\n3UNtvIc4iuh5KxTLLmqrB+GQUn+P5UKjKahK8AvDwUOHs0+u4qxEZPIOQbegzDX7hzlZEVBka/jN\nHYRN6O0c0drR6JWUKZ8Qs6TUEY5s4Id9suKAd/8y5exvct7+dwa8dfsan+UhyeQNDvYTzvbvMmy+\nhVUOpThEdWcY/xCYE9sKbSVZPiXP/n7j2P+w0SltyQpBltva8J1UzOYV86xiNs5YzGLKtMRUFa6j\nXqBs63ENa+tgd73qULlwJDU4qu5gWFtvhIwxv7Q1S1EXHlJYDBVGSpJCs3AMvTDATwtKKUAbKgvC\n2vpkGYsrFa6UWFFL74QjcCpo4zArC1whSKqaVe159UYPa0mTmDBs1xhV10F4Hqm2dLt9iiwjSTJ6\nnTYn43N6zSZY8D0PX1hsWaB1HTot0xI3cDG6wjiyzlmICl8FuL56QWRyoLIkSQwsMaVBurWsLi8L\nSlNRakvUiDDW0Agj5vMZUaNBURY0Wy2ksuQzjRAOutCUVQG4WBTKsWRpjBQeuirw3JoIZSqHvMjx\nfJ9G1GCxXKCnmt7KECEEYRQihEOW5RhdF4nxNCVQBckip91uoooCVeSUYsnp46vcvnaZND5AqTah\nE9FoOBS5i3AtGIlQGmldfL9EC0MY1jmLNK7q620sSZ6htEaLisgECKFQbi1lVLJ+Da3IZzab0GqE\n5GmOUk6N0JUeukyRQqH8OmhNoXACgXQk1oCllij+gkzlOw6l1oS+T15pPFfVnYXQJ8s0jUZEVdXC\nw0JkWKdWNprc0ohCjK5wlYvn+lgDRhcEvo/WBZURWOtSGoPrei8KA41xJZ6RlK4LjsVKgeu5+L5P\nFPiUui5ATZXVI1QOeK5EOQ5CuFhTURZ18SqEwFQGSx1cVw7ooia61bLAX4wV1uSsX8W6fHMHXYyZ\nPLMcv2fRieL80GFxNGf92hWOHsH4bE5+x+fsQ0nSLegNJZ50SdIJpQjoXm6y9dWLpME5p3v36K7l\nXH+1zeaWX5u7GyHimkeSJ4wPR0QrHr0rDQJHkBcppp3gTy2i8ihnhrW3rtCz56hWRcKCRSpYTDXJ\nfEHLbeJpTb/vEmw28RspH5yd4VUhczcjzfs4YUXgGPzQYBeKqnSZPimZHCzwreXSusvewQi17lJ6\nMZ/e2eflcI2Nm9vE8xH77xZYYajKgvF0n8tvdmjfcGG1ieISh58cEc8Ej/9yTqj6rBkXd+GxnJ0h\nBpogzChSBSmUZULQD5gcHOC0Y/rra3ieh7u1ziefHTE5nSFFhOuErF5QJOoUHZyg1YzkWBCaddrh\nCmsX19m/k3N8/oDC9Vi/ukJqY05ORhw/LLn6Up+TA8vxcYVNuiSxIp4ItLLoZUIyt6xEDtYrKEWM\nUCWVI/DbDeRKj9O9QzqlIj7NOPlswZXmKhV1N/H2d7b45NkBExcyT7M0grSCIJPoRcX90zuM53PW\nL/d4/dZbPP6pw/5sj+efjKl2L3D7m5vc+cMRJyqneb3i+HCJ23RoH3UxpwOWixGTY8H8aEnjwgpO\nJ8LzHVYugPBizpfHuB2X2bRkvbyCPx8QdF2efrSkWoKvuzhjWDy0LGWJkynuLM6RVZd0kpAVJb7v\nE/YcVBBSnwFrykxCOMJe0Lz8jT737x5Qns8o15ZsBS3KdZ+GOqeaSMpjyWlW8uNXczZySdv3SUce\n8d6M0Ovw2Q/3UOFl+t0tkmnGhx8/5Mr66zQySZJPmK/HiA1JtN4G47IvmjCpYSuq7TISI1gqpKvo\nr7uMdnPODxJcofCqEFE1cGjgyZjdu8f09TGDSBMvx5iVwa/kWVF4HzHc+Daf/yRhtn/Cz3/UQzX6\ntJtNItVh/dI6Z8szLAu+/O1tnMF7rOws8IIRMxJiHlOZNp7dQlFhxAFK1PuLROYoArT2CSlITUXo\nBHjxBT7+6Skf/+mIZuJz/nRCaed4UZew0aWsOjTdjHh0QGUmOLqijGNmWYFpNHhw9ozbrQ4bdpO3\nr11jf7HBuHcDowpMqLBxjCzAqwKC8BIFH5NFj4FdlklFMbfEaUVZNSmWLxxHlWByWvDxh2POnlhC\nG9MdNqjQnBwsWD57RJn4NJKvs33pt9m5dBHZ/Jytr+xy7YunzGJJ4h0g05wD8xk4DRJzzHiaUi4V\njomxRpFWBVGocN2QJMnJM4Fym1R5gakSGu46nqrIZMrhmSFshHidlxiuvkpZaSyafrCJChOKStLa\nvsCgd5HWqsAJFSlHNNsLbr2xz+WbU2T/A7qvn+JeDgimv8df/NnP+dJLv066eIbrjbjQ6VCu7/JP\nmi/xJ/9jm6ODQ8KLUyLnCcYcU9iyzoI1/pz+Vx/zlTc9Lr37VX78B5vMZorDkwm9xjfZuSo5On9K\n9sFz3vinuzQIwdtBGI+d1w+ZT3M678zgtEGxeIsLawGvf/nrpHOH5ckRm71Ntq908cUjLjzd5aOD\njPHekvvvbPPyVy6R2vfQvq4PWeyEaGPA7mhEnFxkJaq49dUzVm//jM7Obb7/t0PSP/2Uq4drvPSd\njIuvzfCiVRKb8eD5fT76RHD8eMK7PzvE75RMxkDRZLgyJPDPUK7Bkx3CaEZuI3AS3FxTLiQnu4LT\nOwWvt1aYOnP2Pyi597Gi2Y7QakouA7y1x9j+T9DdhJk4Q+klvg1pqDYWwah6jNaGa2+/TkOOmQY5\nl2884Ms7Ac8faLz3vkDv4RXivS66eEa7uUKkQvKkjxudkxZTPHkBnBgpa6XC/9v6BxUaZVGRliVp\nBYu0ZJ7CZF4SJ4LZLCNLK2wFSv4/v621vDh5rT+X1IQfKlljT6WktjvXM+d1ELyCX/RDBLWBvLLg\nRBilWJaaRiCRSByh6xGrymCkqtGktsJzHHQJpahdEVHgEhLg24plUWIrTSWcFzzlqkaYet4vcaKu\no0jyAsf1SDA4RtOIQtI0IV3GrPQHOFVJqQ1pkiFDD9dxcVVNqfJ8Qak1ojL4jsJajbQS6TksFkuE\nkGBASkWj2SSNY/r9DuPZnGarhdaahlIUtqQoChphiC0rXOGQJ7Wsr0hTiiLF8yKyrB7p8X0fKVyM\nMSTJEs93iJMlvX6XNF3QbHeIl2m9cVWSZB6zvrbGMl5iipJ+v0eaxcxnc6KogefVwjiMg1IKVxg8\n18V3fRpRk2We8PzOITffvoHbgiTPcKVHki7wvYBKF6AkjuciKoEbuFQ2R/kSVxtcz6WyFVmZoUtN\npeqsTSokUip0oWv6TlLS6jSZz0ZEYYM0TWt84GhObRoHaw1GSKqqHsdDG0xVF2+m0hghXvgoJMrx\ncSRobdBlgcRSFClSyNrZoRRFXuAH4Quql0+WlfiqlndFfkASL8nLlDLTRFGI1VUdTjcWwwtfiONi\nTYmVIIWq3ReOwGv4iAJwKny/fh9KT+A7EutopKjHDB2nJmlVVYXj1IW0MRaoO33CsTWkVzpUxr64\nb+Qv76X6H1ktNPxVrME1j24vICsyHjxWLHZzHLtJWsSsbLo0k4qt7S+SFY/x4pjGhR7DsMJqQSqX\nXP1CF4xg/UaTxMYcnyypdEyj4SJkRrKQJHGOyVrES4fjvVNubA/Jm1PS8QGm47JxK8D1HQ7vV5wd\nLbl4qkgOBdIIbDsickJmpy6zpxnRSsgoidm5PmBt2KBiyc1qyPmR5uwoZZ5MuHF7E6MnqABawwjv\nyOdwv+TZ+6dsXnZpqgX7ywmXX+sigg5nHx3x9PEUGfVY7At0Idlor6OFJS0yNrY7tC8Z8uEMXWnW\nFy2ev5+x++mUreEq7ZWQ0Z6h7LpUJsMGCU7VJE8E5VxRCs3J6ZTGehPbnpNnAr9luPhKk4PPDLOj\nhFdubbHWAutNqLSgyCv0JEIaBS3Bar/Pnj5iPNVceLnNzpebGN9l+1jz8MMD7rx3hK5cur1LBO0u\n84OKl66sMspmZGVMpTTTYoRWgs5mD98Z8Gx/wvwkZm1nBSfa5ODxft0ZZZ3PfmSZ/dfn/Od/MOBm\nc4ef7h6wO4FvfKvNSM2xZ22k3sKpDHcePeH67QuoYpWTn++yGF/kd7/0Ld47POJRMWLz8QZn5xnh\n6xHutsPFSy/h+AUyzXj2Y4vfWuPw7pTzUcFm6yZVMifzYZGOkc5T3vzNFU4PJck0Y/nMIz3o0Y8C\nqrMIv+kjM81smuLlCu3D0XJK7CZc3FihNVxj4Erm5xl//cef8nbo89arq/icE0rFR8vnnBjB6s42\n2UeGvcMcjc/d8Yxmtc6gf41sUWGeVogtiz6XFAOfGRAGXVTQoWy6jD45pb3SoAhc7t7d5fqX+3zj\nm1eYnZwzjsecuft8fPeYa2sRrckVzo+OKI81USciWnXQwYK1TpdEJOjYIT4rOd1z2Nq+Ruj1kF6P\n+V6GQFO0FdnS5yTOUSuS+dPsV/Ks0GVGfm4oJ6t0GyukcYts6hNIl/5wSJImuF7Frdd7tC49xL/4\nQ2JrSCvJwuYYq3CEQ6ACjMkxYoK1FU1ni9Fxn0Be4PzIYbXfZ5nfo7G2xf6H8LM/SikOVhnNJcnC\no9lfpTAVk+mIyswYLR5xdr6HJwXJGGI9IWpsIPqrjBc+Iw3Pnj7jq1/7FupJjxvbl3iWLziOTyA7\nATnC2iZBO+fCLcVMPWaZn2AlVCbEbXsUOmSSzcjTAhJLaBzS469w9qiJXpwTWE2eLEnmEUud0h++\nxOrFr6Eiieo+4MoXzwnXphyne/gtlzQ5piiOQWSUYskkyZifW5oSpAiJNRTSMloojE7Ip5aW9Jk8\nz1kumyjbxJVtpILQb9PqS/prHXpbb7D90tc5yqZgSgbtLlKOMM6EUp+yshLT7CZcue3gNJ+QOBPa\n3UN894DYHrIQJTs3f593/sUT9n/g8dbgBk8/+wDWM4qdf4UjepwXD9g7uMZfffeE3/mPLaXapXIj\nRsUpnr2J8udIZ5dW8zKt2z9n/Mo1Pv7hClW1z7d/v8mNt6bsPRjw+PkNhuNTttefUlUjPLlDyQPC\nzQ0uXh6wOxrTWvN44zsVb3xtzvt/ewSLDk9P32UjfUDSPeHKV2E8vkJ2eoXTw5S9+xXZiaG3vUI6\nm2K0x9FezNFzwSKF6MY9fuc/S2l3zpgcdbn3wa9x+jDg2d1delcfUjaOifoRp9mYyt1isYCw+qc0\n9JssT5c0/X2CoWJ2/pye2qOYJzRsgS4luj6aQWifKCxoDUv2PoKH7zSYWI/je6e0+A5tXmZVdUjn\nx3jemOPDGSZIiF2PbhtU2MPio21JIC1TCsKXTum0znHcmFb/q/hW4fR+QHTxhD/+Fx9y/uSLXAt3\n6IaXKUcZcgJhtIYrXbJyjnFAi7/f4eU/qNAoKk2alyyLiumyYDKpmExLlsuKZJFRpvUJNVJQVCUK\nMLY2FltqeZnFYqs6jCyleCFY+4Uzow4xC1EHYatK12Qna+sxK1nhGqgch7TUzPKSYdDAS+dUwqEQ\nVR3iReAIg3QkgVQYY9GVpsgtldXkuqSsJJ5b/4xCSJSnMGVJWZa4yqcs/28vR4VFFwVeJKlMjlaG\nRqvJ8WREq+ESegGRaiBtCQKyosCaCtfxUb5CiJr6ZLTCUlHoCjcIwVryrAALaZpTCVgmKcKRpElC\nmmUEflB3OJwXRC3loitNGIRkWU1xyvME5UtMXuIqgaWsx4IQhJGHwMEPoNIVFkmapiSJJvTqDozr\nSubzyYvNueD5s6cMV1YY9PskaYKpNEEQ0O03GZ0eEHbaxHHOrJgzrCr8QDHZO8OKqqYAACAASURB\nVOfg7gGXvtrA+AJXKjqdiEWSolxVeyeoKK3GConyBapUqKIkCF3yykE5uhYYAmVR1ojjUuMFIZIC\n5fmkyxRTQi4KrKnhBELURWqZ5zjKxdqKEosnQQqHqizRSqEUKNd9ESyvKCqDMBoroCgLwqhBnme4\ngU+lS5TrYSpNUYByPYTjINxa/qeUS1FohJAMBj0Wy7gOXOOg8xIpHBxZFzyOcikROI6LF4DSAq0g\n9DokWYbIS3zPwxpdOzRcUUMGXBfnRdcvK1KktZQlKOXh+wFC1HkF94U2xL4AB3hhRKU1FoPj1HoP\nI+2/FlL/x112kNB4vaA6sly0gnsnml6ziVzvU05jGk6L9Q1Bo7eKHp4ghEsrqnMXhJZmS3Dn7kMW\niybbLwcMehHTxRFVBVmqSYsmB6eaybOE8QFUhWXz6hpldkp33SE+m7Ny02HQbbO92eO7f/gBzz8d\ns72zgZg65HGKqBxOP0lJpyFxrGgMurTbHplaItwll15qcHGnw+7ujM8fPyX43BD1JNevhPjGJRCQ\nVzn37485O5tTuTnb1ztc/EqDNC15o3ud+x8ccP/7xwzWOgyHK1Q253xvghfkJLpALWeEl0tCx6UY\nQmvbJ38vYJEKxFnA4nBC/3oEpzFJmRJbHyUj7ByWseZ0d8nOWwHzakLY99CJJVhAL5SUM8tKq0nk\nFUwzg459KtthdJDT8CTTicYXlrwQdAYe3SF4YUxexLj9gtWbEfaRy9bmDcpFyIP3Rpgs5vJKn+Z6\nD+Fp2pdcyplhOp6wEUk67QA3a/L5DxJkIrnc3+b04YRlXjDFMp8HqJ+7/NW/1Pz6f/QFdtYnHPzw\nMz672CJNI/rRFsnIIqQkaPR49Vuvk53l/Pj//Jigs0b8+Rn9fZ/zrk/mX8CguaEiyqPnhO6AaLv+\nZ/3s/QVKKMZP28yOFaZ7Ez08xog5Hd9l7VLAdBjifJDzwY/POXgwo7++ilgkbKy1WbvapbRLJmcJ\nyd6M6FLFcLvN7as9+v0Bs5ng8eGcNIHDkyV3f7RgeClCV2e0epZ5nrLSuk4QRhReyHTapdff4uCj\nPYQOCYoIJxA0A0XoDCgWGe8cPaDV7eHvJTgnDY5+nuIW2+QnLvFoSlXEXP36KkfuD3HfSrn9BZ9K\nujz4vECMGhR5m+SRy+O/fkqcxrz5jct0Xx/CZXBNk9F+yZMHOfMzn0i12di6wMrmBk/uf4bxS1oV\nYCRHnwnGynK+948v6wMI/T65PsKTWxjTZLiyg4za4C/Y3LqK1RmfPfox5/Epa96CeXkf113HdRpI\nM8BWHiYvEU6BrhKsMwEc0tjj6LNLLI66nD7tsnkLGv2byEnE3/2rT5gfNuv5/tFjZiYnSZssJyOy\ncoExFUW1JMkXKLVBM7pCu/EtOu02axe3mT19zuH5jOX4mOgDxcWtlzkcZ7jNmH/z967w/T/5lMlk\ngqNjBtundF55h0njGaMzi+opHFmiMonSY6oyZ60zoNFe55N37jE+u0Y+WsdoTZKdMJsZtL3MYOVN\nVtbf5MpOG7hDVh1TOYbuukO7eYHd+EfoPGaRZ8TzktKWFMalTCUpUBQlo7TECVwmscALoYpBLDvc\n//EpyfwCbekTRB6BcolEA1HENJVmc3PA1k4LZwRNscpwxcN6ktbGKfujc3ypuXL7iP6FMxIxwrfn\nWAHCZri06dg+8+Mmn/3NU35r69/n6OEJz04zdGvIrSstjtMP2Nn5dVbXF0x2d5gfHWM2PiaVCXgN\n5iOFnk65srbDTDxFR1Me7X+CMP8JuXrCxbc1r3wN1q6HHDxvYtw+i/iMXkOyNLsM5O+wsaK4/qWf\nsv94iVmus7rVo7/5gPbagv0nHkLFHI1+TmslZ+WaQ3snJm44TM9X+J//+S5r1yVf+WcHDC+5PH9g\n+ewdzXi/wWq3hbv2iEZHMDbXOZ2+T9h9i1Z/m5P9/4Xndw8Y3EjJkiULDafTA07PA25fGbJ+uUnv\ncpuz5ykfv3/O6YmhWhRUaYIpUgKvjQrnLDOYL2P8QUp7J4IHIQef+zyelVzovM7ahmJjuEJZpkzS\nc37yycdENwTB7Dml4/PGG68QNK5T2AjEY6TIyMQu5/ExRS/lQq8J7CJIKNSCKNgBs052/hYfn99h\ndXMf8zRgfb2BWs8xZGR2TmUhM03+f8fbFpUgLmA6r5iMc6ZzmE9zirLAaI2UFqkcrDFoBFR1MYEA\nR7hoW5N3avSP/eU4Ve3ArgOvxvAir/GLr9X+DRyFK12srlBWUglY5CWR10WpBFMJlKgxp44EayVl\nVVC9EKE5SBzh4CgHqyRtx2cxW+D6LmHgs5wvcB1FIR2qsiCQiiDwCcMQ1xGowKdpK3RRYStJdb5k\n4Ia0UdjKEqcLHEfgKwepfKQA3wuwZVqH6PMC6TjYqkYbBV5AkiYvTNWKrMjptprkeYqxBiPA830c\npXAcKMsS5XhkRU4URVS6wFUupjI0Wy0skmargxSSMsuwpv67+0GTxWxOGLRJ0yWep1guUjy/QVHG\n9DsdlssFFkGr2cIRAgFkSYLxPV5cSfKsNpm7nkOr0WRcTilyzWKxwAsGLEbPObyzztW3vkLuzmk2\nPcajGa21IVWW1NcwL2t0rqsQ0iWMbC1yNCFGF/XsMILSaPI8xSJI4oRmy5AmCe1Om7Kou0S+G5Gk\nCY1mTRPxPBddZMhf7Lpf4GYdx+J5Pp7voXVFRe2iCEIfz4eirHAdr36fGY3EYIsSKyxaQOR7tUU9\n8BGOQIYeZW6xUiGtQ6ktk8kU1/OQrkteFBRViWMNxpYY4YOwqCBAWovILaUwWDTGWjwfXN/HYpBG\nYq3GEZKqqq95VckaaWwNUtUmcCHq11jDFAxG1D4Y80JyKYwBaXGEBCQCKLMMrX81p5SSlG0ZsrEl\nWGwNeHenjf7oTe78y5h7HxyzseWw2o3whwbT85m4Hm5iCF1DMFC4vSXp/QPOsw6dfIDfEnQ7EfNy\nl9zkVLZJq3WNwnN4+HSCP3BJnk/IGzNMkmBcgSNdRCek6w25+ZVVPn7nHt1NweoNjyzXZBMfM26h\nCodkYlndblPlFblIoA2eA+Uy5ubLTSq1zr3He6xuBAx6XagqxKJBq99k2Guj0wrlgt8U6CrBJBWO\nqBCnGUWW0btxFTdQKAzDyxLXl8j+gkQuqZKCdjvEC0P6wyZOWzMrDJGjGE8gvafZ6Q5wpcBtKiog\nzwXjg4qzp4IrLw/IGzFgka7G9R38EJbThE9/uMsr31pBqgFWCmzZxllmBMMtpqOcWZpSpjX5bjmL\nGU0KrC0QTglpQaUMjjGkmaTZaGJbPrt3zqjuPKVxWXFrGCF9zdpFcHTC5/d+jln2+J1/9luExQo/\n/9tHvHz9JapV+OH7z9g7OqNz1OHP/7snrEY9tjYv0j7d49H/lHPl6zfQ/Yg4jxFeyda1Gyys4p2f\nvA9DyWtfXuVn/+0BF7yXKeWSR+PnFHqKKwPsZ5rLb6/jrGesrG7REgkHH02o9lwG+QVOvieQ3RB5\newktQbAm6StDfn3I7r0luw9mhHmDYhazdcHn6HRCJhI0JeGaS+hI0oOcw3FO+xWBxMGZBSxHI9Y6\nHTYGPpWBOYqF1Wy0LzJobfJ5lRG1QyZTj+ydmMi5RSPsMZuPObj7mPWR5Y1v99lpbnH6YEQwiohP\nXJppg2miubJ2gTiJMThc2Wpz81XJopojLp3R2i4RoeVCJXh+74TJB5qt1lXa2StM757wWLu81moz\nKZdIWTA6Suk0+rScFfJpyP/xvU8pq3tcWe/wjd+5wfq1fRbhLqkLqqv4+K+Wv5JnRXLSAxHgt1vk\nhYszHNEYnrO2rYmPR0izwcXtmzx7lpO9E7PzzSs0Oz5h4OCLLUoxRqsllagQqkKJHlJvMDlSTA4T\n9h9O0fE64fQqwnE5uPOMkydLVOmyP9rjbLqP8QtG0yW51ljrInWAUV1UtM1w/Rqd3hU2e7cIoxam\nyNi6tE0h77Ox1mP//icYDWG/x8ArefdPvsv8+JR21EDmEpvPkG6OdsCzF/BMQeCOKBJDNrNkB13O\nztaJj3MWT28SHLmE5QmTGEq3T/vCNVb6X+LWmzcZ9C5QZIKnD4+Q8TO8aMTZyV0eHB9QyJJ0bikQ\nyNypo6MElEZwulzghT4qctFzjV+AYytErph/DKd3u+iqDa7GWoGbNmg3ffzWBoMrHitXD/Ha91kN\nBe32U9zwkMb6AZl8wI2bEclywtLbRTFGWkMmcpRVpDxmzDM2ucWf/dEP6BRvs3n1q0Sv/ymPDwzH\n42+zf/yAkjX+4H/4nIPd6xw8W4fhLV7/rQTVfs6FS306zSV/9r8m/Ex8ypuvWJJum/XVkJ/+4Pus\nfW2Pa187J+YBg+0GcsthYQxxnmA0+PY1ELcJOt9j51XND/78AbM9+PH3HrH2yjZeXzFx73Dl1QC1\n3sJUIWfPEpR9iTff/iIH/SaP767D5BPOH9yjGZScPEy593cWPb/N+qs+t75ZMRYnFEaRMOeN71g+\nX684+26H/U/XuPalfTo7bZLTc57dg5tvvspbbxt62x8yvJFz/68dPnp/CU6D3RPDy0dQHVZ4vTMK\np6KyPkGzYngFxvtnFIHP9OgyrfB1LvQGfGFji15nnVQ0eS6HPD0KeP8vTul+HnHxLUXzy0NSjslE\nhqxKylKjZwMWTwOsEvihAC+ly++R2p/ge+vo8yOaZp3STzmbHpA9Mmx95TqF+ZCz2ZJmp0kxNwj1\njxAGzzJLaTTTScpknDFfeCRxiTEpaMAaDFBhQDk49Wg+wkqssfWp64vgtzB1aNtUpv74gpIjhXoR\nBq9zAUopsIbcWBwkngEcTRW66LRglOZcDmosK1YhHAcqU1uTbYXjKiI3oMgL8rwgcyoq18FPC/zQ\npyor4jghCAJMWd9opQVZVmBTHN9hOlvgSZc0dKlKi+cHhEqxqAoKKlRW0vUDKgHG6hrTi2C+nLLR\niUCCKXWNSMWS5DlpmRP5HrguRVHiKJfRYkoURXiuR5WXuJ7CGmrbuXIIfJ88WxLHMVkW0261Mday\nnM1RUasuwlyXoqjwvdqWPRmNCYIG0+msdlLkBa7n1Teh5zEajQg9j8DzWEynL9wbFi8I6nnMThvh\nOkxGE+LlFGFfIHqlQ391QJGmTOYzHJMzOTzk7KikeVGQJFP6/U3myQxXWFzXpdlskacZpZPVSFoL\nfiCgkuSxwSifsqpIljHSaOryUDGfzWg0Q+bTKUEUIpWLMZIwbGBMLdsripwwCCkqje/7VALKssBx\nApTyqEqN40hcr96sB4FDVqREjYCy0IBlNp/RihpUZYHBgtUsiwzX90jSBC8KEEpSVXXOZj5P8FxL\nEAWYsmS2SImiFsI65Eld/EofrLYgSqrSYoXE9R08V2F0hdYORZFjtEEqiS7qboYnHbSSVLokLwqo\nJe9UFZiqxJEu0gFjavKUI2s3iOupuhsnBEr55HmCFBB4itD91dh+Hy/OGT7QuLFkNpiiVMH47AmT\nw5DNxpCGkaBnSFkxmpyQBROejhO41OH6yiqpmpHYEh2n5LlHiUA2u8zSgKFsU+mALLY4oqaErQ3X\nKMYOoooQYYkwgsokhJEky05QK5adr22ThZo00YznlvGjKWUScWF7g6jdwPFryMAi1ZSFwIsqAiuZ\nzWM6XYcqU6AdSixCgehoXOMQNiWzuAAjKJcFnEOVWdLTlJNxzEu3rtQiMqdCNQRBHxoNh4U7J5SQ\nHln0sSYZZwitubDTZ/TURXS7NC2cnR0SPVRsBatMlwmVY4lHFXufFuTzNme7LkGngbMOhatxMkk8\nKglaTeIlnDzTuKlHdHGN+XjJ0V3L6ss+RtciSU9GWEeSzDWn+/UhTbvZ4ewgphe1iKSLkZawGWAr\ngUNBpSM8L+b8WYKWcy5dW2VFRZzcm1GUHkf5HY4+Kolnls7OVcooYNAZEGrFcKVBbA55+POUTdmm\nnV3C+JL8UcCRHJGvFAwv+XS6Dg+PDskCl5vfuUk2jglvp9z+4oDZ/35IkafERcynkyPaLUl/6EM2\np/lWwWCzx3r/MmNrKY4kH3zvI0aNc261LJ1bgk434LyoODjaZ7Q/ZWB7rPtdmre7+Fsl3UsO2ofR\nXootKkphCYCDZzGjg2ek1qG1OcBRiksrqwyHktn+IVkYcLO7Sl83eKz2aTtrfOs/vMzjH2gO3iuJ\nFwuCbgfcgOHWKovlAUdHEy4Ih0HPYXay5OH7c7puAE6L3BYUVYJC0Bx6nJ0+orE54uolQas7wQQe\n3Vst/MLnkw9ikr0SPYuwNOm2VhGli0ihteqDGbOy2iRNCs7OQLgV3UaT7WtrNIaKqhnTHEpWBxHj\nOObarQD4xz+Y2P0wQmmfeCZZ3VrBb1re+HqH3vanZMcR86cV56d9vrz272G6uxTpDH84Bk4AQ+T4\nICEvKxzZI6408WzJ03uC8fE2y3mLXriDnDWRtuL0XkZ6mhPohOliRCoKsiInSQ1hsIqv2lgimsGA\njZWLdHs9ep1NMo6ozIRQBdhkjhaSJPJ4thjRX0/JTyou+ZcZH52w6l/n5PSQaSIRu23G799GvhUj\nB6eMixI5s8wfpIzvdRj//Dpn5w2qbISTXsVhjOgvSUchDXfAldVf49Llq1zaWENFkvHkDp7zhNHu\nE+7+8DmN2yOiiy4LU+AQUKQFZWzBOCwXS4xSFI7EEwHSlmQvwBlOBXpWcXR/RKO8iZQuDb9L5Hfx\nwh5Or2RwK+bKN2f4lz5Gtd7HmQasX+xyOPoJebSPv5JwtITe5k3yJOQ4rVBS1r4qeYQQB2SzNRrO\nf8X0g/t86+v/Fs8v/Df83q/9lPTdm3z8RzP2PrvCX//oHRrp77FzeZubV36bs8NH/OhP77NyPeCN\nq03GOmZy8FU+/4nL8fop2//2Ls8P7lEEkp0bphYj00eRocUUR97EqTaZxndR4iGJ+895+umMxd4a\nnrmMKN5g7/EjHn66R2sQ8/pvGMLOS4xnHtn0nEG34o2vPWJ8fcHSPWcze43dn3WYnYZMP+0SDSZ4\nucvKhcusv/UTXnt7m1H5ORtuE/9lxfaNhzBYcnb3FkcPE9777hHD6zknZ5J41Oc7/27ItS+/Q8Ie\nnmpyMm6gkyGV4zEvBE8+M+zc8hmua4Sr0GOfLDYEc4fpk5Ri1sBreNx49QrRyGGr2WLl2hjZlxQP\nU9yNNzk52aerW1y59IAqeMSoWrKwpzRVg2JicZdrPH0noR/s4K1v0ex8SMrnFOaYR0//kpPjBZR/\nRbpM0bPfYGPYIs3PMBPDcKXBPF2i/AjP+fsh8/9BhcYySzGFw/FZyWQGRTrH6qK2eksBViK0RCJe\nEKJqQ/MvOhSO4YXN2GDhl7ZiIyUSp+5imIq6IuFfQ92CLxRSOlSuRCBwC3BkAykc9quQnpMSypSk\nKMj9CFVWeFKQ5iWiUuS6wigHVzkExpCJ2tORo1HS4Wx0znpviMWidcnKSg9bSUbzOWHUJXAqWr5P\nnI0ZBk0KnQIVTevjuJaSnFC4tala1rP5SEOaZ2hr8T2fSkjivMRzPawQZEIiyozId3ENNN0GWZaz\nLCxRGJGWGkdCkRQopZgszlGui7SC4WCN2WKOoxTrFy5z8HCX4epKnS2QtbMk0yWudMnTgl47wlWK\n+TLFWkHY9lguDL4f4IcB8XJJ0Gz8MogsigyUy+nJFOE4hI2IwmQMwzaT0SmNdhsQeJ4hzQvaK01E\nETJ9ckr7Vh9T+phkBKFPFEbMltNaLtcQqMpHzC1+ZCickqIYEzRBG4MoHBzZIK9mWGPJsyW+77OI\nMxyV0QbaTYc4XuL5CuUrAs/FCsjLlECESASeEjSaitKWVNIShs16TM/1kY4kqzS+36TIEhynRs7i\nGbIsR2tdU79cgXLrIkUJB/9F9mhZOQShotmuscDS+DhuQCtMKZIZWV7huC4lmkrneEpRChflSkxm\nKMsUgcSYesTK9SXWKdG6wA8URWYpsrQuTAwUaYrvu6TLvIYWSEPpANqiXAcvCDDSRToOwhcEgQe2\nQhcF8sXvbHDQ1vmH3O7/n1e71WBzy2JzGBdLDp9lnNw/4PhZi2+/cZVw4NDq5ERrJZOjGSuXWrih\nR2/N43z5DBuWDDaanDyCct7G60FuXU5nHZZPCvphE73wWM4svhuhHI/5oaE6dJjtCpo9SdBsIQeW\nk/kCG5VsvtZibdWjSU577GKnKftPSkqjEaHD7uMx+aMp/TVBZyPANy5ISyhCzic5oWxRpgXoAKNy\npBTEyyVZnmJFxXKZ8+l7Yx58AmvrQ+KxJgh7BEGPRVES+gbPhZVVaF9okrsF4DM+nmG8NibTlHPL\nRrtDd62JdCJMWfH8CXz+oym91jZOx0W4EnNukFlMr9Xg5FNBFkgaHU131WVxWlDMXdxuC0Uby4Dl\n2YSD3RHxLMeRHfbuOcyWIxbWoFSBVZLkrGTLDnBFQOI4ZIcerVWP83yMrPoMOi2WS0MUCV554wrB\nimA0P+Dp/X2uvb7C86PnjPWMa6+uMt19ypPJGZdv3fy/eHvTH8vS+77v8zxnP3e/dWvfunqdno2z\nkJyRKIoSKYmWINmxYMWREcSAEQQBYhh+k/wLeZ8gyAvHQJAERuAojmNZkhmRJkUOF3GGM82epffq\n7trr3rr72c9znicvbs1QAQJIQiKel911u4Cqe24/v/P7fj8fjDzj8ElKyw7p3miyteNy4ytvUfIx\nJonJBtBZXaG6sOhubSGvGzo3DCpPMcZj6YVtBkcj+uff5kv/xa9TPbrPTjnDH23xnXeekJQVm84V\nsrHDZDjm2s0mcb2k13CQvYo2LSrtcO3qCp//+irB3pQZQ+4/GaJ1na987UVmTwxJHOPWIdi6oPf5\nHLdRsqM97LLO8w8H6JmPJboUhcXwZIyaFPi2j/QE0+OYYprjrto8WhuTB0+hqnhVtrAcif2VgG7Y\n4tGPEqJoiNNwuf7qBieDKeeTJ5zuK1zHwcVl98UN7Pkac1uAyHFDTacLtfWU+bRPb7dipQeZ7FMq\nFyVztl/cpvm3O+y/YzjJCjbeXKW22eR0f0g8Knm+/xC7k/PqG1sou87+fYnru/QPFJPBhEq59FY8\naksunpQ0jc/NF+r8PAaN4wdtbl79Cqs3esjmlO7WY3q3BuB/yGrzBTa2BBcnFwzGh8hOjt2bUMq7\nSI4o9C2UaGJhk4sUz3KwqyU6/k0GMkf517kon6HCgofvf5NKTcjmQ2bxiIPxkJwKJSRFIal5e6y3\nX6TTWsapg2U8hM6QaYTlTFlqBVQGqigmKB2C1h5zmdJ4bYV7px+yHfZ48vSCTtDgvOiT6xRdBagz\nw9n3z9hxrjJZHZEvB1T92xz+ccbkYxepGhRZSu6tEltnuH5ANXAwVY5rjai7BRubGau3/z25PaIc\nz9kxPfY/3OCTO/fZ6xT0WgG5LRB6QYMywiUvKtISqBaUwzRNicoSco+qUrgV2FFAPDVYJsBVkq7f\nod1o070as/tKyfrbh4iNTxhm+4tHfp0e909KPBucyiNLmghRUIkxo+w7tN1XKaYuSXiXlAky0Djj\n3+T9H9fxopLtPY/ar0+JxQ8Iezlfeesf8tF3nvC513+bz725iu9c8O43/zl//N8OcGsN9ta/xrPB\nH5OTsvFKncHhVR5/tMb8/2gjyjlP5vv8zstXmObPKbWhcCqofHw3ZRoXmHKbQXLK/EKx/8M2Zx+s\nEeovsHalxyefPGL3h3U2rozJYgfcAxo3M1o74Dd9RHWKyxGvvN1mvm+jA5/Z4CYfDlNWr1hM+yVX\nXr7g2hsXKHFKw/aJzYSaSIj0LnbRo94WSDtg9PBXefLhexi7xRtf3WTp9jdJbYkQM4ZZQBz7OPlX\nWO1dI5/Z3Lv7U2ovKPw2qOWEvKi4+CTl5F2Hh98PkMUedcdBRxE7zU2ctV1e+toG7dfO6Iw/5vHD\nDu/9kWZw/CHzyTkXhxDcWjz4zBKb0YEieTrj+BONv93k9NEy/uoGE/NjpnPJ6emcfPo6ob6Kx7ss\ndSK2b2a4qw/wOglV0aFh7zIfzzBxAvzl28+/1qAxnSvycsZ0lpLE6eJJsK5wHPuynPqphXhRR/2M\nMWX+wt/xM5SpuIzpCATmcqC4xE1hWGTOP/1abS4jUJdDizaLDUmpCuqeixQOlXBAQKUKZKWJy5Ig\nrAMGx1o4NKqiWGxUFJRGEQQB8/mczc1N0tmcpe4yw9E583lKpRcl8zRNyMoCu2cTNDtk2pCXhsCx\nUXpRXK7XGuiioMyKy0iLRDo2aEMY+OiqIk1TwmadKitAKTxhg7SQGnI0uqqQgYtJc+I4AQz1Wp1G\nw0MIiR8EaANJnJBmizK3ripOTo6pddqMo/llDdiiKFI82wNLUKqc8WxOI1z0QjrNFrP5nE67hVYF\n8XRGq9lkFs1ottoMhwOarRbzOKHbboMjEVWBZbscHp3R2Vih0iW+Z6OVpNNqMZvHeE7E8/tPufa1\nTXSosO0unp5RFBWNWhMw6CpHFBVex2Eyni5idZZNs+FSZoLKMyRxgTCgdYVtOZfDpsJgyLIcx7II\n7TpoC7Sk0qB0ju/6aC2Qn0IHpEXouQhhYwmJ5buL3oMLFhZKF7iuR5LEaKURosK1HZQqEZfY2Pls\nQj1sXWKKS4qypNPuMR1PMAY8z8WUi61DUVRYVn2BrlV6gdgVFnFUgh1f3m4SR8oFvllaGCPQZQnC\nospTFCV5kmFJd7FZMQZVFlRVudgKGoOUDqoy+MGC4GMAzMJYbzQorRBiAVOwbeszVLQQP58yeDPV\nbNcLLnyNM6+YPbaIZjkr9W1aJuTq6jLP+h8wq42IzIT1dodwF+rOBFsaMgw7V3q8/60jmjqit9NA\nhy6WuUIySah1mlwcTJn2warViCc2Eo1HlywzzFXFzmsdng9yisrgNB1a21BrSlaXatT6LrZls7zl\nMx3CxWCEqjKEA6OjjCoVrL7QYD6PyBJD/yiDzCEfSIb7ipVdn1JAlRp8hEGFigAAIABJREFUr6K2\nXMdbCrHdBsP+mKfPZ+jCotnqMJvleJbE8iXNQjBPSmqlIghcBC4XEzgdzilGNmqa0vUEnhsSZSkH\np2f4zSaJgaP9EmoFVmghtGBjbY/AqTMYDtBFzsmzPkfPU9rLTXY2d/GcJsMHU7J5Rbu1jus3cPIp\n03HK0WhGZ7PG9l6Ndi8knmUcP5wSD1y2mpsUZzFNWyw8RbICp6BUCfF8Sme5QetqHSHnLIV1xtMe\n8VhSCZvdzzVZXfUYypzrok7af850fkIZuHR6GygjePejj+i8usav/Wcv0+va3Hn/iPGgoBPWWd7p\n8XR4QOt6ndKBKJuCrHjxCyu89vlN3v/+D+j3Y1564wXkU4/r9xtMjiXvnu1TTreZ+5qtXw05j06x\ntjLKyiEdTymbCb1XOxTyHBNNiNKYqp8irBKVNbFkSN23qW/E3Pq9HGvvgJ7nMasCovOSnW6N0/cL\nDo9SnLJFs72Ebbl0el20nDA9GJP4JRu1BuP3pkjPcOVtmxUzxTaCia2obWtW54Yqsiiiivbtiu1f\n3OT7f7rP0bM5RtYIw3WiuCQfRAjhIKocbU95/c11Nm4GpJHi+OAed350zN6bDexWnSiPWQ1z3BcN\nTmFThIrTRyPGyiIIm5wM51CH3/itKwTrObmasxGs095Z48E7MU///Jjjg4ja7pA2Z7TCiumwIBon\nP5fPik5rD0mT1tqI1VvHXHmxxK4f4OIzHMTo2SGVgOaSQ+Y20CaiMhkuDrkUROVCooucEhiDdPqY\n5BMcb4151CdO50zGR0yfzcjKAWk6JVeGRPvUnBrSQKPusbK0TssxtGoF2vaQ5ECGY4UkZUJT1ams\ngsOje+ytbiJCD1VbJSslIQccP3vO7eUbZLMYW3YpxQUiGDE4HGJPAu5UbWi9RZrtQ+qQ9jeIhWFg\n2ST2Aa41oYxcyvmY1dUdKAz1wMMPA8Ibj0iX/zdS+wTVnuHZbxFM2oiiSRJfUKgKy7NJ0xIpfbS0\nGM5yKgUoRWgtvGVZqhFaooXEU5r+85TzfkA9hnozoO7WWdvssntLUF89YFp9g+wiXqgDBDRrNkcP\nO0RjwfZLLuFujNMcMpo8ZNaXHO7vo6cj/M0SbxkKKfjK7kv84TuP6RiLx3e+x5f/TsrJGLIk5qMP\nCl77wgvc+tt9fOcIiLn96jq9YIXdjTd5fvceO2/VUc2cndfHJOW7DBtf58/+xwrRrnEef479n9QJ\nO0+I7YTdq2BrWGoXiHgVYVw8oXn/kxP6jzq8cf3vsHPlb/He439HIl/i3/2L7/L1377Ce+8+wJRt\nlt/I+eo/WqLT02hvRt3WjOpTqtrH0PgS44mk4Y/55JOAXmuDenDMm6+tk8yf4/p1AveQyrRItcbo\nObVWigz2KbJbXKv/Q8KVDs3ajIv4v8f1j3G1oCa6rASvk67sMrk4JHcuyIYpD745R9RTnJcVdtvw\n7Fjz3rcUYnwTpxGw1tpmK7jClnCp+Y9ZWTNo64BrexnL68958uD7TJ+vMHzcovTus9er4zrL9B8V\nTJ52eOdfHXNt5T9FZ6/Q8rtE43OKXonlthB2jrEztLagsLG9EcJxaG5UFPmMwG2TZpL15WscfjID\nLv7S+/yvNWiMJgVpKZjPM6qiArPAki5M35f42svYk7jMyf/FaxGHWhyM5KfDhpRUmM+M4J/1M/gZ\n9V8IgTAGXamfbUcQKK2RAi6mMWHLxwvrpHFEWabUag3KsiItc8DCcYIFA6jSOEIgHRupBJWqcGyb\nvCgotSFO4wU5y7HQBbi+jUDQ7DQYX0xohSG+bS0y+1qD1pSVYjid0nQ9PC/A6GIhWjMKXzoUlaL6\ntPheKHKVE9gugeujqhyMQeU50nXQStHt9iiVoixLDIbhaIrnuuRFQVgPFkUWA7a0qIQgdByirEBi\n4foeRpUI6aDKkppfpyhzVld6zKaLaNRsPCZo1JlPJ7i2g+M45FlGpdSin1Jv4IYhXc9nPB5TFAkb\nm2tAyermLlExZandJJqPcSwbo23avVWkgPGzYyaPY5Z/oUmcSXwJmTI4jkVlNOLSBm/bLsISuL6D\n40ts4+C4Ajf08LMS260xmUQUZU5RLsrStUYNpUry3GD7Ctf3EcJaOCOEh+U6eCxs8MaA5QhAYUSF\ndHxcz0VYYDs2UlToUlKpCtfzqGRFWaSkWbYweAOqVAgWkkVdKpJ5gh/4RLM5YS2AyhDNI7I0w/Nc\nPHeBxC21haoMUlsIaeMIi6xMsKyFIMpUoFl4V4p8EfVK0pjQdxmPJ2AERZqQxwkgqS4t7cZItLUA\nGvj1gDRWLK+2yDNFWPcQUmI7FlyaZbXRC+KUWnwv/XPyaMweVxy9kTIxJccPHA7e92hNO7Q3l3h0\n9oS5PMPtDbj9WpMwbVA1C6hKcmeGUgXjkYUttrmydp2TJyWTswnGNXhLLsarsNYqZjMLPwjwpIUq\nCopYo5yAfFwjTUqCumSCwWlW+CsSSY6L4OxpH99v0bldI8w8Zt8bMh9HdHtLNDsBVZEyPjlm1guR\njsPJ4ZToQmGXNm7m8+iHKVbp4CBIshjH9nHDAGnBzivb1IcrjAYzhvszLGEvfCemYjSeoxJDXSl6\nQQ0zk7hejaCy8eyA/jilmjqcZyXIGYmq0Nqw1GzRCRrk6YSimOJmFiu9Nr2dGmqm6DgB2rZpsILr\nl6xvrVDkoC5mDOMLLu7NuP7iJqvbPfa2dhiMJrz/4SNWek2CpTr1JQ+vZqMjj/0fDelP5rSMyyuv\n7RFbF8TygnnUxyHE7SSIZRe7NkWpBNekrC0HpHGM6/gErTpuqIhNn7UbdZ5WMZYTsOyFqHnE5GxC\nsxvxwQfv8Er/LZaXbiHWEo4f9xkc9HBPPcqlgrDm4Fuw290gSvqsScMgeoDdOOcf/Je/iBol/Ml/\n/Ud4v3CVX5y+Rfx/nfE0HTBPR2ze2cNbW+LwPOfkwRnpMGPry+usf6HNIH0IUYFnS5au+kjlkcUK\newsuhhcEaxPWXlB0iphrRnJk+XyykaFWDdU4pTXxCYcBUWyYXKTE45iKnOWrTYJaRTEpefz8Ebff\nbqBmiriRkTBkQI61us3nt3Zo6h4/+PZHzPOctc0lQh+mI0Gtt8bxoWTWl/hVSFj3kHHEzRcDdvYU\nwjmmdcWjai7x3refc/rNEf56SbC0RHtdgTfH3R1ztdEmjmrc+fE9zh/muJbhd//xdcbTGUnrnOaK\nRdh2EA2fi+8cc/j4nC9/9WVWWj6j9h1KVzOREuM3gL/5YaO9PuLGm5JrXxwSLL9PGEbMzRmlrnFy\n2GX//YLlbo+1m2Oc1Y/pZ/eo9AOM10R6OblsY7szZvOIad+mGAnqlmI4OOP48ITQW6E/sHn26BO8\nwCPVGZbv4LldeqvrGGUT2DVaoUXDBsckmKqOrC1xOn6IpyxCYUimU4IqoyM7eEkN36pR63U5m01Q\nsWR/cErNbWAmglanx7W1LnefnzHAwSQl9pMGludyMVVEpUVk5ujQwoRTSpWTl5LQB0t1KJOQtdUO\nvbUVVl+Ykds/YBp/hNsuaG7CSPyE+tkvkz2/Rf98gPkgZuV2ALUZjaWC+dQhngA5uNKQVQXCWMSZ\nRZ7k1CxNUTokzzX2JMS2Q5adm6hgwFF/xsmdI1qzx+w5hswx2H7AxUVK359ydv+UtfqvMR1/xNB/\nznbYws6uU54+5+E3RkxPPk/vxZTN16YsXw0Y7I8YjAt2Nz/H0ss+QTUiFV/lJ3eHrK/cJlz/5wTu\nv6QwHeLpC3z7ewaCX8ILXuTk+Qrf+4Mfc/M3BzR6I3bfTDl+/MesdNa4mF/ntRevcue7F4weh2y/\n3aa72aYbHjGxjums91nythgAa/1Nrrb2ePXKBW7rX+G8esQn/82H2N4N/vX/esDLt/8ey7s2194+\nptk84mKyTyEMDVdQk4YbewnTO02WNgNMUeexY2jttAkmB9z5N+e8+HdtutdO0UaQVUNOhlNifYDS\n68xOJiwv3+CVt1e48sY6w/YfMeUcLwE/aXD8xCabtXC8BtZA03H2mDf2+PDxHxD+0YhNyyLdVqhE\ncHba5MXeF4itmLrosla0CZZDVPeU0+QUhkPE6BqmeUHdCYijBj/585Jf33iLoG/oF+9Sz7/I//mN\nH3FxsE7P7OLuNvn4yfvcvv4JuoJpNsdbEpjaCO2MaFy5Ruv2i1hXZgyzD9kLb3OYGro1G0bnnPz5\n34BHYzwtKEo+y7RbYrGP+HRjUV3KwYS+7GGYRdH7060EZvGUWRuN4medDUtfGr2N+dlhSIjPvBuf\nvR6D1ovIkxGflmIh9APGcc5S6GPbGTVLosqM0iye5HKJsLUcG2UMwrIRlcb1HebRnGa9Tppl1Bsh\naZLh+R5CCzCaIs9BgnIDao0GaMiUAmkhjMYVEtf3KaqSSlpkusQREltK0JrcgKsMnpTkQUBmFHUr\nxKoMqS4xpiKwbELPRwqJ43kM+v1FPMy1KXVFPQgWOfugDkj80MFUGikEZWVwJJRa0+t2mY5HSClp\nBgGFEBitcD2Hk5NTut0OaE0QhLjSprBtgjCASpMmMd12l3kS4Qc+s+kMjKbT7VCvr5EmEWkSYbSk\n1gmJ4gjfc8FI6q0600wThBKrsHn27hFbb73OTECIuHRMLIhcrmcvfn5UuJ5NmeeEtZBsluDVHKpK\n49dtojFYlsHz3E8px6hCgeWgAwv0ImpnEAizMMOXZYl0XWzbRdoS2xIYsSB9CQsQBoPEfDrYonBd\nl3meLV4rBZaRVKViNp/jeR6WlKiyJC8VtqcXJm7LICqJKjWYCtdZ/D601lhSkFcpWhuKXH0mnxSX\n713M4gCplQKx6FcUeYJn2+R5hu94JFFKpRaW9KLIMGjAQVqSUpUI6RFHOUHoMJnM8QKPLM0IAn+B\ntDXiL4AZBFAteiLmL+dd//9xyazNwx/OmBdw8qiBiHzKrI4d+hhhuNBDTPGIbdGivRfSn82JFOhM\n4wkLVdbpH+ZkCiynDq6PIwzRcUG906JaEuzeCtl+ySWPSpILybO7MclZhhOGKAT9vgRL0ej6eKoi\nPouYFSUVgoIcYVlUKNZvL2h1KunTXN6iFnawnIyDRxNqSzVUolnfamDrLo5lGFxM2P8wRlcpyxtN\n2o02pWUxT3POj1JKnVPr1nBtm2iSYERFpTLyIiPWNkVfUMsEnuvQbjfRg5JKBUyel8jcQnsOOQl5\nJemGTZa6IXMxpxMKlGODKbDkGLc1phIaX9gELUGv7iKcHDcYkEcK12mz/pqFkBaZM8R4FVWzSSMQ\n1PYrFHOcAlSWkKaKmu/hhDAZTGivtvHaGrutuHZjiaRMUFOXOz8+JzcZz/cNyz1BOUkIbU0hHLIY\nLDTjYZ80ndNouTQ6grYP1cwhKgxTERM6oHTFk7sPePn2y/zOP72Buyf53v9+l5/cOeKr/+TzFFVB\nOjmht1rDCwc0hcXx4IRmI8H1PuLB/X16r9RY/nyP4Pkhu+9L3h+OEMbjyZ8l1NZ9pBfR7NWo7fjI\nHXgyP8NbFth+QKpmLG31qHeXuffOnPk4Yuu1JpuvWUz4CRtWihQ5LhYKh6E1Qy6HdG7ZVJ8YHGUw\nlabfH+NKxUtf2GMSae7/9AGe3eCF7VtozkmFZqLHdGVA7J7j0kXIFCd4hhV4C8Fr3eHsY5sNcZN7\nf7rP9vIWZQKz6ZTWSsLOVoDjjSircwYjjesHCNujf6DgwOeFN3ucTftY1hwrGDKMhqTONRqEePUN\nSBTrvIQa7uPvlZhoiF1PKNwR9XXB0o2Ax09OuPb2Crq9xYwDHlaKo/jnYAUHXvmNp9z+fIzdPECa\nPpGxMdQx1gC7l9PZbeG15uRr75DWPmDar8OsiV3zcMM5jt0iiyzSgx6nPy2QcYuTZ4eMzwrGhyHz\neczq0hq1pU0sW1KzodVqYoShYXsLOImtsVVCnMVIMpLyhJX2K7SKBpVWEBwz5BSRz2kuLdFsKOr2\nFo/v/giVZWSVobZ7hXldErg5KRG+7VLzfNa6yxzFB2TWBUmSMEhnxEIyY47MFToSOF4bx2rSDZew\ncKhSTd2X7F6NWNt9iA7eYR6VCAOjvodVbbP3okurY/Hhj3Z5/OCA6GxG67ogDyXxLMM6bzE+sKCc\nE4gSpTVxCvOpwRXQsWpcPAYhQlqdNTqry3S2thjlU46GQw6il7j39DFV4yHCTlGp5NZ2naVehAn+\nhPnEoogl+fEUpSccfCDIn/0q15f+CSZ/RFPOsey7aPmURnOXqrHJeHaP05MZvbVH/O7vX+Vb/+xb\nfPsPl8h7bVZvHpIVa9jNC37nH32J8cmfcSH/hPf+4MuMz7d44z/6HsnUptcc8G1vQNffpeEZ+pM2\nP7z3W8w7/4Iv9gY4dkBJiONuLv7flwP2bpe0Xxmy3brHUExZU7vsvNHnve+fcWPzy7gO/MbvXEHe\nekpZnzMtJCrTTOeCoPKo9zLC5jeJxg2mI83a0goNHeCFv8LdH25hVh9yq/6M5loEKVQodFVjUhwz\nm92g0dAsvfg/c/XtW6w07nBeNDk8npJEc3760xnqNMaET9h45TWCw4rTc4dJssfRKexEPvH9pxy/\nb+jVWpjQ0Kt7rEsbT11QNCRbbyhEx2OeWSx3NohTm0y/QOfqEvNnG/zkO2egz5hEn+Pp6ROe3lnh\n11797+g0PWQwo1Qxg3NFo2mBtKi1FCsbmrif8vrLW9SDZxTpnGZwzof5PjWvw/joFd79X57z9N+u\n/ZXu87/WoJFnanFwqS6RmYt8C/KyS/EpDedTIZ+0LvsWgs94/phPB4zLJ/xSfDaQoPXCHP3/kPtx\n6dlYXMZ8SquSn722oiJXi0O9bXnYJiPNwPYtVKkuX6PRGioMpc4BG/tSciYAR0qkMbiWoBGGVFmE\n53qLA2GlqfKU0K/hComuoMhzfM9BAaLU2I5NqRS2ESCrS9qWwCkMuuGTVAV+WdHUoD3DvMhxhINQ\nisB1Lp0nhmwes7q2QpYkCyO1hKJYFLjKuCCo1SiVQhowQuC6DmVZEroOk9EQP/Aok5SiXDy5r3RJ\nqxbiSIOqioVh27IoyxIciyLPqKqKVrvNdDamVq/hBh4mygjCkCSOGWUxwjLs7d3g+OiMqiqwbIs0\nKVla7nDc77O0tExSFNTDFhcHF8RPC8JrPrrycSwoCo3jCTQCx7epCoXvexT5YhtQOBn1+iI/6lc2\nReDg65AiK6nMgj5mhEFazsKALRYuiapSYBlsuaBPWbYHtkRYEmwLV9gIS2B7FtKxF8Vpx8ESBhdQ\naY5t2+hKY2FRqhxhwEEuokhKkWclAI60SNOMWq1BEsVYloPnuqjSUJY52kChc7RZ4HYtS1EUFVIY\nVLXAJICNQYFRWJcW+8APmEzGuK5LnGa4rk1ZlljWYq/36XBeGYuiWAwnYbgQLnX9NkWuCOrBwqNR\nVTiOWPg6rApVLGJUQgos++eDtw39FT748yecPFc0Q8nS8gs067tkzwRzNSVYHXPz6w3s7RluoJj0\nI5y0Bk6bCtCVzcUoJUkk3XaTnd01LFtw9905aVLy+Z01up+PsBpDbFUSrDTp9ro8/HGMntdZYYkq\nKXh2vE8RB9TqHmVcMFE52pLIusbOc4xJCaVkdcti2DdkKie0JH7HZ1olmLrNzitt2l6HPAFd2NRX\nGxw+OqLW6LKyWmc+z4giRTQpsSiwbYPxZjiyxAvmvP72FXAMT+8JZkclaiJJpi1muWHmFkjbwrEl\nrq4h3ADhWdhA23Go13ykD8LKWX9F0lxx8V3J2fMZ0/F94rFD41ob0Q1wmgW2N0WanKxQ1JcMa8ES\nlpfjSnCWp+TzMWnu4zUysklOSo7OBVJbWLrF1rLPwWROGSYkwmDcESqskAI2dno8OCyJJjPEFNyW\nT1VGNDyB5zUpyoLp2DCdjfGQpHGM9Ay+63Pw+JT43GVlaQUlXabLE37y032ufOUPeLWzQ/Z7Nt/8\n1yk/+G7Cr/1XEaXIaXcMYXqGb0YUgSB2xmze8LlhAoJftom/LBnuP+bCJDS+uMLKN3yk7nIyjVku\nlmjUWtQ3gZUZ82CI1U5xnQSjJ7SbFpFR2K4h3HYoQ03VqzgvZ5ye93FXBHMEmgYYhyUCGrdtdFcx\nSoZcHE6ZzjQm8xHKZT7NqVRA22kjhMPxnRlLG4rZNU0WJHRqcHI25rRWZyPwWVo2pNmEp38+Zr12\nk8M4J9m3ye7bbK7d4nw8oSVabK+mJKOnPL63z/KmRU5JgzY7y9cQ53D/wZS07uNsWBBosnlKMpMs\nd5rEjRB7eQk9qHjnnz3G/pV99tyMlV88pUvC2OSs3dqCI4f0eMTzT/qsNh2qyqWxVJHd8fl5bDTs\n9pgsfIRWKa7VRBgbKadEZk5jE7zu94mzM2bWOX66iy8domhIlFaE4ZhZPsLoiOTZGs++F2ISm4PT\ngCKvMZ/67Kx+jhvbX8etPsGUMVJo2mGNNJ0STacEoSKajogqwXJ7G0VAvWYRBjFFcUGhKwr7gtWl\nGZ2ajbuq0GXB+/d+QlSsUMVtCkLslTUOzw9ZJccROfOZS8dv02yu82x0wSx3GVVTxjIlsRy0VUfa\nNvV6i259lbpdRypFNovwA0E8T3n2YMTRaJ9JadHZ2sALEoTxWNnI0FvfYJoFuPlL2IM9Tvp3GR2f\n46/mxBHEZ4r4tIFJAqYmox3WUHNDOU9wXIuo8tB9gfSXaC61yKoRebbN9t6X2Qx+nyg/ZxodYAuf\n4eAIYQ95dvcuH6aG5dUJlQ4wToHnpuxcbTB+HpPOJ2x9oY+7e87abcFQjpiMhsi2ZOuVhKW9Oa2d\nO3hoyqjJ0fhdLPX3OXrwgNpqgREn/Op/aGj632f++Es8vfcGgQ0Xj0O+8T90eetrfc4/Cbl1/R/T\nnm2y10sx2TOML7HKJnLS4FQ8p9aVxPljIhqMZg7zEtrr24zFENtsEucDemsWX/jiFzn4oKQmK773\no3/Db7yekoiIvDDYdgA1zWCQE89Ltl+eEE9aHO8HrK2d8PYvv0ppj9i88iJup0OVCPr953iWYLhv\n07+3x70P+yizRpFpCj1hnN2nqH+EZIvQDelcmeD/yg562kO7AeMnP+TwW7tU2duk7h7xuODg7jmJ\nCOk/1GyGLquOwum+SXku6G7PaKz+Gdu/vEVSWnjWHUz9XzLuJ1x79Toia/PxWY1HD2wGyUdY0iKa\nvs2ru/+ApZ2E7b0IufyMiDuENU18Ab7cpP88pqHf5Ois5KTZxzbLeMs2unsTT+aoSvPBHz4iuvOf\nEKQOcO8vv8//Oh8KRZ4hjIVRBiMlAgtzWar+2dbCfGb1/nTTsfjjn1m/EQtXhtH6s6/5DGV76dD4\nNGb1F7ca2miEFKAX/7ZW5SJ7aEpsKyDODR3XoMoSx3apsLCpFpn9yqAtTSUWZe/gMooU+D4oTbNW\nJ0lSpBG4lmCWp7RrIUme4zoSrSscFGmS0ao1QOiFI8EJKNIUqTWe5WCkWdCnUFSVwoQBYh4TSEnl\nWkSWwk01LemibefSng6VgMJUSM/mon+2QLD6HkoYWq0GSRLjBQFRkiONxhEWqqpwcRcxNV3RqtdI\nk5hazV88Wc8zQj8gns5pdNpMpxNc1yVNE9aWVhgXEa1Wh7PTU+I0ptKatCxQVYnJC6Iiw7Jt6vU6\nRmoeP3zEzs4yqZKMxxFL3WVUUeHWPRyvQuiAiIpaknH/h8/50u0bzGIXRIHlGFzbYzTt0wrrlErh\nehIvtKgKszBhW1Cv1ykrBVULxwkYj6aL/oKucB1rYZxX6rMN1+K9IZG2wbJsLFsuit3WAuuKZRDS\nYMRiyDXCBqzFYKAWmGXbXQwvpiqoyhJbSoyRGFWSZwW+JxC2jVIlUjhE0QTfC6hUjtKLTowQElXm\nVJXAGIGqqksviQVaoIRAGLAQCGyUWfSbfNdlnkwIaz7T6RwvCIinGbZtU1GBXNwPeV5hoS/BAjbD\nYZ9Ot8toNKS73CGO4wUcwTVofbnNucRJL3oaAvPzSU5RpPDaK1e4/lLKLGsxuFsymkdMRxqvp7ny\nhR71zTFJ7Rxt1hZDUOWDcTBaUwvrhI0L2uua5WUXPyhpN+tsDtocH5zg+oY4T2iuFliWAhmRJylu\nTyJFTie0IWvw9Pg5swNFNiqpd0Jqe0voIqf/KMavVfS2QrQp0JVGqYzJxYAosTBG09hqsL6zgp6n\naDMlm5d0djawI5vzQ3DbFk7bpd10cQYVB/dj3MSwsh2SqhSvUeKEGY5zQbDpsad8nsaGwYEk0u4i\n3ua5lEXBbNSnMoLAM0jpIhE4to0uU0pnQvtKSnu3oi5LPNtQu9rk23+6Tx43aVU1slGCJQq8ICWT\nMU5DkEdzRAUqL2juOEi7IPZKyrTCs+SCQFYKnNIQtAw6yuhuu5RaYII5Ra3C2oipOlDO56RVjqpm\nzPOU4WFBYQd0lcFdbuJWgsZKFzWvGI4itreXEcIgPUk6KiidCqGg7frMMoWe15kkiicPRnzuKyu8\nRpe/+087/Og/H3Pv4R2ubXfZES5LKIT2GIgRU1JazYJxeo96P6ZtlajdDFOWuI7Dau8mh9+tkz2b\no7MclWncyKGxEnDeSrFXc2o3NVt7qyzZdc4+nnLRP0T7NdxOjSLTNOsd8nmDR6sRj8homTPqZoe2\n9OiZdS5WZ5RfnNE5tClmmumRZhZH/OTbp1zdaLC7eR3lR1D2iWPD+Hkfb8VmKVzjvaPHNLoVUTPF\nMho3sPjJD8asOIYV7zpP/u0Uv38N+ruc/mDErZtdRNWnf5BShAm97R7PH8/otGfU66sk0yn5wGN8\n30Yqi63re3x8nCErD6FDru9tgrPBex9+jFt6vNq8zXJjRs2raFPnRGdc2Vmmdr3iZJxhqorNtR6p\nkxCrY/qj0c/lsyKrSoxooaVPJcak1XO0GKH0CogadvshtVJi5R2yeUIVZYwetnG9DFU9oBxt4+U3\nefyezdNPhuzeyEnKNkl0g5de/iW2VjZZ725AJRgMPiKZTsjmJZbUvyjwAAAgAElEQVS2ERim0RjH\nU2jjktsFazttrHBCFH2DMpzSXdnE68QsvfGUeuMMv5lx+h2fg+PrON7fJzcttve28SrBOJpTTUco\nWWCUZqnR5aOnZ3TEMlFZUhYXpHZFUtl0W3s0Wuusrq7gFIqwUpg0JqxJnGZAHMccHU5JD3My3eXw\nkx7LKxauHaCuzbi1cUIjHGJW75EfrTE9doifXKd82qDXvM3V3jaxjshmEelkQBQvHh7YDcUsHjMb\nDgntBjc7N6EqsITCyg2W3WZr+yWM8yLJ/JwqKxg3L2g1LFL1+5SZ5PD8B0xm55Q8JJqNOHvWJxsW\nvHytTVH7DmXrmxxd2Ly493vcfe8+/8Hv/sd0O1/Ev/qHZIwY5BlO0kfLIVX93/C5LzbJRJtWN6Rp\n5WQ85f7xPrXWL/G5164xGPV5+tES76d3Ked9ltsuLnXy+QU3N3ZorD7j0d0Rj7+7R/jGOa2lkKN4\nzrgQDM419VaJ7z5EqhcwjHAtwS/9ssPz99/h4Y+vczZosnZqcfooI1tNaSyHKNvBCiOe3Zfc/YFD\nq2zy8MkA5W+w/cKUv/X7OX3/x2xvDCjVIoo/p07DgqS+zn7l8+zBC5gLH1UWPH02ILh5QrNdklUD\nKlGSWTmrt55gO09Jsopap06e3kXUhyQ//Rxleot3vzVGBBuIYp2l1R1W2zvU8zGdFUP91pTt35Ko\n8CMK42HpgkkyxulM+NJXlvH0Q84OR0yGG/Sf/B7bq69za3OXF97cwW7+mN6tOab3XWriBOVMmEcK\nr4g5vDvj5N5jLvodPk5bMG7SWlrH3jxivHqKfnKTsx9tEZ5FTAYnf6X7/K81aKisxHYWh31zuckQ\nl1EU4P9lwLgcOoz5WVlca4QAIRZHrsX+A4ypEPJnhKq/OLwIsTjoL2JY8nJDYtBVtfBkGEFlMhJV\nEdg+jfoS0/GIwBZI10VogVpkWPBdl7JYfJ9SKeq1BkWW49oOhVXgORZlnlCr17EtG8+2cR2bLF6Q\nnxq2je1KxDjH9lwm6ZylWg1XlxhboEpFLdco38K2XPxSM6Gi9C2kKmg5HpausAKfrFBI2yMtChzH\nXZTdXZulWmdx+JKS2WRGWSqEsNCqpOF7ZHkBQhLFMXXbIi8LAjcgjpMF4jVLMabC8xdG706nw3B0\nQdhoYIzBqTyiJEGbisODA1rtNtICX/oLYZ3r0Wg1UZVhPosYqgmObbGyvMXp8XMcv0a91uDi4oLN\nnVV0PMeXNllZUKu3cCKPo7uH2PlNZGhTRVMcq4UqJwS1GrEqFi4NE+JYFUU1xQksRCXRpaBe66CK\nES42vu/ieSESSXy55XF9Z3FclyCtAiEEtmihlMKyDVgKaVlIS2KEhWUJbMde/EwdgbQE0nLRVolr\nh6RxsuhUGAvHDcizlKooQV5G/bTBMYYyL5GOBgzarlCXQ4XlLWKDSikwNlW+KP5XpcG2fIosw/IW\nsTDLtRbv9ctIYVkUOJZLVWoafg1jLPxQkGcFhcoR0sYYiRSX2zfHolIVQRCQpinNZmNRtvdDDBpV\nahxrgX0VWGCDMAJ0ifirxSn/P1/xFJZfX+ZKJ2EuPIaNFY7v2jx4/xlX91botG18x6K1skw6Mcwn\nivt3nvGFN18nCAXj8RgjJrz5tW1a6wHDpwPO+kdQM1iyZDYuaI0r4jrkjsJWQAGlAkeEZHmCpTRW\n5WAKm8lU4VIj9Ty0Cuk/KAnRLH25SVzOUDJAxwWTtFj8Lq2Kjb0eljRkVU4RxxRuieu3qEKbxpoh\n7FQs7WqqQiKExcknF3Rur3LzjRvEhcXW6zmFpdHWCDsNWdlp03Y2+OA0IzoSVMqjkIphNCVsabZu\nd3FCi+g0Jz1TFHmJpSVOW9NZDSnsMbLpoPKMLKlQuUW9HZCPMp7e3+fVt7psvrzK8bHEnQuKzCEa\nVKS6ZDorEaKiVKBmGpW6OE6LPJ9hFQpZpvRWbWzLRrYlJ4OY6qpN2SroJxF6FJEmFdoWXLtxlVyU\n1NuCsj9AFE3iCOwhyKSBLUA6NSoyzo8nWDrkq3/vVzj49xEPvzPG8mxs0aQRXufdbx9y8xc+4Lrj\n8Ru/sML/9FsjRvMZr+qYQmpmaDwAbeGvQ9sI/LBgaw0SW1FOC2o7KWm3xpQ1qqGg2W9xnCbcDJos\n93IKZ8DEP6a5GfPyjse6LDlVR2zdbNHtdBg+tHjy0YwnD/pM5j5X37rC1jULSUIhNI4AX0d05CFT\n+rQ2JS/89gbrq20O34WDxwXPjkesNVeY9xMK16ALTZhY0GkzT3MOO00Gj32uvLZEOZEMjgucWhNL\n7PLkjsvV/CpCKWiF/OjHT5mMNV+/eZ0XXtvF2m7x0VlMs75L2+twdH/K3u4qD+7uE5+1eV6kPPpk\nwq/+5uepxjmb19YYzHxOhxHJ+RnPy3Pe3LzJVrND/Pwhs+WCI+8Yv9wCx+CMDWqaIGLDSf8YZ/OE\nncpl1bJZMOv/Zi9DgUZhizZxUTJPRshaQF5lVMUhtpngaUMyVQwPLf5v3t7rV7bsvvP7rLV23pXr\n5HRz6L6d+7LVTYoUOSOJGsuiYFuW4ZkxDBsDGPCDHwbwk/8K24DhJ2MMP4xtDSBjxFGiRInNZuhm\n5759czo5VK5dtfNeyw91uynZDyYxHi7gnA0cHFQV6qxfnfXd31QevYnZ/Rb3H99hNGtQjubUxBln\n+x6zdJUf/HROa/NrvP7t3+Lc5hKtssWSWMa/3sZrDRmeCczcwZcW8dmcycjDmHW0lSJXnnDu6ymt\n7X1meo9MlRg5pLF2D2tJo3RJbwyTqk5n43dph99heHKfuu3QbQc0NzcZRzmng2NsB7bOW2wRsFRY\nTIf7nFWKdvM8DX+F9fYFGn6DupDYdkJVxOTSwlgNojghmvdJygrHv4QnXZSs4XoRzXVBfWdEXtQp\nJk3OHpY8vj9nffUPWHmuSbe9TtgRXHuhzu6TTxkcGQanDUwcElo1+oNjdh89xA9b1D2PhluSzjS1\nxip2lfDcJcPyV8aELcV8fkIWHzPuZYx6BWYe4uguV7auEU1cskKRzOZMIgjWriOLO/z4vR/wwnaX\nbn8Nsm/yxtcHdLb+O/InL6P4AGEuMxlnqIHms5/e4w/+s20aa3tYZoowHpExSPE+V197iQvrBaPH\nfR78uMWk5yJ7X2GaHHBhPSd88zGNKxGXLsf85OQWwz95g+/90T3eaBhce4R0JXtnU9JenWvbHRrm\nhEqdkOnpYt/XXOotC7cm0COfn/7VENUZ87X/vEsZDWhstJj0KzYadW6Xgp++2yc+WCdcXUeER0zE\nXc7t5FTcRStJUDWw2CBnn07tCeqVkEQ5/J93C6reJruPxmzPHeyiTlLOcL0GIgMZ+EyyFDP10X7C\nzq9DfHJKgwn7MiX0X6ayQ2rL65SzOR3PZ7XzBPvCKcv/qE3rjQETc4TkPHleYksLLQQzHrN6bYuw\no/DUq6xu1Tm349C9ktC48B6rFw7wOo9xV3Z5MN4njgRZJvj4h3P+9l+WOMObLK3GpGaf41HB5WnA\nfHeZpdbv8+m7I9KDApmPGDvtX2jOfymgYYzGaImyDJV+BhqketZ/IZ+lTZlFY7FYHMKMXuRPiS87\nNMTCYPvsMaWQzw5AcuHR0F80hIsv2Y0vwIbRGl39XIZlzAKmWMJQsWhpnuQlvheCLCEvSSuBsCSl\nFlha4RmDKAF74RkpioK8rBhHU6qiJPQbZLOMeqvJcDojK3JA4NTaFGlGCbhJRi0MKIqCsBYuiuLc\nxev1jEJbirCyGMiC3AWlJV3cRRKRFMyUxiQzAicky1NsZ8FsKCEp4piw22AyGKKEXKQhIbCUixEV\naE1VlQjbQzoOlVBgS7KyArVoorYdl7IqkEZidEWWpKwsLzMYjQiCEKMN0rMJpIVvu7ieh+tYDAd9\nrl25wtPdXbKiIE0TOssdcq3J04VPodtZx3YcTvqnhM0GJQUNN0DgUegxdp6jTYaeCj78N3tc/w+3\n0E4DJSKUsYnLGcr2qEmHwdkBtXadRjtgPp9hSnC1jbAc/LBOMtfYjiBPDNE0otOtUekKyxYLv4VZ\npEdZUiEEOLaLJcXCLF9WVCzSpkoDlCVCKXSeIe0FENHCYEsbZbs4laAqC2z3WRKU41HmKQhJHM9w\nAh8XG+U5aP0MVAgPgDTJKatykVKWFAspYKnJs4LCPEtOS3MMJca2kUIjnzV2oyuyyiDKkizLsaSL\nBrTUOG6AoaTISnzpkBclZZFijIWy7AXrUWlc5WBKjS7LBfC3K1AWQj0r8tMasVCS/UqW7VmIIqUV\nKuY6oWjss/3aGk8+aHC4f8Bgf4OVtmL6yDBLITvTRCfQezDGr0kS3ae9BuHlIaNqH71lQ6LQjkVe\nJNz//JBXL7fRyRxTVsRFQTotyCILP7QoopRokCOMDcZGVJJoH/JTiWM7+OMV8umc4kmAERlew6NN\nQBFNsYzEtQRh1ub0Vh+sGL8usaySWO6TZpqlawrPBmFN0AVYtZDtl7aQ0uLwbEQ2jdh5XtDcspkR\nk5ZzzDDFIFjfrnP3sCJKJihhWL7sceWtBq0lQ3wyxZQpRQHJsCAvS8qjMX5Ux05nVPac0LbJhUdn\ntcnyxhrbKy06bkkyjNj/YI6/skzHr3N6Nic+KegstUhJ6Q8G2DKgmLvUgwaWtIlmfTpdyfYLPvXQ\npihLsuOMg3iAwF7c1JgWqMzm+BEkQ8XF7jJJFmFPKrKRR1qAcEOefBwR2haNzhqWbSO0Js4z7FQt\nRKq2jXFdsjwmTNooHZA/nvHRBz1uvJmzxYv8s9+/y//8juZ3pKE04GExHsLYq7BDOBMlLxIsjMDM\n8DuC08clOxc1o1fOOP7+Ke1rF+jelTTXSjY3Be45weq1khdfDlgRx1hmiXNK0RcF042UteVVkpnh\n8C7sfRCx5m5y3ABrSUB3xjB7zKaq6IwabHWg4QYcbvQoz4WYDzW28PCrNlFWISJBd71BWQlmsxil\n65iy5Oj9NnZ8nrJXYyBh2luhPFGs6POYuMboqY2uahSqwHVCXn5zDTuw+Jvvf8zD0Z/QOj9GezZp\nZfPw4YiDR/coygCr1qRR3+RsGvD+nw750ffv8cZvO1jOMooalvBZW17HtmyOP5sxOpng1j3Wbqzg\n6w36d1KiJ4a1WoMXr7VYWjVM8xnlUcTass2vAmhUJkGYiFmcUtGm3niVaDLCFkNmvR6jIwsxKdBn\nAclwjXhgs//0EctrXycym0SzPoPeCa67RthdJ6h73Hzj24ROQdeJWdvcQooE15+y9kaDPB1z8KhP\nb08S1peoJS8RqoJpPGSYDrgzucfzz2vq6yEdv46wH5CnIVUxpXd2ATe8wLVvnmfYGnP40/+JC+tv\nEFRzqqMeYbFMbm8wC2ZM533+5id/wWsvvUq7XuNpz+O5znNMfZvCq+NXPioqMGqOV3c5iTPiokSF\nDqWeISwbmRlkukFreYn158esvJLjXHoPSz3i8F6N0wdtTj4HbTa4uPkNljcKtl5RrN34nHHxL1ld\nn2Dt12kctbHKdfLxLvbBABP1iISPq5pkucENFZZTUlUZtbVD3M1bWOtTghy8MqUej2mdatLRNvV2\nRqnmpOUBxgzYuy+R5hWG/TOGvQnN+dc5/nCX61//L+i0fwPUZ9z+8CHNssXOzhaV/j69D7rc/VGX\ngw9fYvztK8TR54Q1zUh8Slb6OFaG1fwE6ie0Wgp55x+SzUMC1mlnHVrbPa784eesvSBI9QnLH5wy\nfvxr1O3vcPrZn7C0bLF7MMcy6wz3RrS/0SQvD3EtQVwapGVxsJtxeubRXW9xFnuU+Sa7txKufGrR\nuqHoZzFFaHA3Qi6/NePhfUV+usP284bX/+NlvJ0Zp3pKTYJHjbia4TgFZTXlTCao1oDaakCxGTPc\nbdIZthmlE4JUY9mQ6pRZXC5CZqoMkWdk0iBsyWn/lEl0TIAhbwrCRkhTCIyusNrvUr/+AO/3BWZL\nI60eNk2S4imlKsisCgqXSZZwNrmPV18DeZf+SY3tC8vUu5dZ2j6lefk2U/k+Uwa4Lrh+l5EQtJYC\nWo1Nsuk1JtOPCYICrWo8ujMn9hp8+jaEo8uY+YyhEDwubv1Cc/5LirYXfotnKZvwjJMwRmOEeQYq\nnnVlVAvjLPD3GQq+kFGJL1OqYHGxlKIyAIv4zy/AyRfyqUUyVfXMYGueMSMSYwocW5HlGUrDLJnj\nBwHpPMJxfHRV4doLPT3GYLmLw5fruaRZRi2sk6ZzglpAaQTG8ZnMMyoDtnIXfR+qwnI85sUcYRSz\nIgNtaEnFRFe42qVk0ehtacOUkjhJ6Kgm4zKl7+QIT+Kh8QoL3/eZpDOC0EdnBbbrYHSJNjZVVrCy\nukaZ5RgN8zQmSRK0Ad8PF+lD1SIti6rEkjZYevE3EYv3veaFaKOJJjEajZUrWq3W4n0UkjRJSLIY\nJSV+njOThqqquP/wAQqJcBwa9SZmoZonSSZok5Ebgxv4NNsdkjwFvZAspUWGEzRIixkWMcv+S3z6\nkzNufGOHsZuwVheMRxme66GMy3QyZHW7zbifIhVgFJYjFs9RDlBJB12leFYdK9DoSmPZCiMkWlbI\nZzIobbxF9p7KobIotUJUBrTBERIjS0wl0cJCmAqh5TM5k0GYRXRxpSuqqqQqC3SxKFzUuqTSGsdW\n+LXGIoVMVKRZiqNstCmBBG0W/iRdFchnHqA8LxaPqTU6T9EIfMehpMKpFEYtGEEhF2xgox6Qphlh\nLaAoNZUWWHnJaDxbxDpbzwRXQmI5NkIo4lmK8haMn20tkreqUmMrjSkFWDzzCWm+CJv+Bbt1/q3X\neDxlUIywoxnUweqsUxYRlVtijOR0N2G50ybLDWmSMD2YsLW+iopt5plmVhh2XgoodIVyNNrNCOt1\nRsrQbAZE/ZTR3ZSWVGSeQKiAPBPoSJPOKvKzOVXmELoOiIC6a0PqkPczErOYv0YrZDiKUF4OeQ4Y\nZKWQcYBAceftnFa7RWunhStyZsmELEoIdhSW0Eg9g3lF4PiowGVjM+Rwd0bvxzGXrxiSxMHEBWZJ\nkokpslBMk1NGxAySFMet43Yd1s/V8MIptlPROBfjrCj4UcX+KAbjEOURu7cyLp7zwHaYI4jnOe6K\ni91I8NoWz7+1xt4DwcHBnOlHKSabYlPDKi18x8aYmCwv6PfmiIGDb3mksmDz6jZr1ydY58Y0bY/J\nvMIa5USTIXvv5bz01UuYRHG2m3Nwe4ZVNknrDnc+7lOvFZx7sUPoKAaRpj8YE5Xg10LyVOBaOXWp\nmaUJH713l2pWp74dMB0WuEIRHwkGY031kx5/tdbnty5c5FtvvswnzU9Qhc2arQip8LsKj2DRVWLm\nnCFYExk/Gme81OyQdIZM5hZRPwZl0bko+fZvv05WjtgPHnF4dh9Wp+RFysPyiKv+FDNvYKFYsj1y\nt6C2NOL5myt88k6fT98/5flqCastkRuC7uvLnK/5xOoQuzRUImMwTLDMOdphDXulRjfMSaqchweH\n3L8b0bwoWbnRwbMC0v0MMy4Iy2WOn2bYRoCxePizMdbsDO/E594HjxmkHu0Nj+s7HuP0mD99+4Dw\nYo/tV7c5f3OH05NH2C2Xr/zDLcJgh1e/2WC+12Dek2xstPDyGsWRpk6XUT9BaQfLsrl4bY3sdMbD\nu6fYxlA79ChXu4yODPIkII9zgkaL06MhD975FLebsR4aWi3/V/JZYWQPLSTCjjGmYDJ2EOM6Z48M\nh0+GMF2mPLvC/j3NeJSSpyVrW2sshVdx1Tk69RnxlYqi0Kz4y/iWwZocoWyF3W4xKn6EtdRn5/kS\nrW7j06f53Cr56DmmZ02GD5rER4qN8msU3u/idP6cWut7CPddDoef01k2zNKEmjnH1QvPYfkVp8cf\n07iaYQc548//nLPb12nlv45TDBA1QxUvfJhL3Q0+ufM57VqbZfsKXpGjyoSqyhHhCCMKQt+mLGLS\ncsrs2f/7VKf4jsMLrzzHyWGCXfuYjVdPsS4dEFUnMNTcemfA2YMCJ3+Zaze+Rn0twV+5A90HJI0P\nUfZj5qcZ7UtdassBOpPMpj2C8wGZkzF8p0YyLFCmgesV9OOUrdUV6lsPiOUplpFIR1IwQtciakGN\n2vkRjr+LYUAujpmNR2w32nhEXA8yHt/ukz/4p0x7NUR6i3PP3+B7P7rNxc1v0H90gQcfpKSmS+9s\nhQ8/OuDmV/45P/n++9z8A4tRdopyu6TFgNKAbTS9/gH0u3zwwQ+p1X6Hvt6js3ZAdXGOOn+Pp3qM\nNbdZr93gyssOD25/wNvfneO5q6h6wA++N+E3f28ZrU6Z5gFupYlSwTQ2jDOH7hXBjee3+ON/cYjU\n6xzcj3jnT4+56Xp0X8mYTiXx/Bi/LlhdMfQe3ea139Xc+LoLLpAJRsbGFpI0ndMUZ2SpIEtdKrHw\nUHY3YSojPNlCFJJkPmRzq0Mv10TRmN7pHO1AKG2k1WHa6zGca5TlIwuXbFjSsGxWtwqC9YCqvczQ\nvcdVe4/NpReY5zWMvo1lSaIsZTIEF0Mysji861LM6hg5ZzorGEzPeLU7oLEyINN7aDHGyULSPMUK\nHDrdiNorMHmr5OCzXXh4mbNji/aVGlHP49XgRVxxwu07h8RZxfH0jCT7xUIjfjmgIcEgwAikvbh+\noX36eTLUz30WX36Y/B2gsYi9/QKgLFKmRLUw3qIlUv78MfQzD8ff9Wp8cZjGfCG7MpjKUEmNxEJK\nh1kcEy6H6GSOshRFVaKLAkdZCKAoyoXcyPcpqgJjSsqqQpYVutJk84QwDDBas9RdojfoUcRzDlJD\ns4SjsOJCs8ve/h7StemEDcgzjDakWtPEInYFbmUzIKce1jFpiiw1yldkoU2pC1wpiUYTwtAjmkxo\nNGqURUZqSgQsYjuLHNuyWVlZYTaLSdICYzRlsehIKI3GQqCVgUKjbUBJ4iJFVBXNTgulFMPBgLBZ\nw3V8anUfKV1qJsR1XfqDPt1mE601Qc1n2OuTJile12EymdJcarHmrhJncxpunSiOyOOYsNmgKAqS\nNGFz+wJpmlELPUxWocsx+Tjhzl92ufGPtymyBq32nDw26DImaNrsHZzRajk0/G2srGTaiyniBLcK\noUyxMhtVFAgsOvUOVZmipUchNbY1QdkJCIuyUtilRJsKWRoqDMJoSilwFRihqAqQWmLkAgDYahG3\na6kFu6aUoDB6AQ6kRGChPAeqikoXVKVA2jZKqkV6FBJMSVkWGMPiqhcRzUWRL2bEGApjMFW1uKNb\nluSZWDSU2wrLsjCmJC9SlAItDZoFkC7KnFarRRxn5PkCaBVF/sz3YZBKUj5jMLIkRoYOUizM5bDo\nBJHKWrCNcpG6peSvxgw+H6YkeylZmFFg0Qkd7p7OSApD2Gjw5M6c+bjCDyLm1RxVCzl3YYfeUcx0\nMKMwNl1njVHvGDd0qGYlVtJAZNWCQRwNefpJxjlcVLdNYRTxoSHvK3QVYlUe0ghc35DmFcYolDY0\nm1vk2QzdzLG3EkwzQjgSkyssW9L0GkxHJfEEJr2IF1++jFqzSaYDphOLcEViu4Y0m9BwXVQFyaSg\nzDStboPT3ZgP7z7ltbdewWtIlJUjg4xGy+P0IOL04Agr3aKz5iPKimk6IU9KXGGj9ZTSmlA6Dmo5\nwOvBcs0niJYYjPa492clOze6SM+F1GCsAm9JY6/MMZWkntqYPigL5mc5cTSn2Whhsgrbd9lYWWWI\n4mxP8fhhn7AmuP5qh8alGUX3iChmYTTtemyutfnkb49p2RfpdjboPRozG4XsbK2TDTz6tw3dmx2E\n8BkXCUmc8ZXfvIaJHB49PePocMbFKwGNDY/JJOekt0/NXEFIzerWCtP+lLzISeYON9e/wn70Lmn5\nARtVyOsOfDzMeU6EDOKUKx3D40bGEI2+7/Iv/mTOP/mv1njnuzMmr1WcfrJMT4SIo2Xmo4Ld4Zyb\nFy0cv8H0pKC21EEsw4MHt7A2bZYCh1gNSIRBOzMEU6692UZYht37HuP9kumBRXVmsA4lrcYSxy+l\nVD0Lzw+YVimH98YEowEnZ3Pa0kMVBt9SnH/5BWwrRYYFg3xIOZakSYEqJGEoKEcx86jHPFIsy1WS\nicPsUNOfZNRaLZ5//jzOVLK9scTJOKJ1SeIszZhkEW6Y8OIbqxSqZJqdUVQGdd4nO00ZpglX2i7X\nXl+hN4Kz3pBrF84x2J+z4zSxOiFzS2ItN/BUm+SeYu/2FHoWW1Ydafl8fu8O2URyaR3OluDwvf/v\nEq7/P1ZGQZH8GpW4yzT9hNMHFWcfBaQPrnD69AXGp5rpOEKpq3Q666ysb7N1cR3bCamteLRMg0DU\nGAyOkZ7L/Cwj699n6fk2XqOH3PkIa3sfe32JlE+Yzh+SyYCKc+TJJarWGqps0K0npCZl5n/IrHiA\nm2WcO3eBaCToiNfw3BpltUde/gycHbwtF1V/imteIDlsM+1NmM8e4VfLOI2CaTHjZBrjWTa2AoqE\nDgG+9pjOx8R6TK6mjLMZw3RG6YbI0CMuEoy9kDb/5N2PaNaXubB9gPTvM5tM0YXL3nsu0W6BGF5i\n6coV7HCDmb3L+tKAIviIs9nnZECUgWqmWLUxZArtJYhGhH0G2fsR05lDEK4TpyFKrDJJYwbRAWn6\nF8wmYAkfpI3trVJzl7CwqJgwKe7hWDGlm9HdXCJUJYiMr3xjm32Z8ZNPf8Tr/8kLzMq/RM8v8/lP\nFWl2BIcdfvreC1w892v8g9/L2HCv86N3En74r884/9YhqjVABZL5tIaoKgZnM5yBZDKcQBLTjx6C\nOuDk3qtYf93i4q/3WV8PmVRnvPKHfeJ/3eDhu6/wZ//rEXY9YdZvEvy+otQjctWk14tJS0GZB1j1\nlG98JyCffcq1/Tkf/ysfVS4xPU3Ye7yHOWcxKSUmbdN7mjEdTti5vMK5F0fM5YQykziuIR1YzFVB\nnkFuMrK5hU2HwaBPaDWoeylpJkkmmnxSYXKHdJ5RJQ6OW/btWY8AACAASURBVGcQ2YyPB7R8lyzt\n4eaCQsD+cMR4liGtJudW6/zGN8+B0+KT3VMe3ktpbhTMyofUd1yazS5HZ8coW1BkFpbukI5KosNz\nDPbWID2HH+ZI/za96jOK9BZ6vtiXriqQZZeqGBAGHTorTephztnekNl8hhvM6Y9KXr+6weG9Q372\n8ed0N88xdYdM5AQtJr/QnP9SJw9dLUq/pBQIo1gwGgqp/j7z8EUfxv/TzP3F1wKYsPhmFoDDaIOW\nf6fk74urMV8+v5AGjMbohblXIDACHOWTFzkGyEtNlmi0cJC2TzSbU6sHFHGJKSukpVBK4Ssfz/ex\nbRstDZZjkesSTzk4rk295jPqx1hUeEpQrwecTmP8pSaOJTk6OeLc+R32j3YJ/AbGtbA01JCMapLV\nGIpmDSYxsmWRGIXwF30dYhDTqdVQStBs1JFS47l1bMvCthSteo3eYEBnaYkkjp8ZRnsUlcAPGwij\nibMEW1mgF14OoRRS2hgqlLTwfYf5bEalK87OeiwvtZnMZlhNi/k8Ic+mZFWOJRV+4DOLY2zH5vDg\ngFazSZ7FRNEMP/BJk4wsSag36jx+/IiVjXWWl5fYPzpkY3sd27EZnPbY3Fgnivq0mqvkaQ8pJ/Tv\nXiednhG4LjlzcjliOh2ztfISO1uXKOMTfvYXt/jwh4/JziTCuJRZgd9oUG+0yHODtGyKKmN78wKV\nm+B1UyovxXZTtDhDUEeXXZSbLqR4ZsFGmHLRCi7KRfO3RGC0wFSGQi4K7ZKqQhcVVVUhqmLRX5Kn\nVM+YGiUktvIwYlGomJYlgW0BGqOrRVeFFlQVFFlBVWksS2HKgqIoqAqD73qUZUpVGpxSIKQGYYEy\neE6ArRYbP05zAsemyMD3AkaTGCEWzISlfKS0yPOKNElRlqDSFZ4lKYsKXS4S4fJcI9UiOEEKA8Jg\nWQ66rBDq57P073Ipo+j1EnRYsXq1RZGHHHx4SqN5lbbVIupPGQ9PON7vc+HmEis7XQZZxCQpKTKB\nlCEiahNEApVklImh/6REFR5aBCgE+SDm+JaisWlhhEV0mhNUTaqpQlQOWud4gUWuCwJbgBQsLS9k\namolYJAek22N8DoFVkOR3E3p385R2QrQpFNvM3zicf/jfS78xgqZaeG/4OPKGdNkTiygIR2UFbJ/\n9wjlNGmveLiVptbqMhnGBJ5DduqhpCaKc7afD1lvLVMe+tz9aM7odo/e04JLN9YwhcRuBGRFxWBy\njN+oc/HqMnVvlaMTh4dPDnn6gwQrFIRtTeeKQgUxE2dEQYl7tcXVekB1GLD7XszDjzMEY9qyi+WB\n8HyKkUvn6iYfPz3FDgx+N8TqaAKTQzAjnVXMC81Kt0Gzyvnsz/pce2GdcS8gmZUos0IVKzxvi43L\nHdavu6TxEfW2wvUyqq5An6QMj6foRxHXn18FS6OdGKUKiniE7bY4Oh0StALGe4q776Q4lcXf3FBc\ndZ/QOG/zUlmy7YacGU2flALYnGwTvXuev/5vf4j7g3Mcpgbn+6/x9P6A6+3naco6bTxODkZ88mGP\nV/7TDYbjiKiYkjw8o9Az1gpNuDPDtQWWrajiEVE4o8EFrtzcYrbb4sPRlPmxxFEust0hnPrIfknq\nKR7qMbqq02Udu+xylmuchouYJjiOxPMMjlURLilmpzCPEgJH0XLAFpJZEtP2mrSEQYkW9/spep6w\n0lrG7zRYXd3gf//TP6JrOWxclSy1V7DbLk7tlPXLiu2NAUaEPNEDhqFh8HDGMKi49MYmtTImEWOu\n31xl6LhIe86n3/uQRuNVfOFjnw8Rlmb6UDM+mqHKDm7kMZSSUsxZ++o2V37XYyfsc2eyS1IE/CKN\nv/+2qxIDwtBwOjjj9HFC/y7c+xvJ5IlNlrbA6RI0d7A9h+Xz5+msrVI0P+bSGxHKrKPsFBPnNAcD\neoenDOZtBrFLeXiX8IrL+vohRX2fYXmXyaCPZXu4jsKpTWis3iPeuE9vN0NV79ANLFrBCH9ZIIIZ\n8ayHZfk4do5odTHmIXm8Ad4euTXFnb5OOnuVWaKYzk4Z9QWt4IR42CczCUUaY80hlAqncum0O4QY\nxmdDZsk+pq6x2yFVBb14StjykG5A6DgU0iXwFOQuZ8czwvdCti+0+fj9CXc/dShSw5q3zYWVb3Hu\n+W0alz6ic8mwcn2H41LT27uNLZcYTSe0lnLmiWKSC/Tc5qSXMxr7ZLMaIlik2p1Nj1Cjiv29E9oX\nnpIkUFUC172B5XQohYWlbRzp45gWRkvKLED6YIkD5mYGZsYf//k/57W1mzTtr/Lo1iscvz9j1Dsk\n4i43v6Z489suL3z1R2xvRKhsxI8f/4w/+z82eeH0PBfevMP5Vyo0EaN+k09/2OTR2zb33y9Zb+xR\n3674nX/yCkf3Vnj3j3fwnKe0fjul7E5Yeh3eCi5y+7OnqNMXmQ5SXvyqYJx8QBS3OY6GmMTGaEle\nGGrNEtc7ZHh2xOXnXuHH4ghHtjk41JyfrzI862Et5dy7dcLn31vhyaeab32nR2elRZFOFzeqYxCF\nwK5KbHuNaT5nMJ2SxmckT0EPR4x2Baa0OHg6Z+teQrgRkwFVXlIYi2k0gSjk6eOIzWVJMdWMz+aM\niimRmXNlaY1G4xZvfqdNVd+g+qjB8K83+PCvVtmRI2pZj2BbUXPrjIcz0nlOq1ti2wHLy13GS3Pi\n1RF6tsrBnmb1cY/WakDWS7C6htJojH/G6mqXPIu487ZLtv8qV9a2+Hw25el0H9+LOJwG5KcNGktd\nhnmfB6efkVQDdJn8QnP+SwENZS3iQeWzZmOM/KLI++8Bg5/7Kv4+yPhyCTAs7iabSi5kV8YghXrW\nGcCXbMYXzIh5VnC26E5YAI4vejSM0Wij0UIglKCzXKez2sQVIfc+u0NVga0WEaGqUtiuTTxPSeL5\nQuZVlgjLpshLlKtQ0jCezSgEpEWG57rEaYLnuNw9PeDFsMPWpXP0Dg54YfMcd8anbGuXUkFmQWeS\nceppNkY5ka+wkwyT5TSCgCgrUTWPygaT5EhrIYHSuiJJM1zf5f79B9QbdaJpRJzF1DyPTqdDmhVU\n2oAlcCqJkQtZTEWFziqULSjzkkIImkGTWRbjuB4XL55nf3+PpdUV5rM5tmXhOQ6zQtGuN8mylKLM\ncF2HRrOJazsUSUJ3qcN4PEbYCs8PiNOUq5evcHh6RLPd5OLF85z2ThZSLb+FYzso6TKYzphnM5Tj\n8vD+Ia0fGG7+3nWi6SmtRouGd53HH93l3ieHPPwwY9I/ZbneoRM6VFXMysUVJpOcVtMCAtI8Q9gB\n/f5TLMcmm3t4jTaimuM3ZqBSdFmQFRMsy8eICiUXbI+gRCgLZTQYa8GmSQNSLhpljVzspWegVSmJ\nsB0qFgxAlmaL/YXB9T0Cy4Jq4dsxQiDlImEKFuV4xbOG8LKoFvOCIU7mOI6F0Yu9KrG/nJgsTyi0\nwA18LMtedGzoRSyu4zhYtiDPFgyWMTZFmZEXOY5jLwziSiFY9HnkWYXru4DAsmyMkM+eR4M06L87\ng/8Ol+u4KFEnmee8/UeHNFZ8Wuoq5197jukB7N3fo9mp89Xf+TWu/sYKo7jHydGQ/klCJgpUqbj7\n/SGb200GeUGhC4aDEscKMbLEazmkM81kUDCbVBirwMwqAl1QloLQk5QVSFui7ArnHMTDOWnN4K84\nnJzc5+PZR7z6yjI7LwRcFTWOXir5V//jbZoDn+ETaEgP269RcxvoCRROwOA4ZZ5GaNtFG4vxKKX/\nqMCtNQh9h/7hGedfbXJwesTx4ITOgcXqlSa6bxBOk4uvL0MSwwXJOS0Yjeo8unXC8Wdd2tebzLIB\nERW9NOPF6y26G2AKzabbYjYtmBxHKBXAGOrCIZmNEJ2YedUn8DOsdgMzL6mdd7D3DeNRzEbZJR2n\n2H6AwqLebKLCHolJGM1GuCczxutntIyL6lr4/ZAIxXLzHI/u5zz6NCXzfRKT8mi3h1d6vPyVG5Ty\nlMlgQm7NcLwUY0E0TQgDRbXepe27jCc2jlUyk5L+aBcraVGc7DE9iPAuNRj1Yj74bsZbF19k8EnE\n2xv7rDeaPC4m+O6EVGTcAR7+TPD2f3OIegjL/Dq++S0avT7zXhvnnqbqdomchG988yanJz/k//pf\nPqJcSqh2WszLGbOzLt3QZ7lw6XRCHgw+5GQSsbossHTOXN5j+PkQO7zMuctLRH1B1ispRxm3vrvP\nTXOOzPKYVyF5LDn5GGqlQM195nFOYWy2LtSYZn0aToZnLHa2AqQTklclZ70zLOMiS7EAI1WLcb/g\nXHeDfmbz/MuX+ezTXbqe5GtvXSM9mxHlfU6eTDFVn7cu2GwuCbzJDOyItieYL9U4SmOmT2d88z96\ngwd37jOeP2XjdYc3tkLm+4LwJwpLemRjQ1N59PYGFE5JPpKYSYblujQ7AcaPqYRBawGzFs1oxuoV\nl18F0JhGffrjv+X4wTFP34W9jzY5efIcbvUqzTXBytJFOtZNyvCM5YspOy/Y7LwoWFodU9cepbfL\nNIlp9U8ovm+zf/8cK+vnSeYj8vKYjIhCTLFJcesNLO1gSwtbVmTqCeVSD98FR7YQ1WV0VWM2ixBF\nDcddBuOh/D5C2Oh8ibI6pkoyOsmvkz59ldvfPyQ6DEnjOoWtGBQZUz1mliUURcrVznkK5WFnBY6q\ncJshbe0RTTRZlnB4MiIyFZ2NHeI4Q5cFqePi2k0sPyVKI/Rkg4PPupx8lrD3RKK8bUajEbUrPtng\nEd2NHval/4G0EXOSxeyfwmQMijGWXeKn0B9VzGLQR5rD24Jy0sYPthH2DONUxLM5Uc/i0Ye7XD8v\n8NdB18HSdUxmKO23iYXG0k0KM2YWD8mJmWqfULap5d/Bkf8e1d5/z+VvX+fgZEI0ukXTmbJ70OO3\n/stLXPnNnzHlh1yqOZzpEseRdDdXuTL+PY4+njEc/DVe+B6yPsAOQDgCx26ydcXh5MmMtaWIb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hUXDtjsOe8wXeTRqI6JTZ2QJ/YGC4I5K4xnc9hGGQVBBGMYG/QVO9hsJCmsdkeo5hh3iNHEWB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y9fpW6UXAxmhKGLLDTWuzvoqs4suUQpDXTHxqk0yaMYKdMoFJCUJYZ2NplhOToSOrazpDup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\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ogrtWxIkjiqZK75NbLDbLjAdTaq0aA2WMhkKmaSBlBEGCKsugqeR5Ri7JiCxFCIFp6mRp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WpmBvT+zs+KkFtEBOh1HyEs1LyGUnjIWHjyPuV1WHrapvogQ/F3eP+1GaF9j4fLBqVWCUUt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\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xOMHBIB8lRGZEnGnoQhANUjRhcv7cAnZpwvVwk5JlkaUZQrNp08ZRdpl5ch6zUOSks83N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\noz/fxEvGqR6bRM0VENoehgqt9T731ppsXz1AcYvkrDKT4zmOHspRKUx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WxvcVdAOWFhRs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TzKdMOm8+WL1F428Zq3uHNzh6mzaxjmder+LpppIVWWaASzUzn67QyRvs2mdgvLTEjL03hBjnZj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MvOl9ZvlSOZUkKCGDkYDBqgc1MDQdTGN6YiCaYJgGAj+mRUAMIZxQC4SRQAjZUjmVzarKSu9u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2pW5cSjOfSLk1zfTJjrpbi+cpPlXsDak9sU8jW81CRTjyfMH3aIaGIIk+L0PB/+l7dR+ZzN\ngb/4KINaxNraNsPQRzENSimD2WzCofk5jk6MMHdYsHHeQ9iSKy9e49HDxyAwiVo6B2+zieKAv/hy\nh3CkxtSd00we8/GXdcytE2R9WHpOsmH0KYyPc+8H5wlTEe2dGyyv3eT2R47jV1qce+ltFu6GCJ2h\nOs3JT5xh9Mhpnv0vTdZf3mD97A79mkTTDeJTLaKwytHjI9jHRhjsaFx4IeaRf3yC+Ts1Im2Noerj\nRxGdRFAdBLTjBG9ywMc+O4tJwlUuMdwJURpl/OoYqsiSLpTxBYSWipIdkjgtfG0P0/bRhU6kB0SK\nTt+NSBSJGhgMex5RX6JmVMambVJS0B/k2FtzibyYdCGNbcaoiqARdtALgmHBo7ORUO9VGJ8q86O/\n9CFOjM2xfqHGq5eXefToCONHZ7h4ZYVWpU9zM+HOUoMD+v/N25sGW5Km9X2/N/fMs2933+re2qu6\nurqru3qb7mlmg1lhBgwDjAyEAIeNLWH8QSE5JA122Nhh2aGwsBzINhYIz8gMA4iJ2deeXqp7pru6\n9qp7q+6+nnv2JU/u+frDrWZAXwCFh/fjycwP57x5nnye/G8ZJp5+noGR8Pr311lZa9Dd7aFJC6vo\nECWCflshDWN0WUBRFHrtAF+6REAkDdyhSnPHZyxrEA4SEjHg5LkKx0+PcfetPVqBJDumsrHaQPty\nn9qJDq4y/AvPsh/u0lIdldeQtCjJy7TSE6SpzzDoMJIhgeKRKzapTmcYxOsIxWTtrsc3Pqsh9qZR\nZY2nL17g0tlJHGOdZtRj0niOSO5TqDbwul3U1MBtLrF9rcawoDLoKFSn64xf8JDZBkMOSWUC4ijd\nu+e2SRIf2wbXSxn0PJqthOXv6Lz0GZds73lmK0skvo+ll+gN9rh3f5uPatMYcpyQgIAVckwzNRZR\n+uBn2RlOYSkTKMU8Qrg8/VPP02/O8+q3TNpbPeYvzkFcJ0YhRNAdZblzFUJpk52MGLWKmEpEqfAm\ndXGDlEk2lw2qtSze3iynimcQ6lvMPdalLscZXbvI7u0ht76i8vSHHqU7qXDjzgZaqUFl9j7nP5zl\n3HMZlnshhmozGihMnrvPwmQFIbvEok9vb5/h3ZN88OTfJ90vsDs4oDzZ5NSTGnpR8u3PvUrtwdMU\nSk+gL3wTpZqjZsHyVpPv/4nJpedPM//82/iZFRRtDmdhnf3wBsKeZ+AmbG61KbmSYOShhBGqouDo\nFqZSRO+leDs9cqqKYqSUcyVQE+JoeBTIp0Bl3kK0BFFPQ7EmGeguPjZRsUCn/oBRmDJfO0bQTRDC\nJGdYRDJGBn1MLcVIjp6nIolIEg9NOKiWRQx4mmSv3yZn5NDNMfxURws1cukUeiTQ5AFaZo3QHzC5\nkMEbrFDKDtHCiwSDpwl3IrxOC13RGMg9Bm6EFC6GBvq4gTuImKjMIweQJB61msNTL55i4mKW7EKW\ntKQSiz5O9gSj8AaG0WHarmF757Ht0+wOvkB/pOE3JrAGs3QOsmwN3sI2LYb7EitjIcwQd3DA+FwO\no2iROENk6mPpFolUGPhF6nvzxLtjTPZMjMkRZj6mudnEP4xwd2vUd/rk1Az9jTxmaKHldhgETaSu\nk4Qmbu+vp/tUP/3pT/+VJ/3mb/7mJPCfWGb2KGWZBJlGfx4YZugS09AQHIWkqUiiKMVQUiRH3Pc4\nkQhNI0WgCYGZzpKmQ4TUEMY+ioCMXaMz2KKcfYQwqLL2wOF7r6q89uoyq7tXiZIRqmah68WHQXou\nQttFqAVSNaDvDUiU6Mj+UzPIRDHFapkrKzc4d6yGqhgEmXEesaa5Un9ANjPOXGGMYbrPuWiS2qTC\nEnnGZxewNJ0gGOGGHqppEiIwhCCKYoRMUZSjhlV7SGt5p8F7Z71jV6roBqYquL+1z+WLZwhcl3OP\nPMbaxj1SvY/r+lhmjmxmjHJxCssok6YKJCr3V1bI5R00PcF2BAvz8xiGw9mzxzl96gTvfc+Pcvbs\nkzz7zI8yPTvL2GQNqaW8+OILPP2uZxifrmI7DuWywLAtwuSAg/oWSbrLrZuvMxiMmKo8x/5ej2Kh\nQrMZ8p4fvcT3Xt9ibavO0PUpF2YYDBz22hGBlsOjy85GH9cdoqBi6SlJGHDu9EVct4uiqEgEx5eW\nePyxp5ianmZ6/DFy+QLlwgKq4eJYFXx/n/X1u7x54w1OHn8373v/T3LqzBxSDmi3D9lcXmU0clGU\nhJEbE8ddqpV5Wu1dcrk8b159izfffhvNKuONAhzHJJVHOoYj2YXycBfEw5i6HwipU3lEqzoaOxQU\nRUVTNIRQ/tJ1R3t49NnRxwJNgWFq44UqnhQMEg9X92kEHcz8CNs8oJhe5Fv9b/HF9huoTpfLYp4/\nGH6JUn/AaMLkx/VP8o3gFeYy52mbe8R2nkWRYSVtM6PkaZgSXTEwNOVh+veRWF1yRO0SQnk48D68\n1x4iNe/cg/8+neqdcyQpYeQC/KtPf/rT/79H/75TJ576+ByO4uGoBnc3WlhyBr2xyO6DlHLWQVFc\nyhWVudksz773JPlKliuvvMbSRZNLz4U4DujxiJiEliLoMCQvFITscOB1CEWN7oMsuw/qnJt9ikz0\nKMryCa50QmZ5gtPGZapU6WzpvHZzA3c0xd2OwAunaZLiyJQZ0eMMKsfDlEDcYif9Ji/+vSKPfHRE\n5pjL7sFNtrYOuXj6JHNncgivTT4vufwjSwy8kKHv0+3F7HcaPH75AqluMKjn6K6bjA7L+B2DrF5D\njEyiQENIk2wmjyI1Ul/gdwTpQEGNTSJdwe8O8c40uFgsscYh65GCI6rceHOTE0+W6HurzD+RkhRc\nBsYGU89lqR1PGCslvPtDE8xf1Bg/reJMRExMSIb6DlphxACfNi322GG9u4qccbHGIQok4+oM0e0i\nZj7LwmNFlp6xGD8x4vS7HF6/9honnxxn9c427V7I8fl5LK2KO3LI1uYpTtjceH2PvWWX/moZa+dR\nNr81Tvf7i7wZRDhJlQ/8wiP89D+7zIlzJvky3PjKddKBywc//giHagOhq3ipS7aoka2WMXMajuKg\n+QESQbO5RaB7jJ0UzMzmmatZVNQCdS+i0d3h5FMTqKZL5LXYOzjkYN1jf9clTBNGXofiE32eW7xI\ng23uNjZZe8Uk3pzDTGsYIkeghiQyIVMSTM5rmFUfP+3iyQ6iHGEUFCJbsn57QOpplJRJjGic/gZk\ny3lqMzaDzpA0TYldQTRKyOZMAnzCUQCaILVDqgsalSlBZdogVkbs7m/QHPYp6A6rK9u8fbjM0Irw\ngoCclkftZ8juDzi4sc58Qaf43pOcOVthvVunm9Y5OOjQ7fmYURnNGCf2dDqdkPsb26SWYKi6pLZC\nqgki3yBwTRAZ+qMB+Xmf8y/kGCYD6gcBhsyQL9rEkUuvtU+73ycjHBo7Nle+G/zQa8XHf96nVE5Q\ndQiw6AcJBf0FIs9miIttnSQOD5k43aG8AAf7Q7butFh/y8aInmN80WRitsD29m1OPK5iZTVMVeCK\nB9jJeZr3Z9m+p4AxwdDNI+MErbTFCz+rY8zuEJjbDOSAkZdHSROitE7X6xMZCfuto8wa2cvz9d/3\n2Xrp3djeGUrFhAvPaJy52CcdNfGjgChs8Mh5Gyu3TzaTIYiXyKk1FOpYZhbNLqNkhgQiIcsAYe/Q\n9iLeemUH6c0RRSMqOZ/j78qQKBGDMCIa1HjxPUsUF1Z4660VkshnYmkPa8xFKLPcuOLzjd8bcfPL\ndylmuvz6/zLG8WcHzJ8+oBfW2e718IZlmg9atJq7FE7keOYTJU5/tM3iC3k66XUcK6DdbCPSGnNj\n82SRRyHKwuXWF1u89rlJVm5B52AZW3U4+UiKfuYW1eMuI/V1BgdVVu51qZXOEwxNDpYn2d08xEou\ngr3OsUd0Um1AJCWBK8j5v4YdXeb+6jUuP3WS762/hrRjgjgkk3foRyMyRh7VD1FwKZZTMqWUWA2J\npE0SpziZDFY2oJgLiP2E7rZONHSIdTByJdCOLIr7nR4ThUmyokROLSCDFFWo2KaDbdnoqUIcJXhp\nSKwq6JU8wjEIlJisZdAbHiIUB5lmAIGqCXwiJhdzyFyEkVNIghTvfkDS0gi3ThE0HRq3FVobHfBK\nFLMz1NtrSNMnUgMa3T5jlVnUyECOIG9mkf6QMyePIUgojdc4ceYYsWpQLuXw433QdpHxkZY00u+Q\nrdhopQ2yhsb21YDmyhiKGFLMPUISpqCFqNaIqXM9CicfUFrwMG3I5xTKzgxJkiVOUvz+iGjvAu7W\nGMO6AoMCcX8crznB6KBKb9tk1M7i9XQQKYlSRxMOitCRiUISKySpYMdb/yvrxN9o0DAsB1URCJI/\nb1x0VUXXFBRNIsQRlqDrKqaukUQeijCIovho0ACSNILEwLT7yFRD0RJ6zTnquxbL9/pY2nFWVvu8\n8VrE9Wt1usE2ii6wrDKKesRBP/ItFUihoAiHUMb4oY8vQ1JSYpkeeSinCvXIZVot0htZbOzcI1uM\nuLp3lR+pvoAd9/EDg5yXoTWpsHx3hZapsLt1m3J5gVpxAVOxsbUUJWqBliVN4iMxuHL0hlw+tBMF\nHg4fPwiEQwjSKETRTXQ1pbG/x+mTx/DdEecuPEIcmqgijyJyRIREaR/VCkgTlzjxmJ2fR1E0FMUm\n58wglBG63iQc+UcuIxHkMwq1qsrji8dRY58MKidnT2FFNkWjTDlfoDvIUKuVGfZNvKFLGApsY4y9\n9reZKD/Oz/+dT7C9f51nnn6Gz//Rv+bk2RkO2116o4CNnQarO+usHmyz3z7A8yc5O38O1XDxw4Sp\nWobDxm1STJ65/BTPPP0s0xMzmFaGzY1tVEUjjEYYhnqkcxEmvpuQJAqTU8d55oX3U6kU8YI6d25e\nYW9ri97uEMWEJAnRjQwjr025OEemoDFyYywLvvjlL7O+tY/QcsRpgibSh+y1d7Qyf/GNnOQhqIFM\nHyIbAlIJQv5grzTtCOA7ok/9AAGBh8gVkEioaAomYCJQpAqJjmUV6Pci6iOThv4Wn6z+x9TKFtr2\niHMnTvFh7SfYM0NeXr/DleAP+eWJXyEXdTievEDByXOj3eZduUVu+YdUA4WAEAXlKNdFglCPhqcj\nd7YfpG68I/7+i+vfp0y9M3ikaUwYjf7KovAfut6pE8++MEfkd9hsNoiHGbbvxmy+GdBvaTh5jcml\nHDNLGvlZiZA+Q6/Pzt4ai5d1nIqHmpXkNUGqQ2sgWXs5Ii8nWd+FMavEUvYEph5xp9Vh7dUsr/xe\nxOZqlURYnJp5HC/1GcYhkarQTXqMT0wxikwymTzTNZOzcxpnJ0zGzAbm+DqLzw6wLzygnXuFtNpg\n6aRFxrLIWnmcnEMcjDhc36VYUnjq6UtMnahy716TJJTsrXcpVWsIKmyuhISdMt09FdnPokY2MrKQ\nI4E/SjAdizAISQOVeCARfgZLcag3B+RqKss3D3jsPafZawg2ribsvZXgWA5PPzODabaYnFA5PFyj\nL/cxnZS232D+vMbcyYjqRJfaUkRlImFiLofvjVDsHOtbLVSZYed2k2azS2UyTz5jUDJ07nz9kM9+\n899xoTDB4x/JcvJyRGlyn0I24P7OPaaOlallK3zmf3qTS08e4/QjC7z88g08t8fUXIFcTaGx4fFn\nn9vjwTcFVe1Jltd1toXgw4++iPUjba6ufx1LbVEsCUbrHlu3dnjyw0toRY2R0WMUBgy8FtkcqDJg\ndjGHVguZPC3R52IKMwmFmk51DhIzpDXq8eBGDzO1KMYm3Y0+92816e1LolhHShPdjojTPmdeiJmS\nc4TGy9zfKNC8VUEMZsiIMUxhYllQLTtMzCropk9quviiR6CHOFUFYVj0uwm9bQVtVMTbUXH3IBmo\njC9WiJPw6MZPFKIBKKGKoTkwFIgsGDZkCzGK3sU0AqambCYXsiSGz803Vhn1YsyaQ07PE/QU4paA\nIczP6Ni1hP5wi51wg7Xda6wO7pKYfWQFUuGzvtKj106QoUVxrEypmkMpC1pKj6EyIlsx0IQDfg7p\nOnguBMQce9xEVjukpopiZLC1LP32kOGwQ6q5mIZGbayCFk3w1S8f/NBrxXs/kjJ7fAZf7TGMGuQq\nBSYqOZrbErdvsra2iaPnUE2TVnOIFuV4+et3Geyb/PgnP8LznzC4cPYSSU9DdeqYRRs1c0gQ5Ln9\nnUdpbc+SNR9jpCQcXzxBvT1g5hSceWEfc2wZYai4vqDdDNi5O6JfV+lGI5pDlX5zmqhT5aXPNejf\n1dm9nWd6Zsj85ev82C9FPPnhBgPjNlq+xNb2gNEgpZI5weFmSMmZpN2uUyo8QkwVqaRIZYcsCtBm\nFG6hZxy2bgf0dsfIOgZFO+bUMwV8+w6KYTA/N8341JDS7DKDaIP7N0e4vXGcmiC0bvP2dzyCBz+L\nsrdE7VidsZMnyU1Klo6dZ+vw24jWPHFngb3mFnpunMsfclh47ybF+ZSefICqbIEMsTMp3a6PbU2i\nqwMQW3SaI179bJad5Wd46t0fp9PpUsmPeOIpG2VuANZNKpN5onTI/k6ZW1e7DNt5SGNCP2Fu8gWW\nLm1jTv8Z/VEbRViEPcl3vuBxsFJHiXy2NvfBCdjcWqGYyaGmEhHHaJGOSD3snEdtHrKTgqFMUA0f\n3ZaUKzaWHaCkAl3NEA0yRIMCYSIJVIHUDYqlPGoimS5O4iQW8SAmb2dQREocxuiphpYKyo6DGaeI\nNKWYz+HoOkqUQBJg2RqGVqSYqZLNZMjpEZrfYLKSJ5Pk2Lmns/P9MmL3DOyeo337FHt3JWk7j4xN\nbEviukMi18LQdJIoIGuWSXsxutQxTQ2ppNQKBTKKTr/eYePeCofrW+iaRBlVUZKEbC5HElfx/BQ/\nqjPqqRw8UJD9BNrniHo6koCJsUWixCRTDLArLWYvJOSPddELKaZSwMDG83PoShVTD1C6Fv3rRZLW\nOYy4QNAK2d2q02oM6PcG9L02lcosplmiMmYzGHXQwphyoYSSqtg2aE7C/eaDv7JO/M00GkKiKpI0\nPXrLqmk6EkGYRmipwDQMpDjSbojURFVN4piHKIggihNMw0Iz+0CN9sCnvTLN7XsH1PdDvHBEyeoi\nRBVf7JOYPeI0SxpJTHOAUDQ8P0JgYhg6KT5eOEBTdRKZYBgOgR+TxjEpIZZlUvY0OqpPoN4lzRn4\noYMeFvnDw89yvHaR0c51ls5dYmynS/XMJTKxpJs7Tqu/zu3G91mYW6B+6JIxFgg0Fz01EYpEpjFp\nnICIUYSOohzx36VMEYqGkClCqBhKTKSZjHydtf0D7q8sY+kGD+5cwc5lMLUpNNNBaCXiKE+vEzJe\nc3DdPnGcECYuuYJDu7OKHjnk87N026uMjVVRlZRCsYI7dLl+6zts7C+jFxwqM5OEgYKnhLQOR0xM\nFUlTBSc/JE2zNA/XOXlyildfLTE//Sahf4Z3XfoVXnr9t/kHv/5b/JN//D9z4dSLfP/em6zsbBIG\ngkuPPc+v/NI/xcjP8NKf/rc8+MYV8qUKo1FC5Kesr99i2DzALleRqcrC4hKnTi2SdbKAThpr5Ao6\nIxd6w3UEJoge1954i6nZLPVGnYydR1dUzIyKG4SYpkG73cS2TYQmCPwIKaHT7bC7s4vQDMIoQdMM\nkNFDDcM7VKIfoEySd1yZ0r/Qoh9lnijiSG8EKUki//zYO8hBmiakUqKKo3FFJaUexKiqgqpIhEiI\n0wBL0zEcH1/body5xP/W/peQppiTOt+91iAw22SQ/Map/5Kv7F7hD7b+BX0t5rSxRDU+wT889Rwv\nuyt80DjDciahsbdB0YCw72OrNqkKUqpEMkDIFF1RjrQb6ZEVrioE0cM08XesbpM0+Uso299WMnhj\neUhhycFPFax0jIw7zoXZs3i7TeqbLt2zFit7A4ppj/2NbVQlYWbqGLV8ggzaCCvFTyUZqaP35zl4\n85C9z6esXu/yvr97hsGPK2xeC9n4XpWNL3rcXB4xIxQKYp78XJ7m8pBW3KAVDdGUANfwOH5hnK31\nfYIxj+XeJrXFhOq5lPyYx8L7C8SHD7i+dpsb3zngz76WsnhsnEcvniKXhe2398hkTGxVsHt4k62d\nBJn6mLZJOqryzc8c8OwHFkmSKu3+ELehYgsT308ZhiM0BwqTDlnHpnnYJ28anHr6DO21gMOGj2iF\nxB2HqDfJ9/40y7Ezz+O/vc6rn3+bH//FJQ72b2DGAxKri5nxOHmhQN3bJNja4PKHnqexvkWUdCnk\nR7Sbh+jaJEaqk+7WGD0Aw8ny1qvrTB0voBSa5CoxETZ7D+5zQY5z/n0qxdI6aXaHnO2RUKUw69Ns\nHDK/MEW9Kfnv/+uX+PnfWOC59xaZnZ5glEaM2uPsXp6hZrXYernGg2VJt5pnTi5insiBpeKUTQoF\nhVQE1KYc1nMGa1d61D5UY9rSGT/jEckNpOszzCyTZLpMfyyP3s4zvmLTakhUfUS/6SOclL0Vg9ZK\ngtJWWL7TZVAfkckVSWYknYaLPaNQUGNypxKO2yk7Yov7/ZTt2228wTjNPQ/bcyk7Nk5VUJ1O0Ioh\nQTBgZ38LMjFWCeJBQtJtoZBjcmKMcF/n/tUGYQDHLxRRhgaJ0NEciecGHDs+x0q9zcrVJrmiydLk\nJCP3kMULRaKkjpFJUOwWg06TiTMOQdNg6+460+IMj77/Itkwz8obGzz3zCxn3lvlC7/7Lyg8FnHm\n3dPc3d4kN27z9ONnCPB49cYuJy9YbL2iEw5NVt7YIFcxeOLDkzx7epwrG9dpbg/ZWemhtRKK6iyq\nqZMzy8Sxy2BwSD7rojltRsKhMdwlW1E5/97HKKuS+7fW+dYf3/tbqRV6OoOpV0lEHU2VeMkKaS5L\nZf49KG+sk01DhnGZf/t7r/Erf+d5XvnqF9hdPc4n//4cH/mZBkE4z/f+bcTalQSZWeXk81V0FgkO\nDLbe8lCGJzh1egrVCWjeOWAkQvLHBInaZP9wQEbPEHVs9l+NWX61xcSsQubSJENzwO0vbhO0n2P7\nRpFessLFj97iAz+RY/ZMSGHyGka+wns+qTK2cA+3q7F+wyfZm6U6eQn37lmKx132nRWyYxG+HDKe\nnsOQfWK1BYpHtbbK2OIkW7cjEsVCl7Ps34yYeX4CT22QmJ9jJMoII8MLPwkH9Qz3HkSc3n+E1E24\n8dU9OGxhzX+Nj37qRXL5FrodEnOVH/uJ8/xx6z473gROc4nyhMfiYz4j+3UO+00quXGghJfs0W/n\nGfZKqO4Mw/w6ob6GHU1QnT3FW4HK8o07tHwXs6Fx9WseT75YQgRtMjmTuRe6+KnH8LVPc/GUpPTc\nPyfJJzT3f59e8wLFziewjT+kP0i5fsVjtvwc8Rg8aPi4mQF3lleYmlxi5DUISFASE02BTDZh4pjO\n7AmNtJTgdwNUXcPKpCRmC9sUYEApUyI4CAm2IgrRcUInILIzuB2TSukkm5vbXD55nt5oSBCG9IMW\npWKZ1DewNYNADWnHLkHUZDAQVNQZ4hgMmaKKAkW7hgxUhCKIE4NsvkzjgYW6ldAa6iThAtLMk4Qq\nRiLJyCVcr08pV+Gw6+KlI2ZO1Njb98kqU+iqJJIjyuUSmuUQRRKpwjBUUaMxHHWKjattbr92lWxx\nh/PvOsaJD+RwpjViUWAqd4nW8jRv/8nXGPR26bduYiVTzM6Xces9FGPA9AmwZgJyC3voJRNhlUEq\nDEZN7GIeJakwWq2w8qdbhPcauOFVTNNm6HbJlMvoRgGtVGJhoYRphGzcv0+7H+A4BUw7Q5IEWMUu\nlfkUVwJ/jVLxNxSDHznaJA+5baEfohsqqq6QShVV1dBQSKOYwA/Q1aPmUDcEsSFJ3ZhMTqPTzLDa\nDljbVFnfvUajOaScz1CqVFCTAm66RX8QIsljGAm6GSKFQxqBZiSk9AizkkMxAAAgAElEQVRkCqlK\nJDVkEoGioqmgCRNVl8gkpBOmmEGILDtk2yW65oj97i3a+Fwee5FWfZuWmmFia8RL7lWOpcfZHW3z\nWPEUpUKZscr76cuUXPYmQ+UQJc2AAnEUowqBoevEKQj1yG5UPAyDE8QgIElDRCJxe11KpQL9tsu9\n9W1m52cZ3QyZmjzO6bMObuASSw+haSycGKdR38TJO8RxgikshLRQ0iwJYJoKmlZA1QoMul367UN2\ntu9j62UsWeLZS8/iuR4yCTk82Kc0XsJ1s0yMR/hdydbGNbK5CoeNQ37uU/+Af/7bnyKO21Scy7z9\n5m2++rX/gl/4pZ+jXHRY21N54vGP8+Zbr/PW2y9TrvxjPvkznyaOt3n0/EXub60T+JI4tJAo+KmP\n29inWKpy9c3XHzogqSjGAF3LIeM8Ug5RRZYUj4yVoVAwuHuzgdCgr/bQNZ1idoIwFYzVqqRE5AtH\nAT66OkG5JLlz7z6Ndg9VtUjiCCFUNEMj9MOj1HnxMD1bKA/D744S399pugXioZ5BwJF58Z8351IK\nFAVUBRQpMQwD3w8QqgJIklRQ1mPiNEIVGn6UYGkWkRvjJxZF5wKdwj0WtOdQpMtWf4tfnHmKLx1c\n4Vce/WX+m+/9Fv/p3Ps5n/9Vztvn+Fdrv01W3+Gf3vgSU84pliZsHm3A+yc/xma4Rb044s291zB8\nE91MMEQOIRWiOETNWODHZBNBW4nI6iZRHKOII3G7QIFUknJE9VPVv5mb9X/ocjcFG3sD/ADUYIjT\nmMMINJJMloO0yWE7g9ccMqoIDtuCeBgyNT9Oe8WlEC+ywSr1CQV/YLHzRyrJyhPUXxJk+0+SfvcE\nhwcB9pSKfLBBPqgwITQgBavP8toVVMtl+jETL2lSm7Pwox0q5RGFQgdjIWX99g2WnhyjtiSo9+7T\nmylTmR/yqY88wu3bs1z5wiaBW+P6GxG3Xl9H4PGLv/ZuHmxc57svvUFHCOZOLmKqWWYmKlz59i2+\n8Ltv8cR7jnPy0dN4xQG9pgu+T+pYlCcqmGUF1wtp73cpLFbY3F5nf3NA3qkwNV0iSXxG9Qmu/I5H\n+X1nmNg7wYNXr1H7zybJ5VfJJRG6Lnj0RJGDWHJ4rUlWV5jK6/i5mE5zn+mpDGkyou8NyGhL3Hwl\nxYwXWd7oox/OMnuyhloPkVZKb7dLog547CMz5E4MUEuH2Ll9skh8mRDoLl7zkIXZMX7qV+f4/ve2\nuXFnm2efXWCpqvPyjTcZdDVEkueT/9X7+eIo5Kufb9PyIzJxSkfLsnpji596bIyoF3NYXyXQRphz\nBa4tN6kKnennPBp+m6iwwZQZYwmF0B4ilSppqYoyrZA2R3QPQ3p1nY21IUlb5XAF9K6BE2TwGgbl\n05NkEkFkrGNlPUZJxMxYSCY+QUvPs3NbcnBNkPQyjI2XqWUqdA/b6EZEu9enXFCpzRssFk+y2z2k\n3Tskk0oK1RKayKCPqwwik+2cSiFvU6wp7K1uE9t9qseKeC70Q8naep/dPcmMzNPbsTHLFZSeRhok\nVKZ0snkVvxgRoeG1E7aaXeqjNa6uB8wXFrjfvcNTcyq361doTq3x5EeXqC0scmgfcuPBPucem6cg\nNIJencTNUrRrFKtVvPqQMVujYBuoNPi1jz3L2s0mv3vzFnurkr53yORkhYqTo33X57CuMLukUB7L\noGUFvfY+pz54mslTCmroMT3IcOJYFb69/UOvFUXtBEG/A3YeKbuEmPQ6XW7d/y7RYIzI12iqPRRl\nns/+0S0K0wY/8v4X+cmfaZLKL7FXfxxveBLTzpOV7yFtu8jqGtZkxOSjY2TDPueOFzj812/zxgOX\nYy88z1f/8HM46TSZguDNGx304Tj9nSp7txtsWvuMr2RJsz1u3PQ5vNajNJbhPb98hp//9T2OVVqk\nmGjUiKWFLdoce3KfpU2T+v3zrN9VmRibxZcdysUXgDap3CCLgSJ8pLQQFMnoGoMoZO5Sn5UH14l3\njnFw32H1GwoLj1/Gyn0JL5lEqhEmk5iZTR55zyHLN0bceeUi3/5yC9l6P6JwlX/43z3Oiad6QMSA\nFjFDMnaO5z40zmder7N7MGTi2AQHGwnuvk2vOcntYUh+IWT23BSV4jTJKOL//Tdf5cTCFNOzl2lt\ndnnztRVSc4KomEe3FBiUeOv6twn/3TqnH51j/IJPJT9PpWSyPfo/qTfnsa03MAo+g515kvASfvcM\naek89cYDOuuPcfPVq9S0MQLLI1eYJOPk6fea2EaMmmiY0iGfs7DHJZOnHazxEaEpUYMUVQvRTYWs\nZWOoAkUYJKqEskJuVsdopzgig4xKJIlHtSa5tXGbduwic1Xibh1V18hndbzQw9ILHBISCZtYWiiR\ngoFNVXPQMMgXLSI/olDIk3VyDDoCxyzTaQ8wsxaamELPTGJnNAbNPrMn5lneWiZONWIri1UUeAPJ\nYBBTzlXpthukscrU9HEM20ZxTIJEMooh6PtkTYug7+LkZ5BhymhH48offRM1GzP9YwsUKmfJ9hf5\nN//3dbTWEs3DlFw5Q5hs8NZrq7z/w2NYhSLZySpjZ/ZQrRJBUkIOyhTzEzhakySC9tUCr/7hDts3\nI2xFJZUrRH5KsTBN56BDbSZPZ7tNUI+pVkZktR7qVMLSI/NYtmAU1jErLhMLGbYOduBzf/X//G/U\neRiGjmkY5HIWSRQjU4VEJniRh+ZDpIBqHQnnoiQijjQkKkgF0oQgFPS6ksZWwOaOwpa7Rz8SmAWD\nTDaLNxoyjDpIdISuIMQQKU3SWEOIiBSBSFRkqoGQJDJFExG+1CCNSWNwLJs0NQjiACsMSC0NZejj\nWwkZqRBEFmUjx9tbb6BqBpaismnsU+iV8bUYRy1ya1Qnad5lvFik10oojlUZ7g/I5GPcYEA25xAN\nImzbIiIiiiN0oZGm4og/n8qjjA2RkGgWeUMhdDuYts3KTp2PZYuIIGIw7LK+tUqhViWbrdJqtbCN\nEVamRhQGKKrG0K2j6Sq5rIJh5oh8KJaKuIMOaexxsFcnY1SoDw+YmhvnwdodLN3CzOQoVCbpD4Ys\njRnIUGF7cxnN0Dg8XGFy+hSMrvLLn/pHfPvKTTb2v8sTz32cs0tzfOXLn+egtcNjZ87zkz/9YSrZ\nAr//mc/x5ut3EdE/YqZaI02HjAY+qh6TJD4HzR6tVofJqSlWVu5w6vRpOp02SaIQDSI0bQhJB93I\nkkRdbMek3R3Q6+fIZHUsy0JVHGrVaYSQTBQnaTWbjE1M0O/3KBSK7NU3MLWU/cMD6u0BVraKEsYY\nuk6QpAhVQaKA8lCsnx7thVCO6FDvUIyOtAsJoJKQIFAeIh3vaB0UFI4QECtrEQXRw5DAECklntCQ\nSQpSoGoGSRKjKAoZXRDEB1iyRt2/iaJoaIrF/7X5JdBm+MLN/4F/cvE3+Gd3vszFg2v8MTA+UeJY\neoqPPv936e8t8zv+F3m941Iyfod3medxPZf/fOpn+V7c5OrBm1jJkLahUFBMBr0WWaNEoAIiIg10\nhPZQlyIVBEe0PqEkJElKnPzt2NvmjSI5TSEn8ihugbA3x+qGjzRrqGnI3q5HteAxakkiskSRRtRy\n2L+jowcFGssOkycr3H0jZvvLDuPBWUYthWceeS+du4cc3t2hOG+w/+aISm6Wk5MOWSeLoutYBR9n\nSuJMHNDx97FLULA0ov4+pTKE4ynaoE3LOnJ5icYP6Fh9Rl6bQm6RzIyNeXyK9pqF2tOoVcrocZ8H\n6wNeu77Cx37hLNVMkdVWwEt/vMqwYXLmfI3+RIlhL2Drzia5jGThlI2ulvH64IaSMDiqD5PTC0RJ\nRKPexKxYKFqMpqaEByZ5e5qD2yk3/ITiqIwlxvn+Vw9wPrJDrWDhhwoyzdCOUyxHJacaXH1phTOX\n5ri/sU2hr6E647z19R6Xjk3SudanYszQuLVCZmaGqK8iCwbNVcHqvRZaqYg6BupkACci+jKkgMGe\nHNEfRtScHMOgzVMfWKS8JFAyEd/8+gPGF3TabohWlJR1k87eJgdrQy4tfJC99RpXxF2c9jnSqkJ9\n1CSb9zDKGuaUwNiQpIpCZ1sSXZeUvBhnpsROdUiKT9CJia0mciApp2OE+ybdLQW/ZbB8PUAENozK\nlAp5ivOzlEyNnJKl39invDhGttpk7MIYlfk+gRyAcsDdbwgy/Wk4mGEURXj5mOnHc0wtWRy2BqSG\nRxhJzKLBjG1jZYvYWkIQu6SoRFJiVGBiPmF20aE4ZzCIA/YPmnS2+vgDh07nkE5XQSkUGQmT9Tsx\nF5+ZY/PqDqKmUvZ8hv1dFNVDVkqYMxVOPpMhPtB482tvsKmskUiXtlGh564x8ZzOzY2bHHYOWLnl\n860/u8v6jT3OPbvIuFLmp/+jD/Cl31vl9uvrRK1tji2dpRYOoeNj9lzcrUNeXFpk6okLrK8qvPTl\nVziMASXCzI+zct9jfFbQ6e4w6LrUTod49iFZZUD1mMXJH6vA7/7wB43d3TZn8hlCv0KzXseRWcaN\nZ3B3+owOMrjtNiM9ZHx8nqJynqWTguc+8SrIA4bJJBOTKTtVH6MYkB1bozyhsi1amGjMffAQxb2F\nmj+kZV5j6tiTvPbqy5TtGnf/xMH0j5FPHqU76jMyCxzGBt3YYe9ai8OWRmnyUxyfvUZk3+bisRyO\nSAnEEhFDoqjLmPYo/VTHVkyG6Q6aJbBLA+Yu7/PEj3k4478HShddTjBIHtAU+ziKiZS1IzMPrc/c\nU12mtl2+/X90GUuPc/XlBvYZyXM/P4kMniPM/BZduYlGgemlKlo25JvfWGb37mUWj2V59HmNk0/8\nHCP+BAUNyQg/9hCag5IBuzbi+OkLXL92Hbs4wf5mhTI/zSDtcOETt5l5ZkiYbnN2QeFTn3yB299d\nYvN7C+Rtgzs3/leeffxdqMVZNte/TmY8i7faIPeZR9GXPWL/GuNzOtW5e+QvhmzsTjFRn8ApuxRm\nttlofJ3P/+8PeORilrz9KarKaWYrLt2DZfa6+wgchGriAAUzh9v3sdUMJAlaTkHPSzx1gNAVClWN\nYBBhajakEEuBrhikZJhcKlLTjuGujuHWDdxOmUjeZxQmFKsF1tbuMps7RaqAYTi0Gm2sQCFQHDK2\nw1Jhks3+iNAdERg97GIGhxJmqjHsHyAyMVEsGcgEwygSWxq5QoV+V4J08Cijlwr0hUIrSqiOj1M/\n2KXXG6GaOoZMcAcdbO2od4tSgSBDRq+CpuIHLYSt0PVHVI4VOThYIcj5aF1JSZnBXUs55/wS9WbE\nd7/5Omvrm3zqZz/Gd15p0VG3SQ4Nxhdnubtyl/OXnyJDHk2vMgja7K2ss3P3DmVnEVNUsOKT3P72\nPXob2xTkRZr+AE1NEapFKipYVp769pDA38dSPNzVIkunZzGMQyxlBWeuxUTFRsueReYOCP3mX+t/\n/jcaNGxLI58z0RSBQCNJU5AmYWgSR8FRsyMUUlWSaCl+GGCYFmEYk6QKMjFp1UMOD1PabgqJTUnV\nMBUVmUpSCVIRCHEUVqYoFkIeWefKVB4dIyYRCUeun5JYSlQlJhYJqZAQH2UkGKpOYupHb6p10NL4\nqCEUHlGaYGoKqgph7MEwJdR99FDiISkIycjOsO8KxksGG02XqTGHOFCploqMvIBESKIoBkXB0hzi\nKH1obavCQ+3GkbA4QagKYRiTz+cZ9Qd0Wm2quRLFaoVypYLl2IShj2FooCjIwMd2TEbDLuNjYwz6\nPcIwBGEwGrmMRi4IyaDTIpUxfdclbxXI5hy80QiEpDvooBtDpqcWKWanOdjfImObNBqHqKrN2oN1\npuZOYIqQT/34e4miIX/w+f+H2yvfpFye4u/93G+RJCq6Mcajl45TfUllMHC5cWuV+RcqkCakwOrG\nHkvzUximiWkImocNZmdmWV1ZxjBMDFMjSXTCoIPj5EhihWJhCd9vMDk1gRAZVFUljmMsw8YLUhw7\nwyhwsbIG+byF5w0II5dysUDjcIdWo00qj5xdkjRFNwzCYPgQpeAhfUjyF+QXwJFWgfQo8O7I4jZ9\naCrwgyWE/HMHEqEIPM9DURXQVIiOBhZVQqqIo706uurhxcoRypKGmCJ71PArKYX8DD3RYMWb5n+8\n+i8Jqj6nJ36KEiHVvQZ/NnqFb7S+Qj/J8qtL72NYbbK2m+HmsI5tKFzXv43f6PIzS+/hDfc+Zten\nGexTNS3iGFrpgKlsFj8QSJk8tF9OjxANcfQDKAqo8i9/1x/W0swRlbLKxJxOayvAl0O0aBHPrhEO\n+mQyEWGSMtzrHtEipcH24YhsW8EY5gjRSIIJOndb9HdM7qzvMp0/xiPvu8iN77zO9rWQ1raPGubQ\nihaTEyoy6BOkLWI5wJyIME5HlNIhzfomdt7B10ImF8cZXxjnmFcgwmP/oMHM2RxOtYAwLDZFzO4w\nRrGzmLaJqjuMEoFdKnJ9fZOmHNEL26y0vsd89RhPvy9FxkWufLNDxrdZnHmU5Z179Dgk5+WJYp9h\nJ0u3q0NqkMnqqIqKliacPjeOZdoc7A0YeAGmXSS/UKZ1d0CjH5NqBpP2M9y8eYWJ1wPylwPyziwF\ns0ji9igUCxTLMctvR4zXskT1Ba4125w+e5bu6hr3NnL07iu4Qx8/VJm5WMGPBiixTuKqJHqZiSUN\nX/FoDBN0P0DN5jhIbBqbEm2Y4tRMuq6HkYuxyxoLUwt4TZPmXolOvcnID9D0Bhs3djj29NOczVYJ\ntqtsfLbD6u2XiJU97O+H+BMjCrpPaKSkSh/SDIpu0WkldDcVaAsUXSdOfRIkuq5iqwqdVNLdNtC8\nKmHDYKlynIxSoz8aoTkqdt4ga+XQLYluSYQZ49kd2uEuyo6Hr0nW3tDY/0qReNuiagqyJzNYFZ39\naA1/P8DIBkzMlInikLX7TYQeY2QFUaQgpIlix0gzJYo9zIWI9P/j7b1ibM3OM71nrT//O4falevU\nybm7T0eGprolikEyKVHUyJqRPWMD44vBAAPDV77wWLZhGIYA27AFj2HPWLLsGQkchZEokmIQyWaT\nbHZg83T3OX1yqFOncu2c/vyv5YtdTV4ZJh34AwUUUBsF7L3XWljf973v+7QGTACjoTi5VCWdSPo7\nJm6lRbiTs7sfkiiNYwjSRPLo8YhSFHMKB6fh4xUVh6ILBZCVkPHOAMOKsIwGoiD4zlevYZ045HxL\nYBiC9tgmwWXp2FOsyjWS7ydc2z7A27zH7u3HlG2XX3zpEq16hfuvP+DU8wsU9+eodnucOHeG+lKd\nZitH5Md4+/07BENJtb7AdD9kklY4uJtw7MQxjJpNQVu4jsZumuStyc/lrBhNIxK9Szgu4kyeZfe6\n4OqNfaKOw63+G5iNFZ5/+gwnL5gU1TLbg7cp1WJ2xG1c0UByi/Un/w7j9kmYe0h3ukvRVUjpkKtD\nymXItOaJ8/P03ghwZMDc4tNcOzykbOYsF+axq/ME6QC71GEaPGDACrVFm73RF3hq8WPUvH+L7vcF\n/aWI0kdMRHkXw3qLKbdxxDx9Drj0DBy8ts9BL8UoRYTWNgVZQnGAkZcw8mMkRkw3ntCy55BCk4iY\nclrh3Pzn6J6NOby6Rb1oUFtcJMliTCdlOPw49XKVzfxPsEyDaqXK42jA+cufpOD3qOp/yL/5/ZiP\n/M4q9fkeEgPLcIjQpAHYlS1GfoWllWd559UuZ0/+CosLNV7+WJ8zvzlB6W0cYw4lFEvH90l5hf/i\nP9rg117+r6nVX+Lt699krXWZC7U6Tz63yJ0TT9LZlWx/yaL0/U1+85/4VJ8qcO7lLSb9P2UU1CgM\nl2lvljF6v85pd4lv/+E3uPTUaf76S3/GcmUJpQdU5hzefP+HlCo+yWhErjyKwqdclDjFCaWmpNC0\noVQlyRN0HqAV5FlCHAhynSOEQtLFsBTm0mOE2cR0l5gOG/hOka3tXVzhUSy5FIsCM68SBjGlwhy2\nG2N7dfbbA1ZrLZI0Y5AMSKYKKQcUi2UsXWZtYYmDQZsgGyHLkq39LtLMsfHBt8jUgCg3SaIB+zsR\nfslgf3+Pfn+HIMqoW3PkeYqhE6RhYvsujlmkPRrTH6Q051qUjBRt21Sri0yDDG2cxU23aTU9Voo2\nemfCN37vVfpTi3G3yEcvPM3r33kXpIMYt9Buwt6kR8W1ufHeu2g9T+FqStgzmfZteg9yRuGQUqXB\nobg6+0yKV1Beh2D7AEd4WKbBKOpRqWQYTkTFdxBTjWEntA/uU0kM+ts9VvoVxIkqxnyb3KogRqvA\n6/+3+/xnKjTm6h7NWhHLBvL8KBEHwigimGqSNEPrjCwXkIJjuaSpxjQ0KEEUG/Q6iiAxyU2FKXIs\nKTG1ROUZUZ4hmRm+TSExpEAfpWflQqN1Ngss1ZDoWcysQJKSzOy+erYAyWdvSwhzdpEUGoREWrOJ\nA1qRqAwpTAypAQPbcomylCIm7WBMvVRDJQlboeZkZYWpGiKSlFEyQdoWru9BLsiTDMOYXVBn0pwc\nND/2CgjLIMszzCPZSp7Ctfdu8KEPPU8YTRlPBiQqp1SuYFgWQRTh2iYH+/v4rsHh4ZBapYIlDAQ5\nURISBWOMIymPZRtYlkcWhQz7MXGaUa23sHOT9ePrlAt1+r0O7YMttAyJ4pBGc44TJ1a5e+MV+tMx\nX9+7xyTKObZ6mk+d+XX8sgXmmErhGIP+kFKpwlx1CeIcww2p1yvojU2KhTK5kvh+gd3dHVpzdZqN\nJo8ePWJleYHhoI/tOWRWhGcvkyZQbZTI0iGt1gmiBAwbPLdArVDA83yiKMIybLSRUS7XCMIppiko\n+T737t6m3qzwcHNz5teJI2zLmRVhiCOjNKDUkS/oJ1yTD6RT+gMWhRQoPSs2pPhgCqAAeRRkq8jQ\n5GpmxnYEWJY1u7hnCsM0ZxMUMStg0jQ9KmQ1Kp9NEgxDgjaIVYAn6riyT72xyr005s/e/ytGrgMJ\nvHzsHGeMiwyTq/zBox8gDIdLdZNm9YDkoMyy+yxtecAfP/hL/sHcZxk027zfjXk4HuKYA+qFCoN2\nhFGSkAuEway7pWe+EqH1EfX85+PRWDhl8JGXDezSEJxFbr86oPNH96iZkicLPkljTOlshbwS45ct\n4sfw6EYP1bX5o6+8x3Prl/GjeU42Frjwq0t85893WFhqsrl1g+5wm3LVQVsh86UyjpyShinNiqBx\nzCL0JkRLEWZhimNplK2pNCRlZdCLOqRDRSZS1o4vEXYsIGYSm1i1MhkKZWfIskQXc0g0o3Q2Fd3c\n7PDEcwuMnAiEZMwhgTlidb7GUsvmB6/1qZYzkj40rpR54RPzPNzZJeg4GBsG47bgoD3E911OHF8g\niycEkyFKRywdLxP1ikw3FXNzVQ4GbbbjCe18in0gKOpnWKt0UMJlNImw3JQkiHj8sIeR1ti5rag7\n53jrhw/xe4skQYHNrQg1sDENg+VTC1j1mNAcMxml5MOcIBPEOqPmK1xTIsMK4bjE7W92GOxbNFtN\n0GUqNYvN+12ufT/nLWOf9p0xX55u4Xg5L358mbmLdVZXTD587gSPvrXL9XGHzz65wqPhDptX36dY\nLeOcF1AzyT2FX3WxlMQ3i5i1EqFhkyWCOB2Ta5fpICKLBCXX5nASI+MSZVFi1I44UVmaxSY7Drbv\n4VZzsjgiq0xonTdIyznlCx7llRpzos7WKyaPv+SQ3XNw9AKN+TPEuk+GxPJN5lddiiUDTMV0MiEM\nY8qeRzhVHHRDKnUH38wwiwpVUxBGpD44VZNcpkQqxigUcHyJDhPWjxdRmUm3PWX1xBxFp0h/f8Lq\nkyv0h2OSWFKSGbm0qZYLmK6FUy2hjleJB0WmE4fD8RT30GTvUGGkkqZj0W1LmFo058+ghiMOr3UZ\nngVRdJiIXXLVJmgv8/BOl/3diCVjlQYLFOOAzvZ1pmnE8nPQ9jx6/YBhB6LDAuqxR9ypMHfpGNvf\nfEzhEzGjcQdDZwyGyc/lrBge2kQTm5Ixzw9fn3D9NZONVyd4Mqd+RfKhT5n8yksFjMzj23+5Q38v\n4d7tQy42VrGdRaKkR3lll6T1kEOuc8qxKcgymoCS6TJUQ0bJPr1Cg7w4plhL2dvdpblYZ79/iG+N\neXDvLUw3JZdFpv0A4T3i1NlP8qS5Quusg96M2drIKF6dI2uFzJ0JqZWWMegjsPD0IsuLuyycbLPx\nzj66d57eRp1yMwbtkJkRhrw1YxQoTZ7s82jDIQufYuONNh///HN86b/5Or50ePIXmixdvkts3mbC\nn2CUlzhILqJNRZbU6Pd2uLT+C5Rlh6efOMXjnR7bV0t8d/Ayz/7qPZrnhsSVQ2wsTh5b5N/9xz1u\nvXeXb/8rzfnWS/TiW3zqc/dpPfkuWjvkmYM2MnLGDMx3WDp9mZc+1eR7336LPFuh5hRQ7S1OrtR4\n/tff5YIV8ZU/3iGbO872j/4uX/nfDzizu8fyhwzOnqtzf3/CbreJiM7z3tsdvvcXD3jppWe4d+cq\nyIA03SOKUx5t3ce1FVKPqZcMSrgo4ePYIXahS6mWE0UQtCPQDlpJbFMhdI40jsi1JjiWR7UBpt0h\nLu3Sn26itUs6WaHktfCsRXbvblJyUhZtE99yIQWEZBRF+I0a7XHA+csf47C7y+7+Q0a9Hn4qqMgT\nYFvYhkkkBWW3TKhslBoyHowQRhXFhE6/jUonKJkRpxEyyXFtge9WQZuoOKPq1shNzSQy0CKZhSqp\nkDzqMJyGCEci44SyV6blZvQi6E63UGaZEiuEuxapSon1iO60zSD2McSYEi5SWqSlPZIgJ48iNt7p\nkqsJmgG2YSAqx5BLVR73++iJwdSNSNgk6mjyKEL4JUzbQqeK7kGbRrGG65eJigGGOSELQmRahV6Z\n3VctNt9uY1RPcfzKGfrB6Kfa5z9ToVEtQKOssGywTQPDnEW7pplDGttMphlJpMk+AKAlmixNUMrC\nNDSd7pDu2CDIJdrRmAaIPMe2HaIsR9gadXS+aaXIANTM1KuFRgqP6bwAACAASURBVMkPgko1ec4R\nM0EcpVB9kCokZ5fHo4ujEMaP2RdCSEw5Sx7y3BJJkqO1JE1ASo00PFI1pupUGU8mOJlkobBOtSLQ\nQ4vT5y/yrauv0KhWabfb+FaBUqnIdDrAtAxylSH1LAoMoRBiJt8RgOt6TMYhtmVy7dZtLl88T1yd\noPPqbDEIyXQ8odZoMersUy2X6Bzu02hUSeOYMIjIVYYpIE0SEpUdxbTOZDsChVIGbqFOtblCuVjB\nlCbjYZ846mE7MWEYEMcJhunwzW99jc2Da3jC56mLH8VzamA59JMcSYX1uTPEoUQwAaPH5z7/y/zP\n/+wPMcQcWTimWvLJ9kcEScra2hpRNGEaRuhen1aryXAwolwsMZ0G+BUPyCiWC2RJju345JmgXC5Q\na9aJowjTMsmzjNkEKCPPZzDI0WAWmdvr9ylXK3iez61bdzDtmT+mWPCZTqZHxSRIIVH6aAKmf2IM\nl1Ic/f6T6FeOmBkKDUcFh0b9eO1JwyTLMtCaLMsxTfPH5mspjgqbo8hcaRhHqVcKIWck01ndopDa\nYGxEDEWVvfEuBb9Kq7jOYlGStFO+s/M234nfRtRK/J3mBWIREo/OoErnaNqHHAzfZm0p4rfSf8y/\njL+M7CecXjzLyZbL3+5/E3c6wTXnicx9ZG79xPStDbTOgaM9IX+W3f7//Gld6SPcx9SXM/YXr7Jy\n4jRy5Tw3/2BEHkjOX17h+C+VOGST+smMklchGp7k4NuCt9+4RbnYIt7PSJVBJ+zQOGVz9vI8D95/\nh8Pt26yfmSeOOywdX8X0QMdT6vMRyxdN3ty8RWW+CDWBKCj8akTmpkhbknc1j3pTxmmA6a0xd/kY\nqRgTDAYoo09u55j1AivnfG4ejtm9vYVTKzLsTMmdKUGpyPdvvo/f0Kw0xjSqHrgK4fhk/YT3vn6X\nUdznhd8+zVzVpU1MNBjQXGpScwXdXkK/P0Kt1ImDEX7RotAwiK0pWU8hik1Wziww2TdpRznjrMV4\nuMiDv/b568U9Tq7dpNxfxnMi7t8dMddqUbWv8P7rPY7NXYJ7MW/9aExjpUwYZIhBgFnWeOWUfjrG\nzXLyUU4ea/yCQ6Ng8+FfbCCKbdp3Olz73gE3/mbA5SfOcu5TS8hQYMUFevt90rjCte/v4bsFLp47\nxjO/sMbSeYnwRggnYGRuM/YO8S74PHvqJKWbZd773yYc3DFYnK+jKwZhGhHqiCwMKRRTVitrDAsW\nbmOeodhkoofUViDYiYm6DkJ4WPgk2mTp3DKtxSLD7YAs6VBfdjDnBJGKqV2wqB2zyWsufS9h0JkQ\npUUevNpi/80lDtoGi0tzjIslAtXDVWMS2SXOBGZq4Zo+eQquX6IyN88737/L9maHs2eauGcrkCcI\nEZMYCUjjaJKjyGWGnE4YdT3cbMQ4jfAqklN1k9ay4HD/JsqxSVKLbqeA0ahS8B10OkLEkt5Wn7Rv\nkgcOIpTItMg4zLHrNof3pzTKNTa1STwoYIkydrDIpDNHpRpy+tknOLeywcrJs3RGKVdf6WCVn+C1\nP36X/Rsxi/UWw/4GB40HyOWQ0kKNZ05IvvbFMe2Hkrq1RtwWzDfWUVOXeL9Lvh1RKZcxhaD8cwqO\nCDaL9F+r4Vfn6TwcsPGDNiSnSBZ6/Pa/c57P/s4aNods3uqxeWCzduwZkvEP0dIlzYfYooHyb/Hx\n3/oID/buMdU7SOWRJBYlLyFJDxgPx9j1Ov7xKi+dWOa1725w/+EIw8voej3ujzc5XT/LvfsdGnaV\nU08KLr+wxS+8VGNvbLL5Rok4suk+XGP3vbuUF0rIooctHKaMSThkZyOl4M1Trs3z7W+0+cTiKrVx\nm1JpnaF+QKQjstETHD4Y8LW/ruFF8xTMUySxx+/+5u8iJ0XchVUebt/lo3qZkABJhCuaxPIBb79a\nY+dqj0dvnGChNOXDn1/h2Zehui149MaIyXaB73/5Hh91XI5dWWXCPbRM8VptXvyEj2m/z1/99+D4\nCm99QFL+LpaokJunCLPHZGabQGQUeZ9KUzNsH5CUL2D0c84WHD7xK1WaV97BNN9j/WqJW3aXtHOJ\nw52/x51/9rv8Q/dTRMvfYXHtOb7xxSHe/gX0do2VouC9Nx9guCnkDpv9QypNj3wQ0qgKdNbHdR3y\npEe5kDCYHrC04CJqIcMcwrGNZcZUfRvp5viNlIInMaiS6IhGKaHoJxgedLogAyjqBebKHyZzFmms\nrDAYfoP+SLPcKlEo+qSDMdWqz6A3otGqc6xyBqO4TtE5i0OdrYN3SYIhW5Pr1AolAqWIbEl/eIAy\nMhAZ4WZItVImS2N0koEtESJHKAGWxDYaOL5NHIeE9MktC8uwiUYDImkiHMhEShqOyFNJ0fVxUOw9\n3sQ2BQXLJVcVlCiR2TaPdkJc10GUcqJAksRD5mpVXMtCyoRp3MAQEZYNBddGDQ3yrEmgwfBqGNRx\nZEhohWRGRhz1SMOEor+MY9SxsgzJGFFwmBoZidBEsUE2TVBRSDCKqRllCkii2MAZPWavP6L4zE93\nqfiZCo3lBZfFOQcp1AwkZkg0OSoXZMoiCgyiBHSuidOMySQlz00MLPrjnEmUkhn2rKucK3KhSJAY\nOiPJMlIlcE0bDTMeg1IzVy6zlCutFUoLFAolZ1IrUwhydWTuVXpGc85nqnuFQpEfMRP0EWgP0KAN\nE9O0cLRJLnOUToniCbkhcMKcgnAoNKo82TzOo8EjqtJnb+cQ3/DpDfoUyxUMJRhPxlimRZ6nSGHO\nAG8IjlrdCClnfgvbwHZdbMvg7s4eb1+/RrVW4fFGzLkLPlaxjGFY7O5tY6MJRxNQOYd7B7ieRTAJ\nSZIYyzYxTYkpHLQWBMGEaRBRcgu4rsPx05dx/SLDfps4Sbl3/wbNOZ9XX/suZ06fpVhqcPvOIxZX\nljl/8mkyLZiEOValyuJii6JvMJ522du9S63WQpBj5B6nVi/woSsv8KMH93F9kzieUPAdtnc22D/c\n59Kli+zt7tLuDdnb69Kab7DfGVApFhn2chpzY+JkQqN+GpW4VOsOST7BNmtI10IKAwSoPCPPBUmS\nEkwCioUiw+GA6WSKX/TZb3cI4wTLdEmCjCiKUOTYtn0kcxJopX4c6WoYxpFUasbYyNUH3f1ZcWoc\nya2EUD+elnGUMKXQCEOAmhV3WBYajSkttFbkuZq9Roij716gdTr7/o+WgCEhzTTLqcUocbEWWgx2\nRnSrDqO9XcpLLRana8hCg1x1+LONN3ELNT6zvshrd77BZ5f/Hn/Ve8CxvsZufo8nsrN8Mfgqcxt1\nWpU6Zxpn2Xj8CNeYoEONMDQSCUKC0Ej9QZEhyH86ts7/68erKDw7o6FdpoMJteoh3ktneP97G6TX\nBdVlxbkTBiX7NmeWm8TxLuNWRhI0+NRvrPDilUvsP0johDG3f3QPkTjs5oqC0px7usLl58ochgMM\ndxetUyZxB2Pd5OSvneLgnQr2QoGD7R4UUy5ePkYYTOjuTajWLCgIwkxw7dYmWaCZO+axermEnQ2Z\na7loPMxWAS9TvDbuEkaCzrDPqZMt9kYHuCWolgSlsiQb22zenXBwI6dRXCOmRO8w5+HVQ3Q5ZO2i\nw6QyRCYl+oYgCQMqDYvaqiR4kGJVbdQ0JE8zvPkivqEpmhZpV1MtVxnvSG4Hb/L4tRbVT89xcFkx\nXx2TMqZp+hw/fYq738s4uDFFu32caJ77N68xiKEQJSzPlajOp2TVMdKZEicThCkxLZtmy+bipRIX\nP+yxvWvzwzdG/A//ZYff+Mgya/5ZgkcG0WZKY8XE227QjKo8vdbkzMUVTl8qQy1AioRE52SjnAc7\nHW68M8BxVmmuLnBmfpW1L7eY3h9R+OUySk+RnqKw5pB1MoJsTNwZU3VspBtSmCvSvCiZHhygTwru\nvJUy6RWZbMa4hTLVVZu0EOA3epxsRdTnxzTWfbrBiEkCh4MBi8fKFDwbFdXZ+I5itLHCgxsG90VG\na3mOwhMlTs0XWLw0ITQmVMsB0TBgOBiiU0GcwdadPvt7U4punSiwGT7OER2NNCzM1MGqVJBmQjKZ\nksQWo52E7uMQ18ppNYu88KunMEPBozv77OwNaa17BIOcye2EYtVjeBASD1PKhYRs6JJnLqb0ibHJ\ncrBkCT3SjO7FyMYs4EIlZXQKj9ojBgdjJiLh7Zs3efTWK3zy7y9ybuEMI9lj7uI6WcHnC//6TZZa\nkuZSzHP/xObMh2qMkyn3YoPj5yxevxOQ7HdQmxZXXlgljXOMYZlHt7dYXo1xShHD+z8fP5cRXaZ7\nbY3H1hbtzZQkMVi8MOBDv5HxC792CpsqWsds3L3BNFTEkyXqaYZvtZjqQ0w5JhERcfgYp54QKQ9D\nagyvy14cESYGXn2B8vqYX/sPqtz+mqJZsen0BLYpuPH+u5QLDTYetKlVc86fzPjl3yny639/DPSw\nt09jjZfJ2j0O9v8G62aDMy8cRy/3iY/AwKM0J5o4DPo5jdoxth6NGW779O5nLD5VoT95mqi3gR6e\n5/DWDovGf8Z+Z4djzyVkIuCJ/POMDl3608cMxz36eRut7oDeQqkOQRhy7TWf733B4nzraTbvS0a5\nJvUTVq/knHh6h8cPXuFgz0CpJXrDMm4JDNnH5CRD3uXk84rSokXefZ4//V+u8w/+8ytsJ+9T1BmJ\n02dnZ4jWArewTKVeYpzcpKifxMpL7I7v8cN7PT7SmxK1Ip78lVO8uCD54d/+iFf+W4P49rP88R/s\n8dtzFwlkwHH7Mv/yq9f5/Cd/l/vv/CsqpuBeZ5uldZv+wOadm28wP+fgFhX1pkOx6dEb9ahUYK7k\nYlU9hOcQBgMsS2FbOaYnKTcSPF/j+zY6V0g1xbAhTj3ytsf4bk7cW6PonmBx/gSdqUOcJiweW2Xw\nYAvtWISxYnFliTvXr/LkubMkicHpY0/wYGdINIwou02WWxdJxwcMogGDcMg4mRCKlMjMyCyJymKS\nUYitq7gFh1E6RgibeJxScqtUSysUbB+daXQckSchOk2YxH2i3EZaFWzXQeQZ8WhIkoYkUxOlNZVy\nCdM0SbIeaS5w8goq1Xiei+dYSEPR6R4ihabozRNHmkSF+G6BXPoULJMkSUhJiVSCVS5j+FUoVPDN\nIsZ4Sjfs4lk1KjUJ0mYy6JPbECiN7zqYTpE0SzFLgmTqYFiC4XCMaefE6T62Z9M/fARJmXTjp5Nj\n/2xmcCun4IEQOYY0kDrDsl2EKJJmOZEMUWgynRCGMX7NQEUuk5FN1usxGEdIfw41DfA8g0hDrDJs\n7aCwcC2fPJsikeQiQ2rIEWRKoclB5GggVx9g2CTqiJugjyBsSmtkrtDSQJoCcdRa1h8QvKUELWc8\nD2GTmpAFCRg5khzMEqEe4jsNjvnH+OGN17ly+SPc3PgBF9c+xkQGdOMBQTLFlw4ChWEY5IkNhgHq\nyIwsNEIpsjzF9zyiMEK6HmGWUW2W+cHrb3BxfY2VY6dJ44TuYZvG/BJKS+JhF8MwSaMMpVIO9nv4\nnkupWGISTslTTU7OeNCjtbxE1s8RosDy6glMxyfKI1I15s7NNymXivzhH/4519+7xT/9px/FsuZ5\n4YXn2Nq5S6VcYBJOWTo2x3g6RRgR7WGCoWck7Mcbt0GDZbq0h0PqDRi9N6VSdKhXSqhuj1KlxDs/\nepNG7RcxS2XmHYfRcEQwSXAtnzQFwxnSac8SkZTaouCXCKICKJ84BNt2mU4CypUilrRwLRNDONjS\notsdYFkWbsGn3mjy4If3mUwDlCMoVZuMehNqlQrjYIxtWSgtEKaFPqJoZ1l2RNH+IO7W5AN4nxBy\ntiaEPioQZyC8D6JhVT5LpPI8jyxJSZIE3/dJwxTTNGdSqqNJSZKkKJ1jWhZpOoNZwozVYUiTURYR\n2Yp+f4/VwgrdoEer7tAe56SRxq7eR/V8VufPM+hEfHH7FYrWab46/RNa5jqn157i6w9eYaE25n+6\n+Hv83p0/Ykc95MPqWQoLNu+Of4SdLZLr6GjNfzDJ0Gg9k4/9nJqUxAiqF2sUTYt1OWSgM4Kgy+pC\nnfu3d9m4+i7rVzLE/F0KYY85v0Vodbm6cpfVj59mFB7w9huP2d9WaEPy3DNn0IOApYZFa0XQWI8I\nwgk77V3WL81RlBm52eeH+0OyeYVdNWk6DR7f3yFa04yGEeNpgF8u4nkJz55e4UffbfPe/T2UUaU0\nr5BhiuumWCIkVD2krVk5rTjYMtnezgg2NKONCcefmqNzrUv9UhM/tJneKRDcK1DWc9h2k/L5Aqt1\nxb03X6FcqjAc2NDW7DwYQpKzerKJYoo1N6W85iOnHoYymR5khHGAkw8ptVyMXoXa2WUG2wfcunad\nw9/r8ITbpX7JINl1OXeyxrWDR7zxRocgOc7De9ukdpFRnLKqfESqENUp9okMWehTLGuslsC1XFzP\np9iQNFoZB+MD9sdDUlXiuRfm+Mzf/Ty996bsX1fomsOondM/SFhqNXnxM+fRXkiYD4knEUEUkSXh\nbBK5Jzi8n3LmGR/Pzyk7Bo2iy/sHj5krNFl5tkZ3kBLnA7rBhHSUwt2E8/MnMKMM389YroeU6gM0\nNqWCx+tfD4kdi5JhACmhTlDGDnNPCXz5iNVjFcrTjKH2UftjTFtRlymmb7H0sfN8+Ss2ZlnyRHSK\nFfMY/YcP2O9c5/5kSON4l/ncRuQCMzbxy2X27u2QJFOWjzVo1aroTBOOpohUM2lnpMqiahfAcwlD\nSSYhixWT8QDtpBQvaaZig+qcw0rFpXGpxo23Yx4/GJIdhLDoIrpNEq2wq5pKvUZWqTAZSMxQ4EUm\n87USflWRGjGZnhBEIywbhoy51gNlxdQWBVv9HQI75tbjPXZ7Eb3YYOPxu8R1ePHTT+N6sL31OncO\nepwQHpPDDNvq8+JnzqAGkj/9Tx7SGC9gXJmR6tNY0NtKGfYnGNaUw0c/n7PCcyr88Dtt9oJbTLoZ\nVnGJypLJ8y+folEMGfEGWaTYeRRjhh/H9y5SsG6QkmFmGtOIccWsWXV3a5eV1XP0E4nUCWFcQ4gy\nmHDy+DrJwU3GgUWaRiyXz3NvZ4dqy2Tc6fHMU0+Tyi7Pfkzzsc8ZRPRIxRBnKcZppaTxGqNdl4VW\nmUJeBwJiHSGJ8Yw5rlxeZaG0ycGl23zrC5J7N+/SLJ7jRrfH/a2AornM2afuc+WFEgu/9hXe+UGJ\nxsqY3f5X+eQnTvCDr3TpvmWxs3ub6eGTxGmAZy8yTnfJpcn+5pia9RlsvcyZExbf+tJ7XDj7Mgun\nIqqnBIXlIhekZJK8xTg/wBYttGqQqpA0XmXSNunvRIiuRefA53t/oVl4QZAt3iUdl9h5aDN4UORW\n0kV0G7jxSYqtOQ6DbTKGfPPL77D+oV+m/uQ8if8asM7C+ZvouSFPz/3HvH39f+Xbf1nnE7+0iDl3\nnU/+1ov83u//M2qjHU43z1GfX6Iz3uCdG7eYm1+g2szwa0OshmLq9Cme0eTGhMwX5MUIpywoxFVk\nbmPYh7i1ANOWuM4JHMdFhscRKkVOHxJ3fPaulpk+cmEyT8E5huk30FFMGMXU6nNMtw+h4JILTTsK\nKJSrTIKAgtNk89Zj0kyho5hmo06/06XkroM/JtRjnHRKLjUTFTLOUiqlCu5STh4EKEPgtTRZDoWa\nj4WDtDw0BnkUYmQ2Jh5BFBDnMYaQxEmfLMzJVUoeg+9XsLFwCw6TcYTwHRy7haENVOQw0QMq5Zxp\nGGGJeRxXk4Qh++09DO0z12pSa7S4f+8+omAjhSTHpTm/BrbFXrdPQSdEUcigu0dCjm+auK7NOIwo\nlW060wFevQaORzDJECLDM0zSRIFpIwtl3FaT8EBiIPC9mIJhsn9r56fa5z9ToVHyLcouGMLHMJwj\nUrHCkBDnGsswyZUgz00856jj7MO8P+HNdyReqUIwPESWC6SpQiiNb3mkOkcZilSPkWQoYSKkQa7N\nmdZdSpQWM7e+BvRsUjGTw2QzTb8GbeQIlc/kLEKQHRUYSNC5QfYBE0EapJZDSVikvTFmQaIsg24+\npJJqCtYiH2mc4+1gi3KlwmlRZWo9x1vbr2EJjyzJ8M3KbFpiCnItESKdTVxkjsREComUFuQQxwoh\nLUSqMIRCZzZDbfPdG7f4dLXCqDuHLNYo6ZzJZIe5pRXauzv4hRL9ToeF+WXavR5h/xDX0AhpopXJ\n8rHTbD7eZWXlBNX5eQxDY+QTbr9/lcl4RK3c4t/8zV/zrXdvY1o+X/vB1/j4M08xOkyQnoNOUixh\n0W93QVpE45AkyRFKYzlFVo4vU6yUUXlKfO1tzp14ltPvvcOxSy9ydx9ae1MOA4u7hzGndw5ZKAoM\nZ5Fyqcgw7hAkKeNRRLwFtXqG62nC0YhwNGbQeYhf9IiCJYrleYrFFkFiEOea6TSnVVaEYR/XEpQr\nRfq9HsPDHtdv3meaSqquRzaZ4js2k2CCNI1Z0pLgiKQNKldHXpaZN0NKidIKKT9gZCgy9ZMiRBqz\ny/kMyAiGmPl34jiabQApCKIQ27JI8hjUETVcCCzLwlQWSRJgSgMMjRIarXJyFWAYJq4McXWDoZ5g\nWy7TRFMQKdqBLCwhSoLRdAAeuHmNzIhw9QkOw5C3d99ivTRHIc35r977T/nk6Y/zrc0bBKUO5jin\n7s+TDTyElZClCsMUoCXyaOqotUZk6v9yb/9/+ey/DeG6YLs1omBoPKeGM6xiRBbLrRPcuP89Tm46\nPHelTKGiyXWM0mM8NyN0exiTx5TXXEp+jSzWxPGQ6eiAWtmiqGN2+xZxuUte3UYuBLQaNspI2Rp2\n6OYWt792n6rVYNwe0FwtYEiH3JFkVkKaTlBiRKGccXptjnia07uTMHepSGdnQNFPcFyJSlO8YoVW\nq862HRH0DKKJjyp6GE2HcnONh+8dcPjGhLX8FCtLp5nEFqXz83zid9b47/7527z6xS6n1ufp9hS7\nm1NKlSKXnz5J7nQp2x64Ic5YUcBlT6Xs3tugPxiRiybLizUa3jKl2ov8/p/dYuvdAS8+eorSy32a\nCykOI6xxwif/7ZOo58/zV7//CLKYi9V51k8JiiWPfnyH0B9RfsKhWjdpLlQY9zNsU+HaOfvDPuP9\njG7H5PGWw7kLT7J0/sO8/hdfYNgOMMsG86vzPHH+CZZP2VAIycuSyUiTZy4qciGuM90aM9zukQ0j\ntq8e0HBbTJw2zVINHwczdahVJP7pEhSmjAcDMHM23x9SvVOiagus5YRpEOAXpuTJhNaZJkv3XfZu\ntundy/Hv1Vk63kSu+WgxIWu00foQx8+xcak3Kkw7I/y6JMiGzDnL7AcP8IvrDMcbyIGgdSpEnZK4\ncxbKtumHAktZZFONPwlIYsnFDy9iuBmeZZMMc7KwiFCS93cP2bkbs3e9zZWPrWGUCmQqQg1jgl6P\nxQtFFo/PI5w2YamHdhS+0eRCw8N6tcDV7wZsDqc0l+qsX2nSPJHimYLJUGMbRXZzg/3umErLI5dj\niqWQ0pLBonCYihB/pMjHUwaPAgZJyl67w9LpEnvbkhu7+1hqgf52l9KpKtYTDtWmyXBlngfXv8e1\n52ucLjv0vJglS/DMZ1a5/bea3W8kYGnqcx7TmubeTgdtj9CR5vHmz+WooFofsnmwy2To0lh0OXli\nldbpLZpLe4zpYxMyikcUWg6rZ0yufv9Npl83Ka5kLF0w0JFNqWRy8841as0y3UmPXEwQAgreEuPJ\nmCA4RKlH7L2fcLjxC3iqwaPdHfyCiSkvcmp1GSHv8/n/0OHFl2OMUsyEkCKnSKWgMhfRXD8gGZ/C\nMiJ62yHaq2GVFX5dYusu9ZKmdili+cwW925E3HnD5H5hnvBqhtUY88KvN1m7ECMMl8mgyXOfdBiI\nVzlpOEy5z8f+/TY7o4yNXcUPvniDFz65RofrJOFTfP/N64wffBZXHmBmOasrS0TxWd77G5M38wnr\nHzrk+c+5OHM30HaHsl4iSgbksoRkysHWkC//CwfVO0/dX+bd6y3e+ErAR5qaxlKRIG2gkoyv/x9F\nPvLMP+I73/0j5isfxuncYdGZJ3Av8vDwff71/3iHFz/fY+WXUsbZdaTOuPipA+z9XVbCFwn0dfam\n3+H5y/8eX/jb17nwxHM8fn3IfnoHo3yS13/0Jqtzq0TqkH4S4NmCqcrRpkI4FoaZUW3Y5GaM6Ssc\nP0TmY6plk0bpPBYVtNojHtWxRYeok7B/M0R0qiQ7Z/HUOmlSJs1KpJaNV7FwbZNh+5BCqUYWRzhO\nBd8soMKQSZIgREJ+uIfl+xQycKKY43Mr7A8GWJZJFGlEIvELPrarsFKTgl/FFRFB0qPZXCCIp2ip\nIAiwhYFKBKlhYxg22nawtUOuhqSBheUUsY0MzRQtcoQtmYYj+t0JtUYRt+gxnLSx5BBHVvDLK4zH\nAWk+xbAMxsM9UhEhBUTBBN8zUJlk1Bmh0YzDIamaIiNN3NZ4hRKG0MTBAIlG21CyfYw8J0unSCNC\n2kXmvUWEVyZTimLdIAnHjLttHKWRqaBcXwKvRC+fMOyOWC75JMrEM5o/1T7/mcjgLz23yvych+f6\ns6hbx8J1bCzbwrFdbNvFtixMSyCkgeeYmI5JFiuuXh8R5hE6M8gNAws5M+wqjeJISy8kQuUIYYAC\n1Ada+tmUROlZd9owJBIblWtmnvCjgkL/hNINR14Olf1Yry8NA+vo4ulMIxILur6mYboMez0W3RqR\nmXKivsbuuEc6nfLxlWf553e/ymfPf5Q3dt9hobzIOAmxTRchBUJrlMo4yrNFCuOoi8zRjzpKPTp6\nf5IjSrNm2OvSKBapVIp4no/telQLZcJowgzEoSmXK4wnU1y/QKlURZk2hunjl6sYtsfx02dZXFom\nTacEwx6bGw8Y9DvYliQIhmzt7vP+3V0KBZve4T5PX7iMQDMMcoI4BgGO52E5Nl6pTKM1T6VaxLZh\nGowZTQbEYYAhFVor+v19ysUqn/70pxkOx+zs7zEcDLh/dJEsbQAAIABJREFU7zHLy0t4RYHSEeXC\nPK7lI82MUq1KomK2dvcYTRVbW23izCGYQjDMOGjvEscD4nDMQnMeV7h4lQZCOpSqdRQC03ExTIM0\nz3n1+69RLpcZRzGu5yOkPPLy8GNA35Ft58fQvlki1U8mGR88H6SEfSC1mvk25NGaUj/+nx+8WhoG\nWZoij2RZhmkixEzqJSWYpjNLfspnci3ELDp3VhzqI+if/HFqVqY4+ns+S0g7Aj8KDExDEuQxeTZB\niArdwWMuXXqeNfsE24OYJ89c4s/f/xK//czn2O7eJjFthuP+rOg6mvblWYZWMwuL0pBm//+TwZ85\nV8ROtmke96hZJfrpAts/KrBUewYrL/CdV65jzsOVl12SUZv+7oBHE8XGJMXsznNq4TLDbYPH7x9i\nC4vWvMf68RqNdQNRjejobUrrktYJSebvk+jHZFaPpBCQF6v0dhV6aGElBrJsYdUd9sb7TJkwoYPh\nGejUpezW6O8EhJOEuZU60k7BypB2yijMgCph22bvwRQzLSIil0qliQ4L7N3JGO9aPN28yNOnrnC4\nPWEYhIhKyPmPrbHzaIM7tw8Z9GweP4wwjALHzi7gzyUcxo+pnpxiFWaxuqgEW5ik0xwlctLIYtCO\nSdIAz3FQfcGDzhbrqkz10gBrDsoyI8pipF/g8DBA+kVe+vglLjy3CHaXJ17yOfYRk8plzdr5mZbY\nkC7RRLG2UCHIIsYHEZvvae695dK54/DWO23OXj7DK9+8yc2tPTZ6AbXlRZ566hSqHDK0e+Dn7Ach\n8chi3BaEBzbhUJJMJLY0GAR9auUCewddSoHHtXvb1KMiL/6j05TnQirrmvZ4h+F+xNbGmH4vZWW9\nRblWpFQxKFcMEiNFGD7b9wN2b0G2X+Xx1TE33+0ynOzS/HCA1driuGshkAzFHntxnyRNWK86nLUr\nWIbm3d1DfMsledjhlz+7RHm+Qzu+TcFPCeMQLXzSxEZkHoePxywtl1g8WSbRfaQzxS6k1OoWg15G\ndzdE6hqO6RH2DBzbgdymczhh0I1YO9MiIaUTHSBrIaocEeRtwjChUqiTtD12743xzTqtsxWswhhD\nZkSTGJXZxFoSZSmNZYfGQsTCWQtndYjZGuM1B5QWctyaTWKGmJ4mdlOSOGU0ymm3U0xZo92PaC7W\niNMhW9sbZGqAPWdSrhns6xHlmoFDgR+8sUPcKWK7HvW1Jt14A7M04sqn6v8nb28aJMl53vn98n3z\nzrqPvnum554BMBiAAEhcvClSJFeiVjIlrdaWrfDaFk0xQorw+go7whEOf9hwOKTYldfhtYOytPJK\nq5MyKZEiKYIkQIAASAyAGQwGM9Mz0/dRd1Vm5Z2vP1TPkN+0dJjM7ojuzqjsrurMfOv5P8//4NkP\nLDG/WOfmlZg33oh+7GvFh5926d0xKZn/kPf8A4vH3z/l/GMB9WM5Sk/J6eHYJdyayfPfeAk7fgTH\nbOE4GYsPTAj9Bo7XpeP3yaRFToomI+IwIoh79AY9pllM3BPsvdnijedstjenHIwn2DWdhdYl3KTg\nfT8d84nPekh3H4WOlgvMIgE5odG4yyTaJk8Mxv0mWWqQ+QOalTpzCxq2iDFoUrCN0nOCns2td0KG\nB0tEUcr7nj3O3IMTvJLC125Tsj7JgC9TaF2m4i0qmkeIwjJdvvnVdaLuEt1Nhau3ee2FiMtfLkFH\nUlVnefrpOh/95YLUDtnvhEw659i53cCwBIunuihzB5N9NP2AqQzobbW5+bcPsfvSRT78D97LlENq\n7Uv87V9vsXJyjN3u4DVqjLtTmtEv8ndfNZimGaMDnfcurHDuwRJqVePgwGd0Y43+1qvEnka9PSYX\nFQq9z6ULT7Kzv8HFJy+gNW6yfnsFI/lZnv/CdRolnVK9xRtvP4djRoyzHUpLEQsndVrHDfRygtuw\nEI6kYpu4ZkzFUjQ8D00lmGaOmzVYFb8M/TMkExNJhr8ZcHDZ5/DVJYL1i3S3SwjbJRJThKeT6ZL+\nuE+YRuxv71AvGbRklcjPMcwSWZpiWBpkAi2HIspYax+n3x2QpilmtUweDZHZiHTaQSsihEipurWZ\nGX7URaYBshCEUUI6DWk4ZcrYkGSUzSq6tBB2CV23qbtVPKPKXHsOadhESU4hPOzyEpZsYZslBJLx\nZEgQKXThkychaRSiGYIgDhn7Y/I0JE8VnnRxDIOKa5H7PXqHe1hCkoQRcTLFMnSKI2fUkm0z7XSR\nUpBZJihBEgSQxigZ4VhNbL2KrbmksUJYioPuITYGQuQYto0wq4wjHcOzUEmEYU0ZjXwm04gr/f+f\nk8GlVFiWhWNaFLmGJjWkbqByNesUZym6ITEzDUvPKZIE25Bsd3yCaYzmCoRhUmg5eQG6lJAV5EWG\nJmZ0Ju3I8wfkrBNbzAp1RcEsDo+jhGdmtp2aIMtSpJTctxk92magY7ZvVr/NCr1CKVJXkocR7Rw2\n6TJfrhMVKZ9oPcpfHX6fVVp84vyH+f1X/phPPfkx/uqNryKlw/64hyldpDCgACEsskyj0GZ2a5DP\nbFTVvdcx0wPMCt0CoUGW5Rimy2jc47WrV1lZnqdSqzHuOCi3TGm+jKVbjAufentuNsnRdTShUXUX\nsSyTLC0wLYt+v8fQ9xnt3yWJAkaDA4o0JkgFnu0wN7+GUq9iOwY6Duu315lrd1hceQ+GZdNotLFd\ni1wp/MkYPwyQmqLqurhlF8MySZIUU1dsbe6y0GoxHPToH+7yG5/5T3Ecm3/9J3/OsD/my8+9yj/6\npQ9TZD7lRptOR8M2DaapjpIGjbkVDM1hNNrnsB/x1t5tFtt1ak2LwfiQRrWOoduszp9GN+p0u328\n8grhNKBIMjqHe/QPuyy25tja26dcbzCKAizdRGYzK9n7V4DGD6WAz7Z79rf3vs/zfBbopySQU6hZ\n0p+6Zy6AAm12vQhtBozvn0uNGYgFigJ0XaIhEIWG0gwMY2aIkOXpTC+hmE3gCsjI0aU+0xiJmTZE\nFQZSv+eCNTtWpSllWydIa0hrQlk7xt++8hXm6y694ZQ19+McX3g3r129zMriWUobGaHXp4ghFhGW\ncJFyBnwLBUcqlB/75k0NlhuKwcaAqyGMxhJ9cIxcJLy9Ocbz5kkCnVubGo8/VFBuZdwddlnyLbo1\nWDzbQj7fpTcJqJlV0jwg1QWBERMUQ/ykhxaYVBspWhEShGPm5hrUqhXU1KHSVLhGnRMnPDItJElC\nMqWIc0WhTMJAYus14tTGNsrs3Nxhbz7AO5lQEYLUsNnphoggobMTUjPbENpM+xnGpIKwTaa9MefX\nlinPu/iyy9Dqknsugab45jef58rVXZB1ImmSWxqaJrmz0WUQhRx7ViOUGsOkh24Jttb3qLPE6YfP\nM+roTNp1dq6mDPe2wYooVU1WOM2dr8Olp1fQH+mwrW1wunmKw0bOcHfIea+EmOwhhEajOSH2erit\nHK/hoek1BvtThrFBHhdsFRb+HRP/sEXn1Yydawa7uxG38wlFz+Bdn3oU7SWTvb0u/WTMzcEhC+2Q\nUlOiSgL6GaaosHnXh0QS+DmuYdI4VkMbDhmYPVJNcP7njrH81Tlee+U2T31ljWO/mHLeaFH+h+d5\ncfUu24cjXv32m5S+32Sq1bm7nnP6qRallSpe0+bMgwXmbpvbmke2ozjcvsv15xsc+3JK+YmTbLNL\nTYsRQFbKSPIRkRYiVZOptsfHPtNA/zmL5x+9xre+8y3+8//yk8QvHTI+0Kkb8wS+xc72GCP3qFol\n2s0lupvbyEqAVdJA00hkSC8csXxhAdc8iYwd7l7bZnwYkmRTDncGJCJndBBCSdIutxj5u9S8HK9k\nYUY5vdsjGq15ynaDfGTSvwpbm1Pc5pgkT7G1iPX9nFrVRrUVxiLktQnjbIxlZ2hiiqMy/L5BFmcY\npkcp09CliRYbWFYDMXJoVQ3W1hrsj7c53N9mvg35KCboNVCBR71eIcsssoOExeUa9bJDrZHiE3Lu\nSY/m6T5mFnH2eIn3vv8cv/8HL//Y14rDA4N37t7isZ/5Cz71uQZ29YugTqJp58jpEJJSo4Fb7yEM\nQGtx7drzHH9SIjWbhabFKBiT9SdEKqK+aKFbi/TzA5KkoNPNyFMXfWTy9vc6HHTgIJQEtQXalUVM\nEkyxy8pZSU5EiMDRPNL8EGlCiUsk03fRbH+bw8aARvxTZHGEoXJq1T652jxqaAqkrKCpEU6piVP1\nIVvmwhPwwHurOPN9emoHg5zd4ldmmrn43ZRkizvqMm27TXvV5p985kP8y392k+7OE9x4NeTuXYWe\nz1H2BGdPFDzxEcnJj16k/fiLfP0bL/DGN+rY+7/CS39+C2lVeeIXHqIbvYVnN1BagLQG1OcXeeIT\nGU9/aszpQY/f+93vsbp2gue+9Ab1tVOMOzGd7Qp//vUvc/Hc5/jWN7t8cu0M5cWMj//XAy6Mb2B6\ngu53PsX+RofVmx3Mx46TeSHVhQ5LCw0qy68xnK6QqlPcuSbYe/5LPHSsTgeH6cSn3Cwx7Aw4ddHB\nWYqoLOZ4nkJJRdePkJlG1ROUnJzji3M0yi2mqSAMB/RvVll/RyGmJ3Hqy5jVm2y8eJvhto2elLGM\nZURTMRI6nlcm0TSGB3cJpz3yQsPRTYzcBFlgl2qkakKqRXS3O9QNnbnyAo5VZTToszDX5nDap1Jr\nYxQ+06RP3XaIjAjDM4nNIXcOdjD1BBXHyDwkjjXK1RKToIv0GmDmpEWM5VgEkzGOpyM0kyzuM/YF\nuunSas5RYOPZJ0h8xYQdShVJur/J4vw8k/E6jj2LTUCDaTigyGNKZhVhlrFFhSwLmYz3yfKA6WSK\nLOagMKl6dQqh4bk2cZQhChMdEysDpZtkRY5dqqDLBN0sQ2qRThWFnlG2DPIip6zXKLkG02SP4aQH\niY3QV0nzCUZhMslslNSYTNJ/p/v8R4wK1jCkxDR1lJolDQspjwS2BTKbGS7lukaeK3JToEvJGxNx\nRCHJEMIjT3wMw5t1+jUQmpwJdXNBrhWI+/awBYWmKPIUIWfuTYpiVuxpxlGKs44Q91SuR65U6t5X\nkLq8txulCtKiwBA60yzGFIJeHvJk6xQ74z4ffeQjfP6FP+STD/wU2zu7fHv72zw+/zh/+d0/5/jC\nGm7qYUqbKEnI8hSpCYSU90XGhUpRSlDcd4L6gb2qQh3RdfLZ61aKaqXJbmfIO3fusLy8jMoUgVFB\njDusLh/HMm3G/pRCaNi2RZYkGELnYGcPwxTkeYakQKUpk1EXQxcICkzXYTSagCaoV2uUHcHpYwt4\nssHOXp9KxSKJfQxpkEynpGGE4znEYUir3cAwTMIkZm97k2q1Sp4qbENn9fg5xsNdrl65zDNPPsHm\n3dv8/Kd+gaWVNf6r//5/wE8L/vILX+XX/tGn2d1eZ+X4Coa8SMyUwG8zHg3pdgfUamVUobBPnSBJ\nI67e2GRxYY79g5DbG/v86j/+FRbmVhE4TP1dPLNEojTSMObi+fN88md+ls/903/Kzc0tmo1F/LFP\nqdxgHIwQuoGmZhqi2WRJoWlH5gI/9PN9AHpPo6E0UDnF/QnU7Jii0GYmAijICxACIe4BEkWWpTNg\niX4U+Qe6plMInaJI0YUxAzQUFMXsutbuZ3kc2S5rGsy08LNkeQ1QAkPPyHNJoTqodAk/3adaPY2T\n53z2waf4/N0v8Ozaw1y+vc57nKfoNDawIo9pEqIVGposZvQ9NTNoKPjJ2E6dfVeZp3/mAaLoBl5c\n4cZbVTZuh9zZ3OdOZ0jz2BoinvLWyzvMPeQhoz3qus3TK8/wcq5x+e1rXLveJ9MludCwXYssT7AN\nA2++zeKJGpoXMu7toIYNzGrGcKBhFhqTyGeuaaEZYMiINBoTRxOYpKRZjmaVCDKHWm4y3S9oGC0m\npQT/ICJXUEgNfIOh73H4VsT4ZsqKOI6MDFZrixiZiwpT1lbnePIj5+gd7LN1eIdeLWEU9rDHLjee\nC5jEYB/3qDgei8dM8FOCQczddw5xTlrMqTrTVFIqWWjelDSR2FWH/mGI9BROWxIFEeNiyPwlj/7o\nLL2tu7z+ZYVYNXjXf3AOI4nZZ53KwhKts1VuvNTFTxRZGqJ0nSuvHRInOp03B2Rjk8VqiTzVcZbq\npOMq0WaC1TUp7drgb/Ie6z3opZQPvG+N9iX4zhdfZ3JryOHWHebnNYyGQsgC0/RJMLnyxjskoWBp\nZZnKqkkqD3jwEy6nnnFJ44xoZ8ijH63y5l/3+Je/8Tf8dw99gORShKmFfOLddY79nsX/+V9scvVr\nb+APTnPsVIsbrw8wawEnT85TqzrMl86w8t4TNNOU6q0H+MIr3+GP/6d1xn6ZnX/f49iawXy1xGSj\nyzRUFM2CbTrcyXLKuuKRRZ1Hf+vDPP/eP2SpFfEffvpx/uD3XmDSbZCOC0phBS0x0JVOPpDsD0c0\nThWzorVZop+EFNUYu6oTdPdxRA2rqcjHE/Q459L7Fqm2Kux2DhgdTkhzxUrJJTdT/EFG0Y+JDkPE\nNMOzKijNpb8rcdIGXsOiMZeh2ZJjrs/csoeuEpwlC1M5jPsmrlVikiuicUE8TtGKHPKMspw500zD\nnCjPCcNkZhUdT6maCQ9/epHFZZfXv7jO9psZRewyfq7CdENQsh9ENlrc2j5gnHbwTobULhhUykM8\nNSWYpJQX6z+RtaK3F3Dpicf45D/JMasJGmeZaFVcBGkcYOjnCYN5tt7sEnVdrl35KlRcTl5aINWu\n4ue3EfEco02dl7+zx6f/ow8wjm6xM4hwrCpbtxK8vMXmlQ7DuwYbOzluawnbrGHbHnmW0m4vkQvY\nnbzJYqlAU2M8s4qmrRBPq/SnL5D6J2FaYTreo9uPOXUpRZT2kVpCqI0oGKLQSTUTq+RQrVRJwi7J\ntEJ3tEWlEaNbbYJkjG1WGUSKtFhHJBaW2eZOv0u5YtFcrbJywuHya7cohSaZXaY2t4BXylHlPc68\nt8y++r9pNXp88N+zGHQE0yLn5tWA737Fo7Dg+BPvITV6VPQJ1cUJpZ96DlnYyPoKKyse82fH3Hr9\nEfZvv4drL4547N0Wu+90WVl4mNe+9RoffvCjiMlNTj1zjKIW0fQOmH/4+9x+5QSJVWKh7oL3ErUl\nweRA8c7kdzjwJSvuLzE4GNLfmKL7O+zspzzw8U9C922+/qWvc+oRE72iaB7zSEVElKW4u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cjb27Y4pqxIknFpAipwg1NGmg2RJLGQTdnAQH7SBm+5ZCXx8zxiccayhNMT9/nL2DCQz6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\nLcCTqvqtSVmuA65V1TtVtVdV7wC+AfxFlH4VYd1zTVT33AP86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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb754543b38>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . . \n",
+      "Iteration: 30\n",
+      "Weight Adj. for Content: 2.66e-11, Style: 1.27e-27, Denoise: 1.27e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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LxnqX2NNAjbBZ4/InxjRfuoat3+Hbr4353v96nu++8eV/O57/XX7UoAFA6PtIJZBSIj2J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\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UwemQDzKyLJBQUFSJvJCwSy6qppEkpwRr3VJQZQXd1GnpDn4QUC6VCaOA8XhAq+OQJSam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nP4Qwkt00hig9Q0abuvk1MaDJq3yCs5Wu6AuapEIFLkqkkj9Ij8OpkTkT/7CoY0x0cPn+a177/D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\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MrefpRjGW71K71+f+5gMeX59idXEZYzKmOP6VsM8hbhgy6ZjsXTzi4lSMf2TwoK9wyymN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zO2nLFmokgZ22PZkRVLsaMwsiSqRZTIUCIBNoAAGzp2sYvte+qe+vb+Pv3Oh3epryGlse5v58uZ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gQpa4miozDkq2Sto/RaAzRVJR/M8445xOLGZ/jV07+MtQ3fGF/ncztv8IvKJNGJ7+bezTVe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\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I3/eoz5oInVMoCuK4jVEXHKQZeaFKMufgL5Ro30zptRPyWwpvSRBXHNwzGlmD+pSmcdgk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\n06maMAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb754473908>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . . \n",
+      "Iteration: 40\n",
+      "Weight Adj. for Content: 2.73e-11, Style: 1.16e-27, Denoise: 1.26e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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dm99gsd0niASxLxnLOwS6Tj/LiQ4X+cb//joye5a5029xodlm83aBX61z+36b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TAAAg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\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4hGCtWwqqrKCbOk3dwfN9SoUSQegzmQxpzjuksYlpVojjEc1iEV02qDfmUZSHJ2lWaY6c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\njk2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axANB4B+yf6vk6UWNrZdOcF3uMBE5gV8l3Ic8s4gzjaIfYtcqnP1ihc6JjDQ+JDjq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/zx72zh6Gv8s1//z6gsKuz73yXsGgw+jJh2xsSpYCi7WKdP8FObP84TH32MRx9/Hrs85PrB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\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8QYq33udJZ4ntsMuLz1eoPP8cP/zGNeYvzNI8DGn2Y0ppkaMrEYPjMfZTfeYuleh5Y6Qi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\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pjFHO/ILJ2nsk2dIt1EwbqzJhcc3BLMHBeEJ31Mf0DHRTp9KwqVQ9Rr2QJClP001jHd/y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0C2L7B1dCfnmifJFgp06x2yqTS6qqMJDWGlEEaChmMj53K0szJ2yqTa0tGUAGwbM54jcGsU4gqy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\nMcYYY4yZdRZoGGOMMcYYY2bd/wM5pWqUtburCAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb75438f5c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . . \n",
+      "Iteration: 50\n",
+      "Weight Adj. for Content: 2.75e-11, Style: 1.12e-27, Denoise: 1.24e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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LzDXPUO5bTq0tEnsaqBE2a1x6ZUTzhavY+i2+/8aIH/6jc7z21tf+9Xj+N/lpgwYAoe8j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vo+lzbfZDEeUGYzrFBU9jGr2z6qe0BqB9hMQOWgK5dASYzJWZxl1N0tQiTz4xek/hyjoXRdJrMz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sWdP7XOf8qJxkLWJ4RGUSxwrItgeIFSObphglVQ8mwqVZuyk+IYGo5l4tgCy8yxbWsh4cuT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cjGgkfv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\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N0pA1hTwTTKUQWQJJzlEz0HRQFRXHMUHOURQFVTNRNQ1Zl1F0Fdu1yLMUy9ZRVY04ifEn\nEbKqoKoSeS6hGxZplqBrFlmWIDj55IOMLAskFBRVIsslbLeAqmnE8QnBWrcUVFlBN3UauoMfBBTd\nItMwYDTq02g5pLGJaZaJ4wGNQgFdNqjVWyjKo5M0qzRHzsC0TIJxeKJmaBpCkUHI6KpMSdeZjCaI\nJKKRZTRKs9ztDvn9t9/hyC2zKFVpavOcHu0zu+ZgLbuUz60heyqnKi0e7XxAlvXB1pGyHKYjOhMf\nVVLIhEEmEmTFYWPrkChImGm2mCQ5H20fsDUY4icxuS3zpaLMlS8+z5dfeR1GNmmoIVyf/fYd9NTh\n0Xobud7gvnpI/eIy1c4I71QBJ44omCrtj++y2Cgx7I2pNqv0lCEaCpmmgZQxnSaosgyaSp5n5JKM\nyFKEEJimTpbmaJoOQiEVgiTN0DSTTAiqzTqkKWkqQQYlq0SjNkPBLTDxAtrjFBFHtEcesiRzamWJ\nD24dIxD0BhOyOERSVM4sr5FGIbX6LA8ePaE1U+XNv/oB165ewh9NKJ5Z4fkbS9y9fwdZuEja+7z6\n2u/weP0mug6jkc/j7Ud87auniSaXmFnqc7RdY+zt0ZydYTKZctzNWFyu4VSg2w3Q1XnG40MunbU4\nPNxitnaFXjBkf73IwlKGH++ga2cYhz8ln8xgWMeMxxayolGdEST5EoarYLj2SWiZoiJLKlku0BUD\npByBQEeQoCDSnDzOEEmCYepkeYSipIgsRKQhWTRFSlOkPDxZi8oEuTiBZCropGmCrqloqoIMRHGM\npVooskye/xxy8YEtMaHgjcjlKoovsbpk4K89RXb1GR60ddyz63jZiInIETtFmrUyN55vcOazOcP3\nY2LDZ3nV4jiIaIfrbA0PUK5qBCInVaBLxLJh0ZvGNAyVQ7HL058rs/5EkI1h4wdTsuk8w50ACkUC\nyceuSRiWTxaHNOcMjr0tjMsaWWVA45TLmlVCKhxTzlS0sYFVtpnphKTWLMPURJMG6GQ06x0efE8i\n3J/S3Qno3pGQuzLBkwlaUaM7sNALKt3DMcVFF0mtI8sK3ScHVEqCXNf46q//Aq2nS6gaJLHMT753\nlxSZ5rzK7/3aGzQWDJrnC+SaD9qYekNhlB5hL6bMFGA4/R6GnRKKKWtX4eO/kjjaCLl6TmGy6+IF\nZd799iHrN4dUwgpxNmauWubs7Bl+97XP4mUd9jdcfvBHG9zp7zDFZjXrY5UHrM0apEabm4ffojl8\nyOzZfXpPMtLjnLXZFa783jXSuy5vf+tjXM1kS4N62WCCj+mqaI7NsJ8SRwrFcolM8zh84qNmNtJI\nQlMyCo5Ec8Eg1wscig7GQkq5HFHXHFzX4pOfjLn54Ta2Y3BjscnhT2KaFywKjkZ5UeX8eoVj7Zh4\nrcjYPObr33tCuNvjC585j33HQq3MctiPGSQBiSphaAqWrTLxU6aJIMoGFOxFKnKDtNSnopSortZw\nZ32KF4v8yj+pUxcQ9BSaxpTVS+c4ethg7+2UR3seZyd1RrtTkpHDwIk5fByB7NJ9YtMLepx9dYkH\nxgZvfjeiWg6QCisUayYMc2Zrdd4ffMSHyZ+xJi2SXixwWnyW4kGTp8rzXP+9Gea+FKHNdyHsc/ze\nEJUI15aQigGq6DIj+xQ4pjvTx9uPGCcS4VhGn9iYw5CwESF7KYnZJYlVHMNFzWS2HwtefFmQAzog\nPVYIdyXk5RUC1SShyzTfRGrLlKWfz1AiyH3UhR3KZ1SS4hSnlDH1YgznRMXI9ZxIilB1FSnLuXij\nQK1iE+NzvDdCK0iMghM1UHIOyRQQIxvTL+Dvduh3bHpBCyE7zM9fIQkTzi5ewM7P8t6D/4qnzpxD\nKjzibP0iH9y9T2VWYuuBxOzrA4qFdxG8Ta2VUb4gGMYQD2XGjwWZUsKbLmLZTaTqA+orU1rnBUEU\nEHTfZtpPSdeXUNKEUd9D7ZcRErimQ6m8hKGXKBSL1CyF6WQEbJNFCmqa4uQxppSRHPsEkx65PMa0\nTWq2ht7fIpOLVOrP8sN313nmIhw++AmRY6GNdyh3FaJ6l6P9mO33XqbdOQBXpj4Pyxczs5s7uQAA\nIABJREFUensDvIHEqWeeEIoxC58c4N+uMWsWmZ3dIJE9+qMjEs/l9ofrvPGV69y5+9ecPzPL+zd/\nnwuXz7C7d5M//8MSy/Ov0VjIqbZidv9mifZEJplYvPbpi8TBfb72mwtsPbC4/f6Q4Vhh7O9RjxfQ\n0gELcyVCo0fLdei0c0ZBAfCQMw25KKMrgs3HA85cXqPbO8YVKpJ+zPUX55DGC+xu7JGaCkaxwnA6\nZeiFREEPLTQwsVlrlVj6WhPNijA/Ehw+Trj/s4DhE4f5xRJmOcKQJ4yGY+YWUuLcYjKMyIQCpRS1\nLGhmETf0Kj/+6z6721BqOXT7I2JFxnFtDEvioJNQm4QYio2QE6b5ANOWSeKMILGYqgEXL2o8+bbE\nl575LexpCzVW0KY+s6sz7Hjv4Gl3uPAPnvDSP3ZxFr7Jp3/xLFs/20Ts3UFbGjFgTA6siCtI4iyD\nBy0WnQrxmYSZap8Lz+5Rnm0R8H3W77f58MNtwuAi+t48ORqdbszdH13HVveZ9u+RZB0mkwYbt6u4\nyoAgOKa/vkg82WUwbFMqZJw+VyGMYoa6IKgOKDZzpl2Zve0Cxxs2TzjiyotNhoR/pzr/ezUasnzy\nKUqzEyVC5CpRmiLJoOoaRpwRqym5AEvXyPMc2zKwLB1VVVAVlUKhgGmpqIpCLucgIEliRC4oFFyC\nSR9VNoiiGFUzSJMc09TwAx9JSk9YGyJB5BKykoPI0VQDkaeAhO0Yf0tCFkRpjmVoaJpAU2R0TUak\nCuWFGsORhFsOSdyIYOwgMgVV86m1dMIsRk9kHK1IkuYnDBBZIUwidFkhSxNIU4SiMpViitmJoevN\nwyn37g8Io4xPrS5zobeLqXVRymXWXnmFRrOJFPhk/R6RJrjb7eKYZbRUY9A5RrEUhqEP4wxJV5hO\nAoSiM56ExLmKZqjs9oe8d3RATxLoasqqKfGrzz7Fpz7/ZZTcZuJlkB+ipD74DpXaAhMSmudXqdbm\nae8ekhwdoxYM7FQiSyXSQKYxu8wgSVCaLjvdfRquzdifYJomw+EA1y0ShlM0TSUMU0zTJg0ESRji\nWjpJHKEaLsPBhHK1zMSLMGwTkSmMJx66pqHKGlKWY5kmM6UGI7/PwmKLg5sbiPxEzSqXiqw/eMBC\nq4XnefihR6VcIQ58XEVHr+QkWYjlalimyuLMeSbjHl4/5fDwmPmFnE+/9Mt841//jzz1/Fd5sL5N\nvTZPyZZZPd/iU69cR1VdnOIBcaJjF4YMew7DXsw4GmLaKVF8jsHhAWfWniORx1gliCYrLC9D52jA\nYfsJjdkFRn0dpxpTdgXS0Ut45tt4nQalWpnGvEkiJGaXNIR6QqWNwoRG2UKSDZI0Q1JAyk8mN5kk\nIwN5pqAAuqITxQGGIiBPT9JJRIZCjkRKJhLyOD3hwuQCSVFPppOGgeDE/K3rBnkak6QhpBIyPx9g\nX0M6w2nriL53SGL5NPRV7mgNLEcjJUbJBFgSxkjG7BZ59toCZs1nYndovqCx/uSQ1nkNpxoj0PjW\nvR2uPu1iVaBHwBEjBvqUzIdMZGSSoG45BCsG3naZrc0EyyqT6SqjWCHXU2qOgWUPcNwApdjj3NMx\ny5+pseNPSMMeXb/HqWYRW1kjrOyR5Qlb81OsrIOjmxwMuzizMrEBm+/CH31yzGrjAtq0TD2dEHNM\na6WGl0yJ0pgCMlmWsv/eNq1KizDwUKs2rdUicwsWTPY5DCd86/v3+cYfR/zqV8/xxn9ygV/+JzOM\nOsecbxocRyGaoXEQbiIrR5iqxoH0MX7k01dg6wHYaREtjzi6pzO+mbJUbDDNFOKBTNGuMVMqsjg3\ny9rqLK+99BJLc3Pcu5vxB//y29wLRlwUV6lKGsVlCZcCN7/+E176xWuc/docn8TfRGtAcOxTtRb4\n5N3b9O/fpdBrkaQyzRccnnFraKsynScJ8cSnuVLA0VVMa4aUkKIrQWqhpxmaamGrGjI+1VaJvjoh\nqSecfl4iTw6pVgSToxGrFwzc4kXGhwkGsPdRFyMyMA2NUtdEmrHpTUYcJz0Wz9dYGTQJzQIHnsyt\ne32yuszhk108S2cjHPOgfUx2EHD+yhrFGY3OxhjEIU8/9wrLM1X8fZmRP+bqtTle+49WaA9u40dN\nRF6gsXZEQRqRVSLK8w7r+7vsYzAVY77zpynm+YSt7S61+bPs7e7R3xQI9y4f3ko46koUSlVm5zTU\nqxaGUWL6k4xG7HC98ipb/X28kssX9Iu8/Moaa5/2GS3/AeKaS+pL1BszLOQGH/zoCf1HY+YuzJKX\nQwro9PHI0Ng7Smm3ZXbXM+pawOwzC3RKHoGTsKSEFC0JFx0pFHiP4V/+C3jtiwrSpMHknoErL3D0\nYMDSUp3Q7WCoMmo9I9z5uTwVmLaCXU5JjRG6pRJIOYGWIxOi2QqGbZJMQ3QlwTEkypUYtAmRpxLX\nLaKojDPbR8kPMXMTb5QSJwHRBI6fNJhOQEkLrM5fYPnUHHPOZ0j6PZpLAc+mX+Cie4HHH/yQy7/2\nLPnst9kd/TEzV3p43hO6+RMWG69w6eyXyJMxarvHVnsDa3wVY5Ly67/6LO/eesjcqW3khY8YuD5S\nUWNazNFWMtz5x6QTKI5ksuMB/paNps9TdpvML51HLx+RpG8Rb21TUldJAgVJMZhmKX4YYZRd6nWZ\nQBtQXeqjhFP0JKJzf8o//q3/lixM+P7/9d9TFmXGOChWmYknE01qVHSH2+/6rCw/gxe0efjJB8TB\nJyS+w8LsBYbjI4Z9OLVyluMnEoWzfZbPxwwGhwQDgd9TUKNf5MHtKvU5ldMvzCG0BW7+KMQtnePS\nVQdZ38TQzvP+zU+YU74G5mOefq7LzieCsX+HleVl7FkwmxHsVki6O7T3FC5c+kfY4ydIyi2O4g4T\npYOqNHF0C9/rsbUXE0YmRkVh/7jPpUylvachJRWe/9IBSnSTj25N2NvQKbUCjFKOrTu4imBmWaXi\nZHAjpj+6jeeBuXxM2JV48/dVktEVPtzo0FrzGXlFvK0mSSulH4+wLI1oAI4sI7wy03iC3eqQxBJP\nflqipmfULnkg2XSOIdMmmHqR4XGIrSeMxwJDN2lUc6ZRQioFTNoacafEtVPPkB2WGY5iTENnae0p\n2ul3eOl3MhovHtKebJCVm3jBGs1yxNIvfZ2Dt/ewKgF+p0zvgzNs759nslmn2riKOEoossnpiwOe\nemOTQPoeOibNCy0uflZDUvv89Lt3+fAHs+i1NUqGzN59hyC7ThJOUGyJzvY839ncIvSOyOUBMVUq\nlRobjzc5+O+GLF3KUWaged7Gn48ZjBPG+zYyGmka0NnLEcfW36nO/16NRhplaIqFyELyPCFOPRQ5\nIUkFaRIhqRKOYwMCRWSYhoGlOVh6AdsxUA3QTIlcThC5gqppqJoMkgRCwpuEWGaBaZKiWtYJNRxB\nFPnYpkYQAPKJPwPlJDVEqCqqEoCkIxBYTokwCalVXPBHFAsWMRmSY5GIDLNUIgpiZloZ06mEaRaR\n8jFSnKMLhxIKutDQdYMg9dEMDZEk1F2b6SRCqBJ+DrasEkcKaZjwTj+gJ5k0FInnay6mnOEND7n0\n/HVqc3XKjkU8GTFpb5LmOYZtE3RG6IqMr8a0A580FeClaGjsDw8p6HW6vSn1ZplIkRkpCe88fIxk\nGbQMnfk85tLaGb7yK/+AcqWCLpt093cpWzJBECIMGywTPw3QrAqhF9ONj9BNnXKjQaZa+KGPYghy\n4ZPnQwpWARKFkuMimxJycGLeNywZTZcYTaCkaeSSTDKZIiOhoOKHMWmmEIQRlWaFXq+L47rIyCRZ\ngmsbhNMpqCqSEEiSgmbYFCWNapwwu9hGKrr86N0NJNmiXreYZgkiBoHBaOBjaQrTNKIxM8O4fUzd\ndNne3+P8U03K1bMsL5xFUUbkvkOtJLHYfIbV1nV2t7/B1Yufp9d7yMJcztETj97I4+wVm9G0zWTi\nUJ+HLLZR4ozZxjy2O6Zir3HUH3LaLSJPdXTtIZFvkGc+hj6DF3QxHYOZ4jKbm/dxrSbeYRW9qqI6\nCZKhIOcJUVAgYR+5toBbKDDxPFxHR/yt4VuSZeI8w5YEURIj5xDHGUJJkMMUPx+jSFNMTUIlIyUh\nz0KkJEORM2SRkuYJZBIImVjKETkkcYqsxBiGBcnJ+lSa/XymlJ/c8zDNNkLKSGyZ3sMO/nHOk+1D\nhKKjTAU122Ls5dw4c5r6uZhutslBtkfYiimupZhFB3coiA8l2j/scfjIoZzJDMwezZaOpDjYxojg\nWKC4EiKWKdcddFtisJVAPUV3NZRAQpd1Ko0ceyWgeT7jaPCYp15oIU13OGXkXCm9jCSVITbZFm/x\nn/95zJkrQy7n0KwL7tzvMi4Kciej/Y5EfEvmVltj5tlZSmfKfHJ0yHG7R2VSQ1blE6aMYZBrMHN2\nFkM2cYYOU3uEoU44Gg/IJ8dMtZTWdZPXV0J+5SunEI7HUPyYQsNjFGhE8YgEBYURquoBU3Zu+tiq\nTKxK7LybURBNkl2VvG9z78Mhm8c9BlqOZrlcuLHCqjPLM3Onqa1UUI0C//V/+eeIocF8fJWcGEOW\nKRRshDqhNzhCLyfsdH9GbBxjnk94HHVQAoE6sDh7tkr94hrH76Q82NmlH+5gX5F5/nNz/OgvPY73\nInTZBDLiUYiqKGjCRspckjikVCpB4uEHe0yNPcScS/FSCV/pYqdHqJpAbQgcuYy77KCJIns7Ht4D\nhTtv9liwmjQKFdxKiyS7zXHfR8pUypZDlLogC7a9lJW5GcZ+zG/9x/8ew2mI1qwhBTruTIWsl9F9\n0ub8lTmqjssoTfnKr36BP/yjv0YxLHQnpRRIFAs6e/s+lm2R5oeM803k4gwLms2DnY8Z7/XZfCLz\n5d+7wcXzNVrXqvzff/rP0VoaQtG48aLOM197lZ3uAUcHPkLInGmZPH5/xLzkMzdZ5nvTLdaYoyKN\nCZxvYqwdI738E1SpSWzUmIQNtKUembPJ9s+OUM4MmD2vIUqCNCzRC2P6GwrHjxXCWGHrscLqtky6\noJPMRIwAfZCjGSrxEZRFmZv/fMCVvVeQc5PgOMCdK/D4wQOuvS4IsjG6pDHdF7Q6P5enAlmu0e52\nqNQySs0UISQMBfJIUDIz9FRBmCp2wURWA4QOQaIxJKTiZsjFDv4E/EhGtWUKygKN9FPsHLUYbr9P\n5+gxK/UZXnruVyg6S9y4dor12+9RKbuoORyvTyjYr/ONf7rD1Rf+Q2rKJZzsx6xeXaPbGbFU+IfM\nalA+U+D0DMibIUuXTyP2/5T5ymmuX8mInQ3C5BNUB2I5RY0Fki6BC1ZFRQpT4iWDjVFASXJx6yHF\nSx8xu9KhfXyLWLJgP0FGYAibQpiitTySwl2yuQHSjE95zcHUJPYfJ/z2F9/gt/+dz/Gv/rOvI0ky\n/X4XT2zzS19a45lfsmgUTvHP/oc/RtbqfO7Lr5KaJXr9Ot/9y7vYzixbaZ/NwwxdycmDRRxjTCZm\nePT4E6RqRpzN88HP9jl/qs9TL/hMog3s2RGDvQe4c89w7TmNQmGLnfWUm7ff59LyP+VA/BCyhLx+\nxP3dbebdT7P+scFe8hPavVkU+SqWOmX38RGfv/Elrr34HP/Ff/MKffsTBhro7jGqJKMaGvPnHMSp\nCQdPIvaPPCaeSa8bs7DsU2rqpFGX1fMy924L9h6nqJaGVYBKY0Iuy4yDnEiTCPScvCxhmxIoLk7N\nozaTMTdzlgdbb1K0zjLYrDB7eoBmx0xHMXpiAwmq6iPpGdMEVudnwK/w4NubWOsV1GaMXhKUlg3s\nRogkVHK/yt59n2EHzi9WyUWHIIzoPi6zaKxRKdTZ6cQUSjWGocTe1h/x1FfvcvZXyuzEj2hdkJFM\nD0e8TDt8C8MKmFmUCSYpt74hY936PLPRL5B5Pl07IvRLlJdUDg6+T2fUo1Qu4okFqs4lSs4DPD7h\n135jiTdef53eJOXRw5vcekvm3ntFnPQy+711jKLLxE+xaw0ypYCj1fB6Cd5Ax5VT/HGHWN1h9qGG\ns5ATazEFNaPblqkUFrj74zaD+P+H1alcZKRZQp5lIElomkacpkjk6LpKHKTEaYSiahRdB9uyMU0T\nxzXRNAnb1snznELBQVNUMhETxTGyLKMqOqZlkkchqqqRZQmSJJGLk4SpKIr/1gj7t5RjBLnIyUWO\nJBwM00SoAkXPqFeKyCKl3JzBKdSxpx6OouJ3j0jDEF3N2TpMiaZjJuMp3XaPo6MuWRZx3E1JVUjS\nlDyVSFNIUBhMEhJX0EgUKorNw70DOlLG7tRndbbKaT2lOTOLZepcvnAGU8sJxkOGgzaxp6EbKkkO\nUi7hDyfEeUKu6kzaE4SkEEcRSCq98QhZqdLpRCSKyU8fbTLOJmwOM+bKKtpwit10+eUvfJHnLl7A\nUiyi7gCt0UKVZPJcQTIUdEOFNMcwNSRFoVSrYheLHBwckIy76NU6euqh6Rr+MGB2dp79vT0qtTK+\n52E4NTIZMiQUWSHLBI1GHX96TCynZJLA1HTMgsN4PCITKXkeMej7FIoWMhme7+OaDpNoivxvqO2g\nCdAUCbtaZa9/hG3aeLt7NKolwlzj0c4T3vj8F/j+D3/A6soqWRJjaApiGrG/vYnnGly5cpXT51cZ\neiMmgw6arDJTn2c8GVOrLnDp8ml6/V2Wly4xGHq0Zm+ws3OLLFMQssVooLLfzrAUnWE3JYoOKVQq\nPP/8KdYff8ygf8hsa4V+2yMMj9l4IFFpQCIE8wsLHBx5gM7h4S6KopDnUKxoKKrOZDLBIUUyDBAR\nuVCYTEZoqoFmlImiCaqhk0sZMioagpgIkYakeUyWntzJEhxTIU5TwiDCNQ1kMtI8RQLCMEYSCaqi\nIXJIM0EwGFEsFtE1lSTNCbwxmq4ipJOm+Odx/C2DeNml7Q3wzIxeP8QcTxkPdXSnyoKrsn60TjKU\nqJ9zKBlFDiZTPL+NvhJTKpeZlVSShkOnHrL+SEXq2+iRTrpdwPxlnXgpJy1JyF6Okht0tkMm+ymO\n5fLK58+z8eiYzEtA5BiSjK5nyPUJxUsJjb7GlV6TQ8NnoXCVLg8YBA5Nq8J0usjF0pjokc0jK6Cc\nyRiewOlKdAcq0XHGmdPn2WhDsJuQ1jvkpRxt1SVTYkQoMCY65fk1JlZIVxvSze8yc0Fw+dkZ5i64\nxMk25ZkaiQFyVmD4YEzB7OPJe7zb3eO360v4aYycZMSxIDH6DPKczbagmEoo4ypv/0kXLV5D0mYJ\nOwp3vr9Dg1kuXlyisNpAWdCQc4WGUmGSSOw8eMB7d57wl7fu87vXfpPPPH+dqJ3T3vCZWG3yls14\nV+UV7Tp5/IRHBze5+IaKdKgyX2wx9STKM0U2tzYZEGNfiXDO5GD1GB57nF0zuXFjgXZ7hC6ZHK4P\nGe4mKIpDbmoITuLMsyDGqajESow7axDsH+Fv7nOmIhMlY6QWKEs5ZD5Jd4ClCc4Vavx0fYfJ1KW7\n7RM2+hTmmqw2DGJfobW4xHAwQbJ1gqnHOFFxKy4XnzvF5u37PP3iaabTCbOVKvmOx9MXLvDFX/oC\n417G7fsHfPV3Ps+FrS0cRydIP0F2JHTnCS1lkY4YYtkmXmefw52AlZUL3B6cGPTtWo0Z/TQLcoz/\n4QCOZhHVjNqiyZXJHN69gEZBZvWlKh+2uvz0f/lzckvn1eLn0eRTpAOFYC9D5R7m0oCj6G8YJvdR\naFLcfJq82UEyfNzWFEOkaIlEo1ZmJzxgKpdx0jrp7gh/vYvtljFmJO5uTpgoAYUL0DFg3gf1MGR/\nD4jLfPLxgB8tT2jNu3R2I16eW0BXS+wc7FJehlQV6KpFEk1/Lm+FU9Ow3acg/4R4coQwJGRVodgU\nWI5CInIMTUNVQ2QjwxsXkdQy5eIhsZew6D5Pvy+jeWfwHj6L4hkEqcH56mmma0usvXKaYdfiytoF\n1h+sU1JK2KLAa585y9CvY1Uq/MV3v0WteIHdT2JK869wauEfURopBHs7SPUq0/zPuPrCmOnsTVrN\nIn/5fxRYWf4UB7cFteoqRvgfULG/jCf9C9b7P6ZVhVRWMR2V/baPL0HkRdQqNq54BWkOhuWvI6Zt\nnN55HO8XSKYZUy+jMzgkUyOkaYfWBQtNjNGMjPqsxM7xCHfGxesNufl/fpNH731E6DiUm0vUmjpn\nLz7D9u23eRDcY6HxMqevN5Cbf8H88gCxmfKVX/80Fy/e4MHW99l+NMPSqYS7H37A01WFn33rFL7/\nEtP+lJ2dNiXrDBeuNJDdmwT+hNu3ekTeGWS5QjRZ4Z3vvU3RtPjKZ08xGP8JW4PvkMQX6LZtKktr\n3Hv4hNB8gWLz11lc6jGMyyy1PsWt927z1l/8Nd/+zrdoP75GZMccBR+xcD2nvPz/8PZeP5an95nf\n55fDyaHOqVM5dFdXp+meHDgczgxJkTIpS7YibAELLAynG8sGjLVvhL3xhW3ANwbWWhiWvdgVtFpC\nopVJMc6QnOGwZ6anc3VVdeVTdU6dfH45+6J0r6Xt5fs/fF+8z/s8389TIkpFXGtCEiqU8gWmZxKn\nz3xaax4JEYf7KqKQI85E5NyUuUqBp/djeqFE+RUTV3YQJYGsWKFzOgY5YXpmEHoia89VyBcekQyX\n6SUqvQMHWV5m//iMm5eX6PeOkMIYQ1dJfZ+KIjE5MSlmNmapwPCkzkHbgXLKy19JqeYCIk/CD1WS\nKKB12SNyEx59qMFkFVODmnGD0f6EPWOfxaV1XL3L5Zm3+eGDO/SzMe2oi14UKOglBDws7wleMiGX\nlLi8LPGzbxv87C82eL5UxTRllLkWkeCjqRHnp3cRw3VygYrMgDwV7HQbhIiSuIbCCkZlj/mywsbi\nS3i7fbp3e1RMgxdfu8bqG0OOzuqUqjc4vlsk6oFdbzCyZE7tT+l2ixgsMXloMf3JKbnqhPqsALHM\n1tM+J22P8ejfgdDIMhCylEwQyYQYMhFD1RFTcEIHUU4wxIsyMl0WkSQQxQRJBlVTMHMaipoiShAl\nF+jUKM6QRJkoTgiCGFUWEFIBUZJJohRJkgmjEBEJIRMgA0GUEdIUQVAhjVB1DdsZ01pq4vsW9VqZ\nSnGW8cjl6Z0nfOdvvs/RsxMcL0HN5YkUhbyTEHki0/4IP4hJFY0AGLoj6mUDEhlTldB1jSgIibOI\nrA0fu22mWkJ1scZSqcGvL60jpTGpltCqVZDShCDocXjSI5Yl8pJO4LpkLozGUxRFI0xFxsMJsqxg\nTV1ExWQ4sVH1AqmSZ3hmsRu57I0nGAUBLUlZl2HdmOGVL97ii6+9TtnQcEcWkpBRmpklTBMUVYQs\nREwlMuHiIRslCXlZJRMyzqdDaotNAs/FVGVSOUOUwPZDou6Q1sICo0mf5Y1LxLGAIGh4zgjVMLCt\nCYZkkEoaak4jlQIERJIsI84uaGI5U8fzXKIwImcWqBR1rMH4wv6OQgRBRMgS4jgmSQJELUeuWKeV\nuJx1R5yeD0jijGJ9lsHpKcsL80ytEaauMewPuNSax9QLkIZsP7jP4toixdkKg/1ziiboyk3Umsh0\n7FEulFBVj6a2yrm1Q7W6wsFxn3qtyNHxKQLXyMiQVJv9w11UVaRQvMn3v/cDxsOY9cuz/Pi7f8fm\n5S9wdHjAtVtXsCdTajM1MsElSQJk2WTYtzFzGlO/Sz7fwIt8zJxKnEaIfsg4E6iXVaLUIwkdMiQ8\nz6ZQLP19G7hCSkKc2Bf9LplPFofEqY+Shnipi5i6iGREhMhChihcwBBUVSb0ImzPQchAVXVkUcRz\nXHzXQ9FUFFkncmOixCcOfjFC4+CzCWI8ZPcEXvu8wKUrSzy7d87C4hqN+hzTnEUUexz5fY7jI/zH\nMcbtiCtLJcT8gJogkTCmQJ2AMXlFJOp4cJpnNm6yNIRgcYQvJFgF0PoBxCpn7QkLC7Ns3qhw8Gwb\nWZSQVRkxFhHEjNaVeRKnzWq1Qdsf4wkSH/OEP/nxfaKTKs/PXSdxE5aEV6nP5dDHNs1zhZe8Ekfb\nu3RuSaSySP3yFdIPXPLNKp3xU8bWlIKao2TnMI0iUQX0eZm0aXPjdswX/uPbLGfChaAUjvjAHYFZ\nYdqZEpwGFI50trVtNp5rYT04ofO6jWu5THo+/nzGyQhiE/ofCBT9ebLzBtLeLKo1x86JTRDpNGbm\n+eX/YJNqUSVWIoZDi2ggc3R4jBLpCLrIdXOJa6/cZixZlF51OOlOmX9F473v7FMYGMwXrlA0NeTL\nAu0VnyPpjEJpyLIo0yjXKC/q9BjQWDEQWiKFpQKD7ojpcZtaswlGiB6FJGlA+UqEFTpUTJOD9hTb\niShosLlZofKcyIJpkZoKp9s+wrjJzuNTWnMVWl+XcXGIRJtgxkdq5BByElpB5XDPJYxj2qM97MDi\nrVev8rMf7PH6V67x5Ogxy40Wu90D1FTk8kIe9/SEojvmi795A9/ss/egQ7g34OX/6HmK1RTFV9n+\n64fs7C4zE9Xp7rT54V+dsvmaz3jqUFUcMruAVGix/eGYJIkoN1/ADmQ6RxqVcgPvRKN3rHPnx0ck\nyWViKUMcqIyFkNXcIgNPpr/dxR1OUC+lXP+ntzG2znjwr/ep1GYJDxy8LOPM65KdhnjH8Kx2Tt55\nQL00g5OkNGcqmJqOsxfQrnuohRmQFNJOg8mDLUpJiWIrZOPzOaIbFubSIqPzPhXNRYkkEHWWl2s4\nzmWM/ISnJ11SRaE/7SPLL2KPi0hOhGSe4hJjOTH+LyZlydLLj1m8Mousa4z6OuOJTGT4zM/miLBI\nxQwvESCJUTAIoymqOCWyocIceve/RdtVGO1OKGYNBDHE9aDfv4+ZdhGzdTZvXubpwRlyyeWvv/u3\nfP2XvsxPnnzEk7sq73x1g89/+R1s55CXSl3U5hA3GvHkvZBLmxtMnadsvvK7wB56piDVP+Xq56ps\nheesbyiEyg8YDQO6Ryol8wZLhRRf/YQ4cQgin6IOkmsST9f40s3fQ/JW6BufMBrdSERlAAAgAElE\nQVQ/z/6ju4RPRCTPYzSwEFWbIIvwmVIWm3R/PCJXqdLYVHD3Izxk0mCGzn5KUnmILK8gRz0arQGN\ndZN8U0JSXVJhyNP3uxyeXaNyPCUTU9pPy+TFmO995/fZvJ2yeLnG5u0VElT6xwa3PlflBz8Zcfa9\nE65tmFy5XiRMdtj6mU3krFEureB6MmedDq7vo0hFcpUzfGePxtyUmcOr7B/M8bDrkRk+b3xhkVz5\nCWJO4OSnXZZfPaIUX0M16+xuH2I2h9RrX+Dh9JuMfYniSEQUeuR0QBPAz+E4Y4ZnIgcPFmktBPSP\n+0SCi6xmTAYqqiqyuJli5FQ++t6Ex5/k2bi9QGaMcXoDolTB90RSYgI8mld1NBVOecLslQK98YjW\n9SHdUOJs1ycTZSwvYJTpGJpBcBAzuRcw3VKxrAJeWCJMjhCsMsEwJrV6+JFwQVlNJpRLGQNVZmzp\n6H6NZrmFNxkyW1uBIMULbAZjn+7gAyr5TQZPRzz5zj3mL42RL3nkaiFZcI4qQiZOECOTGell1HCR\np6fP6OQSrr/yKpu33uGb/9ufMFMIOLg74XD3PlebOYaphiRO0QURKVtGZwOBISOhizNJcPw+ei6g\nXjvj3//dU9ZecOh7JUTjkMNbC+zfqeOe1UkkBVue4dmJTzCYxe9qRL23SeIjwtAiiCL8oM/hjojj\nlgDnH5zzn0toyIqMqqlkYoScSaTpRWQqEgVEQUAWQFQFdF1BlAQMI4eiXLRk6gYIQowsq0iShKYq\niKJAFEWAhCgK5HIKYeAjiJCGGVkKgihc/BjHGXEcI4jKBeIWgTh2UWQdxxsw06wSBTZzjSXcXsC3\nvvEXPPjoM8adc3S5iqnXOez2eP/JQ6IsowrcvFqjYlSIxYxR6DGMQyzbZqHWJPRsosBmMrTJFJHW\nTBlvc54X65dZn5tjNvTJAot+1MYBilmRnd1nKFw4PaOeRaVSY2idE8YZuXwB1xeJrIA4A0QDPxVp\nT4bkizmGaEw8j5P9MwaGTC1RmC8YFKSIOcXkl772Lpc3L7E0U8d1PCw3QzE00kzC8X3MnAmpTCyA\nYqroZh5N1jD0HFIhj5+ENBtNBt1T6pUaJzvbSIUcaRpSm1uhWCzQ6RxRbc0zGI4p5aoI0oWQ0FUN\nXcuRhiF6oYA1GpNmUCmYhFFIsVTCGk+YjF2iOEIzdKZD+6L5VNRJ04titTRJEKSLHRcBAXtqY6o5\nTCVHOV+C+AhJypGTDSLPxbMnrCwtsLe3w63LG+QliYeffMaNWzeI3IDQj5n0BlxeX+Nw7zGFUpln\nB8+oV32SxMOaTpitXaI1V2B1s8bIaZAisLhiUMznMcsug/6YZrOGH3oIaIx6Pjl9jaNn+8ROzOHB\np1SqTaIwoLkwx2gyoNaoUKtXSGKBSrWMH3hoqoqspESui64VCUIfUZLQ0hDPsZELEpNJl3w+IkpE\nMkJkWUPVVNIkIElsotghDRxILcicCwBCYqGJIcgZfiCg/L1oFzUBz7/oedE0jTS+IIQlMRckOEEg\n8kP8JEYQRaIInOkvBlk5V6yh9vdJhzDtwtKVMgVZpFIzKFgpuqZiL5mkpRn273U42rX5jV9qcH1J\n4En7EXkzQE4ScjWo41OqCwzvRuy1LRo5FYYmcbePOAtpDGHExb5Q5DB/xeR48ISFdQ/JLmOdxUiU\nqc8W0RKBWqrQVFO0TGJLH/AH/2REcn8evXud81aT4cmEJE555colRiOLw9MJX/0v3+LwuMr9o0Nk\ns4wyrXDpjVlWL80yHLeJOx0uXa1T6JU5n45QbwWczD+geS3l+q8I1Dijb+3jhCPMikiq2YwpEZ6p\n5M+rzNsL9N8bMHFEQrvI/qDFQWcHTYCCCWc/g/YjmWZuja1HNZy2QvJEJfMSul2XxV/N8Vv/+AWe\nvzTDSW+Hw8+6+Ich1r6Kb0c0c1VaNHE6ExovynRLbcw3U3L9c+bmZrjW7DD9REduR+wcnjF7yWfp\nSoVT7QmtlTyFz3yKeY+T8Kdoqymz84uomUhGwFByiVQPaTbFnvYxqj596xRKOdZWS2QjhX6Q8uxT\nh8z3ufZ8g6l3QrURkzdklIUS0kKdva0hAmWak1Uc9z6y7uHFU2rzIq6XsPBaga07XdrnNntuCkHI\n4q+9yuPMo6Sm3FhUWa6ZnD50WV2p0x4fsvNtC6Pj80l2xsyvKcy/VMW2PWxpiyfulMvPvQQllT//\nVx/z8pWXSKYSZ58q+N088cBG7B8yu9pi8coszz7t46oyvcQnGtdIcjbH0ZTvfdammRXZPVMwgkus\nfjxHPYk5Dn8EgwPyhork5wmmR1TnU5LmOVvDQ6LfqSB3xnSTKUFSZ//umK88dx0tV+Ou/ZhEOuVl\nsUhJXEAOyxRljZLfYvS+y9TNCFIFaRJifxTTKhVoXB5z9dWEZNPDTGpMM42S7pIzBqhSkYY0w6c/\nNrj+2jVkU+LkuI0/9Ll3fITV8VGGawTnhyT5EXpFwJJ/MeWes1f7FOcdhFjE6mr4z0JkLcUnQyzI\nlJoSmargRnmIdAxFJA0dasEbWB/+Ns8GATmvQV6aIukHbB3+kIbxOpI8w9S7RyMWGPqfIZeqvPXa\nL/HgyfdIGiD1K7zw5Yyp8CH1godWuM/slTGW+hMKw3WSS2WuPt/GlQ4RhTb+6F1c+xal5k0W1weM\nz20uNW6y8hrYoz/jj/+vH7Hz4Bpf/o3fI1SG3Lv3V7xe+8fstn/KsD0kcmYRxCV67l2uvzLD/Z2X\n2f5UwU5DUm0KRZl+YIMkQ1zBjRMK0hyJq3P4yQFSmqHoEq3WBiszb3Da88gUkbqhETsei6VLPHr0\nEQW9RxwEqKpCGot4ThFVS3nupWXufdjhg7/Nc/izmxRne5yfPMSaJAzPSxi1U+aWROyzElreZjjZ\n5uy0hJy9Q6Hlka+d0t0JmCk+x8z8PiuLBXrnHlunIZqrESoLzF+Zo1TeZ6Y+QZMjfPkhWqFIbWaB\nvb1TZnQDyyqC4LP1dITe/AaFl08oDkyGrkL/tEA+kMgVQmL94rP0eMdn2hUo5iu0NjooRYOJ5eG5\nGTOrGqW8ROlKiiTq/PQHPn/3512WViuIinMBDBIVyi0VueAQCwmnz1TiAE7aAYJQRc0NWaxr9I6K\n6HkBRXfxY4+hlzD6MMfkY4k0nscTZ0h0GzmukiQTtu6GxFKVxlqAqbvgS5zuVundl5nLXULJ6fj+\nAFWLyJUE/PGIWrNFMV1Crpc46ni091p85w8krj3X493fPSOoD4jigNayyHgqIoYNnhwegbaMni9y\neDTinRWDe3uPWb/xAicfd2lp5xw9zjP70gRHsslnTWxnhkh2idTPgCIms6S6TGPFYPV6joJYYRR+\nn0GQYhozRFi0VkJIZSL3MXOtgHx1xGFPYnRY5P6PYsbPiky7K4Rpgu1GTP0OhVKMJzyD8ek/OOc/\nH96WFEHKkFKRLBPIRIE0iCATL6JLYUCWpYiihKJoF03fkgiAJMvARUQqClISKbjA2iKSpinpxV43\nqaxAfBHNEoSL2FSCBKRE0cXiOZlEmlw4K4mQoufAtibUKy36ByO++1c/pH9qMVuaY6EwiyZqpInA\n1fkaX3ntEpVqgfe2LHzH4umzI4bjKU4cEyoaDdXElDMaCzOsLrcolw2iyEHIMpI0xh1P8U6esK2I\nqEgUAhXB9zjTJmRBjD11adaauJ5InLgEYYyqmziTkHZvgqLqBFGK7VnIhoGv5uhMp5wM+iAJmLUS\n87ZNkvk0goy3b9/k1a++RbFcYS5fwR6PyZt5dMPA8QKCIECRRWRFRTVNZEAr5ckkGTIJ0TBJJSBJ\nsfojcqJK+/CYeq1JUq5RLuYZTAZ4cUi92eD89BRZgMi3ib0QIUpIuUAJW65PTlORRYmECNKUyA9Q\ndBUzlycOM0Q5JIkjCvkimqzgTFziNEQWZFIhQxZkUDJEQUFWNVLXRZZ0DDNPvVrBPx/juyGBZLI4\n0yScjNicn8MfD0mShCtXLkOSUS1XmI4nhNOYerNFTivR7W6zPL/KYHSOqslYVoSlnmBKGaPhFu+8\n8wYP7x+xtlbi4WeH5GUP25ZwPIfQE4gqFmESUMvbRJOYxeWr9Cc7LK+/Qqe/zUzWxHMC+v0hpApB\n5GOYOmZOYzScIJAiisJFV0wsXeylZBKaZBJM+8iSgSiAbhRJAps4cElDHbKEMJmSJQ6+ZyHEDiIu\nWRSiaylBGpKI2UV5JRluEiEJAgIyopSQxFygawURQUiIogu6lCTqZIA9jYn8jMgXfr5x/3953NMz\nXnhtgau3M3pxwtF2jzRbRpICdEUgSmWm+y5hHFEUKiy+WObB1hZ7f/QBn/uNPIVMQhjLJK5LZmZI\nMxn6Yhm7lzHSJJwwgamMBziugBZkeEMXRRMRSwHDsx2UIgQTC6M4SxCNGPVjNKvIWnWZP+3+GGmg\nMr1T5fnB59i88jV2d8+IwoDZgc9O5wnvnU4ZTob0shE7v7dPkpcZxS26QZeEIW8/f5Xtzi7ZNEOM\nJHJ6hYXna3z+esDrv/clLP6SA+cpidUlNfNEekgw8fELAoIId789oTTMMa+uE/ou3Y6MegRuptGT\nND48C8hXVEqPQLTrOIcF9v0aR/cmuLsKpp/n+oszvP5P1rn0RZCyKW1jm+5giN8RGfwgwAt0BF0i\nlUMKsszaWh63ccjMmyN87Sk3Xp8nKo6pRy6mXsCsF7HuH7HjHfGlZYNmocoqBp7jQKWP0ZigpC73\ne7tMPkkJYnjuc3MYSxKBNiEhxQ17BJKNZ1gsNnQ6Rw5ipDLp+awsrODZGmIlJssGxPGUnLmK63no\neoUsMkkPyjy7kzK/LrL53ALOSUCtrCA3VNZvK9jfhjevXOfRwQ6Trs9KrsB6Yczcr6r4UY8vz2hQ\nzjj4E4+6Mk/BFinYMXb7jJlLPlq+S7u9Ry6/gTws0lhZ5vRnPdpxm9pckbJyhbh9zuQgQYsE2rbB\n+NSnmltg8dYCpfE6WXCCJOVx8yM+9XZoVGd5op0yH8xy2bnE2e4pnwyfYTxnoFTyHLQdIsemVmkQ\n2kOWXygTxhF7T0bogyFGUME/NnjwbySERxXSt2a58bUi3R0VN6iRnufQMhlNyIFgMHYDOjsJUWBj\nTQU2CiWq4hQtf4KQHbMgX+fZoUvpskzmB8hmQqWaUssHrJZ1NKmILGecCAM+eXpE3s5z/89TvjDz\nCm3x25yrcLb1C7kq8Ekwyz6Tk4TursHW+zL1+izTYw9zNaC07qHUffRChqKDc6xiWm+QHvwvZNs5\nao3vMmh/ArJJUiqSL1xBmfOJsjErS69y7ZbN6ckz5mc2OXz8Q55/9wGrb95jJemxe2cV+3gdc3KF\nf/Y//B88d/s3+Mo/+nX2T95j//5HzC6eUrr0AYn/eR49/ID5uQZO0kFQGrz21ruEowZOd4bCnMba\naoEXSr9KTp6lJL7F55738KeHjE5bnO/9eyhhzPZwj86JzPRYJugvUtfanLQPGBs+TUEnlWbJ5aoo\nsoNlWUykDCeZoGZllFCBQOH+p9s8lLZZuvYq3WHInJKQjQKkeMrb715n7/iUk6cdFpevMAnOmI4t\njjsTjOIJB4MIpWyy+WpMPh/h+A6yuc7q62sosztE8inb77/IqJOSSMfoWo7NFw7Q6/scHohk8XOI\n2jlJ+ggvmKc3tDl5WuPK5m/hTc/YeeBQq+7Qmp9QKBSYv7TJ448C0vEVatpNdre2uTX/Lt//6B6+\nEnD7apNBfIPl+SMODyek6QxqWkbyarTPBqhqQEmVkNIEWXLoHIFSSAjEDCKdYs7ELAyZ2BH5VoHa\nosHT+y4/uR9S0iSWVnPcfCsgxUYQUvxARDUFzLyGIAY0ZqBeS0H3efbZlJO9PsuXi8wuGbQPLaIO\naMEi51lMXz4FSUAWp+RzJqNexsMPQ5rHBvWSgZjKnG1J5IIaeq5IMI4RFROzsEbXfsb11455+QsH\nPLgLkbjMxuzLOPebmMqbeE9E/uXv/8889xUbpelCqlJZDsiyjL2TY4ZdGWN2ilTS2TrapjNRmddl\nqrNlwkOTnR/M0rgmUXy+TWbI5PIeGgtkxGSxDaJGU5vh5nOzWMc9zp/EPLqb0LpaQZQURDmmlA9R\nNs5IpRMKygSRPosFWF/rUF/OGD55gYc/WuPuez3KhSaFsohYCChMI+61P/wH5/znEhqCIFw8ZkiJ\nBRAyAVlRkSQB17NRspRMAFFVEBQJMhkEEVVVEMUMRZHJUgEUEGTxApOr5wiDgFRIydIUWZVIEpBE\nyGSJ2PeIkxgxTkmjmFQASC+iPWJ68XMbxJRzNZTU5I//6I+wOg51vcLo9JRitYATWUgoBNMpqphw\n3gm5LctUVqv89kvP40YxbhgQRwm56ixukGEoAr3uCYftNkkYUhINQi0lnYbIgoSZKpxPLFxVJQwi\nFA8kzSBJPA7Oemi6wWjqUSjmeHrcJZY1QkFl1J0gSiKyoTKZWIy8gLHjUa2WwXOZdkYsKCJfevV1\nXn7jJVRTphQlFEOJwPaRUZlMbTwvRs+ZzLeauJ5DFCSoqk6aZRj5MoKqI6cSuiHhZxGhE1HJl+j3\nzmldWifLFcgrFRJdRHcGdM8PyUsy+D7lcgV7OCQKY/xgSkhCJsrIksj+1hbNxgyBZ2NFIZIsIwsX\nzlMYBTRmq3S7Z0wnAxRFRsgEwky86F5xQgTtQvTJpgFigsSFy1WtzVKvneP6ES05zzT0mA77NCoF\n1CxF0xTKlQbbO7uUymXCyGdxbZmzwTkn7T2qpTqO36aWLbO8WObwcJtqvkEqdKjkXuJk7yG1isp4\nOGVfPsfxfIrmOvMrQzY2VtjdGWLmQkSpSr4E1qTGeDqh3Jij0hBx0jKffHKHa9evo+gqlUqR7e0t\nVCXGdWKKhTx+CDlDYzAaomsaoiSRJgmdTpdc2cA0wbUHyLJCnPjEmYKHhyIJuN4AQQiJvClC5pOE\nU0RRIPR9NCmmoGrEQkKaicRZiEiKpqlIokgiZKRphigJF3hbVSEjxfU9okAkDEUCDybjf9ji/P/j\nvPjGEo01nz5jykWNjz4d4O+OCBghKTPoDY1UT9g/OmQ1qxDqKs3LC2gvr9LRHjJsx1wJW4hinsT0\nUC/rLOVmOJZCnv7wmOCzjFeWm0zP+lQqYIUS/Y6FksuRKjaB4iKEIpEsU6hJhIFLcX6d1JZZ1b/K\nn/xzl+y7LbyjKr9x7T/BejxlUZrjgfcJptrAFASyiY7OkEA4oJ+V6SR9lMxApMhsSUUtashyTOvm\nKmvvrrN+yyALxwQ8JfRVptxhNZfHTkM0WSKJYUtLsZ7B9c0a98ZjulsCK9dKuCcuUSQR+QJOkHDw\nrI9v58hl83z6rRF6v4A6bbL7dILdziimKmsvSfzq/1imdSUinkk4dg95+t0Bk48SvDsyqqFTbzao\nyLMkTkiYeIyWjhFWHlOat0mFmIqqcuJ1KN0UyChgjc+YNjOmik2ctlhxRNLQJluDHXNCnyMaeoHQ\nh2EXdF9DzWbwzgP2d/tUpQIxEmohz8npmPDwANPboCaUWSs3qUh1vHFKUk5RxzalVR0h5zA8DhBl\nmfBU5MlfDnFGGVJVISeViP0TMsEmFnq8+aUVzFGd2vImqawx3j9G96fk9TM2XpE4n4wxr6mEgcQH\n/3uC243JJQZu5jI477EqZHztnRnOohpu0uTjP+0gjTTSU4naFzTWN+a49sUXmTxt840/+CZTL+DR\nnWdEcsLtd26x+EIJcSLxdv8qZWWTh+1HPJx+xsNwm6yakVeXiNw6p992KL+5SbgwZj86w1Vk0lhB\nSgwiyyXXCJhMu5SvqLxUlGh/7wwrkxBdFfnTEovz7yB+p0K5Wcc33Yu9vt4T1teryOWY6XCCFAmc\nWSp+oNN7ErPx2gyuekJXhlK8g6CnaLkWiZ4x6h4xPQ6RU5nFhoZZKLDx3CyfPGmz1ekhWyYf/OWA\nULSRlhXqsxFJWwH+3UctEx/s85TOfsa4LSPHG9TVF9m+8yG1QR4lDihnI+TYJjg3uJz/z+h//F9x\ndrTFPB9BexlTyJEaVQoLq+Q2PuP2GxLoH7B0eRclayImRX7wB08JR6+ymb+N7P+fSIUzbr75Abt3\n1vjmP/sq1+v/BXt3HnN47RX+1R8ZvPnSPyWyPkURSsj6HsPeCe7+K3z+1zNy1R8xzr6JXrpF6L3N\nw5+W6Bxs8sbvFOlL32Bp9sv00u+TiEf85vyv8+mPfPJxk72jf0mpfoPufpenOx9QM3UWVje5XpeY\nnEBZK5Bv1bFOD+lOP0bSxgSJiyjM0SiUGDlnmPMyw+4Z2fBTAsHk8vK79HtnbLc/ZDXQWLx5wrXn\n5yg15/jDP/w+e1u3cXpvQ3GH/mgLtSjw5OlTajMjBEGmtvaI3PwR7f6ESnmGwmyH7rZKfXaRzasF\nAqfH6ckCmX8bRa1hTZ4ysZqcHyjML61z63kTO/0e03GB1fU6C4slRCkhjkyOHpfottssrZwzeSYx\nN79G1vpr9JWHxEORu9/v8vv/3Xc4GvyI74r/DfnbY2LVRzPHLEQS9kRFDGc4PL/PwIqYvSoRWjJO\n94JSOui6yMUEOwLfjgkEi9e/2kIMSnzwFx2ePg5IJZGZpRxGRSGWXTI3JpUycrrMoBvw9InN5usi\nxbLH3uMMwQu4Wcyjjlz6U5sYm4Hn4AoSGRGqJuM4DjOVecTMwDkaEmYCpjJLZnfImfNMuhabG/MU\nyivIued4eOgzKmxjvLDPtY0Uo9zh+Y1f5v/+ww2+/dfvg1Rk62mKot0iLfQpN46IyxkVKcaMM2TR\no+/EKEWdUqXJg/s/4fLlq8xtXuKHR59QHf8OD977S37tdYUkU5AEnUl2hCRYqHIehZiIgEJVRs4J\nQJHpqYwp21jZLiYBbuhT0FIEoU/EOQo6SpZDEQ6YX/VZXp5lOplhcFpktjjHrVeazN0a8Z0HB/zZ\n3/zDc/5zRqcUyECSL3hDaQqKrBGFAlqqkaQZaZagihfkFdkQ0FQZWZGAC1cjSTPkTCBLE6IwJgoT\n4jhEEAREUUJEIhX+/tGUXHR2ZElGFF3EQqLERxAUhAxSQSIlIpRlItnnL/7qbzh4eML60hxyGtGo\nVJkGF/EYTc8hxJApKoZWwE5C7JGPfbaNqumkiJQKNU4ePMQwRYREQNUN5ETAEHTcqYOk55lYIaIk\nozoRWZQwtgcIks4kFohsC1EzOLcssjBhMrHwOhGlYgUvSnA8i1QWieOU9skpYQr1ooFp5rEnNjUp\n5s1rLX7lK1+nVq1SkQxSy8aOE6SyjirIpIZAfWaGIIpxvIAsSRASgXKzRhwmxEmGrBmIiookyDje\nGENTKM81CPyQfL2OE0XgTcipFfYffYysmhRNnX67zdrcZU4PtzENk063zUy9jOs5OI6HrhUo1+Zw\nfBdBkTmfDBAFCdMpIIgifuxzct4lCHxMTSZKE4QsIScX8IIA08wRhDGiJJJmMf7UoVqrcnTWxzRz\ntOZmSbOMyHGJJYOaaVCQRMTQRRIlet0us60GQhChCgoaApc2LiEZMJNrctJ9hCwnnJ4d05qbY/9g\nF0mOIT4iiDM+uXOPjY3P0x9/TKlSYG93wObtPJkoUR2L6FqJewe7+GGP/plEdUbh6nOf5+T0mHx+\ngY0rBu7Uwx0OGQ08ltZrONOU2uyA9p5GkpwSBhIFQwdBI81Eev0xmnHx+JEUHyGBeNjDNItY9ghd\nM/HTkDB2iAOH0LMQEpcwmKCrMpKYUjAkFCElJUJKMjRdQZF14jBEEkUURUBEJMlAUxVc3yeOQBI1\nJFEnCmJsJyVK/u1QdP9fj9xSyfQIKxawHJtIEulNAnrtPSrr87j5hGqtStVxaD/ex3kksvG1FpFk\noKJQTTJcf4K/4LKPhyyYCOUR1742yzTO8f7722StDL2SR1c1encnjI4T1jcbjIcTckqeTtdCzwo4\nlo+kFokUA/9RjmdWg8/++00qM4vke3NMGwZe4GCXJqxULjMd2jzXfBnZ0xFEjerpXVZLsyjpY26r\ny+jjIY0vqpx39mk1Znj5xRXyr+X56d33yMwhmSDT6exwMo1Zu5mxfx6Qz4/w5JCzWKb3k5T0sI46\nXGTn7JxgrUx72IVSEUE0GfUkTr+b4Jbmsfp5Cto8R/ctwnOL6Tim0tT5+i/P8qV/JFK7eYwl2vQn\nEcffg/j9PNZfKpSKBpIioptlFGUGeTZCadnssc0v/4c51LJDMFZQfZOaVmJz3uTT5AgryVF9WSGz\nipycb6NXUqpVgxNB5uluwqOfhizkwPRLTDoKslmn/6CFEleQDicctYdQLqBXZeKoixspyMoc/jRP\nuaHR74SU8yJ+mKCUVMIwYhrvU8gtkjOLZJmOc+RjGFU0A9JqhmCmuIlF7YpG3rV506vT3RshhQ6m\nluNrv3Od5sI2/fSEwkqZNM7TOzOpt2p4IwUnJ6PVdd786nNUZIdxJ6ZYNFipzXJPsimIJsWaizXq\n4x4WYS9iZqnO1bc22N45ZllrUZpRMMtTUv2Y1BzzK//TF5h8q8Pgn3sYk0t8SxwzbG1zZtTYmdTo\nfeSxcukKH/zJZwRxkSW1gdBP0TZV6lWIrR43Lzdwiuc8bXjsfThi8wvvMvm0zCPrlPBjE/czjfr1\nTQbJMWLTJimoeEaXwmyAnqnMZfP8+A9d7NEMDQSCnTKPvn0P6zdh5MfcMlOmwzPUVsbWkwT/iYV9\nfkatkaMwEzOKDJaXdeRglmLOoL4mcuy8x/B+hDOB7ukvZp8rimHQlZj0MkLPolrRKZkNZovXcXsd\ndj44onBaY+FyFc+PCYQa4fjPuL35n5NYMt3uPZozt5gmPRY33+fr/6mIqP6ELCsRJDqSdIzMAhtv\nFbgzfp9v/emQX/m9GhQyBOEco7pFWPZQtLfIVSS+8f6/YOP5FzgeHnDbGAMQC10azQFbH93CvnUJ\nsSFRm9nDFT/AF+6xfzRHEryNZPTwei4TtY4sv4ZAGSl4xq2NIpeXl4n1t+sHkuUAACAASURBVDg5\nfsjf/NVTwrxC1rtJfDLmrc//Fp3qIZ3hCakO5WqVav4lPnv6AFHLEPUEJxkTayqj4QAhNQjOQuqz\nM3zy4M9ZUhrs3i1yezdAGAy5ccvg4bNvki/lOHky5PbNIpWVda6JJSS7ysM79/j0zoC5+gvkShoH\n2Y+JM5PQknDcx0j6JXJFD8vucXbiUJ9rUFjc4tnDWeLpDIl0wqUXr1KeOScNXML4CL3UYtQ/Jz+B\nUbdKlrRYX7nE9RseTrqN7S6TV+rEwgmtS1XOH60wHW7R3fs7mjMK3pGCkodk0YaShZYoyEqKLvVI\nRgEoNcx8gGFaKFkV255ycghyTsOLApyRxEKjTHPWRzcGRGHED/+4wnDrEv2tEAp7CHmP9csFYsXG\nlFUGToXDLRu95pIza5SkEu6px/EDh6JYQjR8LDEmlXSyOEMr5MgISGKPVJgwGXcoaAp5qYbi5tCz\nApKfcGlpkb3jCYa3Q7WZRzGLdHfWODryufWrPap6gMcJpRf/lneXn3L/PYHnCr+NfezT3v3XvPDV\nGkrjjGF3SkmdxQq6yNo8JhZ3PvoxizObnB/6RMYh9bUW/ZOI87sK7nGZvnNCcy0miHWMvEpMSMiU\nEnlS2UPLNUmlHHneZf/J35GtetSrOgXZQCXER0BKGyhimYyMKBOQhBTHGzLxzphbvMFcQeDypZjG\njXNuxuG/1Zz/nI6GjCRJqKpBHMeEQUySxpAmyIqCliQEfoIAKLJInHpIkkwcB4BJmiTIqnDRqB3E\nF6hTMUGTFRAyBEFEjsHzfSCDTECWRAgEQjclS0VCL0IQA0ThgmRCrCJJIoIWsf1wlyzQAZn2cIDv\ngyiDoRiEdoChacSxQKSA44YUCyY1M08YBGiGgW/ZGIqJP7HJMonhWZ80TYGMXM5kcn5OkoEfeaSS\nRJAkpKlAkMZYQYzjesQChGmGqKmkiQyaweFgTJwmCIJIlMSEQkYhbyL9PaJXD2xeWJ7l5kqLV9+4\njWLLRN0ucaVOQEgxV8QeTyhV6xfN6EgEkU+pViHLRAqlEnGSEQsSck4nDmNUOQMpJs1SJEUmSWMS\nKUPVNKxxH11TaXeOqOYX8ONzEltjrjZP+/QJeXT6208pNhqcDvpYgodeLKCUShzv7FCdaSIIBsW5\nGoqQoogxceAj5vJEUYykFBHJ8CYWpq5iTyxkVWVqOwiKjCGrRJ5PtVZjOJqyMr/Ix08esrq+jhe6\nmI0S/l4bU4mxhkMuzbc4PmuzsLSI6/pMBhaR4xLVi6SlDLcfUFdqZJGM5wxR9TKPnz6gOVshdEHR\nFBRTwXNUNMOjt52xuakyOPdwbTBLDs35Ek8ejCiXZSRJRxAsVlYWeHj/KWtX67hpRJK4uOMIs54n\n9MC2A4qVEmOrjVnQyGUlPCfBD1I810cQZPScgaoJhGlGOLHRNQHL8pElFXs6gLzP2BqhZBJh4BD7\nNnHikGYJvuVi5gyETEIQMwpChixnhG5IJKVoqoyoSIhiBkKELIjYfoAi5RAz8H1wbBff0bCmMRPr\nF+NojPIhS80UuZOQuD66kqfZmiHyy3ROu8iRQL3SpJWr8zTuoGoin324w2LZQWiFpGrMVM0YOC5i\nSaDmjcDKIwQp+VpCrlhg937Axo15upOA8EwhcxxyUpnR/hg3MvH6CaJaI55KLLXWqFprtMTr/PR/\nHdORcvTGFm/fLPHA3qd7do9KJLF6Y5GyOUOp0WT3aJ+ra2V+++3PYx8mXLfnEKMOUWtCDo9cq4iY\nWTz55A7reg0j9Rj5LnG9wPbjAYGm8+xxzNFZRktX6SVFgsdFTK/Ko28JZKqJrhW4ux/RdSRi2STr\ngt1u4DgCar3MeXtAaOuYE43nl9bRb3pUrsf87n8twfwhmeGT+jLnf6Zj/UhDurfESqBjxBqZIhIJ\nBubVGtnGgCDvMjztc2xVWK7qJEpCKvjoToLtDXDzE3JfhOSZw1quzoMnAd94cMTSRgszmCcatMht\naxx2U2qVRV56YY3NtWt89MEdRhOZ6FjE80yyvEgnnVKfa2LWFKSwQm22jqBF7Nzfx090CEzCYYFH\nPzlidkNGUhxUVadny4hKAVkrE4seQy8mk1IsCxYbGVrFYrrcwTkrMe6eMFu/xMalEsXrdaJmh8mg\nDeUWbqqRn8sRbCm4nsRSXmB2UcXJJgh+iKCYWNk5c9UmxVdbWG7Mj598QK83ZDI4J1rvE+PzYO8B\nX/zla1x+ucjp1hMs/8dsPl/m5ksKP7Uibo5aPP4XNdaHV7hcvI6hmYR5mald5bN/mbG3H1PRTbZ6\nPu+8eYOJf87cV0Q8uU0iOYSjLpW8wBe/vs5Oqv4/vL1XkGb3eeb3Ozl9OXZ/nbtnBpMHMxhgEElA\nhEiQIkWJVFjLa6WyZa1dZVftVtlbtRe2y3e+cJWttba8K62ttLJWgQo0SYggCBBEGGBmMHmmp2c6\npy+n850cfNGuvSa1Jb2X5+ZcnPr/z/vW+zzPj/0nImauzrXIoSH3Yf0AezQi74xY+hmVMN/Elvoo\nxSK5+jxPFZb4WGizZjm4H3axvAzPnzbxcw6yBkMvwr1jsHnbo5AqqJbNuQtZZi8IPHow4m9/0EdJ\n88zXdJ55Icu+WWBT3eeqH+E0/0GuCnwbhkFI7MxS1r9EYe48suSQn17i9OyzfHLzA5JNAVV7nS9/\n7tcJggjVXGNuyiaSXPYfXmCwkWW0fYtidoyo9knjMYQzTFolitOzBInDiWdjHm/fZnj1PB/+8VkW\nX2oxdcmgdzjAcUosPb/E02db3G1vMHqUEG5d4OrbFq/P1RDNkxjyfYbxTdK8iFEOCOMmhiiSahqf\n/arKX/3BNVbvfZls9TSp2GbrYUpiX6G29AO8rs2W9E0KUwcsrtT4+n/Z5M9/B+5f+4C0b/HB1U/w\n1A7x5AmzuUs03S3K+ac5v2Sw0/uYveYAWVcJU48wSankKnz1C7/Ag4cb+KM8ewdXaUzVefTRWdBl\nBtsBrqiw9kBkppZlt/NHrDxfJg46SJkUvdTl6fNfozt6zINHqwSTGuOuRZw6SMJpVCnHoDVPOIIw\nfYikZRl0Pbz0PRw/w6XL80jZbzJ2M4STacxKlcAtoUpFJkOL+kyffFahM/wLGsU+Ww8tRHGGdidk\n4taYWww5fazItXdO8o23vsvQuUN+6gzb2zcpVhL8vkqYVkjTAYEXEvkp7jiFQETRZE5eiWnvZ1l/\naLP7wENTZdLEIzdfQCTB8UO8JKVYtnj2aY1eq8ntTyUmj2eJWgJe6lCqZgmiFrFbo7sRoaaHXD59\nml7T584nG9SrKlGSouspWVFjNIoIPJ8oETCwCCcjVCFgqrCM6GYxTQU5bpDNWQyG25w8+zypaJBI\nEv3emLzyLB989yrnv2TRRcSZvEnuxCc885kznH+5yTf//f9K8+NnMB/9Ix685WHd/jbjzTGmLyEG\nA7LRHGF7wONmk2PPnSQSIza27nHiwhy9oUcSzvJb/+IGZy/L3LQ6ZEoi0wtljGxEvW6QLURIns1U\naZoHwgYHB6B/InAiP4NZlhEJmURtBKGMLGYI4oRQ3MRPHRTBQlRgbk5kc0OnN/B457tNPpMvEsQ/\nmpfrxxo0JDlFUQUkOUEQRRBEkkAhDo4IxYokEyvKkXdDFtAVHVFSMLQjeVUcx4ixgChIRNERVVoU\nJQT5SIaFmOL43tEzISX0AgIvIo1ikjQkDH3CyCeOI5LEQRRlNDVBF2McRBw7wBN0Hmw2EVSFOIyQ\ngoixFAMgeCGh62NlMwiej6oYjIcDREnEbbskCYzGNrpp4noelXKd4WCApMocHHSJswUmEwdJ1xmN\nJ6SCxNAeIQkKYiqTCPLR1iYOCcMYQRIJuh1SRSYmISAmERJESUJIRMRJRMWUeebiCi+cX0CLVZJD\nibSQMlWZxXVtaqU6SSpSMEwUPUsQCWhmhkhQKJTqjAdDJFklkWLUOCVrZRjHI3RZwnFt8rksw/EY\nIxaOjMKCiBgeQY10XWd7/T3qxZMkwT6H4wkZvcDV9fdRixUY9VBVjbxeQ0wSVj++T/1UiUKxhO/F\ndDodfLuHPWmiSDKuHRIEPoauUszmqZXLhI5PoVzGj0J0VWE0HJIkEnrGIgh8NEnCiQMyqkrgTghs\nG9XMsFi1IE44vXyave1N5hfqjAZHKQ9e6FOpFUmkkFrRYjZf42D9ERfPv0h/kFAoFJgERQaDHrON\nBv4kpdaoUZjqMxjYXHz6PGqmhyCE+OGEet6i1e6ytDyLKNa59uE9Xv2JN7D9h8zMV0nimEG/TdYy\nONzfpZzKaFaIHE9hmQIH+zrlqsagm6BZHl7gkS9naLb7TNfL7B3uISkyruPiuSFJfEQA94OYMAhI\no4C+OyGNAmx7iDMZkKQBeU3FdUPCjIYQG8iCAUmKpquYmoIsi5AehSaIgoznuaiygRvF+IFAEh/J\npqJIwXdTkij743cCf4dKTYVu5hGPt3ymZjXKJR0/nmEUmQzXPcQ0JB6mODjo+QBBkpAjDdnTECcK\nYyFC1qAzThndTck7MDPng5Kgigknz1fYvNU+algPVcbbCamoEzpZklhn0g1R/SXilsTo0QS/OCBz\nacRXf/6nOPidGyxX4IHyMUP5Nv3hEPCZtuqs3vwEWS5hHCuiSlkerd1hTp4BR2DpxQbNtV0sWWK3\nuYpqJUgVG9FIGKwfEucjtGlQIoWhnaJPzbHxaJfxIE86yNLa1FH9Gmo4T7/Zw/ZDKo0q648c3KiM\nOtK5+d1dzFwWzw3w9zzmxSlysUVatwgzY+Syw+Vfklg8nsFD5DAt0fkApFt5SusVsnqDqBGjFkzy\nJ0usBV22co+58FqGpZkKJ/rPc+vOPdJUpV4QyRZEHEGm7zmYxSp7cR9rsYIQp2TkHP56lkfvxSzN\nlDDlIoWwip6TCcMAAp2r3/uUm3eb6BmLvCCSz+UYRCGRa+B0RKKxSJIEfHjjGre2tpBlia985gRZ\nR6LTDumVYa6m4zkegq3g+iGKKuF7KZXMApPHD9HLeapJSnZkIBeGyAsO44dDDC3P1tqQ1ScRp84p\nxGFI3z/E27LZvNXHyF0kMg0Onxww10vZ37EJpSZekGLJHunugKArIVND0gs4/jxOUARRQEw8BtEq\n+5N1BoLOpJqhVE/Qeh61ms2w9RbqMZfCry0yuGOw8unrTCnnWDl3inFuQOAecuOtRzjjLHpSoJf2\nYXCC4cMR/iUZlmR0LcXVTKw0QaklxJdz7N3U6XVc2oNdPLPPWqvLeaHOyUSEgY8Yy0Qthf5uTPea\nx+ykxoEyoZm2eZAoPPXBM3i/8yLxyvdYP5YS1l28pkYSjAk0AbMRUn25g6QO0E+YBFdj7LGMIp/m\nmWMnaZzeY77QQe7tk4zgzr/5+78rou5LLCy/iHrSQV3pIrkfM+r7iJOENBozO1vi1ed+jnypRvvw\nfY6dPMWp194hV9glEdcQzClEvUyzZ3D9hy6FKYdj5xf46K0x+eocmeoesXhAmm6TKttExofcvX2Z\nS29cIZTfZPH0mM1z91i9l+XK4ud47dUlotfucbh6k7/6gy7ev/kCV156lt1VH1k1MHJ1ovgQWRIQ\nhA6JYOOJQ8zqcfY6G1w4voOoN1k6bTNcP82T+2coZqe4fnPAz37tJxlN3qaebZAvX+UrP/cK7715\nlQsrVdb2Z3nwts/jtTu4XoAfrOF5I3Jmga48ojvu4Qk2TjDh3LkT/PPf/W959PYDvvD6BT738q8w\nO5dj6exDfM/n0b0BRvYYLz47w8HeI/zuAj/8C4dKzSGX1ZnKvciJz/rsj3eREpUn1yw+Wg1R1GmO\nnZoizUh8/MO7FHNjjl/soJkRWw8VvJ2fJlNaZWA/QDZz3P54zMLiGYbjiKnqcUbeA2ZOfEoSrRFM\nJOr1aQ7uv0jUfoVKSaZQv0Gm8DHhuMcocHFkk6Eb0+/OM8ys4YZjenez5MoeM9MdAi9E9Kok45iD\nNZepSoal54foRcgmA+bdPG//mYdpwSs/ZSJqQzwhxXZEdD3P1IlDijN9sgWN9oHERl8hGpQY9HLY\nzTGx6DBdMSmrCqtXW/TaEpmizLHyCtdvbaLnMhSzMtlEoRnaiKZJdwiuIyNJBjnToKQeZzQeUSyp\n2D0Bx9nguVdq+JMN/MklFo69xnA4QRGnOLxf58b/e0Dj0gghMWkcF9DYolBz+Pl/8gIfV3Qexg6P\nV1MePXgJxVZw3IeotREHnYdoqUS9nOX77/0Bn3/+JXSvz+FBQstxmSotEwz+KT/4w2+QqWQxdI98\nVaY4o1OojZgpQ6VoEO0XqWQN2k0XBjmmzITJpIVpdTEUlTBRcNMRxBJiqiJKAWk0hU6dWqGKO6UQ\nDOsYyhlaW3uQjX+kc/5jDRqqIiPLIrIiksQgihIhCbKbEIkCqqQSC0eUYlVRURQFQYRUiBEFBdII\nEuloWZEKJEmMKEqkQJLEJFGCkAKkSIJIkKTEYUQUJUcblMAjjiOCICRJEmQ5QZZUvChEDfKUG9M8\nvLOPGGq4AxdDl4gjH1UVjijJSYKXgOv46FHEePuQarHI1sEB+UKRXn+IWSjS8UMUNcf9vRaGZRL7\nCXqmRM/2cLwQvISJ5yNKCqGgIQoSiiTjxT5R4BGGHokokIagaToBEUFyRFM3RBkhCJDCkM+cf4qn\nT9SYqxQh0smXKpRNjVEsIMgKqllE1LKASCQqmEYGQzMQRZmikSWMUhTdIIhCdATcKGDY7xL4AWno\nEYcesSoiKQpCEqOIIoPWAYE3RlV11h9cp1ZaxhmuEcV52t0+j8MNJr7M6KBDJj9FKmuIaoooC5x7\n4wqHjw/45MbHJImLaw+JvJj5uWMMej0sS6NYzuM57hE8a3OLRq1Os9+lVq3S6/cxdB1ZlvBcn1I+\nh2u3ScOQQt7k5uOHHFtZ4uoHHzFbKTK2bfYPY0rT0+xubJOGMcViFSFRiUnoDwYcN47erZsKG+uP\nUNQcesYgjROm63MEYYTjjpl4I2rSEmbWQ9VMJvY+smaQMSV6nYTp2RK6IdPf13DDADvcJVMqU69N\n44cRw86Qna1DMmYBz0npdjuYWR3ZyDMzO02aCGTyEY4TY2YS/MDBtETMrIo51IljCAOPKApJUwg8\n/2j4GEeIxHieS5KER2dCkgEJ23UJYxFREBBECUGAJKuSJj6iCLquIQigGQqaJCGJMuOhTRIfeZjS\n1CAIA8JIx/FdbPdHy7z+jy3J1wgnJqI65vS5Fbb7VR7+bUyITndoIxdDhCRCSMBUNSa2TRTrDG0R\nwdHway6ykdDbh/078MJxjYKS59Fal72NAafOnOPUyjztRw6jboQp1REUib2dCEHUGPUzKFtZnC2b\nrFJmYbrCyXqe9P4qt6++xXL+OC07z8Zkn5qqoXopoinjOV1K80UO9jaZqR5jsD3EUlRKBZmJOME6\nOyKyOszKJUJxjB0MCWUPJ/YYeSPyvobrDUmElDTS2N/QkYQq7rrCYFdCpEiSkRnEKpEosb3vMYlB\nUVXGbsiBN2Ze1ykoZcyBQeoLKDpc+ckpWvEar/68xfxzYx6ln9J0ArTd0/TftqiNLzLwAgq1Mv6F\nFrXnNdQTAeVskRs7j3H8FuPDlJl6mRutAjfu93j1czPsdGQ6TZd25OM3MuxFEXNLEtuOx7itUVCP\nM2pLdAYJahH0xSqRmvDx9z9k5VSW1dYad9bvIkoqF5fPoMzXUUi59NQ8BUti0HNZv+WzvFJmemkG\nyVLJWDoKOaLQQjzwufbvAmYzITXFIl8psN30efBgn8ZykU445uQbKtMZC0Mw8JMWWimhMpPj5c8e\n5+0/vMf993vMvGBi5fMkukImIzJfy9J46RJPmgYfH47Y73Y45SU42OQzFr12h6gnIzgN5vJ16oZL\nN31I3whwDIc0tAnTAz73ZYPZKwPyCxFSlCJVVfYmbVq6z1KthODvc+I/n0F9AtFexPwZjZGvsna3\nz+deeIHgLYfDYoisVxgbOe58v0vxqQLl2SyFvEs60qkKMlpukb7pYxomJV/n60uv8ql3j31pRDdy\nCKM5emshOTOLXqkh7VeJt+s8ftQiPx1x195CCi3a0QnsP1nGeK0M6ZhO8wZ97wBdNwjNISuXMiyZ\nIT1ahPky6kwZ1TcYH0oMhgKaVqYhHOclZ4p75ibQ+3u/Kwp7v4ExPoatfki67CPO3CRauc7u/ZRz\ntWMcbja4/84TpufnuPTZV3jpS+8jGu/i8S6g8vSLpzn/4oiZixW++39H/O//c5OXLl3EHu/yi/+s\ngWbIhKmNICzz2Ree4WMh5DvX/zda/X/BfPocWvEGr3x1wJ/9j/d5+P7zvHC2R5r5iMxTsPh6j72/\nPc/qB+e4+/gSZ17eRsp2iYV7BH4bWeuArBOFAcfPl/n0zV1ymQqi/tcQT1M+9x7X7/4SevIqWupg\nO13kyl0e7z9hZinLTGPAlZ8+zkcffYtXg1+l0ynSPrxFeFBiv3ULb3yIpR+nUqjS9rZRIxk/SPni\ny5eh3+HT9/6Un3rtZ+h1O5y7MsIqb9FrasjkeP7ZKb749eP89ZurvPP2NppvsniywcxJl3x2TBpG\nONtdMsUKjSWbVz7fxRDrRPGI+0988oUVnn76l+lGf0TKVcq58yjzeywuQuJdYdzss7xwknMXFuiP\nJ3z//bdRpTKqMI83ASlskPgVFGvC/Lm7XPtkB8H16W2dQk6mkS0NSYg5GD9BL9hUFsdkq3l2uxMy\nhsGwKzLuOHj2gN5hSCGTJfITMpKFFMjIYspoEtFqxpxamWH9/pBiPcJSNEaHOrO5LJnZCYnkQiwx\naYdIk3mMwjy1msLI3SWN2ljpNFqYsHmzxXSSZ9LaIJEVcmaVzkGHzKKBVS0i0UNNfdK9EqYkIcsT\niloF2TeR9D3CbIvF8zGHkkT9S7eJdms0Br9Cf2OaE9PneTi6TjB6jg/++BMa90c8/0WwxDIKAvX0\nBIdixDNfqDPYe4DqXaCbFDlsb+EcVOj2LIrZHLoQ0m06VK0xD1e/RRouIGUOEct7LH1uj1K5xqBV\nJKu/xs59C6ebEux7PH6wzcOgTWOmgqJJFMRn6Nb7NHc63P3Ld5n9zBD5pIavxOhCmyQ2keQ8sqAR\nCRVCwcEPAmJxB7OcQyfLqO1y99Y1pBM/Gm/nx/NoqBJmxkCSJKIowXFdREFElBRkjmJqVUVFUjQU\nRUWWJURBJE2OyMQCImkSEUcpcRwjICKKIgKAACkpsiQzse0jG1oKiqzgT2y8yYQ4jInCgDDwj1Kn\nYhkxFRFkiO0hL3/uCquP/5jJKEFAI0xFbA+UOEQOElJBwHcjRDlBkyUkUWLQ6aPoWfZGLrKVZbs3\nIEgEBEEijFLS2CFOYoSRjZyCFxxpV1NJxvF8MlaWsT9hHDgkxCRRjChDHKcgJNikKJp69KPyHXKi\nRKNQ4MJSnXOnZ0mNLNncDLorIUkqm9GEMzOncAOf+co0tusjKApBfERL970AK6OSzRXp9/vEoQ+k\npHGIRIRne2iaAnGCqgj4rotumASei2vbqIqK7/gMBwOmSnPstx/TH4lE2i6+mOBGKaEW89lX32Dt\nwTr1WonWwS6R77D36AmGVcYdeLiTIeWSRRSHHG5vIakakaZwcNjC1FXcic10fRpBUtAUhSAMKeRz\niCkIKZgZHdd1URWNKI4gDDFkiW6nR86yCBMVUTXR9AL9nkO+NI2uGGytr7M0v8D9x4+pThdIYonJ\ncIRpZpAkh1K1iiJNmJ+fZ3tnh0qpQTf5FEV4hs3NPRqLdax8k80HAcvHMnh+xOkzp2gNNmg0cvQ6\nh3z+py/T7e6TyZ/AT4cMBiHTc9OoSpZHj7ZZXpql3Vfp921SKaDRmMaNtpElHUGMqdVydLt9svk8\njm0TuDaSkieJQ4Q0JgySIzWkJyELIpYmo6oQBinECRISgTNB1eQjqVwk4bspEzlEUUQkSUHyfBRF\nRVFExPQo/jkI/SNYkSSRIhNGIq4Hzjhm4qkEYe7HOe5/92r2ufFol7MXRZanffYGWxTUebodH9UW\nkScJ5UyGw+HeEdVcAy07gyBaxCMPzFUMxWSw55M6Iop8nEkSoxQdrrywTCkrYnc9Ou6Q6XIZfJPd\ngz6iqhNLGu44S+jKOMMYoxQj51K6+hbvtf6UUz9XQrk1S3tD4u5kAy+jEY47VCcSXpRH8iz00MEY\nJxSLVYJej4kVstrZYfpMhtQcIIo+/cEWaiFkOBki6DKxNKE3GTBIB0i5DO1eQqJXSFom69dGZPQS\nIyXC7beJVBlFkNnvdvGigDA5+s7LM6cwPZHMKIsyEPnqr60gVze58LMyH9/ax6kLuJLG7hhWvyuh\nPUpQHk8hSBq5JQnz2QDpSzbq8gDB3eOc/jTqtM/a6gaDjshx41mOlVb407+0uTtOuXyhyuGWjasr\ndLYCxoJHZzgmESW6QwFdzCHO6QxbMaGZsL21Q8fps7p3hxsthzXvMY3PZbl4aZnLT88iKALjkUcq\ntHn8UYeDHQ81o/DUwjK6ukD7UKLT2kdRMljyHIqW4eqtT7i+3qWe2+bsxTxX19bBT3ly32MoKFxR\nq0zXPMJJm4xcYkjE5sYtGrMXkSQBrVjnrb+5hzl7SOmcyMnjJvNzC/h3XHbX2zjahP7DfZ73ykzk\nAbLfI/AippZPsf5hn/ff/JS1+3lkv0alNoMW+kycm/zE16ZxpDHG1D5TmoQZ5pDzNX5/OKTppvwz\nY8BxLUH/tQbf/pN32dz5IWfP/CZvfOE5hv+qzcl0heUrv8I339lgr9imVDrLV8+rLF502Rr8HsJ6\ngDWTIYxUJgLsHO5QX8lgyXVEr4EQ6FTNfXb2HvLRR485s1Fj9TsWldo81x+1KVsioZxQLhmUxsfZ\njUbsZhIehFnEvyrj7tXpzT6m/NmYbHWf/IzC5ZMFoqhPVa5imXnMXBXZn0e4M0P3gxy51+bpNVdx\nD1Jq5Rz/EIOG3XxAZ/sJAk+jtl9FvTBGyX+Pz1Qt7A2Zad2iXJ5njMY01QAAIABJREFU5XKbRNpB\nNL6FG+xgqMeJ2EckQEgHPP3MgL3HNrJ/mU9vJiycc6mc+QA3+iGGbOIwJlP9PIVjb5JIfe5e/z+Y\necHAEWp0hSaPho+Y6/5X+IcZhMY0knGPlQs+X7hS5b1vbSM+OU5jOocg3EdEINb6hGkdN3HJylkK\nizHOpV1GwypF4wSy1GQ3uMFLX7zAwbrI4tw0zc2TTCs/B/5fsbv9CZcvQ3v8HsdOVrn+/X/JT//8\nG9y7leHR+g7Xrq4TCSL7ew9ZWmiQ0yOq2WewBJW73/+Uf9f+v9hd32dJnCNvtll9f4BenqZYO8HF\nUzn2997h3bc3EGly+lzM4wcuh22JUdRB01oE/RL9/XlyxTz7O200+QSiU8QZtgi1LfK1eR7vfoPU\n6CIMa4ybDlP5HIebIzq7QxaOz3L6OQlX+pC93j4kJrOzDXbWNykXGuTrIyI/xioFfHT7KoL3ZU7P\nvMwk+gRN7VOfq1GpDNjac3GHDvLBc8zPVeiZ/55cZoKRCGSFlJEYk5VV1FQnUUzGwZhBq4+UmOxs\n25x9tsal8w3e/v4mfm8GwU7Z2zrg2MURiZPQbNXJmvERT0ZxCJz1o1500mZqaopRVyafL5HqCSM7\nxG/mEYwh6XCLhcVTbLUfEMs6sVyi5YQ4SsJSeR63a4NXpO3t8tRXbBYub3DyosRH2z1yz9WY8+d4\n/IN/zbD9ZcLARYyfEIxSbv/gWYZuwH/y39nEQp9WEjMlnMYSYnTVo5DLID69RiPzebRrFrOlLLvN\ne0SSgzd20FIFXxqz04qZra4Q8oArX9nmK/+FDywepb7Ga4x7BdxOmeHBDN3dBTx/gqbGxHEJPwgR\n77t8fB9u3Q34gttgKepSPZNFUjKYckyKhpv4xHRQJJVM1iF7dpd8IeRgrc++79Ltxgibfw8eDVlV\nSEVIBBAVMASTWIpIkoTUgzA8GiaEFKLAwzCOJFOiKCEkKaIgkCYRQRgRRPFR9G0SHUXfCgkg4HsO\noiBAkhD4AZ7jE4ZH8aqIR36JNI2PGB5RRBJ7KFKKH4/RSxL/6Je/wO//2+/Q3G9hZrIoWpaJ5+KH\nAYqs4PkRlpVh6NhYZobRYIxlZYmTlMl4QCaXZTIek82ZOIMhsqQThjEoAnIMgqYdrfRIiFOwPYcg\nDInEBCGBME7QJBGJo/hRAZHYHmOmCfWsxvmVRc4sHqNYTknjgFlxlskYkppMqZhnxZlClDQUUURS\ndBLbQ1YSSCOS2EVIQkJfpnO4RyaTQZANnqytYmkgyyphECJLBqkoEIQRiqbijSMylols6fT6A/Ll\nHG4r4GB8yG5/QqrFpJJOnEJlKs/Swgk+fOttttYecNeQaPb2mZlbJApkTOERpfwUJ09eIIoliuUs\nSTxg4jgcHHYpF4sMRn0sK8thd4BjxKSiQEZXkQQBS9VIAUPTkBWNSPBRJBXTNJibnefe6kPMbJbB\nwEFIYp40H1PIZnBcD0038MMJ3WGLCxfOMHIGOEMbIZZotQZkLZH+cEhtepGk26dWn8NzXSwrhyzH\nJGQQRZuRnfD8C8/QH6/ijBPGXhNZUmm2hswuFdBkkxm/xIPVAyTZY2X5LOPRGKNQ4NjpRRQ1w1xO\notLI0u04DMZ7zEwtMXbXMTUDQYwRkqOUlyR0qRVzDJwYS5cII4E0Sf7/jV6EIAi4/gRV01BVEUFR\nMFMFVRIRpIQklkhSgTCKCQOJIEjRtIQgSBiPbXRdIU4SFFnC0C0Cf4J8FOtGFOmkaETxETHeT/5h\nKFyx1+ef/0aFbGVE82CfST6lXO3waTMk7qVk51WCREG1DLZ3moiRRChoNLc8bFthIqnkKxrd1ZRa\ncYlIzTKYDAlFj+KJgIaREi3kMPw8lcI80lDjze8cMvL6uKmOLGv4yZCeM+LS6/NUSxIbB/fo9z+i\nceU58g2DU39+jPU9n+x4hSfCdXakHHrs09z3kHWdQ+eQjCJTrytYxYDR3gGbiYtWTgliG8WaEIsp\n7miImBEJYpdE9lAyAgM/Yndzgmo3yAUlbAx8WaBre5SqFu4owHY8EjEFQcZXBQqlOpVKhUIvwQ33\nePE3RX7qv6/wZO8JD1sfcv7lBR5ubvDRX9sszpymvC/T+jDFCCV2on1OP1NjOL2D2/iIbBpw2qgh\nDw44k80hzmT4/u/eZ+PbApdf+jK63uM739qiLp8kChYYSy16zgGV5SxP6RZZ2WD+WZlMKcO4o/In\nv3WN9pMmTmKTm7E490aNkbLBmVczLK+YLDRUDg6uY7tddFElIcI1ZSiOKdaWEEpbtLcH+DHkrRKR\nLTAajVDzBqFvkNV1RFXl7t0tbt54xE+8+hwXXniGTOM4qtZEMfoM3F0MRWROhVPnLD79/Y/Y3t9l\n4eIvsPpwH9OfpxxPs/NglzlT5MnWDq4Oxy/OcO3OPT599xD1rE9jFmoFDXs4oTC7wA93mzz2O9Sv\nVFjb2acWmUw9k+fkyQwHw8cUagK6GyOnQyJHxMpC1lfoiSkLkoS9vcnekxTPmmZv9D6+kGPIGvrs\nFNbIwip2ifxD/vbNET97uU53d0DmlSlOrqQMk22c0OPh2k26jkZhfoq5qRmkzTrDjyPi2ohYa/C9\n1R/it6bRsaiEeXbSCWEtQpVjxFzIqZPLpM0DVjO7TGgx38qzMjxOmi9g1T2SqSG1uYCsJ4GRA2ym\naGAVpxDdCuOwxP0f+Cz/moq3qKGLCfR+tAbiP7YEbRZhroSQOATKQ6x7NS7VfoOxlyKLO0y/OM2J\ny0tk0m3u3f1j/uh/Wef5n/uYleUvIIZToOgIaY5U8HnjF4uUKw+Y/J7MwZMxm+/O07j0ImlWIeKP\naAvvIFkDavWf4IO/0Zm/XGHqgkfo5JCDHocbbR58z2TpiyeJq23KxSxx+rfUXllj7+Evcfs9i0J9\nlfKygKrM0w9tFCmHlpTwpavUl2dYXzd5aSbPyH9ELf1J3r/7Dar5gEKjRL2yTdj9Ek/uvYfTWSYT\nv85a72/YP1xnY1tn+fkq//ifHOfTzU+xZqZ5cr9AqarjtmwKgckv/8SvcuPWRyhaj+9+sE21UEG3\nPZBLDLcjCpWQY+dXqU/r/NHvXad0+HXiTJ8oGTC0LRbDLzHaitC0HvboFjPTWSJf4+S5Et1Rn3JG\nobmxT9ZoEaQmO9tdRCp44xzt7gHyJEOuYHDx+RzF6R4te5NBa0Cj9nm2Hq+hGn2WT4QU6ht02tAd\npuy38yxXfxNbiRmnb6JUPgQxxA/OEDp5Fmcjbm/6vHj8As+efY3e92C3+R0O0iGmKqOUZcyphMO9\nLs1Nlcq8QqL7SLFCOavw1LMx1cYWl2KVt/7skHx8kunaU2jSHqtr6wQdiXJOQ5RTag0DbxISORFF\n00AMZTY2d6gtaVRPBHTurxLbM8hAPlPEKveJ2jXuXRvTKC8i2g7nayX8tkdGUUB0yc41eeonJyy/\nECBLLi+eUJj0xnilAZlnr1J66gny+19ncfBFPvnoJhMEMlNZup0RTjuhXBBoDkR8IcWSckzVC5x8\n5R614p9R0vJsvn8Z1Z8l0g+hYbDf7BD64I1qrNt/wVd+JuWLv57BFjZQUZBiHxGben0Zr9xh5sQG\nYpqHpEISajiBzcQROdjbY2b5LM0Hhzy5c43SKQel5qJkHXxTwJREEsmBxEVMc0SJg64FlFeyiMUh\nTCl4P8yxtdP9kc75j2cGRyRjZhHElDiCcWCTAoqmEiUJKRGyLGBoFkmSEicxqmoiqxICMSkpJClJ\nIpAiEccRgiiRRBGiJCBJKaaZYWKPSREQ0hRJkIjjAD8ICMOQKAqJ4+Qo5jZNSNIQqe8jKypx2EW1\nZH79v/5V3v3hHT754DrdgzalSoGsJiOICrIik6QhCCrj4QTDLOC6LhEJumngTmx0WcTu9skYJrIg\n48sRURgxiGIUBPr2EFU3iaIIMZVRZJnE89E1DSkRkYWjeFFBlNDThHw+y1wxx6mFGvVShkJOQE+L\nKEYOrxSjiQpaqCMOBQJhiGDHlIoF7H4PKYlJPR9LlRi2mpj5HMNeC0XVIQ2J/DHlQoZhdx+rUkGV\nFGxnQjZr4acRkRMiSzKt1hBV1RiPx4ycCWPXY6d3SNcbkM1Nsb25zgsXz7F9+y5Pbtzg3pM1qpUy\nBCKLU7PUiseoT19Alo+Gu8jv4Nh7hAcqUaIRJgKV6iyuN6BcruN5DpJ4ZOzP5bOkcUqhmEFIUwI3\n/A/gxtAVMEwd+2DCxLNRNANTyxDEHo1ilWho4I0mlK0MaDrKbA5JEvFx2N7bIkxHZPM5sjkDIRSQ\nZBgNh8wu1BmPmohaROQZ7B8ccuUzl5CsIbKcx4u3KdZCZuYrpFEFJ9olkxM42Io488wyfvcGZ89c\nwMjaNHdiZhfrfP+7Dzl55jgieWQrwTRXEBo38PpnccIPyBgriNkBg86YfNFif7eDKGaQRQlR8jFM\nHT2VUZSQFJFer0epVEEUIuIkRBFFkjAmiUVKuRID3yZ0I5Iw/Q/bC0EWSeKIKIxRNfWI2SFKxHFK\nEE4QUp0YETE18DyB0BfxfYgik8lE+fE7gb9DTZQ2RrXMaCRjuwc8NafDl0d0/SzX/zBCn8khaymX\nT68Q5V0e7O7zeH+HEwWLcD0hThVGOyl5uYTiiLQ2bETlEOVElzP5LApdAk2keDHD3u27qH2N6kJI\nIZW4/uEWZj6HFwUIisigM+ZWb5/isQ5CNmAg3yA55vLab63w+uAVtvZSfvv3ZZoHdzl+wuDSiycY\ne01mFgsEu2O8wSEbu2to8z6B75N6R/yaRjXLcLhPGMWYgsTET+l1fcK+gmZmSbtZelswyUS4QopR\nzKO5Ibqgs7vbZfHkHOluC3SDuarK8UoJY+BQLIes/GOZp17t0fWuU5/R2NVtXNcnqx3jybe7WEoR\nf1fFjRwCa0wuNWi32kzubhLU+zReitiLRsj2Pgv6EtPFMqJaZ+tdBcOdUJx5invjEXeaDvWywWAM\n3sgjm0+YWbIxlYRgnKBn+njlCce/EqA/cvEDkf54g0LRxQ8TiiWT/dsRB+/tcv/jLU6/nrJ0RmQ2\nr3G2foydScrsvMQWfbaKXXo9KKUToklKQkrHdpAsgak5i+PzU8h2hpXTM4ihyPfe+ohf+pULjByf\nvuQgZ1XioUeSjVhago2FMY1zOdpDhwkym7cUluZzWBmTvScTrr/fYm7pAvmyyZncJXY3P6S1BS9/\nXUTNWOiKxCQSyS3qBIcuYXPE8JGIHanIl0QGzpim6zEQUjoIvKxDRtA5pRskwpCBIGN4KeJQ5kTG\nZF9MGe+3+O6//ja9h0OUhYB/+9vfoDlKsJ6us98bcOPjkFeesfn8lacQh9vYEqg1mcKFISefXmbw\nYJvd2yE33rlOcfosVUsBeR4lnWZUjJiuVumHYxbzS4zwWSgt89RMiWSUZbh+DSuXYTP9FEcPaEYW\nx87N0w82mHtO5JhcAh+8bhatpLErdPHjWZScRmgdQC7Hvt3E6Q94MrnLTvMfBtiXdjskbkxxehpf\nGuEM77K2scbs/NNUrJgzJ3Ko029SW/yE6myRP/g/b/P+H75G9PKExefrDO7L3HtwyNOvFijUDzEK\na2yuZimP/jP++l/+gN/87Tyt7CMKwnEmjKlbJRLtEbuHDSbhEqkxYKzuEldgvfuA41qO8XgXwbRR\n3AuIRZVqzaOy9CF/+j+t4PdDfvG/OYFn6Rw0d1k58SKq4mNH1wiCkI/euce08UtUjj3Gj32OHzPZ\nfLLO+bMXubn5P/DM4i/T6tSYnauy3/+QcU8knRxj62ETnj6N4z2gOL3Ff/pPj/P9b7W59lcNbq22\nyWUj7rduI1g1RkMFS9OJhA73hztklZS5qTme3O+Qan3ycyqKNs2tB9voWRE1X+SNL1/h3v3b9Ntj\n9EwL3dxGLImUrQQ9V8UKAvACpF4LyzAJI4FxQWJ9wycNBBpLMscbexSnPMKJxu1bKplKCTICm9tt\n8tYpWq1NEvU+bjDHpF8gY9U5eeoX+OTDDULxE3qtQ6ajr5HIHm1pnyjUmTF/hsKlJntb63T62zT3\n1+knCnp2DocUWQ5I1BZOW6NrJ/TnChSWXCY9AV0A3x0wmkjkZkLOv64wORyxtbbF2ocKcb/K7OyY\n+ZUKWafJcLKD4OZxejppYnDQ8ZFDhaG3zexpjTR26LGFKimoNQE510MOi5TEPGUU7NgiCqFYXcZN\nh+RnzyDMeNQXrxHKHlN5HT0rY8ch3fARlRMODUugWutycHUK43aNzsEhdfks3Z0hsdjl0z/XaD78\nkMaxM7zxtZTZc2uYi3eQBIPzPzvN1Fkd35tld9chpc+FVOX+9Wkm+7NY+gXWt34XX/AYBwJ1tUuY\n2qhJSJxGeImNoYRogkyIgaLlSBMRyypx6uWYwbsLKM451u40GXghz8cRSy/rdEdD4lwP1xuRNVJk\nEUhlIiHFTiOi3AdMP+3RGR7j2s0fDQL84w0aYorr26iahiBImLpBIE3wkwBRk1ElBUmWSCMP1ZAQ\nZRlRjBHTCElWj0zcYUKQRqjqkWwkmrjIqoYgiSSiwDBukSQQBQlJmBKGEXEYI4pAGiMI6REpPAjx\nwwRBhEACIRwy2BOp1+ZQ1SZfe2OJL79+nGu39vj4k8c8eLSDqqmMRhN0OY+seSi6TtvtYxg5Aj8k\n9ARcJ0DRZVTLoO06jMZjdMNi4kwQVR1dAFk3kcUU3dSI44g09pFVgShNkBSVNInIiCkZVaahqVQq\nBk+fm0MSU/K5DFEgo2SzyLKC5EhokoAgu3hhjICBIKZ02kMKeQt70sewTEIvQRIgHA4xdZ008SCI\nID4CtTkBaKOAOIrQMhZ+nCCmMqmYIAkisecSxSGj4T67w0Na4wF7zSdUszWSfhfVG/KHv3MTKVOg\nO/YIJIm8v0MnkmmqO+xUdine+CaiqVG0NBpzx5EzM8hmhdi2sZjQ3l3FyheJYoGsVULKGLg+aFqC\nIsqESUrk+8iKhBuMwZNQ5JhB38cwFaJBhGkorG3t8Nyll/jLb/w/XDx9HHIK+UKJVrtDPBTxXZf5\nhQUa5SqhD4ORz/T8AmIyYmtzl0vPLNM6OOCFlz/DO+9+SC4vUpuq0e+tsVSss7+3Tb4qEE5MzAWQ\nDRsxUfADC9OyeXzzfYqVOZrhE0pilekVjV7LpjajMbG75AyJwf4uaU7ALBbJN0a0thfx5R1EiqSp\nRuj41Ct5HNeFNAYtj2M7BBHIggApFOarRHGAIKaokkkcRYimjiKJpEmKqmcJzZA0TkiTCEOTEVMB\nWdXQLBE/jNESAcfuQSKhy3mCWEGSLPw4JY6PwJlpnBC7Ppr4D7PRmP9MkWbfpeWJlBOJqVzITv4u\n5stLdL61Q2XhNPVLKicXM6gfNei96eC0mgwmCZX5hKnFOkJW5PGmT2/kMVUqkzgZlJGEJogEocxE\nBsGMEGZiCuKICy8WufMDj7taijTy6d1vs9jIQ+wjyBPcvQ6FkyZ6boRQ+/94e68gzdLzvu93cvxy\n6K9z9/Tkmd2Z3dkM7AK7BMDlkrAAmlaRVJESZUsWLVdZVS7zQlUqg7RdDrLFsi9sM5RZpGmTlABQ\nRQAEFouw2DwbZndy7Onc/fWXw8nRF41rC5CKei5Pnapz8z7Ped73ef//3zUe6P81L37mFUxS/vl/\npfN7f/4WV/7qCoXZJzBtmZOvvMC5apGGX2fzSpsPPx4yiXP6E4dMEtg99DkYdLBLOodeBIGIXV7l\nYMfBSysoggIZkImQ5Yi5gIICmkhlyaI8ayIKBrPNWYx8QkFyScUDYmsD7fQhWiXGI0PK57F1g0++\n16Fmn2NGatH+UYyoSfQrDrKlIKYp220XXYyQb5mMNA9XyWgZMu1aTDCV0LR5SpnJ3gdd1MdL5ILM\ntRuHLLZsJp7L8bMVtOIh6kyA2tYQPBm1OGQkdKk+KpMZMomv4FybIuagDKH3DZ10t0KaqphSiJB1\nKRQS9DQmGzusCDlSr43ZnFCYh5nzEpf/6CbdDbBrItX5RWYXMiplFUEYkacq9ZKNFwis3zmg93AR\nPZzQqw45uVRiNIlJfRj4uyRSBLbOX3zvL1lr1Vkp6XzyWp9YdvC7Oc898VnmWosEYUSUCGxvSYiG\nTLwxx+XdAZo8wNjqoMizSJLElcM2J81l7kw3qfan5LLC4UBmsy3gLENtNmOOKbV0mdPyClvcZs+f\nstBVeeXJS+y0dD7+KOG9tz5GUlRGj6S8/8lD1i6domRXiOopVknj3NMNcmGbrek+hUILwz3g+UqB\nbfk+9pN9GlqGdi9EUk36ewn+ToNXTj+PnlWpzGo4XkTmyNQig+oUiq7OsZkGjRPPcsfbRBiMCJw+\nXeGAR8QirWeXWTFkLO8Ab5ghlwX6fsRVbYCkXqQpNEh6Bv7NmDVhjaAYsj/pIg8DoPs3XisqtW3U\nZAPDeYrH5s6QVze4c/UqRbvK4TTgB3/e5vzLAuvvj3jm6V/j5cdqfOMvv8Wfv+ax/Ogaa/OL3Pjw\nISeaEkqq8MafTlmoLHOvfYPDqw5X/lpm5XkRbQVufnLAsltAcHUm/phscAd/Q6IVn6GWbON7Ht6k\nSLN2gR9cvovjvM/PffESVRPUyj52rcLdd2Z4fSFlZ2CweOyXOHduhJO/QZJq7G8dIAYVPvhujQv5\nEmceKSOrB+wPPiBKzzK/UOOjw89z6qUTjO89RpYso0gW557wydJ57mz+CKUmYs6b7B7cZXktpHN6\nj9F6iXC4yOppiysf3kQs1XB9n4f7Owy7eyzVDW5cO2T19Brp9DTTdo6R9lhelTh5wcLPb2KUu1y9\neR1FPEY+uYSYr9J9uMNBNkAQLJRCl9lWkYln4A8NylWb2NEpyieIlX0Mu0MkjUDUmUZDbP1pth/s\nsPLoF4jCeTS5TOY3KOmfRY11GvMegr3OZv8PWDyxxMPNA+oLY6qzXdp7IUKkoCjzCIU+YfIGH1y1\nKRQ16scmpEGMVEwYtDWQa0zHHbxhkXF/RGPuLK64S+BHlGSF4lxIPFUJk4xjpyRouhRkh7vvLzDs\nLyDP7yBqA46fzAgUUOUYx5vQ3c0ZfgTOqIKfVKmfLLDf3uHsrIAeLxA583zy/TFl1UBUbfyxgJIp\nJLFGqut0nbewpSaj9k0Kkk3HGTFfEwjyFLGm0ww9Ir9BZkUUTr+OJszz6YNnePO77+MOBnz3j45z\n7HSB3r2blDjOC1+IKKy+DbJPILSQcwlrts1Sq4MonGIhiMicIbOVJzl7qcb+9VNc/k6bdHycK9+9\nymM/JzKIQcoFPHGMJuiggCZkhDgY5EyEEYJUQk0Sjr9ksTBT5VtfC+n2Ggh+EcG9SppPGOcxvj8m\nT0VCX0ZigoKAbVSQ8gmCHKGSs7Q2JeUnM5j5qTYacRSjaSa5kKLIMr7roKgaohih6yppLBxpLmTQ\nDYU4zZFkCUjJ86OJR5YJIGTESUaSgSrLCIJAlCTkQo6mmiRxjCBkZGJKImSQp4RhSBD65PkRHE6S\nVbIsRpJkpo6LadjIqsLUHTFbWCRDwbQknnlykfOn5+n2BoymLrpR52tfexVvWmFjaxurWKLnDkCK\nSeMYTVOJXZlef4goyZTLZYIoomAXUA2dyWgCWYpZrTIaD1FVFVlVjhpoScRUZAxJoarJVAsWK3Mm\nrZkGBbuALmvkiUSjUiXPQcozMjKmfoShqmgFnTTPcKYPKBTK7G17lCotxt0hhlUhSDxEItLMJvAj\nDNMgiI4I62ma4jhTmo0GbhRCJpJEMVEUUzANciFjr73BzTtX6UzHSJaO5BkECly9t06U1xA12Fkf\n0jThbGOJtGLzzLnPIecKS8cvkBdF2ls77B9u8+3L71BUr6EIIXqxyMLCeczCMqqpYYiQxwFR4FK1\nSyCbyIKAIIjomomiiGRZDnJMHplYxSGHHQijIZNxxPzsDHubt3n6sYv4wz4rS0u88/aPmGnNYJUr\nZHmIG08pFA264x5SrpBGI9Jc5JGLFxmMJpTLVfa2NmjNFPFCh8Goz4Unn2Bn/x5zs8fxk21EScad\npFglnfnZWTJkHo4drEIJ19vh1NolwmCbSVtgd+M6QraAaWp4EeTI9IchetVHpIZZ2EUUZATGJHGC\nZYuEQYyqHokFNS0jS0Us8WgjkCYCjuMgiSK6biJLEpah4/kevudRLB2R1pNEJooiZFEjyyNUTSOK\nfYxMwzQMoihAkmV0vcBk4BLGAppqIooGURwy9VJSVARFIomkf4tW4KePNg6DSoLpLdHr5Ij0kPOQ\n1hmXEydVynHApUZKVe6jLOhMTs/y2r9+l1FZ5tnnisw9IVNarpG8OeDdNzzefadH1t/niyt1pNzC\nS1JCWcfDxS4lpJMhiaDgphN0xaC328XzR9RmFxn4Qxo2qJmKGUaM1ndpzZo8/kyJgv09LBK8pMy/\n+LvPwt9d5p3DLdoDh6udf8lmV+BY0aBZrlF7LmZ8NWPo5liGxcP+EC/UmDm7QBTC7fd28W6MKBZX\nkEsmo4GDrlqU1RJGVUWJY7SGgZe2ee6lGtWSxrRaZ7bZ4vKrn1A5o/H051Rqj1rUZhQCIcCNIMrH\n4NikmcJbf3aXmfhZdsQRciWnJ/kUU52DYUg51CgHJex+xMEbOavnZMI5DWdvQhALyKpEeabMg5tD\nlH5GY6GGu+NzvT8g7E45db6KKvtowtHBj5NmuG7OgRCjKxGleQF/RyQRjgT6mqFx86MBrf55uoMD\nzj+zijuMMFZAVPp43U3suEAYCjyWaFTykO5phcavmAiOxd2NgDibsDOYEGcZVmmJWrlIZw9MWWRm\noUJvp4s6nWAu5vhLOZMwRhJAjGBuQWd5rcKb3x6hnarxxCtn6G2/hztJUaQK860aRUFl/fY29VaZ\nixeO8XCg8vCmiz+SqZYshAy6SQ/H0bCzOmuPnMPP3kOqFPHdiEE3Zxzl6GdAECRSIeZecA9TOUGa\nq6hCke99fMAj1QeIygniLODQHXL+zEk+vPYxTjRiMvGRN11n0YAzAAAgAElEQVSW7UUWVqcU5gRG\nrOOUR8iqgt+LaZaKVJwRVn3IW5vvcuqFY2xe3SJPbFaL8+Ab5FmK0+9RUwzqWsqv/CevEEYDdrf3\nGHttLjw2z+ywhHXjae7tXqds7HP1O3c59wtQWY2ZSgWiEVQTm0CLmLeKzM1W2JZjOqg4Oznt1xP2\nHtylPetx+bWf7ErEv2s8/tkFkqnMx69+i196eYZpFLG5X+fawW1iYZPjK7/GG9/8iItPzPGD//dt\nptMIv/cMpqTQfbhIEvj05ZCvfbVHOUnp3DjHztRh+YUlHtzW+ObXezy3fcjt9gZ316FpnMELYXbu\nKd58/YAX/CW8/lts3PyAqirRPrjH+gOZW691CfuzvPypAYfTe8izYworJvn6C/zl/97h8Rd+lud/\n9Ungd3G5ScIKpWbI8z83yw//3GFh3yR7dEimTpmdVdgdfotGYwZJv8pM8w4ztTFh94sU5F/CD7+K\nXL7D/bcGrKw9y3Y3QC2KGAWFxZMRh7ckfv6L/xBJm/Lq4DJ7Y42CfJGF6uPMmBXu3viImXqJ/f5d\nZtMmZ9cMusHH1GZFlo5f4O137rL1QY+58ueJCmPW975Ja16lOusw6Qs4Pdi8OgeTC2zdPcAWbSRs\n5MyjWtTx0zpKArEH/bbKrQ8zZmZCZsoF2lsfYVshB5PLLK/INCvnGPb6jJI2gndAGp7jw4/6LK7N\nMA1qWBOd+7e7fPrC32d7+y6GGtPdkxFt6CZ30LKQUeKwNK8Sm2Nsy8EOwO1PaO+AYfdJRjPs34/Y\nDXx0ucrSxQjZtnCnAQLDI7yCtkuOyOFGk/19gfqsRmstp7qQUli2GKQOc6dLfPhNibR7Aa06Ynkh\nQAHaN6aM1meoR+cR2SKVSszMLVCrK7jdDlKSYzaeo/NQp7T0i7jdDmbzhzh5CM6UYkGhKC+glJcY\n8wk2p7CXYgqP/TXx5QCnp6D5dbrqmH5H58u/Oc/KYx8SCVMsjuEkp8ilQ7z8AQoQZh0MXcTWBSQ8\nzl68RHPuGHfvHrL98Qle/eN9NNtFbY6oL4KopPhRhqFkJAyJSRCYIkUmliIRyzma5FB67D1mHyTs\nbDo4h6vs3nIxayJSrYirSgiWQ6AmGIpOnkY4sU+ah1iagCQJ3N68hWk98hPl+U850RCJ4/BIxzCZ\nYloaQRAgKwJSLv+YiwFJmpGJGbIoHdHEs5yc9Mg9Ko4RZAlRFEjTjCTPQUhJ0wRRlEjiI79iMZeI\n45AsiiCNIU1RZJU0y8iyjDhLSNKUNI1AUNEMg9F4SjZxIROp1yoIQgXXcZGyjKKeIGQa3/zO94gS\nhS+8co7bd0vs7Y8ZTEwCPyFMPFRRIZNCCpUKsiwzdhyKhRKHnQ7nGzMM2h1OnT7D3v4uZasEQOD7\nFEwDBYGapWELOXVTZqlVwiqLNCtFsihDREYQBTzHRVVg6kxJ4hxNU8nziN64j2VWKRdmEHMdo2CR\nZBGKGTPxHx75tAciOGPSNCPKI2RVpVws0R8MsFWdvb19Ks06SXZETTd0A9d1AI84D1AMgbpqs9+b\nMB3scdhp0Z8otN1b6OIsC4syc/MrXDojcvuewfzcgMu3xhSGHa5+7xPmygatksjsMyfJy7Nsb/YQ\nxyN27l4lFzNqjTlmWsuUKvOYskEs6liSj8iR7iYIQ5JEQlVlskQmF/uoeR3N2EEXSgj5JpKgE3gO\nvd4ABZ0fvXmZmZkFzpw/w8OH6zRn55k4E+r1CpmUYtdKiLJIrzciBY4fP8PG5kMMS4Uk5MSJBZIs\no9/vUbQLDHodFo/V6bTHzLRaTEd9BsMutZlF5hYabG5sULHmIG3z8M6AQrmH7wgsL0vs725z6vyL\nHOx20SyJUrFELmaIQoKpC4wmIxRBQTVkFEUjzQXSRCFMoGiYZLmE5wTkWUyjapMmCYIgo6oiYeRj\nmQLVYgXHnVC0LMIow9BUBHKCWENQRBRJO6KGxxGGoZGT4E598kwkiSHyY8YTkTBSyLHw4pTQB0m0\nf5p0/7eOKFeRgwHd4D6LmoFKkaEg0us6VHWB+myEtewyzTYZZSK+Aqeftjm2rFI/5yNWxsSNCGVG\nRqmYpMMcWVqmIc0yvrtL0BKIYg/Tc2kpOU5hwtV7PmO3hqUUmYgmdrFBMgSlauMnIwqiRFlROblU\nYOZYTDU9YOq2KZgnKEib5PlDcIssNnwuv9qm3qxgNSQcySNqjMlGJmLdRmobRJ5CPNKozZ9he2vM\nrasHOPsRTz35OIZd5cG9NppdYL5Sxgn7tBoiGT4zswoTf8zPvbyClCh8rz0kkyxGvS55JHPmhTUs\nzaQnaOxnLomQ445iptcOkIPzSIWEvVGH7lLMcBCi6jJiNyF3OMqpTEX156jThGFM9aRIT90hmA4o\nn2xQqlhMvxHx0YNb2PYcmaowHYSIWMiiTc1eZaf7AbnmEdZzRoqM+3ZOjICUQfcgJZvC+29CsxHT\nf1DAXjqNWFikUvRJtqbI3Tm82YfEwYj+YUKiGAzjDKtssFIVUdd8hCBgXHToDHJamkY8TRmNB4hC\nFUuvUirPYOkJmizidXfx92S8fo4TjrHUFEnJCBMXTbPxRxnGCBqGxeyTJzj07jPtxmz49ynpLd5a\n/4hz9hL1ls2l+mnufLBLuDVgLAmILYW9LYe5eoNmw6J10cOLbMQ0Ze+uiNIvYQsuC2UYkiGRImYx\nBn00xozFnE4mcLOzhewp+EkBpSIhtvokBY3f/J0X8XsWH7zpULCaOJMxrq8zTDLKhYAk2kDzE3yn\nBAXY7iucOhtREAvcv7pOKlSxVnXmKglhqHN7c52iVeLiZxXE02/SPbhF63ENsdum0KghhjKNVwd0\nxh5Rp4vqi3Tf85CUAfHMkFNlA6Po0d3bYcY6y86mT7E0w7Yc0zem6Ff2GXgBqZdj/vs5k+DY809z\n99XXeeKzv8r/8/1DXv6lJ3Bm3uTRL3ya3Ovw7vff5O/958+y8Oxr7G/f4PWvLVNdfZo8XWfxmR9R\nnV/muVPgjNsM7yyy68Lf++Jj2OfuMumc4qv/Ar7xrafw+o9S0MsUzzyCVLnFKz/zHPvTP+VB+wHv\nvtFDbf59ttc1snfusHvjPpPhGcL8GHsPauwlG8zNHef8Ew1+cLvPsbVXGHi3MFsPcIMruAnE7KCX\ni1SXrjD8vTYCs4wmQ7TCCrq1y2Qo40QbiIGAUjqFoqd04h6+36S/IXK4U6RgzbOzs8Wllz7P1Qfv\nkngeO3sSUkFnUnqDLEhIco+C2OLk/HE+88xn+PAtWFjqkSZTXvzZz3Jv522u3HuHpVMJnWnA2+/a\nDA5O8eSjn8ePrnM4PkTaguH+DIPdOaxygTS0OXE2xTYkSo1DNPGAUJGQLJGNux38icHiUgs3L9E/\nzJhtXMQNrlKuKoT5hMPuB9RnqiT5XXruDn5QY3jYYH75OTS1zOL8eaaDNn465NCrc/7UOVRryOzi\nlB++/iqHu01KMzL1hQJOlqAWJWQMiiUQJAExFtAMBaPoEjoxtjxGHFYQx8uEDwX6+jpUpqBo9DsC\nuwc2K8dUHlmF21d22dnSmR7U0JMSreYWQc9DiwSKQoxFk8N7GiVOUpo5SeRkiIMR1nCAIqYcDjxW\nLqqcvSiz27+KVfIJ4/f40i/+Bj98fRd3nPLat97gqdkebiCwWJXopxnlskqWBxjhKzjiOsP9r9N3\nljj5wjYV+TQfXL3F1l5KJjRoXrrBWPCQcwMva2MJIhEmSr6KFx5pbEwzJ0NFEJo49Ejld1g4lrL+\nXk4YnuaHf/kua0+BacwilvYRpC6xp6DkRSaJgyTHFDUHQQwQs4CSdIr96QOWjp9jd1Xg3bsPkW8W\nSKKMYs3BS3RqZ1X0Vkpoy+RaSE6IHECiQrVqsrza4u2f0DDip9RoCIjCEYJdVVXCIECWZJT0iBgu\nSjmiKCCKMgI5iiKhyALkR1VLFAUQjqjgeS4jiDJxlkEikAugiOKRVaui4bgesiSTCDFxGqNIAnGQ\nIQBpmiEIIEkyaSqg60eQOlEUqVVrPxZ3S1z95D7zC8tMhoeU7TIbG3uMpiLF6hLf/fa7SGqB0cRH\n+bGAV7cVRqMJBasCQk4UJJTLVULfpdmYYdTvsDA7x2TQx1R1pBwkQNYkTEWlokk0bR0zjyjbKgVL\nwbBLpKmE78VMhx1mZuqMp4fUqjVyKSdOU6LII88yLMtGMkS2BnfIEhEJBcsqoGkapmmThCm6FHE4\nnFIwDBB1LFFhMhlQsG2m4zGFYok4jgniCCEHWRCZjMcEyYit3U3cwCWKRPzJGM2YxyqIDBKXC4uX\nWFxMWJ05waC/RbgJ08FN/vW/Mvjr2zvosU2zKiBqJrc2hhS0t3nxlM3zT5ynfu4c0/wMspKgCwpq\nDlISYohQMQU8dAxVQhIUQm/6Y4tXAVnOUZUm/dEuilRG08doksmd69d55uknmTgRcSAws3AC01S4\nt7HL5fdu8cKzl+j1BywurhJ2ezgHbRYWlzh16jSaZuB5U5aW5onTCFHJmIyHWIUaw96YestCEjW2\nN3cpFau4zpQwTFk5sYobRSi6SXOuTuR7bK6nlOs6tllj8dgOaR7TWFDYbd/DsnWyxKHXAT9sk4RT\nlKqGLtlkeYIsiESZS55LxKmPItchj1FFBakgEaoRcZigKCKqIhCFHrZ5ZB+dZyHlokaeZ0gSpKlA\nkmbYqkSeCciyiJDH6LJOFqcIYgpoJAjEoUSWQBSJRIGE4yRE/pFzVZr+ZJ7X/64h9SzqRpnIG1Jo\n6GwJMRnLVA9bXL+/xcnVBp1DB1dyuDrp47WKNM6bNGdF9ob3mFdysmlIs3ACceIzPdCoqAbBYZFY\nVqGQo9Uiyn4MroNhWxzuQ/tGROrqxIUcvxgQKBmzM0260SHDRKGfhJyZtzhxKgBSXFdiMHKwSzqx\n6CA5DrfWp7z6v4554UUd/UQD/WTEIJ4wDVJ6XYvEVZFCCzkE0yjhHebMFHXmyiJ6tYCYp9zf3OAX\nv/w8WiVByRx0rUduuCzMGBSbIAk9ZEWFJKN75wBTPnLo2+mP0OYdlvNlJqLC9mafndsJ/YciLTtn\nea3Gj364TawX0OZNnE5It9OhrFjIhTJ3BjFpe8wTzTkMAa6nBySzW2gzGWtrMvmswtOyyXv/wxT2\nR6ydOUHPvc8kgL3NmEcHc/TuCMSnc0RV4M67GaPLAsKoQIyL72cc3M0pCpCORR57/kXCicQTv/4i\nSzMRD942+MeP/zG/8JsNmqUad67c58KnzvHqX7yFYVv8nX/YYubsDPKcx+pjAfqOwP73dUYTESMv\nE/sRtYJ5tJ5Fg3HsM+lJFO9GzJ0/+lVJmoCR58zXLS6HMfWGzs987jGScY+pdYCr9bAuVojzKR98\nNGY0SnA6ClaqoWoycpBgaBpTZ8okMPGFiPqjEdpMyNTpMmer6BjsfBxzf0thpMNTf0emGCcMlJy+\nk2PZLlbm0SnC479pkX6gcOsbO/jDMqsLOpY8JVd3KZ+sI5spftDlk40JzbrIG3+SEZ3Z5cQrLq4w\n4nihyv5ml5I4Q9w/5ES9xjdfu4oU1Xn0KZNyZYBc7RMLQ5YSH71iIy630U+v0Hi4RblugDNiP9ql\nsmzROq5gP7rIe3/S4XA3RbuW8uSzM5yVygz6t9kP2xwa4N/eYvD184gPNbzEwaxHjNM2p56YA/02\n8qwC/M3Twe985/cQM58/+oO7/NY/+33+4Ov/Db/75xcJ+D84uDfFts7SuRNgVh6lpJVYWPtXXP7e\nVS5dtPhbv/EkgvYqoBJHu0Sncx5sDbj4MxUKjdv4XMcqXOLbf/xZjM0CK0WR5/4jm+Gxq5y8eB0Z\nkzTyOXnpNFfeNrkl2LjOSR5ubWEaGmsnLP6n3/o+tTmwkg7Ly7Ms1DLW7/yA4+emdA86jKu3UPRV\n9ke7VGcMtvt7nHikzO6Gz4mLTRJtSJpY5GlM6s9TMIdIFEHqEVvfguBXsYMvE0zfJky7nDv/HBP3\nI2oNgbs3ROqLMaIw5LUrr3Nq/hyt4iJ3NiZ49gN++T/+Z/idPaajLXxfwrIaHD95nmm4xp0PXBaO\nqUxjiYkz5L0P32N+oYNou5w4u8jH7+Womk9xzqKyuIWERhLfZnlVRVESdAtG/TL4TcZtm3EnRY1t\nmq2cSvWQuN1l7M4Dz1HWBNKBzEFbpFKRqBZPUV9cpD4r88G195GNHYzKdR5ZbvLmj94k8ytIcc7e\ngUOr9ijuaIfnn/sMZrnK1773vyDbU7raGK2goRkaaR4wCWLKpQq9gxILKw4Lxyd012N6/hhlaOIe\naIimiWSCVgppzCvUytuIRYH8ssrmVY+DnSrxWxKtNQOzNWWy71HRfXR5QEk+Q7ovMF3vIrSL6IqP\nF4S0ll/gfvsWQfeQ3/hHj/N//eHv87f/0ae4+FyRnWjMD/4sIe5/lvDOCGn2MqEpkesDJtkmtnAM\nQbtFNK6iGQecffEqL5qn0cQI/c0RNz6c5971AfcfmFSsIWJWpGoNMMUdpkmRJLFwJyaKMiLVczLR\nIqRC6otM9hyURGWuaZLIyzx4v0fi7lOvBYgtsEsJiZMQT3JGo5xqS0VblEnTgJLt0kvW8cQ+oRLj\npxXsZp3NjYvcvfKApYWMykxAdVWhWZzDrjcYC3t0nRHuOCYSZdptF6I2avkny/OfaqMBR1OILEuQ\nyMnzhOzHzyFHEHJkWQJJQhRFJFFAPLo5RZbn5HkGQk4cxaRpjqyo5LlImmdIQJKGSJKKHwaYpslk\nMiaMEyRJxk8TJFkijRPgyH5WlCCKIkQpZTicImsyk8kExw2plWc4ffYUQRhw+/5dNK3Glau7CLLF\njTufYIiAPMHQbcbuhDSKgZSSWULWVKIwRBBzSGKyOCVJPcqlAkmSgiAS+Q6Vgk3gjGhWaohZSN0w\nqWgihqShaRqyphIHOYIpEcQh8/NNNnbWqVZLdJ0h00mAbpWYulNMQ2HY9yh6HpEsIqQpjUoVP84I\nAp/OZECexViGSlnXSYiRIgEnE5AkGUW3CUSRKIrQVQVN08jTI9vbJPEwDBvTKqMaRSbOhFKxhlYy\nqZZWWVq6RS54pKnF97/7fQaRzp6Xc+zR3yDSXud//N/+T1aW1vi1//KfsmQG/Lf/5GV2bu3z19/8\nv7n9nbvYXOOXv/QSs7UTSHpOmoMnZKiGjmuoVI0i3sQhCMbEQYAsSyiqShC4pHmOKKgUizpiV0KS\nRCqlIu+8fw3LtHGCCDeOKWY6miJw+uQa47GD60Z88slVCvUKJ0+dotPrgdCjVK4hCCCKMnkSI0oK\nmqYiJQFpHjI4nLK4dAY/VpB+zKsolSz6vS5GwSbPIkQ5p7UwS6/tkiPSGR5SqZYRcglnMiVzXMaD\nDEULqckNXMejbNh44yEIGrIMSZ6gyvLR9w2JPNUJBchSgTTP0BUJS1fJ8oQ8y9ANDUmCLEmOxNyy\ncLTOxQwpSyFMAIkoyZAlkezHU8MsSwAIggRyHUGUCKOMyEuJo5w8giSCPM2P3N3+PYT0QCb/go5Q\nAzM4AjnuXom5+5cDpocyK8tPkiaHxIaPfGLMsXMVAishETO6P4xohjburQTLtTlmF7k8nhCXc9yh\nQsnQSUsugj6hLw0QJOg8yFHiZfRshmRSxdvvcnZugaZWIx6mxLqGOFNCbITs0aP3cMx8M2fVmsFJ\nVLbWQ7R5g9lKQuehy4WnND76bojZt49YH6tlRnsjgpGI4AnookIqqwQbPqKkcOHCMYLYYzIdEAg+\nn/nZRZTZKaN0j8JySNMc0bRiLC2m1DLY3dlG8BSyIGXnkx7HWguceFLFr/dY3+myNT7EUDWqdoEL\nP7/KaDdi+2GAlMW0jrfY2s9xBjaTjkSW23TXh2TTDrsP98CU+FiYsv5hiLrt8tR/aGOmh4TeBn66\nTV6d45lnBPzdhLzv0qraDEcjOn24dzmjdO5xgvgeH74/JR+K+JsWeaij6CBKLmU55df/wQkSYYUv\nvPBP+Kf//TcZeC635ID5U89yf/IXaLufY//qAe+86XHyiZMkWsaPXv2Ix47VKKxp+Oo6QyFGL5eo\nWXWGSYQkiRiaSK1u0t53KBYMBqMAvdKg3z/k3jUPfdGmWonZ35sy2usx3EoJ0hJOPmYy2EOobBM1\n+2CGJJ7GcEtBF2wO1jOioYadQ7EwQ1iWsFozKHoL+0JOYsgkeYwWScxJKiUrx0lyNKmKFI7ZuBzA\nyQS7kh1N4icRbgxWDZYLKsGKyY4eIckymigjZZC4cO3Dq+xs2KQS+HKM0qiwc1/gzKnn2L3icX9v\nhPULA6IGDOYCxrswafeZmynx6MnT9PdC9jr3qEsp555TEIo+Cg6Ov4+GT84hmjqDXOiykHVI8FGq\nHvLckJkLOhNPQokU9KnF6HBCkmdQAMmB3l2Jvdsp6XqfSBax0xL5WGK7s4f4iMqZx20+YPdvvFZc\nv3KcYHDISy/9PFd3/5B//N9pwLfRcVg9WaJ9f53MP8vWzTGtlUMMY5+TZxTGA3j4wUPWPt0nz3VE\nBVQx4HO/uothvYWEhcYnPPVkxDde/Tr33/k55sQv8fBHCS888wVS3iTJbyKpAk8/L6NmhzRqz1Jd\nWCbMvwzZhCzy2fg9ndA7Qfe2xvX3BzjhkMW5p3i4s8dX/6zLs79uMGjvo5g2QTBBsqB2QuTad1Z5\n7PGX0KQ/Jch6qMaI+dKX6fEGbnRImlRIwoiE24SpxKnVl7nr3eFg+CH+5DIPb+VUCqdorfTZ0YaM\n+rNE4ZiTJw28g12219/gw+9/G83uc2btEYbdCTt3J4SiT17b4fRjRZZXTnD95vsYSpvI0Xl47zy5\nPMBPE9JkCS/fI0gfIIYeUrJEf8+koh9nOmngBSMEMWd/02PvvkOhUKegy0SjIm1vTJIvIOsncBwX\nXfURzevUKgGaXsKT3sAn48H1Os3yl9jdv0rodZn0NpDkGeKkhht4VOxHKdnnGe1+n+PzZ9GMCiVl\nCT8ekidHRkCimFEoJ5gFiTQcsH57SJAvUHu0i3ViTC4mjCcC3V2T2eWA+dWMQkkEE7qeSFTI0RYS\ntIMUL1TZunmRwU7G3HEFd6dHw1xhofY88WAGzY2puT5a6DJWqtRmIya+RrN+jKI14d7gq/zqby1g\nNve5nf4Oaz8/ZfPhGnsf/W3e/osOZ/7WW1RrInkO3QAC+x5hqFMwdWaKYAlNdAJy/ooXP/cpGnOz\nfP+7n/DxD45xtpAjljukhoElKgzcManQY+qq2KZJmHmQ5vhBl+vv5Nx8rYUW2zzxmQqRMMUZHuPO\n21NmZy2Kp6fkx3NCR2D9g5jRnsKlF1sYxys47gGJPaTvTBkPFdbvy6Rhg8WlZxAzkcNcw1c3efz5\nHtU1D19pg58zdTyiUMRJRfw4R5Y0EGUibfQT5bn0la985d/40m//9m/PAv/pz798nkbdRFZlosBH\nkkSyJCNPQFJksixFkAVkWUZRJZQfbziSJCTL0qOrTslRY5XEGVkuIkoSsqSQpRGqIhJmIbqh4/o+\nYi4SRglhmKJIyhE7IxfIjmYrJGmG6x4RrlUVWq05TMtkOgkYDBzyMMZ3hljlWb77vSt0BjKd3hSB\niFhSiNKIiTvG0DSkTGK+vkySJEz9EWmcYOg6YRAgiSKmadKoVugO+oi5iCxB2dZplAtIQkLNMCko\nOaaUocoyRtEilhRIQyRNoNfZ4aPrH7J26izt3gC5YKEVCliVJuVGnURMCOMA1bTpDkZ0uwNu3LhB\nv3eA6/cZjncY+w6DiUuaxohZCnmGrpjYxSKyqmOo2pHlqaGhaCphEBGHE1RVoDscE0YSORKqZlG2\nDdTCCnvbH2MCh9tDPrhyk+bpF/nCL/4D3rqbcvnd3+ef/8+/x+13X0VTl7h699ucO/lp6q1P89yF\nExzPJ3z5M2fYl3PevruLJEyot+YxVJ2CYnNsZgHByciUDNIEw9QwNA1BAs+bIooGkgpJpCCrEWM3\nRTdVDnt9KuU6+/t7FMs2tqViaSruaEi1WCINI1RTo9mqY5VKDIY9cklieb6J407Jkhw3DLELZSS9\nSNEUSb0Bkpxil3SmkwC7JKLrKtPQJ05CZlqzTJwxoiJgFQxSMrJ8im1VkKUcIVFxxhOG7SGZWEKI\ndcoVBWcyxZsOEYRdhBQUS0AWc7I0PeLNpBmCpJGlGbKsYFoGiioendpKCYJwpGfSdZk0jxBEAU3V\nyFIwLOOoeVElVFVBEQRUSUYWBfI8glQgTlPIBTw/JwxFslTGnSZMJxD5MqEvEkxzoggmzphr998A\n+P2vfOUrB//27cH/f5340ivHOftkjpNPsYY5W1HO2//SobNZwvNV6uUyrjlmqPUQzuaUbZNIjAhx\niadT2h9HGHstiuJJpoc2tzcHFEoC040eg/YBpdM5al3BF10UucXuJyZJe57hnZxsUMFySjRqFfJy\nDssi0jK4iksv7OIJU0qLAmk5p6DIyEpG2UgpmjJ3hD027qeUlccI7i1QCE5RtRfo7qbc/niKMDYx\n5Sa6phBHCbmYIYgJVkkkSQeUZ3MSbUztgkBxJeP+4AYrT8icfSpn9WQGiYdYELi/FdA7LDJ8mNEY\nF3nkbIOlLxlMSg+YL5ZY0+ZRdA1fHONNPAQpQ22oTEbbVGsq88sa88sme5ttbCNmbl6mOR9x+rRJ\ndVWksKCwvtPmsO1SbWrIjQwn7CCqPtE4or0TkQ5kisY8y2tr7I3GuNOI3v4YTZTJDiocvO3B/hLB\npIQk1Tl+qk5jLqa86vL5/+IUvqVy8qXP8b03H/D61oe8+YPXeOTSp9m5J/E7v/s7DMcVIl3lT77+\nDndurBPkOdJmBaOREDRjLKVGeVTFv1VEjwwWzxzj0udWMEoqb373Y/LMJBdUkkhkf3MPrZij1nLi\nQEDyRHav5Ozvy+y0E9K6QkpIonjkSkq9WGPzr6D7Wsjx46foOC4bozF7n/RpuxOikohdMYh9B62k\nUZjTiIUQ1eoSxOsI4pDqYomVM4uMx1PSacT+dZ/CEwAUBlgAACAASURBVCKeltEyFXpRSkGDUEi5\n/eYUsV+hpM4R+eBN4MTqAotPnmXqSgweBgjThPK8Qu9wzInyGu9/dZfmgsHSuXmu73WQSimyDEFf\noKQ0MbQZkixjkvXRCz4nH49oyRGSOkRNXYrqGC+cMFOZY8pDbGOKISRoVk5ruYKWlDnoJKxf2+GR\n02skrosoxWSmz9ZejuA+gnntebp3JHxBpDkq8h/8ZxeZ/5KMXM1I5RI//MOtv/Fa8fRzj3HxkS8y\n15ojVd7k05+v0+tNEKMTSIZD62SEOn8bc+kus2cS5k70aJ0WuHbrkG6vx8VP9QGLnB0S0aNVXUWS\nBQThA8RcJQdu3e5z/Y1lxt4NisKUkrJO9eIdoIDMCiCj2QMc6RqffWmelRMHnDx5ixNnHlC70OP4\nC8fYHvuEyjEyfZ7Hnz9HJ95lEnbw+hV2t7vM1kyC4ZioK3DjTRPLe5lo8ghPfeYsP3z9E+arz6Lq\nNprcxs06tPdjpMmXaVXWaJ36GCfcQVOW2Lg/wR+1ufNWhUcfWWXitsllmZs39imaCSUz5aMrD/Hi\nAu12ws5eG0Gw8AOHnd3byJJMwZ5lZa2Al75FozmlVrZQpRr7h9uUqhpLi2sUTAUlU+gPAiZDhXrx\nRZR8EQ0Nu+yAsc/EbZNlBkVjFdcxUaU2zYU+EXdQjAa7HYVGYYl+9xaG0iUJUsZDKJZWIVtDlz9L\nEtax7ISSXaWsn2Np9pdRtGXyuIE7rbF77yZCUOfGtQ+4cvNb1Fo6U6+PIKYoqkKchehmhphnZLGN\nM01RxDqlRoioe4QBhAEsLksE3hRilblmg0DpoKsiTgyaKbJ2XCdnj357gOCVcNo1CtkZnr30JIur\ns4SJgNcPyBONXCnQfCTh0S9EDPzX8Pspo0Ob538lp7B8hzAOMGsBs40VGtWXuHstpLcrohkjZlZT\nJm2Hw90mZBGi7lMqltFyFZkMWRAh/wwpChj32L8Vs3Wvy7AdU66WCJKE3iGMBgH9PR1dzWjWU0zZ\nIs59AsfE7VhI/gyPf2qeZ7+YYzUO+fjGQ7Y3NN79oYfXzxHkgGG7xI03YsRhg0vPVVg408WLZQQp\nQZQLRO5pKvZp1o4vMrMakaYxB52bjLxdzn3aRJsPiMUIz0vwA58wBT8SGBykjLspk0lK7MHl1/J/\nY534qY44fS+AXCCNM2RZx/NcbMsiTgJk6QhzIQmQZymqrJMkMbqmkMYCSZKTRRmkoCo6QZ4SReER\nYCRPgAxBUJGElCxJMFQNL/aRJBnDsPCcKRIZMTFZlhxBAmWBHBFBCPF9iW5vQJYaHHb6GIZOe5iQ\nRCGzzTNYcp1OPAFBIY8FZKkCYkihIKAqObIJU++AKA5JohRdM3AmExRFYTwac/LEGlsbW4iyguOH\nLDYrVC0NPQ+wjSKx76NmQJZhFQqESUrqeUi2yv2bt1EaNj/z8s9y/dZDVtbOErpj9qZbNMWA0M9o\nVFokasLh3g6aFnEw6JFJOdsHA8J1WF5qUaxGrC7PMel0sDWZiTNFVA2Efo5SKUGY8P/x9l4xm6Tp\ned5Vueqr+nL8c+ycZnq6J88GcrXc5TDsMohciwYpi6REmwcWRB4YBGQYBm0Ilg1JNknZFFegaYqU\ntFyJ4gZu5MzO7MzOTE/3TOfw5/jlXDn54KfhQ4qAtC9QqIOqgzqo5wGe973v656fncMJPSwrhyBI\ntOwOUeji+ymlSg3N0On1WgjJFEn0yAsyXSeh3b7DuZf/Nr/y8/+Af/PGtzl3SuLv/uxvsLpWJyPo\nfHBwnx/55C/z7qOb/NbPPcfjb73Fsy/8ADvbH/JyeZW/89IyKCX88CTxOl/J0/I6JGpENjIIwxBd\nURjaQ5IkQVEM/NDHGYjIigupRTbbY9KB2Zk69+5u89Tli4jERHGArmg4kx5+4lNfqrO7+ZBG/jz3\n9h5gx3D64iJBFFKtLHHc3SRrNvB9n2pOwzQMjjsTZqslomDC2vocQ7eHICaUrBKaLmJPhqiiQEbX\nmY4cCsUCgmHhex1UJcvUGeA6EUamgBNO6LRd4sRkbs7Cdz0MTcUexcSjAYqWQVQkkgTMbJ4kBjNn\nMR5PCAWfiBhFE9FFDVGENE0IAw9VOUlfCVyfrJXBDXwkSSQIQkRBwCcAUSBOYwRRQZVV7NEIRVbQ\nZJ3ByMb3wQ9OTgpdL8C1Y9JIQ05OfB7fl5XP0e0f4+QDvGLK5lZIkNRoXFjm8eSYW0/ucnFGpPwD\nEYumTMQhM57EsR5QP7vId7+2TbSb0JYGdCYZzLpMKHsMvIhGJg+hz6TlM0pz6EqeUV8k7WWZpimV\ngsasVMILAyI5ZiQNiFWPpWtllrMFJu0n7NzscHMvoHVxSKMGBUfEMl2ykkk0SMlps1hinv13p1y9\ncJVvvtGkOHMObxyQn1eYRhPIecwuWZTLJmomZSpCphbw7hff4/qFc8ycmuWKUSFypkwfBTiNlEq1\nipjViJQeB90euxs+V8w1jppT1MdHmLU9DEz2nBDZMymv5Lj7eB/LAN2sk1mJkL0Wm483Ed0Zrl6v\ngg+in7D7aJ/abJFR85g0YxDnbERFobWpEolTtCLMLAYgjdDKGUwh5XSjwdlrL+HIKl//7nd57DRp\nfz2k7CVodpHaSgUjr1E+YzK7kOdgeJfLn9C5Wh7T+HiFHEd8+pcLOP9Ixi2v8Mkff5HP/K2XmdcX\nmGsv8S/+4T/nF//eL+GOOmgTiTP5KpsffoAwUDDECP3YZr6kc/b5dcRqgFtqkSkazF0T2buxTW3x\nAisLyzTbhzSPJmSXJZxWB8mxGPcinjp7llzG4Gtv3sdLJvzE564g2yb5YY0Hf7bFYlpHzMiIRYNk\n6hD1YvoTlxfnzhGqNnoiICtTZMdnRkvRCymzqxblBRk/GRFoAdquQK/Zx1MFhFZMuQEeLqkm4MTQ\n7IU0jxWWZmpED0XURMHMZZATE9eP6Bz3aB8MySOQWTJphWPeeQ++9ZrAL77wSR78xQPu3k8pSgaG\n7hF2U9KcArpIIKh09wVKOQs5FZl4HcZjhfEkojcZUa6V2AgOCBA4aopkcgFxDPWMxahqcuFsiQ/f\n3OGrX7/H1etVavY8O3dGGGqNunyGXUlmoA0YqUU+kZ9DlBKMMEclXWR8fPv70io+96sdct47/P4/\nfIjgznNvdoF284Bquc3ln56iVCPqjZQgvUEkBIT2VeqN25yaP8eD1xWSg5cISxvoZgkxWiGWHMLk\nEZooMnJMTDPg9OWY7me7vP3lY5aPTN784oClHzuNWBwSC7dIU1CrAbPxETG3ABtBANvzePGyQI/X\nkUSNL/2TPM/+yHMsXuzxs/W/xb/6g9/md37zNq+8+IMUgh2yxSmvf6HA5HAdo/BlnvlIjrb3Hxim\nHzDurLKwENKO25hqgZy5yqMbCgexT+NiiLXwXRRtQtD9db7zWkiucoeR+whX6/N4AzLqPEe7EeM4\nwpVMBqHCrZ09Lqxc5snRAybtTcolk35vytVXPs39G7dYODOHNaexu9Wl3d/jqWdqPHW1xN7eFs0t\nj+WFWUaU2W/dpjvcI5O/SyoOEDN5wqaJRIN6dR5bzJAmA+LAYjKQ0ApP0e1rlGsqw+lN0O4hi2tM\nBiFm9gxqtIyka2wcPCJTfIfYf0K20McqnefBgw84dW4ZwZ9l2FHQsmX2dt4mb83S73v4+pBMziAR\npxwdTNF1k6yuAyECHrIYc/hwSNVcRtdCRofbSFmX3JyINzLZ34wJ3SlqoYor99ElCVGDam2MkSjk\n0gru7izeeMJKuYjQWmDnIKS2soi5PKDT3+Koc8THfiglc/47XD63x8M/X8A+fJbDW+tIesJe6zZr\nukxeK6I2HrD6A4fU9vK09g32brbotovYWpNKo4JV9BFpEokqKXN4cY5Y6iKmLYTUYW1dpL/9FDuv\nl6noe+TWdpHNMR4K7c0qr37OpWj2SWOVrCZCfYbi0wbtmUOWTg2JNI+pJLH81Aq9SUK1J0NwwHe+\n+ICXXrmOFHxIoeaRyR/TmvQQhDxjO6U/aWEYBsVcG8/3EdvHFJfO8kxU5/VvtHn9yyNeUFXEmkMo\neChGgqIIaEmWcTBl0BQRkgzBIATsv7LO/3oeDUEiTlI0SSMhQlF14gRSAYIgRJIEkiRBFEXSGBBT\nkhTiFIRUQBQEklQgCBLi9ERmpckyoiiQkuIEIboookgKXuQjIpIkMWF0oi1PBBFJkpHSFE3VkSSJ\nSlFn6g1w/YhUqjHsd8mXSqiyhGhITIYit967janL6GZC5AXoeh5NChBFFVWR6Q+GmJZFnMZkC1Um\nxwcUcnlatoMiq6yvrfLg3m0UJYuka4gaIMn0msc8vdwgjSPyhTxCNEWSZMZ+QH84Zn65wa13H3Lx\n49eo61keHXZZPn2GTKJwPB0x6YQcPNnFth386ANGwwHZTAUvDUhSC0EKEAWDjGyxs9lm1tHx+yMq\n+Rz3798lWyigaiqKXkQSE2rZCiQCmpHHT0QUK4eRyZPEGmZOxfVjjo4PSZKQyXiIZR8gRh4qMqcK\nC1y/+CIbN/6Qn3j1f2D30GV2vcaKcJr93duUi1neff/r/Pp//T/Tvd9EGbSQZBs5I0GpwJPOkOUl\njdnZOcIgQVN0dFFHlkSmdg9FkpBEAUlS0DSZKEkRYtC0CEGwULUURTYRxB6apnP61CnaR7uIYoKu\nK9ipSCpK5BolDo72uHr5NIsz6+z0NgldE1U++R/6Q4ckDYjjhEaliOvsEExzmIUiii5TzBXp9HYo\nVGYZjbuYoYgzdTFzJgkC494IVddwxvbJcyuLpDlIGmjZGBIF0XNgJiWjSuxuPmRu0WA8SsgYCpEL\nfhqSNQwiAWRFwvZtiCREGbJmBt8PIIyJw/BECigGQEIax6QIkEakiYQkgiLJKBmDKIpPjHGSjDO1\nSSKIoghDU/D9iNgP0QSVaQC+F+F6Pn4QEkU6USzj+S5J+J9fcw0wkAf0ym2clsitNERYUfjof7NO\n7zsFDt86JqtFBEEXTWwi4DMXpEgti6AcchDqaAUZbdTg7t0mk6lFoors7AT8+A9fYPlSiMYWg8mI\nyJW5+8hDHS/guTJp6jMWx1x8sUhjNcuRP+DG4S7R2GFppkpOnhAeOYSuSbmjcPfPJxzVRWIn5Kmn\nG3SGAoN2SCG/zLmni/zJm1/nwXGDwWjEpStX6Xn7xFFAYLosXjax8hEkXTAEslZIazDAmnMxaiIq\nEtfOXOXBax+y223S+EQWtVYgJECuJKyuFTh+d8JB5HH/wQ7H727y8Zcjxt6IWqRyFI1wN0LmCyqm\nVubtewcszWbY3OtgJwaykNDZa5IrlNB8BUGNEDSPxozA7mREzpDoTmX2HwXs3El57rM1tmmxvBKR\nf9ojOZwgZ48x8xqvvvIR3n3vNv1Qw/E9rhmzWNmETLnAk2hEKpXp3RjSs1Oe/Y15IrZZS9dJhPd5\n3hKpv3SeP/3jR+z83/+W3Md0bgc9xrqDJjTISSMWz5UoxBkyUYaaeREqNp2tAx7cfETjo4tYBZVe\nfYRvbTEWI2Y/onFwELBx+11mCh/DyCk0jwKWh1WskkW31cQNRJLY41RtickFhXce3GH7rkM6jRhZ\nDkpscur8FSYdiQvPXULZ32Bb2MfpbSPFAoVcRGkmQlY89ts9xLLKgCbZQoAxJyNWLfq7KfJSiDtO\naRQFRrfBkASOBDDKMElFcoUl8j9aR97Ms7/RQjUsVCXkq196C+mCjjCpUkxENDTSMMO+16Y37GIt\nLvHmzWOa7x3x/NMXmD7xselTKaiIaY44VciaRcRgC8E1mbZ9YlTCJOVoL8LvxyjnCyQotCcZ3r7V\n5tJyg2cuz5KEdXZ2Jswuz/Cxn3yZ77x2A9sRuLQ+w4evacxn86iyzXg4oDMzRRzqlAtVtLCLac4w\n2muSlb8/4IiIWRqnfWaWJkyHeX7rt9+iSJH/9jfXUCvvEgqPSYjxkmWktEqq3yMjfZR8bszBwXf5\nx/9A5If+y0We+tQMnnwLJc2hpTWExELVPPrBmGefW2J9tshx70M6jx9zcGzzY+PTpLkIVVonjFuk\ncg/ZkpnENzGSOSTFB7mLKFwjsTvko5ikt8mZCytc/uQQMe3x6i8pxO5naH+4yNt/JlPKXeHglkOj\ndhEvGDF0Bsiphr0l0osMRisaWjHPKOwxDdvkVko01M/gCw3icRYtfx9j8U/Z2FC4+rKGE/dodgTM\nrEnT7iEHM3TbClAmU55HLsmMhAFLq6fYCyYcdA/4yKfyLD3tEG+pTPpn6LT6xEKAolxgebmIot/n\neHeDZy/8HJmZO7y7fZeSv8zmwz3OnF9jaoNeP4M3DijmDwntXexJiUSwSSWdg+EEPS7jjFMK0zJO\nnKLmTjGY5jAKMdPoIV6riaGeQvLnOH7SQjEkStpzHB47FJV1Nu9/SAaF2fIVDgcdKsXLtHv7tCZj\nlCOXhgIZq0zQd1CsDDu3Q1LJJZsp4fdsBk2V+6FN0RJwgxxrTxvE3pRyRSAYKdz45oDV8wvMry6h\nZ1pIkc3BRsp0K6GeO4udrzIZiQRHU1JhxOLKPJm8R9fvYho+qbuHmzos1Q+YWz+PLmh854++xP6m\nQdsecvqVLNmCR6/bw0uPOPuiyPxnpvzJP4158NXniAWP6z91l/p6jKym6GmBOIyJZY1ETPAZsL21\nydGdNe6+O2ZhqYSy0ODxhzex3xbIzMSgmlx/RWB2JsBOFUx5QhhJZKQuvp5FmD2iK9mYiJi1Ehc+\n5rNwZpWH7zrc/KYOo/M8eTtP5K2hntpCqwzpdhNUfUqcRiAoTJxdHEXE1BMkLUP+zEO63hSlEHG0\nIXPnGxkWr0NQckCKUKUEb+wwPUzZeitBilJCweA/+aBBnBI4PonikyQpsqRgxza6YeD7HrKsk6YR\nqqqRkqBrOr7vI0syoZQiKxpx4JMk4UlauADpSYwfgiCe6M0lkSCMSWJIUwiD5OQepzjuX+ZpCCph\nkOB6IaqskcQWkjah3x1w5twssqxDoHDvyS1mZ85yLAcMXI8wPDFY1woW7f4QTRNo94ZkrSye51Is\nFnmy8Yj5pXnazRaKqrK4uEi312Fl/TTHh0ckycmJS6/XY7WQw/VjSoUc3V6fYtZk7LsoWgalUGDs\nxlz66ItYicru1GWpMMd7b75DLMSUxCz9YUCqyXiiwlSIoDRDczrEizO0u1tY2exJYJvQplAqcnA0\n4ExOp9kcUSlkkAWJXW+bsDRg3SgQk5ArlZgEIbOLS4wHY8LMiFFnHy8OCEKXlfl5Bt0eqqCR0qJy\nMU/5oU/h6Vc5uP9Nrv/9/5Fp/y6f/fSn+eKXvoggpYSpwfGRx2/897+L9Ph7jLox81WDmw/uYEce\niiRRLuTIZQr4XkQmYyGIArqh4fk+aZIgGwaO66LrOmma4vsuuiqhKgbjyYgwVtF0g0KuRhy30cuw\nv+eytLLI5vYWWcNkbXWFMHY5t7YCkcLOwTYeNoVag2x2Fc/bIJ/NkolLaKqJKCTIsoaqpDQaecLY\nwXNPYG+eM8XQFZI0opjPEQspmioTRRFKeoKSNS2DTMYgDGOyOQ1DUfCCKV6YJ9C6xGkXzRCIQxFF\nd0lSB0G2kBURWZIIwwB76qIqGUQhRVUUwjhA1WQSCcLII0l8xFQg9P2TeohTEAQ81yeRRVzPIZvN\nkqYpggCqKuEKMaZpYk8mCKJAGPiQGgTRCT46jiAIxZMrSPF9AT9I8aK/uiH8p1jO4ZCdd1ykADKn\nYV6VMLMa29ttCopKo2ASOnvoXkLWSEn7Bv6RzEpZY6R0ORgmfPDueyCsk7PKTMOQIBCQ8xKJNyGJ\nBYJRiqrl8PoTCBPGnSHZco7nPpLlygtTZhenLA5E4ncsNu4fkrZtLjy7gFA/w603bDYedxk0U5LN\nIrIn0h7W8Isi6Vhk3Anx97tkLDgcHVCZqzBs+xxteoR7PvbSiMVnsoyjo5NAJDlDgkBcEHnuM8+h\nBhrf/f1HXJk/y/hxATF0sT55Ct+bohsJF0+r9PyAwpzKO6+3WZwrUSjrpOFdfD/iKOgw1PSTHRrP\nYHxzSO9Yo3UzZmSn1Od0fEfi4HhMbigSDkOqxRwPvr1HpPnYOTDzS6TjAoPvTlGmClH1LOF1BeXq\nlGee0VgLz7OzPWJj83X88TlMDPJRlU/+zHU+fWGGOO1y936X1hsHHPw7B+VA5PwnT2OxiJVqQA8x\nPaDYjbh66VPc/e3X+eY/ucXzyVlGpQmL11fw0220qcBCw8KZ2mjigPmLGeQFlbxVAG+F+RfLBEsp\n6XwHXz/GSGOiQOXaS8u8e+ixt/UYe+gRR5CmFp2mx2jssfJ0DdGWGezb5JUMes9A9WV0IwuSgLXQ\nYKSMUKoNZhcy+EaFGVPnL/50k/XVmEFyRGYuRlFUyqWEKPIJnAm9iUc0SCnPZWm6DrKm0d6CBbOI\nsZ8Q2DYjI+LAAvmUzMV6hsJMmaE5oLXpkjlOCYYhhzv7PP3x5+mPItQlGAltPhxNmFRd4swhpg6u\n5FEs62h6hsPWIWIq4E8F5OyY6+cvEefK2B2RnpayrSbUVi2GTsLjd1wU30I5MphbWWDj9hZ+c5aB\nP8uNfkpz5wmTScL1j5zj6Y/V2dmvMt0KOGgpLIgfwzuIGAUOo/SYse5yJnuJOBpz79EHqHs36WS2\neLj5+PvSK9Q4h2ifZnFB4s/vHmPpy8jphLe+0eIHT5WonM4BHop4yPZuzGD/LHvvuXgtg3r1I9it\nj/L4XZcrr4LObRLBI5UbhFMf0dhFVw1UZGaXv8urP5vnX/6vQ5Z0kf7R62i1PrnMKqGgkaYnYA7S\nGoISEadZMlKVcb/Gm2/c4cNvjkk4xah1Gzt9E6hQX5MolA/ILJ5FDn4Kf2wyrr2FvmjiDGP89AnS\nZJX+kxR1LUC19unGbfqdCMuyGEUOQv4dqiuvk4pDHu15COW/4KWP/gy68jS9zu8w8RzM3BTDEMjk\nMsyWn0OIuty81ySKB/ydH/tBfuFv/31+7b/6e3SHOyysL1Odgb1mi3Zvmyie8vIrp2hNtlg+p/D2\njZusn7vOFz7/JutXWpRreSZOhrlqjuPNBF2f4zhqY1qHuF4fSVymsWLR7ahEGFT0a9g2GLn3SJxH\nzFZz2FGJvt8m8CUMw8H1pgR+iTBKKDdUfK+AZy9hZkQCycEe6QjRlIPD1/hf/rt/zj/7P36X1+71\nUKU67f4u2pGAOStSKTnkSi7DXopvG5Bcwe/vEzky7kAn6kAqGew8GLKq6gw6HaJRHsM22Py2R7Cr\nYJXyzM3PUEojul2XRL7MaOcYCwjGU7zKGFNrMzS3qV1+TKEikt/UmUiPEAwdzSiTX/yQ8z/k8NoX\nbV5q/A2uXTsktQb04jazMwFpKiAJAsV1nVvfkCnpJjO1GWZzu+z3QZY9VBksJQZE0ggef/cij94S\nWJqP+PlfljkY/zl3P1zk9a9MGXU1nG6J4qcnpGmCE+ooioMmBSTCBN2yEL2UqT8k8aFkTVg9O2U6\n26JgzTHZnmNrmOdo/y61GRM5mzKNNJquiyHGBBOIgwhRFpGyMVMXAscnlRRS84BnP3qF7311xM1v\nu7QeKZx+oYS+OCTKpbS34fAmbL9VQlUDDsfRf1Sd/7UGDVGUCcMYQZBJSUCGOEoJgxgBhSg6adxx\nEgMpvp8iCBKKrhEEY8IwIJUkREAQJcLQJfATFE1BVUQkVSEKIsLIIwqSvxR6CCfyKklGVlVEKTkJ\n8YtDRBHiOCCTM4iGKrPLDq12l1IuS7FUZmX2Ih/cvcfDjSGxlKVSqdHvHGOoClHgQRJhGjqB76Hr\nBuPRmFqlxrDXY3aujpnJsbmzTRD4DEZDSrksncmUBAnH97By84TeBHsywdA1EhHy1Rp7vRGCKNEf\nO9y8+4hAUVjOVHhv8h7lrMFMKccwGFGqZBhEDp3dQ0YTgeXGMjONJTKeiTBjMeh5xFmDUB6ztXeM\nXmowkTRMEmIxS7M1ImNMkHURefcRqqki2X2s6ixBHFGqlIntIcPOIaalIfoJjjclXyhSm59lfPgu\nM8IlSsv7ONUL1DIi97/8BV756KvEy2V+6b/4cbZv30DuNzm3tIT4wTfoRAN00+B7tx+h5zSctsts\nrUKpUCJNRXRdx7anWJaF47ioioSoakR/uZsuIeB4Hvl8jsFwhKDKqIaBH4XYUx+ShHplhic796nW\nykzdCYtL8wR+hCIrZEwZtz+g3lgjVQtkJYtKdRZDryDrTTQ1IBjFCFKMQEyjVqHTa+G4fSRJRDOz\naJKA49gYkkScOAThiXnbys3g+ieSPklOyWZNprZ7AjaQBJAiyiWNjq0RdaMTfG0cYVoqx+2AQi6L\nZulIqowsS6jRSXnJkkychigyRMnJ6ZwgJIhyShKliElKGseIkkgcJye0tchHEBTENMadjhBFBRBI\nwhRZEkhSH1lWSNMAUVIIw4DAT0kjgThKSGOROBKJYoEgFEhiCYnvD7Ny/9YETRIw6tCYSVmoC2ze\nHDNuJZy/tIQ97NDsuWjbEa4JNdWltJTQnDq0kpSnn60wtE+zcVcgp5Xwpj1Eyefg/janZ3PIUUwY\neRxtjXH6Mv5wQjCB6x+dZ+msQ311EyEdUK+f58VrCgXN5OHjbcr6hHPnLnJ+fYGt+zKJX+agHZBT\ndKJklVVziXvH73PrtQ0UX6Ny1mKUjIiTEs2mQ6leo3KpRu1ZiUAdM6FDeaHIzs09fDFk8aUF6ufz\nvPanjwl7Jq/dPSLqJjz9VBk5I+GkAwQ6lDMxTnZCJWsxOJoyX80jClkefmcHWxgSjVOKV2Qiq4J/\nV6D/QQctLBEKOQqGTuv2CFE1CSYZRnGGyA0pztTwyh5CEnFwMCDcDTBGEgwU8vo5Hv4Hk94tidzV\niAszHmNnypwlcids8eE3ekR+wmQUkltR6ZRvk59xUUYy11++yL0v9JmZr3PlUo2v/ckNfvQnVxCi\nHrrsM7l/hFXd5Of/5ipf3ggZbu2gBjrzocfdwF4qugAAIABJREFU126hHMNIsEnsHdY+nmPhqk1T\nntJoiEjLGqEw5kg5QqKLhY3YBbWrkCYiipSyc9xHt0wacybTIx8ndDj/7Az1RZFJxyMtDimFRYQA\npDiHVYDOXp+1ZYXSSzbnXg5ZvNYj+laLcCFFe2+Hc9fPcjicQGaCO9I4e2GJo2bM0Z0Q1085bkVc\nL1oET0KUoIoyqbH5rsylC2X2HozRTrXYweOVl0RqKQTsIORi1n5exeqUaP17GaUgIgUGnuuyeG2J\nwIt57f1bqI0Mz4ozlJZDPCkhXq0Qxw5Tf4RVlildnMOoVwhMjbe/fofJWCT0C9x4rcnKYQPVjDm+\nG5Gzyvh9hfY45N57HplcBSWaZeP9I0Yjl8qqyWjwkG4r5ML5PN3A4qtfvsnPfuRHOXutTr9rc9AC\n1w2RbZ3D3Q6zcUSvv8GxvIHtDb4vveKtzxdoWmcIXAFT+wbDpEu/NaLydo3vhgcsvdJEKsqk4Qxr\naz9Nr/0WpqrTncTIQhk7iDk8eshkr4Y0L2NIBh3uUDar+IHKZDAmh0lafsz6jIGejhC3foX/7Wce\n8+lfH1M7822e+aE5BrFNSRVo2T0SpYKagCB6+Pmvc/oZg7XC5/jj//0Je08KXBlXIbtOXeozu/KI\nO2/e4fKpTxBV91m/3OBI7NGYSMRxji/9icPBUZb2cJ+N4+8RJJUT+bnWYe/wfQ6297iWjZnaOqlX\nYBoecerl9+htLHB8sEZ9wSeIblPMpNi7HkN7Ql2aISeMmAyP2bpxg6/Iv4073ubKqcuknRLf/vLr\n+LjkM1fp9Hd4sHkLjClvfHeCFDyLm5R54ZMBD985j+qdZS47ZiC/jW/HFBoKnXYLzxapGK+gKVmm\n0g4jf0woOxjmFMHPk7PajKNtitULzBRmeO/BY6z8c6jePBpDupM9YuEJwSQkCmZYmltk8+ERZHrI\n9lUWa3me3LvFr/zEr5JrrHPp9Ks8eeMr6FKfQWePxBGZXyqDE1I2BTIVk0J+SK/n0gkjkmgeTU5I\nEjh6kGX7joAm59AJqFgl0jBl51ZExsrTf2RimhWEaZfmZJ9MUERIDxGUkNiIGWr3qa3eZeFjd8jk\nU5zcOnff2GGxraEX3mT5akqlXmX/wSLNXkRz3MZUYsiE2CHMKetI6XVeedFAah3w1hcOGR/O0Tne\nQtBEEs0njGHMBnGSkoQzLCyd594b9/nMT51mZumQspBn9VKF+bMqX/u3Te4d69y9JTD/8RbTJECi\njhd1yGgdAsnHxsdxBJAkJDGLmmnRm6Z0egFWSWNhpcrFj9S5dXeX5mjK3qFNpJZwUxspFnHtBEkT\nUBGQDYdUypPoPpVTEb7exyhFaIcL7N0a4Pk2+lLMNA5x9mWOn9QxlBqCoDKX0Rn63/kr6/yvGdgX\n4DouaaogCiJR4JKKKY7rY+gagR8iSSLEEnEUoggKsghJLBJHCYkgIYgiyV+SnERRRJUVNE1BECEM\nfYQkIQpjojhFFE4+L00FgsAjiBykRML3AxRFRRBBFGICz0VRRCRBo1Y1mIxtHrxxg8jX6PUjIkFB\nlmSm/R7z9Rm6gx6VcoWpPSGTMWg2m8CJ7EtVRcrFEsSwvb1NLEC1VuOgecycYRANRoiKjOM5CGJK\nEAZY5TzH3RYlvUJnNELRTYaOjTcaEcsKK/k6ej7DiiajZST0okVJq/PBgx28ccJTS0/x4tV11lbW\n6e656NeW8adtdveOKMklvvrlf8NTP/gitx9sctRqszy7wFF3wsJMlSgac9Cb0sgHuP6EpXyGMA1I\nCBhPAmIhRbUyTLwpSZpgWHl0I0elVqNefolI0HlynCK4d/GmLh+5/CxPXvt9zq6+TNedkC1IhJVZ\nHh9ukOo5jh6/w/qpC5y5coq79+6TNTKYuomuKhimhWN7iKJ4Mmi4E3zPQxTEE2OX7yBIIqIk4tg2\nlmkw8ZyTJPhERJQl6vk5HHtIuZBjPOnjex6eGzI/P49AQhzA6tpTdI965KoamUwey8pRrWQYthRE\necjS3ByunRCHPSRpnvnZBTqdI0xTRhZFpq6LqmuIaYIkq/i+jyDHuO4EUdIxMhmiOCZJREgSBEki\n8Dwcx2YyDBASiTiy6HYGzC4YBMmUankOUVIxLAHfC4ijENPKICjqiXGYBEXTUIEkjkmSEFIfkpg4\nERHFkyBKUTjJiYGUJA3QDY3JxCaf0wmCgCCI0TUV1wtRFBHPj5FkAT9JEaWUMPKJ4pQ4SklimSgS\nCP2UwJEJve+PdMqfqjz4Gjz1akp8KBDl6wxuKsRCg0GaYX+rR/3cAt0nXaa1HuPZlLpjU7bgVAzN\npsLxYEBZXyeNssh6RLU+otfvsfH+IfLlHnEVKhWThlbh9psDcpUa5dUMsdbFFLsEaZswnaU9HVK+\n4nHpjMmjW2MGrT4lpcD7b43peFl+9MdeIA0cnJ7N4+4OuUGNbjPguDvi7DOrjJ0J7rFC6AvUzhWI\nnIDjbR+94SFWQ2ZWK/j2lOHIYWG1yJPHPXqbDpY2R2/g0G5GPJedxZ1GiPUhGWz6jPH8gNG0RqGu\nEYoGN74WoegqpXMaxnxAniXGzQzdAx8lKlCrrJOTRUgMho+OWalcYCGrsL/XJjRd7n7lgNn6RVJb\n5lxGZJwX6Q4mBMtFRsoc3v0M5khFcx7hqNssGj5yksOcG3LjYAhJCSu2OLdQZ+a5JrFho9kC5UKJ\nwut53A2Z04vPc39rxDuHB6Rih2uVIvpphdce/AXG5Sof/8QCG3tHZJQK4mOTnXd6yLbCeMcl30jI\nzRwiVPro5QA7ksmdauDbIaLuYQoiOTtD+/EQXShxvOdQbOQ46jvk5AzxMGTn8JhP/s0F5k73iPUW\nQl4gf0pkNBLRGxGClZKtZ5gv5vi5X1ujM/smlwotJETqS3vsKUN+6f+ymL2yTWw/Yn8LDkcpFXOW\n8y8ukTcq3Pz2Pe7c3CPXiTDNM0hpBqd/iBMltNUsncBFL2hUP+JRwEcV7iHFEpGoM6RA00jZOky4\n8MI5rHIeuQTTXMz+wS7mJOTTpy4TTjoYjg/mIeWqQHY1xbMa6HWZcrmMoJrs7fVojaY01hax/Yij\nXZXRNKY9sukey9SWMlQqBfa3AnyxRC5T5sHtPu5wxPM/Pkt+CTYObiBIOmtnLiN1Y+pWmcVPlVi5\nWEP98JCjrwXU+hXqVo1MqnMcPqZ7uEGgH2Ml4velVxRmHyELs9TqEleMBT58vIsdphyXSmzfDjnX\nvYwmVznzQyO0T32PZ8/VSDjC9hLu353wrd95ndb3yvzhr0n8+G++irv2BjVpGVs4wlA1Nh9X+OaX\n7lHPXOKgtcFp8aMMc3022h7/+vM1nrr2g+RqLfSzTY6VGDfx8CY+GaGKabVJRJHGnIVa3eazpsM3\n/k+RN/7c5eoPyPRwCOIp5dIZsO5w8RM7LJwp83v/6o/53Of+EW/e/jMs6xd46ZWPI+b/KcdHFqpl\nI4gBg55MFI7Iup/Fabdx5K/Qbdr44yXml58grIhE8jpt+0MKmSqPD7owcihJPvfuv0fRzCNGWd7Y\nmvKoe48oPU06GBNsbPGx589SXekj5SboB1kO9taYqa3RnwwJ4w7bUxNDfp5soUttuUu9ZPHu+3tU\nGyL1ytN0dkv0OxOMehFH7XPcG9GoX6YzfMR0eoSRsRi25wgmC7Q285gFk/nsJTS1QH8gkMYpihIR\nuworCx9j0Bdot56QleuIk2uEox0WZl7h4g98nM9//rfQpS5f+cYXmMqQUU0Sr04YZ+i2wHfHrK17\nVGf6bN7pMR1nCGKVwSRGzykUzBhJhK2DDqplEaYyvqyTL4qkqUjoJKi5ObJSlX5PR5NkKmaFg3aZ\n5QsNqhfmWHghZS/awBnHDPw28vyYiy+ECFIWSbaBEvXGeV76kSz/z+9u8fjDWWbPP8RLQ+Zncwz9\nJ1iqgdbo8yO/8MO4TsxfvPUGxUtVbGOXYD5D7IrMNkzG0yEqx4w55uXPGsyeGzEKJuS054mFfa5e\nS8kWLhBE99h6YrJ7o4o6d0BsTsnIAlVdR0cn8mwmY/BSESfrY0QCg77EXjMmyY6YefnbVBfmuN0/\nIPKe4lu/16F67pD6OR0hMyRbkum3I3RZwR2r5PI2YeqTCHC8f0zkN2g2D8kadXa2PaR2Edsboekl\nSiyykpOZejmG1Qj+I/Yk/lqDRhzHCIgkcQpiQhJHqIZJEPgnuFpZIYlBVgTSRECUJJIoxfe9E2Sn\nmJ68J6mkckqaRCRJQhBGCEJygmaVVERJgjAmjCLiOCbwE6Lo/8/QSJKUIAhJUgVZFNBknUwh5XBf\nJjB9mkcj7ImOlc/SbO2gZEwCb0K1YOG5NlPfQw5ipraHbfsUCyVk5WQ3WRRSNFXloNlCljXiNKLV\naSNLMr3uEEEQEWURVdNxAo+qLpNEAZosoWk6chowtB28sU0cBFSzeQaTJstylbHXR9fLhLbHBw+3\nmV+o8dyPnEJIUvq9Ef/6i3/EqUsVvvar/5hAijhswt/49FW8cQdrvcTf/fnPcNRx+L3f/wNOL62y\nv7lPvqgyP1OhOexRqEzot1s0ls8gJilmKY8YO7iTLI7vU5tp0BmNsF2HGUNGmEp4co75p3S637vD\nXH2Bd772RSaWhr/1Ia3hAE2WUJQEXVPxbJfT587QarfZ2t+llK+wtryCqskoikDWNAn8AFVVOD4+\nOCGPKRJxKJA1dCLfBRIURaLfGVGdrSEEIUbGJElSplObJA4gTkmImZ2ZRdZ1Wq0OtWqD6XjKC8++\nwqDjszR3iuYgpJFdJAlTcsaYwspZdvf+jFgoIaQJpYLOZDBE1S0MxURMEwLPp5gv0Op1yMtZBCEm\niRKylkESR4hiSEqEQIwiC2iGiCwlxKpKLmvS7wwZjPukSkyuKFObzREzwTJK2LZDIoioRgaBlJAY\nIQmQMzphIiLKCrIk4Tk2SRwjJAlpGoEgoWgKwl9ion0vRFc1poGHpokgpCRpTJKkhFGIomiomooQ\niyiyT6qKJLpIEgiQeiRxSJSeoKjDICaKMgT/n//j+7DKcyuolseDjTZ7xzB6ZLLxTkwYiTjllOqV\nc5x+WeS9vW/R+pKP9dMFiiWLJkN0TPShgZmTKepZWschaT9GTMEIZIoXCpSfBaPqkldVBjs2T+6E\nHDxs0Xu0ipTReDwdo1k+tHpockqqDEgEl8lQ4P73mvTbEUFY59ILq8wtz3N88IjR9oTRzQi3V0cc\nWeiGwU43YBy7XDgzj6J7SEUXN01xmxNKOUhdmVsPtyioArIpMmk1aT46ZO3cLPPXrxEJLTbu3MaT\nc/TH2+S9CUKmT+QLFGYknHDEyuoa794+Zv2KRSaqMRMtojcn+G8VCPs6ZbdEGusMuwlxzsXe98nH\n64zfqTL+cMqj3JBipYaoGejJKVZUGdOQ2Q03eS/XQV9V2GiruA9C1hSN0X4GSa6iBh1IfaxGho//\n1CKPXzfZeHeT3XeeYM0OyJzus/50kfCyQfZ4iTf+px3e/5NbGOtVlI2QaX7Ejf59amsNlJzN3viI\ndjckiSyGxzLt77W4uzfFKwhkZIWF+Rzi6ohI75IJJcaJCopDV+mjTFLyjkAmzePtxZQLFfb3Wriu\niK9KHI7GnKrPouseFy7O4Od7GJbBNPRwhDZCPmH5usVCrcLj9w9ZUCK2H9wlXtjESleI0ZhfHLCv\n9nlxeR2DGN1Mmb0oMHAFHtzd5XS3yGptnZ4WcKs94jv/7oiVZYnYyOOKGlbFoGsnBLrFoLvPx17I\nEiYTBFFBa0UkMxE5ehx4Kk3B47lTZ/C8mMD20KyA4faUlfwM+dQmyfTQFo/Jro1w80O8nMEk44Ka\nozNRKBRVfCEhrU4orMhEdkLdNHlww2XzoYNNwqDogOkjpiFoCaOohSY5nHlOYOW5iH7+iPKlkPTA\n4fjG23S9Etd/coF7B68j1F9EzMhIukCYpGjHGc49s8p4fR63nqdYFMmvlPhD7vxn7xXLz1ucPfc+\n2ZzCuV6A/we7HH4RnOkMz15d4eOfWEOpf4i2dJ+Ah4RBFkNtYekjnrt2ivdW7vDo5kX69/v0fnGT\nj/7sgOIzPkvXa0zFmIF9n8e38tzfnKd25XMUykOMRYPW945Zrz7Pxp0/YusdmXmpTn4uoLXh4pf7\nmDNdEnsdST4ilHs4QgvqGk+mLa6p8+SMAZZ1mvr5fYLtG7S9lHpUpdHYZeU5m6n57/nkz8DdW7/D\nna/kyCYSo8mU+VoRIXDZ3ZA43Cjyw5/QWT1t0hrNYA9c7EON4408zz17nUR6gLeXZ3f7Pp6nYuk5\nJvaYxnKJGw9buLLDeO8NTn/qVUbNEZK3QPtOzB2vxSW1j+wHPHnskNEvsrsBmPtUijPM1V7BET6P\nGHZRq1VuP36PSmke07fYP7yHnitQqIMzfBcpLhC6MaHfJMcMSZhjMu6DApO0xUK9yPHBDoosEmVt\nVE1n1PHxHAHTqtJrb4FcYNSDc4vzhAcF7j5+wg5vYeoVcguz3N5/AIpKgEMUjzCMiGnkkEyLTIcy\nGaGEHErEowRnMEU1Auz4kJ5tsL5YI/QkbNekOxiR1aqkaR27pdGolAhCG4KI/Sd7NMwiZdNiOn5A\ncVaDisxY+Sb3b/fZ3sliAPUXW8ytzTFfPsfG1h3Go/+Xt/cK0iy9z/t+78nnfDn317l7enLcXWya\nxS4SARCCSJoiAILREiWXqCrJZpm0qmj7wnK6YNkq0bKqTFVRJiWSgERaJkUELvJG7s7u5J3pmekc\nv+4vx5ODL3rLtyLoMt7rc/t/633O/3l+T4e0KUBrUp/PcfZijt7WGYJoB7MckhRifHS8OIOVazOK\nH7LyNyU2/ijkzl/C4ksl7j3ocva0xQePj0kbMnKUQTc0rj2zgqM9AARhfJMkniNWAsxKj+mVMaO+\nx/f/oMjSczUWr7bphCq2a1MvxehySCaXonE8od2PyaUNOsc29ZU+YdFBz+fpe/e4/Kkuj77V4fZr\nB5Qfj1jYTjP/nEkkEoSX5e4bA+KBzKmVAn6iMBj02bg1pvnAYXnuEpNQkMsuYGk6piuRM9PMXitg\nj1o4nsb26OivNOc/5EYjIIkTwsBHCBnPc0H6EKPq+5TLBYbDPhWzih84IASGrqEgIYSGY/t4YYAk\nEmQEiqqgKzq6oRKEPpAw6AzQjZPwaxTGRFGCJEmokkzoJsRISJJBnEj4gY9spZGjgEk3S+gds7o5\nYmL7TMYTOj0ZJwgpqiqa8JmfKnDv0QZC1ZFjhXRKUCoWsB0bATiOTbmUJ4lOPGtqziD0IiwzRd8Z\nYegmPdcj9iOiKMCZjFByFkJI5PMFRqMRXgK9bh9ZSCzMzmIPx1y5eJG1hzeZn6mzeOY07919xNxC\niQtn6jy+s0vrqMP6QYOkWOVf/G9vcvriMl/8wm+Qqxr85n/5G/yr/+X3OF67w3tvfo2pgsQ//i/+\nM37nd/5PPnL+Gq2jXbp7bfJnZxiOfCYDD6/vkqmkmUwCZFkmjkIyqQytwx5T9TpHgy6Rb9OzZNyj\n+0RHDq5rcH/12yjaPATHPN74PqXyAuOhzVSpQqvRIJB1Jl0JzcrxkcvPoiCTyaY56jWoVItsbq1h\nWVnS6RRCRJTKRXZ2tkllSowmY9KpNJNxnyiKKJazH27HBOPxhHQ6jW7oTEZtROTT63SYmp1j9fET\nzp27hG17TJVL7Oy0uXDxFbzJLqkQ+oM86WyR0XADXTtNrqCS1lNsrq2iZ9IklOn2XOQ4JqRNObHo\nDHrUpqYZj13mV6boD44wLYveYETW0Ikin4SYKLKRZAdZUxEJiNjC0CyiaMLS6Sxx4qKoEDoSE7+F\nljaJMQn9CYqioKkKbhyjyAm6ZhKRoMoyYRgjAYqikcgRYSKd+INJkCWB70cIWSaXzgIJGSuNjIIs\nxaRzOYIgIo4ERCGGYeL7J1mNMA6QFQVViUnihCgOIFGI4xgviBh4fzXm9f/X8/RzK1hZi5sfvMPh\nfo+v39jAcK9w+Zkpait5nv8xQbTU5sk3TEa7WQ5el5n5WA3Vy+M34fZ3DyhKCxSLLsHE4aDRRvYn\nTF3MM/9ClukLglygkBUxB7M+tU+Z7G153L13xLOKzmBksvxJiyi2CUoNgoyPvaZCb5ppa4mhUGmH\nAduPj5lOK1Sygtxckd7bE3bXhnhRlfS1PK4dkwtBG6rE6gTHt4lVBUmWGI8iFEMnHAiOghbFqkKg\numTyI7JZl63tO0RRhmLeonfUptl1yaUybNLmwE/Q7R4iyTG9Mk/3tfeZXriA2tdJjmQq09MkPRPD\nTZGOZ7h7cxdpJsWNm48Yb8Qszda4uXqTyrlpWhuzOItj5puXiVcVssWE514pIFdbfGbxDO/e8qmv\nxnS0Y0TZZ3fPZevehNJCxFRR59S8SvJZHaWTsP6mxtGNFjmty8Kcz5xsY6v7rM72yV7WuL26yitz\np8h7eTRN0A66tOMeUVqQ6AaN+11Mfwbl2GWtYbMrOiiqSiE7R/GCilQURAMDVViMun2siy51dNIp\nneETj4GcYhz5JP0AdFBDlaWlKm++tcXK4mmWFs9BEoFrEHo+QgOz1sEs9pgcjXj+6s+hS3Mkfpvu\nYZ+6tMIYyAiXiTpA0sEfaqhGmTn1KgesokoJT1ZdJh/0aJnbOK6PWc0xbLqsNbsE/oTz1+ZRhcDt\njUjiPumKhaGYKMLGJUYdgpsJcLWEwahBmgrlisyD19b45MtXWds+4jja4jN/7yJ2uEFlKuSoeUBt\nUcXxuli1IspIo7nhYYox2qkechhSmLUpLuk0J01qp+sMUWgd6xjCoqClkMMQI45QKw7WtMP81JDl\njytEM2sYqiAKEuoVQX06oZCTaH4w5sbrbfp7AYafJbCXkdQqhpshVSth52WWLs+wffSI3fcPfiR3\nhVr8PsaMhxAmRgbc/AZa9ApVaZ/rn5si/9LbZDMTBAOCZBWZFSDAZYTJIZcuZHn4rQQ3uc7OrstX\nfnuDSy8N+MiaoPhCmyd3FZzePD/7d/8x2U/tUSt2WD/4LmNjl623azSPD/jW7yu8uDnk0s+0uPHt\niAsvnyVV9smajxm7KqoU4kcyZqnKMNxj694Zzjy/ST7t8PHrT3Mv+z5f+WcTyod/h9pwl6nTEpnq\nIbrRZP50gsjOcu/eGC1VYHFqlkavhz2aZjTYZ255G5d9zGKDhZkVRjsqS7VrtNvvUikds3q3y/HO\nCpuNfT7zYooXztb5/X/+KtmpCodHY/K1Cl979XtcnX2BtHjAWB6wfpgwt/pxwuwO+XybWr3D4c4q\nlvJpWvs9dpu/RbF+xFRdY/dRmsS/Tsv1EBiocsx0JULSBxwlQ3rHJpGwcLwhmgDJWML1J8ieQU7V\n2b+7Ri5XBjJM2rDbWePiuWW2ezsokg6jKjmlwuBggytnlnl/9w51e5nz89f47uN3mHlmlm/98XeI\njABJBBiaShjISGqKMA6RFJ3tvRDbLRI6Q8ycSRLLJ280L+S42ScjFMREIaXOoaVyqAWNsQIjxyUj\nQhJHIa0aWJqM74a0nA+oV34RdT5BZI9IRxKj3Sx222Ru/gg3GDAZjDBTE+yxheON6fltet6Y8swp\nDtceIB9XmVnKshXvceqsoC/dJmXm8OQ3OTXzEqXUEve/NYsajwkyD9kZp4ilMuv9LpHjkE+NmF2Q\nqKVHJLFEJLWZiBaCWexkF71qE09KbL2TRR7kcCWFzJkhzS2X4dBgYckiZfpolsSgI7G+66Exjzq1\nQ+msij3pMEls6itw/7s90tp19ta2OWo2SeWrEOxQNC06D7s4G0Um932mF17gT37wTdKKBe1pzEoa\n03SpKSn8vkFhOuGFFyyWnvWI/Ous38vjvvXqX2nOfyihkYgEz/NJiIjjkEza+hA1K6OrKvbEx7Ky\nTEYuhpFClnWiSMYLYpIohjjCUiQc2ydQEiRZJpJcnMAniQQIjVy+xtgeYzs+QRAiSYLReITvu4Sh\nRIIgiQOi2MYwskz6Aa43Yv94D9c2CdwQy5SQ5RxHnRGJAHs8QdNM9nshsWpQM02eHOyStSo8fLxJ\npWzheTYLM6fo90fEUkSxVmTguOhpFdtxsBSNSRhiqhK2b6OoKUZeQkq3kGKbWDaQhIRv+6RNGV1R\nCQYtFqZP4TR3qMyeY2pxim9+7y1kPcOpuQJ3bj5mbXfI7ihh+tI13nzjNl7o84WP/yYhN3nqwj/k\nsy/+Antb9/i13/wNDh78HP/7f/VTjEe3+PTVFQ7W1jl7/SX29t7CtatolQhiF031GAyOyZWnGYxj\nLKWIEnUJcxpjyUMyU4w7AwoLl2iNFKKoRSw1mSusEKuCfidDqlTEHo/I5abY6/QpV+cQhs7Z01cY\nO6MT+47vMJz0mKnUsAcjlpfO4HouiQRCVmgcNCnlS7iujyLJjMcj1FgmcAIcNSFWFMxUDk1IhIGH\njEy5UOWw1WFuahHPh0qxSqfTYn5umZgM9UqeR+98lYsrl/ClPIk1pDR1HS04JLEU/EYRx24wVZ8n\nwiP2BswUqgy9EZFUxfZ9clmD0bCNlS9gjzvoRop+yyZfKhAEJ+JMVRSSODmxT2kSApkYn1hJOPvU\nDINeF0tVSOKIjGoQ+zKeF2BYIb4k0EyTMAhQJJXYDRCWgiop+J6Doib4SYSuyiekrTBEVhRCLyCS\nYtLp1AkiQQFZUlDQ8dyATLGEPfZAOcmMJL7AtW00WcEXMlHso8gSYeQiqQpCjfFiF6FmcPwx0o+I\nbutHRzx9VZCdzbO9o/M7v3VEvrdHOtG5MAupwoR+/AgpP8Y6zNJ5O+HwMIPq6ux0O4RJinOfmyU4\n6pDJpxiMbXa7DuGCyqTmoyUJqu3hmS5OeYx5ukptpYL9QcJbD1yWPz5DdTGFp24gFJ+okRAelzi+\nodF4zaY1Scg9VUS3Ba1bfXwRMpXKMdhIQ5yQPTNNVxxRyC8z5SVYjsp49xD1lExGTxEhoSQyjcMx\nubRMbxCh52NUJwB6xFoaczbgzOdLRK6x/6XsAAAgAElEQVTEuzfuU7ymU+0pSMUEGdBECUNP0Tk4\nJqunqRQK5PMqg7VdOp6KYYVMDiL2ey329tqkFYv+fcFC5qNYxVeYeXqD9TcTfud/usj/8K+gPR/x\nlPUxvvxfx3QO/h1rvVf5T/7hn7By7zaPzQH//isHPBm02bk9wbk8hXouoHN8iJybYC1egPk01dks\nG3cGpEomL1NB5pC6OObKMyraT6d54w8OeOPOMU4lR/3HJaSiiuP1CEYKhDLhEHAkQjdm4nmYqTyq\nsHjpE+eYOdVk0vKI/YDUtMBVwQ88pNaIpKnTX/W5026AajE/HVCeN8C1yKTKvHt7jfWNfU7NnyYc\nKugzGWJbwYsaSI5CLqNRTVukUhr1czpbqxL3b4+ZfvI0vWtDMqTQkn2y9JFEnuPjmNpsFcNpYYoQ\nt63QHPnsHG5QLGdZnJlBNiZMvAjXD5GJMELB8uUy5tUSR6rE1tZDLi3DXijInZGRJyGyDiUv5G/8\n7cuMb4yIRIPz159heGHM5z5lwuJ98Po4DgxCl0KmRqjrOKGGLhcYbXocNHr4bYlLT9U47Daw63uY\nRoKeheyKwvlzEvFIw5MgJSaE6SaVcy6FjzjMPu1jKoJxlJD1FepeyLSmkkz5jCodYkWmlrEYHQQQ\nhYyDEZ3+NjP2ED8aUzy9SJjP0v/Axsv9iGyW4S6SWCZMeghfYb6wwO0kxXB8jMj8Pla6h5ScB1KE\nscIgOASphy4kWrtb9PYignGeke9Tvvg3GPTW2Hn0hN7tDwjy+7jpa8yf+QfMfkJl5pl3cLjB88sS\nkbLM96J7jN7Os7mfov81je98f4rM1DXElXNsrX6VjAmKZZFO+QSBxNjuUTBg9caYFz9rcGo6RY8f\nUD4l+Mmf/xR338jQ2Fjm8kvzeBwwCWLGfhddnWZq4Srbh9/jqHWMpJgQCxSpTC/6JpIPsSwIZRs1\nF7O1ucPp53psHN5ldu4VPrhRRCWLXgtZ9/8Y80zA+p/3kMQC7UONbHqKkb2BlsxytnaN7f3b9EYe\nTz9TohX2uLh8luHRERPnG6TKIbI9h9d6lpZ4nTgZMd49z5UrNR49/IC5RZOJ0yGWDjCVMujTLF2O\n6bYbTLpNvGaJjNCZnj3NxtojxlGBQdPBD3pcunKWw0Gbgw1BhjnmjHlW3+tw8doFAh/e+JN36bRs\nEjnmZuMOb7W+z/7GgHq9xqDbwZJT9OwhqUwGd+wgqyaxCFFlha12AzWKSBs6hcTEMIr07IjmwKNt\n2xStOYrZAs1Bh4NGg7zw8aIRK4svcdw4wDIWOO7vMhloVBYvExlp/LHLuDdHo99hMrHYetTn4qFC\nJ2mSTnVIWfM0Wx7dlo4wPaqLTT566af4yu/u8d0/y7Bxw2Dhmk4w7FM63WY4slGAW++9g+KcYjn3\nHA/+9BbTZy/y5Nvvki4W8TWHlz6T5soLyxwOHhPmQXYTIq1FDMR06dsJ1RnBUy+fYb4qWL2ncev/\nsLn+5T6VeaDo0O1qDH2bjJrFz6s8eNfl8M6Yn/7FZRx5k5g5Mpg0Vyf0t218Z0A6naN3bLFzW2Jz\nY4tT0yn6+2k6bZM7j4+5aucI+gvkZzLElRzV0ybajs4FcwE/06F66QrzHxWsvPSETK7Fxefn8MJn\n4K3f/Y/O+Q8lNOIoQgiBJDSiOMZzfSAkTGISRQVZIowUDMM4sTbFoGgKQiTIikQSysSxj5BiJCEh\nS6AIGVVVCUWISBL6owFBEOD5zod2KYEkJ4Rx/GH7sSBKQnK5DIZusfFkB9/zGQ91nn1pnm57n+6R\nxvp6A8XQcV2HbCaNbffQVPA8hygMsbQsRJDPFpFkn1QqRat3zGToIVQFhMDULQI/QAVkWSYIA6L4\nJKQeJhFeGBFKCbKsEHgeoS/QVJmUkkEWERkjzcH+Fn4M08Uer76+j5EpkTEUvvLGKpHQcUYqv/gr\nv4otKSyfvc6v/Oo/Y/P4qzz81zliP41ayrH8zE+x1/Wpzhb5hS/+I4bH3+fNGzd58SfOceNxl1K0\ngO05DPsj+lafyWhCohnEvkcmY9FoHRDHEZIXYWYUEhViKcJ2RszMV9h82MPMFpg4PaQgwEqZmEaO\nSqVCLptmUT5FLMvImkFjd40giiiUCwhkSqUi48GA3qDPYfOYQrGAqmvoqko+nycOQyzdJJEShp6L\npqknAtIwCCXwIgchawgpRjUUksglk7XY329SqtZRFZmxa7Ozs8PpU1dptbqoWg7bj0lUqJVnEEpC\ntzUkZzpIakScRIRRH3c8QJIk+sMQydAxLZBVDSulIskCxZRwHIeMrn9Ib/KRNRlFFgiR4NoOqYKJ\n57goqornR6SyWRzbJl+skyQx7rhF7HtoKR09NrD95KTBPowwDJM4BkSCIikEUYimKqiyAUlEFAeo\nqoIsKwgSVFMmSQziKMFzHAwjTRyfkCrUtE6SJGRzJp73YfllFKGoCsSgyIJUOsV4NCaXy9EdjlBk\nGcNU2Wk0EULDCwY/7Dvgr3UyaZ9ktImu9jh7fYoXv2Ry//+SeLx5n/piCjvXZHL2McsfMzm7VOU7\n/22T7792TLlURF/OsfCZKTq5I9KViJxawQg6pNsxXApxqz5J7KE5LSLFZ2LIyAWZ8tw0H/xli0kv\nwtgucupeCXlJMO6MCIcy7Q2TbLjC/Nxp8plF7se3OO4esrOVUNIserFFZ9Ine6HCYbJPoz+imrWg\npXFmvoAXwag9JNIk/HiM4qgEPYiKaRQpi9u38UoJUSzh+EdIcY9afZrBJZmHr/dwWmXMUQZb5Di6\nPWDyGKQoTRT5fPk/vULS6EIuICFmYkjc3NphuKsRTEzyhsLWzV3GXYP81EeoLJ9HTM7wF9/8F7z6\nlz9PdUqm/cjE/4yF9bLGVDLDN8c3SZJ/Qnx5igu/Psf7Y4/mnkTzict3v97kSHF45W+ZXMHD5yFR\npUxpuUQcFMklglYjIJg+4nxSpJRqM/u8ivWuQ/tBm/UdG31HZzLUGToQeRD5CbqdIWip9Pd7aEqG\namoWQ0voP95GPR2hpiWaaOz3OhwUbLJegrInqAYlLj5XJj44wKyZyF5Mec4i7hn4xy6XZudoH/sc\nrR9iX61STlS6zWMCeUCHIx7dOmb63AqVWYnYSHP2xae48ZpP488UzP1Z6j9hcLR+AdnfJVvLcNw4\npBWO8c0+pqihhCbDVkLfESzVS1w5d4X9nSZvP9wloI1CjEGMYSVMnwuYm62xaj+hF4ZEMngiRMlA\nGVhcriI1PPaGe7z4t0vYZ9cppRqcTzS22SQHGCIhM5uj2UpwvRTymkUmWyTo9mg+GFLXDSZpj2iQ\noAcSUcpH0kcUKyky8yq0JDqOS6YcYS6AWx3St+C0ItBIyEqQPkrQw4Q4IxgOoXhBob0KWUvDSGUJ\nQovm/RFoBVKax2jjA/Jel3wocyG1xNbkR0OdctorHIweEiQxIsowSfoIzSebeplv/uGQX1p5Gb12\nQOQ8Yhz5TMIcWf00o3bMvbd8Xn+nSy96jrnZGufqO5z+WJZWb5Y4XOTJ7jOk/TSZuMXMyhQ9/wBP\n22SCx/UXv0Cutsr28IjDews8flTi/Ox1Pv8rsyxfX+PQNpHcWd6/1Sdt6mi6j5ak6G4LVGmE6dXY\n398hqgpiWyex7vD2zXs895nrjJ3XEYbNcOLSP1ymnCnzt37ZYHP7Es3WkEHvDK3W+3SaGQ4eLZM6\ntc5oKKFrLu3hhO0bMqlSnkZLp5Qt8dz189SmxzjuOugGvTCgXKpRM8/TGGzSGO1y1x3yT3797/OF\nX/47/Ddf/LukqjUc1+Ps4jJ/+pWvMVU3+Ojz59jZDwjLUzw5XKfVeAVF7ZCp7WDHNqlCkziRcIY6\nevgCtVQd19xkMugx2q8g+St4k10Om3dwBh2GtoqSKRE7feLApnl8gBYn+MEQSzMJXYmqVePxrcdk\nUxKoNnJOQSoU+Pp7NzgwHMZyn+bYZbkwS7fVoWKZdMdDLCNDImTiOGYUjJElgaJZBN4YKxLkrQqO\npuDGMjkrR6W8xMgJ0QjQ5CxpT6ZayuMPSkwGNrolMVV5iqhWJF0psdddQ24XaTcLzE5fxtA/4GDv\nNg/fuEjtmQ8IJJtEs+lMBnQ3VU5dlDBMj170AVZBQqJELjNL62CX995LMe/aLJ4xUc0OF64WuHDl\nNFsf3OToT9d4sLHI6cuf5dKL7/PKZ8qUKnlGyQ7d2OHJY5XFWZ3E84g8FS92KBdSVFJZZmee8Pjm\niK1uGulOiWjtx9nsfpPKXIQdZYlEgC+5gMlcXeLmH3f5/h9aLD9nYS3uo6Gy/a7Oxy78El+9/wbm\nlMxgPGb9PhjGZe78xT3mZ1YIgypXr11kb+8hyzM5cqogpxqU+hEzKxWuvVjGz8wwNJbw5Lu4wkWX\nN8itRMx9sgH/9D8+5z8c3jZJ8HwXCUGSJMiqDgJELJASgWM7KMIiICRJJOIkQkg6J5ipBCElyIpA\nkk+oO8QCOEFyxlFMGEakLAPXlXBsF9sZEHgxjusQRRAmgiQOT6wLExvbFgg54crV52mN97l1c43W\nwTFLyxXq8xkO913mZ+bY3tni1Mop1rc3ma7NMBqOCD2biIB8toDtemSyJplsDtvdo1Qq0u32cCYj\nXMdDVQ0szaDrDjEUCUnIJJGMG0WM3ZByXiOnCSQnQU6kk4xBGOIFAalMivEkIpYk2r5E0nPJaIL+\nRCGwm7z00grFTJ+9xwGjUHD+qs3yL/8D5EmXjHqKhnmP8lSJ+XqBqHlEZ/CY0tR1Ljwr0d3ZZmVp\nCreXozvaJZYkAt8nCDx8P0JT+5QrFXLlAm7HI/BsEsfFNDOESYgROrS7EfNnzvHogzukzTxCHSP1\nHTR/iDuc0B1KjO0J2UKe/simUp0l8hyUJMeg36PXbjIcDJhbWOHC5aeRFAiDgOGgj6ro2E6ApSsk\nskCWZWRFgQQ8zyPRVAzTIkAjiX3i5ARz7Lo+EhHN4wYvvfIy/+Gb32B56Sxje0zOyFOtZXDDhHzN\n5MH2MZfPXkOvzOAFOUajIpamIksJhqITxxGmaaKkYtSUShSFxHFITEzKkFBUBU1NmLgOuiFDnBD6\nJ6SzdC6NO5xg5DKEYYJq6gztMYX0NEniQuKjGRZyOgWhh+f4aApIsk4sJIQkiMOQwPdRDQOiiCQR\nwIlgF5KMpChIUYQi6ydCNkxQNIGqZUmEigwnW7wkYTKZYKgSii4hQkESJ4gwQI5lJC1B0wQp6yQ0\nXsxbBIFLKiVjpVSGQwc/GP3wL4G/xvGGPnbkoE/rPDno025HVOvneXDrgMgP+PS0RvpSh2WpyFbc\nZna+wre/3aJYqHPpo/MoT2+yMqtQEy0GyQHVn+njrilstw+Y8XP4akArPaElBOu9EK2jY4Umk0mM\nYyQc93We3NLQj1M0PYtzM1PsrbZpPGlxNrPEy5+vcTH3N/nea69z+9Uh23GAJkUERkDWjNAnGp+Y\n/zTbr3U597KOdukI39vHmAQYC2k2bj2koBWxpJig7VJZWUSIAe21NbR0GX/SwyrFZPN9MtUBU+cl\nVtePmL+5iKotobckwp0M6cCgbiQspi3ado/IjdkddVCUgHcf7TA/s0zjeIdrn3qReNPjinIKpZsw\nfjKksvg8v/j5XyOTkVmUAnZ7T5h6KkM2eRrCDa59rMC/O/x95gsVTi2/zNX/OcPw30zY//cCv1Fi\n+GjCkzuC+GqPtDjN5z57lR8cJrz/jW0ajsad33NY/NV5BtUQRR5jVo5YfDpm64nLxmEP7+0cteU5\nVjds7CBGDRWCdoweOPhxhLGYIRJDrl1fwV5/wK3XG8hal4ZxROppqJ0vUdfmaJZtNu5N6PkRM8/k\ncbQejH1y7ofUurRBreRwvGnjexqjQEY1BMnFNsP2EQoSSZBQLwoKlV2GlsPTn36eQKpw/0/3eW7l\nRfyHGZ58fYv8qZDWioeU3aHrTXCSCF1TyKgK3QNBMV9n+exFlEDCzBsszOfoPm7R2NmhdKnGpZ/T\nCKYGDMUmM4bJ938wYv4cJClIJgLVAjVKcefoCcbHdYorBkFyxFIiMUeHPBA3EsS0ynjWxrZUxGMZ\nZWzh7EQERxpmPMNy5RWy7iGtRzeJizFTV/NEqoksy2jTKaxaht3v7ZFZEFz/hTM0lIQtqcWOSFiK\nBcU4hcOYpCCjEuMhcEcT5ssZZj4xzXh7nrVHOhuix056n3vBe1yNzyIfj7AGEStemelrDrD6//td\ncfvP+9gPZURGYM5XKaiXMfINjjoeU2IZ4WToT7awJ2NAx8hpxIzIVXI895kJ+3s23tqAGaHz9FWd\nqz8JB+ERqakBs7d1tt5d4+533+f//u0S1784wK70yBRTjNRVasuH/PyvS/zBP31A4tSRC/e4+rEW\nXuZdTpea6MLjsGuz+l5Mc92gf6QxlX6FzkGL3/4fV/noj8+TPzeh34mwhzJarHH3nSdMX4TmKCGO\nU5gGxN4h8WSehaUW1aVDxv05br4jMV38caJwn7R1jJB01h42sUcr/NhPW+RqIQ4rBF7M7IU3SFJ3\nYHyKRw9TRIM+5+ZmOVrroAiBToGqeY3++h7TUcDZ5U/wZLXP8aHH7vohc7UaK08lbDVvMPRSJCLi\n+GDI9OJZQs8jQuG4v4+Vd0jUmGI9h+9E9P1bILvI0hkKlRqHaz0UYTHua0wGx5TKRY56B2iKQBYu\n/W6EaWZRrRJaXGF/f4QZ5dAzJgNvwpFjY0cyp6ZrBK0x4/EhiRKDLHHY2aaSrzK2baYzNXoTDzNt\nYdtjLNPE82x0RQfPxsqYOP4IVUgoegrhQbfTREgpinoRESWUU2l6wwNG4yfMzX+aqekyqWxId7hP\neXqO9Nku4+E+55fPYo9izlgfp23ruG2X7fW/ZOEcDHpHkOTpHMPSUobB4ICWe5+4IJE7a5JS7vKl\nXwo5nEzwbIPuwOPCsqBk5BkGG5yp7dN24Ju/m+PS8zk+8hNt5KzgKD5GxDpz1SLhuEu/HeEMZHKZ\nMkb2mJRmEBsT3MihdMZg6cUx+/sjHj3SyVy1cT2JdquNiEGSQ1JSHzkQnD9vsHG/QRRPoz5MMWiO\n2Lxj80h6HU9q0OnEpFKLpLQclqKRmqqSMhZRCw8InJBTM2cJekfM1wI+9vIix84xC88fMH1tG39c\nJNe9h24VMYSHmzRw2cFPxX+lOf+hhEYY+oBAliTiKMZxXYRIUCUIhEzoe3iKgiQphIGHlNYIpABF\nlUGWSATIqkCLVGSSD0UKkMREvk/oBUzGLnGUEEUBAojjk61GGCUEfgAiwVBVPC8mCEZUazW2Dx6w\ntt5D1RRefOka5eIMb7xzk1RO4Ix8purTtDs9ZuvzVMpFQtfnqctZ8rkavf6Yh6sd8tkizWaT5eV5\n1tcfsrS4wmAwQVV0hhPnhD7knggkXdXxJEEUJXTtCRUzhRKHRMGHHSAxhJJAhB6uMKiagoOJIIk8\n6rMLvHnjPU4Vckzl62QGBqXA5PMvP8Pvfe1VGkdlqimL7rHL1vG3+cRPfplPf3IWsTfmL//4D7jy\n/LNglvFSBqt3fwvdSDOMfOIgxHEnOI6N/SEZLNRshnIP13eJZRkRSyh+AqpPJCKEN6JWrOBFIVeu\nXOWDW7cYtXrERGiWQWKk8eIIrZRFz2aplGVUzwdhsL22QSIkTp87z+lTp5EUi7ETUK+WGYZ9RCIR\n+xEp3cL3xif0K00ljGISSWBoKgPHJxYRTuihqRJxpCALHwEIOSFjpXj0aBVFlhkOBzhOTP3sFD3H\nxzQNdlpbJIGJ7Q7wxzGZoo+ZK2AZAnvQQBDhBzbDUYjsa2QUF8uyPgybJ0RRjGmdZDIEIERCFPnE\ncYQsy4xHYzRNZtDro2oaki5RSOcAcVJemSTIskoS+yRJgmZoIGQ8xyUWEq4doesqWi4HcYimagDE\nUYCqaZCESEgnyFsZkkgQxCGqrJ18K+mMx2PiOCKbzaDqOpAQ+iEyCZJxsnkJZBcjgjAIsTImg4lD\nOpVmNPIAiamZLFEc0x3/cP8V/rpn9+EEkfURrQnNocG8MY2bW6BZarDebvF5eYrZdJcpHNy6yqCa\nYm5GRTYyKFh4kc0sCRq7GMScqwdItQyH345obTl0z8RYGejsJuzdhmTLxXviIJuCYdDl0abH/FyO\ngpQBscLjvs+977X57Ocu8tLnapDZIOyY9DoOiAzV83MgEvxEYkyE4WpobcHCXI8v/Xdz3Ov+GcVy\nyNn5WRZn5hn+ywn4McOuxu6BjXzPxzATzGwaT4kpzcikCwm+GGMtC57+wiI79/vc+EHETLbKTLZO\n46hPLEvkagmT0Rqe3+ZgbHM0GTJsdbGdmFJB5/zPLvFrf/8S/+F7Hgc3HSbifRaeyjL3zCHPfinL\nrXvfAGWdf/Tfz/NzSy8Aj2lK30Fys2x+vcfDcZef/o1DPjJzincuPiHzekBjvcWn88t8aqmOGYyw\nE7D1R9iBRiD7jNdk3v09G/3pHK25HabrEZPBmMpMGbmo8M7bPc5LOrFfZrS/iK+GHHQGjA4OUc0e\n1VIOPaWx12yz9kf3SPse1apLvS6hTpvMUqVsp1AljVRsksQuG5sNKs+V8KMQVRsS+i56VgE5i6rF\nKElEIqkMOx7uDRdrxUcJVMZ2wtF+QLbkM5E3sQoj+m7I3Etp7nx/xNrjFr6n8vYfHvO5v1ekvz1E\nLTpoROy3BHQiatoScaSzvXXE3v46a+0Rixd0zl3JUlmc4Z03mySn2zh10BmgJx2KQiMdQeOPZKxU\nRH1mjsLFOVrRiGa8x9XlOTSG1FAIvQa64nFWUTkY+yToYI+5VMoxvCpz/Bcjtt8bMT9zgcaDPrde\n26egjRiMC1T1PJqRZn3/kHCiUJkx8W2JuJLgqYJhAJJWRxURg3aXcVknErPE+R66HBIJl5mcTiab\nphVHjA8GTC0YPHwUkSlVSUU9Gvoxd3YtznZsnvPPEaT2MM3Gj+Su+O6fTtgonWboNrn4ssnyUhVh\njOnaA8aeze5hj8riEDUVIY/BnTTJWAUUI0AtHbD0rMPqd464+8FtrLMyz8yuMKUcY7JL6aVZ6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e518sYUznpFevUZ5co3TyAMefI0s6qhkRVSKy1CH73klahw2e3Nij/1M+3udhsSXoqXPUQhA9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ssQUglNHTI8wW7oktOSBU9nHpNUIshikgKIJhgrJuvpEjs7N7l9dRuzXEbMZzzzo+f51GMr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9aHNhbgY7fxYt9dkfH6FETKiNEVaINS3Zemcf33GYWnZwiBBCMU7AdkG6baypIn4aY+RD\nWqcDHK+E5zSoF9fpXX+Avilp1EY0nA5BkEPMFclXK1z9kyEP9/pMaTZpc0R51UVOe4ROSGyEHN/v\nMUwN7v8g5OJqgfScQtRcysJjizaJKRhrDU45Qh8ZuFHKycFdhtMVFhbP8Pb7XcpF6N0/ZOZnyjz/\ndMy29VUOhlf44n97maI2w93/8UOufecaPT3PwuHj5LjEqJcyXu9xuXCGnfGI5x9v8KWnn+dbf/wT\npp6ocdgecBAEzMQeB2+PiVshIhqw8GidgT/GtGxaW4Kdu23Gc5Iv/ceLGMsAGhgJI2OPYi9g3fUY\n3Onz5rciSq2E+4GCPOzsKKIr7+Fsr/Fp+yKfyr/Ek5+/QLoScu7iJYzMpHb+AmpZwcOMO//yOxzN\n99n8xDmazj7VGw84ev0Gd5tXON3exioOcfI6WWUiNjvmJgiY/dkS00ZEdLfHwoOU+foKSSxID3Sk\nL8jhInuKvOPgpwLPcxh2U2oVh+woxFBVttMh57+0xFe/8n9zcD7CcA85++gy/v19ltZNrt7doZ8b\n8pz/i6DHdKaPMU6fYl08ztie4/7++xjxMp93L9FehSvNkI25TR7cqRGdFwR/8yI/mftjXv6teWQ8\n5mmxinkUco51dn9yh/XXFqCYcL6q040H+L0RsQVu0UHzQz593uLK9ggZD9l4us7uhyNww0kfcQD9\n04TM1XFqOYJbNtlAY75mQ0HQSU+ZiQWDfXBnCmT+iGo/YHHJwsyPaJ3c4/32Hksvz2Jair0bu8SH\nDjPTVZSV0Wnvsv5YBbsREbR3mH/Uo7xwSrySg8GAzd+yeP13IxbPzPFvvv9tfvtvreJaOu60xdgd\nsvW9v/wiOEDrRHHwsED+rI9ywXFckkQyaJkow8Otg1tKKVXaWA74x9s89/lZ7l0Hvz3i4UeSH/6x\nZPYgofKMh1Hs05itkH/GYm32Lkf3Ez7ai7h3TTFdn2b95TZJ6FOrFXnsC3NkRwu8+e0rhNqQ3nGZ\nW7uSol4nJwVqusM7+xr2H66z/daf8Sv/wym/+R85/KMbHkno8vbtK5yfXWP7j7b5zecuYQw+YOF8\nns5PxrSOqgSNNqaQnNtwOd68DicXiUQR4ZSJ+316D3oMhGRpySDJtxEDj9OrK9TkMtlJnrXCJnc/\nbOLv5YhoYxS7nEY3WVo9g1mYJVdf4dyTj9DlgLbfp3NDUC+8jBXu8M1/beBkAispcPvaR9Rn91g8\nu0FjMSWs7GCWDlme+wYDDXrfPoscFVlaa3D13o8Rzohxeo/TBzM0ygVUMiSNCmysfYZucAPTM/Hl\nCeOkihy3sXIJy3MFhP59ktgDLSPVPmJq2sHQTZST4kwlGLUWunFKlh2i1B7KNPEqKc8869A63CKL\nDDRK1KtL6KaPjAXJuIqdVjFaeY67u1g5hVUd4rYD+kcx3/39a3z6F59hHM0Qj110w2C5sUi1arFz\nN2Xs1/nh1464+j3Bz37qKQLjXfaO97n+4evcf1Chc/Qclx79JYZxzKXlBvdO/hdGD6Awo0jDJrV8\nke6Jz7134fD6IbkpSRCfoo/yuP4aN755hMjX+SBn8cSvVOh2TNqnJ7huxtJajYPbMb29yyThHQZB\nF9tU6JFFkvgcnwiOjYhyzUAaRYr5GmW3il7oMUr/lF/+61PMnRXkC3mUJXHNNqYpqBaW0NrH9Ac9\n5FixWq8yUz5GcUp5dZozn6xz967gdKAjZcLO/Q5JtYe5mFG3D2nMKM4/5kNnwFE0Yu/tC+wv56lt\nHmFX7tFPPqTXV4x2nmRWewnTUvjdCl///fdZ2Jwhv96huAhaLcEzy0DvL3zOfzphX6oI4gnzX0pB\nkk2Qt5nSSROBilNQAiFMlAZBqDEcJlimxCpDGEl0UxGFIY7lEMcK19GRcoK8lTLFFAWk1kEmBdDG\naLoGqYcuItBd0iybZPY10D72SVim9THqE4RQGLpBqCRIDSEEoKFUilIWAg2ldKSURPEERasbCsOY\naAQ1DWzHJI7Bdk2UivGDEeWpAisrq2RZTPPklEatQqVawtQ0UhXR7Ya4uTxuziBLh1QqS9zy2nzn\n/dv4ykaODQ46Y2yhEzV9vvnGPQrFMge9LRbzs8RjDc8GEeXojNs4jkHm2OiGYDj0KVcshj2fSiGH\noYfodLFUjnIuT9E+j+fVeO/aLo+tNshlPnMzDeJMI1e20NOEucY8n33hSTzdY3Z6kXqpilksUqxN\ns7BwnjCShN029sAnYkQn6EDUoWIE9JqHdLtNdN2gnbVA1yjkS+Rdh/6oi2VBqVym1xtjYZJ3PTrt\nNpYp0AyTaDxCCYXvj9Etm9ZpB103iJMU07DJVEwURZScGjO1GSqWi2/GLM3NopSakJtkhmYIZBYj\ndBupFGfWa9TLK6Sxz3CwR604T5olCE0QJjGWXcC0dTIVIrBIVMxh8BZ7/R9SbW5S27rEI5vP481/\njdLCu6hwCaVCDGliGqso0SGJDdy8RSYzgjj6GHAg0TUTGSs0NcHUuqYNmYYmTITUcXUdQxnIRGLa\nDlkWkKURuq0jlUCaMZKJcyVJk4nBGw2ZSGSmIVMDKTPQFDJLsE2DcJximCaGBrow0LUJQhk9w5Em\niRaRIECTaJbEMAROJJDCApHihH/xiPP/j8tBx2+N8R636d1uYdRChmiMfY1xq8yGU6VJh8olxVHU\nx9yusP0NMF5bYKS/g/ISRpHCcfJoykIEOvl+Ce1UTGAKrSGu4ZD2Ikb2AC0T6JbJ0sIygbRRdsJH\nV/uUz+Uo+qesbZYodydOn9agi1eu4iRTREc2vnTpH4eoLGXhnMnCKw0yI+b0J23uXmty3FQslgs4\nYpquIWhyQEsVmKnP4ytBLFocjTXid6F5b8D0TMCDc++iv30Vc3WRZNzC+PRNfubTDoPA4p2dh4zn\nYtZKyzzx1wec/sEQ88jEPB2SqQ7//O/+C1773Qbbxk3ePb7F4nqZV56/wLe+8xOijkVOm0FPIlK7\nQDBIWHWe48Z2l8eemeXgwTUaUytcfHKGm7da3PvukO2NBOOFDDnfJbMlvazNz//2FK//yy4fvq3x\n7e8fY16HR79QR6mMx8plGp/cpNE4yzNzT7O6uEzpf1okdq9jiT04ClEzx8CQqO1zp7FNcarI9vBd\n3j/sMHunxu3vfZ+UDr4W4P2cQVyLGOoxSjRJhyZ516VhZrR5l9401H5VY7GwwN0/7aKEjTZQLK7M\nc7h/RPskQTNtXK2ObsYUnSKCGjPTKzwz+zg3rne5duMuK0/kOfWH4BySqyc0agt8bzTiH/9XTX7+\nC/8bz8aXmP7FDe58OCJUMXW/wtOLL7I7uMvVZJcnskWmFxv862gHhcFT1TlO/2yDO8evkP9xAWv5\nmOvtLs3vSexBk8pinZeeeoziF2bpR9/AGEfErZByZZpAppj9kCyFzABzSrCeW+Rd7wjdr9K818Gv\nGriDHPFY4EiHdmKggoyTpoXxTov1501GbYkseqSjAuGeT74yJmUHr6K4/v4RuQsO659e4Mr33kRc\nkDz3i1PMySq33jyhf2fA3MwChUbAzFMBy42UdOeEkunSrh/j/EIOQxaIPpji+r9t8eyVHudeyJHX\npjga+IS7fzWEutNOyM13OsxeKJJvpOjxPFFywGFnjOea5KYchDFiHPaxjAKGX6VW12ic7XKS6rxz\nd0AQrnLt9j1+Zc4lt6azN+4ws2ESaA8wl+/x+Ks5PvzaAlff8In0hOpmi8a6hnD6mKvf4LkvxTy8\nH7C7bVEVnyIMQ5YdnTc7Xe4NOyyrJ2jcOEPP78H0A174QsSX/9kbOIszXN8d8NoTX+T+dw/ZUDU6\nwQE5zSPLjUF6dI81pmZt5h8ZELY9tt50Ue2IwxtT5A5isF1O7tXoHiXkxo+inV5mdGuTwq7PsONT\nHIVMmft0hU+xsMlzL7+MWRkzu9nGm22yeOmP8GZ13r3yAl3nOR6+/wN+9Ee/R756kbujPeYaGyxW\nfo729ojRVUntE0dUF95h5SmHYHzErDliZ3se83SOD64+IDXncIsRx8cHzNYl/f42lm5z8fHzkGjs\nHLzOI7lZcub5yXlZjrDSgFo5xcsdMeyPKDtL5NIyUWSQGQae6zDTGIETYOUhCzqMU5+B9BkGA2J3\nEXvW4HQwwB52MPIGuswT9h3QQaSzaOYYPb9HasTMV28Qth3e+pP7XP+TDi9c+jR+4R2qiwcUSotE\n2o+o5c6gWS5bt/sM/Dz56jN85Zt7xN5VrJLP8uxl5uam+b78ER89bGLm1lnf3GD6kVVGfETOqSBU\nl3HzCb77lWvs3JjnwhMBZy5lfPn/OiHtZdw/PiJXydFNTvjg3TWM8K+RLl0nyZ1w5rzDadqitDyL\nVjlCK0nsnItmGRz1emjKZK+VUq0LrBEU8zHKGtC4oLByxyT6kKc+L6gUR9giR1uFZPioLMLUHrJS\nLNAzpzkZN/E8ieA+UMTwdM48PsPsTw45alXZ33e5/m5M6gR4zQCxdhW3kadyocZGVkTJWQ7f/BI/\n+qPf4fFPm0w/UyfRuiRtHTcXU1lP6CYm/U5Ievsl1DFMRW9hzp3SOcrRGf379T5/qoOGVJAkGaAB\nGWGUoiuJEhOZmZQfc/11HaVDlOiMY4nlZ+RdG6kl2IZCQ8ezHZIkxrZsZCYxDBBKQ5gWSlqTwrkm\nQE2IU7pmo+smKg0QIvuYIKUhlcIUOrr+sXMDBSpDZAKVpRhKEanJl6FpE3SprmuoTE1KwIaGzFLC\nMERLJbpQExGfkaEbgnzRQ6qAOEyo113IHEo5hyzNOG01cXM2ujCoFGtMVTU0TdJsjcm7Lq+8eo65\nmSJXbu7xwd1jrt+UXAOGAczOzvGbv/UMRhTy3T+4QqGyxmDUwlAWuDpJoogsgRamPNzdZcUwKHoR\nQjPIsjo2dQxMkqQHtLm8vMTuxgLj9jH5ZMR0bp7WMMayimw+8hhlr0DBdgmGQ6p5h0wOqKZnyEYB\n+4fXCccDSppF2h0RJQFu1aN7ekCu5NIJ+8RmxrA/IrUzbMshigLsOMA2QKJxfNRiemaGYW+IbRgU\n8nna7SZewQUK9EdDNMMGwyKfz5PIDF0q/GBMnEl0I0e9WCPyfTTH5HQ05Mn1DUZpRN5wUEKRJSm6\nOfG3CDLe/dEAZX2EwSr1fA4pYqRQjOMIqQSGCHF1EzQfmXbRRY00NUFkHCbv0B5c4f6PPWarj3Pu\nzH/JzPr3yJW3iFOFYR5iiQoZMWkqQYCBhil0lARDNz52vFiQSURikkXZxLUhxOQQHCpimaFsge3a\nJEmCrmvIOEVqGnEaYFkOUulIJREaZJFAU5I0SABJ5IfkPJvBICTv5ej3B+S8PGEYoyPQ9RQNnVCk\nmJpA6jqm5ZDpGmQGlq0RJWDqCkP81WweCrqNVS5zddhhqphQqRYY7SiGWwnmiUHdKmG3OzTOT00k\nZn6EupGyPJPn5nsJs69JqtMCc8rhSFMc7ILrGRRHFTLTIu4fIIWBaRqEsUP/MORgK8J18wxHMXbR\nY38nYvrRHLphoRmScThGEzksqWNIAy/O4WQ5Ul+SJAopM0quwcySpO5qfOR79G+bHFkxJyP4yY0h\nM0+aDHSDBTTy0kJGRY4qp9y80qK/J6hnKa4bEBTeQ1s7ZDv7Xf7rf/RZnM2v0I0H6F6eS6s5Bu4+\nu60t1p5VfM4d0t5b4e1/e0StCbfeuccr786we+mAe/3bPP/s87x9/wq1s0X230rwBxqza9P4o4y9\n9pjFjUU6Jw53VgRZXVJohFglxWEYUCnk+e4Vn7NzBbZGx7jLPkuLgqc/u8bM1BzvfdPgW1/fohW1\nGB/YpMOEVz73KepeHTssU6pkFEt94p37hJtvEUgf7BJRyyIeOIQfOZyfqnGyF3Nzu0WoBpzED9m/\n/ZCil7D66hSF5T5RPqWHxE0c7EhHL4ywUsUo22etvM5xzich4cg7xZiZY256iRxlCu48HbPN/vEp\nspVhJGOM2EPU83wU73LxwidpnxxQCuAHv3udy39fwxMZJ1af5KHg0Q3JZx7VWX/MQhVmqGcb1MxV\n2rk6D7stposFlnKr+P0x42HCRtkiOTLpej7X5IcYkc4j/BrXv/0V6oWzfHf8VWqyxNu5fS6MyvzG\nmTUQKT2zzaiYkbQVWWqQUzahHLIXSHRHEA4ku/KUdGyTl0UkeZxdFzvziI9jRMej4Fmk/oCkp+Pf\nEhxclox1MLyEUjKgiyDOaYyyExwU8X2Yq08zHl1n/rmYC0/lqacJvR89xLMMLA16eyH+9Ak/+0IJ\nkz7KMBkdajSmbQZGn9Wf19m/do/F9Sq3f3Kd2ccH6Lkx1WmJ6/+VLBUYuoUYXOTwXot9tcP8wj6u\nkaE5inE8Yv8wRHiCoi2w9xze+qcxq8sZcwWX20ae6cVp9ntQyNZo3fJxiwe4izqu1sZPTzGLQN4k\nTBOyJI8en2Op/gitO99HzadUSzE9P2bzRRfR67H3w6vMOTXeOB0x99qL6P2Mu3/+Q/RpH1+Ak3e5\n8HzE35pd5U//j5h66Ty39u6iZwaH9wSf/W/Os2ts4VgahsooWuDvjbm4meH4t2h9NGB8kmPrLZ+y\n8yyV0nn6QsNxTDbnzzFduow8CBCHP6buhMw0akSRy/q5OcLKIWdejRh6N5g5o6NsH6EnXLuyy1R1\nk9uDP+P6/g/ZqG8ibYvV+mU6/kO2u8fMejUWVyQbm1NMnb3MafQVyqUWS2cFR0//iLtfsfDya6zM\nL1KZep73sm+xs3eF6WmL1fl5anWXnDnG3WtSboBZ6VA25kkGLo9c3KRcyEiCNr3RLl5hgZAxJ0dD\nqrMzuPkcw+EAUxwQDhxQI+IQNFlA1/NUZufJMpd+v4ltBZRzlxkmPqHfYxS1IBmTczKm5kp45kOa\nOwOWVx4jeUEyW1xh+/R9gv6IYeKgtprkpntMLx0xDA949JM5zp07ww++rPHjN77JL/6NS5y5qGgs\nLdO6pXj3xwV27jk49jJZqmOnnyPMBKP4Lo4He9ttWjdeYePsbT79S1tMrVT52p+NCHrzJP4DPvGo\nwljW+OjwdT5q/phw/0Wm8n+bnr/LKPpzpuvzTK9sY2gax/d9SvNDkmjSoUyTlDQsYNYdUtUmjo/R\nysfkljxkPIvmKjqqhS1O6QeSnFXEM3Q0dCwjT7kY0RoZ9PwhniVR8SyaraFXDlj/ZISvOty7ssG7\nrx9z8lDn7Kf2sSo9bKOL7SXUzrgkP+xjOL/E9dc3mZrbRZ/NUz13Bn1myOrnEwZP3uIH34Xbt0+o\n5z9LrRyyubLK8qbHsL2P+e/ZBv+pOhqu56Hp+sSHgZgUWZOMLEnJlEaWZUgFiElcSeg2pqmwzARL\nU9iWjWkIhGZgWTmUTHEdkySJENqkW6FrJjKz0MzR5HWQkGgiBeVONmMIhA5C6Oj6JOsuVIZh6ig1\n2UhFUYiS6YTkpCRKJigkuqZjuy6W7eIWcpiWhuXYgMC2JzQsSUYUhsDkTXqSpNiGSRAlTBU9wmhE\nLm+Sy3vkCx5ZlqDrNp7nEEZdLMsi59RAKQxjRL6a59L6NOvLc2iuIFEBj56f52/+2kt4epPF+QpR\nFHDz5i6V0iyJ6CKVTpplpHGGlApdhywLKJfmiBIDRIrSA1zPRKUSz54iHZ8wvbBMPwjJTGsydSiV\n8ErgeiGaCnBNHVvoyCjDc3JMlQoEowMKlkJPJf7Qp+M3sR2Jf3qIZsCD1g7bvSb9NCCJQ4RpMz+/\njGGaJJlPJhW67qAbDoYJlm7j2A5REOLmXYJxRKYUnf6IUqXKKIoRusY4GKFUOvk9LQfPLrM6vUre\ntkiCUwpr55hZ20QKHV1MDpxKKISwEEKghMZgaPP697/FydFdSvYKETEImwyJppmoTKKyGE2HTDgE\nWUJs9AnVIRmKLJtF2RkPT3Z5sHeN051NXGOTci0il4uw9QTDstAMBSLFtQqTiQomSZxh42JhIjMd\nlUos00FXGroyUTEYwkJXOjLTEEowHgbowiCJJ//zcJygC4M0TkjDDBBEQQTKIBpHSClIU5DKIInU\nZCoTpxiGRZaBlCkTZ7lEZkyKHkIjUQlSgiY1kiBCyYmwL0p07h924C85d/3Zl+eYv5jjVjBg6OUZ\n2RDslGBnGutBnfd+dIiX9yis6hweHTIaHjF80EcJE3NxgLsgKNQ9kmaO4ZYgOnI5vqnIgjzDkY5t\nFfBbGXroMjw12flAoimP5flz9AYxMrEYjgNmGg75eofVKQ1XixmqmLhoc3oU4jYrzMRLWFmNw+MR\nWejzwtM16isZRdskjDMGDzx2bik6o4jBsEerd0TvUpMFTaNmaJhizEDrYs/A8rJJ5rsM9yOiFDYe\nqeOZEZ/7osStfojU7lEQHn15ypzh0h8f4BZGaLMB82cFsZin7kzx+x+8wVf/6B2++s8+BAZMzUt2\n+9uUzy9y570xJZYojgroxxYizHOw26E4XyLqN6me0XGmTSLf4Ma7Q6oz8wz7KW1H4/Zpj9GCZMOr\n8Eh5gfKKRutAZxDYbKxfxNVy9G7A43MXqDBLThkY9pj6KCLaeoCzOiYgRQwM+jfH9P50iPF+kbVw\nlYP3mtx5/wZ2TtENmhw83KET7vDEz5eofi4mskJ6/YRyMsNYixi5PfISBsEQ0ykwlkNMK8fc+WVE\nz2R0KDn6YMD4VFL3Fujei8mlc0wlS/R2dX71i/8Z08vPcbzd5OSdGxyc/pjiMwN+6T99kVTcwU4l\nURhQmjU4bcYgEhr2OqtTr7H79SrBYZkZMcvctETIU3zZoWxP44QunVYP14zZKl4lSbvMlZeQQ8FC\n9QkGaUK58hi3uif4jsG9H21x0rqB2tinVFSUZUKpbFJXFg/3u2iaS+THPHdujt27EaMHLtXoHDPG\nGrtbIXFcZ3RsYsk6cdcgbqUU8ciCBL0aIRsJYawRNGOEMLDLGbu3JOq2RefPM87N5XH1lMufcika\nMSUbcqbN8NCm1zJpPQhxZgwuPVNGMGRW2Az8DjOVDEXGqYw4et2vmQAAIABJREFU+fOMM+V5/MEW\nxvQx8XSX1IbeEXzry/ylrxVrdYu4G5CbyrDLGRFjLNPCH0u6HQVJBcd26Bxl3Plxi9vfVBjDGUat\nDZJgGkgIkh7jkeB4v0usw9FoiCFNBC6D05T9D0Lu33CoOiaXPgELG6foWY5rX+vR33FxizpzZ6tI\np8mtW9fQVZm9wxb1sk3cHFBxWpx5KWDpZzT2D1tYpqK+5LO5YfHO9VPi0EM/aaLFY0rrGSIn6e+W\nqVqC7XfGHLw/i22tMOw1ONqtk4wKuFqdKeMieVmhbJ9lprZAfS7AsHTcsIupeoyCBFFZRF6Yof6Y\nYF99h+Xn7vH4i00O9z7k5o9OMLb/Gt/+531OrhusLz/JjH2RK7stht4p3aFDMD6kqE2jxWfxKpJw\nNOCgfZPFjTNgPokpLA6Or+APYW9nwOrKoyiVcmfrPRozc+S9Cp99+Qs8tvEyWx9epVzvMD19Fsur\nM5YjbK9OvdwgCuFor4urWQTjAeO0Q746TX3qk5RqeUT+Gu3DD/G8PkbmkHfmsZyEzrBDKitkukWx\nnOBZH5Cm+5QbNWSiGPTHFAtTOHmNILiF0K6CJui2A0z1KLbxFL4es3jJpVip4mjT1KcKFGpDypWQ\nTKWk1jYP9/Y4e26aJ55eIBJvomV93vjOFufOnePtN05YWrhIp+1Tr56hr/0JtudjJFWuvdFBRiWe\n/MxtGisS4azw3tsRaWcZIwy5+GSHJ37ZZ+1ZyQuvbHDj9m2MdED/OOPo/jR583n2HnrUlx4SJRHB\n2ETKiCTJc/uGj24bGHqEpwnaLR3TTTk9LPDmn/t85kvT2DmFJ3SCTDIaemR6RBAlWFoJPzsEivSG\nGYaZkrMNLIoEdCjOt6kunJJGNjs3hgyOclx+Yp7ZzRTdCwiyiCRpEh49xvFJEzdbIE53mbt8SpYb\nUpxrYzs6hm3SPI4IDj/J3t41ilP7PPliTFT6EDefcXyY8o0//IvXiZ9uopEp0mSyqUnTGCXAEGAa\nBnzM9de0DJGB7ujINCFJFUgL0BEfF1c1oRFHY3Sdj98W6yilT97opgJhjEmjAsIIyBIwtCJSjDEM\nj8AfU7QK+EGAqRsTEJUuMIwJiSqKIjTUROgnFXGWEMUpmmlAkpJmGXEcQmaTRjpJHFIsFTAssA0H\nlSaEfGw9VwqFhhRQqRYY9/vMzFcIRjFppiiWihjWZNrSaXeYapTpnI5QSQoKCrkSek6gpxH1mSle\nevU8fuhjxSMMvcnswjq9Tpdf+xsvcdz5Kh/dbLE2U0BKHTcv8fsRmQrIMo9up4nj6awunSdfrKEp\nF5SObmaMgmNkqhCWx5MvvIYmMk4PdjE1we72bXbu38fBxNsUeGYO3Xbxkw5bR4fIMGZ04qEyg9nF\neVI9ZK+1TdvvMhj4RKaBXvCwMg3NMLAtm9FoBAq8nIdmQRSMEbaDTBVpFqNp4OYdOu0WQiYM/QDP\nKyA1G6+g0eu18ApF/JMWoa5wrTyREpQ9B6klHG4f8LO/9Z+QJQm2YUzK/UqgaSapBF0HqRSPXHT4\nuZ/7O/zT//W/AD1AxyWTKaZhochIpcQQgkQCJGQiIc4SlCwRpBG2dUA0cCiXKoThiKtHf8CDb51j\n86Mn+MxnHdbOPMA2fDyziq5DlPQQaR1LD5GGSWbEJImJi4Yc28g4m9xjliJjCUYKukaSBuieh5l6\nyMAmUyGpLtAyg0QmSLKJzTsRKKmTpSkGFmEaYRsOYz/G1HSiKMHzXIIg/nfuGimZHJClRAhFmqWT\nyaDMkFKi6wLL0CamcPVXE52yBglO02LFbNALI268pag8MJkeVmnuZTSTJo3KOsGewjAcmvKUQIPO\nm5KnXzzDuHeC6VuMe4LpWpm7LY03bjzktbkzaH6HTDMY+iPk2COJLOJ+RN4q0291SKMEr1AES2Eo\njXTPpTfbpbMw4sTLcE2Phu5Qf2SaxC1ydBtu3zfZO4iJgzzDBwHWYxr1hQKbl4rce1tn+17MsK/Y\n0Jbxxh2s4ohiPKSaNjixY3JanqOGT2iMCU2TqDfk0y89wvDhDlk6IBMDwixiFB3Q8RX5qSq+MqEz\nwplXeKpJaXqGqK7z3/36L9Nv30D3dviNv7dEZbZKUhb4+pDKIzWiXcH//us/4gwbXJ79BK8ffYfF\n93SqjTwzKyYH6QPGg5iFVYO5so4fljhpt6nN1PEGEm2+ShdBGEL5LDzXfpTjqzqjyGQ39tka9jkd\n1EjGMcUoYetOmxftGv43hxT+dpl+L+PkUHL8py3kwQO2jDbHFZ/cvMVonHL7+j084ZCbtTBXMvb6\nA0xN4VgahYLgOB3ioLGn+Tiqzji2yWd1BjIiao7Rcx4NL0duKs8H3+hAI0MN6lw+8wmGxwnvi9vk\najlOozFvvfcRm7MmDx6mfG7tSVp47IWCs8pE2Bnz0ualRxW/8w8iPuh/nf/+n/w2f/fLL/PFx/8x\nnzv7GsOjY3L+GFdZSPMDFjafYrAbMi6lNNp5QiukJe4TnTtlkBc8+eoyuVyB/NZnMDpd3rmxw/sf\nCn5z9jKNX0+I6u+Qijaa06E8r+FmJsk2WHM6o3stlgqfoP9RysbMI3RkiThx2b63TaVcRzZb1NUc\n+jHoQ4n/jSLuUYdyKSMZdCjXHQadKTrf6TE4EqyyxtxhDcc1WB2bJPKAUkFnqzVi72BAPjfP8UHK\n8L0cD7dKGIsn5MqS5eIYoekIBf8vb28WZEl23+d95+Seefel9uqq7up9m+mZAQYzGAwAYgCCBEgt\npEmTFG1ZVDikB1oO2W9SWBF2WJJlhRkMyqEI2UHZpEyRDhLcTBAktsEMZsFgpmd637uquvaqu9+8\nuWceP9wmHX4iaYvMiHqrhxtVec7NX57/7/uyawVrJZuf/LGX+b2vvM+1a2OeXxHMzunYJQkkf+l7\nhbQO0JNPsL++g5gZ0KwrBkGBzC38A4073xmxcCxhbskkLecsf16x+baOnZzmhCUZOg5jfx1VKtMb\nz/PB1w65eGEJvT2hJwZ0BxZ4y+gJxLHG0VaCur+BltY5fHuNPTVCGhHOQo/Fj+s899MOb//yXZZm\nXkC9f52qvkIxO2QyM2CU9plv6Ax7gkqpjH0+YPmKznqvBEqRyZCNqwmt7grvfv2QB+VVepuSTk/S\nv9bANZucUpcQzTJVyyWcGLieoOa1qVYclO7TWPDYSQM0sUK9quP7j0l6v8lsaxndrdG5YbAtyyyt\nLjHMDnn4+iNax85zY/OrlBJBX80hZcDWk4fU6zlLZ0v0jzoYmmRzW9LvtFho2BhiizjfJzb6LJ7T\n0TOL3mHM4eAW6w/2OLl2llZrhc2N+zzefshnX3mZ515x+J3f7rI0MVlZ9LHMIWkY0hmvUy3V0b0Q\nQ8+xyzlhXyD1Cqk8wmkUDMYxi2sJo8NrDI5OYIp5QlUgZRvL0RD2bZq1KjKK6Pfu03loEodzzM+c\nYDiQKKuNP96i5O3RH7bJxhZL7Yy0/B6XnztNaS4io8dwo8bh5Pu46R5RLlH5FYS5zuUXK9x8J+Dq\nnd+lZb3A1d23OXV+GU87RrWxy87Ot/AzG92+xPEX/2NGe/8HueVzsBezfOIuzWM5M61PcTCKWD3n\nc/uORX3V49izjyktmngVm3SnzYVXb9AoGpipzRt/CE9u+8zMv0z31gxz59/iaHKT1dWzjAche+sR\n0dE8i194xMHYwnHm2dt8iCMb2LKH39Ex6gmxPSIVBsO4j9J1jNxAxRmluoterRAmGht7McX8AY5Q\nYOjYRsLMqkZt9T5u22PvZpWdhzMUr/dpPzPCbEpqbhPHtWgttEC/zO5+j4f3H3J6cY/JWHBitsn9\n3gZR6rK5cY+YjIP4HodHOs1TikksCRIBqD9znf8FOxo5WTp9w17kCiEUhS6Is6nULEsTbFMjlQpP\n8zAdhSENpBDoukGe5RS5ji41hFJIJGkGtukgntJ7VB5hyBIpIxyjRlRE5BRohk1WhLgllyzPcU13\n+nAtc1INZDot0aZZDkIjzzPQNGQ+NYprmg66QZErlMjJwwzNMSCDQqVEcYxjeJi2ietZhFGCPw6x\nHIMomoBeYJU8DM1gMJ5gWzaqiDD16fhKqWQRRTGWJcllhuUYU1lgrtBNB6UykskhWp5hVyoYrsHR\nYEJJdxj5R/zDf/TT/JP/+lc4OhpTLtfp9g7wrFkcR2fYy7GcBvfvraMVVaKJj+2YGMLEssuQ6qQq\nQ4RjjDykSDNqls79u/cZ9EakacIwi/E//JBqpUazUqHSaFCJA1aWj7H15BapKHj3jT9gmCSIks2w\nSJmfW0ZXAlNpyDinVK8gZYbKE8peHYSJYbgIIydXGbpeJgh6mJZBGkfYtsFkMCHN4ilZzPLIVIFu\nGCRBTioNXM0gzjOOr51kHA2IB/ssXP4YyrCRQkypTACamJ5YaYKkKLCEQAnB3/iZH+Lf/tv/FkOz\npiEyz0hUAAK0wiXTJHEao2kpqoAiK9B0hTQEsSrQzZAoT0mLDKu0ip/3+fadX+dB9xlePP88r71q\nUGu8QaVWUHMuEMVjVF4hT1P0AMzIIWWCoowpUvJQIJIUkWVkSqGYdjHyWGHaZbI0Q2KSJ9kUXkCO\nMHRUDqnKUBIyVUxL3pogSRKMQhCFKZKCLEsR5FNhZSbJs2S6FskR5BRPDedSKtI8JSsKRF6gaya6\nof3FnwT+P1xF6pDvRNRth7iAxqBG75pHOlHcv7VPabHM/LEKeVpj1pzjwb5C+gd4a6BZZcLNIV1l\nMnwQYh5U6Q7G6GYFp17FkYI830OzPSbjgnSQUy/Vac05DB9NcDQNkeroRY265eHJkEEaEBoBhyjq\nYUYtK9CdDswWOD2LlSWbB9cygiDHMk0CMSCNe5SqgoVlk+tXM8K4Rkm4VHo7lKtd2oUiLXq0c0nP\nHHPnUUbVl8wtOIgOfPTBNT787mNqZ45zbqnOvNnmIMgRscGNGyHdbsHiioGWpOyOQsJ0h9Acc/50\nm6ajc/Ill8Yn+3SPDvDCEl5ln+WXG+y9vMKXOorf+vmP8Nw6r/zIp/nj3/9VTh7p3P21iPZn25Rn\nE2bmBAuVPpevnOTDwxHzz59kmEwohxZ30yN2bh2wdS/h9OwiZxbP8q3vhEySRb761jqXK3X0eoXR\n1phge8j3uhM0ccTc30u4ad6lyAqOzzeptUzk3AHWKZPaYontjw4ZyQle3cA9rZF4E0RTMNYVWqrY\n7j6gWp4hywoev3PA+edb+JMQKwVcl5EfcNw8Rh8TLZWMRgOMos/GdpcvfO6nufnBdWpiDqvc4sP3\nvo2SJcwDmyuLn+HZTzXZ2vk2cX2FXeMI29IwpMaTzYRjyy5H44Dh1kc0nlll9dVrtNfqxF/foF2Z\nQyYllNYljQtqbo4Xl7nMCZ4Md9GjHP8oJK3uI7QJ8y83WHrxBH/8ex/Qy1Islrj7z0pEH3XolLf4\n8j+vUxc+brNLZz9jedbl6CCl6s1SzRs0ZzzMXKealBiOTc6snCI+VITbCY7nMn58yLGL59n81iNq\nRydpzOcMjw5wzy5j2gb6k0OK+zkLp58nXY+ozBTM6jb7nT6BSsgMi6XjHql1gmQnY/d7Y4obpyjJ\nMnfq3+WeU5DrBXWxQL4dQlHmaPKIY59bptoKiLWEwSCjOxB/5jr/D7JXVCJ21w127odUTlaZ02G/\nF9CwFJlvc+91RXxCQ1ypY5saW/e65J0S0pVEdBmNFLYxwzibUGDjpqv0b0dsfH1A45mTBH6OMZrF\n03rY44TOhs3lL36Bj979JuPQQIkKpphBMzbwtT5rH2+z/zDj8VffZUUu4FY+Qp4bwlKH7qRgjhjH\n0+lPRjh2xGt/Y55/+e1rdMYzlCc1krcq3HtHJxzXuHGQ8aVP/Tz34rvkHcHAN5hfnUMXLkliMDdn\nEE0CIv8xQadAVAcszNd44Ydm2N0uuPbBTW4//ICZnsHrXxlTKs0QpbuUioLckfipyfXJW6yd/jyv\n/kCVwn7AYvM079/9OjI0sJUNHZd64fG5lz7B+r03WD2b8cmfPE3S7JGIPv54gKafxp4f0TozYv+q\nB3nCxI8ZBT6t2VnqM2X+/W//Kjff/hadvSd8+cdeZqa9ycZBicNHIS+8cpzqvEepYTAZbWCXS7Tt\nBXQXEuNN/DTHMir0H58nGbdpz1WQ1gPSYAODFxDjMzjeY0znCb6voZkeVWdE4PQR5iEN89OMhx5R\nfJy99dvo84IZofF//o9fZ+C3+Xu/sIU1u4lZ/Cw3PvomtreHJULKsy3K1ZBElTixepGtWxnB9qd5\n8+6HnHmuRqvZ4Ntfu8HP/NyP8b/80i9i5p8kOEw4urdGaL/I9sFX8UcO51/WmVtbRpaGjHa3uXTJ\n5PEfHaKXfdoXFNIYYdklZP0Rz7+suLL6PDff77N1w2O/AyfrgqtfG1O+UyUSOurFE9RmNtAHKbfe\nDTm2qqjPSfSiw1HPxO8aBHsT7ny/x+VGhDEnKbIFlLnFYALBXoCeb7K4alFv+VjlkEkfOmOdthYh\nDY3UCVDZHAsnBPX6HGH9IkebVR7c2OXLbY3mXMhc9STx6oiafgI5SbA3KgzG8wwOc1aaY7a6DxBa\njYp+DFP3CYI1DjdiOncS+tYR7VMmKoj5Dx40imI6y8zTgQ0EiEwCiiKVKAFKSRAZBRmGZmLbEsNQ\nTIvWOoZlYhg2hmagGxLD1NB0gGJK2hEgRIphWOiGwMoERSEosgzHdIjjBNtyyLICQ9dRCGSekOYT\nRF6gKUWaZdPyd6aIohQKRRiNsJRHpGkYhkVghDipg4lGHOa4FQtdGliOicpzbEegaRpRFGLqJZI4\nRrgmaZLjeS4UgnCSoRsaSZKj6zpKRaAkmiZIkhwpBUGcYAsDTQPLcdGkQDcEIkmoVsuEcULVm2Gw\n+5B/8c9/jn/83/xr8n5MVkRkRUZ3FFGq1Tns9bGlzaP1DaJ8lpXleaShMwlDSnaVDInEZvfogFrZ\nw5AGC8eXGQQhfiJxPZ3ucMh+f5NytUx6/zaTTEf/6BYYBpqpIyTMtedZWJ6jofLpiA8Cx7IpWTZV\nr0Kex+RqKtMOkxTPzgnSDNuyGAwGzMzO0D06wrJ0RsMhSZziOh5pJqb3gKYxjmKiMKAol0nHY1zP\nxREWpoxJEp+FFz8PwP/rq06BEIIsm44BCamTActzDY4tLxHtdAAblEIgn8IBUnIVo9AxpIVCoemC\nPC/I8hTDmI41JUWGlJIMH83QkbrLfucuX397hydPnuMzn/wxzlzs0HVvUZcV0gwWjTmCKCFJLbzC\nYBDFZE6OObbICkWRCzQAqaGhkUwyCjNGGDpInVQqpMxAMyjIyApJIRRKFFNJRwGZrpEnaop+zm2K\nIp+utyxGGAqRKmQBqlAUSqKKKTJaU1NxpRAFUgpyXYNMkWd/NdSpXj+lN9BxlqtMBgWD7YLuQczu\nw4DBIOPl184RlkdoWobrmzzbaeEszODXumx+/y6qPCF5PGbcTXDiHp1uTrVSpSzrzM7aOM8WuIsh\nG7eOKDoGFdfGNjL6+yMqwuPoSZ880ZBZGeE0CLMQIhM7Csk7OkU2IRT3MUrzRJ7GyoVjFL+b8mhn\nwOkox04jimCCFgSgObTmLUZByntv7fLac8fxGTO2EwajjLlQcNWHRRvcMy7J933qSyVkoVg95/B4\nK2Xyf5m41YJ2s4Vm1rj+7iOCwiFMbWpByLgnEIkBxghhQ1bdwDqZYiiJ2RIUo4QyJWyVUET7fOqH\nT1DrnOOdX09wrAZVLhMyYvNel3An42N/t4Lw9uhtPCI7pnhmNSAvbuAYNv7AxqxkqLrG7GkTFfYI\ny130YgYnrfOgPmbT+C6NvodMHS6dXeHunS4XTZ1gZsiJZpPFVxw0L8KtFUyMHmLFYn97j/29Ia0v\nGLimgTEnuf5wgN2CxhJYNUEWQUvajI8Kin2BI0y8WsJ60MOdtNl6d0iFRfqPBU2WUGkHXRgITUMk\nBnpS4cqZy/zh1Rv8/uab/H3xJU4dd3kyK9EuWMiKxrJznM3ONq1amYMowjpu8nzJ4vrIYBz/Bmqk\nuPgPNlEb7+F1c/pv92jJFUolm8x5TO0Zi8HjDTwqnK87lBo2w1GNTHXx9/fZfP0hZ3/4E5w95yK4\nyN1b+3xrXZD/rxVOqZ/iQsWj8vcHtJwhfvddnIaNJMKzSxx1Djlz8TKj67ucfWGBQ5UhtRLXHnZY\n5QxFJ0P4AvdJg2WqaB+6ZLs5mT9kc2/AwSTmzu2Uuqqx+oMvUZeguR08a4JSFmkwYaZhUP3MeW7/\nnkm8H+AcuZh7s8RuwGZS47B0wPyzM+T2CUa721h4HO0P0Ncsjs3PwWifSZCzd/D0O/4v+Sq5LTpq\ni0mnYOOBi9ss0Js+ak4QDBWTjslefw49qzDrlSk2lqgaK9zfu8ZAdam1LtJoP0N360PC4ZBxXMY8\nfoH9RzHb148oO5Lleo2Wa3Hj8D5HV0OarxuoksOxH/BRyqKfHzIT2AjXYfXyLP5eyKPbT8jGJs1n\nfEovKuRqxOF+QVFxsDxB9xBqC4pC7HHuWcnVTki3u4K9U6XUqmDIkNOnba5+9A5nT79IFqUcOz5D\nMIyptssM/DucWFsk3NyETGdjskltVOb3fu0XOP7sK1z4wmv4zjY3s0fMuGVOjhZoFTUuNT7L8PY3\n+PiPxPSTglOrFZYv3eDSa2/RHdUIHp3FvVrFsT+FFSYwNPDUAclmF6UdwenXOWy9h1AClVfIoh6t\nJZ/aYkC7foFv5Af0/ZCr792mWVsmHK6gpbNs3R3iGsucOH+Bb71xE33GZLOzz/LsM4x9xeBRTJpX\nkHIZoc8TTOo08s+zMJsRxb9BwnuYtUNC1WVzW6c+s0qep5imhtLvYhkxmpmDKFOfS8iyTUw1xDTn\nODzU6T15lSRrodmf4szaId/45a9x522Xc5dm0YLbJP17+P4f8eGNr/PKZy6xePrzFOwxmrzJ+o1F\n0mCdsHKVi6f/Dp2Oiwhf5Q9+62ssrNV59XM7/Nqv32H46BhG/TT4Jvv3FvGzH+D5Z3O8ygfEiWRz\n9zYyPs7ujToi1XDNRYYHGqrY5ExlGd++x9pMGV0Ijh6lFL0TnDxhsHJ5naG3z+0bHhvra3hHy+Te\nCDSDprNCPE7ZMfc5tXSW+PAOqbHF3GKNt//Yo7LSpqm2qFYLdN0i8mM0rU2jFWLYGkKLcOwIoUmE\nucjR5AAzHGNGiiJN2L7vkahVSq0yuwdj8jRieb5NqfYhtmcw/8we3dYRjruC2gq49d459m5ZzC/d\nI3UD/FBDdyvMrJQZ9TXCnTYfvtnninuRyNkjCgHCP3Od/4U6GrblIKWOUlMnwPRBUE7Hi5geoZim\njqFPMaclV1D2DMquwLE1PNvGtT08x5vOs+vTErfUJFIqTNMgyXM0IShUhlCKIs/QxHQUKsszDN0m\ny3Js0wQx/QS6IcnjFIr/x+WR5ClKaURhhlJTC7Wmm2iaiWU6SCnxyiUKUmzPRSmF57rTsPT0xa9S\nKXmeYxk6qhCYpk6SJliWRRxG6IZOXmToUiOOMxzHIU5CLMMiipJp6TnNcRwLBehyWkTXDB0NDaVy\n7IaDyhLm6hqjScT9LZNbt58gLIdwElJyq/hhH9d1UEoniROC2Ec3wLJ0NGlMy8mWN0X95jm9bo8w\nCrAsl3rTJStG+MF4WuYvJFmmo5t1FheqtJfmOXZymdpMnZJtYUuBjoFleLimQ8Upo7IpTljXdUoV\nDyF0TKeEYdtI3cJxS0wmPo5jk8YRqihQaUauctI0JcxybMfDD2OSLCHJQsIoQ6Q5vmGw1jxOs1XB\n37xH9cwFll9+9U8TsICn/+cpcAAp0IREMg0eSQ6/+Rv/jvFRB013SfP8abFaoUkdXTMQSk3v12km\nRghBnmcIIdDktFukmxpxlqDpGoZlUAgo9D47vQ+5fvc+Nz9qoo+foYjKVCsT8qLAlgX5KJ3K+6IK\nZqCRRAoZi+nUQSogBREDqSKdpIhUouU6RaIoAlDJ9IdETi2bGRSZmjpAEjXt6WRTYAFKm44ZFtMR\nqSzPSfM/OTkR5EIjyxJQgjybnu6lqSLJCgo0/AgebP/ldzSevTQL1SE7owMEOknokHfbdEYO8zNr\neE1BYcQsvmhybK3Cwd0tlmd0Tr3oMnvWpF7R8f0uz1w8Q9lscbSbU15sYuQptariuZ+cwakp/LxD\nduBz4mIZ14ORGFHxXMaHI9IgpjsacfylJlrJYhKM6WwXNKtVDBkSZw/QjZw7j/YpWQu8+fUdanMe\nlbrBqNtnslewewTbtyWh7zIYJRxs+pw6c4zyecEo3gMPeqJgNPWQkqMxu1qn4Rkc7fTQsQiGAiOq\novp1dOcE/qDB+o0MV7YZdRKSjk0RVfEHkm7Px2sXNE5FZMcj5u0q3aGOU5wmsXSy3gGrSYUlUaV7\nbZ5f+K336d7yOL10mn4YYMgmvUhHVy7GcYP1R4/RO4+5+JpGlm5BHpN0Awp3xLOLNiePa3grOY93\nxshwFmdngdPdiwy7KWE0pK43WKhWkS2f+icCFn8wYPa1hKh9n5F/h/ppycgd0PPGbOz32H44QkiB\nVilwlgvETEB7AaSpEycCXdTIJw6TR4qkr7F4qsnRoM/OgxEN7TjWwCPdrfHw3THDXYedhwlp5LC0\nvIw/1PjuzgPM9gI7+QEraZkv9Raof3yCemmTwYX7xGKdSmmM7KZ4JYcsHVFraFw6PsetdwwiXWGU\n+5SLjGC8h6UaHF2b0LAXsVwYORP60SH6Ysbnf+osn/nPr1CoXYy8SzTcoDUrSCcdtPIUk27aFprw\nyKTLyA2Rkybjb+okDxdZP9hE82exjCZL3jkCzWbQC6hUW9TnW7SsKtsfrVO2DZqe5EzpBBv3dqkU\nZaIoYy5bwBm1qZqzaIWDn2fkhsfcmUWeu/Ax5meP8+Z3trl17zpzFyJCYxs9H1A2Haxqm6zfZvP1\nCZXcY6FqYlg5d9f7PLga0UwuY+6t0t0qc+/dfTzTpf3UKnwtAAAgAElEQVRKGWmGDNN90j34/nuK\nG2/zl75X1H0HJ2+hghLh4Rg90xGRYHJosffQ5PH1ADM7T3zk0D8ISXzJo+0NxlaH0Mk4GPU4Gu1R\n0MF0J1ScCv19H91S6EVOFoM/Ttk8iOhnHr1+l97+HovnBWc/7TB/3CIxdsmLmMSH/tEe6djl7s0h\nSVBw8dMecq1HrCmirku1CoNRhCUVw36B5wjS/SXivQbFyGF5dpn6TJXZmXkWW1/g4594AV91OXm2\nhl3yOBo9otv/iNnWPpdO+9Sd29RnJkQTE6nFGOIEiWlzb3Mfu3Se9uxpHj3eYdy9h2cX6JrG0rkE\nfemQ+3sPOPFCn9JMiFf6DJkICEuvU3POs7+VEnGfyvyQovERHW6SVHc590Wf5VMVDOGgy1Pk8oCa\n4yGtLfTSgG5HcfC4zZnZz5P1RyT+IaPRAdVqhTPnX2Zr54j+YIO1tVVOnj6LME0mScjqWYlpByws\njdGcgEJkKP0IvD9GGtdwNYMsqLH5sE/FW6TabpHkXWL/FK2FAqXtk6UQRgFKxfjhOlJNGI0n6FpC\npV4hL0ZM4pRqY4fb199ke/MDFtZynIUMrz7H6187olpr8+pn/zpPOt9AaSEPvr/KjTcazKymPPfC\nl2jPzdHtvsGta0fkuc7acwds7Xe4dX2Ev79AXmicOn+cSkvRnjvOxvB/59R5geu1QbQRxUk2HkYs\nzr/EzoMqu51rnHo2RzoxmTGh6jVIh4tsfu9ZRvsuS8++z6f+1gR95i4rlyrMnDzE9we8893r1Oxn\nkMFJ7ty/zdLiAjvbR+RxxGi7xEdvdjl7/B/gBwXLZ++TMSKL20ziMYe7EtOLSPOC4SigUj7B0VFE\ndzCgXDapli1MVWV3IyUYzNNwP0GcbfNo/V3OP+tw+VM9YuGTVXsI3Sc21tHre+T4fPSNERu3Q2w3\nxfYSJiPF0W6ELWY5PPQJkh66ptE/HOJUdZLC5I1vjf/MfeIvdKKhlJiK8nhKcEIDKUizHCmnYUNh\nYBg6luXgmhmeY+M6ObZlYJomhmajYaBJidRA1zWkpqbSMVngWPZUwqdMsjT+U4JPFMdUa3WGgxHV\nSpVJMMEyTdI4QkejUDlZFKNg+hBWJKSZIFOQZhDFAiVSpJFjhAmGpROGCY6UZMkUiRuEE8zCwvJM\nlFagC21KqZE6MsswDR0zMdA1gzSxKBKFaVqMBzFZlpOmU0KRVBlKFSRJjJDy6R8P0jTFMMG2bUpW\nnbQIyNSIkmMQxYKPbvf597/xPvPHZ5htn+XJ/TepNjIEEpEHFIVBrtsc9np4Xp9KpYptCfzJCJEX\nLMzOsbiwjG2aBJMxcZqgsoKTyyfolAcEQQhSJ0cQhSFus8zDjUfMmceQuo7tmmhKUa/U0BILTYfQ\nD2m0qghpkGg6UQKaYZAylcClwYSyJlAoimyKoI0mAbo5RQibpkGQ5GQFZHmO1BVpllNoGiJPMDUP\nUaqjjjZIDItjn/0RrD+9356Gg6chQzENHkUuUCJDSB3bhIIY09amAjwpUDkUQoLKKUgRSHTNplDF\nn5rl9TxHKEFaJORFjq1ZCASFUiRZQkaKTgspFymcCU/8r/KVb3zIgvYstG8x2y7zMy+vcabU4EiM\nEJMCzwfHNEmTENKMPE/IlSLPkml4SSJSWyDMglxMfR/CfBpsZI4SBYlKKMTT35eCIp3iavMiJy+y\nKUUJC5Hzp/EeCdnTTlGWPcU/K4WGhtAFqlCkcUGS/dV0NJQpqbfa7Ay66DV49F4H3S/jmQs4jkFV\nuiTuDqXjXYg7uGvbNNtNJtkethxx9pNlnhnWsSoGH4UhnqtDVnD7/XU8Mcv27RxWuog4QRoZqpig\nrIz5KxnR3piFQmP7umJ98wkzt1xOnjaIUxNbC5GrIf38iEmoaARHBJlO38yIahbX72aUKg4AtTWT\nfjTCWp5hzV5m8mGfzjjm67+5y4VJgPsCZKeg7MJcXmC2Bf12jhQCdSzhVN2CrRK9Jxa33g7QsNn5\n6m1Or16k1T5D0h9z871HnL5YZvFcm93HT4hUQXrWon8K7AoIZWEakijJkdLG0s4iIw35wGCttsuC\nvspGVnB+5zUG9RpG2MTM97l38x7bCz0qzQXe2jxitb+LURE47S5pMmax2aCkegTxEafdRaL/qMfk\n1CKTZ5bYfCdBv9ri2uaAclgmDnrM/2hKVt/lIN+i7tqUvB6uYxJ5PnvDkK1+woPDjNKxCtIyKVRC\n4BTYyubB92OqJQvdM6hfWAZlMdwZoGUabNhUSjPIoWTnSUI5rNPvpeh5me17Q84tvMTuk0OU12A0\nCSnNzFOaWWZyEPB3nrRovbTOB8kfY3wqZy97zIWWSxONodVj3I2pyBzpKhCP+YPvQf52xj/9xRpV\nC7prAWaUYNQU3d0uwihz7PQi7+5+F3tRcXQu4trjX+f8l84hnwmIb8SYeQS9lKy6gZOUWSrPIAdl\nlp0md32bxIj49naPt77SJf0KvHh5Bt9d58dfPIN2tkW19TxvvX6Nn3jpFK2Xz/HixhGD7hhrtsVM\nrYl+f43eQ0XXz1icPcHufsGS12Rde4S2llMYPcqLZeari1x/7wGThwnuygxPdgJ6bsCVKy2CkU8g\nunSHHZzVjGdXz+Kn2+Q9i4N3Egb9OgNmySsmO3sa9x7krJ02ORcbpGIaFFvK49zxhL+KjsYobjAK\nJzQacySFxYMPusxunqAXTsgISDULXwd/NEKfxBSpojzTZpT79CYD9DylZpjoeolR5HMYd2m4TbZG\nPkUQcWx+kUG3R67lzNeW2DarDPdqHNyKYOUOC8c8oiJl+2aBVynTmIswzYhqo87tj0K2hh3cIwGG\nxXirjggGVNsm29spk/4ctpPRuXmOY/LjnD6xQK1UR7cldW8WuwpnXzI4uxDS6X2IUG2u+fs0JysU\ngwbBg8tsduYJ5YD5Nbi6nlGr26jJhMmDdT72oz+D72yRNx4QaxaH/hZG/YhV9+PUvc8xN3vExUsr\nxOrb9CfvU6/qDOOM+fZZrrwiWT6tcMp7VNuLEJXpHN4k1BM2dyPsak5Jf46yMUcWJhSyRhD2WTm7\nzIOZlL3HH1Kv9AnDHMM+Tqu9SIJJc3aONDmkd2hy7tka7926x8ufeoXJYJN4nMDIIc8E4WSW6oKD\nW64yOsrY3+qT6znPPL+GEh2Myh6TYkCeKrTiMjg9NOseBqBSHSNokiWKknOEZt+mVJ2lGLeIJ4ps\n/+8y32gxu/ybzB7/IqVGxq2PHpMEEbk85M1vbjB/eoVHj94h7cEXf1Ywt1wQBAc8vn2IadSZP+6j\nJWts3ZvhwUO4d3WJRecEP/u3fpRQdvjm1Uf44iFXXpqnXvcYRjt41os05nWeeS3n4PFtBm/7LFUW\nMNzr2KWIOLWpuqscbpsEQw3TzDDa7+DNXGbB2uBEJeDEQDF+lDAae0RbJbRSByO5QraxxqPBv8ER\nH2Pzmke9OuH1t36Hl6smB+slZtZCRmHMYKIIw5xH9+DYMRvHywl8iTR1OttjksOMYTWnXA5oLs2x\nclrR2foIrRzywdWEPK/yxjcfc/7TNSJrgqalZJlBnPeQsmBuaZXH1xPW31ul5kn6yRYlvYTWdEjz\nJxSOTT+asDp7ke3HBxwGnT/XOv8LBo0CVUyPMopCopRCN0BKHYFAkZNniiybOgGUUhi6wDJ0PMue\nuhfc+lMsbYRtOQhtSnfK8gSUDkWCEBIhwLIclJFhmObUbh0GT6VoIY6lo0kJuk78tIieFJDnGWmR\nE6cZaaLIhSAKC4JQEqc5wkjRdR/pKzRDA1nBSVO8ioXKBUJKcjWdjzd0A8PQyJIMwzbI8hzDFGRp\nimnpBEmAJgVSg3q9Srfbw7YtsjjDMDSSJEIVGppmY5oGnjd1hRS5YuB3KJd0mm4JTXPY6Jr8o//u\nn2GXTqMsnf/hX/w7/pOfOsMkGkNiUBSAXqCw0Mwye50AlT5hZTllcb6Noefs7z2hWW+jIWnUG3S7\nB5TrCySTlIpnYtshaAFjf0xrxiMdW/zQy68xGEcIHcqWRzCeIFJ9eqojBDOtFplQmI6LYVtYukWp\nWkcppm/Kk5QkjNFQGIZJGgeYlkUUThBSolkGtukSxxlSNygICeOIJNPxk5gr7RlsW0MNIoxz52jP\nL5BnEzTNm9LL1J+Y36enGkWRYWgaUhgA+H7K3t4uMogpObWn96Ekz2KKHHIyNCw8zQOm4UcVEl03\np1I9QyOIAgimJnkDDVszUHoJipxUP2AykhiajSxr5NousX+RojPhH995D2tB8g8/8TyvzC2yFz3E\nPMhI1QSVFYgsQtckZq4ojBgzUwhtDIYJGuiaQumSREZIqVC2RNNypCYxHEEhFVqmKKRCL6ZhXGkF\nOlN4Ql4YyFwhCgV5RJoWU+pbAQoNptA2VF6QSUWq/fmY1/9/L8cySQYFrvKQqYYtNWqz80xyncmo\nhwgsqrlJM7PJ9QTD6RJlW9SXR5z+chW9FeAZir3eAXWzxJWkzu5jhTy0UFHG5jcDouoY3U4wYsU4\nGiIqGdaiJC+gmZbp72WYvsbB+g4HDyN05XPxCx6FTJhoMUFJ0V/POXwk6QUBtXKDIrZ59FYBeYXL\nM4qLn53BNqrku3WMuMa7r4/pXhsR1cus6Gsw2oXnQ/Y9OIOOq5pESqBZCuuSz0FxiJosM/FiLp3/\nPG//7htsvnOLL//Iczy4vY+gSa1+gqOtEYORSft4E+t0laG1yWUaZEGNCgv4mkAVCYV9wF4vxm09\n5F//VkYz/SluotgTOqdqzzIrlulEdxGuZH3rDru55MRsnTcf9XjtJUWYKlxPsNvvs6fGVGuKtHiA\nkSncSwX2csC2HjM/b5N/x8UMBJv7O/gbgpI5Ifdz+kd9Jv0UPxDowwFK1GiKJpW2gVuvsDOe4EcF\nVbfE2onTaKbHg/fXSX2NuG1jl6vkuYGtSdZvjGmuVFjOymztheweRCQDxalLVzj44AlOVKaFw9L+\nAo+aI0rzbTZ7A8SdO6w+36T1X/UYN3a56+6gywG6muGA+5QtnzmtDipiVPh0x3C/cPG+bVNfOs9u\neJet4ohZK2Du0gJRbrA3GZLsJxilgoU1i4ufd+m98QSWc/rxASf+Wh0rg/6WTd/PuHfzLoZ1RLN5\nEr0ygy00bnWHrDYc/I0Wzvg0v3/9Hj103rl3g1caH+d/+lc/zztf/SVe//UxX/6fF6h98gfxrm+R\nPJkQjy3qyx+najs07qTMRTV8tcfKcJXH4Q0sJ2T+ks1wb4whTcROmXKvjmXC+L2EyRWXvmbSiTpU\nwi5e2+GVv9lk7bjOgwcjtrZHrB/uk8Y1dndC9K7iYWfIMNVIM430IKNY6hAJxWbHZxT/lWwV9Isc\nd7FCpiVkYUEaVzm8C8KaI5D7SKugr08IVJ+mWyIIQ7b7O2iaC7qGyDNGvQGm4aGMRQy3YG+8j2no\nuJ7H/XGP4WTEiYUat+5fw14qoSVtsgOBudOn050QhDm9noW26jHSRkjVp9wwGU1Mdh5UWZIpqjzh\nrd/Z4dy5GpaXI8PnqFjnONyrsig/R3vZomxZ7Bz0MNIhB1v3qBp3EfMjWp/6kBU3ZoxN6YVV3v6V\ntzl4e471Uc64HrC7pTPZgt3+kJ/4qR+ne/A9wm+/xYMHv0nnyfe4cm4W/bhNLJe5u/MOb9yJ2EtH\n9OQGz79agugYx6u73OvfpymeI3PvIcp7eIuPMWsHVOYrVJjl3HmHg14CaoilFhH5AeQWO5sK3T7N\ng633GAy3uPjcJV5YPsnunTtkucujzT5PDm/w6Wcu0BsUzC0vkIY6o6OcT7z0Eu0lxXBkobwtvMoM\nw8OIvBhQyD67Gyn+4Swls8zq5SWONv6Qrb0dirTNKAqZae0ztP4JLfcURdFEtwLGo5R4HLNybIUk\n32d/7xHvffM+efDjON4X+WD3PUTe4m/+7S8zf+U7JDZU4gaffPUkV7/nUbI+Se++y/vvzPCxjykM\n+YRodBG/e8T333mfj7/8w1x4cZfv/ME2C85/wS/+b/+Gs6d+HMN3yOOM2cUKi6c0PrzVI4gmjCYS\nvTWhUT8iCPYo1fa53c04fey/pCT6+J0HNOZCTLugLOHO8AZkK9jlPucvVygyaHpthFagl5oMciiC\nNq3qOSprd+hPrhPGEbe+dpHLl79AZ/MthsERX/zyT7Dz+D7f/aNbPPuaRiGmdYS9eyU2b4e88lnJ\niUuCQ+0uaC5hr8LubZ9Pf26e9oUBYT5mkB2RzV9l9dOLrLw9z8O7HtfvuRx/XicfSaKkQKU1MjnE\nLQKckk8S59y5WufKy5/k/Xf+KaYcs3svJ/RXsTAIwpxHTxSjokY3+vNtFH+hoCGERNN1hNIAhRCS\nopiavXXNIs9BCAMpCwQatmlg6BZSZkhNTk8G/qSvoNtMH4ck2VNTspICS5MMxxOELIAc13XR9KnV\n25ASaRgIIZFSUBQZWR6RphJN1yCGOEnI85wojfGDCUVm0RvGJJGgECFCh7TwMXWbMIwx7QlZ4tDv\nDmk0PZK4oGyXIU8ISbFNk0IDy3PJgglSmRRZQp5l2K7FqD8AoTEe+di2xWjkk2YxQhoYmoZjehRF\ngmHooCSGruM6FjjTkSwvNxhNcn75V7/B3kAw0z6id1Tg9xWf+4HP880/+lXm6x/Dz/aROWhCIXIN\nXQkGgzGeqxP6PWbnl6lVmnR7PaqlBqiCslthPO6j6wXlmsfQL9Ckg9lu0Ol08byYWw8/YHl5mdEw\nJi8S0MCs15BOGc/QSKIASzdQ+RRjHGIh4oQwipidmSEIRlS8CoddnyzPiMIQqcBxbIJoQhxHjIsE\nCp04S0iKmFyC5mi0rHkK26A+OWTfsfnhH/vbjICK7k5PL5SYjks9LWsoBbo0yFKBIVKEbjCZTLhw\n4Sx33v3+NDwEExQChKCQBToFRT4lm+mmTjxJnno4NKQQhPkAzdDRDQOygixNEZnEKqUkSYAjGth2\ngdBNoiCm627QjEJ6c3Wcfh2jJ/mXv/01Ppy9xV9fOk7JqJNPdLK4SxrmpGoanNEKdENHFZKUCKwM\nzdbRHJtcSqIsQtoSTCiMgnQYo3k2aTyV/EmpoaSgUBpKMiVrFSFFJlFEqGJqUI+lDlPmFkmak+Ua\nSZGTKkWu/vJnrgHMVKcSWhjU2Lvls9KY59zyC9zsB6yvH2GcNEmVTpJJKBIGwSGzlYLGxxKaCzkj\nutjCoN96SLW5RmO5SfYrCZO9gryfkB/Y5L5O1hR484JUhphVSZqkjAcheWRRNk0uLrdYWm3zcOMx\nfieit6kxd6JCNCkhqeAfmoS7JdSRwZxbxY98hr0JbXeGY7U2zx4LmeRdli4J9KMUokWufj/kaD3i\n+Y9fIttYIsm3KF3eJm6YLAkDHZuBGhNKGFwBKzvk8Vdi9t99m8acQ+pmdMWQWxtb/OiXXmYUZ2xu\nPMKaMwhkh9FgxNoZh0puMg4yDH1EuTLi0eQJR0HBOSX5738hJX27yUnxGt/Rd/mm+T3+04Vn+GvC\n4Du9czzxt2jNHCMwtylqa9z9IMTVFR97VWejk1NIm5tXFa1FOHVesdrUGPuPeG/9IeHyLFlwnMon\nPOYrgoffiHnQecyZpQbVuMTurQOUDZqnGGoWozBidmkFKxGQGsxT5uSp53DKBh+8eYf5uTrp7iGp\nXrCX5/SMmLLWQNoa/cOUzl6fUtWmVa3TmUDSjdjb28TUE/yuTyws/tD4CLe9wILTYuX7db74n/0c\n3c//Eq/LX8LWRrhlj+bSHHHYx7Ai6kpHDwrukaAMwS6KZ2cNBBdwbr6MV3HQ90L2swF9YrSaZGZt\nlm7cJ7EHbB8FbN39v3l7z2DLsvM871k7731yuDn2vd2343T3JPRgMDPIICIFiFkECYp2waZtucyy\nqyTbouyyS39UtqtkkWVaJQaTIEELJAACJDADzAxmBpjUk6dzvH1zPPnsvPda/nGGlv5RUBW4/p3z\nd6/11Vrf+73vk5Gne7T8AeXpEkI/oFipsNPbo9vz0aoRBUtne+MVJvUmx6wztFsa9Ycr9AoJJXcC\n+UoNrfh+rg/e4NWtPr/95XfYWJ9hg00an7nGh5/4OcxlxcEre/T37rBYOoNrmeACEXyPXR4YjLGS\nLdG7rPjR1vOIhkm2t0Bxo445NDi+ehZvv46xs8Xh2jZhRxDu9ZhqFEgKQ9LSPWYfD9F2Ih7ILK5d\nTig0JZvdDh3fZ3pxiqHvcOP1LdxEkY+DWoRg9e+kVHB8/Aye42DZGoPcZ0BKWguYnl8kSadI/AEy\niKnYU5SQoO1jFFMszcWmjObEyCzFdWqYdh3NyNjqtVG5ye5WC6/sEWQBmwc6ouER9XxKRY9kYLLz\nzRqGOUZKl62tPhuOpHG0yPFHpvGiHnPj03zzK2/zq782iVHWCG6bvHWjQqM+S008RFpp0JhaoCDH\niINbFCYEsp5hOmXuPfMCS5WYcmGfOVdnS7WwRInpY6/wwS/N8r1WkW6QsnU7oLF0QHH5Hp+tf4TN\n6AYP/kOLS5UD+hf77Bp3WZy0Of1Ei/mVR7lvp0Se93npxWfRDZu/+OrbfODjE6Rmg2Z1lZt3n8dy\nfhHPHCc/cKkWCrSvH3Ko2szUH8EqX8VxEzSuYHCFbmyiG2eJQx3PajIwY4yCziB+jomPvAlGzIp1\njFtvLBOEu2RZnRNH56k5gjeff5f7CgK7KKhOjxOGO4SJS6aNQz5Pb/gMjelJSuUF7CyjfU8Sd85S\n0c9SnxzHqg3YW5vFGZwlyFaxCi2K7knsucvc819Ha8xw9a/KvPjkSc6fHGP6jI9wb5Ae1Mh9yfSJ\nIePzY0jjOkLp7N/c5v4HltgPnmGqsshaZ5Pt7XXq18aZP/4if/7/vM7Pf/HzjB1zUdSYmVrmd/7Z\nt1mYeBwk5HbOky/9LtXjl4mEh2ksYrvb+OEG1qBEz7qHnc6x9tIsl5+KOdl4gsvv/AGNkzaFok5p\nfMi6vkZtfJKJIxr77cvMHNPJxA1EWsU2hqh8hu5uSFnT8awX+dzP91l84H6ef/4l8rGMp/7kz7jv\n2CdJ8xlev/gMIqsgev+A/btv4k6/TbOZct/SA3z7+dew9Q6VegnVSTDGXVbf6LPxfM6Z8RInH/HY\n2j3A0B3CPMFzhtj1NrsdndCf4fCeQ+zvc/r8NDu7MYNhTKwSNnZvcvr85/jD/3uV0pjglVc+zPnj\nK9x99zXmjpnIMEe4ZQZdSZjqSLT/oHP+Yz40cmQeg2YihYEmJIZeQBOQ5CmO45KlCrBAgWGUsAww\nTYnjOOhmAduz0QwdlYe4RZcsi3BNiyRNSJMUDLBdG5nmFEouYeijm4p6s4rfD5FpArlEEyNzr2WW\nUKrPoJ8QZzlSE/T9mNBPSZXLMEkZJgnDwCKNTFKZM6mbI3w7FrohcAYdKlWTYb9ACY3E6oBuYXsu\nGRLDMBEaBAp0W0eXGkYmSPwYQ1gITeI6gl7XR2b5e4yRHM3S0fPReEyS+RTsKkJYoBWxojYlR2M7\n8Pi9P32Lr3/7BpbuYRrQGcT4/g2OzS6zNrVMq7dHGECjkaIiUI5JP5BYVpXV1T1OnJohzzoMBzHV\n0jjD/j6O7VEs19BMhzBO8OMI162QxQnkgkZxCl9krKycRShJwUwxDB27UKPfPmTK0fG7OY3KNJkE\nt2xTqriofOTVMJUNmUW5PEU/lBTLDYb9NobtIJOUOExQ0iA3HBjkxDJByJyoP4BckGg6TtNipiQ4\nWIs4/YWfRgqBA//O//Ne6pR67w8hBKgEU9dBGChg2D5g7Wqf3LaQWYBl5hjCYOBnaLpJInNMoQii\nHlpsYBnGez4NRv4czSEmIE8TdF2QZTnCEBipjqkVkUKgaQbkCs2UKCyCYkw66OJ5VfI0Q4unebYd\n8mL6Ap9OPR6rn4MkQ5MO1dwnFEVSNlGDMXT9OpIasdZAWD0kQ4SmYxg5TtXD12KkY2IWXdLAx7UE\nURihWzboGsIIMckJ8oBAKXJNQ2gOuQwJyMhzk1Qp0lyQaxa5oROHGUGukwrrx7wG/MctPbNJ9xS9\nIRQmSsydPYfezzGqgp7R4d7WNgtHHV75q0M0fw+zNMvxjymsY6v4DMiSjKGV01QwLrZZbaRMfGGG\ncqXCy1/bw7+ec+RshWq1gF2+i6bHyD3FzWv7rL6uaBZ0xr05GtMFlhZsGsVxrq76HNzt825fUJlt\nEqkC+pYDG2D1XCZLVaJimV4QIPd1OlcEwSmYOa5TMg9ZelTiTWr4ssn6zXV+8J0Wc/Mu6m2bJf0E\n4eMb2OiYYY9aElGtwBtA2kt4/NNTXPxWH6lKYClefuZteq0hWScl0dosLBTwFkJMt8CJGkwPMkTP\nItaL5FpEvZrT31BcvJnwJ/9vgf7XPBryNznOQ3zUm+KZ+P9k6s6jPLwseHjZZLvyMZ57+BZv9icJ\nk3uo7hyvfWebpF9mYaHCu293ePb3BRcuWByxSwzLKWgpK8uKbWufV66tU33oNEbV4qGpBt/809sE\nuYbvF9CjSYoFDddxKVoOBS9hUkziGxlBlLFQmWS21OTxj36WfPWbRLHi7334DL2gx4F/yLCT4yob\neglNb5Y4qdBfb7GfBIQ9aDQaVOIqsWED40hc5sePcbx6jP2LB7TVM1Q+eJrVC68yTHYoCBhrGBjd\nLrWyjUiqJCIi1B2SJqR0MCjw4MKDXBET1L/zBGs7B9SW5mjXQ7JyQljoUinXmBibYGu7h/9OQPdc\nRHPKJh720M2Qdr9HGo7RGQ5YWJlgdrbOzWt7RIWcTNuk0hyncWdIvi2ZqzQpV0tYF2ZorYU8GP80\nz5mXeXp9nYIzxpSa518klym/FnHsVZeZxSky3+G1gx4bXogTjjHlOnyAh/GkQjJOwgaT3XmanRLl\nuxYPeQ/xDX5EqLvIf6NhP75C2lHImSGel2PGNsKQEPlk8gDD83nfZ0xSGSCTfcpZkyMTy8zNTCJ7\n2xxsC3YPYrIJwUAobr/7d1IqmJ+8D0c00I2EkiMAp+sAACAASURBVHlAb7BPzUmI9YDZwhGadZcx\nN8dIy2xs36UlS3RVTMGqUfemUcJnkI14TmEUo2eK4xMrtAdtxmdcuuEIcNoL9snRaRgesQg5WIPQ\nbBJh44c2/UGNsjuBivcx9osMhkdp7W9xZOoM9645aGxRzI5TFA0a+XFsu0BJniRo77PX+j4nlw84\n/ZGcqfoml9dMqh2D9VWfw3d+nnpjG73xLPr4bQyRMnV0lY98eZL9d0NmPnyDz/3SR9nHo935Kje3\niry9VcRq2LS2c7L8GJevbHF57yUov87f/5lHcasbfOgLAbXpMturFi9d+QETk+OUvJOcXdLpixc4\n7Ezw6vM+8mmfiUaTxz+0SHX8HYZyB40ZBCkhXYSZUpvpsLtd4PTKZ/D2XqUrVtFLLRaXzlNqpvQO\nb2FoS/zo6zf4R//of+PiC3/C25ffoLMb8ta1Ib/wSz9FZeUOxx6b5nBtB6OUU8jOU6yfpVwY4vdD\nNvfbuMYuuRVSq0Ev6KDHdRyjQXvfYO44GI5BOLxJrN2iOTPN1Yur9AY5n/+FBrPnffz8DQbJTfbD\n95F3HmPQBnUtoxOWKRQDTL0PKmT2yCMIofPFLy7wwl+9zs478zz3jXVK9YTm2Fme+eaTfPTzH+Ow\nfZNCRZAPY5aOnsO15ujpGQf5d9jdzcm60NucwjRibHOAZWt01q/xxtMrnJ77MHPnnuL2D/Y4uPQp\nsuFFTjw2wFrcwSp0qZ/XyXY2OfRjqpUBWlYmS8vcvu7x8lMBpewk5eJlyu42lH0+8oUFJhYFrfUQ\nY0NQtMc4cqRAy9/h2luvcar4GGsvF9gwtugdK5JH58gHkovPbXPm4SJhmGJki4R7PZ759j1OfeIC\nnd11EpmRDXTcdAW92+DQv0PdG+drf7jN5/7T41x98y6xtOn7YChFsTHOC8+9xdkHPsCNG2+A2GZ9\nrUdZs3HaZc68/xT1ekC57vD8c5e4fOs/7Jz/WGZw0xyZqUFD0010zRh1a6WGbggM3cAwTFxbwy2a\n1MsCr6DjOBqeVcQyHCzHGFF4yxWiKKRULJJmCY7tkOcKy9TpDwa4rkuaJCByTFNjOBiioSFQo+4z\nI89DnKTIPEFhkEvJMPQJwmhkfh0oDlshcWzS60tarZg4ixCajlnI0ISFhsKQNppmYtkpQs/RDReE\njm6MLmZC6AgEpmEgs4w0yRASDM0gSTKyVJJEkjiJR5ThTL53KVaYVokwGjA2McmwG2NbBp49oDlR\n4bBT5StfeYmvfeOHCNNGqhDHKiOyHm5tmSc+9HneefXfUs3LROk9WlTwhaImBZYmCM33Rsd2A6Se\nYBgOqcpwvSJxPopIjZMEQ0Ch6IECy3UZn5whTnNq1XGytEejVqToldEoUCjYlAsORa9EtV6hXCxR\nqZSxTXtkxEeSRBmOVyBNE3ShYRqCXrtNrV4kTRIcyyQa+OQa5FKSaxDmGUMk3WGfwPeZmpriVGWC\nvc19Sg+c4tzHPg1CoCs1Mn+If29kSow8ICN5Y9Tdl6T4cY8XnnqbrdubbO6+QrUwjx8OyKVOKuWI\nNZHnGKaNbbgYmgFSIOUIhKiUwrRcdN1EKH3EuxPWe2kAYpRypd4bR0KNQPUiQ2WSME8xNB1b1wmy\nIQkZ2kDwohZyxG/isUFTVMh7a+y7GlowJJYuaRog8xwVR8isD3lGGkfE0YAoHBAHISpOMVJJrjS0\nNEPlIz+UyiBPMlQu0TExdXNkDs8UuRiNfiWaQGYpYZqT5BBlgjCBKBcMwoTtzRb8hA2eEwWd4f4B\npqtTOTLF1JmTDAY5ae4wHBzQzQ6ozXvcvHlA55bP+x4rs3xOMbaQYQqDwTDHtU2K/YB5J8PBRVZt\nXK3EztWYNy8dUK4XODIzxdgRm3LJ5vIPV+lvCIJBzsT4NEePzVKv6KRhH9uOmRhzqUzVuHR1k35f\nIw5rqEEDbafG9Ngxlpbn0EtlEmzSdQvWDUpmTmEpZmP9OqfONolrIAuwuwc370bcvh1y9YU2D9w/\njf7gEFO08ZI+dvheE8LVmNEUBb/Ja9+9hyXrBK2YO2sDTp48yrkzs4T+HuFgi8ljGrrbZrFhkG70\nmaw1OLC2ycZbPHtnl/Ydi2t/WmX7awtsqvNUxc9SpcnJiTLP6N9hIn+IT3ke1i9qlB41mHjgaRpn\ncuK9Nvt3BwhK7K0FrL6VMLgl8LdTjL0S9ek6iw9Okao+Ti1n5yAgFYLFpVnIJYmvcXRxHqRGuytJ\nYw/HmoLApWqWmBubIM0iHFHESoucOX6c7TcOuPvSGiIuUS/VqY6NkSSSjbv7+ANB3amgEkV42MET\nLp2NFMedplmf5vCwi3W1ycYNg8ye4OZUwGHRYKE9zRe6i/zCL09S/K23uVH8OltGm9a2YmbaJQ8S\nxl1B1k8pO9O02ylX7ZTEVMyL92FfeZjfe3KVX2j9GsvaOF4ScUvc4OrmPqZTxSmWqHoFbrxykzTs\n88gnxmH8ELOUEqeKUqNCz48JeinNeg2/nXHnSgtNL1Fyami6wtIUiR9SETknl4qsLHucP7nCY4+d\nxFqtcyp/jG2/RaekkUcFLnptFvwpZEFxpF6gisNDtSqqm5O6Cj1O2VIhU84Y97IdIgL6pIDgdPog\nr3OVqmayS5fhvYhkF0RqMnumyc6wQ2INSVWM6ApKeQGtHDMYdhGuw9z8Mnaxyfj4GInMeP3qC2wG\nAb4SbHcEnWvQusNPvFZ8+tTnaBZnSP2YMiklVzGMExreDI9MLXFmOmZi7oDKcoeJ01AuFSkBU/WT\nnFg+wulTMzTdKmmnzQNLp5kvn+fk8goTRZeZpo1QJrbuILMyE+UzhDJAz4r04z6dNKeTpAR2jPCK\nSAG56NHfBz8u0rNCSkMdPSvTTB9n6uhZzs1fIFcaUe05nFKAlS1gZJcx1RblBpz99DbzD+9SO34X\nHI+1q1O0djpUl26hj0EVicw0nMkYt3EDqhVcOU4mrpFXr9HprrF1a5zhtWlu3HiJw/51/uF/fYFP\nful+Mtnl9tV7vPS9hA8+9kvopbtMLfQpV6fIgjoHO23GJ1x6fhuzuEd3/yGOni1y4v3rLJ7Ypp2E\nuGqZcnYKPVyiYB8njxV7wU0ahWOU7EUG+Q9I9bvo4d9Hhl/goLVNx38X4XVIki4rJ47RKFZ58cVn\nKTXPEomMS0/9gAufsvAqV6ibKXF+h3evfot0ME2tYuAPd8iSPlLzcAwXgaBYLtALb9M5zHAr+5Qa\nMf3BKkKTeK6OQcrO6gGNZoMjJ47S29mg1+0jVISuOtx5zeXiUwM2tw44eb7C3PH34xkNdtciVt+4\nzvba0/jJdaZn6xx/3EakKUK+j0uvvUaZOouLj/Hmd9d599VtSsY4rcN97MkpEs7ixyGvv/QOVWaZ\nWrmMWXOoVk26ewW2rhZZmKxy/+MJlQe+BwWPg5sVWmtrrJyqY9S6uGWJbia4ZUF9coBupBj5NJZW\nZON6ytalBVzp8MhnBdMffBvpJfjpIaX0Cd78/rtsXLV44nM7fOLz24ydneLm7RbpXZvcL6KUYn/Y\nxSxYbN1JCVtNXn9xjaJ+nOsXDUS0TC/IGQwDShMFbt/qs3/J5u1vx9A5zs5uinA8tKxJa3uLuen3\n88rzEcX0Apdftrl5rcDOhsv22g6OnqEyn1rd4ej0PI+fHeP8xwo0l27hlUs0plIO+z6X7t77W+vE\nj6VooDSkHEWUKgVKEwilj0ZVlEBo1sjHgUAhRvwEZaApDcNwsGwL2zZGCT9RSrHoEfoJTsEhikJQ\n0B/0qNdqDAZdip5DnEl0BJMTTfxBTBIH5Ekymr+XObrukKuAKIkYhj5ZrlBY9Hoh7a5i4NsEoaIf\nwDDRCHsZkQrI7SIIH0sXmErD1HVMS47m2oWBU3CxLIlm6GgmgCDNIkzLRqYZfhQTRTFCEyAhSWOE\nMnBsi1glxHFCnGfoeoTnFInDhErZplarIdMDrl0L+Ne//0NefmOdds/GLkKhYBOGEUIJVrevE4pP\n8/GP/RZ/+WdfYqY6gy1Twtyll/loukXaj6m4Lr4OW7td4ljDtGD5iIZrVxhEknqxht/tUCi4CNvB\nKZRI0oxKfQLPSJH2InHXRzgxjUoR16uRDjLiYQtyRZT7OG4ZhI3nWNiuS6Xg0Ou2R2lLtka/36dS\n9Ah6AzTDoLV/QLlYZpD4ZEIQRH2GmaIThhx2ulw4cx+ubpB1hgi7xKM/9ysESlJAHz0okgzh2CMl\nA0aRte95NBIVoQmbKDEp2jU+9sGzLDVq/MqXn8EwLYbDiELJHvl3FKCBkhlJHqEJE0M30JRACDAM\ngywZ2cyzNEdoGpZljVKbZEaqsvekwXzEtRCjONlcNxEyphcf4hs6mmUQxYqhXeS0fZr/KvgD/mn6\nzzhe+DqPmbN0Njcw3Jw4s8ksgZn4GGlCEuco00PmGZqAzJeYpkE+MJGdAFGtIyxt5CWyJdJUaEZK\npqUkuoVeGu1VU5MYhoWtS/I4IE1z/DDBlwZhBmGqkQuNXP+7yca3XRdLlHCrBqpQYD/usTcQCDPH\n0lJyLWBjbZ/ubsTx6iLz0w7xwSU0NUrwimVCUUxgG0OyKGTWSekyIDNKKC3AKFi8/s4hK/cdJ1wd\n0AluIoTk5H2TzAwN+r7AGBfkRY1+t0vV1dD8gDFpUJ+26bczhqs+JVGjUKkwvdDkiSfO8MrL22zc\nvUqgDG6uRZjfLWAdBX9iixUiVkvXaTx+mkeHU+idkCt3Wgw1h61bOZWXQH5gQNXTGKqUJJZYiUFu\nwNSRMg++bwG/VWPtTsjDDx5hqemR7LdJD3qUxmyEoZMWdXwDKl2N8lmPrXsppuvxvf/J4da/fZCq\n+gh7FPCYZo2H+U/GPT6UKv7V8DcY2IqvvKnz5UUFX4Lx+xWD4Sr6R0Ht2ASazu7mACKDzpaNkTps\nbOYEa0fI18fppxnObI/mWIszpxqQK4J2gZd3Bhw9fYzZ1gSvv76FjgCjiZQJlrKoFkzwQ1bOzWIM\nTWaPjZPLmPvPPMGr37vM0E/p3Dpkc3ODfHDA0olxdg9WIVBM1McJ9jNmxh/h1tohfV1n0nqA7oYD\nyiKqWDScKaygxNy6zqmPafBvJri4+y+4NnWbQtnj0Bqyl5QJkzYV1yJoRXihiejD/ctjXFf7vJ3d\nY3zvk6wceZzfufYMn702xqlfP8EjywdsBpeIdmM22nfQQolrFFhsNMn7FerNWZyxDS7fvE2/L9jZ\ngbnqUV794Qa92wGViWW6IfQKbfZ7myw/eIpKJBkr7nPmnGDPb1M/Os/B5SreByLW/7jPotIp9RfZ\nZRczD3lTtmgd9jC9Rab7Jtl8ytGDlMGSQl4rcRjvoMWL5MJDcARbxaTKomXETORVElNnEEIgXFY2\n3s/+tet4C2NM1m5y5+47xFWfUtHGLFv0kjZpDBVTkoRd6sUKe+st+laHSFPMnqyxOKVIM8mLV2Ju\n8JM3atTyFGe4SqWUEPiKe31Fw/Lw+iHN4/vc/zmFd5+DmNon6Lm89dxdNr9+m0ol4sLHj9CY0NG0\nJZ55cpubb91lsuqwfFpwetJBtwq88FTK7s2YAtOIfB5dJvhGm8NUkWQxTjEgV3s4uguBjmeATUJT\nm2BRP8v4RBcvO4/MbBTbbCW3Wf6pNo2zdzhSafCDrz7L9aeGGNEKN15U1FYGVN6/xQMXhtjlDV78\n2r9ko3OcE1uf5djxAE1s4Bol+ryCMb9KbLrc3foherfOxPIDnDz9PN95rs2Tf9xgqr6IMK5QnNlE\nVd7lM19qMgjGee5bNr/9u9/mk5+dZnpBkManOXmiyLviW9zZ2cWpuqTuHnnlNXw9Js8dfCIyqgSt\nea682GFwp0waLFF7KKJxsk9zeRsDgzmjgTY8xpu7b+E0v0utGTNVL2BKA/nQFm/u/K+8+Nf7OJMP\nY5Xm6NwI+Ac/+0HKxh06a1e5/cp9mNNDFor/BZPjK/R7f4Hu7GO6EbWxSQrVGdYv3+ba9Q0qFZ16\naQUvfZCd9T+kPBlRLJ0gya6xtZphZo8wM3aBdv8ym7sxSwvHyOhyc+010FImm7/FuHsTrXuVuxc3\nWN+5wcziLEtnz7G/EzM372CXgSTixH1NXm1dpr1xFuH7/A9f/EOSziwldRRDxBSbNoHfwhi/Qtje\nxNAEY8vQac0RGQmatQfS58hZwWSzSGNcsrGdcO9iRHgAc5O/jFX4NoOhg7KhUk3Z2esylniYlqBQ\nDhEqYXZhllo9ptVdo3bUInQzpDCQ4TS9zg1Mr4slJFY5w5uyKHSv8+kvenQuJbzzeo/unobcU4zX\nm2wN9+nFIW71UV7+cxdR6dA8Ms6l53dwn07Z3pas7Vfobhrkuw56tk1GSFVO0N6N6A8muXn3kGLh\nJD/8kwPOrTzBO9cvMnesTqXeYdyUnDp7ntnJ06SxhT6xxZB1orBFK7zC0kNzVO4F8P2//Zz/WIqG\nZTsYuglooBsIZY46rUqhG6Ouv9B0bEtgmBq1ssDzLCxLx9YddN3AcQyEMLA9nTQx0Z2EPDXQdEkq\nMwpugW6vO+JgyAzHtNE08P0hhq4hhIZpmWi6jswAofDDEEM3SPOMKMkJYkXflwxCnd5Q0R/GRCmk\njEziwzAhTj1MM8e1UzQhAQsMc2TENXU0RgRqyDEMDYnE0nXSNCVNkvd8KoIszkmSDJkL4jQliXOS\nbER6NgyTJO9jaEVMHSwnpd3psrdb4nf+r1f44esbxHmCW3RHKo0GQvQIM4/7Ti1zfO4CU4szdPoh\n926+xKxWYqKscxjFDDID2ykik3gUrRbqZFlGPAwwdUGhOIqnFTLHsx0UCse2yRUUS1WiOGayukia\ntvCKOkW3gSEraCrBdTWGfkqp5IJSFAsFTNNGVyZS5URDn1KxhMhzBBKdlH63halr6Bp4jkUuc3pB\nSDsKCP0hkYQ0zpifnsTKFQXdpBNkfPw//w20kouLjpKQqAxNG+0j+HeKBoASo0ekEgLPELS3d7j9\n+jadw5AfvPANLLvKIBhg2S5SyVFEbZaj69qIb2JoaEIfKRQKpJIoHTKZkpODpsikJJOjSGSFHMH2\nVA5CkauMPE9JFKQyJsoHJComIyfTFG5S5OXea3yp+NN8PfkqreQotQQqNSDoI60YsgyNEKVHpLpG\nJjLSbAi6IpMJOhLifPRdcwsRZahIQ0tNtFRHy3M0aYKdY4gKSgzIpUmmIsIcMjnaf0GiCKRBgkEm\nTNBN0jRn894+/IS7lJ/63AS//BvTmJOS3W6XtXt7GIMmM2KKQqqxq9psa32GHZ9TY3N41T6RcZv6\nqRYVEdBWPkM9QgYBnqmIDZtDYbN2VaN1ycEoTtELdYJAY3v7gIN0jWMPeTSmYarRYBho7Hsx6hgM\nxyLSiRA966JUyuycSxBDay2mu5Nw30NnmF2cYdars3mzzb29Q3zDot8XDNoWYSdn7oTGwcwWXaNL\nuSpZKDZ4aHaGvVVJuz8kag9ollJq96XEdkpkQ08oNnMYZPD6K7t0risK7hFsVSHPc8xswMysgTIH\nLNzncXNrFaZc8kIBq2Nz9U2f+tgsr/zjU+x+7QNI9Sm2WcEyZrG1MT4qy/zCww7eRwSNF0tcr7d5\nc/ASlf2MJfcaxtnb1JtbKLeFV4wxqlBv2iyemmNivIyhe6wf9Bn6sH2vR7Qp6d7OmGlMsTIzgwxi\nbFxmm5McrEPWcynaRZaXTmCVygz7EqekIUs+cqqDUfYJRJt+HpE5IbXjZW5dv83UrMe5x5t43i7F\nRsSHfmqFPIrZ3WxTcUp8+6uv8KlPfQLbqtG+BOqHE+R7s5wrfYjObAXhl5kbFlkp3WL5/7gN3mu8\nY3+frasSdWChBTZVvUwwAKNeJjJMdKtAJ2jh1nQMBNrLx2j+9mdRe6e4ZrdQKmHpQybX/LfpGQFB\nnFMsFRG+QvYkmiG5dHOdV66/Rjvv4lZzBAK/H0M2yfqNAFtNU2g0CWJBbGocdjvYXkR9sc9Hf6VA\nPnmNPfUmsnmXZOEGhZnbrN19jYoMmI0XSLIWR5hAkwmxI1lt70DRgKjMZjhA16vstnxOGONULfDM\nSWrZOLlmUqHOUBg4chrfjFBpg31CJrwTaFGDpfUT5O9W2buVMExtslynubDA7VvbqERnUk1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Kcf4yEewaxaeGnOAw0HbeNHaO4b8PjHUKc/jP1rig98VeeG5XA3ynjTDtj97w/5/ISG+f/x9l7B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2QNi4MTg1xfu0rJnWADSb82xLXOBgP6BLW1qzhWdtfDZqn0PEEgFExNf3ep2G2i2rXeqIoK\nfMcjD7u2FpEkJIlBy5O8fvYMB596kpN33c/KVoO9k0co5ibpeKvUaqu8feF50qkcCirHDo9y752H\nERj02gmVap0oFKi6QbNTp9OtU63WWFld48aNa2xsz+NqKp0kxlASgvWEu07cT39ulvGBSUp9o2QL\nBUbHZoiiFjIs8sIL32Bq4iW+8ezn+NqX3uLeh8/y8GOP8eUvvsnCYo8weYlybYWUrrO5UWGn0aRe\nkXSTKk5pBLEdcv7Cee44ZTHSP8Ov/8rP83/+pz/l+vXLvP99j2JqOjcWrpJEKtu1FXbqGer1L7Kv\n9Siz+xSU6ADdaJmsA8+/8AXK5Raf/PivsP/AYfrHsrQ2arQaO7SaVRKpoSt1LNOlXl1DQWF9a4P5\npW36hibZqXnkUxaRSG7b+9hdLrjd0nQ7O7MLslN2f347TK0pOghl11qlSJTb1PAEgZKAJEER2rsL\nZSwUUvZNiq5KX6CRtQ/RafTQNY18OMMFq4+5tb/kN07+a+xN+NbIKn+9dZZfUceIj32Me9dXeKFv\nkcGtNGupecK2Qbp5k3LOZqJrsGkpFBqgWTbN2EPTFHTD2FVm5G7ehCTZbUT7rkwG/Nc5Dvnu95Pb\n2Qz5XTW4/5wnTgkcxyYJ02xtrjE4OsqV0KfZcsjdXaBxK6FX6LDeBK82TZoxVl+t83ZdkgwrFN5r\noZr9NKOADZrQExzNFmnrKmamyFatQirtkRov85O//JP80QcXWPlGhjXbYrG+jk2eInvIlO/k1m8J\nwg2LN2pVltwub7a+TPHIIJnyDqruYk72cbfxIUpbfQTKJtfiFyD3zd2/V3yd9IEAHclUocXK5ZBw\nNabZraOINEldUF4KGZ30qaYkIqewJbdRtkzihkMhmyfuFwihoWUgqEToKQs71ul0TSxhYyoWmcTk\nC3/8FO/73UFS0kK3tpFKmZFjOtdufZn9j3+YbrPOxMkEqxVxT3Q/X/pcg4J6mPWkzNl2m+cuBBy/\nmifMZHh4fx/pfAONDnvNNL3JAfb/+r0sLAm0Ez+A9BxePHOBLj0yJQvHMCm6AUdGTnJq7xGm7urn\n6rlXUXSdK89d5rFPDVGpdqmu5DlwPM/U4BBnz7RJ/fUm6cMhB+4ErzzAQO8O0p0OF9ZUbCqMlqZ4\n4Cfz6GaW2sI8l9cW2BvPcPN8nRu1Fzn+sIKI1vDtBvf/+MPMPPJe/va3N1j79ga33lrHW3QJXJ3g\nUWhtrLM/s5fMB4fwNlI8mQR85pdOsOfegE70JgOFACkj2n6e+eU2idFHMhHwyI8MkVe6NJVbOGUV\nY62EXhkiJoNXSPBUSaD4HCyF9EoNVKeCYngUNAXFgNBUWO20UDM2pqkQ9bqItkY6a+Ee1hmwffav\n5tjZSohqEl1TMCwNTdGodLaxh0LW9C3adRVXq5DT8jxy+hHuPHaMy5dv8eLFszz2CY1UymRusUV7\nNWCu2+ChfSETG0P8xEMfIUnleP3p61w4O48XhlhCxxIFgkhi2Rl6Nxtk7Bxxw6e6WaEjuihpjSTR\niLo2c2fqDDgu3aBOrFeYvTfH/iMW3cV1gk6DrCFYvbiD+40W7n5Y9yFyvi8fFejCQONVJFUK8i6q\nYhYhfDpBnZ4MCVSPTH6H0miKdryIolosXPN49q91lP+HtzeNlSw97/t+79m32qvuvXX37tt793T3\nbD37cDgUJUo0RVISJEoaW5ZDyTAiJ4YMOIgRx1SAQDJgBEEgJLAcK7ItUzIpiopkDilxGZKzbz3T\ne/ft9e637q296uxbPlQPKfsLRQPM+/HUOR+q3nOeev7n+S/bc8h5g8fPnubhE00s7S7teEBTe4o4\n36FU38fv95EzDbe9wsb7DcYlmVFPoj7XYvq0T+7sM2aPLE9BTNK9B26XNA0wTXD9jNHAp91JufFt\nle983sUZPMNCbYU0CDDUCoPRNtdvbvAJZQ4tnyYiJGSVAnPMTsVUfvKP2BzPYkgzSOUiQrg8/nPP\nMGwv8eq3dLrrA5bOLkLSIkEiQtD3HK6ehyg3cZoxXqeMLsVUSu/QEhfJaLJ2Q6PecPC3FzhaPo6Q\n32XxwT6tfBrv/bNsXRlz+Wsyj//UGfpNiYtX76FU9qkt3OTUxx1OPmVzYxChySbeSKJ58ibLzRoi\n75OIIYPtHcbXjvCTR/57sp0SW6Ndqs02Rx9VUMs5L33xVRq3HqdUeQR1+ZtI9QINA26st3n7yzoP\nP3OMpWfeI7BXkZRFrOW77EQXEeYSIzdlbb1Lxc0JPR8pipElCUs10KUy6iDD3xxQkGUkLaNaqICc\nksTjSSCfBLUlA9ERxAMFyWgyUl0CTOJyiV7rFl6UsdQ4QNhPEUKnoBnEeUIeDtGVDC2d/J+KNCZN\nfRRhIRsGCeArOdvDLgWtgKpPEWQqSqRQyGZRY4GS76LYd4iCEc1lG3+0SsUZo0RnCUePE23G+L0O\nqqQwyrcZuTG5cNEUUKc13FHMTG2JfARp6tNoWDz23FFmzjo4yw5ZRSYRQyznMF50EU3rMWc2MP1T\nmOYxtkZ/wdBTCPZnMEYL9HYd1kfvYuoG450cwzYQeoQ72mV6sYBWNkitMXkWYKgGaS4xCsq0tpdI\ntqZoDnS0podeTGivtQn2YtytBq3NIQXZZniviB4ZKIVNRmGbXFVJIx138DfTfcqf+9znfuBJv/Vb\nv9UE/r6hO5OUZVLyLP5eYJim5uiagmASkiaTE8cZmpSRM+G+J2mOUBQyBIoQ6NkCWTZG5ApC20ES\nYJsNeqN1qs4DRGGdO7cs3npV5rVXb3B76zxx6iErBqpavh+k5yKULYRcIpNDhv6IVIon9p+Khh0n\nlOtVXl+9yMkDDWRJI7SnecCY4/XWLRx7msXSFONsh5Nxk0ZTYoUi0wvLGIpKGHq4kY+s60QINCGI\n4wSRZ0jSpGFV7tNaPmjwPlgf2JVKqoYuC26u73Du7HFC1+XkAw9y5951MnWI6wYYegHHnqJansXQ\nqmSZBKnMzdVVCkULRU0xLcHy0hKaZnHixCGOHT3MR57/CU6ceJQnn/gJ5hYWmGo2yJWM5557lsef\nfoLpuTqmZVGtCjTTIEp32W2tk2ZbXL70BqORx2ztKXa2B5RLNdrtiOd/4mHeemOdO+stxm5AtTTP\naGSx3Y0JlQI+fTbvDXHdMRIyhpqRRiEnj53FdftIkkyO4NDKCg89+Bizc3PMTT9IoViiWlpG1lws\no0YQ7HD37jXeufgmRw59iB/76M9y9PgieT6i291j7cZtPM9FklI8NyFJ+tRrS3S6WxQKRd45/y7v\nvPceilHF90IsSyfLJzqGiexCur8L4n5M3feF1Fk+oVVNYIeEJMkokoIQ0n923WQPJ8cmhwWKBOPM\nxI9k/FwwSn1cNWA/7KEXPUx9l3J2lm8Nv8VXum8iW33OiSX+cPwileEIb0bnk+pn+Eb4Cov2Kbr6\nNolZ5KCwWc26zEtF9vUcVdLQFOl++vdErJ4zoXYJId0HvPfvtfuTmg/uwf+STvXBOTkZUewC/N7n\nPve5nb9Rhfgh1gd14slPHyMbjxF+gouP5pVpXzMYZAaGI6PlCtUpk9mZEg+cnkdkKm+++g7lAzEf\nejJHDjNqqYWsw52sS71k4IoUO6uwFytsdAvka01uvXKHh5sfQVw/yf56mffcgCE+B8tLGIHDOC+w\nI6vcHKS8lqzhl1L2WONwwUZe3+eEscRJc4HES9jYPc+n/nadc39vjHzgEu9e+DJ2LnFqaZ7aAZlM\n28asRjz1iaNs7bv4fsa4n7K9s89j5x6iq3eJjTK7d3yi2wX8PRU1LjPqpERjlTTV0FUdx3aQY5vQ\n1VAyDVKJKFfo721hPd3leFWjL4246o2pFRpceO8mx58z8Is3OPJkyEDZQSr1KZ3UmVkp0ayUee7p\noywcUJiZlVCdmPm6wBUdhlELxfFpcYsOW6wZNyifUVHnEtp9gTmoElwqUZ2tcub5gzz0sQrW6Q5L\nT8H7a29y6tESV9+5Tc81WJgr0qisMPItqnMLmA2Fa29v0loV7L1RoHT3KXa+vsjO1WlWUxNyh0/9\nxkO88D89ztEHZfLSPpf//CZmovPUU8fp6i1UTTByfepzBnqhTMk2sUYFKpHKuBPT6W/RjTymZnIO\n2tOULZ2iXGGj7bHXX+PIE2X0uote2WNrf4utS4KtmyHjUUroDigdCnmsdI5utst6Z4ONVzTcqzOI\ncQGzWWY8HZFaOnJZYnHOQK17ZMqAROmQWgGZERE5OZu3Q/REY0qZYcpapH8rpVB1sEoZ3miEqqV4\nXYE7iKnWCwSKR5IFpHJKoseUF1Wq8zr1eQuhpNxbX8VLI4qZxtrqFuusczfYQtgqjj2NMljCuu6z\n+q0bnJwpUfrYwxw7WOLCnRv02WDojWntdbDCBuXaIfpbKe5I5ta9LXJHYWyGJFaGL6WYdoOd9YQ4\nMOgPPJoPCo59xKQT75O7EsWoQLVk4mcjNrZv0I0yCmVwO/DOt/iR14pP/3JApZoiqxBiMAxTSuqz\nxL7JGBfTOEIS7TFzrEd1GXZ3xqxf7XD3XRMtforpgzozCyU2Nq5w+CEZw1HQZYErbmGmp2jfXGDj\nugTaDGO3SJ6kKJV1nv1FFW1hk1DfYJSP8PwiUpYSZy36/pBYS9npyOzcC8gHRb7+7wLWv/MhTP84\nlXLK6ScUjp8dknltgjgkjvZ54JSJUdjBsW3CZIWC3ECihaE7KGYVyR4TihSHEcLcpOvHvPvKJrm/\nSBx71AoBh562SaWYURQTjxo89/wK5eVV3n13lTQOmFnZxphyEdICF18P+Ma/9bj01WuU7T7/6H+b\n4tCTI5aO7TKIWmwMBvjjKu1bHTrtLUqHCzzxMxWOfaLLwWeL9LILWEZIt91FZA0Wp5ZwyCchysLl\n8lc6vPbFJquXobd7A1O2OPJAhnr8MvVDLp78BqPdOqvX+zQqpwjHOrs3mmyt7WGkZ8G8y4EHVDJl\nRJznhK6gEPy3mPE5bt5+n3OPHeGtu6+RmwlhEmEXLYaxh60VkYMICZdyNcOuZCRyRJybpEmGZdsY\nTki5EJIEKf0NlXhskaigFSqgTCyKh70BM6UmjqhQkEvkYYYsZEzdwjRM1EwiiVP8LCKRJdRaEWFp\nhFKCY2gMxnsIySLPbEAgK4KAmObBAnkhRitIpGGGfzMk7ShE60cJ2xb7VyQ693rgVyg787S6d8j1\ngFgO2e8PmaotIMcauQdF3SEPxhw/cgBBSmW6weHjB0hkjWqlQJDsgLJFnky0pLF6FadmolTu4WgK\nG+dD2qtTSGJMufAAaZSBEiEbHrMnB5SO3KKy7KObUCxIVK150tQhSTOCoUe8fRp3fYpxS4JRiWQ4\njd+ewdutM9jQ8boO/kAFkZFKLRRhIQmVPJVIE4k0E2z6d39gnfihgIZmWMiSQJB+r3FRZRlVkZCU\nHCEmswRVldFVhTT2kYRGHCcToAGkWQyphm4OyTMFSUkZtBdpbRncuD7EUA6xenvIm6/FXHi/RT/c\nQFIFhlFFkicc9IlvqSAXEpKwiPKEIAoI8oiMjCTPJh7KmUQrdpmTyww8g3ub13HKMee3z/Ph+rOY\nyZAg1Cj4Np2mxI1rq3R0ia31K1SryzTKy+iSialkSHEHFIcsTSZicGnyhjy/bycK3Acf3w+EQwiy\nOEJSdVQ5Y39nm2NHDhC4HidPP0AS6ciiiCQKxETE2RDZCMlSlyT1WVhaQpIUJMmkYM0jJA9VbRN5\nAb22SxpD0ZZo1GUeOngIOQmwkTmycBQjNilrVarFEv2RTaNRZTzU8ccuUSQwtSm2uy8xU32IX/7b\nP8PGzgWeePwJvvQnf8CRE/PsdfsMvJB7m/vc3rzL7d0Ndrq7+EGTE0snkTWXIEqZbdjs7V8hQ+eJ\nc4/xxONPMjczj27YrN3bQJYUothD0+SJzkXoBG5Kmko0Zw/xxLMfpVYr44ctrl56ne31dQZbYyQd\n0jRC1Ww8v0u1vIhdUvDcBMOAr3z1q9xd30EoBZIsRRHZffbaB1qZvy5mzLk/1CDP7k82BGQ5iPz7\ne6UokwHfhD71/QkI3J9cAWkONUVCB3QEUi5DqmIYJYaDmJans6++y2fqf4dG1UDZ8Dh5+CgfVz7F\nth7x8t2rvB5+gc/O/BqFuMeh9FlKVpGL3S5PFw5yOdijHkqEREhIk1yXHIQ8AU8Td7bvp258IP7+\n6+u/pEx9ADyyLCGKvR9YFP5r1wd14tShOdy+y8ZuF1Mp0NvKuHl1QKIZuEqfA/M15g9LlBoKyWBA\nFIbstO+y/LTO/MGENJeoKzmyE3J9J6C9bXHz0pjcXMDKZ1mI5lm2K1y/tEPvqxYXXzQYOHUsUyMO\n9lmYMRE67Mc+Q2PIdrbJ0uIKBdlgalSk0bd5LDtDyVU5LGwqaZ8DZ7bpTn+NeGmVY48oOIbM8vQ8\n40FIKkf0xrtMn1R58MijLByf5cLbW8iSzPXz+8wvz5MlDbZuuejDGfYvCpSgQe6ZyJIDsUka5aiW\nhshTUl/G38vIYpNM0mj3PSpNmZvX93nop46wNZC48JUed14bIUuCEw/aVMweiDZ64uP2OxDDeBAw\nN6dwclGmWutTmPaYP6QwPasji4woMbh1o0saqtxdW2e7u0d1KkKXdWZnC9x4ccjLF17jrDPLc3/X\n4fhpH7WxiqEO2R7cY3HWYc6e5fP/8jKPPr3AsaPLfPM77xGMXKabKk5DZvvqgBf/0GXwWh3ZPcTb\nowGbZsJzzaeZeiTkWv9LHF0aoQxS4hsW7csJD354ltJCicxqIacJqZdg5xl6lk3c9poR5RMB+vEU\ndSrALmU0D6kkhk8r7PL2K7eoVgrIScCg43Pj0oCtSzFyXCYaqljWJM19bhmM8Ryu9jJbPYvrryRE\n3jRKwUHRFRKRsVCtcXBBRxM+qTkmlgf40gh7RiLXcrxIxt0G0XHoX4qJtiXygYa9WCBSAnIzgUwm\n3APJ01BNi8hPSWWPUtXAUHwKeoYl59QLKoeOFhG2x+0L6wS9BL2oY2Di7nkobZvResyxWpmCKpG4\nbXbVHe6svczW+ArOTIRXHSAZLtcv7tLZS+n1MqoLVUplE8nJaStdBsoAp6mTJRIirJB0HYKxiaRo\nHHxMZ9TYQJg5im6h+Q67Gz282CUzAgoFhVLNRveneOnFwY+8Vnzkb2UsHJonkAeM430KtRIztQLt\njRx3qHPnzhqWWkDWdTrtMUpc4OWvX2O0o/PJz/wtnvkZjdMnHiYdKMhWC71sItt7hGGRK98+Q2dj\nAUd/EE9KOXTwMK3uiPmjcPzZHfSpGwhNxg0E3XbI5jWPYUumH3u0xzLD9hxxr853vrjP8JrK1pUi\nc/Njls5d4GO/GvPox/cZaVdQihXWN0Z4o4yafZi9tYiK1aTbbVEpPUBCnVzKyKVNHCSgixeto9oW\n61dCBltTOJZG2Uw4+kSJwLyKpGksLc4xPTumsnCDUXyPm5c83ME0VkMQGVd479s+4a1fRNpeoXGg\nxdSRIxSaOSsHTrG+9xKis0TSW2a7vY5amObcT1ksf2SN8lLGIL+FLK1DHmHaGf1+gGk0UeURiHV6\nbY9X/8hh88YTPPahT9Pr9akVPR55zERaHIFxiVqzSJyN2dmscvl8n3G3CFlCFKQsNp9l5eEN9Lk/\nZ+h1kYRBNMj59l/47K62kOKA9bUdsELW1lcp2wXkLEckCUqsIjIfs+DTWAKnKRjnKbIWoJo51ZqJ\nYYZImUCVbeKRTTwqEaU5oSzIVY1ypYic5syVm1ipQTJKKJo2kshIogQ1U1AyQdWy0JMMkWWUiwUs\nVUWKU0hDDFNBU8qU7TqObVNQY5Rgn2atiJ0W2Lyusvl2FbF1HLZO0r1ylO1rOVm3SJ7omEaO646J\nXQNNUUnjEEevkg0S1FxF1xVyKaNRKmFLKsNWj3vXV9m7u46q5EheHSlNcQoF0qSOH2QEcQtvILN7\nSyIfptA9STxQyQmZmTpInOrY5RCz1mHhdErxQB+1lKFLJTRM/KCAKtXR1RCpbzC8UCbtnERLSoSd\niK31Fp39EcPBiKHfpVZbQNcr1KZMRl4PJUqolipImYxpgmKl3Gzf+oF14ocCGqZhocgfCE1TFEWd\nNDVSgqJk6JqMJAk0SWCoOpoGApkJLBDIco6uapi2h66W6Q5DNm7P8PpbLd55Z8C1W33urXbZXDPo\neTukSpc4N4ljgaSE5LIgCDOSTEVSVDKR4sdjJAnidGIRGiQxWZIgSDEMGTOQGcoRfWWTQJYoaU3i\nYcabwSuIUp1W6zzVI7OUd4bMLR3igFagXDqKO9rl5vo71Comrc4IU54h0yY5C7IyoUqlSUpOfB94\nTPjvk9C0iWZFkhQ0EjLNYhzFeG6f+XqZgm2SpX0QI1RJR9MUZFVHkQu4I5NGfZY818mBKPEpFDUG\n423SJMe2Zuh1WzQaJQxdoVavQSZx8frL3Fm/jmobHDx8AjSDRElo98dU6gqmUUbRXchl9nbWWFyc\n4rvfvMXM0ojp6hmmKmd5/a0v8Nm/84/50h9/i0OHzrHV7nB3e5N2P+T0A8/wz/7J7/OJT/8G3v4F\nLl57F9W0mK2W8cceYewybnfoj4eMRiMa0w1q1TKzMzPMTM8xVVvi+PHDNGrL6FaIZdsgudxZ3URW\nxqxv3EHXbKRMxzAU/ChGVhRcd4yu69iFErIsEwQxfjDgxRe/RnsUkOTGZCJBSpp9EGw3ARrfC7zj\nr1nA8v3UdiEEspDuN+UfUJA+AI3yJOcCyBFIYuIyJpHTj3MiIUiknExKSTIfVU+RZJ9E36Taf5hv\ntv+c63u32Gz0ePPuNl/zv8a2u8pvHvos/ZHEK70v8168ipC6OKLELy2cYFN0Oa5NM5oq0xoPMTRB\n6HnoqCBP/K2jPCbPP/C7ngCoXIAsJNL7YvDvWd7m2fdcqwDSNCFOfvRAo8kUVlYmGprIURFt0CTv\nVBhmgvFmTiMtoWgJQuqz9uZd4lGObmksPurghW1cLcPQIyzdIB4ucOXLJdb/U5XXfjch8edInBrb\nF3Iu/v6Aey853MHEsJoUVJ2aKnASnZE3Rh0r1MsOadtj0Vqgv7tPoaATpBsoxR6Rf5O558e4D7zO\ngc90+M7dP+bm1jt8+zvvs35jk7o+Q71YIulHJGKIFw7JdY/WIGJjdUyuWfR3BKtv9lkoNhFjk8Ga\nRHstwaLEeBAT+hJRKJBtmfqczdrWNqak8MADZyioBba73iRPKMoY3fEw8iYl5zSDt23e/P07PHSu\nQenEPlOqTxYOkXNwZiJcpcPm+nWe/9Q0wtimtNAhMTcozLuUSwnd8ZiicYy7l1MK8TSv/9UudiCo\nlj2qZYXhXsjXf+88c6NZnvp0lekHdimuXKOstUnYZ9TP8DciZpwin/83N3jzrTba7D6nH5zhk588\nTGPG5fSxIsW6SXbPYLhRYadfYHwso2CW+dDiaaq1Iap5i0NSRrCVsPFqwsbOgLLlcODJJnPzFgeP\nlUC4JMMBjjRmbNyj+BCEzS5zywpKaYzjJLT72yQ23Lycsv++hB6UufZuH3/fhHUHK6kx3BekpkSW\nxpjLcKgmE2gm16I7rF31GG6UicdzZJ5OSVjUCjIzByW0ekgY77O1t4qwI4SZ4ho+w3iIpCjUrTnU\nvknrQsJwC+q1IsaiTGak+KpP0s1ZrB0g2NV59+0dIj9n5YE5RBozt+LgyBFLTZOiFaFIPZyiTxam\n7HW7JIHGoXMrnDh6iqxt8bO/8CQ//o+f5ZXvfp7s4JijPzHH7fZNnGmFh358hrMPW8RVjxOPLCN7\nFRSryK3Lu0Sey09/+ghnPlFly9wgywXbFz38LYu4bxP4AjXXmD+lkZS3qFsqUTok3XdYvb5NZc7m\nwI/NcPLUPNtXe7z8+R1ureU/8lrx6Z+b5+DxaRK5gywyMvpkQiLZO8Jf1w0+AAAgAElEQVTW+5uM\n9yNCrcwrr73Fg7OP8N7Lb3HrRpXP/MOjfPLXHSpzC1x7Xefa1zoI+21OPCOjKbNEW9Nc+EtgdIjF\nxXkk2Wdwq8++GHP0yYTmyh06wQ6ZVyTasVn7lsrlP/NJdgW5WmQwyHj/C23uvX6Cjbdq7I36nP3I\nDh//ez7nftKjsrhDqRyzeAo0u8eolbFxKaB7Y47x1gGSvXOQHkKUh+CEjOlSzZfQ8xykHmE+xLFc\n7q2a7Kw10WSDxfoUxYZCY9FFSH1y+RUysYeQBdOHYja2yty9q3J4aYVsFPNn/zpgvDmD0vwaL/za\nwxTqAcX5EFW5x9KhJhutdcb7FZRwiebBkCc/KeFXv86efx1LtxFkeGmfXqfAsDdFNjxMEI/pheuo\ncZnO+jGuna8RjDP23QFaS0HOYpofURDiLXQ7QpkZQBZR7P4mj586zfEfe53DT6cotVVGw0XK5jwo\nq7iuzFsvuVj+C1SiEm5rjG+MePvme8w2lwjiIZEUkkUqBWHiOD7NoxnLp2W0qkQQZ6iGiuWA4oyx\nDJBUqJZmiL0Ub6tIVTqAZUsYjkPsqjhqhc76FisL8yRuSpIkDP02pYKDmpgYkoasKvR9FzfpkqsJ\ntmbjRaAkKapcpGI1EZGCKkuINMZ2IB0VGO8I9u9EpPsHMLwm9KqISEXK6gR+TNGpMRiBl0ZMLZQZ\ne2M02cFSDUSWUavWcEoVFNVE1jVIFaTYQZemaG1HXP3uLe6+1Ubxi5RqBmbRJk2LNJ1HSa8/yuUv\n73LvrR5rVwaEnZSao0FcIpdHzB33aZxoUTy4hVnLUO0GQrMn1r/FMrLSIFyrc+VLPv7lGLfvk0cD\nBp1tLM1Gkcs4pUXmF05RbZj0+pt47hBZSNi2NdG/GnvMHIkwp+Ddqz8YaPyQYvCJo016n9sWBRGq\nJiOrElkuI8sKChJZnBAGIaosCIMYVRMkWk7mJtgFhV7b5nY35M6azN2t99lvj6kWbSq1GnJaws3W\nGY4icopoWoqqR+TCIotB0VIyBoR5BplMnCvkaQySjCKDInRkNSdPI3pRhh5G5FULp1uhr3vs9C/T\nJeDc1HN0Wht0ZJuZdY/vuOc5kB1iy9vgwfJRKqUqU7WPMswzCs4lxtIeUmaDBEmcIAuBpqokGQh5\nYjcq7ofBCRIQkGYRIs1xB30qlRLDrsv1uxssLC3gXYqYbR7i2AkLN3RJch+hKCwfnma/tYZVtEiS\nFF0YiNxAyhxSQNclFKWErJQY9fsMu3tsbtzEVKsYeYUnH34S3/XJ04i93R0q0xVc12FmOibo56zf\nex+nUGNvf49feuF/4H//3RdIki416xzvvXOFv/yrf8iv/OovUS1b3NmWeeShT/POu2/w7nsvU639\nMz7zC58jSTY4c+osN9fvEgY5SWSQIxFkAe7+DuVKnfPvvHHfAUlG0kaoSoE8KZLnY2ThkOFjGzal\nksa1S/sIBYbyAFVRKTszRJlgqlEnI6ZYmgT4qPIM1UrO1es32e8OkGWDNIkRQkbRFKIgmqTOi/vp\n2UK6H343SXz/YNIkEPcbcsEERuTfy6HIc4EkgSyBlOdomkYQhAhZAnLSTFBVE5IsRhYKQZxiKAax\nmxCkBmXrNL3SdZaVp5Byl/XhOn93/jFe3H2dXzvzWf6Xt36bf7D4UU4Vf51T5kl+787v4qib/POL\nLzJrHWVlxuTMPny0+dOsReu0yh7vbL+GFuioeoomCohcIk4iZNuAIMFJBV0pxlF14iSZgCJAIEGW\nkzGh+snyD+dm/V+7hldh/U6I78GGElMWBTr2kGFzyF66z45nUIxkRkFCa08HETO1Mot3O0Cf6+GJ\nFl6WY44ttr44z43PG2j3lqnlDQrvnWH73S6lGRszOoiLhCo8CqUU0xTEe0W0ocERMYsv+iyaGnXb\nwWz1mJUSlNmYbX0bt56wfDIiOrqFpt7A+ZDDz59dJk5U/uIP3mOqcJA3XurxnhigqGP+/u/8GNd2\n3uTChQv0Ap2TT5wkDSymZxzefukSf/If3uPM400OnpijuFLFGySIMEHWNMxqmdKSip8FtFp9Kgdm\nuH79AqNNCSMrYVRVvEAG6rz8px7K5gzVmyvcvPI2Wt8g762TeAZqPkdDN7ELPpeutZguF7Ezn0QZ\nkltb1BsxuRUSmznZYIp3/srF9k/z/qtt4nYVYzEm3xVkSsi99zZJhc/xZ4pMnc2pHvHQRBsl1VAk\ng7SfILkK1UaBX/zsDF99o8Xrr3V44hGdpx6IeGP9PfRIghB+5Z//PF//HZWvvtVhdfcOtWSR7FjC\n5Ys9fv0nHsf0JYr72yhmgrwgcbG7xfjzHmc+NUaO1vEKW1T0HCnLyNI+JgHyUoyz0GRvd4cgNLh7\nbcz45ZSdWyEimKY7jJCoIpJZzD2LQmIwqtxEEwOycESjDEnPIJ4esrGRc/c9maxvgKRQqTtonYR6\nBnR3cRZV5o6WWeYw/XGXgdelmMhYhTJ2vUQaxgz3VAJibKFRKKqMr+wRzbuIckbuygw8jyvXdrlx\nx2cpLJPsTWOWTOw0J4kTLFJMKcMqQDsWDE4k7I0yhsE66+sGaT3hXvcWXk3nrfMvsnfgAh/7qQeY\nP7TI7dE1rl1a4+iJInZFsLd/m0I6TdGqcvrRM6zf3UVVBVXbICiO+CefeYq1Wwm/+91V8n6V0UjC\n1iWMskX/xpD+tkT+wJhGs0kkxmxtr3Pqk89QPRQwZSmc2JhlfVYGNn7ktaKsHCYc9sAskud9InQG\nvT6Xb36XeDRFHCi05QGStMQf/cllSnMaH/7oc/zsL7TJ8hfZbj2EPz6CbhZx8ufJui55/Q5GM6Z5\nZgonGnLyUIm9P3iPN2+5HHj2Gf7yC1/EyuawS4J3LvZQx9MMN+tsX9lnzdhhetUhcwZcvBSw9/6A\nypTN8589zi//o20O1Dpk6Cg0SHIDU3Q58OgOK2s6rZunuHtNZmZqgSDvUS0/C3TJ8ns4aEgiIM8N\nBGVsVWEURyw+PGT11gWSzQPs3rS4/Q2J5YfOYRRexE+b5HKMThPdXuOB5/e4cdHj6itneemrHfLO\nRxGl8/yP/+tDHH5sAMSM6JAwxjYLPPVT03z+jRZbu2NmDsywey/F3TEZtJtcGUcUlyMWTs5SK8+R\nejH/8d//JYeXZ5lbOEdnrc87r62S6TPE5SKqIcGowrsXXiL6f+9y7Mwi06cDasUlahWdDe//ptVe\nwjTeRCsFjDaXSKOHCfrHySqnaO3fonf3QS69ep6GMkVo+BRKTWyryHDQxtQS5FRBzy2KBQNzOqd5\nzMKY9oj0CZ1WViJUXcIxTDRZIAmNVM6hKlFYUNG6GZawyeMKaepTb+RcvneFbuKSF+ok/RayqlB0\nVPzIx1BL7BERC3PywjKW0DCpKxYKGsWyQRzElEpFHKvAqCew9Cq97gjdMVDELKrdxLQVRu0hC4eX\nuLF+gyRTSAwHoyzwRzmjUUK1UKff3SdLZGbnDqGZJpKlE6Y5XgLhMMDRDcKhi1WcJ48yvE2F1//k\nm8hOwtzHlinVTuAMD/Lv/58LKJ0V2nsZhapNlN7j3ddu89GPT2GUyjjNOlPHt5GNCmFaIR9VKRdn\nsJQ2aQzd8yVe/cImG5diTEkmy1eJg4xyaY7ebo/GfJHeRpewlVCveTjKAHk2ZeWBJQxT4EUt9JrL\nzLLN+u4mfPEHP+c/VOehaSq6plEoGKRxQp5JpHmKH/soAcQSyEZCJuXEaUwSK+TIkEuQpYSRYNDP\n2V8PWduUWHe3GcYCvaRhOw6+N2Yc98hREaqEEGPyXCdLFISIyRCIVCbPFBA5aZ6hiJggVyBLyBKw\nDJMs0wiTECMKyQwFaRwQGCl2LhHGBlWtwHvrbyIrGoYks6btUBpUCZQESy5z2WuRtq8xXS4z6KSU\np+qMd0bYxQQ3HOEULOJRjGkaxMTESYwqFLJMTPjzWT7J2BApqWJQ1CQit4dumqxutvhpp4wIY0bj\nPnfXb1Nq1HGcOp1OB1PzMOwGcRQiyQpjt4WiyhQcCU0vEAdQrpRxRz2yxGd3u4Wt1WiNd5ldnObW\nnasYqoFuFyjVmgxHY1amJt7pG2s3UDSFvb1VmnNHwTvPZ1/4p7z0+iXu7XyXR576NCdWFvnaV7/E\nbmeTB4+f4md//uPUnBL/7vNf5J03riHif8p8vUGWjfFGAbKakKYBu+0BnU6P5uwsq6tXOXrsGL1e\nlzSViEcxijKGtIeqOaRxH9PS6fZHDIYFbEfFMAxkyaJRn0OInJlyk067zdTMDMPhgFKpzHbrHrqS\nsbO3S6s7wnDqSFGCpqqEaYaQJXIkkO6L9bPJXghpQof6gGI00S6kgExKikC6/9b/A62DhIQgTTMM\nxyAO4/shgRF5nuMLhTzNIBfIikaaJkiShK0KwmQXI2/QCi4hSQqKZPBv1l4EZZ6/uPQ7/M9nf5N/\nefWrnN19nz8FpmcqHMiO8oln/huG2zf4V8FXeKPnUtH+FU/rp3B9l9+Y/UXeStqc330HIx3T1SRK\nks5o0MHRKoQyIGKyUEUo93UpuYQguz9hS0nTjCT9/8fedlafoWGVSfUZht0B1eY57rmXIFHRFJ+9\nwT75VoiUqYSJRDbIqRTqtM7nGC0F75pBbUFjb32Bm39UQrlxHIV5puYeYvd2xsbugLKisrtdxyqW\ncFIXXbUxshKlMKMuSzRKPjdbN7AKPpLvUsHl5OMml5VVcvk6LWuD2nGb7OAQrTFgMGWQOgHSoAyF\nOoFfwg8lqnNFQlfiytvrvL22yideOEQQy4yTlK9+8RbdVsaBkwVGTYvO2EO7t4Mtp8wu2ygrDbxA\nJpINomQypWsuniBMYvruCL1mYnsWXpxQyot0VJeNocS7t3c5uncUSVhcuxBQ/pWIIzVBECqMRikD\nOaJgWQSqwe2LXVYenGNrOEIy+qiFjBdfHPL86efYfHXISeMIO6/tU3noGGQ9JC1h45rg5rtDytUZ\nzJqDdDhGqiXs5x3ssUnHT9gbZyw6c7TTHR79WAPtWIBip3zjq1usnDVxFYVRHjN9fI6d22vc3cx5\n7tSnUC6tcF5cp39XRkznXGrtoB8xYUlFNMC751FKLcZbMTcvQDIIsZYFHTmnxZBRBHa2S+CZLE/Z\nFIZ1bl72iG83uXUjIQ2mKMwskNk5pWYDd19wKFtC3ndZPHGAsHgRcynDmdkjHgnyes6f/wtYCVLM\njUPkmYQ0rzH3mEqtlNHL2/RTHzW1KTYyNMvEHpWwVInhuIOnxMR5hjQrM3U058CyRXNOYXMQMd7t\nkXkGjGV2WgPcAKYW67gjwdWXE5768WPsr20jzB1mqyD1e8RBwMiKkQ41cNopInG4eeUt7mxdJ5B9\n+prO3vA6Cx+OuH77dQY7XfZuhfzlFy6zdvc2J547yIHaIT722D/gG72v8+I3z+Ov7/P0pz7MlFDw\nRxILFLl2a52PHz3NkU99mFvXU/70P36ZbUJUw6cxe5ydnX3U4w127rnkOTgLEWQ91DHUtJTlhx34\n4x99rdja6nK8aBMFNdqtFlbuMK09gbs5xNu1cbtdPDVienqJsnSKlSOCp37mVch3GadNZpoZm/UA\nrRziTN2hOiOzITroKCz+5B6Sexm5uEdHf5/ZA4/y2qsvUzUbXPuyhR4coJieoe8N8fQSe4lGP7HY\nfr/DXkeh0nyBQwvvE5tXOHuggCUyQrFCzJg47jOlnGGYqZiSzjjbRDEEZmXE4rkdHvmYjzX9b0Hq\no+YzjNJbtMUOlqST542JmYcyZPGxPrMbLi/96z5T2SHOv7yPeTznqV9ukodPEdm/TT9fQ6HE3Eod\nxYn45jdusHXtHAcPOJx5RuHII7+Ex5eRUMjxCBIfoVhINpgNj0PHTnPh/QuY5Rl21mpU+XlGWY/T\nP3OF+SfGRNkGJ5YlXvjMs1z57gprby1TNDWuXvw/ePKhp5HLC6zd/Tr2tIN/e5/C58+g3vBJgveZ\nXlSpL16neDbi3tYsM60ZrKpLaX6De/tf50v/1y0eOOtQNF+gLh1joebS373Bdn8HgYWQdSygpBdw\nhwGmbEOaohQk1GKOL48QqkSprhCOYnTFhAySXKBKGhk2zZUyDeUA7u0p3JaG26sS5zfxopRyvcSd\nO9dYKBwlk0DTLDr7XYxQIpQsbNNipdRkbegRuR6hNsAs21hU0DOF8XAXYSfESc4oT9G0MomhUCjV\nGPZzyC18qqiVEkMh0YlT6tPTtHa3GAw8ZF1Fy1PcUQ9TmfRucSYQ2NhqHRSZIOwgTIl+4FE7UGZ3\nd5WwEKD0cyrSPO6djJPWr9Jqx3z3m29w5+4aL/ziT/PtVzr05A3SPY3pgwtcW73GqXOPYVNEUeuM\nwi7bq3fZvHaVqnUQXdQwkiNceek6g3sblPKztIMRipwhZINM1DCMIq2NMWGwgyH5uLfLrBxbQNP2\nMKRVrMUOMzUTxTlBXtglCtp/o+f8hwIapqFQLOgokkCgkGYZ5DpRpJPE4aTZERKZnJMqGUEUoukG\nUZSQZhJ5qtNpReztZXTdDFKTiqygSzJ5lpPlkEsCISZhZZJkIPIJDSnP8slnJKQiZeL6mZPkObKU\nkIiUTOSQTDISNFkl1dXJm2oVlCyZNITCJ85SdEVClifUJMYZkRqgRjk+OSWR45k2O65guqJxr+0y\nO2WRhDL1ShnPD0lFThwnIEkYikUSf0BTkeG+dmMiLE4RskQUJRSLRbzhiF6nS71QoVyvUa3VMCyT\nKArQNAUkiTwMMC0db9xnemqK0XBAFEUgNDzPxfNcEDmjXocsTxi6LkWjhFOw8D0PRE5/1EPVxszN\nHqTszLG7s45t6uzv7yHLJndu3WV28TC6iHjhkx8hjsf84Zf+A1dWv0m1Ost/90u/TZrKqNoUZx4+\nRP07MqORy8XLt1l6tgZZSgbcvrfNytIsmq6ja4L23j4L8wvcXr2BpuloukKaqkRhD8sqkCYS5dIK\nQbBPc3YGIWxkWSZJEgzNxA8zLNPGC10MR6NYNPD9EVHsUi2X2N/bpLPfJctTZGkSZKdqGlE4vj+l\nAFm6r2X4vvwCmGgVyCaUogm1KrtvKvD9JUT+PQcSIQl830eSJVBkiCeARc4hk8RkryZX3b9YmkxZ\nsghdOJOGX8ooFecZiH1W/Tn+xfn/k7AecGzm56gQUd/e58+9V/hG52sMU4dfX/kxxvU2d7ZsLo1b\nmJrEBfUlgv0+v7DyPG+6N9H7Ae1wh7pukCTQyUbMOg5BKMjz9L79cjaZaIjJDyBJIOf/+Xf9US2t\n5NJo2hx9Quetd120eJ+51hJ7voOwc4xKgmd3iPyUYRJTljWGvkTn/Yxiu4hhnETuVejdjrh4vkfM\nLkuqwpmTITutHXr5Pp6X0ZI9Di8sU5cN5K5CttdD0wTOCZeDH63g3fCItQtsdW6iLM8z99RxZuSI\nzTUPxZEgGaMHMYWCTTuPyUoOUl5Eq0VkezKRrrA2CHFKJje3e4RpzmhrwHr7JtPTBzn3BJgfafBn\nf7KNGEssVQ8zDvZIszZVEshc9vYVvNhCLljEeYipGySDlNOn58kzwdZdl/5ORNGuo9eLjDZ87iUb\nCL3M9Pw5rq5dpP4uHPkI+LmJLjvIJMxWDLoiontPY2F6mtF2xP74OqefPMHgyvvcbJl4t2M2xZjE\nt7EXZPpuF7ljE+7mqNIci7NF0jyh247ZdiOqdg0/0RkOM3JVQplP6adtjFKE4w2Zm1qidTSltWay\nt2ngDVLGtZirr17k9Ec+zMnGNEuLU6x9ZZO3915B4y7jl3v0hjJSAIOiiqz4pH2fvKCz3UoYpRrK\nTpksGuHoGoOhi63raLKDVM0Ybk2xd6uFMl5mwYH6zBx94aJXbNSqSqpLlA4YZG2XrDgia45JGy1U\nOWYgCXbeqqO+NyTN5om3Y8yTGsq0YFPfZG80pHnUxixYeFFO59YIQwHDUshiiawvI8yMrJbhi10K\nZwWa2mXf3yfVXepzNmpJx9/NMJ1pOld9sr2YUSwYhbDfDumvj7BnfQ4qFpETIuyAHc1DyA4zR3Xu\n3t1HzgUFo07sD/mrP30L+/AujyxY+GFKO43IhE517iBHaw/ivdFhY9hmZudd7lwbUVOL/MavPs6U\nU+Y7/+kNjv9kg9KJEzSGLg8+9TDVpSqNWspea5Fb6y12NzpYehFraLLZ1li72GNqtkmW/H+8vVew\nZdd95vdbO+99crjn5tA5A2jkSECiCEgaSaSp5NFYM64aP0ypyuXwMi9j2X5w2XKuKWtqXLY0Mx5K\noqVRpBhFEiABkAiNbjS60bn79s33nhx2TssP54LUi8vk2OZ6vbfq1L1nr13rW//v+34ZMk7J4hzb\n0GEm/Im8K8ZeSCx3CSZFTPdJdq8JLn+8T9g1uTl4B62xxNOPn+TYWY1ivsj28BKlWsSOuIUlGijc\nZO3RX2HSOQYzD+h5uxStHEUxyfI25TKkUvLImVn67/iYis/M/ON81G5T1jIWC7MY1Vn8ZIhR6uL5\n9xmyRG3eYG/8RR6bf4ma/XfovSUYLISUntcQ5V1U/T08bmGKWQYccP4JOHh7n4N+gloKCfRtCkqJ\nnAPUrISarRKrEb3IpWXMoAhJLCLKSYXTs5+jdyqifXmLelGlNj9PnEZoZsJo9Gnq5Sob2R+iayrV\nSpXNcMiZC69ScPpU5T/kz/5pxPO/sUx9to+Ciq6ahEgSH4zKFmOnwsLSk1z5To9Tx36O+bkar7w0\n4OQvu+RyG1OdIRc5C0f2SXid//I/WeeXXvmvqdVf5tK1b7LSusDZWp1Hn5rn9tFH6e4qbH9Jp/TW\nBr/8HzpUHytw+pUt3MEfM/ZrFEaLdDbKqP3PcsJa4Nu//w3OP3aCv/rSn7BYWSCXQyozJu9ef59S\nxSEej8lym6JwKBcVzKJLqalQaBpQqhJnMTLzkTlkaUzkCzKZIUSOQg9Vz9EWNhFaE81awBs1cMwi\nW9u7WMKmWLIoFgVaViXwI0qFGQwrwrDr7HeGLNdaxEnKMB4SezmKMqRYLKPLMitzCxwMO/jpGKWs\nsLXfQ9EyDBxwdNJ8SJhpxOGQ/Z0Qp6Syv7/HYLCDH6bU9RmyLEGVMYqqYTgWplakM54wGCY0Z1qU\n1ARpGFSr83h+ilRPYSXbtJo2S0UDuePyjd/5DgNPZ9Ir8sLZx/n+Gx+CYiImLaQVs+f2qVgGH1/9\nEClnKVxOCPoa3sCgfz9jHIwoVRq0xeXp/6R4kdzu4m8fYAobXVMZh30qlRTVDKk4JsKTqEZM5+Ae\nlVhlsN1naVBBHK2iznbI9ApivAx8//9xn/9YQmOmbtOsFdENIMsOG3EgCEN8TxInKVKmpJmABEzd\nIkkkmiohF4SRSr+b48camZajiQxdUdCkQp6lhFmKwtRnrgkFVRHIw/asTEikTKeFpRJiOa2ZFSgk\nxNO4r5w+gGTTP0sIbXqQFBKEgqJPJw7InDhPUYSGqkhAxdAtwjShiEbHn1Av1cjjmK1AcqyyhJeP\nEHHCOHZRDB3LsSETZHGKqk4PqFNrTgbyMHgsJUJXSbMU7dC2kiXw0dWPefbZpwlCj4k7JM4zSuUK\nqq7jhyGWoXGwv49jqbTbI2qVCrpQEWSEcUDoT1APrTy6oaLrNmkYMBpERElKtd7CyDTWjqxRLtQZ\n9Lt0DraQSkAYBTSaMxw9usydj19n4E34+t5d3DBjdfkEr538LE5ZB21CpbDKcDCiVKowU12AKEO1\nAur1CnJ9g2KhTJYrOE6B3d0dWjN1mo0mDx8+ZGlxjtFwgGGbpHqIbSySxFBtlEiTEa3WUcIYVANs\nq0CtUMC2HcIwRFcNpJpSLtfwAw9NE5Qch7t3blFvVniwsYFQNIIoxNDNqQhDHAalgTw/bEf7Idfk\nE+uU/IRFoQhyORUbivhkCpADymGRbU6KJMunYWxTgK7r04N7mqNq2nSCIqYCJkmSQyErybPpJEFV\nFZAqUe5jizqWMqDeWOZuEvEn1/+CsWVCDK+snuakeo5RfJnfe/g9hGpyvq7RrB4QH5RZtJ6koxzw\nB/f/nL8/84sMmx2u9yIeTEaY2pB6ocKwE6KWFMgEQmV6uyUP8ylSHlLP5Y+z3f+t1/wzOZ/6tZSk\ndJXnfjalfWOXzX9mcNqdxQ/m0Foa2oLFzGpOuiZJ7gj2tz0ymfDmFz/iwkwL+6klSss2r3xmkQ+/\nBQtzAi0aEow6RD2XZr1J2WpxVm3Q3u6yqtRInG1Ov1TgpnOTQekB5ok22BEnzxSpNAW7zh1E2cD2\nMmq1MqUsxHChLpoMk4xRkKAJnfJSiYmXEnvQlzGZY/D69U0uXHR4EI1IKxYH7g6myNA0WF5V2LkS\nUDwNw07E0pMOz/3aMhvrB1hli/3tqU2sP/EolmzmKhVUVLyJi2LGVBcTmrZJ72aJaq1Jf9LhdnwD\nr+gT3XJ5cfckmiYRQc7Em5CYI3SrzKCbkAYOt69rWM4xtq9klLw5Mu8iV9v7RKaG7O/SfLxAoHkI\ns8D+VoIy1rEpkCcKTklDjxLCHZW9UoH2uxMmvQJWHSIhKR4t0b4X8c0/kuS0iXbgm//qOqYBP/vZ\nFVqNCsu/LHjitEX3g3vs7Kp8/vRJNpK7PLz1AaVCgU61gm3bxCLEkTmFBORIgDFDokTEsUHq6aRp\nzmAvx1Uq6GmJsZeSpwLUFWIMmuYcJeEgxgZNpwlRiNK0wBrReg6GxZjiqxUCVSdLBPmHM9z5oxrK\n/SrurEW1VaBcLaJIBcXSmF+rY5ZMAhmThhlqrqDpgjAQ7O73EQrY9QjdADkbYukKaZqQBpLYjBFG\nQqZVwLRJxjkrxwqQCzaCgFMXj6CaKfv3DjhzvMrDxCcvmIiiS6SomKOYSqLQVHTknE3kahSKDdzI\nY7Kpcedegp3qxMUULyygJwVWKxeYRAM2blyhuyrJbI3EOeBh9yM6Owu8/9E2N0Y95pvHOFo+SUHx\nCbeukuUR517RSG8obN3X2dqKqQgbJ6iTbhpUj5hkOwLjQp/x/iORUJ0AACAASURBVIQ0d+gNJj+R\nd8WobRC6BiV1lve/73LtbY3177jYSkb9osKzr2n83MsF1NTm23++w2Av5u6tNucayxjmPGHcp7y0\nS9x6QJtrHDcNCkoZiU9JsxjlI8bxPv1Cg6w4oVhL2NvdpTlfZ3/QxtEn3L/7HpqVkClFvIGPsB9y\n/NSrPKot0TplIjcittZTipdnSFsBMycDaqVFVAYIdGw5z+L8LnPHOqxf2Uf2z9Bfr1NuRiBNUi1E\nVW5OGQW5JIv3ebhukgaPsf5Oh09//im+9N9/HUcxefRTTRYu3CHSbuHyh6jlBQ7ic0gtJ41rDPo7\nnF/7FGWly+OPHGdzp8/25RLfHb7Ckz9/l+bpEVGljYHOsdV5/r3f6nPz6h2+/QXJmdbL9KObvPa5\ne7Qe/RApTbLURKopGROG2hUWTlzg5deavPnt98jSJWpmgbyzxbGlGk9/9kPO6iFf/oMd0pkjbH/w\n7/Llf3XAyd09Fp9VOXW6zr19l91eExGe4eqlLm/+6X1efvkJ7t6+DIpPkuwRRgkPt+5hGTmKnFAv\nqZSwyIWDaQQYhR6lWkYYgt8JQZrIXMHQcoTMUNRDcq0Gpm5TbYBmdIlKuwy8DaS0SNwlSnYLW59n\n984GJTNh3tBwdAsSQCiMwxCnUaMz8Tlz4SXavV129x8w7vdxEkFFOQqGjqFqhIqgbJUJcoM8HzEZ\njhFqlRyX7qBDnrjkSkqUhChxhmUIHKsKUiOPUqpWjUyTuKGKFPG0VCkPyMIuIy9AmApKFFO2y7Ss\nlH4IPW+LXCtTYolgVyfJEyI5pud1GEYOqphQwkJRdJLSHrGfkYUh61d6ZLmLZIihqojKKspClc3B\nAOlOmUIxG4RdSRaGCKeEZujIJKd30KFRrGE5ZcKij6q5pH6AklShX2b3Ozoblzqo1eMcuXiSgT/+\nkfb5jyU0qgVolHN0AwxNRdWm1a5JapJEBq6XEoeS9BMAWixJk5g819FUSbc3ojdR8TMFaUo0FUSW\nYRgmYZohDEkeTz9L5jkpQD6tjpVCkis/DPdmGYfMBHHYQvVJq5AyPTweHhyFUH/AvhBCQVOmzUO2\nVSKOM6RUSGJQFImi2iT5hKpZZeK6mKnCXGGNakUgRzonzpzjW5dfp1Gt0ul0cPQCpVIRzxui6SpZ\nnqLIaRUYIkeIqX1HAJZl404CDF3jo5u3uHDuDFHVRWbV6cMgFLyJS63RYtzdp1ou0W3v02hUSaKI\nwA/J8hRNQBLHxHl6WNM6te0Ipn39VqFOtblEuVhBUzQmowFR2McwI4LAJ4piVM3km9/6GhsHH2EL\nh8fOvYBt1kA3GcQZChXWZk4SBQoCF9Q+n/v8z/DPf/f3UcUMaTChWnJI98f4ccLKygph6OIFIbI/\noNVqMhqOKRdLeJ6PU7GBlGK5QBpnGKZDlgrK5QK1Zp0oDNF0jSxNmU6AUrJsCoMcD6eVuf3BgHK1\ngm073Lx5G82Y5mOKBQfP9Q7FJChCIZeHEzD5w4C3onwSDv9h9SuHzIwcCYeCQ5L/4NlTVI00TUFK\n0jRD07RpzawARRwKm8PKXEVVD1uvcoQyJZlOdUuOIlUmashIVNmb7FJwqrSKa8wXFeJOwhs7l3gj\nuoSolfiV5lkiERCNT5KXTtM02hyMLrGyEPKryW/xr6O/RhnEnJg/xbGWxd/sfxPLc7G0WUJtHyXT\nfxCCR6pImQGHe0L5cXb7v/2af/WAtH6JyhGXQRVaZ67ybOVT3PvChHDgc/7icY78nRKJvkWep9Re\nW2UwrtG7K7lx9TZ1uUjwQGcUTUg1Db0S4hyxeO+j72HpJivLFeaaAn8nwUiGnJjJWG50CRd2GK0N\nmTs3pMs+tacddrZuo8/WyBdCdu+O6Hng6TGPPnqGi8cX6G7fYzDuojY14tTFNwXlxzMmEwi6CVrF\nYJTF9KMBbsXhrd4BK2eBLcnFlk0mJXa5hJFp7Fw5oLfv8Zl/cJKyY5PPebCe05ptUnAF2/s+43TC\namWFPAnRBBSrKmkUghJSLdlU4xWqns56scdIyTC1Ixx8uczfnLnDhUf6aGoFy9Q5GHrUHAs3XuDG\n+2OWlo7h35/lK+910JqCbjZgtlJlEg1pzreI/AENzWJyEJC6GkVNUF6s8vJrC7TL64T3cj54q8/t\nvxjy2NM1nvj0IqUow/QyNu9JIr/A3bdymlaNi0dP8uLPrzH3qE5ndI/WmoJff0C/tE3j2VmePnsE\n41bG/c0+wV2FSauIdipBSkHihmhSRQ90FitHqc6a6OUFvGwdb9LHNmu4DzXcbkY+1ojiFG22hDPX\noj5TJmznFEoa9WaKsZIT1DrTjMmySlwN8ewIBYPJ0GZw9Si9SyWSzCUvCsyVOlbDIog9vHgTaRSJ\nfEGx0mIyikHoVKpNbl7Z5N71PktrZWqnG8RBHyXX8f0BBcPBL0bIikJqJISTIeFuhBXZ+JmJVtZ5\n4tkyzZWYYNhGMy3cUMFyHZSKhZdNsLBxNA05UjBUiSEscmmhJBZRrmMVTO69s8tss8xNr0szq1MQ\nC2iTOuzUiPwtVp86QbMece7sUdqDjHe/1uOxpQt8468v8eDagMcbS/T69zhYvEPa6tI6U+G5R8H/\n84z+bUHom0T9hEZ5FScx6O/eo34aQrVPEg2wtZ/My8LfKDJ4u4ZTnaX7YMj69zoQHyee6/Prf+8M\nv/gbKxi02bjZZ+PAYGX1CeLJ+0jFIslGGKJB7tzk07/6PPf37uLJHZTcJo51SnZMnBwwGU0w6nWc\nI1VePrrI299d596DMaqd0rP73JtscKJ+irv3ujSMKscfFVx4ZotPvVxjb6Kx8U6JKDToPVhh9+od\nynMllKKNIUw8JsS02VlPKNizlGuzfPsbHT4zv0xt0qFUWmMk7xPKkHT8CO37Q772VzXscJaCdpw4\nsvntX/5tFLeINbfMg+07vCAXCfBRCLFEk0i5z6Xv1Ni53OfhO0eZK3k89/klnnwFqtuCh++McbcL\nvPXXd3nBtFi9uIzLXaSSYLc6vPgZB824zl/8z2A6OfbakLj8XXRRIdOOE6SbpFoHX6QUuU6lKRl1\nDojLZ1EHGacKJp/5uSrNi1fQtKusXS5x0+iRdM/T3vm73P7d3+YfWq8RLr7B/MpTfOMvR9j7Z5Hb\nNZaKgqvv3ke1EshMNgZtKk2bbBjQqApkOsCyTLK4T7kQM/QOWJizELWAUQbBxEDXIqqOgWJlOI2E\ngq2gUiWWIY1STNGJUW3o9kDxoSjnmCk/R2rO01haYjj6BoOxZLFVolB0SIYTqlWHYX9Mo1VntXIS\ntbhG0TyFSZ2tgw+J/RFb7jVqhRJ+nhMaCoPRAbmagkgJNgKqlTJpEiHjFAwFITJELkBXMNQGpmMQ\nRQEBAzJdR1cNwvGQUNEQJqQiIQnGZIlC0XIwydnb3MDQBAXdIssr5KJEahg83AmwLBNRygh9hTga\nMVOrYuk6ihLjRQ1UEaIbULAM8pFKljbxJah2DZU6phJMyyvUlCjskwQxRWcRU62jpykKE0TBxFNT\nYiEJI5XUi8nDAH8cUVPLFFAIIxVzvMneYEzxiR/tPfFjCY3FOYv5GRNF5FOQmKogycgzQZrrhL5K\nGIPMJFGS4roJWaahojOYZLhhQqoa01vlLCcTOTEKqkyJ05QkF1iagWTa+iPzfJrKZcoSkDInl4Kc\nnFyZWq00Icjyw3BvLqc052zqus/JyckOmQnyELQHSJCqhqbpmFIjUzJymRBGLpkqMIOMgjApNKo8\n2jzCw+FDqorD3k4bR3XoDwcUyxXUXDBxJ+iaTpYlKEKbAt4QHF51IxRlmrcwVAzLwtBV7uzscena\nR1RrFTbXI06fddCLZVRVZ3dvGwNJMHYhz2jvHWDZOr4bEMcRuqGhaQqaMJFS4Psunh9SsgpYlsmR\nExewnCKjQYcoTrh772OaMw7fefu7nDxximKpwa3bD5lfWuTMscdJpcANMvRKlfn5FkVHZeL12Nu9\nQ63WQpChZjbHl8/y7MVn+OD+PSxHI4pcCo7J9s46++19zp8/x97uLp3+iL29Hq3ZBvvdIZVikVE/\nozEzIYpdGvUT5LFFtW4SZy6GVkOxdBShgoA8S8kyQRwn+K5PsVBkNBriuR5O0WG/0yWIYnTNIvZT\nwjAkJ8MwjEObk0Aeti8JIabZDJkzBSpCln9yuz8Vp+qh3UqI/AfTsmmYfCpAhCogn4o7dB2JRFN0\npMzJsnz6O0IcfvcCKZPp93/4CKgKJKlkMdEZxxb6XIvhzphe1WS8t0t5ocW8t4JSaJDlXf5k/V2s\nQo1fWJvn7dvf4BcX/y5/0b/P6kBiNN/kkfQUf+l/lZn1Oq1KnZONU6xvPsRSXWQgEapEQQGhgJAo\n8hORIch+NLbO/+tVaiQ0m1AD8hBOtkZsvpZx+Y13SXwDq9Hn5CmXqHWd+WANNVbYlX1uLtV57rE6\njyw9wXA/pp04fPet61iyyoo3Q54UqFUbzDQdKLuYVkh3fInWqoZ23mH1BclOMsI8r3HtG/dZPHKM\nU0stSkWb8dhnaVWnFMGmnfL2ezd4888vMbdo8cwvLBEobSx9RIqkvNyg+ZLC32zuEEQ2Owd9lo6a\nbLhdEgEtBxJd8GAcku7EbF01KJkrSMMGW2Pjag+3tsniCYXJjIvYcZCKTuoGNCoFaos5QS/BLml4\nYYxhJIT+kMZ8BQMFLVWwmgrBRkokOmx8XKW2oXL/iSFrMz1cqTFUTE6eeZZbV2G4lzHxOwSmwdX9\nXYp5AZOYhUqBWgOk1iUXE+JxhgLYpqCyVuGJszWOPiUYbyV89G6X/+m/2efXzh6hFR8h3wPPTRCr\nRbRbC5ziNEuLKefPL7N0ykTMj9AaoBpVJDBc73HlzXUsU8VeOMELCxe59fpVkl0fw6zj+RMyLUbO\nCHwtQU98lM2AFcfGOiZhsURzScd76DK5a3L7g5jhjsPBw4wkgfpqidQWKPUh58+aLMwdUF3Q6A7b\nFGomfTHGNgURkqKYY7yXkqUr9HyX3pEMjkiyNYtSs8qRWoVstoMjA2SsknkTRJKg6IL25pDOboBp\n1kgTA39LEN7XUHUFIp1gSaAuKURKjkwE/g48eH+feiGnuVjgp3/lFE4AO7c3cPsJ1XmTcC+k81ZE\noZbj6TZj28UlQ98PyZQauSowiiUSNyYXFjIoEg08wsRCej5tLUY1VN699ZBCVCRhzJWPP+Sdm3/A\nb/7Hj3B67TSd6BZzJ55DNwR/+Htvcq1SxSmN+YX/bpbqWpVu2md9HDC7mHL9Sk68E2B2TM6cP0km\nEqKBxc6dLvWZCUk5Iu79ZGyWaniB3kcrbOpbdDYS4lhl/uyQZ/+dlE/90nEMqkgZsX7nY7wgJ3IX\nqCcpjt7Ck200ZUIsQqJgE7MeE+Y2qiJR7R57UUgQq9j1OcprE37pP6hy62s5zYpBty8wNMHH1z+k\nXGiwfr9DrZpx5ljKz/xGkc/+5gToY2yfQJ8sknb6HOx/Bf1Gg5PPHEEuDogOwcDjJCN0TYaDjEZt\nla2HE0bbDv17KfOPVRi4jxP215GjM7Rv7jCv/ufsd3dYfSomFT6PZJ9n3LYYeJuMJn0GWQeZ3wa5\nRZ538YOAj952ePOLOmdaj7NxT2GcSRInZvlixtHHd9i8/zoHeyp5vkB/VMYqgaoM0DjGiA859nRO\naV4n6z3NH/+v1/j7/8VFtuPrFGVKbA7Y2RkhpcAqLFKpl5jENyjKR9GzEruTu7x/t8/zfY+wFfLo\nzx3nxTmF9//mA17/H1SiW0/yB7+3x6/PnMNXfI4YF/jXX73G51/9be5d+QIVTXC3u83CmsFgaHDl\nxjvMzphYxZx606TYtOmP+1QqMFOy0Ks2wjYJ/CG6nmPoGZqtUG7E2I7EcQxklqPkHqoBUWKTdWwm\ndzKi/gpF6yjzs0fpeiZREjO/uszw/hbS1AminPmlBW5fu8yjp08RxyonVh/h/s6IcBRStposts6R\nTA4YhkOGwYhJ7BKIhFBLSXWFPI2IxwGGrGIVTMbJBCEMoklCyapSLS1RMBxkKpFRSBYHyCTGjQaE\nmYGiVzAsE5GlROMRcRIQexq5lFTKJTRNI077JJnAzCrkicS2LWxTR1Fzur02ipAU7VmiUBLnAY5V\nIFMcCrpGHMckJIR5jF4uozpVKFRwtCLqxKMX9LD1GpWaAoqBOxyQGeDnEscy0cwiSZqglQSxZ6Lq\ngtFogmZkRMk+hm0waD+EuEyy/qO9J368MLieUbBBiAxVUVFkim5YCFEkSTNCJSBHksqYIIhwaip5\naOGODdJ+n+EkRHFmyD0f21YJJUR5iiFNcnQs3SFLPRQUMpGiSMgQpHmOJAORIYEs/wTDppAfchPk\nIYQtlxIly5GKiqIJxOHVsvyE4K0oIJUpz0MYJBqkfgxqhkIGWolAjnDMBqvOKu9//H0uXnieG+vf\n49zKS7iKTy8a4scejmIiyFFVlSw2QFUhPwwjC4nIc9IswbFtwiBEsWyCNKXaLPO977/DubUVllZP\nkEQxvXaHxuwCuVSIRj1UVSMJU/I84WC/j2NblIol3MAjSyQZGZNhn9biAukgQ4gCi8tH0UyHMAtJ\n8gm3b7xLuVTk93//33Dt6k3+yT95AV2f5ZlnnmJr5w6VcgE38FhYnWHieQg1pDOKUeWUhL25fgsk\n6JpFZzSi3oDxVY9K0aReKZH3+pQqJa588C6N2k+hlcrMmibj0RjfjbF0hyQB1RzR7UwbkfJ8i4JT\nwg8LkDtEARiGhef6lCtFdEXH0jVUYWIoOr3eEF3XsQoO9UaT++/fw/V8clNQqjYZ911qlQoTf4Kh\n6+RSIDQdeUjRTtP0kKL9CVRR4xN4nxDK9JkQ8lAgTkF4QgiyPCPPpo1Utm2TxglxHOM4DkmQoGna\n1Ep1OCmJ44RcZmi6TpJMYZYwZXWoisY4DQmNnMFgj+XCEj2/T6tu0plkJKHEqN4j7zssz55h2A35\ny+3XKeon+Kr3h7S0NU6sPMbX77/OXG3CPzv3O/zO7X/JTv6A5/InKcwZfDj5ACOdJ5Ph4TP/ySRD\nIuXUPvbJoOP/7xXmArVoIeOAk8UMRSqkvS6POHXWs132b28T2imK3cZOAgq2xCgfcKf0Mcu/tIS3\nsc/Nr024mybotRJPXzyLez/ltLlCS9rMLdnsFvr0rQ3mP23jyz3cCyV2kz1mjjfBEpx+Yg4rnV4u\n4Ppk/T0smaGXNJpH13jvzQ73b4VYI4VOf8jIH1FdMiAIiIZdgjhl7UxOe1tjdyvDim3W39jn1AuC\n8TVJq6KS5C2G7Trex0VE0GK+Ns/CS0scmc+4/9GXqdsGrpdjRhHrN9pYXsqJtRL1IuxLD71VpZpa\nrOgVOpddQk0jG3WoLRYIhzqNC0e4+nCd7axL9Gch+cmMxZMg2hbHyjbDdMjGwwNit0F37yEP0wFD\n3aciq1RGNVqRSu2MZJw85MjpAlojg6hE4jssH9XRZybsxJt0xS59P+LESpUXXvs5Nh5sc3ArpjFr\nYO2nHDyIOVqa4cyvLuCUVHayLaIgpbMZcrARsJ0pFDcNDt7UOflqBaOg0nAqLJfn+XD3PRqrixz/\nNROvvU9u3GP3/TZR36f6hsrz1eNkBz5yJcHUN6kdiZgUbexZh+9/NUFzVVRRJtMDRpMxrbUJ5Sdc\nbHuLSklHlTn23CJaGhILjRkRU5Mp4tETfPGPPQbqmLmwzrJs4Y0Sro1vYDouC2aAmQUs1WeIg4BS\nrcbt2+tEnqQ5U6R5bAnXi3APQlAc/HZCMNQp63VUUyVKBkQyR4403AOXynxK80hCXrmL0ipRtWwq\njxYxLsHOdZ+ttwbMLNgUFprkNQV1JsZZLWOutIgwObjj49gWhmOwvGbiDSYc7O0hdYVE7qCXF7i6\neYlWtYR5LOH++i10zeajj+6zddAncXLubVwhi3N+/tdeY3bR5vK7X+HSzU0ecxxG2zqNgsdnf3YO\nKzf4w/9xCyMH21bQi2UO2hHjKyPa1Zg0go37P5mXhW1WeP+NDnv+Tdxeil5coLKg8fQrx2kUA8a8\nQxrm7DyM0IJP49jnKOgfk5CipRJNjbDE9LLqztYuS8unGcQKiowJohpClEGDY0fWiA9uMPF1kiRk\nsXyGuzs7VFsak26fJx57nETp8eRLkpc+pxLSJxEjzIUIs5WQRCuMdy3mWmUKWR3wiWSIQoStznDx\nwjJzpQ0Ozt/iW19UuHvjDs3iaT7u9bm35VPUFjn12D0uPlNi7pe+zJXvlWgsTdgdfJVXP3OU7325\nR+89nZ3dW3jtR4kSH9uYZ5Lskika+xsTavovYMhFTh7V+daXrnL21CvMHQ+pHhcUFoucVRTc+D0m\n2QGGaCHzBkkekETLuB2NwU6I6Ol0Dxze/FPJ3DOCdP4OyaTEzgOD4f0iN+MeotfAio5RbM3Q9rdJ\nGfHNv77C2rM/Q/3RWWLnbWCNuTM3kDMjHp/5x1y69r/z7T+v85mfnkebucarv/oiv/NPf5faeIcT\nzdPUZxfoTta58vFNZmbnqDZTnNoIvZHjmQOKJyWZ6pI6gqwYYpYFhaiKkhmoRhur5qMZCpZ5FNO0\nUIIjiDxB8R4QdR32LpfxHlrgzlIwV9GcBjKMCMKIWn0Gb7sNBYtMSDqhT6FcxfV9CmaTjZubJGmO\nDCOajTqDbo+StQbOhEBOMBOPTJG4ecAkTaiUKlgLGZnvk6sCuyVJMyjUHHRMFN1GopKFAWpqoGHj\nhz5RFqEKhSgekAYZWZ6QReA4FQymk0x3EiIcE9NooUqVPDRx5ZBKOcMLQnQxi2lJ4iBgv7OHKh1m\nWk1qjRb37t5DFAwUoZBh0ZxdAUNnrzegIGPCMGDY2yMmw9E0LMtgEoSUygZdb4hdr4Fp47spQqTY\nqkYS56AZKIUyVqtJcKCgInDsiIKqsX9z50fa5z+W0Cg5OmULVOGgquYhqThHVSDKJLqqkeWCLNOw\nzcMbZwdmHZd3ryjYpQr+qI1SLpAkOSKXOLpNIjNyNSeRExRScqEhFJVMalOvu6KQSzFN60tATicV\nUztMOvX0S5BqhsizqZ1FCNJDgYECMlNJ84xcSlRFJdFNSkIn6U/QCgq5rtLLRlQSSUGf5/nGaS75\nW5QrFU6IKp7+FO9tv40ubNI4xdEq02mJJsikghDJdOKiZChoKEJBUXTIIIpyhKIjkhxV5MjUYCQN\nvvvxTX62WmHcm0Ep1ijJDNfdYWZhic7uDk6hxKDbZW52kU6/TzBoY6kSoWjIXGNx9QQbm7ssLR2l\nOjuLqkrUzOXW9cu4kzG1cos/+8pf8a0Pb6HpDl/73tf49BOPMW7HKLaJjBN0oTPo9EDRCScBcZwh\ncoluFlk6skixUibPEqKPLnH66JOcuHqF1fMvcmcfWnsebV/nTjvixE6buaJANecpl4qMoi5+nDAZ\nh0RbUKunWLYkGI8JxhOG3Qc4RZvQX6BYnqVYbOHHKlEm8byMVjknCAZYuqBcKTLo9xm1+1y7cQ8v\nUahaNqnr4ZgGru+iaOq0aUlwSNKGPMsPsyzTbIaiKOQyP2RkTEF3af5DEaKo08P5lIsCqpjmd6Lo\nMBipCPwwwNB14iyC/JAaLgS6rqPlOnHsoykqqJJcSGSekeU+qqphKQGWbDCSLoZu4cWSgkiQJqRB\nCVESjL0h2GBlNVI1xJJHaQcBl3bfY600QyHJ+K+u/me8euLTfGvjY/xSF22SUXdmSYc2Qo9JkxxV\nEyAVlMOpo5QSkeb/t3v7/8s1vG5hPVOlk3SxI7CLZcTIppwbHK2f46Pdb3Hp1oCnm2DXDPpdHy/b\nJY9SlJaFjMesPllHX8/x6jFoEyJvzNhLaWo2We6glh6Q2dcpnC9RsSYYrTL58IBh5vHht/dxhMV9\nf5fHH5+hXnVwMxBZQORGiJKgUJScOVHH3fG4+Vc9Ws9q+HlGKmI0O8f1RliNGnNhmY+zNu6+hu4J\n4g9MOpsh848f4eYNl+H1gHl5noXKaQozMxROZrz2+Rn+23/xdd7/6oCjq3X644S9jQmLMy2eff40\not4l8lI8YwKhwLFgJsi4+95DEn0CssHsYgVdcch/dpYvfO1D6lf2WXlrhuHchFo1xqjlhPkez37u\nKOfPL/PFP9qg7pdZnTvCXM2gEWjkyUO0ZY/i0ZDGqkOORZ4USBITpQwb0R5Bu0e7H3F3PePo8RXK\nj13gve+9RXDgUn9gsLiyxLNnXuD0agX0CYGd4A59ZGISbhlo+wXMic7+Ow8IHtg8eKPDmVrCntum\naNaIEQihU6qUmXm0w1jTGHkuwbUut66HLHy7iCZ9lo6oZC3QnZhCMSQ+MqR+zmZ9XeDf0wh3YhaX\nKhRmbKS7hzbbQctStLhKOUwwhMkw6BMqQ2K7g6YW2Bp5zCycID7QKecmZinHXrYgCZGuwjA1sU2D\nyMuZyRM04XD6p2pkaoylC6o9kzwroAmdawc77D8U+J2c0y9XyQ0LXQ8ZtwPSoaB5psLsQoUw7iOd\nIQfWDkalQPX5Ipmn0HmgE3Q1inaJlXM1lLUDFC1GiUKWlRLtTQ8905k/LjCLPmY1RqyELJ2ucru7\nT6lgEF6F/sE+Wqaxvb3H8tEK23dSPnjrIfXZI4R7A1ZONSkdtVBnJaWozt3LD5lbXqUM5BpYScDR\nx2c4fU7S+YpHHkO5bjK2VfbGEfEI8Kdk8J/EqtZHbBzs4o4sGvMWx44u0zqxRXNhjwkDDALG0ZhC\ny2T5pMblt97F+7pGcSll4ayKDA1KJY0btz+i1izTc/tkwkUIKNgLTNwJvt8mzx+ydz2mvf4p7LzB\nw90dnIKGppzj+PIiQrnH5/8jkxdfiVBLES4BRY6TKILKTEhz7YB4chxdDelvB0i7hl7OceoKhuxR\nL0lq50MWT25x9+OQ2+9o3CvMElxO0RsTnvlsk5WzEUK1cIdNnnrVZCi+wzHVxOMeL/37HXbGKeu7\nOd/7y4955tUVulwjDh7jrXevMbn/i1jKAVqasby0QBidH9a+TAAAIABJREFU4upXNN7NXNaebfP0\n5yzMmY+RRpeyXCCMh2RKCQWPg60Rf/2/meT9M9SdRT681uKdL/s835Q0For4SYM8Tvn6/1Hk+Sf+\nEW98918yW3kOs3ubeXMW3zrHg/Z1/s//5TYvfr7P0k8nTNJrKDLl3GsHGPu7LAUv4str7Hlv8PSF\nf8AX/+b7nH3kKTa/P2I/uY1aPsb3P3iX5ZllwrzNIPaxDYGXZ0gtR5g6qpZSbRhkWoTm5JhOgJJN\nqJY1GqUz6FSQ+R7RuI4huoTdmP0bAaJbJd45hZ2vkcRlkrREohvYFR3L0Bh12hRKNdIoxDQrOFqB\nPAhw4xghYrL2HrrjUEjBDCOOzCyxPxyi6xphKBGxglNwMKwcPdEoOFUsEeLHfZrNOfzIQyo5+D6G\nUMljQaIaqKqBNEwMaZLlIxJfRzeLGGqKxEOKDGEoeMGYQc+l1ihiFW1GbgddGWEqFZzyEpOJT5J5\nqLrKZLRHIkIUAaHv4tgqeaow7o6RSCbBiCT3UEJJ1JHYhRKqkET+EAWJNKBkOKhZRpp4KGqIYhSZ\ntecRdpk0zynWVeJgwqTXwcwlSiIo1xfALtHPXEa9MYslhzjXsNXmj7TPfyyhoasqTsFEV22EUKfW\nlMOwtSUFSZaTphlJFhHGOY6REwpJlOTE0YRARlOll+VoQkGoYsrk+IFn/hPY2PSQiMwPLSyQkhwC\nyJQpuTm3yLJ0SucWKdOU7g8p3VLKaZYjP/yZlCiqiiGmIWBnEhAWc/p1hWUsOr02y8UmI8VntT7H\nzdEuBD4vLz/J7976Er/1yK/z3rW3WavP46YxmqqTCwWRSbIs4ZOKI0X8LVtNnv7AtvJDOvW0QlVX\nDW7dusexmRa1UpWWpuNNxsxU5wjcMYZpIuOU2bkFBsMhpUoNXW0Qxj5qLjAsG0U1uPjs85SLJUbj\nLt5owMP9XUbDPqahMRp10FSNOALHEVz+4DrPn32U4ajNWNpMFLAtE8dxUDUNo+hQL1VRZEYS+Uy8\nIZNggCZUSpUikLO6ssrO5jq/+fd+lT/5U5PX3/oug+GYL3/t+/zCZ56hOTtBAjPlOeIkwdB6UKvj\n+X0ebO9QsEP8sUej2aBoKwzsDuh7tGYbFIsNjq6dh9zCcCooSYJTsMmylGKtQZbEnD59CvlXX0I3\nNIaTgFLBgVwlz6YiUoipbemTQH5+aKP62yC7vw3zU4SKJENRtGm7meQwJJ4Bn2R/fjgeVFSVOI5R\nFQVVVVBU7XCiEaNpKobhkGURaZqDkk9LCIQGinZo18pRUcjyDFVRSLJp/FwoU3GkKBpCSkBDVcFN\nAjLpEqQzDIYbvPLUz7DSO83dbsSnzn2KL7z3Bf7TF/8Ro7t/Qb8Ag6GPYdjTCmgyZJwfWruYVv/+\nBNbwocfNuw945FmNolQYYrPbdll79hUeVj0u/4uEyn2Tz366SDSAfBASlVYgOKBVbFA+WWDjY9h5\n5z51u4UtCzz5/BmcvZSqLfHjDWaXE1ZX63TN61TrOaqhMDsnSGtVqiUHZayR5RmRkOyNJ3TCCXY1\nZax3yLWY6tIiBkVu3nVxJyn1cYUon5DVQxJriO/GpJMCWZJiygJR10Lkx8lcFdMS3PhmTC5neeHU\nRR6ZfZ63v75J++CA6kyGZJ6l+lHe27zGh4OM/vYYvVhhfnmG3d4Wqd4jbw7QTLA8DSnKFJoqc3Mq\nEzVmtB6TR4JMSVlsVLi4eoTrDzv0vlml/XyCfS5FIaZkTciqfZR6gcefrXN25SL9QYg73GXtKJSP\nrNHV7uPMmTBy8MYquarRWjLxvRGbD/aY9AU7+ypuL+PDa/d5/uAhOyPBne19AD7TPMrPzC/Q1gdQ\nndBoWfTcjELsIEKT1AuIyQlsG/vYPDt+j1Z3jz33IbMNk0Ao3P3yPi/942WOGE3mX3VJ0jGvt/v0\n7iZ85+YWT55f4Ih7HFzIyusojSGpP0Cv+ujFWfTIIH2ocOXmHp1+RrCyjj3rsmSqKGTsODfZ2h9w\ntLZKxYspCBuvuEv90zBJOwx3CpwqrTDs7OPG25RrgnEnJK9VaHckJhYPNjwWVizsosIgGKCrPtKw\n0BWTySghCD1K1Xksw+D+pYy5sw65bjPe84ECTrHFzkaC3jCoFmLMskCW90izAvUTK9SvFtjdDEmJ\nmFNsrGpGbsV4B138VEOZUTDLAYqdsnLGgJZFWYfI3GP5+BgB6JUGm1cS0qGBnml0soThRNJ3dWIJ\nw50R544dYX39fQYf9TDLHgMiDtwJO1mXC8cdnLLKzjvbtBpzZEdKKK0inckeqerx9E8fZ7bexx0I\nvnCjDfwEmqesm6RBifnCL/PkaxucPj+isQx2NSBFkjOhXC1y7kXBB2//G+rVz2MFZ+lc22Lx9JjA\nq1IobiNNj0lqoYsY3UhIghiXGwyHGcKWmK7D/nqTe/fHdLd8On5IreowU13D9hKe+6kCn/kVm5zb\n/F+8vWmsZOl93vc779nPqb3urbsvvW/Ts2hmOBuH5FBcNaKoxfImx44iG1AgC4EDGIkTOPCX5Fvg\nLEaAyIjsRIpjSYxELaZIaihyNOSs4kz3dE/3TO9997q1V506+3vefKjbPUq+2AJCXeDidhVQQHfX\nW+/9L8/z/KSysGUZnRG2kbF+fsDhjk5ePMZg+xg33xMs9AecerxJvSXJ1AhT1cm4iW0rTp7zuXF5\nwocfge1IfvK5k7itEQiNCVcpVf8W/eIPKBjS1T6gwSpTx+LJl3y+962rfPDmBcbtjFM/do4rH0Rc\n/rN1jFGPunmWJ18weOErI969UrB1fZ+48xidPx5gel2e/ukthH8fi+to9pQpA8b3Nrj1nU+Sftjg\n5Z97lI9ubvNE/Qv80R/+CQsXavhLHZrrVUxL8Zlnv8q3/zgmLM5y7yDjp0+uUT3lcdNMGH7/BDff\nWScZXeZsZvLEpwKkXWHueIezj4bsD7Y5du4JlHef194dsFH9T/ja775Kq1rHrS3w7rU/ZanqMExu\nUFuDhQ2b5oqJFBlG2UY5grJp4WoRjgll2yfNYnRTYiVztMKXiSY2U+1D9HKfUTuie31K5/0NtNF5\npmOf+VUozAF2STBKdYaTERgmh/u7tKoOFeURTFLycgVMD83WSVOJkBrZaMrx5ZPsdg/JDahVa4yC\nXTQZMUw6gI3hWSx4y7NgmbSPo6bIyZA0y5F5SqtUwS0MwiSkapZILEXkVslkiaY+R92K8Csu4ySg\nNz5ECnDKNZwECnuMUCGDbo9QKspel6II6KURhlNhGkakWYwldNAsSk4F3TIo2YKsf49ekGJ7ZeIs\nIVEhvu2QkSCnimqpzPiwi132MV2PQkIaTilUirJjTH0OyyijFy6TJAazoDsa4mODnmDYFoXm0B1p\nOPML5N2c2IgY90ekWfIf9DH/S5HBP/3MMovzZTzHQRc6pqVj2Ta6MGYwP02hmzqmEFi6wNQUlmMy\n7Ie8+d4QzRJo2Ci9gGKmn9cKRV7IGckYOTNxHxVFM1mUPFLLz5IGZpPoB38z7SFAUBw5XY9yh2Z/\nVsXDR0J/wElQFKqgsDRknFKJC/aSMU2/RqYkX2xd5Pudq1Ryiy+cfYnfuPR1fvLpL/DdK68R64oo\nTTB1F0M3QSl0TecIfX4UoyqPzNlH1S5H6VPaLCVK6CBlgTBsJpOALAlYXpyjVqugFQJNgl+fSYiS\nXDI3v0CWF1iuh2E71JoLNFsLuF6FaqPJeDKmPx5zuH2H0aDDsL9PkUakeYpj2QSpzjuXP6De8LGF\nS903yOWEenUdx/ZpNhcpV2oYlss0mBBEE8JogmXomK5NqVJCGAJL19ne2kXlYxQ6tXKZl1/+SYJJ\nwLUbtwmmKVs7e1y4cIwiC2jU60wnCk3PSJVJJlNsp4Tr1BiOEsJEcuPGXcIoIpURk6BHEk0wTYeq\nV8GrV+h2O1SqVabRhDxOaB/scv/+Dts7e+wetHF8nzA7IrPnGoWmHv6vK/Ux/fvB9+yMaA/PjVJq\nFmOLdiSf0h4axGenqwBNe0gW145eI46aGXUUQiDlLGFKQyDUDBIodA3xoLnQHkACmSWjITF0gwJt\nBvzWgMJAN2ayLnEEGiTP8SwDKR0sN8QxWly58w5D9rjZv8kj5iojp068d0CttYDd9Rg5A1SukWop\nhrDQH3wulEahcvI8gh8x7felDYdP/WLIqie5r5lsaYpxeAZ37hSvvtGhuzNkaalC6+wcfvMQYSbc\n7nawpU0SlFk8+Sg79zPefeca51dPoWxFvQRhOuQwu00xPyS0b0NlQHkuQOaH1HwLq2rizy9xuBfi\npwbnL1Qol6E36DMho21FHBBgNWv4xRLRHZ3xvZzRTobAoLBH1FahG46Yphade4LRLZtsWEVLK4z2\nFI5WpuI1SUYWK41FGitl/AWLO1v3kKWMwg44yO7w1g+vkgiPQOooVca2XUaDMWEcUH0EaBSM8j5G\nbjDdC9CGERvzC7QWm6SWQ5gZBJMMrZwyikIG1wc0DpZZMG1O/oTNgdZjw/OQjkIYJs1GjZrnkoRt\nVs9bTPW71M5LvNUUr9LizuWI9rZFONGxSjV61zO61wqG75t8dBW2dqbcDYf87FPP0dpokBczwkzJ\nrVCfq2DUI6y1hLQWMzwcUWaBd765RbcXMOxOcC2orzmM4x2s4zGFM+XCc6fZ+4MCq2OyVG8gntlh\nWYfjpwtGa0Nu7xe8c20XkbVIpcXtmyGJXyHTSsTSpDa/SCV6guGegRessSUPGe4sMJVD1l5ycatT\nvIYiUiETXVC4IyYyoJakpN6UZ8+u07ggKC0OufTBq/xn/+1FBvfvkA4i1NjBosredog5KWMpg8ce\nOUN7sIVmSGzdQGUauhezN97DLduce+Y89fkGw8GYeBAzbo/Yud0F3cCr2EyUorpYZiC7UI7J7Sk1\nx0d2KqhJhf2tlOlYYdomw6jPYX+fYZQRBZJeVzLfdGkd16g9ClP3AMogswm4BUpFFKHBYCfEtDSE\nVsxi5iOTqtFCRB6VapUzp+eZ0OP+zZuUS4pOd8Kx4zUmWkx9pcVg6nHjzQhfnKTmN1jerKA3D3j6\nKzVKjS3swqBhVtCKRf7dN/Z+5HfFxY2TXHnvHpsvHvBL/yxh9fHfprJUoJtNCg5ISPBYRuoh7746\nRhu8yI1773Ls0YKNx1IaJZ8guk9vp088znBcDdtpMUgSpgl02pJxzyPYs7j26pitD3IOxhOmfplG\nc426WcaRe3ziK4LWoxEREyytTJS1EWaCr51HTr5CEk0ZdCdY6kWEsGg2JJtnB4jyPQoyUD5CDMlU\nRnd3jnu3R2jJUzzyTJ1PvjxHefGQIdsILaVX/O8U4gOydAHX0NlTV6ias/t5c+Ep/uQb+/S3L3Lv\nksvlP6uh+uepinnOH4cf/5sNTr38BGtndxnor7PX28EKPsXW9Q8w3ZyNc1V68QDTaJJpKTJS5P05\nWssWL/6sz8oje/zw/bdJg3Xu3LvByuYy0SSls+XwO//2DmdOfYZrH7zDZ9bOsbJR8BP/TcjCIx+Q\nRDnW9O/R3jpkfsnk5JlFtLID7iFn1r/KjTvXSOUcgSq48f48t165xHLTJ3QEMghJzCH98DbHLro0\nT0jqG1CqFVhlySjJKUROyZfUSpJjyy3WmsuUvRaOMAm2mozvnma6fRo9XseKLW79maLz4QZatI5l\nrJF5LpltYpbLKKEzHOwTjHeZTno4GpSUwBcuwqxREJKmUzq7HUhDypaHZ9eQSUpjvkmiEuaaS5BH\nGPGImpA4VkK9bGHaknb3BqroIZM+QuaE4RTfN0jjENO2KERGgY7lGoThBMfVMXRBMB6SKoFhOLgl\nC99t0iydxWEBVejU6ktEU52VxXMUqaTkzEMxY8qNg0PybEpJWJhGCc9soIqcJO0Tpj2m4w4WUGQF\nvl0Hw6Lk+xQFOLpPHia4uo4wbIQE27awPQPX99Ckj0zELCTJ0md+zgTKpRJSCxgGI6aZTS6bTOMJ\nKstA5OS5YByk3Bjf+PfeE39JVLCGqetYloFSM9Kw0PUjg22Bns8Cl6ShIaVCWgJD17k8EUcSkhwh\nfGQaYJo+R8NlhKbPjLpSILUC8TAetqDQFIXMELo4KiKL2ZRaM48ozgZCPHC5flzYz36CbugPnkap\ngqwoMIVBmCdYQtCTEc/OnWB33OcLj3+OX//+b/Ly+c+zs7vHn+38GU8tPMXvvfl/s7G4iZf5WLpD\nnKbkMkPXBELXH5qMC5WhlKB4mAT1cbyqetgkydm/WymqlSZ7nSEf3b3LysoKKldMzQpi3GFtZQPb\nchgHIYXQcBybPE0xhUF7dx/TEkiZo1OgsozJqItpCAQz6NRoNAFNUK/WKLuCk+uL+HqD3f0+lYpN\nmgSYukkahmRRjOu7JFHE3HwD07SI0oT9nS2q1SoyUzimwdrGGcbDPa5eeY8Xnn2arXt3+Nmv/hzL\nq5v8F//0nxFkBb/39W/zi3/r59nbuc3qxiqmfpGEkGkwz3g0pNsdUKuVUYXCOXGMNIu5emOLpcUW\nB+2IO/cP+Lu/8LdZbK0hcAmDPXyrRKo0sijh4tmzvPyVn+JX//E/5ubWNs3GEsE4oFRuMJ6OEIaJ\npmYeopk/YbYhE/+fxw/YFw89GkoDJY+2ZrPzIoROUcy2YQoFsgAhZhuqBxyXPDtqYIyjFgYMzaAQ\nBkWRYQgTKWfbkWLWt6A9ZHkcxS5rGugPFjHa0fkQmEaOlDqF6qCyZYLsgGr1JK6U/MqF5/j1e1/n\nk5uP8t6d2zzjPkencR879gnTCK3Q0PRiJt9Ts4CG4q9oo/HICzWO1weMsxhb5jiOzmE+4KOrN/jw\n/jblxUWcTsL9d/c5/hWbvujR9ARnl57g+4Hi+r2rbHULNKWIM0G5bJDrGs6KjabPs/SCQ2H7CH2X\nYG+K6btkvsVomOHmIXVHp7nh4TkJncN90niKhcOgnZL5LpOOix8JskOTiruENp8wGXQY/iDCK+tM\nUo+4bHP1nQD2Rqzai2TSYmV1iXrDoYiGrLaqfO6vXWC3e49r49cZriR0D3Pq0ybXX+3SnySUz7lU\nDJ+FyhLspWTdlN7WAca7Ga2GQGguuvRJowmG7oJuYWLRbFTotnPGaoqZuCyfq3H/xjLZTY+9t2q8\n+28OOPULLQxZcBhts9yqMFfNufXD6wytDCFdzLrGe+9us9+LCbdC4lEJJ9SwDANvy8IebmJ+VKYY\nZrj7Nub0Ns+YK9hzMZ9/aZm5RwO+98ewf6XH3kf32GiYOFGK7khsNyQNx/z5m9ewDIP1pRZrpxvo\n1Tt87pdKPPZzBikW7Zshn3h+ha03+vzOf/UGv/Lkafh8F01N+JlPz3HqkSq/8Z8HbH9zn/bvDll8\npM7VGzmimrO0OMfmZpXl2iM8/VJGx4f9bMLV73W49y2F5jjc+0eKjY2QRU8x1jTaezrPL8NhBhOl\nsckhX1q9wGf+/jO8/tjv0mha/J2/+xy/9t9/AymrZFMde2ARC4npGhCVufPDESuPWEhb4pVdhvYY\nNT+mdtxBJYcoU2dJ+hzc6+IVOhdWF5jbbNDpTsnGMQc3UxoXTXRNQ0YF8VgjneRY6GhmiUIT7NwU\nVEOf5vllKsdMjE2falPR9HUoYnJPUYw0fK1JeJBR1APIcuSgQCsSam6FQs/xhEF7HKFpDpqUlCyL\nybiPzpDPfmWR1bNzvPMtnXvv5fR3TIpXW8ieoCGOo1db3O33GdsHuMc7lBfrHLanVO0qaVjQWDL/\nSu6K3v6Ux55+kpf/vsSqpmicZqJV8RBkyRTTOEs0XWD7/S5x1+PalW9DxeP4Y4tk2lUCeQeRtBht\nGbz1g31+/j/+DOP4FruDGNeusn0rxZdzbF3pMLxncn9X4s0t41g1HMdH5hnz88tIAXuT91kqFWhq\njG9V0bRVkrBKP/w+WXAcwgrheJ9uP+HEYxmidICupUTaiIIhCoNMs7BLLtVKlTTqkoYVuqNtKo0E\nw55nmo5xrCqDWJEVtxGpjW3Nc7ffpVyxaa5VWT3m8t67tyhFFrlTptZaxC9JVHmfUy+WOVD/J3ON\nHi/9NZtBRxAWkptXp7z5TZ/Cho2nnyEze1SMCdWlCaXPfxe9cNDrq6yu+iycHnPr0uMc3HmGa6+P\nePITNnsfdVldfJR3X32XH7/wBcTkJideWKeoxTT9NguP/pA7bx8jtUss1j3w36C2LJi0FR9N/gfa\ngc6q9zcYtIf074cYwS67Bxnnv/wydK/zyh+9wonHLYyKornuk4mYOM/wpI+nSQxLo9QyUXpIqMXE\nwxG++TjL9Z8C3+Tq+yH10pBsPKUiWuxe36WQJlIOkHobzZ0j75tUkzrIgiTqI5M+vl9irnaMpJ8Q\nOxnptM9kdAsRaxxfO0s07DCNJ9h2mSRP8YoS1VKTaW+ETE2S0MFSHqYsECYE4y66LtFsnaQwKXs+\nCyUP00/pDoaMDJtUUxSqR9lwmKT7GAhM00T3JRXPJcslBTGObmDLhEifovsRwjA5trLMwuIKW1s6\npuFimRaD3gFnFxbI8oQwTbGsCpkyyIucQpgcTMdYpsIVI3ThYJkumhRY+axGjKIpGQLdcvDSAt0t\nIWzQjJxgMiFLAmRuMR200USBYegoYVK4MB4H2L6PaXv45RL98SGFzBkFElfTqdZbsPPv/5z/pTYa\nLz61zFzdwtBNdN08ko4odKGwbRPL0jFMga5paCpHN0xMTF6/csjWVoju6hS5h6nFSCUwjpKBQJvB\n+pSGps3WAw8y/5XKZ6Koh5E5Mz28ps205zLPZ1IqxcyArT0gP6ujAlI9nF4rNROPKDErIjMpOWHX\niZCcri3zO5f+kE8ufZoPOx+gGhbP1Z/g7eAKZmWBdDxGN13yPMM0LYpCHun/mRHBhTaLPlX5w0Sj\njyU3R8WtgkLNNh6zhsOgEBrBZMza0jyO42BYFgpBozmP5XjEUYSpGyThaJZC1T7ANTUMTZFMh2RJ\nQKe9TxSF2JZBmkSkWYam26yuHEfTbdrtPc4c30TJAtdzieIEzzap1esUeU6hIE1SHNshSxLccgXL\nrdKoNVhcWMbzK5T8KlIKhChIsinBtI/v1SiXGqyubfLzf+NlPvrgJoNezr371zh5aoUi9xBaRtWv\nUPWqnD55hrNnT3L29CZS5gTBmFE0Yb6xius2idOCSRTwJ9/9Nt/50z/hX/7ab/L222/wh7//h5w6\ncZZoGrO2sckbb73Or/zyL7O3vcP169fxPJ/RZIxlWUeRxv9vZsSDTcYDM/Rsu3S09RCgtAL1cCs1\nk+A9aHQ/jsPlofRNFnIm2TvSZxWqQB69r7oQoBWoQlIwO3O6MWNaCE0cSbIe8DuOonj/4llRCikV\nQhSEYY5u5ZjaHEofYmktCm3AlIzv773Jj5/9Kvp9wcTostM/YNmwOJzGmEKQMUu8klKiqZl8qigK\nsjyEH/GU8ss/P8/G+Q6GrWgCB0XCQVDl+rdGEFR45uI5lpo2H13+AaxkeH7O6UaD3qjHzXHAm9/p\nURzOsVa+wFx5kzPHltGlSaJG5H7MSBvRC6e0+yMiUzK/VkJpEEeKcBojsxRdTDg83CaSKb5jEGcO\nW1tTLGuJutZkXZwgvW/QPUzIJExVhO0VBAnsdyS9HYGdz1OvblKx57CMOqvzcyyslDHkhE+9+Bjn\nnq+QbU64cX+LJC7QM592b0qv3cZtZJy6UGFxSePi6hIrcxWqtsF03CEepMzVGgh7Jke0FwwKXWfY\nzYli2N4dEAQxSuhYrotQFq6qMD6IyF1BJmD5YsityYAFCVWqWCpjmkOp4tDvDRkPc957Zcj0I5/D\n6xpWViPtaVQCF7lvUhza5FOX0Fb0pgblaI5nz53izIs6576Uk3EHNYq5/VobYzLk+XMLeF4bze6j\nVxVJaLJ5bIWLZ1Y5cWIB2wpQSx9y/LMBtdoWNU1xutniyrZG/H7Cu9Ee/ftjvL9usWHO4FxVFbFy\nusqHlwO2LnUpiTrZKCHqCyZ3C4a3EgbvSBbUChWzyb63w5AIqxrQfjdn5wPFd/6XlN/63xSv/JrB\nJ05KTpw5zvWtId09nXY6JZEZWXiLvcyjY3yP04vn+POrN2C8SnuYEkdgViwsy6HfPmTSnzK3ZuM0\nNSbmgFHWoVTTMMyZHzAOM7ymQq/GHH/cxt8oMD2F1ApUkBFNxpTrJlkCTA2cxGP/hzHxuEa/r5OL\nEtFU4SqTs+tz+C0bp5biLSvceXU0AIIiTkmnFllikMY6Fa2B6rkw9siTAtMStFYqZLFAywwsZaHl\nGYfX79JYE5w4V8FftyidqDHa9bB3lul/x6J/yWX51Ck2F0/S3+vT/XALVtssX8iJ0w5qUiGfGLTj\nmK//1uGP/K5YMqqMs0O++A8GDLWrLDhnkYXP7m3J5K5JtP0coyvrHFyRvPb7U2xXsHLyHBe/nJPL\nawijw7Ajuf3uIrfeeAxPPo3Sp+zv3IJJg841jQ9fdfnwBxXu3jHAWKZSXWGp3KRUVIiThFoj4qkv\nuzRPR0BCGqdoes50lDNuL+FximLyOdJeSh5MCKMhK8d1nKXb6BWImKII0DQfAKH7BMOYN165jUqn\nXDixzmG3SzytUKmcoRddRck1sPtIYDptEE0jDncT3vtBwaXvmzj+SVr1BdZObpCqFKaHuFTZWD3P\n8rESsX4ZQ8UsnBjhr79GFNfZvz9l+90SjTmT9eMhUs9IcxdMnyX/HP14i1R0uHFzl2LyCHX/AirY\n4OrlHd7+wZTPXPzbeHHKJ8+6HHuphLmpGE12KddXCO+ZGMFfp+avMbFfZ/GRLSaxj+PmtHeaVEoX\neeObU1raad5/9TZO0cSsedzo/SGmPiGt/zmiUlCay5BGTrVaolzSaTgWvmkSBAGWKlH1TtAoP8pk\nWKJaOsnNSylatMGgHZBkU5AunXsBg70JtapLTo5XqmM6FXRhk4ZTosmYOI7RlKJZWyUNgVhgi4LO\n9jUc2UNOAigsdLNEIWy8ko/vWMg0B+kQDcc4c3X3ZipJAAAgAElEQVSUJRiOhmi6QWEb5J6H9Evo\npQpTKTBLM/iioU/QtBC3VKKwyhTFCE3PESIhL1I0S2DYJsNJRJyAITRMFAYFCQM0PaaQKbowGPW6\n6FaJOItpVH3SMGKpvkTFayFzD5UboBX4lTKG7lLkHrpeRVhVqtVVDFHDyDWMokAVOhomwnLwqh5p\nLEGfDcan0wlFnhDEAwxdw7ENbKvA0AuKIgHbQKYGJa9FlkUk2YCS7zLt98hkjq3b5HnO9e6lf+89\n8ZdqND75YyvUqyaGJhBKI5MStAzdyBG6hmkIbKGj6QJNKQzHxyo0vvnWNr2DDN0VFLmLK1ISNIp8\nRncuiqMMKX22DXgosv8LBOdZpS4eSqR4KKWasTCYveIoBveImaHrsxQsmc8KT1GgazpxHCKkyapf\nJTQUJxaW+O7tK/zyJ/8mb3eu8czK09y6e4P32m+TiQWcSYS1UCefxhQa6BqzwyP02dRbga6bPID1\nKeRDVsOM83EkndJAHC1YdE0hC4mwfCaTEY5esNCq41RcXKeKVApTmERRRJaGxMEQx7VBMzAtkygM\niKKAUX+IylNcv0whM2SeoRkWjl1haeUEtmvSOdymYlcQZkoBDPsR9aoiKzSEJVDo1OdamLaNsCw8\nr0KpVMF2TJI4QVEwP7+IX/Gp1ee5cfMSk3GPR84+yXg8IysPen1+7qsvc9C7z3tXttje67K5WUXP\nE0zbRjd04lAiC4nj+zx+8Wk++9kvY+sek8mI3d1tkiTC0D08v0le2JiOj2GU0Q2Pz33xSwhh4Vd9\nnnjiEaJJwJc++3nae23u3N9CeA5awV9o4sQRNE/nQZOhHbEvHkipZg2pPDo7R54NAZpQwFHzceTn\nEGK2adD+QrMAH4MZhSYQs1zcj0HhMGNqMGts0T6WZT14rXYU08yRpA9mz8lcYZUsZGJR6CPCsYFX\nSRmOFE2rwrSkM97eIl7OWBVLVFWL1uIKUZERpiFpks3AfQIKmc4aIjTyv4pG4x+ss1zSKNsmSqa4\nZoE1f4xr3y/44Lu3WfQqnN2oklsddrc62HMaJxZcUl8jMX3e/4Fk90MbV5QoOSbKCJhMtlk+7aNX\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yP/6vv43peLgYFPrsXM24EUft3BE744Gc6mO5W/5w2/FASvVAXjRrSh40Cg+SwmCWalYA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\nsH3TAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb75409c080>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ". . . . . . . . . \n",
+      "Iteration: 59\n",
+      "Weight Adj. for Content: 1.85e-11, Style: 3.86e-28, Denoise: 1.01e-07\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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2Rf60wLqc+E+bfPdfHmLnA1Q4o7/S5PLzm1x7pUd6/Yj+UxNymTEYfoDWnqxw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TDD27DpbWyztrvKnTdDZrd9pllClrWYHdTYXnsZTX9Kbp+SzUo6vmSr/4v5r7g6lbjveVAt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b/PkfV9hYeZXWakF9KeHwr9fpzATpzObVz14nCe7yzf9slb17Nu+/PWY8VZnOj2gmq+jZ\niNXlCpE5YMlz6XYKJkEJ8BG5jigLDFWyuzPi0hNb9Ac9PKmhGD2e++QyynSVw0dHZJaKWa4xDkPG\nfkQcDNAjEwuHraUK699so9sx1nuS052Uuz8PGD92WVmrYFVjTDFjMp6yvJqRFDazcUwuVahkaFVJ\nO495wajz078ccrgPlSWX/nBCogpcz8G0FU66KY1ZhKk6SJESFiMsR5AmOUFqE2oB16/rPP4rha89\n87s44RJaoqKHcxYvLHDgv4Gvf8C1v/eYz/xTD3f123z205fZ+/ku8ugD9PUJI6YUwKa8iSIvM7q3\nxJpbI7mUslAfcu3ZI6qLSwT8kId3O7z77j5RcB3jaIUCnW4/4c5PnsPRjgmHH5PmXWazFo/er+Op\nI4Kgx/DhGsnskNG4Q6WUc/FKjShOGBuSoD6i3C4I+4Kj/RK9Rw6POePmJ9uMif5Wdf53GjSEOG+K\nsvxciZCFRpxlKAI0Q8dMchIto5BgGzpFUeDYJrZtoGkqmqpRKpWwbA1NVSlEARLSNEEWklLJI5gN\n0YRJHCdoukmWFliWzjyYoyjZOWtDpshCQagFyAJdM5FFBig4rvkLErIkzgpsU0fXJboqMHSBzFSq\nqw3GEwWvGpF6McHUReYqmj6nsWQQ5QlGKnD1MmlWnDNAhEqUxhhCJc9SyDKkqhEqCeX83ND13dOQ\nj++OiOKcly9scG1wiKX3UatVtl55hVa7jRLMyYcDYl1yp9/Htaromc6o20O1VcbRHKY5iqESzgKk\najCdRSSFhm5qHA7HvHV2wkCRGFrGBUvhN559mpe//A3UwmHm51CcomZzmLvUGqvMSGlfvUC9sULn\n8JT0rIdWMnEyhTxTyAJBa3GDUZqitj0O+se0PIfpfIZlWYzHIzyvTBSF6LpGFGVYlkMWSNIowrMN\n0iRGMz3GoxnVepWZH2M6FjJXmc58DF1HEzpKXmBbFguVFpP5kNW1JU5uPUIW52pWtVLm4b17rC4t\n4fs+88inVq2RBHM81cCoFaR5hO3p2JbG2sJVZtMB/jDj9LTHymrBZz/za3zr3/5vPP3i73Dv4T7N\nxgoVR3Dh6hIvv/Icmubhlk9IUgOnNGY8cBkPEqbxGMvJiJMrjE5PuLT1PKmYYlcgnm2ysQHdsxGn\nnce0FleZDA3cekLVkyhnn8G3Xsfvtqg0qrRWLFKpsLiuI7VzKm0cpbSqNoowSbMcRQWlOH+5yRWB\nAIpcRQUM1SBOAkxVQpGdp5PIHJUChYxcphRJds6FKSSKqpEnGbZpIjk3fxuGSZGd78uTKQh+OcC+\nurbJpjVjHA4wxJxNa537WoNKxUbIFCe28c0YS+ro/gLXGy2sWkBodWk/I5jcH7C+bdFoRGSqzo8e\nnnHpSY+JLUjLIadRxpKVIQMNYQpSGdH0HGbLGunI5fRIRTUdYpmi5SpCyWl4Gq46QdUSyg0DYzFg\n5ZkyE3NGfDqi52esllysbInyWkGnd8qwGRGkPRr1GkfjPpVFg8nxlPvvVBj/PODS6lUsPJa8PpNq\nSPtCiTDJiIqMCpIijzh8fZ+K0yQ3YkS7YH2zRrMqEOGAcTHjtXd2+X//dMKrX7nGV/+Ly/zG7y/j\n98ZsLVmcjgcoakIguqAPYFjQze8TzUCInN6JgTKWFIXG8ccKk49TlpwSwyhn7leotl1qkcaFtRVW\nt1t8+oUXWVms89GDiD/99g95qI3YTrep2Rreso5nlbj7Zx/yynMvs/7VJl3rNZRygObrWHqJ/TuP\neO/BI8xBDUU1qF6F9madsSiQoymDkzHVBRO10DANl1k4xjRUZKGh5RKZmJiWgWROuekw1mfIZsTy\nzRyTUyw9Ihg5rCwbfPmLF5mdphhFRueez0Kgo2gF5bnNcs1iMp/RT0fc3F7HmFbxlw1OgoJb97sU\nFY3OcRffhv005P5JH3GQcPHiBUTLoHM6QcYHPLH9MkuLZd7pGyRBxuqNNq/83jr94/uk/gaF4lFp\njygzpHKjhf2jGnExpq9qJAz4zl/4WOsZw+4At7nGWf+AvWFCqD/i4/sqwzOVsqezuuqS+PtI3wAA\nIABJREFU2C5V2UZ9qFE7M3lx5Tke+4/JF9u8kF/glU9eZ/lKSHHhO9g3NbLMwakZVLZz9u936Y8m\nmHWLpBTjxYKREpHoKicHGScH0H8gqOUBzctLjCq79KsKpUTSsiNKmiSbFQwfp/yxL/js53Pk4wr+\ngxq6usLZzoDmQgPFO0E3c6jPCaca50rqf9pjOSpONSMzJxi2RqAUBHqBIEJ3VEzHIg0jDDXFNRWq\ntQT0GbGvkTRt4riKuzhELU6xCgt/kpGkAfEMeo9bhDNQsxIXVq6xsb3MsvsF0uGA9nrAs9mvct27\nxs47P+aJ33qWYvGvOJz8OxZuDvD9x/SLx6y1XuHG5a9RpFO0zoC9ziPs6ZOYs4zf/o1nefP2fZa3\n9xGr7zHy5ihlnbBcoG/meCs7ZDMoTwR5b8R8z0E3Vqh6bVbWr2JUz0iz75Hs7VPRLpAGKopqEuYZ\n8yjGrHo0m4JAH1FfH6JGIUYa070b8k9/938ij1J++K//F6qyyhQX1a4y8wXxrEHNcHn/zTmbG8/g\nBx3uf/QOSfAR6dxldfEa4+kZ4yFsb16m91ihdHnIxtWE0eiUYCSZD1S0+NPce79Oc1nj4kvLSH2V\nWz+J8CpXuPGkizB2MfWrvH3rI5bVb4K1wyee73PwkWQ6/4DNjQ2cRbDaMRzWSPsHdI5Urt34JzjT\nxyjqbc6SLjO1i6a2cQ2buT9g7yghii3Mmspxb8iNXKNzpKOkNV782glqfIv3bs84emRQWQowKwWO\n4eKpkoUNjZqbwwsJw8n7+D5YGz2ivsJ3/1Ajndzk3UddlrbmTPwy/l6bdCljmEywbZ14BK4QSL9K\nmMxwlrqkicLj1yo0jJzGDR8Uh24Pcn2GZZQZ9yIcI2U6lZiGRateEMYpmRIw6+gk3QpPbT9Dflpl\nPEmwTIP1rafpZN/nM7+f0/rkKZ3ZI/JqGz/Yol2NWf/8H3Hy+hF2LWDerTJ45xL7x1eZ7Tapt55E\nnqWU2eXi9RFPf32XQPkbDCza15a4/kUdRRvy2g/u8O6PFjEaW1RMwdFdlyB/jjSaoToK3f0Vvr+7\nR+SfUYgRCXVqtQaPdnY5+Z/HrN8oUBegfdVhvpIwmqZMjx0EOlkW0D0qkD37b1Xnf6dBI4tzdNVG\n5hFFkZJkPqpISTNJlsYomoLrOoBElTmWaWLrLrZRwnFNNBN0S6EQKbJQ0XQdTRegKCAV/FmEbZUI\n0wzNts+p4UjieI5j6QQBIM79GaiCvACpaWhqAIqBRGK7FaI0olHzYD6hXLJJyFFcm1TmWJUKcZCw\nsJQThgqWVUYppihJgSFdKqgYUscwTIJsjm7qyDSl6TmEsxipKcwLcIRGEqtkUcobw4CBYtFSFV5s\neFgixx+fcuPF52gsN6m6NslswqyzS1YUmI5D0J1gqIK5ltAJ5mSZBD9DR+d4fErJaNIfhDTbVWJV\nMFFT3ri/g2KbLJkGK0XCja1L/Oav/z2qtRqGsOgfH1K1BUEQIU0HbIt5FqDbNSI/oZ+cYVgG1VaL\nXLOZR3NUU1LIOUUxpmSXIFWpuB7CUhDBuXnftAW6oTCZQUXXKRRBOgsRKKhozKOELFcJophau8Zg\n0Mf1PASCNE/xHJMoDEHTUKREUVR006Gs6NSTlMW1DkrZ4ydvPkIRNs2mTZinyAQkJpPRHFtXCbOY\n1sIC006PpuWxf3zE1afbVOuX2Vi9jKpOKOYujYrCWvsZLiw9x+H+t3jy+pcZDO6zulxw9thnMPG5\nfNNhEnaYzVyaK5AnDmqSs9hawfGm1JwtzoZjLnplRGhg6PeJ5yZFPsc0FvCDPpZrslDeYHf3Lp7d\nxj+tY9Q1NDdFMVVEkRIHJVKOEY1VvFKJme/juQbyF4ZvRQiSIsdRJHGaIApIkhyppogoY15MUZUQ\nS1fQyMlIKfIIJc1RRY6QGVmRQq6AFCRKgSwgTTKEmmCaNqTn61NZ/stZndp5mFG9MUbqGmiCs4dj\nRqcRh50zFGEjphK3phIlcH1plepGRkCHsbpH0igofb5A1TTc2CQZGgxuTRnsCDKtICnHNESIbtXQ\no5BgCEUzJ+2m1GpleqbJbJjiVEGxVdQEzEKlWsvxVmMa6wV+fMTFS+epM3aU8YnKF1CcJdLA4MD7\nNv/9rQLNnvG8omGIlJ1un6QOWRjz6GcF0W1Jp7fAys0ajSdc7nV36Hb6WPUyihqiC4kCKIbOytVl\nsrmCbRhE+j6ayBnP5qjxlJkI8C4qvPpfq3zlpVVENSbOb2N6Y8LpQ1R1ikwLtHSKJRIUbcLJRxJJ\nSj5XeHQ7RQvWSU5s8qnGvY+n7HZ6TMwMy62wcaPBJXeBm80tylslhOnwL/7lj5geCerhNS6Yc0pt\njQoumekzzydo6yrH49eJK2cYFwP2e0dU0wrOvGB11eCprU1GtwoORh2G6T6VRY+nnnL58MdnjPoT\ndKP2i6E6xxAGsgChOmRZimc7pElElk5RtQF526F0zSPRutjJKYaSkdUd3C2HxmYVkZvsH+Ukx4Ld\nNyKqWCy0y+hmjUQWDCYBWm5S1wtMu4Qsco5DyUrbY55k/MY/+jRBkKJ7DbQkpdRokA9y/MMh9esW\n1apNBHzxC5/hR3/9AcLx0IyMpmVSKVe4vxvQNFxy2SexKkizoN7QeXh4l/BkxsEjm1/9+09z6eIy\n9UsO3/mbf4Wx6IKt8cwnDC5/5VPsnR7Sn/kMikOufmqT4X7AqpGzNF3hNeuIZtjAGYbEpZ8gF3cx\nv/gIETlIcQE/N1HafcJHhwx2ZnhNm/qihlbWUKjT7+VMdlS6D3LiqOBgT2PlQEGuCYRX4NsFVjfG\ntGyyoUDPBDt/XHC192lkqpP6OZankCgR+ae6xPGESuGRdgQLZ78c9VOIBp1+l1ojp9LOkFLBVKGI\nJRUrx8hUpKXhlCyEFiANCFKdMRE1L0eUu8xnMI8FmiMoqau0spc5OFtivP823bMdNpsLfOb5X6fs\nrvPCU9s8fP8talUPrYDewxkl5yt8658d8ORL/xUN9QZu/lMuPLlFvzthvfQHLOpQvVTi4gKI3Yj1\nJy4ij/+UldpFnruZk7iPiNKP0FxIRIaWSBRDAQ/smoYSZSTrJo8mARXFw2tGlG+8x+Jml07vNoli\nw3GKQGJKh1KUoS/5pKU75MsjlIU51S0XS1c43kn5va9+nd/7z7/E//Pf/hGKIhgO+/hyn89/bYtn\nPm/TKm3zz//Xf4fQm3zpG79CZlUYDJv84N/fwXEX2cuG7J7mGGpBEazhmlNyucCDnY9Q6jlJvsI7\nPz/m6vaQp1+aM4sf4SxOGB3dw1t+hqee1ymV9jh4mHHr/be5sfHPOJE/hjylaJ5x93CfFe+zPPzQ\n5Cj9GZ3BIqp4ElsLOdw548svfI2nPvk8/93/+ApD5yNGOhheD00RaKbOyhUXuT3j5HHM8ZnPzLcY\n9BNWN+ZU2gZZ3OfCVcHH70uOdrLzZLYS1FozCiGYBgWxrhAYBUVVwbEUUD3chk9jIWd54TL39r5L\n2b7MaLfG4sURupMQThKM1AFSNG2OYuSEKVxYWYB5jXt/tYv9sIbWTjAqksqGidOKUKRGMa9zdHfO\nuAtX1+oUsksQxfR3qqyZW9RKTQ66CaVKg3GkcLT3//H079zh8q9XOUgesHRNoFg+rvwcneh7mHbA\nwpogmGXc/pbAvv1lFuNPkftz+k5MNK9QXdc4Ofkh3cmASrWML1epuzeouPfw+Yjf+ofrfP0rX2Ew\ny3hw/xa3vyf4+K0ybvYEx4OHmGWP2TzDabTI1RKu3sAfpPgjA09kzKddEu2Axfs67mpBoieUtJx+\nR1ArrXLnpx1GyX+C1alC5mR5SpHnoCjouk6SZSgUGIZGEmQkWYyq6ZQ9F8d2sCwL17PQdQXHMSiK\nglLJRVc1cpkQJwlCCDTVwLItijhC03TyPEVRFAp5njAVx8kvjLC/oBwjKWRBIQsU6WJaFlKTqEZO\ns1ZGyIxqewG31MQJfVxVY94/I4siDK1g7zQjDqfMpiH9zoCzsz55HtPrZ2QapFlGkSlkGaSojGYp\nqSdppSo11eH+0QldJecwnHNhsc5FI6O9sIhtGTxx7RKWXhBMx4xHHRJfxzA10gKUQmE+npEUKYVm\nMOvMkIpKEsegaAymE4Rap9uNSVWL1x7sMs1n7I5zlqsa+jjEaXv82q9+leevX8NWbeL+CL21hKYI\nikJFMVUMU4OswLR0FFWl0qjjlMucnJyQTvsY9SZG5qMbOvNxwOLiCsdHR9QaVea+j+k2yAXkKKhC\nJc8lrVaTedgjERm5IrF0A6vkMp1OyGVGUcSMhnNKZRtBjj+f41kuszhE/EdqO+gSdFXBqdc5Gp7h\nWA7+4RGteoWo0Hlw8Jivf/lX+eGPf8SFzQvkaYKpq8gw5nh/F98zuXnzSS5evcDYnzAbddGFxkJz\nhelsSqO+yo0nLjIYHrKxfoPR2Gdp8QUODm6T5ypS2ExGGsedHFs1GPcz4viUUq3Giy9u83DnQ0bD\nUxaXNhl2fKKox6N7CrUWpFKysrrKyZkPGJyeHqKqKkUB5ZqOqhnMZjNcMhTTBBlTSJXZbIKumehm\nlTieoZkGhZIj0NCRJMTILCIrEvLs/Js8xbVUkiwjCmI8y0SQkxUZChBFCYpM0VQdWUCWS4LRhHK5\njKFrpFlB4E/RDQ2pnA/Fv4wz3lMJVg1m0YRBojANdJQkJggyNMejadfZm3SRssBzVRbtRfxklwAf\n4YZUjRpNHAqRc/aEj3WqoU4d9HchnEjKL0uyco7QJMooR84NugcRylDDyFWefmGN096McBhAlqPr\n542+3phR3k5YHRs82VvhxJyz6F1m2BozSg9xTJjnC2zqR/SOdXbUiKtlhXQ4pypK3O+k5HODhWab\n0UGFrDtnPJmCB8ZGlVSNKOI5DWMBR2shSzpn+YC+dcjWssuV9TIr2xqacv4fbK9EEpuko4y6EzDN\nj7gzH/Erao00VFE1waw3B2vC1JN0fAM7zckSh/e/Oycer1Bx1xifZnz8sxPqos721iLlrSbGugOJ\nyrJZw08EB0c7vPXggJ/eOuPLV77Op5eegBC6d0bk2wG9xhFi3+VmsI5VHXI6+oi1VsCq5dEeNQki\nDaNsstfbZ64WqNshSxdUDO2MWafgQkvl6q9dZhxEKIlC7yDAP82YSp3C1siFwHRVFD/EahfkdopV\nT8k6A0ZpD8/UKEoheclHrEXk8ZwiMCiZCm7Vo7M7Q4lqjEch82aAt9RiswzJSKPaXkSpFgRKhilU\nplJQW6iw/fQGvYfHLC1cpQhSWl4ZPJ+nNq7z2Rc+gz+I2Nnf50tfeom9Xki1YpKqd1BckPoOyyvL\nRCJECkjmQzp7KZutJR6EkhQQJY+WvcKiC9MHPfR4mTRLcBdMrp2uMX53wvZmlcVnhjxYmXL733wP\nz6zyafEcMltBzF3Gd3Mqyin6aspM+z5htkc7r2E/cKGdoLpjzEYMaYytujSWHbrBEOl4uHmdrDMn\nfHyG67nYC5K9fkK0KyhvCdQwJ8kF1lTS7wm6pw7v3Q9xVqa0203ifsZlx6PqljkbPsKuJFh6iKro\n5Mkvh6PhNnQc72koPiKZnSFNBaGplNsS21VJZYGp62hahDBz/GkZRatSLZ+S+Clr3osMhwLdv4R/\n/1lU3yTITK7WLxJurbP1ykXGfZubW9d4eO8hFbWCI0u8+oXLjOdN7FqNv/jBd2iUr3H4UUJl5RW2\nV/8JlYlKcHSA0qwTFn/Gky9NCRdvsdQu8+//ZYnNjZc5eV/SqF/AjP5Las438JX/k4fDn7JUh0xo\nWK7GcWfOXIHYj2nUHDz5CsoyjKt/hAw7uIOruP6nSMOc0M/pjk7JtRgl7LJ0zUaXU3Qzp7mocNCb\n4C14+IMxt/7Vt3nw1ntErku1vU6jbXD5+jPsv/8694KPWW19jovPtRDtv2BlY4TczfjN3/4s16+/\nwL29H7L/YIH17ZQ7777DJ+oqP//ONvP5ZwiHIQcHHSr2Ja7dbCG8WwTzGe/fHhD7lxCiRjzb5I2/\neZ2yZfObX9xmNP0T9kbfJ02u0e841Na3+Pj+YyLrJcrt32ZtfcA4qbK+9DK333qf7/3FX/JX3/8O\nnZ2niJ2Es+A9Vp8rqG5USAtBMJuQJzoVr8T0VOVkJ2JpKyQnZf+xgVBcMinQ3CnLtRL3P8joJSrV\nFxwCbY5QFWS5xtnJGLSc6alNEgq2nqzhlT4iH27Qyw16e3M0bYPHh6fcvLROv3eAmmTYlkERRdR0\nlcmRQ1n6OJUSw6Mme8dzqBY8/+WCuhuThipRYpCnMUuXQtIg56PXTZhcwDGh8f/z9l4/lmXZmd9v\nH2/uud6ENxnps7Iyyxu2q2o2u4fkkCOQGs4DAQF8kHkSMYAEAZIIvehJgKCn0UCAKAkzFCU1hi1y\nSDab3V3V1aaqy1elqTQRGRk+4npz7vFOD8F3Tkti779hr4219vet32c+w/jplF3zKatrW/hGl0ut\nr/Gjux8yKCYcJ12MssAxKggC3OABQTbFzipcWpf54HsmH/zFZZ6r1LEsBXVpkUSE6FpC7+RTpHgL\nO9JQGFKixjx/DCKhIl1AZQOztstyVeXy6osEOwO6n/apWSYvvHqdzddHHJw2qdSf4fDTMkkf5s02\nY1fhZP4J3W4ZkzWm91xmPzvBrk9pLghIFR4+GnB0HDAZ/wMMGkUBosgphEQhUigkTM1AysGLPSQl\nw5TOw8gMRUKWzyV+WQFNV7FsHVXLkWRIsnN0apIWyJJCkmZEUYqmCEQukGSFLMmRZYU4iZGQEYWA\nAoSkIPIcITTIEzRDZ+5NWFzrEIYuzUaVWnmBydjn0YcP+P5fv8XBkyO8IEOzSySqSsnLSAKJ2WBM\nGKXkqk4EjPwxzaoJmYKlyRiGThLFpEVCcQwf+cfM9Iz6aoO1SpvfWdtCzlNyPWOxUUPOM6Koz/5R\nn1SRKckGke9T+DCezFBVnTiXmIymKIqKO/ORVIvRdI5mOORqidGpy07iszuZYjoCPcvZUmDLbPHy\n12/x9Vdfo2rq+GMXWRRUWgvEeYaqSVDESLlMIc4b2STLKCkahSjozUY0VjtEgY+lKeRKgSTDPIxJ\nuiMWV1YYTwesX75ImgqE0Am8MZppMnenmLJJLutotk4uRwgksqIgLc5pYrZlEAQ+SZxgWw61soE7\nnJzL30mMEBKiyEjTlCyLkHQbu9xkMfM57Y456Q3J0oJyc4HhyQnrK8vM3DGWoTMaDLm4uIxlOJDH\nPL57h9ULq5QXagyf9ihbYKg30RoSs0lA1amgaQEdfZOeu029vsHe4YBmo8zB4QmC6xQUyNqcp/s7\naJqEU77JWz98m8koZevSAj/9wd9y9dJXOdjf4/qtK8ynMxqtBoXwybIIRbEYDeZYts4s7FIqtQmS\nEMvWSPMEKYyZFIJmVSPJA7LYo0AmCOY45crfpYGr5GSk2fw836UIKdKYNA9R85gg95FyH4mChBhF\nFEjiHIagaQpxkDAPPEQBmmagSBKB5xP6AaquoSoGiZ+SZCFp9MsZNE63fT4puhwNbJ65FrN4eZHj\np2MWljYo2VWmJmR9n67ncRofYT32qD6T0qlpGHKMLTKEmFDJ6kyNAEsWiElGMbGpydCaZPiNIVEa\nE1Y1pHmKnDv0ux5Wo8LWjTKDHxyjaQpKrkAsU8Q5zZVVZPeMZUvlRPXw9YIPtC9456Nt3HGZ9WIZ\nQ1bZWH6Zy1cyzFFAR65QJD7GcYpodTmoOziXl6jsKdSXZQ6nD5nPAjRJoxrZSJqFUOvoTQO1FdB8\nJudXfutZ1nQJIy3o7T1mv+Tj+/E5Hvw0pDZ0eBI85sKlBU4ejumvhAghmA4CvFJA30+IZZPBu1Mq\nyhpur4Q0WCfb1djupnixxnJrnS//2ioNRyPWM8bDKbmvcXrYR8plYifjgljmytVXmWspjdswnHk0\nNwSffXSA7mWsWR06po19cUKwHtBVDpHMiOVExrGrGE0LzylobWroCzKFI+PNJ0SHM8xSnUQtMMuQ\n+AH1lYQwDKiXdI7GMW6YUNJtrl1vUNpMEapHJgvG3QIxaXE4G1FzdKyXk/PgRdlFbUKuGGBLGGWd\n00GGl3h0p3vMI5fXX7rCR+885fatS+x9dMjW0jLD0xGZyFldNPF7x9jhhNd/6wqF5rLz2RnKacDz\nz96g7ihYssPuTx9zcNah6lkMnk55950uF2/6hHKBUwtJZzqZKPHoUxeJgEp5g0AIBmcytXKNaCAz\nCQ3ee3uXuViheD0n7xfM8pT1cgdvkLB7fIpnBuirCWt/0EJ/2mPnr06oaEv4ex5xVnA6nxEeRuSP\nCswLY4LgDqbQCaOUdrXJvpYQHmaM7QzTaRDlMsVpicnjQyqUqZRTNm+qSM8XeO0O7mRGI59jJTZ5\nYbG2vEQiqpSdJ+yc9ojzgnDm8vy115kMxlwIWuSLI3JD5SzJ8dXsl/JWrL30BatXFlAMnfHAYDJV\nSMyQ5QWbBJdcKggyAVmKikmczNCkGckcaixhdP8z9B2V8c6UctFGSDF+AIPBHay8i1RscfXmJR7t\nnaJUfP7qB9/lN3/tG/zswfs8+FTjjW9d5svfeIO5t8+LlS5aZ4SfjHnwTszFq5eZeY+4+vLvA7sY\nhYrc/IRrv1LnYdxj67JKrL7NeBTRPdCoWM+w5uSE2sekmUeUhJQNkH2LdHaBX735h8jBBgPzY8aT\n53h6/1PiBxJyEDAeukjanKhICJlRlTp0fzrGrtVpX1XxnyYEKORRi7OnOVntHoqygZL0aS8OaW9Z\nlDoysuaTixGPftxl//Q6tcMZhZRz/KhKSUr54ff/iKu3c1YvNbh6e4MMjcGhya1fqfP2z8ac/vCI\n65ctrtwoE2fbPPxgTuJdoFrZwA8UTs/O8MMQVS5j104JvV3aSzNa+9d4urfEvW5AYYa8/tVV7OoD\nJFtw9PMu668cUEmvo1lNdh7vY3VGNBtf5d7sO0xCmfJYQhJ9bAPQBYQ2njdhdCqxd3eVxZWIweGA\nRPgoWsF0qKFpEqtXc0xb4/0fTvni4xKXb69QmBO8/pAkVwkDiZyUiIDONQNdgxMesHDFoT8Zs3hj\nRDeWOd0JKSQFN4gYFwambhLtpUw/j5g91HBdhyCuEGcHCLdKNErJ3T5hIs4pq9mUaqVgqClMXAMj\nbNCpLhJMRyw0NiDKCaI5w0lId/gutdJVho/GPPj+5yxfnKBcDLAbMUXUQ5OgkKZIiUVLfgktXuXR\nyRPO7IwbL7/C1Vtv8J3/8f+k5UTsfTplf+cO1zo2o1xHlmYYQkIu1jG4jGDEWHTxphleOMCwI5qN\nU37r90+48LzHIKggmfvs31rh6YdN/NMmmawyV1o8OQqJhguEXZ2k/zWy9IA4domShDAasL8t4fkV\nwPt76/wXGjQUVUHTNQopQSlk8vzcMpVIAkkIFAGSJjAMFUkWmKaNqp6nZBomCJGiKBqyLKNrKpIk\nSJIEkJEkgW2rxFGIkCCPC4ochCTOf4zTgjRNEZJ6jrhFkKY+qmLgBUNanTpJNGepvYbfj/ibb/8F\nd9//jMlZD0OpYxlN9rt9fvzgHklRUAduXmtQM2ukUsE4DhilMe58zkqjQxzMSaI509GcQpVYbFUJ\nri7zQvMSW0tLLMQhReQySI7xgHJRZnvnCSrnSs+471KrNRi5PeK0wC45+KFE4kakBSCZhLnE8XRE\nqWwzQmcaBBw9PWVoKjQylWXHxJETllSLX/uNN7l09SJrrSa+F+D6BaqpkxcyXhhi2RbkCqkA1dIw\nrBK6omMaNrJTIsxiOu0Ow+4JzVqDo+3HyI5Nnsc0ljYolx3Ozg6oLy4zHE2o2HWEfD5IGJqOodvk\ncYzhOLjjCXkBNcciTmLKlQruZMp04pOkCbppMBvNz5NPJYM8F6iaSp5lCPl8x0UgmM/mWJqNpdpU\nSxVID5BlG1sxSQKfYD5lY22F3d1tbl26TEmWuffxZzxz6xkSPyIOU6b9IZe2LrC/+wVOpcqTvSc0\n6yFZFuDOpiw0LrK45LB5tcHYa5MjWN0wKZdKWFWf4WBCp9MgjAMEOuN+iG1c4ODJU1IvZX/vE2r1\nDkkc0VlZYjwd0mjXaDRrZKmgVq8SRgG6pqGoOYnvY+hlojhEkmX0PCbw5iiOzHTapVRKSDKJghhF\n0dF0jTyLyLI5SeqRRx7kLhTeOQAhc9GlGJSCMBKofze0S7ogCM9zXnRdJ0/PCWFZyjkJTgiSMCbM\nUoQkkSTgzaJfuBH4f3PadhV1klNMCzw3ZVmrMjNl9JKGIXJUTWOGSWKr9B5MmU9m/NpLBkt2iWl4\nSCmOcBQFxYB6EFGuCwYfhoQ9nYquUJ+YCG9E4eSkGRReDL5EEoe0L5kM5oc0F10kt8L8OEAvtag1\nKuiJQhUNpxoheSl7myHf/q9j0idrqMebDGwTkaYM7ZyFvImRwiCXufi1Fzguxnxy7xMK2UYPa3Se\n01ncKnE62UWaKix26lQmTQZhjNfoIi4GdDYjnv8tFeVwj8P8FFnPSCWPRJaJHAlpr4x2JlN1q3Qf\nnNGZSwRZmd2RwywdoiQqYtGnez9nsCdhaRvcf9hh3JURTwzCXog3iWm9ofMbv3+dS4sO4/CU7TtH\nJCcpo6eCOM9o1RwWshbJOKW2Ocdtjig/ExBOR1SaJcKVMckTHenju3QHXTrrBfUFG79eUBEKVhqj\nKAF96R7VJQWnVcaRS8zjCG84Ry8XCDsm8yJMLSFKjylqOmvfqBJOCvr3oXsnIZoGXLzWwQtPqRsh\nFgVmuUJULnHwbkCcWFxRVvCHX2AIHTc8prwkmLpj6s9Y3P94yEF/xtMoQ00Slr55k5Kc0SxpmC2d\npVKFd8fHdC426bnb7L49pDnXuRd3Wf7NEksvGAjZIxFfcOBPaF+4QqHrfO87D3hu6RaxHzN/pOEe\npzAYII+/YPHKBrW1Ott3HjNHopdOycMaSTnjadTlJw9OKCsGu16K0V/iqnmR6u/1UKe5AAAgAElE\nQVS6nBWfUAxPUCOVSnWZfvyElZWEWDthFIyI/0kFcTpmHMf4vkWwb/DS9m2UUof7wTay8pRnS1vo\ntMlHVSxMzFmNyYc+rl/gKyrzvo/7WUTbtGlbMy7dShGbPpJrgmai+BK1iou2ZNNUm2TvWGzdvEAs\nQibDEck05t7BIdkw5sXpJaLhIdOOBCWPifrLoU4tXBtQXvYQqYTb1QmfxCh6TkiB5ChUOjKFpuIn\nJUgMTFUijz0a0eu47/0eT4YRdtCmJM+QjT0e7v+ItvkastJiFnxOOxWMws9QKnW+8uqvcffBD8na\nIA9qPP+Ngpl4j6YToDt3WLgywdV+hjPaIrtY5dpzx/jyPpI4Jhy/iT+/RaVzk9WtIZPenIvtm2y8\nCvPxn/Gn/+tP2L57nW/87h8SqyM+//wvea3xB+wc/5zR8YjEW0BIa/T9T7nxcos72y/x+BOVeR6T\n6zMoKwyiOcgKpDX8NMORl8h8g/2P95DzAtWQWVy8zEbrdU76AYUq0TR1Ui9gtXKR+/ffxzH6pFGE\npqnkqUTgldH0nGdfXOfz985497sl9j+4SXmhT+/oHu40Y9SrYDZOWFqTmJ9W0EtzRtPHnJ5UUIo3\ncBYDSo0TutsRrfKztJafsrHq0O8FPDyJ0X2dWF1h+coSlepTWs0pupIQKvfQnTKN1gq7uye0DBPX\nLYMIefhojNH5Ns5LR5SHFiNfZXDiUIpkbCcmNc4/Sw+3Q2ZdQblUY/HyGWrZZOoGBH5Ba1OnUpKp\nXMmRJYOfvx3yt3/eZW2zhqR658AgSaW6qKE4HqnIOHmikUZwdBwhRB3NHrHa1OkflDFKAtXwCdOA\nUZAxfs9m+pFMni4TSC0yY46S1smyKQ8/jUnlOu0LEZbhQyhzslOnf0dhyb6IahuE4RBNT7ArgnAy\nptFZpJyvoTQrHJwFHO8u8v1/KXP92T5v/v4pUXNIkkYsrktMZhJS3ObB/gHo6xilMvsHY97YMPl8\n9wu2nnmeo4+6LOo9Dr4osfDiFE+eUyo6zL0WieKTaJ8BZSwWyA2F9obJ5g0bR6oxjt9iGOVYZosE\nl8WNGHKFxP+CpcWIUn3Mfl9mvF/mzk9SJk/KzLobxHnG3E+YhWc4lZRAPIHJyd9b578Y3pYcIRfI\nuURRCApJkEcJFNK5dSmOKIocSZJRVf086VuWAJAVBTi3SCVRTiZH51hbJPI8Jz/f6yZXVEjPrVlC\nnNumMmQgJ0nOF88pZPLsXFnJRI5hw9yd0qwtMtgb84O//BGDE5eFyhIrzgK6pJNngmvLDb756kVq\ndYd3HrqEnsujJweMJjO8NCVWddqahaUUtFdabK4vUq2aJImHKAqyPMWfzAiOHvBYldCQcSINEQac\n6lOKKGU+8+k0OviBRJr5RHGKZlh405jj/hRVM4iSnHngopgmoWZzNptxNByALLAaFZbnc7IipB0V\nfO32TV751lcoV2sslWrMJxNKVgnDNPGCiCiKUBUJRdXQLAsF0CslClmBQkYyLXIZyHLcwRhb0jje\nP6TZ6JBVG1TLJYbTIUEa0+y06Z2coAhIwjlpECOSjJxzlLDrh9i6hiLJZCSQ5yRhhGpoWHaJNC6Q\nlJgsTXBKZXRFxZv6pHmMIhRyUaAIBdQCSagomk7u+yiygWmVaNZrhL0JoR8TyRarrQ7xdMzV5SXC\nyYgsy7hy5RJkBfVqjdlkSjxLaXYWsfUK3e5j1pc3GY57aLqC6ya42hGWXDAePeSNN17n3p0DLlyo\ncO+zfUpKwHwu4wUecSBIai5xFtEozUmmKavr1xhMt1nfepmzwWNaRYfAixgMRpCrREmIaRlYts54\nNEWQI0niPCsmlc/3UgoZXbaIZgMU2UQSYJhlsmhOGvnksQFFRpzNKDKPMHARqYeET5HEGHpOlMdk\nUnEeXkmBnyXIQiBQkOSMLOUcXSskhMhIknN/tSwZFMB8lpKEBUn4y2ke4rMB67c2uXwZelnEyf6I\nTNpEkhM0pSAoJKJBTBpkNJQqq1dNnuw9xv9wh2u/opDNQ4rYIRcxJAVSuUBt28QzGa8k8PMcaVYg\nVJlomJO4BQQZBRKFFTHp7qFXMoKJj2Q1kPQZ02lGteggGy1+mN1nPJsj/19rXBm+QLP6Ou5ZgOtN\nEW7A2e4en6uH5FGC4ZSp/Q8xhpAJjWXOglNSa4cXltfZ6Q6RfJMi8NFEm8Vri3zj9pyVb95EMz5h\nR7qD3Avxw5hCV1CDjFgH3/d5/IlG2Z9TStbpzUP6c4PdkWCmqEzbBh8+8lG0jPIZiKDB9KzFSWCz\nfWdAfmRguQWXLzf4+j9fY+WlEIMZQ+cho66HdxLjvi8RJBppOUWRajihycpCnUHpCcuvxiT5PW5c\nXyGsDhhJIbHioOQK2WGPvaDLzbLHQqqxkCgkbopSG9Ks+aTZlMeHI4J9jThVWN3UsZYM4sJH5OB7\nPRI5ZG4GtJo6/mmKFCq4/Yjl1gq+qyBVBarsQexiag5JmqCpZdJYJj2w2fk8Y2VFYnmtQ3yQsWTI\nqA2DtSsZwUindXGFvbMjht2YdbPKhumy/usmvjfBWbQIqoLeDzLqqU11WmCGMe7pGZ2qiSJczvpP\nsWshiadSbS8wmkw5Fke0l00s6SLxuEtwrJD6EacJnBz7tJvLrFVaGP2LZKMuQRxDJ+BO/BhTcTgt\nz6iNOlwKtzjZh8feHq8sqyyadXq9IWnmnofNxh4r1yrMA5+Dpwn6YIo0bpHft/j4XyeYDxrkr425\n9et1hlMTfd4h7anoOJDK54TGLKW7lzH0xsyShC2njCNmoO1jzCeY003SsYNaL5F6LpKaoZdiFuo6\nW3UdshIHE4l+5vHJ7hnVrM3n38t5+XdeZOy+zQSDybb/S3krQjKsasj0KKO7Y/LwxwrN5gKzwwBr\nM6KyFaA2QwynQDXAO9Sw3NfJ9/57isc2jfYPGB5/DIpFVilTcq6gLoUkxYSNtVe4fmvOydETlltX\n2f/iRzz35l02v/Q5G1mfnQ83mR9uYU2v8C/+2/+ZZ2//Lt/8D36Hp0fv8PTO+yysnlC5+C5Z+GXu\n33uX5aU2XnaGUNu8+pU3icdtvG4LZ0nnwqbD85XfxlYWqEhf4VeeCwhn+4xPFunt/jpqnPJ4tMvZ\nkcLsUCEarNLUjzk63mNihnSEQS4vYNt1VMXDdV2mcoGXTdGKKmqsQqRy55PH3JMfs3b9FbqjmCU1\noxhHyOmMr715g93DE44enbG6foVpdMps4nJ4NsUsH7E3TFCrFldfSSmVErzQQ7G22HztAurCNoly\nwuMfv8D4LCeTDzF0m6vP72E0n7K/J1GkzyLpPbL8PkG0TH805+hRgytX/ynB7JTtux6N+jaLy1Mc\nx2H54lW+eD8in1yhod9k5+Fjbi2/yVvvf06oRty+1mGYPsP68gH7+1PyvIWWV5GDBsenQzQtoqLJ\nyHmGInucHYDqZERSAYlB2bawnBHTeUJp0aGxavLojs/P7sRUdJm1TZubX4nImSNEThhJaJbAKukI\nKaLdgmYjByPkyWczjnYHrF8qs7BmcrzvkpyBHq3SK1IGygnIAkWaUbItxv2Ce+/FdA5NmhUTKVc4\nfShjRw0Mu0w0SZFUC8u5QHf+hBuvHvLSV/e4+ykk0jqXF17Cu9PBUr9E8EDiX/3Rf8ez35yjdnzI\nNWrrEUVRsHt0yKirYC7MkCsGDw8eczbVWDYU6gtV4n2L7bcXaF+XKT93TGEq2KUAnRUKUop0DpJO\nR29x89kF3MM+vQcp9z/NWLxWQ5JVJCWlUopRL5+Sy0c46hSJAasObF04o7leMHrwPPd+coFP3+lT\ndTo4VQnJiXBmCZ8fv/f31vkvNGgIIc6bGXJSAaIQKKqGLAv8YI5a5BQCJE1FqDIUCggJTVORpAJV\nVShyASoIRTrH5Bo2cRSRi5wiz1E0mSwDWYJCkUnDgDRLkdKcPEnJBUB+bu2R8vOf2yilajdQc4s/\n/ZM/wT3zaBo1xicnlOsOXuIioxLNZmhSRu8s5raiUNus83svPoefpPhxRJpk2PUF/KjAVAX97hH7\nx8dkcUxFMon1nHwWowgZK1fpTV18TSOOEtQAZN0kywL2Tvvohsl4FuCUbR4ddkkVnVhojLtTJFlC\nMTWmU5dxEDHxAur1KgQ+s7MxK6rEr77yGi+9/iKapVBJMsqxTDQPUdCYzuYEQYphWywvdvADjyTK\n0DSDvCgwS1WEZqDkMoYpExYJsZdQK1UY9HssXtyisB1Kao3MkDC8Id3ePiVZgTCkWq0xH41I4pQw\nmhGTUUgKiizx9OFDOu0WUTDHTWJkRUER58pTnES0F+p0u6fMpkNUVUEUgriQzrNXvBihnw99imWC\nlCFzrnLVGws0Gz38MGFRKTGLA2ajAe2ag1bk6LpKtdbm8fYOlWqVOAlZvbDO6bDH0fEu9UoTLzym\nUayzvlplf/8x9VKbXJxRs1/kaPcejZrGZDTjqdLDC0LK1hbLGyMuX95gZ3uEZcdIcp1SBdxpg8ls\nSrW9RK0t4eVVPv74Q67fuIFqaNRqZR4/foimpvheStkpEcZgmzrD8QhD15FkmTzLODvrYldNLAv8\n+RBFUUmzkLRQCQhQZYEfDBEiJglmiCIki2dIkiAOQ3Q5xdF0UpGRFxJpESORo+sasiSRiYI8L5Bk\ncY631VQKcvwwIIkk4lgiCmA6+fslzv8/zrXbC5Q7IaGdYpsaX+x6eIdjmvKcZlRC7SjkWsZx74D1\nuEykmlSXmli3l9nX7tC0NMyZCYFBEUhoqwZrX2/RtTN2PjzFfRBwuWaT51NsJacbQTQKKLQMYYR4\nzDAKiUxRUSqQKz7GwhJxqNPuvMr3viMz+66BMlvkldo3cacTtto1Ppt+ThG0kCWVhhfj5mPcaUhR\nWMycGI0EyTFo2BJmy0IzZYzVK3RelLn8jIOaTMm1HSKvh6J8wVauYsiCXqZCmnKohkTTgnbL5pGf\ncrqTcfNyk/npHqEEnhfjqxGHe13mMwlLanLvbzyUgY3sl7m/PSEeq9SFw9YzGr/9XzVY2IoInYih\nOOPJT4cMP8yYfZqj2yWatoOpVKjnFaJJhP/cESzfxWhHaCnICUhZgLPpE6t1ZqMeaWwQajFpkXMp\n0IhFRLGicFCaojkztDgiijP63ZiqbKHpTfq9MYeTCRXFRkah0BRcL8S7t08p3aIuO6yXTep6E3+Q\nILegN5lh11UUxWfQ9RDohH2Jh98bE3sCUVMp2w6e1ycVAaoS8fprNRrRIkVtE9UsE5wMKOUJdt7n\nwrMqveGU8nWTcQif/bkgO5GRhUwoF0xHI5qZw5vPNzjNy4R6lXvvziiGKWkXSi8WrF5pcf3F5xl9\nesZbB28RRT4PPu3iqgFXvnqZhWdMpKnO69GzvB6+waG3y333Ew69J1h1mfryKnLcYPh+ROPVa0Rb\nPXr5hERAMZHRsRFegm7GuLFL65LEc2U4fsfl9OcgGTbRbpny2nMU7y1TaqwQyhFpkDDvHrB+pYZc\nTZh5AUVYMIoVkqLM6Khg9UpI7BzSaxesT45Q1CYInVhNyYIB7nGMnK2y3FRRZIfNrSb3ngy4O+iS\nzzXe+8GMMJlQWatSssZkxwrwD2+1zEKY93LOnhZMjhWU9DJN7QUef/gejWEJNY2oFmOUdE7UM7lU\n+o8YfPSfcnrwkGXeh+N1LGGTm3WclU3sy59x+3UZjHdZu7SDWnSQsjJv/8tHxONXuFq6jRL+L8jO\nKTe/9C47H17gO//iW9xo/ifsfvgF+9df5l//icmXXvxvSNxPUEUFxdhl1D/Cf/oyX/6dArv+EybF\ndzAqt4iDr3Hv5xXO9q7y+j8rM5C/zdrCN+jnb5FJB/z7y7/DJz8JKaUddg/+FZXmM3Sfdnm0/S4N\ny2Bl8yo3mjLTI6jqDqXFJu7JPt3ZR8j6hCjzkcQSbafC2DvFWlYYdU8pRp8QCYtL628y6J/y+Pg9\nNiOd1ZtHXH9uiUpniT/+47fYfXgbr/81KG8zGD9EKwsePHpEozVGCIXGhfvYywccD6bUqi2chTO6\njzWaC6tcveYQeX1OjlYowtuoWgN3+oip26G3p7K8tsWt5yzm+Q+ZTc7v1MpqBUnOSBOLgy8qdI+P\nWdvoMX0is7R8gWLxrzA27pGOJD59q8sf/Rff52D4E34g/XNKtyekWohuTVhJZOZTDSlusd+7w9BN\nWLgmE7sKXvecUjrs+ijljHkC4TwlEi6vfWsRKarw7l+c8eiLiFyWaK3ZmDWVVPEp/JRcLrANhWE3\n4tGDOVdfkyhXA3a/KBBBxM1yCW3sM5jNSZkzDDx8IVOQoOkKnufRqi0jFSbewYi4EFjqAsX8DNta\nZtp1uXp5Gae6gWI/y739kLHzGPP5p1y/nGNWz3ju8j/i//7jy3zvr34McpmHj3JU/Ra5M6DaPiCt\nFtTkFCstUKSAgZeilg0qtQ537/yMS5eusXT1Ij86+Jj65J9x951/yz95TSUrVGRhMC0OkIWLppRQ\nSUmIcOoKii2AMrMTBUuZ4xY7WET4cYij5wgxIKGHioFa2Khij+XNkPX1BWbTFsOTMgvlJW693GHp\n1pjv393jz/7676/zX9A6pULBebou5wuwqqKTxAI918nygrzI0CSJIslQTIGuKSjq+WKZrJznByiF\noMgzkjgliTPSNEYIgSTJSMjk4u+apuw8s6PICpLk3BaSZCFCqIgCciGTkxArCokS8hd/+dfs3Tti\na20JJU9o1+rMonN7jG7YiBQKVcPUHeZZzHwcMj99jKYb5EhUnAZHd+9hWhIiE2iGiZIJTGHgzzxk\no8TUjZFkBc1LKJKMyXyIkA2mqSCZu0i6Sc91KeKM6dQlOEuolGsESYYXuOSKRJrmHB+dEOfQLJtY\nVon5dE5DTvnS9UX+8Td/k0a9Tk02yd058zRDrhpoQiE3Bc1WiyhJ8YKIIssQmaDaaZDGGWlWoOgm\nkqohCwUvmGDqKtWlNlEYU2o28ZIEgim2VuPp/Y9QNIuyZTA4PubC0iVO9h9jmRZn3WNazSp+4OF5\nAYbuUG0s4YU+QlXoTYdIQsbyHIQkEaYhR70uURRi6QpJniGKDFtxCKIIy7KJ4hRJlsiLlHDmUW/U\nOTgdYFk2i0sL5EVB4vmksknDMnFkCSn2kSWZfrfLwmIbESVoQkVHcPHyRWQTWnaHo+59FCXj5PSQ\nxaUlnu7tICsppAdEacHHH37O5ctfZjD5iErNYXdnyNXbJQpJpj6RMPQKn+/tEMZ9Bqcy9ZbKtWe/\nzNHJIaXSCpevmPizAH80YjwMWNtq4M1yGgtDjnd1suyEOJJxTAOETl5I9AcTdFMjjmRkNURkkI76\nWFYZdz7G0C3CPCZOPdLIIw5cROYTR1MMTUGWchxTRhU5OQlyVqAbKqpikMYxsiShqgIJiawAXVPx\nw5A0AVnSkSWDJEqZezlJ9u+Govv/eqS2Tq7nRKbE2WxILCROBwH9ySHPNh20uk7VqVJ1fAa9I8Th\njNXXbIpIxxKCdiyIZiOCCy77XoAsbApbZevNJjPZ4NMPT/BLBgsbJs1WzuxpQjgMaS+2CcIxJcOg\nfxJgShWKMENTG1AqMXpk0w8WufdfbqBulLEPOkxfTrDWNY7zJ5SMCp4Us7l2BSvViN2MndEhDaPM\nceWI5bjEQpRjvpITDccsrSxz4+oFqjc17j75lESfMvV99MmUYQLOQoru+0wbCdNwxkmh432i0nca\nFEOb3nRKFNuczmSo26RCZjoV7H6QMbfqDAYmJbND7yii/3RMOJNprVV44/kG3/o9jfLaCbEa0fd8\njj6QCd4zmb8lYTsasgHlRgs9bKPXLNTFESeVu7zwjww0w0NNKtCrolsmNU2ir8wYvNSBF1WiccrM\n28dd0bCWYM/NefDI5/D9Ic1Mx84qzMc6qtNhdrpEmraRT+YcHPQxOnUyJSYUM5SwwLBXyCKL2rKO\n7ys4k4TJTkR6AdJ2Rt/bxTIX0UwbrdBxjwOUagXJyPBqEaEeE0URlTUbueJRV1P2HvhIkYdVN/j1\n375Eu/mQnn9KeXEBkWe4rkGpbhOMVVxLQ1QtXv6ShRJ4jLsypZpBY9nhkaRSyR2yukro+URHHmkj\noXWhxepr6+zcP6BVqnBxsYliz1C0PtJSzDf+85fpfndK/ucF9uQKby/NGRj3KVPj/qRC865gca3F\np+MRYVhwyVokOK3SumRRUWM0P2KrWSVtDXhc9Rg9iFh4fonpts1O0ae9XyXbBrlVpyhFUPUIbYlh\ncUS1lqJpZSppjcN/OyOYmzTmKsFeiScfbHNmjBjoJi8mE5JQIrZyzo5Spo9ccm9MraZTqSWMQ51L\nmyYUK5iOQXvZ4iTZ52DHZVgt6J7+cva5khSGXZlpvyAOXOo1g4rVZqF8A79/xva7BzgnDVYu1QnC\nlEg0iCd/xu2r/zGZq9Dtfk6ndYtZ1mf16o/5zf9QQtJ+RlFUiDIDWT5EYYXLX3H4cPJj/ubfjPjH\nf9gAp0CIHmb9IXE1QNW/gl2T+faP/zcuP/c8h6M9bpsTAFLRpd0Z8vD9W8xvXURqyzRau/jSu4Ti\nc54eLJFFX0M2+wR9n6nWRFFeRVBFjp5w63KZS+vrpMZXODq8x1//5SPikkrRv0l6NOErX/6nnNX3\nORsdkRtQrdepl17ks0d3kfTivBayCamuMR4NEblJdBrTXGjx8d0/Z01ts/Npmds7EWI44plbJvee\nfIdSxebowYjbN8vUNra4LlWQ53Xuffg5n3w4ZKn5PHZFZ6/4KWlhEbsynv8FsnERuxzgzvucHnk0\nl9o4qw95cm+BdNYik4+4+MI1qq0eeeQTpwcYlUXGgx6lKYy7dYpska2Ni9x4JsDLHzP31ympTVJx\nxOLFOr37G8xGD+nu/i2dlkpwoKKWIFudQ8VFz1QUNceQ+2TjCNQGVinCtFzUos58PuNoHxRbJ0gi\nvLHMSrtKZyHEMIckccKP/rTG6OFFBg9jcHYRpYCtSw6pOsdSNIZejf2Hc4yGj201qMgV/JOAw7se\nZamCZIa4UkouGxRpge7YFERkaUAupkwnZzi6SkluoPo2RuEghxkX11bZPZxiBtvUOyVUq0x3+wIH\nByG3frtP3YgIOKLywnd5c/0Rd94RPOv8HvPDkOOd/4Pnv9VAbZ8y6s6oaAu4URdFX8bC5cP3f8pq\n6yq9/ZDE3Kd5YZHBUULvUxX/sMrAO6JzISVKDcySRkpMzIwKJXIlQLc75LJNiTd5+uBvKTYDmnUD\nRzHRiAkRyHkbVapSUJAUAlnkeMGIaXDK0uozLDmCSxdT2s/0uJnG/051/gsqGgqyLKNpJmmaEkcp\nWZ5CnqGoKnqWEYUZAlAViTQPkGWFNI0AizzLUDRxnqgdpeeoUylDV1QQBUJIKCkEYQgUUAgUWYJI\nEPs5RS4RBwlCipCESgGQasiyhNATHt/boYgMQOF4NCQMQVLAVE3ieYSp66SpIFHB82PKjkXDKhFH\nEbppErpzTNUinM4pCpnR6YA8z4EC27aY9npkBYRJQC7LRFlGnguiPMWNUjw/IBUQ5wWSrpFnCugm\n+8MJaZ4hhESSpcSiwClZyH+H6DWiOc+vL3BzY5FXXr+NOldIul3SWpOImLJdZj6ZUqk3z5PRkYmS\nkEqjRlFIOJUKaVaQChnFNkjjFE0pQE7JixxZVcjylEwu0HQddzLA0DWOzw6ol1YI0x7ZXGepsczx\nyQNKGAweP6LcbnMyHOCKAKPsoFYqHG5vU291EMKkvNRAFTmqlJJGIZJdIklSZLWMREEwdbEMjfnU\nRdE0ZnMPoSqYikYShNQbDUbjGRvLq3z04B6bW1sEsY/VrhDuHmOpKe5oxMXlRQ5Pj1lZW8X3Q6ZD\nl8TzSZpl8kqBP4hoqg2KRCHwRmhGlS8e3aWzUCP2QdVVVEsl8DR0M6D/uODqVY1hL8Cfg1Xx6CxX\neHB3TLWqIMsGQrhsbKxw784jLlxr4ucJWebjTxKsZok4gPk8olyrMHGPsRwdu6gQeBlhlBP4IUIo\nGLaJpgvivCCezjF0geuGKLLGfDaEUsjEHaMWMnHkkYZz0swjLzJC18eyTUQhI6QCRxQoSkHsxyRy\njq4pSKqMJBUgEhQhMQ8jVNlGKiAMwZv7hJ6OO0uZur8cRWPupCxVMvATSBLU3KHTbiFRx5u6BN0x\nDbtBS29yWIzJ8pSdu8es1iZkjuA0mGNUDPqhj6jINNIRuQdZHKDoMaps0t2TMLUm6VlIPnXwpyHy\nksHkYI5f6ATDnBwbXJWGvkI93KKRXuSj/2lIf1mmKKa88vwGT6MeyfFT0kOXC9cuUnI6mLUK08mQ\nzZU61+odRkc5N5ILiKhLqeKRZWOkqoMczHn4wQeshQ52yWOAT1F2ODocIFmCySgHJSXWCmZGE/+g\ngghrHG4rTJIMTa3yyc6MYaKSeZCOYdQt400EomZzdtilmqtorsHLmzewShmdKya/8e+F2BsDYuER\nC43R2yW8j1XSuzXWNB0JQZ4qWKJN6WqHfGVMKgXM8j5uatDCJBMSqeRTngqKUoYo+5S/khOeTllV\nLJ6c5nz3rW3K9RqG34Gwg3XqcHIa02iscOPaMhc3rvHRR3cYBzLRLsSxhjdWGYdjmp0F7KZO7pep\nLtQIDZ+jnT5hLmHECvHc5ONPjqkuayiVKpoaMQwlpHIJraSSq9PzFUNDkMYChRBnTWYanZEem0x7\np3RaW6wt6tQvLBKXXdz+iMTOSFIdo6aBpBEGEiuORqMeMh1kiFJBJmQ8f8RC9SrJdQO/KPjoyQ8Y\nHvRwj1zS9SlRFrA/PuD1L1/gwi2T8cEOs+Qjtq5UubSZEE4lns2XuPdtk83ja6w6G5TMEllTYh45\nfPC/j4nSjGA04zh3uLG2SpQWNF9OUEs95vEQ0R3QrsLyV1f4YKgxnBlIUoX7WcJBcsrk0KRkmpht\nl803oGgOiGwfRY+w2y0ulJb4bHjKdsNl8HGfhaLCRv0E41qGsHLmfsr8RMhBE5wAACAASURBVHD6\nGKRIwdR9bqzLbLyo8GR7zg9/7mJKFpdWLa5dNxjoFY5Fn4kn4fVi4B8ehx3NYRonZP4KDePXqa4+\niyL7VBY3ub7yEh9+9i75nkDTf5Xf/PofEMcpmrXN6sKcVA44eXiLyVOH2cHn1P4f3t4r1tL9vM97\nvl5W72vtvmfPzJlypp1eSR6xU6S6LEeOZcFIXBIgARwgCOCLJMhdLhIkcQLEsRM7kixDlkQ1U6RJ\nHR7y9D4zZ3rZva3evt7+udiBr0kZ0nu5btbV++H/4n1/z1OYI+tjRDqHeBG3V6XSWSLKPM4+m/Jo\n9ybT9y/z7u8+ydrLPdpPWYyOJ3helfUX1rn6ZI9b/S1mDzLinSu8/3qOLy03ke1zWOodpul1REnG\nqkXEaRdLlhGGwed/XuePf+sj7t/+JoXGBYTcZ+eeIHOep7n+Y4Khw47yZ5TbR6xtNPnlv9/lD/4Z\n3PnoHcQ4xzvvf0igD0jdxywVn6Lr71ArXeXyusXe6AMOuhNUUycWAXEmqBfr/PxX/wZ3720Rzkoc\nHL3PQrvFg/eeBFNlshvhyxoP78osNgvsD36HjRdqpNEAJS8wq0OuXv4lhrNH3H1wn8htMh/mSIWH\nIl1AV4pMeivEM4jFPRSjwGQYEIg38cI8Tz2zglL4M+Z+ntjtYNcbRH4VXangTnO0FseUChqD6R+y\nUBmzcy+HLC/SH8S4fpPltZgLpyt89MY5vv2D7zP1PqPUvsju7nUq9YxwrBOLOkJMiIKYJBT4cwGR\njGaonHs+pX9YYPOew/7dAENXEVlAcaWMTIYXxgSZoFLL8exVg1Gvy81PFdxHSyQ9iUB4VBsFoqRH\n6jcZbiXo4phnLlxg1A357MMtWg2dJBOYpqAgG8xmCVEQkmQSFjlid4YuRbTLp5D9AratoaYLFIo5\nJtNdzj35AkK2yBSF8WhOSXuWd77/Ppe/kWOIjOd+j+LZD3n6cxe5/EqXP/u9/4nuB09jP/ib3P1B\nQO7mnzPfnmOHCnI0oZAsE/cnPOp2Of3cORI5YWvnNmevLDOaBmTxEv/bP/6EJ59RuZ4bkK/KdFZr\nWIWEVsuiUE5QAod2tcNdaYujIzA/lDhbWsSuqcjEuEkfSaqhynmiNCOWtwmFhyblkDVYXpbZ3jIZ\nTQLe+H6Xz5UqRKn4ifr8pxo0FFWg6RKKmiHJMkgyWaSRRieGYk1RSTXtJLuhSpiaiaxoWMbJeVWa\npsiphCwpJMmJVVqWFST15AwLWeCFwclvkiAOIqIgQSQpmYiJ45A4CUnThCzzkGUVQ88w5RQPGc+J\nCCSTu9tdJF0jjROUKGGunBA0pCAm9kNyhTxSEKJrFvPpBFmR8fs+WQazuYNp2/hBQL3WYjqZoOgq\nR0dD0kIZ1/VQTJPZ3EVIClNnhiJpyEIlk9STrU0aE8cpkiITDQcITSUlIyIlkzJkRUHKZGQ3oW6r\nPH1tgxcvr2KkOtmxgigL2vUlfN+hWW2RCZmyZaOZBaJEwrDzJJJGudpiPpmiqDqZkqKngkIuzzyd\nYaoKnu9QKhaYzudYqXQSFJZk5PhEamSaJrubb9KqnCOLDjmeu+TNMu9vvo1eqcNshK4blMwmcpZx\n/4M7tM5XKVeqhEHKYDAgdEY4bhdNUfGdmCgKsUydSqFEs1Yj9kLKtRphEmPqGrPplCxTMPM5oijE\nUBS8NCKv60S+S+Q46HaetUYO0owLpy5wsLvNymqL2eSE8hDEIfVmhUyJaVZyLJWaHG0+4NrllxhP\nMsrlMm5UYTIZsbSwQOgKmgtNyu0xk4nDtauX0fMjJCkmjF1apRy9/pD1U0vIcouP3r3NF37mazjh\nPRZXGmRpymTcp5CzOD7cpyZUjFyMmrbJ2RJHhya1hsFkmGHkAoIooFTL0+2P6bRqHBwfoGgqvucT\n+DFZemIAD6OUOIoQScTYdxFJhONM8dwJmYgoGTq+HxPnDaTUQpUsyASGqWMbGqoqgziBJsiSShD4\n6KqFn6SEkUSWnpxNJYlG6AuypPDTvwT+EpWZEk5xj6MtEzuvIFdM8vIS/UAhSGIifJJZxlyZo1Ui\nglSgCgPJU9H8DFdWcOWQia/g7QgaoUS54SMMi6KlsLxu09v2CGc6qmMw7/kIJUcaF0DkSaYCNSyS\njRWC3YTdXkCeOS99+XP0/+gerYrPdvlDZqnKeDZHI6Nhaxxu3UHiGKo5KuUGj44HGFgUqVO6WGP2\nsE8qpXQP91H0GFGaYRc1bm/todUlqETYeZ04VMm0Cgf7XeJQRRYSgVdCcmsETpnhJKY3mVFbMDnY\nd0kpI48U7jzuYhVMJo6POQlZSZbIpzlCQ0OvKKRGwLVvqlx6wiAyDTaFweg9Fe7o1I7byAWLfMcm\nSCTsxQr7kUNaP2btFcFCPk8Sn2Pz8SZq3cKQMjo10DOF0NTRtSJ9y8NYLKJFKcaBhrtbxP1ApVGs\nYBklrKyGyCskiUAkBh+/9Rm37w3QSxaWJFEqFpkmCUpaIJrIOKFGN/K5/vCAG/uPsYwcr11uU/Yy\n4t2EaQ1abYWo5yG5gjCJEWqGCBPOFRaJD7ZQ9BK11MZ2BWZ+wqTtMCu4mHKZg12Ph7sx509D7PoE\nwZj5YEJ3EFAqbuAbeYbdA5qTlN2dACX26DopdkMmO9aIhy00tY2qFXGiBbyshJAyiHym0T263j3G\nicCrWZjVENUNqNpD/P4b5NYFQb1DcD/PymcvUxeXWVpdJeoERNMJb3+nSizP8MQCu57FhegU460d\nqhsyWTnBUmWEXaWgxggrYP1agfF+gcE0o+/sMDa7bE67PKOushoqxGMXY80iOA4YDxKGH8dsRBuM\n5AFDMWRmyjQePkv2e+dJnrvH/dIIOgnBSCMIQixTRq4mNF+Yo2g+6pJKZMp4roFhLnFtdY3jjT4L\nuSHZwT7xDG789l/9tyIZvszqqZfQz3noG0MU/wNm4xDZzRDJnKWlKl947lcoVZv0j9/m9LnznH/t\nDYrlfTL5IZLdRjZrdEcWH7/lU257nL68yns/mFNqLJNvHJDKRwixi9B2Sax3uXXzGZ762vPE6vdY\nuzBn+9Jt7t8u8PzaF3ntC+skr93m+P51/vi3hgT/11d5/uVn2b8fouoWVrFFkh6jKhKSNCCTHAJ5\nit04w8Fgiytn9pDNLusXHKabF3h85yKVQpuPr0/4xV/6MjP3dVqFBUq19/nWr7zKm997nysbDR4e\nLnH39ZBHDz/DDyLC6CFBMKNolxmqM4bzEYHk4EUuly6d5b/55/8lD16/y1e/dIUvvvJ3WFousv7k\nPcIg5MHtCVbhNC89u8jRwQPC4Spv/aFHvelRLJi0iy9x9vMhh/N9lEzn8Uc53rsfo+kdTp9vI/IK\nH7x1i0pxzplrAww7YeeeRrD3c+Sr95k4d1HtIjc/mLO6dpHpPKHdOMMsuMvi2U/JkodErkKr1eHo\nzksk/VepV1XKrU/Ilz8gno+YRT6eajP1U8bDFab5h/jxnNGtAsVawGJnQBTEyEGDbJ5y9NCnXc+z\n/sIUswKFbMKKX+L13w+wc/Dqz9rIxpRAEjiejGmWaJ89prI4plA26B8pbI01kkmVyaiI052Tyh6d\nuk1N17j/fo9RXyFfUTld2+DjG9uYxTyVgkoh0+jGDrJtM5yC76koikXRtqjqZ5jNZ1SqOs5IwvO2\neO7VJqG7Reg+xerp15hOXTS5zfGdFp/82yMWnpohZTYLZyQMdig3PX71H77IB3WTe6nHo/uCB3df\nRnM0PP8eenPG0eAehlBo1Qr88M3f4isvvIwZjDk+yuh5Pu3qKaLJP+LHv/1t8vUClhlQaqhUFk3K\nzRmLNahXLJLDCvWCRb/rw6RI285w3R52boil6cSZhi9mkCrIQkdWIkTSxqRFs9zAb2tE0xaWdpHe\nzgEUfjI63U81aOiaiqrKqJpMloIsK8RkqH5GIkvoik4qnViKdU1H0zQkGYSUIksaiAQy5WRZISSy\nLEWWFQSQZSlZkiEJAIEiyUSZII0TkiQ72aBEAWmaEEUxWZahqhmqohMkMXpUorbQ4d5nh8ixgT/x\nsUyFNAnRdenEkpxlBBn4XoiZJMx3j2lUKuwcHVEqVxiNp9jlCoMwRtOL3DnoYeVs0jDDzFcZOQFe\nEEOQ4QYhsqIRSwaypKApKkEakkQBcRyQyRIiBsMwiUiIshObuiWrSFGEEsd87vITXD3bZLlegcSk\nVK1Tsw1mqYSkauh2BdkoADKJrGFbeSzDQpZVKlaBOBFopkWUxJhI+EnEdDwkCiNEHJDGAakuo2ga\nUpaiyTKT3hFRMEfXTTbvfkyzegpv+pAkLdEfjnkUb+GGKrOjAflSG6EayLpAViUufe15jh8d8eEn\nH5BlPr4zJQlSVpZPMxmNyOUMKrUSgeeDLNjZ3mGh2aI7HtJsNBiNx1imiaoqBH5ItVTEd/qIOKZc\nsrn+6B6nN9Z5/533WKpXmDsOh8cp1U6H/a1dRJxSqTSQMp2UjPFkwhnr5L9NW2Nr8wGaXsTMW4g0\no9NaJooTPH+OG8xoKuvYhQDdsHGdQ1TDIm8rjAYZnaUqpqUyPjTw4wgn3idfrdFqdgjjhOlgyt7O\nMXm7TOAJhsMBdsFEtUosLnUQmUS+lOB5KXY+I4w87JyMXdCxpyZpyomsLIkRAqIgPBk+5gkyKUHg\nk2XxSU8oKqDg+D5xKiNLEpKsIEmQFXREFiLLYJoGkgSGpWEoCoqsMp86ZOlJhkkIiyiOiBMTL/Rx\n/J+Mef0fWmqooUhlJG3O2bMdBlGTB+9Cqhh4QUhUDpEzEyVVMSWJyHdIEhMvUdAjlaQdESgQ7SQc\n39eoL2fYis3OzphRL2F5scWFJ1bo3g9xxwlaVscyNI73QVJ0QjdPeE+QjhNsw6ZcK7BQlVC2d7l3\n/S2a5QIjJce2s8+iUiF2BbJp4QVdtKrFeDRFkTUyN8WME8rtHG68Te1ihq9MaKtVEn1OmAWEmUsU\nOKQiRPYSJoMQRIqmGPR6GqpaRhpJzAYySWbjaiq9NCHWbXaOQ/xYQVEEaZJw5M9paEUMtUjJrZBl\nCjnL5vKLZbTKmGdes6mvTbivDHCEhvdoAf/jOmXnFCChN0y0dZ/aOuQ3VBpKkX4yIHP6ZGlKo1Tg\nVq/AzQdzzpw1sAyd0J8y9ufM6zCwFeodOEpi5n0DLW7jHWoMxxlqBYzFOpKS8um7n9BeldkZ7XN7\n+z66YXG+fRproYmpwfraIkUzxfcy7t1wWFmtUF56HjtvkVdUsqiEpBaQxhGffSejZUXUZAOjWGWn\n77H1eA87r2JUYeFpm6IRY+oysTNELyrUF8s89ewqb/3ZXe6957BwWad+qkxMj0pZkAUa569eZbMv\nccMZ0veGIGQUkVG0BOPhGC+IsZw+y80n2TuYMRwm1O2I0IqQsxBZGfPaV8osXJlQWRFIniCqGeyN\nplhFl5VijSTt8cTfLhLcl7CCIu1ykdRU2Z0c8cWnX+L1jyXGqy5BrOJXS1y/46KvSCyezlNqJ8SB\nR1XVUYurTMoS+ZxOY1Tmi4UGd+V7TOyAcbzLurTGeCeiXasSaQWMySrhocn+4x5mwWXOHppd4Gi8\nQfXbZynF68Qrj5CCI/rODnldJbUCFk4brBdgHs6IbQu5UcFMbGYTiWEAklahlTzBs8MO95RNoPdX\n/q0oH/w9rPlpHP1dxKkQefE6ycbH7N8RXGqe5nh7gTtvPKazssxTn3+Vl7/xNrL1IwJ+BOhcfekC\nl1+asXitzvf/RcL/+j90efmpazjzfX7tv1rAsFRi4SBJp/j8i0/zgRTz3Y//F3rjf8yKeA6j8gmv\n/vyE3//v7nDv7Rd48ckRIv8e+Sdg7UsjDv7dZe6/c4lbj57i4iu7KIUhqXSbKOyjGgNQTZI44szl\nGp9+b59ivo5s/gmkHWqX3uTjW7+OmX0BQ3g43hC1fotHh49ZXC+wuDDh+Z87w3vvfYcvRL/JYFCh\nf3yD+KjKYe8GwfyYnHmGerlBP9hFT1TCSPD1V56B8YBP3/w3/Oxrv8BoOODS8zNytR1GXQOVIi88\n2+brv3yGP/nefd54fRcjtFk7t8DiOZ9SYY6IE7zdIflKnYV1h1e/MsSSWyTpjDuPQ0rlDa5e/Q2G\nye8geJ9a8TLaygFra5AFzzPvjjm1eo5LV1YZz11++Pbr6EoNXVohcEGJF8jCOlrOZeXSLT76cA/J\nDxntnEfNOqg5A0VKOZo/xiw71NfmFBol9ocuectiOpSZDzwCZ8LoOKacL5CEGXklhxKpqLJg5ib0\nuinnNxbZvDOl0krIaQazY5OlYoH8kkum+JAquP0YxV3BKq/QbGrM/H1E0icnOhhxxvb1Hp2shNvb\nIlM1inaDwdGA/JpFrlFBYYQuQsRBFVtRUFWXilFHDW0U84C40GPtcsqxotD6xk2S/SYLk7/DeKvD\n2c5l7s0+Jpo9xzu/+yELd2a88HXIyTU0JFriLMdywtNfbTE5uIseXGGYVTju7+Ad1RmOclQKRUwp\nZtj1aOTm3Lv/HUS8ipI/Rq4dsP7FA6q1JpNehYL5Gnt3cnhDQXQY8OjuLveiPguLdTRDoSw/zbA1\nprs34NYf/Yilz01RzxmEWoop9clSG0UtoUoGiVQnljzCKCKV97BrRUwKzPo+t258hHLW/4n6/KfL\naOgKdt5CURSSJMPzfWRJRlY0VE4wtbqmo2gGmqajqgqyJCOyEzOxhIzIEtJEkKYpEjKyLCMBSCAQ\nqIqK6zgnMTQBmqoRug6B65LGKUkcEUfhCXUqVZGFjKRC6kx55YvPc//R7+LOMiQMYiHjBKClMWqU\nISSJ0E+Q1QxDVVBkhclgjGYWOJj5qLkCu6MJUSYhSQpxIhCpR5qlSDMHVUAQndyuCkXFC0LyuQLz\n0GUeeWSkZEmKrEKaCpAyHASaoaMkAiX0KMoKC+UyV9ZbXLqwhLAKFIqLmL6CouhsJy4XF8/jRyEr\n9Q6OHyJpJ6QR1bIIg4hcXqdQrDAej0njEBCINEYhIXACDEODNEPXJELfx7RsosDHdxx0TSf0QqaT\nCe3qMof9R4xnMomxTyhn+IkgNlI+/4Wv8fDuJq1mld7RPknocfDgMVauhj8J8N0ptWqOJI053t1B\n0Q0SQ+PouIdt6viuQ6fVQVI0DE0jimPKpSKyAEmAnTfxfR9dM0jSBOIYS1UYDkYUczniTEfWbQyz\nzHjkUap2MDWLnc1N1ldWufPoEY1OmSxVcKczbDuPonhUGw00xWVlZYXdvT3q1QWG2ado0tNsbx+w\nsNYiV+qyfTfi1Ok8QZhw4eJ5epMtFhaKjAbHfOXnnmE4PCRfOksopkwmMZ3lDrpW4MGDXU6tL9Ef\n64zHDkKJWFjo4Ce7qIqJJKc0m0WGwzGFUgnPcYh8B0UrkaUxkkiJo+zkGjJQUCWZnKGi6xBHAtIM\nBYXIc9EN9eRULlEIfYGrxmiajKJoKEGIpulomowsTvDPURyeyIoUBYFKnMj4AXjzFDfQieLiT9Pu\nf+nKBhNu9x9w5kyF9VZINB1TklfZH3nIbowSxBRli64/Js0iMjNF0tsoZpnYcyB6iCEJppMiaiqj\n6h0cKUKppFxeaKChEbkxnpKRqxZIPJ3x3CVKdDJFxxsVTnjrakogxegVcCvHvD//A87/Sofed9tM\n900eVnaZuRl5D8xARZVrWG6ZshKiTASdcpPpqMtMPyTK7aIulMm0KbKRMR0eoOZCHG9GpqYIIyT0\nZrj+HLNWJJqERFqedG6zc2dCLtfgMHCJMh8pb5HFGcOpSxBF+HEKqcRCewMTiUpcQ58ZfP4Xlih1\nepz9GYvtR3eQlxQyO2PfTdn+UCG8G1Haq2CmGvqyinwmQv7aDKszx55PWQ3XWbYD7t3eJwxVVK1E\nw27xw9dD5L5B5XKNo2MfTzHo7XiEtou0qKJYOp5vUlBttBUDz4WRFDHZ3GLiTdk8vs3t8ZC9cJ/O\n8zmePH+KSxfaoAjCUBBnx2xfHzEfg5KXONVawraWGXZVhpMjdK2MplrImsXH9z7h450pVXufs5dz\nXN/fRolSjrdBn1uce6FEOeehhHNMv0YgMnYf36a1cglNkTEaVd7/0WNqjwcYyyGn13O0F9rEWyHH\nmxMcfOabY2ZRHo0jrDRBxAnttTW2bh3w6KNb7Gyr6FKT+sYqeqLhu/d57stVZO0ApXFEmzGEFkau\nyrd1nxkSq70R64UixrdS/m3yPsO3b/DlS7/Mq1++TPy9CcvuMqtXf5U3HxyykzukmDvPE6JM69IU\nN/hz5CnkGzaOk5CQcNQ7oNy0OUsDf16gSIHN+S67Rw/49HiPRctg/z2DJM2zO52hqWAYOvV8mfL0\nLAN8duwZBWUN7wdQXT2P0Q1QL7hYlS61JY2LK0XiSURdb2AVNcxCA+GsIK4vMFjOY11qkwz2EFOd\nSjnPX8eg4XTvMth9jMRV9P4X0K/M0Up/wecaOZwtlY6Zo1ZbYeOZPpmyh2x9Bz/aw9LPkHCITIQk\nJlx9esLBIwc1fIZPr2esXvKpX3wHP3kLS7XxmJNvfIXy6e+RKWNuffy/s/iihSc1GUpdHkwfsDz8\nzwiP80gLHRTrNhtXQr76fIM3v7OL/PgMC50iknQHGYnUGBOLFn7mU1ALlNdSvKf2mU0bVKyzqEqX\n/egTXv76FY42ZdaWO3S3z9HRfgXCP2Z/90OeeQb68zc5fa7Bxz/8J/zcr36N2zfyPNjc46P3N0kk\nmcODe6yvLlA0ExqFp8lJOrd++Cn/qv//sL95yLq8TMnuc//tCWatQ6V5lmvnixwevMGPXt9CpsuF\nSymP7voc9xVmyQDD6BGNq4wPVyhWShzu9THUs8heBW/aIzZ2KDVXeLT/bYQ1RJo2mXc92qUix9sz\nBvtTVs8sceE5BV95l4PRIWQ2S0sL7G1uUysvUGrNSMKUXDXivZvvIwXf5MLiK7jJhxj6mNZyk3p9\nws6Bjz/1UI+eY2W5zsj+PYp5FyuTKEiCmZxSUHV0YZJpNvNozqQ3Rsls9nYdnny2yVOXF3j9h9uE\no0UkR3Cwc8TpazMyL6Pba1GwU7RYAc0j8jZP3qJun3a7zWyoUipVEWbGzIkJuyUka4qY7rC6dp6d\n/l1S1SRVq/S8GE/LWK+t4A8dCCr0g32e+JbD6jNbnLum8N7uiOJzTZbDZR79+J8y7X+TOPKR08dE\nM8HNHz/L1I/4j/5rh1Qa08tS2tIFclKKqQeUi3nkqw9ZyH8F46McS9UC+93bJIpHMPcwhEaozNnr\npSw1Noi5y/Pf2uVb/2kIrJ1QX9OHzEdl/EGN6dEiw/1VgtDF0FPStEoYxch3fD64AzduRXzVX2A9\nGdK4WEDR8thqisDAz0JSBmiKTr7gUXhyn1I55ujhmMPQZzhMkbb/CjIaqq4hZMgkkDWwJJtUSciy\nDBFAHJ8ME5KAJAqwrJOTKVlWkDKBLEmILCGKE6IkPUHfZskJ+lbKAIkw8JAlCbKMKIwIvJA4PsGr\nIp/kJYRITxweSUKWBmiKIEznmFWFv/kbX+X//b+/S/ewh50voBkF3MAnjCM0VSMIE3K5PFPPIWfn\nmU3m5HIF0kzgzifkiwXc+ZxC0cabTFEVkzhOQZNQU5AM42SlR0YqwAk8ojgmkTOkDOI0w1BkFE7w\noxIyqTPHFhmtgsHljTUurp2mUhOINGJJXsKdQ9ZUqVZKbHhtZMVAk2UUzSRzAlQtA5GQpT5SFhOH\nKoPjA/L5PJJq8fjhfXIGqKpOHMWoioWQJaI4QTN0gnlCPmej5kxG4wmlWhG/F3E0P2Z/7CKMFKGY\npALq7RLrq2d59wevs/PwLrcshe7okMXlNZJIxZYeUC21OXfuCkmqUKkVyNIJrudxdDykVqkwmY3J\n5QocDyd4VoqQJfKmjiJJ5HQDAViGgaoZJFKIpujYtsXy0gq379/DLhSYTDykLOVx9xHlQh7PDzBM\nizB2GU57XLlykZk3wZs6SKlCrzehkJMZT6c0O2tkwzHN1jKB75PLFVHVlIw8suwwczJeePFpxvP7\nePOMedBFVXS6vSlL62UM1WYxrHL3/hGKGrBx6knmszlWuczpC2toep7lokJ9ocBw4DGZH7DYXmfu\nb2IbFpKcImURaqaSxT7NSpGJl5IzFeJEQmTZ/7/RS5AkCT900Q0DXZeRNA1baOiKjKRkZKlCJiTi\nJCWOFKJIYBgZUZQxnzuYpkaaZWiqgmXmiEIX9QTrRpKYCAyS9MQYH2b6T/0Q+MtUlk75+39rBcMY\n0j8aM895NBtDPjl2EYMEta2QKCooOsfzPrKl4Qud7v4EfaAilwqAYNSVKRWXcCWZNIHEyMg1R6ya\nVYJIpyTyKKKJNFf59IbLQX9ClpWIBGRGzNAf88wLa9SLgr3928wmLotPPIcRJlz80UXmj6sMvRT/\nTJ9dX9BySnhHEc1anak/RhpBo2aiKTPCoxGb/g6KHaPqKak0wiwJYhEQiBAdkI0Y3ZAYJwGHxwmq\n36CQlvC0HHM5YRhm1BsWgZfQn4xIkQiSjEhXaCwu0ynVyI1TUmfES78R8ov/yZS9wy16/QErTzTZ\nHR9xeE+lVFinOMnRfZThZBFJ3OfUchG3PkReuElp7nBKXsU4HpO1dLySwSff3+eTXsDFl75MoI/5\n8UcDFusWWbLINDzACyLKlsIp28LEpHyhjFY0mQ5Vvv8HjzjeDRn5E8odk/UXcoySAzae0VldUmiV\nMsaj2/j+DFMyiEVIaKpQ9CnnWuiVA+ZdjySNyallkljFcefItknoGuT0FpKic//hIZ/d2eKVZ69w\n6flrmNU5Mn0UbUycjpA0hVYl5vRpjZt/+gHdowPWr3yT7XtDjLRDSS7QOxhQNwTb3R2CnGCttsij\n7V3uf9SnuDGnmVep5izcUUixY/FZd8Bu4tN8Tmf3YEDLKbN4pczpdQU/OkKzFKpJRqb4hMGQSlVB\njg3mSsiCrDF9vMNoTyG02kzju0RGg1G2z1q5TEdPKWwfI7x9PrybzMiybAAAIABJREFU8KWVGv5Y\nIn+mxlq7yMw/RJYk9o4fMY91rNU2tXIFddghfagwL40J5TbX559x2D9NaeJSLC8yrDpoC2Oqkkmk\nhSwV24hoxIP8Lk56xOq8wyvzRcKhSalmoXdCyqWE+qSNVMiRqFNa8QpWuYEaFglEhe2PM9oDE7kF\nRqSg3vnJHhD/oSUZS0jLVaTMI9Lukbvd5Knm32MeCFR5j85LHc4+s05e7HL71u/yO//jJi/8ygds\nnPoqctwGzUQSRYQU8rVfq1Cr38X9lypHj+ds/2iFhadeQhQ0En6HvvQGSm5Cs/UzvPOnJivP1Glf\nCYi9Imo04nirz92/sFn/+jnSRp9apUAq/h3NVx9ycO/XuflmjnLrPrVTErq2wjh20JQiRlYlVN6n\ndWqRzU2blxdLzMIHNMWXefvWt2mUIsoLVVr1XeLhN3h8+028wSny6Zd4OPpTDo832do1OfVCg//4\nH57h0+1PyS12eHynTLVh4vccypHNb/zMb/LJjffQjBHff2eXRrmO6QSgVpnuJpTrMacv36fVMfmd\nf/kx1eNfJs2PSbIJUyfHWvwNZjsJhjHCmd1gsVMgCQ3OXaoynI2p5TW6W4cUrB6RsNnbHSJTJ5gX\n6Q+PUN08xbLFtReKVDojes42k96EheZX2Hn0EN0ac+psTLm1xaAPw6ngsF/iVOMf4Ggpc/E9tPq7\nIMeE0UVir8TaUsLN7ZCXzlzh2SdfY/QXsN/9Lkdiiq2raDUVu51xfDCku61TX9HIzBAl1agVNJ54\nNqWxsMNTqc4Pfv+YUnqOTvMJDOWA+w83iQYKtaKBrAqaCxaBG5N4CRXbQo5Vtrb3aK4bNM5GDO7c\nJ3UWUYFSvkKuNibpN7n90ZyF2hqy43G5WSXsB+Q1DWSfwnKXJ77scurFCFXxeemshjuaE1Qn5J99\nn+oTj1Hf/mXWJl/nw/eu4yKRbxcYDmZ4/YxaWaI7kQklQU4p0m6VOffqbZqV36dqlNh++xn0cInE\nPIYFi8PugDiEYNZk0/lDvvULgq//3TyOtIWOhpKGyDi0WqcIagMWz24hixJkdbLYwIscXE/m6OCA\nxVNP0r17zOPPPqJ63kNr+mgFj9CWsBWZTPEg85FFkSTzMI2I2kYBuTKFtkbwVpGdveFP1Oc/XRgc\nmbxdQJIFaQLzyEEAmqGTZBmCBFWVsIwcWSZIsxRdt1F1BYkUgYBMkGUSAoU0TZBkhSxJkBUJRRHY\ndh7XmSOQkIRAkRTSNCKMIuI4Jkli0jQ7wdyKjEzEKOMQVdNJ4yF6TuXv/ue/yY/e+owP3/mY4VGf\nar1MwVCRZA1VU8lEDJLOfOpi2WV83ychw7QtfNfBVGWc4Zi8ZaNKKqGakMQJkyRFQ2LsTNFNmyRJ\nkIWKpqpkQYhpGCiZjCqd4EUlWcEUGaVSgeVKkfOrTVrVPOWihCkqaFaRoJpiyBpGbCJPJSJpiuSk\nVCtlnPEIJUsRQUhOV5j2utilItNRD003QcQk4ZxaOc90eEiuXkdXNBzPpVDIEYqExItRFZVeb4qu\nG8znc2aey9wP2BsdMwwmFIptdrc3efHaJXZv3uLxJ59w+/FDGvUaRDJr7SWaldO0OldQ1ZPhLgkH\neM4B8ZFOkhnEmUS9sYQfTKjVWgSBhyKfBPuLpQIiFZQreSQhiPz434sbY1/Csk2cIxc3cNAMC9vI\nE6UBC5UGydQimLnUcnkwTLSlIooiE+Kxe7BDLGYUSkUKRQspllBUmE2nLK22mM+6yEZCElgcHh3z\n/OeeQslNUdUSQbpLpRmzuFJHJHW8ZJ98UeJoJ+Hi06cIh5/w5MUrWAWH7l7K0lqLH37/HucunkGm\nhJrLsO0NpIVPCMZP4sXvkLc2kAsTJoM5pUqOw/0BspxHlRVkJcSyTUyhomkxApnRaES1WkeWEtIs\nRpNlsjglS2WqxSqT0CH2E7JY/PvthaTKZGlCEqfohn7i7JAV0lQQxS6SMEmRkYVFEEjEoUwYQpLY\nuK72078E/hIVqCNEvsHgqEMWDViup8Sv9rjs57n55yZ6NYdmqDy3cQapmLI1GLI93ON8vYB/kKLn\nNGIRUShVkT2JwUGENZugnfJYLwPOBF9KMU4ZDO7voQYSlVYMOXh8v0smKYRRipyohP2QB4MD6mfm\nSKrPJPmUyuWMFz93ga/yPB99cswPbrjE3QOqF+qstqqYhqDQqBMdBMSTEaPxNqX1jGkaIEsm87lD\nY6WEH/cQUoKiwsQLmfhzRF4nRScbFpj3FLqZQ5rq6KZB0ZYRsczs0KG53GI6cjALZeyqwflmDWsa\nU6tC52dlzr06ZjCeU84pOKWUaBKjSSt4b6cIp4LX1aAEk3RIwyrS3/dBOyZ+b0R+3WUzibGzKYtR\nk1qpTqz4HH1ioiou+aV1HsYun3ZHLNQtJiFEXoxdFNQXfCSRQKShmBP8gsfCiy7pA4dyBLN4D6vg\nkKkShaLO8V2Jw96AnTuHnHtRYXFJp1UyWT27whiZRkVwQB8/P8AZqJRTH8/PSJIMx/XQCjKVRZON\npRqaX+DU6Q6kGm+9/Sk/+40NvCRhqrvoCAxXJpspnFoTHKxOWb5Yojd28HWZRzdlXqyWUewc/b2A\nG9d3WDh7Hl1TOFW6yMH229za8rn2BYUsV8IoSvgoaDWFqJcy3RmT7Er4dRM5i+lNxwR4JGbKI0nl\nmhJTlvJcEGVuVick8wJenGH6gg3VZhgL3N6I7/+LN+gde4TXAv70D95j7KdYpy1Gwz63nIjWMxKX\nLiyQ7ewz0ySkvIR9Zsxzp5qkR8c8/NRhc3MHpbxEE5sgbqO5fdR1i7LZYC4FdKw2Q8Z0ahucaVYZ\n9xTig4eQyexLN3D0hImi8cSZFrF2TOEpm7WxTJAIwoGKVTI4LPfw4xpaXccPHsFinkNvC2U8Zye8\nT7//10OdEsMBmZ9S6XQIlRne9BYPtx6ytHKVei7l4tkieud7NNc+pLFU4bf+z5u8/duvkbzisvZC\ni8kdldt3j7n6hTLl1jFW+SHb9wvUZn+bP/knP+Yf/B8leoUHlKUzuMxp5apkxgP2jxdw43WENWGu\n75PWYXN4lzNGkfl8H8l20PwryBWdRjOgvv4u/+a/3yAcx/zaf3GWIGdy1N1n4+xL6FqIk3xEFMW8\n98ZtOtavUz/9iDANOXPaZvvxJpefvMb17f+Wp9d+g96gydJyg8Pxu8xHMsI9zc69Lly9gBfcpdLZ\n4W/9ozP88Dt9PvrjBW7c71MsJNzp3UTKNZlNNXKGSSINuDPdo6AJltvLPL4zQBhjSss6mtHhxt1d\nzIKMXqrwtW8+z+07Nxn355j5Hqa9i1yVqeUyzGKDXBRBEKGMeuQsmziRmJcVNrdCRCSxsK5yZuGA\nSjsgdg1u3tDJ16uQl9je7VPKnafX2ybT7+BHy7jjMvlci3Pn/wYfvrtFLH/IqHdMJ/klMjWgrxyS\nxCaL9i9QfqrLwc4mg/Eu3cNNxpmGWVjGQ6CqEZnew+sbDJ2M8XKZ8rqPO5IwJQj9CTNXobgYc/lL\nGu7xjJ2HOzx8VyMdN1hamrOyUafgdZm6e0h+CW9kIjKLo0GIGmtMg12WLhiI1GPEDrqioTcl1OII\nNa5QlUvU0HDSHEkMlcYpfDGltHQRaTGgtfYRsRrQLpmYBRUnjRnGD6if9VjISTSaQ47eb2PdbDI4\nOqalPslwb0oqD/n0Dwy6995l4fRFvvZLgqVLD7HXPkORLC7/Yof2kyZhsMT+vodgzBWhc+fjDu7h\nEjnzCps7/5xQCphHEi19SCwc9CwmFQlB5mBpMYakEmOhGUVEJpPLVTn/SsrkR6to3iUeftZlEsS8\nkCasv2IynE1JiyP8YEbBEqgyIFQSSeCIhKT4Dp2rAYPpaT66/pNJgH+6QUMW+KGDbhhIkoJtWkSK\nS5hFyIaKrmgoqoJIAnRLQVZVZDlFFgmKqp+EuOOMSCTo+snZSOL6qLqBpMhkssQ07ZFlkEQZWSyI\n44Q0TpFlQKRIkjgxhUcxYZwhyRApIMVTJgcyreYyut7ll762zje/dIaPbhzwwYePuPtgD93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YQ/gEfXlmD2BFt3D3BlFwUXtQxpVk2ioo2WQxbCsKtz672S+fmE+XqF7tb7uE7Cwexd1o+pdBoX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AYvEvavTzcwwe6WShzmg3xXctrp4/R3plwjMvzcnEEZ5dY1QWSG+MECZJaOI2PeZWxOxRiigt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4ZQZmgso0hJopyQqD4Gh6yf87j8pMb3/lhn72qdW/snSNFg8cO7eBtjHHOFOPKo2AO60VU+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\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6RwbNlsPSU0Oijs/Dtzx0J+bgZpNgPwHH4/hBnd5hSjB9BuP0aca3L1J8MmHUnVAaRzSt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\n0g8wTIc//cO3ePzjk6RWk1ZtmZt3n8d2f46C1Sbf9agVi3S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aVX747DL7ssGlndfYqedM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HW5ilBr2VJu17IVPZ81z+poutVbh49ev0R9sMBiPcQYduc5eJ+gRr66v8xE/8BL/32U9y6NRR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xZ55mNVzny4y/EXSvSyN7HNkG67i8iaLE0tUyCfhCgLlxtf6PC9P55l7Qb0Du5gKTanLmZo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\nbPsQSj5KGDpJRKlaZxpFlLw2m9cfkhcak6S0W00G3R4V/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+KtK5qH1/dIOk/Q+doAJ+zy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Dna0bGO46SfQuq0tP0u12aDRqjEcTTLdAr3+bxblzbO1cpzl7AkWJcT0XpETXpo33vu9T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Gi5jJVUGc1uRVUz1MI+S61ZssWIWOmixAUMQ8OXIb1+hUixUA0V4QYYQqBFYKChBT5uGKDELl7s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\nEJEGEWnAf/Bxvaq+CyAilwE3A98BmoDvAv8sIl8O0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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb75468d080>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Final image:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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jQmcCLXrCJrN5KNXmb4r46dl0PHr39vD++Gpylsnh4P7r18eV5joE6UBR1tH6\nyN78cEflZPFkiCewv7PeN4IZMqLYQeJjXfcijbD3wVMmRVPYLMxn5KKhhSOmD7bo6B9/t4ohKg/8\nWFoC7K/fvb8YT5zvoiFDQNvqzX61n5QnMOftEA52whaBOCYlo7R1NZnRfX10hm/2q4iNRBQiW5SV\n4RsWSXNC09XaRynFCGWMxnqveidpteoRaU+ABi5F3K5o62kQ0sVgXInycLWrn8LTV7s7N/DECFeZ\n2SLxwaULTtFypaXHfKySySiIaHNdOBpGrfCGrN9u525gE6dlDMe4q4Fxqp3dFvv9PdNUxzxy3FTa\n+KUVIWeS0kBbLFki27bAnp3LcyJB3/bj80kc5qMUBvGAz2/zmeLk27VuOge7gltNeZYOn15M8vDG\ntGbxQD8Qk6tyvyPr3/6haYKKlfrqs0enzwJJ+wbf3L3FvaA5oTKMjCGvNlsi0PMiezKYJiqRvMdD\ntpgyjKEQe1W9K1Yl9hjoksbndCotk7uhN5Xx1vo9iwUouyt23hBJUhGA9t4qO8jI8391woMeKZ8B\nmw7kKBu/ut5o03mQ80cPBAyiJY9IbNr28OtqwIdAs8V4SRYgCSv0vm2rqncfn07nEwWRZ2xHbCeD\niMzEnck/ib+43G7f3P3UbZtJnsU0MTbUtX379j6XkA+TcIS96ywhbWN720aUMSSffPJwMPNddatb\nnRGsdU96B+C//OjDj3810rCi3D+N4eknc47p3Zv+r//+J0rpyeDk/PxERsE5/e6n15vNnkq2nKfT\nhORoHGGDGe4aPx4NnEyPQP7zX/8RDfns0wcfP57et2r19tC1nUFEAiJLbIOA+Vd/+jkr4hc/fdNV\n+3whxomazOP1y7sxy1DK1hxKYrqOe8mXp7PFl/D+v/u7/3D7n/4Pn/5rNsZokDx7+jz5MHjZ19Ze\nviiPd4XDwae/ej5dpq/bVELVeRul1VDGSkavf2J6HS2ePLgkrY30aTze+s1CnaJVJ9V8+Vw/fvqR\nlNhsjWnsBx98oEOVz4fHfc+6pt32ocLgbUBxcTp8jKfB6NSmQqjR4LyjLZie0Kipd+eD08gmiZwu\nxEmSDG66931ni3KVokqJT3iMh+phOpATM5sjjYPtHJSi1D2yBHo87pr7XRvvhmw2eTp9NlDtq9V3\nGPmNu83v4yC5lKqAPUiSBTHHSSRxc2ifneSTmXryy4mY+uixWL2hL76R5RVJVnN739MDe/N6NUqb\nP/2Tj8kUeEy63jU/gOn6++2eM6KzLpqpgDqiERSSBbo8U0zAbgsjPh4S6Yx9rj6YJgnWGE+ApZqd\ngic3caw//JnzO/wh8OPvYn6xFLLu1O39g4QMHOJm7U2EacMTkgf++ZcXz38RBXsDsY5heX1/Ve7o\noSUxp7Xm8SCN85RJPJ0n6XOa5cn3392iaXw/pB14Apb5MICTxXAm4tSwzkFfHEKilYo8wcIWKs+C\nCRAIB94fW6KM9y1J+4RHBI6DSc7Q2w4HSOl6kyjy4Kl4+IxJGZh0XVte/XRkfne+HDEqx7NRLIjt\nm+NRvF2RYt0C1eAbhIpEa1CFiEfQm1Bh4FE6Y2fs9ObmjmqsnRNAuIo+/ujZPCEqIJyynojChbLb\nR47GyJ8/nn76QQYjE2hwFostZj+E9T3lntPugO2Opzds5HikEM/7Q00VDc1dnCy/+tl8Pp9wibq2\nomv213tJ6Txn2N/fXd+UDooORQJMosa+qalp/SzPHp2O46CfDEXyUKqYp3Lx9//xm09+/sHH/3w5\nFPNU0MCiL748f/9PxgR3Z+62l7oiliRBhx6ciXlmdWlFo7OGzKR7Xne/0W/67SPMPvv54+UX9oC3\nR9aGjlz8anTeZYPRNF/wbl3R6z7luFwmo1BE3mVY/tnHgc3PXpVtIkgRu2SsHpIHX6VfDYt4/DOH\no5f9U+lIv3g0IB1ljO8KNTzN02JzvLJqkjkDPXGudTEXwse+JzMpWCSUzKiaHMp9pX1nOVX4RA3P\nJiO3iFv0tBqv73tdoEgDCLLmh4HgZw+VfNIOz2u0obaG+/g5sL4I6zXKeZJ8Pp25C2NVfa/Ixrd+\ndnVc99b2PAwmkdsF3eweDS6enBGy1qQjUxYWSxDPipN/XTGsBgLk8gjn/Kd/pw9baooQD9gHDx9+\n8ouzi19mJmm11/XBD0+ym58O5FLu+xA4ywYqZzB7NvJIj422Hn2oT0fy6aeJuTOg3IgVKisXD8bZ\nZ5ae1/n50FGpQlQ1XeNZ/AElrxTPYzl05klEn56F2x7ub3k2IJSS01nalykgWNpT1ts6SArkMCgu\nyd2dQN3FcUKIGA7E518uRksyyWg6GBDe7N9jUTbFm6BdyPN8OR4wA9JK6dVskmZP470/bMudpFSg\nmsT5WZQTixkX725uOqZNjOlMW/cuUm3vIeYxJuTyuvfx5uzJyfTE9fZ7RtAp0wDxEUtzeHhx5gAI\n9UKA9h2VLn4wzp1A/eb73/4wPDejx2061TJOMUgbxUCUstMERahVbUBlmkji++bjx/lnT0aoD4yA\njoWn8Q+v3O27rWv6B5mKSAjk4Mcr512mogcdBILNurm6+57v+kXWxcSgS7w1ARPjw8WFePoknw5s\nRNaMAzJ3cSGPX447o2Xa1XAIxBS11Q21ZWh2mRjmncaR5J88mpwria4l0KepGY/Sp0/nr37ITk5H\noywibXn/Yj+m8yeLhZuWITB/467LfRwGbBgRC8IhMXRvN2poUFEu4E//mxPL/uw3//33v9H9//F/\n94tPfjH/9eYyjhjneDKKcz6KVbq+qxNWf6ngfKZikRIbMqthU7e7o+sOxb47iX/GM5nSkyRkKSqV\nN47+wNRlFvuyPPb9hgZKIJbg2/0xQB9HtNh6a5kTkquRNCTlgo86dWKioU8jiNicbjJWt3rFA64G\nD8aDs2Y4iIoWJ92j17Kd3w937a6r6w78YEgguCSDBt/wlBDkpoDxw5PmnT3c61Ty0Wk2WWrdYtpI\ndi3y9rzim24UatRn0cSs3Gggv3y6mHwsbMKN8yX6fXs5ZToGjEmVa6jtbhyrdNKPT8cDMU7l7Gdf\nPT/7BWyOfyS8Zww87dlono2oh7h63XChVEiX/EnGYfgoL539w1/dBK8fPp8sztiB3Z1cDFNVZ8M4\nfdodhweeflfDalwdFJcIEZzHwycSXg14sVrbWYCiO5Z0HwQ/t7/8F6rfJQku/+Fv+xff3kZTNU3B\ndox68e5VtL311KdF4bXhjPDnT06ePM4oqQFDXZWLON+X1t9jd7QODXqippxLmiVSsDD6tB8/DrIN\nN7++D+BiiNhSPv1ohKGnVufP8eZgbusdYig2mDyKO2cYV0bTxvREEiS1Ay8CAlKntxiYB9HVaPyA\nJQoiAgnQqOSkf5Atz88GZdkeurZs+/qm+2BELLYlbvxExmaSmHS4H23vkptt0QZjY9Wsqi+eDtmo\nw6hgOQt1CTB97GV1C4dgLm/vrYdZ7jTtvDDggeUqnZN6H4z1dd2mRWtIpzqw7l7r6OhN8lE0eVxj\nKEmcBEI8Cx4ImVq92ciTaHZKOVPnNvUldRXZ3oVWB+zDZMT6qg/o8ikEYg/hmI5jmfdP/oI8+gip\nK1zdILRtoL4NVPYDObRammjW97RG6z0lmkuaURFCuN/cV8d/OCRnZ19+9fR/+L/9Zx2rdDuSNrO8\nTy6IIGQQwJn9Wu7t2Dz+YPxx/ejyZ5dXL/a3r2/JOHUpseO27c0QJjzHYLANLgMxeyounvMDqUt6\nWbs1j9hwPu4006HKldjv6u5Yh4516OpC2RTHeUIFY6kkM9MO76Ilz8/mpIkyicf3d3JZ8UGXPw+G\nXpP5jDQIW0VokwyEjfNIR65s7KF89U3z8LzsRDVKOLN5EASIDsFlQ0akc36jwdmI08f52LPuJlEH\nSmXcMAiJWjyapHG7d+vpOMtGcXFsE2I2q5vBqUgCw2bT2mwKWef8JMOVrKgaV13xw6sf0k+GckTU\nKYHKVEdNUSejtNwAArXBIW0CIW6K7bBuoX+3vVlOB8Nnjie3o/Pr9MEthQP9cLaTSIVYeOKdmXRR\nTZUnCA5EJKf/LOeEgWTizWX9ysZnf2af/ByWePZt5BZPkuXLePPt/u1P3ZXqYpr6gr54Y1yDA5YE\nYwOV07k8nQ5N57zzJnS9BcpmDJPtsWmVERmkaZwQSVpmyzZ9wIZL71EPLuhHZPri19dchWTCaLam\nAqE1gyF4DjsdtPX1AcKMs3jofXy76r2LOIGugp6HRBHdGAvEBsJrIQg53hcPP5xDhJZsh1MrR3bE\nPSBbb3l9pG0H/V13m4CVlCQtcJMP0jEGOJJip/Zb2mha9x6AGsQ2HIjY8wS8p8z6LB6nA9Lv+WHX\ncED3gFTeEuViDOPRyDn4oXodMQrIGQwVy6Rg1gLj5ORJOl4sfN2EpvBAPCEgoxJ1Y44kJ8PHIHMg\nJoiOgWI8idD1h7cVtSwWke6L16/c6XPuaBm4Z3xq201CnIIDOI8OaXCB2HJ1VHGSSRUyng2UwdzN\nyeVP5ev21TNP2IihDqImxOPF+SSjzxSMIkbsT6fdJQzOT81w1ZSHceipj5VHkWjdrq/s+wP2bB6N\nUTnPV10p5iL60j7cjt98t8c6ylO5iOJk1L7e/aYf/iYZ7QmtUyGnufQdt4wgVMEXwYVyz0Qqwn0w\nK719e/PBs2cyZ4qpSvb5UBKxg76MpVou25MBGoo8qtp+d3c8asusTubzYa5EVIvy/5+l7f64rwe7\nLXtg14zkYCXN2g1sKhcCD7rLiGRR5wzauXGF0FFgSpH5SBtamzAlPJpFJhQmI3GeBEloCLz1/ohO\nR6Gf94bTxlpwz04fNDd4vfEeQ1n291fs9POoOBzqzc43ovfO+3C3qRvTtvaAQDOcRuyBKejrqw02\nyBbGbjYd26cntXH7scChzDQwHgTWTSVaaqG1Kc3yg6n+cHd9ebvjNIGGlHtPFk/tR79MdWu2sfFj\n54/k8aPx6x9W63cdS1VOCNYh8jOZCub5chHRQMYLQfmgaArrZH1wh7et77EvCKE04olQlAItdJV3\nKk7I48+IHPnWbPsdMOIoK+RIshgqWk0GChLvugBTM/XxdmurPXz72/7kZDAci6bhtmF960VLvQh1\nH9IIGM2DJmgVV1wbWF0fZ58IT8po7pUE01wTMZOpnI4H7JbwbZAeoLZRJsgQM4Fht7Jhn57EfzEa\nFy17f18eb5q6KZ2gjnbWdIpLTgWjIolpl0h0YX90YYuhHzbVXoUwORumjMV0lcUqZYSBqLcbNChi\nihEXQ9qxjpBiGCPY1oP3RG3WHQQ4meRoQuh4JGIqIx15Cx4S+8GHGbZRVfvNWh/aO3PtZg/5dBzH\nYl918PiER7SlPIwuRFebbrO/OtRPzn8Wx9B0frM+tvVK0IwDP+Cu6GfL4ejY8FDwcAT7rpVn5L/F\nf/ODb/Sr4c2vC/dvQLvK6x4cOtIX4TAiuXPYG1+PTd/VnlDj+PA8YQnVXOeLKF8Ta5B07+W485wh\nv1NDny714kQqQkPfSJEkQmzJfebsOVGbd+LyCm8v95wljBBQoe6bYDQwH/DApUvPlaD8nGgf8OV1\nE5iIJhRsT7DFxMtsAqlY2Gn/Lpje8CF4be+/7h7NggXPOgVsFDqFNFQOdKfzgS4OVYj6PsX1mFWf\nzfAVdS3JxbniHJIWJ9tkqTfhLbLWj1QwbnTGms7u7rsRyxIR+5gqT3ZHUx89FqB0zFC++/swiQYd\nz4ElJGBXwvpFF/r4PE3vGg+EyThuGSUBXRR+8a8eU7rzriFRP1yyIEMk+WG19YthcKylXYIkpXEX\nTF8fpdEpDRk6bkhzZPXJV+IvvsyshR5tQ+oAZ4eqB0HjB/E3r14u0+GH2ZN0wsdzyhklmtWN+fHr\nq3akvAfbMvQxOkJtEkrWFZYL4CkjkaQxFW2UOvbwTIRwNJ3Ox7FHK6R5/sVws92XWEVIvEkESCX4\nZM54Puq7vt2R1Uu9+akdT+LsjHEWI4beQYM2m1IytIH6/oj7FfQU0jwePErSEwoqIXLrSQ9SYyJJ\nNhlm1B1Z0+PhKgCSKI9QYhuCcoWU4ukCTIgLq6az8aXoXFts37bRwtGRlyKg63vbp5lyA+Z65ENl\nDl1/YATHiFnR2U2rtYeYwf6e8JggSxlBGUmZKKChKnVsgwDrXCUTXnQIlkxolJAJM4RLCZ5Y2yMh\nOtRA6/l4qCbkao8wkeWRkIU9/VAucxf1R04EuxiX29uu6Vm6fPCJuiMhL2E4A+zq3c7s3pU5m4zn\n8TTLt/fzK3JP37aMhQt5orIIMAGrfvVvfnH5N9/9EBXwj1vymXVfHKRyTd3xOCE0VnVUxRtDsPAE\nJ0w2iu7No+Vo25ib+/sXP/1O7Z+fx+e0h1Fcj0fx7EK5VBx16zoepX6YxLGg3vc5b+MURc6en8Ry\nZK9+b7AbCi6bUmPk0wUus2nE7gYqkHBD0EeMWpJ8+ov0663vdANFEQn/5HM1jXxRss2+fH/fB+yk\nwIhQaQbpPVHjiNhxIPLyzpZHHgKKTCbnKlqGntp2W1gm0vPFryYfDf8DQRPl1tOF7tub0bDVZJvl\nw8U8Xl9VLUMAv7kP+XnrRWdZy3PCyHhyksOtOzRGg+lu4e4PXEwS5P7QtrqDEPDi9ByMsl4Wx5Jy\ngW0vx/GjfJ4I0jSFgcaScAxmuhxm0al9Z+Mo6eauFpAEtSOdtERZOEv8rYLCI+enOP9L/9XHklfQ\nVm7KBk3ktteHzfuhv80yqqhjQ66eXORPFyR61jra956/f93Du/KwdcfLGcTAFC/Xxhq2v62cCCKP\nQIoAiNpaBBARDBAyAkKDCsRpgg1BC8ZJSmcTSXQbdMkYJ2ICjAsqmVXj0QijzFE8Voh1ITPQEpcg\nLaUNtk5gmdIdBksCCASKiCEbxx5IABIi2kBBBQMK6ZhEcUwgZGQ4Dlnveodb48uYS7WgtGOEUJ6D\n1cn+TVe+h8VkysGj08fWh7oDygPx2rvQM91hICTLB/N0mCbD0tqA2f7eVK3TUhAKCsJ4CSMJFFXk\nGGvMrj/wHNVE9peInjKt+nsS+ViPJBuDyCMBbX24H8xIvjC+OELtveMnz4cPPh8qX3ASOPUOWEyJ\nzdXkInU9AUqy2s4Y9uRuc+kZnaVjmEYqdMaR3cPF8tXtZd2F5fKUewWSL0bLhx8+maazx3/V38Tf\nP+3byFsObsyJizDIngOnLCARGKucyHVUR2dxwjyg3789KPVQMTYepBnVCWHxyAQog90ThFE6ErT3\nzEPWG6hc0FOfEtmgO2Kg6Sk9edpTZBE7ufy2MUXXfH9oA44f+wfPGSKNHSRBHWv0grkUahsW4+hi\n3M9jZ+tbJJJNx3/yv5wfv8mOf+jarSUH/u7vw8U+IwMSTyNoXW+gaLssYS/fHtjtHsWhqwzFuQu9\nqd9U3o3pkAcaT7i6qPLTPsKG4EvGTvOxdYDQkv2qfXQi0mVUWHK/re7vg/eRQE6OgsRcqnT1XXQy\nG1nduumdpYamDBhAD1+dPkfOGuxvw4YDC4B1WwVAQmnl0TZ+GIZlFdWHJG4iftWzzx4EeuwHbwWx\ntYaIwATCSTTi4y/YBx8JWu/tfgQ0YpamJCjqu9o0bzempQuxmMnB409MNjoi3Fliu0ThLDz4U/b6\nH3fv3r7Jx0O5lJ1BloAGhxi49Vkmk3SIDXBJRjlp8MBYJ4kNxKsFZSTZbC31pNuSfg/jOHBJSSpq\ndLrthBhkUj15+Gj57LRH9/Z2//6nllK+32++/QN8zhMTECls62A0iogrBdrWxa0l4BEpizhlVKRe\nkYZKQc7TQVDf/np986IEDYOfE4gJCNL1DSW9U4ypyDZ9c7RNFcb5IOWL9eHKJ0gkmTyM6UKdnqnd\nnbu7Ll1jJ6Ph2WSSiBgQOMCD+eJQHlgOTQdN43Rpfp4N8nCiC63rdes1VZgtVSUJScViOWsOEsnY\nHaEpMRWCD0lZHlynZx/GhHYY8yihbu+coQEpcEoY85oGGe3bXhEagq+7xgVJlFBDQrWWOU5SNZkP\nw54zoo5FO87UZw8eCYx4Bm9frfFex1TfZVvL1OLZ+Kf7stH44WyOODng0UQ0RxHZgZM+DVmIYtQi\n9ZGPqVCGmZgadDuFvWubTrM2nSxJpuOpakKHtjO92Wx3alTDRzjvR5q6xgbHXWa99beBYDqhwRTU\nnvGImJ5UW+CXhNF09c7kJ5knnfecsrgoIOSKxGKQ0DQYbOwg8HQyczl0hE06DHeJ7p33mYH26g76\n21YmpLLMYAQkyrOEOSdg6SEdJpSpSd+d7iqcSDJKCULTQWnw8r65+/JPBqdURrprTsibras2ZPNP\n5m9+vTuvJoPFAHACXtZvcHNfFZatk/pi8nRdW9ID3Ho0oZ/b6RdxQnsaQI7lYE4zR9e/qW5f3oJz\nNGAyIkINuzZU73XbupExp/LCFZTJpH3f9CcrEnV9RI0F25JDT/2O8MFDgr4ynioaERyu9sf0BD4Y\np/mvhv90Bbt3YSYmJ3FMVI/+hvEjo62lBIZx9CBLvpG7pvOtTA3nPNoHfaT1MB0qMYhVSgT0TSem\nwlBR+qJclTJUucPTOEkylWdq0yfGw+FSLb4YBn6wCRphXaDjc/p4OM6oCryNCD7nOMsWwODv/27z\n/uXKFsnw84RPwGgkThCPpuo8p1FK+gMBrxpvhwmIp0hJTUDQOM0fDp+u5e7ekyMXBUGibdLXcUcp\nceaoRE5k4BSMxq5KZDihXQcjjXnngyadkXkylsGR0L8y6ZgTESh3wSLj4excPXj6IDnjmofXr/lt\ncXn9o/94FhHL7zfgkpCcx71CbzGRC5GP6wA0jnvdRYzoAo/HA7BqfJajwgYdy6iMBMeALVz+UzGd\ncTXj1BNGiTcAgvadppxi5wBYPqFJrIZn0fbroqoai7WEnCRCB005ffN+M4gF6fTsgm1+8qubb08+\nGX78r87+7v+OR++AiBTGgRWBk4jQxGEdXITZjnkZ+BlZEuUNb90GQuf7+zCJHqpwinGLktRY3Xct\nsiMPBlAARoIEZKUKnWZYcEc0D7wtfKm9mH/Gbv+4Dvp0NjzZlPZGY1fQB9lHcSCivvHhnQYfcbHr\njeciTwcRbbnXqicCSMmKBpmB1AyDSZjjXAeoOrutDaEBWG+8YJFK4qy8AxmCIMSj6DhaWWgLmlOc\nUp/S8YkXD7uzf8byUz6XiHBADJFKsqf2xhuIhHHZj98gVTYAMRt3+Y2t9kGQ4b7o9VWfTPIRUK/J\n4cWWQZgonj+mZ3O0/RGQmi1wXicCPFImKDoklKOV2opiq98Va5idKRc+/8VjUMUuFBXje2LsiOw1\nef0ju/ndihOOSEIVUbI3pG0TSXgO7+DloXe9nNz25uyj8/RJaGytshAaV/WOjzkprO+6xTK+vQ57\nMEVT5emo7kw6TAdRQhya2ishP/jZWTQiRVM6YFIOKFDfdFffdliVh53uOsSKvS3cfKjiDyYYOySe\njwnSJnUdub8RgXHKO+pmJ3yz90+fTuGqD+jbGz+wcTZO4uVgU6x1b4NnHGPdeWK4b3g/pAKdRw8Q\nABtXCY/Y7c3tzf4xjZd/wb1ixpNAvU+c9mVtURswwV1v23/8u1d8GR4+jYLsoOuZN0xYH5HkOdCi\ndbQ6trVjkhAiI5KdDTADHoN2/uRRotcL1+J33+51p0lEZZxTYsE4gYwBh0Cjsei74Hw4nSvBqfdB\n5OM47UpX0lSEjnQd5kLYhr7+Q41fTCcDFslAsKSceSSm11GW6x4AIQSsm72SUx4ByxQLg27fKDoP\nQcs0BrXnM85s0kN3LINt+kefuskoGfUUU/LrX79PP3j9ZAoArKaEkBZ80KLYWy1Zd0fL9K3Kj6lZ\nE47jyWRISFbst7fHhjly8TMcolAZ3ZUlcRQIS4zgnrWhpoZ44RRXfek5Z5LL5XPTl6F62Z4MJk3o\n7XoFyOsN2b4AlnTT59TJVgdPVYI2RIFrA6s20JQ1NqzA8i4lnPQj2kUeuAyBR6M0oM0nTFAGQfU9\nBMvLTRsJ5qkHERHuo0E0n88Vn2y/b4/3d452VuxC3kxSQOZkiATlYNyMwNfzWo9EFJjehb6DrvKx\nH08fjvfd7deHq+EFNXLP0/THjbngyZOff/XF/1rR81dIrzx2+TR1VWQlmeQ+xfj+jacWOu1Ij+oJ\nv3g4rtrm8o/t2+19v/LL5+flyxuctvU5roxaBVRHS4WnUcLxoM0HOPSBCgx9SRN/E4J2frU9ruuw\nad1H8TOGuNpqNua6DhTi6uB9S9qVpX7MHHGOlEW3Vho4nQ2HFD2JdYDOME9HEy07Z4PRrak19wFR\ncuRSRVkaXON7R2nA+2v1+KO4qa7qxAAHmWDX3qspkUoGRqIzQCe6TTmax1/Ml6tV27QdNtR7xAEG\nwE8+fZidUClFb3uifdm9rxrrey9jQxgh1NhdY3Wc5YM9tQxiJER7wARMaCkJwDuGCZNyeJoSLwuD\neQtuj5QCll1oeyc1JJTlilyYqt6ymiBKwjAfCZ4bMlIsFtAHaP3ZR9HhD3az66qinz5VKQoVHHQl\nZbTfuXZnjaO6aZUk2UzxPDAhfWqtZEhiSghYGNJ4tpivrjw2lakS3496ssfuEBPpODUudE1LTMII\npx42xyPati6ZrknuaWA8G6iidOiwckdVpblSlDEeCCAb0Mg7PZyl4qzvDg5f4tUSeqeXLQD3iVWV\noDNMHOVvfr+KrvnST1ydGibufbF590qvRvl4AZawlqPpSZSKZOhXIXiqa8WZyrKG2m5zb6jgWIb5\nUiQEiek+/Tm/rKzbVsi9Hro2hDcvNws1FkMvTnsvDpg4Gj1UB8uLmEjWdexH7Kso0JxkfXuv1vUl\ng3yQnZ9WbzWQmMbEcyty9+RJ0neeh/D+m0A71tWWckqIT0ag5iXLWtJvhNdUWMGIAUeAW0DniEbD\nRS0Cezzt/zBvyDo+G5wee7gu/d1hHasYhjKsCfMDGvON2QUjTsJweCKEtNmwH6pg12tiYkt4cj4f\nMrTHNFbp/av+/ng/GvGHH/L5R+bom17ZzW/W+xa/f/ky8M35n7iz5TiGu8wSNsSbPTgIfPO9f5/b\nLz/Ak4SGPNQGD3uk8xAIHy9nwN+/2v5Il/lSQF6OmrbhjN7elxFNpVPcDURtDl2z4a2NyIwOh2k0\nITQ9A6oISJuOmkBNlBN/CL2hTDKISEQg4aI99l0PJhAC5Lbx+SXFVLKxZcMenGn6EkSswfTQ8GHs\nuzR+xBOXdDW1lisRRdHgqPtqV1mw8Yh5iZYDEoYeQsd72ouSsVkMYFIRMy6tC0CQZhxi4iki40TR\nYACINt3eO9nWpKodWGTO0ZS/+GMZnTTLyAw56M7jmMIQ2TmYd7099pUzUQb5Yh7PPUPeI1rqS+uE\nmOYz1u0oFaxtwvXrLl9yPlNN4frCISMejNO7h2dTlnTqJKiB3fVVYMQGwhxRSCfzGa3zLRaZnEeY\nUOCCpUE2zjUOMBB+90qTwsWZPT9bspEEylCqq71xdY0GUVSJzAVLPj150tq9dabuqs3x4Dicv/9p\ndDp7+Pi0ZyWPxmDV4Ttwz92nrXUYdExqGoRxXQ0cCB8g6u5stuhwenm7+b5YU56OapRlRN9JHOvz\nsYum0klNfOIJvv6meAGb+YfgMjccBNs504g0orVRUm7yU/nHH/bHNp/N0mbvVpu7f/jb1elX+mxW\nDTIjFGSkmIhU31XXbRsS2sjAhxgHGFi/bPnDswc90m3vr1/U0wdjkvHTJyGe6XRStbcHxrJPT9L1\nH8zqjaaxsLYCMLNHjg15NrTt0K1erHob1lX59IwDSqAd7WxCbQ122oXHD+hhVVG9iLw9ywZcRbs3\nHaZ4vjwrwsG0fRzyv1SfPx6NB+lNj+ssPkJ75IW2OTPUOlmq57FycPp4YHj7vqzpXPBJoGlDydHI\nwM4WAz1aVffjMcHIbcp9l3LiQnQI5yN+zCIO6yhcDY6LbrU/EhqHkX7Xsc0/4u4PXewC1dQV/fFS\n9ffusAIpRTJnh0pgjSkVNMQskNS4xJP2GIZP1IefDTg1vb+Pcjd/KBLaeYdNRZOA3dFZABHB4mQw\niOPJLI5y99OPZld05bXnesfH3fyJj55pSTpNTQM6QEBqISaF64Yfn7iryjaEMB+I7Wx9LGrjCJVk\nY7QvfDz0kgBtA/EQ05h1PubSBAtepZMkezK8/q4DDLq2bhvkCXXeJxFXUVJXZH/vsBOPzp5RYE4X\nNEOH2tz5e+GNIumExGfK1Z6UkGZyNEyzAfOyTxMMuhIaKcWTQZKcc0F4djK+/m0rCLRota2/+Q6f\n/yyvjkRX1rW7ToMckuGnTZN0NWmwsx4IkiQCkbSKHTDiotjrzV2ZxoyEsH5l5FirnAFilCITudc2\n9CyKgDNidI9AAfzHfzKpr9X+jtY3e9Jbi2E0yGRn98faNIQAdMH++q9ePfi0oBii5eCLf/GB+kT+\n9vZ3vlO1PVjKY0egd43RjVMPn4u4x/bVYVOETXU8GpYtU1vPNpc1dzDayv5F6hMi/ixz0Ham2m5b\nzsET0vT48EMH6NmS3RwRKNG99GUxWM7Pnote+whHb8J2q/sqmIXIXEhkqInW1PkUpT6E4zsnByri\ng+EjpWHbiir2TNDGoGTEJTkB3gK1YuL4s4pTPVs4CJWvoqlTEJnNfatEO1tIObtPY1BxE1emuaGU\n8+ChIn7oXWB6aOMA1CrToB9lsqIeuxUP8iTKTUb2iTN1x4V01A1GExIUtdqSNeQ7lPsjHqy9nY+V\nZESoqIKWc2HV/bZY+0X38CsXTXqAVRuw454PmZwhVKEvuiiLVRZY8NTbQUnyTbwuKReK90fS3NB3\nhqY5irkmicEGqkPa1onzIT7nTbT/44ubYTv+5MFk+cV5v11LNrTOawacKiCEeSZCqRhMlEDskTXe\nrSlnqZSCAM8kZ8JKCANaoicCNNta5GwkB0sFb1pC0buwvfNjADwRELgFoBHHnmpLCAPTByAUSWhs\n5VBShoS6m10RNPPIaaSOrgrSNgHHwLCxaB3j9PDKYwwsUYIKCul4trzB9/E4aXutX1dz6jUNPGVB\nErdi+sCJjAEIZTDMBuy0BzEkyENRO2fRCVzxzgRVxYrJwZAnC2ZyGraNaSBqaAzQ2W44TbRqKWTD\n83D+dIwKX92Y69XN+1eW+ghRhBY5px/8LMZhZaM7IjV2IKKxIYYg3a2r9q2ZT0cUE8cDUFJVfdlr\ncrSnjyHJE2SkLGDToPI8zwYuEiFDGavy0nhTQpyly7zbdVSN+41NyVANhmlk9289ZUATf9v+aC53\n0KhfPV1OF+DNbjE0NxX5acDiID7Z+Qz1bYREYWCk9mU6o2Wxv39fuursQfSMy/OX2xITaKxvYETb\neORozkOTFPfFu2BSlS6hXjNyUlRIKbRds9tqSWwsWM2ObMizUSwPImtjq0kyTSwKU0b9ZsSaqkCB\nltdrGrphbym5ARtRFicwdkigOOhgFB2qeCSx1+MFzhcCoRX+wC0hIPuJjv7kxOb27j/uJUI0drEo\nVZA5uM0oLBeq7f2xhhtw0pNTwhLN+BEmQ7bxoatdlCImARweD8eeisnsvOtJs3J5l432gwROeJSz\nSa+zuocDx5YQKAXRbRVFKXPAys4NHCRBzd1SIrIGgOw3aGNMleJRhJMsHUfjEYI/EKMRKNckUrTT\nNs4If/7zz2fnm+Nxvw+uu4Ljj8p1Zr+L9EYd63akJj3Ixm09Z5dry69AxxjnhCI1Dk23a+IEVfRs\nOoAhxKoq2ptpak/Oo9GIEvCUUPQ0SpkwAMb3to3y4FPngNIgaCQZ8Zxw13jrQ/woHyYqBLS88hxt\niwQ4tKKpDZExpV5FbPBIkEfRsiDbXxu3p8EH7zUERxgqFbhHkZLAOSBBx49vCE2FiaiX7thdb0LN\nxsL46v7NJuBw9HSmYtLete9+52UgTCT72/1wrJ79cuyXLRl67xA3yfq7oi5ovcYQkkwIRojT6IKn\nzxTBDixxNWQ8J8JrT/a26btLmqAXhvH4waO07/l626ELcTTiQIAhAezc0ceFFwKOIHotteSSkDjq\nFX/5dqULcIxPL0YqpU2ht8fy9g1efBRrR+/vfF1zRuNOk077HjBQ17DeEiDcioSTEY+EKDduUzVi\nhDSNKeF13Q5jWflju6l9j7iLdnddzEYiP0N9maVxp/W25nzEfOSoxGCM92BAHjofkD+4GGA/u/+a\nEId9HK7LYlkvbr8mdu9prPFMI5dlDyOSCSfanyijYIjZ1bLUu5hHOKW2z5M0ywfiODSe903QSkbb\ng5vF81bng0fU9/J4D80hOC+wD4lk7gBiwd1JuSYtMsOQtAYCIz54D67etWygpbMqUOUZEdz6bf9B\nP+mC26MB23VEKnsR/HAUfutYsRHZFBjBUmAfSHViSO0Jx1piQ4nxHp2p7j1jk2E+ixl/3fYsFgt2\nSptUONHQ7hAXfBlc7CLB7nJw4AVVkELqVaBG+1qkYvqIuBXb3+j9PTfKqVPCQHLKeJIlhEHo+71T\nA84j54GatPaLIA6Mjx9G/IxEhAvuaelKYFhzLAg4cL7XlJgQRrPZgC9ZpZEylaeKBE6J96EDffJ4\nGg/y4TKCYddUddANocAo2M67EFBIHxxQ0bbEN9A11XwmrWgq632H1sWTccYsX9dgwPda6MrxgsCE\nm+B6tJxE1Q22BYszThiOlypV4IK2LZwvsp7Bduu8scT44TxwacNRx8M8fZaVHVZHtru1fdtMTiOy\ndEVXkzGkQ6yPqt3Bam/MiA8s3r9FwkUkZt4RfwyjIRlPocv6MKprq6M4mhWD8tau7rpcZdkwA4Ld\nXdPpLplhxAOfkLaDEMAC2AbEiGmq4wXv9d710nmYP4h8CsU1D8ZG8eB0EavAjM+DqYLrmQKoETzx\nmgJVaiQPbw4eycnzbPqMMO6mXtDvyea6+uGPDXAacCCSBccMLJ/lJ0GHSld8gNyD1bonJTsbJEzO\njsnq1tqjiU74408effPb74JFQqkPHiD9p3/Xbp39n/2fkgmeX9m3b3+H4z/x8qmDlByMIB2VAAKT\n/YZy7j/8OAl0fPW7Eur0QbK4C3Xx+N2leS38mb2PJlOiJkIko6DOW91mEdts+njAe99fvi87N8tS\nMfCYDyN0UBzaBu9OHsVP1KRoqvWVO4+jegcPSGZLUmniHUUSnLf1DlrQoQG7RXpOkpnggXoeyRnv\ni26/7lt//Og5854GJGRHeEQ0s4qA/TkUf4M3B8JaAop+w7loI8Ix5m4AKX7fV5/BoCOaSCZ9Sa2X\nEz6cBOZXpTUdZlPJB8n9XdvtzMfTD04XH2BFTd/3sLZsf+zrLOKCn+malh1MIDmsDJkEHBh0lluv\nSCxURE22elvzOeSTC0onRI6AyO5oKfTJkFgMRjI7BH2AWsCx7DhbIlu004HkZWNLHmfetiSSnFBK\nM6U7zx1liXz4bCgkZZ4w6VPmiG4TyY0IyYm/by6tJXPJHjyhUHEGfdDh2JhUJVb7xrpDpQ+bUAWH\nHKOEW03AUEaQEv/ks1RPstMZ/8Pvrm9eFfPpeP5g4PsOBI1iRn3U3vdYR7RLs2kaA/WhsQwwwsXj\nyElyeiK+/v7+9Y+Xn+ZzsQCwGDEi8ihQ1Mgq0+2OvTh0Hvt8Jqefcis60uCcDt3R7a/dgXgEWAxn\n3li9biQhWYwIhuIKREeoC5wlD2mvIbwnmlBoMcEoeMNE2r474NJYxfyEWRcwgG+DtdAVLpqi5yEk\nBoDwKEyA+i00ezccxIvTE08aDEI3qgEjCGWa0AMKyrwk5dEH6wllMvMODg76gCE7DXXpDdDl48ep\nmN6/8bhH34Fq2Hk8fdvWnkHbFD4EqbgRRo7a4dmoat12w9r75uJJ/uzDi8O2AowLRKCupjp5Ha1f\nE/rZdEEev7y8X36A07SvoyhnaLu0ufUiqKqunywWy7PZyxfNhu4wF8ye5Edup+wA27KddyUDkw4l\npKdpNGYHdxtadCspgPcVdbsUO+QnZ7N5mkr3/vq7vi7imE7mzKTJ7/64Kxr93fc+GdBdoZwniqko\npSyihDBz9KS1iAwIy4wSliIBQoi2aAEDITGR3baXGYmAiJQ22B4JGHRAeZd4672IZ8N88OKv38OR\nYpNKIUMD5rrMZpINskuy74VriCerNjsmdhfjVlAc2oI1objdtDgi0YWg0f3i48TS2vjtDrdVs1uw\n2dio/Zbe/vp6A86FML8Q7FE0OOcBLPioKdmuzAHB95yEkzQ9Y5P0/rIg1qcJyEyRlHWalkhDQIdI\nieKYlz29yqGY9DAbkZOzft8n29XjlRfFltzWR5nJB2eTk6AkjUrTWkDOSezJVHKIwCX9fbUlwLoq\njJSIKCriEJ0gvfA2IOUkxQDloScBxByEEwEFOqPR0YwxRHVCRip+WC+uf7p6++NeTjKT0DYExoEj\nUJ1jx9oSSBRhB0A9UmPBUknFkA5j/i8n53/33fv3b/d05R8OBn3uHPSm9t77dECCtwDCWzdMyeAs\nHCstAxmMYbN3u6tNNkpPn57IPOkKJ4eYcRKPe3RB1ATXMafeMc+Fj6YMFDWSEYDedqUxZ4FFBYNT\n1RJjBlCGjnUM184ekCDgkDkerOiBoaSCaaRx6LW/vzvOHo3UmPJ4SonmjOjSdNswQsKjCC3tippz\nygT1tqHCExag29PgVWSsowlzBIMpnNaAEfynv30xnaCcQjpJkpHiI065tBFBVxwqEsnZzz78EJKe\nsorPWoLc9PQulLq29rgvupP/7393+5f/ezL4/HlSXr39t/BCkPTCj5eSUx4M7RocpCMe5/uqfn27\nibJZ/iwT94v9uk29uwtvLskqjXLFBK2B3IZUKpmMvKs9gttRs4tjN0r6YH4Kl7aHrD2YLknZ2VlG\nDeWjqDo5//b68vv7be4zVcPpeJwJ0unAEDglHgAIkAqgI7Giiot4mBUBCIK3AMwBRxecjtF70N55\nE87cLCOzK9Kss20C/P4VwX3E3EdRMu47t1tX2FZnz0cDxxLO1/eu1UQxkasp0+nNLdEl4YPUoi+b\nNg/hyw+fnC4T02/zJ3XPr09ysiT08g1r39Qvf12okJkX492tYyzpT+XZfwFizDq904HrHkynKImx\no+9/ywNrqrZ2R/JkIcbPcj47utRTQgWDekWv/kjduuZ+4okmTNDYitEKyYCak1BSl53Mq42xXZVN\n1Hw+YC0CGskQuEBrvCOggI1JT+qOHGwQpCNBj4QgyIihlaZN7wMPjHGWxoITBKDSQ7g3dExlJGto\nHKFG76KxgICTc3L9Go61u7u2o4vUanvcONCBEEkcJ4EQiK11QfuGaCsJFyQBak2nvcnGYnOr3Qbh\nE35sDGeeMgUU51n6wu1BaxIF6Krm1lIKlKZKIdZaAIznI6WICQURKBbAAXzia0IymZg6BBpg6EkK\nasxCTsu+C70BzXXtQxlmNQynGeZNGARPCXpS74h5D5zQyXRIRk5EuvcFIOWMCwGEwnHX/PhPdw++\niFWCjgsGoxgYCBFhGrQoDn210gQASOhL3R8DwY5YhMC0RiEIOERATqVJwAlZVQ7vK3HwySOaD4gY\nc2JJNB/Qvr4Ox3gKcfJw+mTy3T9cl1XNOB0NhmvnetX4GLeQ99ftxffi8weTcfPk5sUrgTjVs7CC\nNe1dxBBx8XRpSbi7u3eiG37Mw9XB3W65HYjVMMvOO9u3un3d31M4ieu4rjV/JOzEJhkHm8Iu8zfI\nJQZvdl9bnFn12VzOSph4rHQkI/GOAxMoIyQyigZxOrDaGoKMgwTPmBcjGgxBQw8v0a38dNkZH6Hm\nxmiHzciBZEpYR0MHxFMFYEytdp3y8pGXm6y7o5v3EIdpEp2i7CSF/b5q1+CmjgzCBLk0ri+CrW23\n9sGlXI44UErJEGnMIJc9qNcq2c8veI+XWaZqTT54yt+/MP0PgaIixwXWWKI2kj6i04GXbaettbvC\nUEWn8dwYvN3Yr7+5RRp98mRx/nAxetS18SUjjHjgBGMOEaF39w33rXPMb1msChLpGJ1khqwv19tV\nXFZyPjxRABACAUuMFyT0vVkVh0kip1SlUVL6lQbvNaRioNtQp0AjAilBhVYjReDB0TIEFwAhj7K+\nROx7fOAtdyCdcQfGckj7ozfJQxYM9xRdR1zLugb7A9KYJDJSSYIy4wmxeNB1HRx33hEXEDpDQjYW\nxy31vaacWxEM1yzzoQWHCoKtyyAUrTeQoKWpZDmYQ7helaN8kKa5JESMA5OIqCMCJEbLmOZge0EF\nga5zRCOy2UlC15FlE55FR1JtdzftpTt7liALQJyhECqyeRmEIYrK4yXBI4uWqWfEKIENFJuGEEAC\njMtqg5YAnyVtU3Vrij2JZgwCaANACAEMAZsSyYoA0DxO+wLWq2L5IAcSoYY8VV0dEBjP00U8jGYN\npjUST5Eg9ZRpfdjxWZTE9P7mh9U38vbdarqIozgzXTmDsXQRiRWxEMfUtPTqJ2qqYbuZfvjBkB3J\n+na3zc3sZ+N8zNSQ9q1mkVp+mpgud3dUjuH0y5PNYaJusvf02uVFka9WVMl+piq7zGTILJ2gPAlZ\nOjt2+qjfdna99dy24kPFA4UgPB0SUpKq24UAi8WcIJ2kiUAvpmT2PHW0Q4/9llAP/hiY4cTS5kiq\n1qM0hnQ8hphF1vUe6JF0TNJEUwUYsLbUTjFeRrP7Z92hS/sKwIamb63x2WTUu7I8Hm8vDVt6zhB9\naO+67o63a67kiCWRRqss5p6ez2bxIDJkq8YmtvsBKxMfyx64nLqExdNBu0s8oh2YOgSWJr3lx2vg\nWdZ1+67YjtRUMKcV3+3pfJ4HpGpMQaIjljIqeyWd3QIZcj/4BLa/Jhw0xYQyr3xE9qf8EtrNkbZa\ntl3vaPxwPoWxowPALKBtwYUoCdEsnQ4Y+K7BOpCjigm21B+YDRnGQiO969ddH7I0LIgUbaj2QAl1\ngQo+cLWu22p/W8UXLJ0xFohTdWM5FXR0SgRPFzMlOUkkkxxvi75tMI14PIwPnb/7YRPA8JzEI0KB\nUEFYntCEsJVm4J3V3iPPwArXK0MYLe8suNCHUB5Rl7Z/3Y5mk3zhd5fee5bEMxcICeC1JyyoFNMc\nQhI8YwfjnQ2MeBk8IELA2ShOSWqqvK5h77BuQtPa7Q8w/TjHjbbOECe5jylhhKaHW2rWnq98PM56\nANsScIRL7iMAknoD7X1XXTpdEYeY8OjVvfam35aagBmORdlYc8CJTmIVuYSVO41mRM2o2gPxgcfR\nCWOuBQxNvmSzx5My8ONh9+5y++jBiCt/123YKObjI6vJ+tLxxJPhFJ1m1EpitWuzKLo4HZ792ZTS\nFUCIxCmEJqZD1pu5jJa/FP5U81lf9x0VYTjNKg3Xv7+haffJ/3wWt3X1j9U0Z+VVdtdVXpDamC16\n6RR762gE2TLIBELr2ZSEAqtdF6iYniXLjwZMtiTyh/Vuf7WP4vDs6dgFYmo6TthsjIMPDT46WNHE\nciisIBXc/9HIIPu1aSwt654n3HtUPYsGqV71ZiOpEezUHTlSAkzANLTQVzGbKOr+9LNHq1M8/MTq\nd1XfkiSio1my2t72+xbf6AdPh85Th5EYLjOy1HXc955SmiZxDKxP27LbyLy9eEZ5Yn3bdlUb86Un\nZPIknmX55bd+Y0ljAHPF03jznsh174fm4N+CcB/9cmZc37qkk2kyptdXxpTW1ciR00AZQggwJgCE\n6mGwgvB+pfljNzv0EdAQazdA29iqbrq2lHKekdF5lhFS9+E9YqdSPjwho7NEWuMPHaEBpX8gkxe/\nDe3WpzMymEqoVegGxhKYKM9VtXHrNQBN6sbsdyQWCTEPdBHgSP0AsovsUFtPQCpqncvmQWRUpVQm\nqSPtg8f5bm9EjNq0XYPB90yCa4Ktw9nDATADBJHAdu1tTwHF6t5fzIia0I7rTMbtxscZUEjUGKXE\n6r7dVmZd176mo3zJqXIdITJye0t6AAEMaPA6ENq6RiSpKzDUNPTEG5MQlvOpV6o+6vvdikSSxez9\nDu6+b73QHqwSjLEoiaaEMKc7Z6C4beDeQvDD+XA8fRimsHlblK3jMsnkMA6JD0Vf6ZrRVveEOZbB\nbDnLBxldN/vS930Uybzf+3BsFSjqpNUguUIgJHiBLlIkXhIfeehhMpu5ilIrgdPJifBjIaCXF1Hf\nuRDA1HfOCgXRwAk5fXTowv1Vf/758IP/8umHX01/8//57qc/vl0fjYrd7LNUnSR72EyyhKfa2d55\nTwA/+FxOk0e0t80PP4yes+XZgzw7TX7PL+tjqaDkxUXC33aHp8hcS3vnQ3MkGEWek1oNptF0LrA/\nhq4MlSc3jlVklNLQhq4gUxYtIpI9KdKfH/z5diFnQbuKOr/GaQi0CL7H1Ip+74HSEIht0XEmRGZX\n4CrKAmk5HZwFb13i0YcgQj0hsbM1zWk0g2YLWZakmcwiKg/55bZZb7nDgCQi6Xi1x1xJVxOiGLFQ\nd3r+eDB6TJDGPLHO9IVppqMJNp56dXCd59JMy+FzcpKp7SYcL+uDDiQS0YztXq5Ipr/619LMVp4w\niRdLngzLMYj+8L6tNrvmuqdPunRojEaOnoKnknz4X17wsIE0KK8OJCFrTjrEuzfUXUPMaCR4WR0n\njYuUVSnGJyFNIUhLXIeuj1RLGaqM0jzZjfD+Leyt7+oaIo95GhC7I+tGqth1toNAuZSRNcy3QDQr\n7lIAJACfZFNb187paAQEUHJwfW90EDSOJJ18kgxavnqjD8cDoyLPOeUkOKO3hp5iQOwbs11Bf6Bg\nyZiOzDa8/a2++BW1IbgYu3tDOCQRR2HOfjEd+8FhhXc/VUAoIQQQQgeNswZNRMC1biKidJZaJ9FZ\nYCIgDZrpDekK5yIPvrB1UXboglcyjnlca02PIR1xMVRKynSSDXjOKO87TgmUHQG0CG5yklOCaEgZ\n0brq71b2iYqkzAaDOIrN7lB6aAfnanQikphzSWdRbi9hf9NDoCmhMh7GIoHQBuN60oHtuKWSMYyD\nT3unCAkaHU5mnABaDJNZWm0DYhuIHl0ErbDqAi2DB1uZArJp8KFt62//QD/4lz8XfnTxZc5Ttjfd\nIpdqkFeHxo4IB4wDmmAIo2kONCINvuyrt+LB7OTBVF/v6/dcyPHPxOMbQ9649zd1PyhD+S6lLUaK\nMm/snS+OQbpsvsjGU077hjAajE8U+JgGznwQ+SwWzkfCTJ/WJw9KAu2j0G29uyV5+SAMHpH2TZ/3\nVG85On6oPHGcoaIBYhJV99uQUTSoSYh0iB+EHoAR2iBFrY58T3A6esaSMe12fbcp+KhNMsKOgRBy\nPMaMZqmYmU5va6trPVJpRFh+hg9/RqIFUSqrdf/u1fXhcHz+fCwjDiLUiBEUAIbPwlioZ3G0e9Gv\nD+UmwP5WyTT78vkHswtr+A2EBEkhngzEAcnr0N+X2yM+PR3EKqOc2dy7imNLmtjhAHl3o0/UIOG1\noK0tQ3Uk5iei6jlPT2ik8KCvvq/Pn5vlzywftkIGdODqAAQAmdUaYgXAGUMQ/ECgaBztnWiFw4Q5\n4qJYinhyQowD14uAWBe+Lz0RU0qktfr9G2AigsybxgtJIThEr5sAgkGAHg3JQS4MVq31wLPZdBrZ\nVm2u79dv98uHOTXE7z0JFD04CADoC9x8T30QTUSIi0bDBABa13oKGDMBVBZCSEU1HUaCAXhjLaJl\nENZ+mmNsFSjBHLNGgJH9Btp7DoHf3wdrKwvEMDJK5Ml4HrwzQVmmjS/6vZfLhA5zkXiKIA1KgSlh\njBIkDASKCElDjxtSl8EYc7u/vzhdxiNGSLRpDtvNLsVcxQykRwYkZcvTqFiHwBiN4keT8dkpBFl7\nURRtG3okGoyvYIyGoJKEmxACVZnsO+c9IiJaBFs7JISDRWRUAcU8iaeGtAYDJeko1/Xtq9f/9MVX\ng0cTefGX0dv/tP/hsqhlOczEw49yGRpOt7ENHBLOE9+Sb4dbNk5PoFz2+t0lDs4SYjjfnzy4lTuX\nbfFNFyy7picuHUXgitrteJaNoskAQFsIwfE4GVLXU+FnY8oKbnthPQUwLO9pXsWkPKlgSg8WBsye\n/CSKCmq96Ae/mtt/wsSKatc1nQs0aM/G00EmmA38eLzsgztAUAMo4ijRifHIBEGGSYcAx0EU37HW\nkDupBpQgB4lNFtzcAnt3UyEBLtrxxZTVQbb4+AFIuaVNT+pRIuHTTx5d3uq3b/d16cbz8eIiY76m\noqWDPZgAfDRI8t0OSsR3t/aXn5y5Xq6+LejndEJZsCWHayTS9bUilATI49yyYsMsUGYZcZbQecrz\njPd7143p2z11Bq83VDeMHnlwMTKmOIvnytC7e3s7Cm6QpApUb6kzQjsTMYaEUkvKwhZHAAyAg3gU\nAzjvStuRgIKR+PShjpf+oDUFxizsX7I333pviUNOpGq6ALqNs6irq9GM9UVIYuY9cU7TmHvdI/hs\n4UcUj1dWk31gC5HCaDloVof9Tlv0nMHFaaqWy2ACENwVdXFzrEozWdDRZILcd7ZvertbGT7ljLE8\nU1kakcannBKAvgHiKKHgDN+8JdkG0lGUTfKyCEjANaGuEAJvbGCUhgBCpieTJJe81ToZYzwTQg2N\nrzx1cnxEIZAwyTBSnkaOgXFBW2cDV3E2XRiwlJVbi1gGommaEqLi3HLwGAx1LIAnrAeIuBBxTuq2\nUb3xCfUake7iM5JQZAJ9CW/fFwj/P5L+a9e2dUsM81r7Y48jj5nWXHmvHc45u06oU9FFSgRJybyQ\nYMGGL3zpB/CjGL7wvSEYNmDABCwLFCWaWSyyyEon7bz3ijOP2HP/Y/OFXuT7oO9ptuKudSFCBIla\nguX77YZi6lyPKD0ynLFSSppEMxiLVQTDuWAis8FtvqyGf/heBP+H/0URPf/6nzd//bfdL3+UXE5+\nv/ObQjSZIBZNgBZoek5arAWr3h12w+020S/T2Ys8/rDNhvVH30+uElP6dHMMY4Prqcx6Mc1yUWRw\nZke9g8TwIprEZRkrGCZyruqQ3JJraPKRPnnC6DR4cKKXkVMsmoYdQfjcyFyw/DHevjG0hTLjzvFD\nDMPBjz2jvvBwNMiTqYJhIJt26IwKHHkCTrrI7GCQd6EHOEBuvN2Pxk0myc1bmsCjLGQPXxxPns86\n6MKejfft+RN5ecnmj8E0Y+gOrBsDWEXkPfhROZvElmwYmGphFQJgwF22LLMPXKeTwrtH7KNLO6X+\nKhppki2jIG0chjrJGHuE4d6/f3M4+YSDXfJw6GOABEZrr397J05mz7O06o/7d7e9qWIYmeZPhToJ\n3TSMfhh8muKLP5iXJ9chdNY63y04L0JkBjwIaVtTV8G3JEBPNHtyubbefriytnbyNHt6MXWz6wAH\nLD1CoM6cPM3NAD4kJswLNtne73dtyw2nyJgoRtfHCDGAg1ggBefJW65DWvjxjACjgVEDS2a8rSHk\nBEjriwkfVRqBWpkkE1Ri6If15frxswUCPjxs6so1NWQ3mI5MJaRs5KHnzF2ezmZP0r7TH26wevD2\nSCCnXUvDA6rCkuIoeGyZG7LBBaY0Y4xLUAqzXCrB0gWUK5xcwlQSKLY1dmduq/GYqKI4zXkCEC36\nI8ORe2MsCByT1XI9sGLGUKBeDERNsIg8FiWjLo7vRzlFkSMEAzRezMWDCxqJU6MFiVWMsGNAklQ5\nS9j7npxrj7HP8mg548o74ikwTYfjUaFwY0yVABdUjsisFMWwJ9bQqixBU2AadHp7u/l//If//v/w\n459/ksvkvy78dvL9PxlZGGZWZKyeemg8PBLRBbPjlYLEmcNFH1POsr+Dg6a2+vCwawY4zenkBPK5\nKzaLfaVayYSmSVEuPTpU1iwxTEjNhNMwmero7Ajx0PXxJOULGNN4DX2mfAHyLoG7EAVkDsKUFAWK\nyE3o8x/jsInFXFSVc26wTm82w/nZvG80ikxIBBvkRhVnYlQjIh4ZL8youeq8dLVPmQaMZhh8w06n\nT65j4zx7+9t7HGAqpemhu3cJny5PJnfHL7ukkQxKUWaptNkgHC8m6+omHl/HqRHJ4/MAatzd3934\npsJZmuV50nOhFu5Q7//2n5vsE3uSZP6nIvPON42j7KMfXdZIt+bQh84eQZ8lkRAkQOr9kTcPRgBL\n2roaDV8v0zp1dU04MowJDKx3FPtu9imbrLiYePJhtNEFDxAiCYqoUpmIZIHeXkSvuAZIMGolFmVW\n3/ciihBhHAOVQCJ6IEEx0KhzxqIrIKYK/JhuK2hvgEfZBcb0VK4U+bHrO9OGZMq1Es4ESwEiOLCH\n/UZxNptMsgtdPClGN0TyQjIwHkXkK8gdLU5SkbO01MCgcJPoeVXb/gYzYKApReR+EBnJSRtnUJyp\nx5MMYmfvVXCaDKFW7d5lCTN9rDtPATEyzhGIGGMKOXIgNkA2Lp/iTEIafABKl7Lbhd2hA88Tgx4I\nQ2v8kaUGU4wRrO0F5ojIMGA2eOgJYkBFHDnjGjIGXAMpRoRgjVW5mk9IM2dj4xiJDDyNmiC4PkSB\n0fbOdDH4K79SRaFUiETBydlsodPqfbSG0oSrnBNIG6Fp2kNkY7SLMgVud01tRvSEu7cy/JHjGi59\n/OQ/o//xb+VVba/wN2scsgBDBBAxRvmgQivH0Y5nRPZacgGtG4blh+RVtf4Tae/C57vTIOVIHvJg\nB25EWsipPW3cSXs8NV7uyzU7P2VnPO3BR2+868PIfMctxbYN0YRtEtsUFYcZEzDKxGsRM+nEQ3Ib\nV0N4brkpl3023OMD0bv7QxjcyVSwdOad41NPBszRe2PEBG0tHNhtaWhfmJqVeRHHewD57grPcsyK\nRXwj77+En33+i9Ca5ssxC+v5c96CO94ci9GcXiatbVwV1s/SYGN3oHHDXU+ZETovg0weOifBaeZt\nVE/PH+3vw4ft+9p0si6Xn5xhn5q2ko5CQMfjfKFwGs0MIw+DcWWPWswRDnc93n9LzKKo99a2YX35\nOM+H0W7dBYvN6b4tvnzrNs1+MdF5wsdDn80hCOxDXTXErTu7OCNOhI4oxMFcXvLJq4W10NzfDRba\ntksoisDaKgbLuNIUlTOJNCoMPlAI0EaeAUt0AVKlY20YpNdvYP1Ua6/HAZt9HHfjxeNk+mzR9RuM\nEYMhAktgwfdhLwtKomIIRC6C8wmDwEaWwsJnA4iEqWnQyyxZS1nyr3+zAQenH1/Oylimo9BbNR0p\njSZUjrRaZi9eFXzP+ntsA0kUjR8OlRkOXarSYj0tM2G6GEwE8mAU44wnbHamEMYudAq9I4dcCaZz\nBYJrtsWmG9ZzUZwUNvIhMKUEWUk+uh4YEGAEBgDgLDiLDBPNimi8NdbLZjWfnU8SO1Jb0r5tvQr9\nOTfKCmKJJ9aidT4yJlcpCUgUSxgfqlZkuWfEWEiyaY2EGBkqIKi6EDh3Ec5fPWVL6LZHQEY4kGXA\nknhH/+LDV//F7+VigGefwqs/C7EUb8Nm4phDJIjvBtgz6VVUjiUQMJXTwpBfm7HLTCYvAP9uPMm1\n+fP1r79oT2NR+SovspfdTLrImLP4sDyx5VP2eMVOTEih5qX3jCW/n9xexfe/s/2xp3poJWV/EJdB\npTwlxjA6BhIB/OiVirl37hOIx8iPOj1ypskh/NDUi8VJQSxWdb6Q3DpuB+DO7EYmEWXy+tfjRycZ\nBLc/IOHSQ3Sju7qDWXJZN2Xy2NYn/Rfjd2xWfsSmj5+XP/mjdPrR/P0P/3NeMmvFu2/fLh+v57N5\ngJsA2JHbtsz9ABcvVkPtk4QLMK3RLAFRwr7Z8wUr0lOtJt3DMXa04/30pGQB27FnQWaJ5IUsV8rI\n6yD6PgiGUSBCFwTnTKVpmiCHkAseE9bxOmezxTluO2AZMYgUKAQZBHqFfRzuv+lsxZ9croLwPbam\nPWbnRU1XuEwoRXftiFtQoun7u4dh9ko6sJGAonSW+dZFH4BriBGD820AwyhK1CKMtt+yaLEPSDAB\nJ+orUgzCKISYSN4PvRmdTwpm0a0+WjPHuQfwPlKIyUiCrNrzqUsGQDLIwwhtVGh0kLOcccV5ohgI\nCkUhxFI0Yh81sQSii2w9mz9CDNgabJ1hgklJ00+K88epLigO8HDdDzvyAQ1FskwytlgmpMaIftTk\neOQJ56RWi2SRnKZCfnj9HjrUUXsq4hCTdN73cLihvguQxthZZ0frfXSKUTbLZxwyO9zLAqYn5WTB\nCk3RQWZZdx9Ik19EC4PwQC6yAVwLUmZnJyc+cTyMRAbqgcmJQ9ZtQ99TArliIsF0Mk+b6qHpiRNe\nPDtNL5J/9k/fOTgCRMUnE3iahnj777/e/15YQ3wazn/+j97+038n3rTulcaDIYrYArnUpgOfiKVF\nhi6okoYaeg5znTIZ7XSnP5KhXl3s+Lyavw96EhdP5UJjnSzD7rQW63YxHT870BzI5i5FtBFSC+kZ\nd29Yf29NbwKm4rEWKxaZH6ErUDlwijSX/WJsWPQ6yuKPM9DTYuRdbzvOHprq6tgXwWUi+oKsCzC1\n05MiSsWUrGK+fbN5uVwqTjfvWp1cNCPlttx9LyQ7N+/1YjJ5/Xbb5cnj4mxOyWirv/iP37K3b7v3\n3z/+9OTZq6cSZt/9xvSH11+/rqo30hA78Dh+6KcfUOVqpiAIRnd6dFb6XNoJCsWIyAbYkHSCzQsn\nGPeTsY2pA0AZm3ZorLscYvDC0WMfuiV7O4BQOUxnmrMQAqScR/Q2acEcTx6v3r0l6l08sOQsC5sq\nlhEcOMOkUN3O1NyxBC1ZSFlUfT3ulMqJKTnLxJRo48zY7fa8iOSNQSYIoo2RHEAkIGZ8YNg3+xAB\nQSgvGGgx2BiOaCMgYo5zHEe3D8AzdJBqzSCOto0DIz+GOnEWeYxizpFY5F4lGHCrlU7OBdnAEz/I\nAZXwCWXn2nm677v7h+H5XExO0og1Ew6E9yGAT9Cn6bkwHWObYOomn6aTc3bySZwWhguAkbSORw3H\nI/W7NhCr7vp339HsZZBz61ILKSFG1FwypRhdTBK9PL/Z3G+/DjBVmKhMXhjXo/W5ivkZ3/T9fgjB\nkAwKQ5roIsNkjFLlcfIoZmuQhvyBckL0R9KRhGKFxTFGy3HE4z12EaRwMY3RdouUodIEFlCHkV39\nZntRFAkXDLzfd77rTGsnRX78bteZJAlS5KVjLXUm7rv6qxFt+O7+bjmzAj7/b07a/wl2qc9Xufbx\naBCdo45hhTQXsYDZxFUkkXH+ZLoceuqJqYnMnrHmzY26XHRHfx6S6UZfTCdcd4iDnLbI6pd9UwJj\nIPMhIFKaxkc+nUPmzr07iKta4A2v/717/ZHRH9s0i65oLfaiF8Ug06Mbl7HX/hi9ax2Ic4Wsc/F8\numhDhwLW6ykyx3DatwoAiXvvMSnmCuVhG4igi7HauPoWSrYoxzmK2IWRZB/d+4vF8gwVPIwIoek6\nPA6TcgEQq2bQC+77qDT/wz/49F0RqmNUYh4myd11/fbdUNSR1u2TbBL1yBmfLiS1Lmrb1e0wduF3\nQ/kZD7M0i3n/QYzfIgxsdpbOc1aN3iBEJ1gqJkv3019ciK5poevZ6lgUPSaNd1Us1oxFfzuAdTbQ\nhyt7MZ/4iQoW28rbHZsvVrkr2j0Ro/ujvfxDHhToLA+amaNTOZ/MkiF34DF20Hww6jmgjhRD8NAN\n0O9BSCmc8hZogIRhmqiKuUwUZIm1kQsd+5ipxEq22+7yAp0JKEKgGAM3HdfJ+vgVlwV78jgXwQPQ\nfvducZLQEEkYJIfgdIjoD0rMcFl2JXtzTd/9dgu9uPhTNaLyDtiKgXOeRoAYCAjGZuCRuFRClrws\nQ4peCcNLsOmQTZTzrPOaN0QQI9jqnmbPuCg5ae7Ag/NqqQpE6gbjlJ7xiSn2rekr0X1gd39z2x+D\nllk5ZQyBQRx9V1VIN8fUZYUwLJPnp2eXH9NYvO6zgNqSQdwB9iH6sP9td/l5iZ6FDt9fW3ZMmZeI\naY9jtY/6R2K5zigSjNBXYTyG3nXlScqij3FYplQdh9i219VbXwmRQItEEtKlxB3cfzjKEr/53a74\nvfiK3eHx9B/8yaa3as/9CWoN/pSLl8A2Fo+J0zhPkczq2HAQmOs4GMVTeTrc561HrtM8K16d//JU\nLHLJTGIq/kZLFaJoyZKSS+8wmXkZ/SgEdyIZy1l3chHHB933zL4ldTfG7/z42NxPq9NH3DskhiEq\n242D4FJnelKyhV4riIMJgA/HrnL9ww1D1588zy5eZl1FSVbaJsSJLtmj+++ClKwopzfNtrlOvXVy\nh4b3u9i63VEpN6th6La7+zKeedIWJMhp0pum++5NMZVnT4qsXLJiBtC5ujRHyebFnC0Wcuy/b3p1\nDya2x15YPlsvmQc+2k19k78CrDVsEn+vnNfwXmGbkGsk6uPVxusg5txE8D6w4KcZE370Yxi56/OV\npyVxzjmDFs37G4OIBLA5wN9+1SVZIAGDx2SaLldrAcX9223TOueS+WRt2g+USSLAgAmbH7ugtBxs\ndF3cvRUnSmgl3cD7A/lOkVHGlT2wQBFTii5yJMkwhuhCxFYtFxNIiRzpQoXYoo4UPeNCClwhf9jU\nhsTORdq6j189Augjdce7MJ2qgJZp5gIpkDL6dEyAYZrMdxlsmbuvfKp4Npt52VFReNYDSUGA3LY7\nTxuHYaEkMC26ru+aeMaAM4/YOVaDyHE91y1LuWBem14P+PDht1XZxuVT4Qk5YsSx5zYt1o2rHAqY\ncPS82VqAxPcROgIdIQOAkIo4L7NJot5dSWfZVdO1HV6sdTohmnbAkt53GZskkj0qV2+Ohy//ZsNi\nfvl49XDT3V6NJZZlMgEq9x9uUOSE3CMRkjXIkF79wXnz3t/2t2LwU2ZZwrJVrDcbzmxUs8n01Nus\nDUnA6GIXyjCbzFP5EZN1we9tt/ovc/v/GcQXo1/3CXOC84ALbUT8ASqGpiwwH1kcuh/eWRpirgp1\nMGZ/uv9bOnzZa5x+Nlnpjx7d/OUPIqFAevSpDp2ZJQxhVwMfIyqlHNTjnZDsNMmbZ7h9p2zHw4Bt\nzZtNn20pLBJ9PqkmpqlDyoXx0I4QapCE+0NFkCB458flbFKUF8LDcqqH4zb23HqjWKaQ+5YSzcdh\naPpt5NgPYTZZt3e18/wu3vGkGAb35PIE2gjokSM5mJaLMd1EGhMRZzN68pFMJWeTuLMNXIzzs5n6\nkBsPqzw7fZR9d48BBjNEphOMIYAlDnIiAXmyygZ20t5Za2O469kdf4qSINtVx/arh2wuF6fBL2Mr\n4viG3765FgolZ4p8uP9wP9Lw7NMJz5P7KwMuXT45AQJrun0c/JtaMswmfD2bNY3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hWxXm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8aJB99ilvmncWlQnCJ0bqXjIDD0hZL8YOkNgHmBlTb/r2/e62qrxUUJxOybzcbz+cH8UvBsPW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xpiNe7iZC+epLRun14K5vsT14IyK+aWllIuHwhkPdwSFSFqjMGOrjsmW05ZZnydHaHbFRUC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JJNEVKDwAmUHAuJvH4+s8u1xUwrhWqcGu8xNEfNKUYCB71Qxdv1p1hQ0j5nhYa21asNQb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\nra3e6Wo6qVYcS0BUsZ4Gbn98CyahSna7CjmKVdlFY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+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=299x299 at 0x7FB7543A71D0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 20min 1s, sys: 45.5 s, total: 20min 46s\n",
+      "Wall time: 3min 4s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "img = style_transfer(content_image=content_image,\n",
+    "                     style_image=style_image,\n",
+    "                     content_layer_ids=content_layer_ids,\n",
+    "                     style_layer_ids=style_layer_ids,\n",
+    "                     weight_content=1.5,\n",
+    "                     weight_style=10.0,\n",
+    "                     weight_denoise=0.3,\n",
+    "                     num_iterations=60,\n",
+    "                     step_size=10.0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed the basic idea of using neural networks for combining the content and style of two images. The results were unfortunately not as pretty as some of the systems that are commercially available, such as [DeepArt](http://www.deepart.io) which was developed by some of the pioneers in these techniques. The reason is unclear. Perhaps we simply need more computational power so we can perform more optimization iterations with smaller step-sizes and for higher-resolution images. Or perhaps we need to use a more sophisticated optimization method. The exercises below give suggestions that may improve the quality and you are encouraged to try them."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook and the other files before making any changes.\n",
+    "\n",
+    "Exercises:\n",
+    "\n",
+    "* Try using other images. Several style-images are included with these tutorials. You can also try using your own images.\n",
+    "* Try more optimization iterations (e.g. 1000-5000) and smaller step-sizes (e.g. 1.0-3.0). Does it improve the quality?\n",
+    "* Change the weights for the style, content and denoising.\n",
+    "* Try and start the optimization from either the content- or style-image, or perhaps an average of the two. You can also mix in a little noise.\n",
+    "* Try changing the resolution of both the style- and content-images. You can use the `max_size` argument for the `load_image()` function to resize the images. How does it affect the result?\n",
+    "* Try using other layers in the VGG-16 model.\n",
+    "* Modify the source-code so it saves the images e.g. every 10 iterations of the optimization.\n",
+    "* Use constant weights throughout the optimization. Does it affect the result?\n",
+    "* Use different weights for the style-layers. Also try and automatically adjust these weights like the other loss-weights.\n",
+    "* Use the ADAM optimizer from TensorFlow instead of basic gradient descent.\n",
+    "* Use the L-BFGS optimizer. This is not currently implemented in TensorFlow. Can you get the one from SciPy working with the style-transfer algorithm? Does it improve the result?\n",
+    "* Use other pre-trained neural networks, e.g. the Inception 5h model we used in Tutorial #14, or the VGG-19 model that you can find on the internet.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python [default]",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index 7186ef3..f86a0da 100644
--- a/README.md
+++ b/README.md
@@ -41,6 +41,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 14. DeepDream ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
 
+15. Style Transfer ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/images/15_style_transfer_flowchart.png b/images/15_style_transfer_flowchart.png
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+         style="font-size:70px">Neural Network</tspan></text>
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diff --git a/vgg16.py b/vgg16.py
new file mode 100644
index 0000000..b10c862
--- /dev/null
+++ b/vgg16.py
@@ -0,0 +1,186 @@
+########################################################################
+#
+# The pre-trained VGG16 Model for TensorFlow.
+#
+# This model seems to produce better-looking images in Style Transfer
+# than the Inception 5h model that otherwise works well for DeepDream.
+#
+# See the Python Notebook for Tutorial #15 for an example usage.
+#
+# Implemented in Python 3.5 with TensorFlow v0.11.0rc0
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2016 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import numpy as np
+import tensorflow as tf
+import download
+import os
+
+########################################################################
+# Various directories and file-names.
+
+# The pre-trained VGG16 model is taken from this tutorial:
+# https://github.com/pkmital/CADL/blob/master/session-4/libs/vgg16.py
+
+# The class-names are available in the following URL:
+# https://s3.amazonaws.com/cadl/models/synset.txt
+
+# Internet URL for the file with the VGG16 model.
+# Note that this might change in the future and will need to be updated.
+data_url = "https://s3.amazonaws.com/cadl/models/vgg16.tfmodel"
+
+# Directory to store the downloaded data.
+data_dir = "vgg16/"
+
+# File containing the TensorFlow graph definition. (Downloaded)
+path_graph_def = "vgg16.tfmodel"
+
+########################################################################
+
+
+def maybe_download():
+    """
+    Download the VGG16 model from the internet if it does not already
+    exist in the data_dir. WARNING! The file is about 550 MB.
+    """
+
+    print("Downloading VGG16 Model ...")
+
+    # The file on the internet is not stored in a compressed format.
+    # This function should not extract the file when it does not have
+    # a relevant filename-extensions such as .zip or .tar.gz
+    download.maybe_download_and_extract(url=data_url, download_dir=data_dir)
+
+
+########################################################################
+
+
+class VGG16:
+    """
+    The VGG16 model is a Deep Neural Network which has already been
+    trained for classifying images into 1000 different categories.
+
+    When you create a new instance of this class, the VGG16 model
+    will be loaded and can be used immediately without training.
+    """
+
+    # Name of the tensor for feeding the input image.
+    tensor_name_input_image = "images:0"
+
+    # Names of the tensors for the dropout random-values..
+    tensor_name_dropout = 'dropout/random_uniform:0'
+    tensor_name_dropout1 = 'dropout_1/random_uniform:0'
+
+    # Names for the convolutional layers in the model for use in Style Transfer.
+    layer_names = ['conv1_1/conv1_1', 'conv1_2/conv1_2',
+                   'conv2_1/conv2_1', 'conv2_2/conv2_2',
+                   'conv3_1/conv3_1', 'conv3_2/conv3_2', 'conv3_3/conv3_3',
+                   'conv4_1/conv4_1', 'conv4_2/conv4_2', 'conv4_3/conv4_3',
+                   'conv5_1/conv5_1', 'conv5_2/conv5_2', 'conv5_3/conv5_3']
+
+    def __init__(self):
+        # Now load the model from file. The way TensorFlow
+        # does this is confusing and requires several steps.
+
+        # Create a new TensorFlow computational graph.
+        self.graph = tf.Graph()
+
+        # Set the new graph as the default.
+        with self.graph.as_default():
+
+            # TensorFlow graphs are saved to disk as so-called Protocol Buffers
+            # aka. proto-bufs which is a file-format that works on multiple
+            # platforms. In this case it is saved as a binary file.
+
+            # Open the graph-def file for binary reading.
+            path = os.path.join(data_dir, path_graph_def)
+            with tf.gfile.FastGFile(path, 'rb') as file:
+                # The graph-def is a saved copy of a TensorFlow graph.
+                # First we need to create an empty graph-def.
+                graph_def = tf.GraphDef()
+
+                # Then we load the proto-buf file into the graph-def.
+                graph_def.ParseFromString(file.read())
+
+                # Finally we import the graph-def to the default TensorFlow graph.
+                tf.import_graph_def(graph_def, name='')
+
+                # Now self.graph holds the VGG16 model from the proto-buf file.
+
+            # Get a reference to the tensor for inputting images to the graph.
+            self.input = self.graph.get_tensor_by_name(self.tensor_name_input_image)
+
+            # Get references to the tensors for the commonly used layers.
+            self.layer_tensors = [self.graph.get_tensor_by_name(name + ":0") for name in self.layer_names]
+
+    def get_layer_tensors(self, layer_ids):
+        """
+        Return a list of references to the tensors for the layers with the given id's.
+        """
+
+        return [self.layer_tensors[idx] for idx in layer_ids]
+
+    def get_layer_names(self, layer_ids):
+        """
+        Return a list of names for the layers with the given id's.
+        """
+
+        return [self.layer_names[idx] for idx in layer_ids]
+
+    def get_all_layer_names(self, startswith=None):
+        """
+        Return a list of all the layers (operations) in the graph.
+        The list can be filtered for names that start with the given string.
+        """
+
+        # Get a list of the names for all layers (operations) in the graph.
+        names = [op.name for op in self.graph.get_operations()]
+
+        # Filter the list of names so we only get those starting with
+        # the given string.
+        if startswith is not None:
+            names = [name for name in names if name.startswith(startswith)]
+
+        return names
+
+    def create_feed_dict(self, image):
+        """
+        Create and return a feed-dict with an image.
+
+        :param image:
+            The input image is a 3-dim array which is already decoded.
+            The pixels MUST be values between 0 and 255 (float or int).
+
+        :return:
+            Dict for feeding to the graph in TensorFlow.
+        """
+
+        # Expand 3-dim array to 4-dim by prepending an 'empty' dimension.
+        # This is because we are only feeding a single image, but the
+        # VGG16 model was built to take multiple images as input.
+        image = np.expand_dims(image, axis=0)
+
+        # In the original code using this VGG16 model, the random values
+        # for the dropout are fixed to 1.0.
+        # Experiments suggest that it does not seem to matter for
+        # Style Transfer, but we do it anyway.
+        dropout_fix = 1.0
+
+        # Create feed-dict for inputting data to TensorFlow.
+        feed_dict = {self.tensor_name_input_image: image,
+                     self.tensor_name_dropout: [[dropout_fix]],
+                     self.tensor_name_dropout1: [[dropout_fix]]}
+
+        return feed_dict
+
+########################################################################

From 2b151ad4dc6cc7f109ba2ca25432cf104eaa14bc Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Dec 2016 14:43:01 +0100
Subject: [PATCH 02/61] Fixed problem with GPU

---
 vgg16.py | 24 ++++++++++++++----------
 1 file changed, 14 insertions(+), 10 deletions(-)

diff --git a/vgg16.py b/vgg16.py
index b10c862..ef3d9a6 100644
--- a/vgg16.py
+++ b/vgg16.py
@@ -170,16 +170,20 @@ def create_feed_dict(self, image):
         # VGG16 model was built to take multiple images as input.
         image = np.expand_dims(image, axis=0)
 
-        # In the original code using this VGG16 model, the random values
-        # for the dropout are fixed to 1.0.
-        # Experiments suggest that it does not seem to matter for
-        # Style Transfer, but we do it anyway.
-        dropout_fix = 1.0
-
-        # Create feed-dict for inputting data to TensorFlow.
-        feed_dict = {self.tensor_name_input_image: image,
-                     self.tensor_name_dropout: [[dropout_fix]],
-                     self.tensor_name_dropout1: [[dropout_fix]]}
+        if False:
+            # In the original code using this VGG16 model, the random values
+            # for the dropout are fixed to 1.0.
+            # Experiments suggest that it does not seem to matter for
+            # Style Transfer, and this causes an error with a GPU.
+            dropout_fix = 1.0
+
+            # Create feed-dict for inputting data to TensorFlow.
+            feed_dict = {self.tensor_name_input_image: image,
+                         self.tensor_name_dropout: [[dropout_fix]],
+                         self.tensor_name_dropout1: [[dropout_fix]]}
+        else:
+            # Create feed-dict for inputting data to TensorFlow.
+            feed_dict = {self.tensor_name_input_image: image}
 
         return feed_dict
 

From ff7a9a3429404e6c5289c99e5b8d349f491feee6 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Dec 2016 15:51:23 +0100
Subject: [PATCH 03/61] Updated installation procedure

---
 README.md | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index f86a0da..d44a51e 100644
--- a/README.md
+++ b/README.md
@@ -105,16 +105,15 @@ NumPy and other dependencies:
 
     conda install scikit-learn
 
-You may also need to install Jupyter Notebook and matplotlib:
+You may also need to install other dependencies, such as:
 
-    conda install jupyter matplotlib
+    conda install jupyter matplotlib scipy pillow
 
-Now you have to install TensorFlow. This procedure might change in the future. At the time of this writing,
-the most recent TensorFlow version was 0.10.0. It comes in different builds depending on your needs.
-I need the Python 3.5 build for a Linux PC with only a CPU (no GPU). So I look at the [list of builds](https://www.tensorflow.org/versions/master/get_started/os_setup.html)
-and find the appropriate link which in my case is:
- 
-    pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl
+Now you have to install TensorFlow. It is now possible to install the CPU-version of TensorFlow
+directly using pip. We also need the [PrettyTensor](https://github.com/google/prettytensor)
+add-on package so we install that as well:
+
+    pip install tensorflow prettytensor
 
 It is much more complicated to install the GPU-version because you also need various NVIDIA drivers.
 That is not described here.

From e51cd7b926536d96ce3cd4e89292957b6992434f Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Tue, 20 Dec 2016 11:29:21 +0100
Subject: [PATCH 04/61] Fixed warnings, PrettyTensor API changes, etc.

---
 01_Simple_Linear_Model.ipynb          |   68 +-
 02_Convolutional_Neural_Network.ipynb |  252 +++---
 03_PrettyTensor.ipynb                 |  335 +++----
 04_Save_Restore.ipynb                 |  342 +++----
 05_Ensemble_Learning.ipynb            |  912 ++++++++++---------
 06_CIFAR-10.ipynb                     |  221 +++--
 08_Transfer_Learning.ipynb            |  413 +++++----
 09_Video_Data.ipynb                   |  247 +++---
 12_Adversarial_Noise_MNIST.ipynb      | 1179 +++++++++++++------------
 9 files changed, 2095 insertions(+), 1874 deletions(-)

diff --git a/01_Simple_Linear_Model.ipynb b/01_Simple_Linear_Model.ipynb
index 767e2bb..d6dacad 100644
--- a/01_Simple_Linear_Model.ipynb
+++ b/01_Simple_Linear_Model.ipynb
@@ -61,7 +61,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.11.0rc0'"
+       "'0.12.0-rc1'"
       ]
      },
      "execution_count": 2,
@@ -326,9 +326,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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WY+smesMF4TrG4zF6vR4vxCiLmBJNptMpXC4XmwykUimkUikkEgkWOLfbvdArZGH1mEwm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\nAABJRU5ErkJggg==\n",
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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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\nvxUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc3b8c2f98>"
+       "<matplotlib.figure.Figure at 0x7f3765ecd390>"
       ]
      },
      "metadata": {},
@@ -704,11 +704,11 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -996,9 +996,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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cLiQSCTx48AAfffQRstksYrEYfD6f1LIJl0ZRFHi9XoTDYaRSKQBnnuL53rbv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Ix8LvkkV6Z8STxuo0m00Wz0ajwW4Im82GaDSK+/fv47333sPa2hrC4TDXLt2l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\nAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc394e27f0>"
+       "<matplotlib.figure.Figure at 0x7f3763c277b8>"
       ]
      },
      "metadata": {},
@@ -1057,9 +1057,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ctzZFUTgmfnp6yuGr6XQKu90Op9MJp9M5NwN2MBig0+mwABuf1ziJql6vA5jZYyQSwcbG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IyK+lHe81H/wpFjvvPwmO8D3gH+G8PRwKrtsCUg8byXYrim8r8ZGsAfAz5mWdav6wPUe4nAX/di\nd3XMi1vWrwJ/DvizwO8wDKn+GwwXsDl0XXwNEGM4wvkxhoEUR5nj/ReuvwP4LwzfxzcYGtIftyzr\n2Hwx4dm8RPuE4Xrf54D/G3iN4cPwdxl+fmKfwlO8RPvsMXSbfoahjX4L8G2HS2HAlbLPv8TQC/Ib\nDIX6U4evdWKuXTNspdQ9hoZxx7KsjYu+HkGwI/YpjDNin+9xHWvbfgz4l9f9gxfGFrFPYZwR+zzk\n2s08BUEQBOFFuY4zT0EQBEF4IUQ8BUEQBOGUiHgKgiAIwikR8RQEQRCEUyLiKQiCIAinRMRTEARB\nEE6JiKcgCIIgnBIRT0EQBEE4JSKegiAIgnBK/n+uOde83IW2SwAAAABJRU5ErkJggg==\n",
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pyExyyUy3NkVROCZ+dHTE4avJZAK73Q6n0wmn0zkzA7bf76PdbrMAG5/XOImqVqsBmNpj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vAAAU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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc50bcbba8>"
+       "<matplotlib.figure.Figure at 0x7f3763336390>"
       ]
      },
      "metadata": {},
@@ -1092,9 +1092,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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u2daehCMp8ZRPzxlg10PkXDR3liG0BaTp1P7f+MCSALIUGZYI422M724K7u9d\nSX8p1ru/1/6fwZgKY9bYDXjRWd22k4CuAU6SxgCHGfHsHO+bp3B53VJZw9DW/j/9FHEIfpUQe4Ik\n8VksWgOsdU1d68bIujqjM8Btz2lrhBWWES1wY0edgn5sWMMvx9vdk+4saMc0ns3ayYNXVxXLZYYx\nC2y069LNAou5h007q2aNgPvAfYLgiIODPg8fDnjyJOHJk4BPPvE4Pm6xcIQaN9vbGd9up4JzBpZL\ns6ll1rXYGAFXHnP3wSXFPja8f41u73YWOGbxxUVbE+4enrNNvGyJcW4GRHcymduK3RjRwaAdK+uw\ncNdQSA+UoBaKwPiEWqBcb9lmpoPcFHxdZdFFwo585z7j+9DtX52C/j7g3gZU9/+g/WC+b9NGx8dw\nPK45Op9xdP6Sw+l/o3r5F6q//pXqr3/BlCWeMbb5YDDYjMUSBwdwYCOe+uhLlif/nsuT/8DTxUP+\n+S+Cf/5nO+TKzncXHB7aawkC6MUCr6/oDXxIIutiuWHTNzd2TKWLgJ3L5HoYplP73tMJZCmyXyKN\nQKK2PKdu7evvVX4N1j+k3Na4uejXrTl2I3biarMZnpeTJJrx2DAM1sSzc1T2FxAvNru86PUsPr6P\nDBL8ShD7wWYsJTgD3I2AncF1eamuQbZG2BrgNgJ28rFhDb8O7y6h0o31hbah4PzcRkVpWpGm644B\nLmgjXmd8g846Bp4Aj/H9Iw4PPR4/9vnqK8Xnn9tWxZOT7TNiuxFw91onE/va7UN3U9dss4PYREbQ\nRmFd0s7Hgvevwbrb1bBet1N85/Pt32nO1iBJLC5u+A60hGXXp+3Ib10nyPPeHgG7Ht2qEuApaqmo\nCKD2UbUgqDrj7LpHNtEaYJcVc5//fer2O21D2vWgYDs15byiONSM/RUH9YrRdE508Q36+V9ZPv8L\n1elrqtmUSmsC3ycKQ1QY2ki1mdBRHNxnPX7AevSA6+gznqcPePEq5ttbwcWFnaZkPR2B50myTG4m\nI93cQIxPL0zoA76o8WSJp5QldIX2ZJaqqijznLIskXWNLwS+lMiiQDhmdLREFgkKhed5G9A+pjTV\nrnwf1m9TVNfF5VqrbcpJU5Yl1sDu9nq6fs8I6ANjwnDI0VHE48eSz3qaw1VKkE5hfdOSLvp9S4XN\nc2w6sfXO3UjKqyuYzyuyLMMSflzNubsL2euQUiGEh+97+L4kCMQmneY2j7uANfw0vLubcl23J1Yt\nFobFwuqTLGKYAAAgAElEQVRjmhryvGqcIBfx9mjvv2WhCxGhVGJn+4Zjer0jkiTh5MTjyy8VX3wh\n+OQTwXhsN+Tue2fZdvq7W8vrziZvyVai4Vy2qWe3b99FvH+JbruDUCYT05Aqc4zJWS5rwtCuohDk\nuSDPJUJY/VLK8i2qyqMsPUDheYLRSHB0CF88MXz1leHJJxXHvYwjkzFeloheguzHiDhqAlyDkoYg\nkqjQpjxMGGGiBBMm5CJiVfjM5mKTLneGfPfgjveB9XthQe+mnZ1HOhw2bOe4pp8u6KcX9GZn1Odf\no59/zfwvf6Gaz9HzObquSeIYbzAgHA4Rh4eIoyM4OqIYfcJs+Dm3o8851Q94Ojng2STiu0vD5aVt\nNdHaUFWqAb89JefmVpCEPoMBDPGIRUkkMjyp2oNnk4Qqy8jKklRrPK2JpUTVNdKxOBYLRLRA5hJF\ntFVucKB9jEoKb8d6V0HdxtidzTyfG7Ksbgxwho04nQFWnRUDA+CAKLIG+MkTxeOg4uDVmuBmZj0p\nl8NyjI2isN6xtieZOaZma4BL8jzDGGeAnQMAzvgKoZoNwsPzFEFgDfCuot4VrOHH8d6kBJvZNc4A\nz+c0xrdivdZUlaaqDC27GZzhdVGvlAm+PyQIBoxGfU5OepycJDx86PHkieTxY8HDh2wM8O7M8e6g\njW4asTtO2AYHYpPOBLYM8Ns25ruC98/RbWeA5/OuAZ6h9RzPK/E8jedVaC2pKkVVWcdWCB8hfIyJ\nqOuIuo4JQxiPJeOx5NEjwRefG/7hq5ovHhYk+YykmBAtM0R0BP4RYhAhhUHaAyhRocCLfIhCTORG\nW/YoZMCq8JjNBavV9jnfDt/3ifU7N8BdSrdTADeP9ejITrU66tdEp3OixRnB7bcszr5m8d1fWf7l\nL+i6tssYRBAQDQaIkxNrfJtu+2L0GbPBV5z3/8Dz+SFPV5K/vpC8em2YTGpWqwqt6+YhkeS5YrWy\nEfD1DfT7PqMjjzERiDWeXGJ2I+DVinWastAav6pQUhK5wR3NUyfiBaIIUegtz+ljSFP9kLwN691/\nu5rObgSstW6mHLkI2G3ILg3pyDgDYEwUDTk+juzmKzSHN2vCrDHAjknjdoGigE4E3Hrntga5WLgI\neIGNfp0DAG7KUtcA2wh4+7D5XS/5Y8cafhxvaNPOsE24WSysPqZpgTEVFm+BNcAO6wDX9y3lAN8/\nIIoOGI0iHj0SfP654PFjwaNH8OiR3UccLi6t6LpQuqdsOazcEYPOaHSZ2+6zdCciuW3gLuL9c3W7\nGwFrnaH1lLq+BAqEKLB6pjDGOVohFusQmwGpAcVoJDk+pjHAhi8+r/mHrzRf3i8Q5zPE2bk9HekA\njN+DAYjmYkVdIyIBkY30TBRTRwlV1CMXilUumM7aCW3ubIjumQPvC+tfZYC/72J2RxA6z9Lz2kL6\nqFcxMgsGkwXx7YT6xTekL75h+fxbVi+es7y9YVWWBIAvBLGUxAcHeF9+Cb//A1n/iNQbknpDrnjA\naXrC67zHq1ufs0vD9Y1hOtWbObLGGLRWlKXZmkO8WAhubiGMBEIa7gcRIhiQHGiIEwQC1mv0ek1W\nlizrGt8YZF0jpSSqKrwsw1utYLVElgMk+qNLTf1UrB3eXfJKNy1oD1uoKUtDVVXUte3DbVnPzgBL\nulOPpAwQIib0fQZhzXGy5kAvifQCs5qTz+eY9Zq66S/x8hyVZZgsp1qX5KlNe7oDHhYLzXpdNM9G\n1/A64+8MMEgpUMquLinjY2TCOvk1eDuHxxi7Kd8202Fvb60BzrIS23Pt8FZ073m7KccI0UPKCKV8\ngsAjjjunoHXIOEK0xnR7vGnbctQtf83n7dAQz2tLCrAd6XQ/48eK97vQ7bKssANuNMZ0dctvljW6\nnhcShiFBEBHHMUkSkSQex2PNp0drPj0u+XyQ8Wm+ZnS6JpgvNr1KJs+hF2EOxlAcIHQFujkdqSo3\ns4zXIma5CliuJReXkttJO104iuyrI3TB+8X6V0fAb7uwrtHtThhxQzYODuAgLhktb0gmr/GnL1g9\n+4bl029YPX9KfnPDejYjA8ZC0JOSsRCER0eEX32F+E//ibU84moecjmPuEiHnC3HnGc+r68NFxc1\nNzc187kd7K+1VXStPaA1wC41dnNjry/Pgfsh8YMRR0cBIrGd/GKxoEpT8qJgaQz2WGeQdY3WmijL\nrDfWXyGKHGk+PgMMP4717tewnZ5qo5K6Mb4lxjiveNcAu/SzhxAeUgZIGRD5kkFQchCUjIo5XjWn\nXs3JFwt0VVE1u3BUFIR5jlmvqdIeeaqbKVia5bJkuSwpy6IZ8l/TRmLd2vObG3AX17f938ckvxTv\n7qjHNN2MZmcyMSwWmqJwGY+34a2wBjjBGuAYKX2Uktsn8HROrHM1XWf4l8t2ilL36MtuLa97hKVL\nOTqCnvucXew/drzfjW53Mxy2rsumpz8BegRByGAQMhwGHB0F3Lvnc+9ewP1BzqNowcNwwoNgysly\nSu/bKdSztokYYDRC3LtvG/2LAsqGVu2K98Mh62XM9czncik4PbWOYJq25bAsa6e0dT/3+8D6b5KC\n3r24LlDdB9j1ch0cwHFY0ptck1x8i/fsT5TffsPsm6+5efaMUmvKqqIC+kIQCMFIKbyjI8RXv0f8\n9/8D6fqAq+eSZ98JTheKi5ni8kZxfgEXFzW3t5rFQmOM9cTAUNd2frCU7XF4i4W91iyzSplEEUcP\nA/TRAJX0wIBYLtGrFVlVsTTG+uvGsrFNVSHznGC1QqxWCFMgTf3RKaiTH8K663S5r7sEjW0vuUJr\nZ3i7ETA4w+uUVggbAXteSOQpBv6aw2DFSC+oqjllOqNaLimMoWxCMFGWeFmGSddUaUmW6qb/ULNa\nlU37i0s7a9qNwg7gALH1Ge+a8XXyS/CuqrbE4Ayhm5e/XmvyvFvz7xpgFx25DToBQoQIkFJspQvd\nec8u+q3rdqiGqzdPJu2xpo7p6q7VpacdwcoZ4W50142E7wLef3vd7maWnHMlsYTKATBsDHDAyUnA\nZ59JvvxS8MUXgk/7KferOffLc0arM7ybC7ybC5hP2rpCGNoa5nxuDbDrgcrztq81SUhXAdfzgOev\n2DLArqM0z9s6sPvc7wvrd5KCdkSG7oMrBCShpidzemVOUt6grl9RvXxK+e3XLF+/Zn5zwzRNt9Vx\nMMAfj/HGY1bHXzKtHjJ9OeZ0NeTVK3h5BpeXhutruL423NxUzOcZWZZ1HoKquS4D2IcjTX2mUxtd\nLRbufGhBkgiiRBL2YHztM0g9Bki0lJRCkLnPTvNoaY2fZcQuBe3nSE9v6gW76+9VfgrW3f9zytnt\nDXQtH1mmm8jTGd23pX/dU2CNsDF2LKSpDbLWeHWJqgvKurQMda03XcNSCGo/oE766GTEYhJzOfF5\n9cpwfV02px454pUbcUjnfdth/0L4KKXwffFWUsauUf4YsIZfh7fLLtkT6AzzuWa1suSrsszQ2g1W\ncbO+M+w9dwzodrM2xs4Kz/OaNPVYLhWzmeL2Vm4IXmG4fciCG+Xujvl2q0uscfVLF1U3XMtNilXr\n7Rrgx4z331a3Xf1f2LnMXh+lbPeJW1GUkCQJcRxzOJQcjypORiUPD3I+DVI+WafcKycclJeMywuS\nRdM4fnHRnh8KiH6/meTRAN5cmJGKXHtkqU9WhLy+8Hj+UvLtMxsBz+ctwc5lbFzr0w9lu94F1u98\ngJqUrXfZCyt69YJkNSNcv6Y6/Y7su6dkT58ym82YpykLrN/rY0vy4eEh3hdfIL74gtvhH/j69h5/\n/b89LpfWk7m9bdNbNsVVkqYpVeWmKXXTiwV2wH5ImiYIkZBlajO71I0oBPtwPX4u+XThkfgRte9T\nGUOuNdoY6uavCa2J85zhcmkj4CRDKr3lOf09K+fPFUfacJ6xS/e7XsvFwuwYYNds6fo+3zTCzvgC\n6MpQVxpTVRit0XW96dbdVI+lQiQ96rFtUZu+TDi9Cvj2W9NMX0qx84bXzfu7wa7uvd1JOxFShg0B\n6/sN8K6C3iX5KXivVhXrdUGe2xOntHYHbXRffdpsRN28lmgdkucRdV0yn4fc3gZcXoaA5Pq6HbDR\nnZzkoppuX+ps1hwS0ETPDrtuVN2doFVVb2fB3mW8fxxrZ4Ct7vp+TBz7xHGPOBbEsSSKBCcnPvfu\nhdy7F3AY5Rx4KQfeinF1wzg/Z/T8gkE5ITYrvHoJaUOyvL62lt5Nb3JjtVw/qfOk4ohVHnG7Cpjk\nPk9fSL59Jvn6r3Bxaa/XYQltK1o32n9fWL8XA+xOOOr7Fb16SbK8JJy8pDx9zvq7p8yfPmVeVcyq\nijlWFRXWEEcHB6jf/Q7+6Z+4mXzJX05P+L/+1eNm2ebvbbrLNG0tFXW9QusZVrG7m7r9WmufNK3J\nc4/ZLNq0lbg5zm5ovz6XJAufR15IHQSUWuPOy3FJNFXXjPIc3RzTIbwcGdUf5WD2H5NdxqRT0u65\nv/ZIwN0IGLZTVNsRsDFu+pSNhuqq8XQbA1was4ljJaCkhDjBjA8pDu4xrSWvbxRPn8JyWbBarbAG\n2G34XRKQpDXAMUK0Brh7ok93Ks7HEgn9XPkpeM/nNG1HOUWRYkyKnXzmDK9bPrvGF3K0DjGmpCwr\nZjPN7a2g3/c3Bz907/nuvdfaGt7ra+uoDwbtaVZuOlM3AnbjcN10pj3erfw03Ras14KqEtgZ3TG9\nnmQ4VAyH9v4Ph4LPPxd8+aVNNx+qjGG+YlDcEJ0/x3v2Nd7zr1GLKUoapDBQZC2RIM/b0zKiqO0n\nvb21vWiNl5WmIdfzgFc3Hs9eCL59Kvj6m3b6lhBtzdcx4l2K/X1i/c4MsLtYT2oSr2IUVIzNhGj6\nCjF7SnH2V7KXz1lfX7FarTaxqgT8ICAJAkZBgBg/YNX/jCL5Ha+u7/N80ufZc8N0VTW9vTVZZtsa\n0rRoIt/rZqW0xX/ZWUHjLdtNvywlRSHJc8l8rpjPJYuFJE1tTd8YgwF0s9G7eT0aKOqaStuITJQl\nQmukqO+MYsKbKSqXnmrJboY0pVnu6EE3darb+9tNAbu0sGm+X2OMxugaUxYb78uUJbqubfOClPhC\nIKVPUYakq4jbacDltOL6NmMyKSiKJWXpIi/Yrvs6J8AdfRg2tWePMBSbOpEj/zjl7BJT7gLuPw/v\nmjyvKMucuu6ecNV1ZZ0T5jCvaDkAmrq2z0SWhUynNWFoWK0MxtRWN02NEAYhaqQ02MM6BMYIplPJ\ndCqZzSRKtTOh3dCN3c3VRcXAHm9+GGuXaXCpfHtvBb6vKEu4d09x/77HvXuKYU8zSDTDRPPpw4on\nhyVPkpJhdUuiL4jXl3jpK8guoZhCsWjf2HlE7Qku7cPWkA3MfE4dJtQDgRYRizzkdu5xcSm5vIKr\naxskZ5nZfBal7IdzRrfbpva+sH6nEbCU4EvNQKYcq5RRdoa6+Ibi6b+Qf/dnlqenrOZzMlz3F8RC\n0E8SRqMRB+Mx8+GnXItHzOcPeTodcTqJuJnULNKCutbUtaYs1xTFAjvUfYo9zs4daecMsKsqu7Nl\nwW6+ZjOBxRiPug4QIsDzApQwiFpDWWGqirpJd1ad33Y+O3Vt+9BoRmU2YLk6yscuLp3TJWW4+lDX\n+K7XhqrSDTO9S4LqTsDqGmBNexxdBbqE3CqeyVNMUWCa4o2nFKFSGBkwXypuTwWvlOHsbM10uiLP\nl1TVDK1X2I2/y7z12SYBuT7UAN9XGwPcbdp3HrSLDj72zbgrPw9vR8rZNb7O+XJOlmOkd2dAC5y+\n2tOsrGENQwPohmlrlxAVQmiEUAhhcU1TjzT1yTKf4dAaCEfe2iUTuaEcUrYDGvZ4vx1rZ/9ce1e/\n78aOyiaaFHz+ueSLLwRffAE9VZHIjERlHPhLDs2S0dWSaHmNP71ATi5hPrUPjpsb2h1V5uoEzjK6\nNGXnfNGqX1IUkkJHzDOPyVxxc2Mz1IuFaZx/C5oQYsPTcSS8bn//+8L6nRjgrkfpC01frTlSU4bV\nOdnlt2R/+v9Y//nfWGUZqyzbVOI8WgM8PD5m/OABs9EnXPMJ380f8nQacjqFm0lNuu4OyZ9R1zfU\n9TX2KLtbYEKTJKbdYANcarHd7KGuA4zxqesArRNAWgMsa6SxPWXOALso2MVrmiZCdk3gnc9/F4zv\nbmpmdxDC9mYMWeYOQGjnLLsI14ozwE52TiuqC5uSSldQ2Mntpq4RjQEOggAtA1Yrj7MzybOq5uws\nYzabkmUTjFljjDvmTtA6aG3dtzXAIVL6eJ4gDMXWUPm3KeldkF+Od0FLuOqy3h3uzgA7rF22ysO5\nvM4ApylI6QywK2UUCOH+piVXGuOjddSULzzKUmyMq2tfcp/BtdO4aM4NwbvLeP8Y1o5J7oYrWYdG\nYoxASsk//IPgH//RrqgsCcuUsFwSzG8IFtcEl9fI2yvk9SXi6tKmG90fU6r16Fwd06UvHGvK5b+X\nS8xiSTUqyQtBWscsMsG0mfFguUHWAJelQUq5eQ6cAf4xZ+tdyTszwC6NE4mcOL2mt35JdPlXstfP\nyE9fsby8JMWqo1O3GFBCEPdGqJNPqT//PTM+53V2wp9f93h+IbmcVKTrijx3EVSOneU7wxrdW2wU\nPG2+55i0boN1R5656Ss24jEmpq4VYVBxMCh5eFxwsCgJ/RJdWaatrusNncslLpWUCM9DRBFEIcL3\nEEpu2JRwN5TVSXcUYHfZ5nx79m8b1TrD2+3Bdb2CXRFNylAgdYVYLeHmGgo7/UpUFQiB9Dy8MET7\nEau1z8Wl5MW65upqzXI5Resr2iMHXdXYdXV3nbQAKX2E8FBKvTELuDsV565EQd8nPw1vF6V2ce9i\n3GWhd58Dt1ymSpPnBXnueAL2gA6r025VtJkMjavpuyiuezBDl0jkhnW4Ddlhvse7FYd1d7yn1l0D\nJpoasY0uDw7gwQN4/BiCVOOvCvxVikhnkN/A9AJmE0iXrfHt96Hfx3SL8a7YvF7bufvO8EJ7uLfy\nKGqPZe4xW3jcTOHm1s7smE5rVquaonDlDJoMyXb6eXfi1fvA+p0YYOeweB7E2Zrg6hR5/a/Up/9G\n+fIl6+WSFW0iStMesx0JSTQ4onzw77j93X/k9OwhT8/G/Pm85uzSMJ3WzfB0x0Nes93O0E1vVTtX\n1jWd3TYIr3l3n1EPPr1f8Y9frDlJM5KXOZkuyJsIWDaDONywvFApvDhGDId2uHUSIzx1p6JgJ90+\nUMckdWWburY13O20I2xvuK4Q0f0e2EEcthdYVQvkdIZ4fYooTxHTKbIsMVIifB8Rx+gwYVmEXN0o\nTheGyWRNlk2By50rds6Zez97HXb0pNgMaHc1oV025MfSYvZL5W+Ld9foto6Q1cug+Rm3W+TNv7v6\n7lgZdL6usXOGa6QUW2NEXf2yO73U9QV32bB7vK3sYu1w7hKXPK/NIrjlgjFJbSdVuVqF61Orqnaq\nShzbwwFGozaklsr+TrfdyDWXV5W18CcnmINDMtVjlgbNUZftsZezme28MKbCjpYVKGU2Ot4lXb1v\nrN+JAXbn/EYRJNma4Oo18k//inn+L5S3t6yXy83hY+701QAYAiMhqfqHFPf/HemX/5HTecizecCf\n/qKZL6zSWAPsmJLrndU1wF2F7Maukm0DHG9ux6gPn90r+ccvS4LrNSQFuS437UeOI+uS2YFSeFFk\nj0ccDhFhjPDVnVXS7ikz7cHaphlH5zbkTeWcLju9bQei8z2B7cW1y9MaOZvB69dQnSJnM2RRYKRE\nNkqsg4RFEXB5qzit6x0D7LIhboXsRuBCyM3kpW4v6C6md3lDhr813rscDeeSu/8zWN2m+VrT1pRd\nDs397TbStpO06qYXtc1kuuMKZzMbTLl0qvtcb8P1LuP9NqydAXZG1s3Ybp2w9ntK1Mh6xwAvl/YH\n7BAGa3gPD+0aDCDpYeLEDta5ubZZr+vOStPWAI8PyHSP2drnctEaX2eA12trgKU0uBOYdtuNPgTW\n78gAG6Koof2vcvz1hPrsFfmLF+RFQZ7nmw7QGpt2DnyfXhAwTPpMBvdZJZ8wCZ5wXlWcL0ouLkvy\nvEvY6JI6XBrKpRe76U3Yjaiskuab31VKN/NgfUbhmhM/5aFcUzBhYVYs64p1Q8ByScsezSwXpYiS\nBDUaoUdjEDEIe1vvQvTrPmO3TaGrpNsKaUlqVto2o5b1uvmrW+/heYIokkSRoudr/GwBVxfUxQWm\nGeor3BnOh4fo3hHrVchkWXK1mrFczigKV5ZwDGfD9hQscBu4VVCxmRHcTU3ttiXctU35bXi7/lu3\nGXfvlz2vVWCMwhjn/DjGR9cY70a9vWbZCFkIq/dtVF1guxx2CXVuwL8A/E2fr6vhuwi3e3JPlm33\n/sKb7Sh3Ee8f022Xhs5ze69cD/Z6bX92sei06K4EYa4IjI+SIdKPkHGMcEfLjseY8UEzp/gA3RtS\nRgPKaIAua2CIYIQUI3yvjx8meOulPQD68BAzGFCtYvLC32qBm07bsZNvYzt/aN1+JwbY86CXGA7H\nhv66RgUlWZ1TFAXrqqJo2kYcBcaTkmA8Jjg8JDi+TzF+xG024OULuLqqWa10M07SrZK2id8Z3zdP\nsnG1o+1N1r2zI24UxHFNv68Y9EMO1A3RzRniT2eUL16wnEy40Zo5rZ+dAAfAEXDgeQySBO/gAD0e\nY4qEuvDQ5d0wwPDmqSi7I+rcsXT23FfnwrgcgsNH7/zVNooJQ814XHNwYDiRJUmxwsxvKdcTqjSl\n1hriGHN4CJ99Rj18TP4qJF1Om+EAF017mj2JxbW3tM/Ltjgj8jYF3VXSbkP/XZEu3t0TkFzK3jLG\nVRNpGrSOGia00z1ocXeOsnse3BxoOyvYpgwdwUc3M4bLRrccmS6lbSVzEbOHEAlxHGz6UPt9+87d\n6Vhp2h4c0Z38tMfbytt0u3vcY5q2mQQpW+MM8OpVe0zkQRBy4A8Z+5JoDKHwCHsJIgps6a4ByCQ9\nTNIjI2aWhswmknUqYNmDhSHIFGNfMT4KGLBsfzeOEVWALNSGf+ScLNuX7BEEAqUkvi83zvX3HTf4\nvrB+JwbY96CfGI4ODHGqyYOStS5I85y0GZzgqj8Sm8YNRiPCzz4j+OxLiugRN/mA58/h6sqeYGM9\nX0e6ymgb+HcNcDfCcga47ixH6rBMTCFK4thwcKA4Pgo5kGvimzP4079RvHjBcjrltq43KXNHFhsD\nD4Ch5xEkCf54TDYeUy8SdOlt0jMfu+xGQt2WDuclWwMsmmlWXQPcHbywa4AdllVjgA2PHsFJUZFc\nNgZ4OaEqS3RVIYIAc3iIefwYM/6MYhGyejllPp+h9QVau8loLtXZJYBti1O+rrf8Q0b4Y4+EurI7\nkKH7nLupd1FEk7GwB68XhT0VR2t3r7tOscPAMdAjnPFtDbBoejYrtM6pqu4ENVeGcvoeNL/rIURM\nHAccHnqcnNjrgnZyk+ti6Y4g7G68dx3v79Pt7rGiy+X2FDInnmcNsG1Ngk/uh3xyT8L9mOEoQPQS\ngntjiEPrGQ0GmCDEKJ/a88lXittbj7NLxWxmoEwwRUBMxKdJQJhEDOLlhr4s/BhZBKhcbrIc7rCF\nupYoZfuTbRnizfLSh8L63ZCw0ISioC9KQpYU9ZqiykmrakOjcNFvKASx5xGPx4SffIL3u99RLB8w\nW/Y5n9gUQpa5mpJLPXUZj7ss2vYIu3Zz7yp6l6xhD1zv9TyOj30ef+pxVKcks3OYfE159pp0NmOu\n9VatOpGSgVKMlaLf6zXnK44xwxGmiDFS3Qnj66S7IXejom6aSmvRiYC7zHQfu4m6Op/DSOGelDiC\n46OaJ59pHi0KBrM1Jl+Sr1abwoP0PPRohHn4EHP4iOp5SiZSsmyFTT2vsM9MwJuGt5sxkZZtLd+M\ngHcV9S6OI4RtvJ044qWtFdqZ6s7x8rwApWry3N0rx2o3TU3OGmBjurVfu2ytzhpgrSvyXDTPmWsx\n7DrZXYZriOfFJEnAaKQ4OWmv2RGw3PQjd/0/lJp8G+7d+/Gx6vvbdHu799t0WpJMc58Mvg/n5/Y+\n2WmFiqxSlJ7gIFKMvYhxNEBFASJMwE9AerZcUcDtUnB+Ay9f2wFYdW331H4YEMWSg76PPuzZs3+N\nhqrEoyLyKvphSeQLpLAjbIWQGwKew7Z7CtbbjPD70u13M4gjz+F2AnqCefWSejKhKoqNKbSzqKDf\nGLJBGDIYjQjv38c8fow+OyZfJ5v0hhvu/SZTso2StlnPboMPaGvDzug6L7kPHCLlfYbDEZ98EvKH\nP8DD8zX9sxvM+Uuq2yv0amVP2KFNkPWDgHAwQA4G8OgT6uN7mMGYOupRByFG7pKJPl7Z9ZC7G5Ej\nbrzte9uEOIepc46ce2anUvWTiM/uCf7973I+m+Qc3JTUviGl7Sj1lCKOY+rRCA7GTRDk+kK7PcfO\nWfM779G9Bq+JuuQb9aKu8nan5dwl6eLtGLBBYP/dTdm5qDIIoCwVZRlQlgKlFEqFSJng+6ZZYEeO\n+hgTbBbYntK6FhjjZjsLplPRTLGLsHoMLYYhSg1RqkcYRsSxR68n6fffPBvYkW7tVCR77UmyfSB7\nF2/XihYE25tzd4jHxyQ/Rbctx8OgdY3WNcbUSGlfZzPRGGDBYiE5O5N8843kaCA57AUc9cCPPUTk\nIyKJ9MSG+LxYWAN+dtYenmAMDHuSgyTk/r0+mSfwFreo+QSxXNDz1hx7JXII3w0Cjgb2pCV4c6yo\nIwo7nD+Ubr87A3xzC7NXmNf/P3tvHmtblt93fX5r7fGMd3z3DVXdVV12d9sYGxnazmBwGysxGMlB\nSJhgQgAlJn+AiACZ6Q/aCBKIDBFxhJAwiTGKEWNskIUwWGm3EWII2Eoiue240zV2vXrTvffMe178\nsc46e53z7qt6r/vdeq/u3V9p6dx7xr33d6/1m3/rXZrTU+o832o4p0UYaM2B1uzHMeF4TLQuGqtW\nh9yD04YAACAASURBVOT3eiw2AnjbQmkFsB/XdW7MTWQZK2hdqULpvd8XwDcYj8e88krM5z4Pt7Ml\ng3ce0rz3LvViRpVlVE2zyZcdAv04Jt7fR924gbl9B3N4TD3ao04HmFBfryARF0/U3Q5DbsG2EO/R\nt4hd3eZ2Heiwl/DKifBd35Zz40GGebuiiZpNACLHhjEGaUqzt2cTOfo5hK7fsy+EnQro7hHt/aaL\nHToBLE8Uvn7SxnWD49YXwBf10bU94IW6DqhrRdMEhGFMENSEYU2aOnc1gKytHLVO2FIYoyhL2Vhb\n5+f2PloshCyzwtbO4zaD2vbu3iOK+iRJQq+n6PcVw6F1N7t7MQjaxkp+1rM7nih6PGHHF8K+slEU\nj3sErgqeZm5Xld0X3XYmtB3Jqqrm/FxYrRSnp8Ldu5okCUhTzeG+4vgg4sZBSJQoVKhRoSJwCk4I\nq6zdbGc+b6/v/lhx8zhm1mjyUDDZQ+TBKeHDu/QOSvQh9EchN0d9DoaK4SDC8DhvrhHHrlX8cc/t\nyxHARQH5ORTvY+7epZlMqItia2fIUIR+EDCOY/b7fRutPzqiOLlJ/X6fUidrt4Z47kt/oYZ20YSL\nBXDo/W2dyNb1laL1Pkod0u8dcTiOuHNoeONkwTCZkOaPqO/foy7bY3ZdukZKMej1rAC+fRtz6xb1\nwRF1b0QVptQaGnmyS+qqLdhPmqC7scInu+l2rWAbyxOJEIkRiRmkETfHNW8czxnXc857GWe6jcsX\ngBFFpmOyaEgWjymDCY1yNabNzmDzOxcpdrbuWG1py7uNGfwJel24hsc5dQkvLgGrLFsrMU1t9yor\nUO21dXW48Tr01+/bx924srufXKLPcglaC7OZEIYK2+kqxfLpGurYe0apAUHQI4qirQYqri7ftZt0\newr78b42hs1GQXALtd+e0sWK/ezgqwhf2bpobhtjaBq317orDbVex6pSLBZ+aNBmvx8eao6PFTdu\n2B7rri7XZavHsb2e/g5L7f2geDSLmFYRSzGQNejzKdG9D0ijkHQ/ZZT0Oe4rjsYRhwc9qka2Yvtu\n7jpFa7fJzsc5ty9HANc15Bks5u0mkU2z5fiLtCYaDtGuXcrhofX/rGeCT3S7SDpN1yZkbLss3eLq\nlza4koT+OrMxXU/MAePxCaPRMYf7CW/sz7id32X/rSnBg69j5mcs14liMTbhqhcE7Mcx+1HE4OCA\n+OQEdecO5sYJVW9E0YSbbN+LErCu4mLssFuO4lu8NrZmrRgRx6Mfz9/NXrcch2FKHPeJ4wGjICeZ\nzlBvzTD336E8OyMvy01cPgBMKZyfByy+EfIwi7n3KGGZuaSeiHaPLUNbwuLakvq+GWsV21KkVrD4\nLqyPiv9dZa4dHLd+T2W/RMXtz+t2LXJwQi1N3e449hFa4etKW4pi02ufILCWb5oGm1aSTSM0TYht\na2o9FyIhkNA0dkOA+dyWjCrV1v46F7RbdP0+wE74uv2BnZLQ67VbGYZhO8ddnsNVc3r5mcD+Pe8E\nITilVNbXYHduu5ptNxnaOm276Y1do4MgQCk7wjAgSTRxHFDXslG8/Cz1MLT3w2Ri+3KwgtDdY0Vh\nPzCdMNQRt456fPazMFu0Pcrd+biNOZyC9aLm9uUJ4GzdZmax2HTPcGJRYTtIhYMB6sYNeOWVLQG8\nScVpXA2hb6G4v50L2iVf+AlXvtZlIRITBPvE8QH9/h4nJz1u3+7zys2Qb0s/4E72Dgdvv0nx4E3K\nxRlL01Bjl+4xMAgC9pOE/cGA5OCA8MYN9O3bVMcnVOmQognI87ZLzEWa01VcmHct3d2MyPaGl7UA\nhjYL1q/ZhpZjQxgm9PtDhsN9RuFD4tkM9fbbNA/fpTo7oyiKTfVnANSlMJloFu9H3F3E3HsUewI4\npnU3G9rSlZ53DO6+cQu5TcbaTdjwJ+m2kriNq8i1gztn58Zz9bU+904Ar7uEAm2M1Q3X9Ghvz77u\nhJpbLN1Oc64v72QipKkmiqwVbDdQSbC7ITnOFMYE1HVAWVoLSutWEXDH4gSp2wfYbVXY67UKgt8f\n2N9L2HV8skrl4wv3Jx27ZTjOKvQVbddgI4qsl7Kd2w1uK8k2qdLPfoc8tz2981yhlC0/E0kIw5g4\njohjm3DlFCa3ljgPxUYATyFcQr+CTXH3colMpwyDPrePSj4bGO6vtxJ2ioOzeD9MAH9cc/u5CeCt\nA61re+Vcnv96zypnAYdAojVRv48+PIRbt+xMXKuWYgxK/IC5rd9qMx6Dnd9WtLuiwHZSj8b29O2T\nJDfp92+yt3fAnVuGN15veONOxuvTCTenbzP+4G8we/A2xeKMlbFbEMYiBMAwitjr9xmPx4RHR3By\nArdvY45uUKVD8iYk9xq6X2W35O65+cLXb77hxwXtpHZashPAF5WOBYAijlNGoyFHR3vsJ+f0VnPU\nN97DPHqfejKhqKpN+44QaGrFdBpw927I27OIB2cxq8ylzYWb720XCNc1rfSOwSoAdjGXrVIkN2mf\ndpLC1eAannx+zooYDu0i5t8HTkA5AewW83WrXwYDK3jd8N3DfiMFa+lagd7rKZJErYWiXdibxqxj\nuNaV6a65taTNpsxoudzeTAMsny765Row9fuGNIFkLaD1OikocpszJKCUbDK6XfLZVeHaF77QNi5x\niUnuXnB7JiQJGwvYlhoajKmwm2/shn6ssm3vDWE+B+uB6gENQWCIIltDLtLePy2/1kXtBPBkAr2V\nscqVJ4AJQgZqj5PDkuIQwsTeA/b3tj0eu5ttfNxz+7lbwMaAqa1vxuQ5kudIVSFNg6btc9PDLo0a\n2LRNuXcPaTTD7JibI/i2b+sxHCoGg4Bez6a5t63u2otTlg153l8X/Yc4y8a6yALCMGQwSLh1a8St\nWxG3b9S8Mjzn1f6EV7KH3Dj/XXr3v0Zz/y148AC1WBAYQxCGtr9wFJEeHBAfHSHHx9Ziv30bbt2i\n3jskNwPmmWbu7Y+5S9BVLFfxMyH9DFP36C/CNpN1N4nOeTHcaGOye3tD3ngj5vOfF74zhFsVRNW2\nfyNUilRrhkHAMkqROmS5UExq1/3Gt7jbBaC1uFu4/WFtz+Dt3Y+eZP3az10PrqE9Z7coR5G1GPv9\ntt6zLFtB6u4Fp0g71y3Yxdzp6W5hdALc3T9OkXVCHSwfo5F9fbUSVqvH3dx+fLKqZOM2dVZbHLfu\n5dHIOt9OTuzop4YoqIl0Q6ANoq1gRwmNUVSlUNX2d+1uT36lxicfjicXWgB7PXu9lq+63jSdW9tZ\nwmKhmM8102nAZBIxn8c8Xvrpzz/jvVZgk/Aq6jqjKKyy3DRmrcgrRCKaJqYoAhYLzfm55tEjw2Bq\nOMyb1u2yWoEOiHoZg7TioAfLfJsnP0nQT8J6EXP7uQrgjdbQNJiygrxtgyTG4PIW+1gRGeEJ4Pkc\n7t9HViWDEm6N+sxT6PfV2h0km4bpRWG2EgNWK7vfo3X/OuJtA/Y4juj1Qo6OIl5/PeFzn4t445WK\nG9kZx/m7HC3epn/+u/Q++BrNO2/BYoFaLtHGEAYBYa9H2OsRHR4S3ryJunULXn3VCuCbN6mTQ/JZ\nwnweMJ+3C8dFxF0l+K5nv+GGWzz9Dlh2AbyoDtg12Wf96CzVkP39hDfeiPnCFxSvlXDzPsT3rM3q\nvkGJ0AtDRnGMilOkiVgtFNNCWK3EWxTdRN+1uFtYV6KsC/ZloyH7G7L7rriPmqRXDe6cncvVuZ99\nAZxl9r0uD8Kth25Bd1Yu2M+7mtzdBCznRdm9x6AVwFXlEqtk8x3buQhmrSCa9XaErQD247tOAN+8\naad1L27QTUVgKpQYUIJoRVkr5quARaZZrFo3eZa19/hVgMtq7/W2E5PS1NXz2mvcthm13oXVSpjN\nNN/4RkBdR8znruRv2/rd7g/unrNeKGPyjbIOdotXO0JE+sCAokiZz0POzoRHIzjMDEXmCeAsA1FE\nSc4gqSn2Dav1uuRyC5zRcFHm88c9ty9HANfGCuDCOvGlrrcs4B62eMDZO9S1tYDzHDmbMNzvcXP/\nGLNnyxjiWBOGAYt1MH212s66nc0UVSUsFpqyrDffrLUmjiMGg5ijI81nPgPf8z3wXa8vGb93xvi9\ntxg8+m2a89+lufs1mrfeArz0rTCkl6b0xmOUN0vNK6/AnTtWADMmWwnzdVcYJ4CvWlLGLnYXx4+2\ngHmCAPaRbMbenuaNNxTf933C8QSir0J0ZgXw5luUohdFjHo9iFOkCVkuNBOxi2ObGOJc3m7CP1kA\n2xZ1suWi8heii7IjrzrXsL0wuYxiFxft99seyk6o+uuhb/X6XaesRWUoC6g997WFW4TlQgvYGOux\ncN/dxp9dVq7zlm1bwG7rvG0BbFoBHBqkqOxNbMxmZV7mAUUhTErFYtFmZucu1+iKwLmWez3opYbY\nywhfzK3b1xjo96DXt/dCnlslaDLR1HXI+bnrcucEsD//XKmhv4OVJdcYW85U105RdiPGNv8VikKz\nWAjn55rTAcxrQ9E00NRt78nGEB1kDJIK9qGozUZJWixks5+xo9ffgtAeR3s9PjGtKN1BGwNGB5ah\n/QMkPyCYzYiCYHPpa6Csa/RqhT4/30o9lN6AdDhjP5jDcE45DMhGAYt5gNs+yk08d8GiSAiCgF7P\nUFUNQWDrN/t9zfFxwNGRcOek5ttvz7kjC0an56TTewTLKRTFxkUugA4CojBEhSHh4SHB0REcHW1c\nzty4QTXYJ2965BPNpLaxKpet53fXuarwuX5SbeDu9nRuwVTKlaU467d1Rw2HmuFQMRopXvsUHO01\nJLqx8ac0hvGIYDiklyTsKYUaDEhfew392ms0g89TLN5guRgxnxjyvFlPZNeAw8+St5mybdP/AVqn\nhKEti3BJQi771ZUr7GrLVyn292Hw+fYzY11ylMt7cJvcOE+Vmwuu5tYlO41GNuVDUaNoUDT2/lkn\nXFa1UDWKspaN+9/V5bqG//4ORs7tDW3WvbO2naBddztkNLIxX5cANhrZ90Sh3ekM00Bjb2jTQI1Q\nm4BVGbAsNEvP7X0V635dgwq3QVESG5LYoKuKYpQR7Ocsw4a4HxIPAghCzmeas7lVUAYDzWgUsbcH\nZVlTFM3aKIJt17M/3PN+vb5/cYPNe5Qy9HqG/X04PjKMpiXxdGW1A5elFUUEkSIJawhzhknIoqdZ\njNRjmfvQenVexNy+HAs4CDC9PjT7qHyf4OFD4iCgxC5/NVA2DWa1Qp2d2bNdFwRKY0irOYQzkuGM\nbJSyWCRMlgGyU5/lLlSvp+j1NHt7tr2d2xx6b0+4c0dx545w66Dkhplyg/sMH31A5AlgZ6IJEIQh\nKk0Jez30wQH65AS5eXPjcubkhHKwz9z0mE4CJoVsBLBTmq/ixNzFbj3grvtwVwBDmyhjTIDdL9Z3\nUTUMh5o7dzS3b2s+/amGo/2aRDeEAahejIzHVgDHMaI1kqakr7+O/sIXaAbfSfG1V1l+bchiYcjz\n2hPATst2iVa+ALZ9h7VOCMOQJJHN4rMrgP1OOtdF+Dr4Lmi/baNffrTyXLNF0VqtLuPUCUA3tGnQ\nTWm3qUMwIhhR5KVmVUJW6K09fLV+XNA716Jf4+mEsFKGfl82tcbud33hOxrZjWPi0KAwSNNYIWwM\nTSNURlE2to3iKlcbAbzb+/iqwAkoOwcMSdSQRg1JnRMMZ4z3J5RJRTBI0cOUUqdEQUxjhPkypN8P\nGI1gf1+zWFiBWpZOAXZuaT/s5FvBrjTRCWDnwXI1xA1am038+fjYMCxLorP11oauQDuKCEJFEjXo\nsGCYCIs+LLO2tNAl0PkZ/S9ibl+OANZWAJvoAMn30b0eURBsXIcNUDQNslzSnJ+3mRfrlMm0mpEE\nc/aGc1sHuNCcLt0WY+3vtIuA67bD2vK14/gYPvMZeP11OBlURN+YEL33DcLTd5HJOXgCWJoGA+gw\nJOj1kNEIcdkZr7xird91pkap91mUfU4nmvNlu6uKK0u4qkk4Pnzhu2sBO+G7bQE7d46irm29pnVJ\nt5NvNLIC+POfV3z61YajvYZUF7bZg7OARyN6SUK8TqkNPvMZ9Pd/P83guyjyhMWbMfN5QZbtWsDO\n/ewLYNf0f4BSCVEUbLlVLxLA/kS9Djw7+C5ov0+2E8DOMvUFo4vbOgt4ONy2gHXVoOuKoMpBiU03\n1oplblCZ0KCIItnE4S+ygJ0Adm5xv3ez1rKxgN1vO+Hrj37PZlUrWuFL02CMojKKDGsBr3JYrpWM\nqwoXA05Te12SsCEJawKTszeaYLIHmLxARpbIpbLVIssi4NEspN/XjMeavT0DlBSFTbCyc9BPinRC\n2Algt5Ws28/dKcsaP3RkBbBhf99w48gwOiuJ65VdhF1BeWwt4CCsiaOcVawY9YVVGSDrTHmXZe2H\nJ17E3L6ULGh7FrZPq9rbIzw6Ijk5sZupr1aoLEPVNaYoqJZLawmVJWY9g3WS2O4oRcawusFJeUw9\nuMFca5apsBjZbAodh+g4oDKKvBDyQjaTrteD/VHNUS9n1BT0lhP06hydLVDZClY2iGOWSwAkTVEH\nB8h6cHCAnJxY9/N4TB6PyGVMlo+ZMOAsjznPFfNMNokYPpG7bmhH5lVasLfCDjsWkt8T2N7kzTqh\nwu5sZXe3aghDu0tJGGrG45C9PevJGKY1seSo1QqpK7sqjMfIK6+gsgxJU4r+HtOTz7Eqj3n3Ucq9\nc+F8VrNc5uR5QV27Rh+GdS8zrNAdYturjBAZIjIgDFOSJKTfl43Q9eO/T2rOfpHH4ypyDdv39O45\nOsXXPToFTEzDOF6xF63YKzJGS0VvKgSi0E2FMhXSVIjXaFkhBEoTenH33VaPraVr/2/d1LJ1jM6l\n6td8+sl1UQR6nczVoKiNxhDQCJRGkTcBRSMUhWwt2D6uEt9+85lAN2hTo6oCtZzD6UO4+14r7EYj\ngmiPaHVMD0W/n24U137fdq3KsmDtMTDrxiku/8PtLbdJqcQqxj2sq9mtC4p+P+HgYMTBQY87J5rv\nen3JZ5JzDhcThtUZUdC0xeVpiiQJBBpMg+QZoVEkgabfh7Jq8xJaz9yLm9uX04hDaQhjCAdIuUd4\nfIxMpzRNA2dnmLMzq8KWJdVySbUWvmY+h/NzwqYhXCxQDx/SP3iNk/3XSPcb8l5EWSuKWkMSI/0e\nqp+S1yHzpWK+FPCSQ4ZxxV60JF1NCapTZDZBVmtfsVOjl0vEGEyv11q8N27Ysd4cmsGAPBpw3gw5\nX42Y1gOmWcg0U2RF645yC9RFWdBwNSbok7AbT3ECy7qltwWvHQ0iDVGk6fUC+n3N3p5mPFY2LhfX\nhE2OLBdAZVeE8di6sYdDzGuvUZkBZ8PP8HBxwFunmg/uN5yflywWGVWVrwWwC3yEWAE8AEbAHiJj\nlHICOCJJAgYD67L0477++bhxXWqAPwz+9XC10s4Ica+rpqGfzenlp/Szc2KtSRpNkOv1Z42lx0lI\nEcRotDSEgdnEmf32l7v12c5qcx2y/Cxq51LdLSnzhw4EFNjdEjW1ERo0BUJeB+SV2gqpXMT5VeHb\nzd8whFBbD4UUhRW6Dx7AO+/Y7YnWnUukf0gYQxINt7qG9XqQZYrVKiBJXE9vTdO48sOMVvhWtL0b\nbEtRrW3f6F5PcXIS8tnPJnz7tyd85nbDLXXGbf2Qo+l9kvKMMDT2eHy3lXOXrFZoExAHMf2eYZW1\nyYCuocju+Djn9uUIYJdKlw5Q7BMeHxOuVjR1TWMMzWJBPZ9Tl6Xdz1Vs/Kdx7C8W6IcP4b33GHxu\nTi+qOX41xsSJdW+rwPqVxiDjgEWpOJvB2VSoG9louSk1w9WCNDslmD+A2TmsFm16pmu3A4jbBuXk\nxGY43769RWiuB0yaIR8sx0zLhOVKWK5kq0sLfHjW3FWZpLvYdU/6CTouKcuWGfgbIliXUhRpBoOA\nvb2I/X3ZuAV7cU1kcqswBU3rF9vfR157DRGhWiScPejz7v0Bb31D88GDnLPzkuUyw5gc2wzA1SLt\nCuB9RMaI2J1zokiTJPLEuO+T4kLXWQA7+HFDJ0c3mxeYhvDegujefcLpXaQJUXmILNYXNtCI1q2/\nOgxRqkaLIfBqr30l10+acSUxfkcuV4vvmmR8pADWgAiNERpR1BgqCSkM5LVsldQ9qcnOVeHbv7aB\nMqiyRIp8WwDfv9/m7IynhCcD0hs3N7F2t2yuVoo0VSSJATRN01CWDW1THNaPTgC7zTUGaB2TJJrR\nSHH7tuK7v1vx+3+/8B2vLIjfmxO/9w3Cu++gyjkSmO1WZmm6JYCDMCYOKvoxzJftS3X94e7mT5wA\n3rgfQ430UmQ4RMI9ZN22RGYzpChsokMcw2qFWa0wed628K5rqvnc5sIVBTpN7Q1RW7ejxDESRcjR\nETQnENcYNaAIEqpeQm0gCWvioCYpFyTFlGB2hpyd2u1UplN7M60zpsSvN0mS1gI+OSHTfXKVkkmP\nR/U+p+WAqQmZF3qrWYCf/OEWiIvwYa990uC7mnfr6XZ3jwkC16y9Wgth63qy+3QGpKliOLTNL0TW\nma2NptYxTdIjE6wlUgTkdWDbftaa6TLkwTRknodUNTRGIypAKbutXdMkGNOjndw1cAQcA4eE4Ygk\nSYjj1vIeDlsB7DffcO4on+PrwjW0fLtzcgl37jl3neLYlq+EqiZQNWGVoWVFYDJ0lYHUIDbprkl6\nNDqmSVKypsdqmrKcRazqgEWlWFZwb73mv/sufPBBzYMHNZNJxXLZbHZKMsZaUsYotNabzOimka1S\nOPe3K5VzOriIbM7Hem1kq5uX+8yTrF+4Ony7ZLrpFEiEFI3oEOXHAopioxWpRpPEHzBO9qkkpNEh\n4UHEmJDJUchkGTJZhKwyxWolZJnCbpph7D0lIUoqtJRgAuxuNoY4LBn2S4Z94c7Nms8Ocu4UBfun\nE9TZu+jze6j5uT2OfgrDfpvS7mrN1skcOoiJdEAatMl88LiL+UXM7ecmgP0JqiKN6q0324xXdk+p\nvr1AIoJab8QpDx6gHjxA5TkFNvy+NIaiLCkWC6KqInrnHeLFgvj999H9PqrXs9bqq6/aGaQUarDe\nLjCMMAKJ5KTkRPWMcDVBTc7sMZyfW/fJdJ185bZEcX3oDg6sy3n9uCr7nGU9TvMek6rPpOozq9Sm\n5aRT2q/CxHsW+FxftF+q/7+Ls1VVQ1W5zOQI13AjDNVaANv321o9WI1CirBPPbIL6vlUcz5VnM8U\nk/XIS02jNEZk7TYL1r+XUlU9jOljzBAbV3L14TexAviYOE4YDmNGI+HgwJanOE+WE8C7+9teN65h\nZ26vFynnvoPWCnV1lVFoCJqSoC4IiiWqzJCqbE2OtRlZBxFVMqQa7nM6j3gwiXh4HjJZBsxXAbOV\ncP8BvP++HaenDbNZxnyekWXVWlDasraiiAmCGKXUpvGLSCtoVyvL6WplF+HFog0xlGUrjP1mDLut\nNS+K/141uA0stIZqqNjrhYQ9Q5imrftAZOMO0OacXnIXiSIicgZqyI3DAbODIUvVZykDlipcN+uw\n118kXHvJNKGuCFRJqCpU3UBhoFgRmIY4qIl1w16ccVtN2Ls7QX9whpw+grNTS6KrMXPmt2vWnST2\nufEYpRMisZs4O859V7MfC/648dwtYBFQYYD0UruLQZJZzWRdByBpiuzvI/v7KMAsFsj5+WaPmgVQ\nFAVZVRGuVvQXC8zdu6gw3HyHGg7tXbLOhFUmIkgj4rQP2tBrClKzJKpmyGqCTM+s4D0/t2M+bw82\nTW2i1auv2mxnr1ntatrn0VmPb6z6zIuArNCsCm2tLc/FdR0aMezCXb7dXsm7wtgKYbMpsndF97bn\nckQQCGkqDIeyLYCrkCLQ1MOE1RxOK+H9Cdy7J3xwT7h3H0DYP4D9A7dpgk3aiCKbbNU0A5omc0eM\nvd1vADcQOSKOFcOh4vCwrQ0djbZdlbsC+DpyDY/HyJw16CzHLXdw2KCLCl1n6GKBlDlU5XYg1xga\nHVGmQ4rhEafzgHfPhbfeVjw6FSZTmEyFhw+tx/PePZjPa6oqpyznNE2B7QFv4/v22Gzfd5DNveka\n+jsh7CdhOX7dJjou09o/Xwe/L/FVhhPAVQWmVkRByHCkWh++y0hcB8RVWdGL7xKHNSM153jv0G7P\nundEOWwohyHlsL9uXCIsl67bnCYIDHFQkeiKOCjRZWE3Al5mSJEjVYmqCoLljOjsHtH7H6Cnp5bM\nbJ2K7oTv8fF22zq33+V4jJYAjEIhm1PwlUeHFzG3n6sF7NCIopSQDFgFA/Rgn+DoGOXa36w7X0lV\nYcoSbQxRnpMUBUVRoJsG1TSourZDKZRStirMBRinU3j0CD74ACkh7K2Ie3NEK6JmRdAs0fNzeHjf\nWr/Tqb27tLbErDO1TL+PuXUbc+sO5uYtCpVQqISySHiUp5zmCedZSlasEzF2ymr85JwnZco+Kcvu\nkwr/PFzChvPg2z1gW7edtRwEEOpaUVWaIFAEgSaK9GbXmWjdFMv1U58vFfNMMc/hdAbvP4A337WW\nkFuQowhEw3DkkqSFmzehrgNmsz6z2T7LpVpnXyqaRhMEB4ThgCCIt+pCneXrFujd5KvryjU8fi5P\nyiB1e6+EWggKQZcalYUo00OiPaQv1CqkkpC6DlksRyzpschi3nlP8+Y78OZb1tKdTmum04bJpObs\nrOb8vCLLMppmjjFz2NqKA7SuUMpseWRc9rMzuv0mMW6fYbdT0m63M59vJ28uEsBXjW/X77lpIAyE\nOFIEoZCvEuJwTHx4QrBYWIPm7AxmM0xdwWoO00fWsJrY5FU1HBMP9zDDPfoZlLlQ5OuOc6EiiIRI\nN8RBRaRrdO3tQ+ky3tZxXJansDi3gleknaxHR3DjBubGjXXySWAzoAdDTJJCEFFWNos9X7dG9XfG\n8nN3XsTcvpQkrLoRsipgVgha9Un6h8hJhRoO2jt5PrcxWK1RaUpyfo45PyeaTDDrFdw0jd01xphf\n0wAAIABJREFUKQgIggCdJDbFPE3tTJjN4P330bMlYXIfiQegFaEpUKa0CVenp3Ysl3aGOeG7v2+b\nwO7vY8b71KMDmvEes0XIZBUyXYaczkLOZiHLlVB6vWl9S8hvZebHyK7KhPwouAzYOG4XON911zbp\n0BRFSFEIUWTjvq7ZhYvLGNOGl+ZzqzOdn1uB++678Hu/B3fv2nl/emqF5sFB2xz+8ND+Vq+nuX+/\nz/37INKnLGUdw9MkSZ9eL6Hft7eAL3w/rOOVn1x2XbmG7drv3QYs7tpVhaCbENWArhUBGt3rofUB\nq1KTFZqs1JyfDZg87DGphPfeh/feszxPJjWLRcFiUbBc5iyXGWW5Wnsz3DDYpDpQKiQM2wY8rpmK\nX3rkjt3fPCTLWgHsON9t6OHndriOW1fZC+KuEcB8AYJt3TiqEvaDQ/ZufZqAtRZz/z7m4UOq2Yzi\nwQOKJKHo9Sh6Pcq0R5Ck6CQliFNULYS1Iq4FFWh0qFGhItCgtUG0VxvsZ9o57clp81HUWr2jkc3X\nOT62k1/Z9xtlm1ebKMYgZJkwnVlxcXZmhfCuAfWi5vblCGCjyCphnmt03IfBIWGqCavxRgWV+Ryz\nrh9QaUry/vuEIgyKgkqEqmmoypJIKaIwJIgiJEkQtykn2CsKqNMzwjAmCCNQCqFBmQbKot2TuGns\najsY2FX7zp11P+dbNGFCHSRUQcq0EO6fCfce2rKmxVKx8AjztePdhfkqacJPC5dlCo+7Jp0Arirb\nw3W5DBBRRFFAv2+TnpwAdqUBrsXfrgB+5x342tfggw8s7a7v9u3b9necMmzDPpooGlDXCXles1rJ\nph2mzazUm23wnAB2C7ZfeuQL4O0GD9eTa2g5dsO5ZouiFWBFIWgJUaIJJCLUKVFvD91vmM2EWQOz\nlfDwPODhuebhuXD3ruX27l3ras6ygixbUZZz6npGXU8xJqNtV7j2FaMRaQhDs+7eJJuE2H5/xzPn\nKQtF0fLo8/0kzt25X5VkqyfBKVebfZ1zYTITFjpGgiN6typ6oRW+lCXm0SNKY8iMYQmstGapNbnW\nxEqTaE2iFKloElGkKCQM7C5zYYBoZTscKnk8ccTXoFzMYB3X3Qhel7uztwdKYUSB0hilMKJpjOtT\nbfcEPj/fFsC7fH/cc/tyBHAtZLkwXYCpI2rVp9JCpHs0dYWhwqgBkmpkL0VXIyI9JkpHJHt7VLOZ\nzYSezwmiiCCKUFFkk69cjnsUbVZtqUo0Bky1NZuMXvufej2M0jSjferRHs3+Ic3eLerBLer4hLzW\n5FlAXgXcP4f75/Dg3HehbmtEuxPUF8zXDf4C5YSuX0dnhbFQVWq9zVjDYKAZDmUjgJ0b2sFZwvO5\n1VgfPrQVEPfu2aiD81K5pJ84boVoVdnWpGWpKMtw4yiZzezE8zsguYxnf37vCt/dx+vM9UXwF6t2\nAwbb07lp1NZ7jNneTP3hQ8unfazXo2G1WlGWS4piiTFLrMXrSspci0KNUiFKRURRzGAQMhopxmPZ\nZLMPBtsbguxused7atxz/sLs/t7dXOUqC2DYnbcgOagoYtAf0o8bVH9B2Dsk7A0hijCrFfVqRZ3n\nm55zTkVy6lKznjxKKfQ6OUSiyFahOKHrtqmCtrB7OKTuDaiClCpMqXtD1PgYGR8hoyNMOsQEIzB9\nmtq2MjW12iqNnM7sPefSf1zHwpdhbl+SAG61jGKlWKiIRIFuIsq8psobmqyHzmK02iMa3WC/d5P9\n268SFg9QZ2foszPk7AyltU2Bd+q1u1quYa9bQZ325Acjw9C6JZSi0SFF0CfXPYqwTx6OKVYjsvsB\ni5VisRTmq3axnk63a1s/zBJ6Uo3odYE7/yd1jrGvCaCIY2EwsGVHLt/Nle7t9pdeLq2r2SWuu+ox\nV+7ivFDOmnVaexS1fbmjaCtctYn7OoHt3N9Psnw6rh+Hv1BtuiYFbecw2C71cfvmrrz5te65s9lY\nfTarmM9zsiyjLDPqegWsaNsSusx5dwwRQTAiDEf0egP29mIODwMODtq2k7YZRDuch6Pj+9lgjC0L\nnJYpQQ5lfcQwucHw8BbRrVPk9BTVNOg8J6JVkVy1bwM0xlA3DZUxGK3RxiCun7Br1O1nNB8cbBoi\n1emYRRExLyJylRAMhgTxAC0DmiKhmUc0ubINVBqh2YnTn53Ze8ytH67czHc9vyiuL0UAu1qyooCF\nUgQqIpCApjHkK0OeGaqiIZQxkaroDXPqwYR4MGGUnqPu30fu38c8eNBuWQhtZk9R2NnkCHM1I0Fg\nZ51bZQcDSHuYNKXRCXmuWeYBiyJgWYQslhHzs4DJRDif2MxLX2P2s3kvmqBPCtZfJ1ykMbpr5HsL\nQCEi7VZnPdlqXJOm2zFFY+w95EL4bgIVRatjuR6/47GN5zoBnCT282Fov/vBg9ab5bfKc5bvRbx2\nXF+M3fwHByeAXYap82BMJi2HrgGeGy46tFhAUVSU5YqimNM0q3UjlYx2OY+wy7lV5ERiwnBMHI/o\n93uMx5rjY83xcbsspGn7/X52fsf308MZIUWtmVU9qiIir1eY5Abx4S3i5SOkrlGLxaaPFVjr163d\nBiuAK2OoRKzXsmlQbpIOBmxKEVxW5I0b8KlPwauvUqcHLM40j84DFrkm7odEcUAgAXWpqQtNjaLy\nQiM+d87rMp+33g5fgXyRXF+KAHYN2m2drG24INI2Une9k53MTHVNEI3QvUPMYA7ZASY/hOIIUxua\n2mAag5Ah9QpRK5SO0UEfFfVRoWtvEyBRD4lHSDLCpEOadEDT61OqhKWBRQmLGhZZuwA4LXw63T6P\n3QC9bwl32rHFh2ULtokO9g1KyVaHKWcxuSQXP1PV3SuTiRWgk0m7D7S2ORZbTfaHw/azQdA2TvDd\njM5x4oTxbunURbHfjutt7PLtrot/HX0FzM37omh3SnIN6NzjYuE4N9S1gc22LcH6O4L10OvnFWEY\nrxPqUobDZGujB6dgJYk9RudV8Xnt+H421EaxqhSVhJhmRJyekB69hm5yapUiQUyUpui6Jmgaorq2\nu1ux7sS+3uKVIKAJIqogotYRZm8fc3iMOTqmGY6p+yOa/hAzPMb0X8X0XiFL9jjLFZNCWClFEUIs\nEDatwHWxfb9jmhtu4w4/ie5l4fpyWlFegN2dVByqCha1cLcMmU4S3tGCmUIziTHTParSbIZqSlvg\nb0piCYijiKSICSRAGo3UGkWEUim6STHLhErHlErbTlvFtmvMH04Z84nwM2J9wjrN+MlwCksYbmeM\nu2SXXVdzVbVuZb/zkJ/oc/++VY6qqo35+m3vnAXtqszcrliOM1cS6FzSrtTIT7zpuP7m4VsTLlrU\n77dc+X0RZjPncrYWsVKu9MVultE0gjEpIhUiFUoJWtsOV0rJWpm3mfSDQcJgEGzczW7++vFdpxwk\nyTavHd/PBndNyxIyEzPrnRBITZmOiA5eJf706yTzBzSrlR3rSW1EMEoRjkaE4zHhaERlIrJaU9UB\nZdSnSodUyZAi6JFJQk5CtRzS3D+gyRPqRNk9omvZJIj5e0BDu+64e9Hl77j13m8W8zJx/bEIYP9C\n+QJ4s2VdJUyLkKpQ1EVEkyc0+R5NXpJnrcAMdUMUNERBzUArhrFmVCpCpVCNoCpBN4qgCQhzjdGa\nvLQlD2W9neHn71nrjs9NYDd8C8l//kWT9rLCdzn7MRa30LlORC4emOfbdYeuacKuguQ8FK5e0wlg\nVz7kWke633ZlJU4gOAHsMrb9sIJvwXVcPxt2r5MTws6t77wU7nE8bvv4+8LX5osEGJNSVTaKaFsV\nNuumDRCGst7jV9ZKlWI41AyHmtGoTflwfDmB4RS/9T4Pm+Ps+H42uHWzaSCXmGl6k6Y/oji6zT6P\niHlEWp9iJhPMdGrrg70gu7p5E3XrFnLzJmURki8Vi6UiqwPyOiRvQhZ5wHylma80+SKkymPqhzE6\nFno9IV3Pc9eB0CXH7dbruyRO11PAlUY6Afwycf2xWcAOblGGNmGnqoVFppnP9dodlW7cCW7BzrI2\nWS4GRhXs1TAuIVag1i7GoIGggmBt1brF3A+8r8MQG4Hsx4fcMbqJu1sX5p9Hh234N/VFAthZn4tF\na6m4Rz+87/fpXa43r1KqtXqdqzFNW4GbZe2kc3vEOuVK61ZA++5m/zg7rr91+Janf63dPPdzBYxp\nFTHbEMNuSenWBrd2+1UpvqvYZb67bOePEsDuezu+v3k4r1WhQiQaU8djqviIID4iiaYkaoI5P4ez\ncyuIxZYDNaLhzh3MbVv6Oc8CZnNhNrMZ807pngOzAqZue/hFm1R5cAB6nWfgcwvbfLljdFayS8Z0\n73vZuH4hAthNRD+5yS3WUdQuwq5ds1u8/cXc7+fp+/z9puq+1gZPdlm0mwa07/ML7n0COzw9Porr\nOPa8IOuJ5ocqnOtwNGrd0es24ozH9vXZrN0hzSlULgFoNmutaz9O2XH9fLA759w+qy6k4Oag6wHs\n7ygElv/RaLvPQlk+rij5rmIHl2/p2gL4+QS+G9rNb18wd3x/a3DralGANIqzKqbKB0xEYZYxTTmk\nMYe2FLBWlLXQcECzGGDuK7LS1uausu2+Aa45in+P+BbubjWKs2h9i9gNF/N1SVdwscB+0fjYBbBz\nEbjFuWm2yxjStNWKV6tW+LraLfc5N6n82lNf0LrFeNfdsFta5OKVbviWsb+IOLxM5L3s+Ciud13N\nFwlf383kFDS/XeRsBm+/vW5LeYELyvd87G5D13H9rcMJObdoOgEK7fV0no0nCWDXA9zx4e4PF6d1\n/O/Gdv36bT+e7891Py7d8f184IRe09jwYVVEzEQTkFDnQ+qyom4qVoWwymCVCfU8ob4f0wSKqoG6\nsm19fWXLN5j8zU8uCmu54ZR3PwHLhbVcIiY8LgdeFq4/VgH8pJN3E8Utrv4kCsPtjbDd8/7k3HVB\n+O+/SHv2SdzdOOCiG+BJ59HhyXgWrqEtHXATcpdrV3rkZ9e6EMNy2XH9IuEWTuf2233NXyR9y8bt\n39vrPT3fTzu3d5X1ju/ni01XMRS2+nebn5J1tUkBi9W2p+tpuHbcOT59j4VTmnxXsxO27jf87SOf\nxOnLwPXHbgE/Cc5ycRbvrkbj13Y5C8lZQr7G7bsh4HGt2L3Pd2f4Tdh3b4KL4povA3GfZHRcXy90\nfF8fPC+u3aPzXEEb5nDVDiKt0N3tQe8E726uh//3y8D1SyOA/QniSPFdEq6O0006PzljN77ja0n+\nZNz9vYu0rd3//fdf9HeHZ0fH9fVCx/f1wfPi2v8+x9fuLkZOKfNDjrv3h3u//30X/f2i8FIIYF8b\ncVqR02B8t5FzI+7GbX0iLvruizIdO7wYdFxfL3R8Xx9cJtewnVD7NLhIOXvZ8FII4F04YmBbu9nN\ngNuN/VyEbnK+3Oi4vl7o+L4+6Lj+aLyUAtjFblw8AR7PaPbdSnD9iLsq6Li+Xuj4vj7ouP5ovHQC\n2MUQ/Ebvz/LZDp8cdFxfL3R8Xx90XD8dnlYAJwB37371Eg/l+sG7nsmLPI4ddFxfAl5SrqHj+1Lw\nkvLdcX0J+Ja4NsZ85AB+AjYbW3Tj+Y+feBoePo7RcX19uO74vl58d1y/fFyLcc75D4GIHAI/ArwF\nZB/5gQ5PiwR4DfhVY8yjF3wsQMf1JeKl4xo6vi8RLx3fHdeXhm+a66cSwB06dOjQoUOH54uXvEqq\nQ4cOHTp0uJroBHCHDh06dOjwAtAJ4A4dOnTo0OEFoBPAHTp06NChwwtAJ4A7dOjQoUOHF4CXWgCL\nyJdE5Def8TNfFpE/f1nH1OFy0HF9vdDxfX3Qcf1kfMsCWET+lIhMRUR5z/VFpBSRv7bz3i+KSCMi\nrz/l1/8M8MPf6jHuYn0MP3YJ3/vdIvIbIrISkbdF5Kee92+8SHRcb74zFpGfF5G/uT73v/o8v/9l\nQcf35jt/UER+WUTeF5G5iPyWiPzE8/yNF42O6813flZE/pqIfLBex/+OiPy7InIpbZufhwX8ZaAP\n/H3ec38/cBf4fhGJvOe/CLxtjHnzab7YGLM0xpw9h2O8dIjIEPhV4E3ge4GfAn5aRP7kCz2w54uO\nawsNLIG/APxvL/hYLhMd3xZ/APgbwD8G/N3AzwP/pYj86As9queLjmuLEvgF4A8BnwX+NPCTwE9f\nxo99ywLYGPO3gQ+wpDh8EfhlrDD6fTvPf9n9IyJjEfnPReS+iExE5NdE5Lu9178kIr/l/a9F5GdF\n5Gz9mT8jIv+FiPzS7nmJyJ8TkUcicldEvuR9x5vYtmG/vNagvr5+/nvWms90fSx/XUS+9xkuxR8D\nQuBPGGO+aoz5b4GfBf6VZ/iOlxod15vrsDTG/AvGmL8E3Hvaz33S0PG9uQ7/vjHmS8aY/8sY86Yx\n5meB/wUrkK8EOq431+FNY8wvGGP+ljHmXWPMrwC/iFVGnjueVwz4y8APef//EPDrwFfc8yKSAN+P\nRxzw3wOuPdr3Ar8J/JqI7Hnv8Vt1/RvAPwn8M8APAPvAP7rzHtavz4HvA/414N8WEecC+QIg6/fc\nXP8P8FeAd4G/d30s/wFWG2J9/I2I/PEPuQa/D/gNY0zlPferwOdEZPwhn/ukoeP6eqHj+2KMgdNn\n/MzLjo7rHYjItwH/0Po6PH88pybffwKYYgX6EMixhPxR4Mvr9/yDQA28sv7/B4AzINz5rt8D/uT6\n7y8Bv+m9dhf4l73/Fbav6V/1nvsy8JWd7/y/gT/r/d8AP7bzngnwT3/IOf428Ec+5PVfBf7Tnee+\nY33On7usBusf9+i4fuy9P+8f01UbHd8Xvv/HgRXw+RfNT8f15XAN/B9rjmt21vXnOZ5XYPnXsfGD\nLwAHwN82xjwSka8Af1ls/OCLwNeNMe+tP/PdWJJPZXsDyAR4Y/cHRGQEnAB/3T1njGlE5P/DakI+\n/ubO/3eBGx9xDn8e+Etr7ejXgP/OGPN177e+8yM+f13w63RcXyf8Oh3f/rH+EPCXscLld572c58Q\n/Dod1w4/jj2v7wF+RkR+yhjzM0/52afGcxHAxpi/IyLfwLopDrAuC4wxd0XkXeAPYonzs+kGwPvA\nD/L4hT//Fg+p3Pnf8BHudmPMvyMivwj8I8CPYhOo/qgx5n98yt/8AHtj+TjxXrsS6Li+Xuj4biEi\nPwj8T8CfNsb84rN89pOAjuut7/nG+s/fEZsB/Z+JyH9o1ubx88LzrAN28YMvsu0v/w3gH8b68f24\nwW9iffe1MebrO+Ox2IoxZopNeHG+fsSmzD9LopRDic1k3f2Nrxlj/oIx5keAXwL+uWf4zv8T+AdE\nxP/ePwz8rjFm8k0c48uM6871dcO151tEvgj8CvBTxibfXVVce64vgMYaq8+9b8bzFsA/gDXZv+I9\n/xvAn8JmCG+IM8b8GlZo/bKI/CER+bSI/AER+fc+JGvtLwL/loj8mIh8FlsGssfjwfuPwlvAD4vI\niYjsiUgiIn9RbL3fp0TkD2JvkN92HxCR3xGRP/Ih3/lfAQXWVfOdIvJPAP8S8B8947F9EnDduUZE\nvkNE/h6spTBeZ19+zzMe2ycF15rvtdv5V9bH9Evr7z4Rkf1nPLZPAq471z8hIv+4iHxeRF4XkR8H\n/izwXxtj6mc8vo/E8ywu/jLW7/9VY8wD7/mvYN0Uv2OM2S3Z+FHgz2BjKsdYV+1v8OTSjj+Hdev+\nAjY4/nPA/wr4mcdPQ+K/ihWM/zzwHrbe63D9vSfAQ+B/YLv269uxmY8XwhgzFZE/DPwnwP+7/o6f\nvqLa8rXmeo3/GfiU9/9vrY/nMY38CuC68/3HgRT4N9fD4SvYpKSrhOvOdQX86+v3CfA2tpz0P36K\n43lmyHN2aX+sEBv1/yrw3xhjvvSij6fD5aHj+nqh4/v64DpzfSnttS4LIvIpbFz1K1gt7V8EXsO6\nfztcIXRcXy90fF8fdFy3eKk3Y7gADfDPAv8P8L8Dfxfww8aY332RB9XhUtBxfb3Q8X190HG9xifa\nBd2hQ4cOHTp8UvFJs4A7dOjQoUOHK4FOAHfo0KFDhw4vAE+VhCUirtH2W0B2mQd0zZBgkw9+1Rjz\n6AUfC9BxfYl46biGju9LxEvHd8f1peGb5vpps6B/BLslU4fLwT/Fy5MB2HF9uXiZuIaO78vGy8R3\nx/Xl4pm5floB/BbAT/7kX+HWre94xmPq8CTcvftVfu7n/hisr+9Lgreg4/p54yXlGjq+LwUvKd9v\nQcf188a3wvXTCuAM4Nat7+DTn/5mWnZ2+Ai8TO6gjuvLxcvENXR8XzZeJr47ri8Xz8x1l4TVoUOH\nDh06vAB8ojphfSvwy52/mdJnf6vL7W0vO7xs6Li+HhCxQykIQwgC0Bqaxg7HvXvU2r5XKfucG1XV\njqZ5cefT4aNx1eb2tRHA8PiEfFa8DIR1eDp0XF99OGEahtDr2RFFrTCt6+37IIrse8PQCtq6tiPL\nYLWy41u9bzpcPq7S3L5WAhharfebxctEXocPR8f11cWu9dvrwd6efSwKO8py29JNEkhT+1hV9vWq\ngtnMCuQ8t9/ZCd+XH1dlbl8JAexrRLvDuaPc8LViaCex/+iGe/1Jw73uf1eHy0XH9cuD3evjOHje\nv+Es3UDVhFITqoqgytGrOXo1J2xW9B/W9HoVcdSgSlAl6AqUDlBKo3RAPIqIhxHxMKZGUxFQGU2g\nNFGsSQaaotZURlMZRVWrjZDuXNOXj+s4t6+EAIY25uPIcY9l2Wq6zi1V19sEBEEbQ3KT3Y2LCPWf\nd+gW5I8PHdcvFu78/WsH7aL4PC1IZ+GGIaRBwzDIGOgVyfIUefQu6hvvoU7vo8jQJkNMQVNDWIMy\nQpSkRElClKQEh+PNaOKUJkqoo4REYoZRTB7FZMTkxOQmZpnDcgmLRSeAPy5ct7l9JQSwm/SOlLpu\nXUxZZodzSTkCfQLiuB1a2+GTqPU2aca0pLnv6PDxoOP65YC7Pu76OThunhecAE4SGEY1R9GKw3BK\nv76HLH8H3vtbmDe/TrGcUyxmlNmSwIAY0KLojUb0h0PS0Qi5dRN18wRZ3MQMRzAYYAZDml6fJh3Q\n9PpkqmGBsCBkutQYY++psnx+59ThYlzHuf2xCmCR7WzFXTjN2Wk4VbXtgth1SfiakiPFaUplaWM6\nq5Ujz2xed5qTJUZIUzbDadvuON3wMygduQ7dwvw4njVRwo+9XeR+ejau2/unadrkmyjadmP5GnLH\n9dPjSa47eHo39Ifx7f9GFBmSGEZDw15QMm7mjMpT0vldmrP3MA/eovzg62TzOdl8zirLMJvfEFiO\n0asxST4GcqiWkM/h+NiOSCDVEESQJARhgxZDoKBR9p4Kgi427OPFzu2rtY5/rAJYa5sk0e9bjdaH\nT8pqZV0/q1W7iLoF1deM3CgKS06et8M957Ib89y936wXX9mQ0O+3I47tQu00Kfe3T+Iu3A123Rfm\nXfgT7ElwC+3upNzVgp+Va/c9SsFwCIPBtrt0d8GPoo7rbwb+NfR5exKehm+RdqHs9yBNDYf7hj1y\n+o+mBKf3MHfvUt+/T312xmo2Y5rnnNU1c0CvRwjExlA1jb15plP7A9Op/T+O4eDAHth6MdCRJgoU\nBJA37f3gLKbOFW3xIuf2VVrHX4gA3t+3i6LDLkGTyXZWops/Zdm6IIqiJWi1snEaJ7SdFeRIc8TV\ntVnHFcyaNCEI7LEMhzAaWcXADadN1bUl76LJ57s0Omxjtx7zIvgxGd86/Va4Lor2u8PQ3jtKtUqf\nvxC4ye/47rh+NjwpUeZJeBq+nUciDEHE0EsMB/sNe2VBcH9C8GgtgB88oHACuGk4rWvOgXg9EqBn\nDLUjejq1Kc/WtLYLUVW1BxYE6FATxYogEvJ6WwA3TWcJO7youX3V1vGPVQC7iZUkVhD7moa/KGaZ\nnR9aW2KqqiXDaUbubxcXaLUls55nhsWiJstKsqykKKr1DWDWvn+FUoogUFSVoiw1RaFIEjvSVNHv\nC2XZEuZcFM51EYbt3y6+sGtZ7eK6WE6+y+mipgi7rka3wPnXz5+8ZWkn4GxmFbTpFBYLQ5Y15Lkh\ny9pRVcZzYUIQCEFg+Y5jIY6FKJItN5ez2vwJ6CdwBEFrJTven3Te/mJzFa2mXXfibobqh/ENLa/O\nCnL8OiXbhQvC0C6YbiGNTYM0JZKvMIvFZlGQokBh2/oFIgRhSBiGRFFEMBqhxmO7KvsptIPBxjVi\nen1IUkwY0egQIxqDPDaP/fN15+Hjus9t2F4P/bnsJ1L5Fq7zdlqh27BY1CyXDVnWrOd2+3eWGYrC\n0DRm87tPu44XRXsMrlbcd1P7a85FuCyuX0gSln+ybsFz2iW0E1TrViDPZo9rQm6AXSD7ffv3fG6J\nWywyquqcqprQNMv1jSKAwhhN02jqWpNlCRBTlglxHBFFEXEcMR63C3MQWKUhjrdjDH5mna9EPGnh\nuU64KM7jL9j+PbBbGuDcREli/3c1nXluteSzM8tzWVaUZU1RVFRVQ1XV1HWDSIOIoSiE2SzEmJDV\nKmQwUAwGmsFAbxaEotjOovTjQ04Q9PuWfycMLnJhuXP2tXv3G1cNF/HqhOmH8b27eDsh7L8/COwc\nG49hMBTCCBqjKBuFFo3WIRKGaK2JtKZRij1jUMYwUoqw3ycaj4nHYwZHR8RHR3B4uJ32+uqr8Npr\ncOcOZjDCpD2auEelIspKU5TCYtG6PP2M3F3l0f19nXDR3HYKb5radXJXwd21ZlcrmM9bx8RqVZNl\nGXmeUxQFVVVQlgVlWVJVdjRNjTGKZ1nHh8OWx12XtD+iqD23XV4vi+uPVQA/KdnCxVcc2sB664qe\nz+1w2pJv+caxnaxWABuUasjzmuUyo2lOaZr3MeZsTZwCNMYEQEhVhRgzpCwHLJcDwrBPGCrCMNok\ngTnXObQC2FlDvuXmJ/745+vO6bphVwPeLS2o623h65Ik/DiN61q0WLTCbT53AthQVRXOSfC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VgE+1JSkDSxDOB4fPQpqnfv4PbWcndnuL1t2GwqyrLCmBKtY0CjlBflngJwuKFCMsVpUwWpA4dp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F+C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\n/Cz8pns5Tuz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u2daehCMp8ZRPzxlg10PkXDR3liG0BaTp1P7f+MCSALIUGZYI422M724K7u9d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\nFdxsID8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc3976d160>"
+       "<matplotlib.figure.Figure at 0x7f3763332eb8>"
       ]
      },
      "metadata": {},
@@ -1152,9 +1152,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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rtEi9wWl4NnUL+uCDDzi7Np1OL3RsWxf7XDvxXMbhcMDn80GSJGxubkJVVUiS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\nt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v1wshBDY3N9Hv9yGE4N1Qp9Ph7DGDwYBEIoG9vT08ePAA6XQa0WiUS13ow6Pd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\n/Ad6wg1N9mmYjwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc39679a20>"
+       "<matplotlib.figure.Figure at 0x7f3763332e48>"
       ]
      },
      "metadata": {},
@@ -1174,9 +1174,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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UHlgBfz1bf51DZhAhfLp5coCbHLC6E9x2a+3mppuPVMJs09MCpAxBl+DkxPGZ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RAAAg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\nv47RGGk6SW0uuFCL3V3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UHlgBfz1bf51DZhAhfLp5coCbHLC6E9x2a+3mppuPVMJs09MCpAxBl+DkxPGZ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CyxdsR2W9O2012p0mYDnQHbOXxn8LmLBv0JntyzXMvwcNXiCeS9xON3APxcN+pTAHwYfjokXuXW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\n/wFBsUa2QhlL0wAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc376d6438>"
+       "<matplotlib.figure.Figure at 0x7f3763399d30>"
       ]
      },
      "metadata": {},
@@ -1219,7 +1219,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 91.3%\n"
+      "Accuracy on test-set: 91.7%\n"
      ]
     }
    ],
@@ -1236,9 +1236,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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PyWTCYDCAqqrscqKmCvSB159IV5MwPuQNI9EkYwDepHlTW0CTyQSPx4NEInFT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\nA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1J9L5JIzP84aRaJK7Api6PKjTEbnjPB4P4vH4bf06hAWDsrDp5FkqlVCtVrmH\nJ4CZeCSdPNPpNNd9Enq7pKSjk5OTa+P7VqsVXq+XZ9fWajUe16d/DJXKWK1W3lharVY0Gg1UKhXk\n8/mZkye50fQlBKuSDSngjfVwvjPQVYlo1zH/eGqoYTAYEAwGuesbgBnxnC9rEfG8I+jNodR5j8eD\n0WiE58+fw2KxYGNj443Bq1SiohdLaj9Wr9e5k8rbYkofArU7q9Vq7ONfFcMQ3uS63svz6DdZ5XKZ\ny6v06MtTqDTgbQlD+tMsnV6tVit3zSIR7HQ6SKVSGI/H3Ec0HA7zaTmXyyGbzaLRaGA8HrOXZ2Nj\nQ1ryrSCapvG4sEajwU1h5q/b8Ja97ZCyiuviwokn8FntGbm6qJN/JBJBs9nkN2I8HqNarXJ7PhLP\nyWSCbDaLdDqN8/NzTua4Lp70odCEl1qtxn14V9FIhCn6kycNuZ4XT4p10uaO+jJXKpU37qdPdKPx\ne9eh3zCS+5dKSShuaTQaWTxzuRwntgWDQd5M1mo1lEqlGfEMBoNYX1/nZvCrktAhgA8SNCKPxuDp\ny+6om9SHcp1HRf//VWShxFP/JlAMhkYkRaPRNx4/Ho95hlyxWJwRz8PDQ1gsFvR6PXahUXP524Ay\nz0g85eS5+ugThgqFwhsJO4TeZfU+NcrvA7mDSZApgYiSkKjcqtFoIJfLodlscuG7z+ebKTHodDro\ndrsYj8ewWq188kwmk3LyXAH0axCdPNPpNF6+fAm/349QKMSTdCjb+n3vd93X5wXzfb5v2Vko8bwp\nSinYbDZ4vV4As28itZaiGBBNBqDFjoLe+oxE6h6kT8igmYfUTUN4vFitVoRCIWxtbaHZbPLA33kB\n1ReC08lQP7R9Pqaojznqu1bps14tFgs36rDZbG+Um5jNZhgMBtTrdXYD62m1WtzkYTwew2Qywe12\nc+tJl8vFXbMk23a5oaRGmttKczoPDw+xubnJeRrvM4SdDh60GaQ1sd1us8evUqng8PAQxWKRDxCr\nLpzACoin1WqFx+Ph+A/wWbchinl2u100Go2Zzi70vbQTC4fDfJnNZuTzeS5HKJfL0DRNxPORQ3XI\n29vb6HQ6MBgMaLfbaDab/Biq85w/Feobrc+Lk9PpZDeay+Xifst69yn1C6Uh1XS6BTDTi7ZSqfBV\nrVZRq9U4u5YS7MjlS0lIbrdbugqtEJPJBO12G9VqlefMHh0d4eDgADabjWuOaaLJ28STPGz9fh/t\ndpvHRdLKLaFXAAAgAElEQVS6SNfZ2RmKxeIbPclXOflsqcUTmPZn1AsnQY26Kc6Tz+dndv+UcBEI\nBJBMJrGxsYGtrS1sbW3BZrNx9xiz2QxN027N/SYsL3Ty3N7e5mbwuVzujceReNrtdm4BSUkZV3Xt\n8fl8vHGjPsrzg6jJVv1+PxwOx8wAYxJCg8GAcrnMJ+Lj42OcnJxwxxcST6vVyrEvOnm63W45ea4I\nFGcvl8tIp9N88jw4OEAkEuGxY+978hwOh3wAyWQybFf69nzUvo9KCedZRQFdavF8W5o1uXMjkQhy\nuRy7Y/Wn08FggEajgUKhwKcCmpxyfn6OTCaDYrGIRqPB2ZN6KMORGizfx1Bj4eEwm83w+/1IJBKc\nFGS1WpFIJPgx1OLM4XCweOozGq8ST5fLBa/XO3MKdLlcMydPi8XCdZ5vc9tS0pHFYkGz2USlUuHn\nQT/XZDJx9yOv18uN6ukeYsPLh16wJpMJWq0WisUizs/PZ9YwslvaIFEDGNqI0UmTQlXknqVEs4uL\nC1xcXCCTyaBer8+M4aNGMhT+stvtWF9fRyQS4c5VZGOrwFKL59ugGBHt5u12+xv9a/v9PqrV6oyx\ntFotWK1WpNNpZDIZ5HI5tNvtK122RqMRFotlZgqFsLrQBAryWjgcDoRCIZTLZX4MNdama35m7FXi\nqR9QQLY0Xz6gTxCiZDpaMPVt++x2O+cCFAoFXrT09klJInrxpK+LeC4/1INZL57NZnNmQhUdFCiW\nCXxWz07Z4eTFyOVy7KotlUrsqqWB6jRAgzLBXS4Xe1K2t7extrYGn8/HdrgqTWRWdrW3Wq1wu90Y\njUbs6qI3jRYdypakuFCz2US1WoXVauWMSiqBuSpLVz96R+Yfrj4WiwU+nw9utxuBQAChUAgbGxsz\nTRIMBsMbQkgXlZPMb7Lmp6FcN7aJHnMV9FjqSzuZTGZ61eobIJjNZjgcDh5MTCdP2fwtPySIrVYL\nhUKBxZMSxshbQfYyP9h6PB6jXq8jk8ng4uIC5+fnfGUyGU4Y6nQ6M41o9PF8l8uFtbU1bG1tYXt7\nG7FYjNfgZZ/hqWdl/1rINTUej+H3+xEMBhEOh7mAnZrN00XtywBwBxeq3SQoQ5fccPF4HJubm3jy\n5Ani8Tg8Hs/KGIbwJpQMpO9oZTabOdubHqMXTEoWolOdPvP2rp4jnSpolmiz2WRPDE12SSQSSCQS\n2NzcRDAYlJm0KwCJYL/f52zwbDbLCWOapqFSqeD169f4zd/8zZkSFRLPyWTCjUDy+Txf1MeZuhTp\nQxLkfbPb7bDZbDy/dn19HRsbG4hEIrDb7fx3syp2ttLiabPZoGkaD2NNJBLcb1SfrQiA60BpF0U+\nfGC26xFlRno8HmxtbeHZs2f44he/iLW1NXbpCavLfAcsinHqv35dqcp9u0Q9Hg8SiQSMRiMikQi2\nt7dRrVbhcrl4iko4HOYJQcLyQqdAyoxtNBool8vI5XJc16tpGgqFAj7++GPUarU3BrLTReI7f/X7\nfQ5XUE4JzTamNZFCZdTdKhQKwe/3w2azrZRwAo9API1GI4tnPB5n/7y+vAAAnz4pMYh2YQTt6Mnd\nFY1Gsbm5iWfPnuELX/gCJ3Ksij9fuB4SSNp9z2cXzrtdH2rRcLvdMBgM8Pl8HJvSL4BOp5NPC9JV\naLkhd+1wOESv1+OTZy6Xmwk75fN51Go1HBwcvGGXZMf0+PmLNooul4vXQLqokxWJJfVhpr7fFDJY\nJVZWPGmBU0rB4/EgFovh6dOnLIKDwYAbKFAsgAqC6fRJpweKXzkcDiSTSb7IXev3+yXm+QjQv7f6\nE+iiQq5Yq9U6M8tTX4dKcVjxmCw/tLbR2DByp5IHjVy6dDLVo2/UQbkcVJtMIQi73Y5QKPTGFQwG\nEQgEuKMV1So7HI6VjqOv7CvTJ2B4PB4kk0mORymlMBgMeFQTnTj1Y6X0xkd1d1Qgv7Ozw1lkkUhk\npgBeEBYFWkQpVksbRPq8PrtWNn3LDa13tDEi13wkEkGr1UKz2Xxrb29qGOPz+bgygTZeVEbl8/lm\n+iU7nU4un6LSFEpOe1f96Cqw0uJJSR0ej4dF1Gw2s09/Mpmg0Wjw4wBw9hgZodvtZpdvMpnkeYnP\nnj3jnRoZyqobi7A8kOeFFlR9y7Sr3MrCcqP3tNG6ReEqo9HIfbiva5tHmeSJRIITH41GIxwOB9bW\n1rC2toZoNMqx8kAgMOOd0190+l31w8RKiyd9tFqtXPtG8YDBYAC32801S1ToS52EfD4ffD4fAoEA\n4vE44vE4EokEtre3sb6+jrW1tYd8eYLwTmRD97jQd04LBoPY2triJgflchmVSuWNvrNkH36/H7FY\nDLFYjMWTYpzRaJRH21FtsD7D/LGysuKph3bfABAMBrG7uwuHw4FEIsEFwJVKhbPKALBgxmIxBAIB\n3m2FQiG43e6HfDmCIAhvQEJoNpsRjUbx0Ucfwefzod1u83XdydPhcMwk+dDGi0qcqPMVNToQHpl4\nGo1GBAIB2O12xGIxlMtlXFxcIJ1OcxZatVqFwWDAkydP8OTJE2xsbHCjbvLn22y2h35JgiAIb0CC\nt7a2Bo/Hg+3tbc7leNu8WKpHpvwNEmJqQUq1ylc1+XisPIrfAsUDgM+aJwDTVH5K2/f5fKjVaqjX\n6zAYDNjZ2cHu7i6SyeRM0bsgCMKioXfPG41GPikKd8ejEM/rsFgs8Hq90DQNTqeTi4mVUohEIjzZ\ngrISBUEQBAF45OJJrdWofolcG5RcpJ9vKIkXgiAIAvGoxZNq3ciNKwiCIAjvg/giBUEQBOGGiHgK\ngiAIwg0R8RQEQRCEGyLiKQiCIAg3RMRTEARBEG6IiKcgCIIg3BART0EQBEG4ISKegiAIgnBDRDwF\nQRAE4YbcRYchGwC8ePHiDm79eNH9PmWky+dD7PMOEPu8FcQ274i7sE913Xy3D76hUj8O4Jdu9aaC\nnp/QNO2XH/pJLCtin3eO2OcHIrZ5L9yafd6FeAYBfBNACkDvVm/+uLEB2ALwq5qmlR/4uSwtYp93\nhtjn50Rs8065dfu8dfEUBEEQhFVHEoYEQRAE4YaIeAqCIAjCDRHxFARBEIQbIuIpCIIgCDdExFMQ\nBEEQboiI5wOjlNpTSk2UUs8e+rkIwjxin8Ii85D2+d7iefkEx5cf56+xUupn7/KJvudztF7z3H70\nhvf527rv7SulXiml/sO7et4APqheSCn1ryqlvq+U6imlskqp/+S2n9iysAz2qUcpFVFK5S+fm+WG\n3yv2uWQsg30qpaJKqV9VSmUu37NTpdR/rpRy3PA+C22fSqmvXT7Hc6VUWyn1iVLqp2/6Q2/Snm9N\n9+8fA/DnATwDoC4/17rmiRo1TRvf9Il9Tn4MwP+l+3/1ht+vAfhfAfzrAOwAfhTAzyulupqm/Zfz\nD1ZKGQBo2j0WzSql/iyAfw3Anwbw/wFwAVi/r5+/gCyTfQLAfwfgnwL4kQ/4XrHP5WMZ7HMM4H8B\n8B8AKGP6/P46ADeAP36D+yy6ff4OABcA/qXLj78LwH+rlOprmvY33/sumqbd+ALwRwFUrvj8NwFM\nAPxzAL4DoA/gGwD+RwC/PPfY/wbA/677vwHAzwI4AdDG9A/uR2/4vKyXP//3fcjr0t3nquf7jwH8\no8t//wkAWQD/PICXAAYAIpdf++nLz3UB/ADAH5+7zw8D+Pjy678B4A9jarTPbvD8wph2IPlnPs/r\nXNVrUe1Td69/B8CvAPj9l++9Rezz8VyLbp9zP+fPAHi1SvZ5zXP+RQB//ybfc1cxz78I4N8GsA/g\n1Xt+z58H8C8A+FcAfAHAfw3gf1JKfYMecOn6+fff416/qJQqKKV+Qyn1rZs99WvpAiD3mgbAB+Bn\nAPwkgC8BqCqlfgrTXdufBvAcU2P+OaXUv3j5/D0A/h6mJ46vYvp7+qvzP+g9Xufvv3w++0qpl0qp\nM6XULyulYp//ZT4KHsw+lVJfBvDvYbqA3uZOW+xzdXjo9ZMenwTwhzDrxftQFsk+r8ILoHKTb7iL\nqSoagP9I07R/TJ9QSr3l4YBSyonpgvI7NU37+PLTf0Mp9bsxdf38v5efO8DUnXAdYwB/FtM3u4ep\nS+xvKKVsmqb94o1fyfS5qcv7/B4Af0n3JQumu6LXusf+xwD+pKZpf//yU6dKqa9g6r74nwH8scvn\n9Sc0TRsBeKmU2gHwn8392He9zh1M3SH/LqY7tQ6AvwLgV5RSX9U0bfIBL/Wx8GD2qZSyA/hlAH9K\n07T8u37u+yD2uXI85PpJ9/s7mG6AbJi6cf/Nm72EmXston3OP8ffjalr+fe+9wvD3YgnMHUZ3IQ9\nTN+oX1OzlmLG9GgOANA07Xe97SaXv9C/rPvUd5VSPkxdDzcVzz+slPqDl88BAP57THc6RGvujfcD\nSAD49pyxGwHkLv/9HMB3Lp8n8RuY412vE1MXjRlTI/onlz//xzH13/8wgF97x/c/dh7EPgH8pwB+\nU9O0v3v5fzX38SaIfa4uD2WfxE9jehLbx3Q9/SuYivNNWGT7ZJRSXwXwdzDdsPzf7/t9wN2JZ3vu\n/xO8mdlr1v3bhemO6/fizR3D550u8JuY7oBvyq8A+Lcw9cdntEvHuI751+i+/PgvY+qT10NvtsLt\nuOqylx95SJ2maRmlVAPAxi3cf9V5KPv8PQCeKKV+8vL/6vJqKqV+VtO0v3z9t76B2Ofq8qDrp6Zp\neQB5AAdKqRaAf6CU+guaptVucJtFts/pzaYhlH8A4K9qmjZ/en0ndyWe8xQBfGXuc18BULj89/cx\n/QVtaJr2T2/5Z38VU0O4KS1N005u8PhzACUAO7qTxTyfAvjRuQy63/kBz+2fXH7cw+XOSym1BsAD\n4PQD7vfYuS/7/AOYJrUR/yymiR+U/XcTxD4fDw+5fhovP96onAqLbZ+4dAf/HwB+QdO0v/Sux1/F\nfTVJ+D8B/LBS6o8opZ4qpf4igCf0RU3TqgB+HsAvKKV+Qim1c1mL8zNKqR+jxymlfu0yqHwlSqk/\npJT6Y0qpj5RST5RSfwpTd8PP391L49egYRq0/1ml1E9fvs4vKaV+SilFMYP/AVP3yl9XSj1X0/rT\nn7nidbz1dWqa9n1Md0y/oJT6hlLqS5iWPvw2Plu4hPfnXuxT07QjTdM+pQufCckL7Y5nYIp9LjX3\ntX7+QaXUT16un5uX7/9fA/APNU0rXPd9t8F92uelcP5DAH8X0xKV6OUVvMlzvhfx1DTt7wH4OQD/\nBaY7UYVpOrP+MX/m8jF/DtMdxv8G4PdhOhiW2AXwthc4wjRL7f/BNG7wRwH8tKZpP0cPUJ91pPjG\nNff4YDRN+68A/ElMg/Tfw9TofxzT9HFomlbHNDD9OzBNRf9zmGaXzfOu1wlMa8W+j6l75B9hWsv6\nB65wjwjv4B7t852IfQrz3KN99gH8G5hucH6Aaazzb2OaxQtgZezzjwDwA/gpABnddaNY/KMbhq2U\n+hEAfwvArqZp8353QXhQxD6FRUbs8zMeY2/bHwHwFx77Gy8sLGKfwiIj9nnJozt5CoIgCMLn5TGe\nPAVBEAThcyHiKQiCIAg3RMRTEARBEG7IrTdJuKyV+SamKdKftzuQ8Bk2AFsAfvWuawJXGbHPO0Ps\n83Mitnmn3Lp93kWHoW8C+KU7uK8w5ScwbS4ufBhin3eL2OeHI7Z599yafd6FeKYA4Nvf/jb29/fv\n4PaPkxcvXuBb3/oWMFv0LNycFCD2eduIfd4KKUBs8y64C/u8C/HsAcD+/j6+9rWv3cHtHz3izvl8\niH3eLWKfH47Y5t1za/YpCUOCIAiCcENEPAVBEAThhoh4CoIgCMINEfEUBEEQhBsi4ikIgiAIN0TE\nUxAEQRBuiIinIAiCINwQEU9BEARBuCEinoIgCIJwQ0Q8BUEQBOGGiHgKgiAIwg0R8RQEQRCEGyLi\nKQiCIAg35C6mqiwck8mEr/F4jOFwiNFohNFoNPO1yWQCTdOgaRoAQCk1c495zGYzTCYTzGYzLBYL\nLBYLzGYzDAbZkwiCsLrQGknQmjocDmeu+bWU1lej0Qir1QqbzQaLxQKj0QiDwQCDwcCP0TSN1+nx\neAyj0Qiz2Qyz2TyzNuv/fZ88CvEcjUYYDAbo9/totVqo1Wqo1Wpot9vo9Xro9Xro9/sYDocYDAYY\nj8cwGAwwGo1QSvGbNx6PZ+7r9/v5CoVCfIl4CoLwGCCR06+r1WoVlUoFlUoFw+EQRqMRRqMRmqbx\nOmq1WpFIJJBIJBCNRmGz2WC322G1WmcOOM1mE61WC81mE06nk9dbi8Xy0C/9cYjneDxGr9dDq9VC\nsVjExcUF0uk0yuUyGo0Gv0GdTgedTgfD4ZBPlEopDAYDDAYDDIdDvqdSCuvr63zt7OzAaDTC7/fD\nZHoUv1ZBEB4xmqaxt67ZbCKXyyGdTuPs7AypVAqnp6fo9/u8lmqaxgcUt9uNL3/5y+j3+zCbzfB4\nPHwapcNOr9dDpVJBoVBAPp9HMBgEALhcrjdOnw/Byq7yehdst9tFrVZDuVzGxcUFTk5OcHJyglwu\nh1qthnq9jkajgVarhVarheFwyC5Zo9GIfr+Pfr+PwWAw8zOePHmCWq2GTqcDq9WKQCDAwquU4kt4\nnMy7tvTuKAohjMdjftz84/Uopdi1RR6ReRsTWxPukqtctbQulkolZDIZpFIpnJyc4Pj4GMfHxxgM\nBrDZbLDZbJhMJmi322i32/B4PPB6vYjH41hfX2fRnEwm6Ha7qNfrqNfryGQyfHW7XbjdbkSjUdjt\ndgAPa/MrK5509B8MBsjn8zg7O8Pp6SkuLi5wcXGBTCaDSqXCp81ut4ter8cuWmAqwHq37Ty9Xg+1\nWg35fB6lUgn1eh2dTgcGgwEmk4lFVHjc0KKjj7XTRq3VavGioY+3z2M2m+F0OuF0OmG32znGThs8\ng8EgtibcG5PJBNVqFaVSCcViEZlMBtlsFtlsFoPBAH6/H8+fP4fFYoHX64XX68VwOEQul0M2m4XZ\nbEY4HIbX64XD4eCTab/fRzabRSqVQiqVQrlcZhcwAEQiEXS7XTgcDnYHS8zzlhmNRuj1euh0Osjn\n83j9+jV+8IMf4OLiAsViEcVikRcuWtToJKBPLgI+Sziah8TTZDKhWCxyHNVsNgMAjEbjvb5mYfHQ\nnyrJJnu9Hi86hUIB/X4f4/EYo9HoWvG02+0cU/f5fHA4HHA4HLDb7dA0DSaTSWLtwr1AnpNarYZU\nKoWjoyOUSiVUKhWUy2VYLBb4/X6sr68jEAggEokgEomg1+vh8PAQBwcHGAwGiEQibMu0Zvb7feRy\nOXz66af47d/+7Zlwms1mw+bmJjqdDjweDwA8qM2vlHjqF57BYIBms4larYZMJoPj42P84Ac/QCaT\nYZfAvBt2nqtOm3p6vR4ajQYmkwnK5TKq1Srq9TosFguUUgsR1BbuHr07dt41q3fPksuq3W4jk8kg\nnU7j4uIC3W6XT6TXiafT6UQ8HmcvidvthsfjgcvlgtVq5YtOoCKkwm2gt0faAI7HY/T7fZRKJVxc\nXODw8BCtVottOxKJIBQKYWNjA4lEAvF4HPF4HO12GxaLBePxGI1GA6FQCF6vFzabDZqmodfrYTAY\nIJ1O49WrV/jOd77Da7BSCo1GA91uF8PhkLNv3xbquGtWSjz1JSelUomP/q9fv8bJyQlKpRKazSZ6\nvd6VJ0k9+tgSLYDzb9RoNEK324WmaSiXy8jlcjg/P8dkMkEkEoHdbpfkoUeApmmcVDYYDNDtdvmi\nXXOn00Gj0eCLXFGVSgWDweBaGyNsNhtyuRz8fj+8Xi/cbjfcbje8Xi+fSAOBAJ9IHQ7HPf8WhFWF\n1tThcIhSqTTjqi2Xy9A0DW63Gz6fDyaTCeFwGPF4HLFYjD0llEXr9/sRj8fh9XoRDofhdrthMBhQ\nKBRQKBSQy+Xw8uVLFItFjEYjrmQIh8PY39/H+vo63G43zGbzg7psgRUTT0qFHo1GKJVKODo6wne/\n+12cnZ3xG00JQW8TT0rOIFcYnQjmT6IknsPhEJVKBfl8Hufn5zCbzbDb7QgEAnf9koUFYDKZYDAY\noN1uz6Ts12o1VCoVTt2vVqucyt/pdNDr9dDtdlk032aTJpMJNpsNVqsVDoeDxdPv92Nrawvb29vY\n2NhAIBCAwWAQ8RRuBX1yW7fbRTab5cMI5YmQeFIZSTgcRjgcRiQSgdvtZrsdj8fw+XyIxWLo9XoI\nhUJwuVwwGAwol8t4+fIlXrx4gWw2i0KhgNFoBK/Xi93dXezv72NzcxPr6+twuVywWCxcF/pQrJR4\n6pOEyuUyjo+P8d3vfhfZbJZ3/KPRaOZ79JmKdFExLhXv9vt9KKVmXHIA2NXW7/dRrVaRz+dxcXEB\nl8uFYDD4ztOtsLzM20G320Wj0UC1WuXU+nw+j1wuxx/1yQ+apt0oS1YfOzWZTJw8FAwGUa/XMRqN\n2I1ltVrh8XiuzMgVhJsymUzYxvP5PA4ODvD973+fazPtdjs8Hg/i8Tg2NjYQCoXg9/sRCARmQlck\nnuPxmJOKnE4nNE1DpVLB4eEhfuu3fovzAgAgEAhgd3cXX//61xGJRDhUQTHSh2SlxJNikPV6Hfl8\nHuVymTNgB4PBGy4xi8UCl8sFp9MJl8sFt9sNl8vFAWx642nBq1arfLpot9sz96JkkGazyT9PxHN1\noYzZdruNRqPBSWj6i8IEVAZFdcAulwsulwsejwdut5s9HPMipw9D6N3BFBsaDAao1+u4uLjgmFA8\nHuc4UyAQ4EvEU/gQKFbfarU4KajZbKLf78Pv92NtbQ1ra2uIRqMc66TT5vyp0Gg0wm63w+fzod/v\nw2g0ckiD7gkAPp+Py1uePXuGZDLJQkv5JIvAyoknnQBJPCkD9ipXrcVigc/nQyQSQTQaZUMIBALc\nBmo0GuHi4gLn5+e4uLhAoVDgeiU9tDPTi+dDBrOFu2U4HKJer6NYLCKXy82k6pfLZV5oKFloPB7D\n4XDA5/PBbrcjFotxIoXNZrsy7V7faaXdbvMGrlQqsY3X63UAQLPZRDabRTweRyaTQSKRwO7uLoBp\nJyxB+BDG4zE6nQ57VKrVKlqtFvr9Pmw2G9bW1vD8+XP4fD74fD5OALpK5IxGI5eY9Pt9roaoVCpo\ntVqcwOnz+Xgt3t3dRSKRgM/ng9PpXKis8pUSz263i2q1imw2O3PynBc6glKqk8kkdnZ28OTJE+zu\n7iIWi3GThMFggJcvX8Lj8cBkMnErqmKxOHOv4XAo4vmIGI1GXMR9cnLCdcTn5+fsqajX6xzvsdls\ncLlcvDA8ffoUe3t72Nvbg8vl4rpg/cJAIYF+v89Z41SIPhqNUCwWUa/X0Ww2kU6nYTabkUwmWciB\nqXBub29L2ZTwQZB4UqcfOnn2ej0Wz729PTidTj4tXidudPK02+3o9XoYDod87/mT59bWFp4/f45Y\nLIZYLAafz7cQrlo9KyWe/X6fXWj1eh3dbveN06Y+nhkKhRCPx7G5uYnNzU3EYjEEg0F4PJ6ZJsWT\nyQSdToe7Cenb9BGUvt1qtTiJSMRztaC2YYPBAMViEWdnZzg4OMDR0RFnC7bbbdjtdqyvr2Nra4sL\nxL1eLwKBACdVkHuVdurXnTxNJhMnRwDgOBM14nA6nRyq6Ha7aLVaKJfL3D6yVCqhVqvBbrez3S+K\n20tYfKilXqfT4UOIw+FAMBiEz+eDy+Xiph36zmpXQbFT8tqkUinuRERePaqEMJlMcDgcsNls77zv\nQ7Gy4lmr1biMRA+9KQ6HA6FQCLFYDFtbW9ja2kIkEuGYFH1fv9/n+Ba5LK6qD6WYZ7vdZvGUmOdq\nQbtw6uN5enqKg4MDHB4ecn9kKv6mbMNoNMqXvoyE2pNR2v1VtZmapsFsNmMymfDplVxjJpOJM2/P\nzs4wHo85Bkv9mKnzVbVaxWQy4Vj+oi1CwuJCZVhUdgWA104ST/1klLfZ1mQyQb/fR7fbRblcxsnJ\nCT7++GO8fPmScwN6vR7XcFKj+EXt1LbS4nlVPSe9KVQfl0gkWDzphGC32zlOZTKZOOZECUNXiaec\nPFef0WjEHoh8Po/T01O8evUKr169YnuxWCxwOBzY3NzE8+fP2auxubnJp0taZOZT7a9aIPRZtj6f\nD5qmIRKJwGq1wm63w2azYTweo1wus532+300m80Z8aTSKylhEW4C1XfqxdPpdHL83u12w263v1dY\ngMSz3W6zeH7ve9/Dxx9/zH8PVNJCtvo+ovxQrJR4Um1lIpFAq9VCpVK5cjdPDY3148goqaher8Ng\nMHDD42q1iqOjI2SzWc7cvcpta7FY4Ha7uWsGudaE1aHX6yGTyeD169d49eoVTk5OUC6XMRgM+ERJ\ndZc7OzvY3d1FNBpFMBiE0+mcyah938XgqseRnZNXpFwuc7IS1eRRrJTsnLqyyIZOeBd0CKDcjlQq\nhXQ6jUqlAo/Hg3A4DJ/Ph3g8zk0O3seeKTuc6uELhQJqtRpn7gYCAYTDYWxubiIajcLj8bCALiIr\nJZ4ulwvRaJRLRnK53BsdfmhhabfbM7PiqtUq++MHgwGnUFerVbx69Yrb+g0GgzdqRQHAarVyMggt\nlpKksVp0Oh1cXFzg448/xqeffopsNotqtcpF4tFoFMlkEk+ePMHOzg62tra4/OmqUpQPxWg0wuPx\nsBBmMhmEw2H4/f6ZchayZRqn9652k4IATMWzWCwinU5zC8l0Oo1GowGfz4doNIqdnR0Eg0F4vd73\nvu9wOEStVuOxZcVikeOolNhGiZuUJGSz2RY21LBy4rm2tgaTyYRCoYCjoyM+8tNCQ+I5mUzQbDZZ\nQKkvLSVf0Neq1SrS6TSL53WTLygeRS2p6KQhrA6dTgfn5+f4+OOP8b3vfY89F1arFS6XC4lEAs+e\nPcOTJ09YQKnN423agslk4l251WrF2dkZx+sp3kmdtsjLQjF4OXkK76LX66FQKHAnoUKhgGKxiPF4\njPn+iWkAACAASURBVKdPn2JtbQ0fffQRl/O9r7CRJ+/i4gKnp6csnkopFs8vf/nLWF9f5xZ++vF7\ni8ZKiae+swr1+qSOFrQL17fZazabyGQycLvdyOfzM2Labrc5OYTqkN62c7dareK2XXFoqDptsCjO\nabVauSUjNd2geORdoJTiUWT0c6xW60zGo745/XxnLEGYRz+bM5/P8+kwl8tBKcWt9tbX12cOB1eJ\nmt7mqJaTvDZHR0c4Pj5GOp1Gv9/nhiHJZBIbGxvY3NzkRguLVNN5FSslnjTz0Gg0IhAIIBgMIhQK\ncSYizU3UTz8/OztDr9fj2iP94GuaZk51m2+DuhWRK+Nt9U7C8qKfkqJPRqO2jvc1W1Pf2o8Sj27T\nNSw8LigeWavVeObx+fk5qtUqJ7xtbGxgfX0dwWDwrbam7zFer9eRy+WQy+WQSqXw6tUrHB4eolAo\nwGq1ctYu9WaOx+Nc/rLodrxS4kk7b0qoIPGkIdedTocXPmpn1uv1kMvlYDAYZtqh6UdK6Wd7XofZ\nbIbb7RbxXGH0TbL1cW+9gNGJ8D7+8Onn6n++iKfwIeiTeUg4z8/PMRgM8NFHH2Fvbw9f+cpXODHu\nbWubvp6z0Wjg4uICBwcHeP36Ndd1ttttFuLt7e0Z8aRN6KKzUuKpT/33+/3Y2NjAF77wBfj9fh6j\nQx2AqOSEapg+xKVF6f+UwOHz+bjJgrhtVw+z2Qyv14u1tbWZ0hOPx4OtrS3E43EEg0G43e47zxCk\nky9l01KiEIm6xWKBzWaDw+HgnfyiJl4ID4N+zet2uyiVStwtq91ucyw/FArxQOvr4vfURnI4HHIy\nZrPZZFftyckJcrkcdyZyOBycXPfkyRMW0mUqpVop8dQTCATw9OlTWK1WFItFlMtllMtl9udTAhAl\nfVyVQfsuLBYLt5vSn3Tl5Lma6Ht5UrIOxdmTySTW19eRSCQQDAZht9vv7HlQ7d1gMOBscXK5DQYD\nKKVm2gGSoFutVhFPYQYS0E6ng1wuh8PDQ2SzWSiluOMalaRcF5LQNI0rGNrtNs/lzOVyXEKVy+XQ\nbre5QYjP52Ph3Nra4tmey8TKiqff74fVakU8Hp+Zq3h8fAyn08kT0amDxodgsVjgdDrh9XoRDAZZ\nPD0ez61nWAoPj76XZzgchsPhgNPpZHd9MBjkgdR3KZ6aps10tKIEplqtxt4XSl4i8aQZiCKewjzU\nfjSXy+Hg4ADVahXr6+tIJpPctpTE8yrhBD5rUFOpVHB2dsYu2kKhwPZJ63E8Hsf6+jr3Ek8mk7wR\nXSZWVjwpA5Hamfn9fjQaDRiNRu4BqmkajEbjG4lEb3PhkvEYDAaepxiNRrlwmE4kwupBCQ47OzuI\nRCIsnnRRpi2l8N8V+l7L1E2LmnXrn4vf74fH4+Gm3YvaqUV4GCj/g9qP1ut1lMtldDodmEwmRCIR\nrK+vw+/384QpWiP1FQzD4ZCn/OTzeZydneHk5AQnJyfodDowGAyw2WwIBoM8hIMSkKi0bxlZWfEE\nPhM6ysI1GAxsEN1ul2vwqPEB+ezfJZ4U6/J6vdwbNxaLcUN5YTWhEXbkpqLyENo10//v2utAi12h\nUEA6nUa5XEa73cZkMuEQAm3oaHDwfWQAC8vFeDzmhhrtdpvDV0ajkQ8GoVCI45DUXY1Ek06UNF2I\nmirow2R2ux2hUAjRaBSJRALr6+ssmn6//049NHfNSosnMBU7mkphtVq5exC5bGncE3W6mC9BmIcE\n12KxcPLIzs4Oi+cyZIkJH4bZbGbvwmQyYRcpiaU+JnSX4jkej7l37cXFBZ8WNE2b2eHr6+Xk1CnM\nQ65/qm2npuzkVQuFQgiHwzAajdA0baZ7VafTQT6f59gmjeQ7PT3lZMzhcIhEIgG/34+9vT1eJ2lQ\nO208l5WVFU/9QqFPfdbHgcrlMrvZ3ifNXynFAW+Px8Njp7a3txGNRmfasAmrB83cfIiMQL2brFKp\nIJvN8oJVq9UAAB6Phz0rNJdWn+ghCHqopETfwnE0GkEpxafRer0+k0mr7wlOCUEknnTRVBSTyQSz\n2YxgMIjNzU3s7u4iFApxAtuys7LieR36Al69C4J6f77t1Gk0GhEOh7G1tcXGsLu7i42NDQQCARZP\nQbhthsMhD9lOp9N49eoVXr58iZOTEwwGA3i9Xvh8Pjx79gz7+/t4/vw51tbW4PV6ZTMnXMn8ZB/9\nBJVUKgWn04lMJjMzQINCWpPJBI1GY6Yr23A4hFIKZrOZB2P7/X4Eg0FEIhGEQiEOI6wCj1I89UW8\ntOuifqBvi3caDAaEw2E8f/4cX/3qVxGPx9kNQTPtZKES7oLBYIByuYyzszMcHR3h5cuXePHiBdLp\nNMemIpEI9vb2sL+/j48++ui9CtqFxwt52shbRuJJg6r7/T6cTidPWOl2u7BYLLBYLDxnlg4cNMuW\nwmSUTEfiGQ6HEQwGYTab3xjWsaysxqt4B5RVRm366vU6KpUKarUaWq0Wj3a6rnE2uX2dTicikQi2\nt7fxxS9+EYFAgEfpyAIl3Db6DleUIHRycoKDgwOcnJxwshC5wqgZ/ebmJtbX16XbkPBWKPmRYo92\nux0Oh4Ozt0ejEQwGA9dvDgYDuN1uuN1uOJ3OGdsij51ePMkbQtcquGr1PArxpOHAzWYTp6enODg4\nwIsXL7jrRafTubZMxWg0cvPiQCCAWCyGSCTCtXNSeC7cFaPRiIcQZ7NZpFIpbnNWLpehaRq8Xi8i\nkQiHEdbW1uByucQmhXdiMplgs9l4kMbGxgb29/fhdrvZM0cZ3OFwGBaLhZOI/H4/ms0mu24NBgNn\n4JpMJj510pCMVUykfBTi2ev1UK1Weef+6tUrfPLJJ7i4uOB2fdedOg0GA1wuF8LhMBf4kniazeaF\nHdQqLD9UklKr1ZDJZLix9uvXr9levV4votEoNjY28OTJEwQCAbjdbhFP4Z0YjUbYbDaYTCYeQt1u\nt+F0Ojm+TqdNj8cDv9+PZDKJZDKJtbW1mVmfJJwU83Q6nTzVSsRzydD745vNJgqFAs7OznB8fIyj\noyO8fv0ahUJhpjmCfjoFxQEo9T+RSGBrawuJRALhcJiHwMoiJdwm+qktrVYLlUrljWbd+XyeXWLR\naJQ7tmxsbHCihtil8C4oHGWxWFgYR6MR7HY7MpkMTCYTut0uIpEIwuEwotEo29na2hrMZjPP6KSc\nDxrM4fP5Zjx0qxLn1LN6r+iSTqfDfT/1okkto7rd7oyrllwNTqfzjb6lm5ubnGG7tbUFv98PQIRT\nuH263S4XnhcKBd7Z03goq9WKRCKBZDKJRCKBzc1N7O3tIRqNwmazcdmVINwEq9WKQCCA8XgMh8PB\noYDBYMCleRSm6nQ6OD09xcnJCV6/fs0t/YbDIVwuF6LRKLa2trC/v4+dnR2Ew+Glrue8jpUVT5oS\nkM/ncXR0hIODA7x69QqZTAalUgm9Xm/GVWsymbhHKbm+6P/b29vY3d3F5uYmvF6vpP8Ld0av10Ox\nWORhxKlUCqlUCqVSCYPBAFarFX6/H8+ePcPe3h6ePHmCtbU1RCIRbsEn4incFBJPm83GYxypaQJ1\nzjIYDKjVaqjX66hWqyyer169AvBZfohePJPJJDwej4jnoqM/SVJ2YiqV4t3Ry5cvUalU3qhZAqbd\nYzweD9bW1hCLxRAIBBAIBBCJRLiec3Nz8wFfnbBK6G1PPzuWOgcdHx9zc+2TkxO02234/X52r9F8\nxb29PdhsNtjtdthstgd8RcIyQ542n8838/n5sWX9fh/pdJo3ddTDlhrP+P1+Htn39OlTRCKRO++4\n9VCslHh2u11Oq6Yd0f/f3psHt7Zl9f2fbU3WbEnWYMmz77Xvfa/fyOuudCUVaEiAzi90EiCQNJAB\nKIZiyEgSEqpDQ9L80pCEUA2BVCCEH4GmqMoAhAqQUEVB0kBDuvv1u+PzPNuSJ1mjNZzfH9La91jX\nd9C99vWg/ak6dX1l6egca2mvvdde67vu3bvH8vIy6+vruhZJ6jntOrXSVurmzZtMTEzoTXKJ3V+m\nPnOGi4+9yfrh4SH7+/vs7++zurrK7Owsc3NzbG1tUSgUdPceEdMeHx/XbZxkr+kqJmQYzh8RlZE9\neInkScJloVDA6XQyODioW4zdvHmToaEhvfd+VaN0V8p5lkol3fR6dnaW27dv8/nPf143we50nn19\nfTidTtxuN6FQiEwmw82bN5mZmdFtpaSZsHGehtNECtLr9bpu42QP0y4uLuqBye12k0gkuHbtGi+/\n/DJTU1MMDAwQiURMqNZwpkj7O+kdu7m5qZ1noVCgWCzicrmIx+Ncu3aN9773vTqhSMr4jPO8gHSW\nlojzXFlZ0c7zs5/9LIVC4cTXK6X04BQOh/XK89VXX9VlKFcxS8xw/ojKVaVSYWdnh4WFBd555x3m\n5+d1Vi1AMpkkmUxq5/nGG28wPT19JoPS49S1hKs6EBqOI7ZgWRa1Wk0LyMvK89atW1rrWZzn9evX\neeuttxgcHNRZ31d5UnfpPUOpVNKHZNPOz8+ztLTE3t4e9Xr9ka+VFlPRaJRMJkMsFsPn8+FyuUwX\nCsOZsr+/z8bGBhsbGywsLPDuu++ysLBANpulWq3qfUwpD8hkMoTDYZxOp26bJwOciHA/b+hW9l7t\nobpGowGge5SayeTVxz6JqlQqup5zYWGBxcVFKpWKbkIgx2uvvcb4+Lhuut4L4+el/iZYlkWxWCSX\ny7Gzs8P8/Dz379/n/v37rK+vs7e3p7/8J+FyuXRPTnGefr8fp9NpuqMYzpSDgwMWFha4desWS0tL\nuo6zXC5jWZbOfhTnOTw8TDgcxuFw6CYGsv0g4bHTcp6dus8APp9PR2oMvYFlWdp5vv3229y+fZut\nrS3K5TLhcJjx8XFu3LjBzMwMo6OjjIyMGOd5WRDnmc1mWVlZ0c7z9u3bHBwc6L6dj0JWnul0mkwm\nQzQa1StPg+Es2d/fZ35+nj/6oz9iZWWFXC5HLpfD4XAcU3RJpVJ65TkwMKBXnnJI4ttpODVZcUrr\nKenfCA80Sw29gUQ2xHl+7nOf44//+I+Bli2EQiHGx8d58803ef/7308wGNQ5Ilc5VGvn0jlP2cBu\nNBpUq1W2t7dZWlri3r17LCwssLW1RT6fp1Kp6MHFjsPh0CGoWCxGOp3WAggSq7/qMybDi0EGIDlE\nX/nw8JD79++zvLzM1tYWe3t7FItFrSVarVYpFou6i4plWezu7hKJRLTcmbTVkwbYXq9X19I9ae/S\n3sTb5XLpMgWRWMvn8xSLRd270ev1MjExwcTEBH6//0X86QznSK1W01ULKysrbG5u6hI/KeVLp9O8\n9NJLjI6OEg6HtUDHVU4Q6uTSOk9p1ip6tbdu3WJ7e5tsNkupVHpkizGHw6FnSIODg2QyGSYmJhgb\nGyMWi5laOcOpIqu5ZrPJzs6O3j+6c+cOS0tL5HI5Dg8PqVarer+xXC5r2z06OiKXy2mFF1F5sctK\nShG7RExOanBgR5I8XC4XgUBAK8hUKhW2trbY3t7WTZCPjo6IRqM0m03dGMFwtRHJPamTlwVJs9kk\nkUjwyiuv8Oqrr5JMJkmlUni9Xr3n3iuOEy6p85SGrfl8ns3NTe08C4WCTh56lNC7aC+Gw2Hi8TiZ\nTIbJyUnGx8dNobnh1JFaznq9rvflb9++zdzcHMvLy2SzWS0VKW2dRMRD9vPtK0SZ4dsdpDhDh8Nx\nLOnnUbjdbp0NKUIg8XicUqmky2R2d3f1vmo6nSYajTIzM/NC/maG80Wc5+rqqnaeBwcHNBoN4vE4\nr732Gl/8xV+ss21ly6CXHCdcQufZaDR0pqJ8uJubm+zv71OtVvWK045kI0qoVnRBp6en9YrT7/cb\nXVDDqSMTvXK5TDabZXV1lbm5Ofb29ujr6yOZTGJZlhbreNQA1NfX91DGqzzXnhlrd572Q15rb2Is\nraSkl2OpVDoWWpY61EAgQLlcfmzmuuFyI0litVqNXC6nxTpE3SoQCOD3+0kmk0SjUUKh0Hlf8rlz\nKZ1nLpdjdnaWO3fu6O4o8uU+KUHI6XTi8/nw+Xyk02lu3LjBjRs3mJycZGRkhHA4rGfuxnkaTgsJ\nu0oD9q2tLS1tJs3VRSVI9i0fZX+yR9n5r0hRSsG6fUVq7ywkTQ8CgQD5fJ6dnR12dnao1+t64JQ9\nVPv128/xNHWghstJvV6nWCxqIQTJI1ldXcXpdBKLxRgYGCCVSpl97zaX0nnu7OwwOzvLZz/7WTY3\nN9ne3n5I6N2OOM9wOEw6nWZmZoa33nqLsbExvY8kmYS9FnownC3VavVYa7G1tTWWlpZIJBIMDg4y\nMTGhGxGEQqHHZs1KMoYoYzmdTprNJtlslmw2y+7uLvAgYUjCxY1GQ+viRqNRNjY29PdIVhvyvGaz\nqd/HXu9pnOfVRpKE9vb2tPO8f/8+W1tbjI6OkkwmmZiYMM7TxqVwno1GQ9ecySC0sbHB2toa+/v7\nFIvFE1ecMgj4fD6i0ahO+0+n06RSqWMNrc2K03AWyH6l1+vVYhzXrl3TnScmJiaIRCK6i8/TlElJ\nTac4T9FgPjg4OObg7OFc6QY0MDBAIBDQe6iyqojFYhwdHel8ANkGqVarJBIJ0um0GTSvGDKmVqtV\ndnZ22NjYYH19XYt11Go13c9Ymq0nk0ljB20ujfMU8ezNzU02NjbIZrPs7e3pzNpO7E2tA4EAiUSC\niYkJRkdHGRwcxO/390wxr+H86O/v18pA169f1yLakrAWj8cJBoN6W+Fp6zXFti3LIhQKEY/HtcCC\nIKvFZrOJ1+vVh6hqjYyM6KYIwWCQWq3G3t6eLp2RwTUUCjEzM6P72BquBtVqlb29Pd2QQDqkbG5u\nks/n9aJjfHxci75Lc2vDJXKehUJBiyHYnaeEnTqxh7ekx9zExAQjIyPaefZaXZLhxaKUwuPx4HA4\ntGOU7hMej0c7zP7+fp1J+7QRkJNCq53RF7s+qSQk9fX1Ua1WGRkZoVQq0dfXp9+/0WhQKpV0jaeE\nc0W7tLNdleFyU6lU2NvbY319nbm5Oe7cucPdu3c5ODjQ++NDQ0OMjY0xNTXFtWvXcLvdV7I357Nw\nYZ2nPVmhVCqRzWZZXFzk/v37rK6u6qJde4q/HbfbrQenVCpFJpNhbGyMdDpNJBLRg5rBcJaIw5KJ\nmszmJZxrr7l8Udne9XqdYDBIvV5/aP9UVpsiASjPkVWr4epQLpfJ5XIsLS2xuLjI2toam5ubNJtN\nXQM/NTWl9zzD4bCRLbVxYZ2nfJFrtRoHBwesra1x79493nnnHb3XKan5JyUyeL1eYrEY8Xhc90Ec\nGRkhmUwSDAaNRqfhhSADjUjoeTyeYwo/4lxf5KAk721PQJKf5XvhcDj0xFSk+UxewNWiXC5rkZmV\nlRU9psqK8+bNm0xPT5PJZAgGg+bz7+DCehC7GMLBwQHr6+vcv3+fz3/+8zo1/3EZgF6vl8HBQUZH\nR485z2g0arpDGF4o4hSlHErCXuKwXvTWgSQcdTpsGRxlL9X+3RIHb7g6SERvfn6e1dVVrQXu9/t1\nSd9LL72ky5zMivM4F9aD2Pdrms0mpVKJvb09nQV2dHR0ovSeZCGKlJhI76VSKZ3VaDC8CDoHG7HP\n8+ZxzvoiXJ/hxVCr1SgUCuzt7VEoFFBK4ff7tepUOp1maGjoWKTC8IAL6zxln8jr9eL3+/X+pey7\nyH6MHY/Ho58rgu/Xr19neHiYSCRiVpsGg8FwAvaxM5PJEIlEtGiHiTiczIX1JuI8RYlFHGd/f7+u\n++zE4/EQCoWIRqMMDw8zPj7O9PQ0iURCqwgZDAaD4TjSnlH0vqPRKP39/ToSYVadD3Nhnac9eUHS\n+MV5Hh0dnRheknrO4eFhvc+ZyWQIh8M6UcNgMBh6FbvesZRSBQIBvF4vQ0NDZDIZRkZGdIcpM2Y+\nmgvrPO0opbQiis/no1qtHpsRyRGNRpmcnOQ973kPk5OTpFIpfD6fEUMwGAwGjqtOSaOMyclJ+vr6\nyGQyDA8PMzQ0pDWXDY/m0jhPp9NJf38/Pp+PYrF4zHlKXF6c55tvvkkymXyoW4pxngaDoZdpNps6\n4VKkGScnJ/F4PAwPDzM8PEw0GtXiHYZHcymcZ19fHz6fj0gkQiKR0CtNe42cw+FgeHiYyclJZmZm\ndKjWhGsNBoOhhV18xu12Mzg4qMU7hoaGSKfTBINBs9B4Ci6F83S73aRSKV5++WXdUkl6DsqKsq+v\nj5dffpmJiQm92jShWoPBYHiAJGIC2knKIiMUCmklLMOTuTTOc2hoCK/Xy+joqO4EUKvVjim4xGIx\nrVvrdDrNitNgMBhsyHaXROz6+/sJhUI4HA76+/tNRUIXXBrnmUgkSCQS530pBoPBcGmx120agffn\nwyzNDAaDwWDoEuM8DQaDwWDoEuM8DQaDwWDokrPY8+wHuHPnzhmcunex/T1N8dXzYezzDDD2eSoY\n2zwjzsI+1aNaej3zCZX6MPCfTvWkBjtfZ1nWL5z3RVxWjH2eOcY+nxFjmy+EU7PPs3CeMeDLgEWg\ncqon7236gXHgNyzL2jnna7m0GPs8M4x9PifGNs+UU7fPU3eeBoPBYDBcdUzCkMFgMBgMXWKcp8Fg\nMBgMXWKcp8FgMBgMXWKcp8FgMBgMXWKcp8FgMBgMXWKc5zmjlPIopZpKqS8972sxGDpRSs207XP6\nvK/FYOjkPMfPp3ae7QtstP/tPBpKqY+c5YU+LUqpL1dK/b5S6lAptaqU+sFnOMcP2e6rppSaV0p9\nXCnlPYtr7hal1Jc95vN4+byv7zy4DPaplHpTKfVJpdSKUqqolHpHKfXtz3CeT9ruq6qUuqeU+kdn\ncc1tuqpnU0p96yM+j5pSKnRWF3mRuQz2Cb0xftpRSvUrpW4/ywSxG3m+lO3nvwJ8FJgGpHNq4REX\n57Asq9HNRT0rSqm3gF8B/gnwYWAU+HdKKcuyrG6N84+BPwe4gT8N/AzgAv7OI977hd0n8L84/nkA\n/DDwXsuybr2ga7hoXHj7BN4LrAJ/tf3vFwI/qZSqWpb1M12cxwL+K/CtgBf4EPBjSqmyZVn/pvPJ\nSqk+wLJeXFH3zwL/peOxTwJly7LyL+gaLhoX3j57aPy086PAPDDT9Ssty+r6AP46sHvC418GNIE/\nC3wGqALvA34R+IWO5/5b4Ndt/+8DPgIsAEVaf/wPdXld/xL4nY7Hvho4ADxdnOeHgP/T8dh/BOba\nP3/5Sfdpe7/PAmXgPvC9tMUo2r+/Afzv9u/ftv3NvvRZPov2OT3ALvB3n/UcV+m4qPb5iGv998Cv\ndfmak673d4D/1f7524AN4CuBu8ARkGj/7tvbj5WBW8A3d5znTwKfa//+U217bgDTz3GPGaAGfOV5\n28ZFOC6qffba+An8xfZ7vdI+R1c2flZ7nh8D/jZwE7j3lK/5KPBVwDcCLwM/AfySUup98gSl1IZS\n6h885hweHpa1qgAB4LWnvI5HUaY1i4IHYSz7fd5VSv0Z4KeAf9F+7DtprQ7+fvv6+2jN7HaBt4Dv\nBj5OR1hMKfUppdRPdHFtXw34gf+v67vqTc7LPk8iTMsenpdO+xygZV/fQGtw2FNKfRPwD2nZ4w1a\ng+3HlVJ/GaAdUv0V4NPAG7T+Tj/c+UbPcJ9/g9Y9/krXd9WbmPHzjMdPpVQG+HHg62hNLrvmLLqq\nWMD3Wpb1O/KAUuoxTwellB/4e8D7Lcv6XPvhn1ZKfRHwLcAfth+7DzxOl/A3gG9RSn0VrbBRhlYI\nAmCou9s4dn3vA76G41/+k+7znwI/YFnWL7YfWmzvGfxjWoPQnweGgT9hWdZu+zUfAf5zx1suAJtd\nXOI3Ar9qWVa2i9f0Kudpn53n/SJaIdcvedrXnHAOBXwQ+ACtGb/gprWqnLU99/uB77Qs69faDy0p\npV6nNUD9Mi0nVwG+zbKsOq0BbRL4Vx1v29V9ts/7c+1zGh6PGT/PePxsf2d+DvgRy7JuKaVm6HJf\nH87GeUIrZNANM7SEe39XHbcUF63QEQCWZX3h405iWdavKqW+D/hp2nsstGY376MVeuqG9ymlDmn9\njZy09pj+bsdzOu/zVeBNpdQ/sz3mAJztWdMNYF4++Daf4sG+h9zHh5/2ItuD2xcB/8/TvsZwPvZp\nRyn1Bq0v/fdalvV7XV4PwFcrpb6ifQ3QCot9zPb7QofjjNAaDH++YzB28GCguQF8psPJfYoOurzP\nDwCTtL6ThqfDjJ8POIvx83taT7P+dfv/j5+dPIKzcp7Fjv83eTiz12X7OUDL838JD8+MuuouYFnW\nx2mFolK0lvcvAf+c1mykGz7Hg/2eNevkzWx9n22j9dMKQ/z6CdfVbD/ntJM2vglYozVrNDwd52af\nAEqp14DfBH7YsqzOVd3T8j+Av0Ur5LRutTdxbHTeY7D971+jZdt2xFmehX1+M/D7lmXdPeXzXmXM\n+PnwdZ3m+PkB4AuVUjXbYwp4Ryn105ZlPVUG/Fk5z06ywOsdj70ObLd//jytL/CoZVmfPo03tCxr\nE3SPvDmr+yzUqmVZT20wlmVZSqnPAjOWZX3iEU+7DUwppaK22dP7eUaDaM/G/hrwMycMnoan54XZ\nZztM+lvAJyzL+qEnPf8xFLqxT2AFyAGTlmV1ZsIKt4EPdWQ+vv9ZL1ApFQb+EvAdz3oOA2DGT+G0\nxs9v4cFkElqRkf9GK4Ho/z7tSV6U8/xt4DuUUl9L6+L+JnCN9odvWdaeUurHgE8opfppLcUHgD8F\nbFuW9UkApdTvAj9rWdaJISCllJPWJvNvtR/6Wlqbyh86qxvr4KPALyulNniQqv86rSyuj9KaUa0C\nP6dadXmDwPd3nkQp9UngtmVZP/CE9/sgrb2I/3A6l9+zvCj7fB34n7TCtT+plEq2f1W3zrgHZntw\n+ijwMaVUqX0d/bRCcv2WZf04rX2g7wd+Sin1I7RKKb77hPt47H3a+Hpag/ovndqN9CZm/DzFTXwC\nXwAAIABJREFU8dOyrJWO5zdorTxnZdLwNLwQhSHLsn6FVlbUj/IgRv2LHc/5nvZzvo/WDOO/A19K\nqzGsMAXEHvdWtGYPv0drk/wDwActy/pNeYJ6oEjxNc93Vye8uWX9Kq2Z9lcAf0Qrpfq7aIc82rP5\nvwBEaGU0fgI4qbh9lIfrOE/iG4Hftixr8XmvvZd5gfb5tbQ++28C1m3H78oT1ANFn/edfIpnp+0g\nv5PWzPttWoPyh3lgnwe0Bsr30ioh+D5a2bmdPOk+hW8EPmlZVum5L76HMePnmY2fx96+2+vtuWbY\nSqmbtDaqZzpnIAbDeaOU+iCtSMKUZVmde18Gw7lixs8H9KK27QeBH+/1D95wYfkg8IPGcRouKGb8\nbNNzK0+DwWAwGJ6XXlx5GgwGg8HwXBjnaTAYDAZDlxjnaTAYDAZDl5x6nadSKkZL6X6RZ1BfMTyS\nfmAc+I2zrgm8yhj7PDOMfT4nxjbPlFO3z7MQSfgy4D+dwXkNLb4O+IXzvohLjLHPs8XY57NjbPPs\nOTX7PAvnuQjw8z//89y8efMMTt+b3Llzh6//+q+H40XPhu5ZBGOfp42xz1NhEYxtngVnYZ9n4Twr\nADdv3uTNN988g9P3PCac83wY+zxbjH0+O8Y2z55Ts0+TMGQwGAwGQ5cY52kwGAwGQ5cY52kwGAwG\nQ5cY52kwGAwGQ5cY52kwGAwGQ5cY52kwGAwGQ5cY52kwGAwGQ5cY52kwGAwGQ5cY52kwGAwGQ5cY\n52kwGAwGQ5echTyfwWDoAsuynvgcpdQLuBKD4emwLOvYcXR0dOJhWRZ9fX309fXhdDpxuVy4XC7c\nbrc+XC7Xed/OM2Gcp8FwAXiUAzVO03BRaTabNBoNGo0Gu7u77OzssLu7q4+9vT2azaZ2kn6/n3A4\nzMDAAAMDA0SjUaLRqHGeBoPh+ZBZvDhMpdSx/xsMF4lms0mtVqNWq7G7u8vy8jJLS0usrKywvLzM\nysoKjUYDn8+Hz+cjFosxNDTE0NAQmUyGRqOB1+slFAqd9608E8Z5GgzngMzY6/U6R0dHVCoVKpUK\nzWYTpRRKKZxO57HQltPpxOl00tf3IFXBOFbDi0Imd81mk2azycHBgT4WFxdZWFhgfn6epaUlFhcX\nWVxcpNFoEAgE8Pv9JBIJCoUCR0dHOBwOwuEw1Wr1vG/rmTHO02A4B6rVKsVikWKxSDabZWNjg83N\nTT2wOBwOAoGADm0NDAwQCoUIhUJ4vd7zvnxDD2JZll5pVqtVFhYWmJ2dZX5+nu3tbbLZLNlsllwu\nx8HBAY1Gg2azqW1a7L1YLFIqlahWqzQajfO+rWfGOE+D4RyoVqscHByws7PD7Owsd+7c4c6dO5RK\nJZ1UMTg4yOjoKGNjYzrM5Xa76e/vNytOw7lQr9epVCoUCgXm5+f5wz/8Q/7gD/6AYrFIuVzWEZRy\nuUy9XgegVqsBUCqVjjnPo6Mj4zy7pV6vU6/XqdVqx7Kx+vr69KzbHpoyGK4a9kEom82yvLzMnTt3\nyOfz+jsQj8c5PDykUqlQrVap1+t6H9QeylVK0dfXZxyq4dSxJwUdHR1xeHjI4eEhu7u7zM/Pc+vW\nLT796U/TaDT0doPD4cDpdOLz+fRWg8vlIhAI4PP58Hg8uFyuSz/On4vzLBaL5HI5stkszWYTj8eD\nx+PB5/MRDAYJBoP09/efx6UZDC8Ep9OJ1+slGAwSi8VIpVKMjo6Sy+WoVqtUKhVKpRLr6+tUq1Vy\nuRzr6+ssLy+TSqVIJBLE43EikYheqV7WrEXDxaVer3NwcEA+n2dvb49cLkcul2N7e5v79++Ty+WO\nLYAcDgfBYJBIJEIkEiEYDOL3+wkEAkQiERKJBMlkklQqRSaTIRAInPctPjPn4jwLhQKrq6vMzs5S\nq9W0w4zFYtqZGudpuMo4nU76+/sJBoNEo1FSqRT7+/u4XC52dnao1WoUi0UqlQpbW1ssLy+TSCRI\nJBIMDw9z/fp16vU6brcbr9dLX1+fcZ6GU6der7O/v8/6+jpra2vHjtXVVXZ2drTzdDgcuFwuBgYG\nGBkZYWRkhGQyqfftZe8+EokQCoUIBoPGeXZLsVhkY2ODu3fvUqlU9CylVCrhdDoJhUL4/X4dBrgM\n4ajOomHJSJOQmsPhOHYfl+GeDGeHOE/LsnQKf6VSwel04nA4aDQa7O3tUSqVKJVKbG9vs7Ozw/r6\nOtvb2zQaDR2tGRgYQCmF2+0GuDTfGcPFRMauRqOho4TLy8vMzc2xtLTE0tISy8vL2jadTqeOHvb3\n95NMJhkfH2d6eprh4WGSySSJRIJIJILf78fv9+PxeM77Np+bc3GelUqFnZ0dlpeXyefzOotQ9nsC\ngcAxBQqn8+LnNUkWmqwY5PB4PIRCIcLhMB6PR4c3zODW2zgcDj2AxGIxXfOWTCaZmppib29PlwHk\n83kKhQLlcplyuUwul+Pdd9/l6OiI7e1tJicnmZqawu126/3Sy/CdMVxMqtUq+/v77O/vs7W1xbvv\nvsvs7CwLCws6o7ZYLNLX10cwGCQcDjM4OEg8HieRSJBOpxkZGWF4eJhYLEY4HCYcDuPz+XC73Zd6\nn9POuTrPlZUVcrmcLqItFosEg0ESiYT+Y4us00WnXq9TLpcplUrs7u5qIwsGg2QyGb1B3lmnZ+hN\nHA6HdnZKKbxeL4ODg8cyFvP5vFZu2djY0LV0uVxOO87l5WXK5TI+n494PI7b7b4Ss3rD+SF77Csr\nKywuLvLuu+/y7rvvsrS0pBcF5XJZh15DoRATExNMTU0xOTlJIpHQYVpZZXo8Hm3vV2X8OxevVK1W\n2dvbY21tjfX1df3HrdVqJJNJxsbGiMfjKKXweDzHpMvOe8Vmvxb52bIsXbd3cHDAxsYGKysrrKys\nEIvF6OvrIxQK6bCarD4NvYusEAG8Xi/RaPSh5xweHrK9vc329jazs7NUq1VWVlbY399nd3eXRqNB\nOBwmEAgwOjpKpVLR4goGQzfYt5zK5TLZbJb5+Xnu3r2rV54rKyt6zFNKEY1GCYfDpNNpZmZmeOWV\nV3j11VcZGBjA6/Xi9Xq1jV9FzuVbZk9ndjgcuvi2VCqxt7fHxsYGAwMDxzJxZe/wPLHvZTabTR3z\nL5VKbG1t6UMGvGw2SzQapVarcXR0RCaT0aENM8AZnoTT6cTv9xOLxSiXy1y7do1yuYzX69VZj/aS\nl3w+j2VZOpPXYHhayuUy+XyefD7P6uoqd+7c4d69e1oAoVgsopTC7/fj8/kIBAJMTEzoQ2qRA4EA\nHo9Hl1BdZc7defb19WlnVCwW2d3dZXNzk4GBATweD+FwmFAoRF9f34XQ+Ww2m7pO9eDggFwux87O\nzjFJqr29PW2IsViMo6MjHdK1LEsnRBkMj8PpdBIIBHA6nXqyZlkW/f39vPvuu5RKJQ4PD3XUI5/P\n6/o6g6EbyuUy29vbrK2tMT8/z71797h37x7Ly8scHh5q5xkIBPQC4MaNG/qQTFrJV7nKK07h3Jyn\npNY7HA5qtRr1el2vPDc3N/UmcyKR0CoU5+044YHzPDo6Yn9/n42NDVZXV7l79y53797lzp07FAoF\nqtUq1WqVwcFBPcg1Gg1CoRDDw8PnfRuGS4AUmNuzE71eL/39/ZRKJdbW1tjb26NSqWjn6fV6taKL\nwfC0VCoVtre3mZub4+7du9y7d4/79++zsbFBs9nUwhyBQIBkMsnExAQ3btzg9ddf59VXX8XlcvXc\ndtS5OM9gMMjIyAivvPIKXq9XJ9dUq1W9irMsS4ekdnd3dUZuIBDQm86d/z6Pc7UraYj6kfSkE0co\ng5TITNlDtaurq2xtbWnZqXq9rsPRxWKRvb099vf3KZVKl1qSyvDisNuz0+kkGAwSj8cpFovE43EG\nBgbY3d1FKUWlUuHg4IBgMGicp+GpsI9tsghYXFxkZWWF3d1dyuUyDodD12VGo1Edph0fH2d8fJxo\nNKojiPZuQCdRqVQ4PDw8lj1eqVT03r1EGaXkRbbrLirn4jwDgQAjIyO8+uqruN1u7t+/z+HhIaVS\nSReIl0ol/cfe2dkhnU4zNDREIpE4pqgiheHPO+MRZy0dLiSrrFAoHOseYD+kZ504xnw+T6VSoVar\n6dmaOM/9/X0ODg4ol8vGeRq6RkK4fX19OqIhGel25yl77AbDkxC5PXuS4+LiohY/kLrjwcFBRkZG\nGBsbO+Y8pT5fMsaf5Oiq1Srb29usrq6yubmpx85qtao1nEdGRgiHwwAXPmv83Faeo6OjOuPw8PCQ\nlZUV9vb22NnZ0f+KhuLu7i7FYhFAC2NLIpGoWzyvuor0ppPkC3GIu7u7xxKBJFFjZ2eHQqGgnax0\nEJCMNUHC0X19fezv7xvnaXgmZOUZCARoNBp65SliIuVymYODA0qlknGehqfi6OiIfD6vpR9XVlZY\nWFhgZWVFl0v5/X4GBwe5du0aL7/8MhMTE0xOTjI2NnZMk/xpqFarZLNZZmdnmZ2d1dUW5XKZV199\nlWq1itvtxrIsXR9vVp4duN1uwuEwjUaDnZ0dUqkU8XhchzwlRLq3t4fD4dD7jIeHh6yvr+taNhFR\nEEdq11e0l5HIc/r7+x/6oMXhVSoVvTqUwnSZlckMSQrX8/k8BwcHWrD7cT3pZM8qEonoFO5e2Ew3\nPMjOlomV2EulUtFbAuLo7HkAMjm09/Ls6+s7dh57RwpJrIvFYgSDwQs/YzecH/atqM3NTVZWVlhd\nXWV+fp7NzU3dSiwQCBCLxRgcHNT1m+Pj4ySTSS348rTvJ454dXWVpaUl5ufnmZ+f1+3LarWaXqwc\nHBwQCAQuxQTw3JxnMBikr6+PZDKpj0KhwOHhoR5wCoWCdmyHh4dsbGwQCoW0Sn/nv/bDLpMXDAYZ\nGBhgYGBA11rCg33Oer1OsVjUJSYS7y+VSvpf+VkMQcKz0nbncfcaCoVIJpPE43GCwaApU+khGo2G\n3j/f39/Xk7BCoaDtHdBlW4FAQNuqZGVLxq0428PDQ8rlMkdHRzr7NhqNMjQ0xMDAgNGFNjySarWq\n9x3Fac7OzrK0tMTGxgaFQoG+vj4t4j4yMsL169eZnJzUIdVuyqDsdr+0tMTCwgJzc3MsLCzo74BS\nSn8X8vn8pdl6OJdR3OVyEQwG8fl87O/va+d5cHCgi3Sr1SqFQkEr9qyvr2vHKAlCnUlDsroUzVAp\ngRHt0KGhoWMfvAxstVqN/f19PQvLZrPH5PZkdSrnk587Q7QnIc5TumAEAgEj4N1DSCsnSXxbX19n\nY2NDh/53dnYAtG3bbXVwcJBoNKrViKRPouQHHB0d0Ww2tcjC0NAQ4XDYOE/DI6lWq+TzebLZrG7O\ncfv2bdbX1/WkzufzEYlEmJiY4Pr160xPTzM1NcXIyEjX3XtE6m99fV07z/n5eRYXF3XJn8fjoVgs\naucpWw9PGlvPm3NxnpKZ5XA4CIfDjIyMkM/n6e/vZ3V1lUAgwM7Ojl7pSYhKFFTs/Qvt/9rDuHZn\nJ3JSh4eHD6085QM8PDzUe5tSLyeDlqwwG43GMcf5KLxery4mHh4eZmpqimvXrjE6Oko0Gj12DYbL\nT2dDgGq1esxh7u3tsbu7q4UzstmsDv/n83ngQVmKbAlsb2/rhAypeZYscDmfZVm6I1E4HNbbAmZy\nZhA6tw7sNeki9L65uUk+n6fRaNDf308sFiOdTmvJvXQ6rW3rafY4pWqh0Wiwv7/P6uoq9+/f5/79\n+7q8qlwu63HU5XI9cUy9iJxb/FA2goPBIOPj43g8HuLxOPPz8wwMDLC2tqZn5vl8/lgpiVJKdyyR\ncymljs3y4cGgJo53b2/vWMjUblgSziiVSkDLAQYCAfr7+491Pxdne1LSj1xHMBgklUoxNDTE+Pg4\nk5OTTE5OkslkiMVixnleQWSiVqvVyOfzOlS1vLzM8vIyKysrHB4e6lBVtVrVkQ14INkoYtxut/tY\nf1v7nv7R0RG5XE5LpEmIV6IaZlvAYEeqCGq1GltbW8zOzvL222+ztrbG5uamrnAQm0ulUoyMjDA5\nOcnExITWqJWFypOSeGQ8lQShxcVF3nnnHWZnZ9na2qJYLD4UuRMNc7Hfy1Aveq7fMnE0breboaEh\n0um0jqlLt3HJgJXVpzjPzvNAq7OJfLj2WYzUWXZKRtmTiuz7n5LRKwkYe3t7KKX0/qY8t/Ma5AgE\nAmQyGWZmZrQBTkxMEIvF9L0Zrg72SdrR0REHBwdsbm6ysbHB7du39SGTrnq9rjPNJc1fbFFWl7Va\nDYfDoTVCZTtCEonEkdr3R6WU5SJnKBpePGKXoiI0OzvLZz7zGbLZrK4Y8Hg8+P1+BgYGHnKedlH3\np30/Ub3K5XLaec7Pz+ukObvjtLdtlG25y2DD56YwJHTG0EVEwOVy6dBnOBw+tvqTbDF7piJwbGZk\nX6k+CqfTqcO8ch3SZ1FEGaQl2uNmQuIw5TUTExPMzMwwPT3NyMgI6XSawcFBgsHgMUFww9VAGgPY\n65K3t7fZ2NjQISrLsvB6vccyxe26zTKBk1IpKSKXvX9AO0/RFu10ls1mE3j+mmfD1UFySCRRbWNj\nQ29PSXKm0+nUAu/Dw8N63JIEx5P6EXciYWEJ1coWhQjKb29vs7+/fyw8K+dzOBy6MbyUX7nd7gvv\nQC9UfEdCt319fTpVOpVKsbW1pes9O0UJ7Hug9tm8OFj5sE5Sv/B4PHpPSWbu8sFJeFbqMu3h2s4u\nL0opBgcHj4kkS9Gv9LOTEhUzsF09ms2mrrOUvU2pC242m0QiEa5du6ZtLRKJHFtNymTPsiwKhYIO\n+YrW6NraGoVCQUdhpDTK6XRSq9WoVqu616c9qc5gsCxLVxKsra2xsbGhqwkkU9vtdpPJZJienubG\njRs6OUgm+0/jxCQ0fHR0xObmJrOzs8zNzXH//n1WV1dPDNXK2CnlfNFolFQqdWkyxi+k8wyHw8Tj\ncVKpFMPDw2xvb+sw2MbGBh6PRwtl2zNvZeBwu91aRFvS+eHhGbk4z3Q6TTKZJBqNEovFcDqdenZW\nKBS046zX6w/NnMRxx2IxZmZmeOuttxgeHiaRSJBMJvH5fPq65P0v+ozK0B2yYjw4OCCbzR7rquNy\nuYhEIsTjcTKZjD78fr8OyYrzbDabOhNSZu2NRoOtrS3K5bK2tWq1qutBZZIoJVWS1GEwwAPnKXuP\n9miIPcqWyWS4fv06r7/+OuPj43qv/Wm3AeyhWmmg/ZnPfIalpSWy2SylUklHRgRJGpUoYzQaJZlM\nEgwG9aTyInOhnKdkHPp8Pr03GAgEtOZhOBzWGYgyINlVLuRQSunU58PDQ61C1GkIkUiEkZERRkdH\ndRmJ3++nXq+zu7ura+pKpRLVavWYihC0wmgyAA4PDzM+Ps709DTJZJKBgQHC4bDJfLyi2PfIC4UC\nW1tbLC8vs7q6ysHBAdVqVYsXyJFOp0mn02QyGXw+n155woN99/39ffr7+3G5XOzv72sFoXq9rjsL\n1ev1Y/1jNzc3WVxcxOPx6CbEUuJi31c19CYStt3Y2GBnZ4disUitVtPjqyxUMpkMw8PDpFKphyb8\nnYj0qBwSGdzZ2dE9QOfn53WC0NHR0bHX9/X16dJC2beXQ7Y1LjoXynnakTi4ZVm6hnNgYEBnsEqq\nv32fU8IGR0dHWpdWinClBZp9EJEBTVYCkiEmKkO5XE7PmkTA2B52kPrNRCLB1NQUw8PDDA4OanFj\nswK4ujQaDb3a29nZYWFhgTt37rC0tKQnYaOjo8RiMWKxGNFolEgkovVopechHN+zh+NNCuz7mPbI\nioiIQGvSWS6X2dzc1PJpgJ7Ymd6evYtE30Tq9PDwkEqloiXwZEwV5SApdXrShMuyLEqlki63kqzy\npaUlVlZWWF5e1o5a6pHt2AVBpKY5FArh9Xp1meBF58I6z76+Pv1B+nw+BgYG9CxH0q47E4bkg8zn\n88e6n9gHHrtBiPJPKpVCKaUL2GVGv7OzQzabPTFkC60ym0wmw7Vr15iamiKTyTA4OIjf7zf7m1cc\n+z7n1tYWCwsLOqNwenqaSCTC2NiYnlwlk0kttSeZi/a0f3u2tmTu2m1OKYXL5dKDS6PR0KUv0ox9\nfn5eTyjD4TDNZlNPQs3Ks3eRpDNxnpLtKpGRVCqlo2Uy5j6pJEWc587ODpubm9y9e1dnlYsu+eHh\noXacj3Keg4ODx5ynSKhehrHzQjvPbgXf9/f39SGrxUql8kjn6ff79apA2qGJIoasbGV2L9hXCbJy\nvX79OqOjoyQSCd1J3XC1qdfr5PP5Y+Ha9fV1stksExMT+P1+3QVI1KUeNRjZW+FJwlAul2N/f1/b\nr+wJRSIR3c9TbLxareqkOsnC9fl8DA0N6cJ3ibqYUpbeQsKr5XL5IfUeUT+Lx+PHdJEfteqTLQPZ\nNtje3taCC9I8++7du7piwr7Y6BRAcDgc+Hw+vc8ZiUR0suZl4cI6z2dBNp6ldERWqJLR1RmKcLvd\n+P1+XC6XLoXJ5XJsb2+Tz+cfitMDOqvX6XTqmqiJiQlSqZQuHTBcfarVKrlcTmcUbm9vU6/X8fv9\nuvehlCc9aUCQbYZiscjq6ipzc3Pcu3ePpaUlrXaVSCR03V0kEtEz+3w+z87Ojl5VZLNZ7ty5Qz6f\n5+bNm9RqNZ2cJKte4zx7C7t4jL3XsIyXkgXu8/keGy6VrQJpmPHuu+/qxtlra2tsb2+fGKI9CYks\nSkODQCBwqRwnXDHnKbMmr9erZz6iRHRSGEKcoITBCoUCuVxOS/Q9ynk6nU4d8hgaGtIDmnGevcPR\n0ZHOiL17966WN5MEN3GeUpv5pHNJfahdb3Rra4ujoyOteTs9Pc0bb7xBOp3m4OCA/f19stksc3Nz\nWJbF4eEhuVyOfD7P3NwctVoNr9fL0NAQlmVdupm94XSwiySI2IxlWcdKROzldI9CpE6z2Sybm5u8\n++67fP7zn+dzn/vcsWYF4jxlvD1Jds/uPKPRqHGe5404wqfFrn8r8nw7Ozt6ALI7Twl5+Xw+/H4/\nwWBQC9qnUil8Pt+lkZUyPD+y55jNZtna2kIphdvt1kkQkiH+KJu06+GWSiVyuRyrq6ssLi7q5ItC\noUAwGGRwcJCxsTGuX7/OSy+9xMjIiHae8t7SwF0caKFQIJFIaLUYGdRECORRE0rD1cNeB28P24t2\nt9QcS/tHaYZhP0TiVNqYLS8v61rO+fl5fT57Ryv7+GpPfJOQbSgUYnBwsOs2ZxeFK+U8u0VmZNIU\nVppf7+3t6XRueLD/6na7SSaTDA8PMzIywszMjE4EMeUAvYVsBYismZSdDAwMkEgkdOu5R9mFXXhD\nJMzu3LnD4uIi29vb1Go1AoEAY2NjjI2NMTk5ydTUFNFoFJ/PB6C1QEVSMhaLace7urpKPp9nfn4e\nl8ulQ74yWIpTNzZ79fF6vQwMDJBMJvUeqKgLibhBpVLRjTVELUuENyR35PDwkJWVlWNHPp/XSWmy\nsKjX68faNsoeq0QFRT83k8kwOjrKyMiIli69TPS082w2m3q/SZyn7B91inbLQJlKpbh58ybvec97\nGB8fJ5FIGOfZg9idp4Rqw+Ewg4ODumbYvsLrRCZusne6sLDA22+/rbO9a7Ua0WiUsbEx3nzzTa5d\nu0Y8HicajR7LQpeC8lgsRiaT0Xv92WxWO8/9/X2tPjQ4OKijI5ehHMDwfCil6O/vJxKJMDQ0pDNv\nO2uGK5XKsV7Iknhp7/6zu7urnaaoBhUKBRwOhw7/SvKlvE6UjEQGMBAIEIlEtADO6Ogoo6Ojx2qe\nLws97Tzr9TqlUkmXpezu7rK/v68bFAN6xSlKHJJd+9prr2ljeVwxseFqIkXedscpRd6yd9RsNh/S\nW5ajVCrpOuTNzU0dBjs4OND2Fo/HGR8f5+bNm1y7dk3vn9oz0BuNBn6/n8HBQVKpFJVKhZ2dHdbX\n17U60cbGhm6YnU6ngVaZVafdmsnf1UMphdfr1c5T6j0dDoeuVZbxT5Sq6vW67mgl46IIIKyvr7O2\ntsbW1pZOQJOkn3g8Tjwep1AoaL3no6MjbWPSxzmRSJDJZLRoSCqVOue/0rPR085TZv0rKyvMz8+T\nzWZ1OzMZ9CQcFo/HSSaTTExMkE6ndYaYCHsbeguXy0U0GmV0dFSLb0vI366e4vP5tGJWpVKhVCrp\n7habm5tsbm4yPz/P9vY2SilisZiuC7Vn14qowkkdhaT+s9FoMDIyQqFQwOVyaX3d7e1tdnZ2uH//\nPpZlMTExwfj4uF69mvKVq4tSSk+uRkdHtfyj2OPq6iput5vFxUUdtpWSKakjtgvOFItFlFK6xCUe\njx9LjBNhm52dHR1Zkexet9utNcCvX7+u5UsvK8Z5tkNmdudp32CXkNjY2JhWb5EuKTLzMvQebrdb\nO0+AhYUF3ehXVqTBYJBoNKozC0X/dnd3l4WFBebm5pibmyOXy3FwcABANBrl2rVrzMzMMD4+TiaT\n0c7zpOJxCR+LzY6OjuJ0OonFYty6dUuvPnd2dvSgJs41mUzqJA3jQK8uPp+PwcFBGo0G2WyW1dXV\nY87z8PBQRzPsfZHlEGGaRqOhbTAcDjMyMqIFYuzC8MViUTfnsGf3ejwe7TyvXbtmnOdlw542Lc5z\ncXGRhYUFcrkc5XIZeJA55vP5SCQSjI+Pc+PGDcbHxxkaGiISiZzXLRguAC6Xi4GBAaBlUxsbGxQK\nBZaXlwmFQrpTT6PR0CUBkgm7sbHB3Nwct27d4tatW9RqNT0RE6nHN954g5GREfx+/2NLTGTlKa+X\nnrjDw8PUajVyuRyzs7O6LnRpaYm+vj4SiQTXr1/XbdJkr8t+XsPlRymFz+cjFovhcrlYW1sjFosR\nCoX0KnRjY4NaraZ7yXaW94ktSOsyKS8ZGxvj5Zdf5tVXX9X5IrlcTk/IxOnK6+0LkcnJSd1d6LLS\nk87Tvu8k6f5bW1scHBzogSwSiegWOdevX+fatWtMTEyQSCTw+/3nfRuGc6avr0/3IIzxL8C0AAAU\nbUlEQVTFYiSTSTKZDKVSiXq9zsLCAvv7+7rJ+9DQkA7Tbm5usr6+rus4g8Ggfp60tZOsWml8/TTI\nKlRCZ8PDw7znPe9BKcXm5qZulSa1oaFQSCtjJRIJfD6fKV+5YsjkSsRjRkZGdE7HxsaG7v4jditZ\n2DJps2dmy8pRDmm7ODAwoPXAl5aW2NjYIJ/P6/NJOFhyRETjWRLfLis96TxFDk26DYjzlEbbTqdT\nd1yR+PzU1BQTExNa9NvQ24jz7Ovro1arkUgkSKfTep9ocXGRu3fv6qSIdDp9zHkWi0VdVB4MBhkf\nH+eVV15hdHRUt8d7FpFsCeE6HA6Gh4dRSjEwMMCtW7eo1+usra1pZSRAt9yTrF3TNu/qIbKkLpeL\nkZERoKXrPTs7y/3793XfYymf8nq9WlJSemtKSVYqldJC8qFQSB9LS0scHBywvLz8kPOU5u3iOMV5\nut3ururyLxqX98qfEXGeR0dHeuW5ubnJ1taWXpVKXdTIyAjT09N65SndKgwGafUl6fWy8szn89y9\ne5elpSXm5+d11550Os3W1pZ2nrJC9Hq92nl+wRd8Ael0Whetdzuw2EO4Ho+H4eFhBgYGGB8fp9Fo\nsL6+rutKAQ4ODjg6OsLv9zMyMkIoFNL3ZkK4VwNJepSwvyT7DA8P4/f7qVQqbG1t6ZaLjUZDK6eN\njY2RSqX0KlS2A0ZGRhgaGnpIAEFWntvb2xQKBRqNBh6P55iSkBzhcFhfz2Wl55xnpVLRqddLS0vk\ncjndZeAkGanL/OEaXgyicyz7jOVyWdfIeb1ems0mhUIBj8dDJpPRDQRk1j49Pc3k5KRuZXdaNcN2\n555KpZienubg4IDDw0MtbL+8vIzP56PRaDA6Oqo7bAQCAcDY/1XD6XTi9XqxLItMJsMrr7xCf3+/\nlpdsNps6zyORSOhkNckcl4hIZ2KRPSPXLtMnK0/ZKxUlNrj8ttWTzjObzbKyssLS0hI7Ozu6v13n\nbNveLspgeBTiPGWwyOfzbG9vk8vldCJOsVg81hg7FovpvSMJhUko67ScpwxSDodDO0+ApaUlVldX\n9XegXq+zt7fH9vY2L7/8si6vMfufVw/ZY3Q6nQwPD9Pf36/rg6ULitRj2vtripqVlF0BxyJ40thA\nnKeoComzttdAXxVlq55znuVyWZenLC4uksvltPM8iavwIRvOFnGeonmcy+VYW1tjfX1dK1WJ1mwm\nk9G9XyVJSLJpT7uBugx6lmUxNDSEUopwOIzL5WJvb09nW+7u7rK4uMje3h5+v5+xsTHi8bhWoTHf\ngauD2ISsJIeGho71jbUs61jnKPt++0k9Z6vVqnaesvIslUrH3u9RK8/LztW4iycgKdiinLG2tsb8\n/DzLy8vs7u4+tvWYiCkbBSHDo5AEHWjV1KXTaW7evInD4dD6tY1G49j+5+Dg4DGhjc7m2KdxTfaf\nZfYPMDk5qUuystmsXjVsbm4yNzfHwMAAxWJR97qVEG7neQ2Xj85omkiP2sXcpWb4ceOeZVk6XLu/\nv0+hUNCJR2LHfX19BAIBXeo3NjZGLBa7MsIyPeM8y+UypVKJbDbL2toac3NzLC0tsb+/T7VaPfZ8\n+fDts6+r8GEbzg4ZZPr7+xkaGgIgHo8fK40SCb9wOIzf78fn82nHedYiBdL4WITkJaN8fn6e2dlZ\nZmdndYs1pRSHh4dcv35d97w19n/16JxgAdp5PmkiJ86zUCiwu7v7kPOUsTMQCGi1rPHxceLx+KXT\nsH0UPeU88/m8bv0kK09Jz+7EHrow6iuGJyEDhsfjYWhoiFgsdqxAHDi2dyQ29aJsy+Px4Ha7CQaD\neL1eotEo4+PjhEIhDg8PuX//Ptlslr6+PvL5vE5wkrIEE769mjxPtEOc597eHoeHhzrxUr4Lsndq\nl5qUTPKrQE84T/uHaV9J2kMY9j1PEYOX+iTpdWcwnIR98BHbkUQJ++/tzvJFOyJ7JxW5LrfbTSaT\nYWxsjPX1da2vK90zhoeHyWQyulheVsqGq8Hz2qC0HisUCrr9mCQcBQIBAoEAsViMSCRCKBTC7/fj\ncrmuzFjaE85TVgTSgcLv9xMIBPB6vbodjx2llNYnlYyzy6yEYXixiJOUCZndeV6E1ZuoxYhM3+Tk\nJMViUdfoiWj96uoqyWRSd3iR74XBYG9nViwWqVQqOoLn8XiOdVqxqwldpS2wnnGeUiQsCkGSci09\nPRuNhn6+rB6k3dRVyhAznD0XxUk+Cqn/9Hg8xONxJicndTF9uVxmcXGRUqnE6uoqsVhMd16xJw4Z\nDLLyLBaLD3VPCYVCWqVIxlC7UMNVoCc8gj1sKwLaIobdOROS5/b39+vSg2dRezH0JpdhYLBnUAYC\nAeLxOM1mk2q1qgW+JRS3srKiw2zicO3fH0PvIslwUuoiY6d9n3N0dFRn2F61ioWe8Aj2FmOy52kv\nQekMq0lYS5ynFPYaDFcNt9vNwMAADoeDWq1GsVikVquxublJvV5ndXWVQqGg26pJ82PJ3DX0Lvby\nFnjQiUpk/G7cuMHU1BTxePxKhvt7wiOI84QHmqSPShwSJ2t3npddwNhgeBRSKhMIBFBK6YxJj8ej\ne5RK/0dxmvJ7E8Y1dNaGulwuQqEQmUyGmZkZxsbGCAaDxnleViS0UKvVqFQqOkno6OhIhxzEYXo8\nHgYGBggGg/j9fh2yvWohB4MBHkwmPR4PkUiETCajO2zs7e0Brc4r29vbLC0t6ebF0orN0LuIwIKE\n8SWUL4pC8XicaDSqJSevGj3hPO0iCdJ3TgSypbBXZt/hcJhkMkkkEtGJQkZhyNALeDweotEo0GoU\nv729zdraGo1Gg1KpxNLSEpZl0d/fTzKZPOerNZw3IvMXCATw+Xz09/drJypi8hK1u4rjZ085z3w+\nz8HBge54USgU9Cxbsmvj8TipVEp3ORcR48uQCGIwPA9ut1tPGmW/Mx6Pc3BwoEtZRKP3+vXr5325\nhnPE3njd7jztCZmSXHZVRWZ6wnk2m01qtRrVapVyuUylUtFhW8HpdBIMBkkkEqRSKd0B4CqGGwyG\nk5A8AGmGPDIywrVr1wD0d0ZWE+Z7YZAQbSgUOlbOZ++V7Pf79XbYVcsbuVp38xw4nU5CoRDJZJJ0\nOq372BkMvYSsEKS7SrPZJJPJ6O4wHo+H6elpHd419CZSF+zz+RgYGNCSe5VKhZ2dHZaWlrhz5w7l\nclnXexrneUWx6zCm02kGBgaM8zT0JEop/H4/o6OjRCIRyuWy3t5wOBy6N6Oht3G5XPj9fq0gpJSi\nUqmwu7vL8vIyfr9fqw6JPN9Voiecp13l3y6U4HK5dB87p9OJ3+8nEonoVlGiiGEw9AL2fSm3263b\npgHH6vnspV+G3kU67jSbTSKRCIODgySTSYLBIA6Hg0qlQqlU4ujoiGazed6Xe+r0hPMUeT6v16sz\naiORCPl8nqOjI6rVqk657u/v1xvfZoAw9DrSNMHeBPkqJn8YukMphcvl0ivOqakpms0msViM/v5+\nYrEYsViMVCplRBIuM+I8fT4fwWBQ91Xc39+nWCzqlWdnirVxngbDyX0fDQaXy6WbBUxNTRGLxXQT\n+P7+ft2J56p24+kJ5ylC7/CguDudTlOr1cjn8+TzeaLRKOFwWMvxmYxCQy9jnKThcUipiiQB+f1+\n0un0OV/Vi6VnnKfoLkYiESYnJ2k0GgwPD1MsFikUCgSDQV566SXS6TShUMj08DQYDAbDI+kJ5ymz\npL6+PqLRKFNTU4TDYfL5POVymXK5jMfjIZPJaOdpn1UZDAaDwWCnJ7yDXRRe0qpTqZROFjo6OtL9\nCgOBgK5ZMhgMBoPhJHrCedqRshX7z5JZa5KEDAaDwfA09KTzlBCuOE7JBBN5MoPBYDAYHkfPOU97\nCNdgMBgMhmfhLJxnP8CdO3fO4NS9i+3vaTZknw9jn2eAsc9TwdjmGXEW9qlEcuvUTqjUh4H/dKon\nNdj5OsuyfuG8L+KyYuzzzDH2+YwY23whnJp9noXzjAFfBiwClVM9eW/TD4wDv2FZ1s45X8ulxdjn\nmWHs8zkxtnmmnLp9nrrzNBgMBoPhqmPqMgwGg8Fg6BLjPA0Gg8Fg6BLjPA0Gg8Fg6BLjPA0Gg8Fg\n6BLjPA0Gg8Fg6BLjPM8ZpdSMUqqplJo+72sxGDox9mm4yCilPG37/NIX/d5P7TzbF9ho/9t5NJRS\nHznLC33Ka/zWR1xnTSkV6uI8n7Sdp6qUuqeU+kdneOnPXC+klEoopbba1+o+zYu6TFwS+3yzbVsr\nSqmiUuodpdS3P8N5Lrx9KqW+XCn1+0qpQ6XUqlLqB8/iwi4Ll8E+4XQ+N6XUD9nuq6aUmldKfVwp\n5T2La34elFL9SqnbzzJB7EaeL2X7+a8AHwWmAWk5X3jExTksy2p0c1HPwc8C/6XjsU8CZcuy8l2c\nxwL+K/CtgBf4EPBjSqmyZVn/pvPJSqk+wLLOp2j2Z4FPAx88h/e+SFwG+3wvsAr81fa/Xwj8pFKq\nalnWz3Rxngttn0qpt4BfAf4J8GFgFPh3SinLsqwL4STOgQtvn6f8uf0x8OcAN/CngZ8BXMDfecR7\nv8jvoZ0fBeaBma5faVlW1wfw14HdEx7/MqAJ/FngM0AVeB/wi8AvdDz33wK/bvt/H/ARYAEo0vrj\nf+hZrs92zgxQA76yy9eddL2/A/yv9s/fBmwAXwncBY6ARPt3395+rAzcAr654zx/Evhc+/efAr4a\naADTz3B/fwf4H8CXt8/hfp6/11U5Lot9ts/774Ffu0r2CfxL4Hc6Hvtq4ADwnLd9nPdxUe3ztD43\n4IeA/9Px2H8E5to/f/lJ92l7v8+27e8+8L20xXzav78B/O/279+2/c2+9Bk+h7/Yfq9X2ufoagw+\nqz3PjwF/G7gJ3HvK13wU+CrgG4GXgZ8Afkkp9T55glJqQyn1D7q4jr8B7NKaTT0vZVqzKGjN/AeA\n7wa+gdYff08p9U3APwT+Pq0P+SPAx5VSf7l9/aH2tXwaeIPW3+mHO9/oae5TKfUa8PdofRGNTFR3\nXBT7BAjTstHn5SLZp4eH5eUqQAB47Vlursc4L/s8y8+t0z7h+H3eVUr9GeCngH/Rfuw7aUVX/n77\n+vto2ecu8BYt+/44HeOfUupTSqmfeNzFKKUywI8DX0drctk1Z9FVxQK+17Ks35EHlFKPeToopfy0\nHMH7Lcv6XPvhn1ZKfRHwLcAfth+7D3SjS/g3gJ+zLKvexWs6r03RCol+gNaMSnDTmrXP2p77/cB3\nWpb1a+2HlpRSr9MygF9uX08F+Lb2Nd1VSk0C/6rjbR97n+29g18AvsuyrK0n/X0Nx7gw9tl+/YeA\nL3na15xwjgtnn8BvAN+ilPoqWtsoGVqhQIChbu+xxzhP+zyTz63twL+G44uYk+7znwI/YFnWL7Yf\nWmzvuf5jWpO4Pw8MA3/Csqzd9ms+AvznjrdcADYfcz0K+DngRyzLuqWUmuEZFiBn1c/zj7t8/gwt\n4d7fVcctxUUrdASAZVlf+LQnVEp9AJgEfrrLaxG+Win1Fe1rgFbY4WO23xc6BqYILWP7+Q5jd/Dg\ng7wBfKbDmX+KDp7iPv8l8AeWZcn+rur41/B4LoJ9vkHrS/+9lmX9XpfXAxfYPi3L+lWl1PfR+u59\nktaq42O0QpDnsa912TgX+zzlz+19SqlDWj7GSWuP/u92PKfzPl8F3lRK/TPbYw7A2V513gDmxXG2\n+RQd455lWR9+wrV9T+tp1r9u//+Zxs2zcp7Fjv83eTiz12X7OUDL838JD8+MnrW7wDcDv29Z1t1n\nfP3/AP4WrSX9utUOktvovMdg+9+/RmvPyI4MRorTCbF+ALimlPoG23kVcKiU+ohlWf/vKbzHVeZc\n7bMdcv9N4Icty+pc1T0tF9k+sSzr47RCwilaYbaXgH9Oa1VgeDznZp+n+Ll9jgf75WvWyclA+j7b\nTt9PK4z76ydcV7P9nNMaP79QKVWzPaaAd5RSP21Z1lNlwJ+V8+wkC7ze8djrwHb758/T+gKPWpb1\n6ed9M6VUGPhLwHc8x2kKlmV1YzArQA6YtK0IO7kNfKgjs+z9z3Btf57W/oTwp2glEEg2p6E7Xph9\ntsOkvwV8wrKsH3rS8x/DRbZPjWVZm6B7Vc5ZlnXrec7Xo7zQ8RNO5XOrdmOflmVZSqnPAjOWZX3i\nEU+7DUwppaK21ef76d6hfgsPJpPQilD+N1oJRP/3aU/yopznbwPfoZT6WloX9zeBa7Q/fMuy9pRS\nPwZ8QinVT2spPkDLKWxblvVJAKXU7wI/a1nWk0KxX0/LmH7pLG7mJNof/keBjymlSsD/pBVKeR/Q\nb1nWj9OKs38/8FNKqR+hlar+3Z3netJ9WpY11/H8kfaPdyzLeqbN7x7nhdhn23H+T1rh2p9USiXb\nv6pbZ9wD80Xap1LKSSvZ47faD31t+zwfOtWb6h1elH2e9+f2UeCXlVIbPCg5fJ1WFuxHaa1IV4Gf\nU6265kFa9noMpdQngduWZf3ASW9iWdZKx/MbtFaeszJpeBpeiMKQZVm/Qisr6kd5EKP+xY7nfE/7\nOd9Ha4bx34EvpdUYVpgCYk/xlt8IfNKyrFLnL9QDxZT3nfC656I9AH0nrZnN27SM/sO0Qx6WZR3Q\nMsT30krR/j5a2Y+dPO19Gk6BF2ifXwtEgG8C1m3H78oTroh9WrRm8b9HK1nlA8AHLcv6zVO5kR7j\nBdrnEz839UDR52ue765OeHPL+lVaEcOvAP6IVknKd/HAPhvAX6D1Hfo08AngJHGQUY7X1T7V23d7\nvT3XDFsp9UHgPwBTlmV17i0YDOeKsU/DRUYpdZNWos9M5wqu1+hFbdsPAj9oBibDBcXYp+Ei80Hg\nx3vdcUIPrjwNBoPBYHheenHlaTAYDAbDc2Gcp8FgMBgMXWKcp8FgMBgMXWKcp8FgMBgMXWKcp8Fg\nMBgMXWKcp8FgMBgMXWKcp8FgMBgMXWKcp8FgMBgMXWKcp8FgMBgMXfL/AyR1JqesKs8YAAAAAElF\nTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc3950d208>"
+       "<matplotlib.figure.Figure at 0x7f3763d02208>"
       ]
      },
      "metadata": {},
@@ -1265,9 +1265,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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A56w80eB5sXdeSyP9yKpq/h7JkYwTQDcdZXHG6rkjVPFYXkzWxvIx1IbmHlEe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\nSF1DPSM2c3Z3lps1fPF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r4X4rrNfCag11LVxfJxtMUx1aqJsbAnm2Ile0efYCJl0TQjqn3Ep+bB4RnF+b\nudGdjjh1IMwF2jloGmI+0ajUvVmLrEJ23Jru/p4jQ9SCaRqM90lZO5PixeKmCfkjg6Rtj1XR0TrE\nprCiFIFFDcFLMrAysCyLyKIKrBeeIULnhS5M15d3vaiizQFYgfdT8ICV3tHl+bnn1qhaNHk1+yz/\nG5smyxdWxGYxdg40Y3I5fVnbwzYI9y2IyFGtVqYDOWDlkHY5KyuwDlGmzFss8pCTWtI67jQ3CLKJ\naabrMDGABbOGaulYr2o6H/n6a7UNpzGl85ERv3gO+MeeQJ4/yotl5kKujwq+KqfHaVHj8AsZxpYQ\nawjWJqu3KIlNGIuxMktN444wVcyt15Mr9PbtaXGAtRwb+/PZh2oG68nMF51WTo+Ab7xQvtiycB2h\n9hx2BmsekTT+lTSP2M8V0hxU1fbJ99mG06hWPiAn3399sUgdKxcXsLQtVXtL/eaOqt9S+h3O74kR\nFuY5L+wL6vKCylaUtsK68qSYPe/9ywvE8qjWvGNNrysvDTg3pu4xKWGlXK7zFMLptajcZBNScqtE\nhbdOQBzLGi/Jw/Bica7DisVai+QDM3QmsFrfTTPlj3P0mzeLhwDSI95j9nusqyipWFLjmhLvIn4I\nhCGwKARnDV4sPqTireAhZOtXg1v5FMzcMFTefwr8npOI4u+4t7Mubp1QlutBtYI1X7haQbNgsCXe\nlgxUdPuSbm/p3uoGScJ+H7m5kWPBpLGTTni+Mry6cLx+VrHuSpqdoW7T7mdH4TRmqri/uDjtGcu9\ndHVl1RnTaIvmJiRFTkxRwWJJYR11KSwXqUVNl9+5/SB+Tl7/JAD+qeg/L+Q4B8RK86jGcdZzGKBr\n0+GKlNw3jmgcphj7gjWkpVU9IlP+abVKmvPFi2no98XFJMjar6YJ/xx84bSSJ/85n1nadSkE7SNF\nv0NcR6gCmwKsMZyalZ8u5Z5unoPN5TgHYLWV9G/zW6tzGcbBU8dAhbLv1StYDgeK7SXu8hvc1Q/Y\n22vs3VtijCy//Ar35VesPv8NYi/Apf7QPFCSjxHO58XmAJx76zDpoLqeZP1kvT7y6MZfLBYUUqGj\nsVOORQHxuEvB6P0sV/iqofeGfjAMXqispTRp3+aTdgeNRmmBlmpADVvnYYk8JKqRsMMeomCNpVo+\nwy6fUTaG6NJghtB7XFngbEGgxJP6wP0sLabXr1HVXB/p+p7vF/CY+a005ffH6IZGHtXSzL1b7dOa\nGU2xWeCg77oqAAAgAElEQVRjSUtJG0u2B8t2b9kcUqDj7TVcXwtv3sAPb1IwMo94fvm54at/KDj8\nxvC5LXm+E5wCsG7moY7SdpuUg66VPIqpDpVa2JqG1MED43VJUWIWCyT0FKagrgzLpaHt5KT7Jt+w\n4efm9U8G4B9LeUhnDr7zcV55dPddAPbjIPAtsaqJ1hIQxDhiIYgz043X5JwyRCvxtNpGOb1eTwzd\nbKZkYF7Kq8Cs1p8meOZl2RkAi/eUw47SdVB7qoInD5hTD9j7Sd9qVEv/Lk8fqQf87Nk0sS73gF+/\nhuW2Rb65RN78K/z+9/Dtt+mIEfc//xeWC4i/auis0NmKgz1tM8jlej7Sdp7j05xvvkmEBkdyhfwh\nhPRvTe8PpQpIdqE5AKubUFXExZKwWhOaFf0hTTTsYgRJWzginPYazgFYNaAaxxqmyHMFCr5ZMYEA\n5eeecumgqcD1YNPhiwXeOjwWHxln+MjJ6ME80JV7wDkA53z+FPh9tsAuZgCsOlAdGNWvOe+aBsqa\nwZe0Q8muL7jdwdsbePtW+OabyLffwjffwLffyiiqqSpdI1r/9E/CvnVI6TCLErczrNoRcG9v4fJy\nGgyigPrsWWpJWq+nC1J9rxb13d3UQjXT69JeJAC2YfSAoetPnYEcgH9RD/ghynN956pA8/dpCHDu\nHT9kZXixBKnwEhFKBIcgiERGc3zqD1ssCD7iq4ZQNgymoO8NvTf4dsD4gCkL7HpJ6W4pmlvKi6wi\nWtFBFYMCbJ53yLfTyHvj7u7SJJa7O7i9Rap7pK0xscYYe5JbeuwtKnnxxvznfB3kr+d5fq0u1HCf\nUt4emsu5RrpWK1gUHVV7wF63yOU3xD/8nvC73xF+/3v89TX++proHMX1Fe7qEnN9BaaC5hk0UxRT\n58Bqzjfvoskr9/MCQVXK8/PTJaNdbOdm0T9mOsnpizDggIiYGlMvMSuPGfrjjfBlw7Yr2V5ZtlFO\n2jmKaCliQQG4/QV2b3ChJnYlcdcQfcNwX9JJRU/J4AXfW3wfsEGoEGocRezH+pCIk0BlB+rlkAJV\nq2eYaoHRqiobIHh0X2+AGOWkNiVfx3kVvEiWyh6rpPOZE3nh4CfhDWuuNowW52IBL14Q+oHQLAn1\nkqFo6CnofUG/K/GHkuGupKPkduu42xput8nrvb6OXF9Hrq56rq56rq97rq8Dd3eBrouE4NhsSkIo\n2W4tICyXwnoRqDcdpttPEzLySl3NIWnkM58PKXIa0tJoiciEFcsloV4wSMXQOQ59amGtG1gOkxGm\nhr8aYj83j//dADwvtvlLAJOD8EPeQ36RHkcv0InFisXhOA4hk/E/LYldLolBGGxNbxsOoWDXC9ud\n0LcBNzhcsaRcP2PZ3LDq15TD7enelnONCpPWVq5oX5wOE9VNxkOYnm/ukDZigsOY9DnnvMPHSnOg\nzZ8/Z4Ap3+cFVvl78roJTQPmztFqBQvXU7b3mO6G+M3XhN//K/53v2P4wx/odju63Y7YNDRv39Jc\nXWGurqC+QJ51xxyftjbqfgEKELoEcuDNFawO4x/l9yRSOh/88egV8RlKADzmUBEwgaLyqa82DMeb\n4Cm535Rc3luut6eFS+IthBK8pUKopKZmTegcYXCEfcG+c2xby+5gObRCe4h0baSwjuergufLhqby\nmLEorCoiz9aBZ0ufWhdXNUVTI7ZArALwqXX/kKGYl34oAKt60fepAXnOO9L79GgpxpQU92FqJ3vx\nghhgKFcM1ZJW6iN/dp2lHdKxay2X12Y84OoqcnUVubyM7HYtu92O3W7Lfu/Z7TzD4AmhIcYlXbdm\nvwcRw2plWTeB2vTYdjdZxXm/qgqz5njnuc1zAKxN+uNGEL5O19J2BW1vESPUtRDixFuNvOd1SR8N\nAM+v+aEQ5EN/k89Jnr+u5MXSYjlImQoiRbKTzj5o3EU5eGGgGRdJcWzIP+yhLJepF7DpQdZUrCAu\nE3hqa1JeSq8SpZaWnqwCcN5XrDs8KwAv7pGuwITmpLry3FjKx0YPKa9zrynlkQ7dzm0e6pzX48w9\n4PUaFr6j3N5htz/A138i/P73DP/jf9D98Y/sQ2AXI/HiArm+pri8pLi8govXxDH3k4+31doOZa8a\n07nHm6f9s2mJJwZCni/6VAFY5TKI4HF0AFaQGmxpsOKPAu37gk1b8MOV5c9vZlXvvaUfLEMfWSxq\nlovIchEJA3gvDEGOwaW3N5KGnoy9100d+eJL+PKLyMXFsbU0TTJ6FjErKF8ClWBqwTqIwafIlDcp\ndJ4B8NwD1vWYn696wPnreX74QxXn/HIUIYYJsMa2sojDlyu6YsVuqLn1cDvA7UbY7rQAWfjzd/Dn\nP6fj8hLevIm8eROJsSXGe0K4JcaOGAdi7IGLsRakYrcziAjLZeSiCdSmw7b7CYDzm62FeZr6gNOc\nQA7Aml7MU4ojAHdSsz16wFA3qbzhWJldTbz+xXPAOeUnci78eK5cH/Ke/BT/L0dLY9LVcixiS8XN\nySJh7CMLCmISkSgIhjhYwlAQvbDZCVf3BVf3lutbuL4OXF15drtIUQjOCYtK+NW64tfrNV8sDHVo\nqJoVdbnDFoJ16Xin31gXguaO8+qdfPbidovsNjhZUDpPbU+9o8curGpMzK8h93KVz/ozTGtDvWBd\nJ7kMaUpxv0+/a4vpERRjoN52hE2qbDzs9+zalkPf0wIHwMRIHSNBhCiCD2nSzeEwfX/TTEZ0Lpdw\nmuvNw+I5AKtRkHvBKqTz6tjHGJrMjSflU7pfQjsu9dAbDkOBHSJhCBx6SzsYbjeWP35t+Ldv4M8/\nBEKI4wHDELNszzAenhg93gdCCGy3gc3Gs9l49vs4GkqRqrLcb0uurktWqxLnHNYWrFaWuy1sD7DZ\nZ/UkLlIZS2UKKl2TRY8tPNZbbLRY4wA5rt08G6U1PLrWdU3n6yAf9DWvbXmcNOUFo3MJjcqKwTu2\nfcN9W3CztWN4OR2aibu5iVxdheORAoNxnKdtEKkR8ZTlQFV5qspT1wsWi5qmcfzn/+T5h4s9zw4d\n1fAG120xEifFqYpgfvP1xqvgqQDDVJA16vB+9ZyufE4vz9n1a7ZDxXZv2Y76QY2uPFqXe78fhQec\nKxRdcLnXq4s3H6Ciizgvcqi16KaIBOQI4Bri1xui91a/JxU6Czq4NOWIhKG3XN0Jf/wmKYBvv4tc\nXg5cXnZsNgFjDNYaFjX8h187/sOvl3z1ZcWL1YoXy57ny46KjlI6rHTvVuJojPL29nQeYT6J5QjA\nW1zdUlWevj5N6D92AIZ3ox76XD7UIJ8clxtnmprTn1WG8tagPFSsuWJroSSw2PaE/YF4OLAfBm5j\nZAcM4+GA3lqCc+AKhmhpOzm2bGuRlxrRh8MkyznwnptJPv85f+6hPNFjBGB4V7ZzuW5b6FvD0DqG\ng7DfRW5uhbd3hssr4d++Fv70Nfz5+0CMgRgjMYbxsxIgF8UB5w4UxYEYe0IYiHGg6zq6rqdtO/re\n0/eRYYg4V3F9vWaxWFPXS4piQVEIFxeW+/tpL4i88v7ZyvBs5Xi2MizKnmXZU5Y9TiqGWKV2KCMn\nXnDuXKn4w+QRqdGlhte8GvpRg7AwFdmZpKyiJD5vdwVXN5Y318m7TR5uOvT37daz3Q5stwP7vdC2\nKe8u4jBmgUhJ0wSePYs8exZ49arg9eua169L/tMXe/7p+S3PtjeU/nvsfpPuqW6mrlaQTmnKx1Rp\n90seVlUrP2Nsv37FtnjBJrxg263YDSW7wXDIOh/y9TMfDvSLe8DzkDOcr4KdTzCLcQo/qqKrxsEJ\nKb8SCSF5u3nHgV7w+TCupJzvYOj6SNcVXN7D7/8E//2/C//6+8APP/S8edNydzcAFhHLonG8+Z8s\n921F6yy/LiL+ZaR4HcHfYf09+Hvos8kL+aSV3APO25mcO6KGbDc411ItPb45DU/m+aLHSvlCVPDM\nc6Y5CKv3lHvAx/qYrIAlDwnm6yyvQG4kcHHoCeO93/U9tyGw4WiPUYnQG4N3jugKhug4dIb9/hSA\nlaXKE5XzvLgzL/Kc7yEwn8R30r+e3afHCL5K81TDabhe2G0LdlvH27fw3Rh+/OZb+PrryJ++jnz/\nfQACMXogAOMQHSIiO0Q2iGyI8QB0QEuMB0LYE+NuDFUm8BZZYsxrjHmNc56qEsqy5PnzqcXz/n46\nZxH44nPL558b+ggvq4Gy7jB+i3UB6wzOlems4qlumW9Dp47DPD2ia+axp5UmkrFYTUNZSXH10bLp\nhasb4bvv0kyj779PhzYfvHkTGYaA9z3D0BGjJQRD8n4dIsngWSzg5cvIF1/Ab38rfPWV4auvhN/U\n9/wq3PJs+y3l/g1y2HCsllfBqqpU9fzsWWLCfD61Au88BDX+3Dcv2ZQvuA7P2QwN+4Nhd5CTglCt\n85pH8j5E29lfNYjjx7wnF1w98cIFKuupxVPHQOmh6CNWIBqXhmsYm3lHgpD2ARVCunggjYOORJ8s\n6b4VDjvL/c5weR357vuBr7/xfPPNgbdvN9zcbNhuO6AACrqu5PJ6yfeXS9bPa4oFLJ7DhY9Y01C6\nQDQxjdHR3V6226Td+z7tT6raOw9Dw3H8pWw32OWB0np8dWqYfUrgmz83L1xSAFYPQknXRl6EpxPj\nVLnnPbh9n+RuvYbORXzriV1P6Hta79nEyIa0mB1gRJCiSIMelgukLrGlPRGkXFbzgRpaTqCKdu7t\n5mNu8+ucpxjmwvrYQVgNo7wVd7MRrq60tzPw5z/3fPttz3ffDfzwQ8/1dcdm40G7FTDkySbYZ0cH\n9OOhsYwxtJLGYgF2/DliTKBtPUWRvOb1WlgsDGSRNGvTnOe6EZaryFIEX6R9YI3VEZRy3FJcrzEP\nZqmI67pIXnCkcoFCAmlCdUp1RJE03CPwqOikAA1BsBjjAIMPjtBb9q1lt59moSvu3d9PHQWHg1aX\nW2J0VJWhrg1VZWgay2LhWCwsL18Kr1+nXv7f/DryD7+J/PYfAq8ZeHbfU9wdMId9Sv5vN9PuGHkh\nhraU5mFV3be7LNNmHqbAG4cPgvep5/sqvuL7zQXfb0p2gzsaWXAaoYRTXfahWgz/6hxwzrT3UR4V\nqFyksT1NbGmGPilLH6FP1WmmrJDCEJ2MCjEed18heGTcwUQghbWCh8HTtpZ2U3F7W3J56Xnz5sCb\nN3uurjbsdjf0/Q0pO1gBJSEs2O89NzcFb94sWK+TUbXdQLkoWCxqWMixGCGGkMaiQfKKrZ3G4uUN\npDEeW5Rku8ENBwrjCdUp2Dx2r+gc5V7wvK9bvRG9dlVyeV5F828aRtTgguZt12v47DMYqkjoPfQD\nPgPgLbBk5LAIrihSk/1qhV3UFI2lrtPn533pCp45iKrHm1c455XO83ajPFd0TmAfO6/zgqUcgO/v\nU/jx66/h2289P/yw5/vvd1xebtlsdhwOOxKw1uNRwXEojQA7klz2gCeBsyEBbZm9z5JUVUPickmM\ndjTsPPt9z91dykuK2OO9L4q0bo4tZ5VhEEcsCqSwowcMhFMPOO9u2Wym7S3X67HNuYwU1uPigB0C\n0VowlmgMEgQ/1rE8FsojmIhBJIWkYoB+sPRBTtr28qlxbZtXi8vo9QIYnj0TXrwQnj8XXr82vHqV\ngFcHZ61W8Ppl5PPXni9ee9atp+k81sRpzK/27opMPUF5a4RWNi8WJ60I3jZ0tqa3NW0rtJ1waOH7\n+wXf3K345tbS+lP8zvcOyVOm+QEfQQ74p4RacuOkKQIL6Viwo/YtJk2RA2tST5+ziClxErE2WbL0\nAZEBGfpT4zkOEHrwA6YtaDeGm7eOy8vA5eWBH3645+rqLSFc4v0lSdgboCGENft9wc3NmqZJ0YxX\nr2CzhaZKG7OzKsAkqxaEaGzafk01+DkADmEC4M0G27eUdoDq1BP6FHLAOeVpgnMesC5mfZ8qOX1O\n/0Zl7uZm2td9u02f89lno2dsAr73xL4nDANtCGxHD7gkqe/CGFxZIosFrFfYZU3ZuGOYOC8iO6ZD\nZjMhjrMFsi1P5835ec3HVFx4vp3uMVMOwFpcqfn5H36Af/s3+OMfPZeXBy4vb7m9vWEYbvH+juTd\nXozHmlNv+AC0JJDWBIJ6u5CAV8G4JIF4QwJgg/cR7weM6cfxv+ZYV6Ae67NnEwD3K4MnWUviHGYE\n4DBMfFIvX1v+teFB043GJAAuJW0eYP0AUoCNRFOM9+txMf0UgNOCjmLxAdo+Fd3ppnL51qKafcvb\ntTTsbIzj4gK+/FL41a/gH/8xhZt/+9upXqIoYL0IPF95nq8GqvsBs/EYGZmg9TbDkABW5FRYdeMP\nHSqQTSj0bk1nVxzcis0uGRBb4Nu3lj9dW/74jWXwp339Gq3VKcYq2x/SkP5ZBnHklFsNqfo1HieX\nNcZTdS1Fu8EN24nrxhw5GWPEMAEffZdmPXddugH6BWMeCSf03vD2RvjT18Kf/uR586Zls9nSdXeA\nHns0pBVjyTAMHA7huBmLYuhub7jfQ9mkux4xBISirymloaoaRCt20oedJsnG+LkQMCbiLMRieqve\no0+FzhUbzYFVAwZ5zjcPyatX3HWB7TZycxPZbAK7Xfp9szFst5bNxrL3nn5/IOxTDCy2LdH7o9qu\ngEaEwlqMNhw7lzZwD9OWgnd37040zAsv8rnU8x7Ah0LL5/j6YyNFj4EUhLVn+v4+deKlXGDk9rbj\n7m7Pfr8hyVtLCiVHFEidS4WQzgnWCs5ZrC2xNmb1AJo3Dlirr5eIFISQhjYMQ0HblrStRcRgrRzr\nTnTd5WI6DND2hn3v2HQVgiOE5K0N/nR78Dz9oXyzJuJMpHKRSnqcP2C6PSaO+ZFYEcuIiQ4jp62V\nj4kiQoipwLX3aSpUnhaah9dFpr7+xUJGOUkbLHz+OXz5Jfz618mAfv58mul+NJIKTy0t1XCgbO9h\ndw/3d0lIR4snVjVxdUF88Zr46nPkYo1pFkhe3ZmXqVtHT8Eu1NwPC272hptxGNZ313B5C3f3UyQu\n3944b5+c67OPHoBzxashPWNg0cBiCU30lIc9dnsHm5tJK4ucDuEVM25fZdIMaNWUeY9LFvPfx4Lv\nrwv+5V+Ef/mXwJs3HYfDlmTzqCLIw1xy0iqVbxJ/vxHEJOs6xHFWbICVNzwbSlzVYPLu7HmpnJ5b\nUWCcwRZCdKc4/Sl4RvPzPwcw+XrIj5x9eU99Mog8t7cprNh1A94P9H3Bbldxf1+z7Qa6zZawvUbe\nvsVtt5TeE0i+0WJ8LI3BjlXQXhy9l+MErJubFDpVQNEir3N7AOd97fr+PEeUVwqfeBJMIfmH7s9j\nJJ0IqamCmxttRYnsdgPDoB4tpJoLR/J8nwMvKUvDYpHytdqClI54DAGmKXepWKsohKZxNI1FxDEM\nlr63bLeOt28t19eW3c5SlpaiSDe7qtJow+fPU5hTozBtb7g/FFRbwXQWcRacvLMzl64Bjd4tFrBc\nRBaVp7aekhbX7TD7DfgueRc+7epgXExtjI8IgOdG5LmIR94OOFfBdT3JkHqUTZOA98sv0z7dzTiF\n7u3bKZ1bVVD0A327J5Z3aSFdXqawyu1tOonlkrhY4r/4Nf43XxG/+DLNES8MNuUiJyTNqPWejQ9c\nD/DmaqrWHocWHo0rBV/15P/WcvpBAVjDQU2TFnAzeCTsMZvxZuc1/noHhuE0ida2cGjTMNk8Uaem\nVF2ziwXfXxv+3//P8K//Gri/72jbHZBb4nMAlndyWrrZhg+pfF5f7wd4VVpsU7JuFlNsMk8C5ivT\nOaRwmMJinYCb7IzHVqDxPlIAemjR5uH2uVesuWFt71MA3mwGbm97uq4lhHR0Xc1+L2w2Jdv9QHu/\nJdy/xdzc4HY7ylH4FIAXIpTWYscqaI+l94Z2SCHFm5sk57lXq9Xa57aYy8E37wDQc1e+qtLOc976\n3KcCwHkUYbOZdvp8+zbivcf7jimkXIxHAmCRl1SVsFoZnj8X1uvIeh1ZrQIXF9P872ldRZpGuLhI\nhzHC4ZBk8+1b4U9/Er7+Wri6SvIcQqodUQB+9WoC4BCgHQybg2C2NnngTjDulMd55bNGPEVG/VV5\natdTxRbpdsj2PumlY7NwGiRhnXtUAAyn6/ohANZ7MgdgVeG68ZxuPvfll+n4/PMpv35zM6V5hgGa\nbmBwO6K9nbamfPNmyj0tl8SXr/Ff/Ir+118RP/8Shj3GH6AfhwXoiSrFSHcY2LSB6zZFaP7851Sp\nrXM5VJbzrd3zeRV/K/rZQ9Bwqmidibg4UPqBot9Bt4fDWEqXbyumf6umlGrHfBNW5XhV4W1BKCN+\nsGxbx80dvLmMXF2lPsJh0PxSTwo9jyHtMf+UwiRyrFwF0MHsqZpvpoCjHKsdj4lDXUnaSJrvkmQt\nYpMn/6lUw+aUX8/7wGXeqjaPAqhgJhZHus5zOPR4rxWxHSIOa0OybRiw7R65vcHc3uIOByrvMYwZ\nfhEqYyicw5QloSjZtY6re8N3uySI2kaRF1dpGO2hjdbnx08B1U8FfPO1O8+8gGBMATQ4t6IohKIw\nOFfg3DOcW1KWDS9eCC9fCi9fjltNrkfgXQVWy8DFMqVuYkhDd5rCc7EYWDcDxkLrC9rguHrmcCIQ\nDUVhjl6sMWnjs4uLaROP5HGlBdcNaViH5vHVO1Z+556QBrWqClbLSFN6Snqs76A7pPF6h8wx+FC7\ntn9g+ks6SWX1TJDvOKJTjRXdxUzvfzO2YM4nQ+qtWlaRvvDEsp+QfL75w2dfwOvP4MVL4sUzQmsZ\nDkIMEeMCUnhMnvy3aYBIHCOd+aG93Jr6Utn8MRsv5HL8c+nxnxWA8xDc8WT9kBZqv4PuLlk22hys\niXaNA8AkRcr1fC6cmlsh4G1NawYOMpbC7wKHQ1Lg3g+EoO0Mmn8yaCuDSCqNXy5TkcZyOYVD9Tq8\nnxZZUcDaBmozYIYxaah75mlDad9PK9LpAjAJtD+ZHsGfRvPe8JyV87BfEsqI94EUqUg9o2AoCkkV\nk6/hRTuwuNpjd/eYzYbicKDxngKoRSiNobAWWxRIVeGLhuurgj98Z/j/vpss4e+/nzoZlsvTrRLP\ngfA5Hs7D6+cK7T6FdAOcKmG9V6oj12tYrx3erwghYsxq9GaF9dqxXK5YrWpWK62KTSC5WnIcRVm7\nntqmw8TUeRBDpPQHar+hvtsi1jDUa4ZmTfW8od2WdG1FUZqTCIue15SbTDxWQ1ttfgWOfC1qrhNO\nK/nXi0hdeGzop4SxLpTjIgnEbJ1/7HTOiM694LyNcO5fZBnA49/O3weTitcteXW3Mb1H6wCdMUQz\nhkpfvpyUxQjA8vwl5sUzbFOAE4IvCQUMweKwOLGYIk8HOpwpqY1jZVMqQg0rzfVqvlezm2X5bn46\nL8DKe8t/8Sroh2gOvjECwadQQbiDw82UXM+rOfJ9eHUUCUyP+oGZVhxkyV48GyL3m8huFzkcPH2f\nwDfNGVUATv2B2ikqYinLtOuGbimZT7TRm+3ctAnA2gfq3mO6fnpRBxRr34J6xlkp7DsGyd8RnQtn\nzTe3z9MAwxAIwZP4phpMKEthvRZevYKXG89CDtjdPXJ/T3E4UIdAAGpjqIyhdO7YBzy4mrebkj/8\nyfLff5ciXKl3NQmmhqI0oHFuH2ANJed8nOe350Kpr31KlKeXFIBVBC4uLH2/YhhqnBv47DPh88/h\n88+Fly8LXr92vHyZwPc4R6GONFWgqSJ26LH9AdvtEe+JIRVfmO0d9uYKe3uFOEcoPiPUA02dRhx2\n3lEt3YnS1DUHU5BKtwVXtZNfT24E9pkjpiNLmwbWTaR2IwDrhKEcSVKYLO3G5uNHD8DvKybMaxg0\nfD/fhTWfGKcUwrsAPAwT+G63k/+lt2xvhL42BGOTstUvg2niyfoC8+IC25TgDIMv6YMjxoLKWIwz\n4PORVRZnKipjWVrhWbYXg2Yvl8vEb+1nFnl356M5AD8KD3heUWpCwHQtHDbp0H08p7jvZHrmz+Um\nB4yJmOXRhOn65Ple7oSrq8D9fUvXdXivhVc6WUfDz46UjyoRqXCuoKpMFqI6DUE4B1UZWDaRi2Wk\n6Txl8Ej0U9JQNZAaEWp+j6sw2lR9+ylVwsLDi++hoqW5x5sf+V6swyBjC4fBWodzBucMFxcFL18Y\nPn8deWEGFq7FtjvCboftOoqQejGLusbVNfLsBX5xQXBLtr7m8s7x9bcy1gfA/b2w2chRIOv6tAo2\nz3nNPeD8eKhC8rGmG96Xy1fRrKrIcpkCW69epUKb3Q6axjIMlmHcyu2LL/SIvH6dohevX8F6FZPH\nvIqUZaQs0iEtxF0k7iIyeBh6xA9Iv4VwA/vLJJS+ALvAVA2fvyjoJNA8188BYyJtKxxaoR+E5XJq\ne9HIVoynQbiHjEP19JoGmipQ0GHaPfTbU3dOE5pBPffHE4U+t0an9FA8rnOdO7RYwOEgx5YkjRTq\nIB1t88sDnDFOXrCqeb3HUQxRdz+gnNqNslCGLFdIXWGcJRjwYumiZQiWaCJSREwxpvycQazBiaMh\nchEP0ESKLtD0gbKC5UpYroRuMNzX6QgYylooK0PdyDF0rqFq+DBdLD8bAOcgk+cLyhhwcVy4mlxV\nraeVT1rhrB5wbo7mYPzZZ8mUXS45DAsub0v+uBW++Wbg5mZL398DV8ANqQBrnE51bOavSI38a6DB\nGHfSp5z3p5UlrJrAshhYmIHK9Dgbx8pJd/pGjXnlc0oXC2JZEo19NML4lygHlnxRzoF3HlrOI3a5\nssvBLukvS4wVxghVlYpzVqvIb35l+dXnli9fB14NPYuiw/iWMGpPGU1vefkSXr0i/ON/ZP/8V+x5\nxpv7ih/eGn64jHz/fU/bGg4HQ9fZk3M714JyVBLxPAi/Lzz9WGluXMBp9brKdlNDOYbyXr5MlaV5\n6PLiYtpofb0ec72rSF0G6jJQGY8TgxmVbTAO72pCaRBabAQ7zZydQhXjAnL1wMUq8GUdWXsoTMCZ\nNJAXe3oAACAASURBVKyn7S2H3tAN9sTLzXWTAkrfp2vMi+by1INevyVgugPS3cL+7TQGSuOuiwUM\nA1KE48Cgj53OhVNzGS9c3k6agpn5e3QGxv19eo+OSPB+yixqxbzKU+67rNewWAllYzFlkbxYxQCY\nQKQokWHAxCTrQy8c9qkgL817r8FZXCG4wmAdlL1nafaY6Klixzq27OlwUagGS9VZBlNw0VQcqpLg\nSkxVYKoCW9qz/f66fn5O+iAhaJg8ySIEXOgRBWBFPJH0u15pHoLW+W/KRdWKuoXNYsH+fsHlXckf\nvjF8/XXLzc2Gvr8CLpkAeM/UCjEBsMgakRpj3OTtnhk3uKo8y7JnIS3O9BgbkPmgY/1DTSSOO8fH\nxQLK6sQD/hTonNA+VDn5EAAfq8v7eZVlGjUo4miayIsX8NlnkV//OvLrL+DLzzwvdz1F0WGHjn5M\n5kmMiWEvXiD/+I+Ef0oA/DY+54e7ih/eRr5/E/jhh4EQ3Fgxe1rflxsCc0/ooZakszUPj5jOXUse\nZtcMy6KB8Czy/Dm8eiV89dXUf5u/73gUyXMuC7AxYGOPiwNiCsQ4EIO3BUNhGWKJjQaCx0ib5mad\nCacU4nm2DlQV9DZio8eGAYKn9QUHX9D6SY3opFgR8pHtbDanw1j06/I8rrVg8cmJuL+D++spnjrq\no5RkTN+fZgD8LTn30+mh6M3JaxZcBIg4A0Q58jhvNT0CdCb/2lmSr4l8j4SmScbZcgRgKR10dgpP\n5FVwfZeiIdFDDAy9GcPaAk2BGIPYksqBlGBLKNotInuquMXHLQNbPFtMMBhfYPuCWDUMiyW+XhKq\nBaGCUFqis++kmuDDyPkHAeC81aTsIzYOSNdOgHuumSwHYM0Na7441+bGwGLBYdPwdlPwzbfCd98N\n3N3tGYZb4JY09aol5RFLEgjXGLPAmBVFsaKu0xZYWminuZ66jtOm6ybQmJ6KFqPV1MLpuevu8QoC\navav1sSqTjNJR0v6MVjFD9FDwjr3CPNQc77R/TlQzgdhADhnaRrLep28qi++gF/9Cn715cDr1wMv\nng2smkB0nhiH4wAOA4SiSB7wb3+L/+o/slt/ydthzffXBZdve65vAre3wwgocrTUc5Cd//4Q2L6v\nKvqdGohHSHMAFiLWRAqTxtIY4zF4gou8qKB7lipSrYn8/+y9aaxs23bf9Rtzrq6qdnuae+599177\nueElDsIGQ4KVBPyMFQyJ5AASJphAQBgSCUQEyKH5wDMCQiJDROJIRBGJMYoRbexIEcJgeH5GiCbg\niCDFzgPbz7zuNu90u6lmNXPwYa5Ra9Y6tU9z7973nL1PDWmdfXbtqlVrrTHn/I/xH83MvOKcsN6s\n13ucE8RLrAhoAjQhdr/Q2O6QTqBTtA2ENiB1A4vluq/6mrvM87Wl5OmYVoHqIEAZP+PqJTQtKwpq\n7ViGnBNxaBcZj3GSnGqfgJMHXK4UEhAXg1YBqLxSiVKqUrRzsvkp7tFDeHSfdQcfiAvI4SHUDVJ2\n0SC8JmL6JX02KCKKoDjpjxx04nDikMS4UJWNHu7GKlhajz3ztJWrYURMWHZInhHyki4UiI97AhA6\nAg5VR+gcoRa6BSxrODtVzk6F84UgzpOVnsIpmXRoaJG2JWsWZPVpZCvqM2hOIZxB62CVQ8hBZlAu\nIW/oqpa2UtrK0Waxd3QbXKx+Seb8s6o+XlSuhIKGwdHNfA/ATT0EDawPoQVaLIaSHilqWWaF8cTT\nKY0rOV1m3L8vPHwYmM9bus7KjpTB690D9nDumLI8pKr2ODiYcPduwZtvet5+OzLbloy13gGngjIE\nsnExnF2b1SdMp8P/qyoGu+7eRY9v0U1mdJKvW9iliTnXGYxNtsVFLaRvk9KSL1LgNY8z7a9iCZCT\nScyQvX071g/euwdv3BP2DjySgzqP9iuA9IcDJM9xR0fIu+/SvftpzlZ3+OB0wtcewsOHHatVLGka\nwhFRxh2uxvd2kfdrgG1dvtIa4acluLzKklKLJiEQqT+NC5trVms2S+oG1yp5o2jX4UIX57qjn0xT\nmE7QoiKUMdHCBXC23ndtTLharXCLmux8iZwvcSePcI/vR6B7/Cjy2ycn8ZzWfFhjn3inHdrWuPk5\ncnqCLhZ4V5L7AqSk7SaEskL85Ak9WkZs5Vv2ipq9osYTCAoaoMgCM9cyW7VMVg8pHr6H+/A9ePDB\n4AGLDO7c4SGUEyR0r7zO0/HtHDiJh2iI178+WuhanDpyLZjkBV3lWRbSl5oNy3JZDlFD2+PbEpls\n2azrzXav09yzNylZOHBFwM86sqBoUOpiRpPPWPkZ52cz5ucF551wPnecnQttN5Q+ZV5xyznSnEF9\nGgvU7Uj7ZsLgmpvFcH6O7B/g9ldkBy1SzWL3tbygI9vIB7nsmv4ro6DXHY98iJPXXKGmGbRi8WDn\nBrp5XBGdpl4m+4HVvuJsmfGNB8LDh8p83vQAbE0ADIBjEwDnblFVh+zt7XHr1oS7dz1vveX41KdY\nZ2bOZspkPTiUbBnwy74PdcqZmgmX5q5b2vzduxGEj24RZEbbA7ANRrul6y4XgW+a2Zz20zWPN929\n0cDY1jCLMEAEYUveeeOeY+9QcIUQesoSZA2+HtCiwB0fwzvv0L37aU6/csCH9yd87WvKgwcdy2Xc\n6i6+O6ZobstkTjMexyB8UZKZffYiIL5Oss0IiVZVg2OFzM+Qk8dw8hhZLPBtwLUd2kSWS5q+Zezx\nLbh1jB4do7MDAp7OFWRBQHsTqG2h7ZCuxZ2cISenuMcnyP1v4D78APnwA5ifDwNGdagT0oBoiJRv\nB3J+Bg8fIqcn+LxEigqfV4TiECkc2d5kw4Y28N3bg5lr2XcLDvw5GV28b8CHljysyFcr/MkDsgfv\n4T98Hz58fwBg52Iws7caZbqPhPaVp6BN1uu1EDe/6aKxFXeCq6PjVNc48eTlFF8KoXLMyxhayDLZ\naM9s8V5r22Dzy4DZMqVtvs8mnoODkoWLmexlCHgHXYA622fh9zhtJtw/zXlwknMydzSN0PT9mvb2\nen/IKX41Rx7fh0cfDkbb6ekwgWEzyJ/ncXGqKmQ+x7fdmh3TSgmZp/PZRtKe+V6XJVcGwGkiFoRo\nSRm4jnsSGrW0zb9PRrIm5lbrCha14+RUODtTlstA11n9qCMusiXRAz7C+2MmkwOOjmbcvVtx717s\n0vLWWxFD1zR0FcF3OgGCQq1I6DaVaIEko9P7lVb39uDWbTi+Rdg/JDQ5bZOtY0nXdVEeyzbwHXu/\nZm8Zi2hN3FM6Os21sGx0Ow4PWdeL3rqlTCeK6zMzzfM1XzYHNMtx+4foG29S3/kUZ+/lfOM05733\n4PFjZbUKQIdIQETXUZCLdi8aD8WLjI0UiO1zqaV8nXSdeuxm/6oSdwPrGqRb4s5P4eGDdbcib4hm\nCl97F0vQDnVxA4TgSkJWEUKH0w5Ci5g1tlohjx7Cgwf4Bw+GzWbfe2+zBa0xZRb3D100jrs2bl13\ndoqenOCqCte1KB2TssKVLdmeRhyvY3/jsgQNseHHTFsOdMm+npHTDkq2ll+LBTy+Dw/ehw/6Li5G\n7eR5pGrSAtdwPSjojVCD0c0EaOuhBXBf4SHe47zAJKMrMorckWd+Iw3Gklhjrpyu51DMiNb1Eedc\n7GyW50I5yan2c9oCqhCYOKET4Yx9zsI+j1YlHzyKj/30dJizk4kSmoB0Mc/ILc+Rx32bOwNf+0CK\nM6nl378udR3ze6qYjBWKDCcVOuoNYWTsZcmlUtCpt7AWkXhjBp4maTTfzFEj2W31SluMrYNxgDic\nd2S59LGF2HFHpCI2I2z7o0LkAJFjiuKI4+Mpb7+d8elPw7vvRvC9cydtXiU4r4gIisZYRJ6jVYWk\ncWu7Hqu5sHubzQizfUI+oZOc0G/rZbe07ed1kTEYjf9mIGT7qNouMttYIHs/bNpgh4dDCD2Ny5eu\nIa9XuEdL3MljpM+mz5yj6lEv+AxHTt3knK5yHp97Hp04Hj8W5vOMpqkAT5aVFH2WY7qpelq/uG1b\nwbQmML3vlMZL48Wwndq+LpLS0dJFD5h6Nexk8ainhm0xM57OWK2E8nCLczLnEQ340OBCA6HZ3HDX\nmko/fBgHjMUtLBnHVnlrAQvx/DAk7lgsY28P9vZhNsOVe+RljuSBzAltDmUnaBO9b21bymZB0S5x\nTQ3tanCTzYI8P48Gh/U0/PDD4T22J21VbeR9vOp1wBuiPecedJjA6Sa/y+VQk5NliHd4zckz6ff8\nHfLQzs+HebVYKKenymIR6LqmP2rOzjwPH+a8/37G++97vvY1x5e/7DmoPBOpmAgowkJLFjjm9aCG\nEKJRfnwMt48Ctydz9pbnZB+e408fxUZJKcNqrY1teyzYrLAxejLLIpOxWBAWK2rXUhOos81dn7pu\ngIDLkEtvRflEJqW5wrbK2h/H6ZVlOXiWMKzmBnTJyqYSkzo2AbjAuYrNDb0niBzg3BFFccTRUc7b\nb+d867dGAH7zzQjAdt3Q1305AEG9R7J86NJh95Emixl/Op2i0z3CbI82r2glJ4hbA/A28L1uC/O2\n5KL0NVOZNeo/PR1A2AZxncyPNPvUYsB378YjTf+vfEO+OsN3J7iTx713FfDOUTlH5hytz2k1Z9UW\nnC1zTs4j+D56JMznOU0jiORkWUZZZknS3ZNdfsbt6MZF+eNnYiBsnqMN7+uo41TWIKwB6doBgG0X\nhocPNzdttgdnq3Fdw2qJ8z6GC0Jf29u20DXD7u62B+XD6AVzcjK0qh2XKVjarXmotkbYe6dT2D9A\ne0vOuZzcx1amuco6qUbrDlY1ulqRdQuysESaVezaZ/dk8ZMxAH/jG8OAsATSqorVDz0AX6M8rH4A\nK9ANxbunp/H+DYCTTbOlyPEh7jhmajHH0ioyqwpOT5VHjzo+/DAQwhLVOSEsKIqCoigpiorj45zb\nt3Nu33bszzzTomRaeESEVZdRB0ebsDGzWSQcbt+Gt98IHLTnzFb3yc8exvBHUw/1crZOW3sr2zUC\nNik4w53+fsOyppaWuSrLbPADVYehd1lyJRT0RtaoCPgMsRQ4c5Vgs7loCtRWQJZlw0PqeXtVBSJ9\nYdhYFA7vc0QmxMzneIhM8f6ALDtkOj3k1q3YOOCbvxnefjsq8vh4M9Fa+lUnKIg4yHrAtWLxto11\np3U9AHPsxYdO9gjFlC4zAAZGMcbrCr4mG8bV6LXUA+63RV4DcOoo2VAwlVfVEEZ7442oI5s7TQNl\n25I1c9ziUaRAm0hLuqIg6xfCOi85lYJVm3O6zDmdw8kZnJ0pq5VH1fXruDCZiJWTrxeL5/GCUz0+\nLQZucl3igE+TOE6V9Z595hU+fhwB0yha1c0ekEYtLxZ9KVEXvcu0ENzAzXbIsMO8LwvWpsX6qXcz\n3iWg3/2KvVmfFHUUjQeLF6eWsO+AGsIy9nXWnp824LXr6mOJagD8/vvDlj6TydC7fg3AJeqvWe2/\nwrp7SArA5+ebANzn4IhGAC58TlnqWg11LRuJrCEoJyeB997rUK2J1SmnxH2dY6gwdiN0HB15ZjPH\nbFYwnRY4N+xS5f0wV8tSKXPl1qHy1p2a8sEZ5el9skcfPDlBx7VkZTk0gjKGxhazPF9n24dVQ03H\nPCiLZMdDY7leSQAeM8Z2f9I6vMvxZRU3SLfJpzqsxNZGJY2xmusBG/0Kpa7ReoXrSjJxFLknzzO8\nj3RzLDuKUhQVR0cHHB0VvPVW9HrfeKNPVuxr/tKucmmgvetAgkM6D12BV4nbgztNaqyKDXpMy5LO\n5bS91TYuP0rrya67jHMaxs010rX6/HxT7QZ4e3tDnPfoKE4wiOufdaDJY/tXfEjqfftyo3XtdZbR\n3fs0y/03OG0mnJwMXXn29mIj/sPD+JotENPpk80irLW3xbOsLZ3Zh6mMCZzx/sHjZu/XTVLDwgWJ\nmec+swDfZoq71cPCEGc7PY2/L5dDbAE2k2DSTD3LAbFNDYxhssQrY5pOTyMwmrVUVUNrJVtsQ0CW\ni8iUwbrEZsOaSoE7tajSerTFInrkH3wA771HePgQ7QuKpaqQw0Pkzp04gPf3YTpBshLJslfewN5g\nsYixcJwOPPKjR/FZG3VlvSW7DjdbURVHhAKkAhpPWzsWhV/T0REwhcnE945nRtcVdF3J0JtBaFtl\nsWhxTqlrx3zuqarYKtjCU5bb+tZb8Pa9lncPTjmen1F+9TH5yQPcyX04O9ksWTDjwYBpnBV6cjLQ\n02Yp9xU5YTKloWDVOFbds1mwjyOXCsCpc7su222F3OVIOcFNV5tIlwKwPSjYXN1gmKxrEF7huppM\ncvLckece7ycY7RxTczx5XnLr1oR33sn5pm+Cd94ZALiqBkPoIgBGHRIyCI7YKE1xLsSNoA2ALTN7\nMoGiInQ5bedokhjQ0+pnr7OM62dTEK5HzkSaxu9cfGS2Z2vfwGo9x8/PB4+0LCFH8U1MFLGGG7zz\nTvxw/6Zw9DbL/bucNhWnpwMA7+/bd8r6e+286WYM5hFHwB7o6NSoHktqJ6ax7BSA4XrqOZ3PLkis\nybSbSgHYulnAMBcMgK3bhYGrKdgG/xiAYdiSyihlY5uMSrTv29tbe52U5WDxG7AulkiTeNB+lHWX\ntsbadtPWxPjBA/jqV9H330cfPaJbLmOGdFXhDw/7ioejHoCnIDni/CsPwJCEj+zf0OvEANgsWZtM\nvd7dwYryWGPnqCqnaXKWdZ5WifbNAIXJxFFVQl3HNsARgK1CRWjbsI4RLxYZeV6Q524I5ffz8e5d\n+PZvh0/fa7lVP+Z4/h7lww9xizPc/AwW55sewDh/yFjVlJ5Ld4+w8TmdotWEti5i1zwddk+6Cvby\n0gE4rffKc2LnEcnJygq66ZAlOQZgs1JMUg+4B2Cph+w81zZk4iiLjKLwZFmVUH4lUFAUGbduOd59\nV/j2b98EYMsHSz3gtANSDEW7SEMDhYCXgEo3eMBlGTOzewDWrKRbOppa1ntKPE1p13Fhhidp16d5\nwBbiMzFQM9r58DAC8J07w+fn8/i8zAPNFfyq/0Lrffjuu0PQaTIhTN5gObnLaTvhZJkCsKybrRg7\naoeBsS0aZrlb/HncmjwV02kaRUl2orx2SXZjSRktHyTmM/j+wYw9YPN2rSOcAavVbFiM1BKW7DDQ\nnM8HMDQPeLkc1oXValgvzAO2dcR2g+j7IIr1Glguhrh0SkvY/9NclNRSGgPww4dx+6z33iPUNd1q\nFZMyqwp3dNRv0dV7wJMpoi4a7tdE96o9A93/u56Algy3HgQ+PvPzc3xd48uc6nhKXk1YrYR54SkK\nTQA4bnZjjBPkhFAg0qIaHSRw/cYVHctlh3MB52If+L29YdiUpXL3Lnzbtwmfeasl//Jjiv/va+Tv\nfXlzwbHYvYUvTd/mwKUAfHIyPADvoxGS58hkglZT2qZg2XpW7ZCrkvqElyUfGYC30WvpWF4nmKmQ\n49EsH7YTTBttpCmxVppkK2C6iqkOyRBf+hIHqwXfcnyL1Xfe4vZdz1e+kvGVr5S9MR53PDo4cHzL\ntwjvvivcuRPniAGvGQsWazTwTeegLapZBrlYA4GkBEkV9RnBFXSdp1VH29mGAq+HpElYqTdsa5/1\nKEhzaWzNsn1Djf5N29dtJEW5HCdTJD+CbjX0F+y6NYfspncp3S1mruRWb/zs7Q2VIuMkK7sWswHT\n7dXSeH1aagTD6+maflEp042RtUImA02wtxefvT1I1fhauuuBTSxb8CwL1R6QlYqYxZUWyxv3aHkj\nqutci/VGswak5vGkVmE6oe01izsZsG+rm0s9JCtq7bdFc1WFDwGdTnF37iC3b0fvdzLpvfVYQ0yf\n6HUtxRbucQs7o+0t8bRPiPMNTJspR26G25sw8xkH04zj42yj5eR87pnPC+bzSDU3jadpfD+3AiEE\nvPcURUaeCwcHQ0uFd9+Fu7eVvUkg9x2Z01gSZcag6c10OqalUpp5nBRsKdVv3IPj41hKOqmQOscv\nJfYkHxnUL90DHi8w49BtSrt7hA6PZsWQYJVOmHHWyrZVzb7k/DzGY6qKg4OOTx97Zp865N67Offu\n5dy54zg5iclTIjHA/9ZbwptvRmXu7z+5K0oKGOP+H5Z0WRQxauGDQJANk0glo/UFTedpgosd9q7r\n5PuIMvaI04xB29zEaF/rdGUAbOvp3t7QKhw2gTHLM1w+hYkM5SuLRXxj33nMTW5RtkfM2pJbzZAt\naUyEHWNHaNxwfTy5UqPCEjFsDo+dqxsJvhDpW1eA14Em2N8fYgXpNnLWa9AWctUhc9ooaHtA5s0u\nFpsLJgwFpWlGZzpgDIDHYAvDazYQU08YNi2rJL/kCYoyAWCZThHv8X3SpRgAHx8P3fC6mFhkuwhd\nS0npWmucZKCbJi71WdGuVSbFAVK0TPYCB7OShVbMu2y94cLt23B25jk7Kzg785yfC/O5MJ+7Xk1x\nC8csc2vK+vAwzt+7d+Gdt+HO7cBsEshdiKWiTjbDIdYUZRstlSZxpAA8mUQD6t49uPcGHN9CZ3tQ\nTXALj88dmT6ZgHmZ8sIAPC6vSME3zWdYe8AitGTRA9ZisKbGtA886VqM3zefRwAOgcNvzdj71AHf\n9JmWt+fCnTvR6ooAPADoevPvvWF9gE2vZpy5nZYzWmggR3CtICrDteU5gYyWgrrLaFQI16cO/9Jk\nW/5K6gHbHhXrvZX3N71fW1PTkP8GAGc5TmYIJWg3ALD3MWX67bdxkyOK84zZeY5vNomUlHQZJ1TY\n/9M4djoG7DUb1zYktyVdXdUkfenifGx7VLgnPeC0fezY+zRD22qHxw/GKOzFYmCVzIof9w2AJwHY\nckdSgx42gdUGooUvYNOoT/umPocHTFnG+757NyKLZQ/28WoloFzjDVhMf+YBW/mCWdRWmdIzFa7r\nmB43TCol7AlNCW2Zs8qium7fjuWeJye+P57sEmkssjUWnM2Giog33oA37+mGBxzb34084PPzYdFI\nd30Yx4RS73g6TQD4Xg8U+5BXSAk+j8nyV2lcX3od8BPgvA6EetBsU4kpoZ4G3dJAXZpOulzGiaGK\nzGZkB/vo/pR9ucW9vCK8MeHsMO7BG3DkhVsn16Tsl321JEaUzcPUkEhZNHFCJrEuWIMnBEVFqTvP\nqstYtkLbU8/j0NJVUBcvW9IkspSWNYeoaQb6CQYAns2UvfUBB/vKXqmUomgGroxsQ1EKVS4UvnfA\nnIBk6GQaJ0oX0VSPbqHllJDluNyTFUJBoPQdhW/JpaPrAp0GQhdwCM45RAXnPC7zuNzTdjF80PjY\niH3s9Rqzk2Y+jyfkTdJvmgcp0icSm8JN2WmvwdSKMeslXciXy83d22EAN/Nm09hAD3aaxA50/wC9\nfZdweBsm+0hRIHm/G05Q6MLQ9Ac2r8kSuazmOJ3cjx/H1x4/jobC2dlmYliex/PaII7t2eD2bfT4\nVmzAUVSxT7k6QriGAJyWaKUHbCZB2CBfreDsLD4XYoKkdC0U50hxgmQVh6cCtVAIHO9PmM8qzu9V\nPHzkePAg5reZ/bVYRLWbcW4AbHbO3j7khcSGSEU+5BSYXlN6a5v3G8IQ3+ozM/X4Fvqpd9A3P0U4\nvktX7hO6nGWQdcPGbcb1S6egL5IUvNYXKkLs9O3j16XcXSqphZIG7VIArushNb6qoJogWUa1f87t\n7Jj8zi2WMqUho1VBkrlslU6WbJVmqtr8tM2iU69oDcyZW7djU1W6FjpVanWsWsdyJbSJh5XaFjeS\nlmQzj8UGqyVhwKa3uG6+PoXZRJlNIqVU5nGP2BxFPOQFVI64t2cm5M7hXNxJBydoNYl9hm2rx8mU\nUFSx65iLnyEESqmpdEUeVmjbEpom9ivOPKIe0QzJCkQKxBe0LqNxDuc9TeLxppUqF61PN1XW9yuK\nEGIt7xiEn0BqGaoZ0ollHmYqNtetnt6O2WyoEZvtwWyKTmfoZEY72aOrZlBWuNzjCh+vLwRc6CD4\nofGClRJZrbKVS43R8eQkJh1Z4pHR4gbAlhhg9I0B8K2+3/XGzmcO5TrGgGXTmBqn8sNA35oXkz7P\nEGBVI1lOlhWIz5mtBL9yTFuhnt2i3rtFvVdy/2FM5dnbGx73yUlUm/Xlt8TMO3fg+Ahms9h4Cfyw\nB7s1grbkPRh0my7kaWKdc3FcHR+jt+4Q3n6H8ObbtAe3aPIpbZOxtDLUEaZfBcN1aQCcLlBPDD7n\nIPMgI85u7EbZqpe2d0wB2CYyRED3HlCqt5YUb3Yc3y5ophlLhaX6dbjWQkXW3c6sGzu1ZW0vFsPX\n2utDDoLgsows1/i6Qhvi1g+rVlisBrbLbmfsCd8kSXU89oBns6HDVdrf2XaZmpTKtAxMiq5vlNAh\nGigyUB8jFeId4l3Us/Q/ne97U5ZweBTnvTo6HKEVxPeJuhooQ0MVFpTdeWwAUdvehzloDpJDmCAy\nhczRKDifIwGQgX4eg21qYN1U3cLI4JBYgy0Wt0mD4NsAOM1uTMF3TClbfCKmyQ4yncYV+I0Yl7NV\nOeQVXedoOofiyPrNAITo5WrXIr7b9Hqsh+D5+WaWbOoInJ0NAGwNKFIAtkXBaPfEA+bWbXR/n1BO\nCC4naGwxca0A2CgOlwCwHbaQ2WJmrw3dNwa6f7HA9WPBiSMTx0wcAY9OA+HNEn3riA8eDFVb9+/H\nx2522O3byaPtbZz9/ciG5blA64YxY3Er+z3dbWPNvMrgJa9Wg3F3cIDevUe49ym6N9+mLfaoG8ey\ndtTNcIrUFhnbI5chLwzAGwXcunnAcN/rv4tDfY4WJapDcsR6MtuH01XOuD+RYd/N+XwIGLRt7GzT\nlyvEuuAVGTU+a3DOkzmllXQWyPphmoGeJkCmW07Zw08z3FWlH2eyXlvWzFZSvjz2lsb/v2liwOsc\nseNQ21GEjq7pKHOlyJWiUIoMCieUKGXbUmpLYa7mlmPVCKslLFuhU0fc5jz+LSbZba6hInGz/H1G\n/QAAIABJREFUhqKIeF20kLWK7xQIoG1M4OqUiLIdEfE7IMRzWSlGEkIxvadr0NhmvEi347lxnSS9\nLwe9B5x4G3t7m3V7KaWb50MJUlpkPZ0O77MWRxazSCsfLHHj8HBYqcsSsgJpBZFYaRCApoNAwOMR\n2UJdWVx3/NMyAtP6krGLYwkgRuFY3dzRUb/n916sGy1K1PmhzeU11Pd6MBuNtb+/ualvCE/uuAAb\nmcaSxGfEuaHMoCzpDmd0k4LgZR3utzJuG1aWK2J1t9Crsom4m3nB4RGfx/BDGlfMssG4SjtcWeza\ne6gqwv4B4egW4egW7eFtmuKIpptQr/In2ppbzshWZveS5CN7wOOEJRgsho2/I2iWoWX/sNpRpoud\nYOxaWKZx2kTYupuYq5rGKPpJ57qWzHeQ99taJbE8OyUMwJrWbaenMgCu640a9PXDT5uumKLgSe8o\nndP289pO0kTs/gwEAUofKLVmnxVa12TSkUmHVyUL4FshU8i0xmsTQTHNtkrGwHIJD88cD889q8bR\ntENzE3ubrRPWvcq5iKk+g6wGh4PObyotTX+3bSSJAJ45HSZXMn/T4ZoSNXYtY2/4uusWNu/HqeKC\nDgPduqiYt5seZpVaQM+ya6yoOwXCZHvRdclBWQ4dWvb3I2XiPRJiP2pRh3MeVIZEuSAU/eveuSe7\nwNj3pTuCWHjLGn8YuFgNaboeOTdkEBoA7++vk0s0ixuvpFUU105M4Vb+ZQl2ZuF23eZcTWmvtP9k\nWmaQlDh01T5NPl33SLD12DA07Q+Q9l+xCrXoQAlOXJ+7USC2f0DqBdiETesH7brLkrB/HIH38DZ1\necBKZiznnkaf7Gy6LYz40j1g2DQuUhC2i04dWxWHZjlaZqhzsXdqO2o5lVopdhjPnwJwng/7O6YP\nPMl6lK4hkxKfK51X6kZidQBDYhwMwDufb2ZEp5nRNo5sH+c0YRu2xwaNphhbTjeNskzvbZ2okAcc\nNeLmuOUCuriXsoQO6WLikzQ6NE3vWja6ZCR5AYslPHwkfPW+53zuWNVD9MG+7+AgspSm18xDWSi5\nKIIgwUHjNpHRLDIDj16hlifova4340AGNiRlX9Mwy0Ue8E0CYReiByzaPzcD4CzbbCOXesH7+0NC\nVrqa9UmUG8A8tE4aPGazrCwMFQJCi5MMLy5yFf1pCDFElKUesG3JZQyaJYIZCE8m8ZoMgNNm4CkA\nGwBNp/F6LEh5cACzGVpVqBQE3Ma6d61EhDje3SYAG0vh/cBsmOFixol5zKl3bJS9UfXHx4Q2o2kz\nVitZN6gyALavTC/HANjmlffSY78HlyHGWZuOzLMyWtyMQcOKPrsrHNyhPbhDfXCXBRWLlWc+j7Sz\nwQg82dHuqtbujxUD3laClHoIcT4KdSMsa5DMk5Hj8xJfJq3C0ppg+6D93xS8t7dZsGvUUQhDxxoR\nZLlE1pO3wreerHMQPN55MpeRFRmhFbo2ZryOaz3tUiz73gbCtiTQcTnLNo83Vdx1piVN0vi2c4p3\nkHvFhwbfnsdNE+ZnAw2Y1mE6t9l2zGrDu45G+2xkyXl04vnggefrXxcen8ramTEG1FpC2+95Do7Y\nqN37EKnlbkuJSUo1pqGOfodhW9i3hVfs3rfp9qYYVltF6AE0MYytFCUFYNP32ANJ561NnLQwPPWA\nR1kviqPrHCEIrToaFZogNN3wtQShLRwhj01xnCvx5QTXdnHz39Vq6JBl123ovVgMcUyzJs0oUB3a\npVnLtqOjuNOSlVbkBaqeoNcYgKEf/gkFbR3N7IZs277xgmfx176FY8gLQl6iRQWTQyj2IJ8SUyti\nY4s816RaQjbKBFNGdSjRlshWtj0VTc+CjBN5U72Z01bXG+xFN92nLvZYMGEZCuoQSdkxk2tzfFzt\n8Ep4wCbpxWzLXLeHuk52yh1V8JS+iAAMw5tS9Esns2XCjIPsRoO0Levmv48eDR3+j46QyYxMMpCY\nmaeTvs9nUSHqY6JA7jdivWmIKq07T+/PmA8zzlNs2eb9wjWdlE+RjUHqNB5dg8zPkPvfgJPHg1UD\nSWPnfDPuD2ujq25hrp65Fnz4OOP9Dz1fe0/WO9SdnAxDYdp3NS2KPkRYQCbKpOjjuynwpj2L0xK3\npOuKIjGBJkSjLMWSsbe7LVx40fO5tgtyL0MeRxYbcYRRDDedq7bgpQZWurJaUpPFVNNNn9P5nNDZ\nQZRGhVozVq1n2TiWdcRV+ypBWE08zRTaUihzKLKcfDrpy2SSjDoYVltr1m8T3e6pqob4isWuDw+H\nzKCDA5jGYKX6DO0cep27XwHrYH+aSWnrry2G22gvM8hmM5jO6PIJTTahzSdIPgFKZAUgOKd9D/44\naZwbCAl7/OP+DOP2toUIEgSPG7hqm4zmBWfZ5okTRiVkU1aac74QGt20u9I8j/G2pFdlYH/sLOg0\nRp8CjgGwvUcVQiFInpHlBfgk2Jp2rtl22KRIJ3bqxZydDX1LbWPZW7eQ/X18XuKKMtaPukOYCF2R\nReDIhbwamCkLH6XNYNLyJFu3YbPUME3sHj+XVK71BB3JOj4o2h8B19XI+Rk8uB+L/NIAudHMRv2l\ntVq9AVZ3wlmb8agt+fCR4/1vyHr/c6sb9H4ILbXtwAzOpsokD7STAK4bZqx5vmdn0VAzqiyNlawB\nuAffLlrbqTNn9zxOVbjo2dyEcMM61CQCPkO9gCRMldXzp80sbPGz12B4iGlWsfcD+NqYSFfcfp53\nKHUQ5sEzrzPmc+F8vtmkyTloD9y6X7VWGa6akGctqn19qsWRUs8gbWGYtjEcx6OtJOroaNg+azqN\ntb9Z3PtXwzUGYBEjgDYT49Iku3HVii16lk01m6F7+3TZHk02Y5XFzmGiHlnJht0rKM4NSbEGAXYp\nMHyVecHrw4MPLu7ONaYbzcCfTIa4f5YNjWP29+n6hKv5ytGx+XH7XmM4rzL72eTSPOCxd5AC8zqB\nSYVcPEWWk/mA8w2SFbis2QzCmuU8tqZTWist9je+2GqJ7JraNm6BOJ2iuUPDDCUgLu4nbNdqTnca\nJrKfBsCWL5Iyl3bf6b1f9HxusohAX6Y7eEhmPduiZj19YU1Dap5DWUW6Ki9pupxFk3G68JwvYtw3\nTYowlgGebNizXEBTK6FNPLRxclByLTqZxFpin6N4OnW0QWg10mL2MbtkM67G43s8B24K+KYSq4Dj\ngqWSQ1ahBSA52nbQdqhvUKlRqcHVce4VLZQNki+RYoFUq80w1cEBun9I2DuIr9m+vdUEzUtUcurg\nmdee05XnfOk2CiLSEsEsk1iC5kGdj91csg6fz8iqBdl+sjVdCiw2JqxWMeUaJ5NhK8WNPtTTft/f\nLHa9eom6uTzpM7idxzZaF6sjNBpwW8czCymtGywAeRa3azRcF03Ysv70qmvHrF3bR8OkSWHARBWC\nCi2eWgpwHc47nAouARsNASaxj7hOZ4TZPqE6oPMzll3FKuQ0bcyiT1l1G5dpL490zVk/qUuc25da\nB5zmLeT5JgMZeq697hzLkMcx7zqyIuBIBn5qoRr1YUX0aVJFygun6cimzcVio/ekOh8zFTWjCRmr\n1rGqHcvV4ECfnGyCcDpHN+Oew31fd4rxo8qaRRaJ+4nagzFLxRgLay9m1nJaHFxWaFESipJQVNRN\nwbLLmc9lHS6czeL3WAMiGCxTy9uKzpXSNQFtOsgTxZnS7PuNTjw6IuwdEIoJAd9vIRn3cU5tPhjW\nZ5uc2+jnmwi8JqqxyYwSt+dUFPUODR1BA4FA0I4QWpQO9S1OA067eIQG3zV4bTYYhK6Y0OUT2mIS\nXxfFuxCzivOSkJcsVzlny4zHp8L5YmAVU/vOWGQL8a9zMkuYNBlVVpFZvYut6uvYP5vrR2pNWyu3\ntP3lOt6RoTJ4vdd6DVBi+EUFiA2HJHVZi2Kz3ac9P3vwEJPkuo7sKHar85USK/oUULyP5WNBbR4p\nJdBmyirrM5yT3BojKIyZXBNmIrSSE2RC6zx5tqJwHhfcEEPsc4Q030OLktpV1H7Cqpkwb6NRl+Z6\npKXtY/Adx4DhckOLVwbAabOrNZUgQt3FpCjnhNJ1uCLE2JI9CVuwU9PIANgOS122L04njXHHBsDr\ntkyeTjIaMuqQUbfCqpZ1G9HHjyPFaQBsJXB2WosRpItvCr7XegJ+BNlIUuozhtc8vYFsmrmWJt9Y\nzGgyRfOSkJV0eUlz5ll2jvliiDxYXWC6RtocSwG4baBrQ++RtZursw1Mazbbx/M07wFAM5pOaFvZ\noJ5tvRkzXdvA137eRAAOPcUagsTFGoe6nJApHdCJ0tEfLhCyWNLlfcwNyLySu0DmQzRkMnA5dJ2n\nCZ6683HoxHQNAkKnkZVYLh3nS+HRiXB+vunA2vjzfqCiU0etKQV1OT6bMNnv0qyezcUqzY63yW4U\nudGXVotcFDHxyucxNn4DDHADowiOAi623H1iCzFLqEyZJZFEKQFfTRGp0ZK1ggRFe4pb1SHEMYFT\nmlzIPT1ADzaOsd4w6Ni5mI/QSkFwGU4LJs7jEXJlYELbFp3uEQ6P0IMjmjpjvvKcL2NJY9253th4\n0kYfg69dw3iO21h7ZQAYBisihMGKMf307yBozGD0DiBHCXQQSz+8QCZI7tDcQe6QAqgEaR2QI66E\nfILTbqA3kqw8LUt0GhMCwvSAUO4Rsj1aptRtyWoRLSAL/6TVCufnm3kkaW+A1Dralt08XnivKmvu\nVZDU6FgnLgUQPFJNkIMDRHXtrqgqYXZAmOwTij2Cn9IxJYQJTV3QtgXNquD+ifDgEeukq8VioKAM\nP20NTTPVrdf/41KY5YLUDhY5siiRuotbiuUO7xtkcohMDmCyT+dyWslpg6Pr72HsOI+Pi4D4poIv\nRA94iBD5IfoT+sNi5u3ghKThqLUz5XuGUuLPVTuEeIygKLpN4/Z8CYvVsPZDshgnSTPx2gZcqOu4\nxjRFRpdXdAWEVUdYKWElfc/oWM4iaFxPNMQ4StYXk1dlH8KK3dcky6KVYPsi3xCFWwJZCCA4nM8G\nz9eM6ZSVtEmYGrp1jdQ1Uha4SQmFHyapxu6B0ZCLXrGI4gjkS0+xyJjMM5wXpgIT13vjtUATMaNq\nHHkTu2t1HWgHqiHmJfgMlZKuDrR0dJ0SmBJkj+APWIhjHmDRxrHaJfmfqeOYer/pWm+yTd0fdwhc\nqgdskjZnSBvTwDBx6lZou4xlUFznkNbjKJF8ClqD1JDXyGSFHPbdrpoVrq1xTY2XjswFMhfid/cX\noHkR28KVU9piyjKbsfIzVmHGcj5ltcpYyQC0th94mqBpIUuzhCyub2Vn20qOxs/hJi/IqZjHAUKn\nOdlkH39b8ZZF2bZopzTZhNpPqX3Fqi1YnhasHhesuoxV51l1caOrDz+MP9MGaLC56Np4srBy00Bb\nC13jWSxyvjEVXOtxbUEWpkyymmlZx9aXkz2838eFgqCeII4gm6Cb1nKbjImWZ2VDp0bKtfeQkryr\nNCyTJj5b3oTRhmn1UepEpVUs4xyL8f7MSYXaEyV/6TgwDylNlIxHTPrs8pI6E+pcaMqSutpDMofL\nXNzAw/deug9DNyfnIkCXJZQFLvOIdzHWCOuqHftp1Lc9r+sm6yRaHOIztCwRy+ewG0u5YEucMQvY\ntpxs2/j/+/c38nWkaZHeUosALOAg04KJlohWSO4pyljvq+Kg8WRtzMDPQ0mhJb7M1mAOUJQOnzs0\nK1h4x1xKzrVFFzOClISkzMnGyrb5m+7dME66Gq/pG+zfq+YBpxdu+kqT6MB0EhfM0DpCm+OkxBNw\nWQcSIA8Quo1YkpcOLwFPoPCx76v3LTAU4KnLCFlFm1WstOBsmXG2zDhfZSxXGcsmYzlKsraYUpro\nI7K5cIxr9J+WDXuDjONnSgjQAl2ATHKY7OMmFegQpAut0jQ5iyZnXmeczj2nc8fZ3LFYOuZLYb6I\nnu/9PoHakhjTUIDRQQYGeZ5WGwmLhefkzLE3zfBS4CVQZh1HB4HjWeDwQMkmGVmWk3Wx7EX7VXRc\napQCcDoBU8PLXhuP+8uanK+KGAAb+KZleqajNEpkSVKWqZzWzKfPK92nwZJprQLG+nFY7N3mYdqI\nyQDciilMP+a8ZTm4zBMyoc4y5kXJotxjPmnxXvCZ4HOhLKAsFS36jd6jRY/46ClL5lBH7IktIaYK\nmUGWgG8KwtdJNmKh5gF7ASvfSi1T86ysi1HXbSbNzOexJ0Mac+8Dum65QpfL+Pz6jKysmDCtZhST\nPSTPcN7hM0H7ng0TicaA0z0cM1xbrilznMflE7xM0Lxi6UoeifAwCGGZo01GONtcq8fe7vhIk67G\nWJb+fll6vhIP2G5gbGWk/TZCkLiJfTsk09kRHKgQB/0oO21dfuZbyv5wGsGaELvCdr6gdQXLNuOk\nhtMOzpOe8FZqlB6wGbu2RcMmfmpZj2ME46zY18X7jdbgQE/i44RwRdXXjMaZ3bZQL4Tl3DFvHecB\nTldwcr4Z2n/0aNgNLt0n1HQ/9iqdG8J5fRCaNkTa0nRWVUDodVbGVpU5UIRNXY2z2rfJeDw/TW4K\n+KaSGhbjPhtpNZKlbVgDqm3PLHWg6npgO8syrt0GrNau2YxfA+rUKDP2CjYZCRGhw1MHT+hgrnAu\nME9ifXkGIQdKkGp7WME5cBLwdKARdLG+z6NndF3n/RqAnRAkIziHZgEpJ/Em+61YyQtwfs33y5gO\nmc/jQDg727DWpPeSxSit/kH76RS/t0exv79Jc+Q5uQ0IZlAHaIB8iA2peFRK1Dk6V9D4jKXLOPcR\n1rQF2sFmSMfhOFfpWcmV9v/Llkv1gFOxix3TeGmmv8WLbQEfV46MG+psgLE4HB4PcacW/NpSC86j\nPmZupuVEKX1m1zZ+4CkVMQ7K22HlZqnStsWFb6psu8d1Dl0bQbkWemJC6DpluXLrrjfm0VTV4M3C\noO+0usziiWbspNSjhQpS+jKlKU1fNu5iycpgDG4zmJ4WQniWcXVTE/IMhOxZ2msw3Kv93foypACc\nVhCmIJ42Uhonv2yWpwzfma4dllsyLlG1WLAZafa5NIM6rWgwFsyuaWu4QWQdrnBK7yFE9iQtS7zu\nohpzIVRd3LLTVzEXR3JcWeGmTYyLW7eso6PBgraa6nUaem8Zpc0yjCYw5VkzFGtNal6ONYW2/tJp\nw4/1JM/oigmtVDRdRhBHVgiz2ZM63BY+uiikdNG8vwr5xAE4vZkUXNPSvLSJSbppQjrIQxC084Qu\nxiNENMZjHHGDbj/0ix03UtjG/6cxpHGbyXRBT+NMrysAw+ZCvI59WVJOEzOjY3MCpetk3U7O5p0t\nvOnCmbJdqc5Seigt+R7H/lIATlkMkWE9SMMiqc4uYjG2TcZtclPBF7Y/nzEzZUaQdSizBMdFUjo0\nZp6smc34WacAfBHTkGanWkgy9c7TLmapUWdH+ln7PYRNRmtj/jvonOCdx6nGvuYhAvBNCzd0KnQA\nIY9raZHjigovASTg2hrZ24OjwyHmkP60/9tETtEutaLTLlvz+WYcQnWgOsbVE/3kVp/RaUFNQd1m\nBBHyQpjq5np9UUhoGwi/yJy/DLkSAE4X5zG1dxEAjymttJGRTWCbSPE9sm6YkGasjmmG1HtK+4in\n3u1m4sbmwj0eO+niPqYtnkVL3hQZ63etz56O3vR2+iSIbkicSCmh1LtKvahUl6muzFuxkNP4feNW\nw9bUaLxIjyfkOOv5dTOoniZjhmD8nGxupXR0uunRfD6AcRoWTOdpCp6mw7EO0lh0CpC2zqc6Hcet\n07Kl8X0ZHthn0msark3wfVWrA0Rv5vgYtlSMNybicXkMB0oG4kFo0WqK7O2jq6hgsSSAx4/RR49i\nAH6xjD9jMD7+zIvN1la9QuIPFw/JwBeQl1BM0GIK5XBYjbL6jLbxNG0MM+DiV0zcJpOZOnjpOLnI\nI/4kdXplHnAq27xh1c3mBra4pgCYdkRLPeBxDGrbxLLvSwF4nGI+BtQx7TxeeFLLOKWqXncZ63fs\nlaTP3kqJ7DDDtq5j7M8MLjvf+DBa0rypFIBTGtM84mQnsjXDlVLT44m30+nTZZuBYqximimdsobT\n6abO0oxz013qqY6N3G1G8zj3Yts6kIL6GJzT+f4sOvKisbHN672O3vD4mW37e8oaa59vIb6AXJCJ\nBx/BkmKKzg7heB4bdjd94+4m+X/XQdf2XasS/XgfAbrI0WqCzvYI0z10tg/lHsg+0lbRKBAPwdOE\n2Id7bMinmcypc2Q/03H2Mo3tTxSAYROEx4xEWnJQlk9SVuNzwZPU00ZGX2Ilj+nk8cI9BmqjuFIP\n3n5uoyxe50V77B3Bk5Rsyl5cFHpIDeN0cU+/I33fNnYrXazHBtVFY2Cbh7eTi8XmlS1i25iFotjs\nCDr2QseMQzp/x/Tv2FDatmBeRDNedP3jc9nr4+9J35/KRd9z3cDX5KIQSuotrmvB464N4Fyso/Yl\nlB3SdeisQesWtQmaxoTtZ6Ls0MUKitDRd9OLig8+o/MFnS9Q85wpkDbDx1xtnBdUY53w2CAc6zWt\nnjIZsyg3EoDHdGW6aJrY60Zjpe17x+faRhMagI/1DJsAu81632bNj2mxbZNqt1BHSfX7PLLNWLIj\nTdaBTf2m7xnX9F1kTD3LSNpRzS8uz/OsLtLv08BpbDi/iGH7tO/YNt+fds7xmvA8331T5Gn3sski\nCJCB9LT0BYbU80ha2pZ+JsWBtOTHBfAdZBILLbZhwjbZpssX1fVVyCfiAafytAeRPow0y3Hb+8bA\nblz/mJoeL8IXTcaLAHmbZZi+vpOPJmP9meeTTt5tOkjj+RfFbbfF5S8adzu5Gkmfbarjp0lqUI3P\n8Sy5yIPbNs+fdd27cXGxbPOQL2Ijnldsnm6Lz297PTWw7bWPIq+Crl8aAG+jdOw1K0+6yPO86POp\nFZ1aTReB7/g8216/KCayA+GPLhc9Y1uAx++9KK637XwX6feiifayJ+BNleeZR2PZlsfxvPK084/n\n+LNkNya2y9No9xfR81i2ea62FqT1//beFzWqnvXdL1M+UQC+jAf2LNkGwCZjr+ijyraEj508n3wS\nY2AnL1d2Or65chWxb2M8X0d5XgCuAL74xV++wku5HNnmIZmMM+E+qqyTEUaxyhddcJLnWX28K7pU\nuTa6vk7yiuoadvq+EnlF9b3T9RXIx9K1qj7zAH4Y+o0dd8dVHD/8PHr4JI6drl8fXe/0/Xrpe6fr\nV0/Xos/BHYjIbeAHgC8By2d+YCfPKxXwaeDnVPX+S74WYKfrK5RXTtew0/cVyiun752ur0w+sq6f\nC4B3spOd7GQnO9nJ5crHjIbuZCc72clOdrKTjyI7AN7JTnayk53s5CXIDoB3spOd7GQnO3kJsgPg\nnexkJzvZyU5eguwAeCc72clOdrKTlyCvNACLyOdE5Jde8DOfF5E/cVXXtJOrkZ2uXy/Z6fv1kZ2u\nL5aPDcAi8gdF5EREXPLaTEQaEfkfRu/9PhEJIvLp5zz9jwPf/3GvcSz9NfzgFZz3O0XkF0VkISK/\nISI/etnf8TJlp+v1OUsR+UkR+Wv9vf/Fyzz/qyI7fa/P+b0i8rMi8jURORORXxKRH77M73jZstP1\n+pyfEZH/UUTe69fxXxWRf0tErqRt82V4wJ8HZsDfkbz2dwFfB75HRIrk9e8FfkNVv/Q8J1bVuao+\nvIRrvHIRkX3g54BfB74b+FHgx0TkR17qhV2u7HQdxQNz4E8C//1LvparlJ2+o/x24P8C/iHgbwF+\nEvhPROT3vNSrulzZ6TpKA/wU8LuAzwB/GPhngB+7ii/72ACsql8kKumzycufBX6WCEbfM3r98/aL\niByKyH8kIh+IyGMR+XkR+c7k758Tkb+a/O5F5E+JyEMR+VBE/piI/Mci8jPj+xKRPy4i90Xk6yLy\nueQcv05sG/azvQX1a/3r39VbPif9tfwVEfnuF3gUvx/IgX9aVX9ZVf8L4E8B/9ILnOOVlp2u189h\nrqr/nKr+OeD95/3cdZOdvtfP4d9V1c+p6v+qqr+uqj8B/LfAP/i853jVZafr9XP4dVX9KVX9v1X1\ny6r6l4GfJhojly6XFQP+BeD7kt+/r3/tC/a6iJTA30miOOC/Aqw92ncDvwT8vIgcJe9JW3X9q8A/\nCvwB4HcAB8A/MHoP/d/PgN8G/BHg3xARo0B+KyD9e97sfwf4C8CXgb+9v5Y/RrSG6K8/iMg/8ZRn\n8D3AL6pqm7z2c8BvEpHDp3zuuskvsNP16yS/wE7f2+QQePCCn3nV5RfY6XpDROTbgb+vfw6XL5fU\n5PtHgBMioO8DK+AO8PuAz/fv+XuADnin//13Ag+BfHSu/wf4kf7/nwN+Kfnb14F/MfndEfua/sXk\ntc8DXxid838D/mjyewB+cPSex8A//pR7/OvA733K338O+A9Hr31Hf8+/6aoarH/Sx07XT7z3J9Nr\numnHTt9b3/9DwAL4zS9bPztdX42ugf+513HHaF2/zOOyAssWP/itwC3gi6r6DRH5AvDnJcYPPgv8\nqqp+pf/MdxKV/EA29/GrgG8bf4GIHAD3gL9ir6lqEJH/k2gJpfLXRr9/HXjjGffwJ4A/11tHPw/8\nl6r6a8l3/ZZnfH6b2HXdpIbbO12/XrLT9+a1fh/w54ng8ivP+7lrIjtdD/JDxPv6LuDHReRHVfXH\nn/Ozzy2XAsCq+qsi8lUiTXGLSFmgql8XkS8TaYbPsklb7AFfIwb0xw/+0dO+bvT7tl14m9HvyjPo\ndlX9N0Xkp4HfA/xuYgLV71PVv/S0zyXyHnFgpWKD5cbECXe6fr1kp+/kYkS+F/hLwB9W1Z9+kc9e\nB9npeuM8X+3/+ysSM6D/rIj8e9q7x5cll1kH/Hmi4j7LJl/+i8DfT+TxU8X9EpG771T110bHE7EV\nVT0hAtlvs9ckpsz/bR/hWhtiJuv4O/5fVf2TqvoDwM8A/9QLnPN/Af5uEUnP+/cCf0MfKdP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gBTjvv0l4dHPZfbyZGLnDw3DF+iHDlZTklwdbZprAQsASue3hvawaarnUpHYZpDSEb99lY47AyL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\ndg3rtMMAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc37391cc0>"
+       "<matplotlib.figure.Figure at 0x7f3763db19b0>"
       ]
      },
      "metadata": {},
@@ -1296,23 +1296,23 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 968    0    0    2    0    2    5    1    2    0]\n",
-      " [   0 1116    2    2    1    2    4    2    6    0]\n",
-      " [  13   15  885   19   19    3   13   14   45    6]\n",
-      " [   5    1   12  916    1   36    1   13   17    8]\n",
-      " [   2    3    2    2  943    0    8    2    7   13]\n",
-      " [  11    3    1   28   13  788   12    7   25    4]\n",
-      " [  16    3    3    2   22   24  884    1    3    0]\n",
-      " [   4   14   18    7   12    1    0  951    2   19]\n",
-      " [   9   15    5   29   11   40    9   13  839    4]\n",
-      " [  12    8    1    9   84   11    0   34    6  844]]\n"
+      "[[ 957    0    3    2    0    5   11    1    1    0]\n",
+      " [   0 1108    2    2    1    2    4    2   14    0]\n",
+      " [   4    9  914   19   15    5   13   14   35    4]\n",
+      " [   1    0   16  928    0   28    2   14   13    8]\n",
+      " [   1    1    3    2  939    0   10    2    6   18]\n",
+      " [  10    3    3   33   10  784   17    6   19    7]\n",
+      " [   8    3    3    2   11   14  915    1    1    0]\n",
+      " [   3    9   21    9    7    1    0  959    2   17]\n",
+      " [   8    8    8   38   11   40   14   18  825    4]\n",
+      " [  11    7    1   13   75   13    1   39    4  845]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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siv1PSvo98AxwGPDL3kfWO07aZmaWrJ4MRHv1sft49bH7CmWb3nq9u/fZHTgcOHZLx0XE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\nm5mZ1QknbTMzszrx/wE1BT0R1/KyWQAAAABJRU5ErkJggg==\n",
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BgW1mZpY5FrgxIhZ3LYiIi6vWPyxpMXCbpA9FxKJ+jlfXk9cd2GZmlq5BdGu/dP9tvPzg\n7T2WrXrrjQG+jD4AHAB8pp9N78m/bgMsAhYDu9dss1n+tbblXYgD28zMkpWd1jWwbTf5yP5s8pH9\neyxb9uxjPHLRVway+7FkAXtDP9uNJ2s5P58/vxv4Z0mbVI1jHwR0AI8MrPKBcWCbmVmyRuJa4so2\nOga4LCI6q5ZvBRxJFuIvAbsC5wK/jYiH8s1uJgvmKyWdAmwBnAVcEBHvDLnwXjiwzcxstDsA2BK4\ntGb5inzdScAGwDPAHOB7XRtERKekTwH/BtwFLAMuA86od5GlB7ak44ETgA/mix4GvhsRN5VWlJmZ\nJWEkZolHxC30vHhK1/K/AB8bwP7PAJ8afHWDU3pgk31iOQV4PH9+DPBLSR+JiAWlVWVmZqXz7TUr\nSg/siPhVzaLTJJ1AdjK6A9vMzIwEArtafk3WycD6ZDPvzMxsNCvYJd7v3T8aSBKBLWlnsoBeF3gd\nODwiFpZblZmZla3rbl1F9m8WSQQ2sJBsuvw44HPAFZL2dWibmY1uvh92RRKBnd/N5In86TxJe5BN\noz9hTfucPG0qra2tPZYd0TaFtvYpw1anmdloMHvmDGbPmtljWcdrr5ZUjXVJIrB70QKs09cG0885\nj/ETJoxQOWZmo8fk9ilMrmn8zJ8/j70nTRzxWjxLvKL0wJb0PeBGstO73kV2a7P9yC7tZmZmo5gD\nu6L0wCa7SPoVZJdz6wAeAA6KiNv73MvMzJqfZ4l3Kz2wI+K4smswMzNLXemBbWZmtiaiYJd4EzWx\nHdhmZpYsn9ZV0VJ2AWZmZtY/t7DNzCxZniVe4cA2M7NkuUu8woFtZmbJkkSLW9iAx7DNzMwaglvY\nZmaWLHeJVziwzcwsWb69ZoUD28zMkiVBi1vYgMewzczMGoJb2E1kTJGPocNg8eVHl11Ct00/f0XZ\nJXRbeuUXyi6hW2dnlF1Ct9R+fiPSeW9WJfDvVNbPis/DrnBgm5lZsjzprMKBbWZmyVL+p8j+zcJj\n2GZmZg3ALWwzM0uWZ4lXOLDNzCxZvh92hbvEzczMGoBb2GZmlizPEq9wYJuZWbJaCt6tq8i+qXFg\nm5lZugq2sJtoCNtj2GZmZo3ALWwzM0tWNoZd5NKkdSymZA5sMzNLVnZ7zWL7N4vkusQlnSqpU9K5\nZddiZmbl6pp0VuTRLJIKbEm7A18G7i+7FjMzs5QkE9iSNgSuAo4DXi25HDMzS4QKPJpJMoENXAhc\nHxG3l12ImZmloet+2EUeA3iN90q6UtKLkpZLul/ShJptvivpuXz9LZK2qVm/saSrJXVIekXSxZI2\nqOd7kURgS2oHPgKcWnYtZmY2ekgaB9wJvA0cDOwI/BPwStU2pwAnAl8B9gCWAXMlrV11qGvyffcH\n/h7YF/hpPWstfZa4pPcD5wMHRsQ7ZddjZmbpaCl4t64B7PtN4OmIOK5q2VM125wEnBUR1wNI+gKw\nBPgMMFvSjmRhv1tEzM+3+RrwK0nTImLx0L+DitIDG9gN+CvgPlX6LsYA+0o6EVgnIqJ2p5OnTaW1\ntbXHsiPaptDWPmW46zUza2pzZs1gzuyZPZa91tFRSi0D7dbua/9+HArcJGk2sB/wLHBRRFyc7/8h\nYHPgtq4dIuI1SfcAewGzgT2BV7rCOncrEMAk4JdD/gaqpBDYtwK71Cy7DFgAnN1bWANMP+c8xk+Y\n0NsqMzMr4Ii2KRzR1rPx88f589hnr91LqWeYz8zaCjgB+BHwPbKA/bGktyLiKrKwDrIWdbUl+Try\nr0urV0bEKkkvV21TWOmBHRHLgEeql0laBrwUEQvKqcrMzEaJFuDeiDg9f36/pJ3IQvyqPvYTWZD3\nZSDbDNiQAlvSHsD/ALYGjoqI5/KJY09GxO/rUFfdvkEzM2tcg+kSX3TXjTx59409lq1Y/kZ/uz1P\n1qNbbQHw2fzvi8mCdzN6trI3BeZXbbNpTd1jgI1ZvWU+ZIMObEmHAbOAa8n679fNV20KHA18qmhR\nEfGJoscwM7PGN5hJZ1vv/Um23vuTPZa9tGgB/+9b7X3tdiewfc2y7cknnkXEIkmLyWZ/PwAgaSOy\nrvML8+3vBsZJGl81jr0/WdDfM7Dq+zeU07rOAE6MiM8D1bO67yCbQGZmZlYXXTf/GPqj35c4D9gz\nvyz21pKOJLuA1wVV25wPnCbpUEm7AFcAfyGfTBYRC4G5wM8k7S5pb+AnwIx6zRCHoXWJ70DVbLkq\nr5I1/83MzBpCRPxB0uHA2cDpwCLgpIiYWbXNdEnrk51XPQ74HfDJiFhRdagjyUL+VqCTrBf6pHrW\nOpTAXgp8CHiyZvleZN+omZlZ3Qz3JUYj4gbghn62ORM4s4/1r5INCw+boQT2pcD5+YnjAbxH0njg\nHGB6PYszM7PRregdt5rpbl1DCez/DYwlG2RfF/g9sBL4cUScV8fazMzMLDfowI6ITuB0SWeTzaTb\nEHgwIl7pe08zM7PBEcUunNI87esCF07JL3gyr461mJmZ9TAClyZtGEM5D7u/gflDhl6OmZlZRXZa\nV7H9m8VQWti1dzEZS3ZrzG2AGYUrMjMzs9UMZQz7hN6WS/o+zTVcYGZmJVPBWeLN1CU+lCudrcml\nwJfreDwzMxvlurrEizyaRT3v1jWBnpcqHVadEXR2ln+PkJYid1ZvcitWdpZdQrfFl3++7BK6TTzz\nlrJL6HbPtw8ou4Rua7iTbmlWJfD7pcuYBH7PlPW7ThScdNZEHb9DmXR2Te0iYAtgb3zhFDMzs2Ex\nlBZ27ceVTuCPwLkRcV3xkszMzDKi2Nht87SvBxnY+f09zwMejYiO4SnJzMws03W3riL7N4tBBXZE\nrJL0O2BHwIFtZmbDajD3w17T/s1iKD0NjwBb1rsQMzMzW7OhBPbJwDmSDpC0saS1qx/1LtDMzEYv\nqdLKHspj1HaJ5+bWfK01Zoi1mJmZ9eBriVcMJbA/WfcqzMzMrE8DDmxJ3wbOiYg1tazNzMzqqoWC\nk87qVkn5BvO9nEF272szM7MR4UuTVgymS7yJvm0zM2sEvvlHxWB7C9K5uK6ZmdkoMthJZ49J6jO0\nI+LdgzmgpDPIuturLYyIvxlkbWZm1mRaKDYO3Uxj2IMN7DMYniucPQTsT6XbfeUwvIaZmTWYouPQ\nTdQjPujAnhkRS4ehjpUR8cIwHNfMzBqYx7ArBtNbMJzj19tKelbSnyVdJcmXPjUzM6symMAero8p\nvweOAQ4Gjgc+BPyXpA2G6fXMzKxBiIKndZX9DdTRgLvEI2JYxu5rLsTykKR7gaeAycClw/GaZmbW\nGHy3roqhXJp0WEVEh6THgG362u6UaVNpbR3XY9kRbe1MbpsynOWZmTW92TNnMHvWzB7LOl57taRq\nrEtygS1pQ2Br4Iq+tvvhOecxfvyEkSnKzGwUmdw+hcntPRs/8+fPY+9JE0e8Fk86qyg9sCX9C3A9\nWTf4+4DvkJ3WNaPMuszMrHw+raui9MAG3g9cA7wHeAG4A9gzIl4qtSozMyudx7ArSg/siPCgs5mZ\nWT9KD2wzM7O+qKlOzho6B7aZmSXL98OucGCbmVmyPIZd0UwfPszMzJqWA9vMzNIloQKPwZzXJelU\nSZ2Szq1a9pt8WddjlaSLavbbUtKvJC2TtFjSdEl1z1d3iZuZWbJGqktc0u7Al4H7a1YF8O/A6VQu\nTb68ar8W4AbgOWBP4L3AlcAK4LShV746t7DNzCxZhW78McAGdn6FzauA44DersG6PCJeiIil+eON\nqnUHAzsAR0XEg/n9MU4Hviqpro1iB7aZmY12FwLXR8Tta1h/lKQXJD0o6fuS1qtatyfwYES8WLVs\nLtAK7FTPIt0lbmZmyRIFryXezzncktqBjwBrulD61WSXzn4O+DAwHdgO+Id8/ebAkpp9llStq+1i\nHzIHtpmZJWs4x7AlvR84HzgwIt7pbZuIuLjq6cOSFgO3SfpQRCzq5+VjkOX2yYFtZmZN4b5br2Pe\nrdf3WPbmG6/3tctuwF8B96lyW68xwL6STgTWiYja0L0n/7oNsAhYDOxes81m+dfalnchDRvYRe/g\nYsNv7bXSmSLR2VnXD7qF3PPtA8ouoduWx6VzU7znfn5k2SX0sNYY/4KpVtblQQfzu37igYcx8cDD\neix75tGH+Jd/PGwNe3ArsEvNssuABcDZvYQ1wHiylvPz+fO7gX+WtEnVOPZBQAfwyMAqH5iGDWwz\nM2t+LYiWAh8W+to3IpZRE6qSlgEvRcQCSVsBR5KdtvUSsCtwLvDbiHgo3+Xm/BhXSjoF2AI4C7hg\nTd3sQ+XANjOzdBXtTR38vtWt6hXAAcBJwAbAM8Ac4HvdG0d0SvoU8G/AXcAyslb6GUMteU0c2GZm\nZrmI+ETV3/8CfGwA+zwDfGoYywIc2GZmljDf/KPCgW1mZslqUbHzsIvsmxoHtpmZJa2JMreQdM67\nMTMzszVyC9vMzJKVjWEX6RKvYzElc2CbmVmyil4kq5m6090lbmZm1gDcwjYzs2SJYi3LJmpgO7DN\nzCxdklCR22s2UZ94El3ikt4r6UpJL0paLul+SRPKrsvMzMqlOjyaRektbEnjgDuB24CDgReBbYFX\nyqzLzMwsJaUHNvBN4OmIOK5q2VNlFWNmZunwlc4qUugSPxT4g6TZkpZImifpuH73MjOzUcHd4ZkU\nAnsr4ATgUbKbfv8f4MeSji61KjMzK52onIs9pEfZ30AdpdAl3gLcGxGn58/vl7QTWYhfVV5ZZmZm\n6UghsJ8HFtQsWwB8tq+dTp42ldaNxvVYNrmtncntU+pbnZnZKDNr5gzmzJrRY1lHR0cptfi0rooU\nAvtOYPuaZdvTz8Sz6eecx/jxPvPLzKze2tqn0FbT+Jk/bx4fnbTbiNfSQrGx2xTGfeslhcA+D7hT\n0qnAbGAScBzw5VKrMjOz8hVsYTfTxcRL//AREX8ADgemAA8C3wJOioiZpRZmZmaWkBRa2ETEDcAN\nZddhZmZpKXp6VvO0rxMJbDMzs95kp2cVmXRWx2JKVnqXuJmZmfXPLWwzM0uWZ4lXOLDNzCxdniXe\nzYFtZmbJ8qSzimbqLTAzM2tabmGbmVmyum7+UWT/ZuHANjOzZLUgWgrEbpF9U+PANjOzdKngvLHm\nyWuPYZuZmTUCt7DNzCxZyv8U2b9ZNGxgi4Ln5tVJZ2eUXUK3zkinFoCWBP59uiRUSlLvy3M/P7Ls\nErq9u/3nZZfQw8szjy27hG6rEvg9U9bvFxXsEk/ov1th7hI3MzNrAA3bwjYzs+bnWeIVDmwzM0uX\nZ4l3c2CbmVmyPIZd4TFsMzOzBuDANjOzZGU3/yjyp5/jS8dLul9SR/64S9LfVa1fR9KFkl6U9Lqk\nayVtWnOMLSX9StIySYslTZdU93x1YJuZWbJagBYVePT/Es8ApwC75Y/bgV9K2jFffz7w98DngH2B\n9wL/0bVzHsw3kA0x7wl8ETgG+G5d3oAqHsM2M7OEFbtwSn+zziLiVzWLTpN0ArCnpGeBY4H2iPgt\ngKQvAQsk7RER9wIHAzsAH4+IF4EHJZ0OnC3pzIhYWaD4HtzCNjMzI2stS2oH1gfuJmtxrwXc1rVN\nRDwKPA3slS/aE3gwD+suc4FWYKd61ucWtpmZJWskZolL2pksoNcFXgcOj4iFksYDKyLitZpdlgCb\n53/fPH9eu75r3f1Dq3x1DmwzM0vWCF1LfCGwKzCObKz6Ckn79nlYGMi1Wut6PVcHtpmZNYXb/t9/\ncPuv/rPHsjde7+h3v3yc+Yn86TxJewAnAbOBtSVtVNPK3pRKK3oxsHvNITfLv9a2vAspPbAlLQL+\nupdVF0bE10a6HjMzS0fXbO+BOPDQz3HgoZ/rseyxh+/ny5/9xKBfFlgHuA9YCewP/AJA0nbAB4C7\n8m3vBv5Z0iZV49gHAR3AI4N94b6UHtjARGBM1fNdgJvJPtmYmdmoNryzxCV9D7iR7PSudwFHAfsB\nB0XEa5IuAc6V9ArZ+PaPgTsj4r/zQ9xMFsxXSjoF2AI4C7ggIt4pUPhqSg/siHip+rmkQ4E/R8Tv\nSirJzMwSMQKTzjYDriAL2g7gAbKwvj1fPxVYBVxL1uq+Cfhq184R0SnpU8C/kbW6lwGXAWcMvere\nlR7Y1SQG9leWAAAS50lEQVSNJft0c07ZtZiZWfOLiOP6Wf828LX8saZtngE+VefSVpNUYAOHk527\ndnnZhZiZWflEsRtuNdG9P5IL7GOBGyNicdmFmJlZ+VokWgr0iRfZNzXJBLakDwAHAJ8ZyPYnT5tK\na2trj2VHtE2hrX3KMFRnZjZ6zJ41g2tnzeyxrKPj1VJqcQu7IpnAJmtdLyG7iHq/pp9zHuMnTBje\niszMRqHJbVOY3Naz8fPH+fP42z0nllSRQSKBLUlkdze5LCI6Sy7HzMxS0kzN5AKSCGyyrvAtgUvL\nLsTMzNJS7Dzs5pFEYEfELfS8eIqZmdmI3PyjUfj2mmZmZg0giRa2mZlZbzxLvMKBbWZm6XJid3OX\nuJmZWQNwC9vMzJKlgnfraqYZ5g5sMzNLlmeJVziwzcwsaU2UuYV4DNvMzKwBuIVtZmbp8izxbg5s\nMzNLliedVTiwzcwsWaLgpLO6VVI+j2GbmZk1gIZtYQdBRJRdRlKnDIxJqRhgxcp07pQ6dkw6n03f\nXrmq7BK6pfS+LL36mLJL6GGnU24ou4RuD//wkLJLoKWk3y8ewq5o2MA2M7NRwIndLZ2P12ZmZrZG\nbmGbmVmyPEu8woFtZmbpKnhp0ibKawe2mZmly0PYFR7DNjMzawBuYZuZWbrcxO7mwDYzs2R50lmF\nA9vMzJLl+2FXeAzbzMysAbiFbWZmyfIQdkXpLWxJLZLOkvSEpOWSHpd0Wtl1mZlZIlTg0URSaGF/\nE/gK8AXgEWAicJmkVyPiglIrMzOz0jXTxLEiUgjsvYBfRsRN+fOnJR0J7FFiTWZmZkkpvUscuAvY\nX9K2AJJ2BfYG0rm3nZmZlaJrlniRR7NIoYV9NrARsFDSKrIPEd+KiJnllmVmZmXzpLOKFFrYbcCR\nQDswHvgi8A1Jny+1KjMza3qS9pF0naRnJXVKOqxm/aX58urHDTXbbCzpakkdkl6RdLGkDepdawot\n7OnA9yNiTv78YUkfBE4FrlzTTidPm0rrRuN6LJvc1s7k9inDVKaZ2egwa+YM5sya0WNZR0dHOcUM\nfxN7A+CPwM+B/1jDNjcCx1Qd7e2a9dcAmwH7A2sDlwE/BY4eZLV9SiGw1weiZlkn/bT+p59zHuPH\nTxi2oszMRqu29im01TR+5s+bx0cn7TbitQz3pUnzCc83AUhrHPF+OyJe6PX40g7AwcBuETE/X/Y1\n4FeSpkXE4qHWXiuFLvHrgW9JOkTSX0s6HJgK/GfJdZmZWckSmXT2MUlLJC2UdJGkd1et2wt4pSus\nc7eSNUQn1eXVcym0sE8EzgIuBDYFngP+LV9mZmZWphvJusoXAVsDPwBukLRXRASwObC0eoeIWCXp\n5Xxd3ZQe2BGxDPh6/jAzM+uhzJneETG76unDkh4E/gx8DPh1H7uK1Yd7Cyk9sM3MzNZoEJPOrv/P\n2Vz/i9k9lr3+Wn0ny0XEIkkvAtuQBfZist7hbpLGABsDS+r52g5sMzNL1mAmnR322TYO+2xbj2UP\nPTCfTx/w0frVI70feA/wfL7obmCcpPFV49j7k33MuKduL4wD28zMRrH8fOltqLTjt8qvuPly/jiD\nbAx7cb7dD4HHgLkAEbFQ0lzgZ5JOIDut6yfAjHrOEAcHtpmZJUwUm+k9gF0nknVtR/74Ub78cuB/\nAh8muznVOLJJ0XOBb0fEO1XHOBK4gGx2eCdwLXDS0KvunQPbzMySNdzXTYmI39L3Kc5/199rRMSr\n1PkiKb1J4TxsMzMz64db2GZmli7f/aObA9vMzJI13JcmbSQObDMzS1fRy4s2T157DNvMzKwRuIVt\nZmbJ8hB2hQPbzMySVfSOW3W6W1cSGjawI7JH2VL6YVjzrVzLsdaYdEZc3nh7ZdkldNtgnXT+241p\nSedn5q13OssuoYeHf3hI2SV02/7r15ddAiuW/rmkV3Ybu0s6v1HNzMxsjdL5qG9mZlbDXeIVDmwz\nM0uWO8Qr3CVuZmbWANzCNjOzpDVTt3YRDmwzM0uWL01a4cA2M7N0eRC7m8ewzczMGoBb2GZmliw3\nsCsc2GZmliyfh13hwDYzs2RlLewik86aRxJj2JI2lHS+pCclLZd0h6SJZddlZmaWiiQCG7gE2B84\nCtgZuAW4VdIWpVZlZmblUh0eTaL0wJa0LvBZ4BsRcWdEPBER3wEeB04otzozMyubszqTwhj2WsAY\n4O2a5W8Cfzvy5ZiZWSo86ayi9BZ2RLwB3A2cLmkLSS2Sjgb2AtwlbmZmRgKBnTuarPfiWeAt4ETg\nGmBVmUWZmVm5VIc/zSKFLnEiYhHwcUnrARtFxBJJM4FFa9rnlGlTaW0d12PZEW3tTG6bMrzFmpk1\nuWWP/Zblj/2ux7LOt5eVUoso2CVet0rKl0Rgd4mIN4E3JW0MHAxMW9O2PzznPMaPnzBitZmZjRYb\nbLcfG2y3X49lK5b+mcWzppZUkUEigS3pILIPQo8C2wLTgQXAZSWWZWZmlowkAhtoBX4AvA94GbgW\nOC0iPIZtZjaKeZZ4RRKBHRFzgDll12FmZqkpOnGseRI7lVniZmZm1ockWthmZma9cZd4hQPbzMyS\n5fthVziwzcwsXU7sbh7DNjMzawBuYZuZWbKKXl7UlyY1MzMbAZ50VjGqu8Rnz5pRdgndZs9Mp5ZZ\nCdWS0r/Rf86ZWXYJ3VJ6X1L6ebl2djr/Rim9L8se+23ZJSRN0lclLZL0pqTfS9q97Jp6M6oDe86s\ndP5zz06oljkJhcG1Cb0vv7h2VtkldEvpfUnp5+U/EgrslN6X2ht5NBoVePR7bKkN+BFwBjAeuB+Y\nK2mT+n4XxY3qwDYzs8QVSeuBpfZU4KcRcUVELASOB5YDx9b5OynMgW1mZskazvthSxoL7Abc1rUs\nIgK4Fdhr2L+5QXJgm5nZaLUJMAZYUrN8CbD5yJfTt0acJb4uwJOPL2S9scWm/73xegcLH5pfl6KK\neuP1DhY8mEYtr7/WwSMPzCu7DCB7Xx5N5N/orWWv85c/PVh2GUBa70tKPy/L33iNJxbcX3YZQH3f\nl18c875C+0+9f13OK3iMBQte4+hsGse6hQ40SI8uXFDoxKxHFy4Yym4CosDLDgtlrf/GIelI4Oqy\n6zAzG6WOiohrhvtFJH0AWACsX4fDvQ1sFxFP17zGWLLx6s9FxHVVyy8DWiPi8Dq8dt00Ygt7LnAU\n8CTwVrmlmJmNGusCHyT7HTzsIuJpSTuSdVsX9WJtWOev8Y6k+4D9gesAJCl//uM6vG5dNVwL28zM\nrF4kTQYuB74C3Es2a/wfgB0i4oUya6vViC1sMzOzuoiI2fk5198FNgP+CBycWliDW9hmZmYNwad1\nmZmZNYBRGdipXDdW0j6SrpP0rKROSYeVUUdey6mS7pX0mqQlkn4habuSajle0v2SOvLHXZL+roxa\nauo6Nf93Orek1z8jf/3qxyNl1JLX815JV0p6UdLy/N9sQgl1LOrlfemU9JMSammRdJakJ/L35HFJ\np410HVX1bCjpfElP5vXcIWliWfVYMaMusBO7buwGZOMlX6X8c/72AX4CTAIOAMYCN0tar4RangFO\nIbsC0W7A7cAv8xmjpcg/1H2Z7OelTA+RjbNtnj/+towiJI0D7iQ7XeZgYEfgn4BXSihnIpX3Y3Pg\nQLL/T7NLqOWbZJOX/iewA3AycLKkE0uoBeASshnPRwE7A7cAt0raoqR6rIBRN4Yt6ffAPRFxUv5c\nZAHx44iYXmJdncBnqs8FLFP+AWYpsG9E3JFAPS8B0yLi0hJee0PgPuAE4HRgfkR8vYQ6zgA+HREj\n3ortpZazgb0iYr+ya6kl6XzgkIgY8R4iSdcDiyPiy1XLrgWWR8QXRriWdYHXgUMj4qaq5X8AboiI\nb49kPVbcqGphN9p1Y0s2jqyV8nKZReRdjO1kF0+4u6QyLgSuj4jbS3r9atvmQyh/lnSVpC1LquNQ\n4A+SZudDKPMkHVdSLd3y/+NHkbUsy3AXsL+kbfN6dgX2Bm4ooZa1yC67+XbN8jcpqWfGihltp3X1\ndd3Y7Ue+nDTlvQ7nA3dERCljpJJ2JgvorlbC4fmddEa6jnbgI2TdrmX7PXAM8CiwBXAm8F+Sdo6I\nZSNcy1ZkPQ4/Ar5HNpTyY0lvRcRVI1xLtcOBVrLzastwNrARsFDSKrJG0bciYsTv+xkRb0i6Gzhd\n0kKy33NHkjVO/jTS9Vhxoy2w1yTJ68aW6CLgb8haBmVZCOxK1tL/HHCFpH1HMrQlvZ/sg8uBEfHO\nSL3umkRE9RWmHpJ0L/AUMBkY6aGCFuDeiDg9f36/pJ3IQrzMwD4WuDEiFpf0+m1kodgOPEL2Ye9f\nJT0XEVeWUM/RwM+BZ4GVwDzgGqD0YRUbvNEW2C8Cq8gm7VTblNVb3aOSpAuAQ4B9IuL5suqIiJXA\nE/nTeZL2AE4iC4SRshvwV8B9ea8DZD00++aTiNaJEieBRESHpMeAbUp4+efJrvNcbQHw2RJqAbqv\nPX0A8JmyagCmA9+PiDn584clfRA4FRjxwI6IRcDH88mjG0XEEkkzgUUjXYsVN6rGsPNWUtd1Y4Ee\n1429q6y6UpGH9aeBj/d23d2StQDrjPBr3grsQtZK2jV//IGsBblrmWEN3ZPhtiYLz5F2J6sPI21P\n1uIvy7FkH7zLGC/usj6r99Z1UvLv2oh4Mw/rjclm9f/fMuuxoRltLWyAc4HL8wu+d103dn3gspEu\nRNIGZK2jrtbbVvkklZcj4pkRruUiYApwGLBMUlcvREdEjOhNViR9D7iRbPb+u8gmEe0HHDSSdeTj\nwj3G8CUtA16KiCHds68ISf8CXE8Wiu8DvkPWzTljpGsBzgPulHQq2elTk4DjyE59G3H5B+9jgMsi\norOMGnLXA9+S9AzwMFnX81Tg4jKKkXQQ2e+XR4FtyXoAFlDC7zurg4gYdQ+ycySfJJsteTcwsaQ6\n9iP79L2q5vHzEmrprY5VwBdKqOVisu7wN4HFwM3AJ8r+uclrux04t6TXngH8JX9fniYbi/xQie/F\nIcADZLcnfBg4tsRaDsx/Xrcp+edjA7JGwSJgGdnkru8Aa5VUzxHA4/nPzLPAvwLvKvM98mPoj1F3\nHraZmVkjGlVj2GZmZo3KgW1mZtYAHNhmZmYNwIFtZmbWABzYZmZmDcCBbWZm1gAc2GZmZg3AgW1m\nZtYAHNhmZmYNwIFtNkwk/bWkTkkfzp/vJ2mVpI1KqOXXks4d6dc1s/pxYNuoI+nSPEhXSXpb0p8k\nnSZpOP4/VF/7905gi4h4bYB1OmTNrNtovFuXGWR3AzsGWBf4JHAR8A7ww+qN8hCPGPpF97vuxEZk\n9/heOsTjmNko5xa2jVZvR8QLEfFMRPw7cBtwmKQvSnpF0qGSHgbeArYEkHScpEckvZl/PaH6gJL2\nkDQvX38vMJ6qFnbeJd5Z3SUuae+8Jb1M0suSbpTUKulSsru5nVTVG/CBfJ+dJd0g6XVJiyVdIek9\nVcdcP1/2uqRnJX19+N5GMxspDmyzzJvA2vnf1wdOBv4R2AlYKuko4EzgVGAH4J+B70r6PGQhSXYv\n5IfI7oF8JnBOL69THeAfAW7N99kT2Ds/xhjgJLJbv/4M2AzYAnhGUivZh4v78tc5GNiU7J7UXc4B\n9gEOJbuH+MeA3Qb/lphZStwlbqOepAPIgu9f80VrASdExENV25wJ/FNE/DJf9JSknYCvAFcCR5N1\nfx8XESuABZK2JOtqX5NvAP8dEV+rWrag6jVXAMsj4oWqZScC8yLi9KplxwFPS9oGeB44FjgyIn6T\nr/8i2X20zayBObBttDpU0uvAWLKgvQb4DjAZWFET1usDWwOXSLq46hhrAa/kf98BeCAP6y5391PD\nR+jZMh6IXYFP5LVXi7zG9cm+p3u7V0S8IunRQb6OmSXGgW2j1e3A8WQTzZ6LiE4ASZB1j1fbMP96\nHFVBmFuVfxU9Z4QPRO3rDMSGwHVkXfaqWfc8sF3+96FOkjOzRHkM20arZRGxKCL+0hXWaxIRS4Fn\nga0j4omax1P5Zo8Au0pau2rXvfqp4QFg/z7WryAbz642j2xc/aleankTeBxYSTYmDoCkjakEuZk1\nKAe22cCcCZwq6WuSts1nah8jaWq+/hqyVu3FknaUdAjwT70cp7pV/ANgd0kXStpF0g6Sjpf07nz9\nk8Ck/AIsXbPALwTeDcyUNFHSVpIOlvRzSYqIZcAlwL9I+riknYFLqfQEmFmDcmCbDUBEXELWJf4l\nspbxb4AvAk/k65eRzcremawVfBZZt/Vqh6o65p/IZnF/GLiH7MIqh5G1kCGb7b2KrPW+VNIHIuJ5\nstnkLcDcvJZzgVeqzhX/BvA7sq7zm/O/31fwLTCzkmno14MwMzOzkeIWtpmZWQNwYJuZmTUAB7aZ\nmVkDcGCbmZk1AAe2mZlZA3Bgm5mZNQAHtpmZWQNwYJuZmTUAB7aZmVkDcGCbmZk1AAe2mZlZA3Bg\nm5mZNYD/Dy0JOPxBG9Q8AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbc39840f98>"
+       "<matplotlib.figure.Figure at 0x7f3763c9c6d8>"
       ]
      },
      "metadata": {},
@@ -1384,9 +1384,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/02_Convolutional_Neural_Network.ipynb b/02_Convolutional_Neural_Network.ipynb
index a72190d..e89e963 100644
--- a/02_Convolutional_Neural_Network.ipynb
+++ b/02_Convolutional_Neural_Network.ipynb
@@ -180,7 +180,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.9.0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 4,
@@ -413,9 +413,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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/6B9RqVTo9/v4/X6sVuvZFr5ut0u32yUej/PgwQNu375NPB4/zUOSHAP9fp9S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\n/6/Ghib4QzPAAAAAAElFTkSuQmCC\n",
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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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\nvxUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f94651c9898>"
+       "<matplotlib.figure.Figure at 0x7f56f4f8a3c8>"
       ]
      },
      "metadata": {},
@@ -1237,11 +1237,11 @@
    "cell_type": "code",
    "execution_count": 40,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -1551,7 +1551,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 13.9% (1394 / 10000)\n"
+      "Accuracy on Test-Set: 10.9% (1093 / 10000)\n"
      ]
     }
    ],
@@ -1579,7 +1579,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:  17.2%\n",
+      "Optimization Iteration:      1, Training Accuracy:   6.2%\n",
       "Time usage: 0:00:00\n"
      ]
     }
@@ -1600,7 +1600,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 15.7% (1566 / 10000)\n"
+      "Accuracy on Test-Set: 13.0% (1296 / 10000)\n"
      ]
     }
    ],
@@ -1629,7 +1629,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Time usage: 0:00:06\n"
+      "Time usage: 0:00:00\n"
      ]
     }
    ],
@@ -1648,15 +1648,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 64.6% (6461 / 10000)\n",
+      "Accuracy on Test-Set: 66.6% (6656 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SCYPBwMzMDD/96U/5+OOPmZmZeWkOrs7ZoNPpkM/nj+0xrK2tkc/nVTza7XZz+fJlfvCD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\nfCOw1Ujhlc1mKRaLVKtVvRWvx+PRmyM1k6O/tkVDc1SmwRykjU8yz0s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/oAkZgUBg4qRMSUeyQYPkTb9/ii9S8pnWQ0deD5p2QjZNzWWm7es6tkazQRuN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\nAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462cdd7f0>"
+       "<matplotlib.figure.Figure at 0x7f56f2f16898>"
       ]
      },
      "metadata": {},
@@ -1688,16 +1688,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    101, Training Accuracy:  71.9%\n",
       "Optimization Iteration:    201, Training Accuracy:  76.6%\n",
       "Optimization Iteration:    301, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    401, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    501, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    401, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    801, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    901, Training Accuracy:  90.6%\n",
-      "Time usage: 0:00:51\n"
+      "Optimization Iteration:    701, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    901, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:03\n"
      ]
     }
    ],
@@ -1717,15 +1717,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 92.8% (9278 / 10000)\n",
+      "Accuracy on Test-Set: 93.1% (9308 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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jpf/BMIz/9bDXeUE4TRv/d8B/A0SOelHaxifKadr4K3OGNkYI8Z8Cfx/oAX7q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\nichNEVkTkeWa188kcFJEztbc45aI7IjIbz7mnF8XkUT1nI9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qtRAMBrG5uYlHjx5xFm6320WhUBDxFN4ao+u12+2iUqkglUphd3cXz549w7e+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\n1Gg0Go1mTLTy1Gg0Go1mTP5/ha2J4E3+0vMAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462cdd780>"
+       "<matplotlib.figure.Figure at 0x7f56f2f24fd0>"
       ]
      },
      "metadata": {},
@@ -1757,97 +1757,97 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:   1001, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1101, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  93.8%\n",
       "Optimization Iteration:   1201, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  95.3%\n",
       "Optimization Iteration:   1401, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1501, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1901, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2101, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  92.2%\n",
       "Optimization Iteration:   2301, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2801, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   2901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3001, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   2401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   2701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2801, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3001, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   3101, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3201, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   3301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3301, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   3401, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   3501, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   3601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   3601, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   3701, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3801, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3901, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3801, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   4001, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4101, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   4201, Training Accuracy:  95.3%\n",
       "Optimization Iteration:   4301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4601, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   4801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   4401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   4501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4601, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   4801, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   5101, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   5101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5201, Training Accuracy:  95.3%\n",
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-      "Optimization Iteration:   5501, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   5701, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   7801, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   7701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   7801, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   8101, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   9101, Training Accuracy: 100.0%\n",
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-      "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9501, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   9601, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
-      "Time usage: 0:11:05\n"
+      "Optimization Iteration:   9401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:26\n"
      ]
     }
    ],
@@ -1867,15 +1867,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.7% (9873 / 10000)\n",
+      "Accuracy on Test-Set: 98.8% (9880 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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ZA4EAMzMz1Ot16vX6l+5ocvCkeMq7otxKvA+DetHRNI1isUgymVSiKT3iMlIi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\nDQaDYRcY0TQYDIZdYETTYDAYdsH/Bw5JF403XW0WAAAAAElFTkSuQmCC\n",
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kkvOOLRbLTBrM/HiWgnq3oM92MpmwpaNWq73wHIrLWFTMhsMhGo0Gcrkcjo6O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\n8JQkqZLhKUlSJcNTkqRKhqckSZW2QsESFjEbpuAAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462adbbe0>"
+       "<matplotlib.figure.Figure at 0x7f56f2d23518>"
       ]
      },
      "metadata": {},
@@ -1886,23 +1886,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 975    0    0    0    0    1    2    0    1    1]\n",
-      " [   0 1127    3    0    0    1    1    0    3    0]\n",
-      " [   2    1 1020    0    1    0    0    5    3    0]\n",
-      " [   1    0    0  994    0   12    0    1    2    0]\n",
-      " [   0    0    0    0  978    0    2    1    0    1]\n",
-      " [   1    0    0    2    0  887    1    0    1    0]\n",
-      " [   8    3    0    0    3    6  937    0    1    0]\n",
-      " [   0    1    6    1    0    0    0 1017    1    2]\n",
-      " [   4    0    2    2    1    4    0    3  955    3]\n",
-      " [   1    4    0    0    9    6    0    5    1  983]]\n"
+      "[[ 973    0    1    0    0    1    1    0    3    1]\n",
+      " [   0 1129    2    1    0    0    1    1    1    0]\n",
+      " [   1    2 1023    2    0    0    0    2    2    0]\n",
+      " [   1    0    1 1002    0    3    0    1    2    0]\n",
+      " [   0    1    0    0  974    0    1    0    2    4]\n",
+      " [   2    0    0    3    0  882    2    0    1    2]\n",
+      " [   4    1    0    0    1    4  948    0    0    0]\n",
+      " [   1    4   11    2    0    0    0 1004    2    4]\n",
+      " [   3    0    4    2    1    2    0    0  960    2]\n",
+      " [   3    4    1    0    7    5    0    2    2  985]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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lG8XqjbF5wMUtqEv1tEVwzybN2Z7UUQGwnaRdgUUR8UzramZmHclT/rZHcAf2BH5JGsQf\nwPey/VcAx7eqUmbWoRzc2yO4R8SvaZOnZc2sAhzc2yO4m5kVyh2qDu5mVkFuuTsVYmZWRW65m1n1\nuOXu4G5mFeScu4O7mVWQW+4O7mZWQQ7uDu69mcyk0q+xsGty6dfYrLv8+zBrO0PIH6wrNrykYrdj\nZmbglruZVVFtXdS851RIxW7HzAzn3HFwN7MqcnB3cDezCnKHqoO7mVWQc+6t/6ySdKqk+yW9JGmB\npJ9Jem+r62Vm1slaHtyB/YDzgH2AA4FhwK2S3tLSWplZ56rl3PNszrkXKyI+Wv9a0nHA88Bo4K5W\n1MnMOpxz7q0P7muwCWmpvUWtroiZdSiPlmmv4C5JwLnAXRHxSKvrY2Ydyh2qbXc7FwLvAz7Q6oqY\nmXWytgnuks4HPgrsFxHz+j9jKjC8Yd9IYFThdTOzMswEZjXsW1FM0c65t0dwzwL73wMfjIinB3bW\nIcBWJdbKzMo1itUbY/OAiwdftHPurQ/uki4ExgKHA0slbZG9tSQiCvoYN7N1inPubXE7J5BGx/yq\nYf9ngSvXem3MrPO55d764B4RFct0mVnLOedetdsxMyuHpLmSetawnZe9/6uG/d1Z2rm+jG0k3SRp\nqaT5ks6SVEocbnnL3cyscOWkZfZsOGoUcCtwXfY6SL3BEwFl+5bVDs6C+M3Ac8AYYGvgKuA1YELO\n2vbLwd3MqqeEDtWIeLH+taTDgMcj4s663csi4oVeijgY2An4cEQsBGZKmgicKem0iFiZs8Z9clrG\nzKqnlnPPs+WIhpKGAccAlza8dYykFyTNlPTNhgkQxwAzs8BeMw3YGNhl4FcfGLfczax6yh8tcyQp\nKF9Rt+/HwFOktMv7gbOA9wL/mL2/JbCgoZwFde/NyFWDfji4m1n1lB/cjwduiYj5tR0RcUnd+w9L\nmg/cLmnbiJjbT3mR6+oD4OBuZuucKT+DKf+76r4lLw3sXEnvIq09cUQ/h96X/bk9MBeYD+zVcEzt\noc3GFv2gObi30Gbdk0q/Rs/bJpd+jSGLyr8Ps1z66VAd+3/SVm/6QzD6wAGVfjwpGN/cz3G7k1rk\ntbmy7gW+Lmmzurz7QcASoPBZcB3czaxyYghEzoeYBvI4ZTYt+XHA5RHRU7d/O+BoUsB/EdgVOBv4\ndUTUZke7lRTEr5J0CmlyrDOA8yPi9Xy17Z+Du5lVTncXdOeMbt0D+zA4ENgGuKxh/2vZeycBGwDP\nANcD36gdEBE9kj4O/BdwD7AUuBwo5auvg7uZVU5PE8G9ZwDBPSJ+wRq6XiPiz8CHBnD+M8DH89Ws\nOQ7uZlY53V1iZZf6P3CVc4ISBq20jB9iMjOrILfczaxyuru66B6ar+3a3dUDFDoDQEu1vOUu6QRJ\nMyQtybZ7JB3S6nqZWefq6epKAT7H1tNVrQnd26Hl/gxwCvBY9vo44AZJu0XE7JbVysw6VjdD6M75\nyGl3SXVplZYH94i4qWHXBEnjSZPsOLibWW7ddLHSwb19ZPMdfxIYQXqay8zMmtAWwV3SSFIwHw68\nDBwZEXNaWysz61Q9dNGdM7z19H9IR2mL4A7MIT2uuwnwD8CVkvZ3gDezZjSXc69WeG+L4J6tQPJE\n9nK6pL1Jj/GO7/2sqaSGfr2RpJWvzKz9zQRmNexbUUjJqeWeL7j3OLivFUOA9fs+5BDSvDtm1plG\nsXpjbB5pGdLB6Wmi5d5TsS7Vlgd3Sd8AbiENiXwraemqD5KmwjQzy20lQ3KPllnZ+sd+CtXy4E6a\nrP5KUjN8CfAQcFBE3NHSWpmZdbCWB/eIGNfqOphZtfQwtInRMk7LmJm1teZy7k7LmJm1teaGQjq4\nm5m1teamH/DEYWZmba25J1SrFdyr9T3EzMwAt9zNrIK6m3hC1WkZM7M259EyDu6VN2TRpNKvESMn\nl1q+ZpV/D1YtHi3j4G5mFeTRMg7uZlZBHi3j0TJmZpXklruZVY5z7g7uZlZBzS3WUa20jIO7mVVO\ndxPzuVet5d52dyPpVEk9ks5udV3MrDN1Zx2q+bZqtdzbKrhL2gv4HDCj1XUxM+tkbRPcJW0IXA2M\nA/7S4uqYWQer5dzzbAPJuUvaWtJVkhZKWiZphqQ9Go45XdJz2fu/kLR9w/ubSvqxpCWSFku6RNIG\nBf8I2ie4AxcAN3p5PTMbrNpomXxb3+FQ0ibA3cCrwMHAzsCXgMV1x5wCnAh8HtgbWApMk7ReXVHX\nZOceAHwM2B+4qKh7r2mqQ1XS3sC/AO8BjomI5yQdBTwZEb9toryjgN2APZupj5lZvZKeUP0a8HTD\n0qBPNRxzEnBGRNwIIOnTwALgCOA6STuTPhhGR8Tvs2O+CNwk6csRMT9XpfuQu+Uu6XDg18D6wL7A\n8OytzYEJTZT3TuBc4NiIeD3v+WZmjXqa6FAdQFrmMOABSddJWiBpuqQ3Ar2kbYEtgdtr+yLiJeA+\nUqwEGAMsrgX2zG1AAPsM/s7f1EzLfRJwYkRcKumIuv13Aac2Ud5o4K+AByUp29cF7C/pRGD9iIjV\nT5vKm58rNSOBUU1UwczWvpnArIZ9KwopuaSHmLYDxgPfA75BCsY/kLQiIq4mBfYgtdTrLcjeI/vz\n+fo3I6Jb0qK6YwrRTHDfibpPpjp/ATZtorzbWD0iXw7MBs5cc2AHOATYqonLmVl7GMXqv/rzgItb\nUJcBGQLcHxETs9czJO1CCvhX93GeSEG/LwM5JpdmgvvzwLbAkw379wXm5i0sIpYCj9Tvk7QUeDEi\nZjdRPzNbx/X3hOrvpjzB76asGq6WL3mtv2LnkRqd9WYDn8j+Pp8UpLdg1db75sDv647ZvL4ASV2k\nhnFji39QmgnulwHnZh0FAbxd0u7Ad4GzCqpXoZ9gZrZu6W+xjj3G7sAeY3dYZd8z0xfy7dE39FXs\n3cCODft2JOtUjYi5kuaTRsE8BCBpI1L65oLs+HuBTSTtXpd3P4D0oXBf/3c2cM0E9/8EhpEqORz4\nLbAS+EFEnFNEpSLiI0WUY2brppVNjJYZwPHnAHdLOhW4jhS0x5EevKw5F5gg6TFSduMM4M/ADQAR\nMUfSNOCHksYD6wHnAVOKHCkDTQT3iOgBJko6k/SptSEwMyIW932mmdnaUcZ87hHxgKQjgTOBiaQ0\n9EkRcW3dMWdJGkEat74JcCdwaETU53yOBs4n9Tf2AD8hDaEsVNMTh2W58ukF1sXMrBBlTfkbETcD\nN/dzzGnAaX28/xfg2FyVa0Lu4C6pvxv7aPPVMTOzIjTTcm98ImsY6enS7YEpg66RmdkgeT735nLu\n49e0X9I3ST2+ZmYt5fnci5047DJW7TU2M2sJz+de7EpMewCeG8bMWs5pmeY6VK9p3EWaB+ADFPcQ\nk3UQzZpUavnx9cmllg+gb5Z7D7Z29fcQU2/nVEkzLffGvHoP8Afg7Ij4+eCrZGZmg5UruGdzIJwD\nPBoRS8qpkpnZ4JQ1zr2T5Aru2dSUd5JWEXFwN7O2VNJiHR2lmbTMI8A2wBMF18XMrBBlTD/QaZr5\nHvJV4LuSDswWel2vfiu6gmZmeZWxhmqnaeZuppFWT5oGLASWN2y5SJokqadhe6T/M83MrDfNpGUO\nLbwWaa2t2pzGkKYQNjNrise55wjukv4D+G5ETCuhHisj4oUSyjWzdZCnH8iXlplEmru9DDtIelbS\n45KulrRNSdcxs3VA/qkHhubugG13ee6mrEnBfgscBzxKetL1NOA3kkZmc8abmeXiJ1Tz59wLX9u0\nIc0zS9L9pGmFP0majMzMLBc/xJQ/uP9RUp8BPiLeNoj6EBFLJP2RND98H6aSlnCtNxIYNZjLm9la\nM5M0lqLeilZUpJLyBvdJlPxkqqQNgfcAV/Z95CGkLI6ZdaZRrN4YmwdcPOiSPVomf3C/NiKeL7IC\nkr4D3EhKxbwDmEwaCulVncysKR4tky+4F55vz7wTuAZ4O/ACcBcwJiJeLOl6ZlZx3U1MP7Auzy1T\nymiZiBhbRrlmtu5yWiZHcI+Ian1nMbPK8miZYtdQNTOzNlGtR7LMzPB87uDgbmYV5PncHdzNrIKc\nc3dwN7MK8mgZd6iamVWSW+7W9vTNSaVfIz4yufRr6I7y78MSP6HqlruZVVDtCdV8W74PA0mnZsuC\nnl2371cNS4Z2S7qw4bxtJN0kaamk+ZLOklR4LHbL3cwqp+ycu6S9gM8BMxreCtLMZxN586n+ZXXn\nDQFuBp4DxgBbA1cBrwETclW4H265m1nl1BbryLMNdLGObObaq4FxwF/WcMiyiHghIp7Ptlfq3jsY\n2Ak4JiJmZutZTAS+IKnQxraDu5lVTt7A3p2vpX8BcGNE3NHL+8dIekHSTEnflPSWuvfGADMjYmHd\nvmnAxsAuuW+0D07LmJkNkKSjgN2APXs55Mek6cufA94PnAW8F/jH7P0tgQUN5yyoe68xzdM0B3cz\nq5wyRstIeidwLvB3EfH6mo6JiEvqXj4saT5wu6RtI2JuP1UodFr1tgjukrYGvg0cCowA/gR8NiKm\nt7RiZtaR+pvPfcmUqbw0Zeqq5yx5pZej3zAa+CvgQUm1ztIuYH9JJwLrR0RjgL4v+3N7YC4wH9ir\n4Zgtsj8bW/SD0vLgLmkT4G7gdlJnw0JgB2BxK+tlZp2rv9EyG479GBuO/dgq+1ZMn83To4/qq9jb\nWH1dwMuB2cCZawjsALuTWuTzstf3Al+XtFld3v0g0vKlj/R18bxaHtyBrwFPR8S4un1PtaoyZtb5\nepqYW6a/0TIRsZSGACxpKfBiRMyWtB1wNGmo44vArsDZwK8jorYS+K1ZGVdJOoW0EPQZwPm9pXqa\n1Q6jZQ4DHpB0naQFkqZLGtfvWWZmvViZ5dzzbU2Fw/rW+mvAgaTRL7OB7wDXA4e/cXBED/BxoBu4\nB7iS1Pov/PHldmi5bweMB74HfAPYB/iBpBURcXVLa2Zm1oeI+Ejd3/8MfGgA5zxDCvClaofgPgS4\nPyImZq9nSNqFFPAd3M0st55sSoG851RJO9zNPNJXmHqzgU/0fdpUYHjDvpGs3t9hZu1pJjCrYd+K\nQkouI+feadohuN8N7Niwb0f67VQ9hNQXYWadaRSrN8bmkaZmGZxuhjBkHZ8Vsh2C+znA3ZJOBa4j\n5dzHkSblMTPLraeni+6enC33nMe3u5YH94h4QNKRwJmkCXTmAidFxLWtrZmZdaru7iGwMmfLvdst\n98JFxM2ksaFmZlaAtgjuZmZF6l7ZBSvzhbfunC39dufgbmaV09PdlTst09Pt4G5m1ta6u4cQuYO7\nc+5mZm2te2UXPa/nC+55PwzaXbU+qszMDHDL3cwqKHq6iO6c4c3j3M3M2tzK/OPcWVmtRIaDe0u9\npf9DBm35WrhG59Mdhc+4upqet00u/RpDFpV/Hx2hidEyeLSMmVmb6xasVP/HNZ5TIQ7uZlY93cDK\nJs6pkGolmczMDHDL3cyqyC13B3czq6CV5A/ueY9vcw7uZlY9K4HXmzinQlqec5c0V1LPGrbzWl03\nM+tQPaQ0S56tpyU1LU07tNz3hFXWwxoF3EpalcnMLD/n3Fsf3CPixfrXkg4DHo+IO1tUJTOzjtfy\n4F5P0jDgGOC7ra6LmXUwd6i2V3AHjgQ2Bq5odUXMrIM5LdN2wf144JaImN/qiphZB3Nwb5/gLuld\nwIHAEQM7YyowvGHfSFJ/rJm1v5nArIZ9K4op2sG9fYI7qdW+ALh5YIcfAmxVYnXMrFyjWL0xNg+4\nePBFO7i3fpw7gCQBxwGXR0TFRpuama197dJyPxDYBris1RUxswrwE6rtEdwj4hes+iCTmVnzak+d\n5j2nQtoiLWNmVqhazj3P1k9wl3SCpBmSlmTbPZIOqXt/fUkXSFoo6WVJP5G0eUMZ20i6SdJSSfMl\nnSWplDjs4G5m1VNCcAeeAU4BRmfbHcANknbO3j8X+BjwD8D+wNbAT2snZ0H8ZlLGZAzwGVJf4+nN\n32jv2iItY2bW7iLipoZdEySNB8ZIepY04u+oiPg1gKTPArMl7R0R9wMHAzsBH46IhcBMSROBMyWd\nFhGFZv3dcjez6imn5f4GSUMkHQWMAO4lteSHArfXjomIR4GngX2zXWOAmVlgr5lGeip/l5x32C+3\n3M2sekoVEgw9AAAMQUlEQVSaW0bSSFIwHw68DBwZEXMk7Q68FhEvNZyyANgy+/uW2evG92vvzchZ\n4z45uJtZ9ZT3ENMcYFdgE1Ju/UpJ+/dxvIAYQLkDOSYXB3czq57+gvv0KfD7KavuW7Gk32KzvPgT\ntVIk7Q2cRFp/Yj1JGzW03jfnzdb5fGCvhiK3yP5sbNEPmoN7Sy1vdQVsLRqyaFLp14h9Jpd+Dd1X\n/n0MWn8PMY0am7Z6z06H80bnvdIQYH3gweyqBwA/A5D0XuBdwD3ZsfcCX5e0WV3e/SBgCfBI3gv3\nx8HdzGwAJH0DuIU0JPKtpLUnPggcFBEvSboUOFvSYlI+/gfA3RHxu6yIW0lB/CpJp5AmxzoDOD8i\n8j5P2y8HdzOrnnKeUN0CuJIUlJcAD5EC+x3Z+ydnpfyE1JqfCnyhdnJE9Ej6OPBfpNb8UuByoJSv\nQg7uZlY9JXSoRsS4ft5/FfhitvV2zDPAx3PWrCkO7mZWPZ7y18HdzCrIwd3B3cwqyFP+tn76gewx\n3jMkPSFpmaTHJE1odb3MzDpZO7TcvwZ8Hvg0aZjQnsDlkv4SEee3tGZm1pk8n3tbBPd9gRsiYmr2\n+mlJRwN7t7BOZtbJnHNvfVqGNN7zAEk7AEjaFfgAA14o28ysQcmzQnaCdmi5nwlsBMyR1E36wPn3\niLi2tdUys47lDtW2CO6fAo4GjiLl3HcDvi/puYi4qqU1M7PO5Jx7WwT3s4BvRsT12euHJb0bOBXo\nI7hPJU2pXG8kMKrwCppZGWYCsxr2rWhFRSqpHYL7CFafy7iHfvsDDiFN8WBmnWkUqzfG5gEXD75o\nd6i2RXC/Efh3Sc8ADwN7kCbguaSltTKzzuXg3hbB/UTStJcXkCa2f440a9oZrayUmXUwd6i2PrhH\nxFLg37LNzGzwesjfEu8poyKt0w7j3M3MrGAtb7mbmRWu9mBS3nMqxMHdzKrHHaoO7mZWQe5QdXA3\nswpyh6qDu5lVkNMyHi1jZlZFbrlbAYa1ugIFyJugbU+6b1Lp14htJ5dW9vRXYfRzBRTk0TIO7mZW\nQe5QdXA3swpyh6qDu5lVkDtUHdzNrIKcc/doGTOzKnLL3cyqxx2q7dFyl7ShpHMlPSlpmaS7JO3Z\n6nqZWYeqdajm2dyhWopLgfcBx5DW2fon4DZJO0fEvJbWzMw6jztUW99ylzQc+ATwlYi4OyKeiIjJ\nwGPA+NbWzsw6Ui2459n6Ce6S9pP0c0nPSuqRdHjD+5dl++u3mxuO2VTSjyUtkbRY0iWSNijknhu0\nQ8t9KNAFvNqwfznwt2u/OmbW8ZrJn/d/zgbAH4AfAT/t5ZhbgOMAZa8b49o1wBbAAcB6wOXARcCx\nOWvbr5YH94h4RdK9wERJc4AFwNHAvsCfWlo5M7NMREwFpgJIUi+HvRoRL6zpDUk7AQcDoyPi99m+\nLwI3SfpyRMwvsr4tT8tkjiV90j0LrCAtmn0NlcuCmdlakbcztbYN3ockLZA0R9KFkt5W996+wOJa\nYM/cBgSwTyFXr9PyljtARMwFPizpLcBGEbFA0rXA3N7PmgoMb9g3EhhVVjXNrEBTXoEpS1fdt6So\n5lwz5Qz+2reQ0jVzgfcA3wJulrRvRASwJfB8/QkR0S1pUfZeodoiuNdExHJguaRNSV9fvtz70YcA\nW62diplZ4cZumLZ6hc0K2U1qD+cxyKGQEXFd3cuHJc0EHgc+BPyyj1NF/tr2qy2Cu6SDSDf4KLAD\ncBYwm9TZYGaWz0re7NJck54pEFNW3RdLCq1CRMyVtBDYnhTc5wOb1x8jqQvYlNTXWKi2CO7AxqSv\nMO8AFgE/ASZEhHPuZla8IWOBsavui+nQPbqwS0h6J/B20rM7APcCm0javS7vfgDpY+i+wi6caYvg\nHhHXA9e3uh5mVhHd9N1yX5N+EiPZePTt60reTtKupAbpImASKec+Pzvu28AfgWkAETFH0jTgh5LG\nk4ZCngdMKXqkDLRJcDczK1zhWWz2JKVXItu+l+2/AvhX4P3Ap4FNgOdIQf0/IqJ+lpujgfNJo2R6\nSFmKkwqvKe0zFHItmFmBa1ThHgBmVOQa/vceiCmvlH6JtSIifh0RQyKiq2E7PiJWRMQhEbFlRAyP\niO0iYnzjmPeI+EtEHBsRG0fEphHxuYhYVkZ916HgPqsC16jCPUBVgpb/vQemcbijrR3rUHA3M1t3\nOLibmVWQO1TNrIK8WkcnBvdszoGFOU9bwZvDTctS9jXa9R7y/jdaQRpMUKa812jmF3vd/Pee3jjP\nYT+WdA/8nNmvvfHXxrlFcvIiqkpTHnQOSUcDP251PcysVMdExDV5T5K0B/Ag/BrYLefZfwA+CGnW\nxul5r91uOrHlPo20YtOTpGaHmVXHcODdZA/+NM9LMXVccI+IF0nTAZtZNd0z+CKcc/doGTOzCuq4\nlruZWf/ccndwN7MKcs7dwd3MKsgtd+fcra1I+mtJPZLen73+oKRuSRu1oC6/lHT22r6uFaHWcs+z\nVavl7uBuAyLpsizodkt6VdKfJE2QVMb/ofqHL+4GtoqIlwZYTwdk482We56tWi13p2Usj1uA40hj\nkQ8FLiT9Vny7/qAs4Ec0/4TcG8ssRMRKGhYVNrP+ueVuebwaES9ExDMRcTFwO3C4pM9IWizpMEkP\nkx4u2wZA0jhJj0hanv05vr5ASXtLmp69fz+wO3Ut9ywt01OflpH0gayFvlTSIkm3SNpY0mWkRwxP\nqvuW8a7snJGSbpb0sqT5kq6U9Pa6Mkdk+16W9Kykfyvvx2jly5uSaWa6gvbm4G6DsZy0VBjACOCr\nwD8DuwDPSzoGOA04FdgJ+DpwuqR/ghRQgRtJk4rvkR373TVcpz7Y70ZaxWYWMAb4QFZGF2lFm3uB\nHwJbAFsBz0jamPRB9GB2nYNJCxXXr1b/XWA/4DDgINKK9cUtqGlrmdMyTstYUyQdSAqS3892DQXG\nR8SsumNOA74UETdku56StAvweeAq4FhSCmZcRLwGzJa0DSnd05uvAL+LiC/W7Ztdd83XgGX1K+BI\nOhGYHhET6/aNA56WtD1p5qzjgaMj4lfZ+58B/jzAH4e1HQ+FdHC3PA6T9DIwjBSUrwEmA58EXmsI\n7COA9wCXSrqkroyhwOLs7zsBD2WBvebefuqwG6u2uAdiV+AjWd3rRVbHEaR7uv+NNyIWS3o053Ws\nbXgopIO75XEHcALpt+a5iOgBkAQpRVNvw+zPcdQFzUytiSTyL2PceJ2B2BD4OSltpIb35gHvzf7e\nWVOkmvXBOXfLY2lEzI2IP9cCe28i4nngWeA9EfFEw/ZUdtgjwK6S1qs7dd9+6vAQcEAf779Gyr/X\nm07qB3hqDXVZDjxGaraNqZ0gaVPeDPrWcTzO3cHdynQacKqkL0raIRuxcpykk7P3ryG1li+RtLOk\njwJfWkM59a3tbwF7SbpA0ihJO0k6QdLbsvefBPbJHoaqjYa5AHgbcK2kPSVtJ+lgST+SpIhYClwK\nfEfShyWNBC6jar/t6xR3qDq4W2ki4lJSWuazpBb3r4DPAE9k7y8ljU4ZSWpdn0FKnaxWVF2ZfyKN\nZnk/cB/pIafDefM387ukoPwIacTOuyJiHmlUzRDSPOEPAWcDi+vG4n8FuJOUvrk1+/uDg/wRWMu4\n5d5xKzGZmfXmzZWYvgNsl/PsJ0if8V6JycysTXm0jNMyZmYV5Ja7mVVQM9MJVKvl7uBuZhXktIyD\nu5lVkKcfcHA3swpyy90dqmZWQeWNc5f0BUlzs2mqfytpr+LrP3gO7mZmAyTpU8D3gEmktQdmANMk\nbdbSiq2Bg7uZVVBp0w+cDFwUEVdGxBzSRHrLSFNGtxUHdzOroOLTMpKGkRZwub22L5u+4jb6n/Bu\nrXOHqplVUCkdqpuRZhxd0LB/AbBjzouVzsHdzCpoPvlHvyxs9mLNrEtQOgd3M6uShcAy+J8RTZ7/\nKr1H+YWk3M0WDfs3Z/XWfMs5uJtZZUTE05J2JqVQmrEwIp7upezXJT1IWizm5wBKy5AdAPygyeuV\nxsHdzColC85rDNAFOBu4Igvy95NGz4wALi/pek1zcDczG6CIuC4b0346KT3zB+DgiHihtTVbnRfr\nMDOrII9zNzOrIAd3M7MKcnA3M6sgB3czswpycDczqyAHdzOzCnJwNzOrIAd3M7MKcnA3M6sgB3cz\nswpycDczqyAHdzOzCvr/JoxuWOZEVREAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f94bbf9b5f8>"
+       "<matplotlib.figure.Figure at 0x7f56f0ad5550>"
       ]
      },
      "metadata": {},
@@ -2090,9 +2090,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP4AAAD8CAYAAABXXhlaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
+      "image/png": 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J+AXwsVLK3V011wGv7VqtABeXUk6fcbeac1avXl279vHHH2+khyVLltSu3WWXXRrpQZqu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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f946306c978>"
+       "<matplotlib.figure.Figure at 0x7f56f0a26048>"
       ]
      },
      "metadata": {},
@@ -2120,9 +2120,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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uXbhwYeVa1ceZsCQlMoQlKZEhLEmJDGFJSmQIS1IiQ1iSEhnCkpTIEJakRIawJCUyhCUp\nkactayeHHnpo5dp77rmncu2SJUsq165atapy7Zo1a2rpAbr7ReLt27d39dpVvfOd76xce+6559bS\ng+rjTFiSEhnCkpTIEJakRIawJCUyhCUpkSEsSYkMYUlKZAhLUiJDWJISGcKSlMgQlqREXjtCMzJ/\n/vzKtatXr65c+/DDD1euXbZsWeXa8847r3ItdPcT8t0444wzKtcODw9Xrn3lK/2T7jfOhCUpkSEs\nSYkMYUlKZAhLUiJDWJISGcKSlMgQlqREhrAkJTKEJSmRISxJibo6xzEiPg6cDvwB8AJwD/CxUsoj\nHTV3Aid0PK0A15VSujtfVANnaGiocu2iRYsq195+++3TaUeaFbqdCR8PfBZ4G/AOYD/gKxHxmo6a\nAlwPzAXmAfOBi2beqiQNnq5mwqWUUzrvR8TZwE+BEeCujoeeL6Vsm3F3kjTgZrpP+CBaM9+nJi1/\nb0Rsi4gHI+KKSTNlSVLbtK97FxEBfBq4q5TyvY6HPg/8EHgCOBq4GjgS+IsZ9ClJA2kmFx9dBSwE\njutcWEr5p467342ILcBXI+KwUsqjM1ifJA2caYVwRFwLnAIcX0rZvIfy+4AAjgB2G8Kjo6M7fXve\naDRoNBrTaVGS9opms0mz2ZywbHx8vPLzo5TS1QrbAfwu4MRSyn9XqD8O+CZwTCll0y4eHwY2bty4\nsatfEJCk2WpsbIyRkRGAkVLK2FS13R4nvApoAKcBz0XE3PZD46WUFyPicOAs4A7gSeAY4Bpg/a4C\nWJL2dd3ujlhC62iIOyct/xCwGvgFreOHLwAOAH4E/CvwtzPqUpIGVLfHCU95SFsp5cfA4pk0JEn7\nEq8dIUmJDGFJSmQIS1IiQ1iSEhnCkpTIEJakRIawJCUyhCUpkSEsSYkMYUlKZAhLUiJDWJISGcKS\nlMgQlqREhrAkJTKEJSnRrA7hyT+eN0gcW/8a5PEN8thgdo7PEE7i2PrXII9vkMcGs3N8szqEJWnQ\nGcKSlMgQlqRE3f7kfR32B3jooYd2emB8fJyxsbG93tDe4Nj61yCPb5DHBntvfB15tv+eaqOUUm83\ne2og4izg86lNSFI93ltKuXmqgtkQwgcDJwOPAS+mNiNJvbE/cCiwrpTy5FSF6SEsSfsyv5iTpESG\nsCQlMoQlKZEhLEmJZmUIR8TSiHg0Il6IiHsj4o+ye+qFiLgkIn416fa97L6mIyKOj4jbIuIn7XGc\ntouayyPiiYh4PiL+PSKOyOh1OvY0voj43C625R1Z/VYVER+PiA0R8WxEbI2IL0XEkZNqXh0R/xAR\n2yPiZxFxa0TMyeq5GxXHd+ek7fZyRKzK6nnWhXBEvAdYAVwC/CHwn8C6iDgktbHe2QTMBea1b2/P\nbWfaDgAeAJYCOx1iExEfA84H/hJYBDxHazu+am82OQNTjq9tDRO3ZWPvtDYjxwOfBd4GvAPYD/hK\nRLymo+bTwKnAGcAJwG8DX9jLfU5XlfEV4Hp+ve3mAxft5T47uillVt2Ae4G/77gfwI+Bi7J768HY\nLgHGsvuoYVy/Ak6btOwJYLTj/oHAC8CZ2f32aHyfA76Y3VsPxnZIe3xv79hOPwdO76j5P+2aRdn9\nznR87WXfAK7J7m3HbVbNhCNiP2AE+NqOZaX1f+2rwLFZffXY77c/4v4gIm6KiN/NbqjXIuIwWjOM\nzu34LHAfg7MdARa3P/J+PyJWRcRvZjc0DQfRmhk+1b4/QutyBp3b7mHgcfpz200e3w7vjYhtEfFg\nRFwxaaa8V82Ga0d0OgT4DWDrpOVbaf1r3O/uBc4GHqb1EehS4JsR8eZSynOJffXaPFpv/F1tx3l7\nv51arKH1Ef1R4E3A3wF3RMSx7YnDrBcRQWvXw12llB3fTcwDftH+R7NT32273YwPWpdJ+CGtT2tH\nA1cDRwJ/sdebZPaF8O4Eu98v1zdKKes67m6KiA203gxn0vp4O+gGYjsClFJu6bj73Yh4EPgBsJjW\nx91+sApYSLXvJfpx2+0Y33GdC0sp/9Rx97sRsQX4akQcVkp5dG82CLPvi7ntwMu0dph3msPOs6q+\nV0oZBx4B+uaogYq20Pqj3Se2I0D7j3c7fbItI+Ja4BRgcSnliY6HtgCviogDJz2lr7bdpPFt3kP5\nfbTerynbblaFcCnlJWAjcNKOZe2PFCcB92T1VZeIeB2tj7J7epP0lXYgbWHidjyQ1jfWA7cdASLi\njcDB9MG2bAfUu4A/LaU8PunhjcAvmbjtjgR+D/iPvdbkDOxhfLvyh7Rm+SnbbjbujrgGuDEiNgIb\ngFHgtcC/ZDbVCxGxHLid1i6I3wEuo/WGn30/fLUHEXEArZlDtBcdHhHHAE+VUn5Ea1/c30TEf9G6\nQt4yWke5/FtCu12banzt2yW09glvadddRetTzbqdX232aB8P2wBOA56LiB2fVsZLKS+WUp6NiH8G\nromIp4GfAZ8B7i6lbMjpuro9jS8iDgfOAu4AngSOoZU560spmzJ6Tj88YzeHlZxH6w/3BVr/+r41\nu6cejatJK4heoPVt883AYdl9TXMsJ9I69OflSbcbOmoupfXlx/O0wumI7L57MT5alylcSyuAXwT+\nG/hH4Ley+64wrl2N6WXgAx01r6Z1rO12WiH8r8Cc7N57MT7gjcCdwLb2+/JhWl+qvi6rZy9lKUmJ\nZtU+YUna1xjCkpTIEJakRIawJCUyhCUpkSEsSYkMYUlKZAhLUiJDWJISGcKSlMgQlqREhrAkJfof\ns7siGVk8TKsAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f94b054e4e0>"
+       "<matplotlib.figure.Figure at 0x7f56f0abf0f0>"
       ]
      },
      "metadata": {},
@@ -2160,9 +2160,9 @@
    "outputs": [
     {
      "data": {
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ACI8yBACERxkCAMKzbnF94803a/L48daCyR/4gDUvpV3uLUmn1tX5u7q7rfll9obqsl2S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\n11QAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462ebbb38>"
+       "<matplotlib.figure.Figure at 0x7f56f09ba320>"
       ]
      },
      "metadata": {},
@@ -2190,9 +2190,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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s9/CW4skQAOA8iiEAwHkUQwCA89rlQ/f//Oc/PdfHjx9X96Snp6uspKREZdaa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\n/wB1n632HVyUlQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f946299e128>"
+       "<matplotlib.figure.Figure at 0x7f56f22ad080>"
       ]
      },
      "metadata": {},
@@ -2220,9 +2220,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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zzTUqs45UmzZtmso2bNjgaVsFj9HuNmPhzhAA4DwmQwCA85gMAQDOC33NMCEh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\nAeYJimIwjwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462a39a58>"
+       "<matplotlib.figure.Figure at 0x7f56f0d59dd8>"
       ]
      },
      "metadata": {},
@@ -2268,9 +2268,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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cL/r3iewd/WvlvaN/9M/1ymr84SJlZWXlSxovqUJSvfkNLS9bUqGkF9Lp9M4WPhb61wyt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\nOAEACPD/AOULKX5U7BsBAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462f81940>"
+       "<matplotlib.figure.Figure at 0x7f56f22ade10>"
       ]
      },
      "metadata": {},
@@ -2297,9 +2297,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Nmg9JIyVlm+FjpM/r+64f1O97WTvq18xrR/2on+uRt/fFRcrLy+so6QxJGUkRv/ViI19S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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f94625d4ac8>"
+       "<matplotlib.figure.Figure at 0x7f56f22ade48>"
       ]
      },
      "metadata": {},
@@ -2331,9 +2331,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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UYxPxiRMAAAcMnAAAOGDgBADAAQMnAAAOGDgBAHDgNKu2oaEhMNNT6zAiIvLl\nL3/Z+YTGjBljjJu6xmhsnYlSqaOjQ9rb2z2x5557Tj1+1apVxvjbb7+t5lxxxRXGeFcbMyP/TL/a\n2lr12FTZsGGD7N69OxD/8MMPjcfv2LFDfSx/96ZuthrNnz/fGL/zzjsDMVtHlFRpb28PtNhbvny5\nevx//dd/GeO2un7xi180xu+77z41Z9iwYZ5t7d8z1aZOnSpTp071xLS2cD3117/+1Ri3dSjyz4AP\n44x4EZFLL7008B7+2c9+tl+e+/Dhw+o+/1jR1V/3jPjECQCAAwZOAAAcMHACAOCAgRMAAAcMnAAA\nOGDgBADAgdPtKJ/+9Kdl2rRpnpitqbi2yK9/Qd1Ed911lzFuux3Fv+jp2Z4mfrbk5+dLYWGhJ3bD\nDTeox1977bXG+N69e9WcSy+91BivrKxUc/zN+A8ePKgemyqjR4+W8ePHB+Jao/J/+qd/Uh+rtLTU\nGH/22WfVHG1R9rKyskAs2Snt/Wno0KEyYsQIT2zp0qXq8VdeeaUx7l/kIdFll11mjFdVVak5/luM\nbI+fSm1tbYGFv23vfYMGDXJ+DtOCASIin/rUp9Qc/wL1tgXrU6mxsTFw65HtNpGeLJTwpS99yRi3\n3Z7Y0tLi2U72vS+cVQYAIKQYOAEAcMDACQCAAwZOAAAcMHACAODAaVatqVG0f0ZrorvvvtsYt82y\nu+OOO1xOSUREWltbPdtHjx51foz+0NnZKR0dHZ6YrSmzv6F+t8svv1zN+dGPfmSM+2dUJrrkkks8\n29ps6FSaOHGicTZ2JBJxfqydO3ca47Zrr7i42Bg3zXjMzMx0Pqe+1tbWJidPnvTEmpub1eOzssxv\nDbNnz1ZztLr6nzdReXm5Z9u/CEJYmGYl9+Ta27Bhg7rvjTfeMMavv/565+cJm5EjRwZmwGsz4kX0\nhRJMM+t7wz+e+d+fNXziBADAAQMnAAAOGDgBAHDAwAkAgAMGTgAAHDBwAgDgwOl2FBPblPb169cb\n41rzchttqruIBBqn5+XlOT9+qtiaMmuNov/4xz+qOdrtLZ/5zGfcTuwc9vDDDxvjWiN3EZHnn3++\nr04nZWy3U1xwwQXOj1dfX2+M26b4Dx061LOdn5/v/Lyp4r+VIdELL7xgjD/44INqzj333NPrc0on\nf/7zn9V92vuY//alZGjN80WC11+yYwefOAEAcMDACQCAAwZOAAAcMHACAOCAgRMAAAdOs2ozMjIC\nDaxtDduV5mcPAAASbElEQVTnzJljjK9cudLlaT96bs3gwYM929ps1DDwz2TMzc1Vj/3Nb35jjK9e\nvVrNmTlzpjFumyXpb6xtazyfKqYm5SIiL774ovH4devWqY/1t7/9zRi/6aab1JyJEyca4/F4PKlY\nGNlmEFZWVhrj77//vppz0UUXGeM33nijmuO/1sJaO9MCF7ZZyTfccIMx/sorr6g5t99+uzEei8WS\nOMPTbA31UykzMzMwdlx99dX98tw5OTnqPv/7b7JjB584AQBwwMAJAIADBk4AABwwcAIA4ICBEwAA\nB8nOqs0REYlGo4EdO3bsUJNaWlqM8U2bNiX5tP+vqalJ3bdnzx7PdnV1dfd/6tOp+leOiOe8klJX\nV2eMHzp0SM1paGgwxjdv3qzm+GfVJvw7h6F+6rUnol9/2rUnInL8+HFjfP/+/WqOVj//TEGR0F1/\nav1sMzC162jfvn3OOVu3blVzBgwY4NkO2bUnYqmfbVat//fqZrvGtPdFl5myYa2f7e6Lvnbw4EF1\nn79XbcJ52usXj8fP+CMi80UknoY/85P5/fr6h/p9LGtH/dK8dtSP+mk/ka5fzioSiRSJyGwRqROR\n5G8qSp0cESkWkbXxeFz/X7x+Qv16Lg1rJ0L9eiM0tROhfr11rtYvqYETAACcxuQgAAAcMHACAOCA\ngRMAAAcMnAAAOGDgBADAQVINEM7VKcX9hfr1XBrWToT69UZoaidC/XrrnK3fx/kmVm4CDn/90rh2\n1C/Na0f9qJ/2k2zLvToRkWeeeUbKy8s9O2wtuLRFQYcMGaLmaO2lsrL0U/UvhhuNRmXRokUiXecd\nAnUipxcHrqio8Ow4fPiwmqS1GRwxYoSaoy3a2tnZmXROdXV1mOpXJyKyatUqKSsrC+zcuXOnMUlr\neSaiL+Dc0dHhnONfRF3kdP0WLlwoEqL6mV67/laLibRa2F6HthZ0yeZEo1FZvHixSDhqJ2J57R49\nelRNsi0Sfjb5F7mORqNy8803i4Ssfk899VTg9Wt7T8rIMH+LqMVFpHugdmK6/m655RaRM9Qv2YEz\nJiJSXl4u06dP9+xobGxUk/yra3cbNmyY/kTKaucuA2fiw6lJ/SsmIlJRURGo34EDB9Qkfx/FbmPG\njFFzTG/kIvaL1LLqeRjqFxMRKSsrk2nTpgV2ar9vdna2+oAFBQXGuG0gKSwsNMbP8AYZmvqVl5cH\n6tfW1qYmabWw/Q+J7U1NYxlsw1A7Ectrt7W1VU3SrrGz7cSJE9quUNWvrKxMpk6d6tnRk4HT1Bu6\nm2UccH4eOUP9mBwEAIADBk4AABwk+6fa0wdnZQX+ZKr9CUtEZMOGDcb4wIED1RxtOagZM2aoOaWl\npUk/firt379f9u7d64k9/PDD6vHbt283xm3Lk2nfuxQVFak5Tz/9dFLPm0qtra3G5YG0f+tx48ap\nj6UtK3bkyBE1R/vawfS9Sk++a+lrtbW1gVr5/92T2Wf7Tl57L5gzZ46a82//9m+ebW1psjCyfaf7\n+9//3hgfOXKkmvPMM88Y47b6XXnllZ7tMF57IqeXQvS/tz/33HPq8Vu2bDHGbX+q/cQnPmGMX3/9\n9WrOhAkTPNu2ryIS8YkTAAAHDJwAADhg4AQAwAEDJwAADhg4AQBwwMAJAIADp9tRTPbv1/vgrlu3\nzhhfs2aNmrNjxw5j/J577lFzli5d6tmur69Xj02lDz/8MDDd+eKLL1aP//GPf2yM2zpkaLcRjB8/\nXs3x37phuu0j1To6OozdbLTuLRs3blQfS2tlaLvlSetcZercYmvdlyqZmZmB3+Ezn/mM8+O89dZb\n6r7hw4cb47YWm/7OWbZuPKnU2dkZ6HSzdetW9XitG5ftunzxxReNcVPHrG7Nzc2ebVsnslQaM2aM\nFBcXe2KzZ89Wj3/ppZeM8U2bNqk5v/zlL41x2zV1+eWXe7Zra2vVYxPxiRMAAAcMnAAAOGDgBADA\nAQMnAAAOGDgBAHDQ61m1/ia5iR599FGneE/5G0/b1ghNpRkzZgTW9Js5c6bz47z88svqPq3p+ec+\n9zk1xz/rzLaWZarEYjFjc/b169cbj1+9erX6WH/729+M8X//939Xc7oWpg4wzdCtqalRHydVxo4d\nKyUlJZ6Yf5Zjorlz5xrjthnd2tqGtlnu/hnIhw4dUo9NpXg8HmigfsUVVzg/ju39Umsa37WwspH/\ntWubwRw2/vU5E2kLhPSEbaas/w4C2yIGifjECQCAAwZOAAAcMHACAOCAgRMAAAcMnAAAOGDgBADA\nQa9vR7H5y1/+YoyPGjVKzbFN19bk5uZ6trUGy6l26tSpwHR+bQq/iMgTTzxhjC9btkzN0Rodt7W1\nqTn+5tW2Ww5SZezYscZr4+tf/7rx+PLycvWxBg8ebIzbmk6vXbvWGC8oKAjEtFuCUmnAgAGBBQa0\n2x9ERHbu3GmM23K0WyFsOf73gj179qjHplJWVpba6N9Ea0ZuuxWvJ7eS+G/n8b+Ww8y0aEM3bbEP\n29ih1c/2evTfEpPsex+fOAEAcMDACQCAAwZOAAAcMHACAOCAgRMAAAe9nlVrm8U1bNiw3j78Oa+h\noUHd9/3vf98Yb2lpUXOuvfZaY/zIkSNqTk5Ojmc7jLNCNf4mzd0KCwvVnFmzZhnjb775ppqjzQCc\nMmVKIBbGWckmVVVV6r79+/cb4/5ZnIm0mtuayftn+vq309W3v/1tY1ybnS0igSby3U6ePKnm+O8g\nCOMCDRpbQ3XtOrDNPO7JjGz/TOlkZ07ziRMAAAcMnAAAOGDgBADAAQMnAAAOGDgBAHDAwAkAgINe\n346SmZmp7vPf5tDtjTfeUHO02yYmT56s5mjTuMMmHo8HzrWmpkY9/qtf/aoxvnz5cutzmNgabfun\nfrs0s+4vptqJ6NPvL7nkEvWx1qxZY4xrt7aIiMyYMcMYNzXptzXuDxPba3fkyJHG+OjRo9WcpqYm\nY9x2C4G/VrbrNJXa29sDCyXYbtt67bXXjPGSkhLn57bdSuZf4CKdDB8+3Hmf7RYW7XaU6dOnu51Y\nEtLjFQ4AQEgwcAIA4ICBEwAABwycAAA4SHYWSI6IvbelifZl7YcffqjmaBMWbKuF+/vlVldXd/+n\neXZS/8sR8ZzXR7Zv364mNTc3G+Pa6vIi+uSgEydOqDn+SQ4hq1+OiEg0GjXu1CYL2CZu1NbWGuOt\nra1qzuDBg5N+/oRzDU39TNdefX29mqRN0tGuSRG9h7Ktrv7nCdm1J2Kpn62vrtav2NZ3Vntd2yat\n+XvVhuzaE+nh2KGxTZTatWtXrx8/4Tzt9euerWj7EZH5IhJPw5/5yfx+ff1D/T6WtaN+aV476kf9\ntJ9I1y9nFYlEikRktojUiUjsjAmplyMixSKyNh6Pm5d56EfUr+fSsHYi1K83QlM7EerXW+dq/ZIa\nOAEAwGlMDgIAwAEDJwAADhg4AQBwwMAJAIADBk4AABwk1QDhXJ1S3F+oX8+lYe1EqF9vhKZ2ItSv\nt87Z+n2cb2LlJuDw1y+Na0f90rx21I/6aT/JttyrExH5xS9+IeXl5Umm6G27ugrqvC9Z1dXV8rWv\nfU2k67xDoE5E5JlnngnUz9ZCSqtffn6+mtPR0WGM29aI9LcHi0ajsnjxYpFw1K9OxFw7EX3tUK0O\nIno7tJ4wPVY0GpWbb75ZJET1q6yslIqKCs8OrSWmiEgsZv5woK2xa6Ot7SkSvC6rqqpkwYIFIuGo\nnUjXeaxYsUJKS0s9OxoaGtSkYcOGGeO29SS19768vDw1x//vsX37drnrrrtEQla/n//85zJp0iTP\nDq1Fo4j++rVdf9o+25ql/vePaDQqt956q8gZ6pfswBkTESkvL3daFDRVA2eCsPxp4KP6TZs2zbPD\n9kLS6ldYWKjmaD19XQbOBGGon/Xa0wZOW2/jvh44E4SmfhUVFYH67dy5U006fvy4Ma717LUZN26c\nus9yXYahdiJd51FaWipTpkzx7LC9IWv/s7B/v/7XP+1asi0EbjmHUNVv0qRJgfo1NjaqSdrr11Zz\n7dq0fdCw9Bu21o/JQQAAOGDgBADAQbJ/qhWR00sK7d692xN77LHH1ONfffVVY3z06NFqzqhRo4zx\nhQsXqjkzZ870bGt/vku1rKyswJ8GbH+a1pbG0pZeExFZt26dMX7hhReqORMnTvRsZ2dnq8emysGD\nB2Xfvn2BuHb9vfDCC+pjmZaIEhH57Gc/q+aMHTvWGL/uuusCMW3ZslQ6efJk4HvLrVu3qsdrr6G9\ne/eqOf73hm7z5s1Tc0pKSjzbtj+xp9Jbb70V+N1tr0Pt9dbU1KTmaMst+l+fifz/pravflKpvb09\nsKTaH/7wB/X4FStWGOMHDhxQcw4dOmSMf/rTn1ZzvvOd73i2k33t8okTAAAHDJwAADhg4AQAwAED\nJwAADhg4AQBwwMAJAICDXt+3YesKonWG2LJli5pTUFBgjA8dOlTN8d8qUF9frx6bSrFYTE6cOOGJ\nvfbaa+rxb775pjGutfMSEVm2bJkxfvfdd6s5y5cvV/eFxYABA4y359x///3G42+//Xb1sf7+978b\n42+88Yaao7WnM/0b2W7ZSJXs7OxAS7IvfOELzo9ju91Bq5Gttd/mzZs929otGamW0Hv1IyNGjFCP\nX79+vTG+ZMkSNcd/a0Q32+08u3bt8mzbOuukUl5eXqAD0qJFi9Tjly5daoz35PezXX/+Tk7+92cN\nnzgBAHDAwAkAgAMGTgAAHDBwAgDggIETAAAHTrNqCwsLpaioyBPrWnTW6I477jDGtXUmRfT1+TZu\n3Kjm+Jst29aeTKWcnBwZNGiQJ2abMaftW7NmjZqjNUe2zeZLB5mZmcbG49osbC0uos8E/+d//mc1\nR6u5qSn5jh071MdJd7a1IbV99957r5ozZ84cz3Zra2vPTqyPXX311YH1TG1N3jW21+63vvUtY9y2\nhqd/VndYZyW3tLQEZrf+6le/Uo/X7jbQFlgXCV5L3Wwz7CdMmODZTrZJfjhHGAAAQoqBEwAABwyc\nAAA4YOAEAMABAycAAA4YOAEAcOB0O0pOTo4MHjzYE7PdWtLS0mKM5+XlqTnvvfeeMT5gwAA1p6Sk\nxLN96NAh9dhU6uzslM7OTk/MNqX93XffNcafffZZNeeHP/xhz04u5Ey38oiInDp1yni87ZakVatW\nGeOzZs1Sc/zT1m1x2yIG6WLt2rXG+OjRo9WclStXGuO223P8jb43b94sDz/88JlPsJ/FYjE5fvy4\nJ3bgwAH1+OLiYmO8vLzc+bltC0H4G8/7t8OiqKhIRo0a5YnZblO65ZZbjHHb7VD5+fnG+O7du9Uc\n/y1uHR0d6rGJ+MQJAIADBk4AABwwcAIA4ICBEwAABwycAAA4cJpVa7Jv3z51X11dnTFua+Q8cOBA\nY1yb1Xgue+yxx4xxW839M4yT4Z+Zqs1UDSOtAfZ//Md/qDn+2X3damtr1ZyysjJj3D/LXOT0DOB0\ncOLECXWfqXm9iMgll1yi5mhNu++++241xz+r0dTIP6weeeQRdZ92jVVVVak52vXnn82b6Morr/Rs\n22adho3tfUabHWxreL9161Zj3HbN9nQWMp84AQBwwMAJAIADBk4AABwwcAIA4ICBEwAABwycAAA4\ncJr7HYlEAk3dbU1xtenGtmn/5513njHun3Z9rrDVT7u1ZO7cuWf1HNKhUbTp2hMROXLkiPH4r371\nq+pjXXHFFcb4xo0b1ZwxY8ao55VMLNXa29ulra3NEzM1ze82Z84cY1y7zUJEv03q/vvvV3P8t8TE\nYjH12LA5duyYuu++++4zxpuamtScV155xRjXGsaLBBeJsC1ukEpZWVmBhTpst2315Laa8ePHG+Pa\nrVUmyd5KFs4qAwAQUgycAAA4YOAEAMABAycAAA6SnRyUI2Lus2jrm6p9EV5fX6/maJM9Nm3aZD3B\nRAnnGZamoTkiItXV1YEdtok4jY2NxnheXp6a41Knbp2dnZ7thPMMQ/3U2ono15jtujT1lxURiUaj\nao42kcY0GSNk159aP/9kjWS4TLTotnnzZnWffzJQTU1N93+GoXYiXedhujZaWlrUpF27dhnj27Zt\nU3MaGhqMcdsEQv/koA8++KD7P0Nfv+zs7LP6RNp7qa1+fkm/98Xj8TP+iMh8EYmn4c/8ZH6/vv6h\nfh/L2lG/NK8d9aN+2k+k65ezikQiRSIyW0TqRCQd5ovniEixiKyNx+N6O/1+Qv16Lg1rJ0L9eiM0\ntROhfr11rtYvqYETAACcxuQgAAAcMHACAOCAgRMAAAcMnAAAOGDgBADAAQMnAAAOGDgBAHDwf46m\nR3VcQRMvAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f94627a8080>"
+       "<matplotlib.figure.Figure at 0x7f56edfb5e10>"
       ]
      },
      "metadata": {},
@@ -2361,9 +2361,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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/fr0xblsk3rSovIj+HzoRCYxnMaz1Y3IQAAAOGDgBAHDAwAkAgIN4/8YpIqeW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\nrkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9462c0d080>"
+       "<matplotlib.figure.Figure at 0x7f56f0c979b0>"
       ]
      },
      "metadata": {},
@@ -2467,9 +2467,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/03_PrettyTensor.ipynb b/03_PrettyTensor.ipynb
index 3e1d9ce..238cc7c 100644
--- a/03_PrettyTensor.ipynb
+++ b/03_PrettyTensor.ipynb
@@ -127,7 +127,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.9.0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -139,6 +139,35 @@
     "tf.__version__"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "PrettyTensor version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -155,7 +184,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -173,7 +202,7 @@
    ],
    "source": [
     "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)\n"
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
    ]
   },
   {
@@ -185,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -217,7 +246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": true
    },
@@ -242,7 +271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -280,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
@@ -324,16 +353,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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/6B9RqVTo9/v4/X6sVuvZFr5ut0u32yUej/PgwQNu375NPB4/zUOSHAP9fp9S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\n/6/Ghib4QzPAAAAAAElFTkSuQmCC\n",
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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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\nvxUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a8a866f98>"
+       "<matplotlib.figure.Figure at 0x7f0cfd19bc18>"
       ]
      },
      "metadata": {},
@@ -392,7 +421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true
    },
@@ -410,7 +439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -428,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -446,7 +475,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -489,7 +518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -501,7 +530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": true
    },
@@ -520,7 +549,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -594,7 +623,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -634,7 +663,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -675,7 +704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -744,7 +773,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -764,9 +793,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
-    "collapsed": true
+    "collapsed": false,
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -778,7 +808,7 @@
     "        max_pool(kernel=2, stride=2).\\\n",
     "        flatten().\\\n",
     "        fully_connected(size=128, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=10, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -812,7 +842,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true
    },
@@ -839,7 +869,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -869,7 +899,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false
    },
@@ -891,7 +921,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": true
    },
@@ -909,7 +939,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -927,7 +957,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true
    },
@@ -954,7 +984,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": true
    },
@@ -974,13 +1004,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -1001,7 +1031,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
@@ -1019,7 +1049,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -1093,7 +1123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -1136,7 +1166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": true
    },
@@ -1194,7 +1224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -1281,7 +1311,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
@@ -1290,7 +1320,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 8.5% (849 / 10000)\n"
+      "Accuracy on Test-Set: 9.1% (909 / 10000)\n"
      ]
     }
    ],
@@ -1309,7 +1339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false
    },
@@ -1318,7 +1348,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:      1, Training Accuracy:   6.2%\n",
       "Time usage: 0:00:00\n"
      ]
     }
@@ -1329,7 +1359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1339,7 +1369,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 8.5% (849 / 10000)\n"
+      "Accuracy on Test-Set: 8.9% (892 / 10000)\n"
      ]
     }
    ],
@@ -1358,7 +1388,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1368,7 +1398,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Time usage: 0:00:06\n"
+      "Time usage: 0:00:00\n"
      ]
     }
    ],
@@ -1378,7 +1408,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -1387,15 +1417,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 82.4% (8236 / 10000)\n",
+      "Accuracy on Test-Set: 83.9% (8393 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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XcvsPqMLS3d3dnD9/nlgshsvl0ncxrwhZfWx1dZU7d+5w+/ZtyuUyNpuN3t5eBgYGVEae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\nGGjR1Gg0mmPw/wHYJlY6cPJ77wAAAABJRU5ErkJggg==\n",
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22Wf4/PPPeYRTuVyG3W5HOBx+o9GG3W7nTRlt3iKRCDRNm2noYR41Ri5gn883kw15VVG6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SHEdwD4MoD/FcBVDD98KWVRCPFhAB8RQlihfXBeAH8LQEZK+UkAEEJ8FsC/l1J+7FFvJIS4Cm0l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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a88269710>"
+       "<matplotlib.figure.Figure at 0x7f0cfaa0f710>"
       ]
      },
      "metadata": {},
@@ -1417,7 +1447,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1427,16 +1457,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    201, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    301, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    401, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    101, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    301, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
       "Optimization Iteration:    501, Training Accuracy:  92.2%\n",
       "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    901, Training Accuracy:  95.3%\n",
-      "Time usage: 0:01:13\n"
+      "Optimization Iteration:    701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    801, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    901, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:03\n"
      ]
     }
    ],
@@ -1446,7 +1476,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1456,15 +1486,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 96.2% (9625 / 10000)\n",
+      "Accuracy on Test-Set: 96.3% (9634 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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LCwaDcs0qFBdFvV6nXq8TiURYXFwkHo9TLBbZ39+nUCiQz+eJRCJEIhFqtZeX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\nhx9+SLVa5ctf/jLhcFiHInURi8XCwMAAiUQCKSXj4+NkMpk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Op1k8X3aqp8/DysoKQqEQ9xkVlgtqmtFut9Htdi9135vNZrhcLoRCISSTSS6LIo8H3cgz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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a8801f940>"
+       "<matplotlib.figure.Figure at 0x7f0cfaa0fa90>"
       ]
      },
      "metadata": {},
@@ -1486,7 +1516,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1497,96 +1527,96 @@
      "output_type": "stream",
      "text": [
       "Optimization Iteration:   1001, Training Accuracy:  98.4%\n",
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       "Optimization Iteration:   9301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9401, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
-      "Time usage: 0:13:08\n"
+      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
+      "Time usage: 0:00:27\n"
      ]
     }
    ],
@@ -1596,7 +1626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1606,15 +1636,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.9% (9893 / 10000)\n",
+      "Accuracy on Test-Set: 98.8% (9881 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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v0ThWypFGo9G8aejluUaj0RwBLZoajUZzBLRoajQazRF4pmgKIYJCiGtCiM+E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\n",
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xpBLBZeHOGU/aeVYqFX58cedJH+jLoA8YmE0wZDiDwSCsVivXHlEqNXW8aLfbbFAp28xs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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a886d2c88>"
+       "<matplotlib.figure.Figure at 0x7f0cfaa0f940>"
       ]
      },
      "metadata": {},
@@ -1625,23 +1655,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 972    0    1    0    0    0    2    1    4    0]\n",
-      " [   0 1132    1    0    0    0    1    0    1    0]\n",
-      " [   1    2 1022    0    1    0    0    3    3    0]\n",
-      " [   0    0    3 1002    0    2    0    0    3    0]\n",
-      " [   0    0    0    0  978    0    1    0    1    2]\n",
-      " [   2    1    0   10    0  873    2    0    4    0]\n",
-      " [   2    2    0    1    2    1  948    0    2    0]\n",
-      " [   0    2    5    0    0    0    0 1018    1    2]\n",
-      " [   3    0    2    0    0    1    0    2  965    1]\n",
-      " [   1    3    0    1   11    1    0    5    4  983]]\n"
+      "[[ 975    0    0    0    0    0    1    1    3    0]\n",
+      " [   0 1127    2    0    0    0    1    2    3    0]\n",
+      " [   2    2 1019    1    1    0    1    2    4    0]\n",
+      " [   0    0    0 1005    0    1    0    1    3    0]\n",
+      " [   0    0    0    0  977    0    1    0    1    3]\n",
+      " [   2    0    0   13    0  870    1    0    6    0]\n",
+      " [   5    2    0    0    1    3  943    0    4    0]\n",
+      " [   0    2    8    2    1    0    0 1007    1    7]\n",
+      " [   2    0    2    3    1    1    0    0  964    1]\n",
+      " [   0    2    0    4    5    1    0    1    2  994]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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GvMrMrA+rspx7vq2pcFjfW18JHEwa/TIH+A5wPXDE6ydH9AIfBXqAe4ErSL3/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\nCvr/LO4zMmrEalQAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a87f839b0>"
+       "<matplotlib.figure.Figure at 0x7f0cfa5bec88>"
       ]
      },
      "metadata": {},
@@ -1671,7 +1701,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -1741,7 +1771,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1749,9 +1779,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUQAAADtCAYAAADHjgxUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": 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f8/zzCfcxSvroR9fbmRsXf8o6v2lTtT2jkpyh30vyrjzLrv1Pe84RV6V9T9z8Mf8WvAsu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\nQwBAeP8LD/OStVmJjUoAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a8866d080>"
+       "<matplotlib.figure.Figure at 0x7f0cfb0475c0>"
       ]
      },
      "metadata": {},
@@ -1782,7 +1812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1790,9 +1820,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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J6Q74mOnz833eD/r3hewd/evgvaN/9M/1yGr54SJlZWX1lXSxpCpJzeYT2l+O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\ngxMAgAD/D+/Yo+b/ftEAAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a881ce278>"
+       "<matplotlib.figure.Figure at 0x7f0cfaecdf98>"
       ]
      },
      "metadata": {},
@@ -1812,16 +1842,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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I/f2YXrcu92es6md993nx+IzX1NjnX7du7rHNmz3Pv2w2az4kzZSU7YKPmT6v76N+UL+P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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3a866b6160>"
+       "<matplotlib.figure.Figure at 0x7f0cf8f4cda0>"
       ]
      },
      "metadata": {},
@@ -1848,7 +1878,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false
    },
@@ -1913,10 +1943,11 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/04_Save_Restore.ipynb b/04_Save_Restore.ipynb
index e83561b..523cdba 100644
--- a/04_Save_Restore.ipynb
+++ b/04_Save_Restore.ipynb
@@ -111,7 +111,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.10.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -123,6 +123,35 @@
     "tf.__version__"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "PrettyTensor version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -139,7 +168,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -169,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -201,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -227,7 +256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -265,7 +294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
@@ -309,16 +338,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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/6B9RqVTo9/v4/X6sVuvZFr5ut0u32yUej/PgwQNu375NPB4/zUOSHAP9fp9S\nqcTu7i6ZTIZWq0W/33+rsqlKpcLe3h7lchmj0Yjf7+fy5cu4XK5jPHLJoOj1enS7XZLJJHfu3OGL\nL74gkUjQ7XbZ3t4GnlnyCwsL4qZ2Zre62hY3Ho/z5Zdf8vnnn7O/v3+ahyQ5Bvr9PsVikd3dXbLZ\nLM1m862Fr1wus7e3x/7+Pq1Wi3A4TCAQeGMLUnKydLtdms0myWSS27dv88UXX1AsFoXw7e3tMTU1\nxSeffEK/3x+47/bEha/X65HL5cRPNpvl8ePHrK6ukkwmqdVqL3xeq9Uin88Tj8dxOp0AWK1WLBYL\nNpsNu90uI72njCZsvV6PfD7Pzs4O2WyWTqfz1kXyJpMJp9OJ0Wgkm82i0+moVqt0u10URUGn0527\nxgPvEo1Gg2w2SyqVIpvNUiwWabVa6HQ6nE4nbrcbr9eLyWQ6kbU8FeE7ODhgZWWFnZ0dYrEYW1tb\nbGxskMvl6Ha7L3yeFuTY3d0FnvkKNF9PKBTCZDJJ4RsC+v0+3W6XQqFALBYjm83Sbrff+nWtVit+\nv59kMkmz2URVVer1Op1OB4PBIKO7Q06tViOVSpFKpSgUCtTrdfr9Pnq9nkAgwNTUFNFoFKvVil6v\nP3vC1+122d3d5csvv2R3d5dEIkE6nSaXy9FqtV76vEajwcHBAYqikM/n2dvbw+/34/f7WVhYQK/X\n4/P5MJvNUgBPiV6vR71eJ5fLcXBwILalPp+PQCCAxfL8yNXvjk6nw2AwiMBJvV6nXq/T7Xal6A0p\nmpWvqiq5XI719XW2trYolUr0es9G7WrCt7i4SDQaxWKxnIjlfirCt7Ozw6effkoul6PRaNBsNmk2\nm698Xr1eJx6PUygUsFgsWK1W3G43brebcrmMzWZDp9Ph8Xik8J0SnU5H3JTi8TiJRIJgMMjU1BST\nk5NvnMMHz0S11WpRrVYpFovodDph8Wl5X5Lho9/v0+/3OTg44MGDB6ytrVEqlcTvdTodwWBQCN9J\nRelPTCHa7TaVSoVkMsnm5iarq6vUarVvvVtr/hstGbZardLv9wGOJD66XC5UVWV+fv6tLjDJ69Pr\n9ej1epTLZWKxGMvLy+zv71OtVpmenmZhYYGZmRnhm30Tms0mpVKJYrEoIrvtdlsETVRVlT6+IaTT\n6dBut0mn0zx9+pRYLEa1WhW/1yy++fl5IpEIZrP5bFl8lUqFe/fucfv2bVZXV0UWfr/ff+UHNRgM\nGI1GDAaTGvunAAAgAElEQVQDer1eJDW3Wi2azSa9Xo/Hjx9TLpcpFAo4nU4ikchJfSwJz07uarXK\n3t4et27d4rPPPiMej2O325mcnOT69essLCzgdrvf+D20dJZkMkmj0cBoNB7jJ5AMgn6/T71ep1gs\nkslkSKfTFItF4fNVFAWDwYDX62ViYgK/339i6zpw4dMaEBSLRR48eMDPfvYzYrEY3W73lZE+nU6H\nXq/HarVis9kwm80YjUZ6vR6lUkk40VutFmtra6ytraEoCjdv3mRpaUk8XzJ4tIj7zs4Od+7c4dNP\nP8XpdOLz+ZienubKlSvMzMy89kl9+PzQ0lkODg6o1+syf+8dQKvg0UQvm81SLpeBZ6Kn1+sxmUx4\nvV7Gxsbeakfwugxc+JrNJuVyWQQxCoUCjUYD4KVJinq9nnA4LHK1AoEAdrsdk8lEp9Mhk8mISo54\nPC4cpZVKhe3tbdbW1ohEIgQCgUF/PAlQKpVYXV3l4cOHpFIpAGZmZrh27RpXr14Vftc3CUJoSe7F\nYpGDgwORFygZfvr9Prlcjq2tLdLp9JHovtFoFILndrtP3E1xIsKXyWSE8BWLRZGO8DLhMxgMRKNR\nlpaWmJqaYmJiApfLhdlsptVqsb+/z87ODjqdjlQqJXx+1WqVra0totEoJpNJCt8JoTWXePjwoYi8\nz87O8pOf/ITp6ek3DjhpzQ6azSbFYpFkMkkmkzkSLZQML1o+5+bm5guFz+/3Mz4+jtvtPvHI/MCE\nT3Nq7u/vc/v2be7evcvW1haVSuUbaSuaH89qteJyuQgEAty4cYObN28SiUQIBoOiFVWr1cLhcGCz\n2Ugmk9hsNlRVPdLWSqfT0W636Xa7+P1+fD6fyA2SDvDjo1KpUCqV2N7eZnNzk3g8TrvdxuVyEQwG\nGR8fF36bN/nee70eyWSSvb09YrEYtVoNo9GI3W4XvRlNJtOJ5H1JXh9VVSmVSuzv75PP50WOrqIo\nOBwOZmdnef/99xkbGztxt9TAhK/dblOtVonFYvzqV7/iyy+/JJvNimz7w1E4vV6PzWbD5/MxOTnJ\n7OwsH374Id/73vdwuVxYrVYMBgOKoogLy263s7Kygt1up9Pp0Gw2yefzItChbX8XFxdxuVwys38A\nlEolYrEYGxsbbG1tkUwmhc8mEAgQDodF49g3odfrEY/HuX37Ntvb2zSbTSwWC8FgkGg0itvtlonr\nQ0y/3xdurmKxSKfTEVkaDoeDhYUFPvroI8bHx8+O8PV6PTqdDqVSiUQiwd7eHq1W60j5kslkwmq1\nEg6HmZiYED+Tk5NcuHCBsbEx0Z9LM4W73a440ScnJ5mbm2N3d5eDgwNarRbZbJZ+vy8sQZPJJByn\nRqNRBjyOkVKpJKpv0uk0rVaLYDDIzMwMoVAIm82GyWR67dfVAldaJ4/Hjx8Tj8dptVq4XC6RIhMI\nBGTVxhCi5VwWCgXh5tLqcrWghs1mIxKJMDMzc7a2ulo0V/PRaIXqh9G2LFeuXOH73/8+S0tLeDwe\nvF4vHo9HiN5hS02n02GxWPB4PMzMzPD++++j1+splUoivUVztlcqFSKRCFevXhXpMFL4jg/N4tO6\nphgMBkZHR1laWiIcDr/xd93v92k0GhSLReLxOGtraxwcHNDpdPB6vVy8eJGrV68SCoWkJT+EdDod\nisUiiUSCRCJBMpn8hvCZzWbcbjeBQACTyXS2ghtaS3ktMge/DmNrkdu5uTmuX7/ORx99xNLSEmaz\n+ZXZ2zqdDpPJhN1uZ2xsjCtXrlAoFNja2qJardLpdEQ1SL1eP5L+IJ3hb4+WLKyqqkgx0ZpLWCwW\nxsbGuHz5MpFI5I3v4ocvnHg8zv7+PpVKBZ1Oh8/nY3Z2loWFBXw+n7T2hpDno/CHMzm0iiu/34/H\n4znRFJbDnLhzRHNsOp1OLl26xPe//32uXLkiylW+q79Gr9fj9XqZnp5me3ubaDRKvV6nVCqJL1ky\nGLSbWblcJpPJUCgUaLVaeDwexsfHuXz5shgR8CZorcqWl5eJx+NUq1UURcHpdBIIBBgZGSESieBw\nOI75k0mOA+3cSKfTVKvVIwaH0+kUrorT7KJ+YsKnfXi9Xo/H42F0dJTLly/zgx/8QJQzvU6dnlaX\nq9PpGB0dJRgMkslkqNfrQvi0aG+r1frWhGnJd6fX64kSxEwmQ7FYpNfrYbfbGR0d5cKFC2/1+q1W\ni0QiIVqV1et1HA6HiPiHw2FCodAxfRrJcdPtdimVSqTTaWq12pHrzuVyMTs7y+LiIj6f79SO8USE\nT9sawbPUlcuXL/PjH/+YixcvMjIygs1meyvf2/N5XdqfWieYr776imvXrokKEMmbo/lutRuKVm8d\njUZFzt7bonV5KZfLIllZ8+tqkVzJ8PK8xae1n9I6KM3NzZ0/4TMajVy5coXf//3fx+v1iqjcmzg3\nD7/ui/7sdDrs7e3x5Zdf4nA4mJmZOZYL87xz2JLWhG9kZISpqam3qsfV0Go8tYCVqqpiwJTL5ZJ1\nukPOYYtP2+pqvvnDwncc58qbMjDhKxaLoqV0vV4XwqYoCiaTCYfD8Vb92bS5Dlr7o0wmQ7lcFs0P\ntCBKKBTiwoULJ9ry5qyj9caz2Wy43W46nY5IP2k0GrRaLXGHf50bmuY7rFQqHBwcsL29TaFQEOlJ\nwWBQ9FyUDB+tVot6vU4ikWBnZ0c0F+73+5hMJkwmEzabDZfLJSqxTouBCV8+n2dtbY3t7W3hnAaO\nLf2g3++LcZRa8XqpVKLdbosKDaPRyPj4OB9++CHT09NyFu8xcLi43OFw4Pf7hV81n8+LyhytouJ1\n0KxI7Ya2ublJu92m1+ths9kIhUL4/X4pfEOKlke7t7fH5uYm6+vrYtCUXq/HaDRisVhEO7nTjMgP\nTPi05NZ4PH7E4ntTNL+SlhhdqVTY2dnh0aNH7OzsUC6XRX82rd2Nliv0thUEkqMctvg8Ho9wYieT\nSVZXV4VABQKBV57c7XZbDArX8j1rtRpra2vs7e1RqVTEYw0GA1ar9cjAaclw0el0qNVqlEol8aNh\nsVjw+Xx4vV5RiXWaDOzdD+d4HUd6iRZJrNfrIpq4srLCrVu32N3dPfIemrVntVpFtYZMcj0+NKtd\nawBrMpnIZDLUajU+//xzisUiCwsLLC4uvvQE18qZyuUytVqNWq1GtVqlUqmISp/DHHaVSIaTfr9P\nu90WWRSHcTgcjIyMEAqFhmLnNTDh02pnte3n26L1fNNaUu3t7bG8vMza2hqVSkVscTXLIBAIMD4+\nTiAQEPmBMtn17Tnc6MHlcjEyMkIqlSKfz5PL5djY2KBQKFAoFKhUKi8NRGg+2lKpRKVSOfJTLBZJ\np9NHRM5sNuNyuXA4HDK4MaS0223K5bKYoAa/Pl88Hg+Tk5Mii+O0eWf2floZ2urqKhsbG2xubrK7\nu0u1WqXdbqOqqtjehsNhrl+/zvXr17l8+TJerxeLxSKF75gJhUJcv35dWIBbW1vUajUODg5ot9vs\n7e299DvX0mL6/b7o5NNoNIT19/wuwev1Mjc3x+TkpExcHlK0uTixWExsczXfXigUYnFxkampqaFY\nv6EXPq3cLZ1Os7KywpdffsnDhw9ZW1v7xmMNBgN2u51IJMKNGzf45JNPGBkZwe12S7/QAAgGg6IG\nutPp0O/32d7eJpfLUSwWWV9ff2nSuE6nE/OQNXHUhgk1Gg3RXUfD7XYzPT3N6OjoqfuHJEfR0sqq\n1arolVkul4/42kOhEPPz80Nz4xr6M2hnZ4fV1VVWVlZYWVn5htP7MCaTSfSCi0QijIyM4HQ6pV9o\nQGjBo9nZWUwmE5OTk+zv7wu/br1ef6nwGQwG0WVbuylpwZHt7W1RCqehjRKQ/trhQ7PYs9ks29vb\nbG9vUywWgWfniMPhEPOvtaHhp807IXw///nPWVlZIZvNksvlRN/+5zEajaKeMxwOE41GZfeOAWKx\nWDCZTDidTiYnJ8XQ6EwmI/x3LxM+o9HI7Owsc3NzwoJbXl7m5z//OfDsYjosfJr1IC334UOL5maz\nWXZ2dtje3qbX6x3J2T0sfMPgcjqRYUOaPwcQbaO0KVwAhUKBRCJBPp8XqQ0ajx8/5t69e6Jms16v\ni9yg5/H7/bz//vt8/PHHTExMyC3RgDncacdoNIoT2mazfavFp3XnOeyGcLvdR1qSHUbL76tWq1gs\nFhngGCIajYYwSmq1migiMBgMeDweJiYmxED5YblxnXjJWq/Xo1AoEIvFRHRnY2ODzz//nLW1Ner1\n+pFhMpVKhXK5LMSu1+uJWarPEwqF+Pjjj/nRj34kp3CdAgaDAafTic1mEzmXL0OzBg7f/TUf7Ysi\nt61WS8zU1el0UviGiHq9TiaTIZfLHRkrobURm56eJhgMDtWaDUz4tCBDMpkUvfHgWbAiFovx2Wef\nieHBOzs7YiaH1rT0MJrIvWzL6nA4cDgcjI+PMzExwcjIyKA+luQVaPWYb/N8bf6KTqc7cnM7bF0O\nw1ZJ8mu0Tj2HrT29Xo/FYhFDw0ZHR4eq4mZgwufz+VhcXKRUKoncHnhm8a2urpLP54Wjulqtksvl\naDabdLvdIyf28yf/i8TP7/czPT0t2ltJ3m1eZM1bLBbZpGBI0eZba5VTmkWuGSPXrl1jYmLirWrz\nj5uBCZ+Wd5VOp9na2kKv14uuHslkkkQiIYTseTE7/O/D1p52x9fr9Ue2RfPz81y4cIGFhQW5xT2j\naNPVhiH5VXIULXFZ64Cu0+lENDcUCjE9PY3P5xuKaK7GwITP7XYzMTHB3t6eSCDW7ghvglYYb7Va\nsdvtuN1uLl26xKVLlxgZGSEajTI6OnqqXV0lkvNIpVIhHo+TSqVoNptiLo42BlarnBqm7IqBCZ/T\n6WR8fJzx8XExA1Xr4nF4Bsd3RbPwtAElIyMj/PCHP+RHP/oRXq/3yBcsebd50U5gmC4ayVF3RLVa\nFcPeNeEzm83Y7XbRWOLcCJ+2NZmcnOTjjz/G5XKRTqdJpVJiq/s6reDdbjcLCwvMzs4Kf97MzAx+\nv182IzgjaK4QLXIPzwIe2o9c2+FCy9ZotVpHtrra7Fwt73IY125gwmcymTAajUxOTgIwMjLC1tYW\nm5ubqKpKKpV6LavP4/GwuLjIRx99xLVr17hw4QIGg0HcSYbti5W8Pofb2ms3Re0CkpHc4UNbr2az\nKbrsaNf04UqbcyV8mhjZ7Xai0Sgmkwmv18vIyAh+v59wOCxGz5XLZSqVCr1eD6fTicvlwuv14vP5\nUBQFVVWZmJjg2rVrIidIS36WnB20AeKxWIxarYbVaiUSiRCJRJiamhqKdkaSb2I2m8WoSK05gdZp\nWUtZOzfCp2GxWAgEArhcLkZHR1lcXGR8fJy5uTnW19dZX19nZ2dHhMSDwSATExPMz8+zsLCAwWBA\nVVW8Xi+jo6NEIhGZsnJGqVarxGIx0eXFZrMxPT3NtWvXmJ2dlcI3ZGiCZrPZCAQCeL1e0um0GBXg\n8XiwWCxDJ3pwAsKnmbtaDk+320Wv1+N2u/H5fIRCISYnJ0kmk3Q6HaLRKCMjI0xPTzM9PS2Ez2q1\n4nQ633pWh2R40bZOZrMZv9+P1+vlxo0bXL9+XY4OGFIURcHv97OwsECtVhOlheFwGL/fj91uP5/C\n9zzaPFyz2YzP52N+fl70X+v3+1itVmw2G06n80hnFS2jXwtiSM4e2jkxNTXF3Nyc+JmfnxcpUZLh\nQbP4IpEI7733HiaTCUVRSKVSjI2NEQqFcDgcUvjgmfBpw0YCgcBJv71kiHE4HExNTWE2m7l06RIX\nLlwgEokQjUblzW7IOCxmXq9X+PK63S6pVErs5jwez1AGpmTSm2RoCIfDfP/736dWq+H3+/H7/UNr\nMUh+jTZ4amxsDIPBQL1eF9PUfD7fUAqf8qpcOkVR1NfJtTsrfB1JPhdXm1zjs49c428yfFIskUgk\nA0YKn0QiOXdI4ZNIJOcOKXwSieTcIYVPIpGcO741nUWmEpx95BqffeQaH+WV6SwSiURyFpFbXYlE\ncu6QwieRSM4dUvgkEsm5QwqfRCI5dxx7kwJFUXzAfwFUIAr0gMzX//5QVdXXmzL03d/3d4A/5pmY\n/ztVVf+XQbyP5PTW+Ov31gN3gU1VVX9vUO9z3jnF6/g/Ar8D7Kuq+t4g3gMGHNVVFOVfAlVVVf/4\nBb87tsppRVEMwBrwm0AauA38nqqqG8fx+pKXc1JrfOg1/yfgGmCTwncynOQaK4ryG0CDZ8bLwIRv\n0FtdkTykKMqsoijLiqL8Z0VRHgPjiqIUDv3+DxRF+fdf/z2kKMqfKYrylaIoXyiK8uG3vM9HwBNV\nVfdVVW0Dfwr8kwF8Hsk3Oak1RlGUSeDHwH8YwOeQvJwTW2NVVT8FCt/2uLflpH18i8C/VlX1MhDn\nmdl8GO3f/wb4V6qqfgj8AfAnAIqifKgoyr99weuOAnuH/r3/9f9JTp5BrTHA/wr8j8d/yJLXZJBr\nfCKcdCPSTVVV732Hx/0YWFB+nW7uVhTFrKrqV8BXgzs8yTEwkDVWFOWfALuqqj5SFOXHHLJCJCfO\nO38dn7Tw1Q79vc9Ri/P5gQofqKra+46vGwcmDv177Ov/k5w8g1rjj4HfUxTlvwKsgFNRlP+gqup/\n9+aHKnlDBrXGJ8ZJb3XFXfprh2j+a5+BDvinhx73c+BfiCcpyrVved0vgIuKoowrimIG/mvg/z2+\nw5a8BgNZY1VV/2dVVSdUVZ0B/lvgb6XonRqDuo4Pv/5ALfqTFr7nfQF/BPwt8EuO+uj+EPiBoigP\nvnag/nN4uW/g69D6f8+zL/ox8H+oqro+gOOXfDsDWWPJUDGwNVYU5U+BX/DMkNlVFOWfHfvRI5sU\nSCSSc4is3JBIJOcOKXwSieTcIYVPIpGcO6TwSSSSc8cr8/gURTm3kY/zNGz6tI/htJBrfPZ52Rp/\nawLzeYz6nrf5BHKNzz5yjY8it7oSieTcIYVPIpGcO6TwSSSSc4cUPolEcu6QwieRSM4dJ92WSiKR\nSFBVlX6/T6/Xo9fr0e1+c4SHoigYDAYURaFSqVAul9Hr9RiNxiM/JpMJo9H4Wu8vhU8ikZw4/X6f\nTqdDu92mXq/TaDS+kXJjMBiwWq0YDAa2t7fZ2NjAYrHgcrlwOp04HA5cLhdut3t4he+wwlerVSqV\nCnq9HoPBgMlkwmKxYDQa0el06PX6t34v7f263S6dTkfcHXS6Z7v785bHJZGcJprItdttOp0OzWaT\nWq1GrVajXC5TLpe/IXxGoxGXy4XZbObx48c8evQIq9WKx+PB7XbjcrkIhULMz8/jdDpf63hOTPj6\n/T7tdptarcbDhw95+PCh+BDhcJjR0VECgQBWq/VYhK/b7dJutykWixQKBdxuN36/H4vFIsRPIpGc\nDOVymWw2SyaTOfJnNpulVCpRKpXo9/tHnmMymfB4PNhsNvb399nb20On02EymTCZTJjNZmZmZvjd\n3/1dJicnX+t4Bi58mop3u12q1SrpdJp79+7xN3/zN7jdbkZGRlhcXMRgMGC321/bZH3Ze9Xrdcrl\nMolEgng8ztjYGDabDZPJhKIo0uI7IbQ10az9fr8vLHKj0YjB8OtTUK7Ju422rqqqirXW1j2VSrGz\ns8POzg7b29vs7u4Sj8dJJBKUSiWKxeI3LD5N+JxOJ+VymUqlQrfbpdfriccuLS1x5cqV1z7WgQuf\ntt1Mp9N89dVX3Llzh5WVFXZ3dwmHw1itVlqtFiaTCYfD8VbCp33JmUyGe/fu8fjxY/L5PLlcjvff\nfx+Hw4HBYBACKBk82ppks1l2d3dJpVI0Gg36/T4XL17k4sWL4mYkebfpdrs0m03K5TIHBwekUinS\n6TSpVIpcLkculyOfz5PP5ykWi5RKJSqVCs1m84Uldb1ej3q9TrfbpdVq0e12xY3zbTkR4et0OqRS\nKT799FP+/M//nHq9Tq1WQ1EUXC4XrVYLs9mMw+F4qwtAVVU6nQ6ZTIbPPvuMv/qrv6Jer1Ov19Hr\n9SwsLOD1eoWpLBk8vV6PdrvNwcEBd+7c4cmTJ+TzeXHnnp2dxWg0SuE7A3Q6HWq1GgcHBzx69IjH\njx+zvLzMkydPqNfrtNttIV7aj2Yhvoher0etVqNer7/ycW/CwIRPO7FTqRRbW1vcv3+fp0+fUiwW\ncblchMNhlpaWuH79OlevXsXn8721761cLrO/v8+jR4/Y2toim80SDAaZmppiamoKn893LD5Eyavp\n9Xpi+5JIJEgkEmxsbLC8vMzu7i7VahW9Xk82mxU3PSl+7z6ahZbL5djY2ODu3bvE43Gy2Sztdvs7\nW2sGgwGz2Xzk52WMjo6+dmADBih8vV6PVqtFPB7n888/58svv2Rzc5NOp4Pf72dhYYHvf//7/MZv\n/AYTExNvdPDPUywWWV1d5f79++zu7lKv14lEInzve9/j8uXLhMNhHA6HFL4B0+/3yWQy4oZ39+5d\nYrEYmUyGUqlEr9fDbrdTKBRoNpvYbLYjvj7Ju0m326XRaAjhe/jwIc1mk1ar9VoWm9FoxOl04na7\n8Xg8uFyulz52cnLylb9/GQM721qtFqVSiUQiwdraGqurq2SzWQCi0SjvvfceS0tLTE9P4/P53uq9\ntFB5KpXiyZMnrKysUK/X8fl8TE1NcfXqVSYnJ3E6nW/lQ5S8Gs2fV6vViMVi3L59mwcPHvDo0SPS\n6TT1ep1OpwM8c0skEglWVlaYmpoiEolgs9nQ6XQy6j6EaFvTVqtFuVymVqthsVgwm81YrVYsFotI\nIet0OiK4qCgKRqNR/M5oNGK1WoWVr0VnNfeTyWTCbreL/DwtuPEygsEg4XD4tT/PwISv0WiQz+c5\nODggHo9zcHBAs9nEZDIxNjbGBx98wNTUFBbL8/OHXx/Nobq3t8fy8jIbGxvY7Xbm5uaYn59ncXGR\ncDgs/XoDpt/v02w2KRaLrK2t8emnn7K7uytEr9f79VzpbrfL9vY2//AP/0CtVsNsNoucTil8w4fm\nq83n82xsbLC/v4/f7ycQCBAKhQiHwyiKIvJwjUajWFO9Xi+CnE6nk1AoRCAQwOVy4XK58Pl8eL1e\nPB4PHo8Hu92OxWLBYrEIUX0ZFouFYDD42p/nWIXvcOJwpVLh4OCAZDJJJpOhXq9jt9uJRCJMT0+z\nsLCAz+d75f79295LK3fJZDLs7u6yurrK5uYmmUyGYDDI7Owsk5OTjI6OvnXEWPLtdDodCoUC8Xic\nzc1NlpeXKRaLNJtNkaOl+fG63S77+/vcunULRVEwmUxMTEyIO7xmTWhI/9/poF3TtVqNdDpNLBYT\nPvTZ2Vl6vR5Wq5VAIIBer8diseDxeBgbG2NhYUH46DqdDq1WS/wuEong9Xrxer0EAgGCwSA+n++I\nH95gMIif4+bYX1HbdmazWba3t0kkEtTrdRwOB0tLS1y9epXFxUWx7XzTE1pVVer1OtVqlUePHvGr\nX/2K+/fvk0qlMJlMhEIhZmdnCQaDmM1m9Hq9vHgGTLPZJBaL8eDBA/b29sTW9kW+nX6/TzabFVn8\nOzs7zMzMMDc3x8zMDBMTE0SjUXQ6nVy3U0RzX8Tjcb744gsePHjA9vY2uVwOs9nMxMSEEEez2YzP\n52Nubo5ut8vU1BR2ux273U6z2aRerwuRdLvdwqKz2WxYrVbxo9XnDtLtcewWX7PZpFKpkEwm2dra\nIh6P02w2cTqdXLp0id/8zd9kfn7+WJKVtQjSkydP+Lu/+zs2NzdpNpuEw2Gi0egR4ZPO88Ghnfj1\nep2dnR3u378vhK/b7YqEcU3AtF1BoVAQFuLdu3eZm5vjgw8+oNFoYLFYCIVCADIYdcIcvlF1Oh0a\njQa7u7t89tln/OpXvyKfz9Pr9ZifnxePVRRFWHd2u51AIMB7772H0+nE5XIJI0Wn0+FwOLBYLKda\nSHCsatDtdtnZ2WFlZYX79+9z//59kskker2ecDjM5OQks7Oz+P3+t1byfr8vKjOy2SyVSgWj0Ugw\nGGR+fp5Lly6xsLBAMBiUPqMBoyWY5nI5dnZ2WF1dJZ1O0+/3sVgs2Gw24czu9/sicVWj1+vR6XTI\n5XKsra1hsVgYGRlhfn4ek8kkhe8U0G5msViM1dVVbt26JQyLkZERwuEwly5dYmpqCr/ff8Sw0Ov1\nYruqCZwWtNCCHadtxR+78MViMT777DMePXrEkydP6Ha7+Hw+otEoU1NTzM3NYTabj0X4NMsym81S\nLpcxGAyMjY2xtLQkhE+v10vhGzBaiaAmfCsrKzSbTXq9nnBeO51ObDabSGI9LHxaHXcul6PVaqHX\n67l69SrNZlPUZp72hXLe0HzosViMX/ziF9y7d4+NjQ16vR7RaJSbN29y6dIlJicnv+E/1+l0Ijih\nrdvh8sRhWMtj3+pqZSutVot2u41Op8NqteJwOESp2JvcwbXtUaPRIJPJkEwmefjwIQ8ePGBra4tG\no8HY2BjXr1/no48+YmxsTEZxT4hOp0O5XCaXy1EqlWg0GpjNZuHeuHLlCoFAAKPRSL1eZ3Nzk52d\nHTKZDJlMhlarJc6XarVKMpnk7t27OBwOFhYWhJNc3sQGy+F0FK3c7OHDh6ysrBCPx2m1Wni9XmZn\nZ3nvvfeYmJjAZrMd6XoEvHQLOwyCpzEQx9fhD6iZu4dF701OXs3JWqlUWF9fF6L34MEDMpkMjUaD\nQCDAzZs3+fjjj3E4HMf5kSSvQOuCk8vlqNVqwsoPhUK8//77/PSnP2VkZARVVSkWizx9+pTV1VUe\nP37M48ePKRQKdDodkfSeSqW4ffs2tVqNTqfD6OiozO87ATTDpdFoiOjtgwcPePr0KblcDp1OJ4Tv\n+vXruN3uY9m9nQYD9/h3u10RCl9fX8fn84ncHofDgdPpfGXgQbMGtPreg4MDHj58KELqe3t7KIqC\n2+0mGo0K/4Pk5NAEq9ls0m63URQFv9/P4uIii4uLzM/PE4lExI1Lq8tuNBokEglarZYQzF6vR7PZ\nJA3VyNgAABNXSURBVJ/Pk0gkKJfLR/L/JIOj2+1SLpdJp9Osra3x1Vdfsbm5SbVaxel0Mjk5ybVr\n11hYWCAcDmM0Gt/ZbImBC1+j0SCZTIqTNx6Pi4ztiYkJZmZmXmmd5fN50b8rnU6TSCTY3t4mFotR\nqVSEpTcyMsLo6Ch2u33QH0nyHIdzKlVVRa/XMzIywrVr15icnBS+Hr1ej91uZ3x8HKvVSiwWw+v1\nUiqVjrg/tFQG7Qb5rl5c7xrtdpt0Os3GxgaPHj3i9u3boq56bm6OTz75hA8//FD46d/lNTlW4dP8\neV6vF6fTidlsFh1Wtc6riURClKbMzs6Sz+dfWWuXyWREixvtz0wmQ6FQEFniWu3v9PS03OKeAp1O\nR3TV1vy6NpsNv98vaqM1v4+W8mAymXC73SJn6/BFpDnHtQx+g8Eg8/lOgMP5t9vb22z9/+2dSWxb\nWXaG/yvOk0hRpDhIpElqpFy2ZE12OQVkU73IIgnSm95k040A2SSbIEGyyr4X6QABEgRIB51FFtl0\nkGw7ExAkgFEFuCwPkSmKGkhKFEVxEh8HcbpZSPcUZatcLhVJUdL9AEKSRT0++j7+795zz/nP9jb0\nej1GRkbg8/mwtLSElZUVmEymG58e1tWzV6lU8Hg8WFhYQLFYJKOA09NTyuo/PT0lwcrlcojFYh+s\n3hD5P8KmWvjzM8YodhgMBrGysoL5+XnYbLZuviXJR1Aul5FMJrGzs0NOuvl8Hnt7e/B4PKjX6+/9\nTbvdJmPak5OTC81m1Go1rFYr3G43rFYrtFotCaSkdzSbTRQKBRweHqJUKoFzDr1eD7vdjtHRUVit\n1ltjKNH1GZ/L5cLQ0BCZE1SrVSiKgmq1StnbYlm0t7d3IUP7sgtb/E50YhKlT2J2abPZEAgE8OjR\nI8zOzl7JqUHy/ajVajg6OkIqlYKiKGi32ygUCtjb28Pk5CTq9Totg4U1UbVaRbFYRCaTQalUQqvV\nAmOMlspGo5Fsx+VStz+IyUkqlSLh0+l01NxHFAIwxmi8bqqbedeFTyw1l5eXodfrcXBwgHw+j0Kh\nQP0vhEebSGy0Wq1wOp2XujDY7XY4HA7aWk8mkwDO4kAWiwVutxtOpxMjIyPfuxpEcjVMJhMmJiYQ\nCARwdHSE/f19ms1lMhlks1kAZ7P3UqlE18DGxgbK5TLZ0A8NDVE6VDKZhMFggM/nQzgcxsjICJUz\nSXqDcDiKxWLIZrOUK5tMJhGJROD1etFqtajG1mg0UlLyTaOrVxFjDCaTif5DZmdnkc/nKU4Xj8ex\ns7MDADg8PKRUF6fTibm5OXg8nveOGQqFMDs7i42NDRwfH5PwDQ0NwWKxwOPxYGxsjITvJg7CTUds\nWBweHiISiYBzDkVRKB6bzWbRbDaRzWaplDEWi+Ht27col8sAQMInrI+SySROT08RDodxfHxMcWEp\nfL1DpBLFYjGUy2USvlqtBoPBAKvVilarhUAggHv37sHpdMJoNF73aV+JrgufEB6DwUDWNCaTCTab\nDQ6HAz6fD36/HwsLC5SVPzo6Cq/XC6vVSssdgYgvxONxCnKLQZiZmcHjx48xNTUFk8l0I/OJbgMG\ng4E65YkNC1HCtr6+Ds45DAYDFEVBoVBAOp3G8fExqtUqnE4nPB4PfD4fFEXB1tYWlbt1Wo21220q\nfZP0BmErpigK6vU67dZzzpHJZPDmzRucnJwgEolQCaqo3BACKEwphM+eeHS68ogeG8KcQLR+7eek\npWe3T5GoLOI1drsdPp8P9Xod1WoV1WoVwNnMTQjkZcvURqOBRqNBcR61Wg2z2QyXy4VwOIzPPvsM\nXq/3xt55bgPCUMDr9cJms0Gj0eD09BTVahXPnz9HNBqFSqVCs9mktp+tVotueCsrK3jy5AnS6TQY\nY6hWqyiVSqhUKkgmk1hfX4fZbIbf75cx3B4iSgc7m3t3GkrUajXs7OxQHub8/Dzm5+fhcrngcDjA\nGKOZoogLCo89MSmpVCooFApot9twOp1wOBy0YXIrhE+8UZGfZTAYrnQcYWIqunPpdDr4fD6qxRUf\nBhnbuz40Gg3djKanp/Hw4UOK4+bzeYrxieeK+l1hEru4uIiFhQXE43Fsb28jnU6j2Wwil8shk8lg\na2sLgUAAJycnNKOUxgXdR6PRwG63w+v1olQqUZNvzjkVEgAgo4FWqwVFUeBwOMhFXYimyWSC2Wwm\ns1GhB9VqlY4rDEk7ffkcDkdXzIm/jYEPmKTTaayvr2NjYwPFYhEmkwkzMzN4+vQpJicnYTabpWvv\nNdMZslhaWgLnHM+ePUOhUKCyMzGD0Ov18Pv9mJ6exsrKClZXV+HxeOB0OlGr1XDv3j0cHBygVCrh\n+PgYhUIB8XgcqVQKuVwOIyMjsm9KjzAYDJQhEY1GqZrmXURpm9jF7zSNFc9Xq9W0hO2smRdOziqV\niuzl3W433G43lpaWsLa2dneFj3OOer1OQe5Xr15ha2sLpVIJZrMZXq8Xc3NzcLvdlOAquT5EypGI\nu+p0OlQqFeqnqigK+fI5nU7Mzs5ieXmZHnq9HiqVCg6HA6FQiHqwHh4e0k5jMplEPB6HxWKBSqWS\nsb4eYDAYEAwGsbq6Cp1OR2lJiqJc6JUi+m8Ui0UUi8UrvVZnDb8QPo1Gg/HxcerL0UuTkYFUjFar\nhWw2i3Q6jUgkgo2NDdrls9vtZHkjk1oHC41GQ16Lq6urUKvVSCQS5OyhVqvhdruxtraG5eVljI+P\nk3GFqLeem5sD5xwnJyeUAiWS4b/66itqCC8T1buPWE2JXfpwOIw3b97g1atXyOfzNNMTy97v0+dW\nxBM55zg8PISiKLT0PT09RTAYvFIvjY9lIIWv3W5Ti7rNzU1sbm4ik8lQRyfxkHG9wUKj0dBSlDEG\nh8OBaDSKzc1Nis96PB6srq5icXHxvd284eFhcvFJpVI4ODhANBpFKpVCMpnEy5cvMTw8jFAodMH5\nV9IdxIzP5/NhcnISmUwGNpsNlUoF+/v7JFaiy5pIRhcFCR/bNxc4mzmKjctKpYJMJkMNh/R6PUZH\nR++m8ImSp2w2i0ajQSkTonmQ0+mUeXsDilj2AmcfJq/Xi0ajAbVaDYvFQsuZd+N0wsjAaDTC4/Fg\namqKyhoVRaFNrpOTE5pByjBHdxGVVOLmtbq6CpvNRhsSwg8zl8vRkjeVSiGRSCCfz0NRFNoE+a6I\nnrz5fP7SMsduMpBXjYgtxONxakhjMBjgdrsRCATg9XrhdDpvbLnMbUcI3/DwMLxeL5UZAqCUpMs2\nJzqFz+v1YmpqCrFYDENDQyiXy0ilUheETxxL0l1UKhUsFgvMZjNGR0exuLhIMzlFUZBMJnFwcEDC\n9+LFC3z55ZfY3t6m2PxVqFartKF11WN8LAN51XTWeoo7y8jICKanpxEOh+F0OuWu3gAjBAzAdxIm\ncRPT6XRwu92o1WqIxWKIRqMoFouo1WpUWeB2uzE+Pi69F7tI5yRCfP/uRpJoDm4ymWijo1wuI5vN\nUv5lqVSia8Bms1G6it1uJweYXC73Xu+Vzo2TXjOwwieWurlcDpxz2O12zMzM4P79+3A4HNd9ipIe\notPpqAH89vY2lbjt7e3h6OgIm5ublO8lha+/aLVa2O12SiQXrtpi+ZtIJAB8nevndrsxNTWF6elp\nTE9Po1QqYWNjA5FIBDs7OxeEr58MlPA1Gg1qRC5SIYQFlcViIbPRy8wMJLcH4efHGMO9e/eo8VAq\nlUI+n0ckEqEWhoFAgHLGZNij9wivxE6cTif8fj8SicSFQgWxgSGs6UTljujJ866ztkqlglarfa+H\nRy8YKOGr1WpIJBKIRCJIJBIolUpoNpvQarVU9jY6OiqbCN0R1Go1xsfH8ejRI2QyGWxsbCCXy2Fj\nYwMAMDk5ifv378NsNsvUpmtE5NaOjY2R8ImmRSJVRVEUZLNZVCoVbG9v4+DgAIqiXDiOSFUSrSl7\nycAJXzKZxOvXr3FwcEApEGazmYLlIrYgiqc55x/085PcPDrjSyKeG4vFMD4+jnK5jOPjY8RiMWxv\nb2Nvbw9erxcGg4H+Tl4H/cVoNGJsbAwul4tckoTjukhyrtfr5NB9eHhIic9iSazVauFwOChjo9fV\nGwMnfMKNI51Og3OO4eFhTExMwO12w2AwkOg1m000Gg00m03odDrK/pfcHoTNmUqlwuTkJJaXl6FS\nqRCJRFAulxGNRvHs2TMsLS1hdHT0wqaKpH/o9XoqPQsGgxSqOj4+pueIRmGimRTw9Q7/6OgoHA4H\nHjx4gE8//ZT8F3vJQAnf6ekpUqkUNjc3cXx8jHa7DZPJBLfbTX1Z6/U6arUadfSq1+uwWCyX5oVJ\nbjYi1mc0GhEKhVAsFskz7uDgALFYjKpF7t+/T7EhOePrL1qtFsPDw3C5XJicnMTR0RG5OYtVWaVS\nQaVSAfD1rr9KpaI0tVAohIcPH2JlZQUTExM9L04YKOG7DJFQWalUkEgkyKoonU6TOeXMzAzm5+dl\n7O8WI/q5ptNpvH37FrlcDoVCAVtbW+QCI1qWSsOK/iI64jmdTiwuLpLVnHBvKZfLtPQV6TEWi4W8\nGB88eIAHDx5gZmYGIyMjfYnX3gjhEz5f8Xgc8Xgc6+vriEQisNvtsNvtUKlUCAaDsn7zFmOz2aBW\nq5FOp+FyuRCLxaiOd39/H7lc7oKxpaR/iBmciM1ZLBZUq1VyX89kMiiXy2i1WrSBIcwq5ufn8fjx\nYzx58oR8+fpx4xp44SsWi9jd3YWiKIjH49BqtTg5OYHJZILX60UoFILX65VuHbcc4fnn9/vx9OlT\nqFQqvHjxAru7u9jf38fLly/BOYfZbO6LrZHka8TsTKvVwmw2Y3x8nNpQismK6LsjGpP7/X56hEIh\nWCyWvlbhDLzw5XI5lMtl7O7ukomlaGwTDofx6NEj2tWT3F7ETMDv90OtVmN4eBj5fJ6Wus+fP4fZ\nbEYgEKA6YUl/ETl+Y2NjMBqNmJ6eJpMRseHhcrmwtLSEqakpWK1WalnZ7/DEQAmfcO+YmZmBXq9H\nu90m3y6TyURxgVAohKmpKczNzSEQCNDmhuT2IlKWhNu2oijU40NRFEQiEQSDQRQKBVitVmg0GlnH\n22eEeAn3JGE5bzQayWPR4XAgHA5jYmKC+nFcBwN1ZZhMJszNzaHRaGB9fR3AWXKkw+HAxMQEQqEQ\nxsfHKbZnt9up4bQMaN8N1Go1fahEve7p6Sl2d3eRSCSQyWRgt9v7vnSSvI+I+xmNRqrW0Ol0ZD11\nnVkYA3VlCOtrYU4pXD5cLheCwSBmZ2fJvFKInUxfuFuINAir1YpgMIhPPvkE0WgU6XQauVwOuVwO\npVIJer1ehj+uGTFDH8QGUQMlfGq1mraz9Xo9gsHghfaUdrudylmk4N1tLBYLFhYWqLbz8PCQ+vmW\ny+WeJ8BKbjYDJXwajYYCnhMTE9d9OpIBRrQ39Hg8ODo6wuvXr6HX6ynB/d0CeImkk4ESPonkY+ns\nsby6ugqtVktGtS6XS/ZZlnwQ9iGPfMYY/z4NRW4qjDFwzu/EOvqmjnFnw+tGo0EtC0Xai3h8E3KM\nbz8fGmMpfJcgPxS3HznGt58PjbHMAZFIJHcOKXwSieTO8a2bGzJl5PYjx/j2I8f4Ih+M8UkkEslt\nRC51JRLJnUMKn0QiuXNI4ZNIJHeOrlduMMbsAP4DAAfgAdACkDn/eY1z3uz2a3a8tgrAcwAxzvkP\ne/U6d53rGmPG2B8B+Mn56/wt5/yve/E6kmsd4ySALIA2gBrn/NOevE4vNzcYY38OQOGc/+yS33U9\nq5Ix9icAFgAYpfD1h36NMWNsAcA/AHiMsw/FrwD8mHO+143jS76Zfn6OGWNxAPc556VuHfMyer3U\npT10xtgkY+wNY+wfGWOvAfgYY/mO3/+IMfZ359+PMcZ+yRj7gjH2jDG29q0vxNg9AJ8D+EUP3ofk\nm+nXGIcBPOOc189nG/8N4Hd68H4k79O3z/H5a/U8BNfvGN8sgL/gnH8CYB9n0+ZOxM9/BeCnnPM1\nAD8C8PcAwBhbY4z9zTcc+y8B/HH3T1nyHenVGL8C8OuMMRtjzATgNwD4evEGJN9KLz/HbQD/xRj7\nkjH2k+6f+hn9dmeJcc6/+ojnfQ5ghn2ddWlljOk4518A+OLdJzPGfhtAnHP+ijH2OTruUJK+05Mx\n5py/YYz9DGdxpxLOYrnSe+p66MkYn/OEc55ijLkA/Btj7P8458+6cdKd9Fv4yh3ft3Fxxvlua6xV\nzvnHXthPAfyQMfZbAAwALIyxX3DOf3z1U5VckV6NMTjnPwfwcwBgjP0UQPSqJyn5XvRyjFPnX9OM\nsX8FsAag68LX76UuzcTOA6K585jBEC7Ga/4dwB/SH50Ftr8Rzvmfcs79nPMQgN8F8CspetdGT8b4\n/DnO868BAL8J4J+6c8qS70hPxpgxZjoPY+D86w8AvO7miQv6LXzvxgL+DGe7c/8DINHx738A4NcY\nY+vnAdTfA741NiAZDHo5xv9y/tx/BvD7nHOlu6cu+Uh6NcYeAP/LGPsKZ7O8X3LO/7PrZw9ZqyuR\nSO4gsnJDIpHcOaTwSSSSO4cUPolEcueQwieRSO4cUvgkEsmdQwqfRCK5c0jhk0gkdw4pfBKJ5M7x\n/6/Ghib4QzPAAAAAAElFTkSuQmCC\n",
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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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\nvxUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bed5e198>"
+       "<matplotlib.figure.Figure at 0x7f52c1adbb00>"
       ]
      },
      "metadata": {},
@@ -377,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true
    },
@@ -395,7 +424,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -413,7 +442,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -431,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -458,7 +487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -478,7 +507,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": true
    },
@@ -492,7 +521,7 @@
     "        max_pool(kernel=2, stride=2).\\\n",
     "        flatten().\\\n",
     "        fully_connected(size=128, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=10, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -515,7 +544,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -542,7 +571,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
@@ -572,7 +601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
@@ -594,7 +623,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -612,7 +641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -630,7 +659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": true
    },
@@ -650,7 +679,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true
    },
@@ -670,7 +699,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -688,7 +717,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": true
    },
@@ -707,13 +736,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "save_path = save_dir + 'best_validation'"
+    "save_path = os.path.join(save_dir, 'best_validation')"
    ]
   },
   {
@@ -734,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -754,14 +783,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "def init_variables():\n",
-    "    session.run(tf.initialize_all_variables())"
+    "    session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -773,9 +802,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -800,7 +829,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true
    },
@@ -818,7 +847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
@@ -843,7 +872,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -950,7 +979,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -993,7 +1022,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": true
    },
@@ -1044,7 +1073,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": true
    },
@@ -1099,7 +1128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": true
    },
@@ -1120,7 +1149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
@@ -1143,7 +1172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": true
    },
@@ -1170,7 +1199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": true
    },
@@ -1204,7 +1233,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -1247,7 +1276,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": true
    },
@@ -1313,7 +1342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1323,7 +1352,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.2% (1018 / 10000)\n"
+      "Accuracy on Test-Set: 8.5% (849 / 10000)\n"
      ]
     }
    ],
@@ -1340,7 +1369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1350,14 +1379,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean: -0.01520, Stdev: 0.29296\n"
+      "Mean: 0.00880, Stdev: 0.28635\n"
      ]
     },
     {
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bcabed68>"
+       "<matplotlib.figure.Figure at 0x7f52bf215b70>"
       ]
      },
      "metadata": {},
@@ -1381,7 +1410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1391,54 +1420,66 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Iter:    100, Train-Batch Accuracy:  85.9%, Validation Acc:  85.7% *\n",
-      "Iter:    200, Train-Batch Accuracy:  87.5%, Validation Acc:  91.8% *\n",
-      "Iter:    300, Train-Batch Accuracy:  93.8%, Validation Acc:  93.4% *\n",
-      "Iter:    400, Train-Batch Accuracy:  96.9%, Validation Acc:  94.1% *\n",
-      "Iter:    500, Train-Batch Accuracy:  98.4%, Validation Acc:  94.3% *\n",
-      "Iter:    600, Train-Batch Accuracy:  96.9%, Validation Acc:  95.4% *\n",
-      "Iter:    700, Train-Batch Accuracy:  96.9%, Validation Acc:  95.7% *\n",
-      "Iter:    800, Train-Batch Accuracy:  98.4%, Validation Acc:  96.4% *\n",
-      "Iter:    900, Train-Batch Accuracy:  95.3%, Validation Acc:  96.4% *\n",
-      "Iter:   1000, Train-Batch Accuracy: 100.0%, Validation Acc:  97.0% *\n",
-      "Iter:   1100, Train-Batch Accuracy:  95.3%, Validation Acc:  97.0% *\n",
-      "Iter:   1200, Train-Batch Accuracy:  93.8%, Validation Acc:  97.1% *\n",
-      "Iter:   1300, Train-Batch Accuracy:  92.2%, Validation Acc:  96.9% \n",
-      "Iter:   1400, Train-Batch Accuracy: 100.0%, Validation Acc:  97.5% *\n",
-      "Iter:   1500, Train-Batch Accuracy:  96.9%, Validation Acc:  97.3% \n",
-      "Iter:   1600, Train-Batch Accuracy: 100.0%, Validation Acc:  97.5% *\n",
-      "Iter:   1700, Train-Batch Accuracy:  93.8%, Validation Acc:  97.8% *\n",
-      "Iter:   1800, Train-Batch Accuracy:  95.3%, Validation Acc:  97.5% \n",
-      "Iter:   1900, Train-Batch Accuracy:  98.4%, Validation Acc:  97.7% \n",
-      "Iter:   2000, Train-Batch Accuracy: 100.0%, Validation Acc:  97.6% \n",
-      "Iter:   2100, Train-Batch Accuracy: 100.0%, Validation Acc:  97.7% \n",
-      "Iter:   2200, Train-Batch Accuracy:  96.9%, Validation Acc:  97.9% *\n",
-      "Iter:   2300, Train-Batch Accuracy:  96.9%, Validation Acc:  98.1% *\n",
-      "Iter:   2400, Train-Batch Accuracy:  98.4%, Validation Acc:  97.9% \n",
-      "Iter:   2500, Train-Batch Accuracy:  93.8%, Validation Acc:  98.0% \n",
-      "Iter:   2600, Train-Batch Accuracy:  96.9%, Validation Acc:  97.9% \n",
-      "Iter:   2700, Train-Batch Accuracy: 100.0%, Validation Acc:  98.1% *\n",
-      "Iter:   2800, Train-Batch Accuracy:  98.4%, Validation Acc:  98.1% \n",
-      "Iter:   2900, Train-Batch Accuracy:  95.3%, Validation Acc:  97.9% \n",
-      "Iter:   3000, Train-Batch Accuracy:  98.4%, Validation Acc:  98.3% *\n",
+      "Iter:    100, Train-Batch Accuracy:  84.4%, Validation Acc:  85.2% *\n",
+      "Iter:    200, Train-Batch Accuracy:  92.2%, Validation Acc:  91.5% *\n",
+      "Iter:    300, Train-Batch Accuracy:  95.3%, Validation Acc:  93.7% *\n",
+      "Iter:    400, Train-Batch Accuracy:  92.2%, Validation Acc:  94.3% *\n",
+      "Iter:    500, Train-Batch Accuracy:  98.4%, Validation Acc:  94.7% *\n",
+      "Iter:    600, Train-Batch Accuracy:  93.8%, Validation Acc:  94.7% \n",
+      "Iter:    700, Train-Batch Accuracy:  98.4%, Validation Acc:  95.6% *\n",
+      "Iter:    800, Train-Batch Accuracy: 100.0%, Validation Acc:  96.3% *\n",
+      "Iter:    900, Train-Batch Accuracy:  98.4%, Validation Acc:  96.4% *\n",
+      "Iter:   1000, Train-Batch Accuracy: 100.0%, Validation Acc:  96.9% *\n",
+      "Iter:   1100, Train-Batch Accuracy:  96.9%, Validation Acc:  97.0% *\n",
+      "Iter:   1200, Train-Batch Accuracy:  93.8%, Validation Acc:  97.0% *\n",
+      "Iter:   1300, Train-Batch Accuracy:  92.2%, Validation Acc:  97.2% *\n",
+      "Iter:   1400, Train-Batch Accuracy: 100.0%, Validation Acc:  97.3% *\n",
+      "Iter:   1500, Train-Batch Accuracy:  96.9%, Validation Acc:  97.4% *\n",
+      "Iter:   1600, Train-Batch Accuracy: 100.0%, Validation Acc:  97.7% *\n",
+      "Iter:   1700, Train-Batch Accuracy: 100.0%, Validation Acc:  97.8% *\n",
+      "Iter:   1800, Train-Batch Accuracy:  98.4%, Validation Acc:  97.7% \n",
+      "Iter:   1900, Train-Batch Accuracy:  98.4%, Validation Acc:  98.1% *\n",
+      "Iter:   2000, Train-Batch Accuracy:  95.3%, Validation Acc:  98.0% \n",
+      "Iter:   2100, Train-Batch Accuracy:  98.4%, Validation Acc:  97.9% \n",
+      "Iter:   2200, Train-Batch Accuracy: 100.0%, Validation Acc:  98.0% \n",
+      "Iter:   2300, Train-Batch Accuracy:  96.9%, Validation Acc:  98.1% \n",
+      "Iter:   2400, Train-Batch Accuracy:  93.8%, Validation Acc:  98.1% \n",
+      "Iter:   2500, Train-Batch Accuracy:  98.4%, Validation Acc:  98.2% *\n",
+      "Iter:   2600, Train-Batch Accuracy:  98.4%, Validation Acc:  98.0% \n",
+      "Iter:   2700, Train-Batch Accuracy:  98.4%, Validation Acc:  98.0% \n",
+      "Iter:   2800, Train-Batch Accuracy:  96.9%, Validation Acc:  98.1% \n",
+      "Iter:   2900, Train-Batch Accuracy:  96.9%, Validation Acc:  98.2% \n",
+      "Iter:   3000, Train-Batch Accuracy:  98.4%, Validation Acc:  98.2% \n",
       "Iter:   3100, Train-Batch Accuracy: 100.0%, Validation Acc:  98.1% \n",
-      "Iter:   3200, Train-Batch Accuracy:  98.4%, Validation Acc:  98.1% \n",
-      "Iter:   3300, Train-Batch Accuracy: 100.0%, Validation Acc:  98.3% \n",
-      "Iter:   3400, Train-Batch Accuracy:  98.4%, Validation Acc:  98.0% \n",
-      "Iter:   3500, Train-Batch Accuracy:  96.9%, Validation Acc:  98.2% \n",
-      "Iter:   3600, Train-Batch Accuracy:  98.4%, Validation Acc:  98.5% *\n",
-      "Iter:   3700, Train-Batch Accuracy:  95.3%, Validation Acc:  98.2% \n",
-      "Iter:   3800, Train-Batch Accuracy:  98.4%, Validation Acc:  98.1% \n",
-      "Iter:   3900, Train-Batch Accuracy:  98.4%, Validation Acc:  97.9% \n",
-      "Iter:   4000, Train-Batch Accuracy:  95.3%, Validation Acc:  98.4% \n",
-      "Iter:   4100, Train-Batch Accuracy:  96.9%, Validation Acc:  98.3% \n",
-      "Iter:   4200, Train-Batch Accuracy:  98.4%, Validation Acc:  98.4% \n",
-      "Iter:   4300, Train-Batch Accuracy:  98.4%, Validation Acc:  98.3% \n",
-      "Iter:   4400, Train-Batch Accuracy: 100.0%, Validation Acc:  98.4% \n",
-      "Iter:   4500, Train-Batch Accuracy:  96.9%, Validation Acc:  98.3% \n",
-      "Iter:   4600, Train-Batch Accuracy:  96.9%, Validation Acc:  98.4% \n",
+      "Iter:   3200, Train-Batch Accuracy: 100.0%, Validation Acc:  98.3% *\n",
+      "Iter:   3300, Train-Batch Accuracy:  98.4%, Validation Acc:  98.4% *\n",
+      "Iter:   3400, Train-Batch Accuracy:  95.3%, Validation Acc:  98.0% \n",
+      "Iter:   3500, Train-Batch Accuracy:  98.4%, Validation Acc:  98.3% \n",
+      "Iter:   3600, Train-Batch Accuracy: 100.0%, Validation Acc:  98.5% *\n",
+      "Iter:   3700, Train-Batch Accuracy:  98.4%, Validation Acc:  98.3% \n",
+      "Iter:   3800, Train-Batch Accuracy:  96.9%, Validation Acc:  98.1% \n",
+      "Iter:   3900, Train-Batch Accuracy:  96.9%, Validation Acc:  98.5% \n",
+      "Iter:   4000, Train-Batch Accuracy: 100.0%, Validation Acc:  98.4% \n",
+      "Iter:   4100, Train-Batch Accuracy: 100.0%, Validation Acc:  98.5% \n",
+      "Iter:   4200, Train-Batch Accuracy: 100.0%, Validation Acc:  98.3% \n",
+      "Iter:   4300, Train-Batch Accuracy: 100.0%, Validation Acc:  98.6% *\n",
+      "Iter:   4400, Train-Batch Accuracy:  96.9%, Validation Acc:  98.4% \n",
+      "Iter:   4500, Train-Batch Accuracy:  98.4%, Validation Acc:  98.5% \n",
+      "Iter:   4600, Train-Batch Accuracy:  98.4%, Validation Acc:  98.5% \n",
+      "Iter:   4700, Train-Batch Accuracy:  98.4%, Validation Acc:  98.4% \n",
+      "Iter:   4800, Train-Batch Accuracy: 100.0%, Validation Acc:  98.8% *\n",
+      "Iter:   4900, Train-Batch Accuracy: 100.0%, Validation Acc:  98.8% \n",
+      "Iter:   5000, Train-Batch Accuracy:  98.4%, Validation Acc:  98.6% \n",
+      "Iter:   5100, Train-Batch Accuracy:  98.4%, Validation Acc:  98.6% \n",
+      "Iter:   5200, Train-Batch Accuracy: 100.0%, Validation Acc:  98.6% \n",
+      "Iter:   5300, Train-Batch Accuracy:  96.9%, Validation Acc:  98.5% \n",
+      "Iter:   5400, Train-Batch Accuracy:  98.4%, Validation Acc:  98.7% \n",
+      "Iter:   5500, Train-Batch Accuracy:  98.4%, Validation Acc:  98.6% \n",
+      "Iter:   5600, Train-Batch Accuracy: 100.0%, Validation Acc:  98.4% \n",
+      "Iter:   5700, Train-Batch Accuracy: 100.0%, Validation Acc:  98.6% \n",
+      "Iter:   5800, Train-Batch Accuracy: 100.0%, Validation Acc:  98.7% \n",
       "No improvement found in a while, stopping optimization.\n",
-      "Time usage: 0:06:30\n"
+      "Time usage: 0:00:28\n"
      ]
     }
    ],
@@ -1448,7 +1489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1458,15 +1499,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.6% (9856 / 10000)\n",
+      "Accuracy on Test-Set: 98.4% (9842 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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nfwH8iqZpd4QQg8AfAtMHH/rf0DTtZz7xumEgI4T4LWAauAP8A03TascZlBBi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\ninOgRFOhUCjOgRJNhUKhOAf/H8Q1+obp23JaAAAAAElFTkSuQmCC\n",
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MFnM6na81ItbPsVMURbxuLpcTDca9Xg8WiwU+nw+z2WxpsfFOn7kJ+tMiDS4olUool8uQ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\ncvE0MzNr6Df4jzw5qjDYsgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bcaa0550>"
+       "<matplotlib.figure.Figure at 0x7f52bf26c6d8>"
       ]
      },
      "metadata": {},
@@ -1477,23 +1518,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 976    0    0    0    0    0    1    1    2    0]\n",
-      " [   0 1129    1    0    0    1    2    1    1    0]\n",
-      " [   5    2  999    4    1    0    1    9   11    0]\n",
-      " [   0    0    0 1005    0    0    0    2    2    1]\n",
-      " [   0    0    2    0  976    0    0    1    3    0]\n",
-      " [   2    0    0    3    0  884    3    0    0    0]\n",
-      " [   5    2    0    1    2    4  940    0    4    0]\n",
-      " [   0    1    5    4    1    0    0 1016    1    0]\n",
-      " [   4    0    2    0    2    1    1    3  959    2]\n",
-      " [   4    4    0    6   11    3    0    6    3  972]]\n"
+      "[[ 974    0    0    0    0    1    2    0    2    1]\n",
+      " [   0 1127    2    2    0    0    1    0    3    0]\n",
+      " [   4    4 1012    4    1    0    0    3    4    0]\n",
+      " [   0    0    1 1005    0    2    0    0    2    0]\n",
+      " [   1    0    1    0  961    0    2    0    3   14]\n",
+      " [   2    0    1    6    0  880    1    0    1    1]\n",
+      " [   4    2    0    1    3    4  942    0    2    0]\n",
+      " [   1    1    8    6    1    0    0  994    1   16]\n",
+      " [   6    0    1    4    1    1    1    2  952    6]\n",
+      " [   3    3    0    3    2    2    0    0    1  995]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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6fS0zs67ktExnBHdgL+AXpDe0Avhutv8y4Ph2NcrMupSDe2cE94j4FZ4KwcyK4uDeGcHd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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bcaa03c8>"
+       "<matplotlib.figure.Figure at 0x7f52bf9ba6a0>"
       ]
      },
      "metadata": {},
@@ -1518,7 +1559,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
@@ -1527,14 +1568,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean: 0.00415, Stdev: 0.30706\n"
+      "Mean: 0.02895, Stdev: 0.29949\n"
      ]
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUQAAADtCAYAAADHjgxUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA2CXaLpnSFEAAAAASUVORK5CYII=\n",
+      "image/png": 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9QK33HlSaLl/9qrqad9CeXJVi0Ny5KUJS/rbb7MwDc0db54s7N+ppe0rlmPW5qXqryrvy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\nlCEAIDzKEAAQHmUIAAiPMgQAhPe/vse2sqTFTz0AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bc442cf8>"
+       "<matplotlib.figure.Figure at 0x7f52bf26c048>"
       ]
      },
      "metadata": {},
@@ -1556,9 +1597,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -1574,7 +1615,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": false
    },
@@ -1583,7 +1624,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 4.0% (397 / 10000)\n"
+      "Accuracy on Test-Set: 13.4% (1341 / 10000)\n"
      ]
     }
    ],
@@ -1600,7 +1641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1610,14 +1651,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean: -0.02354, Stdev: 0.27403\n"
+      "Mean: -0.01086, Stdev: 0.28023\n"
      ]
     },
     {
      "data": {
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meJZ3X1xpfptmZ+lK3/f43QEnqK2Pd+XR555+ONWsI9p/bWee+KR/n6EkPX1D1TpfLpek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\nwqMMAQDhUYYAgPAoQwBAeP8Pbzq89iAmiMgAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bc5b4358>"
+       "<matplotlib.figure.Figure at 0x7f52bf156550>"
       ]
      },
      "metadata": {},
@@ -1639,7 +1680,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": true
    },
@@ -1659,7 +1700,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1669,15 +1710,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.5% (9850 / 10000)\n",
+      "Accuracy on Test-Set: 98.3% (9826 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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0TZsCfhb48rHX+ydCiD/3OaeKApvHHm8f/e514qxs/Aj4qhDCJ4RwAn8e6D/p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\nNy3jYX1hYgAAAABJRU5ErkJggg==\n",
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TYLVaEQgEsLGxge3tbUQiETgcDmiahlKphOPjY2QyGW6vNplMsLe3h93dXbjdbvbpy2Il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\ngg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f26116c3470>"
+       "<matplotlib.figure.Figure at 0x7f52bf341a90>"
       ]
      },
      "metadata": {},
@@ -1688,23 +1729,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 977    0    0    0    0    0    0    1    2    0]\n",
-      " [   0 1132    2    0    0    0    0    0    1    0]\n",
-      " [   3    4 1020    0    0    0    0    2    3    0]\n",
-      " [   0    0    2  999    0    1    0    5    2    1]\n",
-      " [   1    0    2    0  972    0    0    1    3    3]\n",
-      " [   2    0    0    7    0  878    3    1    1    0]\n",
-      " [   8    3    0    1    2    4  938    0    2    0]\n",
-      " [   1    1   11    3    1    0    0 1007    1    3]\n",
-      " [   5    1    5    2    2    2    1    3  950    3]\n",
-      " [   4    7    1    5    9    0    0    6    0  977]]\n"
+      "[[ 973    0    0    0    0    0    2    0    3    2]\n",
+      " [   0 1124    2    2    0    0    3    0    4    0]\n",
+      " [   2    1 1027    0    0    0    0    1    1    0]\n",
+      " [   0    0    1 1005    0    2    0    0    2    0]\n",
+      " [   0    0    3    0  968    0    1    0    3    7]\n",
+      " [   2    0    1    9    0  871    3    0    3    3]\n",
+      " [   4    2    1    0    3    3  939    0    6    0]\n",
+      " [   1    3   19   11    2    0    0  972    2   18]\n",
+      " [   6    0    3    5    1    0    1    2  951    5]\n",
+      " [   3    3    0    1    4    1    0    0    1  996]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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zztfTxNwy/Y2WiYhlNARgScuAFyNijqQdgGNIQx1fBHYHzgd+HRG1lcDvzMq4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\n275e8Q1VB3crTURcQUrLfIb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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bca630b8>"
+       "<matplotlib.figure.Figure at 0x7f52bf17cda0>"
       ]
      },
      "metadata": {},
@@ -1725,7 +1766,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1735,14 +1776,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean: 0.00300, Stdev: 0.30551\n"
+      "Mean: 0.02792, Stdev: 0.29822\n"
      ]
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUQAAADtCAYAAADHjgxUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": 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2ti/YmUcfTTVK46te9wJ1dekGVYiqiy7SweYdtCcMSDFo3rwUISl/22125oF551nni2rW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\nrkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f25bab855f8>"
+       "<matplotlib.figure.Figure at 0x7f52bf8dc358>"
       ]
      },
      "metadata": {},
@@ -1769,7 +1810,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "collapsed": false
    },
@@ -1832,10 +1873,11 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/05_Ensemble_Learning.ipynb b/05_Ensemble_Learning.ipynb
index 123070f..60d1ccf 100644
--- a/05_Ensemble_Learning.ipynb
+++ b/05_Ensemble_Learning.ipynb
@@ -105,13 +105,14 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.10.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -123,6 +124,35 @@
     "tf.__version__"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "PrettyTensor version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -139,7 +169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -169,7 +199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -203,7 +233,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -224,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -243,7 +273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -271,7 +301,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -283,7 +313,7 @@
        "60000"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -302,7 +332,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
@@ -313,7 +343,7 @@
        "48000"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -332,7 +362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -343,7 +373,7 @@
        "12000"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -362,7 +392,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -404,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -442,7 +472,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -503,16 +533,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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/6B9RqVTo9/v4/X6sVuvZFr5ut0u32yUej/PgwQNu375NPB4/zUOSHAP9fp9S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\n/6/Ghib4QzPAAAAAAElFTkSuQmCC\n",
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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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\nvxUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ffacb9a2e80>"
+       "<matplotlib.figure.Figure at 0x7fdddedc56d8>"
       ]
      },
      "metadata": {},
@@ -571,7 +601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -589,7 +619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -607,7 +637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -625,7 +655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -652,7 +682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -672,7 +702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": true
    },
@@ -686,7 +716,7 @@
     "        max_pool(kernel=2, stride=2).\\\n",
     "        flatten().\\\n",
     "        fully_connected(size=128, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=10, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -709,7 +739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
@@ -731,7 +761,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -749,7 +779,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": true
    },
@@ -767,7 +797,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": true
    },
@@ -789,7 +819,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -807,7 +837,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true
    },
@@ -825,7 +855,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": true
    },
@@ -844,7 +874,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true
    },
@@ -872,7 +902,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
@@ -892,7 +922,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": true
    },
@@ -920,7 +950,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -938,7 +968,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": true
    },
@@ -977,7 +1007,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -1042,7 +1072,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": true
    },
@@ -1060,7 +1090,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
@@ -1080,7 +1110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false
    },
@@ -1090,388 +1120,388 @@
      "output_type": "stream",
      "text": [
       "Neural network: 0\n",
-      "Optimization Iteration:      1, Training Batch Accuracy:   9.4%\n",
-      "Optimization Iteration:    101, Training Batch Accuracy:  84.4%\n",
-      "Optimization Iteration:    201, Training Batch Accuracy:  90.6%\n",
-      "Optimization Iteration:    301, Training Batch Accuracy:  90.6%\n",
-      "Optimization Iteration:    401, Training Batch Accuracy:  93.8%\n",
-      "Optimization Iteration:    501, Training Batch Accuracy:  96.9%\n",
+      "Optimization Iteration:      1, Training Batch Accuracy:   6.2%\n",
+      "Optimization Iteration:    101, Training Batch Accuracy:  87.5%\n",
+      "Optimization Iteration:    201, Training Batch Accuracy:  92.2%\n",
+      "Optimization Iteration:    301, Training Batch Accuracy:  92.2%\n",
+      "Optimization Iteration:    401, Training Batch Accuracy:  98.4%\n",
+      "Optimization Iteration:    501, Training Batch Accuracy:  95.3%\n",
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       "Optimization Iteration:   9901, Training Batch Accuracy: 100.0%\n",
-      "Time usage: 0:13:21\n",
+      "Time usage: 0:00:39\n",
       "\n",
       "Neural network: 4\n",
-      "Optimization Iteration:      1, Training Batch Accuracy:   4.7%\n",
-      "Optimization Iteration:    101, Training Batch Accuracy:  84.4%\n",
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+      "Optimization Iteration:   7401, Training Batch Accuracy: 100.0%\n",
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+      "Optimization Iteration:   7901, Training Batch Accuracy:  93.8%\n",
+      "Optimization Iteration:   8001, Training Batch Accuracy: 100.0%\n",
+      "Optimization Iteration:   8101, Training Batch Accuracy:  98.4%\n",
+      "Optimization Iteration:   8201, Training Batch Accuracy: 100.0%\n",
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-      "Optimization Iteration:   8501, Training Batch Accuracy: 100.0%\n",
+      "Optimization Iteration:   8501, Training Batch Accuracy:  98.4%\n",
       "Optimization Iteration:   8601, Training Batch Accuracy: 100.0%\n",
-      "Optimization Iteration:   8701, Training Batch Accuracy: 100.0%\n",
-      "Optimization Iteration:   8801, Training Batch Accuracy:  98.4%\n",
-      "Optimization Iteration:   8901, Training Batch Accuracy: 100.0%\n",
-      "Optimization Iteration:   9001, Training Batch Accuracy:  98.4%\n",
+      "Optimization Iteration:   8701, Training Batch Accuracy:  98.4%\n",
+      "Optimization Iteration:   8801, Training Batch Accuracy: 100.0%\n",
+      "Optimization Iteration:   8901, Training Batch Accuracy:  98.4%\n",
+      "Optimization Iteration:   9001, Training Batch Accuracy: 100.0%\n",
       "Optimization Iteration:   9101, Training Batch Accuracy: 100.0%\n",
       "Optimization Iteration:   9201, Training Batch Accuracy: 100.0%\n",
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@@ -1601,8 +1631,8 @@
       "Optimization Iteration:   9601, Training Batch Accuracy: 100.0%\n",
       "Optimization Iteration:   9701, Training Batch Accuracy: 100.0%\n",
       "Optimization Iteration:   9801, Training Batch Accuracy: 100.0%\n",
-      "Optimization Iteration:   9901, Training Batch Accuracy: 100.0%\n",
-      "Time usage: 0:13:42\n",
+      "Optimization Iteration:   9901, Training Batch Accuracy:  98.4%\n",
+      "Time usage: 0:00:39\n",
       "\n"
      ]
     }
@@ -1617,7 +1647,7 @@
     "        x_train, y_train, _, _ = random_training_set()\n",
     "\n",
     "        # Initialize the variables of the TensorFlow graph.\n",
-    "        session.run(tf.initialize_all_variables())\n",
+    "        session.run(tf.global_variables_initializer())\n",
     "\n",
     "        # Optimize the variables using this training-set.\n",
     "        optimize(num_iterations=num_iterations,\n",
@@ -1644,7 +1674,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": true
    },
@@ -1695,7 +1725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": true
    },
@@ -1723,7 +1753,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": true
    },
@@ -1744,7 +1774,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
@@ -1767,7 +1797,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -1789,7 +1819,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -1813,7 +1843,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -1844,7 +1874,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": true
    },
@@ -1896,7 +1926,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1906,11 +1936,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Network: 0, Accuracy on Validation-Set: 0.9936, Test-Set: 0.9872\n",
-      "Network: 1, Accuracy on Validation-Set: 0.9934, Test-Set: 0.9873\n",
-      "Network: 2, Accuracy on Validation-Set: 0.9940, Test-Set: 0.9883\n",
-      "Network: 3, Accuracy on Validation-Set: 0.9942, Test-Set: 0.9894\n",
-      "Network: 4, Accuracy on Validation-Set: 0.9946, Test-Set: 0.9888\n"
+      "Network: 0, Accuracy on Validation-Set: 0.9948, Test-Set: 0.9893\n",
+      "Network: 1, Accuracy on Validation-Set: 0.9936, Test-Set: 0.9880\n",
+      "Network: 2, Accuracy on Validation-Set: 0.9958, Test-Set: 0.9893\n",
+      "Network: 3, Accuracy on Validation-Set: 0.9938, Test-Set: 0.9889\n",
+      "Network: 4, Accuracy on Validation-Set: 0.9938, Test-Set: 0.9892\n"
      ]
     }
    ],
@@ -1927,7 +1957,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": false
    },
@@ -1936,9 +1966,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean test-set accuracy: 0.9882\n",
-      "Min test-set accuracy:  0.9872\n",
-      "Max test-set accuracy:  0.9894\n"
+      "Mean test-set accuracy: 0.9889\n",
+      "Min test-set accuracy:  0.9880\n",
+      "Max test-set accuracy:  0.9893\n"
      ]
     }
    ],
@@ -1957,7 +1987,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1969,7 +1999,7 @@
        "(5, 10000, 10)"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1996,7 +2026,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false
    },
@@ -2007,7 +2037,7 @@
        "(10000, 10)"
       ]
      },
-     "execution_count": 49,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2026,7 +2056,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
@@ -2037,7 +2067,7 @@
        "(10000,)"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 51,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2056,7 +2086,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": true
    },
@@ -2074,7 +2104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "collapsed": false
    },
@@ -2096,7 +2126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "collapsed": false
    },
@@ -2104,10 +2134,10 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.9872,  0.9873,  0.9883,  0.9894,  0.9888])"
+       "array([ 0.9893,  0.988 ,  0.9893,  0.9889,  0.9892])"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2125,7 +2155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "collapsed": false
    },
@@ -2133,10 +2163,10 @@
     {
      "data": {
       "text/plain": [
-       "3"
+       "0"
       ]
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-     "execution_count": 54,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2155,7 +2185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "collapsed": false
    },
@@ -2163,10 +2193,10 @@
     {
      "data": {
       "text/plain": [
-       "0.98939999999999995"
+       "0.98929999999999996"
       ]
      },
-     "execution_count": 55,
+     "execution_count": 56,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2184,7 +2214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {
     "collapsed": false
    },
@@ -2202,7 +2232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "collapsed": true
    },
@@ -2220,7 +2250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
     "collapsed": true
    },
@@ -2238,7 +2268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "collapsed": true
    },
@@ -2263,7 +2293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "collapsed": false
    },
@@ -2271,10 +2301,10 @@
     {
      "data": {
       "text/plain": [
-       "9911"
+       "9916"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2292,7 +2322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {
     "collapsed": false
    },
@@ -2300,10 +2330,10 @@
     {
      "data": {
       "text/plain": [
-       "9894"
+       "9893"
       ]
      },
-     "execution_count": 61,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2321,7 +2351,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false
    },
@@ -2340,7 +2370,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2349,10 +2379,10 @@
     {
      "data": {
       "text/plain": [
-       "38"
+       "39"
       ]
      },
-     "execution_count": 63,
+     "execution_count": 64,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2370,7 +2400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {
     "collapsed": true
    },
@@ -2389,7 +2419,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 66,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2398,10 +2428,10 @@
     {
      "data": {
       "text/plain": [
-       "21"
+       "16"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 66,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2426,7 +2456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 67,
    "metadata": {
     "collapsed": false
    },
@@ -2448,7 +2478,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 68,
    "metadata": {
     "collapsed": true
    },
@@ -2477,7 +2507,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 69,
    "metadata": {
     "collapsed": true
    },
@@ -2496,7 +2526,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 70,
    "metadata": {
     "collapsed": true
    },
@@ -2515,7 +2545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 71,
    "metadata": {
     "collapsed": true
    },
@@ -2537,7 +2567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 72,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2545,9 +2575,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Zv38/CwsLeL1e3G434+Pj9Pf3c+zYMXbt2kVycrIyeusAl8vF9evXOXHiBGfP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\n",
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jypUrXLlyhXPnztHe3r5vHa4Rp9PJwMAAQgj6+vo4d+4cIyMjTE5O0tHRgdPp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\nxU7OGGNMY7GTM8YY01js5IwxxjSW/wEwQC2raaGyYgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ffac932ff60>"
+       "<matplotlib.figure.Figure at 0x7fdddcb177b8>"
       ]
      },
      "metadata": {},
@@ -2567,7 +2597,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 73,
    "metadata": {
     "collapsed": false
    },
@@ -2576,7 +2606,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.    0.46  0.    0.54  0.    0.    0.    0.  ]]\n"
+      "[[ 0.    0.    0.    0.76  0.    0.    0.    0.    0.23  0.  ]]\n"
      ]
     }
    ],
@@ -2593,7 +2623,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 74,
    "metadata": {
     "collapsed": false
    },
@@ -2602,7 +2632,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.    0.57  0.    0.43  0.    0.    0.    0.  ]]\n"
+      "[[ 0.    0.    0.    0.21  0.    0.    0.    0.    0.79  0.  ]]\n"
      ]
     }
    ],
@@ -2619,7 +2649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 75,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2629,11 +2659,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.    0.17  0.    0.83  0.    0.    0.    0.  ]]\n",
-      "[[ 0.    0.    0.    0.37  0.    0.63  0.    0.    0.    0.  ]]\n",
-      "[[ 0.    0.    0.    0.77  0.    0.23  0.    0.    0.    0.  ]]\n",
-      "[[ 0.    0.    0.    0.57  0.    0.43  0.    0.    0.    0.  ]]\n",
-      "[[ 0.    0.    0.    0.43  0.    0.57  0.    0.    0.    0.  ]]\n"
+      "[[ 0.    0.    0.    0.21  0.    0.    0.    0.    0.79  0.  ]]\n",
+      "[[ 0.    0.    0.    0.96  0.    0.01  0.    0.    0.03  0.  ]]\n",
+      "[[ 0.    0.    0.    0.99  0.    0.    0.    0.    0.01  0.  ]]\n",
+      "[[ 0.    0.    0.    0.88  0.    0.    0.    0.    0.12  0.  ]]\n",
+      "[[ 0.    0.    0.    0.76  0.    0.01  0.    0.    0.22  0.  ]]\n"
      ]
     }
    ],
@@ -2652,7 +2682,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 76,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2660,9 +2690,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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39+P1emOj9NHoi+Hh4UVRWmpRGD2Px8PExATt7e1cunSJH//4xzQ3N+NyuVizZk3stXPn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\nIuIGBpVSv8Ro3/tCSHoxsifcjm8C/hleJ4rLuwrETeM69Py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1uxGSByPtU9pnKyPt83Dt86hEzgO8DgSBwqFfoHWxAMPAZxVF2X3MvpImIe1T\n2mcrI+3zcO3zSEROIpFIJJJWQAaeSCQSieTYIkVOIpFIJMcWKXISiUQiObZIkZNIJBLJsUWKnEQi\nkUiOLc9c5IQQNSFEde/nvVtVCPHxZ92mhyGE+H4hxC0hREEIsSmE+H+a3SbJ0dIO9imE+EcPaWdZ\nCNHZ7PZJjo52sM9GhBA9QojIXttMTWnDs15CIIToaXj57cBPAKcAsfdeRlGU3AOO0yuK8szK0goh\n/nfgHwI/BFwBOoAhRVE+86zaIHn2tIN9CiHMgPOetz8N5BVF+RvPog2S5tAO9nnPdT8D1IC/DlgV\nRXnmVVef+UhOUZRtdQOS9beUnYb3c0KI1/d6Jl8vhLgmhCgCl4QQvyWEuGslvBDiV/e+SPW1Tgjx\ncSHEihAiK4S4IoT45oO0UQjRDXwc+HZFUf67oigriqLckgJ3/GkH+1QUpXhPO43AXwV+/em/AUkr\n0w722XCuf0ldY37pKW75qWn1ObmfBv4XYAKY2+cxPwH8LeAfAJPArwC/LYR4Wd1hz/X4w484xzcA\neWBCCHFHCLEmhPiUEKLvSW5Ccmxpln3ey/cAMeCPD3CM5PjTNPsUQkwB/yvw3UBTM460cqkdBfgx\nRVG+or4hhHjE7iCEsFP/Yl9VFOXG3tu/LoT4MHXX47t7780Dj0obMwpYgX8F/ACQA34W+DMhxAVF\nUWoHvhvJcaOZ9nkv3wP8pqIolQMcIzneNM0+hRBW4FPAP1MUJfK46x41rSxyUJ8LOwinqec/e0Pc\n/c0agb9QXyiK8qHHnEe3d8w/VhTlLdCSpq4DfwV444DtkhxPmmWfGkKIr6XeKZOuSsm9NMs+fx54\nR1GUP9h7Le75+UxpdZHL3vO6xv0uVmPD7x3UezBfx/09jYMkOt3c+6nVflAUJSyESAH+A5xHcrxp\nln028n3AXyqKcucJj5ccX5pln18LjAkh/t7ea7G3pYUQH1cU5WcOcK6nptVF7l52gBfuee8FYHvv\n91tABfArivLeU1znrb2fp9nrwQgheoFOYPUpzis53jwr+wRACOEE/ifgB5/2XJLngmdln98ImBte\nvwb8KvASdW/YM6XdRO5LwA8KIb4NuAr8fWCMvT+SoihxIcR/AH5JCGGhLlAu6l/ytqIonwYQQrwB\n/FdFUR7o4lEU5ZYQ4nN75/kB6kEo//feNd960DESCc/IPhv4GPWH0m8fxc1Ijh3P6vm51PhaCDG0\n9+vsc7GsPiKVAAAgAElEQVSE4GlQFOWPgZ8D/j31P4AAfuueff63vX1+HJgB/gfwUeq1mVROAJ7H\nXO7bqfds/gz4IhAHvlGRtYkkD+EZ2yfUI+A+/aB1URLJvTTBPlsCWU9OIpFIJMeWthrJSSQSiURy\nEKTISSQSieTYIkVOIpFIJMcWKXISiUQiObY8FyInhAjsJSw9/4h9PrS3jyxVInmmSPuUtDLtbp8H\nEjkhxG+I++sZVRuzWLcw+wkjPZJQUyHETwohwkKInBDi80KIsaO4zvOOtM+DI4T410KIWSFERggR\n27PPlx9/pOSgSPs8OKJej+6/CiE29qoifOagz88nGcn9KdDbsPUBf/cJzvOsaUreNCHEjwD/FPhH\nwMvUU+18VjSpgOBzgLTPgzFHPWPKWep5WYPA54QQbbMOqs2Q9nkw/ggYBr6JenaWNeALe0mg98WT\niFzxnvpF24qiJNUP93on3yuE+P095Z0XQnxTw+cuIcQnhRDbeyObOSHEdzd8PiiE+G0hRFwIERVC\n/KEQItDw+W8IIf5ACPFjQoitvf1+XAihF0L8nBBiVwgREkJ8zwPaPiGEeEsIkRf1it8ffNSNCiFe\nE0J8da+dq0KIXxBC2A74ff0L4N8qivIniqLcBr4L6Ae+5YDnkewPaZ8HQFGUTyuK8iVFUYKKosxS\nr7zRCTzUNSV5KqR97hMhxEngFeqJ8q8qirJAvSqMlQN0DI5qTu7j1CsVnwM+A3xSCOHa++z/AsaB\n1/d+/gAQBRBCGIDPUi8G+Ff2tjT1EjeNKcj+GvUe0F8F/iXwk8D/R72m1svAfwR+TQjRf0+7fo56\neq4XqK/4/xMhRNeDbkAIcYJ6r+t3qfdyv22vPb/YsM+/EUKsPOxLEEKMUO+tfVF9T1GUFPAO8OrD\njpMcOdI+H3xOI3WPQwK48ZjdJUeHtM86Zuou0KL6xl7GqSL1VGP7Q1GUfW/AbwBl6l+cuqWAH23Y\npwb8m4bXNqAKfHTv9R8B//kh5/9OYOae90zUXXwfaWjDMnvZWvbemwW+3PBat9e2v7P3OrDXrh9q\n2EdPfej7Q3uvP7TXzs691/8J+NV72vIa9VyBpr3XPwh8/hHf16t75/Td8/5vA791kO9ebtI+D9s+\nG477G3vtqQIh4FKz/5bHcZP2eeDnpwFYoS74rr17+ZG9tvzpfr/3J0nQ/CXgH3O3jzZ2zz631F+U\nejn2NNCz99avAr8nhLgEfA74Q0VR1FpFU8DJvf0bMVPPl/aFvdfTyt63sEfknmvWhBC7DddU+cuG\nfapCiMvUq+Y+iCngnBDiYw3vqfc8AswpivLLwC8/5PhHIWhytdxjjLTPg9vnl/bO5wW+H/hdIcTL\niqJE93Gs5GBI+9ynfSqKUhFCfCv1Wokx6gL5Beqj233zJCKXVRTlcS6Q8j2vFfZco4qi/JkQwk+9\n9/gR4ItCiF9SFOWHqdczugx8B/dPdO485vwPveZjeJjYdAC/BvzCA9qyto/zAmztHeujbkgqPcC1\nfZ5DcjCkfe7fPusXUJQ89d79MvCuEGIe+F7gZw9yHsm+kPZ5APtUFOUacFEI4aA+AtwVQvwlsO9S\nQE0ptaMoyi7wm8BvCiHepO7r/WHq5R/+DrCjKErmCC79AeBNACGEHrgE/IeH7HsVmNyHQT4URVFW\nhBBb1IsQ3ty7bif1ydQnGQFKngHPi30+Ah131wOTtBDPo30qipLeu+5J4EXg/9jvsU8SeGIWQvju\n2fYdbiyE+AkhxDcLIU4IISapF9ib2fv4k9QnUf9oLzJnWAjx4b2onHsnQZ+EHxRCfIsQ4jTwK9T9\nvL/R2LyG338WeFUI8YtCiCkhxJgQ4m8KIRonTn9QCPEFHs2/B35cCPFNQohz1I1znbpvXXL4SPt8\n/14eaZ9CCJsQ4qeEEK8IIfxCiItCiP9CPfr3dw/hfiT3I+3z/Xt57PNTCPE/i/pC8xEhxN+k7qL9\nfUVRvvio4xp5kpHcNwDhe96bA87s/f6g4avS8H4J+Gnqax/ywBvshYMqipIX9bDUnwV+D3AAG9Sj\nE1OPaNPDrnnv6x/d26aAReCbFEWJPegYpV449UPATwFfpf4HXOLuApVeYPQR7UJRlJ8T9bDZX6Nu\nFG8Af11pQvHA5wRpn+/zOPusUo/Q+669fXepu4FeU+rLCSSHj7TP93ns85N6FOi/oz7Fswn8N+oR\npvtG1pOTSCQSybHluchdKZFIJJLnEylyEolEIjm2SJGTSCQSybFFipxEIpFIji1S5CQSiURybHkq\nkRPv10dSt6gQ4k/31oMdCqJe7+qx2UH29qsJIX7lnven9t73H+Cafy6E+HdP0t69479HCHFD1LN1\nbzWuDZE8O6R93nfcd4v765mpr70HPZ/k6ZD2+chzuIUQ63u2+VSFWA9jJPen1NNW9VLPbl0B/uQQ\nztvIftc5FIDvFfcX1Xtm6ySEEP8K+LfU17KcoZ5657PP6vqS+5D2+T6f5v0aZmo9s89ST84r81Q2\nB2mfD+bXgeuHcqZDyKr9+w/INF0FPA3vDVJfBBinviL/D4FAw+cfpl5+JrO3zxvAEPDd1DNOVxt+\nftdD2vKvqaeS+TPgtxven9o7zt/w3lnqST7T1PNL/ibgbrine6/p3+f34aKe8fvDT/O9yu1wNmmf\nj/1+vNTLlnxHs/9Wz+Mm7fOh38sPUE9k/bU0VDZ40u1Q5+SEEB3Ax4AFpZ5f7bE1jkQ9B9ofAH++\n9+V9APh/qfcePg38PDBNvbfTx90r5h/EjwJ/S9SzdD+ojU7qGQCuABep12Xq4f00Rv+Ceq2k/9Rw\nzdDesStCiI8/4tpfT31l/5AQYkbUiw/+thBi8DFtljwDpH3ex3dT75T93gGOkRwR0j5BCHEG+HHg\n71EXyafmMBI0f5N4v7SDnXrKmm9s+PzbqGdW+YfqG0KI76Xe4/gw9S+rE/gfiqIE93aZa9g3A1QU\nRWnMov1QFEW5LoT4HeBnqIvOvfxT4KqiKP9nwzW+D1gTQowpirIohCgBuQdcc5G9AoUPYZR6naUf\nA/459VQ6PwV8XghxTlGUyn7uQXKoSPt8OH8f+KSiKMXH7ik5KqR9vn8eE/Ap6jXqNh7gNn0iDkPk\nGusjuYF/Qr2X8ZKiKCEeU+NIUZQvCCH+G/A5IcTnqdcL+h1FUbaeok0/DswIIT7C3SUm2GvPX3tA\nexTqNZcWH3ZSRVEe9EdvREf9O/1nyl4CUSHE36U+pP9a4PP7vgPJYSHt8wEIIV6lXgvsY4/bV3Kk\nSPt8n5+hXvT1t/Zei3t+PhGH4a7MKoqyoijKsqIol4Hvo94j+f69z9UaR+epf0Hqdoq6aqMoyj+g\nPsx+i3rPZV4I8fKTNkhRlGXgP1P/0gR3f0kdwB8/oD0nqScSfRo2935qyW2V+oR+FNh3dJLkUJH2\n+WC+D7iuKMrhTO5LnhRpn+/ztcDfFkKUhRBl6oItgB0hxL9+0pMeVT25GmDd+31fNY4URbkB3AB+\nVgjxNvXCf+9Sz7qtf4I2/CT1XsW3c3d00FXgW4FVRVEe5vN90mu+tffzNHuZxoUQbuoT/KtPcD7J\n0fC82icAQgg78LeBH3nSc0iOlOfVPr+V9+8b4GXqUZavUS/o+0QcxkiusT7SOPCL1HsiahjsI2sc\n7b3+aSHEB0S9ptVHqfcK1BpJQWBkb72GZ89v+1gURdmmXqLhn9/z0S9Tdwt8WgjxohBiVAjxuhDi\nvwgh1B5LEHhFCBEQDbWehBBfFEL8k0dcc4F6L+cXhBCvCiHOUi8NMUN9Yljy7JH2eT/fTv0h9Kn9\ntFVypEj7fP+aK4qizKgbsEJ9JHdHeZolLk8Tmkk9XLTasCWAvwS+5Z79evb2jQA5YAH4j9SHvj3A\n71MvJJqnrtgfbzjWBPwOEGMfIbD3vNcBbFNfe9IYAnsC+O/U62dlqEcf/XzD5yepj8qyNITA3tu2\nh7Sjg3pk0S51f/bvAgNP8z3LTdrnYdnn3n5vAb/Z7L/P875J+3zs9/MhDmEJgawnJ5FIJJJji8xd\nKZFIJJJjixQ5iUQikRxbpMhJJBKJ5NgiRU4ikUgkxxYpchKJRCI5tkiRk0gkEsmxRYqcRCKRSI4t\nUuQkEolEcmyRIieRSCSSY4sUOYlEIpEcW46kCsFeUs7XqSfqLBzFNVoUCzAMfFbZq+wraT2kfUr7\nbGWkfR6ufR5VqZ3XqWfPfl75TmSG91ZG2qe0z1ZG2uch2udRiVwQ4BOf+AQTExNHdInWY3Z2lo99\n7GOwd/+SliUI0j4lLUsQpH0eFkclcgWAiYkJLl68eESXaGmeJxdDOyLtU9LKSPs8RGTgiUQikUiO\nLVLkJBKJRHJskSInkUgkkmOLFDmJRCKRHFuOKvBEInmuKRQK5PN5MpkMyWSSbDZLuVymWq1is9mw\n2WxYrVYsFgtWqxWbzYbZbG52syWSA1Gr1VAUhUKhQCaTIZPJkMvlKBaLeL1evF4vJpMJg8GATtec\nMZUUOYnkCEin00QiEVZWVpifnycUCpFOpykUCvT399Pf34/P58Pn89Hb20t/f78UOUnbUavVqFQq\nxGIxVldXWVtbIxQKEY/HefHFF3nxxRdxuVzY7XYpcvtBURSKxSLFYpFCoUChUKBWqwFgMBi0nrHJ\nZMJoNCKEaHKLJc8DiqJQq9WoVqtks1kymQxra2sEg0Hu3LnDrVu3WFlZIZFIUCgU8Pv9+P1+hoaG\nGBwc5PTp09jtdjo7OxFCNO1hIJHsB0VRtC2RSBCLxQgGg8zNzbGwsMDq6irxeByn08nJkyc1b0Wz\naCuRq1arbG9vEw6HWV9fJxQKkc/n0ev1dHZ2MjIyQiAQwOPx4PF40Ov1zW6y5DmgVqtRLpfJZrPc\nvn2b6elpVlZWCAaDbG5usrOzQyKRoFgsUi6X2djYIJPJEIlEWF1dpVAo0NPTQ3d3NyaTSYqcpOWp\nVCpUKhUWFha4fPkyc3NzrK6uEolEtGdyJpMhn89TLpdRFKVpbW0LkVN7yfl8nq2tLebm5piZmWFm\nZoZ0Oo1er6e7u5tEIkG1WkVRFBwOB0ajEb1eL0d0kkNF7cXWajVqtRqlUolsNks0GuX69et84Qtf\nYGVlhVAoRLFYvGs+Qq/Xk0qlSCQSRCIRbDYbJpOJyclJhoeH6ejowGg0NvkOJZL7UYWq0ebn5+f5\n4he/yPT0NJFIhEKhgNPpxOfzUalUtHloKXKPIZvNsry8TDAYZHt7m+3tbVwuFx/60IcQQmg96XQ6\nzVe+8hV2dnZIp9P09vbi8/mwWCzNvgXJMaJUKlEqlYjH45pnIRgMsrKywtLSEouLi1QqFXp6evD5\nfIyNjdHb24vBUP93U214Y2ND227cuIHNZuPUqVOMjIw0+Q4lkvtRO3bFYlFzx8/MzBAKhUgkElQq\nFZxOJ1NTU0xNTXHhwgUGBgZwOp2a7TeDthC5TCbD7Ows77zzjjZMPn/+PC+99BKdnZ0Ui0WCwSCf\n+9zneO+998hkMlQqFarVKk6nU4qc5FApl8tkMhnC4TDT09PcvHmTy5cvc+vWLc0+e3t7GRwc5MUX\nX+QjH/kI586dw2KxoNPpmJ6eZmZmhjfeeIP19XU2Nja4efMmVqsVl8slRU7SslSrVQqFAmtra1y5\ncoWZmRnW19eJx+MIITSR+4Zv+AYCgQADAwNNj49oaZHLZrNa1E44HCadTjM4OMjg4CBjY2P09fVh\ns9kol8sIITTR6+vrw+12Y7PZ5Lyc5NDZ3NxkZmaGubk55ufnCQaDpFIpOjs76e7upru7m0AgQCAQ\n4PTp04yNjWmh1ACDg4NUq1Xm5+cxGo1Uq1VKpRLFYpFqtdrku5NIHow6ZRSPx1ldXeXWrVvk83lG\nR0cZHx/H5XIRCAR46aWXGB4epqurC6PR2PQ55pYWuXQ6TTAYZGFhgUgkQqlUYnBwkA9+8IN0dXXR\n0dGBwWCgVqthsVhwOBy88MILlMtlKpUKnZ2dTR0mS44noVCIN998k5s3bxIKhUilUjgcDgKBAOfO\nnePcuXN3BUF1dHRgsVgQQqAoCm63G71ej8/nw2w2UywWm31LEsljqVar5HI54vE4a2tr3L59G5/P\np80nBwIBLWK4r6+v6SM4lZZWgEwmQzAYZG1tDYvFwvj4OKOjowwODmI2m9HpdNqXqI7YzGYz8Xic\nRCKhLVSUSJ4UdR1QqVRic3OTra0t3nvvPWZnZ4nFYlitVjweD36/Xxu5nT59mr6+Pnp6eu4LnVYU\nBZvNhsFgwG63o9frNfdnKpWSgidpOdT/gUQiwdzcHNPT02xvb2sdu4sXLzI2NkZ/fz/d3d10dHRg\nt9ub3WyNlhY5dSS3tbXFpUuXeOGFF+jt7X3gEFhdoxSPx4nFYsRiMSwWi3T/SJ6KWq1GoVAgFovx\n1ltv8ed//ueEw2F2dnZwuVyaO3J0dJRAIIDT6cTpdGKz2R4aJanar8lkQghBoVBgZ2eHSCRCNpt9\nxncokTyaSqVCoVBga2uLt956i6985St0dXVpwSUvvvgifX192O12LBZLy3nPWqs1e6juxnQ6TTwe\n19YRnTt3Dr1ej8FguG8YrA6lY7EYm5ubbG5uYrPZCAQCTboLyXGgVCoRjUYJBoPcuHGDN998E5PJ\nhNvtZmxsjEuXLnHu3DkCgQD9/f37Oqc6MiyXy1pksDqSK5VKR3xHEsn+UD1h2WyW7e1tFhYWuHXr\nFjdv3uSDH/wg586dY3JykrGxMbq6uprd3IfSkiKnBpykUiksFgsejwe73f7I/GdqjzuZTGqhrXa7\n/bmqrCs5fLLZLHNzc1y+fJmNjQ2MRiMTExO8/PLLnDp1ikAgQG9vLw6HY1/nq1ar7O7uassI1KAp\niaTVqFarlMtlwuEw165d49q1a+zs7GC32+nr62N8fJy+vr6WT0fXkiKXyWTY2toimUxiNpux2+2a\nyD0MdYFiOp0mFApx8+ZN/H4/+XyeWq2GEEI+TCQHJpfLsbCwwLvvvksmk8HhcDA5Ocnrr7/OiRMn\ntDRy+6VWqxGLxVheXtZETq/XYzKZMJlMMhpY0lQaYxjULD4bGxtcvXqVa9eukU6ncbvdDA4OcvLk\nSdxu94Hsvxm0rMiFw2FisRg6nW5fWSCEEJorU10YruZV6+7uxmq1tvwfQ9J6lMtlEokEOzs7DA8P\n88orrzA1NYXH43kiUWoUuWg0Sq1Ww+PxcPbsWS5cuEBPT88R3YlEcjCi0SjLy8vaWrharcbZs2c5\nceIE58+fp7Ozsy3S0LW0yMXjcYxGIx0dHY8VKCEEBoMBo9FIpVLRUiepbk+DwSBFTnJgKpUK8Xic\naDTKK6+8wtd93dcxPDyMx+N5IjeNKnJLS0uayHm9XiYnJ3nhhRfw+XxHcBcSycHZ2dnR0ieGQiEM\nBgNnz57lox/9KN3d3XR2draF56ElRS6fzxONRonH43R0dOByuR4aJVmtVqlWqyQSCZaWlrh58yaZ\nTEbLnTY/P4/ZbGZ8fLylwlol7YHD4WBqaopyuczFixcZHBzE5XIdeA2Qmn9VDY7a2Nggl8thtVrx\n+XyMjIwwPDyM0+k8wruRSB6PWullbW2N69evEw6H8Xq9DAwMMDIyQm9vLzab7a4lXK1MS4pcLpcj\nGo0Si8WoVqt4PB7K5fID91VzqcXjce7cucO7774LwNDQELVajZmZGYxGI319ffT19T3L25AcA5xO\nJ6+88gojIyNapQCr1XrgHqyiKJRKpbsigPP5PHa7HZ/PRyAQwO/3S2+DpKnUajXy+TypVIrV1VWu\nX78OwMWLF7l06RIjIyO4XK62EThoUZFTF9jm83mt+GQ6ndYi0XQ6HeVymVKppD0wVlZW2N3dxWg0\n4na7cbvdWo+5s7OTc+fOkcvlMBqNMsu7ZN9YLBYGBga0tFxms/mJKlsUCgXW19dZWloiGAwSjUYx\nGAy4XC4cDgcOh4OOjo4juguJ5NGongY1L+Xy8jKhUIhqtYrX6+XkyZOMj4/T09PTdh2xlhQ5r9fL\nmTNnUBSF6elp1tbW2N3dJZ/PYzQaMRgMZDIZkskkCwsLXL16lfX1dc0tqVZbvnLlinb81tYW8Xic\nzs5OKXKSfaPT6bBYLFrZJp1O90S92Ewmw8zMDG+//Tazs7PE43Ett5+MqpQ0G3UJViKRYHp6mq9+\n9avE43H6+vo4ffo0Z86c4cSJE3R2dja7qQemJUWuq6uLkydPkkwmmZubI5FIsLa2xuzsrNabTqVS\nxONxlpaWWF1dJZPJcOrUKcbGxujp6aGnp4f19XVNEDc3N9nY2NCiNYG2GW5LmoeamWQ/KIqizRGr\n5XhUj4M6v/Hee+8RCoXIZrPY7XZqtRq5XE7zRqhRwmqVe9Xz0OoRbJL2plKpkEwmCYfDLC0tcfv2\nbbxeLydOnODs2bOau74d7bAlRc7hcDAwMEA0GmV4eJiFhQWuX7/OwsKCVkq9Wq1SqVQwmUwMDg7i\n9XoZHh5maGgIm82G3W5neHiYM2fOkM/nWV9fx2KxYDab6e3tBeoPJSl0ksNCURTy+TzZbFZL07Wz\ns8POzg6rq6vcvn2blZUVUqkUiqJQLBZJJpPMz88DcPv2bYxGI1arlZGREUZGRnC73XR1dbWdi0jS\nXhQKBTY2NpiZmWFnZweAvr4+Ll26xPj4OG63u63m4RppSZHr6Oigo6ODRCLB6Ogo0WiUO3fuEAwG\nsVqt2Gw2TewmJiaYnJzk/Pnz9Pf337XOKBAIMDk5STAYZHNzk0KhgN/vZ3x8HL1eL11EkqeisTq4\nmp4rFouxu7urFVBdXl7WqoRvb28Ti8WAuhdBXc+5vLzMxsaGZtOdnZ1cunSJarXK8PAwFotFmwds\nx560pHVRq9zncjlCoZCWeNxkMtHf38/U1BQjIyNaLcR2pCVFTsXj8XDhwgUtEa6aVslgMGiJcPv7\n+xkeHqanpwebzXbX8T09PZw/fx6dTkc8HicSibCwsIDb7daiLaXQSZ6UQqFAKpW6K19qOBxmY2OD\nWCxGIpHQEoYnk0mtwoDqgjSbzdq6TnU+xGAwYLFYKBQKrK6ucuHCBS5duoTf78ftdsvgFMmhUiqV\nyGazbG5usri4yPz8PB6Ph0uXLnHq1ClcLlfbzxm3vMg5nU5OnTrF1tYW0WgUqPc+vF4vPp9PK1vy\noIg3texDLpfj2rVrWpJRq9WKEIKenp62/uNJmkuhUNCyQty4cYNbt26xvLzM0tIStVoNnU6n9ZTV\npMyAJmRmsxmDwUCxWCSRSJDP57VzB4NB9Ho9sVhM289isUiRkxwqpVKJRCKhzcXNz8/zoQ99iBdf\nfJFTp07R1dXV8rkpH0dLi5zqUhRC4PP5sNvt2kPD4XBoaWUehrpgt7+/n/Pnz2Mymcjn81y+fBlF\nUTAYDPT09Dxx9grJ843BYMBqtdLV1cXg4CClUgm3243f70cIgdFoJJFIsL6+TjQa1fKonjx5klOn\nTuF0Ouno6KBYLBKLxdje3mZ9fZ1wOEypVCKfz7OyssLbb79NuVzW5uvMZrOco5M8FWqFgUgkwnvv\nvceNGzfY3d2lq6uLvr4+RkdHteUC7TgP10hLi5yKwWDA4XBo7khVoB5Xt0gVyN7eXl566SWsVitv\nv/0209PTWhqwiYkJ7Ha7FDnJgTEajXR2dqIoCkajEZ/Pp0VV6vV6jEYji4uLvPHGG1QqFQwGA4qi\ncP78eb7+67+enp4eXC6XNpe3vLzMm2++qS3GLZfLrK+vk81mqVar9Pf34/P5cDqdUuQkT4U6nxwO\nh3nzzTe5evUqFouFvr4+BgcHCQQCx2a5VVuI3EHCuBtRw7HVCrZqKPf6+jqxWIzLly8jhMDtdqPX\n67U5EolkP6ih/kIIzGYzbrdb+0xdXJtMJjEYDFSrVSwWC3a7nUAgwNmzZ+nu7sbhcGi1E91uN4qi\nYLFYWFhYYH5+nmKxyNbWFsFgkMXFRXp7exkeHt53aR+J5EFks1kSiQSrq6taRYypqSnOnz+vCdxx\n6fi3hcg9LSaTCZfLhd/v5+LFi+j1ehYWFnjnnXe0KCL1ISVFTrJf1BI5er0ei8Vyl/Ck02mSyaSW\nxiuZTOLxeOjp6cHn89HT06P1lE0mkxaI0tnZyfj4OJ/73OfIZDLs7OxoicYXFhbweDzaEhuJ5EnZ\n3d1lcXGRpaUlLZry5MmTvPbaawQCgZar7v00HJ87eQRqNFtPTw/j4+MYDAZ2dnaIxWKsra0xPz+v\nLby1Wq1tux5E8mxRs588qGOUzWa13rIaWdnR0UF/fz9erxen04nVatX2N5lM2O12enp6CAQChMNh\nZmdnKZVKpFIp8vk8u7u7RKNRcrncs7xNyTFBjWdQFEVblrW0tEQikcBoNOL1ehkdHcXpdB6rZ+Bz\nIXIqJpOJ7u5uACYmJgiHw+h0Oq5fv061WsXhcNDV1bWv+T6J5FGoCW7D4TD5fB6z2UxPTw+jo6Pa\nwtqHodPpcLvdjI6OarlbjUYjDocDp9N5bNxIkmePmkQjEokwMzPD0tIS6XQal8tFoVAgnU5jsVju\nKp7a7rTn6r4nRO2tDA8PMz4+ztTUFEajkZmZGW7evEkkEqFQKDy0rI9Esl+SySTBYFArqWMymfB6\nvQQCAVwu1yN7yTqdDqfTydDQkOZCN5lMdHZ2SpGTPDGNlTC2traYm5tjdXWVXC5HrVYjm82yu7tL\nLpeTItfuGAwG/H4/H/jABxgZGUGv15PJZNje3iYSiZDNZpvdREmbs729zc2bN7lz5w7JZBIhBCaT\nSXOLP0rk1PRgsVhMi6w0m814PB5tKY1EclCq1SrhcJhr166xtLREPB6nWq1qUzSLi4t85StfYWVl\n5Vh19J9rkXv11VcZHR3FYDBobqGtrS0pcpKnZmdnh5s3b2oJxtV1c1ar9bGucLWmVzwev0vkvF7v\nAzP7SCT74V6RSyQS1Go1TeSWlpb46le/ysrKCpVKpdnNPTSeq4mnxt6zGhXn8XgYHBykUqmQy+XY\n2UrdbwUAACAASURBVNnREjhLJE9KtVqlXC5rNRBVd6Xf76erq+uRc3LqSK5R5NTlME9Sy04igXrn\nKZlMsra2Rq1WIxAIaK5xRVHY2Nhga2tL8yAYDIZjUQHjuRK5RtToIXVpQSKR0NI0NaZXkkieBlWQ\nTCYTPp+P0dFRzGbzgUSuVqtJYZM8NbVajVQqRTgcxmAwaFl3XC4X6XSaWCzG+vo6yWSSTCajJQaX\nIteGqA8MNau7mr+yVCpRLBaP1VBd0hqoLsh0Og3wwHk5tQ6dmvQ5Go1SqVRwOBy43W6cTid2u11m\nO5EcCDUxgdpx2traYnBwkKGhIS3/bzQaxW63a53/49Spam+JPgTUml7pdJpyudzs5kiOGWqUWqFQ\nYH19nenpaSKRCLVa7b59K5UKqVSKSCSiBUHVajV8Ph9DQ0P09fXh8XiwWCzP+jYkbYxa9TuVSrG7\nu8vW1ha1Wo3e3l4GBga0BAPqZrfbsVqtxyJvJTynIzn1waMoilbiJJvNasUpZWUCyWFwr52pIqfO\ng6iLyNWedjab1VJ4qW6jgYEBAoEAw8PDWlUNieQgqGnjotEosViMeDxOrVbD6XTicDjIZrNablWb\nzaYlATcYDG3vqoTnVOSg7hpSHyxqKK3dbsfj8dyViUIieVIa3eLFYpGNjQ1u3bqlvaeKXLFY1Oww\nFAqxurrK0tISlUqF7u5uzp07x+nTp3E6nU27F0n7Ui6XiUajrK2tEYvFKJfLWhWCbDZLKBQiGAyS\nyWS0RBjHYS5O5bkSucaedblcplAokMlkSKVSmM1mHA6HFDnJoaAm/DabzdpcWzgc1tyUtVpNEzlV\n4HZ2dgiFQoTDYc0m+/v7OXfuHCdPnqSzs7OZtyRpUyqVCslkkq2tLdLp9F2V7BOJBGtra6ysrJDJ\nZLSi1FLk2pxKpcLGxgZra2tsbW1hNpvp7e1lZGREy8AtkTwNAwMDvPrqq9jtdsLhMMlkknw+z//f\n3pvHR3ZV977fpaEGlWaVptaslnp0u+0ebGPg4jDnXSDc5L5AgE/Iw2Qkl+TeSwh5l5BAghPISz5w\nmTM54ROISW6AQAAbGxxim2DTdmz3qG61WmrN81AqqUpSab8/dp3TJbWk1lBSlUrr+/mcj1Sn9jl7\nn6Ols/bZe+316+vrIxaLMTg4uCTgaXZ21h0yqqmp4dChQxQWFnLq1ClaWlpU81DZNB6Ph6qqKg4c\nOEBbWxvBYJBIJMLly5eZn5/n0qVL9Pf3u6NZmeLcHPack3NUmvv6+njuuecYGBjA5/O5EiYNDQ06\nJ6dsmZqaGu655x68Xi/PPvusO2owOjq6xMHBjcS5hYWFtLS00NjYyJEjRzh8+LBrk/n5+Rn38FF2\nBqcTn52dTV1dHeXl5UQiEdra2giFQly9epXJyUlKSkrc5MyZREY7OScZqSNCOTExwcjICIODg1y+\nfJm2tjY8Hg+1tbU0NjYuCQZQlK1QVlbG4cOH8Xg8FBUV0dTUxPDwMCMjI4RCIaamptwF3kVFRZSX\nl1NdXU19fT319fVusElpaSl+v187XsqmcfQ4i4uLOXr0qBtNHolEiEQibhae1tZWjhw5Ql1dXUbZ\nW0Y7uYWFBaLRKGNjY3R3d9PR0cH58+dpa2tjbGyMsbExjh07xtGjR2lqalIhSiVplJaWkpeX5yZl\n7uvro7u7292uX7/uzts1NDRw++23uwoFzpo4RwFcFTGUreAEOQUCAY4dO0YwGHQ7+TMzM66dHT9+\nnLvvvjvjRrN27X/PwsICCwsLzM3NuT2S2dlZIpEI8/PzzM3NuZpezhDR0NAQIyMjGGMIBoNUVlZy\n5MgRDh06RF1dnSa+VZKGE3Ti6MSVlpZSXl7Ovn37qK+vp6mpiaysLLxerzsHV1tb64ZwezwevF5v\nRqxTUlKLs7g7NzfXXYbipIgrKSmhrq4Or9fLHXfcQWtrKyUlJerk0gFHMmJ8fJzR0VGGh4cZGBhg\naGiIqakpd3hyYmKC2dlZ5ufnycvLo6Ghgbvvvpvq6mqqq6upqKhwVZo1qlJJNo4OnNfrdeVzZmZm\nmJmZcTPuBAIBN5uJE9mWSQ8ZJT1wcqhmZWW5Q+EzMzNEIhGys7MpLS2lpKQk4zpXu9bJOQEk8/Pz\nbrokZ85tYmKC8fFx18ktLi7i8XgoKSmhvr6eEydO0NjYSGNjo7v4O9MmW5X0wFl35Pf7dZ2bklJE\nxLVHn8/nCkhnOrvWyTk95JycHAKBgKu6PD09TSQSIRqNuj+NMWRlZZGfn091dTVVVVXuOLRmdVcU\nRclcdq2T83g87nxHMBhMdXMURVGUNETH6BRFUZSMRZ2coiiKkrGok1MURVEyFnVyiqIoSsayXYEn\nPoCLFy9u0+nTk4TrVVXL9EbtU0ln1D6TiDjyM0k9qcjbgC8l/cS7h7cbY76c6kYoK6P2qfaZzqh9\nJtc+t8vJlQGvAzqBSNIrSF98QCPwiDFmNMVtUVZB7VPtM51R+0yufW6Lk1MURVGUdEADTxRFUZSM\nRZ2coiiKkrGok1MURVEyFnVyiqIoSsaiTk5RFEXJWHbcyYnIoojE4j+XbzER+dBOt2klROT1IvIj\nEQmJSI+I/EGq26RsP7vIPl8iIo+LyISIjIrIt0TkaKrbpWwvu8U+AUTkF0XkrIhERKRfRP6/VLQj\nFVI7VQm/vxX4MHAAcETdplc6SESyjTGxbW6bU9cp4BvA/wLeBtQDfy4ixhiTNkakbAu7wT6LgW8D\nfw/8IuAFHojva9iJNigpI+3tM17f/wv8EvA+4FkgH6jbqfqXYIxJ2Qa8ExhbYf/rgEXgNcB/AFHg\nLuw/9ZeXlf0c8O2Ez1nAh4BrQBh7g9+0wXb9KfCDZfv+KzAJeFN5z3TbuS2N7fOlQAwoS9h3Kr5v\nX6rvm247s6WxfZZjF7Hfk+p7ZIxJ+zm5B4DfBA4Dbes85sPAzwDvAo4CnwW+IiJ3OQXir87vX+Mc\nXm7ONBDB9kaOr7MdSuaTKvu8gO1wvVtEckQkD7gfeN4Y07fxy1AylFTZ5+uBWeCwiFwSkesi8mUR\nqd7MRWyVdFYGN8DvGGN+4OwQkTWKg4gEgP8JvMQY80J891+JyH3YV+dn4vsuA2uljXkE+CUR+Rng\na0ANdugSICV/KCXtSJl9GmPGReSVWNv8Q2zv+zy2B68okNrnZzPgB/4H8KvADPAx4GERudMYs7jh\nq9kC6ezkwL4qb4SD2PxnT8jSv2gu8O/OB2PMK9Y6iTHmmyLyQeCvgIewvZIHsK/8OzauraQ9KbFP\nEcnH2uZ3scNNXuADwL+IyD3GmPkNtkvJTFJin9hOVy7wK8aYp8BNOt2DHWp/YoPt2hLp7uTCyz4v\ncnNEaG7C7/nYHsyruLmnsaFEp8aYjwMfF5EqYAw4AnwUO1atKJA6+/x57HzcLzs74g+RCeAnsUFT\nipIq++yP/3S1c4wxfSIyhQ3i21HS3cktZxi4Y9m+O4Ch+O9ngQWg3hjz42RUaIwZAPchctUYcz4Z\n51Uykp2yzzzsAysRE9/SfZ5dSR07ZZ9PxX8eJP4GGH9ZKAS6tnDeTbHb/iG+D7xURN4iIq0i8gDQ\n4nxpjBkH/jfwaRF5u4g0i8gJEXmviLzVKSciT4jI/atVEp/M/00RORrfPgK8F/j17bs0JQPYEfvE\nzhnvE5FPiMgBETkG/A0wxQ4PBSm7ih2xT2PMWexQ+qdF5K4E+3yOGw5wx9hVTs4Y8w3g48AnsD0E\nwYbFJpb5rXiZD2Kj0L4FvBarzeSwHyhbqyrgzcCT2MnWnwB+0hjz3WRch5KZ7JR9xh8ibwZOA09j\nH17FwOuN6sQpq7CDz0+wa/jOAg8D3wPGgTeY+BqDnUT15BRFUZSMZVe9ySmKoijKRlAnpyiKomQs\n6uQURVGUjEWdnKIoipKx7AknJyINcSmK29co84p4mcKdbJuiqH0q6cxut88NOTkReXAFPaOYiHx7\nuxqYRNYTRpr0UFMR+T0RuSgi0yIyJiKPJiY7VZKH2ufGUfvcOdQ+N46I/BcReVhEhm/laFdjMxlP\nvgP8Ajf0i8BKOaQ7a2cn3T7agPcAHdxIWvpdEdmva5q2BbXPjaH2ubOofW6MAHa98j8Af7GZE2xm\nuDJqjBk2xgwlbJPOl3Fve7+IfFVEwiJyWUTemPB9sYh8SUSGRGRGRNpE5J0J39eKyFdEZFxERkTk\n6yLSkPD9gyLyNRH5HREZiJf7oIhki8jHxaokd4vIL6zQ9sMi8pSIzIpVrP1Pa12oiLxMRP4t3s4u\nEfmkWFmTdWOMecgY831jTKcx5iL2IVIIbLhHoqwLtc8NoPa546h9bgBjzN8ZY/4Qu6B8U452u+bk\nPoTN3n8Mq1b8JbFqxmClQQ5hZUEOYaUYRsCm08KmLJrEZqt+KRDCSjQkvnW+Eit583LgvwMfAf4F\nm0j5LuDzwBdEZN+ydn0c+BNsvrZ/B74pIiUrXYCI7Mf2uv4RuA14S7w9n0oo8/sisu6EzSKSC/wy\nNpHuC7cormwfap8rn1PtMz1Q+0wmG1R8fRCYx944Z5sCPpBQZhH4/YTPeVh5mtfGP/8z8JernP/t\nwIVl+zzYbNqvTmhDB/FsLfF9F4F/TficFW/bz8Y/N8Tb9b6EMtnAdWcf8Ip4Owvjn/8C+NyytrwM\nm8DUE//8HuDRddy3/xxvTwzoBk5uVe1WN7VPtc/dtal9bs4+l7Xh9o3e983MyX0f+BWWvjqOLStz\n1vnFGDMjIiGgIr7rc8A/ichJbBLPrxtjHK2i40BrvHwiXmy+tMfin8+b+JXHGVxW56KIjCbU6fCj\nhDIxETmDVc1diePAMRF5R8I+55qbgDZjzGeAz6xyfCLfj58vCPwi8I8icpcxZmQdxyobQ+1T7TOd\nUfvcuH1uic04ubAx5lavmMtFG10JEGPMwyJSj+09vhr4noh82hjzfqye0Rngbdw8/jp8i/OvWuct\nWC0iKB/4AvDJFdpyfR3nvVGBMbPY3lMH8IyIXAbux6rlKslF7VPtM51R+9ygfW6VlOjJGRu19UXg\niyLyJHas9/1YKYafBYaNMdPbUPU92EgdRCQbOImVlliJ54Cj6zDIzZCF7V0paYjap9pnOrOH7XNT\nSxQ2E3jiFZHKZdutZBdcROTDIvImEdkvIkeBN2AlHQC+hJ1E/ed4ZE6jiNwXj8pZPgm6Gd4jIm8W\nkYPAZ7HyJA8mNi/h948BLxGRT4nIcRFpEZGfEpHEidP3iMhjrIKI5InIR0XkbhGpF6vN9NfAPuyE\nrJJ81D5vXIvaZ/qh9nnjWta0z3iZEhE5DhyNn/9Q/HyV6230Zt7kXg/0LdvXBhyJ/76StzUJ++eA\nB4BGYBYr8vhzYIdNxIalfgz4J6AA6MWGj06t0abV6lz++QPx7TjQDrzRGDO20jHGmLMi8grgo8C/\nYW/wVeArCeWDQPMa7YphI6B+Pl52FPgx8DJjw7WV5KP2eQO1z/RD7fMGt7JPgDdhHalzDxz9uw9j\no0JvierJKYqiKBnLnshdqSiKouxN1MkpiqIoGYs6OUVRFCVjUSenKIqiZCzq5BRFUZSMZUtOTm7o\nIznbiIh8R0SOJauBYvWu/mOd5RZF5LPL9h+P76/fQJ2Pi8ifbbK9rxKbqXtKRHpF5I9FRDsTKUDt\nc8VjT4vIY2Kzz4+J1epSxYEUoPa56vG/ICIviFU7GEhcW7cZkvHw/Q5QCVRhs1svAN9MwnkTWe86\nhwhwv4i0bPL4LRF/WHwLmzn8DuCt2HUef7wT9SsrovYZR0QC2PvRic02n5ilPnsn2qDchNpnAiLy\nP4A/wK4FPIJNXfbIlk6ahKzaX10h03QMKEvYV4tdBDiOXZH/daAh4fv7gKeB6XiZJ4A64J3YzNOx\nhJ8/v0pbfg+bSuZh4CsJ+4/Hj6tP2Hcb1hGFgAFsipzShGtaXmf9Ou/HR4Gnl+17AzYLeGAr91o3\ntc8k2OfJePmaZXXFgOZU/7322qb2eVMbiuPPyvuSeZ+TOowmIvnAO4ArJq4qLLfQOIr3IL8GPB6/\nefcAf47tPTwE/ClwHtvbqWbpivmV+ADwM2KzdK/UxiJsBoBngRNYXaYKbqQx+g2sVtJfJNTZHT/2\nmoh8aI26vdjeUCIRwId9wCgpRO2TNmxWk/tFJFdE/MC7sWmhOm/RbmWbUfvkNdjMKHUickGseOtX\nRKT2Fm1ek2QkaH6j3JB2CGBT1rwh4fu3YDOr/JKzQ0Tux/Y47sPerELgW8aYzniRtoSy08CCMSYx\ni/aqGGOeF5F/wA4RvmaFIr8OPGeM+d2EOt4NXBeRFmNMu4jMATMr1NlOXKBwFR4BfkNE3oqVa68G\nnHqq19N+Jemofd6oe1pEfgL7JuA8bC4DrzPGLK6n/UrSUfu8QTNWp+53gPdiU5F9FHhURI4ZYxbW\ncw3LScab3PeB27GvtXdhNY4eFpG6+PeuxpGzYXuTXmC/MWYc+FvguyLyDRF5r4hUbbFNHwReLiKv\nXuG748Arl7XnIrbns3+tkxpjXmOM+ewa3z8K/BZW8ykKXMLO0Qn2tV3ZedQ+44iID/gr7HDWXcC9\nwDng2yKiqgOpQe3zBlnYF6//Zox5zBjzDDYvZyvwE5u5EOekWyVsjLlmjOkwxpzBDn8EsOKLcEPj\nyPlDOtsB4MsAxph3YV+zn8L2XC6LyF2bbZAxpgP4S2xvRFiaHTsf+MYK7WnFJhLdEsaYTxhjSrBj\n4sF4XQDbIYmi3Bq1zxu8HTuX8y5jzHPxh8jbsSKWP7XFcyubQ+3zBv3xn25ycGOFe0eAdUd3Lme7\n9OQWAX/893VpHBljXgBeAD4mIj/ECv89g826vZnIr49gX4/fytLooOeAnwa61hii2WydLsaYAQAR\neRtWJPC5rZxPSSp71T792GtPxMnurstc0oe9ap9PxX8eJK7UICKl2JeFrk2cD0iOYSfqIx0CPoXt\niThhsGtqHMU/PyAi94jVtHottlfgaCR1Ak1i12uUiYhnPY0yxgwBf4Yd203kM0Ap8JCInBKRZhF5\nnYj8tYg4PZZO4G4RaZAErScR+Z6I/Npa9YrI+0TkNhE5IiK/ixUz/G8mHj6k7Dhqnzd4FCgRkc+I\nyCGxemQPYlWhH19Pu5Wko/Z5o84r2LfET4rIS0TkNuxQ7AW2Yp9bCc3E/oPEErYJ4EfAm5eVq4iX\nHQRmgCvA57GvvhXAV4EerD5SB/ChhGM92CCOMdYRArtsXz4whF17khgCux/4P9ix7Wls9NGfJnzf\niu1VhEkIgV3etlXa8b14W8PAD4HXbuUe66b2mWT7fBV2WGkM+/B8FDid6r/VXtzUPldsRz42MnMU\nGMZGbdasdcytNtWTUxRFUTIWHYdXFEVRMhZ1coqiKErGok5OURRFyVjUySmKoigZizo5RVEUJWNR\nJ6coiqJkLOrkFEVRlIxFnZyiKIqSsaiTUxRFUTIWdXKKoihKxrItKgTxpJyvwybqXK6Uncn4gEbg\nERNX9lXSD7VPtc90Ru0zufa5XVI7r8Nmz96rvJ241pOSlqh9qn2mM2qfSbTP7XJynQB/93d/x+HD\nh7epivTj4sWLvOMd74D49StpSyeofSppSyeofSaL7XJyEYDDhw9z4sSJbaoirdlLQwy7EbVPJZ1R\n+0wiGniiKIqiZCzq5BRFUZSMRZ2coiiKkrGok1MURVEylu0KPNl2jDEYY4hGo4TDYWZmZohEIkQi\nEaanpwmHwxhj1n2+/Px8gsEgxcXFBAIB/H4/IgLg/lSURBz7isVizM3NEY1GmZmZIRwOk5WVRXZ2\ntms7WVlZ+Hw+cnNz3TLT09NMT0+zsLCAMYbc3Fzy8/MJBAJuHSJCVtaNvmhubi4FBQXk5+eTnZ1N\nVlaW2qeirMGudnKLi4uEQiG6u7vp6+tjaGiIoaEhrl+/Tnd3NwsLC+s+X1NTE6dOneLo0aPU1tbi\n8/kAdXDK2iwuLjI3N8fExATj4+P09PTQ09NDTk4OPp+P7OxsALxeL8FgkMLCQrdMZ2cnXV1dTE9P\nA7aj1djYSE1NjXv+nJwccnNzXTssKCigubmZhoYGvF4vXq935y9aUXYRu8LJOT1mY4zbYw6Hw4TD\nYfr6+rhy5QpdXV309/fT29tLR0cHV69eJRaLrbuOAwcOMDc3x/z8PNFoFBFxe9XLe8vq+PY2zptY\nNBolFosRDofp7++nv7+fzs5Orl27RllZGTU1NeTk5BCJRMjKymJ0dJS8vDyuXr1Ke3s77e3tXLly\nhampKQAKCwtpbW2lqamJnJwc18Hl5uZijGFhYYGCggJCoRCRSIRgMEh5eTkej4fc3Nwlb3yKolh2\nhZNziMViDA0N0d/fz7Vr1+jo6HDf4kZGRtzhn4mJCRYXFzd07pGREc6cOcP4+Dh9fX0MDg7S0tJC\na2srXq+XnJwcdW4KAL29vVy6dImRkREikYj7Btfb28vk5CQTExPcc889nDx5Eq/XS29vL0NDQ/T0\n9DA5OUl/fz99fX2MjY0RCoWYn58HIBQK0dnZyeTkJMXFxRQVFbl2Nzs7y+TkJACXL1+mtraWEydO\ncOLECYLBICUlJfpWpygrsGucnDMsNDAwwLlz53j22Wc5c+YMPT09TExMMDs7u6Xzj42NMTY2Rnd3\nN6Ojo0xMTBCLxSgtLaW4uJi8vDx1dHuQxFEEZ4i8t7eXp59+mq6uLkKhEKOjo3R2dtLX1+ced+TI\nEcrKyvD7/QwPDxMKhbh06RLt7e1MTk4yOTnpzrdlZ2ezuLhINBqlv7+f4eFhqqqqqKqqAqztT0xM\nMDAwQDgcxufzUVpaSjQapaSkhKysLAoKCtTJKcoK7AonF4vFmJ2dZXx8nHPnzvHYY4/R2dlJf3+/\nO3GfLCKRiDufNzw8zPPPP8/p06e55557qKioIDs7251nUTIfZ5hwbm6OqakpJicnuXz5MleuXOH6\n9euEw2FCoZA7r+YwMTHBtWvXKC0tdYe+RYS5uTmKioooLy8nGAxSUVHB3NwcQ0ND7rBlVlYWgUCA\nvLw8QqEQExMTTE5OMjc3x+LiIvPz84TDYXp6ejh79ixer5fKysolASuKolh2jZObmZlhdHTUdXJT\nU1PEYjEWFxc3FEV5KyKRCNevX6e3t5fnn3+e7OxsJicnaWpqcnvNyt7BGUGYmZlhYGCA3t5erly5\nwpUrV+ju7mZmZoa5ubmbbHBycpJr164xNzeHz+dzndz8/Dzl5eXU1NRw6NAhjhw5wvT0NBcuXKCv\nrw8Rcd8YFxcXGR8fZ3x83B3WNMbc5OSqqqq47bbbUnSHFCW9SWsnl7hMYHh4mGvXrjE0NEQ4HGZu\nbm7b6ozFYm5YOEBPTw/nzp0jJyeHuro6SktLt6VuJf1YXFxkdnaW0dFRzp8/z5kzZ7hw4QLDw8Ou\ng1tcXCQ3Nxev10tRURFFRUUcOHCAhoYG9u3bh9/vp7y8HICGhgbKy8upqKigpqaGmpoaotEoZWVl\njI+Pu/UuLCywsLDA+fPnERH6+vqYnJxkdnbW/b9w3jCdJQiKslGcl4RoNMrk5CTj4+P09vbS29vr\nBu4FAgFKSkooLy+nurqaysrKXbW8Kq2dHOD+AQYHB+no6GBsbGzDQSVbZWhoiBdeeAGfz0dhYaE6\nuT2EEz05PDzM2bNneeSRRxgdHSUcDjM/P8/i4iJZWVl4vV4KCwtpaGigsbGRY8eOcfjwYSoqKvB6\nvSwuLlJfX8/s7CwFBQUUFBTg8/nw+XwsLi7S3NzsDrs7Dmx+fp6CggLC4TALCwtEo9Etzz0rSiKO\nrTkjA+3t7fzwhz/khz/8IdFoFICqqipaWlq47bbbuOeeeygvL79p/WY6k9ZObnZ2lqmpKa5fv875\n8+d5/vnn6e/vv+XSAGfeLBAIUFBQgDGG2dlZIpGIu0xgIz1f5wFXUlLCwYMHt3pZyi7CGa4Mh8OM\njIzQ09PDzMwMAB6Ph/z8fAoKCtz5tYMHD3Lw4EFaWlqora2luLjYXbQdDAYB3PVtq/WCE0cTuru7\nqa+vZ3h4mOHhYYwxiAiLi4tMT08zNDTE+Pi4O7qhc8bKenBGA6amphgcHKSnp4fLly9z+fJl2tvb\nGRsbc5fIOJ0rYwyNjY3Mz8+Tk5OjTi4ZhEIhOjo6OHv2LE8//TRPP/004+Pjazo5ESE3Nxefz0d9\nfT1NTU3EYjEGBwcZGRlhYmKCqakpd85jPYyMjDA3N8e+ffvc4ABlb+A4nLm5OWKx2JLOkd/vp7q6\nmtraWhoaGmhqanKdXElJCYWFhXg8HkTEnWsD1vVwcNZmFhYWUlVVRTAYdKMnnTaNjo4yOztLd3e3\nG2Hs9/vVySm3xLGhoaEhzpw5w4svvkh7ezvd3d3k5eVx+PDhJWuSh4aGuHLlivssFBFyctLafbik\nZSudceLJyUmuXr3Kiy++yMWLF7l69eqqx+Tk5OD3+8nLy6O4uJiSkhIOHDjA4cOHicVi9Pb20tfX\nx8DAAIODg0tSKi1/eC3HKTs4OEgkolJcewEn+CMajTIyMuKugVvu5JyhnMOHD3Po0CEaGxvdxdyb\nxXGKYN/68vPz3SUsie1z7DLxTU6XESjLcd7anAA+561MROju7uaFF17g2WefZWRkhHA4TE1NDbfd\ndhuRSISJiQm6uroYHBxkYGCAUCjkBvztFtLWyc3PzzM6OsqVK1e4dOkSo6OjK5Z1xoYLCgpoamqi\nqanJnReprq6muroaEXHXM12/fp2uri6uXLnC5cuXmZqaYnp6ekPZUZTMJxaLuTZ49uxZ/vVf/5Vr\n164tsRO/308wGKSuro7m5mZaWlooKipK6jDOwsICkUiEaDTqPlh2w2S/kj44maJmZ2fdTDtO56mt\nrY22tjYGBwcpLy/n6NGjnDhxgpMnTzI6OkpPTw8LCwt0dXWl+jI2TVo6OWd4aGxsjPb2di5fvuxm\ne1iO89rsRLTdddddHD16lKNHj1JQULCkBxwKhbh27Rrt7e34/X6mpqYwxhCJRNTJKUtw5uLGKSsN\nBAAAIABJREFUxsa4cOECTz31FOFwmFgs5joZj8dDcXExlZWVVFVVUVFRAdi5ZGduLCsra91JlJ0e\ntxMMEIvFmJ6eZnJy0g0+2U1RbUp6sLi4yMLCAjMzM1y9epUnnniCQCBAeXm5m4ZuamqKo0ePctdd\nd3H69GlOnz5Nb28vBQUFjIyMkJeXt20R7dtNWjq5ubk59597cnKSUCjkRvosx+PxUFRURE1NDUeO\nHOH06dNUVFSQn5+Px+NZ0qv2eDxUVFRgjGFiYoJoNMqLL77I9PT0qudX9ibO8M78/Dyzs7PucGDi\ncGU0GmV0dJTLly8zNjbG888/735XU1NDQ0MDZWVlFBQU4Pf7b1mnM5w0NTXlpq27ePEiFy5coLOz\nU+eDlU3hvAjk5OQwPT1NX18f8/Pz5ObmMjc3R0lJCY2NjZw6dYqTJ09SU1NDdnY2+fn57Nu3j4qK\nCnw+nzq5ZOIsdp2amnIDRVabM0t0ckePHuX06dM3yZwkli0vL6egoMBNwhwKhWhvb9+Jy1J2EYkB\nJ7Ozs0xPT99kg5FIhJGREQDOnTu3pKN08uRJ7r33XsDa3Xqc3MLCAqFQiIGBAZ555hkef/xxenp6\n3LmQ3fqQUVJLopMLh8P09va6829lZWW0trZyxx13cPLkSU6cOIHH43GdXHV1tevkdmsnKy2d3Pj4\nOFevXnVzA64VFOLMyTkZ29eaeBcRsrOzyc3NxePxaOJlZVUShw5Xy6ozMzNDf38/U1NTRKPRJU4o\nOzvbnbi/9957KS4uXrUuJ9J3amqKtrY2zp07xwsvvOCuC3UcXOJkv4i46+0qKirc3JUaWaksxxn+\njkajS5YD+P1+ampquPPOOzl58iR1dXVLdDSd5+pKLwy7ibR0cmNjY7S1tdHZ2XlTTkBFSRdmZmbo\n6+tzEywnOsKZmRm6urqIRqO0tLTQ0tKy6nmcOZOJiQnOnz/vBrn09fURjUZZWFi46fxZWVmUlJRQ\nW1tLdXU1RUVFS/TrFMXBSQXnOLm5uTl3jef+/fs5deoUp06doqCgYNesfdsIaenknIiy9QSEZGVl\n4fF43FdsRUkGTi/WeRgUFRW5UY6Os3FSbznh2Ik4QqpXr17l6tWrbnovR4wX7HCnMxTqzMO9+OKL\nbjTx9PT0TaHaztBTIBCgsbGRO++8k/3791NQUKCjEsqKzM/PL1FYmZmZoby8nKamJlpaWqivr6e8\nvHxdAVK7MX1cWjq53Nxc8vLy8Pv9t1xvlLg+Ljc3d4daqGQ6WVlZ5ObmEggEKCsro6qqitHR0ZuC\nTxKleBIfEM7ay5GREc6fP++uqXNyWILNpDMwMODqy3V1ddHW1kZ/f/8SZ5pYV3Z2Nj6fj+LiYg4f\nPsx9993H/v373QTQirKcaDRKb28vFy9epLe3l1AoRHNzM4cOHaK1tdVd9rJWBp7En7uNtHRyeXl5\nBINBSktL8Xg8a5Z1HkY5OTluDjaH7OxsN/1M4gLbjeLM9QUCgV2zyl/ZGk7mHCfCrLW1FRFhfHzc\nfbta658+MSvJ+fPnicVi1NbWuhpxIkJ/fz89PT309PTQ3d1Nf38/Y2NjKy6XcerKycmhuLiYmpoa\nWlpauP322yktLcXn86mTU1Zkbm6OkZEROjs73Ywl+fn5NDQ0UFtbS35+fkYOUzqk5RO7pKSElpYW\nenp6yM/PX7Os8zCJRCKMjY3R09PjfufkFXQCTDY7nFlcXEx1dTV1dXWq2bVHcIYri4qKOHToELOz\ns8zNzdHR0eEmUk5M1bWag5mcnKStrY3h4WEKCgqW2LOjRTc1NcXU1BThcHjVjDpOXT6fj9raWo4e\nPUptba1r35n8kFK2RuLSFCfvpN/vp6ioaF0d992+NjNtnFxiNFteXh7V1dWUl5cvmcNYiUQRyYGB\nATo6OtzvysrKlqyZy83NJSsry11ou14tOsfpNjQ03NLpKpmBs4i7oKCA5uZmjDFcuXJlSaTZ8iHK\nlR4CjgNbq8xyG1ytjIjg8/nYt28fhw4dorq6mkAgcMvRDmVv46Snm52ddQV8CwsLKSoqIj8/f0PT\nPLvR0aWVk5uZmSEcDtPe3k5bWxvPPPMMw8PDax7nhHEvLCy4yuEOy52cE25dVFTE9evXGRkZWVdK\nr8rKSu644w4OHz5MUVFRUq5X2R04veBELbdUkp2dTV5eHkVFRUvCvRVlNbxeL1VVVRw6dIjS0lIa\nGxs5ceIENTU1FBQUZHwsQ1o5OUfOxAmjdsQp12J2dpZoNMrQ0BCXLl1aMiRZVlZGeXm56+SCwSC3\n3XYbzc3NDA0NrdvJVVRUuE5urfVOSuaxuLhIOBxmYmIiLZJzZ2VluUnIdR5OWQ8ej4eqqiqi0SiN\njY3Mzs7S0tJCTU0NhYWFGW9DKXdyznKBUCjEuXPnOHv2LGfPnnWTht5KJDJRe2t+fv6m753M7Dk5\nOQwPDzM9PU1HRwehUIhQKER3d/eKD6+srCyKi4spLi6mvr6eyspKioqKMr7Xoyxlbm6O0dFRuru7\nmZycTHn29bm5OYaGhrh69SrBYDDl7VHSH6eD70zVLCwsUF5ejt/v3xNzuSl3crFYzE1l9Oyzz/Lw\nww/T19fH8PAwMzMz7iT/ZohEIszPz7vRlTk5OfT29uLxeIjFYkvW4y3HEbncv3+/m4MwLy9P1+Lt\nMebn5xkZGaGrq2tJZGWqiEQi9PT0cPHiRZqamlLeHiX9yc3NpaysjMLCQjfuwVlbvBdIuZNzwlsd\ndQBHcSASiWz5H9h5w0skFAqt61gRWaLl5fF4dLHtHsKxnVAoRH9/Px0dHa6T83g8+Hw+SkpKqKys\npKCgwO00OfPKztydo27vTPonEggElgQBeDweN1fmwMAAAwMDN9mv0yYn92Cq5wiV9MdRxLhVEF+m\nknInF41GGRgYcBfBTk9P37TgNlU4Q6BOVgtl7+AEnIyPj9PT08PVq1eZmZlhcXGRQCBAMBjk9ttv\n5+UvfznNzc1EIhHC4bC77s1xToODg7S3tzM0NAQsjU6rra2lsbGR1tZWDh06RElJCWNjYwwMDPCD\nH/yAkZGRJU7OyaO5sLDA/Py8ykMpyjpImZObn5935zs6Oztpa2tjYGCASCSypSHKZOHozE1MTBAK\nhdyhz62st1N2D4uLi8RiMaLRqKuI4XR2fD4fZWVltLS0cO+993L8+HFmZmYIhUJ0dnbS2dnp2nBv\nby/5+fn09/ffVEdTUxMHDhzgyJEjHD9+nLKyMvr6+ujo6KC9vX2JnSVmnXAc3XqXwChKstiN9pYy\nJxcOh+nv76etrY0LFy5w8eJFhoeH06Z3GovFGBsbY2Fhge7ubgYHBykuLl63Npiyu8nOzsbj8SxJ\n6+XoG+bm5uL3+92s/1lZWXi9XkSEhoYGiouL3aH21tZWjh07RigUumm4sqioiNLSUoLB4E1LU5aX\ndRaDO5l7EjdF2Ql2o4ODFDo5p9d77tw5Lly4wJUrV5IyD5csHGHViYkJV9OrsrISr9erTm4P4CT+\nDgQClJaWUllZSSwWY2pqys2Gkhitlp2d7c6x1dTUbMr5zMzM3LRvIwvPFWU72K3OzSFlTm5kZIQf\n//jHPPnkk3R2dqbNMOVKTE5O0tXV5Qqu6oLwzMfRHnQET53MIiLC5OQk165do7CwkLKyMubm5qis\nrKS8vByv17tnotaUvcFu71ClzMkNDw/z4x//mCeeeMJNs5WuPYapqSmuX7/Ovn37qKurS3VzlB1g\nuZNzEgo4Ti4UCpGdnY3f72dhYYFjx46Rl5cH2JDt3f5gUJTl7Nbh8ZQ5OSefWjpkkbgVjuRKXl6e\nqhDsEZx/Zq/XS3V1NQcOHGB8fNxN0Ly4uMjo6CiXLl0iEonQ19fHpUuXqKqqorq62l1yUlhYSDAY\nXFfOUyfSuL29nZGRkRWH7nNycsjPz6e0tJS8vLxd+dBRlJ1En9jrwO/3U1ZW5q5lUvYOPp+Pmpoa\nDh8+zLVr15ZkiJicnOTy5cv09vZy/vx5SktLOXDgAAcOHCA/Px+/309dXZ0rvHorIpEIvb29XLhw\ngaGhoVWdXGFhIeXl5QQCAXVyinIL1MnFcRZ+O1FyTsSc1+vl4MGDNDY2UlFRsWcXVO5VcnNzKS0t\npa6ujubmZg4cOMDQ0BCTk5NEo1GmpqYIhULu+jZnbV1eXp6rGNDf309lZSVwI/ekI3HiLBNYXFyk\nv7+f8+fPc/HiRdfJOUP4gUCAkpIS6urqOHbsGLfffjtVVVV7Ii2Tkhrm5uaYnp4mHA6nTdT7ZlAn\nF8cREQwGg2RnZ7sPt7KyMo4fP86RI0eorq52512UvUF2djb5+flUVFRw+PBhZmZmuHDhApcuXWJs\nbIz5+fklck9dXV2Mjo66DiwvL4/CwkI3mXJOTg61tbXU1ta6jhBsDtehoSHOnDnDpUuXbkocXlJS\n4jq3kydPcuzYMUpLS3XNprJtzM7OMjIywvj4ONFoNNXN2TQpc3I+n49gMEhlZSWhUGjF8Omt4miC\n5ebmuurezrZc7r2qqorW1laqqqrcgIOKigrKy8tpamqirq5OteT2II6jKisro7W1ldzcXDweD/Pz\n8/j9fqanp10lDGcbHR11j18eTJWbm0tTUxONjY3ukCbgSkVduXJlxYXjgUCA2tpaDh06xKFDhzh4\n8OD2Xriy55mdnWV0dJSJiQnm5uZS3ZxNkzInV15ezt13383CwgIvvvgibW1tSa/DWbRbUlJCRUUF\nVVVV1NTUuIEBiVFwjtZcYWEhWVlZ7sPN0e7Subi9yUoLvX0+H8XFxXR1dTE4OEh/fz+9vb0MDg7e\ndPxy9XAnYGVhYcENTgFcdfvx8fFV27Jbo9uU3Yljj46i+G4lZU4uGAxy6tQpRIRQKERXV5ebFNfJ\nlL0RnLe2xDmKgoICiouLqa2tpbm5mYMHD3L06FEOHjyI3+9fosfl9NAdx6cPEwVYMjdbUFBAbW0t\nhYWFVFRU0NnZybVr17hy5Yq7UHxxcdHdVrJjYwzj4+NLnNl6lMGdjpezCF1RtpvEObn5+fldOzSe\nMieXl5dHTU0Nc3NzhMNhAoEAvb299PT0EAqFCIfD61oc7gwt5ufnEwwGKS0tdb/bt28f9fX17Nu3\nj3379lFdXU1lZSUlJSXk5OQs0YZzMnWrc1NuhePs8vLyqKqqor6+ntraWlpaWhgdHWV0dNR1ZNFo\nNClrQAOBAHV1dTQ2NmoyAmVHCAQCVFRUEAwG8Xq9zM/Pp+1a5rVImZMLBAL4fD4CgYArz37mzBk3\nymy9GVBycnLcEP/W1laam5vd7w4cOMDRo0fZt28fJSUlBAIBN9fgSrkBFWU9FBYWkp+fT3V1NfPz\n80xMTNDU1OQmVm5vb6ezs5NoNJq0RMrOnFxTUxMFBQVJuhJFWZ28vDwqKyspKytzndxuJGVOzok0\nc3L9Oc6qpqbG7QmPjY0xOjpKOBx2Ix7LysooLS11h2xyc3Px+XwUFhayb98+Kioq3Dqqq6upqamh\nuLjY1YRTlK2SODTuzKnV19fj9/sJBoM0NjbS2dlJR0cHw8PDTE1NMTU1xfT0tCsllRit5vV6CQQC\n5Obmutl//H4/fr+f3NxccnJyaGlpobKy0s28oijbjdfrpaioiIKCgl1tcylfQuBEMRYVFVFbW8vJ\nkyeZnZ1lZmaG7u5ud2GskyzXiSxzhhqd9EuOk/R6ve65vV4vPp9P5XGUbcGxPb/fT2VlJaWlpTQ2\nNhKNRrl+/TodHR309PTQ399Pf3+/+/vU1NQSzUQn0jgQCDA7O8v8/Ly7fMUJfjp48CAVFRX4/X6d\nk1N2BK/X645a7OZUdSl9kwPch4TzNmaMcUUhnXRIIyMjeDwe8vLyaG5uZv/+/Tel13KCRfQBoOwU\njg3n5OTcZI9OcoGqqiqGh4cZGhpiYGCAoaEhQqEQ09PTrpMrKCggGAzi9/vdYfri4mJ3BMLn89HQ\n0EBZWZmmlVN2DCfewXFwznrQSCRCTk7OTcoY6Upa/cc4jsqJIHMyjEQiEXdoqKCgYMVexW642cre\noaCggJycHILBIJFIhNnZWXdzOnGOk3OG3HNycojFYiwuLuLxeFy9OmdBeklJSYqvStnLLC4uEolE\nCIVCbj7f3UDaOLlEJ+X8Y+fm5lJYWJjCVinK5nDm1BRlN+O8dPh8PrKzs5mYmKC7uxvAHcZM96h0\nHdtTFEVRbsIZPcvLyyMYDJKXl0dPTw9PPvkkly9fZnx8nEgkkvZ5LdPmTU5RFEVJHxwnl5+fT2Vl\nJb29vQwMDDAxMUFxcTEtLS14PJ60j7xUJ6coiqLchOPkKioquPPOO8nKyqKtrY3BwUFmZmaSsv5z\nJ1AnpyiKotyEs0SmvLycO++8k5ycHPr7+7l06RIzMzNJyeSzE6iTUxRFUW7CCSZx1nEeOHCA++67\nj9raWk6cOEFJSQk+ny/tl22pk1MURVFWxePxuOob5eXlvPzlL6eoqIiioqJdkWhju5ycD+DixYvb\ndPr0JOF6VT48vVH7VNKZtLfP6elpent7k3rO7bJP2Y4xVRF5G/ClpJ949/B2Y8yXU90IZWXUPtU+\n0xm1z+Ta53Y5uTLgdUAnEEl6BemLD2gEHjHGjN6irJIi1D7VPtMZtc/k2ue2ODlFURRFSQfSOyxG\nURRFUbaAOjlFURQlY1EnpyiKomQs6uQURVGUjEWdnKIoipKx7LiTE5FFEYnFfy7fYiLyoZ1u0wpt\nPCEiD4lIt4iEReSciPxqqtulbD+7wT4BROQlIvK4iEyIyKiIfEtEjqa6Xcr2shvsU0R+eZV2zovI\njguEpiKtV1XC728FPgwcABzVvemVDhKRbGPMTgkXnQZ6gJ+L/3wF8HkRiRpj/nqH2qCkhrS3TxEp\nBr4N/D3wi4AXeCC+r2En2qCkjLS3T+BvgK8t2/cQMGuMmdqhNtzAGJOyDXgnMLbC/tcBi8BrgP8A\nosBd2H/qLy8r+zng2wmfs4APAdeAMPAs8KYktPUvgX9J5f3SbWe3dLVP4KVADChL2Hcqvm9fqu+b\nbjuzpat9rtCeGmAe+OlU3Kd0n5N7APhN4DDQts5jPgz8DPAu4CjwWeArInKXU0BE+kXk/RtsSxEw\ntsFjlMwmVfZ5AZgE3i0iOSKSB9wPPG+M6dv4ZSgZSro8P38B++z8xgaOSRrprEJggN8xxvzA2eFI\nP6yGiASA/wm8xBjzQnz3X4nIfcAvAc/E910G1p02Jn78m4BXrfcYJeNJmX0aY8ZF5JXYIaE/xPa+\nz2N78IoCafT8xDq5LxpjFjZwTNJIZycH9lV5IxzE5j97Qpb+RXOBf3c+GGNesd4TisidwFexBvPk\nBtujZDYpsU8RyQf+CvgudrjJC3wA+BcRuccYM7/BdimZSTo8P38CaMbaa0pIdycXXvZ5kZsjQnMT\nfs/H9mBexc09jQ0nOhWR49gHyZ8YY/5so8crGU+q7PPnsfNxv+zsiGeunwB+khQNCylpR0qfn3He\nDfzIGHNpk8dvmXR3cssZBu5Ytu8OYCj++1lgAag3xvx4KxWJyB3Ao8CnjTF/tJVzKXuGnbLPPOwD\nKxET39J9nl1JHTv2/AQQkSLgvwDv2eq5tsJu+4f4PvBSEXmLiLSKyANAi/OlMWYc+N/Ap0Xk7SLS\nHF/z9l4ReatTTkSeEJH7V6sk7uAew855fF5EKuNb2bZdmZIJ7Ih9Ao8A+0TkEyJyQESOYcO2p4An\ntuPClIxgp+zT4R1Yp/mVJF/HhthVTs4Y8w3g48AnsGPEgg2LTSzzW/EyH8RGoX0LeC1Wm8lhP7CW\nw3oLUIKNWOtL2PQBoqzKTtmnMeYs8Gbses6nsQ+vYuD1RnXilFXYweenw7uAh4wxM1tt+1ZQPTlF\nURQlY9lVb3KKoiiKshHUySmKoigZizo5RVEUJWNRJ6coiqJkLHvCyYlIQ1zq4fY1yrwiXmbHpSCU\nvY3ap5LO7Hb73JCTE5EHV9AJionIt7ergUlkPWGk2xJqKiIfEZE+EZkRkUdFpOXWRykbRe1z44hI\nhYj8jYj0itVO/Lba5/ag9rlxkmGfm3mT+w5W08jZqrG6a+nO2tlJt6tSkd8Gfh34ZazcRRh4REQ8\nqWjPHkDtc2P8M9AIvBGb/eI68JiI+FPUnkxH7XNjbNk+N+PkosaYYWPMUMI26XwZ753cLyJfjXve\nyyLyxoTvi0XkSyIyFH+zaRORdyZ8XysiXxGRcREZEZGvi0hDwvcPisjXROR3RGQgXu6DIpItIh8X\nq5LcLSK/sELbD4vIUyIyKyJnReQ/rXWhIvIyEfm3eDu7ROSTYmVNNsJvAH9gjPmmMeYcNu/gPuxi\nXiX5qH2uExFpBe4GfsUY85wx5grwq4Cf3fHg3Y2ofa6TZNnnds3JfQirBHsMq1b8JbFqxmClQQ5h\nZUEOYRs9AiAiOdiURZNYYciXAiHg4fh3Dq/E9oBeDvx34CPAv2A1i+4CPg98QUT2LWvXx4E/wfYI\n/h34poiUrHQBIrIf2+v6R+A2bBaUlwKfSijz+yJybbWbICJN2N7a95x9xirjPg28ZLXjlG1H7dPi\nxQ4xRZ0dxmaHiAIvW+M4ZXtR+7Qkxz43qPD6IFbhNZSwTQEfSCizCPx+wuc8rGLxa+Of/xn4y1XO\n/3bgwrJ9HuwQ36sT2tBBPFtLfN9F4F8TPmfF2/az8c8N8Xa9L6FMNvbV933xz6+It7Mw/vkvgM8t\na8vLsLnYPPHP7wEeXeN+vSR+zspl+78C/P12qODu5U3tc8P2mYNVgH4ImxbMA/x2vC3fSfXfM9M2\ntc/U2OdmVAi+D/wKS8dolytmn3V+McbMiEgIqIjv+hzwTyJyEitj83VjjKNVdBxojZdPxIvNl/ZY\n/PN5E78LcQaX1bkoIqMJdTr8KKFMTETOYFVzV+I4cExE3pGwz7nmJqDNGPMZ4DOrHL8WwjYFuShq\nn6zTPo0xCyLy01itrzHsA+gx7NuDsj2ofe6wfW7GyYWNMWu9YoLtrSTiSoAYYx4WkXrgPwOvBr4n\nIp82xrwfq2d0BngbN090Dt/i/KvWeQtWczb5wBeAT67QluvrOC/AQPzYSqwhOVQA/7HOcygbQ+1z\n/faJMeY/gBMiUoDtYY+KyI+ALUutKCui9rnD9pkSPTljM6V/EfiiiDyJHet9P/Ac8LPAsDFmehuq\nvgd4EkBEsoGTWGmJlXgOOLoOg1wVY8w1ERnAihC+GK+3EDuZupk3QGUH2Cv2mYgxJhSvtxU4Bfyv\nZJxXST5qnxuzz80Ennjlhr7ahnXWROTDIvImEdkvIkeBN2AlHQC+hJ1E/ed4ZE6jiNwXj8pZPgm6\nGd4jIm8WkYPAZ7HjvA8mNi/h948BLxGRT4nIcRFpEZGfEpHEidP3iMhjrM0ngA+KyBvF6n59EejB\njq0ryUft88a13NI+ReS/il3I2yQiP4UdAvuqMeZ7ax2nbBq1zxvXsiP2uZk3uddjtdUSaQOOxH9f\n6fXVJOyfAx7Arn2YxWq0/RyAMWZWbFjqx4B/AgqAXmx04tQabVqtzuWfPxDfjgPtwBuNMWMrHWOM\nOSsirwA+Cvwb9g94laUCgEGgeY12YYz5uNiw2S9gjeIJ4CeNMXNrHadsGrXPG9zSPrFRdn+GHULv\nB/4WG8GnbA9qnzfYEftUPTlFURQlY9kTuSsVRVGUvYk6OUVRFCVjUSenKIqiZCzq5BRFUZSMRZ2c\noiiKkrFsycnJDX0kZxsRke/E14MlBRH5PRG5ZXaQeLlFEfnssv3H4/vrN1Dn4yLyZ5to6+0i8mUR\nuS428/Z5EXnvRs+jJAe1zxWPPS0ij4nNPj8mIg/LGmKYyvah9nnTce+Um/X2nM/BjZ7PIRlvct/B\npq2qwma3XgC+mYTzJrLedQ4R4H65WVRvp9ZJnASGsIlSj2DXiPyRiPzaDtWv3IzaZxwRCWDvRyc2\n23xilvrsnWiDchNqnzd4iBsae47e3iPY5NEjmz5rErJqf3WFTNMxoCxhXy12EeA4dkX+14GGhO/v\nw8rPTMfLPAHUAe/EZpyOJfz8+VXa8nvYVDIPA19J2H88flx9wr7bsEk+Q9j8kl8EShOuaXmd9Vu4\nR58GHtvKfdZN7TMZ9onthMWAmmV1xYDmVP+99tqm9nnL+xPEyuq8bSv3OalzciKSD7wDuGJsfrVb\nahzFe5BfAx6P37x7gD/H9h4eAv4UOI/t7VSzdMX8SnwA+BmxWbpXamMRNgPAs8AJrC5TBVb3CKzI\n6b9jpSKcOrvjx14TkQ+t/44AUMTNWcaVFKD2SRswiu2t54pVV343Ni1U5y3arWwzap838U6sTNA/\nbeCYm0hGguY3yg1phwA2Zc0bEr5/Czazyi85O0TkfmyP4z7szSoEvmWM6YwXaUsoOw0sGGMSs2iv\nijHmeRH5B+CPgdesUOTXgeeMMb+bUMe7gesi0mKMaReROWBmhTrbiQsUrgcRuRebMPX/Wu8xStJR\n+7xR97SI/AT2TcB52FwGXmeMWVxP+5Wko/a5Ov8P8CVjTPSWJdcgGU4uUR+pFPg1bC/jtDGmm1to\nHBljHhORvwW+KyKPYvWC/sEYM7CFNn0QuCAir2apxATx9rxyhfYYrOZS+2onNcas9EdfERG5Dfsw\n+X2jyW5TidpnHBHxYbW5nsA+PHOA9wHfFpFTW32YKJtC7XMFROQlWK26d9yq7K1IxnBl2BhzzRjT\nYYw5gx3+CAC/GP/e0Ti6HXuDnO0A8GUAY8y7sK/ZT2H/+S6LyF2bbZAxpgP4S2xvRFiaHTsf+MYK\n7WnFJhLdMiJyBGtsnzfG/FEyzqlsGrXPG7wdO5fzLmPMc8aYZ+L7moCf2uK5lc2h9rky7waeN8Y8\nv9UTbZee3CLgj/++Lo0jY8wLwAvAx0Tkh1jhv2ewWbc3E/n1EWyv4q0sjQ56DvhpoGuNIZrN1olY\n+YvvAQ8aYzY6f6fsDHvVPv3Ya0/EyXCva2bTh71qn4AbBfx/A7+92XMkkgzDTtRHOgRoEMouAAAB\neUlEQVR8CtsTccJg19Q4in9+QETuEZF6EXkttlfgaCR1Ak3x9RplIuJZT6OMMUNYiYbl69Q+gx0W\neEhETolIs4i8TkT+WkScHksncLeINEiC1pOIfG+t5QBxB/c4VvPoEwn3ZdNrPJQto/Z5g0eBEhH5\njIgcitvrg1hV6MfX024l6ah93sxbsU7yy+tp6y3ZSmgm9h8klrBNAD8C3rysXEW87CAwA1wBPo99\n9a0AvooVEp0FOoAPJRzrAf4BG6F4yxDYZfvysevWFlgaArsf+D/YSLNpbPTRnyZ834p99Q+TEAK7\nvG2rtCG2wtaxlfusm9pnMuwzXuZV2GGlMezD81HgdKr/VntxU/tc9b48BXwxWfdZ9eQURVGUjEXH\n4RVFUZSMRZ2coiiKkrGok1MURVEyFnVyiqIoSsaiTk5RFEXJWNTJKYqiKBmLOjlFURQlY1EnpyiK\nomQs6uQURVGUjEWdnKIoipKxqJNTFEVRMhZ1coqiKErG8v8DX0wUw10DYywAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ffac9173080>"
+       "<matplotlib.figure.Figure at 0x7fdddcb17710>"
       ]
      },
      "metadata": {},
@@ -2682,7 +2712,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 77,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2692,7 +2722,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.    0.    0.    0.    0.    0.48  0.    0.52]]\n"
+      "[[ 0.5   0.    0.    0.    0.    0.05  0.45  0.    0.    0.  ]]\n"
      ]
     }
    ],
@@ -2709,7 +2739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 78,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2719,7 +2749,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.    0.    0.    0.    0.    0.68  0.    0.31]]\n"
+      "[[ 0.3   0.    0.    0.    0.    0.15  0.56  0.    0.    0.  ]]\n"
      ]
     }
    ],
@@ -2736,7 +2766,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 79,
    "metadata": {
     "collapsed": false
    },
@@ -2745,11 +2775,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 0.    0.    0.01  0.    0.    0.    0.    0.37  0.    0.62]]\n",
-      "[[ 0.01  0.    0.    0.    0.    0.    0.    0.33  0.    0.66]]\n",
-      "[[ 0.    0.    0.    0.    0.    0.    0.    0.91  0.    0.09]]\n",
-      "[[ 0.    0.    0.    0.    0.    0.    0.    0.68  0.    0.31]]\n",
-      "[[ 0.    0.    0.    0.    0.    0.    0.    0.09  0.    0.91]]\n"
+      "[[ 0.3   0.    0.    0.    0.    0.15  0.56  0.    0.    0.  ]]\n",
+      "[[ 1.  0.  0.  0.  0.  0.  0.  0.  0.  0.]]\n",
+      "[[ 0.19  0.    0.    0.    0.    0.    0.81  0.    0.    0.  ]]\n",
+      "[[ 0.15  0.    0.    0.    0.    0.12  0.72  0.    0.    0.  ]]\n",
+      "[[ 0.85  0.    0.    0.    0.    0.    0.14  0.    0.    0.  ]]\n"
      ]
     }
    ],
@@ -2773,7 +2803,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 80,
    "metadata": {
     "collapsed": false
    },
@@ -2837,9 +2867,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/06_CIFAR-10.ipynb b/06_CIFAR-10.ipynb
index de5e49d..8a145e4 100644
--- a/06_CIFAR-10.ipynb
+++ b/06_CIFAR-10.ipynb
@@ -103,13 +103,14 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.10.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -125,12 +126,41 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Load Data"
+    "PrettyTensor version:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {
     "collapsed": true
    },
@@ -148,7 +178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": true
    },
@@ -166,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -176,7 +206,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CIFAR-10 data has apparently already been downloaded and unpacked.\n"
+      "Data has apparently already been downloaded and unpacked.\n"
      ]
     }
    ],
@@ -193,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
@@ -220,7 +250,7 @@
        " 'truck']"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -239,7 +269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -269,7 +299,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
@@ -295,7 +325,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -333,7 +363,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -351,7 +381,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -376,7 +406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -440,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -448,9 +478,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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rr+DBh5hYpiiGaF0WSBlMFLm0KF9Wi4DrWQlfrSCN1d13+gQAYFJF+2Kd0Iq9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AsdhskEjcG9rXuOPGsfSdt7ZEeNnryhJA4JY1lldOAJ7mUSoUCoVCcSjQF6VC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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97dcf58898>"
+       "<matplotlib.figure.Figure at 0x7ff240b9d588>"
       ]
      },
      "metadata": {},
@@ -477,16 +507,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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wmO/fB5TM61cvefXyjqEfgEaNNPp8HSTQePAI1nqsE4ypiFR2u5Grqxd0oSfn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HEyd1eRTZKK1Re21yWjLTvDBNCxqVYRwYy8iQIkGD97KF0DeRtVK/IrJ9//pao4/f9Xru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zOkOCqOpOilHCzZrDF1vqTEVLT/LuQkTOq4OsWMVQzxHp3VhVaXDaoQEUrKNPdtfMzVHsh603TO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5tnVSFpxxw9MShRr5ML5VGrADOcg3H+QdzdKTBw6vEVzyKJSHXZNadWmxfKxhGHB0dPqpQw8p\nj685lrNusGhlzDj1f02qdpXHXFIUrn3wmMfzV/IQHIX6OBU+auPx33z3Cezw8DR0Y+ne0YPDnhbC\nyxPnn76wnBdigPo34Oyf63+9mgjGWLV5w0KDljvrttFEWO+ZtGWFKHMm5Y3SnsltfmSgztPMFGfm\nMOvG4yamvHLPd8gV8SB4jFWSQnFG5SO1aRLIsRE6RxeLH4e3JoYuHmtP+OCIaUJSQnKmGUNzhm4t\nYj9wi97UFzS3Cs7iYyD6GelqZF6yzkJzTkhn+HBaSstsJXPbNr7ebvzl2xu3lnFPJ07PV+brmRA9\ntqOsyNtKvu9YI8wxDCMRIdtPeciPXA9HsoG45SKk2um1YaUTgrKe+zy+vg1osvURo+aYQiD5oIf+\nUtluK3TDcjUKc+LwxuPEjqnWsb9qsfMHUiANaUWZ/L1juxBwVONwgiJiYwTljBs+2hpWgVGj9oPH\nUdvwczWiYQ9Od0PntGuNIWq8GKpiqNVSux1yExlFVVnB1hgtiMEyeYNHXd9s73ir4c/inRKE/lEL\npXoVZmrulNzp1kPTFt0Oa+d+3AxWfQuNcd8RZA6phzxkGSIKL7QBu+rHEUGjqgrgA141VtM3rP2A\nPh+leRRRUQEk1lpar+rSM6BVtakbXrSGhzutsSMA2ljEyGC2jqE29gHxKtTFQ4+pT2pIXuS7/0Yj\ntWz02MnjLgvhcub0+hPL9YkYHE7K/zT6/Fz/++vIE1A7CH2z99zIm+byrffMvmVy0szK2hLGCmIu\n1L4oG895vBe8VRP0EJVc4UzHUIfLks5GREQPU14wBUptGBGwHbGMJA69f8SqWf80WTgthBHhVvcd\n3xpujh+RSq3jaNB5BOra4PVhjwOoQ6qhGL3fNW2+Ubtw21be3r/x7f2Nt/WueYLWEJeZ5elKnGdq\nrrz/8pWaKqTCxUdO55nlHHFGqGlj/+XzEPcjl3XqQIPVSK3cOtuuIc3OaKNQYxzB3CPwvRZK0ZFB\nLwVaxxsLLoyDYCObpP1iCOSU6Lnh0OI2hcjkNLsU6CI9xwAAIABJREFUZGg4Ff07dJXGqA7dGUMY\nMhSVhgyyo3MYpz7D1mieZjdqtN7RzrhbQzeOPmzyrDG4MZ/U95XTUPtuqc5Sm33s9cADsbNjTuuc\nwbZKyxt7b8oILkWf1zwTnaOZ336Q+53TQywWj5WGN06xZePQsjAgx0NQKkNScRShYVY9DHI44qis\nteMF0uJoBynHGgeIDosPb9fvPkhnuOccGk0Z0OoHbCpiRwG0j0xKcHQU4hKRR4jy0UR2wBinnp3W\n8VH/vmPmjqotYj6ITNZ+MHuNgLfY6HCnien5wvxyZXl+Ii4XYlygZdp9pa733+XK/WdY1pkH5d50\nLVp2XNRaOnkvpD2T1p2yZ5ztzIsjRGWQCie8zwQ74SQQXCDayBTAm441416TTd2ivJK8xGvRMk0T\n5u2D2CaI04cjECQyS2QRS2uQc6FsO1IyJzuBc+TWSaWOGTfUUqitKhxaC27kWnodStJcoFhlO+ai\nFnpfbzd++faVb/cba9opIrhp5nS9cnl6xljD+9c3atqYrOcUZl6fX/jyxy88f3lGeuOXn/+VX/7b\nz3/vS/pPtdRjOihy0Cq1Camq3vqQUbSuzNFWClW6MpBzJtdCbo2eKx7zSAxRGWZl7avax5VCTZlg\nHXOInKeZyXukNyWywSNqS3qjW4cZHSuoD3awluiDInxqVD3sDVWr3lun9oodEjor6PxMbbYf3aEL\nWijDyKDsBpqBZg3N2e+CM3Q/fSgQZFiDtqoa4XajiaG0TrCWaZpYYkDsb+d3/K6F0qJ5dm5sRvpx\nFEs1tAR4FMsBgCPo1/belNo+dJYf0Vb63a1Rko2zbriRGPrwdB30Bj4Klj4+NIzfgb7mg4at9Gt1\nj8C4QeYY806Ltv38j3NKMwqsDNhWfw8zZpNjJv3xujj7sDHQO1E7yXCKTNcTpy/PnF+fmM9nvJvo\nTWh7oa0rdf2Uh/yo5bwDO1AN0x/6WDuwJ+kaapvWHamN8zlweZqIs1fI0xg1iibgumOaLM4Egota\nfAdZrXdNqcEabLdYabgm9G7UpKKpyURrVaElNxx3rMEbzyxBPYiLp0RHy5FYlQVZaiV1lQlY4ZFB\nKL3Sqqc59cJyRjuAw+i6tcaed277ytv9jbf7jdt6JzXtRuMya7hvCKSSuH19Y39/4+V85g9/PvPH\n1yv/9//1Z17/+BO5JEzLRB//zlf0n2uZgYIxchw1W1KtCJ37rkiMe6e24YSW8oh/q2OeqDpL4zRc\nvIqw7YmUksqDjGHygfO8cF1OTN7TWiHnHZE27hnNQLVddD8ccyUDOg8dnp86DtB92hndSGtr2Fq1\nwPeuB0OjBgR2sFvtgGr9EaeFzmebQccQzj7Qx4fP9vhza0JF7RlTLmy50QR8mJjmhdM883RaqA/F\nw7+/fvc8StGMKcyIrrJY9fUbySGHIYAZEOZBpjkc6491lL02WKaHcbrCr/2DITYYr4e/qrXfZVcO\n/RHmo9AZI6OoMjSY/QHbHiG4HxfmQ59pxyzykJYcbkKYjwI5ZJT6+f54FtSuejTxDmLAz5Hpcma6\nLpyuZ+bzwjRPWIG83slbotzeqbdv5O2zUP6oZbzBBIWRCJrU4udIrBOLE0iJLo26F9bbxs9/eWO5\nTI/5iXskdESKOIpYJqw63fgZrAc3YeyM9XfWurLXndwSpQm9GcShRua9QrVIK5pcb7paKwpI26FC\nKyohCiJ4cWPTarSuEKwdB0QVhwec9Qovy0euYSpqhL61wr0V1q4ft17JpmPCiAcLHqSTtp1tu7F/\nu5PWFbNMnGbL8/PE9clzOhnsbpgnzxw/C+WPXDklhUatkqiQrrO/aJhDYJkCwftB4lI5G113M4tR\ne0TDYKF6bIwY6zS1pjfa/8feu8favl33XZ8x5/w91n6cc31t3zi2Y4xSEqoAiVSVoEBViZak4lFV\nbQmQCihtxUOVaP+ASEVtUQRqeRS1hYhKlFJoRUKhVCWiEY2ACqVpq9KH0hQaCk0tETCyHd/z2Huv\ntX6/OcfgjzHmb+17Yl/f43vO8bG9xvXy2Xuv12/9fnPNMcZ3fMd3JJ9rWlJiGkem4nMbh5w2cpBa\nH5FljoYQovsxGcmnKzkrFlOagPXylipWFV3XgIFbkI2EVAopx5SkSFJSLpSSKTnFHm/uINU1j7Vz\nRjT24+R+YDXvOZdoG/EBz95feTlNXMwzu2liWt57+9IrdZStNXJr0eLBNlS0Z3Knto/gh0pntUb/\no/Us0J2SRVPqqb0ixAjok0egF75N08lJ9laUSFw1npd65EIXFNB3slrd827FY7P+GnKCg/Ga0v3e\nTkkeIPQBq+KJRUREEuxHQcaBcn1Jub5g9/ABlw+v2e0mh8naynp3x93TG24fP2W9uyWtB+rhXAd6\nUZaLuJauKToIjJk0FUYbkVkYVm+wvsP7xG4e7/nsp992UfMhM80j4zhQSiYXGFQoCqSZIY+MeULK\njlR2lHFmPI7cLk/ZL4lFGi1IDpadFUg6YmtCbfEpOep1UT002rEiC6QmDK0gOkYJYKAlY8mB2KSC\npOIzIiWG+K6NVo8cQ+XnZjlyWxcOohzEWEuiDRlaYRwE8kAZB9qycPf4MYf9Hev+SEGYxsLl1cjF\ntTDMFZM7zBaSqFP6z/bC7HA8sN/fkfKAmnM75iFvg5gvpsHF0ZEI6r2kVVKOdR3XQ4RUMnlw3dcW\nAbyIj6rKKQdD1uXjUrTCZRFvWZM+7MFQ6W1tMRkEcUQsJthg96ZBrc3X3uKtTahRgDx6m0nOQc6U\nOMZAPXIgfLkkr1OKkNRF1A3xgfYSBLbkBEiJklrJGckDklyEYJ5n5nFkzPn1nUfZ4w8LtmiMfvTI\nJAgy7vXklOEZ9ObHzvjqIFagRl4SvseKFbqzA3qfZvbitGu0Ej1k4ZSdqbM5ynwP0lUzUjC0kojT\n9jnBrV3n0k4H6Mcmp+ndXdA8hVO0yCDBozQphTIO5Msd4xsPGB9ccfHgAbvLHUNO2LKw3hzYP3nC\n7eMn3Dx5jB4PDHjN4WwvyGKulapPL3BFE0WGxLybmBid7NVg3a8cj5XHb99RxoFpNzLvRlLxWgvJ\nZcZEDBVhlwpDGRnSwEXOvlFlj6aLFJZUWVtQ/tWoWzCmoBHMqblCky20eoTVSFVgzYguiE0gE1pG\nmjUfF6eCKGQ1cmvRb+zarsflwO3xwO1y4GBKzYm0mynWmDB0HDBzpR/JCU1Cq5VksBsnpnHH9YNL\ndtcjZZcgrdR2x1pXmvpggbO9OGura5qC72dThjEVxmnkYp6ZpzFUalYPtNRcfzcLOQL3jS+Yk6+/\nIXvZZxqcTKkhvC6JKWeKdL6+z0oV6a/SNbC95FCbS5FiTtQRicoUJxTRYli9Rn1TED+2JFvt3Ktd\ngeiltBHrepZJzj6pxDf+jSeyfTpjI/SklChFnHVbRqbZ661Djtd9jta6Vwu99rmKCVIRJ62kXkv0\nC8Q9pqr/z+nJGkSfCGRcy5IuGZe2+mYKlmzO4jqGkim5+IgrTm0Y28W2hlnZ2kM2hyonaTmnIHNi\npoazA7bHeJ+nU/IdDujHK0EYyijqM/5EsASWM3kcyfPMeHnB/PAB4/U18+UVeShYM453d6w3txwf\nP+F4c8P+5gY9LK58QiOfWa8vzIS21XiWZeGwP7LfHzEqu2lk2o3RYK/cmaCrUlfj5smBz33mMXnM\n0dajfZKb98Cax9uziQsyp8RcJh+RJImpzCzLynH1Vo5FG0tb6b3BUQr3jSgrDR+Iu+iBdVlYliP7\ng1DawJQmdvMF87wjq2G60lpnlEWvcfVh0rX6SK1VjFYEmQbmcYfNI3m3Y9eVS3q0vqEgXnuf58Kb\nH75kurrAsgcWWo3jsnA8rqzre6ffn+1LmyRncw4l4MohB6Q4ME8Dw1DQ1ljaPUnMgGIJ9Ko7E0vh\nUMwg4ao2MgAuOVcQBkneDqJKC9HhGulF00oTWNXbqqgWknV+nJKIhChQwlDQEfEEKZcgYSav1RM9\nyH0CTd/7w3NGhilIzoHyNTzR6CMV7V5zoTjL1nAfI36eSvJJVUkNJMZ+vUd7xY7SwwyJuWZOmHG2\n+paBBZnFC5cRWfQ+iqjvGbbBl31SiJG217RgFw5lDCF2HxmUggrfM0+vZ7aT8EBsADmnGDrbBQ9i\ncW1EHFfg6X1NIg4r19pYrUa91A9YDC92Y6gJLYkr3peMjAPp8oLh2jPIywcPmC8uKcNAXSrH2ztu\nHz3m8PgphydPafu9S0uZekFeEuv9HtGzvS9Ta7S2cDxUDncLt0/33Dy5o0xw8XBi2o2ICW1xKH/Z\nL2hTDvuVRz93g9JYdcWSYcmDsKrecrGqspTGPMxMw0gumTGN5Ckz5pmlrByWhWM9cqgLuQlED9gq\nwRcXzxBtrKzlyJ5bni6POdzeUNcGi1AYucS4KIlsynpYOO6P1CVUhdQj+y6soSWR55Fxt2O6vGC8\nnNmZcXVcWZbK2laa1q03WZK3EYzzxO5iZnedGC8SFWGpjYSxLMpxqSxnR/lCzXsKC0NJDOPAEHq+\nwzD41JiUfD4kG7jle2If4xdlJOtoWiB7rswkjOJEmpJSOMtE2nghsW9K/8mn7SyqrgfcDJpnkSUn\nhtwJcA1rMUgi9VppRnPM5E3J+RnYqTvBj9Yzxa2jIOqWwY5VCV5HBAAiEs7YWwpzUqw4LIt4W4pP\nIzGHg5uhzyGx+MpF0V3YtvlFk4AwVU+sUwtCjZj3UGr4TnqGp/dowCF6jl+AEyQa8Cnm07lzDExG\nonPHST5+UD4VvhOI+rQGiQPuYu2BObhjVkNK3oQQ+rGkpBswvD0lNiR6/TM53JDmibybg7RzyXx1\nSZkGEqDHlfX2lv3jJ+zffsTx6Q3LzS22VlClhLpKZw2f7cVYW1f2N3fc3R65eXTL7ZNbDncH5jQ4\no3UaEMmsi6HNA7jlbqGulZune6pVXzNBHGvVhaSrGlUbS15Y6o65zYxljOwyU/KIkBGKE25yJlVX\nq8pATYUshTGPDGTv75xXbssc0+qVO7vjqJVjW8AONB0QXTkc9uxvb336fG+/MoJRODBMA/liZrq6\n4PLhQy6udhjCsjSOyzFg1BpsbyXlxDjNzBeXTBcjeVRS8YHrtWay5GijKtsIu7O9GMs5MxR3luMw\nMGSfTZlz3vq4m53Ex10PtTf9u/Pbtove1qbQOxoVJ734YAijRW0SjfuF0wgKs1DYUdcAXhtavY98\nbAkr2QXT9UTSdDF330NTd3D4PklOSPYh5tv+yanzwJOqrvcqcZzViUI9ycEZ6iVEYrI2p5Tgzy2h\nUiQEsai9poIDyYQYZRByYcmx64BNezqNeR+kqcXE9GCt9gtnvRbpzjVHVunoqfdSduFmrZUVtpqj\nEEzX/lq9ZmjeDuBswRAayDnu89WVfLSJR0cdfg1n6KXU0IS1tnlbiwcrQM6kIVHmiXw5M15dOuR6\ncUHOiboeWe/2LHd7lps7Dk9vWG/3rPs9Vlewtl3ovt47BHy292/rYeX20VOePr7j8eefcvvklro0\nTAePunNGpsx8dRqqra2xHBrrsaKtRZlTsKo+YQOPwKuuHMod+3VkOk6MZWYadkzjTCkTORWGMjn0\n35wSXxAKiZqVkgpznpnzyJgySZXj7oqH08T1PPH2/HkejTfc3q3UVLnVA7UZh/WOw3qLtUZOhXGc\nKWWgTDPTbmZ3uWO+mLm6fsCDh9fMFxeYuUD84Tiy6uooibWtJj+ME/O8Y5gmyBWVBdTPk4mXO4ap\nMe/e+2Dcs31py6W4es44MpRMKZkUmVnTxtqMw7pyV1f2x5hAU72lbshO0Ck5O2SrsrHvmyqLNta2\nekCYE0P2ocupa04HCqEkV4Iyd6xqQgvR9LpWT0ayzxYufQoT4eByAcR7Ny1IQBIJVHIYNmVHBvuu\nllIfXn4qh92/sQ3N8D15yP7dUfEEzI+xc1Dcead31Frfm71a6FV9E5HmJUXr2pTitHavOUJP7tMm\nSpCw1jbItsOmdNFl8ybYnlGqh/sYmboufkLuZV49MxUBa3rP2XWMOxisVU5tH1tGGb03cvpMEEpA\nhFh6zMMU75zdxH8lZMTyPDJfXzE9uGTaXZBKdoX+45H9kxv2j56y3NzRDgdsWV0iCo35aV7TTR0C\nOWeUL8zWZaXWlSeff8zNoxsOtwc2jB+BlEkZypgZdwN1rQzHEkLLxtqM20cHkjrCMU4D8+XEsMto\n8trRIQ0MMjKmkd10xYVes5thGryWPpC9ZIPr/YpBS8qQBnbDjoth5nKYGESou0uupoHdmCjZaDRq\nMvbVWHThUCv79ZZF7xAS8zAgc2HY7dhdXbO72HFxsePi8oKry0uur66Zp9mbwGMYV7ZCEc8oet2r\nlIFhnCh5QDeJRouAwhm246iM8/SVvaBfYyYhOJBzIceoKfAqVW3K0hqHurJfjtyuC8eDC0kkE+ZS\nmMeJaSgMYuShUAJdaE191ulywBKUksPhOPSaDMSkMy+d0CjZ9zk7ladaENFQJZtByZTQNE4hY0fv\ndFCLdr8g/iQJ5aFwlIEfC0486gjfdi66swtxdaNnzafZv0a09G11dXf+Th6o3rv/Hu1VOcoZ4MnN\nHYdD43a/cqx6EjSXPjKri++GAG/QYk+kGOgpnXH6kAJRPO4RQkCiyYu4Ked3OjjHRNmuxFa37BAs\np4jFX9iLyZHDbq9DwANEhBS9aXq/TtDXV0owZGQZydXnw61r4zgdvE2mVo63e/aPb9g/vqEdDuiy\nIq3FZBV//54ZZ4Ekxt3tNhx3fsHX7OvJZoDHn32K0njy9g23T+9YlxXJicPTI08/v49NSlgOK8vt\nkePNwvFuYblbOexXtDaOWWhHRavXpNdqPH1yxzhnUnZxjUKhyMhuumQ3X7GbLpnGC8Y8xpd/pdYj\nS118Np8qRQbmMrEbZi6GiTEJ2lbu9k949PRtPvf2U37uc0/5/JNbbhdjbZnj0jjc3VKPBxKJaars\n58a8qxz2jflyYbc7snt6x+3ujqfzLeMw0ppxPB44LCvVqmtwymnqfM6FUkZyLjRrVHWKx1AKRQqt\nVg6HPZ//zKN3nN+zfdk2A3z68VOmoTCO3i8ZCL/3FVblWBv7deX2cGR/WDiuK3VxlvJUCvMwMo4x\n9SNY14LPHd2vRw7LARWvMZaSQ1rUYVKxhEjwNkIVZ22NYwxMPi5H1rViaow5hl3ELadELpmcy8mB\ntV628j146O/Z99P44F2X2wcOeI1yG0pRfSxc7e194j2XibQlRiq2DdU47dZgrfHpJ0/fcX7fzV6V\no/wkwJ/7qz/9it7u69I+Cfy5r/RBfJXaJwF+8sf/jy9456OfveVnf+qzz/Fyd8Aj4NPv+8C+RuyT\nnNfm+7FPAvwnP/GXv8KH8TVrn+RLrE95FWOaROSDwPcAnwLOHfIv1mb8Qv9pM/u5r/CxfFXaeX2+\nNDuvzRdg5/X50uw9r89X4ijPdrazne1sZ/tqtfeuCnu2s53tbGc729ehnR3l2c52trOd7WzvYmdH\nebazne1sZzvbu9jZUZ7tbGc729nO9i52dpRnO9vZzna2s72LnR3lu5iI/LCI/NALeJ1vFREVkW95\nEcd1trO9m4nILxWR/01Elhexfs92thdpX43r86U4ynAKLf599tZE5He+jPd9CfYvAv/SC3qtcx/O\nV7l9Fa3r3w/8WeDv4MWt37O95nZeny/PXpYyz0fu/fxPAz8AfAsntb6bL/QkEcnmyuivhZnZ03e7\nX0QGM1tf1fGc7StuXy3r+puB321mX1Qa6HX7rp3thdh5fb4keykZpZl9pt+Ax/4n++y9v9+JyPdE\npPOPiMhfFZEj8Iu+ENwpIn9ARH703u9JRH6niPxtEbkVkb8sIr/yeY5RREYR+cMi8ikRuRORvyEi\n/8ozj3nHsYjInxeR/0BEflBEfg74kyIyxef4TSLyY/Faf1NE/okX8N4/LCK/TUT+PxH5jIj8XpGT\nCrqIzCLy+0Tk/xGRpyLyZ0Xku57nPJztvdvrvq47xA9cAD8cWcT3frFjiuf8qyLyMyJyDDjse595\nzW+Ldb8Xkb8Wr6Ei8t1f/pk828uw8/p8eevzdahR/i7gtwK/EPjCYps/334A+DXAbwC+DfiPgT8m\nIn9/f4CIfFpEvv9dXqMAfwv4VfHevwv4PSLyj3+J9/5NwOeB7wR+y72//9vAHwW+HfgTwB8XkU++\nz/f+FcBbwC+J9/2Xge+7d/8fjPf71cDfB/z3wI+JyCe+xGc428u3r8S6/pt4VrHgZYNvBP7kFzmm\nnxaRfwb4d/G1+23AHwF+SES+M94rAz8CfAbfuH4z8O9wLiN8Ldh5fT6P9YkZL+sG/PPA57/A378H\naMAvf+bvPwz80DN/+wPAj8bPl7jq9Lc/85g/Cvyn937/X4Df+JzH+geBP/LFjgX488BPPPOcCRe7\n/z3P/P2v9L8B3xqf9Vue871/+pnH/HfAfxY//134gnvzmcf8OPDbX/Z1/Xq/vc7rGtgD3/sejukv\nAb/3C6yx/yZ+/lVxTG/cu/8fi9f67q/0NTjfzuvzVa3PVzuP8gvb80rifysuZvvj92FIYMAdGQBm\n9ku/1AuJyG8F/lngE/Ga4/3X+CL2l77I3//CF/j9F77P9/6pZ37/NPDx+PnvBTLwqWfOwwj8X1/s\nfc/2yuwrtq6f45j+bjxiv28/Afxz8fO3AD9jZo/u3f8XecdkwLN9ldp5fT6HvQ6O8vaZ35WfDwkP\n936+wlPrXwY8q/j+npX1ReTX4yn9b8Gd31Pgd+AL4nmO993sC0IAz/HezxKFjNO5uQKOOPT67MJ4\nVxLS2V6JfUXW9XMeE/z8NSr3/iZf5P6zffXbeX0+h70OjvJZ+yzwHc/87TtwHBo8y6rAJ8zsf30f\n7/NdwJ8xsz/U/yAiv+B9vN4/APzxe79/J/BnXuJ7/xUc9n3TzM6D6l5/e1Xr+nnsp4F/iHeu2+8C\n/sa9+79ZRD5gZm/H334x5xrl16Kd1+e72OvoKP9n4DeLyD+FO4N/AfgFxAUzs7dF5D8EflBEZjzt\nfwM/oZ8xs/8KQER+HPjP7zujZ+z/BH61iPzDwP8N/EYczvzfv8zj/nUi8pM45PobgL8H+Cfv3X8/\n0nnf721mf11E/gTOHvvXgL8GfAPwy4G/YGb/05f5Oc72cuxVrevnsX8f+MMi8lN4benXAP8o8A/G\n/X8Kh/v/CxH5bcAHgX8z7js7y68tO6/Pd7HXgfX6DjOzHwH+PeD34RdD8ELz/cf86/GY3447lz8F\nfDc+2LTbN+Mn7ovZfwT8KPDf4tOtZ5xQ866H9y73/Q7g1wM/iV/QX2tmP/NFnvvlvPcXsu8D/mv8\nXP00Hnl9O/CzX8Zrne0l2itc1/AeNwkz+2PA9wP/BvDX8drP95nZX4z7K/ArgQ/hJYIfBP6tOPbz\nAOGvITuvz3e38+Dm92kiMuEsrl9hZj/2lT6es53tZZqI/DLgx4BvMrP/9yt9PGc72317WevzdYRe\nz3a2s70mJiK/Fu8b/ls4C/H3A//j2Ume7XWwV7U+z47yxdg5LT/b16o9BH438DGc8PE/4HDY2c72\nOtgrWZ9n6PVsZzvb2c52tnex147Mc7azne1sZzvb62RnR3m2s53tbGc727vYK6lRisgHcT2/T3Gm\nlb9om4FPAn/azJ5VzDjbe7Dz+nxpdl6bL8DO6/Ol2Xten6+KzPM9wH/5it7r69V+HfBVMS38NbTz\n+ny5dl6b78/O6/Pl2pdcn6/KUX4K4Ps/MfPNV4kpG1OCIQtFjCyGGaBKEsgJssBQEkM2koAkA1PU\nFIv/EEGSC94YgjalGdQGtRlNoRk0jftNwEBSQuL5CKgZ1Yy1GetqVKA1UAULNUETQdOMpR3rfMl6\nfc06DdjxCE8fYU9vaCgV4SjCwTJrE7DGTKXUStXMoRb2WqhlZC2FtSQWgdWM1ZSmhrbGZMZsjUkb\ngypSK1ijibH6IZGBx6vx47dtO8dn+7LsUwC/+Jd8J9cPrjcNpU50M1V0m05gZEkIxM3/S5JJuSCS\nkP4CYpg1EAUUpJGy+k3AUMwMbUarvk5RoTUwEqhgJEzBLCb9YChKaw3w7wMA6mtHxB8LvrxVYwKC\nmn8GBbXT5zNVmipmuk1K0Na25xGP8Y9u2+t2nnd/rqr5sZj590WVtVaePHq6nd+zfdn2KYAHVw9J\nZQAShtFqJaMMYuymzAeuLvimb3yLv/ObPspHP/wm1xcDUwFJDUOprdFMUM1oE6oKVTWudQVp5NQo\nIgxZyIiv57jgcfVjXdB3YbbFIAlSAkkYgqlQW2NdlLvjws3tnpu7A49v7rjZH6kG5EIZRrIkchKm\nYeDh9QVvvvGAN64vubqc2E2FIRlWV6gVwcjIthAVQ/sXEhDp38r4Dmv4F3wt+yEbf/vTn+MH/tCP\nbOf33exVOcoDwC/6YOY7HmambIwZSgIRd3ytKa3a5sj6xRqLkAUQxRSaSTgTQCAlP2FqoJqoaqwN\nlmpUE1aF1szvB0DcP8bz3FHij63GkhqrQi1Cs9hUBJSEIlQz9lp5ur9lfxRoC6MdKZP6ZmXCYsK+\nKUeBJMaEMoyCauE4XHAnM/th5mYceJrgUBfulj2r+sUdyUwoDyVxZYmpVXLyi11RVtSDBBVSv/Bn\nSOb92AHgwRsPeOPNN7Y/9iEJ2p2JuiMQDAH/shqklEmpxC37mvRnYjTUVswqIg0JR5mLkZK4E46g\nrK7hMJthltAmmPnNNyg/FgOqNkzdcauq/z2cnS9rX+dNm9/fzL8HsaC1O0b157fWfOOL1+qf15o7\nTDFQbds5ITYetdPz4TS2Twzymnni+vzntfn+7ABQykAuA0rCzAO2RKOgZBGGnLiaJz788JpPfORD\nfPiNK652iVKMqitLXVmbUFumtsRSxX/XSrMVaCQaQ1KGBEPJDDmRU0bkRGcxfC8ybVsAaZKxlJCc\nkTxASpglWjOWY+Pu7sDjp3c8enzD7tETPv/JGhqKAAAgAElEQVT4hrvjwqpGzoWSM7uh8PDqgo+8\n9SE+9pEP8eEPPuTB1cw8JIootBWrC8kgiyAi7jvEMAmn3Z1l10vXU0DYgz7i+CnlHef33eyV9lF+\nYDI+OCpDMnIyJIGJ0UxZ7kXXpkZLmdQ8uzPpG4LRVD1TVA+dRcwjGFWa2eYoV3UnuZq4c239ggoi\nGo4SYq/z5yksLVGbURUaguIbk2KoNlar7A933MqeO38mU2pMomRVUIFmJIUUm0lLgqSMSqKmgpaJ\nYx64S5nH1vhcbTxeVtZamRGuEKZYACIgah5DmpJEybFBZRL5VV7ArwMTETSCDxHZskrCSXlG2VEM\nY8MzJB4UjksiY+xOko43tOoUuqYgiZSSB4LNyD37i7WO+pffHWWiD0swi6WbBFMio000NRIRRcuW\nNkI4Uez0XNSzRXeibbtfezDQH4+SADUliWCmvgmJf3lynCdJCTULtIbtnJ3txZrcgwx65qQGtSmH\n48r+uHBcV5bqTizlTM6OjEnsT4ag+H6kQvybfX3aipkHV6YJS5mBQkqJtGWWjkyYyIY2mCQsFyxn\npAxIHhAy2YQhN6Y0csHIwsDFCreLcWxw2B9Y1oUhp3BGRhkK825md3HBNA2UDJnma1ogmZFIJAEV\n9wGKO8t3KGobkU0qpgLbv/4Z0nNsnq/UUV6Icpl80xfzbaZhHvU2paq5A1QjNbDYCLIQm4dH2615\nZmkm20blGaVQFVbCSao7vIo7S1M/QRKQrUi8B+EomzvLGvCXg1vii8kcum1q1ICmwLCk1NyQZAxA\nNt+skggZc+jXjAbUkjnkzF1KPEnC26p8vlYeLZXHS6OtK9VgyIkqgiVAjGx+8zPmn7iZIWrvWBdn\ne39m4Sgk4KW+Xk4ZG2BGw52GiGyRtkXQZtpo2mHRBjSQ5vCXVSQ1aP7lRTwCT5IpRXwjSgqr1wtU\nG6KxCZiAJSRlkiWscYJDfSluvhEICFYj6m/bhibdWXbH3xqmbXOSQmStqp6x6unxYNvnTpIc1YjH\n9+ACEVISf7xythdsvs5SJAnuKE2NVRtLrRyWhbvDkf2ysLaGEuiZ9T3S99iqQlOhkdEkqBhIQy2z\ntoWmC1o1ckxlkEzOGfFIDO3lMkmezUnCUoKUt5ukQiaTs5CLUcqOVCbUMo1MM+G4VNZlT1VBpwGR\nRCmZcRqZ5okyFhItfKSXy9xRxjrEg1dEt4TqdLLw8ocGcGyylTv6+Xuv9kod5UCjkLCmm+PT5Flg\nbUqtXls09Rpiy+6YMv6l16g71uYO001ir0iebZqwGlTzbLLGz808MvdrmxCNzSQyymYn59oz1mbQ\nknj9BQKmMlSFpJBRGuqfwSLCs4jw8YupAlWEFWERYV8SN1l4YsbjpfH4uPLkuHB3XKE2CrA2RbNH\n6b1em3pmo0qKi/7s5ni292fPTFJngxa3NKw/JjLOlHwTSpHdmVKb0lql1gURi5qkkcS8zi6KavVM\nzbI7oZxOwVsP4BYlm2K1guq2ovyLnvz3vngtnJofMh19gZ5JqmeIatvGCiCmvvncyzgdWu6bkm1O\nz/r6FnfoOZd3nLee6HTYWXBk5WwvznpFkL7+hCBR+L62NuWwVO4OR+72B47rQlN3TB7ka+y14vut\nZZSMpYLkBFmhlXCoXrts1RxZE2PMQiK58xH1emTU7Uk5XiMjKSMpkXKmpIFEZhwT02iUMqGWWGvj\nuKzc3t6yHA/BTUmM48A4jozTxDCN5CH5nhr7tSQhdUQFPHhESQgWZTzgXgLhKCLJvyOaJL4H/p16\nr/ZqJeyaoouikWVpcUh0NfziKTSyw6MmWIMWkIGZYJFN1tYJOsmjBAtoFIefKhKOEqpFVoc7PEOi\n3uzO2JLXa1rUKetWB+1EIENTij1Ewlm64/LaqWyfRxTE3Ak7GcMjIBWhSuaYC7dJeCrG01rZr41l\nWdFVofpi8O0QcpLIJCGbUujkEnGIKxKJdN6LXo4FyWvL1gjYS8RJXvGFTCkFROs19HVdOB73rHWh\nFGGaC0kgZXGoRzopJ0gU2ZGKkgopp63mDrCIoigF9SxVs2+Skv1mESWrnW6BmHi90rNFC8RGiKcD\n2jrE6k7cYVUCowukJV6/Q7t+DpJnFnhtthOcfLN2h5mC0NTW+uqv29eydQQBz9ojenHijHlgv9TG\n3dGzyuNaqc0DvdZa8EA8IWma3IHkgZRHbCiQDcslOBmCtiOrxlrJhURmSL6eJfsVlx5EpuQszMgq\nJWVyypSUyeLP1QzWjIt54nKe2I0Du2FgKQVJsNvN7C52zBcXjLuZYZooxf2AKIg6L6OXEDxf0Hck\nkSInlG1zlskhV0uOwllyhCan19RRLmvjsETNEM/MNLKtNRyVSfF03gTVhtUWhIJwnC1gUfWLGUGw\nw9GxiVVJVLPIJt1ptg6nAcmEZAHaqiNEzcQhUhWHG9QdrPMV5bRpxiYpcjp5ShCCIiiXBsTiNREs\nZZoUFhJ3Zty2yn5V1qXBslKqMZuQLDGLMQIjwoiPGC84w7UnDbpRvOS0GM72vm2DsiQIKUH2ShEw\nAZtj6MiEl+v8y9tUWdYjd/s71vXIvCuM00wpA8OQvCaPoyTO4PagS8SwDEkKqfgmmCJblQRrUodF\n1GhVIitdMRVUk9f1rdcyoddMtTNWtW1MRW3+b+rJKGzMcboz7BuIuWNMCCkKOgkPDHJK2/4kQQ7a\n3jvW5VLOUtIv0u4jhU7mCcpKctLM2ozjWtkf3FEelpVaayBwzX9elVqNZhmykNMAwwzDABmMwYO3\nJNRFqOuKNiWpMFimyICURE5eI4xcIZCVuAkQwVVJvn4kkI+EUTCGnJhKYjcVlnmgDIXr60sur6+4\nuLpg2s2eUSavQ/om3RxI0yjdmZPe/ITEOXqGzOZV1QQpAsnUCT2JLO+9SPlKV/K+CrdLfOclYZax\nJDQRKokmTocXKd6OURdqbejq0II1d4RNPeNT7TXEdCJBWLxeQK4VoeEbnSFOoFAjaUTOET01M1SS\nPzZqoE2CHdjgFKd4RCciZEkojdShX3PmrZBIkn0FpQw5oymzmHBoypFKXSssjbI2dmqM+OZzmeAi\nGZPAmIQxOyIietqAvEwgkBLpjL2+WJNT+LE5Szg5zU5a4QRTEgQb1eYZ5XJkXQ+kMqA2IFLIWUg5\nBYfGCWwdqjWaw7PJENyhptwYRkdKEEOk0aqRTLz2GZuRqa8Id7hlO+6eLXqGJ0gGrd5qRfzNzCIr\ndOfXs+PTZ07uKMWZj/SyQhB2ThC1RA03gohwyqWcqWYv1vy6pPBOZhZBju+barA247C4s9xHVjmt\nEk6yUqvSVlAUSZBTJpcRhhGKgAxYSWhxZK+2PbUtZE2sKmQTMsVr5UmiZu3HkbJEMAi+IzrZUMxr\n99Ya1lbQlWSNIQvzONAuZsbdzPWDK64fXrO7umScZ/IwkKJcQXP0D43SXa+hewESCeTjhP4E2iYd\n6/DShzvL5OUIee/u75U6yqMKd5aopECVnVZv4lmmGk4ztsgMW2atCa0teslSEHp6RpncwQUO7Qlf\nOMYtkwzoVSSgfY/EEr759R6c/jy1IElH8du208y2AUCvCnRWKo7bU9A0kNJALhMpD+7wzXskVzXW\ntlKbIYsyNHUIV41mRhHYARdJ2GVhkGAfJthWYGD1zkS8x8o82/u2fia1f/lENtJWkk548BjVtrpl\n9B5G7dJrOxXVilDwC2bBJGw0XaltpdZjFJiNnBOtLdRh8Eg9apYmDUmVlCq5OGmhVwCLSWSUglYw\nC0cWcKhgzqil+AYDDq3pCZLqTvH+LaW0BQiCuIMkbXCqZ889+ybaTPzktchcLc5feg6yxNm+tDnC\neX9NplNNPTmUujbj7rBwe3dgf1xZlpVlxB1lrdS1sa6KSqYUJaVEKQMyjFBS9KsXtGZMjbp68lEV\njosCFVUvmZXsmWVOQh4k0IZTUil4PZF+jNYwrVHjV1IWxqnQmJgvL7h8cM3F9TW7ywuGeSSNg3dH\nZIOW/PndSTa/eR3kXh1+K5dY9MBvu7efK+kcg/RcXLNX6igPUrjNhdUyJomSB0r06DS1yPzi1pS1\nJWoV2ipbLdKCkVqj5tgQmuCsK+mOzp1TrzuqOORkkY43gtauHqU09U1QBZqEM0aih1Jio3NnrLFZ\nJaI+ELUfkUQqA23YYcMOmS/JZfLPdFxYlyPLckBrg1oZq++TTYySYFVlEOEyJ65LYhal9PaQ7E28\nqCJNvPhq3VGfN6MXZb2HkKjxxV/9/8N56P3ApH8Jo6exbwA5CVZi00iAefO9SKW2Y9wWOtlGkjuV\ndfU6ZSmZnDtUq5CUHDRSiay2SdSlmq9DXwZ9o/J/RZQUrFph88tgwUyN9hRgg6tOULJ/ZneQKV7j\nHkXCei002rm0kSSH45StJnq2F2n+vU8i2+ZP36MQTNJG6Lk9HNkfjhyWhXmB1lZqDfi1GUojqwYf\nIpFLgSGgfwa0ZlSNddXoNKgclkqtjaVUxlK8pSMnSkmMWsAKxRI5n2BPLAQ1msZ7161nVwRyyUxp\nYr6cubi65OL6knE3k4YSyjNGSgUpCSxHLV7R2h2lNyF3stpGbLMgtFlvDznBrhY8gedZoa82o5TC\nXRpZLWFSGFJhkLxR1WtVrylW9V7G1WiLoTXwIhO03WOkStQVw8n1BoreztGzwqbuSB2OEoL4FPh1\n1DbjxKn57+2UPCJByrHukDvrLHrKvAE2I8OM7S6R3TVcPkCHmVYbS77jqK6kgS6Upoi5s9Xk208W\nGBNcDslvKTFSvZWmBFvXsnMtzJzRZHq/jn2292md4Xqqf/jZ7dnWlmmFI22qSLUt82ytBtru9Y9S\nEmqNtS4kU9SCdq8rTSuqrrGUElSMtQplyLSWKEMOZ8bJaYtH4U7kSRCiBKpelhASKQJPwchlcGp+\ndifZHaUg7oijJnlytOBwrm6f3R3lCXbthDLo4gcWxB8PNk/tm6fXONuLsV562TauIPMgguSCJN+/\nlrWy3x+5u9tzdzgwj4BWWvN6o1bDZN2a8DvjNJWBPGRSMrSUEAuoLEuj1jvaurCokkOMoCSh5MRQ\nMvM80NrAOA4MJTl5zVlBaFVqsFyP6+ptK2bIUBh3syNpV5fsri6YLmby6ChIDVcmKbJVku99aqQU\nWaXmqMFp3NeFBSzY3LbBtJvDjPanll9X6DWPHGRkTQWVxNK8/kZVtDbq2py23LxlRNcaWbU4vInD\npy24DQ3zW1DztTsz1cDsuwMkerp8USU9wUKmiiW/u7Pt1dzhWhKv8/Soe2NBSDhdwIxsyZlj047y\nxpvY9RvYfMmaR+6WlT2JY200VbJWZjHashLYFakZQ0rMKXM5Fq6GzEVSJoxRPLMgZV8P5rizOd77\nKi/f17z1FommPfXqwXraMqzTLWqNJ2UkzJRcEuPoFPuc3eksayW15ppKurxDhAAsgjZfp602wNmD\nsknSBbxEZH1WSHlAGFDN5DRgOiIyk2T0DUX8/VPqhMTktHo71RY7cScl2T5P/xy9n9QdZHIWuvmz\nep9lIFveh7ltUN5jrK1tx3y2F2cdGt8iG3H2cVwcajMOy8rd4cjtwZ3lxQhZ/JoYeIBtirWG1opW\n71MsKTMMIzknVAutNYbjkXw4YnZgWZW2LghKyd7PmJNQsjDPI7uLmXkeGcfCULJnvgq6KuvaOCwL\nh+PCog3NmTxNjClhObG7vGbc7cjjgCbhWFdsUWoWsvj7pIQ73yRA3lA2ay2gm3uyHGan7FM7oSVY\nrxo9ysPwns/7q4VeSeylsOKbPs2QWrHaaEul1eZOsjmduePODhvJ9sVseo+kg9OXVU51StcaDGcX\ntx6KSa89mu8aPQ3vhEHrbIeoIXscE5YkHhddbeJOUyRDKsjuCnvwkPrwA+zHmVsVnkjmZlk5zDOq\nlQFP/T2DWDHRYDkKc0lcjJmraeBCjMEEsepfjpS8d72ArbqJMWyMxbO9fzPbJOJMdasHSdTkfv5j\nT/qmm3QbTmJx8k91iFW91misIIpIKOGEqghRO0kB86s1aiWau73Ngy5ygJBliH0hMU0FKxlhIstM\nzjMuTCBRErCtpp1F4jt1Uhk6kXdOhBxVtsywE3rQexqf1ltnui5s8/aDUPlpzSXtaltf1ZX7+rBe\n+4t9rpcCej2w/77Uyv64cLc/cHs4cnnMTEMkCan3ugpYpdUVrRXUyClRcqEMGdXEOFTGYaKUESRT\n1TsXrC5e4TPP4kqCw25iWSvHZWSaRobiaj6ol73WdeWwrCxrY1XFUiGPhWmcSENhd33FtNuRhwE1\n47iuVF0ZikuZlpQoOQfbVjbGee+IFEKIoa97gL7OW9vap4gMU1TJ0/SeT/0rdZR3FW4q1JChs6aw\nVGyttFppVWm1OVFno/myKd34nhJwK84c7NJFKh1PlU3I3M1bNGQrOck7alAWeL/dIzRg3stI1Hs6\ne8rEHaQFxNSPTVJ21ti8o+0uWOcdd2ng7cPK46bcNOVoIJKZhpEiDlfVo0vdDZIYUuKqFC6GzFwS\ngzWyCWIposhgKQqhQHFvoz3bizFzmcIesGvvx8HrbhJBlcSaslC1UVVardEioS5MktTJODQsrYi5\n5qtIQ5IionHtfCFJqDBZ1FqUDiN5DVPQE8FGMlkUUiOLQ/NJxHvWUg42X9o+kyMXLi6QQu5RNMgW\nW6AloTPbtu9Br/H0l/KksctIujPs8ndtc5i6OU/Tc0b5Qi02/o4EbIQp8V5aQdDWWFc4LCu3h4W7\nZeXQlDIODEMhKZASTb0ejvRAzAO1nDI5FW9/K4VSRkoZSLnga6RRlzVQBBfDGEqmBYejtsbhWCkl\n+94pTjpb15Xj4rCrpYSUQh4cqh3n2dtCLq8Yx5mUDbXq/gHxMkPuyY73aToUG6WwdK9dK6dTKcEg\nBdqhzZ26J1uOiOTd/J5P/St1lDeHymNZnGBTXXCZ6kwmrV1f0DbiEinqQwbZPKs0QgjgVM4+YaZs\n2Cn39Sh7NhqP2Mg3RrCkohbUmXz9ZbbHd5jWCDg29AbNC81pKOg00caRYx64afD5w5HP3e55dLvn\n7vaOejgwmSJ5cFZjErIoeV2YBS5z5ipnLrO4yDH++tIMUc8CpDZsrWBrNNqGwzzbC7FNKHxj6fnf\npYsKBGu6w+6qxnqs1HVhXRZqq0gyUjbKIOTRKBNINky8a1qtOclGLJxjvOamUxmwWG0RCLmqXSnO\nLnTKvSHmTlikIrJScmUojZJdxzhJduKbOpHCg0c9tZvkKB+k0JGyrlfrAaer8AktfreeQasrD1kP\nDrQFVNs2x9n1YjsceLYXY6ot2s+I1h+PsFzKzQPp1pSjVfbHzO2ycHOsHBQux4lxN/n6WZRauyKP\nQPKAO6qAW4aaQk5uKIWhFG/Ql1D1WRdobRPISM04Hp0oJIcFcJi45EKSxFory1KpqqSSGSQzT5mL\n+ZLLB9fhKC8Y5wGjBQWjxtfNWwnRAjK48Ib00QQ92PR+detqWRKlMlOk+dSevh4TgBllek0d5dND\n5Unr2SSeAW6KImwZYa8F9lqQiPfvhMygk3g0HFyH6zVA1nCORPSNhARSly4Sd3ISGaIJMaJFYoPx\nn120Gify4L2anfrsBAz1WmcpyDhi08SSMjfNeHRc+LnbI599/JTHNy7RZOuCDplxGpiHCbHG0AYK\nxhXGdU5ciLBLkK0FYSeYXDHzS5q6qLZWQDfG4tlekHnBDTg5SneQLaLUHkEFBNkMXRvrYeVwOLDW\nBbNKHoRxFkbJyJicsZqVZj49RIhWEnxz2pwljmRozyQliAzhIIv4bQv8rAGrCxXIkZxHF8FODv2q\n9Ei/S/FpZKb+Xcn3au8dNt6ID816WcchVaJXNLJF1XuqP5uoQfPvYNTAzoTsF2u9FcPuBSESKESX\nzuyQLCmhKdNywcaZvLtkvLrw1rilIguolsjUfM0DJyJMXL+SM8PgsnLTNHE8jizHA6yB1KWM5IIh\nUTYLZmuULoYyMAwDrTbWWoOnMZByJSFM48T15RWXlw+YdzNpSDRdHBa25g6bTGIgy0SW0YmTfrCh\n4Ocbs4t0pMhuXKvNEC9nWmIrNcQ5KuNrCr3uj5W7lmIvslMm6EUhgI3+LtrbMfx+C2dpAs2aO7eI\niLvj67qH7+gN45SVikhM4pBN+k37exB1meRRimUvFJODTSgJKykaGIXcAn4dCjZP1LGwT8LTWnm0\nGo9ubnn0+DFPbm5ZDgeKNfI0cC0XCMpoPlNtEuFKhEszZoxU61Yrk6ZIbaQ+70vbttF5+Sq0Os/2\nQkyj5QY7KduwsTxD/hCJ2pyXCdalsh5XlsPCWo9AiyAuIWMmteLIJ5XGioQcnSOtvoZOCichCRaK\n57nrpubcu44pqQSDVYJ0VjE9eGtTEzpBKKUZZIwX9iwyD7IhsTkCSNPmk3UUF/doSquAClptI8OZ\nhMOMRkyj96dF5L7Fp07DT/q8nWpn+1J2dbWjpMThcIjs3WId+HVNKTMOid3FxIM3HvLwA29y/eYH\nuXzjTXYPrxl3o7Ov00KiejdBH1EVZYCNJRrckJIz0zSyu9ixrsupphlBZUrikG5AwKrKsjaOyxFB\nmEaNMYee7fqEmd66IZRcmIaJeZwYhwnJgDXWLVH0UsNQRqbhgnGYXW/WzB1hz17uOUkz71fuNfcu\nFtJna0pycRcprymZZ1mVY2wOYsEojY2ng8pboVkS92FFD/CFYLD4v71wmyQYgv56KTJIuf+vSOha\niuunAhCs2N6430+0uHKFpbQdi6TklPqcfA6kuZarjRNtHlnGgTvgyXLk0aK8/fgJTx4/5unNU6yu\nDGZc6AhiFB3ZUdmpMhvsWmNCSdY8me1zBasizbxX04LebFHbMnX1n7OjfHHW2x2IdSR93YXKgwWb\nOupwrTpJQOMaaW1OuxejrkJphdqaJ37Jx2xpqzH9gG36i6+yEAmINe7f/5BBVLyXdtNdDZJZloje\nG2oVtUrOKzlXSvGJJUhxaCyzia732pa1hqr3tena0Cq0aq6A1UJHOU6N9WwlRY+k9MylFzNCsB2v\n6yttc/RnezH2oQ89RIDHj5T9fs9qLvCgzRvoJQ9cXFzz5ptv8JGPfgMf/aaP8w0f+ygffOshV1cz\nYwFdj1AbmmMCkkXmFSLoneTVuwxzSUzTiLaLLTAXEUrJtFbDR4WTbA1dK7U5y9WdkqMo4DtVitoq\nUTVK5ms5SyL3WkSUz1CNfbcwDTO7+ZJ5vHTxj0A1SILkHNGmj0VcV+9TrrVi1kJ+Vrb16sMMMim/\nphJ2azOaSJycgLXCifVQt5dqnM3p6bJHFn3OXdr6F7ETa09S1PSIjBR5Jts83dex+CSCppAJi2Kx\n5VBgwWe1STRmS0pYyf7alpGgWrdhoJXCmjJ7VZ4ejjy5W7m9u2V/d8O6v0PrEptGRcQYqVwl4ZLK\nzhqjNiQUKwLkosZC6dC6RJ0oiJEkUmQUZ3txZltt7SRfF2o4GxHgnSxDVzbxsUCIMz9N1qjZGbU5\nW5ncPKNMMY1ET4Of76G5WECivVKUxAUDsLQ5TVfuIUoJkVVao66V1FzFp5lRSsNsABmccBZ10ZQk\nyD3u3Jset0kRpslrQOb6rqadvBZEMvO+T9QddXxJHJ4uyXkHKKRMyefSwIu0j3zkg2QRxkF4/Dhx\nPB6ptbKuPsV+nifefPOaj37sLT7+iY/xjR/7Rt76yFs8/MAV85gQjdaMJDG7V70OWFfW6opRuQ5Y\ncQxEkpFzZhzHU31PvHY5DMXrlLgyk6qvv6b+HAnVIOjZ7gn67Ptzh3m7yo5p36tD0N+c6d3h33ma\nmacdSYRaV1e/SoKE3J7vm5V1NWpdWZYjRiPnRCFHKSBUpp4ZRv2l7JU6SrXeMybbQTrw2ck2J2qv\nqHtTcdDdma8Bwcbcj61u5PCVO9Ak9wvSPVKPyDYF2lsylv2WDJIpUpIXtosr/VSUFhluEtxRSgeT\nPPJpgKVCk8xisF8bt8fK3f7Ifr9nOe5pbUG0koCiwlxXdke4LMKVNWZRcuggNjEq6uIJsVm3WGwd\n3rL7AcLZS75g6/VyP7HW+ymla1qGi0xCKsKQMuNQ2O1G6jKxLCP74w3H9ZYmy1bvU8Un4CR3wq6d\n6hF0SaF4ow0gskp3Zk6JT1tAaeaswkT0aMboroSPUEoimKw03SPNNWFTnsEGV9bpGWr/YolhsnjE\n33pPiPcNb9NEcrDNU0zSifqqpOAX4IQDzzSI2FaQLJRzRvlC7aMf/wgPrmY++KEHPHr0mKdPnnK3\n37OuFUHYXVzy4bfe4uPf9HE++rGP8uG3PsTV1SXDODoLW3231VBSWhZlXStlSUi+YBgvSakwSHHm\ntoTofykQ3wqJDHIci0OxbaXVyrquCInWlGmcnUvSlGEYyLkEApG2AdA9m2vNVavWWsmtOhrR694B\n86fsaF4qoScL21xMi03QzKjq4h7H5Y7jcsvheAcoZcggIymPDGkgFdcufh6Ox6uV95dEFyY/QaEp\nnICnzsl6bdbx7v5d6yn6VnOWiFDC6YopPvU6dFy7swxM2iwUREpGh4JMI1IKokpS13/NJSND9sG8\nGFWMFIr3fbPaRAwi1TcpNBJVfQjp8VA57o/UxVVXsvimNmVhFtiZcmnKblVmq0xiiDZ3iKEwlHsD\nOITEXohZI7F5RyQPnLeiF2h24tX0uoZvDt7D1dszBCHjo7GGnLAaYuiHW25uhae3jcPqWZ7Pyws4\n1bw2OOSBQQo5lRhDlOhN4GCUKCmUHFPlzbvFalsD3DSGIJeZODxGEOJ8aPTKWm+RtJKpSBrcWZoH\netJ1YQUkKbl4RK8xOsmaRg1VNhTMMJKxtWN1uT4Lce1OlCME05MI03M0dJ/tS9vHP/YWH/mGD3Lz\n9MM8fvKUtz//No8fP+a4LORU2O12fOitt/jGj36MD7/1Ya6ur5nmYRPA1+hz1aa0VTkcDhwO7vgk\nXTCOl+QyxNzlfEpEcPhzHD0OKjkzjSNbJCkAACAASURBVCPremBZjizH4wap9uAwZYdmQcjhFF1O\nEYc9xddWbY1lWViWI3n0sVyqzdeVEDMlPDD1wM7bt5SKErVSNZo11rpyXI4cjjccDjccj3e+p1pB\nRCnF22F633p6XTNKulOLxiyHQQOLBv/yJjkRHeiBr8X8yKhjbhllOj2m126MTW2kT31BBMsJTYIN\nGeYBm0csJiKkql637AXhlJ1w0Qfb9gJ3KPRrRGaNxJpcYejQlGU16uI6hDn5YmrJKKZMCXY5M6fE\niDGYkU2RyCQsspnOzk0Sgu0d8ovzg6QQRD9FUmd7MdaFv1PUMcDXaM7Zae6xrnI0P8/j/8/emzbH\nsWRnmo+vEZGZSIA7eWtpLWOz2Pz/vzImqSXZSK1SSXUXEgQyM8K3Mx+ORyRu95h0qwdDlcngZmkk\nSBAAIyP8+HnPuwwMISKtkpeZ08khJOb0yLIaBmxwrh70NI3D4VxgCAPeBrztRa/r2ZxRuZLrcJLq\nwJIyS6k0dGNQw3LZwp5V/9toktXBqWvILL7PKj1GDBgVbov0DUikm6wr9K/PkXRDawC1yXOdhNHH\n8x2yuXIM9EPbw57lBXp95vXqzS3f/eo983zk4esjt7c7vtzfkHPBWcs4Trx6/Ya3795ye3dLiFEP\nQ6sMrr+fardYybmwzBVjDTFeWJZZY+GCw3mDbWYj+azRaiYEXLetS0k9iX9OcBN8UJ0tJuh9767x\nbVezANO7TmXDppzxJWO8ohRazBwheHx0ep/aRpWi+6EGVIJpNJS8k8rCnM7My4mUz+Qyozur30hH\ntUU2s48/4vb8poVS4R937fRY4dG1FFz1j9oprhDsVQZiOvN1BW63BxSzaYtsf6nZr8N62ztJSwsO\nGSNED9ZhsuaGmNIp1mtic8fva6tILT1z0mhaONCMJRvhIsLshIVGqQptBRsZIwRvkTbgqeyMsDPK\ncvUCRgqtNoqgzEPpNnpyBaKBjRi8XrNuart9hrxw8J9trbMXjZtSuMc7TwgB7z3OeULwPYndsxt3\nxOBptXB+fAAKl0vE+x7AvB3gVoOLroPsom5nAzEORB82Fp9Vc5FeyDrZojVKNhT6TWJWacnKQO1S\nDGswprOlrc6ZlBnoaeIwzevcEX1Zq9mv3joNFmgaM2eqwVQtluprIVjT3a+s/p+aGIzxSvCQ9jOe\nge3PZHyJ2XrWNQye/X5Ui7jgCdGzP+wopeGcYxgG9vsbDjd74hCuc8F+35lmt/dGSUCVUgtIIZdE\nzv1VPLZc76utWej7q3Nu0yJKqzrnrpWcK9YVTUsqfcZo3WY7Z7auU2hGev5v25ycaqnUqvBqjB4f\nYJwicQj4oDBwk9r3QsGqBwJa/SutLeQyk+uF0ha1ikSgNnKxpOzwSaFg5/xmpPFL1n9IsurqsvO0\nG1wx1U13vZ6AzBVuNU9Prk++3uq5ujKftsgg5/Ah4GJAgqVGR/EWGTwyBDSRpNJyU45X05ui9ZN1\nq43SmnaRgODUCsB6xDma9VTryMaTm84wQ7CMDqwMNClAwUpmlEJAcKI6udSMXv2aoaCpIlyntCKt\np6H0bqSHWRtWHdVLgXzuFWNgCBHXyQPea5HcXj4QgxpHD0NgN03E4EnLAlI5nb4+CVzWzcG5q/E4\n9Pe3G5pb4wguEkLo80/dmFyfyYDo5lG0Q3SiNo/X+eL6dbsfsUh38RFs0yIJBRGN/m7iMXj92HiE\nhvNRNWZK9cZikdSh/tI3ylU2023zdAP0SuzxrjOxu2n8NhuR/n94Wc+1rF1hTN0jrLWM0whCv2cj\nPkRCiH0rfELAQRn7tjP51xB7DJvuVWPgNI7L5vV95mf77XrLraQcZ50WzpVFatSQIKVEEyEOVhGS\nHv+mW7X0xJnOtJWrkUWrBu/Ax8AwWIZxIA5Bx2J9Ps5K3uzjOkQbKu0sE7VlhIqYbn7ehFwTLjtc\n8ooQ+cAfY9bybTtKu7bp1wt+PeE8+XPYZphPpSOsw+VeaFfQURM1OgxprJIVrFOdTIjgPc0ZijFk\nFHqQ0pM/SsM1oUh3/0EdHprzmGHQs7c14APWj9gwYsOACQPZWnxp5FQIKeMTxGKYxChBR4pCZnXG\nlBlBqP30npqnisdWT0sJMRlTGh7dmLosHcH0mdCTA9AKOSPIS8F8tjWOIzc3N/jO9PM+dN9KLZo+\nBIJXL8wQA9M0qvmzNTx87ay7PpfRw5rtHaQyqUUqrQi5VawXqkc1jGKedLEKEZmu57VWzQ5UxpGU\nCr/OCbfnYh1FrMxuodGuB02l3bK5/nQtp3OBKkr4xlotekUU5ioN6+xG/zfSC3zHN1Zyxprtt8Jz\na5YnAv7FEONZ11qUNj2gMfgQAGWGOhewzimjs5tOmF4wLUJrts+ctUAZ9D0yLuC93UYFa9Fsrd+b\n656rJ74nJELpn786N/XusCnrev2ztThe/0XvaHsO76qxLKXgisEGQzBa/H3oL6+Hy14nr+S6HlKh\nyGPrDlh1g2VX79ImlVwzLid8WIh1oLXyi6/9ty2U2+vqldqvvRa6FUbscOu2tovcWO22ZHWoWIk2\nRkEG6cckMepM0YxFnCOJ5rQttusSixKJbK7Y3LCiBA0XAsY77BBwk55m/DgSpx3DeEMcD8TdDW4c\nydbx/flM/ekz5/sHzpdCTgJZrelKWsgLpDRTKiwGZm+Zh0AzESsFSqJ1uzEnhVAqoZ/4qiiZR9Br\n0/k+KhXBXOdEL+tZ1vFww93x9udd5Focvcd5PY06rzFYwzDo2W22lNpYlkRKmvunszolNSh8ZXuo\nM5RWEJcxkrSj9LUTF6wegrq0QhCMcV3s76HoRtHQpAcl0qzwplw3o1VruwVQGlbzdfVmLYgP2qW6\npuxZghZX6zGuYcXhLdiqz4UVlaq0PlOHdW6uT3ETlTV54zah99pFv6xnWqYXwFVnawUna3fZuzqj\n8LqxtmsHUTi+G7isNne1w/MxRpxXI/MYfY9fuxYy28GGK47XQ8pXI/z+yiWTsspMWlPXsNoU6dhs\nIaEf+tp2qHpaZEup2Aw2WELrHAFjOsLiAIe0a9bq+iOZzrK2Xl/GgbHKCNfvKUCjNoWYU/akMlNa\n+sWX/tsWShGcUZKAXU8Fq25N28ou+l9Pyv0frkVU6CdnejHtH8v2aeokb3XDqb1gisBiDJcqpKou\n894HsB6iQVw/FXc7Or+b8LuReNgRDzvGmwPj/ob9/hXj7pZxf0PY7UkG7P0XHn7/ex7+8CPlkglZ\nmBZlvl4eHzjdC/l8Is2Fizc8BvDGEkMPw3UOi4Nm8SxAUQ9FVjlNNwbuCPTKYBNRnP8lyej51s3+\nwN3tnc5/OvTq1+LolE6++vRaZ3FBu7uGkGthXhK5qDOPmjo5zaV0VmPhRIleJTeaVeu5NCRi1Dl6\nH2sq8iDdotCCtB755hxU9ehREwQ9dq6HTVnlGvrh1gmsCSfrX7TWfZaNzttt5wIY6TR+69S4vXV6\nv/SgcxHErQiQOvVsExK5bnzG2JcYuP8f1spA1SVsGJP0e8SsExmzSSqMXcmArXeTnZAlgrMOPw7E\nODFNI3GIOqN3azHavvNWlHRs3jZJSEqZlBLLsrDMCynlDdlTJNY+6fy4FkyuiCD95yq1YrLgsqUU\np0YY/b5VIlBPUdpw4NUIBIWVvXJSnHeYso7S+v/D6LORa8aVRMozKc+/+Np/YzKPQgA/k29cd4dr\nF9mp+dfhpP65bJDrtaOUDlFtJ54upq1NVIhrMmIgG8guQvCEmyO721vG/QHvQo9vcdgQceNAmAbi\nfk/YT4TdSJwmhmnPOB57V7nDDgNWGuO04wbL62FizEIWR06V8+MjDz995nsL5es9cyo8zprllowQ\nqjLGBuuY4sRkB1xYMJcLLLM6aKA2emJk7Qt6qkq3L3vpKJ91jdPEfr/77wqkhiGvjOjNcNmtc5f+\nsHYDiFIbtTSFiMRijCYdeKuFxaDxcbXoDLy11o0j1lO3xq9h0JzBdfPrm431rlNOVzjLXueTBlor\nOruhs6mlPfGT1Y8baKG0+nfKXETnimgwulvn/MbhjdOPsZ15a7bvrXbNfTPrEKx0lrq83JzPuqy5\nzhj7UQhj2lUyhr1qFXtHabv5fe3JL+t5yVqH9w7vI8M4Mk6aJRmiJoVc4V06wUyLp8KkVQvkvDDP\nFy6X/povpJyotW2+q66nhKx7F61e9YtmnZd2OVw38C+5kVMjZ0ct12KpxdZi+n74tNDq89LJm+76\nnOqBzSpa0goC5GKZF8OyXH7xtf/G0Kvy7VbzAGtMNxFYH7D2s6L4swuhlKduZN6L5Jbl9+TEg94M\ntVRlpxaDWEsbIgwT4Xjk8O4Dx/cfOLx6zbjbEeKAjxEbAiYG/DjgpxE/aFaacQ7rI95NYAeyCzRr\nWVqhDDvC7R23PnAXBkLc0arweP+Vn37/L4SaOX//r3zJlfN8IbXMY03YThQ5xIG3uz3TLhKGineP\nugm1ipSyyoT6SbFbnPUHQwxPoqBe1v/XNQ6RcRyVLe1cNyS/zoOebvsbKQE9pukJOmCMUyPxItQK\nRhzeBpqtndVcoLv2bPf8+lWsQWikziK0zil8ZvW9Ns4iVTeg1olnxrhtvs82R+qbp2l94+wN5ZOR\nf+0QaiMj9DmUqB2fb1DFEPpGbLHdkUoRG30wewe8Ml57V6rdxNppvhTK51yG9X5cOzWNa2tV/od9\nYJstd37DylpFtOit2Y4hDAzjwDAo/Oqj3sPXYiwbeUe3oC4tSYl5Wbhc5l4kZ+0qlwRYTCfMxDgQ\nvNNutjXND+6kr1UqoozptVhCKb1QLpmcy9UjVi9Crw2recbaKysSsjJa9aDWEccnpJ0mhVIMSxLm\nP91CqcXSdi3gUz8e6bPGlbmqT3cvnE2usIK5wq/SKelrkKkYq0bqxlCNo/mAeA/DhDvscTdHxjdv\n2X34xP7Td+xfv2Xc7wnDgA0B8Q6c0+IYAs05zb1sHeIsDVqidiuopWVOy5lLqrg4crx7xe3da7wN\nnB++cjME6uNXfvyHI9+HyOUCj5eZE41mDEMcSROMw57DNCDBQG2YnDECpXUvUSmsuqM+GFL0uXcj\nL+t51jqPXE/kG3Gs36fS5RLStUq1rTMWnRH5EPE+YnowuXaVDoPHGcsQHdYkstGsxhi9noCtwXnt\nAEDf11wy1IyPAYe67AhaLKm2J4Fo6NbVikthz9bWwOTKmgyyCrztapjRNPLLGgtSkZa7B61BmbIW\noYBokrwyYxUC6w4EvTbbDYq9wnu2J468kHmedZknRevp/LdD3teDl4qHrpRANbOXPhtcGbKIVYJa\n8Hiv6InrYyt4MuJp13mzsrArpRRKzuSsxSynRM59PtlZsCFE4hCJISAipJz1MNcPgd4Hnac+6Sxb\n904uRSilakZxN1Vfc4G32EO4FgWjDFzNz4y4rnteyY7d2r+PDDK5CCkvv/jSf9NC6XpHtJmh9wcb\nYPN91Q+2z7FP5pcb2Wdl+a2zydaofUiM9eA9dpjw04Q7HPDHG/zxSLi9I969YnjzDnt8TR4PNBeR\nZpGlUubSDcn7hiWNUov6IGZNVahFU76XosWySsV6w/544LA7sh933BxuSLsJJ5XzTz/y/fv3/PD6\nFZd05pJOzPNMEeGSCtJgN0zswkiMkcMwEW/ox/5yhR76oah1n1slT7ys51zG2ivE+mQzWk/SWxdp\nVjZy3WwZnQ8Mw0QIQ5dOGFrVF6J6TOOFGDy1qK9viI5xDKoZ86qNU79K9YdVKDd3e+p14GL799Yi\nifGYniiicWD2SfcgmuTRgXuLUWtW6czGTu5xWDDqmuJ8h11z1xFXJcWJsb0o6nX52QRyJWuI2aDY\n0hSGflnPuVYWZ78vu791s9LfU90RmqhBhKm9gegZoYJgrSWESIvoAa/nRYJsRuOmG92rMUF5ki8K\nraqJvn7/7nBju6LBOp1LrtFcw8A07RiGSCkK2SOpFzQlw4XQfYi52jSu366t91O7Rr5di6QWR4U5\nVBPsfMD7SgiR4CPZJz28Se1fW0Bqh4+h/qmyXtd2exvA/ozZyrYRrG3+6k6zJoU81f5sA+ZtQKyb\nh3EeO+5whxvi8Zbx1R3Dq1eEuzvczRG7P2B2R5KNXJZKns+kUlhy6qzFREmFlgu1ZDXXLYm0JHJu\npFSZl8wlJSqNOEaOt0c+fPrAm7t32GbYjRPTEKll4eHjBz5894kf/vkjp3Th9LnyeH5gKUWFwlju\n48jkI9EoCy3uvXbZKZPnRJ9Obmbw3XGTJylyL+uZlhJTngx/VwLDerpWcJ/WD3M9UhUfBna7Pbvd\nnhgGrPHqrdkMUg3OBLw3uAB0XyelvauhuorII026lq05qlQlAFXZ5vs6DrVQ9Z431mNt6PIoh0jB\nWkVA1jg76SjOKrlSB6D+PDWFpqxrWGfwpvsfW0GaajBbK1TTpQn059eYniZhtrlnW7kBVchFKPXl\n7nzW1dmb1wGdaJfZiVfrjFtEPVQFg2laKGspak1oLDFEzGiplT4ME0opmJyoYnBOiWI6L8xaGPvB\ni37IMl3TqS+vGuMo2NqwPhLiwDiOWijHgZxSj2nTGhB7IfU+bGjHhtbIdd6qut3r86cfmJWhw8oS\ntyI4JwTfCGEgxpFSM9AolW6L9/Ra/nGX/huzXjvL1V43oW11v9aV1X512uknC4OyPDthZzvF9rkl\n1kEcMdMOd3OHO95ib2/h7o66P0CcKDao/dySSenM0oTTkjhdzpzOZy6XC/PpTFkWWtLctVbVpX5J\nmZQKlzlxXhJzSgiGw+2RT58+cbM/aFGroq4rPrDb33D7+g3vPn3Hx1//K/eXEz/NZ+zlTMsLYoSZ\nha/ns944XrPZnA8YPzC7gcUN0ARHxYrgeWJpZ+Clr3y+tT6HSpjqs7deKVdGZ1uLpQGa3YgxwXmm\ncWIad+ymPefTIyKFvFQWV3CdOGG9wQePc9q9qV2YI7jQDZ8dQTxVAqlI7wZq/zHa9shoZ9fJQlYP\nVlVKn02qjlKNUOpG97/OnbpBQFMChUbKyWbPZ73R4GaVcFNaj+xq3Uja2C4UVx/i0nQqUQVSVVeW\nUhu5vHSUz7lU8rPOf1f26DqDW1/2ykxtHTmolZYKNVdooqYZxpOzHmqaNHLOlAbWFUyPZitF2a2r\nnMMZ003N+8y7F6p17DAaSxOD84EwjEzTxDCOhKjQqw9eg5udVUeqELCupyDpQF/Hc97ofW28EsRE\nPa5F0wWeoJH0gumwVj1hgxeGWLUTlk5oS302z5pess4y/0TzKO0T2IaVoLD+5coy6MzW1QSc/ktD\nNK2jy0s2k/ImiLO4MOJvjrjjHe72FfbmSN3tOflIqUI9XainhWIc4gPVBubSeLic+fL1K18fHjg9\nPrCcL9SUoBSctM3UvNbKvCycLvq6pIQNEWjkN282QXatQi0N4wLOR6bDkdcfPvHht5/56fHEv97f\n8+PDA7NNNFHh93m+8MV7xdfDCDuPM57FRYqLmFoJTfDoPMn1I2V7IUw865LeEW3gzgr1rzO9VTzd\nu3lsZ6zWhrOWIUQO+z2H/YHL6ZHL/MhyztRclAkqBktUI/TgcLZbLRqnwKgocSf40L+/RmGlVpCm\n5vzIGvass1PXmbjSPVzFquemsX4bZTSRTXW1Euau4/+2pb8Lohq0ZhCn48laO5Iha04hIFAESi+W\nuTVybVogSyX3NPtU6v94kV/W//RSkX2H/teZJPqeSs+mtNJD6buEo+RESZmWix7ijSf4SPQeawt1\nzuRcKXWhtdThTn3Vzso2BmKIDDHivVcyTdNnpfZGxfuA9wPWeXyIxGEgxIiP3TzDKWPbSx8zDOqA\nJQK5lu3/44NRQlEn1NnORNMw6dr32bVw9JGC6fIpsRh/RYCA3l0r1Go79Oy9J4aBcZh+8bX/xukh\nprfTsn28/dpZWzqb7POQ/oav16YJtD6fdJh+GrbgImba4w5H/O0d5u6ONu1ZfORUCuf5xJwKqSjr\nyrhAs46lVL6ez/z05Z6vDxq0vFxOtJQICIN3TDEQgwcjzEvidJm5LIlLKoRph7RKjJFpt8P7QK3C\nkgrNWGq1xGHP7Zv3vP/VIz98vuf199/z05d7SirM6YK0RsqJx8uZEAdCHBHr8bnQxICLOFfItRD7\nKU4wONsPCd/0DfzPvdaMPkSedG7adV1dRq7n+JVsigjeWIYY2Y8TN4cDy+VIq4XT+YFUmkZqdalI\nT0OFoau5t6JowWlnF5xDmqfWhKXp/JEOC/cCaJ48P9ZYmgV1z9EcyU1G0jvMK0tXtrGFHgJ617rC\nW86AV/N/2f4+U3G4HmJXBHLT67XOI3Nt5FpJRedYpb0UyudcZkssaohRa03pUKis9PjeldEgp0w6\nn0nzQktaZMZhIsQJHwfEOJYiSFbP15wVBSilUZsekgC89xhjCDGsKRPK7O4oQhXAdjvGODAOI3Ec\ncF7NMooUbT6dwdIPiUFJPK37vLbWZ/DN0vBb52dYgy+kH9jqkwePrVZYVGNp/BOf8N4Vp6WQrT7X\nzqvr1jiMDOPuF1/7bzyjXK3MTR/GsjEKtwPCtrYrsXWOuWlavFvnk8ZBCJhxj90dMIcb2rTTEOWU\nOV0WHpbEeV5IWYXgGAs+YHxgaZXT6czj6YGHx6+cTg/M5xMtLThpTN7TpohMI8Yalqzu9EvWQui8\nY3ez5+71K25fv2E6HMBacq4IhZYFZyI3N6949+FXfPp8zx++/4H7rw/kXGhfG3Na9M3MhdPlgg8n\nmkAQMKUo3NqEIDA07awjPXkEqC+l8tlW7tl4cJ1TKo9MN6F1BrStftPqQ22IwbPfH3j96hVSCyv1\nNecE1dCSsJyUGZizx0eLDxYXIA6uf2ywTuG0WhItZyh1c2MxrM+PxnAZ29EVjGaqGq98j7oevO02\nk4QeDN7bQuUMdKh5LYgdwjPOId5QSwMp1GaoZDzqBFSaoTQ6zCpbAkTuRbLVuklQXtYzrZVg9rOR\nVf+1E/6sVS40UpFUyOeF5XSmLhWHIRKwB0sMAw3HnBu+qNe1ut1UoCpk0PdZHzxxiOq7GmI3OcmQ\nss6kixpYVAvgGAdD9AEXPBWFQY0R6KSjHg+lIeJiYNM9irK/7VWOtYVbWIMz6M/I1YHtOrBVZMZ1\ntEYdgSCGhHcLzmohDsEr7BtHgh9/8aX/th2lXd9oc33oV2IPcAUS5QopGhWL1qon19bt23AOGwN2\n3GEON3C4oe72FO95uMzcL4mHWYvksqhWzDlPiINeXqcU+yodG7emOztYpOiMpohGGhmvjiySAWdx\nYyTGkbs3r3n76QMffvMd7777yOHuFusDOaunp5SKbZbdeODV63d8+PRrvvvhR74+PjDPC0tK+rlN\nLaZKzpxOj5ScCcbiaiO0QhBhMKYzexWCDkbdUtpLevOzLWU4F2Dt2lbtmPbx1wLDxiVTUb5GYtng\n2e8nDG80dNlaonc8Pj6oO04V0rmwLAl5FFwwhMESB8cwOqadJ0SD9SAUasu0WpDSg5E7VKu/v0Z+\nGafl0+LUsLj0+2KVNXXI+Gf8gHV8uEa69ZN9zhlnu/m+sZqHKgVTIYililrylQa5Qqmitn21knKh\n1NLnYmWDv17WMy3T8XNju0Sp5/HSIbeOxjmsoiBFqJdMPs2US8Yayxh22KbwfjOOWBqjQIgqy8i5\nkbLOmGuXhQQf2O127HY7vAu02liMYV4SDUPKlbwkaIaSK0OMsN93qYnag6o0U7QTboXW+v3rldCm\n/z/Rub2z27jDoF7b3imKtjZQXaG0jRL0spguPezmCK0S/IB3Ee9qD5yOxKidr/O/vPx9Y+gVZeyt\nMOuaMWlNb6lhk34gSBeNNgzN9UwVowf1ZjwmTpjpALsDZdpTreOcC/fzwuevj5wuM/NlodVGDBE/\njtgQcNZQND8I59SZJETPMERoBWeEuug96WLARnWXGJylDQPWR3Y3R95++I7f/sWf8+m3v+Htx/fs\njzcY7ygdSjCl4YwhhIH94cjd6ze8/fCBNz9+z+cvX7j/+pVlXhCpBOMwrbFcLuSU8M6p1R0wOrVq\nMDbiceRWNjiuvhgOPNsqa+wQqxfxtg1dodhtbN7zTm0/xfexghsj3kJwBm8NwTumcWC+XEglcVku\nnM+J1BbENobRM4ye/SEiLTCODuP0ZC8UNW4WDUe2PEmQ6MSKNalEPWG7YbVRn8tW6FAdPU8V4Drf\nWrkQK6Ow1ko2WWf+ziEWCpWKIC1TxRJwII0mjlK1C09dxlTXItlqh75e7s3nXf3wQuUJvABP7lIj\ntr8EU0Fyo83aWVrrqLsMlW6CAcMgiHGbNKMW6TPm1TFK77dxGBmGAWscxTZcbVjvVdphLLk0ai4Y\ngTQnasnQD1X6jOiL2vq9ZrRLDMr2trZr6a1gnejeVoqSiarqjhHzcxkh6+ijsQaGr7rn1nOPlbgT\nCL5ivSUOwxZ4YO2fbKHsLbPpc5ntNKSbQOtkAzGmQ0BG46w6syrQ2VYVrAsw7pDDkTLtuQicLzMP\npXDJhXNK5KoPbPSO6CxTVC9DsYZmoeZK7jrJlDOlls1zUEQoCKlWqlGX/t00cfCB/fGON+8+8OnX\nv+U3f/4XfPzuOw63R/ygsERpDdcUaPbe46IneBgOO6bjgf3tkcPtHXevXuvNkGaQojE3orOdXAwh\nBKpzWO+ZphFvhGBEA07LAmmG+sv9Cl/Wv72kxwyt8KZhdVLVTamrCLeEdLW36x8D/ZNwNuIseAvD\nGDge9pxOjzw8PiD3wmk+s1ySvte5QIsM0WMm3eRsg0btz4Vdv+zPclat8xjvsT5gfATru6ZT0ZFq\noBpoRdB/3ZPj2zbg1AK7CrYRhUpLwdiAhqlr51JENXCtLmqF1iwiXmn3RZnnSvrQ0GlvNRIpvORR\nPv9aZUpPZ9W2cz+M9HvEAg0nFidW9ZRFKK3QUoNmlNTjLDGiaUkNEEMLQqh0ok57YpVpyLlgqNts\n1DnPME6Uok79eU6aGCOVmjO1DAi4YgAAIABJREFUOOygIc9VPKVYVR3USisg1uIGwzho6klt14Nh\nyYU0LyxzIM2BGCzODZvrjsqRnpIZe/Nl1HWq1hXd0LlkIKoUK2qsnXPu58Eb/876poVSQH+4ejWz\nRaFpnuLNTZRJ1ZyhWQtxxA0DzkcEixR1/ZBxou72LMPIfSn8eDpxKpnamYHGOaK1RGsZ48A0Dbgx\nUoIniQ7Ea9NZymrm7INHakSsQgBxN+HHif3tHbubGw7HO959+MCnX/2WT7/6NW8/fOLuzVvGacJY\nS13ZaL3dEGeoVsi1kk2jWjDBMR32HO/uoFaWh3vyfCLlRpKqMTXGkJvCeW6/I+52HIaBHUJIC+b8\nSH34gsy/3F3iZf3bSzaK/XqQAzDbKdVYPQVb20Odu6uOnvvU+UT67CUERzju2e0G5ps9j48PDD8F\nqhRO85nzclE2bBGoBodn8COD90C5Mg9b933tj4fth0ZrLS4ErNeXdIPz2iqt6SdbC7kzq2X7P3bO\nh7VI1XQTlRN0rZkUTMmaZG86F9Y0iqi4vVRBqkWaJjlIDxLfvGGt3eCyOfyHxN3+5139/VidlXTf\ntH1fZXM1W/dTZzzBBryNILMGLGsdUojWBWI0iFXZRquqKHBeG5raGqXHX5VSSSV1cYI66TjnmMZJ\nA8+tI/lLn6ULKV1wizD4AR8t0VtqcLRqSUXjB5u1WBoxqB4zFyH1zNXaNFDaO/BK41Vo2YwKmRrT\nO8ytjKC1o1JbZskLS5r14GvpQdCeGHu2pfm5JeW/t775nbzNLZ6eiOCJ4bnmLzZrKcbQgoch4g83\n+GmHMZ5aRf0ww0AaJk7W8UjhUeBcVV/jrSE4izM6CPZDxI8KoxZjkMrGtHLOM04Tu92ue142rDRC\n8Oz2O463t9y+esXdmze8evOW9x8/8em7X/H2/Uf2N0dcGKCfysTqRuusMgQbjfMy83C656cvP/Dl\ny4+cT49QKzfjhNsfOOfEOS2ILHpj0jTJxDrCODLdHLl9/Ya73Y494C4XypcfmXOi3d9/67fwP+0y\n3fLLGHPt4DDbKX0tkKtZutLXVXCv3q55E3YbmgZBjxPjFPHB0CQz55lLulBqYUkBY2GMA2MYGcLE\nGDwimVy0K8SgJgLSZVG9cK+JutY6tbUzBtOkMwUNuEbtOZetU+fVlo5rZJu13XBAuxIl/OqsUnzr\n7Ep19xGrTEipDZrrGmc1jlfTILN1vGsGZ3jJo3z2pXM56W45OneWzt1gsycUTOMaDG4DViylqRl/\nycr5sBi8jzRboVSVmKxNDHSdbg9h6LaKrbau3VUzgBCCuv0YS/aemhakFS6XE0LGuMbgBryBwTsk\nOFqCpRQqiVay2p0ZJZvRVPdZcqIslZouLJdHzqdH5rsjN8cbhmnCh6ioSvdk7kcIRDRUIKWZZZkp\nJWGMYJ3t2Zb6DK98g1+6vnGh1Cf/egLg+qbUHnXVM7iad1QfqXGAaYe7ucHe3GJCpCmLgCyGRwyP\nAjmMhGNgqupBKDVTRS2fXXCUYCneYB0UEWWLWoVUD4cDPgT2+z23xyPTEBmHwDQO7Pd7Djc33Bxv\nOd7dcXylfq63d6/YHW6wzivrr2pYqXXKPozdceJyOfHl/gd+//t/4h/+/u/4b3//t/zhd/+MXBJj\ngxgGvVmxpNJoS6JZsN4zjiPH2zvevP/Ahw+feLM/MInA4yMXa6kPX1ED45f1PEs3BWfBmU42WAuk\n0Zgf5zSdwHYyDaK6xZwTy3whpYWSEwbY70YOh72aDETPsBu4fXVDozEMA8uyUGomRM/xsGM/7hmi\nQyTjjCUXZZZWgFbQMBG7zWiUjKubC7YzyWXl5fbnypruz9qVKMayxQ0YndMboftpKiPWOY35otVu\nxm4wXgk/eIdtBofDm4AR/T1N4+O2Tlz0sPCynm+t1oqrKUaryjaVIkgBUw1WLNkYXAUrluAGgos4\nE5CiWalpySxLJg4DNnq8tdRmEKmbFrb1CDV6kbySaEQZ3VyF+8F7wqTEtXQxnB7uOZ/PLIulkTH2\nhjAGoncYiZR5IbVKTjPz+cQ5KMkSgxpslEJeFvJy5kuaEalMU+Tu1S2v37zh9tUdN7e37PYH4jhu\nRvHQeq5lIqWFlGZqt+RbG6Z1XKLmBX+ihXI1ld6eH8N2on0qnF9Dl7PzJB8gRBhHzG7CxlF1W6Vy\nmhNfl8xjE4hRvQNpXC6PnB+/kkvBm1VHVqlSsBVSbczdbDeGwLTbc3v3io8fP/Lp4wfubm+52e/Y\n7SYO+z27/Z7d7sDucGCYdsRhxPmguH1RSzs9aamOR/0UHa0Wlssj3//L7/i//+tf8/d/89f809/9\nPQ8//MjeDrzZ3RAEGpZLA9dftovOD/sDr1+94d27j7z/+B1vDkeG1qj397hl4Tz+C9a8wFvPtZRF\nqrILpaS7669G/2wzTLcK3awhxZrPl7hczszzGRXy7AmDYxwiLhjG3QDcMAwDt8cb5stMyonWlNQz\nhoh3BmM83lmWxZBESLn103KHd0UNMHDKILTVdqLu6pfZtiDltjpYSZ/vG5WLyJPZq/7n6SxZ2WY8\nONdZGGC9QrWmGbxYgvFEG3DirkHyTYtua5VSMlLy//uFfln/U8uY1Y1J99JS1G2nFWU6W3GYqnBk\naEpm8S4S/UhwEWsTrUJKmWVO2F3FxdjDxVWXWUrVA1zRAqMayhVNcbQmlFqoVUk3+jwENRbwDtMq\nD/eN8+mhNz0FH+Bg94zTgAuexVuMVHKuzOcT3lqGqeCjGm3QGi1nLqcTX778xPn0Fecst3dH3r3/\nwrv3H3j3sdAa7ATVbIoDq8x17SYvpGWmoY5AmnYjuE4qalyJeb9kfWMyz0Z5uE4kTT8Fm56+jaUY\nR7Kei7GcUTjhUhuxVIwtYB0JeLSWi3UUY/BxwA0jtEKbLUurpJRwzrBIJUoj0rDWMy+ZJStp4XA4\n8vr1G7777lf8+V/8Ob/97W95/eqO3TQxDpFpnBiGsTtNDDivMJfmXfaAXUHDba3tvoVCuVw4P37l\nh3/+J373d3/LP/7VX/HPf/e3/PS7f6Y+nhniDikG6wIhC9F4Rj+QjcEHy+72Fe/evOPTh4+8f/ee\n16/fcre/ITahWE/9es+wO4B7KZTPtVazZr8VSbd1k+t7+1TjtW5czVmCD+Q+O9GNJDO1QZ12xkgc\nA3EMpN3Ecp6Zp4l5XkjzolBnh32toOkOTjMgnVFIuIpGYq2s1ZXtZ1rrmXsVVRg/9UT+eVdpmlUb\nPOMwmm+nc1nRcYPmWq5MgR4aLqiIWwQXHWQlGAXrCMbh+oxSegfauq9oTgt5eZmfP+cyKwGrqwFq\nrSwpqzVdNbhmaUbtCEU8oVms9cQ4Mo47ShF8iNQmLCnhUmEYRY0A3DWiyjk1EbfOdZs5Ryl1I2PW\nqu/1hlwatrBnTexQE5VWk5IYB88QHdMYic4RrMWitnUlLaRF54Zriok4R7JqKFOWhfPjiVZ7l5kL\nKXXtbq4c7xamw44QA8Yaai3My4X5fGZJ8xPkx3cinD7DdNb6L13f1nBAROnEcnXAl7VINqFiKNaS\njOWC5YTlvjZSKvBwwhbBjlM/5TqqcRSv+Wk2RBpK8b8sC48nvVCYtgXxhkUlJstFtZXTdODm+IpX\nr17zm9/+hr/8y/+FP/uz/8LxeINT0Q7BKUPKGh0At9r9LUsl5xXm7cXS6WaaloXHzz/xh9//jn/8\nr3/DP/5ff8Xv//pv+PK731G+3GNzxUao1VPCiJRCsIHD/og1DXYDx/dv+fDpV3z88Il3r99yczgy\njhMDRpNHbm7x4w4X4rd8C/9TL+8cwTuccU/g1i79WDeFJnQPRWUXerBu1JiiYKmtsCxnhIrzgTgO\n7A974hDUhWleeLx/wNlHgnOUOJJLVvlIXmhFCD4wDo4YXO8wG0sRijSKZJRgdDUKUHdrRTI67aH/\nqHJlmmPUPNqss6yiB9dOirXQWYJKatIiWTfds/Oas4lY7Sid07xKWeeahZoKaZkV9sqZy/n0zd/D\n/8xLtYIW0wX6tXu05kUlH04ctfv2ihEMQd+ncWR/c8S4AMGBcaRUcCnhStVwZecYhojpDP9aK955\nLUDGkFLGzlff1Y0T3mUqq0PQimRgNJ1jXmbOpxO7KdJ2k1rXYXBYbEdIWikYUZb0MAw4I5QUGEJg\niJEpRi5z5XI6qd63z1kvl4W7x0dubm8Yp0G17tLIJWlX3Ao+eLzTsHPD1cBgJcb90vXN25Erw3Vl\n4HXs20C1juocNUayD1ys5RHLYypkudDmggkzLgTCOBDiRBgCLgRl/KXE+XzifFKT83m5IAZ8VPNd\n37WY54cTeck00QTu27tXfPjwiU/ffceHjx+ZRk+ukBZleZUqPXKoPXlpuO56ejcYvFHD4CVnzvf3\n/Pi73/OHf/hv/PiP/8TDv3xP/vwVnzIjFp8rMidqs7gQ2e2PhOg4jAF/3HH77i0fPn3H27fvOd4c\nGWLspz2HHSfipGxcF365u8TL+reX9w7vQvdg7WZzPXVjI/XYFYbyOK8Poe0OObkkrLOUVpgvJ8Zp\nJI6RYRrZ73d475jPZ6RW8pLxVmd7Kakf7OVyodLUAcWPYAPWNEQKshRqThsJYdMai7ogW9G0EWPs\nEwehzgewKjtxxqsMoHeRska2rYYExmDsKj9QVyFrRMkPGKzT+C+D6RtPg26sUZZEuswss5IolpxY\nLi/SpWddHdHQ+003+do0G1KKolsNME47yeC4Fkqx+GGkIDTvKK1pd1YysXqV33Uv11rXWbXGZQEs\nS+qzwP48uNzli72B6H6srSeLeOeoxlBy5nx65LIbyTeJ4JQItgVL9/vYGv1ZhxCw0lh8YIyBw26P\n5AUjwjzPLJeZe/lCrfozXS4XzqdbdvsJHzzGyBaPKEaIw6CHgBiQ7txvjDoC/TFUs/8A3K4zlDpP\nXXp8VhXtKGUYsbu9FoHuBZgazM2op2CruGYIOEa1C0Fqo2XdnE6nB06Pj+SlUHJTM/UGPkRMXE/d\nGkdkjLre76Y907QnxlGzBFHXkTlXvWn6KUZF1XoKghV6W3Vt/dXfdJogpWGqYHtq/Gi18x1dYIoT\ncdgz7A64/R572GN2I0yRsJ+4eXXL3ZvXHHYHNcleiRvGY4eAG0fcOEJ86Sifa5nuxGrohfHJbNI5\n1zvOoKbPIXZv3kAIAd+7yd1uhw+O+6+f1eUJQ6k67xnGAQssuwvL5QI1Yo1jmTPn82WbD0pT2YZ1\nhtYGQpvxzeOawzZLldYt9mQbW+if/XcPf+9AkGvwsrNeLcUU/NJZpemEH9u6rhJ1rBKLNQ6Vmrhe\nPA2tFEozUAokoc6FsmTSooUyZxWct/piYfesq79PK+t6I/fAVqiskasMzzmwvhNYPG6I5FZJRmjW\nUEWdmEzwhKDFzbiAGtaYDYl7+vvgA8EH5nlR03Sl4XZ9p0K4IUbiOFDKTCkLl0vjfDoxnw8E56i1\n9u5ujdLiiQJCMREjqsmdYoD9AWctwXlSKQiW5TzzYL4C0GplmXcq/XA6+qo9caeO2q16qzDyEIL6\nFZvVRfaXrW9bKFcz295VKjGh0VZ7Nuew08Rw9wpujpwFwqxYup6oRe3lAGMaxaswVQTm+cLD13vO\npwcupxNlUUh0fR+NszgTiCHSBsHimKZdNwkeMMaRU+PxccF5x3mZOV8ulFKuxr2l6SZmVEOnmLpX\nyy9r1sxcjNXk8Gm34+bmyKtXr1nu7zlbB6UQQ2Qcd0z7I9Pxjng8Em6OhMOOsBvx48AwDQyjBpuK\nQM4ZRPDOEoxBgkdifCmUz7jWDtKuaenOPdkcPEMcGIaRcZoUBh+mzekjDh6R2unrAz/8uOd8eaRK\n4TzPjHlkYsJ6Sxg84xixaAfrQyJ+iSrRqFeht0UPX84/EUh3XHVljjd5ErvG2muurNb+hx06FTFI\n0xLZRHBiVK9m6TeuOhtIk+1kLp0JTEP9PFNBsoVcqdlQ50KdKzUX0rJQSqY0FXrbF3nIMy/TrQud\nohleUQ3nC9I7fWMN1ntsUEMKrMfg9B5qDdsKSCV3P/5cM2S7aYSd0+g2g92+vrWqLw8hEkLsSSFR\nkZC+N0pTBycXPHEamdKeUhP560JOicv5wvl8wXtPzkURCuv0QNilTq0zXmvOGxw7hIjfW4YwMMaR\nOWW1/qyQ58zFnXHWIbVRhoAPmq9Za1FD9pT7AcIQnSNaj2n6PPwxxlHfuFDKRl+X1jRjEhDnMHHA\n7/YMb94SPn5ivL3jkgvD10fM10dMzbScVCNU6Ti1zglra5zPZ04PDzw+fKX2E60+8EpZt80SbWQI\nE4yG6AfG3Z5x2qs8QwyXOfH14YSxlssyc57nzeRZ1I6ia488g1HzaiuaT2hENziDgLWMux23r9/w\n9sMD8+mMbcLj8TMlJd18px274x3D8Zbx9pZ4ODLsdoRxwIcuZO+4f20r9t8IRa3KijSqM9Q/ZiL9\nsv7N5X3och1PcF5T2kMgxsgQB8ae2D5Ne8bOfo5xYOjBy5jGOI2bifQffvgXPt//xGVZuFxmpmnE\nSrdOjI7oIjEMGGuJoyYz1Na2qCqNojNYpz7E1llM081ydWaRPh9aCaw6l9TT6ObaggEcRvTrKTUV\nmvTOsif0WGe3+VJrTefl9PlTrdRSKSlTZyiLYJNBlkZdCq0o3FVq1VpurvDgy3qmZdhMHZxzWrxi\n6DmTBorewz4GXIwY58F4MG7LAjbiu0l+ozidI0ruTlOdye0sPbrtyph21mLD2gF2u0YXKKWQc9b9\nVhoueIZxpJQ9OSfSfGG5FHIuXC6zxnSJajRD10Ku4c2tVVJayMtMSQutVpzttnPBa9TXkjjNM+fz\nTGlN77slk53rqSmqpyxFXdakVI2lw+CxWDG00ojjQE2/HPH49oWyVk0qQCgYinO4YWC8e8X05j37\nX/2a8Ve/YdnteXx4xLd/RS6ZQtFcyVRoXb/mfaaWQG2VtCwsy6yU4JyVgdfTQvRMpZKLIQ4bjLQ/\nHBl3e3wYECypVC5zAquGv/OSKLVucTPOWIx3WOf11Oa7nVIX/lapOiyOnv3tbXeO0BPgME08fPlM\nWhbEgBsGhpsjsRsp+HHCx0joHSpdr6QpFF1CI0JuhSaNuSTmkknyRxyLXta/uaZxx83NLUPP3huG\nQV/r7+PAMCgLOsSR4CPOe0LQEzw0jsfeBTpHroXzfOE8P3KeF/zjI96IiqAt+EHJCxjdDFbHkSVn\nzuczgzhC0M7MeXUvseKoFAWoWuOKXGk+qelZhabfFxaj8UMoh86a1bXHdJ/ghojFGj24PpWLtA4F\nGwpSLC1XypyRS8PMYJNgMlDUULu1Pq23veD+UVOgl/XvL9O7ftNzFQNxGNRhSSziILpIGCMhRpwN\naHSCto96XHJE4zFGmatJKqUkli7LKD7gbcDZoF1oLTinM0zb59+uzzONcZSsHWEyUFrBOIsfIqPs\nKSWR88wafjovCedmQujsWq+Zvb5/XGtFSma+zCzzQkmZ4Ax4HYF4p3Z46yGWUvHGXV84HA7BaGPR\nCjU1FmYtoLmR58x8M7M77Jkvl1985b9xoWz9gVVItDhL8Q53c2T36Ve8/u2fcfzNf2H4+B3nOPDj\nH74nnmbM50caZ3JRiEe6m3wpBZeTPtS1UIs6o7SSkB4aa6zD+KADZFQCYEfVQE77G+I4YX3QANrS\nmFNGDD0yqHbf146n93Bl17VFtQmt5X5CU9KDd/2NnCbuwqCylRCJNzd8vf/C+XKmtIqNET9NuHFE\nnEc6Xt/6daKqyLet4D3qf5vSQsuJh/Mjj/OFpb5o1Z5rHQ43vLp7zTSOTOPEOAyM48gQh80j0oeI\ncwFrHZr92PX+tYIDawP7/YEqhfvHe378/APn+cR5vtAoeCvYVvAo6dR6gwsOH7U7EISUE+cZxOpB\nzAUlcFh/JdOY1V5OZNODyRahpR+BaKcoFqEpy88ItptgO+v1X0nDisV0v1ZYjbN6YLU0pAi5SxHa\nUjGLYDOYDE5sd+e5zsw0SullRvms64n01XQ4dBgG9b4WixQ0lHkY8DFiTQCxaofYrv8ueHXcqSX1\n0OaK5EorWYuki/ryuc9D/SaV0pOZ7VrxleymnanJBuMcYRi6JKMireCcpeWFWgrLPGPtjjioa5WP\nsROC0L/PieVyZplnde3pnaIxK1PV4J0nBsG5RhxGxmFiCIPOH3sqFFagCbVUUm3UVMlzYj5flGG+\nJB4ffzkr+9tb2JWiETDeISFiD0emDx959ed/yYe//N84/Po3mNtXSGsMS8Hvvld9ZCfZPPU6lNa6\nYYFGVJVcFOMuRSnzoNBo0yKae14ezm0FzPqg2XvWUFrrw2JR6UetPzslrzojnYkulLIogWG5UKve\nEDFGdtOO4+HIbtwTDweOHz4gQ2R8eMXpfGYpGbEGGwM4RxU1UpemBVLrbkPaCpWpeXWthbQkLqdH\nPn/+zNfHr1yWF2bhc63b2zvevHnLNExaIHs3GUPAh7CdrI2x1NpIKZNTpknFKm+CEBzW02eLGoFV\npep9Us4EC9EaJu/JNZNLJteKmIYNYLxQW2YuFVsCviksteX3WYvpjFRjXddTdrhV1PTiqTePQf+t\nlW5HhlpESu88m9FDoAqw13SGNQxYT+a1Vkyx0F1gqDrH7Ageq1zFGZ01scoT/gj6/cv695fqd+2G\nUnkfaAEk6nvSaDpT9K6bCGhRo+fYIoK1oveq1Tgu1yy1W9fV1f+6Cs4JrpY+Q3T9cLbOR3VmbozF\nOtVv+k52kxAwwWPGgRgcwVnGGLmcHynLjKD3WAjaDXsflHTTIdx0uagRx7IgtWJCwzvLiuIbo+qF\nIRoEyzBoUPQQojJq+8De9Hl86ykohUxOhbyol2xrcHr4Ey2Ua5RPa0LzHrfb4d+95/bP/oIP//v/\nyXf/6/9BePOOk7HI1wckjvhxR1hPHsErk04arbO7mjQURVCxcyma4afmvMqUlZJguSCPX8mADQPj\n3pBKn6fYHvRp2Ayk1Vxa9Z7WWhXkdip0Wha+fv3C/ecf+XL/mYev96Q0Y6xh2k3c3d7x/t0H3r55\nzzTuMDGyu3uNnXa4y4V5Wfr30aJfWsM2jSdqtnbOk25WCplYaI1aCo8PD3z+8Xt++OEPfP78E+fL\ni1btudbrV294+/Y9MQxaHL0+/K6/9+qvqjqyXDKn0wMPDw/kvIAVXDSM/0977x5s+5bVd33GnPP3\nW2vtvc8593ZDeHWgCQjEVARNoYFoYpEIKpqiSgvRlGBJCktTKlUK8RkrpRIMlAmaAsqEJCLVFIKV\nmEpIiClSkURSwUiM4aFJP6C77+Pc89p7r8fv95sv/xhj/tY6h9unz+3e99zbt3/j1r57n73XXuu3\n15prjjnG+D7WPd06ENPAEA/EMhLLxBD31CkTRNh0AVd6/GEgG3F6zCPVZ9yq6ptbErFmkrlAVClG\n6BZ8dWo1h3Hr2noRRQ3aFAkM6KNncgUHaelngAe1631CocQwBIaibL6GklFVHjV4a9MArTKqPZ4J\nop9obD2nV+7TI0Tc/OGdp/hKCJUcMs5n0wAQEz8zGoS9uK0z4GrFmaevCOYFWSmoRjG2MnLVgsbV\nAkRKNlStC3SrFX2/IvgwI1WDE3qr6EJQPdVyvuFss2Y4O+P68hG7q0tySjMoqAvBRAJ0b5vGUSkg\n46QFTVUXpqP8rNrJdV3ABe0W9r0eZrsQ0ImVzS1TIcdMztWUqKDmrMtfJsTt2F1tn/m5f/6Jsmo5\nzMrRnd9m85mfzZ33fD4vfMFv4M7nfyHl7Jzr7Y7hckvG4UJPt1rTr9eErqOmpG9Mk9ZqIs4lZ9I0\nkWJUiyA7gVdU5qumkbR3jAX69RlZvKpalKpyZJYoi7WzskmTuRMpM4A4TVxdXvLKSx/lox/9MK/d\nfZX7D+4xDHucFzZnZ7z73e/mcz/3PXze525592d8Jhe37uhMy1+wCT3SD6QpzjB61eA03pu0D6u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vmUQp3n8yUlSsqWKFW8oBgQR0dY0RCvaU6W2ZJkOcGj6AhVAUalYAcA7dg41+Fc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\nnqnzwAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97919597f0>"
+       "<matplotlib.figure.Figure at 0x7ff240b3d6a0>"
       ]
      },
      "metadata": {},
@@ -538,7 +568,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -556,7 +586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -574,7 +604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -604,7 +634,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -658,7 +688,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -681,7 +711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
@@ -706,7 +736,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true
    },
@@ -735,7 +765,7 @@
     "            flatten().\\\n",
     "            fully_connected(size=256, name='layer_fc1').\\\n",
     "            fully_connected(size=128, name='layer_fc2').\\\n",
-    "            softmax_classifier(class_count=num_classes, labels=y_true)\n",
+    "            softmax_classifier(num_classes=num_classes, labels=y_true)\n",
     "\n",
     "    return y_pred, loss"
    ]
@@ -758,7 +788,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -798,7 +828,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": true
    },
@@ -817,7 +847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": true
    },
@@ -835,7 +865,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -860,7 +890,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true
    },
@@ -878,7 +908,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": true
    },
@@ -896,7 +926,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true
    },
@@ -914,7 +944,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
@@ -934,7 +964,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": true
    },
@@ -963,7 +993,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -990,7 +1020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
@@ -1018,7 +1048,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -1044,7 +1074,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
@@ -1072,7 +1102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
@@ -1096,7 +1126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": true
    },
@@ -1114,7 +1144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": true
    },
@@ -1133,13 +1163,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
-    "save_path = save_dir + 'cifar10_cnn'"
+    "save_path = os.path.join(save_dir, 'cifar10_cnn')"
    ]
   },
   {
@@ -1151,7 +1181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
@@ -1181,7 +1211,7 @@
     "    # If the above failed for some reason, simply\n",
     "    # initialize all the variables for the TensorFlow graph.\n",
     "    print(\"Failed to restore checkpoint. Initializing variables instead.\")\n",
-    "    session.run(tf.initialize_all_variables())"
+    "    session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -1202,7 +1232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
@@ -1220,7 +1250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -1258,7 +1288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -1333,7 +1363,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -1376,7 +1406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": true
    },
@@ -1416,7 +1446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": true
    },
@@ -1471,7 +1501,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": true
    },
@@ -1494,7 +1524,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": true
    },
@@ -1528,7 +1558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false
    },
@@ -1571,7 +1601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": true
    },
@@ -1637,7 +1667,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": true
    },
@@ -1709,7 +1739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "collapsed": true
    },
@@ -1739,7 +1769,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "collapsed": true
    },
@@ -1758,7 +1788,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "collapsed": true
    },
@@ -1776,7 +1806,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1784,9 +1814,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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5Zi4sm/C9o1wDOt3DpI09mfVEnLPERjXGttBzi+FrCLLhj4j9/cWDnNFqYnZOcYqBVv33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\ngZI7AAAAAElFTkSuQmCC\n",
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3MUyUnH0W3SH/778/fDCFUfselLwrQmcXzNS6U1Kk1erZYB/Bc6Is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g8oBSgMoyYL0CoZuLFa1KYC8khdFeb1OL0ZIEdkMGUnxb5ADG4MAoO4grmCKDyRMsFXY3MxiCzf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w7YbpiHSeK4NL9abgpeIz52TPL0KwGslSzKBA5u9ynWbq6F0dsfcDOXOgkyLMcESKp0UzWZqq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\nRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97911d3c18>"
+       "<matplotlib.figure.Figure at 0x7ff1f010bd68>"
       ]
      },
      "metadata": {},
@@ -1815,7 +1845,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1837,7 +1867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1853,9 +1883,9 @@
     },
     {
      "data": {
-      "image/png": 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bjd9PuqQ/O6hGVAOSA8ZkvI2ItUSl8C/n9oCUIkMUpkox3nK5NHx6KeQpEkPi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\ntW8jXvgH2RuG//LxW1X9+dT+IPAfDzjuV4jIdwElcAPwe8Cvp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61nC367i/27Hb9LStwwkFGOfE4TTzchw5jgXgIiV7YwVSuAHc+4fzHuv9uguzmFWQ5Kzg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\ngAEDBjy0+P8BOJmfbO1XpsAAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9785708588>"
+       "<matplotlib.figure.Figure at 0x7ff1f02c4710>"
       ]
      },
      "metadata": {},
@@ -1898,10 +1928,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
     "collapsed": false,
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
@@ -1914,9 +1944,9 @@
     },
     {
      "data": {
-      "image/png": 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A8vJk+wcPthO7dTRWUVL2zG2wr3v/hG3xUQwAAn37IqgUVlVrf95Yl8nOAPaP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\nghsb9FG+sVjMTAkrI3ojHzW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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9785708198>"
+       "<matplotlib.figure.Figure at 0x7ff1f02c4b70>"
       ]
      },
      "metadata": {},
@@ -1936,7 +1966,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1952,9 +1982,9 @@
     },
     {
      "data": {
-      "image/png": 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ROZDXspkzZ66vrpDaNVJ9cAA4f17vEw6b6eoj8aUso3NLLaAeDuudlpQx2nL2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\nTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f9774f09358>"
+       "<matplotlib.figure.Figure at 0x7ff1f02b9c50>"
       ]
      },
      "metadata": {},
@@ -1981,7 +2011,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "collapsed": true
    },
@@ -2017,16 +2047,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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PcLi182d5/QyjeuXla8bTz1xOzH50xyidniH0eNt3byfdvO/t220v6Fc22x5+\n8XIG613Ft2ncvu0Hn9t2P778yiubbXpz+XlefOsPbvZ55sXtaDHt6cB5POaAeJchY7i37ZK8f8dw\n5Aef2BZqX3j6sjv0s69sC4wvH7ffx9C2p8aDz392s+3p5950cf9d37d9X48+vi1EfvaOzsb22Omo\n8+1mn0//wnaa/OsUr+rcjjF6sdEbKlTXsXjadP0DFVW75A7Buu9yZMiRaUjsJvcPGSybnpIwBGu5\nztJIAkmUSFeHuEqlKa0Wu9xvBljiiglrnmyeyZmhUitKWQplWdZRXMULfTZdHAORYBpqy37H1X7V\nFB478jiZ4mMYSTmvGbCeyxgvCnL+W+eyO+/rhUsN4TSRxoE75rRm2y0lmmf0MUUbLhyjZ6rCkKHU\nxeoBPnm+NlvESmtIE7/a6UnvqQBp7e9uFIXx5d6FTsxeJJZAjtb+riSsDJlATMJXmxhwOz0m2tnt\nTgU5RbIeDjkdG21oK9RlhuOREqJ1cKbXT/KnwN8UkQr8F6r6l57w+a5xjW+VeFXndsrJ/siU9dJX\nektz8GKj4g51gZSju/IlJpfw7ftkmTGx84kygyhZCkkrQevKW6tTGtqaZcjVONo+iix00A7eXNLU\nANvbsuuyOGg7cNdqnHZrZjfRM8zooO0a6jztyNPef1qhsGfbEhNeXfVF6lSYWyG688esq9iaiBuv\n3LNun3EZEyH5mLEU7fNEl/IFm1YDCdS6NHNSllaQ2tbhE7XZ8ISqakMVxNckMW129842CWFdZ29G\n7XRWIESXYUbLzpUAkunyztIqQ4tUrdQCoUE7W7BO80K7zLIbS/lx0mZzNqt5wkgM1FYJ6fUbgvBB\nVX1JRF7ATvBfUtXtFNprXOPbL17VuR0kEJIDhIoDBgZAvRAHRDFjopwi05StuDj5hJkpc2+K1iST\ng02XkWqFsFaMm9VK1UKti3mJFKXW6q3cSsULnNHmPIZgi4dWM14y0K7UebHHLcU4bfVCJKzFQUOq\nRMgDMU+kDti7PXnak0ajSjqFQbT5X2uB7YTZFq5OYQUw6HK4PtG8c9x0jtsz65UvdwomxIDGQFTv\nuMym3l6qEku1Am8MDsAGoLVZsdbyYofQNeP14qBryptTK616Nu+LWJBoU+q9W7WNmdoqpUWWapRX\nasZZRy88rnMEVs95z+715AgJDVpByxGC0GaFmmjLXY5AFk862Pcl//k5Efkp4APA5sT++x/60Pr7\nm9/0Jp7nzQnKAAAgAElEQVR97o1P8rLX+G0c7fgF9LjVo7/W8WrP7Z/98Iedp1W+48U38aY3vugc\ndqBpXYuOQThRIjmynzy7njL7KbIfbBzYGNUoEa3EZnI3LYu78BW0VAdtaylvxZpLqhcQpTZCPDXG\nt9poS6UulVoqrVRqtcG8p6G0zjfHeALNnJE8mJ/2NJF6lu3USC9GBs+yla5QOeWVpxYe6F2j9Oza\nAbxrLkytYlmoeNExnmfcwaxdDdcFtDthe6Y9RFKNJFUKoKLrxM3WGqU4Tx1ONIW4Phvqym8Dbppl\nxdre/ARdSw+jUyJjTiylMKRIqY3SmhlZtd7pY9k5Z5+vW7jSj41WRBeogh5fodw+vINquoxvGLRF\nZA8EVX0gIjfAPwP8B3ft+7ve+96L+3dx2te4xquJMD4H46m20R78ymv+Gr+Zc/ufet/76H7X5mtU\nVxWzPZeZD6UYGJKwHw2w702Zm50N2d273noQJWsjtAptptXF7FPLYsMLSqHWZhmz0yK1e0k3z1YR\nqNhlt5pLXnV6pJXm1MppQo2uukOjJ0gRknPLOTto78i7HXnakaYdaZjW2ZASHLQVRM7T68voCxt0\nbpu167Jpr1l2RUnXq0e/cujt/A7cIRBSL/HZVPakkGtjQCiewpfaXNpnYKkiSLPPGrtCBjP5sttp\n9JtRRtUA2w20rMsy0gRT/AQhR6O7cm0srVFVqFRr4Gm94ep88k0/VlZzEGlA8YariKRn3GxLUH79\nzmP5JJn2i8BPiX1TCfgrqvo37tox58uXGectyf7is5fdgu//3q3d6c3D7TiwT3/mk5tt8/Hy+W/L\n9lLj1778aPu4r2y7JN/wwm6zbXjjixf33/QD797sMz21LZoejncUFx4rwD643ZYi52Wr2Rym7fvS\nuF2db56+tFh95tH2+T/3uS9vtr1wf1v8THlb6Hz48LIQ/PRu+7nf9FghGuCzj7bfpcrl8yfdvq/6\nme34t9chXvW5HYLbjwagVKcHrAxlrePGiXYFyJgC+yFwMybujYndIEzRva9bQ9T8rasDdltmWpnX\nuYKtNnMBPAPs1txfutgswta6s5xRI5ZhN9pS7NJcqwFUxPlrB+uYPMPOyGgOfmkyPnvYPZZp+7AD\n6Z2ceg7Yq+L7VHLrMjg98bzr0POmp/Z4py16W7x0cBXbTggniXiKBBoRIbZGHjJzU7Im01B7M4w2\npaKoGL0SWn8eMWfAkNCg68LSqYvaKlpMzhmjvy8xO4Ik4n4wkSEmltjIsVEUQlNfwPqnP5NDqte3\n+/FS94UJBWnRKKYWLhpzHo9vGLRV9f8D3vONPv4a1/hWjd/suS2Ce1GwglUQKz7GYFnZmANTNsDe\nD8l+5sAUzTckaSE0o0Jand2VbzZZno8JUwfj5t2FTa1Ro6rYlG8VqqtJanN5n9MjbSloNStWp46J\nIsTUNdYRois4cjY+exyI03QqPk67lRoJDtgSelGNC8FIL7StbewO1gbOJ99pBR+9pa6xXo/q2a1r\nnF2W2B/pVwjSnMuPjZgisSmx9SEJStWyGnY1FFI6vYZ7YYeYWP0ZO02i2HutJhWMEukzH6Nn6zEE\nz7YTqSqxKkFccin4FY+9Vh/SLKuGv48+rraCtWKv/zVsWeHaEXmNazxRhBCseIW3iTcMSBy4hxTc\nOyQaFTJE9kNw/hqGbvRUi1Ehy0wtM3W22Y1dnqe1rGqHVf6MeYKoS85q95p2v+m6FGqxn2bHaj4k\nMZqvNFEICirBp9PkE2APA9HbyY3T3rkTn0+m8SG7Bnxwzl2vVcgVsD3zb7oWPlVP9Ih2jXi/6WNg\nj56uMlw5o7X5S5hVaqeGQnRqJQTAbWi9wIgoTeSkR+9KGV8YQgj2/M7PN+8WNVGN+ZOHsPoUErCr\nqC7lTCkSSjXKYy10hvWnDUR2Ogpdr06E3oDUZ0+eL17buIL2Na7xBCHuv6xOi4SA+V34dJkhBXZD\nZDcl9tPAfkoG2AGyVKLigL1Ydj1bhl2WhWWZTVddyipLW0G7g42bQLVmDR6lNpalMs+FpVinXSvm\nr41CQIkNsoBUA23xjDPERIjmbx2HyRppxp3TIjvyOJKGgZitocZM/0/DHi7B+mT+v2rKe8t8u8y0\nVynjGXC36sNva7PiaakstbIU+zwdtPvVxrIYbdSz9T4QWcQLi7aa+vuJ9MG9XTEjvnicOG3bvwN6\n00boAm6aD11w4PZ2+rBUYreGDQGp/fnCeusUTPBzR/ow5VV2084WvrvjmwLa+5vLl3l63I6t+sA7\nL5s08iuf2ezz6U9+erPtC1/ZctMPH102ZTze3APwK7+2VSBk3XLO+xe3LoJv+u53XNx/5jvfstmn\n3OFkWObtez08umzeefDouNmnLdsmk1e+tG0q+o1f3x6zL718yWG3O0Z/1XKHk6FuT5q7TqO5PLb1\ndtuMtBu2r5nCVoe68JgLom6bcoJeHp+vcyX5uoeIurdF8OYKk4xFUWs/n7IrRRL7IbHz5pksSrTp\ntbSyrOPAyuwa6qWwzIWlFFMlOHgZyKlZvXpxLviIMMu2zTr0uJjndF3Kqu2OGFAkcUpBbeCt0tvJ\nE6ErQxywT7fRJtWsuuxzbYiydqSsgH269cnjtXVN+cmLGoBmrfTq7fS9vb6WQi3FJscvC8u8sMx2\nvy9eRhWZ1/XchzTQ5XYrT7OyyyuQd8W4SxG7AdT5VYzt3jd440xvxNHT9x9DIIRGipEYGyFYtox2\nd78+kuzk5d1pEcX27bSMaF0vXr6aXOOaaV/jGk8QIVhG1+VsIQekNYYUXYudTCkyGWCP3u2YKD5d\nxqfKzAtlninzkWUpNvC1NJZivtGdo14zSZp1DQaIKSDNgKrWxlIs0z4eF4oPx8UnmqdomV+M3sWn\niroJVAiJmAbSMJGH6aL7MeUTYJ88RpzCaD2b7moNpzAcjPv76tx1XXlpD61nhVaXJZZCLdWvOArL\nvDAfZo4HuwqpLlnEB+TaZ2Hl89c6n3Prpr8GJbjSx6iiTsGs/Duuclm/U6G6a2OlrioZbW7FrerA\nK+utD2HoU4pOBUhcYnjKrsUzbO1gLZwy768SV9C+xjWeIEwzbNmv6aPNoGiIgWkILvGL7KfElMI6\nrEBqsQYOLzaWZaEcZ5Z5cYqjmPa3NpvWXU1r3JUhIkJCIItNool2qW/7OXB3uZ/PV4x2TY6zvaxt\n5SLmMeLgvLarDx2wzwqP0ifSnA1MaM3B+THwPVO8GN3h0sgL0PbMvHbPbLvVUrzl3gHbrzyOfoxq\nsyk2NpXdrxYknDoQV4rdqJmVCjnl2CuNYnK7TpecdWp28npNto1bh0brzUSdQDnjp3uOHoL4wJyT\ner0vECL9/rm23TP+rxNX0L7GNZ4gzOfDBthKjEhrJDFp3zS6l8iQmHJgCGLzG1s1zfVyoHUvkHlh\nOc6UpRpQl0pRqMUyx3Im79Om7kLX/aPtl6ZKxecN1sa8FEqpq1mSFbu6/M28tbs1ahwGcp4Ypj3j\ntGfc3TBMBtwxOWh7NyC9oFidKjgDbFOs+K2cWu1btQz7nHcGjMftWfn6uLqC9uKZ9nxcOM4Lx2On\njZoP9Q2rK6GEYBI+6dNtHEvF1DXd1ArxYczrwsVa/FwHMPs+6px/qw2C2qIswesLawsTXTEEnBYF\n7V7mfcHwj3zWDdnnUeIDgIMXZ6+Z9jWu8TpFiO6LHYPpeRFywPjsMTEOkSFBCkIUKwi2slCXA8vR\ns+zjzLLUNbOsvTV9LbRpp4rXLFA8u4eTUEHpEje7Lc269Mwxw/29Y+g99UiKhGzmTHkYGHc7pv2e\n6eYe0/6GcdozDJPRIt7Ft/pvO8BaJnuZWa+eKL0J6Mwf5eTd7W/aPohl1z3Ddk6/FAfoeWE5LhwP\nC/NxYZ4L82LT2JsraEKIxJiISdwG5aQUb64uUYw+if31nc/utIT0TWtGHNYia1O1rFmcp1dxTfxZ\nBu+T7fsrW0YtaxHUVCG24IW+WFH9GDhFQwfur37OfVNA+w1vuHyZtz771GafoVwWsP7xx7edbq+8\nsi2Yxbht+Dj1+lvUO9z1vjhvC34vPLsdB/bUd2xb7r/vHZfNNIeH20LhFz6x7WYqhzsKkcvlt3PQ\nbSNQa9v3+uUvbgt+n3pp61L4mc9fvuZ3ftebNvscdXt87hoJl+PW9O7Ro0sLyVa2n7HUu1pyt5/p\n8dKL6rYRKD0mYv3qBpbfnAiOgUFszmAOMATPtN1yNUeIeIZdnbc+HJmPB4oX1oorPWpVqrp3hfYM\nELdM7efKqTmEs0PbPMOs2mxKObhVaCMFH/EWBWJAohCGRBg8yx53DLsd0/6G3f4e0+6GcdyRUrbs\nFSyzRhyUDWQNsE9mVmb12twX5QTY1rWpq3ZaHSF7Ae4C9Et1wHbwXlzGWCrHuRp4L5Ximbb5ksAw\nxPVP30DPin9dYbIubNjrt9ZWy1xPyPFJnquPCtgxDSIOtnKWhXcp3wmkm9ZV1WefrSLeXNOct+6c\ndtdy9yHC9hhDbPkaqH3NtK9xjSeI6C5wKQaGYP7XYwqM3v2YEzabUb3ANi8s85Hj8cjx9rgCkxUa\nm6khetccXcXQM8LemOFbuy9GtzjtOmSEou6F4cDQAtYxm4SQowF2TsQhkYbMMI6M48Q47RinHcM4\nkfNg2bmatatKb503SqeWxWV6fbTZSaZXWzu7YjhvCMIBtKe2rIXLVeJ3BvalNC9EVua5mpxxqSxL\no1Rs8ESEnINRQV5UdcHHmtXbOEc7TlawbIRosz2Dvx16Vqwn18ZVjSIm09Pg+m1vjelFT7vKMZqk\n+RDiXqDs8seuHrEM3GsCnd/uunR8UvzXOOeuoH2NazxBpBSIgk+bCUwpGGh763oSEK1oK7TSAXvm\neJw5HI4sy0Jx3rrVnr15cdD5UMA42+7qjwP2mp45AOppWkrPJq2fQ5Aoa5Yd8okWiSmR8kBy8M45\nk1IietERVfM9cbVGqfWkIS/LaRal+pgzPadBTiDdkLVguFITzgOsfHI7/13MoVBZs/Tetl+K69GL\n0lQI2gjSSMlSaTPraqdFzud0Gj3SiDF6J6kS/VgFP84xhMfUGx3IoQlodbrE4BVgpa86UCumojGV\nSbetkrPn7GT7SUUS/PsLznffdW26nnNPftpe4xq/fSNHGxs2pMiQA0NKLusTMkrQsmbZXW88H48c\nDweOsxXZ6lJXjtTGlEdrhRY5ZYGcAZ6HOr0gp2GTQIcOAyVvyLZ9gw0REB8mkJIBdczuqNe1184x\nl2XxSezWIl+qspSFeZ5Z5pmyzKsB1Ulj529Ouve0/VQRTHToxbs+t9GbYPCCn4nlohs4RawhxW5N\nXZftmXsnJWzww9nNVTyVgBbPuN2qtSqU1ryT1bbFIK4wCU5VuN5DTxy+rY+9SGnSwaqVonKif5zP\n7/y2AbfLIy9H+vgh8kIFveCpXoy8LFw+HlfQvsY1niByjO7gFxhTYsyRIXrzjDak2BCCuhxZHKzn\n48w8L8zH2akRV4VgVqHdECnEs1FV63QVi9NvXf8brH1azstglvHGaNlmiMb/ppxIOVtmnRIpRbMs\n1UatC8vxQCMSqkJYaBJPTTvzbNTO8cgyzyZbbJ2fdZ1ysMJg8IHAZioVUDHTJnPb68OBWaE6SCBI\nJMRsMynjQPAZlUhcgbsvXn0gglmAWwdqSqZBV4TYzBUQfDCBCjQluLpm1VY3KyDbRUt0ekO8Bb4X\nfL1RpitDpNuwnqt7Kk3tptjVR/Pv7/y7gq5S8SLxWqzsypJOq9x9zn1TQPu7nr13cf+N97YdkZ/8\nxV++uP/SS9uxWI+7wAHc3GyLh+WxEV75jg7MescR2d0x1uvevXubbb/8ix+6uP9K+fhmn4989B9v\ntt2/t99s+/4f+h2X7/X+s9v3Ndxstj3/prdttuX7W2fEZx8rMj777NYd8JN32FN/8cG2UPjm+9vj\n/3hxtcZtIfXlR4ft49q2YCmPXROGu/odH9/p68taX9cYUiD1TDsFhhjIUUgo4kNzazH1wzzPzE6N\nHI+zUSOL/fGrZ9hCI8SwZqDik4JXIFYD495evfpnxIAUo0m6O94K+NhYtJiS/8wG2snokRisL7LV\nYoCtASkNSTMqmUakNGFeCofjzOH2wOFwYJmPlll6Jmo+HHGlXPIwELMSoloXpfPuXvEzk621EBgJ\nYgOEUxxMLz6MpDwR3FHQPE987JjzziI2vX4ckg1JzpGUIoqyVFl9uO3Y6QraQmNBkBScqfH9aqcz\n7GD31nowzAjBgLtb8RqvfTbRXt0dEAXvdGzrOXqp6V6XVj0jUM7kmV8trpn2Na7xBDGmSAzBh/CG\n1Wc59MaT2qhLZZln5nnmeNYoshRrntFm/Kg4heH+nN4sgusZ5FJTTNcn4230rJ7Tj69k/RIdEWJM\n6yTzGOy9d3+Ouiw0bqE0NMwQB1QSVSOlwnEu3B6O3D665eBXDFW7pBBSiqSUGcaBcbTuwYHgLdyK\nBF3xsFMhQYKBVIAUE5oG2jBShx3LOJOHW/K4I2Uzqoo5k3ycmKoSooF09sHIOQdSDpTaiFFOzUB+\nDKvqOqVd1AqdIQVTsxAM5NvZYN/eHakO2B2BXUHSAbvUSqmF4tm2FRlPhUZVczJBOjBfNuKsR6Uv\nYlfQvsY1Xp8YcySI0SM5RnIQosuPa3PQLsYPd73xclyseaaYSsK6pHX1oFjly96x2O1Mzd60A9Zp\nlJX4bEUpPoXcc9cVdDyCdAP+aIREiKao8I7LNs+0ojRZaJIsy9ZI0UApcJgXbm+PPHp0y+3hwHJc\nzGsFK8jmbCqU1mzBCSmTcrtoWOmSOen8s89rBJCYITd0qLTJpJDj7sCwe0TePSTf3pKWxTjm0JUY\nOC0iRM+0YzSVSCj2GrZeBeebjQZZik2rkQCpsQ5ywPawhXR1H1RvoLIF0vY92c2eZ9qrl/lakPSC\nqD8zviCc+6+efANdqaL6ZPSIiPxl4CeBz6jqD/u2Z4D/HngL8KvAn1C9Yyz6Na7xLRyvxbk95kwU\ntQw7CilANCLUuuaqTZ2ppVJn/1mdA+2g3fnUYNmYq7/MAro1H+fVdduATzs0YO5FLQdB+ngzMXN9\nQFSsoNjcHtXfQ50LJRUkzISqaEhUZiuuaaBq8BmIyrwoh6OD9u3B6Z0ZFGIMll0Pw9p5mLP9jncF\n9iKhTx0+TaYJYQXy1VPPJSOtVObjkenmlunRIw6Hg9nUAjIfabX4FYYfu2CNNRIw98LOOdD12f57\na7ZYlEpIceWlY5T1+HffkO6TrqrEPnW+H+8oPvDCi6MdqjuAu6Svd0aaOqQXOy9EPytwf60Mu8er\nybT/S+AvAv/N2bZ/F/hbqvofisifBf4933aNa3w7xROf29MQzYgpmLwvinGm3bVO67n/Rm/pPnlx\nqI+fwr2pV8DGAKNhwK1n/wGc/ur7CC6/tO7tdE19wK6CtHUie0vWXl7mhTkn4nGxyTux0ggUDcy1\nsbTAUpS5CvNcORbleJx5+OjA4XDk6AOCDaAT0zyi+x0hBIZxWYfaGriFdd4jbukaQroE7RAgNF94\nXL+hyrIUDscjh8OB4zLb/MUQOAahzEe0FRfO9KsLXQ9NF6dYgmtXLdUBu2GNMqWp68dNbmmMttMg\nrjqBPt1eiCF6d6VRImZdoFZ49O+lF4AfT5WD8yTrWqL9K/zaapHH4+uCtqr+tIi85bHNfwT4Pf77\nfw3873yNE/stz18W8/Qr2yLj4eXLwtTxuFUqhnH7dm/nbU9ceGy3NGyLY6lsO/4efGE7buw3PrEd\ni/Vy+dLF/V/42EubfT77he2orPd/4H2bbfubyyLjvee3xcQ8bAupN+//XZttL332s5ttv/B3L6dk\n5eEOBWje2qTeVYh8cb8tYkq9LBY+9cx23NjyaGupW+649stcfk93aVXbb+Lk/nrxWpzbU47moy2m\n+Y2qoAVpBarZotrN/De0uh67WfHRQOE00UTPZHHNP7BIp0pOfKo10+DAJGcY7jJBz8WrA7jWZiPH\nSqMcF5YYWVIhINSqECNVbar5XJS5KsdFOc6V22PhcCyWaTtgz/Ni2WeKTONonHZOTE4p2Ns8AXaM\nkZiTjcxZ5z8aaK89iRqJLZGiFUxFhFIb87IwFzPQat5k1LniWjC3Ppf62fEwwOwDCzp6N58iU9Qm\npi+l2edvahrs0JtkbOXsqpheQIz9CiEltDWiCMEz//6eTi3zeuLd5eT4d9LLAGfZ9cmPhIvf74pv\nlNN+o6p+BkBVPy0i1/Hq1/gnJX5T5/aQ3CNZG0H1ZGrfTvaknZbQ1guJrC3Q9pfc+dQOtw7aCnix\nagUfPVvMemNNkPVXUdcedx7VhwUQbIZkWSol2s95rlbsJEJRqgTKCtiVw7FweyzcHhZujwuPbmcO\nXfVSjbvNORNDYPFxaDbFp0v/3A8kJlJOhJRsaG3wgb2hjzrjTKcNZFsMRCwzXor7ipdiHLp9UESU\nMgOtGFXR7SqCENQ06yGG01Dg6Lao3qWJ1x1Kbag33JwyYDnjlY3WiL7QmF+61wu8ptDoapJTVq/+\nFZ3UIc7hc7KBPX3ukwa/uwd+tXitCpGvYf5zjWt8S8XXPLez0xGi2GVyN1puxX+qdw268X9V+nW0\n+TY7mb3SJJ6D+aueBGhukn8xMPaMKnHA6kqS9Um6DK1WWotu9+qcerXp4aJYUZIA0Z5KqkCwy/6m\n4o55utI3PTvs471SNLoj5WwywpSIyeV5yeWG+RK0u9WrOGoboNn7ie4qWFVZuqeJGjVia5cdi/kW\n6nIkBZsTGZNl9VWLFWdDIKRIKAmpZQVTT9hP8zSbrpl2/3yqJwvV4PRTjBFJyaihGKEUp0JOz9uJ\nkf67rJB9+u98fMf6fs5KkmvT0R3xjYL2Z0TkRVX9jIi8Cdhel5/FX/4f//b6+3vf9b28983baTDX\nuMariUZbGxxep/hNntt/CzCDn9/5A9/D+77/zTR8gG4H8G7Pt/YPGFD34qMNojFaxC6jxbv1dM2g\n3ZjZHr022ZyyMT37Tbv+1yVnpdljl1oJbo9aRWghQcrEYSIOAxIzgySKQl4a6XAkDEdIByTPEDMh\nWabdmlXpcs5M08S0m5imiWHI5GE4A+94okJiJKR0BtrhYpGx5hq72ghRIQgjRvF0CiK4OVSMQoxw\nSMJyTEQqcZ0iA0EjKUHOSipKVuuQrLqYjtp9tpPISlM1p03spXxsmIS1YSiluNq7Brfh7d9Dad03\npl9Fnfy5T0B94uqtIGnfVf/81c9tRZE7TNx6vFrQPqvDAvA/A38a+PPAnwL+p6/14H/tX/jxi/t3\ncdrXuMarieA+bD3mJx849kTn9r/+x3+fqTS0IrWiZXH/auV8BJd2m7kzOYM4Yq9TuntOfb4mKaiD\nt/EkcgHYiqkhNAT7c2+9cd1+dlgpqgRVEjhgR8iZOO5I+z3jbk8arZFFiSy1cXtYGB8dGR484vbR\ngen2wNH9UpqbVccUGceR/c2O/c0Nu/0N425iGA24Q0qW6cZoP5Nl5OIZ+lowBHrruiBoBEJg7MqS\nYFl0ym6/GsUmykdhOSRoC9KKtf8rJGkkFWJVRhWKLpSGmUzZjGNvnuGsMQa/zLBDb/SO/W56dh8Y\nHILbqhqNVVovKq8XN3T3v7BOXj/ntfvC0M8RQITkMyT791r17oFjr0by91eB3ws8JyKfAP594M8B\n/4OI/KvArwF/4ms9R3zcrrPcYcv5WIUpxm2nY2vbguLhuC1E7tKlhehS7jDw3NbeeDlsrUeff/e2\nePhP/87ffXH/ex/r5gT4wkvb4uQzdxQZ7z9/Wbh7wwvbQl7K21VXn9sWJ3/ij/+Lm23T7vK4fvHX\nP7bZ5zvm7bH+Rz+/3a/cUQXc7y6Lk3pHR+SD262lrrDtrgyP8Xhyx5Q84fFjsX3uVxuvxbmN9kza\nbrLedJWLWaHwdOzOKQE8u3RhHKg59/Vi2GqqhCI+/GB9ab+EVmT1yOjFScWYF4I4V6sUzMq2hogM\nA2GciPs9472n2N27z7S/Rx4nJA7UBofjzP7hgd2DRzx8+Iibg7Xhl3k5yfmCkIfMOA5Mu4ndfs9u\nv2eYJhsEvAK3USYG4MlBW+4AbR+C68dBvGhpXZbWyWke5koQ86WebzNtOUCd0W4XWypRhayBIo2R\nRCWyVJDik9nVioims46nIqRnyWth199Hd1XsdlLV516qno85s1pFb+lZm2pOUM26kANrXWMlwL8+\n1/xq1CP/8lf5p9//9R57jWt8K8drcW73+YvS6Q9tLrUDWd3c4JzZNEN8Vvqji8A6z9qNjBRrq15l\nfIFtFu7ZtXJq+OjKCk/gT2qTILQYISVIA2Hakff3GO4/xe6pp9nff4pxd0PKI02F43FhenRgfPCQ\n3QPTSc+HI2WezUvbryhijORu7zqNNkxhd5re3qmSFbhjcnpE1uMAnAC7X0uF4OZWieSt91agtIHI\nijnpHXKgzJk2H2jF39tSKVLIUqnSKBqIi5JzZZnNs/vcgKsfu77BMuro34m7BXoXpIawzrm0QmbF\nTQ6pzesUzlCvyh689iGyPieu4z6/+rorLXk8rh2R17jGE4TWYn98itEkTU8gfqYa6K3kq0nRWd4F\nnIGH3euaEe3X3J6C2V3xm1PlZwXHHqaWCJadIwaAKSHJZkGGaSJNe/L+HuPNU0z3nmK69wam/T3S\nMKIqpLkQhgMhj6RhYjzYtJ0VtL15x8ya3Jd7GBimiWGaGHu2fc5x53yS+p08o4ATTaQ90xbcTlYd\n7ANBoLVCrQu1Lahau/pyHCjHgTofKMsCaaGEQpFClUZqgTQ3wlzM22UFSj075j3LhrVrU/uIMqea\nmplALbWylOrt67pO5nEX17Nv9rLuYGZ/veqw5t3rfvLYY+6KK2hf4xpPENU5bJwzPg0mtHmCIl2H\nLOvAAulNMSs1cOqy63/AJg/Ui8ybM+VGV3I0vyRfudSzy/kYrL27IhATcRhJ40iadgz7e367z7C/\nT/EYi0gAACAASURBVN7fJ+9uSOOOmEd7D6FYZ2QzW9WYMmU0Z8JWi31Wsaw0dvfAITMMI3kcV4ok\n54E4ZGLKF7K5U5H1dDVyuuroDSdi5lLNaATVylh2LOWGUmcajZgC82FgOYyU4y3LfEQPR0pYKLJQ\nKKQqpFyRcGQtEjpsml+2k3PiObIY9SOu7mmwKoCWUphr47AszKWuskErJ5xUH/bRzlqixBcIOWX0\npzy7W8P2M+vJC5FPFA8+/7mL+zd3jNRK6ZLjlLB1gdO65TjvKkMtj9Gc82MjvQCeeW7LL9/7nndu\ntn3Huz6w2Sb3LqW7b3nXlp/9nndun+vm3tat79nnnr+4P9zhSHhXR8mj43YUV3tm61L4wz/+By7u\n/+ovfedmn088/HubbSFsnQvv4ph5rOHpo5/81GaXVx5teecg25Nykcvv/PFmG4DIY/z76yok+fpR\n5+WCrw7q3LPzyOsfsAQHcdMKrz3MdGlZsCKinIyhwLS/Xf1lSdoJpJvzqa3p2l7dd+yFuyqKBLNI\nTePEuNsz7PYM0w3jzX3Gm/sM+3uk6YYw7JA0QsyW6UYhZCWNygiElEjL8JiHtnULdllfSjZv0m6P\nZdkrLdKpkfMmE05yOe9MPIUBd4jW2JLGgWG3Z6qFhhVD82FgPozMh5FwONDykZqOLByIOhMWXR0C\nOz/dW8rDOsrtNJzX3p+ZctXWbHRbtcx6rsqhVjP+KtUaf1pzv291zrsXG/07c86s9WUp9MKDXVX1\nkW6rudfpsGzimmlf4xpPELXMxmFLl3hxGkyisgJ1L2J1fvSMTV1/KuLNMfYH3U5Ibc/d2tqsoZyk\namZcxMqlmurBhhxoAA2JMIzk3cSw2zPu7zHubxh2dkvTDXHYIXFEQ8Z6O0ElIjERczOr2RhpObvP\ndFvflw0eOBuskLNZs+a8AeywzraU83XLstFO9/gxaSslpOtxkiDElMjTyKg3qEDI0TL5YSTmEUmP\naOFA0UiugbBASMW8vf270PWI48CdVoA9TVX3Lkes6Lg05dgax9K4XQq3S2Eu1Z0aoVa9wNm+yNoJ\n0i4W6d7Ic2Kwzyxav05b+xW0r3GNJ4hayspZt85Vr5hml9bmJmcFtF7QWvkO51Cb/5Wq3TnRKPD/\ns/duMbNk13nYt/alqrr7P9cZ3kSapChSkqkLSVFWLhYQO/GDYQMKoDgyYEORFCEQktgwYD8k8YsA\nwy/JAwPFiIBEkRRLRoDIQhDZgBEkQWDAMZA4pEhJ1IUUJZsXUTMcci5nzvm7qvZl5WGtvWtXV58z\nR/qHo3HSa9DTf9epru6urv5q1be+tb6Wfq2AnYunIpfBUnqxb0SV4b2rjTNwHYzvBbCLB+SwRzfs\n4fodXLfMrBZHFn09fd/GOTiIBK54KIKLhlxND0q7umbbZV63q5SIjmFVl50mn1Tah1GU5fJZWVmE\nha9nBT6yBs536Dir0Y+pY1uNc2DrkOAwZxLA9hFkZ2kgMtLUYwyp+mYBbs65NinJ25IMOYMROWNO\nCWNImFLGOAfMMYvBcMpqzrCQHZWrpnJ6YFS3dj05FNkM8aLnLp+9SAXPxQW0L3GJGwTruM9MhFwo\nENVl81KVQu2FI2mnpqgAocWrOm+iAGYuIK4UqIhOBC9zBrPVv2WWiaGl8Clt44BnbVaxIu/r+gF9\nP6Drd/BdD+s7GOtBxukkQXWVqeoNaHeiZvrWLkVRCPiIyYDw58ZK23qZq+3UdMGolRm1Y1gruJUM\nu2jZFdyg8sW6S9oiq5xILHpR7tarGKMnHUKIDDsnWBdgrIc431BVgJRmmiU35kWGiTI7RE6miUUh\nElJCSBFTSJhjwhwzYkqyrbxcIYkx71JiRAFpWoqdpu14pOX44Hr/+LiA9iUucYNgNSwQD0QGkECl\nw64AdwGVckMZwl8aK/Su6HQZS5bd/nwVL0vXJNfX4Jq5GWvhbIZ3AFmPTBbkOlA3wO8G9Lsdus7L\nLBDTUAUNRVFoVQMjwA01+bXlzamqnJbMXigZo6/vtJ1cnXKqzrmlA8pnKiSEGOeS8spMBMPKATNX\nGWXZT/J6jOya1nqQGhIw3JxgfQDZEZmMOMwwENUseGUqUT5/26TEpb1drmhCSphDwDRHzbAjYtZC\ncG4HPi2XRWLhpktq4RP1dauqSFLyZllbkNzGGwLapwXEB4+2RUbXr4t5xm3fGsVzBa1tQ0yO608c\n520B7X3f+N7Nsv273rNZNo5bq6zT65bbt29v1nBu+752u+2UvFM7M3OmwSefVlYBxGnboHQ8s97+\nsC64vvVd79+sM+OXt8vO1BzjmULwSw9fXT1+7sXtdEPibSeTpe1RmTYV820hkt5seQaX7BDISBAS\nmWX0KnOlPRazAgsyqeF1l4luKxdu5ckBBfDKJzSZaaMiKS8j7dYObBxsBth6kOtg+h3cbifKDu91\nip5sJ2cdH2syiLJm26QFTZHgraR5+p5I53abOh+7mehXAbvI+1Qt0+aRinHl3CXTVSXbNCUnLdXV\nSsuU9yHgVrworVOuOGXEkOD8DOs6wBZ/yWUIV9ZGmCqpbvTtAJo6gQJ2DIgxVonfHKIoRiILlURN\n9yMWqmvJulHOxCsevyyuBgso//hkrfab7BdwiUv8yxWLFI/FplWHROVU1B1aYKSiIBGeGDarp+Oi\n5Vup35QXKPR3O6eClciWJkwWNYf6ShoQnPeS7TMBrgP5HqYb4PoevnPwzilnKs9NMSK5KDRGFheB\nhU+Xq4SaMWJ5T9QCtt4EpK3amZUsfNGn6xaWD9okpyizVgAssw65Sipr52luAVzA2xoLth7OJTjf\nw/kJxnrh4UHq5agZ9urqApsW9HIylOFaCVEz7ZiFIhGqhJGL1BIy2bCOVoXsm1yca7AsR8NfF0VR\nBexyBQWs6ZOTuID2JS5xgxAeFQAKj811RGliWtSaRDJCteqTFwWFMUZneeiqy8brpToV2Ui5+i7S\nwKxZfsoiZyOCJbFAY+NE7uc9jKo4hGc22h2fkQpoxyidiibp1V4LshCuXicMnoL24sKu97SA9Omt\nRsmygWqJVvC7qrWrnKS0GyY0U5nq38Xg15JFtuUzahemccsEQyqZ9kKnAGLOCwXyOqsla+NMTjIW\nNpV78fWUGdymwjGp52QFbC4TAtvzktHLCv2U9fteyrK1weiPmh65xCX+vxpknQ5RjgKwmVXZob6L\nmtkB2gFoshTSKMFYmTHCuRBDJyU3zs2FcputofIhrAYHLKPttNhH1SGGrAM5K+3gzZCmombIWcee\n5gSrVwZLoZEqH1thRcGa6j1V8F4D/ULtbAC7/juv/q5lQM22tZ0GDKEq2rkuRTZDmrVaLfAie2SX\n0PkOne/gfKcKFgFyMhbFn4xBSCzK6ZxRl3FZBpm3kzIj5IzE0gmZWEwTEmf5XmmdZRfjAwbAVKzi\n9BRR+Wpqbu0+0ULkBbQvcYmvTxjXSWYdAc4RGdIhVwx7czYq/WsArmSjUJ2GMWCowW/RZBeeWrPb\nJdtWE4DM4MRgu2TbYjyLpuhpAdsUQNUVHRWwM1KOSCkKr11GlgJrcMZ6jka5Qqhg3gDy0kp/DnXW\nJ6ByfmjOQZphQzlt6TLNnGGKwUJKC1jn0sjU8OzWIjuPznfwvpO2+q6H8101ZDDGVm67DNQSJyCq\njTFRgTqkjJCzPNaTcGJG0vXq+FUyZfTTwmmjfD6V81VgbwF7fVv23+NZ7TcEtIdn3716/PyLn9ms\nY9y6E3B3pjOQz3QBxjqjeAlK6w88XW+fd/vOdpoeme22Xn24Lay99WRk4mG3325rk1lA3aCfHOfO\nsGc+InzafibzYDvyll9dF1Lv9tti6De8412bZb/stl2eR9oWFL86ricoHvP2c587/PzZ3/Tp9s8U\no7Et1P5RhvE9csrS7pxk3nfiqOqRolAooG1qJlyy7WobVgpu1A4uKpkX9MeflyWKdFwUDJpti7hj\n6bojQwLcpcGjFtgSco7CaeckJgmcl+mCGtScYGohsSG3VzC8Ko6e+4IbsF49D8vyphhr9ORickbm\nJBZuOYHSQo2UnpX2BOOMgbMWnYJ3p+DtfQfn3HICKyfLwnkzYMkgQTsgM5AAxCwzvYUX54VOqWcb\nWn0oo/SIfklCf3HC8sloBdxERiuiSo/whdO+xCW+bmG6HRAjmI1kvpSQ2SChFLeUoSUDUFaJnHDK\n1hrRW+coE/iy/PiZGqAu8jDNfCvHXYpghdMu3G7m+mMvXZhyMpBlCy0ifLbJEXaTaXN9TuWvy/ZA\n58/CRT53AtytHHGFQ7r+aaZd/q0ddYucxAwyFt/NLLdq4UZCBWmnKTHDKnh769B5j77rG+CWOShp\nmiQLrsVKg8hAZkJkIEI8MwOzzOJuWtSX64nlaqNV/yznNVoy7eZfCnetNeiytKpQLvTIJS7xdQrb\nDYCJ0pUYI5iC8piqHFHRM2kDjYHeWwuTMgxlAWxWDpegtmWy/apKUMRrcm8Ai3okE8HEBLZ2naAV\nWgVoqBEF7kqRSLa9dFkqt82sb6jZHi3bPZtLr7Ls9RorXNbslJvl9TULkuUsUxRTAGIAxxkcxCw5\nx1ylewyqfpMAwEmA3gAC3M5j6DyGvkfX9ej7HpP3yN7DZK05GIuk+zYyEDIQMgt4ZyCxDN5afbcN\nYC8qbNk3JduWr47qd1YbhhqgXrJt/b6h7vKP8fd4zWtNIvppInqeiH61WfbjRPQlIvplvf3Z19rO\nJS7xZovX49i23R7W72DcALIybIkbXXBFpZKtGmlKKb7rhkSfXA0BUAp+TW5GCxjWZowMyexZuO1c\nTBAaOdyKNlBlR7kql6KpqkeS6rRLxp1SA955AWEF+2q48Jp0SFuMLKQA1c9U0/hTbrcqQyTDzjEg\nhwl5GpGmI+J4jTReIx4f1Vs4PkQ4PsJ8vEYYr5GmERzFycY7i67rxGFnt0OvnaFeuW5jnYKzGBpP\nMWGKGVPKmJMCt2bgGYsYcbl8WYqQhlbER6U56OS/YqtW6LIC7iDVdt8w0/5ZAH8HwM+dLP8YM3/s\nKZ5/iUu8WePGx7bpd2ByMJlBIYK0LZwpgSkvzEQtIqIWIouGueiGC7AxySV+SXIV8wX/S0oOYRBy\nyvVkkKKYzeacUfLtBaz17FBPBtL4QycKkqQ0Sc4JnEm6FDNkrko5YZzJsut0Oj6zXP9p+SyNgS3k\nBbiCd8nws2TUKSKHGWkaEacRcZ4RQ5BGl5ibJpnCUUuhcA4ZKURQzvCG0HuP3dBjNwzY7/cI0wRO\nEXk2AAdkZMxJKJkYE0JmzJExZyBkQtRMO/MJYGuUEyoXSR+XmSaotYDle2zGzurHNboO8GTABp7O\nueb/JKL3nPmnc8zW2di/64Orx/bL24JZjuvOusN+a4EVjsft+zszdjWf1PsevbrtwLzzDdu3vzts\ni3TTvO2IPB4frh73Z7o3z2Ue+/12NKsMZF9CRneuI2Jrl3Z86YXNshc+86nNsq88/+Lq8UvT9prr\nXWds0L7tOz+0Wfbbv/6J7fbH9X7MtC0g2zNed/ZcJ+uJBxyfuRDc7J/XOMCfFK/HsW26PZhmUMow\nLoDcBNgZZBLAojHQ+uKSbWpmbayFZQYnEk6cGZSbvlAWVUMx8l240/r+1WAXQIJYYRUlyfIhtehG\nVU1SpxY1/HYu9EhaQDvnUjRVA61iNlv5aPlQi8EDlAdvZH4NH16IHQaWeSrlbFU/sOrcU0JOQQB7\nHmVO9nhEmCbM84wYGgMCZjDr/Bdou3oGQhKqxBLQOYeh77Hf7zAd94jzDMoZsyGkQOA0I+hVRog6\nZyQLTSKGwFky7TIEZkXsLN9HyZLr91XUKZDvPHNprFm+RyN9+/XQIzq1KFrHTTjtv0JEPwjg4wD+\nBjO/coNtXeISb6Z46mPbdDswDEyXQF2A8ROMn2FiUpUBV3leoQkKn22NZJjGGp17IZZglCFAluuv\nulFYVN5DWFSGSuGA7HjpwtTn1nZzq/I/awFrVdfdcONcnpsXbjvnVfGRNHUsBUdgyZaXhLoidwVw\nNKDO3BQkK3qjbpOVx84xIIUZcZ4QpxFhOiKM15jHEWGeEeaIqGNRUxbgTrxwzwkGGRaZDSgDzhL6\nzmO/GzAf9uJuk8VjcjoywpSQUkBIknGHJB2RoRQgyUjjjRaUm9ouauNT3S9UddpZM+qSdRsy1YcS\nWIwP5Cs1tfj89Zjy95MA/hYzMxH9bQAfA/Cjj1v5v/m5X6h/f/RD34a3Pm7FS1ziNSLyjMhbuePr\nGH+wY/vv/U96CR/wHe9/Nz747rfBdUG8HcmAYwKwcMPGZKFGrIFhC5MzbDZg58Axgq38gjkzchmU\nr5lo5bSxFO1qndAAlBJsyshJtdZ1DKnMAiEv3ZFwXgqWBcjNArKlmYUrn21UUVI4GeCUHCnKlkUf\nftJQUxC9And5ZlMYzVkNeSNSDEgNWM8lyx6PiOMRcRL3nEKRxCR66qLwSAAyOakv6HxwwwxvCJ13\n2O0GpBjBOQKUkTkicQSngARS13ZGVDOGVDrnsQyFWjTzS+NMuXAwqiSBMfUqST5uGSBVeH0tPup9\n5BmJo/zrDTntTTBze23+UwD+4ZPW/7F/b21o/YV/9k/+MC97iUvAUQfXUDBT3lJfN4k/6LH9H/4H\nPywZ4XiN8OhVzA8fgGMEMSMZi2wCcojIpNxzYpAFTGYYI6a4zICltPxOSfTeBrRI2hQElgyXUQRo\nWXuzczZ1SFUpghLZ6s1oux6m68HOg41DtjJYyui868p/131RCqALlVF5dyjVo7RLdSxv5pBUXXop\nQK5S7CUz5ZzAWcA6hglRi43h+Ehu4zXCdJTlsxoLh4gUBLRDEPeYEBW8GcjGgXwPch4wnY7NzfDe\nYBh6xBSQ+QoZGTHNCHEGgkMOBrlotXOuLuty5dGoXSpH1dA/CuiyDtWrElGSNAdNpUa0g1W/UU89\nOjPoC9Bjj+2nBe0V805Eb2fm5/Th9wP49FNu5xKXeLPFzY5t56WDzyfYPsCnAFK5WTIGiSwiAkBB\nRBFOLMmMc7DahWcbQEtEgGbpOWXkQhQbCD9dRocqp8CcULTbhSKo6gaj7evOw3cdXN/D9gPYeWTj\nkIxd3GmcTOdbgPuE1mdoAbRk0QJUAtAC+lYdc4r8bmX4UK4QSjoKqBJFrMtyiohhQpiVBjk+RLgW\nRUgcrzXDnhDnCWkOwmnPqWbc8xwwzUGojSz1EPITTL+D8Una+kGwBPS9A9MOMNAO1oApzDBhBmYH\nNkkmEzBqjSAvQ2TqB5AMWa+ogNUJT8ayypVRLnUF6NVSIfqxqEYK/1+oETrd/+0h98QDUt7I/wDg\nTwF4hoi+AODHAfxpIvowREn4LwD82BO3cfftq8dv+9Zv36zzwmc/t3p8lbcFuXzmgzx4cVucbHIW\nAMBxfrRZx/bbouB73v+BzbKH3bbb0brT93auqLnd/u6w3RZOCmvptIoK4PqVr2yWffbTH98se/D5\n390s+/0vrIu+n/vCc5t17rzvmzbLPvSvfsdm2eef/8Jm2fSVB6vH567q0pmi47mDcjut9Vwh8qlr\nhK8Zr8exzcYBlkHew6YeSKJYKMVG6A+6WEwZBQFpv1HArj9iyFAkkL68AETOqIYJMFKYzCRdkFkJ\n0aRO8KK/1m0VYwLn4bseXT/ADjsFbYtERr4bIzZhi0t6JajX+0uLZJX+aKf72QW8yZaOw2UjLSOy\npl+kMzPFGSnOCNOIabzGdP0I8/VDxOM14nREmiakeUKaZwFrBe4wR4SQMB0njCFimmaEzDIsy8+w\nMcF2AcZ3gPMwxsB7C7gBMITIEVOc0c8TrqcjzORBNur3psoULk08bRFxOVhzo8uuVyGEeqIqDTZ1\nX5SrJVpvqwX2J5XCn0Y98pfOLP7Z13reJS7xZo/X5dg2VgY1WQ/yHWySVmuoa03OMozIMFUFBpsM\nSxGwCQiNMqhmpAW4AYZYVJUB/QDARrL1rJluylH4Uiwt8zAy6c9a8WksoO2GkmkbRJSGEaVQ3GIL\nVif1YQGeZXZKoUGoAn31fzRqK9Y2lDQYVK4Kiqacc5LCY4q18DiPRwHu47VosqcReZqRwixZ9hwR\npogwR8xzwjQFTNOM8Tiqq0wEGwvjO9iY4PcZNouKxNgOzlkYsoAB5rzDOE/wR3GPP44TaHYgE1Ha\n/ktRFww1ZYBSHGvgJp2rXTJmolIPqEcc2qLkMkRqOblR/d/j49IReYlL3CAydGIcWbBxYOvBrgN7\nHWxUAdvBGgfYIFo0o23ZZESGV4p1SppKF3cGk0EmUS1U4CMgk4FBRkpLJlf5Y6LGHMCJyW7Xoet7\nuL4HnEciOYlEBpiKVViZh60a8qI8aQHb6DhW28zRtuuZ2lWbXd5vLca1RUeVGaZyL4OrYgyiw55n\nzNMklMg4IU0z8jwhzgFhCghTxBwS5jFgmgKO44TjOGGaI0LKYGvg+gxPosjxRDCdA5GH9aKggTMY\ncsQwDhj2O/hH1+j6AfMcYV2sRd3iDU/UcDtoC7JFAilXyfUqktNa+ksLZbJUJoxeYWaUWdrET0bt\nC2hf4hI3iFKYyhD6LpPw2Nl4scLqDAgO1gYgdEAIoBBAIYHCBIoONI3qwg6ZHZIZbAtwC4JrbUrC\niFWZvK4w2EZnjFDhlo2Bs+LT6L2vQ5Nc1wHOIZb5zyzvuzq4WwNnjZoYNE1ADWBXkLa2sRtb5mpX\nzKpdnGi605XCSakB7kYjrh2aKSVpcpkjwjQjqtQvjjPmcRKwnhPmacY8RxyvJ0zKayfdRyLVI8BZ\nmC6Ac4IxBGcNqHOgbDGniGG/Q3d9jW7Xw48dunkQSWFIIIpCB2VCFrcCVJeborZR6x05cS6AW4ZG\nrYq7gBL7KoOUvQ8DA2ICseznJ8UbAtrjCU37JWztuQ7f+idWj+89t+VPMW+bR8KDre0WzIkkKW+n\n073lbW/fLHvHO96xWfZi2Da27Ls1D73rtvx7121fk5g3y8bjmm+fz0wyPJ6xZ3v46vZz/8qv/vZm\n2Wd/65+vt3XGR+yb3/bsZtn7vuOPb5d9yzdvlj3/e19dPX7hhec366QzQxTOTes75bkTtvZpNm33\n9R9lZOWqM4s0LGbVCJMFmw7wFjAe5BNsiKAYkOYAmiexHpvnhRVhBmwS/jTmIohD1WQDxZMLIIYl\n/f3rfit+jIsjugC29x6+K7cObK1kzzrWNLPw09YaOEMVsDegTUaNfEsBsmTiDWADi2a55NfV34Hr\nvPGlANk29eTqrZmTjLeVImPEXMD6+ohxnDCNAdM4Y560ADlFTPMsum2GqGWIQN7Bxg4uRQXXDGMJ\n1lkQCH3q0fUdhmHAMOww7eQk4KceMZQrAXlPhiGt/a0ssnxKkn9rp5CUe1p2iQZVfbYhKyw4S6Zt\nocOivk7NNZe4xP/vg9XVO2XUDrqYCZktQATjnEj8OINcgolBOiatE3UHSbaFFKUIGQM4UuWrDWl2\np69Xuw5ZLvtN+ZETYEnHkjonPLbSIl6n23nv4Z0DOyc9LSYDScaQCihDwFq3VZYJcEuPz+k88NLh\nSSiF5EXKJ49U5YKloNeCNisFUQxyi8RQLzCQEkuhcYoYr0eM1yOO1yPG44RpmjFNEfMcMM8BMcos\ncyaCZUZnDVxaBmGxziI3ROqRaeC9Q9/36Ice/W5AfxwxDELBpBgRQ6y0T1aLt3baolAeWb8DUlAv\n39Wi616olLYYSQr0JYmpp4PLaNZLXOLrFSUpSgwEBuZMmDNJCzikoGeNgQVgTAJ0NokRBJSfcM7S\nWBOictGpyW4JoJLNqTZBJXc1gyUAVjJl6z2cswLSvWTWXddJlu2ELmFrtcCm4KGyMzW6Wm6FssHS\nPLKwHwv5zlnMFaTl/oT15XJfpHO5ctpc2+XbIVTluVK0zdroMseEcY44TjOujwLax3HCPEWEKAqS\nGEU3ZqwD2wTHy+zw5SKOly5RPcF579H3PXa7HabdJLrvKSCFhOBDHZ6VQ4YxhJTzqmJYBkAJEBd/\nzaVQabQ4vJzIsHos1YVlgJT4jT4+LqB9iUvcIEqbdobQIgEGczaICoaGDCxp9qo6YWMY5GS4P1IC\nxxkmOBin+uaihQZX1VzJ11DGMDPDWIJhVMWIccJJFzqk63p0fV8zbac+kZkIhhlUfCkzg5GkwCk1\nT6EYjXKycOpJSUDWiaGcQVwaaPKiLgFO1A/cNOnwkvWq7+MyDpbrGUj8KMUWjJmQmBBjxjxHjFPA\nNEccxxnjNFfQTmlpfjFEMOxQJoNX6V0z6XAp2Bo9yQmN1A8DpnFG13eYxwm+6xBCECljIuQkXaiJ\nlxZ/IqGmQARbrp7IaJ1hTfsVl/ekEsJyhWFAIhrCQiU9Li6gfYlL3CDIGNFHkxHQZoOJLWblQQEZ\nw+oAODA8CB0MvPGwLsP4CA4exvraQYgqrdNZz9aAs7oWliYMaOarGTnU/dx6D9f36AaRsHV9D9/3\ncF0xutXtp6SArYYCrF2YlJBJpgWyzbDZgQpKMFDd0PVEQVqALIVIoyexlZy+Uh7KD2sREjmvKBGu\nOnBp0DHGCXgrcCfNuqcQMUdVj6jpbowJxRGIdN6tdHrapuPzhHuHXmFYC+d8vSLpelHadEPAPM2w\n3gMh1KualHOlfayR7TsvVzGlluDUYLgCN5HO/5ZxuCHKySaGCM6MFHTcQZIdvZ2juMQbAtrdbt1o\n8jvjtvHk1RfXtl5/+u3fsFnH7D63WTbstrN8mNfFQxrubNZ55zdvG2n6M1P44pe3hbUXvval1eO3\nnrHrevHllzbLdrvtFMH9ft1wM47bqYLTvC3Iue7WZtlLj7ZF01dOCpv7O9vnDVdXm2U5bguW7/3G\nb9ws+/x71/viay+/uFnnO75920z1nd/14c0y69fF209/+jc363zmU7+xXvBws8obGtL9B8BkZLII\nsJg4YUwGUbM/cVJhdAQMhqXphSyclTkgxnqQNYB1Iu0zdmliMSSt740TOoy4rJiYBNgNQM6qruXv\nIQAAIABJREFUvM8JFaLA7YcBrpMsu2iqi5ID3E7U4zoXg0iUJOwy2C+uK8wM5EKe6IlDddmlMGna\n5pumeaRos08zbS7t4W2mTRZECtrGgcmKUTJDx7EKeJdBUTHn2opkCGBj1MzYwDgrN+tqa31RsYCL\nKbCBdxa+E5pk7gP6fsbcTfB9Dx8CQnCYg9ETC8BMMLC1dtAParAw9Oj74kvpVzLIpPz6NM+Y5lm6\nOMdJujpHmaeSIcXPKv88E5dM+xKXuEFYK9IykEUmiwSLmS3GnDHHjBhZpslxRm8AdgTnCZ21IMcw\nuQO81zncVpp1SgZrDMiKue3KQYZEiSS8rIVI/RS0uw6+H9ANA/xuBz9Ipm2dgDaMqdMDuZgDp1yd\nYGTzCdla4bqxADF0pknhnrNqw2tX5KluuzjDY5H6cToD2rxQG0sGX/ZFYdqNjEYlI2CN4tsIWcew\nZNfOwnUO1jsY77RpyFV5IqB5bOZSOZX37sSSbO4j5iFimGaVEwaEGDDNM6xzoBiAKDUK4cIHDLsd\n9vsddrs99oc9ht2AfhhEYukcrLW1szIEaQQ6jiOOxyOOx6MUVd2IeZwRSOeqnEmaSlxA+xKXuEFY\na2EyQIbBCtqBhdeeIiEEka5ZzsgW8GSxd9qxaI3MGncdrPcg60DOgZwHxQTKGQbKIWuzTWkxJxbl\nSCadzd11cJ0AtB96+GEHPwzw/QDrO1WxWDELUHV3LSnmVtXBIMoqR0swNsHqbG0xHYZmuHoVUVQu\nxiAZI/sj6b1ZeF1hVmQIU05p1WTDOsM7NcXIetOCJJPRudS0gLk1MJBZIZRVo+5dvTnva53A6OwR\nLp+XM8BGa7i2qkhiTEgpI0aZaRJCFKDtZ8Qozj7lc3Vdh/3hgFtXV7i6dQuHwwGHqwMOV1cY9jv0\nvWTb1poVaAtgj7i+PuLhw4c4PrrG9cNrHB9dY7QjZs2+cUbNDFxA+xKXuFFII4uAdsm2MzlEZMyc\nEXVSXM4MR0JrwEjLuHMMiwzqZiTfyXwM62SanzXgrHO2q/pLgA7GCNetUjwuWfbQw2mruhsG+GGA\n7XsYHcda5tyIS0wpIloYw2CTBCRNoWGWgh24yIZVQ628bFZuu1VjlKFR7GQcLJdZJoyldZ2LeoSr\n4YI4wkcFS+V7S6NNoVSARd7oLBx7MEUQK29sDVzJsL2rI2cZqO+33EzOIMMwxsJ5g144LrmSyJCB\nVDEjhIAQI+YQKhfvfYK1FofDAbdu3cKdu3dx584dAe5bV7i6uhL5YKklWNnvKWfZ1hwwjhOur6/x\n8NVHePjqq3jwygM8evAQr77yAMfrI+Ic8PIFtC9xidc/rDUwGTCWQcYBlMGQW0ZG5IXXBhOIHKz1\n6lsIWGLEOCN2PYzvZN517FSzncBGVAWr0pRaWrEh4W07KT4KUO/qzfYDbNeDfFez7OKiIvSLg7Us\nqhAF8Vo81WJgndQHaEGx6VzMi39k4a9Lc0/ODs5lWOu0w0+1zQ2nvXRBSvt6KLcwYw4BYQ4IIQpn\nrfSJZM0OxiV4EqDO2pFIVhuLvJfmGR03m1lOMjEn2CQ3kxkW5aRr4RzgSn0Bsh9SykgxIUX5vKIG\nIuSc0HUdbt+6jXv37+HZtzyLu/fu4dbt2zhcXWF/dcCwkyJwqSWAZFKgFE0jxmnG8Tji0cNHePDK\nA7z04ot45cWX4bsOjx4+wnh9BNZ9azXeENDenRT4jtgWBju7Zt3f/e6tVcLxhS9vll1fb7sF53Fd\nnXrHt37LZp0773n/9nlm2Cy7e3/bOTmN6+Jemc7Vxvjo5c2yl766ndZ379791eNzCs0XX9g+74tf\n/r3NMrfbvv93feDdq8e229qBXY/bSYnLpIslvuujH90sOx7Xxc+33L+/WecHf+SHNsve/20f3Czz\n+/X7/9rLDzbr/MxP/tTq8c/99H+5WeeNDGMtbELloJlk3GmGA0tje9U5WzJwxsFbL5fjnWTKlGbE\nuZeseBpgUhZ1R86gnJFtroOHmJNws6VI6R1s38PvduiGvfDYux3cMMB2A4zOlGajZsPM2kVtYawk\n9qX4l4xmwJBj2hblhcoQWVPuhZ9O1bld+0yEItGMlHMGuyx8svaySzEyKfirsXAD1tM8yW2apFgX\nAqK+DhkpLFpv4eFBiWDYLpppQlVyGOfEEaicKDgjxYgco5hEZOleNKq4gbHwGbCuAyC8eUxZLc2S\njhNgeGvBnLEbdrh77y6efctb8Na3vgX3n322gvbusEc/DDIOt/OiXCHSJiyhiEKIGKcJ14+OeOXl\nl7E/HND3A6x18N3LOA4D8Dvnj7lLpn2JS9wgpJVbslSGBSghw0JEtxYgB2cADwPvDDrXoe86DJ0X\n0HYEkyNSCOjmGSGEFbBBQZaJwDFIEwbpSaITcwO326Hb79EdDuj2B/hhDzvsapYtyGyqrE8UKpB2\nbialSBKMLfRFkcIZcbwxi2N4lTWUrLvhqAGVttmGAmGGTUmoCiw65fK8FIUzDmHCPE+YphHjJPfT\nPImkLwYdQSv72nkPGMCxQ9J5ICXHILOW+ZUZAVW5wsusENLOSO89rPNgKICDlALKCtYAmGGtwdQf\nQSDs9zvcv38fb33rW/C2t78dz77lWVzdvq1Z9h5dL3NenBP9fWmmKdrxlDLmEHB9PeLq1i34rqvv\n23qH6zOjK0o8zTztd0Hcqt8GqYn8FDP/V0R0D8D/COA9kLnDP3DxibzEv0zx+hzbWqBTPjRlQs6E\nxMKROmNhAPTEGLzBruswdD2G3qMfDGzWaX05ISShAqCjUY21iGpkQGFGjpLlgYQWsUqL+P0e/dVt\nDIcD+sMBfreHK1m2Vdkc1AVHG3NgCIYN4AyMycjG6qxvri3WRtUpAtrQOeGqpW6aaRZ/yUaV0rSs\nlxndAvfccMtCFcR5xjxPmKdRwHoaMWrGHcIsfLRIWWC9lZOilde1pANpiz5cTRnIyPRF6+wC6OWK\nuGl+sdbWtn8yFsY5MKPJsOXEaQD03mPe7UDMOBwOuP/MfTzzzDO4/8x93Lt/H1e3b2G3P6AfBrhO\nRuJa75Qe0U/fnERCTNjtR1jnkLJozUv35tnZ+xpPk2lHAH+dmT9FRFcAPkFE/yuAHwHwvzPzf0FE\n/wmA/wzAf/oU27vEJd4sceNjWyRwS+NH0FtKwmFbMhgcYe8IVzuHq12Hw67Hbtdh11sYeDinxTpj\nQM7B9z3mvsN83SN0PcI0IoYZKcikOmkcMQLYww79YYf+6hZ2t29juLqNfndQ1YiHsa4WIMUx2ChF\nzSCrM5+NeFfmCtqyujGL6YE8X4p6lhdwF99L4ZUXsJaTUIoRofGMrPtMM+2UombaM8I0Yx5HTMcj\nxuMRY820g9QFoLSO0XkuTKKBMWWOODeNSaoWIeG/ne9E9uesDJJqnHraG6ksMOcOKe7Aqt6x1qLv\nOhyvd+LiDmC33+Pevbu4fVcKkLvDHsOwQ9fL+IDSfWqVpimtrUJNCW1D1oLB2IUdDrdu4fZxRAgB\nZAyO11vKssTTmCA8B+A5/fshEf0mgHcB+LcB/Bu62t8F8I8fd2Bf4hJvxng9ju3EZbofI0QWn8KQ\nEJNkZ95aDI5wq7e4s/e4te9wtRuwHzyGwcJSRuocjPcytL/vMe12mIYB0/AI83GHMI4I84QYZs3E\nSCby9QP6/YD+cMDu6gr91S0MV7fR7fZwXQ9jhasFGmdvKjRGmTki92xED16bXHTQyMp6jLLao9XJ\nI9oFr8/NTfNMTAg6pXHT2q70jwB7EHpkFtCejyOm8SiAHWaEHOWEQAA5AwOrH8fAaslXpN2lU3QB\nbWOd3mQGi+97OOeVtvBwzq+kiXJFwei8A+96EIQS6bsOx6FHuNojRqnh9P2AW1e3cLh1C/1ugG/k\nhVVaWN4fs85k0R1LZdSunHScdxh2PQ63rhBjhHUW4/gY6Qj+gJw2Eb0XwIcB/F8A3sbMz8t3wM8R\n0WNN1l8+rouML7687fr7ix9aW16971u2HZFve++28/B3v2U7QvTBK+tuxPd+y7YQOdx6ZrMsxG0L\n0tWd7WXK4WSybDozRvHOmeLk8ctf2iz7rd/49dXjOG9Hs77y0raM/JWvbTs1+/vbzkbP6+Ie+e3I\n2Gff8Z7Nsvtv2X6d+0O/WfZn/q3vXT1+9V/57u223vaWzbKQt12eHNbFT7fbjmH9vr/4/avHr1ch\n8g97bIsDOBASY45ZW6uFDzUAvDM49A539h53Dx3uHHpc7Xvsdh794OAMI2cxJ3C9NMRM+z3G3Q7T\nbi+2W+OIeRoRQxCuGwzrHHzfYdjtMRwOlRrpdnuhR3wvmSMVfbIMFSFSkCvArEXS0iXZTuVbZmNT\npVSQFMT1Mh8ommoBbGjRMMVmul4u8A5dn8G5zM0W0I5qeiC3EfM0IcSAGCMSJ5m5YkiAWzfFIqDU\nLFZpn+KqozZrxjr4TrTqXWnv18mHJRs2Sv8YrR14ZwF0sIbgvUPoe+z3A4JOEgSAznfY7XfYH/bw\nXQeyxZ5MrjJYFT+GWe3XqJ4IZVYN6roghuscdocdck5w3iOELQ6UeGrQ1svHXwTw1zQrOUWqxzfL\nX+ISb+K4ybFd6JDiBB6iAlbKMM6gdxaH3uP2vsftfY9be6VHBo++d7BWENSlHla7GDttiinSvQra\nMSClKBSFtej6Hv1uJ2qF/R7dsIPtBthONN9E0hZfCogyu0T/XjdYLh+Sm79l51QgN7kBa9J2dtVf\nZ1VFUErgKNP8QggK3qm2jQMF4FU2qMAcw6xuNVKMjSmKPhu5oCnIGdiso1DBgBZly/sl9eQEEayT\n4qL1HbxbukSXWSwK2q0TPVS66KQl31uDznukIekUQRlMBUBVHh36YYB1DkBRhyQgEYwCuOEMykX3\nrlcDRTvOcnLPnGGsQd93YD7A+w4p3bAjkogc5KD+eWb+JV38PBG9jZmfJ6K3A9jq0jR++if/Tv37\nI3/iewBszQYucYmniU//yifx67/yyddtezc9tv/rn/gJhJRxnBK+4QPfibvv/nYd7gQ4YzB4Ae1b\nu06pkR67oUPXe7jOwjoBHssdTCcmtNZ7UYV0HXzXS+Y5T4gh1B+zsaaCRr/boR92cF0H47x0VarT\neuFRSbPQwn3UpE/2QvP/MoOkPVPpI2NAWXFRuWxjLUyW+R42W2RrkawFxagzOpaGFuRcefAFtNVi\nLKalAYYXY4GqXCFI4RQAdJuFcKija6G6dS0oWrvswzLxUKYe9quph7YWW5d5KTAEdoXyYXRdFoOF\nJNSGUTNkXzThJ+qY2hGVIdMQy7/rZ5GsXNcFw1iD3/i1X8Gn/p9/pkXdxx+zT5tp/wyA32Dmn2iW\n/QMAPwzgPwfwQwB+6czzAAA/+h/91dXjz/yTM640l7jEU8S3f+gj+PYPfaQ+/vt/72dvuskbHds/\n/GP/MY5zwosPZ3zllQlffTCBISNYvTXovcOu99gPHQ5Dh6H36Lyr7udkjZoZiAaYdJkMO3KwXQc/\nTehDEOmbAp/RJpauF1DyXQfrPEgLcExFW91SIQK+i6x57RXUZtrLMl7x12XatiC+qWoNax2yy6vm\nmdZuLMXSjp+rIqPadqEwB4uioyw3zuqcEgtqNOKmyCHbpiOCUkIyS8R5ae0v2XW9dV7UHe1ckgrY\naIqmBBjUdn2hXTK4Ov00zy8u9KZ0mpa920w8pEpUtXtcqRnCR77ne/Cd3/VRJJ0D8ws//zNnj7mn\nkfz9SQB/GcCvEdEn9ZX+JuSA/gUi+vcBfB7ADzxuG194Yd3s8uxu2+DxwfetaUO733LJd+5sOdsP\n/al/c7MshDVfOk9b/jSEbROLMdtlckZfxzStiwTxzGkxnWlOuffM1tbLnaz2/O9tG4jyYduMRO/c\nbj9N24rzo1fXDSrdYTvJ8J3v+8bNsmfetqVxnd3y9PNJY84YtodUt9ty4Wft2E688Uza7vvdfttA\n9IeN1+PYnqIMhgpRR7Ey4IhAltA7i6Fz2PUO+96JzK9z8N7BOvmRQxtlmFCHLkG139Y5+K5H3ImL\nSslEi2NK6T60zlU9daEHCnUB4MQThRQ8ToIXLpuxKEjax8zNdrhCTuWQXXaAL/u2ON4QojFIJmp3\nYayDRZgYauuDVXUTMjDKqiFA0asjZ0Cbear7DSSb5wq6pQGng3MdvI5Z9X0zW7wTF5928mGhR8q+\nqZSR7gixGlsAvbTuLzezGCHrrfxdqRGU65zmVHPSUSonLtSC8bl4GvXIP4Xs0nPxZ17r+Ze4xJs1\nXo9je5wjpiCdczmLYsTpjOveWey8xa4TwB56h847vZxWcG24TrTzqIvXY1d8FFvbrCoFqRngovKg\n9aV14Trq+lswWAA6V331kllzXUe4a721FAZJtg1XlBwC2JbkJBStFRd1CvWjpvqOliy7NQ9ISSYN\nyjjYVMEapY0+J+SkUkOuXmhK2ThRh5S52C1oK3CXTNuoXyaoDqBddkq5Eih/lxMGi4lEgd4KuCsV\nilm52J+eJbUGLJ+9XuI0tyfwI5eOyEtc4gYxzgkhZsSotAUJaHtjMHiD3lv0ndw6L8OJrF5Go15C\nA/VXTahjRK21cIUDLqDRNMBU84CTewCrDK70mFPJtOsqdWXNWBdwZt3GCkr49LX19UiukgxsBWER\nezRZJ5r3VbsMlaIhA5OTzOWmqBSJFjBzBrNDMV/gnJGMDJciSpUyKbI/Yy2MUiPVI7MvfPbimSlF\nyKXFvAJ2Aeqscr0swr3MzbwUHZNruFweFLZoMa8wTfa9qvrWfSsZ9yLbaU8O3Hw327iA9iUucYM4\nTkGaaqKY1BpmeGL0FugdoVfgFsC2sM7CWC10NWqC0ia+XH4DgK0/XktbwBSrqlLo42oyrH5gkP8v\nJgb1kptR4XvhsQvx3a7TAvZjQFs2LK9BJAYPbAErJxnLwklna5FtQjYG2UhDD/MyIJY1/y7Zds4G\nOVvNsJsiZk4VHDNRvfJgoJH6tU704pFZbk7daazrVKNtK6YKWC/bQwZgGGIJ2YIrFpBF+dgtWBfw\nxirLrlcmJcMut+ZxiS35ucQFtC9xiRvEcYrIWUA75wyDDGMgoG0JvSN4R3CWYK38qAuPLcqOJdte\nmgbP/Hw1i2cqmXcWWRn0R08MkHrKGAayokNrnlCyN11eL/0Jul5ZX1UmNdlTooRPAHxhvM/um6UU\nV/5eeFsyGYYNtEcTrK7zBeRMLoCsPLbas+dct4REEKu30toPEgcfa6vdV/F+LNps33ntkFwaa0C0\nFDnL0Ky622W++JmS7aLAaYqYi4N9uYrA5nmF1z73TVfwfgJqvyGg/bkvfm31+P13toXIw9W6MMX2\nDNV45pLhTJ1wdQkIQFwwToLc9qObM9uP05nOJLN+bpy365wTx89ntjWf2IGZM++167aFvP3ujDXa\nmefySTHvcPv2Zp13vvOdm2V3zzTX5DPa0ZdfPFmWHm3W6d22gNnZ7VEZeb0te+b7cE/MQd74uJ4C\nwIwYxQ/LgmENobfA4IDOAt6SmPCWX7MphSkFbqx/o0VxASxAXoGSCs+q9Ea7iwr4lr+brRK4cUuv\nFb8GyKkCfJNv6+V6U4QsXG65hK/3St3UedllMNTJ5X7D80o2agQoeX2MZAU8zvK+mBisgC1FSznB\nEBK4nJhIQNhZC+eKJM+h810D2sV6TUBbjJSh+1MpEErIVK4scpMtc90fhdYowG0UsKner7Xw7f4s\nCpKWGCsXQfXK4/HsyCXTvsQlbhLHKYg6IzNIZzT3xmBwQO+AzhGcxQLYbZchTpLgpjq1FAe50hnQ\n11lRJNwWJrEGa1Ys1n+ocrNVBt1qGbbZJDePNhRJdYBhLMYGMnJVCoVyn9LiuH5aROXyfhkrMBcu\n3qDMSwGqQHzJ1knGtVbAM8VFx9ZBUN7JGFzvPTpVjDidyVKHYekOF946gYq5rhGapnLedSfUnSF6\ndd27huSqoXD6qwun5sqk2aMbmgTN48fFBbQvcYkbxDgnWCJYMDwkq+4tsHPA4AidBayhIm5QfFrz\nnPUHqoDGzf3qb6wBGysQXWpaNQiShZbNYyEzzuDPisNeLuBLkbIFa82mudVkL9ZhKSXkGOv86ipX\nVIXNqojZ0DCrz9BgW1233pf9ocsAUHHiKa70Zk2RdI3UrwzSIrLL9EFmoWTqa2bklXt7UzJus2zd\nU6Yk+7S+FYu2kqU3Z+Nmxzd0Cy+00uPiAtqXuMQNYo4MV8Y2W8AbkhGs3mDnldO2WP2oF8CWX3bL\ndNbsl5u8rCn6rX/3a8AWQKY1GLcZ8wknnWu2fLIdVoFHe6uvJ39nRp2Lzblk1norQB1VX14AvAB6\nWmaSrLL2xqtyfTJYMvmck+q9ZUog58KFZ4AcDGtzjVIkBbA775UaET5bnN5NvRRhzshVS81gXkv2\n1rcz4IzlImqVKZ8Adq0FrACbNctext2aJ6D2BbQvcYkbxBQFrNlJRt05Aex9J/e9I3gj6g/RSBf4\nK2BdfuBtRszN38t9C6BYgWkDqCzFSeZFr10yZeg9F6qimPmeZL4L9XKaZcvrFPlh8YsUMI61LT3F\nIC33IawAOzdO7Bvp4koJs1ArtbOy+bek3aEpygRAAnRuNoljOmmjknXwq0xbipDGSps/atdo4ctl\nJ3MWZcoGrFW+CJSC41JopOabWrjq5ZQp30/TCdru87xk7kavwvITcu03BLRfGtcFsu/71m0RzdPa\ntqqc9dogbAtaIW+LY/FkWt8ct9XKcxP95hC3y84UD+NJQW4+U3R8+GhbkPvqc7+/Wfbi88+tHud5\n2705H7fLXnn5pTPrbd0ujo9eXT3+0Nu39mnvOLOsu9p2YT569HCzjE6+p747U+A9Y6FmsN3/Kaz3\ndZq330fvtkXsP8qImRCNdCAaBe3BW+w7g0EzbRkvsmRaMgdk2QYXmd9CbJ9cPSsVUn/866x48xjN\nsvI3sAZIPpPttuudUDG5uTHnZkhUqnOxYxQHnhhCnf8di8VXXjhvaZjBCrSK6W+hUZJm7iuuXG9x\nnhHjXNc1qmen0oyjzT7OifWY9x6+8+i8uN4bI+bJdV/XEx2DuDjerziOVYHRmDJrvClR6LfWAvZy\nSdVm2uuTZNn/4HIlpq/1hGPukmlf4hI3iMiExFIYc8ZIpt0Z7DqLwRt0FnAGMMSA+kXWzLhcSHO5\nSidUDvnMDRugXn78+Sxwt+C9UCGtK/qKYwZOqBhG6ZJsncyTgqv4O6r7TAVrGbMawizZtoJ2Bety\nAmIWf+Ka8ReX91i3nVNc3qvy5TknxCB+kuL1mMRkAB1cEquw6khTOG3n9ebEQEGz7HIlkvVEeiZP\nrPQFAKVh9ARbsu/KP/NJZ2OjG1H6pQJ2q6hZeCx9CcngtynNEhfQvsQlbhBZncxBosMumfbOGwzO\nwFsZHrVWH6wzbWBZVAqHtWC4pT9Xj/Mq0+btcqACRVFvFBBeioonoF2eo6Bd9NI1C34MWBegDvO8\nzrQb26569snN+8rcmPxGxBwrZy3PLTQJkFOs41xzSiACHMQiTDwfjYC1Fwsx7wS4nbrTlDZzhqnW\na5srn3pSWfZNAd9WrlcbbmqGLVDbSvnKFdKyqp6yTykSBX/G9ur1NC6gfYlL3CCYy4UwCadthcfu\nHaFzUpg0dezzkj/x6lEryFsyMC4cc7PuGpSfDNwLtYE1UJ+C9Ul2DWBxWS88stIVsXDWMZwAtv4d\ng1IkUeeKp0qNtJcALVjLdjNiijKjJMUV4JcTRdkpKZYCJMukPkBntXj4rkc/9Bj6AX2ZM1JmjOhs\nEGkeovpZV1clzRVFvaVGxqgnDzZmuXIoXwxOAXv5hlcwXLN3bg4ChujO13n6ubiA9iUucYMoeVad\nOWIJnXZCdpaUGlnWxYJbJ9kd15XWoFtfZBnZ8TjgzqfA3dAhXHTIp1keV/BZZdjc0iEROSbEJGBc\nOOsQtuAt8j4tPpYMeUWNFMDOkk3HJNuMEXMQk99pmnTbC1fOpXalO8QQ6UgACzIWznl0fYdhGDDs\ndhh2OwFtnXdt6lCtspubk1tTBE0VqJcrikoFaTGVQWL24NwKuFeA3fy9kgLqFUGliUqpklsV0elW\n1vGGgLYza1r9j93Zdu7lExKHebOKjHU8iXimyDidrDadGcMazxT8pjOdjTGcKQyerPfiV1/YrPP8\n722txR6cKR6eFt+uX90W+77wz7+4WfalL/7eZpk9c1n1Hd+5tmP7pg98YLOOOWONdtqpCQAPz7y3\nV156efX4+Gg7HvZcUeXcMnfS0cn8eMulN0uURgpjCJZE3tdZKGBL9l1Bu03K1pTn8g8rIN3SIyVZ\nLYCdG+ApGfWyDVSgbguIBTiXDHsBkJY+ycUSTIFTAFocZopFWAXtqsde6JDWsabe65yUrGAdQkSY\nJVOfpxljsRwrrxEjWN1dkMUswBDBe7sM1nLqItM3gD0M6DrxhCzHN5cdRwK8Zb8Il15u5fMmvcV6\nKxZqtTGoXD1gC9jN1yvcNy9t/GBuyJDlikr+v9Bjj4tLpn2JS9wgRAoGWJKCozOAN8vfRZ+9ojea\n59cfZ6UN8knGu+Y+K1CjBe7TLLlVibSZ81q9gCYjb3nWzFk5ZgFhyYSDgrWC9jwvGXYL2GXOtZxJ\nKuWwALZsOypYz/OMeQ6YxgnTNOn9jDnMNQMvEkFjSGzWOi04WiMZ9jCg1wy7HwYM/SDDobyTiYpE\nNbunholODAXsRQGTFKyrGmZ1S3LS02JnGWG7HAt63yygwoWXwiWX4Vpa+KyA3R4lT44nKUvKQfku\nIvo/iOjXiejXiOiv6vIfJ6IvEdEv6+3PPtUrXuISb5J4PY5ta8T0wBmhQnwBb2LoMD8sJStagffy\nAAtgl/sT95e8ut9m2vmELmnpkTVIn96WzsY2s04pVL11C9QVsMut0WPnKI01haeufLACY4wRIQRM\n84xpGnEcjzgejzheX+O63I6ybBxHTNPcZLfCWxfN9bDfYbfbY3/YY7/fYb/fYxgG9L39cSeUAAAg\nAElEQVSAtStzshWYFw15XBQqJ4DcgnVLzaTWCi21hdvlDFyVJMqDLA02rWxQ/41OyI9apS7xZPB+\nmkw7AvjrzPwpNUD9BBH9b/pvH2Pmjz3FNi5xiTdj3PjY7pTH9m2GTZJ5G4VpboB7aVIu2uyF0lCe\nQ2Y4s9IdOAPUmhUXl8QK1iiJW1NY1HVa/rTwLi133VIiOSXEJE0s4UQZsgLplMBVGZJPzxjLySAt\nJ4MQFipkGidM44hxnDBPknHPswB1TKmCoPci2RuGHrvdDsPQ43DY4XC1x2G/x+Fqj1u3rrDfD+i8\nhzVS1C0SQgaQDau/JUsRESQnupwXkE7L/aqLc2VAgcr/A4WrbqYX0gLOBbwl09aMW4+BJQrqN4/L\nxMXHxNM41zwH4Dn9+yER/SaAMhbuydqUS1ziTRyvx7HdWUKngO1JM2zIrTYQVUClenm+cJ4K7BWw\n11re3NAfbSGyNIM0fgIr9cfykz/z49dL8nXjStJGmdIm/jjALmAWwSkBOYvGmat7pLyHplsypgWs\nwzxjGkfM84zjtWbU44R50teLqXoyWmvhfYdh2OGw3+Pq6oDDYY/DYY/9YYfDfof9fsCwG7Db9ej7\nHs6LMUFOEREkbkI2g4wFmawemhZMC2hXHrvp4FwXHxebt/a7W4O1WpatgHu1u0HlqKJ2I+1XpFt/\njSPvD8RpE9F7AXwYwP8N4HsB/BUi+kEAHwfwN5j5lXPP+2O31izMnrfFvcTrd+rOVCLjNG6Wjef8\nH09Yn3Ba5QTE6v4kctoWOo+PHmyWfe2ra3Purz333Gad+dG2OzGP2/f/wgvrbX32s5/ZrPPFz28L\nke9653s2y37gL/w7m2Xve9+62/HVV7ef5/e/uN0+DVs/zgcPtl/vq6+sC5Fw2zGyzm+7GI3bFqPN\nyWjWM/VR4IyP5+sRf9hju3eEXoG7BWxqM88nvS4KVVJ43wKmW9BezRVBoT9O6BDdboHupXhZTiAt\nf11okVjBOqa4UoS03HWlQBrtNPhMlt1m7Ar+cwiYpwnH4xHTOGKaJgHto/wtNISoN6waBVvrMAwD\nbt26hTt3buPunTu4desKV1d7HA47AeqhqxZuC3+dEUNAThnGRpBxCtpJQFuba8r8lELdFMniqRKm\nFFblhGjK8aLZ9NrFvRggtBwIteuvSHCs6ex6Jr85PVLe5BWAXwTw1zQr+UkAf4uZmYj+NoCPAfjR\np93eJS7xZombHNt9UYtotl0Amxa0XIErgMYdHQu53dAjS5v5UigUKoQqL14ybl79p5ts6Q+022+m\n8WWhNsrckEINFPAKRdY3a0u6ZqC8mh+y3IoVGNcMVZUhMWCep1poPB6vMY4jxnGsmXZQXbeEgSED\n55zSIHvcvXsH9+7fw/1793Dn9i1cXe2x3w/oeyduQEZQr2TNOQVwkqwXxoJMAe4FwIUiEaf1lAuX\n3cgX4zLfJKVcKSqYSoxU+mZFiWDhraHfE5bF5wdQsVJoNSU/AfeTeCrQJiKnB/XPM/MvybHGrc7t\npwD8w8c9/x/94s/Wvz/wwQ8DH/rXnuZlL3GJTXzyEx/Hpz7x8ddtezc9tv/x//zfw1tgZ4Hv/e4P\n453/+kdBKxBubmiQu82mToqEaPXUxWSXIe7lq2tryA9+9Y5qjr0pNq4HMjWKidRI+mKrxZZiZE4L\nHZJzBqeTeSDK+xYuuoB/UMXJOBXAPmIcj5imCeNx1GKjZNkF3brOSqFxGHB1dcCd27dx995dPHPv\nHu7fF9CugO0MjCkSxajvq1V5GIBExw2T9D6qCfAC2kv7/HLSKp89xYRUGmpU/bEAMdV7roDdfAsN\ncpNMsaqdlMQtcEsL/C9/4uP45Mc/8ZrH7NNm2j8D4DeY+SfqwUL0duUEAeD7AXz6cU/+c3/hR57y\nZS5xiSfHRz763fjIR7+7Pv67/91/e9NN3ujY/r5/94ew94R7PfCWHQmPXbNrXgHyBsBL8JJRn72V\na2duntVwom3mziVbKyXIZqRpAdjcqidSaNQSocr7YuGtc9OCDq50CDfT/YqeuTTbhJgwz5NI+oI0\ny0zThGmeMI6jFCFnpURSqh/Ke4++H3B1uMKdO3dw5/Zt3L9/H8/cu4tn7t/Fvbt3cHW1R985iLFV\nmQS4TBaMISKmhJwBRnFpdyCTwKRgTQZMpMVdvapJWbs+o3ZzapatunIGxP9S6RFe72Vsr3m0elFp\nEVOdseoJFfqdkwER47s++t348Hd9VHYxHn9svyZoE9GfBPCXAfwaEX1S3+ffBPCXiOjDkJrIvwDw\nY4/bxrt3a955nrd8pp/WTRnc7TfrxLTlM1PcNmCcUkLnJso9Or66WfbKS1/bLHvxK89vlj146cX1\n+zqe4aqf2z7vc5/7nc2yL31p3STz6pkGllu37m6Wfd+f/3ObZR/+4Ps3y377t9ZZ6fWZGsBstlMX\nXz6eaWw5w7WNJ5MFnz3DtZ/aiAFAPFNT6Ha79eN5+x6OZ2oFf9h4PY7t3rJQIyQuWLU1gqVNm/Li\nc4ichZPnjDYlK0C74qixAPYKuOs9tbgNhrqHt3y1OrEs7jFFvrbMu47Nffm7NS3gnOqJplA+5SRQ\nwL2Ac2mImaZZ9ddzXT5pw0xUflsy2gguRUfn0Pc9DocD7ty5jXt37+L+/Xt45t59PPPMfdy7exd3\nbl9hN/SwVjLrGAPiPCLGGSE09E7SAi1Jpg1KAFlkEnopg7SQuz5R1quQqiDRKws5WGQ/m4aIogLC\nC3jXk7VWHdd8dhm/ujwnM8NwbmoOqCfxx8XTqEf+KeR4PI3/5bWee4lLvJnj9Ti2e8NahBSZX5Hw\n5ayKCl443wrclFXAbRYJWUlksfDV68wcZ4C7oT8Z8lpNJsx1xGmbWceqlKhzQlrAbmZjy/vm+v5z\n5ayjdjNqc4xm0vM8i3wviJxPNNkT5jnU7sYQQqPM0JZwkiaZkmXfvn0H9+7dxf1793Dv3l3cvXMb\nt28dsN8N6LwFZ7kKiNOIaXyEucnaU2akXDQ5FkxFLWKQVOaX9Pspkko9FuoJqUwYTDmBs2TLZKxY\nidXChPzvFKyl/sCLYo/WwG30+5KpgllMjVtOpYD+GfFEiUtH5CUucYPoKaMjgicdYM9GfviZQSmD\nUgZbyXiRM8RhRf0OG8BYKz9OLrd5ye7aHzgTNUDPK455KTC2mXVLgyxKiVKEq11/tbNR6ZAi32sm\n+5VuxtrFOE84qhJEbpJlhzmIIqXQFik1BgySZRudf9154bL3uz2uDle4OlzhsD9gNwzovYezAnFS\n5Jwwj0eM19eYplE+Y+H/QRCv+pJhiwAzMRAzy2jZzEhn1D0rF56cwAwQGRjHsGSkDkmlqxHNBVND\njTTbrAJPKnm3UCGrAmZ9ca1haHv94+IC2pe4xA2ip4wO4hJvuHTgoQ4fMjkDKYNNBuUENlaKh5wb\nguM0mnnKzJA5pjgj6VsAu8zQKI0scVVoPKFElLdO4RxoN04zVRGyaJnrrJB5xjTP2hQz46ja6zI/\nJMySWc8K2oVqkOxazzRKV4AJhiyIFqswYyysWboaU5bW90wsqhZ93SJJTFVHTVpkFFojQyiIBELK\njJgYQb+blPOqtCC7e+melE5MhrEODoBxvurHrbMy7tWoLVlpmqrlCgFrLphdlnHzzfGS4Z++jyf0\n1lxA+xKXuEn0FOGJFtDOjJyBlBSsUwaZBNgEpAwyCuBsagWxXj6fAfGz80ca/js3JgUrc4La3ad0\nxymXXYptZXZIo5iIoWnvLvrtkKSdPUbM0xnuWjPvGJNK+HSMa8rIiZHi0lG4YBSDDIGZkFM58QBJ\n1w8xYZoDjqMMVYvOwBAjxgnzOGGaAkJISKm5UqmKDRm9mjkjMSNmICZGzBmhDIcqfHWj6MmclxOX\nts9bnwBj4TPDGpnX7Z2Hcx6uuLo3revFgYjBILUSgynsB6s8ks9OQIRugx93PscbBNrvpHVfwoMH\n2yaWw2HdpHHY39pu6MwUu3BmMt+jE4utl1/ZTtd76cUXN8sevfzyZtnDr22Lky+cNKN85rd/d7PO\n57+8LUROx+3nTnHdQTKfmUiY07bQ+au/+tnNsq+cec3erQuPV7e2Bd6vPtgWZV945Yx12fV22aOT\n5qM//01/fLOO3dYcwWesxE4Lzcczlm3j9XZf/FFGjwQHguMGtBMQkwFiApskTR0xwRgp7FG2WpA0\ni3SMi8x3OcbbQU5rL0euprrlPmmxsag5yn3hs3NaqI/VzI3QZNxtB+RcOhgD5hARFJwnXS70x1KI\njCkr5ZK12Fn03PK9igDFrFQTIJKLCAXqHBlhjghzxHGccP3oCEMGOWZM4whvBbRzjkhhRJgnhCDg\nWjTQUitYrnhSzohJaJGQBLCj3mp2XrhkcJ0ZHsOMnBMAQtd3sNaDhwwigrMW3qqxgrGwRMp3F8Ia\nSx2CC8VE9XOXoVpV0ZMXl/oywuCMdqLGJdO+xCVuEB1FWGimnY2CNiHFBJgEG6MUsYwFotVmjwRk\n03Dbj492gFTrfp5OW88rLRLr4KNlMFKqUr+ScecYq2t6BWwdArUAtHLWxwlzCFpkDJhmGfokWbXI\n4uQ19ISSeGkMqiNjqS4DSDlbBhkgGUaMCdMUMI4zHj66hncdDFmEEHHsj+i8g7OkUxOTFiMDco4g\nyARAYw3ICAedwUhJ6ZCUEeIJaGeZ55056yxykR6mJCeoGANSiiAipJRhfY8hSmHSEOkoXtOAdcmW\nSce/asE4Z4h+rZH4FZPjMlgrFckh1yuOG6lHLnGJSzw+PDIsCJa1sy0DKSVx7Y4RrEU2JlUyGJkB\nbYxqiJvr4BVPXYt16wl8q2l8hQZp6JBl8FGq9EYug4+avwtg50qNSHYdVQUyjxPGacQ4zTgeRxzH\nCeOkQD4HzM3M6azFMyg4L9QtVSzLqoYoPHIp2pEhZI5gJox2gvdHeOdBMIgx4brvBbCdgTMFLMXZ\nnpBBxDAGcNZoK7tQFRlAykCIWUE7178l0056BbDcWJts5sqTJxgFbec77Hd75fszODX0Rkqi+y6c\nthESm9Shl7NIPKX2cDJEK+nc7pSQYvm+l/11Li6gfYlL3CA6ypJ5QW5KWSImQiaCKf+xmCTAGJnn\naq1k5kRglf6tRrAWlUMpAraGt3nhqgtvvZpSF+Oalz53K7M1NMNeZ9rSej4eR0xzwPVxxDjPmEPE\nOM2YYxQgDE23YFIeNzNQPw8tmXajiMg5r1QX1snVgJytCDkD8xxxvB51wp8V5QjJrjOGZBca/L/t\nnWusLFl1339rV1X3OffeYZhhmAGDTGwDIYmAYQzEFo+I2I5Q5MiWLeM4+UASKU4kO0GKSEziD8hf\nYhNHiSIHf0mcxM7LjlCwjRQ8vEJ4eBjAMMOAgRkSD5jHvLj3nH53V+298mGtXV19ui/3DqfvnTlM\n/aW+3V23endV9T6r1v6vtf4LCUJZQFkW3g+ysEa/UqBYbCF7201SmiZZh5xonHm+pqra3uRMO3xJ\nSolQCE2MlOWAg8NznJvNWR4sKIvSjHJSUlVRNtH1uwv3+EOb1rkOV2iOjLac9lqytqGuXR7WPe/L\noTfaPXqcAlVIGwL3tiIWiJEEBPfAQxsoMw/bSqoLRJKvqI0ySGqpaLHlqXNZeN2WWrcFMrFpMzPa\n/OumIbbZId187KbVv7aO6WvvOtZmrGPT0HjmR84OWTinvVzWLOuGVRMtmFfbs+agK2K53U415GxB\nRWz57zxtt/WZUflqvRsLMYO6su+aTmYMB4M2SyME61IugtEkAYrgjXyrwHBQMahKqqq0jA7vaoPn\nZreGO9p31DFSZw3tNjc9eRaN8faqiaIINHWkKMpOg4Wh0dYxEodDBtWAsqoYxIrS25uZ8S4szNz2\nCKXNwzYaad1ubblcWZxgWRvlFHcEghzXxWjfWG5Wto0n2wc0+fKDG+9vPbddpbcsDre2HV3cESh8\naLPK8Pibj21/7hvbynwPfeUrW9se3qGANz3RYuuh4+0WW8eT7UDbeLwdRDs+EfBbLLcDq1G3x7rv\nvi9tbZOwzY8+7cbNa/a859yytc8znrG97RuPbgdvjy5tB2qLsLmMu/mm7bGaV26f9/Nf9Ge3tlFu\nTsdHHtpu4/bRj9y9/bknEKWlCwAef0rJxZ0AtewBSYmQc4iDedl4d3BBvMoumMHupKOtOeosYNSt\nYmy2jfiGwV4b59warG1gsFxZEK9tZlCTuimAdePVjI0Z6tqqDJumIbm3qgks9VzbFMfco9IyRbzI\nRfGgZM4/zql569xzE8sTlsuaqqqYzowiqaqqvSFmg124x12WBUUpFCFQVQXDQcmgKhkMSoaDirIs\nPZbgpetuuJuYjN6pG+qc6ZJppJTW2TOxAf++GNWM9uCAQTWgKkvzkpuGg7qmGQwZDAZoGjpNVLVi\nUlkF0KZDJw87Z7A00YqS5iagNV8sWC7tmC47567lhO7R4zsdISfUSk7FE6tSV22DjRITko25BKQo\nWolQWzWXJBLRsx26HcjbTiqd5rmtAl0nDzu5wc6FM61n3THWK2+YW7v+R71aWqOD5co/v2o529qN\nmuVHO/8b3RB7hkwu8MzZHzkIad6rUzyNVSnmdL/cNzKXeif1XOgQQJZWyNK5odEpQGlbu4VAUQaK\nIFTOdw8HJYNBxcGwoirtdVWWVNWAUJjAQKZElt6bcrlatV5t7Hjc0QtrBKUoCo9RBAaDgTcKLt3A\n+zU/NDEtAQ9SBooi2O8f1tkgOajcetiex75cLJnNZkwmU6YTU0Hc1Zs2ozfaPXqcAtLhZttX6sZb\nrUybEAnRjJaEgJTmaWuwCj9CQqXwnoWe0ual2qlpSLlbTL0ySqNjvHdz1CeyQeqaOhvs5ZJ6uWx5\n7Nqf1bvQ4M+tvGzSVulEPJUty2enpM65myFvPBOiabqNclNb+HPS006t5sb66okLObX6KrJOlRPE\nu6pDKIwaqaqSqiqo3HAPBxXD1nAPqEqjK8T1s+vGVg6WuthQZ/6/0+wgxoasK1D66q8sSqrKPPgQ\nJFdQ2WpKhCIUVIOB8fU5i6Sj8qfkDvQeePQipax+OJ1MGY/GjEcTZrMZqx26Oxm90e7R4xSQIOsC\njbb4JXuVHoxDSCFajV4wjWeCKc1JSkiZ0FDYfkm9jVez+WhqUl2TViuiP9qMj2zIneqIbqxbw+1e\ndOO6H7paQVMjTUPhHiVBkFCiRUC1Inpec1lHQhORJqF1NKGvlkrIwTyvdMyGO2mbVWJ6IE6ddAz1\nRtk3uNetCJauZwWToa32zDtJshtIiBbYXdU1ZWkUyXJlNEm5KFp+uywrzyixHPGcObJc1URfUeRg\nJLlIqWmsYlVMeTDTJKXfIIoiUBbGtQ8HQ/TQgtFlURitM7BHWVaEwgOirhbYxNj2yVwsrPR/Op0x\nGU8YHY8YHY+ZTqcsdojQZfRGu0ePU0BD7ibj5qfbgcb5XlVBJba6FRoEDRBRM5oxIkVpkqGAxgSt\nwa6hqaGu0XqFrlbocklcLomrpXvOq7UHXRtn3SyXnYa7dUu5kBKiiTIlgiplEKSobGnfxkSkLUap\n6kSxagirBpWaqDXL2gN6OQujbta8tTo94kYqFwCZd21BV9XUGmm7JOvGDnlbzuVujXcuViEnz/lq\nJkJUC9o2MbBqVpRFoCqtE7t1wAl+A6DNyGmaSO1Vj8mPHYxrVldmFBFLUURtrDJQusGuSusKf/78\nOVD11mjm3Q8GFpwMZYlIIKpVxprBNi9/4R72bDozL3s8ZnQ04tLFS0wmTwKjfXSCnzmnOyrrLm1W\n1tU7tNcuPPNZW9vkaDvI2Hx1M6D40Gc/t7XPow8+uLXtcLD9pX/+Wc/Y2jZ84aYE6h9+bnusz330\n01vbjkbb592kzYBDZJvL0h0/U0g7ijJ2ZAk98s0TQdNvbldN7tLASDtKsoodgnjFicP44Ac+sLXP\ny1/xiq1tw8PtQPP/PREIvvtjH9/a513v+P2tbU8kGjfY5Mq3rLRncnJuuMUMsq+a1Y1UoUoRE2EQ\nTdfCvW3L/W2QWCOxAX9I03SM95K0WBDnC5qFVQeuFkvq+ZymQ39obLzSLgJeGAK2rC9DmzNeBDNw\n5hkKDcJqFanqSFgs0bCiUWFRe85xssDkqjZDlNTy07VV2VtXcbY0iHRe+w1MYMOTBhOQylkfmZo5\nqbpiNEoiakJiTpcUxHscFN6NPeSceB8/V0F2tUdSStbcIN9cvHNQ/o4cAC2K0PLpw+GA8xcuUNe1\nZcIEIRQlRVlSlvYcirK9Cce0LstfLBZGicxmTKYTxqMxo+Mxx0dHHF06YjKeMp9vJzdk9J52jx6n\nwKIxekHUPFfjgtPaiCdFk1jATdVqaUQszc9F/IsUCVVDKEpLCUwKTeMURo3EmhAbQqzt0dRIXcPK\njfdyQVwsiLM5cbGgWVogK9XmrYPV5AU3PEGEUBZuWIIZmmpAWZmOhoaCOiqLVQPLmkaFZYSwsoBc\nUlojVDeWPmfdYtZl2pDNq24b7HZVkmu+xb1pCFJ4wZFQrNl0C/R2DKm2n7XxY0qdKktB6qallCWP\n36FaUu404LnWufTdvP5kGUGazBGq67aXQQhQloHDgwPOX7hgnXd8pbGhD6Pef1KhaaJVki6XzBcL\nZvN5S4mMR2NGoxHHR0ccH484PjpmMp6yOI3RFpEh8CFwMTN4h6r+kojcBPwO8DxMKP4Nl2t+2qPH\nkxH7mNuT2ZyAaWmXohu62m6r3IgLREj+16+iJHX5zxQp4gAtSzNaqIlLNWasi+hl227gNx4xukGP\nhNQgKRpPHiMSG7+hqOU0B6EMgaIyb7AsS4qqovAAW1ENkBBICBKVRgVZxZZWaGL0SsiGlfPj9uyc\ntmZNkUx1tMmPLSXS9awzLZJzl90yW29HbeWXOivB7mvDmhe3m4J9wfp7ffgTnyH3JPDRsnefZUM6\n6YhqK4dV3RBkaSmGZcnh4ZTpZGrGdzrj3GzG4ODAvGsJVNGaCCfVVgJgNp8zm82YTqeMJ2NG4xHj\n8YjReMRoNGI8GjEZj5mMJqejR1R1KSKvU9WZiBTAR0Xk3cBPAu9T1X8hIr8A/FPgLVcar0ePJwv2\nMbcvXTyiCMKgKDioCoZVwbCwZrPBqRAR6webnKZIjQcrvbkuTUSrmrKswFPdRBMhRmznxrw+D9Gp\n+CMoqQAtBAqQIiBVQYiBUgtSENBEwPjqsizsMbBc43JgBrsoK0Jl9ExSqJOiTd0a6dliyXRmy/nZ\nbM5itbR0Od8nNrlnzjoPpPV63TPGPVjNhlx89dF62s5Wq5WnI6H1xLPRtSwSL8rR5J+x/9Ec4HSD\na9+7vjnksde/fX5lNwLz8p07l2DjY4VOkpRGEytpKFc1s9mCyWTGaDzh8OIRg+EhoShporJc1pyb\nL6gOhhRFgYpVVC6WS/ewJ2awj48ZHR9z6dIlji4dMR4dMxmPmM2m1vx4vl2vkXFV9IhqS0IP/TMK\n/Bjwl3z7bwIf5DIT+3f/550b73/6R39oa5/DweahTL6y3ZorXNwutnj6+W3VuuKGTaL14Htv29rn\n+OnbnOrBwcHWtnNP3+a077rvixvv//cffmxrn8eOthXqVLYv90nuOO0iptn+ARPbBUp6wgsB7A+g\ngyIMt/YJVDu+cwd2qCymuMnJ3/+lr23t8/Zf/42tbS99+XZz3mK4eX3+4M53b+3z9T/98hUP8/Hg\ntHP7sUcvUZWBw2FFPBgih0PKgyGFlAjinL+2VkJT8mV6bAONEhtoKqQsoShbfeaglt8tKZrOBgrB\nRJakBMqAVIEQSwotKRlSitIIxKqy3yanpBVWCl66sa6qAdVgQPAMB0JhTIA3x62TMl81TGdzxpMJ\no8mE0XjCdLZgNnd9Eve2136thwiVdou2Bjp2M+A6M9U1Osw3pzXc0vWVc562vUt+A7PfL8LG35C0\nxrf1ytsmup462Koq5uesm+qGu/OXlFcDlhFjRrkIJdPpnOPjCVV1RFENiAnmyxWT2Yxz588zPDyg\nrCpbuahSNzXzxYLpbMp4POLo+IijoyOOji5yfHxsXvZkzHw2c8rllCl/IhKAPwK+D3i7qn5CRG5T\n1YftwulDInLr1YzVo8eTCaed24899k2GVcmFc4fIDYkqBIZVBaUFwVSzQbIcQOvaEk2zQoAYiE0D\npRltKUrzmL2SLqj1EAwkghvsUAhSBsKgoNCSgkQZlKoIDKrC87Qb9+yVIBAK87Ity2FANRgah13a\ncj6qGeyUGlZxxWK5YjqbM5pMORqNuXQ04ngyYzZfMl/VrJrc2it70etc6uzlmnF2T5uct244+dqo\nfne2pEC1aXluEWmV78xwr28TIYvqAUJYW3aRjuEWhHUGihnn7Hm7/IB/Br9hBC/sobNKaA33qmE6\nX1KNJkiw/PrFsmY8nXLD6AbOXTjPweEB1XBged5BiMkqH6ezGePJmOOjS1y6eJFLly4xOh4xHlt+\n9nK5sAyg5pTFNWpX/WUi8jTgnSLyF9i8vbHjfY8eT3qcdm5f/OYRhwdWvjwoCs4dHBilKgEJpUl3\nBkWjGynvO5hSNEMgplMisSHFiujVklk7Q8Q6vAdxOqAAKQXRgkBBoKIIUJWBuiysK81gYBxzND46\niFiVYbCuMGVVUQ4GRseEkgSsmsgyrahjYrFqmC6WTOYLjscTf4yZzBbMFitWMbpWSl4phtarzRy1\nOMUAtMawexE7REWnzDt7zznNrwExT7VbCr4e0vYPnYKc1kibRmv7PgctM8yDdp9foPX9JdM73sh3\nc03gBTqRxWLFuJiREJqoLBYrptMZ48mUc+cPOTx/zop7hjlX27Jt5ou5cdjHx2sPe2we9ioHkGM8\nebgbeFzZI6o6EpEPAq8HHs4eiYg8C3jkcp/70D2faV8/71nbVEWPHleLqM1OLZbT4tud2+//5Kct\nMHUw5I4XvYDXvvx2EgJSmNcsgiQlENecr0ZwThu8NZlnnUgsSGVJSgVSmqEFCzTTHmwAAA5KSURB\nVGYGUaNbCgENQGnSpAVOfQSapiQ2Vj5uNs059SCEULjHbVx2DprVMZFctnS+qs1gzxYcj6eMZ3Om\n8wVTl2ddrmoaJxDUPdtc+RmkaL3XbG9Sh+roeuB+1dtn84rteGm57+z5bnrpa746kzJulEVY30DM\nuxZPH/Ry1HZ/o0k2iRo7EjfVHU7djqGwFMNo31vXkdls7mJUpmcyXy45nE45d/4ch+cOGQwra6BQ\nliZBmxKL5YLpdMLR0TGT8YRJ9rAXS+aLOcvlok2TvByuJnvkFqBW1WMROQR+BPgV4PeBvwW8DXgj\n8HuXG+O1t7/kSl/To8dVoZCSohMbqOPlAzZXwj7m9ste8ALOnTvg5hufxq233kISQYNx01KU5i2n\n1PEBrdWYpOyZmhFPUc2se6BOPO3MDI9lKiPOZxdCgcmPGl0SiGWkaApKLyFPUVnH/MTyscXysi3V\nr4IQiCporFk1ifmyYTxbcDSacOl4zGgyZTwxo71cmXhUFG+IizPY2cPNPHL2jMGDian1lDv1jxve\nteqmt732jjMvHnJax0aAMfhnciUlKp6TbS3MssqfXYOi/VxbJq8gIez4fusx6ebdt6vdlPyG1TTR\naZNFW2E5Xyw4nB8ymU4ZHgwZHgypBhWDQdWef93Ulj0yHjGdTJnP5qwWK5q6IVBwUJ1Dvd3ajN3J\neFfjaT8b+E3n/gLwO6r6v0TkY8D/EJG/A3wZeMPlBnh0vkmqpxtu3tpnWGze8aSZbO0znm0rzxXV\ndkBucONmQPHZF56ztc8tt+0I5On25fj6xe2CmDs/tBlEe3hn0HE7aLcrUJhOdPDcdX8V3RV03OVt\n7uqCshl4DLoj6LgjQLqVJ8V6aboxXhhsvK93HNZH7/rE1rZ7dxQ83XzLTRvvH3tsO/B8/mCzDd10\neqos01PP7TopdVIaXzonsTxnysp4ahEkuNGWbLQjaPCCjnXpu6U3m2cqxj0gYrKkNnUsz1sKM5JF\nARIFSYEQC4oyd0PRtdHGSQMxtTsR8ZtJYaHNJtEkWNbG047GU46Op1w6njCazJkulsyXxmE3qsTs\nNW/QDh1OmE2POnvYWYp1zU93PeWcDbIOFm7SJtHH7VAufr1DVtFzQ5ynqGDCXRK6f3OdXOzWk7fD\nSKq+75rrzveNVnfFbxyoUSKK8fqrZl3lOJvPW2M9HJpkazWw9ErECpAWizmTqRXQLJcrmtpu2tbg\nWPw3DuzINQCuLuXvPuCOHdsvAj98pc9nfP2RR/iuW69drPLu+77AX3zxi67Z+Pfe/wAvfeELrtn4\nSRvCLuO5j7FpCNewjirqkkK2s1L2hbpZUZWDK+/4OLGPuR0FvvroY9x0802kUKBFgRYlWpQmNZv1\nRdQ8U9ESUe8TWVhAktTpHa5KVExjI5nh+ORn7+cHXvLnjG8Vo0bE8glNcN8F9ZO3q9KO0TaTleVB\nvbuKWCoayTjpT37hfp5zyzOZzOaMp3OOxhOOx1NG4ymz+ZJl3dAk3cgSEQnu3ZrnmdPmNBtd57ET\nDUU797qVjV3jvnZnsvHuYm3I82c6118bAtUGJWJctlegps5ndP2d2SLnYxXwBg52nDlQGakpw2DN\n2OcqG3KDBeOfJdQUqyVlWVLN59a8oSpNr2RQeXOGgpSSNZhYLlgsFsymU4pQWcohRu8UZbBjuYzR\n/tYN6vaIrz+67TXtEx8/kYa3b9z7wAPXdPy003Pe19iXF1TfB6JePj1pH2jitR3/NEjA1x59FIKp\n9mkoWr1snCaxR95uFIXk7iYSUK8lSZjxjl6eHTUSNXHXZz5vXdex/UzcSSxgWRaEqiAMSiuaGVSW\n0pdFiwYDe66yQH/pQU4z3EmVe+5/gGXdWDBttmAynTOZzpktlixW1qzXVgPdIKGdv0joZGJAGwRs\nr0/TerFZKgphwzCvlfxOGmxvz9UVmWoLduz7os/trEWYDfXmqlDWN61urrafT26V1i3cyftFVu05\nibeOMy9/XQpfu/74crFkPpub+NNoxPHxyDJDvEx9dDxyDnvOcrFsVf5SkwjOv5dFQRDr+H459GXs\nPXqcAu4ou7hRsACdUxEET0ETrFtNcoPWbl8vwXGPMyGI5k42gZAzKrKPmz+DFe+0lICXyGsy7luD\nxztbD9S8bPFuMrg3r87aRm96u1pZp/XcXqyurQdlk9YFNHgqnVEfJy5I5736P6aEqB1v3/U+6BTf\n+BnqiQBc14hnSiMb1y4tsn0Q+ebhvHe76sgG3JYF2uZ7d/n29TjC+qbSnrOPH5MSaUhEuzElCMlS\nCIuV9awcDAbWrsw76iB27rn5Qi77t85HJmoVfKVwOfRGu0ePUyDzr+2/mfyUzYd0jTTbZqY1GJnv\n9cdJ+dIM6Y7Vcq9uhNtAYR54bbzafxPrY1VvXeieYxPXSnjRjTVOUWSqYU1ntEfUXo+T9Eb3OrUf\n9ISOPMDaeK9fb3DP0BrhnH+9SZlIZ791rviuq93+Zq3B747TuTn6tVG17Js2EJob+uaVEV6tqvkW\nEEgasCSnVbtC0LIirx5yp5wc00iqFLLm6Lev4BqyK7i0T4jItf2CHk95qOq3muPXDP3c7nGtsWtu\nX3Oj3aNHjx499ofrFojs0aNHjx6nR2+0e/To0eMM4boYbRF5vYh8QUTud6nLfY//oIjcKyKfFpHt\ndiePf7zfEJGHReQznW03ich7ROSLInKniNy4x7HfKiJfFZFP+eP1pzj254rIB0TkcyJyn4j8wz0f\n/8nx/8G+zkFEhiJyt/+O94nIW/d57PtGP6+vavy9zO2zPK99nP3N7XW3hWvzwG4MX8IE5SvgHuBF\ne/6O/wfctMfxXg3cDnyms+1twD/x178A/Moex34r8I/2dOzPAm731xeALwIv2uPxX278vZwDcM6f\nC+BjwCv3dex7nnP9vL668fc1L870vPZx9zK3r4en/UrgAVX9sqrWwG9jesX7hJUS7Qmq+hHgZM38\nj2Hayvjzj+9xbNjOAvu2oKoPqeo9/noCfB54Lvs7/l3jZ52AU5+DXl7f+tTHvmf08/rqxof9zIsz\nPa993L3M7ethtJ8D/Gnn/VdZX4x9QYH3isgnROTv7nnsjFu1o7EM7Lsm/+dF5B4R+ff7Wv6LyJ/B\nPJ+PAbft+/g749/tm059DiISROTTwEPAe1X1E9fi2PeAfl5fPfY6t8/ivPZx9zK3v1MCka9S1TuA\nvwr8nIi8+jp85z5zJX8d+F5VvR37Qf/VaQcUkQvAO4A3uedw8nhPdfw7xt/LOahqUtWXYV7UK+Wp\nrd1+1uc17Hlun9V5Dfub29fDaH8N+O7O++f6tr1BVb/hz48C78SWrvvGwyJyG4BcQWP58UJVH1Un\ntYB/B7ziNOOJSIlNvP+sqllWdG/Hv2v8fZ+Dqo6wNl+tvrV/916v/SnQz+urwD7nxXfCvPYxTzW3\nr4fR/gTwfBF5nogMgL+O6RXvBSJyzu+OiMh54K8An93H0GxyWVljGa6gsfx4x/YfK+MnOP3x/wfg\nj1X133S27fP4t8bfxzmIyC15+SlrfevPs99j3xf6eX0V4+95bp/Jee3j7G9u7yMqehVR09dj0dgH\ngLfseezvwSL3nwbu28f4wH8Dvo511P0K8LeBm4D3+Xm8B3j6Hsf+LeAzfh6/i/Fc3+6xvwoTdczX\n5FN+/W/e0/FfbvxTn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HIs3gUT6IUGsDcUM6HHDjxk0QZzAnqNp33gC/QZuxVSLof1sVXFzeZcBX1f+diB4C8F/A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\nL9YBAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97755c42b0>"
+       "<matplotlib.figure.Figure at 0x7ff1f0126240>"
       ]
      },
      "metadata": {},
@@ -2047,7 +2077,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2055,9 +2085,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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RYE2OhCt9B0VRkM1mQ8IomUxKy70lH6EI8nFShU8/0HcMgiCkfco67LlcDhcv\nXuQgGGmSjuMgnU6Prf3ous6RbxJQMmAYRqhpHp2RRqPBxRfjtPMlbV/sEjpJ9NPEyS97UshIc7t8\n+TJ838ejR4/gOA5bEa1Wi/dptVqFYRhD5cBxz/tIIep5HlqtFqd+kMZjmiZarRYvmihAaeGp4J+C\nS9Rps1arSXEsLywscJUUOdvphqaqkFGgqpUgCFiQyXA9UMXSIJBbhMZeq9Xgum6oYiUKUbOdJHzf\nP3JBUokqaU/RdCaqAKLvImrKMru/LiwsIJ1Oc3kqFYeIgYZRUBSFA4uqqkqxmgBwMJHGRBkiVO2V\nSqW4pBoYfvlEcyJl47TrJ8tFcvXqVczOzsI0TZYDrVYLrusik8lwkHOSGDkT1PmuWCxibm6Oy+ao\nwydBHFyv14NpmojH45yWQ2lD6XQatm1jfX19ol8EONxIiUQChmHwIpMvljTmcUA3u6qqXJY5aYgC\nlAS9WJNMuYye50HX9RP1054ULMs6cpHE4/FQdF70e1KWQxRnkWRPAo+i1s1mk8uOj+OHoxJVz/Ok\n+XA7nQ7nVJMAzGazKBQKKJfLSKVSQzX9s4KMEm1ZaW5U7Sem4sViMVZIZFTMjX110aDE265cLofS\nnCjoQbyHwPPkZSLLoFQMWSYSjYOCMrlcDvF4HK1W68S+TdmVFpSbqus6HyAA7Eve2dk54hSXGfDo\nNz7y1YkgZhxicqK/GXTo6XKS6b8lMg7yIZumCcdxTuzqoKR8WaAAHUFVVVy+fBn5fB7b29tHUqBe\nJJzmUpSV5qYoSt+iFNd1mcFp0hi7Ykn80jTIlZUVbG1t4d69e6HXWJaFZDKJzc1NTlalqgqq9ZV1\nu0ZNGgrOJBIJ2LY9dvXCsPeUiYWFBei6jq2tLX5sZWUFlUoFm5ubLEzpcurHhzpp0KXU79BEiRxE\n8ofzyAeNjpHYxzzPw6NHj070nrJYp6g0OnpBxuNxXL9+HcvLy3j8+DE+/vhjfPzxx1LGMA4GCcvT\nEFbLPP9R5YJKOmu1Gvb39ydekDC2dLAsi2/MTqfDwujOnTu4fv06/v3f/x3Pnj3Ds2fPAByaU5cu\nXYLnedjc3GQXgGVZ7OyXgX6LQ+YlmfrHhexytUajEVpYqvj66U9/yoG91dVVXLp0CbquY39/n+eP\nzFZixJcBylKI3uJiqkqlUkGtVuN0nfNKrO+3/slkEpcvX0YymcQHH3yAYrF4rPeUZXqS37VSqYTm\nluZseXkaj8juAAAgAElEQVQZKysrODg4wMHBAZ+ts8YgQUnWB+E48yTLtUOKRRTz8/O4cuUKyuXy\niS/TgZ856g/oYBJFHPCcgf3hw4dYWVlBMpnEd7/7XfzoRz/iv11YWIBlWZiZmcHMzAxv3Lm5OWb4\nkYFBWsM4+V6DcJrXjoN+Pqfl5WUkk8kjpgkxzdAmpCCNbI5OsiJE/6BIkRcEAQtQYss5Sw2eQJd1\nP1y4cAGGYaBYLLL/Vsx9HQRZlyilUtVqNVSrVQ4MUlA2Fovh8uXLPI9E3H3W8zrI9UbuGcoYOU6G\ngMx0LAomRX3Zpmnizp07+OlPf4pPPvkEAPC7v/u7p/7MkUKUkneJgMSyLHbOXrlyBevr67h8+TJ0\nXcdXv/pVAODIbKFQQK/Xw/LycigwEiVLnSRk+NtkOvZ3d3exvLwM4PBQ7e/vo9Fo4ObNm0cuGrHv\nEh1+Ssrut2kmCUVR0Gg0Qjmp0aRv0kRIOxHpBAliDq8MjLpMhvGxDoIs+r5qtcqmfLPZDGVXkB/W\nMAysrKwAOD/OAcoU0TTtyB6jopRisQjLssaeW9mX/rAz+7WvfQ2PHz8GcFgquri4eKozPlLiNJtN\n/PCHP8Tbb7/NNb1EdgAcHqTPP/8cN27c4BuImGkWFhbQarWwsbGBvb09pFIpvPrqq4jH43j48OGJ\nB/1/Af/xH/+B73znOyxAgcOL6uLFiwNfE9VYSSuhfNadnR1p46W0H3GziUI0kUgcuRhJM4nyuMq6\nlKrVKgqFAi5fvjxR7XHS5h8hk8mgUqlwapOoRbfbba64EQWX4zjM3ESCttvtotlscpBv0iiXy2g0\nGkgkElhYWAhdKtRehYg/KCdznPeUBaKVHAbqBjEJjBSib731FrrdLj7++GPMzs7i4sWLLEDJ3ADC\npp0I0zSxurrK9GnlchnxePzcyXnPG2+//TYfmoODA9RqNczPz6PT6aBSqbADnFqWmKbJfJee52F3\ndxf1eh3ZbBbz8/MwTRMXLlyQMtZms4mtrS1mxKGuBp7ncR8lUYDath2i6ZuZmUEQHHYJ7Xa7UBRF\nSspWLpeTUvZ469atib8ncDhequQTCyqoVUn0IhCFk2hi67o+llvipEgkEnj69CmTCJH2KbImkeJk\n2zanvVmWFdI4m80mFzCcV4sYGVCGOXin/bHDeFnG+rKME5iOVRZelrG+LOMEBo91qBCdYooppphi\nOKZUeFNMMcUUp8BUiE4xxRRTnAJTITrFFFNMcQoMjc5PHeBhvCxjfVnGCUzHKgsvy1hflnECg8c6\nUhOl5Gj6oWZqtm0feU78IT4/akq3tbWFjY0NOI6DUqmEf/u3f5v4l6QUjEHjGTZe4hHd3d3FJ598\ngl//+tc4ODhgPsJJo9/nExnFqHH2+25i7yXZ4zzJD3UboN//8R//ceJjPTg44I4K1Ayt3W6jVquh\nWCzi8ePH3IeLSilHjZv2+aTx8OFD7iZLZDL0mYVCAYVCAffv38dvfvMbbG5uYnNzE6VSaeQ+ltG7\n7Cc/+Qm/f71eRxAE2N7eRqvVQhAE+PWvf81nr1arsYzo97O3t8f/nzSoaSMl/9PnfP755/z/zz77\nLLTuv/nNb7C+vj5wvPfu3RvZrO5Y5T3U5xoYzk5OFTTBb/PdiMCCKOlarZaUpGDf9wfmn42TAKwo\nCpaWlrC0tBR6XFajsiharRbnBjabzb48lsRGRW0h6vU6yuUylpeXMTs7eybjHATKXSSBMKyCSgZ5\ncBAE6PV6oXxl4nmo1+t8QYktsovFInMDNJtN7kFPBN2yslfoHInNEDOZDIrFInOYkmCinOparYb1\n9XXs7u7Ctm2sra3hwoULuHTpEr+vjHxRca1obuv1OpaXl5mZjR6n8nBFUVAoFGCaJu/LZrOJSqWC\nxcXFiY8ROMxnpfkUa/pprTudDmzbxs2bN/m5dDrN80ddbR3H4Txm6nAwDMcSoiQUgeH1xMT4Iybi\nAuB2HYCc8kxxnNVqdWJtM2SR8kZBnR6Bo/NLm4MuIBJQqVSKHz9vUMI9MTiJQjTKPyuj7DORSEBV\n1VDfeNu2US6XQ22wqd88cFgBVKlUuP10EASctN+Pu2BSSCaTzK9LbbmJ5JoYx4i/l8hmlpaWsLKy\ngtu3b6NareLp06d4/PgxCoUCrly5MlYri5NAXEcS6NVqlWknRSFDpaGkcInFD/2q2iaJTqfDrX1E\nZiyqAvzlL3/J/6cSWrFC0Pd92LYdGiNxIg/DsSTMuBufStWoIofaLVAZIGkqkwZ9WWqp4bouUqkU\nN5+TzcZ0WpCWBBzV1Gi+qLcNlXo2m01mqDpv0PyTW4LIUYIgwM7ODhRF4Qo3GaCqmejcJZNJxGIx\ndDqdI61Out0uP5bL5ViDNgxDKmerbdtcnkhrCRweWtqvNJ/RtSWSbtKWfN9HvV5n4vRJI8reFeU/\npXLkIAi4LxU9J36PTqczNjH6SVCr1fj7i4Jf13XYtg1VVbnMmr4DXQDUkymZTLLSdO/evbGUsGNr\nouPWPUcXnm4wIjKQTShMqj1wOq1XNrGHiGG0cUSb1u12oaoqa6ZkpspixToORBOVOlYC4J5Q4o0u\nY/3b7Tbi8TjPEV081FM+kUjAsiwmDgee90Cn8ZimyVprt9uV0hoGeM7gpOs6W02i8DyOsKEODLIg\ndqzQNA2NRiN0pujSEi1VVVW5RQdhkItqUhAVM/Ei3dragu/7eOONNwAclp5HtXbLstBoNELyTVGU\nELfFIEjRRPuB2v6SOSqbZzIIAu6tQxNar9fhOA4Mw+BNGt2s5M+hxZfNai9iWBsGXddZmFPrEADc\nR4hMkRcBhmEc6blEWgpBhjlPe0pRFK7rppYxxCVLnyvuP9GfJ4L6dcmAaBU5jsN0hv3qykkTHNZZ\nVTZEAen7fsiv2a/rBXB0HyiKwrwLMkBnudPpsLD+1a9+BQDcGDMajyESH3IDiJeD53ljcXxIyxMl\nJ3+73YbjOOw8J21Wtg+PDoS46aiFbrvdRrVa5R8RUW5OmTR40YtkVLAlFouFiKWpkZphGGzSvSgQ\nvxuxEYnfT+blRM0QgeddFoi8mkC8k/QYaTG+76PVajFdo+zAErmcTNNEu93uKyRp7trtNjzPC/lp\naZ5lkZzT57uuy5adpmkcLOp2uwNdSVELUFVVqeueTCbRbrdDn/vjH/+YCWT29va40yeR59D57nQ6\nIdIXYtcCRhNISxeiZKKIvU+IyHXS6KfdigfH932m7qKNKZrJZw1KazoOxG6mpDHTJpZleh4X0YvH\n9/0jjD4yQG4iajlMrVPGObi+78PzPLiui1arBdu2uWOozH5AtBcbjUYolUbMdCBYlsX9rKjJHfD8\nkMtaf5pXUfGhPdevZxFlNYj7oNVq8e9n0V8NAL7//e9zsJHGRVYbtdehv40K+GazyVrzqLQxeSHy\n30I0sQgkuCaNUSYisexXq1VW/cmRT11BPc/jDouyes4TPv/8c+i6jpWVlRP5XelAGYbBlHQvAqix\nHfD8QInRcPH5SWJ3d5ebItJnjyNAqXkeuUk6nQ4ajUaoX9Sk8eDBA8zOznIbX0VRUKvV0Gw2uZUy\npQOS0CHtr1975EQiIU3YkzXZ6/WQSCTYVKa8TDGYBPS33iiAR/+XcaGKrrtWq4V6vY4//dM/BQDs\n7OwwVWSxWDzSXjw6HkVR+G+iPbCiOJUQHdU/nLQlSikhNZpug/NCLpdj/yG1JKZgQzKZPLMovm3b\n7A9bW1sDANZ8xnHAk2uCNAUZh71fYG1YCw4AHNgBnmcc0MFyHIdzICeNjz/+mCPt2WwWuVwOvu9z\n+woSPqTJDwLlNtPfy7hI7969y1y7c3Nz0HUdS0tLME0T1WqVNel8Ph/SNKMCS4SsbgFEdE0s8HQx\nVSoVzM/Pc4+v6J7odrss1LrdLvsXZVkkrVaLP++DDz7A1atXOW+WznS9XkcymeQ1dV2XFSrxO8zO\nzo4dkD6xEO31emg2mwOTe8X2uDQY8ktRDt+kcf/+fdy4cWOsv6XJKpfLnOt2lgIUOGye5bpuaA6p\nImQcIUoHfVAnzknAtu0jQpT8eIMgMuBHtSZKeZJhiaTTaTZ1yarwPI9zVIlBfpCwIYZ23/f5/3TB\nThp/9md/Bt/34bouNjc3kc/nOeWJIu2UtyqmvVHGAGlddJ6SySQcx5GS6nZwcIBEIoF8Ps9nmQJN\ntO9EwUgFD4MuH9d1pfSyp/e8f/8+arUavvWtbwE4FOC5XA7FYhG2bYfS7MS1Jb9oNIuAmkUOwomF\nqKht9EO/dhIA2NyScYhIm7Nte2RUjW4fYtyPQtSyZQmoYrHImjoQ7j1Vr9dHpi2JPdxN05SSPtLP\nRUCX4LD+8oNAvnEZ/rs7d+7ANE32L1qWBV3XeV41TUM8Hg+Z+fQ9yKVDY9R1ncsyZWhO0RYWdHnS\npUXBnN3dXT5n8/PzSCaTHCwj0LhlaXjkVhDPexAEsCwLnufB930W3uT7FFPMKFMmOl5Z6HQ6IUFp\n2zYsy4JhGMhms6HgHI2b0vKAo+4baeZ8v6TmfogKWoomy8oTpEZ6x8lp7QfRRJG16ORWoOR5WtyT\nlBvKSriPrh+V8550bimYJ6PGO5vNsrmbyWRCLgP6HuTvpCCOmFJEhSGUO0oRcRla0w9/+EN84xvf\n4N/pwhQ/a25uDplMhjMNqG6eNGoaN51DmZFvSv0jUFFCVNmgaiVxj5DfniCzlUkQBFhcXORLqlKp\nIJfL8UWZSCSO+MpJSNIYo5bXqPM/thCNHhwydUb5xwZBxq0pCp5BhzwaNKDWvnSjUjI2JVvLIvYA\nDtsi1+t15HI59tUlEgk2146DeDwuRYhGxyH2uT/JGtIYZURou90urx+Z5JT0TULnOMKfSldl+EQp\nsj4qAd0wjCNBEEBOsGsQyL0k7gXKEvE8j4WP6MKJQvQvyszSUBQlxCGhaRo3z0skEuw3pf3X6XSQ\nSCTYNdFut4+49CaS4hTVjCiIQX6nFwXi7RIEh420ognoFOSgHNFGo8HmiK7rTPBBmgj1sJY1XjEF\nI5lMIpVKwTAMji4eBzKEaD/tptPpnDpFTYYQoGTpZDLJUWTDMBCLxULpLONCVlAJeL5WUQE6rptL\ntqspCrE0Vfzc6Jk7T/Tzz1Iwm7qLUhUVBWVd1w2Vi/fLHOl3iYkYS4j6vh96Y1F7azabJ/JvytBE\nopooTcjBwUFImObzeVy+fBmXL1+GoigoFovodDrIZDLsCnBdl00VWQdJ9BsRyLeZSqXQ7Xaxubk5\ntlYqIzrbb53IfDzNGsq4fEVNKBaLsWun2+2iXC5LcSGcFIMuZsMwsLGxgbt37+Lp06d9XyfuZUVR\nuGxVphCLBi9JERFbH0cLAc4a9Nkiz4SmadxV9eOPP+bxWpYFy7KQz+fhOA67d6jYRrRCR8Umxjp1\nYtSSQNKbWHBs22Yt7kUBmXS6rqNcLuPRo0dHAhpLS0vIZrPY2dnB1tYWPM9jE67ZbKLZbEp1hPfz\nKycSCaTTaczMzODixYsj+QwJMoQ9+QdFkIASe6QfF7LG2g8UVLBtG9vb2yMDBWeBYVkgq6uruHXr\nFur1Ov77v/8bruvyvjVNE6lUCtVqlR+jskVZJj5ZZdGUH8oioHGITFkyaQQHgdyLlJUh7lvDMHDz\n5k08fPgQ+/v7oddRWXC1Wg2xzFHmw6h5HcsnShE3yvWi6KVpmnAcB47jcFUScOgkH2VanoXWREQd\nlIPX6XSwubmJcrmMK1euAAAWFxeRz+dhmia2t7fx+PFjmKaJfD6PWCyGZrMpVYOhG14UKuSPpedl\nkkuMAqXhiGYnjTUIAiYVBoYLhihk+8SjSKVSY9VBnxX65clG865ff/11AMCTJ08AHO4LijrTnvA8\nj01qGalYwPOUJQq6iXtVJPIgDU7MCz5rVKtVxGIxZDKZkPJD2QRf/vKXARxmxgCHPunFxUWYpolc\nLodut8vRfPL7ToQKz7btUN4XOWYp0t5sNkNClNIFhglKGXyiVGJKgr3ZbMK2bU5xocNerVb5Nrp8\n+TJWVlaQzWZx/fp1eJ6HUqkE13W5akQmqOooCpl8q8cFJciLEFOrKpXKsSPYMub1RRKSo9CPHWjQ\nml+9ehXAoSB4/PhxqDjjLAhySGDTuR8kVGTmK48DCgxRYImUoFardYSwnCjzVFVlKzqXy0HXdd5H\nlJEwypwf66SSf5A+1LKskKZEScAiDdYoyBASFAgiZnLLspDNZkP5fzMzM0zaCzyvp7VtG+12G8lk\nksvDCDLN+YODA1iWNVAItVotTsiXVZEyDI7jcJpPNPWDiLepa8FxNNEXUeCRT28cIt7TgjShfqD2\nFZRDTIdYURRcu3YN+/v7+MUvfoFarYb5+Xm8+uqrUnk6SYjatj3UwqzVaiFaPsdx4Hke710izJHF\n7fvRRx/h9u3bAA7TlsgF2W9uyAUVpcS7e/cu8vk8VlZWxg7ejSXJtra20Ov12OdAB57o7SgvjMxp\n8o1alhVKFWq320w9JePG+va3v413330Xd+7cwe/8zu/gxo0bmJ+fh6Io8DyPfWFUr0zfgXxK1WoV\nn3/+OZ48eYJyucyEDz/72c8mPlZCNOk6CtM0z4zPtB/m5+cHtl2h/L+THIhoC5YXAWdJe/gHf/AH\nA58bFQ1eXFyU1mKjH9566y0Aoy++qEAiXyNBdjXg6uoqr+He3h6WlpbQ7XaPWFFRfymVfnc6Hayt\nrSEWizGJeCqVGtl2ZywhKubdUWoTVXhQlJUSgIHnUWfypVCtMr1eVVVcv359/NkZEz/84Q8n/p4E\nGT4eui0TicREBCUlZU8SFIGdmZnh2m7gsMKGXDidTgeGYfBzUT9Sr9djTZ8EssyE65cBP//5z9k/\nRyWchUIBnucxeTTl44q0foqioF6vc109CVzXdbG3t8e+/kmiUChgYWEB+/v7mJubYxeUqqqcIkSV\nYWK1ElU5ZTIZToekfEwZJOLie2az2ZB1J3JAiHzGpPjt7+9jY2MDFy5cwOrqKi5cuADP81AoFEa6\nqpRhGqEybe0awssy1pdlnMB0rLLwsoz1ZRknMHisQ4XoFFNMMcUUw3H2kYoppphiiv9DmArRKaaY\nYopTYCpEp5hiiilOgaHR+akDPIyXZawvyziB6Vhl4WUZ68syTmDwWEdqoo8ePUIQBKhWq1wP2++n\n2WyiVCqhVCox5yT9HBwcoNFohB6TkY704YcfwnVdJrid1I9IsjApTHJ84s+kUSgU+L1t2+b/EzkD\nNXjzfR+NRgONRgOVSoVzh/v91Go1bG9vT3ystNeOO2ee56FWq+Hg4ADlchmNRgOe5yEIAmxvb+O9\n996b+FifPn2KWq3GzRMpJajT6TABzt7eHqeH2bbN43v48CHW19ePfA9ZHSPef/99uK6LYrF4ZP3p\np9PpYGNjg/eL67r47LPP8OGHHx45+7QHJo3PP/8cGxsbKBaLODg4QKFQQLlcZvkTHfO4P9R2eRBG\nClHK2h/VE0dMVI7WsIvEsgQZix0E4ZYFk8JZ0/2dR+fRYeg3n1Q9RZuzVCpxue2g1xDG4VY4KShX\nWfz8RqPBcxrlh6VcV9M0sbe3B9u2uZwZkNd7XiS3oLl0XZfPW7fbxcLCAhzHQblcRrlcxtzcHPL5\nPL7whS8c6chQqVSk1qsTbwblh0fXlyoE6buYpombN28il8vh3r17ePDgQejvZRBdi2srNiukTp4n\nrfgbJftGvistDHFtDgIl3PajjjMMA0EQbg8so+yTFpdo+iYF2SWAIqjMs9FoYG9vbywGJxkXEoHK\nOqmqIwrauEQ/R2w/1AuoWq1iY2MDT5484QR9QB5ZBl3WURZ2Gjv10CFUq1UmFr516xbm5+dDAl5s\n9TtJuK6LIAhCnLHiIe90OrwPopU//VAqlaRodzSuer3O5bBi/fzBwQFfnIqiHGFJu3btGq5cuQJV\nVfGrX/1qaLnraUF0gESBSeMkTtmTYtT6j5RkpFUSldigyhoqnwTQt1Z1cXExdAhlHCIyMwzD4NpY\n0pDFdqrHhcy65CjosnFdl+eeNBbiJ6CNQheWTA2E1pR6EwHPBSd9rqZpoZI/z/PY/CTtioQXsc/L\n6LEFgAW+aBmJe7ZUKoU6aFJpH3AogB88eADLskI12DI4C0gINZtNLiuk/atpGkzTRKvVgmEYfcsO\nieOXzpSMCkBCLpdDu93G+vo61tbWYJomr7/neUin0+zWoXJUsWne3NwcE34ACJEkTxK+73M1JRFq\na5p2qvM7TlfakUKUtM94PH6Eab1eryOVSnH517DbkkrCRPafSUMUKkRWSziN0D5LTdTzPO65RMz3\nRPBRrVaZ35RaAhM1oSyIWi7xJ4jzkc/nj7yGxh6tpSZQO2AZmJ+fPyJESdNst9vI5/NQVTWktTmO\nA8MwkEql8Nprr4Wei9ZZTwokiKgcmshz2u02E/qIPBVR9Os9LwvJZBKzs7P47LPPkMlkkM/noSgK\nyuUya6eFQgGJRILHHmW8f/r0KbNRySJ4IS5RKjclXuDTfJZISzkII4WoyGAUJSCgW9o0TSYxHQSx\nDQYgh+yBbmYy3ya1UDLN5Sg0TcPs7OyR+SGORKqzp4ZbiqJw3xgZG5OYcIikRQQJl+i6DxLq9D4n\nJS0ZBzRvVO8PHCoC6XSaP5M4Zgliozqq7W80GtxlYFxS7OPAMIxQS2bXdZnQ5eHDh4jFYkyGcd6g\nS311dRXlcpkvTmL48n0fuVwOpmmyG02cX0VRsLy8jFqtxpwJo4h3TgLi6qBe8md1yYz8FFGARNVi\ny7Lgui77w3q93sD2ANEvJGNz0IKKZuYkcJYsSqTFRUGUaDMzM6zxi/yuMrQlACHaQAAh0plms3ms\njRrtPy8L8Xg8JPiILxI4HLNhGEgmk0gmkyEfmm3bbE5TBFmc70mC+kHRWpOvsNVqYWNjg8mNXwTQ\nes/MzCAWi7EPNJlMolqtot1u81mLx+N9NU2ipZQJcnuJnTjO4uyeSFSTP0vUfgbR8g+CDD8jkTIT\ni8ykBMtZ3WjEZXlcaJom7cBFNdBOp8MX5XEjrCILfrSB4KQhkh6LDFPJZPJI2wgyqykwQcKVDqKM\nbAlVVTlg1O12eRwHBwfwPO9cuGMHQfz+iUSC3XqqqsJxHGSzWaaSHMdqk5l9Qn5lskonMY+jvtPI\nT4jeKL1ejyeR+gCRL4eCH+M0zZJxu5NDnlIazqtFwbgQtfaTtiDudrvStFDgqMZommYoZWgYgiBg\nR7/jOKzFBkFw6m6ho0DUbJ7nYWVlBZ1OB4VCAUD4UjQMgynnyE8JPE+LSqVSUnoyZTIZ1Ot1PHr0\nCNvb25ibm+O0p9XVVW4E9yKAcr+BwyARmeKdTgerq6vcilrXdZRKJTSbzSMWqSgPZFkh9Jmii3ES\nrrhR52vkt4m+AZnMYvQNQEhwDouEk6YoQ80WD7bsqPUkcHBwEDJ9jsuxSP2P4vG4NB/jw4cPkcvl\nOFhDLYmjKUQU/KLf6RKjcYn95qkbgmxQWxvKERw0v5QOQylyJHwpcCcjkgwc7tetrS34vo/Z2Vn0\nej3EYjHcvHkTpVKJzXoxsn0euHjxInZ2dtDtdvHKK6/A8zzU63WOxG9sbODp06e4ceMGgMOAM5Eh\nk8A8i7NIPKGGYXBAli7M43ZeOA5eHJthiimmmOIlxEhNNGp2kdM9qklYlhVKdBbzCEWQJiqjCki2\niThJkPsDONRITlLBoaoqNE1jU0vGTVsqlXD//n0kk0keYzqd5vUjLQ54nr0xzC1BHSFltoog/3w8\nHud9SpVH/awkcR3IPeW6Lmq1GmZnZ6VVV62srCAIAuzu7mJvbw/pdBrJZBKapnFe7sbGBq/vxYsX\npYxjFCgHtVwuY3NzE/F4HAcHB6yJrq6u4unTp7h37x5mZ2exuLjYdw/UajUEQSCte+3Vq1dRqVQQ\nBAFM0+T4wmnLYUe5H0Zqoo8fPw79Tn7H6EYks5T8I4PUd4r2lkqlUR99bMhIRZGFvb091Ov1kB+H\ncJwcSjJVZeVd3rhxA7du3cLMzAxvRvLdqaqKZDKJbDaLTCbTt0SSar+bzSab+5qmSTOR6f13d3dR\nqVT4IInzLFbVkLBNJBJIp9Oh8lDg0DVBnTVl4OLFi3j99dcxNzeH+fl5FuLA83be5+2aeueddwAc\nRucvXboERVFw4cKF0J67cuUKgiDo68elucxms1IrljKZDNbW1nDp0qWQu1DMTz8JRvWWGilEHz58\nGPp9WNoApTdQkuvAD1VVVCqVUR/9fxrLy8vo9Xo8DzSnrVaLfXLDIAo0mQ3WSGvIZrNYWFjgnj7U\nUZWgKAqnuLmuyy2rqYOqZVmsffq+L03oA+BgFmmQtm2z4IxWsIg11dVqlStvcrkcstksyuUyB6Rk\ngLTyXC7H4xA7Ys7OzsKyLFiWxT25zhr/+Z//GTqvqVQKMzMzR+TAnTt3sLKygu3tbRSLRXS7XTSb\nzVBgbnZ2Fjs7O1LHG73IT5twPyo1a6R4jkZh6eD2w3Ha4MrQRGWZCTIQi8WwtLTEgRYyi6m0c5S5\nG825lKWpbGxsHOk+SWWfhmEwY1dU8JumCcMwWGCJ49M0TXrL5CtXrqDT6aDRaCCVSh0RPhQwpXQi\nRVEwOzsLTdPQbrdhmiavzebmprRx9tOQut0uGo0G4vE48vl8qBX5eWikv//7v498Ps9a+7D0xGw2\nG+rVTqWrFNjJ5/PctO5lwSglZeyyT0IsFjuWf4HMviiiRAWTgCzflSyQcKJ8ROpIeFzzTVEUKaw4\nwPNEa9HHbRgGl0qSNnLcvF8Z3R4JpE1SiguZc9VqlS9akRPA8zweP/mqfd/nAhIZdf7dbpeJWsgF\nRtB1HYlEAvv7+4jH40ei82LnyrMAKVLxeJznQ1zvWq0WsjQymQwqlQpM0+TLkvJuY7EYFhcXBxbl\nvIgYlWt67Og8mWvDcqcoVYS0Vvq/iBelGuNFQCwW4yDISfNFZYEOkHjIVVVFKpU6lbNepjlPrg4S\nUl/NStQAACAASURBVFRZZRjGEQtIVVVYlsWcBSTAKEUrHo9LufBpPml8USwtLWFtbQ337t3D3bt3\ncffuXT5zpmlKzQ2OQrRGKa1O1CSz2SwePnyIJ0+e8GP5fB6O47AbgNLaKBH+PPZ4lAZxUji2EKVB\nDAviEF0WRenPqvb8Rc8LHYVBJZ/niWFzqigKGo0GDg4OUKvVuNBCRL+kfDGiLwMUmaUsEsdxuJ/7\n7OwsbNs+4n4gM9XzPNaYJpWs3Q80rxToipL7AIfuqddeew337t3DvXv38D//8z88ZtKOzuJsiQoP\n+b4PDg5CY7516xY2NjbwX//1X/w4uUc2NjY4c0bTtLFIPWSAMlmOG4A+NZ8olVHxC8YgkCDtU2Q/\npxvoZcRZmx5E6fUiQFGUgaljpDVrmgbbtrG7u4vd3d1QSaeu60c4FShwIgt0SHVdR6fTYXOYvgcx\nX/W7ICzLYlIXcgPIuNhICBqGgW63O7AMdnZ2Ft/85jfxzW9+E5Zl4dGjR9jf3+f5PAvFQdyLuq4j\nl8shHo9jZ2cHH374IT/39ttv4/d+7/fw/vvv45e//CWCIEAmk8Hq6ips2w5ZATK5E4bBsiwmES+V\nSmNX3g3DWCxOog9E0zQmHSFOw06nc8QnRpRYojClHFNZCy9L2J21QKOLapA/+SxBa9ZvLJqmDSQM\nJiFGfxdFMpmUM+Dfgmr+ickpKghJoyM+TODQT08aKI2dsiUmjWaziWQyyZFrIs0grU88J+RXfOut\nt9BoNOA4DorFIlKplPR5BI5aE7FYDLlcDjMzM9jd3cU777yDr3/965ifn8f8/Dz++I//GFtbW/jo\no48wOzuLK1euYGFhAd1uF7VajavezguxWIznnegGh/n0Ty1EqdZZBDnjqayKyuuizm7aiFQqGovF\neGPI0ERkpX+clwZ93gIUOBQsJ9nwozQNWZrI7u4ulpeXkUwmOQBDJZ31eh2JRAKpVCokOElg0UGi\nnkCZTAamaUopu6Q9RdHrfD4fEqKDFA3Lso4EEV3XhW3bSCQSUoRTLBYLBbNIMYrFYrh48SIuXLiA\njz76KPT5Fy9exMWLF1Eul7G+vs58raZpHukuIAPihSii2WzCdV2+GDzPY0tpUMbIKCVq5E7e2NjA\n1tYWXnnlFX6sVquh0WhgZ2eHF7RarWJpaYn/hiLOlFjfarWQSCTYDSDDRKKWGvPz86wxi7Xavu+j\nUqkw+z3w3D9HdH4A+Hkip/jNb34z8bG+LCAiDNM0h0aExY1JJCVkGZAp5/s+J7UPImw+LUT2Jhov\nuRz6jb+fBhIVUjIO/D//8z/jL//yL0PpY9VqlRWTfuej1Wphf38fxWKR07BISJAweOuttyY+1m99\n61tHktdF60JVVbz55ps4ODjgmnW6EGZmZnitC4UCDg4OEIvFpJGrdDod7O/vw3Ec5m6gFEIx84IE\nIwW5KpUK0uk08vk8LMsKfb9TtwdZW1s7kmyazWY5OjtIDRad0ZcuXYLjOFzOBoQ3+6Rw7do16LqO\ner0Oy7JCnRRJoyZfGB1w0lKAwwUgxnBZkbyXDX/4h3841t9F94EoJOfn53HlypWJjqsfyuUyfN/H\n3NwcfN/nvkCUUF+r1Zg4R7zMiTbN8zw8ePAAvu8jn88jl8vBsix88sknEx9rv4M5Ks/ZNE2sra1h\ncXGRlQFZmrKIv//7v8c//dM/hR6LxWIoFAohzXh+fp5TtmKxGCqVCp48eQLXdXHjxg0sLCxgYWEB\nruvi3r17Ex9nq9XC1tYWisUiarUazzFdTJS1EaU3JEIk6labTCbZCozFYrh///7Qz1WGCYppf+ww\nXpaxvizjBKZjlYWXZawvyziBwWMdKkSnmGKKKaYYjvOPXEwxxRRTvMSYCtEppphiilNgKkSnmGKK\nKU6BodH5qQM8jJdlrC/LOIHpWGXhZRnryzJOYPBYxyr77PdDDNKjfkqlEv7lX/4F3/ve90KPEwv+\nhL9k6IcSqaM/VEvteR4KhQIeP36M9fV1lMvlvn//3nvvTXys77zzDp48eYKNjQ00m03uW+M4Dvb3\n97G+vo69vT04jjPWPMviKNjZ2Qm9f7Va5WR0mkv6/+bmJjY3N5ker9lsDl2TSYPet16v8/8pVa1W\nq2FjYwP7+/sD5+7Ro0dM0+a6Lp48eYJWqyWFLOXZs2fHWtcgCNBqtVAsFrG+vt53bmXuAVpTYqcP\nggBPnjxBEATodrs4ODjgx0UCInodrUMQBHj48CF+/vOfT3ycnuehVquFPsu2bVQqFZTLZWxvb/N+\ntW2bycLpbykl0nEc5oFot9sj5/TE5ny9XueNMAwzMzN48803oWkafvWrX/HjMuvR+zEPiSDaLsMw\nMDc3x21gHz9+jM8+++wI67qMKhDKTaXcNVosWkixFfV5gj6fcuuCIOD5ECnkHj9+DMdx4DgO933v\nx9Qlm0eyWq2GEtU///xz1Ot1ZDIZ1Gq1gWvZ7XaRyWSwu7vLiexUWSOjMOQk7xmPxzE7O4vV1dVQ\nqa3stjhEKAQ8P1tiyw3P80JrTcUJdJEC4bPYarWknKkgCJg0hgR3t9tFLpfjSjXar+Kl8+TJE3z2\n2WfY3t7G9vY2cy5UKpWxqhVPXHtnGAa3eo2WSzUajVALkVdffRWvvvpqaEAyhQNVcYyzURVFwdLS\nEpaWllAul7GxsYH3338fy8vLWFtbO9LZclKIxWKc2E+thA3DgG3baLVayOVySKfTfQWRzM6FUVBv\nccMwoOs6k+4Cz+f3ww8/xMHBAb75zW/y68RD8uDBAzx79gy2beM73/mOtLH6vh9KWPc8D41GA4uL\ni3jy5AlM0xx4eD/88EOUy2UsLCxgdXUVAPhfGZgkixFR48kqEyYeUeD5uMVuv77v814grg1SEjRN\nYzJnwmmZ5oeNE3hevZVIJLjsV+z26vs+yyzinaVzODMzg3q9Dl3Xkc/nWZsehrGFaKlUgqZpyOVy\nqNVqcF0Xq6urfQ95s9nEvXv3kM/n8YUvfIEfj/b7ftFAJWpf/OIXUa1Wkclk4DiOFAIS2lyJRIJ5\nLzudDjRNQzqdhmEYAzlXz3Lukskker0eX0zEuE4N5wqFAuLxeEiAkmZSr9exvr4O0zTxpS99Cfl8\nXupYo0JkY2MDFy9eRKFQgOM4eP311wEclqESXRuVJa+uruLLX/4yv3Z3d5fbc8jAKO0xCMYn6pHN\nsUAl0yJc12VBJLZA7/V6SCaTiMViaLfbLIDp+wS/rXKUYZHQRULnCXguWKNlqoR4PD7yshx14Y09\n+7Ozs2i1WizVU6kUa1Pil/B9H9lsFtevXw9pqNVqNeQHlcVsLlKKjaOKD+r3Qz1viDRBBoglnMoO\nXdflW/pFIB8BwNoygRi8dF1nFv7bt28DOORUqNVqaLVaqNVqME0Tr7/+Ol599VW+1envZIFMOCr/\nJBYqEqCe56FSqSCVSnHp8oULF3DhwgV+j263yyxJ54VhDd3q9Tp2dnbOrLttr9djflYSRtQDCkDI\n9UQ93wFw5wNVVVkR6XQ6SCQSUoSo53nsPugn+Gncx8UorflYJzWXyzHpyPz8fKglLfDczxCLxbjH\nDrGC53I55pyUCaqFBsabsH4CNLrAoxpVnQQkiIDnwsf3feawfFFanVB9NnDYoXRxcZHX/O7du3w4\nqO1zOp1GNptFPp8PaSfFYpE1KxnzSaA5JFb6zc3NEHmObdtYXFzksRJ9G6Hb7aJUKmFxcZG1GBmN\n6oZZE6Td9wNpRel0OrRHZLIikeJEzE0A+vYBoxr16GuB5xphEAQsCyYNuvCD4LD/V7FYDMkA6nAw\nDP1iPKM00bEa1Yl0UmKrBHLSEoOP2LeGeCbFASwvL/PtKas9hCjUx6FbSyQSaLVaoe/ZarW4S6Us\ngmRxwW3bRiwWYzNeVr+kk4AIJWzbDm2wn/zkJ0gmk7h16xaA4XNNvKMEmT2CxPV///33WQMFDi+r\neDyOdrvN+ziRSIR8zLquj3XYToth2k08Hh9oqem63vc5wzCO5QI4DmguiKCHxhF9vt+cRQUrkRDJ\nEPoi0YjjOKwFA4eXJ1kWYjwmug6dTocvCwowjZJVI3eKOAGmaWJxcfHI37iui0KhgGq1yikw5FjW\ndZ3TRMg8PktQlA4IRxRFkGOeos8UxaM2EjJ67NC8uq7L3Ieqqh5pWnbeoEtQ0zRm3iJf1xtvvAEA\nR2jN+gUNxSCETHOe8IMf/ACmaTKbVLFYxM7ODpLJZGgPdLtd9Hq90EHpdrshYXxW/YCKxSKKxSKy\n2eyxU5VErl4ZoLNDGqXI2jXSZ/jbvd5oNFj4ynBFkGLiOA46nQ5fNrVajbu4UooW0SNSNoz4A4Sz\nCUYFqI8lRIH+HTUp8iVGm6vVKm/MWCyGTqcTMuVldysUJ4MWTFEUVCoVbrQnUmJR9Jl8kmLDMhlj\n9TyPKcNoQ7ZarWN3zZSNpaUlzv2ji7FUKrEftNfrcUScNmHUHUI5uWStLCwsSB3z3t4eCoUCvvKV\nr/BjhmHg5s2bePToEba3t9mctywLuq5zIOTg4ACmaWJlZQXA4YUhg0C63zqLaWEv0kVKWjqdFdd1\nWbA0m82Rl4xo4RFkCFHqSOB5HruMHMdhS4+yNaJZQiRQgcN1IT5Rck2Ocq0de3f0uyGz2Swz3QPP\nTap6vc5aCwBuZnbp0qXjfuzYoHQKsaVJOp1Gq9WC7/swTZODOcBzrYomSmQXp8WXkdNGSef0uUEQ\nIJvN8o0ptq04Tzx48AC7u7u4ceMGZysACLWLAQ79eNRy4dq1a+h2u/A8D8lk8syb72UyGXz729/m\n3xuNBgeLVFUN+UhFrVPMlgDAppwMH24/wTw3Nzdyr1GvsrPslkvCxHVdPkeWZXFCOrm9+pnz4uNn\nodErihKylql99u7uLjKZDJaXl0MtX+iMiUEz8bXjjHmkJho1zehWEoUptQYhiU4aaTweR6fT4aAD\ntQuQ4VQmiOaGOEaKJFPQi8ZIWlSz2US73Ua73eYWAvT9+3ViPC0WFxfR6XTYtE2n02x+GIYBy7LO\nLPo6DP/6r/+K2dlZHtuDBw9C5nur1WJG82vXruHatWtsTkUFQqlUws7OjnQtS1GUkOCLx+OwbRuO\n4+D69esAngdBCfv7+2i326hWq7z2/dpLTApRZUQsYhgGsl7OEiRIqBKJfm+1WscSjGd9mZKr5uLF\ni5iZmUEmk4GmaUgmk1xsQ+4lqnQSXZFAuGPDIIwUon/3d3/XN7BCOV8iSJ2uVqsoFArs6CVBTOlC\nDx48OBMBET2slmWx35HGqigK94YxDAPJZBKWZYWShWX4RFdWVvDKK6/glVde6RvpJKe2jM8+Dv7i\nL/4Ct2/fRiKRwP3797G4uIibN28CODSVKMFd9HUnEolQv6KtrS3WYMRUIhn43//9Xzx+/Jh/v3//\nPgqFAlZXV0P5gBTB13Udn332GR49egTgMIuExkgpMzJaWYhdMmk8LypIiFAXCNqrNH/kV6SYwiCh\nc9bN6XRd52At5Tu7rsuWqO/7KBQK8DwPmUwGQRCEClw0TePYyNDPGTWQ1157De+99x5u3rx5xJc1\naOFzuRzfWtlsFo7joFqtIpfL4erVq/jpT3+KX/7yl+POxUQh3qL0b6/XY8FJ/pBMJsOmiAz3A11M\nhmHgwoULfdOxEokEb8rzajHreR633bhx4wY/Xq1WOakaODxotB80TUOj0cCzZ8+QTCZx9epVAGBX\niqxiga2tLbz55ps8pvv378PzvJD5DiBUyvnw4UPouo6vfe1rob+pVCp4+vQpXnvtNSk+8bt372Jl\nZQUzMzOh3mQvIsQ2G9lslv3jyWQS3W6Xg8aqqh6pRqJ9GzX3Zfedp88TP5MCiGLrH03TMDs7e+Rv\nRYxq2zLyZH73u99Fo9HA/v4+FEVhiT1qY4kmRyKRCLWEvXPnDt59991RH30ilEqlsapMaPwUmaf8\nQnEDNBoN7lMtG/0W8KzNtn5YX1/H//t//49/bzQaMAwDuVyOe7M7jhOKDlP6CgWfCFTY0M/UnwRE\nU5caol29evXI3CaTSVQqFQDA5cuX2S9NB4zKQ+fn52HbthQh+sYbb2B1dRU7OzshIXqeF+Yg0P6n\nzBHxEqRADgViBpn30TWQzaHQD9Rva9IYuVqFQgELCwtIp9NwXZeZjqJmWVTDIKdzLBbj3DBajNnZ\nWWm3bz8BSvW8gw5u9BaifDvqC763tzfxccpg25EBSmvyfR+dTocrV4DnFxEFnMiEjwodEgxi/bKs\nsVLddiqVCjWki46HDhMJ0Eqlgna7zVkmmqZhcXFR2mFvt9uIxWJHtGQq/yUzmVxPBFm5oMNAri3D\nMFhIivuX3GT93H6Dxiv7OwzL8xWDxwRyR+i6fuQioIDpIIwUouKHWZYF13Wxvb0NVVVDgpDIM4BD\n3yf5HMlvRhNNkCVEaQPSRFEwqdVqYXt7G6ZpIpVK8SESJ09MDKZSzFwuF/KxTQovsg9MhEhlJt7i\nIgEF8Nz1ABweHHGtz1KzooBBt9sN+ZOjWRf03M7ODrMj0d81m01OeYvFYlISw4mxK0rOEb2AXNfl\nQ01+3PNCPy1TzMIgQUoXJjB4n8sw5wdlCFDqWiaTQTqdhqqq2NzcBPA8K4Z8p5SOR5fXOMrOyMBS\n9CanKNe7776LH//4x6HnqB6Z2rkC4D7UFP0WfREyQFqn4zhoNBp8O6bTaaysrKBSqWB7exv7+/vY\n39/nw9XtdplHMFplcd50dOcNuoiAQ1M9KkCr1Sq2trb4kIsVLucFXdeRTCY5gFmpVPDxxx/z/qM8\n0QsXLkBVVZRKJU4dSqVS3KNcluZH8ylSIvbbZ5ZlnbvwpDkTz4Q4HrGwBhiv3FpWRVg/4WwYBvL5\nPPb391EsFqFpGlZWVrCysoJMJsN57USBSNYW+U5PXTvfL4q+traG27dv4xe/+AX+4R/+4cjz+Xwe\n5XKZo5oUgGg2myzYTkIEMA5IHY/H42i1WiiXyyiVSvz89evXsbKywulM29vbnCuaSqXYd0sbhyKQ\nk8a4m6jX60mtix4FUZtrt9tHSjiBQ8d7vV5HqVQKzTUJChlls+NAVVUUi0W8++67yGazeOONN6Ao\nypG9l8/nMTs7i1KpxL5SsqYcx5FSoiz636k2XUwlGgRZ5dLDINa/i0EZAEfM306nM5bAl3EpiKXn\nlD5I85VIJHD9+nXkcjkm0aEUR0rh63a7sG2bWamoinCUrBp5kgc5Ym/duoW/+qu/woULF/C3f/u3\nR0ga5ufnkcvlmIbMsizk83koioJ6vc6bddJQVRX1ep19sYZhYH19HT/60Y94QuPxOC5duoRLly4x\nVdrBwUHI7UAMS0D/6pLTYlxNnPLadnd3USwW/397X9IjSZZVfXw0N5/C3WPOiKjIjMrq7JqTrmpo\nNSpAAtQsoXuFkFiwQ/wEFkj8APgBLOkVAqlXIBBUlygWDVVdXd2VVTlXDpUxh89u5mY+fovg3Hxm\nbj5EhD/PjA8/UigjY/Lrz967747nztwqZuHy3t7eQJLl6OgIt27dQq1WwxtvvIHFxcXAmPSsqPv8\nrlepVILrutjc3PQon3A4jHv37uHevXt48uSJKK3l5WWYpom9vT1pD0yn01rkd10XxWIRBwcHHqXp\nui7u3r2L//iP/8DHH3888HvxeByVSsWzD/yKbdpQjYggJenPNUxiIOgwTOLxuKd3Hhi0TKPRqJRq\ncd2Z7GSNOw0sdjONS/COfSfjEgE//OEPkc1m8Y//+I/44IMPAHizsisrK2g2myJQJpNBKpXCvXv3\nxr30ucB4jGVZSCQScF0Xr7zyCr755hv89Kc/xbvvvutJipFPsFgsykXALB7HA+gotj+rYl5fX0ex\nWJR4dD6fn0ndHTeTP5Fo2zbS6bT2Fs6zQD3clUoFtm1jdXXVs4ePjo7w+PFjYW5aW1tDLBaTJpD1\n9XV5rxzboiN+R5IT7lPg1Oq3LAuFQgFvvfUWbNvGJ598IiQqVBL+khvdnUCqgibhugp/6EvNMbiu\nO1DNo/JZ6ECxWITrutjY2JA2ZJKdUy42ucRiMfT7feHISKVSYuz1+33U6/WxycWJroNhAVvGi37v\n934Pr776qridx8fHyOfzctv4FcawTN5F0W63cXx8jEwmIy1+lmUhGo1ic3MTsVgMDx48wNHRkTzU\nlZUVFAoFsaA4x6ZUKknXFTPU08QoIlh1PIgKNisEZRB14S/+4i/wl3/5l/id3/kd+RrbIwmuFy22\nbDYrPcjEf/3Xf2F/fx/b29u4fv06/v7v/37qsnKf2raNarWKzc1NWad6vY5//ud/huu6+IM/+IMB\n5V8oFKRjhaQlqVQKqVRKkhDTxIcffoitrS2kUinpiuG+ZJ1tJpPB9vY2Pv/8cwCnlnIsFpNESK1W\nw+3bt6VFOBKJ4J133pm6rKo7u7S0NPB9NW7sN7qCPNlQKKRlasDDhw+l0aNQKEj8fm9vT0rzFhYW\nsLm56bGER5WwTWKohEa5AaFQqP/RRx/Btm1sbm7i2rVrns4Ux3FgGIbEmagY/UKxDlMV/K//+q/x\nV3/1V+hPcdqf/70wy6rGm46OjhAOhz0mOglcmdklGFdptVrY2NjQJivLh05OTpBIJJDP5yWkwOF1\nZJyJxWLIZrNDwyz/e4NqW9NpQoesf/u3f4vHjx/jz/7sz8SCu3PnDgzDwNrammTc/eAcJhXko1xZ\nWZm6rP/0T/+E73//+5LwWFtbk8SrOlqn2Wzi0aNH/D3EYjEcHx+jVqshkUggl8shlUqh0Wjg+PgY\nv//7vz91WR88eIBXX30V/f7pgMpCoSAF9qzEGObyqvyuKj788EP87u/+7lTlrNfrePDggXDeVioV\nKctj0tsfz3ddV8ab+A1F5gCq1SoWFxeHyjpWiU7h/Y3ENBdxGn9nFC6LrJdFTmAuqy5cFlkvi5zA\ncFlHKtE55phjjjlG4+UY5DPHHHPMcUkxV6JzzDHHHBfAXInOMcccc1wAI0uc5gFwLy6LrJdFTmAu\nqy5cFlkvi5zAcFnH1olOmnhqtVqBkwCBYNYUYPqtX35Z2ePdbDaHFrfX63XYto3FxUXpZmCf/9LS\nEvr9Pn784x/jT//0T6cq6xdffIHNzc1AZqN6vY56vS4jRJaWlsZyGhLTXlNyCsTjcWmDA4Dd3V2Z\nQ1QqlaS2EgAePHggDPK1Wk2YwzkZFNAzT4ojndXSO055tCxL5GRXG/C8m4oEvirUCZHTXtd2u41y\nuYxMJiMlgb1eD/V6HeVyGZFIRFoUWas4rGaRJCZse5x2DfFXX32Fa9eujaUE7PV6ePLkiUyR6Pf7\nQ2usa7Xa1MeucBaYbdvyLDnzzbIs5HI5PHr0CNlsNrCzrtPp4NatW4hEInj11VcRi8XQ7Xaxv78v\nnLhBuHDvVb/fh2VZ6Ha7QwtuXxQvJl931GFlLZlpmjI+QGWhUWdETRtk8iGowEulkrBfqTN/VOgk\nN1bB1tn9/X1cvXoVwOlhyefzAE4P2BtvvAEA0sqrFlJns1kcHR3J+2Q9pg6OTu6/drs98Pc5EDCV\nSsFxHKkXzGQyKBaLODk5QTwel2fNyZC6ptOyYYJ7lLXA7JJbWlryTF0ATptYnjx5IjSTnU4H6+vr\nMlgvHA5r6a0Ph8OevTaMlOXevXuo1+u4cuWKkB0Pgy4OALZzqjWft2/fFlpL13WHytXpdOTSX11d\nxcrKykTK/kJK1LIsWJYlxeK0BDudDrLZ7Asllx2nZChrMpkU6iuCbWIceKejDMwwDCGyJRzHQblc\nRq1WQ7/fl0Pt37Bc81koUVpj5XIZa2trMp+KRNvqZmWzBRUscf36dezv7wszkp8FalpgeyZlUhl4\neCEBp80gqpJdXFyUFkU2NKielS6o1jupIwFgc3PTsz7cIyTOiEajKBQKWF9fRzQaFSPBsiwtLaos\nqFfJmf0olUp48OABdnZ2sLq6Gnj2VeWra86aqrx5dqvVKorFIlZXV+XCD5Lt7t27yOfz+OCDD0TO\nSYicz63lut2uTO9kwz83HU3oWCwmzC/xeFz7mGQV41waLlIulxMCh36/D9u2USqVYBgGbNsOZP2Z\nBtTWTR4Sx3GEZ8AwDJimKW2A6gZULWXd2N3dxY0bN7Czs4PPPvsM3//+9wGcMt5Ho1EZGeK6rmfK\nIvvA2Sa4vr6OR48eYXt7W5vsZJziAfa746P2n6rQAAijl06wvVe98IOsJD73zc1NCQEFgXyY0wbP\neJCFD5zu21u3biGRSODKlSsDCpRdVysrK7IfdDGTkUO42WyiXC7DMAw0m01ks9lABVqpVHBwcCBE\n8+RUAJ4PurswAckwNJtNGZPcbreldQo4VQq0OprNptDJdbvdmQ2rOgtLEslxGVuiJcX52jrIEvyK\nkEPRaElEo1Ehj+bsGkJH3GsY+LwWFhYG+o1XV1eFvMFPMGGaJnq9nkeRpdNpPHz4EK+99poWWfkc\nuVb1eh2pVEqsTLL0TApdrjxBAuNJw11+2clByt+fZEb6ecA5X0GeT6VSwYMHD9Dr9fDGG28MxO45\nawvw9t3rIiBhK6plWZIPCYVC+O53vxv48/1+H4VCAcvLywMeXzQanShue26TgC4dN2YymUQsFpOb\ngF8n/+TCwsLMp/1NCs7VjkQikpTgzTsJn+B5wFk1kUhEAt/s1c1ms8jn80PdCDXBoxvqM/v1X/91\n3L59G7du3RKr8+HDh0gkEgMjtIHBWLR/jPW0kUgkZKooAM+0VLrCZ4HuWL56kZ7HMvP3rDPMM22Q\n4T1o/W7dugXbtvHOO+8ETnI1DANLS0sDF6cOZU8wlhwKhfDo0SNsbW0NGB30PHO5nMSfVZDEZhKc\n+yRSMSYSCZimKSQeJByIRqMwDAOJREJGLbys4AAu4HlcjTOpo9GoFsYpXjC8NTnDO5vNYmVlBel0\nWmTq9XovbCZTJBLxuIiffPKJHPjDw0M8ffoUwKllwedPhMNhjzUXDoeFPUnH+6GS5t+ORqNwBnIl\nPwAAIABJREFUHAeWZc304jkLWq0WyuXymQ0MktOQAcpxHG20fUAwJ+xXX32F/f19fOtb3xoIh6i/\nt7S05PFUWq3WxNUm50UoFMLjx48HptRyrnyz2ZTql6B9wX0zCS6k2cg2w0ymCsZ7aF7T5XsZNzJH\nWjALaRiGLCDHrE4bavafa5dIJLC4uIh4PI5+v49arSYKlJbyrNFutz3VFu+8845YFdlsVg6ParGr\niR31hg+FQnJ4dCQWeHHzNePxuBDsclQIvaWXAZyDPg7+deXv8t9QKIRWq6V1Mq3fUnNdF59++ik2\nNjbGzksLWm9/Odm08ejRI1iWNTAK23VdIW0HnsfK/Vy0rVZr4hKsC5uHHHBPSwp4XrrDmI0/az9L\nDKtRVUEFQOuQ8VvGS3W4SLZtCzktZ/lwWBbwfLxwr9cbeMizBBMdpVIJT58+xc2bN0Xpm6aJmzdv\n4r//+7/x7rvvirXBOVV+pU93O5FIaDlEfF1+kKuTsWbSNapW34tSqPv7+2g2m4hGo1ISViqVZApo\nIpFAu90eOrHUT9uoTtadNoKSSf/zP/+DcDiM733vewPfGzeXSnditNPp4Pj4GDdv3hz4XrPZxOHh\nodSvGoYB13WFMpPUlyyJmwRTeyd02/mRTCY9HH0qw7RO+E1wdWFGgXEfxmpSqRRM00S73daS8Tw5\nOUG73RYFGg6HPYpFHcPgH5ynQtesKj8KhQJu3boF4DTJ9OzZM/neW2+9BcdxpHZRLRnjnC3g+Vyh\n4+NjLTLSVVMTC9lsVkJNrMFk/PlFzX4CgGq1Kpc2XXrbtmHbthSMLywsjCxjo+tOV541vdNGpVLx\nnNu9vT0cHBzg5s2bA2EIda7RMPhHlE8b0WgUN27cGLAkDw8P0el08K1vfUsG1XGeUjgclrMIQJ7D\nJHj5fOs55phjjkuEsUpUHSg3KmhNq5PFwMzSM6bHr7OUSBf8MrKDYZKAu+q2GIaBeDwuFvS0wRIw\n4PTm9LttkUgEiUQCqVRqIJNJq4ouqm7w/f/Jn/yJxPDoMgGnVjsHAj558kSsE9d1JQZKqy8Wi8m4\ni2njypUrWFpawsLCglghsVgM6+vrSKVSYt2zKmKY6zsLC/Xb3/42rl69io2NDYRCIemiWlhYQCQS\nCSy5ITgFoVqtSg12PB5HvV6fOKN8Fnz++eeo1+sATt3hzz77DPl83tPG2+128fjxY5RKpclmtWvO\njfjjtI7jIJ1O49q1a4EhxWq1KsMYmcthdcy4OPPYmOijR49QqVSQzWZlPIFpmgPZdpY5Ac/rRKk8\nedjZluY4jvRdTxtURDww/X4f0WhUFM9ZqgQymcxAa+a0EI1GJe7FelAV3W4X3W5XZG+1WvJ+6N6r\nmWid+Oabb3D9+nWEQiGYpomnT59ie3tbaoRZn7i9vQ0Anl5lQj00b775Jj788MOpy6muoV9Bmqbp\niUPzYHBwmVqLO6vppEQsFsPKygosy0I2m5WQA91JKnXHceT8ZTIZz/tNpVLodrtawmXFYlFqp3d3\nd+G6rkeB9vt9HBwcwLZtLC0taS1fOg/K5bKnfdaPp0+folQqyWymxcVFtNtt1Go1aQkfhbHXATuN\nWDhfrVaHZhTVWSqM9/CgtVotuK6LbrcbOMt+WmCMSe2BZ/nNeTpQstmslo1Jq50WvF+5sw2Q1jzf\nA5U6Faiujirio48+EuVIbG1tyXNWb2nKXCqVPErMv/ZXrlyZafcawZI8db06nY7szxeFYrHo6dOP\nx+MiU7fblTbV5eVlrK+vI5fLDVy6rBn1t9xOA2qbrGEYeO2117C1tSXf53nL5/MjGxTUNdbVsRRk\niS8sLAytuWYyb3t7Gzdu3JCOpVgshmaziWKxODapO9YsS6fT0hrJwL3/0PIg0SpiRpuBfFqh7GXW\nnRFVEzGcKa3WsZ7VldBRNsI1YFmO36IkqxAzzrwMyNQDeAP053lfk2B9fR2xWEymTwKn5UksBYtE\nIjg6OvJMz2QhfrVaxcLCAsLhsOc273a7+I3f+I2py1qr1YYStgDPu8BeNvR6PaTTac/z011HeRao\nlmU+n5eEDADx9BYWFjxdi8BpOKfdbkvXmGrh61KilIMD6sZV52QymYEaVxonJCS6sCXKw8n6Olp6\nKhhf4qFW2xJZexmLxcRS0ekuMeRARKNRmdrJUMJZoePgqQXh8Xh86G2nWtN8b9zAajmPrhgT14sK\ntNlsIpPJSDyUe+Lg4GAg3r2wsBAYix4Vj7wISCBy2bC8vDw1WkAdXpP6DFVlr5boqZlt4HkcXW0a\nUaFz7jxwml2vVCpjz4WqK0ilxz1E934cxlqidDWpPGnNqZaJ+rPq75AFiZ0UakxPF1jjRTB+q/Ji\nnlUGHZaz+vqsURv1s3Tb1Z9Tk3b+vzkt8DX4t1nUvbm5KbyhrCX9+uuvAUDKSABIzW2n09FGKajK\nOuxwMgziOI4nzs29yn/VsrIXAcdxsLu7K52AqtHBC3SYbLrOln9NuQ/ZmcizrvIWjHvWOpUoOXrJ\n7zEqRsuSPOB5OIqhMxqGY0u2JhGKVkMmk0E2m0Umk0Gr1UKxWBz7u4ypMiOq02oCTm9ANWYbDocl\nY8tZ1KwBU+n7RkGH1RREdjBOhkgk4mleUNtCdVlg+XzeE2dKJBKy6a5fv44HDx7I93Z2drCzs4OT\nkxMPh2gkEoFhGNo4JAk2TQRZv6xRtW3b40rS+mC1xIuefksmJHarqV6Q2p4chKD57tOAGs9m92EQ\n2PI9CXS3gUciEbGaHz16hN3d3aFyUB+xFTQUCqHb7UpVz7h4+Vht5t9UiUQCyWQShUIBiURCGMJH\ngZR4s+ihdxwHtVpNLGC+PvlNy+Uy9vb2xLWfRPnosETPc1jV0Ih6Eek6PHxN9bIkz+ovf/lLAKeK\n9Pbt257fefPNN6Uqg9R+QHDny7RljcfjYl0EPdvl5WWkUinhiWSbKOWlx/QiYZomXn/9dSwtLUkx\n+KRrp8Pa93PeDkO9XtcW6zwv+v0+dnd38eGHH+LOnTuBP8MELyuQ2Jyjdl2OwkTufBDYVjcpaCqr\n5rMO1Go1ORT+4LyqhEYRzPqh4/BftAxEjYcCegg9gNP1VDOxLMN59913cXBwgLW1NWxtbeGzzz7D\nd77zHQAY6BQ5ODjA4uIiYrHYmcvMzgK65Bw9MmzvqtYduRFCoZCM2GDyblyY5WWEDo+k1+t5LLSg\nHEG73fYkF8dBd2iHKJfLWF5exuuvvz7UGCJrm0r0Q/o/WqSjMHY3T3sOisrgrQPlclnauFiuwJbE\nZDKJra0tieFMCh1K9Ly9451OB41GQ2pI0+n0WDfvIvjiiy/w1ltv4eDgAIZh4JVXXkG9XkcsFpOC\n5nQ6Ddd1xUpR14suMjcwS4qmPV8JgNTSUgm2Wi2JgbbbbeGz5P+B0/AP65rb7bbwJdD9j8fj2sky\ngior2u02jo+PPXR++XweqVQKruuKdxCJRJBKpWQf6CjVokIBBvctpxSc1VubxeV0dHSEQqHgoeh7\n+PAhHj58KHH8nZ0d5PN5hMNhWJaFvb09pNNpLC0tSX02Gw2GITTKggmFQn2dMaL/TTRNbdrf4eEh\n9vf3YRgGlpeXUSgUPLcIA/RMdACT3Yg/+clP8Ed/9EdTlVXXuk57TdfW1rC/vx/4fcuyPN7IyckJ\nAC/5LgAhZ/Z3ikxb1lKp5KmTVDc/EwyMzfK5q3FlJpZInadWkUxb1st0rv74j/8Yf/d3f3chPuCn\nT5+i0+lgeXkZyWQStm0jm81qW9NyuYxwOOwxAr/++mt88803cBxHlOiNGzeQyWRkNI9pmgMeLJO3\n5572eZnQbDaxs7MjSRgeDJUExd+xQqtDteSazaZYS7FYbIBO6/8Skskk/vM//xO/+Zu/ORD6IGlL\nUKdPv9/HvXv3cOXKFWQyGbTbbezu7iKfz0uiadqgAq3X62i1WqhUKlLLSldNTRgAzy/Uer3umfjZ\narVwfHyMVquFa9euTV3W+/fv48svv0QqlcLq6qokOqPRKFKpFJaWlqRjjrJWq1UJO3D9XNdFpVKB\n4zgIh8M4Ojqauqx//ud/fiEF2u/3B8q4dFn3n376KX72s58hkUjgD//wD9Hr9bC3tyd5ksXFRU8t\nMfduIpEYOpn0Jz/5ycjXHGuJnvO9TIxp3kTT+DujcFlkvSxyAnNZdeGyyHpZ5ASGyzpSic4xxxxz\nzDEalyv1OMccc8zxkmGuROeYY445LoC5Ep1jjjnmuABGZufnAXAvLousl0VOYC6rLlwWWS+LnMBw\nWceWOH355ZdYWlqCaZpCfwZAZrLX63UcHx8jHA4L4wnpz4DgoWWu63qmMk4LZ0mSsTBcLWZmOUkm\nk5HyJkKHrJVKZaAmrVQqoVAowHEcPH78GNvb2zBNUxiSms0mer3eQDnGL3/5S7z77rtTl3N3d1eY\n90nIQCq8RCIhXzsPdKwpy9c48pqy2baNaDQq7D5sCFheXh7btfbxxx/jt37rt6Yu6ziQf5e1zqR3\nG1UedP/+fSF/mRb8snKI4zBUq1U8fvxYanNVAmeetcPDw6mXjh0dHSGZTHq61WzbRiQSgeM4aLVa\nyGQyQ5tnbNvG8fExotEolpeXZToHMHqvjlWiXCx2yBDsKWVtm2EYUkumHipuXLXN8UX3JgPPZUwm\nk55NeXh4KIQbunlP/UQZav0qh/2pME0TjUYDT58+Ra/X80wH0DVOmbW17IpivSVHwLxsUEllOp2O\njE1mzajjOGg0GrL2vAy41pVKBb1eD5lMRt7fLAik/e2w5O+lEgDg4SOgYiU9YqFQ0FZ/68e488sp\nF0Ek0ST00NG1SPIZVf+0223h01hfXx+5PrZtI5fLnblLc6LeebLTUzhab71eD67rIhaLIZ1OD+UJ\n9S/Yi1aiHL8AnCqfTCYjMpFQeBbw9+SyhxuATP9kKx8f/pUrV6R1kiiXyxPNLz8P2Ebpuq7QhJEC\n7WVEIpGQ1kfVGnEcR2YRZbNZ2auu6wo3quM48vnm5ia+/e1vAxh8TjrgX89qtSoNH6ohwymljuOg\nVCqh1+shlUqhVqsJ/ZtujPM8MpnMgLVMxWmapoywnjbS6bTsVcMw0Gg0YNs2XNcV0plR8HfaTYqx\nJ4EHhh0V8XhcNDu7fUYpUGBwZs2LtGBc15XNB5zeXsViUW6gRqMhrFO6+3tpyat95SpjTCwWQ7/f\nH3j4S0tLsv4kwdZFhUf6Pdu2ZY4PoJ/K7CLgfqOM4XAY6XRaZuekUil5tgxNxONxFAoF5PN5Tzur\nbsKcYWBIicMSged9/v1+X/rl+/2+/Fur1TyDJV8GNBoNmbem7mMdtIgkjCEHQigUEo5TnZMCxp4E\nlaiUSrTZbAqDdi6Xk9EbZ2FGmjUY72T7F60Vyq22BPb7feTzeS0kGSoikQiq1arcgGp8FsBQi4+x\naSqChYUFrK+vayOfoCfC+LZKXvyyQr2cUqkUEomEjKjw98STa5ZQrSRaT7MGJ0lQRgASVlFjvZxv\nREuL/AUvEmorMHMf9GTpFeiaacUxRK7ryjQL6ihdGKtEyQHKjdVoNGQSIYmW6e7MekriWcDYETcg\nZfaPHWafd7lclvenC6ZpotlsSszY/1rDXp/M3SpWV1e1yKomFZrNJmKx2FT6nnV0yqnKhbExlcw6\nCEEunv/iChqxO0vwPZFHloQYvBTIQGUYxksxaZOUeZFIRAwX4PncMD9H7TRfl8Qxx8fHMnNLx/A+\nFWP9VVqidC2r1apk3ZLJpPAv8kHOIn50XqjM5bRIWDnA25LvLRwOa48vMbtNd9E0TSSTSblBh92e\nQdlRToicNjgqIRQKidUzjVtd1ygT9XP1+Z3lgvfH614WTlF1Kiy9KSYj6crrnh7gx7DJvaQi7Pf7\nME0TpmkKbyd5W6eNbrcrr1utVpFKpfDKK694Lkom66aJiWKivM2bzSYsy5ISgE6nI0FildNStwV3\nXkSjURQKBRweHnqym/weZ0C1221RcLrlMU1TDgSTIgcHB1hZWRmaFQ5y8UOh0ERTBs4KNePJ2OLL\nClUxnydG3O/3ZXQMQ1jRaHRm45QnIaym9UkOVABS/kYjZ1bo9Xo4ODiAaZoDJXfqwEh1ogX1hy7y\naMdxUKlU0G63sbm56fl+t9vF0dERIpGIxEinESsdq0TV4ViNRgO9Xk9mFjmOI4qVc94BSGD3ZQTj\nibyx1eQOqd1c10U8HpfKA11JlEajIYFvhkeYuKtWq0PHQgyz4nRYomtra2g0GsIW/yLmxU+Kk5MT\nceE5obbZbE4c0wyFQkgkEjAMQ/aFrplgh4eHODw8xMrKClZXV9Hv98X74GDIUVDp8LifOStqVmg0\nGqjVaiMvVl7APEPZbHboHKyLgs95eXkZhmEMPHeOfCev7LQwVjswxpJIJCSzyaJ6TiRUhQP0jCiY\nJshaDcATX2Ish7OXer2e1rlQrPlMJpPY2dkBcLqm+Xwetm3j5OQEGxsbI11fNYGiIwFCRa57Sus0\ncPfuXfT7feRyOWSzWSSTSbTbbSwuLsI0TVFUnKkTBCqvSCQiVpOOOOPu7i4+/fRT5PN5XL9+Hevr\n69LokUqlAtnuh4EhKjUZNW0EWcmO42BhYSFwLAgrTfy1q6x11ZnoiUQigXHQZDKJK1euDBBuqzjL\nuhMTZeeJVCo1QM7KG1EN3DPjPWq864uE6mrk83m5GZlBpPXBDiFdBcwbGxvY3d2VWBYTGNwAlmXh\n6OhoZO1qt9uV9zLJjOzz4mV8jn6wcD6bzaLdbqNUKsnMJYYjxj1LjtzmuBM1qTpNfOc73xHG/8PD\nQ/R6PeRyOSlhYjhpnLLhHmXlhK74reM4UkrFWmESHNfrdRnvTIwaAxSPx7WWHA2DvzIDOD0/1WpV\nFP555BqrRB3HkZs4l8sNuHOckqe68FRKLMnws0i/aIRCIckwO44Dy7JkzjSVP60WZvh0yfHaa6/h\n+PjY477xsLuui1qthng8PjTD+LKGTV4E3nzzTc9zPTo6EsXCy2aYkmEiit4W8wC2bWuLM77++usS\nx2y1WpIcrFQqUrDOrweBFh3jtrwsdCCdTsOyLCnJY/7ANE2ZnGsYxkilr76XizDlTxOsajAM49we\n59jfqtfrokSCHmYsFkMymfTEYtQSIrrIs7BKbdtGo9EQ98Kf8FLB90Il1Ol0RKEyphYKhXB4eKi1\nsJxdSWqrGUMMhUJBrKBhh+llbL18UVCtzEQigcXFRem0YikeO7DUmDhd9ng87um7ZtxfF/hMNzY2\n0Gw2UalUpA6UWXda0gAk3suLQd2XlFtnJQEVH/chqx8mVYjq/n1ZKh78s7bOg7HaoVariTs57IWY\nkFG7gIDnha8sZqdlqgvJZBKlUkluZM6eZ4lFkPxqMkaVj4meUCiktYA5qI+YB53ziFhiNI744f86\nGo3GQEiDcUL1AAfxEgSB8WBdVlMqlZLyQHbJUXHGYjGJcU96URqGoT3xp65FNBpFtVqFZVkoFArI\nZDJjDSZeHC+iCywI6qBC4HzKfawSVWOdrBP0H3q2hfqTNbxN1dgOv6fjJqJ7w+SQOpBMHYHrl50P\nlBuQv8v2Op2JMj9hAuXghM2lpSXPlNLzBL7/r8B/cNlccdEmEF3Pn+VKPE+8NOkenyeZp6u7imdK\nHTfOEsdqtYparYarV6+ObcRgG+ssqwiCwEmwNJSoH7QkllRwMqJfiTKGp05QpOWpUkmptZg6FAHd\noF6vJ+UenU4HqVRKNpeazQZOlejCwgIsyxLXjzExPmidXSDdbheu63o2H0e9sutifX1d3H5a/HNF\nOgh/FxSV50UrC3S59H7Pgi2omUwGh4eH+NWvfoVcLoft7e0z/U0doFenjps2TRMLCwtyrkmEE5St\nV6E2mLwo8LyVSiWJizJEwtj5pF7fmU6iOnrWDyqfVColhcBUaGr2m1/TAcpFa5mtlJVKRX5mmGuU\nSqWQy+XkZlK7LHTGRLmh/JtqaWkJr7/+OlzXxeeffy4hBZ0Z2P9fwfBIo9FAtVqFbdtoNpsTd6Tp\nGuboH9VNhMNhrK+vY3V1Fbu7u/j5z3+On//85xP9TV17g0ZJvV5HqVSSr+dyOWxsbAg3xcHBgTBh\njcKsWsRJg/jNN98Efr9QKKDf76PZbMol4TiOGIyTYCIqPILWpuu6gbEXKptEIoFGoyGBfLV/mUF+\nHWVDKmsLa1jZR3vr1i1sbm6OLGEIh8NSo9loNOQm0hlnSiaTKBaLsCwrcE3efvtt/OxnP8Pjx4+R\nSCRe6o4hWmyxWOyli91Go9Fzr52u589SoWGW8traGtbW1mRdHccZK4uu0iE2oRSLRdi2PRB7TqVS\n2Nvbk4aB5eVlLXKcFcfHxzAMA4uLi0NzCqyEoeJsNpseUpdxCv/MJpbaGpdIJAItO9Zj0fpkCIAJ\nqG63qyVYr/bqEqlUCtFoFJVKBZZlSRZ2FEgo67quR5nqgFqiMgzf+9738OzZM2kCULtVZgmGaNQE\nHLvWWPMInFrXyWRSun9mpVB1WTe6EktBMfognEWJ6wo9lUolPHnyxNNNRaYkJkHffPNNabzxE7H7\nMYsSp0ql4rmkHMdBsVhEt9v1NBHxZ2zbloReKBQScqBxHMMTM9ur/1cPUxDUcSBMLvGNMGOvA8PK\nmQzDkIWYtDWSikAtedEBxjgZx+Wl5N+Em5ubcBwHnU4Htm3LRuAlNQv+03K5LMk7Jg7p4vkrLxzH\nkfbZxcVFrXIRuixGHcX2wPQSVqolq+tsOY6DcrkM0zSxvLyMSqUi3qbaYjlOibPSZBZdjeRAACBN\nLWyooVeyvr4u1QJsGkgkEmJJT5IAG6tE/UqHsU4mXljErCpVtnyRd5QFzNTurVZLS3eNaZpj57ZM\nWi4yq7hjKBTC1atXB74etBmDlITOVj8AePjwIe7evQvLsqSqgllvKnA2KnDN+v2+h3OBMtLyCoVC\nQ2NUF4Gu2PW0ZxYR08qkq4aDDtq3O3fu4OjoCG+//bZUvzSbTeTzeaRSKWFvU/chXeJ4PA7LslAs\nFlGr1eA4DlKplDby6H/4h3/A0dERAODq1avCRcEpHExq82J8/Pgx1tfXPY1C9XodBwcHqFQqcF0X\nv/rVr0a+5pliogDEPeOL0j1Xa8O4eMyWx+NxcVt19qJfJnCEgYpGoyElJOrBYKyGlh/ZmhYXF4VP\nkpt62mDraaPRkPgQDxI9DtY6EpzBRAuFVqtt21IXy40+x8uPeDyO3/7t3/Z8jeWOhN+ypDI6OTmR\n0SzRaBSJRAKO4+DmzZtTl/MXv/gFjo6OpGZVDSsx8UWvjaBnzRrbXq8Hy7LQarWkqoflUMMQGmX+\nz0e7enFZZL0scgJzWXXhssh6WeQEhss6UonOMcccc8wxGvOCwznmmGOOC2CuROeYY445LoC5Ep1j\njjnmuABGpsnnAXAvLousl0VOYC6rLlwWWS+LnMBwWcdaomphPcsE/F/jB+vFXNfF3t4eisWi9Nrz\n+/z8b/7mb3S8Sc9r1et1DxlK0Mf9+/fx05/+FP/+7/+OYrEY+J501DR+8sknQvxcrVbl9dTmBH4c\nHh7i5ORkQK4vvvgCe3t7Y5sfLgL+3WazKZ+z3m7cR7vdxsnJCSqVinSE8L3dv39/6rLevn0bjUZD\n+uIpR6VSgW3bODw8xJMnT/D111/j+PgYx8fHnj0Z9FEsFqUTa5oY9nqlUkk+v3v3rud9kJCm3+9L\nzaX6u5VKRcu6+mVkZyAHw1EvqPu2VquhWq0Kw5NlWWg0GrBtG+VyGZ999pkWObk+/X4flmWh3++j\n0WjIHiRVZtDat1ot6WhSz97HH3888nXP1fYZBJXdqVqtot1uo1AoSL1jqVSCZVnY2toCoJ/lnnIO\nK5pnsW8ymcTW1pbUihGlUgndbheLi4taitn5N1mUTHAsiW3bUvdpGIbUgrJAm+xTHCKnm0dS/fvs\nRBqG/v920Ni2Lezw5DIgdAzVo+IGTusUKTPrax3HkfpGFltz7MUwkH9hVmg0GvLc19bWkEgkYFkW\ngOdMSo1GA/v7+yiVSnjvvffk51mTPSuoo2n8NaPqRAHWaxLkttANylStVqVj0V8nqoIt1arOaDab\nYxtvzqxEhxXKq1+PRCLIZrMiLG8FzhAC9LXSEaM6ebrdrlBh5XI5z1AtciQWi0WxuLiJpwmVe9VP\nXxaLxVAqlZDL5RAKhZBOpz1zxnnol5eX0Wg0ZspuT7rAIPBiMgxDrM6VlRVks1khye52u9o4L9WW\nZNILsglApTnjxFcA0lPtui4qlQparRaSySQ2Njbkb86STMXPzt9sNj0EJGQby2azHoOm2+3i5ORE\n29oG0S+Oa5phZxBZ3PjzfA46oBpnXEvVUBnFOcHhhGpff6fTGavwtbQO+W/2UCg0MKZUZz/yuJvD\nfyiocHu9Hmq1mnT/NBoNWJaFw8PDqcvJrqN8Pi8uHDcAqdpULlZS8+3t7cn60kJ1XVcr5ynwnJG8\n3W4HWm7sBgFO17Ner2NxcVHo3trtNvb29pDJZGCa5sQ0dGeBaZpCf8iLibRmtI4KhULgQWKftX9O\n0azngqnnotVqIZ1Oy14xTROxWExG1nD8MAAZsqarJ11dEyrAYWctHA4jlUqJ9U8jpFAoyMgVXReT\nYRgDcqlrOoo0mgxw6iieXq839mzNrP/ScRwPTZcuFiJ1sN5Z0Wq10Ov1pGWRloAO11PlODVNE6VS\nSYg6jo6OPGulHuRoNIpGo4F0Oi3Uf9VqVbsSpQs/zNJpNBoeTyObzXr+f3h4iFKphKWlJfn5aYPu\npWr1hMNhaT0dRcHIwXB+zMLKV1uAVesunU4L1wRw6nmobdMk8jg5OUGv18Pi4qIo3FlglLESCoU8\nxD9+6FL2fF5qL796fkddiv1+fyB8w3b1UZhJiVO9Xkc8HvfML9LldtA1OysYTI7FYsjlctIfzl5x\nnTBNUxQ4cEoTRnZw9qjz84WFBY8iSKfT2kMjlAkI3oSu6yKXy3mmJvqtVSo2fl2HzK6HE50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Wr4uHW0xPT2N+ft526JfLZdvcRqNRVKtVW0lJ4KBQeK++k5lMxvZxPp/H5uYm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\nAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f97755c40b8>"
+       "<matplotlib.figure.Figure at 0x7ff1e8d14780>"
       ]
      },
      "metadata": {},
@@ -2077,7 +2107,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2085,9 +2115,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Tdfzkk0+mfezi4mJfioL83d/9HcrLy/G9731PH2ttbQUALF682PP2JMMRKhERkQG8oBIR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\nIiIygBdUIiIiA3hBJSIiMuD/Ac2Zg2C+Eg3yAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f978557cf60>"
+       "<matplotlib.figure.Figure at 0x7ff1b44eb1d0>"
       ]
      },
      "metadata": {},
@@ -2114,7 +2144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {
     "collapsed": false
    },
@@ -2133,7 +2163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 66,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2166,7 +2196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 67,
    "metadata": {
     "collapsed": false
    },
@@ -2177,7 +2207,7 @@
        "'cat'"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2188,7 +2218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 68,
    "metadata": {
     "collapsed": false
    },
@@ -2199,7 +2229,7 @@
        "'dog'"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 68,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2224,7 +2254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 69,
    "metadata": {
     "collapsed": false
    },
@@ -2283,10 +2313,11 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/08_Transfer_Learning.ipynb b/08_Transfer_Learning.ipynb
index bd0cd3f..e90922e 100644
--- a/08_Transfer_Learning.ipynb
+++ b/08_Transfer_Learning.ipynb
@@ -115,13 +115,13 @@
    "execution_count": 3,
    "metadata": {
     "collapsed": false,
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.11.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -137,12 +137,41 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Load Data for CIFAR-10 "
+    "PrettyTensor version:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data for CIFAR-10 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {
     "collapsed": true
    },
@@ -160,7 +189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": true
    },
@@ -178,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": true
    },
@@ -196,7 +225,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
@@ -222,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -249,7 +278,7 @@
        " 'truck']"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -268,7 +297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
@@ -298,7 +327,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
@@ -324,7 +353,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -361,7 +390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -427,16 +456,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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Pt8qFPGHHZ0bCcnQsDUCA48CxMsNerG5z7m4EyrdKneOHTM+V51MS7c0vDgL+PY26PscP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BqLetW0LyrRmJQxbv+sBME99sC9RbvhA4M6VORhaVE8zl5P+lDzHnAUi/3tpZzMulcP6tM42mlx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\nt9N8SG210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AsdhskEjcG9rXuOPGsfSdt7ZEeNnryhJA4JY1lldOAJ7mUSoUCoVCcSjQF6VC\noVAoFBNwpNRrr7WJ9tYqKk4hOCQHeJPJpRhSQs3PWrrodU+Kcq5vC02w5ct0fqpu8zMfeUIswN66\nLnmSMTFiu87i6+JFsSa7ePZ80b6+KtP1l176nj3XJll1lcR2boZylG69ZCnbtS1Sg5Gi1yd7vbFV\n32lyoTvVECVW2ROqYThwuUSZUB1xkiBT0euh4Qtf/CKWj5/BzLKl0l/4vlCZI8pBHJFiNHVqwZwU\neT7I9svlRqakJMypGLO3b6hqt8eJ7Lu5JZTvOGeNGFBMN0XpygrF7S33jBBFtbkplNuQKPzE5fam\nI3kefaoeUi3b+C1xniVVchhxWR7YgKzUyux0pjgEtNu7CHa2sHrb5h5Wa9IfPfLYk0V7loq/V111\nmQFZcu7siFVn7CrG9HKqxkFq0KmmKLBrJduuEN0a0E1Oneo1SeRYMXW6A+rPjHtGPFJip7T8RunB\nCHxXtSSjHHQqWr21YSnoTcrfbLcl135nV1TA46WKUmMObVJr3w86o1QoFAqFYgKOdEZ56+ZthJ6H\nUxcfBQCUPRl5ZCMZ4QZkMF127UZDZnD1puTLPPKI5Af99m99GQDQa0nOZXVWRldXbokw4uQJKwI6\ne/mTxbYSjaLPnRKR0O62XRh++RURFI0XwQHg9q78jj0nUBqkMhLb25XF8cVlEf7c2LLbZ0/KDHir\nRDUoMxIBJfa4OdWdG2Yj3M2O9BZ+pPHqay9jdWMTL37veQCAgQhWfJ9G0ZQzKXUAQ9pXRsmBq2NZ\nppgem5ADQET323O5ln4unzcjEWZ4jsWIfRqlk+sTGbIgckblcY/y4MiZakQiDTM2SKfp7YhG96lz\n3um25TtVelYWpuTZDNxsJAqlmIDicNCcnsPswhJm3Iwx4Dij+Gp3REDT6dh7XiLDexa9ZE7kc2xJ\njMNLZWLAKOc3dzWDuwPpqwd7MnPbdTPVrW0pAtGnmeyjj0pfHbqcXyYdfE/+j4U7w649xy1yUdug\n2qojx4T0qABAa1cYwYjyTcd/m9/5ylfQpnzT+0FnlAqFQqFQTIC+KBUKhUKhmIAjJUdev7mNVlzC\nqSc+DQDIIFNlQ1NtZDLd33OLsru7slA7N/vxov1Hv/jjRfvjTz0CAPjVf/mv5LhkADw1JTTW8WOW\nAq2TGMJP5Hpml+VPs3LW0hOtitAbz70geZKrHaEM8tDSwlPLkrM2f16oVZ+o09Tl3r2WSx7alTWh\n1SIynu7QruO5AAAgAElEQVQ7m7Ee/ZmSzEe3cxfAs1AcHM8/9y34YQW9PUvJRKGIJSrVBu1Jtfty\n285pzOmFTL3ae1gu8XKC0K0RmZYHVRsz5UjiJfKI8nWnMGUSC5HwLab6j0Mn0NlHsxlSAdH3grG4\niIQVIKpuqha6f+V31ysR7SrHDY19Vkw6hMm0HuVhIkGOOM+L+AkoRzalGpA+31snwCJWE2WiVvtd\ne4/6VMu0L81i6QAAPJc/mRPd/9orLxftG9eu2eskq9CclqiOrSwX7VlXc7Xfk2Upbu/uCC265awd\n+7Q8x4Umeu57rT1ZWvBIMFcNJG7XnA3j2toaRkMV8ygUCoVCcSjQF6VCoVAoFBNwpNTr9U4JrVYF\nm6mrhBHK1NcbiUopz6g2mqODjq2IevUPf1aUqmWqnnH2tLWj+9K/93PFtv/rX/1G0d5ck3OstixV\nMRhIZY8IMp3f7kv7ynWnoqVcunxeFFwzi0KfZW7Kb8jmLCN6LTNCe4wrPLTIKq0cUhUVqmvYNZZe\niEkxmWcx+oHQEYqDYXa6jnK1htW+VdSlqdA/zVmxLwzo3u5tWkV0e09o+zhlVaFViubZu9QNJWo1\nqtgYH9P3wP4KO57jXqtUiaRWkdhK43ssX1AVBRNRnUxSrVYclTdLVU9OUG7wiRVbbYKLLQwHws95\nuTzHgVsumG5WsFd78OoMivvjxvWr2OkM8NjjjwEAKkShcnh5pCXNXKL1XbJC5IpJw77tP1Ja+mJa\n89yFM0V7YdHGQUonC4n+nXLVO/apZonN59zHV197DcD+ijX8eUzXk+U2lruUG9nvS7/Xc/Z7I8oD\nLhHdurcuy3a7LqcyzXJktMR3P+iMUqFQKBSKCdAXpUKhUCgUE3C01Gvbw3ro4dd+z1rCffy0FBBd\njoT2qVKm8sqyVUqtzAsddf6cJO2DrJdWXeWOX/oXQrc++7yostgyr5jZU2HbnCiztCTnSx09FlAC\nekJq2sST7eXxpVM1icGIzkHys8ApYH2iMnKqDJGQ237oLNJ8Q0nhsYFPbJvigEgGyGODqZqljtoD\nooJSoYguPyKFw/MVS8lubErh3HWy0uq4SiI9UvQxtZUlco5aYJWAj3xMrBTvUEL3hlPj9kdU6YGS\nv9k6r+Qo/BpR9dNUCHyBijwvH7PP2IXjS8W2xZLEd8cZFWxTIrlPashqTdTk9YY9x9zcDFpklaY4\nOJJRD/GgjUHHxoHH6lK2RaQE+9QZCrzxhhSw71CifeT62pBU2WxkkCVURWZsrUhmFHO0JDHu2npU\niL5P7Zs3b71jX+rOkJPhRY8qnLQcXdrdEso4JGo1cb8xoYo33V1RwCZkepAW++QAlHpVKBQKheJQ\ncKQzyr4XIvUi/M6zdnTzxptidP7FTz1WtM8fkzyyq29Z27jPP/1Esa1Mo+T2SEY/v/qvvwMAeO7l\nO8W2XkKWcJTDOM4J4gVdz8hIn2d+qVsQH5LxdUyjF2NE5DN0VmZ5TrlMAZlJk7F0tWpH/RHkWOSd\njZSEHGNT7YQEG1FjGslARk6Kg2F38y4CP0Aa29Fsn0acvZs3ivYs2dnNu1qM4VBmjBVyLe/79hh5\nzlN/crKnnLde385E//DTMmN9/FExu75xw9ZZ3dqVWntDyp3k/OPAieAqZEE2T/mb0zVhcFJ3PWub\n8htf25QaqcaJM5qLkhtcaYrYp9qQY41rXtanplCpi7Wd4uAo+QblwMPIzdJY7GcoB9bzOffR9iHN\nptyLMuX51p2xuk+xUSU7vCSWvu2NV23Bh9a2MAWtrjAeqcuZDCPKI6ZrKUUi8jEuLnvEiGxsCyvT\nI2GP737bDBcAILZnPINNyIA9S7laBCWROhN3YzwY8+DzRJ1RKhQKhUIxAfqiVCgUCoViAo6Uep2a\nnkF1fgHbO3bavUo2RV9/4dWincan6Vt2ur5AVTeMLzTBt7/7/aL9G1/5BgBgmEluGQKqzuC9c1yQ\nEnWVE3WVUaHHMY2akkCHF5MNJwu52mm8IO7T4jpXQfHd9Xi50BspiYsyqkgx5mSXl4WWbjSnsFNK\n8co7fpXivWB+fgrlcgm3bljRQTIkupRo+auvv1a0W5GNNY6sbib3s+uEBlnK1KvEmU/1/Ma5ic/+\n/m8V236sJvHyhIuX/pTQniy2YBvIgRNDtFKp+MEio+uvSp3Lzb6l7wehXEtlUUQaM8uW8io15bny\nycKuOiXCt5Kr92f8YP9zoTgwjPHheT5SJ6phe06Og+GQ6FAXfxXqrzxauuq7ihvDbVmuutkTAU5G\nMWVcP8jVb9iSMyzb6/HorTIayfc7O1R1ZNBx/8qSBVcSKVNfHTsRZgz5vSxiG+dUZiSKNLR0lhAt\nnaf2uFFokKcq5lEoFAqF4lCgL0qFQqFQKCbgSKlX3/MQ+D5CV/g2GQh9c+2uqDeHXSETP//JSwCA\nyvRKsa01kCn2737ru0V74JSFcSLUV4nyg3hqznltxfWRytQwDzB2AyMK1TC/QG1TsvRUpSI5awHR\nHjGpVtuO9kiJ8h0mco1TM5JnuuRsxOplOVa/3UbckxwhxcGwdHIJzekG9lzeYPfWJn1KebFEo267\n+xVR7IxI4TpWAiK/t4WdybkSiP33yovfKbbdbEssL7h8XVZUp0RRdUhtu+Zs5a6QGvcWFWvuVWk5\n4KR9tpbOypJHeVro1CK+ScFYJ0VrlRSwnnu2c+MhfwhVoeL+6HV2YXwf/bZdslq/I/3ncCD3NqX7\nPK4ew/0Ox4/nKMqQrED3q/RJwerUstw3JqnE58BVIhkOpU9q7wlFysLvWsPlkFP85tT3DbsSt+M8\nyRYtk7GF3TgrwbB137s8b+OKKyZ7uAR0jWSFQqFQKCbgSGeUeZrZRWcnWMl8me2NaKF2vSMjomdf\ns4vMf7Qno6B2LovVt3ekXXKj3KQnxxoM5VjVKs3yXH4Rf74vF4kWysfCnZxmjlx/kF0tOi6XZ0S1\nLXl2yaO58eyxS45B9WmZRU4vSP22UWL3ee1VET2FWYre1hoUh4Nas4nmzAwWlqw5+SrNKJlgYC/l\noctBjGlbSjX4UryLGboDO6qMTxLTaLm7KW44XsmKanzKMbtDOZnPQ2L5SuBiqy7Ci9oJcdBZOHas\naM8tWEeeUk3EOiO6rtyNzksBCdS4zcI196x4vl8UNFAcDrZWb6C9u10Y7Kecy82OX1RL1PjjvEH5\nPKLCC9Vq9R2fM/OWkJin07EzOxboZMSIeMZeT0azzKgkMbVIMdftWJedPcoJTrjoBIuI3IPRG/Es\n8x4zZE6XpP8J6W/ju+ex12sjHsnzcj/ojFKhUCgUignQF6VCoVAoFBNwpNQrstz+56gcn6zAslxo\nmpRq9F1bt9TqL/3ql4ttP/FjP1S0r94RaqrncmQypkW5NhpZKFWdMCGqCG3ab1NNQV78dhRpSEIa\npp543zENxdZ4fc5Lou3jfadnJGdtbklES5tbYhW1u2kp1t0bbxTbLpw9u9/zTnEglEoVVMo1lJyd\nV0jG32lMxvUsZigs6Og+cHrWeOf83jlbGVFeuWt3iPp6leimKVeH8tWB5EC+RBT/NuU5zp48CwBY\nOSN01/SKxFmJ8jO9zJ43JgGEH9Bz4wQ6wT4LMrJ43GfnaLd7xoO3TxGnOCi8bAg/85G5Z35fjiPf\nD1oi8nLb5lsxpNzaJLbxxRRqus/+TTAWJYYUBz7VowzG+eYkyuG6p6WK5LTvbNlr6LalbwyJqt9X\n/MEtjyUUn7xkUcQcCYMMPW9l6qs7rrBAr9vaV4PzftAZpUKhUCgUE6AvSoVCoVAoJuBIqddmo4Hm\n9DQGzqqr2xe1Z+RTrUeauo/zsr767ReLbVfviN1SqytKqe2OVQsmVFChRhRTQpRWqfROOqlcEcrB\n9zh/yO6T0rgiIQrVZKwQtMdIyXV/FMsFVciZf37OVlqYmRe6dUQWdkOiLfolew0ZUR3dQR+Dh1Bu\nKSYjSVPEaYJu38ZnY1ru1aBLeWoUR6mjiPa5YdH/mCKk7k1D5kR55S5Pt+sJJfR7I6nBd71nt29X\nJUaCpZNFe/n4QtE+u2DV03NTUvHDo2ehS9TVwNHHAVFUZaomUXa2dEEkf49yRWjeEsU025spDhdZ\nliBL40LlyRVp8oziiCTYYxqVo88QRZm65R+flLDjvhHYn+fouX33rSyQ1Wca22ckJdX2KJRj9aku\nZLdjKdd99DFVHRlQnnvxe7l2Jf8eR73ytoDzM6mP3NmyyxbxqL/PsvR+0BmlQqFQKBQToC9KhUKh\nUCgm4Eip13g0xHDQR8m9noeUmBr6MvVPKE85H1fYqAhtdJ2Urh7RRYmjHJi6HVCBz25Xpv5jhRTT\nDLVIaKMKqWE9Zw0WER1Vqcr1cALupitqmkG2BaGMR2aaUuR2adYmkC8vixpxlyi+NiXjdlpWrTU9\nK/tubmwiaUsFFsXBkGQjxOkQfmTjaGZB7lVcp/gkBey4GRMdy1UJxq5ynABt7qF0BQA4Wj2ggrwx\nVekYTtl7f25qsdg2MytWc/WmPM71qn0uSqTUHlCFiREZFeSOLvVD6g74ulx7v9qRDDnoe35Bz+X7\nzRQUB8YojpF7fqE+5djxuToILc94js5nRai/r8izP95YbGNqNr+H+UBKdGtMMeW7ih5xh6qX0Llq\nZJQxplxZGT3sy+e4By2avYtyfHxdAVc1IROM7bvrcr3OXs+eVqlXhUKhUCgOBUc6oxwNhxj2Byg5\nWyXyZUYWywIwucchc/lpbHKbkd1dMiIhTeoWdXMW13CNSRIJuVHTzo7M2rbpGpp1mU1MuTzHJo26\nypAZZ5rJLDBw6g2/JNfIhsUlmi2M9016IthIerJvZ3dLrt0JgspkTzXwfeAeNTYV7w1+YOCHBtOz\nli2ok2gmpTjjGWXictpymjF6bJLvxqI8cmZrN48MqIPQnqNCs7VGgxiIuq1FWi+J8K0WSTui2Bi5\nZodyQftk5p5SnlrZzUAiMv3n2eN41rFvpkHP1Yisx6LItqPQfzcfeMV7RBBGCEvlIn5CFtrwvaF7\nO446w5OnfeJDFxOUO8liNa5zmcRjCzsyJ6e6kGnfCnASEvPU6PsVEpaN7episu98t7zbgoFhER39\nnjFzUaP+ubsn/fre3i7vbM/lBchMBtzHYrK4tgfaS6FQKBSKP6A4qhllGQD6Ozatw8vsiKPfFi47\nI3lzxq9vzw0BEua3ZRTCTjcjN3NjDt0MZJTNjhOZGyUntIaZU3maYSajol5uz+fxNfRlFsgjrG7H\ncuA84o6pPMweGVcHzlUl3pP1zjalzPQ2xfA8duuVnDIS77WQdAv3HpniKh4WZQDY27Xx2G7ZkXG6\nb02FJPfUvveMkg2dxzNKORlXpvd8Xmey/8Y0y+RzeS50uqFcVyUUGX1AsZGMm6HMOAc0DE9p9F4K\nbeiEtM4VkdF/ENm1+agsKSFl+rxM6/UVlzYSBiXcuHat2AWKg6AMALGLx/GMkt14PHOfGSUdjNfI\ni6ahWeS+9Xaaxbm1wJhS31Lq+8afZ9T/JpSa0W9Lnzl0qSIxPWPmXWeU7vi0prgvHcttH9Jv4OPy\nOut49pllGaeH3Dc+j+pFeQYA3vo3/+iITndw7N1/lw8bzgD4+gd9ET+gOAMA3/6337nPbor3iDPQ\n2DwIzgDAzurND/gyHh6jDcp5p/b7gYeRNb6tqs8Z3Cc+Tf4uSqLDhDFmDsDPALgGYDB5b8VDogx7\no38zz/Ot++yruAc0Pt83aGweAjQ+3zc8cHweyYtSoVAoFIofVKiYR6FQKBSKCdAXpUKhUCgUE6Av\nSoVCoVAoJkBflAqFQqFQTIC+KBUKhUKhmAB9USoUf0BgjLlsjMmMMZcm7POXjTHvb8KbQnEPfJjj\n80P7onR/sNT9+/b/UmPM3/igr/GgMMaU3O/56Q/6WhT3x0ckJu+XD/ZPADx5BNehOGRofL5/OFJT\n9IfEMrV/DsDfBHAJ4sbUudeXjDF+nufpvT77EOLenk2KDys+8jGZ5/kQIJ9FxQ8SND7fJ3xoZ5R5\nnq+P/wPQspvyDdreM8b8jBst/ZQx5jljzBDAp4wxv2KM+WU+njHmF40xX6b/94wxf8MYc9UY0zXG\nPGOM+dmHvU5jzMeMMV82xuwZY1rGmH9rjDnhPvuMMea3jTGbxpgd1+bR0FXYEdS/dr/j5ffyt1Ic\nDX4QYtIYM2eM+RfGmA1jTM8Y84ox5t9/226XjTFfded41hjzKfr+XzbGrNL//x1jzDeMMX/FGHPL\nGNMxxvwfxpgaFB8qaHy+f/H5oX1RPiT+NoC/CuBRAK894Hf+JoB/F8CfA/A4gH8I4P80xnx6vIMx\nZtUY81+92wGMMacBfBXADoDPA3gawD8DMHZirwP4XwD8IQCfBXALwJeNMeMK0E/DjvZ+DnY0+LkH\nvHbFhx8fSEwC+O9hbbl+CsAjAP4TANv0uQHw3wH4bwE8BeAGgH/+tmO8nf56HMCXYG3UvgQby3/v\nAX+T4sMJjc+HwIeZen1Q5AD+6zzPf3e8wbyLCz19XgPwXwL4TJ7nL7jN/9gY82MA/hKAb7ttrwOY\n5AH4nwG4A+BP5+IF+HpxYXn+b9523r8IO9L7EQBfAbDhPtp1o0DFRwMfZEyeBPBMnufPu/+/cY99\n/k6e57/tzvs3AXzXGHMqz/N77QvYgd+fHvthGmP+cwC/aoz5a3meP4wXteLDAY3Ph8RH4UUJAM88\n5P6XYQ1xv2b2R0gI4Bvj/8nz/Efvc5ynAPwuvST3wRizAuBvAfjDABZhZ/ARgFMPeb2KHzx8UDH5\nDwH8ijHmhwH8GwD/Ms9zLouSA/ge/f8q7Ch+EffutADgzbeZRn/DXddFAFpy5QcTGp8PgY/Ki7L7\ntv/P8E5aOaR2HfaGfAHvHP08jDt//z6f/4o77y8AuAm7CP0c7MtS8dHGBxKTeZ7/mlsS+BKAnwTw\nVWPM/5DnOSseY/6K+/e9LMNoRYUfXGh8PgQ+Ki/Kt2MDwMfftu3jAMb05vcAJABOvW0087B4EcCf\nMMaYd5lVfgbAf5Dn+W8BgDHmAoAGfZ7A3kz/Ht9VfLRwVDGJPM83YGX0/8QY820Afx3AQVIDzhtj\n5mjU/hl3rVcOcp2KDxU0PifgoyLmeTu+AuBHjDF/yhhz0RjztwFcGH+Y5/kOgL8P4B8YY37eGHPO\nGPNJY8x/aoz5ufF+xpivGWP+/ITz/D1YEc4vG2M+YYy5YIz5s8aYs+7zKwD+rDHmkjHms7DBUYy+\nnCT7FoCfNMYsGWOmDufnKz6EOJKYNMb8LWPMH3PffxLAHwHAaur3kpI0AvBPjTFPGmN+FMD/COCf\n6frkRwoanxPwkXxR5nn+/wD4u7Avsm/A/vF/5W37/DW3z38De6N+A8BPwxZHHeM8gLkJ51kH8BNu\nn6/B8uF/BkId/BkAKwCeB/C/wiq+3n7z/iqAn4Xl378BxUcSRxWTsCPpvws7A/gd2Ny5P8Onudfl\n3efyXwLwm+6/3wDwTdi4VXxEoPE5GVq4WaFQvCuMMX8HwI/mef7ZD/paFIq346ji8yM5o1QoFAqF\n4rCgL0qFQqFQKCZAqVeFQqFQKCZAZ5QKhUKhUEyAvigVCoVCoZiAIzEcMMbMwRrWXsPDOd8o7o8y\nrMnwb77NxknxgND4fN+gsXkI0Ph83/DA8XlUzjw/g3c6wCsOFz8P4Jfvu5fiXtD4fH+hsXkwaHy+\nv7hvfB7Vi/IaAPz5v/BnsbKyjOr0aQBAyRMrwVqtUrR7o6xo97stAIDnybaM8k99I+xxyQ/dv/Sz\nDImV2PPBbU65XintmmfvPJ8fiNOcZ6R9L+d9s++8cqw8z+6xr3w/DOVvEnpkCZvbtgnl9w5aV3H9\n5m38rb/794H9Sb+Kh8M1AHj08TOo1coIaraU3fZeq9hhryU1b0c9qRvbnLP7+lPTxTYTUDx49n4l\nvaTYtPbqW0U7qMn9Xjo1DwAo+fL9PJFYTlO7vTktcTF/XMycPIr7PLPn8wM5frcl17CztVO0ExeS\nH3vijHx/JM/FN775LABg8dhisa0UyDVsrm3KNZSrAIBquYbuXhcvf+tlQGPzoLgGAP/Fl57GybkG\nru3Ye/fs6zeLHSrlctF+/JTUb27kNmbyvsRsQn1eULUV/zzqRztdsYGNIuqD3D6dgRyrE4+Kdjru\nf6vyLLT6Ytu6tUPVtIb2GmoBH1+aKXXG/cSeIyqV5PNUPs8Se6xqKJ/PTMlzsbolk8VBLM9AZzDE\nczdXgQeIz6N6UQ4AYHn5NE6eOo3q8lMAgHIotTWna3XZOZYbuXbLdip5KjcvZKteeh9Fng2WKJCg\nCeRvh1EsrIXn2xddv9crtvm+vPz4hTUa2ZvtedSBZXJiz5cgGwdWkqS0r1yDoYAMAvvnn5mZKbbV\nG2IF63kUDK5tSnJde6sNpGF1/L9Kybx3DACgudBEc7qO6uISACC4tSY7JNI5zMxL3C5fOAYA2B3w\nAIieeHeP9+7IiymnQV9jQe73qQv2RRTk0nnstSSORol9Wa+cWyi2lauybyZ9FlLXgZVqRXwgLEl8\n9/ryPNUiO0h99LFz8nlHBglf/7q9hiF1kF4ksdloyLNbW14BACT9FIn0SRqbB8MAAM6eXMbFY/Po\nvdwGAHzhk5eKHWan5R402Dm6Y+9dnkpMVmhSkqW2rkOaSpz1G/Ja4EF8MnQvvaa8hPYoJrpDe8OD\nilxAOZcXZdCU8w66dnstlG0hPTb8Mh+5wWJvIGGUpfIMTbk+c6ouz1K9Ks9oANl36L6X5xm2Oz3A\nvijvG58q5lEoFAqFYgKOtHqIyVN4eVLQnSlRkqmRl3qZRjRzp+3o3mvJiLzeIxqMRjRp3c4kM6LB\nGpEMU7xchrieo8RGQ6IOiG4tl2UqOmZROeeUR1rcHh83oSl+9i6TjcjRYpVKhT6mc1C1mQyp+5fG\nNsa8NwthxT3h12sIppoIS3aWVm/KCLW2LTO3pROzRbvSsCPX1khiMiC6E56N5bQvFdkCuoW1urAf\nsZuCeTmPvPekPbLtLJmXbS15brbXxEbYj+w1LJySYwX0LAy7Evfliv0NZWIr0oHMCgY9G4ejnsTm\n0pz8DcpNmc3ELj5Xr99BryNsjeLgSD0fiedjbtr+7ZdXhFkYDYUhGO21i3ZnaO+BH8kMKyVmLBvZ\nmCsTrQmagaVEC4y/Fg8llqvUAQUusCNf4iQO5FgbQ4mH7sD2Z76hpSaKvwrNNBuO6WtUpD8sR7Kv\nN+5/qX8eDogp5JUQtyThGe+hXn46o1QoFAqFYgL0RalQKBQKxQQcKfWaoooEDXiwNFbm0yJrLlSP\nT+2aU+M0qzLVzp6VuqGjTaG8Vp64DAAwG0JnDY1QDnWag7edmKFMVGcpp+n8nNBJnhPzkGYHwyoJ\nhmJS4cb2HO2aUFullggjgpOPFe3etF0UzxKhz5gWKWdC9xlHK3ipbPNTD36mY53DQn1mFlMLc2jv\nWnVeuS5CmMaMxMP0itCOHcf8h6TgLkdCG8WOd09IiBARbWQSiZ2dNRvLZY6zjtBoME7d50vsNUgE\nl8XyxdjRUX4gj3iWCHXl+e9UWvuePHeVkpxj+aQVLJ04ebrYtnJcFLBDonRvXbsFAOj1dzAYyrKI\n4uBI0hRxmmBxyapayyW53yHFRNYjbYpb3qpUJObyXPqmwMVBhZaaUoqTiJT+UcWeo9OWPpfVp6GL\n+/aeLAE0SJBoUomHdtdeo6FXUEiUryEaNQhtnzddleexxgpYR6cmpJrc3ZMli4TEodNO8ON5HkbZ\ng9u3ai+rUCgUCsUE6ItSoVAoFIoJOFLq1Uo0DUw+VvfJFD9NSHVFHKdxdOjAiAIxzIRONfNCAfXa\nllKIr75ebEsM5QwJO4Fu6KbjJEmNYrmG0U1KRoozd/Wy74DUij7l0AWO1RguC9XRX5NE24YRpZqZ\nsupFVtvGRFWErE5ztILvUbKwl8M3Wv3lsBD5HkqBD+PopsXlY8Vne0NJqjehPDbDlqWTIk9iJyQ6\nfKyUHo2E7mIRdGtT1NwVZ3QwKBNVNCcK7nrDxlybcsx6TNtXSant1Iz9lqj/ooieq1Dipuoo5pIn\nz0pzUWiuRz7+iG0QDZdX7p1HXHUU3yc/+zFsr+/ixqu3oTgk5In9D/ZvvNMSWj6M5N6QVwQqji6t\nV+nesWFLau/52KACAOqUZ8leKonLQ48qEv+DHiXvun59cUqWA8JY6NbTx1eK9uZww14r0aL7DWHk\nGtu7Tu1dkmOVSJHuO7WtR9O+UkTmG9RFjhXnvrdffX4/6IxSoVAoFIoJ0BelQqFQKBQTcKTUa5al\nSNO0sB/K+T1NCqQRGQOkLmF1qi00bb6wVLQri6LES3KnLuVp97z4HvaJbgrWnP8f2dZ1y0I55Etz\nRXtMpQ0yoQlqDaF/R22ht4ZORRZUSJ3aFXosmBOq2IT2t6W5UGYNoh98IukSl5hrPPbv891/isNA\nt9NB1AphHBV+88b14rMa+Uj2tkRRl8bONpHuS3dXVH+es5jbpzglPiuiJOu5U5ZmrU2LRViV7OHG\n3FJKKuu4I3SUyeW4nXVL97c2xOfysacvy7mWxTZxzMSVQllOmG5KfNdmmwCAfiq/IabYnKkLPTxz\n0v6d2p0O+h1VvR4mwnIZUaWC4cje57t3hXo9tiRK7FJF7mNhTcf0o38PsxTuV4jaZ6XqmIeNIjl+\nvy/U655L8p9ZlGuZI+V+3pRnKDF2++aGPEsn56TPjWh5Y2vDPk+hkWMlCZux2OcipyUAVm2XSZWd\nufdMFISI/Ad//emMUqFQKBSKCThaMY/V8iB1M7OM81jolc0GvaHLHStdeaPYNnjma0U7eZpGPE5Q\nkeciRIhoJjqAzPzqq3aU4lM+TlajkRQZU6exPUaDhBXhbSpf1pG8onDJLTLflM8DsvgabLxYtP2q\n3Z5dktzKAbn1e2TxFyVupkp5d3m2f6FacTD0+gME3R5iZ1p+7fnvFZ8dPy3CnkaNzfxtrOUUhq2W\n2BObtJAAACAASURBVInBjXzHVmEAUKfvn33qVNGev2BH1D6L2chE/+51y5jcfOVWsW22ITPDx594\nsmh/9yU7G96lPONagyuNkN2Xq+RQnRaBRLlERuc1Ozqv5LLNUP7c/LQI1L73kq008trLr6PXEasz\nxcFRqU+hNjWH1av23o5INFYuS5+XUkWPfGyKn5G5OX1ecYxHQpWKIup3Murbosgdi0VdpMUZ9ezs\nsDUi0Y2RV8wsJQh/6rQVMu40ZOaXE1OSB9LuRfYk+4U/8nu6rtqJR+xghXIuefu4AlTgG/geq4cm\nQ2eUCoVCoVBMgL4oFQqFQqGYgCOlXgMvQOiH8JwAhWuKZZQ/GND7u75jp9XJrTvFtiYJK9p3pGbg\nqGyppRwynTdr60W7dowEOM3c7StCmwqJD6JdWSgfuCoeyeaqfD4Q+iKhAr+lbSt8iPtUu7Iidf52\nr0qx1ahiqazGigiSyIkKOeVMDt1qfEJUxijLCos0xcExGA0RDPoYuZyyIYnKasdEaFDJyD7L0Uxc\nyLtORXQ3tm2e5IAK556nAslnPnG8aA+dtRixrWjfkdh6/evfBwB0qIh07TJV/AAVlF60orES55YR\nvUYpw2gctyK29SHl+1Jtv1rF0lgBCTOKas8AUrLOe8sVE7775jriWJY9FAfHKMkwjFNcv3EDAHD6\n9Jnis2Gfau1SnzAWjnHB+EqVKsq4GqX5iKw8uTKSTzHjEh251m4tkkAaZjZOMnoWcp/yi6lf911V\nEp/qqV69LX15VKdcThfig4FQ+X4mcd92NYVLtIzGRZ4zWp8a2zWmaYbsIfpOnVEqFAqFQjEB+qJU\nKBQKhWICjpR6DcMSSlEZue+mzRlJBUmV5VG7E9p3eeeHniq2NYNPFe1eWyjS2Cn5TIl+Fvk5hZRf\n1E0tzcU5bXFKbvxUSaHvrL84Y7FPytweVXiouXMMyC6sVBe1IKsUU1fgt0PO/qBczwpRWom7TvrT\nIM5zJCp7PTSUKmVU6lV0Nq1d3fLxE8VnZ84LfT5TkXt4482rAIA7b0nO5ewC2S06OnS0LIrTE49I\nbq8Xyj32XLFkk8hNfusZUbh2t+0yxOWPybU88sOPFu3VG0LrNx3n+sjTl+T4TSqMO015wlWXJzyS\n/M+726IaNK7aD6sEU3o+2m2hxDbWrdo7y3LoqsDhYm1tAyVkWF60VnDcH3WpSHadYipzywgh5U4m\nZFfnu1eAD9k2pLzwkG5i5vLTeyO53+lI6PWRW0ob0WulHQslPFWW+Bs76jWoaP3svDxXtTl5Xnqe\njantnsQnF5SenrXfY+o15+ojFKv5e+wvdUapUCgUCsUEHOmMslIpoVarICnbEWqcUp6VkRlaQqMY\n42qcVZZkhLHXlRHPBgkbjMuXGfWonhqLX3ble+PaZSWqDbhHeZ1lcoaAZ9sZOfMMezwblhFLq29H\nOpRKhGogv6dx4mTRLspxcs02HrtQ04ytNWhElOXZex4hKd6J0lQNldkGoh0roPHAAp1m0a40ZbZ1\n7lHrdrN2Q4QIa3clh3bZmed//GMy8ztJZus55cIlno3bN166UmzbuLFRtJfO2nzFR3748WJbY06u\npU+CjmbDjq5L5NjihSzMkBH53Sv2HCcvieNVP5FnMxjHJ4uBiNrY3BCh3c6WnY1XvCqMp1PKw0Ru\nAuQmhO/Ze9ehOreLUxKfUcD2XjamQupf25QbOWak6qHEepVcmWLK226ntq8cRjxjpZzMpo21lHKG\n9zblWYhbEp9LztTcT7kuqjB+IeWFlpvO4P8WFRAIpN8OSy4uvXc68ACAobzkeGiv1/cfztFMZ5QK\nhUKhUEyAvigVCoVCoZiAI6Ve/cBDEHqoNOy0utMTCiCg4mAp51Q6OyUv53p+0ja+TPPHi7Y8qY5H\nQrdWwpD2tT89JDsmFvDwYvFoYHnUhIygwwpN84k+iNxCOtckDBOqFUfG1eP6lmWyA0Mq5+X6bJn7\nHx7ZGBg8uAmT4n4o+QHKQYjQ0YoJWWZxzq8hiqfi7N3OPy6G48989VtF+9Xbth7jk58TunRIgq2w\nJcedy129SYhV4uOXLhbt+YuWGg1rIlro9sQub+G0fC+assfqUyrjbEXi8M3nhSq+dcPmGn/uEbHA\nyzyhycYsVu6JKC1OhfbLYnnGMidyy0xa1FBVHA52Wx3UwgDrt6yA7KnHRKhVJqPyhMQ21bHpPvUr\n01MiNoOxsRR5slbE+cMUntiCpWT9qny/UpMeaXbZxWdb6NbeSOKovSl5uuHAxkmfahInnryOdvfk\nezsuv32DrCFPTMsyQMc9A1zXN6RlBi7ZG7l3gGfMPiHn/aAzSoVCoVAoJkBflAqFQqFQTMAR51F6\niCIfUdmpSKkOY4UUT4mRqX97z9KsKamUylOi5FuqEY3gqB4DVpHK9NpnCyXnExYF9/8T5I52Y+o1\npeoLbA/luXbEBDB5kg295B2bA6IMUlAFE7aSyly+EwvafA+er2Odw8KsV8aiX8W1nqV9UqKrxmo5\nAEjJwstzFmAnLp0ptq1ek5zKtU2nrj4m+WJbidTgW2zJsRqpVXbPVITivPDjX5DrO2bjvtUX2rNj\nhM4akoo8uuMo0K7EVqdC+XFkM3bhE5Y2Ls/Ls7S1JQrDXmz3rUfynRIteZQp1Md0VqfT3kdXKw6O\nb33nOTRKAY7NWgp0qiH3a3NdrDo5r/vUSWtl2KxSlQ6iIjPXr2zvyfcTSusO5kWhffLYx+3xW0LT\n3nF5xACQdF2VpaqoZks1ifu9tlxDVrHXPshpyY0sD7fXJca//4Y9x4Dyi2NWtY6XQgznilIWBS2j\n+W7pyzNGLewUCoVCoTgs6ItSoVAoFIoJOFrVq8kQeCl8Y2mssi9z/N11oZC2O1KlY2PVWnjNNMRy\n64nHRJ0XlmVqP66wERNl5tEUnalXz03XPY+L5FLFD+In0kJ5yzJUTvQn+z0vHB+MjiVT/IC+N644\nUXwHQMhu+yzKGud8EwWdegbRQyi3FJPRb3fRKZfQ7VgVHbGTaO0IXZqTfeHiSWtH55E94hOfEbvF\nJwfnAQC+L7RSf1NopSWqvlAdq6d3RA2+9paYD/i+rTTS9CQZ20/lvMOYCn3vWHosCmTfzTtCp16g\n6iBD2GsYtEVpGFBC917XqhiHpFBcnpbjZnTewNmcHVtawKA/xLW35FlWHAxX1nYRGuD4KVvse4bU\nqz7ZgdbOny3aTVc0vr0n9344kH3HStHNARU9Lgv1Pz0tdov1ujU16G1dK7YFvsTMc88+DwDY2hKT\njDPHpd8ekkVo4Ns4adbkXG2i+3f6ZKwC28dnFH9rbVHATrulvApP+3J6tZGlX+qWA7I8xiimDIP7\nQGeUCoVCoVBMwJHOKI2xs7bAzYoyms21ydx8Y0NyvHZ3bB7a6y9+u9j26gvfKNoXLjxWtM9csDZh\nM/NixcW2RimZAcMtIvN8zPc4A1M+CVyuJc84eSE4oxnG+Hs+5Wfy3JNnqveyn8tJAMGG5+OWIaHT\nYJRgmPC5FQdCOYKplrB8wsbPcCij5TR+Z14tAOys2dHz4hmxJpyZE7FZbds+YsObYvN2PBK7sdgT\nAc7I2BHzsWP0Oc3W4ptWcLER02ibGIYGjc5rFSsMCiLJJ/PIgq5JhSo3t+wMd3RNZrr5rMxUq+4Y\nPg/ZKSd5SCzJmcvWsP3sqePY2WrpjPIQMTc9jUoYoOTs3e4SM8HsU31a7D6HzrR8X13IisTBTtvG\n1JBmYMsk4IkCYexat20dzNG23NNpys195IJlT14go/S5FSkswP3d0Hl8hnWyYNzYLNp7VL915Gz0\nhmSNB3p3VJ1YpxTcg9kDMKRnN3Z1VP3AR6wzSoVCoVAoDgf6olQoFAqFYgKOlHodY0xLlstC7zxy\n+ZGifeHR40W717Y07EvPPltse+673yzaX/uq5Ky98vL3AQCXHv14se3iZanaMD1DFl9OdLDfRZ6J\n2Owe24U6iClPJ0vIJ2y8jWztUhIBZftyPCfDMPVaCH/kliVZjjR7J32reG8oNSooT9cQbVpqqtKU\n+OR827EQAQB27tj4XFwR0UPKtf/2LIUU70gO43oqOZlhWSixpqs0QmX7UG0IDTvoWapo2BNKmIVF\nHcqf6wR2H59EOfCF5ormpPbfSZeXzJUgrrwmdTBnlmwu3pAqTHT6sq9P3UjF1YId5SPE+TufC8V7\nxycunMZCs45G1d7HZ55/rfjssUunivbSiOh6Z8M4oPtVohqQZSfqWqY4m52dp+/LPdy7Y6nXtCuU\n79TcYtGeX7LLD/PHZOmrMUV5lHsiiIscnb91V4Q/XOWjqAgCFMtnVaJpPaqGEjixTr0uz2t/IJ+P\nOE/d0bRhnj/UspXOKBUKhUKhmAB9USoUCoVCMQFHSr1mWY4sy+A5dWlOhV09Uqf6lF85PWen85/7\nMZniX7ggeUK/97v/X9G+etUqZLvPiWJqb2+3aD/5MclvO3nSHpdpNLYmYyf6zKllc9avEi1qDLfd\nv5yfSeMRZkrHOZz7cjbZVmmf6tVz399P6fL/Kw6Gfn+AbreHxKn2qOgLElJMp1TtJahaaqm3J7Rn\neUrUp4ErUPvZH/vRYtu3aBnh97/7XNF+0lUKWZqR/Lj2luRUTjk144mlFbnmrny+tSu5yAXVRlaL\nd7dETV5tCLV1+oK1sDMD+Y1nKQ6vba+73yJqyO5AqLxrb7xZtK++/ioAYOXMjyDqamweJo41azgx\n28TqulWH9ke0/ANWN0vgRqGl9nsQdfXWtuQr1mftclStLrZzIVUiKQVy3JlTVsG6dZcqLpFdXeAU\nsAGpr+NE4mSqIdvHfV+3LMdfOS5Lbi0qe1N2z1g2YuW5LD9U3HNxnL+/J0sdN+6IPd8YBgbJQ9Re\n0hmlQqFQKBQToC9KhUKhUCgm4GgNBzwPxvPhGXtaLxCKNPTZMk6m9uPixh4V4rx46WNFO0vkXb+6\n+n8DAHY2Jbn7jaEotO7eFpXY+YtWZfvo43KsRaK0gkDUiElszx2TC32aC+2R8/V695jOk4XdvUot\n57yNaBM+VD7mbM3+pFrjfSDC5Y8k4uEAo34ftaqliGII/ZOV5R5WmkIhVWsLAPZXGmEDitsta/92\nkYrdfvrJTxbtZ559uWj3hvYYlYokjJepYsd4eeLOnbvFtlJJlilOnzlTtHNXfDokperJjth+rdIx\nrrxir+HS458otp2flULT29+yysRtUu7GVB1na49UkDNWMXnu/HmslTYAiDmI4mComhx1k2PFUZh3\n96T/7JESesAWdePKR1SEfHtH7pfvYnmuKjFdJlvQNtG0kTMt8D35fNSXuC9NO3MDokVzMh9IaSkp\ndIYVizNizpFRsfs2LSn0BpY2vrsly2gVclio1lbcdQtl3JwW5e6tTfne+LfPNyKkSr0qFAqFQnE4\nONLpiGcMPGPgu1mRTyKYiP3G2UrOzaRyeqePaJRy4uSZon3Gjai/c1cslpJEzrGxLiOLDTfrfOWV\nF4ttZ89eKNrnz18s2ktLdpG40ZCRPoyM5Ae0qJ6O7PlCsg5jsQ7nUY435+bd6qKRSMiJdvZZ7sFw\n1UvFAeED8JGjWrej6+acjLKHZDodRWT/dsvGWm1eRsZ7dyT+ypGNk2++/Gqx7Ueeerpo/8l/508W\n7VvXrwEAUorvMtUcHN/8Rp0EaJnse+eWiHWiyAkgKMc3qEjMLp1YKNqtLTvT3FyT3MkrLcl5W1k+\nY69v7VqxLa9LfJ+6LDl81162tQPXbm1ia11mI4qDI8iBMMsxU7Ezu3JF8sJnm9LOSeAXOtP9qWm5\n99fXJD5bXXvvLzclj/LlF79XtDdXRQjzuGPhvFD27eyI7dz66y8BAAyxcfWqXFe3K4xG6liX9lCe\nqzdIdHP1+o2ivbZtY7FPs2KvKuco7ERJKFmiYgPNOTFmv+mEUFG3h25fBE73g84oFQqFQqGYAH1R\nKhQKhUIxAUdMvWbw3X8AABLHwJDd1b78wTEtae75OS/gNpwN0z5BzbvUmDS5PXd7R6b7z20KdfXS\nC98p2rPO7mt5WSpELK+coWsQSnZuzi4sLyyJpZkhS7OMRECJs8FLSOyzL4+Sf4Zb6ObqInmWichH\ncWCUSyVUKxUkzn5whqy8vKHE52AkYoX1265eKt2GJJacysqKzf/dDuW+f/0FyZ380k/8dNHOnWjh\nxptSg7JUIfp3ZHPSji3LdZVK8gjvtkUAUXbUk0nluu8STZZS9ZBKzT5D/a7QrfFQhDu/+9wbAIBr\nPflddaLypuZE3HHiss21m19aQppoHuVhohxEqEZlpI5j3GnJ/TCe0IslsqMbuRqQyUBozwHF8s0r\nNn6ffExsPzsk9plvCvU/65YXbr11s9j27AuydDW1ZPvJrfWtYtvSguTebnYot3HD7tMiEdKd29IX\n93tCyY7zKFnoOFWT32hc/ntzSnI6QdTszLwsM4xSuwTSGo3QSbR6iEKhUCgUhwJ9USoUCoVCMQFH\nm0eZ5zB5hjETyWpPQ5QkV80QTzhWconirk8VE9acmmt1VSjUvZbsG+4rcmud6GtE3VbJrinlXLhV\nS0+8ce2tYttg8JWinaQy3phzRU+ffFIKSl+8IJTtwoJY8TWnLIVWqgiNkEOuB0TDFu56htS/MPAe\nIhdIMRmleg2VqSbSfFypRejFO9evFu1Rjah0Vyz27g1RjJ44I9UTRn1LLc0el/v+8jeeL9q1r36t\naH/iCau0HvSFQo0ov21+2dJgo55QY6ORUFTzs0K/ZWaccynPQjqicfGIKpy4fVOqiFOh6g031y0l\n5s0J5bu9KYrWZFfU5J/8/I8AAJbnl6DM6+HC9zwEnodWz1L02ztiWTg/kHsz4j6haunQgCw1pyh3\n8f/99a8CAC6ekepN58+I+j8lOr7lLBJ3tqXix3RdVK2f/+xPAQBuXnm92Pbqq9K+syXHuuIU0SPS\n7SepPG/LVOmp4qqCrLbk91ZD6SdDR0VzIajpY0L5thJWibttgz56Q7HXux90RqlQKBQKxQQcra2L\nSQGTIBvnRibkfkOCFjJogPHtyDan2ZVPtSJfePaZot3ZsSOd2YbULbu1KqOf5pTM3MLAjkiyRHJp\nmnUyZidHkyiwxwtLsljse7I4vr0rI/zr16zLSWtXZhjPflf+zBEZDp88eQ4AcGxF8tBWjsns89iS\nbK/V7cjQVMhs3SvB0KxHcTCUqmVU6lW0XS27q6+JqKZLQphaVcQBsQuTbl/iwafR7lvXbD7Y3rYw\nH8eflBH7l3/n94p2e2hH3J9+8sli23Agwotq1R43CiWeWjSbG89eAaDiZqJeKEKbUoXchagYwMjN\nJIdUe3BITkMnz50HAHSotmXLE9ZnZkn+HijZZ/ruYAvbI3kuFAeH8QyM76Fasf3RqZPSV5TZSYzy\ncL3I3tuM7iczJbfu2P7xf/6n/6LY9sd/Rgz856dFzFNZt0xH67bEHNpUr/KaZfSON4XZ2KjJ91+9\nKo5pxgl7ZheFfUFN+tcKkYqhy7f3RzID7LTkGtIFG+NjA3gAqFPNzRVic2YXbT+6sbb+UFyczigV\nCoVCoZgAfVEqFAqFQjEBR0q9JskIcTIsLOgMLbJ6hkyl6Ts57HZKRUSHBDyDvogZLl96FADwyY//\nULHtmRe/X7S/9V3JjWy5qX9K9dIWV2QB+HOf+1zRDsp2Sn/t+vVi2ze/KWbPjz8qwp3mlM2pvLsm\nIoq7d8WAOo7lfMvOhP3s2TPFtpTyJLttoa7GtTDDQOiJwSjGKH7wXCDFZER+hFJQwuqGzRO7/qqY\n6D/5tJiE+4HQ8m13v+pTkktb1IIEMDdrhRM3bkrsrFw6XbTPfkpi58o1S9efOyOU+/nTsu/AmZon\nVA9zcVlq8N25JefYcfUxI3qaErK72yEquORyznKquZlTbdaobB++bkvy406clWs8/dj5on17x1LN\nncEInZHkzf3/7b1plF3ZVSb4nTu8OeYIzSkpJ2Wm0+lM4yHtBOMR21UGigW0GbwKaKBdVc3qwr0Y\nqqkGarGqylDgbqCKBaw2YIrBLrCZDLiwoWxctvFEeshROUlKpaSQFHO8+d3h9I9z3t1fRCqfQhmh\nUGZ6f2tp6cR999177rv7nnv2d/b+tmL7KFfKqFSrGMZAdlckOKazJgFgCY2JGdwYsrYg49FpCjwb\nBvksLstY88cf/ljRnpgQ6nSvDwKao3rBAS07ddrufo/PyRLXQlvsLKec3751tthZkaUxS9E4VZLh\n2z/lnq1Z6oulPiTeVptNWUabo0CdWkXOOzXt+rYyfwGh3XoOunqUCoVCoVCMgL4oFQqFQqEYgV2l\nXi0srLUFjchq7yw7F9LrOx9SskS9VmsS1fqa171RjuHf+xFF9B2765VF+8Uvk6oNw6A9zkOcJZX5\nG24QOimquMjbozdL7coDh2+R/lCE1YSn4Fgub3lZKCumVvfMOZk7rkoSRkRHU/hv5qtXJPQ75cYi\nNypht1NoNdtYW10vIuoaNaF3DNGS5bL85tNTPsdrUWifNuU2Hr3RUZQTc1PFticee6Jo33pE7Czw\n0dUDK7RRh6THxn1/mqlEtw4SadeogsTiqst97K5IvuM42VktFtsKjKOupupUhzATKq/uKbXJskQV\nTuyVSMKFvtBnrdRTbbaELFXb3EkEcYSwFAM9Z4sJ1X2kkrhoLUtEaD7uKM71daFplxaoIshRt/wz\nMSORy2co93aR5Oye7Dg76Nclt3eOqnR0yq4Tx2mZ4YkLEi1uyhINvu77O+hT7Uph+7FAVUUSL8N4\ncFryPzkvNPF2duKEVByZ3SPLaGZczjs15mw8xpW9/NSjVCgUCoViBPRFqVAoFArFCOwq9drv9dHt\ndhH6iLzICl/AdFMKqrCROqqSJeVyEh/gwKXUJ9UacssHJMt14PD1snPuCyHnQmUGVr538rTIJXUH\n+dOOOzYhx+L+rKy5PkREodbHj8p5KZprec3RdecuyLlyqgZSDkRGbKjaZ6hob2+lh9W1rcswKUaj\n122h066gVnYU5z1ven3x2a233VC0n1oS6vSM55C6jwn12u0IXdr0UclzDaH1l3Khox5+UAo6f+Pt\ndwIAZhsSNdhcEtp+3FNPJhVaaq1D998wbe/+r1PCd60i1CpXCil7ubrcCA3WKcvntY472A37JcJ2\nKZJ9V9bkemJfVDjtZtgYv67YLrIsR5plhchEg+QNWdazSdTrUJXT0jrX0UNyH48dcdvnz4mdVaiI\n822zIggQltzYZakY+CRVKrnolywePCNR/qdXhcK3VvoVxu4Zi0Ppd0RCCOsUdd1ecuNjqyd2v6ci\n36sddPTx4pIsM5ykiPXrXyTP7sFptwTySBSiT++Uy0E9SoVCoVAoRmBXPcovffkfcfbsKaylroZZ\nPZKgnIzq3yXkoSWZmzFnVFePA2USmt0MRZ05IKbXl1lDlnE9SucJxCT9ND0pwsINEvtNvOh5vkGr\n3VyyHXiv05B4eUCeYUTC64F5+r4b9OC5NKUPuDA1Om5vAfPzkhOl2B7GZyYwvW8a+28+BgC4i/Id\np2YlEGZ8Wma+Je9MRSR/uHSBcoJzx56cfnK+2DZZk2PFc1K39GLX7XsdSXmFFBCT+Rl1OuA8OQlU\nKFEQW8nbVJdq7u3fQ+eSeA60fK7bapfyk4n56K66Yyx0xdYseRqGJNPKPtAjKCeIS7urkPlCx9r6\nGpYiYMV7jIcOHCo+m5iUYLEnV+Xmrs47uztyvQSNzR0Vu148/TAA4OwjwmwcmSAvMhdbr/k8yCQR\nJnCdakzmvs7l9ISMox0r42tCdtL3bZuInbVpjE9JLtH4wLMLbTnX3jF5RowfUxcuSBCS7T9ctCs1\nscO9U47ZOXbTjVhYb+KLZyQQbRTUo1QoFAqFYgT0RalQKBQKxQjsKjdSjiqoxDUkoaNcw1xOXy7L\nonBOQQmZp2EDyh/khemc8tuGFKalhJzcijtvKGfSemrJUAISxf0ggARJRKE7R59yeziwh3M8U0+V\nJSQtF4ZMw8r5hpRtEFx6vjIgqT7rj9ejfKlyuLQhR1OxPfR7fXQ7PZxpnQUADBIJSjhyvQRvHdor\n1NItB1w+bRiIzVZLEpzV99R/vynBL+trYpMvOXasaFd8nuTqRbmnc5FQq2cWHM97lgJ8bCwU1A37\nhDIbq7nAHUOyYF2qvhDRcsBQEjKl6iF7G1Q/s/0YAODBk1KT8/ojFCRUIjkxX8HkqSdPY+28Vg/Z\nSRgYBAiwf48L6ioHcj/b62ITZVrKWfM07QUjOYal6/YX7YaX7TzyUpLynJKcyuWzQk2ef8rZX4Oq\n40xUpZ3X/HhWFXto0Ni2TvKdiz7grTMgCU6qlINM9q0G7hwx1Q5OKXhp3geHXlyiOq0UpNn7igT2\nHPbykEeuO4RoUZ7Ty0E9SoVCoVAoRkBflAqFQqFQjMCuUq95OkCe9tFqu3yXWigRURRkhwwsT+Rc\n80EiEU8pSXghoIoHnmblCh05VSjhqguZz9PhiNOcQk6ZDbXWUa79nuTKbcjrpO/ZYVHqDTlksi/T\nxkPqlQuI8rFCosJST712qJDqvusaWLVKb+0U1pZWEUYBUm8bDx0Xuur6C2eL9j2vFinE2UkX5Xlk\nViIQQ6LXn/IRiNfdJlTmxTOS7/X441LRZnLKRaWOkw1QQYSi6sMjTz5VbNszI8edrQkdNTfpovum\nJmVJ46l5uZ7xmuRUTk67CO92W6LQF9aFllpu+4K967IUAIr07lLO2/kTrth1NbcIu9R5xQ4gABDA\n+sGpz4MmSVnOTErEfm3cUfNnFiUS9rP/IHbwsle5SktpKLTmvQ88VLQbtAyW+iWkqT1CzdYiGSjD\nNT/22UvnpjP1OjHmbC2ngbbTEXvptCUXue6jwENaRkgGsm+/7cbnvbNy3Qf3iYTd3gNCNT/00IMA\ngP3TU1hoyjkuB/UoFQqFQqEYgV31KC9cOIFkcBGPn3czi1pM+YVWPMNsg4/lFoaznHPTxNOKz/VN\nSgAAIABJREFUS8HTtg8VegCAUnM2zIKHATbGsBdpnmHfyB9fvMQBBUbkJHQ+FHcPaCZmjCxus/KO\ntbn/n05L3U1A1zHlZmAH7rit2DZRB9KgAsXOoNdP0OkOMF5xv/VjpySQ4fRJCexprctM9BX3uHqS\n01OSx7ZvVmo11qsuZ/L0yqliW35IAnBaFTnWett5iikFLTQpKKE759iEKLqu2LbSEuWTlAK9hka1\nviJqKDN7Jdin2xImYmXNtQPK8T27JGo7X3rcBfHM3iUKJyViYs48KvmVDe/VlmyCXlnn4TuJLM2R\nphmsD6a5sEI1Remnvn5CbDHw481YWRiElVQYjVPHTwEApkjk/kyblNFoQKr43MaAxuogE6Obitw5\nljMW8qc89VjYjczbdY9Yul6ZcienZd9xrxSUUbRluyvnGObVx8TkjNXFluvk9dZ9EFDe6yInQfbL\nQS1ZoVAoFIoR0BelQqFQKBQjsKvUq7ExAltG7KlGQ3mULEvHATZDdWdD7n5Ei7ohUZyeyURgaRsX\naiM61Q7deK59SdRqGMn3Mt+fhPqQh0IT2IDp1OE24iwor9Pg6ddpiRpIqT12QKiyQ3e4fLvICJWx\n+uj96C1qMM9OoVwpo1qrAKmj1YNM7uGF85Kn9j/+4tNFe3zC2cnNd9xUbKtFQhsdGnOBD+VAbOuR\nXKhKI3EGKPV9MERfaP2kQrmNs44e25PKl9rLIl7epO81rKPlOgOhl6Iq0VFUW3LFG+3JMyeKbcdP\nPS4d84E/ew5KwNJ9n/x80X7ty19etF/xmlcDAD718Y/BCius2AGUKmVUqlUM/Ji20pQAx0nKXez3\nOGfXUe8tysmeqpD8W+Lu/RMPSq7hRFk+P0Kyh522O5bNadnJkpyjzyWeonrBg1jG4piWoNprzjiE\nEAaihiw5xDFJ53n7S0iOcUC2PMy1z608Y3y9Jx6WQKa9Uy4H+ui+PXhqaQW47zFsBepRKhQKhUIx\nAvqiVCgUCoViBHaVes2yBGk6QOZzYJJA6J80pbp6RMkOlcFyoi8Drh6Scz6jc805CjXPZS5QiuV8\nQ3Y3JzrVEF3K7G82zGfk6FbqA1PBQ3rXENUGktGL6cCpj0hLKP9t6haqnXZUoht7F1zU5Ynj9xbb\nKkkLrTWhXxTbQ1Q1iOsBhgxPPCUU0pFJoaDOPCxVCj79t18FANTGhUSq1YVCqlfd/d4zIfc1rklt\nyicXheJc7zg76VXFplfWJPK2OXDt3kWh22sdOVeSTxft1Yqzv1JZ8m4HA6qb2pI8ybM+AnY5pjzj\nMTnuvhl3bQsnnyy2RXSswzdJXcQwchT1ZGMCvSqHnCu2i5WlJdTTPsp1R+3Pkc3tmxWbGlDdxtjT\ntFM1sQOQpGZ5fGzzJpRJjrFCWQFDt8pSWaMe5B5HfodqlcZZSjvotWSZIPE5k+NUBaRSlU6wRGjF\nL4MZkkrs9uW4w8DwhDIjOIN3ZkKq9cz66PRGqYQq0buXg3qUCoVCoVCMgL4oFQqFQqEYgd2trBoA\nCIEw9kn5RPXEEYefsn6ca4egqht0SGsootRLJ5VjSoIdp+Rb+mbmRQlYyCAM5fNyWejQYUUQrj7C\nEbKcCNtsumguCsDaECG7TrRFNOv6dpgqSExNSWWKs8eFllvySd8R9bcSG/Q5I1ixLdi8B5t3sLrk\nkpnnqXLCbXcfLdqDttjt6pKLrvvER/+x2JYGYg+DY+5+HaBqMjPjQpPdsu/2or3SdBToxY4k+4ck\nf1gLHBXcL4lU16NfFrmxearGvP+QK9S7fOIJ6Qsld7MtV/e44x1+0S3FtqnDIprQ7jmbDugZndkv\nCeq2Kte26mXBVte7aLaFAlRsH5VKGbVaFeMNNzaNkQxhqSxU+fKKLGOVfBH7kMRdODrUZu4ezU4K\nBVol4Yk42VBSCQDQosoei0Tzpj2371iFzkVLaiHZT9XTxpbG3IAKj/MymPXLWRW6RtKUQeY/Z4nS\nWl2WA3Ir74PYZx0MOh2kPRUcUCgUCoViR7CrHmWQBQjTAPCBADlkNmJpUThE/LS2MezNcQ1K+7R2\nnsqxOh3Jp9lQQxJD+TgK/KHZUy9hD3Yod3fpGpSUGolseB3Ur5yCfcb2iIc7d8zVOAxIQP2RL0p+\nWp/qEoZehD2ka8it3SCirtgemstNhAFw/N5HAQA98ohCkpWbuU48ukHX7XP2MfECP4evFu3Y57et\nz0nwzPiyfP/AHgnymRxzbEIplntcMyR0XnOfzx2lIKMJCdL45OfEqz3ZdgFHi20Rc5+hgKSDh48U\n7UOHXF7mdQckeGxxSWTOWhjOvMXWxsbEjvs5iUtnrm97Dg6QplsPllBcHnG5jHK1iob3liKS71wn\nSbcz6yJbuL7qxr/ZutjJ+IR4j2HfHeMC1bOskexcmWN5cjeOJaHY5CARlmK16c5lUwpso3zdSlW2\nJ6nPj6dxskQsHufVR94rNpeQIAWAnhdbb9C5GvS8DojxC4e56+kANtt6sJl6lAqFQqFQjMBueZQV\nAFjzShKttvvfUEYIe5TBBo/Sd5GFbmiGwDOS4T48G+kRb31pj5JVdSgFJWCP0qd8bMGj7BbrQORR\nkspPGMkXo3ML/lBy3OYyVemmMjChT00JibsfBBatdsGzqzr6s0cFAJor7vfud5xhJj1hLtYuCDPR\npZScXsvtO+iK7bRWZe3j/CnnSbbXaOYdiqfaXZJHcKzqwuf7fQmjX2vLeVe9gPoirdWcPiOpKgvz\n8r2Vrjtuc0X6GqTyeRyJBzzU3k/awmysrsm+XQwfVFoDqonszsDKtVW9YPfChQtYnC+8FLXN7aEC\nAPNrzhZWB26sjGjNr0PpEudW5N61W85muoncuzoxbsO4jCWyswqtO5Y2eJReoYy8ORblb7Y6/lxi\nR5VYBvm4R4pTw7gPGr/rHfIo8XSPMo5YfUiO1fPXM1yPdZBxMiHWUDzKBOfXi75f1j6N3QXqzhjz\nvQD+8Kqf6Gsb77DWvv9ad+L5CLXPqw61zW1A7fOq47L2uVsvyhkAbwFwCsDWQ40UW0EFwFEAH7XW\nLl1mX8UloPZ51aC2uQNQ+7xq2LJ97sqLUqFQKBSK5ys0mEehUCgUihHQF6VCoVAoFCOgL0qFQqFQ\nKEZAX5QKhUKhUIyAvigVCoVCoRgBfVGOgDHmA8aYbed/GWNuMcbkxphjl99bodgejDGvNcY8aIwZ\n7IT9KhQ7ieejfV6VF6V/KWT+/83/MmPMz16N814FvBPAv9ihY2kezvMczyO7/lUAnwZwBDtnv4rn\nONQ+rx6uloTdPmp/N4CfA3AMoivUeto3ABhjQss6ctcY1trmqM+NMbG1Vsu4f+3g+WLXNwL4eWvt\n/DPt8Fx71hQ7ArXPq4Sr4lFaay8O/wFYc5vsAm3vGGPe4mc632SM+bIxpg/gZZeiO40xv2GM+Qj9\nHRhjftYYc9IY0zbG3GuM+dYr6aMxpmSMeZ8x5pQxpmOMedgY86827bOhL8aYzxpj/h9jzK8ZY5YA\n/Lkxpuyv44eNMR/zx3rUGPMtO3DuDxhjfsoYc94Yc9EY88uGJPSNMRVjzK8YY84aY5rGmE8bY+65\nkt9BsXU81+16SPEDqAH4gPci3v5MffLf+dfGmBPGmL6nw96+6Zi3e7vvGmPu88fIjTFvfva/pOJq\nQO3z6tnnc2GN8t0A3gXgNgCPbPE7PwfgOwD8IIDbAfw6gD8yxrxyuIMxZt4Y85MjjhEBeALAt/lz\nvxvAe4wx33yZc/8wgGUAdwP4Udr+HwD8PoA7AfwpgA8ZY45u89xvBbAHwGv8ef8lgO+lz9/rz/ft\nAF4C4K8AfMwYcxiKa41rYdePwnkVA7hlg/0A/vwZ+nTcGPM9AP4TnO3eDuD3ALzfGHO3P1cI4MMA\nLsINXD8C4BegywgvBKh9XgmstVf1H4DvB7B8ie1vAZABeNOm7R8A8P5N234DwEd8uw6gA+DOTfv8\nPoDfor8/CeCHrrCv7wXwe8/UFwCfBfCZTd8pw5Uiec+m7V8abgNwi7/WY1d47uOb9vkLAL/j2zfD\nGdz0pn0+BeCnr/Z9/Vr/91y2awBdAG/fQp/+EcAvX8LGPujb3+b7NEmfv80f683X+h7oP7XP3bLP\nXS3c/Ay49wr3vwVOzPZTTEMCiOFeZAAAa+1rL3cgY8y7APxzAIf9MUt8jGfAPz7D9s9d4u/btnnu\n+zf9PQ/gkG/fASAEcGrT71AC8PgznVexa7hmdn0FfboVbsbO+AyA7/PtYwBOWGtX6fMvYGOROcXz\nE2qfV4DnwouyvenvHE+nhLlUegPOtX4jgM2K71tW1jfG/ACcS/+jcC+/JoCfgTOIK+nvKFySAriC\nc28OFLKQ36YBoA9HvW42jJFBSIpdwTWx6yvsE/B0GzW0zTzD54rnP9Q+rwDPhRflZiwAuGvTtrvg\neGjAeVkpgMPW2i9u4zz3APiEtfa3hxuMMTdt43ivAvAh+vtuAJ+4iuf+EhztO22tvdLZoWL3sVt2\nfSU4DuAbsNFu7wHwMH1+ozFmylq74re9ArpG+UKE2ucIPBdflB8H8CPGmO+Cexn8rwBugr9h1toV\nY8x/BvBrxpgKnNs/CfeDXrTW/jcAMMZ8CsDv8stoEx4D8O3GmDcAeArAD8HRmQ89y36/wxjzVTjK\n9QcBvBjA/0Kf80xn2+e21j5gjPlTuOixHwdwH4C9AN4E4HPW2v/xLK9DcXWwW3Z9JfglAO8zxtwP\nt7b0HQD+KYCv95//NRzd/1+NMT8FYAbAv/Of6cvyhQW1zxF4LkS9boC19sMAfhHAr8DdDAO30Mz7\n/ITf56fhXi5/DeDNcIVNh7gR7od7JvwXAB8B8CcA/gGOf3/v5bo34rOfAfADAL4Kd0O/01p74hm+\n+2zOfSl8L4A/hvutjsPNvO4EcOZZHEtxFbGLdg1scZCw1v4RgJ8E8G8BPAC39vO91tov+M9TAN8K\nYBZuieDXAPx733ctIPwCgtrnaGjh5m3CGFOGi+J6q7X2Y9e6PwrF1YQx5o0APgbgOmvtuWvdH4WC\ncbXs87lIvSoUiucIjDHfCZc3/ARcFOKvAvg7fUkqngvYLfvUF+XOQN1yxQsVEwB+HsBBuICPv4Gj\nwxSK5wJ2xT6VelUoFAqFYgSec8E8CoVCoVA8l6AvSoVCoVAoRmBX1iiNMTNwen6noGHlO40KgKMA\nPmqt3ayYodgC1D6vGtQ2dwBqn1cNW7bP3QrmeQuAP9ylc32t4h0AnhfVwp+DUPu8ulDb3B7UPq8u\nLmufu/WiPAUA79xbwYFSgNlaDgCYLYXFDiUjNTprZQkwGqs6QZswSIttGe0bRCJ4k/pd2v282NZP\n5PPcCtMceF1fOSrQ7MlfXVJZHfYmqx8qtmW3id55+17RSV/2/VlORCZxvLtStM+ty0+e1equUa0V\n25Z6MmFsJNIudbsAgF4g1xZYYC2z+HQrAzYm/SquDKcA4BXf8EqMTYzDDu84BbqlmdhcRJrQoRdc\niuMqHY5XNJxNhbHYVlwS4+r1B7LnwD0PaSLft7nYUZa5Y/SzbrEtzxNqS3+tNf77si3L+HrEjlL/\n4KSpHCtNpL82zfwx5fssi53QvtnwWFmKNE3RWm0BapvbxSkAGG+MIwojZMaNISbtFzvctH+qaP+z\nN0lJ2tkxZ0spyUanaalo9wfu3gaBjDX1WMZlfgYKU6L4Tw4FNYE7V0Y212yLfT91flnaS2sAgLHp\nuWJbkIvd33h4T9E+etDpF5i+SMHGZICZ76MJZFtg6BkiW0ee+2vJ8eT5Jfzc+/4S2IJ97taLsgcA\n33o4wB3jIcZjdxFhLBfQ6srDFli5UWNl9z8PAr2BveS+feuOt27lB2vTnUzpGMMXbEYP/Dr9+G3a\nnvp2pyUFwk/c+6WiPWE7RftAx52jTC/asVAOVp7aW7Qfb4wBAO5fvUDHkj4ejeX2NLwRdYz8ZmEa\nILbF30rJPHv0AGB8agJTM1O4VCT4YCAPfEjDQ+RfiqWSTHbCUGwys+6lllt5yMs1eYgnTaVod9tu\n0Br0efIn++aZe2kmWVmOn2a0rxidH7OQJNLvfl/25edpMPCTRpo1pmSzuX9x21xsjwtIBPR72Cjw\n28ro9wdooQWobW4XPQCIohhxFMPA2VdAYwHb556pyaL90lv2AQDaAxm7ml15Ua733H0c5GKf9VDs\naLwm9jm06zx/+iQLAPLY2WVQaRTb+l3Zt3xyvmivPvAoAKBFL9Kje0XQ59Uvf2nRPjDjni3Tl2so\n0YswCZxd5wFN5OgRzukZsb6/ubWIasXvcFn71GAehUKhUChGYFcFB/ZECQ7GWTEL7tFMtDOQt35G\nM9vhRClLZGbSFcaBmQEMMvfeb5Gn3ZbDgg6B0M98M5p6tIjy6qUyY+77fZiOCnLpxHpZTtLI3ayr\nRMddMOJhnB0Xb+ChdTeLO7kiHukN9L2oLN+reM+RPQFYINI02B1DnufI87ygKy3ZJ//ueSYz7qhU\n9p+LbayvC8VUqrj7FpWZbhXqtFGvF+2xSecxNtfl86QlbQRuBhxk4hEwzYWMaTJnkxnR9ybbQK8U\nTZs4WzY50/pi06GntMJIaOCY2rYiXseQ/opMgHani/PnF6DYWRhvlwExF2sduc/nFsX+7rx1PwBg\nQPe7Q4xcEk64Rl280LWmeH79juw7OeGXF8iTNbQUhLJ7FkxZliGmGuJdvrguNGuz5477BWLmKlWx\no6k58S7Dkts3omW2kMc9656t3MgzyB6lpaW6zI/FeZYiDLb++lOPUqFQKBSKEdAXpUKhUCgUI7Cr\n1OtaK8GSNej5wJSsLPRN14rbjUjoyfX1dbcv06JEvSYUuJP6CMQuRbd2iJpKad/YR8Mm5Jb3c6Ey\nehTlk3qqgaOnqjTFaBK9u5YOF9qFHuuW5HrODIRmzVYdXbInl9swFcnBxiigaBj3VM7kxJkJQPFp\nim3CGANjDOyQtyH6Jgzld09T+7TtTKeeO/9U0b7xJhdMUa/LPe70JIChNxC6aMwHd40LCwaE8nmv\n7Qw/G8hdTwcU3WepIH3u7MgQhcrUakz2W6qW/LXIcYNA2nHoP6clhICCeTbQ0v68yK3Owq8ShtSr\nMbxUJJ+fuSApgW2/TtVpy7jTIzq1OuejZcckGC2viB2tXBRt8YofoyfHZLkgpqCvqDzsjxw/prE4\nh9j9ZNU9D4f2CcV69Kbri/bYzLQc17px0m6we7pgP1ZzYCdHpiMSu8/hI7iDDOWI3jmXgdqyQqFQ\nKBQjoC9KhUKhUChGYFep1wVUcc6EaIWOimzE4u4PKMer3ZF2p+VzuCgKtUciAj0Kb0q9uz0gipW0\nB2Ah20u+nVKS6oDbdIzhKRKK9ooo3DZK5Wfszx4EAJRnDhbb1uYlisyuSM7kPv9/kyLHjtSEpo0D\n4pirLpIsoJDeLE8BuibF9pBlmRMWuEQeJecNMtJ0sOF/AIhjFrlw25stob66/VU6gkTDNlsuQrTe\nEEoooLDmcs09FyHR+v2ezHUNUa9h6NoTFGUd0BJBFEa079MJfM6ZDOGPS88E55pyLl2SuOsZ9AcI\nn+E3Uzw7BDCO8rbDqGyys0Du/dkLEvW6tOoS+5M+2V9b7u3EAfe9yrhQnYGRSNV2W+zz/IITTuGo\n7EZVbHFmxi0dVCtiWynld3a6kqsJn/O456AICxy44XDRNpLjiDiK/FfkfZH2KFF9eA6yw4wyFHLe\n7gVAsiRB32jUq0KhUCgUOwJ9USoUCoVCMQK7Sr0uBjXMBzHa1rnVdkmSZHvrTE1RsvPwf4qe6lHi\ndJ/o0GFAqCWXmvVdzYYIWXcMlrDbIGBJ7cgfj4JiEZIqQj0UqqJyx10AgCdImmyhLzTBlCWqbX0R\nADDTENrk8LhElDWo79Ynx/ZI79AkKYxOdXYMeZYiS5MiipPNgaNAmXbsdJzdZmQPExNiD82Wo6ts\nIPctCIVSD5gP9edtd4iiImo29GsA1Yroeu7dJ9RVOZJ2YGL/P8vtUXQq0VGB17tjzdYN4hqeemXR\nj35friEdSHvgt/f7fSQDEktQbB/GLQEMIzrthvFK7PPCslD7Zy+6MWZuQqjMkKXvvK3NkEhAqTZR\ntOsNiaCdP+OWkBY663IsK3ayd/8sAGB8XOyfB9iVdZGgCxrjAIADe/cV22qTct4Lq6KPPeYjZOsk\nbBFXpL+pX2YokeQnLyYkpKcc+syFNBkgWmlhq9BhVqFQKBSKEdhVj/LkYgdJM0QylFBKWBaMKoJQ\nUE3uXaYSB+hYktqiBe0gG0o7kdQReZcBeQLD2Tl7ZENZOwAA9QfWe5T0cUwehJ2WGf5JH3T0+RMn\ni23ryzIru2VG8obGfKDH9TT9qZMMU9ijPvhZuyUB9iAwG4SRFdtDnmfIsxS5ty+uvDH0uoCN8lit\nZTcjX1qSIK3KmHw+dcjN5NNIvKuI7jEfbOj9peStlUtcIMCLTmfkkZZkVtxo0DlCF/jQosC4NB/Q\n55RT7OfLSZ8CdEgmeuArlCRcXWQgO2RJ/2ltYzOAcjgV20cUuH9Db98QyxHQ+NiiPN1lT4PdfERy\nFMtNqjgTDgPEqLIS2fcYSdBVa86mVhYvyjbKhV9YcrZ46ox8Pt6Qh6HdFZuZnnNydi+68VbZNjMr\n19CRYyD3ebxWxlmT07g/DJ4rUR6xISYmlt9j+GqphiHqS+IZXw7qUSoUCoVCMQL6olQoFAqFYgR2\nlXpdWu8jjgzKfqmVFeC56GaZKIXMByDk9E63RFdtoE49tRrRRmKYNuR1VXzeUQqqohBRbcuYAopi\nHxhBrr3JZGF5kRavH54/DwA48djxYltEOUyVTOiFm0N37npXPh+QpF7ap2K/nlYOwXJMKmC3k8iz\nFFmWUM4k1VnkQBgKahlKaVkKjum0JRin1He0UUbBPBFJIcZEmQWe8i2RXJ4hmww8jValoIV2X2j9\nlTWhtmp1T4FG49KXmOk1qgXri+imXXpYyL6La+fAIJYu2/Bsunae5BhEmke5k3jZy27DzPQk7vvq\nAwCAlRUJ2oljuV+vfcPXF+2ve803AgDGGkTNJiKxmHiaf5j/CgAmFNuYnBT7ufGmmwEAJbLJLKM8\nSS+T11yQPM4glDxeQwFH1stAlin/sxRIwFFO/WmMu+Wqg/uEPuZAscDTv33qy/kLp4p2XJJrr/p8\n9LhURVTiYuujoR6lQqFQKBQjoC9KhUKhUChGYFep1xwhMgSFCx4xhUrUFlOyw2ZMdCrTYAFtj/32\niCIUQ6J00xpJK824CKoq0Wjlirj+LQiVFvlcoYQqd3SJ9Wymsv3igqPCDOVLjsXS3/09oVn3eFX8\njKIDc6K0+vT7DBm6gCqNZHajjJViezDYGPEX0hJAuSwUUons6OihAwCA1SWJZn748XuLtvVFnvm4\n9arki41VhLa3Prq0tCFqW77X7TfdsUjyMK6I7SWZUK+tzml3rIqUIokDuQaWsIurPqeYFBMrociF\nlTxVnKRUAJcjWjkK3dNgUaW0IWpYsX1801vvwU03HsbrXv8yAMADDzxUfFapyP26+x6hXsf8slA2\nkAjPXldu9NmzjoatNQ4V2/Yd3Fu045KMibOzbtmoXhU7Wl6S6NSFC06CMdt76fseRZSB4GUT19al\nX9UpuQbQElTZP282pGjdQGjWJHXRtkuri8W2pRWhl2s1oVgbY4f9dcWIYpWwUygUCoViR7CrHmUQ\nRAiDsJhds1IIQHmU5CUZPyslJ3GDx8hCzcMaeXEks6D6lCxG98Zk4Tgbd7MXuySLwhkpqLPSStt7\nBXkks/9+RRR0VhPxPBpVN4M/ekRmMdVUZk0R5WeuDVx/8454mRHlB6Xk1WbeCzd2o2etc/adQ71S\nw1i9USz4j4+L7YyPSXuM1JOmJlye2Je/+LliW/wk1cULhgLWvE0CLybGxRONfPBLuSyP5aBPXuKq\ns8MsYGUfEi8nlsOmzvtMcwp6sNLvMJDZe8Vfg8kocKjD6lj58GTFNlOWazAQD6PggLIcfQpGU2wf\n42M1TE010Kg7+5zdI0LmFVLWKVdlnAp8YBjXx80omCzxea+dbrPY1mqLnWwIAPPja60qttOv0ThY\ndsdYa54ttk1MCqOR07je9+xEfyBeYr8ntjozK98bn3LnSKzYfVwlqsUzfq2eeJQp5Zu3yINeWXN9\nr9XrQLD1HHT1KBUKhUKhGAF9USoUCoVCMQK7Sr2WDFA2UsuRAxVyrv/IX/J/sBA1lwu0FCWReXor\njYQKahENe7EpNFYlcu58h2piVqZEbmn88P6ifeT6IwCA/de9qNgWTgtl1vn0Z4p2f9Gd48JTsph8\n9qEvFe3ze4VSWI8dnRddEMpgsimSZBwwMRRADoiazYyFxkvsHK4/cgT7D+xDw8t21etCK3EwT0iy\ncl6rHitrQq9bosfLsbO/NtGQiyQOPVEXexibcOeLSnIuSzmV6MT++GQXRIfmlEcWhsN9SHYu4bp8\nJGoeOQoqjEncn0SnGxXXH8OBZGR4acY1Ut15U2RFwIZiZxDFZcRxtQj6qgr7jZjGvDLR4nHZjRc9\nqiE5ILpzbs6NY40xud+WgrN4XB5Ki/Z6Mo52aNloGJgTxjLmXnpxTSRLM6p72qSxrz5JIu0+QCwM\n5bgwYuu51xaNq7Q00L40rbrWdmLrY+0a2r2VS+5zKahHqVAoFArFCOiLUqFQKBSKEdhd6hU5KgaI\nPJ/KlT3YRd9AN3mQh46c8wv5e776x3pCMnBUoaR+8x1F+9Y3vBkAMHNQ8oeCBlFtExLlOCSs0kxo\n2qVE6IcbXvmqov2awzcBAB783OeLbb9JEZH/cOrJoj025vLpXnv9bXINp6XqSLYk0WOZv2augJJZ\nu4ECU2wPszMz2L9vH+KhZGHI+bhCIxL7jWFp1DASumtAVThi42xmWFMPANqZ0GA50aiBj3q9uCxU\nfLkmlFpQ9pVIekKhlgxLhFEd1sxRYnFEEo1Eo7VJVjH1SxYx1XmtWDlWabh8QRJkvDxBxhC6AAAg\nAElEQVSSg23SL38gKY6r2BkEJkAYBEVUNt/vZEBRypyH63fJKNq+SjmXlaqLnJ2kZacgFFvOc86X\ndf+tra4Vmy5elDzKlRVHZZYpI2B8QpYWul2KwC6WDMRGkoHY6vqq0LADP55XS7TMQBY4fDdUa1QH\nk/Lns1yo5t7AHXf+4mksLp/HVqEepUKhUCgUI6AvSoVCoVAoRmCXqVeLsrWw3i3miiGcSB/Q+3vY\nwZR07SzJ1uUUodXxUVH1G44V22Zf8pKiXT56Q9G+GDna8/5Hz8i2C0IjdFeEXmi2nEr/8orQVasU\n7fXyV728aN/zY68DADReI32891VCzf7pJ/+maC+uzwMA9oxJ4vArPXULAB2KjgwS145IhCC1FplV\n6nWnEIQhwjCE8bSOIaoyoUjBhCq4+Drd2LdPKPyH7peIvbTnqKXZ2bli2/49RIM1hDptNBwl1idq\ntjuQqiOxp4KtEeGMuCRLBFlfIgFTX50BORUCp+cmy8R+88R9b6wm0nr5KkVJJq5fZYqK5TUPTmDv\nepqs1c3Q6W89oVtxeZgghQmSgmoMiVZPqaj2IOGIZC9PSBHPszNii72Bs4lWi0RRSmKfw4ogAGD8\nWMNLEiWSuGt4UY7amNCt+w5I9sD580J1NnxEeUBSirxMBoiND22Zl5m4qk4Yu+dtrCHj6Pi4VDBZ\nb0qFnSGVnGZpEaG9FahHqVAoFArFCOyqRxkiQIQQg6ev48JktABNM/nQv8tXDdVmpIXcxJAc2K0v\ndtuO3Fhs+8KCeIarpySoJve1yB48caLYdvrE40W7RkEWc36he35JZil9koR6zWtfW7TbbTc7r9al\n7uQ3fst3FO3PPiRCxqeeesL14YzkXJaq4iGYMolneymzKbPRo0xVxG7HkGQ5+mkO+Htv2GuiepMc\nvDJs76G82qOHjhbtk6ceBQBEZOx7Dst9NRkFtPmZ89SYeG4Lyy3a1/WB660GJDSdUpSRtc4LzEj2\nKyc2wnBAkvcoA6pZmJFE2HrLeZe1QDzlbkL1DXvizTTbbt9Op4u1jniliu0jjAyiOEBv4O4ps2k5\neZQReVsLT7mAwKwtn++/Tuo6PnnejWnz8xI42Oqw9KDc5wMHXAEAUNBXQkzg/r2OVZmZE491QHm8\nlXGxn5q38XZXGJOA3kb7S/vkD89YmFwCKFm6dCj2P16XZ/DAPmI5ulTgIvYMz/QsFheEgbkc1KNU\nKBQKhWIE9EWpUCgUCsUI7Cr1asIIJgphPGXAuWmWqnVwnmTuaabugLaRjx7fIAE6yz4v8cH7Hyi2\nra6IKv707J6inU65fbOcZL8oT6fTlO+h6mpXxhOSH3Tr7XcV7bvfKNRrzwczRC3p70u+7tVF+3Vv\n/CdF+48/8PsAADuQa7/v8eNFeyySBe25MPb9lX2rSDAIOKNNsR20ul2sd9pF0EIIDjAT8E8e++oK\nVaoo8uq77y7aY17+bZHq9j3wJaH7G1NC4R+8zlH8cYWeBaoxOazkEFEARRDLM1Qi6Tv0hjUmiT+m\nfDKu/zqs0NMiGqxUEnp4zQeSdTOxx34i7SZJQ/b8EoGxKazV6iE7CWMimCCGDRL/N31GtXJLudyb\nzrwLROyuyL09dvOdRXt61n1vYlIO1mzLmMiBk9NTjtpsrsuxOmfOFe3FC669b4/Us7QxdTKkZaPU\n0fJT01NyDSEFJw2kD8P6rBzImNH1Wi9hVy1JfmhWk+PWKtKu++e0Vm+gQstcl4N6lAqFQqFQjIC+\nKBUKhUKhGIFdpV5zA+SBKTThgg1Fl2W/gREXfNBw7vH03luKbb2efL46J9FR9548DQAoUSTg9LS4\n17Mz0j7jizEPKFqsQYV6g7pE084ePgoAeP3LXlFse+Nbv7lozx08Iv31uWNRReixHsmFlYi+veN2\nl+N5/nGJhF3qSpRje0rygl784pe5c3XlWCv3fwGpVep1p5DnA2RZr8g3NEQ7RZTvValwpQZHcyV9\nifCcmBQK6PVvfA0A4PhxuceLn5G8rqQl0dXjZXe/s0xof0PSY0MluUqVKitQhGxCaYvDwh1dWloY\nSAAsDFX2CDwNyxGIYYOKlBv3xW5LpPWQyvMR0jAyWXWdjMNyQekqdgiBAQKDxEdgGy5wT7mNQS7t\neuju42pzVT63Qs1OTbvlqG5X7KTaoCWortDqi4vu/nMVj+sOy9i3XnbLCytLki85d1ii/ydr8r31\nFdefo8NIWmyUVVxeEFs79bizoxtulmjdmIpHm8h9nuZi4KvrkqHQGJd9xya8XduN1PXloB6lQqFQ\nKBQjoC9KhUKhUChGYFepV8C4CgY+MXqj+hqpyBO1tTzpIpambyJpt1S++PiS0FR7b3PVQZ568tFi\nWxZREjYV++x4SbLbX/ziYttb3/rWon3zDUeL9kFfYWR6j9C8Oc0xFpdF1AA+CjEdCBX3h7/7vqL9\n6T/706J9xx53jl4qx1oh/uy226Rv3/AmFy0bXbhQbPvMg/fBBClARXgVzx5hAEQhUC05aqpCUaQV\nKgAexVTA2NNgKytCp168KMnbL7rNySkePCq287b6m4r28rJQRGNezs4aqeSwvCISizZ3NpUQHWsT\njlAUSq0QRQjY/qn6Ryj7BoGzuR4lZg+oCHQwLIhLil+TkSwhRAOab3uptHa7BdtXwYGdRBiGCKMI\nuR8416lYuOnRMgEV856ouUjVc7mMG0tLMl5N3uio0/WmjCHLVL2mWhPaMvRCBi0qsDzWkOWqxkEn\nV/elL3xK+hUJNbv/oETDLp1xz8j86VNyrCmJtF4iubvP/v3HAAC33CbSpPe87vVFe991jr7tUlWd\nleWFol2hZbRK2f02g0Fa2P1WoB6lQqFQKBQjsOsepYFB4IMkEnIpEwqWWClLIMH9Xef5tR98rNhW\nnRTR3fEZmamvewHfJ+dlNkJl9VBZkQXtts8r+rEfF3m57/qe7ynag0SCfIbSYp2WzLL7fZmBReQZ\nRz4Q6SN/8mfFts+9/4PS90XxILot17n9e3nW9dKiffdrZNa0Z4+brZXqMoMrT8yh1O8Ba5TzqXjW\nqFerGKvXUfK2GFO+Ls/SS+SNVX3u7sSkeIGdvtyPmX1OzuvWWZkNH/+K5PnuI7H0Rx59BABw9HoJ\ncCiR8PX8msu/5DzjHkXohDHX6/OgXOW4RGLt5B3mw9zcgAJ/MjluXPHPYyrHqpBcXkJSdcu+PuFq\ncw3rPc2j3FGEAUwYIPIBZOuU6521qe4o5S7uabix8sZbXlRsG8oMAkDVM2vTMxI4ODYunl2VAscW\nfICNwUqxLaDnIvH54CYQ+zx7WurvHtwrEnMl38WUWIfZicNFu7sqnuxU3dnfw199UK6BPOBbX+Lq\n+VYpWIgZkb0H5R0Re9/QBCHiYOt+onqUCoVCoVCMgL4oFQqFQqEYgd2lXjMLBBZD0fuE8iXzcaFT\n979C6jfef8EFSTTPC80wWCPV95IsLJ94zMm/DUhSyxJNNjMhUkbxlHPtJyYkz2f+vCxyLzel3fW5\nRNRdTE3QIjYtFg8jlPbtO1hsuuN2kYzqrAhtsef6mwEAs8duLbaNzwkFQqlRaLbc9U/V5Fz51BTy\nThuQ2BHFNhCHJZTDCqplX42gIXTqDOW07tsvtSenpp391OpiZ7N7xaaOP36/+85BkU+c2SO2XqGg\nmAcedrmWVJwB1ToFU3Tc4zrIiWaj/luqJjHMEYtKFOBD1XpAAXGDxC1ZGKJuk5wlxNz/XZIuW1iW\n9mBZnreup9JMwFl+ip2AMQFMEKBccWNApSa0aKcnFGbcoBzDkrOvWcqLXeV8w6Ybj2anxWbHGmKT\nFcpXrHsKtFaV56LZFDto+wFyz0EZ+04//nDRvnBeZBzj2D1jEcl0DiiP11Jt1Zt9HeGZSRmTLyxK\n+8njbkliknLm+4nYZNaTYzVi99uNT03AXMHKgHqUCoVCoVCMgL4oFQqFQqEYgd2lXvPM5WL5kLvO\njNBRd7/9HUW78jKpvvCJD7q8w9YJye3JqYhuXJVIp9aai2pNWpJfVK4JTVCrCKUws9fRA2FZtl1Y\nkqhYrqTg64ZiiqLB+tSH9QsSZdvwVNlLKc+nRN87QwVS40m3vc9SfhRtm/dE0in3kntPnZe8ugvd\nJpo9zVXbKVx36ChuuvEm7PVVZuZmhY4ap3sYRUJ/9z2tQ4pwuOuulxftx0+7aO2HHn9EjkVPXX1S\nol6HtnzmvFRk2H9Q6LWo7L7Yyzlvlqrq5BLKGvi4V5beCynKL6RQ7WEFnTASm04Gcqx+x9FYHaJb\ng0X5PE7kHCZw12Aiu6Ewu2IHEBggCBB6ic7pGYoitbIE1aCsAAufm0tU+2RNxrzzXurt4gUZlypU\nML5cEfuLI3esGi0HsH11+64PB4+K1FyeCgV68aKM4dcdOerOVRNKePGiULPrtEQ14ankakmeu6lx\nGTMna+5666F8nnVlHD1/cr5ot5bcu+HoLTdg/vTW16zUo1QoFAqFYgR2VxTdWmTWou9rNh567TcV\nn73iB/5l0f7iafGaxudc/mBcf7zYZq3MFhLKIytqSPLnfZlpPXbyiaJ93Y0u9yYok3h5Snlk5NlV\nvSfaJkWKj33kw0X7vvu/VLTn9joP4S1vflux7cZbRGEn2is5cs1VN2vqkBhwn7xIKsmGzro792f+\n598X287Mn0GPE+IU28LtL3oJXvrSu1D2ijyG8nxZIL3dkcCyz33+0wAAG4m9TMzKjHut5xRCVtZk\ntry3JjP+1XVhP8IJd8M7HZlNt8kmI58TWaLH1m6o3UoepWcpYnvpmprJBjF9dwxLIuZ5SgFDXddu\nROJd9ENhMkJyHUM7PFaioug7jMCECIIIceg9O/LGOjHnwAozUKq4e9NL5X4Zqn876b21IWsAAKmV\nMTWhwMh1n689Swpl1VjUq6Z9UYnGpIxx+2clCO6xB+8r2g0fGNShIg9Li+Jx9nrSh5r3gKNY7G8v\n5WTWvXpQn8bRTosrAIgdNtOO78vjOP2kMDeXg3qUCoVCoVCMgL4oFQqFQqEYgV2lXnuZQQcGec3l\nM1aPiKzXRz8v9OX5NaGeJn3+WpmE0g0lmp0/e1qO33fBBqWy7FuqCD1Ro1zN2NNrAUVhDIjrTDlg\nyO/yl3/x58W2P/id3yralhJyTOTmHg/dd3+x7X/7kf+zaB8jGtZ4ymp5iWTt2kLFJW3JFfrU330U\nAHDf5/+h2DYdWRgovbVTiOMSSqUy4DMALRWsCyhooUN0/qc+7wSbl9ZEdLo8LvPPbubuZ60uNtlb\nFfvuDEhWMffbSbbu/ALlBPcdtVqinE1DfcwM69KF/lBi3/mA8h17cg0DHyiW9un7PTluKXHXwwFN\nzUSO212nHD5/iCALCrkwxc7A5oDNgADu/pdLFFRTlvvZasnSQDVy41+FxM17nTZ97paexqaEykyo\nkMT5J2UZbGXRBcVEFZJKDMWuc68X2iuJbUSxLG3to9qTia+7e/HcU8W2JvWLZfTgpRdZgnGYSwoA\nXR/QyJJ+A1qS4vqx1i85nH/qIhYvyLh7OaglKxQKhUIxAvqiVCgUCoViBHaVek2yDANrUZlzbvWn\nv/yV4rO//O33F+2XfJ1Ivt10p2uXiU5NuxTpSlRl5OulBURJvPjrXlm0j9wkUnFVL80UEvW6gW6N\nhd5auOiioz76V0K9Vkjua3pG6qx1fR3KE5Q39xcf+m9F+599u1QoaTbdvkurEu2FTOixz37ib4v2\nfV9wlGvZCj1crTdggxSARHspnj1yY5FxFCnVfWxTbu7JJ0/TPs5+ymXJ141I67Dl7y3T6+mA2kbu\nnfG2WLJCO7XPi633PbV08AaR6oqJec9DsV/rm2ZA9SjpegxFK9Z9NYo4lXOlHVpO8JRsuSrDRWlW\n5CDn6XnMfCWSMAoQRDoP30nkeY4sy4o6vjHVRS1VZLxaWaSqIg1372oTsuxULcv4OMxJDyiqO6B8\n3CpV0Kl6GjVL5H5zjdPM051NWjoLLEViU23UNZ/zfuGC5DjWiG5tjMnzFAbu2vINBYwpatsvP/Dn\n/L5ot+UZa/pnqNvtFFG8W4FaskKhUCgUI6AvSoVCoVAoRmB3BQeQIUOOXu6i7E6fOSUdoWKfTYpe\nKpWcuz9JskyPnZNioAklZJd9Am5tSmTBxiYlmotd8Olpt33PHpHRY0REyT764JcBAGtrQplNEjWw\nsiLbM1/BYZwU+B/8ikT0Hjt2W9Hed+iGDdcIACceEcr20YelUGk5cMedGxParV6pwFKxXcX20B50\n0ey3sXDRiQScPHWy+OxJoltbqxKp2qg6mbsqVVSwRu7Jcu5s+dRJ+X5aEvGBsCQUZzl0NrOnIQnd\nc9Niy49ecLbxwAMSKTh9SOwsqArlW/U2NV4hObKq2E4oJods4J6LlCo2oCX9Cr1EXU5J7bWqnHds\nXNorJAPJid6K7cNa9y9N3fgZUHmhGkl5Woj4RerFB3LyiUokBWc8d2+JIh3QMkMtEApz37DCSEPO\nVWKxieGSQ0SR1rSc1SMRlxUvUcfR5GNU4SSKZHvqBWosUas1iuK1/n1SoUjYnCrsrK1J9oD1WQKN\nxhhqLVnmuhzUo1QoFAqFYgR21aPswKCFAP2Wy5fJ52SGcP3h64p2RrlhwxlAtSo5NBkFJYQlmfFM\n+Nn31L4j8n2S6uq2JU/n0CFXUzAgoehOhwIrqA8XLrgcuYgCfOrkUdZoJtTy51inXLlmUzzOx48/\nULT3Hz7qzyW/w1OnThXtlOSdJituFlfhIpV57v4pdgSf+PuP44knn8CF807kvteXGSfPUDfkJvbd\nbLZNQWU9yrMsBc5ur5u5sdh2cpFm2SSHV224fcdmSQidcnT3H3I5xUtyqg0BM/QoIC65R7tEnl8Q\ni53mEO+w4vPi4rrY4dJ5uQY7LGLQkm0RBXlMTQvbM5R+bDXbG+T1FNtHnucuoMcH22RUMxSBjInl\nKtmnZzcSGjMz8uyMF88PIJ83L8p4dfYRkf3ce52TE23MCUuRUFGG0Ay9Uzk+e6rtphhu5itN1Opi\nnyF7keSJdnw94MDI570eP5vuvByYyawke5rDIJ9kkCCmHM/LQT1KhUKhUChGQF+UCoVCoVCMwK5S\nr8tZANgAg75zuzskmWUrXFdPaK6hi82FCPpEHURELU3MuSCIQ0duKLbNkjQTy71VvTs+Py8K8lw9\ngSXzMt8fEwn1Gkbito9TjlKau0CQtCu0SIcohydPShWUm+ZdUFKrLTTC2ackUGNA1F/iF7I7lOuG\nUhX9RCgKxfbw+KOPYH1tuQiS4PqNCdlcry100zCnN6YAhjLl2FY8vTM+d6jYNtYQe1leOk/7Opux\nAzlXG2I7pbo7bi0X2zMx1YUsxdT2552U6g0xBfast5aKdt8/Y9W6HHf2oAQRNZ90wRCWfoMW2fTk\ntDxjE56GbbY7sAFXKFFsF8NgnuH4mFFd0l5PlpVKFZY1dPc2o/xrSxVlEp/3bYjGffS+h6R971eL\n9t2v/3oAwPhBsakso8AhX/GDCfduV56Vdluo+2HuY5KI/fK43+9TTm+R6ynXtbCwINfjc3fT9NKB\njby81vLLB91uFx2qOXw5qEepUCgUCsUI6ItSoVAoFIoR2FXqtR0aRGEADKmtHlXraBANa4RC6nha\nskH0zoHrperIOBUGvflWl6N4y7Hbi22H9om8HCtqlWuOWi0TXWVzooooWrbuc+QC6ldGc4z9Bw8W\n7bm9jv59+D4pUsrVJs5fEKr3UV/ItN0RemLh4tmiPaDIr/bwfLFQfCgF6EHprZ1C1ush7XbQ91Vk\nEqomw7RQpSx2UK35iFG6LQHRUYmPXG5SRPWgL5/XpIm1BZeDuFKSjZU5iYCt+KohZSry0QXJxxGl\nNoz2DkPpa1Sixz0UgqznjzFIxA7LZbGrasMtU+Rr8hskiSwLcLWKks9vq4/V0accO8XOIfdUI9Oe\ng4Hcu/6AJOx8fnpmJTe3FFMOoh8/Bh2xo4jGwaoROj70VZsGVFSZI1mTovizfL9JttGlZ6DtswN4\nSSNLmYa19D13bWWS3lunguedtjtHrSbRrZx3z8/uMP+yXC6jSdd8OahHqVAoFArFCOyqR4ly5FQb\nfL5N3BFPa5xEfZs0ER2su3zE5WUJPgDl5nRbsiD76MMPAwDOn5aAmAblX8YUjBN7JYuAZj85zWh4\n+9qiU1LJafZTIkHixx59tGiHgev8xQWpT9gnEeFmU1QivviZT7nPqU5gn3InI8qZ7HkPgRfioyDE\nINA8yp3C2uoqwsC6wn8AyqSYVKN2uUR1Ko2v5dgVW+6vS7u77ma7naZsi8n9nJ4WcfG84ma7i21R\nt+mtUV09X2+ynMg9Tzfcftm3kzs7OtcTBqM6TX205IH03DUYCqygRwGxz8Gz5AmDxLC7lF85LBVb\nb9TRzZTt2HFYW4j1pwl7lMJ+DMjbH3hb7lJgYK0sY0ho3X1MSQh9/xFhyGZJCWzmkFPmWV6WIg6t\npuSL24HzdLs9DjKS8/YoSG1h0QXjjFE+ekIM2jDP0rVd3/p0DV0KxBkqFdGpNpx3fFyuYVjHctDv\nbwjYvBzUo1QoFAqFYgT0RalQKBQKxQjsKvUahBGCKEYldnRoG+Jenz8tUkldqiV27iknBH3+olCZ\nbaojZomeHC7/DulPYNNMgOgi48V4uQ6b4Xpn1A7gKIFkIJTCDYcPyPdIWmlx0VHEB/fL4vnDx6Xv\nOeX6rK0s+X7TuUj2a4MEWOhrroU5fW445kixTYSRQRgblHz9O2KoEKREj68KbTnoOwqoSzY5aAot\nZDwdFdGNqk1JoAHneMVVd96G5VqRJN140VOcFPwVEd2aU3HKoQzkItW7jGdEmqzSkOOWfQ6oySQY\nYkC5ot11H0zRk+NXKEcyJ5m9duL6GNfrSDXHd0dh0wR5OsDAS7olKUnFESs+4BxEL4rOevcb6Ho/\n/uWgZak9JM85K3nqLU93cr3JLgXrGG/jyYAkGomGXVmXZaeul76bmZ2Vfm2wF7GvoUC6tdzxp1Oz\nhgTcA5Kz47zOLBvSwz30+1svKKEepUKhUCgUI6AvSoVCoVAoRmBXqdeoUkNcLqMUORc5pwoELFl0\nfl3c+baPGC0RHTu3f798ThJJw8itKHim/C1ywodRXhTtxbXTuJ16+aec9n3wQcmT5LzN/T6P8vRp\nkarr9agqCfVhyPoazoXkZih/GC+LVqJcIRMFMLnOdXYKlTBELYxgE3e/e5T31aV8sUGXK2t4+oai\n9DhkdFhmlSUYA/ojyMgePJ1Upwhbw7nGa87Wo1S+k1JViDy4lJwdfU75dXlFuLrc51oayjezREtZ\nX5uSmD4kgTwflqs6+AjuXpqj3d56npri8mi121hfXy9qOVrw/ZZ7wNWV1tacrXYmaLmgQbVGfSR1\nQGNmRgnnXRqXu34sZsqyT9Rq7IucctRrmyj85WWJ5r5U5Q6uFxxTpaZh9Q+u6MS1KYfRqxtqVNLn\nXElkuH0wSJBcwdKAjrIKhUKhUIyAvigVCoVCoRiBXaVeB0GIfhCJbBJRr5VpqWywvyYJoqbsXPTG\nuERiWaK2Tp08WbSHkVQVEhngYp6hEWrJeLkuLmLKx00pOTbLfZQZJfW2iV546BERHAj8Na2vkbo9\n0alxWSiHoWQeUwpMvXLfI0+llcpCvebWIteo1x1De2kZ5XSArqdqEqp2kFPEM+kNoOYjRgMqOjug\niLzcRy4zHWZZGo+WDowXjyhTJZL1NaF8Q0+5RkTXhhTCyBJ1wwhEk1AkbJso4UiuZ5C6PvCCRUxU\nnPHCARktR/TZ7mi6neZDaquNXpe4WsW2sbK2gotLdaytOgqzUhV6coyKcnOh4s45Nw5dmJcqNbPj\nIutZLnn7oaWBDbQo3fOFBSc0cPbUk8W24TIFAJR9hLahcatDif8Jja8zU05oo0/jrCXqn6nX0Gc2\ncARtlYVk/L78jK2vSYRtRMcaVo2q16uoVlVwQKFQKBSKHcGuepRZXEJaLsP6nJ1oSmre7T10pGjX\n9oiEUuJf5W2SdltdFDm7Ul080cb0HgCbvDbK94op5zLywsI8i7EUkJHQTGjga71xzTf6Gkolmd0M\ngzoySmxikeKAc/N8vh6nb3LAUBySx+0DPELKBc3tYEOOkGJ7WDw3j/5KCcbPostkOyHdlzLNUG3f\n7ctC53lE9QD9MVLKAcsol9bQcYeMRUSz5SATg0n9uSzNnDfm/lJwgvc+Q/o8p8Avk4ttDev5sRD1\nhlqS/nR0WvRzORcHnVk/97a5hc3UOncSK6urWFisYsXnX9fq5DmSpFsYUx6jFyo/15JiCwfnriva\n4+POqxpskJ2TsXaZpDhPnXSe5DzVzGX5wnrDsX7jkyLL2CePs9YQVjD31FmX2JWI6DRm2QbJ0D7z\nS36+6j3slLzfMnnVYxTkU/LPbpIkyO3W7VM9SoVCoVAoRmC3PMoKALR9qHEAN/uOYll/MSS0y6Wj\nUv8qZ1Hf9orwz/22HCMfuNlC2qcZP82ME2pHfibPYcTsUaY00xlWAR/0ZT2JPUpe2xzmAaQkhM5r\nO6RpLuuL7FGS4LuhGf7Qd8wzUpywCZepkSmU4kpRAYCO9wrNUISZ7CUgz29A6RnD9I+MbqJlj9I3\nef3EUGmsXiiz947PvygP5FidFtlRx33O3u0Gp40WGYfrnRnZN3UbtAxaiGyzvUWUapJ7NZOEz8v5\nLhuysZyBp3mOlii0qG1uDxUAOD/vxsh1r3BToTW2aoXKYUVyn+bPOTWmKJd9Hx8XFbR63X2P4y8G\nNNaurYia07mL7vyLKzLmchGHjl8P75ChsdB5RCUNY5/uxwxaSOP+elv6EPr1fx5HOayj69f5+Rkr\nleR6m11KYfHHStMU5xcKZvKy9rlbL8qjAPDAuTO7dLqvSRwF8A/XuhPPUxwFgEfmVy+z205h5fK7\nvLBwFGqb28FRAHjfez98jbvxgsVRXMY+jb0CnvbZwhgzA+AtAE4B6I3eW3GFqPvgvUEAAAhbSURB\nVMDd6I9aa5cus6/iElD7vGpQ29wBqH1eNWzZPnflRalQKBQKxfMVGsyjUCgUCsUI6ItSoVAoFIoR\n0BelQqFQKBQjoC9KhUKhUChGQF+UCoVCoVCMgL4onwcwxswbY9454vOyMSY3xrzZ/32L//vY7vVS\n8VyBMea1xpgHjTEDY8z7r3V/FIrnO7b8ovQDb+b/3/wvM8b87NXs6G7ici+m5xqstX0A+wB8nDdf\no+68YPE8egZ+FcCnARwB8C+ucV8U1wDPI1t91tjsIFxNXIkyzz5qfzeAnwNwDFIYqvW0bwAwxoTW\nki6b4qrAWnvxWvfhawDPl2fgRgA/b62df6Yd9Ll8weP5Yqvbwa4VGdyyR2mtvTj8B2DNbbILtL1j\njHmLf8N/kzHmy8aYPoCXGWM+sJkCMsb8hjHmI/R3YIz5WWPMSWNM2xhzrzHmW6/kYowxJWPM+4wx\np4wxHWPMw8aYf7Vpn88aY969adt/N8b8+vBzAHsB/Ia/lg7t993GmIeMMX1jzBPGmP9j03HmjTE/\nYYx5vzGm5fd5qzFmnzHmr/y2Lxtj7tj0vZHH9ZgyxvyxP8ZpY8wP0/cvO7MyxtxpjPmo//45Y8xv\nG2Mmt/CzKjye68/AkHIHUAPwAe85vP2Z+uS/86+NMSe87T1ojHn7pmPe7p+ZrjHmPn+MXZnFK549\nnuu2Ssd5iTHmI8aYdWPMmjHmE8aYQ/6zVxtj/s4Ys2iMWfFtHjtPwjFnf+Ov46Fn81ttBVdrjfLd\nAN4F4DYAj2zxOz8H4DsA/CCA2wH8OoA/Msa8criDfxH95IhjRACeAPBt/tzvBvAeY8w3X0Hf/ymA\nBQA/CTcrO+LPfQ+APwDwPt+/dwP4xc0DC4AfB/BRAHfCUaF/AOB3ALwXwF0AzgL4XbqmrR73/4LT\nI7wLwC8D+E1jzDds5YKMk8D6OBwddxeAtwG43p9XcXVwLZ6BR+FsdgDgnQD2A/jzZ+jTcWPM9wD4\nTwD+gz/f7wF4vzHmbn+uEMCHAVyEe7H+CIBfgNL6LzRck/HaGHMEwP+EEz/+RgCvgLPBoXp6A27c\nfBWAewCcAfARY8xQ8fwVcF7ld8PZ/ZbGw2cFa+0V/wPw/QCWL7H9LXDV6960afsHALx/07bfAPAR\n364D6AC4c9M+vw/gt+jvTwL4oSvs63sB/B79/VkA7960z38H8Ov09zyAd27a50MA/nzTtl8F8MVN\n3/tN+vsIgBzAv6Ftr/W/0fgVHvdDm/b5s+E2AGV/njf7v2/x5zjm//73AP5s0/dv8t859Gxs4Gv9\n33P5GQDQBfD2LfTpHwH88qZtfwHgg779bb5Pk/T52/yx3nyt74H+e37bKoD/F8BD8FKqW7iO2J/3\nDf7vDePe1fx3taqH3HuF+98CJ1D7KWO4gApiuBcbAMBa+9rLHcgY8y4A/xzAYX/MEh9jG7gN5Al6\nfAZuRsW4n9rDqqcPXGLbHgDrV3Dcz236+7NwD8AzgX/HOwG8xRjT3LSPhVvP0rIuO49r9gxcQZ9u\nhfMoGZ8B8H2+fQzACWstl1X5AnZxbUixK7hWtnongE9a/9bbDGPMfgD/EcBr4MbLAG48P3yF/d02\nrtaLsr3p7xxPp3ljajfgBu03Atis4r5ltXxjzA/A0Ug/CjdbbgL4Gbgby33Z/KDHuDwMnk45XWrA\nSKhtn2GbgfweWz3upbBVCqwB4INwv8XmY5/b4jEUV4Zr8gxcYZ+AS9uevUSbP1e8sHCtbLV7mc8/\n4M/7IwCeAtAH8GW4l+WuYrfqUS7ArY0x7oJb+wCcF5YCOGyt/eI2znMPgE9Ya397uMEYc9Ml+rKf\nPo8BvAhufWeIATaVo4WjCL4BwHto29cDePhZ9JMHn60e91WX+Pv4Fs/xJTh65eQV9lOxc9itZ+BK\ncBzO9j5E2+6B2N5xADcaY6astcMimq+ArlG+0LFbtnofgG8zxphn8CpfDeB7rbUfA4qxfIw+T+Fs\ncfNYvePYLcGBjwP4emPMdxljbjYu6rR4gfmH8D8D+DVjzDuMMTcYY77OR+R993A/Y8ynjDE/NOI8\njwF4tTHmDf48vwDgjk37fBzu5rzZGHMrgP8PQHXTPqcAvM4Ys98YM+23vQfA24wxP2mMucm4qNMf\nBvBLV/pjYOOsfKvHfYMx5l1+n3cB+BYAv7LFc/wqgEPGmD8wxrzM/77/xBjz28/0ZcWOY7eegSvB\nLwF4pzHmh7xd/Ru4YLbhpO2v4dbH/6uPfv1GAP9u2OUd6oPiuYfdstVfgQvCeb8x5qXeBr/fGHO9\n//xxAN9vjDnmgx5/F+SxWpfGcgbAm4wxe40xEztz+U/HrrworbUfBvCLcD/MZ+EG8Q9s2ucn/D4/\nDedl/TWAN8O9tIa4EcDMiFP9FwAfAfAncBGiFbhgHsZvAvgjAO+HM4iv4OlrmP833NrhSfj1O2vt\n5wC8A25d8AEAPwXgJ6y1H+TLuESfRm67guP+AhxX/1UAPwbgf7fWfnrEefgcT8F5qXUAfws3k/sl\nAIuX6JviKmAXnwFgiy8xa+0fwUV3/1s42/s+uBn8F/znKYBvBTALt5Txa3CBYQZaQPgFi92yVetS\nV97g9/kUgC/C2eBwqer74Ni/rwD4Lbj19NVNh3kXnI2exs7EolwSWrhZoVBsGcaYNwL4GIDrrLW6\nvq34msBurVEqFIrnIYwx3wlgGS4/+VY4Gv/v9CWp+FqCvigVCsUoTAD4eQAH4YI8/gaOrlUovmag\n1KtCoVAoFCOgZbYUCoVCoRgBfVEqFAqFQjEC+qJUKBQKhWIE9EWpUCgUCsUI6ItSoVAoFIoR0Bel\nQqFQKBQjoC9KhUKhUChGQF+UCoVCoVCMwP8PDxFFdy/sU9gAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe7ed06b630>"
+       "<matplotlib.figure.Figure at 0x7fe1cb50c9e8>"
       ]
      },
      "metadata": {},
@@ -470,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -490,7 +519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -527,7 +556,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -555,7 +584,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
@@ -573,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
@@ -585,7 +614,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
@@ -615,7 +644,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false
    },
@@ -652,7 +681,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
@@ -663,7 +692,7 @@
        "(50000, 2048)"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -681,7 +710,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
@@ -692,7 +721,7 @@
        "(10000, 2048)"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -710,7 +739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false
    },
@@ -736,7 +765,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -751,9 +780,9 @@
     },
     {
      "data": {
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V6pwlc6XREVfcyGh8bkV3qyRnuxZHS6VK2Vemlx/qd8Ud6jroi2uPtxoqDMVb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\nIgkpCYuIJPT/AXzCtKiP5tRpAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe7a1533860>"
+       "<matplotlib.figure.Figure at 0x7fe17f978940>"
       ]
      },
      "metadata": {},
@@ -768,9 +797,9 @@
     },
     {
      "data": {
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OQNIPQUpNA6Cpd74wfr5t17gkr5PyrQCAtnF6MU0DZmOS0q4A4LOmhLHkoKPj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\n",
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9Tjg9blgRl4WlxzxAjyOQ9EOQUtMAaOqdL4ofb9stLsnrpHwrAKBjnF5M04DZ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe7a1994cc0>"
+       "<matplotlib.figure.Figure at 0x7fe17f92f9b0>"
       ]
      },
      "metadata": {},
@@ -783,7 +812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -798,9 +827,9 @@
     },
     {
      "data": {
-      "image/png": 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79XFjuSNFRGTKKQmLiCSkJCwikpCSsIhIQkrCIiIJKQmLiCSkJCwikpCSsIhI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\nRUQSUhIWEUno/wMVBitmkXySDQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe7a18c0a58>"
+       "<matplotlib.figure.Figure at 0x7fe17fdc1320>"
       ]
      },
      "metadata": {},
@@ -815,9 +844,9 @@
     },
     {
      "data": {
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0r+R+yl4+9VF/zL7xvmBR2mPn7m4o2m8BLHo9BaVqzcyNVU3/WuYX60zLF/lj9ugddrv2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\nXkNzVI+ZdaOy2M/TPrTJ34HdG9y3O5V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0PbdQu2fztIz8tz8K25cu+J7fd7V0F0eqmgoYpCF18VOb8uceC7td/bOfurHO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\nQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe7a1847ef0>"
+       "<matplotlib.figure.Figure at 0x7fe17fd6b2b0>"
       ]
      },
      "metadata": {},
@@ -844,7 +873,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -862,7 +891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
@@ -880,7 +909,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
@@ -898,7 +927,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true
    },
@@ -916,7 +945,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -928,7 +957,7 @@
        "(3000, 2048)"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -946,7 +975,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": true
    },
@@ -964,7 +993,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -976,7 +1005,7 @@
        "(3000, 2)"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -994,7 +1023,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
@@ -1026,7 +1055,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1034,9 +1063,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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RFVWsO+2UyNfVmsROL2Ujhve0TkzcW45WKmIGhwYm797H7rEjQGuKDtZwxqbt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gCOZc/gsRU/JSi99PN3l/UdImT1oAsrfnseiiHxOwrYVbiSHUWncOXRp6mOXYxKjBX8hDn8Hgd+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\nvKS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wA7swmO7dC7FmnwU2GzdlZrIsGOSDYDDhNXpy5YSI9OiQ6SvpIG90Mw+6T8aUAn9H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\nKZmFaWnc19CQ0DVVBxalpakAQvlULF68mMWLF8c91tz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L8Z3aWtZHwpyTt4OJjlqq4vmdHdiZpp3OYO3wyBtw4WAbv1iWfFwTcFKhTo5D4A/0Pujg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\n/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mUqxOJ78MaemVxYuDeNP4BOZoZxcnHYSphe9r8M+w8SjQ1js+TzglXFTw8TT9xRxYxI\nw8o2jJVa8tM3SMDyiqO8X2+cisK6iibh5bx5NDi8BncAgiP2PGoyZ3BFXy3RaABFH0pZ8FUhWScb\n2CSm8TtlFcO6jfGL9EDUTnHRIG53mC/sv4xLS3azpuAIGgrvi3JeEzOJxqMFTEKiSx0dIxtmQLNg\nMeuJg0d59jCZ9jC9fjs+3c6W6BTWao0J7geD2wK2ZM/4t88kIRLK7srjnSpJ8HknJWWDeAv8mK0x\nHM4IhcU+fMMWqmb0sWdHMam2juNJ3LktojByzI67IpB0uxYRREfMPB6cx/qiBvSYAGXMEV/qoMcU\n9C4FpUQmRYkYF0jC447Ow9j4tWUdv9If5Sb9CxQcsFNyTJBVPQjXtdNltfDNoavIqVOoesaO9+k8\nAk6FWbqRl+EjSyYyPMaf4FzTg2JPpjKPBxVQ5PJhGQlQZvPRVZCHLACmaxSf+TIzD9Yze3c9iqJT\nNW8Py057nd88/kMa1ylkSx+9KBz2uViipEbcSB1CH3qo2GBU2lsHTW8DLIpfMca1sGT9myDkvz1Y\nyu4Reh7s4wr9LIYpZRefp50xtftwrjGnbLERQqYMbFEfulCImNKZE8ftkBNEU8x01F3F44NfQheS\n/vIoZ4zczA3NP+K3Sgst0+10Vkmi8SkiNOgv1XEMC9SYggUfl3M+lWyOx4pIQoMuLHW3UOavSWlF\nOlGkjtUfpKZzXRJ4SIyFNKF3e3A1NKNM0dneeHncMXVMBixTOTT1C6zI/zNENZTmAR7MvY2XbF9l\nT/gkrsn4DjMGdozdMDUHClxGXpX6XiOJmNuKVpWH09VBm9LM139Zwg9+oDDf156+4R4HFLmNsY3q\nEDS0GeXDh7ik9jeTAggAtys+Gu3tcOgQlJYmaKxPyJicABCfULmk0sIv94QZjkoebFnO4sxWKh19\n8Th7Y/PLsFdhNecm7lEVC9muMQTdGTuQkpvTHQsyZ6QdJQ1Pa2xS32qjzlW5DTQ0eemJZHDzlHeo\nd+TT4PACJKnK200qj2Wuxdp9kAvSJMwCsAidu3iVJrL5qbIB1aIQ1RQCURMagr3DXj6/9mOe2zGb\nf6rzeYHqNOYSwbnyIJezlzAm3qGSvfnlRnvipgUhINseJtseNkL6ZCX1dV42uBtVWp0AACAASURB\nVOrJUYK0WzLZ6a6g1zLGf9HT5STgn5hDeUy0oMKHq3SD7c+kM2NOLzZbLF5vkJKyYcJhBatVx2LV\nqD2Qh2/IRq70carYj5UYD7OG8SfIdHUJVSb6HAvDQL2L6LDRrn7cPLTPg1DBVRbA5omANLQjwy0O\ntsVsbJiQe2NUukbGOywKIsJEc04BN39RI9yUgTRJ0Bxovyyk475OIquCNOWZOXSpimnDEJWb7cx7\ny4o5AIyYk+owV/hJJwLJlOF2bmrezPtTl8Y/G+v2vtnTyesbpLytEyEkzsxBLlj2DBsbLmSoKkpG\nSZDWw1mUVhhgbfzQxY7ZWTBQmEhwNNQ8sfaxdzMnvzPBWTFRpARdCtSmPvjFZrxRKEBDw8QiHuBl\n7mcXn0cgsAUF8449xw/evxS/ORNHzMf5F/nSljs6AmMVjf1fuUtgHTS0XYoU5DapDHIuTv7Epfpl\n/KX/WVrtY8yhuhk6pkl8Ho3qzSZOl9+knHcTYwxgwc/nDv4UDRMq6TWXyS3TKVO2IKUPyGeilkQK\nSZ7eiCsvii5h26GbGP/Ouuyd3LThKjLsvYhRHoliF1PoR0dlj+Vk9q/fzN2bVlM1GM+kazcbi1hB\nhvED0DaMuvMYiwOP8iiPUpe9hHv77+G7V49QrKpG7orx4nWSOAmYFFCFQaoCVA7to3JwL83uaiOD\naFwUdPIDzcycOwdysqG7e0xztHY1/PqXMK0a3Nn/dtz+G+QEgPiESqZF8OJpDq7Z3MnRgIub9l3B\nOd79fKn8fRxx58WR4BHqWn5Difdi3M7UE3SBsFMvhxLGhMpgL+f17GUiX/2oZBOkhEHayExRi0sE\nC2hjbe4Rdg6W4LX6+dA5FSFT8ypICQ3KAPOIHvfcrQNH3bnMcQ0kbJWxCBT09rNpZBqD0sFnlh7i\n8c65hGSqwVlBpxsXArAR4zQOs3Cog8ftyxKml/EihPHPyKwMnpeLkgDJKODo7XawbXNFWh78eCno\nupLQRs+e32Uk1hLj6gCsVmPUS0qGKC0d5JZNzzGjpy0+lrCGQ/ww93K6Bl3EElk3xxqUNW0Ee57h\naBgZNtF7wB3feMZFbMQUiMHgYRccTm7lMA6WNB1md8VUdBHnbxSCrhEH3SPJEQ8Cyfvty5neYoBB\nEW+PGobie3LZY/Wja2PjuX9NlINrI6z9ux0mUCnrQ2YmKspmHKzjqr8/SXFbBxu/dTFC15ETVABC\n16mbWk55m5FfQVV15iz8mIU/vYl3Hu3CmhVFSsH771RQVjnIdLcPswbRvVms0PP58g1m/P5eGuo2\n0h9WQFxGuhwO/V0FiT1nvGhSEPSZsO08DP/cbZyi49+NbsJn8T8c4kKC8SRv5x2+BxCJbJHT+z7m\nUO6K9GGZcaneBP4cBUWD7DaBJTzxWpUGzqKTeUznVUJz9wPzkxuswEiuwkhBmOquJ3i3+GJqck8m\nIzLAhubHKB45gpCT+92Mh6ujv7v0XjIztxPwp57ChRTsmTOFA+6TOTm2leFgMs38ujn34rT1oUyg\n4zydF3mLc9kvloCAf8z+Ibe/F3dK7A8iM22I0X71+OG9lqS2VQ3u5o7Np/Pssa/zucpKOHIkqXz0\ncQ5IioDKbGgwEnkI4PsfXMmtazfSZy9GVSVaDFzhXn609SKUaAS64nTcApibD55euOtLhjpv+enw\nhdvAcXxK9k+7nAAQn2AptzXyyIInOBLIZSRmZY6rA7OSPEmljHGs62mmld2M2ZTMIrlOKeBdLb4g\nS42zeg+gpGV3N0QA17GdX7IBgZEfQcQdD8+glhKGWeA+RonDeK00MQkUEcapZok8dlzN/cfuSna7\nypIWXJNZ0u7NJdRu5qDfy0G/d1KqWiQJNkgwzk3e6AjTAt3UOQtSLx5XyKhaffT3/j4b2TkhavZ7\n458fD/qI+CFNUlw6nF4dHq9OlTpFQ/34rdbxd3Meu/m4YhovWeahCwWpQ6DLynCzE5Ndw+E1wIOU\n0F+XkQIexkpKj3QsphjmCguLxTH6pR1NUdnd5+WoPzOlHB2B9n4x6ApabhT/1d3EKsJE26y8Mc+O\nHlMTt+S5Rjh7/iGqi7sRl0s6dxSx76l5+DoMPg7/Zi/OU8cSqpU0H+Obv/oDSjzWPpjlTAEPAFJR\nCNqtSZ8pqkb+B3ZMPkHMLOLjIWhuzGbt3SVc9WOV6kvA6RAc3fcKW6b1QTWImRL7BS0Eny8Ffawu\ngca+YjtLFAVkclYTVUg+2FjESa+/ijuSHviaiLCEe3mHHzJYICnaezQpJPn0o3/nUN7KtM8DwOYH\nd58J9ziXFk2V+LMNvwrngOFUCdDBYnJFDQ2eBWnLMsUiFOc8x//O20Zz5hxUPYJE4cnq7/M/O7/K\nmY0PxRlc9KQDg47CMCVk0kqCDWJaDszM42Prckx7NAqPqMg4ChRS0DFNp79Y5wizmKnuw24ZJBgZ\nywteXbIRNQ1TagyVlWxiPwZ51D7vOsMBU4J2eAClIgsphTH9D/Ukvks8E6lhi/q4pO43oE2gcVdV\nWLQOZN0Yj8O8AvBFoGsEBJT46nnw3SW8d+cmjg3YKLz/Z5xy7F/YJpY1rwCme8bWIanDRxthuB9u\n+9skT/O/Q04AiE+w+AKHEUJhmrP3uNdJdIZG9pObdXLS5yXCyVeVmTykH8Eb7ME2CZX1eJlHJz/j\ndV5kNofJJZsgp1PPWhoQAlZ5GgGDArYi2M9RW25KGVKH3sYMihyTq3R1BDsngAcAhMBi0slxhOgL\n2BOfpS1DKKygKemzmBQUhwfTAAijDDMaVmKEMBETagJEfPxeGVpMIRKZJLIhuYeJa0Ta6Jj4NbpA\nU1WOZXq4d9U5nLf/Q84/8DEAz+Qv4QXrAkYBgFDAURDG5NAID5oSGpGIz5RwXP1P2jP696KSVkxo\nZI4EybCGiVjM9FushPwqy2nGjM5eCjlIAaqUVP7LRWjVED0v1SBtOmgCaZacFlZ5d1MlvmEbmfYg\nXzvtPWzmGGqcj6RgSTt5c7t587un4e9zE2tyMvhgBTnXN6ILwRmvvImQMmEy8x5up7/ci1ST+yR0\nHW/vGC+Arik0HJgHUgFNEOg3wIVlBJa+YiVrj8LrF2tk3reX0ou8vDO1B6maQDG2y5y/fciAqhN4\npiKuidCpLHyBd39SSLDrbK7/6C3cYWMjCakmnizZwNOWK6la9Vl+v2lyELCeHzNLfYpf9j1Jl5xH\nDm2JLI8zBtI7KY5KZSD5WXVW6bTM1RPRHNYRqPpIxdUnyLD2oJfkITSZlFgMwBNo41ebT+WpWbfQ\n6poJgKaMOQDfs/geFnW9xSH/taziDlSiSBQUNJpZwxO8xI2cRD4H4eRSKHEbmjlcBBaF8Eyrwdlj\n4mhoNn1FCsEsQ0v1NNfzrjiDs6Ztpvbg+STSjU+WCIRkzhe7GqClYjGRPpVuZtFYu4HPlt2HyzUC\nA8EUzZVxv8Q6ccMHeOwxuOwy2Pwc3P9jYwJZVVhdDroTFp0D5VOwnH8+6zIy4NZboe1JIzxzvJgV\nqMpJXWN0HQ5+DI01MKV60v592uUEgPgEi5gs016aK2Oaj2CkCxDYzHkJrvYFioffiGxurX8PUtM0\nJCRJdUgf3+LdSQiER2uE2f429mUU0W/OSJgxpA6hsImaWi+RBSqWSXI4hBUTYTV9HJwuwZYmZTbE\ntQbSWC9Oo465pKYU7uh3TeircdM0+sjDnzi3d+OkUXjYsqmScMhkmCb+rUhMGTHDbJITpW/Qjicr\nmKqFECIxeKMn7hfmLKe4oYeFwSbuKzuVdFoRa2YMk6IlvpMpGR6TJcMWZmp+H8GwhSNdHnSp4M4P\nskwc4qqnX8Oia+hAS0kBJRUV3MRwwnH0PGrYRwH/GFyK3RWk9claAzyogGqcTs0WjaUrjvH261NZ\nNeNoAjzENMGRrlyCUROVeQOc/os32Hr7Gvy1XvL/r5CvD/2VzpUK8w/WoGZaDYc5BPPe38vhNXOM\nNqijFMwSRdeZVWcAU01T0GJm3nzmCvrmh/ALhZF2O85+wRW3Z+AcNBhAdU3hiS8uZu7ujei/NyWp\n+ZWMGJ7H3yf7VztY33IeuRcuZde5U9CVb7OvuJJvf/YGpvZ2YNJ0juQVEjGZ4R86h1lMp6Mcb6Al\nfbIlwKvV8sv3Tuc5/s5sXjGeVJaN8rwOPht+mDctF+AXyQypqgrrl6rs3CJAQl+xTtOi5I037IBD\nazRWbuxl6hktBKNTyW1S6KmUoICJKOfzBFfu+B6WQC+by69M0EInvXpS8nLpzXTUfgmfycPR+WYK\n2gcZ7FlFXc7JqFFBdMCOzLahlXo4TDUSwZXcz3r5KhmuEXBBL3n8ltvZxYq4rkLQRTEPzyqm2h/E\n1eRAIKhrX0t1yUaUCdpRExofsTr+l6Rf8XIXH+MdVtCFhBq4++DVLLXfxxr5A+wYDrI7C07nkGc5\nrsgAq1ufSk0brqrwwAMGgFh3AcxYAO++BEP9UDUXVp4Ftgk5PVwu0tolMyygHmfet9SfABAn5JMl\nzXKEzXonUZuVFcP/CYeAzmuyi/fEYVSpM2v4Ay61VFNkN6h4TUKh0jYTXW5OoYUGiKCgIpPYGcf/\nP15GP/OZrRz1eFnrP8wRcy4NNi8DUTvNLTnUH/Jg9kZ5V1SyjoaUvAwSAyRY9CgRJY1vg4BQSvij\nJNBlBQWkLjhDreV6z/bEwSGomdClgtMU4am6hVRX9qCqEk/Ex+xAB9kyQNRmZsjmgLhPgBc/ipS8\n6auKg4d/Fy0hMTlj5M0dRhhacNqCTnKyQuhSGvtXOlbB0bET8K2TruaCug/psbjTX4OkxDNMR8Sw\nvVoyYoZeN8WeLzl7Xi1rZjUmtAEhTWVfqJDl7bVct+PtsfEEPMM+iqWxQI9/HnNkJ9cXbefAHyPo\n3lSwpyiQlR0iwxVhqrcPVZEc6fLwyHuL8IetiTavnHaUi3/+BrNfbUZ7s5iZhYeY2QhUZRngQTfq\ndCqCyx5+kY3rT6ZnusGQmdfQTt4/FEL2XAadNo7WzOG9186lp7MEPS/EWecWoegCd7eCqo2p+Udl\n/59Pp+CrL2KemarxUkojFOYMYg8cRjNNS5jkNEWl3juBS1WVSEXlz4t+x23bLkITSiJ7Y9JlaLjo\nwEkvzymPct7y2zGV2FCk5Av8nmu5nzvlHXwk1o4+Kta7FXbeNdbu9pl6alSnAjoSz7q3UFQduxhm\nRo2P7HY3ziGB19bKwtKj2Dp7iClmomr63CtCwD7HZXiwsjD2BIWRSu5a8BB+u4I0GevJt0de48Kh\nP/Cc/CqDwsMCPuIOvpQEmXLo5Xb5Df5HPkGLMo6TQoGaZVas1RruPkmdrYrZ4vXE16NlfCRXs1dZ\nnjC/5bSC92hcazHufd4e/CqzeZxc035+uPpVanOXJ/J//G3+Hdzy0XWsaX16rH5Ng5pxESZFlXD5\n15FSUncEWj+SlIQbmTG0C6WwAFasgMsvNwijJkowdtw5S84kUWn/JXICQHzC5GO9h7/o9QhAt5px\nOouZ729LhGiliqDfZOMDdxlSCGJC5YAjh2atmR9H3GRZjAlww8xc7j+4kNNcuxLr1hiJk4Iljbf2\nZNupDjTkFRBWTQSzrWSgkz80wiOvGil+7d4QrpIQj7GIKfQzhX5iiASR02ue2TQ4vOQHBmlz5CTP\nXSmJ6Cr9wbHFUSAR6DAsGOx2AoKX1HlssB7BpYb53dE1bB8sRyKY4exkMGpD98NqeYSThpoSSlTF\nB8NWG7V5RUhFQQC5BPjJkld5zTmbDz+sYGjQlqh1bBSMv82uGJ5qXyJkUigQ0szs68ylyOWnUu0j\nO+ynLTvVrJMQM/x1yvpJR1cCHZGMxHeKWZJRHGTkmCPpnpOrmlk/O5m8x6pqLHa0cVrD7pTSh71u\n0noPAlWhbnpKamhl8lBWs0UjELYwFLDwwDtLiWlj2jGJYNvhSnIygmgXWcg/pRdG8UtB3AltXL1W\nt4VzH3qZnXvWMLN8C07fEFIK9vRewq6mGxkZySKv6Bi+Pg95O1KzQ6aMmSoJ/KuczB9MYC7VJa7W\nfmyVebB2LXPe3JHe/0KHWLsdelVUonxUdA7fXr+ZKw/+nCVdb6atU8OEh3qU6myU4ng+kzgwtcow\nP+AWruMVZKuXqu0qvljyuIdcpE8oIXQO26dTw3wy+kEPZZDdYWhchgLlvNz/M45Ryfn6jVT176Qh\ne4FBiQ1MHdjNBfW/Z+rAHlz2ANs8X2Hfd/5ITbCIkZrkyoYcmTzk/BGj7/cFPIomFdRx5ghDA6Px\ni7ar+FzJhymbbDgDejIEHg6PvWtSIvxRulttHKKQs8z3U1UY4q+ma8k7msf4xGTjHhTPWe6n56SW\nRJrw0fwfGoL/O+nvzOnZhifUEW+YAtOS85QMDUt+8n8aRw6FuXn7F5jZ8sTYellVBc8/D3/4A3zt\na2CKb4uxGIRi0O6DQtcER1UVcgthzrI0D+m/R04AiE+QRKTGI3pD4pSOEGzKmUmTPZe5gW7mSieq\nYiEQaiWm+QBBlzWH5z0z0capMqVQGFZtvB3cx4WW0wCwmwTXV5/FT1tNnCbryBN+/h977x0fR3Xu\n/7/PzPZd7apXS7JsSe69YLAxNmBCNaEGEkILN5CQG0LCNz2kkUpIvhASSG4ghBQSQsklECBgiivY\n2LgX2ZZk9a7V9jIz5/fHrFZa7cok95d7yTeX5/WSZc2cOXPOmZlznvM8n+fzdOBlDxW8nwOTtinX\nMpdUVOKWTMuByzbGKOeuiCElhIWdL3Aei+mkkX6C2Glyl1Lo1gBJl6uAvqCD0rzY2NwUhSr/AHuM\nEvTUQTcJPs5m3i6o5ld9Js4jqtv42N4rUYRElyINDT0aLkURkoXhDk5JtgKZ83RePEZlYJjOfBNJ\nLwQ845pHfkGSNeuaaWvNp6fLQyKhYrEYxA2VSMiC1WvgroxCitBq/Fwa1yy0DuVRGBjivv2/487z\nPkSnt4iJgSCGBH9sdNcOMgd2AUAaCtIQ6TDOvJooWlQlNmhLP5EzGlqy2iEwJ/3+imKqhjPzDOiq\nmlMbVARY4wlOaz7Ejrkzcm7EkkmFgN/BjpYpTCnMQ9PVnFDcjUemccbMFoZ8XnRFQTWMnLs7CfgL\nZvPsy3cx8m/HOPP0TyPsFhY59rMoRV+uGwo7XjqHF397wySLzjgRkuiIA6/BGB+GDlZN47xXdyO2\nXgtX+yg7Mp11v3qGl65bD7oBqoJMeYvO/cJjXPnkvVhkkr0lp/PEjM9QGTo+qRKtojHEdM6d/mCW\nVU8IiSoNrm56np27P5KzyfYwRHJFCguFAyzmMzyCxxlnugecwdFCZud2cyPLuZ/r932Zr6x+DsXQ\nWdz7El/bfAlSSizoyABczP9h5CvF7FlyL1RfkXkzJYUiFgoF0W5mWvagWnORv0mKC0Msjr3OLuea\nzHOGRp7h5zSxwXR7SQk7OqHVTylwQyqEW6oqdfmP8zNj+yTPUaHTNZv9FTOzTwkFA8mrtVdx+ZEf\nmccMAz6VyUPxg5/oHDkGN+77Mmvafp+x2ZItLYh166ClBdauhd/8BoaGYOVKWLIEDuyFNx6HznFR\nHkVl8PmfmIrE/2J5T4H4f0iOyADRiQRPQnDcVcJxVwmz1flMFXlIKdH0IIpi48HkG0QmwRIcVzR0\nKdkSjbIzFsOFTikhPiMuYi7d3MZmLkspD7kmShN6ln08bsl+rbzOOI3lfRzrLUa1jxE5SRR2Us1O\nqgFJoRGjED+jS6grqvH8K43kF8SIxy0MDzopsEZYXtKKWmZgqTR4v38fP2Q1g0VubL4EiRGzvwYK\nhsxsuYGCkAbOoQRGXvYmTwAl4UBagQCw2g0MCapFUlc/TF392OIb1xRefrmecLeDcLeTorkj2H05\nrDVCYdjqMl0jvUO05xUjDJOwaHTjf2LYi2aoqXER+NQoI7oTFZMIS9cEgVY3kT47SIGwGDgKE+TV\nRLA49Yx+FrpDLDh0jFlNLThjcYbyveye20hrZQUHPVOYz7EMH74rGCFYlB2SpkvB/pFKNkZqObEj\nj5qlwTR/xuja37y9lDU/c9OxoI6WM3rSStvEkfVHHEgJSYeNAw11zDt8PI3FySgpBElhRgxNqduJ\n7nNnZVtUFQNfaX+q5pPjQISmsG9fHSMvBJi2phmrS8PYJ7l60zNYi8zsogiQjcVcSQs1n7+XVy88\nm5bpc0k0e/j0529l/pvb0u6KOf1bmdu/GSmUSSxwCmFKOSzez6X27+VskzQUihmYVPmpOKJwfMXE\nBTvzXQ457Rw8Axb9RaYTqpnjoXGU81nd+y2+9fq5/GbOnXxi560IqaVRU6OlvYkBvrjtQ3wLhc3V\nl08YOMH7j/xfbtr7eZTV1cgS91hYZbpJElxW7uJ2fsTXeImx5FIFsR6+tvkSlMgBpFtFRJLIuJ7d\nW10niQ2ldh8RfR6uwISvUpHMvkiyP55rJE2iq6At9b06HPCtb8EFF8BTT8Hu3QTyKji8/XJU1ckF\nx3+WlaxP6Dp0d8Mzz8AVV8B3vpN5gzlz4Iqr4OgeaD8GReUw/9T/9coD/JMoEEKIW4E7gHJgD/Dv\nUsqTQ5b/F8pE0qfJzgshsFpMH7oDiOTY5QkkFsPKdV1dvB2PY2GUj28xH2Yn53M4Y4HJBZYctLgZ\nUe3UxYcyFmJ3MoFiGBgTzMEfOGUvD2xYgRZWUXxazt2syza2+EoJ4SE7saiVnugYinw46ebFrjm4\nA3HWNR7lOyNnEZUWhICi2UHCPQ5kn0IyaiGWIyGBjoKWmBwYpabCvgwJnXEvEWy4yIH0BlRFYvMm\niQ+b90kErNi82X1TpEFl0s+XV11F15RSBjuchDQ7xRUh4rpKX8hNMD7WRyMpqI0GiGgxCj1ByvJC\n7AjU4fZJ/FGNtTOamTfFNNk2+4voyPcyUOah+WghwYCDU7buY15XK2A+u8LhEc7etIPXTlnEvYFz\neIl6HuIX6Wfs7R1hoKKIhN2WZjTVpUCTCt/vWMcJCtGPq7T0hjnlzHZcbo1Q0EbrrhKW3jSFok6F\nSIlC15tl6PMSOUZKUpIXTo/LW3PmULg3TpWtI2usdF2h9ZCZVpqpEQwtN1x4Mr6SsTua58MF4C9Q\n8P92EXt/uxChSu4r+CjWFZnvhkjtums909HWfpQqIZlX8CMWDG3J+BZUzLTSSg78A0Bc+HhUbiAp\nPfQGp1Piac6yQqiqRtfwrEmVn6I2qPC8xrbZp42LoJj4UkHSBcMVkqLO8ecESpULhq0s6nuVRYOv\npQmUJsooYPi6fXeyecplGfPEvL7XuXnP/zH/aBqAMk+OCtI7Af6db7GNNYSklwW9G7h1120cKl7B\nvUsfpN07k3Wtj3L9vi/jTo6xhXa5p/H1VU+l04jTaJDfZdDwhoqqCVAkdi9c+i2VrT/U6MhBOqkr\nVmZ+4lyomA+nnw7RKMyfD4cPg9VKnqbxa+UOfrTsP7JDNEdFVaG5Ofe50X42LjR/3pO0vOsKhBDi\nA8A9wEeB7cDtwItCiEYp5cnjE/+FRTfiDPg34w/uwZBJPM5pTM1fhVVVSObII+HCwlSyP/BTZQF/\nIZg11Uqh0BYqZE/cVOvHlm2BijwpH4RZyhRNsTA+AVVcqBx0V9CV8JB0WCmWIZxCxxOLUBPv59dL\njrK3u4T7xBlIKcZNWBJFSErdEfMvCTvfnEJba0G67lGxWjVU1cBm0xiJ2QnLsYVXKOCpjOGrjFDd\nFGJD/wz0CXYGgcHRWAlrJ7Irpe4UtJvhoRHdwitDU1HsgmJX9sQjpflTWTvC0W4HRkIh3O3AVR5D\nUWXaXK5gYBM6Z/taeKukDiEk66Y08eyOWezTS1CsMmMRjfTZGDnm4QVZSFFJiJVnxOmzFFDj8yNq\nzUyEc2QPHsV0C80p7WWG6GdXUSV19UMMvGpjfkp5GJVRCOiyPYfYpV9PgOmsZxcXG7tQFElcs3LX\nvnUsqu3hzOImLMJg50g1PzuxkubIWFbP4ZAb130KPdsXkzekcs4OC6omSLgkndMTlHRY6JsVJW5R\nyGRSEFxRMY6q2A7/ufk6rlt6Py5PECXF/mjoComYg63PX4hEssPXQOPgC0wUHUFvY+Kk7guRgkRm\n8oQIivQ+6ovbwSjKwnwIIaia3oyiaqBbmDW0Dca932O15BYpoLdxJi/MaETRNR5yfZQvis9l2A50\nqTIcL+Ngx7qc7U9aDXoWjjBQvQxdsVEaaqHPU5f7hoaJNchoAyqz5m9BuhuRmoESScJfj+W+PtWu\nKaGjOLUgUWsKvCslUwKHiSkOHEYMukPwdhfMKzdZHSfWIcBKkm/LW3D3dFO5bydaWKMi3Mw5rY/y\nZOOneHjedzhUeAr3bjgNVeroQuErq5+lxz01oy5/BTQv1qnfoTJcKYmsNpA+leuvUrjrh0bG01AU\nqKuB5R9ZDOoS8+C118LR1LedNDk7bHqMT751C2HVg1sPZQ+CrsPMHC6Sk8ngoImdCIVM18f8+X/f\n9f8C8s+QSux24GdSykellIeBW4AIcOO726x3Twyp09r1Kwb8W9D0IIYRIxA+TGfXL7laMz/w0Qc3\n+vuDSh3WHOyKF9nnMU0zd0qKNNIMdMtHWtgcc+VQRaCG4XcwCptSrIWZHu1Lo/YHLS4erlzJqwUz\naLEX0y7zeZspWAJx5vR1UR4cwaPFWVnSwS+jv6M8aaaMrmOAC5WDnOdrwqaabR0ccKaUB5iIAygp\nC3P+JU2sXHOCpDGxpRIVgxGclJf6s5QHs4TCX9UGuvEy3qA6ii3p9BUiAY9F49SKTqYV+s1zE7Qw\nIcwsohX2CG5fAqFKjKSg/20vJYFgarwlC+jiLl5gJv18oH8npVoQj9C4avk+1vmazd2tlAgkybCC\n/6gn5R6QLF/ZgWoxFQwllTzQQHBMKU5PoqoisaFTpQQQAi6r2DUJnBbcsRjFyQDCgB8eupa/PnYN\nT/7sVr7w/Z/wXGIhdx09lzO3/Tvr3vw4nz5wCUdCmShzBYPQ1BjfXHovE4+tmAAAIABJREFUml3S\nNk/njUvjPPrdIG1zk1z+iQjPKvcwS3amr3ER5xv8kTuPP46q6cikQGt2M/D7Ofzi63dxYPsKtKQF\nXVM5smsJD33jLkYGShEIXjywiJ1MRRv3nLQUbPb7znMRKW4pOQnfhkDg8SuMpyLw4iedSCaH6JqC\nTIXsxiggV5bMNA5p4v0kvH7kLmZuVHEGBZvEOdzD1xmkJHWdYCencrvjIY4ssjI0RRJ3jfPHC8nh\nMwy6al3EU3kz+tw1uUMMARQz+ydghj4Cp8/6GW7HADuOX4WwquCzmzklTiJBSz7RCURzz9ffzNdO\n/0+So5FQR4fgz4dh0wnY3pFzTOo5TEWZH9ZNxzI1L52Q77Km/8uSvpc4XriYNyovBGBP6Vq68hoy\nqKRH47AHa2Hn5VHmnfYIX9SuRL3tXFbuvYsv3ThMVaVZ1GKBs1cLvvMVFXWUC2NgAJ59NovWWsHA\nrQV5u3zdhNyxmNaH6dNNt8ffKo89BpWVcNNN8OlPw4IF8MEPmsDL/0XyrloghBBWYAnw7dFjUkop\nhHgZOHXSC//FJRA6QCzRPeGogZSSaSMHuL1kHS8bXfQQpQoX56hVzJgQVz4qVqFwTXCYvVonrY5C\nLNKgMdJLaTLIjycZ4j48GPS+o3YpGVNgJPBi0RxiigWEGPtIpWSbZzrzRzqxjqPPdTkMfhJ4nLhw\nYrFi+k/8EA1Y+UPZYpo7ClCEgSGzUQrdnV6kBJtNp8QWozeUIJwwJ8hFdPI2Zvjdq/n1rKw5xpa2\n+rTf00AhrzRCSV2Ir0Tfx9W8zRk0Y8EgYHfSkV9E2O5I4ztKRJh+8kyioxw+l84OL29urkEIiZTm\nPt9IWrio/wDv8x5FKiIjLNIqderj/WAxjfIed4K8RIyA7kQikQMqipAYUqG4NITTmWNCEoIoNsLY\n8JAYPUQ+UdpFAUmn5aQKYBg7UkAwmceeTWs445In+P7KX/F9GedVMZvHilexIzGNvkD2omMgiGBj\n3yVFRM85zGvN1eiGijUvSfG0MNv0o9yiHGcT36SJcgI4mUMnLhKgQ1n/IO1HZtB34+kQVxmJl/LU\nA7eRySCSupeQFG+ycOkVt/NZ/syH2IqbGG9Sz7f1i4m0z+Kj2wT+Vnj+dgieyA1p1FWZEeXaSQ2x\nzjiOXEElhqRpx8LUs4Q9XMsS/mOSkTQTtI1mszRQaOEsWlmL2w8zNyocOsPg5bL1vMIFlNBDBDdB\nkWJpnAYD0wyQUNIimLZTYbhCEi6EDApwoeKWIyyVW7GKJG+zgkFKUaSGIyrxDNrxlxkkHTA8NUqk\neD5bn9tArW8Pyxv+YI7J0kp4vTVnL3Shct+yn5KB6k2963tK1/LS1Os4v/kX5vGkAT1BqM6eb8To\nP6MAmSUV0BmAhI6B4LbtH2V/6SoGnGaq8fGWh7JQCzfs/RKndf4JgWRHxXkk5ldxuncLIFEiwCtP\nscrxPCvveoxIQS02G1gtE5633z+psiURHChbTZ+rhouO/RSrTAG7ly0zFYIc2K2ccuwYfPjDY0rK\nKNPl739vKhKf+9zfVs+/gLzbLoxizC+ld8LxXjhJzNj/o5LUQsTiXaiqE6d9Sk4AGUA42kIusylI\nQpHjzFWuZK5i7s6llIyE9tEa3I1uxHA76yjynZLGQABoyUHq4gPUxTI9Qg0McJTiLGfFFqaylskR\n5qMixp0PqA567DmUGGEmY2pxFNMYHaMwlkKg+ZxZvm2HkeSanu10JrzspvIkdzfrFlJSkx/gUF8R\nAphLT1qB0FFoqS6gsngAOagQlTZm1A1QUR5CUWB/TyE/T6xgoNhLnXMkS0FQABfJ9L3MhpuKhJME\nPiPK8281pg6PTr5mubv7z+H0uhN4lERWnZWhYbpcxTTH8nlmYAbjF89w1I6RWu0slpNzfEy0noy6\nDPZU1RHFikMmM7qkofAG9fSSDxIaDhpc/6WvU1LZmXYhvI99nDO0n8/UXMdvg8uzFDiBpLwhSnKW\ni0vZz/zqbh5+cylFcwMU7rEx42UfnGaOwowcJF6DV62ia+uyCUdlqmZJoMRgsEZiWA1OK9zF6kVv\nsShP46ngcr7C5QihmG4jj+CFTzupcEPFIihfIPhxgxlymVGzkAxMlRkvctxw8njow1x74DGYW5Hm\noEARxEcsPPubj6XLtrOKV/k6a/mq6e4QAnSDJi7kDW7jdL5NNduIUsjb3MQmvsAorFMiqTwoCJRJ\nDFR6qcr9IAX010nC+boZvjlBWX0fT3Kr+B7W1LtooPAYN/HM8EeYttVJoExy7BQj1Ucbom0ZDTEL\nw5bqsXtEsnEpo9/30YLFbK26ZJKmSTZWX5FWICSmlYXGoknDfs0LU8er8qDFj0BSGO9hVcfTqFJn\nc9X72VV6NgD5sV5+tGEVeYmhtMXilO7nEP0Ccc70MeuJoUMsinjiJ7hvuzv3fWtroajIdC/k6Ms1\nP1pJ15TbCAc/Sf6Dd8O+fVBaCjt2QE0N75iGFeCRR3IflxJ++tP3FIh/Asm1embI7bffjs+XuWBd\nffXVXH311f+d7foviZQGPYN/ZSiwndFuWS0FVJddidM+kVIZhJJChucYAjHO3CelpLP/T4yE9qbL\nxxI9+INvM63qJmxWk27Rbi0hGu+CCQ6LK9nDtzgr6x5TGc6wLmTKKENEpsTfAZGcmHB+tHe5Ijss\nUlLsC+QgRzLN+hVVgbH5VQi89iRFrhjhiMpy2vk1SzJrdsKCmd0sy+siz5IgKix0SB+jdJR+3YlB\nIKu/EogyAYQpBGUEqGeIE8M+orHcpuGEtPKcNocrLG9n1CsBR8pNs9VfzShx0ahYPBoMmnUODTox\njNxzmoKBm7FFQQD9mCbvoOLg49zAz3kIFR0dBRWDATx8kmtx63G+Gv0z113yGlZbIkPJsGBgSMEn\n4i/yJ/tCwnFbWolQhEGBK8rC+b3pdaOhbIAvlz7DZRt3UmkdYGBuIXHNhk3NrFdKiEedtO5YkD6m\n2s01IegycIUU2ucadM+UWKTGncvvYVnZXjRDgSB8mK084VjKt33Xc0uNl6um2fDaxm5QMA0ueBCe\nu1mCkBhSIKQg4oO2eWPhoooG+V2CAwdv5q/7XKzqegTXNAVpUeg/XMLDTz5APJ5J4rWROzlRfDGX\nnPs7fFWCrpL38fs71gCCVs7O+fzNZyLIG5STE6ZkFiZSOO6PlNRzkNv4FuPnAgWDD/Fz1rCZ+yy/\nH6c8mGIPCaSQDIdqON5zKlPtr6PuyEYfCkAH/jDv8xgi9/crEQRtBRnXALCt3cwRUeoCe+4oL7Ox\nSsZ1o5Esqzr/xFMzbgfgwmMP4k0MZpByKdJAasCRAVg8biNh6LBro/k7MAwuD9jGEWZZrfC1r5l8\nDhPbcc45uFcvo6G/H845xwzbNAzThfH006YL4je/yWlpzJDu7snL9PXlPv4uyWOPPcZjjz2WcWxk\nZOQfVv+7rUAMYL7DE+m8Ssm2SmTIj370IxYvXvzf1a5/qAz4tzAUeDPjWFLzc6L7URpqPoWqZC5C\nPs88hgNvkS2CfM8YUCcSO5FSHmBsgpHoRoyu/uewqC4i8Q4UYSPXoj+fbu4ttPBVv2TYGDtfy3AG\nMHK8aJgTozrhXGEyjF1P5qaflpIpcX/mIU4+p17m3MNrFY20dxchMJAoCCGxWnXmLhz3akhzsWgo\n9iM1nXjQxo3WXRzQyjgQLiGk2zndd4Llvu70xs4tk8wUA3TZPLydqGBPqJwFnt6cvAldZDNClmKm\npH6nvUrQ6aLdV0ytf8zyI4ABj1lnXzIb9OoqjRPqcIIuicesHDtSTOOsgbG2pf5TzQgKMk321eIv\n4Mmdc3A4DZSQIJp0sNT6da7iTeroNTEDXEQk4eDZ4P3MK2xKR1tMFEVKagd6ue28zbx8oIF9HeUm\nd0ZNN2fPOYpzXKTMvIPHWNZ6iFT0KUXeofTD1aSCRRgpDIHB84/eiJYcF2miQfFMUP9Np+3Hku4U\nhu38updZUmq+15Zx9MeXx95iW20D03ZfyMvfFKgOmHMleMph83fhxOuSgvxuCuzNOD397CltYH9l\nI1JRKKWfgq0lFHYoyJTd643gh9jTej4rCh+krX8pgeJFxOO5XYFtQwu4/8kFfOIIFOWD9U5IRiZ/\n9qMiVZF+0Z0j5tDEvLyzQpGS83gSHQXLhPBtA6gqPIiY0QLUZJyLekGklO8n3/geHytewWQ5I1Xg\n+o5v80bZ+twFhKA5fwEbp1zK6o6nxo6Hk7Ct3XzU5zeC25q9qAphJq7KIZqwsKrjKQ4Vn8b8vtdy\nMnoKCfTlSP9u6HDLWTAyCBYrrF4P1/4fcJoKNLfeCnY7fPOb0N4OLhecdZZpnfjqV03FobV1zPUw\n6or43e/gmmvgvPMmGa2ULFkCv/xl9nFFgUWLTn7t/7Dk2lTv2rWLJUuW/EPqf1cVCCllUgixEzgL\neAZAmHb9s4D73s22/aNESsngyBu5zqAbUQKh/RR4MxUht6OGQu8KhgJvMIafl9htpZTkr06XC0aO\nkNsiIAnHmsedS+v/kJqIVMVJRfF5zPHUgjXMJ3vHFuXB1E42u8UQUa0cc5awOJQJorIA5w3u50+l\ni8ZMsClf5LxQJ/laNKOed1IgikWM6xfvoLW9kKa2UgZ1N8oUmN44iNNlLmCqNKiJDRIYsdKpeDm9\npJOu/AIKiLOSdk71dfDKYC3LvCaeZGJK7VX5bewLlzKYdPHngUbeV3g8bR0wgFYKGCaT6dBmaHhE\nHARUFYzgdcYIRO0TeiOxqgYN5QP0ql4q/YNYUgpXW34RQYeTpGFaBTSpkAxZiI9YUCwSZ1GCkrl+\n7IcM2hPF7N9dhiWmMXtGL3GnjdKgn5k97extrEc18jhyopg3D9bQH3CnFurUyFolUMr3uQiAUkZ4\niP/gVEsTahHvKJrFQoE7xhXL93HF8n1mr3RB8L4ZaJe3YamOYElqLDpwBBizkoz6wTUEz8v5NESH\nKLVV8fS3z6PjWKZXUurQfwAWr1B4qi1JSYcFgeCsKZtztklHcH7/bp7+wbmU7jbDdnc/DGIUXKoJ\noJwhyplZ9Qpfr7qasPAQx0mhM0Zr/Qz+GvosPf5ZgEFN8S6GQlN5tfdLZtbHAfMZ2ryQCGTeWxqg\nJ2Dnz+HMb8KZ34YXP8U4Q6E57mfM/ilza55nV/PlvHH0avqmWVCS0PCGQkG3Qn+twfHlOVxT41O/\njvs6SmQPFpGDQjz12119nIkKhL9SEnNJ7FGIJgoY6iolj6acYyqBgCigPrCLY97cG7IZQzsylYdx\nIgB2d8PKmjGXRur7l0cHIZSY9Du3GKYFLWgrwEDkzi1iTWmmugFxHZxWSMTNHwAtCa89DT0n4M6H\nSZOU/Nu/mQDHzk6T2+HPfzatE4aRBbAca5AFnnzynRWIa66Bu+4yrQ3j6zKM3HTY/8LyblsgAH4I\n/CqlSIyGcbqAR97NRv2jxJBJdGOyrYpCQhvKeaa86By87pn4Q3sxjBgeZz0+zzyUHMlxTnL31O/R\nD1MnP28xPvc8XM4pKMKsa43LxVKHg12xGAbwCvWs50DWIi8Arx5nYagjpwJQFxvk4r632Zo/nUGr\nB48eZ2GwncXBtoxyo9iJqLDgkNqkE8zcSDeRqTZuztsKwK68al53Npo+8Jif9YN7cRljDJd9g3m0\nFpUiU5TBqjR4X+HxSc2zNsWg1BqhK5HHsWgRLZ0FNLgGWeVrR7Ea9JEHGbYYQR2DafO9osAVy/by\ny01LARP4OAr8vGTJfhxWHYnCH9UFNDqHUPIUklYLmhT8oXcOmiEYOpxHfNiWvsNIs5uChiCPVPyc\n7fPmEZcWijwRhCKo6ehmzZadKIbBPfi47+hZhAIOMtWxzN9O4tzARi5mJyoGCWHBKnUsk2YJNWs7\nXluFMCRSEcikQFgl/jsWE3qgkZEvLaT48U1MXb4Xi54bp6GFnbzwxqX8vH8q81+3YgtPbq9ZYKh4\n7Vo6XbPTEsvpWleQuLU4nhMWpD7O5jbu/6NL6+HOs2kbWEJtyU48hCAKdbedwc3fX49+pA+hSJ5z\n/Iq2oWVmOHGqHshUHiQSf4UkOa2PAlcXgcOtyJY5rLhtBlY3vHg7JENj493av5Rl9b9j3YJ7KK/c\nxRcKf8DUXSr5Peb5og5B2zxIOsg0YY3PHz/ui2gRjSzmzXRGz1EZdUsFEx6Ec9TKk2qzAofW6DRs\nU/EMwxD11LCFXLwZAni2+FraXDOzsBejsrrtcXSh5rQSACbV86stMLMECp0QTcJgBDG9EHpDGN1h\nlAngFIvUeKv8XGqG97Fh6oc5revPueuuy0caEv50CGFIWD8T7BPmQMOAg2/Bkd0wc5wFQAiTnnpH\nilIomeQd5W8p4/XC5s1w883w8svmsdpauPvud1Y+/sXkXVcgpJSPCyGKgW9gujJ2A++TUva/uy37\nx4girKiKG93IYYrDwGbNnRdBSo1g5DAjoX1ImSQcPYEh4xR6T0mDL/NcMyaxbkwu/uAuFGHF45qa\nPqYKwc/Ky3lkZIQ/BYOEDR9PW8/g/fHX0zvnjD5NUrcApscGmd6TDWDKJdu9tawcac55D4DyRAB1\n3MSzONjO1MgA9zjWcGt4N9YJk2pJJEjCaqXTl3ImCzGp8jAqiXEgQR2Fw5FigqqdqwoOsIQO+vAQ\nlRaiWAngQFeUjHl2dlUft79vE5ua6ujx51HkibCysZW6EpOtUkp4zphNm+hljeUEAjgYLqEv6SbY\n7koTUKUXDSkZbspj24ULyPfEyBPJ9Lm2qnL2zGlgyb4jbNs5lQiTEAyZFTG3tItHQw9QG+kbK3ES\ndNGoGiKAurZOog47e/xLiB0tJPyLBhLbUnwQhmTwwysp338kZz3tRxv47Q++SEnMSZEC6kkyhto8\n4K0UnNtt47XUs97ZP59KVy9qyn0RGCrkyNtL0A2VfdMLcA6887SlCI1j3SupLdkJgG5YiNxyD56+\n46ipB3hArs0CEI8XQ0iOrtQYrhSo5HNC+tgp5nP088/ymfXPs/vh29Bimdef6F/CH7bcy41nXc/8\n0ldYnbcfZXgqa697grkrtqBaNA7vX8RD7ZdxJAX2RUpUI54ijMqs7zl5OevF7xkNT4ZUjhppEEna\nWHb0CfYtWJa1+Mc9sH+djnME4v03s2DXryCrdjhYeAqrTzzBxprJsWN2PYaYLIx0tNKBCGw+Mfb3\nmdNMa8T8MuJ93Vj1GBapp6Ozdpafw66ys7ms6Udccej7SJ8dMRIfa6AEqn3IqQUwEkPo0nSTTFQe\n0m1Q4Pj+TAUCTFfDZBaHiaJpcOGFf1vZadPgpZdMsGY4DFOm/G0AzH8xedcVCAAp5U+Bn77b7fjv\nECEExfmn0jv08sQzqIoTnzt3KtiOvqdSLgrzw9WNMD2DLzISMqmlLYqL/Lwl+DzzM0CUf4sMBd6k\nyLc8DbIEcCgKtxQUcEuBCZjaodmgbePfXOd/RfrsPvZ4qlkYasvJNKgiGbB5MIBjzlKOO4uZP9TO\n9PAA1hwMDwIoC/rp9BZkTKaGTCX+mYDqC2tWBpLOFJDRFLuqs8BrunOsGFQRAAHN5BPDQideSkQ4\nfT+AioIgV56yN+MYmCPnCYZY03+Q15nFQk8PPkucE1EzjC/c4yB7Sjef4xstNZw7fwLRlRAcmDGN\ngqZhXo3PmWxY03KL41Wm9vVl3UGKbBeSATRTwg+Lz+Oop5Q1HU3MfNlP96dzTKhSIENWXn7sHC6d\ndRgCPYjU4qZrKn+47w4SMQdCCtR3mLtXfh5+fVMA5wf3s/6CbhIJC29tm8Xq8Da8RojtL5zPy3/4\nEGlG8hzA2lwiAVU1TeRJzcb2PZcT6VXw0MM8HsMjezEmmf6Ealoj+qZLhivMYzqW9IC9woUsf+Zz\n2Jq3IbXTJlyt0j64hKffvIuLV3yVG2bvwfLlh/EVD6CmIl1mL3iL783ay33f/zZN9hKmuR5nW83F\n6Dl4XPpEJV+QD/Ip8Q1qMZkS/RThkkFs+9tpmbcSO1Hiwjmu8xKrHsOuRwn5Cnnbt5QfWH/JJ9/6\nOA7dtIYaKLxaezXD9hLmDmw56Vg25y3Kon8eHWNR7IKkDiOmS0G6rWgLa1CLXOY353Xw6XWbWH/k\nJyzqeZmw1cfLtdfwau0HUY0kva4aWvLn4xRRpq8ehN6QqaxUeaHYZW6WDqX2kgl9UisJ0gBfYfbx\nQCD72KiMt/ooCqxeDZfkjkaZVIqKzJ//pfJPoUD8q0uR7zQ0PczgyJuMuhVs1iKqy65AUbJR/LFE\nL8HI4Zx1ReNj2INgtAmHtZKK4gsJhA6kwzgjsTai8U5OtviHIscpzPXBpaQxEaEjJ83UO0tYsRFQ\n7ZQlgzmtFRIIqnY67AVYDZ0lobasMgYwZPPht3n4Xdky+uw+XFqM+dYOZln7kZHcCpPVyGSqG50f\nJCJjF6VKgyWDrXwUjS2yjjZrAfnuONV5IzQo2W6lafgpJ8weKthPGXUMk5eKgghgpwMftQzjSYXa\nSaAPN312B3c3/Z7NfY28MjAbKlVUYdrcpTb5jmV7cw3vm3c0a67UrFa+sPRqOPmcjwBWTfIOpetK\n8Y1a0TlKOReKOxgOudAHLLxFA0UxlQ+f5Pq5RjXi9NvgxTsxknE0VFoPziU8kn/yxmFGTcy+O0K7\n34/z8U0Ih46wSuyA5+IQjx5bT+M9YXb8/qqxiya1nGSzOUppYWblBsKxAn6x4bf4w9UoJDCw8Fdx\nN/ML7qZ++FkOy8uQEyJtpA5zPwj7+wxyoXUUdF6RF3Bp7bM0905UIEzZe+Jippe/QcPZLThs/Yhx\nLiNVNcCW4Oy1/0nkFx9HlM4lOc2Zsx4ktIQWcLv+BNWWY0wPnWBFdCvLpj6NWFzGZ/kqEb7Hj/ga\nm1nHqR1P8/Fdn6I41oUEQtYCutzT2Fj7Aa4/v4kZw2+hSJ29JauJ2PL5xV9mURE6Tkm4jQFnFXJ8\ntJQ0mHniMIE9H+YEv6WareP4VFSTOG1RJUq+HSJJdEMgPXYeErfzEe7FwEzc5fJo3L/kJxhCZXXb\n41y37yvcvPezPDHj0/x6zld5vda0flSGj/MJ9/dYlGe6HIwEKPu6oCOlBCQNaB+BKb7M8FEjFemy\nZE32+K1aBa+/ntsKsW6dSV/t8Zi4hltv/du5IN4T4D0F4n9EhBCUF51Dcf4qYvFuVNWFw1Y+KQ9E\nNJaD8H0SiSW7GA7AtKqb0vXFEn20dD6MISfJPgOIdzDtHySSI/7gnSWiWPld+XIUqXN171s4jGQG\n2dSoibzDno8UghZnMd02L2WJsTDKUdjnMVsVSNNSARBRbTxdtoj6SB9KJHs1kUBcNR0io7pCDx7s\nQqe9zcsyRxt5rjiuZIKScACrYbBWHifZZyU5zUGhN0KNGMEyTnGyahrF4SA2XSNssyNcBi1KEXtl\nBTaSuEQSA5UgdvbgxE0CGzphbCSw4LbH2LhwPqXRIHMag0RcDtaHDyFU6HPno4VVJi5QRYS4KrqN\nWZuOIiutHK+dQsJi4UikiAPhElr0fIRipNkSc8mZs49hGZxcARzAww+4AAF0UsAuavE7neiRsXRL\nw+UG0TwDZzD3fa66wgKFU6HhbOKHXmIb9bweXvuO0SnCIpG7DvOYe4j5m2N4UspD+rwC3sYAu166\nGKHoSCPzXR2vMMi09WgUpZICH3qPsLdtPXtaLyISNxVlI+XykVKw2/952ta2U7c1jIh5kKNToYDp\n74NLHoU/fQRC0ezeGChEceGwnTwc7tm3vsyHzv0O1dOyHSWqajBtnglObSqfi2LoGDlDoQVzNijY\nEgowi8rqVpaf+nRGCScRvsDn+FXnPm7Y+rlxV4InOUyjfycN/p2c2fpb7jjzNRIWG4Ywx+K2s7eS\nVBwYQpjYIUNHCgVFariSAeZt99OBnd/wV07jbhbwCHaCNHM2BYviVOYfNb9rt42o9PAtcTe7WcEu\nTuNCHqeW4zSIgxyUCzm97XG+8MaHMBC8WnMVDy3ITDTW46zla/q9XLfhj1xifAJGEmbExXjZ1Q15\ndihwmoqDwARYbj4BA0NQPQEA/o1vwJo1poVhNOpCVU3a6meeMaM13pP/srynQPwPikV14XFNf8dy\niuJ4xzLjJZboIhJrw+2sBcBhK6W++laaO3+Olov3HYU89+Q8XSMywcPWADcpNtxGIsvUnWuBsFmK\nsFmL2WjXCal2pBD8pvwUlgVaqYsMpK3P+XoMgFmRXo6HSjjqKefJ0sWcNnKcOaEu7FKnx+Zli286\n7Y7CCShOhQSCJlc5K0eaceuJrIRfrd5iDCFIoNKFl27yUIACe4Q7N57L12c8T73PjNWWEl4daOCe\n5jNZM7sZhMAjE+l75kfCNAx0py0aCjBlZAhvWYyIYsOBhp5SxJJS4ZgoYgg3YSRVxgi1xhBCFTTP\nrKU1RVWNECTdVs7zHGeo3s2uPZkI+pUc4XF+jJ0kslOgdhos2nuYOxZfw+tKAwKJooJnSpRg28Ro\nGYnLluDyZSbB04ljFVT25k4n8xcW8vMUB4iKzkxPB12hTFOsYYEdNwdY/YN8pJAIOebsab4ySG+l\ngyJs4K3ESYIzOUhdfZhHWcGkMTYCnFcG2ec2rTyuJf0ZykO6J0mBcBhZyoNZhdmOhAMGaiS+PoE7\nM0qY/sAM+gO533GBAENi+Ks4vETnjNZh4o4S7F5YcB0s+xgoaFQkBENSy8LRCAwW8iZNsUU5rR/p\nckISsiXS4NrxYkgI66bVQRiQiy7bHAiwjOOAOqXxNznDjZGSazyPZNpLbCpiVgnU+BCKYFrXIFe1\n/YC+upm8wBUYQiE8juMBKZGKQlXgCEt7XqQycIy3uR9zNCxs5E42cicACklW9D7ElLqmdGNcIkwD\nh9jNCtqZxgN8HgBVJlnZ/iQ37PtyOtrijzPvQEgdOW5sDcVCQqiESzrhcDT3iCR0eOk4lHtMJSKa\nNC0UmmFGWUyUlSthwwb40pdgyxYzW+e115oZO99THv5/y3sKxD/od+RrAAAgAElEQVShBMIH/u5r\novHOtAIBYLXkUVP+IVq7HsGQCcaWQIPi/JWcLIjyLTnI/FAH7lSYVdr9jBlKpyOwTnBvJLRB6qpu\noN04gBSmGT9kcfBq4UxeLQSkpDY2yGX9u5ESDofK2BuuJJjvoKQswmsFM3gt32R1zLLbT5gxNUXl\nj6VLWN+/m2LN9OnqCHZ4a9nqmZ7VNwMoKImCVfCpA5cyxeGnzB6kLVKA3+WgYF6Q5mAeJaEwlw20\nMNhQjG5RqR/oSVtMRmu06RrThvo4XFKVgcKwCIOZ9HPIgDVDTdRGBlGApKLQ6S2gNy9/XB8E3f48\nlhV1sIvqdO1WNB7hZ9hJpng2zIXVHk9y694XeH1hA1bVoCIvjLd8gMQ8lbamfI4fK8aiGKyY3saF\nCw5hTTFYHp1WQ31LByWDY+nHAY5Tyle5NP23jsqBUKYiMyqdNw6zdWqcWT/Nx9dkI1qqcezaAEdu\nGOGpoI/Z7iKYehrs+i3ddjt1nGDh6a+xe9OarOdgPkto/UjzmIvpJIYwtTqMdnRyO1jSCZpD4vaL\nnIu4qkTRjUlcAwIsSeibrtD+VhGrPgbn/lDCS4/D7Q8RHAgznY9xgCtM/3oKn6CgUSgHWJ14hTum\nPMzUw+AI5VIiJLOmvMxLXWcwp/rRnA14teV0AIraVbpm5waLFHSBMu49K3S35+YwEjDsraTI2Ywa\njYMqYG2duVsfNffX+rhc/0/uT84CW444qlTF3Z5pLO1+Hl1aUNDSlpvM3oGlvRfCzbCqFhwWhJSs\nE8/wR27IKKsLC/MDW6gIt6SPdXoaM5SHsW5I+vMqTzI7paQnZP6AaVE45RQoH0fKl0zCG29AIgEr\nVsCmTaYbQ1FyYyjek/+SvKdA/JNJLN7zX1IgLGo2d4PTXk599ccZDuwkEu9C00aIJwcZ8G9iwL8Z\nn2ceFcUXZBFZ6clh1g4fyfkRH3eWUBMfxmpkm8d1PYJVsYJM5lw7VCkJJO18/tB69gbHaH3dnjin\nnXGCPG+uNNATJPXxz4z0UKxF0hYRgWRRsJ0jrnIGbRMJmiRSCD556ibu3XI6bdFC2qIFeKpiFE0N\nApJQwk6xI8K++umU2KIIw6ClsIRa/0BGXwXgi0VRDR1DVTOOG1Kyvm8PhYlIuvtWw2CqfxCBoMeb\nT/uQj99tW0hfIC/VHSPlbhGs4RDFZFuMVCRzwl1M0/ooqDKwKGZyLZdVI39JL6cvbKWRfuwTqK91\nVeX5M0+j8fgJ6tq7cIejdEe8nMWXCDHRyjWqImY+OH+zm6EqhQM/HsZdEcNiN+8hDUiMkjzZXOw8\n99MMNj1LSdMIF934cw5uX0EinmPxFjqOvxQTW20CUfusLir0EELNtEIIq8QYmZzhUCDwDIMyKY5E\nUp5/hFCslJFIRVa/hBQEi0wTuG4R7LgfZuQ/y9QD32JQFHM7f2CQkgzLgEUmOYtnWdp1iJ93/YSR\npT4OrdGZ/4KKqmUqEULorGj4NVv77+A/W9Zxcd1LaClrikXR2Tswm5d2nUsd4BnROfXgZrbNXoVi\nJNMWD4uRpL5lECGqkClNayRSjtuRqRCC6VZ5RVzIgZWf4WsbLkKt84HXnrFYmunKBbs4DUNMPvUb\nipVvrnyC23d8lDk8zgE+gDERJ4KVOTwOw1EzsdbqqSmStmDGUCtSwyXCzO7cmHF9WaSV9rwZMAE4\nKqSkPHyStNq5xGqFBx4Y+/uFF+D662GU28bjMUMsb7nl76v3PXlHeU+B+CeTcOzE332NImzkuXOn\norVavJQWrqWr/1nC0eOMgxcyEtqHrseorTBBTD2aRp+mURw4nJPnQQAN0f6chC+K4sBqLWC5jNFp\ntGWXEIL6aB/fPbaO/cGKjFORsI2tr9dyzoXZoMHRa8dbIXzJCKeOmJPM+KykVqmzdvgIT5RNZFkT\n9Oge8r0q3131Zzo783jFMoMWr49R+0KN3c+lJWOgQ6koDLrzCNsczOtpm5CYGqzSID4hdsQXj1GU\nyM35URkY4pi1hAc2rCChj103lkND4iNXqO+YFBQlsShKFiFWwOKkM+RlmsefqnPsnG5ROTRjGlp3\niFUn2ni5ZOW48M+Jkq1ExIfM0MJk0EKkx07xvABWt44QMNdhmoA1afBrT5SzLFYEkg61AM3IPbUo\nQmIdGBvNdpFPgRbHIRLmrQ2TcyJ4fyPJne+Mblc1mMyFYFGTnDnvPp5+87uZuAkhCRRLgiVQvVtg\nD5tWqke/dhFe52KCZx9lyFmMRM34CDRhpf3VS+kwFA6sNS0GzoAgXCDx9me2YdXMX1DiO8b5PMX3\nDnybTV2nsqpiO1YlyY7+BezoXUTjMQugU2o7wI3adUT6iml1zGJz4gz64yXcsf16AgvX8MueP1BX\nvoWqwgMMBqdSWXgo4ynpKCSx8Rcuo7+wgterr+TMskyU7UBgKi/vvZ2mrjMInCuZyNA+URIWNz9c\n/hAP9qygLXk6I5i06wIDAytruJNSDprPrCcE4QTSaaU3XITwGMiUYlAc7SRpsxGz5mW0+ZKme7lv\n6YMZ9xSGjioTnNPyyMkbN1Hy88dSaTc1wfr1mVkxQyH42MfMXBfnn//31f2enFTeUyD+ySRXVEbG\neWHPAEcKrFSXX4WqTO7P0/Qww8G3yYaxS0LRJnqivXzdb7AxarJFXoOegtdlKwoTKaxHpch3GgYq\nrlg+BUobQ+N3lEIwNTpAvj/MxqFsF4OUgnDITn+vm5KyMEKAT4vg1JMMWt1oQqEqHkC3eBmxWGmI\n9OdUcBSgJj6MzdBIjBJupdCUYYuDiGqn01HAEnsra/1NtDCW1Ok0n0nLm0FgJAQxm40hl4fiSChd\nXUJVianZGS/diVjOdoFpidh1vIqEZsniHhBIrFaNN5PTJ8WYhFQ7qlfJqWAJJDv6qnnxL/Vcl7eZ\nRVO66JtSxHCBDyWeZP53n8Hb2seBYi8VSjNG0eQmXAUDCzqJLI4JgdRNoquSuQEcUmHfcQv11Rr5\nRVGCJNlSOYs/HljMsyzmkgaYctigqNjEmwz3lQECw1BpmLqffukCIdBQ2W0vZ8oDXgpLRyBkJfzY\nVOIbyicZyUwZrNUpaREMTJFoNig/rmJNCISQNFZtZH7tcyhC44kD34CgC12V9E2TtM8xaNiqUNSZ\nOdqBaCU7LKXZKZ8BISFQD2HFVB7Kjwqm7lZNfMiE8kndhSIkZ/ACR5jDn4av4eBwvRkCi2DKfhVf\nr8BZ08T1Sz6C1ZKHjzjz5R4WKnu4ny/w+pKPcGHxc9zx/jNwWMPohooidKSEEHnkCTOPdw9V/JBv\n0E8FwtDZMuX9nKltSuuCgUgZD234DXHNjUTQ2HaMfbPrkO/AW5BUHXzp7Ce4//mF7ONa2lmFg2EW\n8Cg1E8OAokmE3cKsLc/xiFbP0YLF+OIDzBrYyo+XPsBrNVcxZ1y46LnND9HvqubxmZ9FT+X38SUG\n+Nwb11AcnQAiH5/ILpf09JjU1NOnw4MPmuUmllVVuOee9xSIf7C8p0D8k4nXNZNu8ReknJjGWeB2\n1FFbcQ3h6HGi8S4sqgevZ85JlQeAeGKAXLkwwJxjftf7JsuNAeZg43WmsY9y1nMwZ9nJpvRmSrmy\nrY1G/RgfF1s56KqgxVmMgqQ+0seMSC9PWBeepAaIRqz49CjnDeynKmEi3JNCYUdeLfvdlYQsCj4U\n5sTCJ11a5oS6iKg2mp3FJEd5jgGZ+r0zrxZPT4hQpxMtZCGWUNnbUEnp7GMoE9wAQkqCdgfFkZDZ\nfwHt+UUIITJ2+lJCQpk8jbYEuoLeVNrvCQoUAgzB1Rfs5/Gty/nA8PZ0PaNj/tPqs8a4ECbWLWF2\nspN79F8h/YAf1P2SYHOAwd39bHz4FjSPw2SWVBVu69nIzzatIKZlvzcGKusr9vBk98IcwD5BImAl\nPGShv9XDg/Ek9+9PcmUjyMXw7OF5dJOHJabgPWs//37tryiuNGnEB7oq+cujNzAyWMI1Nb/Ge2gp\nL81YiK5aUN/O49jGOvK3uSnoUVB1SeOSHcxZ9iaKqrPh8avx95dmdF4KSWBakg2/7cHf5EFPmlYd\nawxWPuHg7H0hlkw36ZdnVr3ChYaTDb3X0matZbBGoaBLZCkPo32Uk/jIFQssuBE2vAqWMNTsSSWK\nynie5sL1dvN6Vs38BS6bn5uVezifJ9kuT0fBoPfNs+htM5XXcxffjc2SSEdQjd76Y/J7fLLkES7o\nfRxHrZlcT00pLlJKPs0juIiSwEYr9WNjIwS6tLP7yAW09JyPVY0RS3qIJd1YSHI1F1DRtJ3PVm7g\nWMFihNQpinWjCwvDzkzLIEBPXj1dBdNYMXwfKybLLiCASBJ2dkMgTintlEbaAdM6sqj3FR5Y+ENu\n2vNZHHo0fcm1+7/G+qM/4WDRqTi1EPP6N6azcWZIcTHcfjt88Yu57w+mmwLg6NFM68Oo6DocPnlY\n83vy98t7CsQ/maiqk6qS99PR9xRjy4eBRfVQWXIhQgg8rno8rvq/uc7xqb0niobCOuNtwFzI1nKc\nJ5jLQUqZSV+W6T6XxLBwu99CSOpczl5UabAg3MmCcGe6TJOzlBZfCYpiYEwSfljgi3BF707y9DEL\ni1UanBZoISlUdvqmMkISizaUsy2jo7XG34QAEkLlL0VzaXaVZJXtqyrg7EYT1BUM2Ni7s4Lm1wv5\n2No3MgjlDARGwrxbQlEZdHnQVJWJaTINAdudNdSKAaxSZ+KSMujykO+JTWK/kRS4o5TmhWlfW8tb\nx4PMPtKMOxan01nAA1Vn8qfSJf8fe+8dJcdVp/1/blXnMDM9OWqyskZZsiTLsmRbzhEHbDBgggHj\nJS8sixcDu2CzGPDaXoJZjI3hNTiAsY0jiraSlUZ5JM2MJuc83dOx6v7+qJ7p7ukeSea8+1vz7jzn\n6BxNhVu3blXf+61veB4q/UNkOwLJXggh+Ezrm0mhJcusTLZ/+VYiFhMIYQg7ATNyhrlh0TF+vy+m\nfTCLdq7hIJuZj10NT+F/MjBUZ5TVqiFwjwheCEm+dOQ4n9n7KCdMc9kZvoN/X/OQwXcRRWZ+Jx/6\nxwcIjjmwmkNcc2wf26vmY/rRDDK+WY6uSqQEVRfYCvu4/uO/wOoYQwhJdc1Bfvejf6L11JxYH+aE\n2PZID/0n0hJs47ANtn44wIdLRrD+bIRAyMVTW5+ga2gOioiQD+TWm+Kowww404coKm/A73NS31FB\nf0myIaFpUDNP8Je3JFndAiUlqZWxbXnkUeSWRsRSC+Q6KaGJNH+AN2u/QnfbciSSQMkwNZZ3U46x\ngsZy8y6YkZ6YQIyJTeIagtJGG+VM/lUqIXDsX8KfQ9cjhiKGRog0pvk1/BtlbEOJ6Pxo8zpqc9dT\nNnyMXL+x2J/2LOGxJY9yKmtFrEGpkxFIlmWf2E2UX2V3W+oDhELA5OCqxv/CoiWXlWcEe1nd8VJs\nQ6YditOgaQhGgobn4CMfMUIQ990XK8WMR1ER5EX1GKuqDC6HyUaEqsKsqSvPpvG3YdqAeB8i3TUP\nu7WQodFaIpoXm7WAdNeCc3oapoLF7MFpK8cXaGLysqCix7PoA3AzR/knrmQlLVzH8SnDFuPYTRkj\nUqCiGcyNKXDIVYTVrFFeNUDDqSziJz4hJFk5PpbaW0n3BVKev3y0mQNppVGdi7P3ZyKBUWpc23eY\nJwrXMGqKJQ1KxIQgF4DLHWLVuma2vlVJXWcuc4tikryZY6MUjgyCClZdI987zAFvAW+Y5zDT0c9i\ndxcmRUcFLKrkUHYJi/taMEl9wqDxWaw0eXJYYW9l8/EqtCRXgmDtrDMIAR5LkCNzqzkytxpdlwxp\ndl7uXAgIWofcpNtCmBU9IS2kqqedyr7OpHE4U1JIxJZCJVFVWFTRxXMHwtys7+UfeZVSjHLP+3iJ\n5rE8fhsX3onB6LcSgdXP2Vi4yYI5JAhbJd2r17M066e8rHyaG2veQKCjxJEnKYpE0wSt9dU400Y5\ndbmd8EkP2d8sN/bH0V0HuzLZ8sJtXP2xXwFgtQf42D9/h1ef+jj7t2wE4OgXB+lTTFHjYdIiKuCX\noznMKvoxO58spGvIWDjGF1LjjPEvdp3Lb/8NKy57AyXKFHlDXw7fOfR5TvkqYlp2wKKZYLOd/d0b\nRx5HcI22I7cKztgu4U3bg3QNL0JIFRNj9BaYCZamftfHMX9oB8ezF3GY5TjwsYZNPMI32cvaBGIq\nAKSRnzC/tp9AyPAkSExxnnydcv46QQRl0YOs6Ho9oYmKwVp+sPUyPnv5QbpcFSh6mKVdb5IzOaQQ\nhSZUem67l4Itv48lLE6CKiNsnfFBPnbkPsQUXlDAeISKgGVFRvLn7Bw42Am9Gnzxi9DRkdp4AOPa\nAwOQmWkkSj72WCxvaqKzGnz5yxAKQFsDONIgv2Tq/kzjvPC/j7z77wQWs4fczPUU5lxLZtqyv9l4\nGEdx7k3YLPlJ21O9ABqCZbTxBxbhPw8bs1oNYUZHQ8E3RXaW12RDCsGCxV1UzupHmZBplhQWj3DB\n2hayQ160KfwcDj2MNSqcdcaefV4cmUZ6pGSuL3kCTKijj/5/5pxeTndno+kCXQdrMEhVXzdWJWZs\nKMA11FEe7uPt4Rk82zOXSNSjUsIQPSYXBwrLqM/KozUjixO5hRzLK0ZTVTKdfu5auxe7ORx3bZ31\nc+q5oNJg44zPwVAUQaY5wEyHoS0S0kwc6cymfcTFSMBMMFqBcOWJ/Ya+wyT47UbYIhXMqs715oP8\nnCfJc4yyc2UNz9x8OU/ffCXN1QU8lPdc9H6NkVbjsgI2PGln6euG8QBgDgoyt1byyoFvsp81VKW3\nJMhwj0NVddyeQX79ve9wpK8G5x9ykKYUHBC6yuEdaxO2CSFZudFY8KQicbWYiPhT14BahwVzPmPn\nhZ9cRufgXM42za256mVWXv7ahPEAkOHp54ELHqS0JYBtxJDhTu+Grh2wKyo9M5Qn0ZWpjYkXeJYf\n0M+DDPN04C26h5YiMtr5Kjms55uk9Zhozs9CDgdTxvaFEGxWr+GrPMlv5af5BV/lo7zKXi7CeKuN\n2iNjQCT2yCgfOXI/Wc1qjBQrChedfIaFlJ6DvlRFx6wHuf70owBUDB3my3s/lfJYiVGemT9wAr7+\n9ak5Fe65BzZsIKJYk3J/EpDrNPQzMmyxH8GifDDp0NAAtbVTnxuJwMmoLsusWfDii4n00g4HPPoo\niEG4+2L4xgfhC1fBP98OHWdSNjmN88O0B+J/CVTVyYz8OwiEeghHBjGrabR0/5+Ux0rAgsYqmieo\nmc+GIq2F1ZxhG5Vsp4LLOTkxZfeanbTaMrHqYYTUURSFhUu6mDu/B5/Xgt0eItM8hk+1MqLaUkv6\nYoQjxhMj300rw6RrWPQIZcEBzHFf+8n3InBHjC89IY3s8FQhbkUBT6aftrZsdjeX4PVbWOxvYX6W\nwDRpodCAK6ljN2V0hVycGMumxtUDErrGnEihEHSYsMTlU+iALgVzCnv5l+v/Sn1PNpuOVZFm80+M\near+a1JQaB3lxFg2IAjrKm1DLiwmBzX5hkZAc2YeNZ3NSYJHWf2DSDXF4iklDn+A79mewyusvLxx\nLQGrZSKprqGsGFOhxidqd7Kzt4LuoAurS2N1ehZvHdSY97Z5UtzfyAM4dOZGTPMkPf4syt0tE2JY\nE2OgKYz0Z6NJlY4nViOKQ0ZmYoo7D4esCTkmQoApangJXTBaHsZkS70grX/aSnrX+H2fLVtGcsEV\nryS9D4qqY3f4uNqxm63vbuDEeh1/GgwDb2yVKBGo3KNgtYwSDqRhMEHFSalHEcCD1exF1UJouoWV\n3t9iIsBW/g3NBFIRDNVFyFhuMZ6dEvtqrh8qY2uGwdUxXnIpJ7hBJnVYCBzhUT5Y9wMeIDlP4Ebu\nJJvzi/+rUmNt6/NUDB1mQe/2KUdPYHgx9Lc2wVtvIX75SyORccsWQ1xq/nz4+Mfh4ou5zw+7jtzC\nnOd3pm7spjlgSmEMSiDXBjfdBM88c/aOFxbG/n/11YaM944dBg/E6tWwfxP8bJLU9pkT8O274JFX\nweY4e/vTSIlpA+J/AQZHa+kZ2EJEGwEU0l3zyc+6IqmiYxwmJMNY+RR7zvMKgms5yXrqmYvh/tcR\nvJE1lxPOgolJUcCE391s0fF4/KhS56augzybt5Rui5uAYsKqRxK+GSVwyFWMHi0NG1VtvJE9HwCz\nHmHt0Gmqx3qwx9Fmj0NB4tDClPj7cWlB/KqZM9acyeXn6LqRxJmTZoJyBRcR5nT3oAZTVaJAXhxf\nQ/1YJnPsfbx8YA67GkvRdQWzGmFNdROX1NTTomTQjxOEwK6FUIc0dtSV09xvUCyLdsn6OQ04rcnG\nmkBis0TIsAUZCliNMQwI5lX2YYpWumytWsAlpw5hDwcnPBEagvyuPjz1nQyV5SLjJ2ghWHz0JPnD\nw+yrmZ1gPIBRwhqxCDrTPJxqyaV6Vh+fX2hitd/O8Zf9ScbDOLxuQai0nS+rt3OdUsSH2cEMYsqs\niqqzd9NGhCawbk9n4PF63I8VJrUjhEbp7BMJC7uuKZyqXYIuJEGXpL8yjCNHJ9BmQtU1gqoRojIF\noWqvBaGfu4LDZA7jSk8dctM1lcy8LnRT1DYY/9jH+Lt5kY5tlwO3HKUi8wDeQBYOdzenWzegSMHM\ngq1cUvMwuekNaLqJo62XM7P2l3SwggL2sy54Hy1jT/Fsxue4e8u/wJwcyHKAP4LeOMi35r6agmhp\nPG5l/LWoezM31/2Q6sEDE32r5A3quIFxfY90mqlg0znHIh5ZgS6yzpL3EA8lqrCpffd7mM7Uw7/+\na+IBXS04f/djLhWbieS4UXpHjDCkEMaPzpOR2ngYhyqM8MTICFRXG9oV8boWJhOsX2/IacfDYjG2\nj+NPv0xuW9dguB92vAqX3Hxe9zuNREwbEP+PY2i0lo7eP8dt0Rn2HiEY6oVJPAbjS6UfE3dy8D1c\nRTKDgYSwwn73DE44oiGTaDzymt5D7PBUM2A2SK+yw6NcOlBHdsTH7LFuKvx9+BQrQoItLhu7wVHA\njvTKCQ9C/MoSFiqbPbPxKlYuHGlM+j4TQFWgl6qA8bXebkmnKT85qVJRoCLkwVHWRnnjCSx6hIDb\nlNIzoCFoISYYJZD8Yc9CapsLJ9y0Yc3E1rpKWiMZLFzWOdHnMcUC2XDtBccpsI3SM+pi8/Eq9jTM\n4OLZDQkJnMd92eweLmYwYsekaFSlDVKRNsjmnVVYZ8VGe8Tu4MFLb+aO/duY220kxB2nEN0smHmq\ngxYTdM3IQyoKtkCQxUdOMqvBCJl05OekLudTBEtntqFWS+a29bB871U87wox7E4dPOou03jhn7yE\nbW4kCg/Jq3mYK/it+CkbOYquKWx67nYajy5EItE9EfxXDxBYNYJ1j3tiwRciglBgwwdiX5yaphDw\nudj56rX4MuH0So3ZL4b5aNYPuezobkxSY7dnAffPuYeTYhbKeRgPIImEzYwOZeDOGEraq6ga/Z2F\nOIdEynrhYBocvhyEZme4t5D77LfxaOCfGbF3sXS4gQ9e+Hkk4A1ksb/hZtr7F9CUs4xy31Y+OrgB\n0Pnwse/yH8t+Qa6vmev3/QKlKgOyHGiFGcyy1NGAoJdJlRHR9+ji5mf42p6PoiNQiXngLubb1HMV\nEQyyJxfJuTHnhALku8EXhkAYzCrSH2ZE9ZBm8yGqMo08hdEQ1PejDAdRWs5AczOUl8faGeiBb94B\nY14QEtNFxdA2iujwwoIL4Nbb4AMfgC/dAMPdKcZZQE+UG2VwEF5+GS6/3LjOeI7D/Pnw9NNnvx9d\nh65kwT4AVBO01r/3MZoGMG1A/F0gEvEy6j8NUuJyVE1UVYQjXoZGDxAM9WI2Z+BxL06Q6JZS0jOw\nNUWLkkCoE7u1GH/QT0yIyICD5DIoj3s5ugwx7D00RS8Ti/4OuYsT9pqkTnWgj6rOvolQxXi1hYag\nMDhMWaA/YQ7J8Wwg3TWXcsWJv/8ZdqXNwKsmsushBELqBFQLOqAJBbOcOkPCGQ5w5lgGpXOGEpo5\nXZdFVlOE3qF0jjOPO3mbq62HOb20Gl3EougSgwvjueFFDPY4jRqZ/BEONheSPAMKGhuymLWgF5tN\nG+8uSMmIw0aJGCE/fZQPrz7ISwfmUN+Txcz8fjRdcMSXy6bBCsafTURXqR/xYI5ofGblHoZ8Zhrt\nuejRxb8zPZOH1t+I6NXIGvVSVTaMrsDSI3Vs751BvzeNawdqubKjFlNcqMMcjkT1zif1XUryxob4\n7q5tuPUA33Dm4zvl5wsHVDrFmuhn+fiYSN74tI+wVU4YIxJBWKrcFbyHh393hOaDi2IqnQJ8d3WD\nCYZfPc7i789j4AkrkSGN0pz9XFzzc4qVTkbHigkpNt5tX8rLe6+nc0UGgTQNB14ebf80me19E5Ue\nKwaP8eqOe9jZ+gH2WD+HL5iYqDsOWwbMvB6OPQsRP+x89Vo23v50krfD73NydM8qxDmSbfL8jXzq\nyO2kDx7kPm4hIkx4y8qR0sqAt5wnNv+GQMgwqhShUStvZhQ7a3iIy888iZCSzfPvYuPid7HjQxEG\nx9P9fAUpBVvEFTzM/YSxTjwXVQ9zd+1XADmR4Dze/VyO80lWsI1v0chlBHGjo6JwDl31cVhVQ0q7\nMY7tMmic21K1hPkLogaJIiBbQrkHdrVC+wg88QS8+aaxsN94I+QIGBuNE7FSoDQdyjPhinXw0Y8a\n27/wffjepwzPQnxddI8PuqOevlWrjPyG+nrjGk1NMHcurFuXnCQ8GYoC6VmGt2EydA2yk8tXp3F+\nmDYg3ufoH95DV/+bxNeq5WSsw+2opqnzN+gy5vbuG9rJjLxbJ4SyNN1PWJtKMVDBasmlbnCMl7vn\n0RN0U+Hs49q8Y2RZ/BhTkoYiLGSmryTXczERzYd37DSaHjM6psKYYkksPxMKI6oVtxYkXUvMPleR\nVI91x9dlYDVnk5NxIUIIjngPssDbwp60kpSThRQKwyY7CrFNsSAAACAASURBVKBInUZrJuXB5FJP\nHfjj2CIOHi7m+Kk8CopGUYSkq9PNmG88+VNQh85W5nJ3cBPfOvoydfMrsUUXqlFp5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kxBwStLwNo53whQor3T9SsL1mwhyAlvkR3rqxkPXXfYdqTx+oZnAnetEO/Bf01RlcDUJoVBds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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe75c443940>"
+       "<matplotlib.figure.Figure at 0x7fe0fa32efd0>"
       ]
      },
      "metadata": {},
@@ -1056,7 +1085,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": true
    },
@@ -1074,7 +1103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
@@ -1093,7 +1122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": true
    },
@@ -1111,7 +1140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false
    },
@@ -1129,7 +1158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1141,7 +1170,7 @@
        "(3000, 2)"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1161,16 +1190,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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UqxhX6U1w979bCa+G1hQZiqt55P0KhQJQPhBvC+bps5kpp1NlnsONhxJRRIko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Ppo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\niYgcEJHdIvJXERkS4bjDek+0tgbFA7yFnXg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ANVjC4V4p5WCbouLcQEazKZBw8LUTv57dDeHuxPt3/80KCPQ1xZ1MBZAaDvW6NuIhgVqH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AB2ylpqGMNafQO75G6kWXJTWTFPBxx0hK0EYmaimgmBpMAR4vI8FUeG1skRHHiMEIihQgi44Hr4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\nUq5pAqGUUkop1/4fWGfLoxA8oZIAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe75c1036a0>"
+       "<matplotlib.figure.Figure at 0x7fe0fa0b0e80>"
       ]
      },
      "metadata": {},
@@ -1213,7 +1242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
@@ -1231,7 +1260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -1249,7 +1278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -1267,7 +1296,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -1294,7 +1323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
@@ -1306,7 +1335,7 @@
     "with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
     "    y_pred, loss = x_pretty.\\\n",
     "        fully_connected(size=1024, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=num_classes, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -1325,7 +1354,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": true
    },
@@ -1344,7 +1373,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": true
    },
@@ -1369,7 +1398,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": true
    },
@@ -1387,7 +1416,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false
    },
@@ -1405,7 +1434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": true
    },
@@ -1437,7 +1466,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": true
    },
@@ -1462,13 +1491,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -1489,7 +1518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "collapsed": true
    },
@@ -1507,7 +1536,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "collapsed": true
    },
@@ -1546,7 +1575,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "collapsed": true
    },
@@ -1617,7 +1646,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {
     "collapsed": true
    },
@@ -1662,7 +1691,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "collapsed": true
    },
@@ -1705,7 +1734,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
     "collapsed": true
    },
@@ -1760,7 +1789,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "collapsed": true
    },
@@ -1783,7 +1812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "collapsed": true
    },
@@ -1817,7 +1846,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {
     "collapsed": true
    },
@@ -1874,7 +1903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1884,7 +1913,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 6.3% (629 / 10000)\n"
+      "Accuracy on Test-Set: 9.4% (939 / 10000)\n"
      ]
     }
    ],
@@ -1909,7 +1938,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false
    },
@@ -1918,107 +1947,107 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Global Step:    100, Training Batch Accuracy:  90.6%\n",
+      "Global Step:    100, Training Batch Accuracy:  82.8%\n",
       "Global Step:    200, Training Batch Accuracy:  90.6%\n",
-      "Global Step:    300, Training Batch Accuracy:  96.9%\n",
-      "Global Step:    400, Training Batch Accuracy:  90.6%\n",
-      "Global Step:    500, Training Batch Accuracy:  90.6%\n",
+      "Global Step:    300, Training Batch Accuracy:  90.6%\n",
+      "Global Step:    400, Training Batch Accuracy:  95.3%\n",
+      "Global Step:    500, Training Batch Accuracy:  85.9%\n",
       "Global Step:    600, Training Batch Accuracy:  84.4%\n",
-      "Global Step:    700, Training Batch Accuracy:  92.2%\n",
-      "Global Step:    800, Training Batch Accuracy:  87.5%\n",
-      "Global Step:    900, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   1000, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   1100, Training Batch Accuracy:  89.1%\n",
-      "Global Step:   1200, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   1300, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   1400, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   1500, Training Batch Accuracy:  87.5%\n",
-      "Global Step:   1600, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   1700, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   1800, Training Batch Accuracy:  85.9%\n",
-      "Global Step:   1900, Training Batch Accuracy:  89.1%\n",
-      "Global Step:   2000, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   2100, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   2200, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   2300, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   2400, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   2500, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   2600, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   2700, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   2800, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   2900, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   3000, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   3100, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   3200, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   3300, Training Batch Accuracy:  87.5%\n",
-      "Global Step:   3400, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   3500, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   3600, Training Batch Accuracy:  95.3%\n",
+      "Global Step:    700, Training Batch Accuracy:  90.6%\n",
+      "Global Step:    800, Training Batch Accuracy:  93.8%\n",
+      "Global Step:    900, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   1000, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   1100, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   1200, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   1300, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   1400, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   1500, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   1600, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   1700, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   1800, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   1900, Training Batch Accuracy:  84.4%\n",
+      "Global Step:   2000, Training Batch Accuracy:  85.9%\n",
+      "Global Step:   2100, Training Batch Accuracy:  87.5%\n",
+      "Global Step:   2200, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   2300, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   2400, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   2500, Training Batch Accuracy:  89.1%\n",
+      "Global Step:   2600, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   2700, Training Batch Accuracy:  87.5%\n",
+      "Global Step:   2800, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   2900, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   3000, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   3100, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   3200, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   3300, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   3400, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   3500, Training Batch Accuracy:  89.1%\n",
+      "Global Step:   3600, Training Batch Accuracy:  89.1%\n",
       "Global Step:   3700, Training Batch Accuracy:  95.3%\n",
       "Global Step:   3800, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   3900, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   4000, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   4100, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   4200, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   4300, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   4400, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   4500, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   4600, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   4700, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   4800, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   4900, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   5000, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   5100, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   5200, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   5300, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   5400, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   5500, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   5600, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   5700, Training Batch Accuracy:  89.1%\n",
-      "Global Step:   5800, Training Batch Accuracy:  85.9%\n",
-      "Global Step:   5900, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   6000, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   3900, Training Batch Accuracy:  89.1%\n",
+      "Global Step:   4000, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   4100, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   4200, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   4300, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   4400, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   4500, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   4600, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   4700, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   4800, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   4900, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   5000, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   5100, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   5200, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   5300, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   5400, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   5500, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   5600, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   5700, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   5800, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   5900, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   6000, Training Batch Accuracy:  93.8%\n",
       "Global Step:   6100, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   6200, Training Batch Accuracy:  90.6%\n",
-      "Global Step:   6300, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   6200, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   6300, Training Batch Accuracy:  98.4%\n",
       "Global Step:   6400, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   6500, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   6600, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   6700, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   6800, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   6900, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   7000, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   7100, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   7200, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   6500, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   6600, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   6700, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   6800, Training Batch Accuracy:  92.2%\n",
+      "Global Step:   6900, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   7000, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   7100, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   7200, Training Batch Accuracy:  96.9%\n",
       "Global Step:   7300, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   7400, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   7500, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   7600, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   7700, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   7800, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   7900, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   8000, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   8100, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   8200, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   8300, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   7400, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   7500, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   7600, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   7700, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   7800, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   7900, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   8000, Training Batch Accuracy:  93.8%\n",
+      "Global Step:   8100, Training Batch Accuracy:  95.3%\n",
+      "Global Step:   8200, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   8300, Training Batch Accuracy:  93.8%\n",
       "Global Step:   8400, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   8500, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   8500, Training Batch Accuracy:  96.9%\n",
       "Global Step:   8600, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   8700, Training Batch Accuracy:  96.9%\n",
-      "Global Step:   8800, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   8700, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   8800, Training Batch Accuracy:  95.3%\n",
       "Global Step:   8900, Training Batch Accuracy:  98.4%\n",
       "Global Step:   9000, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   9100, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   9200, Training Batch Accuracy:  92.2%\n",
-      "Global Step:   9300, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   9400, Training Batch Accuracy:  93.8%\n",
-      "Global Step:   9500, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   9100, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   9200, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   9300, Training Batch Accuracy: 100.0%\n",
+      "Global Step:   9400, Training Batch Accuracy:  90.6%\n",
+      "Global Step:   9500, Training Batch Accuracy:  92.2%\n",
       "Global Step:   9600, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   9700, Training Batch Accuracy:  98.4%\n",
-      "Global Step:   9800, Training Batch Accuracy:  95.3%\n",
-      "Global Step:   9900, Training Batch Accuracy:  95.3%\n",
-      "Global Step:  10000, Training Batch Accuracy:  95.3%\n",
-      "Time usage: 0:04:14\n"
+      "Global Step:   9700, Training Batch Accuracy:  96.9%\n",
+      "Global Step:   9800, Training Batch Accuracy:  98.4%\n",
+      "Global Step:   9900, Training Batch Accuracy:  98.4%\n",
+      "Global Step:  10000, Training Batch Accuracy: 100.0%\n",
+      "Time usage: 0:00:32\n"
      ]
     }
    ],
@@ -2028,7 +2057,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {
     "collapsed": false
    },
@@ -2037,15 +2066,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 90.5% (9051 / 10000)\n",
+      "Accuracy on Test-Set: 90.7% (9069 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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YERFiiExpYNLgQXjtflO9Yt1Xq1VeBe/F+vYP6ApNXcy8zxl3cM1hmhjSgIgr\nQwnQQRmOlDUHQVqtfT7ZZThFbzPRVvflxe/fcfvmwHiMgeM48HQ+83g+cRwH1vlKiMp8eSZoI6gP\nb+kitBr09sd0oqCX7K2ryDcEghBCIjYlKVSELIrJ6+LOsGtPNnMxW7M3FaLe2qvD4CLgtW7knH+i\nZu/iuLCJk05rX5ipKgRee+e1tb792lu+zSAlvb2PGMMNOGS19gHz739h7vb7Wd0qn3/4wq//9tcs\nv/4d48sLmzZaAYpwXRs5BkYxhprR0qhVmKswtAClMi+FujwzhH/gOCQkb9Tvf8kvn54YpwkTP7fL\ntvB8eWHNKybGOAwcDwfWkrluG0urrLl66wFI6iLlx3EiiEAPjIfos3MXNi8dee0fb7ldTnuqnYP2\nWimadaCGQRMH9/gWd0cI7oH5ZwD6+5M33yyBq3yZzx292veOwdtL9NoudSDjPji8Bc1/FCB5+/19\nfZm/qLft1ZVvouprq3RH8qu/hjM+9qmjdh/nbdF2g1S/tml9iXJw2FetWK091ntXpJbiFWcptFK7\n8Lj/bmLia9pK5/X+DDoa3xwYHw4j53FgTJHDOHI8nxnGkQYM40DNM1Y3WvOZXjNHG2nwCy/0vWIY\nTVy3UoISDwNhOGKWqMUgNyxXcr+4Vn39Ex0IU0olpcQwDKSUbit8vLIcUTVK2Zjnma/1hVr3DNsV\nKGozNIBII9D1LJHuoPaD4eZZeeu9cx8eh+CzIqqjsFr1Xvrd3tfq2ljXmZfPL8zPV/K80mhsGdql\n8IN+5RoD3x8HzkNkEE9oZouMraKl+q7GWvjV735A6ka+PLO9fGX+8z/n+++/J54Ou/AMOW98/fKF\nWitPT4+cHs4cponz+cTSMktPzsSEFJTTNPLhdGKICcEI1og4GM1a7eeoo673CqLfM7sCU2WvCqC1\n3pbr0mHa5/K7pFizrpyjd1Tqe1vt19CBol2Rpu0k/p2/KD1I7t6n/9sv3Vs+6k+J/tY3YXihIM3l\nHWopbAZVIxJSr9YgitMxpCvOqDTKznc1r+q0Q1Zd77dTMXAB8tBbobsofimZmjsyu+NIdPerfRON\n9O0avk2jMwayf+wL6d/bvjkwPp2OHIfUoebe9owycTg/gQhljdTthW1tSHmFGrs2R4couxyCyxWl\nQJwmjk9PpNMHjjIwbEaaN/S6sOaM0dudKXU1d2MYAofDgcfHBw6HQ1ercaWalBK+usUrx20rrEvF\nmi8L3dV3KDssAAAgAElEQVRMnKFaiBKQ2m4Vo/SMy3eRKbUTz/wAts7T6eusYqAFENqtorzbO1qt\nqFW0bohVisDLVrmWlbmu/FgrOQjT45FfPJ0dnFWNtIGshm3QslAbPJcrvyorkle0ZswKlpSP8XsA\nBg1EhLZltm1lHQbGcYRmJA0MIaJ9UhN7G/7heOS7xyeO0+T7M0qhLjMtZ6xWD3q1omaepPUKoDVX\nvmldX9WDnoBprxh36bhXgAVvulMd1vEul+Ruu3X/gXSdXC8YaL1y63zuXUT8dY9nF37rc8k9Nv40\nSHIT/Q7RNxflUryzViorSlHvTFh19ZlXwfoOxukfuouZ8+b1TXBJutarUkei1upBL+fNVcisPy/c\n9qA60NKIQW/gRWvNd/fm4mda5DbbfE/79orxeGBKgVwL27qxLBuaBjQOjMcHYhRKcCRKq9n32Jn5\nXsagxNuyTZdmCzFx/PDEL/7iLzh9+CUlHnhZK59fZj59eWFe19vFCqET7nvL4Hg88vT0xOFwpNXK\nll1EvPRgiinTdODpURjTgVK89156YNy2mbwttJKxUpDaXOi5S2+JeNYV1HfquTxS324tjRSFMSlR\nEjknX/756b566j0tUplG47uzELfIFiKrNOa5clkbn1cXaVgESlDSOGAE6lzI18o2N+rWZbdCoBlc\n143ffvnEYUycTmem6UgaRg4SeRoOrMczzyJYqVy+fGWtheu6+DLsWokoY0qcpomP5wd++fE7Hk9H\nggjbMvP8WbiUrx016ll2lMAYo8++Q+Symm8/b9WXGhtYk45cdRGKvdKQG7jDusP1AGs/B8/zJ2y2\na9026UATl/rT4IGn7WDVjjhW3qje+LTvjYhD/+4+ExQhpchhmtDoCmROzym+gAFhQUhRKWXz7kSv\nUYzwOuPswETp58lbtK8JmGr0giBERJRcXM/XR1s7DalXq9mXMQRR4hCcMqLO4aylsHWOuTWXpNvX\naL2nfXNgPB1HUgpsy8Z1nqmipGEixIgG53eFNiLN+815K7BlX4liTttAAqgRYmA8n3n8/pd8/5f/\nmg/f/ytqmHhZC9OXZ9LhC/O8gBmxB8UYk2v1IRwOBx4eHhjHEWu+F/H5+SvPL1/J2ddCxRgZxwPy\nMRDCgODZdy4b8/zC5fLMMs/Ylmk5U/JGLpllXUE3tHaFetEO13IxXBVvGYxDYhoT2IBjb57/UNfo\nbt9gSQsfTom/+G5i0CNfnhubwlozL1vmpTakNZZlY75c0VLIOrDNjXXObHNFUFIMHJLwcAzEZFyX\nlR8+feL7hye+Oz7wcDozGjykkfLwSIiu+rTNK8u2smwLpWyoCWMaOKSB0zhyng48Ho88nc6koCwh\nkC8XFnH06C70NsYICsMw+PynFcq2odYwdYe0zxpRRwACNxUc3dtr3dneJeF+HrZzFw1uPEL6Zowd\nWGPsgeltRejB8HXZ9M457J8jN3yFhkhthmwbVp1Lnm1jbkZRodCoYq4X3dGudIUawWklIexcbnPl\nMW0uxm+FGH1Vn0FfXNyrPic8Ok6jNmrZHLA4jowpunQnLkyRi1eLtw0z9gZA9I727co3yXmEtmWW\ndeG6ZYZx4jAeOIyJUSPDcCShHghNKU1p2+pt1X2uGAPj8cTh6Tsevv9LHr//Vzz+4s+pmgjzSgsJ\nU2VdFoC+425gGKYu/6beBusbOKwa47B0CaON2JVDhnFgGA9Mw4EUhy4KAKVunfd4ZZmvlHWjbBvr\nsvByeeY6X7leLuS8QWtEcSSttdKVdPoMVLPD7YeBqS/0vNv7mVA4HQa++zBSmdg0cwGEQEOda7Wu\nPG8bX6/etszaWLOyZSMXQIVJE0+HkadTYgyVtrywXS68/PADX9OEPszEYSLGwGkYkRjZpo1lWQjX\nSydrG/swMsXki7VrYVlnhqi0EMjbQi35ttBbxfeEHmxAq7dIa8lE4HGcYDpQMZat8OlyYVsLrfk6\nrH2KuDvV2/ypt8rudI33Nb3pnr5iGN4S63da2E8D5esiYI+CXW1m1xntc+QQ/KyU0og4mMVXP/kY\nqOTCVn0LkCmYCk07H9esV6qBGJz/GkPwGSINbS5IkGJ0VLY4ANG6WD6tup+0Rm2dClKKLyIWpdZA\ns4jazqtkj+uvaKNepb63fbtWKqDDgCwrW5m5XldSiLTTA/F05HAYGNPAMCWCjqAjFg7ofHWUXS0E\nHQhBOD598ID43b/m+PhLhuOTbyxoylQqD7UwjgnFGOLA6XDgMJ3QED2vVnFRcKQPfYW8bpR1YwsR\nicp4mHh8eOR8fiClofMjvc1UaiHnjbxtlK2wrSsvlxeenz/z9etnnr9+Zr1ekLJBcXWfVgrzsvL1\n4rsb5+KIx+M5IvflPu9ujcIwRR4eTyysXKQwqXKIiRQjQqU+N5aS+bqtDiwYAksJ5M6nGtQ3Zjwd\njvzZ45EkK3NeCMtM+fyJFxR9eWE4ngkP/vFwPKHxkVoKX19eGL58Js0j17JRrAMSBJZl5sfPn9iW\nmSklKJltXaDLwAUVDjGhSZAVXl4ubOvKpANPxzNpHLGgfL5euebMy7Jhsu/e0y4ptVcWfatB124s\nd4L/u5or0PhuV0xuU1+5IY87GbojVIF/FBShw0hvwCp/DNRqbJuvzIux87f3lXwSwIqr1zQXwdi3\nd7jqzFuif/QuW/IVbLVCVXXaXAdMukiFYbV01L8ndvW2Y7Rv0ugz7q1UWDeG6Au+6S3/oE4TUeqN\nevTe9s2B0cR3dKUhOZKuZm8B5QHqADUhUVENpClxCCM2nIjHhW1bvbymkmLg/OE7nr7/Sx4/fs9w\neETC6INh3EGkFFCJBHmd0RymCQ2xi8/Kjc+FBcTgeDjQSiGXEYmB6TDx+PjI6XTu66H4J3QZa42S\nK+uycpovnM5njqcj59OBy9dP1PlCna+UFcpqtKKMMVGK+YHMDV0L2z0wvrttGBYG4uGBo1UegSXO\nXIeNY1BS28hkyqWwVWGlgxrUN7JMBikGhqCMIXBKidEqU3Dx/Hi9UEW4LFeuxxdi+cgQhcNh4nQ4\nOh3jcGQcJh7nK9e8sdVMrq96ky8vL7Sc4Xhw1ZsYmEaXUNQgEJWkAaOyvLyQS2EaJz6OB6bTkZoC\nTeDwZSCIUamIRBq1Vx4NldipAV1Jxe48xvc2B8g43tMvhdxaob5jEV9J1UE6Qt+52VeU7cAqb0SE\n1+DogAq2XJnnlRhrn/X5WigJAbltaPEzoDiS2XV0/fGIECUSQ/BNMcHlBZv28q6BKa4s1mVAebP6\nb696WxNMAoTgSjoIW+erV+tShepz8Z1mV1sj/wza/d8cGMGIUZnGxHEaadtGMGGKwZ/UfDOFmVJD\nIEwjj+cnTsC2zbRaCFIZx8Tx4QOnj7/k+PBEiMkruG0jbytl2/ruLkOjEQQH9JTs10C7SvwuIt58\nl9506JvTW0VCII0D03TwVpNZl4vrFBLVLjE3oGJAQGNkGBLT5LPDKSnzF+FaC1oL1MqQEtMITQO5\nuJj6shXmfGf4v7ctRViYqAnGY+BJE3l4Zh6eeZbMuSaaJZJWwmpgEYmRJAMnwAZvSUU1pBWkbIzS\nOHQqz9kqab2w5pnr8gxl4RDgwzByOp85HY6cDifOhzPLtrHmjSWvXJeZ63Ll6/NXluVKEUXOJ6bD\nhAyJtvq91EoGUcaoSKqsMRFC4hwjT8PINE6UFFi2lWNUBoFNGkZ2OTABE6W14iICXdGkM3Tf+/L8\niZvcEJvSNaO9O2q4zlrnAGG3SaTVfU2Z/7yJECR0Jo/0qnGnsDVm2xhTI4WACo6PUEGiIq0SxPpQ\nwc95Yhcrb2iAQCKpEYXOPDAiu5xgI7eCbQtl27CaX5cP999PNBBSwvZ9vMbN55ZayKW46k0ENLgU\noqoHxvD+hcW3V4w0gsCYAg/TSGyuc3ocD76poBaWWimSaSExnRMPpwfSOHqWYYUUlXFMTMcTw/EB\nTSOtVtZlY56vzNcL67qQ8+IbUtQh8GVbsVw92wgBHRI6DGiInhWHwDiOpBC9MAzigJ2UulyWr/DJ\nJdNaI3ZklWro2n8B1ZGYlJSUGISkDW0VW1eWWqilMozC43hkbLBsmWXLzOvGvM1/uCt0t2+yucDc\nBlQCIQVOKuQIFy1c2spcBqINnAIcLo1YlCqBKMJjjMQqbLlCLeRtZrkYB62cS+EAnABthUspfJ0L\nW80cYsLGAw+PD3x8fOA4nTiMU0dAV9Z1ZVlmnl+eCdn4cckuxGxKDIlxGNE0Uq4zeZ5xmaZISEo7\nFladeDqe+PjwxDiNZGmsIfIg6sHcjEx73fNoSsDJ3L7yTTu8/h4Y39O0zwRD2IFSnYDfAVK7Hure\nYr3xGm2nvfmDm3V1HOiwUg+OjkL1roEkF6cXvHhQ+hIHjGDV9yH22XNtXgE2LU667yo4JorV0j82\navFFw3XbKNsKrXhbdVcU0whxgDBgEqhdiKUZ7vurKzm5/F3oAVIJ0tf8/Qy0pr99xmiNII0BQ8bE\npErSyBhHSjM+Xy58vi5cc4U08GTC+PiRw3QkhoAqjENgGCJpGNGYyLWyLjMvL89cXp6Zry/kvGFi\nDF3jUszI68qSZ0wUTYnhOHGIgTCk3nYAk4CFLkkUfAYZukDzrmijtfYFsM0VQvqB065Kj0UH+Tz4\n70qusG2e1BGYRNFxwmJizYXLsvIPv/uR33y5B8b3tpwLpfhCYZXka6KGiQ82kdsBqwvntjFY4yiN\nujSWmkmqPMSRoSrPl8p13ZhfVj6XGVUj5I1JGpJi3w1aWGrmslyYP/8Aw8TpdOTcOxaH6cA0RCBy\nGgbkcGYZH0hZkaUx1411LlxDJp2OHNJIjB2c0YRQBqb4wPkXT0iC0/nA8TCSMLbrhfb8wg+mfGpC\nwXz3Ka56g+y6mn0FkFpHQb7zxfkTtx0U5W1Sue1+3ZVsGjgIRd5Me2QPkn42ZN+l+EY8HFw8wIOl\nB55cC0Z88zqdeiHOJ0x9V2fOG23L1GUmN8PCiswrIQ6kmICG1UxrlS0XSm1Ohyu9/apOuRvGkTiM\nSJqwMJCr+dL66kChV26IJ2vaqStDGl2pR/IrQfMd7ZsDo1JRaySBNA7ooAwhETTyvCy8bAu//vKJ\nL9cFCSOrJh6+/zMeNBAPR4YhcpgGUuzq/7WR55nL81e+fvqRl5cvLNeLI+1SJGLIOGFSWOeZ5brQ\nMMIwcZRHxuPB+TES+v4xn18jvTPRJekQiOzi4+2238wBYQ2xLjfXnySERDw6pN5yxXJ2hxUGJCiH\nx0fS4UAT4fkys5nwN//w4x/k4tzt2y3nTMmFYLELLyijRp6GCTmujOXIpdaO2tu4iitvSDDSMWGM\n1Lzxkhde1oXtSyErSAykMTEMiTQEaohkVea8YZcX2o+/ZTqOTKND2j88PnE8HBliYkoDp+mADWdY\nGuWa+d3LZ+Y1s2rGRhzhOgR0iFCEIAPDODE9HZgeB4ZjQKWil2fWlyvrUvm4GR+qcDW46iu8z8S3\nK9RmtC4e3qTeZ4zvbD8NZq8IYjrPVHZ0qMhrAAza0aXqFAzdFXL6RgzpjczaF7XvguMYuS85CBpu\nNAoNzseOvkjX+wxlY70+M2+FLCOWFsJw7GBFUBrWKrm6hjTNF2G7rnUkDgPDdGSYJsIw0TTCWrzz\n0sUACI3WFOnCKW9zNOkbR94/LP4+FaMIUcQzZ9POeYk0E7aaeV6u/O75M58vCyFNjNcnlpwpDdCI\nppEwjGjsfMJtZl6uPH/9zNfPP3B9+UrNqyOkbMKGgZZXajO2eWa5XqjWCGUjjolWff9XCA5fFn3V\nVt2XgUropGe1m6qDc8Osr/vpGzzMFeUNX1gcI9SUemCsPTAmNCjnD08cHx8Jw8B1WZlz5T/+/W+A\n3/5BLtDdvs1KLmzLisSCJCNF1yg9aiIOE6dzZTbjsmUuy8bWhPGQSMcHnj78ErORed741d/8PV8+\nfca2hUUMUkJOB0zgoMKs0GKC5nOXeb3y46cfGFOg1o1tnfnw+MjD6Uw8nrHxQAgDx6czH+ePVDHS\nckFVGUOfgx/OyAPQFLVIGkcOHw6Mh0DMC3z5RPu7T9hf/4rx73/N4cevTEshJSN0hZ0bBWBfQYTv\nchTsddP63d7F9sW/t2XFordOFr1tir62UkX7MuBOzTCag3NUepD7R3QO4QaAqbskm0NW/fpb852I\nCFWMlhfW+UJZLrS8YLlgQWg6QNvFwoXQAT43/TLxvaEShKZKJTjatUHNFdMujyn8JAi66k28IXG9\nlVux8vNApMLvUzGKA1YEdRgwQkNYt42XdeHz9YXP8wtf5oVUG5dtYV5X1lJ6u0doEqgi1FZYtpXL\n9eJt1OfP5PmCtEKMEW0RSqaumSaFbbmyLVequNZf7QoO0t8XQRECt3VkHZ8jPRiCb+EI0Yn/rTV+\nIpjbD6qooFGIfecktUHfGSZdseJ4OHM+nTicH3g042XN/PL/+XvgP/whrs/dvtFaa2zbCsUFJZK6\n8sZIYgwHng7KhvLb68L6ciVI4jidOX/8nj//s7+EOvC7334FGtfrheXlmaVWdBhgXckCDxj2MME0\nOpjBINeN55cvBDXytrBeX9jmj9TvvkOoSIzEdECOgfPHM0jl+Ow9s1MamYaR4+nkuyQl0qqPAeIU\niHVDf3fB/uo3lH//1+T/+6/IP/4ONBPHRoyhz5D0RgQX6fPF0EXExZcf3+3nYTdptz6js53HCF0c\nvCsZdbyEq+Io1epeYLpvk3arGl9nyP7ErRlhFwJo5hzv1tiqI5nbemGbn8nzC5YXgigSlTZEGBJN\nk79mzf5+uka08yj7mixVimnXtV5BMtIFBvbASleR8tDqPEj/Wnz1VSk/i2oRfp+1UxqImm6QWzMh\n18y1Fi555Vo3lraxWqaWhWWbmZeZZVnIfRBr4n/UYo0tZ9Z1ZZ1fyMsVykpUSKJEq0irlHXxvvmy\n0vLmSNQhoR0ItK8Cch5heNOOsJ8Exj04hk5ercXnjDQPjEEDEgIaBI3qVWiI2KHRzoVlXpivc4cr\nG1aMqK428eHDAx+/e/oDXZ67fav5HjvrGo4RLKJEAgNRhSENVE1sj4Xr5kLGeTwyPD0wPD6gdeD8\n4ZHHD098+vET88szc878mAvajBqUqwpJDYsHbEzsmVhphet8Qa1B3aBllIrg879xOhNMmQYjngfO\ncoJd+B44mDFhiPUZeDHkatjlSv27f2D9q7/j5a/+nh//46/5YX3h5RzI0+gzd5+y3xxs7Ulo7UID\n7TY+uNt72l4Z7XPF8GaxsO1tVVwYYt+e4WvHHLmqnYfh3MdXIQD5idxf5yWKr/qz6kGx1oLS2Kyi\nliEv3p1r2ZGoqtiUqONAiYks7t+xBtWfbx9ReUQXWl9iW6ujuP1XKE4n6eFu3/ahIfQ5q9MxG676\nY63dhAje236PfYyRKBE0ICFSzP5f9t5sOY4sSdP89Cxm5gvAJTKytm7pGZn3f6aepaqyKoIkCLi7\nLWfTudBjDmbPXUTJIFMCGgISQYALYOamR3/9F3LJ3ErhWjObVBgcuilFC1tauc1XlvlGTg/9JuB+\nOqqtmfNHKTitBA+H4IjBzGZdrdQt2Qs8d4MAHxmHwDREhugJvYmhPfWui/hF9A6nWiPvVGmRHp7Z\nNUDORLAGk3pccIbt91NRiCNhOOD9iBJI20bN5m4SYmR6OBGD43g8/JdcnPf67RXHkThGpNa7Q5Lr\np9TgIjFA8Ec+fI7keEa2je+qlDhyq0pUOH38wH/73/+7ee/WjduXSt4Kl5ThOrM4GHxjiBAcuCEy\n9ERy5x2lZpZ55sVBdIrUSls3zsczh2FicJEpCuFhNDc3dbhlI942QmugFVEzQdemlMvM+n/+wvP/\n/W/8+uUL/5FnfvWV74eB2xSpgwMsWV1lh+xMsdacp7b62jTf6+1Kuryiw6l3n9PeHHe7uJ2E8upI\no3eGqh1u7DCvtjrsj1NrlK7Dr8a0MrkHtVFThpopWlFpeC34Vvr966EqEgfqGClDZPWB2jy5/vDv\natrD2vdQZfsZemSV9oZ9Nyi3OED0dVXlu82cdqlJux8K4Ecy0VvVb2+M4nEuGhbuPLXB2pRbztxK\npgWHGwMhG4mgtMS63liWKyltRtvldclMXyIPQ0CngUmF4xBMZ4OxrWozNlTLCYeaj+UwcJgmxmEg\nhNB3i3aRRG1q2GVBbodH3e432FH8fh32naN33sxxfXcQcaDqLa4lRPCRpsKWCq075jgPp1bIacW7\n9xP5W1cYI+PxgKuV2E/RpvUKtlvB4YJwOB/4NH6gbAvburKqYy6N0DLhdOAf/uUfWbaFNc+m+7pu\nuKpkEbxCy4WyJcYpMkZ7PThvXr4eKDWzLgvPopAzLAv+9EA8nhinA0MYGcXjCtQ5U+dEuq3kdQXd\nUEmoVlpqbJeNl/985suXb/wlL/z7OfJtiKwfDyzngc0Vg9tao9ARmWbxVKUoLXhe6fzv9Vb1v+54\n73FRfVq6O5/2SLwf8cX9c3/4rDtxkP4s2+UgZiRvLjpaC3Uz566aE0atb4hrOApelOhNqibBU4dA\nHgJZ7R7ad4TuPrX+QBbq+9B6Z/WbWYr0r9V5G1Ts93qc0p/qXamp2BRpZNkforbern77jtEHnLMk\niYZQqGwoSyusWmHwjKeJ1ApqmmNKSazrYs431dKc6RNhDIHpcKCdHzhQGMiMNFpVcu7WQs10h9oK\nIo0heg7TxDSN93Biw99f+y3dl/DH9+3+2U9jrWdF7lY4ct8x3llh3TVEepaZDwM+joAjbRt5m8E3\n1ryxtP7/7/W25eBwPjI5h24bdV3YUjWaegg0iQwugIfRTTyEI2ncuORKTo01Z6pUwiny+KdH/rz+\nA2P0lG83/FoYvBBGD6eBGoLZyG0myo8hIoOhFxHzYb1eLrCtDKlwKtWQkTWh6khrpVw3tpeF7TKT\nl4WWE94VQmy4ZnKS5ZZ5eln4ddn4Njnmh0+UUySPQg6NWpUtbRTBjOy1s63pYeCVv3rIvtcble77\nPgsR3if4Vuv9GaXdxWZ3uxGn98nxx0TN/SAkYmkVrh/unQiuNjQlSAXdMrputD4xKg0NIF7xrhmq\nJhDc6/qoSXfGwe4f7xzO/sJ7Uovz/k7EAQyq7abovk/Dfn+GamejYtDxPim6biru6I3R/R0L/EWi\n7RalURS2Vlhy4laSOXAEx3AcOWqlrJUQfTfstsZYcqKWQojB0immCX14YKDQpoDLK65s5HWjaka2\nag4ktSGt4IIQvTBNI+M0EuKAiL+7LHSx4T3bS3szVEB0D3ht3VTZTi9iX9gd55dXdyPusIE4JAR8\nHBAn5Jwoaaa2jS3NJDLr9fr7rsp7/e7KrRLGyGk6ULxwSxs527TkmlJEKOIZgsP7yGmcaNMRlxIv\neuO2JgoZDY3DhwOf2584TCP6YUXmzOgdPjqSr8yusWghl4quiSEMlKiMwRG8R8tGXhNLLiQ/UIcB\ndYG2VrZbZv36wvz1wu35yrKspJyoWoiDYxyMDVjnyrJWnqryFD23jx+o//AROQ1IS9T1SqoLay1s\nNLPhUu7NseorPPcu8H/bUqwpSodUdycui3d6db4R5K+eTSqvSNd+Ddsdju1eqH3qFAXt3qR1niEV\na5DdqUZdMxF/fyY2p1h2bcMZNRLBhhA03BE31wOVXW+KRt7w9uc0S3zR2l4n3z4JO+/Rql2f2dut\n6P3zrJk7pOnfxNnttzdG71Bn4/NaE7dt4ZZX1pbJ0iB0Z/byaqqdNbOVjZQ3aim02pCmeB+Mpi5K\nHTz1MKLrjTrfaNxwbUHKZo2RilAs+NUZycL5CBKwPLFOUe+Ambkr0PeOe3PsIv896gS5w6h3+FR2\n3Jx+quuMLxHUOwgC3kybS0m4reK9Uii07d0S7q3rti7MaeU4Rnw0dyVcYNkyqUFJBjFG55mGSIyg\nUlARnIJHeWkb25ohKtPjgTFEwlmZsnAeBuIQmNvKU5r5vty4LRs1V5Yl4eoFzSP+OBGdEEIkBkcY\nAi6YP2Qpje068/T1G0+/PHG73lhLJaMweFxx+GZQVl4zW1UW79nGiDycGD480kbHbc5mMpA31lbY\neh4eKogNJRay3YkS9Z1887bVoUN6vNRrc2tGKKSz3vu+0KQc9hv7T/Y8Ent29ZAN0213JqtqQ3Om\n3G7o7YbLlSCOoK2zkhWTdTeD1ltDqCANdR58QiUjeERMBmQER4f8sM8U541nAjQRDCH1iFpm7e6G\n40SwlNFefVBpajtwpwqO133jG9dvt4RzniqQamNOKy/LlZf1wlo3KhU80IQQzR6ulspSVm5pZkur\nubHnCrVHWE0BHQfa4UA9HMnXFzYXcepxVfAVvCqNYotm6XlfgKrQ1FHVGfHAvIcMIhX7t6IOxSNq\nlGjt06J2LN45j3fmZkKPZOmOy0ZeaJVaK1XNzAgHeMUF8AG8KNIqQRvh7a/rH76eri/8+v0bHuXT\n4cTp4YE4HmjXhbxsbLnSWuYcIoMEEDvUaAiMj4FpcNR85XqtVFdwo2eME6fzwEd/4KfzA8fDwDWv\n/OflicPzM99fblwvV+bLhZf5gqbEKEI8ThwORx4PE6fHR+LhBH5gWyvPrfGXbeXXNDNLJY+CTAfc\nMKA4SlFSLazHSBVwIRAPB47HA+Mw2sEsJW7LjTmt3EqiOUFqt/9qFnTLft/bC+atL88funbCjXQn\nLvqerWkXzHdt405E2XkQe1Nsqv3j2mFX7ciW8SvEOWhKzZk8z+j1yoDgQjR40zocKmYm3mqlNns9\nqAOvgnMrzR/ADQzeoeLxXRO5M1/F38kbBoU6qKVDv6q4TrrZiabSP3dvj607kCk2xjgRWrU4v7eu\n324i7kxmsebEZVt4Wa5ct5mlbhSpNOnNo5t7Fyq3deZyu3CZryzLQto29HA0V4boETegg+1sBKE2\niE0Ycf0U42CD1jYUM9VtCqW7talF2aGlIa1Cpw2rVwjBhP87jHqfFnfBqTnjyE62Qe8NVFuj9miV\nvPHYKtQAACAASURBVK6UvNFqRmh4DxIcg3MMQBPH8DcBBvyx68vtwr99/4oKxDBwfjxzGo40iTS9\n8ZyvrGljWR1pDHgRvIPRO4J36DBwPhyYT0dUYCsNVx1SA24YOf30yOfHR855w02RGCemcOW7m/je\nYL2+ICpGFlPBx4HxcOJwemA6nHESyCSu08DTGPl2GFinAHFgPB4ZDyfA4NZSC0kqxSljCEiI6DSR\na2POC9f5xnVbmXNi00pT8GqJCl5B93SG3ZNT3+/PNy2hO3FZCDB38kz/sLzKyiyyaec9OErfJ7Y+\nSYrIPZrKHrhig0PPelJV8z9t+ronDHfBo/mXqu03c62oVnwD7xP4DTcMBD8YK98Zy1WlPxu1IS6Y\n/nInb6h9XPbFlUCt9dXRRmwf2dS0lHUfUDwmKSmlZ5K+bf0OE3EhlcJ1W3i5Xfg+X7jmheyqpULv\nC+S+LE4pUdeG18DT9298//gnHh8eeSgPBjfj8c7UqqJQp0osrfuhDvhhxA8D3By5ZWtO6igVSlFy\n1o6bKy03pBbQYo1ObOm7M2/26e/VMNwcHO4QKh0jb/00VTI5bWzrxjrfyNcLdV2QVhmcif/H4Bld\noGojuN8RWvJe/yX163zl/3r6SlU4jSc+nz7y4TAR3YBTC75+Xq5cboUghcNpwh8GcI66FVquPIwn\n/J/+keNy5fv1xvU6c0kLLSkf9ZHPo2cKBz6mB1z1HN2Bh+HIh+nAfHum5g3vlNagNqOtD/HIdPxA\nEM8mK/nDRv7zTBnNgSmGgcN04uFwJhBoRdlaY3aN5LpbCmbK/HS78mV+5uv1ymXbWNVee7UprdU+\nEVjD9xIMGXk/tL19dVW+7AJ+LP9wZ6aaz+2+Z+S+xwMzAG87VO52yZlFONGNxxX7M8SZTVsdInVd\nWLdE9Y7YbBDxLtgOEMG7QO2Bw04LwSd8SLhQiL68Skdo5lKD6Rq92HppN5Tw3tlaSyvaam/MtcPG\n9vW0TtYxv5RGrXtMmqClUOrbr6J+8xO8tcaSNi7zhZflymWdWTSRg9A8d7/S+8mnNZZ1Rarj69M3\nPj78yuPpgYfzI9PxgG8R1PcbI+LDSBgr9MbohgFioHlnxrhbgDBR1ZMLuFxRsXgqrcXYT6q4IIZf\n71MidoJprXUR+P537kxUvS+NWy2UlEjrwrbMbPPCeruRb1dIK7FVXAiImxicI/pAqZXhbyA25Y9e\n37aZ6eUZVPh4/MCfH37iPJw4jiN6qlwvA7cbLGlFL5mTVs7dMSmnQquV4zBxGkfiMFAbzMvKtczM\naeVxPfMxP3DAGs5pGIkSOQwTH85HlvWRl8sz8+1ip+PaqA3EDYzjCRcH80UVsTirxyNDqQwu8BgP\nfByOHNyAF0cWmKUxa6E2S+n49vydy8vK8+3GbdvYWqNoM30aXfvWI9mMOahmgLHr297rzUr2iDzv\nbA+snZHp7Dn0SrdxfS1sjVLF2bMMsf2i9N/TZRIiu1NOf4uRcDgieaW0TJo3SirU5okaiSgu+A51\nmh4xF1sgaij4WnA1E2Kxe8Y5ijaqtL7OCkZq3CdaBPHcTdAbFgJf6+7K4+5SDFX6isoQvFqrfck1\n0fTveGLcUuKyVL7frClurZCoNPFd9GlsFec8IRhF3jlh3Ta+fPvKONje5XQ+MxwmQhwIPthJCg8u\nImGwVV4PzGzeo51tF+YrYTji4qHvYhpVc98vFjxK7Cct6aetnYF61xF1zYz7QcahYhTp1iq1JLb1\nxvzywnq5sN1m8jpTcyKUjHcGuUnzhE5lFqWnc7/XW9YtJ77NV7wKfzl85efDIwcX8Q8fiN7zeD6x\n5Qdenp+Zl9Uo5sEztgOiQsQTmkOlEQmMw0gYB1oQ1rTxZX3i+DJwlgGfwKuDEBjjyPgwcqpHwmjE\nhbQstAolN1oTXJg4nB7wDsp0ZIuReH0h50JQ4eACpzByiiPjMIAT5la45o3rulqCQqfAK0LwkdgC\nS9rIKd0nCPUeYsT5hg87XLeLs9/rrcp1Us0+rQH3yLt7c7wzT3cI3KZFQ1aNeNhovTH2h9fOMG3W\nrFwYGI4nmha0ZkpeyVtCizkqKUpUC0NoWI5jLs34O2rrqEAlSr9/BErfGeYmECI+DhYzhSF9+7/E\nJqOGU3d/5qqaC5OtrjqS5xy00p/NFddyZxG9bf3mxrjkjbIoL8uVuSSSVqqzU4LqK3gtWKOwNIJI\nroXny3ecOE7HEw+PNjGO40QMpkU0/bGzb7jXjrELQRyDOFqDEEebLONIw5FzQSudEtwYvHm4+h6U\nqdoo5XWx64zS+nq6squJ/dhorZDLxrrcuD1/5/b9iTLPaE4EbBflvAM/gTYL8+w05dANBN7r7aq0\nypw2npvw69M3/jUeObrIKJ7H44GH84lGpWYT4K/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+mWzDNImvhgaiCtLu/tPGmmwdGeT1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\n1thljTGTusbhMSoCQMM9+uMTUkaFq6Py9zpXhHyrGU2zYD5fslw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hxNCKgRiZ+hGDMK3WuLbJWaZzuLIIGrJ70brruNltub26prUWNJGmiTgMBTyz\nSCiliFBNFPKYNK8Brb6SaAFNKdlABk5TVq7aNF9Vl8+8bi/xipF7LmMsxuhFmYoxTyKdmjbKoq9N\nl6D59OFf1j6ryrHtOlQgxIgPgeADY1S8bYhiSCFgSJiq4DYlQ0yaaeTyfAJZLatFOKQgWIw1WMlC\npBjruL6JFAOa4lPnTRWnpZQdda1gxWCNlEHy2akrgycXwdCPLJb0Z61PVvCsmdr5fKbve6Zpmns4\nK7273W75i7/4C/7mb/6Gv/qrv+Iv//IveffuHVdXVzNAHg4Huq4DmMGzbVuur6/n+Zp937Pf7xmG\nYRbGLTPOl45I9ZxfWvkt66L1syKSZ432fT/Xa+uGdL1e8+233xJCYL1e8/nz51d4F57HVwXPRgKb\nFt7sBDs5RtswnpVxSByHyP044VW5Bbwh00lY4pQI58B4jgSvGLIiUoExBO4OB9ZNw3q9YbPdcYWh\nU8NV09Gvt0TvSaqMpzP9OQPvOAzEyWMUrG3YtCuu11u+ub7h3Zu3rNsWUqQ/HtinxDT2pBiIpV7U\nGINtO1zbkFQ5aY/3E6KpLFJS1iebqbSijhSy0baautiWRViy/dslXi+0ZljFRD1QsseUskFBpW6p\nYqFMp1Yl7VOdW2cQrfSuMULXtmzWaxLKMI3EmAhxwofAIIYmJqJGQhgzw2EMWkRJKcqzxUXVFBN6\nperEKRNUXOOggGcWWdRB8BmUSVn4hiqNddjW4oydbf9SDPiU8JN/Mki4tFG9eixpzWUJ4aWpuogw\nTROHw4HPnz/TdR19388ZXIxxVtf+9Kc/5bvvvuP29hZrLcMwPDOLr962tc5YzRS6rpst/14a0i8z\nyZd2fi8ZmZcU9LKOW6OaNhwOB1JKHA6HeYB7bbVZrVY/zJvwe+Krg+fttuW7tx2tbHjsIt4Ko3pO\nU+KUst1YP0z0J8n2fVi8F6YhMo25htg4R+catith1RmmEPj8cM/tZsO7q2s6NVjr2OJ4s9mhQD8O\nTOPIMI0MfmTyE0SlKUO2N23HrluxW2+42WzYrFeQEjZGhuMBPzBnlZnibRExNF1D0JizUj9lez+x\n+JgHfUeNqGQPUhYXfpVwi5BFKZek80cQT/2MmqrrUzbAMFrN3U1xCaoLgqFOK6lpXV4EZpsDKPd1\nLptvx5SYfCj1ykxjjdrjQkRMbluKkh1+svDXAhZKTdIUwVC23atG8S772hqydaUYfAh5tFoM5J7R\n3MeZUiA7MeEVAAAgAElEQVQVNaM4Q9s0ZZRfbq/yMRbALVkDTwv1JV4v6nSUpZK1xrJ3EpiVqR8+\nfCCEwG63mynOWu+shge3t7es1+tZkRtCeKZgXdrw1ecax5G+7zmfzwzD8MyMftma8qXyxTJe0tDL\nmig8H6k2jiMxRj59+jQb3vd9v3D9et34ygarge16xdubjsSKyXpOgKghquRRY4Ny9J59r5iUULdi\nCIZxSnifF6WmcezalrdXHetW0fFEHAdO9/ccVlvWU2S12oBzrKzlZrtj3a0Yp5Fzf0bOhlTUjI4G\nY/IcUFC8n+iHHlMEQ8GPxTC7DEi2QtdZttLhYyQlD1HpjODW22waDhyHEZ964hTASLUJLbxe/lGL\nuKhmO5d5nq8bhmqWbgpLwGxSAM+pJ6kmCgtwnLNOkx8ZUyq17nyvEBMxVgqWuX6Za5+BqczhxMoM\nwpR+4dxGlSectM7lge5FAZ7U5kzSOYxQ6vW5lhlTxI8DKQZIqYzai4QYMIUWS64hSVaUQ634ltet\nT2K3S7xuLHsuK1DVvspqIFDdd06n0+wyNAzDXP+8v78nxvjMKKE6BNW6YhXgPDw8MAzDTNnGGDmd\nTqjq3P5SXX+qDWAFtfqYpSUg8HxW8uJrCZzLTHTpgNR1HeM48uHDB+7u7mZ6uD7na8dXBc8kgaaz\n7G42jAycJHAywsZ1dM2AESXsE72fOHiPSQqtYdAGXzb31lhWruGqW/HNbsduBdM+EA4jut9zth/Y\nDyPTZofbbpHrKzbbNbvdDoB+6Fk9PtIcDqz8wJCyIMJZQ4iR/fGARk+/WtEaYeoLHUvCGovYfL6m\nNZz6nsOxJ4XI2nWsVxts1xKN8Plw5DR6+smjmnvpqBlmyRpy/Upn28BwMUl41RAEZ12m2VVK12Zu\nFymFzZyFIsUMvrIIC7rWmHpXoFDBCYJPTFPgfB4zg1/EO1Iy1JRyD6a1BbpMzio1BUSygbsTh7GO\nxjoalwVDKRmcEbRxebyY5pYrjYEwBVLM04NSAc3sQhSJKRuBGJPox5G2cbQuZ6yqWoRHTz7Ml8Tz\n9ePu7o7vv/9+VruGEGbwG4ZhnqZSM7K+7xERxnF8RufWTPBlG0mtL1aB0N3d3WzPVw3j7+7u+Pz5\n80zrVtCsI8TGcZytIpf12JdmDUsQhedmDi8HfqeU6Lpu9rD98OHDnO3W8zifz6/2vtT4quA5qaKu\npVlfsU6JKxEG19K3ExtnaNUz6EQ653mdY+nBjJIH9nYNgKExwrpxbJuGK6cE65hSYjUNsH9g8BPT\n+YgZrmkk0XUNu+2WzXrN1XZH167ZrLecx5EhTkxlh64amcaBffBoDOxWKxDo2gYnWfAjVmid0GCJ\nYeKcEhIj29Zxu97QbNZMVphipHMWoYCmSSiSRzuploVPUZOQZHOj+0XR+KpR65RGnkQ4+ZfVXJ3c\nEwIY457tlCtVKyrFCq9kqUW9G6IyTgFhLMfPbj/OuDymrqZ2mm0ezWyAkMljkbzbd9bQOkvrcpen\nxjzmTskzOFOIWRwUAhrzdZxbp8qoPYQkFiktDQHJPZ+TL/2tFjFZDW6tpW0gpIT/Ha03l/jh4vvv\nv+fq6uoZeNYapPeeT58+zX6vwLOWkmouALlPMoTA8Xjk06dPbDabGXxr3+TxeOTh4YHHx0eAmaI9\nHo+zcKdmrLUeWl2Jlu0qX6pfLgH7pcPQ0nu3CpTqsett5/N59u+tY9T6vv8B34kvx1cFzyEIg65I\nDtqN5cY2hPZA3x44mMAuNQRaWhuxvYHkwDmscawx3FghJKV1QAp5SHYQVoAYwwZlFQZiHziMR8J0\npJXAVeNo12tur6/pdlds11tur2+YfJ7lmU3izxxPRw7HA95PxLbDNVkdSdOQponkJ2KKiLF0FkLT\nMjpHSnDVNNy0K5puxWjh2DSsraEzwqgRJKsWVbOwI+/8haQGbC6YXYzhXzukZGOmZJ861zEhG1vM\neFqtMLI33wy0+Z+5bURTtmcEQGGaAikqXVF6W0yuh7vMqBhNGE1YiihtzmojxmSv2kaUxlBmbipO\nEpG88csK2YkwDWgMECNSrAKltLFgXX6VYtCYGZEpBSK5Rm9TwloQk/1tMQabEv5HUFP6c4/f/OY3\nNE0z07YhhDnzCiFwOBzmmuZms5nbV7qumwVF8ASeHz9+xDnHOI5cX1/PtOz9/T339/ezirb2g1Z7\nvMfHx7ltZb1ez0KlOrIMeKa0rVHPe2lIv7ytftV6qqrOE1xijHN9dZnRVsvBP/mpKn2APja5D60x\nbK0hOOFsIicdOccGk1o6EmsbaYNBjaURy1XjkCgMUx7aG/1Af4KtF9pxYqOwFWhRet9zioGT77Ei\njG1Ht9lye33NbrNhtdux22yzU3/ZmZ3OJ+5NC2Pk1J+QJAiWtu1o2g6aCX86E6Yp02jGom1Cdgli\n4s32ipvdFa5rGDRwMpZrsRxUSVKFQ/nvUBddNYaouVHeVLPxS7xa1BqnkQyNUucUFg/i2YCvgOfs\nKFVKCiiIzcCUD/gkGFJVQql3mpzWYY3BGldo/Agp5kEE5fhxFkt4YMoiJmMJgDiHkHI9PniI+ec4\njfhxRKPHSjact9Yi1qGmAdeSxJJUCD7Tuvl5AiFFbEy0XVbfGmNobVbtugt4vno8Pj6yXq+BJ4HQ\nPJcVZgDZ7Xa8e/eO8/k8Z3ZVQVu/pmni06dPsyq3OgTFGNnv93z69Inz+Tw/ts72rH63leLtum42\naKiTVYCZmn2ppK11yqX5+0ux0BI8a4YNzPXYahcoInNd98cgaPuq4Ol9IMQsjxdpcaZj3XTcblZM\nukHjyDZ6rEY2IjAoUwwYYN06Gmk4npXDwTOcex5jj3WCSYE2BlhVJ3+L9yPHsSftH5iajna1Zrdd\n0zaWq+2OtmkxpmXVOGS1Jq2vuDYrzKB8DIYU4HyacOLoViuaxmEcmMligsNIQ7fa8Wb9DtcZtrs1\n667FpkB/PDDZhjs17BMElHOMqDGIzX17qkJMihqbTRYWHP8lXieE2nqSaqWvqKTz7TXrLHdGtAqM\nZDbBEJHSQrJwS0kLNe6itq0IplDCBsnZnrE0Boxma0ofJ4IfGIaRZHo4j7hujXNtFgxFT4o+i+1i\nwk8TKcRyvCww6roVrlthmhW4Fp+gH6bsYpRiqXMyC6OyqhysNVjnkBC4sLavH0u3nuV0lFp7rP6z\n1RTh06dPPD4+zhToS+FObV25u7tju91ydXVF27YMwzCbJNTMFZhrnxUEq/q19pa+HHC9dBb6kr9t\nrW8uH7O04av11KXidjk+rYKntfZPP/P0kydMAds41OYlpzGOq6aD9Yo2bDjGUJrBR0YzkXykwbDd\ntIhdIyjHR09/POEPAW9yE7ttDJ3dYlYdQYRoHVOYGIYz4fGBpuvYrDuMUVL0ufbZdTTGsW3XdKuW\nDS3xHFCvPI4nfB+YbEA6R+sabGtpQockizMd7XbN6mbF6qqlWQkmedg/0vsDpyFyM0WuA5yNMGqm\nnJf0H5qntCTNf4uLPd/rxrKHbhm1jTP/emFoUYBSy0zW/DNAZhKykDaDYgZkoFQxQ3GscsZl1x/V\nMt7O4KzJv0sBnzxhODGez4zJEt2INAOuWeGcxaCIxtwWlbK5ez03FYt1LbbNm8emW5NMAyHhg+J9\nQMRgjEWtfSocSKm/V7OH+VVf4jWjDq2uhgi1x3G9Xs8ZoPee/X7P999/P2eSlcqt1qDL+Zi1zWO/\n33M+n9ntdjPgVWP53W43D85WVTabzewtW6NmtBVAqyJ3CZDVIrBSz9VyD54y6FrnrD659XXVDUOt\ngVbgrABdwf414+t62xZ+WmJAGqVx2Yh9Y1pss2KzDQwKJx85DiMhQNs62m7HzZtvaNsrUvqeD7/+\nwHH/SBh6ehR1Fll1iCqjQFxZvDG5VpmgH3v2hwc+fmoRImEamG5uub7asVtvSU2DNCva3ZrrNzf0\nYUL2whBH1qahcx3rzQa7uYIAkvIAqXa3Yn2zomvAjmf0/kD85Wfiv/473W++Z/3Qs5oSTZtrWFK8\nSqtLjBYXmYRi5JJ5/hhiBs8qHqo9aoXGTSX9zHNZTaZ2sywst5SYSvlmnRhFGFZKo9RJLKmkeiFF\nGjGl5URJUfFEbAr48YwfToTxjPoB1YYkDeKUUO5ri4FB0ixSUmPz9WUErCGKJWEJEQjZkD4GnetR\nxghqi+kCT/NqkawADoEyDPtybb52XF1dcXNzAzCb/t/c3HB7eztnjXXW5cePH+cOA2st5/OZGOMs\n7qmCnWmaGIaBcRznf1fwrLM6N5sNb968eVYXPZ1Oc3tMBcTl3NAlTbtU3nZdN4ueqkNRpXerKcOy\nr7TOBbXWzuYM9ZxeTot57fi6rSop4acRgmDU4ERwYjE4Wtth1kIwls/DxHQ8Mahj3W5pr9/y7bff\nsWlvOZ08zpqsDnt85OQ9yTlYr/AxcquKu90SNlnW74CoMEw9d/efSGFi6k8M5wN+fIO+eYNxQrQG\nnKG56rgN1ziTGPuepm3YNC2bzZrVekPjWlCDRsG0lqYz2OGMfNwTf/Fr4j/9gumf/xthf4dYT7MR\nrCtjpSpwUrKcYvmWSTIt3y/xmvHcwKJkllqbVpjdoJBM2YqYPGKutK7k7DHb6lX1rhhB0lJRW9S8\n2eyYGEO2f9RIUGH0EYkjYTgyno+oH5DkaVyDbR3aNiTboGIzW1Gfk1K3VcBkII1iGIMypREbEiqm\njMrL5zdnlza3YYFiyk7fh4AQL1nnjyTevHnD+/fvZ6DZbrd88803fPvtt9ze3j4zbf/222/ZbDZA\npl4/ffpE3/ezwEhVnwHnNE1zNldp05pt7nY7vvvuO96/f09Kif1+z36/53A4PBu6/bIPesnkVCDc\n7Xa8ffv2mSFDrc1W2rkO04YnKrfS09fX17x//57b29t5cPdvfvObP31vW2tzv1yKkRQdqMWoRaTF\nGuhsh9qWcBU4D4Gw8oxtR3t1TXd9Rdfu2N1ec/Pmht3VjvPxwDj0PE6eJiaSCIMVVkYRsyVtW7AG\n0QxNwzhwFIEU0DghGso8E/Ax0LgVRpTdxtKlNakxuSndWlYK66S0OcfIAiAP4hP6sCf8228Y/t9f\ncfjFr/j8b7/mLo2cbxsCDRgztx/UxvqokYQQhbI8Xcy3XzteDuk1JpusV9vEmmHOlmMU4DEm92Qu\n6poiOrtHaUrZRk9KfVTquDOD+ojG7JccU8B7JRGRMBDHHqLHEmmtoK1FVy2hafCmIWFzK0pKOQPN\nJ5W3YMai1hCr6jcmTMwALiYLhoAyrcUgYvM1KrmdalYSV7r5sq979bi9veXdu3ezyUHNPG9ubri+\nvp6FQxVca91xs9nw/fffczgcnvnG1raRJX0KT0rZ6+trvv32W96/f88333zD27dvZ1p1vV5zc3Mz\nZ6rw3G+31iiXYOycm8+1Ama13avnXDPMpmlmj94QwrxZWM4UrbTtn4Xatuk6mq7NtK0tH1jJRtbO\nOJwFcRuubxsmt4Nh4D4loltxVoGYaLZbvv1PP+V87glx5P43nthPnGOEc493hs6Bc4qzW9yqo2lb\nrMvS+0RiHAcOhzy5whJzC8rpxHa1oXMtrTi2a4Nt1xgVRBN2f6J5PGFTRDWA5osmhUi4O3D+xQce\nfvnvfP/4wG/iwOcWHteOft0SG/LiqWVwMfl/UZQQlWhyDfTHMJPuzzmUTFFCdoutIWKy0rYAXv4l\nM1BVE4FMeWbroJQiGIssKE+pwEoBrZhVroQ8VCAGD0TUKCZmn2RnawONoKuG2DpG54hYYioiJWOK\nC1GpBUg24tOUN6xL0YYAksjnJoLBgsnjyGxVGReTBzHMTkh1w3CJ14vr62tub2+JMc4UaB0DVvs5\n622qyu3tLX/3d3/H+/fveXh44HQ6PWdVFpnictpJNTmoAH11dcX19fUMaNvtlvV6/ay++dLgoP5c\nRU41as22jjo7nU6za1Kt0S7PrW4A1us1m80GEeHu7o5f/epXM/AfDgc+fvz4Ku/JMr4qeLquodus\nMDHSlJ25qpZ6kSVisxnCds1td0Mce6ah5xiVPpIl+23D2+/eMYw9vT+jyRMejsiUiCKMqmiIOB9o\nQgBtsYB1Dda5bICNEqaJ4/GASQGGEbM9Y7c7mvUG267obEujAlMinjzxPBLPAzINwISKR1Mkjon+\n/szDr+/5dP/Iv8eRX1+1PG4s/dWK89rhTSRpFkIFnjy2I5prUkWlcXHne92omxd9YRFWv2eRV6VI\nzZxpavE8Tkmz1e38OC306NNiYIvRvEkpzxMLgThNRD+VSScJJNKYhJWENdBal2njtiF0DQnDmErd\n9KkbBsq0ziwWktxPXLLJrKiNT2KOUq8lZS9SUs6rq80gqqAZfJceDpd4vahDp0MIz+qB0zTNFOw0\nTXPbyGq14rvvvuPbb7+d20yW4p1aS6wZ69Lu7iUYLp2C6vSWzWYzK3Ff3h+YAXnpU+u9n1tdzucz\n+/2e4/FItRGsFPLy8cuxayEE7u/v+fjxI58/f56P9ScPnhhY7zasjEGniTicGacIKNZZkjga0yAG\n2nbFzq0ZuwnxnmlShtGTNGBXlt3bHe9++h6RxPT5gDlPuKQ0ncOsHbF1JIRxCmUcmKVzba6Dlj66\ncRh4nEbMOLIKgW0IMAWMHUhBGc4BfxwY9memU0/oB0geawOuAXwg9InTceJuf+bj5Lm/6hiurggb\nR1oZIoEYB0JITCmRjMm5ScpzQGOMhTi+LE+vHbqYKF0XA2ttYQyqTV+hM00qHgq1BkoGUtUnUCut\nLlpQ1hmDJDBJ0XFEp4COHsZswKEpYIwijjIXNpscGCmZah7skj1oiyWgMaaYKuR5nJDrl1mxVKwC\nKYrHcl61fFIXJI0xmzRAUdpqZlxqzls+P5d43bDWzoKaCnzVfq9a553PZ9q2nSne3W4306xLihV4\ntqmrwFadiKqy1ns/W/4te0ur2ne1Wj0zfp83oC/6OytNXDPOCqKPj4+cTqfZt/Z4PM5iqArqxphZ\nqFTPtVK+d3d3c8/pa8fXbVVJAdc5tqsNoT9zmkZ88tltRyGI0ImhayzGNmyajtglTJjYn3qO44mA\nJ5mI2zpuvr3FNZZ43SPHCZcSTWNJDnobOWueGTr5hBsDUxtZNQ3GORwJP3qGcWJQCG1HKmKgGHqm\nx57zpz3nhyOnw4nh3OOjBwttJ3TOICHhT4HTlLhX5b5r6N/u0J/cIp0hhYE4nRn7xBA9E0oqnqkk\nKRRuBlMx6VLz/BGF8IJGF/LUL7HzbdVEoS5HWl2HCpMQY0LVYF2lyUymcSePDgOxH9AxoN6jfsqU\nr02o2KzCFkVNtuhDYdb1plhcArMAzdo8noyUMNbm1pgySDupFpu/Mug65WNmG76n6xDNQqGkcX5N\nGVxzVmoujZ6vHtUir7Z8VHXsNE3s93s+fPjA4XBgs9nMvrc3Nze0bYsx5tnYrqXPbAXIWl9s23Y2\nPnhJ78KTCn2ZvS6Pu7xf/V4Zj6V5fc2GK1UbY+RwOMxq4DqDtA74Pp/P83ltt9t5LNlLavi14quC\n52kYOI0Dmy7vntabDWIs/eiZIgSvRBRrDFdNQ9cImGwuYFSwKAcmDlNAbaTdtlh7g11f0U3CxjrW\nXYOXyMN05mE6czj1TFMgBOWwP8HksdsNtnN5t+2aXBNtmiykSDCMnuPDns/ff8/h/sBpGJhiJFoB\ntVgMZhJSyGbfY1J61xDWHXJ9RXtzTTCRdBzpw8TJj5zCRBAQ6zBk6k6VPB/UkdWWF1XG68ayDYXF\nQlD6O0sb5myGUEMo7RwUIe0Tmj79W3INUhTiOBJPR/Q8YBPYeXee7yCF4o+iTDEiEmmsxfiJ5DyY\nFmMs5UrCZTRHiiuQGIuWthopmzM05Z5OzS0DSLUhLP8ur7O20SRmfVMxergMLXjt+Od//ucZOGvP\nZ83A9vs9d3d3s9XeZrOZa6A183sJapUGrerZ0+lEjHEWA202mznTXdYy6zksZ3Uua581ZmZj0Ttd\n6dral7ler7HWzhaCSxVubZHZ7XZz9rlUC19fX7Pf7zHG/On3ed4f93x8vMMKvFlv2Vxd0XQb9Njj\n+4HRJ0L0rK2jWWX7skgiWkO3W7PuHKSB0ykbqtMKrVuzXTdcs+abzY7r7YZI4NPpkQ/7B+73R/b7\nE8f9ntPxTByGnKGaHeu2ZdNuubrasNpdY7s1MVnGsedT8Pz72PMQRwaTSF2D6VZI2xZrs8hoAoMr\n4O4c7XbDdr2mbVrG0DONI8fzidM00EdPMnlShUWRWCdygCSTh2NfsPNV47d30mVMnFQWVGaqNFWX\nC2qPZX37BBG7YBEMqMnfEWKIxMkzHY+YYcSZbMBhrBSFbMxj7TTh68ACAuocYkawI9q0ONOizmAR\nrKZSv0zzuVYVsEq2EzSSzeEN8qytoPZ15kWumMenlFXFkpvpNf44dvZ/7vFP//RPPDw80DQNm81m\nbkWpWeMwDLMDT3UDCiF8wfQjrz11Usrnz59nNW6Mke12yzAMvHnzhpubm2wmU7K8Co71GnpJ1S7B\nuvZ2VpCtwPnw8MD5fKbrOr755huGYXj2uauvx3s/95c2TZM9AgpwW2t5+/Yt0zTx+Pj4pw+en057\nfnX/GQUa69hd79i2FpWGiCWEI+M4MVhhbB2dcYhVWpNdVwTYrVZcbTfEFLA+oFGQ2CDS0N1uefPm\nLcaAO6wwTcuq2bK2B1o1HBKY5EkJYlTEWNquY725Yr29pm1XaIRhSuy7lrtVw2NsidYgbUe32dF2\nKwhCnAolTABnaI3FtC3aNkxlJNDhfOI49gzRZ3N4su1aImFT2QEaWezWLtTYq4aQVeDWUudZqmYx\nUJ2yMtvxlZaPSocKRSghWcEz10eh9FI+UVspJjRlh6EMVAlj85QUMczZbkgQY2JKEU2KNRPGTajx\nGAk0xmIwBRiz3UZ93jxDNqu4jX3qBy05dckS6lDRrACvFoMhpdlnWZPJoqb4+vMS/9yj7/t5uPV6\nvX6WkVVhTZ3buQSsaZpml56XZuxVlFPp29oWUuucdXJJBbe6VtWMclnaeEnZLuneev9xHDkcDpxO\np9lSsI5KW55TdShaip9qpg1PY8o2mw2qyn6///pvwH8QXxU8vz8f2T7cERTW3ZY32zdsNlvemA6L\nxY8j/fnI4exxEtmmFW7TIo0hjpEQPGvX8e3b92zWa+6PJ46nM8NxxMfAJq5518CuXXEVI8krK1mx\nc1uuuzXH3RXjeCoUqeRFAouxLavVjm61JcZEiML09hYfBmK/QcVkAdN6x6bdYJIhBGUgcjaJIFnm\nL6pMYWJ/2PP5/MhDf+I4TQwaiKKkFLCFIVMxOLHFiaaOwbqknq8ZYkz5sgVTtLRTVSs+U9O6DFLF\n2q7ytUIeD1bNB/JilbPOVNpcxDhM02DbFvUT0zgSw0DnbLHby04/xgjO5AzW+4kQA+7/Y+/dgy3L\n7ru+z2+t/Tjve2/f7pkeqedljWRJLtsiroLYkJhgY4cYDCFV4AQHqODClVQgrkrsPOxQIQFBwGAT\nEtuBOBACdgDHJITYpaTiVLAdOSG2bAmNbMmjefVMv+/jvPZrPfLHWmv37qvRaFpW9+2Rzrfq9O1z\n7j777HPOuvu3f7/f9/f90pLpBqVbisziMCT/TRNdVQC0zvrMU4ngYrlLvOCcCX3QmEnquE0oU4c5\nVus8JlmZAd4YrN1lnueNS5cuYYzpM7emafrZSKDvQ+Z53vcL0whLUgAaChek2cqkHFQUBW3b9mXb\n0WjUk4aG0nsJQwWhYSXjrEzfMOCmsmwSfh+6xAB9z3V4DEBfqrbW9llpkuYriqJXUzpPPNDgedRU\nlMsTcLA/WfDY7ALzYsq0KGEyYT0qWWuhbRtO1h2t75jpBZkUGGMxraHIc8bTfUZFiUfRdB0nbk1T\nbxhVBRfaPcL5zDPKctREU+Yj5pMR1f6czWbFarXEtDXWgYmkjiwbU4zmGIFM5xTeMSoUtq7BwVjn\n7BUT5vmYUuUIQiuwEUPtbS+LtT1pWVYVx+s166al8x7rQ0/M+VCOcypYQ4VFJoHwQbId3uG8cLfU\nGf/vQ08xBU8fg2u07w0EoBjo8NLLLIpOJygNcaQl5Hwh4GblGDWdYWxH29XYLoi0l+TkkqPJgjsL\nQcAgtAk6nBiUMWhr0K5FtMaLDzKP1hFN70K2KSocnwhpV86Gq3lrLdaEIIrWeCVBZB7BeglOP/Gk\niRLEBZb7DueLd77znf1cYyrTJnm8IcknSfABffBM5c5UTk3BLgkXpFJw0zS9BdlQaAG4p8eZMAyO\n6Wdi9Q5FEoaOLSlwpmwykZ5SkB7q2qaebvIOVUr1Fw5pNGdot3aeeKBHsO1ajrdrcqe4Pr7DxdGC\nicrRi30yrVjMptTtguXpCVW1xTgHWjOJkxw5Gu0V4jyZ1xR5QVEWUCjquuOoW/L66hZNV1EYQVkQ\nlZGVmnw8Y8KE0bZENKyXgDGYzmGCxxP5aEJZjmA6pylKTFmyqSu8cUGcXufM8pJJHnoAVjwba1i3\nNeuqojFdz7JQosl1jnYtrmtouyjCrHTwKJVgR6ZimULpVBLc4byQRAyCiHtQF5LUI1SCjRupJNWX\n1IKIrFTxIC4EX6X6Mui9JVxFVhRk0xnKdZiupjVNyAhrg7OWohyhvAYRjLMY4zDWh9lQ71DeUohH\na49XhL4mobfkVY7K8+DbKSpkxFruqge50EdNyg7WGpyTIAwfl1/Q3w3qQl1n0d7Cjgl+7kiKPyLC\ntWvXeuGDVM5MfciUnW232z4zHQojnM0UExs3Bcs0hgLcI7wwLMWmXma6pZJsEj04PT3tSUht2/bE\no+VySdd1HB4esre3h9aa119/nVdeeaU3804M3KEwx9DdxVrbG2+n9/go9OQfrDC8s1Rty6lbc/34\niIN8wkTlFEpzMJ0ynYy56PfxtqOpa5qmZbutUSr6auoccQ7bBEmyDE2eFegywxWwNFuuLW+x3i4Z\nk9HylDQAACAASURBVDMiZ5SPyfMRo3KEzguKbELZjGnbmm7rsCacIFrrQRdMZgtGmUZGY3RRstlu\n7to82dAAz8Y54/EIrxS662ALbdcFMlCWURYl43JMg6GxLZUTfGui1ZOFwqNEobRDZx7xLghG7BhD\n54ukQ+fjySWWt+JpBiVgiX1QL6BCrzGMhqTrJglBND5HK4W1UVnKBwN0dI4ejfG2JW9rrG2xWxOE\nEnwo72qfRfEQF6zrPLGg68lwZFhycUimcbGnqpRAVkBWILoICkQu5LziE71JobXC2vA+bFQd8j7M\ntHrC6ItzgU3uncE6Q9TF2uEcURQFV65c6Wcgh7J6KWNLZdAUWJIKUXInScEzIQXEpB0L9IScswIF\nwwA6nDOFkG2enJxw/fp1Xn/9dV577TVu3rzZB0utdS+qMBqNek3epFS02Ww4OTlhuVz2fdqU9YoI\nk8mkzzyHohDr9Rqt9Rf/nKePvZStrTldr7lZHrM/nnIwmzEdjxiXOQuZYboO03ZstxXeWNptTY4m\nH+coETpn0VYQE+ZDyzynHBd0puW4OWVdCyOXUaqc8WjGhBmlasicxrYdlTfYTCG5RnyGcVC1hsZY\n5lnBdD5DyhKVZSzXKzbrNevVis1myaZr6UyLVaHWHk42mkwH1uRsPMUFqiJOPJ0NElINmtrYMLtn\nHDYLJy5jHaJCtrNLPM8Z3iPexzJryCBR4L0Kj4eNgvl13E5nYdzDOxAVSrd9EI0IGd9doXgvGvIS\nNZqgJzW5afCmxTkbxOFNi7UGrySOjESGoVKoOBmcgqcWQCtyrSnJ8NkYVUyxZLTGY4zFORvieVRG\nEq9wSmEhSvqF964kZMlOQhm3LwHH97DD+SKpB+3t7XHhwgUODg4oy5LxeMx8Pmc2mzGfz5lOp302\nmAJeKqEC96gMDWc2h5lp2i5lpKmXmZACrDGG1WrFzZs3eeGFF/i1X/s1Xn75Za5du8ZyuewzyGQn\nloysL1++DMDFixdxzvUl3NQTTXOps9msLz0nklEq8a7Xa46Pj/vP5rzxQINnchWxzrJpK442K25v\nllysNizMnLLMKYuSC3v7aFGcnp6yWq+wbYfNOlRZBpKNZHRotPVo6xhnOXvTKava0zRbqqbhuOvQ\nkjH2WyZSodosjIcYh249ufIUuQY0HZ5VU7Oqa/a9Jy9LFmWBKEErjTeW1clpOJ7Vksl0TGVaJtMZ\neV4GkQdRjPISmWqKrEQrhbEdTVPR5CNs3iFOqLsWb33oUdkg0ybWYnWUZtvh3KDSLCdBkABrw9wj\noNBEXQK88zgkBkXbu5B4H7JO53wYPYmDkz7OhSYpypC9gsoK8skM7S1iOzpvoWuxrguvK8GYIM80\nRZ5TFDlawmiK8pYMh8aRaY3TBV6XSDmFbIqVjG1jaNoO07VY42L/U4GT6FgmeBt7Vj4I2WolSKZQ\naDobMlQtCot6k09uh4eBxFJVSt0TgBaLBfP5vBdUT1lhClZpTjOJpw8JPMNSbMIw00zkn7MkoFRS\nraqK1157jU984hP84i/+Ih/5yEe4evXqPWza+Xx+TwC31nLhwgXu3LnDU089xXg8xhhzT9k5yfR5\n78myrJ9HTQE7jb0cHx/3Yg/njQcaPAudkesMJdA4w2mz5dZmyYX1CfPpmEIr9sbjMDgbr2y892w3\nG5y1tHWDKgryTDGSjLHkTFWByS1eO8AgvmNtG1rTYVzL1niWrcE4j2studPMVMFMFZQKOmsRU1E0\nW/bahs5blCi0ZExGBtN2VLGB7bynblucgB5tsaIZjUFJ6E/lOo/ZrFBnJWNVMM/HuIlFS5BKs52l\nNQ5nHNZYRIdF46Il1Q7nCO8R50Iv00cGtLNRCSpqMEPfx/RRms/ZJIYQVRFUdE2R1Bkl3g+kMIvD\niQoiHXmJGo3JJxOwLQ4HJpasvCDOobWK1Q1FkWm0CgbY4gyanEyCOpAUefCw1Rmt12TK00laU2E8\nRtJ4SqIwJaUYSZZ54XEthLZEpsHu+vGPAoZjJ1mW9TZkFy5cYLFY3GPjlVio6X4qwQ7l8oaB8x7R\nD7lrIZbIRylYDjPZ7XbL1atX+fjHP94Hzl//9V/vVY6SROD+/n5fbk390JOTE1544QWOj485ODig\nKIo+4CbBhCROn3xK0ziKUoqu6+6ZV/2id1UpikCh9sZiHaxNw53NkteOboWTAh7FAXuzOePpBNFB\nXkyJotpuWa5WuNGYvdmUSVbiyykiHukIYvAjxzhXjArNcSYsm4padyydozbhimdEQZtNaQHZtqit\nYess2WzGRd/QxjnMzDsUkGvNuBwxn86YL/ZoTBfKaal8bCw66XEjeBt6sq4xaAtjlaMnC6bjCd56\n6rqha2ucseGWZSGTcS4M5O9wbrgrZUDixsbCZThZWB+zxsi0VUCmVAyrsdzlw3yoeB+yOIkBNSGW\nf50IHo0Sjc4KVDki70Y43+Ga6EjRdIjyWBv+LLVW5LmO5VuPsx3iShSgI1HNO0BZnAmiCMH+z2K6\nDu86BIu3XXB9gf7EKKkoHTVwMyWoTAfBezztbmmeOxIxaOh6kuY9U6l22M9MJc5Uph26nyQMs8yh\n5N5wfjTJ5Q2NqjebDVevXuWjH/0oP//zP89HPvIRrl27hojw9NNP89xzz/Hkk09yeHjY24il4Hn7\n9m2uXbvGjRs3+OQnP9mLzKd9LxaLnsiU+rXJRzR5e3Zdx3g85sKFC2y3W46Ojs7jK7kHD9aSLErh\neW2xnaF1juN6Q3F6h0wJ2rnwBy8wn8+QPKOcTShNx7atqeqKPAsOE+O8JMtU6DnVHi+Wicqwespi\nOmE0Ksi2S45Mw9Y2VLalEUMtDq8LWi90PhgNdxnM3AErX1HZitbWqKwAZ8iUMC5K5rM5Fy5cwAo0\nXRt6mh6MDTqjtoveeNua9WrNermmXm8RPPPphFmu2G4rjk5OqHwTCBs2+CwGjorrT2g7nB9UryEb\nAqAjGEd7wvyj9fQEIaV8r3HbC/z7ZAVGIA55F0uioYcYXiSsHes9OoZppXN0UaJsi/cWE0tWzlqs\nCQEQ0slOYp/Vx58xm/Qe7wxdK3RW6FqHNR3WdH3wVGJxLhDuBMhiFhNKXy3OGIILqA2fg1ZYu8s6\nHwUMfTiBfp4zqQ2l36XglwQQUraa+pnDLDT1MtNtKH6QsrpEHkolVGstR0dHfOpTn+JXfuVX+OVf\n/mVeeOEFsizj6aef5t3vfjfvf//7uXLlSi+/l9ZYXdccHx+zv79P0zS9O4rWmoODA5544gnG43Ef\ntNMxDUlC6RhT/7coii/+zBMVhrJ73VAHjbecVBs0YNuGzXbNyXbN4YVDpuNJYCeOcvL5FKeDWEE2\nHlGUJaUakdkcciFrNEZZfO6p6FjM5kyrJfnmGLs9ofGW2lpqLN5vqTDYvEVNLKPCcMqWU3PKqjlh\n28zJZYYWGOUZfjRiPp2yt9intY51taU1LUm+LZywDFVVs1ytODk64fjkmJPlMTrXjCdjxuWE+XjC\ntByzbVsqY6BzqFzAhtnAXeZ5vpBImlGRQCPReSQ2LXursiBV67EmznNGlmpSIiKOegQTbB33FUQI\nfNBvj7mqCvmtyhBdBBZulmNbFdsWFmuDN2jbdbRdh7ElOo8iDUphHIh1YIOVmfGW1kNnw4WdMR3W\ndnhskN9zUT4NQWshy3Tw/IxZqjUd1rZoCZkzSdp3N6py7ui6DhHpWbUiwsHBARcvXmSxWAD0gRXo\nVYMS8Sc9lqT7UkA8extmqsPnJrRty8svv8zzzz/PJz7xCW7evAnAk08+yQc+8AGeeuopFosF6/Wa\nmzdvUlVV34NNXqBPPvlkL/7+8ssvc3R0dI86URJOSCM3wznVNP6SjnMoVXieeKDB03mPJRryagUK\nOudZdjWdadlsVhwvT7i1PuXS5pQLewcsZjOKLMeNc7JMobICW2SYLEj25XrEnECzd8pDDkY7LnDA\nol2RL0u8Cq9tvGNtWra+oaKD0lFkwlp1nMiKO80djrY3ubgZM8IxzsZkKqPMM8ajEbPJlKptMc5h\nXShp2C5kBttNxfJ0xfGdE45uH3F8fMRydUI5LpnvL5gu5kyKMZNizEhXGOtwBsQ4lAVnHM7ugue5\nIsyT9GXbYGidLvboyT9BhD1kf6ECFsZLktxtUhayuOCrGcu2PqixB2GDNFiOxKCqEJWDDgYFIipc\naPq72UPb5tRti8oLyMLgCp7A3m4NgsVKR+strfF0kVgRMk0DcV/JtzNZjqkk/m4CucibJvRetSaL\nmrne7YLneaOu656ZmjLG6XT6GaScs7J7KQB673vGbhoFSeSf4RzoMHCmWwq4ieH6yU9+kueff55X\nXnmFtm157LHH+Iqv+Ao+8IEPMJ1OuX37Nq+99hpXr17l+PgY7z3z+ZwrV67w7LPPcnBwwPvf//7e\nNu3555/v32cqFyfhmfV6zXQ6ZTQa0bYt2+2W09NTtNaMRiPG4zHT6fQcv5mABxo8rQ3jGcGLMJ5A\nnMdYS+ehQ1Gblo3vODUN+9sV+/MF09GYQufkStNhMeIYW02GkOHRwCgbozKBTOG1Z6IshcrBWMRY\ndBxov1YvOe4qatuAEsZZxspXHJkjbm8ybhyPOcgyCmOR8QGjYoaSPAge6ByRLKjJGIfpDN56qqrm\n6OiYO7eOODo65vjOCcvTE+pmy8xOaaoa2xkUwigvGeUlddfRGYdvLS63/eezwznChQzOJ6EEIYx5\nRMEDkcDIJXCCkCQC5F0cRVF9ideJiyo/d8daQvwNbQkgvk7soaocpXOUyvEqQ6lQRrMu5LTWWpq2\no+gsqjX4zOOd4JyQecG6wCS3Ymidp+kcrQ2ZZgqe3tk4w0qfDYfRm9AuST/FOwQXPFvCXE5fcd7h\n/JBUhYZWYemxpml6wtBw/CRtm7LHoeF16n0Ofw/3at4OA/B2u+XWrVu89NJLfOxjH+PFF1/k5OSE\n2WzGk08+yTve8Q4WiwVt23Ljxg0+/elP8/rrr/ezm5PJhPV6TV3XPPPMMzz55JM8+eSTnJ6ecvv2\nbaqq6vucaa4zCSCkHi/Q+34mQml6j+eNBy6S0BmDuGjh5F0kVzisgBePBdp6w9K23NoumR6PmJZj\nZqMxk9GY2WjEpCgoUWjjGInmYDJlfzqjUDnKhlKTUgrxI1S+Rzl1FJH2bzVUq5aNrTACKIM2cNI1\n3FxbrmnF3Hvy1iALw97UkxUznPNY6+jajqZuqLc1bdtgjGV1uubG9Ztcv3aDO3eOWa83VNUWsGRl\nznZbUVU1znlG5YhxOWLb1Ji2wXcOW3chM253wfO84WNZE2/xiqgPq6LLSJi7VJGFmmTWRQTrg6AB\nScIsEci8j9llfDBlqlri+o+MXNEolfU/ldKBjSs2Sh4LxjqqpsNnBp87rPbkijBOokIPtnUdtbEY\n5zA2lWmDB2jPtI3781GxKET1MGecZjq1JCNs3/dHdzhfpFnHoSReKtNut1vG43E/qpKyyaFUX7o/\nzDDPsm6TrN6QoVtVVc+S/fSnP81HP/pRnn/+eW7evImI8Pjjj/NlX/Zl7O/vs91uuXnzJi+++CKv\nvPIKq9Wq9wutqorT01Nu3rzJ6ekpo9GIK1eucOHCBS5fvszp6SkAo9GI/f39XiIw9WrT+07l3KHE\n4Bf9qEpnLa0x0JcDwlW1FoVV4JTH4NiaDt3V6O2aQmtGWREC53jMeFQyyXMyL2jjmOmCd+wf4oBp\nMUYrTaYl3ESxLxOKEpTSWK1oxLHutlSmZu0bWm/YWstJ55jYjtcRJs6RdwZpOmgNs+kh1ipctaHb\nrqnWK5anx2y3FW3TsVyuuXn9Bjdv3uRkuWZbV1hrUBpGpmVTb1ktV6giZzIasz+dYdoOHHTe4zoH\nEtSOdjg/KARcKNdKbPalzDGcYMLMo+goSUbqY8aZz74fKv32oWcKpCzTJc/OqFzkPLigYSuSISrH\nSzKzDhlB0kW2ztNZh7Khqekyh9OQp355Z+icp7M2OqNEEpoPyla9Ti8xu/Du7knJ2WCmLcG+TIsP\nggwiKAVKdmvzvJGE1bfbbf9YEgtI/p6JEZtGPNItKQjleX7PNkNSTlobaW4yzWWm3uWrr77Kiy++\nyIsvvsj169epqorFYsGlS5e4fPkyo9GI5XLJzZs3+wDZdd09JePlcsnJyQlZlnHlyhUWiwVlWfL4\n44+jlOpnOReLBRcuXOgDZVqn6fjSbTiyct54wGVbQ2e6WB6KPSURjAp6oUbCTxXLucqD6kBLRVat\nKVYZWRZm3QoUhYdFPqI2La21LMpJUBXKcqZlwaTIGJU5Cz3DZxkmzzACVRv0RG3dse4qNl2NWE9u\nO8beUTqHajt8tUWaLSw2CCNYbXHrYzand7h16wanqxXVumaz3HBysgzO6G1FbVsclkJrGt+x3K7J\n1yP29vZZjKfkolHWo1Esm4attdjWY7tdbew8IffUJu+OfngJc56hvJqKnWHWU5RKNpqB4Ui0NVNB\nmF1JJNsSlV2waIlZqg/zpOFlFUiG7TWEVMxs776eE+KIVJiZ8Qa89qA9xhtQDhOTW+ss1scyLEGJ\nSCQqBfnAHPbisd4iPvVvDd524A0iniyDTCust2RqtzbPG9PptGe7phGj1WrF0dFR78WZWLOJVDQM\nnsmtZDQa9SMgqUyatjmrSJT8N69fv87Vq1d56aWXOD097UdGptMp+/v7/XjJarXqy7SpL5vKx0Bf\ngj09PeXll19mPB7386BJ4q9pml7OL5WlhwHz7H6H0oLniQdetg2jHXdLAoigs+Cf6OLsXFDgDCxH\n5yw4jzWJXu/JtJAroUBxUE5pnaUxHfvljHk+Zn80wU6m4MYoCrJCMcnHXMqgHRvqeY0zHeI9r5uO\nlfNsbceR68iMQXUNvlpjNydIvYJqyVjPqdcd3emS6vgmx3eucefolGpV02wbqtZgXYvX4Ypf54rJ\nbMR4UqLywGYstGZvPGOWl4gxeOtoHdRNS2fDbN4O54eUOSoVeilKJKoBxfKsUnetyeKsp/choGpR\nfQYa9qGiRyeI8zjx6EDjDZmnRGUFdDCojuVaJxqLworCRdszFIjWoDLQoSfqVAy0osP4jAdvLT55\njCoNdsBeJNjmaVG46FHqfMiAwcdg7uMtyEGk8i0SwvkO54s09pHGNRLz9JVXXulVfZxz96gLDUu3\nw15i0phNP8fjcR9EtdY9SSgRhO7cucPt27c5Pj7uSUeTyaSXBByPxzRNExKIqDObXjcFOWNMP3Zi\njOH69euMoyjOY489do+ubWIWpxJ0yoSrquqtyIal6UcBD3ZUxYP1oadkfQgyocbu0ISTRRQ1iyNy\nqf5usCbQ7vEWJT4ET6VobEvnDFVb8/j0gMfnB2gtlCYn68J8kqrCeUfljkM15t3zJxgXOZOyJFfw\nirWc1Ccc1RXGb7CyouUOXXYbX59gt6fs6TmmUtQnNfb4CDk9guUKt2mwrQnTDNqFQXRtme/Peefj\nj3Fp/wKTfMoom3Bhvs9sPKFtauq8YJXlZCr1ztIs4A7nhTQv6QmlWOtCpudweKVIjb/QpSQaRgdH\nFdFZYNbKXX3bKI0byr/xPyHxc/1XLUAmCg2IU4jOkLxEugaVWRCFxKamZDk+/l7nI3QxBp1jCV6y\nSAjomcpCpqkFY2L5NQZGz10D7HAvEfiCITdeI3Gu0zqLREcVJbsLu/OGiNB1XR9AtNas12uWyyXL\n5ZLVatVbdKUgePaWAmQq2aasLWnkpuel3mJVVVRVxWaz6a3A0n689z3bNzFhh1ZhQL+/oV9n2n9i\n0kLIqtO8ZgrCaT61LEu22y3L5bKfC12v133wTLZs540HKwwf9Vqsd6EnY21wvPc+yqC5eCUctg7M\nxTBiYnwoQ+ED8cF4MAhda+lMR9Xc9bYrRyWFKfCthP6QsZRaMSo142nGU/ML7E0nwe/TeWzrqNY1\nx2ZNZyqss7TeY9Qxpj2lqU45VHvkbU69dpj1lrxeM7ENnlAuU3H0ptZhsPzChTHvevoyVy4+wUjP\nUDZnpIMazLptyQU0Hq0VKsuCxq3oN/n0dnjQ8N5GV5RQ2gzEcI8X1buaEC92kCB0kMQJMhGyPA9r\n1DmUSpJ3RGariuL/Evdn715ZW9A+iszbIJaQu0moxhgTLjJFkDxHFSOyckIxmZMVY5TOSEE59K40\nSmdY7/EWBIezHXeNB0Ka6n2oNTsfWLZKkq9sjsNiraO10V4tXujucL5IZdTT09M+8zw9Pe0zseGY\nSarspQwulTpT0Dmra5sEF5L7ylnGbdr/sDfqvf+Mku/wtZNN2mg06q3NUqY4zCaHtmhd17HZbDg9\nPe1HVJRSNE3DjRs3uH79OsfHx9R13ZeckwbueePBBk8fSkU9SSE8GNVTwpV9aq24yPJz6Tnehb5T\nHF73OJwF4y2NqamlDiexTKNUCNSdM4zJyJ2Q+agKkwWJs3me8w69TzN/B21jaOoWZS2rtWFrG+6Y\nBqQO+ri244KcMrVjpNW0OCTvGI3CSWfkM1qBRkFmMrrM88RixBOLCVcO9pjk+3iTY1vLdrPGdTW2\nq3Guw+EQnSYLdzhPJBKNUllkuAaST2gvhDEUpXwfXAMRR90z3K1j9STYlrkodRs1Y2XAvA2hmEwF\nMQJlHdoLqsjJZILRmk4XwWHI2WDEnWXocowup+hyTF5O43iLJssz8jxDRQ3l1rTY2mBMDJTehnGW\n+Nfjvev/FnHhuLJYKvY6D28vBl0BDLsLu/PGdrtlu91y/fr1PhClHmMSXB+SZ85q2aZABfSPJyil\n+j7oUAB+6N+ZXFXOEnRSYE4ZbAqCXdf1+rrD5yWC0lDQPWXGScB+vV5zenraB/A7d+5w/fp1bty4\n0Zt7p6wzmYKfNx5w5hn+HTKnvPNBSNvf1QD1kSZhU6DtxbohDACEwXMPGO9w1mCdRa1OQp/KOTpn\nMdZwOJ6zn49CZihg6pa2rTHaMS0zni4fgwNBOcVYhFed4WTZsJGQVTa+4rTz7EvDzJVMZUxRaLK5\npiwyRq3gTWgvdd4xsSF4PlZo9vDMvGeeZaAL1u2WZb2l3q6p6zWdqfGY4MDhXMh8djg39ApPca7R\npRMPirvnmbQOY3+QEJjSLZxUQm8zXQ4JwcHEuRR0Ja5ijxJHhkPpINWnVA55hs1HNNmYpm3R3oXZ\nUJ3FzHNKNpqhywlFMaYoR4xGY8oyB+8xXQPrJXWzxjmDNQ3emqAqJCFzdi5cjDprg8xfrC2H/m4o\nQYtSOB9Kt+YBd3R2+NxYLgMp8dVXX+3Ls6mMm8qkqceYAtFQJWiYNZ5FCmgJn22U5SzLtWmaXsUo\nadQmI+00k1oUBV3X9WSh4Wul/aXXTFnvZrPh6OioL1HfuHGjN8vOsqzPklMvta7rB/a5v1U88Mxz\neEvzmGn2LA2Np5JtqDLde3XknY9jAQI4nA+zd7XtoPXIKpSFO2foTItZtMh0j2w0JdN58BRtWqx3\nFH7M/mSCKy9i9yyua2g3K5pqyco1rGipMKx8zbG3zFzLwncs9Ih5XjL2GSpMmURvUccIy0igaGvM\n8oSNHiOVgEzYbCq26yVttYauRTtDgSdzHrGu1y/d4RwxEDUgqerE3mYvNSRB8L3PMF2cD42CCgpi\nVmeDOLwOzFsdS7ahtRoIRBqHUh7tQ/DMdY6WHJuB6A6fdSgcFkLwzMtQrs1LdDEmHy8YTYIw+Kgs\n8NZQb5bUdRXt04JIAn5Q7UGwzt6tAjkXR2587NmqUK4NnXjw0O0mPc8dt2/f7rVhhyMgiYE6DJxJ\nj/ZsRpaC6DAjhXuD5zDgnp0BHSoXWWup65rNZtOPyxwcHLC3t9eXWhOSjdiw/DsM6ENpwKZpODk5\n6RnC1lpOTk4wxjCdTtnb2+tHXFLJODmunCceaPBMQ+Ph/yHRDC2mSMbwMWimL4s0l5bYFTIoI2ic\nD8IKXiu81zTesTQ1du2o24rNdsV6vaTev0R3cJEnFheY5gXiC5S1+BZwlkmWcznbpxpf5E65xx0Z\ns5UNtTc04mjFUgOV99TW0XSOqjHkW8FvHL62SOeCK4xylGVGDtxoHavbK/L8Fl7GiOgwGmANE6WY\nK03lDOu2Q7cG351/6eFLGWEM5cwcZGR9Jy9aJXFcRZLIgYsBNwQpCdSfEGTjHLMo6WcsvahYviUK\nEYTxlXD1qFCqIM/L8Byfkani7t9MFsXjswKyUQikozHlZEY5mZFnGaZr8Go7OIbgkhKGbSQqDoXq\nTGh9DKpA4kF0T+RTLrFvdwpDjwJu3brV/z8FSLi3jDoMSCkjPCt6MCTXDHVsU1k3BbehWPxQsi+R\niVJ/8tatWxwcHHDlyhUODw+5ePFi73ySMtNh0B6WahN5Kb1+Yvh2XdezitMxHB4ecnh4yOOPP87+\n/j5a63te47zxgMu2LpInCGUhoJ9Ej96H4ctM3ocpgIbtQhxVPZOx/53y+CxkAS0Wbyqqestmu6ba\nbqjbJowKlDmHekGhBHGC6Sy+NUipWBQjLuZzHi8OuFnuUdsa5z0NLVYcnRcaBeIttm2oKotfO8zK\nYDYtyjhy75mPcvYY4ayn2Xbgl1h3E1FTZtN51OpVjL3QecWytRRVhzQttjn/BfClDD/ILH28kEs9\nS6JiUNwIIbqbxB5i8Mu0YRuJ7Fc8KvY2Ja77dLHYu6Ko8LyAuLBRKJ2RlRmtsUistqi8IC/H6KxA\n5zm6GJOVY3Q5gqzAicK5BmsDgz1lyuk1nfWxFE0Mou5uW0Sp6KYW9XpddC+NBD27q4qcO5bLJZPJ\nhPF4/IbkHbhXai+p8yQMy7cpkCX1nrSP/kLqDAHnbFaafiZFofl8zsWLF3niiSe4dOkSh4eHjEYj\nVqsV6/W6L7UOg/x8Pmd/f58sy6iqqmfYptnOVIoty5LDw0MuXLjA008/zTPPPMPFixcBegLVarV6\nIJ/5/eABNzbuXtlrHWY7RQnJD9ETdTcHuFteAGdjyi+R8u+ihqjWIMH3U5JgO5aNabi5PcWJOg1w\nFwAAIABJREFUx2tocVxaHLBXTJjqkokuyHVGoRTiPHMKLpUL3jm9ROs7bO0Rt8W6Nng7OsE4YWs8\nVdVh1h3tqsWsW7T1lFqwhQYFNhc6HMoajG0Rqyn8BJUpCq3ACkVr0esafxrMvv0jcPX0pYygKhRV\nfYgZWQqcg96PEol96hBcA7nNRlUgh3gVs1XVlz613K289Nq23mGtw4uLMoCCSAYSLMpypSmsw3ah\n3KWzknI0YTSekI9GlKMJxWhGXhSAYK2h7To6E8gapjPBhBuFcLev5Hod20gWihkyOvzfdgZnutjv\nNGQieLNbm+eNsiyZzWaf0Zs8q1E7zDzLsqSqqp7tOjS3Phs4U3Z6dl/D/uTwORAYwHfu3GEymfDk\nk09y5coVLl++zHvf+1622y0vvPACt2/f7mc8gV4A4amnnuK5555jNBpx69Ytbt26RdM09zCHh2Xj\n4XP39/f70ZbpdMqdO3ce7If/FvBAg2cS1U7l16QSYZ3vS0Xhwl3u+ZJcVCRCiCckifZREtiFAogm\nU3Hk3KpgWG0cWxcCaCeeVVfz2OaUx2YHHM72OJzsMc/GgaBkOjKnuDhaUO89gRWPEs1Je0rnGvCO\nQmkEhWkctTI0HhpjsC6I1Ossx45nsJijpiMKnaOMQjUZvsvR4wLJdBB9aDrMusKcbjAnaywea3cn\nqPNFrHbErDEZF4gEB5Mg9B6v9n2yLIvEoFgiRTwqauKG+cjIvh30kBCw+EjUiSVcBLIcF2dMldbo\nvKDw0PoGayw6yynLMdPZnOlsSl6O8JJhncN0NabtqLdb6irIRpouCG+EE6FGRUWhyIbCD0q2PSHE\nh9EW01ZY26F8cJbB7loK543FYsHBwQFwN6kYBr83CnZJhCARbxKB582E4NNjZx1WUq9zmH0mck+a\nv6yqivl8zvve977+94nQk5i3o9GIw8NDnn32WZ5++mlWqxVXr17l2rVrPcloWNItyxIR6edN27ZF\nRBiPx70d2Y0bNx7mV/GGeLCWZFE5SKl0IooBMgoi+MRSlGhA7H1wYSGQiRQK3F2SkfI+KLOIxPKa\nJ5OgpJLUYvCeDstJs6HFsu5qTqs1R9slJ/M1l2Z77Jcjppki0xmHi0P0uKAYj9mb7rFsl7S2BoIG\nL52mmhtORzXrcsumXOFrQ4Fifzbh4sU9Hn9sn/3ZmLHOEKvYbBzVxqGMZ9u2bNdb2qMTlkenLI83\n1OuaTgl+J4F2rhC5G0TuJp0+lj77dDEIePg4AsJA3D0s5BBoies0zn16JKr4BPcc512cWxa0yoEc\nUSXWa1rjyLIQbLVS5MbiUIzKMbPpjOlkyqgsQUHT1tRNi22jbdl2S1NtaJqarjFYE47JZ6HREWQD\no8RZHBeIlwphrjSODzjrgiORuquBu8P5Yhgwh8LwQ81XpdQ9ritJCCHJ5Q17mmeFBfoyfgzEw15q\nCqxJ/Sf1NBODtus6bt++zauvvsrjjz/OfD7nueeew1rLYrHoBe1Fgv/mE088wWKxoK5rrl69yq/+\n6q/y6quvUlVVnwWnGdVUHnbOMZvNODo64tKlS0ynUyaTCXmeM5/PH+6X8QZ44CIJCc47vI0B0prw\nx6tSPyY9Hk5Mwzq8iAKXAqSKfdCg6pIpj/IW7T3Eq3yldFB+AdZdzbarOVqfcr24xWPzAx7fO+Cd\nexd4bL7HwWzKfLxgqufsLQ64XD1ObSqMa/HiA0nJeVYrw+lxzfHtFavjJa7umJcjLs5mvONwn3cc\n7rM/m5BniqZzHC0bbtxacfP1G9y+fY3V9VvUt4/Znm443XRsnNDlefAj3eHcIDIcSbkbNFP/ncjA\ntT5mjJKUgkKJFiyZygMRSEVdWxeyztQ/DUmfxVgX12eBEo3WI0RynAdrLM50FN6iohtQgQ6+heMJ\noyIHZ2mbhvVmzWazjVmmo2taTL2lrRtMZzGtC0Yv4sMotYBSAlr1nAEbR3SSAL3zYJwnUzpsrxVO\nNWc/rh0eMpKX5fBC5uwsZwqKqTQLd7PINCaSfp4tjabth/fTPOYwoKWgmTLRpBp0fHzMpz71Kbbb\nLVeuXOGxxx5jsVjwnve8p7ciU0r1VmPOOV566SU+8YlP8KlPfap3VUkzqcNxnKR2NJlMuH37No89\n9lgvC5iy0/PGQxvm6q+cesq8DaQKFbLG4YgKEEcAQp8piWmHHpHCE8tjzqD9XVslJUE31yF0UaWo\n7Vp8Z1jXmm27ZdOuabuK1jUYDjiQBZPxiHkxY5JN8NioIgSiFdbBZtqxmjQsZxvWFzZgLPNizKX5\njHcc7HF5b4/FpES0cLKpcBxx886W1abi9Zu3Obp2neZ4SVe3NEbRSEan0vjNDueNof/mXbb3vcQL\n593dgKRVUBRSGq1VdPbJQuRUgu18MKNO8nw+SOcJmiKfkOmSTOWIKKztsL7DW4OyLUoJuaI3Zc+0\nwltD02xZb1es1iuqaou1IF5wncO0bcgcfbA6S7OnwVLN9tmnJ7RB0B4TpQmtc6E7GudBvQrkPq92\nIgnnjfF4zHw+/4zxk7NiB0PrscSuHQbVJMk3FD5Iv0/3hyMsw4x3yNwdMnhTgD09PWUymXDhwgUO\nDg64dOkSzz77bD/SMlQ6unr1KkdHRyyXy77EPBqN0Fr3c6uJIJVUhMbjcR/Q00VEKkWfNx548BQl\nvexeIi34MK4drsptan7ffY5KIwT+7peahtC9C4QLH7pF/UJSSUvFOLyKJw8tKB8cK1prWHdbWFmM\nadhUK45OjjmcLdibztifLZiPpxRFjtK6H1VwQKY0kzLnYDHCjvcRL4zznPl4xMXFjP3ZhPEoD4vr\ndMvtm3d48YUX+fQLL/La69dY3jnC1Q3eegwZViu8uN04wDnDE7KvJMCB0ojKomTH3XKui9UR0fTC\nA1mWo3VBlhWIyhClybTGO4tWGc50JG8WrUIftCjGjMs5RTYOvXRjwIDtgg9n19Zk3qN0QZYpMnHY\ntqKpOparE9abJZvYy1IqjLUk/m+mFVIUwVpMO1AO5w3egTVdfD+R9RuvVW0cu0GCmpESj+AQrXBn\nmXw7PHQ888wzXL58+TOyTeCen6lsm+YwE2HIGNMHqLNZaXre2dnR4e/T9mcZt+lnCnBlWfbBcj6f\nM51Omc1mLBYLjDE0TUNVVYgIZVly+fJlJpMJwD3BMZV4J5NJ/7rz+ZzHH3+cw8NDptNpr4r0JZF5\n+nto0S7MlrnBF4KLc3Gp7Cp9EtqLKKTelL8rpJAIR4n9aPFowBLcK4KxsZDnGVYBTtEZw6q1NG3N\nerPiVn6HRTHhwnSPywcXuXRwyGwyJsuzGMDDseoOMqOYSE45npHrnEwp8kyjRNFYQ1dZqrrm9Zu3\n+PUXXuSTv/pJXnzxVY7uHNHVFoVHaXAKXAYq87hdW+kRQJzF1AqtQHQWS1wKrTLQhC8t9t2zTMcr\n+ZI8H8XAmZNlOZnWaAFvDN6ZqIRlUD4IzZfllMlknyIfhbGppsa6DpTCYzBdi3eeshR0luG6LVvb\nUjcVJ8sT1ptNKP+qIDmpMwGvyDKP+AzBkWnBi0XEYkwyTw5Sg0GtXvDRrMHHv0OJwV1hUVEwYaeR\ncP5497vfzbPPPvsZfc+hmMGw/FpVVT8qst1u8T4Iuaf+YNu298x2npXNO/saZ7PSN1IdGgohVFXV\nS+cl55YUzJ1zlGXJxYsXezuzodcohIwyEZ5SYE8avJPJpO95JlH788YDdlVJJKDA+HM+uNyHLylm\nn/Scx3jlExm36fI4ltFCSc33WWsKnMaH0QAb2ZB3Ba0FROElloYdIELnHNaGun3dNGyyik1bs2q3\n3FyfMIllBCQct7KgnTCm4GCyx8XFIYvxnEJl1J1h1VR0rqVpa06XS15+5TU+9dJLvH79OqfLU5o2\nyKTZTHCZwmuNzwSf0btZ7HA+EJWhsgJRebD0Sn1zQt8xy0MVwnmLjcS2LNNBT1mHgElWhEwxLxkV\nBVoUCottW7q2pm0btAA6oywnZOUUnWUYW2NxYUSG6FsYPW0773BdQ7PVeKAxlqZpg+etysJr6wKt\ngzWTinNc1gYmO/3fAiiVYSWYF1hjIb6eisepvY8jY54MT6FCNmp2/fhzx9NPP8173/vee+Yx4d4x\nKqDPHquq6h1Xkt1XygDT71MJeChGkMqzw3Jsep3UB00lXu+DyXUKxMPAnkTmk80Y0L9eYtzOZrO+\ntDyZTFgsFn3pNjFu8zzve7Tp9VNpOo3eTKfTh/lVvCEerBm284i7N1iGslG88u3rlikT9XfFhYiM\nQIlKKKRMNPWfwEQ1FRO9CUNgtXHcIOjXigRtUok+id6BVyHoVt7QtZbathzXa/LTW7GvGnoH1lm8\n9WROM8smvOPgcZ5tLY8tLOOsxFtH1dWcbE44Wh5z+/Ztrr9+nVdfeY2j01ParguxP/NIrpFcQ54F\nu6tM47pd6nmuUIqsGKGyEp3lqCwLy88FRauyKNG5xsU1KCperUdNWGLwVUVJUUwoR2PKTKPw2K6h\nWq9wbHCosE1ZovIiMG9xWGcwLug044Igu/UtrnPUSdTAe7xkoEuyvETpEqWLIJyQZeGCUnWhRNtC\nZw14gxDHvRB0VmBiO8NZQ/hDsEEbSQKhCW/JlaeQYJrdsBNJOG888cQTPPPMM58hYADDdtbd4FnX\nde/HeXR0RNM0ffBMDNYU1IaKQikADolCKZhqrXuCTlEUOOf6zBbog9yQwJSC63C/KXsUkX4GdH9/\nn0uXLrFYLPqe7NmZ1rP/TxcNqex7nnhQwXME0N48CabWfeC0d8u33t0tA0g4WSX4QS/TSTDotWF4\nrg+6vaMAoW8aDH/jTFt0rhDigLsKIy9pjAAXZNbEDeTMEmGEWGJ2Lhp5g/aKaT5hs1/RnXQcz08Y\nZyO8tazriuPVCXdOjzg+PuLo9h1Ob52w3dSB+QihXOYlBO5I7PA+9LuGn9cODw1hfW5XVMVxCEpZ\nyDJFBGxg05osR2cZXhOlJcMoiSRWLQp0jhQlZTGiKccUMXg601Jv11TbLV4UKi+p8pwsU+AMTb2l\nrta0TYXtwlxxRtDQdbaL1ZEO6zw6L8mKKboYgRqFMrHOgvm2BHJS19ZU1Za2Du49QbE2DtV7MDYK\nNDgbyEzxZuMNb+kk9HUdnqba3PNZ7fBQMQJ44YUXeuPns8pCw8eGqOua5XLJyckJTdMwHo/7bK+q\nql7gfRg84V4Wb2LZplGY5J6S5zne+z54ptLr2dnQsxlpKhEnYfc0W7rZbPpjTBj2dYePDSEifPKT\nn7znszoPPKjg+QzA6f/yTx7Q7h8+joBX+TXu9x25/t83zTKfAf7vz+e4dvi88AzAKx//2XM+jLcF\nnmG3Nh82ngH49m//9nM+jLcFnuGc1qe8UUngN7xTkUPgm4GXgPP3jnl0MSJ8+R/y3p+/3tSXCHbr\n8y1htzbPCbv1+ZZw7uvzgQTPHXbYYYcddvhihvrcm+ywww477LDDDkPsgucOO+ywww473Cd2wXOH\nHXbYYYcd7hO74LnDDjvssMMO94ld8PwcEJEvFxEnIu95k22+U0Ref5jHtcOXLkTkm+OaPH917B12\nOAeIyDUR+eNv8vsy/o18U7z/Oc/j94sHHjzjAdv48+zNisifetDH8AXA56Ik/03gKx/CcezwBcTb\nfG3uaPLnjLf5+rkvfK5g9ajBe98Al4GfGT78hXyNh2FJdnnw/28D/jTwHu5KT6/f6Ekior33bwuN\nsPhF7QwQ3374ol+bny9ERAHe72bZ3gy79fMIw3t/80Hu/4Fnnt77m+kGnIaH/K3B49tBGep3ishH\nRKQBvkZEflxEfmy4PxH5YRH5qcF9JSJ/SkReFJGNiPyiiHzr/RyjiByKyP8gIrdEZCsinxCRf/XM\nZl8uIv84vsYvicjXDJ7/nSJybXD/z4nIh0Xk3xaRqyKyFpG/LSLnr2a8Q4+3w9qM+/m9IvKpuDY/\nBDz5Btv8CyLy83Gbl0Tk+0VkNPj9SER+UEReE5GViPyciHzd4PffGbOL3y8iv0oYzr90v8f6pYS3\nw/oRkUJE/kZcE+nc9m+e2ebDIvLBM4/9tIj8UPo98Djww/G9bAfbfZuIPC8ijYi8ICJ/4sx+ronI\nd4vIj8Xz4Asi8i+KyGUR+UfxsY+IyFeeed6b7jfiQET+XtzHKyLyHYPn31O2/SyfzVeLyIfi818X\nkR8Vkf238LECj17P84PAdwHvA37tLT7nTwP/CvBvAF8B/BDwd0XkN6cN4hf4PW+yj/+coFbxO4H3\nAn+CoMjX7wL4M8B/Cnw18Arwd87s4+wV+lcA30JQCvkW4OuAH3yL72mHRw/nsjZF5F3A3wP+LmHt\n/R3gz57Z5n3APwT+dnydPwR8I/CXBpv99fj83w98FfCPgP9NRJ4abLMP/EngXye0IY7f4vvc4XPj\nvM5tGfAC8Pvia38Q+H4R+d33cez/EnAL+B5Ctv10fO2vI6y5vxGP74PAXxCRP3Dm+f8e8CHC+vuZ\n+Jz/lrAmPwC8Rmh9pff0Vvf7HxCk+T4A/ADwIyLy297KG5Kg4vQzwM/F538L8Gx83beGJAb8MG7A\nHwGO3uDxbwYs8I1nHv9x4MfOPPbDwE/F/0+BLfDVZ7b574H/ZnD//wL+2Jsc14eA/+qz/O7LCcK0\n3zZ47DfF430q3v9O4PXB7/8cUAGHg8d+L6G0u/8wP/Pd7W2/Nv8S8E/OPPYD8ZiKwT5/4Mw23xDX\nmwLeDbTAhTPb/CzwffH/3xn3+dx5fxdvx9ujun4+y7H+deBvDe5/GPjgmW1+Gvihwf1rwB8/s81P\nAP/Tmcf+ynC9xuf9yOD+0/F8+u8PHvv6+Bkt7nO/P3Fmm3+QHgPK+DrfFO9/eXyN98T7/xnwD848\n/7n4nCtv5XN8GD3P+8Ev3uf2X07QOPxZkXuk+HPCggDAe//1n2M/PwT8uIj8FuB/B37Sez/UgPfA\nxwb3rxGy0ccIWegb4QV/r+bih+NxvRvuW19+h/PHea3N9wH/z5nHPkzIEBO+GnhuWLYirE9NKPF+\nZfz/S2eOpQB+fXB/7b0f3t/hC4fzWj+IyHcRqglPxX0Ww338BvA+BhljxM8TMuUhhufOG/HnP32D\nxx4Dlvex3184c//DhIuYz4bh5/jVwDeLyOrMNh54F3D1TfYDPBzC0P1gc+a+4zNLy/ng/zPCm/0G\n4Kw48FsWVPbe/88i8jQhdf9G4B+LyF/03g/Zct3wKfHn51P23hEw3p44l7VJsrZ9c8yAvwr812/w\nu6uEK/uGcMI462M1PHmcfY87fOFwLutHRP4ooeX07wD/H+H7/o8JwXl4LGfXRc7nxhutzc/0SXvj\nc+fZx4S7n8db3e8b4a2eX2fA3yd8Fmf3/ZbGDh+14HkWtwj16CE+ACQW1ccIrphPnckU7xve+1uE\nq52/KSL/L/AfAb8Rqvm7RORwkH1+bTzW3ZX9Fwce1tp8Hvjnzzz2tWfu/xLwfu/9p99oByLyS4Qy\n1gXv/f1mQDs8GDys9fN1wP/pvf/R9ICIPPcGx/LE4Pc58H7gk4NtWkL1Yojngd8GfP/gsd8KfOLz\nOM5h0Hur+/1n3+D+r77F1/glQin9xfs8zh6PGmHoLH4G+K0i8gdF5N2REdZ/8d77Y+C/AP5LEflD\nIvJlIvLPiMifFJFvS9uJyM+KyB/7bC8iIn9WRH53fP5XAr+L8AX2m3wex94C/52IfKWIfD2hd/W3\nvPcnn8e+dnj08FDWJqGl8FUi8mfi6/xh4CwT/IPAN4rIXxaRr4rb/csi8gPxWP4p8JOE1sS3isgz\nIvJbROR7ReQbviCfxg73i4e1fj4FfK2I/I74On+ez5xJ/xng94nIN4nIe4G/BozPbPMS8NtF5AkR\nuRAf+37gW0Tke0QktQ2+A/iL9/thcO859q3u93eIyHfFbb4L+D28OSlz+Bp/BbgiYQria+Ln+7tE\n5Ec/25PP4pEOnt77fwj8BcIH8mHCm//xM9t8d9zm+wgB738FvonwZSe8Czh8k5cycR8fA/4PwnzW\nHx6+zBsd3uc4/I8TiEgfisf0CwS23Q5fBHhYa9N7/wLwB4A/CPwKYV1+75ltfgn47YST4s8RynPf\nB7w62OxfI7B2f5Bwdf4ThDLu5+zt7PCFx0M8t/1V4KeA/5HATB0RCEND/AiBzf1jhED6y3xmT/R7\nCb3IF4lrxnv/CwRm9x8h9DD/Q+C7vfd/f/g23uCY3vSx+9jvnwf+OcLfxb8L/Fve+597k9cZvsar\nhGx2SuC5fJQQnG+/wbG9IXZ+ng8AIvLngK/33n/d59x4hx122GGHtx0e6cxzhx122GGHHR5F7ILn\nDjvssMMOO9wndmXbHXbYYYcddrhP7DLPHXbYYYcddrhPfNEFTxF5OgoCf9V9Pu/rROSjItKKyE8+\nqOPb4Usbu/W5w6OEz3c9PkxIELZ/5Nb8Qwme8c0nj7tGgkPE90mwPXoQ+Hxq0X+ZMDj7NPBHv6BH\ns8Mjjd363OFRwqO+HkXk6+PxLR7Q8bwt8DAzz58mKPI/R5in+U+A736jDSVY8Xw+wgT9Lj6P57yL\noMRxzXu//CzHdVZhY4cvHuzW5w6PEh7l9Zjk8970eVGp6IsWDzN4Nj543b3qvf9rBDGCb4Wgvygi\nxyLye0Tk4wTtxifj775Dgq9bFX+e9aL7zRL8NSsJsnq/if+fvXcNuWXd8rt+47lV1by977rsvc/Z\n3Sfdh77YrU3yQZSgmIBBEoIRg4gfjCFKa1QUiYgigjYEJCjoBwVBokLQYPwgShNUGm01EUUiQpDu\noE1fkj7n7Mta673NS1U9l+GHp2q+c7177X3O7j5rvbv7zP+i1jtn3WbNqjGf8Ywx/mOMLzGTmt0W\nwFPgP5tme3/yZHb1R0Tkr4lIT02qRUT+ORH5lWlW+Msi8icenPNvk9ov8SAi/4+I/KHpXF+6l+MZ\n7wxn+TzL51cJX1l5pBZSALia5PE/nbb9ooj8ByLy74vIp8B/L29wC4vIxbTuD5ys+9tF5OdF5EZE\nbkXkfxGRb37ONfxdIvKJiLxxMvHO8GVa2fxWF2pftv/6wbr/hqnFDLWSxEBtkfT7qZ1HWmqVid+k\ntvP6EWpPuk+Bf2I6bkGtyP8XqNUv/ii1dmwGfu/JZ/0a8G9+zrXN3VGugX9het1Qi2kX4P+mFmf+\nJrXf4R+frvVPU2eFf4Za5PgPnpzvb1Bnjj9DrS35f0zX9A+9i/t9Xs7yeZbP37nL7wB5/OPTMT82\nyeN62vaL1Kbgf266pp+YruPh+S8m2f0D0/sPqZV9/iuqMv/x6Tv+xMP7Afz91D6zP/voz+kxhIHa\nueQA/LkTYcjAzzw47v8D/rEH6/4N4K9Or/8ZaiHlcLJ97kt4+rB+gVq66Yuu8Qr4kyfv58HpH3yw\n318F/qMH6/4S8PPT6z8yCfZ7J9v/0HSu8+D0FVzO8nmWz6/S8lWXRx703zxZ/4vA//Vg3Y9MsvVF\nyvPfpipx+0X3gzopuAX+0cd+Rqrvtp/nH5PaO81TZy9/kdopfcaotYA1ACKyoM5s/hMR+fMn+znu\nO9z/FPDXVXU82f6ZPnWq+g/8Fq9Z+Wwfvp/ms62f/jfu+yv+JPC3tHZpmfF//hY//4x3h7N8nvFV\nwu9EeYRaV/nL4vcBf0VV8xfs8/uphd//Ea11gR8d71J5/k/AP0t1IX1bVcuD7YcH71fT35/lsz/u\n+SZ/L70Of7t4U4/Dh595eh3v4prO+P7jLJ9nfJXwu0Ue5+t+2ND7FA+/y5vwK1TX7s+KyH+nqvG7\nHfC28S4JQztV/TVV/c03CMJnoKqfAN8CfkxVf/XB8hvTbr8E/D4RCSeHPux1+P3GL1N7zZ3i7+G+\n19zfAH6PiLx3sv3vfsvXdMZvH2f5POOrhK+yPM6W6/fC7p49HF8/WfeQpPTXgb/vu7DFX1DjnT8G\n/KWvArP8q14k4eeAf11E/kWpveh+ZmKa/Zlp+1+kPoQ/LyI/LSJ/lNqa5jWIyP8oIv/8b+Hz30TF\n/neBPyUif1pqH7l/mRpAn3vN/QLwq8BfkNrL8++ldnJXzjP+3234Oc7yecZXBz/Hu5HH35jO88dE\n5LmILD9vR1XtqYS0f01Efkpqb+M/+2C3/xDYUJXi3znJ7Z8QkZ94cK5Zgf4U8F8+tgL9SitPrd3P\nfxb4J6mzk/+ZGiz/1Wn7juoH/xlqAvmfBf7VN5zqm8Dz7/Zx38s6Vf1vgX8J+Feoveb+aeBPqepf\nmbYXamB7SXWf/MfTdQmVUn7G7xKc5fOMrxLelTyq6reBf4vKqv2I2jP0i/BPAYEaD/33+Gw/2ldU\npbicrvmvTd/jM65ZVf142vdngP9c5LeV3/rbwrkw/DvANLv/X4EfV9Vfe+zrOeOMU5zl84wzvjzO\nyvMtQET+YWBLpY7/BLVb/EtV/YOPemFnnMFZPs844/uBd8m2/UHCGvh3gB+mBrp/gepGO+OMrwLO\n8nnGGb9NnC3PM84444wzzviS+EoThs4444wzzjjjq4iz8jzjjDPOOOOML4mz8jzjjDPOOOOML4mz\n8jzjjDPOOOOML4mz8jzjjDPOOOOML4m3kqoiIs+APwz8OueqJV+EFvhR4H9Q1ZePfC0/MDjL5/eE\ns2w+Es7y+T3h0eXzbeV5/mHgv3hL5/7diH+cWnfyjHeDs3x+7zjL5rvHWT6/dzyafL4t5fnrb+m8\n7xgyLWZ6Z9CpfragCAUD92sF1FiKbdCwwl1+Dfvk60hYQhFIBVJCtGC9g7Rn+8u/AL9r7tfvGPw6\nAN+w0JjpEStiFGMVEbDGYI1gRHDWIHZqHF+gFKAIwTkuViuerldcbNasli3eOUoujOPAYbdnv98z\nDCMxRsYxkZJSiqIqeB/YbDZcXFzQhIaSlP1tz8uPb3j18Q23Nwf6Q6JkBSyYuaOUcl8T/kHHp7nU\npyqoThIs1BKggoqpmwQggyuEVlishc1z4eK5JbTCYav80i9u7+/VGe8Svw7w4x+u6Fo8utXlAAAg\nAElEQVR3HIaMc4SmoetamjbgvMVaQcSAMSAWYxuaZsFidUFoFhgjaMnkIVKGkRwTghB8w2qzYb1e\n4hlgvMOUEcHUcU4MSS2HPtIPGSuWVWgIYojDwDAOFCcU74hSGEoiG4MJDZvLZ3zzmz/Bj/yeH6cL\nHeO+Z3tzy83NNdvtDqUAhfGwY7+9pe/3xFLYx5Hb/Z673Z40ZBgzKSZyylhrWW0uWF1swFo+efEp\nf/kv//zxXj0G3pby/FxXw+fV8RURTgs2qOpn1j3cfz5XKeW1fR++fog3nXM+Zt7/fp97BarTACUo\nhowVqYpQBEUpAsVYinGYsITVM+zTbyDthhIVSRkdRpwWbHAQb7/r/TrjraAHMNYhwYAFJYMtFKMo\nSpIEk9JRLUiZZEQm2chgVMiHhNoBmgRhiVdHipHdds/2bst+e6A/RHKCsc/EUUljQRVCaBgOkJKj\nCYmSlLvrHa8+veH2esvYZ8Ah1qAq3IvyaQOUNzSWkDq9q7pWj8qzqlzBGEtWBWPRkkmxEJMi1hCW\njuWFxfljF6yzbL579ACLxrFaBsRaVATrLG3bsFh2dF2LDx7nLKkUsipiPM61hHbBYrmgaTtUlRhH\nTCPIaNGY0FSw1nCxdDy5aNm0DUvb4RjRrKSsxGLpR8PV7YGbmz2aoMXgikJMUAret4TLNdkZBs1o\ncHTrDe998CE/9dO/l5/8yb+D9eKCYd9z8+qKTz/+hJcvP6U/7IjjnnF3y7gOHIY9u5zYl8IzhFQM\neZ8odyN3r264ubklozx7/h7Pv/41TAjYpn3tXj0G3np5vs9XSq/j4T7z6y86blaab1K8b/rs03Of\n7v9w+2evnTqTrytBFUXIKlhkEtwTRW4VLRkpCSkjJg9YDFoSQsJowaqQy6P3c/2BhvTVg6CmPmM1\noCLHZ6koiCDGoqLTswdygQylCPu+wG5guL7hqu2xYsgpM/Qj/WFg6EdyVHIScoSSDSUBCoPNlH6k\nv7vFOUdJhX7fs787MO5TNQ9N/VhjZBLBU0vzs78JnZXltPX4+zlO/RQoGAQt9XhNkEdI0ZCSAXWI\npLd348/43iB1oiPWghjEGIpCSoUxpqM3IZfCmArGGlQThZ6UC2a3radB6ZxnFVqMswz7A2ii5JGS\nBgqebB2KEHNmKIWYLUOxDMaQvEecIVpLjAPbvKfvR1rrWPSFbAp9ihQTiaOla/aMfUQLpJTZH3p2\n/UCclPx2v+Xu+gV5fwvjgSH13KWRvQjSLrB+gW0s5SA0rsEbR8mROCYOfU8wn29UvUu8deU5f8mH\nSuxNVuV3e/9lrciHivJeEX92vzddU+3eJKCZaoVUJ20dvgTEkrUKpygg9VyaM1IiMu6R/TVWC1IE\nyQVbClIUokHj/otv3hlvF3tFkoJRVKqsWDM9X5Gqn6wBo1h7VEdoqSIhBcrBsMvKgRFDxIgh50LJ\nihZBU6ivVaBUBShMcpaFfSz0d4eq7FQpOaNFAD95Ys0ktw/lXE/+vvl3cToBPcq4mY+pMltUKamg\n2VCygRJQNYg8/uD0gw5jLNb66pI1AiIUhWEcKVrQooQCKRdSUYydxqRS2O13FFWsNTTes7h4wqJr\ncWKRXBjHiIhQxDDiAEfWQl8ifYJcHFkCQzBwYbDGYp2hjAcywgFQ1yLqiX3i9q4npkhoR4wsuP7G\nNdu7LSkqV9fXXF/fsN8f2A891zfXvPz4I7S/oyERNbIdB/bG4MXQmgYvnuA9i6ZjbHtMsmgp9IcD\nsSjjMDz243l3lid81qo7tQxPldjDfd+07k2K9NSVa4yZD6JMx35GmfL6kPRGty+KmQYv1TJFN819\n5EkMRkA1V6UsWkfW1KOHG/Q2kPstBovRenQpCmJI4/ZL3Mkzvu8YJ0WIgpEpDji56SdZEicYIzAp\n11IKonJcSiqUpJAzFJ0MQ0GwVR7UMPlRJ9TPMSL1OCAN8TijE5EpbmmPOrHK4qmkzhlms+K8V6Cf\nnZTKZEFPl6FlmhdMn1NqbLQkRbMlJ4uhwZnx+3ijz/itQKybYpmVYaEKOWVSVnLOaIGcFBVDLmB9\noehIQRnjSKEQvMPLCi11yq9Fq+OkwJgKfSzkUQBHVKEfHWNSVD0qAWxAXcB4RwkCeUHjDItugQWK\nGg77W+7uIof9Hh8i3l/xnW9/zLMPvsXm4gl9H9kPA7fbLa+urrm6vuL27hob94iDrJmcRtR6SoqI\nKl0IdBeBlWsJwbPrdyQHWQtxOLDbPf7Y+U66qjz8Qc+KTUQwxry2Pef8uZbg553vodI0xmBO1uWS\nSCmh+oa4KvfD0kOLdbYGqgUKInVArN6SiXgx/ZvsiXqikiEOlN0tMRfEeoxUAkqazp0VUjyHkx4T\nJVXrUZmszNl3e/QyVKWjRqtXAWXWYzI9e4DKIpq8DzrHyGeCGdPkShExR5lDtcbKtRzPLWI4TuuO\n1ubrivB+3anleY83eltkvqLJPY2eXJNCKWgRShTIASkNzr4hlnrGu4WZlWadtBVVlDr5oSgl94xD\nxjqPWEfRBDaTSyamEURpvMMag6DEmEhZGGJmiApRYASMYYhCxDImSylVmTrrEWlwrkG8xzeGxi+4\nvFxzkUbSoedwc8fddmCIcDhkhqHgX97yN3/jN3GLBV//oR9mtbokZeXq9pbvfPIRd7dXDLGnlQLO\nYUVorCDi8NbT2UrEe9JeYLOw2225296yHfbcDXte3d6yv7155IfzDt22p1bmvDjnjgoUarzQWjsp\nOj3GNB+ea8ZDi3VWnNZanHOVMIGSi2CtULKSUr6P9UCNb01xonlgmwc5JgX6eizWUNATS+GU1VhP\nKmZy+aZIGXrERFQLWXMdTid3SdHCGY8HVZAyxxJBjEHUvObWnxVOFZlJMZX6DFUrQ1cmxXsfH59c\n+TJNqyY2L5pr7PLEm8G0X1XW0+cc5fqh7D20NI/Tvjd+PxGhaJkUfb1+M8WLdCK5qeY5jI9moYym\nKk8J38c7fcZvDVV5plIoZfZ61Th9LGVixio+GJy3U1xbySUDigG8tTTeE1xAsBSErNXKtASkBGJ0\nbEdDX4SCQDF4ZwhiaZtAWCzouoaus6w6x3rZ4g30d1teffQJ+12PCS+Jegcpc7vd8e2PPkIbR8bw\n4YeOGBMvXr3io48/JvY3BEm41tEuO5y1+KxEsbhmxaJb8OzygveffEDrGob+wO3dNS+vXiIvP+X2\n7ppxePyQ1zvr53mqREUEay3ee5xzVdEZQyllovRXav9DV+58/EM38GlsZ1bG1hq8t1WBTgouxkSK\nmTGmSoEuOg2E87lOY6JmenE/uE70kkm5lqowVScebjlankUFrMM0S2y7rscOB8qYSHmolkC3QNx5\ngHpUzF7W+bkXqGtOXaBVNoxInfmXWSbqkWVyxTOv594q1ToUHa1VnV4L97Sf46VMcfWqo2ftPVm6\nb4xvnirQ1+OeD38fp7+gMl1nnrYVBKb4WewLcV+Q6PDN2fJ8bJRSGFMiH8NFUyheqLyJUqZHnzEW\nKGBsZeWKFrw1eGdpfGDRLbnYPKUUSypb8mHENGukuWAslkMs7MeqeI0IrVeCq2zf959fcLFasGwd\nq9ZzsV7SOEO/P7AOgTT0vHr5grvdDf1hz37c8/LqFaYNNN0a4xaklPjok0/45MWnOD3wZO1pu5bL\nZ89Ydl11RReD9R3dcsN7z5/z/nvvs1gsKSVxe3NB+LZlGHe8eunexDF/53gUt+2sPJ1ztG2Lcw5r\nLapKSgnvPYfDAYCU7ll/D+OWDy3P2XI9um6N4L3F2urGLVkZx4gbRvYcIGVy1qPDtbpqZxtyYs8e\nXbaT1J66cSmYaYYnszvOGNQ4sA22u8Cvn9c4g1yjRSk5AQXjG+xiQfz07d77Mz4fIhOVldmym7dM\nE6opzlnV06zQarxSdXa1zu7ZSVGVe2UmwusTvNeU2b0bdz7xzFE67nGU8dOr1s95PX8n+czr1yag\nx9/iHNaYY2GQYyYPCsnh2+a738Az3irKFNvM0wTNWHMvQ1plTdDJo1YIzmGMxXkLIgRnWbQti7Zj\ntdhwefGEXBx9cozS45drTLvCDgXygTxEUk5YgVIMrhVWXnl/7Xn+ZMGyCSybwGa5IDhH7DoaUXZ3\n13z00QWvbl7Q556YE7u+J1zf8erVDd3ympQT19fX3N3d0fmEriy+7bh4+ozL9QUlKTkp1gbaxYpn\nTy55+vwJ680GMcJy3THEPa9efcJq0bJo/eM+HN5xqsrnxSmPblZjjtbovL3ve3LOlPJZF+dDRXo6\nlswDRNGajyfW4p3FuoCxnlSUXHoo6Tg43g8q5vUBZ96mcGqVTN7f6oKTaoVUNq7F2BYTlrjFJSVn\nyhgppqfIiJLxzQLbLb6Pd/qML4vTOCScyBFMLrB7pTg/99ntidyvQ09ioZP7dZaX2fV6DIfCMURQ\nyTvz5z9UmHq8jlOcKuR5kjcTme73mSZ+pbz2/uhBUY7pOMdzIJSo5DFj1eLN2Svy2IgpY9MU3jFT\nDB6AMk3Wa4GPeRKnFIxxGCt4G+iawKpbsmqXLNuWtmlJxRCCpwkZ7xzWGkaJhDQS4gGbM0YUUiZJ\nj1wEwrimy55FgVYtPlfrNBhYtoHVsmOxXNIsVoQ+MvQjBUdWR86VlHfPWVPiOLA/GFJWXLOiXT2h\nxEIaEmIs1je4JhAWLc16Bd6xoNB0HS54FsuOi8vl4z2YCe88VeVNinR+ba0lhID3/jggzIrzi3Iz\nZ1T6dn1SqkrKeRK3KmTBWkLrUWNpc6GoUPZ7cs6vnff1QW02TvQ4+ByJH5P7Ns+xKTGoGhCHikds\ng7gOYxXCAfwBTQmxCn6BbR5fAH7Q8ZCZCvPz/pz85GkCdVRtOmlIfbNMvia3wskkTz6z/5tY6fM5\n7v++yXX7+d/p864JPZkWiKmKvihSBCuWcA4pPDpSKZRcau5xqfFPmMILQq2AZS1ihUKmpjUpVgze\nOdrQsPB1CdZhJmKbIeNtoXWFxhUKkUPeQznUzISSSeOBki3xypIuAuoLpjzBABkozoEVpEScgPee\nplngfCSXiLUWkQZr63juMSy7hq4JHHZ3bHd7doeRMRuienLJjLlMRKjCqFCMAe9QLKZpIXhMcHTr\nls3l6vEezIR3FvMEXhuMZvfqbGWWKSg+u1ydc4QQSClV3/9YqfOnBKOZVDS/tqbGUa11WGeO1mFM\nuVbo0FqPxTlH23XknIlxPCrPWXFWTNMl7q2HOb50tCYmiyHPAa16FogZbMKmjMsZYy0mNNhuQZGC\niOLaBWIe3/Xwg4zJSDwSZmAODRy9ucd1MFmMJ5afzutei0vO57xPJzkyd6lkI5HXldqb8p/fxDQ/\ntSTvt+nnnuPh69PfzXF/qcU7UMGIxYgjuI7mPLF7dNRnZLBiQExNf2KKf1b3AcbOKU2FopmSEyUD\nxUBWNBXSMNDvtiCGqEqKB5yBVQOrhcEMSi8D1kR0ktshK5J60s0rtp8Y9l64aFqa9YbgPcUYCpmc\nEjlGSsyUmMmxkGINj1k3MsYIKN5bukVLu2gZx8CYIre7gRdXWwotaUzEMWK9ZaWwipFRFZ3ynI3z\nhG5Bt17Tbhe45p2qrjfineZ5AsfUlFlBWmux1lJKmeKb98qpzmaaStiYfvj1+DoYzZbprESdrbUf\n27bFWFPjBaVarnGMGFMtxeADbdcASi6JnBMp5deu+zWCEzWmWd/Xwgi1XNq9Ar0f9DIQ0XFg7HfY\nwxbbNGAUt2gRX+0W40LNDTzj0fF6SPD+mZ5an3OMc2Zqnxzw2nGz1XpvFcqDcz08XD73/Rd5ah4S\n5x6S5h4ef3rOeb0RIU1sWxCs9TRhQddu6NqLL3EHz3gbEDHTeGcxpi4IlU0rirG16pCxglIoJREj\ndXIuMGLYs8NEJaaI39+hxpByIYSGdXvJ03XADIY7X2DI+DYgxjJYJY09ud9z/cnHbNqGr33wIYtl\nx2KzJmHY7XfEfuSw3TPsdgy7PeN+z6Efa8nAEtnunhDTSNM2hCZU12vfMvTK7b7nb33rO7y82hKH\nSNHCYrngWc6snz/nMCbGXAi2VlpaLtdcPHnKq+sXpPz4mQrvnDD00KVUFdq9Isw5HxWlc46u6wgh\nvE68mHDq1p0VbNM0hBAoJZNSYhwLRatVm8Za3sB1DevVGvPkgovNkt1uxzgO5Jyqm2Sa2ZlKw6XO\n+QxiHIqpaSYIKRdKzuQ4UFKaFDUU8RQneBPxusei4JVsBesCQs39K8M5z/MxUZnWnx9OgBrjvI8n\nfl7e8cyinZSlzrm/p9bfSVm9OZ3FyFHHCg8VXGXGziz016/J3CtFkWMCfP1tyGsK8vi66JHtO0/2\nSrn3mBhjcN7RLjradkEILWc8LurTNFixiNQqP4oiVqrcWsFaw8SZvo+HazkSG3OOxDTAXhnKgHE1\nVz04pfGFdWsYG6ExmYGIKQ5jhMYZggmUPtIfDgz9AdWM84bQeKQIJWf2uwOHux3pcEDyQDCREgp9\njFhjgJGcD+QCYhUTHOIDeRi5ut1S8rfx1tMPIyLC6mJDnxPLyyc8e/+W9foSv1khYmi7jsVyQ9Mu\nEPP4fNt3FvM8fT+7aHOuqSl2SshWrekk1ep0BB9YLlc0TVMZs9NAUpVsmpRsrUVaSqXb13SCQowD\nQ6+1nugkREUzxls2y47f842vc3FxgWohxpFxHBjH4ZhjqlP7DIPgxGDEglhUHMVYUqnu4DgcGA97\nxn5PHHpSjMQMSRzqHdpEklEiECkkpnJoY0++u/3sDTvj3WGKP85lGF8n55yycKvH4jOxyLoDnFh7\nZWZdHz/izfF9cyyYMP17TYGXIxlt3uf02l5T9K/FZavVUcrsMamKelacx/9E6iSxlt6qVosqrrG4\nVnDNaRH6Mx4TVQEmrDqUDJPnToyZqvZN9W+5j3WGEGoB+bZlEVqWTYtrAhIseTIqVEfQiEjCmNrl\nZBgODNsdYhxN29K1Db5r6bwhNA0ihRwPxGHPmGB3u2V7taXf7TEa2SyEtmlQAwlBnOdyY9Cyoz+M\nDOO+FnDIhT4m+n5gOAxoTPTDCAiLqxV9PxCaBRebJ6wWaxZtSxsc1jisDTTtisXi8T0j79RxfJpa\nUpXmgEzB5qoY9cTyFEIT2GzWbDYb2rY9xkbHsSq7mWAENQdvHAeGYWC/36MlkQScAYxiFIwUOi88\nu1jxzW98yIc/9CHd5L5NKTIMPSmnOtjo1G5MwGAw4qrlaRwZW+srjiNjf+CwvSUetvT7LXEY6MeR\nISl9Fg7ZsEvKNmX6bIipKvQUB4jnEmiPClXEmCMBA+6drK/vpsctM9nmlEj0GRY5n3Wtvun1bHm+\nrlzL0ZQ9Zf4+vKiH1zS7hO9/YydfZrqmog+6D1mpZZsRQmcIS+g2BtMksj5+7dAfdJSsUObJTQal\ntsyzhpm+LdV5grXVMvXO4Z2jaRq6rmPZdaymDiw4w5Aih10k55GUelLqUTLGGWJOvLq+IRflYnNB\n0zynbRraNmC9px/2XF99Sj9ExmS4+vSam1c3DPsDThKXa0PoWtpFQK1FxRO6QLA947gnxz05j8Q0\nMgwDse/Zp0SJI0M/kAuEuwXjmOi6Fc+fvs/zp89579lTGu9qJckCjV+wWT997MfzbpUnMCnATM4w\njiP3uZ3uOIN3zhIaT2gC3aKl61ratq2lQydSkfceobLNSinkOJJSIo5jdaHGEc0RS8F5iwl1drYM\njstFw/uXG374vacsF111g1BqgrAR7EThlsmdJmKmZVKeakilTgCq5bkjDvv6ehwZYmE3Jq53Ay/v\nBq72kav9wHbIxKSUWCi7gYP3XL/4lXf9CM6YUMlpFuPt5Pov9wQ0Ttyw9zknlWBzageeWJ33rNrp\nOKkVYI4Kd3bOFpn6LOqUvnLf7A6qMrdSJ4Rztar7UoB6onDn66qVgmZaE2JqG6tjOcqT+LwRxNRk\nemMUYy0uWFYXnqcfeJaXBQkH+vHc8efRMT1nM7nmyxQ2qLnlQlGhVhkSxJoqqbmQYmLoBwZryY2v\nLEkDWRMxHhjGPUmEod+R0gHvDevVgrYNxLHn7m6HEWXReYwuMBRe3VyjfzNxfX1F212g2nJzO3B7\nfcvQ9xhNLFvl8onn4rLBeouqB2sokrnbj2z1gKQ9xJ6SevJ4II4jeRwZx1hDXgq77Za721uuXl1z\nd7sljrVDSxwT4xBpmgVPn7z32E/n3ed5zuSEGqscSCninCPnUPOPmkAIlrYNteGrm6r5a3XzppSp\nI06Ni1ZB6dnv9/T9gWEYSHEkxRFD9dE33tN6hxFhuex4tl7ydNFy2QQa7xAD1vraL2/RslwtCG1T\nk5KnARMElSqFRauVXHKmpJGcR0qO5JKIubBPys0h8fGrHd96sWV5s2e5G9gPkZJAY4Z+4Haz5P/9\npf/9bT+CMz4HAoQmTBOwzDCO1UU7VW45ujq1kjfmmGGtcTxbkfVcxw48U97dUalOrmEj5iSjkiPr\nVrX2gdV5HbWbhmpV7kXzFCBn/qBjIYaaP5rRU4tSQCwYo6+Vf1QRsIL1BucF56FpLU0ndCvL5rLl\n6fuO9VPF+D377Wdju2e8W6hmBH8kqeUYJ9kotf6sKDkLITicM5SUGUpl3JITFmXZBVJJUJRUMsN4\noO93eCMMw5Y49gTXcXm55vJiQ3CWHAf67R37roGciONA32959QKaEGi7Jzi3IhbPoS/EsbqAG1+4\nXArvX9bqbqoGFSEpuAJ3ZsTnAybtYdxTxh7NtUWRMGVaoIgqw6Fnv9+y3+0ZhkhKif7Q0/c9zno2\nmyeP/HTetvI8DiTcu8UexHZyLsydHpwVwOGDJQRHCO6oODUncirEmKFAyTX2mWJkHAcOhz3jOKCl\n1o/1tloVjfeslwvWi5bgHMuu472LDesmEFBMqnVnixHEW0zjaK1l2U5xAmtr1SCZFbatyrtMA6bm\nOoAJFIF9KlztI+NNjy97mrxm04wsckamxeYI48h3mnPPxMeECxbnDdZZxrFgjEwVpypmog1wb/lJ\nZTa+HhSsaU3HxgBM1YKm8nrVjVvJHzUkUMlCs+WpzClXs4VYt2dKFTkpYKpCFwxSaoJ8jXc5jBOa\nxtMtOoL3tZ/o0NPHgTEn1CjOGXxwhMYRgsE30LSwWBrapWF9Ebh8GlivLSEU9pwtz8eGZiWnjJFa\nUGBm85s89ZydGxYUX8NM01w/29parg2ujq3W1HE0Vxl3TrCAlkhOPY1rWbQNF+sVl+sl/faOJjik\nVA9er0p/qG0WjTF4t8OHDZgF2AZlAArBCcvWsukMjYOSEmItSSGHwkIiLveYcQ/DnjIMqE4lI2fe\ngRZSHBmGnt3dlu32jsNhz9AvpnBdxPvAfSrY4+HtKs857jJhrrRyXwGlFqqudzBTSq6BbyM4Z+rA\nZg1aMkUL45CIsSrRNEZSTMQ4VsZrjtU74SzWOpzxONPRNZanF2su12sWbcNmueaD589ovaPEkTJO\n7tc0ogLDfo+USjrqlktcE8BZikyUcUDUzHJbLRIjqKtKNuXI9aHnO9c9H98mbqPHtR3Plw2XQegY\ncfkA44FlevFWb/8ZXwzfWFyQ6Yc75fXOsUOEuWg6x0YBcIx7zjnApdY0lsktC/dxzzkHdFartUZp\nPUe1JKsFqVPqAVLnZXNDbiVXp4et762xOAQvFm883lh8G2iXLU+fPeXrX3ufVddxdXXNRx9/xM3u\nin3aIjbTLjyLZfXmhGDxAXxTCI0SWqHrHKuFZ9EFWu+w/jyxe2zUFDqDYEg5T0QwpgIENc0O0UpS\nHO3kioe2DQTvMFMeaPCepg3YkhApGDJWC84KmiOaI05aNl3Lh++9R5i4JdZZFCHFVCeMWpdh2CMH\nRWzCNR3WJZpQJ2iNMTRi8KqUkjDG4Y2ysEIjhVDGqjgPW3IfKZharEZlctykqjz7PbvdHdu7G7a3\nN6wWTSV05kRMidvbxydbvnXLE319Bn8sC6ZVccqRTl8rZtwvTF1RCrnUxN+UEnEYSTExDiNxUqDW\nUB9caAmz1eqEtjGsuoanl2ueXFxwsVyyXqy4WC/pmgZKIcXI0Pcc+gMpJ9IYESClyHLdE7oWvK+W\nqTgsFqOWKtLT97GCNJ7kPLs+cnV74MX1lle3mUPybJYtq27J87VjJQM+CWWET1fn+qGPCRsMKoWc\nCqVM3XZmJXjsRqLUmiqnpJ/T/MkyO2LrorMCneuQTvsbQedtcK+A51QZUz/LOFApiKnNjY21Vbab\nQOM9nQu01uNxBOvpVkuWlxu+/uHX+JFvfIP1ouNb3/o21hf8VWKfMxIiq41nvelogsc6g/OKdQXr\nMtYq3hm6YAgerNNKtDvjUaGqtQCBVvLQkYHtyuSyTSi10Ev0FucsztWatmh1g8qknBCDq756jFbl\n6Z2thkmMiDo67/ng6RM6axhiJMZIHzNDqkTOufXFOCqpDBQBmxIhFJxJSLEYHKY4KIk8ViMEW9BU\nkJRrbntKaIykYaT6CS2KwTghkyfy5oHd7oab65e8fPkJ3sP1zTV321vGIfLi008e9dnAu7A8ecAm\nLPqaAhUBZ0xtS2MNzk5+72lGXlLCWofmap0yrdOc0ZywogTvWC07VssFi0VD23q6ts6iN5slTzdr\nLjcbNssli7al8R4nNU9JUVx2hBIwucYTdndbSskcDgdC14F3FFOzPWvGp8HoffcWGyyua5CmJcaM\n5Iin4Kklp0p0DOPItodIxsRCGTPXh/Ps/jGRKcRUyEOpTYWzIGprb06Z2lQwd05RyHOcco4lTrFw\nFVQtx0DplENZ46RlImwUxAIPJokYQU0lBmEUY0GMYu2UrtU0rBYLVl3HxXLFpluw8AFJ1QPSLpds\nnj3j+Qfv80Nf/xreOfrDlo8/bei1oZEG2wnrjWW5AmsVNE+fUzBGESlYU0BGlAFVS9YzE/yxkVMm\naU0pKqWmIFlrq7fDTiS1Mrv8S+2kMuWRu6lI/DBG7u62ZM2E1tfUO+dxWrDGgkxUTy4AACAASURB\nVCo5ZsgRU2AZGtx6TRxHhhjZj4ndkBliYoyJmGrefMrKIR3I/Z5FZwjGUPIKSoPokqIjY4KShETh\nbhs5DEpKhpyFmCDFQipKoSDGYlRw3lJyJI09+90tr64+4dvf+Q3GuOP25pZPPvmU/jDw0cffftRn\nA++IMDRDpxw40amYuirOWoJztCHQNg3eVquOomjO5BRrk+GsSMmIZmSKNToD1hiWi4Ynl2ueXG5Y\nrRaslh3LVcd62bJZr7jcrFmvlnRtR5iar2pOpGFAhWPXAomRlCLbuzv2+z1he4dvG8S7Sr3GUE0E\nQVQwMrmXG0+zaHGLjhGDxEhnIksbySgShf3OIjlgSkJTj44DV7tzXOkxkUohxVwVZxQMDtFqTc6e\nVWVivAKV+VP/YKrXwWCg3Ec7X6tAZCoTElcQr1hP9Yz42qTAWYv1pnZvsUzEtep1aYInhIblYsnF\ncsXTzYZnmzWXiwWd88QhMvQR13Qsnzzl8ukFm1VLKQXvDU1j6LKlaQJuoSzXQtsqoqkW95gmBLnM\nfKRMKgOS6ncY0lk2Hx1aO6aoQk4FVCr3Qs0xx1hnRvZEIjNS+xnbqYhA3w9V2ZXMWlY0YYqVi8WI\nRVTQktBokCy0zhLaluQsY3Q4VxBT80FLHklkIFFIHIYDfRyISeh8xzAsiaNlGD0pCze7mnkwpJ6b\n7YGbXaaPhqS+Fo0vNZZbVLGWOqGbFERMPbvdDS9ffMy3vrVgu73h7vaOly9eMY6RTz75+PGey4R3\n1wx7WmalqUp1t5qpiHHTELzHWz8py4LGjJKotd5lsjwLlIQTRU0djFZdw5OLJe8/v+Tpk0s2F0vW\nqyXL5YLVasF6uaLrWoLzmMlFrDkx9j0ZZRgG+nFgt90yHHpyjhgjhLYhdA228xjvKCLkqXVOTpW4\nJFZx3hEWgbDskNAwqsOpZR0Eh0ElEdgjcZxo5rmmB3Rnt+1jIouSZSIrqDlO7o7xzSmJrkhBphQP\nMXKs7FI5CwVkblNWz1utTgFyTZNytSFB1wVWq45FGwjO1omiq4Sl2v6M6oFxjkXT0oSWZbfgcrXm\ncrXgctGxbCymFG5ubrnKPWPesd2Bmgw6Ihj6wx1oJHgheTOxMQvWCFnzMaY/Za7Uai2iZB3QPDLm\nyHDWnY8OmTr45FInO1Nb4mpp5vvwQCULyeQtqX67VJRDPzKmRBgdvvGsAWsdaIJSavzT1DHKqCBU\n3kYWGKmETCNlYorX7aUUhjGxGwa2+z19GlAsu4Nltx+52SacjxyGGrraHUb6MbHrR+52PbtBGZJQ\ncKjxlBQx1mK9J7RtHUsbD6IMw4Gb21d88nHHdnvL7fUd11c35Jy5u7t51GcD78LyPPk7z5aM1GZP\n80DRtQ3LrsNP6SSiVLdsSpTJWaoFyAWjBVcnX4gR2mBZdp6LVcezJ2vef/+SZ08vWa1XtG1L13a0\nbTvlhTIJmkHwIOD6A5nCdrfn5cuX9NsdogXnHU3jaRaBEFts58nAOMZKXBpqQ+2iGXHgGkezbAiL\nFb5bYv2KpV3SLRqKphqDKAZvDI03LBpPf3FuSfaoMGCDJcXJ3ZrL7HWtDNeT2KMYsL4yVo2b8iTd\n5AaVqphOu5Mg1EHBGprGs1x0bFZLnmzWbJZLGudw1lTlOuUUI4KznmWzomsWNL6lCYF117JZBDoH\nJvfs97fclp794Yqr/cAojqZdcXv5nK5p2e9uUK0TQCsWSiZHJcoUwc2lKvhKdToOzCkPtbh4SWx7\n+cJbd8bbh7UWo6U2tpjD6VpqtgEANQQ2tyEzzmOcJ6vQDxFlj3OGmDybtK5WqTG17myOaGmql8NZ\nvPOYbCixMEipxVxKZoyRYYjEmMmlEFOtBnR3t2XXHxhLRIxj1weudwMvbg+MarnZ7vj2J6+42+0Y\nxuryTUXph0hUixqPuFyDYMYQ2oama6unxFuME1KJ7HZbXrx8QbftuL29Y3u7xTpL/goUmHknbtt5\nNi9SCUKGmi/UhMCia1kuFnRtOzFrK6NLc6mxTYSC1NlPqX59ZwCpiebBGYITGi803rDsPOtVy3q1\noGlavA9YV79mKrULQK11mxn7nsM4MMZIP/TsdzsO2y3kjLOW2DjG2OLjAdN7MkLMhbFPxDGTYiKX\nWnTPeiFsPc3ijm55QbuMhDZh/QorAdRgxBDE0RpPZw2tPefSPSZcW13vwTrKqJC0uuOtYNxUDs1W\nl6r1ldDgvOCCmdjgljY4vK2dL8zkpq1syLmEWvWsLELHZrXi2eaC9WJB6z1+IgM5ZzHWVWZkWLDs\nNiy6Nc4GnDEsWseqNZhyYH/3KbvtwL6/4WZ3xau7A1E8K4XN+oKl6Wia+rsqcWCQsXa+SAB5ipUZ\nRApzWUAjhqyFmJWUlX4YudmdZfOxIbbmv80WKDAV6JgKJ1DHV2MNPnis94itLbzGlCkCQQ3GQoq1\n0XWKMMYRk0Zy204TtlrL1uOhEWxv6MeBMWd2+z23255+VGKuxkM/7DkMB4ZxIFLwyTAWGLNhNypl\nH3lxs+ejV1uurm/oh4FcSuWuIKQiGBdwodRUQAF/LBzf4oOdWLUjh8OB/tBDFkoqeOdZLBq8+wGo\nbTtbm0e3rTE1xtnWeOR6taJtAs65Y45PLUCQKNmgYhDrquUGOKmNrUGwVnAGhEJOIzH25DSgJYIm\nVCtza4yRNOWFxjTSDz19fyAOA3msirNomZLXC6kfiKrk6BlTgoOheFvb8BRDKUJJte9cLgWlIKYq\n1fFQ6LeZtkuEbiA0Iz4s8L7B+1Bn/gZGMv1h/7Zv/xlfgLaDpnOYAmlIlLE2+XW+FuYQF1BTMFaw\nXsCWykwNNU6/bBesmzWrsMKJO8bw266baP6V9GHF4sXThYZVu2DVtLQ+EJw7Kk/fNDTtgm65Ybl6\nQrNYVzecZtogdI2Shit2+5fsxgNXuxtebW/YxkyzbFldXPDs/fd57+Ipu+0t2IzcFfJQi3ekGFGt\ndZqtBessM+E3qRKTMEbPYRDu9pnru7Pf9tEhTHmZthKHpsyFuYCVtbamMHmHCwHnPcY5xFqyKjLV\n+hYj5Jw47HdosqRhjy2ZsUtTr2RwFjrv8L7mt9/se/oUudlueXl1Rz9mjPUMqTDGnlxq4YIkSlah\niCMbRzaBsRh2Y+Z233N1t6Pve1Spcu49RbWWVRVhTGP9Lt4izuKCwweHxkLsR1JOVWl2gXbdYo1w\neblmPxwe++m8XeVppjw3O7UQE8A7S9e2rFdLLjcbLjZrnDOT4oyIGrLUoLaUMjv5EVOp/3Yqhixi\nMRNzseRUk2p3W+5uO9omkHPB+QNFZXIbxKlCTGEYe/p+T8kZb6pF631gsejIh579YSAOA0OsPeai\nNURryGJBHIjD6FwWZg7aK6nPjPuM8Zldo9iQ8Z3iO6VZQGgNTRSCLwRTeHGzfZu3/4zvguXKsrz0\nWAxpFEqsRIym8dOP2aAGrJfawFwSRgqND6y7NU8WT3hv9TUumqdYNeSUsNbQTR3vS6E2ZM+CKeDE\n0VhPYx2Ns5PytFN/2SXLzQWLzRMWm6eEboWKkPOI9wXvRvYykp1nEEOyFkLNybx49pznH3yND77+\nIc8vnrC760gMRHp2acdhPFAK5Fxd0N5bjAhFC3Es9IPSD4XDoBxGYXuA7fbcLu+xMZOBrK0VzeZU\nJ+ss1k55kVNOvHXm2KKsTPnKueTKYrWGlBO73Z7hoMR+j0dZtUvGdUaDYn0ttNEuFuASrrkh5cL2\ncOD65pYhJULTosZSNE7lIDNahJSrAh0z7IZInxLbw8Buf2Df9/T9gJaC955cCj4EnHVkLRi1lKkx\nQZ7y+csU540pYo0j5+ol8c6z6BqePrmg7R+/WftbVZ5zjYSZiOGco2taNqslTy8vuLy8YLXqEArj\n2COTOyKn6lqyYnDGTIUJTs96f/L5Rh8OPXd3Wz6xhmGIhOYaVUM/Zrb7A2NMhDbQdQ0+1LSY4OtM\nyHshAA3gUkb3PeXQMx4G8jDSA4N1JFO7qogYLAYriqVgp/JSIkoRQ7ZK8YbcOOhaSjsg+wbTpPpZ\nDjqTuH7x+LOnH2SsNw0XT1ugkFMt9ehsdbM6b9GpM4D4mn9JERzCZXfBh0++wdcvv8F7mw/ZNBsk\nK0N/mLr9MLmjHJjaYNpikALkjFHFGoOfetl6H+gWK5brpyyPynMJ1pDziDJSyhZ1HbQb2ov3efpB\nxiyeo67h8ukHvPfe13n23nss2haxicvxgrv+lnB3hWbDoU8Ynwitx5o6+z/slNubzNXLge0ukRTU\nGoZS6MfH75f4g45aea2mQNXWeFWROmfqe80gBVUzFfrI6FTvFmZlW+P5KWV2+54SR/Z3t3hgYRc8\n654QQ0E6iwsNoWmJJFzTYLwnZ2V/ODDEjA0B7zzOW8TWdMKcapW3/e7AlbtlHEZElKvra7a7HcMw\nklI8EptyKdicKVKmlpFj7fQSR3LyoAXv7eQtSSST2O13OOtpQwBdcOhDLQn4yHjLbtta27MWM660\nfm8di67GJNerluUiUEo8Fh3AW0quKSFa5viRqdVXyn0ZM50T0tUwxsRhGOF6S9+PvHx1SynCOBb2\n/cjt3Y6sysWTDV/72nOePr3kyeWKRdexbBuCCKZpWFqHHUbizR3jdseYcl0QoiuMYkgSAcGK4ERp\nBByK0ZrekMUxWMfBKfuh0I+ZoS/EQ0ZdwlilMYWNHclX536ej4nlMrBc+9pqKRtKcRhhSiMxNS3F\nAK5Ut22CUBzvLZ/wo89/lG9+7ad4tn6P/5+9N2uO5UqudL89xZSZwJlIlqpUart9//9vutZqlUTy\nDBgyMyL26PfBd+JQ1tZ6Y6FMxKaB4ADAcJCB8HD3tb41+YmWM9v1zL6v5JxpxuCGmWFcCMOEtw6p\nGmFXU9I1RLcUhGFiXE6M85FhOujHD2PPXvSkYkhxJxOw4x3HD//En4cjn3LFDyOH0zuWw4lxHGlS\nESe40WK9diwpFVKqmNbIGUqxpL3x8KXy68+Rzz9vPD8nTLAMi0MGyOlt5/nap93udwbdn/ciqoEG\n2l0KDSggrt8f1UdlLFij665aa5++NeK2sT6dCQL3w5XrXaTcgbUjPkwYHyBLz8vU4OyU1G+KMViv\nYh7X/ci0Stoj5+cLJWUenUWksO4r67YqAa41rBFa0wKac0bQVKptXalVVem1ZEpJLw8HxhlSSpwv\nZ3LKTONASjPDULmxul7z/O6dp1rjbskkHcvXmbStZBCPM8I0KCFIA6ihVUMuvUAaq/tKUQVkbX1U\n2gxUKM1RWmPbsxbZ2oixsG6JbUvsKTHOE9Y7Pn36wBAGjovaWeZBDcO2VHwpxHnisMxs00RLhVZ3\npIGtSpppLVMAcYDThI0A6g8USxRYreHaHFczsdeFLQ+UBtiMMzuzydhQYHvrPF/zhAGGQffwtYI0\nHYcFZ3FOcL6DBJzgnYAzjC3wfj7w6fSJj8cfOAxH5S53GLcVwVuH9Zo7OC4nxnHGOU8tmWgd0ay0\nWjAWfAgM08AwD4TZ4waHWKFK6U2D0LofU4wnTEeO0hjmBakV6z0uDIgVtnhh2y5czt94+PYLXx4+\n8/j8wLZtlCZ444irRXLj/BT5/MvGl193Hr8W4g64StoFO/02APztvNZRO5HpMPibstZijHZ93nXL\ncQddAF0EppMNa3WfWWslpUITw7ZlrpfEIIZ9LaQoSHOqyRhGjHWU2thjZtv76qoJrdtfXKvUprg+\ngxZFaY20J3JUTngpkVwjuWb9vYDvIjqjdpnWGrUUTYtplZwa0qqOg5uq1J04/Tp7ZvMD0zgg7cjd\nUSlZr33+DoKh75FNtVV92th3LhfHGAzBNQ6HgWke+xjVIw1K0QKYS6M1RULVJrpAFnkpoGCwrXXy\nRdSnrJi4Xjcul42cK9Y5PjqVY58OR97f3/P+/p67w0ywQE5Ia1RDt87MHJaFlgqmCiEVCgZfC1Ya\n0YiOuMRqITW2f0+GbCxXcayMrGZiMzOZQfe1ZcfLTpCN0Bo1vwmGXvMoWQdVgBsHTklX3oH3gvcV\n7wRnBG90pRCs5WA9ox2w4tjWjX17eglDR8APE8EPjOPENM6Ece43PUPxQSkxUgAFvpsADI3mCoWt\nE1881nmMMZp/mPYXxeI4zYRgaFVHXqlsrHHn6XLm4emBx29f+PL1Zz5//syvX78QU2acJowE1id4\niDuPXze+/Hrl/JQp2dKKRbIgpeFyh9+/nVc9L3aiWyxZd1sq8q7rP7yKhoyR/qbeTeeMTk/Qe2bF\nUKshxkouBieGlg0Ug7eBcZwJYVSby554vlx5fD6zp9LpBQqTSbkLhXJ+4ZDX1ogxUpuQc6KURG2J\nRn5RBjunpUZE8F7v3bc/X0c+KCKzWsQJxqllMedEThVpF5Z5Jjhh3w8Mw989TfP/OL//2JbON2iC\n6QKKddsYvGGZHMclEMzE/eHI4TARvKUJxJhY151cGikXjNEM0NYgi14kt/yL2rQbrVXIpRJjYY/q\nLbLGsiwz7+7v+PThPR/fv+P+dGQZRwbn0HW1fg0VJhn8ODAMI955LIZRwDftgl9ChoGCIEY7A4yh\nGsgt02xBasLUogkqKPA4yM4sO5NsBEDeiuerHmvU+mTFEuzA4LXoheC08zQFIzueHVciFMG2Bqmw\nX1aewxNSK/v+pCQshGGYGMaJeTkyjgvBDzjr+1O37SsI08MOMqY1ijhSs1B0b9rEUCu67zKW2iox\n7+QSKXWntgQt0kpkz5HLtvJ4vvDl4YFfv33h4eErDw/fuF7ObFvEWl2FlGpZr4mnh52Hh42nh4SK\nHbW7MZ3qVZq8XONv5/WObiw7a7mTg6xVkWQIMI4OH7Q5uVHSpIsovbPYngWbc6NlIVVDjpWUGqMb\nsMYTXGAcJqZpwYWBfYtc1o2Hhye+Pjxyvq5UAYyOcKV2EZxo5+l77qw0oeSqPvgUFW5D7gXdvgBE\nNIqyR+j1wopz2qF2aIezDmd7hJ+IOjCqkJwlxajqXf6bC4ZuKSpNpNuxIZWMy7DHSMkLNGGeZt7f\n3XN/WnDOUktm9RvOKl7K2QbNUIOhVb1YWtNkcWO9jhRK60QYi/PqmZvnmWkc+fTxA3/5yz/xL3/9\nMz9+es9xHrHSqCmqp7RkWi60WtVWY5VKX2tVqX8smGZxBgbvadZQqGSpGgskqky0AgEFjJsCNllG\nU2k+4Kh4El42RpNxApLfdp6veYxm2+GMZ/YTx+mOaTwxhrkL1yJSVshPkJ6oKdJKYS3PfOHfyZtX\nQZspDENgnhcOhztOdx9Z5jusH9EIO72JyU09Lo1WM7luVGOpvpDMjqmeBqScyakoMxf7ojzMNVGq\n5sdSC7VEtn3n6XLl29MzP3/9xpeHRx6fnlnXFWOEMQwqEMqObS88fI18/XXlek3UrNoC5Yo6zQ9t\nGv/32yzQt/M6R5DOAgfrrKZFOQg99GKePeMUEBFS0bSR3OqLC8AYS62NlAqxGFLR4kkWjHeMfmQZ\nlWI1TjPWB2JZebqsfHl84svXh148XfcC65qsNoAOs2mlQ7a0y22tabPUXQiCYETFQaUUvNeRrbJ3\n1QdNj+Yz8IJr9a6v+RoEF2im4fr1mUvB5v/mPk8dN/QfKje2FPpCZ32xEQjWc5wP3M0HrIHiknL2\npTEY2I2OZk3P6tQRrT6NYT0Nq4Dv2nrupuHueND3dyf+9NOP/PmffuLPP33i/rgwOAs1U7I+BVGU\nc5tiIpdKrY0qkGtjzwVJWjwJASO+p2IovkFj1GrvYBq2ZRyVII2QhSwR8QHnDJaCtxVn9IlN8puX\n7jWPAbx1BDyzn7kf37FM7xjCEcSRJJHSM614aoK6PZFTosYV075QcmAZF5Z5ZOo+zcPxnsPxnnE8\n6N4+F1rVXVDNiVYS8vKmfuLETk2QTSXVQkqZnLJe4zhdCUil1EypiVIiUjWWb902Hi8Xvjw888uX\nB758O3O57pTSmKdAuJtp4khJuDwlHr9snB8TLTUwDtNZ0qpmtzirBbzU11cz/tHP9yxkbRic0yCK\n4DUAe5knxinQpGFjUgZuk5fM2Fabrr9SYY2NVC01NUYMQxiYpoHDMjPPE2EYwDpyE/ZcWLfIHrPm\niDqLCyPWB7XO+Iq1CWOK4h3piMueP9t7iZcUIqGnsjTp+c3fU4Wsder/p+9yRX8nXQdDOGt7Rm3j\nFvFXSkPs64dq/O5jW+EW4qpd6MsPsrf6UgVKwxbBFo1CsgLOjwyzIbrA5hKDdQzGMlpHro2KAesx\n1lEb7ElBCA3lPXofmOaZd+/e8dOPP/DDx3cc5xEnDUrWV7gntNSYSPvGtm4avNoTBWLOxFrUv2eC\nPlVZQzWGKjoqwTSsabhW9Gs3ARrFCK4I3lSaGUCUY2pFsAi0W2TV23mtE4JnDCMjM7M7MNkDszkR\n5IiIx0hFGNgKpKz2jZJXBI8008OUwBtL8CPjMBOGGetC/yXPpLhrdFSr1LyT45UWV2xN+FaIubKV\nzHNeedgurGlHmuljXo+xOkUxzgKF0gq1RlUmpswlrpy3C8/XM0+XC0/PV66XSM1CGRsme5yx7NfE\n9Ry5PifaVvooTdWSpdK7AOXcNtfB02/nVY/cujfRjq7W2sexFu88QxgYw0DKyjTuYbB6X6miGcgp\ns++JLVZStVhxzD4wzQOHw8wyB8bRq7LbeQgDdpgI08IwL4zZgp/0n5dJr5HtTI6ZagvNaCRkRaCq\nXQ8jXWELN0/hSw0Q6QKmRPCe4OkC0YppWvBTSgwo31afH/QvmlpuYqoE899+5ykvTxkiKrm+FTcR\nQapi+CRX8raR/U1irbzFwQ0MweLF4orgRiFgqQLNGKUPWaVpxDEQc1bYtXMM48TxdMe7d+94f3/k\nMA84GiXtuNpZoq1SYyRtG/u2sV3V0BuTepOKEYozZG+UtWscTSoZS0HpHbSbTaVhm7IaW5ePN1Oo\nEmmi32vFIMbfIh9p7W2x9Jpn8IExjExtZnQzQSZ8DTjxQKAxKBvWVGIt7LWQC2AciNOi6RzBDwxh\nIoQZ5wdA+aG5JFLaqSXRaqamnRpXpGw4qVgDuRVy3nh8+sbfvnzmvO/4MDBNSqWyzuODV2iDFWrT\nsW2tmZh39hrZ605sqm4sNVNLoyaItfGUdkxDU1i2RK1AsOoHNB2H2bSzrSI41xDXfpMk83Ze8+gE\nVl6KTim6vpJ2S2gUzTrOVZs/7VCUgIYyuFMspFzZCwx+YJgOLIeJw2FknjzO6S4SLzg/MB2OnO7f\n8f79R5q5Um3ADxPz8ah71FrZ/ZXqPMUmjKm6lrNNkZZGlcGtTx5f9rZ8B9uXckvYuoXPqxWxlIpN\nGRC8d0pxK43a/5w5Nba9UP4IxfNWKF8KKD3+C31CaqUS953r85nQKoMFbw0hBKyxuofMGVeECYcL\no0ZF9adx4zwNIfXsuyoN5wPjsnA4nlgOM4NXZWLrhmIR29FpiXRd2daVfduJMVFzwWDw48h4WBhy\nprDrmJlEbpVSLMX2GGSxlGpANOuzGt1uZjsR/UIMB+qwUG0A67FAAJxk6u8vdn47/9URwTfLYAK+\nekyxYJRhizG4LtIQO9LsgdiubPFKyY3ZJw5jYvaCwePsgLMjzo4YG7onTklFrRmkKHBdWobWcN5g\nbGBoDVctNVfWy8bT84V5OeDNrOv0cKNiKUc5151SE7lupBrZ886aN4psiEuECcbiqVisBIw4rDWM\ns2Wcht5tmg6H15tuqY3Wmq5WfMUMagl723r+A5w+9nzxt/eYspwr67pTciGVpCrY1rQDNUqTqqIu\nhFKrvi8QnHrnp3FkGj1DcEjNxO2qlmbvuDud+OHTR7799Ix1j6ypIcYRrKHU0uPPegxfZ4wbUaGS\ndRbbLGpPNb8RPNE9qFoHajUq2MP0UIX+dfofu9VKRbRwFs3bxRhsLmxbIv4DALB+/7v3DQgk8vIv\nN8at75ipkiPresW1wuSMxpQ5zVZsArVqipxFGK0F5zDOYEPAhoBYDTauCFiL9Z4wzUzLjPOWWnb2\nsmPHCT8MtGbItZL3nfVyYVtX3TE17YqH0SHGUESoFlqwxPOZmBJbEWpzWrytfo+2ed1LGUfDU/xM\nCkf28cQ23WnxNAGLxbXKIIWx7iR7/t1//G/n/35qbtgKg9VxukhVeb0tGhXmwAuEMWD2gSyO69bY\nSiK0lYNfmYYjp/7wBB5DwLpRUWnO9VQWVVtLibqTt8pnth4Chkkqo59wzeGqZZCB2c54N4KxpJTV\ndB5XctmJZaNIJLWVIoncMtUkxkVvckNwlHGg7hbTbBczeYZJzfW1FhWSRIUnpFTJpZJKoVAQr3up\n198q/bGPMRq2fms0RLSYZFtZJZJj7q4DnRwYp2LJW6GqVXeMqt4WmmiOp/eBYRgYQsAZIe8b18cH\nQqm46cjdMvPjxw+c/3TBG8vj05UtZnLeaSm9CC1voqDWmyNrHMFrR4zVrFwR0Wv+N0M2nXpot6tF\n0yvD12lNuE17S9YpSk5V783WkrNlXSOk1786/y5WlZvP03QyzxA88zhwOh64vz9yuj8yTQPD+D2h\nwjR9wqqlKLHlFlhtFH1mncWI4IzBjgGcB9+7Ue+xg1cKRyuaziJCMZCl6iI97sR1Y7teFCllFZPm\nh4ANI24qVGfIthFNxUvCrI26R8rLn0VTOAQoTW821TmqGdjtSAwHdn8kuQPVqvLSt8bQEtUEqn38\nfX/8b+e/PJKrisFcwdhMk0RzidZUoToGjwmBJMK4D3g/UJslp8Z1zTxfNg7HXfftpfWbgse7ATcE\nvBlwQdNXvDNYGmtJ5FqIRYMIqjEYE5jCgdN0RLLhuNxxvxyxIZBbZd93Lucrz9cnUlH/XLWJ5go4\nVZn7YJiswTpwxrE3o78/sdFo+MlxfDcwjICpmiqUCik2YtI90p4ie2k0CyU13rTgr3tuRUTzZbW7\nq534U3MliuorjBWMN/jBg2ndKaDTuCqaSiUYpCmAxhvP4Ad8tyeldSXFpLjnaQAAIABJREFUHR8j\n413F4rmbR/70/g6XM0MrPFM4b5FSNqi7KrJrpbSmrgejjZBvhur0vn0jzAG87Kq61a9H6FKbrrus\n83rvNr1fbVW7z1KpteiKqzkaGexOta+/k/+7zA1/y7cdvGMZB+7vj/z400f+8td/4of3J+7mwDzo\naIDWqLmStsh23cjXQt4SJUaa6qQVazYOjMvCUCbCMnUjrkPE0HIll6wqNevw1iBFQ6/zurGez+zX\nlRwTxhgOpzuNxDksuHEg1kqywkBhbIUZYTcWL9BK1agpZ4BCrVmX5FRV6bZAY6LVoqNpsRQGmhnI\nDoodoVnETX+PH//b+b+cVho1JqrdqM4jg0dCQMyC9Y55OTBbj1jLuq/MwTMNA3sHFuwlc12vXNYL\nd2mnNcFaj/dKa8FDaAGmkToOXIwh7ZF1XYkparfgLTiYwswP7z5xmo4clwPz8Uim8byv1LKzbRfO\nlzNVKi4Y3OgYgwdfwRaKRLyAc1Wf+G0lV2HbG6l43FQJh4nhNLAc1S9Yq6EWiKmxx8KWLFs0WrCf\nM0/E136J/uDH9lFnX3cJYA0N6bpEVbhar00EpSLGIPU33ndREZi1gFRM04xXh8XhkAqpX488Xxiu\nK3Y84Bt8OE7YOOP3QCgGX4WWKlfJSEvEvLPFCCYwTqN+PcnUIuTeNUtTm01H7L6IhhQkZ7RDbg3X\nUYRie5faRH333eJVWxciFUGiQTO2Xvf8XYqn7fNxj2EMnrvjgR8+vudPP/3An//yJ374eM9x9ozB\n4iy0omkm23XDPg9IMPo0XBMlZWpSi4uLA6VUSqmMTQhVYBD1YUqlULHeMk8T3ntyzexb4vp05vz4\nSFx3jMB0WDgao4Gsy4QZgipsS8TtDj8N+DTih4QPmdqyGpZVYw0OqlSkVbAGS8K2iKsbPm8EM9IY\nwHswOhKuOMS8vlfpj3xaEVouFHZq8DQ30GRGKFiv0WLej5TWOIyBZQrMo4ccsNZQWuESrzxenjhd\nz3zKSeOdvGcYR3CGKhYrHpylxIgPIw1PrpYiTff73jOPM++Pd+Rh0lQXDzVnclrZtwvX9cy6X2nA\nYAYGH/Ay4AwYW3BdjW5NJI4JO+iOPlUhV4tbC2ErzHVmdooCHI1BxDAWy5QdYTcMyZCKkrXezuse\nnbap39xajZBrrZFr3w3KbSVgXryVrRQafWzbBLG2k6oa3jiC80w+MIdRV2OtkffMen0miWDOZ8Jy\nYlyOzN5jlgF7HAllwLVIyYaza5gSaSXr9+YD1nqcG6gFsi1qPbl1nrocfRENadatefESq8Wm0qqh\nWc18dmjuc+uF1hj9GIOBXCi3TvYVz9/FqgKqoPXOclhm3r+749Onj/zw0498+uET93cHhgDeKmJK\nWsNOgpsXxuMdy90d6/nK5esjl4cnzk9n9utG3DZSqYSUCTHhp1ELlLOIs5ig3amlUJ0gKZPWjfW8\nsl52pFaGcSAMA2Ea8eOADZ5mhWYqYqri02h4NSjgRIUkplPDre1RQMZhauuA+wY1YctGcBeCtYwI\nhYhYh5FKaJHS3gZjr3la7fmsBs0nbFHpPVbwQXeFYZgY48YQHPPoOSwDRgLBWfxg2PPGt6cvHO/f\n8ae8IrYRRsc4Bt3Dp0YrFcmVVhrSDCGMnHzADTrSNVa4Xs/EfSPFjXWN5Jb4dj3z6/mZzw8PXLaV\nvYtCYqm4vTBulWkZWA4DwxwY5olx3JF6Ie4XpgOkKORY2BNcrsJ4brgpQ1eyW+ewweINjMapGT0Y\nyvz6O6U/+qlFUXtyKz7GdA9n7RYOUYGOU6EOVu0ppXspWy9W1hiCcxjXmIPn3enIu7sTh2nEdddB\nSYnrvhHbM3a8cP/hB+7u7pjHgH//jjFodF4uha+Pj5iaMa3gu0goBI+1HuNyB9n3MPgm39d25jcF\nz9CxfKJCUjGdd9uLpe1ja2Nf9rrGdIgHKnZ77fP7s2374N4gDMFxWEY+fHjPDz984uOHj9zd3TMv\nI0qJrQocdobBO0broEFLmf288ny8I8xfaMYRS6OsGykmJGXctmNDAGvBe00mXxZKUVunAVrO5G0n\nbYncRMe508ywLIR5Au+oKMEippUUN0rcqHGlxo26RyRlpIJY0bzHnnjgcCDl+1NTy0jdKdkRaNQW\naXUA5xCpOBrX/Jbn+ZqnFE8pjuINRVAGaI956lMn1Mh9o7p4ljlgzYSzuoZYr1cd6R7v+PPlkS1d\naWSsbdRayCnS0k7bN3JSf+U8HZiXmfk4Yaywp41SEk0a1/3KdT1zWS98vTzz+XzmYd24Zs1JTLlS\nW0KqxbvA6XSkvXO8szNuBOc901SYlo3pYEmRbnHJbHvlcqmEuYApTFNQVbsLSO8UFIsmhH8A8PYf\n/dRaseK+Yx272rYWJaF5rx0n1un1ag21KPtbYVZqR7JW/cjWWe6WmfenAx/vT5yWieCdFqxWidvO\n455ofqMYbQzeHQ4cjwdGHzBiuK47x+ELkzHMThsHCV4tLKb1cez3qcWtYNr/Ykd54/XWomEfYg04\n1cdgjI6dUQWvlZdPevXzO+P5bvQJwTklZEzTyP39iQ8fPnB3d2JaDgyjVwk/+tOxzmKH0HeYRgHt\nbqBiKQ1iFZKA+DPbulFLUcFGjf1CKuRmKOKwqSHsgHI7nejc3DgVB7lxwg4j1RhSrRAbsSW2fdW3\nbWVfV/brVTvdmEkVjNfvRzNH1bJijf0+aqAiNeNsRJzpoiWnW3IAGkXedkqveZ4fC5dRGGaLF0fw\nHhGn/ORcWLcroROCxiFwXGby3QlrK6UkYoo8XS7EveCnz3z8+T+4//ADh9OdetREqFnHW62P3pbl\nxLKcOJwOTPNEKjupZFKprPvG8+XM8+WR5/XMw/XKZdvZcyZmFfVseyanSkkGSyWeLWV1lN1QU2A8\nWvJuaGLxo2M8GdwINEsIECYHRtm5OettzhZVwrfasIjmRLZ/AC/AH/zcGCq63tSp3G/+rxZJkRcf\n+c0a2KRQalfm5ILvczLnLMd55NP7e374+I539ycW19hr7NdE1ekHEeMGDTewjvl4YBoHTvPMu2Xm\n4+nED/cnxDmuVUgm9OlNZ95aHcsq0q9933PyfeepddH07/m7dVG6w6I1jSTTuZ8qdp13OOv151Jf\n//r8fYtn59kqHNgQvGOeJ+7v77i/P7EcFkIIOK/EFgzqf/MOO3iwllYbrYKEgFsWxvvKqQrNBsz4\ngH3WAhpjVPRTR9y2VKkmU9bEnnQ2ryrfoF3tMGCnERNGCoa9d7LNCLHubPvK9XLhfL7yfNb36zWy\nx0aqIK5hc2UIgeYswd4QZ3rRWv0BdCyhBiDTTN//6swhyBsC7TXP49fMQ6hM7yyjHRGZaW0gZ3oo\nwTe8CwTvGAfP8XAkZ+0Sn54z1zXy+LxxPq808yuH078yL3eM4ww0hjComKzqPtwGzzHcE8LAtCwY\nZ9ifC9ct8fh85tvzMw+XM8/XM2vaia3RrENQX1/aG/s1k2Ij70CDaHauj431KRO3idNHRzQQoxK4\nxqUxLervGwdHGCxhcAiOlHVs7azGRdWm4rfaMqW8oSNf++jr8j3KUXoKieliiyaF2jTVxN+Y3EaR\nd0Kltr44k4rFMDjPYQjcHw98uL/j/u7IJIkarwpoR2eEpTTO5wvWOCbnWEJgdo7gLMd54tP9iTV+\nxI0TX7bEOTXWovfpJqJELNuBN/zW538roHwvoCgVSemQGgqiq1AVRYlRvrOOhgcGPwAGYgJed3L3\n+xZPAWg4qyzGw3Hh/v7E3f2J092RaZ5wt+LZzdzOO3DaulcRSmukJmQxNOux08x0L1TrlTU7TvB8\npl2utBiVJdoESgWJ5Nq4rBslZ8ZxIJeRwzxhnMOJsNdKTZnYKtbrDSSWyLZtXK8XLs9nnp+uPD+v\nrFsmFaHhkCp4USuMWmTAGbDWgXU062g20NyI2EHHyRYMDWduye9v5zXPdq08PyUWGxn9wmH2lALb\nHslc8PtO8IHDsjANgcF7hjABjnXNfP124dvTxrpmxJxZ/vYzy3JinmZEKnfHg8ZCiXZ1gx84Hu4Y\nlgN+nEglc153fvn6lf/4/Jkvjw98Oz9xjSuxFmIVslhSEeJe2ddKWhtpr7Ssdq5YM7tUamyIVFJ2\ncChUb9XzHHTqMw2ecXB4r28itxuwQar0m2yP+bthM9/OKx8taK2hoHd32x1qkZSmohvpwiJdFroX\nDKp2q7araw2D94xDYAzqBfYdaOCse7kPW2OUXrVeaQLLOHE3zdhpRGojGFiGwHEaueTCJoa9ZWxV\nRbAxN+CBjn0VjGNeuuhboop58X7qezGmW14szlqK6CKhKQ4d5xw+jMzzDKLxaK99fufOs72QI47L\nzKcP7/jxx498+HDP6XRgmka89zgfsF2BZazinHIppFJeEiZyrmr6NRYzTozGIX7AjDNmWpDhgfL0\nTFw34h5prajlpVbNhCuJKoXSEqVlMpUomSEH3GZx3nY1WyWlnXXbuFyvnC9XzueNdUvsuarR2Bpd\nhFPxonE7tar/VNxANarczOFAnd6R3USzDhAsFW8qvkaKfQvDfs1jjWfdMg/myhwm7g4ZFxIJICXG\ncWQeJ4KzWFHItjRL3IWHx5Wff37i4TlSqkFI/Pr5gXn6d4YQyGnnh4/vOSwzdHP7shwxfsBPCy1X\nLuvGz5+/8P/967/xv/72N3798pnLvhJboRjYS2ONjcs1sV0L2yVTdkHxVv1JvjWMGNKWuDwK1Rgm\nY/D3RlXdDWhCqUJoPRbNOv19u43KlBQNVX3LFoez4VVfm7fTx5rSkXYiLxM8Zy3QVIFrzUvHZvoD\nkaD3UWNaT2IJeGMYhhFnLbUU9m1jDYaGcsZDGBhHjWEUScQYKaXxPE2cDwuuNUzOmqdcMq1qkDV8\nB97YTs6y9XsM2W8h8Led7Y3Hd7PeAL346+pL4z+gtI5AtYKzHh9GwjhhRAj/AJOR37V4WgzOwDJP\nfPjwjj//5U/89NMPvHt/z7TMWO9vKEbl1BplbtaeQZeSZnLmXNSSUtWQK85jR8vQQcbVBaIIW21Q\nKjn1sZNUBWi3QqmFXLPG8tRCapUhhT4auS20hVb18/cYuawr58vKNWbWmCn9ycjbxug0SseUBh68\nher1+6oYih3I4UgK95Rw0E4ZwbTMQCKwkd8IQ696rHPEWHgsheM08e5+p1kU3D4ESl3UfiSwb4Fa\nhfNl4/m88+Xbla+PG+vesHbAOng+R3759QvBW0qOXC4feXd/h0GTIO7u32GHEbEKfH98euJ//8e/\n87/+7d/417/9O+frI0kS1epD4rpXrtfE5Zy4XhJpa5ANiO1iCsAbqHonWi8b1QBTYJocEoCmXsFm\nDVL1c63RdI6b0lFejPgaCm6sxfvXf7L/o59bRynakvVOUtdgthdNLZIeEYvB9cLpgdpVuF6Ja84S\nhgER2LaNp6dnZimUYDBVi+c0TerX3HZlytbEum5c15Uggu+h1zElctZVmPQ4Mu0YdXpo7M1aY16E\nQqbvVOHm+6ePdh03ea1YC87r+BmryuJWVF0rDjEWa9UiGPzrP9z9vsXTGU6nhU+f3vMv/+Ov/M//\n9//hr//yVz58/MgwjYgxpNqoFFWEWddbfaE2voOO6dJHo0/TDVEwvHMQAm4aGQ5Hhj3hY8GkTCuV\nEhM5JvZt02QLEVWkCVTAp6xf88aPrE2JRimzx8Rl29liZsuVvVYE7Tq9MUQLoxWibYwexiHgjceK\no9mR6heSXyjhQAkLtSOpvHWUAtY20hvb9lVPE4i5kWvhYdo4PT2TakS84IeBkiMp7lwvK7UYYqo8\nXTY+f3vkaS2k5mnGY0ygiWMvled14z8+fyaWyPP1wv3dnXau1vJ+T7gQiDlRG3z99o2//fu/8cuv\nv/D4eGaNidQKSRqpNrY9s2+FfSvkTZBs+97c9vREHbEqJdzQipC2xv5sMAH8bHGDJwyWyXuCdzjj\nFdBhzG9EG73ztE5vwt7izNta4bVP7cVS5PZat95gFLXHofezG0dBHSwOg8LeMQbjvGIivfo9m8D1\nsvL12yNDLdRlYPaqaB3HmWVZWGJmS4V9T5Ra2LeVDQ2C3/eN0poKlKzHOM0bbU06rL6TjDBdIVyh\n821tD85GBGutJgb5gHFBLSnWYZ3Huf7frVdhXrwogKYJuVQG/4/hj/9d797OO053R37604/881//\nmX/+67/w408/MC0zVQxrytTaQLRLtVYVj+ptUli1iD69ONf5sdIUr9c0d7O02uPJHDYM2GEEF6js\nGim2R+IetRM1Os4oVYhZVWF0xmKpHaCcCzkVYsrsWSOjUmud89nn+dIYnGHoBXQMlkkcwYINHSMl\njmoCpROPjAFHz/w0HaDxorx9O69xWtMJh+TKed359vRMYcAPEKqnVg2bbsWxx8ZlzTxdd56vO9dc\nMcOEN2gYsNNc2T0XHi5XYs1cYuTufGUeB6bBa2hBgPP1iZQL37498PMv/8bj4yPn88qeMrFW1pTY\nUyGmSooFKYZWwTR1EXd33He1frfUiBhKNuznRmuZ6S4wndSOMvmBaXBYr9ciAtJ6eoo0brFP1oYX\nE/vbed2j7Fft6ix0gpXuMgVwRkPxWrMYcarmNwGMV8Zt0713u3V2GEoRLlftPBcL3hzwh5HBe+Zl\n4a5W9irErDRxZ91LTJipyj+uTVQzEkBKfQHXl1xppRdx6V5PMS/XGn2vrg2LNhLWj1g/apHvehEX\nAuN8JIwTpSTkyVL2M6k0Yk5YE/6zZ/SVzu9aPH1wnE4nPnz4yPsPH5iXI9jAlip1S5Te5aWUKTkr\nd7ErYedpYJpGhsF3iXKnaHCb/7eXmJ6ci2ZwpkxMhVKEnIXScxhj0o+5FU9JFTFJ8VAoHqrUSq69\nIJdGynqR5NYo0tGMfX5vRFTqbyA7Q6yNXSqBirMV6wrGZ8yQsCEpRYZKMBXX1FyMFNLrv/5/6FNb\npWeJEFtmbRuhFQ5WGaElg8RCSrBHYd0r+5bUW1wLwYJxKqO3HYyNCYpjbI6UYUsV4yrWWZ7XC+3X\njP/maK3xfL7w7eEr58uFy2Xnsu5sqRBLJffr0FR6uLBFjLYYcosSo/Vianr4MRgc8SKUKOS9UCPM\nYeTwceH9hxnrhFQyMSZiVDqXcV3Age3pHQqPfzuve1qFdgPHoMHQIjqKdd7hgycMvoMSHNZp4RTx\niFEBUO2s2Bu44DbGtT5gvMd4jx8GpjEQpCHeU62m8oRw4TBNHA9KG5JWaM7hSkNS6dxkVfveBGgG\nHf3bLvxBbE/sud23f4PnM1Ytg+OC6Z1mwyDW4cYD8+me1jKCsDuDqTspVwanX/+1z+/ceXqmWaPB\njA2se6Y9XiilkFIi50pMkfVy4XK5UHLGdQrRp48f+PHTe+7v71gOM953z6d8T0lPIorx265czhfO\n5wvX85V9Tz0popGLjuZSqvrEg+YWVuhQ407laKrsrU0l0rW/4B3uwYsqrD85VTpWqgipwSYNT8FJ\nxMmV0cwEd2b2nlECkymMZBwVI6L2mLfcilc9QsU43b1U30g2UYPBzwHvFM5RYqYVqz5eKsE25gC0\nSpaK09sF3mu49hAmlnnueYkT8zwwz555ctSW+fLwlVIi1mpaymW7EEtmj5nLZee6RprRTpbWeaZ9\nxCo0xbVxK5zQRPnJt72XZIsUKLESt0LeC8dlZPmfEz99+kAYYN1Wvj09E2Mk54prFvoYsJaMSKGU\nNxvVax+DOhZ0/Klv3g2EccIHrz51r9ME63TfiWhBEhOQHoEo0jCmU4msY5wWltOJ6XjHuMyMy8yy\nDLpWmhZMGBHjmcaJ0Q/cLwuj97TakOGKL4LdM2KydsHyXV1rLb1wOrz1tNo/phsX9X6qY10xDlxQ\nEd0465i2iYL53MQwH7FGdMfpIJ6/UeOFWhv+H2B0+7sWT+lROOua+PbtmZQa1jlVe8VIKYW4R87n\nM+fzmX3fsUY4Hhf+/KcfSTFRmoC1LIcZazVOBzE9/HUnxsj1svL09Mzj4xPn88p63YjrTtwj+64j\nsFS0U71BlXPTGbp2nv39zVfUuliiP629SK277xhu3En9+FoFSyNuCd82vDhKs8wiBMnIPOCDMDjB\n628Dznj8W/F81eO9I9GopVIMJFMoLlB9Rbyl5UYz8hK87r2wzDCMjnkKpHLbnzus9QzDwDIvnE4n\nDseFeQkMg2FZAtPoKBn2fGHPimWsrSG24YLD9ZGq8x386I26hY2azaVfb60DtjWXVrouQMU+Bvpo\nBiW1FCHHRs2Ct45lGlmOjjAKe9r59g1yrGQa3use3jnTb4Cv9aq8ndtRfrbDGI9zAe8CwzjjhwEf\nBqy3WG91PNpfL4PDudALqNOM4ypQm3qFU1bhJRaxDnEBO4yEaSZ4ixsrYh25tBdoQRbNfa0ibGIQ\n17vVqTIXSxQhNsGWhq0V13UhFR3bSvdxinX9YVAfBJpRvrdYr0XUBUyVHp+mOcnTGJiXOxwVSRrs\ngfXw331sW3Lj4eGMdz/z+HjRfaZz1FqpVSNnUspcr1eu65UYIyKVwzJxvaz9ha7d12SZJw0adt5i\nnVI0rtvO8/nMw9MT3x6fuJ5Xtj2yrzsx7qSksutcSh/QafeqxVJenoQEQzO9Qt4mAjfU1MvTHy9e\nOPuyydebltSqloC2UnOhpoikDZMuuOPCdJgY54B4VTt6q4X17bzeGcaJXCIx7dhs2Ktlq4W1FRCD\n8VADOrpvQLDMy6DjL6u5iUX0RtRqwJqRaZw43R04HQ+EAVyoLItjGDy1zRhf8ZMjp0iMkTB7ju9n\nqm24wbBtkVJUlSjc/HD6ANdEKKWnZTRFbYiqSXQkRlV7mCjarDaDCw4fDLUWSs4Ya5lnzzRoZ7uv\nmZQqzjuOh5HxNBCGQD28Jf689vE+ENyAdSNhmBiGGR9GXBgw1naPpz78WcA7xzAMOKc7T0GpablV\nct7YSuTZFL4dJ+6PM9M4ME8jWSzNBewYmLyuC5bxytlaHp8vXLfEljK5NsSAt4ZlnhE3YIaMnDOR\nRKwRU9SiKLVBZzmD03ut1R2siOkj2qAUuGaxonxwjI6pS6lcLxekzSzjwDzfk+eNmqLu6flvThjK\nqfD0eCbFinNfVfhjVSZ/o03UqnmFMSVSStSqaSo1VxAVMIRxBqPio+AdIo11izyfVx4eHvn89Rvf\nHh55eHxmvW7sMbJvkZQ0YV3jeVo34naSP7x0kfIbc++Ny/gym5e+J7098vdPu729FNH+lVrJ1JJp\neaelFZNXXLkjcId3J4RBVY+t4t+K56ueIUysFGoW9l2IWbjGyhAzjcZgPQw6Js00ggvYoTGNA8Pk\nlS1qhVIbNQcQT/CW49EyL4YwNIyrjGNgmBzWBoYpMB0mtu3C5XoG17ADDLPlcPLELZKi2gCqJgC/\nmMdLbeT+Jt1Arui2qrBwGsYITnkc1ObVgzfDNW58e3zETUfCqFevswGLp6SKlIY9WpZ5Yl4CJr/+\nWOyPfoZxYhqP+GEmhIlhnLU7s67bRNSKdxuLeesZnFdecS+urVZS3ilpJ6eNp5b4PHrm4AlOY+2O\nxwOHBpMNBAfTWJiGEW8d67bxt1+/8vXpwpYL8zTyl58+8eOnjxxxDHul+pVLvXDeCyaiRb2JkuHE\n6pSuq3NxGoamBXToO1pDax1BqO5jSs5sTfDGchgnxvHAspyoccMSyWV97Zfn9y2eVYRti7Sq+8/v\nxbMvfF+UroIqu5Rb2JolZ+Fy2fj27ZnD4StNDMfzFe8tpRTOl2e+fP7Czz//wi+/fObh4Ynz+UqM\niRQzMWftNm+7S2NePKVwk+hzW2W+IKToKjHNH+17zta+K4b631vvOG+d53/CT6GdaN1W9lZ1K+Y8\nuJGFwGwNs6Nbgd/Oax3nBgwDUhx5b1yfK2o7q+SDZ5oCDkMzhuqhkqkvU4uKx+oY3nVCT7PgHcV4\nMkUnDA4djTmD9yricM5iTEbMRhhGDneOfXPEzZP2kbgpKSuXont40Q1n686U2lB1udUndekJQCKF\nRsF1NmRMlZQaNRS+XZ9pPyfO6cq8BGoyTOOR9/eBwW4YK7w7LdydDhyOIyaNr/vivB2Wd+84LvdY\nN+r9g85dLupb7/R3rLEM3jKNA8uksPdSC1tM5H0j7Rsp7pAzWyt8fXggGCWieWNYDgt37+64Mw4/\nBCYxHI87y/KMdZ6YCl8en3g4X7g/nfjzj5/4cH+PG2fCNbHWwM/nDJ0MFEtlL5XcIDdLNRrWYZxX\n9jgKerfGY0SxpqZf2CIGKVUjHl2jTQVnDGMIlHFiHwakFv4RNl6/a/FstVFMhZQJIsqxda6PYbUw\nWecI1hFCD0O9GYFtIGXh6Xkl/PKFbY/My4QxjZR1T/rt4YGvX77y8PDE9bKy98JZXxLO5WU3eTu/\nlTjfRrIvmv9eXaX+ZxbjS8d5k/hrtdSnK7T7vBVf8xsAchMhx4S4HcZEHSplcLQh4FxD3ornKx+D\nMwGah5jZzg1s7cSWQrONaQzgHVhPbVDQghSkMDYFZigJL2Ct/k5vOSNuolrPaAd88/g6YkzAOUsI\nlmlyGBsoc9P9ztGQdkOOjhwDKWVVj+dMao0mpgcbW7UJWI8ffF8fVSqZ3JSiJeikZdstl0thj4Uv\n58hzvPD1eeR0nHl/+sBxuec4ObbjTmuZ07uBd/e6q63rW+f52udw/567+w8YrF57uRBj0muz5B41\nZvHu/2fvzaMlyfL6vs/v3hsRubz3aq/q2Vg8DIsZGBBiGcACCRAHbJAlYUBsA0ZGljC2EBYSss4I\nLYBYjo4xWCAEAnHMAMeSjNABiVVsMjKIQWKkEdsMM8P09Ex3V9XbMjMi7vLzH/dGvnyvqruriq7K\nqu74npPn5YuIvHEz85f3e3+7KSbYmmlTA7kWcvA9q3bFarUixVhM+crR8QKjQ00fYb475/z5c+zt\n7jKdTKgnU2bzPebzY5pmShKh7XoODo6wxuCc4+KF89TTOVp1XF/ftqHcAAAgAElEQVRC0yzAOIKC\nT9AliOIIRlHroDycrRByQ+7KVVR1jatrrLVYY4lJCSYXQ7CuYlrX1M5hpLRWc5aQhIehJ9l9ztLP\nIe/C0CnMlvzNkCtPDNy1roeYHcpC/mzaLnBwmGssHi2WVJUFIl3fslgec3h4xOHBIcvlitWqK77U\nRIwbkbIbWBdY3qzwXxJ4y3TX6SiaNghU88mBSwfNlA2L7XosM/Tcy9QYyWS8ihaNFSlUpOAQ9eC3\nb7d/MSPFnEuMGohC6pR+GemayGTiQBVXWSrXIDSklM1LiGKNYCrBmJx7l4tbJ6J0qHpS3+HV0qcm\ny2QPTR1oqhpjclRP4WRUlLqCujLEaUXyjhAaeu/pfGDle3yIhCJTxgpVJdSNIBbUCH0UFp2y6nPO\nsldllQJL9Sx9T9f1mJXQhYSxE87vNOztXmRiG8JuT0o99RQmM0vdWJwbo223jcl8h2Y6A4UYMvkZ\noDYGbapcwc2YXD3IWWpXGmbHSIqBFHPxC2OzLNusGRBi5HjRYtjHiGEynTCdTWmamklVszebUU/n\nTOe7TGY7uGqCdTlIqalq5pMJ53Z3qCY7LIJlMmmp6hrr6tzoHUM0dYkhAVNSYoxxVLaiMo7GVTRV\nlV0gVYU4i8hQIckymc6Y7ezSTBqqyuJ9m6vFhUB6SDr+3HfyhERUj0lCTDZ3qBeXTVxk7S+bcy0D\nTyXNGlzbemJa0nlPdZTDoJMGgs9BHsvlksViRdf1hBBLMA+w4Yc8S5hnjw2m1/W58r8pBGoKKW4S\n8eZYUEy4puTbARgygZax1NYEO6EzuWtH7C1Ki1uNPs9twocup3pIDvxSn1CvSDSYJDTWsTOZUFVT\nrJmh6rJFISlKQkyOss7lXYboRMXHXD+584rtVnSup2sC02rGtGlKE2oPklATUDpUPMalXFKtyf7T\nEBvavqf2Nhf88D0xRYxNuKqnnkTEKkmUftXR+hUHi45Vl2j7xKrV/LwN9H2kqSxJKup6zmy2x+78\nPLvTGWggpha1PWID2NEi8jCgdg2VrdAYitZlmFUTnHUnkdWAppz+lptJB3rfE2JOzXNVTYOgVY1D\nkRTB90Bisep48vp+LgpfV9SuYne6w6SeYlxDM93Jj8mM6WyH83uB83vn2N3ZYdI0GOewxpUsiAbr\nasRVmGqCJCmuOcFUueSeEUtja+b1hJ3JhL3ZjL35lKpyRfGwiHU00ykXLl7m/MWL+BS5fv1p3vPk\nAW27pGtXWfF4CKx29zdVpcS35mhATwggUpOLGucPNqdQWiTlD2+os5nzORMhBXzoS6JwQjUQk6fv\nW/ouF0ZYd1Ip42VyG54PsxlCfE4ODhqn2TTRrievG2MNqZ6bfs2SwsKggW6aes+QcanwEZFc0NtH\nJHS4Rft8fdQj7gG+a0lRC3myTvGQKBAM2gthpZiY64gacTk3TXMHk0SuPJWLdSgpBiCfM05wLn/7\nPStyMasekQlKjVPBWCWmSNCORJd948ZQGVuKgIMl+6WSAWwp2WYirgZXR1SUECN97Fh1K44XPYuV\n0vbCqk30PvevJQDOMGkm7O3ssDufM500TKcTjCSiGrzmpuBJE7l98ohtwmFpjM2VoKxinMmdfSYT\nQPA+58sHr7kJdoyE4g9NKlhX0xiHrSalgUDEpEhyFcRACoE2KDcOFkzffZ1zu+e5cukqs+kOO9MJ\n4hpsNcG4BlfV1PWEuqoxxhJDlrls9WuLApNQctk9V5vi7shuhlyZTZjWEy7snuPq+QtcOrfLhd05\nTW1zhLkx1JMJ091dLl66ws7eOW4eHnCw/zTt8ph2tSCEHivhpLrWFnHfNc9MeBBiKP8lXLK5Ioax\nWJMrdSYU0Vw/ViUvEmndESKbfVUTSSMp5coofl0sXteuyzSkkbChXd7GXMsG2aUzxDkQ3mBSzu9k\n4+Ta3HziLl37PaFooCfl0ywJS8DEDokrYlRW3TEsttuP7sWOrm0JwZQCBPnLFBU0CLETjm4G/KrD\nGgFNGCqMrYo1osTgaiBqNiWlmHKieS3MZjV752tmk4aqVpzzOAdqE9FEhJoYye3GYiCkDkzI1bQk\nIepIUQkxj68asC7hrOZULZdQiXQx0PpA2+YoXd95fC/E3pK8oH3O90SFWix7k5oLuw27M0vtcvJ8\n1JjzAbX0VxGLsP3C2y92uKhMh4pC1mANVFWFqyqigm87+q6j60qh9lIqT0RyFSExWIRKS4mCpGgM\naOXRFNEYcJKLsS/7xI3DJe96zw2m9YwrFy+QEgQVogreJ1Zdz7LtODpesH9wRB+F9zy5z5NP3uDG\n9essFwuiDzjnMJVBnEONrJUak2BaV1y+cJ73ftnLeNnVy1w+t0vtTM6KQJnt7DLd2WW6s0NCODi8\nwfL4kMODG3TtEiktLh+Gjo73N2AI1gE0miJJU95pW4stIdWKRSNYbCEzKYXhSw3HUh3emEx4Wvyo\nQ4cVGAhO1+R4QqCDBff0J30SCKTrwJ5hnFOaa8n/zARsSiK6lIodeUGF7HQfTL2DI/tU9G0MmH6F\n6Y+BbE7ploeE5fbDrV/MaFtPirlVXK5MkGUmJctqqfgucCQr0B7SCmsanMsBD2KUqL48wroRu3OO\nurHEc5ZJbWDusDYirie5HIQURXNpd7X4mFh1AZ882ID6DqMdqM3dUEoZPutydGRlBLUQSLnIiI+5\ngHzr8X3KWmYsUeNJkAhGLUaUaeXYnVacmzvmEzA2FyEJMRE0kCTlz6DUQR2xXdgQqGKkygWgSnQs\nGCMEH/Des1y2rNo2dywRyZkM1lK5GmPtupiAaFEHUiKFAJoQBWcNlTOYqmHVK9f3j5lPb2b/ZOXo\nfcJHJWpub7dqPYdHS27cPKL1kevXb7K/v89ysST0HZU11JVDXI2pKrAlIjwlHMK52ZzHrlzkfV7+\nEl7x2DUun9ulskLbdfiUmO7sUE2n+KTcPDjkcP8G+zee4vDgJjF0NLXgrMnFc7aM+97WY9OAOfiK\n1tV5AFd6bhpbOqbrSQm+GDLhZpKjRLjmSkEhhpwgXCJ04TRh3S6S9VQEbbn/qf9L6b18LRsaqZwU\nS9g0/7KpccqadIexBs01eo9ZLtAI4pYoSugW+NVott0qVNaFCIbi6CkK3VKJPlfcyebTgEjAmD4H\nNaQhLy3LckiRFLXU9wxUtWW1SPQtLI57di7C7FxiMhcmTaKpUi6pJhWOhANSyPmkST0qIed1ppRT\nwUXwCUwUOg8EJaXSpi8kuj6XoczBTIKxYFLWgk0p9NE0hp15ze5uzXynYjKVTOoCpjQsECBJ7nNq\nzdjxZ9torGA1ojESvCeKojrJeZAlL3Ld3aQUkpGSEpJMDsDJrefyOmXzoobU5OAjyZG6TVMxn02Y\n7MyIUnG88tw4WFA7y7LzGFsxme0w7QNV7fDJcLTq6PpA12dZndQV53Z2sp/VVZiqxtZ16YKVZWtS\nOS7tneN9Xn6Nlz92hWuXzrM3nWAln+tCAGvwfcv1/QPe/vjjvP3tb+Xp60/SdUusSTnvv7JofIHX\ntt3EiU+Q0i0l79bDkPe50fctFYJU1bL7jutz6+IKKWbCSmfI78w9h9fdDsN4p0h34+/Q0DUfgDWJ\nbr5+4/T6+qERbL4KkiGsOqSLuXOAQIodhIcgWenFDOtAc1pKdlwL0WcS8l6xFVQVuDphnAcDSS1B\nIURDCIImgyYhRkqHIKVtA+3Kc3zcc/Nmxd4Vx7mrhr2Llp3dyHwWEKNM6hrTJCbWYIKj9X2J1C71\nl43ik+Rm22KJQYmrYr3pPakUEhFj6X02r6kIYsDYhDEJJWErYTKpmc4MzdTiasnmYzrQoeB83vhl\nJ0occ5AfAliTiKGl7ZbE0CGiuH5CPdsjSDbdiq2wdUmRE4NxNchJTrAmstshG26xzuFK3dnKOeq6\nYjqbMp9PmU4qpHK0feLgaIk12TpT1VP2zl1ETUVtDeImdH0iRKiqmt25cM3M2PU5biVXksskHskp\nedYadmYTLp8/z8uuXuTi3pRZbbDEkq8aiKFn1S64cXzM29/1OL/zlt/jbe98OzdvXs++ztpgjeRI\nd/ciIc9TuZWDqbQQZEolXUDWCSPr88Atf4fzQw/Ozf83cUsA0Ma9z56/3bVrbWRdlu8kiHdtCt7Q\nOrNwGsS6dcFjU5oek0B9qeIiObpTBIyrSH13l5/miOcTuU9iXJvgU3b0EKtc2q6aGOZ7QjPLAT5J\nE30v+E6IviKWdmEpZktFrvySv99Iz6L1hJsWb2pWveH4GPb2HH7Ps7c7oZkYTAW1MyRrUW8JUfF9\nYNUnuh7aXumj4JPiQyKESAqR5GNOV3COmJSuT/SR3JElKYEENs/b1YKrDZHIsm9hCVZziUFjyB0w\nxGCkQgmEuNryNzOi61ckv+TgaJ8Q+hwwNJkxTYJt5kQctqqpbE1Icb3+pEQuMhAT3vcYEs5Y6qpG\nbW5pZ22uKaumIqohJKHzCZs8pobKBprKYWzFdDrjHAY33aG2ht0Lu0zm02zlmCvTHs5Hi0/mRMMt\nBB5iJBAQI8ymDefmM2aNQFzh26w5pxhZdT0HiwVPHx7wxI2nedvvP847Hn+cJ59+kuXymFw9S3Lg\nqEY0bD9d5YFqnpvPBxJLaag4eyu5bWqFtyPINYmeSUN5Jm1y89zZ655t/Pw8tx+WWyJrWecmKRY1\nFaaeIdUU28wwVYOGRFqtSN2KGPtcgLuxWJPo+jFoaFvILe5ys17W1S/ydl2AuhHm5wwXr1r2Ljpc\nDTEJvjcE39B32XwUg2afZ6kzGqPmbjt9yI+YuHE9cXxkmEyVwx1YXWrpL604f3HKbLfOReHFIuro\n+8iiVY4XkcUqP1qvdEHpQ8ljjglSNsc5G4dgYcJQui+V6p8WxAl5D5dYtC1P7h/QuCWiQmUMTZML\nN1SuwhqHYGnbo+19MSMAOFzu07crbuzfJCRP1VTM5nvsScUUh3EWsbk4h0mGpJJDEzUSEvjOk0KL\nhp7aWqbTGZWriDYRU6lWpUIfIst2xbR27NUOZhPmk4qZq2iAWUqoq2l2cqWfc7tT9nYmVFXFBWPx\nUtFREzGlUlAk+kDvA13o6aNHJWKt0FjFr47Y71e0rsYZRwiR4+WKpw72edd7nuQd7343777+NNcP\nDmjbFUrugWyNoDGQRHJ/5i3jgZDn7cjrFJkOBLpBhpsEd3aMzbGe7Z6nyU9uOX873KqZbkbtDsFH\nGwFFgzlXKWHZNbgJZrqLm1/ATedoVMLimNgeE/sFqj1m1mBcott/z519iCOed1S1Yzpv0KBozMnl\nfdfhfYt1kaoRZjuOnfOOc5ct9ST7mkKwxDDB9w5NkEIo6SqBFA19F2nbyGopsIDFccIvYHEQqF1i\nOVP8osOvKryPnAszqqklEFl1keNVYv84cnQcOF6E3Ee0T/Qh4SOn3BUipUiDkVK8g2yBTiV62Cji\nLEmUlffcOFqwCiE3n1ehroTdecVkkgM9rBg0Gq7vj8Fs28bx8pjl4pgbh4dEhcZ3RHGYeonaCVVl\nMCZ3g8plHEtkbEz44Om7FaFbkXzLpK5zwGUzIRiP9z0pReo4pLZEagN+PkXinFltqayUKPJQolxz\nnnOIkbb3GGtwlUOsyd2l1inPSoye2Lck34F6kkaiKL0qxylhUqJ2FZWp8DFycLTgyRs3ePw9T/L4\nk09x8+iILgRC9AwF6VJM2dOVWDdP2CbuO3nejgBvd+525+/0ms3rnm2M26asbIx7lmw3/bTlILnG\nRzpzn80gpJxfZeoZbr5HvXsha6bTHVgdoatDNLaYnRprti8AL2bMduZcvXaNnekcDbBarDjcP+DG\nzaeJ0uKc5A4VtsJal9uEpYgxFqlcfpBKs+oECH0XkTZlU5UPqMnO79gpsYNVSsRFQluhX0ZWS7h5\nEKh3LMkluhhYtJ7FwrNqA23J1ex9XhyHiPNMjLm4CJLl1Zhc5QiFJDnYyTiDovikHC47FmXRI4FR\nYTZ1nNtx7MwtdWWyqa9LPPXE6E7YNrq+o+89qYRGaBQ0gu893WpJt+yzz10p9bstEcGnVBqet0Tf\nQvQQGyorCBFnbK43mzzBOXrf03YtlRX8akLqd5DUs1pOsQa87+mi0muO3j0UeNoJOzsTJvMp0ToW\nXulLjnQKidXxguXiGE09SCqhH5ZENutaoKkclavovedwseKpmwc8dWOfo8UCHwKaEhbJbgoDyRiC\nKGKzmXnbuP/RtrchzGc692yvfzYCfCYT7+ngn1vNtM80hxMSPYmsFRk6wWgJ+z6JuRWRdbszSlSw\nLRFnpp4grkZthVYOKoemFjuvMWn0K20Tu+fnvOK9X8a1y1eRKBztH/Ge9zyJqZSj1U2aiWJdhaol\nRov2iYghak7lMEMDAZcb9uaIcEPvQ26bJCdBG0RFe1Cfa9imLtEuleNFy+Smp94x0ChBAm2MdD4S\n14WLBOcsNseErBsPW5s1AYqVZjA/xxBLiTbJhR8U2lWELgcihai5ehYwn1m6vqLtHbUltylbRfZv\njsFs24ZGxWCpbYUI1KbCYZGU6FcLoldCH0vqlAUxmWBUS5WhnuB7DEoySvSWJJE+JawYJHUEY2i7\njmWbC3loP0XiitQvOJ42NFZAI0FhFaDrIxJ6Kkns7k6Z7c7wAvurjmUbQWuIwnJxTL86xhKYNg5T\nObxUJFNhjaG2hsZZrJWseR6vOFx2HLc9UXOxEAFCLPmpSQmSivICqi+CgKFnIrSz1wx4Ji31LBGe\nHft2195uDre75iwBnxxbX1HMYTkiM69TJ5lwJVSIpAHRiDWlt2LKeXsaIqnv0T5iTI2pK6qmypVr\nRmwNu3sTLl7a4erV81SmYXl+l2pmSNWK6RGYyjOZASS6FkzIi1BOt8oRuqJgcFgLzhmIEYuF1JF8\nTmQPvZK85kLHCcAQulwIJARo24Q9iGidoM6LRDKCrQxVbXHO5CbZtnQlMhZnLda5HKy2QZyqOf+z\n7wLtMtC3Cd9FUsnn1CLLIhBEWWmidiFXNaprJrZht66RncQ7eef2vpwRudhALaSJYESoq9wQWzSV\n2rUB0YQTS5VLWKGieI0oPaIeY7K/0JlIJRFCi8ZIFyLJVxgx+BiJ3qMidJ2yNAkJHb51zGtH4ywh\nKcs+0vWB0LU4IinNiLqi1cj14yVHy0AMFg2G2LcY9exOKqY7c2xlOA6Jru/wCp7EorTRa3vP0keW\nXSSoRQEjhqglErcElOa1N6fg8BCkUm0lYOhOzj9bIM/tAoKeKR3l7Pk793VupJ6sB9qY13ANFNVi\n6FIQkeQx6qFfEsWQIvQrj6pSTSc4N6Wp6pyuMmJrmMwsOzs183nNbLrDfG+KNIHeHlLdDERtwXiU\nlm4VMDaXSVNSrvwTFcFhxFI5C5UFBAkeiZbQRvql0q9CzvEVgzGSqxhhi1wo3gMLRZ0idcJMBTsR\nKlcxrWomc0szMdSVxbkKJy4TqHOl2lGOGlaNxJiDlFa2h77HB4+uIHZpbeLDGdQmqCKSwHfQV8Ku\nnbMzucjO9Dy7JvGmkTy3irqqsKbBJJe1tcqBy6bLqKWxALmzyqTKXUmSQh8TksAkJQqIEWonOEkY\nUfrQEfue1OeiChHJUdvWoSnS9y0Se9QbzLTBThqiKr7vadse9T2JSN9D73OFrNyftqPvBLxBNLHT\nWObTGZfO7+aezMee7rjNBR5CT9+v6PuOPkbaCEFz20Zjq0KcQNE6VbKv35hSnS69cDXPdRv6uzHN\n3u7YM73+TlJT7vT8M98jAeY21yq3fnVlCYseQod2xwRVpFuRghJaDxhMmmNlRkgO+sPhxZNbhhtx\nPzEB6JYtN6/fpFLHfLYkIRwfHdF3HTEE2r4nxZ4YOpJ6kIi1mvsWhtzoALUYcjWWpso/p94Hlsee\n/jjhl4nU5/QXTQknjrwqmLznCop2pRWaU7RWkgcJkuOABSg1kanI5jdRxCaiBKJIiV/LWmdMidBF\nwiqRjpV0rMTjRGxTua0dCuZCJTnXOghdUFY9TDxUHvzy9Gc14oFiAlmOjFoCOd+dmFBJJRUpF0+w\nyjrtz5qcHuJTwPuOEHL/2dzPqxgoktK1HaHvS1CmAWNQa7HREqKj91k8FkZo+5rjtkaBRe9pu0Dy\nPVYSnQSOU0+fIjcXCw4XHaulQhScGFKqmLUV8+USFxMHy+zb7Lue6Du6Qp5diAQ1JFPnnGpT6vT6\nPheHiKU+qwV6CMnQ+/bUZ7UNyJ2Q210PKvJ5wA887wO/cPH5qvqGbU/ixYJRPu8Ko2w+YIzyeVfY\nmnzeL/K8BHwq8DZgrEH3zJgA7wP8hKpe3/JcXjQY5fOOMMrmljDK5x1h6/J5X8hzxIgRI0aMeCFj\n+17XESNGjBgx4hHDSJ4jRowYMWLEXWIkzxEjRowYMeIuMZLniBEjRowYcZd40ZGniHyqiCQRqbc9\nlxEj7hQi8gki8p9EpBeRMXVkxIgt43klz0JKsfw9+4gi8vrn835/AIwhxiOAR0pmvxX4JeC9gT+3\n5bmM2AIeIVm9Z4hIU97PH9/2XJ4Lz3eFocc2nn8u8DeB9+ekhvptm1eKiFXVR7rFiIg4VR2raT96\neFRk9pXAN6jqE890wQvhdzTiWfGoyOofBI9Mwe/nVfNU1SeHB3CQD+lTG8eXG2bTTxGRXxeRDvgI\nEfnBs+YoEfkOEfnxjf+NiLxeRH5PRBYi8msi8pn3ON2PEZE3isixiPy8iLzvmXv/zyLyVhHpirns\nszfODbujLxWRHxORY+AvicglEfkhEXlKRJYi8p9F5M9svO69ReSfiMh+ueafisjL73H+I54HPOwy\nKyIfICIJmAE/WDSMz36mOZXXPKPslvMfLCK/LCIrEfmNMsYjsdt/MeNhl9WNcT5URH5cRA5F5EBE\n/vWwzonIa0Xkp0XkaRG5WZ5/yMbLf49sGfxX5X28+V4+qweBbfo8vx74i8AHAb91h6/5m8CfBv57\n4IOBvw/8sIh81HCBiDwhIl/9HOMI8LeBLwc+EqiB79oY488A3wj8nXKf7wfeICIffWacvwW8oVzz\nA8DfJVe9+BTgA4GvAG6UMWvgp4F3A68F/gjggR8TkRed7/kRxTZk9rfJGkcPfBnwEuBHnmFOv/lc\nsisiFvhR4Eky2X45WW5HV8YLC1tZX0XkvYFfAG6S17iPJMtgVS7ZAf4h8DHAxwLvBH5cRJpy/iPJ\n6/PnkuX+4+9w7g8c2+rrosDXqOrPDwfkWbqilPNz4KuA16rqfyiHv0dEPpG8qPxKOfbbwHOVa1Lg\nr6jqvy1jfxNZSERzyaWvAr5TVf9Ruf4bReRjgf8V+O82xvleVV3XoBSR9wJ+TVX/fTn0jo1rvxA4\nUtX/aeP6LwH2yUL0S88x5xHbxVZktsjjk+Veh0XrGO59uzk9l+x+BpmAP0JV98trXk8m1BEvDGxz\nff1fgHcBX6An5et+ez0x1Z86c9//gaxFfxzws8BT5dT+IOsPK7bZFO3X7vL6DyDXM/xFOS0JFfDL\nwz+q+gl3ON6bNp4/Qa7Zfwl4mqw1fuOZ6/8N8EVnjp19D3+fbFr7aOCngH+mqr9azr0GeLWIHJ15\njSX7s0byfPixbZm9kzk9l+y+P/DWgTgLfoVHyNc04o6wLVl9DfDzG8R5CiLyEuDrgP8KuEq2ftbA\ne93lfLeObZLn4sz/t/b/OlH1Iav7CnwSt+587qV4st94PnzR5jbHBshtjp16D6r6z4vZ4r8GPhn4\nBRH5ZlV9PXn+/y/wJdy6UD3UO6wRa2xbZu9kTvDssns7OR6J84WHbcnq6jnO/2C575cDvw90wK+T\nCfSRwvbbcZ/gKeDDzhz7ME6I5U1AAN5rQ5u7X/hNsq39n2wc+1jgPz/XC1X1KeD7gO8TkV8B/hrw\neuCNwKcB71bV5xKwEY8GHiaZHfBcsvubwCtF5IKq3izHPpLR5/lCx4OS1d8A/tsNF9hZvBb4PFX9\nSQAReT9gd+N8IMui/QPM4YHgYQpU+Vng40Tkc0TkVSLy9cD7DSfLD/3/AL5dRD5fRP4LEflDJbLw\nc4frROQXReRL7+H+m7vvbwa+THI07fuJyF8BPh34lmcdQOTrROS/KXP7EDJZDtFi/5i8G/wREflY\nEXkfEfljIvLtInL5HuY7YvvYtszeDs8luz9GdlP84xJ1+0eAvzFM+Xmaw4iHDw9KVv93cqDPG0Tk\nw4sMvk5Oshl+F3idiLx/8cV/HxuabUmpeSfwySJyTUTOPT9v//nHQ0OeqvqjwDeRP/xfJpPZD565\n5i+Xa/46mZR+DPjj5L53A15J9l3e9RQ27vPDwFeTtcb/SPYXfZ6q/srtrt9AKPN7E/Az5LyrLypj\nHpHt/O8hR0u+GfjO8j5vZ3ob8ZDjAcvsHRHbc8luyUX+TOAy8O+AbydHngtj78gXLB6UrJYgnz9W\nrvlF4FfJMji4yb6IHLD274HvJvvn988M8xfJMvoONvytDxvGfp4jRrzIISKfBPwk8ApVfde25zNi\nxKOAh8nnOWLEiAcAEfkscv7xW8jRud8K/PRInCNG3DlG8hwx4sWHc8A3AC8jB5L8K7Kpd8SIEXeI\n0Ww7YsSIESNG3CUemoChESNGjBgx4lHBC548JRdjTyLyoduey4gRcG8yKbmfZxKRvWe55nUicuMe\n5/SvReTv3ctrRzz6eL7WyTuR0xcKtkKeIvK9ctKDrhOR3xGRvy73r0D6A7dNl/d3rx1fRjxgPCIy\n+Vyv+SFy+b0RLwA8IjJ5P8d5qLHNgKF/CXwxuZ7ip5HrwnpurctJERZ9pnqJd4Cx/NiIO8EjLZOq\n2pHLnd3+hmPP2UcRj7RM3g88D+/zecE2zbZd6UX3+6r6XeSiAp8JICJfLLnX22eIyH8iJ2+/opz7\nsyLyZsm9CN8sIn9+c1AR+SjJfTpXpTzeh3MPOyER+S9F5F9I7kd3KBs9P0XkD4vIT0ruybkvIj8n\nIh++8dqhJ92PlJ3jW+/tIxrxgPFQy2TBx4vIfyhj/bKIfJpvU4AAACAASURBVPDGfV4nIjc3/v8b\nkns6fmmRwbYcn4nI94vIkYg8LiJ/6R7nMuL+46GWSRH5dBH5Lcn9i3+G3JLx7DUfLyK/UK55u4h8\nq4jMNs7XIvItIvJOyf2Vf1lEPmHj/Oue6X1uEw+Tz3PFSXFgJTf//WrgS8m95Z4Ukc8Hvhb4GnJ+\n2l8D/paIfCHkRQH4F+TKKn+oXHtLST3JzV5f/0wTEZGXknvSrYBPLGP9I0409V1yWamPAz6a3HLn\nxyW39YGTnnSvI5eq+sg7/xhGPER4aGRyuIxcAeYrgT9MTjP5Uck9OgecXQDfD/hTwJ/kpLbpt5Cr\nXX0GuYLMJ1IaaY946PHQyKTkBtf/FPjn5G4q303uDbt5zSvJ2vP/Dbwa+BzyuvltG5f9n+R19LOB\nDynX/svy2gG3vM9nmtcDg6o+8AfwveR2XcP/n0wWir9b/n8dEIFXn3nd7wCfc+bY/wb8Unn+ZeQP\ntd44/+fKWB+6ceyngL/wLPP7enINRnuH78eQe9J9+saxBHzmNj7f8fGClMlPKDL1WRvHLpBLO37W\nxhxvbJz/G+Rd+sWNY/Ny7E/dZpy/t+3vYXw8UjL5dcCbzhz7hjLOXvn/HwLfceaajyeXMh1akXng\nsTPX/BTwd57tfW77sU2f52dI7m1ZkXfUbyB3Mh/Qq+p/HP4pu6VXkhu0fvfGdY7ctRzyLus3VLXf\nOH9LbURV/ZTnmNtrgF/UXKT4FojIVbLgfAK5J50FpjyCPelGnMLDLJOQNY1/u/GamyLyW8AHPctr\n3q6qmxG4ryS/v3Wd5o1xRjx8eJhl8oOA/+/MsbPjvAb4EBH5go1jg2/1fctcLfDbIqf6iNbk3soD\nTr3PhwHbJM+fBf5H8q7jXaqazpw/27Zrp/z9s2z88AsGkrtdr8J7wXO1DPt+8m79K8jFizvyovbI\n9aQbcQoPs0w+G55t/LNNB4YF6kUREfkCwMMsk3cyzg7wD8glIM8GJL2DTK6BbD4++96ON54/dG0c\nt9oMW1V/704vVtUnReRx4JWq+kPPcNmbgc8XkXpjV/Xae5jbbwBfJCL2GbTPjwX+vKr+BICIvILc\npWITnkegJ92IU3iYZRLy4vMxlF6dInKBnJrynH1mN/C75MXqY8j+qs1xfu4e5zXi/uFhlsk3k/3m\nmzg7zhuBD36m9yAiv05eJ6+p6r+5hzlsDQ9TwNCd4GuBrxGRr5Dck+7VJeLsK8v5N5B3Qt8tIh8k\nIp8OfNXZQUTkZ0TkLzzLfb4d2AN+WEQ+QnJPui8QkVeV878DfKGIfKCIfDTwfwHLM2O8DfgkyT3p\nzt/rGx7x0ONreTAyOeD1kvvAvpoctPYUOWDjjqCqC+B7gG8WkT9axvleTrSSEY8+vpYHI5PfCbxK\nRL5Jcn/OzyP7JzfxjcBrReTbROQ1ZS39EyLybQCq+jtlPt8vIn9Scp/jjxKRvyoin/YH+hTuMx4p\n8lTV7yGbI76ErB3+HPnLems5vyDvhF5N3vH8bW5f8Pp9uVVT3LzPDXJPunm5x78r9x160n0p2Wz7\nRnKT62/l1uivrwI+hWyaeONdvM0RjxAelEwOtwP+KlnefhW4AnyG3n3u5l8m91r8UXIrsl8Efu0u\nxxjxkOIBrpO/D/xp4E+Q+3N+GTnCd/OaN5FjQ15FzmB4I5ncH9+47IvJrrBvAX4T+H/I0eTvuLN3\nvB2MheFHjBgxYsSIu8QjpXmOGDFixIgRDwNG8hwxYsSIESPuEiN5jhgxYsSIEXeJkTxHjBgxYsSI\nu8RIniNGjBgxYsRdYiTPESNGjBgx4i4xkueIESNGjBhxlxjJc8SIESNGjLhL3JfatiJyCfhUcom6\n9n7c4wWCCbl57E+o6vUtz+VFg1E+7wijbG4Jo3zeEbYun/erMPynAj9wn8Z+IeLzyfUdRzwYjPJ5\n5xhl88FjlM87x9bk836R59sAvv07/gEf+P4fgDOG3KlN0dLBZnimKKqgmkhJiWn4qyTNj9x8tFyb\nFFSRUlVQRE49gKGZKpuVBxVImkgp5TFTQpOS0HxSQBCMCGIEEYM5NT5l/LNddUAEjBGstVgjGGPW\nc0kprZunbj4H5S2/+7t81Vd+5frzGvHA8DaAa3sTppVDxKJJCSnRxUCXOipnuTidcnlnzsX5jFlT\n41Ng0bX4EDAIlXVMXE1tHcaYLNnW4JxDUTrv6foOHwIxRCprmTcTamOJwRNDwIjgKkvlKqx1GGvz\n70JBJQtm/ulo+VskUCTfT9PJ7wjJvyotv4HyyPJ20j1q+Fc1ltcYUgLfB4xRrlysSFXiu37yt9af\n1YgHircBfNqXfx5X3utlWFMhYgALIgQgqOJTpI2BPgba6FmGnlXf0fqeznt85wnek9qO1Hm09yQf\n0BTRlNbrkYiAKkYVg2BSRIJHQo+NkTomqpAwXjEJQIhO8M7ia4evDdFaksnroyTFJsXEgNVEY5Vp\nU3F+Nufc7g4Xds5xbmeXncmMWd3QVDWVq3DWUpXfgJH8e/IpsfSBo67jxnLJzdWCw77l6Sef4tf/\n2c+uP6tt4H6RZwvwqle9P695zYfhjMGIgGj5kSdS+bFTyDOVLzPESIiJOBDoQHaFSPPF5J+8mDVR\nDX9PiDMvKZkVBVXymDESUyTFQXgyWUMmyEyeeb5mY9yBPIUNki6EKwLWGKwTnDW3kOfph5Jb8q07\npq8/rxEPDC2ANYIt33VCEWNQY0At09pxaXfCS87tcmE6ZVJXdKnHusiyixgME2uZOcfU1RjriChY\ni6srokZcm3DkhaWaNkxcxc5kigO61Yq+z5uupmnyY9JgTCFPMiEiguitG8ZTJamlbNI4aa6omjKJ\nlgUS8jWy/j3E8jpFxRGj4nuPs8pLLtVovW6yMsrmg0cLsPuSx7j2ylcyq2dUpsKKAzEkBa+JLkXa\n6FklzzJ6lrFnEXqOvWcVAn3vCX0gdB2p7QldR+w7YgiZVGNAkiIx4gATlSopBE/yK9Sv0K5F+h7p\nAzYoEhXEgLOkykLjkNqRnEOtyQoIgoRIpcrMCXtTx6XdHV52+TIvv/oSXn71MR67dJW9+Q5NVReZ\nF1IhckXQmAghsgqRw+C50bbsLA6ZLI5wy2MWb6lOfVbbwH3v57nWCDcUNj2lvZ0mPE1AyhpmSnqK\nOAetTQDJ68op4hzuN+ymhoUiC5wiKeXNeGJDGxw01EygCTBJUSNrDWDY6edngqoMb2RNoMO1KSki\nG+/nlkdaE3sm7RHbQkDpNWG0aGvkdWFqa3anNbvNhN26YVbVWBH6lL/fqAokoiaSJkJKpNjTq5IM\niO9REn3XEvqe2jlq52iqCiNCDJEQIiEE6rrBGId1FWIsGAODhSWrhwAYMUV5LIQqg6zd+r7yMYNq\nOmWNkfXFGxtMkTO2FEWMFK13xDZxs/Oc9wmpDIIDHCYZSIqoYBK4pDRJUDUYLNbU1FXEWyXWYBRE\nlRQi0XtC3+NDTwielCKkhNE8jlOoEqS+pWuPWC0PaJdHrI4PSasO33k0pCyHNpNnqhziLK52RXah\nMpbpfMZuXXNlb4fHzu3x0ssXecXVa7zs8jWuXbrC3nwXTbBYLtk/Omb/+IjDxZLe+/zb8IHQB7oY\nWaXIkXoOQs9h7DgOnmV7tgPkg8d9Jk/ZeJw+mk1HhVAKkWStbNNcm04IJw2a5zCalEXktKkWOEWk\na9Iri6MWk9bm/U43linmr6RFCyGPobK+J6zXtLUxTFM2s6WyMA3r1K3m2pPjz08z9xH3ikDCia53\nvAYy0dWGvcmE3WbCrKqpxZ5suhLrTZmQNcAQIn1KLEPAo6iU7WEKWBRrDJOmprYVGhMxBGKMmalF\nEOfyYlRIMctZkSMtroQy5xPN8oQA1xvUcixv5tKp30GMcf18sPac/C50fQ8jMuwu7/fHP+I5cHPV\nc6EN2Cpv8itVnCYom7iQBpeXYNVQqcOoZaKQxGCdY1JVVK5CEFKMhODpo8dHn60TklMuHIJLgk2J\n1HccLfc5PLrBzYOnMPWE1fExcdWiPhY/FYgTjDNI5TDOYIrbatZMOD/f4bELF3jFlSu8z9VrvNfV\na7zs8hUu7Z1nZ7pDSnD95k2eOjjmrY+/k7c/8QRP3LjOYrmi73v8sif2gRADwSjRgXeQakM0wuLp\ng21/PfeXPAeNbTB7rn+ORdNTJRNlMWeuCS3p2tykxWyb/ZSDv/REkz1LSKeIc+P4CWGeudewCJHX\nK1M0zpMd+ekNwHC7k/uekHdKwx3TKfK8PXGO2DYiStCIVTCa/dyVEeZVzU7dMHMVFQaDIaQEKsXn\nnknGlp12AroQOGpb2uBRgdpZGmdo6opJk/06FqHvPH3vswwbA9YSilXEJcEai8kslq0rt5v4KQ3y\nxHJDcTXoYJ4d4go2CDYV60t++eALBTRl2S/mXB03dltHTJauFxbLSLKeWhNWDUbzRil/t3ljL2qx\nCpqKZc4YqmSZmJqpbbJrwijBBrwEoo0kYS0zFsGqYJKSqh7nGpyb4KopTb1Lu7Mgdh0aAylGYvKE\n6IkExAh17ZhOG3ZmMy7u7XHt4iVecuUyL798lZdfuspLLlzm4u45pnWDquFgseD6suWd+we85cYN\n3nLjaZ64cYODo2O6tiMse7T1EAIQEKPY2mCcwVaO7vCFrnkOWtrJgfJ3+OLT2ve4SWhJBxPupul2\ng7hE1zZyUjrl6xwWCVMWNgaCjieEvOmDPEVkks0fmNOBSAMG8+7azKusM2UHjTZPSZAzq96Jhsxt\nCX7Eg0dUJaZQFiOwxjKRit2qYrdqqDAkH+kTBKAPiaQCarBYDAZrLSkJfYos+45F3+eN4qRmPpkz\nn87Ymc6orEVDJHhP7z1iDLZuCAgxBHpRGqmpRKmsxYnJJDoshhQNMqWT39NJDND6X1RzcIkmtATA\nqZxs4ERM0TgMaFxrrFmkE8ZmzTONG7ytY2JnEBztIhABp4ZKLNZY3Hp3znotjAlCjOvvLtmE6RWp\nIiY7uPO6R7aQqRHUGFSEJELUHOyjSRCdMm8M1kyYT86TYo/ESAqe4Fv6bsVycUDXLTBG2ZlNuHTh\nHNeuXOKlV6/w2JUrXLt4mUt75zk33WXezGhsgw+Jw+WSJ27c4K1PPc1b92/yjuWSd6Ncrx1H0wk9\nQlILyWLpsX3C+p7U9jhT1vHj7bvi7yt5rgMfVFkbnuTkeNyIrt0kyhMyzebabMrNIw7aYI68TfnL\n39DsBuLMQTkn/qM8xunI13SiKp7MeTCnnrE4a3F+ymBS29i0r31IDOR46uR6XvlxoqGuCX7EVuAE\nKmNwMVEpTFSZAI2CjYlEYOkjYh29KovY42MiKRhjs6/dGJTsB115z7LvsNZQR4e1lqaucdZCSsTe\nk2IkJcU6C9bSx4jvO5w6kgFMTeVsjvgulpC1pYYsM6n4KimBZyImaxxSNONi+hVhLfMDTjaEG4Qp\nFiVrnpDWm80R28XczqiCJYQc5GjV4I3FWZcDFAuBGpRIIsaYzZwpm+i9eJLxdLbDJkixrH9AMjkw\nUq05CdJRRWKWKWOy9ioyZVLXOAO1AdFI6lf07THLusZ3M5pauLi3w7Url3j5S67x0qtXuXzhIud3\nzzFrZlS2QTDEqBytOt5zc5+3P/UUv/f0U7z9YJ93dUtuAMdNQycO7xqoAuJ6WLWYvkLbFYSe5HtS\nFwgrv7XvZcD9Jc9Bexw4QlgTYSZHTpFk/ptOAoROpatsjDtornBbAszHDCKJwaw1hO6fDeA57XeU\njesTqrImzXxWio9AyGqBchIuNGgH5coN7fJsGs1AmtbaP/iHPOKeMW1qZgKWSJUSTUhUnUdch0/K\nsbHEpHiEzghdCgQidWWYaY6wRoQkikfxqkSK6dXl71ZTylGOIRH7bPIyRlDJYfir4Fn5HhstWKgq\ne8oHO+y0Btk7wQlpZm2T/JeTILfsrpf1cxhMuCfBRloc9oZsxs631PUCPGJ7mJgKp5beF/lJEMTi\nbMBag6VEaEhWJ4ImYgolkA1Q8Pi8XkVFQ8z7rWzXRWxxHUiWR03ZH5+1U7LrQARnhUllmdeOiVVs\nMsxdw3z3HNX5Hc7vzXjJtcs8dvkSl86fZ2++y7SZUmmNhGyZya4Nz0G74qnjA544uM4Thzd4cnHE\nza5jkZTe1IRKSdKATZgqoNOe2HfQtcS+ha6FVUvot7+5u8/kCbH4X7Qwi6LFxLChYcbTptSBRAct\ndNNkSzHRqpSAHk5H2G7cfe3SOTFzDSknZUdP8RmcCvLJUqebFF3GEdnMAwXYTBk48YEaI2X8E+Ic\nCHNTSx41z+1iXtXsGLAacN7TaML1AZWW1odsqlVYqNKiRAPWGfbshAjZ9GkkW1DQnOdms0/G2vzT\n8n1Pm0BiQmNeuYyzRCMElC4l2pSokhBPxaUVZhODDOQomwYPWUcHk8r1UdfBPyAn7o2U1rxrjBTi\nzD7elHIKjAolNSuf9yN5bh2VClWCGJUUSlqdJmKKaDSEYX0qa9o6CVCVxEZQUUz59SGiccO1ZcsL\nBRAlhIDvPT54fFJSWU8ra9ipK5jV2NpRVTCvLfPdPc7vTbh25QIvfewqF8+fZ1JNMGogCr6LROOx\nDqLAMrQcLI+5vtjnqaMbPH10wP7ymONVSyeOaCowjpKRg60ViQGNgeiz1onviYsF8SEQz/tKnjHG\nHOVXfIA6aJ5kc22MkRTjKV9kTMUPqhsa6VknjwzPT7BJUiIn5AU5oENMDts2VrCYsuveDALS9S2G\nndxAtEPA00CKxpxokpnsN6a31jzNOmf0hNSz2XbT/zRie7AJajE4hEYsNTlwKIVEr55OhKUmjmJi\nRV5MJpOKOiQihiSGlBKt97R9DrEXDNbkogkxJNrYklJOfzJicE2DrSq8Kn1KmNrR1Ja6dlSTBlPZ\nbE7TvOks28OTSRvBaN5QGoSkKaeWpLQRpKtrq8wQ/AasNVQRwVpTZPDEapIjlPL/Md5q0RnxYOFD\nzFa0smlPSTDDekT+ztaKZNlVWTE5XapsnhJZY83EK3kdNAYRgy3JBEgipezPjL4lBE8XY0nJAg9I\nb5nEhtl8wqSZcXFvztXLe1y5vMfFC3uc29tjUjcQhRAUoqDJImpIAkEDve9YtUuOjo84ONxnf/8G\nBzdusuhi1jptg5oaJbtDhvchrkIqR0oNGgMymxH99tnzvpJnSAkfY/6CN4gzFf9jSnFNkGxEw24W\nRzhlsh20vdvEIBpjTj1OpbAU01SOBCoRtW5Tnd2oBFRIdNiFW2s2iHkgzoF8B3LVk/sU85oU4tzU\nLs9G2Y5Rt9uFCRGrSp2EqRiaYk7tgKjQobQKq6QsY8xmrGDpo+ITeIXgA8u2o/N+7Xe0YhAVQh9Y\nxZzG4hDqpsFYizhHCIFoBNvUNJOGpnFMK4MrPvz8u8hJ52JMzrtc78GK/KWTqO58vGiunPxmsj+r\n/AQGV4KxmWyzp2ttERKTfV2qiTDmIG8dXZd97GIs1glWUo6MLYVY1oFeoidLz8mOHyWnUQWJCBa1\nMVe0Kj7TLEORlAIxKmohuWxJcWRTvqaASRGTDBICFcLOZM7lczNeevUCV69eZDqbAELb9fhOSUGo\npKF2DjCkmIjJ47uOrl2yWh5zfHTE4vCQ1eEx7SrgTUOyAYwH67JV0QlSGUztEOfQusbYbGqRttva\n9zLgvmueIYQNr2LROvWkus9JGTHWQUODyfbENwmD1rleK0Q2yEvWpGmt3ag2VHwCmk1TYkBKtOQp\n3lLdMBHnOQ2pCHnc4usUk0225b2cDXVUSvWgwVe6nuqZQhDre40L1FYRE6LgVHDlbywbPA/0BnoR\nPJD1wFzKLiq0IbLocrj+ouvpfWAojZditp50MRG8xwFWhGAdofcYMfQo0RjqumG2M2fSOCpJWI2k\nNhCCYtRgxWHMGTlZ+zelRE7Cur6QUCwaWrSPrJXmqmoCpUCIkbz4isnveTMvNBXrz4jtwodAjAln\nsjUC8prknFtvygftc6gas85BLiZ+KxFDxBkHSTHWULmKyho0RUL0pCAErxipsKLUlTAngSQMidok\ndpzlwqTm6u6MK+cnnN9x7E4rprXDAm3b0fWRFC1Ga6hMDqoTSBqJvqNvl7SLBavFkna5olt2+FVP\nWAWCEaRyJQJYkdoBglhDLEUhxORKRtYJZjbb1teyxgMgzxPNk7XmGTeiAPWEhzYDeXRDm9sIXh08\nkkkhh2TI2hdprf3/2XvP5kayLE3zucrdoShCpKjq3pnZD/v//9N0V1WKCJIAXF119sO5DkbOijZb\n22imdfGYMZkRAZIg3HGPesUteW7Jdut2DQb7bVL7w6cteW5AIT0q3TZ6bfvarajjBihqnaoRlBog\niBiqGKzYG7KNrT74BuVba6WU/D1f/vf4jyIXsE3VqrRBhDVUDNVAMbqHtN7jqNhW8VeBKaa2lsgs\na6IIbSKhO8ZljZQKrghWKs45ljXqQVj1cPC+x3UdXd8TOocjIakoiX3NCB7n9RB6Hfw39Lh53dXX\nWm+cPQOqDYq5JUZFnNdvELSKM7DWULfn3UQ+oCjd6r2we/MouSmg2Ya1cOCdx4eAc45vtba3/eRr\n6BllxGJw4LVQ8t7ThYCzhpoSMRoSgkUI3nIYeqUf20oXYBfg0Fseho7Hfc9dH9gFyxCAvLBOI1UM\n85Io1dJ3R7q+p+96RY1LoaRIijPzPDKOI8s4sy6JmtEdLDqp2cCZ1mnXbK2DdpZSdayioiEOXOCt\n47smTxV4L9/mPjZY/y3xCE27c0P+vX79DSf4zX1hNhQQomM0zG23+O3YFrgBhhSVprJ628/8NgTB\nCojd6CxVu1XA3gRFYcviW4ep1JpX+otBb2JrLNXURpnR5PpHkYaqlIX36v5tI2VwbS9TdMKRBYq1\nFCzFtM4NTX7eK8euijDHSDTS9Jg1mYW+13FYFVIRSi7YIrqnktLuqRVbBC/CPnSkonrOPfaG3o21\nUpIqwDg8GIMPvqn/tPvxts+0GKdrC+cdzjtC6PDe3Ua2RYSUMjknSizUVKBUas5sgAKlxmwI3G8F\nP97j7ULPEm9c22carPd473Eu6DlnDNJE1JHWhTYpLBHVYHa27U2tJXhPCAGDosNtbvedszhjGYJj\n33uGznAcDHd7z8M+cL8P3A2BjkpaJ1JcWcYzJReKOFIB53fsBkfXd3hvtUkqK/M6cp0vnK8vnC8X\nLuPCshRSEjAe56RhCLYJSsVa385fi7FOVw1YrHE0SYe3vDDAd0fbqv6n8IpZgK17NLfxZqOrQevc\ngNuQzLR9zPZ1W61l2tJ749pt49VtB6mPrw3/0NJwO3xeN5tbbGOOTaoeMJXWg9xuzG1UTOsipXWP\nG7jCWe18b1wq0Y5Um9VvRCDKJtrwXt2/ZdgKphVLtQhZIFtDsUI2QsaQGgcO2a6XJsz4DaUKZxmG\nHbv9TrVrYyLPKzErII7WeZoKUhO2Ch6ltxQqhoI3R3aHHt/3rG5myZlUC1UMB4SD1xGuqhxtR4wm\nbdcF/DAwHPbs9juG3UDf9Yr4NYZcEsu6sswLcVmJS2S9XlmniqzxhjtoZaEiOv8McMZ/8tgSnff+\nBord9p3WqRweRj8qepbaKi15FsAiprwWSK0YrFWTay0ZKUU/54L1luA8+77n4dDxeAx8PHY8HDz7\nAIFEXlfWOLNOM9M4Y8KK9Ttc2OM7j/MdznuKVNZ1Yl2uXKcXvl6e+O38xO+XF75er1zmlbUAtsO4\nqp0nApJbXsiN8mWx3mG7gOk6xFuMc5T/S6f9nx/fWdt2G7Ly2vEZ8w3gAV4z5zcgB75Ngq8pbft3\na7Vacs7eRmkbAvb1Na3tQ8cCiN1WRa9j4fbIrUJ/xbBtz/31ud3+ii2BavdZcialjFTBWocPga4z\nWKd7pNtKd+OslnqzQ/tfO+D3+M8NW3V0KW2CkKuQjdUkKpArFAyFb+4Nsary08b0ekRZ6ALdfk/w\nnjgvjV6QWWPCYPBGVwlSweSqo6uUyDkhJTF4y+N+IIQeFzqytWor1UwKQh8I+Ne7U4RqwAZPdzyw\nPx05PT5yur9jf9zT9x0hBDCWnBLzMjONI/M4M18vXIIBU6g1IbFijL4GuqOSd7TtnyBcG7GG4JVW\nju6qlZ9Jmzo4BKetRgVjGhK7Ia+r5aYwVQVMURCn1KJFXs7U0swRakVyhuwwxeOK4KvgihZ4OU8s\n84XpeuY6zsRiwEW6HRwfjjg/4HyHGENMC5fxrBq51ye+nJ/57fzC18uVp+vEeVyZk1CMw4aA21Zh\nFqpkjFisEawRdT/yDnEqZ1mt5ZV89XbxfbVtncW4b1R+WopyVkH4moN0QYzUVy3P24LndUfzzXfF\nWPPNiPZ/tQ3bHv/tDLhV1doOcsto2xi2Ldu3cey2i/0j7xP4g6bktxO0yjKvxDXivOPu/p6TP2Gx\nOtblNYFuAKg/Jur3eKsQRO/RVnyJgWJN48lte0A0bzaOHa07ExrX2DRPzIYEN85jQsCEDtvVNpFQ\nAETaEOi1EHNCaqHzlpwKxnh8GAjDnrBfieVKShniSpcCzlq6hr6lVoxzdPsdpw+P3H/6wOnDA8f7\nO3b7HSF0NxGOUgr9ujDMB5ZpZDr3eG8xtmBMZbkKeY3qJiT63Mr73PbNQydsjuC9NgkbqrYh+qU1\nFxtuWke2up6qtw70NtbTx4kob7JEalypKREM+OChFMbLhfn5Ky8OvvSW3w6eD8fAw9Fx3BkMiWWe\nmOeFNas1GUEQPNhAwbDmxLLOXOcz5+sTT5evPJ1feDlfebmOjOPKslZKMojX94bzlmJqQ3oXkIIs\nkzq/iO70rW1WaK2Dfuv4rslTRwzmG4rK5idom4db6yqraHf4bbIz5jZ+3ZKcseaGKPvWY9Oa5sN5\ne0HbDvIGDmqZbhOdl3obfdGAFq9oWT1AMK8wfpr2qWz34x/AFBYRwzwvPH19aohfz/F0BMw3yfNb\nXSQab/Sd5/mWIQi0EVBwvr0prXLjGiG9VoHGjUPUx+OFCAAAIABJREFUD9YY1RK9OdOJqGZtTIpm\nrYJ1nm7Y4XzAGof3QSlYayStC2uMGClYA3HtSbGQYqX2Bt/v8LsViYrklZIYYqRzDusCwSp03w0d\nu7s7Hj5/4vHHzxwe7xgOe0LX4axjG++YWrF9wO06ul1H6DzGCdjaZNhgvUBcV72/ebfL+zOEgma0\nCQmhSTaiwgdVdKEktSJNSa2KuTUIqiZU2tqptaIYRb6WTMkJSsEaoesC+y6wTle+fHnh5cvvpOuV\nUBPHDj7dd/zlpzv+5ecH7k496xqZ15UsgwLoTMD4HqzX4nCNjPOVy3zhPJ25jBeu48Q4zsxjJC6V\ntIryQTGKJfABG0CkkFMkxpUc5dYdq3WaApukC41q9bbxfce222iziSXUWnFusz6yN4COcU3yjtcq\nf8tprx3kpuyzcTgbdcU0ZaH/p0LkNnHdkpfuA0ReCeTmDw/eMiTIN0ILt9Frfd3L1qo3a62VGCPj\nOOKcI+d8E0nI2153+xGtO1Ye6f8fL/J7/H8NsZZsAWdZrcE5TwKyCFXhq4qMbQXathOoslGpdLUg\npZJTJs0rhEpjZ9L3PaYfsE7BDjEXasrkqgOQWiqhCCkVruPMy8sVEUOmUowlAtGAQ0hGKAbwDuM8\noQv4w47Dwz2nD48cHu/oDntMH5BtJyTckrzxVqkIUvBlYEh7UlqptR1MxuBmx7ou1Jx4+6PpPbwT\nnKt0oeKD0lT0HDJQNm/ZtkLYRnZN6GI7Irf+YxPEMCiAzQVP3wc6bzkOPYOzXGriS0lM5xfGr0/k\neaIj8bR3XF9OpPUHPn9+wHlHNQG8x/gO1w34fsB2HdVASpFxmbhOV+Z5JqVMyZWchZSEFCtlrdRU\nMdXibKELnuAd1hmSVFzOTGVRPegYYY3YlCBG3G6HzP/FheFLraSYyM3GBpqpb9tiYrh1jbZ1mhvU\n59vdDu2xTQ3tllz1kbQu8dv8adCO8PVPoDeV3DwFFAW8HXTfdr23VCcOkVdZvU1OcOOX1go5V1LM\n5FTYdEOdtXjrlGJQtv7atMQp7ffYVJDe462ieku2lmJQuL6pZAzRGEX/NfUe5xv9qYFdKwKbyHau\nKpZtEskskAvOWkII7HZ7+qGnGsuaMus4U0Q1SLNoUi4iLDHxchkJ9ncu44zpPdkIc8okoHcO13f4\n3QDOY0PHcDww3N9x+vDA7nTA9b3+HilhS3MaqqJjrzbJQQq5FJJUxDv8bmCXjxgxhNAxXkbMaFmm\nxHvj+fYRfKXrMiGgoBksgsMbj8ESxSiFo2ErjDG42xnpVK6xmoa90A5UO1nP0A08nA7c7XfsOw8x\nYtPMaeh5CY5odMqyLDNpzJS0UKVwnSMPHz9wvD/Qd3v8cCDs93SHPX7oEEnEEhmXkct4ZVkjiMPZ\nHkNG5FXnWdaMTQVbCr5W+toRdoHqAtZXsk3UdVFU/DRjryN+N2D3B+RyfevL852TZy5qbJoiIDck\nqqUlDnnVpHUWNM19g25tcUuQxmCs/C+dYmsIzNY1vk5pRcw3O9T2798m0AbJ/4Yu1cBEujfYvnjb\nU75+bDq6QoqReZnJJRGCZxgGhYJvLOUbKql9O8uNBvMnGNv/U0e1ltU0/WVjsAWyMWSj3LfbWJ8m\nzegsueo6QMqrwIcxhpISGYMpFRsCYRi4Ox053d8TS+XpfEammVI1gW27q1LV6uw6zpSYGa4Tbugw\nvWfNSW/ZLtAdD/THA73z9F3P/u6e44dHDg/3+N2AWKOJsZZWDjZDd2km2E5tynLOpFJIVSjGYrqe\n/mSwzoPvwFpqjTj/nbGE7/EfRu8rnV+xToU1DA6RHmsc1Shtw7ZdpzWCMwqAc6LrB3BttNs6VF4V\nhnZ9z+l0x+Pdkc5AvF4I1tF5yxAsu85TvWUSWHPl+bwg7oVkO3I44U6eLuzxuyPd7oDrAhghxpXr\neOHl+YWnL8+sSwQxzGtlXgtrUmqXqYJNGRdVV9qlhMs9vu6QwREEgrFaZMYVYsRbi7t42O2Q9b+8\nq0ohpci6Lg3c4258tOD9bTSqiaQtv2+gnJYIdQPTRBBeDYhvo9xb5tOv2+ggwB9IxN88qdtnuQEj\npO0g9fHSUJVNl+W2s9we5xpUHCopLYzXMzlF9vuB0/FE13XaaZtmCWW+SdANZKui3e/l/VvGWos6\nVWwVVDFqTm0M1W4AjO0/erWcU7kxY9uioSrAxgLVpEZo7xiGjk+fP/Lphx8Yl4WlRMzLMylH1rjq\nyLapp8TGu1yXiFtWTHDYPmC9ZbcLdLsdh4c77j58YOcDnQuc7u85PD4w3B2xIVDgpgstVW7AOGnd\ns8UhQCqVNVfWVEipIhWs87jdnp3xjZscCb9/eavL8h4tgo94O2mxVi1VutYcdNjq8HQY6xQIZHR/\naW1tZ5tKw5QqjU6XqJvtnDHEUlljYZpVx3Y5XxmvI3FZqDmzmaLjHFU8c4U6V8w54e8LwwI7elyv\nUw8RYZknLucnvvzyK7/++z/4+99+YbxO5GKZsvAcKy9LYk2qSBJE8GsiLBU7QZ08adlRDz21UzER\nbwy2FkxacCWpP+3akePbLxa+b/Ks2pkt64JvnKVbmIY43biXsu0jv1EZ2naUG1qsIa+k6s7SNl7l\nNqJ9dWhR0XXnFDSxccu/BdlKhZIrKUdqU/pRLVtFfxnjWtI07Rxqz8NIA90aUlwZxxfO569Ya7k7\nfeL+/kTfeUrJ2t9uLeYfRrStk31Pnm8aKVc1xKYVOcrTQJxriEW95u421pcbt9g6uYHMqKV1eA5j\nwAfH4Xjgh59+4K//27/y9fmZ35+/KB2kZkpRapO6AmkCXYu6q7BGqoUw9Oz2PYfDwLDfcXp84P7z\nRwbv8c5zON2xO93h+pY4sybxWoq6t5TtfjUYVKlFEEqBmCrTkpjHGcmZYC2ddbh+oDeWfV4Z9se3\nuzDvAYC3CWtWjAhVPCKuIfUtlgCmxzWlnWoyGCVWlTZtKFJUXzyXG4IVaylkmCOWK8sYIa0sL1+5\n/P6V82VkTUmVqbwlHHZY2el7xDsWesbsmJIlmw7f7wm+p5ZCWiaef//Cr3/7hV///Vd+/fffeH4Z\nmTNM1TA7T7SO2OzwAtDVip0XbMmUEco6U+aeuB+QzmNLwVKxFKwkTCkUScj89ups35eqYiCXRFwW\npOuo/dA4jqqyY28j0aaGYdTj0luPJph6G7mmrBDpZVmIcaGWonulYY8PHcY4Nh4dKPjDWUWobaPW\nDbktTeqp5MoyrSzLRE4JY2A3DBxPJ/peDYJL4z+Vqgi1lBMpR1JamaeJX3/7lfP5hdPpnt3gOTaO\n3abUIgKb5YG6nyn6UUFx70T0t4xSGoTMmAbjt8hNbUiTpTWbaUCjV7UxrXWugTRqQ0EaihSsM4Sh\n4+7xnp/++hP//X//7wy//IN/+/f/Sd85vLMqjYb6fuoO1VBK03tWgKyOtZxnGPYcjycOdyf290d6\n77HG4fYDdI4MpJx0gtIQ5eSiVBZjcN4q2dx5vZclknNlmiPn80iKEe8du9CxDz2D8/S7HYfT6S0v\nzXsAKpVoQALWDBh7wHJE2GMZgAHBK/gMrzQjySCZKpEshYQl4RRBjkGKsOTMssxMU6EzhjyNLM9f\nmJ5/Zz6PzGsmCtSuw+89+90e6wPWe3b7Pf3xDnyH9R2hG+hCTzCGdc1cv154+vsXnn75yvVZaSlT\nsczWswYhWgUOIYYOg82VUCvEhORKrgmpaj1mh07XdaXqOsE5xOmAqLq3bzy+c/I05JSZ54lcMl3o\ncM4jRfB+aXJj3DpJHxzD0LcOVZOncwrUSDHy9ekrX79+ZZ5Gainsdzvu7u4Zhh3WeaxRH0XvAl2v\nOpDbmFYKr8IbbaeZc2WeFy4vF6bpCrVwf39HHwJ98Mr5KwqVjnFhXmbG6cr1euZyfuF6vXC5XqhV\nGDqLMZngDc69CnVLW5zJt61vg1z/3xl5v8d/XkiVNp2ATaWlbt6cVdGJ1hvd0W/Up9sEYeMbu9uI\n1BgD3hB2Hfv7Az/8/CP/8t/+BWzl4eHEYd+zGwLr0FEyeBfUa7EUPQCNBUvTH+057A/c3d1xPJ3Y\nHfZ0u0HvaQzVGWIp6laR0q0YdSiSzVZRKTfrCT5gfVCHDiw5CdO08nwemaYRRNgNA/f7Aw/7PTsf\n3jvPP0FkBJEekRPeHfHuiLV7DAPQAQHBUquhVDVup2QgqdAFBTGB6qFWp91hSqxLJMcFX6+QMvF6\nZnn5Srw+k5czUjOCxfeB4XTk7v6B/fFIPwz0XUcXAsN+R9919EH/3BmDKYb5PPHy5YX5slASWNcT\n+oFkHQuGvJkUVKX4GWMbaFOQUpCUKdeEjSth7anBko0gviOHQHGKOs91etNrA9+dqgLLPPP89IRz\njrRGXp6eVX2lGQNvSFhrFdp/OOzoug5QpGDXqzzVOF75xz/+wfPzV6RW+i6AqH7sNE2sa0LEcNgf\nubu75wgN8frqitiayNaFtkV60hsqrRGpmbiuxHVhDYZcM/M6sa5LS5oXzucXXs7PXM4vTNNITCve\nBw67wPnld46HA/vDPa4bMC5gzCYG8fqa0BCb8vbF0z91DGLwNICQUSWhIobckIuWihNDEBhaYk2m\nKBhD9O5VeUiHlKJiCQaVOesC+8OO+/sT55cjx8PA6bDjw8MJIxBjBbEsS9QkiNJKnFFMwLDrubs7\n8eHxkfu7O/p+0P1W64RrzphS1XKq2aF568DaG7/ZoWLgm5SlFnOGUoR1zVyuE0/PL6SUCN4z3t9T\nHgsPO0+174Cht45SO+AOZz8S3Anv9ljbpmxNEWY702xWEQWDV5yIeASPsbovzcUjJlOTkNLMfJmQ\ndaWuK+v5ifXyTF2uWCLOFkLvVOZx6Ai9ZxgC+33Hfr9nNwycDkeOxz0huGZvptObNWWmNZHE0B2O\nuDBw2N/RO48sK2mciHWmmkgW6Ju6m3OWmquOaaUiOSIpIn2H2w1EHyh9R9l5sm3YmDeO77zzLIzX\nC7/+8gsiwjB8ZV0jT1+fuVzGJmmnMntdF9jvd+z3e7ouNK/Pwm6/Y7/fEePK09cnYlx5fLxn/+kT\n3ntyylyvL/zjl19Z5pXPn3/gX//lX9lsyjAG70KzIpNmd9Ysl6rKkQVrGLqAVAWDr8uoUlRx5Dqe\nuY5nXs4vnF+eeWkd5zxPKq2GMPQ9X7xj6HpyKnz64S/cPX5i2J2w3mGMvYnhb4du09f6ni//e/wH\ncWct1lhmY0hUCmpFlo12cIMNDEY4ook2ipC/Ga1aazCiLiYbuluTk8o2SlUQR/CW3dDz+HCipMSu\n6xmnlWmK5JxZVyGXDFbNjEOn4/8Pj/d8/vSB+7s7Qgjqi5hrE2rIYEz7u6zVmfNKZTEgRg/TYlR7\nxtaqVX+VBiKpLGvifBl5OZ8xGMZpJcZMfDiy/gkAGf/0IXus+UBwn3H2gDVdo7hVjC1gdK+tJtkG\nVw3eGoJTjdrOd6zV4WshlUKMibwmTKmUZSFfL+TrhTJdYLlg84Izhb63HPvAruuwtVCuL8x5wZc7\n9t5w93jHD58eeLzfEzqDmKoFqK1EB6Vz2NOBftjT3X2g+/CZyXh4eiL++rtiDcZZefDG4J3VVZoV\nkIIpGVcFqRkDRN/B0EF/pOwHamcaD/tt4zu7qlSmeeTrl9+JMeG95+Xlwr/9z7/x5fev5JwbkMiz\n2+1aotzjvSNnHZfudgOHw55aC+M4EoJH6v/G3fHI0PdkU3h+fubvf/sb1+uI1MrD/T390CuAsmS6\nMLT9kgI21J4pU2sCyRgK1lTEFFKceH6aKXVlnM9cLs+8nJ85n595fnnicr4wLzOlZLX4cRbJO16a\nAfK6JtaYiLlw/1jZHe7woWdDBBtj2eyJ/wwSU//McWyCGwXBNWS1TvW1U/PGMhg4GhgEplIZayUb\nHX8iWvg5a8htp16ruqmkGFmXmbTOIJVh6Hh8uKNzntNh5MuXF5Az0zzf/GKNga73HE87Hh/v+Pjx\nkQ+Pj5yOR1VAKmpEoCIcRacazaEH1MAbkRugyYjDVFWasVjtUptgSS6FmDLjtPDyojKA46y+pCXr\n4fUebxspeXLeIWEPdQfGNZGDrNKKVvW7FY9okWrVD7MagnOkGgji8M1b1ogl2gVXKqwr5XqhnJ+Q\n5YpNE1YSnYeheobi6XOkxEQqiewsdTzT1QT3JwYLQ3AEb8GpsMgKrNYQu4BYjz3c0X/8yOHTD1gs\n+yL484gNHWItBaN4A2sQp8/bVFEHoqI6u4LFdoKtFiEgYYfsAsT/4lSVWpVk+/LywrIshNDx8nzm\n6ekrT89P5JhwDYXbDxP9pafrAoLKneWcmvC7oRQ9kHb7gZIS1MqPP/7IYb9nnmfiupJzotZCzpFp\nvBLXVb93P9B1HV3X4d1m0JooZSHFiWW5ME8jcV3IeSWXSIwT0/zCOF+4XF64Xq9cr1cd1cZIFcE7\nR993OIQRQy3CGhPTsvJyHfnx55nPP/6V4+mR0PWN3qLI3eZY9z1f/vf4DyKgb4ClVjojLOjYtDaw\nkKvCYAyDwE6MgigoVPs61TDtQ3WMdRSfUyatkWWamMYJKYXdsOPx4QPH3Z79bkfJhWleCN5irGAd\nhD5wOh34/PkjP/74ic+fP3J3f2I3DI2iVdTPEO2YjbFI4w2rP6yqeFln1cqsZGpWIW1njXYfORFT\nIuXcjOeFGDPjNLPEpDxsETr79pZP/+zx8pJ5eVmQsrDfqSKQdSobZK3c6H3WNtS3UcpVteCqxYrS\nAYsVxFSqMwTjMQXMGmG8Us/PsJxxdcWbgvVA9ZS6kNdASomYVrJUlr6HeeHgA4e+53Q48vj4kX63\nZ14Tq1im6rgWx1oqsVjSWojXhYhhWRSsVnPzk20cPmOt0vlce08JCnirAqlQlghLxMSMqwZxger7\nN7463zl5phQbqmtknhe8j0zz1HY0r4LpWq1XVllJKaswdcms60KMyhNNKVJq5bjfYwRKzszTzIcP\nn8hZQRMbry1nBSmJKOJQk7N2sHoQQU4r03jmev3C+fyF6+XMNI4sy1WtdNaRZb2yLCPzMrPMC8uy\nkJKaIAuAU1KxlExaZ3IujPPCy+XK0/OZeclquWM7js7T+aAyEDfRhffO8y3DUgkiDAirCNEo57OK\n4KzQAT2Ovu09N+H0XE3jKm9yadI4xook34Bwy7wwXUdyLuyGgcfHB2ou9F3POOq+MQRL13tccByO\nez5//sjPP//IX//6M58+feBw2BNCUFHwWlWhy2660TpNyaiFUymaEK3o7rWm5i2LwTsFyKWUiSmp\nUMM3vOg1JpYY9etrZd+9/eH0zx7XMfJyHjHmrAWW3+Hxf5D4/APXvXGSFXxmEHEUsTjAi2CdwZqA\nF6tOKeuKmUeYR6ysGJMxHkqEdXIUa9Q1qjR7PGPI44StYI3jdPfIh08/4QeYlsJ5SpyXynmFOVaC\nJLp0IYyFLPB8HUnjQlkiErfuUlcJ3lpFs2Pa76WIc0kJu6zYccLvB+q8wwzh1TPkDeO7Js/xOjZt\nw6jVS86sq37eEpu1G0/TYGwzarUGqQXnnL6x16i0AoGUC89PLzgM0zhzPP4dqZXreKXrAofDgY+f\nPuKDo+86nHcYK+SyMC+ZlC6UHJmnkfH8zMvzV84vT8zTtXWfMyktpLgQ08KyzCzLTFyjajS2EZl3\njuC8qnmUSpVMLUJaVp5fLjyfR4wfON5/YLc/0Q97QhgQlCJB25+9x9tGQNgbQ5Em9o7KZDip7HDs\nROiqrmPYXHFcS04Iru0ddYeu04jdMLDf77DGEteIAMOwx+JwxrAbBq7Xia9Pz5wuI0UEGwIfPnzg\nL3/5iX/917/y008/8nB/R9/3zTatcUMbmMkY15JnbWAgbt2nGA9OwRcmKpBOvKU0g+7SgEYpJlLK\nt/s6l4ph4ewcyce3vCzvAVgfEFMpdaaIV/EWOh3ftrPTorJ9TZyNiqr3NAkZDK45T9EARYGN72Eq\nOp4vBVczzmTlCDsUcY650QoRpe3NXPjifqULe+5Pnxj6e4b7kecl8re/f+Hr14nLNbPGQlhXRpMw\n5qyda4zEecYukZALvug9Ss5Uydiq4gkqzyvNb7cgstD7gFyv1F2gdpaU1ze+Ot85eV4uZ6Zx0jdq\nykjNpJh0V+g9tSof0/vQOJs7DseDqg8ZIa4Lfd/TdR3zPFCrOlqklPnt9y98fXq66cPWWrm7O3J3\nd+KHHz9zd3/H/e6OYehex7DTlbjOjOOZy8sz1/Mz18sL83Qlx4WUVqjlRmSvTc2/5kJt3DlvLd55\nvO8IXYe3DkcDjJRCyZXzeMUumcPpFz7/8IXHxx+4u//IMGiyzEnlAUv+E5RP/8QhphKsUy/DTU4R\nQAoew14KOwyhebFudJRN3EMMlCq6VywFEeiC5+H+jseHB7quI+eCNZY+7Oh9Tx88Xej4+vDM/f0d\n47zgusBuf+Dnv/yFv/71Z3768Qc+PD4wdJ26SNT8jRj9JvqtVBkp5g8d5Pb/pgo1V6RkNTCoVoVB\nihp/q3RmaoVp0eTfuucYI/VPsFP6Z4/jYcewd5iQwa6qV2sadcp4vPE4oyN8RFXLKoXc7B21K1Ve\nsIrCZyUzGad/bz3WBYwLODKmZl0BFNXBNa0LtKiYhxihxsr4dOEf8jc6fyJGT3f/yDXDL88Xfvv7\nE9PzQs6VTKKWTM4rpajwgtSCyxmXEqHoZ5OT6t7W1ABDinK3gK1VxRGmkdoZSmconcXU/+IiCc8v\nL5zPui+c57l5GgrBe4Z+IGU9cKwB7x1dCDhj8U4ramssXdcx9IMis4p2rCUl5mWlNrSrc7YJExx1\nrJZWFTIuKzkVlnVkHJ+ZxgvX65nr5UWpJuOFuE7EdUaKXmjFbghSlHBuRPDG6t6ozeed8zgXcNaD\nsZRqb56QuTbQRZrUhmcamZdFq/tWEeami1rKe/J80zDgEfXI3Pi4TcLMGcPJGPYidFjWKljAm2Zs\n3WzJjFQdP7Vx7Tb9OJ2OOGtZl1XvewFnw01pq+879rsd93cn+t2e0/09//Kvf+Hnn3/m8eGewzBg\nraHmRJFXmUljNq3HZkzQ/EH1ntLfwRirIiBFrdVKUWUhqehapOj4dp4XYus+NyQ4FTU6eL813zxO\npyP7fa9doy04U7AUnBWCtQTn8EaNsFX2s4m6tEupa6E22UMtvUyt1Ipq9hhPsQHrAqVGvAm3FQSy\nCYhwcxXy6D1XpoVzfuLf3P9kXA3++MBqPZc1cz5fSOcrZAWylbSQ4nyT+7NG8IDNCZ+iInxLRMqK\nkQxkTNVGhapJlJzwgJ8dbgyw7/XXeuP4rsnz/PLC71+/8PvvX6ilcDgccc6z3+9w1jNPM8uyYpzD\nG5CcWKfCfBVKzW2XGSklg1ScgSLqSuK9wwTL0HfsdwPH04HPnz7w4fFEHwwpXnl5yohkpunM5fLE\neL0wjgoOWpaZkiMlrU2eT0+X3IS1KYJpPEDxHmta92EsxnoVWaiixsRYLB3VuOZ0XqhV9w25QCrq\nwVfa2C0rLPLdueKNwxjdBQVVXVQDbAPBWrw1nAQOjViUW9LsjBAMpFJ0dCtKA5FaMV4VhHa7nqHv\nqVWYxgnrPLUoD1NqZl1WSi4Eb7m7O/IQOu4fH/n5px/59PEDu75vRRxgLeJU+Qjcq+gHkEtumIBI\nzkWRmNbfeJ2bVVolY21BKsSYSTkT16TI8DVSclWko21Um8qrF+57vFkcDnv2+z1Skk5IMHhjVE7R\nWTpnGuFNC30xFWtVTtJZ8KLm6b6AUJhLQnLSpAYk44gmYExH74oS6KRqx3cDzm0a4YKj5axSyUvk\n669feJoy7E4w7CnGENeIjQsmRkxcMHnFlNg8R0XBbCKYkrE5a9dZEtQEVZkPsiVPaIpsgi0GmzPE\nCDk3Rbm3je+aPGPWN+e6rOSkzgDDMBB8h7cgtVndWIOVHimJZck6Toqrct/QZGkMWKfUkOADzg3s\ndj2n44H7+xP390ce7o883B8wrIznr4znTFwX5vnM9XpmGi/M00ROkdpUjQxN7UfaHraNvazc9Frw\nThOmEtRVTg3jMLbD2B5jO8R6qrFUFwi9wZuA7/aIcVRR0e5c1SdUxej1kHqPtwsjurP0bSKwM7o7\n6i04YzgIhCJU+2q+7g34dg1LbvZy1jY1LIdzVgs7Y8kpMU0z1m6dpyFGwzJPxLioHORuYDgc+Pjh\nA48P9xwPe0WDl2YlZq2KukszKWhcZf35OnqNMTavXNcEkMyNMrPG3DAGigbPuXyTOBtAbwOwVX2O\nUqG+T0XePHa7PcfdnpwiwaqcozMWby3BGnzr5KwAtiJG8AbVRhb1Ei4NhpNMwVft6gxQjSOZQPYD\nxq1YqTjUmcUUg0jRc7etC9y2rhCDc4GEZ0mZ9TpTI9glK4itJGyacXHBxBlKxKsECNtexKITGylF\nC8+S9c/SaFXSJFxFZfwwylCopSV4Y/8Udo7fNXnu9wdOp5Vh2HGJievlyjLNdCFgMaRlosRFUV2x\nQ5yKHsQ1KsorJR3fOtXotNYz7Hp2u4Hj8cj9/YmHhzvujnuGIdB3Dkvhev5KKZGSIjHOOppdZnUn\nT7GRzEEVV4Qqpaly1FdEY9svWaOzfmMttWayCFiL7zq64UTX3+G7A7HAOK+Ymtgf93T9jsPpAR86\nHX9UUdFuXpNnfa/u3zY2ucQqSjJH2BuLWIsVYVBJdWKpRGfJaBHnRBGtVQSLVYUVG+iCx3tHyVq0\nrUtPLYKzmryc1Y5gXRZSTJScsT4w9Nqpdp1X3hzQRJobPdgiopV2abvVkiuxgX1yLk3q0TZNZRUC\nWWJinhfWmNRXN6nTxjwt2q2m5k/7WuRrF2rMa+X/Hm8WfdezG45UH7EiBGdwxuMw2A1UA83DU1cP\n2/S9iMGJcn+loa3VN9khJoDtMX6PuBkbdLKnNo0FrCKxBZV8tBuSt0IxjuR7YugpuxN2d8T3Okkk\nJaQkJCVKWvASMZKwUnS9gd6btMRppDlL1aqjF01IAAAgAElEQVR4Fqm64297fRGoRjR5WgW9SXDY\nocMP4f/9xftPiO+aPO8f7nHe8cMPn1mXmZenJ1JMDF2HM0YTWS4UZ1nmEecCpYoCdIp+5JIxRfBi\nCZ2l7wMPj/d8/PjI4+MDD/cndr1C+VOcmMcL18sz83QhxYWSIlITUnWshaibeq3yetDUckugpjEw\nb/us5sBdqyLQskAInv3dA8e7Twz7B4wbuIwr1/UFrKHveo6nO/aHE9b5tn9oP0NoQviba8d7vFW4\n9g6tDTBkDQ0aoUo/VoQisACXWlm9SpAZjHqyCs0fces4teiKMTKOV4LvkEFwzquEGsrPW5eJdZlV\nJMS65tQCm56zNZtN3yswaQMCiShaNjUQXs6vBu0bIKiUSq6ZZYlM06wcznklrgmwxJgYx4lc9Gtr\n279vXra1HXTv8bbh8PTdAD5AcxcxjZlQqzSLMe3EvFNMxtYQFFGEeGrUJWtNU6DqcGGHC0dct+C6\nFVNUCUtipYgCO8Wo+ILU9jMrSn1xPak/UI93DJ9+IDw8Yn0HayJfXljiRBZ9rtVUggNblOZ1c8Sq\nmjyhJVM2j+bXZkIaGKYUpTQmA8UY8A7bBfzw9lSq75o8H+7uebi74/ryzHS58PLlK8s0UtYF71So\n2BhIUZVevC+apMq2H1R9W6mV0PX0Q8/heFC+5n4geEfJiams5LSwTBdenr9yvTyzLhMlR4yUVnUJ\nzupnoHl+vtqfSau8dH+pn6m6A6oAzuK6jt3+wP3Hz/z01//Gw4efqCZwua5c5idSVsmzUA1DzuSm\n1iJFE7czIMZQTCM1y3vyfMuwegsgTZcTmjxeMxnOFBYRXqTy7GAWQ3UO4wAprZI3r6hEa6hSmOeJ\n6/VK3+/wPuieOxct4kpS6lNUqL1zTpOvda/7K5r+fBtN2WooplmKNYBQypo4S217eGOaf6wmw5gy\nMUWWZWG8jpzPF+ZpvR28l8uVdV3bvrMdWq9Ykfd7808QtQpUvbbGGqVtoOdjpmAcOBQc5gx4Z26g\ncSsKeiyt3MMaNQroB/xwpNuvhDlSk35Pmxxb8VZEaVfGZKy1FFxbS3XksEPuHuk/fObwl79w+PgJ\noTJ9fSKtk04RjYKXvJLa26SmCb9v1Jdvdprtf/S/zUlLKauyNbxq77h1rLXqe/eN47smz8N+4P7u\nxDpeef79N375939jfBHSulKdmglb51hjpIrB+6obyJawyiakgOC8Svjt93v6Qc2mx+nK5ZyI66Q8\nzVH3mss8ISVhrd5QXbAEv40utmrHNKsppR9U0UrLIGSpiKjcVa0KDBJrOYYD++NHfvr5f/Df/8f/\nweOnH3k+j4zz34hxZZ4nxusF7wLOQOcd8e5EzStGCs40Q2XTOgzeD6i3DIfDWjBWk04xOm2wbUSa\njeVK5sUIX2ohOafADavgfaXXbeLcus+uOTONmqz2+yN9N+C8J6eVFFfSOhOjim1YY5Wm5bzu1dnU\np6xaMW3yjW3FoB2iioCkrFMZQZp+snarWnwWUiqsa2RZVqZp4vn5hetlbNq7MI4T87yQm9LQ5hID\nm4Xfe+/51pFTIeei+8ZGGSm1EpOCvzRpSgOTSSvgUBEF0UkZpTbLMjA+4Icd/SHT3xX6XLT4cha7\neIzZ3KCADEaS0lN8R7Udye1gf0//8UcOP/7Mw1/+heOHR+b5yjReWY2QHBQLnTVIVg4ppWBa0tvc\npXSVVZVCY75xnWpn8eZEVdsY2iD6PdaEWSLW/RcHDOW40odHHu/v+OHjRz59fGSdrszTfNv/iWg1\nXVMkldIIwAqywaDo1zb3ts62TjWS00ItmbjMLPPEeD2zzCO5cTV1SmGpfhtlQK3bUFZunLnXScFW\n+egQoVajNj5iialiXKDbOyoD1h1w4YCxPTFfuI4j58tFE/c06kKbyq7vWOeRHFdqjkiJWhiktWHJ\n37l0bxnWqlqPennKrWvTos2y1sqCMFGZrSDe4L3BeKuw/bZzqqWoN21RtOF0uXINPecw4ETpK1UK\nKa1tXKv+m9Z5vPe45tEJNJPs10Om5c2W0LT6Lm1HpIWfSu8Z20Z5ksm1EnNiWSLzNHO5XLmcL1wu\n48YAYJ7XG0r3dX2g3S3mBup9jzcMFb1Qk3Zj2tifNrVCVXlquy9aq6Yo7cZscgIYpTCJAXFACNjd\njnDKdLmQqlC8wzgt5bcVAAB5xljA98hwoO7uCPefGT79xOnzTzx8+IH9aUcpkVwLa15IkrBtpGMF\nnBhMrdAQtLrz1D3ntka7jW1t83em/U6vxGsQUXTuvOCu058CL/Jdk+fX33/jtN9hpHB33POXHz9j\nSuL56ZlxmpRjVhTcULI0OHNGS3rz2hFarabXNTLPE+s63ZJnyYllnpmnqxr7OkPfgBtmAwQVIUml\nFJU1g2ZJ1g6jjSNfmyFxrkKtFowH0xGTjs7GufJyjvzy25mw+42vLyu/f/2df/vb33l6+so8b5xR\n7WDG3Y64TMRlIq0TcZ4opbAsK95aSG+vkvFPHc6qKLWoq0kWHdfnBiKLIkQjVKc2YxIMvncEaxBR\nKH/JtZX1jporeU7M9cpLFnwR6rKy2+/wnfqG5hTJNWOswzg1qXbON8rTNg3Rw8MKjT7y7S5IP6sh\nd9uN2u1I1b1ozokYE8sauVxnzpeJ6zgzjvOtq1yWSIyaxDe0rb1JLQt/Cv2zf/ZoneC2YjINDStG\ncGKotw+aAIEmSdvQ4hvDE/QaZ4TiBHqH2e/wtdJZiF6l+CqQqzYORlSIvVIQ3+H293QffmL36UdO\nH37kdP+oPsoiSJzJy5W4XKl5wVObJKCKHJgmjiC1ucCI9rd/0CVp5FT9+5ZEWwOFCKZmXDb4dUUu\n403p7S3juybPX/7xd/ad6hAGZ/n4+IDkSOcsL5fAdZxYYiLmSi7SKB16sbfCQ9CFd8qJeZlxZ3C2\nUor6b5acWZeFZVqopeB3A94H7SpEK51ciqr1G8FkHW+IvB4229hNKQDtolnUG9E4xFpydUxz5evT\nRLW/s2RHv+s5j2d++/0L58uFuC5IyZSUWSdhHi9cXp45P33h6293SIqNYxfZDwNpeXtD13/mKM5S\nnFUtZVGJPmMMyYBYS3XqhxmcZd8ZCI4hKM9OpLmnNB/QmitVHKUUVbNaEz4W8nXidH/H7rDDdZ6C\nyvvhlXLgvMM6dxtDbYdGrRs0yd7eC0ZeheidfXXnMVLUH7ZWSs0qAJ8y13Hmep24XiamaWVZ062L\nzTk3WUEtJDFWReWt1W7jfaPw5lEpVF41wI1IE1BXCkpB79lclTueb4C3ZtSOasXXWsgbvclA7Qxm\nH3DscUbRurqnNFTxiO2oNkAYyDWSvaXr79jdfWT34UcOD5/UnN07JE+U+Uoen6nzGZMWghSCCB6D\nEZX4U0xJuZ272CYy0nb1bB200enLtrLYAEUWkKx81zrOpPxfPHn+9suv9NbSB0/JieAsd8cDtSSc\nN+x2A9OaWGJmTZmUNdHVWpsiT7l1hzEpgtGYyvHQq+xeQlWGpLa6W5p+rvKA7O0UKBiquhFsThiY\ndmC0PVLSn2Wtw4VA6AbCsMe4gZRgjRCL5ellZopfuMyZft8jKOncWVVGqs3ctZbM0na9/+YMcZ7Y\n7/eUnKm18sOnT0zT/D1f/vf4DyJ6S/K2ASsUVS3WYbsBvMNLYbDCnYfgXxOebYjtbA2zFJYqlAo1\n6b68s4KkyhILdZyo40Q8HQi7ATqPHdTg1+UCGOWH3jpPfW7qDcrNh3Yr1V2Th9wOpFoqVUob52rx\nmUthWRPTqHZj55eRZUmU3LrMqnzP2+oCPaSstdQGhGoD3Pd4wyg1UynQeMKIoRqhAFkMsQjW1JYA\n1cvTN6ELU43e17kQYySmQqxCMgbxDtNbIGAYlOteDcYEnNtRuz0MA3V9ocaJIpXanXDdkdAf6YY9\nfugxoaphdRwx8xU/XbHLTAcE0e5Xx8GKE2bTj94AafYVHUw7k2+7T3i97zcUOhZJEbssqon7xvF9\n5fmenxicofcO15CDzlmO+x3eWw65Mq2ZeU1MS5O1q4WcM8uyskY1Cxa07VdbM8v9aeB42JOiom3N\nrJQBwZDbeNdaq1U0GyVFbpW6c+5W2ZRiyElQP2FD13u6YU8/HNgdT7huxxoFMxWmKbOsmSWOjEti\nOHQMe08IBu88uUn4idmS58jvtbBMV77+9it934FAFwIS55vM2nu8TSQH0avkItZrxRsCZj/guo7B\nKM7POdhb9V+98dOk6njXWhKVXCo5qwqLGFWSz2ukTjMyLeRxojsc8HcHfBU1K97pvemdvd2T365y\ntgR6G2EJWtx5Ry22dZuFXKJSvLDkqhQWHdlOnM8jU+N1bgC5rWCsLQFrIblV/tuY8D3eOmKOpKqF\nuZoAAKrBQ5KGAmqMBWs3HrGic50xlNzs8WIipUKqIMZCsCq+YSxOArYKtli86VXYZX+krjvyeiCN\nZ2xOuGGP83uC63DB83+y9+7BtqbbWddvvJfv++aca629dl/OJcQQuSRFIQlqYS5oUKKAgphSS1KJ\nCZSikTIlsbyUlEAVlgawtKCUgj+QAo2Q0kJKLQ0YLVIQy1giIgZBEzAh13N6d+/e6zLnd3kvwz/G\n+821u3O6+/Q5Z/Xap3s+XbvXZa71zbnmfOc73jHGM57HRYf3GZUFVyf8vCdMB8K8EMTmUFUVvJWW\nCd6qetXY3VaNLU36z9pzlmTqMQtdZ02Pc1NtfFCXGXkBRDzuNXiKqqn5LHqkUVvwEjZDT6jgY0EZ\nWVICCXTdBnHC3GTH5tmUhkwlxTattWxVpJUEMANg9doWT6NQIrZYAHH+aBpck+l/VlWWxfqtOZlC\nS4gR5zZ0/Tnb3SO6zZZN8QybymZbmGc71S95YRonICC7eBwCBsgpsUwzyY0s02ii89PB5LY2GzZ9\nQMtCSg+/AD7KWDykILhqjSIngtsOhIsz4tA3F4pCJ5hGbErUJVlQzAVKxeVyHE7PteIR1AxjkQpQ\n0Wps8lSMQV5FiMNA5yN96OhjJPqmUQo0ZQQrDbdKzPpRdeUemjRgrcVKr22T0WpjKtM0N6atzXiu\nVZz13xogpWn0Pt9v4pRzvhC4nSdup5GuU6ILhCYCX8WYIetsr1qnC60CxTTTIkrJSk0K2RxKPKaH\ni7fg5gVzLskeKT3Vd8hmC3lLWTpy2iDjObVkutAxnF/gu0gIEEIleMVFofcQqYRq7ixOjDmOiGWc\noaMUk75EzD7PdNqkjaoIrpH17iidTcmNO7cjWl/eyHIP7/pzr8Fzs9nQdz15Glmm2VQkHHR9xHlP\n9A4Vh8iBWjLBey4udmy2G3IuzLNln/MyNxHrBe9bSanaxlJKOb7XvQ/H8unaGzoKZWNVApM1a2LZ\nWZnnSs4V1FGro68RJeJcj48D/bBlcB3bbQSJaHXs9weevPGEq5s3qbmQZrWh4FLIKTEdRsbDASeQ\n+w7vlKEzBZqXX77k5ceP2W16Xt8/u8+n/4T3QHWQnR24nADe484HwuMt3W7bpM9aqTNn8jgzJ3Oe\nSKkguUBbR6VCqvZ2TyKoM6k/X8FlYMqozBQnhI2xcIfYsekHuthZ5tnGRIy4I6ySZKUUW7ctgL7l\n35EcYF6IqkpOuelGTyzzwrwsrSzbhs5VnwvEa9UGGyFoDN9T+Hx43I4jV4c921LZhh7xAXHexAOc\neaQkEVJVclayNN5IUQataCroorgseA10zlODpwvCgDJKJdSKSyDJo84TvSDSMy+BlAaGaqMy0Tn6\n4BgGT4hK5yubCDIEboeOoe9aRW25q16YdiVFARmgeJBsffy0WJisLQNVNcZ66/UfF6CYrRptNr62\nhkLVD7mrytAP9oSmhXnMzIuVXWMfCNGjRcl5odaMYD0X76DvPF3nCQH6PjDNnhg9yxxBKzFEO0HX\nNcUHC5JrCc5ZqVctIz2+AN6BFpRCLollKaQEpVrfS6NnXpRpruwPC8Q9qSix2xDDhrPdlu3unIuL\nM5SE1pk5jZRlIeVEWWbyYkzHeZqNsFQzfReQRxdsNz2vvPSYj736CiUt3N5e3efTf8J7IKuyUAki\neO/wQ4BNQLYROeusHFYKHpAccKXYplUq5EJdMloAFYoqubFsFhWWqni1TMHV5ryyJGpw1JyJznSe\nu+65wLmmf2qDerVYC8OCprZMcw2a5o6xrn0a+W1pknyHw4HxMLI0OUoLmHDX43wrg9fGOk2KTdEm\nnXbCQ2I/L+ynGSeeDsfA3SxvFSF5+9xlx+SEefEk78lOzGu2FHQpuCIEdQTx9OIQD+qqmb1XwWfw\nxaHVE/qI99BlRy4dznm6EAmidJrofWXTQx+VIXqCdpxtB853O/bbDfMyU1OyGXZZ2w60eU0zNxBR\nnFdjKcldD/RuTbY12JKedRRnTYhq0yB/aNxr8PQuEHxkaRT8lBZ87IldpOsiy2FkHPeUNLcTj5Lm\nA/vbcgx6oHTREfxA6TsEoYvBZtuaIbATR6HcbRLPvRDeV5zEux6osxdsJVeYKINpC6WsyJzRqz2H\necE9fYrvPMOw5eL8kk98onJ2tuXifGCZLyhpz/VN4XY/MR8OpGVhmWwAHoScYBEbpwnesdtseOnx\nIy4fnfPk05/m2dPX7/PpP+E9oDSKPxY8ghdKEEoUsrfyqkrzT0QRb9Zz68HMvDGtp1OqklvmNivM\nVYgCBfAtQxRv+qPBe7q+p+t7fAjWutKVXdvcdpoWcsnZ5k5bH2j17LQZ0Goi8mKM4ZQKh3Hi5uaW\nq6trbm/35LS2O6zce/x9nhNhgOPnx/+vKlgnPBiMQLlWF6xyJs2YeqmFicqCHaK8wkaERYTiHXhh\nI0ItghR3XMO+KgElONj0jo0zY4RQLYmIg8NHR64DuZpdWR8jvReiZAaX6STT6cI2VIJ0nO92PH78\nmP3FBTpNLDlTi1Xj1jWkKxOutlEGF0Bt5AuKGXNQj4GycYbt7+aOHrKydf2HPXhypNzbmzP40PqK\nAecdKS3M84RzsNvZRmIE2WQVcbGA57yVwYauQ3A2q6mKdwEnNieXcznODdXWGwWs0O7bQC4cM1Na\n/R1nG5rNhELKhTJOMI0sZaZQ2GwGHl1cE7xwcb5BuCD4Sh8Ep4Uyz8zjZH3OlJpurhACxODou57t\nZsPZ2Y7zszN22w2fyolnV6ey7UPCBBHsFC/tIGz6xQVPtRKRKN75to5ckx8TljYPXLT1MbExgtLm\n6cxcydlwuojpkAqELhD7nth3hBjBOzMvrtUOhFi2u/Y7SyltlATWmYVVg9ZmoR0iRraY54X97YHr\n6xuurq45HMZmQvDWbFN1naVbA2TzM1WbK0Xt1F95eEbjRxk5l+P0wWpaUVWNb5EW9iVxyImcC+TK\nplQWoAaH7yN0HeoH1A/W06fiA3QKncOIZ8HM3n2tLBlcrLhg8wkiERciXezoo2MIHZ1kQl0IGTau\n4KVjt9tx8eiCi0eXTFfXLLe39gc01ypqObpVidoerGJzzuLskFglH6VYabZoAFT7fM00BTsohBfg\nYHevwXOcZ4Zg4yB9N7AZeuJgATQXo8qH4E1I/eyMzWYg9gHxMM8z4zSyPCd+XUvCu0D0EcERfWC1\nyem7wTYC0ZbyaztA2+lGxFiQ2krxIRh7za++q2vzvT32XLNlFijLNHPrrnjy2s/iXWG72TBNE7c3\nt9ze3nLYj+QlkVOhZrsPHwKb3ZaXHl/wysuPOT8/Zxj6Y29ARMjp4ev2H2UY4cIC5OoBjKxDGla6\nRO+ysUoLjA6yExYgKVRdSQ6KtaTEWhDe4yRAC4a+7+jPdmwfndOf7XBdQL204GniIJ5GstCKNpNt\nG397npl9fFDHj6VUpmnm9uaWm+tbDq1kaxJo8rbASWMH3V3XNOjtBufcybTgBUBeEqW57+ScSApS\nCtMyMc4j1/PI7TQxzzN1TPTLwlgyNTrcdqDuLvBnl6TtJbU3QQ7nHJ2HTcDaSeKIongK+ymzlBnN\ndmB0MRK9ErwyeKXzJrsX1BFcoHcOL7Yfnp1fcHZ+zrPO3E5US5tNLngtrEOD9l6xqiHeZBxcVOwU\nm6k5oyUZP6bWJqdajmuztpGqF8H1536D53igQ/Fa2AwDZ2cb1ClzmRlnk+jbDAPn5+e88vLLXD5+\nxO5soFJ4dvWMN954g9v9yCKZaU6UYlFOu54Yg9ngVLPZ8cERYkDE1GFMmcVOarWYa4RIRR04r3RD\nxHl3FKJH72S5q0KnkaF2prChGdHCzfUb5HRrxIvmalGz2gZc2zbUsuUuBl559VV+3pd8nJcfP2q2\naUPrb4GWujaaTngoVNN5tVEmWwsoiKl12Bt2pfmpsf+yCDMwi7CIBc9UatsQbBQrRkcXPNF3RBeQ\nlNEMbtMznJ8xXJwRNj1ET8FEDqQ2pxYx3VytjdTTvEZX7dp1prw1gViZuaVk5nFmf3vgcBgZx9mM\nsBtBaCUJGexaWhXnnuu1yhpEP+DX4YTPiGUamQ4jUwyMqiALUgvTPHIz7rk+3HCzv2W8PVD3E/04\nUvNMjIHdowu6xxNBHdlvWOJAWc0xHAQnDDGYrrIDISGaubqdmVPCh4h3NiURVfDqjfwm2kTom5OL\nRrq+N3Lo0BNCsJJ/KSZGT7Vjp1aqGslJ1aQARTw4k2MVr1ZxkcUmJPJCVWt/tWYGd8odyouwRO81\neO7HkYjSiYnEd31P1sw03rA/jKDKMAw8Oj/npceXPH58ybDtbDSlmHJQ8JF5KQxL4nCYqdmEDO76\nN21WrdnyOC+AR2kvVs7UJpAgzhGcN0djhNrFY1brnJV/Q4jHE1oIHq2ZcbplGm8QqXTRKN7qPX1w\naBXyoqSsOFFCALcZONtt+NjHXuWTn/gkLz2+YLvpOD+/IARPSmZgnPIp83xIVLWBchBqAZr1Uitg\nHDPOo0+iCFWEDCwoWYRFldIMe7sYONtELjeBy6Fj6wJBhXKYSQvQBcK2p9ts8H1nogyN6FNLtfng\nZh7A82xyOFL/3zII2uokVc28evX2TMlIRmt1B95KEDoWa4+znfa99XS/vqdOeFhMNzdcv/mUmmam\nbmDjTHI0pYVx3nO9v+b29prDs2fozR6WGdVK2A50m0DHBUolqTI3N56QhZCEIXpEhS4EvLcTUymZ\ncRaWpaAFanYQHJ5gFn2yGlm3Eqo4fAgWaH3AOW/KRs05ShpFyCa37ADnxQ6MRnCrLYCuLQhwRJoo\nIaDmRKTSii0WRF2bpX9o3GvwnOaZ2YmVp0Rx3qGZxgYcGfqezdBzfnbG+e6Moe/RqqQlo0XoorFc\nz8UxL5nreMvtfgKcGfzm3GaDmu6jgxAs6NVaWVKiuoo4o1uH4AnthfY+kEslLVae9T7SdwPDsGGz\n3bLZbNhsBoTKs6s3ePbmE6CwHTqGvsc7T83KuJ/Z387sDzNTqqg4hqHnpceXfPxjH+PVV1/h8tE5\n203HbjsgzrWyy0RKDz+r9FGG6YK22Tlt6j5qlQxZT7xVj+4pteqdGIEKS8Wk0VQR79n0HY/OBl59\nvOPxrqf3gZoqh2c31D1oF5AYkOBtBq6aQpCX5vLD2mqwrLDkQsnlLutcdW6P4ym0XpgFyVpXQtEd\ny3FlpR/HUtx6ktfjRwucbyVlnLLPh8d8fc2zJ68x7rdcxZ7ed819p7IsI/vDDePNm0xXT/E3t0he\n2HWRl88jr/SeR5uBfd9x44SxVqaUcGJ7VOeVXW+98xgCgzg2KdHtA25y5hmbEiFYMHOtrG+2eCZW\nUH2bqW+zmOv4k7bM0LV5Z1Rx4lp7pInVaGuCKGbk4bxVboLgJVKkcQiy3s0xA+v7pLwAC/R+CUOA\neCsTxC7Q9R1JzQIppwy9DYhvNwO7zQ6H4+r6mmfX19zu9yxLYths2J7tgIS4mVon5sV8CIsqu7Md\naIej0veR3W5LP/TGelySzYmmhQoEHwixI8aIE0/KmXGcmKcFEUcXoe8dm8Fzft5z8eicLnq2O8d2\nY356m6FnOwwEH6DA/nbi2dNrnl0fuL4dUfHszs94fHnJSy895vLyEZePzhiGji7aKWtOC0tJTQj/\nhIdCUUillWmDUBRUHCpiwu1gxEAxeW2TyrNsVXGmK6pGGurEymDn2w2PL3e8dLEleMc0JXLNNgMa\nPVmVlBNpnolLTwwda8ZbaJZQLeiVNpZyDJ5qG8eqOKTHgFmP5dmVTXsXPJ/rc7LOPrfCrbS/CXPj\n8M4sAp3z5FwYx1Nl5CGRpxum2xtSVfpBKL2NrDgxTdtaK5SMzzNdPnCmmVeC49Xe8fKuY9gEDsEx\nqXKTCyMQpOJ9YJM8c6osWYmuVR+cA2/enbkUfJXjgWyV1Vs1lKnN6kxMmD7lbG2stU/p7pryNsGJ\naYs3cqZTExkx+UGHtkmI1eTAOfPOdQSrHFZT01oNQ16Eysj9+nnutmx3A5vOc3a+4+x8B95IQr6V\nULsY2PQDQ98xTjOvfeoNfuqnf5ab/QFxjsvHL/EyPUUrh8PCm89uGGfL2HabgU++8gk6byMuXrSV\nfx/jQ2RJhWlZ2B9G5rSANCFuZway4zhyJSC1kFKyjFcT6ILzmW5QQtyxO+vYDB9DtOJF6EJk6Adc\nFc6GkcEHQnPGWLIy9JHN0HG223B+vmN3tjNxBzGj2VQLOMV39352OeFdMDeX+vWE3NXWk2mOJ9AC\na3vztwIWUkALTVXIxp1EhM57Nn3gbNNzcb4BL2h0be43UVWYl5n97R7X9/gQ6SRYv90rZQ2G2uzG\nnNiJHO5cgGgbWWMmmpACzeez3Ok0V70zuV5nOJ3c9XFlHR9ogdMLfR/puo4QA7Uo43higz8olgmv\nla7rGXbnbLYXdJ0lCnm+oZYRN0X66Nj2wsfF8yXnkY9vPRediYCkWrhNC1fqmemIXogVziqMSYlT\nJtZKEmXKyaopeKpzOPEUPLkoKZvjkBNTztIKWe3Al0u14JmTqbjpKq23Fm5blaXxB6QWPNK8c0FL\nm3rwDsTb4bU198V5fIhoafXFaiYfTuMum7gAACAASURBVN27PnUfBO519+76yO5sy6ZzDJuOYdOx\npGCWYV6IwVsZQuyUfbs/8Kmf/TQ//mM/yc3tAR87UhL6zY6K8uzqhmdX1xymGR8C52dbLi8fcTYE\n5sM11MQrjx/x6quvEGNPLnCYZm4PI4dparV1e2wlF4JzxmZbFmrJpJTIS2F2Sj945jmy2QbOtlui\n30JW0rKY7Fq18lcMkc3Qs9sOLLkwLtnmUL3gffN/FLO8KiVRtTDOM1kLLj586eGjjDkXqigBh+RK\nqkoqSlYhawuqapknqiZMXYAqaDV/WG1i1zShhegdXfTEaBqiUT3dpqPbdKTFSmGH21tC19GFSC+e\nTgWJ0Wyj1AQRFBopzkMbh1Gtx7GX2oJ3rUKphZSLBellIRczUV6N3g1rn0paNi1GnkPx3piXdtjd\n0cXIsmQ+9elT8HxIuMUcSoYY2Wy27M7PCd2Ao5CCoss1ceyI255Len5egE/uOl7eBHqn3OSF27rn\nTYSrWMj9wCADm+A4pEA/F9BEyI4slds5M6bCouAkICFQxbNUM7bOVIKAa+S5VCGIspTCkjNLzse5\n6WOFQ6wdorjjHKcT0JptZhWOxLhaHDiPiod1kkLAO0fzaLHrlIKrD18VudfgqdUKUcEHY6hWEwyo\nJRnVWE3O7rC3uaDXn7zJa6894fXX3+AwzoSu5/zigsPhgIowHg7c3Nwwp0wXI9M0mTF2aCObzqFV\nmQ4HZrewLIUpFcbG1PUh4II/MieD79ltz3ES6OOBXDLOe3a7LbvzLReX55yd7dgMA0EC4958Qw83\ne0rKpkq0eoBm08bdDAEfA7TGvs3aJaOa50QuC/v9Ddc3101M4YSHQkUpWsx/tTjGpdBPmf1+Rpwj\nBmeZpxeoQiqVVCBVIRdnWrUr80aO4aldXZvkGIToGLY9zhezfqqJ+XDL3glBwQOl61DnWnC0rBPa\nJqRKKUYCsvu6m6vSquRi/f3DOLHfH5inidXKSdcssyWhKjQBcTv4xWDBfrcbuLi4YHd2Rt8PHPYz\n/MhPfrAvyAlvQUwzftzD/po67EjdYBKS3lHFNeUhzyMf+GTf8yVR+cSm5yI4xrRwdf2MpzrzZr3h\nOuxgd4bkcyYqB+eIEsk1EApUJ+xn5TAXlpToglogc0JWoRQTC/Fiylm9KEu1r+daORRlqsqCrI7M\nwB1R7a1qQXem3uaWYtUU14R6VQpaM8iqUy54AdpBsqpp4T407jV4pmWCukUkUktimQ7kNCPNqUKo\nlJK4ub1iv7/hyZM3ub29Yp5Hm12isqSRtEwUrUzTgXkaTRnIO5Zp4vr6CqkbOqdED/v9nmVeyLk2\nB5RMKoB4un6gHwbA/AxzzqCevtvixE7+XbRs+ex8R7/p6HzAaSCnymE/8/T1K15/7XVub25Zphnv\nPJthsGtvNy1wQs4LN7fXhCD4IOS0sKSZUjPjeOD6+vrEtn1wmIRY0cJSHG5O7PcLXT9Ri9L3gegd\nxSuCZ1wKY6qMqTLlah6gVVEnxzd5RUk5k1M2W6iciV4YNhEfPKk0z83pwCQQMNPistvh+w4JoQ2P\nW/9HRCiltRXSYnJ/vklRNmJQzpVxmrk9HNgfDozzRCn5udlNE29Y+0XeOzZDZNNHtkPHZohsdxsu\nLx9zcfmIrut5882bh31pTiAsC/5wg149JbloIi5lIQw9ukzUZaEvlTOEV0LglShchIhXm3R4UjOv\nzdc8zZFDf0Y3npPyzKyVURyigal4uuypTphnmKdEygvRgXcRHCw0F59irkF9s+5bqljmWU1Va1JH\nwlFdaH36uxEoXTPSluBA4xVo61/WxsHV0t6Wpk/k2igLSFv7ngJIffiq3T27qlSCF/oYcKKmYSuV\nzdChdUff9wQv1JJNraUkvBeGIZJLwnlAC6UsZrW0zJa5KqDVSq3LgtYeH4OVyoBxHJnnxDjZv2k2\nO54QIiFYkCylHLUSnx8KjzFQS2WZF/pNh/d2e14yV1fXvP7a67z59BnXV9csy0L0gd1ux3ZX2Gil\nH3oqyjQLKU2Mh5tWtrXsc/04HvZvGzs44YOGNEGN2spIc/LIYQRR5nmm70xTOcaIw3N7O3EzzhyW\nzFKU/FzWWZttcamVnDPLMrdqi83zdn0AyehSoVQ0L5TZkXxgiREfAxI90UVcsN68D3Y+zzkxjnuW\nZSE4RwyBEAOIbzJ+1u9cmq5yWftOzQAeoO1MeCcMfeRsu+HyYtuCZ8dut20qMRfE2JHnk7rQQyPk\nBbe/BR9JCLkkmG7wfY8rC3LzlHDzDFkOOLeADxbIivKmZt5IhatROcww3hyot2YZNldl74SinlA8\nsfcEF0iLedKGUgidEkTIOJYqLMUOaR6ldo7YmZhHVet9LsU0nROO0txfaDLuK3X7OK/ciGp1DZio\nEfUaW1cAVbNiqyWDU0S8BWBx3EnZPCzuNXgGB0MM9J03TXYtBC9cPjpntxkQ1wS5vaXjm03Ho4st\ny7LQdYGsSt85HAWqCRWslOnojXW2zuPFGIjRU1JqzK9ESibQfn1z4GY/kssqjn0nWSbthTZReRtn\niTHQ913bOO1Fy7kwjTP7vQ2hz/NsRsRVYRxNfaYmxrkNCWvl+tpZ79PJUbux1sLqMRrjiTD0kJCj\nfLKRdJY0UynUWpjmZmIQffPa9Izjwn5cOKSFrJUqNra9rifj4rSDUrKgWtRmiJ137SBWkVxwOLxW\nSAtlnqhLh+w2+CDELljwdI6aC/M8cTjsmQ4jXQg2QqU9LoDUJpJ9ZNm2cm6bVXVN+aBqJThPHwNn\nw8DjizNeefyI3aYzCcm+53yzYdsPhGC8hBMeFi4v+PlA2TtSKeRpT+17fBdxNRHHG7p5z1xGDkF5\npgOxHyiu8ikcb1TlJiXmMZGWA+52ZFkWq3gER1KPL46+OPrQI7ngkxJUGNT69bk6pgKHuZLnjBcl\nSoDOIzjLHKtQgKRCEQ+hAzfZFusUafrhous8lGkxq4iNrFSh1oype7X3Eqv8h6KlGOO2ZZ9tSvTh\nXpiG+xWGFzH6uyiqBS2VEDznZ9vWJDZ3CLDezW7b8/jyDBHYnQ3kopydb+g6K10FD52XpuSUqdlK\nWcs8MwWhJGGeRm5v9ixzYp6tf3V1fcv17ci8pMZILMeSlunnmoWZd85cdEQIwR0JTcpqHqymfVtW\nwWMjayxpQSnkuuAmOQq/rLNz3lvpds1iQ/BsNwPeD/f59J/wHgjR+pop12YSUKk1syyQc3u9fKPP\ni5BSZZoyS7YTc5vqfq7LaRFLqwm6W+XEtgIVMXUWJza+hSN6IWhF8gIpITXjMeF475wZXS8z02HP\n/uaGaTxQY0fQSqDx39S8GR02nG5eivbfOvKyjroE59j0PRdnOx5fXPDSo3M2fWdtlBDoQqDznuC9\n+T6e8KBwNeNKIs+jebouB4p3VA++LsgysZSZUSpXnY39zamSAnzKCW+ocGjZoaaZdJiZayFEQaIj\nVCFkKBk0bOm10C2ZXqCvHq+BWhzzouzHTDosdK7yKCh+A77aGitFSamSi6IugO8gdGidUVFE3XPJ\nYpstFtcY46ZEpCarZT9Lo/Ous8hH9i5oq6S8CKYF95t5eiNHpDTjpEL0xC4SYzCtQ61GhKhKzpkY\nPecXW2IXuMwFVTHXcu/JSeij/ZumTF5mxoPj0HucJg639mIcbvfs9yNpMU3cZcnMqZCWRE7JFkp7\nQawfVKguW+lWVqVPJQksTlrwrMc5p5WCjQjOexTre0mp6JyPmSaubYIx0MVgc55dpB86O+WfnbE/\nzdE9KDabni56Ui7mXtF0ZIFWcrXxEVUTITCXCz3ad2lTrrK5tNWHs7bKwkqKAGqhNoWUKMasDWJB\nyiH4WiAvtKiNKwWhklNi3t8y3twwXl+RlgXfZ0rwlGCqLxgH2Fi+PhJcsNN5syvTllnb4dCzHQYu\nzs+4PD/jYreji55lns28uw2wuyYxecIDQ5SCrUtXMkELPhVEF7wu+DQhoiwhckWkVOFZhiULT4Pw\nVIXJBzRWxGd0mVnGG3imFA99VYYCslR8nOjEETTRR0esAapdc5ky42Fmuh058xWGSswQClArZSlM\n00LKBXWeMGxxdaEujfHd9ssmj2AtBer6hjFpU2/XMk1caXPVTaxDVmGFNmPa1vRD437ZtppZlgnv\nKlojWmOb7VFccK1dZNqeaME7ZTNEhj4emValVpacyMlxvu1YzgZEJ5alQrE+6CiF2zZ4fjiMjAcj\nfKjeETn6ztPF1ttc+9giOG/iyGv/U+BYWvVNtkzbIHnjL6J6FziRNTPRIwkKhOC89Xs73+Y+e7bb\ngc12w263Y7fd4vx0n0//Ce+BIUaGPpBjPRpO23vSUUozTq82m1urmUlH5yjVAmEpxdi2Sustamsr\nmALLKii2qvwIjuisv9S5SHAezWotibSgy0ydRooT1HvyPDPf3LDsb6nTRFlmq4LEQHHOSECxxwHR\neTYxMsRIbKbwdS1tOXsc3lt59my35exsy2bTI1pJx8rKWxViTnhYFKqZsQNOzYZLNOPKDHnE18VE\nV4LnCs8kAVc9S1JugVuFRTzEiHQZTTOlJsbDFUWsXOqSw20Trj8jhQ4JjrDdEIpSqrNh0apoTmia\nqSnj50q/VNzckUtiGkfmcWZeEuoCbhigDOQy216vHElAugbOVpQV50xfOTfl2rrefmf9t05brczz\ntWr50LjX4LnMI4e9J6fAMkem6Om7zvqKTaxAsWBVnhPANlZV6yU5857bbjpeefmSvuvYny+MY8J7\nR4hWN69UnIOuC3i3Nd1FFwjB+kduFWSvxrA0qzO7PYRwLN06aYO4tFEbLZRaTG83F3LTiFQ4Puaj\n7ZNqC55WUnMrozhbD2waW6k6Z8qycLM/yfM9JIJzDMGjhDsPWG1tAbUxlForud2mIqgTSlFyKaQl\nIw4TJcDWq4mxe1sLimV0GHXfO+vVB3HEJs6hYJPmaaEcDiwAS8IFzzLN5P0ePy90peIRQqnoslCc\nkFRxVXEEOoEheLZdx7aLTN5RmhGivTcEHz3Dpmez3TBsBkIX0JyPhKdSC6lkAh0vwAz6Rx61yaob\njOka4Dhz7HzEeU+NG6a4YZKOmmHWwpQW8/YUSxiqV6R35GVB8kI+QK6eNCqyGZHNOWmzIW97qi/U\nco5qYRsjjzcddZ54dpvwaaSbM/2Y0TqyTxO3V8+4vblhXjLeBzR6tEyQD8b6LgVqq86IQ5xHW9FG\nmjwfzq0TYccZ5sYoAN7aGnHNRvKhca/BM6fENI3k7EiLp+sC0+SaFJizoOUtiEprEIZgNGet2ej6\n0npDQ8926Hl0fs48V8ZxaQFttr5nEkoOnLHF+0AMHdEHYozELpoHaEv3nTNP0VVNpYvdnVm2SLOi\n0rvAlzNzWpjmhXE2ub+cC6llK2vJzxjA5a2nIwHhjimc5oV5DBz2t9wcTnOeDwlXbfTalHcCrGUl\nnJXpkdUTwr5uKii5FOZlYXTcBV2hCbNnSgmU0ohoatf3Yi2AznucClJtSNRVjLmUM2V/i6ZEPYyI\n85RspbawJM68t9KvKm5ZKFrRUgilQNgQtbIJjrM+su8jUx/RWliaH6Jrffeuj2y2A10fES9WoXFK\npZKaIUOqhRdgEuAjj9WF2GYh3dEeOvjYpgSsBaBxw+J7UnXkpbKwkAWy2EiJttlgDY20s1R0Gimz\nkG8r0k+wvaE/31F0RxkqOZ3j6jnbrqfvOmLpcHvrtZ6XTD/OpClzdbjl6dMnHA4HllzoNh2192jZ\nUOcOlhmXy92e6u5m8kWhHvkn9jdbYLSsszbC91vk+NY9/MOubdv3ka6PuMZi9SHgnRC8ERqM4GAE\nnXVkxDtaoJP2cSX0eJx46hZyVqY5Mc0LyzK14NmZ11vLOGOIdCE2Wr83eTzXDLmDxwdP7CzA+uDf\novl5NM6uhaqVXDLLsjCnzDjNpqaREkWrlbvWXmhZlTKMlJSzGbxaYDW7Ke893tu8kuMUPB8SOWVq\nDu3Ua+tvLSt5mtirSFNTsfKRa2Sf6h2pCW6UYq2HUgo55Sag4Vtv1KT9QvQEXCP3WBC0vs5qJmsi\n9DVXcsg4WbVLCyEXfLXMt9aK5mwd12bzJJ3gS2YQ5bzzHPrAMkS0ZnzJpKr46Bj6SN8ZK901zemM\nlazNGLwdBmumvADaoR91OMxnU3TB1YJYOY6qJp6OD+AiVbom3pHIZLJaBuecp4g141XWloJpfngU\nlplShTInaplYZKQMMy45ZL7ALWd0ZcAPG+JZZPPSgO8PvMrCZj5wGK+5vnrK9dM3mOaZ4gI59KTo\noB+oXYdPnVVdUmk+t9JmOptAgqykttYqUCMFVZTgmtuR1qMpgrSRljt7sofDvQbPy8tLHj8azIrG\nO7ou0gXfSDVNY6LoMcOk9WWcvxthkSbTJGIfa4USzcy67wPz4km5o+qmqVkYAyw6YyzaGIrivNA1\nslLomrOKE5x3ljEq1JKPc0Z2WNPWwLbfj+IQ39lQMX2TZXPHnqnpiVaovGVcptZmDLseEFoAxd3e\n59N/wntgXhLTaAc7O3TZSAdqYuw+BMSZsMFSKuIcvgQKNltZsknplVyP5ducMyVnagk0tzMbVVEh\niLfh7tavsRk4GzcxJpu2enGxrqNaqU5LtVO6VqqWI4mJ6qkY21aWQq+FrYfHmw7NPY7C7QJLqYQu\nsu0DXTR9UlaJv7VikjNaTcDBhOZPc54PjaCFUCeq81A9mgMVh6oHCahGRAM5KSUvrcet1h/1AcXh\nXbTSrQNxRgoLOKKzQ1ypCzUVypQ42yR8hZh74vwmHLbI0NNFx9nG8fGPnzGMmd3NU8qbe9Kbn+b6\nyWvcPLslV4VuoHQ9KQrSdbjNlijKNiX8skAplJxQhWKLr7U3qv2jNUfV5klRazeoOqrWo2i8OneU\n9ntI3GvwfOnlx7x0uSNlUzvporfMM3hrBzdNwyPruJEtnEDorBfZctS2mZifosgatCyoxmgnq6ME\nWbUmtW+O47WdcJwozpnvJjU1G6qMFiOFlJyPbDBp5A+wOnttIwdOlBh9Iwm5Y+/URgTsj6ilNqHu\n1JwGWvB0Npu6ZtWH+QUo3H+EkatQcM1Q3WTu0IKqnZJVFedhWUypqorgFssoc1WW2RjdpShenM38\n0uzAqrbqisepw6uzIMiqldf6NkeCTjW95HYSv1vMjXCBkUashMedsfWymLF6UUJNbKRSO4duIo4O\nL+bn6GJk1wd673BY9lodlGVBc7GAXTKai/XkT+pXD45ApieRa6Kqp9aAElEBdd763UWpmlDNCBnX\nZuGdjygBlUzBo95RnNk2+rUfLxUcFM2g9npvwpbzmEBGUrqi7DtmKruLHZ+47Lk4Pwe55Y2rxDxe\ncf3maxxuE9XtCMOOsB3YbAPd1jGcRbbLxDBPsN8z395yuL0hl4zWYuu5tRXuAqmVZE2NSCxGHNnt\n64BKS5IeGPeceT7mlY9dMs3Wl6w5AaXN+WAn+8ZWpG0MSm0p/Eq+afNAbVZITQ27dZUzRuOqzS9u\nZdA2CxzFyk+1UlIhy6qnu9xlqXAcLBehbYAtG8YMtK2vBbR5vZU1ZvHTNUr1XR3erYcEL02xqBw1\nHqE5BrQM9ISHg+s6XDfgg5WCSsmNWVhM4KDaCXlZCocxkbFymDZxhCUXlmV1ixDzinWB6Du8CzgJ\neLFxlJpq8w01M99Vu1bFgZS2HTSmYSMSHd8bIpaRNskzWasj1R6nGjWYUDIDBbyinUDxBO2YqxL6\nnqHr6FFkSVQHGUWXhM4JVyuhgqsVKdW82k54UIRaCSXhVChSyXInzEGThqwlWYamCU9B1QhgFjw9\nIh1VA9U51Dtqq8KZy9c6jF5xzrEdNlyeB15+1JMGuNIDN9evMe9v6HiF/vHHuTzbMU1bahcYa2Y/\n7ZlTRoeeYePZng9cXp7x8u5VHntlVxJc37B/8oQnP/3TjOOI6mzVjlqtslLNtEy1mpa0NhMzbftv\nrW0yw1FaVehFwL0Gz+1uy8XFBd2ymELKeDBz01bz9mLO4m2kG97y/1YCVW0a2GoZPbRsMR1ZsXds\nWyMfBW+yZVrsFFaxJ79k2xBWSv76cWXZGvv3ziTYOUF8UxGiVdueE1bAi2UqHlQK1a2+dW2EpQ3F\nOxeO0lPH4CltHvSEB0O3PWO4OCN4R84LOs/U3MZBamU1lV6ysmQYl2T+nbRZTxHm3EZSnMc7Txe7\nO8JaiJZ9VoFiKkYiNhCu62kNbYSOthbqKuh+Ny4iamNduvaKpBE/wNiyanPGLid6KagU8ILrPB2Q\nxUEIdF1gQJFloWoBlLokXMqg4FLBpQKyUJdTP/6h4bQSam3z51ahK856n0UtESEbITGsKmxtr9OS\ncS6CFgQLnrU4qnPWIfAOxXr6TirRC5tYudhFLs8H5i4w58LT22uulmsudg6VV4ibM8bthnnoGL0w\naaaQ6Xrh7Mzzyss7PvHxl/mSlx/xytDh54XDk9d5rSpPnz4FHyhgSQh37NlajBRlXbd6HPlbZ5RF\nzchBZHUxetjXBu7bDFutaR1jpO8Has0kKiXXI6lGNOGk9SePTCxjJ/pViknsf+Kt5r26l+O81ffl\naKuCb71OmyFxaPCodlDrUSlmve+19CUrOYP2mhxJTI0VtjLBvN3oxLdMwayqarHSgtRylPk7lqJb\ntmr3w/H+nHNHEfkTHgYXL73Co5cucILNCx/2TOOeglBSNuslhYKgzpwsUpvtVGllpWZO7BpT3DVS\nmOCsx6lGwde1LAWsffm7DUBaVcXGqNZS7trSkHVgQWks4HWsyx3VV6gVqRWvlb6NpTiUPpjeqVk8\nVWLJyDQh2dv9lYJP2QhTywIHR00ZPYwP8pqc8Byc1d9E5biuXPC2p4nNG9dacGoZHKzjH61fqGsw\nLdQiKJ5cbUa9qO1jdsgvdEmJaSaURHCK3wQuZODaLUz7hO8qGiFFYYyeQ+c5BGEJghscjy47PvHJ\nc/6OL3uZT378VR6f7YilcptmrqaR1/d7rpbEJEKNxjeRkvE264fgLIAKUFpwXYOk2ntNVmY7d3vp\nQ+J+XVVSsjkfTG2n6zorSdVMWkx8vaRC8IEYAl30hOisN+hDYz/anJpggVFEkKLgAlJrq48L6p0x\ncp0FXVHAO6PpH0k9puhf6vPBUxtHozQCSCsROEGCt7EaWXPj1ZC1Vd7bZlZLAWk07LuoSWvi2mer\ndJrzdn3vmkLMCQ+F88eXXL76Kmhlng7mqSmOVJRSJlsfonYoCx5f7cCkTZ7x7nwkrcwvtsG1Q5wg\nBDFbs6OgRiu7rpvCKvN4jKXVPDttWPy53ierTJm1LurKUJS7DVNai8K3A6jEQKzKoGYTpSguLTit\naLYV7dUISmtFRFWpy4KOp+D50ChgZKGWKPgQcV3E9RF1jpTNx5UKHmd7Ymlld61ILTi3EuBAq7es\ntapNLmAsVqmJqEpYZuo8oyXT9ZGL7Y7LLrJ0E90uUCIcUPZO2QfHFD2lC3S95/FLG770Exf8wi99\nmU9+7CWCOK7fvOJmf83PvPE6P/XGGzw7HFjUpCBDcPjicKUiriUgGFfECjKWiKwqXc+32Z7//0Pi\nvoLnAPAzn3rSylvebJjyYqop80iaJuZ5pqSCE2ezRJ2NlQTfRlvW4NmGgn0bEiqayXmh0lT2Ze1F\nWvnMtZKAtAH1sBqrNjJHrTYQvp7uq5orRX6OJCHSNEgtkh7r7EfZMyxTqI1sZH1SOKacurarVuWi\ntsG28p73jjeeHd7yfJ3wgWEAGOfM7X4ElGmaGceFw5I5LNbn1JKhVEpWllxIxWZ6y5rtNXKPFjUL\nvCVxfZjpvZJTYROibWrFfmal3CN3+se0vuaq2bmWcjkyt1eFlbb+yp1UJALPX6ZkY8quAdlE6yFX\nyOtojPftIMkxmz1uQ84j3rKRNw/zW56rEz5QDACHUmHJpriykiDF9MJVxObNU26kMjEGatbWN6zN\n87K1B9YkQzxFfNs3TRmNmlCnPH0z8NOffh3tBvqlkM8ueH1KvLGfmG5v6UriU5sNz5495ad++id5\n8voT9rc3iBeWmyvGN17jZjfQLxOlFJ4+ecZP/OTP8BN/+2/z6U99mvHqGl1GYs0UwGvF5WqH0VKp\nxQ6WWquN5jQW7lqoWbPOUgvjHRv8wdan3BFZvoAXFfkW4E9+wS/84cW3quqfeugH8VHBaX2+L5zW\n5geM0/p8X3iw9XlfwfNl4NcCPw6cBFzfGQPw5cD/oKpvPPBj+cjgtD4/K5zW5gPhtD4/Kzz4+ryX\n4HnCCSeccMIJH2acGCsnnHDCCSec8D5xCp4nnHDCCSec8D5xCp4nnHDCCSec8D5xCp4nnHDCCSec\n8D7xkQueIvK9IvJ5U5tF5CtFpIrIV3whHtcJJ5xwwhcrROTXtv2we5ef+Q4R+ZnP8fo/JCLf/bk/\nwi88Puvg2Z6Y0j6+/V8Rkd99nw/0C4h/EfiOL9C1TlTlDxE+RGv8HSEifft7fs1DP5YTPjt8Ea3L\n99oP/wTwyz6Ax/GB4P0oDH3iuc+/Gfg9wFdwJ1DyGc0pRcSr6gtj0aCqN+92u4hEVT2pYn808aFY\n4++Bh9c1O+H94kOxLlV1BuZ3uv2Lbe/9rDNPVX1t/Qdc2bf0yXPfPzyXuv8jIvJXRGQG/t7PVCoV\nkT8iIt/33NdORH63iPyYiOxF5C+LyG98P3+MiHQi8sdF5MdF5CAif0NEftvbfuYtj6WVA/5DEflD\nIvIG8F8/dzr/rSLy/e1aPyIi//gX4L6/V0R+h4h8SkReE5E/IM957IjIICJ/UER+WkRuROR/FpGv\nfz/PwwmfG74Y1ni7zleJyPeJyLWIXInID4jIl7bbvk5E/icReV1E3myfP3/a/zEsQ/hz7e/465/L\nc3XCB4cvlnXZ8A+JyA+LyNj2rq987n6+Q0R+9rmvf2/bf3+biPwY8Gb7/pmI/CkRuRWRnxSR7/wc\nH8u94r56nt8NfBfwS4D/97P8V2JRNQAAC7FJREFUnd8D/FPAPwf8UuAPA/+FiPx96w+IyM+KyL/5\nLtcIwN8Cvqnd93cD/4GI/Ib3uO/fCjwFvgb47c99/98Fvgf4auDPAH9aRL7887zvXwd8DPgH2v3+\nS8C3PHf7H233908CXwX8d8D3i8iXvcffcMIHiwdZ4yLy84G/iG003wD8CuA/A2L7kTNsDX0t8PXA\nTwHfJyJ9u/1XYBnLN2MZzd//WT72E7448FB7L9i6+v3Ad2Lr7Ab4b55PDvi5pd1fiu2JvxHbfwH+\no/b7/xjwjwK/of3cC4X7EIZX4Heo6l9Yv/HW5+7nQkR2wL8GfJ2q/tX27T8mIv8g1qP839r3fgR4\nRykmVT1gAW/F94jINwD/DBaE3gl/TVWPfYPnNpr/XFW/p33+b4n1ib4T+Nc/j/v+tKr+q+3zHxWR\n7we+EfiTIvKLgd8EfEJVn7af+X0i8uuBb3/b9U94ODzYGscOdz8D/LN6Jw/2I8cHpvo/vu1+/wUs\nW/mVwJ8HnrSbnrVM5oQPDx5yXa74nev9i8i3Az8J/Hreef912Fq+ab/zGPg24J9Q1b/Yvvdt7Tov\nFO7LVeUvv8+f/0pMq/AH33ZKicAPrV+o6q96rwuJyHdhT/6XtWt2z1/jHfC/v8P3/9fP8PUv+Tzv\n+4ff9vXPAl/aPv9lgAd+/G3PQwf8zXe63xMeBA+1xr8a+AvPBc63QEQ+Cfx7WGXjY9jm1GFr8oQP\nPx5s78WC93HPVNUnIvL/YXvmOwXPv/U2HsovxtbsGrSfv84LhfsKnvu3fV35uSXi+NznZ9gT/438\n3NPNZy2MLCK/BcvOfjsWEG+A34UtkPfzeN8N77Rpfbb3/faGuHL33JxhDfWv5ucSO96V6HTCB44H\nWePAexltfm+7338ZO63PwF/BAugJH3481Lp8N7wbC/ftj3fd9174SYZ7NcN+Dk+AX/627/1yYC0b\n/TCQgS9T1b/0edzP1wM/oKp/bP2GiPyiz+N6Xwv86ee+/hrgB+7xvv8PoAdeUtX3e4I84WHxQa3x\n/wv4JhGRd8g+vw74FlX9fjiuwfPnbjdfbKtwnPDhxwe1Lld8LS3LFJGPAb8A+Bvv4/d/BAv4Xwv8\n92+7zguFD0ok4c8Dv1JEfpOI/GKxYddjYFHVN7Em8R8SkW8VkV8gIn+PiPwrIvLN68+JyA+KyD//\nLvfzo8DXicivbvfz+/j85oq+VUS+rV3r9wJ/F9ZMPz6kL+R9q+pfw4hJ3ysiv1FEvlxEvkZE/m0R\n+cbP4+844f7xQa3xP4gRff6UiPzdIvKLROQ3i8jf2W7/m8BvFpGvEGNp/wmeyyDa6MJPAf+wiHxc\nRB59Yf78E15QfFDrEmw//HdE5FeJMbz/U8xW7c9+tg+2PZ7vAf6AiHyDiHwV8Md5lxGXh8IHEjxV\n9b8F/n3sjf9D2JP8vW/7mX+j/czvBP46dur4NdiTv+IXAi+/y139x8D3Af8V8L9gtfw/+l4P711u\n+13AbwH+KsZG+6dV9fna+/O/+7nc92fCtwD/JfZc/T9Y5vvV2IZ3wguKD2qNN5LPr24/84PAX8LI\nZGs74NuBTwL/J/CfYOzHZ2+7zHdh7Maf4L35ACd8EeMD3HuhEZaAP4L1LM+Ab1LV+j4f9tr6+j4s\n8P454P9+n9e4d5z8PD8DGtt2BH7dWv464YQTTjjhhBUfOW3bE0444YQTTvh8cQqe74xTSn7CCSec\ncMJnxKlse8IJJ5xwwgnvE6fM84QTTjjhhBPeJz4UwVNEfr6YKPJXPfRjeSeIicb/mYd+HCc8PL5Q\n67WNBFQRufhCPbYTPpo4rcn3j3sLni1YrH5zs4j8qIj8ThG5r/t8X/Xnj9KLfMJ740Vfrx/AdU54\nwXBaky827lth6M9ic5IDpo7/h7F5tN//9h9sC+L/b+9sQ6yowjj++6PuBzXtg5CFYcuy5daWbJZY\niRLWh4RFTEwsdS0WC0Mjo/eoBXtRs0AMKl/6UCL2pYKIAtFNTXozBbeW1EzUlMwlwVRMk9OH51ya\nZvde96p3d+7u84Nh755z5sw5Mw/zzDlz5vmHfDE7O0GxOoXCLnLB/VRmGnPORZFle3V6J26TKS5B\nPy8JpZ62/Tvqzh0MIawANmAfZyNptkxvsF7ST1gUlKtjXqOkVpkmXKva62KOlrQ95n8H1FHE045M\n1mlj/PdYfLJ7L+Y1S1ou09k8iuketpvSkDQ4po1LpF0v6VOZxuJxSZsSkV/SbbhVpuf5ZGfb7ZSc\nTNprop6JknbJ9GI3ANd0UGaKpB8lnZbpMy5I5Q+V9FmsY6+k6bHc/GLb43QJPcEmx0raHMvsl7RM\nUv9EfoWkpZJ+k2l4fi1pfCK/IV8/u5UQQkk2LKTSR6m0T4Dv4+8GLOTSFiyOYTX2dPUAFk1nEjAc\n08c8CsyM+/UHjmAahjWY5tsvwDngpsSx9gEv5mmbgMlxnypMfeKymNeMSTgtim2qju1I1z8Yi8E4\nLv5/FdCGRQeqw0JgNQDV6fOBRYg5BjSW6vz71nPsNeYPwwJ3LInHno4p8pwDBsUyo7A4pc9F+5uF\nBd6elahnPaa8cQsW47QZOAHM7+5r4FuPtMkqTNRiHhafdgwWPWh1op6VsQ+3A5XAAuAUUFWon91+\nfbrqwgN3xRO9KHFCzgG1qf32ANNSac8DX8Xfc7CgxhWJ/Ic7uPDrgbkF2jc+eZET6c3AD6m04Zij\nLOQ8X40G2KfQ+YgGfRyY2t0X37eystdXgJZU2mupG9Ua4ItUmcW5/YAR0WbrEvlVMc2dZ8a2HmKT\nK4G3U2XGYg95Oam8s5iGMaljv1yon929lfqdZ72kvzAJHAFrMdXyHGeCBUMHIA7lqzAx1lWJcn2x\nkRrYDWBnCOFMIr9dfM4Qwt0X0e58+p6FGAlsCRZ4Ox9jgHpgSrCYk062yLK91gDfptLS9dRgI5Mk\nW4HHJAm4FjgbQtiROO5eScdwskq52+RI4EZJMxJpuXerlbGtfYDd0UZzVGAzeTn+188sUGrnuRF4\nBHuyOBzaBwhOaxMOjH8bSYihRnJOKbfQp5R0pImXO3aOfqky59NZBBuZtgGNkj4PvhApa2TZXjtT\nT0dllOd3vjJOtih3mxwIvAsso72dHcCc6z/Azfx3n81xIvG7M/fXLqXUzvNkCGFfZwuHEP6QdAib\n616Xp1grJhVWkXhyuu0C2pbbtzO6hkfj3ysxhRVo/4J9JzBLUp8Co8824F5gE/ChpKnnGak6XUuW\n7bUVm7VIkq6nFZsSS3IHsDuEECT9DPSVVJcbfcr0Pi+/gPY4XUO52+R24IZ8fZC0A7sHXxFC2HoB\nbeg2shgkoQl4VtI8mf5cbVxV9njMX4s5rVWSaiRNBJ5IVyJpg6S5BY6zP9ZTL2mIpAH5CoYQTgPf\nAE9LGhFXgi1MFXsLGIQ5xVEyncUZkqpTdbVhC4ZGAOskuShxedNE19jrO0C1pCUyrc77sXdBSd4A\nJsi+BayW1AA8CrwOEELYha3WXBlXe9dho4JT9JJv83oJTWTHJhdjOsfLJY2M98VJkpYDhBD2xPa8\nL2myTMN4tKRnJN1zUWehxGTOeYYQVmNTDg9io7kvsQvya8w/iT3t1GJPNQuBpzqoqhIYUuA4h4GX\nsFW1v2N6nIV4CJuH3wa8ib2AT9b3J+YUB8Q2b4v9aDc1G0I4EsvWAmtSc/1OGdGF9noQ05SdhGl1\nzsG0E5NldgD3AdOAFuwm+kII4YNEsZmYvW/CtGdXYNNjp3F6BBmzyRZscWY1sDkerwk4lCg2G1v5\nuxTTMP4YWw1+oHM97h48MLzj9GIkDcNuUhNCCM3d3R7HKRfceTpOL0LSndgijhbs2+QlwFDgOn//\n7jidp9QLhhzHyRb9sG+SK7GP17cC091xOk5x+MjTcRzHcYokcwuGHMdxHCfruPN0HMdxnCJx5+k4\njuM4ReLO03Ecx3GKxJ2n4ziO4xSJO0/HcRzHKRJ3no7jOI5TJO48HcdxHKdI3Hk6juM4TpH8C/um\nuGfVDa87AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe756941908>"
+       "<matplotlib.figure.Figure at 0x7fe0f9361400>"
       ]
      },
      "metadata": {},
@@ -2056,16 +2085,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[919   8  11   9   5   0   1   5  30  12] (0) airplane\n",
-      "[  6 949   2   4   0   3   1   2   2  31] (1) automobile\n",
-      "[ 19   0 884  33  17  11  24  10   1   1] (2) bird\n",
-      "[  6   2  11 843  15  81  17  23   1   1] (3) cat\n",
-      "[  1   0  22  37 829  13  27  67   3   1] (4) deer\n",
-      "[  3   0   8  73  10 876   4  25   1   0] (5) dog\n",
-      "[  3   0  18  27  15   8 924   3   2   0] (6) frog\n",
-      "[  2   0   3  15   9  15   1 953   0   2] (7) horse\n",
-      "[ 33  10   0   3   2   4   1   0 937  10] (8) ship\n",
-      "[  6  38   3   0   1   1   1   3  10 937] (9) truck\n",
+      "[926   6  13   2   3   0   1   1  29  19] (0) airplane\n",
+      "[  9 921   2   5   0   1   1   1   2  58] (1) automobile\n",
+      "[ 18   1 883  31  32   4  22   5   1   3] (2) bird\n",
+      "[  7   2  19 855  23  57  24   9   2   2] (3) cat\n",
+      "[  5   0  21  25 896   4  24  22   2   1] (4) deer\n",
+      "[  2   0  12  97  18 843  10  15   1   2] (5) dog\n",
+      "[  2   1  16  17  17   4 940   1   2   0] (6) frog\n",
+      "[  8   0  10  19  28  14   1 914   2   4] (7) horse\n",
+      "[ 42   6   1   4   1   0   2   0 932  12] (8) ship\n",
+      "[  6  19   2   2   1   0   1   1   9 959] (9) truck\n",
       " (0) (1) (2) (3) (4) (5) (6) (7) (8) (9)\n"
      ]
     }
@@ -2091,7 +2120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 66,
    "metadata": {
     "collapsed": true
    },
@@ -2156,9 +2185,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/09_Video_Data.ipynb b/09_Video_Data.ipynb
index 09605ca..f0e39d7 100644
--- a/09_Video_Data.ipynb
+++ b/09_Video_Data.ipynb
@@ -119,7 +119,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.11.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -135,12 +135,41 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Load Data"
+    "PrettyTensor version:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {
     "collapsed": true
    },
@@ -158,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": true
    },
@@ -176,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": true
    },
@@ -194,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -212,7 +241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -241,7 +270,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -273,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
@@ -303,7 +332,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -314,7 +343,7 @@
        "['forky', 'knifey', 'spoony']"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -333,7 +362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -351,7 +380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
@@ -362,7 +391,7 @@
        "'/home/magnus/development/TensorFlow-Tutorials/data/knifey-spoony/forky/forky-05-0023.jpg'"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -380,7 +409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
@@ -398,7 +427,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
@@ -409,7 +438,7 @@
        "'/home/magnus/development/TensorFlow-Tutorials/data/knifey-spoony/forky/test/forky-test-01-0163.jpg'"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -427,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -465,7 +494,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -538,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true
    },
@@ -563,16 +592,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
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v0t0Tp1gvkKvkmFvZRvKECEfCFItF3K4ALpebjcQ2Ho+fZkNHbRocO3rqR8e0\n4rEu7ty5gykZ7BZS5Gs5fvW3P0t7R4iZO1eQFRlDMXn50sucPnaEI+NDvP3SD1mbW2NooIsVKQum\nyMr0Mh2xAfpHe3HYPVQrDSbHJpi5m0fp9FErNAh5/ESDIRKFBvmdAh3t41TGKxTKq6zvbFDYrXLy\n8CEeeHiCzeIijZaDr3zpVdxyB+n0Mh/7lYc4NH6apYUVvvW1b/HIA+e5cfMGbYE20ttpvHgY6x5j\nPbH2z8b9ffXibC6HM2fH6/VimiaKoiCIAuVSGUVRkCRp72hAucyDDz6EKFjIbu/NLsrFKe6/72Eq\nlQrJZBK324PXrbC93aReryJZbTTVOkMHBvH7K6ws3iISjnD9+jTDQ0NIsoJi91EsFFnfWiGX38Xh\nsGICHq+DZDKJqlU4c+4hBLGCblTo7e1jJ5HG0Wow0tVHsVrg0qUL5HZShN0+9HqDlZV5JKuJN+Ql\nEHQzNNyH0drb4n/hwhtE2yJ4nIPMLcxg87pQsZC6u4hqtDh0ZJJMaYFKRmdrI4+ak/G4PfzCuWdY\nurvKgYlxxiZHeeH7z+EI2CnUKsR743g6XFx5+Qq9PT0kE/vVkn5aBJtMSW3QTCVxOp0Um3UWN9fo\ncXio1WpEo1HK5TK6ru/t5DUE7HY7oWAIxamQTCUplUq0Wi0ioQjkVEDEMDVaLTBNC5cv38Dr81PW\nG1T0JhbFTry3m87kNs1mk6baZHNrk2Jlb1emYRGYmrqJPxBgfmEeZ1cQr+RAVwXevHCFQ92DtDSR\nj3/ss7x56VXmyjl+4zf/BW6vnfzaJg2Lg+7Bfnw2J4YgYsGkqmtUGyYe2cb/9ed/hWSVCIfDGIbB\ntalrfOyXP8PWxi7d0U7Oj5zmhRde4NXvvb53PEe0USgWaEUMqmqV3Y0UNp8N3dKkXCnTaDSwOd20\nDINms/nzbtIPFL3ZpLibpZTLYxetVOtV/Iobu92OxWLB6/WSzWZxu93k83nSqTSengCvvXmR3/29\n32JzK0E2myTSHmZh9S63b99mdHSCSrlOLNqFLEscmpxk7t4Cfl+EbLqEKNhwKnbqNZ3kTopWy4LF\nDoZgMDE5jmgXSOWTpHJJivUCATNMIV8gFAkiqS2i/R2MnBigaReJd0S4/Mo1theyJO8VKOzU+Z1/\n9Xt4gjq7yQqyLKM6JWySj3w+yfrsNDtFkZHJPl74zrc5c+4M3s4uLC2D4raBIcJWbZaW3YZkG+Tc\nuXa642GOfQSAAAAgAElEQVSqxVncAQf3NmeRFRu/8ItP4kRBr7eIh+PcvjBDTAxjMd9b3N/X7cpG\nvU61VkXVVEzTREAAARqNBqIo4vP5CAaDHDx4EKfTAZiIgojfH6Baq+4NrlaLRCKBJElsbC7h9tjo\n7Ixz4MABBNNKvaYjWRSGh4cxMXn8scfZ3N7i7t1Z3G43qqaxm95EtOg0tQoWq05TLdMy6uTyKTyR\nIDbFgSFApVjCbXdwe2qZt9+4QL6QYnnlLppeJZPfplzJMrdwG6tsgrC3UlNcEobZwKRJb18Hqlrn\nwutTqHU7/T1HCfn7CHi6adZlNtZq3Llew9Ti0AqQ3CkxcXCchlri8LEJLl5+iy/8xX/ilYuvM3V7\nGotDJlcq8sbFN9na2mJ8bPwnGCr7fpxMIYfktOFvC9EwVMYnDyHIVkql4t/v3C39o9dCoUA4FKLZ\nbLK4tMj8/DzhcJjR0VFy+Rx2pwiihtqsU6/XkKwOLKKDY4fPcHVhlopkYosGqEoQ6OvE0x1jrZjh\n7t273L13j0gkwsGDB5GsVtxuF26XC1GQcdjdeL0hnnrywxRyFc6cfpCVpQT+gIeOjihz83fw+Z2c\nO/8g7R1tXHzrVexWCbG1N+Z0vYUoC5jA5etXOXzkMI899hif+9znePrpp3jpxZfwer0U8gWW7y3T\n19nPsYPHsIt2tKpG0BUkn87TarUolUoICAiCSC6Xo16vI9ts1Ov1vWM3+35qTL1FLp1FNMHlcGKX\nbQT9ASRJQhAEnE4npmnS1tZGIBDA4XSQq+T4H/7w35IppMmVMwSjAbZSm9z/8P0IgrA3eWtrY2rq\nBsvLyywvL3Pw4EHa2uKEwm1UKnVUVcfvDzJ4YJinn/4wg6ODpPNpHF47lWaJZCbJTmabqlbDLBQY\nbI+D0cQZcCKHXUw+coq0WEEQddBb2A2JZqaOZAi8+L3nuTFzjZXpWbRmk86RQXpOTFB1Sww8cIyK\nLPDnf/qfuTN7lztLMzSEOquJVdxOH8MDo8guP4HwMOtbu7T3yRRqt3E5LeTyVTRZw5BaZEsZvv6t\nrzMwMMDq0hpuxYlp0TCs723j3vtKcja7DYfDgVWy7h1CxaSltwgE/djtdnRNR7JK6HqLjY1NhodG\n2E2nEAU4OH6QxYVFvB4fklVma3ObcqVIU22QzaeZunGDQr5ILlfCYrGhqSrhUJjl5RWGD4wgy3ZC\nkQiVahVBMFAUG16vC9NsoaoNWq0WjXqVt9+9ysbWDqYJht5i9MAIY4Nx7jt5moMT4wwPDdFo1JCt\nVhx2mUqpSCgUwO/3YNIin8+QWF/Grdg5NDHKb/76r/MH/+oPOXPyEdxKmJtT87zz7jQLi5uoqp2N\nLZ1MVuT69QVGxyZJrK1z8cJrrG+scPnqu1QbDdra43T0duMNB6iqdXbzaTo6OyiU9r9EfpoGR4YY\nHBlBN00Sm5ssJ1ap1hs0Gg0qlb3zQaVSiWq1Sr1ep1atYrfbCAT8xGNRPvLRD+P3+0gmdxgdHUWS\nBSwiaHoT0wTJauO/+5f/miOTJwj3dVM2W/g647QUO8MnjvDQh57iyMNnaTbqjAwNcfTwUe7O3qOp\nqvzw9ddoGhrhcBuxeAc9vQMobi+dHd2IpgWfx8/G+jK+oJtqo0QqtUWxlCHeEeF3f/9zIFoQDBMR\nE5fdjmKX2ClpPProM9TLKmpNZ2VxlXi0g7Gxcex2+94xhJlZGpUGzYpKZ6wLRXbR29GP2+6mv7eP\neDzO0MgwLVoUy0Wq1QqyLNGo16mUKz/vJv1AMfQWxWIev9dLqVigLRzGIdtA4EfP6ePxOKZp0NHR\ngVtxIdskltdW8AQ8XLn2Dpl8GptTZnVzhb7+PoqlIhtbW3R399DV1YXL6WJjfYvXfvga5VKFu7N3\nCQXDOB0K62vrrK6ukS/lyJdzKF4XgiSiCxoNvYlFFpF1A7VcxWmzI0oimVoea1AhZ9RZW1thoHcA\nn91LPVejVTeo1+q8dekCq/NLbG5usVurcmFqCndnnJTa5L4nn+Txh57gqSd/gWqjwt3FWUrVIi6n\nm4AnytSNDez2djp64xSat7C7MmDYkIQ2vG1uCrU8wViQlqnz0MMPsrO9hYmOaVFpCep7ivv7ul3p\nxI1dV7BrTqJKnFatRWeki2ZTQm02ECQB2S0xcXCIRGKBv/n2/0NbpI/t7W3SuSzBsI/Zhet0d3cT\nag/Q736AarXKhQsX6Ovpw9frw+12IwoCu2qA1M4iyA2uX73IM499mEZ6h7nLV7FGu/iDf/05/s/P\n/6+cf/RBTNNGvpDnzr17eL0hGrIDz9g45XIVl+Ch5bCSzRawVGR2c0kkr52yqCEIAoH+bsx2D9s3\nE0zfu4cpWzl04izJpgPF6UcPDYGm0d95GLWo0nrtJjMv3GZi6CDFWo7obIDqbAG7aeVW9hZ9Yz2E\n26P8xV/+BeNjw8iCSCqRJTJygspslcJ2mex0loDsIJ1N/USDZd8/zW4VEfQGrUYFn2KnXspTzu8S\nDsaxWgXSmSQjI8NUKtW9w9q1EtZGmK21BJFIJ6IWxWMPYY91oes6NauFfGUDQTBBaDI01kONJNly\nnWRyBofdjiSa3Lr1Mp/4xMcJBGRGDnjRHngCrU3inrqEEFFZXZihObPF6pzGdx/UeYqn0Fs6jfQ2\nol3HDCoED8aRUh7e+vZlSsUafX0jzJRTfPRDH2NcGcfUFGQFVCRqmFQRuNN4iWXPnyEGLbgsPnJG\nkVhPD++8+hZBRxtT00U629vZLaRw+O1k9DKHnz7EbjGFRbNQkcDt9JK5tUGvHKeaNBjwH2NtLonS\n5ScSi/+8m/QDpSU7UUJxKvU6rkgHJU1Ha4G3KZFbyZBJZumK9eEKhbDaC9g9QRy1CnF3hGw6S9jW\nzuvPv0tnZweDnQOEhRgIFSq5BAjDeAJBVEuFF176MmcOPcNuMsWRh0+zuZbGNE2suMhul6k3XXR7\n+zgY7qFWqXDp9auceuABljbWSdWTnHxiguXkDHrdz/pSnaRtA7WVpf9gN/aAm2ZApxWuMXg4QiK9\nQrWUoGrKGMUay/lvMnZshLrcwuY2CQRa7Jp1zGYeZ9OgtmkhvZNn/BF47s0v4r/PxVLqu1RLZRpF\nlbauTspaCo87grZkI9B0sZPI8ZFHP8Gf/tmX8Q9NEHV4Sc4uYurvLcm9r5Wcy6Vgs8k/qq3WaDYo\nl8vEolGisSgWq0h7PI4oiGxubrK1tc3i4iJWq5VYLIbD6SAWi3HlyhUMw0AURTY3t+ho70DVVSqV\nCoZhUCwWyeWyNNUmsiTz+ONP0GiozM/Ns7i0hN1uQ5KtnDx5gvb2OJqm8uJLL9HZ2YndZsfv9aO3\nWshWCUEQaWuLUiqVyGWyJFbWcDlciKaAbJHIpbPMTt/l4sUp3nl7Fq8nAujcuXMNf1Ck1kzS1Os0\ntL2/kw+c5ODRCSpqmYXVecpqEQ0VrGAaBm++8SaCLnKg9wCtpko4ECQcCLIwN0c+k2Xm1i3sNhuj\nY2P7Zb1+ykrFIk6nk6mpKQRBoFqtkslkWFlZod6os7u7y/T0DJlMBp/PR3dXN36/j57ebkLhIIIA\nmqZRrVbI5/P09fVyePIwgwOD+H1+rJKVcrnM1uY2uVyOdCZDJpelt7cXh8OJqqq0jBZjo6NEQmEM\nvcW5c+dIp9N0dnUSioRxexQS6ytM3bxGpVqiWMwzOjrE3bu3qTvKRIZCePu8zG7fRumw84Nr3yfY\nH0IQQWBvt6Omg9oySa4ncUkhbKqCVXVgbTnIpspMHjxCvlAmEIkghbz4u+LgcRId7KUiGhiKHdUi\nUClX0DSNUqmEx+vF5/dRKBaIx2M/55b8YBJNcCsKVgQqxdLeF3u1xtbWNqZpIssy5XKFTCaD3W5j\ndnYWr8ezN4G/c4d8Pk97e5z+/n4K+QKKV8HudlCr1pi+NU2j3qRerDE5cZzFpRlyxW0Ul4hTEShX\n0sg2A9lhIEkCg4MDaJrKt7/9HBsbW5x7+FH6+4cYGRlHcXowDbh9+zZut5Pl1QXGJ0apN+q4XB5G\nR0ZRHArBQBCPx7tXYN9pw98eR7BIeJQgYaWNHl8naq6BQ3Zitdrp6uvl1JlTPHDuQb76za9x+PAx\nfNY2PEIYlxnCKFhpk9tJzubIrZWJBmO89upFRscOcujwJI8++ig97Z30Dfdx/tNPYu94bxWj3tdK\n7h8GRK1Wo16vI0kSDqcDXbJiE2zkEjlaRotsNks6nUYURcp/vwSXrBL5fB6bzYbf72dzc5OWZkdR\nnFSrFWZmZnjooYdoNpusra2RbdYRaCJ77QwODvLuxWvcmLqOpqtEwhHUporP68fn87G8PE8kEsHv\n91MuNQgEA5iGiSRJiKpALBbj5vwtkjdSOCSFNk+UtsE2GvUGy8vLzE1NM9F/P/5gO26XF9kmYQp1\nbt+9wn2+M+iEECwC9VYTi0Pgd/773+ELn/8CZh1ERcDpc2CxuThz9jS5UpZ4PM6rz79K2N1G1B+k\nVWuwsrLC2vwitWIJ1YTl5WXq9fpPNFj2/Xh2u53+/n7m5+cZHx+nXC5Rq1d/tKtSVVXW19ex2+30\n9vZSSBfI5XLM3ZtjYHAAn89HKBRCkiQ2V5YoFArcvn2bQCBAKBTCIlpoNBpYLBYsFguCIOD1eKlU\nKhQKRXZ3d/ELCi2hhWgR9yaBsRgrby8hla309/vJ5VLkcjl8vr1C5jdvXcPhlNisr9M2FsOvhuhT\nBxkdneT//tP/hIgJVjBMaa8MVEWgKTXYXNzEF41RaxSxSS4kUaFa0klnd5icPMa9W8t0T46C1WQn\nt01bT5hCo4DXG8O5k+Pyd95m88483f4ws3fuoDslNit5fulffvJ9fjPsey8ckoRomAiGgSSICEIL\nvbVXvaZaqxIOh5Elaa++r1PBKllZTawhyTK3bt0iGo1Sr9eZmprikfPnUDUNf5uX/tEeJKmNRrVJ\ntpBjNbFCqVCku6ebpZVZLKKVxaUZIuEI9UadM6cfYHNxjampa6RSKRTn3rPiULCNQLANo6WyvbXD\nxuYaHdFhfD4Fj9eJy9ZFM1snEAyQyWao1WsUC0VK5TLBWIy6KeDwBGnVRVyCk+TqOremb+GIdXNo\n4iCqprNdSnL86Am+9OEv88IPXmQwOsHcnTmmr02hlRv0yCM4KyFaTZHv332F+089zM1bdzh40EFb\n0Ek1m+FL3/gb3IrA1vb2e4r7+1rJ/cPDaEmS8Hg8qKrK9tY2bpeLSnlv9ttsNrl+/QYLC4t4PB6K\nxSKmYeJyu+jt7cXj8XD27FkefPBBtre22djYoFgsUq1WKRaLlEoldE0nFApTKBZRNY1Lly7h8/mx\nWCyYLZGBwQGcipPJw4dwOBw0GnWOHz++9z61KpJVolQuoqoqCNDb20ehUMAhKvidQeamFzAbAqvz\nCUb6xhjpH8Pv91GpVKlWq3u14rxeLl16G5vDTraSZju7RaGWQ3AK3Jq7SbAjSLGZR7Npe9VMdrd5\n9lvP8o2vfJO/+vOvMNIzStjnpysax6+4CXsD7CQ2CLq9yBYrtVqNXG5/Z+VP09b2Nj/4wQ8wDAOv\n10s+n8c0TXxeHyvLKyhOBafTyaOPPsrAwACLi4ssLS6BCY89/hiDg4M/mlGvrq1htPbeJxQKMXlo\nEpfLRblSZmFhnuGhYQCCwSB2h51SqUy9XqOQL3Bn9g6lUpFMNkMhX+DMfWfw+wOMjI7SP9CJP+BC\ntkM2v4PP5+SdKxfo7Goj3h0Dm4E74GRlc4l7i7N89rc+g0oDXTDREWjUAQOW5xZplQzcRgwz7cDM\nOvCJUa5cvMHRw/fRFuvg5P33YcoWjpw+ycr2Ogurq1gVB4FIGNnlpLOrk67uLmDvDOw/FEkvl0p4\nPB4s+2XnfqoCHh8RX5BKrohWayBjxS076OvrBxOcDidOp5NUKoUsyzQbTSSrRGItgaZpDA4O4nK5\nOHPmDHabHVVsIikytWaNU6dOs5XY5PIb7xB0RChVcyR3N2mqFXKFFO0dUWxOCwgtMrlt3F4784tz\npHczdHX3IUlODk4cw2F3o6omhingdrnJF7IcOXIQp2KhXq/hcruIx2K43V5u3rzJ3MIcAAfGD9Js\ngYmdrY0sq/M7fOebr9IoWJGtTjLpInPzi5x97Bymw8JmdZuzjz9ENNiDXfTz+nNXsFbdrN1MUksI\n5JZqVLaqoNvo7hti5u4c3/jbr5OYXSDqdKGm0gRs76246vuuXWmz2ajVaqiqisfjIRDc+3kdQRSw\nOxxkM1mSyR3AJOAPMDQ0RGdXJ5qmIYoi4XAYxaXgc/tIppKsra1RKpWw2+0UCgVWVlYYGR2hUqkQ\nj8Vp6S0a9QZX3n2H4eFhQuG9gqWiKBIIBP7+fEmBcDhMJpNhcHCQzq4u/D4/pVKJTCZDqVigu7ub\n/ng/ckumsFPg2a8+S8ARYH1hnd/89G/Q1m7j0NG+/5e9N42V7DzvO39nqXNO1al9X27dfel9Y7O5\nNJsU2RRFkbI1smXHtmJEk7GdcZxgEiMz/pBJnBlj4gAZTIwgM5MEsMdJ7MSbZMmkJEpcRXaz2U2y\nF/btvn3v7btX3Vv7vp1T59SZD8XhYABrQhoKBAj8fW6ggfPUe9/3fd7/8/+TTsfweYP4fSmwgyx/\nsEfHatMym3TtNtV2GTWo8NmfuEh2aQLB4yBqAo7gEAqGmU5NYzRNzIaBYFjcX17BZcPi5DSHpudY\nnJzmcxef5uTJk6gfs0if8vGwLItGo8Hq6iq9Xg9ZlllYWMAcDkmmkly6fImJiQny+TzBYJC9nT0e\nfvRh7JHN+vr6h0PgXRr1sfLQMMcmBh6Ph16/RyKR4NKlSwiCwFMXn2JmegbTMEnEE4iiQC6Xo9Vu\n0Wm3ESWJUCiE2+1Gcbnweb30uj0CITeCaCKIQxwMHNHA61PQfS6GbRtt5GF7ZQ+fGEA0ZdLBCWQU\nTMByoNNxaNbh8psvc/3S+/SKAoOcQGW9w51rm/ziz/4t3njtMrdurTI3s8iLf/J1vvJTX6ZdrCIP\nR6gjqB0U2dvYxOVykU6lEUWRfD7PI488QigU4tKlS3S73R91OX/s0FWNbr2JKkrE/CFGhokqSnh9\nXk6ePEkymaTZGB/4dY+HWDTGmTNn8Ogezp49i2VZnDhxgoWFBQREZA8cPX2EUDxMs9mk1+zTLDVZ\nubFCs95jezOPY7nodyxEQaVcbDKyZUrFPFeuvEU0EuKhhx7i8NJRBFS8eph0chqQGfQMJqcmqTfL\neH0KxWIen99Hvz9+oorFIizfXh538zSN+l6FycQkI1Nk5e42K2v7zB1+kEYHvO4AsqxiWDa7xX1s\ndUTD6mBrDo6msnjkKOefepJiscP2WomDnRal7QZOC/7JP/wt/uwb32IkSAwNi7UbN/EHQ2jZDL2P\nOcf5iTY5Sfp/UwhcLheRSARZksnlcugenXAwhGGaeDwepqanicZiHD16lFgsjq7rH40Y2JbN3dW7\nFAoFKpUKhUKBdrvN1772NSYyE3zzm98kkUiwuLSIbdmUKiWi0RhbW1tkJ7L4/X4G/QGjkYNpmqiK\nimkY4wFW2UU0GmF2bg6Xy4UkiOzu7RGNRgnqYWrFBpWDGpl4lonEJF7Vz2/95m/h8dc59cAEvqCL\nVrNHNDTPdOoRXnt5hd6oR9/q0bN7tIw29XaVerdOuVlCj3iIZiJkpycQbAj7Ypw9ehYFF91mi6tv\nX6G0X+BgL481MKgUS9hD60Nz6E+9AX+YDE0Ty7KQZZlIJILf76daqRKLRXHJ44DeGzduYFkWu7u7\nPPb4Y+Rzee7du8ehQ4eo1+sMh0PW79/HJctYQwtN1VhcWCSZTPKtb32LRrPBQWE8hzc5OcmJkyfR\n3Bq9Xo9bt24R8AeQZBmv10symURVFEBgIjtBrV6j2axQLOcQJZup6QwwxB/wUKsVCFphvvXvXuLq\nt99nwj1Fb3dARpvEjY8hDoMh1JsCzsjg7Utv0K50eP/1ZfZXqtS2Wyxfu8fLL76O3xNGFGX+5e/8\nSxIunV/56V+gt19mwhtC6Qypru+QW93EGloEQyFisTjlcglFUcZ5e5UKe7t72Pan3qo/TKqlCvVK\nlXg0hs/rxaO5sYcWiqLQaXewbRvdp5NKpT4cyh9x584yk5NTZLNZpqenqdVqbG1toWka2cUpyrUS\noiRQrVR484230Fwe6oUauifCrZur9LoOgz6Yhsjnn/0S4UCag+Ielm1QLBU/zP0MMugPkUSNaDgJ\njogoSYTDYbxeN5ILZGVEr9fHGg4RRJFEIkEkGhlrLTQ3WzfuMmoaPPXo0yQys0jeCDMnzmHpIbx6\nGN3jx3YErr53laFkU+3VKPWqNEdd9ptl/vvf/B8JxiI4sowkq/i9ESKeOP/in/8rorEUne6AyfQE\nS9OzaLKbeHoew/54tnOf6K+sLMsoioLf7ycej6O4FPYPDqhUqiiqgtfrJZPJcOTwYbLZCTweFcMw\nqdfrzC8s4PcH8Pv9HOwf8L3vfY9iqYCquRhaJv6Aj8NHDrOyusJzzz/Pk089QSDgwxwanH3gLKIg\ncvGppzl+/CSWbVMslajXa2xtb7KwOMf6/VUyE0kSmRg9s8u199/hzr07aB43qXias6cexO/241U9\nTE9keeapiwg2JCIJPvfUM+yXbiLJLUrFPba395CFMHMzD5Hb6WMLFn27j2Eb7BdzDB0Lyxly8vQJ\nUpkkk1OTLC4s4tG8hH1hJlPTMBSYn50lm0nj0VT63TayKGL0e3g0DUVxMZnN/lXWyqf8AAaDPn6f\nD9M06fV6xKIxMpkMqWSajY1Nfu7nfoF0JsPAMLCdEXfvrXB35S6qprG7t0uj0cAe2eTyeSRZZjQC\nWXKRyUzwwa0Pxo7tN6osLi0SCgWxbQuXIpHL7VEul9jfz3Pk6GH8up+AN4ADSIoLB4iF4wy6A96/\n8S73N9bQPCoPPHgaRZMBm3trd3nlT1/BKBhkPBnCYgSjaBKRI4gjAXAwLeh3HQ5yHS6ce5hGqYlk\nuinsVlBFL5rLy6W3rvDyq6+yurGJV/fitkWsZofpaIKI5kG1bDqlMp16jc6gS6VaYXIyy4Xzj7G7\nu8v9++v0+j1KlTL2yP7RFvTHjNXVe2iaSjKRoNNuk0ml6bbbjCyb7MQEbreb/fw+3XYHy7bx6l4c\nHPL5HI7jcPnyZY4fP441HFIsHCDIArlSjv1inj/4wz+kXKzgUTx4PV7cWpiLT36BXK6Crkf58k//\nIrLkQ1WDhIJ+Di8u8fiFx4hF45w+dRZV0amUG/QHJjgOqVSSdrvJ1PQkgujw4ENnCIWDjEY2ezt7\nrK/dZyKTZWPzPst3btE5KFLayXPpzTd54onPEoxnqBojotk53KqOS/GAKLCydg9HhM6gQ982qZtN\nMouTrO6so0cC9EwT0xlh9k2EoUij2WWvUCA1OcHdlTsEdQ9+W2HBm2V48F/AoHk4tPD5/KiKSr/X\nZ3pmmtHIQRm1EcURILF1f59gKIgqpek0JAS5QeEgh6pIyLJMt9PEGPRYX18hIp8h6PLR6FcYtfqE\nfEF0wUVc19GUWfy+HjMzpyjs3SOWClGsbnOQr6LqQ/z+KMNiB68epVnvMyE9jqU4fO933qLWKhCb\n9HP8xAOUC/v4ZxVeufEqZ45dwNsNElOOsd7ukT+4RzRps7GxzIWHvkypHaBY36B47wrPPhvA4+rz\n4HGFu6/c4uLTF8nn8ggjg67do1su4wqqBFNx3B6JUddEnXAoVnaxjB7VYY2okWF+7iHef/860UiW\nWDSGYRisrO2jh+NsbGz8FZbKp/wghiMRR9JQPQFSmRmGI4lGqYkcOOCRJ4+wuBRnKjjN7/7b36Nd\n7RDUgyiWjNU3aRebqKqKNBI4s3SS+m6VhnuNSEAiX28QCCoM6h0WT03y6MJD1EpDzpx8Ahi38a/X\nr3P+3LPcu3VAN1FkqGdwjyTMSodULIl2TGd0pUYzJzCdnKFf7NEv9lhILlIqlSgWi7STCR56+jxr\ny7epKy088QQe7yIu0cvaNmhu2Oq26eo3yD4f4KdOf5Y//t2/4EHzOMKBQVzz8df/9j/ivTs3WDp8\nhDdefR2X38Pc4eNs7O3z9su30HWdzdUKRxNHSQphdts5wgtZtg9yFMplZhbmuf6tG5w5coz+oPWj\nLeiPGarPT2/kMGq2CSVS7ORzTC8d4m5tl0FQAcdBjwVRNZV6o4rX52Zp/jz9Xp9Wq81jjz3NiRPn\naDYNJMlFbWsNn+Vhf6eM2B8wEXeTiUboND2YUhVNE5Akk5mkn6A6Qk/4udGtYmYUat0OMg4Hgw0+\n2HiFpROnMG2HYiuJpk3harpxjB2mohNMBVOkpcPcqb9MoWyQmgjy0LNHiPiCyOIjrC9Xiasyj554\nnHK/xO/9/v/GQ888RGpeJ304yKhYJ5U9AXcUWg2T5ZvLxCe8FLdXcdsJyp0SHkvjsbPH+cBcppar\nE8hmqNcq3P3OWxxqeln/15fwBj3UYwrBVAxfKEQilOT2x/jun+gm5/P5ODg4QNd1EsnER2KTaCyK\noiqEI2F0r04ikaBWq3H+0fOcP/8Y8VicSCRKp9Oh1WrR6XY+tAGTCEf9SJLD1PQEx44fwrIMvvb1\nP+ZbL3wDo9smk0rQ73QQbZGgN0QmkYZdlcbtNjtvFVh7ZZtgO8YXT/8Mv/TM3+If/sY/5tSxs2C5\nyG+WODZ/hkbB5KEHnqbR6CBLMvF4iOmZDC5V4ks/9bOIjotmvsTb33uDW5ffJXdvkztXbzCsdfEJ\nGuVimdxOnoA3QDgQoVqqMmgPiIUTBD0hFNGFPbSRVRfNdoNau0Z2foKhZNCxWih+iaZZp25UqfRK\n7BV2WVtbQ9M+fZP7YeL3+fF5fRw7eoxjx4/h9Xrx+XxEozE8Hje3bt6iNWjjOHDr1i1CoRC7e7tj\n95N6g263S7VapT/o4w/4cRyZ3N4+Ozs51tbXMM0eHrdCKhPD5XIhyzKyLOM4DoZhEA6HqdWreDUf\nipIeqtMAACAASURBVKgg2CKGYbG3X6BnWkzNzzM9eRyfJ8XQ0PiTP3qJe3fzTGWPEQlOo3tV8vld\n2u0mIDCVnSEc0hiNwOeDas1h5HRRNQdFEel2u2SyWUaeEaY0oGf1ePE7L/D2lbdZvbuKORjgOA7D\noUkkEqHdbrO8vEytVmN9fZ2dnR2ajSaX3nqLVrPJzMwM29vb9KwBN6/fYL9w8KMu6Y8VZ8+eZWJi\ngmgsykR2AlmW+eCD2wT8AdrtFpIsEY1FKZVKdLtdPLqHu8t3cRwHv9/H6dOncRwHSZLweDwMTZta\ntY5ljXC73Rw5ehhd16hWS7hknYAvjqb4+Xe//0f8+ddeZHv7gPOPPonZMuk3+3hdHs4//ChvX7pC\nu9VmY20dtyLg0zVGlkk8EiW3vcd//Pf/id/49d/g2pVrTGWmaNbbdLptItEQxUqR4WiIPx5E1RUE\nFxw9cpTi7gFGo4/dsxAQCfkDHDtyHGEkcPvmbdyqTqfTZru0zlAZ0Hd1mTw2gSvuwpPxUOgVkHQR\nYzTAcEy8gXEXsNvporhUYrEYqvrxDMQ/0U3OMAzCoSD5/TwzMzMM+gOi0Qj1Wh1zYBIIBhgOh4xG\nI86cOUMgGMBkSCqdwu/3Ua/rlEpF2u02Ho+HbCBBq1Wn22sSDs/S73fodOvE4yHev/omGysCiYjM\n7sYWdiRD2JNGcXRky4Xb7UXRvWiqn9OHz3L40DyMIJF6hIWZRa7eusx7t68Q8y3iFgp0K6B7wrS7\nq2zt3GN7Z51g0Mv2Vp6Ln/kCb/yH11lb22VhcRKf18u1715h9ueyaIaM0TDZWd0lfPoMoiEyEZ0c\ny8cHoGoausuH5HVxLf8u4VQYo2Ngq0M6vSr1ZpUuLWxnhOAW0HUN3fEwyA+Ix+J/pcXyKX85wVAI\nn9+H1+dFkiREURz/9pJQLdZpt7vs7e2xvb1NPBHnzp07SJJEt9vl5q2bPP/c89TrdQRB4Pz58xjL\nZSrFKnZ//N6bSIRxhoAw+P8sMNu2xwKURILXXn+dL1y4yEx6FqPXJ6xH2Fi/T6PRxXAkYp4MjXqd\n7c0683OLNGsO33nxMs8993kSahnVBaVEHNuGmdlFNEmiXAZ/CJZXTGwa7ORuEZ22cGseLlz4DKs7\nVxm4evSMIZPRBNFhhKvXrhELRXCcsSAnEol8pNybmJhAHI3QdZ39UoFgMs7du3cZirC6usr58+e5\ncvsSmcinoak/TGq1Gi7dNRbqCQJPPPEEB/sH5PslquUq0WiUWq2G3z9OoS8Xy/jDfgzDYG5ujmKx\niGEYFItFRnYBX0ik2ehhdIdoqoYgOuzsbTG0uxxaeozNjQ3u37/PM08/z+b9HHeW15mfXWBre4ND\n2TmGxpCf/a++zHvv3KCU38eyh4iOjeqSMbpdVm+vcP3a+xgdg2g4jJpQGRk2sWgMkQaCS+DRJx4h\nv9MnGw5wa+0OrUGNfHmHzz5/EUWU0TUPV966gksMIIouHn/4Cd69/Rb9Zo9QJIgp1yh097A6DlWh\nwsDbx+vzkgrOonQF9leKdIZDTpw6wo17twkE/Lz6yqtcv/beh+/d/3k+0Sbnco0f7z1uD/V6Hcuy\nCAXDVFoNRs6IcrmMLMn4fD5SqRTdTpfvX30Vx3bY293Dsi36/T6maWKaQ/pGk1rjgJmZNPV6iUBI\n48zZE3h1hWhLZ3vzNjfffR+GA0xlSGfQp1Hss26t4tX9RCMpTp9+mCt7b6Ev6ATdQaSWws5agcpe\nj8n4cXQyHMo+xjvvvoMnOSASDqO5VbITE9zf2KBR67C3XcVsDVFGDtlIFkVRyKtFrr99k/Rkmrg/\nwc69HdqlNisrK3zmM5/B5/Oxur7Gg0fiTGSz/Na//Z8REDh6/Aizs7P0OwbdxpBUKoUsSwT8AV5/\n4w1u3/6Aaq7O3OQCB/ufnpR/mITDYY4fP87e7h5bW1sMh0OWlg7x3srrRIJR+r0e3/7Wt9na2mI6\nPT1W8GbTlMtlPB4PnW6HRCLBuXPniEQiZNJzdNs2omwxn5lFQaSQ22NyKk7rw8ioRCJBqVTCpbjo\n9XrMzc4ym5ghqIVQ/Em+853vEAxEsByb8IRBjBS1SotoOIUsaVy4cAFRFPn+69+n493il776VWqF\nA/qdHgtzR7ARCAYc+rbAwGjTHR0gudrsF/IoapRAIEFgTqfTGhCQA6zv3MPojbjw2FPsbe3gxuH7\n3/8+mUwGt9vN9PQ07Xab48ePUy8WiMfjRFJJPEE/lgiPPfYYU8emmD0xxe13P/hRl/THilarxfH4\ncSrlCrVajXA4TL/XJxaPMegPqFarDPoDJqcm6XQ62JZNrVHDtu2P5uM2NzfRdR2Px0vPMClXangk\nL7qmUC4fEAlFUF0C165dZWpyiqeeehLHcZidm6Feb7C1s4U+cJO7vcvixBTf/tMX6NVb2OYQezTk\nzgfX8agaN669w8a9bSRLQnZc6IqfoBLEo/hQVJvBwMvbVy+hyFk8ygQLZw8zWhWoVVXOPnyGu3dv\nEY9HsG2L5evLvPfOHX7zt36b9bde49DsYf78j/+cn/+vv0yzW8boWLRqfaLeIcFsCJfgIZlJITdM\ndrb2iGWi9KwBqWSKg2aRkydOYgz61Evlj/XdP9Eml4gnkDwCPp+PXreH5tawhkMkUUISJQzbIBKJ\n4na72djYoHBQZKdw/6Oh7cFggGmY4IAoiLQ7NdKZKCNniGH1ESQJl8uhb7TRZI1UzI8uzVHdL1LY\nPqBZ3Mc18uI6apKeS9PuN7mdv8HC4lG+8NXP86u/9rf5m0d/mX59hDIM4Pb50KwEPkEk4qqhBYtk\npyaoNXKkJgLs7AkIKCRic9z3bXH2sSW8sRjb29s8/uznefnllxG9PtxxN7poMepB3Jfk1tXb/MyX\nf4bugcHl711h+b27DLoG/82v/E0i6QimbVAf1AlOh/DF3YiCwO7+FkceXUSJixyslOjtmkRj0b/S\nYvmUv5xapcrt27cJBAJYQwtd11m5u4LH40aSZMqVMoVcCcdx8Pl8uGU3LcnC5xs7wVerVZaWljiy\neIRmp4nRF3Grfnx+hUa5QHF3h3qlwPWbYeJLD9LpdAiHw/h8PiLhCKPRiGAoROF+geX3VsgV9vFH\nwgTCbpAERoqXqYkkteYB3X4V3SdhDJuMRiPiqQBHjpwgt7+JqrrI7zTw6R5GFrhEqDQdBmaToVhC\nVBv0u1VGthuGXcQYpDJxQnqKTH2K3bUCju0w6A0IBLzjmSvDoNkc/1+qqiIIAtvb23gDfjweDyub\n99FDAQLRMIIoADA3O8dl3vwRV/XHh2AgOHZ1ckb4fD46nQ7JVJLN+h6SKKFpGgIC+/l9ItEIxUIR\n22UyPzfPu9feZXJqkt3dXSazk9TqNYzBCGekYDGi2+siiA7hsI+mM8IUe/hCErGk/tFhWtGGeAMC\nmpVAcIZcfukSbo8LwzG48e67+BMR3JKArPuxBwOG3QGD1hAZN85AAFNiKj1JrngfyzK5+PmnuXXz\ngG/8+QvEp0Jce+cyn7v4NH63m731XW5dukalVCM1OcnynQ0Odg9wCRqlXI5kNMXKrRV8CQ2vT6J+\n0KYvGWQzCwgjCdEjU9jfZerwFOtXdlBcPrrdAbrmZWha5HN5hh/TTOMTbXKRaATNPw4xLRQKRCIR\n+v0+mltDEAVM0ySX26Pf76G4FFyKC0mUseyx08Q4NHJspixKEiPbQHaN1XCiaDNyhvT6LQZmB6/i\nRrKHyI6N1R+gCgoLU5PMpo9zt3GVuJSiZfeZDS1i7FtcOPoZsp5pMGBQt/EpMZKRLAJu3IhkosdQ\nUir+4IhA2GEwaCOJAvm9IrMzxwnNTPPI44/TbrfxT2b50z/9U5JTk+TbLU6kM7hDbjqdDicOn2Qw\nGPAXX/sLTh45Q35jG5/uYzIzhTfoJRDxMRQ1DNHApagY8oBWq4UaUWg06iyeXmA2Oc/3/9PbCJ90\nlXzK/y8DY8AXvvAF8vk8o9EIv9/P/v4BdaOKaRr0e30cxyEWi5JMJGlU6oBAOBzGtsZKwldeeYVK\npcLRI0c4deoct268z876XQJujUw2yeJCmv3CNoSmsIbj37XX60VRFXrdHiPH5ut/9HWGtoXLp3Py\n4RiWIGKJAkPRxW7uA6IxGbc3QzqVplrdZm1tnU6ng5LNks3EGXZU8vk13JqHVtMh5INyWaDTqTHU\n6wxHNXqDGv22Tt8VRE9pTMQzuIY6Pl1he30fERFNcX90ezs4OMC2bUajEZIkoaoKkUiEkQjr6+so\nLhderxfDMKhWqlQHVVzWp8ngP0ziiTi1Wg1N09jd3UUSJWzLwjs5ThxQFIVer0en2xm/oXba+KM6\n1WqVQCDAnTt3OHfuHLu7u8Tjcba3N5AlhaFpMhpB0OdjN7dNyBcgHHHRbu+T2x9btjkjh77ZpT8s\nEbQjfHDzfSLuEOlMgit3rzE3NU2pXaPdLCPbDqOhxUQqzVYzjyZrlIt1UgtxSvuV8ciWbVGqlrCF\nIcnJBOnFLOekh6nWqzDw0qu3kQwQeianjp1GFv38we/9IX/vf/j7vHqpwu2bt5iff45D2VlW17ZI\n+lMMeqC7fIiCisOI7qiNYwzoGC0sezyX3ei0WDh0iL3dbWz746l/P/GcnCiKiIJIp91GURWckYOq\nqowch5EzGv87WULRVBSXwuKhBSLRMIZp0Ol26PW7jBwbQQSf38d+IYcgOShuCUQLGwPD7NI3O+QK\n29y89R69bod0MkU8nGT13n1m5DnM+xYZa4poL84/+Gv/gN/59X/BM0vjsQCzZ+N2+YgEEsiOjosA\nYf8Ebk1nd2+XcMRHp1cmkY5QrbUIBtP4Eyk80RiTh5b4g69/DcmnU+l3aBp9ZMGFT/cjOBJm30RE\nIpVIUy3WODS7xG/94/+FxZlFWq0W9Xad/WKecqOEQZ9qp8xeaYdqu0RiMoInpBCKBojH49Rq9U++\nUj7lB/Lo+UdRVQW3241pjt8uREFkZ2+HgTlA9+lkMhmy2Uk8uofcXh5BcPB5x2GnQ9PEti1yuT1e\n+ItvcvfuGvlcgVx+n1a7xeLiHJ99+knu3r0xjuvpdD6c1Rx+lHJQKBZxIaO63Pi8fiRZZTgSsAUZ\nAzDNJiOnS6OZZ2omSnoiyMOPHuPX/u7fwBEsXnzpm9xdXaZYOUB2qXR7MLKg1RxhmhbWaMDQbmLa\nbeqtBs1OH09IQ9Ac9gp7uHWNdqdDpVyj3eygaSrxeBzbtpiYmEBVFdrtFs1GA8EZkZ3IMDUxyfGj\nJ5idmsXoDel2evh8Pr7/5us/6pL+WOGSXbjdbjY3t/D7/BSKBUKhMOFImFgshjkc0mg0SSaTGEMT\n3a0zHFlUa1V6/R72yMYwDHTdQ61awzRtJMmFbTvUGzUse8jO7gY9o4PkMqi385SrOxTKm+wc3OPu\n+vvcuneNd69c48j8Ao1yFa/Hy+zMHMOBydHDh+m3O1iGgW0aPHDyDCFfCJeoUtmvkN85IBKI8Nu/\n/c/YP9jDH9Z56nNPsbR0iK7RZXphjq3tTbITk0RDEZLhBKlIkpFpo0gK1tDmpe+8hEt2ockK1955\nhz/59/+Rd9++CqaDKmhUCy2Mro2DwMzRGS6/+xa+kH+cc+hyYZtD3rlyjVg8jiB8vGvCJ7rJrW1u\nMDGfIZPJcPLcWfrDIeVWHc2SWVhY5PqVdzl8+DCKI1Pc3afX65FOZxi1wD1yQ6dLKjTJ9u42us+L\nVemQ8sXx9XzcvnYbWZYpFovU23WeCLhoNRySvpNkFzPk9/KkT8iEHghz594Izd1HiXVYOVhhq1pi\nIpWg05LYLZap2w3CkkTfqJFJhGnV6gSEDrlWmIfPXeD69e/TL08iDSWW5lusrP5TTh1+Aq+0A6aL\nv/9LP8s3v/ES2Yk5YokoetJgaA7ptVp4gxqhUAjFEHGJKrOpBS5vvI4ch6n5CfrDPpdevcS5C+fY\n28/jcqno3iiqO0Sr6UHTdIKaxvSxSW6uXv8rLZZP+ctxKz567SGWAVv3c4RCIVRVZcq1xP6NApYp\nYNsW0UyC9+5cJzwdxhx5sBw3SDLmoMup0xfw+rzs7eW59t2vUywWUVWVu8UCIV+USm2DnpOm36nh\ndru5feMqHt0Dts3/+b//Hzz//Ge5tL7N6dNH0QQXhbv3uXj6obHoYOQjcjrA8gf3WKvmWKzXub68\nydnTD7FRgf03trFaMuu1Do+c+HlCCAxkgbvLNsXuCtfX/w3pSYFjR59BqOyjCPcJBA5IJR5Ak9z0\nAzK9fhfDbIGrQyCqsp9vYBoyzsjN5sYBkUgaZ+Tmvds7aMEgtgnVQQXVXWIiFsbjb5DOJEmGFqnu\nNsi/tfejLuuPDZVGGX/UTyQeotGpk52eQPd7GPS6tBotorEovsV5isUisViMjW6LqOkmkvCzs7FH\nLJnA7o5oNwfIisZMdI5apYLsyAS9QeSezEOHniQcCLJb6dDKSazc3ySpB+kcVIgFQjw38SzNoINf\nTJNOWNgth6lghHy1hD0dZ6/TpDUSSB+bYaO8wcWfv8A7b15Fioc4dHoSSbeZnj5BsxzGas2hZkL8\nxE9eYG33Hhheyq0DcuUcHcHi9EMP8kg0zuUbt5ldOIlKiPztHEfOzpOOzFDZr+PuZ+l1a7TaDpNL\nEd598xInz51iWJBZf3OZo4FjTM8voOhBND1E/0BksL1Nq1Wgb368qLJPtMnl8nlCqSAw9rHUNI1A\nMIA9Gg/f6rpOu93G6/ViWRaSKDIwBoxGI1wftkNMyySZTOIIEP4wTdyluHjssQuMbJtGs8FgOCCY\n86FH3Wznt2m0Gzz5zGfYr+QRNYmJKZFWp0az12JhYYn/8Ef/K0cWH+O5Z79IpzPOwPL7fR860RvY\ntk0oHKKrdShu76AKOrdvXkUSJCT1gOxciJHbg61pOI4LLSbwxV/8GayhiDOyCIZN2u02gUAAAYE7\nd+4QDAZxbIEzxx/if/qn/4Tnn3+Ob37jm1y6fIl4Ik5qMo0YFxBkB0EWkfQgI8eg71gIVo+RzyKz\n9Knb+w+TYrFI+VKZ9fV1LMsikUjg0T0InT6DwQAYdyPq9fo41V4Qsawym5s7PPHE40AYtzb2QvXo\nJlbLDYEo3W6XUCDGa99+mf39fdyam+bRJqurqySTSbLZLNVKFVUVGBgDrCHU6zWq1SpPPvkkzWYT\nSZIwBgP6PRfBYIRAsEUqleLUKYkbN99namoal6ZhNgf0DYOJyUn6FhyUHEo1m62DdWr1Ms1elUKh\nQSySxUGkUm7SNu/z+YvPUd6osn5/nemFadxulVg8ht0V2N7ZwRPwoKKQr+RwRiOiqRAHpRoPnj/G\n8svXyOgRRFEh4I8yNC0KBweo2seTaH/Kx2Nkj9A0jcFggGVZY0ss3c3AbGGP7LG5dyhEr9dDUZSx\nGjZfJJpMcOrUKXYO8pQrZTx+L+VqFbc3iiAISJKELIlIiPQHfeqOQ7fR5NjUHA9OLbLy/k0Wjh6n\nnMtTPyiSWTwJQY1ZfQqrU2ZgDejU6xT28kSjURwTOs0OfGgkDw5LS0vs5bbZ3tni8OFFvvbiC/zU\nX/sCvX6HWCLCxqZFr1fl4mfOo6jgC7tZPD5DNJ7i6soK333lJR49+TC5/W1sLNJTaSS3TGe7weRM\nht3cNt6wB7M+ZOXtu+xtb6MIMv/tr/4dApE4nkCIVs+gZNR49omfJJEIcOf927z1+qX/7Hf/RO3K\naCRCJBwZpxD0+rhcCuFwGFmW6ff6+Hy+cUpBt4dt20iSjDEwwAFVVfH7/ViWRTKZJBAIfGTKXCwW\nGQz6HBQOxqGWnS5DycQf9RNOhfiJn36ecrNEIBZgp7CDW3ehaiKSPKJQ2EOSbIJBDy55rGCC8Uyf\nKI5niWzbJhKJcDQ7zep7m1gNmStvXmJz6x62I9JsSQw9Xizdg6Vr9BQHx69QMmt4Uj7cbjeiKH7k\nZ+h2u3Ech8npLBv763z1V75KKpMmmUyRjk0wFZ8iHU+AOGQkGYxEA1UXEFwmht1hILYZhYYo0U/f\nPH6YdLsdmo3muDbZSUzDZDi0aLXbGIYBjH8X29vbJJNJbNvBowyYyQYoHaxi9gq06juYgyKpuELK\nm2A+MUtQ8lHeLhJzRzg+fYSg5KPX6xEMBscK41AIe2QzOztLIBAgGFKQ5bFUfGdnB1VVee2118az\ndZLO9NQi2YlJ2u0WC4szrG/cRfe5CETDJLJpklMTJCYn6FoCOwcdCtUq3W4NlyLSaNb44NYyL77w\nXcw+SLh5+9UrmG2Tr/3Z19jc3uTQiUWe+9JzLJ1eRA5LPPLMOc48cYrPfvkiX/zrX+DQg4sIuk0s\n7md3dxNFlWm3u4iCi1AowdzcEvMLC2x+albwQ6XT6TCyx2+iAgKqouJxu4nH4wQDQZrNJuvr6/i8\nPtbW1vB5fczOzOLVvSwvL9Pr9XDJLtrtNrruwTAMDNPk8OHDeNxuEGA0GlEslzg5NU8rV+Taq29y\nZGaesMfL4vQcc9lpPGkvUshk4VSWyZlJEpFJ3KIXwRwyOTmJYRpY9li4FYvGKJfKlMtlpqYygMXp\nMyeJRMOUygdoHolqtYhi2gRUjXajSqdXZ/74NKY2oGnXSEwkCMUDtPtNLMek2a0ju2Uq3SKRRS/h\nSS/BmE69UsYvegk7Ic6dfATbK9OSDJS4m6JRZjl3G8tvoU6o7Fn7FO2Pp678RJucrutEY1GajSaD\nwYC9vV1MY0i/36NWr+H3+QmHwkiShN/vx7ZtiqUi3V6XTrtDtVrF5/MhyzKmaTI5kf0oU80ZjQ2d\nv/SlL9HpdEnOJMguZMnMp3nr3bd4/cprXH7/LSQdjI6PqcxZ5qce5ld/+R/x67/22zx09inW7nUw\nTRNZlj9SkCmKgqIoTE97OZbOMhs+wh//7l/g17zEon6efvp5ZmfP4tGj9AYOfdNEcImU6gUE15BT\nZ48iiiL37t1DURRarRZPPPEEoigyGA5wR92kZ5PEk3F2tnYZdkyahQ6vvvAaAU1HG7lw46JbaZAJ\np+jXOlSLFSzHYmtv6xMvlE/5wWiqhs/nw+/z0+v1yExkMA0Tx3Go1+s0Gg36/T5Li0vs7OwQCASJ\n+nQ8soBgDLD7Xax+m36jRjm/Q8D2UF7bZ/P6GlEpiNIVmY/OcDxzGE3TOHrkKMFgkMJBAYB6vY7H\n7eHo0aN4PB4SiQTBYJBSqUyn0+Hy5csE/Qncmp8Ljz3BYNDn/sYqF544S72xjzsSYHJxnl/+u7+G\nJ+Tnfs5hr3RAy+xRa+yjagKKInH48GEuPPYk6+t7bN3fx2WoFLZLfHBjmVQmxfyROXwJHcHvIEZH\nTD8wSfZkGttvoKZdHDq/wOnHjxNL+MhMxJidnSEYDHHsyBkS8SmC/hiNRoMjR478iCv644Uoity8\ndZNWs/Whv+8Ue7t7IIBlWyguBVmScbvdH5kL+Hw+2p02oUAQTdVQNfXDvDmNjY0NJFGkWq1SqVbp\ndbvoupd0JkPU4+eRk2f4qS/8BFhjk/FMNkulXufc8w+RPRUFvUexWuEbf/Y9AkqIYbPH1atXiUai\nnDp9iitXruDgEAgE6Pf7+IM6hWKOiWyCzz17kW99+xtIImxvbzAVmuTG2zeJBuMUKyUKjTI1o4U3\nFeTMw6c5d/5B9KCHn/8bP8fTz10kPhElPZ1kq3CfwaiNrIAsQSjgJ51I8JnHL/DMF58lmPJTbBfo\nOU2UECydmcIYNei2S2D/F1BXIoz9K/8f6Xu1VqVULiJJAs7IAcDv92OYBv1+f6w608apBeVK+aN4\nnnKpTCAcpJyv0O12WVpaYmFhgVwuRy6XI51KIXskunaLQyeXEN0QX4xS79a4fO0N5pUj1Gv7PHnx\nUdLRJRxHxjYhHPBimiaapn2U9zUYDAgEAsiyAF2bx49/hnfmr7FWvcyZkwv0uhazMw+yVTgAYQTC\nEBixd3+NcCTAV7/yZaKaF7/fz+nTpzl16hQ+n49wOMzcwix91WBAH58ngNetUy808UT8nFo8QrAf\nIByKsXx7HdGv0B02sfZMmp0GL3z3zxGMT/WVP0yKpRJRNUoqnaLTHh94ypUybtshk8nQbrfH+Vm6\nTq1Ww+PR8feHwNiIeHdt9cM2psD27jbu/AaKojAZzJLxp2k1m/hGHiRHYLte4qBw8FHbfnl5mfPn\nz1MoFkilUpTLZVRVpdPpoOse5ufnefHFFxnZKqFgEJ/fw0Ehj20bKIpD3+jh0hRcmhtTHCFqLvKV\nMr2RxaDX5/7GMlMLEnPzMxRzA3weDU0JIotDVHuIKqh89StfRfG7EFR4+4PLeP0+8I+o25WxK4to\njIVjfpFDZ+bYunmPgdmhXCki6wq1WotALEK/bxEIBAgEAj/agv6Yobk1op4oHt1DIplgY2MDY2CQ\n2819qDAXSafTtNotFJdCpVJhWGviSCLJdIp2vYZhD0mnM+zs7IzjxWp1arUa2YkstmmS29vj9KnT\n4/QLRaFaqyK6VWKZDM16nSe+8DkacpueVmfk6WPYFiFfGo/oIxB3s1rdJL+fwzZsZudmyeVyeHQP\npmHidrtYWDzKa2+8jNvjQRRHvPzqt1lamOOF33+JnYM9hgMXjtfF8fNnyMxOUjX6BCIRjp0+irNo\n0W418IZ1ur0GoXCQ7daQdCSFX/ShOgqdRpeT545gMKBRL+NyHcLot1m++wGKrhKKK+ys7xPUAoz6\nw4/13T/RJufW3NTrdbxe73iWxuHDtqQEwniTM0wDWZIRZAFzaH7k2B6NRsdxOvUG/UGfoTmEkT2O\nZZddKMrY4HlzY5NMZgJxBC7VTTQVoWHUCCVC9ModDmolhMENUukgL738x9hOk3NnL3J45jCvvnZj\nfILPZD66zVWrVSYn00gS0DXJZiN8+Se+wvfvOgQzYIxEXFKY/eV3EAQbRzBwKTY+y0butPnyZ5/B\nsBw8Hg/hcJiXXnqJ2dlZarUa6X4aKSjTt3okwykePPMg967cJxuZJEiYD178gGaziyRq2MNderYp\n0AAAIABJREFU7vt3KRVrOKpDXEyxurn6iRfKp/xg+v0+I2eELMsw9jRmZNu4XOpHp2NgnBQgSUxO\nZWnvVjBMg0G/jyZE6VT79Hpd/FoGadgmGYmRzmTw+3xUcBNQA7g649ZTuVTG6/WysrLCoaVDlMol\n4ok4+/tlNjc3SSQSzM7OYtvjVqbu8VA8qJFJZ1GVcataECwcwQTBRFJ1NL+XzqBPJOBmdfU+puWm\n2ety/OQhvOECu/kVOh2LZNRFMBDHr8uojQaS7eLkiZOYsoHqVfEENa7deoephSnK/QK2beMAmqai\n614kweFzzz7Jv/rX/wbFp2MYQ9bXtjkXy2BbDuFQiHj8U0eeHyYiIolkAo/HQ7lcRveMD1v9fh1/\nwM/QGtLutMnn8yQTSRRNRfXaCPI4tqlYrzI0LURNwbIsisUikWCIkWmxtbXJ4uw49NcYDLACYA4N\ncrUybo+HXLPK0BlyZn6K95vLFDtbaAOHF771Hc5OfY5EKMm7915By/qJhmMMh0OSySS9dh/d5aXf\n6+Fg0em2qFaLLKaO89/9vb/DyuYt7q+tsnungiW76dTh9ANnMC2VatfC6/dRKhTx+N0MbAPFVokm\nY5TzB6Tjaaz0SZp7db7xwtd5+vPP0Oo3WC6+z0svvcKXfvJneP/ty9zfWWX3YJvnvvh58lt38ftT\ndHoiQ/HjvRl/onal2+3moFCgXK7QbLWQFRfxRAIH5yM5Z6FQwOf3MTU9xc7uDslkEtklU2/Ux7e5\ngJ9oNMru3i7x+DhyYmPjPteuXmVoWQzMAZIsgSAQT0Wptaq8+fb3+c6rL7KycQfN62IkFai17zGz\nqPPCS7/H//UH/5x8LYeo1hgMBiiqgiiJqCoMBgNCIQFBAEfTwBB4+PQJFhem2T/YxOsPsLa2y+13\nrnPj8jU+uPIuL33tm3hFgaVMhi89+zmCgSDdTpcrb79NLBal3+9x49Z13rryJqgOpjV2gZnIZDk0\nf4iLj19kb3UXuSWTVBIU7hTwWwHEuoxv6GcxcYh6roU20j/xQvmUH0woHMKluNg/2KfZaqJoCrF4\njHAkTLlSBmF8CCuWi9Rq1bGgxJsiHppkbvoYU+klRobCsCeRCE8x6A7oNroUtw4IqkF8shevrCOP\nXChuBSQIhoIsLSzR6/XQVI27K3eJRmOoiko4HGZ+fp5qpYooiExNTZPbLTIYDOl2x0IYlyYhSA6O\nOESSXbgUBWNoIqsyB8UDDHtEezBkenKCubkpkokonU4XxxEJhaJEI0kSkTSCLXLz+i26nQ7VZokX\nXvomG7trSG6Z7rBPe9ClP+xjOkNwgaxI1CsVDi8u0KjWGPQMDvJFXJKGpuooLgXN7f4RV/THC8Mw\nUBSVzc1NfD4fiqJgGiaxRIx4PIGiqoycEYFgkE63Q6FYwCXLODisrq4ytIZobjebW5uk0imq1QoD\nw8QRoFQqMTmZpdVssbW9xfbeHsV6BYMRkVSSQDzKsbMP0B4OydX2KbT2KHf28YcC3F/f4fp7twh6\nfVSrtY/8WDudLmdOnyYaiRCLxZAEgTfefJ2nnv4M3X6b3b1tVlbv8NIr3yPoSbE4c5yf/uJXmEgv\noPvjNLpDDip1LMdGUmR6/Q4eXSMQCiJ+GIPWyXW4/N1L/MKXv0KtUSY1HSM5H+Opz13ggeMnqOzn\nWb55k7Onj2MO2iiORb8/wPH4EHTvx/run+gm12nUGYy6uGwbXZYRBAGr06F2UEVVVVT1/2bvvWPk\nTO87z8/7vvXW+1bOobuqcyTZzGEoTo6aIGvGkmzJ6wSvvQF39h7ucMZi/7m9wwKXjF3c+XZtr7W2\n5ZMlW8lKkyTOaIYzoxmSwzAkm6HZubuqu7pyDm+8P4rTlg2HoU9YAQK/QKFBgA28/Tz1hPf3+waF\nmD9KMVugmCkwEErS3G4gCAIqCmbHpGd2+xEeNZNi0MAdGqBbbbB/+ijF7DZBzYu22mTdX6CSaVHM\nljArHsakw3i6Xg5MPozTEURRFI4fOsE/eSxMt9Mh7Uuw4bhNNxAl6A3jwEmrbjI7NYmp2Ziije7t\nl1UFS+CBI/8tqnCUSv4GbkcDva4zMjFKJr/JE899Bkux6LhjrDd0PENhNFkg2LbwiX4aOw1GxQOk\nWyNIV8Mcf+F+VkpLuKNu7D02a8oGUw8fZPXiBvO3buGOJ9lpV/sXAQHyCzkSkRiRUJD1hbV/zHq5\nh78Fle0qoiQRCUTp0KFVaBNUQuilNlHXIIqiMBhw3LGV06jlutiNbVSXi1qnQ6vVYk9qjFwux4Av\nzL6Dz/BW9SLT/+wI75obTCVT3H7zJmKzjX8pjBbscLt+A0/ahTfmIyDEuHXxJtv2OsnhCC2tima1\nCIQD9OwWn/7cJ/mD7/4hwpkcD598mLQnyb/+rX/N557/LLWtGsKDRQ7PHEOsDWPlBnBXynj0NTz+\nNYwhKGgizsgk8ZEGTt8O3/ra13nmqY9TdhTI6i42qgs8ufcx/pvf/G2cTjef+Mxz9Iw229vbDA0N\n4fV48fq86EaXleYm3pMJwqERPvnxGS6cfx+nbHFl6XXCgThBT4yO1v5JT+lPFQyzR7NVIRj0omlt\nsoUCksNG0kxapTKKdYe1joBugqWblGsdLMvaNb0XGhazkXGklkheE4hrKvVyi6HhCd66fYvpA4dp\nLW7gTQzRWc3iqnVYXrtKMwip4DZKD67+xVtkF7aJOOOMeCZpphtEkyqRQIpm9ypWt0Fxp8STjz/H\nrYUVLi1cZ3x0Ct0ho+d1yAkYNRUx6sdVg1OxMYbGR/GNJGjJFYZHJ9m5+gExjxu/pdKuF7m9tUxH\nM/jS17/E1L4UXatMKBhi4uFj/OqxJzlz5gcEZ8PoLoOW1WLu/iNsltpozQCHIo9TuwJDD6bwplVa\nHZMAErL40Yh7d5lv3y9JSg4Jh9zfLHpar29HIwjouo7skPthoAIIf8PTwzCMfr3Z6SSVSlMqldgz\nPYtHlFlfX8fq6pimRb1Zxw7aeINe1lc3qTYq4BGIRKKEgyEEM874+DiHDp/CG1CwLYGNjSyXLt8i\nPXgUp+LAqYBpSshOcCogyQK6/VfPFIvaeFwRNrIGmqExOjhJOV9E69g4BQ+iAC7Jh0cNE1RN3NEE\nzextVMlLanYPRteDy+1iaXGR1FKCwdkkjXaDgYEBBrwDWKU+08nj8WDb9l8TLsoOGUSbxx95nDdf\nuWeb9ONCIOhHVVV28jtAn0np8rhZXLvJ3P45ZFmmUe9fumzbxrIsOp0uo2NjfRq2Q+b69Xn27dtH\najhNobzGk6eeYu6ho8zv3GDx4nUkwcnlaxeZnr6f8KyfrLmBrRg0Wy1UR78sr2l9ssuH8z48PMxr\np19D2ruXjz/6OKIpMn/lKj946U327p/je2+8zq//2q9T8RepF1vEFZlKtUJLq6OKHZyqQTKZplGp\n0qrUuHjpEp3xOp/59Gfw+L10giLORJBPfuZTWIbJ48dPYXUtfB0orBcZH5lAaxv9np/hRDAktG4H\n2zDwOz1EIzEef/gJKpUyAKrD3SeH6R+t53EPHw1OxYksyyCD1+fdlVeZpomu6zjuBPW6XK5dJqYg\n9b+rAA7JQU/rUSwVaTYayB4fCytLJMNRZsZnyLVrbG9tMTEwwPr6OiHdxO12kyltooYjWKbF0toK\nze02qcgIRttkK7+NM+yg5exw6GAaShrXb9xCFGROv3Ya0xSIRsNcnb+E23+MT33qZ3njtZc49TPP\nML+8wOJChiMTe1DifkyvSA+NWrnE26++RkBSiAb8BFJ+0iOTfO/0m/ziL/4y5XqWajfH5Pgkds1L\nZjXH4f3H2NhcYTCRJBaKIxgytqnQ00TWt3KkUgmK+TaOqAt/LERTr7LT3PpI436X0dT9jdrp7E+W\nbdm7jXdB6Nt6mZa52w+x7xyKH8IwDBqNBqZpkkgkmJqcYn1jHVEUWV5eolqt0O12KRQKGJJGeDBE\nU6uztr3Owuotzn9wlh+8dZpG18IbTOAJqZiALUG1ZeAJJXAqAk4nKIqNU+kfcA5n/1l2n0cA0wLT\ntHAIEVzOFHNTR3j2sZ/lxP77sdsOHHjwq1GCagyzqaMITuq1Gm6fQrGZ48RDh1jZWmBjc5MvfvGL\nvPzyy7zy0itsbm4iiALtdpvLly9jmiZer3f3iwr9EqphGty8efPuhv8e/l4UiyWcTifBYHB3o1he\nXmJoeIhqtUq9Xt894ARBwDRNnn76GWzbxuVykUoNEggEaLfbbK5vYIVl9p/Yx62rV/HaMjFXiMWb\nKxSLTSzL4vbtRRqNBtFolFarSaVaIRKJEA6HCYX6fq2SJPU3nHCIWq3GUCxJIhzm1vUbhCNhtkt5\nfuFXfxlXOMhwdIraTgcsmUq1TL1bwpBq9MQ6b731FpcvX2ZpaYnPffZzPPHEk/S6PZbXVvFOpsjr\nbZKjaVrVOovvXyF3ZQF30ya/XGI6uQexKaFqnjsfNy7N1e8tbtfZvL2JV/HjdYcIh5M4nP2k8w+Z\nz/fw44FpmDSbTXRdRxAEREFEFAQMo29c73A4aDQbVGtVUoMpZKf81/aNdqcvzQoGg4yNjyP0DEr1\nKqvbGSRRROjoaN0elV6LTru9S76q12pEwmFC4SBb21n0pojeslCdHmb27WH/xw7gSrgQIxJ+fwRD\ntwGReCLGvn0zmFYPG52J0UNUqxW++/LrdIxtiuUMN66vUsgbrPW2qQpNLKdFyO+jsLSGUGygbZX5\n3ulXmJ+f59THThEJJ5mdPcj46F48Sgi9I/D2G+/xxum3uXLxOg7LRWG7gir5ScZG+dhDD+MOBenZ\nAg48XH93jdHwNLQsHNpHI+7d1SFnWRbRaJRqtUqj0cDGpt1uE41GcTqddDqd3QkURAFRErFtm3K5\njCRJ6LpOt9tFFEUkSaRcKbO6skomm0FV+ozIQMDPQw88hDfm4fW3X6PYyjM6M0y5XeTY/Ucptouc\nOfsOf/nyt7k4v8p2uYMuQLa4w3algNfnZHjUR6fXoVjawuuHdrv/PIWigS0AEljYrKxdR5IUFCnI\nUHQKvzPGoemTTA8fIBUao77d48q565jtAvXyGrN74jjddVzhNqERk8CgzdLSEnNzc5QrZQKBAMeP\nH+fs2bN89WtfQ1VVVlZWCIfDu+PUbDYJBPxsbW2xtLR0N8N/D/8AVFWl0WhQKpV2LxapVIpAILD7\ndhWNRXcNA2RZZmNzg7m5OaLRKOfPn8fv9xOJRBhIDqAM+XBF3LidEpd+8A60DNaXt/EHBymXyyiK\nQq/Xw7ZtPB4PA8kBPB43c3NzuxIar8/LG2+8wdjYGOsb69RzBW5dvkar3mBgcJAnnn4abzyEJxok\nro4S9w5xYO9hCuUCTh9kGqvorhobGxtks1kSiQSy7GBx8Taze2YJhkK0LQNfMIBmGEQjER598CFi\ngRCtYp3WRofc9TwxMUFzvU3IihA0w1SWyrz9nR/wB7/ze8yfm8fsgoCCbkqsrmySy+XYymZ/wjP6\n04XcTg5RFAkGgywsLCA5JELhMF6vd1c3HAwG0XWd9Y11pqamcLvdKIpCrVZDFEV6vR7Ly8vkC3nc\noozsdZMcH2F9dRWr1UHvdLFUB0vLywSCQWrVGp/69Ke5eesmlXKV9bV1UCVcQR/RVJLbaytcu3ET\nE+hqBuVSE7c7gGFYd/gNMv6Ays9+6llu3Vzirbfe4jd+4xkKhS1KpRKhYJhz5y+ymLvFZmEVS9LB\n0kjF48TcfnJrGzz15BPEY3FK5RoT43uIBAcRBS/NusmFdz7g5OEHcYtBlq9vsHR9HYfuolZogSTT\ntXqERqI88YknaNY6OFpOPv9vv8CVr11j8fWPpuO8q3KlbdnIDhnTNBEQsLERRZHNzU0cDgfxv+En\nJtB/o+l0OnQ6nd0bs8/no9lo0m63ObB/P4og4nO6WF9cZvb4fWTXt2i462hiD8kjsZlbZ3R2hOlD\nk9xavcHs+ByWZfGbv/1rPPbYYxzYv59mq0Uk7UJ1SWxs5ohEooTCcTpdG7cfKqUWi6uXefX1ebx+\nhbl9+wnHbVoNk2qxiV8dQJQMRFHH4VDRbQ0TA9Ps0apvoesWHbNLIhXFK4PDJxFMBJFlmXAogs/l\nYXxqHK/tZW11jfzODmPByd1yJUA2myUUClGqFBkcHERW77JafA9/Lz4UyrrdbpyyE03TWFlZ4eDo\nvt1G//Xr15menqZcLrO6vgaxMa5du9b3X7UsWq0Wtm3TaXYIHIqzUdrg2sULBGUV1VAIemIYbQeF\nQoFQyIclm3zv1e/xyU88z/uvXeRnn/40N27d5OrVq6RSfar3UHqItbU1jh47Rq+eRdAtktEYsXgC\nh+qi2u3QLufZWC3iDvhJeJ1IioSg6dhqE9FncOTIEWrFMrquo8gS1WqVb3zjG/jCAUJhEXdSori9\nw4HhPSQnRvqO7cEIvkabm2dvU6mUqVarLAwtYts2xa1tuvUqIdGP2BPZ2ShiqjKaYKK6vARdCu1y\n6yc9pT9VCAaClMtlDMMgHOpffH0+H7bVL51bloVhGHS7/TJmtVIhHA6zuLjI+Pg4xWJfChIIBHC5\n3aiAEHCTmhjl3GtnmE6PEBwOka0Wuf/UKbSdMgcOHuDy5cvs2bOHK1euMD01zZZdRY2oPPzoo9z+\ngyUePvkQXWeb7331TcamRpElFzj7STH5/BbtTo1er0GpXMJqtVHlcVptgb2zB+hke4yEUzBuEkvE\n2Fi/zfr8Ai6vm2q1Rb3RotFo0O5KDKZmUBUvpg3x2DDFTJ6HTz6O3tQJqFHQJNZuZ/gnP/eLCKKL\nlqZz5P79LGx+gCbWSaeTXHtnnkDXS2enTbfZ+0jjfldvcrZt4ZDvpCHfKf0JgkCp1J84n8+H4lT4\nkargrhj7wxKn1+slGo2S3drq32CCQZqNJuvr6xw6dJi1tbU+tbZZwhA0PEEX0/umOXzfITpGh5be\n5IPb73Bz7X3G9sbYqtzm2tJ7zC+9x1ZlAa9PYXw6icfroNFs0mhW+N3/6/e5eOkCO6V5NNYJxmt8\n9Zv/gbXMecrVddJDcSRTRTJdSKaKWwrgEj/8RPAYc7jMvbisvZi9UYL+g7TaCcLRfYyNjpIcSBCJ\nRWg2m3S7PR555JFdIWcoFKLX66Eoyu44NJst2u024WD4bob/Hv4B2PQ3i0ajwcLthb7sIxQmn88D\n0Gq1UBSF1dVVotEo4XCYrWyWkZERqtXqbh+t2+1Sq1apOzpcvXmZS+fO8u0vf5O//OJfYGng8cUI\nh8OMjo1x6PBhhoeHOXPmDKMjo1y9cpV8Ps+ePXuo1+vkcjmOHjuK1tPY2dlB0Ezy2SzVcgVEMEUB\nXbTpCTbl7Q6jAzNIgojXreDwgOg2cPgsJiYmGB0bxbZtXvzud4lFY4yOjrIwf4Pm4iZeXSCoujEl\nkfBYmuDsOEbIw1Rihp3FPCtX1pHaTirrNZrbHbz4iKkhUsEB3j9zjmalhYRMV7ep1Pq5iT9aKruH\n//9wyI6+NaAg4HK70HWder2Obujoev/jkBzIsoxlWei6QbVaZWxsDOjLtT40GfD5/YiWjSGB4RDQ\nul1Wb96mXW9w6tGHsWybcrkvEO/1emxv51AUBVmQUaedHPvEcRxBGVVxMZ6cZv3SFvelH6BSbuB2\n+fD5AwRDPnby2+hGD0EyCUT6Zf4rH2wwN/swiuLnU595lkBQZyIR5dj+WQ7sm8G0dMqtOtHRIfae\nPIbX56FWqzOQTKHrIIpO4tEhZIeHeqnNvukD9Fo6v/K53+DW1UVe/c7rOCWZbq9CS88zsT+JJyoi\nSRpTg4NorRYun4pD+WjH110ecjayw7FrS/Mh3O6+7VW31+81ffh/TdsiGu5vJpFwBFmWURRlN0vp\n4sWLLC4ukkwmSSaTZDKbBIMhlpYWaXZa6JjIqhPd0ihVi+QKOxw4eJCBlJ/Dx2aoN7fQzQo9vYzL\nazE9O8jX/uIr/Of/+Md87avf4ObNBX7n//z3rK2uUy5W+N73v87bP/wO71/8PiMTAYrldd5481Xy\nO1kky4loOBAtGafkwikpKJKC6vASdh8j4jlCyHuY0o4PvTdIsaCiKEOMT0zg9/tpd9oMDA6AAI89\n9hjdbo/gHZeCeq2OS1WZGB+n2+2wd+8ewuEwhvXRoiLu4aPBMPoi5nQ6jeSQ0A2DtfU1MtnMrn3c\nh647S0tLxGIxUqk09XodURSJRGMoqoooSmBDprTNSnaNcqmIT3Fg6RZebxDTEinkC7RbLWzLIhQO\nYZr9fsuHfpbtdhvTtPjVX/1VypUqZ8+fYzCVximKrK+sMH/tJqVCiVang8vjJTYwwMTQFMcPHqJc\ns3GqLiRZQlRsbFmj1Wqhuvol/V/5lV+m3WkxNjpKr92msZlD0Sz2TExTrlawFAc9l0TTNhlJj+L3\nBBiMD6I6VCzNxmE7kCyBVrlBOp7C7fTicwdIJlPEYkmCwTD1eoNK6V5Kxo8TtmUzNTVFMBikVOyX\n1CVRwjAMLNPENE2cSl8vrKoqTsWJZVqUSiXKpTJO2YmiKASDfXb51Ng48UQCxeOh19Mwuxprq6tc\nvXWdRr2Bz+Oj1WpTKZcRRGi2+nZgzgGZtfIqDa3B3L4DnH/rEs6eG6ssUq83kZ1OXKqLWCyBaego\nigO/z4duNXC5VBo1E4cUYnxsGujgCwqomDTLZSxDJ5aIEYpFeeaFTxJLDzI8PIRgg8/ro1Fv0euY\nyA43y0sbHDp4jNu3Vgj6owwOptm7Z46tzDZn3jiDQ7ERFYOuWUUXWqTSUVr1KopHpO2o0bSrH2nc\n76peJqkquiBgCAKa2WdeuQMBZLtDr62hixp+vw+dvu9ZpVzGE/KiWwbFcgmX243f50d2OonFYjRM\niA6nuHz7Bof37sd3J9frwP334SjVGJuaIjIwgOxxU221MUQRZ8/DgHMEv9/PPmWOs2fPEggEEcUe\ntyuLfLn7FuNbEsPbFlOlJK+d/x4PPPsC//6Vl/jECw/S7Q6xvrWNHTRxDMjMJUMsay/STJT7bEop\njKSkoeOHlgyWicO9TEBxEBJFQpYHX8lkT2gaOzTCy8UbNDbq7I3uwVt2sWdoiuzWGo/+zHEWr6ww\nengKWfJQq2oM7z/I4k6duiDwwj/9JX7w6mt3vVDu4e+GYjnwoNLIVfEJbujBRHKUbrWDIioILgF/\nwo/e00nFU6iyQrbUwljJEJYkTEGn1S2T06ocvP84PlNnJ1dHq8uMDM+QX88jdCt8bG6EjENFUBSm\n04cwlmU27SJNoUd4LsLAxCjr+SwPPXyKl7/9dSTD5MTkKOWbVyh7Q0iD43jlDOXOFil0jHaP/LqB\nXpghEo1y+s3btLSz9KyLBF1eYo4jDIWm2NjYYHL8eL/akZxhx7CZuu8xthav8P033qItSYzNTpHX\nSwztDSE0RRqXauQrOSRJwhZMkKDRqyEaDgR/kmf+2bOY579NUVni/Vdfo7Bc5uSpI4xOurh54fZP\nekp/qpCvlrhy8zqRSARX0IfT5ULTNDqImKJMIOyj02iCJhBWg5gVjUA4wNLyEhMTE2iaxvLyMgf2\nH2BzaY1g8iA3Lp1HM5rMPXmIQqbM/oEpAo4Qm8HbnF28zCc//izeW2XS0QnGJg6Cx8VDnhqZTBZf\nzCBwQCBzbZWP/8Jz/N7v/yGTIwN4VReWFxp0qWttQqpCZTvHQfc43/rgGvvvGyGsVGlvyvg8UzDX\nId/axqhlcalhonEvk4fHydpFph47wfpOgYpcY62eIRQKM7/wfZLJNOP74iyZb2MN2ozGB2nUc1xa\nOke6kWa9dZuXb/wFMyNziB0Xx+47xE6uwmsf3OTw5EG8bRNnIMT7nP8Hx/3u2JU2/DXC5B1K/o/2\n4TqdLplMBlV1oagqa+trSKKE2+0m4A9gmibLy8uMjIzw4P0PMD09haIopNJpup02yyvLlMplgv4k\nyfgIPm+I82cvomkmgijw4kvf5X//P/5X3n3vHfL5HC63gixLmKZOu9tkQgnSzOywurJCpdvkyZ97\nBinqY/jALIuLt5EkCbfbw9rqGoZhUK1U8Xl9yLJEKBKg2awiOjRsoY0lNEDoIBIit1Xn8qUbKIqE\n5NRwKG28Xg+nDv46o/FHEbUBrK6bcqFEvZpH79VQVYme1sAXUNneWeatd14hGJHoWGU2K6tUteJd\nDf89/P0QhT65qdfroes6hm5gGMYu6aRWq+HxeJicnCSTyXD+wvtYkoApCpgi2KKA4HQQTyXpGBqV\nep1au4nsUtnY3CQYDlNrNrhyfZ6lpSVmZma4cf0Glm3trgFRkCiWttC0NqrqpF6rUyqWcbt8uFxB\nAoEge/fsZXZ2lmg0SjQSJRAMEgwGSaXTuEWo1pq7f5NAnw0qOSA9NIBpaeh6l0ajis/v5tHHH8Ew\nDNbWVvnKV7/KN7/5Ta5du8b598+TTCbZ2dmh2Wz2UzN+pPxoWSa5XI7Tp0/jdMp85atfod5ocP7c\nOdJDQwwODhOJxv6rz+FPM5KJJLJDplwu90kk3R61ag1Zdu6yfW2r/136UFPbaDSAvpB8aWmJ9fV1\nOt0O4XAYSRB47NHHqNZqVMoVjh450k979/rAFBhOjZLfKjA1MYtH8TI+MsmBvQdpdDoEwjEqtTq6\nafDEM09Ra9X4uc9+hngyjm5rVGvVfladYdGstagUyly5OY8adHDs5HFyOwVefPWb/NmXv4CqeHC7\ngvQ6JltbO9xeWEagzxqNRaOMjsRQHAb1co7M+gKFnTW2MgtsrC0gIDCYGmRsfIxAIEAoFOLw4cM8\n/fRzHD92H8eOneDYsWN881vf5Dvf+RbJgRjLKwu4fS7qrY8WtXN3h5zw4Y+/OtRs7N1eBtC3lbnD\nOMtms6ytrSEIAm63e5eBiN2PPDlw8ABXr11Ddbm4fPkyvV5fc1etljn73jW+9pUX2dwoUK7Uabda\nxGNRhodTjI6lWN9Y4vTrL6O6JESHiW62afVqqNsNmps79Ho93AMx0vtn2P/gSUzVgarp+5U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CSK5BCo1WqkBlOsra+h9XrIssz62gqCIHD2vR/icaskYzGWi4ssF5cQQwJVq0S9U2F6bJxut82t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QP8+sRTeKMxhBp4lTY2oHXyRKIiNB3QXaSaRVvv0hI8vI/PU1rZI7Lk8MjsJ/jq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\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SzqT5tV/7NaLROK1WDzUqEdJE+oMWQWATDsmsLJ7guFTl6OCI6ckplhdP8OpLr5HN5Qmp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SMa0chmCxweNRh2DM6dWWV+fp5Op0tlZgZRcpjoExq1JpIiUa1WGQ6H6LqOKItIUYHDwxozxixn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\nbK60r3HywY+w1WpQ1Wd4/KGfxGw5uIbDN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v0t0Tp1gvkKvkmFvZRvKECEfCFItF3K4ALpebjcQ2Ho+fZkNHbRocO3rqR8e0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CSK5BCo1WqkBlOsra+h9XrIssz62gqCIHD2vR/icaskYzGWi4ssF5cQQwJVq0S9U2F6bJxut82t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IBO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lPYto2u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\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s5pmaKRDWNOq1JulMml/7tV8jGo3TavVQoxIhTaQ/aBEENuGQzMriCY5LVY4OjpienGJ5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K4X4Pse2WyeanWOaEQjmy1weNRg2DE4d2aV+fl5Op0ulZkZRMlhok9o1JpIikS1WmU4HKLrOqIs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\nSEj40JI4uYSEhISEDy3/P8pvWhTX1r+pAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2088fc4978>"
+       "<matplotlib.figure.Figure at 0x7f5427cf6978>"
       ]
      },
      "metadata": {},
@@ -606,7 +635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -626,7 +655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -663,7 +692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -691,7 +720,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false
    },
@@ -709,7 +738,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false
    },
@@ -721,7 +750,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
@@ -747,7 +776,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
@@ -780,7 +809,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
@@ -791,7 +820,7 @@
        "(4170, 2048)"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -809,7 +838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
@@ -820,7 +849,7 @@
        "(530, 2048)"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -838,7 +867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
@@ -865,7 +894,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -880,9 +909,9 @@
     },
     {
      "data": {
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a7u/u+eKLL1gulxSzbfK0Xqx1NG1N33U873Zsn7Y8755pjg1N02ISzTDEtXIq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\n5HlOPdRLISGK/DUEJraFDD2yVG6aeaAlzAkh+q9Wa/LcMUtfbZKgVEp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G8Tfxs1hApghF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t/PE8LKSuENZlpx63laoZv31+sCTS2Mk2VBnaqIqiLReYJVqKiJKeDtzGyyWZRKmGTQUQsXvDBM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Qgpjl1xXbbYPWiq4/zX4fIz5M4gninymkeWYc5Nkov+uF9zz0A9PgSTNFbFHqjcMoIhBX44dA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k0hFGUh0NpQ5MlxUJuMzGQsl0suLq44OzvHOctqteb29o6Hh3vyPA2Hy6JMZl1SJUMgqdFS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\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urvYrfXClmvY949RzuixA429z3uuc5cXwUSHMkcZLI1RQhCZBJwV2s+nZdTvhV2dDCYXT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\nXVErpRzw+4H/eflck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2CWVR0TQN93f3fPHFFyyXS4rZGnlaL9Y6mram7zqedzu2T1ued880x4amaTGJ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\n8On5ia7vyPOceqiXIkIUS2sITKoKWXBkqVww8/JKFBIi4l+t1uS5Y7a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TyDQWxCC8Ej8L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DEIIY3dcV222D1oquP83+HSM+TOLx4Z9ponlmFuTZ5L7rhdc89APT4EkzDWxR4I3DKAIPV+OH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guDFjneG7RKrnR5njLvJsYDpA5TCEVZCLQ2FHlyDtQmIzMZy+WSy8trLi5WOGdZrzfc3X3m\n4eGePE+D4LIok/GWVMncR2q0lKdiTUw7rpTSE8An9gdCMLQd+8OB3XbL5/t73rx5zbs3b9jcbgk2\nEko/iqgSRVPGcTgYxjPKUxc9WnSMj0kY34YgAqjEP0clTrVQUwP0OEYIIsKYnaiUJM+TI15ZVhRF\neTLiF0JQ1zVd153sEs4L9LlR0iPckY5+6NnuNhzaA4MdsN5hR2c/ERMfXY5e2CGm4F5E4nz3QyIa\nJAHZQCQk+9fJfS8GettjtYVMML9Ykmc5T26e8OTpU8pDxe3dHW3fkRf5uGPN/82aBz+zIn1ejE84\n11cQyPT5+Rs22XoCXxh6Tx+nIcsjZJGOkwUqX6ajTB+/HlJYa8dkiEnEYun67gQnLMoZz548Yz6v\ncd6x2+3oQkp8WcznXF9fU/QdRmt22x3q/QcWywXL5ZL5fM58saDM8wR3ILDdQJu1aKWwJKFL2yWO\n5363S/lqx+Npezj5jmQmbaPn8zlCiC+GhFLKU47idKOYMHwzbi2bfuBwbHEu0nd9GhgGSV3NuLl+\nyfPnL3n16pe8evktq/k1INjsG6wDKQrW61tuP93hved3v/s9T58+G9OtSw4OCi14OL7nrx/+H95+\neM9mu8HGgWpWoVVB0wY6G2m7Dm89mROEqIiklBNxKs4jzJHercdCHZOJv9AKWYIpJVmdkc1yynk6\ns1qjisTycHT03jC4Fo9NcIgKROEZXIP1PcE6tFAURifKY4g431OWJVHOQaQ4LSSo0VdcZwVPnjwD\nPo/MDMdgU/ST0hopDVIahEiRVIdDw/39hoeHzZgoLsiyikwnCXWuDZnSGDlmbkpJiOAnMCKK00fv\nPO2+YX13z+3dLXd3d3x4/57N/ZpwSGyF6JLJSXQeGRRCBFRMARUTpAGknzvCHHIs3JMfDnKkznoB\nbhThnB8BiIkv3R07+q5HSkGep3nRtC6nYfyEP09GY+cFevqa82v0dC2LFFS73jzQ9kf86NJ3WiaA\nyjR5zDGFGQtzx+BTlmn0CfoU49/OWY9QyQM+hMjQDdihY+BIyAIXqxVXV9c8e/6cb775JqWSO8v9\n+oF6Pj+F/v49x8+qSE/QxE853J0P9KbhwvT515Ht5yZIE3789c8EHvmeXz3/9P/TMHIyDh+GgaM4\n0vVpKj/h0lOI7byoWSwvyPPiZI40RAcRirxgNpvjZaIN7fY7goTF5ONcFBRFTp4VROkYtEbKdLOy\n1tL3aTB0u7/lc//A0KctYV3XzOfzMSC0phxpeBOMAYxT/clEJo67gQalFJeXl8QYxwtmhhSCpmlZ\nP2yZ1X5kmmgW80ue3DzjV9/+jpcvv+Hpk+esltcUeQkIrBWEoBEYvIUYUijvt9+84uXLp8Qo2B9a\ndnvPkClev/+Rv7z+LzS7FjvGIWmdaHZKWbIskucS5wIIl0QrQo0DwomnK07DQxE1RIWIBmKiMspM\nYSpFPi8oZgXloqK+qKjnFUVVoIzEY2mHlnD09LbB5IKiMin2KkaG3uLagBMuZVxGSSY1bojsdluk\nUBiZYXuPljH5SUSfpNBBcHExQhlNk+CudmAxl/StZRPS93uX1tZ+d+RwOLLfH8myAu8iUijyLCPL\n8pRwkmXk4yBbiJHpLD1u7LSjT9ze5nhku9nw+e6Ou9tb7u/vOe73+MnwTUBwjq5pGNoeEVI2pY+P\nhXq8SFLOYlSnjyqq5IFC6rinrno6zyl7MqZBY9f1fL5bs9ltcM6ednyJZqdPNMLpWgO+GNSfDw2/\n3vUKUjHuh4HdYYcNjqLKEVGQlRnSSLTUzNWM6CN5ViCMoLNpwNp0R47ugBs8BDBKk5kcZTQ5GdZZ\nXGM5tgcGWqpLw9XNDc+fv+D6+prl6oKsLHj2/Hka9I5S9vzfo1Xp11jy14/Box/sdIedqEeTpei0\n5Z8mq+f/fu7n/IVHNfFfdNFTcYZHs/4p8/D8dQAjy6SgKMuTUCbJeDU+gBpTQmIcM9U8EDw6zwgj\nI2OK5ZFS4k/0Pp/8BpqWw/FA1za4vccfIpnJyIucq6srqqo6dckhBNqupW3bE8Vr8jiYsPSJtjib\nzajK6hQ9P72+7XbH/ec13kGW5RhdMKuXvHr5Lb/99T/w/MXLZDSksjGPL2J0xtBH7ABaFywvrrhY\nzFku5lQCrAQpPIduYL1t+esPf+L1+z9SF3OKvEZpsGGP7X0SBmnPbJbjvBnd2hxg4JxxAIllwNhB\nn7poDQSkVuhCYcqMfFZSLSrqZU21qMirDDRJddkeaCxYP1DVBfNZlTL1ekcbGpq2RYYO5QXSR5Qw\n9Mee7TbJi623yLalLEuMycBamqbjeGzITE51VXMsj7x584a27fHWJ4rYYNludlxdXSGEZL8/0LU9\nzqZObrAJwst0yv0zRpGNUW7T+pYiJbl4b4ghufx1ux37zZaHh3se7j+zWa9pjkeiDxgFNk/MDO8j\nzeHI4bAnxsskF5/W9DhInKThRBAhfV8UCWsWcKKUEr66fk80vcSq6bqOj58+8vnzZ9r2cdenVLoh\n9H2y+NVa041+7Kc80Ul8NhbpCeo4L9RSpG790BxARKpZhVHJvVIbhdGGsiqTOlIZTG5G+XpH0x1p\nDg3toUeMMWoXywvm9RyTaVQmsWFg3xyIyjI3JRdXKy5WF+hM0zubGo3MIJXCujEar/h3CHecd9Ln\nTI7pOF8E565104Bvgh0mtsdkT9r57gR5nNNivuZJT3DI1JVPRfo8l3B6nqnoT7aJ2ZgE0TRHLlYX\nlFXFxWpF5yy7rsEHT3NMXOSgBfm8RsrH7Vt6Xk4DwcRQsfRDT9sl/Piw3zFTc57cPEGNVLupw5jw\n8SkZZvo7TVS7EAL7/Z6+70/uY/P5gouLJUopdrsdt7f33H76xPvbew6txWQFQpg0VFysePbsJb/4\nxa948uQKkBwPnt0eqkIwrxVr29IcB/KsZDFfsFwtsEGys5HKwHxR0/YDb//yA3/98Y/c7d5SvPoV\neTVHAtvdjuO+SZBAUTJfVoQgOR5b4pjq/kWBJrkREuWIf0qi+hLuEEZiCkNR5eR1TlGnyCaVp/Dd\nIQyEzmJDGsrOZ3PqeUWuc7pxKDn0LQzQBoWOEhkkza5lvVmzbbbJ00Ikh7rZfM7hcKBtGzabBFvM\nVmn7K8R4s3eWzWbLdrtB65RYXZU1zQilnYbU40BOq1SctZYYpRM2PYYhCyBojdcpLFhEcNax2W7Y\nrjfstjuO+wPeOqRIHHllBtwAbhDstnv2231S6UmDxCJGtW8UARGTV3QIkSBiCk4QJDZHMvkYH5gk\nMKnjjsQTnU8Khe0dd2NA7HQtTgV46qLbtk02n+NAfpqtnBfoqU58WTiSeMYHR2e7JK2fVRRZPrr2\naQqTj6ZmBXrckXVtj43uFH212+yIUbCYLahmFVGN9aST+Ohp2j26UuRVRb1YoLIsKSb7nqHv2e33\n7A8HlNE0fTfSH//t42dVpOERB562+RNFbCqKUxcx3VFPXOjxDZ2wLOsswaeBwDAMaK2Zz5LA45wV\nMbnaTRdG13UJX+r70887F7B8/bpOg8rxhnHoPdvtlsVhRTWfcexbPn36xPfff89fXv+Il4Jf/vbX\nfPf73/Lql99QlCXDkHyoY4ws53O0UifS/2Gk+pRlQZ4ZVsUl19WTE73w2BzZbDZst9tTnE9VVSdG\nijFpGBh8OA0Z/chQ6buOvi9Obn/OJS+P6+trvpmvqGdzFrMLbq6f8d2vvuO7X/2ap0+uqCvDYKGT\nkEJpIdNQForZrKQoM+o6Y7lIyjnnLfddy+6w4eOHWz7dvsVowepygZKRYThidEZd5WTGMAzJ73mw\nHd4lRkeSBBu8i7gh4F1K1xZRI6U6UdqUNEQvcc5jTEY9qzFFRpTggksqvjaQyzylyuQp2klplSxB\npSRYS+8CoY8oAWWW452jbxt8a3FdoNklNzVZKfKyRClD1w4QdqMDmidGyTB42i6tpZubp/R9z+fP\nDzRNh0AlXm474D3YwVGWM5TKqKs5g/VsNluurwZklewQjNLk2pwgAj9Yjrs9682G3XbL8djQNi3B\nepSUZFpTlSXOGOZyhr5WSQnrUzBvHLfldx9vqeqSyW1yopWeoLzZnLIqKfICBBwOB/quRwSBHzx9\n6Ak2ELLRXVKkLny6Rm2XdqFTczVR7pRUdG3HdpsUiHVdnyilk8jqZIY2NkXTGWOCFJtjQ9elFKPF\nRXINrOoqWaPqjExnGJ1htEksj3agbVoOuyOb/YZ9s+fQHBi8JTePmPWhOaSd7KHBBctytcTXnt4O\nBCLlrCKvCtbrNR9uP/H+/Qd2uy3L1QXDMGDiv0NMetqKT+naX0euK6VOuGvTNBwOB7TWJ1qZGrsL\nHzxt236R/p1lGfPFHOBUhCfI4iTzHodpm82GpmlYLpfUdX26OWitT13AuahAKYV0Fuvh2Hse7u9R\neYYlsGuO/PDDj/y3//rf+HB/x9NXL3j54iX/8T/+R7751be8e/+e169f07YtwXuKLGNe1njv2R8O\n7A97YoysVpfUVUklajKfBDqDHdgf9qzXa+7u7hBCcHNzw3w+ZzFfpBtVCNR1+nlVU53UaH3fs9vv\nEFKcJMNGa+bzBS9e/ZJvvvstMcJyecW3v/w1v/n2VyyLAksy1CdGtFZkGZRFcorLMsPllcF7KHJB\nXYKKkYdjz+t3P/Lj3/7C/d091g1cXi0oypfstmm7XZ4M9nMOh46P7z9y93mNHQJ1tWC5rCnzgh5P\nj08uY3b05dYFmSkwJk8EBx8ZBkdZVqwuLxFGIZQguEDf9kQZCCpQZSVaacqyIsuzFOVlHe2hIbpI\nGCLCB0qdMUjojykVvDv0DMceISRX1y/IlxXeOu7v12no5BzBC2b1ghgjbdOTZzk310/59OkTb968\npSgKFosVRVGQ3NWSSX5VzlnME/fdu8j6fsN2tUGTbACiS3x8OSpiN9std3d3fPr4iY+fPrLdbrla\nXbK8uKAuSpbzBUokD5YsfyyCSeg0MPSW/XHH+zfvKaqCi+UFRVGcrp08zylnJVerKy4vr6iqRBn9\ndPuJtVunnZ9NnbBXHmfcydY3xpjSkITA2iTzlkol+9CRfSSk4NgcWa8fyPPkjnd5eUlZltzd3SXp\n+thAmSxlB9Z1fWpS0nWy5+7ujq7rePrs6cggUeR69PkuS4zOCC7QHFp2zY7dOp3bzY79cU8zNKca\ncXGxQBvF/rDn4fND4mybjOun1xz0kWPXsm+OCK24mF+wOyabhA93nxAxMveLZE7V/zSj7OvjZ1ek\nJ3aGRhNM+GL7B4nJ4az7F8NAeBS7wGOS9/n5hZT1K0hl+vqvP/6UwOanPk8f0888HI9wd0cfHI0d\nOB4PFGXB1dUlz54942K1PEE1E0wxDAP9MNB3PUaoUYY9TsMRo5+BZ9/tsbsNZVESiRyPxxO88QVN\naXyZj787pxvR9PvmeU5ZlmRZRtu2iWfaNFg3UJQ5dV3z7OlLXr16mVgnMVnI+pDM+bUCo0HKhEV3\nvcC5OCY+k5JeguV+c8eHj6+5vX3LfrdHqohtj3QMOJfgCu9CGnbZPZ/vHnj35gPrzR6tc0KQVNUS\nIVJM0iRemegHUaRRYgxpp+NDsuusq5pSgtAKlUlUoTAjDS+rDEVtyEqDzhPuGGNyYbTWYjuHbQa6\nQ09/sPjGMRwtvg/oIJAqS6kcMnXtXZNYAiEkE/wiT51/gjiSorNpUzpLek/keE7zisnzYlq7EqUM\n1jrevn2bHNUkKRhAiPScXcfhsGe727Hb7RL23LaY32kur67ItCE3GYPJsHEg+qRkVDLRQrXSmMqM\nN7zReKhOuxSBRCuTulCTkZk04Et8ao8SSRRFBC+TTgABUihiAM+ZClEk5kRK0FYp0eSMnRVDPEGW\nUwMxWT+cm/0H/6i4PCllwxjkwRhXlUtUHP2vtUQagdACqZM9qzQCNQbjCi2wbqDrW1xwow1rROqU\nvm5yneiZXiKNBAXSKFCBzW7Hm/fvmM1m7A4HsiLj5uY6hdES+dvb1+zv/h0aLE1vysSs+NqPAzgN\nASdByDlVL8b4L8z+z2l0KREj8VjPAynPC+3kbXGuNDz/mq+x8q+52xOm1gw9u/aIJdD3A4vFguX1\nFd/88hsuL68QQpwUgX3f42xapF3fQYgnube1FiUk1jnsMHBcN2w/7E/ZatPfY4JlJv/rU2wRY9EZ\n7EkuPP3uU1xXlmXpa4UYDdojVZ3z7PkTnj15wryuUzcUIy7CMES8B61TkY4R+j49jkwFWqqIjZHN\nbsPt5/fc3b1lu7tjGDqyXNMPLa2wxKhQwhCCZLc7sl5veff2E+/f3dP3gfncUVcrYhCjiVJASo2U\nLhU15ChRTpzdlBiSLuZJgGGUIc9y8jIjqw2mUqhCJlvTKAhDUuYpKZIDo5O0naXZHjhuGtpth2s8\nwgoMGZnK0CpDm4zgoT12HPeHE+tnNpuR58k/RWlN1yVDo/3uQNv2KGWQyfz6xFBR0uD9MK6lhPEm\n7wfJbr1l7TbJD7ntTpDcdIN33qXGxTtiiKzvH6jLCh8CWilWy+VJJzCtjb7pxmsH2mOD6xNm7QZP\nZkgeJ9pQmJIyK8l1gRKa4CK2TwZDZVYmjnJIHfOk2E9y8cdmKP02krIokqWweDQyA07e7FMK0X6/\nP2kApjU8XWOTT8n5Lnu61k1mEEEnRopIYR7SpAItjUBIhc4UeZlT2IK863DRYYNLmYm5ISszTK4p\nihwkVLNqfHKBC468zKmuFjgRWW+3DNaileTy+oqiLDns9xx2ezabDbcfbv+uuvezKtJTpuBkgkNK\nzjlhx1PHON1Bp8f92Rs/Hec41mlAMQ6fThfxeJwPCKdzioT/qeOnOJqQFopWsO979l2Lbo5Eo3Ai\nJB705QXPn7/g8vISrfUpv3CwKaU5DVAs0foRZ0uLVOlxV0ASwXy+/5xSXqrytNgnGt8U0zVh7iGE\nL7r1qZM+54JPxXo2m7FYLlldXvDk6RUvXz7jYnaBFolG1TvBsY14l4pzWZDUg17gPQgZyTIwWSQK\nwbFt+Pzwibu7d7SM5XIAACAASURBVGx2d7TDGklE6oRripijhEKgsEOgbTrubjd8vt2yfkgXZ12l\nblOrfOyqPVpalPJ4OSrhkOO6CGOAa7qQD9sj/rCnWlQQR2VdDtIJhB3FSQzJvN5ZjNGURYFtB/p9\nR7tpOTzs6Xcd7ujRwaRggUxR5AUqGDbtwNY1HHeHk0quKlPAwmy2GM32IYYdbdNjB4+SBil0OqUe\nKWQRKfRY1BRyDI+V45DLWkt/bFk/PLBerxMHv+tOO6jJSN8UhvXne467PavViuvra64uU+q7EIKm\nadhut2w2mxOs13YtfTegpcEPgZjFNHDVGUVWUuYVhSkwwiR/5SGi0FRZfbo+T/DfeLPwo+VAEpGA\nIkGV1qdG6YsEb5+YU13bcTgcTru8yZZhWqcT5XW6tqfuO4QUPWYyg1ElIaS1o0QSo2ij0EaDSukx\nWWkoXUHXlOhcp6JsCupqxmw5o17UKSHJKKxNtsV9N+C8ZTmbs3x+k9hXMeBjSN+nDXXdJV3G4GjH\nXNK/5/hZFemf7KR5dPmaOM/TMQ3yvpaPS5GmsV9DH9bZZEM4hlqec6vPBxNTJ32uWPzXjolqpLQi\nz02itHUt3jtUli4gWWQslxcsl8tTIfXDSIkTyQ5Ua4UQiRaWFp8/EfuLIgkapq3x9PqnAczURRdF\ncYqxn+CN3W53uiGcbxUnNshUoLXWrFYrfvO773jx4oaLuqYSBg/c7x64fzjQtYKqXLG6mCHHuCOl\noKqnHUcKl901Bx7WH7gdC7TzR7QJZEZQVhDykkHMR49fR9MObLct+93AMECeKfK8ZDG/YlZdkmVJ\n6BKVRyuLlh4nIoxy5uAhCp8KxLh93m/29A8bnPUQBLlJf0eZa6QHHy3Rg7cOO/R4ZQmtZ2g6+m1H\nv+/wB0s8BugiIgSkTp7m+IgbLNuhYe0bwpCKBSSYQilDskx9FN7EUXU8QRlSqnQKiQ8BKadBtB6Z\nPwolNVmuEQG6RiSnOu+TP8e0I9Lp5rJYLCiLgru7Oz7f3SFi5PLigiLPWMzmhBhww4B3juZw4LDb\nJcaPHQhqhMRcCuxFpe7X6IzcFGQ6RwmNcz1uSMpXrRTiTAFoh4Fgw0gddQSfums1/p51PUtJLS51\nzhMX2/lUfI/NEa1TySqK4otG7Pw6nR47N1NDCLIsURVDSKyYqY4oo1BGQhDoXJOXOd4HyrpnsVyg\nlGJWzpiVM1bLSxazBUoqhmZgGJLfhwseNySFojI6ec/bgPUeT0SLJBsfbHLCq+qK5y+e/11172dV\npIMPJw5z6hA1QYd/oTSausRzieg5LQ7BqcBO3OjpTT1nZ0xfMykOJ7VTlmUnuOPr4wsS/VeUICkl\nRZb8nS0BlWWoIsNrQR88SslTgZ1OKUUyMh+51mk4maKHxDhZr6uaWT1DSsF8Nme1WpFnObP57NRB\nnwdtnm8Jp2Ho1Emfpu0jHj51Y4vFgpcvX1HkBc9eXXO5nJMJSR8bNruGv/74ltvbLVIUvHimuVjO\nTpRBgDwDGSNDFKwftnz49JaPt3/h7v5vbHe3+NCQ5ZE8F+jMIZUGV9K1LbtdN7IT9hyPA1LkLJc1\n8/mSy9UTinyGVgVGF8TgUKpDSYuU/jEZfCxYyeg9/f7toaXbNOSmwJeBaEEGhSFJ9qPUWCQyCLRO\nCc/r+wd8Z7HtQGwD2qrEDyZi0MhBIDyE3mHFwFZu2KmeXE4300keLsYgY+jaAec8UukkOR9tOFMR\nT+Gzk0sfMPLlpwKuCC6cTJMEkJlUjKYYuDzLqYqCIs8p8jythTOYsGkaYkwipvV6zcPne46HpDrN\nTOL2OiJGmhQhFSLBRwhjavdobyAQBJ+GqzFGpJHJBF8qAhEv0vvhrMP2KT5KConUApUlppT2BjsM\nWGFxo7JmouBNAzrEo8vlVKDP9QtTdz193yP331BUxamjJ3AySRIyndroUd7vKOuSmyfXrFYXVP8v\nd+/VJFeWXWl+R17p7iEhElmVRU5VGYfNMZu3+f8v3WPTzS7KZpfOSokEEMrFVUfNw74eyCQ51vU4\nSU9zAxAWCYRH+N13n73X+lbTsWk2dE2Hd5W4KFE0S8O0TMzLTAwLp3Eg3X1gHAbIyJ9Lpm0almmS\nP+csLl/d/ll170dVpPk3NXEVyv87jez3C/X59//aVWi0+cHnn2dY52J97jiVkh/g92EuZ5nf/2oW\n/cOZtAj0+67DVJ6678BZTnFi2j8xjiP7tXtR3pKQJI66rrHGyBbaeeIcoCD62KZlu9my2W4pOcG1\noimdHAnr6pl+d952j+PI6XT6wSzveJSj+PeXqedTSYwRrTVXV1d89tnPeHX7Cu8hMhIYeff0yO9/\n+yW//+2XHA+Bi91Lrq8+QWxmhozk6ikLWSmOx8Cfvvgjv/7tP/L117/lML5FmZGu09StAqVZYibE\nyDjDw8PMd28fePfuHcfDCaVWRu/lCy4uL+naHoomLmBtBUXkdtrMaG0kP68UUo4fDUApEIJIwlQy\nEBUqGnSy2GJxylNpj7IViYpgZkqdWU4zD9/ekZeIw0FU+OLlIregg8y481IIaWYukYM5cvIR123w\nXsZNznrmsBD3aYVdjcSY8a4iukQIy3MTIh2zLETPJzKlRNtrjZidhsOR6SSKpJIy1lhqX8kSEfUc\nBVdSJobIxXbHtt/Q9z05Jj68ey+d6unE/nBgGiWItalq+qsOtObxJEopZ2Smm6OETeSYBOSfAVXI\nKZKWdaGXMqqq0U5LaHQSIl+YF5bpY0OQlcGqdYRo5GYTU5Sb33nOvBpAxmmUbjnJta30R+fv90/S\nOZ/HnknGHWYdd1QOFVdZbSwrpyOTyRhl0EZm1MYa6qbm5uUNVglGtfEtVllSTCxzkDzG2tG0NdM0\nEuaFx8Oe4x8+MIwjKhV22y3TMHJxeYEzVr4WK3jUHP8DZhyeRxzA81Z3CSu5ai2S39crnwvMuUif\nH8/drpZO4PsLh7Ns7vtddqFgtX3+Grz3Pyjm/1rVAf8WvnT+WC5grKX1jnbTk41iPq5Lv2VE157u\ncks2YrY4MzO8F87z2Rab8g8TO9q2JSwz9VXDq229Lvo+Lv/OM+6UEqfT6QeL0fNrPs/Zz6/xrO7Y\nbrfc3Nzw4vaWjevJZWRi4u74yOd/+orf/f5zvvnmPSVXdN0FBYGnl2Jkqy+AUI5T4etv3vLb3/6W\nf/qnX/Gnr/6FJT6y2WlevNqwoyKkQsoLT8lwP2Y+fDjy9ttH3n77wOlU6DpP11oqv6GpdmhlOR4H\nvJuxtkarjHMjxkxoHTnfi87vgRCDzJjDwjIszPuZ0U2c3AlnLUpBComqc1inSDqRiWhdGJ9GjndH\nVALlFLY4XHE4tXa1etX+poyei3AvKsArrHEr4c0RU6GcZjkirwjRlDNamVWxkZ7n0fIU04eoVIS9\nzPpvKhDKYsroVTUiv9bk8y7mubmQX2tfoVbXa8lljeeamYaRHKJE1Fkrad2+wnqPrWpBfSolfOo5\nyGlgEpleDAmKknFGEImr1orcFVjBSClm4pKYx4VxkCVqXVfC/FBa4HqlrOYT9TybBp6liyEEFrs8\n+xfOO5OzQgnKcx6pKGnUqpNfNdTOiEsyQFJC8kslPY8/zwAobTXWWzrbUbmKtmqx2hEXUc1Ms3A9\n0JL8VFUVs59ISSh7x+NRqH9FJK7b3Y5u17PbbikpoYri4fThz6t7f9Zn/f/kce5kc85ybC2BeZp/\nEDN0LuTn4/x5bPDcFa+jizM8CYW4hctHmQ983BTDR1UH6qPd/AddtvqhC/LfK9hKCfB9TCfZYDtL\nTomEZl4WhnHgtExko2l3W6IC42V+fVZkKKUlVmuVIaWYKA6cE3dhDIG+77npXjKNI8vakZ1n3CAj\nF8pH9sh5Cfp9l5dzjr7vub665vXr17z+5DXXN9fUviGSOJUn3h2/5esvv+GLL77mw4d3hBjpu56u\na3BOnH4xS+ZbzoXHY+T9hwe++uorvvnmS77+5gu++upzQnrkaqnx9RVKt/glEePE49LyMFiO+8B4\nyoyDhKgaDWFRkB2qeGIoHA6jzKR1BbpgjJeZrlpQq9QrFymeKQViDM8yuvm4cNBHchbr8el44nFb\n4xuD8UpSynVBkznu97AIq0JszwVVioxDskUlhStm7cpkGN9UDbEtWOsoRaBb55Pfecfy/Ru9RElJ\np6xQMg5QGrRAmeS9pWShqiQctfI1Oiuqkomrpv37f+e/5i3nld/xjPU8n8qc/8G1BDxfM7e3L1BK\nrUD+PTFEUlwX2MPEMi+QISVpjk7H06qSEmehNAkiIV3mhWWVGnrn5aSgDLHEHyy0n01kqzrkLKc7\nf87302eMNh9vxOuJuOSy7oEqtHYiiTQaFeVml4uwZ1QKP1ziKUlkV1os9WdccYhCuHx6fJIR0RpW\nYKyhaWqWZabJia0zWOcI80JVVSgjUWNV5cUwB8zjxPv03Z9V935URfp8x8xZnIIppWdlwtn9dDaV\nnAFC/3rM8czkONdRJVvepNJzYT7L5Z67zfXzjfqo4fw+6vT7j+930N8ff2htSCmxH0aRYjnLnALZ\nGp6OTzw97RnjTLGGh4cHlpLQzrLd7ej7XrbCIRBzYRwGhpMwIypXfTzqhYCtLbvdVpgNp/xvbhxn\nAwF8jPzabrcAzycI5xyXl5f89LOf8otf/oLPfvoZu91OTi4svH3/Lb/74n/w9u177j4cKCRubi64\nuX7Dq1cvaZpqPZk4qrowh4X/+euv+HB3x+PTO0IYyCUSU2CaB47Hif1B4aqZJkPME8NkWGaH1S19\ne8Vum9Ec1+7PEqMiRKBAWBIpivROLthV9bC648o6FpMbdiTmQMpBeBIRwhQ5lhPTNPP09IRrNMaD\ncWCsQq0hrVYpKlNL6GhS5JAIkWd8tc0WXRzeeJraU5vC7Y1GNzMu62c1wtkRdy6S5wbhXLDPx/gf\n6vj/lcZfy++NNfR9R6lEvhbWG9D3jVhuDUw+L4+HYXh26p1vypWvnpdyS1iepW77pydKydze3KC0\n5sOHD8/jsZQSdV2vbOYZkNDbnLOwZFby4lm2Klr/+Xkh/Ry6oVeeeyqEFGX3lD+OKM+y2e9jGqRo\nygnaWku08RnzIGEbKwaiuPWEKEHK5+9hLpmY44rF/p6fYSX4oSSCdzgNTEws9UKKmf3DE/fvH5hH\nSdvZbDZ4Vwn/JVRcVp5+66QpCKJi0Simaebh8REFaxLUn//4URXps8i8IFvTZVmYw8wSFwqIPrWS\nO6cZ5M6sisJiiESccWSVSUo6kkIhKVFPLCXwNB2FG7suC713ZFvAa6oskJa5BGYiC5Epi25VI8dS\njCYDSWeyEQmOIqOVxajEOEemhwPH44GoYH88obzlsEwcDwcWMrYRxu8pzGStMNZJMGmRzjTHwDhO\nDIMAkpZ6IYTIsgSmaSY3mUrXjMwQ11GGTmgjzq8UP6pj6rqmqitSiaQSebi/Z5wmqloCVd98+oaf\nffYzri4u8doxl5m7u3v+8Idf8+s//hNPD0dytHTdFZ988opPXv+Uq91LnPXEmIkRamDUhi/+9DVP\nhyeqJrPZbbm5ueL9XUvIENPIOBvmkNbUlkDKO6zp6XY7mnpL5Xveu3eEuKBURU6GEldJpK5wpsFa\nv94UzXOR1kgmZCmZQpbuKMjFv+23dFc1uEJSkjQeJ9nYZ5NQJqNMxlhAwdXFBZfXO3QqhNMsKqAp\nkJaZlB2Naamdo/UVG9tDYzm93qDdkcOHR/b7/XOR3vT9ysE25LQwTfMzebDve84Zm5K6Ikf5czRV\nKQjzAumyrXWkVJ6lbec0oPNehXVsUa2Zgdt+Q8oCqnpeFltDVQnHulBY2g7vHKoU2s2Gm9sXpFI4\nnQZQmnkJK9xrYhhnpnFBKTEdlQyHw4HDfr9yRGT8IjK6gWkYiMvyzLw2SkILCglKpCAjplKkmdBK\n7PhKn01kQjYMi7zGyotTRilxIseYmZdlJe4JW0SCaSHkhZhFGZXWIq3QJJPQOaHQZGTkkSk8PD4S\nY2LX7whz4P7uju++fUeYw2qFr2m7Fu8EJ5urjN+2bDYbrNacjke++fprfv/lHyl/SFzsdry6fcn1\n7kIi3/6Mx4+qSHtTY7JEqscYyUGRZihBZmVGW2zyuOxxyWGjxRmPSx4bJGTUFIPLdu1UgCLZfwaF\nqwrFiVxHaU21Mj/aWvgVBQgEJjomPbLPB0lmKfJvkJB542IhJFyWC8gXT6s6Qj7yuJw4hpGkIAwF\nnRxDXEgloq1BqQI5UZKCDMNxz95qwtSgi2zxT6cD03RimgaW0BLTQikJoxXKF2I9M9sTAwdSSWgl\nN7BsMpnEEpZnklrlNJVp2TYZcymuwdsXt3z26Wf85M1PeHH9AoNjjjNv393z6//5G/7w9Rc8PB1Z\nlkzja/rukuurW17cvOBie0WKhpSkM38Mmm/ffsW3b//IMJ7YXlSkvFBVjovLHZhrjJvp21Vv6xWQ\nGHNDSpq2q+naGucN1imGcVi7vvV7pbKApKwml1UN41YjioaiM5RMyYmcI/MyEcJMSlGWOUoz55k5\nyowxpomiPFknis4ondFrp2tijaeDlAhzJk2FeAroACkXbKXIxqF0jfMdqnJou0fpQiERo7gOYzI0\njUfbjqat8JUlZjlVKF3QBoljskrGN1qji0Dwn5VNVoGRhdccRUe/xMS4LMLZjhFrHWaVb2alCDmj\nU6LdSLjD035PeBLWhMoJtMZWlYQPNA22rnB1TeUrai/uRu8MzoBRmaUsKBaMjliXcA4pfiVQ1RUx\ndVhfoZ08jTLYakF5QRwECoFEXo1N45BYYiEGcajGKOMGYyJaW5xP5JJQWpajrtKkWFAqEuNETLOc\nNsNCyVFUXKZC6wKsJ23bUKxm0QlVEnkNA0kktJGEHJnxQ0mRcToyDTNxmpnHhaeHPafjkRwLTntO\nhxGvZRlsVMW2sriuZ9tvoWTSYWS8P/D1b//Ew/09m77n/vUn/MVPP4PxP6AtvCu31PO1bJVDIMdA\nk1pUKRg0Llmq5LFHS7+/QC0WGw1uFsqVd3YNWq2EuWsM2hhygZuq5T+9fMFl06HrmtK2KGclKScs\nhHlmXGbmFClKjkvffPcdH+7vJHV6EHnNMI8swVPosZWnNg2Nqtmw4Vv/lvdX32GvN2yrBue9sAum\nCToxMXddy2Xvubm9paoqvvzqK/741Z9o25bLS2E5zKeBNB1QeaKkEaUW2t7R91f0bxzHT97yLn3F\n3XSHzgZ/9YauvSLvNekhcRhOHO5ONHZi2yZ0ttxe/Yz/669+wV/+5c95/eaG3ZWn33ZUNIQM3379\nyK/+7gv+9m//Ge0Lt2/+T9yFQGnatiOHlpw0m66mMjXTMvHu/ht+9Q//xL/8y//g2+/eMgxH/vDF\nwDDsWZYBb2p+9ulfs7vo2e16qspjtCammYl3DNMjSzyhFNSN4vWnG4y+WGOWHKXMLGEBfSKVmuPx\nPdvdln7rmBfLMGVMSFirGEtgmJ54fHxgjgu1rai3OxpbUQZFHBMuQNN01L6iaQTuk5PYoafThNlb\nptBRQiLOnjwH8pJXt6Njzg2n1FBiC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ZIiqkyoUkEW1YzCUpKRUZITUNi8zKS8EMLEtEzk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\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ZbNsVbsopY+uCsHheLIO45V7Z1eLhvefqar9SBFc6ad8zTj2nywIu/janvc5VXgwaFcIQ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\nHPA6UoosbM45xrsTx6MEuP726wc+P12FOqbgcnllXWdyDmhTxW/CWbp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Mg7HUdnYWMeNv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\nYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f202c1a4630>"
+       "<matplotlib.figure.Figure at 0x7f5425a08c18>"
       ]
      },
      "metadata": {},
@@ -897,9 +926,9 @@
     },
     {
      "data": {
-      "image/png": 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YX/d4upHyzOCplGhOzuvVS/1YE/4YtTP9hLT4CX8X+ejsL/l9NiaPMwBoXUXKeGEJb5M/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\nCv/+knefm5FL99gM4FkAfer7uP+N81P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1Lv7gTTeWOfordMjsW0+7MevYzW+YcO5nzvm2G6Opbi38+mEZkj4H8OebaMCX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\niIikgCZ8ERGRFNCELyIikgL/HwqBraJwOc8gAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f202c116e10>"
+       "<matplotlib.figure.Figure at 0x7f54254f6cf8>"
       ]
      },
      "metadata": {},
@@ -912,7 +941,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -927,9 +956,9 @@
     },
     {
      "data": {
-      "image/png": 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PdNGvVcLgJ65DP/uqf7H4XgG1cGGSkXjv5xuswlqDNmoWdeZ23BAIwWPtjrIq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6zAIuZAZjZDtYrMCC7tnJsy73znJ7dE59z03Ofz+XRYOJcYFuKuqI1g3D/+8CMv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X2+u0oMfB1fYaNWn+9H/9O58/fKbtWlbrFdurLVVdyYIwM2yvthRlgTaaj58/UjVCE3x9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tv8XXp3uGFLbsYAqe6zQuvuk/PH6hQFq0L2EiIYTl5mqw1qCNWgo4S4ttjMQY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c9i5NOFnDqARBOq6ormeKY7N1Pxgcsh8ZfUo/T78/lcQni5MD3GcUQNanqPpsOBAE6YLC6a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gpyoqyrykKirqIqgOtWK9WnN9dU2WZ5xOJ56/PPOyl0Sd6+11Wsbj4Gp7jZo0f/x//42P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\nD5dLRew4jrx9+zbBfsZIuvo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xtOlzOe73kiTuJcQiT5llUTB/mDSdW7lcLvzwl78wTI7/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3p5nwz0yoFBEH6gmPdSBemuE71ZrTW+54nqlLuAhdiv8JXUVgdKXAfdvGYxm/PKw8fO9aIhOxzZ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2086810438>"
+       "<matplotlib.figure.Figure at 0x7f5425968be0>"
       ]
      },
      "metadata": {},
@@ -944,9 +973,9 @@
     },
     {
      "data": {
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2qzxuREwHXgVOL6Xc3fPYUuBPSinX9fzcCSwHfr2U8s02y5gD3P/zO/+FOSee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\n",
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VomwqFqWmndCeLaVX8t3wAOKgo/JFFY9VcVKQ65tEFzm5zI26o2VMPzy/TBkxFBE4ALWv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\nrkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2086da59e8>"
+       "<matplotlib.figure.Figure at 0x7f5425942240>"
       ]
      },
      "metadata": {},
@@ -973,7 +1002,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -991,7 +1020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
@@ -1009,7 +1038,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false
    },
@@ -1028,7 +1057,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": true
    },
@@ -1047,7 +1076,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1059,7 +1088,7 @@
        "(4170, 2048)"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1077,7 +1106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": true
    },
@@ -1095,7 +1124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1107,7 +1136,7 @@
        "(4170, 2)"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1125,7 +1154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -1160,7 +1189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1168,9 +1197,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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e50/om34aGgVYfkeR2nabnkgCD49FqtQjGvaWQRZG8gxNNzH0IDWnyVzMIaJC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\n0t9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fx8OngYqopGlPhQQihlI1ERLCnox2lAbIhI+b87D29Wg/2KTtbyXpLGHmK6jXrxLb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\niWYBjwt99px2pP9eNVrrnFLqOCC7AK6OSUAR9POLRyH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Dpbsffxw2bgxbW8rlsN7iE59Y3UiLwUHYuhWeeCLcj2mGYeLcuTD8rFv3hr8+IcRblwQI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\neoihfadwEhEaPRnMjsO22x8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ayh04xEizyD6+RVLZxVN0EDb7Nv6MxeJ97K5O47oZnG2B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SAS6hE6AQtMUgwpCEMoHQPQrqJhl/mw1tAIUgUjZmpk5eu47adhjkFQh0GsEEuuMzdvo8iVqL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\n6dDmKwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f203c162588>"
+       "<matplotlib.figure.Figure at 0x7f53fc055b70>"
       ]
      },
      "metadata": {},
@@ -1190,7 +1219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
@@ -1208,7 +1237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -1227,7 +1256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -1245,7 +1274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false
    },
@@ -1263,7 +1292,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1275,7 +1304,7 @@
        "(4170, 2)"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1295,7 +1324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1303,9 +1332,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ef1xoAfEg8DPgCLAQ+Afgl0KIq6WU0/lz12je8NSvgA8/Avn/GIDveTjDR1hw5DleGtlE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jB42rfurEZzs+z2f/lLua5CQcbmdLbGAxGRiK+JyWTkGj7xibmzUooiu/If/xje+lbcsTEsx8Bx\nVRRLQTfLqLrqL9DBoG/j7rFzNTWywHZ1CVPy0Y/K53LokHym7e3CHL2S8J6VhgZ5FnI5nzWYXlrt\nLerTU1KeIDOdlvPesUPA0JIlcoyODmGjPKHlhRcKg7VihfwfJJV07bUy1jwBpXdsXRex6XwL8Ndl\nzAOIM4hyBp75Kmz5BhQnZVENJqByivYOTgnUKJz3Xvk+eVD0Dl5qg5PJBLzn2RZDHqZnBTRQ3OpL\nvOpAU86rkoNQnWgqdv4IWtaKjmIukRkUBiLR5adEFFWYk6lDkH4xSV1Tk0wmmzb5DpbTy828bpeV\nCo4CaBqhVB5cqNSEOXTteQzdcRWRXugYrqKsbFbyqDt2yCS/cKEc54YbRNz2r/8qC5umSXXIs8+e\nmCbxzKG6u2V3feiQLAxeq+U1a4SqPpMwTZk0TVOO77rwkY9Iyaqu+zXyHkswU1pC08RfYWhIyitv\nvVWskLdunV14ed11AlJ+/nO/E6lnR+y5RnoVKo4jue6+PinPu+MO3wUxlZLXey3P4/Fj3Uhra2Xx\njUaPbV1+/PmvXu03C/t9CVWVtMtPfiLXMNvu3WMqPEbhve+VBmB1ZyAiuuAC7A9/nIGvbqYu+QKq\nY1KiljIrqHcHiNpD8jpPoOj1HgH5rBYulHNIJuV8w2EBQsmkfDaNjb4DJPjMwVzTXY2NknqJRMSy\n3UsBeoyLFx5oOJ49dBwZ75GI35m3WBRQ/v73y/O0b5+ANV2HjRsFvHqVFZomrEc+L2ZmHksZDsu4\n/PznT/eOz8fvSfxeAAhFUT4OfAZoBV4CPum67vPn9qxmDseGh/4ctv2baBO8ON6md7aoaYPCmFRT\n7PklJPeCZXIsIJgtVNCDYE2fExUBFUxnjF3RXbiOMBPZQUlhJPfB5D5Rw88lXFuOcbyeQtHk546r\n+rsVz553OnjwJqLq4m4HDApNtRj5ElM9rYxctIxSYxw7k+ZIPkPHQLUVsWWJWvzhh2WyW7FCaOIF\nC0T0eNttMmEZhjjkbdo08wV4aRVvt75jh2/169l5n27s3SsmW4cO+S2eUylZ+D0tQLHoewx4+e3p\n+gZV9S1/bVt2Z5/+tFD/+/fDd78rqQfPsTIWk9996UtyPzo6BGwMDvptqOFE+3Fv93j4sDiOnn++\n7EJHR8UkLB73u5H29sri4GlX0unXrxXx8uWyOJ1Me6Mo8hk0Nsoi+J73HJOfdywB+OkB0QCV0lC/\nFNouhGBMKqeOhq5zaO2n2Lo8yepD/0hL8nHyVgtFJ4HpxOhiHJ3qolkoHFu9Eg6L5sETBXd1CYjp\n6pLPfXJSfu+xKF7aavrnfLJobZU04Pi4CDlzOb/SqZrKcRUF29UBFZ0ZvCZKJQGTqirnb5oCvicm\nZMw0Nsq51NZKGnL1ar9MtliU86+vF+3Fjh1SneKlitaunfeBeB3HOQcQiqK8A/gS8GFgM/AnwIOK\noixzXXfipH98DmJsl9D67snYgtmimoboewx2/0JKNa05VmkpBhghiDRVdRTDgCOABoej6QyvakNR\n5b0UFezyiWnHuURNB9R2wlQvNCz3j5E5DDULoPaqhfB4i0xMnohq1gtQKNXXMLRhJQ37R1Adl0pt\nDGprMSyHgmpJzvqii+R4gYAsYKWSiNWKRdmphEKy8F10kZzMs8+e/KI8Y5t16yR3H49LWZ6XNjid\nmJqCb35Tdu2LFslEvmeP0PievsKb3D0lv+vKgrBmjYCPkRFZKLxeGBs2yM5XUYTN6O4WpmTbNt+E\na+1auV4vPXDZZVJj39AgbITXW8Ozw/Zi+n3JZEQJrygCbsbGxFFS03yqfGxMzj2bFdA1OSnAZdEi\n2VFeeunchH2mKffdK6F9rcOj/I/3FJketi33/847pURx2nWNboff/X+iJ0oPHKtL0sLQfTVc+D5Y\n+kYIVqsV+38XRF/URnbd/yBx/xjRgd0EnEkijOOgY2Oh4ArOn77Tn5wUkWt7u7hTrlsn4/UtbxHX\nR6+pGggI8DraegLEk439UEjGXkeHmJgNDx9bxuy6lNQEOaeTfbyJKZbQzvMs41dE1aS/KfC0Obru\nW25PTcmz+fWv+1VNU1OSOvrwhyGVwn5qMxNjdZiJDmpuv4j4m9ehrF17opvtfLxu45wDCAQw3O26\n7vcAFEX578CtwAeAfzqXJzZT9P8WzFkY5pOGIot5rE129oPPHVdtMUuoVQ+mdR+SdIdmyDF2/xyy\no/jMRXVO0ILCUtgV0KLy82iTOF7GWqHhNDaUmiHGPy98E8Z2gBGRcw7Vwaq3gt5aB+94B/Y938bJ\nVtBtf/E6YZmJxVA0DVwo1EaIDSeJ5CukeuKU62upn1T9dEBtreyKR0dlpz8+LoxDd7c0bFJV2SH/\n7Gd+e+HZIpeThfZjHxO/g1cS27bJ4tTcLJNlPO5TvNN3lV5ppecNEQzK5H3ZZZKu2LFDdm8dHVJC\n6rlDeqHrUk548cWzn4uqiisgiGhy796T70i9XhnBoCzsY2NCS3tlsY2NwjYUCrIgjIyISNLLif/o\nR5Km+fM/n107UigIk/LTnwoICQRkUfze947tTPpqRyrlt+aezb1RUaSE8aMfJTOqM/KipPnUAOz4\nIQz+DlJHOCGtaBfh0CZJV6YPw2V/LJ4u5QwYYSjVL2Zg5X+j9tA3aEdI1AwLSHAIFQuX6rPhleA6\njoC7q64S/UUkIj+78kpJEXgumrYti/OTT/rajlBImIq+Pt9xcvr1hcMCwkdH/RLoaaXOphMg6XQz\nyKVMsRgnFGGv9RZSLGFj9OsE8qP+sbyum15fDU+c6gGKiQmfFXn0UfINK3gu8ZckiwtwihaBJ/N0\nb+1j7ecXoZ9jmcx8nL04pwBCURQDWA/8g/cz13VdRVE2Aach93vtwraYW7phemiyGKu6TDRTh6Ay\nB/AA4JoQrIMLPwRb74bBzQISuq+GgadkEju6CVFlMtODwmzYFWEjKgUwqi6AwfhJ3+6EaFsHG/8c\nBp4WAFPTDl0bpWQUINV1FU+nutGKlxJiiFr6WcpviDJxLIgwDMK2SjRVINeaIJwpoFUs3EyK1p0Z\nuvP1MgmOjIiyfXBQdsyZjCxgmYzkb5uaZCf8oQ9JBciphIqhkJSs3X776V24F0NDwoBs3SoU7K5d\nPiiIx+X4XtMlx/H/9WjiBQskz3vkiHy/c6cILgsFAUVPPw033ijMxunm3xsaxJfgbW+T3PI//qOA\nAo9q8kCNB3JAJvv+/mN3rqYpi4ymiShwxw5fEOu1k56akvu/YoWI3o6PVEqu44UXjj3uww+LpfS2\nba+d0r6x0fe6eH7mTKhjBChffANDj+ns+omUKKOISVvmMJhlZtUkuRYUk1JCPbZdnpHGFdD7CGgh\nGLE3UqvtIe70McUSFmgvoNoOLioKVbCZSPgL8AUXyH2urRVW6Je/FODsugK8rrhCGKhLLpFxuH07\n/Od/yngpFASsTV/APU3Mhg1yDx591E+hKQopt5NxVjLEega5lKBWJKEOoIVMIoUJxtTzGQpezkLz\nPrlgzw7eG1OersQ05ZwnJ/029LqOU7bIDCtYhSS1yxrQdYviUIn9vygRvshlxcZJec7jcQE4Z90F\nbz5eqzjXDEQjoAGjx/18FFj+2p/OqWPJG+Dhz8zhhdVUghGuej1kpKmQVZzGPh5fpjnTYTQI1cMj\nn4XsYcgMiY4hXCd52mBcdBVGRCZB1xWmIdoI8S7xbajvgY5LpQPimUT9kpmbezk2PPxZ2P94N7r7\nbjp5hCEupp+ruISv0aa8jOItVKUSmmHQvuMI2XgALVekefMu2p94mZilEWpqk8myoUEW2b4+mRR1\n3d81jYxIU6gf/lAmRcM4sRWyF5omO/zly2V3dybx29/Cd74jpaNjYycK8ryWzYYhaZHxcfmZ5yrY\n1iZ+/zU1IjT9yU/843givmJRejEMDwvQWbpUFpFcTnaX69ef3ObXy+V/4ANCf998s7wHHAsivJiJ\n8vZapk9OSulmLufn2r2UjFfNsmkTvOlN8prHHxdAVVMjwGU6eJgeQ0Pw938vXhWvRSxYIOzNxITs\n6Kf1THFQMLU4E+pqHv1QlD5TGLXmNcIM5kahkDyunHqGKKdF+JwZFACx4DJJbQ5vAasUoqhcyBJ+\nRZhJIrZ8HjZBVEw0Q/XN0Dz7a1UV/cvXvib32TD8MtR77xXQfNttfi+L3/xG0neeo6bXETORkJRT\nTY0AE9OESgU3X8BUYyTVHrbwR+RoJU0XRerRHZOSUke7uwdNd8B0yNitfn8bzyo9GvW9Hjo7RVvj\nuY96z2mpRJ5WLEJ0lh5l1GkHJUgkYVNJTzLwjZ0s/dX/QctMynX39Eh1VU/Pqzki5uNVinMNIM44\n/uRP/oTa43oz3HXXXdw10+7oLEbjStBjYJ2i0ZyiCRuAArF2yFHNlzrS78J1OSV4AFmkkwdEAKmF\nQA/IsXMj4iux+GZhHArjkiIpJqHnerj8Myf20TjbMblf8sSOBRUlhqVGaXZeIk0XL/AxbnT/jLBS\nNRuqthsOhMM0DBWxcYkVLLSWNpRAdfKMx2Vn75UYerspzy7bMOCpp3xBmfd1fOi6LKoXXCATqVcD\nfzrhCQ83bz62j8L08N7fa4p0+eXy2hdflIn89tv9/LXX2tkTTk4Px5HF4otf9MtMPT+BNWvEFOr4\nNMdMccEF8OUvCxXuNYCaVgUza1QquI6D7WiMFldQdC6gwdlN3BoEw0XVFRSPwchmpbrj3/9dwEM2\n66eajovpw9v86a9Q/98vo0e0E1531kNRpKoiHBbmp68P23SxlQBJdQlHcucRLKUZpQcbyI/AoREI\nJEQvZM/BisOIyvNtRORZPvwsGEqRhXV7qUwUyBg15NUu4u4R8k4HNWY/DhqqYvmAzTRlfJimsAWP\nPea3VPecG72mZ6mU6F3a2uQz9Z6R6eH5gHitvF94AWIxJqca2evcxpi9hqTbg0mIhTyCRQiTCEEl\nT5pOEpEckcwhsc8vJwWct7TI5xsIyLkahjBNliUgcnzcd5isajJsJYhDAMNKyThsaIBKhYCVoby3\ngB3Jo+3bJaD5oYeEcfnrv5ZeNMc7n87HK4of/vCH/PCHPzzmZ+njx80riHMNICaQhEDLcT9vAUZO\n9odf+cpXWLdujuUEZzEGnhQgcFIAocvE4qUSChMifiyMy64lWMucwAMAdlUoSbWywgUjIBNdKQ37\nfyXv4brVhlwKbP2WAIybvgSh00xZnE5M9UI5K6BIMxRGwhvQ83mijJBlAcOsp4fHTqwzDwbRLAsK\nJVlUQyGhQgcGZBccjcrkOL0JkOfY54EHw/BFctPr1puaZPFuaJDXnX/+meXfX35ZFsWpKfnec9qc\nLTwHw6VL5RzS6WMtpbPZk7cgLxSEdYnFJOXhLfovvSS7zXe/e27n/ba3iR7iO9/x/QZO0bXU1TTK\nZgQbnaKV4GXeiYLNMn7NUvN+bEtFQ0ELhYTV+cUv5Jw8IegMVuXHD+/8lM7W/11hwydDROpeA8o6\nFoM/+iOs5g5y/+seMiM6E+lWnFyZoJPkGT5Djo5j/qSSAnUu+XkFFF1YwNbz4cjvYO+/jqAN9lNx\nstSrvSzTdmJrcSw1gR3rxJpIo1dSshCrqm8wVlcn2pjrrxd9yaFDMlY8FsI0BQgFqw//009LGiOZ\nnPncbFu8UtraYN06pi56O09t0UiqEWqtgxRowCTCMBdTSx9ppRs7WINjBSgGWinHaoh2BGhrVaAv\nJmBk5Uo5XiYjz+lnPysNsDo6fGDsdTPVdYJaGb2QYcKuOsNOTkIkQqHSSFPdEMbzj8PUpM9uHD4s\n7e7r64VBm4+zFjNtqrdu3cr69WfHX/6cAgjXdU1FUbYA1wO/BFAURal+/8/n8txmCtuEffdJGuKk\nUV3MA9GqjbUi/QDSh4XidGyZgNzTNJizKwJMyhnxd8CFStb/vVkFNaombpSRRrj+730DqFS/AI/4\ngrl7QZwsEguRMlJHWBHNsdAUG8sNYRGkSJ2/uHvuf14dOcjOqlj0HRlTKZlQPfyH6A4AACAASURB\nVOX+dLo9nZa/81wPp1ccaJq/kIXD8v+xMZmM3vWuM8uxlsu+4t1rwHSyKJWE6fjKV2RC/MpXZJfY\n2CjHSqVOvrvyWAxPT+FVRzQ2wnPPidhyLhUNwSB85jOi6v+P/xBgMzbmp1WObyYGWJZBhQhFtZm4\nMsRCfssAV7CHt1DHIRrd3dhoOPWtGNu3yyJW/SwcVcdxNUBHwUbBPUFAaxk6z3zmNra++1met1yW\nUc9GFtPC2Ue3rguDz8NL/1fs3guTNxLOr2RJ4Wc0mS9SdoM8yx8zwnpmkPpK6kLFr2qaKRQxjssM\nwciL8NK3ypi9o8T0ERqVvdQVdhN2JtDdAv36DUw2xmnr7KTZ3UlYS8m4MgzRNXzkIwIgIhHR/UxN\n+Z+TJ3z1XCNDIQEPDzxw8ptgWcK8PPwwA8EPMqF0Uw6UidSaBJMFXFcnoy4i6OZoMPqYshZSsSNk\nszFaVoZZ+7crqb14nYyfxx7zn7ulS6UaZ+lSATy9vcJ6FYu+T0U4TKg8iaK2MMBVaDkLwy2QzybQ\nEmWW6L9FSU8JyPf0NSDX/aMfidfLPAvxuolzzUAAfBn4bhVIeGWcEeC75/KkZopSCib3VE2fTqJf\nMMJiUW1bsrAGa2RiMsJSQZE+dPrgASRHa5WqpZ8nYTDKKQjUiL32yz+oGkLtF0fJ4ricU/c1cNX/\nFJvrM42mlVC3CCZ2gVVyabNexnZhhI0omPRzJe32Furol0ktHj+ayjhmEUulfC+D0dGZTXK8nbRn\n+ws+EPH8F1pa4KabZGJbvBg+97kzK9cE37yqmkM+ZViWTLb33itGRn/8x6In2L1bGImbbhJB32wm\nUSA7tclJoYbf8hbfp2G2NuSzRTwueeUPflAqIL78ZdkJeozEcWFaATJ0YifaCKUHMChTwxjjrGCI\n9cQYxlUNyuUumrc8dfR+W66BY6uomCiASRgNCw0TV1WoREOU6mNs+dDNbPuTK3CDRSou7HCHGFRS\n3Moaemia+3XNIfb9Gh75CxFCKhqYRYUMnYypn6K5dYLJAZ2SfZJB7yDPdnWIefbzdkV+pwYEoLu2\nNLt76P+BGj1Lk7qHBdbTtJpbKBEna7UQdSu0uC9woOlv0N79cbruyqIc2CP3z2sf7sXYmD/eCgW/\nmsfTN4yO+tVHcxmPrgvDwzT8x9+w3jiPfcp1FLRFaLEyTj6A7RoU9VaaaofAHKeupsBFfxqn4509\nhJoCQEjAzVvfKulFVRU9US4nz9fGjfLcbtokIGLv3qNpRyUYpKk5z7KRhxgwL8VUIjSWX2ZJ7gna\nnR1+WhL8SiWPiSiXzyzlOB/nJM45gHBd9yeKojQCf4ukLl4EbnZd9yRNBM5NBKLCHrg2R0WSx/tB\nhBth+e3y2r7HqznViii2XVssqM0Sp97leKFUvxx/InNOsRkGyI+LHuLXH5kGOBQpC1WQ/hv9j8Ib\nvw6dl53WbfBPTYFr/w7+64/ASRcoOLWMsZwAORbxNFFG2c2bWcIDNDv7/CqFmdIB00vCThbTWwZP\nr4M3DCl989oXv/OdZw4eQGrVE4lT0v/HRCYji3UqJcZEn/ykzybs2ydswtDQqY/T3y+Cw/e8Rybl\nW26Ra0mnJaVRKAh9vHLlzGZYg4NiNPXQQ9j7+sgPg1tsIGZnABVVcX1xayRCWltNRllChBTgUFZr\nsYhQcWoYVDeiGAHilT6SQytoCDyNFo1CNovjKgIWcFFwUHEZYTXK4jzlzjBj53Wz861XMLRxRdWQ\nBPnSIEORzfTRQR3BszQNZYfgsf8FqUNS8eSYvhjSdVSS2WZKGqesolJUQBGWTgtJLxvNAEVxaA4f\nJEySnNlA2u0hdVAlVJ8jYe6jvvQyWWpJs4gKUUwCdAR30uP8hp2PrqFpRQ2LrjtJaa5pCsAsVXOS\n5jQl5xNPCDu3ZIkAxLn0TLFtFNcmUdrNGneU/c7bmAr0ECpnyFqtlN0YabuD+lU6F/xtD+3XJ048\nRmOjfA0MwN13i+5lfFzOb/VqGZttbZIy1DSpBOrtxdixg9XB/2J54zOYhAnkBlFsEzfriJ7Ge84r\nFUmLlMsCqGZzPp2P38s45wACwHXdrwNfP9fncaowItC0Gg4+yFEGQA1Mc2zUpJyrNCX6hEoWUGXR\nD9dLS+9CUrQR5hx7JilVNs/1rAbm6F7rlBDraPxzxQWnKGY4WkDEmU/+Hdz6DTGMOpNY8SZIfg62\n/vUkgWKOOnrZyBep5yAuCiZRKsSx0dHyeT+dMZ1l8MBAOHxqAOHVxB8fgYDfVfHOO1+558PkpBwr\nHPa7Tp4qSiURru3ZI0LKN79Z3PZUVVITq1YJI2GeQuIPcm9+8APxr3jjGyUd8q1v+b4XhiFlfR/6\n0LFVGk88IdUc/f1Y6SLj5lKmnBW0W7/DIiwJBlUnGDJRcCEQIBSooFgKYXOUspogbzZSpJaSUk+T\nvp9a9QhZpZVB83yWuO3U10/i5gq4qDioVfbB4AiX0he+huGlnWRvC5G7QaW4sMbPFChIMxhcHFwm\nyJMkTxtnR+27517pZosi6UbHOhbgl9Py9qd6hFxHUozBhAAQRYWokWR1/tu0WS+huwUqbpQh50K2\n2u9nshBmrT1EkBRpFmARQMMkQA5bC5OwetHVEn2Ph1l03SxvWlPjl8/OFJomu/+DB4UdSyZPPY4U\nhag7xqB6GUEtTaO7i7GWG6jU6AQqJo0Lwqx6Zx0972kjXH+SNF82C1//Os6uvZTGSqgDfaiVPNrL\nu1FffAnl2mvE2XX7dgHPu3bJs5hIoGkVXLeIpTmku5pRLYv4kSRGJoMSDgt4UBR5fu+8c96V8nUW\nvxcA4vUUa94OL34HilNV4FBlI1AlbXHpp0QjUUzKonzot5Ly0KrmTnZF2AmrAq7rVms5TxKeQVQI\nQgmItggwyQwJSDiTsEtCzaqGCCEP/s5kUadJlACB0xwSigpr7oLNX6xHKfaxjntoZB95mnDRcdDR\nKFMhRjhk+r4Nuu472E0XQc75jav3TdPkWM3N4ij41rf6lQ+vJNJp36xnrgDCi1xOSuwyGVncr7pK\nSgsvukjU9V7nxlOFZUlaJpHw0xArV/qLyZNPynHf/nZ5/eCgiNF6e6GujmIqRNJaRFwfwVAqoOko\nro3jKlTquwjGFejtJV7aRVlTmXCXMhRYx5TZQp5WWtwXWW7/goLSRl/4FgJWmpTTRbwwjqtGSNNG\nmEkC5NjG+9jR8HaKjTUUijWY9wexJ4vwiX6otY/u6tFd0c0Ac1cSzy3G98h7eP4nwDFMnzPdsXW2\nqBq+adVMme2AormsKP6AjsrT5MKLqFCDWsrQaT+BqQTYZb+dSWcR7TyDQQEFMCgQUVJopSyWo2PU\nGNI3Z4bKWkDSX9P7XRwfhiH6lnRaxlRXl98pc7YIhahlgLLRSE7vpC63B3OqiFLbQPcNQS75eIzW\nC05xPwC2bcPafYCx4RYi+57FVmLYeguh/Bj6FEQ2bxbxZyolz7dnIZ/JYMdjjHfWsfuOGxhf1Ymr\nKiiuwiXffIDu7YNoping6Q//UHQ+8/G6inkAcZrRvFa8IAaekh2NVZbdfHyB+OR3XyE+DCBCx1+O\nwuGn/DLLSLOLuXYK5Q2DuL9shAeboeLlKaozSxWEayHx3W+/GBZeIwZOzWth73/CE38veoxZY9rh\nTpinXQERgRqHcqDC1uEJ+hgnjMFimlhCc3VfeepwLBh9Ecp2jCkWM8KFGBSJkJQdLi4FGmRC/+Qn\nRb1/+LBMhpOTvhjSc+XTNJlhTyVa9BwSvVJPx5FJ9WyABxD2ob7+zK2YBwaE4n3kEWFDFMVPSXz5\nyyfXQkyP7dtlR3f4sOTNPYFZLCaU9lNPwR134KgGhfu3oB1MEm5uxtLC5CxA03BcFUfRsYNxdDON\n6rhYWphgRvwJtFVLSVxwGZPb23B2BAjqJSpOibg6xBgXkAysIVhnECo7HMlspKP8PKolLFCROsZY\nxUtdf0hxRRC1voDTrGErGryQgKeycGs1GzlNW6Ci0ESMBs5eR9RwvYBiXI6m/Ly+LSDahZO2j1BA\nD0t1RXyB9MBwXUiEhmnObiPtdFIx40Ke2bWoajsd7vNMqitJOd2Ms4oYo+RoJcIEQS2L7hSZiKyk\nkNLpumIW8OA48O1vn5x985g3yxIW4pprfDBanuZV70XVx0MBmitbqNP6KCRaeWPrP1C/Uif2pqtR\nW9YBbae+sZOT5EfAHE6j6xWoqUN1wckGKR0pYNQGMPY/Iw3holF5Zh56CBObQxd18/x/fyO5tjri\nh8epRMMcuWo1RzauZN2mfVydb0e7/ArRV8wbSr3uYh5AnGboITjv3aIrMAvCJigaOBVYdL0PHkBy\nqJd+QlIaoYR8Ja8c4PCGQ7gBC5Zm4UgY+iKQ1iXnoInXQ80C8Zy45OOw5KZjz2HtO6G2G57537Dv\nlyeeY91SUYlXclWt5wx6CxcXO2Lj1JgEWx1qCFGgwssMoqGyeA7iNteFHT+Cvf8lk66bKjPMelIs\nZBn3kaCfEnWEmMIIWDJJbNwou+Q9e46dMD2zopoa+XkweOpF1gMPnpHN2fTYb2iQ7pfbts1Nt3B8\nFIuS/vCMo4JBYUn+8i/lPnz6034uebbQNJmMi0W51uP1DsEgVqbMS//H5ODTBtaWHoyxvyWYzGOE\nHdqsTYSdSSZZSEhNElOmcIwwlh1Er+ShkIWODpwbb8FwFVbr97JqUYZKssLDuc8zxRpsY4KwmUSJ\nRiiuuJJyf5JU/aMwfphyKECOFnan30aqcQExrZ+yG6YSiYDiQNCGbRGU2zgG0CpALSEuZdFpM14n\niwWXig11JSIsoGsjYEIVYBCKy7fF8Wpp9HG3/ihrgbSsdx3xcGlpyhLKFMlaLdLltvp3phsj7E4S\n14dY6vySnNNEQhmgnS04GCgujBkXsI9bCCWg58ZZTvyJJ8QHBGbvtBkK+aZYpinuqNmsGDCpqgDM\n6Xodzyq7XEZxHAJhl0B9mUT6V/BoEXZukrTB+edLqu2KK3zwbZoy5qJR0DTcRD3FJGi60K3jhYVM\nVBaiV7JE3ST6yABGpSLAJin+EeXVKxmOmoyu7qZcE6Zx1wBmNMzU8gUoukGxoYbn33EpLaxlNe0z\n3xfXldLmgwflWlatEkZuPn5vYh5AnEEsvrFaKvkQFCek4mHh1bD01hNf236RNN3pfwIybpHhDf1Q\nY6KrCu76HPa7hnA3NUBJI7ijHhUVPSSW0Z2XQtflJx5TUaH7SvmyKvDbv4S+R0TAue6/wdJb4Mdv\nFc/+Ezp1VsOIOriJCjUrTZo2WBho1BJmigKHmGAhDWgz/eG0yA5KiibSBCvuhNGvHUGrTFGhhkNc\nx1LuI0iBFm0XWl21Adbq1UJ1fuxjJ+6aSiVxuLvgAtmpv/iivNbL9c602Ho/W7bs7Fslv+1tkjbY\nt2/ujIEXHt28du2xYk6vtn/DBvn5iy+Kyn2maGoSwNXd7Te3amyU37ku5d4x9k1s4PFNYUpJUAod\nwAJMIhiZIvlQgMXl+4m5Q+SpJ6iaVJwYhZoOGtbUYCfrmAouJ7lJA8smOtFKfb1OuHaMhU0D7By+\niqLiEtZVkg0Xkyp00vDeDJs/+NeEH3yG9u8+hlKqYHYAGYdSPEKhtRY0L70E6Cqq6xzVSkQJ0E09\nV7GUprNcxtl9tThCHnxYGs95zqxqoIozC6KJ0GMulZINZXWaHayCaylYKhRTsiYHa8T9de/BFhY4\nCcLuJFm3/WiaI8wEBbeBg6VrgRIruBdbj1B2NCy1ltHAejK1a2i6rJ6l74LmmTqfO46wVAsXyjjw\nqhKO73ynab63SEeHAIorr5QxAgJyH3pIfr9okfiYjI8LO6Hr8mylUvKMHDgggMV1Zfw98ICUT37u\nc7B7N+YDj0E6i7awFfWWm+GCCyjEewgNbGNr+u302tdQQbQtRqWEa32LFZHdaLt2ybi3LCo1AYav\nWMPhDSso1cUoJ2LkOpsoJSKouCgouLiMkJkZQNi2OLc++KCfQmxslFTHtdeezWEzH68g5gHEGYSi\nQs8N0H2ViCUDMSnRnCm0AKz/sBjObC1M4jaUMQKgBFx0VcX9yCjFVgvnqVpqE2EimSj1S2RB7r7i\n1H4NegBu+uKJP7/ze/CTP4DBp6tVG9UdoKIJ1Zs436Z0YYauu8qEOv10QQidAhUq2IRPASDSA3L9\nzVU7+5Yrayk91Ue5XMLFoFHZR4PRT0jPwfVvFVdFkN1TqSQT2/RyLq9k8kc/koX7+efhz/5M0gGW\nNftuPRQS0HG2IxgUlflTT8m5jIz47o5e+mQmTlxVhcEIBGRink7NZjLwu9+JuVVrq+yqtm2TFsfT\n2323tgolfNNNAiCuvlp6caRSEIngTEwyOdHIrtwtmDlFSouJo1IBFCrE2FW6lUNcSpRxVMfBzoRw\nDZ3acJ7Wujq6Sj8nfOA53Faw3SCjuYWUcwoLGjM0t48wkJ6ib2otqcY6LEVBWztE8rYjBHIaS2++\nnQPFFej3bcNuNzGHDUq1DRB0ZD2uqFBW0VZNUjdlEm/s4DIW0kPTKYHpmUYgCtd+QdiHgacE2DtW\ntRrD8hwmXejMwVjAL9m0FVBdOeeKghKU1xeTIsa0nAS9XM9qfoxKhbJbS8hOYVBkD7eTU9rY7r6b\ncVZxhf1PBLUiDfVHWLw8S+WdyzDuqgUVxndJiqVukVSJADLmJyYEQCxbJszc8WNd04QRiMVknE9M\niC5mOmD2qnIsS4CmZQkD5rUIHxmRhVjT/DbxgYCMuWQSHn4Yq/cI+WGLXKWRUrCJ6LYDxF/oJfIX\nH6Z0zR3s+8Yi+uwN1HGQeg5gu0Gydju5UoKM2oAZqSMTqkdxdAwrSfPWfva//41MLk5UiSABa3a1\nK4iBisEsng+bN4tDZV2d32RvYEAcUBctkvs1H+c85gHEKwgtIJ0uTxV6UMDGFC69gF2VFiooKDGH\nwLtGsN48SmehyC11K9DOQgfkWDN84DFpHf7C3eJMWdMhNOqCiyETNHmxawTDCDJ9GJSxiBAgMNuD\nPf26Qn65nBaA4Pk9GNkR3L159Eqa5sBhAoYDV98C3/iG/4deJYJn5+uZJtm2TGZTVaOZm26C++6T\naoST5YcdR9Tcr0YsWiRfXhpieNj/XTQq5z3d6lpVRTtx5ZViYrVx47HHKxZlV5iYVjJ34YUy+T/w\ngOyyOjulwuKmm+S9QZwoFyyQ/hOpFMXzrmWHdSOTh5ZT8pxpVQ3X0atWTiouBkVaKNCOR0MZISgA\nh++DvtBbuLxuksmRJobN83Bsk5pCL1P2TgwrTDmvkn97Bvv8PEolgNJiYdeXKCsKA0dKLH/vSnaE\nVpI2MpBKwyMNcEQBraoUvDSFctkEtakSGxp76KERZY7amjONRDdc9FGY6pMUXn6Mo6kKuwIoLgwF\noagJ2NGQpllhG1IGWAqqLsyePa2R5x7uwCTMIn5LWElRcJvo5UZ6uQFUFdsJMmpcym/j32RB/V7W\n3TrI4fhlHHh8IdkfKlgVYTQCNQIg1n0IGpfht1LftUt6XYTDvq7BNGUBPf98YRYWLhRKv61tZm1O\nNCpA8/HHZcGNRmXRra2V58pzuPRAsAdYHQd3dAyGk2h6PbFoEj1eJBlai7m/H+f/3k9nWyeP6bcy\npTbjagFCdhLFNdHcMmF3gv6m5ZR6dFxNxplTWkDjgSESjzgMthmYYRNHkQ9CAXRU4oRpn60CZ/Nm\neaY8kOS1u9++XViTeQDxexHzAOI1jFbi6GhUsI7mfl1cLGwisQBazEL1G/6elVh4jXwdHw1EGKGG\nI6SIE8JAp0gFE5seGue0S2xcCYkuKQdtWAZqTQ3WuisouVOsan6CwNr3y0J6443+hGeaktME3wDK\nYx+8cs6775aJT1EkLxuLnVxt7vUKeDUiEpEqh3/7NznPSERAhKe5uPlmYVaefFL0DitWSOOj9etn\nNsSpr5cFoL//WNCTSkkDqC98QUDE8XoHrwfBDTeA61I6oJLdVy1TnFam62JM+4GKi1f+IP84ZaiY\nkt8fLvbwkPM/iThjJNQB9JDCEfsq+krXsqr8CJOtTVjXVlDzMSjqqGUwsxpKnUV6wRQHrCL1b9Mp\n95uUukbRepK4L9eCraKuyaBcPEFAK9Ki1M5JU3O2IlQnQKKUEdBglUU0DGCaLmR1ARJe9sIBojZk\nNbBUqa46juxy0TnArRziBgJujjI1uHoAVZc0oaorKIZGutzKsre1sm0Cev9T3rtc9UjTq5VUw1vE\nF+aNX4Pm1Yq4Ou7ZI+Pq6quFiTh8WBbJRMLX4PT1CaDcuFHo/WTSN6MaHxcm7tJLheFbuFBYCZCx\nls0em4bz2LNqBZRrObiKilNXj2HnCU5sxWjIMaGtIfjyCM32CHV1G8lZjZQVscMO6iXCzhiWrkFM\nQc+56KpNxQ5gx13sGKR2RAg914R74QR2vIKrQgCdOiIso4VOZulAm8kIYIeqveig3JP+fknVXHih\nAIr5OKcxDyBew2imhh4a2ckQJcyjeUDRH0RoJPaq79C8UFG4kC50NEbIUKBCCIPVtNND4zGvdXEZ\nYIoBJilQoZ4oi2ikMRzjwg/ClnvEmApANaJ0/UGU5R9+JzOmuH/xi2MXe9fFIkjObcVQSkSCLspz\nz8muzHVlJzKX5i/33Qcf/vAJOxPXFYOh4qRM3vEz6R58+eWSknj2WXEEbG0Vp8ueHgEDiiKpjmlR\nycPgb2Fsh7A0rRdINY1mGJKauPtuWTTq66Uks1gU98lT9e2ogqx4p3RhHds5/WKPvmjmv/XS6q6k\n4ZwK5PMxKpEobnMHekwlP2xgZm32Rd9JeWkBp/YwykgAVHDSGoqjYsUr4EBasclEbZwVLooLwfOH\nMVb142hVrwfFwA0EifecYRvYOUZ+XJpZpfsEPNQvlvb147vk93ZJml9JTxkXTEUEy1b1PukuhOyj\nt80sgTuLxYJNkCKysOkBaVhXzsj9VAOSRonUw44fgB6RFAhK1VCuLCnESKM8L098AW77JoQ2bJCU\n3n33CQiNRCTX/4d/KJ/3li0CFhoaBJjG4/JMbNrk+4LEYgIs7r9fGIiJCWEgFi0S8DlbVdMxaTiF\nYPaIDDHbombkRZRYlqy6GrdQpCv0AiNaNxFnAsPIY54PyUth87Ib6ZjYQuLQFJERC8sOU3+wn3xn\ngmR8CYEGC2V7iHbzCImwQ2ThUprbltFFPUFmoVtXrBDbbtv2K5G8Bl6PPy5Myt/8jQiS5+OcxTyA\neA1DReUGVlDGYoAkChDCIEaARHVRfi0jQoBLWEiWMhUsYgQJzfBAv8QRtjJAERMNlSNOiv3JFAu3\n9dAZjXPlX8iEWMmJ+LNp1bQc7/Hx2GOyu47HcTMZ0nQyxHoOczklt562wBhrlkCkptrq+PDhGRs1\nFamjSD0qFjF1HGN0VMDJpz999HVmAV7+d2l2VM7K5N62Hs5/7xl0Kl2+fM6TVSUPz3wJ9v9a8uiO\nI6mutXfBJZ8A9fLL5R489JDsrNrapOLj+utnPWZhEqYOVs3Klos2ZsWdMHEAxrYzZ0sFRa0aLFW/\nt8tgmwqOHUTV5fd6RKNsxXDzCoqp4oRtlJyOGnZwNQccF3SXslE5ekwVMFviWBXJ37uqgm1oBBSD\nJqVm1vN5pZHql2qkwefFat61pUKp5bzq7j8tbItZkDSbHnKxKlUQYSoQsyFuQaZaBWWI66Q1B7do\nx/JN4qKtIiruuBQGn5PPnWTVMG4acCtNyfm4toC/oReg5wZFPv/LLxeWYf9+AdmPPy7pixtnKN94\n73slzbV3r0/v/+AH8Ktf+c3m8nlZfKtNrlDVkzJ5tquhlQvYoVoIBFHNEqFUHzmlBWUoxZr03Rx0\nVzFe7oErVCp/NIldo5NPtOKsXUFq7SRLfv4SjVv3U6qpZdeVNxLoa2XlvQdpfvDHJKaGaegAva0O\n/dYbhNk7PlOaSokZ2+SkXNcvfnHU4tqpVESMOz4hgs3Nm4X5a5+limM+XvWYBxCvcYQJ8CbWsodR\nDpPEBeqJspRmGjkLHa5OMxQU4sxuH5skx2b6yFPBQKVi2kxOVXCLFfoHDhP5p5W0X6By4xerzbVO\nFfm86AkqFWwlSMDNspAnaOFlDhq3c8B+F0OPqCxZcoCaqV20JcsEvMmvVKJEDWk6GWMtCg4KEDBM\nFtg7Ce/cecxb7fwpHHhAQE1Nh+wUD/1WFryLP/bqlZ0feAC2fUsWNC8jVZyA331VfDx6rleEar7k\nEtl5BgIzNhAqZ2HXz+C5r0GqVxa2xELouATOfx90XQGr9sPIC5AbrVbcHB/HlfDaFf/nqlHdlVct\n0lVD9Dpet0l9KILRW0N5RQr7UBi7voIbMVE88zPVrR5KvldUBSdk4ODiIu216olwgHHaScwITl9J\nuC7s/Inc71Ja0jmuK54rhTEROu/5LzFcC9YKO1FMa2QiBZgywFRFr5HXJKVRVyEeCqPp0jdmNhbC\nYxo8zwnXhewR8Y5Y9RZ45HMCHJRqR/bjredVXViOwgSMvCTnCchY+NnPJMfvlXL++teipTkeXKqq\nCHBXrZLvn31Wmq6BMGOFgt9bpVQShsKyBEjMxEaEw9hWDNu20MsF0Ta5OgUaiEem4MqrqA09z207\n/5zfqXex6/ZVuGENRoIoDTa52gZsTWPXH1xOg5ZmZMVyUq3ddDxt0/qrn6BOjDMUXE4Kg+jQGPWH\n7qWmuRXlumv8c+jrg699zW8Nf+gQDA3hFIqYtoaGhoqDi4KNitLbi7pxo1RJnalfy3y8opgHEOcg\nghiczwJW04aNS6AqqPx9jL2MMkVBdphAOaPgai40mri3DWONRuj/1y4e+QuNO78v5a2zhutKfj+f\nx7VtcloXphMmSJqwk6LT2Mze/B/Q27uKdLqWcKGVhlKES4x7iKlj9IWuZbC0ihZ2UqSeAAWiehJT\nryNZ7qRZjx1doopTcPgZiDYLZQxVrwpHctDZIYh3zHqmryhe+j7kJ6r96hyxzwAAIABJREFUE1SO\nLuLZYXjyH+Q8mtdKC3TCM5fvWCV46ouw5e7qrrWaqy8kIXNEWI6avxO/kPZLZeEf3ykdX71OrZ7r\n4dFKRfx/NUN25E5FQIQeEnBSSoprauMKyA4rlL7fhXonuOuncNoL0GAeFR8qiichcNFR0au6GQun\nOs0rpChg4tBDI0s4u2W2lSz0PiQpDE0Trweleu+memHpbbDyDth/v4ArMw96jYsesbEWF1GX52Ew\nhFNU4eI08WaFZXsXM7lHoTBZ1S4cV2Sj6PLZxTugcwMke+XzaVoJa98F+35VxYzViidF9ftxgJxH\nOS0mca4lje6OxoMPSrpixQq/fffAAPz4x6KzOZkHwsSEgHMPbMdiksKoqZEd/HRztukCyur3KhBy\nJ7HcAK7rYtoRMtHlhIIl4rV5qUKamKC+rsIli+4hteYdDAVXo09laTmwlakLGqk0BMk01uLeqVAs\nB9A21RN5fh/qaD+T9hJ0xUZVVcrBFlKH09g/eJK6666p3hhXqq8OHRJQZNty7apKyu4gyhgKLk6V\nsrDR0Kn6RPzgB/D+95/+AJqPVxzzAOIcho72e/8B9JHEwiaIjmU6shiVVAi4oLrYV06gD4YZ2tTK\n6MvixjljPPgg3HMPPPkkTsXERcdSAqjYOARwdAfNKVCjHCatdROvyVJjjDI+sZxdxltZkNjH1vF3\n4WLSwnY0ShSpxyJKQh/FRSPdddXRJFA5LbR1zXFGe8G4KPPLaeBVABCOBRO7ZWE+qjWwRbwIMPAk\n3Ps+WHmHzcbb9hCY7Jec93nnHdOdcXibOI6WMz79DYANuWEx7+q4BHqul91wuF5SG5P7Yej5acK9\niICm0pTsmK1ilaIvy/8DNYi1tAWVjPy/fT284Z/lOkZGHLYuzjDWMwlRW1ibqr52OiZRq76jGqrY\nP1T/b+KQosDLDLKYprMOlDNDskCHan1GSdfksx/fCXd+XwS+++8TVsBJWNhdJQLLyzjtFRQqFKfA\nipcJdUIk6TKyRUEPV1kEqo6WatX7oUEAoGZIZdUVn62eiGlSHi0yuTdGTZtKYdxPVUzv3Ot11HVM\ncIIC+FwXFNfBfvJZ3EgdmhFEKRZF96DrorvZtevkACKRkF34dDMpT6Dc0CCAZP9+Xx3q2cd7N822\n0WwT1a2If6xTpsY8hOYoYnJXKYv2IhRCtfO4KFjpGJ25Z6krHiZkpplY3kGxNU5T7yFW/XoLz2++\nmIjWS8QexVUUTDOK1RegdnEAS4+S3zlBwjuFoSFJx3R2ChosFKBSoRysQ6GERqUqCFZRcHAJYKOg\nUkK55555AHGO4vd9/ZqPcxgmNuWq7sHGxXJdKOpCXasuajKImjdwL09i/qaZ3LAKMwGIhx6CP/1T\nrIks+XwtAbdChRhlN4qiqgRCJo5l4FTAjgaxHZ30sMaktRZTsShX6siVF2MFapm0FjBoX0qbso2K\nUsZxDAy3SKb5AuyVPoCINMqiUkxKEzQvikkBEZFXqSjALMl7uHa1snP67h9ZOMZ32uT3pNB/sZUr\nV/6XTOTt7fCBD4i6HOkomR+t/q1fVHF0R1zOSHlu6/nQsBT6n5Qddjkr7x+IibFZqB4O3C+n0blR\nRJ2lKdAqLqW0S6gRNEUhWKPQtFrA1Zq7RAjYutHiCV5iDOnRcLKlX0FBR6Ui5DJGdWoJoFDCZYIc\nk+TPapouUCNW7+60zbTr+mJFFHGf3PBpuPCD0tJ+XKmwe9kwdXqIwrCKVRSh42jRwjkcIT+q4DoC\n+EJxuY/FKQFiHgh0TOlJ07gS0ek8+CA89hhGKsfyl9sJBm8m23gZjqVQzlaFlNX0kqIJkHMdYYBy\nQzC0GaZ6XYKPapTyrcS3DNLKNgJqAcVzWt2z50QDJdcV5mF0VMCnZ53u+URks5K+WLFCml19/OMi\nPvQcTisV0UR4plVVcJGNNZMPNFKgiUPZG4kPJVm2aDu1Vho1oJDIWNQOJBlaXCDiTOCoKmpBIZA3\nab/3Zdb/wyYixTSZmquJOP04zRXcrikIFyhn67DH+ok4CuOBO2i3hdXBrj4wXiovFIJQCNsqoWFX\n5eYqVHu/goLrWVLNpTndfLwqMQ8g5mPWKGMRRCdMgBKm5IvDtixkJQ3jQA1KRcPSLSK1Lg3LZjiI\n48C//Rv2ZIqDlWsYLixmBfdikMfGwHEMzIJBDWmyLGQgeyEZmsiW6onWmRhtJsnxJsrpWmrUYQo0\n8oL2SRZHnmIBz+KWTXZwI1Ox62l6qondT8qOs+d6WHSdWBunXdk1ltKyuK5489z8O043HBue/Puq\n9sGLGcSNGiYVK8Bze29GjeoQiREbHGBR/ufEv7oY4nH0kCwyjsNRHcX0cG2Y2AU/ejME4gIeVF0W\nukCNLHJDL4j+w8xDXY9UJ6gaDO42MQMlGNXIpnQCCZf4ApWMY1F49yCPXzfK8xgkCNHPSRo8TYsa\ngsQIMYhcvCQxvPSGhopCjvJZBRCKAotugLFd8tnqhr/BNiLQNs1bLFQrrrBNRJggxCQ5Ej0RdFQy\nBZPoExGCT7eT6lWItgrbUEwJW6AaUE7J+wVrpZJn7V0QTrjw3f8QnUI8jhoK0Wo+T/jwNsoNn6bf\nuRrVEH2Jh3GCtfI5WSVJFQVqYPNXSqi7thMZWU4k10/UHmDEaKB+cS01gSnZjT/zDNxxhwhuQUDC\nd74josnhYWEYenoELBw8KOWOwaAIfz/5SfEUeeIJePhhuUnlspR+BgJSQm1ZOAoMnr+S4a6V2AGd\ntgP76FQfxDkQZ3KfSooolh6ltrmGpU8NMcog4Xya6HgSK5QikpxiwX2HQDHQKdOg7GP01hDKzjIL\nDh7C1nRK0RhORKEy1ciUEsHNJP3S5s5OOfflywXgLFqE3vsclaPelWKr6yBeJypVP/KTiI/n49WN\neQAxH7NGCJ16opSQ3KmlOjgauBMG7IvC4SBmew53b4xFHQPUx6NAM64r+WlFhfJgFv35/eRzLfQX\n1rGH24gwxlJ+Qx19mARRgIn6Hp5e934yCR3GJrH/f/bePEqy667z/Ny3xR6REblnVmZW1r6pJFWV\nXNosb7JlbAvwQmMbMEM3NPQZ6MHN2gOnGabhANMzuKFpN7S7gTMcYwzumbGw8SZjy5ZtWUupVKp9\nz32LjH17650/7ouozKqsRaUqlcTJ7zmpk4qKjHixvHd/9/f7LocyVIoRrC6L3j0WTj7KbHkLjojg\n+zpHW+/nmPbDqk3cFBhnwY6r3fj5J2H+MBz4OTWXvvCPak5uJWH3j6oC4nZg4Qic/sLqHfEVEBJT\n1nGJUPdzfPu5d5EWswhzMy+esnlo9xRbf2k3/XtVrkqzrWBd2YkIEbhKndFYVjtbM6E6K9JXstX6\nvLJP3vIDijchNIjvsdHfMY04aWCejhNPa3jCJ99rY//4JP7WKlpUPdFFJGvxMi+HhU4XcXxkxz8k\nCA9aR6CjYaHfkDnZK8X+f6ls4pdPA1ItzpqhCqbd/0zdxydAIMLOiM4BxjjMFMvUqV0UFP7DIP73\n00SbUWJZ6B5SdvDzh2H+RWjokOiGvr2w+V2K9Ng1BkzPKBXAwABOycX//hGsaoXuRpX99v9Goecv\nWaiNoRmqgPHsS+okPZSAypk5Br77p3T7JzB0h2xwDF02mXDfgn3eITG+hLZvn5IvHjqkJMCOA5/8\npPKCaDQu5cccOaIKiN/4DbUA9/cr58q23fX7369UP56nZKBh4cD8PEhJYesQS1s3ElRNUovLpGcW\nSBsLLGzdivdiEiPwKXhjfGv2w2Q/PcGBJ7/AiPctpBkgXA2j6mIHGRKiihazKPTkGCl/E48oxdwI\n0VqZaKmO121w7uFdpIrPUPirGXr/dXi8H/gA/OmfqljzZBIcB3PPOP6RGn6hiIGNRBIgMGgiCNAy\nGZUvs447gvUC4nWAgIB5Kh2fhc30MPoauPZdDwY6Y3QzSQFJgCEEbtJHVnTQApzNRfSyZOsL53kn\nfw3/vpvie3+eUye3s3RcGfm0ZiO8s5hAtGosBLtp0MNhPkaFITbyFC26OLX97Zz+uXtwRiyQs4CA\n03H45BhO2aKxvYnup2kt6WoOnQa7Bl5DdHIJAg+KZ8OckLeqpNJzX4WHflW5b7aKavcXuX2KQhZe\nUgt352NbI8RMxyFAx0fJHWzSVGRAzCmiuS2+/9/i9HwAspvhvn8NT/4aONewwdCMUEkhVNGWPxnK\nPNNqzLF0DEZCS/T8CXDeUcS5q0g0miLzvhaxB+osixpLVJFCKSciqBTHGtfXMuoIEmH3oYGDjoaN\ni4mOR9BZvHU01cW6xegag8f+EJ77pBpRSKmKh33/AqxdTV5gkQUqCATDdLGNfjLEeDNbOXe2wTd+\nVcN7LkI8qyzc6kuq62Ml4OHf9pkp1yiKBskNAYPRFH2kLp2Xs7NQLlPMpyh8fZqp1jupyiFS2gKb\nrG/w+PBvce4jv8vpQ8Nouipy2vbalWlwqpKR4qfJtl5m2dhK1lrEEDZRWWSUp1nw7qUV6Sder6vR\nw/HjqmPw9NPwxBPIZgs3OYBjW8qZWuQxp2fQpqbUonq5zOjhhxWv4itfUR0M21ZjgyAgAMojvUjH\nQG8GJEvLRJpN8oMbKG4cIpjvxSq2SMfPIeI19Pka0dk6ZWMbA/IwQpNogU9CqyO6UngHHiBRyRMr\nlFju2UwgNYTvEwsK5OoXsQZrJEYMnMMv4M9MoW8YVR4Xv/IrqiibmoKhIcRDDxGLDDH5E/+R3Pc/\nQ0LOh8waC2OkF774eUUWXccdwXoBcYdRx+bvOcIZFjsbzKc5j4FgN8NspY8xcggEeWoEqOTMLHG0\n25Qp0EZAQIEaOhoRTAICXN1H3+ASSy6iL9mk3IBN/9MSZ1sHmHN8po5OIWZ76DZzFM8JqrNRZlLv\nZLT2mc7rc8hwhvdxyPxpmpEc/OR5GGrAsYTS4hsB7KrBj87Bn43SSrQI6nGSAxqtkugkKWpG6Gng\ngR+olvPsC+q2vruUQ6ZdUTs96zW4xojwbBICWCHxW9k5kDLAIcmlKkPHI0mNOI6s4E82mX/eJzuu\nc9/PqlHL3/+0KoDUg4c/7RwHDYR/KZfMdxWzX/rqfaguwOTTkoO/5pN/WeNC1EYLNPp2CCI7W8xp\nNTz8FVMSgYNPFIMIOvY1ehA6AguDDXSRIkqKKCY651jEwScg6HQiijT4HIe4hxEeYjOJ0IzpVmD4\nPuj7pPq8ZaBGNXayxfe4wDI1XAJqtDjNAkeZ5VF20CvTzP5NguZLkAyJM82SUrc08mDXAuy3LuH+\n0KxSHQHnWWQrfexhSBURySSOG+Hiky7Hmz9DlWG1K/ZdJpv3s+P88+z/V89Q1z7I6S9e4qe0P6dc\nfJbByDEq7gaywVl6qicRWkAgdGJymRH3KcRElurFGHotj3fsU4jxMZJZG39yjonavbzMj1GSG4lq\nFcb1b7El8RRdF6bQW60rFT6apsYgb3mLWqT/zb+BfB4fg4aeQy9JNM0n8CFdWMA3DOrpPnw9gkwI\nHBEFG1KtWQa0F2noOQrsxBQ+3bFJzJiDcGw4+Casf/frbPqdf4+9ZGPoLTTfwbLqRGQFT0RINiqI\n4RFYWMatFNEZVce4bZv6WYE4sOU7v03x5V+m8v3DxP0FEg/vQOzZvR4BfoexXkDcYXyN45xm8Yrb\nPSQvMU2FJseYQ0dQpE6JJgEBcSy2M8AY3Qigik2ROjYui1QpoQxjuklwLyOM0UPyFV6089SZo8IG\nsgjgLEvo6Pi+R6RWJxm4LI6l+dK2MbUANTVk2SEWvIR4bhz/OxtJDwueLf0CetdZuvOnmeceJJL6\nWIqml4I9JdhWh6mocgR0BHgaTEdhTxUGbMREjABJ9h4Pf8mkPKVmyLLND9DUPDlw1c/8YbWTHNir\nWsWvFQbvUZyDtnmUboVhTp2NfDsLIECG7XyBh04LiYFDCmELWhcLEFo/7/qA6myc/P+UUZFTU4+0\nMqch5JapH191JDQdokmwen2WZwJeWFyg9zeL9DQEtahHnymZoRk2hFcjCDsHynbdX9OjSkcQwyRL\nggyXWKopolgYWECFVud2CbTwOMwkGoK3sg3jFo40zBj0r0hzP0OBAnVcfKrYGGhoaMxT4Zuc5i2V\nXRTOxDGi6rvULKi/00zFpyicgvJvpul7SWPg/U2S99g0cDjLIgOk6SUF27Yx39rGQjNDgz7STGJi\nY1Jjmvt5bnaY+F98l6W06gjFbFWcuNVQ5tmoI5p1cBMYVHGI4RkJkr5LVBbx0SgW0njEiOFiuTUK\nx2ym+7dRbj3EEecD1BhEajr4OovuDhbdbRwoTjEYWftctyvQKGWJJkaI5XLY83WeF/+Smt9Lj/UM\n8UYeUWrSstIQk9RyOQLfAFtDBgE0dDyRAstHpj28Hp9J+Saqje1s2lMjkr+gHDEdh9yWcYrzZ7B6\nysTyJUQg8SImhudjRGIYy0VkJo3Zf30jKKFB7u4U3P3mW/F1WcctwnoBcQdRosHZ65DUKjRZpt5p\nAfuoVbNIk+9zkZeZxkfSwkOGBj4rUabFeZZJE+FuNrCXDeRIXHc80sDhKDPMUiZJEzfsRgSA1KE2\nnGK5fWchlDuhrrRubtxj4aEJojuzmBe6sI00T977h/SeOoGY9ijlRgjiEuZNaBhgXS62b5sVSEQi\nQGZdzAEbv5FhwwMmsZziOUilG0Q31SLdVqUJlJ9BIw+li0qjvxIBknMs8hLTFGiQCt+bHQx2TJFu\nBr274N5/Dt/6XaWg8Ft0TJmEBjIQ4NFhk4NAww0FkB4BFr5vkehbbfSz4aBymxx9M0x/T7W/G3n1\nEDKQaBZIX3Y+C4FQM/Z+n2rgEMShdTqC1CXVVIMGDnlqOHj4BDTC0UL7KICwfyCxMNjDIOfId0YU\nvSTZSh+LVMLXcOk98/DxCGjgrFl4tPC5yDLzYWF6u6C6dZIaDjHMTrfOJ6BMiymzgBGLY6XU6Kv9\nEuxyaPwUk2i2RuO5ODOzFiO/UiS+DWrY5KmpAsIwOJr8aeaYIMUUUSpIDOpiEFcm8IMIJ45uI/1h\n6N2tFDDzrVBiKySFSi8Vt5ckc1QYoUmOlD2LRRwNlynup0UOhyQbxLN4MkpEljkzv5lJ8WZapEky\nh6aBK2PU/F5OBu+lfLrJ+ya1VcZuvqtMtS7+o3p+szbEiPNRtMhZppoPk+MMc80D1D4ELStD/EKV\nu5//AprpwIKJ1vTJME0j6GEhs5vY3rNsL32Z+mYTXzMpOgal2Qr9hQI89RSFqVOc3reBoZNdpGfz\nVPoyiCAgvlxDGAaxSgPhehgf+BB692uXk7KOW4v1AuIOokwTl6t41Ieo4RBBp4GNBCIYBEg8XECG\nNj1XFg6Xo4LN05xjngq7GOQuhq86Amng8DWOczHkZNRo4YWs+g7Wah0GEmJA1cTPeXiPLlD6tI7f\n4yK6PRq7duDM+gQ75uB8HL5lgi8VS63XUbdFAtACGLZhPgI/NYnxgRJy2aT+x9vIXzTIjBhEu8Gb\nUbt8LbLarAeUzC6SUWZSKwsIieQQE3ybszTDhXOJKlMUmaXMO9hx09wTocH+n1Vku2f/SHk5SKE4\nCTt/SLkOvvhnGoEnELjo4WffZpVLdAytRe/Dq/MwRh6CmWfV32dGVPfBroDvBiqjwgiQmmrFaJrE\nyghiWUHT9XDdAIYdyrKJQYUsMXwCdAQBATVstLCb0MJdMWbyMdDYxSDv4S5E2DdRExT1/pxkniPM\nYOOGIy5JhSb2isdZCzVa1G+AX/FqEOm8HomGRlDRcS5aOFWL6IDG8kiVDfdLlk+p1+LUQpfOdi2b\n8ggCidbl4xZ0St+ME99WvqJIF6MbmKWXHKdJiAK2SOPIJAKPgDh5bTe9KdXVmH9J+VMEnir4LENy\nVryHe+WnyHGGOr1Y1HBJ0qQHmzQCnxYZpBTh+y6o009VDCOlwKCF7WeoyT5c4gSayexCL0//gSIR\nD9ytjvP038Oxv1FunKlhsOdTnCw+guccIKmdx4pIzNMawRMGzcdMZu/ZwYA+weB3Jkgtn0HaERpW\nFy8nPkz5gRTnfvBuev7fk/SdmCIwIuiRJk2jSWv3Nvz7D/LcwwOUTQ9HfwcDL08SvzCBVqlhCoMg\nkcLr68F866P0vfejt/V7sI7bi/UC4g4iRQQTHfdypt0K6OH+1EdiooViJj/8N6W7v1FIYJkaR5hF\nQ2M3Q53do4fPPBXq2JxlifPkQ+a8QfPyBUFwmb0hCCmRBuCD5wuwoVbxkdmqik7WHJp1SWKfR/AL\nF5AtDfk7W+A7WfhCP7xnAe6uqmjlhA9lE57oR9xVQxtZoG/Uwv35OYJ/kHiTWbq3CPwWOA1lOSy0\nkIGvKZ+H4YOKB1CbX/0eVGnxPBM0cYmEAsOAABuPl5hmN4MM0sXNQtNh7GH147tqwbCS6vbAg3o+\nwvHPqq6DQS000oqGgtkWqVFBasPqwi6agft/UXk9zB1SoVxmXPLis1XKRw1EzcAc8Ek8Wmb56Sj1\nik49EPhxF0ab0NTx7ikwR5k8VTLEuJcRfAKe4kzIcVHvRTPsHFjovImNPMLWTsFweXdmM71UaDFN\nkXLYH5sij3edcrbNsbidGKaLU8zjyoD6V9I0PttD68U4wbJBVZcs7m4w+rEpEm/tQpxK4he1Dq9E\nS/nIPocg6mP7Pom0QeuCQQsXA40clwg1+34GDv1ZhOXWDhw5g0UTZECTXqRu4icTuE0lqa0vqGI3\nbCLScpKc5V20SLCPP0fDYZb7mOAhNvBdskxQYDM+Uer00sfLFNiKRxSJrrgLooeaMUqgmUihIwOd\nxKAayRz/nFLheLZSIkW7LrmvmuNxmE9z8Tu9JI1ppG0jZUDisItxPqDx0GYO/8/vp/moRuSzX2Op\nNMri3H6KhW2wf456T45n3v0xNr58jp78OYh4NN4exW9GCNIJytkovYtNgqjFzE99CH8qR/6cQ6pr\nE9vHNDbsyxCNr5W2t443EtYLiDuILAk208PLzF31Pj0kyNPoFBJwadm+mX2yutAHfIdznGWRNDGi\nmJRo0MAmAKYo4OKTJIKFgb1WiXNZESE1DSIghMTXPfi/B+GJPqiYynhqLgoDLVrJJroBfreL9WsX\n8X9fw/vrfjgfg3cvIvpdOGkhjyXhfJxAEzAVpX80hb3fx713ioOzSaa/ZHHov6mAKc9GZTvoYMXV\nRTM9rFQHmdHVh12gQZkWWqgMABVypl6nxzmWXlUBsRK6CfqK0C7NgPf/JdQXTSa+YYSTedVJEgSI\niMH+/3VQ5VFchmgXbH9c/bRfx4x9gd7zMXSpEdnkMGktIz+Vw/9qt/p84h5UTdhah0fVqMwloIga\nY2yil15SeATYuCSJMECaWGgIvo+xaxJ1TXTuY4xxuinR5JucusrgYjVsPAbWjGq9dRimi90M8fTz\nSxT/spvgeBy5YIKjIR0N5xsW548m6Prfp5C/7SMOxeB0EiZjBHdVICIh6tPo9ggmU6QGGtSwGaeb\nvhVeFv274d6fgef/i0nFGwUZhKeGjmEJGnnlGtosKKmtbqiRlmkEeI0AKU3mzPt5ytiC3bRIMUOD\nbqZ5kDRTmDTJch6XBA36CDAY4jkqxjhFf4yq3IAbJJRxlg9GPCCyq0V1Q4ulCR1zpkpXLErDy5Du\nWp0XEb9vM+aFGmX3Pizq+G6L6t0JZn5siNZGA7nX4dmEQ8+md5F5/jwR/yw9yzMUdncTSAtELzPb\nEhQ2DzHgPEsrJ/C+fJhkIyA2/DaEiBF4OvN/u4HS6c207IAoBk4ySet9sPtDodX7Ot6wWC8g7iAE\ngnexmyoOFy8xCjrIEidGhB4EJZo0cXBCrgPIDhH/+pfslc+pdpcVmhSooyHCibxgmAyDdIVmQD41\nbLqIYWKEIxMFDYEvJRQNWDIRgy2IStBBRgOMpoX3VDf4Aq3XU/N/CUE+gj/lM/b0ZmbfcR5/wIY/\nOAkTFjybhScGEZZEGlJFLRsShKTW8jjFAlFMIp7FoU/7LHxZcQiiOWXyo+mKqDZ4j8p0KJxRORij\nD1/9fViJtgrhervnVwsjCh/7Knzpf4EXP63hG5pa3B8sYe1pYT+UpcEIca7N/izRIB8pw84yEnDw\naOGh/9QM/uYafC8LNR0ey8PblhFDl1iXPpJl6uxjlG4SNHFIkel4JSxTp5sEyescA6jvcIoohZBw\neyOQwDRFNt/ibIyV0BDsZ5SZb+U4lQ9oFQ0VnmUFEA1HP0mP4hNp5O8fh0cELJrw56NQMGGwCTEf\nWTHxEi4DD/vsYyM5ElykQAuXOBaDpPmBPzLRTHjhv2oEjoYWZmDoFuiWpFH3cRwBjobvgdUlka6G\n7kgCNyAWrdNwcgjTw/FStGQOlyh1+omzRJ4dXOBtCCQ9nKY/dY7B8TqVhTReMQE+iEAikj7e3jKz\nm4vIlg7C5LvaOXqyJu6HupBf30jvCsKrXRF03ZXCSMU5Xnk/znAN/73zyJSLSAWQ8JEClve28HZs\nYudxQa6pk99iMeM6JBefR28USAYzkHRwnAyZU5MklmuM/y3UDt5D60uC1klBavMEYluSjNaNfQKe\n+89Kdrzrg6o4XscbE+sFxB1Gggg/zkGmyfMMExSpkybGZnqJY5EmRooIJ1ngWS7QwEWgxhcakCZC\nGft6T9NBDLNDn2vzKVQ5IlkKnzuOiYOHExLiLPQOX4DwvnylByaisKWBDAQi54ImEYtR5O9tgQsx\nyLgEjgA9NNBJ+JCP0PN0NzvfYfEiU9QjNnysQO1YF37ZIBiwwdGgZEDUh011/KEmRXxlqT0Z43xr\nCmNvlMjRLFYlSWJAYKVg6F4lw2uVlc3wrg9Cdnz16x8gTZII5VDNooX5fh4+Bjojt5HY14ZmwL1/\nUubir5+goDWQWQesgKYBT7LAM1xgN0O8mS1rFhINHL7HeUo0MNCwMKnSUgWlBeLRZXj0yoJ0Jaq0\nsDDYTj8vMU2RBmaouohhsoOB68qEZagUepEpZile876X43kmbmurW8wmAAAgAElEQVQBAaq4ic2n\nyLZ85guo4iHjw+bwPe+zkWdiMBtFvLmIHAVGT0LNgqz6PtPS8NBYGDMoYnKCOUo0CFBFSo4EbxIb\nyY7F2Pyokt0uHAntxDc6lBM1yDrIkkCbjqIlJf5sFL+kE2gWQvPxbAMhfdKJAhVnGLcZBSlwSVFm\ntXFJXttDdY8yTOuahpypRiM126V5YIlgpKkcY89EEXdX8Icb1DSLyHaDxcUZot/eQjwrsCtK1TP+\nKIy9J2D2G8vYjg1jDWUkNqaCQNqFdcvyWLqni3HG2fzyRb577mkqvTbRoEjDMnC6ehj57gl6nz9F\n0NdL//ePkz16nuOzP4FlF0k7k8Smu6iIR6jP1LEXGxx65iIXf6vGxl/Zz93/Kv2aKqbWcWuwXkC8\nDqAhGKWXUa7ORn6ATexjhHPkWaaO6kBISjQ4wfwNcyEEGgFex164TcHUENi4lGnSS4p62O1o4HR2\npoROg15Rg8/3g6MhyhG00z4i5eF/O0vwRB9UDEWGLJuKHJnyCSSqwHA0UkmLA4yxn1GauEy/r8RX\nny9R+GwX8kJcFQ5xHzY24X2LiKRiffgESOHDwSJuLMB91wLmoRziRBJ/3qT1Yxex7m3gi4AlE2Y0\niyEybKWfIbrQ0Yhi8gCb+DonaeKFS6Sa8m+im3G6X+3HeUM4JRaojpRDauLqrkcNm5eZpobN+7l7\n1UJepM7fcYgFKmHnIaCxgoh7o/0TF49ZSvST4n42MUWBGjYZYoyRo/s6ltNlmnyZo5xe4V/ySuBc\nhzx8q5Adh4vf0FWUbNRH7qpCylMdrqQPH56DcSV5FhFgxEXigo3yJOmVSB2WgG9yihgWkXDcBUol\nZaLhTG8jlhWkhhRZ0ujyqI+U8PGIRw2kJ7GTHuI9eZLzabwFk1bEJjJuo08ZOMfiuHODsGxhagK3\nwWoTstD/Q7egMqkCz97088qufWna5f/5L0WaMwba6QTSF4jRJtqH55GaxMajexCcg3WcI03s83HM\nBGx+DO76KETSJqPjdU4wjyRQHcaO5JiQeaVGfXPTR9n0n/+G+48+z7l9IyzuHiVSrLP9S4fY/K0T\n6H6A3mjRVWxS3TJMdWwjzlIcr6sb61QNtzKLa6fwSdAigZg5TvmXvsNzc/+Cg783uG7r8AbDegHx\nBkIEk12sjpdshdK6QugRUaW1pnJfOQZadBHHxUeiLix+eJVqX87nKdNHmgxR6jjEiWCi0UsKHx8f\nSfVChOJSFGtnEyMhaD1UwJuKwPkoRHwwNTADaGqwZEG6oYqCpQgRQ2fn423LIkEci5JZp/93CkQf\nrjL7DxFk0VDeEI8uwwOXdrYyAFo6lAyk4cCeMs5dFcRMBFkyKfTXINpa9brPs8wzXGCQLt7GNjbS\nwz5GSWDxHBcp0yKCwXYGeNN1Zv63EnlqobJl7eU3IGCGIhMUGA8jwjx8vsYJlqgCaxpd3jDmKPMZ\nnsNAY5xu3sp20qwdLb7W336D05y7yeIB6Lym242Nb1VW14vHITADSHiQtyDtwj0lpfbRg0uzwFAG\nTBRWlmMBqmvj4BEPuUESSROX0yyydWwjpQuKvGIlod5w8SIe+pKFlYJWugUtkyDp0hqvIB6wMfdW\n0Ta2SNYTlF+0EP84QPoLg7SW1Xfda4ZProEmVM6Jbqqcjy2Pwbb3qX+OZFokfnOCxnMmcskg6LfR\n7iuj9bnttAiEIenaLLn/VyXWolIorUyq3csGLrJMJRSEwyXPsrb6K4FF5LmXkHOzZGeLHDh6jkCA\ncD1EEKgALE2Dvj7MfJ6u3fexza5zZC6BUXSYLm6i4eXCrU+AhscsB8CXuJ/6HPM/83MMbl7N01jH\n6xvrBcQbHFEsNtJDHYftZAgIWKTGMjU0YJRudjGAgc4RZvDwMdGohYTJtiNBGx6SAnVMdA4yzgg5\nTHRyxCnQYIICE5ZDzdCwNZfWYzOqy/BEryJV3l+CggWH0+rqUzVgNgLxAMPTeevPJa4I3ZKAEIKh\nH3BYfvdF7MBDalcqRQUgUx50ObA5jC0OpCosLB/61pYGekimKPJpnmMvQ9zHRiSSPlJ0k2IjObbT\n/5oVD6BGV+1cwbUWYQ+Ji8cStc5im6fGLOVVF/abRSvs6QAcZoYzLPF2tnMPI9eUsXr4vMwMc5Ru\n+vm7iLGXDTf5168MvbvgwV9WapzJOR95Pq64NTkbMp4aU/SH35u1XvaK2wJUQm0UAx09lHRKGjiY\n71qmPhPhrOYR2Z7APQzulKkSYXUbZ8ZA219BvG0ZLxZgpSCbtmjpGokuDX2vTyk3jXWsC28mjvQV\n6VKE5GDRHgMKpTIqT6ljkhJMoRMfgMjjy7hhV+3SaFK9hCYuFiZurkVPThVAK7GRbh5hC9/gDHWc\nTmHbTlkdJEMLj0yxhRC6so+u1dAcR7mm+b5K/jQMlbGRTqP1D7CVOSaOFTl5fDtNL4kafOmYtNCx\n0aMt8vHNdO//K/5O+zJjjPIgm5TPxjpe91gvIF7HKFDnJWao0CRHnBxxdHQiGPST7szHt9FHjRaz\nlEP1ucUgQ+xjlBwJfAIcXGYpcYrF0BZK4fIdrBsWGBEMUkQZDhUJPgEF6ixTo7m1hjumI3tt6HGg\nosNCOMAsG9Bnw4ESwgJ5Ig4bWnBXhe0/Krj3gVEu/9r1kWKCAj4+mlCcibWu5VKgeBRZX82zmxrk\nXDCb4AuIXXs/7hPwItMcYQadS12QU8xxnjzvYmcnhvp2YxcDHGaqY9x0JRRJNs6lHZmNh4cfFjry\nGn97JRRvhs6O9HLUcXiac3STZJTcVR+nFJJvX0nxYHS8NzWG6OLd7L7hbsetwNAB+MhXAj7/+RKn\njjcIzsQRozZsbiEHGx0L8huBh8QnwMXvjPkCJN/b+jLy4xb+nEVQ1mFLF/JwGrtqImc19O0N9J+c\nQdtq4xPgAXUkTRxsfMxuDTfj4f/xEUb/aA9z/yNJbTY0tTKUQ2bgKWJwNKMSX5/+A1g+BdFcjOTj\ng0QeqeMJv2MCdin4WlDHxkTjWS7SRSwk0F4aUwkE9zBKH2me4QIXyePgE8eijzTtPJPc8FaE+L5K\nz6zXVRhXtap+FwKyWXj8cRXQNT+PNRJB1MroOBhh0dCO4q7rvaS3H6POMGfes59qn8NLTDNHiY9y\nH+kVhM91vD5xRwsIIcRFaJugA+ra9m+llP/HnTmi1wckkic5wfNMrBJQCpR3RDdJuklyDxsYogsL\ng4OMM0eZMywyR5l5Kvw9R7BxiWJ2xg+lVeXD2mjg0sDla5zAJ2CcHqYo8CJTSKAUqcPHWjAdUQt3\n2YQhG04m6WziR5vImZgqIjY1Sb3JwT/YYCJ0MVyJDWSZochzTFwzcEmIsAORdtXz9DtqTt3UEb0O\nN9pA8JGrxjx2uKseIM1+xm7sQV4lRsmxhV5OsnDFv7W7QjoCB48aNnGsDpFVGUHdeLfEQidLnBYu\nZVpr3kegiogzLFyzgGjvTI0OK+ba2E4fP8J+qtid4K1XExInA6jOqSdODqrd+fUQEHA0MgX/bAnL\nX8Zrhrv5qFrIX2knZT4cIa1EE49IL/RkTUp2HeeBIkY5gj8ZQUQCjK0tfNNDoKGFn2uFJsrY3KWJ\nRBhQ31BB+w8vsP/HdjLxG91Mfl8ZXOlCI77Jw/vxCWbeMc9800T/eh/6TC/y6wn0LwyR/GkD45fO\nUhVNXHx0dBJYiLCDkCXe2Qi8yNQVduIqcCzLB8lSocFJFlikio8kRZSt9NF93wg8+Qy89JJKzKxW\nIR5Xv2/fDh/9KPzUT8HXvw5/9Vc0nj1LZeHN9OnHyXub8aWOQQuPGG40QjEzhkxCY2cEP6ZGQIvU\nOMQkb2XHK/xk1vFa4053ICTwm8CnuLTpvPLsfJ1AIslT4wJ5CjToJsFOBkiqgektw1FmeJ7JK3aY\nErW4x3GpYXOYabIkiGHSxOUE85xknhZuaOvz6iSJFVp8lRMM00WeGk0cAqR65N3AWF2tdsM2PL4A\n0zE4F1MqimULzsaRQzaJvTY7H9NpahozFNlKX+e9VPN8FcrkExDB6Bx5sMbxCwvk1oZ6M1ygbqou\nSNq/OWOMEA4+h5jkHkZe0eJ8szjHEhIVmd5iNaGwHUDVxOVrnOQpzpAhRhQDM1TEtM3EbgQSwmyU\n630fJNXrKHqyYSesQAMDvRPEtRZGyPJB9qGhkbkFHYflM3Dsb2H5jAQpyG6CXR9Svh/XwjxVLrJM\nhhhdeoxa0iZA4iAx0RGIDiny1cDBo2o0EYYyK6fbge5W2LUgjBMXHV8V1R2QISNJFWVdxKhjc/Ke\n03Q/kaDnySjLX4vivGcO+83FTrfElcCBPNqPJEj9j3Hkn49S/1Q/B+9K0f2YUtT0kOApzuISkA6v\nUToaWRKUaLBEjUEya70U0sR5E+M4eLihMkdDgxzwC78An/scPPsszM2pscUDD6igrv37VaX/jnfA\nwADuEy9iv9CDb8Sx64N4dZ9oUECnha3HkJU0qb1HaOy1FNEjxDHm1wuINwDudAEBUJNSLt3pg7gR\nvMw0T3KKemgrLYDvcI4fYDfbGbjen98wXmIaL1wgLt/lqewCmx6S1LFZpMIY3ZxliQmWkSFF6dUW\nD23YuMxQpImLiYYRLvAAIhk+R9yDrIf8xQvwhT44lkS4OunHK/T/YJOBByVCAztsZfsEPMMFTjBL\nHRdJgBu6Qard97WtuTstZxOI37qI6Dy1cOd2ewuIInW+yzkWQyKlhljzNQchD8INPTlSRBklxzxl\n8tRv+PkuLVJXf1eVEbag/zqzZwOd3QxTwQ5VOoS9LTDRyBBlkC4OMMrILVS01Bbg23/isjDjEIw0\nMYRG6Vic6qLFI7+ukRm5+t/mw110BJMuYrj4RDBp4hDFRCBo4mCisxzmvayF65FWVYGvSM1+WCKY\naASXnY0rmS+XP56PxMGnToWCXkc+FuC+U5E8hVxxLQhnUsGWOtWfPEsy5eF+Ypylzye5753J8Hxz\n8QgwLvs+6wh8Apap4eMTqznkjl1EtGwYGYHx8Q4BSQWjXbZMjI7Cxz8Oy8s0lgKKlV70iKB7O5jt\nGkAI2LOH9M49mN+FpUMBsksNVVpNTbVVkg7ig1PUPmbjDKwuZG5H9Ps6bj1eDwXErwsh/h0wCfw1\n8Akp5Y1vr14jFGnwFU5c5oegdun/wFEcPHpJ0UvqVS1AEkk1bDO3i5TLEXBpkfXC0OSZUIcfhDvX\nV4s2UQ/o7M40tA53YM2/2dpA/uJForUIOT3OhniaWMjT8MMCYZAM51jiMFP4BMRCSVw1LMpuRlWg\nhWZGMgxxulkzqHZ41O1EEBZPC1Sv6DysRHuJCfPCCFCfwzI10sSoYt/wrtnt9DSuTb7MkrihQniY\nLt7BDs6zxDxlHHx6SbGHIbpu09z61PdtJqZaaHvqWJqOh4e9s4X9coap78bJ/Oj12k/qVWdJUMcJ\nB3nqLMoR5z7G2EE/f8sLTFK8VG61v5BCTcuuh/Y5qezAlQBShAWiCr1Tn4aFholOI7SJF6hzpEqz\no87pfJPbl5MVRUTHCFYoQ6zmW+aJPJ+hVe7BaymlhoVBFzEWqBALCyVQEtwCdf6RUySOnuGuv/gK\npckivUGcdLIHHnkEfuInwLq6MYOUglPf6eHMFy+5bGZG4O6PQf/etq9MjQl9GfuPSzh/kcL/ag+4\nUaSIoGkR/N88hvjZEojoFRe69C2Me1/H7cOdLiD+CDgEFIAHgd8HBoBfvpMHtRZeYqqzMLe9A9pE\ntyo23+M8OZLkiLOfsZtu2QoE3aTIU1+R2bjSvlqEQUjtHZ96HhmS1F4Jse7qx7DyaERIxhKdJNBr\nISo03prajInOefLUsdHQcPHpI8VGuvkqJ3DxyIQz2VfbPk5isYkemriUw9bszbwPifCSfzuxRI1Z\nStcsHtpof/7t/auHT4EGZijAvVGstD7XEZhr2JNnifJe9qzKebgWsuH3/LXCxfkqnqGR06zOQugJ\nn1rUZm5GZ881xoi9pDjDIq2QDzRClmVqFGgySo49DDNMFxqCH+ZenuAl5rwy9jcz+M90KZLwpgY8\nUkDsrF9zVCa4VHNY6NghbbV9Dmth9ooXdihW2tNLVOT59TodVxSBekDgCoIHl8lMdGNE1bm6SJUI\nBg4+C1RIEsXGY5YidRyMSp37//uXSc4WmN82wJJhsb1gkv3Sl2B4GN797s5T1LGp0ArN7aLMPCs4\n9lkwUgHddwG2xvJ5yTOftXlgGJa7CxxiiiJNnE0e0V8q4b+ngPjrYbSyyaa3CCZ+tEh5jb2WAB5g\n8zXegXW8XnDLCwghxO8Bv3aNu0hgp5TytJTyP664/agQwgH+TAjxb6WU19xGf/zjHyeTWd32+shH\nPsJHPvKRmz30a2JhlU2vuoKsPIk1BF3EyIcEoEfYetOdiP2McpH8mouMtoIvsIleusNo7kG6yFO/\nJctfu2jRQgmX6gwEmOjYa+zvNdRsVUcjQYRekmykGxVUXMYNd6ij5IiGreN2ceJ0GuA3B7VzkxRp\nMEwXGaIUaNxUAbFvFZ/39qBAnSLN696vvaCshB+WEyqr4ubeMzXK8DDCYrM9e99C/23rHrxaSCTN\nnjq62xVmtqvbdakTtEQow1y7gKjRohYufMvUOpwHHZ19jHCAsVVEwjRRHmcvf/efCix8MYYhwBts\nwJkEPJNF/u5JxPDVk0TVeUNIlRQdjsgl6e2l0cVa5m/qE74GwuphZYdK+AKtYmIOu2zaCrbm8jwT\nLFAJCcMqsr0Wejy0QjXP4JFzpKaWWN6xgcDQCQiY7dboKscQTz0Fjz1GS3g8w3mOMksjTFDtJ0Vm\ndpz822y0u6ssAkbDopmtU9NsLpoODnanq6KhkewSyAcaxB+YIEscE50fZg9/yws0V1znBLCTQXYx\ndK13YR03iM985jN85jOfWXVbuVy+ZY9/OzoQ/yfwF9e5z/mr3P4s6pg2Ameu9QCf+MQn2Ldv3ys+\nuJtFZsXFda1pchwLA50siVDuWKfvJrXMm+jhMXbxFGeo0KIdoxzDpJskQ2TYTB8byXV2Y1voJU+V\nJs51iXCXQ0OQIUIFO3wu0bk9joVEzVMV+18p4NsXv7YYsu3y6Ie7Kw2NEXKMrMHo7ybJLOWwf3Pp\nGHxk2F25fjx5+7lj4Y5oH6PsoJ88Nc6yFE5/bxzb6efB12DXU6D+qlwYfSQNbCKYNG5wVKWHhaCN\nj4mOgcDGR4QzehOdPDVeYJKH2PSa+mHcKLoOOhSfdGiejBAZU/kqrUkdrdth4IG1/2aSAkeYDscE\nMpSS6ozSRT8ZhsisKh7acE/FaP3XIVKmjzXuUE43cfta+Bei8NVe5E/OrBkCpcLndEwEDjIUUyq0\n5ZS3hJu0oogA9bu2pcFYOcfGnYKjLDBDiRwJdASzlMhTD0d0WmfBFrZ6X3yjzTyCZerMxzwMv8Lp\n4DSH9GlKtFaNUycowuMltKpB1I5gNE3qA1UVKV/TsWMqIM4KizWB4oYkiNDCRQ+JpBni/ByP8DwT\nTFAggsm9jLCdfl6NUmcdl7DWpvrQoUPs37//ljz+LS8gpJTLsEYy1I3hXlRxvnjrjujWYD8jHGYK\n5yqXgEQ4szPQQiLUzS8SAsHdjLCbIeYp0cIlQwLFKNDXPLlSRHmILYyQ5ZucZpHadZ9HdQ50+kmR\nI0FAwCAZ8jSohha9PSQZIMM0JQ4ziYfEQBDF6CzRak6vEi0jGJ2dytWwl2HOs0SJZseQp10kqYwP\neV2pafvYNZQMdCcD6Gj0k+Yg4zzDeUo011RyrHyMIdK8jZ2M0X3bxxegSIiv5uLYbm/nSLABk4th\ncuparzKCHlqWayjnUR8DjSwxGmGcuYFOC5cEERapsESN/tuclPlKIRBsG05T+NlFWp/pw55U55rc\n0GToR2ps2XQlg7KOzRFmcAnoJUlbaVGmSYb4NaWqi0fBqQq6NhrIusBwDHTHwDEl7hf6ET80D7nV\nfQI9fPwWDnEsEmHeShuXzpRbhLCIMH2dWCwCKY/NI1G8MFHWxWeOEktUVwm3V5bVC3vHqfd1YVUa\nOGm1QXKiBi/s72b2wZ0s6mdXnYWrxyaSIOIjHUm9v0pg+AhXAwGG1PFD8q8RfgeVF40XqqxUNzOK\nSRSTt62rLd6wuGMcCCHE/cBB4Bso6eaDwB8CfyWlvHU9lluEHlLsZYjnmVrz36cokCFOM7wwp26B\ntNNAZ8MrYLLHsdjBIKN08w+8zGkW1iQUtv0kBIIYFnEi6GjcxTCb6FlzgVPhSjBNmR4SFGlQpknb\n5a6HJL2kqNJac1e3Ev2keSe7+C7nKFLvLHJqcQxwV82Mr9y5tXdzAhgkwwNs6oyLBCqFcYgMZ1hg\nngoByv1wG/1sXFEo3IldTjcJ4pjUruDmXx0rXJaJYqLCvwIsTPYzynb6Oc8STVxiRDjHEgtUOmMl\nUAZhAmVJ7COJYYYpq0oFokLW7FtCwL0dGKeH0t1NJnfO0LxggITsRsG90eEOUXcl5qlQoE4MkyIN\nkkSIhDLYKQpso/+qzxXvVpkTbgMihk6kFKPRW0PYJkZLI+pEqYcqGA1l9iURtMK+nFITadcsXl8t\nNCAlokQNk6ihCJIBASeYYzrcdNidIdXaaHanOP7BB3nTn3yRVjaBE4+w/OBO8jtHKAznrl3CC8AK\n8FsafjbsRroaIhaoyPJQ4guExlbKfCtJBBuXzQwSZd22+o2OO0mitIEPA78FRIALwP8FfOIOHtNV\nIRDXdM8r0CRPlQDYSl9Hd30nEMfiA9zLBAVOMM8i5dDK1mATvWyllxgWPpI6NgJBD0mS12A+CwQ7\nGKQcXibjWJRCxniOOBvo6uxqB25gB7uJHkbJhtLJgBo2MxQp0SCCQQSTBSosUsXDR+cSL0NHJ47F\nHoY4yMYr3CMFgiG6GOL1lxM8TJYhupiiQAPnumMWPRR5+uFoKQjHPC4+Dh4bGWaUbkZXFJqb6OHz\nHKYSDp7aS0iKKDkS1LDDpU4ZGqWJhc8jXrcXdROdA4yx0eqmvL2JiU4fqTXTSh08jjAT8pZkqHpQ\nSasWRuhmot5PiaRCi3zYsesmweADUbI7JUsvCRAasSCJWwe3JIm9u4gccEMppAyfzw8L2nb3zMdH\nOU62uQ+vltqsI9jFEG2V1ga6IDx+HY0lqlSxWaSKHnIvVgtG14CmMfnIHsy6zaZ/fIlGd4q5fVuo\n96RxstcOU0OE9topT5nJmRItIrEsDalJDMBDdPptPhILQZoom+ll52WZPut4Y+KOFRBSyheBq0wv\nX5+orWjNt3fBK/kQNWweYBOb6b3jMzwNjXF6biC06MZ5GkNkuJcRTrNADZskFk6oqV+mThSTnQzQ\nfYNMfgOdgRVGNjsvkxA2cJikQJ4aBhpxIiSwSGC9arnsnUIMk7ezne9wjnMsXZOvYkC4d2sXTorB\nr6FjYbCLQTat8fmOkuP93MP3OM8cFQRqzPMwmynS5EWmmKNMgCRLjC5iFGkwQJre66Rw3kloCPpI\nXZdbdJJ5pih0bKYVh8fjOPNY6AyR4UUmEQgukGeCAg5+hzSsRcD/gwTOH49SOpzBuBBHN9NsvNfD\n+efnKKD4Dg0clJ+ZKhQSRKiH6bUWOq2QC3SrlFE54ozTw7NcxCXoFHvKplqnHUufwKIS8hauB2ka\nnP3Bg5x7zwGE7yMtS8lDbwCaJojngEDD1jw0UxLHooVDCx8DQY4kHj4ZYhxgjAHSt9x4bx13Dnda\nxvmGwkqTnavxEDaQvaKF38DBJyCKQZ46BeqUaXbMUrIkGCN3wxK6OwWBYJweNpClho0W7nQKNBAI\nekmSJnrLiic1krl1Bl2vF3ST5H3s5ThzfJszLF2Fr2KGpl1KsquTJIKJToooBxm/ZnG4gRw/Qq5T\n3rY/k17SjJHjGHNMUcTDxyNghCx72fCGLMpWQiLDeHsv/P/VcPCZoUiBOl4oIV5rlCT22Gi/X0c+\nl6F3vo+He0eJvKXGE4kyCSx0dNyw6Gg/RjvEyqQdgK32/zdi+X09BEjOsYSFQUDARfJoCKJYpIiw\nnf5O8RLBJI5FA6dj+nY9SENHGu1+140drYbAFRJNF6EySODiAYIIBlniDJBmiC620tfhia3jnw7W\nC4hXgN0M8WWO4a7iVysIlJPhE7xEkmjoQa9YzcvU8UK5YjS8vFRphdLPeJiyWOI+Nt60cuO1hBlm\nK7TR/Tretb5eoSHYTj9F6pxgnhKNzsU+jsXDbCFFFJ+AJi6LVAkI6CbJJnpumOi4VjEXwWQfo+xm\nkGq4e72Vhd+dRh0bfwUx9/LlUKCFgkbZUf5oiCtyZ2I5sB/LU6BEhizlcCwRD6nMEUxaKxQe7Q5l\nQNsESoaDokvSzsvJwe3ORfOq9GwFDY1l6rzIJBVaoTxSkMBlgDRb6WOKEhfId8ixaWJUwjFje4xw\nK6FcLmErA+xhiGXqzFEhisE2+hkkHZrPvbGL0nVcHesFxCuAhcE+RnmeiStOxrZUqUYLA4MIOgXq\n4c5EdObXNVpYmCSJoCE6BMQGDqeY7zDG1/FPH2quv5Eu4kxSoB5alN/DyBXdqPYi1f4u3QpEMIm8\nTjkPNwsRztnnQ9+WyzkI6nd17q7caV9pI65gouPgMUmBcXowV6hWkkQw0Ciu4Bu0F2o//P92LyKC\ngUAjCmFOjRpB9JGiGRYhKnfiynHHJXWSoEKr83gB7c7EIqPkwtC7NPOUiaBTw+78neK3GCSJkO9Y\nqKvU3TRR3LCL0kuKaYo3JAVvG18tUOUA5mtqLLaO1wfWC4hXiLezHZeAMyEPoG3Es1K+qBPQ4FJI\nThuKuKXRwiWOSZQIdWyaOCSJUqRBE3dNYtg6/mkihsldDLOLwbD9vbaCpe1Auo7rYxeDnCePH5YK\nV3Yg1H/bi32bUHnlfS5BR9BNgo10c5oFZPhZuSGBMoFJ8zLNU9tFdIAUfaSJYDAZkmcFl5wq00Sp\nYRPBwEKukl22i4VoGJgXIENvFlVSmiEp9DQLbKefNzHOBZa0ImgAACAASURBVJaYpkSNFiYG3STo\nJclIaOT2IpOcYoEEEWKYtPBoYLOTAfb8/+y9d5xcd3nv/z5l+uzO9iKtVl1Ws5qRZRu5AsbEEDCQ\nAAEHyC8BUiDwI7nhksuLlhtyE0rwhVCDwQ6xCd242wFXuUiWbDWrl+19Z3b6nHb/eM7ZmV1tkyy5\n6Xz8Gu/ulHO+c0a7z+f7PJ/n8zCf/fSyjSMMumUeD6GK9+tlduKESZLncY7yDl48Xx4fLw/4BOI0\nEUDnetZymCbuYDem+0cjWyGwnDwp0fszVrnfqaxNek6PiptK9XH+QVoufZwNXEALxxlyh9KdmikM\noI23CBtT/HYC7gAqMUwLExgXRl/DBWionGSYIuZ4+WeM3LQtkw4O1YTpZJRR93kqYkcvOiiHOCEy\nFAkTGBd9et1RMt+m5K5o4t8H7++FZyoWIcBq5s3o5LiW+agodDDKGAWCaKyihVW0oqCwmlYaiNPN\nKCcZ4QgDrgGZRpJ8hembeL84OPQxxhiFl7T7zMeLD59AnAEUFDf74Iz/AZoNKmJR6ym2MxQpYBBw\nfwEzFFhK48u2jc6Hj9OG44xPdXwxoaFyHWupJcYuOl03V/k91dxsoTh5lojguMqGib/FnvZERWU1\nreMt3BGCvJHVpMiTx0BH4W72MTLDdNR+MgxNmvKpoJCjhO76RYg/SJAqwmQpYruuryH08em/ljuV\n1RsCJlkp2Xw0nUbpM4DGehawgmbXOyToiiDLa2ummmaq2Ug7D/I8++kbL7VYbiY1Oj47xjPpPne+\nFz5envAJxBnAwOIkI3jDjmbDZH97L7XpdYsfcmuYy2g6J+v14eNFxfPPw4MPwsGDUFcHV10lEx71\nF+/PjYbKZSxlI+30kHQNyxTyWBhYrh5ARKr9jJEiR8idWNlPanzUugIcoh8Dk2tZTcHVQ6TIEyNI\nG7UTgu90mNwL4R3ba70MoXMZS1lNy3gpS8Z6Fxke6+MJ/SQDIQNTszEoorvkIk2JBBHW0QbAWBf0\nPAPDR6AwAuEE1K+AtksgPqmhSYjDzOVSBYWtLEdD45hrUAYywK6KEA4yYXQeCT/7cB7CJxBngGGy\nGG76krPg3Gfj0M0InYy8bAca+fAxJ+zZAzfdBF1dMDYGpRLs2AG9vfDe977oy4m45QdonPY5FzJ/\n/PskWf6dx8dnvZSwKJFnF130kqKZhJs51DCx6WCEWqJn1KrpPd9GCM8S6tEtoLML+voI7d1L4amH\nOHTdcmqxqFUD9K1tY3BxE45uo9oKDalatvTXUR8aoqdb55lbwvTvESJhmxCugZpFcOJ3sPmvoH75\naS4SuYZXs4L1tLGNoxxhwB09Xu5K2cJiX/x9HsInEGcAL30YI0SSwlk5poHDYxzhApoJ+mWMaWG5\nieCpWsMKGDxHF4cZIEuRBBHWMI/VtL7iWslsHIoY5CiRx8Bw5whIG7BMPZ1OcPmSIZuFr38dfvUr\nGB2VEoaqQjAIPT1w5ZXQ1vZSr3JapMjznzxNdppNQR9pCpisYd74v6dBMvQyeMbJewWHWqLUmDr2\nj38IP7gNOjshkwHbputtF9Py39uZt+MI2A6qYWAGAxSdKHYqTmZwJcetDRwJVdHFJaRpo2REQFEI\n14BVlI8h1QXP/xxe+3dnVlVSXBHp9azlAH0coJ8cJeqJsZ62l6Xrq49zD59AnAHqiBInRIrcWT3u\nKHk6SLKMxvFech111tkSr1SMUSBFnigBaonOOAWykxHuZR9DZHAQy+HXcQHL3JkGKfLcz36OMoTp\nzn0YJksPSQZIczUXvKwFqhkK9DFGCZMsBoOk6XZFbvkKy2tvbkUL1WxgASvdIWIvKSwLvvMd+OpX\n4ejRiY/ZNuTzsG8ffP/78LnPvSRLnAv20s3ILL/TBQzyGMTd9H2eIknyBNEpnsEAvQAai2ig9fu3\nEf3KT6BogGkKGTMMYse6qSmYlOIRgqNjVB/pI5QrUM5fPE6ROD2Zi4hwmF38KSVtAXpYoTgGagAy\n3dB2GQwfguwAxKcfAzIrRBMys0jTx/kDn0CcAUIEWEnLuH/+2YLjljJC6BxhgIxr8rOQOpbT9Koh\nEv2kuIPdDJBxxWIqjcS5ihUso+mUVGgHw/yYpyf0yPeT5ic8w+tZxUUsYDfddDCCgz0uTLNxyGGw\nneM8Ty8OUEuUDbSxmtazPrbaxmGYDDlKVBOmdo7Ooj0k2UUnWYpkKZFyzX8s1ylx8jmylOghOd75\ns2amP+aFAtx8M2zfLsF83TrYuhU2bJDMwJmiWITBQQl2N90E3/2uBL3JcNxAZ5pw770vWwLh6Zpm\nyyR4mgWQTom0m4E80xZbBYVSfzftv3gYzbRgwQI4dgyiUUilaNx7kt7XrEC1LKo7hgjkyt1eXi9H\nkCwNHMEgxhpu52nn49hWENVRsEtQylHmG77O0cdZhE8gzhCLqCeIzr/z+Fk7poXDbrrpJDk+iEdD\nJUmOHCU20f6KrDM6yPRIDYWTjPATtk8YI2Vi08cY97GfADqLJk0gvY/94+RBdQ25QK7XA+znIH3j\nf9htJC1caepTwmGUHBoqaQoMkGaYLFew/AVfTxub7ZxkJx2MksNyCUyEAIto4GpWkJhB11LEZDdd\nFDCpJ06GYdcVceZJipZb4jhI/4TuHasku0zbcog/cCv6p/8GhoeFPKgqhEKwahW8+93w538O8dN0\nEc1k4Je/hFtuEZ2D48DJk0IoZsPRo5KNiEw/lO6lgoK0bnotitM9Bxgn8iaWO3lTGX/8dOKz4h4j\n3J+kejiLEonKZ6QoctM0wqkcimWBbaOniyjjBVSZzypjqyzCjOKg0MR+qulmzFmMZbiHCUJuGOa9\nBmIvIPvgw8dk+ATiDKGgMJ8a6okyfBZLGaPkSVEggDo+RCnijnBeSuPLSmTpuP/lMVDcdXoB2RuE\ndYA+BslgYBEjwPA0MygdIEmevXTTTu14dqCIwdD46ORTffptcG2enfH2Ns95z6k4j4pClKA7xdJi\nP72sYR4NM9hwG257X9CdKWhhM0YBDYUAKrvo4kmOTRiyJq+zMSlywJ3J8Pusn7Y915uiWE8ME5sS\nlutBoLhjtKaGpwWRrEWRkBOg4zHY9X04+Ri09N3LG/P/iypnFFUBRXWzLaWSBPJ774UVK+Ctb532\nHKee1JIyxA9+AH19cl8mI1mOucA04emnRQvxMoOOxlIaXaOnqTUQIXS3zbIwPmdCWkKV8bk2s8Ej\nId6/KR2NC7V2gpE4jPULgaiqgqEh0DS0YpHm57sZWejNPfEGuysT7K8UbFQsVAx0pYDjgFUAPSQE\nItEGq9/5knTV+ngVwycQLxCXs5xf8dxZPaY3QTCCjolDjiJ97i795UAgkmS5hSdIVtjdBlBYSxuv\nZQn9pHmMowwwNr6bU1FIMXHewGTYOBxnkJzrzAkSjMuFhqk7zR3XmMtxKYPqBt/KM3kpZilvmOQx\n6CU1JYEYJM3d7KOPJCY2IfTx0dEKMsekn/SMNW8H2V12kaSL0WlbdL3P2hsGLWuf3VBMdfegQbed\nr+dJk22fy9PxTBinYHCh9UM0p0SK+cSdQQIBC8Wxy5qEZBLuuw82b4aWFglcs+HgQfjtb2FgQMhA\nIDD3iKQo0NwMu3e/LAkEwEpa6GKUg/RTmPTZRt2M0pUsZ4wCaYpECJAkx0H6MLDcMdozzbOQiaoR\nAoTQyGOylEbalq2EjRvh7rvl2lZXQzotJaFAgPhginAyg2V7NlLevxnHpckqlktQ80o9dl0TAUNB\n0aBuMVz0EVhx/altnD58vFD4BOIFYjWtdDHKTjpmCI1nCgUdBQsFA4vkWRZtnglS5LiJh06538Bh\nF50MMkYJmxEyE1LwngHNbBilwGEG2Eg7IH+4xZ8/OeX1VSr+72G68cmWqyuwsNHcYUSTkabArTxJ\n1h3VDOLyd8LVpiQIn2IKNB1sIE+JXsYmEIhRcvS7gskAGgFUspSIEyJBhCHSeHMUprtm3oyD1t5m\nsrtHeP6LRxnevRgrp9MQPEKV1QOAQRyDLJqVRdMq9Ah9ffDQQ5DLwdKl8I53wOrVM7+h7m55XS4n\nQU7XhRjk5vDvsrER5s2bG1EpFEQHEAzCkiVze81ZQIwQ17GW5TRxyO3kCaHTSoJ51LCQOlRUGisG\n3pmuFfUB+lw3xjzFCtcH1e1eWEg9nYyQd50nDWzaqOFKVkhZ6WMfE9Lw1FPQ3y/XdtUquP56sCz0\nEyew9+zB2ncQzXWpLLtL6OSow1TidFa9kVKwnmgCFl4JW/4KWja8KJfPx3kIn0C8QOhoXMcaFtPA\nNo6SIk/ItcodJX/GmiWvPCDfg45C8GXwcf2EHTM+3kOKALpbQvC0CApz8+sUPMlxltBIgggqKlex\ngp+zy/3jOxExgogtsYKKNj71dDJK2JQm2I0b7KaLBBHaqB2//3ccGBcnTl67hcUwudMmit2MkqdE\nhCDHGWI7J0iSx8Ym6I5eLmFRcJ0JVTQiBIm52Y4SE22IdFSivVUkblvK4LO19D11gIHuxWSMWhQN\nLCVC0Y65O1QbmwCOmA1IBkJRJAuxejXU1EhWoK8PPvUpEfFNh3gcjEmfQSgkgb5Umvo1ug61tXDB\nBfJ1/frpj//cc/CVr8A990gw1TQhEJ/+tGg2XoT8ewj9tLoMdDRW0coymihiEkQljzk+gbeOKPWu\nS2SawvjQtFpiLKSu/Du9fDl84xuwaxccOQL19fC610HMFeIaBsF0mtzXbyH/r98mnO5CdQxMNUwu\nvpDkimsprHgLtYuuoLlKYf5maN8qJQwfPs4VXvqI9CqAisoqWllOE72kSJJHQ+EAfRxmYMKOZK5Q\nUMZ30ioKVURI8NKLz/pIz/i4De4O33P7F5yOwGyYLDs4wSpa6SWFicXlLOUwA3SRHC+DRNyJhBYW\nATS3ndFBg1OC7mQ4wAlGgCNcwwXj47G7SLnrPVVvYbop49N5PxECWNh0kWQ+NTzBMYbIjKezc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MD3bhfGUJtqmMEwSQDotQDMI1FqHeI9imTbbUgkEUG51QNTQ2DFFzy7fIfu2nRKz97oIUKU/c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\nPw7//M+yqw6FRE/gzZu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iG3MM1E2HNZvy+KWoYmZJGaQMdmZgw3M+4rBzK9l8CVEwsH0d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\naAQG3La2feybmfjioTf7r0X7lxDCLjNbCLw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HEMIOpHwUBuB3fw8rbhFRciqIEOA6ljNAiu10jrpepXFfGE4SUyoglFJXAp8E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6jhMazdMb6thSfBhmxtC5cTo9Do37QkT/Mpu3X5vXZ+iawXA0GAFhOGUIEWAlU9nMwdQwLcVO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\nIDWvzwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f203c0a63c8>"
+       "<matplotlib.figure.Figure at 0x7f53a909f978>"
       ]
      },
      "metadata": {},
@@ -1348,7 +1377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
     "collapsed": true
    },
@@ -1366,7 +1395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": true
    },
@@ -1384,7 +1413,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": true
    },
@@ -1402,7 +1431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": true
    },
@@ -1429,7 +1458,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": false
    },
@@ -1441,7 +1470,7 @@
     "with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
     "    y_pred, loss = x_pretty.\\\n",
     "        fully_connected(size=1024, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=num_classes, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -1460,7 +1489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "collapsed": true
    },
@@ -1479,7 +1508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "collapsed": true
    },
@@ -1504,7 +1533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "collapsed": true
    },
@@ -1522,7 +1551,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "collapsed": false
    },
@@ -1540,7 +1569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {
     "collapsed": true
    },
@@ -1572,7 +1601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "collapsed": true
    },
@@ -1597,13 +1626,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -1624,7 +1653,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "collapsed": true
    },
@@ -1642,7 +1671,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "collapsed": true
    },
@@ -1681,7 +1710,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {
     "collapsed": true
    },
@@ -1752,7 +1781,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false
    },
@@ -1807,7 +1836,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "collapsed": true
    },
@@ -1850,7 +1879,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {
     "collapsed": true
    },
@@ -1905,7 +1934,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 66,
    "metadata": {
     "collapsed": true
    },
@@ -1928,7 +1957,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 67,
    "metadata": {
     "collapsed": true
    },
@@ -1962,7 +1991,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 68,
    "metadata": {
     "collapsed": true
    },
@@ -2019,7 +2048,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 69,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -2029,11 +2058,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 25.8% (137 / 530)\n",
+      "Accuracy on Test-Set: 30.0% (159 / 530)\n",
       "Confusion Matrix:\n",
-      "[ 8 73 70] (0) forky\n",
-      "[10 39 88] (1) knifey\n",
-      "[56 96 90] (2) spoony\n",
+      "[151   0   0] (0) forky\n",
+      "[122   3  12] (1) knifey\n",
+      "[237   0   5] (2) spoony\n",
       " (0) (1) (2)\n"
      ]
     }
@@ -2059,7 +2088,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 70,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2071,15 +2100,15 @@
      "text": [
       "Global Step:    100, Training Batch Accuracy:  95.3%\n",
       "Global Step:    200, Training Batch Accuracy:  96.9%\n",
-      "Global Step:    300, Training Batch Accuracy:  96.9%\n",
-      "Global Step:    400, Training Batch Accuracy:  98.4%\n",
+      "Global Step:    300, Training Batch Accuracy:  98.4%\n",
+      "Global Step:    400, Training Batch Accuracy: 100.0%\n",
       "Global Step:    500, Training Batch Accuracy: 100.0%\n",
       "Global Step:    600, Training Batch Accuracy: 100.0%\n",
       "Global Step:    700, Training Batch Accuracy: 100.0%\n",
       "Global Step:    800, Training Batch Accuracy: 100.0%\n",
       "Global Step:    900, Training Batch Accuracy: 100.0%\n",
       "Global Step:   1000, Training Batch Accuracy: 100.0%\n",
-      "Time usage: 0:00:27\n"
+      "Time usage: 0:00:02\n"
      ]
     }
    ],
@@ -2089,7 +2118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 71,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -2099,15 +2128,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 70.4% (373 / 530)\n",
+      "Accuracy on Test-Set: 71.3% (378 / 530)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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lcAdDKEEP5XqZSqmKQ1QoNdo4lf4aytM0N3mMTk1FxkrIPcDE4CRnz5zH6VBw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\n3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sxmM0ajwtDQAH/+Fx9hemaGyfFJLGYLVouVYDBIJBxheGSEkZFRnA4vd911D15PCzqh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uR7fbxW63o6oqmUyGdruN2WLG5XLR7XZZWFjA6/NilWXqSg2bzUYs4aGnN9nZ20RtdQiH+2m3\nTFitMsPDw1jtVgYGB9A6bSwWC91ag2cvXMSkijhFHxHnIIWtFo39FmpJ5frH17k5f5OOrFHVS1gx\nsTa/yPUPr1BIZviLL/4ZAZebgC/GhfPPMjY6TbPeI5et8t47H+NwOrFYzNSUGmpL5eWXX0aSJXzW\nABsrW/jkAKJqxqRZsHRkUJok72+yvblFTwBnyEfPacXtcmExP674HiVMNhmP30chm+Mr//nL7C7f\nRakZ8q+jR48agbKLC2QyRoXearV47713qVQqnDx5kuGRYSMvb2eb3/7t3+Y3f/M36XY7uFxO3Ac+\nyhubG4eku9HxMT744H0kyXBheRCibDb/uFD8QQGjdTQcDgfNVpNPfepT9Pf3o2kalUqFa9eM9Ihc\nLoff7+f555/nyQtP4vf5DpPcy+UyxVKRTreLzWZD0zRe+tRL9Ho96o0GnV4XySKhYyTKi6JILpfD\nbrfT6XRwPkTy1UO9+CrlqnGAqG0GBgboaJ3DSkjA0DEFg0EC/gAWiyEuj4Qj7Gf2GR0ZxWZzsL+9\nx/2lVUaGhun1dMJ9cWxeN7LHidXtJLOfwSyY0Ftt1EoNTdVot9t0O10EBMO6x+XG6qjxz37nf8Dj\nEnnx0mnaqk6r2aBQKCKKIqViCVVVKRaKpJJJlpaXiESi7O9nOH78BMFggHq9QaVipHXfvnWbIxNH\niEQinL5wCqvNarQFWi2jFXDQGvjRFPYHLc92u43abtPpPHa/f5TI5XJ43J6fqMplWcbn8+FwOEgm\nk+zv7+M80ORpmkan00G2ygQCQRCaFAopBAEcThdKpcXczFlSyZRhZdfT2dnawSpbjcdRr0s5k0fq\nmPmD/+OP0Bsyb3/7GqcnniC3U6AvliCVSbG2tUpDrBFx+xFaHYION6V0ls88/yloadCTmZyYQ+9K\nqE0dehJ2q5fLl9/ig/ffJxAMYLFYCAQCjI+PMTs2R1+gn9df+yY/+OZlPn77KkvXl/nwb17n7//j\nl/jy7/8BcZePgMNN0OEiu5+lXC4/6i36uUa6kKPeu6emrwAAIABJREFUajI9OUWtUELuCUTCEdKp\nNCaTiVwuR1+i7zCc9c033+T+/ftks1ksFgvLS8uggyzLvPP2O/zRH/0Ru7u7bG1sYTaZEUUjbFvv\n6YSCIcwmE1arjVarhdPpJBwOk0qnkCQZ8UfOMavVSiKWQJZksvv7iILIn/zJn+D1elGUGq+99hov\nvfQSjXqDSrnC/J15vvKVr3D146usrq6ysbFJKpUyAr9Fg7XZ39/PhQsX+MN//4d0Ol1AwGY1yCwC\nhqmE2+Xm9KnTOBwORoZHcNgenhzsoV58ksVCt9vFHwhQPkhQ7x3UyYIg4PP5CPj9VCpl7ty5g47O\n9s42uVyOwaFBbFaZf/qrv45SKrO7tc1Oao+eIFBtNkjms9jdLmwOJyLQbbVplKtsbG4wNTXF1vYW\ne3t7FAoFakqNT5yfIxTy8sYbt1HqAl/4/G+R3k8hyzLRSAxJMkyrZVmiWCryCy9/mps3bhCJRLl9\n8yZttc34+DjDw8MUigUsksT+viFefuH5F5AshrvHAybSg/GdIfwUAOHAb659aBqraY9jiR4lQsEQ\nlaqR5GGIZEPGpSbLeDwexsfHEQQBi9mMw+FAFE20223GxsaQJJlcNguCRqG4T0/vYpPtPHvpJWaP\nnsTtdnPp0iVWV1fY3t1CkiREkwmh26WSL0AHRqPjdJsiI4lJipki/ZEBRgbHeO6FS/gjPmweGzev\nXmdnY5NYKExmL0W9UqXTUIknBlCqDeLxAfz+EH2JQcZHJ+j1emxtbR1qBUPBEGOjRxB7ImFfmOX5\nZbpqh+31bd59+32cjQ79Ng8TQ8Ps3l5h684ymwurWO32wzibx3g0mDg6RbvTIZNKMzY4gt/uoq2p\nxOIx8rk8kiyTTCWJhCMsLy0xNDTEs88+S7lUYmF+AZMoUqvXGB4aptfr8elPfxq9Z3gEN5oN4rE4\nFy5cYHBokFA4xNraGs988pPYbXY0rU0oHCKVTB5yFwAQBCRJIhyNIFllcoU8JpOJixefNnyUXYYD\n11tvvYXd4cDhcKCjc3RqGqvVitPlJBQK0tfX/2OjH1mWWV1ZIXDg1QlgtdlIJpOk0ilS6RR3795F\nEATu3b3H1vYW9ebP6oyvsk98KMri3Tt0zBq72W3cmoBebbB08zY6kC7mubefZDgaRO80QdbJtAus\nKnvcqmyR7Cn0fDI9m4jP48QtmemWSohlhdS9eyRiIWrdBnLcQ8MtcvTUcapqk4HxUUS7jC6bMTtt\nLCS3CYwLfO3N/42rV94kJIaINC7itdfZXL2K3Ouyu7yHWHfzO7/8b/joxlWOP/cUKVuXckCGoIv+\noQHcI8cJugeJdp1kl1cYnetnvrWCCysOZJy6lW5ZpVNp0VPa6EKLLk16epOe3qLZKlOuZGlqNVSt\n8TCX+zF+SnS1Ll6Xl52NHcKBMD2th2S3YXM5cft9pLL7NDSV9d0dlhcWCEfCWFx23rz2AfuiSsVj\nJr2/R6PbIDQSIzg9gGkkQNbVJSXuUTb32N6HbmcAUydExJ3AdqSP66l72Pp8iBYBt8dMs54hXWky\ndfIEseEo7oDE6ISP6dkA9kmddgi0gIcXfutzOCf9ZO2byLYobTo4gz0K9S1avTZma4hP/dLn2d8r\ncP/mPAGvjYyQwXzGg2yz0dc3gAMPLtWPrx4lUu+ntOVGsvbRdAp8eP8jzj5xiieGjtNsZFhfX3jU\nW/RzjdvXP6JnUtmu7vGdxXfpjbiwmSRsFgkzAkKny2A8gajrnP3kJ5k5c4bdXA53JEJLAEcoiGoS\nuX3/Ltm6Qk3vYgsGUC0mPLE4qWKJmtIit7PPrbeu4G5Z2Be2OPXsOQRLGK3uRWp7qOwW6Ig2uiYV\ns5ijWbzP2dExrEXwNDJoqTVEJY+l28EsSkSjg8QDMYb7htB0geDgILOXLpLW21hsAZI5hUbHRLWp\n448MUu+YWf7wDplMkZZZwhkIY26L+BoWKp0aVp8dT9QHdpG//ebX0G0CugV8oZ9RVqe5J2DuCrhl\nO0q+RLepEg5HKJaK+AMBTKKJcCjMkfEjPPfyS/QPD1NvNDgydoTNe/dxmmUK1RIjR8bJV0osrq3Q\n1NokhgaYnZ1FFIxU83w+j2yR6XY6LC0u4ff7MZvMCAisrKxQrVTZW9/C1IWx4RH+5//191jbWOSF\nzzyD3hzh6XNf4NyZT0NPJhQMsLxyg3wux+XLl9nd2UFRFHxeH3a7A7fdQs/UodyuUWk0qeaqxGxh\nqjWFdruNaBIRTSKdTgdFUYx0dn48iV0UBUwmkU73ccX3KLG9vUUoGMTtcaO1tUNPQVkyTAbsNjse\nt4dgMMDkkQmq1SoBf4Djc8cIh0KIgoBsceB2+QmHoricTpRKEb2rMjszxbvvvcXc3BS3bl8DoYtV\nNiHogiHK1QFdQJJlbDY7I6N9tNo1JiYm8Hn9oFsoFurEYnGmJ6c5f/48R6enUSpVnHYnotCjrTao\nVAqEQj7a7Sbr9+8yPTVNp9vlypUr/P6//be88fobJHf2mJya5I03voU/4AcOrPME8HjcRCJhnnv2\nOT7365/jBz94i/fffx904VA4/BiPBpaDPNBarca/+pf/kkqpQl9/P+12m6XlJbweL2t371Kv17l+\n7TrnPvEJTp8+gyiInD59GqWqkM/nCQdDRCNR0qk0HrcHj9NFqVhicnKSSCTCzs4OSk0xLPjS++Tz\nBZ69dInlpSUSfQncbvchUx0EotEof/3Xf029XmdmZpZjx04gy1YGBwcNIXyhwN7mNtc/voZdtlLY\nz2K3yHRbGuFwmE5bQ5ZkbDYb6NBWVSyYsBxcP06Pm2ZHw+5x4XV7UKoKek9neGiYl158Ca2tcfz4\ncToPsWP2cNMZdBC7PeySTCVfoNNUWV5ZZmhwiEQ8QalcYnNrk1u3bvKfv/pX7JcKnDp9GpvVis/u\nopTeB8lCuVVHtErEhwZodNvMr62wsrJCNBYll80xMDBAoVhgZmYWr9fL7s6uQSQRYGhoiIpSwdIz\nYekBvTanz87yl1//T7xz7ds8e+F3qBbc7Kc0Bvon2NrZoKJkOXfuPB6Ph+PHjnPmzBlm52YB2E2u\no5k0fIMxcjWFak4hbglQLpdpt9uHF1y73aZarf7YejxoF+gYB8/D3LjH+OlhtztQ1TaVSoWNzQ0q\n1cohc8xqtbKxuYHb5eb8ufOMjo8ZAceRMFvbW6gtFafDyfDQNJMTxzl+4iTTM5N4fFZifT6Ozo7z\nL/6732Tq6Chen42+viCdbgNd+CE7ThAEI15FklDq+2jdBl/96l8RCIZBlygXVeNQUqqYRBGfz8/E\n5ATFYpFUZpPNrVWWl+9gtZkIhd2MjiWo1+uEQkGOzR3jueeeY2xsFJPZzGuvvYbVamVvd+/HGHrd\nTpf19XUymTR//Md/TL1e48tf/guisSjhcPhRbMtjHKA/0YfL5WJycpLXX3+dozNHuX//HltbW+zs\n7Bz6ZM7Pz+Nyu5BlmYmJI8TiMd544w1sNhtzc3NsbW9hNptxOp28dfktUpk0jWYDh8PB/Pw8w8PD\nOBzOgwDiHt/5zrd57733mZmZIZ1KU6vV6PV+yEK32Wy4XW5OnT7Fq6++yrFjs2xsrHP58mXmjs3x\n4ksvMdY/SHZnD0HtsHD9FtV8kd31DUKh4GHautlszBkbzQZSV8fcBYsgsrK6iifkZ3H9Lkq9xviR\ncfaSe6htIzZrYHDgoB378DgSD/Xia1ZrhD0+TFoPu0ki4HCjdTRK5RJOlxOPx0Ov10NVVUJDfZSa\nNZRWg5tXrxHx+LGoXYqtGorWIlerUGgoZCpFdKuFzc1NFhYWGB4ZRtM0wxkjn+P06dOYzCbUtkp/\nfz/j4+M0Gg0mE6PoqkYmtYPJ2mVoMsr1++/zpS99mampSZ566ily2SxW2YrL5WJra4toNMp+dp9k\nMsnu7i7r6+u88k8uMTg5gGJqY3G78cg+WhsKDocDl8tFs9mkXq9Tr9dptVrs7u3h9XoBDvVhvW6X\nzIEY8zEeHR58M61WC/vBTEtRFD786EMWlxYZHBw8ZK7duX0bl8vFjRs3DvZ1l0azwUcfzLO3s4/N\naqdULmCRQanv8+//7z/iP/zHP2Rja5lLz50nnd1GF1vGt9FoUKvXEBDQ2hqhUJit7RX+/M//AydO\nzfHtN77L7s4+99Z2uXXrJsVyyTAcrtcIhkJcuPgUWrfGXnqDZrvMnYWr1FtFYn1+XC4Xp06don9w\nALfbjdPpYmpqkr3dXWo1BdEkEo1Fqdfrhrdss4HNZsPn82O3G3PBi09/kmKxwPrG+qPeop9rvPX2\nZWw2G91ul1gsxt//w9+TSqbodrvMzRkhwRaLhbNPPMHo2Bh37tyhUCiwu7trVFMCOJ1OQqEQG5sb\nFItFY+am6/gDAfb2dilXysbsWYDNrU08Hg+JRIJms4HW0SiXy8iyjN1uP/DTtDEzM0MwFCQSieD1\nePB4vTz55AVMJpHmQcC43BPwO1z47E6mR8ep5gr4bA6UWg2P10M4HOKXf/mX2djcoNvtUtpNE3S6\nSe7s0epopEp5VEngyJFxSqUSkUgEp9PJxOQE9XrdCCxwu/5by/dT4aFefB6rjcp+nlqhhJIrEPUa\n7U23y01NqRktJVlmd3eXakdFcjno6TrxSJR8Mo3TJNEVBcxWK3aPi7mTxxmfmqRvaIAj40fodDrc\nvHGTcDiMKIjUajXeefsdrLKV7e1tioUi6MYB162phL1+dnY26B+KsJ5ewt9nx+HL8NH1r/O1v/si\nO8l7DA+PQlfCbrMRDAQZHh5mf38fv9/P7du3uX7tfVxBB/f2dxibmWEgPEhE9NJSjQ23Wq0/5tkZ\niURot9vIsowoimiaZrRAD1sHj/HIoHPIKLNarfQl+vD7/JhMJiqVCpubm8iSUQGm0kZStMft4amn\nnmJycpJgIMjI0FGuXb3Ne+98QE2psLm1RqWa4ZVXLtLTW/zd3/0Nt29fQxDa2Owi1XIVu82Goiig\ng9/nY25ujoGhMGfPGokh58+dp6eZ8bpjzM7MMj19lKMzR3G53LhdbtwuD/fuLSMIGr1eA7vdhCho\ntFQF6cALVpYkpIOwTrPZzJNPXiAUCpFIJEgmjZQTt9vQ+q2vr2OxWBgZHuWzn/0sJ0+cRFUN44XH\neHSYnZnBKlvp6+ujUq4wNDCEP+CnfWD+4XK5CfgDvPDCCyzcmeejjz5ib3ePYrHI1NQUN27cYHl5\nmS984Qs/Zp4viiLfeuMN7t+/z/LyMvfu3j00UrfKMvFYnNnZWSSLZOjmZJl2u33443A4kGWZyclJ\nLLrhdTs1NYnb5aGQL3D16sdU80V+8Rc+Q3U/T9DhYe/eBienjfGUrsPS4hK1Wo3JiUlcLhd79zYw\nd3VEHXaTe7z78UeU1SZKRUFrawgI1Gt17q7dJbmXpKN1sP+ssjobjSaD/f0EvX7Onf0E1VKJdCaD\nUq+xuraK1tEYGBhgoL+fl1/9DJVaFYfTgdZu0x+NU9rPoepdTFYJh9fLve0tlu7d5fr8Hbq97oEs\nQOXNN9/kxs0bbGxscO/+Pe7eu4umaahtlcx+hsWlJdySjU5L5ekLT3JvawVv0EliLMbcEw7CcZW+\nYQfHT0zyzjvv4fXEODozjdfnodlscerUKT766ArRaAxQUfU2wb4oDp8XUTfRKjRQVfWQ6nsoYBcE\ngoEArVYLSZIQBAG13aZSqRoOdI8vvkeKB/FDD1LIdV3H5rATTySYOTqD2WxGlmTW76/jcjpxOg35\nzMqqEeOCAP5AmCfOPInD6aJSLbGxsUqlmqevP8ZLLz7P7/3e/4jHYyfRF6PTaVOqlLFarZTLJSPF\n2utlbm4Ou9OMqjX4zpvfZnl1lXfe/ZBux0S5UqJSKlGpVKlWqwdRXgr31pfQ0ej0NKwOCcQuLVUx\ncgXzRrbgA19YSZa4+NRFAv4g8VicySOTTE1OIiBglaycOH4cqyxjMoskk0mCwQBen4df+qXPPuot\n+rlGMBAkm8syODhItWrM90LBEFq7jVWyUqmUCQSDfP/7P+DW7Vv4AwG2trcYHR3F4/Ecmll/5Stf\n4ej0DPBDlrkgity9e4+xsTEikQiSJFEpV/AH/ejoFPJFwyUlb3xPDyRYqqqyvLzM8MgI5XKFertC\nsVjA6/XS39/H8PAQ42NHkAQTizfvIIlmlEqFkD+E02bn/JPn2c9kcLlciIKA86CL0q03uX3tOvFo\nlJ29XXzBIMVmjXLlhyMkt9eDUjcSQ1ptFbvjZ9Sk2lrrcvnjj6l6bSxV8iwXs8StLvRiDV1pIrQ7\n+B0u4qEI1LuYBYl727tk2yppsYOWCGEzdXFaBXLJDSRBo9eq4HfJjA6NUSlV6XV0QoEwHpeXdkvD\nY3ZDXUcttchspKllFRKeGFdKa9xO3cUVDOPq+gk1Y7Cgs7Fc4dq1e6xt7rKws0zsRJgbhQ956ztN\nOu0pLl36At5gmIEjfiLDsLhZZPtugUDDi3mpTmBTYCjrQimWqOQKlPfzWEUzrWoNU0envy9GTSkf\n/mhqA5NJR2lkqTeLD3O5H+OnRLenIUkmqpUSbpeD3d0ttGIel0ng1VdfptoqYw5Zmbp4nCeeOoto\nge37d4na7NS2d4kLFub/4Qq2ioXipkK1KHLi3C/g7T+O/+gE0qiL9c4iaqzKzewC3YifhGBC2Sxz\n/sjLCNjpj/XhS/gY0/3ENCszwX7axQrjIwP0DYS4836KiDtBp14h4LSSurfP3/75W2xdvs2YJQxp\nC0LRQWozQ72WI9vb4m52AYtTIBFOEHcMEDEN8PrSN0jJu6Ste/R/Mk41UKLTp/L99ru88K9epVDT\niIeOsnB3m8mLp/CHz3B34zHr+JHCJuOOhrm+tEB0ZMhwq7LVcR8JEhwLEB8KYhab2KUOjVKWM7OT\n1AoZLD0Vh6mH3qpSqZSQZQs+v5tg0M+5c2fR6TLoi+CTnagNFaffj6c/wWf+2W/QXHMSNvVh6Wm4\nvRZcYS/2QIz9dpJhqwnFXMIU0KmsLRCMubitdLivmSiYJQJjw+wWkrx15XvUuw2WtlaJTw4yfvoo\n9ws77Dbz/Olf/iWZaoV8vcZ/+frXafS6aCYz7YF+lvQWb+4s0AtaCDp6TFt61Ap5/HYrzXKR9cUF\nhiJhNKWCUxLQmspDW+qHevEFI2H6+wcIeHyotTq0O4SjUdweN9MTk2i1JmqlTl8wQmk/j97S8Fgd\nRHxBpkbGUQolBEGgVCohmgz/zHg8YQjUe10mJyeZODIBQLFY5OWXX8ZqsxKPx5mYmDC0WGPjPHPp\nGU4cO4FVNggL2VyWeqNOp9c15ibBIHabnVAoRNAfwO8NcPZCP/c3rvDXf/Ml+hKjpHdVaMfxuHzI\nFhtdAVQ0iq0Ke5XM4fxO62iHLxRJljh16hSNRgNd13G73bjdbjxuD5qm0e12H+ZyP8ZPCfHATEFR\nFMN3s9Egm80SDAT56MOPkA/aPA6bnet3bmNzO5mcOcq97U384RAf37rBi//k02yn9xBNJmaPzlDN\nFbDooDU63F++j0t2YxNtxAJx0Iy2+0BfP6MjI2gH1aaqqiwsrpJK7dNoqDidXiSzjW984x8QRSPX\n0el0cuWjKywsLCBZLBw7PsbVqzdwOjwMDYzicfnpdQQ6KmhqD7XVwejlaghCB6WiEA6FefL8k1y9\ncpW3fnCZVrPFidljpHb2GIgnGOzvw4zA9771Jk5HG6u1/ai36OcaFrOZgf4BHA4H3U6XUrHE1OQU\nyWSSa9euceXKFUrFEsFgmFdf/UVSyRT1ep35+XmUWo10Os1+NovH7cFqteL1eEklUxw/fpyZ6Rku\nPHmBXq/HnTt3SCWT/M3ffBWzxYzT6UBRaijVA6a6KCJLRrszGonS0TrMzs6SbxRQlCrVSoVr165T\nLBZp1BuMjozQ0rvE+/tIpdJoLZWnPnEeh1k2PI0lCbPJjNvlJh6PY7fbWFtb48zpM6ytrXHqxEnc\nLjfZbI6xUUMzm88besG7d+8iiCKiIKK1f0ZZnT2ziMlippDL0VLqHOkfRut1URQFv8uDptTRq3WG\nPGHymX26ahuXbKOSL7C1tk7YY1CvH2Q1mc1m0pk0oWCIjz76iKefNkSTkUiEV155hVu3bhmJDrqO\nx+1BEIxDrZAvsL5xH0mSmZ2d5eTJk3g8bnZ2dkgkEvh9PtLpFNphH1sjmbvC6KSHRqvEf/rTv+Tl\nF36LoPsYHnsQWXKg6aB0W+TbJbaqu7TVH/bAH5BWbDYb7777LvVGnZWVlcMDVlGqhuXPQ2QlPcZP\nDx39xx4kLpcLQRDY2Npgc2uT6alpJElie2eHSrPON7//JrX/h703jZEkvc/8fhGZkfd9VOVVlXVf\nXdV39/QxPQfnpEiREiWNeFNrcleibGNtYA3DEmBgbcD6IMAfCMtewFpBWq5mRI5GPEQOr5nhDGe6\np7unj6o+6r6r8r7vjIjMDH+ImhoJMLDgutdNgP0A1Sg0CgXU+1blm/F/n+f5dWR8/X00ugpGqwVF\nEghGwjjcLi6/+y4//v4PkAtVdpf38Fn91HNN3v3pZbr1Hi6jh1Zb5/FZbVZkVUBFNz3dXVghsZ+n\nXleJRoYoFGp4XP14vV7ev/I+/8u//V/593/175lfmGdmZganI4CAhWKhzuDgGE6Hn15PYn09ydzs\nGTbWt0im9kkkt9lPrtEfDuHz+fF6vezt7TEzM00gEECp1DF2NTJ7Cebf/wBjR6PP5aGcX6NeTjzs\nLfq1Vq1Ww+GwUy6X2dvfY3FpkY2NDU6fOk04FObUqVPY7A6S+/tksxlC4TBjY2MYjUbW19YZGBjg\n+eefx263853vfIet7S1EUaTb7TI7N0uhUDg0BgJcevwSkWiE5eUVHbdWrSDLMqIoYjQaUVSVYDCI\nPxCg2W4jGSUy6TQejwePx02xWKRWqxEfiFPrKPTFIqRyGSYnJqjkCuwsr2Gz2Q7Zq2aL+aDUWnej\nvvzyy0xNTrG+sU6tXsMoGQmFQyzcWeDo3FGd4H7woIMA6gNsvnqgB1+uUiJdyFKvVvFabJjVHtV6\njUAwSDqRQKu1SCyuYWt1MKg9tLZKpyVj0gQ0RaVdqVEoFDCZTASDwQNyuRtZkTl75iyJRAKD0UAs\nFuPu3bvMzExz4cIF1tbXsNltmM1m5hfmyeVzeD1e1I5KKpmko3YolyvMzc2xu7vLYDxOs9VkP5FA\n7XSIRCJU62kajSKf/exLXLr0FG/+7F1czhAzEyfIZiqMT04jOE2k5DyWqJV6vX7YxQlgt9vpdbtc\nuXIFAQFJ0p2o1WoVo1HCaDQ+Mg88ZJlNZjLZDDabDZvNRrGo19dFo1FkWebOnQXGx8dxOZ0IdjNP\nvfg8555+EpPHQbpUIFUpsF/KMTI7zd3Fe3zqE5/kxac+Ri2T49blW9Sydd574z1Go2MMBAbp1rvk\n83nuL95nd3eXbrdDu61SKpXodY20ml2a9Q43P7hHRzWAZsLt8YAA0WiEF198kYGBAdpyG6PBRnxw\nHK1n4vat+0iSnYX5JZp1DavFRafbJZ1Osr27wtLyTSxmC3Nzs6iqym/91m9x5sxZrDYrpi4sXP2A\nof4IT527gM/m4B9e+Ra3r16HR2/MHqoKxQJra2tsbGwwODjIsWPHMJkkXC4XsiIzv7BAJpOm3myQ\nyWS4efMGk5OTfOpTn6LT7TAyMoJJktjY3GBkZIRcLsedu3e4du0a169f5+q1q5hMJqamphgeHqYt\nt7Farbz00kvUGzV2d3exWq3IsozVaqVSLlMqlZi/fZuxkWFq9Rr37t/n8uXLLC3pEbNiqcjA4AD5\nVo2e2cjtuwtkEikK+ylc4kcdoOlMmhdeeIGrV69y9uxZLj1+CZ/Py/DwMNPTMxSLRS6cv8DGxgZP\nP/00Pa2Hw+FAVnTIgdX6YHuOH+jBd39thUw2S6veoJIrkNtNYHHYyRfydNsqUV+QAXcAOVvCIhhw\nSmb8Nid2gwm11sBu1A+8UqmE3+c//L6CILCxucHGxgYdtUMmncHj9mCxWHnvvfcwm80U8rqtVxRF\nPXPlcLK+vobcVtjc3KTb7VAqFjFbLIehZa/HS7PRZGx8lK988b9hdGSOq5evUauVGJ2IUK7ssb6y\ny4XzT+Hw+JhfuYds7jC/e/8jFNE/yWaZLRYE8SMDy2E33Yd9pY/MLQ9V29vb2O32j7BEgoBkMtGo\nN3QzkijyysuvcO3qNcZmpgjGIriDfoqNGt5QH6cvnGdhfYVys8a//KM/xON2s3F/mWs//wUR3wBy\nWWVmeJaZoVmkrgUb+h+sx+OhUCxgsxgwGCRef/11GvUO0cgo1YrM2Ogsbmcfo0NHiEYiWC1W+vr6\n8Hq8BANBstksTzz+HPHBSYwGO/H4JFazh5PHzmEyuGnUOiT209RqFVS1jkFSURU9r/hhPOcb3/iG\njoc5eRq5WudH3/1HfvGzN7l/a4Gv/1dfI7fV4EevvfWQd+iR0GB6appmo0mtWmNra5tUMkVfUM9Y\nBgJBAGRZxuVyoaod5ufnqdVq9PX1895779FoNJBlmXA4jNvtxmg0UigW+M1P/uZhDOtzn/sca2t6\nRvDll/+WmRm9BFtV9N+dZrOF2WKhPxRibHScb7/6GouLi5glM1aLlVgsxu7uLvV6HUmSOHLmJNfm\nb3H02DGSewk2V1YZCcdoNBoYDAacDic2m42NjQ3C4TDFYkkHFZQrXLt+jY9//ON8+9Vvk81m2d7a\nZmJiAr/Pj8vpwiSZCIVChzSIB6EHevD5AgHsLhcetweH2YqxB0Mjw0hGIwGfj3K2QNDtJez247Tb\nKReK3L55k5H4EC67g9H4MM1Wi8HBwcMCYUHQC0s9Hg9Oh5Njx49hsVqwO+ykk2mOHj3K3Owc2VyW\noaEhfVFLRa5/cB27w4EgCgwND+P3+1nf2KCQz1MoFCiWSogGkTd//ha3bt3mf/6f/nfWlhN4ff3s\nJ7cpV5NMzvWjqQb+7pVXyeTzPP+JF5DFDprTOci5AAAgAElEQVRNOLDG6zJJJv3gM5vRev8U56F9\nFGL/p2yPR3ooGooP6ST0g98rTdMwSRLPP/ccJslEwO+nvz9EKp3CYDHTEwUaapt7y0vUlTZ90RBf\n+/ofUWk2WFlbZXdrB7nR5MSROeamj+J1eHnq4tOMj0xg6BkwibrD0uFwks3kMAgCNgl+8IMfMDUx\njaCJTE8cYXhohC996SsMj44RDof54pe+yODgIG/9/E29ZeXZZ1hb3SCdyFCrNNhc3+bI7DFy+RKf\n/8JXeOGFT3Lh/OMUS3lkpYXRCG1Fod6ok8/mWV9f53d/53eYnp4iubtPo1LDiIDYBbvZwt7GNp/5\n5JexSf7/9CI+0n8xffhGGgEajQahUIh4PM73//F7WKxWIuEw29tbRCPRgzLyCR1ZVK3yzDPPUCoW\ndTeky0WxWKRSqWC325manOLixYt0Oh2+/OUvU6lUePfdd/W+YQ1mpmdYXlzSu4UVGUVVaTYbmE1m\nwqEw8eE4//Daq9y/v0ilWmZra4s33ngDs1lnVO5s77C+u0VX0HjhxRcpl4p47S62l1cJRyKIgsDu\n3i7b29s4HU6CgSC1WpVwf5hKtcKFCxe4evWqzrKMRPD5/bz187cIhUPYHXZMZhPXrl1jcnLqga31\nAz34nOEAHVWlWK1QsQgs9irQMhANxKkW29RqCgajg3bXQDOZxy5KiBosb64Tn5lkt17Eapeotyqo\nWosuCon0Lt6gi7KxwmZti4JYRHGr9M+GmHn6CC6Pg3Q+idvnxN/nJZVNMDI+xLh3gJgrRD6ZJ5cv\n0z84THx2jmKhRiw4wNbddTrpOv/9S1/jTGAcrU/m8d84g9svcnQ8xubNy5iKeQYu9NMxFticv0Z5\ndYdPPvEblAoKLWS6Jg2jw4QsKihih3K7islgRBINSIKI0NNwO5wIPQ3R2EEQH42SHqq0HhZJoqeo\ndGSFaCiMuU9ipb1DMdRh7LmjCOYWlmYZQ9RKqZbEqbRQEjuEfDbMPolv/c2/RW2t4Qp0eflH/wHj\noIvBS8cxxhT6jrvwHbFSlPYpSPuowQqR6AjTJ0yER2UyRXjltXcJxBT8/Scx9Y+TNtmwxQdo1atM\nuTxYXUbuL9+hraj4/YPEB4/zwdUtNtttBs9NMn1pELOvhcGgMjowxZXL3yQalTEak5iMWZL7N7l8\n+VVadxL8zf/11yhOB8HJST549wZbP7mBYgV72IvosVDs1rGHvSg2gb2tLE9efPZh79CvtbJ7SSqZ\nHMOhKKPRAdbv3kdrGvDbwzSaGvZAFEMwzHazjTcaoWcxUWg1MTgd/PzaVapdFY/DTaetMjI4TLQv\nwvEjxyjliyi0EC0a12+/z8buKqV6nrHpYeY+MYR3OsDzv/P7qF0HHnsfvXYbi6XLhlRhaXGRVr3L\nak9jcSFBrVDAaTZhAsrZLDajkeT2FufPnCUUCbOS3KH/2CQZu0bCBQ6Pi0qrgc3jJFPMU1daXP7g\nGuYhkdiEB61RRKvVESQLstON0DUiahK1UotcuoSomQj6wkQkH83kg6OHPNCDr9PpoGka6VSKdqvF\nF7/wBd658h7LG2vkKkXUXo/YcJzrt27wwgsvcOTILF6fD5PJRCqZolatsr+/j9lsZnd37zBMaZJM\naD0Nv8/Py3/7MlazFbOkB3cNRgN7e3vYbXYMooF4PE4mm6FSrZBKpzAajTSbuk3baXcQjUTYTySY\nnZ2lr7+fzc0tbs/P8wef+xJv/eQN1lZWmb+zwOe//GX+7rW/57WXv8Xvf+Z3CfgCeH0+/vZbrzAw\nOkxPFA4+wO330RWhLxr+6JlOEP7ZSO3D3rtHenhKJJJkczkajYb+ztjpollvYLVYqZYqFAsFFFlF\nMpnI7SUJB/q5/O57WOx2llaXKTcbjI2OU683CAQC/OG/+kOeuPQE4VAYARG5JVMulVGVzgGRo4Mi\nt1FaRtS2gXIlzauv/Q2S0Uy+8TYWzzaKcJv5+6+wsPQt5pdfZm9nn1wmx7Vr17hw/jy7u7ucPn2a\n/qCffC5DMOjD7jAjy03eeecttrcSrK3uYJZsuBw++oJhhgbHeef6+3g9XowdjaDdhdVioSsZWN1Y\nxxcI0O4oFColhkZHMEgSxcYm/oj5YW/Rr7W8Xi8Gg4GlxSXQYO7oMdLpNHaHnVQqhdFgxO/1YRBE\ntra29FIQs5n4YJypqSl90mZ3EPAHaDaaCKJALpdjbW2NfC5PsVDk8uXLxKIxtre3KRfLtNsyrVaL\nVqt1kE3WYbOKouJ2ueh2O1y7do0//dM/RVZkqrUqtXqdgdgAgUAAi8WC2umgygovPvcCVslMYnuP\ngVAUgybSbrUJBoJYLVa2NrfoC/bRVfWvz2fzWG028oUCwUCQS48/jtPhQtM0BmID1Ko16vUG1WoV\nTyBA959U7/1/1QM9+BRFt/hPT0/jdrt5/fXXiY+PYHU7qbabPP+pT7CwdJ/oUJzLly+jKApH544S\nCoUQBAGn04nH66FYLOLz+ZAkSe9StFoxSjqR96knnyJfyFMsFcnlc0xPT3Nk5gj7iX3SmTSSJHH7\n1m2qVZ0NCBCJRACdiK0BN2/ewOVyHTLZhoaH+Nn3fsB4PE64P0RH67G+u8WTH3+OZx9/gnfeeIto\nOMw3/uL/4MzF85TaDRShhyqCLPQ4ce4sCj2K9SofIpg+HKXpB96HlPYHudqP9MtKVVUkSSIWiwGw\nt79HJpfhzsICJ0+eJBAI0G63WVtfw4qB1NYOuzs7mCxmRqenqHVlfvazn+JwOLDb9RejfC5PqVhE\nNIjIskylUv2I6i7L+uioZUORTRRKe3S0PAaDRCa3hsUm05RTWJwKFpuMxa7g9XnJ5XN84hOfwGa3\ns729zQ9/+ENacpmRsSiKUmdrexVZrZFMbfHMxz5OMBAlHB7CbvcQ9MeIRUcYmBrj2WefI+R0E3J6\nMFvMtMQeqVKBRk/hM5//LDMnjpEq5ql3ZGok6EjV/8QKPtJ/SbmdLoDDaq5atUKn02FyYvKQnP5h\n6fjQ0BBOlwtZlhkZHWF5eRmX283e/h5+v59YLIbL5WJ+YZ6zZ86ytbWF5cDfUKvX+JM/+RMGBgc/\nKtMXxH/mTm+329jtdlRVZXt7i79/9e/xer1UyhXq9TqxgQEymQySJDE6MkIjV+Llv/prtpdWSW3v\nMByJYhckmq0mXq8Xq8XK2vqa3kSjKrRlmXwhj91mJ5/Ps7W9xfz8PJVqhWQiicFgoN6oU61UaDaa\nZCtFVHr/7wv3n6EHm+Pz+9E0jbt37zI3N6cT1oUeuXqF3/jtT1NqN8hUijTp4HS5WF1d4edvv8Xy\n8jJLy0tomka308Xtdh9CMd1uNwsL82iaRqPZYGV1hXa7zc2bN9nf39dZZDYruVwOr9fL6uoq/f39\nyLLM2bNnaTQauN1utre38Xq9hMNhXC4Xp0+f1l/AHHa8Xi/mDuyubrC1to7BbMLgsLKe3KPP5sLU\nBaXV5r/97/41I0em+Nq//q8ZnzuCyeVg6tgci1vriDYLG8k9FFU/TGVZxmg0Uq/XEUWd+v1Pi18f\n6f9/fUjLaDabBAIBDAYj+VweX8CP2+PGKEmMjo0QjUYp7ad484c/plGpMjAcx+xz4RuMcO6xc4yM\njpDNZrFarWzvbLO7t0s2k8VgNAAaiqLojDEBarUqP/3xDYyCl3xpA4+vp/dwlj0YiTM68ATvvrFO\nueBA6MS4ffsWR44cQZZl/H4fJrOJ559/ntmjY7TkMpK5y9T0EEtLt3F7TXxw7S4GwcJPfvQOFrMX\ng8GKgBX3YAjJJLF9Z4mbb1+mkC9QFToMjo9w5vHzWFx2wsODSE4bZbmJYO1SkR8VLDxM9YX66fV6\n5HI5xifGWVxa4syZM9TqNSRJYn19nWq1qncTyzLXr19ja2uLv/iLv8BmsxEI+An1h7DarNy8dZNq\ntcrnPvc5EskEGxsbmMwmwuGwHpl5/33MFhN2uz4pS6VSqJ2O3jncauF0OTl9+jRnz57F4XBQKpcO\nnwobjQbFYoHBwUH6+vooVyo4JDMGtYfUA6XWYGn+DpIGkkki2BdkbX2NyclJjhw5QjqtH5ipVIp8\nIY/FYtEJO0Yjo6MjDMYHQUCvjvT7SGfS2P0eJNevaGVZtabXLD1+8XH+/M//nNkjs1hdTi48eYn7\nm6sksxmylRJ9g1F63R6ZbJah+BClYpFSqUShUPjownRnR48LHNTw1Gs6rqPRaBCLxjh69CixWIxW\ns0Wj3iAcDtNutbl44SL9/f089+xzLC4uMj42TiFfwGK2oKofoWhWlldI7CdoNposLy1DW0WpNSnm\n83o9T6OOJ9zP4s15SpkcLoeDerPBxu4Ol29cxxP04wr4SBcLaEYDXYOeYzwMth98fEhht1gsSNIj\n0OfDVKfTQVEUvabLH2BwYAC3243L4cLldoOmUavVuXDhIiYVLBgQETh34QKjR6bwRUOEQ2F9nJ/O\nUK1UGR0Z5ciRI9gOkCvtVhu7zY7clnnnF++wurrByaMfw2Hrx2zpYHHIWK02bOZ+ttaKzB15nN/7\nzFc5f/YFBmNzXLx4UZ+AIGK12hAFkWajiYaKIKgIosre/gaiQWVwMMzi/TX+4ze/jc/dx62b95Fb\ncGd+ibZBL1SIuQIkljdwulw4w0Emj82C1YTksqOKoBqgaxSpKwJdHo06H6Z2d3YoFos06g329xNI\nRiN7e/sEA0EajQbxwTgmk5lYLEa5VCbUHyLUH+KLX/wiLqeL9957T69ubMt0u108bg9vvfUWLqeb\nubk5LBYrToeT119/HafTSbFQIpFIUKlWuH9fd6qLggiCoBNMNjcxGo2YTCYGYgMYDAbcHjeKouB2\nuQFIJpMMDAyyeuc+8b4IxWSGmeFx8vspOvUW1Ypeq3fh/AXQdJOfKAp4PV6cTidej5ex0TEikSg+\nr4/1tXUcDgeXL19mbHQM5aBD1up1I5qlB7bWD/bgq9aoVCrkC3n++OtfZ2NjA8Fk4OdX3iMQ7Mdo\nt3Dm3GM0mi329/fo7+tDEASMRgnzQcRAVRXcbjdDQ0OH75rNJjM2hx2nw4nT5eT6jQ/Y3dnl1s3b\nbG9vs7a+jqqqLK8ss7e/R7vdplqrEY/HWVpeIpfPYTaZkWWFVDp1SBje3d+l2WqyvLpCyB/AZXdi\nMZkplkuYbFZWdjaIh6I8fu4877z9Di6vB7nbYSedwGA2MTV7hJmjc6haj46A3u7SbqOqKkpPRe4q\nh513kiQhScYHudyP9EtKUWTachu7w4E/4Kdeb+ByunA4HbhcTqx2G6urq9RrNar5AmJPw+tyY5Ak\nSrUqaztbhCMhABL7e4QjYYZHhvWmC4t+aLRaTbq9DsG+IKJooNEsocgGxkfmyBX2yeV3yGay+INm\n+sM28qUt5G6RvcQS12+8QavVoqf1sNn1dnxNA1lWQFBB7AFdHE4LGl0qtQKnz5xneXmDwcERMukc\n7115n1yuiCx2sZjN+GxOnj73OM997BmGx8dwetxk83mK5TK7iX32kkl2E/v4gkMs3F17iLvzSPVG\ng1OnTh+M+xKIBpGe1mN7Zxun00VX6+kZ0F6Pk6dOcuLkCWx2G1euXKFSqTAQG8Af8HP5ymX8fj+V\nqj6WrFYrOJ1O8rkcpXKJRqPBxvoG2ztbvH/lCn/2Z3/Gj3/yY8QDR6kgCAzFhxgZHiaXzfOlL32J\nZDJBLpulUq4wNzt3iGBLJBJEohHOnT4Dmka9UmVnc5OBcASrZGJyapJ8Pg/oo9oPr4B8Pi92ux2P\n14vZagF0Tl8+n+eVV15hYmKCza1NNrc29YehVp1S9VfU3JLP5+jr69Nrce7cod6os3/jDgNOD0aj\nRrHTgJiHzoiPSr+J0WdP0w3ZmX3yNJLfhj1gp1ls02l0MXSMBBx99JoaZiyMeEJ4MBOxePFhYe/O\nKtXtFAapR09r4/bYiESDVGsFPD47PUFhe2+DQL+HaqPEB/NXefrZx/G7A6wtrVMr12lV22ytbnP8\nyHEGZsbYTu9hd9oJ+fwM94U4PjhKu5Rnb3WJIZ+XzRs3ya2tEDJKLDbWyNsq7JJEGJSwTbqwTbmQ\nu13UbheDpmEBtFwVf0ugJwu4bJ4HudyP9EvqaN8QvWQFn9EGSo/9nX2UqBFH0EZzN0vi/RV+9B9/\nQj7doetwsqEkcT3mIittY5U6jJr6MJhclKsyZ849hWCwsbGVpIeZriGAaApik8IoBYntD/axV+ws\nvFvi3JMhQlMVMnKdsQvP45oNkzYn+Pm179ErpDjmD0GhSS3fxmiyk0pnGRqNIXeLjM74eOPdVzgx\nOku10aQo9aiYRexuD4PeMFpSJdgJkp4vUV8Rqd4z46nNEMHCfjHFXqRD7qyVtVgOZbZDr1ki7Lfh\nNPeQtBaS1sREi+u33mJkMvywt+jXWiMDQ6zcXSSzl0LoaAxHh8htbBC0WDDLbbLr6/hNEmqhQGpn\niw8uv8vywm1Q2jxz6QJCp83+5jYemwMTItur68xNTrO1uobD7iHUH6VaahAfGKHVVBCROHXuN/k3\n/+Z/I5tt0pE1Ou02vXad7ep9NI/MXm2XG6t3CI6MUFB7hL195BNZtHYXl8mB3WBlcnAMJeSg6hL5\n+L/6HMc++TRqv4PVdo7ttWVa9TL1Sh6rJLKzscroYJSf/uJdpI5IZn6N9maG/bUtiq0WDaGAf8BF\noVkiPDyC0R6g1bWyvCVTrf2KllRPTU3r31QUmZqcYmZ6hsnJKZwOJ9VKjUI+TyadwSKZuXTpceSW\nzOs//CFKW6ajqty/d59O56MxYblcQlEVtne2WVlZIZ3WmXaxaAyrzUpsYIBGo0E0GiV4QB222WzE\nIjGSySSf+MQneOKJJ3nhhRd4/OLjbGxukc1kGR4exmq1oigKLreLdquNqvXw9/ehCQLFfIG/f+Vb\nlLMFErkM7Y7KsVMn6RoFBKMBTRRx2B0szM8zd2SOfD5PwB/A7/PjG4ph6/cj2hz0DCZakkCh10Z4\nhCV66BIkI7LWpdZscvXGB+TKRYbiQyiKggb8h29+E7Uks7a2xskTJ5iemmFhfh5RNByOaRwOBydP\nnkTTepjNepjXbDbjdrsxm/SnPkWR6XRUZEXhxGPTZDM5RkZGkdsy9WqNUrGI3OkwNjmFJhooVKqE\nB2JEBwewWa0szC+QSqWQZYXpqWm+8gf/gkajqdfkyQoG0YAiK5TLZfqCQQLBAPlCnkg0wvkL57BY\nzBQzJcqZMsV0EVPXiNQ1YuwYcDicbG/tIAgifcEgfcE++oP9+P0+spnsw92gX3OpBzWI4+PjNBp6\nO8vE+ASDg3Hu3L3L+PgE9ZrOaKxWa5RKJTLZLJVKhW+/+irr6xuIosiJEycJ+AOcOH6CjY0NHA4H\nP/nxjynkC7zw4gtYrVbW19cZiscp7aeoZPI89/THEABBENEQOHVK90A8+eSTyG2Z8+fPY7Na6fW0\nwx7QYLAPj8fDxvo63/7Wt/B6PLRbbd584w3KpTKzM7N0O12sFis+n543TCVTTE1Po2kaZrMZf8CP\nyWzm7bffIdTXj81mx+/z66bDeFyvlZRl+j1OjNqvqLlFECAUCuFwOHj7nbfZ2dvF4/VQb9RZWl7C\n6/WSSqdIJBP83St/h6qqfPpTn+b2/G1UVaXdbtOW5cMOTJPJdLgI5XIZQRBwu9x0uh3y+Ty9Xo96\nvU40EiUQDLC7t8vgwCC7e7tMTExw+/Zt/uqv/orXXnuNYrHIzvY2qVSKoaEhzCYzHo+HyYlJPF4P\nsgHcfX66vR6jw8MMhMJMDg4RiISYmJ3h2sItOiIoaMiCPnIQBAG7w84zzzyDLMvEB+M4Bvux9PvA\nY0O1mWhJUNJkeIBW3Ef6z9P9tRUCkX56JgOqQeDjv/0pYrGYzqJTVUZGRzj5hP4Hv7Ozw8rqMvHB\nIXq9Hh/unqqqyLLMN7/5zUOMS6FQoNFokM/n2dvdO3AL6yanU6dOkclkGHeMc/XaVapVPbirmSUk\nh40fv/0G3/rea6gijM1NY7fbGR0dJZ/L881vfpOlxSVsBzVSyoFpSjSIKIpMtVIhf+CA/tCReu3a\nNZKpJA7JhcPowmlwIXZNSF0zZs3Gy6+8jCzrFva2LOt/c+02MzMzdHuPStQfptxez+E+1mo1fD7d\n3PT66z/ks5/9LNlsBofTqWOznA5MJt0zEI/HmT0ySzAQZHx8nP39PUrlEoViAa/XSyAQIBgMUigW\nyGZz+Hw6wHhjcxOh3GTt1gImVcPYAw3QRBgdGWFleYXdnV3acptioYjFaqXX7WI2m/F4PWQyaTxu\nD5LJhM/vZ31tnV/84hdMTk7qdWOyjMlsIpfPsbAwz+zsLMlUkkq5wvDQECaTiXw+j8lkwu6wE+wL\nYrGY9W7QZgtFVVFUhXh8iD6XDYP2q9rVmcuzv79PuVzmzJkzuJxONjc3SaVS9Pf3H8Iwg31BwuEw\nu3u7SCaJz3zmMwQCAUZGRg6dj+VyGZ/PRy6fY3h4GJvNRq1Woy23CQb12p5ms4nf7+fK+1e4fPky\nHo+HQDCAx+NhbW0NWZb1i1Gr9RAcG4lGKBaLWKwWwuEwtXoNm9XG3a01dtJJNKPAmz97g63FFbR6\nm0Kzxl4ugzPoo38wSmxiBLvPQ61Ww2AwHMJnY7EY4UiY8+fPEw6FiUQj+Hz6BW65VKZSqdBsPiKw\nP0yNTE1QUdoMTIzyxHMfwxH0HcKCK9UK9+7eo9NRyWTSfO/739cduQbxn8VQ/H4/jUaD8kGPYbVW\n5cqVK9y+fYtarYbSUQ76CbsYDLqbt9lqkhNyXHz8IulMGrXbwe73UFVb+CL9eEJB8o0KHaPAzs4O\ne/t7GIwGbDYbCOh35YKArMoANOoNmq0WhWKRe/fucvLkSaxWveZMVVWGhoZYm1+jmCozFBrGZ/Zh\nwUa31uPihQu8/c7b3Lt3j9XVVaw2Kx6fB5PJxNjo2EPamUcC3cVoNBrp9XoEg0GsVitbW1t8+tOf\n1kkIzSYTE+O4PW5yuRx2u514PM7k5CTzC/Nsbm2wt7fH7u4upVIJ0A1dsViMaDSKJEnkctlDurnZ\nYsFYaSOUmlTTOXqKTviot5rMzs7Sltuk0ini8bheuWe10ul2cTgc3LhxQ6fSiAIfXL+uE9tt+hTN\nZrOxsrpCo9lgb1enw9tsNpLJJKqqEo6Ecbnd9PX3USmXqVWrzB6Z5e69e9hsdlZXV5mbm8Pr9VIq\nlvD6fWwt3sHreHDmwAd68MWiMUZHR2k0GiwvL5PNZmk2m4TDYcKhMPl8Hq9Hv9Q0GowEA0EWFxdZ\nvL9Io9HA4/bgdrtJpVKcPnUaySjhdrkJ+AP6WMmq03+vXLmCxWKh0+ng9Xjp9Xr4/X6KxSKFfIFi\nsUiv1yMc0rvqQB+/AoiCiNPpolarcfz4cdLpNPlcjmZXpdXtICsKs1MzPHXhEuaeQP9AjEQ+w73V\nZaqKjMXp4NbiXU4cP0EkEuHHP/4x+3v7xAfjeD1eJgJRuuUaw95+vKIFqwpiXUaWFUTx0ajzYUo1\nwKXnPobBakYRNWpKC1VVqNd059nY2BiVSpViscQXv/BFPv+5L+B2ucnnChQPnu6y2SxOp5PTp06z\nvbVNo95gbW0NVekcjiLRwGLROzrdbg9ulxuX5kJu6c33dquNjghdg4AiQCASpiMK7BwULszMzDAz\nPcPJEyeZvz3P+++/z1/+5f9NMpHEZDLRarao1+qEQiF6PY1atcpjjz2GLMsMHOSrcntFhLaIzxbA\nLjrwWwMM9g2xurbG2TNnKRaLGEQDy8vL3L9/Xw/dPyqpfqjSDqIMmqZRKBRYWVlhenqGbrfLd77z\nHURR5I033mBhYYH19XUKhQLj4+OUS2VEUcTn8+njxFQKg8GAKIq4XW5CId2N3D4gLFTKFZwOJ6Ig\nMurpYzQYgYaMxWhCVVX8/UFK5TJWi5VyuUylXMHj9jA1pUMBCoUC4VCYlZUVAoEgKysrGEQDclum\nWq2Sy+aIRWP6OL5SJpVKAdBRO8SiMbKZLO1Wm2qlevDwUScSjtBqNvnud79PNBolmUywurLC1//4\n62xvbRP1Oskkdx7YWj/Qg69cLul5Op+PSqVCt9slFAoRCUeo1WuHWTu7zcbE5Djf+e53iIYjLC4t\nUqvVcLv1TeoP9dNsNblz9w5r62v6k+GHaAuzGVEQGYoPUSwUaTQbHD96nFarRf7g0Mvl8oTDYVKZ\nNJMTk/T19REOhenvDxGORFhfX8Nhd7C1tUU4HMZolGh0FZodGbnbYW93h+W793BbbKhCjx4aI+Pj\nGM0S1UadmaOzdHtdEokEsYEYGhqZTIa5Y3PcfucyfWYnHtHMTDTOcCBEzOGl2W7xaNj5cPXk008T\njkUxWi10BWjKMh21Q7VaI51Kc+nSJex2m97kUq0yNBRHVRXy+Zz+u5Uv0G61qNaqVGoV7i8v8sab\nbxAfGKTdbiEr+ihyd3+XfD534KbTSe4iAo1W8+Buw4Qq9OgK0BF69MfCdIQe++kkbpcbp8PBfmIP\nq83C7flbFIoFNtbX0TQNRZFptOrUqlVCfSEsZgtHjsxSq9YIBoKcf+wcBoMRt9VFp90lvZehkC7S\nrLTotLr4/T7CkTDjY+PcuXuHpeUlRFEkEPTj8bgf9hb9Wsvn03PQwWAQk0knG6SSCbKZLF/+0pcw\nm808/9xzjI+N88QTT/DSSy9Rq+nUctDweryUS2VOnzqFKIq4XC5q9RoryyvUG3VefPFFJqcmsdqs\nTExOEIvFiPtDDIYiKI0mFklCVVWCff1cv3Yds9lMMNhHbDCGw+lAOiDMxAfixIeGsFqtdFQVh9OB\nIICi6sXo6UyaWCyGoiq4XC4EQdA5rcEAiWQCk0mi1W5Rq1bp6wvhdDhIppI4HU6efvoJkqkEMzNH\nuHDxIt/73veoN+r85Affpyc/OF7kAz34PBYnnVqbwl6a8dgwEwMjlLNZbt76ALPDQmAkwnY9R80p\nYh8a4oWXfp+lvX0Eg4XR+ARCG+aiY6KKLDoAACAASURBVBibPdqVJnaHC1UQKaoySqmKxWDE7rAz\nMDlK2yzQ8duoNUvspjaROw3cPhuBkJsz548j9TSQFZRGg6FIlHa1Sqyvj2ZyH4PcpFbN0zV3aZhV\n5ICBT4+e45R/lOfPPs3vf+FfMH3pcd5P7lIyCbjHh3FEQgQjMZKJNL12l9Wb6/zRF/6Yqz+7zs79\nPb762X/J5vw2daGFz2RlVgjylDTBc9ZjPOO7yJESuHZLD3K5H+mX1L38fRquGr5hC21y3F+7wubG\nApJZJlnZpmqs8PwffILTv3OR0KyTrFrCPTiGYnFRN7UpGRN8570F/ofP/49Ib2Ywv5Ul0OkndvIS\nZslJOd/GLLjZX8pjbLqYDJzAFg4wM/osRtWLvJPF7/bhG7hAzBXHLQaIOkbZXywRsk4gVny8t/Zz\nqoKG1z9LxHeOJ45/itpek4svfpJw/xzttBOTFqHiEMjGGoz9dh931PdImdc58cIkm/lFBsb9BC0m\n1u7cwOXqsJ75gIXkW+x1bzMRHIayQnErzW+cf4a4K0x9r4ABLw5b6GFv0a+1Wo0W0VAMUTPgtnuo\nleukWzJXFpdINFpUEPnBu5f5xZ27WO0CG5srKIrK7VsreFwj7O+2wWhENJnJFoqsb21jttmpt9t8\ncOMWP3/7F9xfXCY2EGc/kSKXL/COpcW1RpaCKJNrZqiZiih9Lbo2qFfytPb3+fb/+e+QxB7vLrxP\nVtui66nRMdZ46Xc/DU2FuCfK2uoqvU4Xt9PFzOQ09+/dQ261KSQLdDJ1+lQzfaIDyWJHDXpRKk1q\nHZXNVomCCRRRILG1y8pClm7Dxnj8CLeu3UQSesxODWMO9ZGpVh7YWj/YOEMhj9frZWpyClVVqdfr\ndFSVaDRKNpfDYrYiCgJyq43X6+X48WOcOnGKx86cpVarsbq6SrPZxGwxU67oWZbz587TaDSQJIm+\nYD8/+tGPKOQLlEolvvbVr+FxuUmn01gsFn2cqQloPY2hoWGmJqew2+xUK1UsFiuVahXJZsUT8NNW\nZGrlKpraYWt5nXyxwMrqKlevXuUf//H73Llzh0qlwmTfACO+EBN9Me784n2CJgd+0YrJJHH5ymU0\nTeOrX/0q3/7Wt1EVha5RoCsKdAxgctgIRMOMTU9idzqo1GoPcrkf6ZdUp6OPI2X5AL8iqwedmgqq\n2iGbziK3ZKxmK2iCTmzXYHZ2ltGRUSLhMJ//7d9hYCDGWmKH4SOTmCSJfrePwf4huu0eBgxcevIS\nQ+ODmFy6+9LpsKNpGlvb29TrNcwmCXom0CQ0DS5ePM8PX/8ugkGlkCtQr1VRFBnQ9LZ6n4/F966z\nf3eZiNWFrd2DfJ2Y1YvSVqhXG+SzeXZ3dllaWubatevU6w2sVgvVao2u2qNe078mmUzyjW98g0Qi\nwejYGCaTib6+fuYX5h+NOh+yPB4vV65coVqtUigWdBOKw8nQYJxMKs1jZ8/icroI+AMsL6+ws7ND\nOp3G4bATi0Q5fvQoQ/EhgoEgJ0+c1O/TwhHy+TwXL1xEMkqYTWa63S4/+9nPyGYyGEQolwpoWodO\nR2Z4aJCR4Th+r5+dnV3GRsfxBwI06g26nS4T09M4XG7KtRrleo2uKGB1OBiIDWKSTMSiMZrNJhsb\nG1gsFgYGBnju+RdYWl4mm8sjiiK5dBZB0K+fDKII2oFT1OMhmUwSDoVZW13FaDASjUSw2+185Stf\nYW529oGt9YOtLAsEGBwYJJVOsbOzo1/S9vWRSqUwm0yYzCYEQe803NzYAAQUVUE0GqjVajhdThYW\nFpAkif7+fvr7Q9xbvMfM9AyZTIbvfu+7nHvsHKlUkmKxyAfXP8Bis3Lq5Cl8Xp/uvtM0REHk3ffe\npVKpoKgK1VoVs8VCrVIlOjbM+OwMHq+PxP4+fR4/Q/0Ret0uwUCQyclJTp48ycjIKD6fj/JuktJW\ngup+mt27y/RbnFBt4vJ4UBSFl37vJV599VWmZ6ZZWVtDRaNjAFXQkBxWAtF+hqfHefHFjyMZHwXY\nH6ZUtXPoGJZl+SDQLh9+ns6kkGUZu92GdmCd7vV6uFwuTCYTGlDY1uHF1qCX2NQYkiQR9wZpF2S0\npsb01AyxeBSDXSBV0y/znS4nvZ6m9yTWamxvbaP1zGhdCUEwsLy8xMhIjHIlTTqTpl5voCgqPU0j\nEgnjcrtwqHDt9bf4u3/3l5R2EpwemaJXqKJ0FGq1KtlcluXlZZ579jm9U7FSwWy2UK/VUDvq4VXD\nh5gvURQpFosMDw0fcCtlfvrTnz7cDfo1l6ooDA8PH7ZYeb1eNAEuXLzAxOQEy8vLTExO0O12qVTK\nurlEEPB4PIBGLp8/cPwqBIIBAoEAqaR+L+z26Fy+o8eO6lw9sxmXy83m5iKFYpKR0SiD8X6GhsOo\nnTorqys8//wL5Ao5UqkUjUaD0ZERepKI2ePEG+7jxLkzBKNhFKFHNBY57MFdXVvF7dYNOG6Ph/ff\nv0KoP0QqlUTTIJPNHOLagAM8mAmn08mTTz4JQC6Xw3hQ+LGyssr3v/99ut1f0ThDuVImkUyQTCY5\ndeoU6XSa27du6a0B+TyqqnLj5g0EUSSVSnHjxgf09ffx1ptvUi6X6Xa6xONx4vEhZFlmeGSYfD5P\nLp/F4XQyOjrK6toqNrudarXKrdu32NvdZX1jnaXlJfb29K5Mtas/ZVqsFhqNBkajEYNBZHdvl0qn\nTVcSKdbKXHzsHB6LjXo2TzaXY2d3h7fffpvd3V3SBw0vuVyOYF+QdrvN1NQ06+trBAJBnA4HXq8X\nRVXQNI179+7h9XjoSAItrYO3P0BL6+IOBnH4fQwODHDkyJEHudyP9EsqmUqyv79PqVSi1W4hiCK5\nXPbQ0t9u61EBTdOw2x2onQ52hx1Jkg4beNKrm1QqFWyhADvFLD6fj3/467/l9rt3GQmPIXRFwoNh\ndvI7qBaZ119/naAnSK1dw+vzUigUyeazDMdnOHPmIqVSlWvXr+DxWWkrRSRJYmtrC4/HjaZp+AMB\nTp8+rb9QuZ2Mj0/gdDgwmU3E43Hd0i5AKBzi8uXLZHMZBuODDAwMcP/+fdY31vXoQrtNq91CFEUm\np3S7+dbWFm6PG7XTodPtEAgGHvYW/Vqr1W4fRrTcbjeKLCMZjSwuLqIoCtVqla2tLWZnj+jZUqBS\nqRAKhUikkgSCQU6ePEm1VqXdbmMwGDBbzHi9XgqFApWqXkNmt9uxWCwEggE2NhfxeK2MT8YJR/2Y\nzBo9oc3o6CjxoUFqtRrTU1PcvXcXm93G2t42RoeFjlE3i4WHBlja2aDVanH6zGlWVlc4fvw4U1NT\ntNttOqrK9PQUmWwGj8fLs88+Qy6f0yd4fX1IkkS326XeqON0OujrC7K1vcXyyjKZTIZMNsv9+/d0\n49mv6qizVq1RLBaJRqPs7u4SDof5vd/7PcL9IcxmM81GA6PRQGI/odN7aw02NzZ5/rnnGR4eRhAE\nrl67yt27dzCbTZRKJR47+xjXrl7TDQKigKqq+ghKEDAYDJTLZdLpNDs7O4iiyMbGBmjgdDhRZP1y\nNZFIUCqW+NjHPoZmMVFp1jFbrGSSaXptlYBVBzcaDAYCgQBaT2NiYoJup8vU2ZNIfhfmoIehY9M0\nJYGbG0tYzBbQ4N69e6iqSjqd1l+InHZaXZX9Qg6b14nZ7cDishMKh/AHHr2wPEyNjYwSiUTY293j\n+vXrzM3OYhANFIqFw5b6Ql7/XJFlfQSqqKwsrwAgIHDv/Rt6+bnYRbUYiEaj5Hf20aoCrVKbeGyQ\n7Z0tIsNhxk6MoCgqfp8fo9GIy+Xi/LlzuJwubJYAJsnB0dljWKwmVlbu0laKCAgUCgU99qn/g9bt\nMfv4OQaPzRAYi9N1WFjJJljLJ1FlfVQrt2SeefYZVLWD0WBEFEVOnTrF7u7e4c9mEA3k83kqFb31\nP9QfwmwyMzE+zoVz55mdmXmo+/PrLoPBQKVSQTwouxANOnItFAqhyPrT4P7+vh7b8vsRBIFgIMjG\nxgaNRoPt7S16vR61Wo1sJosoiiSTSaLRGOVyGY/bgyDo/1coFOjv78fulJiYHEJR65gtYLGJmEwa\nkWiUK5ev4Ha7iQ0MMDM1g8vpRjUIZItFFEHDGfSxtr9DfHwMl8PFW2+9RSaTQW7L7Ozs4Pf78fsD\noEGpVEIURLLZLIIgMjo6isViJeAP6CSGep29vX0KBb0ovVwus7m5SaPR4MTxE0xNTXHz5s0HttYP\n9OD7ECOkd7H5MBgMLNy5QyKVYHh4GLvDQTgSodvt4fV6GR8fJRAIIIhgNBqxmM187vc/i8lkZnNj\nE0VRWFxaJD40hGQ00utpNJtNer0DzA8CJpMJQRBotVtoaKytrYGmYXfYUVQFh93BU089RblcYn8v\ngcFmplKvI5lN5HI5um0Fq2TC4/Uc2ojDkTD1eoNoLEoZhdubq9zZ2SA4Fsc9GMYa8hMMBEin00xP\nTWM0SkTCEfZ2d5EsZlqqQi6fo1pvUG3UqdbrNBsN/P7/h703D5PrKg+8f6f2vbr26n1R75K1WJYs\nL9jGNthgDDZ4IGSDhHwhgcmXTCaT5cuEhAyZZJJJMgGGfElsICSAmSSA8RLbeN+0ry11q1vqvau7\nq6uqa9+XM3/ckmjasq2lrZbR/T1PPd33nnvOPXXuW2d573veV41wvZ5YbVaqlSo7rt/JDbtuwO60\nU6lWiEQjIAQSSXQ5BgjyxcLZjei1+gA0dnqMWGgRKSWB1iYaO9qYnw+hrdRoC3aQiWfJprJE41Gk\nrsLM4iSFQh6P3YMOpVNraW0hmUqyvJwhGkngcDawYUMX6Wwcr9dJTdaUgVgjQGhQhlsI5RMIj532\nLQM0X9NL1iwo2fTkC7mzqtq+3l62bN7MwsIC7W3t5HN5KpWK4llCgNAIwkthEskE1UqFQjHP0lIY\ni9XK8ZFhaqrZ8boiazVcDQ3IWg1Zq1GrVunu7mb79u0kEgmOHz/Opk2bePHFl3B73QgBPp+PUqmE\nzWajVCqxf/9+0uk0Tc1NGE1GmpuaGRsbJR6PKypRKRUVd1cXJ0dG6R/oIZFaxudzYzLpMei1mM0G\nwktLTExNMjx8gsWFhbOOrKVGEF6OIjWCbLGA2+fFaLOwGF7EZrXhbGhgYmoCj0dxPBJbjgHg9XgB\nSTQSAwHRaJTjQ8eYnJxAo9GQSqWYmZnBZDLS1KSoTaWUpNNpHA4HI8Mj3PP+e9asrdd04CuUiiwn\n4iyEF8kV8uSKeXqbN5GPFVmYnMNMDa9Nh92Yo7+9j862bhwNHixeP0ulIqOJGGPJENtuvwGD20q+\nlKOUz0Iuz8HUNBm3lpYd/Zga7WhsOgrVLBmMVOM1eqo+mlMW2hraKeisxLIp7H43iVIOu8/NfDxK\nUVPlxJ5D2DUm8vE0PqcHu92BrEFP+yCpWI5KHuwmF5qKnthCEmeDGZvdgEZb5uVXniObiyMosWgp\n4O4O0NnVTLGYouIQHIpP0NQURN/kZHd6lu/OHOKV5QlOV+O8Nn6KpOq9ZV2JZhaoijAmsgy/ehxH\npgVdugF7xcfc8RCVWJ5aMoUmn8Zaglo1SVrOoSGDJaYl/L054u44Gk+FSinF1p5eTDUjk6dCGJJL\nWC15UsYlEoYi2aILc34rO0034hU68vkix/fFGXlmAV+0SmZhDJPMYDZWqWpyWIJ25vIRHLUWjNEq\nL37tH5l89SXmpsPoAn0kkgu0NvpYGJ+loWTlGtsALYVGdg2+l2BDH4WinkSpzFwhRsv2bk4VTxDc\n5GTjlnaq0SXMixnMUymsizqKKT3Ons0MLSZJxwX+tJPq6TiGpBo2az0p6/W0DW7E0djE4M7rcbW0\nkoxF+aP/+vscO3yQA7tfo9HnpTnoo1Hbho4GFrN5DB4HhXwcR62Ap8FDc6CJyVMTvOe2O1mcW6Cj\npZ1ENIZeo2F5aYnujk4Cbg9LC/OMHDiF3uwmbbKSNtkYm1pkaXqZoR88j7/oZEtwJ+OHZ6iWUrRu\n0NLf2IWtpmPp1Az2qp6Te44QHp2iFC9QihfQ5sFrctOgd5CNZJg5MoLGbuW0zJCy6yjG07zL2orW\nbsPkcnFgeJhMpULnwADX3XwzS8klouko23Zto7mrGZvHxkJikWRujlR+cc3aek0Hvht27eK973kP\nN+y6Ab/PTzajWGOeOH4cj9eD1+NlfHwct9tLPpfC43EyNzPFyPAQHW3NdLa3ksvmGTp2jIG+/rPB\nYh1OB0a0yGKZXCLFwvQclXwRf4MHm86AyWQEkx5hNmIw6LHpjAgEba1t3HnHHRQKBTraOyiXyjQ4\nGzh8+DBIxXDh1NgYp8bGiMVilMtlzGYzx4eOk8/nOXz4MI9//wfUCiXyyQzXbdmKw2TFYbYSjURp\namxieHiE63bsIBgIKJvj3Q5aO1owO4xkC1mGRod45PHvMTZ2ikpFtZpbTzQICoUiNSl5/rnnOHBg\nP8VSESEEFouFjo4OHA4HJ06cYHZmjnQqjV6nRwgNx44dI5VJYTFZACiWSjz01YdwOOwM9Pejs+uw\nNlhZCi9xemgEl7CSmArT2dlBrlqhWq1y/4fvZ3pmmmBjI9VKDRCcGjtNqVhCSLCYLZRlFG+jgcf+\n/V95de+/88qeJwhHThEMNlEulTEZTVisVswWMxarlYmJCY4ePYLX48HpcCoWqTWole34XBs4NbqE\n1dSIz72BYt5IMpdh08AguzZvw2910tHcSpkaC+NTvPjvT63n47nqsZgtxKJKvxJdivD8888jpWR+\nfp62tja2bttGqVQiGGzi8ccfx+lw4Pf5GOwfIB5fpq+vn0I+j9PhVNzX7dlL/8CA4r+4RdlQrtPp\nSSaT2Ky2epBvE5lMBrPJDFLWNXDKK6Xt122nUCjgDyhRdNwuL9dcs4lMOoPVYuOll16mpaWF7u4e\nLGbFy1Aul0MIQTqdxtXQQGdXF1NTkzQ3NpFMpEgk4kzPzLAwv4DVYmXb1q3Mzc0ha5LGxkacDieZ\nTIaRkRFisRixWIzl2DIGvYnRkbE1a+s1HfiefOopHv7Od3jyqSeZC83hcDqIRCPcf//9lMtlJqcn\nSafTzM3Ncnz4MPv2vYLRrKFGkeGTR8jkFDXjkSNHMBgMJJNJNm7cSDqdRi8F1XyRfCKFLJYJujxs\nHdiITeiVZbHZQM1iwGAw0qA3sRxfJhpVvG3MzMxgMBiYnFJe5jc2NVKtVXE4HTgcDq7dvh2dTovL\n5aKrs0sJJlsq8q53vQuLzsCWwU0Y0OI023CaLFy3eSunT59mYX4et8uF2+Xi0KHD9HT3MB+bI9gZ\nZOO1g1QMJbRmLXq7DovZQlh1AryuSKBQKFCtVrHb7ezfv598/YdqMimGUA67g0qlwtTMFKlUGq1G\n8YAxNDREPB7HZDbV4+7l0QgN6XSam268EekAk8tAZDFEMZpmat8I3pyV1o420pk0tVqNRx99FI/H\nw549u2lsauTAgf3kcjnyhTwgMJvMWOxViuVFXF7o6vFRrkYpV6MUS0UmpyaJRqMMDQ1xfOg4J46f\nYHJ6iq7OLtxulzJBNBqo1qoEvL1MjMfIp/WYDEF87h7yGSNGh5X3v/tOfvjtf6Pd5uHInn2URI1r\nNvThd7jW+xFd1WQzGfr6+lgML2I0Gunu7iabzbJ161aCgSCNjY14vV5++PRTZDJpTo6OYrPZSGVS\nisVwMkUun8fZ4FSc97c0k81kSMQTJBIJxSfrxkFee+017A47gwODZ2XYarVQqVTwerxICW63Eund\n5/et+N/P0NAQdrudfCGP1+th3759DA0dY2FR8c7S3NyMlJJUKoXL7ebUqTFcLhcberpJJOLE43El\nzJLDjtVqxaA3YLFYlNdVuTytba309fax/drtZ1+d6Q16Rk9O4fe1rFlbr+nAt3HjIJ2dnXg8HoLB\nIBazhUK+QKVa5X13vw+9Tk8wGOTgoUOcOHmYp599nHhqEafLRCa3TLmW5cTxE/T19bEUWaKjowOr\n1Uo2m6WaK+C2OrAbLWxobqPF38jI0SESswvccfsd9O/YSqBb8ea995kXADhZj+oejUaRSLLZLHNz\nc5hNZpLJJJMTk/W/SsynHTt2cOToEYQQTE5OYjabafU3MnlyDLNWx9OPPs7YiWH2v7Kb2++4HX/A\nj9fv4/T4OD6fTwneGD6Nq8mB2W0k0O5jKTNPzVRjenrqrP88lfXBYDJgtpgRAlrb2igUC2zZsoVs\nNovdbsdisZBIJvD5fBSLRWx2G1q9lqmpSY6fGMblclEulTEajdRqSmwxvV7P0aNDBAcbycg0tWoJ\nU0FgiFRpLNjZvn07TqdioanT6ZRYZ52dDA8PA0okh9jysuIL0Wohn8+zceMmens3kMlkFN+NskZ7\nezt7du/j2NAxJicnSaVTLIYX8bjd+Pw+mltacDqdzMzO4nA6aGpqwu/3UygqjqsXFhdoampi87Xb\neOrRxwgfG+N7f/s1wjNz1DSCUCqGxqwGol1PLFYLIyMj2Gw2ujZ0nQ3xFggEiEQjNDU18cgjjxBe\nCnPP+++hra2V8fFxajWJ2+1Bo9NgMZtJp9O0tLQwPT1NJpthKbLEDTfcQLAxyPj4OBs2bECr1eIP\n+FleXiYYDLJ37150OsVBSCgUIhAMkE6lz259sFitzMxMc/LkSSQSu8PO4cOH2bJ1C8WiEvi2t7eX\nQCBANpulXC4jhGDLli1s3bqVpXCYzs5OisUSfp+f40PHWQwvUpM1GhsbMRgNvPzKy2g0Gto72nE2\nKF68kskkDrudxmAHLldgzdp6TQe+oaEhvF4vfr+farWK2+Xm9ttvp7Ozky9+8YuMT4yTyWRoaGjA\nYtFTqeaJLYcJzU+zobsdh8NCU2MTLc0tZDIZBEIx7W1oQFOqsm3wGgJON8lIjKnRUyQjy7iNVoZP\njrCUS1Ez6hEaweTQCGOnxlhcXOTgwYME/AHGxsZIJOIYDAbC4TB+nw+tVovP66evv18JAFqrnXWG\n3dLSwsMPP0yLx8/i1CyiUOaOm27h4/c/wEBnN4sLi0gJB/YfYO+ePRgNRrq6OrE0mDk6chSL20K2\nksEZcKKzCnz+AI1Naryz9cSoN2A0mjDojTS3NDM7OYVAKOqdunpGq9UyMzODVqtsPk8lUljMVt71\nrpspFAqYzCbS6TQmkwl/wE+xUMRsMpHX5anoSghZ4/rBbTQUjHzyto/S1KLMgKvVKtVqlVQqxXxI\n2fITCoWYC4XQabWUy0qYoZbgAKGZDCdPLBJbKtISHKRatJKIxxkY7MPj8eB0OtFoNLz3ve+ltbUN\nh0NZpSYSCcqlMlqNloWlkzQ1WymWl7A6KlRqUbx+HYVqhdjcIhv9bbxn2/XcsvMGZsMLVINOOrZf\ns96P6KomGouh1WqxWqzUaspkJ5PJIGsSu81+1l+nTqfngx/6IHqdnng8TrVSZXJyguXYMpOTk3R1\ndeF2e/D5fGiEhoA/wFJ4iWgkSiwaY9PGTVQqFZbCS1QqFbLZLF6PlwZnA3Nzc7hcLoQQzC8o0dU1\nGg0LC/OkUymqlSqZdIbIUoTx8dNMT01js9kwm80UC8Wz+w+V/hsWFhY4duwYTocDo8GIyWSq7+cW\nZ8O0nThxgnQ6jU6nIxqJkklnqJQrmIyKU5JisUg2XabBuXZW8Ws68F2/cxeFQgGX2021VsMX8HH4\n8GFGT46i0+nw+3zYbFY0QoPJoqVYyrAUDZHOLmM0adh/8DVGT42h1WqRUlJDseppaGjArDdwYM8e\nRo4fx6w3UMxksZvMRGZD9Pf109TezvxyhObmFrqaW2ltbSUYDLIcjxONRenv66ehwUU0EqUx2Eip\nXMZsMVMo5plfmKdYLCIQmExmstkswUCAW2+7jSMHD+F3ebCbrUTDSzzz5NMcP3KU1rY2FhYWkLUa\ng4ODHB8+TjyewOw0cWTkCNYGK5limgZvAwazDp/XSzCouoRaTxKJBLFIhHKlTGguRGtHJ03NTWzd\nvIWW5uazpuTT09MIBMVikWQqSXdvNx/76EfxuD0YDAZSqRQmk4lCocC2bduYX1ygrC9S1daoyjJb\nBzfx7Qf/mZvefy8NNieVmrJPzuF0sHHTJu66+24amxppbm6mpblFUcHW75VOapifzSIrVnTCw9xs\nhoC/l9hyjL7ePlyuBgIBPzuu26F4vtBqSKcyzM7MkkqlKBSKSAm3vnsLrR1OPnTfu9m8tZ1SNUok\nPs741CTtjc3YhA6H1sj81Awuj5um7RvJrp3ze5WLIODzY7VY2bJlM1JKisUi119/Pc3NLdRqNT71\nqU8BEI8v8/TTP6S5tQW3x0OxVGDzNVsIh8O0trby9a9/HavNSi6fJzQfolAoYDAYMBgMmEwmFhYX\nmJudI5PJkM/nlRBIHg8Op4O5uTmcDgdSQmguRHNTMwLB/Pw8iWRScZiQSbMUWSKdyVAslejt6z+7\n1zUcDuN0OkkkEkgkLS0tHD12jJHRUZaiEW688UYiSxFQov8B0NfXT2guxAMPPMBCeFGJclIqYTab\nkVKSz+dx2F0szIfXrK3XdOCTuRL2cIHutIHOrJHlQ6d59chRvBtM5HXLdA7sonfzbZSMFTQpB43W\nHqrLZtKzNUha6XBtopxPMDdzilI+SToeJrI4A+Us49kcY9MLJBbSZGMFkkVJqFIh5TOQ0pWYX5ql\nuTXIaGSajtuvw+h14XG5MaRLJCdDnB47hau9mdnEaeKVGGaPlVxVUpRG2rq20tUVwO4x0twboOKo\n8cyJV1i25enu28DB0WMcnBjmdDqMsSfIokOy91tfZ1N/GzMyTswoaPV3kD4UwjSmp0XTSSFnpCHY\nxnIsTi2dwyg1BJxrt1RXuXBmT88zPHKSZ3c/g6fXza4P7aRk1hOvFnD5fGhrMHX8JNaSIFxdwGa3\nkTiVIaBrRKvTctvH3oVYqBJ0tBJLlhnsuY7HH/wBtzo34Y91snlmE3/Z8Uf8eudvYSi1IMJldGip\nZQw4tQ48ehMzQ4cZ3f0CVFzUSR7BDQAAIABJREFUcmaClmbcJQfd+iC2cJnExDGKyTT+QC9OYxO7\nAp2UX9tDhSTliqQ5uIX25u243D6M5jKlQozl2CSzM8NElybZ0OWlXIyyZNNxZDlE1eugYjaSKhQI\nBJq4+2M3k2mvsd8Ro3prL+3veReLyTzloTHkYnS9H9FVTbZawupt4NTcNNKoY/fhAwivnYXMMul8\nliOv7qXD5uGnb30fzz75ND97132Up5Yw52qMz0xTcFtoMJtwmU0cfu1VPFYL3a0thCbGOTgxRDDo\nITw6Sp8/QCg0hc5r4f6Pfhh/c4Dl9DI1rcRoN1GijMtWo6QJE61OordpuLHnDsyn/GinjcQOxunR\nd9Aq3fiKWhb2HkZKSTwR5+abbyaTybBlyxbsNjvX79xOwGxh8dgwdglL2WU813aTK89jbajQ1G6j\nsc2MK6Dl9PRBAk4nwyeOEs/FmU2Fad3eT8FloGrIgfEKdVK9tLjIls1biKeSzEUWGZ2aoFBMg1R0\nwgvzizzx2JP4vc00NTfi8bix2awMDA5w+MhhQvMh4vWAs16vl1AohEajIZPNYjQYcDjsBAJ+5ubm\naGpqRKvRsHn7tRiNRgxSw9zEFM3NzYxNT+BxuxX/ctUKy8vL9Pf1E41EcDocOGz2eugODXv37uXU\n2BiHDh2iXC5z+tRpert7Gejvx6g3kMvmyOVyBAMBdFod0WgUvVaHTq/nc3/4h3zgnnu4ZuNGpJRU\nqlVuvOlGUukUY2OjNDU2UiqV0Oq02Bx2yqpV57piMBixWixMT00z0D9AIV8gFAoxH5onFJpTgrxq\nNFgsZkwmIw1OJ7e/+93Mzs4yOnKSl158iUBTkJGREeKRGAYEDSYLO6/Zyif7b+W3P/YrNDoCSJ0O\nmSkgbRp0UuKwg91uwuZ0YHM5CcUinDhxmMcef4RIJIzRaKJUquH3t9DVuQGn00m5VKKpqYnvff/7\nuL1enPYGhIS21lb0ei3pVIqpySlOnhzF5/UjEPXQMCVSyRSlYhGn3UGxUGB6aoqAX3n3UqtUmRyf\n5JabbsFqMoOsUSqVGDl5kkgkst6P6KrmzDu0dCrNciyGx+0hdHqamfFJJsZOs7AU5vCJIcxOB1ar\nlfGJCaw2G909PegNepqbmjl65Ai9vX1YrFYiSxEMegNSSro6uliYX6BcqXBydBSn08nc7BzValUJ\nyu1sIBAI0NHWgRAabHYHPp+ftrZ2kqkkRqPhrJGW0WQiEo0QjUYVf8zVKsFgI9PT0+RzeYrFIr29\nfeh0ekxGI+VKhdD8PEJoCIXmiNZDL+VzeeLLcTLpLEajkUwmy7Vbt2E1mrGbbSzOhQi4POQzGYwm\nE1arfc3aeq2cR5oANBXBU08+TTy2DFYjNbMei9tGeG6B8eFJTJpu7r71bvK1RRKJJcrlMrV8jcRi\nArveTjqTRq8zkoikiMzHmJycpKmxiUKhQFFvxKw1otEaMBtsJKMp2vq6yZWrxI6NEZqYoqmpkVg6\nhsakZ/TYSSrLaYJ2F9n0HJOnpshlcxRzaQ7ED9Hb3gMV8PsCjI+PozEWOLz/CLIiOHn8JNlygVgy\ngTFbxOPxshRaos1iJxNJEWhuYi6S4q5b7+I7X3+Y/t5raHL4CSUnePSRx2mwNkCxxr7X9rGtrYds\nLMViOU4qE/2x9lK5bJgACst5MmYtXlOAqeOThOZStLR5SS0nyMazxBeT2AxmLAYjuqyByWMzeGxZ\n9DUDyXCKUydOM7hhgOh8hOu27SI+t8QXfv8P0MUK5KZLHJo+CtkSojGIzCbA70agp5yTJPIxTgyP\n4G1yk6tWMYgSP/vRBzi8fw96Y43YcoiurjbS5ii1IrjsLg4dOIjNZmffvkMUOktcu/kWwlPzzM7N\n4QuYqJHGUDFw8OVDZLIZAoEAcaG4DbRYJjHodETmFmgwuThxaIiAx8fYyRl2bt5JNBSmkq0RXUqS\njETZNNjCxOjkj7WXymXDBFDJVSinS5yOnSI2r2z8Hj5xGJvFit1so5ivYLc6ODB0HDtGvvKVv2Ng\ny2YiC1FaA62EZhawmhxMjk8Tj8dZWojS2NhMbClOYdJItFDFarCRy+eZPDpK/45tHN5zhGg0Ssqf\n5kR+BJPRSKVSYWxqgkg0wYxvnqZgK0NDYxiNJqr5Gla9jUQsTS5TIp8rY9IbmJsOIaoa9r66j+3X\nbef0yGnKlQqvZkrEIgk0NR37dx+kKKs0tjSTjmQJ6ReQEvR6HRqhIbGYxpI6xszwJK2BNqaOnuL6\na3ayfHqBbAHMOsuPtdelIOQabKoWQvw08M1LLujq4WeklN9a70pcLajyecGo8nkZUeXzgrlk+Vyr\ngc8D3AVMAYVLLvAnFxPQATwlpYytc12uGlT5PG9U+VwHVPk8b9ZMPtdk4FNRUVFRUXmnsKbGLSoq\nKioqKlc66sCnoqKionJVoQ58KioqKipXFerAp6KioqJyVaEOfCoqVwhCiFuFECeEECUhxEWbawsh\njEKImhDivWtZP5WrCyHEXXU5umhndkKITwsh5led+zUhxJwQoiKE+OVLr+mFc94DX70BqvW/qz9V\nIcTn3s6KqqhcLO8g2f0b4BWgHfj0OtdF5W3kHSSTl2r2/3XgrPfz+taNvwI+BzQB/3iJ5V8UF+K5\nZaWH5Z8CPg/0csbTKGTOlUkIoZVSVi+ueioqa8I7RXY3AH8qpVy42AKEEPo1rI/K28c7RSYvCSll\nESiuONWJsuB6XEq5bgFKz3vFJ6VcOvMBksopGVlxPrdiafweIcRhIUQR2C6E+PZq1Y0Q4m+FEE+s\nONYIIT4nhJgUQmSFEAeFEB+8kC8jhPAIIR4WQkSEEDkhxIgQ4uP1tL563R4QQuwRQuSFEEeEEDes\nKuNOIcQBIURBCBESQvyxOBM/Q0k3CSG+IoRYqpfxghBi64r0M21wixDikBAiI4R4UQjRWU/vqacP\nrrrv7wohTl7I91U5P6502T0jm4AF+HZ9xv/RetpbyeNuIcRfCiG+LISIAd9/g3v8DyHEjBCiXwjx\nJ0KI/ee4ZkQI8XvnW2+Vi+dKl8lzIYSwCiGeEUI8J4SwrehT7xVCvFS/zyEhxPYVeT4thFg48z+w\nr560UJdzfz3tgXp/nBdCjAkhfu+MnAshvimE+JdVdTEKIZbP9O8Xytv1ju+/A78BDACj55nn88BH\ngF8ENgJfAb4jhNh55gIhxIIQ4rffpIz/gbKz/z1AP/BrwPKqa/4c+AKwDTgCPCaEsNfL7wAeBV4A\nNgP/Efgs8F9W5P8b4P3Ax4FrgRDwlBDCtuo+/62edwdgAP4eQEp5CngJ+IVV138C+OqbfDeVy8N6\nyO4YygqgBPwy0Ah8XwjRzlvLI8Avocj59cCvr0wQCv8A3AfcJKU8CTwEbBNCbFxx3Q1AN4pqSuXK\nYr3607MIRUX5HMpK9G4p5coV6ReAPwa2ADO83v3aGXXp14F76v9vAhqllEtCiDuBv0PpvwdQ5PzT\nwG/Vr30Q+IAQwrWizA/X/373fOr/OqSUF/xB6aSXz3H+LqAK3Lnq/LeBb60697fAE/X/rUAO2LLq\nmn8CHlxx/CLwqTep11PA/36DtD6gBvzHFecMwOKZc8BfAodX5ftPwFL9/wagDHxoRboRCAOfXdUG\nu1Zccz9Kp3bGU87PAQuApn58Yz09eDHPQ/2882W3fk0e+OiK4//5ZvJYP94NvLrqGmNd1u8F/g/K\nBM+36ppngf+54vjvUNRP6/6MrrbPlSqTK+7fBZwAvnGmz6qnn+lTf2rFuW31PG31408D8yvSr6+n\n+1ecexn49VX3/hQwvuL4FD/ed79hX38+n7WKzrCagxd4fR+KH7aXV6pxAD3KDxsAKeWtb1HOV4CH\nhRDXAz8EviulXK3S2bOivJIQ4hDKLAOUVeJrq65/FfAIIbz8SD/92ooyikKIgyvKOMPQiv8XAC3g\nAaLAv6CsHD8A/AD4JIr/ucW3+H4qbz/rJbvnYoA3kUcp5ZlwHwfeIP//BtLAjVLK5Kq0fwD+lxDi\nd+p1/ShKZ6Ny5bGeMilQNA4vSSl//hzpktf3dQLwo6z+zofNwLVCiC+sOKcFdEIIjZSyhqKl+AXg\ny0KIFuAO4KLV8m/XwJdddVzj9WrVlS/hbSgNeAew2vnoeTttlVI+IoRoQ1lO3wm8JIT4CynlelhI\nrQy+d2aprwGQUhbqOvpfEEI8jdLpfPLyVk/lDVgX2b1EVtf5DE8CP4vyW/i3VWnfBb6EMvmyocjr\nD96uCqpcEustk48B9wkh+qSU51K1vmFf91bUB2Yriir3idXp9UEPFDXp54UQW1Bk9oSU8tD5Vf/1\nvF0D32oiwNZV57YCZ6x6hoAKyvL4dS/dLwQpZQSlkb4uhNgH/H8oprNn2EV9hiwUC7htwOP1tBEU\nYVnJzUBMShkVQlRQhO4m6kYEQggTsB3lXcyF8CDKi97PoFg9XWh+lcvDZZPdc/Cm8nge+f8VRaX5\nT0KIqpTyrOFLXdvxzyjvgCzAN6WUlTWqt8rby+WUSYkyKFWB54QQt0nFTmFNkFJKIcQRoE9K+eU3\nuW6xbrzzKeBuFG3GRXO5Br7ngM8KIT4GHEJZsnZTf1BSyrgQ4osoy1gTynK8AeVHviSlfBhACPEy\n8HUp5UPnuokQ4k/qeYdRZhHvq/+/kt8QQkyj6Ix/B+U93z/V074EfEYI8Zco7zyuAX4f+LN6PRNC\niAeBvxZCZFCW9b+PIhzfeIs2WKlyQEp5RAhxDOXF9ZflO8hE+SrjssjuG/Cm8ng+SCm/I4TQAN8U\nQvyUlHLlBOuh+ncSwG9eQL1U1pfLLpNSyl+ry9GZwW+8niTeLN8bsDrP54F/qVt/fq9+bivQK6X8\n/IrrHkKZzAH880Xc9yyXxXOLlPIHKNaU/wvlIQiUF7Qrr/kv9Wv+K8pg9TjwXpQYVWfYgPKe7I2o\n1MsYQpnpZoCVemkJ/C7KCvAwymrvA1LKVL0O0yjL6FuAoyjv4b6EYmRwht+s1+1bwH4UC7y7pJRv\npG5aee/VPISiovjaW+RVWScuo+zCKhk5T3l8ow3GZ89LKb+NYmTwsBDifSvOH0f5HRyRUg69vgiV\nK5HLLJMry/xsvZxn6xbwcG75e6tN76vl/FEUA8B7UbRxr6JY5E+uyvcEiur2B1KNx3d+CCH6UARg\nQEo5tt71gbMr1DuklLvWuy4qVx/1Gfwk8N+llH+33vVRUXkzhBANwBzwESnlU5dS1uVSdV4pXMyy\nfM2p7/nrRpmF/7/rXB2Vq5C6lfInATuXqDZSUXk7qU/QvCj2GqFLHfTg6hv4rpTl7T8AHwL+j5Ty\nop0Rq6hcDEIII8r7oDDKPq63UtOrqKwnPSiGXlMoVsqXzFWj6lRRUVFRUQE1LJGKioqKylXGO2bg\nE0K01x2ibr6APLfW8zgu4b6fEEIsrzr3y0Jx+FsRQqjv6K5CLkYeVVSuBC5WdoUQNwohjgklXuTF\n+cj8UVk1cYlOsy+FSxr4hBBfEz+KH1UUQpwSQvxB/WXk28HF6GUvVZf7MEq4EADqDq2/BPwpSjyp\nv7/E8lXWiHeIPKqovI53iOz+Fcq+wXbe4Z6m1sK45d9RGsGEsmH8KyieSP589YX1hyjlxb9YvOxW\nmfL18aTaUdrtCbmO8aRU3pCfaHlU+YnmSpfdDcDfykuMFymlLL/1lW8vazGbKEoljtSslPLvgWdQ\nLBYRQnxSCBEXSrymEyh+4lrrab8khBgWSvylYSHEr64sVAixUyixnfJ112PbuMQZthDCLIT4dyHE\ny0IIx4ol//1CiTGVFUpMqF0r8nxCCBE/8z9wrJ40WZ+dtdXTPiSUmFd5IcRpocTC0tTTHhJCPLqq\nLjohRFgIsTo8kcqlccXKoxCiQSixxZaEEi9ytC5TK9VPHxNCvFq/z5AQ4pZVZdwqhNgrlPh880KI\nP125KhBCGIQQX6zLVr4u69etyl8TQtwuhNhfl/lXhRC9K+pRFUJcu+q+vyGEmLqQ76tywVyRsntG\nNgE38LW6fPx8Pe2t5PF5IcSXhBB/LYSIoPiPPdc9Pi+UeJOb6ivd1zlUqPfNnz9X/gvmYsM61Cca\nX0OJgLDy3PeB/fJH4TaKKGEndqGYpZqAn0HZiPghlBXUfSj+535O/iisRhjFDdgASvy70yj+4jav\nuNck8Lk3qd+t9TwOFJc9r6Ls/jfV09tRfG+eQPH/1o0SxmWCH4UMOhsyBCXcy+31Mq9F8UAugHcB\nCRRT23YU/4rjwB/U892AEnYosKJu9wMpwHIpz0D9vKPk8csonva3AW11WbpnlSxO1+/fh6JGTwKu\n+jVNKN6Ivoiifv8gyraEz624x98AsyheOvrrbRIDGlb8JmooUR9url/zIvDyijKeBL60qu5H3uy7\nqZ+fXNnlR9EWEiix8vwofeH5yOPzdRn+s3qde+rna8AH6/9/CaW/7KwfN6M4vt6+opxtKJ652tek\nvdfyYaF4gc8Df7biYVWBTavynQI+turc7wOv1P//5XoDGlakf/ocD+uHwGfepH5nBr6++g/3O4Bu\nRfqZzuaTK84N1PP0rvgOyyvSt7Ai3tSKevzOqnv/DMpmyzPHx4HfWnH8CPDQev/gfpI+7wB5fIQV\n8dBWpZ2RxZUyokUJ7fJb9eM/AYZX5ftVIFn/34LSOX5sRboOpWP8z/XjM7+J21Zc8776OUP9+D+g\nhM/S14+v5UdOj9f9Of8kfq502a1fEwd+fsXxm8pj/fh54MA5yqqhBMr9Zr1vDK5KfxzFh/GZ4y8C\nz65Ze6/BwyqjxPwq1H90XwXMKx5WflUeS/1LZ+r5znzy1AMWorxEfWZVvs2rH9Z51O/M7HYGJQae\nWJV+prNZObNoqJ+7ecV3eKuBbwkldMjK75OrdxZnVpe/gRJKAyCAsgK88XL/wH6SP+8Aeby7LieH\nUaJN33AOWbx5VZ7vUp8goYQWeugN6tGC4sS6CrSeo4wHV/wmqoBnRfrWM2XUj/V1mf5o/fiLwA/X\n+/n+JH+udNmt51s98L2pPNaPnwf+7hxlnemXxwD3OdLvQ9FUGOryGAF+eq3aey2MW54DfqX+0Obl\nj+InnSG/6thW//tLKGF5VvJ2RSh4DGV2sRFldrGai44nVceG4vj6dSa+Usoz8a++AfypUILk3gxM\nSClXBxlVuXSuWHmUUj5Zfyf8fuA9KM5+vyyl/O21vM958mbxIstCiG+gxIv8HvBxFKfBKm8vV6zs\nXiJv5BnoaRTZuhvF6f9KHkUZ/O9HaQ8dr48pedGsxcCXlVJOnu/FUsolIcQ8sEHWw2OcgxHgZ4UQ\nBillqX7uhousn0SJyJBF6Whuk1KOrEq/VA6hxJOaeMNKSLkshPg+SvyzG1AjMrxdXNHyKBWv8v+E\nEiPvFRSLvZUD3y7gFQAhhBYl1uMXV9Tjw6uKvBlISynnhLLftIwSL/JM6BkdsANl5n8hPIgySfwM\nisr1e29+ucoacEXL7huU/YbyeB75f4AywH1bKPEiv3MmQUpZrU++fhFFO/awVCzs14T12sD+h8Dv\nCSF+TQjRU7fk+aQQ4j/V07+FMiA9KIQYEEK8H/jPqwsRQjwrhPjMW9xLwNkwHd9EiSfVtzr9Almd\n54+Bn69bcg4KIfrr1nn/bdV1D6GoLPqBf7yI+6q8PVwWeaxbrn1QCLFBCLERJeTQ6niRnxVC3FeX\n0a+gqN7PTJK+ArTWreT6hBAfAv4I+EsAKWUO+FvgL4QQdwkhBlEGMDOK2uxsVc5VvZUHUsqTwB4U\nley31rLTUVlTLmdfupo3lcfzQUr5CPBzwFeFEB9ZlfwgigHYXfy4/F4y6+KkWkr5kBAiizLT/XOU\n1dgQSnwppJRZIcS9wP+Pspoarl+7eqnbieK1+01vt+K+v1mfRT8rhLgNZXZ8rhXfW60CfyxdSvm0\nEOIDKOrO366XexLlwa287hmhBFscklIuvsU9VC4Tl1EeSyiBhztQ1FYvo6h6VvK79c8WFOu7e6WU\ny/V6zNc7rr9AMdZaRnF4/ier8gsU1bodJb7Ze6WUyZVf+VzNcI5zD6GsDta001FZO9arL62XfT7y\n+EZ96cp++d/qWyC+UV/5fb9+/rQQ4jUUq+ZLjST/Y6hOqi8jQggrEAI+UZ/pqKgAyl4plG0026SU\nx97q+suBEOIPUGKfbV3vuqhcnQghTqFYd/7NWpZ7tYUlWheEEALwoagY4ih6bRWV1VwRnmDqE7RO\n4LMoMdBUVC4rQokX+XEUC/ivr3X56sB3eWhD2SA6i7LaW22tpaICV47vzy8DP4Vi0KIaYamsB0so\nWxj+n1Vq+jVBVXWqqKioqFxVvGPCEqmoqKioqKwF6sCnoqKionJVoQ58KioqKipXFerAp6KioqJy\nVaEOfCoqKioqVxVrsp1BCOFBcSszheJZXOXcmFC8djxV99mochlQ5fO8UeVzHVDl87xZM/lcq318\nd6H4wVQ5P36G13sjV3n7UOXzwlDl8/KiyueFccnyuVYD3xTAT/3KhzGYNOTyOVpbW8nm8pj0WuZm\n5/D6fPh9XjQaDal0GjJlajWIRiNUKhUaGlwYDHocDiu+pkZCS4scHT6O0+PBaLOQjMYwGkyUK2Vs\nNhv5XI5KrUopXyKVSjHQ3088HsdqtZFKpwg0eQkvLhEIBBAaQa1aY3pmBrPM093Vh9lkZ2JihsGB\nLYyePE0xGaGxqZlKpUIhn8Nmd5DJpJlNx2lv72B5OUZnVxenTp2iXCrhcjrR6/QkUwmsVhuRSIT2\ntjaK1TKVSoVisYTL7SIRT6DT66jla2SSOZ74lx+ebS+Vy8YUwK4HNtO6oRmhFeRzeaxWKyeGT9Le\n1EqlUMRltbMcjuB3exAaiTfo55kXn0drNrKht4f5SASjs0qxWKJcLGGxWilXypTLJZrsnWg1RsLh\nKBqNCaPORiSyzC3v3shLL72ERqOhVquRTCYZ6B9AYxV85LbP8MUvfIXWDgs923spCAvF8iKVchKt\nLk9nWztGnYu5qRhz0xMM7TmBDQfB5gCTy6e5/xc/xO6jz2LXBSikdWjLOjKJCCZDlUJSYmtwUpRV\ndCYDhWqZTCFP50ALsVgMr8dLoVhgZmaGWq1KS7CTVCTF7n/de7a9VC4bUwAf/vV70dv1hJcWcTqc\nlMsVirUabrsTCmV0VUk8HCGyEMbT0YLH62U5naT3mgEOHDnMNdu2MTR8CJvNjNVqIp2NkUzE0OoE\nDTofM1NR2lsG0Ol1ZPMRdPoilbKJqakpyuUK7e3tdLR3MHZqlFwxQaVSIRJZYnBwI1JKNg5uxN3m\nI7K4xJEDB/nofR9mdmKKaHiJzEwOa8cGkokS2uU0uWIEd7+flCXBgHeQ/U8c5r67P8wre1/GGXQS\nLh5hcPAacukKj/7gOWzmJtpa+jF7MsxNhghNzFFNV2nxNLMYWuSaW7cwcXKCqYNzZ9vrUlirga8A\nkEhHCTb48bk8mOwGtCaBx+mgSpG2tjai0SjtLe0YUzpq8SIej4dSqYVKpcJrr73GXXfdxVJkkQa3\njblImU3bBikLqGqhJosYDAaMRiPRaJRcNQsCzHYz/uYubrz1BoaHhzly5Ci33XYrRqueTClNoM2H\nwWBQBset7yE2NUxrSztHjwzT2d3OTGiK1o4Wcmk9ra0tpNJpjMYmdDodsWgUp6UZvU5HY1uAfD7P\n4OZ+xsfH8Qc9AHgbXdRqNXoGukin00i9llg0it1jUwboShaTycTgtRsZGRr9sfZSuWwUAHo3d9M5\n0EY4HMZubyGTSTNg6keUq4iynsRSlOYOP9VCiXI5j8mmYWBLDza3E5PdRk6XB3OWG7buYGRkBL1e\nT6lUolQqUUmnafCasHiaSCUKmM028jJL35Yedh9+FaPRyODgIKFQiGw2Qy5R4333foRH/umHmO0J\nPE1WvJ0DzE7mGBoZxmqGhp5B2tt68W0s80Hvu1keS/OHn/1jmvxBFtNz9HX0Eq6NMnp4HpupGb1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AbwB1yUy4dk9jM0W00kSUJtqrhcLqamJpk/e5pgPMoAKOYLDDo61z/+lJ+9/SMyB9vU1SPU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\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tg0A0wqVbN4YL1mjjWBaOZbF87TriwOUzn/o1xjKj7O7uYlnWEM+R32Nmdo62YSBJEtmR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\n6wrd8Gk0Go1mXfH/AWbhcokx9LaEAAAAAElFTkSuQmCC\n",
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LP77MidBZuORk69slMs9n8OgGKvoSUrhJdGCEoHyMbD6LWtEQCgbu8N3FztNF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VVvINcaXLpymd1Clhde/CwOu4P7D+7jcDjweDx4vV78fj+ykkFRiijtKrlcGp/PSz5fYGt7i0Kh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\nOIO4JS/TF+a46/ARaoUGTouL9Hoaq8VqBK4Vgp6eHixY0DSNWq1Gb6zHcJU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gG2Hq14Cd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8vlwbbA6w0QiyR56eOXOffEDBMzIVrdLBZVWr19dm9XuPrt1ylurTISUIjJYWYiZwnLGvWD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uXblA+9EDlpaWqFQqTI+p7bdv3eLhzg5nV1bpHTS49tzzJCIRHJ+kIMUdkMGAjB7PGEVR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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f202ce02278>"
+       "<matplotlib.figure.Figure at 0x7f53a8354b00>"
       ]
      },
      "metadata": {},
@@ -2118,9 +2147,9 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[35 39 77] (0) forky\n",
-      "[ 8 99 30] (1) knifey\n",
-      "[  2   1 239] (2) spoony\n",
+      "[35 36 80] (0) forky\n",
+      "[  6 101  30] (1) knifey\n",
+      "[  0   0 242] (2) spoony\n",
       " (0) (1) (2)\n"
      ]
     }
@@ -2146,7 +2175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 72,
    "metadata": {
     "collapsed": true
    },
@@ -2210,9 +2239,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/12_Adversarial_Noise_MNIST.ipynb b/12_Adversarial_Noise_MNIST.ipynb
index 037fc56..6a11e12 100644
--- a/12_Adversarial_Noise_MNIST.ipynb
+++ b/12_Adversarial_Noise_MNIST.ipynb
@@ -124,7 +124,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.11.0rc0'"
+       "'0.12.0-rc0'"
       ]
      },
      "execution_count": 3,
@@ -136,6 +136,35 @@
     "tf.__version__"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "PrettyTensor version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.1'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pt.__version__"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -152,7 +181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -182,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -214,7 +243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": true
    },
@@ -239,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -277,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
@@ -331,16 +360,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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4RdmvX7+02wwePNjn7bbbLvE2oXSF09jhmcDZmD59eq3Hjz76qM/h2ZnhtGY4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\nWv8fezSXIp23dFcAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29fe27d898>"
+       "<matplotlib.figure.Figure at 0x7f2059353828>"
       ]
      },
      "metadata": {},
@@ -392,7 +421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true
    },
@@ -410,7 +439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -428,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -446,7 +475,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -473,7 +502,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -493,7 +522,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": true
    },
@@ -513,7 +542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -531,7 +560,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -549,7 +578,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
@@ -570,7 +599,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -590,7 +619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -608,7 +637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
@@ -633,7 +662,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true
    },
@@ -651,7 +680,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -665,7 +694,7 @@
     "        max_pool(kernel=2, stride=2).\\\n",
     "        flatten().\\\n",
     "        fully_connected(size=128, name='layer_fc1').\\\n",
-    "        softmax_classifier(class_count=num_classes, labels=y_true)"
+    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
    ]
   },
   {
@@ -691,7 +720,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -710,7 +739,7 @@
        " 'fully_connected/bias:0']"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -730,7 +759,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
@@ -755,7 +784,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
@@ -773,7 +802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -785,7 +814,7 @@
        "['x_noise:0']"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -805,7 +834,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": true
    },
@@ -823,7 +852,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true
    },
@@ -841,7 +870,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
@@ -870,7 +899,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": true
    },
@@ -888,7 +917,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -906,7 +935,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": true
    },
@@ -933,7 +962,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": true
    },
@@ -953,13 +982,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "session.run(tf.initialize_all_variables())"
+    "session.run(tf.global_variables_initializer())"
    ]
   },
   {
@@ -971,14 +1000,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "def init_noise():\n",
-    "    session.run(tf.initialize_variables([x_noise]))"
+    "    session.run(tf.variables_initializer([x_noise]))"
    ]
   },
   {
@@ -990,9 +1019,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -1017,7 +1046,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": true
    },
@@ -1037,7 +1066,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -1126,7 +1155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {
     "collapsed": true
    },
@@ -1149,7 +1178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "collapsed": false
    },
@@ -1186,7 +1215,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -1233,7 +1262,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -1276,7 +1305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false
    },
@@ -1365,7 +1394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1375,18 +1404,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      0, Training Accuracy:  34.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
       "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  84.4%\n",
       "Optimization Iteration:    300, Training Accuracy:  84.4%\n",
       "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    500, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    600, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    700, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    800, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    900, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    999, Training Accuracy:  93.8%\n",
-      "Time usage: 0:01:01\n"
+      "Optimization Iteration:    500, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    600, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    700, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    800, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    900, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    999, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:03\n"
      ]
     }
    ],
@@ -1403,7 +1432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1413,15 +1442,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 96.5% (9647 / 10000)\n",
+      "Accuracy on Test-Set: 96.3% (9633 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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AFhpjdiS4LymL9RkzrM8oYH3GTNTrM+qDJxERUbrjCUNERESOOHgSERE54uBJ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\n",
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JkyZNiqaIRABCx/m0r1qdNm2ayQ8++KDJ9mkIu1vMfkyTPfBGtOzH5NmPhmrX\nrl3Y6du0aWPy+eef77w+Sl+7du3KcZratWuH/GwPXrN3716TN2zYELuCxQGPPImIiByx8SQiInKU\nlN229hVYkcatLVq0qMn2+LT2zcCR/PLLLyZnZGSEvGd3bRUowO8WlDv2Vav2YBtvvvmmyevXrzf5\n7rvvNvmzzz4zuVy5clGtzx6441//+pfJ9tW9ZcuWNXnUqFEmJ/LRaJQaLrzwQpPtx9n16tXL5NWr\nV5v82GOPmXz22WeHLOvGG2802a6fqYatAxERkSM2nkRERI6SstvWHoPTHofWZt+oe/HFFzst377i\n0b66FgDq1KnjtCyicOx69Prrr5ts1z37SvJIXa3Rsh8NZatUqZLJgwcPNrlnz57O66D0dfrpp5ts\nd9X279/f5NGjR5tsnwqwx/wGQgcNSWU88iQiInLExpOIiMhRUnbb2l1N27Zti/nyTz311LCZKGj2\nQAp2d67d/TV8+HCTo+3CtbvV7C5Ze7CGzMxMt8IShWE/3nHx4sUmL1iwwOTLL7/c5EsuuSRk/mXL\nlgVYuvjhkScREZEjNp5ERESOkrLblijd2GPK2t25diZKNvb4zPbV4y+88ILJ+aWb1o9HnkRERI7Y\neBIRETli40lEROSI5zyJiChXTjvtNJMfeughk48dO2ayPfKQX6tWrUyuX79+jEsXLB55EhEROWLj\nSURE5IjdtkRElGeVK1c2+cUXXwyb8xMeeRIRETli40lEROSIjScREZEjNp5ERESO2HgSERE5YuNJ\nRETkiI0nERGRoyDu88wAgLVr1waw6PRl/T4zElmOfID1MwCsnzHBuhmQIOqnKKVitSy9QJEOAKbG\ndKFk66iUmpboQqQq1s/AsX7mEutmXMSsfgbReJYF0BTAJgAHY7rw9JYBoCqAhUqp3xNclpTF+hkY\n1s88Yt0MVMzrZ8wbTyIiovyOFwwRERE5YuNJRETkiI0nERGRIzaeREREjth4EhEROWLjmWAiUkNE\njolI9USXhchPRIp69fPaRJeFyC+R9TPqxtMr4FHvf/+/oyIyMMiCuhKRCiKyzStbEcd5Z1jbdUhE\n1onIw0GVFUCu7hcSkdtF5CsROSgiW0TkmVgXLFWkUv3M6+cmIsOt7ToiIhtEZISIFAuqzK5EpJyI\nzBSRP0TkdxF5KZnKF2+pUj9F5FIR+VBEdnmf27sicoHjMpK+fmYRkQwRWZObAxiX4fkqWbk9gCEA\nqgMQ77UyGhKSAAAZxklEQVS9EQpXUCl11KVQMfIqgOUAmudiXgXgbQB3ACgGoCWAF0TkgFLqH/6J\nRaQAAKXieNOsiDwCoCeABwB8DuBkAGfEa/1JKCXqZww/t88BXAegCIArAEwEUBhA3wjrjfff4b8A\nFAdwpff/ZAAvAugRxzIkk6SvnyJSCsB8ANMB3A6gKIBh3mtnOi4u2etnllEANgCo4TynUsr5H4Db\nAOwI83pTAMcAXAPgSwCHADSA/jCm+aYdB2C+9XMBAAMBbASwD/qX3zKX5esLYAGAZgCOAijiOH+4\n8n4M4H0v3wlgC4DWAL4BcBhABe+9Xt5rBwB8DaCHbzmXAVjlvb8UQBuvjNUdylceegSSS3Lz+8nv\n/5K1fsbqcwMwHMD/+V57DcD3Xm4Wbju999oAWOnVv/UA+sMbLMV7/zwAS7z3/2f9zq51KF8dr05n\nWq/d6P2dlEl0/Uj0vySun5d5n1tZ67V63muV80v9tJZ1k7eumt4yot4HK6UCO+c5DMC9ADIBrIty\nniEAbgbQDcAFAMYCmCkiDbIm8Lq4HsxuISJSC8D90BU0lkeCB6C/RcFbbikAdwO4FfqXv1NEugN4\nCPqo4jzoyjxCRNp6ZSsBYA70EXEd6N/TyDDbkNN2NvPKkyki34jIjyIyTUROzftmpoVE1c8gPzd/\n/QRCt/MbEbkawHgAT3uv9YbuXXnAK38B6Pq5A3qneTeAEfD9HYnIUhEZm01ZLgGwTSllj3C+ELqn\nq34uty+dJKp+rgGwG0APESkkIicB6A5gpVJqs/tmhEim+gkROQ3AGAAdob/UOQviqSoKQH+l1MdZ\nL4hINpMDIlIcusG7VCm1ynt5gohcCd3F9V/vtfUAIo5L6PWpTwPQRym1Laf1RkP0QpoDaAz9jSpL\nEeijyu+saQcD6K2Umue99IOI1IauALMAdIE+8rhTKfUndIWpBuA532qz3U4A1aC7k++DPtLdD13h\nFohIHaXUsVxsarpIWP1EQJ+bt4O8BXrHkiXcdg4C8LhSarr30iYRGQrgEegvcS0AnA59ZLzDm2cg\ngLd8q9wIYGs2RaoEYJv9glLqoIjsQWj3JZ0oYfVTKbVTRJoAmA3gCeij2a+hj+5yLdnqp7dPnwzg\nGaXU1yJSA7k40Aqi8QR0l4GLGtAD934qoTWlMHTXJgBAKdUoh+U8C+AzpdRs72fx/e+ijYjc4JUB\n0N0Ow6z39/oaztIATgMwxVfZC+L4B3kegC+9hjPLUvhEsZ0FvHLdqZRa4q2/A4CfobtePs1h/nSX\nqPoZy8+tgdcYFfL+vQ3dKNv82/kXAHVF5AnrtYIACnnf6s8DsCFrx+RZCt/fj1Kqg0M5bYLY9gbl\nVwmpnyJyMoAJABZBdwsXBfAwgHkicolS6ohDmZK5fvbTk6nnvZ9zdZQVVOO5z/fzMZx4ZW9hK58M\n/Ud1FU78ZuTydIHGAM4RkVu9n8X7t0dEBiqlnnJY1gIA90Af0m9WXie5xb+Np3j/d4Y+p2nLaixj\ntfPY4v1vusWUUptF5A8AVWKw/PwuUfUzlp/bKhw/X/6LCn+xhdlOb6daHLqbbL5/QqXUMW+aWNTP\nrQAq2i+ISAb073Fb2DnIlqj62Rn6fOcdWS94X+52Qfe+zYk0YxjJXD8bA2gkIvaXAQGwWkQmKKV6\nRbOQoBpPv18B1Pa9VhvAdi9/Bd3AVFFKLc/DelpAf1vK0hD6G1R96G/3LvYqpTY6TP8TgN8AVLOO\nfP3WAGjpu7LsUsdyAfqEOaC/cS4FABGpBKAEgB9ysbx0F6/6GcvP7ZBL/VRKKRFZCaCGUmp0hMnW\nADhbRMpY3+4vhfsOaymAiiKSaZ33vBb6d5iX31+6ilf9PAm6obYp75/r9THJXD974vjBDqBPp7wD\nfQHRF9EuJF6N5wcA7hKRdtCF6wrgHHgfvtfX/gKA0d431KXQF+Q0BLBdKTUDAETkUwCvKqUmhFuJ\nUup7+2cRyboFYK1SKlcnhaPlffhDAAwTkf0A3oPuSmkAIEMpNQa6n30wgPGi7+2rDn3SO0QU2/mV\niCyC/n31gj4ZPxL6d7sk3DyUrXjVz0R/bkMAzBKRLdDntQC9E66ulBoC/Y3/ZwCTRd/XXA66voYQ\nkRkA1iilHg+3EqXUShH5GMBEEekNfUTxPIDXfF1uFJ241E/oi7qeEJFR0BccFQXwKIA/EJ9TQfGq\nnz/5pj8KfeT5nVIqu3P5IeIywpBSag70VVGjcLyPerpvmn7eNAOgv2G8C/1tdZM12dkAyualLHJ8\nRJ8GOU/txmsge0N/s/kfdKXvAH0CG0qp3dD3jNaHvkR7APTVuX7RbGd76G+cCwC8D2AngBZhupcp\nB3Gun9l+bnJ8xJRb8rZVJ1JKzQXQCsANAFZAN9h9cLx+HoW+paQ09BHiaOhzXn5VkPOFP22hj6Y/\nhN4RLvTWRY7iVT+VUl9BH33VB/AZ9P6rFIBmynuAdD6qnyes3rW8afcwbBFpDmASgLOVUv5zC0QJ\nJSKZ0BdS1PB/QyZKNNbP49JxbNvmAIay4aQk1RzAmHTfMVHSYv30pN2RJxERUV6l45EnERFRnrDx\nJCIicsTGk4iIyFHM7/MUkbLQYyFugtvoFpS9DABVASzMumyc3LF+Bob1M49YNwMV8/oZxCAJTQFM\nDWC5pHWEHvyecof1M1isn7nHuhm8mNXPIBrPTQAwZcoUZGZmBrD49LR27Vp06tQJCL3pmdxtAlg/\nY431MyY2AaybQQiifgbReB4EgMzMTNStWzeAxac9dufkDetnsFg/c491M3gxq5+8YIiIiMgRG08i\nIiJHbDyJiIgcsfEkIiJyxMaTiIjIERtPIiIiR2w8iYiIHLHxJCIichTEIAkxdejQIZNHjhxp8ubN\nm03+8ccfTX733XfztL7SpUub/Oijj5p87733mlywYME8rYOIiFIbjzyJiIgcsfEkIiJyxMaTiIjI\nUdKf8+zdu7fJEyZMyHF6ETH5iiuuMLlq1aomL1261ORvv/02ZP5du3aZ3K9fP5Pnz59v8uTJk00+\n7bTTciwTERHlLzzyJCIicsTGk4iIyFFSdtv26dPH5Ndff93kvn37mnzTTTeZfNFFF4VdTpEiRUwu\nVOj4ph4+fNjkP//8M2SenTt3mtyxY0eTP/nkE5OvvvpqkxctWmTyGWecEbYcROEsX77c5Jdfftnk\n9evXm3z22WeHzNO6dWuTL774YpPLly8fRBEpjdinrIDQU1rTpk0LO8+oUaNMtk+ZZadSpUom26fQ\nzjzzzKjmTxY88iQiInLExpOIiMhRUnbb2t0HZcqUMfmhhx4yuUKFCrlevt2da2cAOOmkk0z+6KOP\nTK5bt67JK1euNLl58+YmL1y40GRehUvhbNmyxeQ2bdqYbI+SZZ9isE8XAMCkSZNMrlevnsnPPfec\nyZdffnlsCkv53pQpU0weNmxYyHvr1q3LcX67q7ZWrVomHzlyxOS1a9eGzLNt2zaTt27dajK7bYmI\niPI5Np5ERESOkrLb1h6coEuXLiaXKlUqAaXR7EESGjVqZPKaNWtM7tatm8n2APV2NxyltwIFjn9f\n3bNnj8l23Z4+fbrJ/isg+/fvb/KKFStMnjNnjsnstqXs2FfO9urVy+T9+/eHTGefMrOv8ra7Z+2B\naOxuV/suBv9dCAcOHAhbFvvq8VTAI08iIiJHbDyJiIgcJWV/4l/+8pdEF+EE9o29Q4YMMblr164m\nL1682GT7KskmTZoEXDpKFRUrVjTZ7l61u13tbv727duHzN+wYUOTx44da/K4ceNM/utf/2pyq1at\n8lhiyg/sLtlXXnnFZHuAmQEDBoTMc9lll5lcrFgxp/XZXbPZDZ7Qtm1bp+UmEx55EhEROWLjSURE\n5Cgpu22Tnd2VNnXqVJPtK2ztcXHtG+OJsth1xO627d69u8mDBw8Omcee7osvvjB53759YTMREDr4\nywcffBD4+p599lmT/VfxnnvuuSZnZmYGXpag8MiTiIjIERtPIiIiR+y2zaMGDRqYbHfb/v777yZ/\n+umnJvMGdspid6XZVyTa49zaA2/4ZWRkmGxfQdmpU6dYFZEoavYj9p5++umI09kDM5QtWzbQMgWJ\nR55ERESO2HgSERE5SptuW/sROUqpqOaxb1a3xyS1tWvXzuRBgwaZbI/tuGnTJpPZbUtZWrRoYfIb\nb7xhsv3IuyeeeCJkHrvu1q9f3+TOnTsHUUSibB07dsxk+5GM9hW2JUuWDJmncePGwRcsDnjkSURE\n5IiNJxERkaN80W27e/duk2fOnGnyZ599ZvJbb70VdvrsXH/99SZXqFAh7Ov2WKP2Y6X8j5Iiyo79\nyCc7P/XUUyHT2acf2FVLiTZhwgST7dNWNn8dTsaxy3ODR55ERESO2HgSERE5YuNJRETkKGXPedrP\ny7z99ttN/vbbb2O2DnvEINukSZNMrlWrVthp7NFfrrvuupiViShL4cKFE10ESnPz5s0L+3qVKlVM\nvu222+JVnLjikScREZEjNp5ERESOUqrb9o8//jD55ptvNvnQoUMm289ItAdtt1155ZUm2yNkAMCp\np55qsn3by549e0y2L71etWpV2HUUL17c5FQe/Jjiz36oQHajYbFeUSJ8+eWXJs+dO9dk++EG/fr1\nM7lo0aLxKVic8ciTiIjIERtPIiIiRynVbdu7d2+T7a6tZs2amfz666/HbH19+vQJ+3rNmjVNtgeG\nP3jwYMzWTenL7gqzHzAAhHaB2QPLEwVp3759Jg8ePNhk+7TCVVddZfLf//73uJQrkXjkSURE5IiN\nJxERkaOU6rbdsmVLoosAIHSQePuZn7a2bdvGqziUz2zdujXie926dYtjSYg0e2AYe2CEYsWKmdy1\na9e4linReORJRETkiI0nERGRo5Tqtk2k/fv3m2xfSbZ3716Ty5cvb/KaNWviUzDKF+yrx8ePHx9x\nOp4OoHixxwl/9NFHw05jD4bQoUOHwMuUTHjkSURE5IiNJxERkaN80W175MgRk48ePWpywYIF87Tc\nXbt2mXzRRReZvHHjRpPt8UXtq9DOP//8PK2b0sv27dtN3rRpU8TpSpYsGYfSUDryj6M8fPhwk+3T\nU7Z0HqiDR55ERESO2HgSERE5Sqlu206dOpn86aefmvz++++bPHToUJPtMRijtWzZMpNbtmxp8m+/\n/RZ2+ieffNLk+vXrO6+PiCgZvPnmmyE/v/baa2Gn69Kli8npvM/jkScREZEjNp5ERESOUqrb9rbb\nbjN5ypQpJtvdtnY3qn0F40033WTy4cOHTX7nnXdC1vHGG2+YvHv3bpPtp6RPnDjR5I4dO0a/AURE\nSWr9+vVRTTdgwACn5c6cOTPkZ/sxjqmMR55ERESO2HgSERE5SqluW9vIkSNNfuSRR0xesGCByS+9\n9FLYnBv2lWf2Vb9ERPnBihUrIr732GOPmVylShWTDx06ZPJbb71lsn3Xw4svvhirIiYVHnkSERE5\nYuNJRETkKGW7bWvXrm3yjBkzTJ49e7bJb7/9tsn+q2ojefjhh01u3769yRdccEGuyklElAqWLl0a\n8b0dO3aYbD9u0b7b4IcffjDZfoRZo0aNYlXEpMIjTyIiIkdsPImIiByx8SQiInKUsuc8bSVKlDDZ\nHoXIzkTJrGLFiibXq1fPZP/tA5dddpnJDRs2NHnx4sUBlo7SQatWrUJ+Hj9+vMljxowJm+1ngPbs\n2dPkBx98MIgiJhUeeRIRETli40lEROQoX3TbEqW6MmXKmDx//nyTK1euHDKdPaJL7969gy8YpY0h\nQ4aE/LxkyRKTV69ebbJ9m6A9SHzTpk0DLF3y4ZEnERGRIzaeREREjthtS5Rkypcvb/KRI0cSWBJK\nJ3a9A4BVq1YlqCSpgUeeREREjth4EhEROWLjSURE5IiNJxERkaMgLhjKAIC1a9cGsOj0Zf0+MxJZ\njnyA9TMArJ8xwboZkCDqp9hjE8ZkgSIdAEyN6ULJ1lEpNS3RhUhVrJ+BY/3MJdbNuIhZ/Qyi8SwL\noCmATQAOxnTh6S0DQFUAC5VSvye4LCmL9TMwrJ95xLoZqJjXz5g3nkRERPkdLxgiIiJyxMaTiIjI\nERtPIiIiR2w8iYiIHLHxJCIicsTGM8FEpIaIHBOR6okuC5GfiBT16ue1iS4LkV8i959RN55eAY96\n//v/HRWRgUEWNMoy1hWRGSLyk4jsE5HVItIrF8uZYW3XIRFZJyIPB1Fmj9P9QiJSUUQWishmETko\nIj+IyPMiclJQBUx2qVA/AUBEmonIMhHZIyI/i8jQXCxjuLVdR0Rkg4iMEJFiQZTZlYg0zebzuCDR\n5UuEVKifabT/vCPC53FEREpEuxyX4fkqWbk9gCEAqgMQ77W9EQpaUCl11GE9eVEfwM8A/ub93wjA\nSyJySCk10WE5CsDbAO4AUAxASwAviMgBpdQ//BOLSAEASsXvptmjAN4A8BCA36E/h/EATgHQI05l\nSDZJXz9FpB6AOQAeBdABQBUAL4uIUkq57jw/B3AdgCIArgAwEUBhAH0jrDuef4fvI/TzAICRAOor\npb6OUxmSTdLXT6TP/vNVALN9r80AcEAp9UfUS1FKOf8DcBuAHWFebwrgGIBrAHwJ4BCABgCmA5jm\nm3YcgPnWzwUADASwEcA+6J1Dy9yUz7eeVwDMc5wnXHk/BvC+l+8EsAVAawDfADgMoIL3Xi/vtQMA\nvgbQw7ecywCs8t5fCqANdGNYPY/b2Q/Aurz+vvLDv2StnwCeBfCx77U2AHYDKOqwnOEA/s/32msA\nvvdys3Dbaa1vpVf/1gPoD2+wFO/98wAs8d7/n/U7uzYPn0dRADsA3JfoupEM/5K1fkYoa77ffwI4\nDcARAK1d5gvqnOcwAPcCyASwLsp5hgC4GUA3ABcAGAtgpog0yJpARLaIyIOOZSkJ/YebVwegv+UD\n+ptVKQB3A7gVQE0AO0WkO/TR4APQO6GBAEaISFsA8LoE5gBYDqAO9O9ppH9FrtspIqcDuAnAR7nZ\nsDSUqPpZFCcOu3YQwMkAakVZjkj89RMI3c5vRORq6B6Kp73XekMfHTzglb8AdP3cAaAedP0eAV+3\nmIgsFZGxDmVrA6A4gNedtyo9cf8Zx/0ngC7Q2zjHZYOCeKqKAtBfKfVx1gsiks3kgIgUB3A/gEuV\nUqu8lyeIyJUAegL4r/faeuhuyqh487cEcFW084RZhgBoDqAx9Df+LEWgvxV9Z007GEBvpdQ876Uf\nRKQ29A5qFvSHdBDAnUqpP6F3aNUAPOdbbVTbKSJvQR9lZEB3497lun1pKJH1cyGAniJyM3S30WnQ\nXbgAcKrbZoSUrwGAWxD6xx9uOwcBeFwpNd17aZN3zvUR6J1QCwCnA7hEKbXDm2cggLd8q9wIYKtD\nEbsBmKuU+tVhnnTF/Wec9p+WLgAme8uMWhCNJ6C7DFzUgG4APpXQmlIY+tAcAKCUahTtAkWkDvQf\nfX+l1H8cywMAbUTkBq8MgO4WG2a9v9f3wZeG3hlO8VX2gji+ozkPwJe+D2kpfBy2sxf0N8NMAE9B\nH1HcH+W86Swh9VMpNVdEBgCYAO8cC3SdagDd9eSigYjsgf4bLgR9juk+3zT+7fwLgLoi8oT1WkEA\nhbyjzvMAbMhqOD1Lcfy8XNZ2dIi2kN7O7UoA10c7D3H/aQly/wkRaQygGvTfpJOgGs99vp+P4cQr\newtb+WTob1xX4cRvDM5PFxCRWgAWARiplPJ/K4nWAgD3QPfHb1Ze57jFv42neP93hu6Tt2V92ALH\nK8Oyo5TaBmAbgPUishfAIhEZqpTaFat15FMJq59KqRHQXVGVoLuKzgfwJPTRnItVOH6+5xcV/qIS\ns53eTrU4dHfg/DDlOuZNE+uLNroD+AX6qJuiw/1nqED2n54eAJYppb5xnTGoxtPvVwC1fa/VBrDd\ny19B/4KqKKWW52VF3mH+YgCjlVLDc5o+G3uVUi47tJ8A/AagmlLKfyVXljUAWvquoLs0D2W0FfT+\nL5LtVBRO3OpnFqXUVsA8w/F75X4V6iGX+qmUUiKyEkANpdToCJOtAXC2iJSxjj4vRS53WN7RbGcA\nE8PsPCl63H9qMd1/ikhJAK2Qy9Nd8Wo8PwBwl4i0A/AFgK4AzoH34SuldorICwBGi0gG9KF4KQAN\nAWxXSs0AABH5FMCrSqmwh9jeB/8edHfDSyJS0XvrTxXwMwa9ndMQAMNEZL9XjgzoLrkMpdQYAJMB\nDAYwXkSegb5U/e4w25HTdt4A/fv5HPobXC3oc1bvKaW2h5uHshWv+lkI+iKdxd5L7aA//5ZBbZjP\nEACzRGQLjl+qXxv6SsUh0EekPwOYLPq+vHLQ9TWEiMwAsEYp9XgO62sOfS53UmyKn7a4/4zh/tPS\nCfpLx8zclDkuIwwppeZAX7U3CsfPoUz3TdPPm2YA9DeMdwFcC/1g2CxnAyibzaraASgN3VW02fr3\nadYEcnxEigbhF5F73gfcG/ok/f+gK30HeF1ySqnd0DvK+tCXog+AvrrML6ftPATg79C3FHwNfa5z\nBvTVduQojvVTQV8V/R/oizgaA2iulFqUNYEcH9HnlrxtVZiVKzUX+pv2DQBWQNefPjheP48CuBH6\nb2g5gNEAwt3cXgUn3scZTjcAHyilNuW17OmM+8+Y7z+zdAMwQym1PzflTbuHYYtIc+hvwmcrpfz9\n7kQJJSKZ0D0KNZRSPyW6PEQ27j+PS8exbZsDGJruHzwlreYAxrDhpCTF/acn7Y48iYiI8iodjzyJ\niIjyhI0nERGRIzaeREREjth4EhEROWLjSURE5IiNJxERkSM2nkRERI7YeBIRETli40lEROTo/wEt\nwtpDP97oCAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29fbdf7048>"
+       "<matplotlib.figure.Figure at 0x7f20571306a0>"
       ]
      },
      "metadata": {},
@@ -1448,9 +1477,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -1466,7 +1495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1476,18 +1505,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    300, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    500, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    400, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    500, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    600, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    700, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    800, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    900, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    999, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:59\n"
+      "Optimization Iteration:    700, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    800, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    900, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    999, Training Accuracy: 100.0%\n",
+      "Time usage: 0:00:03\n"
      ]
     }
    ],
@@ -1504,7 +1533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1517,14 +1546,14 @@
       "Noise:\n",
       "- Min: -0.35\n",
       "- Max: 0.35\n",
-      "- Std: 0.175878\n"
+      "- Std: 0.195455\n"
      ]
     },
     {
      "data": {
-      "image/png": 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8NkiaJKmh9G9O2ukM24GS1ku6VFK/S2zM7ApJSyT9jaSTJL2h4nEcem2YyjDo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\nhAEgIYowACREEQaAhCjCAJAQRRgAEvp/XqGQ15fCWYcAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9ea2400>"
+       "<matplotlib.figure.Figure at 0x7f2056bad3c8>"
       ]
      },
      "metadata": {},
@@ -1548,7 +1577,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1558,15 +1587,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 11.8% (1181 / 10000)\n",
+      "Accuracy on Test-Set: 13.2% (1323 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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9vl75kAv3T848CSGEEEc4eBJCCCGOxJ5tu2fPHnmtefPmonW22JgxY1K61lNP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\nzTdHtquzvl9++WXRr7/+eug16M/cJll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GOwF448aNofPZicL2OuyE5ebNm4fKkeJTam8CYX9++umnqpcsWaLaTla3oyHn\nzJmTWMdi+TPqOfqzfJSz7UzjTSCdPxtS28k7T0IIIcQTdp6EEEKIJ+w8CSGEEE/KNlUlH/a5o+W5\n555Tfcopp8SWSUoebIdbR59zWuwzg5///Oeq7QoCJ5xwguqpU6eqtln+bT3s8Oxo/WwGDZtlIzos\n2yZaJsWnFN78+OOPQ6+7dOmi+s4771Rtn9988cUXqu2zp3nz5qn+5JNPQse1/rz77rtV77///qr3\n3Xdf1Un+tN4E6M9yUs62066KkuRNIOzP++67T7V9XvvMM8+ots9VmzdvHluPutx20vGEEEKIJ+w8\nCSGEEE8yC9suX74cS5cuRYcOHbz3TUp2bLNIJJW3Zeyw6hEjRnjXwx7LhrnGjx+v2mavsMmJ7bp1\nX375pWq76CsQXq8uiY0bN4YWeCWFUS5vjho1KvTe2rVrVduQ1OLFi1X369dPtfWA9Z31JhD25xNP\nPKH6888/Vz1lyhTVSf5M402A/iw2daHttNM70ngTCCd6T6rHGWecoXr06NGxZepL28k7T0IIIcQT\ndp6EEEKIJ5mFbSdNmoQVK1Zg69atum3YsGGxZZNu36OceeaZqpPCAjY58XXXXRdbxoa89ttvv9B7\ndlSuHWV2xx13qO7fv79qO7rNZsxIWofR/j2AcGh5t912iz13q1atuF5iEfHxJpDOn0ne3LJli+o2\nbdqE9rGf6YABA1Rb71iv2pGHe+yxh+poOMu+d+SRR6p+8MEHVduR4XYkuf2bWG8C9GepKFfbactY\n0ngTyD+LoQqbyN5mPbKjZetL28k7T0IIIcQTdp6EEEKIJ5mFbY877rivrTWXFC6ITgBOKmfDAkmT\nhs8991zVdnLskCFDVNvJvUkTg4FwAgSrH3vsMdV2cvshhxyi2iY6tqFdOyIXSF73zobV1q1b97X9\nSO3x8SYQ9pqvN+2oxX//+9+hfa6//nrV7dq1q6HW4UTf7777rmq7JiMQfnRRWVkZeyz7eOK4445T\nbX2Wb81Q+jM7ytV2JpHGmwDw8MMP11jm+OOPV23Dq3akb31pO3nnSQghhHjCzpMQQgjxJPPctiNH\njlQ9cOBA1TYElS9kZkd09ezZM7bMn//8Z9VJa7fZkV12BGQ0bGvDCmPHjk2sVxU33HCDajs53Y4M\ns3lI995778Rj2TCGvW7mDc2GNN4Ekv2ZxptXX321arveIQB885vfTF9ZhEcUWn/NmjUrVM76O2k0\nJv1Z9yl4hpWEAAAgAElEQVRF21lMbFKH+fPnx5bp3bu3avt4wY4Qry/epOsJIYQQT9h5EkIIIZ5k\nHrZ1zqkeN25cbBnf0V9RZs6cqdrepifdss+dO1f1PvvsE3rPhncvu+wy1S+//LLq2bNnxx73gQce\nUG2XM8sXbrDYJAtR8o18JLUjjTcBf3/+85//VG3z1/7ud7/zOg4AzJkzR/U777yTah+bDzQJ6yf6\ns25SirazEKJJFSZPnlzjPvaabPtst9cXb/LOkxBCCPGEnSchhBDiSeZhW0sxQww//vGPVUdXvK/C\nTo61o7bsCNuhQ4eG9omuQl6FDR/ceOONsWX+9re/qbbhX5tTNC0bN25UvXnzZqxbt877GCQ9xfTm\nv/71L9XRxwJpsEuX2VGEabGJOyx28nh0RLEv9GdpKWd41mK9+cwzz6Tax+YYt8kQ7Kham9vW+rQ2\nlMqbvPMkhBBCPGHnSQghhHhS0rBtMfn0009Vt27dWrXN5XnggQeqtksz2aWd0mLDtoceeqjqt956\nK7b8Qw89pPqSSy6JrVM+bGi5WbNmieFkUjd49tlnVS9evFh1Ugg1Sr7J7jURzV+7YMGC2HJPPPGE\n6o4dO6q2yz7Z5aDyQX9uP1hvvvnmm9772/y0NlS70047qd53331V27BtXfYm7zwJIYQQT9h5EkII\nIZ5kHrbNapSYDdV++OGHqu2q4TZfYm1CtUl85zvfUZ0Utu3SpYvqtKFaG9Jg7tDsKaY3//Of/6i2\n3sy3nFMhoVpLmqWgAOCII45QbUeDp4X+LC3lHGGb5M20iTo6d+5cY5lNmzap3rx5s2qbwzkt5fAm\nXU8IIYR4ws6TEEII8YSdJyGEEOJJvZ2qsmrVqtjtb7/9dux2G8O3zxKisf2k9+x2+4zpoosuUv3S\nSy+ptomO7733XtXDhw+PrR8Qzr5hnwEAyeuUkrrBtGnTVF944YWp9knjtTTbTz755NBxbQL622+/\nXfWee+6Zql5J0J/bD0les+uCRp9/durUSfUVV1wReyy7RrJdO7lQyuFN3nkSQgghnrDzJIQQQjzJ\nPGxrE7KnXZstCZvFxSbMttlSSoENXTz22GOqbULipUuXqs4Xqk0iOtya0wGKTzG92aNHD9U2C8uw\nYcMKOm4S1l/RjEI2o8vRRx8du/+MGTNU27qnhf7MnmL6sxBef/111S+++GJiuUGDBqlOekSQJlRb\nX7xJxxNCCCGesPMkhBBCPMksbDthwgQsXrwYXbt21W123c01a9aoTpONAgCmTp2quqKiQrW9TU+i\nNtk6DjvssNjtAwYMUG1DuDaUZkNnhbJp06avjSAjtcfHm0A6f9rw6N///nfVdqT1D37wg9A+1rfd\nu3dXbdcfHDFihOpWrVqpfvzxx1V/85vfDB33/fffV7127VrVhYbDkqA/i0sWbWchXH755ao/++wz\n1dEQ7jnnnKP6kEMOiT2WzQa3//77q66P3uSdJyGEEOIJO09CCCHEk8zCtmvWrMGqVaswZcqUGsvW\nJvSQJlSbhnzh3Pvvv1/13XffHVtm+vTpsdvPPfdc1XZ9xx133DFUrk2bNrH7N24c/mjsGnekMHy8\nCaTz5ymnnKLaJsgYNWqUahvWAsKf8auvvqrarj371VdfqX7llVdU2zCXDdNGsf5av369ajvB3U5u\nt/5M8ma07gD9WUyybjt9+dOf/qTaPjqIrq+ZNLJ7yZIlqu2jrY8++ki1Da2m8SZQ/raTd56EEEKI\nJ+w8CSGEEE/qRG7bfPllLZWVlartbb7Na1goNlftF198EVvGhgFsPQ499FDVdqSczXt6zDHHpKqH\nXevOrlFKSk9SftkkTj311FidD5t/M82kbrvm4Q033BB6z4atunXrptqGk1977TXVdvQm/Vm/SNt2\nFoJN1mDZZ599Uu1v/XXssceqXrFiher66E3eeRJCCCGesPMkhBBCPMk8bJtv+a8kbLm99tpL9ejR\no1W3bt1a9U477aQ6Kfxll8ixE463bNkSOrcNUUyePDm2fkmTbm0O2/bt26s+4ogjYsvnw06Ub9Kk\nSSisQYpDMb3Zu3dv1dabafHNvzlr1qzE96ynH3zwQdVdunRRbXOP0p91k3L604ZLbc5uGwZ96KGH\nEvefP3++6oULF6q2sxOsZ+z56os3eedJCCGEeMLOkxBCCPGkpKNtk0aC5QtJfP7556rthFkbmlq+\nfLlqu+SNDec2a9ZMtV3OLDoaKylUa0c32km/Rx11VGx5Gyaxo2179eoVKrdy5cpYHc3dW6ykECSe\nfKMUk/xpvWl1FiMegXCSAztBfNdddw2Vs6PETz75ZNU2r2gaf1o/Rl/Tn6Wl0LbT1592JKxtI+1M\ngwMPPDC0T5I/bejV1tfmtvX1JlD+tpN3noQQQogn7DwJIYQQTzIL2w4ePBh9+/YNbUs7YixplNnp\np5+u+sYbb4zd14ZnW7ZsqdrmZLQro0fzM3bo0EG1DdXasMKtt96qevfdd6+x3jZ8HA092PCzDb8x\nV2h2ZOFNy5gxY1QPHDhQdTTnZhJJI8Ztbk87QT0pmQcQ9q2vP6Mj0enP0lAX/PmHP/xB9YIFC1Tb\n0GyUaO7ZKv7xj3/Ebi/Em0D5207eeRJCCCGesPMkhBBCPMksbDtmzBjMnDkztC3p1jzt6ESbw9Mm\nM7AjsuxyNjYkm7RsU3REYc+ePVWPGDFC9dChQ2use1KYxIZ2V61aFXrPhiWaN2+u2iZiYIisuPh4\nM/peEkn7f/DBB6qjoTiL9XNS2HbvvfdWbfN32kcNQHjZp0L8ab0J0J+lIou209efEyZMUD1x4kTV\n1ivRnLfWnxb7uK0htZ288ySEEEI8YedJCCGEeFLS0baW2kwkt7f2Nmen3W5XVrfhLxuesGHea6+9\nNnSOCy64QHX37t1j62HrbpdJsyupz507V/VBBx0UexwAmD17tmq7fJQNy4nI10Y+ktqTtTeTwlH5\nQnE25PXCCy+otnlIbZlnn31WdYsWLULHtf8bhfjTehOgP0tFufxp28VvfOMbqu1jADvy1noLSA7b\nWhpS28k7T0IIIcQTdp6EEEKIJ+w8CSGEEE8yTwyfJtZe6HDrNPufcMIJqvv06aPaJkAGkp9zJp1v\n0aJFqm2GDXuc8ePHq44mkrdZjL766qvYc7ds2TJ1dhqSnrTD5guZqpLvuEnD8/P5swq7XmzUs5dd\ndplqO83A15/WmwD9WWpK3XYmjR2ZM2eO6gsvvFB12mkgDbXt5J0nIYQQ4gk7T0IIIcSTzGMtacIK\ntQmT+WKH89tpK2eddVao3OjRo1X36NFDtV17zq4f2r9//9jzTZo0SbUdRh3FTkWwcOh/9qT1WW3C\nZL6k8af15j333KN67dq1oWMVy59J3gToz1JQzrZzjz32UD1y5EjVGzZsUH3YYYeF9tne2k7eeRJC\nCCGesPMkhBBCPCnpELlRo0apzhdeSBMm892eliFDhqh2zql+7733VIuIajsacuvWrao7duyo2q4l\nmg+7Vp4dfbZ169bQsUnxaSjeBOjPhkhD8WdD8ibvPAkhhBBP2HkSQgghnmQWtl29ejVWrVqFNm3a\n6LYTTzwxtqwdwZUVdsTYsGHDUu1jQwwHH3yw6ldffVW1XVOuS5cuqisqKmKPuXjx4tBrG6Kw4QZL\no0aN0KhRo1R1JjXj402gbvozyZtA8fxpvQnQn6WCbWf9aDt550kIIYR4ksWdZ3MAmDVrFoB0D3w3\nbtwYem2XpJk8eXJRKlXMY1ZdGxCen2dTRLVr1y5232XLloVeL1y4MNU5p0+fXiWb5ytH8uLtTSDs\nzyy8WezjFsufab0J0J9Fgm0n6k/bKXZUVFEOKHIOgL8W9aDE8l3n3JPlrkR9hN4sCfRnLaE/M6eo\n3syi89wFwPEAKgFkH5DffmgOoDOAsc65L8tcl3oJvZkp9GeB0J+ZkYk3i955EkIIIQ0dDhgihBBC\nPGHnSQghhHjCzpMQQgjxhJ0nIYQQ4gk7T0IIIcQTdp5lRkT2E5FtItK93HUhJAr9SeoyItIs589B\npT536s4zV8Gtud/Rn60iMiLLiqZFRLqIyBgRWSsiC0XkV7U4xkhzXRtFZKaI3JBFfXN4zRcSkd1E\nZGzu+jaIyDwR+a2ItKh574ZJffFnFSLSQUSW5OrW1HNf+rOeUV/8KSIPiMiknK/erOUx7jDXtVlE\nPhWRu0QkPgFtiRGRRiLyvIh8JiLrRWSBiDwmIh18juOTns9miR4G4BYA3QFUZQBek1RR51xJFvsT\nkcYAxgCYCeAQAJ0A/FlE1jvnbvM4lAPwHIDvA9gRwMkA7s0d539jzrsDAOdKN2l2K4C/A7gewJcI\nPoeHAbQCcEmJ6lDXqPP+jPA4gHcBDKmhXBz0Z/2jvvhzG4DfAzgSQJcayuZjEoATADTNHetRAE0A\n/CiucBmu8yUAtwJYDGAvAP8D4EkAA1MfwTnn/QPgfADLY7Yfj+CPfxyAKQA2AugH4CkAT0bKPgjg\nX+b1DgBGAJgLYC2CP/7JnvU6FUFmjjZm29UAliKXECLlceLq+xqAl3P6MgCLAJwGYAaATQA65N67\nPLdtPYCPAVwSOc7/AzA19/5EAEMRNDbda/NZmONeC2BmIcdoKD911Z/mWD9C8CVvcO6zb+q5P/1Z\nj3/quj9zx7sDwJvF2hfAEwDm5PTguOvMvTcUwPs5/80CcCNM2w2gB4A3cu9/YP5mgwr8TM4AsMFn\nn6yeed4O4IcAeiK4C0zDLQBOB3ARgG8AeADA0yLSr6qAiCwSkevyHONQAJOdc6vMtrEAdkHwLa8Q\n1iP4FgUE3/zbAhgO4DwA+wNYISIXI/i2fQ2CD3kEgLtE5Ixc/VsDeB7BHce3EPyd7o6eKMV1Rsvv\nCeAUAONrc2HbIeXyJ0TkAAA/QdCAFvNOkP5sOJTNnxkS9ScQvs4ZIjIQQYTi17ltVyGIrlwDaATl\neQDLARyEwN93IfJ/JCITReSBtBUTkfYAzkbwBTQ1Wayq4gDc6JzTiohZ2y0OEWmJoEHp75ybmtv8\niIgcBeB7AN7JbZuFIAyUREcASyLbliAIjXREeiPaugmC0NrRCL5RVdEUwbf2T0zZXwC4yjk3Krdp\nnoj0QWCAZwBcgODO+DLn3BYEhukK4L8jp63pOqvO938IvsU1RxAmu9L3+rZDyubP3DOfJwH8wDm3\npKbzpoH+bHCUs/3MhFwHfiaCjq+KuOv8OYBfOueeym2qFJFbAdyE4EvciQD2BHCoc255bp8RAP4v\ncsq5CMKxNdXrtwAuBdACwH8QPP5ITVaLYU/yLL8fgn+w1yXslCYIQkcAAOfcgFrUpep4vt/yh4rI\nSbk6AEHY4Xbz/ppIw9QOQAWAv0TM3gjVH2QPAFNyDVMVExHB4zovB9AGwbe0OxF8Y/tJyn23Z8rl\nz98AeNs592zutUR++0B/NlzqUvtZW/qJyGoEfUxjBM/ofxwpE73O3gD6iogdn9IIQOPcXWcPAJ9W\ndZw5JiLy/+OcOydlHW8DcD+Argju3B9FEDZORVad59rI6234+sjeJkbvhKBzOxZf/2bks7rAYgD7\nRrZ1yB07ekdaE2MQPC/dBGChywXGDdFrrFp8778QPDOyVDVGgiKG6pxzSxBc1ywRWQPg3yJyq3Nu\nZbHO0UAplz+PBrCPiJyXey25n9UiMsI5d6fHsejPhku5/FlMpqL6efkCFz8YSK8z1+m3RBDG/Ve0\noHNuW65MMf35JYK/1yciMgfAbBE5wNy95yWrzjPKFwD6RLb1QTCQBwA+RPAP3Mk5924B55kI4GoR\naWOeew5C8Aea7XmsNc65uTUXUz4HsAxAV3NnEWUagJMjI8v6e9YriUa5317THgiA0vnzRADNzOvD\nEQz8OBjAfM9j0Z/bD6XyZzHZ6ONP55wTkfcB7Oecuy+h2DQA3URkZ3P32R/F6VCr/NksbylDqTrP\nVwBcKSJnAZgM4EIA+yD34TvnVojIvQDuE5HmCDrBtggal6XOuZEAICKvA3jcOfdIwnleRBDv/pOI\n3IxgqsoIAL91zm3L7OqgH/4tAG4XkXUAxiEIpfQD0Nw5dz+APwH4BYCHReQeBIOYhkePVdN15sJ1\nbRGEPdYCOADBM4FxzrmlcfuQvJTEn865Ofa1iOyVk9Odc5uKf1mhc9Of9ZdStZ8QkX0Q3Ml2ANAi\nN8ANAD7Mug1FEDp9RkQWAaj6gtcHwUjvWxDckc5H0L7fAKA9Ar+GEJGRAKY5534ZdxIROQxBiPhN\nACsR+Pw2BJ3ze2krW5IMQ8655xGMivofVMeon4qUuTZX5mYEF/EigrvGSlOsG4KRs0nn2YzquUVv\nAfgjgIecc5ooQaozpvRLOEytyTVAVyF4SP8BAtOfg6BDR+5u+GQEdxpTEFzr9TGHynudCIZ2X4Fg\nyPbHCJ4ljUQw2o54Uip/poH+JFFK7M8/I/jScwGCUdqTcz/tgVBGnzMLuaY4nHMvIJhueBKCTuwN\nAD9AtT+3AvgOgHYIRoTfByAuOUgnhOfVRlkP4CwALyOYtvUQgv7iGJ8vCNvdYtgiMgTAYwC6Oeei\nzxYIKSv0J6nLiEhPBJ3rfs65z8tdn3KyPea2HQLgVjZMpI5Cf5K6zBAA92/vHSewHd55EkIIIYWy\nPd55EkIIIQXBzpMQQgjxhJ0nIYQQ4knR53mKyC4IMt1XonzZLRoizQF0BjA2lxmDeEJvZgr9WSD0\nZ2Zk4s0skiQcD+CvGRyXBHwXQXJx4g+9mT30Z+2hP7OlqN7MovOsBIArrrgCFRUVGDx4sL4xZswY\n1Z06dVLdq1evxIN99tlnqqdNm1bjye35kti0qTqZy+bNm0PvtWzZUnVlZaXq1atXq7YjlHv37q16\nzZrq9WxXrFihet26dar32GOP0PmaNKlOUdm4cfXHYevYtGlTzJgxA+effz4QnvRM/KgE/LwJJPsz\nC28Cyf5M402geP603gTozxJQCbDtrC9tZxad5wYAqKioQJcuXTBzZvUqYDfddJPqp56qTpDRt2/f\n0AHse2effbbq9evXq7aLB9gPxP6xDz/88Boru3JlOEd127ZtVe+wQ/UjYfvhdO9evTTotm3VCSk2\nbKiOtCxfXp34v6KiQnWzZqlTJ4aOu3Wr5lVmOKf2eHsTCPuzWN4E/P2ZxpsA/VmPYduJ+uNNDhgi\nhBBCPGHnSQghhHiS2aoqgwcPzhtSSLM9ig1DWGx4o1u3bqpnzJgRW75Hjx6qbagBCIciWrdurbpr\n166q586tXmln0aJFqm14omfPnqqXLVumul27dqHztWjRQnVSaKVZs2Zo2pQrORULH2/W9F4Vvt4E\n/P2ZxptA8fxpvQnQn6WCbWf9aDt550kIIYR4ws6TEEII8aRUi2EDCIcOJk+erDoaovDFDt22w7Nt\niCEpDBFl6dLqtXp33HHH2DLt27dXbUMEu+xSvVTeggULVO+8886qo6EwS6NGjVRHQw32PKT4JHkT\nKMyfSd4E/P2ZxpsA/dkQYdtZ97zJO09CCCHEE3aehBBCiCclDdsmTeCN8v7776veddddVdtbeBsW\nsPrtt99WbUd5ffrpp6qXLFmiOjoZ2I44mzNnTmz9WrVqFatt2MOGGOwE4I0bN4aOZScK2+uwE5ab\nN28eKkeKT6m9Cfj7M403geL5M+o5+rN8sO2se20n7zwJIYQQT9h5EkIIIZ6w8ySEEEI8KdtUlXz0\n6dMndvtzzz2n+pRTTlFtEv/inHPOUf3hhx+qthkvDjnkENVffPFF6Bw2vj9v3jzVn3zyieoTTjhB\n9dSpU1XbLP82Vm9XNDj33HND57MZNGyWjeiwbJtomRSfrLxpyZfY2q48YZ/fWH+m8SaQzp+2Lnb6\ngN1uvQnQn+WknP5M402geG1nGm8C5W876XhCCCHEE3aehBBCiCeZhW2XL1+OpUuXokOHDt77JiU7\ntlkk7PDj6HqGVcyePVv1d7/7XdWLFy9W3a9fv9A+diFVm5li3333VT1+/PjYMva4w4YNi63Tnnvu\nGXp91FFHxZazbNy4MVQvUhhZezOpfLSMTaT9ox/9SLVNmG0XBk7jTSDZnzZ5tl1X8csvv1RtFyW2\naynmg/4sLnXBn7Z9teHSrNpOX28C6fyZpTd550kIIYR4ws6TEEII8SSzsO2kSZOwYsWK0EjYpFDm\n6NGjUx3z2GOPVZ0Uhhg+fLjq//3f/1Vtw192Hbpo0mA7umuPPfZQbUMGdvuqVatUP/zww7F1uuGG\nG1RH1160GTt222031XaEW6tWrbheYhHx8SaQzp9nnnmm6qTQmT0fAJx00kmqbajWYr2axpvR96w/\nbUaXpHVCbR2tNwH6s1Rk0Xam8actYxkwYIBqO8LVzigAgHvuuUf1hAkTYsv9+Mc/Vt2rV69Yncab\nQPnbTt55EkIIIZ6w8ySEEEI8ySxse9xxx31trbmkcEF0AnBSub/85S+q7W36/vvvr9qGai3t2rXL\nX+EcNpnyu+++q9que2fXrZs0aZLqV199VXXnzp1V33HHHartqDIged07O2l43bp1X9uP1B4fbwJh\nfyaVmz59emx5i32kAAB77bWX6uOPP1619Zf186BBg1TPmjVLtfVmdH+bTNs+6rCJuO3EeuuzfGuG\n0p/ZkUXbmcafSbzyyiuq7aMpGx4FgLfeeqvGY9m2MAmbxMYes661nbzzJIQQQjxh50kIIYR4knlu\n25EjR6oeOHCgahsezRcys/kT7TptNlT74osvFlzPKmw42I7usmEyu2ber371q9jj2PyRNs/j3nvv\nnXhuGwaxo4CZNzQb0ngTSPan/Yx69uwZW+add95RvXz58sS62JG0doL6uHHjVD///POq7cTvyy+/\nPHQs6xfnnGo7Ctd6m/6smxTadqbxp8UmMHj66adV2xHb1k+9e/cO7T906FDVjzzyiGobMk6DXVf0\nxhtvVJ0v5FsOb9L1hBBCiCfsPAkhhBBPMg/b2tt8G4Ky5Bv99bOf/Uz166+/rtpOMC9kEuycOXNC\nr22YLYn//Oc/sdvtCNtLL71Udb5QmMVOYo+Sb+QjqR1pvAn4j060PProo4nvHXDAAart44Jf/vKX\nqufOnVvjOU477bTQ644dO6pOCuFaP9GfdZNC284kbHj22WefVR1dYqwKGzJeu3at6qOPPjpUzi4B\nadttu0zkiBEjVFufJzFmzBjV+cK25fAm7zwJIYQQT9h5EkIIIZ5kHra11CbEYJedsaMFrfZl1KhR\nqqMTfS12cu1tt92mOimU9uc//1m1nahbG+zk9s2bN4dGGpPiU0hoNh9fffWV6iOPPDL03mWXXRa7\njx1VmyZsa/OFAsCDDz6ouk2bNqrt0n30Z/2iUH/a2QJ//OMfVduR3XYJtAsvvFC1fbxg204bpq0N\nF1xwgerHH388tsyWLVu8j1sqb/LOkxBCCPGEnSchhBDiSUnDtrWhZcuWsdvt5GAberVL2Jx77rmq\nf/rTn6Y6nx2JVllZWWP55s2bq7YrptuwmK2TXW4nH3b19mbNmqFFixap9iPlx4aJ7GjXU089NXEf\n6+czzjhDtR0NmRabw3annXZSTX9uX9iQ7K9//WvVNulBjx49VN99992xx8mXiMFiE298/vnnqm3u\n5DQjbC1dunTxKg+Uzpu88ySEEEI8YedJCCGEeJJ52LbQUWLnnXeeartEmA2H3X///ao/+OAD1ddf\nf31B507DLbfconrz5s2q7aT3tNiwB3OHZk9WI2yTRiTefPPNoXLHHHNMUc4XXZLMhmptDlz6s35R\nqD/t4wObcMEmFJg5c6bq3/3ud6ptmHfBggUF1cOXgw8+WLUdeZ6PcniTrieEEEI8YedJCCGEeMLO\nkxBCCPGkzk9Vsdx7772x2//yl7+ovuqqq1S3a9dOtc1UYZ+j2qxAAPDGG2+otgmzbbJtOwT8uuuu\nS1X3NNgpBvb5VPScpG5jFy2wyaxtlhcgnDz7hz/8oeqk6VnWj3YNzmj5xYsXq/7Rj36Utto1Qn/W\nL+yz7759+6qeMGGCajulxD6Tj36+VdhFOOzzdABo3bq1aptZy7ad1pt2CotNMv/f//3fsefORzm8\nyTtPQgghxBN2noQQQognmYdtbXgp7bqBvthMQlZbbJYMOwR8//33D5WLDvuv4sorr1QdnXIQx4wZ\nM1TbLB5piQ635nSA4pOVN+36gTarj51GBQCHH364ahs+23nnnWOPazNeWX/07NkzVM5mvUqC/qz7\nFNOf9nGW1Xad0CeffFK1zcpj2067TrGdzgIAhxxyiOqXXnpJdf/+/VV/+umnsfW4+OKLVdcXb9Lx\nhBBCiCfsPAkhhBBPMgvbTpgwAYsXL0bXrl1127Jly1SvWbNGdefOnbOqhpI2W8fYsWNjt9tQrc0a\nY8O+hYYbkti0aVPi6Dfij483gcL8+be//U21DU1Fz2PX2nzooYdUJ2V3GT58uOovvvgi9N4VV1yh\n+vLLL1dNf9YPStl2Dhw4MFZb7rvvvtjt0UTy7du3jy1n1wm1j8WKGapNIktv8s6TEEII8YSdJyGE\nEOJJZmHbNWvWYNWqVZgyZUqNZUsRtk3ChssA4IknnlBtRz2OHj1atZ0o/NFHH6m24YF33nlHtQ1V\n2JGYANCmTZtU9bLrL5LC8PEmUDx/PvLII6HXdkTigQceqHrQoEE1HstOJLejdqPYyfH2/Gn8meRN\ngP7Mkrrcdn722Weq841itW3kfvvtp7p3796q63vbyTtPQgghxBN2noQQQogndSK3rZ2EC2S3zmIc\nr776auJrmxe0e/fuqrt166Z6xYoVqu2aea+99ppqOzou7RqONm+kDYGQ0pOUYKNQjjvuuFidBpvL\n89vf/nboPRv2svl07TqOdsQ4/Vl/KUXbuXz5ctW/+MUvVEfDo7btPOWUU1Qff/zxqnv16qW6vred\nvPMkhBBCPGHnSQghhHiSedjWhhGiIYYkbLm99tpLtR2pZZe/KQQbLgDC4Vl7voULF6qePn167P42\nxBKtlfIAAA23SURBVLDnnnuqPuKII7zrtW7dOtVNmjT5Wj1J4dR1b+Zj/vz5qqP+skuUrV69WvWJ\nJ56o+g9/+EPi/mmgP7Onrvjz6quvVr1hwwbVQ4YMCZWzYdjTTjtN9Zdffql61KhRqut728k7T0II\nIcQTdp6EEEKIJyUdbZs0EixfSMIu1WR1IaPKPvnkk9hjAghNTLarm9uRira+NretHcFowyTTpk1T\nbUebAcDKlStjdUVFhWoRCS2zQ4pPPj8l+TMLb+Zj/fr1qu0E8QEDBoTK2Xy2d911l+qZM2eqtsuW\nJfnT+jH6mv4sLaVuO99++23VNlS7atUq1W3btg3tc+2116q24daG2nbyzpMQQgjxhJ0nIYQQ4klm\nYdvBgweH8moC6UeMpRllNmbMGNV2KZ3oxN04Tj31VNXRsK0Nedlww+OPP656yZIlscdNqvdOO+2k\nOhp62LJli+pdd91VNXOFZkdd9iYAbNu2TbXNHxrN7VnFP/7xj9DrPn36qP7Wt76l2o4Y79evn+qn\nn35atfWn9SZAf5aKuuBP2w7aEP/EiRNVX3PNNaHjnnDCCbHni/qzChuqrY9tJ+88CSGEEE/YeRJC\nCCGeZBa2HTNmTGh0H5B8a552dGLS/h988IHqaLijinnz5sVqO4kcAHbbbTfV48aNiz3fK6+8otou\npZMUJtl9991V29FqQDgsYcMj9rgMkRUXH29G30uiEG8CYU8mhW333nvv2H1PP/300Gt7/kmTJsUe\ny2InqFt/Wm8C9GepKGXb+eabb6q+4IILVK9du1b10qVLVdtHWZdcckmqc1t/JtW9PradvPMkhBBC\nPGHnSQghhHgixc77JyJ9AUyaNGlS3jBVWpJu59Pc8ieFNPJNmu3atatqu5yNHUl2ww03qLbhDRs6\nmDt3rur+/fsnnm/27Nmq7VJndkJ8s2bNMHnyZBxyyCEAcKBzbnLiAUkidcmb0XKWF154QbXNQxpN\nhpCGyspK1Tb8lvMSAOD8889XbUeVW28C9GfWlMOfVo8cOVK1zY/cuXNn1XbpPLvsGODvT+vN+th2\n8s6TEEII8YSdJyGEEOIJO09CCCHEk8wTw6cZmlzocOuk7Ukx/4ceekj18OHDQ+9ddtllqi+99FLV\n//znP1XbbBY2ybzNAGPXBR0/frzqo446KnQ+OzXmq6++iq1vy5YtU2enIelJO2y+kKkq+Y6b5E+b\nIciukZhEvvouWrRItfWnzTz0xBNPqL7++utV2wTbAP1ZakrRdtq1iS12LIedIvK9731PdRpvRs+X\nxpv1pe3knSchhBDiCTtPQgghxJPMYy1pwgq1CZP50qJFC9U208rGjRtD5UaPHq3ahiUOPPBA1cuX\nL1edNJTaZnaxw6ij2KkIlmhSblJ80vqsNmEyX6w/bVais846S7X1Zo8ePVTbdRGBdP78zW9+o/rY\nY49VbYf/9+zZM7G+9Gf2lKLtTAp3Wn7605+qTvImkM6fDant5J0nIYQQ4gk7T0IIIcSTkg6RGzVq\nlOp84YU0YTLf7WkZMmSIapt96b333lNtMxTZ0O7WrVtVd+zYUbVNppwPmxnDjj7bunVr6Nik+DQU\nbwLp/GlHNK5cuVJ1UigMoD/LSVb+XLdunWo7kvb+++9XbWcg5GN7azt550kIIYR4ws6TEEII8SSz\nsO3q1auxatUqtGnTRredeOKJsWU3bNiQVTUUm/R42LBhqfaxIYaDDz5Y9auvvqrarinXpUsX1dEJ\n5lUsXrw49NqGKGy4wdKoUSM0atQoVZ1Jzfh4E6ib/kzyJlA8f1pvAvRnqShl23nxxRfHagvbznh4\n50kIIYR4ksWdZ3MAmDVrFoB0D3yjcy3tkjSTJxdnBZliHrPq2oDw/Dw7Z6pdu3ax+y5btiz0euHC\nhanOadJoNc9XjuTF25tA2J9ZeLPYxy2WP9N6E6A/iwTbTtSftjOL9TzPAfDXoh6UWL7rnHuy3JWo\nj9CbJYH+rCX0Z+YU1ZtZdJ67ADgeQCWA7B8WbT80B9AZwFjn3Jdlrku9hN7MFPqzQOjPzMjEm0Xv\nPAkhhJCGDgcMEUIIIZ6w8ySEEEI8YedJCCGEeMLOkxBCCPGEnSchhBDiCTvPMiMi+4nINhHpXnNp\nQkqLiDTL+XNQuetCSJRy+jN155mr4Nbc7+jPVhEZkWVFfRGRDiKyJFe3pp77jjTXtVFEZorIDVnV\nFYDXfCER2U1ExorIQhHZICLzROS3ItKi5r0bJvXFnyIyWETeEpHVIjJfRG6txTHuMNe1WUQ+FZG7\nRCQ+wWeJEZFGIvK8iHwmIutFZIGIPCYiHcpdt3JBfzY8f/rceXYEsHvu9w8BrAKwm9l+T1JFfSpU\nRB4H8G4t93UAnkNwbfsC+B2A20Xk6rjCIrKD2EzI2bMVwN8BnJCr30UATgJwbwnrUNeo8/4UkYMA\nPA/gHwAOAHAugLNE5Je1ONwkBNfWGcBPAfwAwO15zl3q/8OXAJwOoDuAMwB8A8D2nHmI/mxo/nTO\nef8AOB/A8pjtxwPYBuA4AFMAbATQD8BTAJ6MlH0QwL/M6x0AjAAwF8BaBH/8k2tZvx8BGANgMIKO\npqnn/nH1fQ3Ayzl9GYBFAE4DMAPAJgAdcu9dntu2HsDHAC6JHOf/AZiae38igKG5OnavzbWa414L\nYGYhx2goP3XVnwB+A+C1yLahCBrSZh7HuQPAm5FtTwCYk9OD467TnO/9nP9mAbgRuWQpufd7AHgj\n9/4H5m82qMDP5AwAG8rtjbrwQ382DH9m9czzdgTfrnoCmJlyn1sQfBO4CMG3gAcAPC0i/aoKiMgi\nEbku30FE5AAAP0Fg0GKmT1oPoCr86wC0BTAcwHkA9gewQkQuBnA9gGsQfMgjANwlImfk6tYawTe7\ndwF8C8Hf6e6Ya6jxOiPl9wRwCoDxtbmw7ZBy+bMZvp52bQOAnRB80y+EqD+B8HXOEJGBAB4G8Ovc\ntqsAfB+BXyEiOyDw53IAByHw912I/B+JyEQReSBtxUSkPYCzEXwBJTVDf9YHf2bwzWkrgIGR7Xm/\nOQFoCWAdgAMiZf4M4I/m9WsALs5Trx0R3O2dGqlPre88AQiC8OhGAL/Ibft+7rj7RPb7HMB3Ittu\nBTAup4cDWACgsXn/akTuPGu6TlPu/3J/t20A/maPuz3/1GF/noQgSnE6gjuFvRBEH7ZGfVPD9YW+\n2SO4O1kO4PEarvN1AFdHtl2M6juCk3PXubN5/zu5Yw0y254EMCJFPX8LYE3On+MBtC63N+rCD/3Z\nMPyZ1WLYkzzL74cgee/rkWeHTRB8eAAA59yAGo7zGwBvO+eezb2WyG8fhorISbk6AEHYwcbs1zjn\nPql6ISLtAFQA+Evk8WcjAFWruPYAMMU5t8W8PxERUlxnFZcDaIPgW9qdCL6x/STlvtszZfGnc+4F\nEbkZwCMARiL4Nn47gsZlq2ed+onIagTLCjZG8Iz+x5Ey0evsDaCviNxmtjUC0Dj3rb4HgE+dc8vN\n+xMR+f9xzp2Tso63AbgfQFcEd0aPIgjLkfzQn9XUWX9m1Xmujbzehq8PTmpi9E4Ibr2PBRDNeu+z\nusDRAPYRkfNyryX3s1pERjjn7vQ41hgEd4WbACx0ua8qhug1Vi2+918InmlaqjpLQRFDyc65JQCW\nAJglImsA/FtEbnXOrSzWORoo5fInnHN3IQjld0TwbbwXgF8heFblw1RUPy9f4JyLa9z0OnONaksE\nYbJ/xdRrW65MMf35JYK/1yciMgfAbBE5wDkX/f8gYejPr9erzvkzq84zyhcA+kS29QGwNKc/RNDB\ndHLO1XaELACciCBuX8XhCMIbBwOY73msNc45H8N8DmAZgK7mzjfKNAAni0gjY6b+nvVKomq0mte0\nHAKgdP5UnHOLAV3DcY5z7mPPQ2z08adzzonI+wD2c87dl1BsGoBuIrKz+XbfH8VpsKr82SxvKRIH\n/RlQp/xZqs7zFQBXishZACYDuBDAPsh9+M65FSJyL4D7RKQ5glvxtgg6v6XOuZEAICKvI4ibPxJ3\nEufcHPtaRPbKyenOuU3Fv6zQuZ2I3IJgSss6AOMQhFL6AWjunLsfwJ8A/ALAwyJyD4Jh0sOjx6rp\nOnPh5LYIwh5rETzMvxvBs9WlcfuQvJTEnyLSGMEgiJdym85C8PmfnNWFRbgFwDMisghA1Re8Pgie\nt9+C4Bv/fAB/kmBec3sEfg0hIiMBTHPOxU5hEJHDEITg3gSwEoHPb0PQ+L1XzAvaTqA/66A/S5Jh\nyDn3PIJRUf+D6hj1U5Ey1+bK3IzgIl4EMAjBwrBVdAOwSyF1keqMPv1qLu1HroO8CsD3EAyjfgXA\nOciFPJxzqxAY8WAEQ7RvRjA6N0pN17kRwBUIhmx/jOBZ50gED/qJJyX0p0MwKnoCgHcQPGYY4pz7\nd1UBqc6YcmZhVxVzcudeAHAqgoEh7yHwzw9Q7c+tCAZgtEMwIvw+AHHJQTohmMOXxHoEDe/LCKZt\nPQTgLQDHOOe2FeNatifoz7rpz+1uMWwRGQLgMQDdnHPRZwuElBUR6YkgorCfc+7zcteHEAv9Wc32\nmNt2CIBb2XGSOsoQAPdv7w0TqbPQnzm2uztPQgghpFC2xztPQgghpCDYeRJCCCGesPMkhBBCPGHn\nSQghhHjCzpMQQgjxhJ0nIYQQ4gk7T0IIIcQTdp6EEEKIJ+w8CSGEEE/+P9U6Puxxz2uPAAAAAElF\nTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9e00c88>"
+       "<matplotlib.figure.Figure at 0x7f2056ba3e80>"
       ]
      },
      "metadata": {},
@@ -1577,16 +1606,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[  26    0    1  950    0    3    0    0    0    0]\n",
+      "[[  85    0    0  895    0    0    0    0    0    0]\n",
       " [   0    0    0 1135    0    0    0    0    0    0]\n",
-      " [   0    0   75  957    0    0    0    0    0    0]\n",
+      " [   0    0   46  986    0    0    0    0    0    0]\n",
       " [   0    0    0 1010    0    0    0    0    0    0]\n",
-      " [   0    0    0  955   27    0    0    0    0    0]\n",
-      " [   0    0    0  884    0    8    0    0    0    0]\n",
-      " [   0    0    0  935    0    1   22    0    0    0]\n",
-      " [   0    0    0 1019    0    0    0    9    0    0]\n",
-      " [   0    0    0  970    0    0    0    0    4    0]\n",
-      " [   0    0    1 1008    0    0    0    0    0    0]]\n"
+      " [   0    0    0  959   20    0    0    0    3    0]\n",
+      " [   0    0    0  847    0   45    0    0    0    0]\n",
+      " [   0    0    0  914    0    1   42    0    1    0]\n",
+      " [   0    0    0  977    0    0    0   51    0    0]\n",
+      " [   0    0    0  952    0    0    0    0   22    0]\n",
+      " [   0    0    1 1006    0    0    0    0    0    2]]\n"
      ]
     }
    ],
@@ -1611,7 +1640,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "collapsed": false
    },
@@ -1646,7 +1675,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "collapsed": false
    },
@@ -1657,73 +1686,73 @@
      "text": [
       "Finding adversarial noise for target-class: 0\n",
       "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  73.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    299, Training Accuracy:  89.1%\n",
-      "Time usage: 0:00:18\n",
+      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 1\n",
-      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  46.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  42.2%\n",
-      "Optimization Iteration:    299, Training Accuracy:  45.3%\n",
-      "Time usage: 0:00:21\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    299, Training Accuracy:  75.0%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 2\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:20\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 3\n",
       "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
       "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    200, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:19\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 4\n",
-      "Optimization Iteration:      0, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    299, Training Accuracy:  90.6%\n",
-      "Time usage: 0:00:20\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    299, Training Accuracy:  82.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 5\n",
-      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    299, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:21\n",
+      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 6\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    299, Training Accuracy:  87.5%\n",
-      "Time usage: 0:00:22\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 7\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  79.7%\n",
-      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    299, Training Accuracy:  89.1%\n",
-      "Time usage: 0:00:21\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    299, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 8\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
       "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:22\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 9\n",
-      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    299, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:22\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  84.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    299, Training Accuracy:  90.6%\n",
+      "Time usage: 0:00:01\n",
       "\n"
      ]
     }
@@ -1748,7 +1777,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "collapsed": false
    },
@@ -1783,7 +1812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1791,9 +1820,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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xtpOz58blSpKlL094vz5K8XuvXtoOaY4kiXVV/2Tbmyy27CS4gTHWzSavY5bO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\nv8+kR2spReVsC94eLTdJiI/bh87HHoxMUr5yclOu/5l94DB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K1Jw/gE0F/Aj5grvEVcnly+1/52HD7F5XD7Fyb2rXNcunFMuLp9n2KxfFElSTN/bd1Sad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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9b4cc88>"
+       "<matplotlib.figure.Figure at 0x7f205683b2b0>"
       ]
      },
      "metadata": {},
@@ -1838,7 +1867,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "collapsed": true
    },
@@ -1893,7 +1922,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {
     "collapsed": false
    },
@@ -1904,23 +1933,23 @@
      "text": [
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   0.0%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    300, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    400, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:38\n",
+      "Optimization Iteration:      0, Training Accuracy:   3.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 12.0% (1200 / 10000)\n",
+      "Accuracy on Test-Set: 14.4% (1443 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  25.0%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:14\n",
+      "Optimization Iteration:      0, Training Accuracy:  42.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    199, Training Accuracy:  89.1%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9553 / 10000)\n"
+      "Accuracy on Test-Set: 95.3% (9529 / 10000)\n"
      ]
     }
    ],
@@ -1937,7 +1966,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "collapsed": false
    },
@@ -1948,23 +1977,23 @@
      "text": [
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  23.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  26.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  21.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  32.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  32.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  29.7%\n",
+      "Optimization Iteration:    400, Training Accuracy:  34.4%\n",
       "Optimization Iteration:    499, Training Accuracy:  26.6%\n",
-      "Time usage: 0:00:37\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 84.5% (8448 / 10000)\n",
+      "Accuracy on Test-Set: 72.1% (7207 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  84.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  75.0%\n",
       "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:14\n",
+      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 94.7% (9472 / 10000)\n"
+      "Accuracy on Test-Set: 95.2% (9519 / 10000)\n"
      ]
     }
    ],
@@ -1983,7 +2012,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
     "collapsed": false
    },
@@ -1994,203 +2023,203 @@
      "text": [
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:37\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:    300, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    499, Training Accuracy:  90.6%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 20.2% (2019 / 10000)\n",
+      "Accuracy on Test-Set: 23.3% (2326 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  29.7%\n",
+      "Optimization Iteration:      0, Training Accuracy:  34.4%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:17\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.0% (9605 / 10000)\n",
+      "Accuracy on Test-Set: 95.6% (9559 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  78.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
-      "Time usage: 0:00:38\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    300, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    400, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    499, Training Accuracy:  67.2%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 25.8% (2576 / 10000)\n",
+      "Accuracy on Test-Set: 42.2% (4218 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  43.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:14\n",
+      "Optimization Iteration:      0, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.4% (9540 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9555 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  64.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
-      "Optimization Iteration:    300, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
-      "Time usage: 0:00:38\n",
-      "\n",
-      "Accuracy on Test-Set: 27.3% (2732 / 10000)\n",
-      "\n",
-      "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  34.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:15\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  43.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  70.3%\n",
+      "Optimization Iteration:    400, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  71.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9554 / 10000)\n",
+      "Accuracy on Test-Set: 46.4% (4639 / 10000)\n",
+      "\n",
+      "Making the neural network immune to the noise ...\n",
+      "Optimization Iteration:      0, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:01\n",
+      "\n",
+      "Accuracy on Test-Set: 95.5% (9545 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    200, Training Accuracy:  32.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    499, Training Accuracy:  40.6%\n",
-      "Time usage: 0:00:38\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  46.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  50.0%\n",
+      "Optimization Iteration:    499, Training Accuracy:  48.4%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 71.0% (7096 / 10000)\n",
+      "Accuracy on Test-Set: 56.5% (5648 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.1% (9608 / 10000)\n",
+      "Accuracy on Test-Set: 95.8% (9581 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  87.5%\n",
       "Optimization Iteration:    400, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:40\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 14.8% (1479 / 10000)\n",
+      "Accuracy on Test-Set: 15.6% (1557 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:14\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.7% (9570 / 10000)\n",
+      "Accuracy on Test-Set: 95.6% (9557 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    499, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:40\n",
+      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 14.8% (1485 / 10000)\n",
+      "Accuracy on Test-Set: 17.4% (1745 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.7% (9571 / 10000)\n",
+      "Accuracy on Test-Set: 96.0% (9601 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  60.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  67.2%\n",
-      "Optimization Iteration:    300, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    400, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  67.2%\n",
-      "Time usage: 0:00:41\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 36.8% (3678 / 10000)\n",
+      "Accuracy on Test-Set: 17.6% (1762 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  51.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  20.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.1% (9606 / 10000)\n",
+      "Accuracy on Test-Set: 95.7% (9570 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    400, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    499, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:40\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    300, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    400, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    499, Training Accuracy: 100.0%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 13.3% (1334 / 10000)\n",
+      "Accuracy on Test-Set: 12.8% (1281 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.9% (9593 / 10000)\n",
+      "Accuracy on Test-Set: 95.9% (9587 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  64.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  78.1%\n",
       "Optimization Iteration:    499, Training Accuracy:  84.4%\n",
-      "Time usage: 0:00:39\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 21.1% (2106 / 10000)\n",
+      "Accuracy on Test-Set: 24.9% (2493 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  23.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  25.0%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.1% (9613 / 10000)\n",
+      "Accuracy on Test-Set: 96.0% (9601 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  37.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    499, Training Accuracy:  54.7%\n",
-      "Time usage: 0:00:38\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  50.0%\n",
+      "Optimization Iteration:    300, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  64.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  65.6%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 51.9% (5194 / 10000)\n",
+      "Accuracy on Test-Set: 45.5% (4546 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.1% (9606 / 10000)\n",
+      "Accuracy on Test-Set: 96.2% (9615 / 10000)\n",
       "\n"
      ]
     }
@@ -2216,7 +2245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "collapsed": false
    },
@@ -2227,403 +2256,403 @@
      "text": [
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    300, Training Accuracy:  79.7%\n",
       "Optimization Iteration:    400, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  70.3%\n",
-      "Time usage: 0:00:41\n",
+      "Optimization Iteration:    499, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 33.5% (3353 / 10000)\n",
+      "Accuracy on Test-Set: 29.2% (2921 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  42.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  29.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.0% (9600 / 10000)\n",
+      "Accuracy on Test-Set: 96.2% (9619 / 10000)\n",
       "\n",
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    200, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    400, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:      0, Training Accuracy:   1.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
       "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:40\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 94.8% (9476 / 10000)\n",
+      "Accuracy on Test-Set: 94.4% (9437 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:      0, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.6% (9660 / 10000)\n",
+      "Accuracy on Test-Set: 96.4% (9635 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  39.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    499, Training Accuracy:  84.4%\n",
-      "Time usage: 0:00:41\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  42.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  60.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:    400, Training Accuracy:  70.3%\n",
+      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 30.9% (3095 / 10000)\n",
+      "Accuracy on Test-Set: 28.7% (2875 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
       "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:14\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.0% (9602 / 10000)\n",
+      "Accuracy on Test-Set: 96.4% (9643 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    200, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  25.0%\n",
-      "Optimization Iteration:    499, Training Accuracy:  10.9%\n",
-      "Time usage: 0:00:41\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    499, Training Accuracy:  12.5%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 89.9% (8994 / 10000)\n",
+      "Accuracy on Test-Set: 94.3% (9428 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9647 / 10000)\n",
+      "Accuracy on Test-Set: 96.9% (9685 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  65.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  60.9%\n",
-      "Time usage: 0:00:41\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  60.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  64.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:    499, Training Accuracy:  82.8%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 50.6% (5060 / 10000)\n",
+      "Accuracy on Test-Set: 34.3% (3427 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  31.2%\n",
+      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9654 / 10000)\n",
+      "Accuracy on Test-Set: 96.6% (9657 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    400, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:   7.8%\n",
-      "Time usage: 0:00:40\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  17.2%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 94.5% (9446 / 10000)\n",
+      "Accuracy on Test-Set: 94.3% (9435 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
       "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:17\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.7% (9666 / 10000)\n",
+      "Accuracy on Test-Set: 96.6% (9664 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    200, Training Accuracy:  29.7%\n",
-      "Optimization Iteration:    300, Training Accuracy:  45.3%\n",
-      "Optimization Iteration:    400, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    499, Training Accuracy:  50.0%\n",
-      "Time usage: 0:00:40\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  20.3%\n",
+      "Optimization Iteration:    200, Training Accuracy:  40.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  54.7%\n",
+      "Optimization Iteration:    499, Training Accuracy:  64.1%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 51.8% (5181 / 10000)\n",
+      "Accuracy on Test-Set: 48.4% (4837 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  59.4%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:17\n",
+      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9649 / 10000)\n",
+      "Accuracy on Test-Set: 96.5% (9650 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
       "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  17.2%\n",
       "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  14.1%\n",
-      "Time usage: 0:00:38\n",
+      "Optimization Iteration:    400, Training Accuracy:   1.6%\n",
+      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9545 / 10000)\n",
+      "Accuracy on Test-Set: 95.7% (9570 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  90.6%\n",
-      "Time usage: 0:00:17\n",
+      "Optimization Iteration:      0, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.6% (9660 / 10000)\n",
+      "Accuracy on Test-Set: 96.7% (9667 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  43.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  87.5%\n",
-      "Time usage: 0:00:39\n",
+      "Optimization Iteration:    100, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  79.7%\n",
+      "Optimization Iteration:    400, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    499, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 22.8% (2283 / 10000)\n",
+      "Accuracy on Test-Set: 23.7% (2373 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  21.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  26.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9645 / 10000)\n",
+      "Accuracy on Test-Set: 96.3% (9632 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:43\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  14.1%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9546 / 10000)\n",
+      "Accuracy on Test-Set: 92.0% (9197 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:24\n",
+      "Optimization Iteration:      0, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.0% (9696 / 10000)\n",
+      "Accuracy on Test-Set: 96.3% (9632 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    200, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  89.1%\n",
-      "Time usage: 0:00:40\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 21.8% (2176 / 10000)\n",
+      "Accuracy on Test-Set: 23.0% (2297 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  28.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
       "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:16\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9647 / 10000)\n",
+      "Accuracy on Test-Set: 96.6% (9663 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
       "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    400, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    499, Training Accuracy:  10.9%\n",
-      "Time usage: 0:00:44\n",
+      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  20.3%\n",
+      "Optimization Iteration:    499, Training Accuracy:  21.9%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 92.2% (9224 / 10000)\n",
+      "Accuracy on Test-Set: 88.2% (8824 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.7% (9672 / 10000)\n",
+      "Accuracy on Test-Set: 96.7% (9665 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  21.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  29.7%\n",
-      "Optimization Iteration:    400, Training Accuracy:  28.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  37.5%\n",
-      "Time usage: 0:00:44\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  40.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:  56.2%\n",
+      "Optimization Iteration:    499, Training Accuracy:  62.5%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 72.9% (7290 / 10000)\n",
+      "Accuracy on Test-Set: 44.0% (4400 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.8% (9675 / 10000)\n",
+      "Accuracy on Test-Set: 96.4% (9642 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  17.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
       "Optimization Iteration:    300, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:   6.2%\n",
-      "Time usage: 0:00:42\n",
+      "Optimization Iteration:    400, Training Accuracy:  20.3%\n",
+      "Optimization Iteration:    499, Training Accuracy:   7.8%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 94.9% (9494 / 10000)\n",
+      "Accuracy on Test-Set: 94.6% (9457 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:20\n",
+      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.0% (9703 / 10000)\n",
+      "Accuracy on Test-Set: 96.8% (9682 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  45.3%\n",
-      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  78.1%\n",
-      "Optimization Iteration:    400, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    499, Training Accuracy:  87.5%\n",
-      "Time usage: 0:00:55\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  65.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  90.6%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 21.3% (2133 / 10000)\n",
+      "Accuracy on Test-Set: 18.1% (1809 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  23.4%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:21\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.8% (9680 / 10000)\n",
+      "Accuracy on Test-Set: 96.8% (9682 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:55\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  28.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  18.8%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 93.2% (9324 / 10000)\n",
+      "Accuracy on Test-Set: 84.1% (8412 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:20\n",
+      "Optimization Iteration:      0, Training Accuracy:  84.4%\n",
+      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.7% (9668 / 10000)\n",
+      "Accuracy on Test-Set: 97.0% (9699 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  21.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  45.3%\n",
-      "Optimization Iteration:    300, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  60.9%\n",
-      "Optimization Iteration:    499, Training Accuracy:  70.3%\n",
-      "Time usage: 0:00:46\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  46.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  70.3%\n",
+      "Optimization Iteration:    499, Training Accuracy:  75.0%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 45.9% (4594 / 10000)\n",
+      "Accuracy on Test-Set: 36.8% (3678 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
+      "Optimization Iteration:      0, Training Accuracy:  48.4%\n",
       "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:18\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.0% (9703 / 10000)\n",
+      "Accuracy on Test-Set: 97.0% (9699 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  14.1%\n",
       "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  14.1%\n",
-      "Time usage: 0:00:47\n",
+      "Optimization Iteration:    300, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 96.1% (9608 / 10000)\n",
+      "Accuracy on Test-Set: 96.2% (9625 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:18\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.2% (9722 / 10000)\n",
+      "Accuracy on Test-Set: 97.2% (9720 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  25.0%\n",
-      "Optimization Iteration:    200, Training Accuracy:  26.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  42.2%\n",
-      "Optimization Iteration:    400, Training Accuracy:  34.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  43.8%\n",
-      "Time usage: 0:00:48\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  23.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  43.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  37.5%\n",
+      "Optimization Iteration:    400, Training Accuracy:  45.3%\n",
+      "Optimization Iteration:    499, Training Accuracy:  39.1%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 68.0% (6798 / 10000)\n",
+      "Accuracy on Test-Set: 64.9% (6494 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  75.0%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:16\n",
+      "Optimization Iteration:      0, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.4% (9743 / 10000)\n",
+      "Accuracy on Test-Set: 97.5% (9746 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
       "Optimization Iteration:    400, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    499, Training Accuracy:   1.6%\n",
-      "Time usage: 0:00:52\n",
+      "Optimization Iteration:    499, Training Accuracy:   4.7%\n",
+      "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 97.3% (9728 / 10000)\n",
+      "Accuracy on Test-Set: 97.1% (9709 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:26\n",
+      "Optimization Iteration:      0, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.4% (9741 / 10000)\n",
+      "Accuracy on Test-Set: 97.7% (9768 / 10000)\n",
       "\n"
      ]
     }
@@ -2657,7 +2686,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -2670,14 +2699,14 @@
       "Noise:\n",
       "- Min: -0.35\n",
       "- Max: 0.35\n",
-      "- Std: 0.272709\n"
+      "- Std: 0.270488\n"
      ]
     },
     {
      "data": {
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rm4rTWdXmtvtXjz+eX9t3df5076dvnvg9fu65/Nf2Aj6SVJEhLEkVGcKSVJEhLEkVGcKS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\nUWC8ewAAAABJRU5ErkJggg==\n",
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9e4d0b8>"
+       "<matplotlib.figure.Figure at 0x7f2057188518>"
       ]
      },
      "metadata": {},
@@ -2697,7 +2726,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {
     "collapsed": false
    },
@@ -2706,15 +2735,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 97.4% (9741 / 10000)\n",
+      "Accuracy on Test-Set: 97.7% (9768 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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i4ElERGQpsLJtbm4usrOzfa0bW2bYv3+/63pepS0/h+jm1WKjRo3ScZs2bTz3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\nhDo/RaR3nNfjjEz3LxMqQn6KSLaITBO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OnFzLz7KyMt95mJ9Vj01uet8LYpubQGwuTJ06NeEytWvX1vHYsWN1/K9//Sth+wD7/DRz\nE8h8fvLMk4iIyBI7TyIiIkuRlW337t2LXbt2xTzj0rbMlAl16tSJef3555/ruGvXrpFvv2fPnr7T\ni4uLddyqVavI21HVMD/DYX5mXi7mpvm1mccee0zH5jNlzdHWPvjgg8jbFJSbQGbyk2eeRERElth5\nEhERWYqsbNuyZUu0a9cuZloyI2OsXr064TypDCislIp5bY7gEkaYO3pN8UZwWb9+vY6XLVumY5bF\n0o/56Y/5mX25npunnnqqjhcvXqzj+vXr67hLly6h1pVKfnrbnun85JknERGRJXaeREREliIr2xYX\nF6N+/fro0KGDnmYO/BtP0Ol7+/btddy9e3ff+cOUIdL53Lgw6w1TjgCANm3a+MaUfszPCszP3JLL\nuWkzn63Klp888yQiIrIUxZlnbQBYu3YtAGDfvn36jd27d+u4YcOGgSswL/yajh49quPq1av7zr98\n+fKE6wyaJyzbdQXtj01bCgsLy8Pa8eajhJifceb3Yn5mVE7mps18YaQrP23aEUV+ivduvpRXKDIU\nwItpXSmZhimlZmW7EZUV8zNyzM8kMTczIm35GUXn2RhAfwBFAA6mdeVVW20ArQG8rZTakeW2VFrM\nz8gwP1PE3IxU2vMz7Z0nERHRiY43DBEREVli50lERGSJnScREZEldp5ERESW2HkSERFZYueZZSJS\nS0SOicjF2W4LkZeIdHLzs2O220Lklc3jZ+jO021gmfu/91+ZiIyLsqE2ROR/ROQLETkoIptE5PeW\ny08y9uuIiKwTkcki8oOo2mxLRJqIyMsisldEdojIk7nUvkyrDPkpIvkiMltENohIqYj8S0RuSmI9\ns439OiQia0Tkjija7LL6PpuInCYib4vIRvdv8FsReURE6kTVwFxXGfITAESkQESWisg+ESkRkQlJ\nrKMyHD/vE5ElIvK9iGxMZh02w/M1M+KfARgPoCMAcaftD2hkdaVUWTKNS4aIjAVwPYDRAJYBqAeg\nZRKrWgbgEgA1AfQG8AyAGgBuDdhuRvcTwF8A1AXQx/1/BoDHAfwyg23IJZUhP7sDKAFwlfv/hQCe\nFJFDSqlnLNajAMwFcAOAHwAYDGCKiBxQSj3mnVlEqgFQKnNf6i4D8CqA/wWwA87vYRqA+mB+Ajma\nnyLSDcAbAO4CMBRAKwB/FhGllLLt3HP9+HkSgJcA/APAFUmtQSll/Q/A1QB2+kzvD+AYgIsArABw\nCEAPt5GzPPP+CcB843U1AOMArAdQCueHP9iyXafCGZmjZzL7ZaxnEoC/e6Y9D2CtGxf47af73mUA\nPgNwAMBXAO6EOxiF+35nAIvd91caP7OLLdp3LpwDVJ4x7VIAhwE0SmXfT4R/uZqfAW19GsCblsv4\ntXchgPfd+EYAmwD8BMBqNy+auu/d5E47AOBLAL/0rOc/AXzuvr/EzecyAB1T3M8xANZkOzdy4V+u\n5ieAhwEs9Ey7DMAeALUs1pPTx09Pu24AsDGZZaO65jkRwG8A5AFYE3KZ8QB+CuBaAD8E8ASAl0Wk\nR/kMbgn29jjrKIDzQ80TkdUiUiwis0Tk9GR2wuMAnE9RQEUZy9zP1SLyIzifsH/nTrsFzi9ntNv+\nanA+2e0E0A3ASACT4SmLueWEJ+K0pSeALUqpQmPa23A+TXX3X4QM2cpPPyfDyYdUefOzIZz8GgGg\nC4BdInIdnLPB0XAOQuMATBaRywFARBrAyc9P4HxAmwjgIe+GbPdTRFoAGALgw2R2rArKVn7WwvHD\nAh6EU73rGrIdQXLp+JkWUTxVRQG4Uym1sHyCiMSZHRCRugB+C6CXUupzd/J0EekDpwT7T3faV3DK\nQEHawilj3QbnE/b3cH4RC0TkXKXUMeu9cdrXA86p/RvGZL/9vBfA/Uqp8gfQFbnXDMbCOQgNBNAC\nzpnxTneZcQBe92xyPYDNcZrUDMAWc4JS6qCI7ENseYiOl8389K63D5ySa7+wy/isQwAMANAXzif+\ncjXhnFV+Y8x7H4BblFJvupO+FZFz4BygXgFwDZyD5Y1KqaNwDmhtAfzBs9lQ+ykir8P5QFsbThn3\nZtv9q4KymZ9vA7heRH4KYA6A5nBKuACQ9AlIDh4/0yKqh2Evs5y/E5w/sI8lNlNqwCkdAQCUUhcm\nWE81d5kblVKLAf2kghI45aiPLdrUw+2MTnL/zYXTKZu8+3k2gHwRecCYVh3ASe6nps4A1pX/4l1L\nUHHdAwCglBpq0U6TwPLmjioqW/mpici5cP7o71RKLbJsDwBcJiKD3DYATllsovH+fk/HeQqcg+FM\nz8G4OioONJ0BrHA7znJL4GGxnzfBObPOA/AgnA+yvw25bFWWlfxUSs0TkbsBTAcwG87Z4kQ4pWPb\n65GV8fhpJarOs9Tz+hiOv7O3hhHXg3PQ74fjPxnZPF1gk/u/LmcqpTaKyF44F79tfI6K6z3fKf+L\n2Xo/3aStC6cMMd87o1LqmDtPOjq3zQBOMyeISG04P8ctvkuQKVv5CQAQka4A3gHwkFLKe1YX1gIA\no+Bcz9yo3As4Bu8+1nf//zmc3DaVd5Zp/fCllNoCJx+/EpH9AN4RkQlKqd0JFq3qspafSqnJcEr5\nzeCUR88E8H9wzuZs5PLxMy2i6jy9tgE4xzPtHABb3fgLOH/ArZRSn6SwncXu/53gfuJyk6ABgG8t\n13VIKRU6YZRSSkQ+A9BJKTU1YLZVANqJSCPj01Mv2CfEEgCniUiecd3zYjg/w1R+flVVpvITbpn0\nXQBTlVKTEs0fx36b/ASwAcB2AG2VUnMC5lkFYLDnzsdeKbTRVP4E5ppx5yI/GcvPckqpzYCu3K1V\nSn1puYpcPn6mRaY6z78BuFlErgSwHMAvALSH+8tXSu0SkSkAprpnUEvg3PBwPoCtSqnZACAiHwN4\nTik13W8jSqkvROQddz03wSk7PORuc7HfMmk2HsArIrIJzjUDwEnyjkqp8XA+UZUAmCHO9/KaALjP\nuxIRmQ1glVLqfr+NKKU+E5GFAJ4RkVvgfGJ7BMDznpIGhZOR/HQ7zvfglGufFJHy6sFRFfEzMN2D\n03gAE0Xke7cdteGU5Gorpf4I5+tO9wGYJs53ozvCuSnDux+J9nMQnJ/PMjhnF13h/B2+p5Ta6rcM\nxZWp/DwJzk0677qTroTz+x8c1Y55ZOT46c7TCsApcL7GeJJbDQKAr5RSB8I0NiMjDCml3oBzV9Sj\nqKhRv+SZZ4w7z91wPmH8Fc7ZVJExWzsAjRNs7mdwPoktAPA+gF0ABpaXtaRiRIrkvtsTh1JqHoD/\nBjAIwKdwOuxfwy15uJ/mL4XzS/sEwFQAfl9ub4XEN/5cDuds+gM4ifa2uy2ylMH8vBLO7/46ABuN\nf/pavFSM6NPDfxXJczvIW+DcRLISzkF5KCrycw+cA2V3OF8huBvO3bleifbzEIBfwcn/L+Fc65wN\n525QspTB/FRw7opeBOcmo74ABiil3imf4QQ6fv4OzgeRO+H8TJa7/7qEbW+Vexi2iOTB+UTcSSm1\nIdvtITKJyAAAzwJop5TyXvsiyioePytUxbFtBwD4Y1X/xVPOGgBgAjtOylE8frqq3JknERFRqqri\nmScREVFK2HkSERFZYudJRERkKe3f8xSRxnBGui9CEqOvUKDaAFoDeDvq7wSeyJifkWF+poi5Gam0\n52cUgyT0B/BiBOslxzAAs7LdiEqM+Rkt5mfymJvRS1t+RtF5FgHAzJkzkZeXhwULFug3CgoKdPzR\nRx/puHfv3oErC1o+01asWKHjFi1a6HjZsoqxjaNsX2FhIYYPHw7EfumZ7BUBzM90Y36mRRFgl5tA\ncH7mYm4CJ05+RtF5HgSAvLw85OfnY82aisfR5efn67i0tNR3upf53ksvveQ7z1VXXZV8a0OqUaNi\nHOYuXSoGoejfv7+OCwsrHq+5e3fF2Ne9elUMD1pcXByz3latEo9Xv23bNuzatav8Jcs5qWF+gvmZ\no6xz0/te0PRcyU0gffkZJjeB6PKTNwwRERFZYudJRERkKbKnqixcuBAlJSU4+eSTfd+/4IILdBxU\nUgBiywqZKDEEMUsNQfLy8hLOE6/UsH//fh3Xq1dPx3v27Il5j1LH/PTH/Mw+m9wEwpVkcz03gcqX\nnzzzJCIissTOk4iIyFJkZdsDBw6gtLQ0VLkgmyWFXHL48GHf6e3bt8fevXsz3JoTW9T5OWPGDB0/\n8sgjOv700091XL16dev1ZhPzMzNschPg8bNcpvOTZ55ERESW2HkSERFZiqxsW1BQEPfL5evWrdNx\n27Zto2pGpdKoUaNsN6HKiDo/zfKsd4SVyor5mRk2uQnw+Fku0/nJM08iIiJL7DyJiIgssfMkIiKy\nFNk1z0RYpw/v66+/Pm7AbopWqvkZdNv8iYj5mVmZOnZu375dx02aNMnINqMQVX7yzJOIiMgSO08i\nIiJLkZVtv/zyS5SVleHss8/W02rVqhXV5nzddtttOn7xRf8HtG/dujXm9bBhwxKu97TTTtPxww8/\nnGTrwmvQoAHq1q0b+Xaqkqjzs2bNmgnniTfgfJBcHE2G+Zle2Tp2LlmyJOb1f/zHf+h41qxZCZfP\nxdwEostPnnkSERFZYudJRERkKbKybbVq1VC9enW8/vrretoVV1yh43QOij1w4EAd//Wvf004//Dh\nw3U8c+bMmPeCyrtBy2fChg0bsGXLloxu80SXyfy0Lc+a5S/vsmHWlenyGfMzvTKZm2PHjtXxpEmT\nYt679dZbfZcJys+weX6i5CfPPImIiCyx8yQiIrIUWdk2Ly8P+fn5MQMcHz16NJJthSnVfvDBBzo+\n55xzdNyyZcuY+Vq3bq1js70333yzjs1S7y233KLj8847L1yDQ/jwww913KdPH1Srxs856ZTJ/Awj\nnaUss3wWVYmM+RmdTOamt1RrqlOnjo6Zn8djxhMREVli50lERGQpsrLtBx98gOLiYgwZMqRiYyel\nb3Mi4jv9F7/4hY6feeYZ33nMskGXLl0Ct3HgwIGE7UhnqdbUp0+fSNZLjqjz8/HHH9dxr169fOcJ\nKlklM3hCpjE/oxN1bl577bW+070DIaSSn2vXrtXxrl27Yt7r1q2b7zLe55T6CTuubybyk2eeRERE\nlth5EhERWYqsbNu3b1/k5+ejsLBQT8vLywu1bJiyQNBYi+kshT300EPWy/htL9U7yubOnRtTBqHU\nRZGf3vKUn3Tm54wZM3S8YMECHd94441W22N+5paoj51vvfWW7/R4eWCud+PGjToePXp0qHYF+eqr\nr3T89ddf69gcrMYcb9x8NFrz5s1j1jVmzBjfbUSVnzzzJCIissTOk4iIyFJkZdsFCxZgzZo1KZeE\nTj/9dB1v2rTJd554Y4EmEq995sAKq1ev1nGPHj2S3l5Yn376qY6HDBmC5cuXR7KdqiqK/Awq20aV\nnwsXLvSd/uSTT+q4U6dOOjYfpZcq5md0osjNZcuW6Xjz5s06Vkrp2HyEIwCcccYZOm7atKmOzVLt\nfffd57uub775Rsfe8cI7dOig4+eff17H69evD9iTCtu3b9ex+cg2r0zkJ888iYiILLHzJCIishRZ\n2bagoCBmbEYAWLRokY7PPPNMHTdq1ChwPeaXXYNKXmHuHAx7d6FZOnjqqad85/mv//qvwOXLmeNC\nmubNmxfzetCgQb7zNW7cWMdFRUUxd7hR6qLIz1WrVvnOk878LC4u1vG0adN0/OCDD+r4jjvu0PGz\nzz7rO535mbtschMIzk8zN/v27es7jznYzL333hvz3qhRo3Rs5uerr76q45/+9Ke+6zUHYjAHrgGA\n3r1763jDhg06HjdunO+6TGYJ2Ps4SVMm8pNnnkRERJbYeRIREVmKrGxbbv/+/To2T9Hbt2+vY/MO\nKq8wdycG3c0YpkQ2ePDgmPeCxk688MILdRzvLq9yl156qe/0oDKYV2lpqY5r1aqV1cdlncjSmZ8N\nGjTwnSeV/PTOY94BWatWLR23atVKx+Y4qCtXrvTdBvMz94XJTSA4P3/zm98k3IZ5h6x3vHDzTlrT\n4cOHfaebeXvRRRcl3DYQuy/mZQjzUZFmqfa9994Ltd5M5CfPPImIiCyx8yQiIrLEzpOIiMhS5Nc8\nzfp42BFy8/utAAAgAElEQVQzUhlZw3ZZ7635Qa655pq0bzues846S8dr1qzBsWPH0rZuqhBVfvbr\n10/Hf/7zn3V8/fXXW7Quvs6dO/tOr1+/vo7NUY+Yn5VLqrlpDqJuXhcN+kqIef0zG8y/jeHDh6e0\nrkzkJ888iYiILLHzJCIishR52Xbx4sU6DnsbfBTMcsbtt9+u43gjT5glL/MZeOksfwVZunSpjnv2\n7Blz6zWlT1T5aQ7K/cUXXyScP5nB4998800df/zxxzr+3e9+p+Nq1aL5fMz8jF4yuWk+H9Mcgef8\n88/XcceOHa3bYpuf8eY33zPba45KZH7Nplu3bnaNRWbyk2eeRERElth5EhERWYq8bBum3BDvtD6M\nMKO2PP300zp+6KGHQq3XLNVmWs+ePbO27aokE/k5depUHU+YMEHHDRs2DNxG0PRzzjlHx+YoLObz\nFs3Rg8477zyrtobF/Ixe2FKtmSPmtwfMkn1Q+T7sAwnC5mei6UDss0XNZ9KaDy5IprRsykR+8syT\niIjIEjtPIiIiS5GXbc3nD5qDV5tSvXs1zPLPPPOMjs0v4NasWTNmvunTp6fUFqpcMpGf5pfPzWcm\njh8/3np75ns7duzwneeVV16xbSLloDC5CcTmxJw5c3RsHtv27duXcNmwbJd5//33Y15PmTJFx+Zd\n6amWajONZ55ERESW2HkSERFZirxsG6/cYCvsnWF+zGdwml+YNQdMoKon0/l56qmn6rioqCjh/PE0\nbtzYd3rXrl11vGrVKuv1Um5IJjfNZ7maRo8erWMzb8KM2Q2Ey8/CwkIdP/jggzr+8Y9/HDOfebmi\ndevWobafi3jmSUREZImdJxERkaXIyrZbtmxBSUkJWrRokbZ12pa23n33XR0HjW3YqVOnlNpElVO2\n8vOWW27RsXnJYPLkyWlrx9y5c3U8ZsyYtK2XMiOV3Gzfvr2Ot23bpuNhw4bp+L333tOxeSf4L37x\ni5h1/eUvf9HxN99847u9vXv36njUqFE6fv75522aXSnxzJOIiMgSO08iIiJLkZVtjx49iiNHjkS1\n+lBmzJjhOz3sHWbZtHLlSh2bdwpTeuRCfpql2rFjx+p44sSJKa3XLNc1adIkpXUFYX5GJ5XcvP/+\n+3VsXraqX7++jpcsWaJjcwAD72AGQcw7es1Hh5kDHmRbJvKTZ55ERESW2HkSERFZiqxs27x5c7Rp\n0yam/FCjRo2oNqeZXzwP0q9fv8jbkSrzLjZKv2zlZxCzVDt06FAd5+fnx8x3+eWX69h8DNnDDz+s\n4+7du0fRxBjMz+ikKzcvuugi3+nm47oeeOABHW/dujXUes3SsPlYvVySifzkmScREZEldp5ERESW\nIh/bNtOlsE8++cR3+j/+8Q/rdZkljbvvvtt3nlTG243n/PPPT9u6KFg2S7WmWbNm+cbmHZMAsGzZ\nMh3v3LlTx926ddNxQUGBjpmflVcmcjPouOZl5lE6S7WVOT955klERGSJnScREZGlyMq2u3fvxo4d\nO2Ief2OOL1u3bt2U1h90um9+AdgUNGDCpEmTYl6bX1bfsGFDwm2bDh8+rGPzKe7xljXbPm/ePB0P\nGjTId3lKj2zlZxDzDluT947JkpISHQeNfcr8rNxyLTfDzhcmN73bN9nmp7dNmc5PnnkSERFZYudJ\nRERkiZ0nERGRpciueYoIRCRmmlmrT6aGH1QrN6c/++yzOh44cKCOe/XqFWobCxcu1LE5AHIYr732\nWsJ5vHX6pUuX6jjbA5VXJdnKT5OZC0HzmKMIAbGjY23evFnHzZo1S9g+5mflYJOb3veC2OYmYJ+f\nqeQmYJ+fZm4Cmc9PnnkSERFZYudJRERkKbKy7d69e7Fr1y40atRIT0vmVN7W+PHjdTx37tyE848e\nPTrmtTmqR1RtNJmDNJuKi4t13KpVq8jbUdVkKz9t1alTJ+b1559/ruOuXbtGvn3mZ+ZVltwEYvMz\nV3ITyEx+8syTiIjIEjtPIiIiS5GVbVu2bIl27drFTEtmZIzVq1cnnCdo9IuRI0fqOOhusTPOOCPm\ndb169SxaF+6ONFO8EVzWr1+vY3MAcJbF0i8X8jMMpVTM62rV7D7vMj8rn8qSm0Bsftrmpnf7tvnp\nbXum85NnnkRERJbYeRIREVmKrGxbXFyM+vXro0OHDnqaOfBvPEGn7+3bt9dx9+7dfecPU4ZI53Pj\nwqw3TDkCANq0aeMbU/oxPyswP3NLLuemzXy2Klt+8syTiIjIUhRnnrUBYO3atQCAffv26Td2796t\n43hPIzcv/JqOHj2q4+rVq/vOv3z58oTrDJonLNt1Be2PTVsKCwvLw9qhFqAgzM8483sxPzMqJ3PT\nZr4w0pWfNu2IIj/FezdfyisUGQrgxbSulEzDlFKzst2Iyor5GTnmZ5KYmxmRtvyMovNsDKA/gCIA\nB9O68qqtNoDWAN5WSu3IclsqLeZnZJifKWJuRirt+Zn2zpOIiOhExxuGiIiILLHzJCIissTOk4iI\nyBI7TyIiIkvsPImIiCyx88wyEekkIsdEpGO220LkJSK13Py8ONttIfLKZn6G7jzdBpa5/3v/lYnI\nuCgbGrKN+SIyW0Q2iEipiPxLRG5KYj2zjf06JCJrROSOKNrssvq+kIjcEPD7OCIiDaJqZC6rDPlZ\nTkT+R0S+EJGDIrJJRH5vufwkY7+OiMg6EZksIj+Iqs3JEpHaIrKqqn9AZH7mVn6KyGaf38HIxEtW\nsBmer5kR/wzAeAAdAYg7bX9AI6srpcpsGpWC7gBKAFzl/n8hgCdF5JBS6hmL9SgAcwHcAOAHAAYD\nmCIiB5RSj3lnFpFqAJTK3JdmnwMwxzNtNoADSqm9GWpDrqkM+QkRGQvgegCjASwDUA9AyyRWtQzA\nJQBqAugN4BkANQDcGrDdjO6n4VEA6wB0ysK2cwnzM7fyUwEYA2AGKn4HdsdOpZT1PwBXA9jpM70/\ngGMALgKwAsAhAD0AvARglmfePwGYb7yuBmAcgPUASuH88Acn0z7Pdp4G8KblMn7tXQjgfTe+EcAm\nAD8BsBrAYQBN3fducqcdAPAlgF961vOfAD53318C4DIAZQA6prCPzQEcAfCTVH9eJ8K/XM1PAKfC\nGTmmZ4r7NwnA3z3Tngew1o0L/PbTfe8yAJ+5+fcVgDvhDpbivt8ZwGL3/ZXGz+ziJNo5xN1WF3cd\nSef4ifSP+Zn9/IRz/L4+lf2M6prnRAC/AZAHYE3IZcYD+CmAawH8EMATAF4WkR7lM7glhNst23Iy\ngJ2Wy/g5AOdTFOB8amkIYCSAEXAODrtE5DoA/wvnU1tnOMk8WUQuBwC3pPoGgE8AnAvn5/SQd0NJ\n7Oc1cPbxDeu9qpqylZ8FcPIoT0RWi0ixiMwSkdOT2QkPb34Csfu5WkR+BGAagN+5026BU10Z7ba/\nGpwc2gmgG5z8ngzPZQURWSIiT8RrjIg0B/BHAMPgfLik8JifEeen614R2SYiy0RklLv+0KJ4qooC\ncKdSamH5BBGJMzsgInUB/BZAL6XU5+7k6SLSB04J4Z/utK8AhB6X0F1+MIB+YZfxWYcAGACgL5xP\nVOVqwjmr/MaY9z4Atyil3nQnfSsi58BJgFfgdHIHAdyolDoKJ2HaAviDZ7NW++mud4a7Toovm/nZ\nFs5lgNvgVCi+h3OgWCAi5yqljlnvjdO+HgCuQOyHJ7/9vBfA/Uqp8gckFonIBABj4XyIGwigBZwz\nj53uMuMAvO7Z5HoAm+O0R+CUw36vlPpSRDrB8rp+Fcb8jDg/XQ/BOYnZDeACOMf2UwHcHXa/onoY\n9jLL+TvBGbj3Y4nNlBpwSpsAAKXUhWFXKCLnwvmh3qmUWmTZHgC4TEQGuW0AnLLDROP9/Z6O8xQ4\n5dOZnmSvjopfZGcAKzyd3BJ4WO5nXzhJPz3sMpS1/KzmLnOjUmoxoJ+kUQKnnP+xRZt6iMg+OH/D\nJ8G5Rn+bZx7vfp4NIF9EHjCmVQdwkvupuzOAdeUHJtcSVFwTAgAopYYmaNsYZzb1iPs6/tGfvJif\nFaLITyilzBOWL0REAfi9iNyj3LpuIlF1nqWe18dw/J29NYy4HpxPIv1w/Ccj66cLiEhXAO8AeMjz\nQ7KxAMAoOCWnjT4/UO8+1nf//zmca5qm8s5SkP5P4L8EsFQptTrN6z2RZSs/N7n/64cLKqU2ishe\nAK0s1gM4OVZ+vfw75X+zhd5P96BaF06ZbL53RqXUMXeedORnXwAXisgRY5oA+JeITFdKWd8BX8Uw\nPz3SnJ9+/gHnA0gLABvCLBBV5+m1DcA5nmnnANjqxl/A6WBaKaU+SWVDbpn0XQBTlVKTEs0fx36l\nVPBTgo+3AcB2AG2VUt47YcutAjDYc2dZr2QbKCInA/hvADcnuw4CkLn8XOz+3wnuGYGINAPQAMC3\nlus6ZJOfSiklIp8B6KSUmhow2yoA7USkkfHpvhfsD1jXo+LDJOBURv4fnBuIUnuSctXE/HSkKz/9\nnAvnZ7g97AKZ6jz/BuBmEbkSzh/PLwC0h/vLV0rtEpEpAKaKSG04v7iGAM4HsFUpNRsARORjAM8p\npXxLlG7H+R6ccu2TInKa+9ZRFfEzBt1f/ngAE0Xke7cdteHcLVdbKfVHONeB7gMwTZzvTnWEc9Hb\nux9x99MwHM4v/OW07UjVlJH8VEp9ISLvuOu5Cc5NFA+521zst0yajQfwiohsQsVXnc6BcxfseDif\n+EsAzBDne81N4ORrDBGZDWCVUup+v40opTZ45i+Dc+b5jVIq0bUoOh7zM435KSIXAOgK5xsU++Fc\n8/wdgOlKqQNhG5uREYaUUm/AuSvqUVTUqF/yzDPGneduOJ8w/grgYjgPhi3XDkDjOJu6EsApAK4D\nsNH4p2v1UjGiTw//VSTP7SBvgfPJeyWcpB8K5wI2lFJ74NzA1B3OLdp3w7k71yvRfpa7FsBspdT3\nKTe+CstgfgLOd/y+gHNZ4H0AuwAMLL8sIBUjplyR2l4dTyk1D06lYhCAT+EcEH+NivwsA3ApnL+h\nTwBMBeA3OEgrxH5vMdTmk2s1MT/Tnp+H4HxL4iM4+zoGwP+52wqtyj0MW0QGAHgWQDullPfaAlFW\niUgenBspOnnP4IiyjflZoSqObTsAwAR2nJSjBgD4Y1U/MFHOYn66qtyZJxERUaqq4pknERFRSth5\nEhERWWLnSUREZCnt3/MUkcZwRrovQhKjA1Gg2gBaA3g76u+snsiYn5FhfqaIuRmptOdnFIMk9Afw\nYgTrJccwALOy3YhKjPkZLeZn8pib0UtbfkbReRYBwMyZM5GXl4cFCxboNwoKCnT80Ucf6bh3796B\nKwtaPtNWrFih4xYtWuh42bKKsY2jbF9hYSGGDx8OxH7pmewVAczPdGN+pkURYJebQHB+5mJuAidO\nfkbReR4EgLy8POTn52PNmorH0eXn5+u4tLTUd7qX+d5LL73kO89VV12VfGtDqlGjYhzmLl266Lh/\n//46LizU4ylj9+7dOu7Vq2L42uLi4pj1tmqVeLzlbdu2YdeuXeUvWc5JDfMTzM8cZZ2b3veCpudK\nbgLpy88wuQlEl5+8YYiIiMgSO08iIiJLkT1VZeHChSgpKcHJJ5/s+/4FF1yg46CSAhBbVshEiSGI\nWWoIkpeXl3CeeKWG/fv367hevXo63rNnT8x7lDrmpz/mZ/bZ5CYQriSb67kJVL785JknERGRJXae\nREREliIr2x44cAClpaWhygXZLCnkksOHD/tOb9++Pfbu3Zvh1pzYmJ/2mJ+ZYZObAPOzXKbzk2ee\nRERElth5EhERWYqsbFtQUBD3y+Xr1q3Tcdu2baNqRqXSqFGjbDehymB+2mN+ZoZNbgLMz3KZzk+e\neRIREVli50lERGSJnScREZGlyK55JmLW6adMmRLzXqdOnXRsDhxcVX399dfHDdhN0YrqOtIbb7yh\n49mzZyecv3PnzjGv77nnHh2LSPoalgLmZ2bxGqedqPKTZ55ERESW2HkSERFZiqxs++WXX6KsrAxn\nn322nlarVi3feZ9++umY12eddZaOzUGPa9eubdWGadOmWc0PAJs2bdJxzZo1fed5++23dZyJ0T0a\nNGiAunXrRr6dqsQmP1P1+9//XsefffaZjuMNOB/kq6++0rF5SWPEiBFJti51zM/0ymRuxjNx4kQd\n33XXXTqeNGmSjs844wwd5+pIR1HlJ888iYiILLHzJCIishRZ2bZatWqoXr06Xn/9dT3tiiuu0HH1\n6tV1fOqppx63bLmjR4/qOOiZbC+++KJV24YNGxa47Omnn261/LZt23Q8cuRIq3aEtWHDBmzZsiWS\ndVdVNvmZjHvvvVfH999/v+88jz32mI7NvwGz/PXUU0/FLPPKK6/o+Oc//7mOb7/9dh2blx4ygfmZ\nXlHnpinepYP333/fd/ro0aN1bOZj2MsQQeXdjz76SMe9e/cOta4wospPnnkSERFZYudJRERkKbKy\nbV5eHvLz82MGODZLsKbXXnst5vV7772XcP1muTRM2dYstabK3F6PHj3Stl7Thx9+qOM+ffrElLIp\ndTb5mYy1a9f6Tp81a5bv9KBSVr169WJe//jHP9bxu+++q+PNmzfrePLkyTo2y7npxPyMTtS5mYx0\n3kl7zTXX6NjM7507d+p4z549Oh40aJD1NjKRn8x4IiIiS+w8iYiILEVWtv3ggw9QXFyMIUOGVGzs\nJP/NNWzYMOb1ZZddlnD91157bcJ5gkq1tnfnAkDTpk11bD43Lqo7bPv06RPJeslhk59hmaVaM8fM\nL5KbgkphyQyeYDK3HVXZlvkZnShy0xQ2v2688UYdz5kzR8dmGdW84zvIW2+9FfP6hRde0PH//M//\n6Pjxxx/XcePGjUO1MUgm8pNnnkRERJbYeRIREVmKrGzbt29f5Ofno7CwUE/Ly8sLtWyYssJ3333n\nOz1MqbZDhw469pYd2rVrF6aJCZn7kOqdanPnzg28e5OSE0V+mmWuIKmWalMtZ/ltj/mZW6I+dgbx\n5sH06dN911tQUJBwXVu3btWxWab1MkvAZm5XhvzkmScREZEldp5ERESWIivbLliwAGvWrEn5lNsc\na9Z8HNM777yj43hj1frNY37RPGz7gsohqd4ZGeTTTz/V8ZAhQ7B8+fJItlNVRZGfQd58800d2+ZL\nvPbVr19fx+admSbmZ+UTRW4GjXdsbsObK7/85S99l+nXr5/v8qYwA90AwLp16wK3n4pM5CfPPImI\niCyx8yQiIrIUWdm2oKAgZmxGAFi0aJGOzzzzTB2bgw54mV92feaZZ3znMUu1Znm2Tp06On722Wd1\nPHz4cB0fPHgwZl21a9fWcSplBHPbpnnz5sW8Dhq30bzzrKioCBs3bky6LXS8KPLTvFN7xYoVOu7S\npYuOlVK+60nm7sK77rrLd/rKlSsTLsv8zF02uQkE56eZm2EuO3nzzlyveYet+Ugy065du3R80UUX\n+c7j3Y45+IwpTH7GG/M2E/nJM08iIiJL7DyJiIgsRVa2Lbd//34db9iwQcft27fX8fbt2wOXN8sK\nAwYM0PEnn3yi43//93/XcVAJ13ykj7keb6nCvDPSHE/ytttu0/Gpp56qY7O8YM5/6aWX+u5P2Mfr\nlJaW6rhWrVpZfyTRiSqd+Xnrrbfq2Bx8w8xDM3fMx+qVlZXp+LnnntOx+fgmAOjYsaOOv/7668B2\nlTt8+LCOa9asqWPmZ+4Lk5tAcH6GuewU727boMsHLVq00PG3336r46DycefOnWNeh8mxypCfPPMk\nIiKyxM6TiIjIEjtPIiIiS5Ff8zSvuYS9BT/MfOY8Zt3dvI171apVobZn2rdvn+/0e+65J+GyQV9D\nSMZZZ52l4zVr1uDYsWNpWzdViCo/R4wYoeMJEyb4zmN+ZSpoZCzzKy9A7HVO89q995mJ5czBvT/6\n6KM4LbbD/IxeVLmZzLJXXnmljl9++WUdm3keZOzYsSlv31Ym8pNnnkRERJbYeRIREVmKvGy7ePFi\nHYe9zdjWGWecoeOgEsHMmTN13Lp1ax1feOGFMfMFjbhhTu/atauOzTLx0KFDdXzFFVfo+LzzztNx\nmIHEAWDp0qU67tmzZ8yt15Q+mcjPoJL/ggULdGyWcKdMmaLjxx57LGaZbt266dgsmZmjGJlfmbr6\n6quTaHFizM/oZSI3w5o9e7aOzbJtEPMSVtivwKRTJvKTZ55ERESW2HkSERFZirxsG6bckOppfZhB\ntc15Jk2apGPzjjYAmDZtmu98pg4dOui4WjX/zx+vvvqqjs3BjB966KGY+YJG5ejZs6fvdEqvbOan\nOdi2OY9ZjvVu2yzJmu9dcsklOjZHo4kK8zN6YUu1yTxUwHbZp59+OuHyJvNBHObDNjIlE/nJM08i\nIiJL7DyJiIgsRV62LS4u1nGrVq1850n17ivb5cPOf/3111ut984779SxWTo7dOiQjkeOHBmzjHkX\nMGVeZc7PoGVee+01HRcVFVmvi3JDmNwEohsYwfTwww/7LtOsWTMd/+EPf0i6HZURzzyJiIgssfMk\nIiKyFHnZNl65wVYqd5Vl4ou55gAImbjjkVJ3Iuan+czPOXPmpG29lFm5kptA7J3hW7Zs0bHtpa0T\nCc88iYiILLHzJCIishRZ2XbLli0oKSlBixYt0rbOSy+9VMePPvqojn/4wx/q+KKLLkrb9oKYAyC8\n//77Og56nJmpXbt2kbSJ7ESRn5m4NJAK8/Fm5557bhZbQvHkSm6+++67MW0qd9ppp+m4c+fOqTWs\nEuOZJxERkSV2nkRERJYiK9sePXoUR44cSes6H3jgAR2bXyD+6quvdGw+YqxmzZq+61m7dq2OP/zw\nw5j3RETHixYt0rF3DFwbderU0fH48eNDLbNy5Uodn3322Ulvm/xFkZ+2Ur0DMkjQnd7pLNUyP6OT\nC7kJxD4yz/Tggw9muCX2MpGfPPMkIiKyxM6TiIjIUmRl2+bNm6NNmzYx5YcaNWqktM7Nmzf7Tt+7\nd6+Or732Wqt1Hjt2LOZ10CPGgtSqVUvHbdq00XGDBg107B3PNgxznyj9osjPMG655RYdX3zxxZFs\n45VXXtFxjx49ItkG8zM62crNv/3tbzGvN23apGPzuGoe83JVJvKTZ55ERESW2HkSERFZinxs23SW\nG8477zwdFxYW6nj79u0Jl33xxRd1PGzYsFDbM++SPeWUU3T8q1/9Ssd33323b5yq888/P23romCZ\nKIeZRowYoeOpU6fq2BwAxLxbNuwX5d98800dm+W+UaNG6TiZywdBmJ/Ry3RuKqUC33vqqad0/KMf\n/Sht24zqjvNM5CfPPImIiCyx8yQiIrIUWdl29+7d2LFjBxo3bqynlZaW6rhu3brW67zhhht0PHny\nZB2bpS1zAATT/PnzddyzZ8/AbZjrnTRpku88Zqnhkksu0bE5kELQAA3mskBsqWLevHk6HjRoUGAb\nKXVR5KcpqBxlXnow7whs27atju+4447A9Ya5/GDOM3DgQB0zPyuHbOVm9erVY+YzB9UYM2ZMwvWW\nlJToON7lBm+OlbPNT2+ZN9P5yTNPIiIiS+w8iYiILLHzJCIishTZNU8RiRlkHYit1SdTwzfr3S1b\ntvSdp3nz5jo2a+LmsuaAx02bNo1Z3rzOaY5o1KxZs4Tte+211xLO463TL126VMe5MBh0VRF1foaZ\nbubCmjVrdPzFF1/oeM6cOTHLmNc5zWub5vWeDh066Lhjx446Zn5WDja56X0vSJjcHDp0aMx75ldX\ngpY3j5/9+vXTse2xE7DPTzM3gcznJ888iYiILLHzJCIishRZ2Xbv3r3YtWsXGjVqpKclcyofNXMU\nIQD4/PPPddy1a9fItx/0tRnzeaWtWrWKvB1VTa7lp/m1hMsvv1zH3q8ImPk6c+ZM33Xt27cvbe1i\nfmZetnLTvOQFAI8//riOmzRp4ruMmY+5cuwEMpOfPPMkIiKyxM6TiIjIUmRl25YtW6Jdu3Yx05IZ\nGWP16tUJ50llQGHvYMi2z/MMuqM3SLwRXNavX6/jZcuW6ZhlsfRjfvpjfmZftnIzXp4G5Y6Zn7a5\n6d2mbX5625vp/OSZJxERkSV2nkRERJYiK9sWFxejfv36MV/YNgf+jSfo9L19+/Y67t69u+/8YUpk\n6XxuXJj1hilHAECbNm18Y0o/5mcF5mduyeXctJnPVmXLT555EhERWYrizLM2UPFoMPM7Z7t379Zx\nw4YNA1dgXvg1HT16VMfm43PM+ZcvX55wnUHzhGW7rqD9sWlLYWFheVg71AIUhPkZZ34v5mdG5WRu\n2swXRrry06YdUeSneO/mS3mFIkMBvJhwRkrWMKXUrGw3orJifkaO+Zkk5mZGpC0/o+g8GwPoD6AI\nwMG0rrxqqw2gNYC3lVI7styWSov5GRnmZ4qYm5FKe36mvfMkIiI60fGGISIiIkvsPImIiCyx8yQi\nIrLEzpOIiMgSO08iIiJL7DyzTEQ6icgxEemY7bYQeYlILTc/L852W4i8snn8DN15ug0sc//3/isT\nkXFRNjRkG08TkbdFZKOIHBSRb0XkERGpk3jpmPXMNvbrkIisEZE7omo3AKvvCxkHNO/vYHBUDcx1\nlSE/AUBECkRkqYjsE5ESEZmQxDomGft1RETWichkEflBFG1Ohoh0FpF5IrJdRHaLyEIR+c9stytb\nKkt+lhORpiKyxW1bTctlc/r4CQAi8oSILHPb9/dkNmozPF8zI/4ZgPEAOgIQd9r+gEZWV0qVJdO4\nJJQBeBXA/wLYAad90wDUB/BLi/UoAHMB3ADgBwAGA5giIgeUUo95ZxaRagCUyvyXZn8G4EPj9a4M\nbz+X5Hx+ikg3AG8AuAvAUACtAPxZRJRSyvbguQzAJQBqAugN4BkANQDcGrDtTP4dAsBbAFYAuADA\nEQC3A5gvIq2VUlUxT3M+Pz2eA/AJgAFJLFsZjp/HAPwZzt9OcqPIK6Ws/wG4GsBOn+n93UZdBOcP\n533BWvAAAAchSURBVBCAHgBeAjDLM++fAMw3XlcDMA7AegClcA4Og5Npn2c7YwCssVzGr70LAbzv\nxjcC2ATgJwBWAzgMoKn73k3utAMAvgTwS896/hPA5+77SwBcBqfT72jRvlruz/niVH8+J+K/XM1P\nAA8DWOiZdhmAPQBqWaxnEoC/e6Y9D2CtGxf47aexvc/c/PsKwJ1wB0tx3+8MYLH7/krjZxY61wA0\nd5f5d2NaE3faf2Q7P7L9L1fz01jXrQAWuHlUBqCm5fI5ffz0rO+4v6Ww/6K65jkRwG8A5AFYE3KZ\n8QB+CuBaAD8E8ASAl0WkR/kMIrJJRG4P2wgRaQFgCGLPzpJ1AM6nfMD5ZNUQwEgAIwB0AbBLRK6D\nc9Y7Gs5BaByAySJyudueBnDOPD4BcC6cn9NDPu0Ou59Pi8hWEVkiIsNT2bkqJlv5WQvHD7t2EEA9\nAF1DtiOINz+B2P1cLSI/glOJ+Z077RY4Zwej3fZXg5OfOwF0g5Pfk+Epi7n59kSctmwGsA7ANSLy\nAxGpAeeA+R2cAx/Fl7Xjp4h0BfBbOB18Os8Ec/H4mZIonqqiANyplFpYPkFE4swOiEhdOL+wXkqp\n8j+u6SLSB8D1AP7pTvsKTjk20fpeh/OpqTacMu7NdrsQsy6BU7roC+dTSrmacD4VfWPMex+AW5RS\nb7qTvhWRc+AcoF4BcA2cg+WNSqmjcA5obQH8wbPZRPtZBmAsnA8FB932TReR2kqpp5PYzaokm/n5\nNoDrReSnAObAOUO7y33vdLvdiGlfDwBXwDmwlPPbz3sB3K+UKn9AYpF7zXUsnIPQQAAtAPRUSu10\nlxkH4HXPJtfD6SB9KaXKRKQfnNLdfrct3wHor5QqTXY/q4is5ad7zXwWgF8rpbYk2m4YOXr8TIuo\nHoa9zHL+TnA6uo8l9jdWA86pOQBAKXVhyPXdBOBkOJ/cHoTzSfu3lm26TEQGuW0AnLLYROP9/Z5f\n/ClwDoYzPUlXHRUHms4AVri/+HJL4JFoP93lHzQmfSYiDeGUqNl5JpaV/FRKzRORuwFMBzAbzqfx\niXBKc7bXtXqIyD44f8MnwemobvPM493PswHki8gDxrTqAE5yzzo7A1hX3nG6lqDiulz5fgyN1zB3\nXdPgDHB+A5xrnjfCueaZ71k/HS9bx8+HAfxDKTXHfS2e/23k7PEzXaLqPL2fLo/h+Dt7axhxPTif\nuPrh+E8M1k8XUEptAbAFwFcish/AOyIyQSm1O8GipgUARsGpx29UboHc4N3H+u7/P8fxpanyX7Yg\nvaUQ0z9w/MGT/GUtP5VSk+GUoprBKY+eCeD/4JzN2fgcFdd7vlP+N5Xo/XQPqnXhlAPn+7TrmDtP\nOvJzAIA+ABoopQ67024QkW8BDAcwJQ3bOJFlKz/7AmgvIiPc1+L+2yci45RSDwYvepzKdvy0FlXn\n6bUNwDmeaecA2OrGX8D5AbVSSn2S5m2XP/nV6nZrOJ+MbA5oGwBsB9DW+OTmtQrAYM8ddL0s2xXk\nXDgfGMhexvNTKbUZ0M9wXKuU+tJyFYds8lMppUTkMwCdlFJTA2ZbBaCdiDQyzg57wf6A9QN3Ge9y\nfp0AJZap/BwI57p8ufPh3JjUHUCJ5boq2/HTWqY6z78BuFlErgSwHMAvALSH+8tXSu0SkSkApopI\nbTin4g3h/PK2KqVmA4CIfAzgOaXUdL+NuGWChnDKHqVwbsJ4CMB7Sqmtfsuki3twGg9gooh8D+A9\nOKWUHgBqK6X+CGAGgPsATBOR38O5VX2kz34k2s8hcPbzn3A+2Q2AU5a+L827VVVkKj9PgnOTzrvu\npCvh/P4z9f3c8QBeEZFNcK65As5BuKNSajycM9ISADPc7+U1gU9OichsAKuUUvcHbOdjOCXp50Vk\nIpwcvRnAaXC+wkJ2MpKfSqm15msRaemGhUYFIRKZPH6687SHc8beFEAd90YpAPhCKXUsTJsz8ilQ\nKfUGnLv2HkXFNZSXPPOMcee5G84njL8CuBjOdZNy7QA0jrOpQwB+BedW+y/hXOucDecuNAAxI1L0\n8F9F8txf8C1wLtKvhJP0Q+GW5JRSe+AcKLvDuRX9bjh3l3kl2s+jcMpvS+F8ULgawE1uSZAsZTA/\nFZy7vxfB+eDTF8AApdQ75TNIxQAYV6S2Vz4bV2oegP8GMAjAp3D+Tn6NivwsA3ApgFPg3NE4FYDf\nl9tbIfZ7i97tbIFzw14TODe1/QNAPoCBSqmwd4+SK4P5mdAJcvwEgBfgHDuvgXO373L3X5Ow7a1y\nD8MWkQEAngXQjnf+Ua4RkTw4f9SdlFIbst0eIhOPnxWq4vWHAQAmVPVfPOWsAQD+yI6TchSPn64q\nd+ZJRESUqqp45klERJQSdp5ERESW2HkSERFZYudJRERkiZ0nERGRJXaeRERElth5EhERWWLnSURE\nZImdJxERkaX/DwKd5IMD2nhyAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9bd17f0>"
+       "<matplotlib.figure.Figure at 0x7f20572d0080>"
       ]
      },
      "metadata": {},
@@ -2725,16 +2754,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 966    0    2    0    0    3    5    1    3    0]\n",
-      " [   0 1121    3    2    0    0    1    0    7    1]\n",
-      " [   5    3  989    4    1    1    0   15   13    1]\n",
-      " [   0    0    2  994    0    6    0    6    2    0]\n",
-      " [   1    1    3    0  968    0    3    0    2    4]\n",
-      " [   2    0    0    8    0  878    2    1    1    0]\n",
-      " [   3    1    0    0    3    6  940    0    5    0]\n",
-      " [   0    5   14    5    0    1    0  997    2    4]\n",
-      " [   5    0    4    3    2    2    2    5  949    2]\n",
-      " [   8    8    3    8   13    5    0   20    5  939]]\n"
+      "[[ 972    0    1    0    0    0    2    1    3    1]\n",
+      " [   0 1119    4    0    0    2    2    0    8    0]\n",
+      " [   3    0 1006    9    1    1    1    5    4    2]\n",
+      " [   1    0    1  997    0    5    0    4    2    0]\n",
+      " [   0    1    3    0  955    0    3    1    2   17]\n",
+      " [   1    0    0    9    0  876    3    0    2    1]\n",
+      " [   6    4    0    0    3    6  934    0    5    0]\n",
+      " [   2    4   18    3    1    0    0  985    2   13]\n",
+      " [   4    0    4    3    4    1    1    3  950    4]\n",
+      " [   6    6    0    7    4    5    0    4    3  974]]\n"
      ]
     }
    ],
@@ -2754,9 +2783,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -2772,7 +2801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false
    },
@@ -2781,15 +2810,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 90.0% (8999 / 10000)\n",
+      "Accuracy on Test-Set: 92.2% (9222 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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pRA3tMyVDY6dlbnfKrIM9T+qz6PWZp73/kHRPseuiVH6oz/J4/0zrYtj/jFy+k5KJe583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\nRKLzBAAgUtkN226zzTY+H3r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RFrkziMgGEbmtgGWUx4HDWu0EcCjst4ui2AH7zQTI68Zyt3OFiJwL4AkA9wfT+sMeHQwO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\nAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f29f9f1d400>"
+       "<matplotlib.figure.Figure at 0x7f2056abcdd8>"
       ]
      },
      "metadata": {},
@@ -2800,16 +2829,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 970    0    1    0    0    0    8    1    0    0]\n",
-      " [   0 1128    2    1    0    0    4    0    0    0]\n",
-      " [  13    4 1007    2    1    0    0    2    3    0]\n",
-      " [   0    0    2  991    0    9    0    6    2    0]\n",
-      " [   4    6    1    0  949    0   21    0    1    0]\n",
-      " [   2    0    1    3    0  876   10    0    0    0]\n",
-      " [   5    2    0    0    0    1  950    0    0    0]\n",
-      " [   9   27   28    3    8    1    0  949    3    0]\n",
-      " [  34    6   14   11    6   28   71    4  800    0]\n",
-      " [  40   18    5   14  339   75   25  101   13  379]]\n"
+      "[[ 970    0    1    0    0    1    8    0    0    0]\n",
+      " [   0 1121    5    0    0    0    9    0    0    0]\n",
+      " [   2    1 1028    0    0    0    1    0    0    0]\n",
+      " [   1    0   27  964    0   13    2    2    1    0]\n",
+      " [   0    2    3    0  957    0   20    0    0    0]\n",
+      " [   3    0    2    2    0  875   10    0    0    0]\n",
+      " [   4    1    0    0    1    1  951    0    0    0]\n",
+      " [  10   21   61    3   14    3    0  913    3    0]\n",
+      " [  29    2   91    7    7   26   70    1  741    0]\n",
+      " [  20   18   10   12  150   65   11   12    9  702]]\n"
      ]
     }
    ],
@@ -2834,7 +2863,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {
     "collapsed": false
    },
@@ -2919,9 +2948,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:tf-gpu]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-tf-gpu-py"
   },
   "language_info": {
    "codemirror_mode": {

From a2dae09a3ca7e0dbcbc2b87bdc3b28b083ce10fb Mon Sep 17 00:00:00 2001
From: Hvass-Labs <Hvass-Labs@users.noreply.github.com>
Date: Thu, 16 Feb 2017 09:44:14 +0100
Subject: [PATCH 05/61] Create ISSUE_TEMPLATE.md

---
 .github/ISSUE_TEMPLATE.md | 38 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 38 insertions(+)
 create mode 100644 .github/ISSUE_TEMPLATE.md

diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
new file mode 100644
index 0000000..2de1e4f
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE.md
@@ -0,0 +1,38 @@
+# STOP!
+
+Most of the problems people are having are already described in the
+[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
+
+## Python 3.5
+
+These tutorials were developed in **Python 3.5** and may give strange errors in Python 2.7
+
+## Missing Files
+
+You need to **download the whole repository**, either using `git clone` or as a zip-file. See the
+[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
+
+## Questions about TensorFlow
+
+General questions about TensorFlow should either be asked on
+[StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow)
+or [GitHub](https://github.com/tensorflow/tensorflow/issues).
+
+## Suggestions for Changes
+
+The tutorials cannot change too much because it would make the
+[YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)
+too different from the source-code.
+
+## Requests for New Tutorials
+
+These tutorials were made by a single person on his own time. It took a very long time to
+research and produce the tutorials. If a topic is not covered then the best thing is to make
+a new tutorial by yourself. All you need is a decent microphone, a screen-grabbing tool, and a
+video editor. I used the free version of [DaVinci Resolve](https://www.blackmagicdesign.com/products/davinciresolve).
+
+## Other Issues?
+
+Please carefully read the
+[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md)
+and only open an issue if you are still having problems.

From 5e7b5bd0b56a814c25bc82347f60fe1acfeb2424 Mon Sep 17 00:00:00 2001
From: Hvass-Labs <Hvass-Labs@users.noreply.github.com>
Date: Thu, 16 Feb 2017 09:47:44 +0100
Subject: [PATCH 06/61] Update ISSUE_TEMPLATE.md

---
 .github/ISSUE_TEMPLATE.md | 18 +++++-------------
 1 file changed, 5 insertions(+), 13 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
index 2de1e4f..617efab 100644
--- a/.github/ISSUE_TEMPLATE.md
+++ b/.github/ISSUE_TEMPLATE.md
@@ -1,7 +1,6 @@
 # STOP!
 
-Most of the problems people are having are already described in the
-[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
+Most of the problems people are having are already described in the [installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
 
 ## Python 3.5
 
@@ -9,20 +8,15 @@ These tutorials were developed in **Python 3.5** and may give strange errors in
 
 ## Missing Files
 
-You need to **download the whole repository**, either using `git clone` or as a zip-file. See the
-[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
+You need to **download the whole repository**, either using `git clone` or as a zip-file. See the [installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
 
 ## Questions about TensorFlow
 
-General questions about TensorFlow should either be asked on
-[StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow)
-or [GitHub](https://github.com/tensorflow/tensorflow/issues).
+General questions about TensorFlow should either be asked on [StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow) or [GitHub](https://github.com/tensorflow/tensorflow/issues).
 
 ## Suggestions for Changes
 
-The tutorials cannot change too much because it would make the
-[YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)
-too different from the source-code.
+The tutorials cannot change too much because it would make the [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ) too different from the source-code.
 
 ## Requests for New Tutorials
 
@@ -33,6 +27,4 @@ video editor. I used the free version of [DaVinci Resolve](https://www.blackmagi
 
 ## Other Issues?
 
-Please carefully read the
-[installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md)
-and only open an issue if you are still having problems.
+Please carefully read the [installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md) and only open an issue if you are still having problems.

From 74ebebaf37e28ca24a7570cee89faecff62569a4 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 6 Apr 2017 09:26:06 +0200
Subject: [PATCH 07/61] Added requirements.txt for easy pip installation.

---
 requirements.txt | 36 ++++++++++++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 requirements.txt

diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..fd87a52
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,36 @@
+################################################################
+#
+# Python package requirements for the TensorFlow Tutorials:
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# If you are using Anaconda then you can install all required
+# Python packages by running the following commands in a shell:
+#
+#     conda create --name tf python=3
+#     pip install -r requirements.txt
+#
+# Note that you have to edit this file to select whether you
+# want to install the CPU or GPU version of TensorFlow.
+#
+################################################################
+# Basic packages used in many of the tutorials.
+
+numpy
+scipy
+jupyter
+matplotlib
+Pillow
+scikit-learn
+
+################################################################
+# TensorFlow can be installed either as CPU or GPU versions.
+# You select which one to install by (un)commenting these lines.
+
+tensorflow		# CPU Version of TensorFlow.
+# tensorflow-gpu	# GPU version of TensorFlow.
+
+# Builder API for TensorFlow used in many of the tutorials.
+prettytensor
+
+################################################################
+

From f71ee62a1e11f531aaa548c6d3d0eb5bcef191f8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 6 Apr 2017 10:13:50 +0200
Subject: [PATCH 08/61] Updated installation instructions.

---
 README.md | 49 +++++++++++++++++++++++++------------------------
 1 file changed, 25 insertions(+), 24 deletions(-)

diff --git a/README.md b/README.md
index d44a51e..dde8d74 100644
--- a/README.md
+++ b/README.md
@@ -56,7 +56,7 @@ If you want to see the exact versions of the source-code that were used in the Y
 then you can [browse the history](https://github.com/Hvass-Labs/TensorFlow-Tutorials/commits/master)
 of commits to the GitHub repository.
 
-## Installation
+## Downloading
 
 Some of the Python Notebooks use source-code located in different files to allow for easy re-use
 across multiple tutorials. It is therefore recommended that you download the whole repository
@@ -79,16 +79,22 @@ This also makes it easy to update the tutorials, simply by executing this comman
 You can also [download](https://github.com/Hvass-Labs/TensorFlow-Tutorials/archive/master.zip)
 the contents of the GitHub repository as a Zip-file and extract it manually.
 
-## Requirements
-
-These tutorials were developed on Linux using **Python 3.5** (the [Anaconda](https://www.continuum.io/downloads) distribution) and [PyCharm](https://www.jetbrains.com/pycharm/).
-
-There are reports that Python 2.7 gives error messages with these tutorials. Please make sure you are using **Python 3.5** or later!
+## Installation
 
 There are different ways of installing and running TensorFlow. This section describes how I did it
 for these tutorials. You may want to do it differently and you can search the internet for instructions.
 
-### Example Setup
+If you are new to using Python and Linux, etc. then this may be challenging
+to get working and you may need to do internet searches for error-messages, etc.
+It will get easier with practice.
+
+### Python Version 3.5 or Later
+
+These tutorials were developed on Linux using **Python 3.5 / 3.6** (the [Anaconda](https://www.continuum.io/downloads) distribution) and [PyCharm](https://www.jetbrains.com/pycharm/).
+
+There are reports that Python 2.7 gives error messages with these tutorials. Please make sure you are using **Python 3.5** or later!
+
+### Environment
 
 After installing [Anaconda](https://www.continuum.io/downloads), you should create a [conda environment](http://conda.pydata.org/docs/using/envs.html)
 so you do not destroy your main installation in case you make a mistake somewhere:
@@ -99,24 +105,23 @@ Now you can switch to the new environment by running the following (on Linux):
 
     source activate tf
 
-Some of these tutorials use [scikit-learn](http://scikit-learn.org/stable/install.html)
-which can be installed in your new conda environment as follows. This also installs
-NumPy and other dependencies:
-
-    conda install scikit-learn
+### Required Packages
 
-You may also need to install other dependencies, such as:
+The tutorials require several Python packages to be installed. The packages are listed in
+[requirements.txt](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/requirements.txt)
+First you need to edit this file and select whether you want to install the CPU or GPU
+version of TensorFlow.
 
-    conda install jupyter matplotlib scipy pillow
+To install the required Python packages and dependencies you first have to activate the
+conda-environment as described above, and then you run the following command
+in a terminal:
 
-Now you have to install TensorFlow. It is now possible to install the CPU-version of TensorFlow
-directly using pip. We also need the [PrettyTensor](https://github.com/google/prettytensor)
-add-on package so we install that as well:
+    pip install -r requirements.txt
 
-    pip install tensorflow prettytensor
+Note that the GPU-version of TensorFlow also requires the installation of various
+NVIDIA drivers, which is not described here.
 
-It is much more complicated to install the GPU-version because you also need various NVIDIA drivers.
-That is not described here.
+### Testing
 
 You should now be able to run the tutorials in the Python Notebooks:
 
@@ -125,10 +130,6 @@ You should now be able to run the tutorials in the Python Notebooks:
 
 This should start a web-browser that shows the list of tutorials. Click on a tutorial to load it.
 
-If you are new to using Python and Linux, etc. then this may be challenging
-to get working and you may need to do internet searches for error-messages, etc.
-It will get easier with practice.
-
 ## License (MIT)
 
 These tutorials and source-code are published under the [MIT License](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/LICENSE)

From 3269e213801f98931b8d2aa1e0547bdacaa55b8a Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 21 Apr 2017 10:10:37 +0200
Subject: [PATCH 09/61] Added Tutorial #16

---
 16_Reinforcement_Learning.ipynb  | 4758 ++++++++++++++++++++++++++++++
 README.md                        |    2 +
 images/16_flowchart.png          |  Bin 0 -> 154737 bytes
 images/16_flowchart.svg          | 1135 +++++++
 images/16_motion-trace.png       |  Bin 0 -> 15453 bytes
 images/16_problem.png            |  Bin 0 -> 62522 bytes
 images/16_problem.svg            |  770 +++++
 images/16_q-values-details.png   |  Bin 0 -> 101358 bytes
 images/16_q-values-details.svg   |  427 +++
 images/16_q-values-simple.png    |  Bin 0 -> 73449 bytes
 images/16_q-values-simple.svg    |  835 ++++++
 images/16_training_stability.png |  Bin 0 -> 78121 bytes
 images/16_training_stability.svg |  787 +++++
 reinforcement_learning.py        | 1828 ++++++++++++
 requirements.txt                 |    6 +
 15 files changed, 10548 insertions(+)
 create mode 100644 16_Reinforcement_Learning.ipynb
 create mode 100644 images/16_flowchart.png
 create mode 100644 images/16_flowchart.svg
 create mode 100644 images/16_motion-trace.png
 create mode 100644 images/16_problem.png
 create mode 100644 images/16_problem.svg
 create mode 100644 images/16_q-values-details.png
 create mode 100644 images/16_q-values-details.svg
 create mode 100644 images/16_q-values-simple.png
 create mode 100644 images/16_q-values-simple.svg
 create mode 100644 images/16_training_stability.png
 create mode 100644 images/16_training_stability.svg
 create mode 100644 reinforcement_learning.py

diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
new file mode 100644
index 0000000..a3fbaae
--- /dev/null
+++ b/16_Reinforcement_Learning.ipynb
@@ -0,0 +1,4758 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #16\n",
+    "# Reinforcement Learning (Q-Learning)\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "This tutorial is about so-called Reinforcement Learning in which an agent is learning how to navigate some environment, in this case Atari games from the 1970-80's. The agent does not know anything about the game and must learn how to play it from trial and error. The only information that is available to the agent is the screen output of the game, and whether the previous action resulted in a reward or penalty.\n",
+    "\n",
+    "This is a very difficult problem in Machine Learning / Artificial Intelligence, because the agent must both learn to distinguish features in the game-images, and then connect the occurence of certain features in the game-images with its own actions and a reward or penalty that may be deferred many steps into the future.\n",
+    "\n",
+    "This problem was first solved by the researchers from Google DeepMind. This tutorial is based on the main ideas from their early research papers (especially [this](https://arxiv.org/abs/1312.5602) and [this](http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html)), although we make several changes because the original DeepMind algorithm was awkward and over-complicated in some ways. But it turns out that you still need several tricks in order to stabilize the training of the agent, so the implementation in this tutorial is unfortunately also somewhat complicated.\n",
+    "\n",
+    "The basic idea is to have the agent estimate so-called Q-values whenever it sees an image from the game-environment. The Q-values tell the agent which action is most likely to lead to the highest cumulative reward in the future. The problem is then reduced to finding these Q-values and storing them for later retrieval using a function approximator.\n",
+    "\n",
+    "This builds on some of the previous tutorials. You should be familiar with TensorFlow and Convolutional Neural Networks from Tutorial #01 and #02. It will also be helpful if you are familiar with the PrettyTensor builder API in Tutorial #03."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## The Problem\n",
+    "\n",
+    "This tutorial uses the Atari game Breakout, where the player or agent is supposed to hit a ball with a paddle, thus avoiding death while scoring points when the ball smashes pieces of a wall.\n",
+    "\n",
+    "When a human learns to play a game like this, the first thing to figure out is what part of the game environment you are controlling - in this case the paddle at the bottom. If you move right on the joystick then the paddle moves right and vice versa. The next thing is to figure out what the goal of the game is - in this case to smash as many bricks in the wall as possible so as to maximize the score. Finally you need to learn what to avoid - in this case you must avoid dying by letting the ball pass beside the paddle.\n",
+    "\n",
+    "Below are shown 3 images from the game that demonstrate what we need our agent to learn. In the image to the left, the ball is going downwards and the agent must learn to move the paddle so as to hit the ball and avoid death. The image in the middle shows the paddle hitting the ball, which eventually leads to the image on the right where the ball smashes some bricks and scores points. The ball then continues downwards and the process repeats."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Illustration of the problem](images/16_problem.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The problem is that there are 10 states between the ball going downwards and the paddle hitting the ball, and there are an additional 18 states before the reward is obtained when the ball hits the wall and smashes some bricks. How can we teach an agent to connect these three situations and generalize to similar situations? The answer is to use so-called Reinforcement Learning with a Neural Network, as shown in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Q-Learning"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "One of the simplest ways of doing Reinforcement Learning is called Q-learning. Here we want to estimate so-called Q-values which are also called action-values, because they map a state of the game-environment to a numerical value for each possible action that the agent may take. The Q-values indicate which action is expected to result in the highest future reward, thus telling the agent which action to take.\n",
+    "\n",
+    "Unfortunately we do not know what the Q-values are supposed to be, so we have to estimate them somehow. The Q-values are all initialized to zero and then updated repeatedly as new information is collected from the agent playing the game. When the agent scores a point then the Q-value must be updated with the new information.\n",
+    "\n",
+    "There are different formulas for updating Q-values, but the simplest is to set the new Q-value to the reward that was observed, plus the maximum Q-value for the following state of the game. This gives the total reward that the agent can expect from the current game-state and onwards. Typically we also multiply the max Q-value for the following state by a so-called discount-factor slightly below 1. This causes more distant rewards to contribute less to the Q-value, thus making the agent favour rewards that are closer in time.\n",
+    "\n",
+    "The formula for updating the Q-value is:\n",
+    "\n",
+    "    Q-value for state and action = reward + discount * max Q-value for next state\n",
+    "\n",
+    "In academic papers, this is typically written with mathematical symbols like this:\n",
+    "\n",
+    "$$\n",
+    "    Q(s_{t},a_{t}) \\leftarrow \\underbrace{r_{t}}_{\\rm reward} + \\underbrace{\\gamma}_{\\rm discount} \\cdot \\underbrace{\\max_{a}Q(s_{t+1}, a)}_{\\rm estimate~of~future~rewards}\n",
+    "$$\n",
+    "\n",
+    "Furthermore, when the agent loses a life, then we know that the future reward is zero because the agent is dead, so we set the Q-value for that state to zero."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Simple Example\n",
+    "\n",
+    "The images below demonstrate how Q-values are updated in a backwards sweep through the game-states that have previously been visited. In this simple example we assume all Q-values have been initialized to zero. The agent gets a reward of 1 point in the right-most image. This reward is then propagated backwards to the previous game-states, so when we see similar game-states in the future, we know that the given actions resulted in that reward.\n",
+    "\n",
+    "The discounting is an exponentially decreasing function. This example uses a discount-factor of 0.97 so the Q-value for the 3rd image is about $0.885 \\simeq 0.97^4$ because it is 4 states prior to the state that actually received the reward. Similarly for the other states. This example only shows one Q-value per state, but in reality there is one Q-value for each possible action in the state, and the Q-values are updated in a backwards-sweep using the formula above. This is shown in the next section."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Q-values Simple Example](images/16_q-values-simple.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Detailed Example\n",
+    "\n",
+    "This is a more detailed example showing the Q-values for two successive states of the game-environment and how to update them."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Q-values Detailed Example](images/16_q-values-details.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The Q-values for the possible actions have been estimated by a Neural Network. For the action NOOP in state *t* the Q-value is estimated to be 2.900, which is the highest Q-value for that state so the agent takes that action, i.e. the agent does not do anything between state *t* and *t+1* because NOOP means \"No Operation\".\n",
+    "\n",
+    "In state *t+1* the agent scores 4 points, but this is limited to 1 point in this implementation so as to stabilize the training. The maximum Q-value for state *t+1* is 1.830 for the action RIGHTFIRE. So if we select that action and continue to select the actions proposed by the Q-values estimated by the Neural Network, then the discounted sum of all the future rewards is expected to be 1.830.\n",
+    "\n",
+    "Now that we know the reward of taking the NOOP action from state *t* to *t+1*, we can update the Q-value to incorporate this new information. This uses the formula above:\n",
+    "\n",
+    "$$\n",
+    "    Q(state_{t},NOOP) \\leftarrow \\underbrace{r_{t}}_{\\rm reward} + \\underbrace{\\gamma}_{\\rm discount} \\cdot \\underbrace{\\max_{a}Q(state_{t+1}, a)}_{\\rm estimate~of~future~rewards} = 1.0 + 0.97 \\cdot 1.830 \\simeq 2.775\n",
+    "$$\n",
+    "\n",
+    "The new Q-value is 2.775 which is slightly lower than the previous estimate of 2.900. This Neural Network has already been trained for 150 hours so it is quite good at estimating Q-values, but earlier during the training, the estimated Q-values would be more different.\n",
+    "\n",
+    "The idea is to have the agent play many, many games and repeatedly update the estimates of the Q-values as more information about rewards and penalties becomes available. This will eventually lead to good estimates of the Q-values, provided the training is numerically stable, as discussed further below. By doing this, we create a connection between rewards and prior actions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Motion Trace\n",
+    "\n",
+    "If we only use a single image from the game-environment then we cannot tell which direction the ball is moving. The typical solution is to use multiple consecutive images to represent the state of the game-environment.\n",
+    "\n",
+    "This implementation uses another approach by processing the images from the game-environment in a motion-tracer that outputs two images as shown below. The left image is from the game-environment and the right image is the processed image, which shows traces of recent movements in the game-environment. In this case we can see that the ball is going downwards and has bounced off the right wall, and that the paddle has moved from the left to the right side of the screen.\n",
+    "\n",
+    "Note that the motion-tracer has only been tested for Breakout and partially tested for Space Invaders, so it may not work for games with more complicated graphics such as Doom."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Motion Trace](images/16_motion-trace.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Training Stability\n",
+    "\n",
+    "We need a function approximator that can take a state of the game-environment as input and produce as output an estimate of the Q-values for that state. We will use a Convolutional Neural Network for this. Although they have achieved great fame in recent years, they are actually a quite old technologies with many problems - one of which is training stability. A significant part of the research for this tutorial was spent on tuning and stabilizing the training of the Neural Network.\n",
+    "\n",
+    "To understand why training stability is a problem, consider the 3 images below which show the game-environment in 3 consecutive states. At state $t$ the agent is about to score a point, which happens in the following state $t+1$. Assuming all Q-values were zero prior to this, we should now set the Q-value for state $t+1$ to be 1.0 and it should be 0.97 for state $t$ if the discount-value is 0.97, according to the formula above for updating Q-values."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Training Stability](images/16_training_stability.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "If we were to train a Neural Network to estimate the Q-values for the two states $t$ and $t+1$ with Q-values 0.97 and 1.0, respectively, then the Neural Network will most likely be unable to distinguish properly between the images of these two states. As a result the Neural Network will also estimate a Q-value near 1.0 for state $t+2$ because the images are so similar. But this is clearly wrong because the Q-values for state $t+2$ should be zero as we do not know anything about future rewards at this point, and that is what the Q-values are supposed to estimate.\n",
+    "\n",
+    "If this is continued and the Neural Network is trained after every new game-state is observed, then it will quickly cause the estimated Q-values to explode. This is an artifact of training Neural Networks which must have sufficiently large and diverse training-sets. For this reason we will use a so-called Replay Memory so we can gather a large number of game-states and shuffle them during training of the Neural Network."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "This flowchart shows roughly how Reinforcement Learning is implemented in this tutorial.  There are two main loops which are run sequentially until the Neural Network is sufficiently accurate at estimating Q-values.\n",
+    "\n",
+    "The first loop is for playing the game and recording data. This uses the Neural Network to estimate Q-values from a game-state. It then stores the game-state along with the corresponding Q-values and reward/penalty in the Replay Memory for later use.\n",
+    "\n",
+    "The other loop is activated when the Replay Memory is sufficiently full. First it makes a full backwards sweep through the Replay Memory to update the Q-values with the new rewards and penalties that have been observed. Then it performs an optimization run so as to train the Neural Network to better estimate these updated Q-values.\n",
+    "\n",
+    "There are many more details in the implementation, such as decreasing the learning-rate and increasing the fraction of the Replay Memory being used during training, but this flowchart shows the main ideas."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Flowchart](images/16_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Neural Network Architecture\n",
+    "\n",
+    "The Neural Network used in this implementation has 3 convolutional layers, all of which have filter-size 3x3. The layers have 16, 32, and 64 output channels, respectively. The stride is 2 in the first two convolutional layers and 1 in the last layer.\n",
+    "\n",
+    "Following the 3 convolutional layers there are 4 fully-connected layers each with 1024 units and ReLU-activation. Then there is a single fully-connected layer with linear activation used as the output of the Neural Network.\n",
+    "\n",
+    "This architecture is different from those typically used in research papers from DeepMind and others. They often have large convolutional filter-sizes of 8x8 and 4x4 with high stride-values. This causes more aggressive down-sampling of the game-state images. They also typically have only a single fully-connected layer with 256 or 512 ReLU units.\n",
+    "\n",
+    "During the research for this tutorial, it was found that smaller filter-sizes and strides in the convolutional layers, combined with several fully-connected layers having more units, were necessary in order to have sufficiently accurate Q-values. The Neural Network architectures originally used by DeepMind appear to distort the Q-values quite significantly. A reason that their approach still worked, is possibly due to their use of a very large Replay Memory with 1 million states, and that the Neural Network did one mini-batch of training for each step of the game-environment, and some other tricks.\n",
+    "\n",
+    "The architecture used here is probably excessive but it takes several days of training to test each architecture, so it is left as an exercise for the reader to try and find a smaller Neural Network architecture that still performs well."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The [documentation](https://github.com/openai/gym) for OpenAI Gym currently suggests that you need to build it in order to install it. But if you just want to install the Atari games, then you only need to install a single pip-package by typing the following commands in a terminal."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "- conda create --name tf-gym --clone tf\n",
+    "- source activate tf-gym\n",
+    "- pip install gym[atari]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This assumes you already have an Anaconda environment named `tf` which has TensorFlow installed, it will then be cloned to another environment named `tf-gym` where OpenAI Gym is also installed. This allows you to easily switch between your normal TensorFlow environment and another one which also contains OpenAI Gym."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "You can also have two environments named `tf-gpu` and `tf-gpu-gym` for the GPU versions of TensorFlow."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "deletable": true,
+    "editable": true,
+    "id": "xu2SVpFJjmJr"
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import prettytensor as pt\n",
+    "import gym\n",
+    "import numpy as np\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The main source-code for Reinforcement Learning is located in the following module:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "import reinforcement_learning as rl"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6.0 (Anaconda) with package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.0.1'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# TensorFlow\n",
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.7.4'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# PrettyTensor\n",
+    "pt.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.8.1'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# OpenAI Gym\n",
+    "gym.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Game Environment\n",
+    "\n",
+    "This is the name of the game-environment that we want to use in OpenAI Gym."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "env_name = 'Breakout-v0'\n",
+    "# env_name = 'SpaceInvaders-v0'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This is the base-directory for the TensorFlow checkpoints as well as various log-files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "rl.checkpoint_base_dir = 'checkpoints_tutorial16/'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Once the base-dir has been set, you need to call this function to set all the paths that will be used. This will also create the checkpoint-dir if it does not already exist."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "rl.update_paths(env_name=env_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Download Pre-Trained Model\n",
+    "\n",
+    "You can download a TensorFlow checkpoint which holds all the pre-trained variables for the Neural Network. Two checkpoints are provided, one for Breakout and one for Space Invaders. They were both trained for about 150 hours on a laptop with 2.6 GHz CPU and a GTX 1070 GPU.\n",
+    "\n",
+    "#### WARNING!\n",
+    "\n",
+    "These checkpoints are 280-360 MB each. They are currently hosted on the webserver I use for [www.hvass-labs.org](www.hvass-labs.org) because it is awkward to automatically download large files on Google Drive. To lower the traffic on my webserver, this line has been commented out, so you have to activate it manually. You are welcome to download it, I just don't want it to download automatically for everyone who only  wants to run this Notebook briefly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# rl.maybe_download_checkpoint(env_name=env_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "I believe the webserver is located in Denmark. If you are having problems downloading the files using the automatic function above, then you can try and download the files manually in a webbrowser or using `wget` or `curl`. Or you can download from Google Drive, where you will get an anti-virus warning that is awkward to bypass automatically:\n",
+    "\n",
+    "* [Download Breakout Checkpoint from Google Drive](https://drive.google.com/uc?export=download&id=0B2aDiIly76ZvUjZTcXRuRFY0RjQ)\n",
+    "\n",
+    "* [Download Space Invaders Checkpoint from Google Drive](https://drive.google.com/uc?export=download&id=0B2aDiIly76ZvWDR4TExwdmw1RVE)\n",
+    "\n",
+    "You can use the checksum to ensure the downloaded files are complete:\n",
+    "\n",
+    "* [SHA256 Checksum](http://www.hvass-labs.org/projects/tensorflow/tutorial16/sha256sum.txt)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Create Agent\n",
+    "\n",
+    "The Agent-class implements the main loop for playing the game, recording data and optimizing the Neural Network. We create an object-instance and need to set `training=True` because we want to use the replay-memory to record states and Q-values for plotting further below. We disable logging so this does not corrupt the logs from the actual training that was done previously. We can also set `render=True` but it will have no effect as long as `training==True`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[2017-04-19 11:19:43,800] Making new env: Breakout-v0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Trying to restore last checkpoint ...\n",
+      "Restored checkpoint from: checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
+     ]
+    }
+   ],
+   "source": [
+    "agent = rl.Agent(env_name=env_name,\n",
+    "                 training=True,\n",
+    "                 render=True,\n",
+    "                 use_logging=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The Neural Network is automatically instantiated by the Agent-class. We will create a direct reference for convenience."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "model = agent.model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Similarly, the Agent-class also allocates the replay-memory when `training==True`. The replay-memory will require more than 3 GB of RAM, so it should only be allocated when needed. We will need the replay-memory in this Notebook to record the states and Q-values we observe, so they can be plotted further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "replay_memory = agent.replay_memory"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Training\n",
+    "\n",
+    "The agent's `run()` function is used to play the game. This uses the Neural Network to estimate Q-values and hence determine the agent's actions. If `training==True` then it will also gather states and Q-values in the replay-memory and train the Neural Network when the replay-memory is sufficiently full. You can set `num_episodes=None` if you want an infinite loop that you would stop manually with `ctrl-c`. In this case we just set `num_episodes=1` because we are not actually interested in training the Neural Network any further, we merely want to collect some states and Q-values in the replay-memory so we can plot them below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "87584:127640000\t Epsilon: 0.10\t Reward: 22.0\t Episode Mean: 22.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "agent.run(num_episodes=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "In training-mode, this function will output a line for each episode. The first counter is for the number of episodes that have been processed. The second counter is for the number of states that have been processed. These two counters are stored in the TensorFlow checkpoint along with the weights of the Neural Network, so you can restart the training e.g. if you only have one computer and need to train during the night.\n",
+    "\n",
+    "Note that the number of episodes is almost 90k. It is impractical to print that many lines in this Notebook, so the training is better done in a terminal window by running the following commands:\n",
+    "\n",
+    "```\n",
+    "source activate tf-gpu-gym  # Activate your Python environment with TF and Gym.\n",
+    "python reinforcement-learning.py --env Breakout-v0 --training\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Training Progress"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Data is being logged during training so we can plot the progress afterwards. The reward for each episode and a running mean of the last 30 episodes are logged to file. Basic statistics for the Q-values in the replay-memory are also logged to file before each optimization run.\n",
+    "\n",
+    "This could be logged using TensorFlow and TensorBoard, but they were designed for logging variables of the TensorFlow graph and data that flows through the graph. In this case the data we want logged does not reside in the graph, so it becomes a bit awkward to use TensorFlow to log this data.\n",
+    "\n",
+    "We have therefore implemented a few small classes that can write and read these logs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "log_q_values = rl.LogQValues()\n",
+    "log_reward = rl.LogReward()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now read the logs from file:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "log_q_values.read()\n",
+    "log_reward.read()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training Progress: Reward\n",
+    "\n",
+    "This plot shows the reward for each episode during training, as well as the running mean of the last 30 episodes. Note how the reward varies greatly from one episode to the next, so it is difficult to say from this plot alone whether the agent is really improving during the training, although the running mean does appear to trend upwards slightly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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A5L8TESYl7VxAhySuOZDGpDAkUwqnXR7+QEX0cPkFXszNRq4Po2kOu5iPUdp4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\nK1NHOaXUzdgC/Q3hLos7paVG782C4459lFIx2G5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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be4b9eb38>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(log_reward.count_states, log_reward.episode, label='Episode Reward')\n",
+    "plt.plot(log_reward.count_states, log_reward.mean, label='Mean of 30 episodes')\n",
+    "plt.xlabel('State-Count for Game Environment')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training Progress: Q-Values\n",
+    "\n",
+    "The following plot shows the mean Q-values from the replay-memory prior to each run of the optimizer for the Neural Network. Note how the mean Q-values increase rapidly in the beginning and then they increase fairly steadily for 40 million states, after which they still trend upwards but somewhat more irregularly.\n",
+    "\n",
+    "The fast improvement in the beginning is probably due to (1) the use of a smaller replay-memory early in training so the Neural Network is optimized more often and the new information is used faster, (2) the backwards-sweeping of the replay-memory so the rewards are used to update the Q-values for many of the states, instead of just updating the Q-values for a single state, and (3) the replay-memory is balanced so at least half of each mini-batch contains states whose Q-values have high estimation-errors for the Neural Network.\n",
+    "\n",
+    "The [original paper from DeepMind](https://arxiv.org/abs/1312.5602) showed much slower progress in the first phase of training, see Figure 2 in that paper but note that the Q-values are not directly comparable, possibly because they used a higher discount factor of 0.99 while we only used 0.97 here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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eDkUppRqVXyf3owWlAMS2DPVyJEop1bj8Orln5pUAmtyVUs2PXyf3rMrkHqnJ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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be4d362e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(log_q_values.count_states, log_q_values.mean, label='Q-Value Mean')\n",
+    "plt.xlabel('State-Count for Game Environment')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Testing\n",
+    "\n",
+    "When the agent and Neural Network is being trained, the so-called epsilon-probability is typically decreased from 1.0 to 0.1 over a large number of steps, after which the probability is held fixed at 0.1. This means the probability is 0.1 or 10% that the agent will select a random action in each step, otherwise it will select the action that has the highest Q-value. This is known as the epsilon-greedy policy. The choice of 0.1 for the epsilon-probability is a compromise between taking the actions that are already known to be good, versus exploring new actions that might lead to even higher rewards or might lead to death of the agent.\n",
+    "\n",
+    "During testing it is common to lower the epsilon-probability even further. We have set it to 0.01 as shown here:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.01"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent.epsilon_greedy.epsilon_testing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We will now instruct the agent that it should no longer perform training by setting this boolean:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "agent.training = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We also reset the previous episode rewards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "agent.reset_episode_rewards()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can render the game-environment to screen so we can see the agent playing the game, by setting this boolean:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "agent.render = True"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now run a single episode by calling the `run()` function again. This should open a new window that shows the game being played by the agent. At the time of this writing, it was not possible to resize this tiny window, and the developers at OpenAI did not seem to care about this feature which should obviously be there."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "87586:127640046\tQ-min: 1.767\tQ-max: 1.787\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
+      "87586:127640089\tQ-min: 1.798\tQ-max: 1.806\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
+      "87586:127640129\tQ-min: 1.902\tQ-max: 1.919\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
+      "87586:127640165\tQ-min: 1.995\tQ-max: 2.002\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
+      "87586:127640198\tQ-min: 1.940\tQ-max: 1.965\tLives: 5\tReward: 5.0\tEpisode Mean: 0.0\n",
+      "87586:127640231\tQ-min: 1.830\tQ-max: 1.853\tLives: 5\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "87586:127640265\tQ-min: 1.772\tQ-max: 1.811\tLives: 5\tReward: 10.0\tEpisode Mean: 0.0\n",
+      "87586:127640316\tQ-min: 1.689\tQ-max: 1.708\tLives: 5\tReward: 11.0\tEpisode Mean: 0.0\n",
+      "87586:127640382\tQ-min: 1.723\tQ-max: 1.773\tLives: 5\tReward: 12.0\tEpisode Mean: 0.0\n",
+      "87586:127640446\tQ-min: 1.659\tQ-max: 1.699\tLives: 5\tReward: 13.0\tEpisode Mean: 0.0\n",
+      "87586:127640513\tQ-min: 1.689\tQ-max: 1.708\tLives: 5\tReward: 14.0\tEpisode Mean: 0.0\n",
+      "87586:127640556\tQ-min: -0.225\tQ-max: 0.076\tLives: 4\tReward: 14.0\tEpisode Mean: 0.0\n",
+      "87586:127640599\tQ-min: 1.937\tQ-max: 1.965\tLives: 4\tReward: 15.0\tEpisode Mean: 0.0\n",
+      "87586:127640654\tQ-min: 1.658\tQ-max: 1.685\tLives: 4\tReward: 16.0\tEpisode Mean: 0.0\n",
+      "87586:127640716\tQ-min: 1.737\tQ-max: 1.754\tLives: 4\tReward: 17.0\tEpisode Mean: 0.0\n",
+      "87586:127640765\tQ-min: 2.054\tQ-max: 2.106\tLives: 4\tReward: 21.0\tEpisode Mean: 0.0\n",
+      "87586:127640803\tQ-min: 2.102\tQ-max: 2.130\tLives: 4\tReward: 22.0\tEpisode Mean: 0.0\n",
+      "87586:127640835\tQ-min: 1.970\tQ-max: 2.002\tLives: 4\tReward: 23.0\tEpisode Mean: 0.0\n",
+      "87586:127640868\tQ-min: 2.083\tQ-max: 2.102\tLives: 4\tReward: 24.0\tEpisode Mean: 0.0\n",
+      "87586:127640918\tQ-min: 1.700\tQ-max: 1.789\tLives: 4\tReward: 25.0\tEpisode Mean: 0.0\n",
+      "87586:127640980\tQ-min: 1.742\tQ-max: 1.766\tLives: 4\tReward: 26.0\tEpisode Mean: 0.0\n",
+      "87586:127641045\tQ-min: 1.598\tQ-max: 1.731\tLives: 4\tReward: 27.0\tEpisode Mean: 0.0\n",
+      "87586:127641113\tQ-min: 1.751\tQ-max: 1.777\tLives: 4\tReward: 28.0\tEpisode Mean: 0.0\n",
+      "87586:127641161\tQ-min: 2.024\tQ-max: 2.047\tLives: 4\tReward: 29.0\tEpisode Mean: 0.0\n",
+      "87586:127641197\tQ-min: 2.000\tQ-max: 2.013\tLives: 4\tReward: 30.0\tEpisode Mean: 0.0\n",
+      "87586:127641229\tQ-min: 2.098\tQ-max: 2.196\tLives: 4\tReward: 31.0\tEpisode Mean: 0.0\n",
+      "87586:127641262\tQ-min: 2.001\tQ-max: 2.041\tLives: 4\tReward: 32.0\tEpisode Mean: 0.0\n",
+      "87586:127641297\tQ-min: 2.056\tQ-max: 2.077\tLives: 4\tReward: 33.0\tEpisode Mean: 0.0\n",
+      "87586:127641330\tQ-min: 2.088\tQ-max: 2.105\tLives: 4\tReward: 34.0\tEpisode Mean: 0.0\n",
+      "87586:127641363\tQ-min: 2.145\tQ-max: 2.162\tLives: 4\tReward: 35.0\tEpisode Mean: 0.0\n",
+      "87586:127641383\tQ-min: -0.242\tQ-max: 0.024\tLives: 3\tReward: 35.0\tEpisode Mean: 0.0\n",
+      "87586:127641429\tQ-min: 1.918\tQ-max: 1.968\tLives: 3\tReward: 36.0\tEpisode Mean: 0.0\n",
+      "87586:127641477\tQ-min: 2.036\tQ-max: 2.095\tLives: 3\tReward: 40.0\tEpisode Mean: 0.0\n",
+      "87586:127641535\tQ-min: 1.808\tQ-max: 1.863\tLives: 3\tReward: 41.0\tEpisode Mean: 0.0\n",
+      "87586:127641586\tQ-min: 2.076\tQ-max: 2.126\tLives: 3\tReward: 45.0\tEpisode Mean: 0.0\n",
+      "87586:127641619\tQ-min: 2.161\tQ-max: 2.188\tLives: 3\tReward: 46.0\tEpisode Mean: 0.0\n",
+      "87586:127641654\tQ-min: 2.148\tQ-max: 2.255\tLives: 3\tReward: 50.0\tEpisode Mean: 0.0\n",
+      "87586:127641690\tQ-min: 2.114\tQ-max: 2.262\tLives: 3\tReward: 54.0\tEpisode Mean: 0.0\n",
+      "87586:127641740\tQ-min: 1.787\tQ-max: 1.920\tLives: 3\tReward: 55.0\tEpisode Mean: 0.0\n",
+      "87586:127641779\tQ-min: -0.254\tQ-max: 0.236\tLives: 2\tReward: 55.0\tEpisode Mean: 0.0\n",
+      "87586:127641826\tQ-min: 2.345\tQ-max: 2.511\tLives: 2\tReward: 59.0\tEpisode Mean: 0.0\n",
+      "87586:127641839\tQ-min: 0.116\tQ-max: 0.221\tLives: 1\tReward: 59.0\tEpisode Mean: 0.0\n",
+      "87586:127641873\tQ-min: -0.079\tQ-max: 0.146\tLives: 0\tReward: 59.0\tEpisode Mean: 59.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "agent.run(num_episodes=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Mean Reward"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The game-play is slightly random, both with regard to selecting actions using the epsilon-greedy policy, but also because the OpenAI Gym environment will repeat any action between 2-4 times, with the number chosen at random. So the reward of one episode is not an accurate estimate of the reward that can be expected in general from this agent.\n",
+    "\n",
+    "We need to run 30 or even 50 episodes to get a more accurate estimate of the reward that can be expected.\n",
+    "\n",
+    "We will first reset the previous episode rewards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "agent.reset_episode_rewards()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We disable the screen-rendering so the game-environment runs much faster."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "agent.render = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now run 30 episodes. This records the rewards for each episode. It might have been a good idea to disable the output so it does not print all these lines - you can do this as an exercise."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "87588:127641916\tQ-min: 1.755\tQ-max: 1.765\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
+      "87588:127641957\tQ-min: 1.791\tQ-max: 1.807\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
+      "87588:127642001\tQ-min: 1.871\tQ-max: 1.878\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
+      "87588:127642038\tQ-min: 1.969\tQ-max: 1.993\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
+      "87588:127642059\tQ-min: -0.183\tQ-max: 0.103\tLives: 4\tReward: 4.0\tEpisode Mean: 0.0\n",
+      "87588:127642100\tQ-min: 1.892\tQ-max: 1.924\tLives: 4\tReward: 5.0\tEpisode Mean: 0.0\n",
+      "87588:127642143\tQ-min: 1.910\tQ-max: 1.925\tLives: 4\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "87588:127642184\tQ-min: 1.879\tQ-max: 1.922\tLives: 4\tReward: 7.0\tEpisode Mean: 0.0\n",
+      "87588:127642222\tQ-min: 1.901\tQ-max: 1.941\tLives: 4\tReward: 8.0\tEpisode Mean: 0.0\n",
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+      "87588:127642288\tQ-min: 1.963\tQ-max: 1.996\tLives: 4\tReward: 10.0\tEpisode Mean: 0.0\n",
+      "87588:127642325\tQ-min: 1.927\tQ-max: 1.978\tLives: 4\tReward: 11.0\tEpisode Mean: 0.0\n",
+      "87588:127642373\tQ-min: 1.702\tQ-max: 1.722\tLives: 4\tReward: 12.0\tEpisode Mean: 0.0\n",
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+      "87588:127642683\tQ-min: 2.032\tQ-max: 2.119\tLives: 4\tReward: 24.0\tEpisode Mean: 0.0\n",
+      "87588:127642720\tQ-min: 1.864\tQ-max: 2.069\tLives: 4\tReward: 28.0\tEpisode Mean: 0.0\n",
+      "87588:127642753\tQ-min: 2.052\tQ-max: 2.083\tLives: 4\tReward: 29.0\tEpisode Mean: 0.0\n",
+      "87588:127642775\tQ-min: -0.131\tQ-max: 0.460\tLives: 3\tReward: 29.0\tEpisode Mean: 0.0\n",
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+      "87588:127643281\tQ-min: 2.371\tQ-max: 2.501\tLives: 2\tReward: 57.0\tEpisode Mean: 0.0\n",
+      "87588:127643301\tQ-min: 2.364\tQ-max: 2.523\tLives: 2\tReward: 58.0\tEpisode Mean: 0.0\n",
+      "87588:127643315\tQ-min: 0.041\tQ-max: 0.210\tLives: 1\tReward: 58.0\tEpisode Mean: 0.0\n",
+      "87588:127643358\tQ-min: 2.213\tQ-max: 2.263\tLives: 1\tReward: 62.0\tEpisode Mean: 0.0\n",
+      "87588:127643403\tQ-min: 2.129\tQ-max: 2.290\tLives: 1\tReward: 63.0\tEpisode Mean: 0.0\n",
+      "87588:127643447\tQ-min: 2.044\tQ-max: 2.162\tLives: 1\tReward: 67.0\tEpisode Mean: 0.0\n",
+      "87588:127643486\tQ-min: 2.325\tQ-max: 2.404\tLives: 1\tReward: 68.0\tEpisode Mean: 0.0\n",
+      "87588:127643519\tQ-min: 2.200\tQ-max: 2.273\tLives: 1\tReward: 69.0\tEpisode Mean: 0.0\n",
+      "87588:127643552\tQ-min: 2.272\tQ-max: 2.318\tLives: 1\tReward: 70.0\tEpisode Mean: 0.0\n",
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+      "87588:127643638\tQ-min: 2.055\tQ-max: 2.470\tLives: 1\tReward: 75.0\tEpisode Mean: 0.0\n",
+      "87588:127643658\tQ-min: 2.335\tQ-max: 2.428\tLives: 1\tReward: 76.0\tEpisode Mean: 0.0\n",
+      "87588:127643679\tQ-min: 2.365\tQ-max: 2.520\tLives: 1\tReward: 80.0\tEpisode Mean: 0.0\n",
+      "87588:127643691\tQ-min: -0.361\tQ-max: -0.116\tLives: 0\tReward: 80.0\tEpisode Mean: 80.0\n",
+      "87589:127643734\tQ-min: 1.775\tQ-max: 1.792\tLives: 5\tReward: 1.0\tEpisode Mean: 80.0\n",
+      "87589:127643776\tQ-min: 1.863\tQ-max: 1.872\tLives: 5\tReward: 2.0\tEpisode Mean: 80.0\n",
+      "87589:127643818\tQ-min: 1.907\tQ-max: 1.938\tLives: 5\tReward: 3.0\tEpisode Mean: 80.0\n",
+      "87589:127643852\tQ-min: 1.988\tQ-max: 2.028\tLives: 5\tReward: 4.0\tEpisode Mean: 80.0\n",
+      "87589:127643885\tQ-min: 1.973\tQ-max: 2.000\tLives: 5\tReward: 5.0\tEpisode Mean: 80.0\n",
+      "87589:127643915\tQ-min: 1.935\tQ-max: 1.953\tLives: 5\tReward: 6.0\tEpisode Mean: 80.0\n",
+      "87589:127643946\tQ-min: 1.792\tQ-max: 1.812\tLives: 5\tReward: 7.0\tEpisode Mean: 80.0\n",
+      "87589:127643992\tQ-min: 1.667\tQ-max: 1.687\tLives: 5\tReward: 8.0\tEpisode Mean: 80.0\n",
+      "87589:127644059\tQ-min: 1.696\tQ-max: 1.716\tLives: 5\tReward: 9.0\tEpisode Mean: 80.0\n",
+      "87589:127644124\tQ-min: 1.669\tQ-max: 1.691\tLives: 5\tReward: 10.0\tEpisode Mean: 80.0\n",
+      "87589:127644191\tQ-min: 1.621\tQ-max: 1.673\tLives: 5\tReward: 11.0\tEpisode Mean: 80.0\n",
+      "87589:127644240\tQ-min: 1.960\tQ-max: 1.983\tLives: 5\tReward: 12.0\tEpisode Mean: 80.0\n",
+      "87589:127644274\tQ-min: 1.907\tQ-max: 1.978\tLives: 5\tReward: 13.0\tEpisode Mean: 80.0\n",
+      "87589:127644306\tQ-min: 1.994\tQ-max: 2.017\tLives: 5\tReward: 14.0\tEpisode Mean: 80.0\n",
+      "87589:127644337\tQ-min: 2.081\tQ-max: 2.093\tLives: 5\tReward: 15.0\tEpisode Mean: 80.0\n",
+      "87589:127644358\tQ-min: -0.094\tQ-max: 0.319\tLives: 4\tReward: 15.0\tEpisode Mean: 80.0\n",
+      "87589:127644400\tQ-min: 1.875\tQ-max: 1.904\tLives: 4\tReward: 16.0\tEpisode Mean: 80.0\n",
+      "87589:127644443\tQ-min: 1.952\tQ-max: 1.981\tLives: 4\tReward: 17.0\tEpisode Mean: 80.0\n",
+      "87589:127644495\tQ-min: 1.737\tQ-max: 1.758\tLives: 4\tReward: 18.0\tEpisode Mean: 80.0\n",
+      "87589:127644547\tQ-min: 2.005\tQ-max: 2.084\tLives: 4\tReward: 22.0\tEpisode Mean: 80.0\n",
+      "87589:127644583\tQ-min: 2.197\tQ-max: 2.347\tLives: 4\tReward: 26.0\tEpisode Mean: 80.0\n",
+      "87589:127644607\tQ-min: 2.098\tQ-max: 2.379\tLives: 4\tReward: 33.0\tEpisode Mean: 80.0\n",
+      "87589:127644629\tQ-min: 2.282\tQ-max: 2.418\tLives: 4\tReward: 37.0\tEpisode Mean: 80.0\n",
+      "87589:127644650\tQ-min: 2.283\tQ-max: 2.413\tLives: 4\tReward: 41.0\tEpisode Mean: 80.0\n",
+      "87589:127644671\tQ-min: 2.381\tQ-max: 2.468\tLives: 4\tReward: 42.0\tEpisode Mean: 80.0\n",
+      "87589:127644692\tQ-min: 2.358\tQ-max: 2.503\tLives: 4\tReward: 46.0\tEpisode Mean: 80.0\n",
+      "87589:127644716\tQ-min: 2.211\tQ-max: 2.720\tLives: 4\tReward: 53.0\tEpisode Mean: 80.0\n",
+      "87589:127644740\tQ-min: 2.252\tQ-max: 2.455\tLives: 4\tReward: 54.0\tEpisode Mean: 80.0\n",
+      "87589:127644760\tQ-min: 2.455\tQ-max: 2.532\tLives: 4\tReward: 55.0\tEpisode Mean: 80.0\n",
+      "87589:127644783\tQ-min: 2.226\tQ-max: 2.391\tLives: 4\tReward: 59.0\tEpisode Mean: 80.0\n",
+      "87589:127644802\tQ-min: 2.444\tQ-max: 2.583\tLives: 4\tReward: 60.0\tEpisode Mean: 80.0\n",
+      "87589:127644815\tQ-min: 0.052\tQ-max: 0.276\tLives: 3\tReward: 60.0\tEpisode Mean: 80.0\n",
+      "87589:127644878\tQ-min: 1.634\tQ-max: 2.413\tLives: 3\tReward: 64.0\tEpisode Mean: 80.0\n",
+      "87589:127644935\tQ-min: 2.321\tQ-max: 2.362\tLives: 3\tReward: 65.0\tEpisode Mean: 80.0\n",
+      "87589:127644979\tQ-min: 2.174\tQ-max: 2.536\tLives: 3\tReward: 69.0\tEpisode Mean: 80.0\n",
+      "87589:127644994\tQ-min: -0.034\tQ-max: 0.382\tLives: 2\tReward: 69.0\tEpisode Mean: 80.0\n",
+      "87589:127645044\tQ-min: 1.599\tQ-max: 2.176\tLives: 2\tReward: 76.0\tEpisode Mean: 80.0\n",
+      "87589:127645066\tQ-min: 2.362\tQ-max: 2.540\tLives: 2\tReward: 77.0\tEpisode Mean: 80.0\n",
+      "87589:127645088\tQ-min: 1.918\tQ-max: 2.701\tLives: 2\tReward: 84.0\tEpisode Mean: 80.0\n",
+      "87589:127645102\tQ-min: -0.022\tQ-max: 0.068\tLives: 1\tReward: 84.0\tEpisode Mean: 80.0\n",
+      "87589:127645159\tQ-min: 1.981\tQ-max: 2.173\tLives: 1\tReward: 85.0\tEpisode Mean: 80.0\n",
+      "87589:127645231\tQ-min: 1.785\tQ-max: 2.009\tLives: 1\tReward: 86.0\tEpisode Mean: 80.0\n",
+      "87589:127645289\tQ-min: 2.147\tQ-max: 2.292\tLives: 1\tReward: 87.0\tEpisode Mean: 80.0\n",
+      "87589:127645329\tQ-min: 2.359\tQ-max: 2.482\tLives: 1\tReward: 88.0\tEpisode Mean: 80.0\n",
+      "87589:127645365\tQ-min: 1.856\tQ-max: 2.511\tLives: 1\tReward: 95.0\tEpisode Mean: 80.0\n",
+      "87589:127645388\tQ-min: 1.407\tQ-max: 3.038\tLives: 1\tReward: 99.0\tEpisode Mean: 80.0\n",
+      "87589:127645407\tQ-min: 2.163\tQ-max: 3.081\tLives: 1\tReward: 100.0\tEpisode Mean: 80.0\n",
+      "87589:127645419\tQ-min: -0.183\tQ-max: 0.050\tLives: 0\tReward: 100.0\tEpisode Mean: 90.0\n",
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+      "87590:127646661\tQ-min: 2.252\tQ-max: 2.288\tLives: 2\tReward: 52.0\tEpisode Mean: 90.0\n",
+      "87590:127646682\tQ-min: -0.102\tQ-max: 0.229\tLives: 1\tReward: 52.0\tEpisode Mean: 90.0\n",
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+      "87591:127647177\tQ-min: 1.931\tQ-max: 1.940\tLives: 4\tReward: 12.0\tEpisode Mean: 79.0\n",
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+      "87591:127647323\tQ-min: 2.038\tQ-max: 2.059\tLives: 4\tReward: 16.0\tEpisode Mean: 79.0\n",
+      "87591:127647360\tQ-min: 2.017\tQ-max: 2.061\tLives: 4\tReward: 20.0\tEpisode Mean: 79.0\n",
+      "87591:127647410\tQ-min: 1.760\tQ-max: 1.781\tLives: 4\tReward: 21.0\tEpisode Mean: 79.0\n",
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+      "87591:127647598\tQ-min: 1.660\tQ-max: 1.691\tLives: 4\tReward: 24.0\tEpisode Mean: 79.0\n",
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+      "87591:127647674\tQ-min: 2.064\tQ-max: 2.089\tLives: 4\tReward: 26.0\tEpisode Mean: 79.0\n",
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+      "87591:127647773\tQ-min: 1.913\tQ-max: 2.158\tLives: 4\tReward: 32.0\tEpisode Mean: 79.0\n",
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+      "87591:127647827\tQ-min: -0.069\tQ-max: 0.166\tLives: 3\tReward: 33.0\tEpisode Mean: 79.0\n",
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+      "87591:127647962\tQ-min: 2.088\tQ-max: 2.182\tLives: 3\tReward: 39.0\tEpisode Mean: 79.0\n",
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+      "87591:127648037\tQ-min: 2.193\tQ-max: 2.259\tLives: 3\tReward: 44.0\tEpisode Mean: 79.0\n",
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+      "87591:127648299\tQ-min: 1.462\tQ-max: 1.818\tLives: 3\tReward: 52.0\tEpisode Mean: 79.0\n",
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+      "87591:127648386\tQ-min: 2.260\tQ-max: 2.447\tLives: 3\tReward: 57.0\tEpisode Mean: 79.0\n",
+      "87591:127648406\tQ-min: 2.177\tQ-max: 2.367\tLives: 3\tReward: 58.0\tEpisode Mean: 79.0\n",
+      "87591:127648426\tQ-min: 2.419\tQ-max: 2.528\tLives: 3\tReward: 59.0\tEpisode Mean: 79.0\n",
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+      "87591:127648530\tQ-min: 2.056\tQ-max: 2.156\tLives: 2\tReward: 67.0\tEpisode Mean: 79.0\n",
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+      "87592:127649438\tQ-min: 1.618\tQ-max: 1.713\tLives: 5\tReward: 9.0\tEpisode Mean: 90.0\n",
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+      "87592:127649569\tQ-min: 1.584\tQ-max: 1.635\tLives: 5\tReward: 11.0\tEpisode Mean: 90.0\n",
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+      "87592:127650147\tQ-min: 2.042\tQ-max: 2.062\tLives: 5\tReward: 37.0\tEpisode Mean: 90.0\n",
+      "87592:127650181\tQ-min: 2.132\tQ-max: 2.282\tLives: 5\tReward: 38.0\tEpisode Mean: 90.0\n",
+      "87592:127650217\tQ-min: 2.311\tQ-max: 2.349\tLives: 5\tReward: 42.0\tEpisode Mean: 90.0\n",
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+      "87592:127650300\tQ-min: 2.212\tQ-max: 2.416\tLives: 5\tReward: 54.0\tEpisode Mean: 90.0\n",
+      "87592:127650323\tQ-min: 2.300\tQ-max: 2.828\tLives: 5\tReward: 61.0\tEpisode Mean: 90.0\n",
+      "87592:127650345\tQ-min: 2.156\tQ-max: 2.609\tLives: 5\tReward: 68.0\tEpisode Mean: 90.0\n",
+      "87592:127650371\tQ-min: 1.411\tQ-max: 3.465\tLives: 5\tReward: 75.0\tEpisode Mean: 90.0\n",
+      "87592:127650394\tQ-min: 2.413\tQ-max: 3.230\tLives: 5\tReward: 79.0\tEpisode Mean: 90.0\n",
+      "87592:127650423\tQ-min: 0.923\tQ-max: 6.278\tLives: 5\tReward: 86.0\tEpisode Mean: 90.0\n",
+      "87592:127650428\tQ-min: 3.001\tQ-max: 6.274\tLives: 5\tReward: 93.0\tEpisode Mean: 90.0\n",
+      "87592:127650433\tQ-min: 3.775\tQ-max: 6.792\tLives: 5\tReward: 100.0\tEpisode Mean: 90.0\n",
+      "87592:127650438\tQ-min: 4.326\tQ-max: 6.050\tLives: 5\tReward: 107.0\tEpisode Mean: 90.0\n",
+      "87592:127650442\tQ-min: 4.084\tQ-max: 6.912\tLives: 5\tReward: 114.0\tEpisode Mean: 90.0\n",
+      "87592:127650446\tQ-min: 3.861\tQ-max: 6.375\tLives: 5\tReward: 121.0\tEpisode Mean: 90.0\n",
+      "87592:127650451\tQ-min: 3.899\tQ-max: 5.700\tLives: 5\tReward: 128.0\tEpisode Mean: 90.0\n",
+      "87592:127650456\tQ-min: 3.069\tQ-max: 5.369\tLives: 5\tReward: 135.0\tEpisode Mean: 90.0\n",
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+      "87595:127654660\tQ-min: 1.702\tQ-max: 1.728\tLives: 5\tReward: 9.0\tEpisode Mean: 124.3\n",
+      "87595:127654727\tQ-min: 1.678\tQ-max: 1.689\tLives: 5\tReward: 10.0\tEpisode Mean: 124.3\n",
+      "87595:127654772\tQ-min: -0.204\tQ-max: 0.125\tLives: 4\tReward: 10.0\tEpisode Mean: 124.3\n",
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+      "87595:127654924\tQ-min: 1.964\tQ-max: 1.985\tLives: 4\tReward: 13.0\tEpisode Mean: 124.3\n",
+      "87595:127654952\tQ-min: -0.139\tQ-max: 0.220\tLives: 3\tReward: 13.0\tEpisode Mean: 124.3\n",
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+      "87595:127655216\tQ-min: 1.989\tQ-max: 2.022\tLives: 3\tReward: 22.0\tEpisode Mean: 124.3\n",
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+      "87595:127655298\tQ-min: 1.708\tQ-max: 1.734\tLives: 3\tReward: 24.0\tEpisode Mean: 124.3\n",
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+      "87595:127655493\tQ-min: 1.721\tQ-max: 1.764\tLives: 3\tReward: 27.0\tEpisode Mean: 124.3\n",
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+      "87595:127655583\tQ-min: 1.993\tQ-max: 2.055\tLives: 3\tReward: 32.0\tEpisode Mean: 124.3\n",
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+      "87595:127655742\tQ-min: 2.050\tQ-max: 2.101\tLives: 2\tReward: 38.0\tEpisode Mean: 124.3\n",
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+      "87595:127656218\tQ-min: 2.150\tQ-max: 2.171\tLives: 2\tReward: 57.0\tEpisode Mean: 124.3\n",
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+      "87595:127656285\tQ-min: 2.148\tQ-max: 2.171\tLives: 2\tReward: 62.0\tEpisode Mean: 124.3\n",
+      "87595:127656318\tQ-min: 2.195\tQ-max: 2.320\tLives: 2\tReward: 66.0\tEpisode Mean: 124.3\n",
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+      "87595:127656389\tQ-min: 2.213\tQ-max: 2.269\tLives: 2\tReward: 71.0\tEpisode Mean: 124.3\n",
+      "87595:127656426\tQ-min: 2.358\tQ-max: 2.574\tLives: 2\tReward: 75.0\tEpisode Mean: 124.3\n",
+      "87595:127656441\tQ-min: -0.137\tQ-max: 0.415\tLives: 1\tReward: 75.0\tEpisode Mean: 124.3\n",
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+      "87595:127656578\tQ-min: 1.994\tQ-max: 2.153\tLives: 1\tReward: 83.0\tEpisode Mean: 124.3\n",
+      "87595:127656633\tQ-min: 2.128\tQ-max: 2.158\tLives: 1\tReward: 84.0\tEpisode Mean: 124.3\n",
+      "87595:127656674\tQ-min: 2.155\tQ-max: 2.412\tLives: 1\tReward: 88.0\tEpisode Mean: 124.3\n",
+      "87595:127656696\tQ-min: 2.417\tQ-max: 2.483\tLives: 1\tReward: 92.0\tEpisode Mean: 124.3\n",
+      "87595:127656718\tQ-min: 2.471\tQ-max: 2.509\tLives: 1\tReward: 96.0\tEpisode Mean: 124.3\n",
+      "87595:127656741\tQ-min: 2.288\tQ-max: 2.486\tLives: 1\tReward: 100.0\tEpisode Mean: 124.3\n",
+      "87595:127656756\tQ-min: -0.398\tQ-max: 0.151\tLives: 0\tReward: 100.0\tEpisode Mean: 121.2\n",
+      "87596:127656800\tQ-min: 1.752\tQ-max: 1.776\tLives: 5\tReward: 1.0\tEpisode Mean: 121.2\n",
+      "87596:127656843\tQ-min: 1.811\tQ-max: 1.845\tLives: 5\tReward: 2.0\tEpisode Mean: 121.2\n",
+      "87596:127656898\tQ-min: 1.726\tQ-max: 1.790\tLives: 5\tReward: 3.0\tEpisode Mean: 121.2\n",
+      "87596:127656947\tQ-min: 1.975\tQ-max: 2.010\tLives: 5\tReward: 4.0\tEpisode Mean: 121.2\n",
+      "87596:127656979\tQ-min: 1.966\tQ-max: 1.980\tLives: 5\tReward: 5.0\tEpisode Mean: 121.2\n",
+      "87596:127657009\tQ-min: 1.879\tQ-max: 1.901\tLives: 5\tReward: 6.0\tEpisode Mean: 121.2\n",
+      "87596:127657029\tQ-min: -0.026\tQ-max: 0.200\tLives: 4\tReward: 6.0\tEpisode Mean: 121.2\n",
+      "87596:127657071\tQ-min: 1.842\tQ-max: 1.867\tLives: 4\tReward: 7.0\tEpisode Mean: 121.2\n",
+      "87596:127657114\tQ-min: 1.897\tQ-max: 1.913\tLives: 4\tReward: 8.0\tEpisode Mean: 121.2\n",
+      "87596:127657168\tQ-min: 1.680\tQ-max: 1.711\tLives: 4\tReward: 9.0\tEpisode Mean: 121.2\n",
+      "87596:127657215\tQ-min: 1.969\tQ-max: 1.988\tLives: 4\tReward: 10.0\tEpisode Mean: 121.2\n",
+      "87596:127657252\tQ-min: 1.557\tQ-max: 1.687\tLives: 4\tReward: 14.0\tEpisode Mean: 121.2\n",
+      "87596:127657286\tQ-min: 1.904\tQ-max: 1.924\tLives: 4\tReward: 15.0\tEpisode Mean: 121.2\n",
+      "87596:127657322\tQ-min: 2.066\tQ-max: 2.095\tLives: 4\tReward: 16.0\tEpisode Mean: 121.2\n",
+      "87596:127657368\tQ-min: 1.692\tQ-max: 1.720\tLives: 4\tReward: 17.0\tEpisode Mean: 121.2\n",
+      "87596:127657431\tQ-min: 1.703\tQ-max: 1.725\tLives: 4\tReward: 18.0\tEpisode Mean: 121.2\n",
+      "87596:127657496\tQ-min: 1.739\tQ-max: 1.753\tLives: 4\tReward: 19.0\tEpisode Mean: 121.2\n",
+      "87596:127657537\tQ-min: -0.069\tQ-max: 0.212\tLives: 3\tReward: 19.0\tEpisode Mean: 121.2\n",
+      "87596:127657590\tQ-min: 1.665\tQ-max: 1.690\tLives: 3\tReward: 20.0\tEpisode Mean: 121.2\n",
+      "87596:127657642\tQ-min: 1.944\tQ-max: 1.986\tLives: 3\tReward: 21.0\tEpisode Mean: 121.2\n",
+      "87596:127657698\tQ-min: 1.724\tQ-max: 1.814\tLives: 3\tReward: 22.0\tEpisode Mean: 121.2\n",
+      "87596:127657748\tQ-min: 1.969\tQ-max: 1.993\tLives: 3\tReward: 23.0\tEpisode Mean: 121.2\n",
+      "87596:127657782\tQ-min: 1.926\tQ-max: 1.983\tLives: 3\tReward: 24.0\tEpisode Mean: 121.2\n",
+      "87596:127657814\tQ-min: 1.967\tQ-max: 2.028\tLives: 3\tReward: 25.0\tEpisode Mean: 121.2\n",
+      "87596:127657847\tQ-min: 2.010\tQ-max: 2.035\tLives: 3\tReward: 26.0\tEpisode Mean: 121.2\n",
+      "87596:127657897\tQ-min: 1.694\tQ-max: 1.734\tLives: 3\tReward: 27.0\tEpisode Mean: 121.2\n",
+      "87596:127657963\tQ-min: 1.684\tQ-max: 1.748\tLives: 3\tReward: 28.0\tEpisode Mean: 121.2\n",
+      "87596:127658030\tQ-min: 1.734\tQ-max: 1.755\tLives: 3\tReward: 29.0\tEpisode Mean: 121.2\n",
+      "87596:127658095\tQ-min: 1.687\tQ-max: 1.738\tLives: 3\tReward: 30.0\tEpisode Mean: 121.2\n",
+      "87596:127658143\tQ-min: 2.046\tQ-max: 2.068\tLives: 3\tReward: 31.0\tEpisode Mean: 121.2\n",
+      "87596:127658176\tQ-min: 2.011\tQ-max: 2.042\tLives: 3\tReward: 32.0\tEpisode Mean: 121.2\n",
+      "87596:127658213\tQ-min: 2.052\tQ-max: 2.119\tLives: 3\tReward: 36.0\tEpisode Mean: 121.2\n",
+      "87596:127658249\tQ-min: 2.020\tQ-max: 2.121\tLives: 3\tReward: 37.0\tEpisode Mean: 121.2\n",
+      "87596:127658281\tQ-min: 2.072\tQ-max: 2.136\tLives: 3\tReward: 38.0\tEpisode Mean: 121.2\n",
+      "87596:127658315\tQ-min: 2.020\tQ-max: 2.088\tLives: 3\tReward: 42.0\tEpisode Mean: 121.2\n",
+      "87596:127658353\tQ-min: 2.306\tQ-max: 2.636\tLives: 3\tReward: 46.0\tEpisode Mean: 121.2\n",
+      "87596:127658374\tQ-min: 2.334\tQ-max: 2.455\tLives: 3\tReward: 47.0\tEpisode Mean: 121.2\n",
+      "87596:127658395\tQ-min: 2.047\tQ-max: 2.537\tLives: 3\tReward: 51.0\tEpisode Mean: 121.2\n",
+      "87596:127658416\tQ-min: 2.345\tQ-max: 2.731\tLives: 3\tReward: 58.0\tEpisode Mean: 121.2\n",
+      "87596:127658439\tQ-min: 2.366\tQ-max: 2.544\tLives: 3\tReward: 62.0\tEpisode Mean: 121.2\n",
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+      "87596:127658504\tQ-min: 2.038\tQ-max: 2.065\tLives: 2\tReward: 63.0\tEpisode Mean: 121.2\n",
+      "87596:127658561\tQ-min: 1.930\tQ-max: 2.016\tLives: 2\tReward: 64.0\tEpisode Mean: 121.2\n",
+      "87596:127658620\tQ-min: 2.147\tQ-max: 2.177\tLives: 2\tReward: 68.0\tEpisode Mean: 121.2\n",
+      "87596:127658660\tQ-min: 2.240\tQ-max: 2.259\tLives: 2\tReward: 72.0\tEpisode Mean: 121.2\n",
+      "87596:127658694\tQ-min: 2.320\tQ-max: 2.563\tLives: 2\tReward: 76.0\tEpisode Mean: 121.2\n",
+      "87596:127658715\tQ-min: 2.466\tQ-max: 2.543\tLives: 2\tReward: 80.0\tEpisode Mean: 121.2\n",
+      "87596:127658737\tQ-min: 2.368\tQ-max: 2.592\tLives: 2\tReward: 84.0\tEpisode Mean: 121.2\n",
+      "87596:127658753\tQ-min: -0.032\tQ-max: 0.342\tLives: 1\tReward: 84.0\tEpisode Mean: 121.2\n",
+      "87596:127658800\tQ-min: 1.889\tQ-max: 2.049\tLives: 1\tReward: 88.0\tEpisode Mean: 121.2\n",
+      "87596:127658844\tQ-min: 2.164\tQ-max: 2.220\tLives: 1\tReward: 89.0\tEpisode Mean: 121.2\n",
+      "87596:127658886\tQ-min: 2.279\tQ-max: 2.364\tLives: 1\tReward: 93.0\tEpisode Mean: 121.2\n",
+      "87596:127658934\tQ-min: 1.056\tQ-max: 2.037\tLives: 1\tReward: 100.0\tEpisode Mean: 121.2\n",
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+      "87596:127658973\tQ-min: -0.243\tQ-max: 0.129\tLives: 0\tReward: 107.0\tEpisode Mean: 119.7\n",
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+      "87597:127659066\tQ-min: 1.621\tQ-max: 1.648\tLives: 5\tReward: 2.0\tEpisode Mean: 119.7\n",
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+      "87597:127659179\tQ-min: 1.917\tQ-max: 1.930\tLives: 5\tReward: 4.0\tEpisode Mean: 119.7\n",
+      "87597:127659212\tQ-min: 1.970\tQ-max: 1.983\tLives: 5\tReward: 5.0\tEpisode Mean: 119.7\n",
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+      "87597:127659278\tQ-min: 1.738\tQ-max: 1.780\tLives: 5\tReward: 7.0\tEpisode Mean: 119.7\n",
+      "87597:127659327\tQ-min: 1.629\tQ-max: 1.649\tLives: 5\tReward: 8.0\tEpisode Mean: 119.7\n",
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+      "87597:127659455\tQ-min: 1.630\tQ-max: 1.658\tLives: 5\tReward: 10.0\tEpisode Mean: 119.7\n",
+      "87597:127659517\tQ-min: 1.650\tQ-max: 1.719\tLives: 5\tReward: 11.0\tEpisode Mean: 119.7\n",
+      "87597:127659564\tQ-min: 1.988\tQ-max: 2.015\tLives: 5\tReward: 12.0\tEpisode Mean: 119.7\n",
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+      "87597:127659630\tQ-min: 1.926\tQ-max: 1.975\tLives: 5\tReward: 17.0\tEpisode Mean: 119.7\n",
+      "87597:127659665\tQ-min: 1.984\tQ-max: 2.018\tLives: 5\tReward: 21.0\tEpisode Mean: 119.7\n",
+      "87597:127659700\tQ-min: 2.028\tQ-max: 2.077\tLives: 5\tReward: 22.0\tEpisode Mean: 119.7\n",
+      "87597:127659734\tQ-min: 2.169\tQ-max: 2.327\tLives: 5\tReward: 26.0\tEpisode Mean: 119.7\n",
+      "87597:127659757\tQ-min: -0.114\tQ-max: 0.223\tLives: 4\tReward: 26.0\tEpisode Mean: 119.7\n",
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+      "87597:127659857\tQ-min: 1.806\tQ-max: 1.820\tLives: 4\tReward: 28.0\tEpisode Mean: 119.7\n",
+      "87597:127659925\tQ-min: 1.780\tQ-max: 1.814\tLives: 4\tReward: 29.0\tEpisode Mean: 119.7\n",
+      "87597:127659973\tQ-min: 2.143\tQ-max: 2.427\tLives: 4\tReward: 33.0\tEpisode Mean: 119.7\n",
+      "87597:127659996\tQ-min: 2.260\tQ-max: 2.368\tLives: 4\tReward: 34.0\tEpisode Mean: 119.7\n",
+      "87597:127660008\tQ-min: 0.231\tQ-max: 0.392\tLives: 3\tReward: 34.0\tEpisode Mean: 119.7\n",
+      "87597:127660050\tQ-min: 2.000\tQ-max: 2.056\tLives: 3\tReward: 35.0\tEpisode Mean: 119.7\n",
+      "87597:127660104\tQ-min: 1.788\tQ-max: 1.853\tLives: 3\tReward: 36.0\tEpisode Mean: 119.7\n",
+      "87597:127660162\tQ-min: 1.819\tQ-max: 2.164\tLives: 3\tReward: 40.0\tEpisode Mean: 119.7\n",
+      "87597:127660201\tQ-min: 2.244\tQ-max: 2.290\tLives: 3\tReward: 41.0\tEpisode Mean: 119.7\n",
+      "87597:127660236\tQ-min: 2.125\tQ-max: 2.217\tLives: 3\tReward: 42.0\tEpisode Mean: 119.7\n",
+      "87597:127660268\tQ-min: 2.130\tQ-max: 2.243\tLives: 3\tReward: 46.0\tEpisode Mean: 119.7\n",
+      "87597:127660302\tQ-min: 2.197\tQ-max: 2.219\tLives: 3\tReward: 47.0\tEpisode Mean: 119.7\n",
+      "87597:127660349\tQ-min: 1.765\tQ-max: 1.831\tLives: 3\tReward: 48.0\tEpisode Mean: 119.7\n",
+      "87597:127660415\tQ-min: 1.657\tQ-max: 1.840\tLives: 3\tReward: 49.0\tEpisode Mean: 119.7\n",
+      "87597:127660491\tQ-min: 2.188\tQ-max: 2.759\tLives: 3\tReward: 53.0\tEpisode Mean: 119.7\n",
+      "87597:127660511\tQ-min: 2.256\tQ-max: 2.470\tLives: 3\tReward: 57.0\tEpisode Mean: 119.7\n",
+      "87597:127660525\tQ-min: 0.033\tQ-max: 0.183\tLives: 2\tReward: 57.0\tEpisode Mean: 119.7\n",
+      "87597:127660588\tQ-min: 1.652\tQ-max: 2.244\tLives: 2\tReward: 61.0\tEpisode Mean: 119.7\n",
+      "87597:127660657\tQ-min: 1.894\tQ-max: 1.975\tLives: 2\tReward: 62.0\tEpisode Mean: 119.7\n",
+      "87597:127660720\tQ-min: 1.984\tQ-max: 2.009\tLives: 2\tReward: 63.0\tEpisode Mean: 119.7\n",
+      "87597:127660770\tQ-min: 2.436\tQ-max: 2.488\tLives: 2\tReward: 64.0\tEpisode Mean: 119.7\n",
+      "87597:127660804\tQ-min: 2.209\tQ-max: 2.258\tLives: 2\tReward: 68.0\tEpisode Mean: 119.7\n",
+      "87597:127660842\tQ-min: 2.111\tQ-max: 2.718\tLives: 2\tReward: 75.0\tEpisode Mean: 119.7\n",
+      "87597:127660865\tQ-min: 2.376\tQ-max: 2.468\tLives: 2\tReward: 76.0\tEpisode Mean: 119.7\n",
+      "87597:127660886\tQ-min: 2.358\tQ-max: 2.477\tLives: 2\tReward: 80.0\tEpisode Mean: 119.7\n",
+      "87597:127660910\tQ-min: 1.924\tQ-max: 2.500\tLives: 2\tReward: 87.0\tEpisode Mean: 119.7\n",
+      "87597:127660932\tQ-min: 2.473\tQ-max: 2.577\tLives: 2\tReward: 91.0\tEpisode Mean: 119.7\n",
+      "87597:127660954\tQ-min: 2.096\tQ-max: 2.563\tLives: 2\tReward: 95.0\tEpisode Mean: 119.7\n",
+      "87597:127660975\tQ-min: 1.886\tQ-max: 2.625\tLives: 2\tReward: 99.0\tEpisode Mean: 119.7\n",
+      "87597:127660993\tQ-min: 2.135\tQ-max: 2.649\tLives: 2\tReward: 103.0\tEpisode Mean: 119.7\n",
+      "87597:127661016\tQ-min: 1.828\tQ-max: 2.659\tLives: 2\tReward: 107.0\tEpisode Mean: 119.7\n",
+      "87597:127661037\tQ-min: 2.431\tQ-max: 2.550\tLives: 2\tReward: 108.0\tEpisode Mean: 119.7\n",
+      "87597:127661057\tQ-min: 2.465\tQ-max: 2.723\tLives: 2\tReward: 112.0\tEpisode Mean: 119.7\n",
+      "87597:127661073\tQ-min: -0.070\tQ-max: 0.399\tLives: 1\tReward: 112.0\tEpisode Mean: 119.7\n",
+      "87597:127661129\tQ-min: 2.122\tQ-max: 2.860\tLives: 1\tReward: 116.0\tEpisode Mean: 119.7\n",
+      "87597:127661143\tQ-min: -0.218\tQ-max: 0.260\tLives: 0\tReward: 116.0\tEpisode Mean: 119.3\n",
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+      "87598:127661263\tQ-min: 1.674\tQ-max: 1.685\tLives: 5\tReward: 2.0\tEpisode Mean: 119.3\n",
+      "87598:127661323\tQ-min: 1.664\tQ-max: 1.678\tLives: 5\tReward: 3.0\tEpisode Mean: 119.3\n",
+      "87598:127661369\tQ-min: 1.971\tQ-max: 2.008\tLives: 5\tReward: 4.0\tEpisode Mean: 119.3\n",
+      "87598:127661400\tQ-min: 1.955\tQ-max: 1.971\tLives: 5\tReward: 5.0\tEpisode Mean: 119.3\n",
+      "87598:127661436\tQ-min: 1.857\tQ-max: 1.902\tLives: 5\tReward: 6.0\tEpisode Mean: 119.3\n",
+      "87598:127661467\tQ-min: 1.752\tQ-max: 1.774\tLives: 5\tReward: 7.0\tEpisode Mean: 119.3\n",
+      "87598:127661514\tQ-min: 1.695\tQ-max: 1.717\tLives: 5\tReward: 8.0\tEpisode Mean: 119.3\n",
+      "87598:127661577\tQ-min: 1.667\tQ-max: 1.682\tLives: 5\tReward: 9.0\tEpisode Mean: 119.3\n",
+      "87598:127661643\tQ-min: 1.624\tQ-max: 1.745\tLives: 5\tReward: 10.0\tEpisode Mean: 119.3\n",
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+      "87598:127661758\tQ-min: 1.936\tQ-max: 1.955\tLives: 5\tReward: 12.0\tEpisode Mean: 119.3\n",
+      "87598:127661789\tQ-min: 1.967\tQ-max: 2.024\tLives: 5\tReward: 13.0\tEpisode Mean: 119.3\n",
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+      "87598:127661896\tQ-min: 1.922\tQ-max: 1.965\tLives: 4\tReward: 15.0\tEpisode Mean: 119.3\n",
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+      "87598:127662001\tQ-min: 1.951\tQ-max: 1.978\tLives: 4\tReward: 17.0\tEpisode Mean: 119.3\n",
+      "87598:127662037\tQ-min: 2.090\tQ-max: 2.104\tLives: 4\tReward: 18.0\tEpisode Mean: 119.3\n",
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+      "87598:127662221\tQ-min: 1.697\tQ-max: 1.741\tLives: 4\tReward: 25.0\tEpisode Mean: 119.3\n",
+      "87598:127662264\tQ-min: -0.043\tQ-max: 0.257\tLives: 3\tReward: 25.0\tEpisode Mean: 119.3\n",
+      "87598:127662316\tQ-min: 1.898\tQ-max: 1.918\tLives: 3\tReward: 26.0\tEpisode Mean: 119.3\n",
+      "87598:127662361\tQ-min: 1.909\tQ-max: 1.937\tLives: 3\tReward: 27.0\tEpisode Mean: 119.3\n",
+      "87598:127662407\tQ-min: 2.013\tQ-max: 2.042\tLives: 3\tReward: 28.0\tEpisode Mean: 119.3\n",
+      "87598:127662444\tQ-min: 1.961\tQ-max: 1.991\tLives: 3\tReward: 29.0\tEpisode Mean: 119.3\n",
+      "87598:127662477\tQ-min: 2.115\tQ-max: 2.183\tLives: 3\tReward: 30.0\tEpisode Mean: 119.3\n",
+      "87598:127662509\tQ-min: 2.000\tQ-max: 2.069\tLives: 3\tReward: 31.0\tEpisode Mean: 119.3\n",
+      "87598:127662544\tQ-min: 2.006\tQ-max: 2.097\tLives: 3\tReward: 35.0\tEpisode Mean: 119.3\n",
+      "87598:127662593\tQ-min: 1.437\tQ-max: 1.659\tLives: 3\tReward: 36.0\tEpisode Mean: 119.3\n",
+      "87598:127662665\tQ-min: 1.732\tQ-max: 1.751\tLives: 3\tReward: 37.0\tEpisode Mean: 119.3\n",
+      "87598:127662729\tQ-min: 1.667\tQ-max: 1.811\tLives: 3\tReward: 38.0\tEpisode Mean: 119.3\n",
+      "87598:127662793\tQ-min: 1.746\tQ-max: 1.779\tLives: 3\tReward: 39.0\tEpisode Mean: 119.3\n",
+      "87598:127662843\tQ-min: 2.004\tQ-max: 2.053\tLives: 3\tReward: 40.0\tEpisode Mean: 119.3\n",
+      "87598:127662878\tQ-min: 2.104\tQ-max: 2.161\tLives: 3\tReward: 44.0\tEpisode Mean: 119.3\n",
+      "87598:127662912\tQ-min: 2.015\tQ-max: 2.115\tLives: 3\tReward: 48.0\tEpisode Mean: 119.3\n",
+      "87598:127662945\tQ-min: 2.035\tQ-max: 2.218\tLives: 3\tReward: 52.0\tEpisode Mean: 119.3\n",
+      "87598:127662981\tQ-min: 2.047\tQ-max: 2.229\tLives: 3\tReward: 56.0\tEpisode Mean: 119.3\n",
+      "87598:127663017\tQ-min: 2.274\tQ-max: 2.418\tLives: 3\tReward: 60.0\tEpisode Mean: 119.3\n",
+      "87598:127663057\tQ-min: 1.995\tQ-max: 2.390\tLives: 3\tReward: 64.0\tEpisode Mean: 119.3\n",
+      "87598:127663079\tQ-min: 2.243\tQ-max: 2.510\tLives: 3\tReward: 68.0\tEpisode Mean: 119.3\n",
+      "87598:127663101\tQ-min: 2.320\tQ-max: 2.541\tLives: 3\tReward: 72.0\tEpisode Mean: 119.3\n",
+      "87598:127663123\tQ-min: 2.323\tQ-max: 2.403\tLives: 3\tReward: 79.0\tEpisode Mean: 119.3\n",
+      "87598:127663144\tQ-min: 2.353\tQ-max: 2.557\tLives: 3\tReward: 83.0\tEpisode Mean: 119.3\n",
+      "87598:127663168\tQ-min: 2.320\tQ-max: 2.440\tLives: 3\tReward: 87.0\tEpisode Mean: 119.3\n",
+      "87598:127663188\tQ-min: 2.030\tQ-max: 2.488\tLives: 3\tReward: 91.0\tEpisode Mean: 119.3\n",
+      "87598:127663203\tQ-min: 0.163\tQ-max: 0.445\tLives: 2\tReward: 91.0\tEpisode Mean: 119.3\n",
+      "87598:127663249\tQ-min: 2.209\tQ-max: 2.274\tLives: 2\tReward: 92.0\tEpisode Mean: 119.3\n",
+      "87598:127663306\tQ-min: 2.173\tQ-max: 2.579\tLives: 2\tReward: 96.0\tEpisode Mean: 119.3\n",
+      "87598:127663321\tQ-min: -0.015\tQ-max: 0.340\tLives: 1\tReward: 96.0\tEpisode Mean: 119.3\n",
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+      "87598:127663423\tQ-min: 2.059\tQ-max: 2.137\tLives: 1\tReward: 101.0\tEpisode Mean: 119.3\n",
+      "87598:127663475\tQ-min: 2.365\tQ-max: 2.465\tLives: 1\tReward: 102.0\tEpisode Mean: 119.3\n",
+      "87598:127663516\tQ-min: 2.050\tQ-max: 2.623\tLives: 1\tReward: 109.0\tEpisode Mean: 119.3\n",
+      "87598:127663539\tQ-min: 2.045\tQ-max: 2.740\tLives: 1\tReward: 113.0\tEpisode Mean: 119.3\n",
+      "87598:127663560\tQ-min: 2.421\tQ-max: 2.652\tLives: 1\tReward: 117.0\tEpisode Mean: 119.3\n",
+      "87598:127663581\tQ-min: 1.980\tQ-max: 2.516\tLives: 1\tReward: 121.0\tEpisode Mean: 119.3\n",
+      "87598:127663603\tQ-min: 2.362\tQ-max: 2.860\tLives: 1\tReward: 125.0\tEpisode Mean: 119.3\n",
+      "87598:127663623\tQ-min: 2.004\tQ-max: 3.475\tLives: 1\tReward: 129.0\tEpisode Mean: 119.3\n",
+      "87598:127663644\tQ-min: 2.571\tQ-max: 2.768\tLives: 1\tReward: 133.0\tEpisode Mean: 119.3\n",
+      "87598:127663665\tQ-min: 2.195\tQ-max: 2.878\tLives: 1\tReward: 137.0\tEpisode Mean: 119.3\n",
+      "87598:127663679\tQ-min: -0.607\tQ-max: -0.022\tLives: 0\tReward: 137.0\tEpisode Mean: 120.9\n",
+      "87599:127663726\tQ-min: 1.737\tQ-max: 1.761\tLives: 5\tReward: 1.0\tEpisode Mean: 120.9\n",
+      "87599:127663778\tQ-min: 1.641\tQ-max: 1.655\tLives: 5\tReward: 2.0\tEpisode Mean: 120.9\n",
+      "87599:127663828\tQ-min: 1.883\tQ-max: 1.905\tLives: 5\tReward: 3.0\tEpisode Mean: 120.9\n",
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+      "87599:127663928\tQ-min: 1.930\tQ-max: 1.946\tLives: 5\tReward: 6.0\tEpisode Mean: 120.9\n",
+      "87599:127663949\tQ-min: -0.241\tQ-max: 0.163\tLives: 4\tReward: 6.0\tEpisode Mean: 120.9\n",
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+      "87599:127664072\tQ-min: 1.938\tQ-max: 1.957\tLives: 4\tReward: 9.0\tEpisode Mean: 120.9\n",
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+      "87599:127665067\tQ-min: 2.250\tQ-max: 2.432\tLives: 2\tReward: 48.0\tEpisode Mean: 120.9\n",
+      "87599:127665090\tQ-min: 2.432\tQ-max: 2.499\tLives: 2\tReward: 55.0\tEpisode Mean: 120.9\n",
+      "87599:127665110\tQ-min: 2.427\tQ-max: 2.559\tLives: 2\tReward: 56.0\tEpisode Mean: 120.9\n",
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+      "87599:127665169\tQ-min: 2.424\tQ-max: 2.512\tLives: 1\tReward: 60.0\tEpisode Mean: 120.9\n",
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+      "87600:127665516\tQ-min: 1.885\tQ-max: 1.940\tLives: 5\tReward: 6.0\tEpisode Mean: 115.9\n",
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+      "87600:127665664\tQ-min: 1.683\tQ-max: 1.699\tLives: 5\tReward: 9.0\tEpisode Mean: 115.9\n",
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+      "87600:127665796\tQ-min: 1.660\tQ-max: 1.680\tLives: 5\tReward: 11.0\tEpisode Mean: 115.9\n",
+      "87600:127665847\tQ-min: 2.012\tQ-max: 2.020\tLives: 5\tReward: 15.0\tEpisode Mean: 115.9\n",
+      "87600:127665879\tQ-min: 1.947\tQ-max: 1.995\tLives: 5\tReward: 16.0\tEpisode Mean: 115.9\n",
+      "87600:127665914\tQ-min: 1.703\tQ-max: 1.790\tLives: 5\tReward: 17.0\tEpisode Mean: 115.9\n",
+      "87600:127665949\tQ-min: 1.917\tQ-max: 2.071\tLives: 5\tReward: 21.0\tEpisode Mean: 115.9\n",
+      "87600:127665972\tQ-min: -0.073\tQ-max: 0.402\tLives: 4\tReward: 21.0\tEpisode Mean: 115.9\n",
+      "87600:127666015\tQ-min: 1.913\tQ-max: 1.929\tLives: 4\tReward: 22.0\tEpisode Mean: 115.9\n",
+      "87600:127666067\tQ-min: 1.786\tQ-max: 1.824\tLives: 4\tReward: 23.0\tEpisode Mean: 115.9\n",
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+      "87600:127666156\tQ-min: 2.017\tQ-max: 2.055\tLives: 4\tReward: 25.0\tEpisode Mean: 115.9\n",
+      "87600:127666187\tQ-min: 2.090\tQ-max: 2.105\tLives: 4\tReward: 26.0\tEpisode Mean: 115.9\n",
+      "87600:127666219\tQ-min: 2.035\tQ-max: 2.050\tLives: 4\tReward: 27.0\tEpisode Mean: 115.9\n",
+      "87600:127666252\tQ-min: 1.887\tQ-max: 1.992\tLives: 4\tReward: 28.0\tEpisode Mean: 115.9\n",
+      "87600:127666302\tQ-min: 1.616\tQ-max: 1.821\tLives: 4\tReward: 32.0\tEpisode Mean: 115.9\n",
+      "87600:127666364\tQ-min: 1.836\tQ-max: 1.865\tLives: 4\tReward: 33.0\tEpisode Mean: 115.9\n",
+      "87600:127666433\tQ-min: 1.642\tQ-max: 1.861\tLives: 4\tReward: 37.0\tEpisode Mean: 115.9\n",
+      "87600:127666501\tQ-min: 1.760\tQ-max: 1.850\tLives: 4\tReward: 38.0\tEpisode Mean: 115.9\n",
+      "87600:127666550\tQ-min: 2.020\tQ-max: 2.126\tLives: 4\tReward: 39.0\tEpisode Mean: 115.9\n",
+      "87600:127666585\tQ-min: 2.036\tQ-max: 2.090\tLives: 4\tReward: 40.0\tEpisode Mean: 115.9\n",
+      "87600:127666616\tQ-min: 2.141\tQ-max: 2.219\tLives: 4\tReward: 41.0\tEpisode Mean: 115.9\n",
+      "87600:127666649\tQ-min: 2.192\tQ-max: 2.298\tLives: 4\tReward: 45.0\tEpisode Mean: 115.9\n",
+      "87600:127666684\tQ-min: 2.144\tQ-max: 2.288\tLives: 4\tReward: 49.0\tEpisode Mean: 115.9\n",
+      "87600:127666707\tQ-min: -0.094\tQ-max: 0.164\tLives: 3\tReward: 49.0\tEpisode Mean: 115.9\n",
+      "87600:127666761\tQ-min: 1.728\tQ-max: 1.789\tLives: 3\tReward: 50.0\tEpisode Mean: 115.9\n",
+      "87600:127666801\tQ-min: -0.084\tQ-max: 0.261\tLives: 2\tReward: 50.0\tEpisode Mean: 115.9\n",
+      "87600:127666859\tQ-min: 1.661\tQ-max: 1.769\tLives: 2\tReward: 54.0\tEpisode Mean: 115.9\n",
+      "87600:127666917\tQ-min: 2.044\tQ-max: 2.237\tLives: 2\tReward: 58.0\tEpisode Mean: 115.9\n",
+      "87600:127666974\tQ-min: 1.945\tQ-max: 2.079\tLives: 2\tReward: 59.0\tEpisode Mean: 115.9\n",
+      "87600:127667026\tQ-min: 2.108\tQ-max: 2.221\tLives: 2\tReward: 63.0\tEpisode Mean: 115.9\n",
+      "87600:127667062\tQ-min: 2.305\tQ-max: 2.482\tLives: 2\tReward: 67.0\tEpisode Mean: 115.9\n",
+      "87600:127667087\tQ-min: 2.277\tQ-max: 2.414\tLives: 2\tReward: 68.0\tEpisode Mean: 115.9\n",
+      "87600:127667108\tQ-min: 2.357\tQ-max: 2.434\tLives: 2\tReward: 72.0\tEpisode Mean: 115.9\n",
+      "87600:127667134\tQ-min: 1.988\tQ-max: 2.563\tLives: 2\tReward: 79.0\tEpisode Mean: 115.9\n",
+      "87600:127667158\tQ-min: 2.256\tQ-max: 2.404\tLives: 2\tReward: 83.0\tEpisode Mean: 115.9\n",
+      "87600:127667180\tQ-min: 2.289\tQ-max: 2.489\tLives: 2\tReward: 87.0\tEpisode Mean: 115.9\n",
+      "87600:127667201\tQ-min: 2.392\tQ-max: 2.561\tLives: 2\tReward: 91.0\tEpisode Mean: 115.9\n",
+      "87600:127667223\tQ-min: 2.205\tQ-max: 2.615\tLives: 2\tReward: 95.0\tEpisode Mean: 115.9\n",
+      "87600:127667246\tQ-min: 2.355\tQ-max: 2.599\tLives: 2\tReward: 96.0\tEpisode Mean: 115.9\n",
+      "87600:127667259\tQ-min: 0.162\tQ-max: 0.229\tLives: 1\tReward: 96.0\tEpisode Mean: 115.9\n",
+      "87600:127667318\tQ-min: 2.092\tQ-max: 2.474\tLives: 1\tReward: 100.0\tEpisode Mean: 115.9\n",
+      "87600:127667338\tQ-min: 2.278\tQ-max: 2.649\tLives: 1\tReward: 101.0\tEpisode Mean: 115.9\n",
+      "87600:127667358\tQ-min: 1.856\tQ-max: 2.470\tLives: 1\tReward: 105.0\tEpisode Mean: 115.9\n",
+      "87600:127667381\tQ-min: 2.661\tQ-max: 2.842\tLives: 1\tReward: 112.0\tEpisode Mean: 115.9\n",
+      "87600:127667395\tQ-min: 0.031\tQ-max: 0.259\tLives: 0\tReward: 112.0\tEpisode Mean: 115.6\n",
+      "87601:127667437\tQ-min: 1.772\tQ-max: 1.784\tLives: 5\tReward: 1.0\tEpisode Mean: 115.6\n",
+      "87601:127667478\tQ-min: 1.801\tQ-max: 1.829\tLives: 5\tReward: 2.0\tEpisode Mean: 115.6\n",
+      "87601:127667534\tQ-min: 1.698\tQ-max: 1.733\tLives: 5\tReward: 3.0\tEpisode Mean: 115.6\n",
+      "87601:127667580\tQ-min: 2.026\tQ-max: 2.073\tLives: 5\tReward: 4.0\tEpisode Mean: 115.6\n",
+      "87601:127667613\tQ-min: 1.956\tQ-max: 1.969\tLives: 5\tReward: 5.0\tEpisode Mean: 115.6\n",
+      "87601:127667646\tQ-min: 1.951\tQ-max: 1.978\tLives: 5\tReward: 6.0\tEpisode Mean: 115.6\n",
+      "87601:127667676\tQ-min: 1.863\tQ-max: 1.884\tLives: 5\tReward: 7.0\tEpisode Mean: 115.6\n",
+      "87601:127667695\tQ-min: -0.098\tQ-max: 0.156\tLives: 4\tReward: 7.0\tEpisode Mean: 115.6\n",
+      "87601:127667751\tQ-min: 1.660\tQ-max: 1.695\tLives: 4\tReward: 8.0\tEpisode Mean: 115.6\n",
+      "87601:127667809\tQ-min: 1.827\tQ-max: 1.867\tLives: 4\tReward: 9.0\tEpisode Mean: 115.6\n",
+      "87601:127667849\tQ-min: 1.889\tQ-max: 1.934\tLives: 4\tReward: 10.0\tEpisode Mean: 115.6\n",
+      "87601:127667886\tQ-min: 1.946\tQ-max: 1.981\tLives: 4\tReward: 11.0\tEpisode Mean: 115.6\n",
+      "87601:127667920\tQ-min: 1.944\tQ-max: 2.004\tLives: 4\tReward: 12.0\tEpisode Mean: 115.6\n",
+      "87601:127667957\tQ-min: 2.018\tQ-max: 2.054\tLives: 4\tReward: 16.0\tEpisode Mean: 115.6\n",
+      "87601:127667990\tQ-min: 1.935\tQ-max: 1.957\tLives: 4\tReward: 17.0\tEpisode Mean: 115.6\n",
+      "87601:127668036\tQ-min: 1.710\tQ-max: 1.733\tLives: 4\tReward: 18.0\tEpisode Mean: 115.6\n",
+      "87601:127668100\tQ-min: 1.683\tQ-max: 1.779\tLives: 4\tReward: 19.0\tEpisode Mean: 115.6\n",
+      "87601:127668164\tQ-min: 1.713\tQ-max: 1.733\tLives: 4\tReward: 20.0\tEpisode Mean: 115.6\n",
+      "87601:127668229\tQ-min: 1.737\tQ-max: 1.761\tLives: 4\tReward: 21.0\tEpisode Mean: 115.6\n",
+      "87601:127668275\tQ-min: 2.023\tQ-max: 2.044\tLives: 4\tReward: 22.0\tEpisode Mean: 115.6\n",
+      "87601:127668307\tQ-min: 1.987\tQ-max: 2.020\tLives: 4\tReward: 23.0\tEpisode Mean: 115.6\n",
+      "87601:127668339\tQ-min: 1.988\tQ-max: 2.029\tLives: 4\tReward: 24.0\tEpisode Mean: 115.6\n",
+      "87601:127668373\tQ-min: 2.085\tQ-max: 2.160\tLives: 4\tReward: 28.0\tEpisode Mean: 115.6\n",
+      "87601:127668411\tQ-min: 2.098\tQ-max: 2.124\tLives: 4\tReward: 29.0\tEpisode Mean: 115.6\n",
+      "87601:127668445\tQ-min: 2.101\tQ-max: 2.198\tLives: 4\tReward: 30.0\tEpisode Mean: 115.6\n",
+      "87601:127668478\tQ-min: 1.852\tQ-max: 2.134\tLives: 4\tReward: 34.0\tEpisode Mean: 115.6\n",
+      "87601:127668513\tQ-min: 2.055\tQ-max: 2.151\tLives: 4\tReward: 35.0\tEpisode Mean: 115.6\n",
+      "87601:127668547\tQ-min: 2.125\tQ-max: 2.159\tLives: 4\tReward: 39.0\tEpisode Mean: 115.6\n",
+      "87601:127668581\tQ-min: 2.101\tQ-max: 2.164\tLives: 4\tReward: 40.0\tEpisode Mean: 115.6\n",
+      "87601:127668605\tQ-min: -0.338\tQ-max: 0.211\tLives: 3\tReward: 40.0\tEpisode Mean: 115.6\n",
+      "87601:127668650\tQ-min: 1.977\tQ-max: 2.007\tLives: 3\tReward: 41.0\tEpisode Mean: 115.6\n",
+      "87601:127668701\tQ-min: 1.801\tQ-max: 1.886\tLives: 3\tReward: 42.0\tEpisode Mean: 115.6\n",
+      "87601:127668755\tQ-min: 1.908\tQ-max: 2.023\tLives: 3\tReward: 46.0\tEpisode Mean: 115.6\n",
+      "87601:127668792\tQ-min: 2.100\tQ-max: 2.161\tLives: 3\tReward: 47.0\tEpisode Mean: 115.6\n",
+      "87601:127668826\tQ-min: 2.139\tQ-max: 2.307\tLives: 3\tReward: 51.0\tEpisode Mean: 115.6\n",
+      "87601:127668862\tQ-min: 2.257\tQ-max: 2.364\tLives: 3\tReward: 52.0\tEpisode Mean: 115.6\n",
+      "87601:127668896\tQ-min: 2.252\tQ-max: 2.286\tLives: 3\tReward: 56.0\tEpisode Mean: 115.6\n",
+      "87601:127668950\tQ-min: 2.458\tQ-max: 2.644\tLives: 3\tReward: 60.0\tEpisode Mean: 115.6\n",
+      "87601:127668969\tQ-min: 2.445\tQ-max: 2.567\tLives: 3\tReward: 64.0\tEpisode Mean: 115.6\n",
+      "87601:127668990\tQ-min: 2.207\tQ-max: 2.511\tLives: 3\tReward: 65.0\tEpisode Mean: 115.6\n",
+      "87601:127669016\tQ-min: 2.154\tQ-max: 2.517\tLives: 3\tReward: 69.0\tEpisode Mean: 115.6\n",
+      "87601:127669038\tQ-min: 2.318\tQ-max: 2.589\tLives: 3\tReward: 73.0\tEpisode Mean: 115.6\n",
+      "87601:127669062\tQ-min: 2.291\tQ-max: 2.456\tLives: 3\tReward: 77.0\tEpisode Mean: 115.6\n",
+      "87601:127669085\tQ-min: 2.295\tQ-max: 2.671\tLives: 3\tReward: 78.0\tEpisode Mean: 115.6\n",
+      "87601:127669106\tQ-min: 2.310\tQ-max: 2.570\tLives: 3\tReward: 82.0\tEpisode Mean: 115.6\n",
+      "87601:127669120\tQ-min: 0.417\tQ-max: 0.690\tLives: 2\tReward: 82.0\tEpisode Mean: 115.6\n",
+      "87601:127669179\tQ-min: 1.564\tQ-max: 2.235\tLives: 2\tReward: 86.0\tEpisode Mean: 115.6\n",
+      "87601:127669240\tQ-min: 2.395\tQ-max: 2.511\tLives: 2\tReward: 90.0\tEpisode Mean: 115.6\n",
+      "87601:127669287\tQ-min: 2.236\tQ-max: 2.443\tLives: 2\tReward: 91.0\tEpisode Mean: 115.6\n",
+      "87601:127669328\tQ-min: 2.062\tQ-max: 2.538\tLives: 2\tReward: 95.0\tEpisode Mean: 115.6\n",
+      "87601:127669341\tQ-min: -0.015\tQ-max: 0.200\tLives: 1\tReward: 95.0\tEpisode Mean: 115.6\n",
+      "87601:127669387\tQ-min: 2.552\tQ-max: 2.691\tLives: 1\tReward: 99.0\tEpisode Mean: 115.6\n",
+      "87601:127669411\tQ-min: 2.696\tQ-max: 3.138\tLives: 1\tReward: 106.0\tEpisode Mean: 115.6\n",
+      "87601:127669434\tQ-min: 2.198\tQ-max: 3.207\tLives: 1\tReward: 110.0\tEpisode Mean: 115.6\n",
+      "87601:127669448\tQ-min: -0.426\tQ-max: -0.075\tLives: 0\tReward: 110.0\tEpisode Mean: 115.2\n",
+      "87602:127669494\tQ-min: 1.846\tQ-max: 1.862\tLives: 5\tReward: 1.0\tEpisode Mean: 115.2\n",
+      "87602:127669536\tQ-min: 1.860\tQ-max: 1.868\tLives: 5\tReward: 2.0\tEpisode Mean: 115.2\n",
+      "87602:127669580\tQ-min: 1.858\tQ-max: 1.872\tLives: 5\tReward: 3.0\tEpisode Mean: 115.2\n",
+      "87602:127669620\tQ-min: 2.002\tQ-max: 2.026\tLives: 5\tReward: 4.0\tEpisode Mean: 115.2\n",
+      "87602:127669641\tQ-min: -0.373\tQ-max: 0.258\tLives: 4\tReward: 4.0\tEpisode Mean: 115.2\n",
+      "87602:127669685\tQ-min: 1.873\tQ-max: 1.892\tLives: 4\tReward: 5.0\tEpisode Mean: 115.2\n",
+      "87602:127669737\tQ-min: 1.650\tQ-max: 1.670\tLives: 4\tReward: 6.0\tEpisode Mean: 115.2\n",
+      "87602:127669801\tQ-min: 1.640\tQ-max: 1.661\tLives: 4\tReward: 7.0\tEpisode Mean: 115.2\n",
+      "87602:127669850\tQ-min: 1.912\tQ-max: 2.008\tLives: 4\tReward: 8.0\tEpisode Mean: 115.2\n",
+      "87602:127669881\tQ-min: 1.983\tQ-max: 2.014\tLives: 4\tReward: 9.0\tEpisode Mean: 115.2\n",
+      "87602:127669917\tQ-min: 1.920\tQ-max: 1.981\tLives: 4\tReward: 10.0\tEpisode Mean: 115.2\n",
+      "87602:127669938\tQ-min: -0.144\tQ-max: 0.120\tLives: 3\tReward: 10.0\tEpisode Mean: 115.2\n",
+      "87602:127669982\tQ-min: 1.895\tQ-max: 1.932\tLives: 3\tReward: 11.0\tEpisode Mean: 115.2\n",
+      "87602:127670025\tQ-min: 1.828\tQ-max: 1.842\tLives: 3\tReward: 12.0\tEpisode Mean: 115.2\n",
+      "87602:127670075\tQ-min: 1.724\tQ-max: 1.734\tLives: 3\tReward: 13.0\tEpisode Mean: 115.2\n",
+      "87602:127670123\tQ-min: 1.911\tQ-max: 2.000\tLives: 3\tReward: 14.0\tEpisode Mean: 115.2\n",
+      "87602:127670154\tQ-min: 1.969\tQ-max: 1.996\tLives: 3\tReward: 15.0\tEpisode Mean: 115.2\n",
+      "87602:127670185\tQ-min: 1.919\tQ-max: 1.964\tLives: 3\tReward: 16.0\tEpisode Mean: 115.2\n",
+      "87602:127670215\tQ-min: 1.985\tQ-max: 2.007\tLives: 3\tReward: 17.0\tEpisode Mean: 115.2\n",
+      "87602:127670265\tQ-min: 1.564\tQ-max: 1.657\tLives: 3\tReward: 18.0\tEpisode Mean: 115.2\n",
+      "87602:127670336\tQ-min: 1.535\tQ-max: 1.684\tLives: 3\tReward: 22.0\tEpisode Mean: 115.2\n",
+      "87602:127670405\tQ-min: 1.777\tQ-max: 1.811\tLives: 3\tReward: 23.0\tEpisode Mean: 115.2\n",
+      "87602:127670467\tQ-min: 1.716\tQ-max: 1.739\tLives: 3\tReward: 24.0\tEpisode Mean: 115.2\n",
+      "87602:127670515\tQ-min: 2.014\tQ-max: 2.067\tLives: 3\tReward: 25.0\tEpisode Mean: 115.2\n",
+      "87602:127670548\tQ-min: 1.974\tQ-max: 2.002\tLives: 3\tReward: 26.0\tEpisode Mean: 115.2\n",
+      "87602:127670580\tQ-min: 1.974\tQ-max: 2.119\tLives: 3\tReward: 27.0\tEpisode Mean: 115.2\n",
+      "87602:127670615\tQ-min: 1.962\tQ-max: 1.986\tLives: 3\tReward: 28.0\tEpisode Mean: 115.2\n",
+      "87602:127670647\tQ-min: 2.032\tQ-max: 2.077\tLives: 3\tReward: 32.0\tEpisode Mean: 115.2\n",
+      "87602:127670680\tQ-min: 2.066\tQ-max: 2.091\tLives: 3\tReward: 33.0\tEpisode Mean: 115.2\n",
+      "87602:127670713\tQ-min: 2.021\tQ-max: 2.056\tLives: 3\tReward: 34.0\tEpisode Mean: 115.2\n",
+      "87602:127670745\tQ-min: 2.046\tQ-max: 2.105\tLives: 3\tReward: 38.0\tEpisode Mean: 115.2\n",
+      "87602:127670783\tQ-min: 2.086\tQ-max: 2.412\tLives: 3\tReward: 42.0\tEpisode Mean: 115.2\n",
+      "87602:127670805\tQ-min: 2.380\tQ-max: 2.468\tLives: 3\tReward: 46.0\tEpisode Mean: 115.2\n",
+      "87602:127670818\tQ-min: 0.071\tQ-max: 0.488\tLives: 2\tReward: 46.0\tEpisode Mean: 115.2\n",
+      "87602:127670865\tQ-min: 1.958\tQ-max: 1.985\tLives: 2\tReward: 47.0\tEpisode Mean: 115.2\n",
+      "87602:127670919\tQ-min: 1.791\tQ-max: 1.872\tLives: 2\tReward: 48.0\tEpisode Mean: 115.2\n",
+      "87602:127670979\tQ-min: 2.222\tQ-max: 2.258\tLives: 2\tReward: 52.0\tEpisode Mean: 115.2\n",
+      "87602:127671021\tQ-min: 2.213\tQ-max: 2.297\tLives: 2\tReward: 56.0\tEpisode Mean: 115.2\n",
+      "87602:127671054\tQ-min: 2.162\tQ-max: 2.189\tLives: 2\tReward: 57.0\tEpisode Mean: 115.2\n",
+      "87602:127671075\tQ-min: -0.140\tQ-max: 0.236\tLives: 1\tReward: 57.0\tEpisode Mean: 115.2\n",
+      "87602:127671125\tQ-min: 1.914\tQ-max: 1.943\tLives: 1\tReward: 58.0\tEpisode Mean: 115.2\n",
+      "87602:127671178\tQ-min: 2.243\tQ-max: 2.269\tLives: 1\tReward: 62.0\tEpisode Mean: 115.2\n",
+      "87602:127671238\tQ-min: 1.732\tQ-max: 1.933\tLives: 1\tReward: 66.0\tEpisode Mean: 115.2\n",
+      "87602:127671291\tQ-min: 2.280\tQ-max: 2.326\tLives: 1\tReward: 67.0\tEpisode Mean: 115.2\n",
+      "87602:127671328\tQ-min: 2.262\tQ-max: 2.353\tLives: 1\tReward: 71.0\tEpisode Mean: 115.2\n",
+      "87602:127671364\tQ-min: 2.267\tQ-max: 2.402\tLives: 1\tReward: 72.0\tEpisode Mean: 115.2\n",
+      "87602:127671401\tQ-min: 2.009\tQ-max: 2.370\tLives: 1\tReward: 76.0\tEpisode Mean: 115.2\n",
+      "87602:127671456\tQ-min: 1.768\tQ-max: 2.448\tLives: 1\tReward: 80.0\tEpisode Mean: 115.2\n",
+      "87602:127671478\tQ-min: 2.276\tQ-max: 2.643\tLives: 1\tReward: 84.0\tEpisode Mean: 115.2\n",
+      "87602:127671501\tQ-min: 2.352\tQ-max: 2.703\tLives: 1\tReward: 88.0\tEpisode Mean: 115.2\n",
+      "87602:127671524\tQ-min: 2.497\tQ-max: 2.574\tLives: 1\tReward: 92.0\tEpisode Mean: 115.2\n",
+      "87602:127671546\tQ-min: 1.849\tQ-max: 2.531\tLives: 1\tReward: 99.0\tEpisode Mean: 115.2\n",
+      "87602:127671571\tQ-min: 1.826\tQ-max: 2.690\tLives: 1\tReward: 103.0\tEpisode Mean: 115.2\n",
+      "87602:127671592\tQ-min: 2.442\tQ-max: 2.700\tLives: 1\tReward: 110.0\tEpisode Mean: 115.2\n",
+      "87602:127671613\tQ-min: 2.514\tQ-max: 2.937\tLives: 1\tReward: 114.0\tEpisode Mean: 115.2\n",
+      "87602:127671634\tQ-min: 1.072\tQ-max: 1.905\tLives: 1\tReward: 121.0\tEpisode Mean: 115.2\n",
+      "87602:127671648\tQ-min: -0.075\tQ-max: 0.241\tLives: 0\tReward: 121.0\tEpisode Mean: 115.6\n",
+      "87603:127671690\tQ-min: 1.763\tQ-max: 1.773\tLives: 5\tReward: 1.0\tEpisode Mean: 115.6\n",
+      "87603:127671729\tQ-min: 1.778\tQ-max: 1.796\tLives: 5\tReward: 2.0\tEpisode Mean: 115.6\n",
+      "87603:127671769\tQ-min: 1.926\tQ-max: 1.961\tLives: 5\tReward: 3.0\tEpisode Mean: 115.6\n",
+      "87603:127671807\tQ-min: 1.948\tQ-max: 1.971\tLives: 5\tReward: 4.0\tEpisode Mean: 115.6\n",
+      "87603:127671838\tQ-min: 2.037\tQ-max: 2.049\tLives: 5\tReward: 5.0\tEpisode Mean: 115.6\n",
+      "87603:127671870\tQ-min: 1.952\tQ-max: 1.976\tLives: 5\tReward: 6.0\tEpisode Mean: 115.6\n",
+      "87603:127671903\tQ-min: 1.955\tQ-max: 1.988\tLives: 5\tReward: 10.0\tEpisode Mean: 115.6\n",
+      "87603:127671953\tQ-min: 1.723\tQ-max: 1.739\tLives: 5\tReward: 11.0\tEpisode Mean: 115.6\n",
+      "87603:127672020\tQ-min: 1.764\tQ-max: 1.810\tLives: 5\tReward: 12.0\tEpisode Mean: 115.6\n",
+      "87603:127672087\tQ-min: 1.706\tQ-max: 1.776\tLives: 5\tReward: 13.0\tEpisode Mean: 115.6\n",
+      "87603:127672151\tQ-min: 1.714\tQ-max: 1.727\tLives: 5\tReward: 14.0\tEpisode Mean: 115.6\n",
+      "87603:127672199\tQ-min: 2.007\tQ-max: 2.077\tLives: 5\tReward: 15.0\tEpisode Mean: 115.6\n",
+      "87603:127672229\tQ-min: 1.977\tQ-max: 1.998\tLives: 5\tReward: 16.0\tEpisode Mean: 115.6\n",
+      "87603:127672260\tQ-min: 1.934\tQ-max: 1.969\tLives: 5\tReward: 17.0\tEpisode Mean: 115.6\n",
+      "87603:127672291\tQ-min: 2.022\tQ-max: 2.062\tLives: 5\tReward: 18.0\tEpisode Mean: 115.6\n",
+      "87603:127672325\tQ-min: 1.969\tQ-max: 2.009\tLives: 5\tReward: 19.0\tEpisode Mean: 115.6\n",
+      "87603:127672358\tQ-min: 1.991\tQ-max: 2.011\tLives: 5\tReward: 20.0\tEpisode Mean: 115.6\n",
+      "87603:127672391\tQ-min: 1.996\tQ-max: 2.031\tLives: 5\tReward: 21.0\tEpisode Mean: 115.6\n",
+      "87603:127672413\tQ-min: -0.426\tQ-max: 0.296\tLives: 4\tReward: 21.0\tEpisode Mean: 115.6\n",
+      "87603:127672469\tQ-min: 1.668\tQ-max: 1.694\tLives: 4\tReward: 22.0\tEpisode Mean: 115.6\n",
+      "87603:127672530\tQ-min: 1.771\tQ-max: 1.785\tLives: 4\tReward: 23.0\tEpisode Mean: 115.6\n",
+      "87603:127672582\tQ-min: 1.946\tQ-max: 1.987\tLives: 4\tReward: 24.0\tEpisode Mean: 115.6\n",
+      "87603:127672620\tQ-min: 1.989\tQ-max: 2.026\tLives: 4\tReward: 25.0\tEpisode Mean: 115.6\n",
+      "87603:127672654\tQ-min: 1.998\tQ-max: 2.088\tLives: 4\tReward: 26.0\tEpisode Mean: 115.6\n",
+      "87603:127672690\tQ-min: 2.024\tQ-max: 2.072\tLives: 4\tReward: 30.0\tEpisode Mean: 115.6\n",
+      "87603:127672724\tQ-min: 2.083\tQ-max: 2.123\tLives: 4\tReward: 31.0\tEpisode Mean: 115.6\n",
+      "87603:127672771\tQ-min: 1.733\tQ-max: 1.756\tLives: 4\tReward: 32.0\tEpisode Mean: 115.6\n",
+      "87603:127672833\tQ-min: 1.771\tQ-max: 1.959\tLives: 4\tReward: 36.0\tEpisode Mean: 115.6\n",
+      "87603:127672899\tQ-min: 1.730\tQ-max: 1.757\tLives: 4\tReward: 37.0\tEpisode Mean: 115.6\n",
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+      "87603:127673038\tQ-min: 2.124\tQ-max: 2.300\tLives: 4\tReward: 46.0\tEpisode Mean: 115.6\n",
+      "87603:127673057\tQ-min: 2.286\tQ-max: 2.395\tLives: 4\tReward: 50.0\tEpisode Mean: 115.6\n",
+      "87603:127673078\tQ-min: 2.265\tQ-max: 2.469\tLives: 4\tReward: 54.0\tEpisode Mean: 115.6\n",
+      "87603:127673099\tQ-min: 2.380\tQ-max: 2.475\tLives: 4\tReward: 55.0\tEpisode Mean: 115.6\n",
+      "87603:127673123\tQ-min: 2.106\tQ-max: 2.561\tLives: 4\tReward: 59.0\tEpisode Mean: 115.6\n",
+      "87603:127673145\tQ-min: 2.153\tQ-max: 2.521\tLives: 4\tReward: 63.0\tEpisode Mean: 115.6\n",
+      "87603:127673168\tQ-min: 2.169\tQ-max: 2.521\tLives: 4\tReward: 67.0\tEpisode Mean: 115.6\n",
+      "87603:127673192\tQ-min: 1.558\tQ-max: 2.663\tLives: 4\tReward: 74.0\tEpisode Mean: 115.6\n",
+      "87603:127673215\tQ-min: 1.016\tQ-max: 2.691\tLives: 4\tReward: 81.0\tEpisode Mean: 115.6\n",
+      "87603:127673229\tQ-min: -0.185\tQ-max: 0.329\tLives: 3\tReward: 81.0\tEpisode Mean: 115.6\n",
+      "87603:127673283\tQ-min: 1.876\tQ-max: 1.961\tLives: 3\tReward: 82.0\tEpisode Mean: 115.6\n",
+      "87603:127673353\tQ-min: 1.985\tQ-max: 2.072\tLives: 3\tReward: 86.0\tEpisode Mean: 115.6\n",
+      "87603:127673407\tQ-min: 2.380\tQ-max: 2.514\tLives: 3\tReward: 87.0\tEpisode Mean: 115.6\n",
+      "87603:127673447\tQ-min: 2.269\tQ-max: 2.633\tLives: 3\tReward: 91.0\tEpisode Mean: 115.6\n",
+      "87603:127673481\tQ-min: 2.455\tQ-max: 2.735\tLives: 3\tReward: 95.0\tEpisode Mean: 115.6\n",
+      "87603:127673518\tQ-min: 1.768\tQ-max: 3.135\tLives: 3\tReward: 99.0\tEpisode Mean: 115.6\n",
+      "87603:127673531\tQ-min: -0.043\tQ-max: 0.415\tLives: 2\tReward: 99.0\tEpisode Mean: 115.6\n",
+      "87603:127673585\tQ-min: 2.326\tQ-max: 2.456\tLives: 2\tReward: 100.0\tEpisode Mean: 115.6\n",
+      "87603:127673655\tQ-min: 1.971\tQ-max: 2.831\tLives: 2\tReward: 104.0\tEpisode Mean: 115.6\n",
+      "87603:127673715\tQ-min: 2.525\tQ-max: 2.808\tLives: 2\tReward: 105.0\tEpisode Mean: 115.6\n",
+      "87603:127673755\tQ-min: 2.514\tQ-max: 2.690\tLives: 2\tReward: 109.0\tEpisode Mean: 115.6\n",
+      "87603:127673778\tQ-min: 2.405\tQ-max: 2.939\tLives: 2\tReward: 116.0\tEpisode Mean: 115.6\n",
+      "87603:127673801\tQ-min: 2.501\tQ-max: 2.843\tLives: 2\tReward: 120.0\tEpisode Mean: 115.6\n",
+      "87603:127673816\tQ-min: 0.207\tQ-max: 0.486\tLives: 1\tReward: 120.0\tEpisode Mean: 115.6\n",
+      "87603:127673871\tQ-min: 2.058\tQ-max: 2.291\tLives: 1\tReward: 121.0\tEpisode Mean: 115.6\n",
+      "87603:127673931\tQ-min: 2.451\tQ-max: 2.619\tLives: 1\tReward: 125.0\tEpisode Mean: 115.6\n",
+      "87603:127673961\tQ-min: -0.120\tQ-max: 0.246\tLives: 0\tReward: 125.0\tEpisode Mean: 116.2\n",
+      "87604:127674004\tQ-min: 1.712\tQ-max: 1.727\tLives: 5\tReward: 1.0\tEpisode Mean: 116.2\n",
+      "87604:127674058\tQ-min: 1.601\tQ-max: 1.640\tLives: 5\tReward: 2.0\tEpisode Mean: 116.2\n",
+      "87604:127674121\tQ-min: 1.680\tQ-max: 1.701\tLives: 5\tReward: 3.0\tEpisode Mean: 116.2\n",
+      "87604:127674169\tQ-min: 1.970\tQ-max: 1.998\tLives: 5\tReward: 4.0\tEpisode Mean: 116.2\n",
+      "87604:127674203\tQ-min: 1.933\tQ-max: 1.956\tLives: 5\tReward: 5.0\tEpisode Mean: 116.2\n",
+      "87604:127674236\tQ-min: 1.899\tQ-max: 1.954\tLives: 5\tReward: 6.0\tEpisode Mean: 116.2\n",
+      "87604:127674270\tQ-min: 1.745\tQ-max: 1.791\tLives: 5\tReward: 7.0\tEpisode Mean: 116.2\n",
+      "87604:127674317\tQ-min: 1.633\tQ-max: 1.675\tLives: 5\tReward: 8.0\tEpisode Mean: 116.2\n",
+      "87604:127674384\tQ-min: 1.578\tQ-max: 1.663\tLives: 5\tReward: 9.0\tEpisode Mean: 116.2\n",
+      "87604:127674450\tQ-min: 1.639\tQ-max: 1.650\tLives: 5\tReward: 10.0\tEpisode Mean: 116.2\n",
+      "87604:127674516\tQ-min: 1.689\tQ-max: 1.715\tLives: 5\tReward: 11.0\tEpisode Mean: 116.2\n",
+      "87604:127674566\tQ-min: 1.901\tQ-max: 2.028\tLives: 5\tReward: 12.0\tEpisode Mean: 116.2\n",
+      "87604:127674590\tQ-min: 0.057\tQ-max: 0.177\tLives: 4\tReward: 12.0\tEpisode Mean: 116.2\n",
+      "87604:127674633\tQ-min: 1.909\tQ-max: 1.937\tLives: 4\tReward: 13.0\tEpisode Mean: 116.2\n",
+      "87604:127674664\tQ-min: -0.219\tQ-max: 0.060\tLives: 3\tReward: 13.0\tEpisode Mean: 116.2\n",
+      "87604:127674710\tQ-min: 1.899\tQ-max: 1.941\tLives: 3\tReward: 17.0\tEpisode Mean: 116.2\n",
+      "87604:127674757\tQ-min: 2.001\tQ-max: 2.061\tLives: 3\tReward: 18.0\tEpisode Mean: 116.2\n",
+      "87604:127674803\tQ-min: 1.963\tQ-max: 2.027\tLives: 3\tReward: 19.0\tEpisode Mean: 116.2\n",
+      "87604:127674846\tQ-min: 2.039\tQ-max: 2.065\tLives: 3\tReward: 20.0\tEpisode Mean: 116.2\n",
+      "87604:127674866\tQ-min: -0.039\tQ-max: 0.309\tLives: 2\tReward: 20.0\tEpisode Mean: 116.2\n",
+      "87604:127674974\tQ-min: 1.860\tQ-max: 1.882\tLives: 2\tReward: 21.0\tEpisode Mean: 116.2\n",
+      "87604:127675021\tQ-min: 1.838\tQ-max: 1.922\tLives: 2\tReward: 25.0\tEpisode Mean: 116.2\n",
+      "87604:127675076\tQ-min: 1.763\tQ-max: 1.800\tLives: 2\tReward: 26.0\tEpisode Mean: 116.2\n",
+      "87604:127675123\tQ-min: 2.048\tQ-max: 2.080\tLives: 2\tReward: 27.0\tEpisode Mean: 116.2\n",
+      "87604:127675155\tQ-min: 2.133\tQ-max: 2.219\tLives: 2\tReward: 31.0\tEpisode Mean: 116.2\n",
+      "87604:127675194\tQ-min: 2.141\tQ-max: 2.510\tLives: 2\tReward: 35.0\tEpisode Mean: 116.2\n",
+      "87604:127675215\tQ-min: 2.279\tQ-max: 2.456\tLives: 2\tReward: 36.0\tEpisode Mean: 116.2\n",
+      "87604:127675234\tQ-min: 2.268\tQ-max: 2.562\tLives: 2\tReward: 37.0\tEpisode Mean: 116.2\n",
+      "87604:127675256\tQ-min: 2.287\tQ-max: 2.381\tLives: 2\tReward: 41.0\tEpisode Mean: 116.2\n",
+      "87604:127675277\tQ-min: 2.396\tQ-max: 2.486\tLives: 2\tReward: 42.0\tEpisode Mean: 116.2\n",
+      "87604:127675297\tQ-min: 2.355\tQ-max: 2.560\tLives: 2\tReward: 46.0\tEpisode Mean: 116.2\n",
+      "87604:127675317\tQ-min: 2.484\tQ-max: 2.578\tLives: 2\tReward: 47.0\tEpisode Mean: 116.2\n",
+      "87604:127675335\tQ-min: 2.340\tQ-max: 2.505\tLives: 2\tReward: 48.0\tEpisode Mean: 116.2\n",
+      "87604:127675355\tQ-min: 2.345\tQ-max: 2.403\tLives: 2\tReward: 49.0\tEpisode Mean: 116.2\n",
+      "87604:127675369\tQ-min: 0.086\tQ-max: 0.281\tLives: 1\tReward: 49.0\tEpisode Mean: 116.2\n",
+      "87604:127675413\tQ-min: 2.118\tQ-max: 2.130\tLives: 1\tReward: 50.0\tEpisode Mean: 116.2\n",
+      "87604:127675459\tQ-min: 2.116\tQ-max: 2.176\tLives: 1\tReward: 54.0\tEpisode Mean: 116.2\n",
+      "87604:127675519\tQ-min: 1.917\tQ-max: 1.969\tLives: 1\tReward: 55.0\tEpisode Mean: 116.2\n",
+      "87604:127675566\tQ-min: 2.229\tQ-max: 2.280\tLives: 1\tReward: 56.0\tEpisode Mean: 116.2\n",
+      "87604:127675597\tQ-min: 2.174\tQ-max: 2.217\tLives: 1\tReward: 57.0\tEpisode Mean: 116.2\n",
+      "87604:127675629\tQ-min: 2.081\tQ-max: 2.246\tLives: 1\tReward: 58.0\tEpisode Mean: 116.2\n",
+      "87604:127675663\tQ-min: 2.156\tQ-max: 2.261\tLives: 1\tReward: 62.0\tEpisode Mean: 116.2\n",
+      "87604:127675712\tQ-min: 1.844\tQ-max: 1.940\tLives: 1\tReward: 63.0\tEpisode Mean: 116.2\n",
+      "87604:127675777\tQ-min: 1.842\tQ-max: 1.905\tLives: 1\tReward: 64.0\tEpisode Mean: 116.2\n",
+      "87604:127675843\tQ-min: 1.753\tQ-max: 1.884\tLives: 1\tReward: 68.0\tEpisode Mean: 116.2\n",
+      "87604:127675909\tQ-min: 1.849\tQ-max: 1.920\tLives: 1\tReward: 69.0\tEpisode Mean: 116.2\n",
+      "87604:127675960\tQ-min: 2.219\tQ-max: 2.309\tLives: 1\tReward: 73.0\tEpisode Mean: 116.2\n",
+      "87604:127675996\tQ-min: 2.236\tQ-max: 2.317\tLives: 1\tReward: 74.0\tEpisode Mean: 116.2\n",
+      "87604:127676031\tQ-min: 2.235\tQ-max: 2.344\tLives: 1\tReward: 75.0\tEpisode Mean: 116.2\n",
+      "87604:127676055\tQ-min: -0.184\tQ-max: 0.132\tLives: 0\tReward: 75.0\tEpisode Mean: 113.8\n",
+      "87605:127676100\tQ-min: 1.728\tQ-max: 1.741\tLives: 5\tReward: 1.0\tEpisode Mean: 113.8\n",
+      "87605:127676143\tQ-min: 1.782\tQ-max: 1.821\tLives: 5\tReward: 2.0\tEpisode Mean: 113.8\n",
+      "87605:127676184\tQ-min: 1.895\tQ-max: 1.924\tLives: 5\tReward: 3.0\tEpisode Mean: 113.8\n",
+      "87605:127676221\tQ-min: 1.982\tQ-max: 2.001\tLives: 5\tReward: 4.0\tEpisode Mean: 113.8\n",
+      "87605:127676254\tQ-min: 1.910\tQ-max: 1.944\tLives: 5\tReward: 5.0\tEpisode Mean: 113.8\n",
+      "87605:127676285\tQ-min: 1.929\tQ-max: 1.943\tLives: 5\tReward: 6.0\tEpisode Mean: 113.8\n",
+      "87605:127676319\tQ-min: 1.768\tQ-max: 1.815\tLives: 5\tReward: 7.0\tEpisode Mean: 113.8\n",
+      "87605:127676342\tQ-min: -0.167\tQ-max: 0.291\tLives: 4\tReward: 7.0\tEpisode Mean: 113.8\n",
+      "87605:127676395\tQ-min: 1.653\tQ-max: 1.662\tLives: 4\tReward: 8.0\tEpisode Mean: 113.8\n",
+      "87605:127676451\tQ-min: 1.953\tQ-max: 2.010\tLives: 4\tReward: 12.0\tEpisode Mean: 113.8\n",
+      "87605:127676499\tQ-min: 1.979\tQ-max: 2.121\tLives: 4\tReward: 13.0\tEpisode Mean: 113.8\n",
+      "87605:127676538\tQ-min: 2.028\tQ-max: 2.045\tLives: 4\tReward: 14.0\tEpisode Mean: 113.8\n",
+      "87605:127676570\tQ-min: 1.959\tQ-max: 2.040\tLives: 4\tReward: 15.0\tEpisode Mean: 113.8\n",
+      "87605:127676602\tQ-min: 1.958\tQ-max: 1.976\tLives: 4\tReward: 16.0\tEpisode Mean: 113.8\n",
+      "87605:127676634\tQ-min: 2.033\tQ-max: 2.050\tLives: 4\tReward: 17.0\tEpisode Mean: 113.8\n",
+      "87605:127676685\tQ-min: 1.723\tQ-max: 1.733\tLives: 4\tReward: 18.0\tEpisode Mean: 113.8\n",
+      "87605:127676746\tQ-min: 1.699\tQ-max: 1.722\tLives: 4\tReward: 19.0\tEpisode Mean: 113.8\n",
+      "87605:127676811\tQ-min: 1.658\tQ-max: 1.797\tLives: 4\tReward: 20.0\tEpisode Mean: 113.8\n",
+      "87605:127676873\tQ-min: 1.677\tQ-max: 1.725\tLives: 4\tReward: 21.0\tEpisode Mean: 113.8\n",
+      "87605:127676923\tQ-min: 2.103\tQ-max: 2.153\tLives: 4\tReward: 22.0\tEpisode Mean: 113.8\n",
+      "87605:127676959\tQ-min: 2.068\tQ-max: 2.133\tLives: 4\tReward: 26.0\tEpisode Mean: 113.8\n",
+      "87605:127676996\tQ-min: 2.054\tQ-max: 2.265\tLives: 4\tReward: 30.0\tEpisode Mean: 113.8\n",
+      "87605:127677010\tQ-min: 0.105\tQ-max: 0.230\tLives: 3\tReward: 30.0\tEpisode Mean: 113.8\n",
+      "87605:127677066\tQ-min: 1.419\tQ-max: 1.752\tLives: 3\tReward: 34.0\tEpisode Mean: 113.8\n",
+      "87605:127677128\tQ-min: 1.803\tQ-max: 1.830\tLives: 3\tReward: 35.0\tEpisode Mean: 113.8\n",
+      "87605:127677198\tQ-min: 1.737\tQ-max: 2.505\tLives: 3\tReward: 39.0\tEpisode Mean: 113.8\n",
+      "87605:127677220\tQ-min: 2.372\tQ-max: 2.562\tLives: 3\tReward: 43.0\tEpisode Mean: 113.8\n",
+      "87605:127677239\tQ-min: 2.331\tQ-max: 2.440\tLives: 3\tReward: 44.0\tEpisode Mean: 113.8\n",
+      "87605:127677251\tQ-min: 0.008\tQ-max: 0.249\tLives: 2\tReward: 44.0\tEpisode Mean: 113.8\n",
+      "87605:127677307\tQ-min: 1.818\tQ-max: 1.864\tLives: 2\tReward: 45.0\tEpisode Mean: 113.8\n",
+      "87605:127677359\tQ-min: 2.208\tQ-max: 2.258\tLives: 2\tReward: 46.0\tEpisode Mean: 113.8\n",
+      "87605:127677390\tQ-min: 0.039\tQ-max: 0.266\tLives: 1\tReward: 46.0\tEpisode Mean: 113.8\n",
+      "87605:127677436\tQ-min: 2.228\tQ-max: 2.285\tLives: 1\tReward: 47.0\tEpisode Mean: 113.8\n",
+      "87605:127677481\tQ-min: 2.194\tQ-max: 2.596\tLives: 1\tReward: 51.0\tEpisode Mean: 113.8\n",
+      "87605:127677503\tQ-min: 2.291\tQ-max: 2.988\tLives: 1\tReward: 58.0\tEpisode Mean: 113.8\n",
+      "87605:127677519\tQ-min: -0.284\tQ-max: 0.126\tLives: 0\tReward: 58.0\tEpisode Mean: 110.7\n",
+      "87606:127677562\tQ-min: 1.736\tQ-max: 1.756\tLives: 5\tReward: 1.0\tEpisode Mean: 110.7\n",
+      "87606:127677617\tQ-min: 1.675\tQ-max: 1.694\tLives: 5\tReward: 2.0\tEpisode Mean: 110.7\n",
+      "87606:127677672\tQ-min: 1.797\tQ-max: 1.816\tLives: 5\tReward: 3.0\tEpisode Mean: 110.7\n",
+      "87606:127677711\tQ-min: 1.939\tQ-max: 1.988\tLives: 5\tReward: 4.0\tEpisode Mean: 110.7\n",
+      "87606:127677746\tQ-min: 1.982\tQ-max: 1.997\tLives: 5\tReward: 5.0\tEpisode Mean: 110.7\n",
+      "87606:127677778\tQ-min: 1.881\tQ-max: 1.989\tLives: 5\tReward: 6.0\tEpisode Mean: 110.7\n",
+      "87606:127677810\tQ-min: 1.759\tQ-max: 1.842\tLives: 5\tReward: 7.0\tEpisode Mean: 110.7\n",
+      "87606:127677857\tQ-min: 1.647\tQ-max: 1.674\tLives: 5\tReward: 8.0\tEpisode Mean: 110.7\n",
+      "87606:127677916\tQ-min: 1.698\tQ-max: 1.744\tLives: 5\tReward: 9.0\tEpisode Mean: 110.7\n",
+      "87606:127677987\tQ-min: 1.660\tQ-max: 1.681\tLives: 5\tReward: 10.0\tEpisode Mean: 110.7\n",
+      "87606:127678054\tQ-min: 1.626\tQ-max: 1.679\tLives: 5\tReward: 11.0\tEpisode Mean: 110.7\n",
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+      "87606:127678163\tQ-min: 1.971\tQ-max: 1.991\tLives: 5\tReward: 14.0\tEpisode Mean: 110.7\n",
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+      "87606:127678258\tQ-min: 1.935\tQ-max: 1.957\tLives: 5\tReward: 17.0\tEpisode Mean: 110.7\n",
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+      "87606:127678359\tQ-min: 1.986\tQ-max: 2.003\tLives: 5\tReward: 20.0\tEpisode Mean: 110.7\n",
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+      "87606:127678426\tQ-min: 2.020\tQ-max: 2.039\tLives: 5\tReward: 22.0\tEpisode Mean: 110.7\n",
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+      "87606:127678481\tQ-min: -0.098\tQ-max: 0.338\tLives: 4\tReward: 23.0\tEpisode Mean: 110.7\n",
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+      "87606:127678568\tQ-min: 2.071\tQ-max: 2.099\tLives: 4\tReward: 25.0\tEpisode Mean: 110.7\n",
+      "87606:127678625\tQ-min: 1.695\tQ-max: 1.800\tLives: 4\tReward: 29.0\tEpisode Mean: 110.7\n",
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+      "87606:127679032\tQ-min: 1.541\tQ-max: 2.350\tLives: 4\tReward: 49.0\tEpisode Mean: 110.7\n",
+      "87606:127679045\tQ-min: -0.339\tQ-max: 0.173\tLives: 3\tReward: 49.0\tEpisode Mean: 110.7\n",
+      "87606:127679088\tQ-min: 1.919\tQ-max: 2.063\tLives: 3\tReward: 53.0\tEpisode Mean: 110.7\n",
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+      "87606:127679245\tQ-min: 2.150\tQ-max: 2.552\tLives: 3\tReward: 62.0\tEpisode Mean: 110.7\n",
+      "87606:127679268\tQ-min: 2.253\tQ-max: 2.441\tLives: 3\tReward: 69.0\tEpisode Mean: 110.7\n",
+      "87606:127679289\tQ-min: 2.212\tQ-max: 2.487\tLives: 3\tReward: 70.0\tEpisode Mean: 110.7\n",
+      "87606:127679309\tQ-min: 2.323\tQ-max: 2.647\tLives: 3\tReward: 74.0\tEpisode Mean: 110.7\n",
+      "87606:127679332\tQ-min: 2.343\tQ-max: 2.527\tLives: 3\tReward: 78.0\tEpisode Mean: 110.7\n",
+      "87606:127679352\tQ-min: 2.450\tQ-max: 2.544\tLives: 3\tReward: 82.0\tEpisode Mean: 110.7\n",
+      "87606:127679374\tQ-min: 2.394\tQ-max: 2.458\tLives: 3\tReward: 83.0\tEpisode Mean: 110.7\n",
+      "87606:127679394\tQ-min: 2.342\tQ-max: 2.522\tLives: 3\tReward: 87.0\tEpisode Mean: 110.7\n",
+      "87606:127679408\tQ-min: -0.282\tQ-max: -0.029\tLives: 2\tReward: 87.0\tEpisode Mean: 110.7\n",
+      "87606:127679469\tQ-min: 1.934\tQ-max: 2.336\tLives: 2\tReward: 91.0\tEpisode Mean: 110.7\n",
+      "87606:127679490\tQ-min: 2.275\tQ-max: 2.529\tLives: 2\tReward: 95.0\tEpisode Mean: 110.7\n",
+      "87606:127679511\tQ-min: 1.537\tQ-max: 2.859\tLives: 2\tReward: 99.0\tEpisode Mean: 110.7\n",
+      "87606:127679533\tQ-min: 2.336\tQ-max: 2.599\tLives: 2\tReward: 103.0\tEpisode Mean: 110.7\n",
+      "87606:127679555\tQ-min: 2.316\tQ-max: 2.783\tLives: 2\tReward: 104.0\tEpisode Mean: 110.7\n",
+      "87606:127679576\tQ-min: 1.995\tQ-max: 2.765\tLives: 2\tReward: 108.0\tEpisode Mean: 110.7\n",
+      "87606:127679597\tQ-min: 2.346\tQ-max: 2.770\tLives: 2\tReward: 115.0\tEpisode Mean: 110.7\n",
+      "87606:127679618\tQ-min: 2.309\tQ-max: 2.690\tLives: 2\tReward: 116.0\tEpisode Mean: 110.7\n",
+      "87606:127679630\tQ-min: -0.457\tQ-max: 0.076\tLives: 1\tReward: 116.0\tEpisode Mean: 110.7\n",
+      "87606:127679677\tQ-min: 2.395\tQ-max: 2.593\tLives: 1\tReward: 120.0\tEpisode Mean: 110.7\n",
+      "87606:127679735\tQ-min: 1.948\tQ-max: 2.202\tLives: 1\tReward: 124.0\tEpisode Mean: 110.7\n",
+      "87606:127679806\tQ-min: 2.060\tQ-max: 2.495\tLives: 1\tReward: 128.0\tEpisode Mean: 110.7\n",
+      "87606:127679823\tQ-min: -0.506\tQ-max: 0.177\tLives: 0\tReward: 128.0\tEpisode Mean: 111.6\n",
+      "87607:127679877\tQ-min: 1.689\tQ-max: 1.702\tLives: 5\tReward: 1.0\tEpisode Mean: 111.6\n",
+      "87607:127679929\tQ-min: 1.845\tQ-max: 1.866\tLives: 5\tReward: 2.0\tEpisode Mean: 111.6\n",
+      "87607:127679981\tQ-min: 1.693\tQ-max: 1.738\tLives: 5\tReward: 3.0\tEpisode Mean: 111.6\n",
+      "87607:127680027\tQ-min: 1.962\tQ-max: 2.002\tLives: 5\tReward: 4.0\tEpisode Mean: 111.6\n",
+      "87607:127680064\tQ-min: 1.922\tQ-max: 2.053\tLives: 5\tReward: 5.0\tEpisode Mean: 111.6\n",
+      "87607:127680096\tQ-min: 2.018\tQ-max: 2.050\tLives: 5\tReward: 6.0\tEpisode Mean: 111.6\n",
+      "87607:127680128\tQ-min: 1.803\tQ-max: 1.831\tLives: 5\tReward: 7.0\tEpisode Mean: 111.6\n",
+      "87607:127680177\tQ-min: 1.645\tQ-max: 1.662\tLives: 5\tReward: 8.0\tEpisode Mean: 111.6\n",
+      "87607:127680242\tQ-min: 1.739\tQ-max: 1.793\tLives: 5\tReward: 9.0\tEpisode Mean: 111.6\n",
+      "87607:127680308\tQ-min: 1.656\tQ-max: 1.699\tLives: 5\tReward: 10.0\tEpisode Mean: 111.6\n",
+      "87607:127680378\tQ-min: 1.677\tQ-max: 1.700\tLives: 5\tReward: 11.0\tEpisode Mean: 111.6\n",
+      "87607:127680425\tQ-min: 2.023\tQ-max: 2.058\tLives: 5\tReward: 12.0\tEpisode Mean: 111.6\n",
+      "87607:127680459\tQ-min: 1.954\tQ-max: 1.999\tLives: 5\tReward: 13.0\tEpisode Mean: 111.6\n",
+      "87607:127680493\tQ-min: 1.998\tQ-max: 2.057\tLives: 5\tReward: 14.0\tEpisode Mean: 111.6\n",
+      "87607:127680527\tQ-min: 2.008\tQ-max: 2.044\tLives: 5\tReward: 15.0\tEpisode Mean: 111.6\n",
+      "87607:127680559\tQ-min: 2.022\tQ-max: 2.067\tLives: 5\tReward: 16.0\tEpisode Mean: 111.6\n",
+      "87607:127680594\tQ-min: 1.967\tQ-max: 2.004\tLives: 5\tReward: 20.0\tEpisode Mean: 111.6\n",
+      "87607:127680624\tQ-min: 2.048\tQ-max: 2.151\tLives: 5\tReward: 21.0\tEpisode Mean: 111.6\n",
+      "87607:127680657\tQ-min: 2.051\tQ-max: 2.088\tLives: 5\tReward: 22.0\tEpisode Mean: 111.6\n",
+      "87607:127680678\tQ-min: -0.184\tQ-max: 0.397\tLives: 4\tReward: 22.0\tEpisode Mean: 111.6\n",
+      "87607:127680723\tQ-min: 1.909\tQ-max: 2.042\tLives: 4\tReward: 26.0\tEpisode Mean: 111.6\n",
+      "87607:127680768\tQ-min: 1.944\tQ-max: 1.974\tLives: 4\tReward: 27.0\tEpisode Mean: 111.6\n",
+      "87607:127680809\tQ-min: 2.074\tQ-max: 2.107\tLives: 4\tReward: 28.0\tEpisode Mean: 111.6\n",
+      "87607:127680848\tQ-min: 2.161\tQ-max: 2.240\tLives: 4\tReward: 32.0\tEpisode Mean: 111.6\n",
+      "87607:127680882\tQ-min: 2.087\tQ-max: 2.127\tLives: 4\tReward: 33.0\tEpisode Mean: 111.6\n",
+      "87607:127680915\tQ-min: 2.135\tQ-max: 2.224\tLives: 4\tReward: 37.0\tEpisode Mean: 111.6\n",
+      "87607:127680951\tQ-min: 1.990\tQ-max: 2.214\tLives: 4\tReward: 41.0\tEpisode Mean: 111.6\n",
+      "87607:127681007\tQ-min: 1.553\tQ-max: 1.975\tLives: 4\tReward: 45.0\tEpisode Mean: 111.6\n",
+      "87607:127681081\tQ-min: 1.772\tQ-max: 1.872\tLives: 4\tReward: 46.0\tEpisode Mean: 111.6\n",
+      "87607:127681147\tQ-min: 1.825\tQ-max: 1.870\tLives: 4\tReward: 47.0\tEpisode Mean: 111.6\n",
+      "87607:127681213\tQ-min: 1.874\tQ-max: 2.023\tLives: 4\tReward: 48.0\tEpisode Mean: 111.6\n",
+      "87607:127681262\tQ-min: 2.039\tQ-max: 2.453\tLives: 4\tReward: 52.0\tEpisode Mean: 111.6\n",
+      "87607:127681300\tQ-min: 1.558\tQ-max: 2.585\tLives: 4\tReward: 56.0\tEpisode Mean: 111.6\n",
+      "87607:127681324\tQ-min: 2.214\tQ-max: 2.458\tLives: 4\tReward: 63.0\tEpisode Mean: 111.6\n",
+      "87607:127681345\tQ-min: 2.441\tQ-max: 2.550\tLives: 4\tReward: 64.0\tEpisode Mean: 111.6\n",
+      "87607:127681365\tQ-min: 2.225\tQ-max: 2.242\tLives: 4\tReward: 65.0\tEpisode Mean: 111.6\n",
+      "87607:127681381\tQ-min: -0.027\tQ-max: 0.256\tLives: 3\tReward: 65.0\tEpisode Mean: 111.6\n",
+      "87607:127681429\tQ-min: 2.047\tQ-max: 2.081\tLives: 3\tReward: 66.0\tEpisode Mean: 111.6\n",
+      "87607:127681477\tQ-min: 2.280\tQ-max: 2.430\tLives: 3\tReward: 70.0\tEpisode Mean: 111.6\n",
+      "87607:127681498\tQ-min: 2.250\tQ-max: 2.408\tLives: 3\tReward: 71.0\tEpisode Mean: 111.6\n",
+      "87607:127681516\tQ-min: 2.347\tQ-max: 2.513\tLives: 3\tReward: 75.0\tEpisode Mean: 111.6\n",
+      "87607:127681529\tQ-min: -0.143\tQ-max: 0.359\tLives: 2\tReward: 75.0\tEpisode Mean: 111.6\n",
+      "87607:127681575\tQ-min: 2.035\tQ-max: 2.133\tLives: 2\tReward: 79.0\tEpisode Mean: 111.6\n",
+      "87607:127681625\tQ-min: 1.562\tQ-max: 2.504\tLives: 2\tReward: 86.0\tEpisode Mean: 111.6\n",
+      "87607:127681650\tQ-min: 2.111\tQ-max: 2.595\tLives: 2\tReward: 93.0\tEpisode Mean: 111.6\n",
+      "87607:127681673\tQ-min: 2.018\tQ-max: 2.358\tLives: 2\tReward: 97.0\tEpisode Mean: 111.6\n",
+      "87607:127681694\tQ-min: 2.262\tQ-max: 2.581\tLives: 2\tReward: 101.0\tEpisode Mean: 111.6\n",
+      "87607:127681716\tQ-min: 2.455\tQ-max: 2.569\tLives: 2\tReward: 102.0\tEpisode Mean: 111.6\n",
+      "87607:127681737\tQ-min: 2.342\tQ-max: 2.699\tLives: 2\tReward: 106.0\tEpisode Mean: 111.6\n",
+      "87607:127681760\tQ-min: 2.547\tQ-max: 2.743\tLives: 2\tReward: 107.0\tEpisode Mean: 111.6\n",
+      "87607:127681779\tQ-min: 2.343\tQ-max: 2.583\tLives: 2\tReward: 111.0\tEpisode Mean: 111.6\n",
+      "87607:127681794\tQ-min: 0.046\tQ-max: 0.261\tLives: 1\tReward: 111.0\tEpisode Mean: 111.6\n",
+      "87607:127681846\tQ-min: 2.121\tQ-max: 2.734\tLives: 1\tReward: 115.0\tEpisode Mean: 111.6\n",
+      "87607:127681867\tQ-min: 2.635\tQ-max: 2.878\tLives: 1\tReward: 122.0\tEpisode Mean: 111.6\n",
+      "87607:127681891\tQ-min: 2.746\tQ-max: 3.404\tLives: 1\tReward: 123.0\tEpisode Mean: 111.6\n",
+      "87607:127681903\tQ-min: -0.278\tQ-max: 0.238\tLives: 0\tReward: 123.0\tEpisode Mean: 112.2\n",
+      "87608:127681952\tQ-min: 1.705\tQ-max: 1.727\tLives: 5\tReward: 1.0\tEpisode Mean: 112.2\n",
+      "87608:127682017\tQ-min: 1.662\tQ-max: 1.675\tLives: 5\tReward: 2.0\tEpisode Mean: 112.2\n",
+      "87608:127682069\tQ-min: 1.885\tQ-max: 1.895\tLives: 5\tReward: 3.0\tEpisode Mean: 112.2\n",
+      "87608:127682107\tQ-min: 1.982\tQ-max: 2.009\tLives: 5\tReward: 4.0\tEpisode Mean: 112.2\n",
+      "87608:127682139\tQ-min: 1.951\tQ-max: 1.975\tLives: 5\tReward: 5.0\tEpisode Mean: 112.2\n",
+      "87608:127682172\tQ-min: 2.009\tQ-max: 2.028\tLives: 5\tReward: 9.0\tEpisode Mean: 112.2\n",
+      "87608:127682206\tQ-min: 1.868\tQ-max: 1.909\tLives: 5\tReward: 10.0\tEpisode Mean: 112.2\n",
+      "87608:127682254\tQ-min: 1.723\tQ-max: 1.741\tLives: 5\tReward: 11.0\tEpisode Mean: 112.2\n",
+      "87608:127682317\tQ-min: 1.762\tQ-max: 1.793\tLives: 5\tReward: 12.0\tEpisode Mean: 112.2\n",
+      "87608:127682376\tQ-min: 1.661\tQ-max: 1.687\tLives: 5\tReward: 13.0\tEpisode Mean: 112.2\n",
+      "87608:127682437\tQ-min: 1.724\tQ-max: 1.744\tLives: 5\tReward: 14.0\tEpisode Mean: 112.2\n",
+      "87608:127682485\tQ-min: 2.060\tQ-max: 2.081\tLives: 5\tReward: 15.0\tEpisode Mean: 112.2\n",
+      "87608:127682518\tQ-min: 1.960\tQ-max: 1.978\tLives: 5\tReward: 16.0\tEpisode Mean: 112.2\n",
+      "87608:127682548\tQ-min: 1.963\tQ-max: 1.994\tLives: 5\tReward: 17.0\tEpisode Mean: 112.2\n",
+      "87608:127682580\tQ-min: 1.937\tQ-max: 1.969\tLives: 5\tReward: 18.0\tEpisode Mean: 112.2\n",
+      "87608:127682612\tQ-min: 2.015\tQ-max: 2.045\tLives: 5\tReward: 19.0\tEpisode Mean: 112.2\n",
+      "87608:127682647\tQ-min: 1.952\tQ-max: 2.102\tLives: 5\tReward: 20.0\tEpisode Mean: 112.2\n",
+      "87608:127682680\tQ-min: 2.053\tQ-max: 2.100\tLives: 5\tReward: 21.0\tEpisode Mean: 112.2\n",
+      "87608:127682714\tQ-min: 2.073\tQ-max: 2.150\tLives: 5\tReward: 25.0\tEpisode Mean: 112.2\n",
+      "87608:127682751\tQ-min: 2.129\tQ-max: 2.155\tLives: 5\tReward: 26.0\tEpisode Mean: 112.2\n",
+      "87608:127682788\tQ-min: 2.132\tQ-max: 2.283\tLives: 5\tReward: 30.0\tEpisode Mean: 112.2\n",
+      "87608:127682821\tQ-min: 2.081\tQ-max: 2.142\tLives: 5\tReward: 34.0\tEpisode Mean: 112.2\n",
+      "87608:127682852\tQ-min: 2.203\tQ-max: 2.245\tLives: 5\tReward: 35.0\tEpisode Mean: 112.2\n",
+      "87608:127682883\tQ-min: 2.171\tQ-max: 2.215\tLives: 5\tReward: 36.0\tEpisode Mean: 112.2\n",
+      "87608:127682914\tQ-min: 2.053\tQ-max: 2.085\tLives: 5\tReward: 37.0\tEpisode Mean: 112.2\n",
+      "87608:127682935\tQ-min: 0.017\tQ-max: 0.323\tLives: 4\tReward: 37.0\tEpisode Mean: 112.2\n",
+      "87608:127682989\tQ-min: 1.815\tQ-max: 1.885\tLives: 4\tReward: 38.0\tEpisode Mean: 112.2\n",
+      "87608:127683045\tQ-min: 2.031\tQ-max: 2.077\tLives: 4\tReward: 39.0\tEpisode Mean: 112.2\n",
+      "87608:127683099\tQ-min: 1.778\tQ-max: 1.807\tLives: 4\tReward: 40.0\tEpisode Mean: 112.2\n",
+      "87608:127683140\tQ-min: -0.037\tQ-max: 0.215\tLives: 3\tReward: 40.0\tEpisode Mean: 112.2\n",
+      "87608:127683186\tQ-min: 1.998\tQ-max: 2.027\tLives: 3\tReward: 41.0\tEpisode Mean: 112.2\n",
+      "87608:127683230\tQ-min: 2.024\tQ-max: 2.086\tLives: 3\tReward: 42.0\tEpisode Mean: 112.2\n",
+      "87608:127683277\tQ-min: 2.062\tQ-max: 2.135\tLives: 3\tReward: 46.0\tEpisode Mean: 112.2\n",
+      "87608:127683321\tQ-min: 2.004\tQ-max: 2.147\tLives: 3\tReward: 50.0\tEpisode Mean: 112.2\n",
+      "87608:127683354\tQ-min: 2.193\tQ-max: 2.238\tLives: 3\tReward: 51.0\tEpisode Mean: 112.2\n",
+      "87608:127683389\tQ-min: 2.188\tQ-max: 2.450\tLives: 3\tReward: 55.0\tEpisode Mean: 112.2\n",
+      "87608:127683409\tQ-min: 2.289\tQ-max: 2.449\tLives: 3\tReward: 56.0\tEpisode Mean: 112.2\n",
+      "87608:127683429\tQ-min: 2.306\tQ-max: 2.389\tLives: 3\tReward: 60.0\tEpisode Mean: 112.2\n",
+      "87608:127683450\tQ-min: 2.301\tQ-max: 2.498\tLives: 3\tReward: 61.0\tEpisode Mean: 112.2\n",
+      "87608:127683464\tQ-min: -0.149\tQ-max: 0.277\tLives: 2\tReward: 61.0\tEpisode Mean: 112.2\n",
+      "87608:127683524\tQ-min: 2.171\tQ-max: 2.437\tLives: 2\tReward: 65.0\tEpisode Mean: 112.2\n",
+      "87608:127683546\tQ-min: 2.401\tQ-max: 2.473\tLives: 2\tReward: 69.0\tEpisode Mean: 112.2\n",
+      "87608:127683567\tQ-min: 2.388\tQ-max: 2.501\tLives: 2\tReward: 73.0\tEpisode Mean: 112.2\n",
+      "87608:127683589\tQ-min: 2.242\tQ-max: 2.397\tLives: 2\tReward: 77.0\tEpisode Mean: 112.2\n",
+      "87608:127683608\tQ-min: 2.429\tQ-max: 2.583\tLives: 2\tReward: 78.0\tEpisode Mean: 112.2\n",
+      "87608:127683627\tQ-min: 2.494\tQ-max: 2.581\tLives: 2\tReward: 82.0\tEpisode Mean: 112.2\n",
+      "87608:127683646\tQ-min: 2.393\tQ-max: 2.474\tLives: 2\tReward: 83.0\tEpisode Mean: 112.2\n",
+      "87608:127683666\tQ-min: 2.321\tQ-max: 2.410\tLives: 2\tReward: 84.0\tEpisode Mean: 112.2\n",
+      "87608:127683686\tQ-min: 2.301\tQ-max: 2.409\tLives: 2\tReward: 85.0\tEpisode Mean: 112.2\n",
+      "87608:127683705\tQ-min: 2.244\tQ-max: 2.517\tLives: 2\tReward: 89.0\tEpisode Mean: 112.2\n",
+      "87608:127683726\tQ-min: 2.359\tQ-max: 2.571\tLives: 2\tReward: 93.0\tEpisode Mean: 112.2\n",
+      "87608:127683746\tQ-min: 2.380\tQ-max: 2.589\tLives: 2\tReward: 97.0\tEpisode Mean: 112.2\n",
+      "87608:127683767\tQ-min: 2.436\tQ-max: 2.557\tLives: 2\tReward: 101.0\tEpisode Mean: 112.2\n",
+      "87608:127683782\tQ-min: 0.033\tQ-max: 0.460\tLives: 1\tReward: 101.0\tEpisode Mean: 112.2\n",
+      "87608:127683825\tQ-min: 2.161\tQ-max: 2.451\tLives: 1\tReward: 105.0\tEpisode Mean: 112.2\n",
+      "87608:127683850\tQ-min: 2.134\tQ-max: 2.880\tLives: 1\tReward: 112.0\tEpisode Mean: 112.2\n",
+      "87608:127683872\tQ-min: 2.234\tQ-max: 2.596\tLives: 1\tReward: 116.0\tEpisode Mean: 112.2\n",
+      "87608:127683894\tQ-min: 2.373\tQ-max: 2.713\tLives: 1\tReward: 120.0\tEpisode Mean: 112.2\n",
+      "87608:127683916\tQ-min: 2.372\tQ-max: 2.832\tLives: 1\tReward: 127.0\tEpisode Mean: 112.2\n",
+      "87608:127683940\tQ-min: 2.511\tQ-max: 3.344\tLives: 1\tReward: 134.0\tEpisode Mean: 112.2\n",
+      "87608:127683962\tQ-min: 2.660\tQ-max: 3.282\tLives: 1\tReward: 138.0\tEpisode Mean: 112.2\n",
+      "87608:127683987\tQ-min: 1.914\tQ-max: 4.166\tLives: 1\tReward: 145.0\tEpisode Mean: 112.2\n",
+      "87608:127684012\tQ-min: 2.029\tQ-max: 3.421\tLives: 1\tReward: 152.0\tEpisode Mean: 112.2\n",
+      "87608:127684040\tQ-min: 2.152\tQ-max: 3.147\tLives: 1\tReward: 159.0\tEpisode Mean: 112.2\n",
+      "87608:127684066\tQ-min: 2.143\tQ-max: 3.272\tLives: 1\tReward: 166.0\tEpisode Mean: 112.2\n",
+      "87608:127684091\tQ-min: 2.826\tQ-max: 5.456\tLives: 1\tReward: 173.0\tEpisode Mean: 112.2\n",
+      "87608:127684116\tQ-min: 2.854\tQ-max: 3.919\tLives: 1\tReward: 180.0\tEpisode Mean: 112.2\n",
+      "87608:127684144\tQ-min: 2.312\tQ-max: 6.596\tLives: 1\tReward: 187.0\tEpisode Mean: 112.2\n",
+      "87608:127684148\tQ-min: 1.792\tQ-max: 6.289\tLives: 1\tReward: 194.0\tEpisode Mean: 112.2\n",
+      "87608:127684153\tQ-min: 3.303\tQ-max: 7.197\tLives: 1\tReward: 201.0\tEpisode Mean: 112.2\n",
+      "87608:127684189\tQ-min: 2.544\tQ-max: 6.305\tLives: 1\tReward: 208.0\tEpisode Mean: 112.2\n",
+      "87608:127684195\tQ-min: 3.050\tQ-max: 3.946\tLives: 1\tReward: 215.0\tEpisode Mean: 112.2\n",
+      "87608:127684200\tQ-min: 3.800\tQ-max: 5.113\tLives: 1\tReward: 222.0\tEpisode Mean: 112.2\n",
+      "87608:127684206\tQ-min: 2.798\tQ-max: 5.010\tLives: 1\tReward: 229.0\tEpisode Mean: 112.2\n",
+      "87608:127684212\tQ-min: 1.488\tQ-max: 4.776\tLives: 1\tReward: 236.0\tEpisode Mean: 112.2\n",
+      "87608:127684217\tQ-min: 2.993\tQ-max: 4.443\tLives: 1\tReward: 243.0\tEpisode Mean: 112.2\n",
+      "87608:127684221\tQ-min: 2.288\tQ-max: 4.760\tLives: 1\tReward: 250.0\tEpisode Mean: 112.2\n",
+      "87608:127684226\tQ-min: 3.077\tQ-max: 4.747\tLives: 1\tReward: 257.0\tEpisode Mean: 112.2\n",
+      "87608:127684245\tQ-min: -0.034\tQ-max: 0.486\tLives: 0\tReward: 257.0\tEpisode Mean: 119.0\n",
+      "87609:127684288\tQ-min: 1.793\tQ-max: 1.815\tLives: 5\tReward: 1.0\tEpisode Mean: 119.0\n",
+      "87609:127684331\tQ-min: 1.806\tQ-max: 1.825\tLives: 5\tReward: 2.0\tEpisode Mean: 119.0\n",
+      "87609:127684374\tQ-min: 1.904\tQ-max: 1.916\tLives: 5\tReward: 3.0\tEpisode Mean: 119.0\n",
+      "87609:127684411\tQ-min: 1.956\tQ-max: 1.980\tLives: 5\tReward: 4.0\tEpisode Mean: 119.0\n",
+      "87609:127684443\tQ-min: 1.983\tQ-max: 2.007\tLives: 5\tReward: 5.0\tEpisode Mean: 119.0\n",
+      "87609:127684478\tQ-min: 1.911\tQ-max: 1.938\tLives: 5\tReward: 6.0\tEpisode Mean: 119.0\n",
+      "87609:127684512\tQ-min: 1.798\tQ-max: 1.811\tLives: 5\tReward: 7.0\tEpisode Mean: 119.0\n",
+      "87609:127684556\tQ-min: 1.644\tQ-max: 1.655\tLives: 5\tReward: 8.0\tEpisode Mean: 119.0\n",
+      "87609:127684619\tQ-min: 1.700\tQ-max: 1.718\tLives: 5\tReward: 9.0\tEpisode Mean: 119.0\n",
+      "87609:127684685\tQ-min: 1.713\tQ-max: 1.743\tLives: 5\tReward: 10.0\tEpisode Mean: 119.0\n",
+      "87609:127684751\tQ-min: 1.632\tQ-max: 1.655\tLives: 5\tReward: 11.0\tEpisode Mean: 119.0\n",
+      "87609:127684798\tQ-min: 1.963\tQ-max: 1.979\tLives: 5\tReward: 12.0\tEpisode Mean: 119.0\n",
+      "87609:127684830\tQ-min: 1.980\tQ-max: 1.994\tLives: 5\tReward: 13.0\tEpisode Mean: 119.0\n",
+      "87609:127684864\tQ-min: 1.991\tQ-max: 2.009\tLives: 5\tReward: 14.0\tEpisode Mean: 119.0\n",
+      "87609:127684898\tQ-min: 2.052\tQ-max: 2.070\tLives: 5\tReward: 15.0\tEpisode Mean: 119.0\n",
+      "87609:127684928\tQ-min: 2.022\tQ-max: 2.052\tLives: 5\tReward: 16.0\tEpisode Mean: 119.0\n",
+      "87609:127684961\tQ-min: 1.990\tQ-max: 2.025\tLives: 5\tReward: 17.0\tEpisode Mean: 119.0\n",
+      "87609:127684995\tQ-min: 2.058\tQ-max: 2.099\tLives: 5\tReward: 21.0\tEpisode Mean: 119.0\n",
+      "87609:127685030\tQ-min: 1.981\tQ-max: 2.051\tLives: 5\tReward: 22.0\tEpisode Mean: 119.0\n",
+      "87609:127685064\tQ-min: 2.072\tQ-max: 2.088\tLives: 5\tReward: 23.0\tEpisode Mean: 119.0\n",
+      "87609:127685096\tQ-min: 2.144\tQ-max: 2.192\tLives: 5\tReward: 24.0\tEpisode Mean: 119.0\n",
+      "87609:127685131\tQ-min: 2.037\tQ-max: 2.160\tLives: 5\tReward: 28.0\tEpisode Mean: 119.0\n",
+      "87609:127685155\tQ-min: -0.157\tQ-max: 0.391\tLives: 4\tReward: 28.0\tEpisode Mean: 119.0\n",
+      "87609:127685200\tQ-min: 1.942\tQ-max: 1.993\tLives: 4\tReward: 29.0\tEpisode Mean: 119.0\n",
+      "87609:127685256\tQ-min: 1.632\tQ-max: 1.856\tLives: 4\tReward: 33.0\tEpisode Mean: 119.0\n",
+      "87609:127685312\tQ-min: 2.047\tQ-max: 2.110\tLives: 4\tReward: 34.0\tEpisode Mean: 119.0\n",
+      "87609:127685347\tQ-min: 2.252\tQ-max: 2.447\tLives: 4\tReward: 38.0\tEpisode Mean: 119.0\n",
+      "87609:127685369\tQ-min: 2.322\tQ-max: 2.428\tLives: 4\tReward: 39.0\tEpisode Mean: 119.0\n",
+      "87609:127685389\tQ-min: 2.230\tQ-max: 2.453\tLives: 4\tReward: 40.0\tEpisode Mean: 119.0\n",
+      "87609:127685409\tQ-min: 2.276\tQ-max: 2.474\tLives: 4\tReward: 44.0\tEpisode Mean: 119.0\n",
+      "87609:127685428\tQ-min: 2.284\tQ-max: 2.461\tLives: 4\tReward: 45.0\tEpisode Mean: 119.0\n",
+      "87609:127685445\tQ-min: 1.991\tQ-max: 2.370\tLives: 4\tReward: 46.0\tEpisode Mean: 119.0\n",
+      "87609:127685465\tQ-min: 2.400\tQ-max: 2.440\tLives: 4\tReward: 47.0\tEpisode Mean: 119.0\n",
+      "87609:127685485\tQ-min: 2.303\tQ-max: 2.431\tLives: 4\tReward: 48.0\tEpisode Mean: 119.0\n",
+      "87609:127685506\tQ-min: 2.367\tQ-max: 2.503\tLives: 4\tReward: 52.0\tEpisode Mean: 119.0\n",
+      "87609:127685519\tQ-min: -0.025\tQ-max: 0.163\tLives: 3\tReward: 52.0\tEpisode Mean: 119.0\n",
+      "87609:127685566\tQ-min: 2.125\tQ-max: 2.173\tLives: 3\tReward: 56.0\tEpisode Mean: 119.0\n",
+      "87609:127685623\tQ-min: 1.802\tQ-max: 1.973\tLives: 3\tReward: 57.0\tEpisode Mean: 119.0\n",
+      "87609:127685693\tQ-min: 1.866\tQ-max: 1.932\tLives: 3\tReward: 58.0\tEpisode Mean: 119.0\n",
+      "87609:127685747\tQ-min: 1.513\tQ-max: 1.983\tLives: 3\tReward: 62.0\tEpisode Mean: 119.0\n",
+      "87609:127685759\tQ-min: -0.099\tQ-max: 0.154\tLives: 2\tReward: 62.0\tEpisode Mean: 119.0\n",
+      "87609:127685819\tQ-min: 1.546\tQ-max: 2.547\tLives: 2\tReward: 66.0\tEpisode Mean: 119.0\n",
+      "87609:127685837\tQ-min: 2.272\tQ-max: 2.381\tLives: 2\tReward: 67.0\tEpisode Mean: 119.0\n",
+      "87609:127685858\tQ-min: 2.128\tQ-max: 2.495\tLives: 2\tReward: 71.0\tEpisode Mean: 119.0\n",
+      "87609:127685872\tQ-min: -0.050\tQ-max: 0.239\tLives: 1\tReward: 71.0\tEpisode Mean: 119.0\n",
+      "87609:127685918\tQ-min: 2.039\tQ-max: 2.260\tLives: 1\tReward: 75.0\tEpisode Mean: 119.0\n",
+      "87609:127685964\tQ-min: 2.164\tQ-max: 2.339\tLives: 1\tReward: 79.0\tEpisode Mean: 119.0\n",
+      "87609:127686011\tQ-min: 2.306\tQ-max: 2.872\tLives: 1\tReward: 83.0\tEpisode Mean: 119.0\n",
+      "87609:127686035\tQ-min: 2.208\tQ-max: 2.769\tLives: 1\tReward: 90.0\tEpisode Mean: 119.0\n",
+      "87609:127686048\tQ-min: -0.010\tQ-max: 0.147\tLives: 0\tReward: 90.0\tEpisode Mean: 117.7\n",
+      "87610:127686091\tQ-min: 1.730\tQ-max: 1.747\tLives: 5\tReward: 1.0\tEpisode Mean: 117.7\n",
+      "87610:127686143\tQ-min: 1.629\tQ-max: 1.657\tLives: 5\tReward: 2.0\tEpisode Mean: 117.7\n",
+      "87610:127686208\tQ-min: 1.713\tQ-max: 1.742\tLives: 5\tReward: 3.0\tEpisode Mean: 117.7\n",
+      "87610:127686251\tQ-min: 1.949\tQ-max: 1.982\tLives: 5\tReward: 4.0\tEpisode Mean: 117.7\n",
+      "87610:127686284\tQ-min: 1.976\tQ-max: 1.991\tLives: 5\tReward: 5.0\tEpisode Mean: 117.7\n",
+      "87610:127686313\tQ-min: 1.894\tQ-max: 1.917\tLives: 5\tReward: 6.0\tEpisode Mean: 117.7\n",
+      "87610:127686344\tQ-min: 1.839\tQ-max: 1.871\tLives: 5\tReward: 7.0\tEpisode Mean: 117.7\n",
+      "87610:127686390\tQ-min: 1.618\tQ-max: 1.636\tLives: 5\tReward: 8.0\tEpisode Mean: 117.7\n",
+      "87610:127686432\tQ-min: -0.040\tQ-max: 0.307\tLives: 4\tReward: 8.0\tEpisode Mean: 117.7\n",
+      "87610:127686476\tQ-min: 1.875\tQ-max: 1.899\tLives: 4\tReward: 9.0\tEpisode Mean: 117.7\n",
+      "87610:127686517\tQ-min: 1.867\tQ-max: 1.885\tLives: 4\tReward: 10.0\tEpisode Mean: 117.7\n",
+      "87610:127686557\tQ-min: 1.946\tQ-max: 1.969\tLives: 4\tReward: 11.0\tEpisode Mean: 117.7\n",
+      "87610:127686597\tQ-min: 1.940\tQ-max: 1.959\tLives: 4\tReward: 12.0\tEpisode Mean: 117.7\n",
+      "87610:127686632\tQ-min: 1.907\tQ-max: 1.936\tLives: 4\tReward: 13.0\tEpisode Mean: 117.7\n",
+      "87610:127686667\tQ-min: 1.965\tQ-max: 1.985\tLives: 4\tReward: 17.0\tEpisode Mean: 117.7\n",
+      "87610:127686701\tQ-min: 2.265\tQ-max: 2.471\tLives: 4\tReward: 21.0\tEpisode Mean: 117.7\n",
+      "87610:127686725\tQ-min: 2.356\tQ-max: 2.428\tLives: 4\tReward: 25.0\tEpisode Mean: 117.7\n",
+      "87610:127686750\tQ-min: 2.179\tQ-max: 2.463\tLives: 4\tReward: 29.0\tEpisode Mean: 117.7\n",
+      "87610:127686770\tQ-min: 2.372\tQ-max: 2.468\tLives: 4\tReward: 30.0\tEpisode Mean: 117.7\n",
+      "87610:127686789\tQ-min: 2.280\tQ-max: 2.383\tLives: 4\tReward: 31.0\tEpisode Mean: 117.7\n",
+      "87610:127686808\tQ-min: 2.272\tQ-max: 2.440\tLives: 4\tReward: 32.0\tEpisode Mean: 117.7\n",
+      "87610:127686821\tQ-min: 0.033\tQ-max: 0.192\tLives: 3\tReward: 32.0\tEpisode Mean: 117.7\n",
+      "87610:127686891\tQ-min: 1.759\tQ-max: 1.832\tLives: 3\tReward: 33.0\tEpisode Mean: 117.7\n",
+      "87610:127686955\tQ-min: 1.827\tQ-max: 1.860\tLives: 3\tReward: 34.0\tEpisode Mean: 117.7\n",
+      "87610:127687020\tQ-min: 1.674\tQ-max: 1.740\tLives: 3\tReward: 35.0\tEpisode Mean: 117.7\n",
+      "87610:127687074\tQ-min: 2.207\tQ-max: 2.296\tLives: 3\tReward: 39.0\tEpisode Mean: 117.7\n",
+      "87610:127687089\tQ-min: -0.018\tQ-max: 0.184\tLives: 2\tReward: 39.0\tEpisode Mean: 117.7\n",
+      "87610:127687134\tQ-min: 2.019\tQ-max: 2.062\tLives: 2\tReward: 40.0\tEpisode Mean: 117.7\n",
+      "87610:127687188\tQ-min: 1.810\tQ-max: 1.915\tLives: 2\tReward: 41.0\tEpisode Mean: 117.7\n",
+      "87610:127687241\tQ-min: 2.169\tQ-max: 2.252\tLives: 2\tReward: 45.0\tEpisode Mean: 117.7\n",
+      "87610:127687281\tQ-min: 2.391\tQ-max: 2.477\tLives: 2\tReward: 46.0\tEpisode Mean: 117.7\n",
+      "87610:127687314\tQ-min: 2.391\tQ-max: 2.472\tLives: 2\tReward: 47.0\tEpisode Mean: 117.7\n",
+      "87610:127687349\tQ-min: 2.098\tQ-max: 2.484\tLives: 2\tReward: 54.0\tEpisode Mean: 117.7\n",
+      "87610:127687371\tQ-min: 2.337\tQ-max: 2.577\tLives: 2\tReward: 55.0\tEpisode Mean: 117.7\n",
+      "87610:127687392\tQ-min: 2.367\tQ-max: 2.465\tLives: 2\tReward: 59.0\tEpisode Mean: 117.7\n",
+      "87610:127687411\tQ-min: 2.380\tQ-max: 2.512\tLives: 2\tReward: 60.0\tEpisode Mean: 117.7\n",
+      "87610:127687424\tQ-min: -0.228\tQ-max: 0.172\tLives: 1\tReward: 60.0\tEpisode Mean: 117.7\n",
+      "87610:127687470\tQ-min: 2.006\tQ-max: 2.056\tLives: 1\tReward: 61.0\tEpisode Mean: 117.7\n",
+      "87610:127687514\tQ-min: 1.924\tQ-max: 2.011\tLives: 1\tReward: 62.0\tEpisode Mean: 117.7\n",
+      "87610:127687559\tQ-min: 2.072\tQ-max: 2.121\tLives: 1\tReward: 66.0\tEpisode Mean: 117.7\n",
+      "87610:127687600\tQ-min: 2.294\tQ-max: 2.366\tLives: 1\tReward: 67.0\tEpisode Mean: 117.7\n",
+      "87610:127687621\tQ-min: -0.196\tQ-max: 0.134\tLives: 0\tReward: 67.0\tEpisode Mean: 115.5\n",
+      "87611:127687664\tQ-min: 1.729\tQ-max: 1.744\tLives: 5\tReward: 1.0\tEpisode Mean: 115.5\n",
+      "87611:127687717\tQ-min: 1.652\tQ-max: 1.662\tLives: 5\tReward: 2.0\tEpisode Mean: 115.5\n",
+      "87611:127687778\tQ-min: 1.706\tQ-max: 1.731\tLives: 5\tReward: 3.0\tEpisode Mean: 115.5\n",
+      "87611:127687828\tQ-min: 1.978\tQ-max: 1.993\tLives: 5\tReward: 4.0\tEpisode Mean: 115.5\n",
+      "87611:127687860\tQ-min: 1.933\tQ-max: 1.955\tLives: 5\tReward: 5.0\tEpisode Mean: 115.5\n",
+      "87611:127687891\tQ-min: 1.960\tQ-max: 1.971\tLives: 5\tReward: 6.0\tEpisode Mean: 115.5\n",
+      "87611:127687924\tQ-min: 1.744\tQ-max: 1.775\tLives: 5\tReward: 7.0\tEpisode Mean: 115.5\n",
+      "87611:127687973\tQ-min: 1.639\tQ-max: 1.650\tLives: 5\tReward: 8.0\tEpisode Mean: 115.5\n",
+      "87611:127688035\tQ-min: 1.706\tQ-max: 1.740\tLives: 5\tReward: 9.0\tEpisode Mean: 115.5\n",
+      "87611:127688101\tQ-min: 1.666\tQ-max: 1.698\tLives: 5\tReward: 10.0\tEpisode Mean: 115.5\n",
+      "87611:127688169\tQ-min: 1.679\tQ-max: 1.750\tLives: 5\tReward: 11.0\tEpisode Mean: 115.5\n",
+      "87611:127688219\tQ-min: 1.997\tQ-max: 2.017\tLives: 5\tReward: 12.0\tEpisode Mean: 115.5\n",
+      "87611:127688250\tQ-min: 1.939\tQ-max: 1.967\tLives: 5\tReward: 13.0\tEpisode Mean: 115.5\n",
+      "87611:127688271\tQ-min: 0.062\tQ-max: 0.184\tLives: 4\tReward: 13.0\tEpisode Mean: 115.5\n",
+      "87611:127688324\tQ-min: 1.693\tQ-max: 1.712\tLives: 4\tReward: 14.0\tEpisode Mean: 115.5\n",
+      "87611:127688388\tQ-min: 1.675\tQ-max: 1.700\tLives: 4\tReward: 15.0\tEpisode Mean: 115.5\n",
+      "87611:127688455\tQ-min: 1.696\tQ-max: 1.726\tLives: 4\tReward: 16.0\tEpisode Mean: 115.5\n",
+      "87611:127688503\tQ-min: 1.935\tQ-max: 1.997\tLives: 4\tReward: 17.0\tEpisode Mean: 115.5\n",
+      "87611:127688537\tQ-min: 2.007\tQ-max: 2.051\tLives: 4\tReward: 21.0\tEpisode Mean: 115.5\n",
+      "87611:127688572\tQ-min: 2.072\tQ-max: 2.103\tLives: 4\tReward: 22.0\tEpisode Mean: 115.5\n",
+      "87611:127688606\tQ-min: 2.079\tQ-max: 2.111\tLives: 4\tReward: 26.0\tEpisode Mean: 115.5\n",
+      "87611:127688654\tQ-min: 1.744\tQ-max: 1.785\tLives: 4\tReward: 27.0\tEpisode Mean: 115.5\n",
+      "87611:127688720\tQ-min: 1.739\tQ-max: 1.834\tLives: 4\tReward: 28.0\tEpisode Mean: 115.5\n",
+      "87611:127688795\tQ-min: 1.728\tQ-max: 1.873\tLives: 4\tReward: 32.0\tEpisode Mean: 115.5\n",
+      "87611:127688862\tQ-min: 1.820\tQ-max: 1.842\tLives: 4\tReward: 33.0\tEpisode Mean: 115.5\n",
+      "87611:127688903\tQ-min: -0.170\tQ-max: 0.218\tLives: 3\tReward: 33.0\tEpisode Mean: 115.5\n",
+      "87611:127688946\tQ-min: 1.959\tQ-max: 2.032\tLives: 3\tReward: 34.0\tEpisode Mean: 115.5\n",
+      "87611:127688992\tQ-min: 2.069\tQ-max: 2.191\tLives: 3\tReward: 38.0\tEpisode Mean: 115.5\n",
+      "87611:127689038\tQ-min: 2.113\tQ-max: 2.156\tLives: 3\tReward: 39.0\tEpisode Mean: 115.5\n",
+      "87611:127689077\tQ-min: 2.040\tQ-max: 2.087\tLives: 3\tReward: 40.0\tEpisode Mean: 115.5\n",
+      "87611:127689110\tQ-min: 2.259\tQ-max: 2.468\tLives: 3\tReward: 44.0\tEpisode Mean: 115.5\n",
+      "87611:127689131\tQ-min: 2.239\tQ-max: 2.321\tLives: 3\tReward: 45.0\tEpisode Mean: 115.5\n",
+      "87611:127689151\tQ-min: 2.311\tQ-max: 2.448\tLives: 3\tReward: 49.0\tEpisode Mean: 115.5\n",
+      "87611:127689174\tQ-min: 2.184\tQ-max: 2.402\tLives: 3\tReward: 53.0\tEpisode Mean: 115.5\n",
+      "87611:127689197\tQ-min: 1.841\tQ-max: 2.174\tLives: 3\tReward: 60.0\tEpisode Mean: 115.5\n",
+      "87611:127689217\tQ-min: 2.384\tQ-max: 2.471\tLives: 3\tReward: 61.0\tEpisode Mean: 115.5\n",
+      "87611:127689230\tQ-min: 0.197\tQ-max: 0.306\tLives: 2\tReward: 61.0\tEpisode Mean: 115.5\n",
+      "87611:127689277\tQ-min: 2.105\tQ-max: 2.176\tLives: 2\tReward: 62.0\tEpisode Mean: 115.5\n",
+      "87611:127689322\tQ-min: 2.283\tQ-max: 2.353\tLives: 2\tReward: 66.0\tEpisode Mean: 115.5\n",
+      "87611:127689382\tQ-min: 2.052\tQ-max: 2.270\tLives: 2\tReward: 70.0\tEpisode Mean: 115.5\n",
+      "87611:127689429\tQ-min: -0.143\tQ-max: 0.227\tLives: 1\tReward: 70.0\tEpisode Mean: 115.5\n",
+      "87611:127689487\tQ-min: 1.924\tQ-max: 2.064\tLives: 1\tReward: 74.0\tEpisode Mean: 115.5\n",
+      "87611:127689539\tQ-min: 2.145\tQ-max: 2.299\tLives: 1\tReward: 75.0\tEpisode Mean: 115.5\n",
+      "87611:127689582\tQ-min: 2.220\tQ-max: 2.257\tLives: 1\tReward: 76.0\tEpisode Mean: 115.5\n",
+      "87611:127689626\tQ-min: 2.219\tQ-max: 2.519\tLives: 1\tReward: 83.0\tEpisode Mean: 115.5\n",
+      "87611:127689647\tQ-min: 2.457\tQ-max: 2.644\tLives: 1\tReward: 87.0\tEpisode Mean: 115.5\n",
+      "87611:127689668\tQ-min: 2.354\tQ-max: 2.502\tLives: 1\tReward: 91.0\tEpisode Mean: 115.5\n",
+      "87611:127689691\tQ-min: 2.458\tQ-max: 2.631\tLives: 1\tReward: 95.0\tEpisode Mean: 115.5\n",
+      "87611:127689706\tQ-min: -0.110\tQ-max: 0.026\tLives: 0\tReward: 95.0\tEpisode Mean: 114.7\n",
+      "87612:127689750\tQ-min: 1.751\tQ-max: 1.769\tLives: 5\tReward: 1.0\tEpisode Mean: 114.7\n",
+      "87612:127689790\tQ-min: 1.795\tQ-max: 1.821\tLives: 5\tReward: 2.0\tEpisode Mean: 114.7\n",
+      "87612:127689833\tQ-min: 1.881\tQ-max: 1.913\tLives: 5\tReward: 3.0\tEpisode Mean: 114.7\n",
+      "87612:127689870\tQ-min: 1.958\tQ-max: 1.973\tLives: 5\tReward: 4.0\tEpisode Mean: 114.7\n",
+      "87612:127689900\tQ-min: 1.974\tQ-max: 1.990\tLives: 5\tReward: 5.0\tEpisode Mean: 114.7\n",
+      "87612:127689935\tQ-min: 1.944\tQ-max: 1.996\tLives: 5\tReward: 6.0\tEpisode Mean: 114.7\n",
+      "87612:127689967\tQ-min: 1.818\tQ-max: 1.843\tLives: 5\tReward: 7.0\tEpisode Mean: 114.7\n",
+      "87612:127690014\tQ-min: 1.702\tQ-max: 1.738\tLives: 5\tReward: 8.0\tEpisode Mean: 114.7\n",
+      "87612:127690082\tQ-min: 1.677\tQ-max: 1.687\tLives: 5\tReward: 9.0\tEpisode Mean: 114.7\n",
+      "87612:127690148\tQ-min: 1.712\tQ-max: 1.742\tLives: 5\tReward: 10.0\tEpisode Mean: 114.7\n",
+      "87612:127690189\tQ-min: -0.052\tQ-max: 0.091\tLives: 4\tReward: 10.0\tEpisode Mean: 114.7\n",
+      "87612:127690240\tQ-min: 1.706\tQ-max: 1.735\tLives: 4\tReward: 11.0\tEpisode Mean: 114.7\n",
+      "87612:127690299\tQ-min: 1.686\tQ-max: 1.711\tLives: 4\tReward: 12.0\tEpisode Mean: 114.7\n",
+      "87612:127690372\tQ-min: 1.751\tQ-max: 1.860\tLives: 4\tReward: 13.0\tEpisode Mean: 114.7\n",
+      "87612:127690423\tQ-min: 1.986\tQ-max: 2.016\tLives: 4\tReward: 14.0\tEpisode Mean: 114.7\n",
+      "87612:127690455\tQ-min: 1.965\tQ-max: 1.998\tLives: 4\tReward: 15.0\tEpisode Mean: 114.7\n",
+      "87612:127690475\tQ-min: -0.006\tQ-max: 0.193\tLives: 3\tReward: 15.0\tEpisode Mean: 114.7\n",
+      "87612:127690519\tQ-min: 1.897\tQ-max: 1.910\tLives: 3\tReward: 16.0\tEpisode Mean: 114.7\n",
+      "87612:127690564\tQ-min: 1.922\tQ-max: 1.952\tLives: 3\tReward: 20.0\tEpisode Mean: 114.7\n",
+      "87612:127690608\tQ-min: 1.945\tQ-max: 1.976\tLives: 3\tReward: 21.0\tEpisode Mean: 114.7\n",
+      "87612:127690645\tQ-min: 2.070\tQ-max: 2.110\tLives: 3\tReward: 22.0\tEpisode Mean: 114.7\n",
+      "87612:127690676\tQ-min: 2.045\tQ-max: 2.079\tLives: 3\tReward: 23.0\tEpisode Mean: 114.7\n",
+      "87612:127690710\tQ-min: 2.001\tQ-max: 2.037\tLives: 3\tReward: 27.0\tEpisode Mean: 114.7\n",
+      "87612:127690745\tQ-min: 1.910\tQ-max: 2.610\tLives: 3\tReward: 31.0\tEpisode Mean: 114.7\n",
+      "87612:127690767\tQ-min: 2.287\tQ-max: 2.336\tLives: 3\tReward: 32.0\tEpisode Mean: 114.7\n",
+      "87612:127690789\tQ-min: 2.112\tQ-max: 2.379\tLives: 3\tReward: 36.0\tEpisode Mean: 114.7\n",
+      "87612:127690812\tQ-min: 2.176\tQ-max: 2.347\tLives: 3\tReward: 40.0\tEpisode Mean: 114.7\n",
+      "87612:127690830\tQ-min: 2.378\tQ-max: 2.467\tLives: 3\tReward: 41.0\tEpisode Mean: 114.7\n",
+      "87612:127690849\tQ-min: 2.432\tQ-max: 2.491\tLives: 3\tReward: 42.0\tEpisode Mean: 114.7\n",
+      "87612:127690874\tQ-min: 2.261\tQ-max: 2.397\tLives: 3\tReward: 43.0\tEpisode Mean: 114.7\n",
+      "87612:127690896\tQ-min: 2.270\tQ-max: 2.462\tLives: 3\tReward: 47.0\tEpisode Mean: 114.7\n",
+      "87612:127690911\tQ-min: -0.162\tQ-max: 0.121\tLives: 2\tReward: 47.0\tEpisode Mean: 114.7\n",
+      "87612:127690942\tQ-min: -0.062\tQ-max: 0.110\tLives: 1\tReward: 47.0\tEpisode Mean: 114.7\n",
+      "87612:127690988\tQ-min: 2.038\tQ-max: 2.127\tLives: 1\tReward: 48.0\tEpisode Mean: 114.7\n",
+      "87612:127691043\tQ-min: 1.831\tQ-max: 1.892\tLives: 1\tReward: 49.0\tEpisode Mean: 114.7\n",
+      "87612:127691094\tQ-min: 2.045\tQ-max: 2.178\tLives: 1\tReward: 53.0\tEpisode Mean: 114.7\n",
+      "87612:127691130\tQ-min: 2.256\tQ-max: 2.296\tLives: 1\tReward: 54.0\tEpisode Mean: 114.7\n",
+      "87612:127691163\tQ-min: 2.092\tQ-max: 2.152\tLives: 1\tReward: 55.0\tEpisode Mean: 114.7\n",
+      "87612:127691199\tQ-min: 2.212\tQ-max: 2.310\tLives: 1\tReward: 59.0\tEpisode Mean: 114.7\n",
+      "87612:127691235\tQ-min: 2.541\tQ-max: 2.658\tLives: 1\tReward: 63.0\tEpisode Mean: 114.7\n",
+      "87612:127691257\tQ-min: 2.391\tQ-max: 2.556\tLives: 1\tReward: 64.0\tEpisode Mean: 114.7\n",
+      "87612:127691279\tQ-min: 2.441\tQ-max: 2.611\tLives: 1\tReward: 68.0\tEpisode Mean: 114.7\n",
+      "87612:127691301\tQ-min: 2.411\tQ-max: 2.553\tLives: 1\tReward: 72.0\tEpisode Mean: 114.7\n",
+      "87612:127691314\tQ-min: -0.039\tQ-max: 0.191\tLives: 0\tReward: 72.0\tEpisode Mean: 113.0\n",
+      "87613:127691359\tQ-min: 1.745\tQ-max: 1.768\tLives: 5\tReward: 1.0\tEpisode Mean: 113.0\n",
+      "87613:127691401\tQ-min: 1.827\tQ-max: 1.859\tLives: 5\tReward: 2.0\tEpisode Mean: 113.0\n",
+      "87613:127691444\tQ-min: 1.878\tQ-max: 1.923\tLives: 5\tReward: 3.0\tEpisode Mean: 113.0\n",
+      "87613:127691480\tQ-min: 1.994\tQ-max: 2.023\tLives: 5\tReward: 4.0\tEpisode Mean: 113.0\n",
+      "87613:127691512\tQ-min: 1.955\tQ-max: 1.972\tLives: 5\tReward: 8.0\tEpisode Mean: 113.0\n",
+      "87613:127691549\tQ-min: 2.132\tQ-max: 2.209\tLives: 5\tReward: 12.0\tEpisode Mean: 113.0\n",
+      "87613:127691569\tQ-min: 2.072\tQ-max: 2.212\tLives: 5\tReward: 13.0\tEpisode Mean: 113.0\n",
+      "87613:127691588\tQ-min: 2.069\tQ-max: 2.352\tLives: 5\tReward: 14.0\tEpisode Mean: 113.0\n",
+      "87613:127691608\tQ-min: 2.225\tQ-max: 2.355\tLives: 5\tReward: 15.0\tEpisode Mean: 113.0\n",
+      "87613:127691627\tQ-min: 2.158\tQ-max: 2.320\tLives: 5\tReward: 16.0\tEpisode Mean: 113.0\n",
+      "87613:127691646\tQ-min: 2.036\tQ-max: 2.218\tLives: 5\tReward: 17.0\tEpisode Mean: 113.0\n",
+      "87613:127691659\tQ-min: -0.011\tQ-max: 0.188\tLives: 4\tReward: 17.0\tEpisode Mean: 113.0\n",
+      "87613:127691706\tQ-min: 2.005\tQ-max: 2.059\tLives: 4\tReward: 18.0\tEpisode Mean: 113.0\n",
+      "87613:127691759\tQ-min: 1.721\tQ-max: 1.749\tLives: 4\tReward: 19.0\tEpisode Mean: 113.0\n",
+      "87613:127691814\tQ-min: 2.004\tQ-max: 2.048\tLives: 4\tReward: 20.0\tEpisode Mean: 113.0\n",
+      "87613:127691854\tQ-min: 2.058\tQ-max: 2.087\tLives: 4\tReward: 21.0\tEpisode Mean: 113.0\n",
+      "87613:127691887\tQ-min: 2.067\tQ-max: 2.160\tLives: 4\tReward: 25.0\tEpisode Mean: 113.0\n",
+      "87613:127691922\tQ-min: 2.128\tQ-max: 2.171\tLives: 4\tReward: 26.0\tEpisode Mean: 113.0\n",
+      "87613:127691956\tQ-min: 2.042\tQ-max: 2.120\tLives: 4\tReward: 27.0\tEpisode Mean: 113.0\n",
+      "87613:127691977\tQ-min: -0.151\tQ-max: 0.272\tLives: 3\tReward: 27.0\tEpisode Mean: 113.0\n",
+      "87613:127692019\tQ-min: 2.068\tQ-max: 2.130\tLives: 3\tReward: 28.0\tEpisode Mean: 113.0\n",
+      "87613:127692063\tQ-min: 2.098\tQ-max: 2.317\tLives: 3\tReward: 29.0\tEpisode Mean: 113.0\n",
+      "87613:127692114\tQ-min: 1.773\tQ-max: 1.810\tLives: 3\tReward: 30.0\tEpisode Mean: 113.0\n",
+      "87613:127692165\tQ-min: 2.143\tQ-max: 2.306\tLives: 3\tReward: 31.0\tEpisode Mean: 113.0\n",
+      "87613:127692196\tQ-min: 2.128\tQ-max: 2.189\tLives: 3\tReward: 32.0\tEpisode Mean: 113.0\n",
+      "87613:127692227\tQ-min: 2.140\tQ-max: 2.178\tLives: 3\tReward: 33.0\tEpisode Mean: 113.0\n",
+      "87613:127692261\tQ-min: 2.074\tQ-max: 2.304\tLives: 3\tReward: 34.0\tEpisode Mean: 113.0\n",
+      "87613:127692307\tQ-min: 1.637\tQ-max: 1.851\tLives: 3\tReward: 38.0\tEpisode Mean: 113.0\n",
+      "87613:127692374\tQ-min: 1.796\tQ-max: 1.816\tLives: 3\tReward: 39.0\tEpisode Mean: 113.0\n",
+      "87613:127692442\tQ-min: 1.801\tQ-max: 1.872\tLives: 3\tReward: 40.0\tEpisode Mean: 113.0\n",
+      "87613:127692511\tQ-min: 1.829\tQ-max: 1.987\tLives: 3\tReward: 44.0\tEpisode Mean: 113.0\n",
+      "87613:127692557\tQ-min: -0.002\tQ-max: 0.216\tLives: 2\tReward: 44.0\tEpisode Mean: 113.0\n",
+      "87613:127692609\tQ-min: 1.668\tQ-max: 1.715\tLives: 2\tReward: 45.0\tEpisode Mean: 113.0\n",
+      "87613:127692674\tQ-min: 1.819\tQ-max: 1.864\tLives: 2\tReward: 46.0\tEpisode Mean: 113.0\n",
+      "87613:127692740\tQ-min: 1.784\tQ-max: 1.839\tLives: 2\tReward: 47.0\tEpisode Mean: 113.0\n",
+      "87613:127692787\tQ-min: 2.032\tQ-max: 2.136\tLives: 2\tReward: 48.0\tEpisode Mean: 113.0\n",
+      "87613:127692820\tQ-min: 2.179\tQ-max: 2.296\tLives: 2\tReward: 52.0\tEpisode Mean: 113.0\n",
+      "87613:127692856\tQ-min: 2.184\tQ-max: 2.645\tLives: 2\tReward: 56.0\tEpisode Mean: 113.0\n",
+      "87613:127692878\tQ-min: 2.029\tQ-max: 2.462\tLives: 2\tReward: 60.0\tEpisode Mean: 113.0\n",
+      "87613:127692895\tQ-min: 0.059\tQ-max: 0.351\tLives: 1\tReward: 60.0\tEpisode Mean: 113.0\n",
+      "87613:127692954\tQ-min: 1.990\tQ-max: 2.033\tLives: 1\tReward: 61.0\tEpisode Mean: 113.0\n",
+      "87613:127693009\tQ-min: 2.110\tQ-max: 2.242\tLives: 1\tReward: 65.0\tEpisode Mean: 113.0\n",
+      "87613:127693071\tQ-min: 1.809\tQ-max: 2.087\tLives: 1\tReward: 69.0\tEpisode Mean: 113.0\n",
+      "87613:127693123\tQ-min: 2.208\tQ-max: 2.296\tLives: 1\tReward: 70.0\tEpisode Mean: 113.0\n",
+      "87613:127693156\tQ-min: 2.282\tQ-max: 2.346\tLives: 1\tReward: 71.0\tEpisode Mean: 113.0\n",
+      "87613:127693178\tQ-min: -0.106\tQ-max: 0.113\tLives: 0\tReward: 71.0\tEpisode Mean: 111.3\n",
+      "87614:127693222\tQ-min: 1.750\tQ-max: 1.774\tLives: 5\tReward: 1.0\tEpisode Mean: 111.3\n",
+      "87614:127693264\tQ-min: 1.777\tQ-max: 1.796\tLives: 5\tReward: 2.0\tEpisode Mean: 111.3\n",
+      "87614:127693306\tQ-min: 1.857\tQ-max: 1.881\tLives: 5\tReward: 3.0\tEpisode Mean: 111.3\n",
+      "87614:127693342\tQ-min: 1.973\tQ-max: 1.983\tLives: 5\tReward: 4.0\tEpisode Mean: 111.3\n",
+      "87614:127693373\tQ-min: 1.980\tQ-max: 1.996\tLives: 5\tReward: 5.0\tEpisode Mean: 111.3\n",
+      "87614:127693407\tQ-min: 2.012\tQ-max: 2.063\tLives: 5\tReward: 9.0\tEpisode Mean: 111.3\n",
+      "87614:127693442\tQ-min: 1.857\tQ-max: 1.899\tLives: 5\tReward: 10.0\tEpisode Mean: 111.3\n",
+      "87614:127693488\tQ-min: 1.685\tQ-max: 1.719\tLives: 5\tReward: 11.0\tEpisode Mean: 111.3\n",
+      "87614:127693554\tQ-min: 1.658\tQ-max: 1.684\tLives: 5\tReward: 12.0\tEpisode Mean: 111.3\n",
+      "87614:127693595\tQ-min: -0.077\tQ-max: 0.110\tLives: 4\tReward: 12.0\tEpisode Mean: 111.3\n",
+      "87614:127693639\tQ-min: 1.935\tQ-max: 1.953\tLives: 4\tReward: 13.0\tEpisode Mean: 111.3\n",
+      "87614:127693692\tQ-min: 1.743\tQ-max: 1.785\tLives: 4\tReward: 14.0\tEpisode Mean: 111.3\n",
+      "87614:127693756\tQ-min: 1.742\tQ-max: 1.772\tLives: 4\tReward: 15.0\tEpisode Mean: 111.3\n",
+      "87614:127693808\tQ-min: 2.016\tQ-max: 2.040\tLives: 4\tReward: 16.0\tEpisode Mean: 111.3\n",
+      "87614:127693837\tQ-min: 2.046\tQ-max: 2.066\tLives: 4\tReward: 17.0\tEpisode Mean: 111.3\n",
+      "87614:127693870\tQ-min: 2.004\tQ-max: 2.048\tLives: 4\tReward: 18.0\tEpisode Mean: 111.3\n",
+      "87614:127693904\tQ-min: 2.007\tQ-max: 2.039\tLives: 4\tReward: 22.0\tEpisode Mean: 111.3\n",
+      "87614:127693955\tQ-min: 1.739\tQ-max: 1.798\tLives: 4\tReward: 23.0\tEpisode Mean: 111.3\n",
+      "87614:127694016\tQ-min: 1.755\tQ-max: 1.785\tLives: 4\tReward: 24.0\tEpisode Mean: 111.3\n",
+      "87614:127694083\tQ-min: 1.750\tQ-max: 1.790\tLives: 4\tReward: 25.0\tEpisode Mean: 111.3\n",
+      "87614:127694148\tQ-min: 1.707\tQ-max: 1.768\tLives: 4\tReward: 26.0\tEpisode Mean: 111.3\n",
+      "87614:127694196\tQ-min: 2.009\tQ-max: 2.071\tLives: 4\tReward: 27.0\tEpisode Mean: 111.3\n",
+      "87614:127694227\tQ-min: 2.116\tQ-max: 2.152\tLives: 4\tReward: 28.0\tEpisode Mean: 111.3\n",
+      "87614:127694259\tQ-min: 2.037\tQ-max: 2.085\tLives: 4\tReward: 29.0\tEpisode Mean: 111.3\n",
+      "87614:127694292\tQ-min: 2.018\tQ-max: 2.095\tLives: 4\tReward: 30.0\tEpisode Mean: 111.3\n",
+      "87614:127694314\tQ-min: -0.285\tQ-max: 0.053\tLives: 3\tReward: 30.0\tEpisode Mean: 111.3\n",
+      "87614:127694371\tQ-min: 1.691\tQ-max: 1.742\tLives: 3\tReward: 31.0\tEpisode Mean: 111.3\n",
+      "87614:127694434\tQ-min: 1.687\tQ-max: 1.788\tLives: 3\tReward: 32.0\tEpisode Mean: 111.3\n",
+      "87614:127694488\tQ-min: 1.859\tQ-max: 1.963\tLives: 3\tReward: 36.0\tEpisode Mean: 111.3\n",
+      "87614:127694528\tQ-min: 2.115\tQ-max: 2.230\tLives: 3\tReward: 40.0\tEpisode Mean: 111.3\n",
+      "87614:127694561\tQ-min: 2.051\tQ-max: 2.173\tLives: 3\tReward: 41.0\tEpisode Mean: 111.3\n",
+      "87614:127694597\tQ-min: 2.074\tQ-max: 2.582\tLives: 3\tReward: 45.0\tEpisode Mean: 111.3\n",
+      "87614:127694619\tQ-min: 2.325\tQ-max: 2.481\tLives: 3\tReward: 49.0\tEpisode Mean: 111.3\n",
+      "87614:127694642\tQ-min: 2.416\tQ-max: 2.450\tLives: 3\tReward: 53.0\tEpisode Mean: 111.3\n",
+      "87614:127694663\tQ-min: 2.358\tQ-max: 2.467\tLives: 3\tReward: 54.0\tEpisode Mean: 111.3\n",
+      "87614:127694683\tQ-min: 2.331\tQ-max: 2.552\tLives: 3\tReward: 55.0\tEpisode Mean: 111.3\n",
+      "87614:127694696\tQ-min: -0.492\tQ-max: 0.288\tLives: 2\tReward: 55.0\tEpisode Mean: 111.3\n",
+      "87614:127694739\tQ-min: 1.990\tQ-max: 2.128\tLives: 2\tReward: 56.0\tEpisode Mean: 111.3\n",
+      "87614:127694797\tQ-min: 1.893\tQ-max: 1.925\tLives: 2\tReward: 57.0\tEpisode Mean: 111.3\n",
+      "87614:127694854\tQ-min: 2.099\tQ-max: 2.424\tLives: 2\tReward: 61.0\tEpisode Mean: 111.3\n",
+      "87614:127694898\tQ-min: 2.109\tQ-max: 2.136\tLives: 2\tReward: 65.0\tEpisode Mean: 111.3\n",
+      "87614:127694935\tQ-min: 2.176\tQ-max: 2.392\tLives: 2\tReward: 69.0\tEpisode Mean: 111.3\n",
+      "87614:127694956\tQ-min: 2.303\tQ-max: 2.598\tLives: 2\tReward: 73.0\tEpisode Mean: 111.3\n",
+      "87614:127694976\tQ-min: 2.456\tQ-max: 2.828\tLives: 2\tReward: 77.0\tEpisode Mean: 111.3\n",
+      "87614:127695000\tQ-min: 2.335\tQ-max: 2.567\tLives: 2\tReward: 81.0\tEpisode Mean: 111.3\n",
+      "87614:127695019\tQ-min: 2.435\tQ-max: 2.554\tLives: 2\tReward: 82.0\tEpisode Mean: 111.3\n",
+      "87614:127695040\tQ-min: 2.345\tQ-max: 2.483\tLives: 2\tReward: 86.0\tEpisode Mean: 111.3\n",
+      "87614:127695053\tQ-min: -0.225\tQ-max: 0.476\tLives: 1\tReward: 86.0\tEpisode Mean: 111.3\n",
+      "87614:127695101\tQ-min: 2.318\tQ-max: 2.462\tLives: 1\tReward: 90.0\tEpisode Mean: 111.3\n",
+      "87614:127695163\tQ-min: 1.764\tQ-max: 2.016\tLives: 1\tReward: 94.0\tEpisode Mean: 111.3\n",
+      "87614:127695227\tQ-min: 2.137\tQ-max: 2.588\tLives: 1\tReward: 98.0\tEpisode Mean: 111.3\n",
+      "87614:127695248\tQ-min: 2.451\tQ-max: 2.519\tLives: 1\tReward: 99.0\tEpisode Mean: 111.3\n",
+      "87614:127695260\tQ-min: -0.245\tQ-max: 0.131\tLives: 0\tReward: 99.0\tEpisode Mean: 110.9\n",
+      "87615:127695313\tQ-min: 1.644\tQ-max: 1.656\tLives: 5\tReward: 1.0\tEpisode Mean: 110.9\n",
+      "87615:127695365\tQ-min: 1.792\tQ-max: 1.807\tLives: 5\tReward: 2.0\tEpisode Mean: 110.9\n",
+      "87615:127695403\tQ-min: 1.872\tQ-max: 1.891\tLives: 5\tReward: 3.0\tEpisode Mean: 110.9\n",
+      "87615:127695441\tQ-min: 2.002\tQ-max: 2.014\tLives: 5\tReward: 4.0\tEpisode Mean: 110.9\n",
+      "87615:127695474\tQ-min: 1.930\tQ-max: 1.958\tLives: 5\tReward: 5.0\tEpisode Mean: 110.9\n",
+      "87615:127695507\tQ-min: 1.958\tQ-max: 1.969\tLives: 5\tReward: 6.0\tEpisode Mean: 110.9\n",
+      "87615:127695540\tQ-min: 1.767\tQ-max: 1.786\tLives: 5\tReward: 7.0\tEpisode Mean: 110.9\n",
+      "87615:127695586\tQ-min: 1.630\tQ-max: 1.665\tLives: 5\tReward: 8.0\tEpisode Mean: 110.9\n",
+      "87615:127695646\tQ-min: 1.651\tQ-max: 1.676\tLives: 5\tReward: 9.0\tEpisode Mean: 110.9\n",
+      "87615:127695714\tQ-min: 1.686\tQ-max: 1.746\tLives: 5\tReward: 10.0\tEpisode Mean: 110.9\n",
+      "87615:127695781\tQ-min: 1.688\tQ-max: 1.709\tLives: 5\tReward: 11.0\tEpisode Mean: 110.9\n",
+      "87615:127695828\tQ-min: 2.002\tQ-max: 2.024\tLives: 5\tReward: 12.0\tEpisode Mean: 110.9\n",
+      "87615:127695859\tQ-min: 1.929\tQ-max: 2.010\tLives: 5\tReward: 13.0\tEpisode Mean: 110.9\n",
+      "87615:127695894\tQ-min: 1.987\tQ-max: 2.036\tLives: 5\tReward: 14.0\tEpisode Mean: 110.9\n",
+      "87615:127695928\tQ-min: 2.012\tQ-max: 2.038\tLives: 5\tReward: 15.0\tEpisode Mean: 110.9\n",
+      "87615:127695962\tQ-min: 1.989\tQ-max: 2.046\tLives: 5\tReward: 19.0\tEpisode Mean: 110.9\n",
+      "87615:127695998\tQ-min: 1.958\tQ-max: 2.017\tLives: 5\tReward: 20.0\tEpisode Mean: 110.9\n",
+      "87615:127696031\tQ-min: 2.078\tQ-max: 2.125\tLives: 5\tReward: 21.0\tEpisode Mean: 110.9\n",
+      "87615:127696060\tQ-min: 2.000\tQ-max: 2.057\tLives: 5\tReward: 22.0\tEpisode Mean: 110.9\n",
+      "87615:127696091\tQ-min: 1.998\tQ-max: 2.015\tLives: 5\tReward: 23.0\tEpisode Mean: 110.9\n",
+      "87615:127696124\tQ-min: 1.998\tQ-max: 2.097\tLives: 5\tReward: 24.0\tEpisode Mean: 110.9\n",
+      "87615:127696158\tQ-min: 2.085\tQ-max: 2.110\tLives: 5\tReward: 25.0\tEpisode Mean: 110.9\n",
+      "87615:127696191\tQ-min: 2.076\tQ-max: 2.096\tLives: 5\tReward: 26.0\tEpisode Mean: 110.9\n",
+      "87615:127696226\tQ-min: 1.985\tQ-max: 2.069\tLives: 5\tReward: 27.0\tEpisode Mean: 110.9\n",
+      "87615:127696257\tQ-min: 2.051\tQ-max: 2.086\tLives: 5\tReward: 28.0\tEpisode Mean: 110.9\n",
+      "87615:127696290\tQ-min: 2.114\tQ-max: 2.177\tLives: 5\tReward: 29.0\tEpisode Mean: 110.9\n",
+      "87615:127696320\tQ-min: 2.070\tQ-max: 2.181\tLives: 5\tReward: 33.0\tEpisode Mean: 110.9\n",
+      "87615:127696355\tQ-min: 2.082\tQ-max: 2.118\tLives: 5\tReward: 34.0\tEpisode Mean: 110.9\n",
+      "87615:127696393\tQ-min: 2.118\tQ-max: 2.194\tLives: 5\tReward: 38.0\tEpisode Mean: 110.9\n",
+      "87615:127696430\tQ-min: 2.048\tQ-max: 2.562\tLives: 5\tReward: 42.0\tEpisode Mean: 110.9\n",
+      "87615:127696452\tQ-min: 2.323\tQ-max: 2.461\tLives: 5\tReward: 46.0\tEpisode Mean: 110.9\n",
+      "87615:127696472\tQ-min: 2.380\tQ-max: 2.524\tLives: 5\tReward: 50.0\tEpisode Mean: 110.9\n",
+      "87615:127696487\tQ-min: -0.145\tQ-max: 0.130\tLives: 4\tReward: 50.0\tEpisode Mean: 110.9\n",
+      "87615:127696535\tQ-min: 2.262\tQ-max: 2.437\tLives: 4\tReward: 54.0\tEpisode Mean: 110.9\n",
+      "87615:127696557\tQ-min: 2.189\tQ-max: 2.453\tLives: 4\tReward: 58.0\tEpisode Mean: 110.9\n",
+      "87615:127696572\tQ-min: -0.210\tQ-max: 0.358\tLives: 3\tReward: 58.0\tEpisode Mean: 110.9\n",
+      "87615:127696618\tQ-min: 2.260\tQ-max: 2.367\tLives: 3\tReward: 59.0\tEpisode Mean: 110.9\n",
+      "87615:127696675\tQ-min: 1.786\tQ-max: 1.954\tLives: 3\tReward: 60.0\tEpisode Mean: 110.9\n",
+      "87615:127696735\tQ-min: 2.186\tQ-max: 2.563\tLives: 3\tReward: 64.0\tEpisode Mean: 110.9\n",
+      "87615:127696758\tQ-min: 1.883\tQ-max: 2.417\tLives: 3\tReward: 71.0\tEpisode Mean: 110.9\n",
+      "87615:127696781\tQ-min: 2.119\tQ-max: 2.631\tLives: 3\tReward: 75.0\tEpisode Mean: 110.9\n",
+      "87615:127696801\tQ-min: 2.197\tQ-max: 2.471\tLives: 3\tReward: 76.0\tEpisode Mean: 110.9\n",
+      "87615:127696820\tQ-min: 2.283\tQ-max: 2.550\tLives: 3\tReward: 77.0\tEpisode Mean: 110.9\n",
+      "87615:127696841\tQ-min: 2.156\tQ-max: 2.532\tLives: 3\tReward: 81.0\tEpisode Mean: 110.9\n",
+      "87615:127696855\tQ-min: -0.188\tQ-max: 0.150\tLives: 2\tReward: 81.0\tEpisode Mean: 110.9\n",
+      "87615:127696899\tQ-min: 2.084\tQ-max: 2.306\tLives: 2\tReward: 85.0\tEpisode Mean: 110.9\n",
+      "87615:127696943\tQ-min: 2.099\tQ-max: 2.307\tLives: 2\tReward: 89.0\tEpisode Mean: 110.9\n",
+      "87615:127696972\tQ-min: -0.173\tQ-max: 0.569\tLives: 1\tReward: 89.0\tEpisode Mean: 110.9\n",
+      "87615:127697032\tQ-min: 1.803\tQ-max: 1.997\tLives: 1\tReward: 90.0\tEpisode Mean: 110.9\n",
+      "87615:127697097\tQ-min: 2.094\tQ-max: 2.214\tLives: 1\tReward: 94.0\tEpisode Mean: 110.9\n",
+      "87615:127697156\tQ-min: 2.298\tQ-max: 2.593\tLives: 1\tReward: 98.0\tEpisode Mean: 110.9\n",
+      "87615:127697183\tQ-min: -0.134\tQ-max: 0.380\tLives: 0\tReward: 98.0\tEpisode Mean: 110.4\n",
+      "87616:127697225\tQ-min: 1.703\tQ-max: 1.717\tLives: 5\tReward: 1.0\tEpisode Mean: 110.4\n",
+      "87616:127697278\tQ-min: 1.614\tQ-max: 1.670\tLives: 5\tReward: 2.0\tEpisode Mean: 110.4\n",
+      "87616:127697329\tQ-min: 1.848\tQ-max: 1.875\tLives: 5\tReward: 3.0\tEpisode Mean: 110.4\n",
+      "87616:127697362\tQ-min: 1.979\tQ-max: 2.041\tLives: 5\tReward: 4.0\tEpisode Mean: 110.4\n",
+      "87616:127697394\tQ-min: 1.945\tQ-max: 1.984\tLives: 5\tReward: 5.0\tEpisode Mean: 110.4\n",
+      "87616:127697423\tQ-min: 1.952\tQ-max: 1.963\tLives: 5\tReward: 6.0\tEpisode Mean: 110.4\n",
+      "87616:127697452\tQ-min: 1.739\tQ-max: 1.772\tLives: 5\tReward: 7.0\tEpisode Mean: 110.4\n",
+      "87616:127697495\tQ-min: 1.631\tQ-max: 1.654\tLives: 5\tReward: 8.0\tEpisode Mean: 110.4\n",
+      "87616:127697555\tQ-min: 1.644\tQ-max: 1.668\tLives: 5\tReward: 9.0\tEpisode Mean: 110.4\n",
+      "87616:127697616\tQ-min: 1.641\tQ-max: 1.662\tLives: 5\tReward: 10.0\tEpisode Mean: 110.4\n",
+      "87616:127697682\tQ-min: 0.999\tQ-max: 1.069\tLives: 5\tReward: 11.0\tEpisode Mean: 110.4\n",
+      "87616:127697733\tQ-min: 2.047\tQ-max: 2.073\tLives: 5\tReward: 12.0\tEpisode Mean: 110.4\n",
+      "87616:127697765\tQ-min: 1.928\tQ-max: 1.949\tLives: 5\tReward: 13.0\tEpisode Mean: 110.4\n",
+      "87616:127697799\tQ-min: 1.990\tQ-max: 2.029\tLives: 5\tReward: 14.0\tEpisode Mean: 110.4\n",
+      "87616:127697834\tQ-min: 2.052\tQ-max: 2.094\tLives: 5\tReward: 15.0\tEpisode Mean: 110.4\n",
+      "87616:127697869\tQ-min: 1.954\tQ-max: 2.032\tLives: 5\tReward: 19.0\tEpisode Mean: 110.4\n",
+      "87616:127697902\tQ-min: 2.165\tQ-max: 2.206\tLives: 5\tReward: 20.0\tEpisode Mean: 110.4\n",
+      "87616:127697935\tQ-min: 1.969\tQ-max: 2.142\tLives: 5\tReward: 24.0\tEpisode Mean: 110.4\n",
+      "87616:127697968\tQ-min: 2.081\tQ-max: 2.098\tLives: 5\tReward: 25.0\tEpisode Mean: 110.4\n",
+      "87616:127698001\tQ-min: 2.022\tQ-max: 2.087\tLives: 5\tReward: 26.0\tEpisode Mean: 110.4\n",
+      "87616:127698030\tQ-min: 2.072\tQ-max: 2.114\tLives: 5\tReward: 27.0\tEpisode Mean: 110.4\n",
+      "87616:127698061\tQ-min: 2.032\tQ-max: 2.050\tLives: 5\tReward: 28.0\tEpisode Mean: 110.4\n",
+      "87616:127698095\tQ-min: 1.993\tQ-max: 2.009\tLives: 5\tReward: 29.0\tEpisode Mean: 110.4\n",
+      "87616:127698128\tQ-min: 1.861\tQ-max: 2.085\tLives: 5\tReward: 30.0\tEpisode Mean: 110.4\n",
+      "87616:127698161\tQ-min: 2.075\tQ-max: 2.110\tLives: 5\tReward: 31.0\tEpisode Mean: 110.4\n",
+      "87616:127698194\tQ-min: 2.077\tQ-max: 2.090\tLives: 5\tReward: 32.0\tEpisode Mean: 110.4\n",
+      "87616:127698225\tQ-min: 2.082\tQ-max: 2.113\tLives: 5\tReward: 33.0\tEpisode Mean: 110.4\n",
+      "87616:127698261\tQ-min: 1.975\tQ-max: 2.015\tLives: 5\tReward: 34.0\tEpisode Mean: 110.4\n",
+      "87616:127698294\tQ-min: 2.130\tQ-max: 2.170\tLives: 5\tReward: 35.0\tEpisode Mean: 110.4\n",
+      "87616:127698329\tQ-min: 2.118\tQ-max: 2.168\tLives: 5\tReward: 36.0\tEpisode Mean: 110.4\n",
+      "87616:127698363\tQ-min: 2.075\tQ-max: 2.104\tLives: 5\tReward: 37.0\tEpisode Mean: 110.4\n",
+      "87616:127698401\tQ-min: 2.063\tQ-max: 2.154\tLives: 5\tReward: 41.0\tEpisode Mean: 110.4\n",
+      "87616:127698437\tQ-min: 2.146\tQ-max: 2.295\tLives: 5\tReward: 45.0\tEpisode Mean: 110.4\n",
+      "87616:127698460\tQ-min: -0.165\tQ-max: 0.070\tLives: 4\tReward: 45.0\tEpisode Mean: 110.4\n",
+      "87616:127698501\tQ-min: 1.846\tQ-max: 2.047\tLives: 4\tReward: 49.0\tEpisode Mean: 110.4\n",
+      "87616:127698549\tQ-min: 1.692\tQ-max: 1.968\tLives: 4\tReward: 53.0\tEpisode Mean: 110.4\n",
+      "87616:127698609\tQ-min: 1.560\tQ-max: 2.071\tLives: 4\tReward: 57.0\tEpisode Mean: 110.4\n",
+      "87616:127698663\tQ-min: 2.200\tQ-max: 2.331\tLives: 4\tReward: 58.0\tEpisode Mean: 110.4\n",
+      "87616:127698697\tQ-min: 2.231\tQ-max: 2.292\tLives: 4\tReward: 62.0\tEpisode Mean: 110.4\n",
+      "87616:127698719\tQ-min: -0.132\tQ-max: 0.132\tLives: 3\tReward: 62.0\tEpisode Mean: 110.4\n",
+      "87616:127698766\tQ-min: 2.324\tQ-max: 2.472\tLives: 3\tReward: 66.0\tEpisode Mean: 110.4\n",
+      "87616:127698780\tQ-min: -0.485\tQ-max: 0.170\tLives: 2\tReward: 66.0\tEpisode Mean: 110.4\n",
+      "87616:127698845\tQ-min: 1.700\tQ-max: 2.194\tLives: 2\tReward: 70.0\tEpisode Mean: 110.4\n",
+      "87616:127698858\tQ-min: -0.183\tQ-max: 0.237\tLives: 1\tReward: 70.0\tEpisode Mean: 110.4\n",
+      "87616:127698912\tQ-min: 1.906\tQ-max: 1.984\tLives: 1\tReward: 71.0\tEpisode Mean: 110.4\n",
+      "87616:127698981\tQ-min: 1.634\tQ-max: 2.061\tLives: 1\tReward: 75.0\tEpisode Mean: 110.4\n",
+      "87616:127699002\tQ-min: 2.364\tQ-max: 2.565\tLives: 1\tReward: 79.0\tEpisode Mean: 110.4\n",
+      "87616:127699023\tQ-min: 2.297\tQ-max: 2.456\tLives: 1\tReward: 83.0\tEpisode Mean: 110.4\n",
+      "87616:127699047\tQ-min: 2.357\tQ-max: 2.603\tLives: 1\tReward: 90.0\tEpisode Mean: 110.4\n",
+      "87616:127699071\tQ-min: 2.331\tQ-max: 2.936\tLives: 1\tReward: 97.0\tEpisode Mean: 110.4\n",
+      "87616:127699094\tQ-min: 2.704\tQ-max: 2.889\tLives: 1\tReward: 101.0\tEpisode Mean: 110.4\n",
+      "87616:127699118\tQ-min: 2.564\tQ-max: 3.139\tLives: 1\tReward: 105.0\tEpisode Mean: 110.4\n",
+      "87616:127699140\tQ-min: 2.534\tQ-max: 3.215\tLives: 1\tReward: 109.0\tEpisode Mean: 110.4\n",
+      "87616:127699152\tQ-min: 0.192\tQ-max: 0.497\tLives: 0\tReward: 109.0\tEpisode Mean: 110.4\n",
+      "87617:127699197\tQ-min: 1.694\tQ-max: 1.702\tLives: 5\tReward: 1.0\tEpisode Mean: 110.4\n",
+      "87617:127699252\tQ-min: 1.658\tQ-max: 1.666\tLives: 5\tReward: 2.0\tEpisode Mean: 110.4\n",
+      "87617:127699301\tQ-min: 1.892\tQ-max: 1.912\tLives: 5\tReward: 3.0\tEpisode Mean: 110.4\n",
+      "87617:127699338\tQ-min: 1.997\tQ-max: 2.023\tLives: 5\tReward: 4.0\tEpisode Mean: 110.4\n",
+      "87617:127699372\tQ-min: 1.976\tQ-max: 2.003\tLives: 5\tReward: 5.0\tEpisode Mean: 110.4\n",
+      "87617:127699403\tQ-min: 1.906\tQ-max: 1.942\tLives: 5\tReward: 6.0\tEpisode Mean: 110.4\n",
+      "87617:127699434\tQ-min: 1.797\tQ-max: 1.812\tLives: 5\tReward: 7.0\tEpisode Mean: 110.4\n",
+      "87617:127699478\tQ-min: 1.615\tQ-max: 1.650\tLives: 5\tReward: 8.0\tEpisode Mean: 110.4\n",
+      "87617:127699542\tQ-min: 1.665\tQ-max: 1.680\tLives: 5\tReward: 9.0\tEpisode Mean: 110.4\n",
+      "87617:127699610\tQ-min: 1.693\tQ-max: 1.714\tLives: 5\tReward: 10.0\tEpisode Mean: 110.4\n",
+      "87617:127699671\tQ-min: 1.673\tQ-max: 1.692\tLives: 5\tReward: 11.0\tEpisode Mean: 110.4\n",
+      "87617:127699720\tQ-min: 1.956\tQ-max: 1.970\tLives: 5\tReward: 12.0\tEpisode Mean: 110.4\n",
+      "87617:127699754\tQ-min: 1.901\tQ-max: 1.931\tLives: 5\tReward: 13.0\tEpisode Mean: 110.4\n",
+      "87617:127699789\tQ-min: 1.956\tQ-max: 2.007\tLives: 5\tReward: 14.0\tEpisode Mean: 110.4\n",
+      "87617:127699823\tQ-min: 2.002\tQ-max: 2.022\tLives: 5\tReward: 15.0\tEpisode Mean: 110.4\n",
+      "87617:127699856\tQ-min: 1.966\tQ-max: 1.983\tLives: 5\tReward: 16.0\tEpisode Mean: 110.4\n",
+      "87617:127699889\tQ-min: 1.925\tQ-max: 1.947\tLives: 5\tReward: 17.0\tEpisode Mean: 110.4\n",
+      "87617:127699922\tQ-min: 2.050\tQ-max: 2.089\tLives: 5\tReward: 18.0\tEpisode Mean: 110.4\n",
+      "87617:127699956\tQ-min: 1.911\tQ-max: 1.959\tLives: 5\tReward: 19.0\tEpisode Mean: 110.4\n",
+      "87617:127699987\tQ-min: 1.982\tQ-max: 2.019\tLives: 5\tReward: 20.0\tEpisode Mean: 110.4\n",
+      "87617:127700020\tQ-min: 1.983\tQ-max: 2.017\tLives: 5\tReward: 21.0\tEpisode Mean: 110.4\n",
+      "87617:127700053\tQ-min: 1.962\tQ-max: 1.982\tLives: 5\tReward: 22.0\tEpisode Mean: 110.4\n",
+      "87617:127700087\tQ-min: 2.054\tQ-max: 2.074\tLives: 5\tReward: 23.0\tEpisode Mean: 110.4\n",
+      "87617:127700119\tQ-min: 1.990\tQ-max: 2.013\tLives: 5\tReward: 24.0\tEpisode Mean: 110.4\n",
+      "87617:127700153\tQ-min: 1.946\tQ-max: 2.082\tLives: 5\tReward: 25.0\tEpisode Mean: 110.4\n",
+      "87617:127700187\tQ-min: 2.120\tQ-max: 2.171\tLives: 5\tReward: 29.0\tEpisode Mean: 110.4\n",
+      "87617:127700221\tQ-min: 2.097\tQ-max: 2.204\tLives: 5\tReward: 30.0\tEpisode Mean: 110.4\n",
+      "87617:127700255\tQ-min: 2.083\tQ-max: 2.144\tLives: 5\tReward: 34.0\tEpisode Mean: 110.4\n",
+      "87617:127700289\tQ-min: 2.044\tQ-max: 2.494\tLives: 5\tReward: 38.0\tEpisode Mean: 110.4\n",
+      "87617:127700303\tQ-min: -0.229\tQ-max: -0.038\tLives: 4\tReward: 38.0\tEpisode Mean: 110.4\n",
+      "87617:127700350\tQ-min: 2.320\tQ-max: 2.658\tLives: 4\tReward: 45.0\tEpisode Mean: 110.4\n",
+      "87617:127700371\tQ-min: 2.498\tQ-max: 2.616\tLives: 4\tReward: 46.0\tEpisode Mean: 110.4\n",
+      "87617:127700389\tQ-min: 2.313\tQ-max: 2.581\tLives: 4\tReward: 47.0\tEpisode Mean: 110.4\n",
+      "87617:127700409\tQ-min: 2.397\tQ-max: 2.636\tLives: 4\tReward: 48.0\tEpisode Mean: 110.4\n",
+      "87617:127700429\tQ-min: 2.397\tQ-max: 2.452\tLives: 4\tReward: 49.0\tEpisode Mean: 110.4\n",
+      "87617:127700442\tQ-min: 0.100\tQ-max: 0.184\tLives: 3\tReward: 49.0\tEpisode Mean: 110.4\n",
+      "87617:127700489\tQ-min: 2.196\tQ-max: 2.277\tLives: 3\tReward: 53.0\tEpisode Mean: 110.4\n",
+      "87617:127700549\tQ-min: 1.910\tQ-max: 2.034\tLives: 3\tReward: 54.0\tEpisode Mean: 110.4\n",
+      "87617:127700603\tQ-min: 2.033\tQ-max: 2.343\tLives: 3\tReward: 58.0\tEpisode Mean: 110.4\n",
+      "87617:127700643\tQ-min: 2.113\tQ-max: 2.383\tLives: 3\tReward: 62.0\tEpisode Mean: 110.4\n",
+      "87617:127700678\tQ-min: 1.847\tQ-max: 2.895\tLives: 3\tReward: 66.0\tEpisode Mean: 110.4\n",
+      "87617:127700700\tQ-min: 2.374\tQ-max: 2.658\tLives: 3\tReward: 73.0\tEpisode Mean: 110.4\n",
+      "87617:127700724\tQ-min: 2.356\tQ-max: 2.610\tLives: 3\tReward: 77.0\tEpisode Mean: 110.4\n",
+      "87617:127700738\tQ-min: 0.235\tQ-max: 0.481\tLives: 2\tReward: 77.0\tEpisode Mean: 110.4\n",
+      "87617:127700785\tQ-min: 2.617\tQ-max: 3.107\tLives: 2\tReward: 84.0\tEpisode Mean: 110.4\n",
+      "87617:127700808\tQ-min: 2.499\tQ-max: 2.759\tLives: 2\tReward: 88.0\tEpisode Mean: 110.4\n",
+      "87617:127700824\tQ-min: -0.013\tQ-max: 0.391\tLives: 1\tReward: 88.0\tEpisode Mean: 110.4\n",
+      "87617:127700878\tQ-min: 1.760\tQ-max: 1.912\tLives: 1\tReward: 89.0\tEpisode Mean: 110.4\n",
+      "87617:127700945\tQ-min: 1.799\tQ-max: 2.087\tLives: 1\tReward: 93.0\tEpisode Mean: 110.4\n",
+      "87617:127701003\tQ-min: 2.359\tQ-max: 2.529\tLives: 1\tReward: 97.0\tEpisode Mean: 110.4\n",
+      "87617:127701041\tQ-min: 2.311\tQ-max: 2.677\tLives: 1\tReward: 101.0\tEpisode Mean: 110.4\n",
+      "87617:127701075\tQ-min: 2.481\tQ-max: 2.649\tLives: 1\tReward: 105.0\tEpisode Mean: 110.4\n",
+      "87617:127701107\tQ-min: 2.365\tQ-max: 2.683\tLives: 1\tReward: 106.0\tEpisode Mean: 110.4\n",
+      "87617:127701142\tQ-min: 2.326\tQ-max: 2.703\tLives: 1\tReward: 110.0\tEpisode Mean: 110.4\n",
+      "87617:127701197\tQ-min: 1.775\tQ-max: 2.206\tLives: 1\tReward: 114.0\tEpisode Mean: 110.4\n",
+      "87617:127701271\tQ-min: 2.262\tQ-max: 2.510\tLives: 1\tReward: 115.0\tEpisode Mean: 110.4\n",
+      "87617:127701340\tQ-min: 1.927\tQ-max: 2.832\tLives: 1\tReward: 119.0\tEpisode Mean: 110.4\n",
+      "87617:127701363\tQ-min: 2.547\tQ-max: 2.709\tLives: 1\tReward: 123.0\tEpisode Mean: 110.4\n",
+      "87617:127701384\tQ-min: 2.411\tQ-max: 3.237\tLives: 1\tReward: 127.0\tEpisode Mean: 110.4\n",
+      "87617:127701405\tQ-min: 2.788\tQ-max: 3.000\tLives: 1\tReward: 131.0\tEpisode Mean: 110.4\n",
+      "87617:127701424\tQ-min: 2.188\tQ-max: 2.956\tLives: 1\tReward: 132.0\tEpisode Mean: 110.4\n",
+      "87617:127701443\tQ-min: 2.006\tQ-max: 2.765\tLives: 1\tReward: 136.0\tEpisode Mean: 110.4\n",
+      "87617:127701458\tQ-min: 0.031\tQ-max: 0.288\tLives: 0\tReward: 136.0\tEpisode Mean: 111.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "agent.run(num_episodes=30)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now print some statistics for the episode rewards, which vary greatly from one episode to the next."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rewards for 30 episodes:\n",
+      "- Min:    43.0\n",
+      "- Mean:   111.233333333\n",
+      "- Max:    381.0\n",
+      "- Stdev:  62.8424927011\n"
+     ]
+    }
+   ],
+   "source": [
+    "rewards = agent.episode_rewards\n",
+    "print(\"Rewards for {0} episodes:\".format(len(rewards)))\n",
+    "print(\"- Min:   \", np.min(rewards))\n",
+    "print(\"- Mean:  \", np.mean(rewards))\n",
+    "print(\"- Max:   \", np.max(rewards))\n",
+    "print(\"- Stdev: \", np.std(rewards))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can also plot a histogram with the episode rewards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAD8CAYAAABXe05zAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ntyQVY3FLUjEWtyQVY3FLUjH/B5xF3PzU8tyZAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0263400>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_ = plt.hist(rewards, bins=30)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Example States\n",
+    "\n",
+    "We can plot examples of states from the game-environment and the Q-values that are estimated by the Neural Network.\n",
+    "\n",
+    "This helper-function prints the Q-values for a given index in the replay-memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def print_q_values(idx):\n",
+    "    \"\"\"Print Q-values and actions from the replay-memory at the given index.\"\"\"\n",
+    "\n",
+    "    # Get the Q-values and action from the replay-memory.\n",
+    "    q_values = replay_memory.q_values[idx]\n",
+    "    action = replay_memory.actions[idx]\n",
+    "\n",
+    "    print(\"Action:     Q-Value:\")\n",
+    "    print(\"====================\")\n",
+    "\n",
+    "    # Print all the actions and their Q-values.\n",
+    "    for i, q_value in enumerate(q_values):\n",
+    "        # Used to display which action was taken.\n",
+    "        if i == action:\n",
+    "            action_taken = \"(Action Taken)\"\n",
+    "        else:\n",
+    "            action_taken = \"\"\n",
+    "\n",
+    "        # Text-name of the action.\n",
+    "        action_name = agent.get_action_name(i)\n",
+    "            \n",
+    "        print(\"{0:12}{1:.3f} {2}\".format(action_name, q_value,\n",
+    "                                        action_taken))\n",
+    "\n",
+    "    # Newline.\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This helper-function plots a state from the replay-memory and optionally prints the Q-values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_state(idx, print_q=True):\n",
+    "    \"\"\"Plot the state in the replay-memory with the given index.\"\"\"\n",
+    "\n",
+    "    # Get the state from the replay-memory.\n",
+    "    state = replay_memory.states[idx]\n",
+    "    \n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(1, 2)\n",
+    "\n",
+    "    # Plot the image from the game-environment.\n",
+    "    ax = axes.flat[0]\n",
+    "    ax.imshow(state[:, :, 0], vmin=0, vmax=255,\n",
+    "              interpolation='lanczos', cmap='gray')\n",
+    "\n",
+    "    # Plot the motion-trace.\n",
+    "    ax = axes.flat[1]\n",
+    "    ax.imshow(state[:, :, 1], vmin=0, vmax=255,\n",
+    "              interpolation='lanczos', cmap='gray')\n",
+    "\n",
+    "    # This is necessary if we show more than one plot in a single Notebook cell.\n",
+    "    plt.show()\n",
+    "    \n",
+    "    # Print the Q-values.\n",
+    "    if print_q:\n",
+    "        print_q_values(idx=idx)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The replay-memory has room for 200k states but it is only partially full from the above call to `agent.run(num_episodes=1)`. This is how many states are actually used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "935"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_used = replay_memory.num_used\n",
+    "num_used"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the Q-values from the replay-memory that are actually used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "q_values = replay_memory.q_values[0:num_used, :]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "For each state, calculate the min / max Q-values and their difference. This will be used to lookup interesting states in the following sections."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "q_values_min = q_values.min(axis=1)\n",
+    "q_values_max = q_values.max(axis=1)\n",
+    "q_values_dif = q_values_max - q_values_min"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Example States: Highest Reward\n",
+    "\n",
+    "This example shows the states surrounding the state with the highest reward.\n",
+    "\n",
+    "During the training we limit the rewards to the range [-1, 1] so this basically just gets the first state that has a reward of 1."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "40"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = np.argmax(replay_memory.rewards)\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This state is where the ball hits the wall so the agent scores a point. \n",
+    "\n",
+    "We can show the surrounding states leading up to and following this state. Note how the Q-values are very close for the different actions, because at this point it really does not matter what the agent does as the reward is already guaranteed. But note how the Q-values decrease significantly after the ball has hit the wall and a point has been scored.\n",
+    "\n",
+    "Also note that the agent uses the Epsilon-greedy policy for taking actions, so there is a small probability that a random action is taken instead of the action with the highest Q-value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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BWTO7JVT75F3XJZfL1eXed/pCJTJVoRCiY3meh1IqmLivv7+fVCpFLBYLUi8B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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be02be160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.682 \n",
+      "FIRE        1.676 \n",
+      "RIGHT       1.685 \n",
+      "LEFT        1.691 \n",
+      "RIGHTFIRE   1.690 \n",
+      "LEFTFIRE    1.699 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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rRLtJ3d54TCrGcRwsy+Jf/uVfOH/+PA888ACf/vSn2b9//w1z13fLcGO5MlYI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\nITqcBHohhOhw/x/PY5u5EMbGGgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be02ba080>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.731 \n",
+      "FIRE        1.727 \n",
+      "RIGHT       1.734 \n",
+      "LEFT        1.734 \n",
+      "RIGHTFIRE   1.730 \n",
+      "LEFTFIRE    1.741 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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l+vDi1UBwFqghCV/AwqOCzNnEjTEkRLeLXKIH6qYdCE8UJsRizARswKpmuBSik0Uq0YcP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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01769e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.744 \n",
+      "FIRE        1.729 \n",
+      "RIGHT       1.753 \n",
+      "LEFT        1.751 \n",
+      "RIGHTFIRE   1.754 (Action Taken)\n",
+      "LEFTFIRE    1.752 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Dg4NYlkWpVGrYrpfmGm5F6M8D57XWh+vL36V2cVxWSm0FqP8db62JgrDmiG2v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\nb4n4PQoAWgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be017c208>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.782 \n",
+      "FIRE        1.776 \n",
+      "RIGHT       1.789 \n",
+      "LEFT        1.787 \n",
+      "RIGHTFIRE   1.796 (Action Taken)\n",
+      "LEFTFIRE    1.784 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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2G2UkeTsx+quBC8BfichNwCvAF4Htxphz9XXOA9tbbSwiDwMPA+zevbuNZijK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\noihdjgq9oihKl6NCryiK0uX8fz3QJsgkVBabAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0108e48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.777 \n",
+      "FIRE        1.766 \n",
+      "RIGHT       1.789 (Action Taken)\n",
+      "LEFT        1.783 \n",
+      "RIGHTFIRE   1.783 \n",
+      "LEFTFIRE    1.782 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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1j1Jqi1LqJ0qp09W/g2tVWCE2itTt+LMsC9d1sW27JvBHLzNaf1W2TtVsL8XX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\n0AshRJv7/zXc4QGRmPldAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01ce588>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.794 \n",
+      "FIRE        1.805 (Action Taken)\n",
+      "RIGHT       1.787 \n",
+      "LEFT        1.786 \n",
+      "RIGHTFIRE   1.790 \n",
+      "LEFTFIRE    1.794 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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8+uqrjI2N+XMymMJ9wtKI0AuCEDqCYZhyucxPfvITjhw5QqFQYPfu3fzyL/8y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\na8BVrfUd9c9GgO8BE8Ak8Ft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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be031d400>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.774 (Action Taken)\n",
+      "FIRE        0.768 \n",
+      "RIGHT       0.764 \n",
+      "LEFT        0.768 \n",
+      "RIGHTFIRE   0.769 \n",
+      "LEFTFIRE    0.771 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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ByOaBBx7gC1/4ArD8EJ+dnSWTyQQdJsPTiS4tLcn/u04iJ/SNf2C4YdZk4hhB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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0124e10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.817 \n",
+      "FIRE        0.828 \n",
+      "RIGHT       0.820 \n",
+      "LEFT        0.832 (Action Taken)\n",
+      "RIGHTFIRE   0.825 \n",
+      "LEFTFIRE    0.832 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(-5, 3):\n",
+    "    plot_state(idx=idx+i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Example: Highest Q-Value\n",
+    "\n",
+    "This example shows the states surrounding the one with the highest Q-values. This means that the agent has high expectation that several points will be scored in the following steps. Note that the Q-values decrease significantly after the points have been scored."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "908"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = np.argmax(q_values_max)\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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pSqVCIpGgVCpx5coVO2rW9PCjRLhHn0qlmJ6eJpfLXTeeIEzzMZvRwo7j4Hke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\nAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00c2f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        2.212 (Action Taken)\n",
+      "FIRE        2.169 \n",
+      "RIGHT       2.113 \n",
+      "LEFT        2.097 \n",
+      "RIGHTFIRE   2.161 \n",
+      "LEFTFIRE    2.157 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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PWs/ziKKICxcukM/nmZycbLqUX0mrx3Vdm/d1HIdCoUAmkyGVStkOzSQGejM6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\nTE1N3fZ7sTxKKVKpFLlcjnw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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0345898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        2.194 \n",
+      "FIRE        2.149 \n",
+      "RIGHT       2.140 \n",
+      "LEFT        2.141 \n",
+      "RIGHTFIRE   2.198 (Action Taken)\n",
+      "LEFTFIRE    2.170 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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YEu72GnePCW0zLeOoCb1pjZsBSxNmGab12n3ft9fT2usJgoCRkRF27NhBqVQi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\nemnRr45W2yyXy+RyOYaGhpo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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0080668>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        2.028 \n",
+      "FIRE        2.058 \n",
+      "RIGHT       2.083 \n",
+      "LEFT        2.100 (Action Taken)\n",
+      "RIGHTFIRE   2.095 \n",
+      "LEFTFIRE    2.084 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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y8803c//995NIJDhx4gQnTpygXC6jlCKRSAAfZN2YcIXp+ocV4436vm//9zyP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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0165cc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.979 \n",
+      "FIRE        0.992 \n",
+      "RIGHT       1.000 \n",
+      "LEFT        0.997 \n",
+      "RIGHTFIRE   1.001 (Action Taken)\n",
+      "LEFTFIRE    0.995 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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P8vd///eMjY3ZY/jDPoLQSDMe/QPAP1NKfRqIMxfH/DrQo5SKzHs+g8BIMwVc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\nQi8IgtDm/P+4HHIR/f5GqwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00f9b70>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.024 \n",
+      "FIRE        1.026 \n",
+      "RIGHT       1.013 \n",
+      "LEFT        1.027 (Action Taken)\n",
+      "RIGHTFIRE   1.040 \n",
+      "LEFTFIRE    1.022 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(0, 5):\n",
+    "    plot_state(idx=idx+i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Example: Loss of Life\n",
+    "\n",
+    "This example shows the states leading up to a loss of life for the agent."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "201"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = np.argmax(replay_memory.end_life)\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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zEuiFEKLPSY5eCLGhwmkarfWKna9i60igF0JsKBPolVL4vi+BPQIk0AshOmJZ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\nGZxRSu0CaPx7pfH+NLAv9Lm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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01bb048>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.293 (Action Taken)\n",
+      "FIRE        0.179 \n",
+      "RIGHT       0.225 \n",
+      "LEFT        0.261 \n",
+      "RIGHTFIRE   0.236 \n",
+      "LEFTFIRE    0.279 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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rpWokyHeHBHohREcFx8TLiJpwkNSNEKItSiksa+1QIkG++6RFL4Roi2nBK6XQ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\nXAR+AIw23quA/w28DZwFHpS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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01406a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.160 \n",
+      "FIRE        -0.055 \n",
+      "RIGHT       0.183 (Action Taken)\n",
+      "LEFT        -0.004 \n",
+      "RIGHTFIRE   0.082 \n",
+      "LEFTFIRE    0.259 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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1BPgukxa9EKIjSqkNO1slwMeDBHohRMfaA7204uNFAr0QQvQ5CfRCCNHnJNAL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\ncxLohRCiz0mgF0KIPvf/AV8tjERJmt71AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00b1f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.157 (Action Taken)\n",
+      "FIRE        -0.030 \n",
+      "RIGHT       0.069 \n",
+      "LEFT        -0.042 \n",
+      "RIGHTFIRE   0.093 \n",
+      "LEFTFIRE    0.103 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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lNXql1KbRBB8PmuiVUh1rH1Gjtfh40USvlFJ9ThO9Ukr1OU30SqlV0xOfepMm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\nAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0180160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.047 \n",
+      "FIRE        -0.058 \n",
+      "RIGHT       -0.008 \n",
+      "LEFT        -0.001 \n",
+      "RIGHTFIRE   -0.027 \n",
+      "LEFTFIRE    0.052 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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MxpgelUZ10kCvlFJ9TgO9Ukr1OQ30SinV5zTQK6XWbLWRNJqPTzav1wVQSiWX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\nqT6ngV4ppfqcBnqllOpzGuiVUqrP/X9MSpiQ8i+IpQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be02ca9e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.066 \n",
+      "FIRE        -0.018 \n",
+      "RIGHT       0.007 (Action Taken)\n",
+      "LEFT        0.056 \n",
+      "RIGHTFIRE   -0.016 \n",
+      "LEFTFIRE    0.112 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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olVKqx2nQK6VUj9OgV0pt2Hp98caYXS6J2gwNeqXUhuiAa/fyOl0ApVSyacB3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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0304208>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.013 \n",
+      "FIRE        0.044 \n",
+      "RIGHT       0.089 \n",
+      "LEFT        -0.120 \n",
+      "RIGHTFIRE   0.029 \n",
+      "LEFTFIRE    0.115 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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RK6XUgNNEr5RSA04TvVJq3USk10VQm6CJXim1Lprk+5fX6wIopeJNE3z/0xq9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\nTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00b8588>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        -0.117 \n",
+      "FIRE        0.109 \n",
+      "RIGHT       0.040 \n",
+      "LEFT        -0.123 \n",
+      "RIGHTFIRE   -0.003 \n",
+      "LEFTFIRE    0.116 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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NeqWU6nMa9Eop1ec06JVStyQi3S6C6pAGvVLqtjTse5sGvVJK9TkNeqWU6nMa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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be035b940>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.168 \n",
+      "FIRE        0.004 \n",
+      "RIGHT       -0.061 \n",
+      "LEFT        0.089 \n",
+      "RIGHTFIRE   -0.060 \n",
+      "LEFTFIRE    0.273 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0218748>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.096 \n",
+      "FIRE        0.034 \n",
+      "RIGHT       -0.001 \n",
+      "LEFT        -0.031 \n",
+      "RIGHTFIRE   -0.153 \n",
+      "LEFTFIRE    0.247 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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STgO9UkolnAZ6pZRKOA30SimVcBrolVIq4TTQK6VUwmmgV0qphNNAr5RSCaeB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\nAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0326860>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.018 \n",
+      "FIRE        0.080 \n",
+      "RIGHT       -0.099 \n",
+      "LEFT        0.073 \n",
+      "RIGHTFIRE   -0.089 \n",
+      "LEFTFIRE    0.395 (Action Taken)\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(-10, 0):\n",
+    "    plot_state(idx=idx+i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Example: Greatest Difference in Q-Values\n",
+    "\n",
+    "This example shows the state where there is the greatest difference in Q-values, which means that the agent believes one action will be much more beneficial than another. But because the agent uses the Epsilon-greedy policy, it sometimes selects a random action instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "730"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = np.argmax(q_values_dif)\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mrPFE0+k01WqVubk5O2s2iYIS9+iz2SxLS0sUi8VbJpbFaf3OZlDThEKuXl1L\n/w6CwI5X5HI5FhcXKZVKNqMlPrnMsLy8zNWrV1FKUa1WdyxGb8pY5HI5KpUKhUJB4vCCsE16Xujj\nA7bxATzf95mZmeH8+fMMDAzYdL4kDcYaTLs8z6NSqTAzM2O/13orSsW/czzfPYoiFhYWePvtt+0F\nzoxLmHGK2dlZG+KK9xesTV77+c9/bnPwTehmJ0InZhDZ1Lp5//33m0Jve6lGkSB0m54X+jhxcYii\niJmZGVss7U5L8CUBEz9fXV1t8m5vJ3qt32thYcFm1Jg0RRN+qdfrrKysNKWzxrN6isUi7733nvXo\nd0NszQS4UqnUNN4gQi8Im6evhL6VcrlMuVzudjN2lWq12pSmuBXCMLQzU7tN0i/KgpAkkhenEARB\nEDqKCL0gCEKP09ehm50aSNxp2h1PuN33vtO+u9Vne2EMRRCSSl8Lfb+KRzvfu1/7bKdJ2tKNQm8h\noRtBEIQeR4ReEAShxxGhFwRB6HFE6AUhAUh8XthJROgFQRB6HBF6QUggezHtV0guIvSCIAg9jgi9\nIAhCjyNCLwgJRcI3Qqfo65mxgpBUTBaOEXvJyhHaQTx6QRCEHkeEXhD2ABLGEdpBhF4Q9gBmbV4R\nfGE7iNALQoKR2LzQCUToBUEQehzJuhGEhBP36sXDF7aDCL0g7AFE4IV2aCt0o5QaUUp9Syn1tlLq\nklLqU0qpMaXUD5RS7zb+jnaqsYKwWyTZts1yjnt1KUxh92k3Rv9V4LTW+qPAx4FLwJeBH2qtTwA/\nbDwXhL1GYm3bZOBIFo6wWbYt9EqpYeAp4GsAWmtfa70M/Bbw9cZmXwc+324jBWE32Qu2Ld68sBXa\n8ejvBeaBf6+U+qlS6t8qpQaAg1rrmcY2s8DB9T6slHpOKXVOKXXuxo0bbTRDEDpOx2x7JxpnFmiP\nokhi98KmaEfoPeAU8Kda618GSrTcyuo1K1zXErXWz2utH9VaPzoxMdFGMwSh43TMtneicVprwjAk\niiIAG8YRhI1oxzqmgWmt9dnG82+xdnLMKaUOAzT+Xm+viYKw6+wp25ZYvXAnti30WutZ4IpS6mTj\npWeBt4AXgC82Xvsi8O22WigIu8xetG0J4Qi3o908+v8B+IZSKg1cBv471i4e/1Ep9SXgA+D32zyG\nIHSDPWPbWms7OCuCL6xHW0KvtT4PrBeHfLad/QpCt9lrtm3i9PHYvSAYZGasIOxhTAYO0DQgK2Iv\nxBGhF4R653T1AAASTElEQVQ9jhF1pRSu6+I4DkEQEIZhl1smJAXJyRKEHiCKIoIgsPF6SbcU4og1\nCEKPEEWRePHCuojQC0IP0bqouCCACL0g9BRG4CXNUogjg7GC0EOYWH3rAK0pmyD0JyL0gtBDRFHU\nlFqZSqVwXVeycPocCd0IQo8j8XpBhF4QBKHHkdCNIPQwZlA2lUrZKpdaa+r1usye7SNE6AWhhzEl\nElzXxfM8Ww9HauL0FyL0gtDDBEFg/3dd18br43F7qXrZ+4jQC0KPEwQBjuNYMTfLEBpE5HsfGYwV\nhD7A1L+R1aj6E/HoBaEP0FrbiVRRFDV5+CBljXsdEXpB6AOMyJvqlqlUinw+j1KKer1OpVIRse9h\nROgFoQ9onTGbzWbJZrM2jFOr1UToexiJ0QtCH2IGZE36pcTtexsRekHoA1rTKc3DEK+DI6Lfe4jQ\nC0KfstFKVCL0vYfE6AWhD4hn2JgMnGq1Cqx58+l0mnq9LjNmexQRekHoQ3zfp1arobUmnU4zNDRE\nFEUUCoWmWvYymao3EKEXhD4k7rVHUUQqlSKdTqOUolgsUq/XReR7CInRC0Kfo7XG930cx2F0dJTR\n0VE876YPKDH7vY8IvSD0MUopoihidXWVcrmMUopMJtM0SLvegK2wt5BfUBD6GBOH932f1dXVdUM2\nEsLZ+4jQC4IArGXfmMXE4+EaycLZ+4jQC4IAYAudmRmzBonR733aEnql1P+klHpTKfUzpdR/UEpl\nlVL3KqXOKqXeU0r9uVIq3anGCsJu0S+2HffWwzCkUCiwuLiI7/uk02kOHDjA2NiYxOn3ONv+9ZRS\nR4D/EXhUa/0xwAX+APgj4I+11vcBS8CXOtFQQdgt+tW26/U6hUKBUqkEwNDQEAcOHGB4eFgGZ/c4\n7f5iHpBTSnlAHpgBngG+1Xj/68Dn2zyGIHSDvrNtU+DMYEokxEM3ZvESYW+x7V9Ma30V+L+BD1k7\nCQrAa8Cy1tosVDkNHFnv80qp55RS55RS527cuLHdZghCx+mkbe9GeztFa+2bKIoIw/CWBUriBdCE\nvUE7oZtR4LeAe4G7gAHg1zf7ea3181rrR7XWj05MTGy3GYLQcTpp2zvUxB2jtcql53lNk6dA0i33\nIu3cg/0qMKW1ntda14G/AJ4ARhq3uwBHgatttlEQdpu+te3WwdlqtUqlUrHink6nSaf3/Bh039GO\n0H8IfFIplVdrbsCzwFvAj4HfbWzzReDb7TVREHadvrTt1hh9pVJhdnaWmZkZwjBkYmKC++67jwMH\nDjR9TtIvk087MfqzrA1MvQ5cbOzreeBfAP9UKfUeMA58rQPtFIRdQ2x7Dd/3KRQKBMHasMTw8DAH\nDhxgcHDQbuM4Dq7rdquJwiZpq3ql1vpfAv+y5eXLwGPt7FcQuo3Y9q2EYUgQBE1ef2tWjpBMpEyx\nIAjrYjJwWrNs4sJuvH0h2UhCrCAIm8bzPAnV7EFE6AVBWJfWnPlarcaNGzdYXFwEsCUShoaGutVE\nYZNI6EYQhHVpzZdfWlqiUChQLpcBOHHiBHfddRdTU1MUi0VgLaxjatwLyUE8ekEQNkW1WrUiD2tZ\nOKOjo2SzWftaOp2W0E4CEaEXBGFTtAq47/v4vt80INta4lhIBhK6EQRhU5gFSeLC7nle00zZer3e\njaYJd0A8ekEQNsV6Bc3MQiVCshGPXhCETdEalrlx4wbVapXp6WkAjh49ysTEBNevX+fatWvdaqaw\nDiL0giBsilbPfWZmhlqtBkAul+ORRx7hwIEDvPzyy1boPc8jiiLx+ruMhG4EQdgWvu/b/13XZWho\niEwmY1eoAhgcHCSVSnWjeUIMEXpBELZFXMDDMKRUKlGv15uKnq2urkqZhAQgQi8IwraILysYRRHV\napWJiQk+85nP8PDDDwNrtXDCMJT8+i4jMXpBELZFvV63sfcwDJmfnycMQx577DEOHjwIwPnz54Fb\na90Lu0uihN5MnxaErbKe3SilRFx2kHiqZRAEXLhwAc/zGBkZ4eGHH+bAgQP81V/9FT/60Y9YWVkB\n5DfpFokS+vWu+r1oFNu9mPViX3SKuO2Y/yXH+1aMM9UJhyoMQxzHIZVKUavV8H2fc+fOMTQ0xJEj\nR3j22WcZHh5mamqKN954A1gbnDXbxkM5t/utTFvN77vZtsv5cpPECH0URbfE8Hrxh2r3JOvFPtkJ\nJFSwPmax7+0sGKK1vqUWvRHnTCaDUopqtcrf/u3fcujQIT7ykY8wPj7O6Oio/Uwmk7GrUsXbUK/X\nqdfrtxyj3QtS/KLfzyRG6M2P3voj91ooR4xuZ4jbilIK13XtlH3hJkZQd4JMJgOsrTX74osv8vjj\njzM8PMz8/LzdZnl5+Y5ZOHJ+dJ5EZN3EbyeVUnYkvxeFXtgZjLgD1mMVsb+JOad2EjN5CtZKGtdq\nNWq1mq1fD7IiVbdIhEevtbYDO/FZdL02o04pZVfo2cqglNk2CAI5UTYgiiLbNyalz4QC+tlDNLYT\nRRFKKcbHxxkbGyObzW47dGP2WSqVbO58LpdjfHycarVKoVDg8ccf56Mf/Si5XI5f/dVf5Tvf+Q6e\n53Hw4EFSqZRtj+u6RFHEwsIC8/PzBEGA53n2GPEVrbbzO5p1bs1at+2Mj8W1qFNO6O2+k+mDTthv\nYoS+Xq8TBAG+7xOGIfl8nlqttueFLS7omUyGI0eOcPDgQRzHsd/NcZxbLmjx1zzPIwgCZmZmuHbt\nmr31lgyGNbTWVmBc12VlZYUgCMhkMusW4uonUqmUncGaSqX4zGc+w+c//3nuvfdeXNdFa43jOE0i\n2GpT8Ti653nk83nK5TJvvfUWr7/+OktLS9x999184hOf4J577rHHOnToEENDQxw7dozf/u3fZmpq\niqGhIU6ePMnAwAD1ep3h4WGq1Sp/+Zd/yZ/92Z+xsLDA+Pg4rusShiHDw8Ps27cPuJnls5HAtgp5\nGIasrq6ysLBAoVCw44DxhVFuty+4eSfk+z6VSsW+bqp2bmZfrfuM93O8flDr+Rx38Nq14UQIvZlV\n5zgOvu/jeR6ZTIZyuWy9sr2K67pW0PP5PKdOneKxxx6z3894Let9xyAIcF2XfD5PsVjkpZde4saN\nG1bo4/vuN+L9FYYhhUKBmZkZyuUyhULBTtKJoqivS+fGQzau6zI5OclTTz3F0aNH29732NgYlUqF\nubk5Tp48ydNPP83Y2Jh933jnk5OTTE5OMjc3h+d5jI+P37Kvqakpvvvd71IsFtm3bx+e5+H7PuPj\n43b7MAzthWk9WoXe931SqRTVapVKpUIQBKRSqTuugBUX3I0WSHddt+nOYzt3C+auZiOhN85eJxyV\nRAi98eiVUvi+TxRF+L5vvfz4l99roh83ymw2y8mTJ/n0pz9NPp9nZWUFrTWpVGpdL8pc9Pbt28eN\nGze4du0aP/nJT9bdd78R768oiqhUKiwvLxNFESsrK01C388efRxz52Ny2ttlZWWFSqViV54qFApW\n6I0nGp89ayZRwdpvFrff1dVVK+RBEFgxjg8eG6dms4JqPGHjNcdDWLfTkc2ES9ZL590q8YygeJvi\nzzuld4kR+mq12iRu5XKZSqW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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00c2128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        1.219 (Action Taken)\n",
+      "FIRE        0.195 \n",
+      "RIGHT       -0.083 \n",
+      "LEFT        0.199 \n",
+      "RIGHTFIRE   0.455 \n",
+      "LEFTFIRE    0.990 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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SBSXu0WezWebn5ymVSrcMLIvTecymU9OEQq5cWU7/DoLA9lfkcjnm5uaoVCo2\noyU+uMywsLDAlStXUEpRr9e3LEZvyljkcjlqtRqLi4sShxeEDdL3Qh/vsI134Pm+z/T0NCdPnqRQ\nKNh0viR1xhpMuzzPo1arMT09bY9rpRml4sccz3ePoojZ2VnOnDljb3CmX8L0U8zMzNgQV/x8wfLg\ntffff9/m4JvQzVaETkwnsql1c+HChbbQ206qUSQIvabvhT5OXByiKGJ6etoWS7vTFHxJwMTPy+Vy\nm3d7O9HrPK7Z2VmbUWPSFE34pdlssrS01JbOGs/qKZVKnD171nr02yG2ZgBcpVJp628QoReEtTNQ\nQt9JtVqlWq32uhnbSr1eb0tTXA9hGNqRqb0m6TdlQUgSyYtTCIIgCJuKCL0gCEKfM9Chm63qSNxq\nuu1PuN1x32nbvTpnO6EPRRCSykAL/aCKRzfHPajnTBB2MhK6EQRB6HNE6AVBEPocEXpBEIQ+R4Re\nEAShzxGhFwRB6HNE6AUhgezEtF8huYjQC4Ig9Dki9IIgCH2OCL0gJBQJ3wibxUCPjBWEpGJGHxux\nl9HIQjeIRy8IgtDniNALgiD0OSL0grBDkJi9sFFE6AUhwZhqoUbkReyFjSBCLwg7COmUFTaCZN0I\nwg5ABF7oBvHoBUEQ+pyuhF4pNaqU+pZS6oxS6rRS6pNKqV1Kqe8ppT5o/R3brMYKwnaRdNveqdNg\nCr2hW4/+q8BxrfWDwCPAaeDLwPe11oeB77c+C8JOI7G2bURexF5YKxsWeqXUCPA08DUArbWvtV4A\nfg34emu1rwO/3m0jBWE7EdsW+o1uPPr7gBvAf1dK/UQp9V+VUgVgj9Z6urXODLBnpR8rpZ5TSp1Q\nSp24efNmF80QhE1n02x7KxspHbTCWulG6D3gGPCHWutPABU6HmX1siWuaI1a6+e11o9rrR+fmJjo\nohmCsOlsmm1vReO01kRRZIXecRwJ4Qi3pRuhnwKmtNavtj5/i+WL45pSah9A6+/17pooCNvOjrJt\nidULd2LDQq+1ngEuK6WOtBZ9BjgFvAB8sbXsi8C3u2qhIGwzYttCv9HtgKm/B3xDKZUGzgF/m+Wb\nx/9USn0JuAj8dpf7EIResGNsO17SWOL2wkp0JfRa65PASnHIz3SzXUHoNTvFtk0dHPOKx+4FwSAj\nYwVhhxP36KVjVlgJEXpB2OGYLBxYzsDxPA/HkUtb+AixBkHoA7TWhGEISBaOcCsi9ILQJ8Q9exF6\nIY4IvSDMX9r8AAARZUlEQVT0EdIRK6yECL0g9BHiyQsrIROPCEIfYWL18RCO4zhtYR1h8BChF4Q+\nolPMXdfFdd028RcGDwndCEIfIxk4AojQC0JfI52zAkjoRhAGAtd12zx7CeUMFiL0gtDHaK3RWuM4\njhX7KIpE5AcMCd0IQh8ThiFBEBBFkcTrBxgRekHoc8IwJAxDG683Xr4wOIjQC8KAEC9nLAwWEqMX\nhAHB1KpfKYwjHn5/I0IvCANAFEU0Gg1g2bP3PA/P81BKEQQBvu9LB20fI0IvCANAp4inUinS6bT1\n6pvNZi+aJWwTIvSCMKDEO2eF/kY6YwVhwFipMzbu8Utnbf8hQi8IA4hk4AwWEroRhAHDlDL2fR9Y\n9uZTqZQdWCWhnP5DhF4QBpAgCGg2m2itSaVS5HI5tNaUy2Ur9EopEf0+QYReEAaQeEw+iiI8zyOV\nSqGUolKptI2kFXY+EqMXhAFHa00QBDiOQ7FYZGhoCNd1e90sYRMRoReEASeKIqrVKrVaDaWU9ewN\njiMysdOR/6AgDDBG0IMgoFarEQTBLetICGfnI0IvCALwUdzecRypg9NniNALggAsC7wpehYXd8m1\n3/l0JfRKqX+olHpXKfVTpdT/UEpllVL3KaVeVUqdVUr9sVIqvVmNFYTtYlBsOy7oYRhSrVYplUoE\nQUAqlWJ0dJShoSER+x3OhoVeKbUf+PvA41rrjwMu8DvA7wG/r7W+H5gHvrQZDRWE7WJQbTsIAiqV\nCvV6HYBcLsfo6CjFYrGtQ1Y6Z3ce3f7HPCCnlPKAPDANPAt8q/X914Ff73IfgtALBtK2O0M2nWmW\nUjZhZ7JhoddaXwH+PXCJ5YtgEXgDWNBam677KWD/Sr9XSj2nlDqhlDpx8+bNjTZDEDadzbTt7Wjv\nZqGUavPWoygiDMO2dUwMX9hZdBO6GQN+DbgPuAsoAL+01t9rrZ/XWj+utX58YmJio80QhE1nM217\ni5q4LRiPvjNUI1k4O49uQje/AJzXWt/QWjeBPwWeBEZbj7sAB4ArXbZRELabgbTtzknDoyjC9318\n37fLTakEYWfRjdBfAp5QSuXVctDuM8Ap4AfAb7bW+SLw7e6aKAjbzsDadlzoG40Gc3NzzM7OEkUR\nIyMj7N+/n9HR0bbfSMw++XQTo3+V5Y6pN4F3Wtt6HvhnwD9SSp0FxoGvbUI7BWHbENteptls2gJn\nAIVCgbGxMXK5nF2nM64vJJOuqldqrf8l8C87Fp8Dfq6b7QpCrxHbvrVM8UqDqUTkdwZSplgQhBUx\n3rrx6I3Qx0M1nVk5QjKR27EgCKvSmVfveZ548TsQ+Y8JgrAinTnzjUaDpaUlSqUSgC2RkM/ne9VE\nYY1I6EYQhBXpzJcvl8tUKhUajQYA+/fvZ3x8nJmZGarVql1PpiBMHuLRC4KwJnzftyIPy1k4w8PD\nbXn1qVRKQjsJRP4jgiCsiU4Bj08wbhBPPplI6EYQhDVhJiQxmTamREK88NlKM1QJvUc8ekEQ1sRK\nBc2kyNnOQDx6QRDWROdgqYWFBXzfx1SfnZycZGRkhPn5eWZnZ3vVTGEFxKMXBGFNdMbfZ2dnOXfu\nHOVymUwmwwMPPMCDDz7I0NCQXWel6pfC9iP/AUEQNkSz2bTvHcchn8/jeR61Ws0uz+Vyt0xeImw/\nIvSCIGyIeFplFEXUajXCMGwremaWCb1FhF4QhA0Rn1YwiiKazSYjIyN84hOf4P777weWa+FEUSSl\nE3qMdMYKgrAhgiCwcfsoilhYWCAMQx588EFbs/7s2bN2fcmx7x2JEnqZeFjYKCvZjQzF31riaZVh\nGPLhhx/iui7FYpHDhw8zOjrKa6+9xptvvtkWtxe2n0QJfedUZmaZ8BEbuREOwjmM2455Lznet2Ls\nZzMcKlOy2PM8ms0mQRDw/vvvk8/n2b17N48//jhDQ0Ncu3bNevaFQgHf92k2m5vWSRv/fwsrkxih\nj6Loln+8/OM+YiNPO3GPdtDOpVz4K+M4Dp7nbcietNa31KI35zmVSuG6Lr7vc+rUKSYmJrj77rsZ\nGxtjeHjY7ttk4Xiet2GhN/9XcwymFEMYhnZZZ1mGQbeFxAi9GV4dNyQJ5XyEGOvtidtKfGi+2E87\nYRhuWRZMFEVEUUS1WuXll1/mgQceoFAo2AFVURTZ91uFXCMrkwihNxepeZneeRF6Ya0YcQfwPI8g\nCKzQiw1tT39F/AZSrVapVqsopZibm9vS/Qp3JhFCr7W2RmK8gs73g0zcQzU3wTtdtEbczLk1aW79\nShRFtqBWEASEYWgrKw6yl2cE3oRdhoeHGR4eJp1Or3tbZhtmm41Gg1qthu/75PN5Jicn0VpTqVQ4\nevQox44dI5VK8Qu/8AucOHGCfD7P6Ogovu/bG/FGjsfYseM4uK7L4uIiN2/epFqt2jTOeB/NZjzF\nrGRHK4WJtoLN2H5ihN505vi+TxiG5PN5Go2GVMMDMpkMu3btYnJy0g4vj58Xx3GIosj+BeyNodFo\nMD8/z40bN1hcXOxLsddaU6/XWVxcxHVdlpaWCIKATCZjL/RBxXVdayuu6/Loo4/y1FNPsXfvXjzP\ns+LdGX9fCSPOmUwG3/e5dOkSZ86cYXZ2loMHD/LZz36Whx9+GFj+n0xMTJBOp3niiSdYWFjA8zy7\nz42Il3naNxoxOjpKJpPhlVde4Y/+6I84deoUIyMjDA0N0Wg08H0f3/dZWlqiXC7bfsD4zWK1Y473\nA5hj933fLjd9DBsR+rgTdrvfmm0HQdD1dZsIoQ/DkEqlYv+JnueRyWSoVqu31LseBOKGAMuZCocP\nH+bYsWPce++9uK5LtVolDEM8z2v7nfHcM5kM2WyWhYUFTp06xRtvvEGlUsH3fYC2m8JOJG4TYRiy\nuLjI9PQ01WqVxcVFwjAknU7bgTyDSnyQkuM47N27l0ceeYRDhw7dIvTGE+4kLjiu65LL5ajX64yO\njlKr1UilUnzsYx/jySef5L777rvl97t3797SY1RK8cMf/pCLFy8yOjrK2NgY9Xqder1unzgajQZh\nGK5b6Fd7gjZP2d0K/e2uwbXegNdCIoTeePRKKXzfJ4oim4IVH5Rh1u13Oo0nl8tx4MABjh07xqOP\nPornedZrTaVSbRdqs9kkiiLy+TyFQoGZmRmiKOLChQtcvHixbR87mfj5McPvFxYWiKKIpaWlNqEf\nZI++E9/3qVQqlEolXNdtE/hOB8MQ92rNE0KtVrPTCjabTer1OktLS/Y35gabyWS25DiCILBOztLS\nkhXyIAjaXsbxWS0FczU96cxWu5PurEeQV9p2/Le3+19slMQIfb1et0LveR7VapVarTaQHn0nJs7u\n+76NQ9ZqNWvIZh3HcewyEz+s1+tt6/ULndlZruuSTqftK4oiUqnUpnlE/YKJa5vQg7EbE/pbzaOH\nZRszvzW/Nx6v4zhttW8cx9kykQfanmRNXL4zqaObMQPbaTPbsa9ECL0ZdGEeqTzPI5VKDWx9jE7P\no1qtcv78eX784x9z8eJFXNelVqutOPbAeC9G8JaWljh79iw3btxoi+vv5LBNJ0opUqkUuVyOfD5v\nn2qM4A+iDa2G67qkUinS6bQV+rWEbsxfc0M1YcO48G+kg3czMMdi2hjP3lstZbszBt9J5/d3EuON\n3kxud743ut2VSITQu67L6OhoW4x+dHQUrTX5fL7tQh0E76zzn1+pVPjwww+ZnZ0ln8/bQSJw6/mI\nG6jrujSbTUqlkq1Dsto+dhqdMfqFhQWmpqZYXFykVCq1efSmX2IQid/QTQjv5Zdf5vTp020hm7U8\n+YRhiOM4pNNpms0m09PTnDt3jvn5eZrNJvl8nqNHj6KUolwuo7W2DtxmYcKTYRja7KE333yTDz/8\nkFKpBCw7Riazx/d9yuWyvfmb0bxrtf942KozXBgEQddZN2vpjO2brBtzoSql7NBorTULCwvUarWB\ni9F34vs+s7OzzM/Pryt2FzeUfkszjAtYo9Hggw8+IJvNks1mrc0YOzICMIjEn+KCIODkyZOcPn26\nq/IDxq5MCmsURZw6dYof/vCHNnyzVbbW6Y2bcG+1WiUIAmZnZ2/Jaom/NnrT6TyerRx4thUkQuhn\nZ2f5xje+AXzkNeRyOarVKidOnKBardp1d9LJ3UziYw2EdqGv1+ucOXOGa9eu2XhzPGQT7yQcVIxA\nmpTDzcaIbdLpJ2dnPagkHHgqldLj4+PArYMyqtUqlUqlr2LKwuZzuxGwrX6LnsT8lFK9v8CEvmYt\ntn1HoVdK/Tfg88B1rfXHW8t2AX8MHAQuAL+ttZ5Xy1faV4HPAVXgb2mt37xjI+RiuCOdmQSwekrX\nSulZg36jXOliGETbNp2nm9FBbVJXTUduN4XK1kvcIVypqJlZx/xNgkO7VazJiVkpjtUR030aOAb8\nNLbs3wFfbr3/MvB7rfefA/4PoIAngFfvtP3W77S85LWVL7FtefXra012uEZjPUj7xfAesK/1fh/w\nXuv9fwG+sNJ6t3sppXQ6nW57ZTIZnU6nteu6PT+R8kr+SymlXddd8QWrXwxssW33+rzIq/9fa9Hw\njXbG7tFaT7fezwB7Wu/3A5dj6021lk3TgVLqOeA583mQU+CE7tGb11m96bYtCL2m66wbrbXeSBxS\na/088DwkL44pCCC2LfQPG+2RuaaU2gfQ+nu9tfwKcHdsvQOtZYKwUxDbFvqOjQr9C8AXW++/CHw7\ntvxvqmWeABZjj8GCsBMQ2xb6jzV0Jv0PluOQTZbjkl8CxoHvAx8A/xfY1VpXAf8J+BB4B3hcMhPk\nlYSX2La8+vW1FjtMxIApiWMKW42WAVNCn7IW25ayfoIgCH2OCL0gCEKfI0IvCILQ5ySieiVwE6i0\n/iaNCaRd6yGJ7bq3h/sW214/0q61sybbTkRnLIBS6oTW+vFet6MTadf6SGq7eklSz4m0a30ktV1r\nQUI3giAIfY4IvSAIQp+TJKF/vtcNWAVp1/pIart6SVLPibRrfSS1XXckMTF6QRAEYWtIkkcvCIIg\nbAGJEHql1C8ppd5TSp1VSn25h+24Wyn1A6XUKaXUu0qp320t36WU+p5S6oPW37EetM1VSv1EKfVi\n6/N9SqlXW+fsj5VS6e1uU6sdo0qpbymlziilTiulPpmE85UExK7X3L7E2Xa/2XXPhV4p5bJcLOqX\ngYeALyilHupRcwLgH2utH2J5uri/02rLl4Hva60Ps1zwqhcX7e8Cp2Offw/4fa31/cA8ywW5esFX\ngeNa6weBR1huYxLOV08Ru14XSbTt/rLrtVQ+28oX8Engu7HPXwG+0ut2tdrybeCzrDK93Da24wDL\nhvUs8CLLlRRvAt5K53Ab2zUCnKfV1xNb3tPzlYSX2PWa25I42+5Hu+65R8/qU7T1FKXUQeATwKus\nPr3cdvEfgX8KRK3P48CC1jpofe7VObsPuAH899aj939VShXo/flKAmLXayOJtt13dp0EoU8cSqki\n8CfAP9BaL8W/08u3821LVVJKfR64rrV+Y7v2uQ484Bjwh1rrT7A81L/tcXa7z5ewOkmy61Z7kmrb\nfWfXSRD6RE3RppRKsXwxfENr/aetxatNL7cdPAn8qlLqAvBNlh9xvwqMKqVMraJenbMpYEpr/Wrr\n87dYvkB6eb6Sgtj1nUmqbfedXSdB6F8HDrd62tPA77A8bdu2o5RSwNeA01rr/xD7arXp5bYcrfVX\ntNYHtNYHWT43f6G1/uvAD4Df7EWbYm2bAS4rpY60Fn0GOEUPz1eCELu+A0m17b606153ErQ6Nj4H\nvM/yNG3/oofteIrlx7G3gZOt1+dYZXq5HrTv08CLrfeHgNeAs8D/AjI9atOjwInWOfvfwFhSzlev\nX2LX62pjomy73+xaRsYKgiD0OUkI3QiCIAhbiAi9IAhCnyNCLwiC0OeI0AuCIPQ5IvSCIAh9jgi9\nIAhCnyNCLwiC0OeI0AuCIPQ5/x+5Swy7yR87GQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00f69b0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.608 (Action Taken)\n",
+      "FIRE        0.085 \n",
+      "RIGHT       -0.416 \n",
+      "LEFT        0.350 \n",
+      "RIGHTFIRE   0.517 \n",
+      "LEFTFIRE    0.358 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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jKChRjz6dTrOwsEChULhhYFmU9ms2nZomFDI5uZL+7fu+7a/IZDLMz89TKpVs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\nf91girH5mSJ2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be017bb00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.071 \n",
+      "FIRE        -0.186 \n",
+      "RIGHT       -0.509 \n",
+      "LEFT        0.225 (Action Taken)\n",
+      "RIGHTFIRE   0.152 \n",
+      "LEFTFIRE    -0.182 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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qNoqCEvboU6kUCwsL5PP5WwaWhWm9ZtOpaUIhk5Mr6d/1et32V6TTaebn5ykW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\nIvSCIAg9jgi9IAhCj/P/AZzEAaq5lwplAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be003e048>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.050 \n",
+      "FIRE        -0.050 \n",
+      "RIGHT       -0.196 \n",
+      "LEFT        0.108 \n",
+      "RIGHTFIRE   0.177 (Action Taken)\n",
+      "LEFTFIRE    -0.285 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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aUbNJFJS4R5/NZllYWKBUKt0wsCxO+zWbTk0TCrl8eTX9OwgC21+Ry+WYn5+n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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0049128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.134 \n",
+      "FIRE        -0.051 \n",
+      "RIGHT       -0.145 \n",
+      "LEFT        0.155 \n",
+      "RIGHTFIRE   0.300 (Action Taken)\n",
+      "LEFTFIRE    -0.286 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(0, 5):\n",
+    "    plot_state(idx=idx+i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Example: Smallest Difference in Q-Values\n",
+    "\n",
+    "This example shows the state where there is the smallest difference in Q-values, which means that the agent believes it does not really matter which action it selects, as they all have roughly the same expectations for future rewards.\n",
+    "\n",
+    "The Neural Network estimates these Q-values and they are not precise. The differences in Q-values may be so small that they fall within the error-range of the estimates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "373"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = np.argmin(q_values_dif)\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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CXAIl9DDXO7158yZvv/02ly5dorOz045lYjxdf4/I+tb4TCbDhQsXeO+990JR\n3TPhp6mpqRrvdiHRq//do6OjlEolG6MP+jUxsdjp6ema9gYR+uBias3mGTV25rc147hEIhFSqZS9\nz36RN2it7UveZOSYNNyN5rS1ikALvdaayclJBgcHmZmZsa3w/jS7hSiVSoyMjKxVUTck+Xx+ydcv\nyAT9BbWZaZT+WN9WZLYpl8s1GTT1+/mHP5jPbjeCw9JqAif0jfDfxPq8cUEQgk13dzfd3d1UKhWG\nh4dtb20zpPTY2Bj5fJ5oNLqs57tRRz8T8pX2nFoCL/SmEdK/LGIvCMHECLgJ2bS3t7Njxw527txp\nBXlqasoOa1IsFpmYmEBrXdOL27CYp+4PC5lzm17wwm0CJ/T1N9rfMGticvWdLBY7XtjieM1WVTfi\nNZHqeXDxD5gXiUTYuXMnXV1d9p51dHQQj8eB2fTeSCTC1NQUN27cmHNfl3OPK5WKnXAHbrcNSPvN\nXAIn9I0ySIwHXz/GyVKPJwJRi1wTYTXxzwAXiUTo7e3lx37sx1BKMTw8zNjYGNeuXbMT4Rgnw/Rg\nXyla6zm1e0mzbEzghF4QhI3BYuPEmyEshoaGGB8ftz3b68W5fsyblWKcwIX6lWxWbz/wQr8RwwyC\nEEb8z6IRVaUU6XQaz/OYmZnB8zw7lSPMjlU1NjZWkyvvP16j1MuVMt9xTEhnM8ftAy/0giAEBzOc\niEl1dByHgwcP0tHRwTvvvMPNmzfxPI9UKmXz5IPgqG12h1GEXhCEeTGDiJme5fUTADmOw969e+nv\n72d0dJSbN28yMjLC8PCwHUnWL7CRSMTG0dcrlj5fjv5mQoReEIR58c837J/4pR7Xde0w4oODgxw/\nfhyYHSrceP+tGpNmodi9+X/YEaEXBKEGMwWnmXPZCHwikaCnp4dyucyNGzeAWZG8fPky2Wy2phf6\n0NDQnOO2Mhum0bnr2xzCjAi9IAhzMJ2P/A2Yd999Nx/72Md49913efHFF4FZAb1w4QLnzp3bsENr\n+EfXhHCKvgi9IAjA7SF/y+UynucRjUY5dOiQHfX1p37qp/jIRz5i53uAWaEfHx+3y/WiGeSURjOi\npv8T1LI2iwi9IAjA7YZXk+e+e/duPvvZz7Jv3z4ymQzxeJx8Ps/o6GjNfv5hSYIs7PWYuH3Q5kxe\nC0ToF8E/CYr0uhPChFLKTslpxp0BSKVSHDp0iMcee4xHH32UAwcOkM1m+eY3v8kLL7zA66+/bo/h\nH2NmvbO1hi4oAAARXElEQVRpVgsz3wOEd1RUEfpF8HfoCKsRCJsTrTWFQoFUKmWnbAQ4evQov/d7\nv8ehQ4e4evUq586dw3EcTp8+zTe+8Q07dEE8HqdQKNjQzkZ+PhrVQvyNtRv9+RehXwIbpSoqCEvF\nH24x8zwY7rrrLh544AEAnnvuOV577TV27tzJhQsX5h2fZiOL4GZAhH4RTLUUZgdMEtEXwkD9cADG\nxgE7EciPfvQj/vIv/5LTp08Ds+PK+/E3ygrBRoS+Aa7r2gdh69atHDx4kEQiwblz5xgcHLTbyDyV\nwkbDTMWptWbr1q088sgjbNmyhe9+97ucP38egPPnz/M7v/M7XLt2zYo8zE5Daaag9E/rGFZWOnxy\nEBGhb4A/f7inp4ef+ZmfoaOjg1wuVyP0Gz1uJ2wulFKkUinb6HrnnXfy27/922zbto0nn3zSCv3F\nixf5wz/8w5rJ2A2N1oWZ+Z5vf+x+IyBC34D62ep37drF1q1baW9vt+tlYmJho+EPQ8KsbR86dAiA\nrq4uu96fgeO6Lul0mlKpVDO362ZmIz73IvQN8L+lp6enuXz5MiMjIzUNURK2ETYa9SGXqakp3nrr\nLfr6+mqGLzAzRhUKBTzPY2JiohXFDSwmpbT++Q9y5lFTQq+U6gT+DDgEaOCzwAXgq0A/cAX4tNZ6\nfJ5DBBL/xAgjIyO89NJLxONx3nvvvZptgnpTheYJo21rrcnlcnb5xo0bfPGLXySZTPLOO+/Y9cVi\nkWg0itZ604VqlspGe/ab9ei/BLyktX5cKRUDUsBvAa9qrX9fKfV54PPAbzZ5nnXFn5GQyWR48803\ngdo0S6nChp5Q2rYRbsdxyGQyfP3rX7f/MyEJ/8tAWDpBFn9n8U0ao5TaAhwDngHQWhe11hngMeDL\n1c2+DHyq2UK2Gs/zpFfsJmIz2HajOLO0OzVHkK/dioUe2APcAv5CKfV9pdSfKaXagD6t9fXqNjeA\nvkY7K6WeUkqdUEqd8McHg4iZiizIN1JYVVbNttepvMvG8zyUUkSjUWKxmJ1qT2qqKyfIjmAzQh8B\n7gX+VGt9BJhmtipr0bO/vOGv11o/rbW+X2t9f09PTxPFWFtMN2j/iHxC6Fk1217zkjaJcWKEcNPM\nHR4ABrTWx6vLX2P24biplNoGUP073FwRW4vWGs/zpPF1c7FpbLtQKEja5CZgxUKvtb4BXFNKHaiu\nehg4CzwPPFFd9wTwXFMlFIR1RmxbWE2CEPJtNuvmPwJfqWYlXAL+PbMvj79WSj0JvAd8uslzCEIr\nENsWVoUgRAKaEnqt9UmgURzy4WaOKwitRmxbCBPSCiMIghByROgFQRBCjgi9IAhCyBGhFwRBCDki\n9IIgCCFHhF4QBCHkiNALgiCEHBF6QRCEkCNCLwiCEHJE6AVBEEKOCL0gCELIEaEXBEEIOSL0giAI\nIUeEXhAEIeSI0AuCIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4Re\nEAQh5IjQC4IghBwRekEQhJAjQi8IghByROgFQRBCjgi9IAhCyBGhFwRBCDki9IIgCCGnKaFXSv1n\npdQZpdRppdRfKaUSSqk9SqnjSqmLSqmvKqViq1VYQVgvxLaFMLFioVdKbQf+E3C/1voQ4AK/CPwB\n8Mda633AOPDkahRUENYLsW0hbDQbuokASaVUBEgB14GPA1+r/v/LwKeaPIcgtAKxbSE0rFjotdaD\nwP8ErjL7EEwAbwEZrXW5utkAsL3R/kqpp5RSJ5RSJ0ZGRlZaDEFYdVbTttejvIKwGM2EbrYCjwF7\ngDuBNuBnl7q/1vpprfX9Wuv7e3p6VloMQVh1VtO216iIgrAsmgnd/Cvgstb6lta6BPwd8FGgs1rd\nBdgBDDZZRkFYb8S2hVDRjNBfBR5QSqWUUgp4GDgLfBt4vLrNE8BzzRVRENYdsW0hVDQToz/ObMPU\n28Cp6rGeBn4T+DWl1EWgG3hmFcopCOuG2LYQNiKLbzI/WuvfBX63bvUl4GgzxxWEViO2LYQJ6Rkr\nCIIQckToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4ReEAQh5IjQC4IghBwRekEQhJAjQi8IghBy\nROgFQRBCjgi9IAhCyBGhFwRBCDki9IIgCCFHhF4QBCHkBErolVLMzvNwG601lUqlZlkQ6qm3m/nW\nCcJmpKnx6FcbrfUcIVdK4bquXXacue+m+R5oeSlsHvy2Y77XOwlBxG+7WutFX07mNzZyiBqtX+g4\nZlt5TsJPYIS+UqnUCDrcNkaz3nEc+1nKQ6GUCvyDLqwNjZyGoGFse6V2Wv+SaJZWXS//C9qglAr8\n/dtIBEboHceZE7pRSuF5HoVCAZh9GZTLZftQiCEIBr/tGAE1Iho0TFmNPQtzkWd7dQlEjN4YvvmY\n8IwR+nw+b7cVD11ohL/mF4lEcBwnsGLvui7RaLTVxRA2EYHw6LXWeJ4HzAq5+a61JhKJ0NbWRjab\nJZFIkEwmyeVyVCqVhvF6uF2l9TyvpgYghBe/d1wul/E8j1KpFKgQjrHLcrlMuVzGcRw6OztxXZdC\noVATvmzUVgWzv1NrjeM49mVhbNw4Skv9vf4YfaVSsc/Jcl+Mpkwrwd+W0ih008yxhdsERuhLpRLl\ncplisYjruhSLRYrFIj09PRw5coRr166RTqeJx+M2lOPHcRxrqJHI7M8aGxvj2rVrZLNZQOJ+YUVr\nTT6fZ2JiAtd1mZycpFwuE4/HaxyHVhOJRNBa2xdSX18fDzzwALFYjBs3bpDP50kkEjW2DFhhV0rZ\n5ySZTNLZ2QnA5OQk+Xwe13Vt+9VimDYux3EolUrkcjkKhUJNG9hi+5rnqVAoUCwWAZb9sjEv5EKh\nQKlUsg6c4zi2Nm+ObRy7IL28NwqBEHrP85iengZuG5GJze/evZtHH32UTCZDLBbDdd2aB9cYlTEM\nrTXJZBKAU6dOMT09bYXe7CtGsvHx30PP85iYmOD69evMzMwwMTGB53nEYjEqlQqlUqmFJb2NKYfj\nOPT29vKhD32I/v5+K+qFQoF4PG5tGRpn17iuS0dHB+3t7RSLRUZHR5mZmSEajVqRXihZwVw78/Io\nFotks1ny+bxdtxD+l4TnefYlsZQEiXqMc+evsZiwW7lcnnPvxFlbGYEQeuPRm+9wuzra19dHR0cH\n5XJ5jrfgr3o6jmP3aW9vt9seP37cnsf/AAkbG//DXqlUyOVyZDIZKpUKk5OTNULf6ntuwjGmHP39\n/Xz4wx9m586d5PN5xsbGKBaLaK2t91qPEe9YLEYqlSKZTFIul5mZmaFQKFgHxnXdJYUq/RltpVLJ\n1hSMN72UYxjHyYRI4bbX3Wh//3H93rnneTZE0+hTX25h+QRG6HO53BwRN1XyXC6H53kLegt+oY9E\nItZTkfh8OKnPznJdl1gsZj+VSoVoNLoiL3O1qRenUqlkQxKO49jGY3+IxsSnzbKx/3rnxnzqkxkW\nasMy8XzTUG328SdBzLev2X8+z9+sm29//zn8+7T6HoWdQAi9Uso2LBkjjMViFAoFrl27xqlTp2zo\nZqFqrfEKEokEABcuXGBiYsL+v9WenbA2GPtJJpOkUikb6zWCv5BorQd+L1ZrzbVr1xgdHeXHf/zH\nOXLkCJ2dnUxPT1MqlWps3F9u//MxOTlJpVKhs7OTeDxuY/Mmy2ixRAX/S8X/AWri/PO9JP0vFf+5\n/dsvFDaqF/lGx/V/6s8tXv3yCYTQu67L1q1brRduYpAm7vryyy/z3nvv0dHRYRtjjaH6MQZgqsqT\nk5OMj4/b/0sLfnioj9FnMhkGBgaYmJggm83WePTzhUPWGyOGJuRy6tQpotEo8XicmzdvUiqViMfj\n1oP3YzxoE7dOJpN0dHQAkM1mbe1gqWGX+mPm83lKpdKSvOv6XrUm9AMry9gplUoUi0WbJeWvlfj7\nGcwXzhEWJxBC73ke4+PjVuhN1sz4+DhXr17lzJkzjI+P47ouiUSCfD6/YJXc37Aj4+SEE/99LRQK\nvPvuuyQSCRKJBLlczsartda2Mb7V1Dcsjo+P873vfc8Ke302Sz1mvV8MoTYLZbker/+YKw1zrYb4\nzncM/zp5fldOIIR+dHSUr3zlK9a7cByHVCrF9PQ0b7zxhg2/+LNzhM2NX+jz+Tznz5/n5s2b1hP0\nhy8mJydbVcyGRCIRmzvv7wwoCGuFCsJbMhqN6u7uboA5Vbfp6Wmmp6flbS4syEIhh2rIriWtfUop\nMVxhTVmKbS8q9EqpPwc+CQxrrQ9V13UBXwX6gSvAp7XW42r2SfsS8CgwA/w7rfXbixZikYfBNPaY\nGPtC1cv6+KFk3QjQ+GFotW37M1+WYqf1YRl/mGc1HKFWOVPmvI16xgqLsyQnZr7cVZ/xHAPuBU77\n1v0P4PPV758H/qD6/VHg/wEKeAA4vtjxq/tp+chnLT9i2/IJ62dJdrhEY+2n9mG4AGyrft8GXKh+\n/7/AZxptt9BHKaVjsVjNJx6P61gspl3XbfmFlE/wP0op7bpuww/M/zCwxrbd6usin/B/lqLhK22M\n7dNaX69+vwH0Vb9vB675thuorrtOHUqpp4CnzHJQUuCEjYnWerX6Say6bQtCq2k660ZrrVfS4KS1\nfhp4GqTBSggmYttCWFhpl8GbSqltANW/w9X1g8BO33Y7qusEYaMgti2EjpUK/fPAE9XvTwDP+db/\nWzXLA8CErxosCBsBsW0hfCyhMemvmI1DlpiNSz4JdAOvAu8C3wS6qtsq4H8DPwJOAfdLZoJ8gvAR\n25ZPWD9LscNAdJiSOKaw1mjpMCWElKXYdiDmjBUEQRDWDhF6QRCEkCNCLwiCEHICMXolMAJMV/8G\njR6kXMshiOXa3cJzi20vHynX0lmSbQeiMRZAKXVCa31/q8tRj5RreQS1XK0kqNdEyrU8glqupSCh\nG0EQhJAjQi8IghBygiT0T7e6APMg5VoeQS1XKwnqNZFyLY+glmtRAhOjFwRBENaGIHn0giAIwhoQ\nCKFXSv2sUuqCUuqiUurzLSzHTqXUt5VSZ5VSZ5RSn6uu71JKvaKUerf6d2sLyuYqpb6vlHqhurxH\nKXW8es2+qpSKrXeZquXoVEp9TSl1Xil1Tin1kSBcryAgdr3k8gXOtsNm1y0XeqWUy+xgUZ8ADgKf\nUUodbFFxysCva60PMjtd3K9Uy/J54FWt9X5mB7xqxUP7OeCcb/kPgD/WWu8DxpkdkKsVfAl4SWv9\nfuAws2UMwvVqKWLXyyKIth0uu17KyGdr+QE+ArzsW/4C8IVWl6talueAR5hnerl1LMcOZg3r48AL\nzI6kOAJEGl3DdSzXFuAy1bYe3/qWXq8gfMSul1yWwNl2GO265R4980/R1lKUUv3AEeA4808vt178\nL+A3gEp1uRvIaK3L1eVWXbM9wC3gL6pV7z9TSrXR+usVBMSul0YQbTt0dh0EoQ8cSqk08LfAr2qt\nJ/3/07Ov83VLVVJKfRIY1lq/tV7nXAYR4F7gT7XWR5jt6l9TnV3v6yXMT5DsulqeoNp26Ow6CEIf\nqCnalFJRZh+Gr2it/666er7p5daDjwI/r5S6AjzLbBX3S0CnUsqMVdSqazYADGitj1eXv8bsA9LK\n6xUUxK4XJ6i2HTq7DoLQvwnsr7a0x4BfZHbatnVHKaWAZ4BzWus/8v1rvunl1hyt9Re01ju01v3M\nXptvaa1/Gfg28HgryuQr2w3gmlLqQHXVw8BZWni9AoTY9SIE1bZDadetbiSoNmw8CvyQ2Wna/msL\ny/Egs9Wxd4CT1c+jzDO9XAvK9xDwQvX7XuAN4CLwN0C8RWX6EHCies2+DmwNyvVq9UfselllDJRt\nh82upWesIAhCyAlC6EYQBEFYQ0ToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4ReEAQh5IjQC4Ig\nhBwRekEQhJDz/wECMawHvHJf0QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be0121fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.788 \n",
+      "FIRE        0.785 \n",
+      "RIGHT       0.784 \n",
+      "LEFT        0.787 \n",
+      "RIGHTFIRE   0.789 (Action Taken)\n",
+      "LEFTFIRE    0.787 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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JP83OztZ4MEuJXv3/npiYwLZtL0Yf9HNiOsLNzc3VtDeI0AcX/xhD/kly6tcx\nNXBTU9da14i8H/+1N7a/EZ22dhFooddak81mGRkZIZ/Pk8/nSSaTNR7AUti2zfj4eKuKuiEpFovL\nPn9BJugPqM2M6bPipz7Jwj+sgRmEzv+7fzvzoPDX6OqPJyxN4IS+Ef4LWZ83LghCsOnq6qKra35I\n/8nJSc9rNzXUbDbrDdxX/4C4nYjXty3JNJKNCbzQm0ZI/7KIvSAEl2g06qVDdnR0sHXrVrZu3QrM\nC3ehUPA6RNm2TT6fr2lDWwn1I1yatj0R+loCJ/T1F9p/8UwLe6MedUvtL2xxvGZj6xvxnGyE9oTN\nium5alJ1BwYG6Orq8sS2o6PD6+yYSqW8pILJyckF13Ul11hrvWDWsWYmmwkzgRP6RhkkxoOvH+Nk\nufsTgahFzomwlvjHGrIsi+7ubnbu3IlSiunpaWZmZrzUZtPHBWB2drap4zZqC5DhjBsTOKEXBGFj\n4Xca6oemsG2biYkJZmdnvZp5o5z3tejHsZgT6B+0b7M6OIEX+o0YZhCEsNJorP9UKoXW2pvy059F\nY2aIa5Tp5Rf3tRLgxYTePzXhZiTwQi8IQnAwue/+Cdh3795NOp3m0qVLTE1NobUmmUx680GIo9Z+\nROgFQVgU/yCAZrC8+vDMjh07GBgY8EaZNe+RSITZ2dma9f3DDK+Xd+3PzNmsiNALgrAoZugNf1JE\nI8E0o6sCjI+Pc/78eWB+SIP6oSvWW3AbNdrCrbDwZmi8FaEXBKEG48WbXHcj8PF4nC1btuA4jjd3\nr+u6XL9+nbm5OWZmZrx9LNYjPUhetX847CCVqxWI0AuCsID6OVsBBgcHuf/++xkeHub1118H5oX7\n6tWr3lAGG5H6NoQwir4IvSAIQO2Qv2b4771793o9Vg8fPszBgwcXTGaTy+W8z42y5IIaGmmUFhpG\nkQcRekEQqph5CUw8+4477uBXfuVX2LlzJ7Ozs97Isf4QjdnObLPYpCFBxD90Qtgzg0ToBWETY6bo\nLJVKnqeeTCYZHBzkE5/4BB//+MfZs2cP2WyWEydO8NOf/pRz58552/vHmFnvbJq1YrVDMGwkROgF\nYRNjZhiLx+PeBOz33HMPv/d7v8eePXsYHR3l/fffx7IsLl++zM9+9jNv6AIzKUwYBhlcTODDEtIR\noW+Af+IEM262IIQBMxpsLBYjl8tRqVQoFApEo7ekYPv27Tz66KPYts3f/d3fcfr0aQYGBhgeHm56\nfJqNRJiEu5pvAAAQsUlEQVTCOSL0DTB5t5sh7UrYXDiOQ6FQoFQq1Xji/uG/bdtmZGSEa9eu8cor\nr3DlyhUAb0x5Q32jbNjwT8O50RGhXwIReSEs+Af1MvOwAjz55JNs27aN1157zevkNDw8zNe+9jVG\nR0c9kQfIZrPEYjFc1900k3GHRQNE6BvgH6PDdBoJywUXNifGO+3q6vKyZg4ePMiXvvQltm/fzjPP\nPOMJ/fXr1/nWt77VMC8+7F78ctlosXsReqiZrMCyLLZv386OHTtIJBKMj49z9epVL1fYsqwNmVkg\nbE5MgynMZ9h86lOfYnBwkOHhYR555BHuu+8+YH5yEEO5XK4ZtCyVSlGpVGpGpdzMbMRwjgg9C4V+\n586dfPSjH6Wzs5MLFy4wNTVVI/SbebhTYWORSCQ8oY/FYjzxxBP8zu/8Ts06J0+eZGhoyFu2LMvL\nmXddl7m5uXUtc9AxtaPFJjIPIlYzGyulupVSLyilziul3lFKfVwp1auUekUp9V71vWetCtsq/E9o\npRSpVIq+vj62bt3Kli1biMVibSyd0A7CYtsmewzmbbu3t7fm97/6q7/i85//PG+99Zb3XbFY9MKX\nQmOCKuiL0ZTQA18BXtJa3wMcAt4BvgC8qrXeD7xaXQ40/ovmui4zMzN88MEHvP/++9y4caNm+rON\ndoGFVRMK2/Y3mlYqFY4fP+4t/+hHP+LLX/4yP/zhD8nn86TTaRKJhJeZE4b8+PUkyNqw6ke2UmoL\ncBT4XQCtdRkoK6WeBB6prvZ14J+AP26mkK3GfzO4rsvQ0BD5fJ5oNEoulyObzdb8HuQLKjRPmGzb\nP7NTuVzm29/+Nu+++y5dXV2cP3+et99+2/vdtm3pM9IEQQ7dNFM32wOMAV9TSh0CTgCfA7Zpra9X\n17kBbGu0sVLqWeBZgF27djVRjOap7wI9Pj6+IYZZFVrGmtl2uzFOjMkgO3PmDGfOnPF+V0qRSCS8\nxlZh9QRZG5oJ3USBB4C/0FofBuaoq8rq+X/e8N9rrZ/TWj+ktX6ov7+/iWIIwpqzZrbd8pIuk8Uy\nRcw4NRsxk0RYPs0I/TAwrLU+Vl1+gfmb46ZSajtA9X20uSKuP2YIBPMSNh2hs20TkolGo6RSKdLp\nNPF4HNd1yefzEo8POatWMa31DeCqUupA9atHgXPAi8DT1e+eBr7TVAnbTJCrY0JrCLtty/hNm49m\n86f+DfANpVQcuAT8K+YfHt9SSj0DfAD8RpPHWHekQ5RASG3bPzWgsHloSui11qeARnHIR5vZryC0\nG7FtIUxIAFoQBCHkiNALgiCEHBF6QRCEkCNCLwiCEHJE6AVBEEKOCL0gCELIEaEXBEEIOSL0giAI\nIUeEXhAEIeSI0AuCIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4Re\nEAQh5IjQC4IghBwRekEQhJAjQi8IghByROgFQRBCjgi9IAhCyBGhFwRBCDki9IIgCCFHhF4QBCHk\niNALgiCEHBF6QRCEkCNCLwiCEHJE6AVBEEJOU0KvlPp3SqmzSqkzSqm/VkollVJ7lFLHlFIXlVLf\nVErF16qwgrBeiG0LYWLVQq+U2gH8W+AhrfV9QAT4TeBPgS9rrfcBU8Aza1FQQVgvxLaFsNFs6CYK\npJRSUaADuA58Enih+vvXgc80eQxBaAdi20JoWLXQa61HgP8GDDF/E8wAJ4BprXWlutowsKPR9kqp\nZ5VSx5VSx8fHx1dbDEFYc9bSttejvIJwO5oJ3fQATwJ7gDuBNPCp5W6vtX5Oa/2Q1vqh/v7+1RZD\nENactbTtFhVREFZEM6GbfwZc1lqPaa1t4G+BTwDd1eouwE5gpMkyCsJ6I7YthIpmhH4I+JhSqkMp\npYBHgXPAD4Cnqus8DXynuSIKwrojti2EimZi9MeYb5g6CZyu7us54I+BzyulLgJ9wFfXoJyCsG6I\nbQthI3r7VRZHa/0nwJ/UfX0JONLMfgWh3YhtC2FCesYKgiCEHBF6QRCEkCNCLwiCEHJE6AVBEEKO\nCL0gCELIEaEXBEEIOSL0giAIIUeEXhAEIeSI0AuCIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAI\nQsgRoRcEQQg5gRJ6pRTz8zzcQmuN67o1y4JQT73dLPadIGxGmhqPfq3RWi8QcqUUkUjEW7ashc+m\nxW5oeShsHvy2Yz7XOwlBRSkltiq0lMAIveu6NYIO8zesX+gty/Je5relUEptiBtdWHsaOQ1BJBKJ\nrNpO/fbfzv+6FsfeCNdqIxMYobcsa0HoRimF4ziUSiVg/mFQqVS8m0KMQzD4bcc4B0ZEg4Ypk9Ya\nx3HaXBphMxCIGL25Sc3LhGeM0BeLRW9d8dCFRvhrftFoFMuyAiv2lmURjQbGxxI2AYGwNr9n47qu\n91lrTTQaJZ1Ok8vlSCaTpFIpCoUCrus2jNfDLY/JcZyaGoAQXkxtD6BSqeA4DrZtByqE47dLx3Gw\nLItMJoNlWdi2vaRNG8z/UUp5DwvHcZYVyrzdPld7ntZi28X2EaTrt5EJjNDbtk2lUqFcLhOJRCiX\ny5TLZfr7+zl8+DBXr14lk8mQSCS8UI4fy7I8QTc3wOTkJFevXiWXywHS6BVWtNYUi0VmZmaIRCJk\ns1kqlQqJRKLGcWg3RsRNeXp6erj33nuJxWJMTk5i2zaxWKyhnRoRN45LPB4nk8kAkM/nKZfLNe1X\nt8M8GJRS3n1nHpTL3Ycpp7l3/eVstL3/f9U7Y2Yf5mFn2i385Vpq38LSBELoHcdhbm4OuGWAJja/\ne/duHn/8caanp4nH40QikZob1xiPZVmeZ5NKpQA4ffo0c3NzntCbbcVQNj7+a+g4DjMzM1y/fp18\nPs/MzAyO4xCPx3FdF9u221jSWxi7VUrR09PDvn372L59u+egGKH3Oy2NsCyLjo4OUqkUtm2Ty+U8\noV+uV2/uM1ObyOfz2La9olqBKadxylZTqzDb+5fNA8s8BITmCYTQG6/AfIZbnsu2bdvo6uqiUql4\nHki9V2CE3mzT2dnprXvs2DHvOMZ4hI2PX+hd16VQKDA9PY3rumSz2Rqhb/c1N568Ee877riDgwcP\nsnXrVkqlErOzs16YybbtBUJvlrXWxGIx4vG499/K5bLnDRuBXEmoMhKJUKlUvHBXo/LWl8O/rQlD\nua5bkzl3O2fK3Ltmu/oQjoRs1pbACH2hUFgg4qZKXigUcBxnSW/BL/TRaBSlFOVyWeLzIaU+OysS\niXgCaEQwFos1FbtuFZVKhVKpRKVS8RqMjYgar7x+GRb2F6lPYjDf3S7OD7fSmesTIPzHabSf+vX8\n5Wu0j5UStGsVFgIh9EopYrEYMG+ASini8TilUomrV69y+vRpL3Tj98rrjcJ4BslkEoALFy4wMzPj\n/d5uz05oDcZ+UqkUHR0dXsOmEfzlCF8rMc6GsdexsTFyuRwHDhxg3759pNNpisUilUrFc1JMLdVg\nvje1F4B0Ok0sFvO8cvPA8DfYLkajTLfFUpzr8e97sfeV4C+Hv+1ARH/tCITQRyIRenp6PC88EonQ\n1dXlxV1ffvllPvjgA7q6urzG2PobAW5VF031MZvNMjU15f1uHgTCxqc+Rj89Pc3w8DAzMzPkcrka\nj94fA24n/sbYYrHIpUuXiEajxGIxpqenvRh9PX5hNaGoWCxGOp1GKeU1xq4klbR+n+VyeVEHarFt\nzYPHH/ZZboOp/9imMdafPWT27XfOglg72ygEQugdx2FqasoTepM1MzU1xdDQEGfPnmVqaopIJEIy\nmaRYLC550evjfwYR+fDgv66lUon33nuPZDJJMpmkUCigtSYSiaC19hrj2019jTKXy3H69GlP1JYj\nZP7Qpl9Um02v9L83s4+13r7+e7mHV0cghH5iYoJvfOMbXqqXySqYm5vjjTfe8MIv/uwcYXPjF/pi\nscj58+e5efOmF9v2h2yy2Wy7itkQE2KxbTswtQ0h3KggPCFjsZju6+sDatO+XNdlbm6Oubk5eZIL\nS7JUTLfqLbelzq+UEsMVWspybPu2Qq+U+kvgCWBUa31f9bte4JvAIHAF+A2t9ZSav9O+AjwO5IHf\n1VqfvG0hbnMzmO7sy6ne+n/fKKMXCq2n0c0QBNteyaBm9R2p/PeBDGq2eVmWE7NY/qovj/Uo8ABw\nxvfdfwW+UP38BeBPq58fB/4voICPAcdut//qdlpe8mrlS2xbXmF9LcsOl2msg9TeDBeA7dXP24EL\n1c//C/hso/WWeimldDwer3klEgkdj8d1JBJp+4mUV/BfSikdiUQavmDxm4EW23a7z4u8wv9ajoav\ntjF2m9b6evXzDWBb9fMO4KpvveHqd9epQyn1LPCsWZZGKaEZtF6zIX/X3LYFod00nXWjtdaraXDS\nWj8HPAfSYCUEE7FtISystsvgTaXUdoDq+2j1+xFgl2+9ndXvBGGjILYthI7VCv2LwNPVz08D3/F9\n/y/VPB8DZnzVYEHYCIhtC+FjGY1Jf818HNJmPi75DNAHvAq8B/w/oLe6rgL+B/A+cBp4SDIT5BWE\nl9i2vML6Wo4dBqLDlMQxhVajpcOUEFKWY9uBmDNWEARBaB0i9IIgCCFHhF4QBCHkBGL0SmAcmKu+\nB41+pFwrIYjl2t3GY4ttrxwp1/JZlm0HojEWQCl1XGv9ULvLUY+Ua2UEtVztJKjnRMq1MoJaruUg\noRtBEISQI0IvCIIQcoIk9M+1uwCLIOVaGUEtVzsJ6jmRcq2MoJbrtgQmRi8IgiC0hiB59IIgCEIL\nCITQK6U+pZS6oJS6qJT6QhvLsUsp9QOl1Dml1Fml1Oeq3/cqpV5RSr1Xfe9pQ9kiSqm3lFLfrS7v\nUUodq56zbyql4utdpmo5upVSLyilziul3lFKfTwI5ysIiF0vu3yBs+2w2XXbhV4pFWF+sKhPAweB\nzyqlDrapOBXgD7XWB5mfLu73q2X5AvCq1no/8wNeteOm/Rzwjm/5T4Eva633AVPMD8jVDr4CvKS1\nvgc4xHwZg3C+2orY9YoIom2Hy66XM/JZK1/Ax4GXfctfBL7Y7nJVy/Id4DEWmV5uHcuxk3nD+iTw\nXeZHUhwHoo3O4TqWawtwmWpbj+/7tp6vILzErpddlsDZdhjtuu0ePYtP0dZWlFKDwGHgGItPL7de\n/HfgjwC3utwHTGutK9Xldp2zPcAY8LVq1ft/K6XStP98BQGx6+URRNsOnV0HQegDh1IqA/wN8Ada\n66z/Nz3/OF+3VCWl1BPAqNb6xHodcwVEgQeAv9BaH2a+q39NdXa9z5ewOEGy62p5gmrbobPrIAh9\noKZoU0rFmL8ZvqG1/tvq14tNL7cefAL4NaXUFeB55qu4XwG6lVJmrKJ2nbNhYFhrfay6/ALzN0g7\nz1dQELu+PUG17dDZdRCE/k1gf7WlPQ78JvPTtq07SikFfBV4R2v9Z76fFpteruVorb+otd6ptR5k\n/tx8X2v928APgKfaUSZf2W4AV5VSB6pfPQqco43nK0CIXd+GoNp2KO263Y0E1YaNx4F3mZ+m7T+2\nsRwPM18dexs4VX09ziLTy7WhfI8A361+3gu8AVwEvg0k2lSmjwDHq+fs/wA9QTlf7X6JXa+ojIGy\n7bDZtfSMFQRBCDlBCN0IgiAILUSEXhAEIeSI0AuCIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAI\nQsgRoRcEQQg5/x823QprZ9/p4QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01072b0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.777 \n",
+      "FIRE        0.777 \n",
+      "RIGHT       0.784 \n",
+      "LEFT        0.783 \n",
+      "RIGHTFIRE   0.780 \n",
+      "LEFTFIRE    0.790 (Action Taken)\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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ZY+/maa/5OMLNCbTQa62Zn59nbGyMfD5PPp8nkUg03PFvRqVSYWpqaq2a2pMU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\nAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00f31d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.831 \n",
+      "FIRE        0.822 \n",
+      "RIGHT       0.825 \n",
+      "LEFT        0.823 (Action Taken)\n",
+      "RIGHTFIRE   0.824 \n",
+      "LEFTFIRE    0.831 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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SiYY0u6WoVqtMTEysVVE3JKVSadnXL8gE/QW12WnlRDSHB02tzZ9Bs9h9Nf1g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\nAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00ad128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.841 (Action Taken)\n",
+      "FIRE        0.834 \n",
+      "RIGHT       0.822 \n",
+      "LEFT        0.838 \n",
+      "RIGHTFIRE   0.833 \n",
+      "LEFTFIRE    0.831 \n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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TOKFvhd8IFnviC4IQTGKxmNeCLJfLDVNnm9HPJjy5EjEPykC/zUDghd50Qvq3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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be00dac88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Action:     Q-Value:\n",
+      "====================\n",
+      "NOOP        0.833 (Action Taken)\n",
+      "FIRE        0.831 \n",
+      "RIGHT       0.809 \n",
+      "LEFT        0.829 \n",
+      "RIGHTFIRE   0.824 \n",
+      "LEFTFIRE    0.827 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(0, 5):\n",
+    "    plot_state(idx=idx+i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Output of Convolutional Layers\n",
+    "\n",
+    "The outputs of the convolutional layers can be plotted so we can see how the images from the game-environment are being processed by the Neural Network.\n",
+    "\n",
+    "This is the helper-function for plotting the output of the convolutional layer with the given name, when inputting the given state from the replay-memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_layer_output(model, layer_name, state_index, inverse_cmap=False):\n",
+    "    \"\"\"\n",
+    "    Plot the output of a convolutional layer.\n",
+    "\n",
+    "    :param model: An instance of the NeuralNetwork-class.\n",
+    "    :param layer_name: Name of the convolutional layer.\n",
+    "    :param state_index: Index into the replay-memory for a state that\n",
+    "                        will be input to the Neural Network.\n",
+    "    :param inverse_cmap: Boolean whether to inverse the color-map.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Get the given state-array from the replay-memory.\n",
+    "    state = replay_memory.states[state_index]\n",
+    "    \n",
+    "    # Get the output tensor for the given layer inside the TensorFlow graph.\n",
+    "    # This is not the value-contents but merely a reference to the tensor.\n",
+    "    layer_tensor = model.get_layer_tensor(layer_name=layer_name)\n",
+    "    \n",
+    "    # Get the actual value of the tensor by feeding the state-data\n",
+    "    # to the TensorFlow graph and calculating the value of the tensor.\n",
+    "    values = model.get_tensor_value(tensor=layer_tensor, state=state)\n",
+    "\n",
+    "    # Number of image channels output by the convolutional layer.\n",
+    "    num_images = values.shape[3]\n",
+    "\n",
+    "    # Number of grid-cells to plot.\n",
+    "    # Rounded-up, square-root of the number of filters.\n",
+    "    num_grids = math.ceil(math.sqrt(num_images))\n",
+    "\n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids, figsize=(10, 10))\n",
+    "\n",
+    "    print(\"Dim. of each image:\", values.shape)\n",
+    "    \n",
+    "    if inverse_cmap:\n",
+    "        cmap = 'gray_r'\n",
+    "    else:\n",
+    "        cmap = 'gray'\n",
+    "\n",
+    "    # Plot the outputs of all the channels in the conv-layer.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the valid image-channels.\n",
+    "        if i < num_images:\n",
+    "            # Get the image for the i'th output channel.\n",
+    "            img = values[0, :, :, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, interpolation='nearest', cmap=cmap)\n",
+    "\n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "\n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Game State\n",
+    "\n",
+    "This is the state that is being input to the Neural Network. The image on the left is the last image from the game-environment. The image on the right is the processed motion-trace that shows the trajectories of objects in the game-environment."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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pSqVCIpGgVCpx5coVO2rW9PCjRLhHn0qlmJ6eJpfLXTeeIEzzMZvRwo7j4Hke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\nAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be01804a8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "idx = np.argmax(q_values_max)\n",
+    "plot_state(idx=idx, print_q=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Output of Convolutional Layer 1\n",
+    "\n",
+    "This shows the images that are output by the 1st convolutional layer, when inputting the above state to the Neural Network. There are 16 output channels of this convolutional layer.\n",
+    "\n",
+    "Note that you can invert the colors by setting `inverse_cmap=True` in the parameters to this function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dim. of each image: (1, 53, 40, 16)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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srF7qPIYSkw97yQRW+swEVgBg+A10zkjlKU95SpLkJ3/yJ5Mkn/vc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\nRgCAojQjAEBRmhEAoCjNCABQ1P8BPh7lSkA/2rMAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be022a9e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_layer_output(model=model, layer_name='layer_conv1', state_index=idx, inverse_cmap=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Output of Convolutional Layer 2\n",
+    "\n",
+    "These are the images output by the 2nd convolutional layer, when inputting the above state to the Neural Network. There are 32 output channels of this convolutional layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dim. of each image: (1, 27, 20, 32)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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AAJxDBwcAADiHDg4AAHAOHRwAAOAcOjgAAMA5dHAAAIBz6OAAAADn0MEBAADO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\n/7rgud/73vdqfN9992lcW1u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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be02ba160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_layer_output(model=model, layer_name='layer_conv2', state_index=idx, inverse_cmap=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Output of Convolutional Layer 3\n",
+    "\n",
+    "These are the images output by the 3rd convolutional layer, when inputting the above state to the Neural Network. There are 64 output channels of this convolutional layer.\n",
+    "\n",
+    "All these images are flattened to a one-dimensional array (or tensor) which is then used as the input to a fully-connected layer in the Neural Network.\n",
+    "\n",
+    "During the training-process, the Neural Network has learnt what convolutional filters to apply to the images from the game-environment so as to produce these images, because they have proven to be useful when estimating Q-values.\n",
+    "\n",
+    "Can you see what it is that the Neural Network has learned to detect in these images?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dim. of each image: (1, 27, 20, 64)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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V7caURXBlbOPrX/864M5a/u3f/q1oeyX/kY6ODsBV64Lw72PLlhs2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\nZ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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8bb81282b0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_layer_output(model=model, layer_name='layer_conv3', state_index=idx, inverse_cmap=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "deletable": true,
+    "editable": true,
+    "id": "Nv2JqNLBhy1j"
+   },
+   "source": [
+    "## Weights for Convolutional Layers\n",
+    "\n",
+    "We can also plot the weights of the convolutional layers in the Neural Network. These are the weights that are being optimized so as to improve the ability of the Neural Network to estimate Q-values. Tutorial #02 explains in greater detail what convolutional weights are.\n",
+    "There are also weights for the fully-connected layers but they are not shown here.\n",
+    "\n",
+    "This is the helper-function for plotting the weights of a convoluational layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_conv_weights(model, layer_name, input_channel=0):\n",
+    "    \"\"\"\n",
+    "    Plot the weights for a convolutional layer.\n",
+    "    \n",
+    "    :param model: An instance of the NeuralNetwork-class.\n",
+    "    :param layer_name: Name of the convolutional layer.\n",
+    "    :param input_channel: Plot the weights for this input-channel.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Get the variable for the weights of the given layer.\n",
+    "    # This is a reference to the variable inside TensorFlow,\n",
+    "    # not its actual value.\n",
+    "    weights_variable = model.get_weights_variable(layer_name=layer_name)\n",
+    "    \n",
+    "    # Retrieve the values of the weight-variable from TensorFlow.\n",
+    "    # The format of this 4-dim tensor is determined by the\n",
+    "    # TensorFlow API. See Tutorial #02 for more details.\n",
+    "    w = model.get_variable_value(variable=weights_variable)\n",
+    "\n",
+    "    # Get the weights for the given input-channel.\n",
+    "    w_channel = w[:, :, input_channel, :]\n",
+    "    \n",
+    "    # Number of output-channels for the conv. layer.\n",
+    "    num_output_channels = w_channel.shape[2]\n",
+    "\n",
+    "    # Get the lowest and highest values for the weights.\n",
+    "    # This is used to correct the colour intensity across\n",
+    "    # the images so they can be compared with each other.\n",
+    "    w_min = np.min(w_channel)\n",
+    "    w_max = np.max(w_channel)\n",
+    "\n",
+    "    # This is used to center the colour intensity at zero.\n",
+    "    abs_max = max(abs(w_min), abs(w_max))\n",
+    "\n",
+    "    # Print statistics for the weights.\n",
+    "    print(\"Min:  {0:.5f}, Max:   {1:.5f}\".format(w_min, w_max))\n",
+    "    print(\"Mean: {0:.5f}, Stdev: {1:.5f}\".format(w_channel.mean(),\n",
+    "                                                 w_channel.std()))\n",
+    "\n",
+    "    # Number of grids to plot.\n",
+    "    # Rounded-up, square-root of the number of output-channels.\n",
+    "    num_grids = math.ceil(math.sqrt(num_output_channels))\n",
+    "\n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids)\n",
+    "\n",
+    "    # Plot all the filter-weights.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the valid filter-weights.\n",
+    "        if i < num_output_channels:\n",
+    "            # Get the weights for the i'th filter of this input-channel.\n",
+    "            img = w_channel[:, :, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, vmin=-abs_max, vmax=abs_max,\n",
+    "                      interpolation='nearest', cmap='seismic')\n",
+    "\n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "\n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Weights for Convolutional Layer 1\n",
+    "\n",
+    "These are the weights of the first convolutional layer of the Neural Network, with respect to the first input channel of the state. That is, these are the weights that are used on the image from the game-environment. Some basic statistics are also shown.\n",
+    "\n",
+    "Note how the weights are more negative (blue) than positive (red). It is unclear why this happens as these weights are found through optimization. It is apparently beneficial for the following layers to have this processing with more negative weights in the first convolutional layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min:  -0.68262, Max:   0.14787\n",
+      "Mean: -0.05167, Stdev: 0.11923\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUoAAADuCAYAAABf005JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8b94683748>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(model=model, layer_name='layer_conv1', input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can also plot the convolutional weights for the second input channel, that is, the motion-trace of the game-environment. Once again we see that the negative weights (blue) have a much greater magnitude than the positive weights (red)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min:  -0.95588, Max:   0.09746\n",
+      "Mean: -0.03578, Stdev: 0.15025\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUoAAADuCAYAAABf005JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUchDAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8ba87b1240>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(model=model, layer_name='layer_conv1', input_channel=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Weights for Convolutional Layer 2\n",
+    "\n",
+    "These are the weights of the 2nd convolutional layer in the Neural Network. There are 16 input channels and 32 output channels of this layer. You can change the number for the input-channel to see the associated weights.\n",
+    "\n",
+    "Note how the weights are more balanced between positive (red) and negative (blue) compared to the weights for the 1st convolutional layer above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min:  -0.30984, Max:   0.24492\n",
+      "Mean: -0.02332, Stdev: 0.09427\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8ba87b1cc0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(model=model, layer_name='layer_conv2', input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Weights for Convolutional Layer 3\n",
+    "\n",
+    "These are the weights of the 3rd convolutional layer in the Neural Network. There are 32 input channels and 64 output channels of this layer. You can change the number for the input-channel to see the associated weights.\n",
+    "\n",
+    "Note again how the weights are more balanced between positive (red) and negative (blue) compared to the weights for the 1st convolutional layer above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min:  -0.33228, Max:   0.24060\n",
+      "Mean: -0.02068, Stdev: 0.09566\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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ut8R8yk2T9Bf40fty5rWvnk+T8v6ItybeLubWP/8P/QWe/50S6muk/cprb8Xlm+Udw9Yo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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8be006c208>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(model=model, layer_name='layer_conv3', input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Discussion\n",
+    "\n",
+    "We trained an agent to play old Atari games quite well using Reinforcement Learning. Recent improvements to the training algorithm have improved the performance significantly. But is this true human-like intelligence? The answer is clearly NO!\n",
+    "\n",
+    "Reinforcement Learning in its current form is a crude numerical algorithm for connecting visual images, actions, rewards and penalties when there is a time-lag between the signals. The learning is based on trial-and-error and cannot do logical reasoning like a human. The agent has no sense of \"self\" while a human has an understanding of what part of the game-environment it is controlling, so a human can reason logically like this: \"(A) I control the paddle, and (B) I must avoid dying which happens when the ball flies past the paddle, so (C) I must move the paddle to hit the ball, and (D) this automatically scores points when the ball smashes bricks in the wall\". A human would first learn these basic logical rules of the game - and then try and refine the eye-hand coordination to play the game better. Reinforcement Learning has no real comprehension of what is going on in the game and merely works on improving the eye-hand coordination until it gets lucky and does the right thing to score more points.\n",
+    "\n",
+    "Furthermore, the training of the Reinforcement Learning algorithm required almost 150 hours of computation which played the game at high speeds. If the game was played at normal real-time speeds then it would have taken more than 1700 hours to train the agent, which is more than 70 days and nights.\n",
+    "\n",
+    "Logical reasoning would allow for much faster learning than Reinforcement Learning, and it would be able to solve much more complicated problems than simple eye-hand coordination. I am skeptical if someone will be able to create true human-like intelligence from Reinforcement Learning algorithms.\n",
+    "\n",
+    "Does that mean Reinforcement Learning is completely worthless? No, it has real-world applications that currently cannot be solved by other methods.\n",
+    "\n",
+    "Another point of criticism is the use of Neural Networks. The majority of the research in Reinforcement Learning is actually spent on trying to stabilize the training of the Neural Network using various tricks. This is a waste of research time and strongly indicates that Neural Networks may not be a very good Machine Learning model compared to the human brain."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises & Research Ideas\n",
+    "\n",
+    "Below are suggestions for exercises and experiments that may help improve your skills with TensorFlow and Reinforcement Learning. Some of these ideas can easily be extended into full research problems that would help the community if you can solve them.\n",
+    "\n",
+    "You should keep a log of your experiments, describing for each experiment the settings you tried and the results. You should also save the source-code and checkpoints / log-files.\n",
+    "\n",
+    "It takes so much time to run these experiments, so please share your results with the rest of the community. Even if an experiment failed to produce anything useful, it will be helpful to others so they know not to redo the same experiment.\n",
+    "\n",
+    "[Thread on GitHub for discussing these experiments](https://github.com/Hvass-Labs/TensorFlow-Tutorials/issues/32)\n",
+    "\n",
+    "You may want to backup this Notebook and the other files before making any changes.\n",
+    "\n",
+    "You may find it helpful to add more command-line parameters to `reinforcement_learning.py` so you don't have to edit the source-code for testing other parameters.\n",
+    "\n",
+    "* Change the epsilon-probability during testing to e.g. 0.001 or 0.05. Which gives the best results? Could you use this value during training? Why/not?\n",
+    "* Continue training the agent for the Breakout game using the downloaded checkpoint. Does the agent get better or worse the more you train it? Why? (You should run it in a terminal window as described above.)\n",
+    "* Try and change the game-environment to Space Invaders and re-run this Notebook. The checkpoint can be downloaded automatically. It was trained for about 150 hours, which is roughly the same as for Breakout, but note that it has processed far fewer states. The reason is that the hyper-parameters such as the learning-rate were tuned for Breakout. Can you make some kind of adaptive learning-rate that would work better for both Breakout and Space Invaders? What about the other hyper-parameters? What about other games?\n",
+    "* Try different architectures for the Neural Network. You will need to restart the training because the checkpoints cannot be reused for other architectures. You will need to train the agent for several days with each new architecture so as to properly assess its performance.\n",
+    "* The replay-memory throws away all data after optimization of the Neural Network. Can you make it reuse the data somehow? The ReplayMemory-class has the function `estimate_all_q_values()` which may be helpful.\n",
+    "* The reward is limited to -1 and 1 in the function `ReplayMemory.add()` so as to stabilize the training. This means the agent cannot distinguish between small and large rewards. Can you use batch normalization to fix this problem, so you can use the actual reward values?\n",
+    "* Can you improve the training by adding L2-regularization or dropout?\n",
+    "* Try using other optimizers for the Neural Network. Does it help with the training speed or stability?\n",
+    "* Let the agent take up to 30 random actions at the beginning of each new episode. This is used in some research papers to further randomize the game-environment, so the agent cannot memorize the first sequence of actions.\n",
+    "* Try and save the game at regular intervals. If the agent dies, then you can reload the last saved game. Would this help training the agent faster and better, because it does not need to play the game from the beginning?\n",
+    "* There are some invalid actions available to the agent in OpenAI Gym. Does it improve the training if you only allow the valid actions from the game-environment?\n",
+    "* Does the MotionTracer work for other games? Can you improve on the MotionTracer?\n",
+    "* Try and use the last 4 image-frames from the game instead of the MotionTracer.\n",
+    "* Try larger and smaller sizes for the replay memory.\n",
+    "* Try larger and smaller discount rates for updating the Q-values.\n",
+    "* If you look closely in the states and actions that are display above, you will note that the agent has sometimes taken actions that do not correspond to the movement of the paddle. For example, the action might be LEFT but the paddle has either not moved at all, or it has moved right instead. Is this a bug in the source-code for this tutorial, or is it a bug in OpenAI Gym, or is it a bug in the underlying Atari Learning Environment? Does it matter?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "celltoolbar": "Raw Cell Format",
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index dde8d74..e48ed29 100644
--- a/README.md
+++ b/README.md
@@ -43,6 +43,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 15. Style Transfer ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
 
+16. Reinforcement Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
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diff --git a/reinforcement_learning.py b/reinforcement_learning.py
new file mode 100644
index 0000000..9c4c2f8
--- /dev/null
+++ b/reinforcement_learning.py
@@ -0,0 +1,1828 @@
+########################################################################
+#
+# Reinforcement Learning (Q-Learning) for Atari Games
+#
+# How to run:
+#
+# To train a Neural Network for playing the Atari game Breakout,
+# run the following command in a terminal window.
+#
+# python reinforcement-learning.py --env 'Breakout-v0' --training
+#
+# The agent should start to improve after a few hours, but a full
+# training run required 150 hours on a 2.6 GHz CPU and GTX 1070 GPU.
+#
+# The hyper-parameters were tuned for Breakout and did not work
+# quite as well for SpaceInvaders. Can you find better parameters?
+#
+# Once the Neural Network has been trained, you can test it and
+# watch it play the game by running this command in the terminal:
+#
+# python reinforcement-learning.py --env 'Breakout-v0' --render --episodes 2
+#
+# Requirements:
+#
+# - Python 3.6 (Python 2.7 may not work)
+# - TensorFlow 1.0.1
+# - PrettyTensor 0.7.4
+# - OpenAI Gym 0.8.1
+#
+# Summary:
+#
+# This program implements a variant of Reinforcement Learning known as
+# Q-learning. Imagine that we have an agent that must take actions in
+# some environment so as to maximize the cumulative reward over its life.
+# The agent sees the state of the game-environment through images
+# which are sent through a Neural Network in TensorFlow, so as to
+# estimate which action is most likely to maximize the cumulative
+# reward of all future actions. These action-values are also called
+# Q-values. If the Q-values are known in advance, then the agent merely
+# has to select the action corresponding to the highest Q-value in
+# each state of the game. But the Q-values are not known in advance
+# and must be learnt while the agent is playing the game.
+# This is done by initializing all Q-values to zero and then having
+# the agent take random actions. Whenever the agent obtains a reward,
+# the estimated Q-values can be updated with the new information.
+# The agent gradually learns to play the game better and better
+# because the Neural Network becomes better at estimating the Q-values.
+# But this process is very slow and the basic algorithm implemented
+# here typically requires 100 million steps in the game-environment,
+# although it will typically start to show improvement much sooner.
+#
+# Main classes:
+#
+# - MotionTracer:
+#
+#   This takes raw images from the game-environment and processes them.
+#   The output is called a state and consists of two images of equal size:
+#   (1) The last image from the game-environment, resized and gray-scaled.
+#   (2) A motion-trace that shows the recent trajectories of objects.
+#
+# - ReplayMemory:
+#
+#   Successive image-frames of the game-environment are almost identical.
+#   If we train the Neural Network to estimate Q-values from a small
+#   number of successive image-frames, then it cannot learn to distinguish
+#   important features and the training becomes unstable. For the basic
+#   Q-learning algorithm we need many thousand states from the game-environment
+#   in order to learn important features so the Q-values can be estimated.
+#
+# - NeuralNetwork:
+#
+#   This implements a Neural Network for estimating Q-values. It takes as
+#   input a state of the game-environment that was output by the Motion Tracer,
+#   and then the Neural Network outputs the estimated Q-values that indicate
+#   the cumulative reward of taking each action for a given state of the game.
+#
+# - Agent:
+#
+#   This implements the agent that plays games. It loads an Atari-game from
+#   OpenAI Gym and inputs the game-images to the Motion Tracer, which in turn
+#   outputs a state that is input to the Neural Network, which estimates the
+#   Q-values that are used for selecting the next action. The agent then
+#   takes a step in the game-environment. During training, the data is added
+#   to the Replay Memory and when it is sufficiently full, an optimization run
+#   is performed so as to improve the Neural Network's ability to estimate
+#   Q-values. This procedure is repeated many, many times until the Neural
+#   Network is sufficiently accurate at estimating Q-values.
+#
+# The Q-Value Formula:
+#
+# The Q-values for a given state is a vector with a value for each possible
+# action, indicating the total future reward that can be had by taking each
+# action. The Q-values are initialized to roughly zero and must then be
+# improved iteratively when new information becomes available.
+#
+# We know which action was taken in the current step and what the observed
+# reward was, so the estimated Q-value can be improved with this information.
+# The Q-value estimates the total cumulative reward for all future steps, which
+# is why we use the max Q-value for the next step.
+#
+# The formula for updating Q-values is implemented in the ReplayMemory-class
+# in the function update_all_q_values(), which does a complete backwards-sweep
+# through the Replay Memory. The formula for updating the Q-values is:
+#
+# Q-value for this state and action = observed reward for the current step
+#                            + discount factor * max Q-value for next step
+#
+# The discount factor is a number slightly below 1.0 (e.g. 0.97) which causes
+# distant future rewards to have a smaller effect on the Q-values. This means
+# that if the reward is the same, then it is considered more valuable to get
+# the reward sooner rather than later.
+#
+# Pseudo-Code:
+#
+# There are many lines of source-code required to implement all this, but the
+# main ideas of the algorithm can be described more simply in pseudo-code:
+#
+# 1) Initialize all Q-values to roughly zero.
+#    We use a Neural Network to estimate the Q-values, so this means
+#    we have to initialize the Neural Network with small random weights.
+#
+# 2) Reset the game-environment and Motion Tracer.
+#
+# 3) Get the state from the Motion Tracer which consists of two gray-scale
+#    images. The first is the image of the game-environment and the second
+#    is a motion-trace showing recent movements in the game-environment.
+#
+# 4) Input the state to the Neural Network to estimate the Q-values.
+#
+# 5) Either take a random action with probability epsilon, or take the
+#    action with the highest Q-value. This is called the epsilon-greedy policy.
+#
+# 6) Add the state, action and observed reward to the Replay Memory.
+#
+# 7) When the Replay Memory is sufficiently full, first perform a full
+#    backwards-sweep to update all the Q-values with the observed rewards.
+#
+#    Then perform an optimization run of the Neural Network.
+#    This takes random batches of data from the Replay Memory and uses them
+#    for training the Neural Network to become better at estimating Q-values.
+#
+#    Save a checkpoint for the Neural Network so we can reload it later.
+#
+# 8) Input the recent image of the game-environment to the Motion Tracer
+#    and repeat from step (3).
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2017 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import numpy as np
+import tensorflow as tf
+import prettytensor as pt
+import gym
+import scipy.ndimage
+import sys
+import os
+import time
+import csv
+import argparse
+import download
+
+########################################################################
+# File-paths are global variables for convenience so they don't
+# have to be passed around between all the objects.
+# You should first set checkpoint_base_dir to whichever you like,
+# then call the function update_paths(env_name) to update all the paths.
+# This should be done before you create the Agent and NeuralNetwork etc.
+
+# Default base-directory for the checkpoints and log-files.
+# The environment-name will be appended to this.
+checkpoint_base_dir = 'checkpoints_tutorial16/'
+
+# Combination of base-dir and environment-name.
+checkpoint_dir = None
+
+# Full path for the log-file for rewards.
+log_reward_path = None
+
+# Full path for the log-file for Q-values.
+log_q_values_path = None
+
+
+def update_paths(env_name):
+    """
+    Update the path-names for the checkpoint-dir and log-files.
+    
+    Call this after you have changed checkpoint_base_dir and
+    before you create the Neural Network.
+    
+    :param env_name:
+        Name of the game-environment you will use in OpenAI Gym.
+    """
+
+    global checkpoint_dir
+    global log_reward_path
+    global log_q_values_path
+
+    # Add the environment-name to the checkpoint-dir.
+    checkpoint_dir = os.path.join(checkpoint_base_dir, env_name)
+
+    # Create the checkpoint-dir if it does not already exist.
+    if not os.path.exists(checkpoint_dir):
+        os.makedirs(checkpoint_dir)
+
+    # File-path for the log-file for episode rewards.
+    log_reward_path = os.path.join(checkpoint_dir, "log_reward.txt")
+
+    # File-path for the log-file for Q-values.
+    log_q_values_path = os.path.join(checkpoint_dir, "log_q_values.txt")
+
+########################################################################
+# Download TensorFlow checkpoints.
+
+# URL's for the checkpoint-files.
+_checkpoint_url = {
+    "Breakout-v0": "http://hvass-labs.org/projects/tensorflow/tutorial16/Breakout-v0.tar.gz",
+    "SpaceInvaders-v0": "http://hvass-labs.org/projects/tensorflow/tutorial16/SpaceInvaders-v0.tar.gz"
+}
+
+
+def maybe_download_checkpoint(env_name):
+    """
+    Download and extract the TensorFlow checkpoint for the given
+    environment-name, if it does not already exist in checkpoint_base_dir.
+    You should first set this dir and call update_paths().
+    """
+
+    # Get the url for the game-environment.
+    url = _checkpoint_url[env_name]
+
+    # Download and extract the file if it does not already exist.
+    download.maybe_download_and_extract(url=url,
+                                        download_dir=checkpoint_base_dir)
+
+########################################################################
+# Classes used for logging data during training.
+
+
+class Log:
+    """
+    Base-class for logging data to a text-file during training.
+
+    It is possible to use TensorFlow / TensorBoard for this,
+    but it is quite awkward to implement, as it was intended
+    for logging variables and other aspects of the TensorFlow graph.
+    We want to log the reward and Q-values which are not in that graph.
+    """
+
+    def __init__(self, file_path):
+        """Set the path for the log-file. Nothing is saved or loaded yet."""
+
+        # Path for the log-file.
+        self.file_path = file_path
+
+        # Data to be read from the log-file by the _read() function.
+        self.count_episodes = None
+        self.count_states = None
+        self.data = None
+
+    def _write(self, count_episodes, count_states, msg):
+        """
+        Write a line to the log-file. This is only called by sub-classes.
+        
+        :param count_episodes:
+            Counter for the number of episodes processed during training.
+
+        :param count_states: 
+            Counter for the number of states processed during training.
+
+        :param msg:
+            Message to write in the log.
+        """
+
+        with open(file=self.file_path, mode='a', buffering=1) as file:
+            msg_annotated = "{0}\t{1}\t{2}\n".format(count_episodes, count_states, msg)
+            file.write(msg_annotated)
+
+    def _read(self):
+        """
+        Read the log-file into memory so it can be plotted.
+
+        It sets self.count_episodes, self.count_states and self.data
+        """
+
+        # Open and read the log-file.
+        with open(self.file_path) as f:
+            reader = csv.reader(f, delimiter="\t")
+            self.count_episodes, self.count_states, *data = zip(*reader)
+
+        # Convert the remaining log-data to a NumPy float-array.
+        self.data = np.array(data, dtype='float')
+
+
+class LogReward(Log):
+    """Log the rewards obtained for episodes during training."""
+
+    def __init__(self):
+        # These will be set in read() below.
+        self.episode = None
+        self.mean = None
+
+        # Super-class init.
+        Log.__init__(self, file_path=log_reward_path)
+
+    def write(self, count_episodes, count_states, reward_episode, reward_mean):
+        """
+        Write the episode and mean reward to file.
+        
+        :param count_episodes:
+            Counter for the number of episodes processed during training.
+
+        :param count_states: 
+            Counter for the number of states processed during training.
+
+        :param reward_episode:
+            Reward for one episode.
+
+        :param reward_mean:
+            Mean reward for the last e.g. 30 episodes.
+        """
+
+        msg = "{0:.1f}\t{1:.1f}".format(reward_episode, reward_mean)
+        self._write(count_episodes=count_episodes, count_states=count_states, msg=msg)
+
+    def read(self):
+        """
+        Read the log-file into memory so it can be plotted.
+
+        It sets self.count_episodes, self.count_states, self.episode and self.mean
+        """
+
+        # Read the log-file using the super-class.
+        self._read()
+
+        # Get the episode reward.
+        self.episode = self.data[0]
+
+        # Get the mean reward.
+        self.mean = self.data[1]
+
+
+class LogQValues(Log):
+    """Log the Q-Values during training."""
+
+    def __init__(self):
+        # These will be set in read() below.
+        self.min = None
+        self.mean = None
+        self.max = None
+        self.std = None
+
+        # Super-class init.
+        Log.__init__(self, file_path=log_q_values_path)
+
+    def write(self, count_episodes, count_states, q_values):
+        """
+        Write basic statistics for the Q-values to file.
+
+        :param count_episodes:
+            Counter for the number of episodes processed during training.
+
+        :param count_states: 
+            Counter for the number of states processed during training.
+
+        :param q_values:
+            Numpy array with Q-values from the replay-memory.
+        """
+
+        msg = "{0:.3f}\t{1:.3f}\t{2:.3f}\t{3:.3f}".format(np.min(q_values),
+                                                          np.mean(q_values),
+                                                          np.max(q_values),
+                                                          np.std(q_values))
+
+        self._write(count_episodes=count_episodes,
+                    count_states=count_states,
+                    msg=msg)
+
+    def read(self):
+        """
+        Read the log-file into memory so it can be plotted.
+
+        It sets self.count_episodes, self.count_states, self.min / mean / max / std.
+        """
+
+        # Read the log-file using the super-class.
+        self._read()
+
+        # Get the logged statistics for the Q-values.
+        self.min = self.data[0]
+        self.mean = self.data[1]
+        self.max = self.data[2]
+        self.std = self.data[3]
+
+########################################################################
+
+
+def print_progress(msg):
+    """
+    Print progress on a single line and overwrite the line.
+    Used during optimization.
+    """
+
+    sys.stdout.write("\r" + msg)
+    sys.stdout.flush()
+
+########################################################################
+# A state is basically just a multi-dimensional array that is being
+# input to the Neural Network. The state consists of pre-processed images
+# from the game-environment. We will just convert the game-images to
+# gray-scale and resize them to roughly half their size. This is mainly
+# so we can save memory-space in the Replay Memory further below.
+# The original DeepMind paper used game-states consisting of 4 frames of
+# game-images that were gray-scaled, resized to 110 x 84 pixels, and then
+# cropped to 84 x 84 pixels because their implementation only supported this.
+
+# Height of each image-frame in the state.
+state_height = 105
+
+# Width of each image-frame in the state.
+state_width = 80
+
+# Size of each image in the state.
+state_img_size = np.array([state_height, state_width])
+
+# Number of images in the state.
+state_channels = 2
+
+# Shape of the state-array.
+state_shape = [state_height, state_width, state_channels]
+
+########################################################################
+# Functions and classes for processing images from the game-environment
+# and converting them into a state.
+
+
+def _rgb_to_grayscale(image):
+    """
+    Convert an RGB-image into gray-scale using a formula from Wikipedia:
+    https://en.wikipedia.org/wiki/Grayscale
+    """
+
+    # Get the separate colour-channels.
+    r, g, b = image[:, :, 0], image[:, :, 1], image[:, :, 2]
+
+    # Convert to gray-scale using the Wikipedia formula.
+    img_gray = 0.2990 * r + 0.5870 * g + 0.1140 * b
+
+    return img_gray
+
+
+def _pre_process_image(image):
+    """Pre-process a raw image from the game-environment."""
+
+    # Convert image to gray-scale.
+    img = _rgb_to_grayscale(image)
+
+    # Resize to the desired size using SciPy for convenience.
+    img = scipy.misc.imresize(img, size=state_img_size, interp='bicubic')
+
+    return img
+
+
+class MotionTracer:
+    """
+    Used for processing raw image-frames from the game-environment.
+
+    The image-frames are converted to gray-scale, resized, and then
+    the background is removed using filtering of the image-frames
+    so as to detect motions.
+
+    This is needed because a single image-frame of the game environment
+    is insufficient to determine the direction of moving objects.
+    
+    The original DeepMind implementation used the last 4 image-frames
+    of the game-environment to allow the Neural Network to learn how
+    to detect motion. This implementation could make it a little easier
+    for the Neural Network to learn how to detect motion, but it has
+    only been tested on Breakout and Space Invaders, and may not work
+    for games with more complicated graphics such as Doom. This remains
+    to be tested.
+    """
+
+    def __init__(self, image, decay=0.75):
+        """
+        
+        :param image:
+            First image from the game-environment,
+            used for resetting the motion detector.
+
+        :param decay:
+            Parameter for how long the tail should be on the motion-trace.
+            This is a float between 0.0 and 1.0 where higher values means
+            the trace / tail is longer.
+        """
+
+        # Pre-process the image and save it for later use.
+        # The input image may be 8-bit integers but internally
+        # we need to use floating-point to avoid image-noise
+        # caused by recurrent rounding-errors.
+        img = _pre_process_image(image=image)
+        self.last_input = img.astype(np.float)
+
+        # Set the last output to zero.
+        self.last_output = np.zeros_like(img)
+
+        self.decay = decay
+
+    def process(self, image):
+        """Process a raw image-frame from the game-environment."""
+
+        # Pre-process the image so it is gray-scale and resized.
+        img = _pre_process_image(image=image)
+
+        # Subtract the previous input. This only leaves the
+        # pixels that have changed in the two image-frames.
+        img_dif = img - self.last_input
+
+        # Copy the contents of the input-image to the last input.
+        self.last_input[:] = img[:]
+
+        # If the pixel-difference is greater than a threshold then
+        # set the output pixel-value to the highest value (white),
+        # otherwise set the output pixel-value to the lowest value (black).
+        # So that we merely detect motion, and don't care about details.
+        img_motion = np.where(np.abs(img_dif) > 20, 255.0, 0.0)
+
+        # Add some of the previous output. This recurrent formula
+        # is what gives the trace / tail.
+        output = img_motion + self.decay * self.last_output
+
+        # Ensure the pixel-values are within the allowed bounds.
+        output = np.clip(output, 0.0, 255.0)
+
+        # Set the last output.
+        self.last_output = output
+
+        return output
+
+    def get_state(self):
+        """
+        Get a state that can be used as input to the Neural Network.
+
+        It is basically just the last input and the last output of the
+        motion-tracer. This means it is the last image-frame of the
+        game-environment, as well as the motion-trace. This shows
+        the current location of all the objects in the game-environment
+        as well as trajectories / traces of where they have been.
+        """
+
+        # Stack the last input and output images.
+        state = np.dstack([self.last_input, self.last_output])
+
+        # Convert to 8-bit integer.
+        # This is done to save space in the replay-memory.
+        state = state.astype(np.uint8)
+
+        return state
+
+########################################################################
+
+
+class ReplayMemory:
+    """
+    The replay-memory holds many previous states of the game-environment.
+    This helps stabilize training of the Neural Network because the data
+    is more diverse when sampled over thousands of different states.
+    """
+
+    def __init__(self, size, num_actions, discount_factor=0.97):
+        """
+        
+        :param size:
+            Capacity of the replay-memory. This is the number of states.
+
+        :param num_actions:
+            Number of possible actions in the game-environment. 
+
+        :param discount_factor:
+            Discount-factor used for updating Q-values.
+        """
+
+        # Array for the previous states of the game-environment.
+        self.states = np.zeros(shape=[size] + state_shape, dtype=np.uint8)
+
+        # Array for the Q-values corresponding to the states.
+        self.q_values = np.zeros(shape=[size, num_actions], dtype=np.float)
+
+        # Array for the Q-values before being updated.
+        # This is used to compare the Q-values before and after the update.
+        self.q_values_old = np.zeros(shape=[size, num_actions], dtype=np.float)
+
+        # Actions taken for each of the states in the memory.
+        self.actions = np.zeros(shape=size, dtype=np.int)
+
+        # Rewards observed for each of the states in the memory.
+        self.rewards = np.zeros(shape=size, dtype=np.float)
+
+        # Whether the life had ended in each state of the game-environment.
+        self.end_life = np.zeros(shape=size, dtype=np.bool)
+
+        # Whether the episode had ended (aka. game over) in each state.
+        self.end_episode = np.zeros(shape=size, dtype=np.bool)
+
+        # Estimation errors for the Q-values. This is used to balance
+        # the sampling of batches for training the Neural Network,
+        # so we get a balanced combination of states with high and low
+        # estimation errors for their Q-values.
+        self.estimation_errors = np.zeros(shape=size, dtype=np.float)
+
+        # Capacity of the replay-memory as the number of states.
+        self.size = size
+
+        # Discount-factor for calculating Q-values.
+        self.discount_factor = discount_factor
+
+        # Reset the number of used states in the replay-memory.
+        self.num_used = 0
+
+        # Threshold for splitting between low and high estimation errors.
+        self.error_threshold = 0.1
+
+    def is_full(self):
+        """Return boolean whether the replay-memory is full."""
+        return self.num_used == self.size
+
+    def used_fraction(self):
+        """Return the fraction of the replay-memory that is used."""
+        return self.num_used / self.size
+
+    def reset(self):
+        """Reset the replay-memory so it is empty."""
+        self.num_used = 0
+
+    def add(self, state, q_values, action, reward, end_life, end_episode):
+        """
+        Add an observed state from the game-environment, along with the
+        estimated Q-values, action taken, observed reward, etc. 
+        
+        :param state:
+            Current state of the game-environment.
+            This is the output of the MotionTracer-class.
+
+        :param q_values: 
+            The estimated Q-values for the state.
+
+        :param action: 
+            The action taken by the agent in this state of the game.
+
+        :param reward:
+            The reward that was observed from taking this action
+            and moving to the next state.
+
+        :param end_life:
+            Boolean whether the agent has lost a life in this state.
+         
+        :param end_episode: 
+            Boolean whether the agent has lost all lives aka. game over
+            aka. end of episode.
+        """
+
+        if not self.is_full():
+            # Index into the arrays for convenience.
+            k = self.num_used
+
+            # Increase the number of used elements in the replay-memory.
+            self.num_used += 1
+
+            # Store all the values in the replay-memory.
+            self.states[k] = state
+            self.q_values[k] = q_values
+            self.actions[k] = action
+            self.end_life[k] = end_life
+            self.end_episode[k] = end_episode
+
+            # Note that the reward is limited. This is done to stabilize
+            # the training of the Neural Network.
+            self.rewards[k] = np.clip(reward, -1.0, 1.0)
+
+    def update_all_q_values(self):
+        """
+        Update all Q-values in the replay-memory.
+        
+        When states and Q-values are added to the replay-memory, the
+        Q-values have been estimated by the Neural Network. But we now
+        have more data available that we can use to improve the estimated
+        Q-values, because we now know which actions were taken and the
+        observed rewards. We sweep backwards through the entire replay-memory
+        to use the observed data to improve the estimated Q-values.
+        """
+
+        # Copy old Q-values so we can print their statistics later.
+        # Note that the contents of the arrays are copied.
+        self.q_values_old[:] = self.q_values[:]
+
+        # Process the replay-memory backwards and update the Q-values.
+        # This loop could be implemented entirely in NumPy for higher speed,
+        # but it is probably only a small fraction of the overall time usage,
+        # and it is much easier to understand when implemented like this.
+        for k in reversed(range(self.num_used-1)):
+            # Get the data for the k'th state in the replay-memory.
+            action = self.actions[k]
+            reward = self.rewards[k]
+            end_life = self.end_life[k]
+            end_episode = self.end_episode[k]
+
+            # Calculate the Q-value for the action that was taken in this state.
+            if end_life or end_episode:
+                # If the agent lost a life or it was game over / end of episode,
+                # then the value of taking the given action is just the reward
+                # that was observed in this single step. This is because the
+                # Q-value is defined as the discounted value of all future game
+                # steps in a single life of the agent. When the life has ended,
+                # there will be no future steps.
+                action_value = reward
+            else:
+                # Otherwise the value of taking the action is the reward that
+                # we have observed plus the discounted value of future rewards
+                # from continuing the game. We use the estimated Q-values for
+                # the following state and take the maximum, because we will
+                # generally take the action that has the highest Q-value.
+                action_value = reward + self.discount_factor * np.max(self.q_values[k + 1])
+
+            # Error of the Q-value that was estimated using the Neural Network.
+            self.estimation_errors[k] = abs(action_value - self.q_values[k, action])
+
+            # Update the Q-value with the better estimate.
+            self.q_values[k, action] = action_value
+
+        self.print_statistics()
+
+    def prepare_sampling_prob(self, batch_size=128):
+        """
+        Prepare the probability distribution for random sampling of states
+        and Q-values for use in training of the Neural Network.
+
+        The probability distribution is just a simple binary split of the
+        replay-memory based on the estimation errors of the Q-values.
+        The idea is to create a batch of samples that are balanced somewhat
+        evenly between Q-values that the Neural Network already knows how to
+        estimate quite well because they have low estimation errors, and
+        Q-values that are poorly estimated by the Neural Network because
+        they have high estimation errors.
+        
+        The reason for this balancing of Q-values with high and low estimation
+        errors, is that if we train the Neural Network mostly on data with
+        high estimation errors, then it will tend to forget what it already
+        knows and hence become over-fit so the training becomes unstable.
+        """
+
+        # Get the errors between the Q-values that were estimated using
+        # the Neural Network, and the Q-values that were updated with the
+        # reward that was actually observed when an action was taken.
+        err = self.estimation_errors[0:self.num_used]
+
+        # Create an index of the estimation errors that are low.
+        idx = err<self.error_threshold
+        self.idx_err_lo = np.squeeze(np.where(idx))
+
+        # Create an index of the estimation errors that are high.
+        self.idx_err_hi = np.squeeze(np.where(np.logical_not(idx)))
+
+        # Probability of sampling Q-values with high estimation errors.
+        # This is either set to the fraction of the replay-memory that
+        # has high estimation errors - or it is set to 0.5. So at least
+        # half of the batch has high estimation errors.
+        prob_err_hi = len(self.idx_err_hi) / self.num_used
+        prob_err_hi = max(prob_err_hi, 0.5)
+
+        # Number of samples in a batch that have high estimation errors.
+        self.num_samples_err_hi = int(prob_err_hi * batch_size)
+
+        # Number of samples in a batch that have low estimation errors.
+        self.num_samples_err_lo = batch_size - self.num_samples_err_hi
+
+    def random_batch(self):
+        """
+        Get a random batch of states and Q-values from the replay-memory.
+        You must call prepare_sampling_prob() before calling this function,
+        which also sets the batch-size.
+
+        The batch has been balanced so it contains states and Q-values
+        that have both high and low estimation errors for the Q-values.
+        This is done to both speed up and stabilize training of the
+        Neural Network.
+        """
+
+        # Random index of states and Q-values in the replay-memory.
+        # These have LOW estimation errors for the Q-values.
+        idx_lo = np.random.choice(self.idx_err_lo,
+                                  size=self.num_samples_err_lo,
+                                  replace=False)
+
+        # Random index of states and Q-values in the replay-memory.
+        # These have HIGH estimation errors for the Q-values.
+        idx_hi = np.random.choice(self.idx_err_hi,
+                                  size=self.num_samples_err_hi,
+                                  replace=False)
+
+        # Combine the indices.
+        idx = np.concatenate((idx_lo, idx_hi))
+
+        # Get the batches of states and Q-values.
+        states_batch = self.states[idx]
+        q_values_batch = self.q_values[idx]
+
+        return states_batch, q_values_batch
+
+    def all_batches(self, batch_size=128):
+        """
+        Iterator for all the states and Q-values in the replay-memory.
+        It returns the indices for the beginning and end, as well as
+        a progress-counter between 0.0 and 1.0.
+        
+        This function is not currently being used except by the function
+        estimate_all_q_values() below. These two functions are merely
+        included to make it easier for you to experiment with the code
+        by showing you an easy and efficient way to loop over all the
+        data in the replay-memory.
+        """
+
+        # Start index for the current batch.
+        begin = 0
+
+        # Repeat until all batches have been processed.
+        while begin < self.num_used:
+            # End index for the current batch.
+            end = begin + batch_size
+
+            # Ensure the batch does not exceed the used replay-memory.
+            if end > self.num_used:
+                end = self.num_used
+
+            # Progress counter.
+            progress = end / self.num_used
+
+            # Yield the batch indices and completion-counter.
+            yield begin, end, progress
+
+            # Set the start-index for the next batch to the end of this batch.
+            begin = end
+
+    def estimate_all_q_values(self, model):
+        """
+        Estimate all Q-values for the states in the replay-memory
+        using the model / Neural Network.
+
+        Note that this function is not currently being used. It is provided
+        to make it easier for you to experiment with this code, by showing
+        you an efficient way to iterate over all the states and Q-values.
+
+        :param model:
+            Instance of the NeuralNetwork-class.
+        """
+
+        print("Re-calculating all Q-values in replay memory ...")
+
+        # Process the entire replay-memory in batches.
+        for begin, end, progress in self.all_batches():
+            # Print progress.
+            msg = "\tProgress: {0:.0%}"
+            msg = msg.format(progress)
+            print_progress(msg)
+
+            # Get the states for the current batch.
+            states = self.states[begin:end]
+
+            # Calculate the Q-values using the Neural Network
+            # and update the replay-memory.
+            self.q_values[begin:end] = model.get_q_values(states=states)
+
+        # Newline.
+        print()
+
+    def print_statistics(self):
+        """Print statistics for the contents of the replay-memory."""
+
+        print("Replay-memory statistics:")
+
+        # Print statistics for the Q-values before they were updated
+        # in update_all_q_values().
+        msg = "\tQ-values Before, Min: {0:5.2f}, Mean: {1:5.2f}, Max: {2:5.2f}"
+        print(msg.format(np.min(self.q_values_old),
+                         np.mean(self.q_values_old),
+                         np.max(self.q_values_old)))
+
+        # Print statistics for the Q-values after they were updated
+        # in update_all_q_values().
+        msg = "\tQ-values After,  Min: {0:5.2f}, Mean: {1:5.2f}, Max: {2:5.2f}"
+        print(msg.format(np.min(self.q_values),
+                         np.mean(self.q_values),
+                         np.max(self.q_values)))
+
+        # Print statistics for the difference in Q-values before and
+        # after the update in update_all_q_values().
+        q_dif = self.q_values - self.q_values_old
+        msg = "\tQ-values Diff.,  Min: {0:5.2f}, Mean: {1:5.2f}, Max: {2:5.2f}"
+        print(msg.format(np.min(q_dif),
+                         np.mean(q_dif),
+                         np.max(q_dif)))
+
+        # Print statistics for the number of large estimation errors.
+        # Don't use the estimation error for the last state in the memory,
+        # because its Q-values have not been updated.
+        err = self.estimation_errors[:-1]
+        err_count = np.count_nonzero(err > self.error_threshold)
+        msg = "\tNumber of large errors > {0}: {1} / {2} ({3:.1%})"
+        print(msg.format(self.error_threshold, err_count,
+                         self.num_used, err_count / self.num_used))
+
+        # How much of the replay-memory is used by states with end_life.
+        end_life_pct = np.count_nonzero(self.end_life) / self.num_used
+
+        # How much of the replay-memory is used by states with end_episode.
+        end_episode_pct = np.count_nonzero(self.end_episode) / self.num_used
+
+        # How much of the replay-memory is used by states with non-zero reward.
+        reward_nonzero_pct = np.count_nonzero(self.rewards) / self.num_used
+
+        # Print those statistics.
+        msg = "\tend_life: {0:.1%}, end_episode: {1:.1%}, reward non-zero: {2:.1%}"
+        print(msg.format(end_life_pct, end_episode_pct, reward_nonzero_pct))
+
+########################################################################
+
+
+class LinearControlSignal:
+    """
+    A control signal that changes linearly over time.
+
+    This is used to change e.g. the learning-rate for the optimizer
+    of the Neural Network, as well as other parameters.
+    
+    TensorFlow has functionality for doing this, but it uses the
+    global_step counter inside the TensorFlow graph, while we
+    want the control signals to use a state-counter for the
+    game-environment. So it is easier to make this in Python.
+    """
+
+    def __init__(self, start_value, end_value, num_iterations, repeat=False):
+        """
+        Create a new object.
+
+        :param start_value:
+            Start-value for the control signal.
+
+        :param end_value:
+            End-value for the control signal.
+
+        :param num_iterations:
+            Number of iterations it takes to reach the end_value
+            from the start_value.
+
+        :param repeat:
+            Boolean whether to reset the control signal back to the start_value
+            after the end_value has been reached.
+        """
+
+        # Store arguments in this object.
+        self.start_value = start_value
+        self.end_value = end_value
+        self.num_iterations = num_iterations
+        self.repeat = repeat
+
+        # Calculate the linear coefficient.
+        self._coefficient = (end_value - start_value) / num_iterations
+
+    def get_value(self, iteration):
+        """Get the value of the control signal for the given iteration."""
+
+        if self.repeat:
+            iteration %= self.num_iterations
+
+        if iteration < self.num_iterations:
+            value = iteration * self._coefficient + self.start_value
+        else:
+            value = self.end_value
+
+        return value
+
+########################################################################
+
+
+class EpsilonGreedy:
+    """
+    The epsilon-greedy policy either takes a random action with
+    probability epsilon, or it takes the action for the highest
+    Q-value.
+    
+    If epsilon is 1.0 then the actions are always random.
+    If epsilon is 0.0 then the actions are always argmax for the Q-values.
+
+    Epsilon is typically decreased linearly from 1.0 to 0.1
+    and this is also implemented in this class.
+
+    During testing, epsilon is usually chosen lower, e.g. 0.05 or 0.01
+    """
+
+    def __init__(self, num_actions,
+                 epsilon_testing=0.05,
+                 num_iterations=1e6,
+                 start_value=1.0, end_value=0.1,
+                 repeat=False):
+        """
+        
+        :param num_actions:
+            Number of possible actions in the game-environment.
+
+        :param epsilon_testing:
+            Epsilon-value when testing.
+
+        :param num_iterations:
+            Number of training iterations required to linearly
+            decrease epsilon from start_value to end_value.
+            
+        :param start_value:
+            Starting value for linearly decreasing epsilon.
+
+        :param end_value:
+            Ending value for linearly decreasing epsilon.
+
+        :param repeat:
+            Boolean whether to repeat and restart the linear decrease
+            when the end_value is reached, or only do it once and then
+            output the end_value forever after.
+        """
+
+        # Store parameters.
+        self.num_actions = num_actions
+        self.epsilon_testing = epsilon_testing
+
+        # Create a control signal for linearly decreasing epsilon.
+        self.epsilon_linear = LinearControlSignal(num_iterations=num_iterations,
+                                                  start_value=start_value,
+                                                  end_value=end_value,
+                                                  repeat=repeat)
+
+    def get_epsilon(self, iteration, training):
+        """
+        Return the epsilon for the given iteration.
+        If training==True then epsilon is linearly decreased,
+        otherwise epsilon is a fixed number.
+        """
+
+        if training:
+            epsilon = self.epsilon_linear.get_value(iteration=iteration)
+        else:
+            epsilon = self.epsilon_testing
+
+        return epsilon
+
+    def get_action(self, q_values, iteration, training):
+        """
+        Use the epsilon-greedy policy to select an action.
+        
+        :param q_values:
+            These are the Q-values that are estimated by the Neural Network
+            for the current state of the game-environment.
+         
+        :param iteration:
+            This is an iteration counter. Here we use the number of states
+            that has been processed in the game-environment.
+
+        :param training:
+            Boolean whether we are training or testing the
+            Reinforcement Learning agent.
+
+        :return:
+            action (integer), epsilon (float)
+        """
+
+        epsilon = self.get_epsilon(iteration=iteration, training=training)
+
+        # With probability epsilon.
+        if np.random.random() < epsilon:
+            # Select a random action.
+            action = np.random.randint(low=0, high=self.num_actions)
+        else:
+            # Otherwise select the action that has the highest Q-value.
+            action = np.argmax(q_values)
+
+        return action, epsilon
+
+########################################################################
+
+
+class NeuralNetwork:
+    """
+    Creates a Neural Network for Reinforcement Learning (Q-Learning).
+
+    Functions are provided for estimating Q-values from states of the
+    game-environment, and for optimizing the Neural Network so it becomes
+    better at estimating the Q-values.
+    """
+
+    def __init__(self, num_actions, replay_memory):
+        """
+        :param num_actions:
+            Number of discrete actions for the game-environment.
+
+        :param replay_memory: 
+            Object-instance of the ReplayMemory-class.
+        """
+
+        # Replay-memory used for sampling random batches.
+        self.replay_memory = replay_memory
+
+        # Path for saving/restoring checkpoints.
+        self.checkpoint_path = os.path.join(checkpoint_dir, "checkpoint")
+
+        # Placeholder variable for inputting states into the Neural Network.
+        # A state is a multi-dimensional array holding image-frames from
+        # the game-environment.
+        self.x = tf.placeholder(dtype=tf.float32, shape=[None] + state_shape, name='x')
+
+        # Placeholder variable for inputting the learning-rate to the optimizer.
+        self.learning_rate = tf.placeholder(dtype=tf.float32, shape=[])
+
+        # Placeholder variable for inputting the target Q-values
+        # that we want the Neural Network to be able to estimate.
+        self.q_values_new = tf.placeholder(tf.float32,
+                                           shape=[None, num_actions],
+                                           name='q_values_new')
+
+        # This is a hack that allows us to save/load the counter for
+        # the number of states processed in the game-environment.
+        # We will keep it as a variable in the TensorFlow-graph
+        # even though it will not actually be used by TensorFlow.
+        self.count_states = tf.Variable(initial_value=0,
+                                        trainable=False, dtype=tf.int64,
+                                        name='count_states')
+
+        # Similarly, this is the counter for the number of episodes.
+        self.count_episodes = tf.Variable(initial_value=0,
+                                          trainable=False, dtype=tf.int64,
+                                          name='count_episodes')
+
+        # TensorFlow operation for increasing count_states.
+        self.count_states_increase = tf.assign(self.count_states,
+                                               self.count_states + 1)
+
+        # TensorFlow operation for increasing count_episodes.
+        self.count_episodes_increase = tf.assign(self.count_episodes,
+                                                 self.count_episodes + 1)
+
+        # Initializer for the layers in the Neural Network.
+        # If you change the architecture of the network, particularly
+        # if you add or remove layers, then you may have to change
+        # the stddev-parameter here. The initial weights must result
+        # in the Neural Network outputting Q-values that are very close
+        # to zero - but the network weights must not be too low either
+        # because it will make it hard to train the network.
+        # You can experiment with values between 1e-2 and 1e-3.
+        init = tf.truncated_normal_initializer(mean=0.0, stddev=2e-2)
+
+        # Wrap the input to the Neural Network in a PrettyTensor object.
+        x_pretty = pt.wrap(self.x)
+
+        # Create the convolutional Neural Network using Pretty Tensor.
+        with pt.defaults_scope(activation_fn=tf.nn.relu):
+            self.q_values = x_pretty. \
+                conv2d(kernel=3, depth=16, stride=2, name='layer_conv1', weights=init). \
+                conv2d(kernel=3, depth=32, stride=2, name='layer_conv2', weights=init). \
+                conv2d(kernel=3, depth=64, stride=1, name='layer_conv3', weights=init). \
+                flatten(). \
+                fully_connected(size=1024, name='layer_fc1', weights=init). \
+                fully_connected(size=1024, name='layer_fc2', weights=init). \
+                fully_connected(size=1024, name='layer_fc3', weights=init). \
+                fully_connected(size=1024, name='layer_fc4', weights=init). \
+                fully_connected(size=num_actions, name='layer_fc_out', weights=init,
+                                activation_fn=None)
+
+        # Note that the architecture of this Neural Network is very
+        # different from that used in the original DeepMind papers,
+        # which were something like this:
+        # Input image:      84 x 84 x 4 (4 gray-scale images of 84 x 84 pixels).
+        # Conv layer 1:     16 filters 8 x 8, stride 4, relu.
+        # Conv layer 2:     32 filters 4 x 4, stride 2, relu.
+        # Fully-conn. 1:    256 units, relu. (Sometimes 512 units).
+        # Fully-conn. 2:    num-action units, linear.
+
+        # The DeepMind architecture does a very aggressive downsampling of
+        # the input images so they are about 10 x 10 pixels after the final
+        # convolutional layer. I found that this resulted in significantly
+        # distorted Q-values when using the training method further below.
+        # The reason DeepMind could get it working was perhaps that they
+        # used a very large replay memory (5x as big as here), and a single
+        # optimization iteration was performed after each step of the game,
+        # and some more tricks.
+
+        # Loss-function which must be optimized. This the mean-squared error
+        # between the Q-values that are output by the Neural Network
+        # and the target Q-values.
+        self.loss = self.q_values.l2_regression(target=self.q_values_new)
+
+        # Optimizer used for minimizing the loss-function.
+        # Note the learning-rate is a placeholder variable so we can
+        # lower the learning-rate as optimization progresses.
+        self.optimizer = tf.train.RMSPropOptimizer(learning_rate=self.learning_rate).minimize(self.loss)
+
+        # Used for saving and loading checkpoints.
+        self.saver = tf.train.Saver()
+
+        # Create a new TensorFlow session so we can run the Neural Network.
+        self.session = tf.Session()
+
+        # Load the most recent checkpoint if it exists,
+        # otherwise initialize all the variables in the TensorFlow graph.
+        self.load_checkpoint()
+
+    def close(self):
+        """Close the TensorFlow session."""
+        self.session.close()
+
+    def load_checkpoint(self):
+        """
+        Load all variables of the TensorFlow graph from a checkpoint.
+        If the checkpoint does not exist, then initialize all variables.
+        """
+
+        try:
+            print("Trying to restore last checkpoint ...")
+
+            # Use TensorFlow to find the latest checkpoint - if any.
+            last_chk_path = tf.train.latest_checkpoint(checkpoint_dir=checkpoint_dir)
+
+            # Try and load the data in the checkpoint.
+            self.saver.restore(self.session, save_path=last_chk_path)
+
+            # If we get to this point, the checkpoint was successfully loaded.
+            print("Restored checkpoint from:", last_chk_path)
+        except:
+            # If the above failed for some reason, simply
+            # initialize all the variables for the TensorFlow graph.
+            print("Failed to restore checkpoint from:", checkpoint_dir)
+            print("Initializing variables instead.")
+            self.session.run(tf.global_variables_initializer())
+
+    def save_checkpoint(self, current_iteration):
+        """Save all variables of the TensorFlow graph to a checkpoint."""
+
+        self.saver.save(self.session,
+                        save_path=self.checkpoint_path,
+                        global_step=current_iteration)
+
+        print("Saved checkpoint.")
+
+    def get_q_values(self, states):
+        """
+        Calculate and return the estimated Q-values for the given states.
+
+        A single state contains two images (or channels): The most recent
+        image-frame from the game-environment, and a motion-tracing image.
+        See the MotionTracer-class for details.
+
+        The input to this function is an array of such states which allows
+        for batch-processing of the states. So the input is a 4-dim
+        array with shape: [batch, height, width, state_channels].
+        
+        The output of this function is an array of Q-value-arrays.
+        There is a Q-value for each possible action in the game-environment.
+        So the output is a 2-dim array with shape: [batch, num_actions]
+        """
+
+        # Create a feed-dict for inputting the states to the Neural Network.
+        feed_dict = {self.x: states}
+
+        # Use TensorFlow to calculate the estimated Q-values for these states.
+        values = self.session.run(self.q_values, feed_dict=feed_dict)
+
+        return values
+
+    def optimize(self, min_epochs=1.0, max_epochs=10,
+                 batch_size=128, loss_limit=0.015,
+                 learning_rate=1e-3):
+        """
+        Optimize the Neural Network by sampling states and Q-values
+        from the replay-memory.
+
+        The original DeepMind paper performed one optimization iteration
+        after processing each new state of the game-environment. This is
+        an un-natural way of doing optimization of Neural Networks.
+
+        So instead we perform a full optimization run every time the
+        Replay Memory is full (or it is filled to the desired fraction).
+        This also gives more efficient use of a GPU for the optimization.
+
+        The problem is that this may over-fit the Neural Network to whatever
+        is in the replay-memory. So we use several tricks to try and adapt
+        the number of optimization iterations.
+
+        :param min_epochs:
+            Minimum number of optimization epochs. One epoch corresponds
+            to the replay-memory being used once. However, as the batches
+            are sampled randomly and biased somewhat, we may not use the
+            whole replay-memory. This number is just a convenient measure.
+
+        :param max_epochs:
+            Maximum number of optimization epochs.
+
+        :param batch_size:
+            Size of each random batch sampled from the replay-memory.
+
+        :param loss_limit:
+            Optimization continues until the average loss-value of the
+            last 100 batches is below this value (or max_epochs is reached).
+
+        :param learning_rate:
+            Learning-rate to use for the optimizer.
+        """
+
+        print("Optimizing Neural Network to better estimate Q-values ...")
+        print("\tLearning-rate: {0:.1e}".format(learning_rate))
+        print("\tLoss-limit: {0:.3f}".format(loss_limit))
+        print("\tMax epochs: {0:.1f}".format(max_epochs))
+
+        # Prepare the probability distribution for sampling the replay-memory.
+        self.replay_memory.prepare_sampling_prob(batch_size=batch_size)
+
+        # Number of optimization iterations corresponding to one epoch.
+        iterations_per_epoch = self.replay_memory.num_used / batch_size
+
+        # Minimum number of iterations to perform.
+        min_iterations = int(iterations_per_epoch * min_epochs)
+
+        # Maximum number of iterations to perform.
+        max_iterations = int(iterations_per_epoch * max_epochs)
+
+        # Buffer for storing the loss-values of the most recent batches.
+        loss_history = np.zeros(100, dtype=float)
+
+        for i in range(max_iterations):
+            # Randomly sample a batch of states and target Q-values
+            # from the replay-memory. These are the Q-values that we
+            # want the Neural Network to be able to estimate.
+            state_batch, q_values_batch = self.replay_memory.random_batch()
+
+            # Create a feed-dict for inputting the data to the TensorFlow graph.
+            # Note that the learning-rate is also in this feed-dict.
+            feed_dict = {self.x: state_batch,
+                         self.q_values_new: q_values_batch,
+                         self.learning_rate: learning_rate}
+
+            # Perform one optimization step and get the loss-value.
+            loss_val, _ = self.session.run([self.loss, self.optimizer],
+                                           feed_dict=feed_dict)
+
+            # Shift the loss-history and assign the new value.
+            # This causes the loss-history to only hold the most recent values.
+            loss_history = np.roll(loss_history, 1)
+            loss_history[0] = loss_val
+
+            # Calculate the average loss for the previous batches.
+            loss_mean = np.mean(loss_history)
+
+            # Print status.
+            pct_epoch = i / iterations_per_epoch
+            msg = "\tIteration: {0} ({1:.2f} epoch), Batch loss: {2:.4f}, Mean loss: {3:.4f}"
+            msg = msg.format(i, pct_epoch, loss_val, loss_mean)
+            print_progress(msg)
+
+            # Stop the optimization if we have performed the required number
+            # of iterations and the loss-value is sufficiently low.
+            if i > min_iterations and loss_mean < loss_limit:
+                break
+
+        # Print newline.
+        print()
+
+    def get_weights_variable(self, layer_name):
+        """
+        Return the variable inside the TensorFlow graph for the weights
+        in the layer with the given name.
+
+        Note that the actual values of the variables are not returned,
+        you must use the function get_variable_value() for that.
+        """
+
+        with tf.variable_scope(layer_name, reuse=True):
+            variable = tf.get_variable('weights')
+
+        return variable
+
+    def get_variable_value(self, variable):
+        """Return the value of a variable inside the TensorFlow graph."""
+
+        weights = self.session.run(variable)
+
+        return weights
+
+    def get_layer_tensor(self, layer_name):
+        """
+        Return the tensor for the output of a layer.
+        Note that this does not return the actual values,
+        but instead returns a reference to the tensor
+        inside the TensorFlow graph. Use get_tensor_value()
+        to get the actual contents of the tensor.
+        """
+
+        # The name of the last operation of a layer,
+        # assuming it uses Relu as the activation-function.
+        tensor_name = layer_name + "/Relu:0"
+
+        # Get the tensor with this name.
+        tensor = tf.get_default_graph().get_tensor_by_name(tensor_name)
+
+        return tensor
+
+    def get_tensor_value(self, tensor, state):
+        """Get the value of a tensor in the Neural Network."""
+
+        # Create a feed-dict for inputting the state to the Neural Network.
+        feed_dict = {self.x: [state]}
+
+        # Run the TensorFlow session to calculate the value of the tensor.
+        output = self.session.run(tensor, feed_dict=feed_dict)
+
+        return output
+
+    def get_count_states(self):
+        """
+        Get the number of states that has been processed in the game-environment.
+        This is not used by the TensorFlow graph. It is just a hack to save and
+        reload the counter along with the checkpoint-file.
+        """
+        return self.session.run(self.count_states)
+
+    def get_count_episodes(self):
+        """
+        Get the number of episodes that has been processed in the game-environment.
+        """
+        return self.session.run(self.count_episodes)
+
+    def increase_count_states(self):
+        """
+        Increase the number of states that has been processed
+        in the game-environment.
+        """
+        return self.session.run(self.count_states_increase)
+
+    def increase_count_episodes(self):
+        """
+        Increase the number of episodes that has been processed
+        in the game-environment.
+        """
+        return self.session.run(self.count_episodes_increase)
+
+########################################################################
+
+
+class Agent:
+    """
+    This implements the function for running the game-environment with
+    an agent that uses Reinforcement Learning. This class also creates
+    instances of the Replay Memory and Neural Network.
+    """
+
+    def __init__(self, env_name, training, render=False, use_logging=True):
+        """
+        Create an object-instance. This also creates a new object for the
+        Replay Memory and the Neural Network.
+        
+        Replay Memory will only be allocated if training==True.
+
+        :param env_name:
+            Name of the game-environment in OpenAI Gym.
+            Examples: 'Breakout-v0' and 'SpaceInvaders-v0'
+
+        :param training:
+            Boolean whether to train the agent and Neural Network (True),
+            or test the agent by playing a number of episodes of the game (False).
+        
+        :param render:
+            Boolean whether to render the game-images to screen during testing.
+
+        :param use_logging:
+            Boolean whether to use logging to text-files during training.
+        """
+
+        # Create the game-environment using OpenAI Gym.
+        self.env = gym.make(env_name)
+
+        # The number of possible actions that the agent may take in every step.
+        self.num_actions = self.env.action_space.n
+
+        # Whether we are training (True) or testing (False).
+        self.training = training
+
+        # Whether to render each image-frame of the game-environment to screen.
+        self.render = render
+
+        # Whether to use logging during training.
+        self.use_logging = use_logging
+
+        if self.use_logging and self.training:
+            # Used for logging Q-values and rewards during training.
+            self.log_q_values = LogQValues()
+            self.log_reward = LogReward()
+        else:
+            self.log_q_values = None
+            self.log_reward = None
+
+        # List of string-names for the actions in the game-environment.
+        self.action_names = self.env.unwrapped.get_action_meanings()
+
+        # Epsilon-greedy policy for selecting an action from the Q-values.
+        # During training the epsilon is decreased linearly over the given
+        # number of iterations. During testing the fixed epsilon is used.
+        self.epsilon_greedy = EpsilonGreedy(start_value=1.0,
+                                            end_value=0.1,
+                                            num_iterations=1e6,
+                                            num_actions=self.num_actions,
+                                            epsilon_testing=0.01)
+
+        if self.training:
+            # The following control-signals are only used during training.
+
+            # The learning-rate for the optimizer decreases linearly.
+            self.learning_rate_control = LinearControlSignal(start_value=1e-3,
+                                                             end_value=1e-5,
+                                                             num_iterations=5e6)
+
+            # The loss-limit is used to abort the optimization whenever the
+            # mean batch-loss falls below this limit.
+            self.loss_limit_control = LinearControlSignal(start_value=0.1,
+                                                          end_value=0.015,
+                                                          num_iterations=5e6)
+
+            # The maximum number of epochs to perform during optimization.
+            # This is increased from 5 to 10 epochs, because it was found for
+            # the Breakout-game that too many epochs could be harmful early
+            # in the training, as it might cause over-fitting.
+            # Later in the training we would occasionally get rare events
+            # and would therefore have to optimize for more iterations
+            # because the learning-rate had been decreased.
+            self.max_epochs_control = LinearControlSignal(start_value=5.0,
+                                                          end_value=10.0,
+                                                          num_iterations=5e6)
+
+            # The fraction of the replay-memory to be used.
+            # Early in the training, we want to optimize more frequently
+            # so the Neural Network is trained faster and the Q-values
+            # are learned and updated more often. Later in the training,
+            # we need more samples in the replay-memory to have sufficient
+            # diversity, otherwise the Neural Network will over-fit.
+            self.replay_fraction = LinearControlSignal(start_value=0.1,
+                                                       end_value=1.0,
+                                                       num_iterations=5e6)
+        else:
+            # We set these objects to None when they will not be used.
+            self.learning_rate_control = None
+            self.loss_limit_control = None
+            self.max_epochs_control = None
+            self.replay_fraction = None
+
+        if self.training:
+            # We only create the replay-memory when we are training the agent,
+            # because it requires a lot of RAM. The image-frames from the
+            # game-environment are resized to 105 x 80 pixels gray-scale,
+            # and each state has 2 channels (one for the recent image-frame
+            # of the game-environment, and one for the motion-trace).
+            # Each pixel is 1 byte, so this replay-memory needs more than
+            # 3 GB RAM (105 x 80 x 2 x 200000 bytes).
+
+            self.replay_memory = ReplayMemory(size=200000,
+                                              num_actions=self.num_actions)
+        else:
+            self.replay_memory = None
+
+        # Create the Neural Network used for estimating Q-values.
+        self.model = NeuralNetwork(num_actions=self.num_actions,
+                                   replay_memory=self.replay_memory)
+
+        # Log of the rewards obtained in each episode during calls to run()
+        self.episode_rewards = []
+
+    def reset_episode_rewards(self):
+        """Reset the log of episode-rewards."""
+        self.episode_rewards = []
+
+    def get_action_name(self, action):
+        """Return the name of an action."""
+        return self.action_names[action]
+
+    def get_lives(self):
+        """Get the number of lives the agent has in the game-environment."""
+        return self.env.unwrapped.ale.lives()
+
+    def run(self, num_episodes=None):
+        """
+        Run the game-environment and use the Neural Network to decide
+        which actions to take in each step through Q-value estimates.
+        
+        :param num_episodes: 
+            Number of episodes to process in the game-environment.
+            If None then continue forever. This is useful during training
+            where you might want to stop the training using Ctrl-C instead.
+        """
+
+        # This will cause a reset in the first iteration of the following loop.
+        end_episode = True
+
+        # Counter for the number of states we have processed.
+        # This is stored in the TensorFlow graph so it can be
+        # saved and reloaded along with the checkpoint.
+        count_states = self.model.get_count_states()
+
+        # Counter for the number of episodes we have processed.
+        count_episodes = self.model.get_count_episodes()
+
+        if num_episodes is None:
+            # Loop forever by comparing the episode-counter to infinity.
+            num_episodes = float('inf')
+        else:
+            # The episode-counter may not start at zero if training is
+            # continued from a checkpoint. Take this into account
+            # when determining the number of iterations to perform.
+            num_episodes += count_episodes
+
+        while count_episodes <= num_episodes:
+            if end_episode:
+                # Reset the game-environment and get the first image-frame.
+                img = self.env.reset()
+
+                # Create a new motion-tracer for processing images from the
+                # game-environment. Initialize with the first image-frame.
+                # This resets the motion-tracer so the trace starts again.
+                # This could also be done if end_life==True.
+                motion_tracer = MotionTracer(img)
+
+                # Reset the reward for the entire episode to zero.
+                # This is only used for printing statistics.
+                reward_episode = 0.0
+
+                # Increase the counter for the number of episodes.
+                # This counter is stored inside the TensorFlow graph
+                # so it can be saved and restored with the checkpoint.
+                count_episodes = self.model.increase_count_episodes()
+
+                # Get the number of lives that the agent has left in this episode.
+                num_lives = self.get_lives()
+
+            # Get the state of the game-environment from the motion-tracer.
+            # The state has two images: (1) The last image-frame from the game
+            # and (2) a motion-trace that shows movement trajectories.
+            state = motion_tracer.get_state()
+
+            # Use the Neural Network to estimate the Q-values for the state.
+            # Note that the function assumes an array of states and returns
+            # a 2-dim array of Q-values, but we just have a single state here.
+            q_values = self.model.get_q_values(states=[state])[0]
+
+            # Determine the action that the agent must take in the game-environment.
+            # The epsilon is just used for printing further below.
+            action, epsilon = self.epsilon_greedy.get_action(q_values=q_values,
+                                                             iteration=count_states,
+                                                             training=self.training)
+
+            # Take a step in the game-environment using the given action.
+            # Note that in OpenAI Gym, the step-function actually repeats the
+            # action between 2 and 4 time-steps for Atari games, with the number
+            # chosen at random.
+            img, reward, end_episode, info = self.env.step(action=action)
+
+            # Process the image from the game-environment in the motion-tracer.
+            # This will first be used in the next iteration of the loop.
+            motion_tracer.process(image=img)
+
+            # Add the reward for the step to the reward for the entire episode.
+            reward_episode += reward
+
+            # Determine if a life was lost in this step.
+            num_lives_new = self.get_lives()
+            end_life = (num_lives_new < num_lives)
+            num_lives = num_lives_new
+
+            # Increase the counter for the number of states that have been processed.
+            count_states = self.model.increase_count_states()
+
+            if not self.training and self.render:
+                # Render the game-environment to screen.
+                self.env.render()
+
+                # Insert a small pause to slow down the game,
+                # making it easier to follow for human eyes.
+                time.sleep(0.01)
+
+            # If we want to train the Neural Network to better estimate Q-values.
+            if self.training:
+                # Add the state of the game-environment to the replay-memory.
+                self.replay_memory.add(state=state,
+                                       q_values=q_values,
+                                       action=action,
+                                       reward=reward,
+                                       end_life=end_life,
+                                       end_episode=end_episode)
+
+                # How much of the replay-memory should be used.
+                use_fraction = self.replay_fraction.get_value(iteration=count_states)
+
+                # When the replay-memory is sufficiently full.
+                if self.replay_memory.is_full() \
+                    or self.replay_memory.used_fraction() > use_fraction:
+
+                    # Update all Q-values in the replay-memory through a backwards-sweep.
+                    self.replay_memory.update_all_q_values()
+
+                    # Log statistics for the Q-values to file.
+                    if self.use_logging:
+                        self.log_q_values.write(count_episodes=count_episodes,
+                                                count_states=count_states,
+                                                q_values=self.replay_memory.q_values)
+
+                    # Get the control parameters for optimization of the Neural Network.
+                    # These are changed linearly depending on the state-counter.
+                    learning_rate = self.learning_rate_control.get_value(iteration=count_states)
+                    loss_limit = self.loss_limit_control.get_value(iteration=count_states)
+                    max_epochs = self.max_epochs_control.get_value(iteration=count_states)
+
+                    # Perform an optimization run on the Neural Network so as to
+                    # improve the estimates for the Q-values.
+                    # This will sample random batches from the replay-memory.
+                    self.model.optimize(learning_rate=learning_rate,
+                                        loss_limit=loss_limit,
+                                        max_epochs=max_epochs)
+
+                    # Save a checkpoint of the Neural Network so we can reload it.
+                    self.model.save_checkpoint(count_states)
+
+                    # Reset the replay-memory. This throws away all the data we have
+                    # just gathered, so we will have to fill the replay-memory again.
+                    self.replay_memory.reset()
+
+            if end_episode:
+                # Add the episode's reward to a list for calculating statistics.
+                self.episode_rewards.append(reward_episode)
+
+            # Mean reward of the last 30 episodes.
+            if len(self.episode_rewards) == 0:
+                # The list of rewards is empty.
+                reward_mean = 0.0
+            else:
+                reward_mean = np.mean(self.episode_rewards[-30:])
+
+            if self.training and end_episode:
+                # Log reward to file.
+                if self.use_logging:
+                    self.log_reward.write(count_episodes=count_episodes,
+                                          count_states=count_states,
+                                          reward_episode=reward_episode,
+                                          reward_mean=reward_mean)
+
+                # Print reward to screen.
+                msg = "{0:4}:{1}\t Epsilon: {2:4.2f}\t Reward: {3:.1f}\t Episode Mean: {4:.1f}"
+                print(msg.format(count_episodes, count_states, epsilon,
+                                 reward_episode, reward_mean))
+            elif not self.training and (reward != 0.0 or end_life or end_episode):
+                # Print Q-values and reward to screen.
+                msg = "{0:4}:{1}\tQ-min: {2:5.3f}\tQ-max: {3:5.3f}\tLives: {4}\tReward: {5:.1f}\tEpisode Mean: {6:.1f}"
+                print(msg.format(count_episodes, count_states, np.min(q_values),
+                                 np.max(q_values), num_lives, reward_episode, reward_mean))
+
+########################################################################
+
+if __name__ == '__main__':
+    # Description of this program.
+    desc = "Reinformenct Learning (Q-learning) for Atari Games using TensorFlow."
+
+    # Create the argument parser.
+    parser = argparse.ArgumentParser(description=desc)
+
+    # Add arguments to the parser.
+    parser.add_argument("--env", required=False, default='Breakout-v0',
+                        help="name of the game-environment in OpenAI Gym")
+
+    parser.add_argument("--training", required=False,
+                        dest='training', action='http://github.com/store_true',
+                        help="train the agent (otherwise test the agent)")
+
+    parser.add_argument("--render", required=False,
+                        dest='render', action='http://github.com/store_true',
+                        help="render game-output to screen")
+
+    parser.add_argument("--episodes", required=False, type=int, default=None,
+                        help="number of episodes to run")
+
+    parser.add_argument("--dir", required=False, default=checkpoint_base_dir,
+                        help="directory for the checkpoint and log-files")
+
+    # Parse the command-line arguments.
+    args = parser.parse_args()
+
+    # Get the arguments.
+    env_name = args.env
+    training = args.training
+    render = args.render
+    num_episodes = args.episodes
+    checkpoint_base_dir = args.dir
+
+    # Update all the file-paths after the base-dir has been set.
+    update_paths(env_name=env_name)
+
+    # Create an agent for either training or testing on the game-environment.
+    agent = Agent(env_name=env_name,
+                  training=training,
+                  render=render)
+
+    # Run the agent
+    agent.run(num_episodes=num_episodes)
+
+    # Print statistics.
+    rewards = agent.episode_rewards
+    print()  # Newline.
+    print("Rewards for {0} episodes:".format(len(rewards)))
+    print("- Min:   ", np.min(rewards))
+    print("- Mean:  ", np.mean(rewards))
+    print("- Max:   ", np.max(rewards))
+    print("- Stdev: ", np.std(rewards))
+
+########################################################################
diff --git a/requirements.txt b/requirements.txt
index fd87a52..43c0e28 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -33,4 +33,10 @@ tensorflow		# CPU Version of TensorFlow.
 prettytensor
 
 ################################################################
+# The tutorial on Reinforcement Learning uses OpenAI Gym.
+# Uncomment this line if you want to run that tutorial.
+
+# gym[atari]
+
+################################################################
 

From 75f27c63dc42ba991d919286e6f211d08291d347 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Tue, 25 Apr 2017 10:35:16 +0200
Subject: [PATCH 10/61] Added PayPal donation link to README.

---
 README.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/README.md b/README.md
index e48ed29..370eea1 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,12 @@
 
 Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
+##  Donations
+
+All this was made by a single person who did not receive any money for doing the work.
+If you find it useful then [please donate securely using PayPal](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=PY9EUURN7GRUW).
+Even a few dollars are appreciated. Thanks!
+
 ## Introduction
 
 * These tutorials are intended for beginners in Deep Learning and TensorFlow.

From 9d330b619a418ce77452944be1c9581a8bb420a5 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 3 May 2017 11:44:29 +0200
Subject: [PATCH 11/61] Updated issue template.

---
 .github/ISSUE_TEMPLATE.md | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
index 617efab..22726d5 100644
--- a/.github/ISSUE_TEMPLATE.md
+++ b/.github/ISSUE_TEMPLATE.md
@@ -2,6 +2,11 @@
 
 Most of the problems people are having are already described in the [installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
 
+You should first make a serious attempt to solve your problem.
+If you ask a question that has already been answered elsewhere, or if you do not
+give enough details about your problem, then your issue may be closed immediately. 
+Please don't waste my time!
+
 ## Python 3.5
 
 These tutorials were developed in **Python 3.5** and may give strange errors in Python 2.7
@@ -12,7 +17,7 @@ You need to **download the whole repository**, either using `git clone` or as a
 
 ## Questions about TensorFlow
 
-General questions about TensorFlow should either be asked on [StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow) or [GitHub](https://github.com/tensorflow/tensorflow/issues).
+General questions about TensorFlow should either be asked on [StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow) or the [official TensorFlow repository](https://github.com/tensorflow/tensorflow/issues).
 
 ## Suggestions for Changes
 

From e6490c4338b3e7c7c6525be96f658436c5d212a7 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 13 May 2017 11:55:38 +0200
Subject: [PATCH 12/61] Tiny fix: Use num_classes in placeholder variables
 instead of 10.

---
 02_Convolutional_Neural_Network.ipynb | 956 ++++++++++++++++++--------
 03_PrettyTensor.ipynb                 | 733 ++++++++++++++------
 2 files changed, 1205 insertions(+), 484 deletions(-)

diff --git a/02_Convolutional_Neural_Network.ipynb b/02_Convolutional_Neural_Network.ipynb
index e89e963..ee6f239 100644
--- a/02_Convolutional_Neural_Network.ipynb
+++ b/02_Convolutional_Neural_Network.ipynb
@@ -2,7 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "# TensorFlow Tutorial #02\n",
     "# Convolutional Neural Network\n",
@@ -13,7 +16,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Introduction\n",
     "\n",
@@ -28,14 +34,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below."
    ]
@@ -45,6 +57,8 @@
    "execution_count": 1,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -67,7 +81,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled so the image resolution is decreased from 28x28 to 14x14.\n",
     "\n",
@@ -84,14 +101,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Convolutional Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following chart shows the basic idea of processing an image in the first convolutional layer. The input image depicts the number 7 and four copies of the image are shown here, so we can see more clearly how the filter is being moved to different positions of the image. For each position of the filter, the dot-product is being calculated between the filter and the image pixels under the filter, which results in a single pixel in the output image. So moving the filter across the entire input image results in a new image being generated.\n",
     "\n",
@@ -104,7 +127,9 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -125,7 +150,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The step-size for moving the filter across the input is called the stride. There is a stride for moving the filter horizontally (x-axis) and another stride for moving vertically (y-axis).\n",
     "\n",
@@ -140,7 +168,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Imports"
    ]
@@ -149,7 +180,9 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -165,7 +198,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
    ]
@@ -174,13 +210,15 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.12.0-rc0'"
+       "'1.1.0'"
       ]
      },
      "execution_count": 4,
@@ -194,7 +232,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Configuration of Neural Network\n",
     "\n",
@@ -205,7 +246,9 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -223,14 +266,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -239,7 +288,9 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -260,7 +311,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
@@ -269,7 +323,9 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -292,7 +348,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
@@ -301,7 +360,9 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -310,14 +371,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
@@ -326,7 +393,9 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -348,14 +417,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -364,7 +439,9 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -399,7 +476,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -408,14 +488,16 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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ANzuvq96Vd4EErN/vzxz4UwG4NbuSQkvW2jq6z6u7OhK5eDyOSCSCQCDA7vIE\nfU4o41jXdSmpWUFozBYKBd7Jjcdj2Gw2uN1u+P1+hEIhhMNhLq+i8PUys1QiR+cM0+kUjUaDa4EO\nDw9RLBa5VIA6Ma+vr2NjYwMbGxsscKqqLv3KRHhc7HY7wuEwtra20O/3uT+c2+2eaZR6EzRuKf2f\nMtyuq3WbTCYcHqWQJblOXF2UuVwuPrujyYgsxAhVVWcMyP1+P2dTEg6HA4FAgENUmqaJyK0IVw3r\nad60FoA7nU74/X42yKBFELUck+zKR4R2b6PRCMViES9fvsT+/j4ODg6Qy+VgGAY8Hg93st3e3sbu\n7i7W19cRj8e5V5wgfAgOhwPxeBzPnj2Drus4PT3lLEjaVb1L6EajEQaDAQzDQLfbRaPRQLPZvPH8\nzm6386ramml59QyZen7RGbPb7Ybb7Z5ZebtcLmiaxn3uSBStz0XhWLo8Ho98TlaEq044jUYDpVKJ\nuw5MJhP4fD4EAgEkEgkkEgkEAgE4nc6VEDhgSUXOMAyUSiW8evUKv/jFL3B2doZarYZ+vw9d1/kc\nbm9vDzs7O8hkMojFYtLuRPgoHA4HYrEYe1NGIhHOzr3JZsuKYRhc20ap/1SfdB02m43bQKVSKRYe\nr9c787hYLMYLOr/fz2JmHeNWw13rjvDqrpDO/+jxEspfDWhsTiYT9Pt9NJtNlEolbpJKxzq6riOZ\nTCKRSHC4ehUEDlgykSMrGuowkMvlcHZ2hsvLSy5odLlcCAaDSKfTLG5XzyAE4UOw2WycsKHrOobD\nIffduq3IdbtddLtd1Ot1Fqd2u33t410uF5cTJJNJTgqwhhgBsCtFPB6H3+/n3Zos5ITroIx0Khkg\nC69wOIxUKoVsNjvT4FdEbg70+31UKhWuE6pUKmi32zP9kOx2O3w+H4LBIJ+dSKmAcF/QmW8qlYLb\n7WZxe1fIcjweYzAYYDgczhRqDwaDa8sA7HY7gsEgn5GRI/xV8aLzNTpju627ivBpYU1Qog4DqqrC\n4/FA13VkMhlsbGxge3sb6+vrCIVCKxWuXiqR6/V6qFQqeP36NYsc1cRR3NnhcMDn83GWkCSaCPcJ\niRz1JCTedSZnzYokj0my6rrpNegMjoTrOtNkqnmjx6xC7y/hfrkqcDRmaMfvcDiwtraGbDaL7e1t\nZDIZrpVcFRZ+9re6rjcaDRQKBZyeniKfz6NWq/EujrDZbHC5XHyITtlp8uEX7gNFUa4NHQrCokJC\n5/P5EIv/VAK/AAAgAElEQVTFkM1mMRwOOXvXapQRCoVu3TljWVh4kRsMBuj3++j3+ygUCjg/P8fx\n8TEuLi7QarVmBE4QBEH4Flrc22w2RKNR7O3tweVyYTwe884uGo0ik8lAVdUbowbLzMKL3HA4RLvd\n5iJGEjlrDyRBEAThemgnF4lE4Ha7sba2hul0ymLm8XigqipUVV2pHRyxFCLX6XRQrVZRLpdRKpVQ\nLBbRbDZn2kPQG2ZNlV6VOg9BEISPwTr/UZJSKpWa4x09PksjcrVaDa1WC71eD6PRiB3WKaOSDuB9\nPt+MGe2qbb0FQRCE27PwIkcGzNVqFY1G4y2RA2aTTcjVgQyYJaVaEATh02XhRW48HqPf76PVaqHb\n7c50saVDUjLPJSPaYDAIn88nQicIgvCJs/AidxMOh4NNbBOJBDY2NrC5uYnt7W08efKEvSrdbreI\nnCAIwifKUoucx+OBpmlIp9P4zne+g+9///vY3NxENBrlvnGr0CpCEARB+DgWXuRsNht3N/Z4PPD5\nfJzqSs0gs9ksnj17hh//+MfIZDLsFiFOJ4IgCJ82C68CmqZxyqvP50MymcTTp0/5LI76xm1vb7PP\nn5zDCYIgCMASiJzf72e/QBK4drvNNXFOpxO6rnPXY/Lxk7IBQRAEYeFFTtM0aJo279sQBEEQlpDb\nipwHAF68ePGAt/LpYfl9itvv3ZDx+QDI+Lw3ZHw+ALcdn8q7WoTwgxTlrwD4g7vflnADv2+a5h/O\n+yaWFRmfD46Mzzsg4/PBeef4vK3IRQD8FMApAOPebk3wANgE8MemaVbnfC9Li4zPB0PG5z0g4/PB\nuNX4vJXICYIgCMIyInn2giAIwsoiIicIgiCsLCJygiAIwsoiIicIgiCsLCJygiAIwsoiIicIgiCs\nLI8ucoqiTBVFmXzz59VroijK33jse7rmHv+dG+5zpCiKPu/7Ex6OJRmfP1IU5Y8URTlXFKWrKMpX\niqL8u/O+L+HhWYbxCQCKovxtRVF+pSjKQFGU/3ee9zIP78qk5e//GoC/CeApAHJU7lz3TYqi2E3T\nnDzwvRF/H8D/duVrfwSgb5pm65HuQZgPyzA+/xkAOQD/+jd//gUAf0dRlIFpmv/jI92DMB+WYXwC\nwBTAfw/g9wBsPeLrvsWj7+RM0yzRBaD55ktm2fL1nqIoP/1mZfIvKYry54qiDAD8WFGUf6Aoyox9\ni6Io/52iKP+75d82RVH+hqIoJ9+scn+lKMpf+sB7HFy5TyeAfx7A37v7b0BYZJZkfP5d0zT/Q9M0\n/4lpmqemaf5PeGMb9a/cw69AWGCWYXx+c5//nmmafxfA2V1/5ruy6Gdy/zmAfx/AcwAvb/k9fxPA\nvwrgrwH4DoC/DeAfKoryE3qAoiiXiqL8xx9wH38VQA3AP/qA7xFWn0UZnwAQwJsxKgjEIo3PubHI\nrXZMAP+JaZr/D33hfT3iFEVRAfwHAP5Z0zR//c2X/56iKP8CgH8bwC+++dorAB/ixfdXAfzPpmmO\nP+B7hNVmYcbnN9//lwD8xdt+j7DyLMz4nDeLLHIA8KsPfPwe3ph2/mNl9h11AvhT+odpmn/htk+o\nKMq/CGAbEqoU3mYRxucPAfyveDOh/ZMPvB9htZn7+FwEFl3kulf+PcXbIVan5e8a3qxg/iLeXml8\nrPv3vwXg/zNNc/8jv19YXeY6PhVF+T6A/wPAf2Wa5n/9od8vrDyLMH/OnUUXuauUAfzgytd+AKD0\nzd9/A2AMIGua5i/v+mKKogQA/MsA/vpdn0v4JHi08akoyg8A/J8A/pZpmv/FXZ5L+GR41PlzUVg2\nkfu/Afx1RVH+MoB/CuDfALCLb94k0zTriqL8twD+lqIoHrzZYgcB/HMASqZp/hEAKIryjwH8fdM0\n3xeC/BnevOn/8CF+GGHleJTx+Y3A/V94E6b8O4qiJL75r7H0fRPewaPNn4qi7OLNzjAOwPdN1AEA\nfmOa5vRBfrobWCqRM03zHymK8l8C+G/wZpv9PwD4BwA2LI/5jxRFuQDwn+JNfUYdb2LT/5nlqXYA\nRG7xkn8NwB+Zptm7n59AWGUecXz+ZQAhAP/mNxfxEsBnd/9JhFXkkefP/wXATyz//qff/JnCtzvH\nR0GapgqCIAgry6LXyQmCIAjCRyMiJwiCIKwsInKCIAjCyiIiJwiCIKwsInKCIAjCynKrEgJFUSIA\nfgrgFEtc+b6AeABsAvhjqW/6eGR8PhgyPu8BGZ8Pxq3G523r5H6KN608hIfh9wH84XsfJdyEjM+H\nRcbn3ZDx+bC8c3zeVuROAeDnP/85nj9/fg/3JADAixcv8LOf/Qz45vcrfDSngIzP+0bG571xCsj4\nvG9uOz5vK3IGADx//hw/+tGP7nZnwnVICONuyPh8WGR83g0Znw/LO8enJJ4IgiAIK4uInCAIgrCy\niMgJgiAIK4uInCAIgrCyiMgJgiAIK4uInCAIgrCyiMgJgiAIK8tSdQa3YpomqOHrcDhEv99Hv9/H\nYDDgazqdwuFwwG63w+VyQVVV+Hw+eL1e2Gw2vgRBEITVZKlFbjqdYjqdotVqoVgsolgsolKpoFar\noV6vYzgcwuv1wuv1IhgMIpPJYH19HYlEAk6nE06nU0ROEARhhVl6kZtMJmi328jlcjg4OMDp6Sly\nuRxyuRx6vR4CgQB0XUcqlcL3vvc9OJ1O+P1+3s05nc55/yiCIAjCA7HUIjeZTDAajdBut1EoFHB4\neIiDgwMWuX6/D13Xoes62u02AoEAEokEYrEYptMp7HY7PB7PvH8UYYmZTCaYTCaYTqccMu/3+3C7\n3dA0DZqmweG4n48ZjfnxeIzxeDwTcqdLURQoinIvrycIxHQ65XE3Go3Q6/X4eMjtdsPj8cDj8cDl\ncsHpdMLlcvH3zns8Lq3ITadTjEYjGIaBVquFUqmE8/NzXFxcoNlsYjQawTRNDAYDtNtt1Go1VCoV\nFItFxONxmKYpAifcGRqDhmHg8vIS+Xwe+XwesVgMOzs72NnZgaZp9/Z6hmGg2+2i1+vB4XDA7Xbz\nxOJ0OuFwOOY+qQirx2QyQbfbRafTQaPRQD6fRy6XQ7lcRiKR4CsYDCIYDCIUCvGCyzTNuY7JpRc5\nErFyucwiNxgMMBqNMJ1O+e8ul2tG5NxuN4LB4Lx/DGHJoVVtu93G6ekpvvrqK3z55ZfY2dmBw+FA\nJpO5V5EbDAZotVqo1WrweDycTOXxeKAoCux2+729liAQ0+kUvV4PtVoN+XweX375Jb788kscHR3h\n6dOn2Nvbw5MnT5DJZOBwOBAIBBZmLC6VyFFGpWma6Pf7aDQaqNfruLy8RKlUQqVSQaPRmHk87eho\nFdJut9FqtdDv9zEej+f40wirwHA4RKfTQa1Ww8XFBY6OjvDb3/4WNpsNe3t7GI1G9/p6hmGg0Wig\nWCzC7XZDVVWoqgpd1xEIBOB0OhdmchGWG2sG+2AwQL1eRz6fx9HREfb39/Hll1/i1atXMAwD4/EY\n0+kUAKBpGpLJJCf1zTuysFQiR4kmk8kEtVoNp6enOD09xf7+PgqFAgxDOoIIj4thGGg2myiVSqjX\n6+j1enxGRxPEfb9eo9HA5eUlFEXhEGUqlcL6+jpUVZVkKuFeoDNg2sUVCgW8evUKX3/9Nc7Pz9Fu\ntzGdTlGv13FycoLhcAi32414PI7JZAK73c7nxPNk6URuPB5jOByiVqvh5OQEv/71r3F8fIxCoYDB\nYDDvWxQ+MQaDwYzIdbtdXtVaV8L3gTWCUSgUMBwOuYzGMAz4fD6k0+l7ez3h04Yy2EejEbrdLi4v\nL/Hq1Sv85je/QaVSQavVYpEbDAYol8uIx+PY3d3FZDJ5kEXex7DwIjcej3n3ZhgG+v0+DMPAxcUF\nTk9P8fLlS+RyOTSbTQyHwxufx5qNORwO+bm63S6vNqwZaouwAhEWj6sf3Jt2cvctcMR4PEa/30e7\n3Uan00G/30ev14PX60Umk+HwPCFjWPhY6LjHmtx3dnaG4+NjTraihddgMECn00G9Xke/3+cxuAhC\nt/Ai1+120Ww20Wq10Gw2+e+Hh4c4OTlBuVxGu92GYRgcE74OWu22Wi2Uy2W43W7Y7XYMh0O4XC7O\nUvN4PPB6vZJ5KbwT+vCSyBWLRf6Av2sc3gVFUdi5JxQKYTweo9vt8kVnI5PJhBdqgvCxTCYT9Pt9\nNJtN1Go1tFotdDodGIbBiX2KosDn80HTNPj9fkSjUWiatjChSmBJRK5YLOLi4gLlcpmvfD6P8/Nz\nFjn6cN8E1TE1m02Uy2XYbDb+Gh3eq6qKQCAAm80Gt9u9EG+QsHhYV6kUPiSR6/V6DyZyAOB0OqGq\nKoLBIIeLOp0Out0uZxLTeci8U7eF5WYymaDX66HRaKBaraLRaPBiivIjSOSi0Sji8fiMyC1KzebC\ni1yn00GxWMTR0REuLi5QKBRweXmJarWKarXK9l3vgwSt0WjA4/FgPB7zKjwQCPA1mUzgcDigqipP\nEovyZgmLwdUD+UajgVKpxPWZDoeDsxzve9w4HA54PB5omgan04nxeIxOp4NerzeT5SY7OeFjsIYX\nKVJQq9VQKpVY5Kzzrd1uh6qqiEQiyGQyiEajUFWVd3KLwMKLXLPZxNnZGR92NhoNNJtNDlG+a/dm\nhYoZK5UKxuMxT0y0zaZre3sbg8EADocDXq8XLpcLLpdLRE5g6Dy33++jXC6jUqmgWq3CNE3+wCcS\nCfj9/ntP57cmX1FhuDWMRBGNRZlghOWDzpMHgwEqlQpOT09xdHSEYrGIXq8381hFUaCqKmKxGLLZ\nLIvcIs2XSyNyX331FZrNJncYGA6HnF12GyaTCTqdDv9J4kVnHGTBNBqN4HQ6EQwGMZlMeMUsCAD4\nw99qtdBoNFjgqtUqdF1HJBJBMplEIpGArusPInKUQGUYBheiU7iSdnIPVcIgrD6UVWkYBovc4eEh\nSqXSrUTO5/OJyL0La8E3paeen5/j66+/Rr/f/+jQIcWX6TkIRVHg9Xrh8/ng8/ngcrmg6zoSiQSA\nN+Ehn893bz+fsHxYxcIa9i4WiyiXyxw2V1UVfr8fmUwGyWQSfr//3nwrra9PTj+UHUzhShI5CrkL\nwodi7e5iGAaq1Spev36Nk5MTNBoN9Pv9mcdbz+TW19d5J7coSSfAgoochYDK5TL29/dRLpdndmy3\nXaGSzZG1PIDCOGR0S+EfSoc9Pz+Hy+VCt9vF3t4e9vb2oOu6TBqfMJRKTbsn6nhxdHSEk5MTdDod\neL1ePpd48uQJstksQqHQvY4b0zRhGAa7/NRqtQdPdBE+LSaTCUfLms0mGo0GHxFddYmi+dXn8yEU\nCrF35aJlpi/czD2dTlGpVLC/v4+XL1+yyH1McSGJm8PhgMPhgM1mY9GjpqoU+iGxOz8/R7fbRS6X\nw2AwgK7r2N3dfaCfVlgWrB6V5+fnePHiBb744gs0Gg0WuWg0ikwmg6dPnyKVSt27yAGYKQa/WpMk\nCHeFdnCdTodLthqNBlqtFkajEYsc7dJsNhv360wkEtyNYFF2ccCCihzt4P70T/+UfSkpwYQ+0Lf9\nJdrtdm79YLfbedKhsI9pmtxCYjAYsMABgKqq2NnZEY/LTxzTNDEcDjmTMpfL4cWLF/jFL37BY4t2\ncuvr63jy5AnC4TAvru4Tq62X7OSE+4Z2ciRytJNrtVpvPZY2EV6vF6FQCMlkcub/FoWFELnpdMqJ\nJGR2S0Xf/X5/xuT2fb88SiTx+XycUKKqKrxe78yk02q12KyZjJs7nQ6Ab4W01+uhXC7j9evXiMVi\n/LwSuvy0mEwmaDabXJuZz+fRaDQwGo0QDoeRTCaRTCaxt7fHq9n7KoalMxJajHW7XU54aTabHGan\nxwrCXaD+nOVyGcVikXdwViiPwePxIBQKQdf1ha4rXojZms4a2u026vU66vU6Go0G2u32TBz4Nkkn\nbrcb4XAYsVgMkUiEextRlqTD4YBpmvw6tVoNl5eXuLy8RLfbnXmufr/P2UXj8Zhb9IjIfVqQyOVy\nObx69Qr5fB7NZhOTyQSBQABbW1t4/vw5dnd3kUgk2E3nvtL4KaxOu8lms4lqtYp2u81hd0G4D8bj\nMdrtNkqlEkqlElqt1lt1yDabDR6PB8FgELFYDIFAAG63e053/H4WYra2Wm5VKhXeyV0VOeJdQkci\nl8lkkMlkEI/HEYvFEAwGubEkJbfQakVRFHQ6HRQKhZnnop3c6ekp7HY7P7fwaTGdTlnkXr58ySI3\nHo8RCASwubmJH//4x0gmk4hEIryTu8/Xp9o4srmrVCoYDAayexPuldFoxD6VN+3krOdwsViMd3KL\nytxEjlwjyB+tUCjg5OQEJycnODo64pqM4XCI8Xj81oeZVsp2u529Jz0eDxKJBHZ3d7Gzs4O1tTWE\nw2HeyTkcDtjtdkynUz5H8Xg8aDabKBQKcLlcMzVG7XYbFxcX8Hq9fG6nKApCoRB8Ph+HQEl0F3W7\nLnw4dDZhzWaki1qM+Hw++P1+jhwEg0F4vd57TZ+eTqczEY5CoYBWq4XxeMxjn8pefD4fRyukGFz4\nGMbjMXq9Hke5ut3uW8dFTqcToVAI2WwWu7u7SKVS99oY+L6Zq8hRR4B2u418Po8XL17gq6++wuXl\nJQqFAnq9HnvxXcVms/EHXNM0DktSdhtluJEnpcfj4RKC6XQKt9vNHZULhQJ0XYfL5eI6I9q25/N5\nTqmlHWU6nUY0GkUsFuMVuwjcakGmAVQPRwJXKpV4HFBdXCAQ4IXUfZ9NmKaJVquFfD6Ps7MzXFxc\noN1uA3gTtSATg2AwyK9PIidjUvhQrCJnbR0FfHtc5HQ6EYlEsLGxgefPnyOTyUDX9Tnf+c3MVeQo\no7HVaiGXy+Hrr7/GL3/5S/R6PS7cpp3VVWw2G5xOJ8eGU6kUUqkUn488e/YMyWSSV7bWczTrKlxV\nVZyennJcWVEU3jXSmUepVOLQkKIobIAbCAS4JkQmlNViOp2yDVw+n8fFxQUuLy+5IzcJDHXkpt39\nffucUqg0n89jf38f+XwerVYLpmnC5XLB7/cjEokgFApBVVUROeFOkP2hdSdnFTmad8PhMDY3N/HZ\nZ58hHA7D7/fP+c5vZq4iRwfq1COr1WqhVqtx4e1VayI6U3O5XAiFQojFYux+Tdfa2hqHKTVN45Cm\nNXxDwkm7ulgshnQ6jY2NDU6ZpZoQyvwsl8tcyQ8AHo8H0WgUHo+HBfS+LZyE+UE7uUqlgouLC24S\nORgMoGkaQqEQIpEIotEo/H4/GzLfB1YDaKqLu7y8xOvXr1EulzlBSlVVxONxZLNZpNNpPncWgRM+\nBKoVHo1GXDZQq9XQaDTQ6/XeEjkysKc5mBZXi8rcE09I7MbjMYcv6QN+FafTCb/fD03TkM1msbOz\ng52dHcTjce4iEAqFEA6H4fP53tnugYRJ0zT2XSMLMcqmIzG0Jh70+33Y7XaEw2Fks1kOEckZyGpB\nK9pyuYyLiwtUq1VuiOr1ehGPx7GxsYFkMsmLqfuCohyUaFKv11EsFnF+fo5qtcrWSn6/H6lUCk+f\nPsXGxgbC4TCcTqd0zRA+CDI66Ha77MNKyX9k+m11jaIImqZpCAQCcLlcC+3vO1eRs/qkWbt239RV\nmc7fwuEwNjY28N3vfhc/+tGPEI/HudkphWvetbJWFIWTUBRFYZGjrgbNZpPDliS2rVYLhmFww9X1\n9XW0Wi2Ew2F+44XV4epOjkI3FOqOxWLY2tpCPB6Hpmn3fg5nNSewihx1P1AUhUXuyZMnWF9fnxE5\nQbgtdA5HOzi6Go3GzHER2XhZ2z3puj5jl7iIzH0nB3xrynzd+ZvdbudwI3kDZjIZ7O7uYnNzE5lM\nhj/ctw0ZWVe6tDuMx+MwDAO1Wg2FQgGqqvIqhrbyFFal0gZKipE07tXAag5Oq1sqvKbzWeBNmDCR\nSGB7exuJROLeRY761NXrdZRKJZTLZe7MTL3iPB4PdF1HLBbD2toaYrEYZxCLyAkfApnXU6iy0+m8\nZcJBRvUU+QoGg2xov+gshMi9C5fLxX5oa2trePr0Kfb29rC1tYV0Og1VVe/UoJKq90OhEEajES4u\nLhCNRhEKhdButzkmLUK2+ljPia01aZRlNhqNoCgKNE1jkQuFQvD7/fe6kqWygUKhgLOzMxQKBW4z\nRYs5p9OJQCBwbfmCIHwItHi3ukxdzWh3OBwIBAJIJBLY3NzkljrLwMKLnNPphM/ng67rLHI//OEP\nkUwmEQwGWeQ+9hzCKnJ2ux3xeJydUuisUExwPx2ucxd5l8jRecR97p4mkwna7TaKxSJOT0+5KHc4\nHHLilaqqfAZNBbmL1I1ZWB6siX90LHNV5Ox2O3RdRyqVwsbGBmKxGLxe75zu+MNYOJG7KibUn2tt\nbQ17e3vY3t5GNpvllg5kvHwXKMY8mUy4yNvj8dwY/iR/t0qlgmAwCEVR4Ha7l2LrLtzM1YxfakpK\nZ3H0HgeDQb4eIjRINneNRgPlcpnbnFDHb4/Hw53sNU3jek9B+BjIkOO6nRxtHtxuN0KhEGehy07u\nI7Ceh1iJRqN4/vw5fvCDH2BjYwNra2vw+/2cYPJQk8x1prdW4+ZisYjDw0PYbDaYpsnmzcJyYxU6\n6h83HA7h9Xo5gzccDj/oKpbOBElkrUYETqcTXq8Xuq7D6/VKwpNwZ27ayVFGpd1uZzPmtbU12cnd\nlZtE7vd+7/e4NIDKA+67HuiqyN70d6vIUeJKKpW6t/sQ5sdVkSO3GxK3VCqFSCTy4CJHO8lut4vB\nYMAra4fDAa/XC7/fzzZekmgi3AXKrrxuJ0fZlF6vF+FwGGtra9jc3EQgEBCRex9UZN3tdq9tqUPQ\n+cfu7u6D7ZSsEwqlaBuGcWP2pHUSJBswObNbHaxepNbaILfbzbsnm83G4cP78C61RjKumiN0Oh12\ngqfzOKuNl4ic8KFQLTLVg1Jo3OpyYi3+drvd7K4Ti8Xg8XgWugDcytxEbjKZoNVqsZNDpVLh+h8r\nD13Yapom+v0+p2uXSiWuEel2uzNtJuhefD4fC+/W1hai0aicx60IVtNvr9fLtUB2ux3D4RCtVosX\nQ6PRaKbE5S5cNSxvNBoolUq4uLjgRSDwba1oJBLhsL2InPCh0EKq3++jXC6jUCggn8+zATglWZHI\n0SKP6pGXyQR8biI3Ho/RbDZn7IquE7mHxipyZMBbqVTQaDS4To48K+miOqnd3V1sb28jGo0uzapG\nuBnrGQSdfVGCh8Ph4DYkVEdE2Y4A7uUDT1mdlARAIkcNhQGwX2U4HF74ZpXC4jIajXgHVyqVcHl5\niVwuh0KhgOFwyCJHizjK6qVyrkUvALcy151cp9NBqVRCLpdDrVaDYRjX7uTuA2siibX4fDgc8oRy\nfn6OYrE4475N30cCR9ltoVAIqVQKiUSCyxiE5ccqch6Ph7vLkwPJaDRCvV5HpVJBsViE1+vl6zYf\nemunb/qTdnGGYbAheLlcRrVaRb1e5+8lpx7KrqTQqYic8KFYjS0ajQbq9Tqq1SoajQY/hsztvV4v\nZ50vYxb5XM/kut0uarUaisUiF7s+FFfTw2m10u12kc/ncXx8jJcvX3Irk6tnbDT5ORwOuFyuGVsw\nmWRWA+tCht5n+oDTudhgMMDZ2Rn8fj9M00QkEuHrNiJHuzW6rJ6tdBZcq9VwcnKCZrN57T2+69+C\ncBuseQU35R7Y7XY2Yo5Go9A0bekEDpjzTq7X6z2ayNFrUsYctfOhNiYnJyd4+fIl6vU6tzKxQqto\nKv59iOxOYf5YQzTUc9Dn83Eqf6PRwPn5OUzTRKPRQDabRSaTwfr6+kw7p5ugZCtrOynDMPh8hEKV\nJycnM6vqq/coiyvhLlhNwN8lcj6fD+FweKbbxrIx152cYRhoNpuc0WNN8niI1yMXC7JrajabqFar\nODs7w+vXr3F6esor7KthSspqI/cVSt8WsVsdrMJBYRpd1xEKhdDtdmGz2bjt0nA45PY7ZP12G5Eb\nDAZot9tot9vodrsseJTM0uv10Ol0UK/X0W63Z8YVCTAlAdzFzk74tLGe/1Im+VXfYKfTyUlO5Koj\nO7kFZjweo1arcQYlXcViEScnJ3zgSj3kgG/NoR0OB6LRKDdmff78+YzrCqWUC6uDw+HgbheDwQAe\nj2cmPG1tvzQYDFCtVj8qXEl1eIPBYGZHRzZiV/H5fIhGo9jY2OAOCDL2hA+FohKUbNdut2cKwG02\nG7xeL5viZ7NZhMPhpXTW+WREjhIGzs7OcHJygvPzc+RyOeTzeXbfHgwGM50QKGTlcrkQj8exu7uL\nZ8+esbUYdQaXndzq4XQ6EQqFkM1m+TyWznPb7TY6nQ77SdZqNbx+/fpWY+BqmJHKBiiMTsknFEa6\nCrX5yWaz3A1cxp7woVDC3eXlJcrlMjqdzlu1cVQAnk6nsb6+jkgkIiK3aFiTTXq9HiqVCs7OzvDy\n5UscHx/j+PgYuVzuxu+nMziaWLa3t/G9732P33BK4RZWD4fDgWAwyOcSFO4eDocoFAosROQOcbWL\n/U1Y642s4U0K35PIWXsZWqEzkrW1NXi9XjFlFm6NdXySN2qhUOCdHImc1eWE/CrX1tYQCoVE5BYN\nKnSk7s7Hx8ccmrxNoovVQikYDHKWEVnayOSyuiiKwh0wptMp1tfXYbPZEA6HOcWfzuZo13UbkaM+\ncLquz0wYg8EAxWIRxWIRlUqFz+uoCNx6X7SzlAiC8CFQVxUy4iiXy8jn82+JnLV8xu/3s2crFYEv\nG8t3xx+AYRjI5/PY39/H8fExCoUCTyS3FTmqSaK2JpFIBIFAAG63+87dD4TFhZKNKHRjs9kQDAax\nvr6OWq2GarWKWq02kx15G5GjppPRaBSqqvLX2+02Dg4OcHBwgJOTE1QqFXY/uXpfInLCx0BhcXLu\nqVQqyOfzKBaLnDxltfHy+Xy8wA8EAlw6tWws3B3fNFFc16HgffR6PeRyOfz617/G119/zVlt5FhB\nYXn+nmMAACAASURBVKGbsO7kyKCXes0Jq43NZoPL5eJwNb3n0+kUjUaDz3G73S46nQ663e6txmcg\nEMDa2hrW1tYQCAT469VqFeFwGHa7nQ2Z2+32tc9hTQ4QhNtizai8KnIEZe16PB4WuUAgsNRz3sKJ\n3FWozKBUKs24XlOlPiWM0AG+daKp1WrY39/H0dERSqUSr7rp3ONqY8CrBINB7Ozs4LPPPsOzZ8+Q\nTCaXsk5EuF9I+ABwWOd9CyaCJo6r44hW0DS53NQn0WreTE47MiaF20DmF9ZuA9eVDfj9fsRiMcTj\n8aWtjbOyMCJ3Uz85OiAtFoszZxiXl5c4PT3F6ekpG4oOh8OZN63X6/HZSbPZZHcJiktbbbuuIxQK\nYWdnBz/5yU+QyWQQi8WWsk5EuD/ozIIERlVVjMdj7vf2Puic72rYh57X6/VCVdUbw+Gj0YhFjrra\nP1RfRWG1IJEjwwvDMG6sjbOK3LLPeQshcld9Ja1YzWqtmYyHh4f44osv8Od//ucol8u8Q7NONpSh\ndjXz7bZhz2AwiN3dXfzu7/4ugsGghIgEAGDXG9rNfWgY/Tq3EuuBv8/ne6fI9Xo9tFot9haUNk/C\nbSC3nVqtdqPIORwO3slRAbjs5D4Su90OTdMQj8exvr6OcrnMqf5W6vU6jo6OeGKhySGXy+H169cz\n/baGw+G1IUjrJPCuFS+tjMnKKZlMcpLJsr/Rwv1wH73jbvP8xNWxSyFNVVW5DEF2ccJtmE6nXI9J\ncyV1WKEkJlVVuQ4zm80iEoksfZnU3ETO4XAgEAgglUphY2MDAHiVYaVWq+Hg4ACtVotXtoqisCUX\nCRyJ23WThKIoM+1ybkJRlJnst2QyCb/fL7s34dF4367MajdGZ3eCcBvIr/Jqs2drbRzNf9lsFhsb\nG0tbAG5lrjs5XdeRSqXY/69UKr0lQrVaDc1mE8fHxzPGtNaaD2uY8zoRu9oP7iYURYHf70cikcDG\nxgaSySR0XReREx6dm8SOzu0owiBGzcJtIWMMquukYxxr1w0SuY2NDWxsbMDr9YrIfSwUrozFYmi3\n2ygWi9A0DU6nc6bX1tUEkfeJlfXrN7XLoTeVzG41TePmmJTevba2xv6UUg8nPDbvGt80jmVcCh/C\ncDhEp9PhjQNlV1IY3O1283ENmdGvgi/vXEVOVVVEo1H0+32cnZ1B0zS43W7OVntfiv+HYN2SU4db\nt9sNVVW5VQrZdVE9XDweRygUkslEEISlh4rAy+Uy6vU6er0eptMpbDYbJz3RRYXfq2A4MHeRo7Bj\nOByeacpHW+v74mqbEur4HAwG8fTpU3z3u9/F559/zisYOth3u91Lv5IRlofbhB+XfdIR5sNgMJgR\nOdrJWUWOun9T5q6I3B0g2yRN0zAcDpFKpbC1tYVarcb9tbrdLlsmGYZxp1RpCo+SB2U4HOZmgHt7\ne9jZ2cH6+jp3HaBiXOnXJTwmV0terNmcUsIifCjW8iyqsWw2m+h2u9x1xdpSjI5xrLZxyz7/zVXk\nKC2fzsKeP38Oh8OBer3OV6VSQaVSubWjxE1Q65T19XVkMhnuDZdKpRCPx5FIJKBp2sybvQpvsLA8\nXK3rtAqd+FUKHwuNpfF4DMMwuCM9mYrTPGcdY6u0oJqryFm3w2tra1AUBcFgkE2Ui8Ui7HY7DMNA\ntVq90+tRE8xsNou9vT1sbm5ic3MTmUwGbrebL2tii0wmwmNxNdnKWqQrIid8LCRwVCNnGAZ3t7CK\n3HUCtyrjbK4iR79cAGwASjVAwWCQO9HSISi9MZQCSzUflC1JPn4UcrTb7fwm67rOwraxscE7unQ6\nPa9fgSAw1E+u2WxyUsB4PIbD4WBzAlVVEQqF4PV6V2YCEh4PEjKKVNHcSxsOl8vF53EicveMzWbj\nPlvk6BAMBpFKpRAMBhGNRpFKpVCr1VCv19FoNGY6CpAVjaZp3BKHJgMSOZ/Px1X8iUSC64wEYRGg\nrgPFYhG5XA71eh2j0QhutxvhcBiJRILdgQKBwMpMQMLjYPVcDQaDbNBMwudyuaCqKrxeL7eYWhUW\nQuQURYHb7eZVazAY5F0aCVwmk0E+n+erVCphOp2i1+uxczY9dm1tDZlMBrqu82u4XC5EIhEuEdB1\nXdwihIVhPB6j1WqhUCjg/PycfVhp3G5sbGB7exuZTEZETvgoyG81GAyiXq+j2WxyaJL6x61KbZyV\nhRG5m1qGWN+YQCAAXdfh9/sRDodRLpcRDofhdrvZUJQEkSYDwuFwQFVVvjwej/hRCgsDJQZQKJ7K\nXLxeL7a2trC7u4snT55gbW0Nuq6LyAm3wjpOvF4vwuEw1tbWuN1Yp9OZ6VavaRo8Hs9K1QYvhMi9\nC7fbjUAgwDVugUAA6XQarVYL7Xab3djJscRaImDtP0erFbqcTudKvZHCckMhe03TEI1GEQwGEQwG\neRdHVyQSgaZpInLCB0GWhWtraxiPxzMdLBwOB5LJJCKRCHRdF5F7bOgXTru5dDrNHQdGoxEnntBO\nkA5Pr7Zqp2Lwq1lEgrAI0CKMwu7kwkPlLul0GslkEm63Gx6PR0ROuDU0Vvx+P9LpNLxeL0exyDIx\nGo3yMY7X6xWRe0yk87HwKeBwOKDrOpLJJAaDATY3N7G1tYVsNss2c5FIZN63KSwZV8OVNpsNqqpi\nMplgNBpxuQqFKyORCFRVfaup7zKzOj+JICwxLpcLqVQKn3/+OZLJJKLRKGKxGIcnJRNYuCsU8QKA\nSCSC8XgMj8cD0zTh9Xq5u0UoFFqppDwROUFYANxuN1KpFFRVhWEY3OKEEqRWadIR5gNZFNrtdkQi\nEXi9XsTjcT6Xo1o5KiNYFUTkBGEBcDqdEpIUHhRrHoLL5ZrJPl9lJPNCEARBWFlE5ARBEISVRURO\nEARBWFlE5ARBEISVRUROEARBWFlE5ARBEISV5bYlBB4AePHixQPeyqeH5ffpmed9rAAyPh8AGZ/3\nhozPB+C241MxTfO9T6Yoyl8B8Ad3vy3hBn7fNM0/nPdNLCsyPh8cGZ93QMbng/PO8XlbkYsA+CmA\nUwDGvd2a4AGwCeCPTdOszvlelhYZnw+GjM97QMbng3Gr8XkrkRMEQRCEZUQSTwRBEISVRUROEARB\nWFn+//bONEbS7azv/1P7vm9dVb3N0jNz5xpf2+AEhEIQIo4jgpD4AAEjBB+QIvYgkEiQEyeAkCMU\nhCxIAEtOWAyfkIiCsCIRkIVtsGxf47n3zp2ZXqa7a9/3vU4+dD/PfatnuX1nuruqq5+f9KqWqX7r\nraoz53/Os4rICYIgCEuLiJwgCIKwtIjICYIgCEuLiJwgCIKwtFy4yCmlpkqpyfHtyWOilPr4RV/T\n01BKbSql/kop1VFKZZVSvzbvaxLOn8syPgmlVEwpVTi+tuVp5yw8lcsyPpVSv6OU+opSaqCU+sI8\nr2UencEThvs/COATALYAqOPn2k/7I6WUWWs9Oedro/eyAPgrAG8D+CcA1gD8oVKqp7X+1Yu4BmFu\nLPz4PMFnAHwZwEfn8N7CxXNZxucUwO8B+GcANi/wfZ/gwndyWusiHQAaR0/pkuH5rlLqI8crk+9W\nSn1NKTUA8CGl1GeVUjPlW5RSv6uU+kvDY5NS6uNKqd3jXdhXlFLf+x4v818DWAfwI1rre1rrvwTw\nnwH8jFJKPf9PhcvMJRmfdK6fx9H/4U+9xEcWLhGXZXxqrX9Ka/0/AOy/7Gd+WRbdJ/frAH4OwB0c\n7apOwycAfD+AHwdwF8DvAPgzpdSH6QVKqZxS6peec45/CuCrWuuG4bnPAQjjaNUkCMD8xieUUu8H\n8AsAfhSAlC0SnsbcxuciMQ9z5WnRAH5Za/239MS7baKUUm4c/cf/Vq3114+f/rRS6p8D+AkA/3D8\n3AMAz6vFlwBQOPFcAUcmgQROP2CE5WVu41Mp5QTwJwB+WmtdEOOC8BTmOX8uFIsscgDwlff4+ls4\nKtr5+RNmRSuAL9IDrfV3vMC10Plk1SwQ8xqfvwng77XWf378WJ24FQRgsebPubHoItc58XiKJ02s\nVsN9D45E6Lvw5ErjvVT/zgO4eeK52PG5T+7whKvLvMbndwK4oZT6kePH6vhoKaU+rrX+jfdwLmF5\nmdf4XCgWXeROUgLw2onnXgNQPL7/DQBjAGta6y+/xPt8EcDPKqX8Br/cv8DRD//wJc4rLDcXNT6/\nB4Dd8PjbAfwugG8BcPgS5xWWm4sanwvFZRO5vwbwk0qpHwDwVQA/BuAGjn8krXVNKfXbAD6llHLg\nSKwCOJoEilrrPwUApdTnAXxGa/3pZ7zP/wGwC+B/KaV+BUcpBB8H8N+01tNz+3TCZedCxqfWetv4\nWCm1enz3La318Ow/lrAkXNT8CaXUDRztDGMAXMeBUgDwjYueQy+VyGmt/0Ip9UkAv4WjbfbvA/gs\njsL96TW/qJTKAvgVHOVn1HBkmzbmt13HUaTks95npJT6VziKLPoSgCaA/661loRw4Zlc1PgUhBfh\ngsfnHwL4sOHxV49vV/DOzvFCkKapgiAIwtKy6HlygiAIgvDCiMgJgiAIS4uInCAIgrC0iMgJgiAI\nS4uInCAIgrC0nCqFQCkVBvARAHu4xJnvC4gDwAaAz2mtL00tuEVDxue5IePzDJDxeW6canyeNk/u\nIwD++AwuSng6P4yjgrvCiyHj83yR8flyyPg8X547Pk8rcnsA8Ed/9Ee4c+fOGVyTAABvvfUWPvax\njwHH36/wwuwBMj7PGhmfZ8YeIOPzrDnt+DytyPUB4M6dO/jgBz/4clcmPA0xYbwcMj7PFxmfL4eM\nz/PlueNTAk8EQRCEpUVEThAEQVhaROQEQRCEpUVEThAEQVhaROQEQRCEpUVEThAEQVhaROQEQRCE\npeVSdQYXBEEQ5ovWeuaYTqd8PAuTycTHaDTCYDDAYDCA1hpmsxkmk+mpt3S8DCJygiAIwntiOp1i\nMplgMplgNBrx8SwsFgusVitsNhva7TYqlQoqlQomkwnsdjscDgdsNhvsdjvfOhwOOBwOETlBEATh\n4qDd23g8xmg0Qr/f5+NZkGgBQKvVQi6Xw+PHjzEajeDxeODxeOB2u+FyueB2u+F2uwEciaPNZnup\n6104kTu5Fe71enwYt7BWq5VXBsatsFLq3K+LfuDJZAKlFCwWCywWC0ymd1yc53UdgiAIFwHNcyeP\n4XCIwWCAfr+PXq+HbreLbreLXq/3zHM5HA4WsHK5jL29Pezt7WE4HLLAkci5XC4Eg0Ekk0mYzWa4\nXK6X+hwLJ3IAZkQkl8shm80im83CarXC6XTC6XTC5/MhEAggEAjA4XCw6L3s1vZZaK0xmUwwnU5n\nflyz2cw/kM1mg1JKBE4QhEvPeDxGu93mo9PpoN1uo9Vq8W2r1UKn00G320Wn03nmuZxOJ4tZs9lE\noVBAPp/HcDiEzWabMVXabDbE43G8//3vh8vlQjgcfqnPsZAiN5lMeMWQz+fx5ptv4t69e3A4HPD7\n/fD7/UgkEkgmk7x7oh3VeUGO1fF4jF6vh3q9jnq9DqvViul0CpvNBqvVytciCIJwmZlMJuh0OqhU\nKiiXy3xbLpdRq9VQrVZRq9VY/J4nci6Xi82Sg8EA9XodjUYDw+GQNwZGi9zq6ipcLhfW19df+nMs\nhMhprfl2Op2i3W7zl/Do0SPcv38f9+7dg9vtRiQSQSQSgVIKHo8HsViMzYjncV103l6vx6sX+oGr\n1SqcTiem0ymcTidsNhvMZrPs5q4oxvFCjvjhcMgWgOl0CovFwg5146JMxotwkUynU55vaVMxGo3Y\nJDkajdBut1EsFlEqlZ64pfmvVquxubLb7T7z/RwOB1u8JpMJu6BGoxFfi3EOHwwG+KZv+qbnmkBP\ny0KIHPBOtM5wOMTh4SEePXqE7e1ttt2WSiWMRiPYbDY4HA5eARgnjLOeKIyhsaVSCXt7e9jd3UWl\nUkGz2USz2UQkEoHWGh6PZyYyyOifE64GxnDqRqPBq99Op4PhcMj+h1QqhVQqhUAgAEAETrh4ptMp\nL8La7TYajQZvLJrNJhqNBh/0uNlsotVqodlsotPp8DEYDDAej5/7fpPJBIPBgN+bFn/GWIfzYmFE\njlYTg8EAh4eHeP311/GlL32JzYL1eh1aa3ZgnhS58wg6IT/cZDJBqVTCW2+9hS9/+csoFovsk1tb\nW4Pb7UYikYDf74dSis2WwtXCuCqu1+s4ODjAzs4OKpUK+yyi0SjG4zH8fj98Pp/s+oW5QKLT6/VQ\nrVaRyWSQyWSQzWaRy+WQy+VQrVbR7/c5p40WasPhcGbnR3Pkad5vPB7PxDect8ABcxS5kybKfr+P\nTqeDRqOB/f193L9/H1/72td4ZUyvN5vNMzkUtHs6D8j/1uv1kM/nsb29jX/8x39EpVLha3K5XGi1\nWhgMBjM/nHA1oP/g9J+YQqkPDw+xvb2Nt956C8VikU3dq6uriMViuH79OqbTKUwmE7TWInTChUJW\nMxK5w8NDPHz4ELu7u9jf38fBwQGq1Sov3J6X6P0saAFnPIzz+POCBO12+xMR6y/KXHdyxsmBIigP\nDw/x4MEDFItFDAYDtuN6PB5sbGzg+vXruH79OjY2NhCPx89N4ACg3W6zHXpvbw+FQgGtVgsmkwmh\nUAjBYBBbW1tIp9MIBoNwuVyc0iBcDbrdLkefVSoVlEollMtlZDIZ7O/vY39/H41Gg8XP6/Wi3W7z\nqvY8zOyC8G6QubLf76PRaCCfz2Nvbw/7+/uoVCro9XpPbDDeK2azmQPyKGqSItDfDbKMncX8Pted\nHJl2ut0ustks3nzzTdy/fx87OzsoFAoYDocIhUKIRCJIJBK4ffs27ty5g1deeQWRSOTMvoRn0W63\nkcvl2DdYKBTQbDbh8XgQiURw48YNFrlQKASXy3UmZWiEy0Ov10OlUkGxWMTjx4+xu7uLvb09FItF\nVKtVnjBorAcCgRmRo6gyQbhIjCJHIf17e3s4ODhAr9dDv9+f8Zm9CBRk5XQ6Z3LgThMFTyJnt9tf\n6L1nruOlz/CCkMgNh0N0Oh0UCgU8fPgQr7/+Opd8GY1GsNvtiEQi2NjYwM2bN3H79m28+uqrL50g\n+LzroqPZbCKXy+Hhw4e8whkMBgiFQojFYrhx4wZu3LiBZDIJv98Pp9N5LtckLA5GMzvwzm7/8ePH\nuH//Ph/1ep39tkZTj9GB3+122Z9sXBjJzk54LxhF6GQtyZPmQopdoHSowWDAVohsNotCofDE+Wk8\nGv/e+NyzDkoZ8Hg88Hq98Pl88Pl8p9oERCIRhEKhyy9yg8EArVYL9XqdV73lcpl9XADg9XqRTCZx\n+/ZtrK6uIhgMnmvCtzH0u1Qq4eDgAI8ePUK5XAZw9OVTdFw6nUY8HofX65VgkysE7cooIGl3dxf3\n7t3D48ePkc/n0Wq10O/3MRqNnlgF9/t95PN5vP322zCZTIjFYojFYvD7/VyYVkROeK8Ya0lS5Hez\n2eT4BbvdzoU0aDFOomU2m7m2pNVqnRmDJJomk4n/lopvkCnSbrfPRJaTWZJ2cS6Xi2/dbvep5m+v\n14u1tTV4vd6X/m7mJnLT6RSDwQCdTofzzijRkCJ4gHdEbmtrCysrK/D7/edq3hmNRpzzUSqVOJ3B\nuKtMJpMsdLFYDF6v91wT0YXFgiwQtBAikSsWi6jVami1WhiNRmzuMUJBTG+//TaAo/FGEcNa6zNz\ntgtXC2N0Ou3Kcrkc76C8Xi+nrNjt9icSsEnoKKaAhIjE02KxwO/3IxAIwOfzsemR4iVot0YxFFQB\n6mQ1k9OmV9lsNgSDwcsncsb/8CRyJ5Orq9Uq/wBmsxl+vx8rKyu4efMm++DOcid3cqtP5tN6vY5i\nsYjDw0Ps7u7C6XQilUqxyNERjUa5dqVwNaDJhBZCjx8/xptvvolms8niZxxXxp1Zv99HoVCAxWLh\nSjnBYHDGv2w0+RiRHZ5AnJy3xuMx+v0+ut0uB8ptb29z8QwqoOFwODh1hcSMdmO02DLOZ5QcbrVa\n2U0TjUZZOP1+P4LBIB+BQIDFkBZsJKAUr3DRi7gLFzmyFVNprGKxiFwuh3q9jn6/D6UUQqEQRy/e\nvHkT8XgcTqeTa1Oe9X92o4mSIuL29/fxxhtvIJ/PYzwew263czkx+pGNYa4yAV0NptMpWq0WCoUC\nisUiMpkMqtUqB5K8WzTaaDRCo9HgcaO1Rr1ex/b2NoLBIEKhEAKBALxeL9f6A0TghCeh2AFjdHo2\nm8XBwQEfGxsbsFgsCAaDM0EkFosFLpcL0+kU6XQar776KsxmMxqNxkwUJC3azGYzj89gMMimSyrX\nRTs62uHRju3kMY9xfOEiR/2Her0eGo0GSqUS8vk8arUaBoMBh+dfu3YN165dw40bNxCPx9kOfNar\nAPLDkYny4OAA9+7dwze+8Q0cHBygUChwz6NAIPCEyEkZr6uFMSBpZ2cHh4eHqNVq6Pf77Kd7HqPR\nCM1mk6OK6/U69vf3EY/HkU6nsbq6ilQqhUQiAeCosK3RyS8IBG0YBoMBcrkc7t27hzfffBPFYpEP\nq9WKYDDICzDCarXC7XbDarViMpnwvDsYDNjvppSaaaFDpk+Px8P+u5PpAcbnjUEq85wjL9zGRiLX\n7XbRaDRQLBaRzWaf2Mldu3YNH/rQh7C+vo5YLAan03luASfG69nf38e9e/fwd3/3dxxAcHInF4vF\nZkROuDporbkf1sOHD2d2cs9rGkmQ1aDZbHJgE01Et2/f5sUeAHg8HoTDYbEUCE9AuzJjnvG9e/fw\nhS98YaYkVzAYxOrq6hPpAGSSpKCQUCiE69evQynFuzGlFEcITyYT3r0ZfXqXYVxeqMgNBgOUSiWU\nSiVkMhk8ePAAjx49wsHBAZrNJpRSCAQCCIfDSCQSSKVSCIfDcLvd5/aFGqM8K5UK6vU6Wq0Wer0e\nzGYz25bX1tawtraG1dVVxONx+Hw+SeS9IhjLu/X7fdRqNeTzeTx+/BilUgmdToeDRqxW6xP+B/Lh\nUb0+gsK4gaOk8nK5zD4Rl8uFaDSK4XD41H6FwtXDmL5CASblchnZbBYPHjxANptFs9mE2WxGJBJB\nLBbDxsYGB8j5/f6nlkCkKlIEuWGUUrDZbOxmstlsT7hnLsP8d6EiNxwOUS6Xsb29jUePHmFnZwc7\nOzvIZDIcphoIBDj5O51Ow+fzzZhszpqTItdoNNBut9Hv9+F2uxEIBBAMBrG+vs5CF4vF4Ha7Jdjk\nikCOfQpKqtVq3Nm4Xq+j0+lgOp3OhGkbTTeUcHuyxp+xAW+/30elUgFwJH6RSATr6+u8OxSBE4BZ\nP1w+n8ejR4/w8OFDFrlWq4VwOMzH5uYm0uk0YrEYAoHAU+dSk8kEq9XKGwkSOON9rTUv3C6DsBm5\ncJErlUrY3t7GvXv3OMCjVCpxoiCJXDweRyqV4tXDRYkcTVr9fp+jhFZXV2dEjtIYLtuPLbw4JESd\nTgfVapXLIA2HQ86Hs1gs3NCXzDp2ux3tdhvj8fip/baMgVhUyHkwGGBtbY37bZlMpheqHSgsH7Qw\nGgwGKBQKuH//Pl5//XVks1lkMhk0m03E43HEYjHcvHkT165d43xe6tZycsFkMpme2Q+TFmqXub7q\n3AJPaHIgZz1V73e5XJy8SNGUZ7GKNdqjyenf6XTQbDZ5R7mzs4NsNotGo4HpdAqfz4e1tTW8733v\nmwmAkR3c1YJSS7rdLprNJtrtNrrdLvr9PkwmE4der6ysIJ1OI51Os9nRarVyoEo+n+dFFLUoofwm\naj8CAM1mE5lMBm+//TacTicnjMdisadWnRCWF2MFJmqLQ+UGqZgyxTSMRiNYrVYEAgGkUincvHmT\n6+qSCfJpMQSnMT1e5rE2t9n65Jdm7C5w0vZ7Vl8wrYKGwyEqlQry+Tzy+Tx2dnawvb2N3d1drk+p\ntYbf78f6+jpee+01pNNpRCIRqWxyBTHmTxrN2ePxeKYu3+bmJu7evYu7d++yH9lkMqFWq3EbExpz\nhUIB9Xodg8FgploFTWSZTAZvvPEGhsMhtra22F9tzDkSlp+TaVcUjf748WPs7OxwBDj5ex0OB4LB\nIFKpFLa2thAOhzmu4DKaGs+CuYjcyZUD2X5tNhubeUjkztIseFLkHj9+zL5BEjkqTkoit7Gxgdde\new3BYFCSvq8ozxK50WjEVR5CoRA2NzfxgQ98AN/2bd8Gj8fDk1OlUsHBwQEXFrDb7WzNIH8fHeSz\ny2QyGA6HqFar0FqzX5hCs0Xkrg60CCKR293dxYMHD7C9vY39/X0UCgUOeHK5XAiFQkin09ja2pqx\nil1FgQMWpGmqcSteq9WQzWaxvb0Nj8fD5kra6VEOx2lMmGQapYMaABpNlLu7u8hmsygWi2g2m2x+\noonL7/fD6/WeW0FoYfExBojQiplCsp1OJyKRCJspY7EYd6QwFsmdTqfs22i32yiXy2g2mzwuje9l\n7PV12s7LwnJCrpVut4tCoYCDgwNsb29je3sbxWIR/X4fVqsVkUgE0WgUiUSCSyBSPttVz+VdGJHr\ndrtQSrEJiCpL0DabsvbD4TAikcipdlSj0Yht2NS0kgpCZzIZHB4eIpfLcU4Jrcwp6TESibDZSbja\nkF+EhAsAV1qPx+Mz3SjI+kALMcpDslqtGA6HKBaLCAQCKJfL6Pf7z/STUDQbLfToEK4O4/EYrVaL\nG5vu7e2x9anT6WAymcDn82FjYwO3bt3C1tYWrl+/jpWVFa5DedXHzEKIHNmbh8MhWq0Wr3bz+fxM\nBn0qlcLa2hpGo9Gp+sj1+32uh1mpVPiW8ktKpRKq1eqMqchms3Flk3A4DJfLdeUHiXCEsYkkBTF5\nPB4kEglcu3YNyWRyppUICRVV6/H7/RiNRjg4OIDf74fL5UK73X6qyBkL5xqF7iqvyK8i4/GY2zll\nMhl2sezu7rL7JBAIYGNjAx/84Afxzd/8zQgEAggEAk+NlryKXKjImc1muN1uBINBRKNRNJtNHelb\nTAAAGq1JREFUuFwuWK1WbuI3Go247Xq32+Uf0mKx8G6s0WicKgBkMBigXq+jVquhXq/P3KdWFO12\nmycUErhUKoXNzU2etETkrjZaa851q1QqaLVaHAl5sn8XiZ9xYjH6csnUTqb0yWTyRHoARRo7nU54\nPB7Ou5NWPFcPSj2p1Wool8uoVqtoNBrodDrwer2w2+3w+XxcQCOdTnPqiiyIjrhQkaPw1nQ6zRWz\nK5UKSqUSxuMx/6cnv9l4PJ5Z0XY6HZTLZezv75/aXNntdrk0Dd2ngxJtKejFbrdzlYC7d+9ifX39\nXPvXCZeD6XTKY+/w8BDVahW9Xg/AkbWgXq8jn88jEAggGo0+N6eNqqY0m000Gg3uGm7EZDLBbrfD\n6/UiFArB6/XO5DjJouvqQAEnjUYD9Xod3W6XO8rb7XZ4PB5uf+N2u+F0OiX69gQXLnLBYJDz48rl\nMg4ODuBwOGZCqcnR3u12AbyzKi6VSlwQ9DQrFGNoNuUi0WO6T5GdFGxCIvfKK68gGo0iEAjIpHLF\nIZEjkxElbQNH1oJGo4FCoYB4PI5er/euItfr9diS0Ov1nggqoQnM6/VyTy1jfqaszq8OzxI5sjy5\n3W4OjnO73TNlu2ScHHGhImexWOB2uxGJRDAajVAul1Gv1zGZTGZ2WsaQ6sFgwIex0d/JatdPg15H\nkZEUgEIFcAFwfTYaLNQzKZlMwuv1wul0isgJMw0mjSZDY7UcaphKhcZpIUVjeTQaIZvNolKpPCFw\nZrOZTZ+UVjAYDNjqYGx5Iru5qwP55CiOgEzlJyN+qbBFrVZj87ixmMZVzZEDLljkKDwfOFqhbG1t\nwWazIZVKzURBdjodvqVAkUqlwrsui8UCj8fDZbee5Z+z2Wzw+/3w+/2YTCbY3d3F7u4ucrkcv8a4\n7Q+HwwgGg7z1p4AB4WpjMpl4cZZOp9Fut1EsFgEcmcTJZ0K+3larNbM463Q6HNlLuU1Uy5JqApIo\nArM968xmM6LRKNLpNFqt1kyHZWH5GY1GaLVaKBaLyOfzXOqNYhZI1Pb39xEKheBwOLhLt8fjgcPh\ngMPhuNLmywsXOUr0pm608XgcjUaDzTeNRmNG2Gw2GyfFmkwm9p9Rx/CVlRUWzpO43W6srKwgkUhg\nPB7DZrOhXq8/IXI2m439H2Tf9ng8HIJ7VVdAwhEkchQsVSqV2Dpg7CRvFDmz2cyLtmq1imKxyK11\nqOsGmZ0oenI0GvHuj6KMh8MhUqkUB7xQIXMRuasBpRAUi0UUCgV0Op0ZkSP3SzAYhMfjgcVi4Zy5\nSCQCr9fL4+WqzmMXLnJkQrTZbHA4HNyoj1a6zWYT5XKZD2PGPtmhKUAkmUwimUzC6XQ+9f3cbjcS\niQQSiQT6/T729vb4tXQt1Aw1Ho9zhwFj129BoB5boVAIvV4Pjx8/ZjO20WdSLBaxv7+PYDAIpRRa\nrRabmqiTOKWtTKfTmZJgJpOJo4cpKIp2ezTB5fN5hMNhmM1m7vclLDcnfXIUz0CVmyj1KZfLwel0\nQmuNaDSKarWKWq2GUCiEUCiEcDjMASlk6ibTuNEN9Kwu3sYoYrI+GM2gxrzQRWOutSuNW+jpdDpT\n1YRy1SjRtlwuz5grySkfCASemTNH3W/dbjdGo9GMQ5bE0uPxIJlM4saNG7h79y7W1tYQCARkAhEY\nMrMHAgEMh0MEAgHuqjydTtHv9zGdTrG/vw+tNarVKoAjf12/30e73Z4JNJlMJvB4PFyhYmVlBVar\nFQcHB1ymiYKjKA0mm81iZ2eHLRLBYHDO34pwEZwsak8mbvo38svVajXs7++j2+1yRxefz8eL/EQi\nwcXvHQ4HtNYsmMYuBNTh+2RDaBJVKipOlacoIGqR+x3OdatirAxhNpvhdDpZvIyluIwt2OlvjD/G\ns75c4+qDSnYZRY5y9kjk3ve+93EipYicQCiluAqP1hqBQIDzOymHjnZflUoFDx8+BPBOdK+x6wb5\nk71eL5dgunXrFpxOJ77+9a9zoAGdczAYcKk7r9fLAkcTnbDcGINLyJxtFDngyG9Xq9XQ6/VQLBbZ\nb2uz2bC6usrNnskV4/P5eHE2GAy4RZTT6YTL5eKNgXHzQPl6nU4Ho9EIfr8fPp8PWutTl1mcF3Pd\nyZGQmM3mcwnwoFVwo9HgPl2UNkClllZWVpBKpbC6uoqNjQ0eHCJyAkGLIhqzoVCI/R6dTmcmMrhc\nLj/x98bOAYFAAB6PBysrK9jc3MTt27dx9+5dOByOGd+LUooDVygIxeFwcPAL5UoZD2H5MMYh2Gy2\nmXQo4J2dHgkQQWOCfMStVostX4FAgPM1e70eR727XC54PB4+jH5f8g22222MRiMEg0E+H/2ty+Wa\n2REuyphcaqcTdRs4PDzEo0ePUCgUuIpKKBTCxsYGrl+/jvX1dYTDYd6iL/KqRLh4yLSuteZgqVu3\nbqHT6XALnWw2ywEBJ/Pk7HY7R/murKxgfX0dGxsbvMKORqMsnvF4HCsrK1BKcREDo8+PGvu22204\nnU5OoxGWE5vNhlAoxE10jfly7waVRyTzd7FYZDEyVpii2AQ6jGZIgvKX+/0+JpMJ1/f1+Xx83+/3\nIx6P8yEidwGQyFFR06eJHFU2CYfDUtBUeCa0onY4HEgkErh16xasViveeOMNTCYTlMtlNi09TeTC\n4TCXi6NCuul0mieJwWDAIlcqlbiSCplD6/U6lFKoVCrc7ocmEYvFsjATinC22Gw2hMNhrK+vo91u\n4/DwEIPB4F1FjkyZVMS52Wzygshiscy4cmgRR2OcLA/GedCY8wmAxZJcPhTgcufOHVgsFkSj0YWZ\nR5dO5MhmbaxSQQ0GafKwWCzw+/1IJpO4fv06otEofD7fqYo+C1ePk9Fn4XAYWmv4fD6MRiM0Gg1k\ns1kuNEDJugQFAGxsbGBrawu3b9/GK6+8gng8zpNLq9VCKBRCIpHgnVq5XIbFYmE/3WQy4ULjtVqN\nr+lZKTTC5YcWSOvr6xyXQL40Ep2TZeGMBcSpmMBZQrnF1P8zHA5zdxjjzpMsY/NORF86kTM6SA8P\nDzliLZPJcDsdytMjO/ciRwYJi4fD4YDf74dSChsbG9wmqlarcc4n5bOZTCYkk0ncunULN2/exObm\nJuLxOKcgkIBarVaEQiGsr69z5NvJCkDGRVsoFMLq6ipSqRT3XRSWD0qXGg6HnHK1srKCTCaDUqmE\nUqnEO346jOJ3XgFKFFCllEKj0eBAFuqn6PV6uSs5dbSfF0sncpRfVC6XkclkWOTIZzIejzn8m5yk\nInLCaVFKweFw8G2v14PJZILH4+FcuGKxyCkxFosF6XQat27dwu3bt5FMJjk60/gfn/olUhpNt9vl\noClj8BTVe3U6ndzPjlIQhOXDbrcjGo2ywCUSCayvryOTyeDBgwd4+PAhRqPRTL9D6pBhDE45S0hI\njSZPKjpOAud0OrG2tgalFLxer4jcWUIiVywWkclk+Mjn8zORP0ZH6/PqXwqCETLVUOQZhVCHQiFu\nxOvxeLgTuNVqRTqdxtbWFra2trjh78kAJ+rQQeWYarUaSqUS+/ooSZyaZyql4PP5sLKy8sSKXfxz\nywOZBUngUqkUN322WCzo9XpcCYfEp9frsYnQuMMz1kY1mjRfBBI3qrEKHI07qrxCgSs+nw/JZPKs\nvo4XYulEzljQtFQqccgrVYmg/KRoNMplvCjnSRDeKxQ5Sc57SvKmqhBmsxnhcBjxeJx3b88qFWcs\nPu71ehGNRpFKpbj5LwBuQ1UqlVCr1dButzEcDiVoaokxplo5HA74fD6Mx2Pcvn0bNpsNa2trM6ZK\nqhxlFD+tNffibDQa6Pf7XPT7eV0z3ivD4ZCtEDQ2553TuXQiRwVzjVW7SeTcbjdHsJHI+f1+CcMW\nXhhqWknVc6LRKHq9HrTWLGa0uHpRkatWq1yOjkTOZDLxRDIYDLgMneTMLSfGLvNkBrdarYjFYlzn\nFDjyldVqNQ5OMgbi5XI5duFQhC711DwrjLVcqc6miNwZQzs5qn15cidHHXSj0Sg7RgXhRTGaLl8G\nozgZRa7b7SKbzc6IXKvV4lJOnU6H+y/KLm75eFqHeafTCZ/Ph3g8/sTrJ5MJSqUS10k1itzDhw9h\ns9m4DB317DwZnfmiUMAUiZzs5M4Jo7myUqmg0+lgOp3CbrdzRNq1a9cQi8W4krwgLBLG1j7j8RjZ\nbBbpdBr5fJ6rzvf7fdRqNeRyOezu7qLX63G+kojd1YUCovx+PwDM+N9arRZ3y6BSYRRxTn9rs9k4\nB47y4MgCYWyDRqkJlNawyCytyNFOjkTO4XAgHA6zyJGPRBAWDRI54Gj1nsvlkMvluJ9Yo9Hg1TKJ\nHPkAfT6fmN6vMBQYRSZ0Y53LdrvN44e601PUI1kS7HY7gsEgl62jw2q1cicMqrxDhQoWnaUTudFo\nNLOTo8rdFAG3urqK69evIxgM8kQiCIsEiZzT6YTH45kROaUUOp3OzE5uZ2eHeyKurKzM+/KFOUPt\nyU6aCTudzkxpsEKhMJOrSeW9QqEQ0uk01tbWsLGxgY2NDTgcDmxvb2N7e5sLk5+mtNgisBQiR2Vu\ner0estksN5js9/scAGC1WuFyueD3+1ngZMUrLCoUaGCxWBAIBJBMJnHz5s2ZjhqdTgf5fB4Wi4X7\nIiaTyZmC0GK6vFqQD+9pwUdkxozFYsjn82yGNO72hsMhp2DR+KE0mYODA2SzWZRKJTSbTU4dMEJz\nrcPhWJim00sjctVqlRNlKXVgOBxyGLfVauVWPtIUVbgskAkylUpxJXgStm63i1wuh263y0nhjUaD\nV/JS7kswYrPZ4PP5EI1GEQwGueoOQf0La7UaRqMR+93a7TbsdjsXI8/n82xNOInZbOaG2FRNat7M\n/wrOABK5g4MDHBwccFTlcDhkMaM6a16vF36/fyFWGILwbphMJk6otdvtyOfz2N7ehtls5jY/+Xwe\ngUAAm5ubaDQa8Hq9HEQg5b4Ewm63w+v1YjweIxgMzlTdod3cYDDAaDRCvV5HrVZDq9VCrVaD3W7n\nqE1KTXhaVKZxQ0Hjb97z7FKIHCXLHhwcIJPJoFqtYjAYcPFan8+HYDAIr9fLRUNPZv/TfWrgKiIo\nzAvjuDMGEiilsLKywsFT1WqVe4VREMrOzg601ojFYrBarU8EFghXF4vFApfLhclkgmAwiHA4jGg0\nylVLqOgzHb1eD/V6HcBRWosx942gxRSl0iSTSayvr+PGjRtIJpPw+XxzN5kvhcgZd3KHh4eo1+sY\nDofchTkcDiMWi3FnZeCd+muUL0I/rLH0lyDMG5pEgKNVciKR4B0bLeoorDuXy+H+/fvQWkMpBb/f\nD7vdLgs2AQC4VZTWGsFgELFYDKlUCpPJBPV6nedAgvLoKHK31+vNpBsA4CIb1FuOOm28+uqrSCQS\nCAaDInJnAYnc4eEhMpkMi5yxysnJdjrG/kjUPJB6Jc37RxEEI+TbcDgc7HcbDoccaZnL5dDpdJDN\nZrnguM/nQzqdZtMlCZ9wdaExZDabWeSSySQ3Qm21WjOvp90cBZicbAhMEZkulwvBYBDxeBzr6+vY\n2trC3bt3uYblvE3mSyFyVHmbHKWUZU9NAKkIMznui8UiJzbSSoUO6o1EleYFYZ4Yw7uph10ikeBE\n3kKhwCaoRqOBw8NDBINBrK2tod1uc96cWCYEitg1Fve+efMmj6/hcMiJ4tT8lyxdtJujqF3qHu5y\nuZBOp/kgM2UwGBSf3EVBk8R0OuVW8NPplJ2o1WqVa1fabDZsbm5y53BBWDRcLhcikQi01igUCtjf\n34fX6+XCuKPRCLFYDJVKBc1mE4FAAE6nkycn4epCYkYil06n2RyulMJwOITVauXNApWLIwsXBfA5\nHA4Eg0H2621ubuLatWvY3NxEIpGY8QcvglVs6UUOOPpxJ5MJ2u02SqUSOp0OHj9+jN3dXWSzWXg8\nHrjdbni9Xm5eOe96a4LwNKj+qtPpxOHhIcLhMLxeL9exHA6HKBQKqFaraDab6Ha7sFgsZ1ppXric\n0IKfLAIkdlarlWuiUh4mvQ4AB+WRVczr9bKpk3ol3rp1C1tbWzPtyxYl2GmpRY5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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f4f8a3c8>"
+       "<matplotlib.figure.Figure at 0x7f210fe38c50>"
       ]
      },
      "metadata": {},
@@ -435,7 +517,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -458,14 +543,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-functions for creating new variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Functions for creating new TensorFlow variables in the given shape and initializing them with random values. Note that the initialization is not actually done at this point, it is merely being defined in the TensorFlow graph."
    ]
@@ -474,7 +565,9 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -486,7 +579,9 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -496,14 +591,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for creating a new Convolutional Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This function creates a new convolutional layer in the computational graph for TensorFlow. Nothing is actually calculated here, we are just adding the mathematical formulas to the TensorFlow graph.\n",
     "\n",
@@ -528,7 +629,9 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -593,7 +696,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for flattening a layer\n",
     "\n",
@@ -604,7 +710,9 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -635,14 +743,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for creating a new Fully-Connected Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This function creates a new fully-connected layer in the computational graph for TensorFlow. Nothing is actually calculated here, we are just adding the mathematical formulas to the TensorFlow graph.\n",
     "\n",
@@ -653,7 +767,9 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -679,14 +795,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
     "\n",
@@ -697,7 +819,9 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -706,7 +830,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
@@ -715,7 +842,9 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -724,7 +853,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
@@ -733,16 +865,21 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
-    "y_true = tf.placeholder(tf.float32, shape=[None, 10], name='y_true')"
+    "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
@@ -751,7 +888,9 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -760,7 +899,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolutional Layer 1\n",
     "\n",
@@ -771,7 +913,9 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -785,7 +929,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Check the shape of the tensor that will be output by the convolutional layer. It is (?, 14, 14, 16) which means that there is an arbitrary number of images (this is the ?), each image is 14 pixels wide and 14 pixels high, and there are 16 different channels, one channel for each of the filters."
    ]
@@ -794,7 +941,9 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -814,7 +963,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolutional Layer 2\n",
     "\n",
@@ -825,7 +977,9 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -839,7 +993,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Check the shape of the tensor that will be output from this convolutional layer. The shape is (?, 7, 7, 36) where the ? again means that there is an arbitrary number of images, with each image having width and height of 7 pixels, and there are 36 channels, one for each filter."
    ]
@@ -848,7 +1005,9 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -868,7 +1027,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Flatten Layer\n",
     "\n",
@@ -879,7 +1041,9 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -888,7 +1052,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Check that the tensors now have shape (?, 1764) which means there's an arbitrary number of images which have been flattened to vectors of length 1764 each. Note that 1764 = 7 x 7 x 36."
    ]
@@ -897,7 +1064,9 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -919,7 +1088,9 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -939,7 +1110,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Fully-Connected Layer 1\n",
     "\n",
@@ -950,7 +1124,9 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -962,7 +1138,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Check that the output of the fully-connected layer is a tensor with shape (?, 128) where the ? means there is an arbitrary number of images and `fc_size` == 128."
    ]
@@ -971,7 +1150,9 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -991,7 +1172,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Fully-Connected Layer 2\n",
     "\n",
@@ -1002,7 +1186,9 @@
    "cell_type": "code",
    "execution_count": 30,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1016,7 +1202,9 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -1036,14 +1224,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Predicted Class"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The second fully-connected layer estimates how likely it is that the input image belongs to each of the 10 classes. However, these estimates are a bit rough and difficult to interpret because the numbers may be very small or large, so we want to normalize them so that each element is limited between zero and one and the 10 elements sum to one. This is calculated using the so-called softmax function and the result is stored in `y_pred`."
    ]
@@ -1052,7 +1246,9 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1061,7 +1257,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The class-number is the index of the largest element."
    ]
@@ -1070,7 +1269,9 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1079,14 +1280,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Cost-function to be optimized"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "To make the model better at classifying the input images, we must somehow change the variables for all the network layers. To do this we first need to know how well the model currently performs by comparing the predicted output of the model `y_pred` to the desired output `y_true`.\n",
     "\n",
@@ -1099,7 +1306,9 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1109,7 +1318,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
    ]
@@ -1118,7 +1330,9 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1127,14 +1341,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Optimization Method"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now that we have a cost measure that must be minimized, we can then create an optimizer. In this case it is the `AdamOptimizer` which is an advanced form of Gradient Descent.\n",
     "\n",
@@ -1145,7 +1365,9 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1154,14 +1376,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Performance Measures"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We need a few more performance measures to display the progress to the user.\n",
     "\n",
@@ -1172,7 +1400,9 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1181,7 +1411,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This calculates the classification accuracy by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then calculating the average of these numbers."
    ]
@@ -1190,7 +1423,9 @@
    "cell_type": "code",
    "execution_count": 38,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1199,14 +1434,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## TensorFlow Run"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -1217,7 +1458,9 @@
    "cell_type": "code",
    "execution_count": 39,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1226,7 +1469,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1237,7 +1483,9 @@
    "cell_type": "code",
    "execution_count": 40,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1246,14 +1494,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1264,7 +1518,9 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1273,7 +1529,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for performing a number of optimization iterations so as to gradually improve the variables of the network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
@@ -1282,7 +1541,9 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1340,14 +1601,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
@@ -1356,7 +1623,9 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1390,7 +1659,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
@@ -1399,7 +1671,9 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1437,14 +1711,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1457,7 +1737,9 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1533,7 +1815,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance before any optimization\n",
     "\n",
@@ -1544,14 +1829,16 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.9% (1093 / 10000)\n"
+      "Accuracy on Test-Set: 10.1% (1009 / 10000)\n"
      ]
     }
    ],
@@ -1561,7 +1848,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
@@ -1572,14 +1862,16 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:      1, Training Accuracy:   7.8%\n",
       "Time usage: 0:00:00\n"
      ]
     }
@@ -1593,6 +1885,8 @@
    "execution_count": 48,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1600,7 +1894,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 13.0% (1296 / 10000)\n"
+      "Accuracy on Test-Set: 8.3% (834 / 10000)\n"
      ]
     }
    ],
@@ -1610,7 +1904,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 100 optimization iterations\n",
     "\n",
@@ -1622,6 +1919,8 @@
    "execution_count": 49,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1641,22 +1940,24 @@
    "cell_type": "code",
    "execution_count": 50,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 66.6% (6656 / 10000)\n",
+      "Accuracy on Test-Set: 70.2% (7019 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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/oAkZgUBg4qRMSUeyQYPkTb9/ii9S8pnWQ0deD5p2QjZNzWWm7es6tkazQRuN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\n1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KOB01z0VEUlClKSKSgipNEZEUVGmKiKSgSlNEJAVVmlJRw4YNY9iwYZgZZsak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\njdGXqwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f2f16898>"
+       "<matplotlib.figure.Figure at 0x7f210fe38d68>"
       ]
      },
      "metadata": {},
@@ -1669,7 +1970,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 1000 optimization iterations\n",
     "\n",
@@ -1681,6 +1985,8 @@
    "execution_count": 51,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1688,15 +1994,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    201, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    301, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    401, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    101, Training Accuracy:  76.6%\n",
+      "Optimization Iteration:    201, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    301, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
       "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    601, Training Accuracy:  84.4%\n",
       "Optimization Iteration:    701, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    901, Training Accuracy:  89.1%\n",
       "Time usage: 0:00:03\n"
      ]
     }
@@ -1710,6 +2016,8 @@
    "execution_count": 52,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1717,15 +2025,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 93.1% (9308 / 10000)\n",
+      "Accuracy on Test-Set: 93.0% (9303 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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qtRAMBrG5uYlHjx5xFm6320WhUBDxFN4ao+u12+2iUqkglUphd3cXz549w7e+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vwTFLlmSWKw/P/oqEJZYnT57c4O9g7bXXzm6ffvrpVJIiTRGRFCoWaf75z38G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\nNEVEUlChKSKSggpNEZEUVGiKiKTw/wFYhGeufg/ivgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f2f24fd0>"
+       "<matplotlib.figure.Figure at 0x7f210fe38400>"
       ]
      },
      "metadata": {},
@@ -1738,7 +2046,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 10,000 optimization iterations\n",
     "\n",
@@ -1750,6 +2061,8 @@
    "execution_count": 53,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1757,97 +2070,97 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:   1001, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1101, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1201, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1401, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   1501, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1801, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:   1901, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2201, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   2301, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2401, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2501, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2401, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   2501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2601, Training Accuracy:  95.3%\n",
       "Optimization Iteration:   2701, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   2801, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2901, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3101, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3201, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3301, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3501, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   3601, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   9501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:26\n"
+      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:25\n"
      ]
     }
    ],
@@ -1860,6 +2173,8 @@
    "execution_count": 54,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1867,15 +2182,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.8% (9880 / 10000)\n",
+      "Accuracy on Test-Set: 98.6% (9859 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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kkvOOLRbLTBrM/HiWgnq3oM92MpmwpaNWq73wHIrLWFTMhsMhGo0Gcrkcjo6O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KcM011yS3fU3AR5rvv/8+ENYUfC0iOjm233fPPfekvJ4+fToAzz77bPLYFi1y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\nYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f2d23518>"
+       "<matplotlib.figure.Figure at 0x7f210fe38cf8>"
       ]
      },
      "metadata": {},
@@ -1886,23 +2201,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 973    0    1    0    0    1    1    0    3    1]\n",
-      " [   0 1129    2    1    0    0    1    1    1    0]\n",
-      " [   1    2 1023    2    0    0    0    2    2    0]\n",
-      " [   1    0    1 1002    0    3    0    1    2    0]\n",
-      " [   0    1    0    0  974    0    1    0    2    4]\n",
-      " [   2    0    0    3    0  882    2    0    1    2]\n",
-      " [   4    1    0    0    1    4  948    0    0    0]\n",
-      " [   1    4   11    2    0    0    0 1004    2    4]\n",
-      " [   3    0    4    2    1    2    0    0  960    2]\n",
-      " [   3    4    1    0    7    5    0    2    2  985]]\n"
+      "[[ 975    0    0    0    0    1    1    1    2    0]\n",
+      " [   0 1128    1    2    1    0    1    1    1    0]\n",
+      " [   5    5 1002    7    1    0    0    6    5    1]\n",
+      " [   1    0    0 1008    0    0    0    0    1    0]\n",
+      " [   0    0    1    0  981    0    0    0    0    0]\n",
+      " [   1    0    0   17    0  870    1    1    1    1]\n",
+      " [   7    2    0    0    4    4  940    0    1    0]\n",
+      " [   1    2    3    3    0    0    0 1017    1    1]\n",
+      " [   3    1    1    6    1    1    0    2  957    2]\n",
+      " [   2    4    0    5    9    2    0    4    2  981]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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FkqZLGtfvWWZmvViZ5dzzbU2Fw/rW+mvAgaTRL7OB7wDXA4e/cXBED/BxoBu4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\nswpycDczqyAHdzOzCvr/JoxuWOZEVREAAAAASUVORK5CYII=\n",
+      "image/png": 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2ZhHwZE8XaFq22iKxvY6qaxIRbWs/sdH7gMskbQfcD7yXkupU0hnAg8A7yrHfBE4AVgHP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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f0ad5550>"
+       "<matplotlib.figure.Figure at 0x7f210d4ea710>"
       ]
      },
      "metadata": {},
@@ -1916,7 +2231,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Visualization of Weights and Layers\n",
     "\n",
@@ -1925,7 +2243,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
@@ -1934,7 +2255,9 @@
    "cell_type": "code",
    "execution_count": 55,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1986,7 +2309,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for plotting the output of a convolutional layer"
    ]
@@ -1995,7 +2321,9 @@
    "cell_type": "code",
    "execution_count": 56,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -2046,14 +2374,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Input Images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Helper-function for plotting an image."
    ]
@@ -2062,7 +2396,9 @@
    "cell_type": "code",
    "execution_count": 57,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -2076,7 +2412,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Plot an image from the test-set which will be used as an example below."
    ]
@@ -2085,14 +2424,16 @@
    "cell_type": "code",
    "execution_count": 58,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f0a26048>"
+       "<matplotlib.figure.Figure at 0x7f2101cde400>"
       ]
      },
      "metadata": {},
@@ -2106,7 +2447,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Plot another example image from the test-set."
    ]
@@ -2115,14 +2459,16 @@
    "cell_type": "code",
    "execution_count": 59,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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q+tgl+irkuPEOPyAoLvgBQRF+ICjCDwRF+IGgCD8QFOEHgiL8QFCEHwjq/wHi31d/HSnF\nFwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f0abf0f0>"
+       "<matplotlib.figure.Figure at 0x7f21019c4828>"
       ]
      },
      "metadata": {},
@@ -2136,14 +2482,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolution Layer 1"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now plot the filter-weights for the first convolutional layer.\n",
     "\n",
@@ -2155,14 +2507,16 @@
    "execution_count": 60,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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jx+vFHBtGzcze+4d/k5mpt1wjM/mnTrnmxaa722z3bhlrXrpUZv7kHOnZ8p90ZLJ7K7+Z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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f09ba320>"
+       "<matplotlib.figure.Figure at 0x7f2101d870f0>"
       ]
      },
      "metadata": {},
@@ -2175,7 +2529,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Applying each of these convolutional filters to the first input image gives the following output images, which are then used as input to the second convolutional layer. Note that these images are down-sampled to 14 x 14 pixels which is half the resolution of the original input image."
    ]
@@ -2185,14 +2542,16 @@
    "execution_count": 61,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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BJEoACEhorXdxcXEkV9cJ19fXy6FDhwrCd2ZHcXFxpLKyMtvdSMqePXta/bPN1c+tiMjG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\nYiAAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f22ad080>"
+       "<matplotlib.figure.Figure at 0x7f210889c2e8>"
       ]
      },
      "metadata": {},
@@ -2205,7 +2564,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following images are the results of applying the convolutional filters to the second image."
    ]
@@ -2215,14 +2577,16 @@
    "execution_count": 62,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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keujQocaGO6f8bqkodnRas2aNOcaUme8WNnbsWNVPP/20ah9eL1q0SPXixYuN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\njpIQQgL8Hy5wLN51ZjFMAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f0d59dd8>"
+       "<matplotlib.figure.Figure at 0x7f210b123438>"
       ]
      },
      "metadata": {},
@@ -2235,21 +2599,30 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "It is difficult to see from these images what the purpose of the convolutional filters might be. It appears that they have merely created several variations of the input image, as if light was shining from different angles and casting shadows in the image."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolution Layer 2"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now plot the filter-weights for the second convolutional layer.\n",
     "\n",
@@ -2263,14 +2636,16 @@
    "execution_count": 63,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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v6B/9c718t9yrkKSSBQuUGDbMnfXkk2ahB/debeZM33abfUTf/rYzlFq9WsXT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\nOAEACPD/AOULKX5U7BsBAAAAAElFTkSuQmCC\n",
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kd+J95+tF3cr0sIuEjeM/E5rMpyF5rctgqq2NqJI/Tlq27Ua1ZEbhm2Lu9Wj+U5P5Y7a+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\nzRQAwACaKQCAATRTAAADaKYAAAb+D6eqlk+kAJCNAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f22ade10>"
+       "<matplotlib.figure.Figure at 0x7f2101c042b0>"
       ]
      },
      "metadata": {},
@@ -2283,7 +2658,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
    ]
@@ -2292,14 +2670,16 @@
    "cell_type": "code",
    "execution_count": 64,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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Nmg9JIyVlm+FjpM/r+64f1O97WTvq18xrR/2on+uRt/fFRcrLy+so6QxJGUkRv/ViI19S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\n",
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EEyEPzaiYGPFZz1sP36+WjHLLufZoIhFRVRXPnnsuyNgMueIKoh07hAP7B6g1JybcK+Z5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\nKQCAAWimAAAGoJkCABiAZgoAYMD/AM6smdqQb8ZdAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f22ade48>"
+       "<matplotlib.figure.Figure at 0x7f2101cbfeb8>"
       ]
      },
      "metadata": {},
@@ -2312,7 +2692,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "It can be difficult to understand and keep track of how these filters are applied because of the high dimensionality.\n",
     "\n",
@@ -2326,14 +2709,16 @@
    "execution_count": 65,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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UYxPxiRMAAAcMnAAAOGDgBADAAQMnAAAOGDgBAHDgNKu2oaEhMNNT6zAiIvLl\nL3/Z+YTGjBljjJu6xmhsnYlSqaOjQ9rb2z2x5557Tj1+1apVxvjbb7+t5lxxxRXGeFcbMyP/TL/a\n2lr12FTZsGGD7N69OxD/8MMPjcfv2LFDfSx/96ZuthrNnz/fGL/zzjsDMVtHlFRpb28PtNhbvny5\nevx//dd/GeO2un7xi180xu+77z41Z9iwYZ5t7d8z1aZOnSpTp071xLS2cD3117/+1Ri3dSjyz4AP\n44x4EZFLL7008B7+2c9+tl+e+/Dhw+o+/1jR1V/3jPjECQCAAwZOAAAcMHACAOCAgRMAAAcMnAAA\nOGDgBADAgdPtKJ/+9Kdl2rRpnpitqbi2yK9/Qd1Ed911lzFuux3Fv+jp2Z4mfrbk5+dLYWGhJ3bD\nDTeox1977bXG+N69e9WcSy+91BivrKxUc/zN+A8ePKgemyqjR4+W8ePHB+Jao/J/+qd/Uh+rtLTU\nGH/22WfVHG1R9rKyskAs2Snt/Wno0KEyYsQIT2zp0qXq8VdeeaUx7l/kIdFll11mjFdVVak5/luM\nbI+fSm1tbYGFv23vfYMGDXJ+DtOCASIin/rUp9Qc/wL1tgXrU6mxsTFw65HtNpGeLJTwpS99yRi3\n3Z7Y0tLi2U72vS+cVQYAIKQYOAEAcMDACQCAAwZOAAAcMHACAODAaVatqVG0f0ZrorvvvtsYt82y\nu+OOO1xOSUREWltbPdtHjx51foz+0NnZKR0dHZ6YrSmzv6F+t8svv1zN+dGPfmSM+2dUJrrkkks8\n29ps6FSaOHGicTZ2JBJxfqydO3ca47Zrr7i42Bg3zXjMzMx0Pqe+1tbWJidPnvTEmpub1eOzssxv\nDbNnz1ZztLr6nzdReXm5Z9u/CEJYmGYl9+Ta27Bhg7rvjTfeMMavv/565+cJm5EjRwZmwGsz4kX0\nhRJMM+t7wz+e+d+fNXziBADAAQMnAAAOGDgBAHDAwAkAgAMGTgAAHDBwAgDgwOl2FBPblPb169cb\n41rzchttqruIBBqn5+XlOT9+qtiaMmuNov/4xz+qOdrtLZ/5zGfcTuwc9vDDDxvjWiN3EZHnn3++\nr04nZWy3U1xwwQXOj1dfX2+M26b4Dx061LOdn5/v/Lyp4r+VIdELL7xgjD/44INqzj333NPrc0on\nf/7zn9V92vuY//alZGjN80WC11+yYwefOAEAcMDACQCAAwZOAAAcMHACAOCAgRMAAAdOs2ozMjIC\nDaxtDduV5mcPAAASbElEQVTnzJljjK9cudLlaT96bs3gwYM929ps1DDwz2TMzc1Vj/3Nb35jjK9e\nvVrNmTlzpjFumyXpb6xtazyfKqYm5SIiL774ovH4devWqY/1t7/9zRi/6aab1JyJEyca4/F4PKlY\nGNlmEFZWVhrj77//vppz0UUXGeM33nijmuO/1sJaO9MCF7ZZyTfccIMx/sorr6g5t99+uzEei8WS\nOMPTbA31UykzMzMwdlx99dX98tw5OTnqPv/7b7JjB584AQBwwMAJAIADBk4AABwwcAIA4ICBEwAA\nB8nOqs0REYlGo4EdO3bsUJNaWlqM8U2bNiX5tP+vqalJ3bdnzx7PdnV1dfd/6tOp+leOiOe8klJX\nV2eMHzp0SM1paGgwxjdv3qzm+GfVJvw7h6F+6rUnol9/2rUnInL8+HFjfP/+/WqOVj//TEGR0F1/\nav1sMzC162jfvn3OOVu3blVzBgwY4NkO2bUnYqmfbVat//fqZrvGtPdFl5myYa2f7e6Lvnbw4EF1\nn79XbcJ52usXj8fP+CMi80UknoY/85P5/fr6h/p9LGtH/dK8dtSP+mk/ka5fzioSiRSJyGwRqROR\n5G8qSp0cESkWkbXxeFz/X7x+Qv16Lg1rJ0L9eiM0tROhfr11rtYvqYETAACcxuQgAAAcMHACAOCA\ngRMAAAcMnAAAOGDgBADAQVINEM7VKcX9hfr1XBrWToT69UZoaidC/XrrnK3fx/kmVm4CDn/90rh2\n1C/Na0f9qJ/2k2zLvToRkWeeeUbKy8s9O2wtuLRFQYcMGaLmaO2lsrL0U/UvhhuNRmXRokUiXecd\nAnUipxcHrqio8Ow4fPiwmqS1GRwxYoSaoy3a2tnZmXROdXV1mOpXJyKyatUqKSsrC+zcuXOnMUlr\neSaiL+Dc0dHhnONfRF3kdP0WLlwoEqL6mV67/laLibRa2F6HthZ0yeZEo1FZvHixSDhqJ2J57R49\nelRNsi0Sfjb5F7mORqNy8803i4Ssfk899VTg9Wt7T8rIMH+LqMVFpHugdmK6/m655RaRM9Qv2YEz\nJiJSXl4u06dP9+xobGxUk/yra3cbNmyY/kTKaucuA2fiw6lJ/SsmIlJRURGo34EDB9Qkfx/FbmPG\njFFzTG/kIvaL1LLqeRjqFxMRKSsrk2nTpgV2ar9vdna2+oAFBQXGuG0gKSwsNMbP8AYZmvqVl5cH\n6tfW1qYmabWw/Q+J7U1NYxlsw1A7Ectrt7W1VU3SrrGz7cSJE9quUNWvrKxMpk6d6tnRk4HT1Bu6\nm2UccH4eOUP9mBwEAIADBk4AABwk+6fa0wdnZQX+ZKr9CUtEZMOGDcb4wIED1RxtOagZM2aoOaWl\npUk/firt379f9u7d64k9/PDD6vHbt283xm3Lk2nfuxQVFak5Tz/9dFLPm0qtra3G5YG0f+tx48ap\nj6UtK3bkyBE1R/vawfS9Sk++a+lrtbW1gVr5/92T2Wf7Tl57L5gzZ46a82//9m+ebW1psjCyfaf7\n+9//3hgfOXKkmvPMM88Y47b6XXnllZ7tMF57IqeXQvS/tz/33HPq8Vu2bDHGbX+q/cQnPmGMX3/9\n9WrOhAkTPNu2ryIS8YkTAAAHDJwAADhg4AQAwAEDJwAADhg4AQBwwMAJAIADp9tRTPbv1/vgrlu3\nzhhfs2aNmrNjxw5j/J577lFzli5d6tmur69Xj02lDz/8MDDd+eKLL1aP//GPf2yM2zpkaLcRjB8/\nXs3x37phuu0j1To6OozdbLTuLRs3blQfS2tlaLvlSetcZercYmvdlyqZmZmB3+Ezn/mM8+O89dZb\n6r7hw4cb47YWm/7OWbZuPKnU2dkZ6HSzdetW9XitG5ftunzxxReNcVPHrG7Nzc2ebVsnslQaM2aM\nFBcXe2KzZ89Wj3/ppZeM8U2bNqk5v/zlL41x2zV1+eWXe7Zra2vVYxPxiRMAAAcMnAAAOGDgBADA\nAQMnAAAOGDgBAHDQ61m1/ia5iR599FGneE/5G0/b1ghNpRkzZgTW9Js5c6bz47z88svqPq3p+ec+\n9zk1xz/rzLaWZarEYjFjc/b169cbj1+9erX6WH/729+M8X//939Xc7oWpg4wzdCtqalRHydVxo4d\nKyUlJZ6Yf5Zjorlz5xrjthnd2tqGtlnu/hnIhw4dUo9NpXg8HmigfsUVVzg/ju39Umsa37WwspH/\ntWubwRw2/vU5E2kLhPSEbaas/w4C2yIGifjECQCAAwZOAAAcMHACAOCAgRMAAAcMnAAAOGDgBADA\nQa9vR7H5y1/+YoyPGjVKzbFN19bk5uZ6trUGy6l26tSpwHR+bQq/iMgTTzxhjC9btkzN0Rodt7W1\nqTn+5tW2Ww5SZezYscZr4+tf/7rx+PLycvWxBg8ebIzbmk6vXbvWGC8oKAjEtFuCUmnAgAGBBQa0\n2x9ERHbu3GmM23K0WyFsOf73gj179qjHplJWVpba6N9Ea0ZuuxWvJ7eS+G/n8b+Ww8y0aEM3bbEP\n29ih1c/2evTfEpPsex+fOAEAcMDACQCAAwZOAAAcMHACAOCAgRMAAAe9nlVrm8U1bNiw3j78Oa+h\noUHd9/3vf98Yb2lpUXOuvfZaY/zIkSNqTk5Ojmc7jLNCNf4mzd0KCwvVnFmzZhnjb775ppqjzQCc\nMmVKIBbGWckmVVVV6r79+/cb4/5ZnIm0mtuayftn+vq309W3v/1tY1ybnS0igSby3U6ePKnm+O8g\nCOMCDRpbQ3XtOrDNPO7JjGz/TOlkZ07ziRMAAAcMnAAAOGDgBADAAQMnAAAOGDgBAHDAwAkAgINe\n346SmZmp7vPf5tDtjTfeUHO02yYmT56s5mjTuMMmHo8HzrWmpkY9/qtf/aoxvnz5cutzmNgabfun\nfrs0s+4vptqJ6NPvL7nkEvWx1qxZY4xrt7aIiMyYMcMYNzXptzXuDxPba3fkyJHG+OjRo9WcpqYm\nY9x2C4G/VrbrNJXa29sDCyXYbtt67bXXjPGSkhLn57bdSuZf4CKdDB8+3Hmf7RYW7XaU6dOnu51Y\nEtLjFQ4AQEgwcAIA4ICBEwAABwycAAA4SHYWSI6IvbelifZl7YcffqjmaBMWbKuF+/vlVldXd/+n\neXZS/8sR8ZzXR7Zv364mNTc3G+Pa6vIi+uSgEydOqDn+SQ4hq1+OiEg0GjXu1CYL2CZu1NbWGuOt\nra1qzuDBg5N+/oRzDU39TNdefX29mqRN0tGuSRG9h7Ktrv7nCdm1J2Kpn62vrtav2NZ3Vntd2yat\n+XvVhuzaE+nh2KGxTZTatWtXrx8/4Tzt9euerWj7EZH5IhJPw5/5yfx+ff1D/T6WtaN+aV476kf9\ntJ9I1y9nFYlEikRktojUiUjsjAmplyMixSKyNh6Pm5d56EfUr+fSsHYi1K83QlM7EerXW+dq/ZIa\nOAEAwGlMDgIAwAEDJwAADhg4AQBwwMAJAIADBk4AABwk1QDhXJ1S3F+oX8+lYe1EqF9vhKZ2ItSv\nt87Z+n2cb2LlJuDw1y+Na0f90rx21I/6aT/JttyrExH5xS9+IeXl5Umm6G27ugrqvC9Z1dXV8rWv\nfU2k67xDoE5E5JlnngnUz9Z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Njo4OqaurU2XPPPOM0u+//75phy6nCy64wNSZMGGC0ugKwNR/+SKRSJjX79WrVyvtShl5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\nsQtzBuwAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56edfb5e10>"
+       "<matplotlib.figure.Figure at 0x7f21014f8160>"
       ]
      },
      "metadata": {},
@@ -2346,7 +2731,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "And these are the results of applying the filter-weights to the second image."
    ]
@@ -2356,14 +2744,16 @@
    "execution_count": 66,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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/fr0xblsk3rSovIj+HzoRCYxnMaz1Y3IQAAAOGDgBAHDAwAkAgIN4/8YpIqeW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\nrkJggg==\n",
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4dOlS0wfzSey9997N/v3r4Gs+IYR4gMaUEEI8ELtOBr4mlZSUKI2+ThGRiy66SGlM5SYi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\ngg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f56f0c979b0>"
+       "<matplotlib.figure.Figure at 0x7f21019781d0>"
       ]
      },
      "metadata": {},
@@ -2376,7 +2766,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "From these images, it looks like the second convolutional layer might detect lines and patterns in the input images, which are less sensitive to local variations in the original input images.\n",
     "\n",
@@ -2385,14 +2778,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
@@ -2401,7 +2800,9 @@
    "cell_type": "code",
    "execution_count": 67,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -2412,7 +2813,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2425,7 +2829,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Exercises\n",
     "\n",
@@ -2450,7 +2857,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2467,9 +2877,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2481,7 +2891,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
diff --git a/03_PrettyTensor.ipynb b/03_PrettyTensor.ipynb
index 238cc7c..bb3fbb8 100644
--- a/03_PrettyTensor.ipynb
+++ b/03_PrettyTensor.ipynb
@@ -2,7 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "# TensorFlow Tutorial #03\n",
     "# PrettyTensor\n",
@@ -13,7 +16,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Introduction\n",
     "\n",
@@ -28,14 +34,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See the previous tutorial for a more detailed description of convolution."
    ]
@@ -45,6 +57,8 @@
    "execution_count": 1,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -67,7 +81,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled so the image resolution is decreased from 28x28 to 14x14.\n",
     "\n",
@@ -84,7 +101,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Imports"
    ]
@@ -93,7 +113,9 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -112,7 +134,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
    ]
@@ -121,13 +146,15 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.12.0-rc0'"
+       "'1.1.0'"
       ]
      },
      "execution_count": 3,
@@ -141,7 +168,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "PrettyTensor version:"
    ]
@@ -150,13 +180,15 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.7.1'"
+       "'0.7.4'"
       ]
      },
      "execution_count": 4,
@@ -170,14 +202,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -186,7 +224,9 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -207,7 +247,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
@@ -216,7 +259,9 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -239,7 +284,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
@@ -248,7 +296,9 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -257,14 +307,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
@@ -273,7 +329,9 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -295,14 +353,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -311,7 +375,9 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -346,7 +412,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -355,14 +424,16 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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xGFs30RsuCNcxHo/R6/V4IUZZxJRoMp1O4XK52GQglUohlUohkUiwwLnd7oVeIQurx2Qy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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfd19bc18>"
+       "<matplotlib.figure.Figure at 0x7f5b75981ac8>"
       ]
      },
      "metadata": {},
@@ -382,7 +453,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -405,14 +479,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
     "\n",
@@ -423,7 +503,9 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -432,7 +514,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
@@ -441,7 +526,9 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -450,7 +537,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
@@ -459,16 +549,21 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
-    "y_true = tf.placeholder(tf.float32, shape=[None, 10], name='y_true')"
+    "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
@@ -477,7 +572,9 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -486,14 +583,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## TensorFlow Implementation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This section shows the original source-code from Tutorial #02 which implements the Convolutional Neural Network directly in TensorFlow. The code is not actually used in this Notebook and is only meant for easy comparison to the PrettyTensor implementation below.\n",
     "\n",
@@ -502,14 +605,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-functions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "In the direct TensorFlow implementation, we first make some helper-functions which will be used several times in the graph construction.\n",
     "\n",
@@ -520,7 +629,9 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -532,7 +643,9 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -542,7 +655,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following helper-function creates a new convolutional network. The input and output are 4-dimensional tensors (aka. 4-rank tensors). Note the low-level details of the TensorFlow API, such as the shape of the weights-variable. It is easy to make a mistake somewhere which may result in strange error-messages that are difficult to debug."
    ]
@@ -551,7 +667,9 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -616,7 +734,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following helper-function flattens a 4-dim tensor to 2-dim so we can add fully-connected layers after the convolutional layers."
    ]
@@ -625,7 +746,9 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -656,7 +779,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following helper-function creates a fully-connected layer."
    ]
@@ -665,7 +791,9 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -691,7 +819,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Graph Construction\n",
     "\n",
@@ -706,7 +837,9 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -757,14 +890,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## PrettyTensor Implementation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This section shows how to make the exact same implementation of a Convolutional Neural Network using PrettyTensor.\n",
     "\n",
@@ -775,7 +914,9 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -784,7 +925,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now that we have wrapped the input image in a PrettyTensor object, we can add the convolutional and fully-connected layers in just a few lines of source-code.\n",
     "\n",
@@ -796,6 +940,8 @@
    "execution_count": 22,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -813,7 +959,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "That's it! We have now created the exact same Convolutional Neural Network in a few simple lines of code that required many complex lines of code in the direct TensorFlow implementation.\n",
     "\n",
@@ -822,14 +971,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Getting the Weights"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Unfortunately, not everything is pretty when using PrettyTensor.\n",
     "\n",
@@ -844,7 +999,9 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -862,7 +1019,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Using this helper-function we can retrieve the variables. These are TensorFlow objects. In order to get the contents of the variables, you must do something like: `contents = session.run(weights_conv1)` as demonstrated further below."
    ]
@@ -871,7 +1031,9 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -881,14 +1043,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Optimization Method"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "PrettyTensor gave us the predicted class-label (`y_pred`) as well as a loss-measure that must be minimized, so as to improve the ability of the Neural Network to classify the input images.\n",
     "\n",
@@ -901,7 +1069,9 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -910,7 +1080,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Performance Measures\n",
     "\n",
@@ -923,7 +1096,9 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -932,7 +1107,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Then we create a vector of booleans telling us whether the predicted class equals the true class of each image."
    ]
@@ -941,7 +1119,9 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -950,7 +1130,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
    ]
@@ -959,7 +1142,9 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -968,14 +1153,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## TensorFlow Run"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -986,7 +1177,9 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -995,7 +1188,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1006,7 +1202,9 @@
    "cell_type": "code",
    "execution_count": 30,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1015,14 +1213,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1033,7 +1237,9 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1042,7 +1248,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for performing a number of optimization iterations so as to gradually improve the variables of the network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
@@ -1051,7 +1260,9 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1109,14 +1320,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
@@ -1125,7 +1342,9 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1159,7 +1378,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
@@ -1168,7 +1390,9 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1206,14 +1430,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1226,7 +1456,9 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1302,7 +1534,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance before any optimization\n",
     "\n",
@@ -1313,14 +1548,16 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 9.1% (909 / 10000)\n"
+      "Accuracy on Test-Set: 9.8% (977 / 10000)\n"
      ]
     }
    ],
@@ -1330,7 +1567,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
@@ -1341,7 +1581,9 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -1362,6 +1604,8 @@
    "execution_count": 38,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1369,7 +1613,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 8.9% (892 / 10000)\n"
+      "Accuracy on Test-Set: 9.0% (905 / 10000)\n"
      ]
     }
    ],
@@ -1379,7 +1623,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 100 optimization iterations\n",
     "\n",
@@ -1391,6 +1638,8 @@
    "execution_count": 39,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1410,22 +1659,24 @@
    "cell_type": "code",
    "execution_count": 40,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 83.9% (8393 / 10000)\n",
+      "Accuracy on Test-Set: 87.5% (8748 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SicMb1BP3sVg68ZxMJmi1Wsjn8zg6OmLxrNfrHDeirEPq+E/i+ezZM2QyGYRC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\nA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80f/dzF4j88d9ZbS/msr4YqA9MMIyw2CK2Z1UrYpVxr8AJpnZTDL9mo+5+xPR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\nNkkEGgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfaa0f710>"
+       "<matplotlib.figure.Figure at 0x7f5b7325b5f8>"
       ]
      },
      "metadata": {},
@@ -1438,7 +1689,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 1000 optimization iterations\n",
     "\n",
@@ -1450,6 +1704,8 @@
    "execution_count": 41,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1457,15 +1713,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    301, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    501, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    101, Training Accuracy:  84.4%\n",
+      "Optimization Iteration:    201, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    301, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    501, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    701, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    801, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    901, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:03\n"
      ]
     }
@@ -1479,6 +1735,8 @@
    "execution_count": 42,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1486,15 +1744,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 96.3% (9634 / 10000)\n",
+      "Accuracy on Test-Set: 96.6% (9656 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Op1k8X3aqp8/DysoKQqEQ9xkVlgtqmtFut9Htdi9135vNZrhcLoRCISSTSS6LIo8H3cgz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\ne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Q+A950MzeIfGLXxOs7wx8nUGMtwGLgLlmNh+4hUS2/QiJQl4IjAem+x0qae96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\nO2cUQAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfaa0fa90>"
+       "<matplotlib.figure.Figure at 0x7f5b7325b048>"
       ]
      },
      "metadata": {},
@@ -1507,7 +1765,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Performance after 10,000 optimization iterations\n",
     "\n",
@@ -1519,6 +1780,8 @@
    "execution_count": 43,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1526,97 +1789,97 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:   1001, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1101, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   1201, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1401, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   1501, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1901, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2101, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   9401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9401, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9601, Training Accuracy:  96.9%\n",
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       "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:27\n"
+      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:26\n"
      ]
     }
    ],
@@ -1629,6 +1892,8 @@
    "execution_count": 44,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1636,15 +1901,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.8% (9881 / 10000)\n",
+      "Accuracy on Test-Set: 98.9% (9887 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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xpBLBZeHOGU/aeVYqFX58cedJH+jLoA8YmE0wZDiDwSCsVivXHlEqNXW8aLfbbFAp28xs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\nL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0vmpmTYHmwDfVnVRm8pXHOwOHm1nP4DpNzWysc65/mvMKmsfOucXAYcH5TYEjnHMrYl+o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\nTRGRGFRoiojEoEJTRCQGFZoiIjH8PzBnVOmSu4nHAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfaa0f940>"
+       "<matplotlib.figure.Figure at 0x7f5b727aef98>"
       ]
      },
      "metadata": {},
@@ -1655,23 +1920,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 975    0    0    0    0    0    1    1    3    0]\n",
-      " [   0 1127    2    0    0    0    1    2    3    0]\n",
-      " [   2    2 1019    1    1    0    1    2    4    0]\n",
-      " [   0    0    0 1005    0    1    0    1    3    0]\n",
-      " [   0    0    0    0  977    0    1    0    1    3]\n",
-      " [   2    0    0   13    0  870    1    0    6    0]\n",
-      " [   5    2    0    0    1    3  943    0    4    0]\n",
-      " [   0    2    8    2    1    0    0 1007    1    7]\n",
-      " [   2    0    2    3    1    1    0    0  964    1]\n",
-      " [   0    2    0    4    5    1    0    1    2  994]]\n"
+      "[[ 979    0    0    0    0    0    0    1    0    0]\n",
+      " [   1 1128    1    0    0    1    2    0    2    0]\n",
+      " [   5    1 1008    2    2    0    0    6    8    0]\n",
+      " [   1    0    0 1001    0    3    0    0    5    0]\n",
+      " [   0    0    0    0  975    0    1    1    1    4]\n",
+      " [   2    0    0    3    0  883    1    1    2    0]\n",
+      " [   5    2    0    0    1    1  948    0    1    0]\n",
+      " [   1    1    1    2    0    0    0 1022    1    0]\n",
+      " [   5    0    1    0    0    1    0    1  964    2]\n",
+      " [   4    3    0    2    8    3    0    6    4  979]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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GvMrMrA+rspx7vq2pcFjfW18JHEwa/TIH+A5wPXDE6ydH9AIfBXqAe4ErSL3/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\nCvr/LO4zMmrEalQAAAAASUVORK5CYII=\n",
+      "image/png": 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5vBx4e5m9WQI80dMFmpFttkhsb6DqmkRE29pPbPQu4HJJOwD3A++kpDqVdBbwAPCWcuzX\ngZOANcDT5di+bDOQSPoHttL4sr1l/ywi+lBnRqYu26uArXV/lm7lWAPntHHeOmMk3+h5vAB4Ey8c\n6Y2IJoZ8+Xsddbo2X+h9Lukfge92VqOYUhtJiY64pZ3FzHe8ImsM43n9XGtzMM/PQ0dEQ212bQal\nzhjJRp5vfG0HPM4Wc9MR0cC4Z0iTJKr1+pNzyxNlgCYi2mDG4kq0aTvMJWh8vdwMfHOCSET72rrW\nZpDqjLytkpQ75kV0ZZwTG0mab3sT1W03b5J0H9XafVE1VraZu6BcsPck1bU5m7axvDdibhryIFHH\ndGMk/0J1AdApDc/xWtuPNSwjYiyNQreljukCiQBs3zdLdYmYm8Z81mZfSe+d6kXbH61RvoFrJRn4\ne9sXzbSCEWNvzFsk84BdaXbTjd+1vU7Si4HrJN1t+4beA0pOhbMBFrBzg1NFjCaNwfTvdIFkve2/\nbFK47XXl6wZJVwHHADdsccxFwEUAL9JeYxCbI2ZgTMZIppv+bdRxk7SLpN0mHwMnAnc0KTNiLI3z\n9C9buex4hvYDrqoWxzIf+JztqxuWGTF+hjxI1DFlILH9eJOCbd9Ptbw+IqYx7l2biIhachPxiEEb\ngxZJAknEIHn8p38HQy2s8stFylNqK7PZm+56tJVyrjp831bKGWlj8Os6fIEkYg4R4zHYmkASMWgJ\nJBHRyJisbE0giRi0BJKIaGocZm06XZAmaQ9JyyTdLWm1pFd1eb6IkTTm19q04RPA1bbfXO5FmjwB\nEb1GIEjU0VkgkbQ7cBzwDgDbzwLPdnW+iFE1DoOtXXZtDgYeBT4l6VZJF5d0AhHRawy6Nl0GkvlU\nyaMvtH0UVQb6X7tDn6SzJd0s6ebneKbD6kQMp7lyX5t+rQXW2l5Rni+jCiwvYPsi24ttL96eHTus\nTsSQSotkarYfBh6SdFjZtRS4q6vzRYyiuq2RmbRIJM0rwwlfLc8PlrRC0hpJXygTH0jasTxfU14/\nqN/P0XU+kncBl0u6DTgS+KuOzxcxetpvkZwLrO55/mHgY7YPATYCZ5X9ZwEby/6PleP60mkgsb2q\ndFt+x/Zptjd2eb6IUdRmi0TSIuCNwMXluYDjqYYWAC4DTiuPTy3PKa8vLcfPWDKkRQxauy2SjwPv\nBybXy+4N/LTcfheqscuF5fFC4CGA8voT5fgZSyCJGLT6gWSfyRnOsp3dW4ykk4ENtm+ZxdoDudYm\nYrBmNpD6mO3F07x+LHCKpJOABcCLqFaX7yFpfml1LALWlePXAQcCayXNB3YHfjLzDzGMgSTZzUZC\nW5nN/vz+Va2U8z9/88hWyhmIln7lbX8Q+CCApN8D/tT2v5f0JeDNwOeBM4GvlLcsL8+/V17/pt3f\nH2C6NhEDpol6WwMfAN4raQ3VGMglZf8lwN5l/3vZyoLRuoavRRIxx3SxatX2t4Fvl8f3U90ud8tj\nfgn8YRvnSyCJGKQRWLVaRwJJxKAlkEREE+OSRb6zwVZJh0la1bP9TNJ5XZ0vYmSNwUV7nbVIbN9D\ndX0NkuZRzVlf1dX5IkaVxmDJw2x1bZYC99l+YJbOFzEacsvOGTkduGKWzhUxWka/QdL9grSS++AU\n4EtTvJ4MaTGnJUNaPW8AVtp+ZGsvJkNazHkZbK3lDNKtidi6EWht1NH1DbJ2AU4AvtzleSJGWlok\n07P9FH0mSomYC8ZlQVpWtkYMmCZGP5IkkEQM0gh0W+pIIIkYsCxI60J/SaxfaAyWHM8VbWU2O+Pu\nH7dSzhUvPaCVcmZkDH5dhy+QRMwxGWyNiGbMWLSgE0giBixjJBHRSNaRRERz9lh0bbpeIv8eSXdK\nukPSFZIWdHm+iFGUq3+nIWkh8G5gse0jgHlUeUkioleutalV/k6SngN2BtqZ7I8YI8Pe2qijsxaJ\n7XXAR4AHgfXAE7av7ep8ESPJwITrbUOsy67NnsCpwMHAAcAukt66leOSIS3mtFm4ZWfnuhxsfR3w\nQ9uP2n6OKifJq7c8KBnSYs6bnLnZ1jbEuhwjeRBYImln4BdUmeRv7vB8ESMpYyTTsL0CWAasBG4v\n57qoq/NFjKS6MzZDHmy6zpB2AXBBl+eIGGXVytYhjxI1zEYW+YiYzkTNbRskHSjpW5LuKgtBzy37\n95J0naR7y9c9y35J+qSkNZJuk3R0vx8hgSRiwGTX2mrYBLzP9uHAEuAcSYcD5wPX2z4UuL48h+pW\nMYeW7Wzgwn4/QwJJxCC55hqSGutIbK+3vbI8fhJYDSykWoZxWTnsMuC08vhU4DOu3AjsIWn/fj7G\n8F20Nwb9xc6MY/a4Nj4T7WU2O+sHP2xcxn1vmtl6qC5mbSQdBBwFrAD2s72+vPQwsF95vBB4qOdt\na8u+9czQ8AWSiLmmfnDfR1LvEoqLbP/aTKikXYErgfNs/0w9wdq2pfZDVwJJxCB5RqtWH7O9eLoD\nJG1PFUQutz15Y7pHJO1ve33pumwo+9cBB/a8fVHZN2MZI4kYtJZWtqpqelwCrLb90Z6XlgNnlsdn\nAl/p2f/2MnuzhOp6uBl3ayAtkojBa6+jcSzwNuB2SavKvj8DPgR8UdJZwAPAW8prXwdOAtYATwPv\n7PfECSQRA9bWgjTb36Va47Y1S7dyvIFz2jh31xnSzi3Z0e6UdF6X54oYSQY2u942xLpMI3AE8EfA\nMcDLgZMlHdLV+SJGkai3GG3Yl9F32SJ5GbDC9tO2NwHfAf6gw/NFjKYxSCPQZSC5A3iNpL1LKoGT\neOFUU0TAWASSzgZbba+W9GHgWuApYBWwecvjJJ1Ntc6fBezcVXUihpOpdUHesOt0sNX2JbZfYfs4\nYCPwg60ckwxpMaeNwxhJp9O/kl5se4Okl1CNjyzp8nwRI2nIg0QdXa8juVLS3sBzwDm2f9rx+SJG\niw0To9+36TpD2mu6LD9iLIx+HMnK1ohBG/bxjzoSSCIGLYEkIhqZvNPeiBuqQPIkGx/7hpc9sI3D\n9gEea3iqNsqY/XK2/fs2ep9ryD7TNw5tpZzfqFclgOFfbFbHUAUS2/tu6xhJN28ructslJFyZqec\nYapLm+W8QAJJRDRiYPPoT9skkEQMlMEJJIPQxm0/27p1aMrpvpxhqkub5TxvDLo28hh8iHEjaTPV\n/ZLnU92b5EzbT/dZ1u8Bf2r7ZEmnAIfb/tAUx+4B/Dvb/3eG5/hvwM9tf6SfOs5lu++wn1/9r86o\ndezVD33iltbHZ1qS5M/D6Re2j7R9BPAs8J96XyzJemf8s7O9fKogUuwB/OeZlhsNjUEagQSS4ffP\nwCGSDpJ0j6TPUOV6OVDSiZK+J2mlpC+V+5kg6fWS7pa0kp5kUpLeIelvy+P9JF0l6ftlezVVkuDf\nkrRK0t+U4/6LpJvKvWH/oqesP5f0A0nfBQ6bte/GOBqDQDKKYyRzhqT5VPdnvbrsOpSqm3OjpH2A\n/wq8zvZTkj4AvFfS/wL+ATieKjv4F6Yo/pPAd2y/SdI8YFeqe8IeYfvIcv4TyzmPoUoqvFzScVT5\nZU4HjqT6HVoJ3NLup58jbNj8a2l6Rk4CyXDaqed2Av9Mda+SA4AHyj1aoUrJcDjw/8qd1HYAvge8\nFPih7XsBJH2WkjhqC8cDbwewvRl4YvIu9T1OLNut5fmuVIFlN+CqyXEbScsbfdq5bshbG3UkkAyn\nX0y2CiaVYPFU7y7gOttnbHHcC97XkIC/tv33W5wjdwRo0xgEkoyRjK4bgWMnM/NL2kXSbwN3AwdJ\n+q1y3FRTAtcDf1zeO0/S7sCTVK2NSdcA/6Fn7GWhpBcDNwCnSdpJ0m7Av235s80hrq61qbMNsQSS\nEWX7UeAdwBWSbqN0a2z/kqor87Uy2LphiiLOBV4r6Xaq8Y3Dbf+Eqqt0h6S/sX0t8Dnge+W4ZcBu\ntldSjb18H/gn4KbOPui4M9gTtbZhlnUkEQO0+/x9/aoXnVbr2Gs2Xjy060gyRhIxaGPwzzyBJGKQ\nMv0bEW1wkj9HRDPDv2q1jgSSiEEak1SLmf6NGDRP1NtqKNdZ3SNpjaTzO675r6RFEjFABtxSi6Rc\nM/V3wAnAWuAmSctt39XKCaaRFknEINlttkiOAdbYvt/2s8DngVM7rX+RFknEgLm96d+FwEM9z9cC\nr2yr8OkkkEQM0JNsvOYbXrZPzcMXSLq55/lFtttP/diHBJKIAbL9+haLWwcc2PN8UdnXuYyRRIyP\nm4BDJR0saQeq5FOzkismLZKIMWF7k6Q/oUr/MA+41Pads3HuXP0bEY2laxMRjSWQRERjCSQR0VgC\nSUQ0lkASEY0lkEREYwkkEdFYAklENPb/AQt2+8kVSzSKAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfa5bec88>"
+       "<matplotlib.figure.Figure at 0x7f5b727e0f60>"
       ]
      },
      "metadata": {},
@@ -1685,7 +1950,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Visualization of Weights and Layers\n",
     "\n",
@@ -1694,7 +1962,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
@@ -1703,7 +1974,9 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1755,14 +2028,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolution Layer 1"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now plot the filter-weights for the first convolutional layer.\n",
     "\n",
@@ -1774,14 +2053,16 @@
    "execution_count": 46,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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f8/zzCfcxSvroR9fbmRsXf8o6v2lTtT2jkpyh30vyrjzLrv1Pe84RV6V9T9z8Mf8WvAsu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\nQwBAeP8LD/OStVmJjUoAAAAASUVORK5CYII=\n",
+      "image/png": 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gGpmb2OlI7XBkzrrmxWVI1mmrKHle5pbfp89Ibt7sm/kvpb+UmeDekY6VrvsGxmRIx2dW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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfb0475c0>"
+       "<matplotlib.figure.Figure at 0x7f5b5d320780>"
       ]
      },
      "metadata": {},
@@ -1794,14 +2075,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Convolution Layer 2"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Now plot the filter-weights for the second convolutional layer.\n",
     "\n",
@@ -1815,14 +2102,16 @@
    "execution_count": 47,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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J6Q74mOnz833eD/r3hewd/evgvaN/9M/1yGr54SJlZWX1lXSxpCpJzeYT2l+O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\nZ9cBeyfRv7aITe8k+tdWJ2v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zDKD8glEiVrZpU+wJOuBlZqJ8+HARH3DAaGYCoPxP7+sDAZ/X26bJLzirViXn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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cfaecdf98>"
+       "<matplotlib.figure.Figure at 0x7f5b732e24e0>"
       ]
      },
      "metadata": {},
@@ -1835,7 +2124,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
    ]
@@ -1844,14 +2136,16 @@
    "cell_type": "code",
    "execution_count": 48,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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16+K1o37Uz/UoaH9xkQoKCkolnScpIyn6n67xUCipQtKz2Wx2RycfC/XrgC5Y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\nAASgcQIAEIDGCQBAABonAAA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jWRb7l78EHJ8Rly8THT3K4pofOdRs3y7G+ZGRakn2H/8oH7jlFqfRGRNtN8ivSObrrzLP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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0cf8f4cda0>"
+       "<matplotlib.figure.Figure at 0x7f5b72743630>"
       ]
      },
      "metadata": {},
@@ -1864,14 +2158,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
@@ -1880,7 +2180,9 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1891,7 +2193,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Conclusion\n",
     "\n",
@@ -1904,7 +2209,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Exercises\n",
     "\n",
@@ -1928,7 +2236,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -1945,9 +2256,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1959,7 +2270,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,

From 4452ba3e72ec6cbf7948864c3d8595969be81dc8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 15 May 2017 16:24:14 +0200
Subject: [PATCH 13/61] Added support for both tf.layers and PrettyTensor.

---
 16_Reinforcement_Learning.ipynb | 4156 ++++++++++++++++---------------
 reinforcement_learning.py       |  177 +-
 2 files changed, 2280 insertions(+), 2053 deletions(-)

diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index a3fbaae..21fef0d 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -31,7 +31,7 @@
     "\n",
     "The basic idea is to have the agent estimate so-called Q-values whenever it sees an image from the game-environment. The Q-values tell the agent which action is most likely to lead to the highest cumulative reward in the future. The problem is then reduced to finding these Q-values and storing them for later retrieval using a function approximator.\n",
     "\n",
-    "This builds on some of the previous tutorials. You should be familiar with TensorFlow and Convolutional Neural Networks from Tutorial #01 and #02. It will also be helpful if you are familiar with the PrettyTensor builder API in Tutorial #03."
+    "This builds on some of the previous tutorials. You should be familiar with TensorFlow and Convolutional Neural Networks from Tutorial #01 and #02. It will also be helpful if you are familiar with one of the builder APIs in Tutorials #03 or #03-B."
    ]
   },
   {
@@ -361,7 +361,6 @@
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "import tensorflow as tf\n",
-    "import prettytensor as pt\n",
     "import gym\n",
     "import numpy as np\n",
     "import math"
@@ -412,7 +411,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.0.1'"
+       "'1.1.0'"
       ]
      },
      "execution_count": 3,
@@ -434,32 +433,6 @@
     "editable": true,
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'0.7.4'"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# PrettyTensor\n",
-    "pt.__version__"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
-    "scrolled": true
-   },
    "outputs": [
     {
      "data": {
@@ -467,7 +440,7 @@
        "'0.8.1'"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -491,7 +464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -515,7 +488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -538,7 +511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -567,7 +540,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -611,7 +584,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -623,7 +596,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "[2017-04-19 11:19:43,800] Making new env: Breakout-v0\n"
+      "[2017-05-15 15:48:47,348] Making new env: Breakout-v0\n"
      ]
     },
     {
@@ -631,6 +604,20 @@
      "output_type": "stream",
      "text": [
       "Trying to restore last checkpoint ...\n",
+      "INFO:tensorflow:Restoring parameters from checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[2017-05-15 15:48:47,868] Restoring parameters from checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Restored checkpoint from: checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
      ]
     }
@@ -654,7 +641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -677,7 +664,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -702,7 +689,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -714,7 +701,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "87584:127640000\t Epsilon: 0.10\t Reward: 22.0\t Episode Mean: 22.0\n"
+      "87584:127639721\t Epsilon: 0.10\t Reward: 12.0\t Episode Mean: 12.0\n"
      ]
     }
    ],
@@ -765,7 +752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -789,7 +776,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -816,7 +803,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -827,7 +814,7 @@
      "data": {
       "image/png": 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A5L8TESYl7VxAhySuOZDGpDAkUwqnXR7+QEX0cPkFXszNRq4Po2kOu5iPUdp4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\n3SjZ08d/0AAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be4b9eb38>"
+       "<matplotlib.figure.Figure at 0x7f8851b78940>"
       ]
      },
      "metadata": {},
@@ -860,7 +847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -872,7 +859,7 @@
      "data": {
       "image/png": 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eDkUppRqVXyf3owWlAMS2DPVyJEop1bj8Orln5pUAmtyVUs2PXyf3rMrkHqnJ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be4d362e8>"
+       "<matplotlib.figure.Figure at 0x7f8851b78710>"
       ]
      },
      "metadata": {},
@@ -902,7 +889,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -915,7 +902,7 @@
        "0.01"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -936,7 +923,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -959,7 +946,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -982,7 +969,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -1005,7 +992,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -1016,49 +1003,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "87586:127640046\tQ-min: 1.767\tQ-max: 1.787\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
-      "87586:127640089\tQ-min: 1.798\tQ-max: 1.806\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
-      "87586:127640129\tQ-min: 1.902\tQ-max: 1.919\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
-      "87586:127640165\tQ-min: 1.995\tQ-max: 2.002\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
-      "87586:127640198\tQ-min: 1.940\tQ-max: 1.965\tLives: 5\tReward: 5.0\tEpisode Mean: 0.0\n",
-      "87586:127640231\tQ-min: 1.830\tQ-max: 1.853\tLives: 5\tReward: 6.0\tEpisode Mean: 0.0\n",
-      "87586:127640265\tQ-min: 1.772\tQ-max: 1.811\tLives: 5\tReward: 10.0\tEpisode Mean: 0.0\n",
-      "87586:127640316\tQ-min: 1.689\tQ-max: 1.708\tLives: 5\tReward: 11.0\tEpisode Mean: 0.0\n",
-      "87586:127640382\tQ-min: 1.723\tQ-max: 1.773\tLives: 5\tReward: 12.0\tEpisode Mean: 0.0\n",
-      "87586:127640446\tQ-min: 1.659\tQ-max: 1.699\tLives: 5\tReward: 13.0\tEpisode Mean: 0.0\n",
-      "87586:127640513\tQ-min: 1.689\tQ-max: 1.708\tLives: 5\tReward: 14.0\tEpisode Mean: 0.0\n",
-      "87586:127640556\tQ-min: -0.225\tQ-max: 0.076\tLives: 4\tReward: 14.0\tEpisode Mean: 0.0\n",
-      "87586:127640599\tQ-min: 1.937\tQ-max: 1.965\tLives: 4\tReward: 15.0\tEpisode Mean: 0.0\n",
-      "87586:127640654\tQ-min: 1.658\tQ-max: 1.685\tLives: 4\tReward: 16.0\tEpisode Mean: 0.0\n",
-      "87586:127640716\tQ-min: 1.737\tQ-max: 1.754\tLives: 4\tReward: 17.0\tEpisode Mean: 0.0\n",
-      "87586:127640765\tQ-min: 2.054\tQ-max: 2.106\tLives: 4\tReward: 21.0\tEpisode Mean: 0.0\n",
-      "87586:127640803\tQ-min: 2.102\tQ-max: 2.130\tLives: 4\tReward: 22.0\tEpisode Mean: 0.0\n",
-      "87586:127640835\tQ-min: 1.970\tQ-max: 2.002\tLives: 4\tReward: 23.0\tEpisode Mean: 0.0\n",
-      "87586:127640868\tQ-min: 2.083\tQ-max: 2.102\tLives: 4\tReward: 24.0\tEpisode Mean: 0.0\n",
-      "87586:127640918\tQ-min: 1.700\tQ-max: 1.789\tLives: 4\tReward: 25.0\tEpisode Mean: 0.0\n",
-      "87586:127640980\tQ-min: 1.742\tQ-max: 1.766\tLives: 4\tReward: 26.0\tEpisode Mean: 0.0\n",
-      "87586:127641045\tQ-min: 1.598\tQ-max: 1.731\tLives: 4\tReward: 27.0\tEpisode Mean: 0.0\n",
-      "87586:127641113\tQ-min: 1.751\tQ-max: 1.777\tLives: 4\tReward: 28.0\tEpisode Mean: 0.0\n",
-      "87586:127641161\tQ-min: 2.024\tQ-max: 2.047\tLives: 4\tReward: 29.0\tEpisode Mean: 0.0\n",
-      "87586:127641197\tQ-min: 2.000\tQ-max: 2.013\tLives: 4\tReward: 30.0\tEpisode Mean: 0.0\n",
-      "87586:127641229\tQ-min: 2.098\tQ-max: 2.196\tLives: 4\tReward: 31.0\tEpisode Mean: 0.0\n",
-      "87586:127641262\tQ-min: 2.001\tQ-max: 2.041\tLives: 4\tReward: 32.0\tEpisode Mean: 0.0\n",
-      "87586:127641297\tQ-min: 2.056\tQ-max: 2.077\tLives: 4\tReward: 33.0\tEpisode Mean: 0.0\n",
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+      "87586:127640751\tQ-min: 1.981\tQ-max: 2.006\tLives: 3\tReward: 21.0\tEpisode Mean: 0.0\n",
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+      "87586:127641074\tQ-min: 2.312\tQ-max: 2.515\tLives: 3\tReward: 56.0\tEpisode Mean: 0.0\n",
+      "87586:127641094\tQ-min: 2.310\tQ-max: 2.421\tLives: 3\tReward: 60.0\tEpisode Mean: 0.0\n",
+      "87586:127641117\tQ-min: 2.284\tQ-max: 2.431\tLives: 3\tReward: 64.0\tEpisode Mean: 0.0\n",
+      "87586:127641137\tQ-min: 2.328\tQ-max: 2.442\tLives: 3\tReward: 65.0\tEpisode Mean: 0.0\n",
+      "87586:127641156\tQ-min: 2.411\tQ-max: 2.459\tLives: 3\tReward: 66.0\tEpisode Mean: 0.0\n",
+      "87586:127641178\tQ-min: 1.457\tQ-max: 2.612\tLives: 3\tReward: 73.0\tEpisode Mean: 0.0\n",
+      "87586:127641192\tQ-min: -0.155\tQ-max: 0.483\tLives: 2\tReward: 73.0\tEpisode Mean: 0.0\n",
+      "87586:127641236\tQ-min: 2.176\tQ-max: 2.289\tLives: 2\tReward: 74.0\tEpisode Mean: 0.0\n",
+      "87586:127641282\tQ-min: 2.060\tQ-max: 2.132\tLives: 2\tReward: 78.0\tEpisode Mean: 0.0\n",
+      "87586:127641340\tQ-min: 1.806\tQ-max: 1.967\tLives: 2\tReward: 79.0\tEpisode Mean: 0.0\n",
+      "87586:127641389\tQ-min: 2.202\tQ-max: 2.385\tLives: 2\tReward: 80.0\tEpisode Mean: 0.0\n",
+      "87586:127641418\tQ-min: 2.359\tQ-max: 2.446\tLives: 2\tReward: 81.0\tEpisode Mean: 0.0\n",
+      "87586:127641454\tQ-min: 2.278\tQ-max: 2.435\tLives: 2\tReward: 85.0\tEpisode Mean: 0.0\n",
+      "87586:127641487\tQ-min: 2.157\tQ-max: 2.391\tLives: 2\tReward: 86.0\tEpisode Mean: 0.0\n",
+      "87586:127641546\tQ-min: 1.722\tQ-max: 2.306\tLives: 2\tReward: 90.0\tEpisode Mean: 0.0\n",
+      "87586:127641570\tQ-min: 2.165\tQ-max: 2.662\tLives: 2\tReward: 94.0\tEpisode Mean: 0.0\n",
+      "87586:127641591\tQ-min: 2.422\tQ-max: 2.789\tLives: 2\tReward: 98.0\tEpisode Mean: 0.0\n",
+      "87586:127641605\tQ-min: 0.044\tQ-max: 0.432\tLives: 1\tReward: 98.0\tEpisode Mean: 0.0\n",
+      "87586:127641664\tQ-min: 1.532\tQ-max: 2.163\tLives: 1\tReward: 102.0\tEpisode Mean: 0.0\n",
+      "87586:127641723\tQ-min: 2.338\tQ-max: 2.518\tLives: 1\tReward: 106.0\tEpisode Mean: 0.0\n",
+      "87586:127641783\tQ-min: 1.870\tQ-max: 2.321\tLives: 1\tReward: 110.0\tEpisode Mean: 0.0\n",
+      "87586:127641830\tQ-min: 2.606\tQ-max: 2.781\tLives: 1\tReward: 114.0\tEpisode Mean: 0.0\n",
+      "87586:127641852\tQ-min: -0.278\tQ-max: 0.069\tLives: 0\tReward: 114.0\tEpisode Mean: 114.0\n"
      ]
     }
    ],
@@ -1092,7 +1095,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -1115,7 +1118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -1138,7 +1141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -1149,1603 +1152,1724 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
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-      "87588:127641957\tQ-min: 1.791\tQ-max: 1.807\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
-      "87588:127642001\tQ-min: 1.871\tQ-max: 1.878\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
-      "87588:127642038\tQ-min: 1.969\tQ-max: 1.993\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
-      "87588:127642059\tQ-min: -0.183\tQ-max: 0.103\tLives: 4\tReward: 4.0\tEpisode Mean: 0.0\n",
-      "87588:127642100\tQ-min: 1.892\tQ-max: 1.924\tLives: 4\tReward: 5.0\tEpisode Mean: 0.0\n",
-      "87588:127642143\tQ-min: 1.910\tQ-max: 1.925\tLives: 4\tReward: 6.0\tEpisode Mean: 0.0\n",
-      "87588:127642184\tQ-min: 1.879\tQ-max: 1.922\tLives: 4\tReward: 7.0\tEpisode Mean: 0.0\n",
-      "87588:127642222\tQ-min: 1.901\tQ-max: 1.941\tLives: 4\tReward: 8.0\tEpisode Mean: 0.0\n",
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-      "87588:127642325\tQ-min: 1.927\tQ-max: 1.978\tLives: 4\tReward: 11.0\tEpisode Mean: 0.0\n",
-      "87588:127642373\tQ-min: 1.702\tQ-max: 1.722\tLives: 4\tReward: 12.0\tEpisode Mean: 0.0\n",
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-      "87588:127642502\tQ-min: 1.691\tQ-max: 1.720\tLives: 4\tReward: 14.0\tEpisode Mean: 0.0\n",
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-      "87588:127642649\tQ-min: 1.931\tQ-max: 1.972\tLives: 4\tReward: 20.0\tEpisode Mean: 0.0\n",
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-      "87588:127642720\tQ-min: 1.864\tQ-max: 2.069\tLives: 4\tReward: 28.0\tEpisode Mean: 0.0\n",
-      "87588:127642753\tQ-min: 2.052\tQ-max: 2.083\tLives: 4\tReward: 29.0\tEpisode Mean: 0.0\n",
-      "87588:127642775\tQ-min: -0.131\tQ-max: 0.460\tLives: 3\tReward: 29.0\tEpisode Mean: 0.0\n",
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-      "87589:127643734\tQ-min: 1.775\tQ-max: 1.792\tLives: 5\tReward: 1.0\tEpisode Mean: 80.0\n",
-      "87589:127643776\tQ-min: 1.863\tQ-max: 1.872\tLives: 5\tReward: 2.0\tEpisode Mean: 80.0\n",
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-      "87589:127643852\tQ-min: 1.988\tQ-max: 2.028\tLives: 5\tReward: 4.0\tEpisode Mean: 80.0\n",
-      "87589:127643885\tQ-min: 1.973\tQ-max: 2.000\tLives: 5\tReward: 5.0\tEpisode Mean: 80.0\n",
-      "87589:127643915\tQ-min: 1.935\tQ-max: 1.953\tLives: 5\tReward: 6.0\tEpisode Mean: 80.0\n",
-      "87589:127643946\tQ-min: 1.792\tQ-max: 1.812\tLives: 5\tReward: 7.0\tEpisode Mean: 80.0\n",
-      "87589:127643992\tQ-min: 1.667\tQ-max: 1.687\tLives: 5\tReward: 8.0\tEpisode Mean: 80.0\n",
-      "87589:127644059\tQ-min: 1.696\tQ-max: 1.716\tLives: 5\tReward: 9.0\tEpisode Mean: 80.0\n",
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-      "87589:127644191\tQ-min: 1.621\tQ-max: 1.673\tLives: 5\tReward: 11.0\tEpisode Mean: 80.0\n",
-      "87589:127644240\tQ-min: 1.960\tQ-max: 1.983\tLives: 5\tReward: 12.0\tEpisode Mean: 80.0\n",
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-      "87589:127644306\tQ-min: 1.994\tQ-max: 2.017\tLives: 5\tReward: 14.0\tEpisode Mean: 80.0\n",
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-      "87589:127644358\tQ-min: -0.094\tQ-max: 0.319\tLives: 4\tReward: 15.0\tEpisode Mean: 80.0\n",
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-      "87589:127644815\tQ-min: 0.052\tQ-max: 0.276\tLives: 3\tReward: 60.0\tEpisode Mean: 80.0\n",
-      "87589:127644878\tQ-min: 1.634\tQ-max: 2.413\tLives: 3\tReward: 64.0\tEpisode Mean: 80.0\n",
-      "87589:127644935\tQ-min: 2.321\tQ-max: 2.362\tLives: 3\tReward: 65.0\tEpisode Mean: 80.0\n",
-      "87589:127644979\tQ-min: 2.174\tQ-max: 2.536\tLives: 3\tReward: 69.0\tEpisode Mean: 80.0\n",
-      "87589:127644994\tQ-min: -0.034\tQ-max: 0.382\tLives: 2\tReward: 69.0\tEpisode Mean: 80.0\n",
-      "87589:127645044\tQ-min: 1.599\tQ-max: 2.176\tLives: 2\tReward: 76.0\tEpisode Mean: 80.0\n",
-      "87589:127645066\tQ-min: 2.362\tQ-max: 2.540\tLives: 2\tReward: 77.0\tEpisode Mean: 80.0\n",
-      "87589:127645088\tQ-min: 1.918\tQ-max: 2.701\tLives: 2\tReward: 84.0\tEpisode Mean: 80.0\n",
-      "87589:127645102\tQ-min: -0.022\tQ-max: 0.068\tLives: 1\tReward: 84.0\tEpisode Mean: 80.0\n",
-      "87589:127645159\tQ-min: 1.981\tQ-max: 2.173\tLives: 1\tReward: 85.0\tEpisode Mean: 80.0\n",
-      "87589:127645231\tQ-min: 1.785\tQ-max: 2.009\tLives: 1\tReward: 86.0\tEpisode Mean: 80.0\n",
-      "87589:127645289\tQ-min: 2.147\tQ-max: 2.292\tLives: 1\tReward: 87.0\tEpisode Mean: 80.0\n",
-      "87589:127645329\tQ-min: 2.359\tQ-max: 2.482\tLives: 1\tReward: 88.0\tEpisode Mean: 80.0\n",
-      "87589:127645365\tQ-min: 1.856\tQ-max: 2.511\tLives: 1\tReward: 95.0\tEpisode Mean: 80.0\n",
-      "87589:127645388\tQ-min: 1.407\tQ-max: 3.038\tLives: 1\tReward: 99.0\tEpisode Mean: 80.0\n",
-      "87589:127645407\tQ-min: 2.163\tQ-max: 3.081\tLives: 1\tReward: 100.0\tEpisode Mean: 80.0\n",
-      "87589:127645419\tQ-min: -0.183\tQ-max: 0.050\tLives: 0\tReward: 100.0\tEpisode Mean: 90.0\n",
-      "87590:127645462\tQ-min: 1.782\tQ-max: 1.796\tLives: 5\tReward: 1.0\tEpisode Mean: 90.0\n",
-      "87590:127645508\tQ-min: 1.808\tQ-max: 1.828\tLives: 5\tReward: 2.0\tEpisode Mean: 90.0\n",
-      "87590:127645561\tQ-min: 1.690\tQ-max: 1.713\tLives: 5\tReward: 3.0\tEpisode Mean: 90.0\n",
-      "87590:127645608\tQ-min: 1.970\tQ-max: 2.003\tLives: 5\tReward: 4.0\tEpisode Mean: 90.0\n",
-      "87590:127645630\tQ-min: 0.005\tQ-max: 0.280\tLives: 4\tReward: 4.0\tEpisode Mean: 90.0\n",
-      "87590:127645670\tQ-min: 1.899\tQ-max: 1.914\tLives: 4\tReward: 5.0\tEpisode Mean: 90.0\n",
-      "87590:127645718\tQ-min: 1.676\tQ-max: 1.734\tLives: 4\tReward: 6.0\tEpisode Mean: 90.0\n",
-      "87590:127645776\tQ-min: 1.920\tQ-max: 1.942\tLives: 4\tReward: 7.0\tEpisode Mean: 90.0\n",
-      "87590:127645813\tQ-min: 1.961\tQ-max: 1.988\tLives: 4\tReward: 8.0\tEpisode Mean: 90.0\n",
-      "87590:127645846\tQ-min: 1.993\tQ-max: 2.033\tLives: 4\tReward: 9.0\tEpisode Mean: 90.0\n",
-      "87590:127645877\tQ-min: 1.902\tQ-max: 1.921\tLives: 4\tReward: 10.0\tEpisode Mean: 90.0\n",
-      "87590:127645910\tQ-min: 1.969\tQ-max: 2.000\tLives: 4\tReward: 11.0\tEpisode Mean: 90.0\n",
-      "87590:127645931\tQ-min: -0.106\tQ-max: 0.325\tLives: 3\tReward: 11.0\tEpisode Mean: 90.0\n",
-      "87590:127645975\tQ-min: 1.846\tQ-max: 1.880\tLives: 3\tReward: 12.0\tEpisode Mean: 90.0\n",
-      "87590:127646020\tQ-min: 1.888\tQ-max: 1.929\tLives: 3\tReward: 13.0\tEpisode Mean: 90.0\n",
-      "87590:127646064\tQ-min: 1.934\tQ-max: 1.972\tLives: 3\tReward: 14.0\tEpisode Mean: 90.0\n",
-      "87590:127646103\tQ-min: 1.943\tQ-max: 1.964\tLives: 3\tReward: 15.0\tEpisode Mean: 90.0\n",
-      "87590:127646136\tQ-min: 1.991\tQ-max: 2.022\tLives: 3\tReward: 19.0\tEpisode Mean: 90.0\n",
-      "87590:127646174\tQ-min: 1.887\tQ-max: 2.583\tLives: 3\tReward: 23.0\tEpisode Mean: 90.0\n",
-      "87590:127646193\tQ-min: 2.312\tQ-max: 2.485\tLives: 3\tReward: 24.0\tEpisode Mean: 90.0\n",
-      "87590:127646212\tQ-min: 2.187\tQ-max: 2.307\tLives: 3\tReward: 25.0\tEpisode Mean: 90.0\n",
-      "87590:127646234\tQ-min: 2.104\tQ-max: 2.327\tLives: 3\tReward: 29.0\tEpisode Mean: 90.0\n",
-      "87590:127646256\tQ-min: 2.364\tQ-max: 2.421\tLives: 3\tReward: 30.0\tEpisode Mean: 90.0\n",
-      "87590:127646278\tQ-min: 2.345\tQ-max: 2.527\tLives: 3\tReward: 37.0\tEpisode Mean: 90.0\n",
-      "87590:127646299\tQ-min: 2.452\tQ-max: 2.531\tLives: 3\tReward: 38.0\tEpisode Mean: 90.0\n",
-      "87590:127646317\tQ-min: 2.391\tQ-max: 2.537\tLives: 3\tReward: 39.0\tEpisode Mean: 90.0\n",
-      "87590:127646340\tQ-min: 2.395\tQ-max: 2.524\tLives: 3\tReward: 43.0\tEpisode Mean: 90.0\n",
-      "87590:127646359\tQ-min: 2.258\tQ-max: 2.519\tLives: 3\tReward: 44.0\tEpisode Mean: 90.0\n",
-      "87590:127646371\tQ-min: 0.218\tQ-max: 0.566\tLives: 2\tReward: 44.0\tEpisode Mean: 90.0\n",
-      "87590:127646436\tQ-min: 1.883\tQ-max: 1.924\tLives: 2\tReward: 45.0\tEpisode Mean: 90.0\n",
-      "87590:127646505\tQ-min: 1.933\tQ-max: 1.983\tLives: 2\tReward: 46.0\tEpisode Mean: 90.0\n",
-      "87590:127646578\tQ-min: 1.977\tQ-max: 2.124\tLives: 2\tReward: 50.0\tEpisode Mean: 90.0\n",
-      "87590:127646629\tQ-min: 2.229\tQ-max: 2.280\tLives: 2\tReward: 51.0\tEpisode Mean: 90.0\n",
-      "87590:127646661\tQ-min: 2.252\tQ-max: 2.288\tLives: 2\tReward: 52.0\tEpisode Mean: 90.0\n",
-      "87590:127646682\tQ-min: -0.102\tQ-max: 0.229\tLives: 1\tReward: 52.0\tEpisode Mean: 90.0\n",
-      "87590:127646723\tQ-min: 2.112\tQ-max: 2.132\tLives: 1\tReward: 53.0\tEpisode Mean: 90.0\n",
-      "87590:127646767\tQ-min: 2.276\tQ-max: 2.451\tLives: 1\tReward: 57.0\tEpisode Mean: 90.0\n",
-      "87590:127646782\tQ-min: -0.150\tQ-max: 0.203\tLives: 0\tReward: 57.0\tEpisode Mean: 79.0\n",
-      "87591:127646829\tQ-min: 1.771\tQ-max: 1.805\tLives: 5\tReward: 1.0\tEpisode Mean: 79.0\n",
-      "87591:127646870\tQ-min: 1.784\tQ-max: 1.796\tLives: 5\tReward: 2.0\tEpisode Mean: 79.0\n",
-      "87591:127646915\tQ-min: 1.882\tQ-max: 1.889\tLives: 5\tReward: 3.0\tEpisode Mean: 79.0\n",
-      "87591:127646950\tQ-min: 2.012\tQ-max: 2.057\tLives: 5\tReward: 4.0\tEpisode Mean: 79.0\n",
-      "87591:127646982\tQ-min: 1.971\tQ-max: 1.977\tLives: 5\tReward: 5.0\tEpisode Mean: 79.0\n",
-      "87591:127647013\tQ-min: 1.945\tQ-max: 1.953\tLives: 5\tReward: 6.0\tEpisode Mean: 79.0\n",
-      "87591:127647044\tQ-min: 1.875\tQ-max: 1.892\tLives: 5\tReward: 10.0\tEpisode Mean: 79.0\n",
-      "87591:127647068\tQ-min: -0.056\tQ-max: 0.195\tLives: 4\tReward: 10.0\tEpisode Mean: 79.0\n",
-      "87591:127647122\tQ-min: 1.693\tQ-max: 1.703\tLives: 4\tReward: 11.0\tEpisode Mean: 79.0\n",
-      "87591:127647177\tQ-min: 1.931\tQ-max: 1.940\tLives: 4\tReward: 12.0\tEpisode Mean: 79.0\n",
-      "87591:127647217\tQ-min: 1.986\tQ-max: 2.007\tLives: 4\tReward: 13.0\tEpisode Mean: 79.0\n",
-      "87591:127647255\tQ-min: 2.036\tQ-max: 2.085\tLives: 4\tReward: 14.0\tEpisode Mean: 79.0\n",
-      "87591:127647287\tQ-min: 2.034\tQ-max: 2.065\tLives: 4\tReward: 15.0\tEpisode Mean: 79.0\n",
-      "87591:127647323\tQ-min: 2.038\tQ-max: 2.059\tLives: 4\tReward: 16.0\tEpisode Mean: 79.0\n",
-      "87591:127647360\tQ-min: 2.017\tQ-max: 2.061\tLives: 4\tReward: 20.0\tEpisode Mean: 79.0\n",
-      "87591:127647410\tQ-min: 1.760\tQ-max: 1.781\tLives: 4\tReward: 21.0\tEpisode Mean: 79.0\n",
-      "87591:127647473\tQ-min: 1.782\tQ-max: 1.823\tLives: 4\tReward: 22.0\tEpisode Mean: 79.0\n",
-      "87591:127647536\tQ-min: 1.745\tQ-max: 1.767\tLives: 4\tReward: 23.0\tEpisode Mean: 79.0\n",
-      "87591:127647598\tQ-min: 1.660\tQ-max: 1.691\tLives: 4\tReward: 24.0\tEpisode Mean: 79.0\n",
-      "87591:127647645\tQ-min: 2.131\tQ-max: 2.185\tLives: 4\tReward: 25.0\tEpisode Mean: 79.0\n",
-      "87591:127647674\tQ-min: 2.064\tQ-max: 2.089\tLives: 4\tReward: 26.0\tEpisode Mean: 79.0\n",
-      "87591:127647706\tQ-min: 1.983\tQ-max: 2.032\tLives: 4\tReward: 27.0\tEpisode Mean: 79.0\n",
-      "87591:127647739\tQ-min: 2.011\tQ-max: 2.067\tLives: 4\tReward: 28.0\tEpisode Mean: 79.0\n",
-      "87591:127647773\tQ-min: 1.913\tQ-max: 2.158\tLives: 4\tReward: 32.0\tEpisode Mean: 79.0\n",
-      "87591:127647806\tQ-min: 1.973\tQ-max: 2.135\tLives: 4\tReward: 33.0\tEpisode Mean: 79.0\n",
-      "87591:127647827\tQ-min: -0.069\tQ-max: 0.166\tLives: 3\tReward: 33.0\tEpisode Mean: 79.0\n",
-      "87591:127647876\tQ-min: 1.890\tQ-max: 1.962\tLives: 3\tReward: 34.0\tEpisode Mean: 79.0\n",
-      "87591:127647919\tQ-min: 2.035\tQ-max: 2.102\tLives: 3\tReward: 35.0\tEpisode Mean: 79.0\n",
-      "87591:127647962\tQ-min: 2.088\tQ-max: 2.182\tLives: 3\tReward: 39.0\tEpisode Mean: 79.0\n",
-      "87591:127648001\tQ-min: 2.207\tQ-max: 2.255\tLives: 3\tReward: 43.0\tEpisode Mean: 79.0\n",
-      "87591:127648037\tQ-min: 2.193\tQ-max: 2.259\tLives: 3\tReward: 44.0\tEpisode Mean: 79.0\n",
-      "87591:127648073\tQ-min: 2.094\tQ-max: 2.231\tLives: 3\tReward: 48.0\tEpisode Mean: 79.0\n",
-      "87591:127648106\tQ-min: 2.185\tQ-max: 2.267\tLives: 3\tReward: 49.0\tEpisode Mean: 79.0\n",
-      "87591:127648160\tQ-min: 1.744\tQ-max: 1.795\tLives: 3\tReward: 50.0\tEpisode Mean: 79.0\n",
-      "87591:127648227\tQ-min: 1.767\tQ-max: 1.814\tLives: 3\tReward: 51.0\tEpisode Mean: 79.0\n",
-      "87591:127648299\tQ-min: 1.462\tQ-max: 1.818\tLives: 3\tReward: 52.0\tEpisode Mean: 79.0\n",
-      "87591:127648365\tQ-min: 2.078\tQ-max: 2.492\tLives: 3\tReward: 56.0\tEpisode Mean: 79.0\n",
-      "87591:127648386\tQ-min: 2.260\tQ-max: 2.447\tLives: 3\tReward: 57.0\tEpisode Mean: 79.0\n",
-      "87591:127648406\tQ-min: 2.177\tQ-max: 2.367\tLives: 3\tReward: 58.0\tEpisode Mean: 79.0\n",
-      "87591:127648426\tQ-min: 2.419\tQ-max: 2.528\tLives: 3\tReward: 59.0\tEpisode Mean: 79.0\n",
-      "87591:127648439\tQ-min: 0.049\tQ-max: 0.212\tLives: 2\tReward: 59.0\tEpisode Mean: 79.0\n",
-      "87591:127648484\tQ-min: 2.005\tQ-max: 2.081\tLives: 2\tReward: 63.0\tEpisode Mean: 79.0\n",
-      "87591:127648530\tQ-min: 2.056\tQ-max: 2.156\tLives: 2\tReward: 67.0\tEpisode Mean: 79.0\n",
-      "87591:127648589\tQ-min: 2.019\tQ-max: 2.510\tLives: 2\tReward: 71.0\tEpisode Mean: 79.0\n",
-      "87591:127648642\tQ-min: 2.222\tQ-max: 2.368\tLives: 2\tReward: 75.0\tEpisode Mean: 79.0\n",
-      "87591:127648677\tQ-min: 2.273\tQ-max: 2.310\tLives: 2\tReward: 76.0\tEpisode Mean: 79.0\n",
-      "87591:127648710\tQ-min: 2.219\tQ-max: 2.331\tLives: 2\tReward: 80.0\tEpisode Mean: 79.0\n",
-      "87591:127648742\tQ-min: 2.265\tQ-max: 2.504\tLives: 2\tReward: 84.0\tEpisode Mean: 79.0\n",
-      "87591:127648767\tQ-min: 2.339\tQ-max: 2.488\tLives: 2\tReward: 88.0\tEpisode Mean: 79.0\n",
-      "87591:127648788\tQ-min: 2.077\tQ-max: 2.568\tLives: 2\tReward: 92.0\tEpisode Mean: 79.0\n",
-      "87591:127648809\tQ-min: 2.260\tQ-max: 2.533\tLives: 2\tReward: 96.0\tEpisode Mean: 79.0\n",
-      "87591:127648830\tQ-min: 1.901\tQ-max: 2.720\tLives: 2\tReward: 103.0\tEpisode Mean: 79.0\n",
-      "87591:127648853\tQ-min: 2.081\tQ-max: 2.668\tLives: 2\tReward: 107.0\tEpisode Mean: 79.0\n",
-      "87591:127648873\tQ-min: 2.564\tQ-max: 2.679\tLives: 2\tReward: 108.0\tEpisode Mean: 79.0\n",
-      "87591:127648892\tQ-min: 2.543\tQ-max: 2.745\tLives: 2\tReward: 112.0\tEpisode Mean: 79.0\n",
-      "87591:127648905\tQ-min: 0.118\tQ-max: 0.498\tLives: 1\tReward: 112.0\tEpisode Mean: 79.0\n",
-      "87591:127648962\tQ-min: 2.145\tQ-max: 2.298\tLives: 1\tReward: 116.0\tEpisode Mean: 79.0\n",
-      "87591:127649025\tQ-min: 2.106\tQ-max: 2.738\tLives: 1\tReward: 123.0\tEpisode Mean: 79.0\n",
-      "87591:127649040\tQ-min: -0.075\tQ-max: 0.226\tLives: 0\tReward: 123.0\tEpisode Mean: 90.0\n",
-      "87592:127649096\tQ-min: 1.651\tQ-max: 1.673\tLives: 5\tReward: 1.0\tEpisode Mean: 90.0\n",
-      "87592:127649148\tQ-min: 1.824\tQ-max: 1.838\tLives: 5\tReward: 2.0\tEpisode Mean: 90.0\n",
-      "87592:127649192\tQ-min: 1.875\tQ-max: 1.903\tLives: 5\tReward: 3.0\tEpisode Mean: 90.0\n",
-      "87592:127649228\tQ-min: 2.067\tQ-max: 2.100\tLives: 5\tReward: 4.0\tEpisode Mean: 90.0\n",
-      "87592:127649260\tQ-min: 2.018\tQ-max: 2.133\tLives: 5\tReward: 5.0\tEpisode Mean: 90.0\n",
-      "87592:127649294\tQ-min: 1.890\tQ-max: 1.913\tLives: 5\tReward: 6.0\tEpisode Mean: 90.0\n",
-      "87592:127649325\tQ-min: 1.776\tQ-max: 1.824\tLives: 5\tReward: 7.0\tEpisode Mean: 90.0\n",
-      "87592:127649370\tQ-min: 1.625\tQ-max: 1.662\tLives: 5\tReward: 8.0\tEpisode Mean: 90.0\n",
-      "87592:127649438\tQ-min: 1.618\tQ-max: 1.713\tLives: 5\tReward: 9.0\tEpisode Mean: 90.0\n",
-      "87592:127649503\tQ-min: 1.632\tQ-max: 1.649\tLives: 5\tReward: 10.0\tEpisode Mean: 90.0\n",
-      "87592:127649569\tQ-min: 1.584\tQ-max: 1.635\tLives: 5\tReward: 11.0\tEpisode Mean: 90.0\n",
-      "87592:127649619\tQ-min: 2.002\tQ-max: 2.035\tLives: 5\tReward: 12.0\tEpisode Mean: 90.0\n",
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-      "87592:127650616\tQ-min: -0.359\tQ-max: 0.338\tLives: 4\tReward: 228.0\tEpisode Mean: 90.0\n",
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-      "87592:127650792\tQ-min: 2.058\tQ-max: 4.554\tLives: 4\tReward: 300.0\tEpisode Mean: 90.0\n",
-      "87592:127650812\tQ-min: 0.003\tQ-max: 0.512\tLives: 3\tReward: 300.0\tEpisode Mean: 90.0\n",
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-      "87592:127651023\tQ-min: 1.857\tQ-max: 4.926\tLives: 3\tReward: 351.0\tEpisode Mean: 90.0\n",
-      "87592:127651075\tQ-min: -0.036\tQ-max: 0.720\tLives: 2\tReward: 351.0\tEpisode Mean: 90.0\n",
-      "87592:127651144\tQ-min: 1.646\tQ-max: 3.200\tLives: 2\tReward: 355.0\tEpisode Mean: 90.0\n",
-      "87592:127651164\tQ-min: -0.252\tQ-max: 0.717\tLives: 1\tReward: 355.0\tEpisode Mean: 90.0\n",
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-      "87592:127651294\tQ-min: 1.397\tQ-max: 2.044\tLives: 1\tReward: 360.0\tEpisode Mean: 90.0\n",
-      "87592:127651314\tQ-min: 1.209\tQ-max: 3.124\tLives: 1\tReward: 364.0\tEpisode Mean: 90.0\n",
-      "87592:127651322\tQ-min: 2.887\tQ-max: 4.312\tLives: 1\tReward: 368.0\tEpisode Mean: 90.0\n",
-      "87592:127651329\tQ-min: 1.640\tQ-max: 2.904\tLives: 1\tReward: 372.0\tEpisode Mean: 90.0\n",
-      "87592:127651339\tQ-min: 1.747\tQ-max: 3.081\tLives: 1\tReward: 376.0\tEpisode Mean: 90.0\n",
-      "87592:127651348\tQ-min: 1.704\tQ-max: 2.896\tLives: 1\tReward: 380.0\tEpisode Mean: 90.0\n",
-      "87592:127651359\tQ-min: -0.101\tQ-max: 2.532\tLives: 1\tReward: 381.0\tEpisode Mean: 90.0\n",
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-      "87593:127652332\tQ-min: -0.201\tQ-max: 0.293\tLives: 1\tReward: 25.0\tEpisode Mean: 148.2\n",
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-      "87593:127652652\tQ-min: -0.131\tQ-max: 0.119\tLives: 0\tReward: 43.0\tEpisode Mean: 130.7\n",
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-      "87594:127652831\tQ-min: -0.221\tQ-max: 0.168\tLives: 4\tReward: 3.0\tEpisode Mean: 130.7\n",
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-      "87595:127656441\tQ-min: -0.137\tQ-max: 0.415\tLives: 1\tReward: 75.0\tEpisode Mean: 124.3\n",
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-      "87595:127656578\tQ-min: 1.994\tQ-max: 2.153\tLives: 1\tReward: 83.0\tEpisode Mean: 124.3\n",
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-      "87595:127656674\tQ-min: 2.155\tQ-max: 2.412\tLives: 1\tReward: 88.0\tEpisode Mean: 124.3\n",
-      "87595:127656696\tQ-min: 2.417\tQ-max: 2.483\tLives: 1\tReward: 92.0\tEpisode Mean: 124.3\n",
-      "87595:127656718\tQ-min: 2.471\tQ-max: 2.509\tLives: 1\tReward: 96.0\tEpisode Mean: 124.3\n",
-      "87595:127656741\tQ-min: 2.288\tQ-max: 2.486\tLives: 1\tReward: 100.0\tEpisode Mean: 124.3\n",
-      "87595:127656756\tQ-min: -0.398\tQ-max: 0.151\tLives: 0\tReward: 100.0\tEpisode Mean: 121.2\n",
-      "87596:127656800\tQ-min: 1.752\tQ-max: 1.776\tLives: 5\tReward: 1.0\tEpisode Mean: 121.2\n",
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-      "87596:127656947\tQ-min: 1.975\tQ-max: 2.010\tLives: 5\tReward: 4.0\tEpisode Mean: 121.2\n",
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-      "87596:127657537\tQ-min: -0.069\tQ-max: 0.212\tLives: 3\tReward: 19.0\tEpisode Mean: 121.2\n",
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-      "87596:127658753\tQ-min: -0.032\tQ-max: 0.342\tLives: 1\tReward: 84.0\tEpisode Mean: 121.2\n",
-      "87596:127658800\tQ-min: 1.889\tQ-max: 2.049\tLives: 1\tReward: 88.0\tEpisode Mean: 121.2\n",
-      "87596:127658844\tQ-min: 2.164\tQ-max: 2.220\tLives: 1\tReward: 89.0\tEpisode Mean: 121.2\n",
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-      "87596:127658973\tQ-min: -0.243\tQ-max: 0.129\tLives: 0\tReward: 107.0\tEpisode Mean: 119.7\n",
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-      "87597:127661016\tQ-min: 1.828\tQ-max: 2.659\tLives: 2\tReward: 107.0\tEpisode Mean: 119.7\n",
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-      "87597:127661057\tQ-min: 2.465\tQ-max: 2.723\tLives: 2\tReward: 112.0\tEpisode Mean: 119.7\n",
-      "87597:127661073\tQ-min: -0.070\tQ-max: 0.399\tLives: 1\tReward: 112.0\tEpisode Mean: 119.7\n",
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-      "87597:127661143\tQ-min: -0.218\tQ-max: 0.260\tLives: 0\tReward: 116.0\tEpisode Mean: 119.3\n",
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-      "87598:127661709\tQ-min: 1.667\tQ-max: 1.704\tLives: 5\tReward: 11.0\tEpisode Mean: 119.3\n",
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-      "87598:127661789\tQ-min: 1.967\tQ-max: 2.024\tLives: 5\tReward: 13.0\tEpisode Mean: 119.3\n",
-      "87598:127661810\tQ-min: -0.354\tQ-max: 0.091\tLives: 4\tReward: 13.0\tEpisode Mean: 119.3\n",
-      "87598:127661852\tQ-min: 1.892\tQ-max: 1.921\tLives: 4\tReward: 14.0\tEpisode Mean: 119.3\n",
-      "87598:127661896\tQ-min: 1.922\tQ-max: 1.965\tLives: 4\tReward: 15.0\tEpisode Mean: 119.3\n",
-      "87598:127661952\tQ-min: 1.670\tQ-max: 1.706\tLives: 4\tReward: 16.0\tEpisode Mean: 119.3\n",
-      "87598:127662001\tQ-min: 1.951\tQ-max: 1.978\tLives: 4\tReward: 17.0\tEpisode Mean: 119.3\n",
-      "87598:127662037\tQ-min: 2.090\tQ-max: 2.104\tLives: 4\tReward: 18.0\tEpisode Mean: 119.3\n",
-      "87598:127662074\tQ-min: 2.078\tQ-max: 2.103\tLives: 4\tReward: 22.0\tEpisode Mean: 119.3\n",
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-      "87598:127662221\tQ-min: 1.697\tQ-max: 1.741\tLives: 4\tReward: 25.0\tEpisode Mean: 119.3\n",
-      "87598:127662264\tQ-min: -0.043\tQ-max: 0.257\tLives: 3\tReward: 25.0\tEpisode Mean: 119.3\n",
-      "87598:127662316\tQ-min: 1.898\tQ-max: 1.918\tLives: 3\tReward: 26.0\tEpisode Mean: 119.3\n",
-      "87598:127662361\tQ-min: 1.909\tQ-max: 1.937\tLives: 3\tReward: 27.0\tEpisode Mean: 119.3\n",
-      "87598:127662407\tQ-min: 2.013\tQ-max: 2.042\tLives: 3\tReward: 28.0\tEpisode Mean: 119.3\n",
-      "87598:127662444\tQ-min: 1.961\tQ-max: 1.991\tLives: 3\tReward: 29.0\tEpisode Mean: 119.3\n",
-      "87598:127662477\tQ-min: 2.115\tQ-max: 2.183\tLives: 3\tReward: 30.0\tEpisode Mean: 119.3\n",
-      "87598:127662509\tQ-min: 2.000\tQ-max: 2.069\tLives: 3\tReward: 31.0\tEpisode Mean: 119.3\n",
-      "87598:127662544\tQ-min: 2.006\tQ-max: 2.097\tLives: 3\tReward: 35.0\tEpisode Mean: 119.3\n",
-      "87598:127662593\tQ-min: 1.437\tQ-max: 1.659\tLives: 3\tReward: 36.0\tEpisode Mean: 119.3\n",
-      "87598:127662665\tQ-min: 1.732\tQ-max: 1.751\tLives: 3\tReward: 37.0\tEpisode Mean: 119.3\n",
-      "87598:127662729\tQ-min: 1.667\tQ-max: 1.811\tLives: 3\tReward: 38.0\tEpisode Mean: 119.3\n",
-      "87598:127662793\tQ-min: 1.746\tQ-max: 1.779\tLives: 3\tReward: 39.0\tEpisode Mean: 119.3\n",
-      "87598:127662843\tQ-min: 2.004\tQ-max: 2.053\tLives: 3\tReward: 40.0\tEpisode Mean: 119.3\n",
-      "87598:127662878\tQ-min: 2.104\tQ-max: 2.161\tLives: 3\tReward: 44.0\tEpisode Mean: 119.3\n",
-      "87598:127662912\tQ-min: 2.015\tQ-max: 2.115\tLives: 3\tReward: 48.0\tEpisode Mean: 119.3\n",
-      "87598:127662945\tQ-min: 2.035\tQ-max: 2.218\tLives: 3\tReward: 52.0\tEpisode Mean: 119.3\n",
-      "87598:127662981\tQ-min: 2.047\tQ-max: 2.229\tLives: 3\tReward: 56.0\tEpisode Mean: 119.3\n",
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-      "87598:127663057\tQ-min: 1.995\tQ-max: 2.390\tLives: 3\tReward: 64.0\tEpisode Mean: 119.3\n",
-      "87598:127663079\tQ-min: 2.243\tQ-max: 2.510\tLives: 3\tReward: 68.0\tEpisode Mean: 119.3\n",
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-      "87598:127663188\tQ-min: 2.030\tQ-max: 2.488\tLives: 3\tReward: 91.0\tEpisode Mean: 119.3\n",
-      "87598:127663203\tQ-min: 0.163\tQ-max: 0.445\tLives: 2\tReward: 91.0\tEpisode Mean: 119.3\n",
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-      "87598:127663306\tQ-min: 2.173\tQ-max: 2.579\tLives: 2\tReward: 96.0\tEpisode Mean: 119.3\n",
-      "87598:127663321\tQ-min: -0.015\tQ-max: 0.340\tLives: 1\tReward: 96.0\tEpisode Mean: 119.3\n",
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-      "87598:127663423\tQ-min: 2.059\tQ-max: 2.137\tLives: 1\tReward: 101.0\tEpisode Mean: 119.3\n",
-      "87598:127663475\tQ-min: 2.365\tQ-max: 2.465\tLives: 1\tReward: 102.0\tEpisode Mean: 119.3\n",
-      "87598:127663516\tQ-min: 2.050\tQ-max: 2.623\tLives: 1\tReward: 109.0\tEpisode Mean: 119.3\n",
-      "87598:127663539\tQ-min: 2.045\tQ-max: 2.740\tLives: 1\tReward: 113.0\tEpisode Mean: 119.3\n",
-      "87598:127663560\tQ-min: 2.421\tQ-max: 2.652\tLives: 1\tReward: 117.0\tEpisode Mean: 119.3\n",
-      "87598:127663581\tQ-min: 1.980\tQ-max: 2.516\tLives: 1\tReward: 121.0\tEpisode Mean: 119.3\n",
-      "87598:127663603\tQ-min: 2.362\tQ-max: 2.860\tLives: 1\tReward: 125.0\tEpisode Mean: 119.3\n",
-      "87598:127663623\tQ-min: 2.004\tQ-max: 3.475\tLives: 1\tReward: 129.0\tEpisode Mean: 119.3\n",
-      "87598:127663644\tQ-min: 2.571\tQ-max: 2.768\tLives: 1\tReward: 133.0\tEpisode Mean: 119.3\n",
-      "87598:127663665\tQ-min: 2.195\tQ-max: 2.878\tLives: 1\tReward: 137.0\tEpisode Mean: 119.3\n",
-      "87598:127663679\tQ-min: -0.607\tQ-max: -0.022\tLives: 0\tReward: 137.0\tEpisode Mean: 120.9\n",
-      "87599:127663726\tQ-min: 1.737\tQ-max: 1.761\tLives: 5\tReward: 1.0\tEpisode Mean: 120.9\n",
-      "87599:127663778\tQ-min: 1.641\tQ-max: 1.655\tLives: 5\tReward: 2.0\tEpisode Mean: 120.9\n",
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-      "87599:127664422\tQ-min: -0.064\tQ-max: 0.073\tLives: 3\tReward: 16.0\tEpisode Mean: 120.9\n",
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-      "87601:127669341\tQ-min: -0.015\tQ-max: 0.200\tLives: 1\tReward: 95.0\tEpisode Mean: 115.6\n",
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-      "87612:127690475\tQ-min: -0.006\tQ-max: 0.193\tLives: 3\tReward: 15.0\tEpisode Mean: 114.7\n",
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-      "87612:127690911\tQ-min: -0.162\tQ-max: 0.121\tLives: 2\tReward: 47.0\tEpisode Mean: 114.7\n",
-      "87612:127690942\tQ-min: -0.062\tQ-max: 0.110\tLives: 1\tReward: 47.0\tEpisode Mean: 114.7\n",
-      "87612:127690988\tQ-min: 2.038\tQ-max: 2.127\tLives: 1\tReward: 48.0\tEpisode Mean: 114.7\n",
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-      "87612:127691235\tQ-min: 2.541\tQ-max: 2.658\tLives: 1\tReward: 63.0\tEpisode Mean: 114.7\n",
-      "87612:127691257\tQ-min: 2.391\tQ-max: 2.556\tLives: 1\tReward: 64.0\tEpisode Mean: 114.7\n",
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-      "87612:127691314\tQ-min: -0.039\tQ-max: 0.191\tLives: 0\tReward: 72.0\tEpisode Mean: 113.0\n",
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-      "87614:127694696\tQ-min: -0.492\tQ-max: 0.288\tLives: 2\tReward: 55.0\tEpisode Mean: 111.3\n",
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-      "87614:127695053\tQ-min: -0.225\tQ-max: 0.476\tLives: 1\tReward: 86.0\tEpisode Mean: 111.3\n",
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-      "87614:127695260\tQ-min: -0.245\tQ-max: 0.131\tLives: 0\tReward: 99.0\tEpisode Mean: 110.9\n",
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-      "87615:127696487\tQ-min: -0.145\tQ-max: 0.130\tLives: 4\tReward: 50.0\tEpisode Mean: 110.9\n",
-      "87615:127696535\tQ-min: 2.262\tQ-max: 2.437\tLives: 4\tReward: 54.0\tEpisode Mean: 110.9\n",
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-      "87615:127696572\tQ-min: -0.210\tQ-max: 0.358\tLives: 3\tReward: 58.0\tEpisode Mean: 110.9\n",
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-      "87615:127696972\tQ-min: -0.173\tQ-max: 0.569\tLives: 1\tReward: 89.0\tEpisode Mean: 110.9\n",
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-      "87616:127698294\tQ-min: 2.130\tQ-max: 2.170\tLives: 5\tReward: 35.0\tEpisode Mean: 110.4\n",
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-      "87616:127698401\tQ-min: 2.063\tQ-max: 2.154\tLives: 5\tReward: 41.0\tEpisode Mean: 110.4\n",
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-      "87616:127698460\tQ-min: -0.165\tQ-max: 0.070\tLives: 4\tReward: 45.0\tEpisode Mean: 110.4\n",
-      "87616:127698501\tQ-min: 1.846\tQ-max: 2.047\tLives: 4\tReward: 49.0\tEpisode Mean: 110.4\n",
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-      "87616:127698663\tQ-min: 2.200\tQ-max: 2.331\tLives: 4\tReward: 58.0\tEpisode Mean: 110.4\n",
-      "87616:127698697\tQ-min: 2.231\tQ-max: 2.292\tLives: 4\tReward: 62.0\tEpisode Mean: 110.4\n",
-      "87616:127698719\tQ-min: -0.132\tQ-max: 0.132\tLives: 3\tReward: 62.0\tEpisode Mean: 110.4\n",
-      "87616:127698766\tQ-min: 2.324\tQ-max: 2.472\tLives: 3\tReward: 66.0\tEpisode Mean: 110.4\n",
-      "87616:127698780\tQ-min: -0.485\tQ-max: 0.170\tLives: 2\tReward: 66.0\tEpisode Mean: 110.4\n",
-      "87616:127698845\tQ-min: 1.700\tQ-max: 2.194\tLives: 2\tReward: 70.0\tEpisode Mean: 110.4\n",
-      "87616:127698858\tQ-min: -0.183\tQ-max: 0.237\tLives: 1\tReward: 70.0\tEpisode Mean: 110.4\n",
-      "87616:127698912\tQ-min: 1.906\tQ-max: 1.984\tLives: 1\tReward: 71.0\tEpisode Mean: 110.4\n",
-      "87616:127698981\tQ-min: 1.634\tQ-max: 2.061\tLives: 1\tReward: 75.0\tEpisode Mean: 110.4\n",
-      "87616:127699002\tQ-min: 2.364\tQ-max: 2.565\tLives: 1\tReward: 79.0\tEpisode Mean: 110.4\n",
-      "87616:127699023\tQ-min: 2.297\tQ-max: 2.456\tLives: 1\tReward: 83.0\tEpisode Mean: 110.4\n",
-      "87616:127699047\tQ-min: 2.357\tQ-max: 2.603\tLives: 1\tReward: 90.0\tEpisode Mean: 110.4\n",
-      "87616:127699071\tQ-min: 2.331\tQ-max: 2.936\tLives: 1\tReward: 97.0\tEpisode Mean: 110.4\n",
-      "87616:127699094\tQ-min: 2.704\tQ-max: 2.889\tLives: 1\tReward: 101.0\tEpisode Mean: 110.4\n",
-      "87616:127699118\tQ-min: 2.564\tQ-max: 3.139\tLives: 1\tReward: 105.0\tEpisode Mean: 110.4\n",
-      "87616:127699140\tQ-min: 2.534\tQ-max: 3.215\tLives: 1\tReward: 109.0\tEpisode Mean: 110.4\n",
-      "87616:127699152\tQ-min: 0.192\tQ-max: 0.497\tLives: 0\tReward: 109.0\tEpisode Mean: 110.4\n",
-      "87617:127699197\tQ-min: 1.694\tQ-max: 1.702\tLives: 5\tReward: 1.0\tEpisode Mean: 110.4\n",
-      "87617:127699252\tQ-min: 1.658\tQ-max: 1.666\tLives: 5\tReward: 2.0\tEpisode Mean: 110.4\n",
-      "87617:127699301\tQ-min: 1.892\tQ-max: 1.912\tLives: 5\tReward: 3.0\tEpisode Mean: 110.4\n",
-      "87617:127699338\tQ-min: 1.997\tQ-max: 2.023\tLives: 5\tReward: 4.0\tEpisode Mean: 110.4\n",
-      "87617:127699372\tQ-min: 1.976\tQ-max: 2.003\tLives: 5\tReward: 5.0\tEpisode Mean: 110.4\n",
-      "87617:127699403\tQ-min: 1.906\tQ-max: 1.942\tLives: 5\tReward: 6.0\tEpisode Mean: 110.4\n",
-      "87617:127699434\tQ-min: 1.797\tQ-max: 1.812\tLives: 5\tReward: 7.0\tEpisode Mean: 110.4\n",
-      "87617:127699478\tQ-min: 1.615\tQ-max: 1.650\tLives: 5\tReward: 8.0\tEpisode Mean: 110.4\n",
-      "87617:127699542\tQ-min: 1.665\tQ-max: 1.680\tLives: 5\tReward: 9.0\tEpisode Mean: 110.4\n",
-      "87617:127699610\tQ-min: 1.693\tQ-max: 1.714\tLives: 5\tReward: 10.0\tEpisode Mean: 110.4\n",
-      "87617:127699671\tQ-min: 1.673\tQ-max: 1.692\tLives: 5\tReward: 11.0\tEpisode Mean: 110.4\n",
-      "87617:127699720\tQ-min: 1.956\tQ-max: 1.970\tLives: 5\tReward: 12.0\tEpisode Mean: 110.4\n",
-      "87617:127699754\tQ-min: 1.901\tQ-max: 1.931\tLives: 5\tReward: 13.0\tEpisode Mean: 110.4\n",
-      "87617:127699789\tQ-min: 1.956\tQ-max: 2.007\tLives: 5\tReward: 14.0\tEpisode Mean: 110.4\n",
-      "87617:127699823\tQ-min: 2.002\tQ-max: 2.022\tLives: 5\tReward: 15.0\tEpisode Mean: 110.4\n",
-      "87617:127699856\tQ-min: 1.966\tQ-max: 1.983\tLives: 5\tReward: 16.0\tEpisode Mean: 110.4\n",
-      "87617:127699889\tQ-min: 1.925\tQ-max: 1.947\tLives: 5\tReward: 17.0\tEpisode Mean: 110.4\n",
-      "87617:127699922\tQ-min: 2.050\tQ-max: 2.089\tLives: 5\tReward: 18.0\tEpisode Mean: 110.4\n",
-      "87617:127699956\tQ-min: 1.911\tQ-max: 1.959\tLives: 5\tReward: 19.0\tEpisode Mean: 110.4\n",
-      "87617:127699987\tQ-min: 1.982\tQ-max: 2.019\tLives: 5\tReward: 20.0\tEpisode Mean: 110.4\n",
-      "87617:127700020\tQ-min: 1.983\tQ-max: 2.017\tLives: 5\tReward: 21.0\tEpisode Mean: 110.4\n",
-      "87617:127700053\tQ-min: 1.962\tQ-max: 1.982\tLives: 5\tReward: 22.0\tEpisode Mean: 110.4\n",
-      "87617:127700087\tQ-min: 2.054\tQ-max: 2.074\tLives: 5\tReward: 23.0\tEpisode Mean: 110.4\n",
-      "87617:127700119\tQ-min: 1.990\tQ-max: 2.013\tLives: 5\tReward: 24.0\tEpisode Mean: 110.4\n",
-      "87617:127700153\tQ-min: 1.946\tQ-max: 2.082\tLives: 5\tReward: 25.0\tEpisode Mean: 110.4\n",
-      "87617:127700187\tQ-min: 2.120\tQ-max: 2.171\tLives: 5\tReward: 29.0\tEpisode Mean: 110.4\n",
-      "87617:127700221\tQ-min: 2.097\tQ-max: 2.204\tLives: 5\tReward: 30.0\tEpisode Mean: 110.4\n",
-      "87617:127700255\tQ-min: 2.083\tQ-max: 2.144\tLives: 5\tReward: 34.0\tEpisode Mean: 110.4\n",
-      "87617:127700289\tQ-min: 2.044\tQ-max: 2.494\tLives: 5\tReward: 38.0\tEpisode Mean: 110.4\n",
-      "87617:127700303\tQ-min: -0.229\tQ-max: -0.038\tLives: 4\tReward: 38.0\tEpisode Mean: 110.4\n",
-      "87617:127700350\tQ-min: 2.320\tQ-max: 2.658\tLives: 4\tReward: 45.0\tEpisode Mean: 110.4\n",
-      "87617:127700371\tQ-min: 2.498\tQ-max: 2.616\tLives: 4\tReward: 46.0\tEpisode Mean: 110.4\n",
-      "87617:127700389\tQ-min: 2.313\tQ-max: 2.581\tLives: 4\tReward: 47.0\tEpisode Mean: 110.4\n",
-      "87617:127700409\tQ-min: 2.397\tQ-max: 2.636\tLives: 4\tReward: 48.0\tEpisode Mean: 110.4\n",
-      "87617:127700429\tQ-min: 2.397\tQ-max: 2.452\tLives: 4\tReward: 49.0\tEpisode Mean: 110.4\n",
-      "87617:127700442\tQ-min: 0.100\tQ-max: 0.184\tLives: 3\tReward: 49.0\tEpisode Mean: 110.4\n",
-      "87617:127700489\tQ-min: 2.196\tQ-max: 2.277\tLives: 3\tReward: 53.0\tEpisode Mean: 110.4\n",
-      "87617:127700549\tQ-min: 1.910\tQ-max: 2.034\tLives: 3\tReward: 54.0\tEpisode Mean: 110.4\n",
-      "87617:127700603\tQ-min: 2.033\tQ-max: 2.343\tLives: 3\tReward: 58.0\tEpisode Mean: 110.4\n",
-      "87617:127700643\tQ-min: 2.113\tQ-max: 2.383\tLives: 3\tReward: 62.0\tEpisode Mean: 110.4\n",
-      "87617:127700678\tQ-min: 1.847\tQ-max: 2.895\tLives: 3\tReward: 66.0\tEpisode Mean: 110.4\n",
-      "87617:127700700\tQ-min: 2.374\tQ-max: 2.658\tLives: 3\tReward: 73.0\tEpisode Mean: 110.4\n",
-      "87617:127700724\tQ-min: 2.356\tQ-max: 2.610\tLives: 3\tReward: 77.0\tEpisode Mean: 110.4\n",
-      "87617:127700738\tQ-min: 0.235\tQ-max: 0.481\tLives: 2\tReward: 77.0\tEpisode Mean: 110.4\n",
-      "87617:127700785\tQ-min: 2.617\tQ-max: 3.107\tLives: 2\tReward: 84.0\tEpisode Mean: 110.4\n",
-      "87617:127700808\tQ-min: 2.499\tQ-max: 2.759\tLives: 2\tReward: 88.0\tEpisode Mean: 110.4\n",
-      "87617:127700824\tQ-min: -0.013\tQ-max: 0.391\tLives: 1\tReward: 88.0\tEpisode Mean: 110.4\n",
-      "87617:127700878\tQ-min: 1.760\tQ-max: 1.912\tLives: 1\tReward: 89.0\tEpisode Mean: 110.4\n",
-      "87617:127700945\tQ-min: 1.799\tQ-max: 2.087\tLives: 1\tReward: 93.0\tEpisode Mean: 110.4\n",
-      "87617:127701003\tQ-min: 2.359\tQ-max: 2.529\tLives: 1\tReward: 97.0\tEpisode Mean: 110.4\n",
-      "87617:127701041\tQ-min: 2.311\tQ-max: 2.677\tLives: 1\tReward: 101.0\tEpisode Mean: 110.4\n",
-      "87617:127701075\tQ-min: 2.481\tQ-max: 2.649\tLives: 1\tReward: 105.0\tEpisode Mean: 110.4\n",
-      "87617:127701107\tQ-min: 2.365\tQ-max: 2.683\tLives: 1\tReward: 106.0\tEpisode Mean: 110.4\n",
-      "87617:127701142\tQ-min: 2.326\tQ-max: 2.703\tLives: 1\tReward: 110.0\tEpisode Mean: 110.4\n",
-      "87617:127701197\tQ-min: 1.775\tQ-max: 2.206\tLives: 1\tReward: 114.0\tEpisode Mean: 110.4\n",
-      "87617:127701271\tQ-min: 2.262\tQ-max: 2.510\tLives: 1\tReward: 115.0\tEpisode Mean: 110.4\n",
-      "87617:127701340\tQ-min: 1.927\tQ-max: 2.832\tLives: 1\tReward: 119.0\tEpisode Mean: 110.4\n",
-      "87617:127701363\tQ-min: 2.547\tQ-max: 2.709\tLives: 1\tReward: 123.0\tEpisode Mean: 110.4\n",
-      "87617:127701384\tQ-min: 2.411\tQ-max: 3.237\tLives: 1\tReward: 127.0\tEpisode Mean: 110.4\n",
-      "87617:127701405\tQ-min: 2.788\tQ-max: 3.000\tLives: 1\tReward: 131.0\tEpisode Mean: 110.4\n",
-      "87617:127701424\tQ-min: 2.188\tQ-max: 2.956\tLives: 1\tReward: 132.0\tEpisode Mean: 110.4\n",
-      "87617:127701443\tQ-min: 2.006\tQ-max: 2.765\tLives: 1\tReward: 136.0\tEpisode Mean: 110.4\n",
-      "87617:127701458\tQ-min: 0.031\tQ-max: 0.288\tLives: 0\tReward: 136.0\tEpisode Mean: 111.2\n"
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+      "87588:127642159\tQ-min: 1.926\tQ-max: 2.292\tLives: 5\tReward: 14.0\tEpisode Mean: 0.0\n",
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+      "87588:127642323\tQ-min: 2.339\tQ-max: 2.423\tLives: 5\tReward: 31.0\tEpisode Mean: 0.0\n",
+      "87588:127642343\tQ-min: 2.365\tQ-max: 2.458\tLives: 5\tReward: 32.0\tEpisode Mean: 0.0\n",
+      "87588:127642364\tQ-min: 2.278\tQ-max: 2.398\tLives: 5\tReward: 33.0\tEpisode Mean: 0.0\n",
+      "87588:127642382\tQ-min: 2.226\tQ-max: 2.399\tLives: 5\tReward: 34.0\tEpisode Mean: 0.0\n",
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+      "87588:127642437\tQ-min: 1.988\tQ-max: 2.028\tLives: 4\tReward: 35.0\tEpisode Mean: 0.0\n",
+      "87588:127642478\tQ-min: 1.929\tQ-max: 2.025\tLives: 4\tReward: 36.0\tEpisode Mean: 0.0\n",
+      "87588:127642522\tQ-min: 2.039\tQ-max: 2.062\tLives: 4\tReward: 37.0\tEpisode Mean: 0.0\n",
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+      "87588:127642897\tQ-min: 2.480\tQ-max: 2.536\tLives: 3\tReward: 63.0\tEpisode Mean: 0.0\n",
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+      "87588:127642960\tQ-min: 2.096\tQ-max: 2.239\tLives: 2\tReward: 64.0\tEpisode Mean: 0.0\n",
+      "87588:127643019\tQ-min: 1.741\tQ-max: 1.920\tLives: 2\tReward: 68.0\tEpisode Mean: 0.0\n",
+      "87588:127643087\tQ-min: 1.986\tQ-max: 2.044\tLives: 2\tReward: 69.0\tEpisode Mean: 0.0\n",
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+      "87588:127643168\tQ-min: 2.441\tQ-max: 2.554\tLives: 2\tReward: 74.0\tEpisode Mean: 0.0\n",
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+      "87588:127643225\tQ-min: -0.176\tQ-max: 0.268\tLives: 1\tReward: 78.0\tEpisode Mean: 0.0\n",
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+      "87589:127645348\tQ-min: 3.802\tQ-max: 5.502\tLives: 3\tReward: 123.0\tEpisode Mean: 102.0\n",
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+      "87589:127645410\tQ-min: 3.764\tQ-max: 6.270\tLives: 3\tReward: 158.0\tEpisode Mean: 102.0\n",
+      "87589:127645415\tQ-min: 3.677\tQ-max: 5.796\tLives: 3\tReward: 165.0\tEpisode Mean: 102.0\n",
+      "87589:127645421\tQ-min: 2.668\tQ-max: 5.257\tLives: 3\tReward: 172.0\tEpisode Mean: 102.0\n",
+      "87589:127645427\tQ-min: 3.923\tQ-max: 5.098\tLives: 3\tReward: 179.0\tEpisode Mean: 102.0\n",
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+      "87589:127645493\tQ-min: 1.740\tQ-max: 4.088\tLives: 3\tReward: 246.0\tEpisode Mean: 102.0\n",
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+      "87590:127647542\tQ-min: 1.660\tQ-max: 1.909\tLives: 3\tReward: 40.0\tEpisode Mean: 244.0\n",
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+      "87590:127647629\tQ-min: 1.994\tQ-max: 2.072\tLives: 3\tReward: 42.0\tEpisode Mean: 244.0\n",
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+      "87590:127647778\tQ-min: 2.284\tQ-max: 2.583\tLives: 3\tReward: 59.0\tEpisode Mean: 244.0\n",
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+      "87590:127648081\tQ-min: 2.299\tQ-max: 2.460\tLives: 2\tReward: 82.0\tEpisode Mean: 244.0\n",
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+      "87591:127649719\tQ-min: 1.564\tQ-max: 1.715\tLives: 3\tReward: 42.0\tEpisode Mean: 207.0\n",
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+      "87591:127649821\tQ-min: 2.199\tQ-max: 2.354\tLives: 3\tReward: 50.0\tEpisode Mean: 207.0\n",
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+      "87591:127649869\tQ-min: 0.025\tQ-max: 0.418\tLives: 2\tReward: 54.0\tEpisode Mean: 207.0\n",
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+      "87591:127650047\tQ-min: 2.191\tQ-max: 2.541\tLives: 2\tReward: 64.0\tEpisode Mean: 207.0\n",
+      "87591:127650066\tQ-min: 2.439\tQ-max: 2.499\tLives: 2\tReward: 65.0\tEpisode Mean: 207.0\n",
+      "87591:127650086\tQ-min: 2.355\tQ-max: 2.534\tLives: 2\tReward: 66.0\tEpisode Mean: 207.0\n",
+      "87591:127650107\tQ-min: 2.535\tQ-max: 2.644\tLives: 2\tReward: 67.0\tEpisode Mean: 207.0\n",
+      "87591:127650128\tQ-min: 2.424\tQ-max: 2.611\tLives: 2\tReward: 71.0\tEpisode Mean: 207.0\n",
+      "87591:127650149\tQ-min: 2.291\tQ-max: 2.567\tLives: 2\tReward: 72.0\tEpisode Mean: 207.0\n",
+      "87591:127650173\tQ-min: 2.357\tQ-max: 2.671\tLives: 2\tReward: 76.0\tEpisode Mean: 207.0\n",
+      "87591:127650198\tQ-min: 1.918\tQ-max: 3.150\tLives: 2\tReward: 83.0\tEpisode Mean: 207.0\n",
+      "87591:127650223\tQ-min: 1.593\tQ-max: 3.739\tLives: 2\tReward: 90.0\tEpisode Mean: 207.0\n",
+      "87591:127650253\tQ-min: 2.184\tQ-max: 6.902\tLives: 2\tReward: 97.0\tEpisode Mean: 207.0\n",
+      "87591:127650258\tQ-min: 2.303\tQ-max: 6.611\tLives: 2\tReward: 104.0\tEpisode Mean: 207.0\n",
+      "87591:127650263\tQ-min: 3.708\tQ-max: 6.076\tLives: 2\tReward: 111.0\tEpisode Mean: 207.0\n",
+      "87591:127650267\tQ-min: 2.672\tQ-max: 6.862\tLives: 2\tReward: 118.0\tEpisode Mean: 207.0\n",
+      "87591:127650272\tQ-min: 1.783\tQ-max: 6.216\tLives: 2\tReward: 125.0\tEpisode Mean: 207.0\n",
+      "87591:127650277\tQ-min: 2.125\tQ-max: 5.576\tLives: 2\tReward: 132.0\tEpisode Mean: 207.0\n",
+      "87591:127650283\tQ-min: 3.175\tQ-max: 5.794\tLives: 2\tReward: 139.0\tEpisode Mean: 207.0\n",
+      "87591:127650288\tQ-min: 4.208\tQ-max: 6.206\tLives: 2\tReward: 146.0\tEpisode Mean: 207.0\n",
+      "87591:127650293\tQ-min: 3.793\tQ-max: 5.610\tLives: 2\tReward: 153.0\tEpisode Mean: 207.0\n",
+      "87591:127650298\tQ-min: 3.057\tQ-max: 5.366\tLives: 2\tReward: 160.0\tEpisode Mean: 207.0\n",
+      "87591:127650304\tQ-min: 3.419\tQ-max: 5.766\tLives: 2\tReward: 167.0\tEpisode Mean: 207.0\n",
+      "87591:127650308\tQ-min: 2.737\tQ-max: 6.274\tLives: 2\tReward: 174.0\tEpisode Mean: 207.0\n",
+      "87591:127650313\tQ-min: 4.419\tQ-max: 6.346\tLives: 2\tReward: 181.0\tEpisode Mean: 207.0\n",
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+      "87591:127650386\tQ-min: 2.746\tQ-max: 4.343\tLives: 2\tReward: 265.0\tEpisode Mean: 207.0\n",
+      "87591:127650425\tQ-min: 1.870\tQ-max: 5.265\tLives: 2\tReward: 272.0\tEpisode Mean: 207.0\n",
+      "87591:127650432\tQ-min: 3.059\tQ-max: 4.681\tLives: 2\tReward: 279.0\tEpisode Mean: 207.0\n",
+      "87591:127650438\tQ-min: 2.537\tQ-max: 4.428\tLives: 2\tReward: 286.0\tEpisode Mean: 207.0\n",
+      "87591:127650445\tQ-min: 1.591\tQ-max: 4.291\tLives: 2\tReward: 290.0\tEpisode Mean: 207.0\n",
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+      "87591:127650552\tQ-min: 1.948\tQ-max: 2.805\tLives: 1\tReward: 309.0\tEpisode Mean: 207.0\n",
+      "87591:127650573\tQ-min: 2.012\tQ-max: 3.112\tLives: 1\tReward: 313.0\tEpisode Mean: 207.0\n",
+      "87591:127650586\tQ-min: -0.178\tQ-max: 0.125\tLives: 0\tReward: 313.0\tEpisode Mean: 233.5\n",
+      "87592:127650631\tQ-min: 1.738\tQ-max: 1.756\tLives: 5\tReward: 1.0\tEpisode Mean: 233.5\n",
+      "87592:127650681\tQ-min: 1.608\tQ-max: 1.681\tLives: 5\tReward: 2.0\tEpisode Mean: 233.5\n",
+      "87592:127650745\tQ-min: 1.693\tQ-max: 1.710\tLives: 5\tReward: 3.0\tEpisode Mean: 233.5\n",
+      "87592:127650791\tQ-min: 2.007\tQ-max: 2.043\tLives: 5\tReward: 4.0\tEpisode Mean: 233.5\n",
+      "87592:127650823\tQ-min: 1.982\tQ-max: 1.999\tLives: 5\tReward: 5.0\tEpisode Mean: 233.5\n",
+      "87592:127650855\tQ-min: 1.947\tQ-max: 1.978\tLives: 5\tReward: 6.0\tEpisode Mean: 233.5\n",
+      "87592:127650891\tQ-min: 1.860\tQ-max: 1.888\tLives: 5\tReward: 7.0\tEpisode Mean: 233.5\n",
+      "87592:127650936\tQ-min: 1.647\tQ-max: 1.686\tLives: 5\tReward: 8.0\tEpisode Mean: 233.5\n",
+      "87592:127650996\tQ-min: 1.627\tQ-max: 1.706\tLives: 5\tReward: 9.0\tEpisode Mean: 233.5\n",
+      "87592:127651058\tQ-min: 1.615\tQ-max: 1.658\tLives: 5\tReward: 10.0\tEpisode Mean: 233.5\n",
+      "87592:127651120\tQ-min: 1.606\tQ-max: 1.666\tLives: 5\tReward: 11.0\tEpisode Mean: 233.5\n",
+      "87592:127651171\tQ-min: 2.078\tQ-max: 2.122\tLives: 5\tReward: 15.0\tEpisode Mean: 233.5\n",
+      "87592:127651194\tQ-min: -0.342\tQ-max: 0.180\tLives: 4\tReward: 15.0\tEpisode Mean: 233.5\n",
+      "87592:127651249\tQ-min: 1.698\tQ-max: 1.723\tLives: 4\tReward: 16.0\tEpisode Mean: 233.5\n",
+      "87592:127651314\tQ-min: 1.764\tQ-max: 1.785\tLives: 4\tReward: 17.0\tEpisode Mean: 233.5\n",
+      "87592:127651374\tQ-min: 1.671\tQ-max: 1.684\tLives: 4\tReward: 18.0\tEpisode Mean: 233.5\n",
+      "87592:127651421\tQ-min: 1.929\tQ-max: 1.945\tLives: 4\tReward: 19.0\tEpisode Mean: 233.5\n",
+      "87592:127651453\tQ-min: 1.996\tQ-max: 2.010\tLives: 4\tReward: 20.0\tEpisode Mean: 233.5\n",
+      "87592:127651485\tQ-min: 1.951\tQ-max: 2.018\tLives: 4\tReward: 21.0\tEpisode Mean: 233.5\n",
+      "87592:127651521\tQ-min: 2.054\tQ-max: 2.101\tLives: 4\tReward: 25.0\tEpisode Mean: 233.5\n",
+      "87592:127651571\tQ-min: 1.697\tQ-max: 1.773\tLives: 4\tReward: 26.0\tEpisode Mean: 233.5\n",
+      "87592:127651639\tQ-min: 1.759\tQ-max: 1.799\tLives: 4\tReward: 30.0\tEpisode Mean: 233.5\n",
+      "87592:127651707\tQ-min: 1.742\tQ-max: 1.765\tLives: 4\tReward: 31.0\tEpisode Mean: 233.5\n",
+      "87592:127651752\tQ-min: 0.088\tQ-max: 0.286\tLives: 3\tReward: 31.0\tEpisode Mean: 233.5\n",
+      "87592:127651796\tQ-min: 1.841\tQ-max: 2.045\tLives: 3\tReward: 35.0\tEpisode Mean: 233.5\n",
+      "87592:127651844\tQ-min: 2.039\tQ-max: 2.095\tLives: 3\tReward: 39.0\tEpisode Mean: 233.5\n",
+      "87592:127651899\tQ-min: 1.763\tQ-max: 1.800\tLives: 3\tReward: 40.0\tEpisode Mean: 233.5\n",
+      "87592:127651950\tQ-min: 2.205\tQ-max: 2.345\tLives: 3\tReward: 44.0\tEpisode Mean: 233.5\n",
+      "87592:127651973\tQ-min: 2.190\tQ-max: 2.513\tLives: 3\tReward: 48.0\tEpisode Mean: 233.5\n",
+      "87592:127651997\tQ-min: 2.491\tQ-max: 2.628\tLives: 3\tReward: 52.0\tEpisode Mean: 233.5\n",
+      "87592:127652020\tQ-min: 2.352\tQ-max: 2.592\tLives: 3\tReward: 53.0\tEpisode Mean: 233.5\n",
+      "87592:127652042\tQ-min: 2.402\tQ-max: 2.633\tLives: 3\tReward: 57.0\tEpisode Mean: 233.5\n",
+      "87592:127652066\tQ-min: 2.368\tQ-max: 2.562\tLives: 3\tReward: 61.0\tEpisode Mean: 233.5\n",
+      "87592:127652088\tQ-min: 2.472\tQ-max: 2.575\tLives: 3\tReward: 62.0\tEpisode Mean: 233.5\n",
+      "87592:127652110\tQ-min: 2.395\tQ-max: 2.561\tLives: 3\tReward: 63.0\tEpisode Mean: 233.5\n",
+      "87592:127652132\tQ-min: 2.375\tQ-max: 2.585\tLives: 3\tReward: 67.0\tEpisode Mean: 233.5\n",
+      "87592:127652157\tQ-min: 2.473\tQ-max: 2.893\tLives: 3\tReward: 71.0\tEpisode Mean: 233.5\n",
+      "87592:127652176\tQ-min: 2.306\tQ-max: 2.499\tLives: 3\tReward: 72.0\tEpisode Mean: 233.5\n",
+      "87592:127652197\tQ-min: 2.349\tQ-max: 2.556\tLives: 3\tReward: 76.0\tEpisode Mean: 233.5\n",
+      "87592:127652210\tQ-min: -0.203\tQ-max: 0.078\tLives: 2\tReward: 76.0\tEpisode Mean: 233.5\n",
+      "87592:127652270\tQ-min: 2.092\tQ-max: 2.818\tLives: 2\tReward: 80.0\tEpisode Mean: 233.5\n",
+      "87592:127652291\tQ-min: 2.315\tQ-max: 2.478\tLives: 2\tReward: 81.0\tEpisode Mean: 233.5\n",
+      "87592:127652312\tQ-min: 2.388\tQ-max: 2.683\tLives: 2\tReward: 85.0\tEpisode Mean: 233.5\n",
+      "87592:127652333\tQ-min: 2.325\tQ-max: 2.544\tLives: 2\tReward: 86.0\tEpisode Mean: 233.5\n",
+      "87592:127652356\tQ-min: 2.417\tQ-max: 2.561\tLives: 2\tReward: 93.0\tEpisode Mean: 233.5\n",
+      "87592:127652380\tQ-min: 2.176\tQ-max: 2.591\tLives: 2\tReward: 97.0\tEpisode Mean: 233.5\n",
+      "87592:127652400\tQ-min: 2.240\tQ-max: 2.582\tLives: 2\tReward: 104.0\tEpisode Mean: 233.5\n",
+      "87592:127652423\tQ-min: 2.176\tQ-max: 2.865\tLives: 2\tReward: 111.0\tEpisode Mean: 233.5\n",
+      "87592:127652447\tQ-min: 2.034\tQ-max: 3.135\tLives: 2\tReward: 118.0\tEpisode Mean: 233.5\n",
+      "87592:127652472\tQ-min: 2.173\tQ-max: 3.220\tLives: 2\tReward: 125.0\tEpisode Mean: 233.5\n",
+      "87592:127652494\tQ-min: 2.264\tQ-max: 3.115\tLives: 2\tReward: 126.0\tEpisode Mean: 233.5\n",
+      "87592:127652514\tQ-min: 2.601\tQ-max: 3.100\tLives: 2\tReward: 127.0\tEpisode Mean: 233.5\n",
+      "87592:127652534\tQ-min: 2.156\tQ-max: 2.808\tLives: 2\tReward: 131.0\tEpisode Mean: 233.5\n",
+      "87592:127652555\tQ-min: 2.541\tQ-max: 2.808\tLives: 2\tReward: 132.0\tEpisode Mean: 233.5\n",
+      "87592:127652577\tQ-min: 2.678\tQ-max: 3.090\tLives: 2\tReward: 136.0\tEpisode Mean: 233.5\n",
+      "87592:127652590\tQ-min: 0.011\tQ-max: 0.967\tLives: 1\tReward: 136.0\tEpisode Mean: 233.5\n",
+      "87592:127652640\tQ-min: 2.543\tQ-max: 3.653\tLives: 1\tReward: 143.0\tEpisode Mean: 233.5\n",
+      "87592:127652665\tQ-min: 2.447\tQ-max: 4.720\tLives: 1\tReward: 150.0\tEpisode Mean: 233.5\n",
+      "87592:127652689\tQ-min: 2.704\tQ-max: 4.175\tLives: 1\tReward: 157.0\tEpisode Mean: 233.5\n",
+      "87592:127652711\tQ-min: 3.109\tQ-max: 4.645\tLives: 1\tReward: 161.0\tEpisode Mean: 233.5\n",
+      "87592:127652725\tQ-min: -0.014\tQ-max: 0.422\tLives: 0\tReward: 161.0\tEpisode Mean: 219.0\n",
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+      "87593:127653049\tQ-min: -0.249\tQ-max: 0.235\tLives: 4\tReward: 7.0\tEpisode Mean: 219.0\n",
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+      "87593:127653140\tQ-min: 1.693\tQ-max: 1.709\tLives: 4\tReward: 9.0\tEpisode Mean: 219.0\n",
+      "87593:127653201\tQ-min: 1.706\tQ-max: 1.724\tLives: 4\tReward: 10.0\tEpisode Mean: 219.0\n",
+      "87593:127653248\tQ-min: 1.998\tQ-max: 2.038\tLives: 4\tReward: 11.0\tEpisode Mean: 219.0\n",
+      "87593:127653281\tQ-min: 1.933\tQ-max: 2.007\tLives: 4\tReward: 12.0\tEpisode Mean: 219.0\n",
+      "87593:127653315\tQ-min: 1.936\tQ-max: 1.983\tLives: 4\tReward: 16.0\tEpisode Mean: 219.0\n",
+      "87593:127653350\tQ-min: 2.174\tQ-max: 2.322\tLives: 4\tReward: 20.0\tEpisode Mean: 219.0\n",
+      "87593:127653365\tQ-min: 0.036\tQ-max: 0.426\tLives: 3\tReward: 20.0\tEpisode Mean: 219.0\n",
+      "87593:127653408\tQ-min: 1.847\tQ-max: 1.862\tLives: 3\tReward: 21.0\tEpisode Mean: 219.0\n",
+      "87593:127653462\tQ-min: 1.701\tQ-max: 1.795\tLives: 3\tReward: 22.0\tEpisode Mean: 219.0\n",
+      "87593:127653529\tQ-min: 1.778\tQ-max: 1.801\tLives: 3\tReward: 23.0\tEpisode Mean: 219.0\n",
+      "87593:127653578\tQ-min: 2.010\tQ-max: 2.020\tLives: 3\tReward: 24.0\tEpisode Mean: 219.0\n",
+      "87593:127653611\tQ-min: 2.053\tQ-max: 2.078\tLives: 3\tReward: 25.0\tEpisode Mean: 219.0\n",
+      "87593:127653647\tQ-min: 1.991\tQ-max: 2.196\tLives: 3\tReward: 29.0\tEpisode Mean: 219.0\n",
+      "87593:127653682\tQ-min: 2.111\tQ-max: 2.268\tLives: 3\tReward: 30.0\tEpisode Mean: 219.0\n",
+      "87593:127653729\tQ-min: 1.767\tQ-max: 1.797\tLives: 3\tReward: 31.0\tEpisode Mean: 219.0\n",
+      "87593:127653799\tQ-min: 1.709\tQ-max: 1.831\tLives: 3\tReward: 32.0\tEpisode Mean: 219.0\n",
+      "87593:127653866\tQ-min: 1.755\tQ-max: 1.803\tLives: 3\tReward: 33.0\tEpisode Mean: 219.0\n",
+      "87593:127653933\tQ-min: 1.789\tQ-max: 1.811\tLives: 3\tReward: 34.0\tEpisode Mean: 219.0\n",
+      "87593:127653987\tQ-min: 2.132\tQ-max: 2.257\tLives: 3\tReward: 38.0\tEpisode Mean: 219.0\n",
+      "87593:127654008\tQ-min: 2.290\tQ-max: 2.414\tLives: 3\tReward: 39.0\tEpisode Mean: 219.0\n",
+      "87593:127654029\tQ-min: 2.187\tQ-max: 2.466\tLives: 3\tReward: 43.0\tEpisode Mean: 219.0\n",
+      "87593:127654049\tQ-min: 2.475\tQ-max: 2.549\tLives: 3\tReward: 47.0\tEpisode Mean: 219.0\n",
+      "87593:127654072\tQ-min: 2.380\tQ-max: 2.476\tLives: 3\tReward: 48.0\tEpisode Mean: 219.0\n",
+      "87593:127654092\tQ-min: 2.384\tQ-max: 2.493\tLives: 3\tReward: 52.0\tEpisode Mean: 219.0\n",
+      "87593:127654105\tQ-min: 0.072\tQ-max: 0.224\tLives: 2\tReward: 52.0\tEpisode Mean: 219.0\n",
+      "87593:127654162\tQ-min: 1.802\tQ-max: 1.834\tLives: 2\tReward: 53.0\tEpisode Mean: 219.0\n",
+      "87593:127654229\tQ-min: 1.875\tQ-max: 1.913\tLives: 2\tReward: 54.0\tEpisode Mean: 219.0\n",
+      "87593:127654301\tQ-min: 1.697\tQ-max: 1.889\tLives: 2\tReward: 58.0\tEpisode Mean: 219.0\n",
+      "87593:127654351\tQ-min: 2.277\tQ-max: 2.401\tLives: 2\tReward: 59.0\tEpisode Mean: 219.0\n",
+      "87593:127654375\tQ-min: 0.016\tQ-max: 0.213\tLives: 1\tReward: 59.0\tEpisode Mean: 219.0\n",
+      "87593:127654435\tQ-min: 1.763\tQ-max: 1.906\tLives: 1\tReward: 60.0\tEpisode Mean: 219.0\n",
+      "87593:127654499\tQ-min: 1.852\tQ-max: 1.911\tLives: 1\tReward: 61.0\tEpisode Mean: 219.0\n",
+      "87593:127654566\tQ-min: 1.833\tQ-max: 1.903\tLives: 1\tReward: 62.0\tEpisode Mean: 219.0\n",
+      "87593:127654618\tQ-min: 1.870\tQ-max: 2.419\tLives: 1\tReward: 66.0\tEpisode Mean: 219.0\n",
+      "87593:127654631\tQ-min: -0.017\tQ-max: 0.137\tLives: 0\tReward: 66.0\tEpisode Mean: 193.5\n",
+      "87594:127654685\tQ-min: 1.651\tQ-max: 1.682\tLives: 5\tReward: 1.0\tEpisode Mean: 193.5\n",
+      "87594:127654736\tQ-min: 1.850\tQ-max: 1.864\tLives: 5\tReward: 2.0\tEpisode Mean: 193.5\n",
+      "87594:127654780\tQ-min: 1.891\tQ-max: 1.934\tLives: 5\tReward: 3.0\tEpisode Mean: 193.5\n",
+      "87594:127654817\tQ-min: 1.999\tQ-max: 2.044\tLives: 5\tReward: 4.0\tEpisode Mean: 193.5\n",
+      "87594:127654850\tQ-min: 1.971\tQ-max: 1.982\tLives: 5\tReward: 5.0\tEpisode Mean: 193.5\n",
+      "87594:127654882\tQ-min: 1.880\tQ-max: 1.913\tLives: 5\tReward: 6.0\tEpisode Mean: 193.5\n",
+      "87594:127654916\tQ-min: 1.829\tQ-max: 1.878\tLives: 5\tReward: 10.0\tEpisode Mean: 193.5\n",
+      "87594:127654937\tQ-min: -0.237\tQ-max: 0.162\tLives: 4\tReward: 10.0\tEpisode Mean: 193.5\n",
+      "87594:127654990\tQ-min: 1.683\tQ-max: 1.710\tLives: 4\tReward: 11.0\tEpisode Mean: 193.5\n",
+      "87594:127655040\tQ-min: 1.909\tQ-max: 2.004\tLives: 4\tReward: 12.0\tEpisode Mean: 193.5\n",
+      "87594:127655083\tQ-min: 2.002\tQ-max: 2.042\tLives: 4\tReward: 16.0\tEpisode Mean: 193.5\n",
+      "87594:127655127\tQ-min: 1.953\tQ-max: 1.996\tLives: 4\tReward: 20.0\tEpisode Mean: 193.5\n",
+      "87594:127655164\tQ-min: 2.028\tQ-max: 2.074\tLives: 4\tReward: 21.0\tEpisode Mean: 193.5\n",
+      "87594:127655196\tQ-min: 2.035\tQ-max: 2.054\tLives: 4\tReward: 22.0\tEpisode Mean: 193.5\n",
+      "87594:127655229\tQ-min: 2.120\tQ-max: 2.405\tLives: 4\tReward: 26.0\tEpisode Mean: 193.5\n",
+      "87594:127655251\tQ-min: 2.246\tQ-max: 2.396\tLives: 4\tReward: 27.0\tEpisode Mean: 193.5\n",
+      "87594:127655268\tQ-min: 2.243\tQ-max: 2.392\tLives: 4\tReward: 28.0\tEpisode Mean: 193.5\n",
+      "87594:127655286\tQ-min: 2.245\tQ-max: 2.390\tLives: 4\tReward: 29.0\tEpisode Mean: 193.5\n",
+      "87594:127655308\tQ-min: 2.304\tQ-max: 2.416\tLives: 4\tReward: 30.0\tEpisode Mean: 193.5\n",
+      "87594:127655330\tQ-min: 2.293\tQ-max: 2.345\tLives: 4\tReward: 34.0\tEpisode Mean: 193.5\n",
+      "87594:127655343\tQ-min: -0.039\tQ-max: 0.290\tLives: 3\tReward: 34.0\tEpisode Mean: 193.5\n",
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+      "87594:127655434\tQ-min: 1.858\tQ-max: 1.963\tLives: 3\tReward: 36.0\tEpisode Mean: 193.5\n",
+      "87594:127655487\tQ-min: 2.120\tQ-max: 2.189\tLives: 3\tReward: 37.0\tEpisode Mean: 193.5\n",
+      "87594:127655527\tQ-min: 2.145\tQ-max: 2.264\tLives: 3\tReward: 41.0\tEpisode Mean: 193.5\n",
+      "87594:127655559\tQ-min: 2.238\tQ-max: 2.304\tLives: 3\tReward: 42.0\tEpisode Mean: 193.5\n",
+      "87594:127655580\tQ-min: -0.035\tQ-max: 0.260\tLives: 2\tReward: 42.0\tEpisode Mean: 193.5\n",
+      "87594:127655636\tQ-min: 1.821\tQ-max: 2.036\tLives: 2\tReward: 46.0\tEpisode Mean: 193.5\n",
+      "87594:127655705\tQ-min: 1.870\tQ-max: 1.949\tLives: 2\tReward: 47.0\tEpisode Mean: 193.5\n",
+      "87594:127655772\tQ-min: 1.753\tQ-max: 1.917\tLives: 2\tReward: 48.0\tEpisode Mean: 193.5\n",
+      "87594:127655821\tQ-min: 2.071\tQ-max: 2.226\tLives: 2\tReward: 49.0\tEpisode Mean: 193.5\n",
+      "87594:127655852\tQ-min: 2.208\tQ-max: 2.255\tLives: 2\tReward: 50.0\tEpisode Mean: 193.5\n",
+      "87594:127655885\tQ-min: 2.251\tQ-max: 2.297\tLives: 2\tReward: 51.0\tEpisode Mean: 193.5\n",
+      "87594:127655906\tQ-min: -0.061\tQ-max: 0.177\tLives: 1\tReward: 51.0\tEpisode Mean: 193.5\n",
+      "87594:127655952\tQ-min: 2.156\tQ-max: 2.214\tLives: 1\tReward: 52.0\tEpisode Mean: 193.5\n",
+      "87594:127655991\tQ-min: 2.186\tQ-max: 2.215\tLives: 1\tReward: 53.0\tEpisode Mean: 193.5\n",
+      "87594:127656034\tQ-min: 2.292\tQ-max: 2.545\tLives: 1\tReward: 57.0\tEpisode Mean: 193.5\n",
+      "87594:127656055\tQ-min: 2.133\tQ-max: 2.445\tLives: 1\tReward: 64.0\tEpisode Mean: 193.5\n",
+      "87594:127656076\tQ-min: 2.376\tQ-max: 2.508\tLives: 1\tReward: 65.0\tEpisode Mean: 193.5\n",
+      "87594:127656099\tQ-min: 2.311\tQ-max: 2.453\tLives: 1\tReward: 69.0\tEpisode Mean: 193.5\n",
+      "87594:127656122\tQ-min: 2.194\tQ-max: 2.632\tLives: 1\tReward: 73.0\tEpisode Mean: 193.5\n",
+      "87594:127656135\tQ-min: 0.041\tQ-max: 0.202\tLives: 0\tReward: 73.0\tEpisode Mean: 176.3\n",
+      "87595:127656179\tQ-min: 1.787\tQ-max: 1.804\tLives: 5\tReward: 1.0\tEpisode Mean: 176.3\n",
+      "87595:127656232\tQ-min: 1.614\tQ-max: 1.645\tLives: 5\tReward: 2.0\tEpisode Mean: 176.3\n",
+      "87595:127656293\tQ-min: 1.658\tQ-max: 1.683\tLives: 5\tReward: 3.0\tEpisode Mean: 176.3\n",
+      "87595:127656342\tQ-min: 2.007\tQ-max: 2.039\tLives: 5\tReward: 4.0\tEpisode Mean: 176.3\n",
+      "87595:127656371\tQ-min: 1.982\tQ-max: 2.006\tLives: 5\tReward: 5.0\tEpisode Mean: 176.3\n",
+      "87595:127656402\tQ-min: 1.909\tQ-max: 1.933\tLives: 5\tReward: 6.0\tEpisode Mean: 176.3\n",
+      "87595:127656436\tQ-min: 1.743\tQ-max: 1.803\tLives: 5\tReward: 7.0\tEpisode Mean: 176.3\n",
+      "87595:127656456\tQ-min: -0.313\tQ-max: 0.038\tLives: 4\tReward: 7.0\tEpisode Mean: 176.3\n",
+      "87595:127656499\tQ-min: 1.838\tQ-max: 1.848\tLives: 4\tReward: 8.0\tEpisode Mean: 176.3\n",
+      "87595:127656537\tQ-min: 1.963\tQ-max: 1.978\tLives: 4\tReward: 9.0\tEpisode Mean: 176.3\n",
+      "87595:127656590\tQ-min: 1.693\tQ-max: 1.720\tLives: 4\tReward: 10.0\tEpisode Mean: 176.3\n",
+      "87595:127656638\tQ-min: 1.960\tQ-max: 1.993\tLives: 4\tReward: 11.0\tEpisode Mean: 176.3\n",
+      "87595:127656657\tQ-min: -0.459\tQ-max: 0.010\tLives: 3\tReward: 11.0\tEpisode Mean: 176.3\n",
+      "87595:127656706\tQ-min: 1.820\tQ-max: 1.841\tLives: 3\tReward: 12.0\tEpisode Mean: 176.3\n",
+      "87595:127656748\tQ-min: 1.909\tQ-max: 1.929\tLives: 3\tReward: 13.0\tEpisode Mean: 176.3\n",
+      "87595:127656793\tQ-min: 1.927\tQ-max: 1.964\tLives: 3\tReward: 14.0\tEpisode Mean: 176.3\n",
+      "87595:127656833\tQ-min: 2.082\tQ-max: 2.122\tLives: 3\tReward: 18.0\tEpisode Mean: 176.3\n",
+      "87595:127656868\tQ-min: 1.989\tQ-max: 2.011\tLives: 3\tReward: 19.0\tEpisode Mean: 176.3\n",
+      "87595:127656900\tQ-min: 2.109\tQ-max: 2.127\tLives: 3\tReward: 23.0\tEpisode Mean: 176.3\n",
+      "87595:127656934\tQ-min: 2.041\tQ-max: 2.196\tLives: 3\tReward: 24.0\tEpisode Mean: 176.3\n",
+      "87595:127656983\tQ-min: 1.759\tQ-max: 1.890\tLives: 3\tReward: 25.0\tEpisode Mean: 176.3\n",
+      "87595:127657045\tQ-min: 1.616\tQ-max: 1.682\tLives: 3\tReward: 26.0\tEpisode Mean: 176.3\n",
+      "87595:127657107\tQ-min: 1.712\tQ-max: 1.735\tLives: 3\tReward: 27.0\tEpisode Mean: 176.3\n",
+      "87595:127657169\tQ-min: 1.645\tQ-max: 1.729\tLives: 3\tReward: 28.0\tEpisode Mean: 176.3\n",
+      "87595:127657218\tQ-min: 2.122\tQ-max: 2.151\tLives: 3\tReward: 29.0\tEpisode Mean: 176.3\n",
+      "87595:127657251\tQ-min: 2.031\tQ-max: 2.106\tLives: 3\tReward: 30.0\tEpisode Mean: 176.3\n",
+      "87595:127657285\tQ-min: 2.027\tQ-max: 2.106\tLives: 3\tReward: 34.0\tEpisode Mean: 176.3\n",
+      "87595:127657318\tQ-min: 2.200\tQ-max: 2.330\tLives: 3\tReward: 38.0\tEpisode Mean: 176.3\n",
+      "87595:127657356\tQ-min: 2.014\tQ-max: 2.550\tLives: 3\tReward: 42.0\tEpisode Mean: 176.3\n",
+      "87595:127657379\tQ-min: 2.378\tQ-max: 2.420\tLives: 3\tReward: 46.0\tEpisode Mean: 176.3\n",
+      "87595:127657402\tQ-min: 2.039\tQ-max: 2.519\tLives: 3\tReward: 50.0\tEpisode Mean: 176.3\n",
+      "87595:127657423\tQ-min: 2.143\tQ-max: 2.505\tLives: 3\tReward: 54.0\tEpisode Mean: 176.3\n",
+      "87595:127657436\tQ-min: 0.032\tQ-max: 0.222\tLives: 2\tReward: 54.0\tEpisode Mean: 176.3\n",
+      "87595:127657488\tQ-min: 1.849\tQ-max: 1.884\tLives: 2\tReward: 55.0\tEpisode Mean: 176.3\n",
+      "87595:127657542\tQ-min: 2.099\tQ-max: 2.417\tLives: 2\tReward: 62.0\tEpisode Mean: 176.3\n",
+      "87595:127657558\tQ-min: 0.040\tQ-max: 0.255\tLives: 1\tReward: 62.0\tEpisode Mean: 176.3\n",
+      "87595:127657615\tQ-min: 1.877\tQ-max: 1.897\tLives: 1\tReward: 63.0\tEpisode Mean: 176.3\n",
+      "87595:127657683\tQ-min: 1.949\tQ-max: 2.054\tLives: 1\tReward: 64.0\tEpisode Mean: 176.3\n",
+      "87595:127657735\tQ-min: 2.190\tQ-max: 2.218\tLives: 1\tReward: 65.0\tEpisode Mean: 176.3\n",
+      "87595:127657773\tQ-min: 2.213\tQ-max: 2.361\tLives: 1\tReward: 69.0\tEpisode Mean: 176.3\n",
+      "87595:127657812\tQ-min: 2.257\tQ-max: 2.287\tLives: 1\tReward: 70.0\tEpisode Mean: 176.3\n",
+      "87595:127657846\tQ-min: 2.189\tQ-max: 2.253\tLives: 1\tReward: 71.0\tEpisode Mean: 176.3\n",
+      "87595:127657881\tQ-min: 2.073\tQ-max: 2.765\tLives: 1\tReward: 78.0\tEpisode Mean: 176.3\n",
+      "87595:127657904\tQ-min: 2.204\tQ-max: 2.673\tLives: 1\tReward: 85.0\tEpisode Mean: 176.3\n",
+      "87595:127657925\tQ-min: 2.340\tQ-max: 2.609\tLives: 1\tReward: 89.0\tEpisode Mean: 176.3\n",
+      "87595:127657946\tQ-min: 2.491\tQ-max: 2.714\tLives: 1\tReward: 96.0\tEpisode Mean: 176.3\n",
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+      "87596:127658040\tQ-min: 1.857\tQ-max: 1.868\tLives: 4\tReward: 1.0\tEpisode Mean: 166.2\n",
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+      "87596:127658215\tQ-min: 1.923\tQ-max: 1.957\tLives: 4\tReward: 5.0\tEpisode Mean: 166.2\n",
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+      "87596:127658450\tQ-min: 1.920\tQ-max: 1.935\tLives: 3\tReward: 10.0\tEpisode Mean: 166.2\n",
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+      "87596:127658635\tQ-min: 1.676\tQ-max: 1.695\tLives: 3\tReward: 18.0\tEpisode Mean: 166.2\n",
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+      "87596:127658764\tQ-min: 1.651\tQ-max: 1.702\tLives: 3\tReward: 20.0\tEpisode Mean: 166.2\n",
+      "87596:127658827\tQ-min: 1.536\tQ-max: 1.713\tLives: 3\tReward: 21.0\tEpisode Mean: 166.2\n",
+      "87596:127658880\tQ-min: 1.987\tQ-max: 2.016\tLives: 3\tReward: 22.0\tEpisode Mean: 166.2\n",
+      "87596:127658911\tQ-min: 2.022\tQ-max: 2.084\tLives: 3\tReward: 23.0\tEpisode Mean: 166.2\n",
+      "87596:127658941\tQ-min: 2.085\tQ-max: 2.137\tLives: 3\tReward: 24.0\tEpisode Mean: 166.2\n",
+      "87596:127658975\tQ-min: 2.006\tQ-max: 2.028\tLives: 3\tReward: 25.0\tEpisode Mean: 166.2\n",
+      "87596:127659009\tQ-min: 1.986\tQ-max: 2.021\tLives: 3\tReward: 26.0\tEpisode Mean: 166.2\n",
+      "87596:127659040\tQ-min: 1.968\tQ-max: 2.005\tLives: 3\tReward: 27.0\tEpisode Mean: 166.2\n",
+      "87596:127659073\tQ-min: 1.963\tQ-max: 2.024\tLives: 3\tReward: 31.0\tEpisode Mean: 166.2\n",
+      "87596:127659106\tQ-min: 2.057\tQ-max: 2.103\tLives: 3\tReward: 32.0\tEpisode Mean: 166.2\n",
+      "87596:127659126\tQ-min: -0.127\tQ-max: 0.197\tLives: 2\tReward: 32.0\tEpisode Mean: 166.2\n",
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+      "87596:127659263\tQ-min: 2.251\tQ-max: 2.506\tLives: 2\tReward: 48.0\tEpisode Mean: 166.2\n",
+      "87596:127659284\tQ-min: 2.396\tQ-max: 2.576\tLives: 2\tReward: 55.0\tEpisode Mean: 166.2\n",
+      "87596:127659310\tQ-min: 2.400\tQ-max: 2.546\tLives: 2\tReward: 59.0\tEpisode Mean: 166.2\n",
+      "87596:127659333\tQ-min: 2.413\tQ-max: 2.656\tLives: 2\tReward: 63.0\tEpisode Mean: 166.2\n",
+      "87596:127659353\tQ-min: 2.393\tQ-max: 2.510\tLives: 2\tReward: 64.0\tEpisode Mean: 166.2\n",
+      "87596:127659367\tQ-min: 0.114\tQ-max: 0.326\tLives: 1\tReward: 64.0\tEpisode Mean: 166.2\n",
+      "87596:127659412\tQ-min: 2.210\tQ-max: 2.251\tLives: 1\tReward: 65.0\tEpisode Mean: 166.2\n",
+      "87596:127659466\tQ-min: 1.759\tQ-max: 1.894\tLives: 1\tReward: 66.0\tEpisode Mean: 166.2\n",
+      "87596:127659525\tQ-min: 2.140\tQ-max: 2.177\tLives: 1\tReward: 67.0\tEpisode Mean: 166.2\n",
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+      "87597:127659813\tQ-min: 1.925\tQ-max: 1.954\tLives: 5\tReward: 5.0\tEpisode Mean: 155.2\n",
+      "87597:127659847\tQ-min: 1.937\tQ-max: 1.965\tLives: 5\tReward: 6.0\tEpisode Mean: 155.2\n",
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+      "87597:127659930\tQ-min: 1.663\tQ-max: 1.684\tLives: 5\tReward: 8.0\tEpisode Mean: 155.2\n",
+      "87597:127659994\tQ-min: 1.693\tQ-max: 1.731\tLives: 5\tReward: 9.0\tEpisode Mean: 155.2\n",
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+      "87597:127660122\tQ-min: 1.646\tQ-max: 1.711\tLives: 5\tReward: 11.0\tEpisode Mean: 155.2\n",
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+      "87597:127660203\tQ-min: 1.916\tQ-max: 1.961\tLives: 5\tReward: 13.0\tEpisode Mean: 155.2\n",
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+      "87597:127660470\tQ-min: -0.343\tQ-max: -0.004\tLives: 4\tReward: 26.0\tEpisode Mean: 155.2\n",
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+      "87597:127660758\tQ-min: 2.147\tQ-max: 2.391\tLives: 4\tReward: 36.0\tEpisode Mean: 155.2\n",
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+      "87597:127660790\tQ-min: -0.046\tQ-max: 0.138\tLives: 3\tReward: 37.0\tEpisode Mean: 155.2\n",
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+      "87597:127661061\tQ-min: -1.010\tQ-max: 0.276\tLives: 2\tReward: 45.0\tEpisode Mean: 155.2\n",
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+      "87597:127661293\tQ-min: 2.387\tQ-max: 2.612\tLives: 1\tReward: 65.0\tEpisode Mean: 155.2\n",
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+      "87598:127662581\tQ-min: 2.076\tQ-max: 2.144\tLives: 2\tReward: 35.0\tEpisode Mean: 146.2\n",
+      "87598:127662616\tQ-min: 2.132\tQ-max: 2.203\tLives: 2\tReward: 36.0\tEpisode Mean: 146.2\n",
+      "87598:127662651\tQ-min: 1.996\tQ-max: 2.062\tLives: 2\tReward: 37.0\tEpisode Mean: 146.2\n",
+      "87598:127662685\tQ-min: 2.059\tQ-max: 2.100\tLives: 2\tReward: 38.0\tEpisode Mean: 146.2\n",
+      "87598:127662718\tQ-min: 2.218\tQ-max: 2.223\tLives: 2\tReward: 42.0\tEpisode Mean: 146.2\n",
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+      "87598:127662822\tQ-min: 2.088\tQ-max: 2.438\tLives: 2\tReward: 51.0\tEpisode Mean: 146.2\n",
+      "87598:127662844\tQ-min: 2.259\tQ-max: 2.415\tLives: 2\tReward: 52.0\tEpisode Mean: 146.2\n",
+      "87598:127662864\tQ-min: 2.365\tQ-max: 2.445\tLives: 2\tReward: 56.0\tEpisode Mean: 146.2\n",
+      "87598:127662884\tQ-min: 2.356\tQ-max: 2.439\tLives: 2\tReward: 60.0\tEpisode Mean: 146.2\n",
+      "87598:127662905\tQ-min: 2.422\tQ-max: 2.500\tLives: 2\tReward: 64.0\tEpisode Mean: 146.2\n",
+      "87598:127662919\tQ-min: 0.224\tQ-max: 0.494\tLives: 1\tReward: 64.0\tEpisode Mean: 146.2\n",
+      "87598:127662966\tQ-min: 2.476\tQ-max: 2.743\tLives: 1\tReward: 68.0\tEpisode Mean: 146.2\n",
+      "87598:127662989\tQ-min: 2.496\tQ-max: 2.813\tLives: 1\tReward: 69.0\tEpisode Mean: 146.2\n",
+      "87598:127663010\tQ-min: 2.405\tQ-max: 2.518\tLives: 1\tReward: 73.0\tEpisode Mean: 146.2\n",
+      "87598:127663024\tQ-min: -0.284\tQ-max: 0.232\tLives: 0\tReward: 73.0\tEpisode Mean: 139.5\n",
+      "87599:127663067\tQ-min: 1.753\tQ-max: 1.762\tLives: 5\tReward: 1.0\tEpisode Mean: 139.5\n",
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+      "87599:127663357\tQ-min: 1.644\tQ-max: 1.661\tLives: 5\tReward: 8.0\tEpisode Mean: 139.5\n",
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+      "87599:127664490\tQ-min: 2.089\tQ-max: 2.205\tLives: 4\tReward: 43.0\tEpisode Mean: 139.5\n",
+      "87599:127664513\tQ-min: -0.521\tQ-max: -0.111\tLives: 3\tReward: 43.0\tEpisode Mean: 139.5\n",
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+      "87599:127664719\tQ-min: 2.275\tQ-max: 2.449\tLives: 3\tReward: 54.0\tEpisode Mean: 139.5\n",
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+      "87599:127664820\tQ-min: 2.384\tQ-max: 2.539\tLives: 2\tReward: 62.0\tEpisode Mean: 139.5\n",
+      "87599:127664842\tQ-min: 2.198\tQ-max: 2.455\tLives: 2\tReward: 66.0\tEpisode Mean: 139.5\n",
+      "87599:127664864\tQ-min: 2.476\tQ-max: 2.600\tLives: 2\tReward: 70.0\tEpisode Mean: 139.5\n",
+      "87599:127664886\tQ-min: 2.233\tQ-max: 2.521\tLives: 2\tReward: 74.0\tEpisode Mean: 139.5\n",
+      "87599:127664907\tQ-min: 2.210\tQ-max: 2.531\tLives: 2\tReward: 78.0\tEpisode Mean: 139.5\n",
+      "87599:127664929\tQ-min: 2.236\tQ-max: 2.470\tLives: 2\tReward: 82.0\tEpisode Mean: 139.5\n",
+      "87599:127664951\tQ-min: 2.313\tQ-max: 2.487\tLives: 2\tReward: 83.0\tEpisode Mean: 139.5\n",
+      "87599:127664973\tQ-min: 2.177\tQ-max: 2.553\tLives: 2\tReward: 87.0\tEpisode Mean: 139.5\n",
+      "87599:127664987\tQ-min: 0.015\tQ-max: 0.203\tLives: 1\tReward: 87.0\tEpisode Mean: 139.5\n",
+      "87599:127665035\tQ-min: 2.091\tQ-max: 2.143\tLives: 1\tReward: 91.0\tEpisode Mean: 139.5\n",
+      "87599:127665089\tQ-min: 1.995\tQ-max: 2.141\tLives: 1\tReward: 92.0\tEpisode Mean: 139.5\n",
+      "87599:127665161\tQ-min: 1.824\tQ-max: 2.351\tLives: 1\tReward: 96.0\tEpisode Mean: 139.5\n",
+      "87599:127665203\tQ-min: -0.230\tQ-max: -0.095\tLives: 0\tReward: 96.0\tEpisode Mean: 135.9\n",
+      "87600:127665258\tQ-min: 1.623\tQ-max: 1.681\tLives: 5\tReward: 1.0\tEpisode Mean: 135.9\n",
+      "87600:127665323\tQ-min: 1.673\tQ-max: 1.694\tLives: 5\tReward: 2.0\tEpisode Mean: 135.9\n",
+      "87600:127665382\tQ-min: 1.696\tQ-max: 1.725\tLives: 5\tReward: 3.0\tEpisode Mean: 135.9\n",
+      "87600:127665429\tQ-min: 1.982\tQ-max: 2.019\tLives: 5\tReward: 4.0\tEpisode Mean: 135.9\n",
+      "87600:127665458\tQ-min: 1.942\tQ-max: 1.968\tLives: 5\tReward: 5.0\tEpisode Mean: 135.9\n",
+      "87600:127665490\tQ-min: 2.015\tQ-max: 2.054\tLives: 5\tReward: 6.0\tEpisode Mean: 135.9\n",
+      "87600:127665526\tQ-min: 1.801\tQ-max: 1.817\tLives: 5\tReward: 7.0\tEpisode Mean: 135.9\n",
+      "87600:127665574\tQ-min: 1.669\tQ-max: 1.709\tLives: 5\tReward: 8.0\tEpisode Mean: 135.9\n",
+      "87600:127665615\tQ-min: -0.153\tQ-max: 0.143\tLives: 4\tReward: 8.0\tEpisode Mean: 135.9\n",
+      "87600:127665660\tQ-min: 1.875\tQ-max: 1.899\tLives: 4\tReward: 9.0\tEpisode Mean: 135.9\n",
+      "87600:127665705\tQ-min: 1.866\tQ-max: 1.891\tLives: 4\tReward: 10.0\tEpisode Mean: 135.9\n",
+      "87600:127665747\tQ-min: 1.927\tQ-max: 1.947\tLives: 4\tReward: 11.0\tEpisode Mean: 135.9\n",
+      "87600:127665784\tQ-min: 1.979\tQ-max: 2.002\tLives: 4\tReward: 12.0\tEpisode Mean: 135.9\n",
+      "87600:127665815\tQ-min: 1.992\tQ-max: 2.034\tLives: 4\tReward: 13.0\tEpisode Mean: 135.9\n",
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+      "87600:127665933\tQ-min: 1.660\tQ-max: 1.804\tLives: 4\tReward: 19.0\tEpisode Mean: 135.9\n",
+      "87600:127665995\tQ-min: 1.712\tQ-max: 1.726\tLives: 4\tReward: 20.0\tEpisode Mean: 135.9\n",
+      "87600:127666054\tQ-min: 1.695\tQ-max: 1.713\tLives: 4\tReward: 21.0\tEpisode Mean: 135.9\n",
+      "87600:127666119\tQ-min: 1.669\tQ-max: 1.699\tLives: 4\tReward: 22.0\tEpisode Mean: 135.9\n",
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+      "87600:127666189\tQ-min: 0.049\tQ-max: 0.201\tLives: 3\tReward: 23.0\tEpisode Mean: 135.9\n",
+      "87600:127666233\tQ-min: 1.899\tQ-max: 1.930\tLives: 3\tReward: 24.0\tEpisode Mean: 135.9\n",
+      "87600:127666287\tQ-min: 1.692\tQ-max: 1.740\tLives: 3\tReward: 25.0\tEpisode Mean: 135.9\n",
+      "87600:127666345\tQ-min: 1.973\tQ-max: 2.027\tLives: 3\tReward: 29.0\tEpisode Mean: 135.9\n",
+      "87600:127666390\tQ-min: 2.341\tQ-max: 2.606\tLives: 3\tReward: 33.0\tEpisode Mean: 135.9\n",
+      "87600:127666409\tQ-min: 2.472\tQ-max: 2.503\tLives: 3\tReward: 34.0\tEpisode Mean: 135.9\n",
+      "87600:127666429\tQ-min: 2.264\tQ-max: 2.515\tLives: 3\tReward: 38.0\tEpisode Mean: 135.9\n",
+      "87600:127666447\tQ-min: 2.428\tQ-max: 2.572\tLives: 3\tReward: 39.0\tEpisode Mean: 135.9\n",
+      "87600:127666466\tQ-min: 2.377\tQ-max: 2.562\tLives: 3\tReward: 43.0\tEpisode Mean: 135.9\n",
+      "87600:127666488\tQ-min: 2.328\tQ-max: 2.461\tLives: 3\tReward: 47.0\tEpisode Mean: 135.9\n",
+      "87600:127666510\tQ-min: 2.380\tQ-max: 2.607\tLives: 3\tReward: 51.0\tEpisode Mean: 135.9\n",
+      "87600:127666533\tQ-min: 2.363\tQ-max: 2.568\tLives: 3\tReward: 55.0\tEpisode Mean: 135.9\n",
+      "87600:127666553\tQ-min: 2.401\tQ-max: 2.500\tLives: 3\tReward: 56.0\tEpisode Mean: 135.9\n",
+      "87600:127666575\tQ-min: 2.114\tQ-max: 2.592\tLives: 3\tReward: 60.0\tEpisode Mean: 135.9\n",
+      "87600:127666598\tQ-min: 2.280\tQ-max: 2.538\tLives: 3\tReward: 64.0\tEpisode Mean: 135.9\n",
+      "87600:127666620\tQ-min: 2.412\tQ-max: 2.506\tLives: 3\tReward: 65.0\tEpisode Mean: 135.9\n",
+      "87600:127666632\tQ-min: 0.158\tQ-max: 0.395\tLives: 2\tReward: 65.0\tEpisode Mean: 135.9\n",
+      "87600:127666681\tQ-min: 2.151\tQ-max: 2.262\tLives: 2\tReward: 69.0\tEpisode Mean: 135.9\n",
+      "87600:127666728\tQ-min: 2.302\tQ-max: 2.573\tLives: 2\tReward: 73.0\tEpisode Mean: 135.9\n",
+      "87600:127666748\tQ-min: 2.387\tQ-max: 2.597\tLives: 2\tReward: 77.0\tEpisode Mean: 135.9\n",
+      "87600:127666769\tQ-min: 2.162\tQ-max: 2.485\tLives: 2\tReward: 81.0\tEpisode Mean: 135.9\n",
+      "87600:127666791\tQ-min: 2.353\tQ-max: 2.633\tLives: 2\tReward: 85.0\tEpisode Mean: 135.9\n",
+      "87600:127666811\tQ-min: 2.475\tQ-max: 2.603\tLives: 2\tReward: 86.0\tEpisode Mean: 135.9\n",
+      "87600:127666832\tQ-min: 1.714\tQ-max: 2.607\tLives: 2\tReward: 93.0\tEpisode Mean: 135.9\n",
+      "87600:127666847\tQ-min: 0.025\tQ-max: 0.334\tLives: 1\tReward: 93.0\tEpisode Mean: 135.9\n",
+      "87600:127666884\tQ-min: -0.352\tQ-max: 0.459\tLives: 0\tReward: 93.0\tEpisode Mean: 132.6\n",
+      "87601:127666925\tQ-min: 1.749\tQ-max: 1.771\tLives: 5\tReward: 1.0\tEpisode Mean: 132.6\n",
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+      "87601:127667077\tQ-min: 1.974\tQ-max: 2.042\tLives: 5\tReward: 5.0\tEpisode Mean: 132.6\n",
+      "87601:127667111\tQ-min: 1.965\tQ-max: 1.987\tLives: 5\tReward: 6.0\tEpisode Mean: 132.6\n",
+      "87601:127667142\tQ-min: 1.820\tQ-max: 1.833\tLives: 5\tReward: 7.0\tEpisode Mean: 132.6\n",
+      "87601:127667162\tQ-min: -0.263\tQ-max: 0.170\tLives: 4\tReward: 7.0\tEpisode Mean: 132.6\n",
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+      "87601:127667331\tQ-min: 1.933\tQ-max: 1.976\tLives: 4\tReward: 11.0\tEpisode Mean: 132.6\n",
+      "87601:127667363\tQ-min: 1.970\tQ-max: 2.004\tLives: 4\tReward: 12.0\tEpisode Mean: 132.6\n",
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+      "87601:127667432\tQ-min: 1.974\tQ-max: 2.020\tLives: 4\tReward: 17.0\tEpisode Mean: 132.6\n",
+      "87601:127667478\tQ-min: 1.677\tQ-max: 1.694\tLives: 4\tReward: 18.0\tEpisode Mean: 132.6\n",
+      "87601:127667544\tQ-min: 1.690\tQ-max: 1.733\tLives: 4\tReward: 19.0\tEpisode Mean: 132.6\n",
+      "87601:127667606\tQ-min: 1.794\tQ-max: 1.832\tLives: 4\tReward: 20.0\tEpisode Mean: 132.6\n",
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+      "87601:127667718\tQ-min: 2.080\tQ-max: 2.130\tLives: 4\tReward: 22.0\tEpisode Mean: 132.6\n",
+      "87601:127667751\tQ-min: 2.029\tQ-max: 2.068\tLives: 4\tReward: 23.0\tEpisode Mean: 132.6\n",
+      "87601:127667781\tQ-min: 2.010\tQ-max: 2.046\tLives: 4\tReward: 24.0\tEpisode Mean: 132.6\n",
+      "87601:127667812\tQ-min: 2.073\tQ-max: 2.228\tLives: 4\tReward: 28.0\tEpisode Mean: 132.6\n",
+      "87601:127667835\tQ-min: -0.028\tQ-max: 0.177\tLives: 3\tReward: 28.0\tEpisode Mean: 132.6\n",
+      "87601:127667891\tQ-min: 1.767\tQ-max: 1.842\tLives: 3\tReward: 29.0\tEpisode Mean: 132.6\n",
+      "87601:127667946\tQ-min: 1.970\tQ-max: 2.021\tLives: 3\tReward: 30.0\tEpisode Mean: 132.6\n",
+      "87601:127667991\tQ-min: 2.062\tQ-max: 2.180\tLives: 3\tReward: 31.0\tEpisode Mean: 132.6\n",
+      "87601:127668030\tQ-min: 2.031\tQ-max: 2.068\tLives: 3\tReward: 35.0\tEpisode Mean: 132.6\n",
+      "87601:127668063\tQ-min: 2.128\tQ-max: 2.416\tLives: 3\tReward: 39.0\tEpisode Mean: 132.6\n",
+      "87601:127668085\tQ-min: 2.294\tQ-max: 2.450\tLives: 3\tReward: 43.0\tEpisode Mean: 132.6\n",
+      "87601:127668108\tQ-min: 2.309\tQ-max: 2.417\tLives: 3\tReward: 47.0\tEpisode Mean: 132.6\n",
+      "87601:127668130\tQ-min: 2.342\tQ-max: 2.450\tLives: 3\tReward: 54.0\tEpisode Mean: 132.6\n",
+      "87601:127668154\tQ-min: 2.212\tQ-max: 2.443\tLives: 3\tReward: 58.0\tEpisode Mean: 132.6\n",
+      "87601:127668176\tQ-min: 2.301\tQ-max: 2.701\tLives: 3\tReward: 65.0\tEpisode Mean: 132.6\n",
+      "87601:127668199\tQ-min: 2.417\tQ-max: 2.585\tLives: 3\tReward: 69.0\tEpisode Mean: 132.6\n",
+      "87601:127668226\tQ-min: 2.306\tQ-max: 2.719\tLives: 3\tReward: 76.0\tEpisode Mean: 132.6\n",
+      "87601:127668247\tQ-min: 2.650\tQ-max: 3.426\tLives: 3\tReward: 80.0\tEpisode Mean: 132.6\n",
+      "87601:127668270\tQ-min: 1.950\tQ-max: 3.292\tLives: 3\tReward: 84.0\tEpisode Mean: 132.6\n",
+      "87601:127668284\tQ-min: 0.406\tQ-max: 0.723\tLives: 2\tReward: 84.0\tEpisode Mean: 132.6\n",
+      "87601:127668333\tQ-min: 2.601\tQ-max: 3.435\tLives: 2\tReward: 91.0\tEpisode Mean: 132.6\n",
+      "87601:127668364\tQ-min: 2.556\tQ-max: 5.411\tLives: 2\tReward: 98.0\tEpisode Mean: 132.6\n",
+      "87601:127668369\tQ-min: 2.444\tQ-max: 5.953\tLives: 2\tReward: 105.0\tEpisode Mean: 132.6\n",
+      "87601:127668374\tQ-min: 3.765\tQ-max: 5.552\tLives: 2\tReward: 112.0\tEpisode Mean: 132.6\n",
+      "87601:127668378\tQ-min: 3.498\tQ-max: 6.066\tLives: 2\tReward: 119.0\tEpisode Mean: 132.6\n",
+      "87601:127668384\tQ-min: 3.315\tQ-max: 6.838\tLives: 2\tReward: 126.0\tEpisode Mean: 132.6\n",
+      "87601:127668388\tQ-min: 3.629\tQ-max: 6.227\tLives: 2\tReward: 133.0\tEpisode Mean: 132.6\n",
+      "87601:127668394\tQ-min: 3.125\tQ-max: 5.766\tLives: 2\tReward: 140.0\tEpisode Mean: 132.6\n",
+      "87601:127668399\tQ-min: 1.872\tQ-max: 5.354\tLives: 2\tReward: 147.0\tEpisode Mean: 132.6\n",
+      "87601:127668405\tQ-min: 1.891\tQ-max: 5.260\tLives: 2\tReward: 154.0\tEpisode Mean: 132.6\n",
+      "87601:127668444\tQ-min: 3.421\tQ-max: 5.474\tLives: 2\tReward: 161.0\tEpisode Mean: 132.6\n",
+      "87601:127668450\tQ-min: 3.133\tQ-max: 5.921\tLives: 2\tReward: 168.0\tEpisode Mean: 132.6\n",
+      "87601:127668454\tQ-min: 1.863\tQ-max: 5.537\tLives: 2\tReward: 175.0\tEpisode Mean: 132.6\n",
+      "87601:127668459\tQ-min: 1.319\tQ-max: 5.649\tLives: 2\tReward: 182.0\tEpisode Mean: 132.6\n",
+      "87601:127668463\tQ-min: 3.745\tQ-max: 5.352\tLives: 2\tReward: 189.0\tEpisode Mean: 132.6\n",
+      "87601:127668468\tQ-min: 3.931\tQ-max: 5.100\tLives: 2\tReward: 196.0\tEpisode Mean: 132.6\n",
+      "87601:127668473\tQ-min: 3.457\tQ-max: 5.721\tLives: 2\tReward: 203.0\tEpisode Mean: 132.6\n",
+      "87601:127668479\tQ-min: 2.423\tQ-max: 3.470\tLives: 2\tReward: 210.0\tEpisode Mean: 132.6\n",
+      "87601:127668488\tQ-min: 1.242\tQ-max: 2.573\tLives: 2\tReward: 211.0\tEpisode Mean: 132.6\n",
+      "87601:127668496\tQ-min: 1.938\tQ-max: 3.770\tLives: 2\tReward: 218.0\tEpisode Mean: 132.6\n",
+      "87601:127668503\tQ-min: 2.297\tQ-max: 3.498\tLives: 2\tReward: 222.0\tEpisode Mean: 132.6\n",
+      "87601:127668511\tQ-min: 1.545\tQ-max: 3.395\tLives: 2\tReward: 226.0\tEpisode Mean: 132.6\n",
+      "87601:127668520\tQ-min: 1.693\tQ-max: 3.364\tLives: 2\tReward: 233.0\tEpisode Mean: 132.6\n",
+      "87601:127668527\tQ-min: 1.683\tQ-max: 3.130\tLives: 2\tReward: 240.0\tEpisode Mean: 132.6\n",
+      "87601:127668565\tQ-min: 1.745\tQ-max: 5.647\tLives: 2\tReward: 247.0\tEpisode Mean: 132.6\n",
+      "87601:127668571\tQ-min: 1.912\tQ-max: 3.448\tLives: 2\tReward: 251.0\tEpisode Mean: 132.6\n",
+      "87601:127668611\tQ-min: 1.719\tQ-max: 3.410\tLives: 2\tReward: 255.0\tEpisode Mean: 132.6\n",
+      "87601:127668619\tQ-min: 2.959\tQ-max: 4.002\tLives: 2\tReward: 259.0\tEpisode Mean: 132.6\n",
+      "87601:127668655\tQ-min: 0.753\tQ-max: 4.262\tLives: 2\tReward: 263.0\tEpisode Mean: 132.6\n",
+      "87601:127668663\tQ-min: 2.337\tQ-max: 4.141\tLives: 2\tReward: 267.0\tEpisode Mean: 132.6\n",
+      "87601:127668715\tQ-min: 0.070\tQ-max: 0.779\tLives: 1\tReward: 267.0\tEpisode Mean: 132.6\n",
+      "87601:127668780\tQ-min: 0.650\tQ-max: 2.531\tLives: 1\tReward: 274.0\tEpisode Mean: 132.6\n",
+      "87601:127668794\tQ-min: 0.176\tQ-max: 0.366\tLives: 0\tReward: 274.0\tEpisode Mean: 142.7\n",
+      "87602:127668849\tQ-min: 1.660\tQ-max: 1.689\tLives: 5\tReward: 1.0\tEpisode Mean: 142.7\n",
+      "87602:127668901\tQ-min: 1.762\tQ-max: 1.772\tLives: 5\tReward: 2.0\tEpisode Mean: 142.7\n",
+      "87602:127668955\tQ-min: 1.668\tQ-max: 1.699\tLives: 5\tReward: 3.0\tEpisode Mean: 142.7\n",
+      "87602:127669000\tQ-min: 1.975\tQ-max: 2.019\tLives: 5\tReward: 4.0\tEpisode Mean: 142.7\n",
+      "87602:127669020\tQ-min: -0.215\tQ-max: 0.113\tLives: 4\tReward: 4.0\tEpisode Mean: 142.7\n",
+      "87602:127669074\tQ-min: 1.651\tQ-max: 1.672\tLives: 4\tReward: 5.0\tEpisode Mean: 142.7\n",
+      "87602:127669129\tQ-min: 1.880\tQ-max: 1.922\tLives: 4\tReward: 6.0\tEpisode Mean: 142.7\n",
+      "87602:127669171\tQ-min: 1.946\tQ-max: 1.986\tLives: 4\tReward: 10.0\tEpisode Mean: 142.7\n",
+      "87602:127669212\tQ-min: 1.944\tQ-max: 2.002\tLives: 4\tReward: 11.0\tEpisode Mean: 142.7\n",
+      "87602:127669242\tQ-min: 1.973\tQ-max: 2.019\tLives: 4\tReward: 12.0\tEpisode Mean: 142.7\n",
+      "87602:127669274\tQ-min: 1.926\tQ-max: 1.975\tLives: 4\tReward: 13.0\tEpisode Mean: 142.7\n",
+      "87602:127669307\tQ-min: 2.105\tQ-max: 2.278\tLives: 4\tReward: 17.0\tEpisode Mean: 142.7\n",
+      "87602:127669357\tQ-min: 1.747\tQ-max: 1.796\tLives: 4\tReward: 18.0\tEpisode Mean: 142.7\n",
+      "87602:127669417\tQ-min: 1.715\tQ-max: 1.727\tLives: 4\tReward: 19.0\tEpisode Mean: 142.7\n",
+      "87602:127669482\tQ-min: 1.681\tQ-max: 1.718\tLives: 4\tReward: 20.0\tEpisode Mean: 142.7\n",
+      "87602:127669553\tQ-min: 1.743\tQ-max: 1.765\tLives: 4\tReward: 21.0\tEpisode Mean: 142.7\n",
+      "87602:127669603\tQ-min: 2.072\tQ-max: 2.117\tLives: 4\tReward: 22.0\tEpisode Mean: 142.7\n",
+      "87602:127669636\tQ-min: 2.084\tQ-max: 2.119\tLives: 4\tReward: 23.0\tEpisode Mean: 142.7\n",
+      "87602:127669670\tQ-min: 2.010\tQ-max: 2.060\tLives: 4\tReward: 24.0\tEpisode Mean: 142.7\n",
+      "87602:127669704\tQ-min: 1.898\tQ-max: 1.979\tLives: 4\tReward: 28.0\tEpisode Mean: 142.7\n",
+      "87602:127669738\tQ-min: 2.096\tQ-max: 2.180\tLives: 4\tReward: 29.0\tEpisode Mean: 142.7\n",
+      "87602:127669772\tQ-min: 2.142\tQ-max: 2.170\tLives: 4\tReward: 33.0\tEpisode Mean: 142.7\n",
+      "87602:127669807\tQ-min: 2.072\tQ-max: 2.183\tLives: 4\tReward: 34.0\tEpisode Mean: 142.7\n",
+      "87602:127669841\tQ-min: 2.174\tQ-max: 2.224\tLives: 4\tReward: 38.0\tEpisode Mean: 142.7\n",
+      "87602:127669873\tQ-min: 2.093\tQ-max: 2.191\tLives: 4\tReward: 39.0\tEpisode Mean: 142.7\n",
+      "87602:127669910\tQ-min: 2.197\tQ-max: 2.437\tLives: 4\tReward: 43.0\tEpisode Mean: 142.7\n",
+      "87602:127669931\tQ-min: 2.435\tQ-max: 2.479\tLives: 4\tReward: 44.0\tEpisode Mean: 142.7\n",
+      "87602:127669952\tQ-min: 2.251\tQ-max: 2.526\tLives: 4\tReward: 45.0\tEpisode Mean: 142.7\n",
+      "87602:127669974\tQ-min: 2.238\tQ-max: 2.452\tLives: 4\tReward: 46.0\tEpisode Mean: 142.7\n",
+      "87602:127669993\tQ-min: 2.353\tQ-max: 2.468\tLives: 4\tReward: 47.0\tEpisode Mean: 142.7\n",
+      "87602:127670013\tQ-min: 2.226\tQ-max: 2.469\tLives: 4\tReward: 51.0\tEpisode Mean: 142.7\n",
+      "87602:127670035\tQ-min: 2.220\tQ-max: 2.600\tLives: 4\tReward: 55.0\tEpisode Mean: 142.7\n",
+      "87602:127670058\tQ-min: 2.358\tQ-max: 2.584\tLives: 4\tReward: 59.0\tEpisode Mean: 142.7\n",
+      "87602:127670082\tQ-min: 2.341\tQ-max: 2.521\tLives: 4\tReward: 63.0\tEpisode Mean: 142.7\n",
+      "87602:127670103\tQ-min: 2.369\tQ-max: 2.522\tLives: 4\tReward: 67.0\tEpisode Mean: 142.7\n",
+      "87602:127670126\tQ-min: 1.917\tQ-max: 2.413\tLives: 4\tReward: 68.0\tEpisode Mean: 142.7\n",
+      "87602:127670145\tQ-min: 2.342\tQ-max: 2.609\tLives: 4\tReward: 69.0\tEpisode Mean: 142.7\n",
+      "87602:127670158\tQ-min: -0.303\tQ-max: 0.424\tLives: 3\tReward: 69.0\tEpisode Mean: 142.7\n",
+      "87602:127670202\tQ-min: 2.325\tQ-max: 2.465\tLives: 3\tReward: 73.0\tEpisode Mean: 142.7\n",
+      "87602:127670224\tQ-min: 2.308\tQ-max: 2.635\tLives: 3\tReward: 74.0\tEpisode Mean: 142.7\n",
+      "87602:127670245\tQ-min: 2.460\tQ-max: 2.646\tLives: 3\tReward: 78.0\tEpisode Mean: 142.7\n",
+      "87602:127670269\tQ-min: 2.455\tQ-max: 2.712\tLives: 3\tReward: 85.0\tEpisode Mean: 142.7\n",
+      "87602:127670292\tQ-min: 2.240\tQ-max: 2.845\tLives: 3\tReward: 92.0\tEpisode Mean: 142.7\n",
+      "87602:127670315\tQ-min: 2.779\tQ-max: 3.246\tLives: 3\tReward: 96.0\tEpisode Mean: 142.7\n",
+      "87602:127670328\tQ-min: 0.010\tQ-max: 0.268\tLives: 2\tReward: 96.0\tEpisode Mean: 142.7\n",
+      "87602:127670382\tQ-min: 0.438\tQ-max: 2.764\tLives: 2\tReward: 103.0\tEpisode Mean: 142.7\n",
+      "87602:127670406\tQ-min: 2.238\tQ-max: 4.566\tLives: 2\tReward: 110.0\tEpisode Mean: 142.7\n",
+      "87602:127670429\tQ-min: 2.586\tQ-max: 3.575\tLives: 2\tReward: 114.0\tEpisode Mean: 142.7\n",
+      "87602:127670457\tQ-min: 2.830\tQ-max: 6.067\tLives: 2\tReward: 121.0\tEpisode Mean: 142.7\n",
+      "87602:127670462\tQ-min: 3.539\tQ-max: 6.227\tLives: 2\tReward: 128.0\tEpisode Mean: 142.7\n",
+      "87602:127670467\tQ-min: 2.655\tQ-max: 5.876\tLives: 2\tReward: 135.0\tEpisode Mean: 142.7\n",
+      "87602:127670472\tQ-min: 2.309\tQ-max: 6.446\tLives: 2\tReward: 142.0\tEpisode Mean: 142.7\n",
+      "87602:127670478\tQ-min: 2.977\tQ-max: 6.508\tLives: 2\tReward: 149.0\tEpisode Mean: 142.7\n",
+      "87602:127670483\tQ-min: 2.145\tQ-max: 5.609\tLives: 2\tReward: 156.0\tEpisode Mean: 142.7\n",
+      "87602:127670487\tQ-min: 1.552\tQ-max: 5.483\tLives: 2\tReward: 163.0\tEpisode Mean: 142.7\n",
+      "87602:127670493\tQ-min: 0.675\tQ-max: 6.091\tLives: 2\tReward: 170.0\tEpisode Mean: 142.7\n",
+      "87602:127670499\tQ-min: 3.525\tQ-max: 5.526\tLives: 2\tReward: 177.0\tEpisode Mean: 142.7\n",
+      "87602:127670506\tQ-min: 3.911\tQ-max: 5.610\tLives: 2\tReward: 184.0\tEpisode Mean: 142.7\n",
+      "87602:127670513\tQ-min: 3.107\tQ-max: 4.286\tLives: 2\tReward: 191.0\tEpisode Mean: 142.7\n",
+      "87602:127670519\tQ-min: 3.875\tQ-max: 5.261\tLives: 2\tReward: 198.0\tEpisode Mean: 142.7\n",
+      "87602:127670524\tQ-min: 3.681\tQ-max: 4.988\tLives: 2\tReward: 205.0\tEpisode Mean: 142.7\n",
+      "87602:127670530\tQ-min: 3.829\tQ-max: 5.252\tLives: 2\tReward: 212.0\tEpisode Mean: 142.7\n",
+      "87602:127670537\tQ-min: 3.661\tQ-max: 5.947\tLives: 2\tReward: 219.0\tEpisode Mean: 142.7\n",
+      "87602:127670543\tQ-min: 0.818\tQ-max: 6.100\tLives: 2\tReward: 226.0\tEpisode Mean: 142.7\n",
+      "87602:127670550\tQ-min: 1.349\tQ-max: 4.426\tLives: 2\tReward: 233.0\tEpisode Mean: 142.7\n",
+      "87602:127670556\tQ-min: 3.577\tQ-max: 4.942\tLives: 2\tReward: 240.0\tEpisode Mean: 142.7\n",
+      "87602:127670563\tQ-min: 1.653\tQ-max: 3.518\tLives: 2\tReward: 244.0\tEpisode Mean: 142.7\n",
+      "87602:127670569\tQ-min: 1.497\tQ-max: 4.850\tLives: 2\tReward: 251.0\tEpisode Mean: 142.7\n",
+      "87602:127670606\tQ-min: 3.148\tQ-max: 6.722\tLives: 2\tReward: 258.0\tEpisode Mean: 142.7\n",
+      "87602:127670611\tQ-min: 3.101\tQ-max: 4.130\tLives: 2\tReward: 265.0\tEpisode Mean: 142.7\n",
+      "87602:127670616\tQ-min: 4.503\tQ-max: 5.602\tLives: 2\tReward: 272.0\tEpisode Mean: 142.7\n",
+      "87602:127670623\tQ-min: 2.842\tQ-max: 5.075\tLives: 2\tReward: 279.0\tEpisode Mean: 142.7\n",
+      "87602:127670629\tQ-min: 2.633\tQ-max: 5.970\tLives: 2\tReward: 286.0\tEpisode Mean: 142.7\n",
+      "87602:127670635\tQ-min: 2.501\tQ-max: 5.630\tLives: 2\tReward: 293.0\tEpisode Mean: 142.7\n",
+      "87602:127670641\tQ-min: 2.565\tQ-max: 5.003\tLives: 2\tReward: 300.0\tEpisode Mean: 142.7\n",
+      "87602:127670648\tQ-min: 1.812\tQ-max: 2.868\tLives: 2\tReward: 304.0\tEpisode Mean: 142.7\n",
+      "87602:127670655\tQ-min: 2.751\tQ-max: 3.801\tLives: 2\tReward: 311.0\tEpisode Mean: 142.7\n",
+      "87602:127670661\tQ-min: 2.372\tQ-max: 4.040\tLives: 2\tReward: 318.0\tEpisode Mean: 142.7\n",
+      "87602:127670682\tQ-min: -0.290\tQ-max: 0.641\tLives: 1\tReward: 318.0\tEpisode Mean: 142.7\n",
+      "87602:127670749\tQ-min: 1.195\tQ-max: 2.524\tLives: 1\tReward: 322.0\tEpisode Mean: 142.7\n",
+      "87602:127670757\tQ-min: 1.663\tQ-max: 3.343\tLives: 1\tReward: 326.0\tEpisode Mean: 142.7\n",
+      "87602:127670781\tQ-min: -0.047\tQ-max: 0.144\tLives: 0\tReward: 326.0\tEpisode Mean: 154.9\n",
+      "87603:127670833\tQ-min: 1.652\tQ-max: 1.663\tLives: 5\tReward: 1.0\tEpisode Mean: 154.9\n",
+      "87603:127670884\tQ-min: 1.845\tQ-max: 1.871\tLives: 5\tReward: 2.0\tEpisode Mean: 154.9\n",
+      "87603:127670925\tQ-min: 1.900\tQ-max: 1.927\tLives: 5\tReward: 3.0\tEpisode Mean: 154.9\n",
+      "87603:127670963\tQ-min: 2.001\tQ-max: 2.066\tLives: 5\tReward: 4.0\tEpisode Mean: 154.9\n",
+      "87603:127670996\tQ-min: 1.983\tQ-max: 2.002\tLives: 5\tReward: 5.0\tEpisode Mean: 154.9\n",
+      "87603:127671027\tQ-min: 1.927\tQ-max: 1.968\tLives: 5\tReward: 6.0\tEpisode Mean: 154.9\n",
+      "87603:127671060\tQ-min: 1.748\tQ-max: 1.767\tLives: 5\tReward: 7.0\tEpisode Mean: 154.9\n",
+      "87603:127671081\tQ-min: -0.046\tQ-max: 0.168\tLives: 4\tReward: 7.0\tEpisode Mean: 154.9\n",
+      "87603:127671130\tQ-min: 1.708\tQ-max: 1.726\tLives: 4\tReward: 8.0\tEpisode Mean: 154.9\n",
+      "87603:127671184\tQ-min: 1.876\tQ-max: 1.902\tLives: 4\tReward: 9.0\tEpisode Mean: 154.9\n",
+      "87603:127671225\tQ-min: 1.927\tQ-max: 1.958\tLives: 4\tReward: 10.0\tEpisode Mean: 154.9\n",
+      "87603:127671266\tQ-min: 2.034\tQ-max: 2.070\tLives: 4\tReward: 11.0\tEpisode Mean: 154.9\n",
+      "87603:127671303\tQ-min: 1.926\tQ-max: 1.949\tLives: 4\tReward: 12.0\tEpisode Mean: 154.9\n",
+      "87603:127671336\tQ-min: 2.010\tQ-max: 2.036\tLives: 4\tReward: 16.0\tEpisode Mean: 154.9\n",
+      "87603:127671366\tQ-min: 1.950\tQ-max: 1.971\tLives: 4\tReward: 17.0\tEpisode Mean: 154.9\n",
+      "87603:127671409\tQ-min: 1.646\tQ-max: 1.664\tLives: 4\tReward: 18.0\tEpisode Mean: 154.9\n",
+      "87603:127671468\tQ-min: 1.675\tQ-max: 1.699\tLives: 4\tReward: 19.0\tEpisode Mean: 154.9\n",
+      "87603:127671535\tQ-min: 1.714\tQ-max: 1.759\tLives: 4\tReward: 20.0\tEpisode Mean: 154.9\n",
+      "87603:127671597\tQ-min: 1.722\tQ-max: 1.766\tLives: 4\tReward: 21.0\tEpisode Mean: 154.9\n",
+      "87603:127671642\tQ-min: 1.999\tQ-max: 2.018\tLives: 4\tReward: 22.0\tEpisode Mean: 154.9\n",
+      "87603:127671664\tQ-min: -0.050\tQ-max: 0.210\tLives: 3\tReward: 22.0\tEpisode Mean: 154.9\n",
+      "87603:127671719\tQ-min: 1.703\tQ-max: 1.715\tLives: 3\tReward: 23.0\tEpisode Mean: 154.9\n",
+      "87603:127671777\tQ-min: 1.927\tQ-max: 2.036\tLives: 3\tReward: 27.0\tEpisode Mean: 154.9\n",
+      "87603:127671830\tQ-min: 1.748\tQ-max: 1.798\tLives: 3\tReward: 28.0\tEpisode Mean: 154.9\n",
+      "87603:127671884\tQ-min: 1.995\tQ-max: 2.128\tLives: 3\tReward: 32.0\tEpisode Mean: 154.9\n",
+      "87603:127671907\tQ-min: -0.121\tQ-max: 0.204\tLives: 2\tReward: 32.0\tEpisode Mean: 154.9\n",
+      "87603:127671947\tQ-min: 2.019\tQ-max: 2.045\tLives: 2\tReward: 33.0\tEpisode Mean: 154.9\n",
+      "87603:127672004\tQ-min: 1.658\tQ-max: 1.772\tLives: 2\tReward: 34.0\tEpisode Mean: 154.9\n",
+      "87603:127672069\tQ-min: 1.687\tQ-max: 1.790\tLives: 2\tReward: 35.0\tEpisode Mean: 154.9\n",
+      "87603:127672121\tQ-min: 2.131\tQ-max: 2.251\tLives: 2\tReward: 36.0\tEpisode Mean: 154.9\n",
+      "87603:127672157\tQ-min: 2.166\tQ-max: 2.329\tLives: 2\tReward: 37.0\tEpisode Mean: 154.9\n",
+      "87603:127672190\tQ-min: 2.115\tQ-max: 2.157\tLives: 2\tReward: 41.0\tEpisode Mean: 154.9\n",
+      "87603:127672224\tQ-min: 2.188\tQ-max: 2.245\tLives: 2\tReward: 42.0\tEpisode Mean: 154.9\n",
+      "87603:127672270\tQ-min: 1.796\tQ-max: 1.822\tLives: 2\tReward: 43.0\tEpisode Mean: 154.9\n",
+      "87603:127672330\tQ-min: 1.802\tQ-max: 1.857\tLives: 2\tReward: 44.0\tEpisode Mean: 154.9\n",
+      "87603:127672396\tQ-min: 1.711\tQ-max: 1.784\tLives: 2\tReward: 45.0\tEpisode Mean: 154.9\n",
+      "87603:127672464\tQ-min: 1.600\tQ-max: 1.845\tLives: 2\tReward: 49.0\tEpisode Mean: 154.9\n",
+      "87603:127672520\tQ-min: 2.268\tQ-max: 2.461\tLives: 2\tReward: 53.0\tEpisode Mean: 154.9\n",
+      "87603:127672540\tQ-min: 2.428\tQ-max: 2.548\tLives: 2\tReward: 54.0\tEpisode Mean: 154.9\n",
+      "87603:127672554\tQ-min: 0.115\tQ-max: 0.197\tLives: 1\tReward: 54.0\tEpisode Mean: 154.9\n",
+      "87603:127672609\tQ-min: 1.839\tQ-max: 1.941\tLives: 1\tReward: 58.0\tEpisode Mean: 154.9\n",
+      "87603:127672663\tQ-min: 2.221\tQ-max: 2.305\tLives: 1\tReward: 59.0\tEpisode Mean: 154.9\n",
+      "87603:127672717\tQ-min: 2.086\tQ-max: 2.380\tLives: 1\tReward: 63.0\tEpisode Mean: 154.9\n",
+      "87603:127672771\tQ-min: 2.328\tQ-max: 2.475\tLives: 1\tReward: 67.0\tEpisode Mean: 154.9\n",
+      "87603:127672793\tQ-min: 2.290\tQ-max: 2.543\tLives: 1\tReward: 71.0\tEpisode Mean: 154.9\n",
+      "87603:127672813\tQ-min: 2.222\tQ-max: 2.463\tLives: 1\tReward: 75.0\tEpisode Mean: 154.9\n",
+      "87603:127672827\tQ-min: 0.138\tQ-max: 0.258\tLives: 0\tReward: 75.0\tEpisode Mean: 149.9\n",
+      "87604:127672885\tQ-min: 1.693\tQ-max: 1.714\tLives: 5\tReward: 1.0\tEpisode Mean: 149.9\n",
+      "87604:127672948\tQ-min: 1.663\tQ-max: 1.679\tLives: 5\tReward: 2.0\tEpisode Mean: 149.9\n",
+      "87604:127673000\tQ-min: 1.873\tQ-max: 1.875\tLives: 5\tReward: 3.0\tEpisode Mean: 149.9\n",
+      "87604:127673035\tQ-min: 2.045\tQ-max: 2.064\tLives: 5\tReward: 4.0\tEpisode Mean: 149.9\n",
+      "87604:127673066\tQ-min: 1.967\tQ-max: 1.997\tLives: 5\tReward: 5.0\tEpisode Mean: 149.9\n",
+      "87604:127673101\tQ-min: 1.931\tQ-max: 1.941\tLives: 5\tReward: 6.0\tEpisode Mean: 149.9\n",
+      "87604:127673134\tQ-min: 1.836\tQ-max: 1.872\tLives: 5\tReward: 7.0\tEpisode Mean: 149.9\n",
+      "87604:127673182\tQ-min: 1.651\tQ-max: 1.662\tLives: 5\tReward: 8.0\tEpisode Mean: 149.9\n",
+      "87604:127673246\tQ-min: 1.671\tQ-max: 1.690\tLives: 5\tReward: 9.0\tEpisode Mean: 149.9\n",
+      "87604:127673310\tQ-min: 1.638\tQ-max: 1.679\tLives: 5\tReward: 10.0\tEpisode Mean: 149.9\n",
+      "87604:127673378\tQ-min: 1.585\tQ-max: 1.661\tLives: 5\tReward: 11.0\tEpisode Mean: 149.9\n",
+      "87604:127673428\tQ-min: 1.931\tQ-max: 1.982\tLives: 5\tReward: 12.0\tEpisode Mean: 149.9\n",
+      "87604:127673461\tQ-min: 1.894\tQ-max: 1.993\tLives: 5\tReward: 16.0\tEpisode Mean: 149.9\n",
+      "87604:127673496\tQ-min: 1.928\tQ-max: 1.944\tLives: 5\tReward: 17.0\tEpisode Mean: 149.9\n",
+      "87604:127673529\tQ-min: 2.050\tQ-max: 2.108\tLives: 5\tReward: 18.0\tEpisode Mean: 149.9\n",
+      "87604:127673550\tQ-min: -0.158\tQ-max: 0.070\tLives: 4\tReward: 18.0\tEpisode Mean: 149.9\n",
+      "87604:127673605\tQ-min: 1.720\tQ-max: 1.787\tLives: 4\tReward: 19.0\tEpisode Mean: 149.9\n",
+      "87604:127673657\tQ-min: 1.970\tQ-max: 2.001\tLives: 4\tReward: 20.0\tEpisode Mean: 149.9\n",
+      "87604:127673701\tQ-min: 1.980\tQ-max: 2.030\tLives: 4\tReward: 21.0\tEpisode Mean: 149.9\n",
+      "87604:127673738\tQ-min: 2.030\tQ-max: 2.057\tLives: 4\tReward: 22.0\tEpisode Mean: 149.9\n",
+      "87604:127673774\tQ-min: 2.097\tQ-max: 2.124\tLives: 4\tReward: 23.0\tEpisode Mean: 149.9\n",
+      "87604:127673807\tQ-min: 2.042\tQ-max: 2.060\tLives: 4\tReward: 27.0\tEpisode Mean: 149.9\n",
+      "87604:127673841\tQ-min: 2.120\tQ-max: 2.154\tLives: 4\tReward: 31.0\tEpisode Mean: 149.9\n",
+      "87604:127673889\tQ-min: 1.773\tQ-max: 1.815\tLives: 4\tReward: 32.0\tEpisode Mean: 149.9\n",
+      "87604:127673952\tQ-min: 1.786\tQ-max: 1.805\tLives: 4\tReward: 33.0\tEpisode Mean: 149.9\n",
+      "87604:127674015\tQ-min: 1.828\tQ-max: 1.850\tLives: 4\tReward: 34.0\tEpisode Mean: 149.9\n",
+      "87604:127674080\tQ-min: 1.758\tQ-max: 1.826\tLives: 4\tReward: 35.0\tEpisode Mean: 149.9\n",
+      "87604:127674132\tQ-min: 2.034\tQ-max: 2.092\tLives: 4\tReward: 36.0\tEpisode Mean: 149.9\n",
+      "87604:127674166\tQ-min: 2.050\tQ-max: 2.077\tLives: 4\tReward: 37.0\tEpisode Mean: 149.9\n",
+      "87604:127674199\tQ-min: 2.194\tQ-max: 2.223\tLives: 4\tReward: 38.0\tEpisode Mean: 149.9\n",
+      "87604:127674237\tQ-min: 2.105\tQ-max: 2.220\tLives: 4\tReward: 42.0\tEpisode Mean: 149.9\n",
+      "87604:127674268\tQ-min: 2.101\tQ-max: 2.207\tLives: 4\tReward: 43.0\tEpisode Mean: 149.9\n",
+      "87604:127674302\tQ-min: 2.200\tQ-max: 2.251\tLives: 4\tReward: 44.0\tEpisode Mean: 149.9\n",
+      "87604:127674332\tQ-min: 2.115\tQ-max: 2.179\tLives: 4\tReward: 45.0\tEpisode Mean: 149.9\n",
+      "87604:127674364\tQ-min: 2.114\tQ-max: 2.247\tLives: 4\tReward: 49.0\tEpisode Mean: 149.9\n",
+      "87604:127674400\tQ-min: 2.137\tQ-max: 2.320\tLives: 4\tReward: 50.0\tEpisode Mean: 149.9\n",
+      "87604:127674435\tQ-min: 2.079\tQ-max: 2.216\tLives: 4\tReward: 54.0\tEpisode Mean: 149.9\n",
+      "87604:127674475\tQ-min: 2.200\tQ-max: 2.377\tLives: 4\tReward: 58.0\tEpisode Mean: 149.9\n",
+      "87604:127674499\tQ-min: 2.350\tQ-max: 2.537\tLives: 4\tReward: 62.0\tEpisode Mean: 149.9\n",
+      "87604:127674520\tQ-min: 2.408\tQ-max: 2.597\tLives: 4\tReward: 66.0\tEpisode Mean: 149.9\n",
+      "87604:127674543\tQ-min: 2.412\tQ-max: 2.525\tLives: 4\tReward: 67.0\tEpisode Mean: 149.9\n",
+      "87604:127674565\tQ-min: 2.482\tQ-max: 2.556\tLives: 4\tReward: 68.0\tEpisode Mean: 149.9\n",
+      "87604:127674585\tQ-min: 2.394\tQ-max: 2.539\tLives: 4\tReward: 72.0\tEpisode Mean: 149.9\n",
+      "87604:127674600\tQ-min: 0.053\tQ-max: 0.197\tLives: 3\tReward: 72.0\tEpisode Mean: 149.9\n",
+      "87604:127674656\tQ-min: 1.584\tQ-max: 1.884\tLives: 3\tReward: 76.0\tEpisode Mean: 149.9\n",
+      "87604:127674714\tQ-min: 2.218\tQ-max: 2.353\tLives: 3\tReward: 80.0\tEpisode Mean: 149.9\n",
+      "87604:127674759\tQ-min: 2.189\tQ-max: 2.243\tLives: 3\tReward: 81.0\tEpisode Mean: 149.9\n",
+      "87604:127674802\tQ-min: 2.331\tQ-max: 2.365\tLives: 3\tReward: 85.0\tEpisode Mean: 149.9\n",
+      "87604:127674843\tQ-min: 2.299\tQ-max: 2.737\tLives: 3\tReward: 92.0\tEpisode Mean: 149.9\n",
+      "87604:127674865\tQ-min: 2.367\tQ-max: 2.514\tLives: 3\tReward: 96.0\tEpisode Mean: 149.9\n",
+      "87604:127674889\tQ-min: 2.248\tQ-max: 2.649\tLives: 3\tReward: 103.0\tEpisode Mean: 149.9\n",
+      "87604:127674912\tQ-min: 2.439\tQ-max: 3.002\tLives: 3\tReward: 107.0\tEpisode Mean: 149.9\n",
+      "87604:127674938\tQ-min: 2.280\tQ-max: 2.987\tLives: 3\tReward: 114.0\tEpisode Mean: 149.9\n",
+      "87604:127674963\tQ-min: 2.794\tQ-max: 3.503\tLives: 3\tReward: 121.0\tEpisode Mean: 149.9\n",
+      "87604:127674991\tQ-min: 2.500\tQ-max: 7.708\tLives: 3\tReward: 128.0\tEpisode Mean: 149.9\n",
+      "87604:127674997\tQ-min: 2.156\tQ-max: 7.000\tLives: 3\tReward: 135.0\tEpisode Mean: 149.9\n",
+      "87604:127675002\tQ-min: 2.477\tQ-max: 6.028\tLives: 3\tReward: 142.0\tEpisode Mean: 149.9\n",
+      "87604:127675007\tQ-min: 4.239\tQ-max: 6.303\tLives: 3\tReward: 149.0\tEpisode Mean: 149.9\n",
+      "87604:127675011\tQ-min: 3.918\tQ-max: 7.023\tLives: 3\tReward: 156.0\tEpisode Mean: 149.9\n",
+      "87604:127675017\tQ-min: 3.540\tQ-max: 6.474\tLives: 3\tReward: 163.0\tEpisode Mean: 149.9\n",
+      "87604:127675023\tQ-min: 1.202\tQ-max: 6.183\tLives: 3\tReward: 170.0\tEpisode Mean: 149.9\n",
+      "87604:127675028\tQ-min: 0.965\tQ-max: 5.638\tLives: 3\tReward: 177.0\tEpisode Mean: 149.9\n",
+      "87604:127675035\tQ-min: 2.349\tQ-max: 4.229\tLives: 3\tReward: 181.0\tEpisode Mean: 149.9\n",
+      "87604:127675042\tQ-min: 2.396\tQ-max: 5.087\tLives: 3\tReward: 188.0\tEpisode Mean: 149.9\n",
+      "87604:127675048\tQ-min: 3.254\tQ-max: 4.975\tLives: 3\tReward: 195.0\tEpisode Mean: 149.9\n",
+      "87604:127675054\tQ-min: 3.008\tQ-max: 5.374\tLives: 3\tReward: 202.0\tEpisode Mean: 149.9\n",
+      "87604:127675060\tQ-min: 3.376\tQ-max: 5.494\tLives: 3\tReward: 209.0\tEpisode Mean: 149.9\n",
+      "87604:127675065\tQ-min: 3.540\tQ-max: 5.774\tLives: 3\tReward: 216.0\tEpisode Mean: 149.9\n",
+      "87604:127675070\tQ-min: 3.060\tQ-max: 4.781\tLives: 3\tReward: 223.0\tEpisode Mean: 149.9\n",
+      "87604:127675077\tQ-min: 1.581\tQ-max: 5.604\tLives: 3\tReward: 230.0\tEpisode Mean: 149.9\n",
+      "87604:127675081\tQ-min: 1.432\tQ-max: 4.240\tLives: 3\tReward: 237.0\tEpisode Mean: 149.9\n",
+      "87604:127675086\tQ-min: 3.265\tQ-max: 4.325\tLives: 3\tReward: 244.0\tEpisode Mean: 149.9\n",
+      "87604:127675092\tQ-min: 2.793\tQ-max: 4.364\tLives: 3\tReward: 251.0\tEpisode Mean: 149.9\n",
+      "87604:127675098\tQ-min: 1.659\tQ-max: 4.788\tLives: 3\tReward: 258.0\tEpisode Mean: 149.9\n",
+      "87604:127675104\tQ-min: 2.185\tQ-max: 3.692\tLives: 3\tReward: 265.0\tEpisode Mean: 149.9\n",
+      "87604:127675110\tQ-min: 3.059\tQ-max: 5.168\tLives: 3\tReward: 272.0\tEpisode Mean: 149.9\n",
+      "87604:127675116\tQ-min: 2.764\tQ-max: 3.735\tLives: 3\tReward: 279.0\tEpisode Mean: 149.9\n",
+      "87604:127675154\tQ-min: 2.274\tQ-max: 4.377\tLives: 3\tReward: 283.0\tEpisode Mean: 149.9\n",
+      "87604:127675162\tQ-min: 2.393\tQ-max: 5.473\tLives: 3\tReward: 287.0\tEpisode Mean: 149.9\n",
+      "87604:127675199\tQ-min: 2.164\tQ-max: 3.879\tLives: 3\tReward: 294.0\tEpisode Mean: 149.9\n",
+      "87604:127675206\tQ-min: 1.621\tQ-max: 4.900\tLives: 3\tReward: 301.0\tEpisode Mean: 149.9\n",
+      "87604:127675213\tQ-min: 2.385\tQ-max: 4.757\tLives: 3\tReward: 308.0\tEpisode Mean: 149.9\n",
+      "87604:127675220\tQ-min: 3.074\tQ-max: 4.138\tLives: 3\tReward: 315.0\tEpisode Mean: 149.9\n",
+      "87604:127675226\tQ-min: 1.986\tQ-max: 2.857\tLives: 3\tReward: 319.0\tEpisode Mean: 149.9\n",
+      "87604:127675250\tQ-min: -0.037\tQ-max: 0.340\tLives: 2\tReward: 319.0\tEpisode Mean: 149.9\n",
+      "87604:127675303\tQ-min: 1.394\tQ-max: 2.884\tLives: 2\tReward: 326.0\tEpisode Mean: 149.9\n",
+      "87604:127675327\tQ-min: 1.153\tQ-max: 2.299\tLives: 2\tReward: 330.0\tEpisode Mean: 149.9\n",
+      "87604:127675348\tQ-min: 1.783\tQ-max: 2.660\tLives: 2\tReward: 334.0\tEpisode Mean: 149.9\n",
+      "87604:127675371\tQ-min: 2.439\tQ-max: 3.126\tLives: 2\tReward: 338.0\tEpisode Mean: 149.9\n",
+      "87604:127675391\tQ-min: 2.384\tQ-max: 2.837\tLives: 2\tReward: 339.0\tEpisode Mean: 149.9\n",
+      "87604:127675412\tQ-min: 1.705\tQ-max: 4.095\tLives: 2\tReward: 343.0\tEpisode Mean: 149.9\n",
+      "87604:127675431\tQ-min: 1.738\tQ-max: 3.458\tLives: 2\tReward: 347.0\tEpisode Mean: 149.9\n",
+      "87604:127675462\tQ-min: 2.482\tQ-max: 4.338\tLives: 2\tReward: 354.0\tEpisode Mean: 149.9\n",
+      "87604:127675485\tQ-min: 0.097\tQ-max: 0.350\tLives: 1\tReward: 354.0\tEpisode Mean: 149.9\n",
+      "87604:127675583\tQ-min: -0.169\tQ-max: 0.298\tLives: 0\tReward: 354.0\tEpisode Mean: 161.9\n",
+      "87605:127675625\tQ-min: 1.748\tQ-max: 1.756\tLives: 5\tReward: 1.0\tEpisode Mean: 161.9\n",
+      "87605:127675666\tQ-min: 1.814\tQ-max: 1.842\tLives: 5\tReward: 2.0\tEpisode Mean: 161.9\n",
+      "87605:127675705\tQ-min: 1.902\tQ-max: 1.919\tLives: 5\tReward: 3.0\tEpisode Mean: 161.9\n",
+      "87605:127675743\tQ-min: 1.980\tQ-max: 2.007\tLives: 5\tReward: 4.0\tEpisode Mean: 161.9\n",
+      "87605:127675778\tQ-min: 1.964\tQ-max: 1.994\tLives: 5\tReward: 5.0\tEpisode Mean: 161.9\n",
+      "87605:127675810\tQ-min: 1.965\tQ-max: 2.003\tLives: 5\tReward: 6.0\tEpisode Mean: 161.9\n",
+      "87605:127675843\tQ-min: 1.766\tQ-max: 1.801\tLives: 5\tReward: 7.0\tEpisode Mean: 161.9\n",
+      "87605:127675891\tQ-min: 1.605\tQ-max: 1.707\tLives: 5\tReward: 8.0\tEpisode Mean: 161.9\n",
+      "87605:127675954\tQ-min: 1.706\tQ-max: 1.718\tLives: 5\tReward: 9.0\tEpisode Mean: 161.9\n",
+      "87605:127676023\tQ-min: 1.680\tQ-max: 1.760\tLives: 5\tReward: 10.0\tEpisode Mean: 161.9\n",
+      "87605:127676089\tQ-min: 1.653\tQ-max: 1.678\tLives: 5\tReward: 11.0\tEpisode Mean: 161.9\n",
+      "87605:127676138\tQ-min: 1.868\tQ-max: 2.061\tLives: 5\tReward: 12.0\tEpisode Mean: 161.9\n",
+      "87605:127676172\tQ-min: 1.976\tQ-max: 1.995\tLives: 5\tReward: 13.0\tEpisode Mean: 161.9\n",
+      "87605:127676193\tQ-min: -0.059\tQ-max: 0.295\tLives: 4\tReward: 13.0\tEpisode Mean: 161.9\n",
+      "87605:127676235\tQ-min: 1.906\tQ-max: 1.942\tLives: 4\tReward: 14.0\tEpisode Mean: 161.9\n",
+      "87605:127676288\tQ-min: 1.763\tQ-max: 1.829\tLives: 4\tReward: 15.0\tEpisode Mean: 161.9\n",
+      "87605:127676346\tQ-min: 2.014\tQ-max: 2.055\tLives: 4\tReward: 19.0\tEpisode Mean: 161.9\n",
+      "87605:127676385\tQ-min: 2.041\tQ-max: 2.080\tLives: 4\tReward: 20.0\tEpisode Mean: 161.9\n",
+      "87605:127676418\tQ-min: 2.044\tQ-max: 2.170\tLives: 4\tReward: 21.0\tEpisode Mean: 161.9\n",
+      "87605:127676451\tQ-min: 2.075\tQ-max: 2.162\tLives: 4\tReward: 25.0\tEpisode Mean: 161.9\n",
+      "87605:127676475\tQ-min: -0.099\tQ-max: 0.215\tLives: 3\tReward: 25.0\tEpisode Mean: 161.9\n",
+      "87605:127676530\tQ-min: 1.829\tQ-max: 1.890\tLives: 3\tReward: 29.0\tEpisode Mean: 161.9\n",
+      "87605:127676595\tQ-min: 1.862\tQ-max: 1.896\tLives: 3\tReward: 30.0\tEpisode Mean: 161.9\n",
+      "87605:127676649\tQ-min: 1.995\tQ-max: 2.130\tLives: 3\tReward: 31.0\tEpisode Mean: 161.9\n",
+      "87605:127676685\tQ-min: 2.184\tQ-max: 2.242\tLives: 3\tReward: 32.0\tEpisode Mean: 161.9\n",
+      "87605:127676718\tQ-min: 2.100\tQ-max: 2.182\tLives: 3\tReward: 33.0\tEpisode Mean: 161.9\n",
+      "87605:127676752\tQ-min: 2.150\tQ-max: 2.231\tLives: 3\tReward: 34.0\tEpisode Mean: 161.9\n",
+      "87605:127676785\tQ-min: 2.192\tQ-max: 2.229\tLives: 3\tReward: 35.0\tEpisode Mean: 161.9\n",
+      "87605:127676836\tQ-min: 1.745\tQ-max: 1.770\tLives: 3\tReward: 36.0\tEpisode Mean: 161.9\n",
+      "87605:127676902\tQ-min: 1.591\tQ-max: 1.756\tLives: 3\tReward: 37.0\tEpisode Mean: 161.9\n",
+      "87605:127676973\tQ-min: 1.822\tQ-max: 1.921\tLives: 3\tReward: 41.0\tEpisode Mean: 161.9\n",
+      "87605:127677046\tQ-min: 1.600\tQ-max: 2.286\tLives: 3\tReward: 45.0\tEpisode Mean: 161.9\n",
+      "87605:127677099\tQ-min: 2.053\tQ-max: 2.102\tLives: 3\tReward: 46.0\tEpisode Mean: 161.9\n",
+      "87605:127677134\tQ-min: 2.109\tQ-max: 2.140\tLives: 3\tReward: 47.0\tEpisode Mean: 161.9\n",
+      "87605:127677167\tQ-min: 2.327\tQ-max: 2.429\tLives: 3\tReward: 51.0\tEpisode Mean: 161.9\n",
+      "87605:127677189\tQ-min: -0.038\tQ-max: 0.213\tLives: 2\tReward: 51.0\tEpisode Mean: 161.9\n",
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+      "87605:127677280\tQ-min: 2.027\tQ-max: 2.063\tLives: 2\tReward: 53.0\tEpisode Mean: 161.9\n",
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+      "87605:127677362\tQ-min: 2.116\tQ-max: 2.305\tLives: 2\tReward: 58.0\tEpisode Mean: 161.9\n",
+      "87605:127677399\tQ-min: 2.268\tQ-max: 2.319\tLives: 2\tReward: 62.0\tEpisode Mean: 161.9\n",
+      "87605:127677433\tQ-min: 2.207\tQ-max: 2.433\tLives: 2\tReward: 66.0\tEpisode Mean: 161.9\n",
+      "87605:127677453\tQ-min: 2.363\tQ-max: 2.507\tLives: 2\tReward: 67.0\tEpisode Mean: 161.9\n",
+      "87605:127677474\tQ-min: 2.441\tQ-max: 2.623\tLives: 2\tReward: 71.0\tEpisode Mean: 161.9\n",
+      "87605:127677487\tQ-min: 0.035\tQ-max: 0.164\tLives: 1\tReward: 71.0\tEpisode Mean: 161.9\n",
+      "87605:127677533\tQ-min: 2.462\tQ-max: 2.580\tLives: 1\tReward: 75.0\tEpisode Mean: 161.9\n",
+      "87605:127677558\tQ-min: 2.145\tQ-max: 2.673\tLives: 1\tReward: 82.0\tEpisode Mean: 161.9\n",
+      "87605:127677581\tQ-min: 2.687\tQ-max: 2.993\tLives: 1\tReward: 86.0\tEpisode Mean: 161.9\n",
+      "87605:127677602\tQ-min: 2.374\tQ-max: 2.936\tLives: 1\tReward: 90.0\tEpisode Mean: 161.9\n",
+      "87605:127677625\tQ-min: 2.129\tQ-max: 2.879\tLives: 1\tReward: 97.0\tEpisode Mean: 161.9\n",
+      "87605:127677647\tQ-min: 2.395\tQ-max: 2.794\tLives: 1\tReward: 101.0\tEpisode Mean: 161.9\n",
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+      "87606:127677716\tQ-min: 1.678\tQ-max: 1.684\tLives: 5\tReward: 1.0\tEpisode Mean: 158.6\n",
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+      "87606:127678056\tQ-min: 1.690\tQ-max: 1.730\tLives: 5\tReward: 9.0\tEpisode Mean: 158.6\n",
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+      "87606:127678186\tQ-min: 1.940\tQ-max: 1.950\tLives: 4\tReward: 11.0\tEpisode Mean: 158.6\n",
+      "87606:127678243\tQ-min: 1.645\tQ-max: 1.722\tLives: 4\tReward: 12.0\tEpisode Mean: 158.6\n",
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+      "87606:127678321\tQ-min: 1.960\tQ-max: 1.993\tLives: 4\tReward: 14.0\tEpisode Mean: 158.6\n",
+      "87606:127678357\tQ-min: 2.025\tQ-max: 2.069\tLives: 4\tReward: 18.0\tEpisode Mean: 158.6\n",
+      "87606:127678393\tQ-min: 1.958\tQ-max: 2.482\tLives: 4\tReward: 22.0\tEpisode Mean: 158.6\n",
+      "87606:127678413\tQ-min: 2.310\tQ-max: 2.430\tLives: 4\tReward: 23.0\tEpisode Mean: 158.6\n",
+      "87606:127678436\tQ-min: 2.148\tQ-max: 2.430\tLives: 4\tReward: 27.0\tEpisode Mean: 158.6\n",
+      "87606:127678449\tQ-min: -0.273\tQ-max: 0.286\tLives: 3\tReward: 27.0\tEpisode Mean: 158.6\n",
+      "87606:127678495\tQ-min: 1.984\tQ-max: 2.000\tLives: 3\tReward: 28.0\tEpisode Mean: 158.6\n",
+      "87606:127678538\tQ-min: 2.054\tQ-max: 2.119\tLives: 3\tReward: 29.0\tEpisode Mean: 158.6\n",
+      "87606:127678592\tQ-min: 1.758\tQ-max: 1.815\tLives: 3\tReward: 30.0\tEpisode Mean: 158.6\n",
+      "87606:127678635\tQ-min: -0.036\tQ-max: 0.414\tLives: 2\tReward: 30.0\tEpisode Mean: 158.6\n",
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+      "87606:127678793\tQ-min: 1.934\tQ-max: 1.967\tLives: 2\tReward: 33.0\tEpisode Mean: 158.6\n",
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+      "87606:127678933\tQ-min: 2.284\tQ-max: 2.330\tLives: 2\tReward: 37.0\tEpisode Mean: 158.6\n",
+      "87606:127678983\tQ-min: 1.702\tQ-max: 1.807\tLives: 2\tReward: 38.0\tEpisode Mean: 158.6\n",
+      "87606:127679049\tQ-min: 1.585\tQ-max: 1.716\tLives: 2\tReward: 42.0\tEpisode Mean: 158.6\n",
+      "87606:127679097\tQ-min: -0.064\tQ-max: 0.265\tLives: 1\tReward: 42.0\tEpisode Mean: 158.6\n",
+      "87606:127679155\tQ-min: 1.777\tQ-max: 1.864\tLives: 1\tReward: 46.0\tEpisode Mean: 158.6\n",
+      "87606:127679215\tQ-min: 2.128\tQ-max: 2.154\tLives: 1\tReward: 47.0\tEpisode Mean: 158.6\n",
+      "87606:127679261\tQ-min: 2.095\tQ-max: 2.386\tLives: 1\tReward: 51.0\tEpisode Mean: 158.6\n",
+      "87606:127679301\tQ-min: 2.240\tQ-max: 2.281\tLives: 1\tReward: 52.0\tEpisode Mean: 158.6\n",
+      "87606:127679336\tQ-min: 2.182\tQ-max: 2.221\tLives: 1\tReward: 53.0\tEpisode Mean: 158.6\n",
+      "87606:127679371\tQ-min: 2.146\tQ-max: 2.200\tLives: 1\tReward: 57.0\tEpisode Mean: 158.6\n",
+      "87606:127679403\tQ-min: 2.166\tQ-max: 2.235\tLives: 1\tReward: 58.0\tEpisode Mean: 158.6\n",
+      "87606:127679452\tQ-min: 1.818\tQ-max: 1.949\tLives: 1\tReward: 59.0\tEpisode Mean: 158.6\n",
+      "87606:127679521\tQ-min: 1.925\tQ-max: 2.035\tLives: 1\tReward: 60.0\tEpisode Mean: 158.6\n",
+      "87606:127679585\tQ-min: 1.918\tQ-max: 2.098\tLives: 1\tReward: 64.0\tEpisode Mean: 158.6\n",
+      "87606:127679662\tQ-min: 1.814\tQ-max: 2.746\tLives: 1\tReward: 68.0\tEpisode Mean: 158.6\n",
+      "87606:127679687\tQ-min: 2.350\tQ-max: 2.740\tLives: 1\tReward: 72.0\tEpisode Mean: 158.6\n",
+      "87606:127679702\tQ-min: -0.177\tQ-max: 0.151\tLives: 0\tReward: 72.0\tEpisode Mean: 154.0\n",
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+      "87607:127679845\tQ-min: 1.796\tQ-max: 1.842\tLives: 5\tReward: 3.0\tEpisode Mean: 154.0\n",
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+      "87607:127679915\tQ-min: 1.970\tQ-max: 2.004\tLives: 5\tReward: 8.0\tEpisode Mean: 154.0\n",
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+      "87607:127679978\tQ-min: 1.781\tQ-max: 1.889\tLives: 5\tReward: 10.0\tEpisode Mean: 154.0\n",
+      "87607:127680025\tQ-min: 1.672\tQ-max: 1.699\tLives: 5\tReward: 11.0\tEpisode Mean: 154.0\n",
+      "87607:127680088\tQ-min: 1.748\tQ-max: 1.833\tLives: 5\tReward: 12.0\tEpisode Mean: 154.0\n",
+      "87607:127680154\tQ-min: 1.716\tQ-max: 1.752\tLives: 5\tReward: 13.0\tEpisode Mean: 154.0\n",
+      "87607:127680222\tQ-min: 1.707\tQ-max: 1.769\tLives: 5\tReward: 14.0\tEpisode Mean: 154.0\n",
+      "87607:127680274\tQ-min: 1.999\tQ-max: 2.047\tLives: 5\tReward: 15.0\tEpisode Mean: 154.0\n",
+      "87607:127680306\tQ-min: 2.011\tQ-max: 2.029\tLives: 5\tReward: 16.0\tEpisode Mean: 154.0\n",
+      "87607:127680328\tQ-min: -0.113\tQ-max: 0.253\tLives: 4\tReward: 16.0\tEpisode Mean: 154.0\n",
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+      "87607:127681064\tQ-min: 2.042\tQ-max: 2.128\tLives: 4\tReward: 42.0\tEpisode Mean: 154.0\n",
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+      "87607:127681135\tQ-min: 2.349\tQ-max: 2.475\tLives: 4\tReward: 47.0\tEpisode Mean: 154.0\n",
+      "87607:127681156\tQ-min: 2.286\tQ-max: 2.440\tLives: 4\tReward: 48.0\tEpisode Mean: 154.0\n",
+      "87607:127681171\tQ-min: 0.047\tQ-max: 0.248\tLives: 3\tReward: 48.0\tEpisode Mean: 154.0\n",
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+      "87607:127681276\tQ-min: 1.874\tQ-max: 2.028\tLives: 3\tReward: 53.0\tEpisode Mean: 154.0\n",
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+      "87607:127681408\tQ-min: 2.468\tQ-max: 2.547\tLives: 3\tReward: 59.0\tEpisode Mean: 154.0\n",
+      "87607:127681431\tQ-min: 2.280\tQ-max: 2.690\tLives: 3\tReward: 63.0\tEpisode Mean: 154.0\n",
+      "87607:127681453\tQ-min: 2.054\tQ-max: 2.563\tLives: 3\tReward: 67.0\tEpisode Mean: 154.0\n",
+      "87607:127681466\tQ-min: -0.662\tQ-max: 0.099\tLives: 2\tReward: 67.0\tEpisode Mean: 154.0\n",
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+      "87607:127681557\tQ-min: 2.152\tQ-max: 2.228\tLives: 2\tReward: 72.0\tEpisode Mean: 154.0\n",
+      "87607:127681615\tQ-min: 2.401\tQ-max: 2.595\tLives: 2\tReward: 76.0\tEpisode Mean: 154.0\n",
+      "87607:127681628\tQ-min: 0.216\tQ-max: 0.360\tLives: 1\tReward: 76.0\tEpisode Mean: 154.0\n",
+      "87607:127681673\tQ-min: 2.201\tQ-max: 2.312\tLives: 1\tReward: 80.0\tEpisode Mean: 154.0\n",
+      "87607:127681716\tQ-min: 2.240\tQ-max: 2.314\tLives: 1\tReward: 81.0\tEpisode Mean: 154.0\n",
+      "87607:127681758\tQ-min: 2.284\tQ-max: 2.382\tLives: 1\tReward: 82.0\tEpisode Mean: 154.0\n",
+      "87607:127681799\tQ-min: 2.332\tQ-max: 2.451\tLives: 1\tReward: 86.0\tEpisode Mean: 154.0\n",
+      "87607:127681835\tQ-min: 2.389\tQ-max: 2.679\tLives: 1\tReward: 90.0\tEpisode Mean: 154.0\n",
+      "87607:127681848\tQ-min: -0.115\tQ-max: 0.157\tLives: 0\tReward: 90.0\tEpisode Mean: 150.8\n",
+      "87608:127681894\tQ-min: 1.754\tQ-max: 1.766\tLives: 5\tReward: 1.0\tEpisode Mean: 150.8\n",
+      "87608:127681946\tQ-min: 1.615\tQ-max: 1.667\tLives: 5\tReward: 2.0\tEpisode Mean: 150.8\n",
+      "87608:127681999\tQ-min: 1.888\tQ-max: 1.900\tLives: 5\tReward: 3.0\tEpisode Mean: 150.8\n",
+      "87608:127682034\tQ-min: 1.989\tQ-max: 2.028\tLives: 5\tReward: 4.0\tEpisode Mean: 150.8\n",
+      "87608:127682066\tQ-min: 1.922\tQ-max: 1.962\tLives: 5\tReward: 5.0\tEpisode Mean: 150.8\n",
+      "87608:127682098\tQ-min: 1.921\tQ-max: 1.948\tLives: 5\tReward: 6.0\tEpisode Mean: 150.8\n",
+      "87608:127682132\tQ-min: 1.779\tQ-max: 1.816\tLives: 5\tReward: 7.0\tEpisode Mean: 150.8\n",
+      "87608:127682184\tQ-min: 1.663\tQ-max: 1.689\tLives: 5\tReward: 8.0\tEpisode Mean: 150.8\n",
+      "87608:127682253\tQ-min: 1.671\tQ-max: 1.748\tLives: 5\tReward: 9.0\tEpisode Mean: 150.8\n",
+      "87608:127682311\tQ-min: 1.656\tQ-max: 1.672\tLives: 5\tReward: 10.0\tEpisode Mean: 150.8\n",
+      "87608:127682374\tQ-min: 1.611\tQ-max: 1.666\tLives: 5\tReward: 11.0\tEpisode Mean: 150.8\n",
+      "87608:127682420\tQ-min: 1.993\tQ-max: 2.024\tLives: 5\tReward: 12.0\tEpisode Mean: 150.8\n",
+      "87608:127682452\tQ-min: 1.965\tQ-max: 2.005\tLives: 5\tReward: 13.0\tEpisode Mean: 150.8\n",
+      "87608:127682486\tQ-min: 1.916\tQ-max: 2.050\tLives: 5\tReward: 14.0\tEpisode Mean: 150.8\n",
+      "87608:127682517\tQ-min: 1.985\tQ-max: 2.014\tLives: 5\tReward: 15.0\tEpisode Mean: 150.8\n",
+      "87608:127682549\tQ-min: 1.885\tQ-max: 1.936\tLives: 5\tReward: 19.0\tEpisode Mean: 150.8\n",
+      "87608:127682585\tQ-min: 1.965\tQ-max: 1.990\tLives: 5\tReward: 23.0\tEpisode Mean: 150.8\n",
+      "87608:127682620\tQ-min: 2.079\tQ-max: 2.127\tLives: 5\tReward: 24.0\tEpisode Mean: 150.8\n",
+      "87608:127682653\tQ-min: 2.049\tQ-max: 2.104\tLives: 5\tReward: 25.0\tEpisode Mean: 150.8\n",
+      "87608:127682685\tQ-min: 2.052\tQ-max: 2.088\tLives: 5\tReward: 26.0\tEpisode Mean: 150.8\n",
+      "87608:127682717\tQ-min: 2.025\tQ-max: 2.052\tLives: 5\tReward: 27.0\tEpisode Mean: 150.8\n",
+      "87608:127682748\tQ-min: 2.003\tQ-max: 2.024\tLives: 5\tReward: 28.0\tEpisode Mean: 150.8\n",
+      "87608:127682782\tQ-min: 2.108\tQ-max: 2.209\tLives: 5\tReward: 32.0\tEpisode Mean: 150.8\n",
+      "87608:127682818\tQ-min: 2.094\tQ-max: 2.108\tLives: 5\tReward: 33.0\tEpisode Mean: 150.8\n",
+      "87608:127682849\tQ-min: 2.079\tQ-max: 2.142\tLives: 5\tReward: 34.0\tEpisode Mean: 150.8\n",
+      "87608:127682881\tQ-min: 2.000\tQ-max: 2.105\tLives: 5\tReward: 35.0\tEpisode Mean: 150.8\n",
+      "87608:127682916\tQ-min: 2.170\tQ-max: 2.207\tLives: 5\tReward: 36.0\tEpisode Mean: 150.8\n",
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+      "87608:127683033\tQ-min: 2.332\tQ-max: 2.442\tLives: 5\tReward: 50.0\tEpisode Mean: 150.8\n",
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+      "87608:127683078\tQ-min: 1.800\tQ-max: 2.672\tLives: 5\tReward: 58.0\tEpisode Mean: 150.8\n",
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+      "87608:127683162\tQ-min: 2.416\tQ-max: 2.487\tLives: 4\tReward: 63.0\tEpisode Mean: 150.8\n",
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+      "87608:127683244\tQ-min: 2.376\tQ-max: 2.586\tLives: 3\tReward: 71.0\tEpisode Mean: 150.8\n",
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+      "87608:127683330\tQ-min: 2.334\tQ-max: 2.649\tLives: 2\tReward: 82.0\tEpisode Mean: 150.8\n",
+      "87608:127683350\tQ-min: 2.408\tQ-max: 2.508\tLives: 2\tReward: 83.0\tEpisode Mean: 150.8\n",
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+      "87608:127683959\tQ-min: 2.963\tQ-max: 5.873\tLives: 1\tReward: 143.0\tEpisode Mean: 150.8\n",
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+      "87608:127683994\tQ-min: 2.415\tQ-max: 4.049\tLives: 1\tReward: 154.0\tEpisode Mean: 150.8\n",
+      "87608:127684008\tQ-min: -0.035\tQ-max: 0.309\tLives: 0\tReward: 154.0\tEpisode Mean: 151.0\n",
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+      "87609:127684360\tQ-min: 1.695\tQ-max: 1.724\tLives: 5\tReward: 11.0\tEpisode Mean: 151.0\n",
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+      "87609:127684484\tQ-min: 1.606\tQ-max: 1.772\tLives: 5\tReward: 13.0\tEpisode Mean: 151.0\n",
+      "87609:127684549\tQ-min: 1.759\tQ-max: 1.908\tLives: 5\tReward: 14.0\tEpisode Mean: 151.0\n",
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+      "87609:127684726\tQ-min: 2.015\tQ-max: 2.051\tLives: 5\tReward: 19.0\tEpisode Mean: 151.0\n",
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+      "87609:127684788\tQ-min: 1.963\tQ-max: 2.037\tLives: 5\tReward: 21.0\tEpisode Mean: 151.0\n",
+      "87609:127684823\tQ-min: 2.093\tQ-max: 2.138\tLives: 5\tReward: 22.0\tEpisode Mean: 151.0\n",
+      "87609:127684846\tQ-min: -0.186\tQ-max: 0.232\tLives: 4\tReward: 22.0\tEpisode Mean: 151.0\n",
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+      "87609:127685033\tQ-min: 0.000\tQ-max: 0.368\tLives: 3\tReward: 29.0\tEpisode Mean: 151.0\n",
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+      "87609:127685123\tQ-min: 1.812\tQ-max: 3.201\tLives: 3\tReward: 47.0\tEpisode Mean: 151.0\n",
+      "87609:127685140\tQ-min: -0.555\tQ-max: 0.613\tLives: 2\tReward: 47.0\tEpisode Mean: 151.0\n",
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+      "87609:127685357\tQ-min: 2.606\tQ-max: 2.748\tLives: 2\tReward: 61.0\tEpisode Mean: 151.0\n",
+      "87609:127685377\tQ-min: 2.519\tQ-max: 3.619\tLives: 2\tReward: 62.0\tEpisode Mean: 151.0\n",
+      "87609:127685389\tQ-min: 0.083\tQ-max: 0.184\tLives: 1\tReward: 62.0\tEpisode Mean: 151.0\n",
+      "87609:127685436\tQ-min: 2.103\tQ-max: 2.290\tLives: 1\tReward: 63.0\tEpisode Mean: 151.0\n",
+      "87609:127685494\tQ-min: 1.586\tQ-max: 3.198\tLives: 1\tReward: 70.0\tEpisode Mean: 151.0\n",
+      "87609:127685515\tQ-min: 2.646\tQ-max: 2.753\tLives: 1\tReward: 71.0\tEpisode Mean: 151.0\n",
+      "87609:127685529\tQ-min: -0.298\tQ-max: 0.219\tLives: 0\tReward: 71.0\tEpisode Mean: 147.3\n",
+      "87610:127685572\tQ-min: 1.771\tQ-max: 1.787\tLives: 5\tReward: 1.0\tEpisode Mean: 147.3\n",
+      "87610:127685612\tQ-min: 1.795\tQ-max: 1.833\tLives: 5\tReward: 2.0\tEpisode Mean: 147.3\n",
+      "87610:127685653\tQ-min: 1.886\tQ-max: 1.906\tLives: 5\tReward: 3.0\tEpisode Mean: 147.3\n",
+      "87610:127685684\tQ-min: -0.097\tQ-max: 0.119\tLives: 4\tReward: 3.0\tEpisode Mean: 147.3\n",
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+      "87610:127686270\tQ-min: 2.048\tQ-max: 2.107\tLives: 3\tReward: 26.0\tEpisode Mean: 147.3\n",
+      "87610:127686319\tQ-min: 1.779\tQ-max: 1.806\tLives: 3\tReward: 27.0\tEpisode Mean: 147.3\n",
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+      "87610:127686441\tQ-min: 1.784\tQ-max: 1.854\tLives: 3\tReward: 29.0\tEpisode Mean: 147.3\n",
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+      "87610:127686552\tQ-min: 2.130\tQ-max: 2.151\tLives: 3\tReward: 31.0\tEpisode Mean: 147.3\n",
+      "87610:127686586\tQ-min: 2.020\tQ-max: 2.132\tLives: 3\tReward: 35.0\tEpisode Mean: 147.3\n",
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+      "87610:127686653\tQ-min: 2.146\tQ-max: 2.168\tLives: 3\tReward: 40.0\tEpisode Mean: 147.3\n",
+      "87610:127686688\tQ-min: 2.089\tQ-max: 2.103\tLives: 3\tReward: 41.0\tEpisode Mean: 147.3\n",
+      "87610:127686722\tQ-min: 2.044\tQ-max: 2.106\tLives: 3\tReward: 42.0\tEpisode Mean: 147.3\n",
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+      "87610:127686778\tQ-min: 2.339\tQ-max: 2.568\tLives: 3\tReward: 47.0\tEpisode Mean: 147.3\n",
+      "87610:127686793\tQ-min: -0.078\tQ-max: 0.390\tLives: 2\tReward: 47.0\tEpisode Mean: 147.3\n",
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+      "87610:127686864\tQ-min: 2.580\tQ-max: 2.685\tLives: 2\tReward: 55.0\tEpisode Mean: 147.3\n",
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+      "87610:127686902\tQ-min: 2.405\tQ-max: 2.642\tLives: 2\tReward: 57.0\tEpisode Mean: 147.3\n",
+      "87610:127686922\tQ-min: 2.280\tQ-max: 2.503\tLives: 2\tReward: 58.0\tEpisode Mean: 147.3\n",
+      "87610:127686941\tQ-min: 2.468\tQ-max: 2.574\tLives: 2\tReward: 62.0\tEpisode Mean: 147.3\n",
+      "87610:127686962\tQ-min: 2.408\tQ-max: 2.591\tLives: 2\tReward: 66.0\tEpisode Mean: 147.3\n",
+      "87610:127686985\tQ-min: 2.310\tQ-max: 2.628\tLives: 2\tReward: 70.0\tEpisode Mean: 147.3\n",
+      "87610:127687008\tQ-min: 2.512\tQ-max: 2.766\tLives: 2\tReward: 74.0\tEpisode Mean: 147.3\n",
+      "87610:127687030\tQ-min: 2.183\tQ-max: 2.847\tLives: 2\tReward: 78.0\tEpisode Mean: 147.3\n",
+      "87610:127687043\tQ-min: 0.031\tQ-max: 0.250\tLives: 1\tReward: 78.0\tEpisode Mean: 147.3\n",
+      "87610:127687082\tQ-min: 2.263\tQ-max: 2.332\tLives: 1\tReward: 79.0\tEpisode Mean: 147.3\n",
+      "87610:127687134\tQ-min: 2.101\tQ-max: 2.186\tLives: 1\tReward: 80.0\tEpisode Mean: 147.3\n",
+      "87610:127687203\tQ-min: 2.399\tQ-max: 2.755\tLives: 1\tReward: 84.0\tEpisode Mean: 147.3\n",
+      "87610:127687217\tQ-min: 0.028\tQ-max: 0.155\tLives: 0\tReward: 84.0\tEpisode Mean: 144.6\n",
+      "87611:127687262\tQ-min: 1.731\tQ-max: 1.745\tLives: 5\tReward: 1.0\tEpisode Mean: 144.6\n",
+      "87611:127687313\tQ-min: 1.651\tQ-max: 1.690\tLives: 5\tReward: 2.0\tEpisode Mean: 144.6\n",
+      "87611:127687367\tQ-min: 1.864\tQ-max: 1.887\tLives: 5\tReward: 3.0\tEpisode Mean: 144.6\n",
+      "87611:127687403\tQ-min: 1.930\tQ-max: 1.957\tLives: 5\tReward: 4.0\tEpisode Mean: 144.6\n",
+      "87611:127687433\tQ-min: 1.943\tQ-max: 1.969\tLives: 5\tReward: 5.0\tEpisode Mean: 144.6\n",
+      "87611:127687467\tQ-min: 1.962\tQ-max: 1.975\tLives: 5\tReward: 6.0\tEpisode Mean: 144.6\n",
+      "87611:127687500\tQ-min: 1.687\tQ-max: 1.752\tLives: 5\tReward: 7.0\tEpisode Mean: 144.6\n",
+      "87611:127687549\tQ-min: 1.655\tQ-max: 1.674\tLives: 5\tReward: 8.0\tEpisode Mean: 144.6\n",
+      "87611:127687613\tQ-min: 1.662\tQ-max: 1.678\tLives: 5\tReward: 9.0\tEpisode Mean: 144.6\n",
+      "87611:127687651\tQ-min: -0.105\tQ-max: 0.128\tLives: 4\tReward: 9.0\tEpisode Mean: 144.6\n",
+      "87611:127687705\tQ-min: 1.583\tQ-max: 1.631\tLives: 4\tReward: 10.0\tEpisode Mean: 144.6\n",
+      "87611:127687773\tQ-min: 1.727\tQ-max: 1.743\tLives: 4\tReward: 11.0\tEpisode Mean: 144.6\n",
+      "87611:127687828\tQ-min: 1.937\tQ-max: 1.957\tLives: 4\tReward: 12.0\tEpisode Mean: 144.6\n",
+      "87611:127687864\tQ-min: 1.992\tQ-max: 2.010\tLives: 4\tReward: 13.0\tEpisode Mean: 144.6\n",
+      "87611:127687897\tQ-min: 1.985\tQ-max: 2.009\tLives: 4\tReward: 14.0\tEpisode Mean: 144.6\n",
+      "87611:127687937\tQ-min: 2.044\tQ-max: 2.064\tLives: 4\tReward: 18.0\tEpisode Mean: 144.6\n",
+      "87611:127687970\tQ-min: 2.033\tQ-max: 2.052\tLives: 4\tReward: 19.0\tEpisode Mean: 144.6\n",
+      "87611:127688019\tQ-min: 1.712\tQ-max: 1.740\tLives: 4\tReward: 20.0\tEpisode Mean: 144.6\n",
+      "87611:127688085\tQ-min: 1.721\tQ-max: 1.762\tLives: 4\tReward: 21.0\tEpisode Mean: 144.6\n",
+      "87611:127688149\tQ-min: 1.650\tQ-max: 1.725\tLives: 4\tReward: 22.0\tEpisode Mean: 144.6\n",
+      "87611:127688214\tQ-min: 1.663\tQ-max: 1.756\tLives: 4\tReward: 23.0\tEpisode Mean: 144.6\n",
+      "87611:127688263\tQ-min: 2.057\tQ-max: 2.084\tLives: 4\tReward: 24.0\tEpisode Mean: 144.6\n",
+      "87611:127688299\tQ-min: 1.769\tQ-max: 1.903\tLives: 4\tReward: 28.0\tEpisode Mean: 144.6\n",
+      "87611:127688335\tQ-min: 2.005\tQ-max: 2.049\tLives: 4\tReward: 29.0\tEpisode Mean: 144.6\n",
+      "87611:127688367\tQ-min: 2.091\tQ-max: 2.151\tLives: 4\tReward: 30.0\tEpisode Mean: 144.6\n",
+      "87611:127688399\tQ-min: 2.170\tQ-max: 2.212\tLives: 4\tReward: 31.0\tEpisode Mean: 144.6\n",
+      "87611:127688431\tQ-min: 2.025\tQ-max: 2.069\tLives: 4\tReward: 32.0\tEpisode Mean: 144.6\n",
+      "87611:127688465\tQ-min: 1.990\tQ-max: 2.026\tLives: 4\tReward: 33.0\tEpisode Mean: 144.6\n",
+      "87611:127688500\tQ-min: 2.126\tQ-max: 2.194\tLives: 4\tReward: 37.0\tEpisode Mean: 144.6\n",
+      "87611:127688519\tQ-min: 0.121\tQ-max: 0.461\tLives: 3\tReward: 37.0\tEpisode Mean: 144.6\n",
+      "87611:127688552\tQ-min: 0.028\tQ-max: 0.190\tLives: 2\tReward: 37.0\tEpisode Mean: 144.6\n",
+      "87611:127688599\tQ-min: 1.996\tQ-max: 2.115\tLives: 2\tReward: 41.0\tEpisode Mean: 144.6\n",
+      "87611:127688647\tQ-min: 2.269\tQ-max: 2.482\tLives: 2\tReward: 45.0\tEpisode Mean: 144.6\n",
+      "87611:127688661\tQ-min: -0.118\tQ-max: 0.097\tLives: 1\tReward: 45.0\tEpisode Mean: 144.6\n",
+      "87611:127688708\tQ-min: 2.254\tQ-max: 2.884\tLives: 1\tReward: 52.0\tEpisode Mean: 144.6\n",
+      "87611:127688732\tQ-min: 2.380\tQ-max: 2.510\tLives: 1\tReward: 53.0\tEpisode Mean: 144.6\n",
+      "87611:127688751\tQ-min: 2.509\tQ-max: 2.535\tLives: 1\tReward: 54.0\tEpisode Mean: 144.6\n",
+      "87611:127688773\tQ-min: 2.214\tQ-max: 2.313\tLives: 1\tReward: 55.0\tEpisode Mean: 144.6\n",
+      "87611:127688784\tQ-min: -0.137\tQ-max: -0.064\tLives: 0\tReward: 55.0\tEpisode Mean: 140.8\n",
+      "87612:127688825\tQ-min: 1.743\tQ-max: 1.756\tLives: 5\tReward: 1.0\tEpisode Mean: 140.8\n",
+      "87612:127688868\tQ-min: 1.769\tQ-max: 1.795\tLives: 5\tReward: 2.0\tEpisode Mean: 140.8\n",
+      "87612:127688922\tQ-min: 1.657\tQ-max: 1.705\tLives: 5\tReward: 3.0\tEpisode Mean: 140.8\n",
+      "87612:127688973\tQ-min: 1.955\tQ-max: 1.978\tLives: 5\tReward: 4.0\tEpisode Mean: 140.8\n",
+      "87612:127689006\tQ-min: 1.986\tQ-max: 2.008\tLives: 5\tReward: 5.0\tEpisode Mean: 140.8\n",
+      "87612:127689035\tQ-min: 1.966\tQ-max: 1.974\tLives: 5\tReward: 6.0\tEpisode Mean: 140.8\n",
+      "87612:127689066\tQ-min: 1.749\tQ-max: 1.813\tLives: 5\tReward: 7.0\tEpisode Mean: 140.8\n",
+      "87612:127689111\tQ-min: 1.692\tQ-max: 1.708\tLives: 5\tReward: 8.0\tEpisode Mean: 140.8\n",
+      "87612:127689176\tQ-min: 1.702\tQ-max: 1.741\tLives: 5\tReward: 9.0\tEpisode Mean: 140.8\n",
+      "87612:127689241\tQ-min: 1.659\tQ-max: 1.676\tLives: 5\tReward: 10.0\tEpisode Mean: 140.8\n",
+      "87612:127689302\tQ-min: 1.630\tQ-max: 1.654\tLives: 5\tReward: 11.0\tEpisode Mean: 140.8\n",
+      "87612:127689355\tQ-min: 1.973\tQ-max: 2.007\tLives: 5\tReward: 12.0\tEpisode Mean: 140.8\n",
+      "87612:127689378\tQ-min: -0.112\tQ-max: 0.204\tLives: 4\tReward: 12.0\tEpisode Mean: 140.8\n",
+      "87612:127689419\tQ-min: 1.939\tQ-max: 1.980\tLives: 4\tReward: 13.0\tEpisode Mean: 140.8\n",
+      "87612:127689465\tQ-min: 1.912\tQ-max: 1.950\tLives: 4\tReward: 14.0\tEpisode Mean: 140.8\n",
+      "87612:127689522\tQ-min: 1.673\tQ-max: 1.718\tLives: 4\tReward: 15.0\tEpisode Mean: 140.8\n",
+      "87612:127689570\tQ-min: 1.962\tQ-max: 1.988\tLives: 4\tReward: 16.0\tEpisode Mean: 140.8\n",
+      "87612:127689603\tQ-min: 2.014\tQ-max: 2.075\tLives: 4\tReward: 20.0\tEpisode Mean: 140.8\n",
+      "87612:127689627\tQ-min: -0.091\tQ-max: 0.199\tLives: 3\tReward: 20.0\tEpisode Mean: 140.8\n",
+      "87612:127689682\tQ-min: 1.711\tQ-max: 1.726\tLives: 3\tReward: 21.0\tEpisode Mean: 140.8\n",
+      "87612:127689724\tQ-min: -0.040\tQ-max: 0.209\tLives: 2\tReward: 21.0\tEpisode Mean: 140.8\n",
+      "87612:127689767\tQ-min: 1.848\tQ-max: 1.880\tLives: 2\tReward: 22.0\tEpisode Mean: 140.8\n",
+      "87612:127689811\tQ-min: 1.961\tQ-max: 1.978\tLives: 2\tReward: 23.0\tEpisode Mean: 140.8\n",
+      "87612:127689853\tQ-min: 1.906\tQ-max: 1.925\tLives: 2\tReward: 24.0\tEpisode Mean: 140.8\n",
+      "87612:127689894\tQ-min: 2.037\tQ-max: 2.090\tLives: 2\tReward: 28.0\tEpisode Mean: 140.8\n",
+      "87612:127689933\tQ-min: 2.121\tQ-max: 2.210\tLives: 2\tReward: 32.0\tEpisode Mean: 140.8\n",
+      "87612:127689973\tQ-min: 2.198\tQ-max: 2.401\tLives: 2\tReward: 36.0\tEpisode Mean: 140.8\n",
+      "87612:127689995\tQ-min: 2.288\tQ-max: 2.436\tLives: 2\tReward: 37.0\tEpisode Mean: 140.8\n",
+      "87612:127690009\tQ-min: -0.031\tQ-max: 0.069\tLives: 1\tReward: 37.0\tEpisode Mean: 140.8\n",
+      "87612:127690057\tQ-min: 2.013\tQ-max: 2.063\tLives: 1\tReward: 38.0\tEpisode Mean: 140.8\n",
+      "87612:127690116\tQ-min: 1.884\tQ-max: 1.909\tLives: 1\tReward: 39.0\tEpisode Mean: 140.8\n",
+      "87612:127690174\tQ-min: 2.133\tQ-max: 2.171\tLives: 1\tReward: 40.0\tEpisode Mean: 140.8\n",
+      "87612:127690200\tQ-min: -0.037\tQ-max: 0.172\tLives: 0\tReward: 40.0\tEpisode Mean: 136.8\n",
+      "87613:127690252\tQ-min: 1.621\tQ-max: 1.693\tLives: 5\tReward: 1.0\tEpisode Mean: 136.8\n",
+      "87613:127690315\tQ-min: 1.643\tQ-max: 1.659\tLives: 5\tReward: 2.0\tEpisode Mean: 136.8\n",
+      "87613:127690366\tQ-min: 1.864\tQ-max: 1.898\tLives: 5\tReward: 3.0\tEpisode Mean: 136.8\n",
+      "87613:127690401\tQ-min: 1.925\tQ-max: 1.938\tLives: 5\tReward: 4.0\tEpisode Mean: 136.8\n",
+      "87613:127690435\tQ-min: 1.933\tQ-max: 1.949\tLives: 5\tReward: 5.0\tEpisode Mean: 136.8\n",
+      "87613:127690469\tQ-min: 1.935\tQ-max: 1.977\tLives: 5\tReward: 9.0\tEpisode Mean: 136.8\n",
+      "87613:127690504\tQ-min: 2.179\tQ-max: 2.305\tLives: 5\tReward: 13.0\tEpisode Mean: 136.8\n",
+      "87613:127690525\tQ-min: 2.128\tQ-max: 2.241\tLives: 5\tReward: 14.0\tEpisode Mean: 136.8\n",
+      "87613:127690545\tQ-min: 1.717\tQ-max: 2.213\tLives: 5\tReward: 15.0\tEpisode Mean: 136.8\n",
+      "87613:127690565\tQ-min: 2.135\tQ-max: 2.274\tLives: 5\tReward: 16.0\tEpisode Mean: 136.8\n",
+      "87613:127690585\tQ-min: 2.200\tQ-max: 2.348\tLives: 5\tReward: 17.0\tEpisode Mean: 136.8\n",
+      "87613:127690605\tQ-min: 2.118\tQ-max: 2.305\tLives: 5\tReward: 18.0\tEpisode Mean: 136.8\n",
+      "87613:127690627\tQ-min: 2.129\tQ-max: 2.312\tLives: 5\tReward: 19.0\tEpisode Mean: 136.8\n",
+      "87613:127690641\tQ-min: 0.014\tQ-max: 0.224\tLives: 4\tReward: 19.0\tEpisode Mean: 136.8\n",
+      "87613:127690695\tQ-min: 1.714\tQ-max: 1.727\tLives: 4\tReward: 20.0\tEpisode Mean: 136.8\n",
+      "87613:127690750\tQ-min: 2.040\tQ-max: 2.111\tLives: 4\tReward: 21.0\tEpisode Mean: 136.8\n",
+      "87613:127690792\tQ-min: 2.043\tQ-max: 2.105\tLives: 4\tReward: 22.0\tEpisode Mean: 136.8\n",
+      "87613:127690828\tQ-min: 2.116\tQ-max: 2.167\tLives: 4\tReward: 23.0\tEpisode Mean: 136.8\n",
+      "87613:127690860\tQ-min: 2.157\tQ-max: 2.172\tLives: 4\tReward: 24.0\tEpisode Mean: 136.8\n",
+      "87613:127690893\tQ-min: 2.138\tQ-max: 2.167\tLives: 4\tReward: 28.0\tEpisode Mean: 136.8\n",
+      "87613:127690915\tQ-min: -0.427\tQ-max: 0.563\tLives: 3\tReward: 28.0\tEpisode Mean: 136.8\n",
+      "87613:127690960\tQ-min: 2.085\tQ-max: 2.117\tLives: 3\tReward: 29.0\tEpisode Mean: 136.8\n",
+      "87613:127691006\tQ-min: 2.026\tQ-max: 2.062\tLives: 3\tReward: 30.0\tEpisode Mean: 136.8\n",
+      "87613:127691053\tQ-min: 1.836\tQ-max: 2.660\tLives: 3\tReward: 34.0\tEpisode Mean: 136.8\n",
+      "87613:127691075\tQ-min: 2.278\tQ-max: 2.366\tLives: 3\tReward: 38.0\tEpisode Mean: 136.8\n",
+      "87613:127691089\tQ-min: -0.006\tQ-max: 0.138\tLives: 2\tReward: 38.0\tEpisode Mean: 136.8\n",
+      "87613:127691129\tQ-min: 1.988\tQ-max: 2.011\tLives: 2\tReward: 39.0\tEpisode Mean: 136.8\n",
+      "87613:127691170\tQ-min: 2.044\tQ-max: 2.122\tLives: 2\tReward: 40.0\tEpisode Mean: 136.8\n",
+      "87613:127691224\tQ-min: 1.812\tQ-max: 1.864\tLives: 2\tReward: 41.0\tEpisode Mean: 136.8\n",
+      "87613:127691272\tQ-min: 2.171\tQ-max: 2.215\tLives: 2\tReward: 42.0\tEpisode Mean: 136.8\n",
+      "87613:127691301\tQ-min: 2.344\tQ-max: 2.418\tLives: 2\tReward: 43.0\tEpisode Mean: 136.8\n",
+      "87613:127691334\tQ-min: 2.161\tQ-max: 2.215\tLives: 2\tReward: 44.0\tEpisode Mean: 136.8\n",
+      "87613:127691372\tQ-min: 2.097\tQ-max: 2.232\tLives: 2\tReward: 48.0\tEpisode Mean: 136.8\n",
+      "87613:127691422\tQ-min: 1.736\tQ-max: 1.760\tLives: 2\tReward: 49.0\tEpisode Mean: 136.8\n",
+      "87613:127691494\tQ-min: 1.720\tQ-max: 1.880\tLives: 2\tReward: 53.0\tEpisode Mean: 136.8\n",
+      "87613:127691560\tQ-min: 1.820\tQ-max: 1.934\tLives: 2\tReward: 54.0\tEpisode Mean: 136.8\n",
+      "87613:127691626\tQ-min: 1.752\tQ-max: 2.086\tLives: 2\tReward: 58.0\tEpisode Mean: 136.8\n",
+      "87613:127691676\tQ-min: 2.129\tQ-max: 2.214\tLives: 2\tReward: 59.0\tEpisode Mean: 136.8\n",
+      "87613:127691710\tQ-min: 2.299\tQ-max: 2.406\tLives: 2\tReward: 63.0\tEpisode Mean: 136.8\n",
+      "87613:127691745\tQ-min: 2.035\tQ-max: 2.164\tLives: 2\tReward: 64.0\tEpisode Mean: 136.8\n",
+      "87613:127691785\tQ-min: 2.293\tQ-max: 2.472\tLives: 2\tReward: 71.0\tEpisode Mean: 136.8\n",
+      "87613:127691808\tQ-min: 2.143\tQ-max: 2.440\tLives: 2\tReward: 75.0\tEpisode Mean: 136.8\n",
+      "87613:127691829\tQ-min: 1.921\tQ-max: 2.489\tLives: 2\tReward: 79.0\tEpisode Mean: 136.8\n",
+      "87613:127691841\tQ-min: 0.072\tQ-max: 0.313\tLives: 1\tReward: 79.0\tEpisode Mean: 136.8\n",
+      "87613:127691888\tQ-min: 2.163\tQ-max: 2.211\tLives: 1\tReward: 83.0\tEpisode Mean: 136.8\n",
+      "87613:127691932\tQ-min: 2.358\tQ-max: 2.504\tLives: 1\tReward: 84.0\tEpisode Mean: 136.8\n",
+      "87613:127691978\tQ-min: 2.047\tQ-max: 2.285\tLives: 1\tReward: 85.0\tEpisode Mean: 136.8\n",
+      "87613:127692017\tQ-min: 2.251\tQ-max: 2.327\tLives: 1\tReward: 86.0\tEpisode Mean: 136.8\n",
+      "87613:127692055\tQ-min: 2.361\tQ-max: 2.563\tLives: 1\tReward: 93.0\tEpisode Mean: 136.8\n",
+      "87613:127692078\tQ-min: 2.379\tQ-max: 2.775\tLives: 1\tReward: 97.0\tEpisode Mean: 136.8\n",
+      "87613:127692101\tQ-min: 2.345\tQ-max: 3.082\tLives: 1\tReward: 104.0\tEpisode Mean: 136.8\n",
+      "87613:127692125\tQ-min: 2.469\tQ-max: 3.301\tLives: 1\tReward: 111.0\tEpisode Mean: 136.8\n",
+      "87613:127692151\tQ-min: 2.195\tQ-max: 3.053\tLives: 1\tReward: 115.0\tEpisode Mean: 136.8\n",
+      "87613:127692174\tQ-min: 2.053\tQ-max: 5.052\tLives: 1\tReward: 122.0\tEpisode Mean: 136.8\n",
+      "87613:127692196\tQ-min: 3.218\tQ-max: 3.777\tLives: 1\tReward: 129.0\tEpisode Mean: 136.8\n",
+      "87613:127692225\tQ-min: 2.640\tQ-max: 7.819\tLives: 1\tReward: 136.0\tEpisode Mean: 136.8\n",
+      "87613:127692231\tQ-min: 3.148\tQ-max: 6.144\tLives: 1\tReward: 143.0\tEpisode Mean: 136.8\n",
+      "87613:127692236\tQ-min: 3.346\tQ-max: 6.952\tLives: 1\tReward: 150.0\tEpisode Mean: 136.8\n",
+      "87613:127692241\tQ-min: 3.525\tQ-max: 6.480\tLives: 1\tReward: 157.0\tEpisode Mean: 136.8\n",
+      "87613:127692245\tQ-min: 2.161\tQ-max: 6.309\tLives: 1\tReward: 164.0\tEpisode Mean: 136.8\n",
+      "87613:127692249\tQ-min: 3.869\tQ-max: 6.309\tLives: 1\tReward: 171.0\tEpisode Mean: 136.8\n",
+      "87613:127692253\tQ-min: 3.571\tQ-max: 5.777\tLives: 1\tReward: 178.0\tEpisode Mean: 136.8\n",
+      "87613:127692258\tQ-min: 3.166\tQ-max: 5.918\tLives: 1\tReward: 185.0\tEpisode Mean: 136.8\n",
+      "87613:127692262\tQ-min: 2.885\tQ-max: 5.234\tLives: 1\tReward: 192.0\tEpisode Mean: 136.8\n",
+      "87613:127692270\tQ-min: 2.900\tQ-max: 3.831\tLives: 1\tReward: 193.0\tEpisode Mean: 136.8\n",
+      "87613:127692278\tQ-min: 2.557\tQ-max: 5.713\tLives: 1\tReward: 200.0\tEpisode Mean: 136.8\n",
+      "87613:127692284\tQ-min: 4.380\tQ-max: 4.935\tLives: 1\tReward: 207.0\tEpisode Mean: 136.8\n",
+      "87613:127692320\tQ-min: 2.739\tQ-max: 5.609\tLives: 1\tReward: 214.0\tEpisode Mean: 136.8\n",
+      "87613:127692327\tQ-min: 3.526\tQ-max: 5.042\tLives: 1\tReward: 218.0\tEpisode Mean: 136.8\n",
+      "87613:127692334\tQ-min: 4.065\tQ-max: 5.043\tLives: 1\tReward: 225.0\tEpisode Mean: 136.8\n",
+      "87613:127692339\tQ-min: 1.078\tQ-max: 4.988\tLives: 1\tReward: 232.0\tEpisode Mean: 136.8\n",
+      "87613:127692343\tQ-min: 4.129\tQ-max: 5.668\tLives: 1\tReward: 239.0\tEpisode Mean: 136.8\n",
+      "87613:127692348\tQ-min: 3.897\tQ-max: 6.170\tLives: 1\tReward: 246.0\tEpisode Mean: 136.8\n",
+      "87613:127692355\tQ-min: 3.166\tQ-max: 5.217\tLives: 1\tReward: 253.0\tEpisode Mean: 136.8\n",
+      "87613:127692395\tQ-min: 2.545\tQ-max: 3.698\tLives: 1\tReward: 260.0\tEpisode Mean: 136.8\n",
+      "87613:127692402\tQ-min: 3.140\tQ-max: 4.613\tLives: 1\tReward: 267.0\tEpisode Mean: 136.8\n",
+      "87613:127692408\tQ-min: 2.794\tQ-max: 4.494\tLives: 1\tReward: 274.0\tEpisode Mean: 136.8\n",
+      "87613:127692414\tQ-min: 2.961\tQ-max: 4.157\tLives: 1\tReward: 278.0\tEpisode Mean: 136.8\n",
+      "87613:127692420\tQ-min: 2.604\tQ-max: 4.554\tLives: 1\tReward: 285.0\tEpisode Mean: 136.8\n",
+      "87613:127692427\tQ-min: 2.394\tQ-max: 4.361\tLives: 1\tReward: 292.0\tEpisode Mean: 136.8\n",
+      "87613:127692465\tQ-min: 2.877\tQ-max: 4.571\tLives: 1\tReward: 299.0\tEpisode Mean: 136.8\n",
+      "87613:127692485\tQ-min: -1.033\tQ-max: 0.680\tLives: 0\tReward: 299.0\tEpisode Mean: 143.0\n",
+      "87614:127692527\tQ-min: 1.766\tQ-max: 1.789\tLives: 5\tReward: 1.0\tEpisode Mean: 143.0\n",
+      "87614:127692565\tQ-min: 1.803\tQ-max: 1.843\tLives: 5\tReward: 2.0\tEpisode Mean: 143.0\n",
+      "87614:127692591\tQ-min: -0.225\tQ-max: 0.154\tLives: 4\tReward: 2.0\tEpisode Mean: 143.0\n",
+      "87614:127692638\tQ-min: 1.861\tQ-max: 1.883\tLives: 4\tReward: 3.0\tEpisode Mean: 143.0\n",
+      "87614:127692677\tQ-min: 1.971\tQ-max: 1.990\tLives: 4\tReward: 4.0\tEpisode Mean: 143.0\n",
+      "87614:127692719\tQ-min: 1.868\tQ-max: 1.902\tLives: 4\tReward: 5.0\tEpisode Mean: 143.0\n",
+      "87614:127692757\tQ-min: 1.970\tQ-max: 2.008\tLives: 4\tReward: 6.0\tEpisode Mean: 143.0\n",
+      "87614:127692789\tQ-min: 1.890\tQ-max: 1.911\tLives: 4\tReward: 7.0\tEpisode Mean: 143.0\n",
+      "87614:127692823\tQ-min: 1.920\tQ-max: 1.938\tLives: 4\tReward: 8.0\tEpisode Mean: 143.0\n",
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+      "87614:127693141\tQ-min: -0.065\tQ-max: 0.344\tLives: 3\tReward: 16.0\tEpisode Mean: 143.0\n",
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+      "87614:127693248\tQ-min: 1.985\tQ-max: 1.995\tLives: 3\tReward: 18.0\tEpisode Mean: 143.0\n",
+      "87614:127693305\tQ-min: 1.598\tQ-max: 1.688\tLives: 3\tReward: 19.0\tEpisode Mean: 143.0\n",
+      "87614:127693358\tQ-min: 1.962\tQ-max: 1.997\tLives: 3\tReward: 20.0\tEpisode Mean: 143.0\n",
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+      "87614:127693423\tQ-min: 2.144\tQ-max: 2.350\tLives: 3\tReward: 25.0\tEpisode Mean: 143.0\n",
+      "87614:127693444\tQ-min: 2.376\tQ-max: 2.448\tLives: 3\tReward: 26.0\tEpisode Mean: 143.0\n",
+      "87614:127693462\tQ-min: 2.332\tQ-max: 2.458\tLives: 3\tReward: 27.0\tEpisode Mean: 143.0\n",
+      "87614:127693483\tQ-min: 2.290\tQ-max: 2.491\tLives: 3\tReward: 28.0\tEpisode Mean: 143.0\n",
+      "87614:127693504\tQ-min: 2.354\tQ-max: 2.425\tLives: 3\tReward: 29.0\tEpisode Mean: 143.0\n",
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+      "87614:127693942\tQ-min: 2.223\tQ-max: 2.292\tLives: 2\tReward: 54.0\tEpisode Mean: 143.0\n",
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+      "87614:127694008\tQ-min: 2.152\tQ-max: 2.202\tLives: 1\tReward: 58.0\tEpisode Mean: 143.0\n",
+      "87614:127694057\tQ-min: 2.324\tQ-max: 2.604\tLives: 1\tReward: 62.0\tEpisode Mean: 143.0\n",
+      "87614:127694079\tQ-min: 2.336\tQ-max: 2.557\tLives: 1\tReward: 66.0\tEpisode Mean: 143.0\n",
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+      "87614:127694120\tQ-min: 2.384\tQ-max: 2.646\tLives: 1\tReward: 71.0\tEpisode Mean: 143.0\n",
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+      "87615:127694863\tQ-min: 1.640\tQ-max: 1.660\tLives: 3\tReward: 22.0\tEpisode Mean: 140.4\n",
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+      "87615:127695066\tQ-min: 1.545\tQ-max: 1.706\tLives: 3\tReward: 25.0\tEpisode Mean: 140.4\n",
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+      "87615:127695414\tQ-min: 2.005\tQ-max: 2.129\tLives: 2\tReward: 47.0\tEpisode Mean: 140.4\n",
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+      "87615:127695489\tQ-min: 2.176\tQ-max: 2.210\tLives: 2\tReward: 49.0\tEpisode Mean: 140.4\n",
+      "87615:127695521\tQ-min: 2.159\tQ-max: 2.215\tLives: 2\tReward: 50.0\tEpisode Mean: 140.4\n",
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+      "87615:127695612\tQ-min: 1.677\tQ-max: 1.804\tLives: 2\tReward: 55.0\tEpisode Mean: 140.4\n",
+      "87615:127695679\tQ-min: 1.717\tQ-max: 1.984\tLives: 2\tReward: 59.0\tEpisode Mean: 140.4\n",
+      "87615:127695750\tQ-min: 1.788\tQ-max: 1.857\tLives: 2\tReward: 60.0\tEpisode Mean: 140.4\n",
+      "87615:127695817\tQ-min: 1.672\tQ-max: 1.933\tLives: 2\tReward: 64.0\tEpisode Mean: 140.4\n",
+      "87615:127695868\tQ-min: 2.129\tQ-max: 2.172\tLives: 2\tReward: 65.0\tEpisode Mean: 140.4\n",
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+      "87615:127696204\tQ-min: 2.727\tQ-max: 7.415\tLives: 2\tReward: 126.0\tEpisode Mean: 140.4\n",
+      "87615:127696208\tQ-min: 4.507\tQ-max: 7.164\tLives: 2\tReward: 133.0\tEpisode Mean: 140.4\n",
+      "87615:127696213\tQ-min: 4.021\tQ-max: 7.264\tLives: 2\tReward: 140.0\tEpisode Mean: 140.4\n",
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+      "87615:127696224\tQ-min: 4.086\tQ-max: 6.433\tLives: 2\tReward: 154.0\tEpisode Mean: 140.4\n",
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+      "87615:127696233\tQ-min: 4.404\tQ-max: 6.600\tLives: 2\tReward: 168.0\tEpisode Mean: 140.4\n",
+      "87615:127696237\tQ-min: 4.124\tQ-max: 6.776\tLives: 2\tReward: 175.0\tEpisode Mean: 140.4\n",
+      "87615:127696242\tQ-min: 3.961\tQ-max: 5.944\tLives: 2\tReward: 182.0\tEpisode Mean: 140.4\n",
+      "87615:127696247\tQ-min: 4.544\tQ-max: 5.938\tLives: 2\tReward: 189.0\tEpisode Mean: 140.4\n",
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+      "87615:127696262\tQ-min: 4.059\tQ-max: 5.634\tLives: 2\tReward: 203.0\tEpisode Mean: 140.4\n",
+      "87615:127696268\tQ-min: 3.037\tQ-max: 4.725\tLives: 2\tReward: 210.0\tEpisode Mean: 140.4\n",
+      "87615:127696274\tQ-min: 2.643\tQ-max: 5.178\tLives: 2\tReward: 217.0\tEpisode Mean: 140.4\n",
+      "87615:127696280\tQ-min: 3.061\tQ-max: 4.737\tLives: 2\tReward: 224.0\tEpisode Mean: 140.4\n",
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+      "87615:127696298\tQ-min: 3.064\tQ-max: 5.131\tLives: 2\tReward: 245.0\tEpisode Mean: 140.4\n",
+      "87615:127696302\tQ-min: 3.054\tQ-max: 4.238\tLives: 2\tReward: 252.0\tEpisode Mean: 140.4\n",
+      "87615:127696309\tQ-min: 3.495\tQ-max: 4.537\tLives: 2\tReward: 259.0\tEpisode Mean: 140.4\n",
+      "87615:127696318\tQ-min: 2.442\tQ-max: 3.859\tLives: 2\tReward: 263.0\tEpisode Mean: 140.4\n",
+      "87615:127696325\tQ-min: 2.675\tQ-max: 4.446\tLives: 2\tReward: 267.0\tEpisode Mean: 140.4\n",
+      "87615:127696332\tQ-min: 2.903\tQ-max: 4.970\tLives: 2\tReward: 271.0\tEpisode Mean: 140.4\n",
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+      "87615:127696347\tQ-min: 3.840\tQ-max: 5.684\tLives: 2\tReward: 285.0\tEpisode Mean: 140.4\n",
+      "87615:127696354\tQ-min: 3.338\tQ-max: 5.494\tLives: 2\tReward: 292.0\tEpisode Mean: 140.4\n",
+      "87615:127696359\tQ-min: 3.294\tQ-max: 5.389\tLives: 2\tReward: 299.0\tEpisode Mean: 140.4\n",
+      "87615:127696366\tQ-min: 2.294\tQ-max: 3.083\tLives: 2\tReward: 300.0\tEpisode Mean: 140.4\n",
+      "87615:127696373\tQ-min: 2.104\tQ-max: 3.364\tLives: 2\tReward: 307.0\tEpisode Mean: 140.4\n",
+      "87615:127696379\tQ-min: 1.393\tQ-max: 4.202\tLives: 2\tReward: 314.0\tEpisode Mean: 140.4\n",
+      "87615:127696402\tQ-min: 0.235\tQ-max: 0.449\tLives: 1\tReward: 314.0\tEpisode Mean: 140.4\n",
+      "87615:127696467\tQ-min: 1.152\tQ-max: 2.538\tLives: 1\tReward: 318.0\tEpisode Mean: 140.4\n",
+      "87615:127696475\tQ-min: 2.140\tQ-max: 4.579\tLives: 1\tReward: 325.0\tEpisode Mean: 140.4\n",
+      "87615:127696481\tQ-min: 1.566\tQ-max: 2.914\tLives: 1\tReward: 332.0\tEpisode Mean: 140.4\n",
+      "87615:127696491\tQ-min: 1.893\tQ-max: 2.961\tLives: 1\tReward: 336.0\tEpisode Mean: 140.4\n",
+      "87615:127696499\tQ-min: 2.189\tQ-max: 3.113\tLives: 1\tReward: 340.0\tEpisode Mean: 140.4\n",
+      "87615:127696523\tQ-min: 0.266\tQ-max: 0.417\tLives: 0\tReward: 340.0\tEpisode Mean: 147.5\n",
+      "87616:127696566\tQ-min: 1.755\tQ-max: 1.768\tLives: 5\tReward: 1.0\tEpisode Mean: 147.5\n",
+      "87616:127696607\tQ-min: 1.822\tQ-max: 1.860\tLives: 5\tReward: 2.0\tEpisode Mean: 147.5\n",
+      "87616:127696650\tQ-min: 1.905\tQ-max: 1.942\tLives: 5\tReward: 3.0\tEpisode Mean: 147.5\n",
+      "87616:127696686\tQ-min: 1.920\tQ-max: 1.984\tLives: 5\tReward: 4.0\tEpisode Mean: 147.5\n",
+      "87616:127696717\tQ-min: 1.984\tQ-max: 2.012\tLives: 5\tReward: 5.0\tEpisode Mean: 147.5\n",
+      "87616:127696748\tQ-min: 1.915\tQ-max: 1.942\tLives: 5\tReward: 6.0\tEpisode Mean: 147.5\n",
+      "87616:127696778\tQ-min: 1.698\tQ-max: 1.758\tLives: 5\tReward: 7.0\tEpisode Mean: 147.5\n",
+      "87616:127696825\tQ-min: 1.582\tQ-max: 1.633\tLives: 5\tReward: 8.0\tEpisode Mean: 147.5\n",
+      "87616:127696887\tQ-min: 1.685\tQ-max: 1.710\tLives: 5\tReward: 9.0\tEpisode Mean: 147.5\n",
+      "87616:127696929\tQ-min: -0.020\tQ-max: 0.235\tLives: 4\tReward: 9.0\tEpisode Mean: 147.5\n",
+      "87616:127696986\tQ-min: 1.568\tQ-max: 1.667\tLives: 4\tReward: 13.0\tEpisode Mean: 147.5\n",
+      "87616:127697052\tQ-min: 1.726\tQ-max: 1.766\tLives: 4\tReward: 14.0\tEpisode Mean: 147.5\n",
+      "87616:127697114\tQ-min: 1.681\tQ-max: 1.714\tLives: 4\tReward: 15.0\tEpisode Mean: 147.5\n",
+      "87616:127697161\tQ-min: 2.009\tQ-max: 2.051\tLives: 4\tReward: 16.0\tEpisode Mean: 147.5\n",
+      "87616:127697180\tQ-min: -0.006\tQ-max: 0.308\tLives: 3\tReward: 16.0\tEpisode Mean: 147.5\n",
+      "87616:127697223\tQ-min: 1.883\tQ-max: 1.921\tLives: 3\tReward: 17.0\tEpisode Mean: 147.5\n",
+      "87616:127697264\tQ-min: 1.967\tQ-max: 1.993\tLives: 3\tReward: 18.0\tEpisode Mean: 147.5\n",
+      "87616:127697320\tQ-min: 1.846\tQ-max: 1.892\tLives: 3\tReward: 19.0\tEpisode Mean: 147.5\n",
+      "87616:127697370\tQ-min: 2.026\tQ-max: 2.101\tLives: 3\tReward: 20.0\tEpisode Mean: 147.5\n",
+      "87616:127697406\tQ-min: 2.037\tQ-max: 2.075\tLives: 3\tReward: 21.0\tEpisode Mean: 147.5\n",
+      "87616:127697436\tQ-min: 2.030\tQ-max: 2.055\tLives: 3\tReward: 22.0\tEpisode Mean: 147.5\n",
+      "87616:127697469\tQ-min: 2.059\tQ-max: 2.080\tLives: 3\tReward: 23.0\tEpisode Mean: 147.5\n",
+      "87616:127697521\tQ-min: 1.619\tQ-max: 1.701\tLives: 3\tReward: 24.0\tEpisode Mean: 147.5\n",
+      "87616:127697583\tQ-min: 1.657\tQ-max: 1.745\tLives: 3\tReward: 25.0\tEpisode Mean: 147.5\n",
+      "87616:127697651\tQ-min: 1.690\tQ-max: 1.752\tLives: 3\tReward: 26.0\tEpisode Mean: 147.5\n",
+      "87616:127697718\tQ-min: 1.667\tQ-max: 1.827\tLives: 3\tReward: 27.0\tEpisode Mean: 147.5\n",
+      "87616:127697766\tQ-min: 2.042\tQ-max: 2.062\tLives: 3\tReward: 31.0\tEpisode Mean: 147.5\n",
+      "87616:127697800\tQ-min: 2.033\tQ-max: 2.101\tLives: 3\tReward: 32.0\tEpisode Mean: 147.5\n",
+      "87616:127697830\tQ-min: 2.066\tQ-max: 2.106\tLives: 3\tReward: 33.0\tEpisode Mean: 147.5\n",
+      "87616:127697863\tQ-min: 1.952\tQ-max: 2.108\tLives: 3\tReward: 34.0\tEpisode Mean: 147.5\n",
+      "87616:127697898\tQ-min: 2.262\tQ-max: 2.323\tLives: 3\tReward: 38.0\tEpisode Mean: 147.5\n",
+      "87616:127697912\tQ-min: 0.078\tQ-max: 0.422\tLives: 2\tReward: 38.0\tEpisode Mean: 147.5\n",
+      "87616:127697968\tQ-min: 1.802\tQ-max: 1.856\tLives: 2\tReward: 39.0\tEpisode Mean: 147.5\n",
+      "87616:127698031\tQ-min: 1.838\tQ-max: 1.876\tLives: 2\tReward: 40.0\tEpisode Mean: 147.5\n",
+      "87616:127698099\tQ-min: 1.856\tQ-max: 1.898\tLives: 2\tReward: 41.0\tEpisode Mean: 147.5\n",
+      "87616:127698150\tQ-min: 2.508\tQ-max: 2.578\tLives: 2\tReward: 45.0\tEpisode Mean: 147.5\n",
+      "87616:127698172\tQ-min: 2.409\tQ-max: 2.576\tLives: 2\tReward: 49.0\tEpisode Mean: 147.5\n",
+      "87616:127698193\tQ-min: 2.089\tQ-max: 2.658\tLives: 2\tReward: 56.0\tEpisode Mean: 147.5\n",
+      "87616:127698216\tQ-min: 2.436\tQ-max: 2.506\tLives: 2\tReward: 57.0\tEpisode Mean: 147.5\n",
+      "87616:127698236\tQ-min: 2.420\tQ-max: 2.482\tLives: 2\tReward: 58.0\tEpisode Mean: 147.5\n",
+      "87616:127698257\tQ-min: 2.457\tQ-max: 2.508\tLives: 2\tReward: 62.0\tEpisode Mean: 147.5\n",
+      "87616:127698278\tQ-min: 2.433\tQ-max: 2.551\tLives: 2\tReward: 66.0\tEpisode Mean: 147.5\n",
+      "87616:127698291\tQ-min: -0.079\tQ-max: 0.126\tLives: 1\tReward: 66.0\tEpisode Mean: 147.5\n",
+      "87616:127698343\tQ-min: 1.843\tQ-max: 1.872\tLives: 1\tReward: 67.0\tEpisode Mean: 147.5\n",
+      "87616:127698399\tQ-min: 2.090\tQ-max: 2.351\tLives: 1\tReward: 71.0\tEpisode Mean: 147.5\n",
+      "87616:127698456\tQ-min: 1.968\tQ-max: 2.183\tLives: 1\tReward: 75.0\tEpisode Mean: 147.5\n",
+      "87616:127698512\tQ-min: 2.150\tQ-max: 2.390\tLives: 1\tReward: 79.0\tEpisode Mean: 147.5\n",
+      "87616:127698549\tQ-min: 2.398\tQ-max: 2.454\tLives: 1\tReward: 80.0\tEpisode Mean: 147.5\n",
+      "87616:127698584\tQ-min: 2.203\tQ-max: 2.419\tLives: 1\tReward: 84.0\tEpisode Mean: 147.5\n",
+      "87616:127698620\tQ-min: 2.034\tQ-max: 2.903\tLives: 1\tReward: 88.0\tEpisode Mean: 147.5\n",
+      "87616:127698641\tQ-min: 2.441\tQ-max: 2.569\tLives: 1\tReward: 89.0\tEpisode Mean: 147.5\n",
+      "87616:127698661\tQ-min: 2.446\tQ-max: 2.627\tLives: 1\tReward: 93.0\tEpisode Mean: 147.5\n",
+      "87616:127698684\tQ-min: 2.499\tQ-max: 2.649\tLives: 1\tReward: 94.0\tEpisode Mean: 147.5\n",
+      "87616:127698707\tQ-min: 2.364\tQ-max: 2.641\tLives: 1\tReward: 98.0\tEpisode Mean: 147.5\n",
+      "87616:127698721\tQ-min: -0.372\tQ-max: 0.212\tLives: 0\tReward: 98.0\tEpisode Mean: 145.8\n",
+      "87617:127698766\tQ-min: 1.752\tQ-max: 1.767\tLives: 5\tReward: 1.0\tEpisode Mean: 145.8\n",
+      "87617:127698808\tQ-min: 1.814\tQ-max: 1.833\tLives: 5\tReward: 2.0\tEpisode Mean: 145.8\n",
+      "87617:127698846\tQ-min: 1.934\tQ-max: 2.003\tLives: 5\tReward: 3.0\tEpisode Mean: 145.8\n",
+      "87617:127698884\tQ-min: 1.993\tQ-max: 2.013\tLives: 5\tReward: 4.0\tEpisode Mean: 145.8\n",
+      "87617:127698913\tQ-min: 1.983\tQ-max: 2.006\tLives: 5\tReward: 5.0\tEpisode Mean: 145.8\n",
+      "87617:127698943\tQ-min: 1.895\tQ-max: 1.934\tLives: 5\tReward: 6.0\tEpisode Mean: 145.8\n",
+      "87617:127698975\tQ-min: 1.748\tQ-max: 1.790\tLives: 5\tReward: 7.0\tEpisode Mean: 145.8\n",
+      "87617:127699023\tQ-min: 1.579\tQ-max: 1.655\tLives: 5\tReward: 8.0\tEpisode Mean: 145.8\n",
+      "87617:127699090\tQ-min: 1.652\tQ-max: 1.752\tLives: 5\tReward: 9.0\tEpisode Mean: 145.8\n",
+      "87617:127699159\tQ-min: 1.698\tQ-max: 1.752\tLives: 5\tReward: 10.0\tEpisode Mean: 145.8\n",
+      "87617:127699202\tQ-min: -0.031\tQ-max: 0.225\tLives: 4\tReward: 10.0\tEpisode Mean: 145.8\n",
+      "87617:127699246\tQ-min: 1.889\tQ-max: 1.922\tLives: 4\tReward: 11.0\tEpisode Mean: 145.8\n",
+      "87617:127699296\tQ-min: 1.914\tQ-max: 1.953\tLives: 4\tReward: 15.0\tEpisode Mean: 145.8\n",
+      "87617:127699353\tQ-min: 1.757\tQ-max: 1.781\tLives: 4\tReward: 16.0\tEpisode Mean: 145.8\n",
+      "87617:127699403\tQ-min: 2.019\tQ-max: 2.053\tLives: 4\tReward: 17.0\tEpisode Mean: 145.8\n",
+      "87617:127699434\tQ-min: 2.157\tQ-max: 2.220\tLives: 4\tReward: 18.0\tEpisode Mean: 145.8\n",
+      "87617:127699468\tQ-min: 1.990\tQ-max: 2.004\tLives: 4\tReward: 19.0\tEpisode Mean: 145.8\n",
+      "87617:127699501\tQ-min: 1.990\tQ-max: 2.028\tLives: 4\tReward: 20.0\tEpisode Mean: 145.8\n",
+      "87617:127699549\tQ-min: 1.681\tQ-max: 1.707\tLives: 4\tReward: 21.0\tEpisode Mean: 145.8\n",
+      "87617:127699614\tQ-min: 1.751\tQ-max: 1.785\tLives: 4\tReward: 22.0\tEpisode Mean: 145.8\n",
+      "87617:127699674\tQ-min: 1.735\tQ-max: 1.746\tLives: 4\tReward: 23.0\tEpisode Mean: 145.8\n",
+      "87617:127699736\tQ-min: 1.770\tQ-max: 1.788\tLives: 4\tReward: 24.0\tEpisode Mean: 145.8\n",
+      "87617:127699784\tQ-min: 1.994\tQ-max: 2.046\tLives: 4\tReward: 25.0\tEpisode Mean: 145.8\n",
+      "87617:127699816\tQ-min: 2.013\tQ-max: 2.036\tLives: 4\tReward: 26.0\tEpisode Mean: 145.8\n",
+      "87617:127699837\tQ-min: -0.117\tQ-max: 0.201\tLives: 3\tReward: 26.0\tEpisode Mean: 145.8\n",
+      "87617:127699880\tQ-min: 1.936\tQ-max: 1.952\tLives: 3\tReward: 27.0\tEpisode Mean: 145.8\n",
+      "87617:127699937\tQ-min: 1.639\tQ-max: 1.781\tLives: 3\tReward: 28.0\tEpisode Mean: 145.8\n",
+      "87617:127699992\tQ-min: 2.026\tQ-max: 2.058\tLives: 3\tReward: 29.0\tEpisode Mean: 145.8\n",
+      "87617:127700030\tQ-min: 2.014\tQ-max: 2.034\tLives: 3\tReward: 30.0\tEpisode Mean: 145.8\n",
+      "87617:127700066\tQ-min: 2.029\tQ-max: 2.075\tLives: 3\tReward: 31.0\tEpisode Mean: 145.8\n",
+      "87617:127700098\tQ-min: 2.160\tQ-max: 2.572\tLives: 3\tReward: 35.0\tEpisode Mean: 145.8\n",
+      "87617:127700118\tQ-min: 2.057\tQ-max: 2.423\tLives: 3\tReward: 39.0\tEpisode Mean: 145.8\n",
+      "87617:127700139\tQ-min: 2.400\tQ-max: 2.545\tLives: 3\tReward: 43.0\tEpisode Mean: 145.8\n",
+      "87617:127700158\tQ-min: 2.066\tQ-max: 2.565\tLives: 3\tReward: 50.0\tEpisode Mean: 145.8\n",
+      "87617:127700180\tQ-min: 2.392\tQ-max: 2.474\tLives: 3\tReward: 51.0\tEpisode Mean: 145.8\n",
+      "87617:127700200\tQ-min: 2.233\tQ-max: 2.483\tLives: 3\tReward: 52.0\tEpisode Mean: 145.8\n",
+      "87617:127700221\tQ-min: 2.048\tQ-max: 2.191\tLives: 3\tReward: 56.0\tEpisode Mean: 145.8\n",
+      "87617:127700245\tQ-min: 2.330\tQ-max: 2.450\tLives: 3\tReward: 60.0\tEpisode Mean: 145.8\n",
+      "87617:127700271\tQ-min: 2.389\tQ-max: 2.500\tLives: 3\tReward: 61.0\tEpisode Mean: 145.8\n",
+      "87617:127700293\tQ-min: 2.307\tQ-max: 2.508\tLives: 3\tReward: 65.0\tEpisode Mean: 145.8\n",
+      "87617:127700306\tQ-min: -0.006\tQ-max: 0.113\tLives: 2\tReward: 65.0\tEpisode Mean: 145.8\n",
+      "87617:127700351\tQ-min: 1.970\tQ-max: 2.111\tLives: 2\tReward: 69.0\tEpisode Mean: 145.8\n",
+      "87617:127700399\tQ-min: 2.366\tQ-max: 2.450\tLives: 2\tReward: 73.0\tEpisode Mean: 145.8\n",
+      "87617:127700422\tQ-min: 2.140\tQ-max: 2.488\tLives: 2\tReward: 74.0\tEpisode Mean: 145.8\n",
+      "87617:127700442\tQ-min: 2.122\tQ-max: 2.493\tLives: 2\tReward: 78.0\tEpisode Mean: 145.8\n",
+      "87617:127700464\tQ-min: 2.243\tQ-max: 2.550\tLives: 2\tReward: 82.0\tEpisode Mean: 145.8\n",
+      "87617:127700488\tQ-min: 2.414\tQ-max: 2.670\tLives: 2\tReward: 86.0\tEpisode Mean: 145.8\n",
+      "87617:127700510\tQ-min: 2.252\tQ-max: 2.626\tLives: 2\tReward: 93.0\tEpisode Mean: 145.8\n",
+      "87617:127700533\tQ-min: 2.150\tQ-max: 2.691\tLives: 2\tReward: 100.0\tEpisode Mean: 145.8\n",
+      "87617:127700556\tQ-min: 1.972\tQ-max: 2.779\tLives: 2\tReward: 101.0\tEpisode Mean: 145.8\n",
+      "87617:127700567\tQ-min: -0.020\tQ-max: 0.190\tLives: 1\tReward: 101.0\tEpisode Mean: 145.8\n",
+      "87617:127700613\tQ-min: 2.301\tQ-max: 2.671\tLives: 1\tReward: 105.0\tEpisode Mean: 145.8\n",
+      "87617:127700659\tQ-min: 2.437\tQ-max: 2.946\tLives: 1\tReward: 106.0\tEpisode Mean: 145.8\n",
+      "87617:127700709\tQ-min: 0.855\tQ-max: 2.276\tLives: 1\tReward: 113.0\tEpisode Mean: 145.8\n",
+      "87617:127700735\tQ-min: 1.749\tQ-max: 3.022\tLives: 1\tReward: 120.0\tEpisode Mean: 145.8\n",
+      "87617:127700761\tQ-min: 2.380\tQ-max: 3.517\tLives: 1\tReward: 127.0\tEpisode Mean: 145.8\n",
+      "87617:127700778\tQ-min: -0.098\tQ-max: 0.169\tLives: 0\tReward: 127.0\tEpisode Mean: 145.2\n"
      ]
     }
    ],
@@ -2765,7 +2889,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -2777,10 +2901,10 @@
      "output_type": "stream",
      "text": [
       "Rewards for 30 episodes:\n",
-      "- Min:    43.0\n",
-      "- Mean:   111.233333333\n",
-      "- Max:    381.0\n",
-      "- Stdev:  62.8424927011\n"
+      "- Min:    40.0\n",
+      "- Mean:   145.166666667\n",
+      "- Max:    386.0\n",
+      "- Stdev:  105.131372842\n"
      ]
     }
    ],
@@ -2805,7 +2929,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -2814,9 +2938,9 @@
    "outputs": [
     {
      "data": {
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+      "image/png": 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cOseM1zJ+e/wDxnNbL98sH+NPyN/CeM7xM8DKguT9ly7P3d2L6Iw127+2y3sfcMkc8j6f\n8VTJ3cD+7nbpoo7xFnkXcoyBXwTu7HIdAP6qW/90xv+Z3A98EDihW39it3x/9/jTFyTvbd34HgDe\nw4+PYJn779ya7L/Gj49Omdn4esamJDVsoadTJElbs8QlqWGWuCQ1zBKXpIZZ4pLUMEtckhpmiUtS\nwyxxSWrY/wErup7CCPwjeQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0263400>"
+       "<matplotlib.figure.Figure at 0x7f8851c83e10>"
       ]
      },
      "metadata": {},
@@ -2843,7 +2967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -2891,7 +3015,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -2938,7 +3062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -2948,10 +3072,10 @@
     {
      "data": {
       "text/plain": [
-       "935"
+       "656"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2973,7 +3097,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 30,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -2996,7 +3120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -3025,7 +3149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3036,10 +3160,10 @@
     {
      "data": {
       "text/plain": [
-       "40"
+       "41"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3065,7 +3189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3074,9 +3198,9 @@
    "outputs": [
     {
      "data": {
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BWTO7JVT75F3XJZfL1eXed/pCJTJVoRCiY3meh1IqmLivv7+fVCpFLBYLUi8B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\nbndavW57oFdK2VQni/p3wK3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ylKAgdBFhsVZKUS6XWVxcZHFxkWw2W+ejhyvhlCLy3Y0IvSB0EeVyOYiy8X0f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\ngiAIXY4IvSAIQpcjQi8IgtDl/H+HLMff60gFRgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be02be160>"
+       "<matplotlib.figure.Figure at 0x7f884c190a90>"
       ]
      },
      "metadata": {},
@@ -3088,20 +3212,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.682 \n",
-      "FIRE        1.676 \n",
-      "RIGHT       1.685 \n",
-      "LEFT        1.691 \n",
-      "RIGHTFIRE   1.690 \n",
-      "LEFTFIRE    1.699 (Action Taken)\n",
+      "NOOP        1.576 (Action Taken)\n",
+      "FIRE        1.573 \n",
+      "RIGHT       1.564 \n",
+      "LEFT        1.574 \n",
+      "RIGHTFIRE   1.571 \n",
+      "LEFTFIRE    1.571 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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rRLtJ3d54TCrGcRwsy+Jf/uVfOH/+PA888ACf/vSn2b9//w1z13fLcGO5MlYI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\nvVLqU0qpt5RS55RSX25jOXY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3ruN6w21bENpNy1k3Wmu9njik1vpp4Gno7jim0LmIbQvdwnqHDF5S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\nMwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be02ba080>"
+       "<matplotlib.figure.Figure at 0x7f884c199e48>"
       ]
      },
      "metadata": {},
@@ -3113,20 +3237,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.731 \n",
-      "FIRE        1.727 \n",
-      "RIGHT       1.734 \n",
-      "LEFT        1.734 \n",
-      "RIGHTFIRE   1.730 \n",
-      "LEFTFIRE    1.741 (Action Taken)\n",
+      "NOOP        1.630 (Action Taken)\n",
+      "FIRE        1.626 \n",
+      "RIGHT       1.610 \n",
+      "LEFT        1.617 \n",
+      "RIGHTFIRE   1.606 \n",
+      "LEFTFIRE    1.625 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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l+vDi1UBwFqghCV/AwqOCzNnEjTEkRLeLXKIH6qYdCE8UJsRizARswKpmuBSik0Uq0YcP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\neiGE6HCS6IUQosNFYvZKYBK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l2dv3fwS+rZRKAB8A/57KzeNvlFKfBz4EfrvJYwhCO+gK296yZQvJZJJisUhf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\nCEKXI0IvCILQ5fx/1kBidRXA6xoAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01769e8>"
+       "<matplotlib.figure.Figure at 0x7f89608fd710>"
       ]
      },
      "metadata": {},
@@ -3138,20 +3262,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.744 \n",
-      "FIRE        1.729 \n",
-      "RIGHT       1.753 \n",
-      "LEFT        1.751 \n",
-      "RIGHTFIRE   1.754 (Action Taken)\n",
-      "LEFTFIRE    1.752 \n",
+      "NOOP        1.641 (Action Taken)\n",
+      "FIRE        1.635 \n",
+      "RIGHT       1.632 \n",
+      "LEFT        1.627 \n",
+      "RIGHTFIRE   1.617 \n",
+      "LEFTFIRE    1.641 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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QIPQ6iRN6oKHsQLxQmCAshinABqyowqUgdDOJEvr4Y7f538yvauq+CL3NQp68cQhMpdG4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\nbFvoPpbQmfR31OKQVWpxyc8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vDZoR+glgQmv9evX9d6lcHFeUUrcCVP9OrbC+IMSVrrFtI+pQybIxAm86ZbPZ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\nuhwRekEQhC5HhF4QBKHL+f8NrAmvL0LNtwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be017c208>"
+       "<matplotlib.figure.Figure at 0x7f884c303c18>"
       ]
      },
      "metadata": {},
@@ -3163,20 +3287,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.782 \n",
-      "FIRE        1.776 \n",
-      "RIGHT       1.789 \n",
-      "LEFT        1.787 \n",
-      "RIGHTFIRE   1.796 (Action Taken)\n",
-      "LEFTFIRE    1.784 \n",
+      "NOOP        1.710 (Action Taken)\n",
+      "FIRE        1.703 \n",
+      "RIGHT       1.694 \n",
+      "LEFT        1.703 \n",
+      "RIGHTFIRE   1.693 \n",
+      "LEFTFIRE    1.705 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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2G2UkeTsx+quBC8BfichNwCvAF4Htxphz9XXOA9tbbSwiDwMPA+zevbuNZijK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\nbK6vK8D/Bt4CXgNu18wEfSX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Ly1y4cIELFy6Ez6P96mUO2P7RTh39fuAK8FdKqcPA68AXgB1a60u1Zd4HdjRb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\nn/v/pZDTVTkwkZ0AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0108e48>"
+       "<matplotlib.figure.Figure at 0x7f884c0d44a8>"
       ]
      },
      "metadata": {},
@@ -3188,20 +3312,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.777 \n",
-      "FIRE        1.766 \n",
-      "RIGHT       1.789 (Action Taken)\n",
-      "LEFT        1.783 \n",
-      "RIGHTFIRE   1.783 \n",
-      "LEFTFIRE    1.782 \n",
+      "NOOP        1.743 \n",
+      "FIRE        1.736 \n",
+      "RIGHT       1.741 \n",
+      "LEFT        1.739 \n",
+      "RIGHTFIRE   1.725 \n",
+      "LEFTFIRE    1.747 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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1j1Jqi1LqJ0qp09W/g2tVWCE2itTt+LMsC9d1sW27JvBHLzNaf1W2TtVsL8XX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\nDCPlWok4lmtfC9ctdXvlpFz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utCFB6HUiJ/RAXdqBcKIwQVgOk4ANWFOGS0HoZiIl9OHXbvPdjK9q8r4Ivc1SNXlTITCZ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01ce588>"
+       "<matplotlib.figure.Figure at 0x7f884c0e07f0>"
       ]
      },
      "metadata": {},
@@ -3213,20 +3337,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.794 \n",
-      "FIRE        1.805 (Action Taken)\n",
-      "RIGHT       1.787 \n",
-      "LEFT        1.786 \n",
-      "RIGHTFIRE   1.790 \n",
-      "LEFTFIRE    1.794 \n",
+      "NOOP        1.768 (Action Taken)\n",
+      "FIRE        1.749 \n",
+      "RIGHT       1.753 \n",
+      "LEFT        1.757 \n",
+      "RIGHTFIRE   1.747 \n",
+      "LEFTFIRE    1.764 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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8+uqrjI2N+XMymMJ9wtKI0AuCEDqCYZhyucxPfvITjhw5QqFQYPfu3fzyL/8y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\na8BVrfUd9c9GgO8BE8Ak8Ft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TbTzOZDLJwMAAiUSCmZkZpqenwx6xZh/hypihJqJ2YIavFtaGZDKJ4zjk83kA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\nTbHn3JAAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be031d400>"
+       "<matplotlib.figure.Figure at 0x7f884c0bd2b0>"
       ]
      },
      "metadata": {},
@@ -3238,20 +3362,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.774 (Action Taken)\n",
-      "FIRE        0.768 \n",
-      "RIGHT       0.764 \n",
-      "LEFT        0.768 \n",
-      "RIGHTFIRE   0.769 \n",
-      "LEFTFIRE    0.771 \n",
+      "NOOP        0.751 \n",
+      "FIRE        0.753 \n",
+      "RIGHT       0.762 \n",
+      "LEFT        0.757 \n",
+      "RIGHTFIRE   0.768 (Action Taken)\n",
+      "LEFTFIRE    0.755 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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ByOaBBx7gC1/4ArD8EJ+dnSWTyQQdJsPTiS4tLcn/u04iJ/SNf2C4YdZk4hhB\n69SMCiPWxusxgjY0NMR73vMedu7cyfnz55mfn79K6A2dem183w/O1diBGb5a2F6E/7NwW9LCwgLf\n+c53ePHFF8nn82SzWc6ePRv83i2OXiuJnNA3eqRhoTODH3XLLEqNA5eZVLO+vj56e3uvmjR9tRun\n02icgEJmINt+NGbMmJ7dlmUxPDzMxMQE3/rWt4Lfe3p6SCaTQXp1pVIRwV8HkRN64QqND72lpSXO\nnTtHuVxmenqapaWlunW7JWwjbH8aa2DJZLKuFprJZOp+v/XWWzl48CCpVIq33nqLiYmJoDYb7lsj\nrEzkhb4xJNFNNIr3/Pw8L7/8MplMhnw+X5dZs4kTZEeebrWP7UyjMM/OzvLmm29y8OBBXn/99brM\nurGxMW6//XYeeOAB+vv7+eEPf8jJk1fmbDftNeLhr07khb6bWcmjL5VKQY9AGeBJ2K5UKpU6e/3J\nT37C5z73Ofr6+lhYWGBycjIYwNA4MH19ffT19QWd5QzdlISwUUTotxEy9rbQKYRnRvN9n8nJSSYn\nJ1dcd3Fxkddee43+/n7i8ThvvPEGAwMDzM/PUy6XgzGfhNURoRcEoW2sxRN3XZcTJ05w8uRJyuUy\nw8PDHDlyhPHxcY4fP87ly5eBKymb4t1fjQj9NiPsuYhBC9udcCpxeL6Jcrkc1F593w8aXmFZ+O+5\n5x5s22ZiYiL4Xmq7qyNCv00RkRc6Cd/3qVarQUy+Ma04PG6TGdgwPC+D2YfcFysjQr/NEEMWOpFG\ncW8kmUxSLBbRWpNKpVBKEY/H2blzJ/l8nnQ6jW3bzM/Py9AIKyBCLwhC5PE876oOcr29vRw6dIiR\nkRESiQSXL18ml8sFQh+edrTbEaEXBCHSaK3rhiReXFzk9ddfJ5vN4jgO+/btw7btOpGHKxPIC9CZ\nA6IIgtBRhOcCLhQKPP/88/z85z9nZmYmmCi+cfhyCXNeQYReEIRtgZk/2mB6hiulKJfL2LbN2NgY\nqVRKvPkGJHQjCMK2oHGYj0wmg23bwXDHQ0NDJJNJEokEb7/99lWdsroZEXpBELYFjdNmVqtVzpw5\nQz6fZ3BwkL6+PpLJJDMzM3XevPSaFaEXBGGbYfLql5aWWFpaYnZ2loMHDwJQKpXqxoMCidWDCL0g\nCNuQsHgvLi5y7ty5wJP3fZ/R0VEKhQJLS0vBZDWN23UTIvSCIGwrGsXasqxgvBuAkZERxsbGWFpa\nCiaNNzPGYm5uAAAQi0lEQVTSdavQN5V1o5QaUEp9Tyn1ulLqpFLq/UqpHUqpJ5VSp2rvg60qrCBs\nFWLb0cdMM9oYgzfTS5rPhm5ukG02vfLrwD9orY8AR4GTwJeBp7TWh4CnasuCsN0Q2444WusgVBOe\nnSqcWhmeb9p87kY2LPRKqX7gPuBRAK11RWu9AHwM+GZttW8CH2+2kIKwlYhtbz8avXrbtkmn0wwP\nD7Njxw6GhoZIpVJtKl37acajPwBcBv5SKfWSUuobSqkMMKa1vlBb5yIwttLGSqmHlVLHlFLHZmZm\nmiiGILScltn2FpW36wmnU5bLZYrFIgC9vb0MDw/T399f19kKuivtshmhd4DbgT/XWt8G5Gmoyurl\nANmKrR9a60e01ndqre8cHh5uohiC0HJaZtubXlJhxSk333nnHWZnZ/F9H8dZzjnp5p6yzQj9eeC8\n1vq52vL3WL45LimldgHU3qdX2V4QoorY9jbE5Nd7nhdk3Jjhj13XRSlVF8vvpgycDQu91voicE4p\ndbj21YeB14DHgIdq3z0E/KCpEgrCFiO23RnYth148wCpVIq+vj7i8XgbS9Uems2j/w/At5VSceAt\n4N+z/PD4a6XUZ4G3gd9s8hiC0A7EtrcZjR661ppCoUA8HseyLDKZDI7jUKlU6oY9Vkp1vHfflNBr\nrSeAleKQH25mv4LQbsS2tzdKKfL5PJVKhUwmQ09PD/F4HK11nah3S4Os9IwVBKHjMGJeqVTqJiA3\nE5M4joPruh3vyRtE6AVB6Ghc1yWbzQYdq1KpFPF4nFKpRLlcbnfxtgSZeEQQhI7FhGbMnLOe56GU\nIhaL1WXgdHoIR4ReEISOZbXQjO/7XRO2ARF6QRC6AOOxW5YV5NuHvfhOF30RekEQOh4j5J0u6Ksh\njbGCIHQ0YXHXWlOpVHBdN8ilt20b27ZxXbdjhzIWoRcEoasol8uB+FuWRTKZRCkVDJfQiUjoRhCE\nrqIxfNMYrzffdRIi9IIgdDUrxe07LZYvQi8IQlexkve+klffSYjQC4LQVaw0+FljXn2nib40xgqC\n0LX4vh+Mh+O6LkAwE1UnjYUjQi8IQldjBjqD5Syc8IxUnSL0EroRBEGoYUI2nSLwBhF6QRCEGp0m\n8AYRekEQupqVGl6lMVYQBKGDaPTiTe/Yxiyc7ezti9ALgiDU8H2farUaTDloWRa2bQP1jbbbDQnd\nCIIghAjn1CulsG1724dyROgFQRCuwXYO2RhE6AVBEDocEXpBEIRrsN3DNiBCLwiCsCpmQnHP84Lv\nzHSE2wnJuhEEQViFxslITBaO7/t14h91xKMXBEFYI9t1SGMRekEQhHWy3TJxJHQjCIKwTizLump+\n2SiLvwi9IAjCGjE9ZgFs2w4+R31S8aZCN0qp/6SUelUp9YpS6q+UUkml1AGl1HNKqdNKqe8qpeKt\nKqwgbBVi28JKmCwcI+zbJV6/YaFXSu0B/iNwp9b6FsAGPg18DfgTrfWNwDzw2VYUVBC2CrFtYTXM\ntINmmITtMthZs42xDpBSSjlAGrgA3A98r/b7N4GPN3kMQWgHYtvCNTGefEd79FrrKeB/AZMs3wSL\nwHFgQWvt1lY7D+xZaXul1MNKqWNKqWMzMzMbLYYgtJxW2vZWlFdoDyZe39EevVJqEPgYcADYDWSA\nX1vr9lrrR7TWd2qt7xweHt5oMQSh5bTStjepiEKbMSGccLzesqzI9pptJuvmXwFntNaXAZRSfwd8\nEBhQSjk1z2cvMNV8MQVhSxHbFq5L48QkYYGPmpffTIx+ErhbKZVWy2f4YeA14MfAJ2vrPAT8oLki\nCsKWI7YtdBTNxOifY7lh6kXg5dq+HgG+BHxBKXUaGAIebUE5BWHLENsWOo2mOkxprf8A+IOGr98C\n7mpmv4LQbsS2hY0Q1XRL6RkrCILQAqKcgSNCLwiC0CSNIt+YedPuB4CMXikIgrAJRGl4BBF6QRCE\nDkeEXhAEocMRoRcEQdhk2h3CkcZYQRCEFtPuxtdGxKMXBEHYBFbKxGmXZy9CLwiCsIlEIb9ehF4Q\nBKHDEaEXBEHocEToBUEQOhzJuhEEQdgC2hmnF49eEAShw4mU0EdpbAgh2oS9IzOVWyNiS4KwTKRC\nNyulIbU7LUmIJpZ1xUexbbtuHPDwpM2rPQQEAbbOGTD2aWzUHDe83DiWfeM2zRAZofd9H9u2674T\nkRcM4RtBKRVMxOz7fjAhc9heopC7LEQb27YDh6FRgBsxdmfWWc8EI2Y7M5l4eF+w7LQ0OitmO601\nrus27bBERujNzRq+ABLKEQxh4W40/kqlEgg+LNuNbdvBzSMIK+F5Hp7nteXYYUHfinJEIkZvBN28\nwjes3KjCSoQ9nFKphOd5OM6y3+I4TuAlidgLjWxHe2hWCyPh0Wutgyea7/vBTRz+LHQ3tm0HQq6U\nIpVKUSwWKZVKZDIZbNvGdV0AXNfF8zyq1aqEcISrMKGTTCZDKpUCrjgOK8XOw8vGDtcautFaB9GK\nSqVCPp+nWq1iWVawfTKZJJ1O4zgOnucFtVPHcahWqywuLlIoFJo658gIfbVaxXVdKpUKnueRTqcp\nl8vBzSt0F4032PDwMHv37iWVSuH7Po7jUKlUWFpaYt++ffT395PNZtFak8vlgnXCToTQ3TiOE+hJ\nLBbj5ptv5tChQwCBkBqbMRg7dF0Xy7Lo7e1lYGDgKlFeCeOoJpNJHMdhamqKEydOMDMzQzwex/d9\ntNYcOHCAW265hYGBAfL5PMVikVQqRX9/PzMzMzz99NO88sorAEE75nptOhJC73ke+Xwey7KoVCo4\njkMikaBQKARemdBdGI/H/Pfj4+Pcf//97N69OwjVKKXwPI9MJsPw8DDvvPMOsVgssBmzj2q12uaz\nEaJAOPRh2zYjIyPccMMNKKXIZrMopYjFYnV2F7YhpRQ7duxgbGyMeDxeZ2dQH3e3LCtoR0qn0yQS\nCVKpFFNTUxSLRZLJZNAwu3PnTt71rncxMjJCLpcjm83S29vL8PAw586d48SJE3XnYOx+PURC6MMX\n0jSsVSqVwMtvzKYQOp/GeOTu3bt5//vfz0033cTS0hLFYpFEIhEYfaVSYXFxsS6jwdiK1AqFRozm\nlEollFKUy2WAQHzNOkbETbilXC5TKBRwXTcQ8pUyd4xdGkF2XZdisUi1Wg2+N3ZZrVYpFosUCgUK\nhQLFYhHbtsnn85RKpZbYb2SE3lxw49GbExaPXoDlG6VUKlEsFikWi5TLZXzfr0u5jMfjK267WtVa\n6G5MdhZcsZFw7Dws9CadN9zI73le3fbh9kTbtuvi+islBphtwllijccw8f1miYTQK6WCBg4TW43F\nYkH2hNB9NDbCnzt3jmeeeYaTJ09SKpXqvPW+vj4OHz7MgQMHiMfjVCoVtNbBzSY2JKxEOH/dvJsY\nvbE/Y0PhBlLzAlaN0Ruv3nVdYrFYnZ6Z4xrbNA28RvfMuuZzxwi9bdsMDAzUxegHBgbQWpNOp+su\n5HZMjRLWT6PQT05OBuEa07nOVIdHRkbI5/M4jkM6naZQKKC1Dm7aSqXSprMQokTYpjzPY2pqKnAw\ni8UicKWxszHrxrQJZTIZ+vr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KYQ/YbGu8/1YRM9klRnzNcTpp/OZY1Wo1eNporV1j6pbcqt2daEu9Xm9K1TTHMRk27fCX\nf/mXnWim0CFWkikmdJZICH0sFmPPnj3dbobQo4Q7+ISNwzg5YefAOESmQJ95Og6HFOv1unjzHSYS\nQg9EoQTtDSGWWxEerdnOtq316FsLfrXO0tOOZ9+6bbvt7qRX39rJul7HEjaOcAjTLC+1jvmt5Tde\nHyIh9GZyjVbWcnGvZJvWddYyX6UJc4RFeqWdRkttaz43y63C3k5JYLOP1u8MqystcLN2t9Mus6/l\nvnP4WGshCk7EVuZm4x5Mn5SwvkRC6GH5Yf1rieOtZJvWdcLLN+vsXK5TcKmOzKX2tdS+l1teybqr\nYaltl+snWG272423LnfT69T+BWErEwmhtyxrQ/PohRuJSmhkPdohFRGFrU4khH41YQ9BWC1RuIEJ\nQjeJhNDD8qV3xRsTVoo4C4KwNJER+psh8VnhVojXLgjLE1mhN6NVzUCadkaDCr2LsQtTJkGGzAvC\njURO6MOTV8P1+usGEXwBls4KMqORW21IELY6kRN6aK79Ei4UJgjLYQqwAWuqcCkIvUykhD782G3e\nm/lVTaExYWuzlCdvHAIzlD7s2YtXLwgREvpwyVulFIlEgmKxyJkzZ3jhhReYmZkhmUxi23Yw0k6E\nf+thOl3NdIflcpkdO3bw0EMPce+99wZ2Ey5NIQhbncgIPSwKt6lNbkaZ/uIXv+CrX/0qExMTQb1y\nM+WdCP3WI+wIlMtlSqUShw8fZmhoiHvvvbcpPm8qiwrCVidSQg83psnlcjmmpqYAmibgELY2YTuY\nmpqiUCg0/d/cEEToBSGCQt9KIpFgaGiIcrkcTFggHv3WxfzuyWSSUqmE7/sMDQ3hum7TeiLygnCd\nyAl9q3jbth3UEzcTcJhHchH6rUc4b95xHKrVKrFYTDKzBOEmRE7oW72wer0eTC9XrValrKkANJe3\nrVarUopYEG7CmlMSlFL7lVLPKaV+qZQ6q5T6fOPzbUqpHyulzjX+jrTbyE6WwxV6g/W0iY20bUHY\nCNrJPfOAf6G1vgt4P/BPlFJ3AV8AntVaHwGebSx3DBF6AdbdDrpi24KwXqxZ6LXWV7XWrzTe54A3\ngb3Ax4GvN1b7OvCJdhoowi5sNBtl24KwUXRkNIlS6iBwD/AisFNrfbXxrylg5zLbPK6UOqWUOjU7\nO3ur/XeimUKPsp720a5tr1vDBGEVtC30Sql+4PvAP9VaZ8P/04s9q0vmuGmtn9Ba36e1vm9sbKzd\nZghCx+mEbW9AMwXhlrQl9EqpGIsXwje11k82Pp5WSu1u/H83MNNeEwVh4xHbFnqJdrJuFPBV4E2t\n9X8M/esp4DON958BfrD25gnCxiO2LfQa7eTRfwD434DXlVJnGp/9KfDvgO8opT4LvAt8sr0mCsKG\nI7Yt9BRrFnqt9c+B5XrBPrTW/QpCtxHbFnoNqeEqCILQ44jQC4Ig9DiRF3ozF2h4WRDCdiCzSAnC\nzYm80IPUuhFuRGxCEFZO5KpX3qxMsW3bTbNPyTRxWw8zd7CxA9/3pUyxINyCyAn9UmWKTTnaer1O\nvV4PHtWlNO3WRGvdZAe1Wk1sQRBuQuRd4mq12jRNnNSiF6DZDgqFQjBngUEmphGE60TOo2/Ftm3i\n8TgAlmUFU8jd6kJeaiq55T4LE/7/Svex1OcrXa+1HTfbh1leybpLbbOW9oWPdbPp+ZZq03KE97Pc\n/pd77/s+lmWRSqUoFov4vk88Hse27RuOLR33grBI5IS+VXjHxsa48847mZiYYHh4GNd1qVQq4rFt\nUczvbuwgnU5z6NAhRkdHpYNWEJYhUkIf7mA1nW4HDx7kgx/8IDMzMyQSCRzHwfM8EfotivndjR2U\ny2V27tzJgQMHgOuplqbDXhCECAm9eSRXSmFZFp7nAbB3715+8zd/k1wuh+M4wQUsQr81Mb+7Ugrf\n9/E8j4GBAfbu3QsQ2I2xDcmxF4QICX0r5gLt7+9n9+7djIyMYFmWpFQKAb7v4/s+iUSCvr6+4DOT\ndikIwiKRFXrjkdXrdSqVCqVSCdu2xYsXAkyapVIqSK80nr4gCNeJrNAbjNBXKhXx6IUmjEfvOE5T\nHr149ILQTOSF3nEckskkQODRSyebYLx4rXXQSS8IwtJE9uowGTiu6zI0NEQqlQo6a6UzdusS7ow1\nBe9isRiu60qmjSAsQ2SEPhySMamVcH3AlKltIh69ADQJvamBBDdWO5VQnyBESOiXw6RbGg9fhF6A\n5tGyxi4EQViayAu98dCMlyZCL0CzRy9euyDcnMgLvcHE5c17QTA2EbYNQRBuJPJCb0I34dRKeUwX\n4LodSOhGEG7OphB6M9FEONtC2NqEq3KalyAISxNpofd9vylcE06tBPHstyLhm7yEbARhZURa6E2o\npjVlziAX+daltT692IIgLM+mSVcw3rt48QKIPQjCaoisR288NDNgygyikhi9ADSF8SzLahowFUZq\n3ghChIR+uXxoU4NeEG6G2IggLE9khB6axd68dxxHipkJy2Lsol6vBwPrwjYkCELEhH4pbNsmFot1\nuxnCJkCEXRCWpu3nXaWUrZR6VSn1dGP5kFLqRaXUuFLq20qpeJv7b7eJwhZgPexkvW1bEDaKTgQ2\nPw+8GVr+c+AvtNZ3AAvAZ9vZeWsuvVmW19Z+LWUX68C62rYgbBRthW6UUvuA/xX4t8A/V4tu1QeB\nTzdW+Trw/wB/tdJ9mgvWxFk9z8PzvE33WH6zYflGoDbbd4oq4Y7YTs0utR62LQjdot0Y/X8C/hUw\n0FgeBdJaa6+xPAnsXWpDpdTjwOMA+/fvv6EDzXSyVSoVyuVyMFXcZpomzgj6UkhIqj3CdmDbNolE\nAtd1m85rm5k4HbHtXsSUJIHrNm7Oe+vTlhAN1iz0SqmPADNa69NKqUdWu73W+gngCYCTJ08uaRW+\n71OtVsnlclSr1U2VfXOrcIIU4mqPcLZNPB4PZiPr0L47ZttKqegb6yox2XCts72ZidlrtdqmuEa3\nEu149B8APqaUehRIAIPAl4FhpZTT8Hz2AZfbaWDYQ6jX65vGozfZQmFPp9XrCU9oLawOYwdh+zCz\nTXWADbHtzUb45nor290sDtlWYc1Cr7X+IvBFgIbX8y+11v9IKfVd4PeAbwGfAX7QTgMtywrSKzfD\nDFNa66DNZrBXa7+DeVLxPK/pBiCsnNY5Yzs5YGqjbHuzsdprL+rX6lZiPfLo/wT4llLq/wVeBb66\nlp0Y8avX69RqNarValCTfjN49KVSadlOZNu2g0dfYW0YOzDndzmb6LCtdMS2Nxut53rXrl3s2bOH\neDxOuVzG8zwSiQSO45DP57l06RKZTAZojt0L3aMjQq+1/inw08b788ADq91HawkEYyDlcpnZ2VnK\n5XIwQXjUjMbEJpVSOI5DtVplamqKqakpisUisVgM27YD4R8YGGDv3r2MjY2hlKJerwdPAlH7blHF\nnPN6vU4qlcJ1Xfr7+7Esq6MhsU7Y9mbHcZwmp+X+++/nk5/8JGNjY0xPT5PL5RgbG2NkZIS33nqL\nb3zjG7zyyisAxGIxfN/H87ybHUJYZyIzMrb10dss53I5Ll++TDabDQQzah69EWvLskgkEuRyOV57\n7TXOnDlDPp+nr6+PeDxOsVikUqmwc+dO7rvvPo4ePYrjOFQqFbTW2LYtQr9CjKDXajWGhoYYGBhg\n+/bty9qRsHZaEwf27NnDAw88wJ49e5iYmCCdTrNv3z527txJIpHgb//2b5u2FZvuPpERekO4Bx+g\nUqmQzWZZWFggHo9j23bgsUUl9KGUwvM8bNsmlUqxsLDAuXPneOmll6hWqySTSZLJJJlMhnq9ztjY\nGNu3b2fXrl3EYjGKxSJaaxzHkYviFhj7sCwLz/Oo1WoopahUKoCECjaCcrnMwsICruuSTqdJp9P0\n9fXhOA6ZTIZarRasK79DNIic0LdeqCYcYjo3TZGz5apddgPTZsdxcF0Xx3Go1+tUq1VgMV5fq9WC\nG1SpVEJrTSwWIx6PB+loIvS3xvzuYS8z3N/RmtcttE/rE3Q2m+Xy5csopUin0ywsLACLdj0zM0O5\nXA7WNemXQneJnNCHCWewxGIxXNcNRD5K2SrGwzQplfF4nFQqRSKRCIzexDkB+vv7SSaTxOPxYH1A\nQjcrIOzRm1TKm5WyjlqYbzPSep25rsvAwEBg48lkkoGBAQYHBwPPPrxtVK7TrUzkhD58ISulKBaL\nXLt2jWvXrkVa6E3oxoRoSqUSsViMcrkcCJFJN7MsK/CKYrEYpVIJEKFfCWH7qNfrVCoVPM8LzmF4\n+snwsrB2WmP027dv54477qC/v5/5+XkGBwc5cOAAO3bsYGpqqmngWlSu0a1OpITeCGF4iPXMzAxn\nzpzh0qVL9Pf34zhOEAOMkhGF6+eXy2UuXboUePOm09CITz6fZ3x8PMgkiuL3iSrmHMZiMWq1GoVC\ngQMHDnDw4EGApqH5ksfdGVrDL5lMhqtXr7Jjx47gJnvt2jW01mSzWYnRR5BICT3caBjT09O88sor\nnD9/nuHh4SAcEiWPPozxNHO5XGDwWusm4y8UCpw/f57p6ekgTVBYGeZ3N3awsLDA3Nwc73//+29Y\nT+gM1Wq1yUZ/9KMfUSgUePTRR9m1axdnz57lySefZGBggGq1yszMTLCuSR0Wukukhd54CJcvX6ZY\nLFIsFpvi3psV3/eDbAVhbYTt4PLly+Ryuab/i7h0DiPyqVSKcrnM9PQ03//+97nzzjs5fPgwFy5c\n4Bvf+AZAkCxhkPz5aBA5oV+K8EUb9oyFrUtYQETUN4ZKpRKI/r333svdd9/N2NhY0/k3ZcVbkTBa\nd4l8T5XjOCQSiWBZphUUgKbMDjP8PkwUw3qbldbxKw8++CB/9Ed/xLFjxxgfH2dycjJYd3R0lIGB\ngWC5tXNc6A6R8+hbL9Bwx6zp/Q9nr0SVW+UPm1zwlawrXMeUmgjbgSlfLawPJhxjMpsOHz7Mbbfd\nxtmzZ/nKV77Cc889x44dO/jjP/5jDh8+zLe//W2eeeYZAIaHhykUCsGANqE7RE7oWwUvXCfDFFbq\nhRmawkWihNXROrnFZpyBbDNhKq0arl27xgsvvMAbb7zBc889Byw+aT/22GMcP36cn/3sZ8G6ZtS3\n0F0iJ/SCIEQD88TUGnN/7bXXuHDhAoVCIfjMPJXW6/WmJINyuRzpJ++tQuSFvldH1oXDUOLdt0cv\n2kcUCI9ZcF0X3/cpFotcuXKFK1euMDAwEJQw9jyP+fl5lFLcdddduK6L67rs2bOHK1eukM1mAemU\n7RaRF/peIWzglmUxNDTE4OAgSikKhQLpdLpp4JRcDEK3aJ2/ee/evRw9epS5uTleffXVoFM23Ddi\nwmmWZfG5z32O+++/n6GhIcbHx/nSl77E2bNngcXyCeG6T8LGIM9UG0T48dVxHPbu3cvJkye5//77\nOXToUFNmkcwnK3QTU7PJsGfPHk6ePMnhw4cDuzTTZBrBrlQqvPDCC0xPT7Nr1y4+8pGP8NBDD/HI\nI48wNDQU7Esm3OkOIvQbRKvQ7969m7vuuovjx4+zd+9eqQ8iRIpWGzST/oQ9+PDAxWw2y5e+9CU+\n97nP8fzzzwefz83NScZNBBChFwQhwHjpYRE39abOnz8fhHNMjRulFCMjIwCk02n++q//mnfeeSfY\nVsI00UBi9BtEuLPV8zyuXr3K2bNncRyHS5cuNXk9Ep8XukE4OSDM5OQks7Ozy4p2eH1TrtjQ19fX\nVBJB6A4i9BtEq9Cb+ixKKfL5fJMHFc4RF4SNwCQAmIGIQ0NDKKXIZrOUy+Um+wwnC7SGcIaHh3nt\ntdc4evQoqVSKZ599tind0vM8se0uIEK/QYSN2/d9MplMkHJmMhaWWlcQ1hsz+tzkyw8PD3P8+HEq\nlQqvv/568Hn4ZhAm/DQ6MzPDV77yFb71rW9h2zbZbJa5ubmmdcW+Nx4R+i4hefNCVAh3vMZiMQ4d\nOsThw4eZnp4Okggsy8J13aAMwnJUKhWmp6eZnp5u+jw8YZCw8YjQC8IWpXXAXiKR4LbbbmPPnj3B\nnAomJh8uRbIWpEO2u4jQd4nW9DXxdISNpjUMY1kWg4ODVKtV3n77bS5evBhMcA8rKxGulCIejwfp\nwrVaramp+tO+AAASLUlEQVS8sdAdROi7hAi7EAVMCQNYDNtYlsXc3By/+tWvgj6kcIniW6G1plqt\nNt0gxNa7jwi9IGxRbNsOsmtqtRqjo6PB5PbhgmVmesyVIsIePUToBWELEfbgbdtmcHCQoaEhPM/D\ndd0gAywejwcdrxJ22fyI0AvCFiLcN6SUwrIsYrEYsViMUqlEOp0ml8s1ibt0pG5+ROgFYQsRDqvU\n6/WmDtZCocCVK1eC+HrY+xc2N23VulFKDSulvqeUeksp9aZS6jeUUtuUUj9WSp1r/B3pVGMFYaPo\nVdtu9dQty8JxHFzXxbKstlIohejSblGzLwM/1FofA04AbwJfAJ7VWh8Bnm0sC8JmoydtO1xDPhaL\nBQXMSqUS9XqdeDwerCudqr3DmkM3Sqkh4GHgHwNoratAVSn1ceCRxmpfB34K/Ek7jRSEjaSXbTuV\nSpFKpbAsi1qtRj6fp1AooJTC87ymeLwIfe/QToz+EHAN+C9KqRPAaeDzwE6t9dXGOlPAzqU2Vko9\nDjwOsH///jaaIQgdp2O23W3CBciUUriuy/DwMLFYjGw2y9TUVFPOu9CbtBO6cYCTwF9pre8BCrQ8\nyupFC1vSLdBaP6G1vk9rfd/Y2FgbzRCEjtMx2173lt6C8JzL4aJkSxUnE3qXdoR+EpjUWr/YWP4e\nixfHtFJqN0Dj70x7TRSEDadnbDss6KaoWLi4WLhWvExh2busWei11lPAJaXU0cZHHwJ+CTwFfKbx\n2WeAH7TVQkHYYHrJtlu9dqUUjuNgWZYI+xai3Tz6/wv4plIqDpwH/g8Wbx7fUUp9FngX+GSbxxCE\nbtATtm3mevV9PygVXCgUsG2bcrnclE4pOfO9S1tCr7U+AywVh/xQO/sVhG7TK7Ydj8fp6+vDcRxq\ntRrlcrmpVrzkzW8NZGSsIPQQ4SwbWPToXdcNJg3J5/OSZbMFaXfAlCAIEcZ0vtbrdXzfl5j8FkWE\nXhB6iKVSJk2KpSliZpDO2K2DCL0g9DhhMQ/fCCSPfusgMXpB6CFs28Zxrl/WWusgy8bzvKbOVxH6\nrYMIvSD0ELZtk0wmicfjeJ5HsVgkk8mgtZYwzRZGhF4QegilFLZtY9v2DaUOxIPfukiMXhB6CJNl\nY17ixQsgQi8IPYfJrgkXNDOfi/BvTSR0Iwg9RrhwmWTZCCBCLwg9gZkS0LIsSqUS5XIZrbWUOBAA\nEXpB6AkcxyGRSASZNoIQRmL0gtADmLh8eOSrIBjEKgRhkxLuWPV9P5jzVTpchVYkdCMImxAzgYgR\nda015XK5afYoQTCI0AvCJsQMjIrFYmitqVar1Gq1bjdLiCgi9IKwSZG8eGGliNALwiZEa029Xg/e\nm1GwErYRlkKEXhA2IVprarVakCffOjhKEMKI0AvCJsGEaZRSS458FYTlEKEXhE1AuColQL1el1Gv\nwooRoReETYDWOihzYKjX6+LRCytChF4QNhFSW15YCyL0ghBxTBql7/tBrrwMjBJWgwi9IEQc27ZR\nSlGv1/F9v9vNETYhUutGECKO8ejFgxfWigi9IEQck0Ypo2CFtSJCLwgRxkwJKAjtIEIvCBElPPcr\nSKaNsHbaEnql1D9TSp1VSr2hlPqvSqmEUuqQUupFpdS4UurbSql4pxorCBtFFGzbiLzv+5IzL7TF\nmoVeKbUX+L+B+7TWxwEb+APgz4G/0FrfASwAn+1EQwVho4iKbZtiZZJtI7RLu6EbB0gqpRwgBVwF\nPgh8r/H/rwOfaPMYgtANumLbJsPGZNlIvrzQCdYs9Frry8B/AC6yeBFkgNNAWmttinBMAnuX2l4p\n9bhS6pRS6tTs7OxamyEIHaeTtr2a44bnfTVCLyIvdIJ2QjcjwMeBQ8AeoA/4nZVur7V+Qmt9n9b6\nvrGxsbU2QxA6TidtexXHbKpOKZOKCJ2knZGx/wtwQWt9DUAp9STwAWBYKeU0PJ99wOX2mykIG8qG\n23Y4s0a8eKHTtBOjvwi8XymVUotW+iHgl8BzwO811vkM8IP2migIG05XbVti80KnaSdG/yKLHVOv\nAK839vUE8CfAP1dKjQOjwFc70E5B2DC6advi0QvrQVtFzbTW/wb4Ny0fnwceaGe/gtBtumXbUtNG\nWA+keqUgRAARd2E9EaEXhAggQi+sJ1LrRhC6iKRQChuBCL0gdAkReWGjEKEXBEHocUToBaFLSFxe\n2ChE6AWhi4jYCxuBCL0gCEKPI0IvCBFAOmaF9USEXhAEoccRoReECCCxemE9EaEXhAghdeiF9UCE\nXhAiiIi90ElE6AUhQpgQjoRyhE4SKaGXx1ZhrSxlN5vVlkTkhU4TqeqVS026sNWMfi3itNXO0VKE\nbce8NzM1CRuDmdR8OVqfVsJ2ayZGv9W25r3Y/OqIjND7vo9t202fbbUfMzwp9Gq+u1l/q52vmyHn\nY+OJxWLE43GA4AYbngvXTI9o3tfrdXzfRykVbBu25dZ5dM32ZtuV/r5iBxESeuMNhD2CrRbKEXFa\nO2FbUUph2za2bW8p++kWRpwrlQqVSmXV22utqVarVKvVdWidABGJ0Yc92fAj3FYTemHtGHEHcBwH\ny7JE7DeIm4VchGgQCY9ea029XgcWH/nMY1/4fa9jRMk82azEszcC5vs+nucFj7ZbEXMOADzPo16v\nU6vV5ClpHbEsKwij2LbN3r172b59O0Dg2TvOosR4nke5XMbzvOB9Pp+nXC7jOA7bt29nx44dxGIx\narVasE+lFL7vU6lUqNVqTdtWq9XAMWwN9xiMhmwVHVmOyAi9+RGr1Sr1ep1UKkWlUgku3l7Gtm2G\nh4fZvn07w8PDxOPxQLjh+gVl/hocx0FrTSaTYXZ2lvn5+S35+Ku1plwuk8lksG2bbDaL53m4rhsI\n0VZjtU8xq1nf2GIqlSKfzwPQ19fHH/7hH/KpT30K27a5cuUKWmsGBwdRSjE3N8elS5e4du0a8/Pz\nnD9/ntOnTzM+Ps7Q0BC///u/z6c//Wl27NjBzMwM5XKZvr4+4vE4+XyeS5cuMT09TSaT4Z133uHV\nV1/l0qVLxGIxEolE8Du3fo9qtUqhUKBUKq3qfPQakRD6er1OoVDAsiyq1SqO4+C6LsViMfDKeo2w\naMfjcXbv3s19993HsWPHGBgYoFQqUa1WgxCEubi01nieh+M4JJNJarUa58+f59SpU8E20NwJ1ouE\nv1e9XieTyXD16lWKxSKZTIZ6vU48Hsf3fWq1WhdbujraDTOFvdrV7GstNwbjrcNiR+z73vc+fu3X\nfg2A22+//YZt3nnnHSYnJ4ObwPj4OACu63LnnXfy67/+6wAcOnTohm2np6eZmJjg2rVrKKWYmJhg\nZmYG13VJJpPBdRH+HlprLMuiXC7f0PZevS6WIxJCbzx6pRTVahXf96lWq4GX35patdlpvajMo+vx\n48f5wAc+wLZt24LHWtu2cRwnyE4wnV6u6zI4OEipVGJoaIirV69y4cIFMplM0zF64XwtRfh7+b5P\nqVQinU7j+z7ZbLZJ6DerR79UKGKt2y23L/P5Wo7Vel0WCoVg2ThoJgsnn8+TzWbJ5XIUi0UqlUpT\nuLZYLDbtu1wuk0gkgn1nMhlyuRyFQiEIAZkMHPOq1+tN/QUSsrlOZIS+XC4HQu84DsVikVKp1LMe\nfRhjsLVajVKpRKlUolwuUyqVlhT6Wq2G7/vEYjFKpVJw0fT6eQrTmp1l2zbxeDx4mfOzVrHsNdbj\nHLTuM5webc59eNlxHBzHCfqiwvtpTa2OxWJN/zfbhfuxzP9abcEgncTXiYTQmx/SdLw4jhMYRi/+\nWK2C7Hke09PTnD59mnQ6TV9fX9D5tNQgFBO6SSQS1Go1Ll68yMWLF5seUbea6MdiMZLJJKlUKrgR\nGsHfrDa0VnFez5DNzfYTFufWfbuui+u6xOPxJcW+Vehbl+PxOLFYrEkXwmJvWdaS14rc5BeJhNCb\nzshwjH54eBitNalU6oa7fy8QFuJqtcqVK1colUq8+eabOI7TNJhkqUwCE7uv1+sUi0XS6XRTh1Ov\nC31rjD6dTjM5ORk84oc9+s3UQd2J363dfazkKaj1vFYqFZ577jn6+vqwLIvp6WkA+vv7UUqRTqeZ\nmppifn6edDrNpUuXmJubA6BUKvHSSy/xne98h9HRUebn56lUKiSTSWKxGMVikampKWZnZ8nlckHH\nrHniN0/9S3XGmv938vxsRiIh9OZCVUpRq9WwbRutdSBevRajb8X3fXK5HPl8flUjY8PrbbXUynDs\ntVKpcO7cORKJBIlEIrAZY0e5XK6LLe0eq7WH1Vxnpl/EUCgU+PrXv853v/vd4P+mM9QsG+fFpMIa\nAc5mszz55JP88Ic/DJyX8LZGxM3n4ey8sCO0XJu30nWxHJEQ+rm5Ob75zW8CBB0qyWSSYrHIqVOn\nmjpqNmvH2q2QfO/VERb6crnMW2+9xfT0dJDNFA7ZZLPZbjWzpzH2asQ5l8ut6abq+z6FQqGpM3e1\nbRBujorCiYrFYnp0dBS4/thovNVisUihUJDec+Gm3GwUdcO77ErMTynV/QtM6GlWYtu3FHql1NeA\njwAzWuvjjc+2Ad8GDgITwCe11gtq8Ur7MvAoUAT+sdb6lVs2Qi6GphIQhlulxIWX5Yng5ix1MYht\ndxbT2QqdLWpm9idFzZZmRU5MWCSWegEPAyeBN0Kf/XvgC433XwD+vPH+UeC/Awp4P/Dirfbf2E7L\nS17r+RLbllevvlZkhys01oM0XwxvA7sb73cDbzfe/3/Ap5Za72YvpZSOx+NNL9d1dTwe17Ztd/1E\nyiv6L6WUtm17yRcsfzGwzrbd7fMir95/rUTD19oZu1NrfbXxfgrY2Xi/F7gUWm+y8dlVWlBKPQ48\nbpY3UwqcED201p3qqO+4bQtCt2k760ZrrdcSh9RaPwE8AVsrjilsHsS2hV5hrUMGp5VSuwEaf2ca\nn18G9ofW29f4TBA2C2LbQs+xVqF/CvhM4/1ngB+EPv/f1SLvBzKhx2BB2AyIbQu9xwo6k/4ri3HI\nGotxyc8Co8CzwDngfwDbGusq4D8D7wCvA/dJZoK8ovAS25ZXr75WYoeRGDAlcUxhvdEyYEroUVZi\n25uzrJ8gCIKwYkToBUEQehwRekEQhB4nEtUrgVmg0PgbNcaQdq2GKLbrQBePLba9eqRdK2dFth2J\nzlgApdQprfV93W5HK9Ku1RHVdnWTqJ4TadfqiGq7VoKEbgRBEHocEXpBEIQeJ0pC/0S3G7AM0q7V\nEdV2dZOonhNp1+qIartuSWRi9IIgCML6ECWPXhAEQVgHIiH0SqnfUUq9rZQaV0p9oYvt2K+Uek4p\n9Uul1Fml1Ocbn29TSv1YKXWu8XekC22zlVKvKqWebiwfUkq92Dhn31ZKxTe6TY12DCulvqeUeksp\n9aZS6jeicL6igNj1itsXOdvuNbvuutArpWwWi0X9LnAX8Cml1F1dao4H/Aut9V0sThf3Txpt+QLw\nrNb6CIsFr7px0X4eeDO0/OfAX2it7wAWWCzI1Q2+DPxQa30MOMFiG6NwvrqK2PWqiKJt95Zdr6Ty\n2Xq+gN8AfhRa/iLwxW63q9GWHwAfZpnp5TawHftYNKwPAk+zWElxFnCWOocb2K4h4AKNvp7Q5109\nX1F4iV2vuC2Rs+1etOuue/QsP0VbV1FKHQTuAV5k+enlNor/BPwrwG8sjwJprbXXWO7WOTsEXAP+\nS+PR+/9XSvXR/fMVBcSuV0YUbbvn7DoKQh85lFL9wPeBf6q1zob/pxdv5xuWqqSU+ggwo7U+vVHH\nXAUOcBL4K631PSwO9W96nN3o8yUsT5TsutGeqNp2z9l1FIQ+UlO0KaViLF4M39RaP9n4eLnp5TaC\nDwAfU0pNAN9i8RH3y8CwUsrUKurWOZsEJrXWLzaWv8fiBdLN8xUVxK5vTVRtu+fsOgpC/zJwpNHT\nHgf+gMVp2zYcpZQCvgq8qbX+j6F/LTe93Lqjtf6i1nqf1vogi+fmJ1rrfwQ8B/xeN9oUatsUcEkp\ndbTx0YeAX9LF8xUhxK5vQVRtuyftutudBI2OjUeBX7E4Tdu/7mI7HmTxcewXwJnG61GWmV6uC+17\nBHi68f4w8BIwDnwXcLvUpvcBpxrn7G+Akaicr26/xK5X1cZI2Xav2bWMjBUEQehxohC6EQRBENYR\nEXpBEIQeR4ReEAShxxGhFwRB6HFE6AVBEHocEXpBEIQeR4ReEAShxxGhFwRB6HH+J2W2xoyuJmxD\nAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0124e10>"
+       "<matplotlib.figure.Figure at 0x7f88457e69b0>"
       ]
      },
      "metadata": {},
@@ -3263,12 +3387,12 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.817 \n",
-      "FIRE        0.828 \n",
-      "RIGHT       0.820 \n",
-      "LEFT        0.832 (Action Taken)\n",
-      "RIGHTFIRE   0.825 \n",
-      "LEFTFIRE    0.832 \n",
+      "NOOP        0.796 \n",
+      "FIRE        0.806 (Action Taken)\n",
+      "RIGHT       0.794 \n",
+      "LEFT        0.790 \n",
+      "RIGHTFIRE   0.797 \n",
+      "LEFTFIRE    0.791 \n",
       "\n"
      ]
     }
@@ -3292,7 +3416,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3302,10 +3426,10 @@
     {
      "data": {
       "text/plain": [
-       "908"
+       "161"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3317,7 +3441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 35,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3327,9 +3451,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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pSqVCIpGgVCpx5coVO2rW9PCjRLhHn0qlmJ6eJpfLXTeeIEzzMZvRwo7j4Hke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\n7xAJoVdK2UfDIAiIxWLE43E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UHNbVaMeo0U5sez3CI5bDI2NbHWYJlyYGIjkDmdAbNIZuFhcXuXDhAsePH+fS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\nC4Ig9Dgi9IIgCD2OCL0gCEKP8/8B8s+udmS2ndkAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00c2f28>"
+       "<matplotlib.figure.Figure at 0x7f884c1334a8>"
       ]
      },
      "metadata": {},
@@ -3341,20 +3465,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        2.212 (Action Taken)\n",
-      "FIRE        2.169 \n",
-      "RIGHT       2.113 \n",
-      "LEFT        2.097 \n",
-      "RIGHTFIRE   2.161 \n",
-      "LEFTFIRE    2.157 \n",
+      "NOOP        2.008 \n",
+      "FIRE        2.006 (Action Taken)\n",
+      "RIGHT       1.995 \n",
+      "LEFT        2.014 \n",
+      "RIGHTFIRE   1.996 \n",
+      "LEFTFIRE    2.006 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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PWs/ziKKICxcukM/nmZycbLqUX0mrx3Vdm/d1HIdCoUAmkyGVStkOzSQGejM6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\nTE1N3fZ7sTxKKVKpFLlcjnw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Y/1pS48L7KqVqHpywUOVPJpM4jtPwuep7YwqtwzgE5n/NZrO8+uqrt93P2LKIfGuIhNAP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\n6Befi7weAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0345898>"
+       "<matplotlib.figure.Figure at 0x7f884c2c9c88>"
       ]
      },
      "metadata": {},
@@ -3366,20 +3490,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        2.194 \n",
-      "FIRE        2.149 \n",
-      "RIGHT       2.140 \n",
-      "LEFT        2.141 \n",
-      "RIGHTFIRE   2.198 (Action Taken)\n",
-      "LEFTFIRE    2.170 \n",
+      "NOOP        0.982 (Action Taken)\n",
+      "FIRE        0.977 \n",
+      "RIGHT       0.975 \n",
+      "LEFT        0.977 \n",
+      "RIGHTFIRE   0.968 \n",
+      "LEFTFIRE    0.980 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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YEu72GnePCW0zLeOoCb1pjZsBSxNmGab12n3ft9fT2usJgoCRkRF27NhBqVQi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\nemnRr45W2yyXy+RyOYaGhpo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nMkqg3qM3opZIJEin02QyGYBAgJcj/H06nSaZTBKLxQLhA5YN3YQzWmKxGMlk\nEtd1A2/Wdd2gltPb2xsc24R7ljt2s9fEiK3jOEG5ent7mZ6eBghi8QA9PT1BmMn8l8169Cbj6XaN\nvFFouBfWJ2F9icVipNPpoPaaSCTo7e2lv7+f+fn5IKa/1L5RIHJCH76RlVIUCgVu3LjBjRs3ui70\nAIlEglqtRjabrZvlKJxmGS6XKacpt/FIs9ksExMTuK4b1AyWE3oTukkkEszOzlIqlYKaQKPIWZbF\n3NwcExMTWJZFqVRa9tituCbhGP38/HxQFvP/mVCbCSNNTk6SzWYplUpritGH7cP3/cCrMtcw3K8h\nvCwIq6Gxc9+mTZu4//772b17N4VCgb6+Pvbv38/u3bvRWpNMJoNtG+P7USBSQh/OUjHCOTU1xenT\np7ly5QrpdBrHcYKW8E5eTBN3i8ViaK2DjBvzXbVava33GO41msvlOH/+fJBJdKffE27QLRaLTExM\nBKEgk71iyGaznDt3jkKhgGVZbb1W5qFmPPcrV66Qz+eD78K9BYvFImNjY0F7hRm/aLVCbH6rqdHk\n83l2797Nnj17AOpmmopqTrMQfRrj7PPz84yPj5NKpahUKhSLxaB9bmZmJrjPlto3CkRK6OHW2Nb1\n69c5deoUFy9eZGBggEQiQalU6qhHH8bE6guFArlcLlh/pxBB+Pt8Ps/Fixe5fv16kNGz0nOb9gAT\nEtFa14WM8vk8Fy5cYHJyclXHbgZzTXK5XF2sMmz85XKZsbExZmdnm+oLYf53Ywezs7NMT0/z6KOP\n3rKdIKwV025meO2115ienuZ3f/d3efjhh/nwww/5q7/6K5RSpNNpzp8/H2wbxXFvIi30WusgxFEo\nFCgUCsENvp6p1WpkMpkgvt9KfN9ndnaW2dnZlh+7Webn5+/YaL1SwnYwMTFxy3GjdqMJ6wtjP6aN\nq1QqceLECQ4fPswjjzzC7Ows3/ve94LtwqGbKLYLrYsAZvimDXuJQvQw2VHtJlyLEVEXWo3pnFku\nlymXy2zfvp0//MM/5Atf+ALbtm1j27ZtPPzww8H2xWKxLuQcNSLn0TdiGiEN4QwTIXp06kEczmJK\nJBKRz3oQ1hdmcD7TyP/kk0/y9a9/PdAi08Hxueee46WXXgr2i6rdRU7oGy9U+ClpWsJNI1s3Myqa\nbXBppmX+TufuZKt/eBiDxiprY2NoK8plGoDDdmCGrxaEVtFoq4lEos7hvOeee5icnGTLli0kk8ng\ngRBVIie3OZ91AAAUVUlEQVT0jQJWq9UCz82kJ5ptohgLWyntbJnvdKu/qWGZXHnTWSrcg9mUqRXl\nMg8Vc6wozkAmrG8a06QzmQxjY2Ps2rWLmZkZjh8/zuuvv86ZM2ciL/IQQaEX1g+Ns4Ldd999HDly\nhGvXrvHjH/84SD+1bfu2nckEIYqEhT6VSuH7PidPnuTrX/86r7/+OpVKhRs3btTtE1WHI/KNsVHs\nfCAsYHL7DQcOHOBzn/scjzzyCKlUKljf7gYqsQ+h1TTa9s6dO9m7dy9TU1P85V/+JRcuXODKlSuM\njIzQ29sbdPyLqtCLRy+0DNd1g0HWRHyF9Uyjg9nT0wPUp1E+9thjPPTQQ1y6dIkzZ84wMTFRt2+U\nRF+EXlgzjR7M2NgYr7/+OmNjY3V9HaJk8IKwEszYVoYPPviA06dPc+rUKQYGBkgmk/zqr/4q9957\nL6lUiitXrtQJfVQmSDKI0AtrptGQz549y/Xr12/pNSzxeWG90Zgm/PLLL/PBBx8EnTf37duHZVkU\ni8VI9oRtRIReWDONxn3z5k1u3rx5x+0EIeo0zsU8NjbG2NhY8P3Nmzd544032LNnD7lc7hanJ2o2\nL0IvCIKwDMsJ9tjYGHNzc8zPzzMyMhLZHrGGyGfdCOsHM3dA1I1eEFZKeK5oM0ua8fLn5ubIZDK3\n9A+JYqagePRCy9Ba39KIJQgbATP3QWM8PhaLRS7DZinEoxdaRmOPVUHYKBgnxgyRDgRTdRaLRXp6\neujt7QUWHgpRS0AQoRcEQVgh4fG1PM8jm81SKBTYtGkT+/fvZ3BwMPg+SiEcCd0IgiCsEc/zsG2b\n/v5+arUa169fD75rnLC+m4hHLwiCsEbMyK2lUolCoRC5kI1BPHpBEIQV0uid53I5xsbGcF03mAXP\nEKUGWhF6QRCEFdIo9O2aErTVSOhGEARhgyMevSAIQpM0ZtdEoQE2TFMevVJqQCn1HaXUL5RS7yml\nfkkpNaSU+qFS6tzi++CdjyQI0UJsW1gptm3T19fHtm3b2LlzJ5s2bSIWi3W7WHU0G7r5GvBftdb3\nAYeB94CvAC9rrQ8ALy8uC8J6Q2xbWJZwPr3v+ySTSbZs2cLOnTvZvHlz3fyyUcinX7PQK6X6gSeA\nbwBorSta6wzwNPDNxc2+CXy+2UIKQicR2xZWi+M4xONxEokEruvWCXu3RR6a8+j3AjeA/6CUeksp\n9e+UUj3AqNZ6cnGba8DoUjsrpZ5RSp1QSp1YamhbQegiLbPtDpVX6DCNMfhSqcTMzAzT09PMz8/X\n5dNHIV7fjNA7wMPAn2mtjwB5GqqyeuEXLvkrtdbPaq2Paa2PDQ8PN1EMQWg5LbPttpdU6AqN4p3N\nZpmYmODSpUtMTU1RqVTqtu222Dcj9OPAuNb6+OLyd1i4Oa4rpbYCLL5PNVdEQeg4YtvCqqhUKszP\nzzM3N0cul7tlhqpus2ah11pfA64opQ4urvoM8C7wAvClxXVfAp5vqoSC0GHEtoWNRrN59P898G2l\nVAy4CPwTFh4e/0kp9WXgQ+D3mjyHIHQDsW1hVViWhW3bwcQ7ZrjibodtoEmh11qfBpaKQ36mmeMK\nQrcR2xZWglKqTsjNuPSWZVEoFJibmwvi9Y3bdhLpGSsIgrBGwuKttSYWi9Hf34/jOCilyOVyXS7h\nAjLWjSAIwhpZykM3s6xFIWRjEI9eEAShRRQKBWZmZrBtm1KphO/7wXfdFH4RekEQhDUSFm+tNfl8\nnmKxGIR0ojImvQi9IAhCizCTiEcNidELgiBscMSjFwRBaCGWZeG6Lq7rAgsTiFcqla6GcUToBUEQ\nmqQxRz6RSJBOp7Esi3w+j+d5gdB3I59ehF4QBKHFmGGLlVKUy+WuD1UsQi8IgtBiTLhGKYXv+13P\nqRehFwRBaJKwkNdqNfL5PLVajXg8Tq1Wq/PouyH6knUjCILQIoyge55HPp9fcrjiboRxROgFQRDa\nQGNnqm4iQi8IgtAGwhOIhz9L6EYQBGEd0yjiJq0ynFffDaQxVhAEoQ3UarWgITYejwMLk5F0o+OU\nePSCIAhtQimFZVkopbqaSy8evSAIQpuo1WpUq1W01sF7NxChFwRBaANaayqVSiDw3ZyMRIReEASh\nTch49IIgCHcBSqkg46Zb4RsRekEQhDZihi2GhXRLEXpBEIQNSLd7xorQC4IgtBGTeQPdE3wRekEQ\nhDZiUiu7iXSYEgRB2OCI0AuCIGxwJHQjCILQAcxwCLAw5k0nEY9eEAShAyilcBwH27Y7Pu5NU0Kv\nlPoflVJnlVI/V0r9R6VUQim1Vyl1XCl1Xin110qpWKsKKwidQmxbaAfdGtxszUKvlNoO/A/AMa31\nxwAb+ALwx8CfaK3vAWaBL7eioILQKcS2hXbRrfFumg3dOEBSKeUAKWASeBL4zuL33wQ+3+Q5BKEb\niG0LLUVrHYx90+nwzZqFXms9AfxfwBgLN8EccBLIaK29xc3Gge1L7a+UekYpdUIpdeLmzZtrLYYg\ntJxW2nYnyiusH7TWKKWwbRvbtjt23mZCN4PA08BeYBvQA3xupftrrZ/VWh/TWh8bHh5eazEEoeW0\n0rbbVERhnWJi9J2O0zeTXvmrwCWt9Q0ApdT3gMeAAaWUs+j57AAmmi+mIHQUsW2hLZjwTadj9c3E\n6MeAR5VSKbXwePoM8C7wKvA7i9t8CXi+uSIKQscR2xZajtYa3/fxPA/P8zqaS99MjP44Cw1Tp4Az\ni8d6FvhXwD9XSp0HNgHfaEE5BaFjiG0L7SLs0XeSpnrGaq3/NfCvG1ZfBB5p5riC0G3EtoV2Eu4l\n2wnhlyEQBEEQOojJujENsp2I18sQCIIgCF2iUyEc8egFQRA6iInTdzLFUoReEAShwxih75TYS+hG\nEAShS4jQC4IgCC1BQjeCIAhdIDzIWbsRoRcEQegSncq6kdCNIAjCBkc8ekEQhC4RzrxpZ8cp8egF\nQRC6RKdSLMWjFwRB6BLSM1YQBGGD06lx6SV0IwiCsMGJlNB3Y4otYWOwlN2ILQnCApEK3SxVjen0\nAP1Cc6xFXFvxH4dtx3zuZIcUIdqsxi4bt1VKrTjEcrt9b7d/eL92aF5khL5Wq90yK7qI/PphLbUx\ncxMopVouyJ2ek1OILpZl1Y3/fjvCk3drrbEsC8uyqNVq+L4f2JT5fql9gcCuHcehVqtRrVbxPK/u\n2OFjNR4nfOxW2HFkhN6yrFvEQkI564duC2vYVszEDiu9uYWNTa1Wi0zNbql75K5pjA0/RcNTbInQ\nCyvFiDuA4ziBFydif/ci//tHRMKjN7OjQ/3TN0pPYuH2GFE1YrvSeKaJo/u+H9jAWqjVanieB4Dn\nefi+T7Va7XpNQ+ge5n9PJBKk02lc11220d7YiW3bxGKxYF0sFiMej1Mul8nlclSr1cB5aAyvWJZF\nPB4HCLbr6+vD8zympqbIZrNYloXjOLfY+1IxenMOz/Oa1sHICL2JYVUqFXzfJ5VKUS6Xg5tXiC6x\nWIzBwUFGRkbo7+/Htu064zQxTvNu1jmOQ6VSIZPJcPPmTTKZzJr+b601pVKJubk5bNsmm83ieR7x\neDx4iAh3D7Zt1024vWPHDo4cOcKWLVtwHCeIn5t3y7LwPA/P8+jr62Pr1q2BDW/fvp1du3YxOTnJ\nG2+8wdTUFOl0mlgsFtiq0a9kMsn27dtxHIdsNsvIyAgf//jHuX79Ot/61rd4/fXX6enpoa+vj1wu\nRy6XCx4wYaE394pt21SrVebm5igUCk1dk0gIve/75PN5LMuiUqngOA7xeJxCoRB4ZUJ0CDc4wYLH\ntHv3bo4ePco999xDLBajWCzieR62bd8i9L7v47ouiUSCQqHABx98wMmTJykUCsHN03iORsLrfd9n\nbm6OyclJCoUCc3Nz+L5PLBYLGsKEu4dGr72/v589e/awb98+HMcJtjEJIEopqtUqlUqFkZER9u7d\nGzgh9957L0NDQ+RyOQqFAmNjYwwMDJBMJimXy8EDo1KpkEql2LNnD0NDQwDs27ePdDpNLpfjtdde\n4+2336a3t5fh4eHggbOUExJuyK1Wq+Tz+Vt+22o1MRJCb56ISikqlQq1Wo1KpRJ4+a1ugRaao9HY\nYrEYW7du5ciRIxw7doxUKsX8/DylUolYLFYn9CakkkqlSKfTZDIZ4vE4V65c4dKlS3XnuN1/Hf6u\nVqtRLBbJZDLUajWy2Wyd0ItHf3fj+z6lUolCobCk0AOBR18oFMjlcnXe9NDQEJlMhnw+T7FYDGqK\nxoEwgl2r1ZieniaVSrFjxw7S6TQAU1NT5HK5YFsTqTBZPI2hmkanqFH/1tL2EBmhL5VKgdA7jkOh\nUKBYLIpHvw4whl4ulykWiyilKBaLwUM7nKrm+37gtdu2HWzXaNB3ojE7y8RWzatWq+G67ppvDGFj\nYdqPTKKHWWfSJ43AhtuaarVa8GCIxWJ125vQjhFkE993HCfY12D2NckljWnkcGviSWMWWXj9WoiE\n0JtqinnKOo6D67pB9oQQLRoFuVwuMz4+zvHjx7l27RrxeLwudNPY0GRuqGQySbFY5OLFi0xOTtaF\nWFbTiKqUwnVdkskkqVSKarVKrVYLBF9s6O4mnIEVi8Xq+m40Nqy6rkssFgsE3jSuxuNxHMcJtCns\nRBihj8Vi9Pb2AjA+Po7ruoyOjtLb2xvYItQnLpjaZljUw6nmrbLdSAi9bdsMDAzUxegHBgbQWpNK\npep+rHhn3adRgEulEh9++CHZbJbTp08HBryUyBoBNzef7/vkcjlmZ2epVCrLnuN2ZfB9n0wmw/j4\nOHNzc8zPz9d59OHjChufxgyV6elpzp49y9TUFLZt39IYq5QKsmB6e3t59913g9rnW2+9xdatW7lx\n4wZvv/12EJpxXTcQaWNjiUSCCxcu4LoumUyGoaEhHnjgAWZnZ/nFL37B3NwclUolCCMVCoUlQzem\nXKbW0OgArYVICL25UU2jiPkzMpkMxWJRYvQRx/M8MpkMc3NzdT3/7kRj9/DV/Lfhm7lcLnPu3DkS\niQSJRCKwGWNH8/Pza/pdwvqkUegnJiaYmpoKPOXlCPeENbYZDuOYEONSXnZYnE0ZLMsKPPlCoUC5\nXK479kqGRWhVenAkhH56eppvf/vbAMGFTCaTFAoFTpw4UZdaJA1r0aTT+erhm7lUKvGLX/yC69ev\nBzHTcG0im812rFxCdAjnoUclTbtb/YJUFDxk13X1pk2bAOqqU1prCoUC+XxeOk4Jt+V2vagXY6hd\nifkppbp/gwkbmpXY9h2FXin174HfAKa01h9bXDcE/DWwB7gM/J7WelYt3GlfA54CCsA/1lqfumMh\n5GZY94SHsDAsl/HSuH4toZvVstTNILZ9d3CnQc3CocZWDGpmGmjNeU0Mf7lBze7ECtqr7uzENMZI\nl4iZPgE8DPw8tO7/BL6y+PkrwB8vfn4K+P8ABTwKHL/T8Rf30/KSVztfYtvy2qivFdnhCo11D/U3\nw/vA1sXPW4H3Fz//P8AXl9rudi+llI7FYnWveDyuY7GYtm276xdSXtF/KaW0bdtLvmD5m4E223a3\nr4u8Nv5rJRq+1sbYUa315OLna8Do4uftwJXQduOL6yZpQCn1DPCMWZYUOKEZtF66O/kaaLltC0K3\naTrrRmut1xKH1Fo/CzwLEscUoonYtrBRWGu3q+tKqa0Ai+9Ti+sngJ2h7XYsrhOE9YLYtrDhWKvQ\nvwB8afHzl4DnQ+v/QC3wKDAXqgYLwnpAbFvYeKygMek/shCHrLIQl/wysAl4GTgHvAQMLW6rgP8b\nuACcAY5JZoK8ovAS25bXRn2txA4j0WFK4phCu9HSYUrYoKzEtmVYP0EQhA2OCL0gCMIGR4ReEARh\ngxOJ0SuBm0B+8T1qDCPlWg1RLNfuLp5bbHv1SLlWzopsOxKNsQBKqRNa62PdLkcjUq7VEdVydZOo\nXhMp1+qIarlWgoRuBEEQNjgi9IIgCBucKAn9s90uwDJIuVZHVMvVTaJ6TaRcqyOq5bojkYnRC4Ig\nCO0hSh69IAiC0AYiIfRKqc8ppd5XSp1XSn2li+XYqZR6VSn1rlLqrFLqjxbXDymlfqiUOrf4PtiF\nstlKqbeUUt9fXN6rlDq+eM3+WikV63SZFssxoJT6jlLqF0qp95RSvxSF6xUFxK5XXL7I2fZGs+uu\nC71SymZhsKhfBx4AvqiUeqBLxfGAf6G1foCF6eL+6WJZvgK8rLU+wMKAV924af8IeC+0/MfAn2it\n7wFmWRiQqxt8DfivWuv7gMMslDEK16uriF2viija9say65WMfNbOF/BLwA9Cy18Fvtrtci2W5Xng\nsywzvVwHy7GDBcN6Evg+CyMp3gScpa5hB8vVD1xisa0ntL6r1ysKL7HrFZclcra9Ee266x49y0/R\n1lWUUnuAI8Bxlp9erlP8W+BfArXF5U1ARmvtLS5365rtBW4A/2Gx6v3vlFI9dP96RQGx65URRdve\ncHYdBaGPHEqpNPBd4J9prbPh7/TC47xjqUpKqd8AprTWJzt1zlXgAA8Df6a1PsJCV/+66mynr5ew\nPFGy68XyRNW2N5xdR0HoIzVFm1LKZeFm+LbW+nuLq5ebXq4TPAb8A6XUZeA5Fqq4XwMGlFJmrKJu\nXbNxYFxrfXxx+Tss3CDdvF5RQez6zkTVtjecXUdB6H8GHFhsaY8BX2Bh2raOo5RSwDeA97TW/yb0\n1XLTy7UdrfVXtdY7tNZ7WLg2r2it/xHwKvA73ShTqGzXgCtKqYOLqz4DvEsXr1eEELu+A1G17Q1p\n191uJFhs2HgK+ICFadr+ly6W43EWqmPvAKcXX0+xzPRyXSjfp4HvL37eB7wJnAf+MxDvUpk+DpxY\nvGb/LzAYlevV7ZfY9arKGCnb3mh2LT1jBUEQNjhRCN0IgiAIbUSEXhAEYYMjQi8IgrDBEaEXBEHY\n4IjQC4IgbHBE6AVBEDY4IvSCIAgbHBF6QRCEDc7/D6qIPhWEUsTZAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0080668>"
+       "<matplotlib.figure.Figure at 0x7f884c0d1748>"
       ]
      },
      "metadata": {},
@@ -3391,20 +3515,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        2.028 \n",
-      "FIRE        2.058 \n",
-      "RIGHT       2.083 \n",
-      "LEFT        2.100 (Action Taken)\n",
-      "RIGHTFIRE   2.095 \n",
-      "LEFTFIRE    2.084 \n",
+      "NOOP        1.048 \n",
+      "FIRE        1.047 \n",
+      "RIGHT       1.052 (Action Taken)\n",
+      "LEFT        1.032 \n",
+      "RIGHTFIRE   1.043 \n",
+      "LEFTFIRE    1.043 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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y8803c//995NIJDhx4gQnTpygXC6jlCKRSAAfZN2YcIXp+ocV4436vm//9zyP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\nDd1EgaRSKgqkgGHgE8CP5t/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SKWKxWODNxmKxoJbT29sbHNuEe9Y6drPXxIit4zhBuXp7e5mbmwMIYvEAPT09\nQZjJ/JfNevQm4+lmjbxRaLgXtj+O4wThyGq1Gth7T08PxWIRx6mX0qg5GpET+vCNrJSiWCwyMzPD\nzMxMx4UeIJlM4vs+uVyubpajcJpluFymnKbcxiPN5XJMTk4Si8WCmsFaQm9CN8lkkoWFBcrlclAT\naBQ5y7JYXFxkcnISy7ICT6MdQt8Yo8/n88F1MP+fCbWZMNLU1BS5XI5yubypGH3YPjzPC7KfzDUM\n92sIrwvCRgiHjwH6+/vZt28fo6OjlEolenp62L17N2NjY8CyLjTuHyUiJfThLBUjGNevX+f06dNc\nvnyZTCaD4zjUarVg+63CZNTE43G01kHGjfmuVqvd1HsM9xpdWlpiYmIiyCS61e8JN+iWSiUmJyeD\nUFBjj7xcLse5c+coFotYltXWa2UeasZzv3z5MoVCIfjOVG1hOVx16dKloL3CjF+0USE2v9XUaAqF\nAvv27WP//v0AdTNNRS3FTdg+NNpNoVBgZmaGZDKJ67pUKhXm5+cDp83cZ2vt32kiJfRw4wW6du0a\n7777LufPn2dgYIBkMkm5XN5Sjz6MidUXi0WWlpaCz28VIgh/XygUOH/+PNeuXQsyetZ7btMeYEIi\npvt1+Ng///nPmZqa2tCxm8Fck6WlpSBGD9QZf6VS4dKlSywsLDTVF8L878YOFhYWmJub4/HHH79h\nO0HYLCZUa/jZz35GLpfj6aef5q677uLatWu8+uqrKKVIpVJMTn7WSTo8smpUiLTQa62DEEexWKRY\nLAY3+HbG932y2WwQ328lnuexsLDAwsJCy4/dLPl8/paN1uslbAeTk5M3HDdqN5qwvQjXHGHZafnk\nk084dOgQ9957L/l8nr/6q78KtguPs2Rq/1FiWwQwwxetsYok3J6EazFRu6mE7Y/J7DLDduzYsYPn\nn3+eZ599luHhYYaGhjh8+HCwvQmlRrVNKHIefSOmEdIQzjARbl/CWUzJZDLyWQ/C9sLYk8mPf/jh\nh/md3/kd7r///iBM4zgOr7/+OidPngRubMCNEpET+sYLFW6YNZkcppGtk0/PZqtnzRjFrc7dKYPb\ninKZBuCwHZjhqwWhlYRtynRYHB4exvM8CoUCc3NzDA4Okkgk6vrJRJHICX2jUPi+H3huJj3RbLOd\nc6TbGceLYowQWleu8NDEQCRnIBO2N412Wi6XmZmZYWJiggsXLvDhhx9y5swZLly4EHmRhwgKvSAI\nQqcxMXrRwitHAAAT90lEQVTDzp072bdvH5cvX+Zb3/oW77zzDrZtBynWEF0HC7ZBY2yU415CNBD7\nEFqNGe7bcOedd/LII4+QTCb54Q9/yNzcHNevX2doaIhUKhXYYFRrlpEXekEQhK2m0cE0w5Sk0+ng\nsyNHjvDEE0/wwAMPMDQ0VLdv1LJvJHQjNE34poiqRyMIGyHcqxvg008/5d133+Wtt96ir68P13V5\n9NFH2bdvH7Ztc+3atWCMpyhGIUTohaZpx3j3gtBJzKivsBzGeeONN/jggw+YmpqiVCqxb98+lFKU\nSqVt4dyI0AtNs90nThaE1TCOi5loaGJiIvgul8tx9uxZ5ufnIz9EMYjQC4Ig3EB4+s/VuH79OoVC\ngUKhwMDAQORCNY2I0AsbpnGSj9HRUcbHxymXy1y6dKluyGDx9IXtRHgIbK01Y2NjHD58mGq1yrlz\n5+omAC8UCiwtLTEwMFDnxUcxRh+tpmFhW2AmGzHcdddd/Pqv/zrPPPMMAwMDweeNwxIIQtSJxWJ1\nQ658/vOf54/+6I/4vd/7PZLJ5A1hGdNrP+qI0AsbZrXOJMeOHePIkSN16WdRSzEThFth23YwYiXA\nPffcw9GjR/nSl75UZ899fX3BXBLVapVEIhHYvu/7kRuPS+5EYcM09gAsl8vMz8+zuLgoo0oK25pG\n2zbDX09PT9dtZ8S8UChQLpfp6+tj165dZDKZYJsohXCkbi1smMa4+8TEBK+88gqLi4t1XcKj5tUI\nwq1onLHt+PHj/P7v/z6Tk5N1tm3aoczgiplMBq01CwsLdRMSRQURemHDaK3rRPzChQtMT0/jeV7d\nDFM3myxdEKKI67p1dnvy5Enef/99PM8LhiyGz5wYE6OvVquUy+XI2rwIvdA0lUqlbgQ/matV2O6Y\nIdE9zwu8d/hsrmJDqVTi2rVrOI5zw30QpXtAhF5oOVEycEHYDGulBTfOcLe0tBTJUE0jIvRC01iW\nhW3bQUhHhF7oFhzHIZFI4Ps+5XI5sO3tVmsVoReaRoZAELqVxpi9YTWRb+xIGCWaSq9USg0opb6n\nlPpIKXVWKfWEUmpIKfWqUurcyutgqworCFuF2LawXizLoqenh5GREXbs2EF/f39dLn4UaDaP/pvA\nD7XW9wAPAWeBrwOvaa0PA6+trAvCdkNsW1iTcH687/skEgkGBwcZHR1lcHCwTuijkE+/aaFXSvUD\nTwHfBtBaV7XWWeB54Dsrm30H+HKzhRSErURsW9gotm0Tj8eJx+M4jtNxYW+kGY/+ADAD/Gel1Cml\n1H9USvUAY1rrqZVtpoGx1XZWSr2glDqhlDoxOzvbRDEEoeW0zLa3qLxCh6lWq+TzeXK5HMVi8YY2\nq07H7ZsRegd4BPiW1vooUKChKquXf92qv1Br/aLW+pjW+tjIyEgTxRCEltMy2257SYWO0CjchUKB\n69evMz09zcLCQl0aZqdFHpoT+ivAFa312yvr32P55rimlBoHWHm93lwRBWHLEdsWNoTrupRKJZaW\nliiVSpHrIbtpoddaTwOXlVJ3r3z0ReBD4CXgqyuffRX4QVMlFIQtRmxb6DaazaP/P4DvKqXiwHng\nH7L88PivSqmvAZ8Cv9XkOQShE4htCxtCKYVt28Fwxp7n4ft+JEI3TQm91vo0sFoc8ovNHFcQOo3Y\ntrAZkskkqVQKy7Iol8sUCoVIhHGkZ6wgCMImaRwKwXEcenp6ghTL8IiWnRw2QSYeEQRBaCFa6yBk\nE4WwDYhHLwiCsGnCQq61plKpkMvlsCyLWq1Wl0/fSdEXoRcEQWgR5XKZSqUShGnEoxcEQegyoiTu\nYSRGLwiC0OWIRy8IgtBClFI4joPjLMur53nUajWJ0QuCIHQT8Xi8Lp/e87xgQvFOIEIvCILQJI05\n8mbYYvhsovFOIkIvCILQJI1hGROuUUpFYhgEEXpBEIQWorUOJhKPxWJorcWjFwRB6BZMCMfzPEql\nUiSmEQRJrxQEQWgrjfH7Tgi/CL0gCEKLWE3QG0M3nYjXi9ALgiC0Cc/z0FrjOA62bXesHCL0giAI\nbcD3fXzfRylFLBYjFot1LF4vQi8IgtAGTENs49IJJOtGEAShTfi+H0w84rpux/LpRegFQRDagNYa\n13WDOL2MdSMIgtCFdFrgDSL0giAIbSYWiwGdC99IY6wgCEIbsSwrSK+UrBtBEIQupdPhGwndCIIg\ntJFw5o1k3QiCIHQpRug7hYRuBEEQuhwRekEQhC5HQjeCIAhbQHgIBN/3t/TcIvSCIAhbhBnBcqs7\nUjUVulFK/Z5S6oxS6gOl1H9RSiWVUgeUUm8rpSaUUn+qlIq3qrCCsFWIbQutJuzRb3X2zaaFXim1\nG/g/gWNa6yOADfw28AfAH2qt7wQWgK+1oqCCsFWIbQvtwHjxnZhDttnGWAdIKaUcIA1MAc8A31v5\n/jvAl5s8hyB0ArFtoeWY2Py2EXqt9STwb4FLLN8Ei8BJIKu1NkmjV4Ddq+2vlHpBKXVCKXVidnZ2\ns8UQhJbTStveivIK24NwuMayLCxr65IemwndDALPAweAXUAP8Mvr3V9r/aLW+pjW+tjIyMhmiyEI\nLaeVtt2mIgrbmE5MQtLMI+V/By5orWe01jXgz4BfAAZWqrsAe4DJJssoCFuN2LbQFkyM3kwzuFU0\nI/SXgMeVUmm1/Gj6IvAh8BPgN1e2+Srwg+aKKAhbjti20Ba01nieh+/72yO9Umv9NssNU+8C768c\n60XgXwD/VCk1AQwD325BOQVhyxDbFtpFOPNmK2mqw5TW+l8B/6rh4/PAY80cVxA6jdi20E4ac+rb\nLfwy1o0gCMIWopQKsm62qkFWhF4QBKHLkbFuBEEQthCTdbNd0isFQRCETbCtBjUTBEEQNocIvSAI\ngtAyROgFQRA6xFaFcEToBUEQOsRWhW9E6AVBELocEXpBEIQOshUjWYrQC4IgdAjpGSsIgtDlbFWM\nXnrGCoIgdBDJuhEEQRCaJlJCv9XTawndw2p2I7YkCMtEKnSzWueBrR6gX2gvmxHf9dhA2HbCkzts\n5XRtQnTZ7EN/vc7nWh2f1rN/477t0LzICL3v+9i2XfeZiHz30GxtbaO20IlZfIRoYsZ/v5UNaq1v\n2MayLGzbrpskRClVt63Wmlqthud5dZ8ppXAcB8uybtjXHFtrjeu6VKvVG44ZLlezREboV/sjJJTT\nPbRbeMO2opTCtu26G1S4fTHztHaCarW67m2VUm2rgUYiRm9uUrOYJ6AIvbBejLgDgRclYi8Iy0TC\now8/cX3fD55q4ffC9iXsYYersbfax2zneR6u6950H9/3cV0XANd18TyPWq0mIRyBeDxOKpXCcW6U\nu8Z5W23bJhaLBevJZJJMJkM8Hg/0qDE0U6vVyGazFAoFHMfBtm1c18W2bfr7+0mn0zfsCwTnmZ2d\nZXp6mmq1SiwWu8Gz9zyvaRuOjNDXarUgVuV5Hul0mkqlEty8wvYlnU4zPDzMyMgI6XQaIPhfLcsK\njDr83njlxWKR+fl5ZmZmyOfzwTHDXrrWmnK5zOLiIrZtk8vlcF2XRCKB7/sdq7YLnSFsRwCjo6Mc\nOnSIoaGhunZArXUQMjbORG9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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0165cc0>"
+       "<matplotlib.figure.Figure at 0x7f884c14f908>"
       ]
      },
      "metadata": {},
@@ -3416,20 +3540,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.979 \n",
-      "FIRE        0.992 \n",
-      "RIGHT       1.000 \n",
-      "LEFT        0.997 \n",
-      "RIGHTFIRE   1.001 (Action Taken)\n",
-      "LEFTFIRE    0.995 \n",
+      "NOOP        1.053 (Action Taken)\n",
+      "FIRE        1.058 \n",
+      "RIGHT       1.056 \n",
+      "LEFT        1.051 \n",
+      "RIGHTFIRE   1.058 \n",
+      "LEFTFIRE    1.055 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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P8vd///eMjY3ZY/jDPoLQSDMe/QPAP1NKfRqIMxfH/DrQo5SKzHs+g8BIMwVc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\nQi8IgtDm/P+4HHIR/f5GqwAAAABJRU5ErkJggg==\n",
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PhR4gmUzau7g5vvGYATtA2fx9TLuNR5rP55mamiIWi9mewWpCbwwrmUwyNzdH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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00f9b70>"
+       "<matplotlib.figure.Figure at 0x7f884c256908>"
       ]
      },
      "metadata": {},
@@ -3441,12 +3565,12 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.024 \n",
-      "FIRE        1.026 \n",
-      "RIGHT       1.013 \n",
-      "LEFT        1.027 (Action Taken)\n",
-      "RIGHTFIRE   1.040 \n",
-      "LEFTFIRE    1.022 \n",
+      "NOOP        1.050 (Action Taken)\n",
+      "FIRE        1.028 \n",
+      "RIGHT       1.035 \n",
+      "LEFT        1.041 \n",
+      "RIGHTFIRE   1.022 \n",
+      "LEFTFIRE    1.043 \n",
       "\n"
      ]
     }
@@ -3470,7 +3594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3480,10 +3604,10 @@
     {
      "data": {
       "text/plain": [
-       "201"
+       "217"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3495,7 +3619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3505,9 +3629,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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zEuiFEKLPSY5eCLGhwmkarfWKna9i60igF0JsKBPolVL4vi+BPQIk0AshOmJZ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\nGZxRSu0CaPx7pfH+NLAv9Lm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QoorXcGq1GufPn4+8ejN+0VaF2PxWU6MpFovceOONHDlyBKBhpql+97kQBo94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\nAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01bb048>"
+       "<matplotlib.figure.Figure at 0x7f884c278908>"
       ]
      },
      "metadata": {},
@@ -3519,20 +3643,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.293 (Action Taken)\n",
-      "FIRE        0.179 \n",
-      "RIGHT       0.225 \n",
-      "LEFT        0.261 \n",
-      "RIGHTFIRE   0.236 \n",
-      "LEFTFIRE    0.279 \n",
+      "NOOP        0.531 \n",
+      "FIRE        0.466 \n",
+      "RIGHT       0.695 (Action Taken)\n",
+      "LEFT        0.507 \n",
+      "RIGHTFIRE   0.407 \n",
+      "LEFTFIRE    0.543 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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rpWokyHeHBHohREcFx8TLiJpwkNSNEKItSiksa+1QIkG++6RFL4Roi2nBK6XQ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\nXAR+AIw23quA/w28DZwFHpS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adGr/grCbiYTQW5a1rXn0wkqiEhrpRjmiMpa9IPSKSAi9jFondJMoPMAEoZdEQuhh7R5y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\nOSL0giAIfc7/D4oTSAUqWcXyAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01406a0>"
+       "<matplotlib.figure.Figure at 0x7f884c1e1860>"
       ]
      },
      "metadata": {},
@@ -3544,20 +3668,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.160 \n",
-      "FIRE        -0.055 \n",
-      "RIGHT       0.183 (Action Taken)\n",
-      "LEFT        -0.004 \n",
-      "RIGHTFIRE   0.082 \n",
-      "LEFTFIRE    0.259 \n",
+      "NOOP        0.462 \n",
+      "FIRE        0.746 (Action Taken)\n",
+      "RIGHT       0.673 \n",
+      "LEFT        0.544 \n",
+      "RIGHTFIRE   0.561 \n",
+      "LEFTFIRE    0.626 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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1BPgukxa9EKIjSqkNO1slwMeDBHohRMfaA7204uNFAr0QQvQ5CfRCCNHnJNAL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\nQohdEItAr5T6JaXUa0qpC0q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Dhw8DNM001e8+F8LgYYQeVjsVUSZSQg+rb9rMzAyvv/4658+fZ3R0lGQySaVS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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00b1f28>"
+       "<matplotlib.figure.Figure at 0x7f884c07aa90>"
       ]
      },
      "metadata": {},
@@ -3569,20 +3693,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.157 (Action Taken)\n",
-      "FIRE        -0.030 \n",
-      "RIGHT       0.069 \n",
-      "LEFT        -0.042 \n",
-      "RIGHTFIRE   0.093 \n",
-      "LEFTFIRE    0.103 \n",
+      "NOOP        0.258 \n",
+      "FIRE        0.317 \n",
+      "RIGHT       0.035 \n",
+      "LEFT        0.463 (Action Taken)\n",
+      "RIGHTFIRE   0.183 \n",
+      "LEFTFIRE    0.227 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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lNXql1KbRBB8PmuiVUh1rH1Gjtfh40USvlFJ9ThO9Ukr1OU30SqlV0xOfepMm\neqXUiqJJ/UZJXtvj402HVyqlViQiOI6jibzHaY1eKXVT2lzT2zTRK6VUn9OmG6VU6GY1dx0f35s0\n0SulQo7jhMm+Palrku9dHTXdiMi/F5E3ROR1EflzEUmLyAEROSwiZ0Xk2yKS3KjCKrVVtltsO46D\n67rhyJposq/X69TrdU3yPWzdiV5EdgP/DnjYGHM/4AK/DnwV+CNjzB3APPDFjSioUltlu8W2iOC6\nLq7rArQk9uhN9a5OO2M9ICMiHpAFLgCfAr7TfP0bwOc7XIdS3dCXse04DolEgmQyGSZ2uDZG3hhD\nEARag+8z6070xpgZ4H8A52nsBDngKLBgjPGbb5sGdi+3vIg8KSJHROTI7Ozseouh1IbbyNjeivKu\nheM4eJ6H53lhU020eaZerwPaHt9vOmm6GQU+BxwAbgUGgF9Y7fLGmKeMMQ8bYx4eHx9fbzGU2nAb\nGdubVMQNFwQBQRBocu9TnTTd/DPgXWPMFWNMDfhr4FFgpHm4C7AHmOmwjEpttb6M7eVG07R3uqr+\n1EmiPw98XESy0oiWTwMngReBX22+5wngu50VUakt1zex7bouyWSSZDJJIpFYdmSN6n+dtNEfptEx\ndQw40fysp4DfB35HRM4CY8DTG1BOpbZML8e2nZvGsp2vqVSKRCIBaDPNdtTRCVPGmD8A/qDt6XeA\nRzr5XKW6rVdi23amWp7nkUgk8H2farVKvV4Pk7/tbPV9P1xWm2u2Bz0zVqke1l4rtzV4+3wQBNRq\ntTDBR2vyWqPfPjTRK9Vn2hN4tVoNa/Sa3LcnTfRK9SB7Nitw0/Z2exKU2r50mmKlekR0lIzrumSz\nWbLZbEvnq46oUcvRGr1SMRZN2NFau22Lb+9MrdfrVKvV62rw7Z22anvRRK9UjN0oOUenLLBqtRq1\nWu265TTJb2+a6JWKiZVq71YqlcIYEw6bBFqabVZaTilto1cqJm40JbDrugwNDTE0NITruiuOoNG2\nebUcrdErFUMiQiaTCYdFplIpstksvu/jui7VapVyuYzjOFqLVzeliV6pGBIRstksw8PDwLVpC6rV\napjYy+XydZ2smvTVcjTRK9Ul7Ul6ZGSEZDJJLpejUqkgIgwODuK6Lvl8nkKhQKFQCKcwAE3sanU0\n0SvVJe2JfseOHezYsYN6vU6lUqFcLlMqlfA8j2KxyOLiItVqddlllboRTfRKxYi9SDfA4uIiV65c\nwXEcSqUkUtd1AAAMY0lEQVQSlUql5b2a7NVqaaJXKibsxT+iFwOZn59f8b1KrVashlfqqdtqvZaL\nm16LJdd1SafTLRftVmojxKpGv9wY4q2uuawnOWjtqvuisRMdjx73+dajzS+VSoVCoRC2wwMtE5e1\nL9ceqzeK3fYx+mtZ/kbj+1VviE2ir9fr19VktjKwOj2a0J0gXnohMdlmGht3ly9fZnZ2FoBEIhE+\nHwTBdfHpOA6e5133XLTZJ/qa7/v4vh+u0/O8665EFV0WriX+er1OrVYjCILY/3Cq5cUm0dtAiwbn\nVjbl9EJiUCuLxoqdwtdeHzXOojFnv8Nyc9W0vzd6paj10GmLt5dYtNFHp1aNXvNS2+zVakXnZ7e1\n1bgn+/ZyfehDH+KBBx5g165dXSqR6lexqNFHL4wQnZFvudn5NkO0Bmh/ZG5Wu48e5tqzFvWwtnui\nNVx7yTxbM47rkZptnqlUKiSTSW655Rb27duH4zhUKhWCICCdTrO0tESlUiGdTuN5HvV6nWQyydDQ\nUHjZQNuRa6dECIIgjOkgCCgUCiwsLFAsFkkkEgwPD5NOp8OyRC8e3j5hWqlUYn5+nnw+T7lc3voN\npToWm0Rfq9XCCxoHQUA2m6VSqXR0eLpamUyG8fFxxsfHyWazAOF67Vwj7fftTlQsFpmfn+fKlSsU\nCoXYJpV+ZoyhXC6Ty+XCs0h93yeVSlGv12PbTJFKpRgaGgqTsq3Y7N+/n71795JMJsnn85w+fZp8\nPs/4+DipVIpyucz+/ft59NFHmZqaolQqMTQ0xP79+xkeHqZSqVAqlUilUgwODlIoFHjllVf4wQ9+\nwJtvvsn4+DiPPfYYd911F77v4zgO+/btY3JykiAIWFpawnVdBgYGMMZw6tQpfvCDH/B3f/d3vPvu\nu2GMR/cHFW+xSPQ2uBzHoVqt4nkeqVSKYrG4YntlJ9oDdHh4mHvvvZcHHniA3bt3Y4yhVCpRr9db\nLrQsIuEPgK1dzc7O8vrrr3P06FGWlpbCpKI7weaKxkQQBORyOS5cuECxWCSXyxEEAclkMuxIjIP2\nE5xc1yWTyYRJ3vd9yuUyk5OTjIyMkEgkWFxcJJPJkMvlqFar4XfbtWsXDz74IHfccQeLi4uMjIyw\nb9++FdftOA6nTp1ienqayclJ7r//fh555BGq1Squ63LvvfeuuOzExATvvPMOx44da/kOcW0SU9eL\nRaK3NXoRCefarlarYS1/oydtag/QgYEBDhw4wMc+9jHuuecejDHk8/nwEDlag7FD3wYGBkin07z3\n3ntUq1XefvttpqenV1yH2ljtHZOlUomFhQXq9Tr5fL4l0ce1Rg/XOkWjMeY4TljJyWaz3H///VSr\nVd544w3Onz8f7hf2R81WkuyRATQuQGKbYgAKhQLlcjnct4rFIvl8nlqthuM45HK5cAK1er3eMiIn\nl8tRLpdvem1aFV+xSfR2Jj5boy8Wi5RKpU2p0S+3ft/3w0Peer0e7hTRHdFxnLA8ti20XC63zCio\ntkb76CzXdUkmk+EtejQW1x9dG0e2fHYIpG1zt4l7YGCA4eFh9u3bFybcPXv2kMlkAMLvHh2eHE3y\n0Oigth3TtqPa87ywDNFl2y9m0j4UU/WeWCR6O65XRKjX63ieRyKR2LQAa29SKRQKnDlzhkQiwenT\np8MEbne49mWNMWHn1dzcHKdPn2Zubq7lczXxbx0RIZFIkMlkyGaz1Gq18GisvXYaR57n4ft+OLeN\nndzMlj+fzzM5OclHP/pRPvaxj+H7PsPDw4yOjoYxavuWVpJIJFoSfSKRIJlMho/tj8ZyUqmUJvse\nF4tE77ouIyMjLW30IyMjGGOWvcp9p9qTcD6f58033+TChQtkMpmWUUDt64u2T7quS6VSIZ/Pk8vl\nWhK9ts9vrvY2+oWFBaanp8nlchQKhZYaffRM025qj7tqtUqhUCCZTFKr1ahWq5RKJYwxzM3NhR3K\n9957L+Pj49x9993s2bMH13U5c+YML7/8MufOnSOVSrF792527dpFOp0Oj04TiQQDAwMsLS3x2muv\nhRUSgJdeeonp6enwZKwjR44wNjYWNoM5jkM2m8UYw9mzZzl27Nh18+5oZaZ3xCLR2x3Vniziui7G\nGBYWFsLAtzYjuGzzy+zs7HVnB96I7ZjqhVPt+010e1cqFc6cOUM6nSadTocxY+OoUCh0saQrK5fL\n4bzzNoYKhQK5XI5arUalUmFiYoKpqSmMMeRyOTKZDJlMhpMnT/L1r3+d48ePk06nGRsbC5t+2s94\nte3ylUqFWq3GxYsXOXv2bMtAg2iNvb2z1XYSVyqV6/pGVG+IRaK/evUq3/zmN4FG0reHksVikSNH\njlAsFsP3blbHmgZtb4n+v8rlMm+++SaXLl0KE1u0ySafz3ermDe03Bj/IAhYXFwMH1++fJlXX32V\nWq1GOp0mk8mQTqc5ceIEx48fBxrff2ZmZtXrtVeqUtuHxOHwK5FImLGxMeDaHB22llMsFllaWtJE\nrG7oRmdRN/tVutIjKyId72DtZ/iKSHhCmFKrie2bJnoR+TPgF4HLxpj7m8/tBL4N7AfOAb9mjJmX\nRiR+DXgcKAL/yhhz7KaF2ICdoVPRKRis1YzY0Jn9esNyO0McYjtaqYk+Z5O7HW68HDsO3x7B2DO7\nbTxGP9v+MKx2UrNo3OukZvG2qkpMNFEtdwMOAQ8Cr0ee++/Al5v3vwx8tXn/ceB7gAAfBw7f7POb\nyxm96W0zbxrbeuvX26ricJXBup/WneE0MNW8PwWcbt7/P8AXlnvfjW4iYpLJZMstlUqZZDJpXNft\n+obUW/xvImJc1132BivvDGxybG/Ed/M8z6RSKZNOp00mkzHZbNYkk8mub3O9xeO2mhy+3s7YSWPM\nheb9i8Bk8/5u4P3I+6abz12gjYg8CTxpH2vnkOqEbZ7YABse252yo2mUWq+OR90YY8x62tiNMU8B\nT0E82uiVaqexrfrFek91uyQiUwDNv5ebz88AeyPv29N8TqleobGt+s56E/0zwBPN+08A3408/y+l\n4eNALnIYrFQv0NhW/WcVnUl/TqMdskajXfKLwBjwPHAG+H/AzuZ7BfhfwNvACeBhHZmgtzjcNLb1\n1q+31cRhLE6Y0nZMtdlMD58wpdSNrCa2dTo6pZTqc5rolVKqz2miV0qpPheL2SuBWWCp+TduxtFy\nrUUcy7Wvi+vW2F47LdfqrSq2Y9EZCyAiR4wxD3e7HO20XGsT13J1U1y3iZZrbeJartXQphullOpz\nmuiVUqrPxSnRP9XtAqxAy7U2cS1XN8V1m2i51iau5bqp2LTRK6WU2hxxqtErpZTaBLFI9CLyCyJy\nWkTOisiXu1iOvSLyooicFJE3RORLzed3isgPReRM8+9oF8rmishPROTZ5uMDInK4uc2+LSLJrS5T\nsxwjIvIdEXlTRE6JyM/EYXvFgcb1qssXu9jut7jueqIXEZfGZFGfBe4DviAi93WpOD7wu8aY+2hc\nLu63mmX5MvC8MeZOGhNedWOn/RJwKvL4q8AfGWPuAOZpTMjVDV8Dvm+MuQc4SKOMcdheXaVxvSZx\njO3+iuvVzHy2mTfgZ4C/jTz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SQg83nrRr165x6tQpzp8/z+joKMlkknK53FOPPoyJ1ReLRVZXV4PlN3tsC39f\nKBQ4f/48165dCzJ6Nnts0x8QTmMMC2qhUOC9995jdnZ2S/tuB3NOCoVCg9CHvXvXdbly5QrZbLat\nsRDm/27sYHl5mcXFRR566KEb1hOEbhLup4o6kRZ6M6x+ZmYmKHdrLvBBxvd9stlsEN/vJJ7nsby8\nzPLycsf3vVVahW7MU1C7hO1gZmbmhs5wEXqh25in/EGwtcgJfSvCJ9KEIoRbm/BTzCBcaMLg0+y5\nm3pNgyD2ke+pMp2QBplWUIA1uzAkk8mGzyDplULnCWfZhEd+R13kIYIeffMFGu6YNb3c4WH4/aLd\nu3g7sb2bHbtfccNetMt0AIftoDl/XxC6wXo1bcw4jigLf+SEvvkk+b4fPKY3n8go563ejG4+7kX1\nUbJT7WoekRjFGciEnUe45IF5b0qGm0SJarUayWsvckIvCIIQRcJCbwg/XUY5AyfyQh/lkydEA7EP\noVc0P5Wa9OZw4cMoEnmhFwRBiAKt4vPhUtxRFXkQoRcEQdgU680VMQiI0AuCINyEm5W/NjWnejVf\n81aJfB69IAhC1DE1nDo0OX3HEaEXBEHoAFFNawYJ3QiCIGyKjUTcjOWIYtgGROgFQRBuys08dZNi\nGVWPXkI3giAIHcCUZQlPbRkVROgFQRA6RCKRaFlkr9+I0AuCIHQApRSxWGzDOYz7RbRuO4IgCBHi\nZvnzzZjqqlGL1YvQC4IgtGCrcXatNZVKJRg4FSVE6AVBEFqwnXmpwzOfRQkRekEQhHWIWghmu0Sr\nx0AQBEHoOG0JvVJqVCn1PaXU20qpt5RSH1VKjSulfqSUOlf/O9apxgpCrxDbFraLUopkMkkqlYpM\n7Zt2PfpvAv9Xa303cAJ4C/g68LzW+hjwfP2zIAwaYtvCpgnH8o3Qp9Pphnz6fg6i2rbQK6VGgEeA\nbwForata6yzwReA79dW+A3yp3UYKQi8R2xbaxbbtSOXTt9OKo8B14L8ppU4rpf6rUmoI2Ku1nq2v\nMwfsbbWxUupJpdRJpdTJhYWFNpohCB2nY7bdo/YKfaa507ZSqVAqlajVan1qUSPtCH0MuA/4fa31\nvUCBpkdZvfbrW3Zba62f0lo/oLV+YHJyso1mCELH6Zhtd72lQuTwfZ9isUg+n29It+xnBk87Qn8F\nuKK1frn++XusXRzXlFL7Aep/59troiD0HLFtoS3MCFnbtiMRvtl2C7TWc8BlpdRd9UWfAt4EngGe\nqC97AviszOgSAAAUk0lEQVR+Wy0UhB4jti20g1KKVCrF6OgoY2NjDA0N9V3s2x0w9feBp5VSceA8\n8HdYu3n8D6XU14D3ga+0eQxB6Adi28KmCde3CQu9ZVnk83kqlQrVavWGdXtFW0KvtT4DtIpDfqqd\n/QpCvxHbFtrF930sy0Ip1ff69FICQRAEoU3CHrrWmnK5HIh7qVSiUqn0q2mACL0gCEJHMUJfqVTQ\nWuP7/g3f9xoRekEQhA5jxN2yrKAUguu6VKvVG4S/F4jQC4IgdIhwR6tlWYyNjTEyMoJSinw+z/Ly\nciD0veyU7X+CpyAIwg4kFosxNDTErl27SKVSfZ1HVjx6QRCELuD7PrVaLQjX9CNkYxChFwRB6BDh\nUIzruiwvL6O1JpPJEIvF+pZmKaEbQRCEDmNGwpbLZfL5PLZtMzQ01LeyxeLRC4IgdJiwiPu+j+M4\nWJbVUApBhF4QBGGACYdwlFJBueJwnL6X+fQi9IIgCB0mLOi1Wo35+XmUUnie13KdbiNCLwiC0EVq\ntRrLy8t9bYN0xgqCIOxwxKMXBEHoAaYzVmvdEMLpBSL0giAIXSJc5iCdTjM5OYnneczNzQUdtJZl\ndT1eL0IvCILQBcxUgmbe2GQyyZEjR3Bdl2w2K0IvCIKw07Asi3g8jmVZPa97I0IvCILQBZpr0ZdK\nJS5fvky1WiWXyzWs121E6AVBELpEWOgLhQLvvfdeELJptU63EKEXBEHoAVprlFKMjIzgOA6VSoXV\n1dWGScW75d2L0AuCIHQBMym48djT6TR33HEHhw8fxvd93n//fc6dO9fQKduttEsRekEQhC4RzqhJ\np9McPXqUD33oQ+Tzea5fv95Q2KybRc5kZKwgCEIP8H2fSqVCsVikXC4HaZeGbnbKikcvCILQBZpH\nwObzed5++208z2NsbIxkMtmwvnj0giAIA4jWOsibr1arXLx4kcuXLzM0NMTevXtxHCdYN1yrvtOI\nRy8IgtBFjNCbUI3ruoyOjhKLxUin0xQKhe63oetHEARBuIVpHjhl2zblcpnV1VWq1WpP2iAevSAI\nQhfxfb+hozWXy3H69GkWFhZYWVlpWK9biNALgiB0Ea11g9DPzs4yOzt7w3rNWTidpK3QjVLqHyml\nziqlfq6U+u9KqaRS6qhS6mWl1LRS6o+UUvFONVYQeoXYttBpbNtuKGa2e/duPvOZz/Doo4+ya9eu\nhvU6zbaFXil1EPgHwANa63sAG/h14LeB39FafwhYBr7WiYYKQq8Q2xa6gSlbbDh+/Di/8iu/wj33\n3NMQq4/HO+8/tNsZGwNSSqkYkAZmgU8C36t//x3gS20eQxD6gdi20FVSqRRDQ0N4nke5XA6WR8qj\n11rPAP8BuMTaRbACvAZktdYm2HQFONhqe6XUk0qpk0qpkwsLC9tthiB0nE7adi/aKwwmuVyO5eVl\n4vE4u3fvDpZ3IxOnndDNGPBF4ChwABgCPrPZ7bXWT2mtH9BaPzA5ObndZghCx+mkbXepicKAEu6U\nrVarJBIJPvGJT/Abv/EbnDhxAqVUIPSdnJyknT39VeCC1vo6gFLqj4GPA6NKqVjd8zkEzLTfTEHo\nKWLbQscx1SwN8Xic22+/nc9//vN87GMfo1qtcvbs2SD7Jh6PdywTp50Y/SXgIaVUWq21/lPAm8CP\ngV+rr/ME8P32migIPUdsW+g4zbVsYrFYkG1z4MABRkdHN1y/Hbbt0WutX1ZKfQ84BbjAaeAp4Fng\nu0qpf1Nf9q1ONFQQeoXYttANfN9vqGeTy+U4deoUtVqN8+fP89Of/rRh0FTzTFTt0FYQSGv9r4B/\n1bT4PPBgO/sVhH4jti10Gs/zGoT80qVLfPvb30ZrzdzcHNlstuH7TnbKyshYQRCEHmBGyJr0yaWl\nJZaWlgA4ePAgk5OTzM/Pd2VqQSlqJgiC0EMcx2kYFPWrv/qr/MEf/AG/+Zu/2ZBpk0qlOnZMEXpB\nEIQeYtt2w6CoL3zhC3zuc5/jK1/5ShDDV0qRSCQ6dkwRemEg6ea0a4LQS1ZXV4G1ztluVbCUGL0w\nUCilGmbsCS8XhEGgVqs12OsPf/hD0uk0b775JqlUilqthtaaYrHYsWOK0AsDhenQEo9eGFSas2n+\n7M/+jNdeew3P86hUKsHy8Pt2EaEXBg7f9xuKQIGEcoTBw7KswHNv5b1bltWxUI7E6IWBw7btGzIS\nJHQjDBrNM08100nnRTx6IdIYr0drjVKKO++8k8OHD5PNZjl9+jSe5zWsJwiDgsmw8X2feDzOQw89\nxLFjx3jnnXd48cUXA5uPxWJtj5IVj16INLZtBxeEbdvcd999fPnLX+ahhx7CcZxgvfDQcpBQjhB9\nUqlUkE9frVb57Gc/y+/+7u/yxBNPBOvYtt2RNEvx6IVIE674p5Riz5493HnnnSwtLTWIe7PQC0LU\nsW27wSG54447SCaT3HPPPcEy49G3i1wdQqQJZ9horZmfn2d6epq5ubmGjqpu5R8LQrdorn1z4cIF\nXNflrbfeCpZprYPwZDuIRy9EGs/zAqH3fZ/Tp0+zuLjIyspKQ9yyWeilc1aIOpVKpcGj/5M/+RPO\nnz/Pu+++GyxrnmZwu4jQC5Gm2Wt/5513mJ6eJpFINHg6vu+LuAsDhZlUxBQve+mll3jppZeC783y\nTpQrjpTQN8/AIgjNaK1xXfeGx9lWna+drP4nCN3C5Ms326plWR0J20DEhL7ViMdBvlC3e9Ma5N/c\nCyzLIpFIUCqVGpaHY/nmNWixe2Mz4VK1BpNu1w6t9rvZNt1sWavjtGrzZo59sxzznYQRc5Nh5vs+\nnud1TOQhQkLv+35DRTcYbMFr9+lkkH97NzHndTNCM2jn0NTx2ehJJJyBtBnCQhu+8VmWFVxvNztP\npl3rfW4+llIK3/dxXRetdfCbDM2fW21brVaDkEXzzW+nYmo4dVrkIUJCb/75YQMY5FDOIArNIGCy\nEJonTW5OwzSlYAfJfjqVYbEZjBAPArfKdVSr1To6fWCYSKRXhr20sLcwyEIvdJdW4QDjocZiscBj\nHQSxj3r7hMEnEh592JPxfT94vAy/HzRisRixWGxLHYLmgvc8LyhVKmyOsIdqOmvNOYz6eTTtSyQS\nJJPJIHwBrWP24dHC6007F/5snCfP8yiVSmitSafTQb0gz/Na3mzM9o7jNIxCdhyHRCJxwzFNmMa2\nbcrlMtlsFtd1SSaTOI4TTKMXj8eJxWIN23qeh23bOI5DtVplbm6O69evo7UOriNzTtarYNoJx7DV\nPsPHHFQiI/S1Wg3XdalWq3ieRzqdplKpDMzjZdjoLcti3759HDhwgHg8vuFvCFeoM8a/sLDA5cuX\ng4p2kj2yMVpryuUyKysr2LZNLpfDdV0SiUTQsRVFmqsT7t+/n6NHj+I4DuVyGd/3g1GRxulJJBJk\nMhmSyWSwzAhcK6H3PI9YLEYqlSKfz3Pu3DlqtRrHjx/n7rvvBtYmvjA3kHBM39jt5OQkk5OTwfK9\ne/dy+PBh4vF4QyndarVKOp0mnU5z6dIl/uIv/oLFxUWmpqaYnJykUqmQyWSYmppi165d1Gq1oP3l\ncplEIsHevXu5evUqf/iHf8jTTz9NtVplZGQEy7Iol8vBDatcLuO6boOwx2IxHMe5oT7SerTqv1hP\n6I3jMKhEQug9z6NQKGBZFtVqlVgsRiKRoFgsDoxnG06RisViHDt2jMcee4zx8XFKpRKu694wlNl4\nQOaCSqfTeJ7HqVOnyOVygdDbtj0wN7xe0ewNrqysMDs7S7FYZGVlBc/ziMfj+L4f2Qu0WYQymQz7\n9u0jkUhQKBTwfR/HcVBK4bouvu+TSqUYHx8nnU4HN7GNhN51XRzHYXh4mMXFRRYXFymXy0xNTfGR\nj3wErTUrKysopXAcB9/3g6eFSqWCUooDBw5w6NChQECnpqYYGxvb8LfdfffdJJNJZmdnOXjwIKOj\no1SrVSYnJ7nttts23PbIkSP85Cc/CUJxiUQC27YDr984hM3n0XRmblbowxihX2/g3SBo0EZEQuiN\nR6+UolqtNvS6m5778LpRJGxclmVx5MgRPv7xj3Po0CFyuRy1Wq3h8Rc+EHojRMPDw7iuS6VSaRg4\nIXVcbiRsB77vUyqVyGaz+L5PLpdrEPqoevTNGLuHtY45M0TeeLEmM61SqTSk4W0UsjD7icViwROy\n67qUy2UKhQIAxWKxpdCbthQKBfL5fGDjKysrNxX6arXKrl27KJfLeJ7H0tISnueRTCZbOj3N14cJ\nMZnzYm5cG0080/z9VrQivE1Y3EXoO4h59DZCH4vFKBaLlEqlgfHom3Fdl1KpRKlUolwuByGpVoMi\njNA7jhN4K4PaN9ErmrOzTOzXvIw33Inc815hYummAzn83oidZVlBhlpzymPzvsxvD+8nnPBgPGbz\nXfgzfJAJZzq1zfE2U2TLhCGNM2Pi7LZtt9y+2Qlq/m3bycXf7P99vdDooNjNZoiE0JsKbcagTazN\nPIYNAuH4nud5nD9/nhdeeIHR0dHAq2keJ9C8bSqVwvM8zp49G0wYbPYnrI/xRlOpFOl0Ooj9GsEf\nFBsKi2qz6Ib/mk7L8NNKc7zffDbXkRFYI5omWcDsMxz2MOfL7Dvc+QpsqmyuUor5+XlmZ2eZmppi\nZGSESqVyg6CvR/hm0JyVdzMB3mjQmaH5u62OTxg0IiH0tm0zOjraEKMfHR0NsgM28lyiQrPQnzt3\njqWlpaAmy0aepdnOtu0g9JDL5Rr2LTTSHKPPZrNcuXKFlZUV8vl8g0ffPEdnVGj2IrPZLBcuXAjC\nLCZLBT6wL8dxGBoaIh6PN4Qn1ovRm3BPMplkdXWV+fl5qtUqb775ZjCy2Pw1nbHmejPh1NHRUcbG\nxgL7nZycZN++fUGGjMHzPBKJBKlUipmZGU6ePMny8jKHDx9mbGws6Kw9dOgQmUymZWfs5OQk8/Pz\nnDp1KrjRFItFLMsKQlbhAUXNITwTqtpqFGCjTB6z70EmEkJvLlSlFLVaLTC4bDbbEKuD6MbKmg1u\nYWGBpaWlLadXGmMLG1ZUf3M/CZ+fSqXCuXPnSCaTJJPJwGaMHeXz+T62dH2axWN2dpbr168DtBRt\n834raYStRqsCzM3NBf1Azamc4W2hcRRt+HMr2zbHMn1N5gk9nNHTKu3YfGc6XQuFQhDSNE7Pejpg\n3reqgbQVdvJ1FgmhX1xc5OmnnwbWRN+yLFKpFMVikZMnTzZMnDsoYYxejnK8FQmLZLlc5u233+ba\ntWtByCIcsgk/HUWRcCpkr2zGdMgOAlvxpneyWLeDisKJcRxHT0xMAI0eiNZrM6SbVDNBWI+NvNx6\n2KMvMT+lVP8vMGFHsxnbvqnQK6W+DXwOmNda31NfNg78ETAFXAS+orVeVmtX2jeBx4Ei8Le11qdu\n2ogdeDE0P2JvJ6dX6BytLoao2Xa43tN61+VWOw1bDQqCxrl4N6EBmypqFv6+naJmWmsqlcotV9Rs\nu2zKiWmVe9rUMfEIcB/w89Cyfw98vf7+68Bv198/DvwfQAEPAS/fbP/17bS85NXNl9i2vHbqa1N2\nuEljnaLxYngH2F9/vx94p/7+vwBfbbXeRi+llI7H4w2vRCKh4/G4tm277ydSXtF/KaW0bdstX7D+\nxUCXbbvf50VeO/+1GQ3fbmfsXq31bP39HLC3/v4gcDm03pX6slmaUEo9CTxpPkc1BU4YDHTnOr87\nbtuC0G/azrrRWuvtxNi11k8BT8HOjNELg4/YtrBT2O6QwWtKqf0A9b/z9eUzwOHQeofqywRhUBDb\nFnYc2xX6Z4An6u+fAL4fWv631BoPASuhx2BBGATEtoWdxyY6k/47a3HIGmtxya8BE8DzwDng/wHj\n9XUV8J+B94A3gAckM0FeUXiJbctrp742Y4eRGDAlcUyh22gZMCXsUDZj24NR1k8QBEHYNiL0giAI\nOxwRekEQhB1OJKpXAgtAof43akwi7doKUWzXkT4eW2x760i7Ns+mbDsSnbEASqmTWusH+t2OZqRd\nWyOq7eonUT0n0q6tEdV2bQYJ3QiCIOxwROgFQRB2OFES+qf63YB1kHZtjai2q59E9ZxIu7ZGVNt1\nUyIToxcEQRC6Q5Q8ekEQBKELRELolVKfUUq9o5SaVkp9vY/tOKyU+rFS6k2l1Fml1G/Vl48rpX6k\nlDpX/zvWh7bZSqnTSqkf1D8fVUq9XD9nf6SUive6TfV2jCqlvqeUelsp9ZZS6qNROF9RQOx60+2L\nnG3vNLvuu9ArpWzWikV9FjgOfFUpdbxPzXGBf6K1Ps7adHF/t96WrwPPa62PsVbwqh8X7W8Bb4U+\n/zbwO1rrDwHLrBXk6gffBP6v1vpu4ARrbYzC+eorYtdbIoq2vbPsejOVz7r5Aj4KPBf6/A3gG/1u\nV70t3wc+zTrTy/WwHYdYM6xPAj9grZLiAhBrdQ572K4R4AL1vp7Q8r6eryi8xK433ZbI2fZOtOu+\ne/SsP0VbX1FKTQH3Ai+z/vRyveI/Af8M8OufJ4Cs1tqtf+7XOTsKXAf+W/3R+78qpYbo//mKAmLX\nmyOKtr3j7DoKQh85lFIZ4H8B/1BrnQt/p9du5z1LVVJKfQ6Y11q/1qtjboEYcB/w+1rre1kb6t/w\nONvr8yWsT5Tsut6eqNr2jrPrKAh9pKZoU0o5rF0MT2ut/7i+eL3p5XrBx4EvKKUuAt9l7RH3m8Co\nUsrUKurXObsCXNFav1z//D3WLpB+nq+oIHZ9c6Jq2zvOrqMg9K8Cx+o97XHg11mbtq3nKKUU8C3g\nLa31fwx9td70cl1Ha/0NrfUhrfUUa+fmBa313wB+DPxaP9oUatsccFkpdVd90aeAN+nj+YoQYtc3\nIaq2vSPtut+dBPWOjceBd1mbpu1f9rEdD7P2OPY6cKb+epx1ppfrQ/seA35Qf3878AowDfxPINGn\nNv0ScLJ+zv43MBaV89Xvl9j1ltoYKdveaXYtI2MFQRB2OFEI3QiCIAhdRIReEARhhyNCLwiCsMMR\noRcEQdjhiNALgiDscEToBUEQdjgi9IIgCDscEXpBEIQdzv8H8cb51Kq+mZ0AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0180160>"
+       "<matplotlib.figure.Figure at 0x7f884c072550>"
       ]
      },
      "metadata": {},
@@ -3594,20 +3718,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.047 \n",
-      "FIRE        -0.058 \n",
-      "RIGHT       -0.008 \n",
-      "LEFT        -0.001 \n",
-      "RIGHTFIRE   -0.027 \n",
-      "LEFTFIRE    0.052 (Action Taken)\n",
+      "NOOP        0.169 \n",
+      "FIRE        0.261 \n",
+      "RIGHT       -0.042 \n",
+      "LEFT        0.104 \n",
+      "RIGHTFIRE   -0.020 \n",
+      "LEFTFIRE    0.306 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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MxpgelUZ10kCvlFJ9TgO9Ukr1OQ30SinV5zTQK6XWbLWRNJqPTzav1wVQSiWX\nHSapgXxn0xa9UuqWdEz8zqaBXiml+pymbpRSbW7WetcUzs6kgV4pFXEcJwr0GtT7R1epGxH5DyLy\nqoi8IiJ/KSJZETkqIidFZFJEviEi6c0qrFLbZbfVbRGJgnx8nhpjDGEYEoahBv4dbMOBXkQOAf8e\neMQY8yDgAr8OfBn4I2PMXcAC8PnNKKhS22U31m3HcXCcZjiIB3UN7v2h285YD8iJiAfkgRngE8A3\nW69/Ffhsl+tQqhf6sm47joPrunieFwX2ONuCD4KAMAx7UEK1FTYc6I0x08D/BC7R3AmWgNPAojHG\nb71tCji00vIi8oSInBKRU3NzcxsthlKbbjPr9naUdz1EBNd1o5tlJyHT4N6fukndjAKfAY4CtwED\nwC+sdXljzJPGmEeMMY+Mj49vtBhKbbrNrNtbVMRNY3PxNg+v+lM3qZufAy4YY64ZYxrA3wIfAUZa\nh7sAtwPTXZZRqe22K+u25uP7VzeB/hLwYRHJS7NZ8EngNeB54Fdb73kc+FZ3RVRq2/VN3XYch1Qq\nFd1Wysur/tdNjv4kzY6pl4Czrc96Evh94HdEZBIYA57ahHIqtW12ct3uvISf4zh4nkcqlcJ13Wje\nGh0uubt0dcKUMeYPgD/oePpt4NFuPlepXtupddt2sgZBgO/7UTB3HCfKwwdBEL1fg/3uoGfGKtVH\n7KgaG8CDICAIAowxbffV7qKBXqk+12g0opSNBvndSQO9UjuQnbIAWDHfHs/Ta4BX2gWv1A7R2cma\nzWbJZDJtz+u88WolGuiVSrDOCcbiz7uue8NwSdvZGu9wVUpTN0ol2M1SLiulZLTDVa1EW/RKJcjN\nUi+pVArPa7bNbCDvfL/m49VKNNArlSCrBWnHccjn8+Tz+WhMvDFGc/JqTTR1o1QCiQjpdDoK6qlU\nikwmQxAEOI6D7/vU63Ucx9EWvLolDfRKJVQ2myWfzyMiUd7d9/3o9Xq9Ho2PV+pmNHWjVEIMDg4y\nMjJCKpWK0jK5XI58Po/rulSrVcrlcluw1yCv1kJb9Er1SGdrfGBggIGBAYwxLC0tUavVqNfruK5L\nrVajUqnQaDRWXFapm9FAr1SCxM94rVQqLC4u4jgOtVotCvKgLXm1PhrolUoIOzQyPpJmeXm5hyVS\n/SJROfrOubSVWquV6k3S61Jn+VzXjeaNV2ozJapFv9LJHtt9iLqR4KCH0b0Xrzv2ftIvdt1Zb+r1\nOuVyuS0kBZu+AAAL10lEQVRFE5+4rFNnXb1Z3e3ct9az7ErLq50lMYE+DMMbWjLbWbG6PZrQnSBZ\ndkJgsmka+3dhYYGlpSWA6GpQ0Nw3Ouum4zhtV4yy9Tc+L058GTs1gv0sO0/OastC+4XDdWqFnS0x\ngd5xnBuC7XamcnZCYFCri9cVG8jiwTKp4kchdh+IXxlqNd1MXJb0Ix21+RKRo4+3KOKjDjRnr9bK\nBncAz/OiFm+Sg31nufbv38+xY8cYGRnpUYlUv0pEi95e5gyIrmvZeX8rxVuA9kfmVi2q+GFu/LBY\n9UYYhtGJRL7vEwQBjUYj0UdqdoKyRqOB53mMjo5y4MABXNelXq8ThiHpdJpqtUq9XiedTkeXCUyl\nUuRyOVKpFGEY4jhONGVCfPSOTe2Uy2WWl5ep1Wp4nsfAwADpdDoqS3zCNFuP7b5Qq9VYXl6mVCpR\nr9e3eSupzZCYQN9oNKL5O4IgIJ/PU6vV2s4C3Cq5XI7x8XHGx8fJ5/MA0XrtXCOd9+0PQ7lcZmFh\ngWvXrlEsFhMbVPqZMYZqtcrS0hKu61IoFPB9n0wmc8PFsJPEBusgCKKjkTAMmZiYYHx8nFQqRblc\n5vLly5RKJfbs2UM6naZer3PgwAEefPBBxsbGqNVq5HI5Dh48yMDAAI1Gg1qtFn1+pVLhjTfe4IUX\nXuDy5cuMjIzw/ve/n8OHDxMEASLC/v37GR0dJQxDarUaAPl8HmMM77zzDi+++CIvv/wys7OzbTl8\nre87QyICfRAElEolHMehXq/jeR6ZTCYagbDZlSkesAGGh4e5//77+cAHPsChQ4cwxlCpVKLJpOIV\n2/4AZLNZPM9jbm6OV155hdOnT1MqlaKg0rkOtbnidSIIApaWlpiZmaFcLrO0tEQQBKTTacIwbBvF\nkiSO45DJZKJWeKPRoF6vs3fvXgYGBvA8j0qlQjqdZnl5mTAMKRQKGGMYGRnhnnvu4dChQ5TLZYaG\nhrjzzjsZHh6mWq1SqVTIZDIMDQ1RKBQQES5evMjc3BwjIyMcOXKE+++/H9/3cRyHI0eOcODAgbZ9\ncXBwMFrXzMwM58+fbyu/BvqdIxGB3lZyEYkOWev1etTKj1emzahYnbnRgYEBjh49yoc+9CHuu+8+\njDEUCoXo0Nmu0/4Q2WWy2SzvvPMO9Xqdt956i6mpqVXXoTZXvB6EYRidRWqDYTzQJ7VFbztF4w0J\ne6vVapRKJTKZDEePHsX3fS5cuMDs7GyUmqpWq5RKJSqVCo7jUCwWERGq1WqU7jHGUCwWo0aTTXHF\nh3K6rkuxWCSfzxMEAeVyuW0q5FKpRK1WS+x2VLeWmEBfrVajQO95HuVyOZrbY6tbDXZWQDufSBiG\nVKvVtiBhR0XY8thWWHyHUtunc3SW67qk0+noFj8aS/KPbjyPbvt54iNwXNeNjh4PHDiA7/v4vs/4\n+DiZTAZoNkA8z4tuqVQK3/fbnrP9T/EBDzbfH19eRKLObM/zotc7L1modpZEBHpbuUSEMAyjymor\n3GbrTKkUi0XOnz9PKpXi3LlzUQA3xtwwtt/uiJlMhlQqxfz8POfOnWN+fr7tczXwbx8RifLR+Xw+\narnagJ/0IOV5Hr7vUy6XWVxcjC4wYgNtuVxmdHSUe++9N0q3DA4OMjg4GJ1/ks1mSafT0TL2iMbe\n4oHeBnm7z9ntZ8/K9X0/eg6IOnmTvh3V6hIR6F3XZWRkpC1HPzIygjEmuqKOtRmts84gXCgUeOON\nN5iZmSGXy7WNAlrpUm32eTurYKFQYGlpqS3Qa35+a3Xm6BcXF5mammJpaYlisdjWok/qSJFGoxEd\ntdqWuk1d2tSh53kcOXKE4eFhDh8+zL59+3Ach+npaV599VVmZ2fxPI99+/bx6quvRqNw7H6UzWap\nVqu8/fbbXL58mWKxCMDZs2eZm5uL6vm5c+cYHh6OOmNt/0EYhrz77rucP3/+hsEG2pjZORIR6O2O\nKiJRztAYw+LiIpVKZcsrl02/zM3N3XB24M3YQ249AWX7xbd3rVbj/PnzZLNZstlsVGdsPbLBLWnq\n9XrbqLIwDCmXy5RKJXzfp9FoMDIywvj4eJQrz2QyUd/Qd77zHSYnJ0mn0+zZsyca5tt5xqvtA7M/\nKNevX2d6errtaDV+vkHnskEQRH1mcRrod45EBPrr16/zta99DSCqqLlcjnK5zKlTpyiXy9F7t6pD\nSAP1zhL/f1WrVd544w2uXLkSdSLGUzaFQqFXxbylznpnO5atxcVFJicn8X2fVCoV5esvXLjA5OQk\nQNRIWc86t2PYskoOScKvciqVMmNjY8CNrQnbwtFArG7mZmdRt/pVetIjKyJd72A2px77zK6mQFD9\nZS11+5aBXkT+HPhF4Kox5sHWc3uBbwBHgIvArxljFqS5p30FeAwoA//aGPPSLQuxCTtDtzondoIb\nJ4ZaSXymRJVcK+0MSajbq02vbDs/fd9ftZETz6PHR+q0vu+aJjWLr3O1ZXVSs2RbUyMmHqhWugEn\ngIeAV2LP/Q/gi637XwS+3Lr/GPAdQIAPAydv9fmt5Yze9LaVN63beuvX25rq4Ror6xHad4ZzwMHW\n/YPAudb9/wN8bqX33ewmIiadTrfdMpmMSafTxnXdnm9IvSX/JiLGdd0Vb7D6zsAW1+3N+G6u65pU\nKhXtF5lMxnie1/Ntrrdk3NYSwzfaGbvfGDPTuj8L7G/dPwRcjr1vqvXcDB1E5AngCfs4qUPg1M5g\njNmsnPWm1+1uaT5edavrUTfGGLORHLsx5kngSUhGjl6pTlq3Vb/Y6KluV0TkIEDr79XW89PA4dj7\nbm89p9ROoXVb9Z2NBvqngcdb9x8HvhV7/l9J04eBpdhhsFI7gdZt1X/W0Jn0lzTzkA2aecnPA2PA\ns8B54P8Be1vvFeB/AW8BZ4FHdGSC3pJw07qtt369raUeJuKEKc1jqq1mdvAJU0rdzFrqtk5Hp5RS\nfU4DvVJK9TkN9Eop1ecSMXslMAeUWn+TZhwt13oksVx39HDdWrfXT8u1dmuq24nojAUQkVPGmEd6\nXY5OWq71SWq5eimp20TLtT5JLddaaOpGKaX6nAZ6pZTqc0kK9E/2ugCr0HKtT1LL1UtJ3SZarvVJ\narluKTE5eqWUUlsjSS16pZRSWyARgV5EfkFEzonIpIh8sYflOCwiz4vIayLyqoh8ofX8XhH5noic\nb/0d7UHZXBH5kYh8u/X4qIicbG2zb4hIervL1CrHiIh8U0TeEJHXReSnk7C9kkDr9ZrLl7i63W/1\nuueBXkRcmpNFfRp4APiciDzQo+L4wO8aYx6gebm432qV5YvAs8aYu2lOeNWLnfYLwOuxx18G/sgY\ncxewQHNCrl74CvBdY8x9wHGaZUzC9uoprdfrksS63V/1ei0zn23lDfhp4O9jj78EfKnX5WqV5VvA\np1jl8nLbWI7baVasTwDfpjmT4hzgrbQNt7Fcw8AFWn09sed7ur2ScNN6veayJK5u92O97nmLntUv\n0dZTInIE+CBwktUvL7dd/hj4PSBsPR4DFo0xfutxr7bZUeAa8BetQ+8/E5EBer+9kkDr9doksW73\nXb1OQqBPHBEZBP4G+G1jTCH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kZIREIkGlUumrRx/GVNVKpRKFQiFYvl6IIPx7sVjko48+YmZmJsjo2eixTXtA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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be02ca9e8>"
+       "<matplotlib.figure.Figure at 0x7f884c313cf8>"
       ]
      },
      "metadata": {},
@@ -3619,20 +3743,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.066 \n",
-      "FIRE        -0.018 \n",
-      "RIGHT       0.007 (Action Taken)\n",
-      "LEFT        0.056 \n",
-      "RIGHTFIRE   -0.016 \n",
-      "LEFTFIRE    0.112 \n",
+      "NOOP        0.193 \n",
+      "FIRE        0.247 (Action Taken)\n",
+      "RIGHT       -0.042 \n",
+      "LEFT        0.119 \n",
+      "RIGHTFIRE   -0.032 \n",
+      "LEFTFIRE    0.120 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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K5XIYt40KvTGiRqNBJpMhm83y9ttvc+bMmZZ9m/WEwWOyMoyYVyoV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\nAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0304208>"
+       "<matplotlib.figure.Figure at 0x7f884c178c88>"
       ]
      },
      "metadata": {},
@@ -3644,20 +3768,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.013 \n",
-      "FIRE        0.044 \n",
-      "RIGHT       0.089 \n",
-      "LEFT        -0.120 \n",
-      "RIGHTFIRE   0.029 \n",
-      "LEFTFIRE    0.115 (Action Taken)\n",
+      "NOOP        0.160 (Action Taken)\n",
+      "FIRE        0.154 \n",
+      "RIGHT       -0.122 \n",
+      "LEFT        0.141 \n",
+      "RIGHTFIRE   -0.039 \n",
+      "LEFTFIRE    0.132 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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RK6XUgNNEr5RSA04TvVJq3USk10VQm6CJXim1Lprk+5fX6wIopeJNE3z/0xq9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\nCfwmzdu27TgREeBx4A1jzB9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stvbdCuaaFIvFBqGPevee53HlyhVyuVxLfSHMfTd2sLS0xMLCAo899thN6wlC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\nEaEXBEHoc0ToBUEQ+hwRekEQhD7n/weEbO2POhAScgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00b8588>"
+       "<matplotlib.figure.Figure at 0x7f884c06e7f0>"
       ]
      },
      "metadata": {},
@@ -3669,20 +3793,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        -0.117 \n",
-      "FIRE        0.109 \n",
-      "RIGHT       0.040 \n",
-      "LEFT        -0.123 \n",
-      "RIGHTFIRE   -0.003 \n",
-      "LEFTFIRE    0.116 (Action Taken)\n",
+      "NOOP        -0.076 \n",
+      "FIRE        0.045 \n",
+      "RIGHT       -0.298 \n",
+      "LEFT        0.085 \n",
+      "RIGHTFIRE   0.018 \n",
+      "LEFTFIRE    0.106 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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NeqWU6nMa9Eop1ec06JVStyQi3S6C6pAGvVLqtjTse5sGvVJK9TkNeqWU6nMa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\nRK5CYII=\n",
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L8doFYWUiK/Sm16fpSCOz0AjtMHZhhkkI9xYWBGGZyAl9ePJqIOgFahDBF6B9VpDpjdxq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\nYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be035b940>"
+       "<matplotlib.figure.Figure at 0x7f884c1ca9e8>"
       ]
      },
      "metadata": {},
@@ -3694,20 +3818,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.168 \n",
-      "FIRE        0.004 \n",
-      "RIGHT       -0.061 \n",
-      "LEFT        0.089 \n",
-      "RIGHTFIRE   -0.060 \n",
-      "LEFTFIRE    0.273 (Action Taken)\n",
+      "NOOP        -0.075 \n",
+      "FIRE        0.067 \n",
+      "RIGHT       -0.214 \n",
+      "LEFT        0.122 \n",
+      "RIGHTFIRE   0.073 \n",
+      "LEFTFIRE    0.148 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Ar5RSKaeBXimlUk4DvVJKpZwGeqWUSjkN9EoplXIa6JVSKuU00CulVMppoFdK\ndRARRKTfxVCbqKdALyL/QUReE5FXReTPRSQvIkdE5LiInBWRb4hIdrMKq9R22al1WwN8Om040IvI\nAeDfAw8aY+4DXOBXgC8Dv2+MuQOYBz6/GQVVarvs1Lptg7wxps8lUZut19SNBxRExAOKwEXgk8A3\n23//KvDZHr9DqX7YUXW7O8hrsE+XDQd6Y8w08D+B87R2gkXgRWDBGOO3PzYFHFhpeRF5XEROiMiJ\n2dnZjRZDqU23mXV7O8q7Xivl4I0xGtxTrJfUzSjwKHAEuAUYAn52rcsbY54wxjxojHlwfHx8o8VQ\natNtZt3eoiIqtS69pG7+OXDOGHPFGNME/hr4KLCnfboLcBCY7rGMSm03rdsqVXoJ9OeBj4hIUVrn\ngZ8CTgPPA7/U/sxjwLd6K6JS2y5VddumanTY5M7VS47+OK2OqZPAK+11PQH8DvCbInIWGAOe3IRy\nKrVt0lS3Vwrymo/febwbf2R1xpjfBX636+13gId6Wa9S/TaoddsGdBvMjTHXvKd2np4CvVIqeVYb\nKqlBfufSQK9UymlLXulcN0oNMO1cVWuhgV6pASQiuK6L4+gurG5Ma4lSA2q11rymalQ3zdErNaBW\nCuYa5NVKtEWv1IDoHguv1FppoFdqQLiui+u6/S6GGkCaulEqoRzHiS50chwH13WjC6CMMYRhqKNu\n1JpooFcqoRzHwfNau6hN1YRhGP1d8/FqrTR1o1RCuK6L53lRK90OoXRdFxEhCAKCINDgrtZNA71S\nCeG6LtlsNsrDh2FIGIZRmkaDvNooTd0olTC2RR8EAY1GAxGJAr5SG6GBXqkEC4Kg30VQKZCo1M1q\nN0aIt2S0VaNWslK9GbQRKTZVo8FdbbZEtehXG0UQ32FXmtvjeju0Hhh2hnjdic/FHh+lkjQiguM4\n0ZBJz/NwXZdMJkOz2Yw+Exevzxs5kK11f+j+nO5Hgy0xgT4Mw2suBrGVywZ3x3Gih905VmPHGsfX\no3aOQRh66Hke2Ww2qs+2TmcyGTKZzIrLxA9edpy9fX8tgd+eNcC189bb1/FOYNs/oH0Egy0xgd5W\n2u7WuzEG3/eBVgX0fT+qqFrxlBWvO93DEpPGNkKazWbUcldqKyUiR7/azYttS94GetDOKbUyG9yh\n1VK2V5ImMdjrTbrVdktEi94YEwXwMAyjAG/fy2azAOTzeQqFAtVqteNz3eKnpPYikyTnalXv7Nke\ntBoGQRAeYYLzAAAJ20lEQVTQbDYTlcKJp0YAxsfHueWWW/A8jyAIKBQKUf2uVCrXpDNFBN/3qdVq\nQGt/sFfOrjYdQvyesWEY0mg0aDQa0fri95K1+1Oj0Yj2MRGh2WxSrVaj5dTgSUygbzQaOI5Ds9mM\ndtrl5WVc1+Xmm28mm81y6NAhCoUCS0tL1wR6x3GiHci25Or1OlevXmV2dpZSqaTBPqWMMdRqNRYX\nF3Fdl1KphO/75HK5RI1iyWazhGEYpWsefvhhvvCFL3Drrbdy6dIl6vU6IyMj0f5gBUFANpslk8lw\n5coVJicnAbjtttsYHx+Pgrc9e+meD8deiFWtVpmammJmZgZjDNlsNjp4hGEYHTimpqZ48803WV5e\njr7zjTfe4NKlS7oPDahEBPogCKhUKgAdlXRxcRHP87j77rspFovcd999FItFFhcXCYKgo8PKXiIe\nhiG5XI58Ps/c3BynT5/m5MmTLC8vd3RiaYUdbPFWehAELC4ucvHiRSqVSlQ/ugNrv3UPNvjABz7A\nxz/+8ej5Wr311lsA3HXXXesuw+zsLJOTk4RhSKFQQERoNBoYYygWi2QyGd544w1832dxcZFcLofr\nupw/f17TTQMsEYHetmDiM/XZ01fP8zh48CB33HEHH/nIRxgaGmJubo5ms0kul4vWET8bKBaLFItF\nZmZmADh37hyu6646ZE0NnnigD8OQarXKwsICYRhSKpU6An1SWvTdaaRGo0Gz2YwaLLVajXw+f911\nVKtVyuUyAJVKhWKxuK4yLC4uUi6Xo7NmG+jt60wmQ6VSoVarRSkimwpTgysxgd5WKiDqSKvVajSb\nTXzfp16vU61WcRyHWq2G7/sdwycdx4lOQW3usVarRa0VlS7xg7XtiM1ms9EjDEMymcyahx1ul+7B\nBvGzUtsXdT1BEOD7fsfMluvheR6e50UpHcdxCIIgWp8dyx8fBWfH+6vBlYhAby8WsR1GjuOQz+fJ\n5/PU63XOnTvHhQsXmJ2dpVAoUC6XCYLgmopux/ranb1UKnHmzBmuXLnS0SLRtE262LHnhUKBYrEY\nndnZgJ/UINWdyllLOXO5XDTx2VoODKstb7dPfAy/7QfIZDJ4nhf9m8SRS2p9EhHoXddldHQ0Sr+4\nrsuuXbuiynX27FkuX77M66+/Tj6fp1qtrhjo4xd+2FRNuVxmfn6+Y4imtvAHX3eOfmFhgampqY7U\nhG3RJ2W0SPfor9OnT/Nnf/ZnHDhwgCtXrkSpG9uHZM9Us9ksw8PD5HI5FhYWuHDhArVajZdffpmR\nkZGOVn43e6DLZDLU63VmZmaYnZ3FGEMmk4k6Y22g9zyPmZkZzp07R7VaxfM85ubmdDDDgEtEoLc7\nqs0Xep6HMYbl5WUWFxe5fPkys7OzzM/Pk8/nqdVqa74yNv5Q6REPOvV6nTNnzkRngdVqFWNMdEcm\nm9Put+4Dzt///d9z8uTJaHilDez2zNb2M4yNjbFnzx4ymQyu6xKGYbRf2JFp9reuVs/t/mCHG9v3\nrPgwTHvgsGlQ26Gt+9DgSkSgv3r1Kl/72tei1oXjOBSLRSqVCidOnIh21CAIWF5e7nNpVRLEA32t\nVouG/9nWcDxlUyqV+lXMFdlgXa1WqVarN/y8HVQArRx7LpfT/UCtiyThKJ3JZMzY2BjwfsvC7rCV\nSoWlpSVtTajrut7Vpu00SF+SzCKiFVdtqbXU7RsGehH5E+DngMvGmPva7+0FvgEcBiaBXzbGzEtr\nT/sK8AhQAf61MebkDQuxhp3BdlzdKGUT//tK99lUO9NKO0O/63Ymk1lxUrPYslEKJ36nKXu2Yse4\nr7Tsaux6rvd5m+KJX9Oid7dKrjU1Yrrz2CvktY8B9wOvxt77H8AX28+/CHy5/fwR4NuAAB8Bjt9o\n/e3ljD70sZUPrdv6SOtjTfVwjZX1MJ07w5vA/vbz/cCb7ef/B/jcSp+73kNETDab7XjkcjmTzWaN\n67p935D6SP5DRIzruis+YPWdgS2u2/3eLvpI/2MtMXyjnbH7jDEX289ngH3t5weA92Kfm2q/d5Eu\nIvI48Lh9nZQhcGow2fTCJtj0uq1Uv/U86sYYYzbS4WSMeQJ4ArTDSiWT1m2VFhu9ZPCSiOwHaP97\nuf3+NHAo9rmD7feUGhRat1XqbDTQPwU81n7+GPCt2Pv/Slo+AizGToOVGgRat1X6rKEz6c9p5SGb\ntPKSnwfGgGeBM8D/A/a2PyvA/wLeBl4BHtSRCfpIwkPrtj7S+lhLPUzEBVOax1RbzegFUyql1lK3\nkzmtn1JKqU2jgV4ppVJOA71SSqVcImavBGaB5fa/STOOlms9kliuW/v43Vq310/LtXZrqtuJ6IwF\nEJETxpgH+12Oblqu9UlqufopqdtEy7U+SS3XWmjqRimlUk4DvVJKpVySAv0T/S7AKrRc65PUcvVT\nUreJlmt9klquG0pMjl4ppdTWSFKLXiml1BZIRKAXkZ8VkTdF5KyIfLGP5TgkIs+LyGkReU1EvtB+\nf6+IfFdEzrT/He1D2VwR+ZGIPN1+fUREjre32TdEJLvdZWqXY4+IfFNE3hCR10Xkp5KwvZJA6/Wa\ny5e4up22et33QC8iLq3Joj4D3At8TkTu7VNxfOC3jDH30rpd3K+3y/JF4FljzJ20Jrzqx077BeD1\n2OsvA79vjLkDmKc1IVc/fAX4jjHmHuAorTImYXv1ldbrdUli3U5XvV7LzGdb+QB+Cvjb2OsvAV/q\nd7naZfkW8GlWub3cNpbjIK2K9UngaVozKc4C3krbcBvLtRs4R7uvJ/Z+X7dXEh5ar9dclsTV7TTW\n67636Fn9Fm19JSKHgQ8Dx1n99nLb5Q+A3wbC9usxYMEY47df92ubHQGuAH/aPvX+YxEZov/bKwm0\nXq9NEut26up1EgJ94ojIMPBXwG8YY0rxv5nW4XzbhiqJyM8Bl40xL27Xd66DB9wP/JEx5sO0LvXv\nOJ3d7u2lVpeket0uT1LrdurqdRICfaJu0SYiGVo7w9eMMX/dfnu128tth48CvyAik8DXaZ3ifgXY\nIyJ2rqJ+bbMpYMoYc7z9+pu0dpB+bq+k0Hp9Y0mt26mr10kI9D8E7mz3tGeBX6F127ZtJyICPAm8\nboz5vdifVru93JYzxnzJGHPQGHOY1rZ5zhjza8DzwC/1o0yxss0A74nI3e23PgWcpo/bK0G0Xt9A\nUut2Kut1vzsJ2h0bjwBv0bpN23/uYzk+Rut07GXgVPvxCKvcXq4P5fsE8HT7+W3AC8BZ4C+BXJ/K\n9CHgRHub/V9gNCnbq98PrdfrKmOi6nba6rVeGauUUimXhNSNUkqpLaSBXimlUk4DvVJKpZwGeqWU\nSjkN9EoplXIa6JVSKuU00CulVMppoFdKqZT7/46vRddb20FwAAAAAElFTkSuQmCC\n",
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EVujNqE8zkEZmoRHaYezClEkIjxYWBKFO5IQ+PHk1EIwCNYjgC9A+K8iMRm61IUHY70RO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\n4gAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0218748>"
+       "<matplotlib.figure.Figure at 0x7f884c0c7ac8>"
       ]
      },
      "metadata": {},
@@ -3719,20 +3843,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.096 \n",
-      "FIRE        0.034 \n",
-      "RIGHT       -0.001 \n",
-      "LEFT        -0.031 \n",
-      "RIGHTFIRE   -0.153 \n",
-      "LEFTFIRE    0.247 (Action Taken)\n",
+      "NOOP        -0.428 \n",
+      "FIRE        -0.168 \n",
+      "RIGHT       -0.416 \n",
+      "LEFT        -0.043 (Action Taken)\n",
+      "RIGHTFIRE   -0.103 \n",
+      "LEFTFIRE    -0.119 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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STgO9UkolnAZ6pZRKOA30SimVcBrolVIq4TTQK6VUwmmgV0qphNNAr5RSCaeB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\nAElFTkSuQmCC\n",
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N9vzY22W90I15C+qWsB3Mz8/f1Bge9QdP2P3sJo9+VwQwwzfShCKEvU34LWY3\nPGjCaLJbbC/yQm8aIQ0yraAATbswJJPJtnWQ9EpBCBO50E3nAxpumDWZOOFu+MNiJ932w4Q7hfX6\n3N0cuxsGUS7TABy2g878fUEQ2omc0HcKhe/7wWu6SU802+zmHOluK4phHbsbelWu8NDEQCRnIBP2\nDp3p1FEk8qEbQRAEoTsi59F3MqwwhLB7EPsQhklUvfgw4tELgiCMOCL0giAII44IvSAIwogjQi8I\ngtADotxWJEIvCIIw4ojQC4Ig9IAoZ9+I0AuCIIw4IvSCIAgjjgi9IAhCj4hqB08RekEQhB4SRbEX\noRcEQegxUWuYjfxYN4IgCLuFqI4cKx69IAjCiCNCLwiCMOKI0AuCIIw4XQm9UmpSKfVdpdQ7Sqm3\nlVIfUUpNK6V+oJQ61/o71avCCsKgENsWuiFqmTfdevRfB/5Wa30vcAJ4G/gK8ILW+m7ghda6IOw2\nxLaFHaOUCua4jgI7Fnql1D7gMeAZAK11XWudAz4HfKO12TeAz3dbSEEYJGLbQrdEReAN3Xj0x4Hr\nwJ8ppV5XSv1vpdQYcEBrvdDa5hpwYL2dlVJPKaVeUUq9sry83EUxBKHn9My2B1ReIWKYyeujkmrZ\njdA7wIPAn2itHwBKdLzK6uZVrnulWuuntdYPa60fnp2d7aIYgtBzembbfS+pEEm01vi+P+xiBHQj\n9FeAK1rrk63179J8OBaVUgcBWn+XuiuiIAwcsW1hpNix0GutrwGXlVL3tL76BPAW8CzwZOu7J4Hv\ndVVCQRgwYttCt5jGWNu2sazhZ7F3OwTCvwW+qZSKA+8D/5pm5fHnSqkvApeAX+vyHIIwDMS2hR1j\nWVYg8L7vo5Qaary+K6HXWp8G1otDfqKb4wrCsBHbFrohKo2wBhnUTBAEoceEG2NNBs4wEaEXBEHo\nMVprPM8bdjECht9KIAiCMMJEoZesePSCIAh9wrZtbNsGwPO8oXn5IvSCIAh9wHjy4eybYSFCLwiC\n0AfMEAjDbogFEXpBEIS+YUI1JkY/rHx6aYwVBEHoEybNctjj04vQC4Ig9BGt9dAzbyR0IwiC0GeG\nHa8XoRcEQegzrusO9fwi9IIgCH0kCr1kJUYvCIIw4ojQC4IgjDgSuhEEQRgAZiISrfXAY/Yi9IIg\nCANAKUUsFgty6wc5JIIIvSAIwoCQPHpBEIQRRmtNo9Fom5RkUIjQC4IgDADf96nX60M5twi9IAjC\ngDBj3phHycbiAAAQcklEQVTBzQbl2YvQC4IgDADLsojH48RiMQDq9Tr1en0gwyJIHr0gCMIAMFk3\niUQCx3GCCUkGgQi9IAjCgDDhmkEPcCahG0EQhAHg+z61Wg1oziU7yFRL8egFQRAGgEmvbDQaWJYV\nxOoN/RR+EXpBEIQ+ExZxrTW2bQ80Ti9CLwiCMGB838fzvIHF6SVGLwiC0GfCgu77PtVqFdd12/Lo\n+yn6IvSCIAgDxHXdgY9e2VXoRin175VSZ5VSbyqlvqWUSiqljiulTiqlziulvqOUiveqsIIwKMS2\nhX5j2zaZTIaxsbG+x+p3fHSl1CHg3wEPa63vB2zg14GvAX+otf4pIAt8sRcFFYRBIbYt9Itwo2wy\nmWR8fJxEItEWtulH9k231YgDpJRSDpAGFoCPA99t/f4N4PNdnkMQhoHYttBXzJg3QHSFXms9D/wP\nYI7mQ7AGvArktNYmAHUFOLTe/kqpp5RSryilXlleXt5pMQSh5/TStgdRXmF3YiYfUUph23bwfT8a\nZbsJ3UwBnwOOA3cAY8Bntrq/1vpprfXDWuuHZ2dnd1oMQeg5vbTtPhVRGAG01iilGBsbY3p6mmQy\nGXzfa7rJuvkkcEFrfR1AKfVXwEeBSaWU0/J8DgPz3RdTEAaK2LbQczpDMkop4vE44+PjpNNptNZU\nq9W233sl+t3E6OeADyul0qp5BZ8A3gJ+CPxqa5snge91V0RBGDhi20LfMSGbeDyO4zht4Rvze6/o\nJkZ/kmbD1GvAmdaxngZ+D/htpdR5YAZ4pgflFISBIbYt9INO79zzPCqVCqurq2SzWUql0qbbd0NX\nHaa01r8P/H7H1+8Dj3RzXEEYNmLbQj8Ii3ej0WB1dRVodqLyPG/DbbtFesYKgiAMAc/zAnF3HAfH\ncfrWY1YGNRMEQRgg4fx5gImJCQ4dOsT09PRN2/UKEXpBEIQBsp7Q33777UxMTLR938thEUToBUEQ\nBkhn7N33fVzX7ev0ghKjFwRBGDBhQS8UCiilqNVq2LYdxO3DQxh3iwi9IAjCAOn02ovFIuVyGaBv\n49OL0AuCIAwRrfVNqZW9RmL0giAII4549IIgCBFgYmKCVCpFpVIhn88H3/dizBvx6AVBEIaAZVlt\n6ZRTU1Pcdddd7N+/P/hOKdWTNEsRekEQhCHQmU+fSqXYt28f6XT6pu26RYReEARhCHTmzVerVfL5\nfJCBE96uWyRGLwiCMAQ6hX55eZlqtdqWT9+rjBwRekEQhCGwXj59sVjsy7kiFbrpjFlB82b0qxOB\nMDqsF8fsxyTLgrAbiZRHv95YD50T567XAr3RAy2Vwt4hbDvmc6eTEDXCGRVbtdXwdsYx2sm+4XXz\n/Gy0LgwOpRSO42BZFr7v02g0enLcyAi97/s3TaVlJs8131uWFSzmt81QSkX6QRf6Rz8HiOoVjuMQ\nj8dRSgXx2M1s2sRrtdZYlkUsFmvbFzZ3enzfv6lCXA9zDLP9Rr/3ck7T9cob9f9frzB6ZpZDhw6x\nf/9+lpaWmJubw/f9rivfyAi9ySkNG6ox4lqtBtwY5c2I914xBOHWhG3HOAe2bUcyfGMEstFodOWx\n1ev1HpZq68hz11ssy2prcJ2dneXYsWNUq9VA68zb304nJolEjN48pGYxr7NG6MMzo4uHLqxH+M3P\nvPpGVew7O8oIQie+77dV5Ou1X26HSHj04RQi3/eDz1prHMdhbGyMQqFAMpkMugj7vr9hjzFzQzzP\na3sDEEYX87YHN+bfbDQakQoBhO0Smp7bHXfcgVKKYrGI53lBxbRemV3XpVKp0Gg0SKVSTE1N4TgO\nlUqFer3eFtYMn1Nrjeu6NBqN4N54ntfmLcLNMXrXdanX60GoyGAqUcNWwqjhbdd7Hs0xwuXt17R6\nUaPzf12tVmk0GkxOTpLJZALb6EbHIiP0xgjr9Tq2bVOv16nX68zOzvLAAw9w+fJlMpkMiUQiCOWE\nMY0X0PToAFZXV7l8+TKFQgHob0xRGB5aa6rVKmtra9i2TT6fx3VdEolEm+MwbOLxeFsD2yc/+Um+\n9KUvkUgkePXVV8nlcoF4hwXWvNmurq5y/vx5lpaWuPfee/nMZz7D1NQU77zzDteuXSOVSpFMJgPn\nxgiy67qsrKxw/fp1crkchUKBYrFIpVJpC5kaYY3FYliWxcrKCgsLC9TrdZLJZFCJpFIpMplM8Dxt\ntb0MmhNi12q1IO5sjmEqOcdxaDQaZLNZstksQFCpdDa2b3aenTAsbVivzJOTk9xxxx1MTU1x+vRp\nFhYW2irc7Yp+JITe8zxKpRJwo2Y3sfmjR4/yxBNPkMvliMfjbQPzww3xNnEuY4gAZ86coVQqBUIf\n7oQg7G7C/0PP81hbW2NhYYFyucza2hqe590krMPGeOumPMePH+fRRx8FmpXA9evXOXDgAI7jBGLo\nOE6wz+LiItAU4vvvv59Pf/rTAOzfv58LFy4wPj5OOp0OnCYTunJdl4WFBebm5lhaWmJ1dZVsNhv0\nwAxXJlprkslkkMiQy+VQSpFOp7FtG9/3yWQyTE1NtT1Pt8p8MyHZWq0WvJWYNxDf94OKKR6PU6/X\nKZVKwbMdfuPYSqNkt2K/3v6D1IxEIsHBgwc5duwY+/btY35+noWFBeBGCGdXCr3x6M1nIPBKDhw4\nwMTEBK7r3pROFv6nm4YK3/cZHx8Ptj158mRwns5GD2H3En7wfN+nUqmQy+XwfZ98Pt8m9FH5n6/X\n5d14ssbLTiaTxOPxQOiNN2ucoWq1Sr1ep1wuk8vlmJycJJ/PB86MCdF4nhdk5jQaDUqlEuVymUql\nQq1WC96Yw+1ixqMPC78R4XA41VSeJsSyFcyzZ0Iy5ti2bQcevVnvVbh1K1lM61Uc2wlF9YOwmPfq\nXkRG6CuVyk0ibl7JK5UKnudtevPDQm+8oHq9LvH5EaUzO8u2beLxeLD4vk8sFhv6QxumsxzG44Zm\nuNG2bWKxGI7jBI6NseXw9iYkY0KUjuME+zuOEzxD4XWzr9nfLHBD2MNpy52LKb/5PbzPZu1lQFt6\noDlOZ9JF+Jjr3at+EBW76HxbWF5e5syZM1y8eJGlpSWWl5eD3zrv5VaJhNArpYjFYsCNCzFezeXL\nlzlz5kwQugl75Z0XbPJ+k8kkAO+++y5ra2vB71Hx7ITeYuwnlUoFoQvf9wPB78Uwr70ibLNGqIG2\nSioWiwW2bMI9xjs3Yh2LxQI7N/uY/c32ZjsgqEBMhWAEPyywRnDCFYER4XBfFrNPZ8WwHuYazP8g\nXNF07hfephcivNNjDLoC6NSlq1evsrKyEjiv4TbJnSYXRELobdtmamoq8MJt22ZiYiKIuz7//PNc\nunSJiYmJoDG2MxMAaPNkAPL5fNCgAxt3ABF2H50x+lwux5UrV1hbW6NQKLR59MPKN+/Edd22cp85\nc4ZvfetbxONx3nzzTQqFAhMTE8ED3tkYm8/nuXTpEisrK0EFNjExwYULF7h+/XoQ9jFhkHBj7Nra\nGisrKxQKBUqlEqVSKbgvnQ18pgLK5XIUi8W2UJC5n9VqNfDmtxMiCYeWwm8RprzGkatUKsG96uw3\nc6tneKfP+FaP3y9MZWvCar0kEkLveR7ZbDYQemNo2WyWubk5zp49SzabxbZtkskk1Wp1U+MK9+yT\ncXJGk/D/tVarce7cOZLJJMlkMhAJE/818eth0/nwvvjii5w6dQogeAu5VQjExLdfe+01/vqv/zrI\nlrnVK72Js6/XQ7aT8POzXmNrOOyyXbbSK7czBXM7z/Bufsb7WfZICP3Kygrf/OY3A6O1LIt0Ok2p\nVOLUqVNB+CWcnSPsbcIPf7Va5Z133mFxcfGmLA6gbVq2KGAqoEqlQqVS2dExarVa30Y6XI9OEZIw\naP8wb2KmQbYXmYIqCjVgLBbTMzMzwI3XPPPAmtfMKJRTiC6bxYlbHuxQWt6UUmK4Ql/Zim3fUuiV\nUn8K/CKwpLW+v/XdNPAd4BhwEfg1rXVWNZ+0rwNPAGXgX2mtX7tlIW7xMJgabrvxwI164Ql7j/Ue\nhmHbtmlADeew38q2NxvU7Fb7htuothq6WW+bziycfrDTRse9yJacGHNDN1qAx4AHgTdD3/134Cut\nz18Bvtb6/ATwfwEFfBg4eavjt/bTssjSz0VsW5ZRXbZkh1s01mO0PwzvAgdbnw8C77Y+/y/gC+tt\nt9milNLxeLxtSSQSOh6Pa9u2h34jZYn+opTStm2vu8DGDwN9tu1h3xdZRn/ZiobvtDH2gNZ6ofX5\nGnCg9fkQcDm03ZXWdwt0oJR6CnjKrEclBU7YnZiwRg/ouW0LwrDpOutGa6130uCktX4aeBqkwUqI\nJmLbwqiw0y6Di0qpgwCtv0ut7+eBI6HtDre+E4Tdgti2MHLsVOifBZ5sfX4S+F7o+3+pmnwYWAu9\nBgvCbkBsWxg9ttCY9C2accgGzbjkF4EZ4AXgHPD/gOnWtgr4n8BPgDPAw5KZIEsUFrFtWUZ12Yod\nRqLDlMQxhX6jpcOUMKJsxbajM6yfIAiC0BdE6AVBEEYcEXpBEIQRJxKjVwLLQKn1N2rMIuXaDlEs\n19Ehnltse/tIubbOlmw7Eo2xAEqpV7TWDw+7HJ1IubZHVMs1TKJ6T6Rc2yOq5doKEroRBEEYcUTo\nBUEQRpwoCf3Twy7ABki5tkdUyzVMonpPpFzbI6rluiWRidELgiAI/SFKHr0gCILQByIh9Eqpzyil\n3lVKnVdKfWWI5TiilPqhUuotpdRZpdSXW99PK6V+oJQ61/o7NYSy2Uqp15VS32+tH1dKnWzds+8o\npeKDLlOrHJNKqe8qpd5RSr2tlPpIFO5XFBC73nL5Imfbo2bXQxd6pZRNc7CozwL3AV9QSt03pOK4\nwO9ore+jOV3cl1pl+Qrwgtb6bpoDXg3jof0y8HZo/WvAH2qtfwrI0hyQaxh8HfhbrfW9wAmaZYzC\n/RoqYtfbIoq2PVp2vZWRz/q5AB8Bng+tfxX46rDL1SrL94BPscH0cgMsx2GahvVx4Ps0R1JcBpz1\n7uEAy7UPuECrrSf0/VDvVxQWsestlyVytj2Kdj10j56Np2gbKkqpY8ADwEk2nl5uUPwR8LuA31qf\nAXJaa7e1Pqx7dhy4DvxZ69X7fyulxhj+/YoCYtdbI4q2PXJ2HQWhjxxKqQzwl8Bvaa3z4d90szof\nWKqSUuoXgSWt9auDOuc2cIAHgT/RWj9As6t/2+vsoO+XsDFRsutWeaJq2yNn11EQ+khN0aaUitF8\nGL6ptf6r1tcbTS83CD4K/LJS6iLwbZqvuF8HJpVSZqyiYd2zK8AVrfXJ1vp3aT4gw7xfUUHs+tZE\n1bZHzq6jIPQvA3e3WtrjwK/TnLZt4CilFPAM8LbW+g9CP200vVzf0Vp/VWt9WGt9jOa9eVFr/ZvA\nD4FfHUaZQmW7BlxWSt3T+uoTwFsM8X5FCLHrWxBV2x5Jux52I0GrYeMJ4D2a07T9pyGW41Gar2Nv\nAKdbyxNsML3cEMr3OPD91uc7gVPAeeAvgMSQyvQh4JXWPfs/wFRU7tewF7HrbZUxUrY9anYtPWMF\nQRBGnCiEbgRBEIQ+IkIvCIIw4ojQC4IgjDgi9IIgCCOOCL0gCMKII0IvCIIw4ojQC4IgjDgi9IIg\nCCPO/wct33o0WAo9mQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0326860>"
+       "<matplotlib.figure.Figure at 0x7f884c30c358>"
       ]
      },
      "metadata": {},
@@ -3744,12 +3868,12 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.018 \n",
-      "FIRE        0.080 \n",
-      "RIGHT       -0.099 \n",
-      "LEFT        0.073 \n",
-      "RIGHTFIRE   -0.089 \n",
-      "LEFTFIRE    0.395 (Action Taken)\n",
+      "NOOP        -0.179 \n",
+      "FIRE        -0.293 \n",
+      "RIGHT       -0.518 \n",
+      "LEFT        -0.155 \n",
+      "RIGHTFIRE   0.095 (Action Taken)\n",
+      "LEFTFIRE    -0.152 \n",
       "\n"
      ]
     }
@@ -3773,7 +3897,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3784,10 +3908,10 @@
     {
      "data": {
       "text/plain": [
-       "730"
+       "503"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3799,7 +3923,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3808,9 +3932,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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mrPFE0+k01WqVubk5O2s2iYIS9+iz2SxLS0sUi8VbJpbFaf3OZlDThEKuXl1L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\nzzuld4kR+mq12iRu5XKZSqW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PNE07YNYwFYTVaDQadv76jcxwKQg7mUgJffix2/yfy+WaJhoTdjftPHnjEJiZRsOevXj1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\nAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00c2128>"
+       "<matplotlib.figure.Figure at 0x7f884c29ca20>"
       ]
      },
      "metadata": {},
@@ -3822,20 +3946,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.219 (Action Taken)\n",
-      "FIRE        0.195 \n",
-      "RIGHT       -0.083 \n",
-      "LEFT        0.199 \n",
-      "RIGHTFIRE   0.455 \n",
-      "LEFTFIRE    0.990 \n",
+      "NOOP        0.666 \n",
+      "FIRE        0.905 \n",
+      "RIGHT       0.768 \n",
+      "LEFT        0.408 \n",
+      "RIGHTFIRE   1.149 (Action Taken)\n",
+      "LEFTFIRE    0.213 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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f+9rXuHDhgq1XXq/XJVY/oMQdgXq9Tq1W49ChQ4yMjPDYY4+1xedNiWNBGHQSJfRwa5pc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\nn2qM4A+iDa2G67qkUinS6bQ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t7VgOX8NKpcL8/Dye5zWlV25E6MPz5pj+BKWUbUhb+xUEQYig0LfeqK0dn2bw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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00f69b0>"
+       "<matplotlib.figure.Figure at 0x7f884c2c2198>"
       ]
      },
      "metadata": {},
@@ -3847,20 +3971,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.608 (Action Taken)\n",
-      "FIRE        0.085 \n",
-      "RIGHT       -0.416 \n",
-      "LEFT        0.350 \n",
-      "RIGHTFIRE   0.517 \n",
-      "LEFTFIRE    0.358 \n",
+      "NOOP        0.784 \n",
+      "FIRE        0.383 \n",
+      "RIGHT       0.674 \n",
+      "LEFT        0.731 \n",
+      "RIGHTFIRE   0.611 \n",
+      "LEFTFIRE    1.086 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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jKChRjz6dTrOwsEChULhhYFmU9ms2nZomFDI5uZL+7fu+7a/IZDLMz89TKpVs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\nbDZrPT4j+P1sQ1GMAHqeZ0V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3N3nyRng7O5aj17BarbKwsEAQBG3plVsR+ui8OaY/QSllG9LOfgVBEGIo9J03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\nBEEYcEToBUEQBpz/H98s16pZ3IKEAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be017bb00>"
+       "<matplotlib.figure.Figure at 0x7f884c0f2ac8>"
       ]
      },
      "metadata": {},
@@ -3872,20 +3996,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.071 \n",
-      "FIRE        -0.186 \n",
-      "RIGHT       -0.509 \n",
-      "LEFT        0.225 (Action Taken)\n",
-      "RIGHTFIRE   0.152 \n",
-      "LEFTFIRE    -0.182 \n",
+      "NOOP        1.094 \n",
+      "FIRE        1.070 \n",
+      "RIGHT       0.808 \n",
+      "LEFT        1.409 (Action Taken)\n",
+      "RIGHTFIRE   1.315 \n",
+      "LEFTFIRE    0.993 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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qNoqCEvboU6kUCwsL5PP5WwaWhWm9ZtOpaUIhk5Mr6d/1et32V6TTaebn5ykW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\nIvSCIAg9jgi9IAhCj/P/AZzEAaq5lwplAAAAAElFTkSuQmCC\n",
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jvK0dy+FrWC6XmZubw/f9pvTKjQh9eN4c05+glLINaWu/giAIERT61hu1tePT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\niNALgiD0OCL0giAIPY4IvSAIQo/z/wMphXH5TzEoOQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be003e048>"
+       "<matplotlib.figure.Figure at 0x7f884c333e80>"
       ]
      },
      "metadata": {},
@@ -3897,20 +4021,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.050 \n",
-      "FIRE        -0.050 \n",
-      "RIGHT       -0.196 \n",
-      "LEFT        0.108 \n",
-      "RIGHTFIRE   0.177 (Action Taken)\n",
-      "LEFTFIRE    -0.285 \n",
+      "NOOP        1.382 \n",
+      "FIRE        1.363 \n",
+      "RIGHT       1.342 \n",
+      "LEFT        1.431 (Action Taken)\n",
+      "RIGHTFIRE   1.374 \n",
+      "LEFTFIRE    1.368 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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aUbNJFJS4R5/NZllYWKBUKt0wsCxO+zWbTk0TCrl8eTX9OwgC21+Ry+WYn5+n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\n",
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NnrwR3uaO5fA1LJfLLCws4HleQ3rlZoQ+PG+O6U9QStmGtLlfQRCECAp9843a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\nEAShyxGhFwRB6HJE6AVBELqc/x+kQhBdGpYT4gAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0049128>"
+       "<matplotlib.figure.Figure at 0x7f884c190fd0>"
       ]
      },
      "metadata": {},
@@ -3922,12 +4046,12 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.134 \n",
-      "FIRE        -0.051 \n",
-      "RIGHT       -0.145 \n",
-      "LEFT        0.155 \n",
-      "RIGHTFIRE   0.300 (Action Taken)\n",
-      "LEFTFIRE    -0.286 \n",
+      "NOOP        1.345 (Action Taken)\n",
+      "FIRE        1.331 \n",
+      "RIGHT       1.317 \n",
+      "LEFT        1.345 \n",
+      "RIGHTFIRE   1.284 \n",
+      "LEFTFIRE    1.295 \n",
       "\n"
      ]
     }
@@ -3953,7 +4077,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3963,10 +4087,10 @@
     {
      "data": {
       "text/plain": [
-       "373"
+       "630"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3978,7 +4102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -3987,9 +4111,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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CXAIl9DDXO7158yZvv/02ly5dorOz045lYjxdf4/I+tb4TCbDhQsXeO+990JR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\nZqFqrfEKEokEABcuXGBiYsL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EX4Db7SD6JHO7DQnCfid2Qg+0TDuQSqXsI/iCsB7mNYjAtma4FIR+JlZCH+12m++FQqFl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\nQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be0121fd0>"
+       "<matplotlib.figure.Figure at 0x7f884c0b99e8>"
       ]
      },
      "metadata": {},
@@ -4001,20 +4125,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.788 \n",
-      "FIRE        0.785 \n",
-      "RIGHT       0.784 \n",
-      "LEFT        0.787 \n",
-      "RIGHTFIRE   0.789 (Action Taken)\n",
-      "LEFTFIRE    0.787 \n",
+      "NOOP        0.791 \n",
+      "FIRE        0.791 \n",
+      "RIGHT       0.790 \n",
+      "LEFT        0.791 (Action Taken)\n",
+      "RIGHTFIRE   0.789 \n",
+      "LEFTFIRE    0.791 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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JP83OztZ4MEuJXv3/npiYwLZtL0Yf9HNiOsLNzc3VtDeI0AcX/xhD/kly6tcx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\nQsgRoRcEQQg5/x823QprZ9/p4QAAAABJRU5ErkJggg==\n",
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0pVKJ06dP8/rrrzM7O2unzzUTX4nw7zxaXwNZqVTYvXs3n/zkJ3nssces3URn5RSEnU5s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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01072b0>"
+       "<matplotlib.figure.Figure at 0x7f8965455518>"
       ]
      },
      "metadata": {},
@@ -4026,20 +4150,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.777 \n",
-      "FIRE        0.777 \n",
-      "RIGHT       0.784 \n",
-      "LEFT        0.783 \n",
-      "RIGHTFIRE   0.780 \n",
-      "LEFTFIRE    0.790 (Action Taken)\n",
+      "NOOP        0.781 \n",
+      "FIRE        0.799 (Action Taken)\n",
+      "RIGHT       0.791 \n",
+      "LEFT        0.809 \n",
+      "RIGHTFIRE   0.764 \n",
+      "LEFTFIRE    0.796 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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ZY+/maa/5OMLNCbTQa62Zn59nbGyMfD5PPp8nkUg03PFvRqVSYWpqaq2a2pMU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\nAAAASUVORK5CYII=\n",
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eeOABazfRWTkFYbcTG6EH7FS45tVeWmtOnz7NV77yFS5dumTnK69UKhKr36VEHYFKpUK5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\nHBF6QRCEPkeEXhAEoc/5/+ZhsAJWyUBuAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00f31d0>"
+       "<matplotlib.figure.Figure at 0x7f884c0cfe48>"
       ]
      },
      "metadata": {},
@@ -4051,20 +4175,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.831 \n",
-      "FIRE        0.822 \n",
-      "RIGHT       0.825 \n",
-      "LEFT        0.823 (Action Taken)\n",
-      "RIGHTFIRE   0.824 \n",
-      "LEFTFIRE    0.831 \n",
+      "NOOP        0.785 \n",
+      "FIRE        0.801 \n",
+      "RIGHT       0.793 \n",
+      "LEFT        0.808 (Action Taken)\n",
+      "RIGHTFIRE   0.766 \n",
+      "LEFTFIRE    0.802 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SiYY0u6WoVqtMTEysVVE3JKVSadnXL8gE/QW12WnlRDSHB02tzZ9Bs9h9Nf1g\nmvcnLI/ACX0r/De/OW9cEIRgk0gkSCQSaK0pFAqe125qa2Z02tW0nS2Why+OQCOBF3rTCOlfFrEX\nhODSPJ9AOp0mk8l4v8/MzDQMOGhi8quJszfXHEToWxM4oW81xoVpmDUxPf86N7uhG7Hx9Wa0G1vf\niNdkI7QnbFaaOzSZFF7AS4c2z7DpB2LGqWoH/8i2cMOuxU4WEjihb5VBYjz45jFOlrs/ufGNyDUR\nOom/cVTVJ4vZsmULSimKxSKlUonZ2VkvgcI4Gf7smtXSbMdi260JnNALgrBx8adIw3w4Zm5ujnK5\n3JDmuxYsJfKb3dMPvNBvxDCDIISVVjFw08vaDC1tat0mo6ZcLi+aNrke+DVks4p94IVeEITgYETT\nNJwqpejv7ycWizExMUGxWPTmPfD3ZhW6iwi9IAiL4veGW01BqZRiy5YtZDIZSqUSxWLR+5ihN5rX\nX2+v+mY5+psBEXpBEBbFZL2ZDJdWmCE6jPc+NzfnzWlsZkUzdEtsN7PIgwi9IAhNmJCL8eCNwNu2\nTTKZxHVdCoUCMC+g+XyeWq3W0OO63dTJ9WKzNNJKAE0QhJY0x9f7+/u59dZb2bZtm/ed1ppsNsvo\n6Cj5fH69iygsE/HoBUEAGgciM0MSDAwMeENG79q1ix07dizowWrmf/Dvx0+QPWZ/KqhZDiMi9IIg\nAAtTmXt6erjtttvo7e315n1wHGfBoHjN4Y+NJpbNYh9GROgFYRNjJutxHMeLxUciEQYGBti/fz97\n9+5lcHCQUqnE8PAwly5d4tq1aw37CEOO+kYu+3IQoReETYwJ0ZgJfQCGhob4yEc+wsDAAPl83hvq\ne3JykkuXLnmhGtu2G14QYSQMLzEQoReETYWZh9e2bUqlErVabcHMbD09PfzMz/wMjuPw5ptvcvXq\nVTKZDDMzMwvi8cLGQIReEDYRrut64874G1X9Qwu7rks2myWXy/Huu+8yNTUF0DBcOMj0fRsJEXpB\nCDGRSIR4PE4kEqFarVIoFBpCLXfccQc9PT1cvHjR6+SUzWZ55ZVXmJ2d9UQe5mcnM55/mMM1fjZ6\nyMYgQi8IIaZWq3k9U5VSDVNxDg0N8YlPfIKenh6efvppT+hzuRynTp1q6bFvFoEPGyL0grBJ0Fpz\n++23c8cddzA7O8uOHTu47777yOfzRCI3pMBxnIZBy6LRaMO8EMLGQ4ReEEJEc5ZIJpOhWq1SLpfp\n6+vjl39xsWYSAAAQnElEQVT5l/n85z9PLBZjZGSEq1ev8sYbbzSEaOBGRo3WuiMThAjdpS2hV0r1\nAX8B3Alo4D8A54Cngf3AJeCzWuvptkrZQfzTjYUl/iZ0no1m2yabJpPJUKlUmJmZAeDBBx/kE5/4\nBIlEgmKxyKFDhzh06BCJRIJKpcK3vvUtvvnNbzIyMuLtq1arEYlElhzITNhYtOvRfwV4Xmv9qFIq\nBqSAPwBe0lr/sVLqceBx4PfbPE7HEIEXlsmGsm3XdSkWi1Sr1YYQy7333stjjz3mLX//+9/nhRde\noK+vj3fffZeXX36Z4eFhYD6rxnEcqtVqVycKETrPqoVeKbUFOA78BoDWugJUlFKfAh6or/Yk8H0C\n8jAIwnLYSLbdnAXTHEf3e+Raa37wgx/w7LPPesMKX7hwwfvdzBAlhI92PPoDwDjwV0qpo8BrwJeA\nIa311fo614ChVhsrpR4DHgPYs2dPG8VYGZZlNYRuxLsXWtAx215LzABkALFYjK1btzI0NMTs7Kwn\n4Llczls/n89z+vRpTp486X2XSCS850EaW8NLO8MUR4B7gK9qre8G5pivynroeRVtqaRa6ye01vdp\nre8bHBxsoxjLJ5FIsG3bNvbs2cPOnTvJZDINv4d9YCNh2XTMtteqgNFolGg06i3fdddd/NEf/RHf\n+c53ePLJJ3nggQcAGgYg6+3tbdgGbrRZie2Hm3aEfhgY1lqfqC9/g/mH47pSaidA/e9Ye0VcPf5Z\nb2A+A+Hw4cPcd9993HXXXQ3japv1BYENYNu2bWPbtre8Z88ePvOZz7Bt2zbuv/9+fvZnfxaAn/70\np7z//vsAnDx5smFCkHQ63TCZtxBeVh260VpfU0pdUUod0VqfAx4CztY/XwD+uP732x0p6Spo9lIy\nmQy33norhw4dYmpqisnJSS5evOgZuXg1AmwM224eWtd1XUqlEr29vQAkk0ksy+I73/kOv/mbv8mO\nHTu4ePEi58+fx7IstNZUq1UZxmCT0G7WzX8Cvl7PSrgA/Hvmawl/q5T6IvA+8Nk2j9FRzByYJlYv\nCIuw4Wzb75Uboa/Varz44ost15f8+M1DW0KvtT4FtIpDPtTOfjtFc3W0UCh4w6zOzs4yOTm55PrC\n5iXott3spESjUXp6erzlWCy23kUSAkyoe8a6rtvwQORyOc6dO8eVK1eoVqtks9kGcZfUMmGjYKb3\nM4yOjvLcc8/x4IMPcunSJU6fPu3ZcyaTIZVKkc/nKZfLYuebkFALPTR66eVymbGxMe8BaY5Pikcv\nbBSaUyHfeOMNHn/8cXp7eymVSoyPj3uCXi6XvcHNxMY3J6EXej9aa2l8EkKBEWyTKTY3N9fQ+cmg\nlJKersLmEnpBCBs3C8OIBy/AJhR6f1xTHgIhLNi2TTwe94YULpfLklUjeGw6oRdxF8KI4zgUi0Wv\nJ6zYueBn0wm9IIQVGbtJWAzp8y8IghByROgFQRBCjgi9IAhCyBGhFwRBCDki9IIgCCFHhF4QBCHk\niNALgiCEHBF6QRCEkCNCLwiCEHJE6AVBEEKOCL0gCELIEaEXBEEIOSL0giAIIUeEXhAEIeSI0AuC\nIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4ReEAQh5LQl9Eqp/6KU\nOqOUeksp9TdKqYRS6oBS6oRS6rxS6mmlVKxThRWE9UJsWwgTqxZ6pdQu4D8D92mt7wRs4NeAPwH+\nTGt9CJgGvtiJggrCeiG2LYSNdkM3ESCplIoAKeAq8CDwjfrvTwKfbvMYgtANxLaF0LBqoddajwD/\nC7jM/EMwA7wGZLXWtfpqw8CuVtsrpR5TSp1USp2cmJhYbTEEoeN00rbXo7yCcDPaCd1sBT4FHABu\nAdLAx5a7vdb6Ca31fVrr+wYHB1dbDEHoOJ207TUqoiCsiHZCN/8GuKi1HtdaV4FvAh8F+urVXYDd\nwEibZRSE9UZsWwgV7Qj9ZeAjSqmUUkoBDwFnge8Bj9bX+QLw7faKKAjrjti2ECraidGfYL5h6nXg\ndH1fTwC/D/yOUuo8MAB8rQPlFIR1Q2xbCBuRm6+yOFrrPwT+sOnrC8CxdvYrCN1GbFsIE9IzVhAE\nIeSI0AuCIIQcEXpBEISQI0IvCIIQckToBUEQQo4IvSAIQsgRoRcEQQg5IvSCIAghR4ReEAQh5IjQ\nC4IghBwRekEQhJAjQi8IghByROgFQRBCjgi9IAhCyAmU0CulmJ/n4QZaa1zXbVgWhGaa7Wax7wRh\nM9LWePSdRmu9QMiVUti27S1b1sJ302IPtLwUNg9+2zH/NzsJgrBZCYzQu67bIOgw/8D6hd6yLO9j\nflsKpZQ86JuUVk5DEDGOy2rKauw/COcZhDIIixMYobcsa0HoRimF4ziUy2Vg/mVQq9U88RbjEgx+\n2zHOgW3bgQ3fKKXarnGI/QvLJRAxevOQmo/xcozQl0olb13x0IVW+Gt+kUgEy7ICK/Z+GxeE9SAQ\nHr3WGsdxgHkhN/9rrYlEIqTTafL5PIlEgmQySbFYxHXdRR8W82A7jtNQAxDCi6ntAdRqNRzHoVqt\nBjKEY+xdKUUsFsOyLBzHWVY40pyL/2Xhuu6ytr3Zftu5Tp3YttU+gnbvNiqBEfpqtUqtVqNSqWDb\nNpVKhUqlwuDgIHfffTdXrlwhk8kQj8e9UI4fy7I8QY9E5k9ramqKK1eukM/ngRvVZSFcaK0plUrM\nzMxg2za5XI5arUY8Hm9wHLqNaVsyNphMJtmxYweWZVEoFHAcx7PdVkkJcEPUI5EIsVgMgEql4r04\nbmbj/t/9+zQvx+Xso3lf/mvsbzdo9eJpdWyzvf+FZdrXzPetyi8sn0AIveM4zM3NATcMxMTm9+3b\nxyOPPEI2myUWi2HbdsODa2683ytKJpMAnD59mrm5OU/ozbZiKBsf/z10HIeZmRmuXr1KoVBgZmYG\nx3GIxWK4rku1Wu1iSW9gBEspRTKZZNu2bfT29nrnslQt1Y9lWUSjUaLRKK7rUiqVPJFeKea5MS8L\nU76l8Iux1tp7SawGs32rfTcnUwQtBLeRCITQG4/e/A94IZehoSF6e3up1WoLvA2/92BZlrdNT0+P\nt+6JEye84xijFjY+fqF3XZdisUg2m8V1XXK5XIPQd/ueN2fH9PT0sGPHDlKpFK7rUi6XPc/WrO8/\nP7/nHIlEvI8RSXOOJqFhuY6McaiM1+w//s0wgmzKZWoqKxVj/7atjiF0hsAIfbFYXCDipkpeLBZv\n6rH4hT4SiaCUolKpSHw+pDRnZ9m2TSwW8z6u6xKNRtuOXa8FJlTS7L0aoYaFYtsqJu9f37/NcoW6\n1Tb+7KWlwi+rPa5/m+bzF9aOQAi9UopoNArMG7FppCqXy1y5coXTp097oRu/V95sHOYBSCQSAJw7\nd46ZmRnv9257dsLaYOwnmUySSqWoVqu4rusJfrczXJo909nZWUqlEtu3b2fbtm3E43Ev/GFi9K3w\nh0oA4vG49wLwZ6otF7OuP7XZX2tebF+LvRxW+lJdTnuC0BkCIfS2bbN161bPC7dtm97eXi/u+sIL\nL/D+++/T29vrNcYaj8aPMRqTZpfL5ZienvZ+Ny8CYePTHKPPZrMMDw8zMzNDPp9v8OgrlUoXS3oD\nf2NsrVZjcnLSSwM1mWTGdm/WGGtqMADVanXFDanN+/Q3eq6mMXa1NWf/9s2Nsc0hHXl2V08ghN5x\nHKanpz2hN17N9PQ0ly9f5syZM0xPT2PbNolEglKptCyPo9kAxVDCg/++lstl3nvvPRKJBIlEgmKx\n6Imh1tprjO82zWJYLpe5evVqy0bHVrbaKnZvWK1tdyKLpRPPlTyba0sghH5ycpKvf/3rKKWo1WpY\nlkUqlWJubo5XXnnFC7/4s3OEzY1fGEulEu+88w7Xr1/30mz9IZtcLtetYrbEhFtMQ6ggrDUqCG/S\naDSqBwYGgBsNPeaBnZubY25uTt74wpIs1aBXDwl0JeCrlBLDFdaU5dj2TYVeKfWXwCeBMa31nfXv\n+oGngf3AJeCzWutpNf+kfQV4BCgAv6G1fv2mhbjJw2DimMvpAej/XUYvFAytHoag2Ha9fCs4G2/f\nq9620wShDJuV5Qj9ctIR/hr4WNN3jwMvaa0PAy/VlwE+Dhyufx4Dvrrcwi6F6fRiGoxMlbfVx/+7\niLxwE/6aANi2P5d8JZ92tu30Rwg4y7yJ+4G3fMvngJ31/3cC5+r//z/gc63WW+qjlNKxWKzhE4/H\ndSwW07Zta0A+8lnyo5TStm23/AC6W7bd7esin/B/lqPhq22MHdJaX63/fw0Yqv+/C7jiW2+4/t1V\nmlBKPca8ZwQQmBQ4YWOite5Uw2bHbVsQuk3bWTdaa72aBiet9RPAEyANVkIwEdsWwsJquwxeV0rt\nBKj/Hat/PwLs8a23u/6dIGwUxLaF0LFaoX8G+EL9/y8A3/Z9/+/UPB8BZnzVYEHYCIhtC+FjGY1J\nf8N8HLLKfFzyi8AA8xkJ7wHfAfrr6yrg/wA/BU4D9y2zsbfrDRryCfdHbFs+Yf0sxw4D0WFK4pjC\nWqOlw5QQUpZj2zJxpSAIQsgRoRcEQQg5IvSCIAghJxCjVwITwFz9b9AYRMq1EoJYrn1dPLbY9sqR\nci2fZdl2IBpjAZRSJ7XW93W7HM1IuVZGUMvVTYJ6TaRcKyOo5VoOEroRBEEIOSL0giAIISdIQv9E\ntwuwCFKulRHUcnWToF4TKdfKCGq5bkpgYvSCIAjC2hAkj14QBEFYAwIh9EqpjymlzimlziulHr/5\nFmtWjj1Kqe8ppc4qpc4opb5U/75fKfWiUuq9+t+tXSibrZT6iVLq2fryAaXUifo1e1opFVvvMtXL\n0aeU+oZS6h2l1NtKqZ8LwvUKAmLXyy5f4Gw7bHbddaFXStnMDxb1ceB24HNKqdu7VJwa8Lta69uB\njwC/VS/LYtPLrSdfAt72Lf8J8Gda60PANPMDcnWDrwDPa61vA44yX8YgXK+uIna9IoJo2+Gy6+WM\nfLaWH+DngBd8y18GvtztctXL8m3gYRaZXm4dy7GbecN6EHiW+ZEUJ4BIq2u4juXaAlyk3tbj+76r\n1ysIH7HrZZclcLYdRrvuukfP4lO0dRWl1H7gbuAEi08vt178b+D3ADPb+QCQ1VrX6svdumYHgHHg\nr+pV779QSqXp/vUKAmLXyyOIth06uw6C0AcOpVQG+Hvgt7XWOf9vev51vm6pSkqpTwJjWuvX1uuY\nKyAC3AN8VWt9N/Nd/Ruqs+t9vYTFCZJd18sTVNsOnV0HQegDNUWbUirK/MPwda31N+tfLza93Hrw\nUeBXlVKXgKeYr+J+BehTSpmxirp1zYaBYa31ifryN5h/QLp5vYKC2PXNCapth86ugyD0rwKH6y3t\nMeDXmJ+2bd1RSinga8DbWus/9f202PRya47W+sta691a6/3MX5vvaq1/Hfge8Gg3yuQr2zXgilLq\nSP2rh4CzdPF6BQix65sQVNsOpV13u5Gg3rDxCPAu89O0/bculuN+5qtjbwKn6p9HWGR6uS6U7wHg\n2fr/B4FXgPPA3wHxLpXpQ8DJ+jX7FrA1KNer2x+x6xWVMVC2HTa7lp6xgiAIIScIoRtBEARhDRGh\nFwRBCDki9IIgCCFHhF4QBCHkiNALgiCEHBF6QRCEkCNCLwiCEHJE6AVBEELO/wek9ZFhDMbjcgAA\nAABJRU5ErkJggg==\n",
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0ZGPhBw8etPU3rZW+vj4rlidOnKBWq5HNZm3mTr1eZ2ZmhnvuuYeJiQmSySSL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\nvh7cmwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00ad128>"
+       "<matplotlib.figure.Figure at 0x7f884c27b748>"
       ]
      },
      "metadata": {},
@@ -4076,20 +4200,20 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.841 (Action Taken)\n",
-      "FIRE        0.834 \n",
-      "RIGHT       0.822 \n",
-      "LEFT        0.838 \n",
-      "RIGHTFIRE   0.833 \n",
-      "LEFTFIRE    0.831 \n",
+      "NOOP        0.812 \n",
+      "FIRE        0.824 \n",
+      "RIGHT       0.810 \n",
+      "LEFT        0.829 (Action Taken)\n",
+      "RIGHTFIRE   0.807 \n",
+      "LEFTFIRE    0.818 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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TOKFvhd8IFnviC4IQTGKxmNeCLJfLDVNnm9HPJjy5EjEPykC/zUDghd50Qvq3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\nPe0JvcmamZ6e5urVq5w5c4b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Zs4exsTGSySQLCws2/dP3/SaRX+o6fd+3+fvFYtHG+13XJZ/P8/rrr/OLX/wC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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be00dac88>"
+       "<matplotlib.figure.Figure at 0x7f884c0b8588>"
       ]
      },
      "metadata": {},
@@ -4101,12 +4225,12 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.833 (Action Taken)\n",
-      "FIRE        0.831 \n",
-      "RIGHT       0.809 \n",
-      "LEFT        0.829 \n",
-      "RIGHTFIRE   0.824 \n",
-      "LEFTFIRE    0.827 \n",
+      "NOOP        0.861 (Action Taken)\n",
+      "FIRE        0.854 \n",
+      "RIGHT       0.851 \n",
+      "LEFT        0.846 \n",
+      "RIGHTFIRE   0.853 \n",
+      "LEFTFIRE    0.845 \n",
       "\n"
      ]
     }
@@ -4132,7 +4256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true,
     "deletable": true,
@@ -4212,7 +4336,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 43,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4222,9 +4346,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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pSqVCIpGgVCpx5coVO2rW9PCjRLhHn0qlmJ6eJpfLXTeeIEzzMZvRwo7j4Hke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\n7xAJoVdK2UfDIAiIxWLE43E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UHNbVaMeo0U5sez3CI5bDI2NbHWYJlyYGIjkDmdAbNIZuFhcXuXDhAsePH+fS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\nC4Ig9Dgi9IIgCD2OCL0gCEKP8/8B8s+udmS2ndkAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be01804a8>"
+       "<matplotlib.figure.Figure at 0x7f884c17c470>"
       ]
      },
      "metadata": {},
@@ -4252,7 +4376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4269,9 +4393,9 @@
     },
     {
      "data": {
-      "image/png": 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RmhEAoKieNSMbN27Mxo0be7U7AGBMSEYAgKI0IwBAUT17a+8v/MIvJEluvfXW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\nxmnSWLcTWHfu3Jkkuffee7u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QumuvvTZJcuuttxauhOVqJ93oViKyatUzeUQP0pCWSUYAgKI6SkZWr17drTqG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\ncRKoNwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be022a9e8>"
+       "<matplotlib.figure.Figure at 0x7f884c148c50>"
       ]
      },
      "metadata": {},
@@ -4296,7 +4420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 45,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4313,9 +4437,9 @@
     },
     {
      "data": {
-      "image/png": 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AAJxDBwcAADiHDg4AAHAOHRwAAOAcOjgAAMA5dHAAAIBz6OAAAADn0MEBAADO\nqQ1TuKamxq+tHf9LhoaGNG5oaBARkUWLFumxgYEBjV955ZVDyoqIHHPMMTnL2J3PjzzySI37+/s1\n3rZt2yF1KqZsNpvV/2azWe/Q7yxenucV3Pbd8w5WO2gr+/MaHh7WuKbmYN82+N7HK19Bnb7vt8dx\n4fF4nufb9s2lublZ46B9u7u7851P45aWFo1t+XzXs78H+c5ZStm3yye2/Uv5usmTJ2vc09NTsLz9\nGfb29hZTL43ztXWYsr7vp/LZ4win7v1JkyZpbD+Xoyrf2NiocV9fXxRlI2//UB2c2tpamTFjxrhl\nbKdh4cKFIiLyyCOP6LGNGzdqfOaZZ2q8YMECjR9++GGNTz/9dI1to//gBz/Q+NVXX9X461//+iF1\nKqZs0PHat2/fIV+fFrZzErTV9OnT9diOHTs0bmpq0tg++POVL+aahTpERZbdXPCiMfA8Twp17js6\nOjQOfqHtvW/Zh4m9x215W8Z+IOZ7+OSqX5iyb5dPZPuX6uSTT9b4mWeeKVh+6dKlGv/+978vWN7+\njAYHByMrmzT2D6Jc7B9J5bx2vuvkql+Ysm+Xd+renzlzpsZbtmwpWL69/WDfYuvWrQXLL168WOMX\nXnghirKRtz8pKgAA4JxQIzie5436K6SQl19+WURE5s6dq8duueWWnGXXr1+v8bx58zS2fxXv3LlT\n4//93//V+MUXX9Q4V/2KKRuMKBRKQyRZrr/Wu7q6cpbNN1xfzKiNFSaNFVPKKxK+7xcctn3yyScP\nOXb++edr/NBDD2ls/4K3ozb2frd/RRXzF1Uxw8qllE2zYkZtrGJGbawwIzFpG7WxyjlCE8W1w9TP\nlk3z8z6f8847T0QOZlBERG699dacZc8++2yNN23aVPDchx9+uMZ79+6NrGy5MIIDAACcQwcHAAA4\nxyv05v+owlXyNr2rMxnCvPU+nilTpmicb5ZQmLKf+9znNL711ltX+b7fkbNgjOrq6vzZs2ePW8Z+\nf7leVp86darG9iXf3bt3F7y+TdvalwHt0G+utFMxZb/4xS9q/KUvfSmR7Z/JZHw7wymXSy+9VOPb\nbrtt3LL2+y8m7W5nuu3fv1/jO++8U+OrrrrqkK8rpqwtk9Znj723C03UsLNq7aSPsGbNmqVxodR6\nkWUTee+X+uyvr6/X2M5ezsfOZLazjfNpa2vTON+rECHLRt7+jOAAAADn0MEBAADOCZWiymQyvl04\nyyXB8Fyo7BnfAAAgAElEQVRXV5cMDQ0lcpi40FoUaWXTNYODg4kdJs5kMnFXoyxGRkbs/ya2/V2c\n8SIyeo2jpKaoqqHtJcH3vqvPfntfjYyMkKICAAAohA4OAABwTqiF/rLZbMFZM2llty5IqjgX28Ih\nqZxUK7TtRBKFSacjWrR9vHI9++3MpDSxz55Cs68mihEcAADgnJL/jDvppJM0jmsZ5omym5G98cYb\nMdYEqKw0b5sBoPyjH+ViXywu98QNRnAAAIBz6OAAAADnlJyicmFdBFfXNUF52TUpePEbAIpXyRfW\nGcEBAADOoYMDAACcU3KKas2aNVHWIxZ25lSwGy7rPVTG0qVLNV6/fn2MNQnPpqXsTLw02blzZ9xV\nCKW5uVlOPPFEERF57rnn9HhjY2NcVZqQvr6+uKtQtEwmI62trSJS3M73iNakSZOkvb1dRES2bt0a\nc22iVe7PW0ZwAACAc+jgAAAA54RKUXmeJ3V1dSIiMjAwUJYKxSXYTby3tzfmmhRmZ/GkdTbbxo0b\nNU5bWtDOvkvrkH19fb3Gafhd7uvrkxdffFFERtc9rQsW2nso6VuAjIyMyL59++KuRtUaHh7W50xa\nn/eWfd6X+/thBAcAADiHDg4AAHBOqBTVlClT5IwzzhARkRkzZujxBx98UOOkD7daaaqrZWfxpHFX\naBGRoaGhuKsQSiaT0Zl25557rh6/++6746rShKTt3s9msznTx9OmTdM4remq/fv3x12Fotn23rNn\nT4w1qR6+7+dMI9sZhGlK89tnD7OoAAAAQqKDAwAAnOOFGSLyPK9g4Si2QrdDzVOmTNG4u7tb46OP\nPlrjDRs2aJwrZVPM0PXs2bNFRKSzs1OGhoYS96p6MW2fVsHMPBGRwcHBVb7vd8RYnZxqamr8YKad\nXaTtAx/4gMaPPvpopNc8/fTTNX722WcjPXe+3x8RSWT7h73/J0+eXNJ1enp6Svq6fNcMez7f91P5\n7LHP/UqlS8qwJ1zi7/2LL75Yj+dLj9vnaRiDg4MFy4x5Vo97zWLOZz+vh4eHI29/RnAAAIBz6OAA\nAADnlJyi+tKXvqTHv/Od72jc3NyscaUWzTv22GM1LrSv0eLFizW2Q8pvvvmmiIh0dXUlMkWVyWT8\noG2/973v6fFPfepTcVUpMmlIUXV0dPgrV64UkfyLU9n9ta6//noRCZ8qWb58ucZdXV0aB3vRiIic\nddZZGj/55JMa33nnnYdcM9/5xpHa9ndBElNUbW1t/vvf/34REbnnnnsKlm9qahKR8K8o2FcJwu7V\nleuaJZwvkff+8ccf7//iF78QEZGTTz5Zj5999tkaP/XUU5Fe0z7Lot530v6M7O8yKSoAAIAi0MEB\nAADOiWQW1V133aXxxz72sQlXqrW1VeNg6FFk9FbxYfbSyXe+ww47TOM33nhDRJKborJtb39mweJz\nIqNnmaVJGlJUtv2vu+46Pf7v//7vGqdpwbZxJL79rVmzZmm8Y8eOitWnXJKYoqqW9KCk7N5P235y\nuTCLCgAAICQ6OAAAwDmRL/R3xBFHTKhClTRz5kyN05Sisr785S9r/K1vfati9YlS2lJU1n/8x39o\nfM0111SsPmWUqvZ3TRJTVK2trf673/1uERm9uN6vf/3ruKpULqm69+1nbfD5lTakqAAAAEKKfCtq\nu17Hrl27oj49xvjDH/6g8cKFCzXeuHFjHNWpOj/60Y/irkLVsRMFDhw4EGNNqsO+ffvkgQceEBGR\nJUuWxFwbBE499VSNW1paNF63bl0c1UkkRnAAAIBz6OAAAADnlPyS8UknnaTH165dm7P8GWecISLJ\nfQHKhZeMrY6Og+9nBetWpEGaXzK2itnpNwVS2/4uSOJLxtXS9uLIvR+sVVSpXd0ngpeMAQAAQqKD\nAwAAnBPJLKp88/GfffZZERGZN29eFJdBATYtFaQQ86UPEb0Up6WACbHr42Sz2RhrgjSkpiqFERwA\nAOAcOjgAAMA5kS/0N+ataBER2bZtmx6bM2dO1JdEDkFqatKkSXpsaGgoruoAcFhjY6PGvb29MdYE\nOIgRHAAA4Bw6OAAAwDmRp6gOO+wwjffs2SMiIvv379dj7CNTWW1tbRrv2LEjxpogWIBLhJkOcEuu\ntFRzc/O4/47KqdZnDyM4AADAOXRwAACAcyJPUVnTpk0TkdEpqvXr12tsFwhEedi0lJ3p0NfXF0d1\nqlpDQ4PGtD9cR1oqOar12cMIDgAAcA4dHAAA4JyypqgC+faqYv+SyrJDkywAWHnVNDQMIDmq9dnD\nCA4AAHAOHRwAAOCciqSorJkzZ2q8detWjWfMmKGx3c8K5UFaCkCl5NqjEPFz/TURRnAAAIBz6OAA\nAADnVDwXZBccsnuV2AXp5s6dW9E6VbtMJqPxyMhIjDWpTizACNfZtBTPm+RwMS1lMYIDAACcU5ER\nHLv2zQ033KDxtddeq/G3v/1tjW+99VaN6+vrNbZ/BUTxkqx98c3VHVbzrUHU0tKi8cDAgMb2r6vB\nwcEy1+6v6urqKn7NSjn22GM1ttuUWHGP2kyePFnjnp6eGGtSOUuWLNH4zTff1Hjfvn1xVCfxgpdR\no/iLP0mjNtUymtTe3q7xwoULNbb3+2uvvaZxpdrCjl7bLZ2iwggOAABwDh0cAADgHC9Maqaurs6f\nNWuWiIi0trbq8e7u7nG/zqZGohLFTuS2XpdeeqmIiDz88MOye/dub8Inj5jneWXLoXnewW833/1Q\nzvUS7Ivn/f39q3zf74j0AhEoZ/tfddVVGt988805y5RzKH3MS85Otf+NN96osU2JJ5Xv+4l79mQy\nGT/4HT1w4EDRX2fTIrt27Yq8XmXg1L1vXXLJJRrbtejuvfdejd96662JXmaiIm9/RnAAAIBz6OAA\nAADnhEpR2aFKO/PCphjSZMuWLRoH30NfX5+MjIwkbpi4nCmShHF2mDip7DYpnZ2dtH+Mkpiiqpa2\nF549cSNFBQAAUAgdHAAA4JxQC/1lMplRs6cCad0dNpgRJnJwgTm76B1QDTo7O+OuAhCLYmaQIr0Y\nwQEAAM6hgwMAAJwTKkU1NDTUuXXr1s3lqkxCzI+7Anl0iojrbS9C+8eN9o8PbV9hY9JStH+8Im//\nUNPEAQAA0oAUFQAAcA4dHAAA4Bw6OAAAwDl0cAAAgHPo4AAAAOfQwQEAAM6hgwMAAJxDBwcAADiH\nDg4AAHAOHRwAAOAcOjgAAMA5dHAAAIBz6OAAAADn1IYp7HleqK3HPc8b9V8RkWw2O27ZYsuXk+/7\nXuFSleV5nm/bJRe7M3xra6uIiOzdu7fguadNm6bxnj178l0/53XylQlTdkyZTt/328epbizC3vvT\np08XEZH9+/frscHBwZxl29raNO7p6dF4aGhI43ztGIUxPwsn2r+lpUVERrdhf3//uGWLLW/V1dVp\nnO/nW6hs0P6+7yf22ROmfE1Nzaj/iogMDw+PW7bY8vm+ttDnRJFlnbj3A1OnTtV43759BctPmTJF\n4+7u7lIuOVGRt3+oDk5YkyZNGvVfEZHe3t6cZevr6w/5OpHRHxDVzPO8UW2Ui30gn3322SIi8utf\n/7rgud/73vdqfN9992lcW1ubM8734M9Vv2LK2ofZ8PDw5oIVjkkmkxn330dGRjQ+//zzRUTk6aef\n1mObNm3K+XVBWRGRp556SuPt27fnPLeNC9WvmLI2HhwcTGz7h3HaaaeJiMhbb72lx9avXz9u2bHl\nX331VY3zfSgefvjhGm/cuHHcOuUrG/xuFfOhngaTJ08WEZHGxkY9tmPHjnHLiog0NDRovHPnzoLX\naWpq0tj+YTCBsk7c+4EzzzxT4//+7/8uWP7000/X+JFHHilLnQqIvP1JUQEAAOd4YYa+Sx0qs+xI\nQDF/sRSTGrG98wMHDox7vmLKujBMnCZj7olVvu93xFidnGpqanxbz1yOO+44jdeuXSsio7+3ZcuW\nafz8888XvOb8+fM13rp1q8Zz5szR+I033tDYjnyGKWtHcPr7+xPZ/p7n+TbNkIsdZfnHf/xHERE5\n9thj9dg111yT8+vsKMKiRYs0tiM49llhr7N48WKNX3vttXHrlK9s8LMYHByUbDbLs6dI8+bN0/jN\nN9+Momxi7/2461Ahkbc/IzgAAMA5dHAAAIBzypqiCt7KLuaN7GJSUZVCiipWVT1MbNMYr7zySiUu\nOZaz7d/c3Kyxnexg03jbtm0reB4766rQJIgwZUWS+ezJZDK+fWE4lyOPPFLjl1566ZB/X7JkicbB\nDE8RkWeeeSbn+WwZO7PNvqhtXxbONVu0mLJjJr0k8t5vbm72bao1l9WrV2scvDRv0+D5ZvDZNPjm\nzQff8T355JM1tqnhv/zlLzm/1r76EabspZdeqvE111xDigoAAKAQOjgAAMA5FZ9FlQZJHCb2PM8P\nZrsUWvAvbew9ODIykshh4mJm8aSVbX/f9xPb/oXWIUq7kZGRxD574q5DhST23o+7DhVCigoAAKAQ\nOjgAAMA5Zd2qIekWLFigcb5l9JMkSE25sqR7IC2pnzj2RSsXu7idXcQu7hmM4wm2nTj66KNjrsnE\nbdiwQWPXU29AXNLxyQIAABBCVY/gpGHUxnJt5CaQ5FGDXGbMmKFxMbv0JlGS1p0Ka8uWLRoPDAzE\nWJPSzZw5U+Pdu3fHWBPAXYzgAAAA59DBAQAAzqnqFBVQirSldHJJ8/eQ5roHXE03A0nCCA4AAHAO\nHRwAAOAcUlSIXRpSDpMnT5Zly5aJiMhTTz0Vc20mzu7QnLatP/r7++OuwoQdccQRGufafTup7O7o\ndlfqNLHrKK1bty7GmoRnd0hvaGiIsSalq6+v17jc7c8IDgAAcA4dHAAA4Bx2E88hqTv6Bku6B0vW\nu2LMonOJ3NE3k8n4jY2NIuJGisTeQ2lof8/z/KCeaUhphmF/r5P67Im7DhWS2Hs/7jpEKXiOioj0\n9fXZf2I3cQAAgELo4AAAAOeEmkXleZ7U1dWJSHr3gEkz11JTaZLNZqW3t1dERJYsWaLHX3/99biq\nNCE2zZaWfaly1c3uxJ222WCBJLc5ELVKzr5jBAcAADiHDg4AAHBOqBSV7/s5U1MzZ87UeOfOnROv\nlTF9+nSNd+/erbFdrGnDhg0lnXv+/Pkab968uaRzoPrkW5ht0qRJGtuF9MrJLvZV6uyutKV2vvOd\n72j8pS99KWcZm7oKI18aeM6cORo3NzdrbJ89ua5pz3feeedp/Oqrr2q8adOmkuoKVMLkyZM17unp\nmfD5KvmqBSM4AADAOXRwAACAc0pe6M8Ox0Y95BR2Vkeh8mHPx2JbsUrkYlsdHR3+ypUrRUTks5/9\nrB6//fbbNV64cKHGGzdurEi9zj33XI0fe+yxccs2NTVpXFt7MDu9f/9+jZO80F8Qn3TSSXr8+OOP\n1/iXv/xlpNe87LLLNP7JT34y4fPZdOLUqVM17uzsFJF0LPR3zjnn6PEnnngilvqUUeLvffv5lbbU\nchFY6A8AAKAQOjgAAMA5Jaeo7Ncdd9xxGq9fvz6iqsUn6cPElk2L2JlgUaQN7aygbDab89xhZvHk\nm2WUlr2Qch0PFr4UqewCVhNlZ0YECxiKpKP97bPn8MMP19jeX4sXLy7pOjt27NB47dq1Gh9xxBEa\nt7a2arx3795xr5nvfDNmzNA4mB2ahhQVKZLKs+3/D//wD3o86pRsApCiAgAAKIQODgAAcE7JKSrr\nnnvu0fiiiy6aeK1ilsRhYjuLx7Wh4TSnqCybIkm6+vp6jdOWorL++Mc/avzOd76zYvWZqLSmqKzT\nTjtN4+eff75i9SmjVN37DiJFBQAAUEgkIziWXcbc/mWYJkn/K8q1ETNXRnDsOjOV2qqhVK6M4Fgn\nnHCCxn/5y1/KWp+JSusIjl2/Z9++fbHUp4xSe+/b0cvnnnuurPUpI0ZwAAAACqGDAwAAnBNqN/Gi\nTlgb+Skxhk1LLV++XOP77rtP41NOOUVERFavXl25ilWJfDvcHzhwQONgfZwwKWAUp7GxUeO+vj6N\nX375ZY2nTJkiIqO3ocDEOZiWckKw3QdGYwQHAAA4hw4OAABwTuT5JIYwK8umpSxSU5WRb/uJYNuG\nNK2Nk0Y1NQf/RrPbicybN09ERqetAFdt2LAh7iokEiM4AADAOXRwAACAc5jy5JAlS5Zo/NJLL8VY\nk+pk01FBPDw8rMeYUVU5wf1vZ1wNDAzEVR0AMWAEBwAAOIcODgAAcA4pKofYtNSiRYtEROTVV1+N\nqzpVzS76lwuzq6KXa0aVXQiQdBVQXRjBAQAAzqGDAwAAnEOKylFBamrOnDl6bNu2bXFVp+oEKSi7\n+B8qJ0hX2cX/bLrKprMAuInfcgAA4Bw6OAAAwDmkqBxHWipedraUXfTPpq6YUVU++faqsosuep5X\n0ToBqAxGcAAAgHPo4AAAAOeQoqoi06ZN03jPnj0x1qQ61dbm/nUjXVV5NkWVL40IIN0YwQEAAM6h\ngwMAAJxDiqqK2LTUlClTNO7u7o6jOnibncVDuqp88s2oIi0FuIkRHAAA4JyKjOA0NTVpXGiX5Uqq\nq6vTeHBwMMaaVMaSJUs0tjuPF6OcP0P7wqdr7IhMR0eHxg0NDRo/++yzOb/WtouNo9hmwN7vLre/\nHak56aSTNLa/+9u3b9d4165dGtsRNPtzjGL7Dfvzz7WthMvmzZunsR1V7unpiaM6VWfGjBkad3Z2\nxliT8k98YQQHAAA4hw4OAABwjhdmeDqTyfiTJ08WkehfTI1j2MwOEwcGBgYkm80mbu12z/P0B5XU\nlF9EVvm+31G4WGXla/9C6Yorr7xS45tvvjmSukTx8rGtd319vcYDAwOpav/+/v5xv66YtE/YVHUU\nKUJbr+CF/56eHhkZGUn0s6dUs2fP1vhd73qXxrYdfvOb30z0MhOV+HvfcZG3PyM4AADAOXRwAACA\nc0KlqKplqMz3/UQPE+eb3ZEm46zDk6ph4rSuVTPOfZPI9m9ubvaPPfZYERFZs2aNHk/rDLAg1S9y\n8Hdhx44dMjg4mOhnj+MSee/T/qVjBAcAADiHDg4AAHAOWzWkhOd5OXejTmuKpK+vT+O0zArL1f5p\nTZHY7yWTyWg8MDAQR3UK6uvrk7/85S8iMnrWU1rZFOHu3btFhC0jgKgxggMAAJxDBwcAADgnbIqq\nU0Q2l6MiCTI/7grk4vt+59DQkJNtP2ZGTyLbX0Q6h4eHnWz/MamRRLa/7/udfX19Tra/kci2l+p4\n7ovQ/nGLvP1DTRMHAABIA1JUAADAOXRwAACAc+jgAAAA59DBAQAAzqGDAwAAnEMHBwAAOIcODgAA\ncA4dHAAA4Bw6OAAAwDl0cAAAgHPo4AAAAOfQwQEAAM6hgwMAAJxTG6aw53nObj3ueZ6IiPi+L77v\nezFX5xCe5/k1NeP3R9/xjndovG3bNhER2bp1qx6bPn26xrNmzdJ47969GtvymUxGY7vrfGtrq8Zd\nXV0a56pfMWWz2az9kk7f99sPOVHMorj37c/nz3/+c8nnWbZsmcarVq2KrOzbEtv+he7/trY2jTs7\nOyO9/jj3a84ypZZN6rOnUJm5c+dqPDQ0JCIiBw4c0GPz58/XeP/+/Rr39/drbMv39PTkvM6SJUs0\nfvnllzXO1c5hyr4tsfd+oTJTpkzRuLu7e9yy9rk+MjIygZpFLvL29+wHV8HCnufX1o7fJxoeHp5o\nnfKy1853nVz1K6Zs8EMfHByUbDabuIdMJpPxm5qaxi1jHxzf+MY3RETkK1/5ih67/PLLNb766qs1\nXrFihcZf+9rXNJ42bZrGwUNLRORDH/qQxj/72c80njx58iF1KqasfcgNDw+v8n2/45ATxSyKDk5v\nb6/Gzc3NJZ/H/s4GHfMoyr4tke2fyWT8xsbGcctcfPHFGt9xxx0TvqZ9PtTX12tsf45Wrp9pMWWD\nn1F/f7+MjIwk7tnjeZ5f6N654YYbNA7+uPrTn/6kx374wx9q/OSTT2r82muvaWzLP/PMM/b6Gr/y\nyisa2857rg5RMWXHfP4l8t4v5tlz3nnnafzII4+MW9Y+1/fs2TOBmkUu8vYnRQUAAJwTegSnjHXJ\nadKkSRrbUQTrlFNO0Xj16tXjnq+YsmkdJrZuuukmERH5whe+EOo6//RP/6Tx97///VBfG5HU/hUV\nhzB/uRVZNpHtX1tb6+caIbT27dtXtutPnTq14HVsmTBlgzTBgQMHEjuCU8rX2VGvgYGBUF8b0yhD\nIu/9Ytr/kksu0fjnP//5uGUXLFig8aZNm3KWmcjPbgIYwQEAACiEDg4AAHBOWVNUs2fPFpHRb3Wf\nfPLJGv/+97/X+LTTTtP4+eefL3juCy64QOMHHnhgwmWDWUW7d++WoaEhZ4aJ0+A973mPxr/73e9S\nO0xcqjPOOENj+3JlTBLb/oUmONiZPJs3bz7k3+fMmaPx0qVLNX700Udzns+W37VrV84yxx9/vMZ2\npk6YsnYShAvp8RRL7L0fdx0qhBQVAABAIXRwAACAc0KnqOwiQS4J3hpP8loUrrZ9XV2dxn19fQwT\nxyux7R+kqIpczyc17OzQpKaoCi2ymFZjFv1L7L0fdx0qhBQVAABAIXRwAACAc0LtRSVycFEqOxvK\n7rGTJnZ48he/+IWIHLJ0d6IkbN8QoKLKuQ0MxhekBXkGVV57e7ssX75cREQefPBBPb5ly5a4qjQh\nlfyMZQQHAAA4J/FbNVRKsCXE8PBwIjfbdLnt7SaKvGQcu0S2v91s1r5knNaXX/Nt4ZDEl4xramr8\nYCKAfSF6nF250yqR9z7PntKl8+kAAAAwDjo4AADAOaFfMgaAOASpKbtlg4NpkkQK2t61NYjSJqZd\nvlOLERwAAOAcOjgAAMA5VZ2i+tznPqfxf/3Xf4kIa23EgTQDCslkMjJlyhQR+et2KoGenp64qlQ1\n6uvr5aijjhIRkXXr1sVcm+pGWiocRnAAAIBz6OAAAADnVHWK6tZbb9U4WOgvyYLdxF1bLt3VXdIR\nneHhYdm9e7eIMExfaQMDA/Lqq6/GXQ0gNEZwAACAc+jgAAAA51R1iipNWltb5T3veY+IiKxYsSLm\n2kQryTu45/Ld735X46uvvjrGmlSXIDWbtvsl7XzfH7UHVcAuuJgmaZspO2fOHPn0pz8tIiLXXXdd\nzLVJF0ZwAACAc+jgAAAA53hhhnvttu326xYvXqxxe3u7xn/4wx9KqlTYhd+WLVum8Z///Odxz3f0\n0UdrfOaZZ2p81113ichfhy9930/chiu27fOZP3++xps3by5rfQILFizQeNOmTSWdo7GxUeO+vr5V\nvu93TLBakSum/eNgZ6BFNLsuke1fV1fnB8+WrVu35izT3NyscW9vb0XqNX36dI2DWV4TkcRnT01N\njV9XVyci5Z3BFiwmKCLy+uuva2z3vwrzeZXvfONI5L1fqWfPVVddpfHNN9+s8ac+9SmNgwVxJ3K+\ncUTe/ozgAAAA59DBAQAAzik5RfX000/r8YceekjjG264YcKVskNbdgjezl659tprNb7xxhuLPl++\nobJgob/h4WHJZrOJGyYOO0wZ/EymTZtWzLk1/upXv6rx448/HuaSes22trZQ50tDimrhwoX+v/3b\nv4mIyMUXXxxzbcoqke3f0dHhr1y5UkRG36+zZ8/WePv27ZFec+rUqRrv27dvwuezi4nmmpUkkswU\nlX32nHHGGXr8mWeeiaU+pQhSbCIig4OD+Yql6t53ECkqAACAQujgAAAA55ScosqnpuZgn+nd7363\niIh0dXWFqtSaNWvyXV9jO2Oip6dH42AxPHvNfOezXEtRpUkaUlQut/8YiWz/U045xX/qqadERGTK\nlCk5y5x00kkaBymlsEP6nZ2dGttnjE2FvfbaaxqfeOKJGgcpMnvNfOfbsWNHzusnMUVlUyQXXXSR\nHv/Vr34VV5XKJZH3Ps+e0jGCAwAAnEMHBwAAOCdUimrWrFn+Rz/6URER+d73vleuOsUiTSkqu6Ce\nXWgvrUhRJUpq29/Oekq6fLOykpiiam9v9z/84Q+LiMgPf/hDPW73YbMzXFMstfe+I0hRAQAAFFLy\nS8YNDQ16vL+/P9paxSBNIziWfdHv7//+7ytWnyileQTnlltu0fjzn/98xepTRols/0wm4wf3STHb\nMCR9NCdNIzg1NTV+fX29iIhcfvnlevy2227T2K4Ndffdd1euctFK5L3PCE7pGMEBAADOoYMDAACc\nE/k6OGmV1hSVdd9992m8fPnystYnSmlOUVl2HZa1a9eWtT5llMj2tymq2tpaPW63P7BrzgSSmqpK\na4rKvo6Qb9uGYIf1KHZXr7BE3vsuf+6OQYoKAACgEDo4AADAObWFi5Qu2LYhm82W8zJ42yWXXKLx\nYYcdJiIiW7dujas6VSfFaanUyrcrN8rPpqXsVhZz584VkVSmqOAYRnAAAIBz6OAAAADnlDVFFaSm\nTjjhBD22bt26cl6yqg0MDGhMagrVJkiJi4jMmjVLRES2bdumx5I6o8oF3d3dGge7qjc1NemxAwcO\nVLxO1aS1tVXjvXv3xliTZGEEBwAAOIcODgAAcE5ZU1Tt7e0iQloqTh0dB9dNWrlyZYw1AcqrpaVF\n41wzeOzieqSropUrBWUXZAwWChQZnUpHNEhL5cYIDgAAcA4dHAAA4Jyypqh27dpVztOjCDYttXTp\nUo3XrFkTR3WAigj2rbIzq+w+Sig/O7PK7hkGVAojOAAAwDl0cAAAgHPKmqLKpaGhQWOGjCvLpqU8\nz9PY9/04qlN1bLqE/dkqw87ese3PjKrKsnuGzZgxQ+POzs44qoMqwQgOAABwDh0cAADgnIqnqEhL\nJQNpqcqzaSk7q8QO36N8bFp25syZGu/cuVNj0lXlZ9NS/B6gnBjBAQAAzqGDAwAAnFPxFJXFTB5U\nK4bjK8/ujdTb26uxnWll91RqamqqTMWqjJ3NZn8PmGWIqDGCAwAAnBPrCE6SRm1c/Yv6a1/7msZf\n/yw8bkUAAAoASURBVPrXY6xJfnYkzzXsohyNbDaroyv2ReBCzxC7PcnTTz8d6pp2rRyr2l5E9jxP\nR1fCjLq/733v0/jUU0/V2G4f88wzz2hsR8/saI5V7SM7YdrfjlgODw+XrU5JxggOAABwDh0cAADg\nnFApqoaGBlmwYIGIiKxfvz7aihQxnFbONRMOP/xwERHZsWNHpOeNSmNjoyxevFhERF544YWiv66Y\ntNSFF16o8b333puzjH3h0g4ll+r222/X+Morr5zw+ZKqmLTU5MmTNe7p6SlndVItGJK3LwgXehF4\ncHCwrHWqBjY9GOzSLiLS19c37tcFnxUiIj/60Y803rZtW8FrJun1hSQJ0y7bt2/X2G6PUU0YwQEA\nAM6hgwMAAJzjhRnyymQyfjBEaYeJXTBt2jQREenu7pbh4eHETevxPK9axmxX+b7fEXclxnKt/TOZ\njMZj1oFJZPvX1NT4QRq7paVFj4+MjMRVpQmxbb5r1y4R+Wv6wfd9nj3xSeS9T/uXjhEcAADgHDo4\nAADAOaFmUWWzWedSU4E9e/bEXQWgYmxqJ4pZcZUQpKgKzd5JAzu7q6GhQURE+vv746oO4CRGcAAA\ngHPo4AAAAOeE3YuqU0Q2l6MiCTI/7grkUQ1tL0L7xy2R7e/7fmdfX5/r7Z/Ithfu/bjR/iUKNU0c\nAAAgDUhRAQAA59DBAQAAzqGDAwAAnEMHBwAAOIcODgAAcA4dHAAA4Bw6OAAAwDl0cAAAgHPo4AAA\nAOfQwQEAAM6hgwMAAJxDBwcAADiHDg4AAHAOHRwAAOCc2jCFa2pq/Nra8b9kaGhoQhUaz6RJkwpe\nx5YJU9b3fRERGRkZkWw2602knuXgeZ5fytfV1dVpPDg4GHn5mpqDfeRsNhtF2U7f99sLXjgCM2bM\n8BcsWFCJSzlp1apVE/pZ0f6lo+3jRfvHq9j2D9XBqa2tlRkzZoxbZtu2bWFOGYq9dr7r5KpfMWWD\nTtDevXsnUsXEOfzwwzXeuHGjxrajOjw8XLB8Ps3NzRrv378/irKbC140IgsWLJCVK1dW6nLO8Txv\nQj8r2r90tH28aP94Fdv+oTo4IyMj0tPTU1qN3vaxj31M47vuuqtg+UWLFmlsOyrnnHOOxk888YTG\nuepXTNngQ35kZKRgndLkyCOP1Hj79u0aHzhwIGf5LVu2FDxnY2Ojxr29vZGVBQAgKryDAwAAnEMH\nBwAAOCdUiqqtrU0+8pGPjFvm9ttvH/fff/Ob3xS8zte+9jWNb775Zo0/+tGPapwvlWTLhCl7//33\ni0h5X5KeCM/zcr5AbdmXgufOnSsiIn/84x/1mE0X2RRVfX29xva9pO7ubo0HBgY0tu/vTJ8+XeOd\nO3ceUqcwZcd+DwAAlIoRHAAA4Bw6OAAAwDmhUlR79uyRe++9d9wybW1tRZ8vX9lbbrlFY887uCRN\nvmvb84Spny0bTI9O6kwf3/c11Ras2TOWXWcm19R4+73ZsjYtV8w0fzutvFB7FVPW/owBAIgCIzgA\nAMA5dHAAAIBzQi/019XVVa66xCqYPVRou4E4ubYIYSCTycRdBQCAYxjBAQAAzgk1gpNPS0tLFKep\nOLsfUpJHbsayL+Xme+EYAIBqxggOAABwDh0cAADgnEhSVC6w68IAAIB041MdAAA4hw4OAABwTqgU\nVUtLi3R0dIiIyKpVq/T4e9/73mhrVSErVqzQOOmzqDzPk4aGBhEZvW6M3eU7Tez2EMwEAwBEjREc\nAADgHDo4AADAOaFSVL29vfKnP/1JREandB599NFoa1UhM2fO1Li29q9NkdSdrX3f17SOTe+kFdsz\nAADKiREcAADgHDo4AADAOaFSVNlsVnp6espVl4rr6+vTuLW1VUSSPaNneHj4kGPBzCqRZNd9LFtX\nV3dJBwDEhxEcAADgHDo4AADAOexF9bY0pEmC/bIWLVqkx9avX5+zbDArLKxcabBi5bpmMedjRhUA\nIGqM4AAAAOfQwQEAAM4hRfW2pC7wF5g7d65cddVVIiLywx/+UI+3t7drvGvXLo0nkmoKHHbYYRrv\n3Lmz4LkLXTNIsYkkf+8vAEC6MYIDAACcQwcHAAA4hxRVSsyePVuuvfZaERFZvXq1Hn/44Ycjvc7k\nyZM13rp1a84yjY2NGvf392uca6FBez6XFokEACQbIzgAAMA5dHAAAIBzQqWoli1bJitXrhSR/LOO\nWlpaJl6rCtm/f3/cVSjayy+/LEuXLhURkf/8z//U4+vWrdP4pZdemvB1ikkj2T28ojgfAABRYwQH\nAAA4J9QIzqpVqwquF2NHRdI0mpN0fX19snbtWhERueiii/T4mWeeqbF9Kbirq6tylQMAIGEYwQEA\nAM6hgwMAAJwTyTo4t912m8ZXXnmlxkG6ilRVtDZ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sv0Xt3btXRMamvypQ1+0f1le+8hWN3/3ud0/6fElNUcVdh2oZN6rsxLX/hje8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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be02ba160>"
+       "<matplotlib.figure.Figure at 0x7f884c14d9b0>"
       ]
      },
      "metadata": {},
@@ -4346,7 +4470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4363,9 +4487,9 @@
     },
     {
      "data": {
-      "image/png": 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V7caURXBlbOPrX/864M5a/u3f/q1oeyX/kY6ODsBV64Lw72PLlhs2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\nVQ5EJQzSj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B4pQPpYqw+SJV6jMf+MAHAM+P8ZFHHhm0bUlTTokxqimpEqTE+FTfyNdLC9bX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heN7Av+PTTwVhqXXHKJ+5qtRqIoS/2BfJFPV1xxRRLNESnBUtIfffTRAHz84x/vcUxfiramHcsZ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8bb81282b0>"
+       "<matplotlib.figure.Figure at 0x7f884575b320>"
       ]
      },
      "metadata": {},
@@ -4395,7 +4519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4485,7 +4609,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 48,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4505,7 +4629,7 @@
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8b94683748>"
+       "<matplotlib.figure.Figure at 0x7f8802991e80>"
       ]
      },
      "metadata": {},
@@ -4528,7 +4652,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 49,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4548,7 +4672,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUoAAADuCAYAAABf005JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACX1JREFUeJzt3UFvVNcZgOHvjo1xLQtN7UGlYOOrKMqy6oIgIUXJLqso\n+yz7S/I/8iOyKRJVFqiLSKjISKGLVqpQZROEaBlIRFwzgfHcLrKqUvTNnMONh+R51vP5HA6X1zOS\nfWi6rgsAXm1w2hsAWHZCCZAQSoCEUAIkhBIgIZQACaEESAglQEIoARKri7x4NBp1e3ttT1vJNbOT\n4tmD+/dj/ORJ8xq381qNtra6dmen/AusrFSt3w3K5w8PD2I8Hi/v2W5vd+3ubvkXmM3qNjCoez9y\n5+7dcdd15+s20Z+trVG3s9MWz6+tVp5vU/7oHRwezvXsLhTKvb02bt3aL95UrbXJs+LZKx988Bp3\n8vq1Ozuxf/16+RcYDqvWf7F+rnj22rUrVWv3rd3djf0vvij/ApNJ3QY2N6vGm+3tw7oN9Gtnp43r\n18u7cHl0XLeB1YUy9j+uXLs21+t89AZICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigB\nEkIJkBBKgMRC124005exNn5Yvtr6evlsRMyGW+XDldeQ9W22uhbHo8vF85VHG2tH5Tcz1Vx/95Op\nuGGm9mamh0flNzO9CdbWImpuCIxpxd9NRMR0Wj7bdXO9zDtKgIRQAiSEEiAhlAAJoQRICCVAQigB\nEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEgtdBDdbORPHw4vFiz16VDwaERH39stnn5Vft/iT\nmM0iJpPTW391vfzOxG6w3Hd9xmwWcXRUPl952edw+PO+jzJevozBo4p7amvuk4yIGI3q5ufgHSVA\nQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlACJpuu6+V/cNI8j\n4rC/7fRqr+u686e9iVdxtv15w882wvn2aa6zXSiUAL9EPnoDJIQSICGUAAmhBEgIJUBCKAESQgmQ\nEEqAxOoiLx79+tdde+lSxWoLLfdjg/KuH9y/H+PxuKnbQH/W10fd5mZbPH/2bN36Dx8eVEwfRddN\nlvZsR6NR17btaW+j2J07d8bL/Js5w+Gou3ChLZ7fXJ1Urf9isF48++DBQTx9mndhoXK1ly7F/uef\nF28qhsPy2YiIzc3i0SvvvVe3ds82N9v4+OP94vnaDnz66R8qpv9Yt3jP2raN/du3T239WeUHt5WV\nZql/PfDChTY++6z82X3/wj+q1r+//k7x7EcfXZnrdT56AySEEiAhlAAJoQRICCVAQigBEkIJkBBK\ngIRQAiSEEiAhlAAJoQRICCVAYrF7z86erbum5uiofDYiYjotn13y/7+86+r+eLdu1e5gXDFbsfGf\nwMlJxLOj8vcE51aPq9YfTOquEVt2m786ifd//6ziK1yoW7/i8Zv35kbvKAESQgmQEEqAhFACJIQS\nICGUAAmhBEgIJUBCKAESQgmQEEqAhFACJIQSICGUAAmhBEgsdB/lrGvieLpWvNj6cKt4NqLyOsrB\nStXafXv+POKrr8rna6/6jPhtxeyZ2sV7tbIScW5zVjx/PNmoWv9Pf66b/7n7y9/PVc2/+2757Oqc\nBfSOEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgETTdd38\nL26axxFx2N92erXXdd35097Eqzjb/rzhZxvhfPs019kuFEqAXyIfvQESQgmQEEqAhFACJIQSICGU\nAAmhBEjM+d9//2B7e9Tt7rbliy202v8xnRaPHnz9dYyfPGkqd9Cb0WjUXb7cFs8PYla1/vPvy79n\nPnx4EN98M17qs93ba09t/abyZO7cuTNe5h84r312T07q1j9zpnz24OAgxuP82V0oXbu7bdy8uV+8\nqeGweDQiIgbjfxfPXvnww7rFe3b5chtffll+thtxXLX+X+9tFM9+8smVqrX7trfXxq1b5Wdbq/YN\nwspKs9S/9VL77H73Xd365yu+hVy9Ot+z66M3QEIoARJCCZAQSoCEUAIkhBIgIZQACaEESAglQEIo\nARJCCZAQSoCEUAIkhBIgsdAFUKurEVvD8nsP//W4rsu/WdobD+sNXn4fG4/+WTz/t8lbVes/f14+\nO6u7CnPpPXhQN/9W+/M+oMEgYn29fH7j24dV6x9PLhbPzvvsekcJkBBKgIRQAiSEEiAhlAAJoQRI\nCCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAYqH7KGeziONJeVtPTopHfzCdlM8u+aWJk+5s\n1Z2SNfcBRkS8/Xb57MZG3dp9a06msXb0tHj+raO6CymPJ7+rml92k0nEvXvl8+9MxlXrj6fl91FO\np/O9zjtKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEk3X\ndfO/uGkeR8Rhf9vp1V7XdedPexOv4mz784afbYTz7dNcZ7tQKAF+iXz0BkgIJUBCKAESQgmQEEqA\nhFACJIQSILG6yItHW1tdu7tbvNjJ4EzxbETEykr57MHBQYzH46ZqAz3a2hp1u7tt8fyZlVnV+l1T\n/j3z8HC5z3Z7u+5sVxf6V/Jj02nd/N27d8bL/APno9Goa9u2eL72R7mbiidv3i4s9Ai0u7uxf+NG\n8aaebV4sno2I2Nwsn7169UrV2n3b3W3jxo394vmLw+Oq9V+sbhTPXru2/Gd782b52Q6Hdet/+23d\n/PZ2s9S/9dK2bdy+XX6+td9Iar6RzdsFH70BEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJ\nkBBKgIRQAiSEEiCx0L0bs5UzcTysuAGo8paQwaTihpxZ3TVkfWuaiPX18vmnk/Lbf2qdnJza0nNZ\nWam7eWowfVG1/ta08vqgJXdyEnF0VD5f89xHREwm5bPzZsE7SoCEUAIkhBIgIZQACaEESAglQEIo\nARJCCZAQSoCEUAIkhBIgIZQACaEESAglQEIoARIL3Uc5GERsrJff6/jsqLLLNZfeLfl9lKvf/ye2\n7t0unn+4c7Vq/YvT+8Wzq7O6+xqX3rTyItXaCxeXXO19n6epaeZ7nXeUAAmhBEgIJUBCKAESQgmQ\nEEqAhFACJIQSICGUAAmhBEgIJUBCKAESQgmQEEqAhFACJJqu6+Z/cdM8jojD/rbTq72u686f9iZe\nxdn25w0/2wjn26e5znahUAL8EvnoDZAQSoCEUAIkhBIgIZQACaEESAglQEIoARJCCZD4Lwga+Wql\nUchDAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8ba87b1240>"
+       "<matplotlib.figure.Figure at 0x7f8801f0cac8>"
       ]
      },
      "metadata": {},
@@ -4575,7 +4699,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 50,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4594,7 +4718,7 @@
      "data": {
       "image/png": 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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8ba87b1cc0>"
+       "<matplotlib.figure.Figure at 0x7f88029365f8>"
       ]
      },
      "metadata": {},
@@ -4621,7 +4745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false,
     "deletable": true,
@@ -4641,7 +4765,7 @@
      "data": {
       "image/png": 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ut8R8yk2T9Bf40fty5rWvnk+T8v6ItybeLubWP/8P/QWe/50S6muk/cprb8Xlm+Udw9Yo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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8be006c208>"
+       "<matplotlib.figure.Figure at 0x7f8802915a90>"
       ]
      },
      "metadata": {},
diff --git a/reinforcement_learning.py b/reinforcement_learning.py
index 9c4c2f8..3805ab2 100644
--- a/reinforcement_learning.py
+++ b/reinforcement_learning.py
@@ -23,9 +23,9 @@
 # Requirements:
 #
 # - Python 3.6 (Python 2.7 may not work)
-# - TensorFlow 1.0.1
-# - PrettyTensor 0.7.4
+# - TensorFlow 1.1.0
 # - OpenAI Gym 0.8.1
+# - PrettyTensor 0.7.4 (not required if you use tf.layers instead)
 #
 # Summary:
 #
@@ -158,7 +158,6 @@
 
 import numpy as np
 import tensorflow as tf
-import prettytensor as pt
 import gym
 import scipy.ndimage
 import sys
@@ -1101,15 +1100,23 @@ class NeuralNetwork:
     better at estimating the Q-values.
     """
 
-    def __init__(self, num_actions, replay_memory):
+    def __init__(self, num_actions, replay_memory, use_pretty_tensor=True):
         """
         :param num_actions:
             Number of discrete actions for the game-environment.
 
         :param replay_memory: 
             Object-instance of the ReplayMemory-class.
+
+        :param use_pretty_tensor:
+            Boolean whether to use PrettyTensor (True) which must then be
+            installed, or use the tf.layers API (False) which is already
+            built into TensorFlow.
         """
 
+        # Whether to use the PrettyTensor API (True) or tf.layers (False).
+        self.use_pretty_tensor = use_pretty_tensor
+
         # Replay-memory used for sampling random batches.
         self.replay_memory = replay_memory
 
@@ -1151,36 +1158,10 @@ def __init__(self, num_actions, replay_memory):
         self.count_episodes_increase = tf.assign(self.count_episodes,
                                                  self.count_episodes + 1)
 
-        # Initializer for the layers in the Neural Network.
-        # If you change the architecture of the network, particularly
-        # if you add or remove layers, then you may have to change
-        # the stddev-parameter here. The initial weights must result
-        # in the Neural Network outputting Q-values that are very close
-        # to zero - but the network weights must not be too low either
-        # because it will make it hard to train the network.
-        # You can experiment with values between 1e-2 and 1e-3.
-        init = tf.truncated_normal_initializer(mean=0.0, stddev=2e-2)
-
-        # Wrap the input to the Neural Network in a PrettyTensor object.
-        x_pretty = pt.wrap(self.x)
-
-        # Create the convolutional Neural Network using Pretty Tensor.
-        with pt.defaults_scope(activation_fn=tf.nn.relu):
-            self.q_values = x_pretty. \
-                conv2d(kernel=3, depth=16, stride=2, name='layer_conv1', weights=init). \
-                conv2d(kernel=3, depth=32, stride=2, name='layer_conv2', weights=init). \
-                conv2d(kernel=3, depth=64, stride=1, name='layer_conv3', weights=init). \
-                flatten(). \
-                fully_connected(size=1024, name='layer_fc1', weights=init). \
-                fully_connected(size=1024, name='layer_fc2', weights=init). \
-                fully_connected(size=1024, name='layer_fc3', weights=init). \
-                fully_connected(size=1024, name='layer_fc4', weights=init). \
-                fully_connected(size=num_actions, name='layer_fc_out', weights=init,
-                                activation_fn=None)
-
+        # The Neural Network will be constructed in the following.
         # Note that the architecture of this Neural Network is very
         # different from that used in the original DeepMind papers,
-        # which were something like this:
+        # which was something like this:
         # Input image:      84 x 84 x 4 (4 gray-scale images of 84 x 84 pixels).
         # Conv layer 1:     16 filters 8 x 8, stride 4, relu.
         # Conv layer 2:     32 filters 4 x 4, stride 2, relu.
@@ -1196,10 +1177,125 @@ def __init__(self, num_actions, replay_memory):
         # optimization iteration was performed after each step of the game,
         # and some more tricks.
 
-        # Loss-function which must be optimized. This the mean-squared error
-        # between the Q-values that are output by the Neural Network
-        # and the target Q-values.
-        self.loss = self.q_values.l2_regression(target=self.q_values_new)
+        # Initializer for the layers in the Neural Network.
+        # If you change the architecture of the network, particularly
+        # if you add or remove layers, then you may have to change
+        # the stddev-parameter here. The initial weights must result
+        # in the Neural Network outputting Q-values that are very close
+        # to zero - but the network weights must not be too low either
+        # because it will make it hard to train the network.
+        # You can experiment with values between 1e-2 and 1e-3.
+        init = tf.truncated_normal_initializer(mean=0.0, stddev=2e-2)
+
+        if self.use_pretty_tensor:
+            # This builds the Neural Network using the PrettyTensor API,
+            # which is a very elegant builder API, but some people are
+            # having problems installing and using it.
+
+            import prettytensor as pt
+
+            # Wrap the input to the Neural Network in a PrettyTensor object.
+            x_pretty = pt.wrap(self.x)
+
+            # Create the convolutional Neural Network using Pretty Tensor.
+            with pt.defaults_scope(activation_fn=tf.nn.relu):
+                self.q_values = x_pretty. \
+                    conv2d(kernel=3, depth=16, stride=2, name='layer_conv1', weights=init). \
+                    conv2d(kernel=3, depth=32, stride=2, name='layer_conv2', weights=init). \
+                    conv2d(kernel=3, depth=64, stride=1, name='layer_conv3', weights=init). \
+                    flatten(). \
+                    fully_connected(size=1024, name='layer_fc1', weights=init). \
+                    fully_connected(size=1024, name='layer_fc2', weights=init). \
+                    fully_connected(size=1024, name='layer_fc3', weights=init). \
+                    fully_connected(size=1024, name='layer_fc4', weights=init). \
+                    fully_connected(size=num_actions, name='layer_fc_out', weights=init,
+                                    activation_fn=None)
+
+            # Loss-function which must be optimized. This is the mean-squared
+            # error between the Q-values that are output by the Neural Network
+            # and the target Q-values.
+            self.loss = self.q_values.l2_regression(target=self.q_values_new)
+        else:
+            # This builds the Neural Network using the tf.layers API,
+            # which is very verbose and inelegant, but should work for everyone.
+
+            # Note that the checkpoints for Tutorial #16 which can be
+            # downloaded from the internet only support PrettyTensor.
+            # Although the Neural Networks appear to be identical when
+            # built using the PrettyTensor and tf.layers APIs,
+            # they actually create somewhat different TensorFlow graphs
+            # where the variables have different names, which means the
+            # checkpoints are incompatible for the two builder APIs.
+
+            # Padding used for the convolutional layers.
+            padding = 'SAME'
+
+            # Activation function for all convolutional and fully-connected
+            # layers, except the last.
+            activation = tf.nn.relu
+
+            # Reference to the lastly added layer of the Neural Network.
+            # This makes it easy to add or remove layers.
+            net = self.x
+
+            # First convolutional layer.
+            net = tf.layers.conv2d(inputs=net, name='layer_conv1',
+                                   filters=16, kernel_size=3, strides=2,
+                                   padding=padding,
+                                   kernel_initializer=init, activation=activation)
+
+            # Second convolutional layer.
+            net = tf.layers.conv2d(inputs=net, name='layer_conv2',
+                                   filters=32, kernel_size=3, strides=2,
+                                   padding=padding,
+                                   kernel_initializer=init, activation=activation)
+
+            # Third convolutional layer.
+            net = tf.layers.conv2d(inputs=net, name='layer_conv3',
+                                   filters=64, kernel_size=3, strides=1,
+                                   padding=padding,
+                                   kernel_initializer=init, activation=activation)
+
+            # Flatten output of the last convolutional layer so it can
+            # be input to a fully-connected (aka. dense) layer.
+            # TODO: For some bizarre reason, this function is not yet in tf.layers
+            # TODO: net = tf.layers.flatten(net)
+            net = tf.contrib.layers.flatten(net)
+
+            # First fully-connected (aka. dense) layer.
+            net = tf.layers.dense(inputs=net, name='layer_fc1', units=1024,
+                                  kernel_initializer=init, activation=activation)
+
+            # Second fully-connected layer.
+            net = tf.layers.dense(inputs=net, name='layer_fc2', units=1024,
+                                  kernel_initializer=init, activation=activation)
+
+            # Third fully-connected layer.
+            net = tf.layers.dense(inputs=net, name='layer_fc3', units=1024,
+                                  kernel_initializer=init, activation=activation)
+
+            # Fourth fully-connected layer.
+            net = tf.layers.dense(inputs=net, name='layer_fc4', units=1024,
+                                  kernel_initializer=init, activation=activation)
+
+            # Final fully-connected layer.
+            net = tf.layers.dense(inputs=net, name='layer_fc_out', units=num_actions,
+                                  kernel_initializer=init, activation=None)
+
+            # The output of the Neural Network is the estimated Q-values
+            # for each possible action in the game-environment.
+            self.q_values = net
+
+            # TensorFlow has a built-in loss-function for doing regression:
+            # self.loss = tf.nn.l2_loss(self.q_values - self.q_values_new)
+            # But it uses tf.reduce_sum() rather than tf.reduce_mean()
+            # which is used by PrettyTensor. This means the scale of the
+            # gradient is different and hence the hyper-parameters
+            # would have to be re-tuned. So instead we calculate the
+            # L2-loss similarly to how it is done in PrettyTensor.
+            squared_error = tf.square(self.q_values - self.q_values_new)
+            sum_squared_error = tf.reduce_sum(squared_error, axis=1)
+            self.loss = tf.reduce_mean(sum_squared_error)
 
         # Optimizer used for minimizing the loss-function.
         # Note the learning-rate is a placeholder variable so we can
@@ -1384,8 +1480,15 @@ def get_weights_variable(self, layer_name):
         you must use the function get_variable_value() for that.
         """
 
+        if self.use_pretty_tensor:
+            # PrettyTensor uses this name for the weights in a conv-layer.
+            variable_name = 'weights'
+        else:
+            # The tf.layers API uses this name for the weights in a conv-layer.
+            variable_name = 'kernel'
+
         with tf.variable_scope(layer_name, reuse=True):
-            variable = tf.get_variable('weights')
+            variable = tf.get_variable(variable_name)
 
         return variable
 

From 6d698713ee6e88fa3f24f4dd98d0f57dde68e44c Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Tue, 16 May 2017 12:25:12 +0200
Subject: [PATCH 14/61] Added Tutorial #03-B.

---
 03B_Layers_API.ipynb | 2633 ++++++++++++++++++++++++++++++++++++++++++
 README.md            |    2 +
 2 files changed, 2635 insertions(+)
 create mode 100644 03B_Layers_API.ipynb

diff --git a/03B_Layers_API.ipynb b/03B_Layers_API.ipynb
new file mode 100644
index 0000000..dcc8f72
--- /dev/null
+++ b/03B_Layers_API.ipynb
@@ -0,0 +1,2633 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #03-B\n",
+    "# Layers API\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "It is important to use a builder API when constructing Neural Networks in TensorFlow because it makes it easier to implement and modify the source-code. This also lowers the risk of bugs.\n",
+    "\n",
+    "Many of the other tutorials used the TensorFlow builder API called PrettyTensor for easy construction of Neural Networks. But there are several other builder APIs available for TensorFlow. PrettyTensor was used in these tutorials, because at the time in mid-2016, PrettyTensor was the most complete and polished builder API available for TensorFlow. But PrettyTensor is only developed by a single person working at Google and although it has some unique and elegant features, it is possible that it may become deprecated in the future.\n",
+    "\n",
+    "This tutorial is about a small builder API that has recently been added to TensorFlow version 1.1. It is simply called *Layers* or the *Layers API* or by its Python name `tf.layers`. This builder API is automatically installed as part of TensorFlow, so you no longer have to install a separate Python package as was needed with PrettyTensor.\n",
+    "\n",
+    "This tutorial is very similar to Tutorial #03 on PrettyTensor and shows how to implement the same Convolutional Neural Network using the Layers API. It is recommended that you are familiar with Tutorial #02 on Convolutional Neural Networks."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Flowchart"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See Tutorial #02 for a more detailed description of convolution."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Flowchart](images/02_network_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled using max-pooling so the image resolution is decreased from 28x28 to 14x14.\n",
+    "\n",
+    "These 16 smaller images are then processed in the second convolutional layer. We need filter-weights for each of these 16 channels, and we need filter-weights for each output channel of this layer. There are 36 output channels so there are a total of 16 x 36 = 576 filters in the second convolutional layer. The resulting images are also down-sampled using max-pooling to 7x7 pixels.\n",
+    "\n",
+    "The output of the second convolutional layer is 36 images of 7x7 pixels each. These are then flattened to a single vector of length 7 x 7 x 36 = 1764, which is used as the input to a fully-connected layer with 128 neurons (or elements). This feeds into another fully-connected layer with 10 neurons, one for each of the classes, which is used to determine the class of the image, that is, which number is depicted in the image.\n",
+    "\n",
+    "The convolutional filters are initially chosen at random, so the classification is done randomly. The error between the predicted and true class of the input image is measured as the so-called cross-entropy. The optimizer then automatically propagates this error back through the Convolutional Network using the chain-rule of differentiation and updates the filter-weights so as to improve the classification error. This is done iteratively thousands of times until the classification error is sufficiently low.\n",
+    "\n",
+    "These particular filter-weights and intermediate images are the results of one optimization run and may look different if you re-run this Notebook.\n",
+    "\n",
+    "Note that the computation in TensorFlow is actually done on a batch of images instead of a single image, which makes the computation more efficient. This means the flowchart actually has one more data-dimension when implemented in TensorFlow."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.1.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.examples.tutorials.mnist import input_data\n",
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t55000\n",
+      "- Test-set:\t\t10000\n",
+      "- Validation-set:\t5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
+    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Data Dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# We know that MNIST images are 28 pixels in each dimension.\n",
+    "img_size = 28\n",
+    "\n",
+    "# Images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = img_size * img_size\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "img_shape = (img_size, img_size)\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = 1\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None):\n",
+    "    assert len(images) == len(cls_true) == 9\n",
+    "    \n",
+    "    # Create figure with 3x3 sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "    fig.subplots_adjust(hspace=0.3, wspace=0.3)\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Plot image.\n",
+    "        ax.imshow(images[i].reshape(img_shape), cmap='binary')\n",
+    "\n",
+    "        # Show true and predicted classes.\n",
+    "        if cls_pred is None:\n",
+    "            xlabel = \"True: {0}\".format(cls_true[i])\n",
+    "        else:\n",
+    "            xlabel = \"True: {0}, Pred: {1}\".format(cls_true[i], cls_pred[i])\n",
+    "\n",
+    "        # Show the classes as the label on the x-axis.\n",
+    "        ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f633bf49e48>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the first images from the test-set.\n",
+    "images = data.test.images[0:9]\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = data.test.cls[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## TensorFlow Graph\n",
+    "\n",
+    "The entire purpose of TensorFlow is to have a so-called computational graph that can be executed much more efficiently than if the same calculations were to be performed directly in Python. TensorFlow can be more efficient than NumPy because TensorFlow knows the entire computation graph that must be executed, while NumPy only knows the computation of a single mathematical operation at a time.\n",
+    "\n",
+    "TensorFlow can also automatically calculate the gradients that are needed to optimize the variables of the graph so as to make the model perform better. This is because the graph is a combination of simple mathematical expressions so the gradient of the entire graph can be calculated using the chain-rule for derivatives.\n",
+    "\n",
+    "TensorFlow can also take advantage of multi-core CPUs as well as GPUs - and Google has even built special chips just for TensorFlow which are called TPUs (Tensor Processing Units) and are even faster than GPUs.\n",
+    "\n",
+    "A TensorFlow graph consists of the following parts which will be detailed below:\n",
+    "\n",
+    "* Placeholder variables used for inputting data to the graph.\n",
+    "* Variables that are going to be optimized so as to make the convolutional network perform better.\n",
+    "* The mathematical formulas for the convolutional neural network.\n",
+    "* A so-called cost-measure or loss-function that can be used to guide the optimization of the variables.\n",
+    "* An optimization method which updates the variables.\n",
+    "\n",
+    "In addition, the TensorFlow graph may also contain various debugging statements e.g. for logging data to be displayed using TensorBoard, which is not covered in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Placeholder variables"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
+    "\n",
+    "First we define the placeholder variable for the input images. This allows us to change the images that are input to the TensorFlow graph. This is a so-called tensor, which just means that it is a multi-dimensional array. The data-type is set to `float32` and the shape is set to `[None, img_size_flat]`, where `None` means that the tensor may hold an arbitrary number of images with each image being a vector of length `img_size_flat`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_true_cls = tf.argmax(y_true, dimension=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## PrettyTensor Implementation\n",
+    "\n",
+    "This section shows the implementation of a Convolutional Neural Network using PrettyTensor taken from Tutorial #03 so it can be compared to the implementation using the Layers API below. This code has been enclosed in an `if False:` block so it does not run here.\n",
+    "\n",
+    "The basic idea is to wrap the input tensor `x_image` in a PrettyTensor object which has helper-functions for adding new computational layers so as to create an entire Convolutional Neural Network. This is a fairly simple and elegant syntax."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "if False:\n",
+    "    x_pretty = pt.wrap(x_image)\n",
+    "\n",
+    "    with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
+    "        y_pred, loss = x_pretty.\\\n",
+    "            conv2d(kernel=5, depth=16, name='layer_conv1').\\\n",
+    "            max_pool(kernel=2, stride=2).\\\n",
+    "            conv2d(kernel=5, depth=36, name='layer_conv2').\\\n",
+    "            max_pool(kernel=2, stride=2).\\\n",
+    "            flatten().\\\n",
+    "            fully_connected(size=128, name='layer_fc1').\\\n",
+    "            softmax_classifier(num_classes=num_classes, labels=y_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Layers Implementation\n",
+    "\n",
+    "We now implement the same Convolutional Neural Network using the Layers API that is included in TensorFlow version 1.1. This requires more code than PrettyTensor, although a lot of the following are just comments.\n",
+    "\n",
+    "We use the `net`-variable to refer to the last layer while building the Neural Network. This makes it easy to add or remove layers in the code if you want to experiment. First we set the `net`-variable to the reshaped input image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = x_image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The input image is then input to the first convolutional layer, which has 16 filters each of size 5x5 pixels. The activation-function is the Rectified Linear Unit (ReLU) described in more detail in Tutorial #02."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv1', padding='same',\n",
+    "                       filters=16, kernel_size=5, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "One of the advantages of constructing neural networks in this fashion, is that we can now easily pull out a reference to a layer. This was more complicated in PrettyTensor.\n",
+    "\n",
+    "Further below we want to plot the output of the first convolutional layer, so we create another variable for holding a reference to that layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "layer_conv1 = net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We now do the max-pooling on the output of the convolutional layer. This was also described in more detail in Tutorial #02."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We now add the second convolutional layer which has 36 filters each with 5x5 pixels, and a ReLU activation function again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv2', padding='same',\n",
+    "                       filters=36, kernel_size=5, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We also want to plot the output of this convolutional layer, so we keep a reference for later use."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "layer_conv2 = net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The output of the second convolutional layer is also max-pooled for down-sampling the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The tensors that are being output by this max-pooling are 4-rank, as can be seen from this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tf.Tensor 'max_pooling2d_2/MaxPool:0' shape=(?, 7, 7, 36) dtype=float32>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Next we want to add fully-connected layers to the Neural Network, but these require 2-rank tensors as input, so we must first flatten the tensors.\n",
+    "\n",
+    "The `tf.layers` API was first located in `tf.contrib.layers` before it was moved into TensorFlow Core. But even though it has taken the TensorFlow developers a year to move these fairly simple functions, they have somehow forgotten to move the even simpler `flatten()` function. So we still need to use the one in `tf.contrib.layers`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.contrib.layers.flatten(net)\n",
+    "\n",
+    "# This should eventually be replaced by:\n",
+    "# net = tf.layers.flatten(net)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This has now flattened the data to a 2-rank tensor, as can be seen from this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tf.Tensor 'Flatten/Reshape:0' shape=(?, 1764) dtype=float32>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now add fully-connected layers to the neural network. These are called *dense* layers in the Layers API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
+    "                      units=128, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We need the neural network to classify the input images into 10 different classes. So the final fully-connected layer has `num_classes=10` output neurons."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.dense(inputs=net, name='layer_fc_out',\n",
+    "                      units=num_classes, activation=None)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The output of the final fully-connected layer are sometimes called logits, so we have a convenience variable with that name."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "logits = net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We use the softmax function to 'squash' the outputs so they are between zero and one, and so they sum to one."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = tf.nn.softmax(logits=logits)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This tells us how likely the neural network thinks the input image is of each possible class. The one that has the highest value is considered the most likely so its index is taken to be the class-number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_cls = tf.argmax(y_pred, dimension=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We have now created the exact same Convolutional Neural Network in a few lines of code that required many complex lines of code in the direct TensorFlow implementation.\n",
+    "\n",
+    "The Layers API is perhaps not as elegant as PrettyTensor, but it has some other advantages, e.g. that we can more easily refer to intermediate layers, and it is also easier to construct neural networks with branches and multiple outputs using the Layers API."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Loss-Function to be Optimized"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "To make the model better at classifying the input images, we must somehow change the variables of the Convolutional Neural Network.\n",
+    "\n",
+    "The cross-entropy is a performance measure used in classification. The cross-entropy is a continuous function that is always positive and if the predicted output of the model exactly matches the desired output then the cross-entropy equals zero. The goal of optimization is therefore to minimize the cross-entropy so it gets as close to zero as possible by changing the variables of the model.\n",
+    "\n",
+    "TensorFlow has a function for calculating the cross-entropy, which uses the values of the `logits`-layer because it also calculates the softmax internally, so as to to improve numerical stability."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_true, logits=logits)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "loss = tf.reduce_mean(cross_entropy)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Optimization Method\n",
+    "\n",
+    "Now that we have a cost measure that must be minimized, we can then create an optimizer. In this case it is the Adam optimizer with a learning-rate of 1e-4.\n",
+    "\n",
+    "Note that optimization is not performed at this point. In fact, nothing is calculated at all, we just add the optimizer-object to the TensorFlow graph for later execution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Classification Accuracy\n",
+    "\n",
+    "We need to calculate the classification accuracy so we can report progress to the user.\n",
+    "\n",
+    "First we create a vector of booleans telling us whether the predicted class equals the true class of each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Getting the Weights\n",
+    "\n",
+    "Further below, we want to plot the weights of the convolutional layers. In the TensorFlow implementation we had created the variables ourselves so we could just refer to them directly. But when the network is constructed using a builder API such as `tf.layers`, all the variables of the layers are created indirectly by the builder API. We therefore have to retrieve the variables from TensorFlow.\n",
+    "\n",
+    "First we need a list of the variable names in the TensorFlow graph:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<tf.Variable 'layer_conv1/kernel:0' shape=(5, 5, 1, 16) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv1/bias:0' shape=(16,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/kernel:0' shape=(5, 5, 16, 36) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/bias:0' shape=(36,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/kernel:0' shape=(1764, 128) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/bias:0' shape=(128,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/kernel:0' shape=(128, 10) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/bias:0' shape=(10,) dtype=float32_ref>\n",
+      "<tf.Variable 'beta1_power:0' shape=() dtype=float32_ref>\n",
+      "<tf.Variable 'beta2_power:0' shape=() dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv1/kernel/Adam:0' shape=(5, 5, 1, 16) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv1/kernel/Adam_1:0' shape=(5, 5, 1, 16) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv1/bias/Adam:0' shape=(16,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv1/bias/Adam_1:0' shape=(16,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/kernel/Adam:0' shape=(5, 5, 16, 36) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/kernel/Adam_1:0' shape=(5, 5, 16, 36) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/bias/Adam:0' shape=(36,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_conv2/bias/Adam_1:0' shape=(36,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/kernel/Adam:0' shape=(1764, 128) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/kernel/Adam_1:0' shape=(1764, 128) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/bias/Adam:0' shape=(128,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc1/bias/Adam_1:0' shape=(128,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/kernel/Adam:0' shape=(128, 10) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/kernel/Adam_1:0' shape=(128, 10) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/bias/Adam:0' shape=(10,) dtype=float32_ref>\n",
+      "<tf.Variable 'layer_fc_out/bias/Adam_1:0' shape=(10,) dtype=float32_ref>\n"
+     ]
+    }
+   ],
+   "source": [
+    "for var in tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES):\n",
+    "    print(var)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Each of the convolutional layers has two variables. For the first convolutional layer they are named `layer_conv1/kernel:0` and `layer_conv1/bias:0`. The `kernel` variables are the ones we want to plot further below.\n",
+    "\n",
+    "It is somewhat awkward to get references to these variables, because we have to use the TensorFlow function `get_variable()` which was designed for another purpose; either creating a new variable or re-using an existing variable. The easiest thing is to make the following helper-function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def get_weights_variable(layer_name):\n",
+    "    # Retrieve an existing variable named 'kernel' in the scope\n",
+    "    # with the given layer_name.\n",
+    "    # This is awkward because the TensorFlow function was\n",
+    "    # really intended for another purpose.\n",
+    "\n",
+    "    with tf.variable_scope(layer_name, reuse=True):\n",
+    "        variable = tf.get_variable('kernel')\n",
+    "\n",
+    "    return variable"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Using this helper-function we can retrieve the variables. These are TensorFlow objects. In order to get the contents of the variables, you must do something like: `contents = session.run(weights_conv1)` as demonstrated further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "weights_conv1 = get_weights_variable(layer_name='layer_conv1')\n",
+    "weights_conv2 = get_weights_variable(layer_name='layer_conv2')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## TensorFlow Run"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Create TensorFlow session\n",
+    "\n",
+    "Once the TensorFlow graph has been created, we have to create a TensorFlow session which is used to execute the graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "session = tf.Session()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Initialize variables\n",
+    "\n",
+    "The variables for the TensorFlow graph must be initialized before we start optimizing them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "session.run(tf.global_variables_initializer())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to perform optimization iterations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
+    "\n",
+    "If your computer crashes or becomes very slow because you run out of RAM, then you may try and lower this number, but you may then need to do more optimization iterations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "train_batch_size = 64"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This function performs a number of optimization iterations so as to gradually improve the variables of the neural network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Counter for total number of iterations performed so far.\n",
+    "total_iterations = 0\n",
+    "\n",
+    "def optimize(num_iterations):\n",
+    "    # Ensure we update the global variable rather than a local copy.\n",
+    "    global total_iterations\n",
+    "\n",
+    "    for i in range(total_iterations,\n",
+    "                   total_iterations + num_iterations):\n",
+    "\n",
+    "        # Get a batch of training examples.\n",
+    "        # x_batch now holds a batch of images and\n",
+    "        # y_true_batch are the true labels for those images.\n",
+    "        x_batch, y_true_batch = data.train.next_batch(train_batch_size)\n",
+    "\n",
+    "        # Put the batch into a dict with the proper names\n",
+    "        # for placeholder variables in the TensorFlow graph.\n",
+    "        feed_dict_train = {x: x_batch,\n",
+    "                           y_true: y_true_batch}\n",
+    "\n",
+    "        # Run the optimizer using this batch of training data.\n",
+    "        # TensorFlow assigns the variables in feed_dict_train\n",
+    "        # to the placeholder variables and then runs the optimizer.\n",
+    "        session.run(optimizer, feed_dict=feed_dict_train)\n",
+    "\n",
+    "        # Print status every 100 iterations.\n",
+    "        if i % 100 == 0:\n",
+    "            # Calculate the accuracy on the training-set.\n",
+    "            acc = session.run(accuracy, feed_dict=feed_dict_train)\n",
+    "\n",
+    "            # Message for printing.\n",
+    "            msg = \"Optimization Iteration: {0:>6}, Training Accuracy: {1:>6.1%}\"\n",
+    "\n",
+    "            # Print it.\n",
+    "            print(msg.format(i + 1, acc))\n",
+    "\n",
+    "    # Update the total number of iterations performed.\n",
+    "    total_iterations += num_iterations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to plot example errors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function for plotting examples of images from the test-set that have been mis-classified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_example_errors(cls_pred, correct):\n",
+    "    # This function is called from print_test_accuracy() below.\n",
+    "\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # correct is a boolean array whether the predicted class\n",
+    "    # is equal to the true class for each image in the test-set.\n",
+    "\n",
+    "    # Negate the boolean array.\n",
+    "    incorrect = (correct == False)\n",
+    "    \n",
+    "    # Get the images from the test-set that have been\n",
+    "    # incorrectly classified.\n",
+    "    images = data.test.images[incorrect]\n",
+    "    \n",
+    "    # Get the predicted classes for those images.\n",
+    "    cls_pred = cls_pred[incorrect]\n",
+    "\n",
+    "    # Get the true classes for those images.\n",
+    "    cls_true = data.test.cls[incorrect]\n",
+    "    \n",
+    "    # Plot the first 9 images.\n",
+    "    plot_images(images=images[0:9],\n",
+    "                cls_true=cls_true[0:9],\n",
+    "                cls_pred=cls_pred[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to plot confusion matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_confusion_matrix(cls_pred):\n",
+    "    # This is called from print_test_accuracy() below.\n",
+    "\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Get the true classifications for the test-set.\n",
+    "    cls_true = data.test.cls\n",
+    "    \n",
+    "    # Get the confusion matrix using sklearn.\n",
+    "    cm = confusion_matrix(y_true=cls_true,\n",
+    "                          y_pred=cls_pred)\n",
+    "\n",
+    "    # Print the confusion matrix as text.\n",
+    "    print(cm)\n",
+    "\n",
+    "    # Plot the confusion matrix as an image.\n",
+    "    plt.matshow(cm)\n",
+    "\n",
+    "    # Make various adjustments to the plot.\n",
+    "    plt.colorbar()\n",
+    "    tick_marks = np.arange(num_classes)\n",
+    "    plt.xticks(tick_marks, range(num_classes))\n",
+    "    plt.yticks(tick_marks, range(num_classes))\n",
+    "    plt.xlabel('Predicted')\n",
+    "    plt.ylabel('True')\n",
+    "\n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for showing the performance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Below is a function for printing the classification accuracy on the test-set.\n",
+    "\n",
+    "It takes a while to compute the classification for all the images in the test-set, that's why the results are re-used by calling the above functions directly from this function, so the classifications don't have to be recalculated by each function.\n",
+    "\n",
+    "Note that this function can use a lot of computer memory, which is why the test-set is split into smaller batches. If you have little RAM in your computer and it crashes, then you can try and lower the batch-size."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Split the test-set into smaller batches of this size.\n",
+    "test_batch_size = 256\n",
+    "\n",
+    "def print_test_accuracy(show_example_errors=False,\n",
+    "                        show_confusion_matrix=False):\n",
+    "\n",
+    "    # Number of images in the test-set.\n",
+    "    num_test = len(data.test.images)\n",
+    "\n",
+    "    # Allocate an array for the predicted classes which\n",
+    "    # will be calculated in batches and filled into this array.\n",
+    "    cls_pred = np.zeros(shape=num_test, dtype=np.int)\n",
+    "\n",
+    "    # Now calculate the predicted classes for the batches.\n",
+    "    # We will just iterate through all the batches.\n",
+    "    # There might be a more clever and Pythonic way of doing this.\n",
+    "\n",
+    "    # The starting index for the next batch is denoted i.\n",
+    "    i = 0\n",
+    "\n",
+    "    while i < num_test:\n",
+    "        # The ending index for the next batch is denoted j.\n",
+    "        j = min(i + test_batch_size, num_test)\n",
+    "\n",
+    "        # Get the images from the test-set between index i and j.\n",
+    "        images = data.test.images[i:j, :]\n",
+    "\n",
+    "        # Get the associated labels.\n",
+    "        labels = data.test.labels[i:j, :]\n",
+    "\n",
+    "        # Create a feed-dict with these images and labels.\n",
+    "        feed_dict = {x: images,\n",
+    "                     y_true: labels}\n",
+    "\n",
+    "        # Calculate the predicted class using TensorFlow.\n",
+    "        cls_pred[i:j] = session.run(y_pred_cls, feed_dict=feed_dict)\n",
+    "\n",
+    "        # Set the start-index for the next batch to the\n",
+    "        # end-index of the current batch.\n",
+    "        i = j\n",
+    "\n",
+    "    # Convenience variable for the true class-numbers of the test-set.\n",
+    "    cls_true = data.test.cls\n",
+    "\n",
+    "    # Create a boolean array whether each image is correctly classified.\n",
+    "    correct = (cls_true == cls_pred)\n",
+    "\n",
+    "    # Calculate the number of correctly classified images.\n",
+    "    # When summing a boolean array, False means 0 and True means 1.\n",
+    "    correct_sum = correct.sum()\n",
+    "\n",
+    "    # Classification accuracy is the number of correctly classified\n",
+    "    # images divided by the total number of images in the test-set.\n",
+    "    acc = float(correct_sum) / num_test\n",
+    "\n",
+    "    # Print the accuracy.\n",
+    "    msg = \"Accuracy on Test-Set: {0:.1%} ({1} / {2})\"\n",
+    "    print(msg.format(acc, correct_sum, num_test))\n",
+    "\n",
+    "    # Plot some examples of mis-classifications, if desired.\n",
+    "    if show_example_errors:\n",
+    "        print(\"Example errors:\")\n",
+    "        plot_example_errors(cls_pred=cls_pred, correct=correct)\n",
+    "\n",
+    "    # Plot the confusion matrix, if desired.\n",
+    "    if show_confusion_matrix:\n",
+    "        print(\"Confusion Matrix:\")\n",
+    "        plot_confusion_matrix(cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Performance before any optimization\n",
+    "\n",
+    "The accuracy on the test-set is very low because the variables for the neural network have only been initialized and not optimized at all, so it just classifies the images randomly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 5.8% (577 / 10000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_test_accuracy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Performance after 1 optimization iteration\n",
+    "\n",
+    "The classification accuracy does not improve much from just 1 optimization iteration, because the learning-rate for the optimizer is set very low."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimization Iteration:      1, Training Accuracy:   9.4%\n"
+     ]
+    }
+   ],
+   "source": [
+    "optimize(num_iterations=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 6.6% (659 / 10000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_test_accuracy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Performance after 100 optimization iterations\n",
+    "\n",
+    "After 100 optimization iterations, the model has significantly improved its classification accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 368 ms, sys: 56 ms, total: 424 ms\n",
+      "Wall time: 308 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "optimize(num_iterations=99) # We already performed 1 iteration above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 81.2% (8125 / 10000)\n",
+      "Example errors:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+t912W/4SKzmxYsUKABYsWJDcNmHCBAB++OEHAD7++GMgMQMTwC233JLcd/fd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\nD2mCwyX2kvPaAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339b686d8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print_test_accuracy(show_example_errors=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Performance after 1000 optimization iterations\n",
+    "\n",
+    "After 1000 optimization iterations, the model has greatly increased its accuracy on the test-set to more than 90%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimization Iteration:    101, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    301, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    401, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    901, Training Accuracy:  98.4%\n",
+      "CPU times: user 3.55 s, sys: 500 ms, total: 4.05 s\n",
+      "Wall time: 2.96 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "optimize(num_iterations=900) # We performed 100 iterations above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 94.5% (9455 / 10000)\n",
+      "Example errors:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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f9BFwTZKTMg5MCdJOAYY451YEz7cHvs4ijzcCC4DZZjYXGEviiup/JCrB+cB4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\nQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339b68b00>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print_test_accuracy(show_example_errors=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Performance after 10,000 optimization iterations\n",
+    "\n",
+    "After 10,000 optimization iterations, the model has a classification accuracy on the test-set of about 99%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimization Iteration:   1001, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2501, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   2601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3001, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3501, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   4201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4501, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   4601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4901, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5301, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5901, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   6001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   6101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   6201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   6301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   6401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   6501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   6601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   6701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   6801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   6901, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7001, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   7401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   7601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   7701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   7801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   7901, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   8101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   8301, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   8601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8901, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
+      "CPU times: user 34.6 s, sys: 4.08 s, total: 38.7 s\n",
+      "Wall time: 28.2 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "optimize(num_iterations=9000) # We performed 1000 iterations above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 98.8% (9884 / 10000)\n",
+      "Example errors:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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QfDA3zIjrVFHPnpvZFKBneLkkDUyYkTzrnDu+1LFIYTSEMq6oSlNEpNT0GKWI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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339eaa780>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Confusion Matrix:\n",
+      "[[ 975    0    0    0    0    1    2    1    1    0]\n",
+      " [   0 1127    2    0    0    0    2    2    2    0]\n",
+      " [   2    0 1024    1    1    0    0    4    0    0]\n",
+      " [   0    0    0 1006    0    1    0    1    2    0]\n",
+      " [   0    0    1    0  979    0    1    0    0    1]\n",
+      " [   2    0    0    7    0  879    3    0    1    0]\n",
+      " [   5    2    0    1    1    3  946    0    0    0]\n",
+      " [   0    1    4    2    0    0    0 1018    1    2]\n",
+      " [   1    0    3   10    1    1    1    2  951    4]\n",
+      " [   1    3    0    6    8    4    0    6    2  979]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f633bf49470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print_test_accuracy(show_example_errors=True,\n",
+    "                    show_confusion_matrix=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Visualization of Weights and Layers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting convolutional weights"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_conv_weights(weights, input_channel=0):\n",
+    "    # Assume weights are TensorFlow ops for 4-dim variables\n",
+    "    # e.g. weights_conv1 or weights_conv2.\n",
+    "    \n",
+    "    # Retrieve the values of the weight-variables from TensorFlow.\n",
+    "    # A feed-dict is not necessary because nothing is calculated.\n",
+    "    w = session.run(weights)\n",
+    "\n",
+    "    # Get the lowest and highest values for the weights.\n",
+    "    # This is used to correct the colour intensity across\n",
+    "    # the images so they can be compared with each other.\n",
+    "    w_min = np.min(w)\n",
+    "    w_max = np.max(w)\n",
+    "\n",
+    "    # Number of filters used in the conv. layer.\n",
+    "    num_filters = w.shape[3]\n",
+    "\n",
+    "    # Number of grids to plot.\n",
+    "    # Rounded-up, square-root of the number of filters.\n",
+    "    num_grids = math.ceil(math.sqrt(num_filters))\n",
+    "    \n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids)\n",
+    "\n",
+    "    # Plot all the filter-weights.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the valid filter-weights.\n",
+    "        if i<num_filters:\n",
+    "            # Get the weights for the i'th filter of the input channel.\n",
+    "            # See new_conv_layer() for details on the format\n",
+    "            # of this 4-dim tensor.\n",
+    "            img = w[:, :, input_channel, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, vmin=w_min, vmax=w_max,\n",
+    "                      interpolation='nearest', cmap='seismic')\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting the output of a convolutional layer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_conv_layer(layer, image):\n",
+    "    # Assume layer is a TensorFlow op that outputs a 4-dim tensor\n",
+    "    # which is the output of a convolutional layer,\n",
+    "    # e.g. layer_conv1 or layer_conv2.\n",
+    "\n",
+    "    # Create a feed-dict containing just one image.\n",
+    "    # Note that we don't need to feed y_true because it is\n",
+    "    # not used in this calculation.\n",
+    "    feed_dict = {x: [image]}\n",
+    "\n",
+    "    # Calculate and retrieve the output values of the layer\n",
+    "    # when inputting that image.\n",
+    "    values = session.run(layer, feed_dict=feed_dict)\n",
+    "\n",
+    "    # Number of filters used in the conv. layer.\n",
+    "    num_filters = values.shape[3]\n",
+    "\n",
+    "    # Number of grids to plot.\n",
+    "    # Rounded-up, square-root of the number of filters.\n",
+    "    num_grids = math.ceil(math.sqrt(num_filters))\n",
+    "    \n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids)\n",
+    "\n",
+    "    # Plot the output images of all the filters.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the images for valid filters.\n",
+    "        if i<num_filters:\n",
+    "            # Get the output image of using the i'th filter.\n",
+    "            img = values[0, :, :, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, interpolation='nearest', cmap='binary')\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Input Images\n",
+    "\n",
+    "Helper-function for plotting an image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_image(image):\n",
+    "    plt.imshow(image.reshape(img_shape),\n",
+    "               interpolation='nearest',\n",
+    "               cmap='binary')\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot an image from the test-set which will be used as an example below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339d11240>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "image1 = data.test.images[0]\n",
+    "plot_image(image1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot another example image from the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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q+tgl+irkuPEOPyAoLvgBQRF+ICjCDwRF+IGgCD8QFOEHgiL8QFCEHwjq/wHi31d/HSnF\nFwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6334ae6518>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "image2 = data.test.images[13]\n",
+    "plot_image(image2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Convolution Layer 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Now plot the filter-weights for the first convolutional layer.\n",
+    "\n",
+    "Note that positive weights are red and negative weights are blue."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Pf65/l0uXupZKehlmNsITXL9eRvr7vVP7HBndQ2aOPwLjjhIAJIoSAASKEgAEihIABIoS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\nPeDeZgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6334ba5da0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(weights=weights_conv1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Applying each of these convolutional filters to the first input image gives the following output images, which are then used as input to the second convolutional layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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U2Gcj/5PJteyht+M4TgRZlV/r168Hgp1D3r2jowOA5uZmADo7O20XKSoqsp8d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\nSsdxnAj+P9VNNSIcvuqDAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f63392957b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_layer(layer=layer_conv1, image=image1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The following images are the results of applying the convolutional filters to the second image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Er5VInS52fD6feCWMm2/fvl32ZdNG3OLp8XgkjpZowwT7WHZ0dMTF0NasWRO3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\nlIqiKDboRKkoimLD/wOiM0RW41gr2AAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339d11630>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_layer(layer=layer_conv1, image=image2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Convolution Layer 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Now plot the filter-weights for the second convolutional layer.\n",
+    "\n",
+    "There are 16 output channels from the first conv-layer, which means there are 16 input channels to the second conv-layer. The second conv-layer has a set of filter-weights for each of its input channels. We start by plotting the filter-weigths for the first channel.\n",
+    "\n",
+    "Note again that positive weights are red and negative weights are blue."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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YUcxyr31YCgvlvKBAr0mfMIplecX8vJ0hEHDovvv4uXbu1GtGj5bzv/9dr7n6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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339d2b7f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(weights=weights_conv2, input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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6KhAAsG2bWbKwQC6cMmdOcvbUyc/3cP/98hpvv92u6dFDz1ML7N9/WNmDqeQP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\nCbwTyk8Td2ZOAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339d2bcf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(weights=weights_conv2, input_channel=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "It can be difficult to understand and keep track of how these filters are applied because of the high dimensionality.\n",
+    "\n",
+    "Applying these convolutional filters to the images that were ouput from the first conv-layer gives the following images.\n",
+    "\n",
+    "Note that these are down-sampled to 14 x 14 pixels which is half the resolution of the original input images, because the first convolutional layer was followed by a max-pooling layer with stride 2. Max-pooling is also done after the second convolutional layer, but we retrieve these images before that has been applied."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dq+KSEyohW2fHMAxjgFK1ZCpPmjyHHR0dQDhAWNKqikP4XQ7l6c6irVSUc2xX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\nALaYGoZhJMD/A/8aY2yG4odpAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6337ce2a90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_layer(layer=layer_conv2, image=image1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "And these are the results of applying the filter-weights to the second image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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y77coKjQr9diWAxOvvvoqEJc2y/se1SyA/nHn2Xpage17LnONrq3K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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6339d117b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_layer(layer=layer_conv2, image=image2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Close TensorFlow Session"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We are now done using TensorFlow, so we close the session to release its resources."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# This has been commented out in case you want to modify and experiment\n",
+    "# with the Notebook without having to restart it.\n",
+    "# session.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use the so-called *Layers API* for easily building Convolutional Neural Networks in TensorFlow. The syntax is different and more verbose than that of PrettyTensor. Both builder API's have advantages and disadvantages, but since PrettyTensor is only developed by one person and the Layers API is now an official part of TensorFlow Core, it is possible that PrettyTensor will become deprecated in the future. If this happens, we might hope that some of its unique and elegant features will become integrated into TensorFlow Core as well.\n",
+    "\n",
+    "I have been trying to get a clear answer from the TensorFlow developers for almost a year, on which of their APIs will be the main builder API for TensorFlow. They still seem to be undecided and very slow to implement it."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Change the activation function to sigmoid for some of the layers.\n",
+    "* Can you find a simple way of changing the activation function for all the layers?\n",
+    "* Add a dropout-layer after the fully-connected layer. If you want a different probability during training and testing then you will need a placeholder variable and set it in the feed-dict.\n",
+    "* Plot the output of the max-pooling layers instead of the conv-layers.\n",
+    "* Replace the 2x2 max-pooling layers with stride=2 in the convolutional layers. Is there a difference in classification accuracy? What if you optimize it again and again? The difference is random, so how would you measure if there really is a difference? What are the pros and cons of using max-pooling vs. stride in the conv-layer?\n",
+    "* Change the parameters for the layers, e.g. the kernel, depth, size, etc. What is the difference in time usage and classification accuracy?\n",
+    "* Add and remove some convolutional and fully-connected layers.\n",
+    "* What is the simplest network you can design that still performs well?\n",
+    "* Retrieve the bias-values for the convolutional layers and print them. See `get_weights_variable()` for inspiration.\n",
+    "* Remake the program yourself without looking too much at this source-code.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index 370eea1..a2b1d63 100644
--- a/README.md
+++ b/README.md
@@ -25,6 +25,8 @@ Even a few dollars are appreciated. Thanks!
 
 3. Pretty Tensor ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
 
+3-B. Layers API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
+
 4. Save & Restore ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
 
 5. Ensemble Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/05_Ensemble_Learning.ipynb))

From 5ac357242900881523bd40a2bb7efb4740bc99c4 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 9 Jun 2017 10:50:58 +0200
Subject: [PATCH 15/61] Changed the word rectangular with square.

---
 07_Inception_Model.ipynb | 478 ++++++++++++++++++++++++++-------------
 1 file changed, 319 insertions(+), 159 deletions(-)

diff --git a/07_Inception_Model.ipynb b/07_Inception_Model.ipynb
index e00ebb4..1ae5c56 100644
--- a/07_Inception_Model.ipynb
+++ b/07_Inception_Model.ipynb
@@ -2,7 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "# TensorFlow Tutorial #07\n",
     "# Inception Model\n",
@@ -13,7 +16,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Introduction\n",
     "\n",
@@ -28,14 +34,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The following chart shows how the data flows in the Inception v3 model, which is a Convolutional Neural Network with many layers and a complicated structure. The [research paper](http://arxiv.org/pdf/1512.00567v3.pdf) gives more details on how the Inception model is constructed and why it is designed that way. But the authors admit that they don't fully understand why it works.\n",
     "\n",
@@ -49,6 +61,8 @@
    "execution_count": 1,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -71,7 +85,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Imports"
    ]
@@ -80,7 +97,9 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -96,7 +115,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
    ]
@@ -105,13 +127,15 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.10.0rc0'"
+       "'1.1.0'"
       ]
      },
      "execution_count": 3,
@@ -125,14 +149,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Download the Inception Model"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The Inception model is downloaded from the internet. This is the default directory where you want to save the data-files. The directory will be created if it does not exist."
    ]
@@ -141,7 +171,9 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -150,7 +182,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "Download the data for the Inception model if it doesn't already exist in the directory. It is 85 MB."
    ]
@@ -159,7 +194,9 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [
     {
@@ -177,50 +214,53 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Load the Inception Model"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "Load the Inception model so it is ready for classifying images.\n",
-    "\n",
-    "Note the deprecation warning, which might cause the program to fail in the future."
+    "Load the Inception model so it is ready for classifying images."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py:1811: VisibleDeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future\n",
-      "  result_shape.insert(dim, 1)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model = inception.Inception()"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Helper-function for classifying and plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "This is a simple wrapper-function for displaying the image, then classifying it using the Inception model and finally printing the classification scores."
    ]
@@ -229,7 +269,9 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -246,16 +288,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Panda"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image of a panda is included in the Inception data-file. The Inception model is quite confident that this image shows a panda, with a classification score of 89.23% and the next highest score being only 0.86% for an indri, which is another exotic animal."
+    "This image of a panda is included in the Inception data-file. The Inception model is quite confident that this image shows a panda, with a classification score of about 89% and the next highest score being only about 0.8% for an indri, which is another exotic animal."
    ]
   },
   {
@@ -263,6 +311,8 @@
    "execution_count": 8,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -280,16 +330,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "89.23% : giant panda\n",
-      " 0.86% : indri\n",
-      " 0.26% : lesser panda\n",
-      " 0.14% : custard apple\n",
-      " 0.11% : earthstar\n",
-      " 0.08% : sea urchin\n",
+      "89.11% : giant panda\n",
+      " 0.78% : indri\n",
+      " 0.30% : lesser panda\n",
+      " 0.15% : custard apple\n",
+      " 0.12% : earthstar\n",
+      " 0.09% : sea urchin\n",
       " 0.05% : forklift\n",
-      " 0.05% : soccer ball\n",
-      " 0.05% : go-kart\n",
-      " 0.05% : digital watch\n"
+      " 0.05% : digital watch\n",
+      " 0.05% : gibbon\n",
+      " 0.05% : go-kart\n"
      ]
     }
    ],
@@ -300,7 +350,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Interpretation of Classification Scores\n",
     "\n",
@@ -310,23 +363,29 @@
     "\n",
     "It is perhaps better to call the output values of a neural network for classification scores or ranks, because they indicate how strongly the network believes that the input image is of each possible class.\n",
     "\n",
-    "In the above example with the image of a panda, the Inception model gave a very high score of 89.23% for the panda-class, and the scores for the remaining 999 possible classes were all below 1%. This means the Inception model was quite certain that the image showed a panda and the remaining scores below 1% should be regarded as noise. For example, the 10th highest score was 0.05% for a digital watch, but this is probably more due to the imprecise nature of neural networks rather than an indication that the image looked slightly like a digital watch.\n",
+    "In the above example with the image of a panda, the Inception model gave a very high score of about 89% for the panda-class, and the scores for the remaining 999 possible classes were all below 1%. This means the Inception model was quite certain that the image showed a panda and the remaining scores below 1% should be regarded as noise. For example, the 8th highest score was 0.05% for a digital watch, but this is probably more due to the imprecise nature of neural networks rather than an indication that the image looked slightly like a digital watch.\n",
     "\n",
     "Sometimes the Inception model is confused about which class an image belongs to, so none of the scores are really high. Examples of this are shown below."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Original Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "The Inception model is very confident (score 97.30%) that this image shows a kind of parrot called a macaw."
+    "The Inception model is very confident (score about 97%) that this image shows a kind of parrot called a macaw."
    ]
   },
   {
@@ -334,6 +393,8 @@
    "execution_count": 9,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -351,16 +412,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "97.30% : macaw\n",
+      "97.18% : macaw\n",
       " 0.07% : African grey\n",
-      " 0.07% : toucan\n",
+      " 0.06% : toucan\n",
       " 0.05% : jacamar\n",
       " 0.04% : bee eater\n",
-      " 0.04% : lorikeet\n",
+      " 0.03% : lorikeet\n",
       " 0.02% : sulphur-crested cockatoo\n",
       " 0.02% : jay\n",
       " 0.01% : kite\n",
-      " 0.01% : sandbar\n"
+      " 0.01% : indigo bunting\n"
      ]
     }
    ],
@@ -370,14 +431,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Resized Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The Inception model works on input images that are 299 x 299 pixels in size. The above image of a parrot is actually 320 pixels wide and 785 pixels high, so it is resized automatically by the Inception model.\n",
     "\n",
@@ -390,7 +457,9 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -407,9 +476,12 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "Now plot the resized image of the parrot. This is the image that is actually input to the neural network of the Inception model. We can see that it has been squeezed so it is rectangular, and the resolution has been reduced so the image has become more pixelated and grainy.\n",
+    "Now plot the resized image of the parrot. This is the image that is actually input to the neural network of the Inception model. We can see that it has been squeezed so it is square, and the resolution has been reduced so the image has become more pixelated and grainy.\n",
     "\n",
     "In this case the image still clearly shows a parrot, but some images may become so distorted from this naive resizing that you may want to resize the images yourself before inputting them to the Inception model."
    ]
@@ -419,14 +491,16 @@
    "execution_count": 11,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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JFa46MTwTMQi3g/FXruFP7mBzDS8XmeulMTiIAf7NP4Ff3h7ACauugvc3B/h2gjk7ogak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\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wD5QSh7UQVkJJEjwQFSFKaCdtmm0U1JKEGVg3vwXIubKEyLIEYsigRIknLiWgkHQZmkmU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\nxBFHHPH/M4561EccccQRNxzHQH3EEUccc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DuPWUOaDqyKmmYaEpNC20q8CTJw2Nzyz9zFq3kAuWYdrBuINfbqvMGYUfRni0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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f4c076f9f98>"
+       "<matplotlib.figure.Figure at 0x7f392ff90630>"
       ]
      },
      "metadata": {},
@@ -439,16 +513,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Cropped Image, Top)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image of the parrot has been cropped manually to 299 x 299 pixels and then input to the Inception model, which is still very confident (score 97.38%) that it shows a parrot (macaw)."
+    "This image of the parrot has been cropped manually to 299 x 299 pixels and then input to the Inception model, which is still very confident (score about 97%) that it shows a parrot (macaw)."
    ]
   },
   {
@@ -456,6 +536,8 @@
    "execution_count": 12,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -473,7 +555,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "97.38% : macaw\n",
+      "97.52% : macaw\n",
       " 0.09% : African grey\n",
       " 0.03% : sulphur-crested cockatoo\n",
       " 0.02% : toucan\n",
@@ -492,16 +574,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Cropped Image, Middle)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This is another crop of the parrot image, this time showing its body without the head or tail. The Inception model is still very confident (score 93.94%) that it shows a macaw parrot."
+    "This is another crop of the parrot image, this time showing its body without the head or tail. The Inception model is still very confident (score about 94%) that it shows a macaw parrot."
    ]
   },
   {
@@ -509,6 +597,8 @@
    "execution_count": 13,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -526,16 +616,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "93.94% : macaw\n",
-      " 0.77% : toucan\n",
-      " 0.55% : African grey\n",
-      " 0.13% : jacamar\n",
-      " 0.12% : bee eater\n",
-      " 0.11% : sulphur-crested cockatoo\n",
-      " 0.10% : magpie\n",
-      " 0.09% : jay\n",
-      " 0.07% : lorikeet\n",
-      " 0.05% : hornbill\n"
+      "94.21% : macaw\n",
+      " 0.76% : toucan\n",
+      " 0.58% : African grey\n",
+      " 0.11% : jacamar\n",
+      " 0.10% : sulphur-crested cockatoo\n",
+      " 0.10% : bee eater\n",
+      " 0.09% : magpie\n",
+      " 0.08% : jay\n",
+      " 0.06% : lorikeet\n",
+      " 0.04% : hornbill\n"
      ]
     }
    ],
@@ -545,18 +635,24 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Cropped Image, Bottom)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image has been cropped so it only shows the tail of the parrot. Now the Inception model is quite confused and thinks the image might show a jacamar (score 26.11%) which is another exotic bird, or perhaps the image shows a grass-hopper (score 10.61%).\n",
+    "This image has been cropped so it only shows the tail of the parrot. Now the Inception model is quite confused and thinks the image might show a jacamar (score about 26%) which is another exotic bird, or perhaps the image shows a grass-hopper (score about 10%).\n",
     "\n",
-    "The Inception model also thinks the image might show a fountain-pen (score 2.00%). But this is a very low score and should be interpreted as unreliable noise."
+    "The Inception model also thinks the image might show a fountain-pen (score about 2%). But this is a very low score and should be interpreted as unreliable noise."
    ]
   },
   {
@@ -564,6 +660,8 @@
    "execution_count": 14,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -581,16 +679,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "26.11% : jacamar\n",
-      "10.61% : grasshopper\n",
-      " 4.05% : chime\n",
-      " 2.24% : bulbul\n",
-      " 2.00% : fountain pen\n",
-      " 1.60% : leafhopper\n",
-      " 1.26% : cricket\n",
-      " 1.25% : kite\n",
-      " 1.13% : macaw\n",
-      " 0.80% : torch\n"
+      "26.51% : jacamar\n",
+      "10.56% : grasshopper\n",
+      " 3.58% : chime\n",
+      " 2.15% : bulbul\n",
+      " 1.93% : fountain pen\n",
+      " 1.64% : leafhopper\n",
+      " 1.31% : kite\n",
+      " 1.22% : cricket\n",
+      " 1.09% : macaw\n",
+      " 0.81% : bee eater\n"
      ]
     }
    ],
@@ -600,16 +698,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Parrot (Padded Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "The best way to input images to this Inception model, is to pad the image so it is rectangular and then resize the image to 299 x 299 pixels, like this example of the parrot which is classified correctly with a score of 96.78%."
+    "The best way to input images to this Inception model, is to pad the image so it is square and then resize the image to 299 x 299 pixels, like this example of the parrot which is classified correctly with a score of about 97%."
    ]
   },
   {
@@ -617,6 +721,8 @@
    "execution_count": 15,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -634,9 +740,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "96.78% : macaw\n",
-      " 0.06% : toucan\n",
+      "96.87% : macaw\n",
       " 0.06% : African grey\n",
+      " 0.06% : toucan\n",
       " 0.05% : bee eater\n",
       " 0.04% : sulphur-crested cockatoo\n",
       " 0.03% : king penguin\n",
@@ -653,16 +759,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Elon Musk (299 x 299 pixels)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image shows the living legend and super-nerd-hero Elon Musk. But the Inception model is very confused about what the image shows, predicting that it maybe shows a sweatshirt (score 19.73%) or an abaya (score 16.82%). It also thinks the image might show a ping-pong ball (score 3.05%) or a baseball (score 1.86%). So the Inception model is confused and the classification scores are unreliable."
+    "This image shows the living legend and super-nerd-hero Elon Musk. But the Inception model is very confused about what the image shows, predicting that it maybe shows a sweatshirt (score about 17%) or an abaya (score about 16%). It also thinks the image might show a ping-pong ball (score about 3%) or a baseball (score about 2%). So the Inception model is confused and the classification scores are unreliable."
    ]
   },
   {
@@ -670,6 +782,8 @@
    "execution_count": 16,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -687,16 +801,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "19.73% : sweatshirt\n",
-      "16.82% : abaya\n",
-      " 4.17% : suit\n",
-      " 3.46% : trench coat\n",
-      " 3.05% : ping-pong ball\n",
-      " 1.92% : cellular telephone\n",
-      " 1.86% : baseball\n",
-      " 1.77% : jersey\n",
-      " 1.54% : kimono\n",
-      " 1.43% : water bottle\n"
+      "16.63% : sweatshirt\n",
+      "16.45% : abaya\n",
+      " 4.62% : suit\n",
+      " 3.40% : ping-pong ball\n",
+      " 2.89% : trench coat\n",
+      " 2.37% : baseball\n",
+      " 2.31% : cellular telephone\n",
+      " 1.99% : jersey\n",
+      " 1.42% : water bottle\n",
+      " 1.34% : dumbbell\n"
      ]
     }
    ],
@@ -706,16 +820,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Elon Musk (100 x 100 pixels)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "If we instead use a 100 x 100 pixels image of Elon Musk, then the Inception model thinks it might show a sweatshirt (score 17.85%) or a cowboy boot (score 16.36%). So now the Inception model has somewhat different predictions but it is still very confused."
+    "If we instead use a 100 x 100 pixels image of Elon Musk, then the Inception model thinks it might show a sweatshirt (score about 22%) or a cowboy boot (score about 14%). So now the Inception model has somewhat different predictions but it is still very confused."
    ]
   },
   {
@@ -723,6 +843,8 @@
    "execution_count": 17,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -740,16 +862,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "17.85% : sweatshirt\n",
-      "16.36% : cowboy boot\n",
-      "10.68% : balance beam\n",
-      " 8.87% : abaya\n",
-      " 5.36% : suit\n",
-      " 4.57% : Loafer\n",
-      " 2.94% : trench coat\n",
-      " 2.65% : maillot\n",
-      " 1.87% : jersey\n",
-      " 1.42% : unicycle\n"
+      "21.65% : sweatshirt\n",
+      "14.51% : cowboy boot\n",
+      " 9.11% : abaya\n",
+      " 8.70% : balance beam\n",
+      " 5.92% : suit\n",
+      " 5.65% : Loafer\n",
+      " 3.66% : trench coat\n",
+      " 1.75% : maillot\n",
+      " 1.44% : jersey\n",
+      " 1.44% : unicycle\n"
      ]
     }
    ],
@@ -759,7 +881,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "The Inception model automatically upscales this image from 100 x 100 to 299 x 299 pixels, which is shown here. Note how pixelated and grainy it really is, although a human can easily see that this is a picture of a man with crossed arms."
    ]
@@ -769,14 +894,16 @@
    "execution_count": 18,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
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Xg6Qsccgbk62emfoFBDEGsAvkdzWpYK1V2LBezimtlwH0lvUBFuVk7InbeyhY5xyKNbDV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zXKr/yuQAqwa5T7ssMlZdUwzkk50pqbyPo0BY6HA0+PD1Aj+544nSKnY1QOOUYK2obtvK08v7xw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\nt+kluKI7p+7buuWNbdtYttUdlS45avGV+rYV8lbIRbv7eq312xtRl1pYt42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9Hpf7A568/z3cXF/j5voKN5dX4qjU5xpsNUTKGed5wnk644//5Bf45NPPsKQX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\nXotzAl5fAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f4c07bca4a8>"
+       "<matplotlib.figure.Figure at 0x7f392f412f98>"
       ]
      },
      "metadata": {},
@@ -789,16 +916,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Willy Wonka (Gene Wilder)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image shows the actor Gene Wilder portraying Willy Wonka in the 1971 version of the movie. The Inception model is very confident that the image shows a bow tie (score 97.22%), which is true but a human would probably say this image shows a person.\n",
+    "This image shows the actor Gene Wilder portraying Willy Wonka in the 1971 version of the movie. The Inception model is very confident that the image shows a bow tie (score about 98%), which is true but a human would probably say this image shows a person.\n",
     "\n",
     "The reason might be that the Inception model was trained on images of people with bow-ties that were classified as a bow-tie rather than a person. So maybe the problem is that the class-name should be \"person with bow-tie\" instead of just \"bow-tie\"."
    ]
@@ -808,6 +941,8 @@
    "execution_count": 19,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -825,16 +960,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "97.22% : bow tie\n",
-      " 0.92% : cowboy hat\n",
-      " 0.21% : sombrero\n",
-      " 0.09% : suit\n",
-      " 0.06% : bolo tie\n",
-      " 0.05% : Windsor tie\n",
-      " 0.04% : cornet\n",
-      " 0.03% : flute\n",
+      "97.98% : bow tie\n",
+      " 0.63% : cowboy hat\n",
+      " 0.14% : sombrero\n",
+      " 0.07% : suit\n",
+      " 0.05% : bolo tie\n",
+      " 0.04% : Windsor tie\n",
+      " 0.03% : cornet\n",
+      " 0.02% : flute\n",
       " 0.02% : banjo\n",
-      " 0.02% : revolver\n"
+      " 0.01% : revolver\n"
      ]
     }
    ],
@@ -844,16 +979,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Willy Wonka (Johnny Depp)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
-    "This image shows the actor Johnny Depp portraying Willy Wonka in the 2005 version of the movie. The Inception model thinks that this image shows \"sunglasses\" (score 31.48%) or \"sunglass\" (score 18.77%). Actually, the full name of the first class is \"sunglasses, dark glasses, shades\". For some reason the Inception model has been trained to recognize two very similar classes for sunglasses. Once again, it is correct that the image shows sunglasses, but a human would probably have said that this image shows a person."
+    "This image shows the actor Johnny Depp portraying Willy Wonka in the 2005 version of the movie. The Inception model thinks that this image shows \"sunglasses\" (score about 34%) or \"sunglass\" (score about 18%). Actually, the full name of the first class is \"sunglasses, dark glasses, shades\". For some reason the Inception model has been trained to recognize two very similar classes for sunglasses. Once again, it is correct that the image shows sunglasses, but a human would probably have said that this image shows a person."
    ]
   },
   {
@@ -861,6 +1002,8 @@
    "execution_count": 20,
    "metadata": {
     "collapsed": false,
+    "deletable": true,
+    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -878,16 +1021,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "31.48% : sunglasses\n",
-      "18.77% : sunglass\n",
-      " 1.55% : velvet\n",
-      " 1.02% : wig\n",
-      " 0.77% : cowboy hat\n",
-      " 0.69% : seat belt\n",
-      " 0.67% : sombrero\n",
-      " 0.62% : jean\n",
-      " 0.46% : poncho\n",
-      " 0.43% : jersey\n"
+      "34.47% : sunglasses\n",
+      "18.10% : sunglass\n",
+      " 1.29% : velvet\n",
+      " 0.95% : wig\n",
+      " 0.85% : cowboy hat\n",
+      " 0.72% : sombrero\n",
+      " 0.64% : seat belt\n",
+      " 0.50% : jean\n",
+      " 0.44% : stole\n",
+      " 0.41% : poncho\n"
      ]
     }
    ],
@@ -897,14 +1040,20 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources. Note that the TensorFlow-session is inside the model-object, so we close the session through that object."
    ]
@@ -913,7 +1062,9 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -924,7 +1075,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Conclusion\n",
     "\n",
@@ -937,7 +1091,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## Exercises\n",
     "\n",
@@ -954,7 +1111,10 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -971,7 +1131,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -985,7 +1145,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,

From d4e1375d4d48a441039520813ba061c36f1af3fe Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Jun 2017 14:06:20 +0200
Subject: [PATCH 16/61] Added link to Chinese translation.

---
 README.md | 21 ++++++++++++++-------
 1 file changed, 14 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index a2b1d63..b86ad58 100644
--- a/README.md
+++ b/README.md
@@ -57,14 +57,13 @@ Even a few dollars are appreciated. Thanks!
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
 
-## Older Versions
+## Translations
 
-Sometimes the source-code has changed from that shown in the YouTube videos. This may be due to
-bug-fixes, improvements, or because code-sections are moved to separate files for easy re-use.
+These tutorials have been translated to the following languages:
 
-If you want to see the exact versions of the source-code that were used in the YouTube videos,
-then you can [browse the history](https://github.com/Hvass-Labs/TensorFlow-Tutorials/commits/master)
-of commits to the GitHub repository.
+* [Chinese](https://github.com/naivechen/TensorFlow-Tutorials)
+
+You can help by translating the remaining tutorials or reviewing the ones that have already been translated. You can also help by translating to other languages.
 
 ## Downloading
 
@@ -140,6 +139,15 @@ You should now be able to run the tutorials in the Python Notebooks:
 
 This should start a web-browser that shows the list of tutorials. Click on a tutorial to load it.
 
+## Older Versions
+
+Sometimes the source-code has changed from that shown in the YouTube videos. This may be due to
+bug-fixes, improvements, or because code-sections are moved to separate files for easy re-use.
+
+If you want to see the exact versions of the source-code that were used in the YouTube videos,
+then you can [browse the history](https://github.com/Hvass-Labs/TensorFlow-Tutorials/commits/master)
+of commits to the GitHub repository.
+
 ## License (MIT)
 
 These tutorials and source-code are published under the [MIT License](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/LICENSE)
@@ -149,4 +157,3 @@ A few of the images used for demonstration purposes may be under copyright. Thes
 
 You are very welcome to modify these tutorials and use them in your own projects.
 Please keep a link to the [original repository](https://github.com/Hvass-Labs/TensorFlow-Tutorials).
-

From 7121887da7cea1803812ae84bcdc1edb417c6843 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Jun 2017 14:16:44 +0200
Subject: [PATCH 17/61] Fixed bug in one_hot_encoded()

---
 dataset.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/dataset.py b/dataset.py
index b4099cf..0a759ee 100644
--- a/dataset.py
+++ b/dataset.py
@@ -37,15 +37,16 @@ def one_hot_encoded(class_numbers, num_classes=None):
         Assume the integers are from zero to num_classes-1 inclusive.
 
     :param num_classes:
-        Number of classes. If None then use max(cls)-1.
+        Number of classes. If None then use max(class_numbers)-1.
 
     :return:
-        2-dim array of shape: [len(cls), num_classes]
+        2-dim array of shape: [len(class_numbers), num_classes]
     """
 
     # Find the number of classes if None is provided.
+    # Assumes the lowest class-number is zero.
     if num_classes is None:
-        num_classes = np.max(class_numbers) - 1
+        num_classes = np.max(class_numbers) + 1
 
     return np.eye(num_classes, dtype=float)[class_numbers]
 

From f104aafb806637cb5462a3bfb161c3aff37e9f58 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Jun 2017 14:17:32 +0200
Subject: [PATCH 18/61] Fixed bug in one_hot_encoded()

---
 dataset.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dataset.py b/dataset.py
index 0a759ee..545c190 100644
--- a/dataset.py
+++ b/dataset.py
@@ -37,7 +37,7 @@ def one_hot_encoded(class_numbers, num_classes=None):
         Assume the integers are from zero to num_classes-1 inclusive.
 
     :param num_classes:
-        Number of classes. If None then use max(class_numbers)-1.
+        Number of classes. If None then use max(class_numbers)+1.
 
     :return:
         2-dim array of shape: [len(class_numbers), num_classes]

From 3f81852979292f3e1c507eee0906c68f03607148 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 5 Jul 2017 09:29:58 +0200
Subject: [PATCH 19/61] Replaced link to Chinese translation with more complete
 version.

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index b86ad58..f33153f 100644
--- a/README.md
+++ b/README.md
@@ -61,7 +61,7 @@ These tutorials are also available as [YouTube videos](https://www.youtube.com/p
 
 These tutorials have been translated to the following languages:
 
-* [Chinese](https://github.com/naivechen/TensorFlow-Tutorials)
+* [Chinese](https://github.com/thrillerist/TensorFlow-Tutorials)
 
 You can help by translating the remaining tutorials or reviewing the ones that have already been translated. You can also help by translating to other languages.
 

From 9c48432ab879132ef3f4814cfa18cce425d5fbe0 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 27 Sep 2017 08:18:12 +0200
Subject: [PATCH 20/61] Added Tutorial 13-B

---
 13B_Visual_Analysis_MNIST.ipynb          | 2302 ++++++++++++++++++++++
 README.md                                |    2 +
 images/13b_visual_analysis_flowchart.png |  Bin 0 -> 89704 bytes
 images/13b_visual_analysis_flowchart.svg |  779 ++++++++
 4 files changed, 3083 insertions(+)
 create mode 100644 13B_Visual_Analysis_MNIST.ipynb
 create mode 100644 images/13b_visual_analysis_flowchart.png
 create mode 100644 images/13b_visual_analysis_flowchart.svg

diff --git a/13B_Visual_Analysis_MNIST.ipynb b/13B_Visual_Analysis_MNIST.ipynb
new file mode 100644
index 0000000..b5098dd
--- /dev/null
+++ b/13B_Visual_Analysis_MNIST.ipynb
@@ -0,0 +1,2302 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #13-B\n",
+    "# Visual Analysis (MNIST)\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "Tutorial #13 showed how to find input images that maximized the response of individual neurons inside the Inception model, so as to find the images that the neuron *liked to see*. But because the Inception model is so large and complex the images were just complex wavy patterns.\n",
+    "\n",
+    "This tutorial uses a much simpler Convolutional Neural Network with the MNIST data-set for recognizing hand-written digits. The code is spliced together from Tutorial #03-B for constructing the neural network and Tutorial #13 for finding input images that maximize individual neuron responses inside the neural network, so a lot of this code may look familiar to you."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Flowchart"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. Note that there are two separate optimization loops here:\n",
+    "\n",
+    "First the weights of the neural network are optimized by inputting images and their true classes to the network so as to improve the classification accuracy.\n",
+    "\n",
+    "Afterwards a second optimization is performed which finds the input image that maximizes a given feature or neuron inside the network. This finds an image that the network *likes to see*."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Flowchart](images/13b_visual_analysis_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.3.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.examples.tutorials.mnist import input_data\n",
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t55000\n",
+      "- Test-set:\t\t10000\n",
+      "- Validation-set:\t5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
+    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Data Dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# We know that MNIST images are 28 pixels in each dimension.\n",
+    "img_size = 28\n",
+    "\n",
+    "# Images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = img_size * img_size\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "img_shape = (img_size, img_size)\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = 1\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-functions for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None):\n",
+    "    assert len(images) == len(cls_true) == 9\n",
+    "    \n",
+    "    # Create figure with 3x3 sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "    fig.subplots_adjust(hspace=0.3, wspace=0.3)\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Plot image.\n",
+    "        ax.imshow(images[i].reshape(img_shape), cmap='binary')\n",
+    "\n",
+    "        # Show true and predicted classes.\n",
+    "        if cls_pred is None:\n",
+    "            xlabel = \"True: {0}\".format(cls_true[i])\n",
+    "        else:\n",
+    "            xlabel = \"True: {0}, Pred: {1}\".format(cls_true[i], cls_pred[i])\n",
+    "\n",
+    "        # Show the classes as the label on the x-axis.\n",
+    "        ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 10 images in a 2x5 grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images10(images, smooth=True):\n",
+    "    # Interpolation type.\n",
+    "    if smooth:\n",
+    "        interpolation = 'spline16'\n",
+    "    else:\n",
+    "        interpolation = 'nearest'\n",
+    "\n",
+    "    # Create figure with sub-plots.\n",
+    "    fig, axes = plt.subplots(2, 5)\n",
+    "\n",
+    "    # Adjust vertical spacing.\n",
+    "    fig.subplots_adjust(hspace=0.1, wspace=0.1)\n",
+    "\n",
+    "    # For each entry in the grid.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Get the i'th image and only use the desired pixels.\n",
+    "        img = images[i, :, :]\n",
+    "        \n",
+    "        # Plot the image.\n",
+    "        ax.imshow(img, interpolation=interpolation, cmap='binary')\n",
+    "\n",
+    "        # Remove ticks.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "\n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot a single image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_image(image):\n",
+    "    plt.imshow(image, interpolation='nearest', cmap='binary')\n",
+    "    plt.xticks([])\n",
+    "    plt.yticks([])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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zh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff410829320>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the first images from the test-set.\n",
+    "images = data.test.images[0:9]\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = data.test.cls[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## TensorFlow Graph\n",
+    "\n",
+    "The neural network is constructed as a computational graph in TensorFlow using the `tf.layers` API, which is described in detail in Tutorial #03-B."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Placeholder variables"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph.\n",
+    "\n",
+    "First we define the placeholder variable for the input images. This allows us to change the images that are input to the TensorFlow graph. This is a so-called tensor, which just means that it is a multi-dimensional array. The data-type is set to `float32` and the shape is set to `[None, img_size_flat]`, where `None` means that the tensor may hold an arbitrary number of images with each image being a vector of length `img_size_flat`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The convolutional layers expect `x` to be encoded as a 4-rank tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_true_cls = tf.argmax(y_true, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Neural Network\n",
+    "\n",
+    "We now implement the Convolutional Neural Network using the Layers API. We use the `net`-variable to refer to the last layer while building the neural network. This makes it easy to add or remove layers in the code if you want to experiment. First we set the `net`-variable to the reshaped input image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = x_image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The input image is then input to the first convolutional layer, which has 16 filters each of size 5x5 pixels. The activation-function is the Rectified Linear Unit (ReLU) described in more detail in Tutorial #02."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv1', padding='same',\n",
+    "                       filters=16, kernel_size=5, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "After the convolution we do a max-pooling which is also described in Tutorial #02."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Then we make a second convolutional layer, also with max-pooling."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv2', padding='same',\n",
+    "                       filters=36, kernel_size=5, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The output then needs to be flattened so it can be used in fully-connected (aka. dense) layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.contrib.layers.flatten(net)\n",
+    "\n",
+    "# This should eventually be replaced by:\n",
+    "# net = tf.layers.flatten(net)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can now add fully-connected (or dense) layers to the neural network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
+    "                      units=128, activation=tf.nn.relu)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We need the neural network to classify the input images into 10 different classes. So the final fully-connected layer has `num_classes=10` output neurons."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "net = tf.layers.dense(inputs=net, name='layer_fc_out',\n",
+    "                      units=num_classes, activation=None)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The outputs of the final fully-connected layer are sometimes called logits, so we have a convenience variable with that name which we will also use further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "logits = net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We use the softmax function to 'squash' the outputs so they are between zero and one, and so they sum to one."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = tf.nn.softmax(logits=logits)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This tells us how likely the neural network thinks the input image is of each possible class. The one that has the highest value is considered the most likely so its index is taken to be the class-number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_cls = tf.argmax(y_pred, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Loss-Function to be Optimized"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "To make the model better at classifying the input images, we must somehow change the variables of the neural network.\n",
+    "\n",
+    "The cross-entropy is a performance measure used in classification. The cross-entropy is a continuous function that is always positive and if the predicted output of the model exactly matches the desired output then the cross-entropy equals zero. The goal of optimization is therefore to minimize the cross-entropy so it gets as close to zero as possible by changing the variables of the model.\n",
+    "\n",
+    "TensorFlow has a function for calculating the cross-entropy, which uses the values of the `logits`-layer because it also calculates the softmax internally, so as to to improve numerical stability."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_true, logits=logits)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "loss = tf.reduce_mean(cross_entropy)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Optimization Method\n",
+    "\n",
+    "Now that we have a cost measure that must be minimized, we can then create an optimizer. In this case it is the Adam optimizer with a learning-rate of 1e-4.\n",
+    "\n",
+    "Note that optimization is not performed at this point. In fact, nothing is calculated at all, we just add the optimizer-object to the TensorFlow graph for later execution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Classification Accuracy\n",
+    "\n",
+    "We need to calculate the classification accuracy so we can report progress to the user.\n",
+    "\n",
+    "First we create a vector of booleans telling us whether the predicted class equals the true class of each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Optimize the Neural Network"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Create TensorFlow session\n",
+    "\n",
+    "Once the TensorFlow graph has been created, we have to create a TensorFlow session which is used to execute the graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "session = tf.Session()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Initialize variables\n",
+    "\n",
+    "The variables for the TensorFlow graph must be initialized before we start optimizing them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "session.run(tf.global_variables_initializer())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to perform optimization iterations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
+    "\n",
+    "If your computer crashes or becomes very slow because you run out of RAM, then you may try and lower this number, but you may then need to do more optimization iterations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "train_batch_size = 64"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This function performs a number of optimization iterations so as to gradually improve the variables of the neural network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Counter for total number of iterations performed so far.\n",
+    "total_iterations = 0\n",
+    "\n",
+    "def optimize(num_iterations):\n",
+    "    # Ensure we update the global variable rather than a local copy.\n",
+    "    global total_iterations\n",
+    "\n",
+    "    for i in range(total_iterations,\n",
+    "                   total_iterations + num_iterations):\n",
+    "\n",
+    "        # Get a batch of training examples.\n",
+    "        # x_batch now holds a batch of images and\n",
+    "        # y_true_batch are the true labels for those images.\n",
+    "        x_batch, y_true_batch = data.train.next_batch(train_batch_size)\n",
+    "\n",
+    "        # Put the batch into a dict with the proper names\n",
+    "        # for placeholder variables in the TensorFlow graph.\n",
+    "        feed_dict_train = {x: x_batch,\n",
+    "                           y_true: y_true_batch}\n",
+    "\n",
+    "        # Run the optimizer using this batch of training data.\n",
+    "        # TensorFlow assigns the variables in feed_dict_train\n",
+    "        # to the placeholder variables and then runs the optimizer.\n",
+    "        session.run(optimizer, feed_dict=feed_dict_train)\n",
+    "\n",
+    "        # Print status every 100 iterations.\n",
+    "        if i % 100 == 0:\n",
+    "            # Calculate the accuracy on the training-set.\n",
+    "            acc = session.run(accuracy, feed_dict=feed_dict_train)\n",
+    "\n",
+    "            # Message for printing.\n",
+    "            msg = \"Optimization Iteration: {0:>6}, Training Accuracy: {1:>6.1%}\"\n",
+    "\n",
+    "            # Print it.\n",
+    "            print(msg.format(i + 1, acc))\n",
+    "\n",
+    "    # Update the total number of iterations performed.\n",
+    "    total_iterations += num_iterations"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to plot example errors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function for plotting examples of images from the test-set that have been mis-classified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_example_errors(cls_pred, correct):\n",
+    "    # This function is called from print_test_accuracy() below.\n",
+    "\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # correct is a boolean array whether the predicted class\n",
+    "    # is equal to the true class for each image in the test-set.\n",
+    "\n",
+    "    # Negate the boolean array.\n",
+    "    incorrect = (correct == False)\n",
+    "    \n",
+    "    # Get the images from the test-set that have been\n",
+    "    # incorrectly classified.\n",
+    "    images = data.test.images[incorrect]\n",
+    "    \n",
+    "    # Get the predicted classes for those images.\n",
+    "    cls_pred = cls_pred[incorrect]\n",
+    "\n",
+    "    # Get the true classes for those images.\n",
+    "    cls_true = data.test.cls[incorrect]\n",
+    "    \n",
+    "    # Plot the first 9 images.\n",
+    "    plot_images(images=images[0:9],\n",
+    "                cls_true=cls_true[0:9],\n",
+    "                cls_pred=cls_pred[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to plot confusion matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_confusion_matrix(cls_pred):\n",
+    "    # This is called from print_test_accuracy() below.\n",
+    "\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Get the true classifications for the test-set.\n",
+    "    cls_true = data.test.cls\n",
+    "    \n",
+    "    # Get the confusion matrix using sklearn.\n",
+    "    cm = confusion_matrix(y_true=cls_true,\n",
+    "                          y_pred=cls_pred)\n",
+    "\n",
+    "    # Print the confusion matrix as text.\n",
+    "    print(cm)\n",
+    "\n",
+    "    # Plot the confusion matrix as an image.\n",
+    "    plt.matshow(cm)\n",
+    "\n",
+    "    # Make various adjustments to the plot.\n",
+    "    plt.colorbar()\n",
+    "    tick_marks = np.arange(num_classes)\n",
+    "    plt.xticks(tick_marks, range(num_classes))\n",
+    "    plt.yticks(tick_marks, range(num_classes))\n",
+    "    plt.xlabel('Predicted')\n",
+    "    plt.ylabel('True')\n",
+    "\n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for showing the performance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Below is a function for printing the classification accuracy on the test-set.\n",
+    "\n",
+    "It takes a while to compute the classification for all the images in the test-set, that's why the results are re-used by calling the above functions directly from this function, so the classifications don't have to be recalculated by each function.\n",
+    "\n",
+    "Note that this function can use a lot of computer memory, which is why the test-set is split into smaller batches. If you have little RAM in your computer and it crashes, then you can try and lower the batch-size."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Split the test-set into smaller batches of this size.\n",
+    "test_batch_size = 256\n",
+    "\n",
+    "def print_test_accuracy(show_example_errors=False,\n",
+    "                        show_confusion_matrix=False):\n",
+    "\n",
+    "    # Number of images in the test-set.\n",
+    "    num_test = len(data.test.images)\n",
+    "\n",
+    "    # Allocate an array for the predicted classes which\n",
+    "    # will be calculated in batches and filled into this array.\n",
+    "    cls_pred = np.zeros(shape=num_test, dtype=np.int)\n",
+    "\n",
+    "    # Now calculate the predicted classes for the batches.\n",
+    "    # We will just iterate through all the batches.\n",
+    "    # There might be a more clever and Pythonic way of doing this.\n",
+    "\n",
+    "    # The starting index for the next batch is denoted i.\n",
+    "    i = 0\n",
+    "\n",
+    "    while i < num_test:\n",
+    "        # The ending index for the next batch is denoted j.\n",
+    "        j = min(i + test_batch_size, num_test)\n",
+    "\n",
+    "        # Get the images from the test-set between index i and j.\n",
+    "        images = data.test.images[i:j, :]\n",
+    "\n",
+    "        # Get the associated labels.\n",
+    "        labels = data.test.labels[i:j, :]\n",
+    "\n",
+    "        # Create a feed-dict with these images and labels.\n",
+    "        feed_dict = {x: images,\n",
+    "                     y_true: labels}\n",
+    "\n",
+    "        # Calculate the predicted class using TensorFlow.\n",
+    "        cls_pred[i:j] = session.run(y_pred_cls, feed_dict=feed_dict)\n",
+    "\n",
+    "        # Set the start-index for the next batch to the\n",
+    "        # end-index of the current batch.\n",
+    "        i = j\n",
+    "\n",
+    "    # Convenience variable for the true class-numbers of the test-set.\n",
+    "    cls_true = data.test.cls\n",
+    "\n",
+    "    # Create a boolean array whether each image is correctly classified.\n",
+    "    correct = (cls_true == cls_pred)\n",
+    "\n",
+    "    # Calculate the number of correctly classified images.\n",
+    "    # When summing a boolean array, False means 0 and True means 1.\n",
+    "    correct_sum = correct.sum()\n",
+    "\n",
+    "    # Classification accuracy is the number of correctly classified\n",
+    "    # images divided by the total number of images in the test-set.\n",
+    "    acc = float(correct_sum) / num_test\n",
+    "\n",
+    "    # Print the accuracy.\n",
+    "    msg = \"Accuracy on Test-Set: {0:.1%} ({1} / {2})\"\n",
+    "    print(msg.format(acc, correct_sum, num_test))\n",
+    "\n",
+    "    # Plot some examples of mis-classifications, if desired.\n",
+    "    if show_example_errors:\n",
+    "        print(\"Example errors:\")\n",
+    "        plot_example_errors(cls_pred=cls_pred, correct=correct)\n",
+    "\n",
+    "    # Plot the confusion matrix, if desired.\n",
+    "    if show_confusion_matrix:\n",
+    "        print(\"Confusion Matrix:\")\n",
+    "        plot_confusion_matrix(cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Performance before any optimization\n",
+    "\n",
+    "The accuracy on the test-set is very low because the variables for the neural network have only been initialized and not optimized at all, so it just classifies the images randomly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 9.3% (933 / 10000)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_test_accuracy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Performance after 10,000 optimization iterations\n",
+    "\n",
+    "After 10,000 optimization iterations, the model has a classification accuracy on the test-set of about 99%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimization Iteration:      1, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    101, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    301, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    501, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    901, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2301, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   2701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3001, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3801, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4101, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   5401, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   7401, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   7601, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   8101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   8201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8301, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   8901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9001, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
+      "CPU times: user 38.6 s, sys: 4.3 s, total: 42.9 s\n",
+      "Wall time: 31 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "optimize(num_iterations=10000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy on Test-Set: 98.9% (9888 / 10000)\n",
+      "Example errors:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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//A8AvqTOJpu0jNn2FGmKiKRQ8UjT2yTrs+666wJw2WWXAXD++eeXJU1SGh41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\nA2AvH/r72fAdAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff40bd9d8d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Confusion Matrix:\n",
+      "[[ 977    0    0    0    0    0    1    0    1    1]\n",
+      " [   0 1134    0    0    0    0    0    1    0    0]\n",
+      " [   2    3 1021    0    1    0    0    4    1    0]\n",
+      " [   1    0    1  999    0    3    0    3    1    2]\n",
+      " [   0    0    0    0  981    0    0    0    0    1]\n",
+      " [   2    0    0    3    0  883    1    1    0    2]\n",
+      " [   3    3    0    0    4    2  946    0    0    0]\n",
+      " [   0    2    5    0    1    0    0 1019    1    0]\n",
+      " [   7    2    4    2    3    1    4    4  941    6]\n",
+      " [   1    5    0    0   10    3    0    2    1  987]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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MeF+ZvVkMPDGuCzQlW22RSPoSEzSFbG/erIqIHkxhRqaODwIXSdoOuBf4ACVnsqSTgPuA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\nCSQR0VgCSUQ0lkASEY39f2GvAFCULtk9AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff3ad7e4278>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "print_test_accuracy(show_example_errors=True,\n",
+    "                    show_confusion_matrix=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Optimizing the Input Images\n",
+    "\n",
+    "Now that the neural network has been optimized so it can recognize hand-written digits with about 99% accuracy, we will then find the input images that maximize certain features inside the neural network. This will show us what images the neural network *likes to see* the most.\n",
+    "\n",
+    "We will do this by creating another form of optimization for the neural network, and we need several helper functions for doing this."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for getting the names of convolutional layers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function for getting the names of all the convolutional layers in the neural network. We could have made this list manually, but for larger neural networks it is easier to do this with a function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def get_conv_layer_names():\n",
+    "    graph = tf.get_default_graph()\n",
+    "    \n",
+    "    # Create a list of names for the operations in the graph\n",
+    "    # for the Inception model where the operator-type is 'Conv2D'.\n",
+    "    names = [op.name for op in graph.get_operations() if op.type=='Conv2D']\n",
+    "\n",
+    "    return names"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "conv_names = get_conv_layer_names()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['layer_conv1/convolution', 'layer_conv2/convolution']"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "conv_names"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(conv_names)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for finding the input image"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This function finds the input image that maximizes a given feature in the network. It essentially just performs optimization with gradient ascent. The image is initialized with small random values and is then iteratively updated using the gradient for the given feature with regard to the image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def optimize_image(conv_id=None, feature=0,\n",
+    "                   num_iterations=30, show_progress=True):\n",
+    "    \"\"\"\n",
+    "    Find an image that maximizes the feature\n",
+    "    given by the conv_id and feature number.\n",
+    "\n",
+    "    Parameters:\n",
+    "    conv_id: Integer identifying the convolutional layer to\n",
+    "             maximize. It is an index into conv_names.\n",
+    "             If None then use the last fully-connected layer\n",
+    "             before the softmax output.\n",
+    "    feature: Index into the layer for the feature to maximize.\n",
+    "    num_iteration: Number of optimization iterations to perform.\n",
+    "    show_progress: Boolean whether to show the progress.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Create the loss-function that must be maximized.\n",
+    "    if conv_id is None:\n",
+    "        # If we want to maximize a feature on the last layer,\n",
+    "        # then we use the fully-connected layer prior to the\n",
+    "        # softmax-classifier. The feature no. is the class-number\n",
+    "        # and must be an integer between 1 and 1000.\n",
+    "        # The loss-function is just the value of that feature.\n",
+    "        loss = tf.reduce_mean(logits[:, feature])\n",
+    "    else:\n",
+    "        # If instead we want to maximize a feature of a\n",
+    "        # convolutional layer inside the neural network.\n",
+    "\n",
+    "        # Get the name of the convolutional operator.\n",
+    "        conv_name = conv_names[conv_id]\n",
+    "        \n",
+    "        # Get the default TensorFlow graph.\n",
+    "        graph = tf.get_default_graph()\n",
+    "        \n",
+    "        # Get a reference to the tensor that is output by the\n",
+    "        # operator. Note that \":0\" is added to the name for this.\n",
+    "        tensor = graph.get_tensor_by_name(conv_name + \":0\")\n",
+    "\n",
+    "        # The loss-function is the average of all the\n",
+    "        # tensor-values for the given feature. This\n",
+    "        # ensures that we generate the whole input image.\n",
+    "        # You can try and modify this so it only uses\n",
+    "        # a part of the tensor.\n",
+    "        loss = tf.reduce_mean(tensor[:,:,:,feature])\n",
+    "\n",
+    "    # Get the gradient for the loss-function with regard to\n",
+    "    # the input image. This creates a mathematical\n",
+    "    # function for calculating the gradient.\n",
+    "    gradient = tf.gradients(loss, x_image)\n",
+    "\n",
+    "    # Generate a random image of the same size as the raw input.\n",
+    "    # Each pixel is a small random value between 0.45 and 0.55,\n",
+    "    # which is the middle of the valid range between 0 and 1.\n",
+    "    image = 0.1 * np.random.uniform(size=img_shape) + 0.45\n",
+    "\n",
+    "    # Perform a number of optimization iterations to find\n",
+    "    # the image that maximizes the loss-function.\n",
+    "    for i in range(num_iterations):\n",
+    "        # Reshape the array so it is a 4-rank tensor.\n",
+    "        img_reshaped = image[np.newaxis,:,:,np.newaxis]\n",
+    "\n",
+    "        # Create a feed-dict for inputting the image to the graph.\n",
+    "        feed_dict = {x_image: img_reshaped}\n",
+    "\n",
+    "        # Calculate the predicted class-scores,\n",
+    "        # as well as the gradient and the loss-value.\n",
+    "        pred, grad, loss_value = session.run([y_pred, gradient, loss],\n",
+    "                                             feed_dict=feed_dict)\n",
+    "        \n",
+    "        # Squeeze the dimensionality for the gradient-array.\n",
+    "        grad = np.array(grad).squeeze()\n",
+    "\n",
+    "        # The gradient now tells us how much we need to change the\n",
+    "        # input image in order to maximize the given feature.\n",
+    "\n",
+    "        # Calculate the step-size for updating the image.\n",
+    "        # This step-size was found to give fast convergence.\n",
+    "        # The addition of 1e-8 is to protect from div-by-zero.\n",
+    "        step_size = 1.0 / (grad.std() + 1e-8)\n",
+    "\n",
+    "        # Update the image by adding the scaled gradient\n",
+    "        # This is called gradient ascent.\n",
+    "        image += step_size * grad\n",
+    "\n",
+    "        # Ensure all pixel-values in the image are between 0 and 1.\n",
+    "        image = np.clip(image, 0.0, 1.0)\n",
+    "\n",
+    "        if show_progress:\n",
+    "            print(\"Iteration:\", i)\n",
+    "\n",
+    "            # Convert the predicted class-scores to a one-dim array.\n",
+    "            pred = np.squeeze(pred)\n",
+    "\n",
+    "            # The predicted class for the Inception model.\n",
+    "            pred_cls = np.argmax(pred)\n",
+    "\n",
+    "            # The score (probability) for the predicted class.\n",
+    "            cls_score = pred[pred_cls]\n",
+    "\n",
+    "            # Print the predicted score etc.\n",
+    "            msg = \"Predicted class: {0}, score: {1:>7.2%}\"\n",
+    "            print(msg.format(pred_cls, cls_score))\n",
+    "\n",
+    "            # Print statistics for the gradient.\n",
+    "            msg = \"Gradient min: {0:>9.6f}, max: {1:>9.6f}, stepsize: {2:>9.2f}\"\n",
+    "            print(msg.format(grad.min(), grad.max(), step_size))\n",
+    "\n",
+    "            # Print the loss-value.\n",
+    "            print(\"Loss:\", loss_value)\n",
+    "\n",
+    "            # Newline.\n",
+    "            print()\n",
+    "\n",
+    "    return image.squeeze()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This next function finds the images that maximize the first 10 features of a layer, by calling the above function 10 times."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def optimize_images(conv_id=None, num_iterations=30):\n",
+    "    \"\"\"\n",
+    "    Find 10 images that maximize the 10 first features in the layer\n",
+    "    given by the conv_id.\n",
+    "    \n",
+    "    Parameters:\n",
+    "    conv_id: Integer identifying the convolutional layer to\n",
+    "             maximize. It is an index into conv_names.\n",
+    "             If None then use the last layer before the softmax output.\n",
+    "    num_iterations: Number of optimization iterations to perform.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Which layer are we using?\n",
+    "    if conv_id is None:\n",
+    "        print(\"Final fully-connected layer before softmax.\")\n",
+    "    else:\n",
+    "        print(\"Layer:\", conv_names[conv_id])\n",
+    "\n",
+    "    # Initialize the array of images.\n",
+    "    images = []\n",
+    "\n",
+    "    # For each feature do the following.\n",
+    "    for feature in range(0,10):\n",
+    "        print(\"Optimizing image for feature no.\", feature)\n",
+    "        \n",
+    "        # Find the image that maximizes the given feature\n",
+    "        # for the network layer identified by conv_id (or None).\n",
+    "        image = optimize_image(conv_id=conv_id, feature=feature,\n",
+    "                               show_progress=False,\n",
+    "                               num_iterations=num_iterations)\n",
+    "\n",
+    "        # Squeeze the dim of the array.\n",
+    "        image = image.squeeze()\n",
+    "\n",
+    "        # Append to the list of images.\n",
+    "        images.append(image)\n",
+    "\n",
+    "    # Convert to numpy-array so we can index all dimensions easily.\n",
+    "    images = np.array(images)\n",
+    "\n",
+    "    # Plot the images.\n",
+    "    plot_images10(images=images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### First Convolutional Layer\n",
+    "\n",
+    "These are the input images that maximize the features in the first convolutional layer, so these are the images that it *likes to see*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Layer: layer_conv1/convolution\n",
+      "Optimizing image for feature no. 0\n",
+      "Optimizing image for feature no. 1\n",
+      "Optimizing image for feature no. 2\n",
+      "Optimizing image for feature no. 3\n",
+      "Optimizing image for feature no. 4\n",
+      "Optimizing image for feature no. 5\n",
+      "Optimizing image for feature no. 6\n",
+      "Optimizing image for feature no. 7\n",
+      "Optimizing image for feature no. 8\n",
+      "Optimizing image for feature no. 9\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAADFCAYAAABjLIjfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACEpJREFUeJzt28FqXGUbwPHnnKaZUIYSh1ZaEYziriAUlEqluhH0Gtyo\nFyC4dq+gKHgBgrfgRehCaRbSnYtCu2naNBCpJKGdnONCvn4mno7OnHNyniS/33KSlqcvb//zzjsz\nRV3XAcDwyqEHAOAvggyQhCADJCHIAEkIMkASggyQhCADJCHIAEkIMkASS/P88oULF+q1tbWIiNjf\n34979+7F/fv3+5grm4d1XV88/GBRFKfqa46rq6vx/PPPx9bWVjx8+LA4/PPJZFK/+OKLUZZlPH78\nOB48eBBbW1tDjHrUGvfH3/+/nCbr6+vPXI/JZBIPHjyI33//fYjRhtK4Hk3mCvLa2lrcvHkzIiK2\nt7fj888/j2+++SZOwdev7ww9QAaTySSuXLkSP/74Y+PPy7KM119/PZaWluLRo0fx66+/npYgN+6P\nv/9/Oenquo6i+Os5uiiKxvUoyzKuXLkST548OW1B/s/9mCvInG63b9+O27dvP/PnW1tb8f333x/h\nRLlVVRU7OztDj9G5/x3AiqKIs2fPxtmzZ5/GeJbNzc344Ycf+h7vWBNk6MnGxkZ8+eWXQ4/Ruaqq\nYm9vL8bjcbz11ltx48aNGI1GQ491Iggy9GRjYyO++uqrocfo3HQ6jel0GuPxOKbTaVy7dk2QOyLI\n0JO6rmNvb2/oMXrzxx9/xPb2dlRVNfQoJ4aPvQELW1lZ+U/3x/w3ggwspCzLOHPmzNBjnCiCDJCE\nIAMkIchAK+6QuyPIQCun4Ju6R0aQAZIQZKAVVxbdEWSgFVcW3RFkoBUn5O4IMtCKE3J3BBkgCUEG\nSEKQgVbcIXdHkIFW3CF3R5ABkhBkoBVXFt0RZKAVVxbdEWSgFSfk7ggy0IoTcncEGSAJQQZIQpCB\nVtwhd0eQgVbcIXdHkAGSEGSgFVcW3RFkoBVXFt0RZKAVJ+TuCDLQihNydwQZIAlBBkhCkIFW3CF3\nR5CBVtwhd0eQAZIQZKAVVxbdEWSgFVcW3RFkoBUn5O4IMtCKE3J3BBkgCUEGSEKQgVbcIXdHkIFW\n3CF3R5ABkhBkoBVXFt0RZKAVVxbdEWSgFSfk7ggy0IoTcncEGSAJQQYWtrS0FKPRaOgxTgxBBha2\nvLwsyB1qFeSqqtwfwSm2vb0dGxsbERExnU5jZ2dn4ImOt6VF/2Bd17G7u9vlLMAxUlVV/PLLL/Ht\nt9/Gc889F48fP47pdDr0WMfawkEuiiJWVla6nAU4Zn7++edYX1+Poii8Wu7AwkFeXl6ON998Mz7+\n+ON49OhRnDt3LsryeF5JF0URo9Eodnd349atW3Hr1q148uTJ0GNBetPp1Km4QwsHeWVlJd599914\n4403Yn9//9jGOOKvd4rPnz8fm5ub8d1338Vvv/0myMCRWyjIVVVFWZYxmUxiMpl0PdNgVldX45VX\nXokzZ84MPQpwChXz3PsURbEZEXf6Gyetl+q6vnj4QetxkPU4yHocZD3+3VxBBqA/x/fiF+CEEWSA\nJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGS\nEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhC\nkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlBBkhCkAGSEGSAJAQZIAlB\nBkhCkAGSEGSAJJbm+eWiKOq+Bsni0qVLcfny5SjL/z9Xra+vP6zr+uLh3z0N6/EsdV0Xhx87Desx\nz/64cOFCvba2dpTjpWA9DnrWejSZK8gnXVmW8eGHH8Znn30W58+ff/p4URR3BhyLJObdH2tra3Hz\n5s0jmy8L63HQPP1wZQGQhBNyg6L4x6txeMr+WMz+/n5sb28PPUZqgtygrk/8VSgt2B+LuXfvXnzx\nxRdDj5GaIDdwAmIW+2Mx9+/fj6+//nroMVIT5AZOQMxifyzO2s3mTb0GTkDMYn/QF0Fu4FmcWewP\n+iLIAEkIMkASggyQhCA38KYNs9gf9EWQAZIQZIAkBLmBjzUxi/1BXwQZIAlBBkhCkAGSEGSAJAQZ\nIAlBbuCD/8xif9AXQQZIQpABkhBkgCQEuYFvYjGL/UFfBBkgCUEGSEKQAZIQZIAkBBkgCUFu4JtY\nzGJ/0BdBbuBjTcxif9AXQQZIQpAbeEnKLPYHfRHkBl6SMov9QV8EuYETELPYH/RFkBs4ATGL/UFf\nBLmBExCz2B/0RZAbOAExi/1BXwQZIAlBBkhCkAGSEOQG3rRhFvuDvggyQBKCDJCEIDfwsSZmsT/o\niyADJCHIAEkIMkASggyQhCADJCHIDXzwn1nsD/oiyABJCPLfVFUVVVX5nCkwCEE+ZG9vT5CBQSy1\n/QvK8vg3vaqqiIhYXl6O8Xh8Iv5N9McTNn1pFeRr167FO++8E+PxOHZ3d5+G7bipqir29vZiPB7H\n22+/HcvLy0OPBJxCCwd5NBrF+++/H59++mmsrq7Gzs5OTKfTLmc7MnVdR13XUZZljEajGI1GQ48E\nnEJzB3llZSVeffXVuHHjRrz33nuxuroaERHnzp3rfLgh1XXt402HvPzyy/Haa6/FTz/9NPQocCLN\nHeRLly7FRx99FB988EFcvny5j5lSEON/unr1anzyySdx9+7doUeBE2nud6/G43FcvXr1QIyP690x\n83nhhRfi+vXr3vSEnhTzvGNcFMVmRNzpb5y0Xqrr+uLhB63HQdbjIOtxkPX4d3MFGYD+eO0JkIQg\nAyQhyABJCDJAEoIMkIQgAyQhyABJCDJAEoIMkMSfIigooEGu4hwAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff3ad6a7a90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "optimize_images(conv_id=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Note how these are very simple shapes such as lines and angles. Some of these images may be completely white, which suggests that those features of the neural network are perhaps unused, so the number of features could be reduced in this layer."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Second Convolutional Layer\n",
+    "\n",
+    "This shows the images that maximize the features or neurons in the second convolutional layer, so these are the input images it *likes to see*. Note how these are more complex lines and patterns compared to the first convolutional layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Layer: layer_conv2/convolution\n",
+      "Optimizing image for feature no. 0\n",
+      "Optimizing image for feature no. 1\n",
+      "Optimizing image for feature no. 2\n",
+      "Optimizing image for feature no. 3\n",
+      "Optimizing image for feature no. 4\n",
+      "Optimizing image for feature no. 5\n",
+      "Optimizing image for feature no. 6\n",
+      "Optimizing image for feature no. 7\n",
+      "Optimizing image for feature no. 8\n",
+      "Optimizing image for feature no. 9\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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nIzQ0dNnzL3n58fHxbN++XRjm2traNUVEUVFRZGdns2XLFmw225oFl9ZkkO12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\nQEAOIIAAAnhG8H8ATXk4o6pSZFEAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff3aa99bf60>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "optimize_images(conv_id=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Final output layer\n",
+    "\n",
+    "Now find the image for the 2nd feature of the final output of the neural network. That is, we want to find an image that makes the neural network classify that image as the digit 2. This is the image that the neural network *likes to see the most* for the digit 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iteration: 0\n",
+      "Predicted class: 1, score:  79.35%\n",
+      "Gradient min: -0.564165, max:  0.727934, stepsize:      5.89\n",
+      "Loss: 0.974301\n",
+      "\n",
+      "Iteration: 1\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.570292, max:  0.710277, stepsize:      5.12\n",
+      "Loss: 26.5427\n",
+      "\n",
+      "Iteration: 2\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.409457, max:  0.470393, stepsize:      6.22\n",
+      "Loss: 37.2067\n",
+      "\n",
+      "Iteration: 3\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.496705, max:  0.523132, stepsize:      5.94\n",
+      "Loss: 38.8357\n",
+      "\n",
+      "Iteration: 4\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.408904, max:  0.465926, stepsize:      5.98\n",
+      "Loss: 41.3122\n",
+      "\n",
+      "Iteration: 5\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.476362, max:  0.522812, stepsize:      5.89\n",
+      "Loss: 42.0313\n",
+      "\n",
+      "Iteration: 6\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.398669, max:  0.488273, stepsize:      6.10\n",
+      "Loss: 42.4584\n",
+      "\n",
+      "Iteration: 7\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.470078, max:  0.545729, stepsize:      5.88\n",
+      "Loss: 42.6654\n",
+      "\n",
+      "Iteration: 8\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.470376, max:  0.456324, stepsize:      6.17\n",
+      "Loss: 43.9691\n",
+      "\n",
+      "Iteration: 9\n",
+      "Predicted class: 2, score: 100.00%\n",
+      "Gradient min: -0.471091, max:  0.535464, stepsize:      5.92\n",
+      "Loss: 43.4301\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "image = optimize_image(conv_id=None, feature=2,\n",
+    "                       num_iterations=10, show_progress=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Note how the predicted class indeed becomes 2 already within the first few iterations so the optimization is working as intended. Also note how the loss-measure is increasing rapidly until it apparently converges. This is because the loss-measure is actually just the value of the feature or neuron that we are trying to maximize. Because this is the logits-layer prior to the softmax, these values can potentially be infinitely high, but they are limited because we limit the image-values between 0 and 1.\n",
+    "\n",
+    "Now plot the image that was found. This is the image that the neural network believes looks most like the digit 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO4AAADuCAYAAAA+7jsiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff3ad6eecf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_image(image)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Although some of the curves do hint somewhat at the digit 2, it is hard for a human to see why the neural network believes this is the *optimal* image for the digit 2. This can only be understood when the optimal images for the remaining digits are also shown."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Final fully-connected layer before softmax.\n",
+      "Optimizing image for feature no. 0\n",
+      "Optimizing image for feature no. 1\n",
+      "Optimizing image for feature no. 2\n",
+      "Optimizing image for feature no. 3\n",
+      "Optimizing image for feature no. 4\n",
+      "Optimizing image for feature no. 5\n",
+      "Optimizing image for feature no. 6\n",
+      "Optimizing image for feature no. 7\n",
+      "Optimizing image for feature no. 8\n",
+      "Optimizing image for feature no. 9\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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XsLUnz2q32+l2mnxPkvwiCbVInHGDwYBvvvkGWq0WDAYDVqsVCwsLyMjIeOBE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KxIT0/HD3/4Qzz33HNUCYxgdnYWPT09mJqaglwux8rKCsbHxwO0kO/evYtf/OIXYLPZsFqtAQHh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\n+H+odrS0zIdNqQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff3a1f70c88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "optimize_images(conv_id=None)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "These images may vary each time you run the optimization. Some of the images can be seen to somewhat resemble the hand-written digits. But the other images are often impossible to recognize and it is hard to understand why the neural network thinks these are the *optimal* input images for those digits.\n",
+    "\n",
+    "The reason is perhaps that the neural network tries to recognize all digits simultaneously, and it has found that certain pixels often determine whether the image shows one digit or another. So the neural network has learned to differentiate those pixels that it has found to be important, but not the underlying curves and shapes of the digits, in the same way that a human recognizes the digits.\n",
+    "\n",
+    "Another possibility is that the data-set contains mis-classified digits which may confuse the neural network during training. We have previously seen how some of the digits in the data-set are very hard to read even for humans, and this may cause the neural network to become distorted and trying to recognize strange artifacts in the images.\n",
+    "\n",
+    "Yet another possibility is that the optimization process has stagnated in a local optimum. One way to test this, would be to run the optimization 50 times for the digits that are unclear, and see if some of the resulting images become more clear."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Close TensorFlow Session"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We are now done using TensorFlow, so we close the session to release its resources."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# This has been commented out in case you want to modify and experiment\n",
+    "# with the Notebook without having to restart it.\n",
+    "# session.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to find the input images that maximize certain features inside a neural network. These are the images that the neural network *likes to see the most* in order to activate a certain feature or neuron inside the network.\n",
+    "\n",
+    "This was tested on a simple convolutional neural network using the MNIST data-set. The neural network had clearly learned to recognize the general shape of some of the digits, while it was impossible to see how it recognized other digits."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Plot the images for all features in each convolutional layer instead of just the first 10 features. How many of them appear to be unused or redundant? What happens if you lower the number of features in that layer and train the network again, does it still perform just as well?\n",
+    "\n",
+    "* Try adding more convolutional layers and find the input images that maximize their features. What do the images show? Do you think it is useful to add more convolutional layers than two?\n",
+    "\n",
+    "* Try adding more fully-connected layers and modify the code so it can find input images that maximize the features of the fully-connected / dense layers as well. Currently the code can only maximize the features of the convolutional layers and the final fully-connected layer.\n",
+    "\n",
+    "* For the input images that are unclear, run the optimization e.g. 50 times for each of those digits, to see if it produces more clear input images. It is possible that the optimization has simply become stuck in a local optimum.\n",
+    "\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index f33153f..d940757 100644
--- a/README.md
+++ b/README.md
@@ -47,6 +47,8 @@ Even a few dollars are appreciated. Thanks!
 
 13. Visual Analysis ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
 
+13-B. Visual Analysis (MNIST) ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+
 14. DeepDream ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
 
 15. Style Transfer ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
diff --git a/images/13b_visual_analysis_flowchart.png b/images/13b_visual_analysis_flowchart.png
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+         width="217"
+         id="rect10893"
+         style="opacity:1;fill:none;fill-opacity:1;stroke:#000000;stroke-width:2;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:1" />
+    </g>
+    <path
+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2;stroke-linecap:butt;stroke-linejoin:miter;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:1;marker-end:url(#marker10908)"
+       d="m 15.556349,63.998497 1001.263251,0 0,96.948373"
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+       inkscape:connector-curvature="0"
+       sodipodi:nodetypes="ccc" />
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+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:2;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#marker11950);stroke-miterlimit:4;stroke-dasharray:none"
+       d="m 890.38341,343.38293 0,-84.85282 126.57209,0 0,-50.28484"
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+       sodipodi:nodetypes="cccc" />
+  </g>
+</svg>

From b941b878209cdc8e56fe1f1cace0942cb4145287 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 27 Sep 2017 08:21:12 +0200
Subject: [PATCH 21/61] Typo fix.

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index d940757..1c3c50e 100644
--- a/README.md
+++ b/README.md
@@ -47,7 +47,7 @@ Even a few dollars are appreciated. Thanks!
 
 13. Visual Analysis ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
 
-13-B. Visual Analysis (MNIST) ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+13-B. Visual Analysis for MNIST ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
 
 14. DeepDream ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
 

From 43abc6ceb6ba9d8487b719c8b9ea92e06b4cf5b8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Tue, 3 Oct 2017 11:20:22 +0200
Subject: [PATCH 22/61] Added forks.md

---
 README.md |  4 ++++
 forks.md  | 10 ++++++++++
 2 files changed, 14 insertions(+)
 create mode 100644 forks.md

diff --git a/README.md b/README.md
index 1c3c50e..8eb52d7 100644
--- a/README.md
+++ b/README.md
@@ -67,6 +67,10 @@ These tutorials have been translated to the following languages:
 
 You can help by translating the remaining tutorials or reviewing the ones that have already been translated. You can also help by translating to other languages.
 
+## Forks
+
+See the [selected list of forks](forks.md) for community modifications to these tutorials.
+
 ## Downloading
 
 Some of the Python Notebooks use source-code located in different files to allow for easy re-use
diff --git a/forks.md b/forks.md
new file mode 100644
index 0000000..93f6a3b
--- /dev/null
+++ b/forks.md
@@ -0,0 +1,10 @@
+# TensorFlow Tutorials - Forks
+
+These are forks of the [original TensorFlow Tutorials by Hvass-Labs](https://github.com/Hvass-Labs/TensorFlow-Tutorials).
+They are not developed or even reviewed by the original author, who takes no reponsibility for these forks.
+
+If you have made a fork of the TensorFlow Tutorials with substantial modifications that you feel may be useful to others,
+then please [open a new issue on GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials/issues) with a link and short description.
+
+* [Keras port of some tutorials.](https://github.com/chidochipotle/TensorFlow-Tutorials)
+* [The Inception model as an OpenFaaS function.](https://github.com/Hvass-Labs/TensorFlow-Tutorials)

From dedf34c6333a5e86bcc201d9ba8579845b26666b Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Tue, 3 Oct 2017 11:46:47 +0200
Subject: [PATCH 23/61] Fixed link.

---
 forks.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/forks.md b/forks.md
index 93f6a3b..aa88cf4 100644
--- a/forks.md
+++ b/forks.md
@@ -7,4 +7,4 @@ If you have made a fork of the TensorFlow Tutorials with substantial modificatio
 then please [open a new issue on GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials/issues) with a link and short description.
 
 * [Keras port of some tutorials.](https://github.com/chidochipotle/TensorFlow-Tutorials)
-* [The Inception model as an OpenFaaS function.](https://github.com/Hvass-Labs/TensorFlow-Tutorials)
+* [The Inception model as an OpenFaaS function.](https://github.com/faas-and-furious/inception-function)

From 8523ed45bdf1bad9c4490f5a526a0bd9a2ca77db Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 20 Nov 2017 18:28:26 +0100
Subject: [PATCH 24/61] Added Tutorial 17

---
 17_Estimator_API.ipynb | 1568 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 1568 insertions(+)
 create mode 100644 17_Estimator_API.ipynb

diff --git a/17_Estimator_API.ipynb b/17_Estimator_API.ipynb
new file mode 100644
index 0000000..e26fcbf
--- /dev/null
+++ b/17_Estimator_API.ipynb
@@ -0,0 +1,1568 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #17\n",
+    "# Estimator API\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "High-level API's are extremely important in all software development because they provide simple abstractions for doing very complicated tasks. This makes it easier to write and understand your source-code, and it lowers the risk of errors.\n",
+    "\n",
+    "In Tutorial #03 we saw how to use various builder API's for creating Neural Networks in TensorFlow. However, there was a lot of additional code required for training the models and using them on new data. The Estimator is another high-level API that implements most of this, although it can be debated how simple it really is.\n",
+    "\n",
+    "Using the Estimator API consists of several steps:\n",
+    "\n",
+    "1. Define functions for inputting data to the Estimator.\n",
+    "2. Either use an existing Estimator (e.g. a Deep Neural Network), which is also called a pre-made or Canned Estimator. Or create your own Estimator, in which case you also need to define the optimizer, performance metrics, etc.\n",
+    "3. Train the Estimator using the training-set defined in step 1.\n",
+    "4. Evaluate the performance of the Estimator on the test-set defined in step 1.\n",
+    "5. Use the trained Estimator to make predictions on other data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.4.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.examples.tutorials.mnist import input_data\n",
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t55000\n",
+      "- Test-set:\t\t10000\n",
+      "- Validation-set:\t5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
+    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers so we calculate that now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "data.train.cls = np.argmax(data.train.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This is an example of one-hot encoded labels:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.],\n",
+       "       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.],\n",
+       "       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
+       "       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.],\n",
+       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.]])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.train.labels[0:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "These are the corresponding class-numbers:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([7, 3, 4, 6, 1, 8, 1, 0, 9, 8])"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.train.cls[0:10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Data Dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# We know that MNIST images are 28 pixels in each dimension.\n",
+    "img_size = 28\n",
+    "\n",
+    "# Images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = img_size * img_size\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "img_shape = (img_size, img_size)\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = 1\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None):\n",
+    "    assert len(images) == len(cls_true) == 9\n",
+    "    \n",
+    "    # Create figure with 3x3 sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "    fig.subplots_adjust(hspace=0.3, wspace=0.3)\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Plot image.\n",
+    "        ax.imshow(images[i].reshape(img_shape), cmap='binary')\n",
+    "\n",
+    "        # Show true and predicted classes.\n",
+    "        if cls_pred is None:\n",
+    "            xlabel = \"True: {0}\".format(cls_true[i])\n",
+    "        else:\n",
+    "            xlabel = \"True: {0}, Pred: {1}\".format(cls_true[i], cls_pred[i])\n",
+    "\n",
+    "        # Show the classes as the label on the x-axis.\n",
+    "        ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f00292a1978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the first images from the test-set.\n",
+    "images = data.test.images[0:9]\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = data.test.cls[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Input Functions for the Estimator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Rather than providing raw data directly to the Estimator, we must provide functions that return the data. This allows for more flexibility in data-sources and how the data is randomly shuffled and iterated.\n",
+    "\n",
+    "Note that we will create an Estimator using the `DNNClassifier` which assumes the class-numbers are integers so we use `data.train.cls` instead of `data.train.labels` which are one-hot encoded arrays.\n",
+    "\n",
+    "The function also has parameters for `batch_size`, `queue_capacity` and `num_threads` for finer control of the data reading. In our case we take the data directly from a numpy array in memory, so it is not needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "train_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+    "    x={\"x\": np.array(data.train.images)},\n",
+    "    y=np.array(data.train.cls),\n",
+    "    num_epochs=None,\n",
+    "    shuffle=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This actually returns a function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function tensorflow.python.estimator.inputs.numpy_io.numpy_input_fn.<locals>.input_fn>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_input_fn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Calling this function returns a tuple with TensorFlow ops for returning the input and output data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "({'x': <tf.Tensor 'random_shuffle_queue_DequeueMany:1' shape=(128, 784) dtype=float32>},\n",
+       " <tf.Tensor 'random_shuffle_queue_DequeueMany:2' shape=(128,) dtype=int64>)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_input_fn()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Similarly we need to create a function for reading the data for the test-set. Note that we only want to process these images once so `num_epochs=1` and we do not want the images shuffled so `shuffle=False`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "test_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+    "    x={\"x\": np.array(data.test.images)},\n",
+    "    y=np.array(data.test.cls),\n",
+    "    num_epochs=1,\n",
+    "    shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "An input-function is also needed for predicting the class of new data. As an example we just use a few images from the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "some_images = data.test.images[0:9]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predict_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+    "    x={\"x\": some_images},\n",
+    "    num_epochs=1,\n",
+    "    shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-numbers are actually not used in the input-function as it is not needed for prediction. However, the true class-number is needed when we plot the images further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "some_images_cls = data.test.cls[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Pre-Made / Canned Estimator\n",
+    "\n",
+    "When using a pre-made Estimator, we need to specify the input features for the data. In this case we want to input images from our data-set which are numeric arrays of the given shape."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "feature_x = tf.feature_column.numeric_column(\"x\", shape=img_shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "You can have several input features which would then be combined in a list:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "feature_columns = [feature_x]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "In this example we want to use a 3-layer DNN with 512, 256 and 128 units respectively."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "num_hidden_units = [512, 256, 128]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The `DNNClassifier` then constructs the neural network for us. We can also specify the activation function and various other parameters (see the docs). Here we just specify the number of classes and the directory where the checkpoints will be saved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Using default config.\n",
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-1/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f0028f03198>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = tf.estimator.DNNClassifier(feature_columns=feature_columns,\n",
+    "                                   hidden_units=num_hidden_units,\n",
+    "                                   activation_fn=tf.nn.relu,\n",
+    "                                   n_classes=num_classes,\n",
+    "                                   model_dir=\"./checkpoints_tutorial17-1/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "We can now train the model for a given number of iterations. This automatically loads and saves checkpoints so we can continue the training later.\n",
+    "\n",
+    "Note that the text `INFO:tensorflow:` is printed on every line and makes it harder to quickly read the actual progress. It should have been printed on a single line instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Create CheckpointSaverHook.\n",
+      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial17-1/model.ckpt.\n",
+      "INFO:tensorflow:loss = 300.688, step = 1\n",
+      "INFO:tensorflow:global_step/sec: 370.039\n",
+      "INFO:tensorflow:loss = 26.462, step = 101 (0.271 sec)\n",
+      "INFO:tensorflow:global_step/sec: 521.366\n",
+      "INFO:tensorflow:loss = 22.0528, step = 201 (0.191 sec)\n",
+      "INFO:tensorflow:global_step/sec: 549.886\n",
+      "INFO:tensorflow:loss = 32.07, step = 301 (0.182 sec)\n",
+      "INFO:tensorflow:global_step/sec: 548.856\n",
+      "INFO:tensorflow:loss = 13.8037, step = 401 (0.182 sec)\n",
+      "INFO:tensorflow:global_step/sec: 516.064\n",
+      "INFO:tensorflow:loss = 23.2653, step = 501 (0.194 sec)\n",
+      "INFO:tensorflow:global_step/sec: 552.268\n",
+      "INFO:tensorflow:loss = 17.7141, step = 601 (0.180 sec)\n",
+      "INFO:tensorflow:global_step/sec: 529.426\n",
+      "INFO:tensorflow:loss = 25.7157, step = 701 (0.189 sec)\n",
+      "INFO:tensorflow:global_step/sec: 513.375\n",
+      "INFO:tensorflow:loss = 5.08285, step = 801 (0.195 sec)\n",
+      "INFO:tensorflow:global_step/sec: 536.319\n",
+      "INFO:tensorflow:loss = 10.3937, step = 901 (0.187 sec)\n",
+      "INFO:tensorflow:global_step/sec: 534.847\n",
+      "INFO:tensorflow:loss = 3.12976, step = 1001 (0.187 sec)\n",
+      "INFO:tensorflow:global_step/sec: 540.827\n",
+      "INFO:tensorflow:loss = 5.54126, step = 1101 (0.185 sec)\n",
+      "INFO:tensorflow:global_step/sec: 483.467\n",
+      "INFO:tensorflow:loss = 10.2708, step = 1201 (0.209 sec)\n",
+      "INFO:tensorflow:global_step/sec: 527.042\n",
+      "INFO:tensorflow:loss = 7.62363, step = 1301 (0.187 sec)\n",
+      "INFO:tensorflow:global_step/sec: 557.67\n",
+      "INFO:tensorflow:loss = 2.30585, step = 1401 (0.180 sec)\n",
+      "INFO:tensorflow:global_step/sec: 547.406\n",
+      "INFO:tensorflow:loss = 7.69151, step = 1501 (0.182 sec)\n",
+      "INFO:tensorflow:global_step/sec: 557.682\n",
+      "INFO:tensorflow:loss = 10.7881, step = 1601 (0.179 sec)\n",
+      "INFO:tensorflow:global_step/sec: 547.859\n",
+      "INFO:tensorflow:loss = 7.09411, step = 1701 (0.184 sec)\n",
+      "INFO:tensorflow:global_step/sec: 544.495\n",
+      "INFO:tensorflow:loss = 2.6387, step = 1801 (0.182 sec)\n",
+      "INFO:tensorflow:global_step/sec: 549.648\n",
+      "INFO:tensorflow:loss = 0.772691, step = 1901 (0.182 sec)\n",
+      "INFO:tensorflow:Saving checkpoints for 2000 into ./checkpoints_tutorial17-1/model.ckpt.\n",
+      "INFO:tensorflow:Loss for final step: 7.35222.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.estimator.canned.dnn.DNNClassifier at 0x7f0028f03a90>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.train(input_fn=train_input_fn, steps=2000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Once the model has been trained, we can evaluate its performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Starting evaluation at 2017-11-17-12:07:56\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-1/model.ckpt-2000\n",
+      "INFO:tensorflow:Finished evaluation at 2017-11-17-12:07:56\n",
+      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9727, average_loss = 0.0934177, global_step = 2000, loss = 11.825\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'accuracy': 0.9727,\n",
+       " 'average_loss': 0.093417682,\n",
+       " 'global_step': 2000,\n",
+       " 'loss': 11.825023}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Classification accuracy: 97.27%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Classification accuracy: {0:.2%}\".format(result[\"accuracy\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions\n",
+    "\n",
+    "The trained model can also be used to make predictions on new data.\n",
+    "\n",
+    "Note that the TensorFlow graph is recreated and the checkpoint is reloaded every time we make predictions on new data. If the model is very large then this could add a significant overhead.\n",
+    "\n",
+    "It is unclear why the Estimator is designed this way, possibly because it will always use the latest checkpoint and it can also be distributed easily for use on multiple computers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=predict_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-1/model.ckpt-2000\n"
+     ]
+    }
+   ],
+   "source": [
+    "cls = [p['classes'] for p in predictions]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([7, 2, 1, 0, 4, 1, 4, 9, 5])"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_pred = np.array(cls, dtype='int').squeeze()\n",
+    "cls_pred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaj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\nIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0026103a20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=some_images,\n",
+    "            cls_true=some_images_cls,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# New Estimator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "If you cannot use one of the built-in Estimators, then you can create an arbitrary TensorFlow model yourself. To do this, you first need to create a function which defines the following:\n",
+    "\n",
+    "1. The TensorFlow model, e.g. a Convolutional Neural Network.\n",
+    "2. The output of the model.\n",
+    "3. The loss-function used to improve the model during optimization.\n",
+    "4. The optimization method.\n",
+    "5. Performance metrics.\n",
+    "\n",
+    "The Estimator can be run in three modes: Training, Evaluation, or Prediction. The code is mostly the same, but in Prediction-mode we do not need to setup the loss-function and optimizer.\n",
+    "\n",
+    "This is another aspect of the Estimator API that is poorly designed and resembles how we did ANSI C programming using structs in the old days. It would probably have been more elegant to split this into several functions and sub-classed the Estimator-class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def model_fn(features, labels, mode, params):\n",
+    "    # Args:\n",
+    "    #\n",
+    "    # features: This is the x-arg from the input_fn.\n",
+    "    # labels:   This is the y-arg from the input_fn,\n",
+    "    #           see e.g. train_input_fn for these two.\n",
+    "    # mode:     Either TRAIN, EVAL, or PREDICT\n",
+    "    # params:   User-defined hyper-parameters, e.g. learning-rate.\n",
+    "    \n",
+    "    # Reference to the tensor named \"x\" in the input-function.\n",
+    "    x = features[\"x\"]\n",
+    "\n",
+    "    # The convolutional layers expect 4-rank tensors\n",
+    "    # but x is a 2-rank tensor, so reshape it.\n",
+    "    net = tf.reshape(x, [-1, img_size, img_size, num_channels])    \n",
+    "\n",
+    "    # First convolutional layer.\n",
+    "    net = tf.layers.conv2d(inputs=net, name='layer_conv1',\n",
+    "                           filters=16, kernel_size=5,\n",
+    "                           padding='same', activation=tf.nn.relu)\n",
+    "    net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)\n",
+    "\n",
+    "    # Second convolutional layer.\n",
+    "    net = tf.layers.conv2d(inputs=net, name='layer_conv2',\n",
+    "                           filters=36, kernel_size=5,\n",
+    "                           padding='same', activation=tf.nn.relu)\n",
+    "    net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)    \n",
+    "\n",
+    "    # Flatten to a 2-rank tensor.\n",
+    "    net = tf.contrib.layers.flatten(net)\n",
+    "    # Eventually this should be replaced with:\n",
+    "    # net = tf.layers.flatten(net)\n",
+    "\n",
+    "    # First fully-connected / dense layer.\n",
+    "    # This uses the ReLU activation function.\n",
+    "    net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
+    "                          units=128, activation=tf.nn.relu)    \n",
+    "\n",
+    "    # Second fully-connected / dense layer.\n",
+    "    # This is the last layer so it does not use an activation function.\n",
+    "    net = tf.layers.dense(inputs=net, name='layer_fc2',\n",
+    "                          units=10)\n",
+    "\n",
+    "    # Logits output of the neural network.\n",
+    "    logits = net\n",
+    "\n",
+    "    # Softmax output of the neural network.\n",
+    "    y_pred = tf.nn.softmax(logits=logits)\n",
+    "    \n",
+    "    # Classification output of the neural network.\n",
+    "    y_pred_cls = tf.argmax(y_pred, axis=1)\n",
+    "\n",
+    "    if mode == tf.estimator.ModeKeys.PREDICT:\n",
+    "        # If the estimator is supposed to be in prediction-mode\n",
+    "        # then use the predicted class-number that is output by\n",
+    "        # the neural network. Optimization etc. is not needed.\n",
+    "        spec = tf.estimator.EstimatorSpec(mode=mode,\n",
+    "                                          predictions=y_pred_cls)\n",
+    "    else:\n",
+    "        # Otherwise the estimator is supposed to be in either\n",
+    "        # training or evaluation-mode. Note that the loss-function\n",
+    "        # is also required in Evaluation mode.\n",
+    "        \n",
+    "        # Define the loss-function to be optimized, by first\n",
+    "        # calculating the cross-entropy between the output of\n",
+    "        # the neural network and the true labels for the input data.\n",
+    "        # This gives the cross-entropy for each image in the batch.\n",
+    "        cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=labels,\n",
+    "                                                                       logits=logits)\n",
+    "\n",
+    "        # Reduce the cross-entropy batch-tensor to a single number\n",
+    "        # which can be used in optimization of the neural network.\n",
+    "        loss = tf.reduce_mean(cross_entropy)\n",
+    "\n",
+    "        # Define the optimizer for improving the neural network.\n",
+    "        optimizer = tf.train.AdamOptimizer(learning_rate=params[\"learning_rate\"])\n",
+    "\n",
+    "        # Get the TensorFlow op for doing a single optimization step.\n",
+    "        train_op = optimizer.minimize(\n",
+    "            loss=loss, global_step=tf.train.get_global_step())\n",
+    "\n",
+    "        # Define the evaluation metrics,\n",
+    "        # in this case the classification accuracy.\n",
+    "        metrics = \\\n",
+    "        {\n",
+    "            \"accuracy\": tf.metrics.accuracy(labels, y_pred_cls)\n",
+    "        }\n",
+    "\n",
+    "        # Wrap all of this in an EstimatorSpec.\n",
+    "        spec = tf.estimator.EstimatorSpec(\n",
+    "            mode=mode,\n",
+    "            loss=loss,\n",
+    "            train_op=train_op,\n",
+    "            eval_metric_ops=metrics)\n",
+    "        \n",
+    "    return spec"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Create an Instance of the Estimator\n",
+    "\n",
+    "We can specify hyper-parameters e.g. for the learning-rate of the optimizer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "params = {\"learning_rate\": 1e-4}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then create an instance of the new Estimator.\n",
+    "\n",
+    "Note that we don't provide feature-columns here as it is inferred automatically from the data-functions when `model_fn()` is called.\n",
+    "\n",
+    "It is unclear from the TensorFlow documentation why it is necessary to specify the feature-columns when using `DNNClassifier` in the example above, when it is not needed here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Using default config.\n",
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-2/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f00290fac88>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = tf.estimator.Estimator(model_fn=model_fn,\n",
+    "                               params=params,\n",
+    "                               model_dir=\"./checkpoints_tutorial17-2/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "Now that our new Estimator has been created, we can train it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Create CheckpointSaverHook.\n",
+      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial17-2/model.ckpt.\n",
+      "INFO:tensorflow:loss = 2.33444, step = 1\n",
+      "INFO:tensorflow:global_step/sec: 190.454\n",
+      "INFO:tensorflow:loss = 0.810317, step = 101 (0.527 sec)\n",
+      "INFO:tensorflow:global_step/sec: 198.129\n",
+      "INFO:tensorflow:loss = 0.349305, step = 201 (0.504 sec)\n",
+      "INFO:tensorflow:global_step/sec: 184.116\n",
+      "INFO:tensorflow:loss = 0.288062, step = 301 (0.543 sec)\n",
+      "INFO:tensorflow:global_step/sec: 195.138\n",
+      "INFO:tensorflow:loss = 0.0948148, step = 401 (0.512 sec)\n",
+      "INFO:tensorflow:global_step/sec: 199.116\n",
+      "INFO:tensorflow:loss = 0.203272, step = 501 (0.502 sec)\n",
+      "INFO:tensorflow:global_step/sec: 190.777\n",
+      "INFO:tensorflow:loss = 0.22347, step = 601 (0.524 sec)\n",
+      "INFO:tensorflow:global_step/sec: 198.669\n",
+      "INFO:tensorflow:loss = 0.161297, step = 701 (0.505 sec)\n",
+      "INFO:tensorflow:global_step/sec: 192.277\n",
+      "INFO:tensorflow:loss = 0.154663, step = 801 (0.518 sec)\n",
+      "INFO:tensorflow:global_step/sec: 158.865\n",
+      "INFO:tensorflow:loss = 0.136487, step = 901 (0.634 sec)\n",
+      "INFO:tensorflow:global_step/sec: 121.05\n",
+      "INFO:tensorflow:loss = 0.144933, step = 1001 (0.826 sec)\n",
+      "INFO:tensorflow:global_step/sec: 118.257\n",
+      "INFO:tensorflow:loss = 0.103951, step = 1101 (0.848 sec)\n",
+      "INFO:tensorflow:global_step/sec: 118.136\n",
+      "INFO:tensorflow:loss = 0.133236, step = 1201 (0.845 sec)\n",
+      "INFO:tensorflow:global_step/sec: 112.046\n",
+      "INFO:tensorflow:loss = 0.060983, step = 1301 (0.896 sec)\n",
+      "INFO:tensorflow:global_step/sec: 99.9212\n",
+      "INFO:tensorflow:loss = 0.0838628, step = 1401 (0.997 sec)\n",
+      "INFO:tensorflow:global_step/sec: 115.121\n",
+      "INFO:tensorflow:loss = 0.118691, step = 1501 (0.868 sec)\n",
+      "INFO:tensorflow:global_step/sec: 96.8269\n",
+      "INFO:tensorflow:loss = 0.179758, step = 1601 (1.038 sec)\n",
+      "INFO:tensorflow:global_step/sec: 99.8103\n",
+      "INFO:tensorflow:loss = 0.0996531, step = 1701 (0.998 sec)\n",
+      "INFO:tensorflow:global_step/sec: 128.677\n",
+      "INFO:tensorflow:loss = 0.097964, step = 1801 (0.775 sec)\n",
+      "INFO:tensorflow:global_step/sec: 124.224\n",
+      "INFO:tensorflow:loss = 0.086759, step = 1901 (0.806 sec)\n",
+      "INFO:tensorflow:Saving checkpoints for 2000 into ./checkpoints_tutorial17-2/model.ckpt.\n",
+      "INFO:tensorflow:Loss for final step: 0.0712585.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.estimator.estimator.Estimator at 0x7f0026148f98>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.train(input_fn=train_input_fn, steps=2000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Once the model has been trained, we can evaluate its performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Starting evaluation at 2017-11-17-12:08:18\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-2/model.ckpt-2000\n",
+      "INFO:tensorflow:Finished evaluation at 2017-11-17-12:08:18\n",
+      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9761, global_step = 2000, loss = 0.0760049\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'accuracy': 0.97610003, 'global_step': 2000, 'loss': 0.076004863}"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Classification accuracy: 97.61%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Classification accuracy: {0:.2%}\".format(result[\"accuracy\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions\n",
+    "\n",
+    "The model can also be used to make predictions on new data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=predict_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-2/model.ckpt-2000\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([7, 2, 1, 0, 4, 1, 4, 9, 5])"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_pred = np.array(list(predictions))\n",
+    "cls_pred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaj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\nIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0026645d68>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=some_images,\n",
+    "            cls_true=some_images_cls,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use the Estimator API in TensorFlow. It is supposed to make it easier to train and use a model, but it seems to have several design problems:\n",
+    "\n",
+    "* The Estimator API is complicated, inconsistent and confusing.\n",
+    "* Error-messages are extremely long and often impossible to understand.\n",
+    "* The TensorFlow graph is recreated and the checkpoint is reloaded EVERY time you want to use a trained model to make a prediction on new data. Some models are very big so this could add a very large overhead. A better way might be to only reload the model if the checkpoint has changed on disk.\n",
+    "* It is unclear how to gain access to the trained model, e.g. to plot the weights of a neural network.\n",
+    "\n",
+    "It seems that the Estimator API could have been much simpler and easier to use. For small projects you may find it too complicated and confusing to be worth the effort. But it is possible that the Estimator API is useful if you have a very large dataset and if you train on many machines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Run another 10000 training iterations for each model.\n",
+    "* Print classification accuracy on the test-set before optimization and after 1000, 2000 and 10000 iterations.\n",
+    "* Change the structure of the neural network inside the Estimator. Do you have to delete the checkpoint-files? Why?\n",
+    "* Change the batch-size for the input-functions.\n",
+    "* In many of the previous tutorials we plotted examples of mis-classified images. Do that here as well.\n",
+    "* Change the Estimator to use one-hot encoded labels instead of integer class-numbers.\n",
+    "* Change the input-functions to load image-files instead of using numpy-arrays.\n",
+    "* Can you find a way to plot the weights of the neural network and the output of the individual layers?\n",
+    "* List 5 things you like and don't like about the Estimator API. Do you have any suggestions for improvements? Maybe you should suggest them to the developers?\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

From b9788e51c98c64d6c9b4cedfa93f123ce303b8e0 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 20 Nov 2017 18:30:36 +0100
Subject: [PATCH 25/61] Added Tutorial 17

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 8eb52d7..9346d7a 100644
--- a/README.md
+++ b/README.md
@@ -55,6 +55,8 @@ Even a few dollars are appreciated. Thanks!
 
 16. Reinforcement Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
 
+17. Estimator API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).

From fb1f30357cae6823e6cf170da6f0dabef67cbaa8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 25 Nov 2017 16:48:48 +0100
Subject: [PATCH 26/61] Added Tutorial 18

---
 18_TFRecords_Dataset_API.ipynb | 2274 ++++++++++++++++++++++++++++++++
 1 file changed, 2274 insertions(+)
 create mode 100644 18_TFRecords_Dataset_API.ipynb

diff --git a/18_TFRecords_Dataset_API.ipynb b/18_TFRecords_Dataset_API.ipynb
new file mode 100644
index 0000000..c3c6b91
--- /dev/null
+++ b/18_TFRecords_Dataset_API.ipynb
@@ -0,0 +1,2274 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #18\n",
+    "# TFRecords & Dataset API\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "In the previous tutorials we used a so-called feed-dict for inputting data to the TensorFlow graph. It is a fairly simple input method but it is also a performance bottleneck because the data is read sequentially between training steps. This makes it hard to use the GPU at 100% efficiency because the GPU has to wait for new data to work on.\n",
+    "\n",
+    "Instead we want to read data in a parallel thread so new training data is always available whenever the GPU is ready. This used to be done with so-called QueueRunners in TensorFlow which was a very complicated system. Now it can be done with the Dataset API and a binary file-format called TFRecords, as described in this tutorial.\n",
+    "\n",
+    "This builds on Tutorial #17 for the Estimator API."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.image import imread\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import sys\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.4.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "import knifey"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The data dimensions have already been defined in the `knifey` module, so we just need to import the ones we need."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from knifey import img_size, img_size_flat, img_shape, num_classes, num_channels"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Set the directory for storing the data-set on your computer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# knifey.data_dir = \"data/knifey-spoony/\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The Knifey-Spoony data-set is about 22 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "knifey.maybe_download_and_extract()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Now load the data-set. This scans the sub-directories for all `*.jpg` images and puts the filenames into two lists for the training-set and test-set. This does not actually load the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Creating dataset from the files in: data/knifey-spoony/\n",
+      "- Data loaded from cache-file: data/knifey-spoony/knifey-spoony.pkl\n"
+     ]
+    }
+   ],
+   "source": [
+    "dataset = knifey.load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the class-names."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['forky', 'knifey', 'spoony']"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "class_names = dataset.class_names\n",
+    "class_names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training and Test-Sets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This function returns the file-paths for the images, the class-numbers as integers, and the class-numbers as One-Hot encoded arrays called labels.\n",
+    "\n",
+    "In this tutorial we will actually use the integer class-numbers and call them labels. This may be a little confusing but you can always add print-statements to see what the data actually is."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "image_paths_train, cls_train, labels_train = dataset.get_training_set()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Print the first image-path to see if it looks OK."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/home/magnus/development/TensorFlow-Tutorials/data/knifey-spoony/forky/forky-05-0023.jpg'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "image_paths_train[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "image_paths_test, cls_test, labels_test = dataset.get_test_set()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Print the first image-path to see if it looks OK."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/home/magnus/development/TensorFlow-Tutorials/data/knifey-spoony/forky/test/forky-test-01-0163.jpg'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "image_paths_test[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The Knifey-Spoony data-set has now been loaded and consists of 4700 images and associated labels (i.e. classifications of the images). The data-set is split into 2 mutually exclusive sub-sets, the training-set and the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t4170\n",
+      "- Test-set:\t\t530\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(image_paths_train)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(image_paths_test)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None, smooth=True):\n",
+    "\n",
+    "    assert len(images) == len(cls_true)\n",
+    "\n",
+    "    # Create figure with sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "\n",
+    "    # Adjust vertical spacing.\n",
+    "    if cls_pred is None:\n",
+    "        hspace = 0.3\n",
+    "    else:\n",
+    "        hspace = 0.6\n",
+    "    fig.subplots_adjust(hspace=hspace, wspace=0.3)\n",
+    "\n",
+    "    # Interpolation type.\n",
+    "    if smooth:\n",
+    "        interpolation = 'spline16'\n",
+    "    else:\n",
+    "        interpolation = 'nearest'\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # There may be less than 9 images, ensure it doesn't crash.\n",
+    "        if i < len(images):\n",
+    "            # Plot image.\n",
+    "            ax.imshow(images[i],\n",
+    "                      interpolation=interpolation)\n",
+    "\n",
+    "            # Name of the true class.\n",
+    "            cls_true_name = class_names[cls_true[i]]\n",
+    "\n",
+    "            # Show true and predicted classes.\n",
+    "            if cls_pred is None:\n",
+    "                xlabel = \"True: {0}\".format(cls_true_name)\n",
+    "            else:\n",
+    "                # Name of the predicted class.\n",
+    "                cls_pred_name = class_names[cls_pred[i]]\n",
+    "\n",
+    "                xlabel = \"True: {0}\\nPred: {1}\".format(cls_true_name,\n",
+    "                                                       cls_pred_name)\n",
+    "\n",
+    "            # Show the classes as the label on the x-axis.\n",
+    "            ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for loading images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This dataset does not load the actual images, instead it has a list of the images in the training-set and another list for the images in the test-set. This helper-function loads some image-files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def load_images(image_paths):\n",
+    "    # Load the images from disk.\n",
+    "    images = [imread(path) for path in image_paths]\n",
+    "\n",
+    "    # Convert to a numpy array and return it.\n",
+    "    return np.asarray(images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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I2agQT1JqahM5g5PHu8w6fSpGDt/Is7m8yh3X+xtX+9kiyzJGoxFxHLG4uEg+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\nkkuAy8nwkksuuQSA/xeciVsSrGqkOwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fe813303c88>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load the first images from the test-set.\n",
+    "images = load_images(image_paths=image_paths_test[0:9])\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = cls_test[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true, smooth=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Create TFRecords"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "TFRecords is the binary file-format used internally in TensorFlow which allows for high-performance reading and processing of datasets.\n",
+    "\n",
+    "For this small dataset we will just create one TFRecords file for the training-set and another for the test-set. But if your dataset is very large then you can split it into several TFRecords files called shards. This will also improve the random shuffling, because the Dataset API only shuffles from a smaller buffer of e.g. 1024 elements loaded into RAM. So if you have e.g. 100 TFRecords files, then the randomization will be much better than for a single TFRecords file."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "File-path for the TFRecords file holding the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'data/knifey-spoony/train.tfrecords'"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_tfrecords_train = os.path.join(knifey.data_dir, \"train.tfrecords\")\n",
+    "path_tfrecords_train"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "File-path for the TFRecords file holding the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'data/knifey-spoony/test.tfrecords'"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_tfrecords_test = os.path.join(knifey.data_dir, \"test.tfrecords\")\n",
+    "path_tfrecords_test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Helper-function for printing the conversion progress."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def print_progress(count, total):\n",
+    "    # Percentage completion.\n",
+    "    pct_complete = float(count) / total\n",
+    "\n",
+    "    # Status-message.\n",
+    "    # Note the \\r which means the line should overwrite itself.\n",
+    "    msg = \"\\r- Progress: {0:.1%}\".format(pct_complete)\n",
+    "\n",
+    "    # Print it.\n",
+    "    sys.stdout.write(msg)\n",
+    "    sys.stdout.flush()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Helper-function for wrapping an integer so it can be saved to the TFRecords file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def wrap_int64(value):\n",
+    "    return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Helper-function for wrapping raw bytes so they can be saved to the TFRecords file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def wrap_bytes(value):\n",
+    "    return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This is the function for reading images from disk and writing them along with the class-labels to a TFRecords file. This loads and decodes the images to numpy-arrays and then stores the raw bytes in the TFRecords file. If the original image-files are compressed e.g. as jpeg-files, then the TFRecords file may be many times larger than the original image-files.\n",
+    "\n",
+    "It is also possible to save the compressed image files directly in the TFRecords file because it can hold any raw bytes. We would then have to decode the compressed images when the TFRecords file is being read later in the `parse()` function below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def convert(image_paths, labels, out_path):\n",
+    "    # Args:\n",
+    "    # image_paths   List of file-paths for the images.\n",
+    "    # labels        Class-labels for the images.\n",
+    "    # out_path      File-path for the TFRecords output file.\n",
+    "    \n",
+    "    print(\"Converting: \" + out_path)\n",
+    "    \n",
+    "    # Number of images. Used when printing the progress.\n",
+    "    num_images = len(image_paths)\n",
+    "    \n",
+    "    # Open a TFRecordWriter for the output-file.\n",
+    "    with tf.python_io.TFRecordWriter(out_path) as writer:\n",
+    "        \n",
+    "        # Iterate over all the image-paths and class-labels.\n",
+    "        for i, (path, label) in enumerate(zip(image_paths, labels)):\n",
+    "            # Print the percentage-progress.\n",
+    "            print_progress(count=i, total=num_images-1)\n",
+    "\n",
+    "            # Load the image-file using matplotlib's imread function.\n",
+    "            img = imread(path)\n",
+    "            \n",
+    "            # Convert the image to raw bytes.\n",
+    "            img_bytes = img.tostring()\n",
+    "\n",
+    "            # Create a dict with the data we want to save in the\n",
+    "            # TFRecords file. You can add more relevant data here.\n",
+    "            data = \\\n",
+    "                {\n",
+    "                    'image': wrap_bytes(img_bytes),\n",
+    "                    'label': wrap_int64(label)\n",
+    "                }\n",
+    "\n",
+    "            # Wrap the data as TensorFlow Features.\n",
+    "            feature = tf.train.Features(feature=data)\n",
+    "\n",
+    "            # Wrap again as a TensorFlow Example.\n",
+    "            example = tf.train.Example(features=feature)\n",
+    "\n",
+    "            # Serialize the data.\n",
+    "            serialized = example.SerializeToString()\n",
+    "            \n",
+    "            # Write the serialized data to the TFRecords file.\n",
+    "            writer.write(serialized)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Note the 4 function calls required to write the data-dict to the TFRecords file. In the original code-example from the Google Developers, these 4 function calls were actually nested. The design-philosophy for TensorFlow generally seems to be: If one function call is good, then 4 function calls are 4 times as good, and if they are nested then it is exponential goodness!\n",
+    "\n",
+    "Of course, this is quite poor API design because the last function `writer.write()` should just be able to take the data-dict directly and then call the 3 other functions internally.\n",
+    "\n",
+    "Convert the training-set to a TFRecords-file. Note how we use the integer class-numbers as the labels instead of the One-Hot encoded arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Converting: data/knifey-spoony/train.tfrecords\n",
+      "- Progress: 100.0%"
+     ]
+    }
+   ],
+   "source": [
+    "convert(image_paths=image_paths_train,\n",
+    "        labels=cls_train,\n",
+    "        out_path=path_tfrecords_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Convert the test-set to a TFRecords-file:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Converting: data/knifey-spoony/test.tfrecords\n",
+      "- Progress: 100.0%"
+     ]
+    }
+   ],
+   "source": [
+    "convert(image_paths=image_paths_test,\n",
+    "        labels=cls_test,\n",
+    "        out_path=path_tfrecords_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Input Functions for the Estimator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The TFRecords files contain the data in a serialized binary format which needs to be converted back to images and labels of the correct data-type. We use a helper-function for this parsing:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def parse(serialized):\n",
+    "    # Define a dict with the data-names and types we expect to\n",
+    "    # find in the TFRecords file.\n",
+    "    # It is a bit awkward that this needs to be specified again,\n",
+    "    # because it could have been written in the header of the\n",
+    "    # TFRecords file instead.\n",
+    "    features = \\\n",
+    "        {\n",
+    "            'image': tf.FixedLenFeature([], tf.string),\n",
+    "            'label': tf.FixedLenFeature([], tf.int64)\n",
+    "        }\n",
+    "\n",
+    "    # Parse the serialized data so we get a dict with our data.\n",
+    "    parsed_example = tf.parse_single_example(serialized=serialized,\n",
+    "                                             features=features)\n",
+    "\n",
+    "    # Get the image as raw bytes.\n",
+    "    image_raw = parsed_example['image']\n",
+    "\n",
+    "    # Decode the raw bytes so it becomes a tensor with type.\n",
+    "    image = tf.decode_raw(image_raw, tf.uint8)\n",
+    "    \n",
+    "    # The type is now uint8 but we need it to be float.\n",
+    "    image = tf.cast(image, tf.float32)\n",
+    "\n",
+    "    # Get the label associated with the image.\n",
+    "    label = parsed_example['label']\n",
+    "\n",
+    "    # The image and label are now correct TensorFlow types.\n",
+    "    return image, label"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Helper-function for creating an input-function that reads from TFRecords files for use with the Estimator API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def input_fn(filenames, train, batch_size=32, buffer_size=2048):\n",
+    "    # Args:\n",
+    "    # filenames:   Filenames for the TFRecords files.\n",
+    "    # train:       Boolean whether training (True) or testing (False).\n",
+    "    # batch_size:  Return batches of this size.\n",
+    "    # buffer_size: Read buffers of this size. The random shuffling\n",
+    "    #              is done on the buffer, so it must be big enough.\n",
+    "\n",
+    "    # Create a TensorFlow Dataset-object which has functionality\n",
+    "    # for reading and shuffling data from TFRecords files.\n",
+    "    dataset = tf.data.TFRecordDataset(filenames=filenames)\n",
+    "\n",
+    "    # Parse the serialized data in the TFRecords files.\n",
+    "    # This returns TensorFlow tensors for the image and labels.\n",
+    "    dataset = dataset.map(parse)\n",
+    "\n",
+    "    if train:\n",
+    "        # If training then read a buffer of the given size and\n",
+    "        # randomly shuffle it.\n",
+    "        dataset = dataset.shuffle(buffer_size=buffer_size)\n",
+    "\n",
+    "        # Allow infinite reading of the data.\n",
+    "        num_repeat = None\n",
+    "    else:\n",
+    "        # If testing then don't shuffle the data.\n",
+    "        \n",
+    "        # Only go through the data once.\n",
+    "        num_repeat = 1\n",
+    "\n",
+    "    # Repeat the dataset the given number of times.\n",
+    "    dataset = dataset.repeat(num_repeat)\n",
+    "    \n",
+    "    # Get a batch of data with the given size.\n",
+    "    dataset = dataset.batch(batch_size)\n",
+    "\n",
+    "    # Create an iterator for the dataset and the above modifications.\n",
+    "    iterator = dataset.make_one_shot_iterator()\n",
+    "\n",
+    "    # Get the next batch of images and labels.\n",
+    "    images_batch, labels_batch = iterator.get_next()\n",
+    "\n",
+    "    # The input-function must return a dict wrapping the images.\n",
+    "    x = {'image': images_batch}\n",
+    "    y = labels_batch\n",
+    "\n",
+    "    return x, y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This is the input-function for the training-set for use with the Estimator API:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def train_input_fn():\n",
+    "    return input_fn(filenames=path_tfrecords_train, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This is the input-function for the test-set for use with the Estimator API:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def test_input_fn():\n",
+    "    return input_fn(filenames=path_tfrecords_test, train=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Input Function for Predicting on New Images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "An input-function is also needed for predicting the class of new data. As an example we just use a few images from the test-set.\n",
+    "\n",
+    "You could load any images you want here. Make sure they are the same dimensions as expected by the TensorFlow model, otherwise you need to resize the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "some_images = load_images(image_paths=image_paths_test[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These images are now stored as numpy arrays in memory, so we can use the standard input-function for the Estimator API. Note that the images are loaded as uint8 data but it must be input to the TensorFlow graph as floats so we do a type-cast."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predict_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+    "    x={\"image\": some_images.astype(np.float32)},\n",
+    "    num_epochs=1,\n",
+    "    shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-numbers are actually not used in the input-function as it is not needed for prediction. However, the true class-number is needed when we plot the images further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "some_images_cls = cls_test[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Pre-Made / Canned Estimator\n",
+    "\n",
+    "When using a pre-made Estimator, we need to specify the input features for the data. In this case we want to input images from our data-set which are numeric arrays of the given shape."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "feature_image = tf.feature_column.numeric_column(\"image\",\n",
+    "                                                 shape=img_shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "You can have several input features which would then be combined in a list:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "feature_columns = [feature_image]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "In this example we want to use a 3-layer DNN with 512, 256 and 128 units respectively."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "num_hidden_units = [512, 256, 128]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The `DNNClassifier` then constructs the neural network for us. We can also specify the activation function and various other parameters (see the docs). Here we just specify the number of classes and the directory where the checkpoints will be saved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Using default config.\n",
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial18-1/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fe810e90940>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = tf.estimator.DNNClassifier(feature_columns=feature_columns,\n",
+    "                                   hidden_units=num_hidden_units,\n",
+    "                                   activation_fn=tf.nn.relu,\n",
+    "                                   n_classes=num_classes,\n",
+    "                                   model_dir=\"./checkpoints_tutorial18-1/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "We can now train the model for a given number of iterations. This automatically loads and saves checkpoints so we can continue the training later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Create CheckpointSaverHook.\n",
+      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial18-1/model.ckpt.\n",
+      "INFO:tensorflow:loss = 943.377, step = 1\n",
+      "INFO:tensorflow:global_step/sec: 21.6937\n",
+      "INFO:tensorflow:loss = 31.8647, step = 101 (4.614 sec)\n",
+      "INFO:tensorflow:Saving checkpoints for 200 into ./checkpoints_tutorial18-1/model.ckpt.\n",
+      "INFO:tensorflow:Loss for final step: 31.5808.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.estimator.canned.dnn.DNNClassifier at 0x7fe810e179e8>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.train(input_fn=train_input_fn, steps=200)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Once the model has been trained, we can evaluate its performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Starting evaluation at 2017-11-25-09:31:37\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-1/model.ckpt-200\n",
+      "INFO:tensorflow:Finished evaluation at 2017-11-25-09:31:38\n",
+      "INFO:tensorflow:Saving dict for global step 200: accuracy = 0.456604, average_loss = 1.07088, global_step = 200, loss = 33.3863\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'accuracy': 0.45660377,\n",
+       " 'average_loss': 1.0708818,\n",
+       " 'global_step': 200,\n",
+       " 'loss': 33.386318}"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Classification accuracy: 45.66%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Classification accuracy: {0:.2%}\".format(result[\"accuracy\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions\n",
+    "\n",
+    "The trained model can also be used to make predictions on new data.\n",
+    "\n",
+    "Note that the TensorFlow graph is recreated and the checkpoint is reloaded every time we make predictions on new data. If the model is very large then this could add a significant overhead.\n",
+    "\n",
+    "It is unclear why the Estimator is designed this way, possibly because it will always use the latest checkpoint and it can also be distributed easily for use on multiple computers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=predict_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-1/model.ckpt-200\n"
+     ]
+    }
+   ],
+   "source": [
+    "cls = [p['classes'] for p in predictions]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([2, 2, 2, 2, 2, 2, 2, 2, 2])"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_pred = np.array(cls, dtype='int').squeeze()\n",
+    "cls_pred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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8YhNFMDX6oYtLwmgyoVLLGAwGjMcT7LxNmBYYjcfU6zV6URtcD9eREFKD4tQCR70Dpi8t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\nyDJuAMeMGfOR5f8HwXVtFSwXLVgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fe80adc0630>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=some_images,\n",
+    "            cls_true=some_images_cls,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions for the Entire Test-Set"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "It appears that the model maybe classifies all images as 'spoony'. So let us see the predictions for the entire test-set. We can do this simply by using its input-function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:Input graph does not contain a QueueRunner. That means predict yields forever. This is probably a mistake.\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-1/model.ckpt-200\n"
+     ]
+    }
+   ],
+   "source": [
+    "cls = [p['classes'] for p in predictions]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_pred = np.array(cls, dtype='int').squeeze()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The test-set contains 530 images in total and they have all been predicted as class 2 (spoony). So this model does not work at all for classifying the Knifey-Spoony dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "530"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cls_pred == 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# New Estimator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "If you cannot use one of the built-in Estimators, then you can create an arbitrary TensorFlow model yourself. To do this, you first need to create a function which defines the following:\n",
+    "\n",
+    "1. The TensorFlow model, e.g. a Convolutional Neural Network.\n",
+    "2. The output of the model.\n",
+    "3. The loss-function used to improve the model during optimization.\n",
+    "4. The optimization method.\n",
+    "5. Performance metrics.\n",
+    "\n",
+    "The Estimator can be run in three modes: Training, Evaluation, or Prediction. The code is mostly the same, but in Prediction-mode we do not need to setup the loss-function and optimizer.\n",
+    "\n",
+    "This is another aspect of the Estimator API that is poorly designed and resembles how we did ANSI C programming using structs in the old days. It would probably have been more elegant to split this into several functions and sub-classed the Estimator-class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def model_fn(features, labels, mode, params):\n",
+    "    # Args:\n",
+    "    #\n",
+    "    # features: This is the x-arg from the input_fn.\n",
+    "    # labels:   This is the y-arg from the input_fn.\n",
+    "    # mode:     Either TRAIN, EVAL, or PREDICT\n",
+    "    # params:   User-defined hyper-parameters, e.g. learning-rate.\n",
+    "    \n",
+    "    # Reference to the tensor named \"image\" in the input-function.\n",
+    "    x = features[\"image\"]\n",
+    "\n",
+    "    # The convolutional layers expect 4-rank tensors\n",
+    "    # but x is a 2-rank tensor, so reshape it.\n",
+    "    net = tf.reshape(x, [-1, img_size, img_size, num_channels])    \n",
+    "\n",
+    "    # First convolutional layer.\n",
+    "    net = tf.layers.conv2d(inputs=net, name='layer_conv1',\n",
+    "                           filters=32, kernel_size=3,\n",
+    "                           padding='same', activation=tf.nn.relu)\n",
+    "    net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)\n",
+    "\n",
+    "    # Second convolutional layer.\n",
+    "    net = tf.layers.conv2d(inputs=net, name='layer_conv2',\n",
+    "                           filters=32, kernel_size=3,\n",
+    "                           padding='same', activation=tf.nn.relu)\n",
+    "    net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)    \n",
+    "\n",
+    "    # Flatten to a 2-rank tensor.\n",
+    "    net = tf.contrib.layers.flatten(net)\n",
+    "    # Eventually this should be replaced with:\n",
+    "    # net = tf.layers.flatten(net)\n",
+    "\n",
+    "    # First fully-connected / dense layer.\n",
+    "    # This uses the ReLU activation function.\n",
+    "    net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
+    "                          units=128, activation=tf.nn.relu)    \n",
+    "\n",
+    "    # Second fully-connected / dense layer.\n",
+    "    # This is the last layer so it does not use an activation function.\n",
+    "    net = tf.layers.dense(inputs=net, name='layer_fc_2',\n",
+    "                          units=num_classes)\n",
+    "\n",
+    "    # Logits output of the neural network.\n",
+    "    logits = net\n",
+    "\n",
+    "    # Softmax output of the neural network.\n",
+    "    y_pred = tf.nn.softmax(logits=logits)\n",
+    "    \n",
+    "    # Classification output of the neural network.\n",
+    "    y_pred_cls = tf.argmax(y_pred, axis=1)\n",
+    "\n",
+    "    if mode == tf.estimator.ModeKeys.PREDICT:\n",
+    "        # If the estimator is supposed to be in prediction-mode\n",
+    "        # then use the predicted class-number that is output by\n",
+    "        # the neural network. Optimization etc. is not needed.\n",
+    "        spec = tf.estimator.EstimatorSpec(mode=mode,\n",
+    "                                          predictions=y_pred_cls)\n",
+    "    else:\n",
+    "        # Otherwise the estimator is supposed to be in either\n",
+    "        # training or evaluation-mode. Note that the loss-function\n",
+    "        # is also required in Evaluation mode.\n",
+    "        \n",
+    "        # Define the loss-function to be optimized, by first\n",
+    "        # calculating the cross-entropy between the output of\n",
+    "        # the neural network and the true labels for the input data.\n",
+    "        # This gives the cross-entropy for each image in the batch.\n",
+    "        cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=labels,\n",
+    "                                                                       logits=logits)\n",
+    "\n",
+    "        # Reduce the cross-entropy batch-tensor to a single number\n",
+    "        # which can be used in optimization of the neural network.\n",
+    "        loss = tf.reduce_mean(cross_entropy)\n",
+    "\n",
+    "        # Define the optimizer for improving the neural network.\n",
+    "        optimizer = tf.train.AdamOptimizer(learning_rate=params[\"learning_rate\"])\n",
+    "\n",
+    "        # Get the TensorFlow op for doing a single optimization step.\n",
+    "        train_op = optimizer.minimize(\n",
+    "            loss=loss, global_step=tf.train.get_global_step())\n",
+    "\n",
+    "        # Define the evaluation metrics,\n",
+    "        # in this case the classification accuracy.\n",
+    "        metrics = \\\n",
+    "        {\n",
+    "            \"accuracy\": tf.metrics.accuracy(labels, y_pred_cls)\n",
+    "        }\n",
+    "\n",
+    "        # Wrap all of this in an EstimatorSpec.\n",
+    "        spec = tf.estimator.EstimatorSpec(\n",
+    "            mode=mode,\n",
+    "            loss=loss,\n",
+    "            train_op=train_op,\n",
+    "            eval_metric_ops=metrics)\n",
+    "        \n",
+    "    return spec"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Create an Instance of the Estimator\n",
+    "\n",
+    "We can specify hyper-parameters e.g. for the learning-rate of the optimizer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "params = {\"learning_rate\": 1e-4}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then create an instance of the new Estimator.\n",
+    "\n",
+    "Note that we don't provide feature-columns here as it is inferred automatically from the data-functions when `model_fn()` is called.\n",
+    "\n",
+    "It is unclear from the TensorFlow documentation why it is necessary to specify the feature-columns when using `DNNClassifier` in the example above, when it is not needed here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Using default config.\n",
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial18-2/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fe80a0fbe80>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = tf.estimator.Estimator(model_fn=model_fn,\n",
+    "                               params=params,\n",
+    "                               model_dir=\"./checkpoints_tutorial18-2/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "Now that our new Estimator has been created, we can train it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Create CheckpointSaverHook.\n",
+      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial18-2/model.ckpt.\n",
+      "INFO:tensorflow:loss = 29.6568, step = 1\n",
+      "INFO:tensorflow:global_step/sec: 15.1419\n",
+      "INFO:tensorflow:loss = 20.0903, step = 101 (6.605 sec)\n",
+      "INFO:tensorflow:Saving checkpoints for 200 into ./checkpoints_tutorial18-2/model.ckpt.\n",
+      "INFO:tensorflow:Loss for final step: 3.11824.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.estimator.estimator.Estimator at 0x7fe80a0fba20>"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.train(input_fn=train_input_fn, steps=200)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Once the model has been trained, we can evaluate its performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Starting evaluation at 2017-11-25-09:32:03\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-2/model.ckpt-200\n",
+      "INFO:tensorflow:Finished evaluation at 2017-11-25-09:32:04\n",
+      "INFO:tensorflow:Saving dict for global step 200: accuracy = 0.390566, global_step = 200, loss = 6.8253\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'accuracy': 0.39056605, 'global_step': 200, 'loss': 6.8253026}"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Classification accuracy: 39.06%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Classification accuracy: {0:.2%}\".format(result[\"accuracy\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions\n",
+    "\n",
+    "The model can also be used to make predictions on new data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=predict_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-2/model.ckpt-200\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 0, 0, 0, 0, 0, 0, 0, 0])"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_pred = np.array(list(predictions))\n",
+    "cls_pred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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SMJpMqNQyBoMB4/EEO28TpgVG4zH1eo1e1AbXw3UkhNSgOLXAce+Q6UtLTGnr3Lv5Ke+/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\nmTR0EyZMeOyZNHQTJkx47Pn/AVw5IEth4SmmAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fe8000484e0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=some_images,\n",
+    "            cls_true=some_images_cls,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Predictions for the Entire Test-Set\n",
+    "\n",
+    "To get the predicted classes for the entire test-set, we just use its input-function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(input_fn=test_input_fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:Input graph does not contain a QueueRunner. That means predict yields forever. This is probably a mistake.\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial18-2/model.ckpt-200\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,\n",
+       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,\n",
+       "       0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0,\n",
+       "       0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0,\n",
+       "       0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+       "       0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 2, 0, 0, 0, 2,\n",
+       "       0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 2, 1, 0, 0, 2, 0, 0, 0, 0,\n",
+       "       1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 1, 1, 0, 0, 0, 2,\n",
+       "       2, 0, 0, 2, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 2, 0, 2, 0, 0, 0, 0, 0, 0,\n",
+       "       0, 1, 1, 2, 1, 0, 0, 1, 2, 0, 0, 1, 0, 1, 1, 0, 0, 0, 2, 0, 1, 0, 0,\n",
+       "       1, 0, 0, 1, 0, 0, 0, 2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
+       "       2, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1,\n",
+       "       1, 2, 1, 0, 1, 0, 0, 1, 1, 0, 2, 2, 0, 2, 1, 0, 1, 2, 0, 0, 1, 2, 1,\n",
+       "       1, 0, 1, 0, 0, 1, 1, 0, 0, 2, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 2, 2, 0,\n",
+       "       1, 0, 0, 1, 1, 0, 0, 2, 1, 0, 1, 0, 0, 1, 0, 0, 1, 2, 2, 0, 1, 1, 2,\n",
+       "       1, 0, 0, 2, 2, 2, 0, 1, 1, 2, 2, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1,\n",
+       "       2, 0, 1, 0, 1, 0, 2, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1,\n",
+       "       1, 0, 2, 1, 2, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 2, 0, 0, 0, 0, 1, 0, 2,\n",
+       "       2, 2, 0, 0, 1, 1, 1, 0, 1, 2, 0, 0, 0, 2, 2, 0, 1, 0, 1, 1, 0, 0, 1,\n",
+       "       0, 0, 1, 2, 0, 0, 1, 1, 1, 0, 1, 0, 1, 2, 0, 0, 0, 1, 0, 0, 1, 2, 1,\n",
+       "       0, 2, 1, 1, 1, 1, 1, 0, 1, 2, 0, 0, 0, 1, 0, 2, 1, 0, 1, 1, 1, 1, 0,\n",
+       "       0, 2, 1, 0, 1, 0, 2, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0,\n",
+       "       0])"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_pred = np.array(list(predictions))\n",
+    "cls_pred"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The Convolutional Neural Network predicts different classes for the images, although most have just been classified as 0 (forky), so the accuracy is horrible."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "333"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cls_pred == 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "144"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cls_pred == 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "53"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cls_pred == 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use TensorFlow's binary file-format TFRecords with the Dataset and Estimator APIs. This should simplify the process of training models with very large datasets while getting high usage of the GPU. However, the API could have been simpler in many ways."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Train the Convolutional Neural Network for much longer. Does it get any better at classifying the Knifey-Spoony dataset?\n",
+    "* Save the One-Hot-encoded label instead of the class-integer in the TFRecord and modify the rest of the code to use it.\n",
+    "* Make shards so you save multiple TFRecord files instead of just one.\n",
+    "* Save jpeg-files in the TFRecord instead of the decoded image. You will then need to decode the jpeg-image in the `parse()` function. What are the pro's and con's of doing this?\n",
+    "* Try using another dataset.\n",
+    "* Use a dataset where the images are different sizes. Would you resize before or after converting to the TFRecords file? Why?\n",
+    "* Try and use numpy input-functions instead of TFRecords for the Estimator API. What is the performance difference?\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

From 218baf29c3b58b530a7530e42ff9cc9fefd22383 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 25 Nov 2017 16:49:05 +0100
Subject: [PATCH 27/61] Added Tutorial 18

---
 README.md | 2 ++
 knifey.py | 3 +++
 2 files changed, 5 insertions(+)

diff --git a/README.md b/README.md
index 9346d7a..823797a 100644
--- a/README.md
+++ b/README.md
@@ -57,6 +57,8 @@ Even a few dollars are appreciated. Thanks!
 
 17. Estimator API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
 
+18. TFRecords & Dataset API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb)) 
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/knifey.py b/knifey.py
index 7b741e6..0845fb1 100644
--- a/knifey.py
+++ b/knifey.py
@@ -41,6 +41,9 @@
 # Number of channels in each image, 3 channels: Red, Green, Blue.
 num_channels = 3
 
+# Shape of the numpy-array for an image.
+img_shape = [img_size, img_size, num_channels]
+
 # Length of an image when flattened to a 1-dim array.
 img_size_flat = img_size * img_size * num_channels
 

From b181c48f0d8bca7a5dd51523fbcb719476efe496 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 1 Dec 2017 09:56:50 +0100
Subject: [PATCH 28/61] Added Tutorial 03-C

---
 03C_Keras_API.ipynb | 2340 +++++++++++++++++++++++++++++++++++++++++++
 README.md           |    2 +
 2 files changed, 2342 insertions(+)
 create mode 100644 03C_Keras_API.ipynb

diff --git a/03C_Keras_API.ipynb b/03C_Keras_API.ipynb
new file mode 100644
index 0000000..a87cf6f
--- /dev/null
+++ b/03C_Keras_API.ipynb
@@ -0,0 +1,2340 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# TensorFlow Tutorial #03-C\n",
+    "# Keras API\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "Tutorial #02 showed how to implement a Convolutional Neural Network in TensorFlow. We made a few helper-functions for creating the layers in the network. It is essential to have a good high-level API because it makes it much easier to implement complex models, and it lowers the risk of errors.\n",
+    "\n",
+    "There are several of these builder API's available for TensorFlow: PrettyTensor (Tutorial #03), Layers API (Tutorial #03-B), and several others. But they were never really finished and now they seem to be more or less abandoned by their developers.\n",
+    "\n",
+    "This tutorial is about the Keras API which is already highly developed with very good documentation - and the development continues. It seems likely that Keras will be the standard API for TensorFlow in the future so it is recommended that you use it instead of the other APIs.\n",
+    "\n",
+    "The author of Keras has written a [blog-post](https://blog.keras.io/user-experience-design-for-apis.html) on his API design philosophy which you should read."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Flowchart"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See Tutorial #02 for a more detailed description of convolution.\n",
+    "\n",
+    "There are two convolutional layers, each followed by a down-sampling using max-pooling (not shown in this flowchart). Then there are two fully-connected layers ending in a softmax-classifier."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "![Flowchart](images/02_network_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We need to import several things from Keras. Note the long import-statements. This might be a bug. Hopefully it will be possible to write shorter and more elegant lines in the future."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Sequential  # This does not work!\n",
+    "from tensorflow.python.keras.models import Sequential\n",
+    "from tensorflow.python.keras.layers import InputLayer, Input\n",
+    "from tensorflow.python.keras.layers import Reshape, MaxPooling2D\n",
+    "from tensorflow.python.keras.layers import Conv2D, Dense, Flatten"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.4.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.0.8-tf'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.examples.tutorials.mnist import input_data\n",
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t55000\n",
+      "- Test-set:\t\t10000\n",
+      "- Validation-set:\t5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
+    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Data Dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# We know that MNIST images are 28 pixels in each dimension.\n",
+    "img_size = 28\n",
+    "\n",
+    "# Images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = img_size * img_size\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "# This is used for plotting the images.\n",
+    "img_shape = (img_size, img_size)\n",
+    "\n",
+    "# Tuple with height, width and depth used to reshape arrays.\n",
+    "# This is used for reshaping in Keras.\n",
+    "img_shape_full = (img_size, img_size, 1)\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = 1\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None):\n",
+    "    assert len(images) == len(cls_true) == 9\n",
+    "    \n",
+    "    # Create figure with 3x3 sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "    fig.subplots_adjust(hspace=0.3, wspace=0.3)\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Plot image.\n",
+    "        ax.imshow(images[i].reshape(img_shape), cmap='binary')\n",
+    "\n",
+    "        # Show true and predicted classes.\n",
+    "        if cls_pred is None:\n",
+    "            xlabel = \"True: {0}\".format(cls_true[i])\n",
+    "        else:\n",
+    "            xlabel = \"True: {0}, Pred: {1}\".format(cls_true[i], cls_pred[i])\n",
+    "\n",
+    "        # Show the classes as the label on the x-axis.\n",
+    "        ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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zh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc310557978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the first images from the test-set.\n",
+    "images = data.test.images[0:9]\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = data.test.cls[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function to plot example errors\n",
+    "\n",
+    "Function for plotting examples of images from the test-set that have been mis-classified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_example_errors(cls_pred):\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Boolean array whether the predicted class is incorrect.\n",
+    "    incorrect = (cls_pred != data.test.cls)\n",
+    "\n",
+    "    # Get the images from the test-set that have been\n",
+    "    # incorrectly classified.\n",
+    "    images = data.test.images[incorrect]\n",
+    "    \n",
+    "    # Get the predicted classes for those images.\n",
+    "    cls_pred = cls_pred[incorrect]\n",
+    "\n",
+    "    # Get the true classes for those images.\n",
+    "    cls_true = data.test.cls[incorrect]\n",
+    "    \n",
+    "    # Plot the first 9 images.\n",
+    "    plot_images(images=images[0:9],\n",
+    "                cls_true=cls_true[0:9],\n",
+    "                cls_pred=cls_pred[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## PrettyTensor API\n",
+    "\n",
+    "This is how the Convolutional Neural Network was implemented in Tutorial #03 using the PrettyTensor API. It is shown here for easy comparison to the Keras implementation below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "if False:\n",
+    "    x_pretty = pt.wrap(x_image)\n",
+    "\n",
+    "    with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
+    "        y_pred, loss = x_pretty.\\\n",
+    "            conv2d(kernel=5, depth=16, name='layer_conv1').\\\n",
+    "            max_pool(kernel=2, stride=2).\\\n",
+    "            conv2d(kernel=5, depth=36, name='layer_conv2').\\\n",
+    "            max_pool(kernel=2, stride=2).\\\n",
+    "            flatten().\\\n",
+    "            fully_connected(size=128, name='layer_fc1').\\\n",
+    "            softmax_classifier(num_classes=num_classes, labels=y_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Sequential Model\n",
+    "\n",
+    "The Keras API has two modes of constructing Neural Networks. The simplest is the Sequential Model which only allows for the layers to be added in sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Start construction of the Keras Sequential model.\n",
+    "model = Sequential()\n",
+    "\n",
+    "# Add an input layer which is similar to a feed_dict in TensorFlow.\n",
+    "# Note that the input-shape must be a tuple containing the image-size.\n",
+    "model.add(InputLayer(input_shape=(img_size_flat,)))\n",
+    "\n",
+    "# The input is a flattened array with 784 elements,\n",
+    "# but the convolutional layers expect images with shape (28, 28, 1)\n",
+    "model.add(Reshape(img_shape_full))\n",
+    "\n",
+    "# First convolutional layer with ReLU-activation and max-pooling.\n",
+    "model.add(Conv2D(kernel_size=5, strides=1, filters=16, padding='same',\n",
+    "                 activation='relu', name='layer_conv1'))\n",
+    "model.add(MaxPooling2D(pool_size=2, strides=2))\n",
+    "\n",
+    "# Second convolutional layer with ReLU-activation and max-pooling.\n",
+    "model.add(Conv2D(kernel_size=5, strides=1, filters=36, padding='same',\n",
+    "                 activation='relu', name='layer_conv2'))\n",
+    "model.add(MaxPooling2D(pool_size=2, strides=2))\n",
+    "\n",
+    "# Flatten the 4-rank output of the convolutional layers\n",
+    "# to 2-rank that can be input to a fully-connected / dense layer.\n",
+    "model.add(Flatten())\n",
+    "\n",
+    "# First fully-connected / dense layer with ReLU-activation.\n",
+    "model.add(Dense(128, activation='relu'))\n",
+    "\n",
+    "# Last fully-connected / dense layer with softmax-activation\n",
+    "# for use in classification.\n",
+    "model.add(Dense(num_classes, activation='softmax'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Model Compilation\n",
+    "\n",
+    "The Neural Network has now been defined and must be finalized by adding a loss-function, optimizer and performance metrics. This is called model \"compilation\" in Keras.\n",
+    "\n",
+    "We can either define the optimizer using a string, or if we want more control of its parameters then we need to instantiate an object. For example, we can set the learning-rate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from tensorflow.python.keras.optimizers import Adam\n",
+    "\n",
+    "optimizer = Adam(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "For a classification-problem such as MNIST which has 10 possible classes, we need to use the loss-function called `categorical_crossentropy`. The performance metric we are interested in is the classification accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "model.compile(optimizer=optimizer,\n",
+    "              loss='categorical_crossentropy',\n",
+    "              metrics=['accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "Now that the model has been fully defined with loss-function and optimizer, we can train it. This function takes numpy-arrays and performs the given number of training epochs using the given batch-size. An epoch is one full use of the entire training-set. So for 10 epochs we would iterate randomly over the entire training-set 10 times."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/1\n",
+      "55000/55000 [==============================] - 5s - loss: 0.2261 - acc: 0.9335        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\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fc30e732f98>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fit(x=data.train.images,\n",
+    "          y=data.train.labels,\n",
+    "          epochs=1, batch_size=128)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Now that the model has been trained we can test its performance on the test-set. This also uses numpy-arrays as input."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 9152/10000 [==========================>...] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(x=data.test.images,\n",
+    "                        y=data.test.labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can print all the performance metrics for the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loss 0.0618685603024\n",
+      "acc 0.9801\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in zip(model.metrics_names, result):\n",
+    "    print(name, value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Or we can just print the classification accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "acc: 98.01%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"{0}: {1:.2%}\".format(model.metrics_names[1], result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Prediction\n",
+    "\n",
+    "We can also predict the classification for new images. We will just use some images from the test-set but you could load your own images into numpy arrays and use those instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "images = data.test.images[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "These are the true class-number for those images. This is only used when plotting the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_true = data.test.cls[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the predicted classes as One-Hot encoded arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = model.predict(x=images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the predicted classes as integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred,axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaj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\nIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc30d870dd8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=images,\n",
+    "            cls_true=cls_true,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Examples of Mis-Classified Images\n",
+    "\n",
+    "We can plot some examples of mis-classified images from the test-set.\n",
+    "\n",
+    "First we get the predicted classes for all the images in the test-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = model.predict(x=data.test.images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Then we convert the predicted class-numbers from One-Hot encoded arrays to integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred,axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot some of the mis-classified images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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bZs2aAbBs2bKkYzRv3hyAl14KZ/mcOHEiAJ06dcpF2JIGn1mOGTMGCNuZpfa6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\nAaR5sjHzAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc30d870d30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_example_errors(cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Functional Model\n",
+    "\n",
+    "The Keras API can also be used to construct more complicated networks using the Functional Model. This may look a little confusing at first, because each call to the Keras API will create and return an instance that is itself callable. It is not clear whether it is a function or an object - but we can call it as if it is a function. This allows us to build computational graphs that are more complex than the Sequential Model allows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Create an input layer which is similar to a feed_dict in TensorFlow.\n",
+    "# Note that the input-shape must be a tuple containing the image-size.\n",
+    "inputs = Input(shape=(img_size_flat,))\n",
+    "\n",
+    "# Variable used for building the Neural Network.\n",
+    "net = inputs\n",
+    "\n",
+    "# The input is an image as a flattened array with 784 elements.\n",
+    "# But the convolutional layers expect images with shape (28, 28, 1)\n",
+    "net = Reshape(img_shape_full)(net)\n",
+    "\n",
+    "# First convolutional layer with ReLU-activation and max-pooling.\n",
+    "net = Conv2D(kernel_size=5, strides=1, filters=16, padding='same',\n",
+    "             activation='relu', name='layer_conv1')(net)\n",
+    "net = MaxPooling2D(pool_size=2, strides=2)(net)\n",
+    "\n",
+    "# Second convolutional layer with ReLU-activation and max-pooling.\n",
+    "net = Conv2D(kernel_size=5, strides=1, filters=36, padding='same',\n",
+    "             activation='relu', name='layer_conv2')(net)\n",
+    "net = MaxPooling2D(pool_size=2, strides=2)(net)\n",
+    "\n",
+    "# Flatten the output of the conv-layer from 4-dim to 2-dim.\n",
+    "net = Flatten()(net)\n",
+    "\n",
+    "# First fully-connected / dense layer with ReLU-activation.\n",
+    "net = Dense(128, activation='relu')(net)\n",
+    "\n",
+    "# Last fully-connected / dense layer with softmax-activation\n",
+    "# so it can be used for classification.\n",
+    "net = Dense(num_classes, activation='softmax')(net)\n",
+    "\n",
+    "# Output of the Neural Network.\n",
+    "outputs = net"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Model Compilation\n",
+    "\n",
+    "We have now defined the architecture of the model with its input and output. We now have to create a Keras model and compile it with a loss-function and optimizer, so it is ready for training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from tensorflow.python.keras.models import Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Create a new instance of the Keras Functional Model. We give it the inputs and outputs of the Convolutional Neural Network that we constructed above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "model2 = Model(inputs=inputs, outputs=outputs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Compile the Keras model using the `rmsprop` optimizer and with a loss-function for multiple categories. The only performance metric we are interested in is the classification accuracy, but you could use a list of metrics here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "model2.compile(optimizer='rmsprop',\n",
+    "               loss='categorical_crossentropy',\n",
+    "               metrics=['accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Training\n",
+    "\n",
+    "The model has now been defined and compiled so it can be trained using the same `fit()` function as used in the Sequential Model above. This also takes numpy-arrays as input."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/1\n",
+      "55000/55000 [==============================] - 2s - loss: 0.1924 - acc: 0.9409       \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fc30c02ceb8>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model2.fit(x=data.train.images,\n",
+    "           y=data.train.labels,\n",
+    "           epochs=1, batch_size=128)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Evaluation\n",
+    "\n",
+    "Once the model has been trained we can evaluate its performance on the test-set. This is the same syntax as for the Sequential Model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 8992/10000 [=========================>....] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b"
+     ]
+    }
+   ],
+   "source": [
+    "result = model2.evaluate(x=data.test.images,\n",
+    "                         y=data.test.labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The result is a list of values, containing the loss-value and all the metrics we defined when we compiled the model. Note that 'accuracy' is now called 'acc' which is a small inconsistency."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loss 0.0654281976447\n",
+      "acc 0.9786\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in zip(model.metrics_names, result):\n",
+    "    print(name, value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can also print the classification accuracy as a percentage:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "acc: 97.86%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"{0}: {1:.2%}\".format(model.metrics_names[1], result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Examples of Mis-Classified Images\n",
+    "\n",
+    "We can plot some examples of mis-classified images from the test-set.\n",
+    "\n",
+    "First we get the predicted classes for all the images in the test-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = model2.predict(x=data.test.images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Then we convert the predicted class-numbers from One-Hot encoded arrays to integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot some of the mis-classified images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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0Br5wzq3MILails0yBpYCvzazuhbUZl2BReG2xfQ5bhJ52IOgbbdK2eyneSXB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\nQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc310343470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_example_errors(cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Save & Load Model\n",
+    "\n",
+    "NOTE: You need to install `h5py` for this to work!\n",
+    "\n",
+    "Tutorial #04 was about saving and restoring the weights of a model using native TensorFlow code. It was an absolutely horrible API! Fortunately, Keras makes this very easy.\n",
+    "\n",
+    "This is the file-path where we want to save the Keras model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "path_model = 'model.keras'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Saving a Keras model with the trained weights is then just a single function call, as it should be."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "model2.save(path_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Delete the model from memory so we are sure it is no longer used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "del model2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We need to import this Keras function for loading the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from tensorflow.python.keras.models import load_model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Loading the model is then just a single function-call, as it should be."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "model3 = load_model(path_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then use the model again e.g. to make predictions. We get the first 9 images from the test-set and their true class-numbers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "images = data.test.images[0:9]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_true = data.test.cls[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We then use the restored model to predict the class-numbers for those images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = model3.predict(x=images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Get the class-numbers as integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot the images with their true and predicted class-numbers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaj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\nIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc310396ac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=images,\n",
+    "            cls_pred=cls_pred,\n",
+    "            cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Visualization of Layer Weights and Outputs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting convolutional weights"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_conv_weights(weights, input_channel=0):\n",
+    "    # Get the lowest and highest values for the weights.\n",
+    "    # This is used to correct the colour intensity across\n",
+    "    # the images so they can be compared with each other.\n",
+    "    w_min = np.min(weights)\n",
+    "    w_max = np.max(weights)\n",
+    "\n",
+    "    # Number of filters used in the conv. layer.\n",
+    "    num_filters = weights.shape[3]\n",
+    "\n",
+    "    # Number of grids to plot.\n",
+    "    # Rounded-up, square-root of the number of filters.\n",
+    "    num_grids = math.ceil(math.sqrt(num_filters))\n",
+    "    \n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids)\n",
+    "\n",
+    "    # Plot all the filter-weights.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the valid filter-weights.\n",
+    "        if i<num_filters:\n",
+    "            # Get the weights for the i'th filter of the input channel.\n",
+    "            # See new_conv_layer() for details on the format\n",
+    "            # of this 4-dim tensor.\n",
+    "            img = weights[:, :, input_channel, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, vmin=w_min, vmax=w_max,\n",
+    "                      interpolation='nearest', cmap='seismic')\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Get Layers\n",
+    "\n",
+    "Keras has a simple way of listing the layers in the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "input_2 (InputLayer)         (None, 784)               0         \n",
+      "_________________________________________________________________\n",
+      "reshape_2 (Reshape)          (None, 28, 28, 1)         0         \n",
+      "_________________________________________________________________\n",
+      "layer_conv1 (Conv2D)         (None, 28, 28, 16)        416       \n",
+      "_________________________________________________________________\n",
+      "max_pooling2d_3 (MaxPooling2 (None, 14, 14, 16)        0         \n",
+      "_________________________________________________________________\n",
+      "layer_conv2 (Conv2D)         (None, 14, 14, 36)        14436     \n",
+      "_________________________________________________________________\n",
+      "max_pooling2d_4 (MaxPooling2 (None, 7, 7, 36)          0         \n",
+      "_________________________________________________________________\n",
+      "flatten_2 (Flatten)          (None, 1764)              0         \n",
+      "_________________________________________________________________\n",
+      "dense_3 (Dense)              (None, 128)               225920    \n",
+      "_________________________________________________________________\n",
+      "dense_4 (Dense)              (None, 10)                1290      \n",
+      "=================================================================\n",
+      "Total params: 242,062\n",
+      "Trainable params: 242,062\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "model3.summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We count the indices to get the layers we want.\n",
+    "\n",
+    "The input-layer has index 0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "layer_input = model3.layers[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The first convolutional layer has index 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras._impl.keras.layers.convolutional.Conv2D at 0x7fc30c26cb70>"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "layer_conv1 = model3.layers[2]\n",
+    "layer_conv1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The second convolutional layer has index 4."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "layer_conv2 = model3.layers[4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Convolutional Weights\n",
+    "\n",
+    "Now that we have the layers we can easily get their weights."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "weights_conv1 = layer_conv1.get_weights()[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This gives us a 4-rank tensor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(5, 5, 1, 16)"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_conv1.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot the weights using the helper-function from above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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DfLOyXEOD2Zo1OnfCviAz+V/8omtn9KsXZaa5eZbMjBhR6drHJ0oAEChKABAoSgAQKEoA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\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc302a554a8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(weights=weights_conv1, input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can also get the weights for the second convolutional layer and plot them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "weights_conv2 = layer_conv2.get_weights()[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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S8Ew4fj8VDxjADyR5fKt27xbj4+/qK2r0FBZHqa6Oz8IRTlERFb/7Lsvf25mh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\nQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc2cc6bde10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_weights(weights=weights_conv2, input_channel=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Helper-function for plotting the output of a convolutional layer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_conv_output(values):\n",
+    "    # Number of filters used in the conv. layer.\n",
+    "    num_filters = values.shape[3]\n",
+    "\n",
+    "    # Number of grids to plot.\n",
+    "    # Rounded-up, square-root of the number of filters.\n",
+    "    num_grids = math.ceil(math.sqrt(num_filters))\n",
+    "    \n",
+    "    # Create figure with a grid of sub-plots.\n",
+    "    fig, axes = plt.subplots(num_grids, num_grids)\n",
+    "\n",
+    "    # Plot the output images of all the filters.\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Only plot the images for valid filters.\n",
+    "        if i<num_filters:\n",
+    "            # Get the output image of using the i'th filter.\n",
+    "            img = values[0, :, :, i]\n",
+    "\n",
+    "            # Plot image.\n",
+    "            ax.imshow(img, interpolation='nearest', cmap='binary')\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Input Image\n",
+    "\n",
+    "Helper-function for plotting a single image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "def plot_image(image):\n",
+    "    plt.imshow(image.reshape(img_shape),\n",
+    "               interpolation='nearest',\n",
+    "               cmap='binary')\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Plot an image from the test-set which will be used as an example below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc2cc21aac8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "image1 = data.test.images[0]\n",
+    "plot_image(image1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Output of Convolutional Layer - Method 1\n",
+    "\n",
+    "There are different ways of getting the output of a layer in a Keras model. This method uses a so-called K-function which turns a part of the Keras model into a function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from tensorflow.python.keras import backend as K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "output_conv1 = K.function(inputs=[layer_input.input],\n",
+    "                          outputs=[layer_conv1.output])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then call this function with the input image. Note that the image is wrapped in two lists because the function expects an array of that dimensionality. Likewise, the function returns an array with one more dimensionality than we want so we just take the first element."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1, 28, 28, 16)"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "layer_output1 = output_conv1([[image1]])[0]\n",
+    "layer_output1.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then plot the output of all 16 channels of the convolutional layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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4cnIyoRrHbaa3YRiGByHTKIeKOMDFxJPH4SBaaUFBwaAnfDwgp3J6erqmPogJ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\n8MAEpWEYhgcmKA3DMDwwQWkYhuHB/wPu2gEcRxkXGwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc2cc21a2e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_output(values=layer_output1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### Output of Convolutional Layer - Method 2\n",
+    "\n",
+    "Keras also has another method for getting the output of a layer inside the model. This creates another Functional Model using the same input as the original model, but the output is now taken from the convolutional layer that we are interested in."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "output_conv2 = Model(inputs=layer_input.input,\n",
+    "                     outputs=layer_conv2.output)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "This creates a new model-object where we can call the typical Keras functions. To get the output of the convoloutional layer we call the `predict()` function with the input image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1, 14, 14, 36)"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "layer_output2 = output_conv2.predict(np.array([image1]))\n",
+    "layer_output2.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can then plot the images for all 36 channels."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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347B4PKSbgCITvPjii3Zb1hslpNJ9zyRhSGPS5m688UYgPulOFHKypsojjzxi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\nSUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc2a94760f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_conv_output(values=layer_output2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use the so-called *Keras API* for easily building Convolutional Neural Networks in TensorFlow. Keras is by far the most complete and best designed API for TensorFlow.\n",
+    "\n",
+    "This tutorial also showed how to use Keras to save and load a model, as well as getting the weights and outputs of convolutional layers.\n",
+    "\n",
+    "It seems likely that Keras will be the standard API for TensorFlow in the future, for the simple reason that is already very good and it is constantly being improved. So it is recommended that you use Keras."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Train for more epochs. Does it improve the classification accuracy?\n",
+    "* Change the activation function to sigmoid for some of the layers.\n",
+    "* Can you find a simple way of changing the activation function for all the layers?\n",
+    "* Plot the output of the max-pooling layers instead of the conv-layers.\n",
+    "* Replace the 2x2 max-pooling layers with stride=2 in the convolutional layers. Is there a difference in classification accuracy? What if you optimize it again and again? The difference is random, so how would you measure if there really is a difference? What are the pros and cons of using max-pooling vs. stride in the conv-layer?\n",
+    "* Change the parameters for the layers, e.g. the kernel, depth, size, etc. What is the difference in time usage and classification accuracy?\n",
+    "* Add and remove some convolutional and fully-connected layers.\n",
+    "* What is the simplest network you can design that still performs well?\n",
+    "* Change the Functional Model so it has another convolutional layer that connects in parallel to the existing conv-layers before going into the dense layers.\n",
+    "* Change the Functional Model so it outputs the predicted class both as a One-Hot encoded array and as an integer, so we don't have to use `numpy.argmax()` afterwards.\n",
+    "* Remake the program yourself without looking too much at this source-code.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index 823797a..63dd275 100644
--- a/README.md
+++ b/README.md
@@ -27,6 +27,8 @@ Even a few dollars are appreciated. Thanks!
 
 3-B. Layers API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
 
+3-C. Keras API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
+
 4. Save & Restore ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
 
 5. Ensemble Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/05_Ensemble_Learning.ipynb))

From 761ebfaaea52ac2ae4a92f9b4a1e6f616920eec9 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 9 Dec 2017 09:32:19 +0100
Subject: [PATCH 29/61] Added Tutorial 10

---
 10_Fine-Tuning.ipynb                      | 2007 +++++++++++++++++++++
 README.md                                 |    2 +-
 dataset.py                                |   70 +
 images/10_transfer_learning_flowchart.png |  Bin 0 -> 78791 bytes
 images/10_transfer_learning_flowchart.svg |  907 ++++++++++
 knifey.py                                 |   27 +
 6 files changed, 3012 insertions(+), 1 deletion(-)
 create mode 100644 10_Fine-Tuning.ipynb
 create mode 100644 images/10_transfer_learning_flowchart.png
 create mode 100644 images/10_transfer_learning_flowchart.svg

diff --git a/10_Fine-Tuning.ipynb b/10_Fine-Tuning.ipynb
new file mode 100644
index 0000000..924ca7c
--- /dev/null
+++ b/10_Fine-Tuning.ipynb
@@ -0,0 +1,2007 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #10\n",
+    "# Fine-Tuning\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "We have previously seen in Tutorials #08 and #09 how to use a pre-trained Neural Network on a new dataset using so-called Transfer Learning, by re-routing the output of the original model just prior to its classification layers and instead use a new classifier that we had created. Because the original model was 'frozen' its weights could not be further optimized, so whatever had been learned by all the previous layers in the model, could not be fine-tuned to the new data-set.\n",
+    "\n",
+    "This tutorial shows how to do both Transfer Learning and Fine-Tuning using the Keras API for Tensorflow. We will once again use the Knifey-Spoony dataset introduced in Tutorial #09. We previously used the Inception v3 model but we will use the VGG16 model in this tutorial because its architecture is easier to work with.\n",
+    "\n",
+    "NOTE: It takes around 15 minutes to execute this Notebook on a laptop PC with a 2.6 GHz CPU and a GTX 1070 GPU. Running it on the CPU alone is estimated to take around 10 hours!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "The idea is to re-use a pre-trained model, in this case the VGG16 model, which consists of several convolutional layers (actually blocks of multiple convolutional layers), followed by some fully-connected / dense layers and then a softmax output layer for the classification. \n",
+    "\n",
+    "The dense layers are responsible for combining features from the convolutional layers and this helps in the final classification. So when the VGG16 model is used on another dataset we may have to replace all the dense layers. In this case we add another dense-layer and a dropout-layer to avoid overfitting.\n",
+    "\n",
+    "The difference between Transfer Learning and Fine-Tuning is that in Transfer Learning we only optimize the weights of the new classification layers we have added, while we keep the weights of the original VGG16 model. In Fine-Tuning we optimize both the weights of the new classification layers we have added, as well as some or all of the layers from the VGG16 model."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Flowchart of Transfer Learning & Fine-Tuning](images/10_transfer_learning_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import PIL\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the imports from the Keras API. Note the long format which can hopefully be shortened in the future to e.g. `from tf.keras.models import Model`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from tensorflow.python.keras.models import Model, Sequential\n",
+    "from tensorflow.python.keras.layers import Dense, Flatten, Dropout\n",
+    "from tensorflow.python.keras.applications import VGG16\n",
+    "from tensorflow.python.keras.applications.vgg16 import preprocess_input, decode_predictions\n",
+    "from tensorflow.python.keras.preprocessing.image import ImageDataGenerator\n",
+    "from tensorflow.python.keras.optimizers import Adam, RMSprop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Helper Functions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for joining a directory and list of filenames."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def path_join(dirname, filenames):\n",
+    "    return [os.path.join(dirname, filename) for filename in filenames]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Function used to plot at most 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None, smooth=True):\n",
+    "\n",
+    "    assert len(images) == len(cls_true)\n",
+    "\n",
+    "    # Create figure with sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "\n",
+    "    # Adjust vertical spacing.\n",
+    "    if cls_pred is None:\n",
+    "        hspace = 0.3\n",
+    "    else:\n",
+    "        hspace = 0.6\n",
+    "    fig.subplots_adjust(hspace=hspace, wspace=0.3)\n",
+    "\n",
+    "    # Interpolation type.\n",
+    "    if smooth:\n",
+    "        interpolation = 'spline16'\n",
+    "    else:\n",
+    "        interpolation = 'nearest'\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # There may be less than 9 images, ensure it doesn't crash.\n",
+    "        if i < len(images):\n",
+    "            # Plot image.\n",
+    "            ax.imshow(images[i],\n",
+    "                      interpolation=interpolation)\n",
+    "\n",
+    "            # Name of the true class.\n",
+    "            cls_true_name = class_names[cls_true[i]]\n",
+    "\n",
+    "            # Show true and predicted classes.\n",
+    "            if cls_pred is None:\n",
+    "                xlabel = \"True: {0}\".format(cls_true_name)\n",
+    "            else:\n",
+    "                # Name of the predicted class.\n",
+    "                cls_pred_name = class_names[cls_pred[i]]\n",
+    "\n",
+    "                xlabel = \"True: {0}\\nPred: {1}\".format(cls_true_name, cls_pred_name)\n",
+    "\n",
+    "            # Show the classes as the label on the x-axis.\n",
+    "            ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for printing confusion matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import a function from sklearn to calculate the confusion-matrix.\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "\n",
+    "def print_confusion_matrix(cls_pred):\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Get the confusion matrix using sklearn.\n",
+    "    cm = confusion_matrix(y_true=cls_test,  # True class for test-set.\n",
+    "                          y_pred=cls_pred)  # Predicted class.\n",
+    "\n",
+    "    print(\"Confusion matrix:\")\n",
+    "    \n",
+    "    # Print the confusion matrix as text.\n",
+    "    print(cm)\n",
+    "    \n",
+    "    # Print the class-names for easy reference.\n",
+    "    for i, class_name in enumerate(class_names):\n",
+    "        print(\"({0}) {1}\".format(i, class_name))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for plotting example errors\n",
+    "\n",
+    "Function for plotting examples of images from the test-set that have been mis-classified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_example_errors(cls_pred):\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Boolean array whether the predicted class is incorrect.\n",
+    "    incorrect = (cls_pred != cls_test)\n",
+    "\n",
+    "    # Get the file-paths for images that were incorrectly classified.\n",
+    "    image_paths = np.array(image_paths_test)[incorrect]\n",
+    "\n",
+    "    # Load the first 9 images.\n",
+    "    images = load_images(image_paths=image_paths[0:9])\n",
+    "    \n",
+    "    # Get the predicted classes for those images.\n",
+    "    cls_pred = cls_pred[incorrect]\n",
+    "\n",
+    "    # Get the true classes for those images.\n",
+    "    cls_true = cls_test[incorrect]\n",
+    "    \n",
+    "    # Plot the 9 images we have loaded and their corresponding classes.\n",
+    "    # We have only loaded 9 images so there is no need to slice those again.\n",
+    "    plot_images(images=images,\n",
+    "                cls_true=cls_true[0:9],\n",
+    "                cls_pred=cls_pred[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Function for calculating the predicted classes of the entire test-set and calling the above function to plot a few examples of mis-classified images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def example_errors():\n",
+    "    # The Keras data-generator for the test-set must be reset\n",
+    "    # before processing. This is because the generator will loop\n",
+    "    # infinitely and keep an internal index into the dataset.\n",
+    "    # So it might start in the middle of the test-set if we do\n",
+    "    # not reset it first. This makes it impossible to match the\n",
+    "    # predicted classes with the input images.\n",
+    "    # If we reset the generator, then it always starts at the\n",
+    "    # beginning so we know exactly which input-images were used.\n",
+    "    generator_test.reset()\n",
+    "    \n",
+    "    # Predict the classes for all images in the test-set.\n",
+    "    y_pred = new_model.predict_generator(generator_test,\n",
+    "                                         steps=steps_test)\n",
+    "\n",
+    "    # Convert the predicted classes from arrays to integers.\n",
+    "    cls_pred = np.argmax(y_pred,axis=1)\n",
+    "\n",
+    "    # Plot examples of mis-classified images.\n",
+    "    plot_example_errors(cls_pred)\n",
+    "    \n",
+    "    # Print the confusion matrix.\n",
+    "    print_confusion_matrix(cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for loading images\n",
+    "\n",
+    "The data-set is not loaded into memory, instead it has a list of the files for the images in the training-set and another list of the files for the images in the test-set. This helper-function loads some image-files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_images(image_paths):\n",
+    "    # Load the images from disk.\n",
+    "    images = [plt.imread(path) for path in image_paths]\n",
+    "\n",
+    "    # Convert to a numpy array and return it.\n",
+    "    return np.asarray(images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for plotting training history\n",
+    "\n",
+    "This plots the classification accuracy and loss-values recorded during training with the Keras API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_training_history(history):\n",
+    "    # Get the classification accuracy and loss-value\n",
+    "    # for the training-set.\n",
+    "    acc = history.history['categorical_accuracy']\n",
+    "    loss = history.history['loss']\n",
+    "\n",
+    "    # Get it for the validation-set (we only use the test-set).\n",
+    "    val_acc = history.history['val_categorical_accuracy']\n",
+    "    val_loss = history.history['val_loss']\n",
+    "\n",
+    "    # Plot the accuracy and loss-values for the training-set.\n",
+    "    plt.plot(acc, linestyle='-', color='b', label='Training Acc.')\n",
+    "    plt.plot(loss, 'o', color='b', label='Training Loss')\n",
+    "    \n",
+    "    # Plot it for the test-set.\n",
+    "    plt.plot(val_acc, linestyle='--', color='r', label='Test Acc.')\n",
+    "    plt.plot(val_loss, 'o', color='r', label='Test Loss')\n",
+    "\n",
+    "    # Plot title and legend.\n",
+    "    plt.title('Training and Test Accuracy')\n",
+    "    plt.legend()\n",
+    "\n",
+    "    # Ensure the plot shows correctly.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Dataset: Knifey-Spoony\n",
+    "\n",
+    "The Knifey-Spoony dataset was introduced in Tutorial #09. It was generated from video-files by taking individual frames and converting them to images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import knifey"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download and extract the dataset if it hasn't already been done. It is about 22 MB."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "knifey.maybe_download_and_extract()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This dataset has another directory structure than the Keras API requires, so copy the files into separate directories for the training- and test-sets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Creating dataset from the files in: data/knifey-spoony/\n",
+      "- Data loaded from cache-file: data/knifey-spoony/knifey-spoony.pkl\n",
+      "- Copied training-set to: data/knifey-spoony/train/\n",
+      "- Copied test-set to: data/knifey-spoony/test/\n"
+     ]
+    }
+   ],
+   "source": [
+    "knifey.copy_files()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The directories where the images are now stored."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_dir = knifey.train_dir\n",
+    "test_dir = knifey.test_dir"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pre-Trained Model: VGG16\n",
+    "\n",
+    "The following creates an instance of the pre-trained VGG16 model using the Keras API. This automatically downloads the required files if you don't have them already. Note how simple this is in Keras compared to Tutorial #08.\n",
+    "\n",
+    "The VGG16 model contains a convolutional part and a fully-connected (or dense) part which is used for classification. If `include_top=True` then the whole VGG16 model is downloaded which is about 528 MB. If `include_top=False` then only the convolutional part of the VGG16 model is downloaded which is just 57 MB.\n",
+    "\n",
+    "We will try and use the pre-trained model for predicting the class of some images in our new dataset, so we have to download the full model, but if you have a slow internet connection, then you can modify the code below to use the smaller pre-trained model without the classification layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "model = VGG16(include_top=True, weights='imagenet')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Input Pipeline\n",
+    "\n",
+    "The Keras API has its own way of creating the input pipeline for training a model using files.\n",
+    "\n",
+    "First we need to know the shape of the tensors expected as input by the pre-trained VGG16 model. In this case it is images of shape 224 x 224 x 3."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(224, 224)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "input_shape = model.layers[0].output_shape[1:3]\n",
+    "input_shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Keras uses a so-called data-generator for inputting data into the neural network, which will loop over the data for eternity.\n",
+    "\n",
+    "We have a small training-set so it helps to artificially inflate its size by making various transformations to the images. We use a built-in data-generator that can make these random transformations. This is also called an augmented dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datagen_train = ImageDataGenerator(\n",
+    "      rescale=1./255,\n",
+    "      rotation_range=180,\n",
+    "      width_shift_range=0.1,\n",
+    "      height_shift_range=0.1,\n",
+    "      shear_range=0.1,\n",
+    "      zoom_range=[0.9, 1.5],\n",
+    "      horizontal_flip=True,\n",
+    "      vertical_flip=True,\n",
+    "      fill_mode='nearest')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We also need a data-generator for the test-set, but this should not do any transformations to the images because we want to know the exact classification accuracy on those specific images. So we just rescale the pixel-values so they are between 0.0 and 1.0 because this is expected by the VGG16 model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datagen_test = ImageDataGenerator(rescale=1./255)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The data-generators will return batches of images. Because the VGG16 model is so large, the batch-size cannot be too large, otherwise you will run out of RAM on the GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "batch_size = 20"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can save the randomly transformed images during training, so as to inspect whether they have been overly distorted, so we have to adjust the parameters for the data-generator above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if True:\n",
+    "    save_to_dir = None\n",
+    "else:\n",
+    "    save_to_dir='augmented_images/'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we create the actual data-generator that will read files from disk, resize the images and return a random batch.\n",
+    "\n",
+    "It is somewhat awkward that the construction of the data-generator is split into these two steps, but it is probably because there are different kinds of data-generators available for different data-types (images, text, etc.) and sources (memory or disk)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 4170 images belonging to 3 classes.\n"
+     ]
+    }
+   ],
+   "source": [
+    "generator_train = datagen_train.flow_from_directory(directory=train_dir,\n",
+    "                                                    target_size=input_shape,\n",
+    "                                                    batch_size=batch_size,\n",
+    "                                                    shuffle=True,\n",
+    "                                                    save_to_dir=save_to_dir)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The data-generator for the test-set should not transform and shuffle the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 530 images belonging to 3 classes.\n"
+     ]
+    }
+   ],
+   "source": [
+    "generator_test = datagen_test.flow_from_directory(directory=test_dir,\n",
+    "                                                  target_size=input_shape,\n",
+    "                                                  batch_size=batch_size,\n",
+    "                                                  shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Because the data-generators will loop for eternity, we need to specify the number of steps to perform during evaluation and prediction on the test-set. Because our test-set contains 530 images and the batch-size is set to 20, the number of steps is 26.5 for one full processing of the test-set. This is why we need to reset the data-generator's counter in the `example_errors()` function above, so it always starts processing from the beginning of the test-set.\n",
+    "\n",
+    "This is another slightly awkward aspect of the Keras API which could perhaps be improved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "26.5"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "steps_test = generator_test.n / batch_size\n",
+    "steps_test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the file-paths for all the images in the training- and test-sets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image_paths_train = path_join(train_dir, generator_train.filenames)\n",
+    "image_paths_test = path_join(test_dir, generator_test.filenames)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the class-numbers for all the images in the training- and test-sets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_train = generator_train.classes\n",
+    "cls_test = generator_test.classes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the class-names for the dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['forky', 'knifey', 'spoony']"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "class_names = list(generator_train.class_indices.keys())\n",
+    "class_names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the number of classes for the dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_classes = generator_train.num_class\n",
+    "num_classes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9TojWc7Q4AkW20rtfPT4YDB8WQwB8ZonTG0GYJF9bzByApdfrEScJFt9MCpjP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\njx495smzE0bDEUmS0u32SVttBgPH8fEzwDeT398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p4UZU3bGCNAM6qtHHoLmfDj0bfAvD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lDXQimfs7A9HmlKRr2c/aMHpMMxx6cnnB4fk3h459EjZodHZIMJpfT47Pic849/m3f6S4ajEZ5N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\nGudAm4TpbE6SpOR5wXq9wRhDY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h0gk8e4YjmpFYGwMOEclvMCJd1hsT/F798v9DLLublr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\nK0PHcRwAXgMj6KEkZif7PAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c185f6320>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load the first images from the train-set.\n",
+    "images = load_images(image_paths=image_paths_train[0:9])\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = cls_train[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true, smooth=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Class Weights\n",
+    "\n",
+    "The Knifey-Spoony dataset is quite imbalanced because it has few images of forks, more images of knives, and many more images of spoons. This can cause a problem during training because the neural network will be shown many more examples of spoons than forks, so it might become better at recognizing spoons.\n",
+    "\n",
+    "Here we use scikit-learn to calculate weights that will properly balance the dataset. These weights are applied to the gradient for each image in the batch during training, so as to scale their influence on the overall gradient for the batch."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.utils.class_weight import compute_class_weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class_weight = compute_class_weight(class_weight='balanced',\n",
+    "                                    classes=np.unique(cls_train),\n",
+    "                                    y=cls_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note how the weight is about 1.398 for the forky-class and only 0.707 for the spoony-class. This is because there are fewer images for the forky-class so the gradient should be amplified for those images, while the gradient should be lowered for spoony-images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.39839034,  1.14876033,  0.70701933])"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "class_weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['forky', 'knifey', 'spoony']"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "class_names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example Predictions\n",
+    "\n",
+    "Here we will show a few examples of using the pre-trained VGG16 model for prediction.\n",
+    "\n",
+    "We need a helper-function for loading and resizing an image so it can be input to the VGG16 model, as well as doing the actual prediction and showing the result."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def predict(image_path):\n",
+    "    # Load and resize the image using PIL.\n",
+    "    img = PIL.Image.open(image_path)\n",
+    "    img_resized = img.resize(input_shape, PIL.Image.LANCZOS)\n",
+    "\n",
+    "    # Plot the image.\n",
+    "    plt.imshow(img_resized)\n",
+    "    plt.show()\n",
+    "\n",
+    "    # Convert the PIL image to a numpy-array with the proper shape.\n",
+    "    img_array = np.expand_dims(np.array(img_resized), axis=0)\n",
+    "\n",
+    "    # Use the VGG16 model to make a prediction.\n",
+    "    # This outputs an array with 1000 numbers corresponding to\n",
+    "    # the classes of the ImageNet-dataset.\n",
+    "    pred = model.predict(img_array)\n",
+    "    \n",
+    "    # Decode the output of the VGG16 model.\n",
+    "    pred_decoded = decode_predictions(pred)[0]\n",
+    "\n",
+    "    # Print the predictions.\n",
+    "    for code, name, score in pred_decoded:\n",
+    "        print(\"{0:>6.2%} : {1}\".format(score, name))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then use the VGG16 model on a picture of a parrot which is classified as a macaw (a parrot species) with a fairly high score of 79%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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IRzi+V6ajk6dAzZno0IkyJGc7GP1YiUNAkkCqjEMl9lAIPBwKXTV6E3bJebaF6xGGXpAk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GrYGpOUkpp0AguvBt77b5tQTXiYh3Y+4jLb5RUCdWEWxZ7Pi6PMjy81vuyRiyKyklPnudagMt\nmLrMPYW4yLFlwYR+jxUFUaGboAth4aRHFOjF+QUL7O22VMgif10eVAUfEgUaWFlagLRU3uB++zEb\n2iImthicQEyRmBo5CzkvM/BsRIQ5+KowLJ3GPLkbczEvDJaUFbDKcbHZgjT0dN1AUGHohPW6IzW4\ntD1WDYtLenFwBFlLg6autY/mVGoTQs5ggSci3MgrXjfQtCbmQn74mOfnN/gzP/UT/I0f+5/5sfxD\n/P6LX+DuRWbePWI4Ahm2iGX3PbCRROfrwxiwWokxIdlNUhq+C0/uqOImH8FBuZz95tXWiAodS0GY\nfZptrRJ6SMkxA9XmfhAWmHdKDoGcA+2ioqrMLZFUWc3wZv4+ympgrk8pPCUfv0B55/PE7kW6+g/Z\nP7rkwae/iVwUuejpXz6Ed7Zc5sa1+zfp212G4WO8efaYu4eZy3jOZTjgcDvTHXUcH90gSIdxSd7A\n5ppwdMNYHwo5OpBXiMyzMk6BuTgvYL93zwLTwDRVprFhCMMQyF2i7x2baE2ZJzdB0SpIi0gRSmtc\njs0zK4OrcDwxXJ0u3twGPsawbD4i7s7kYKLZotGIiww6gIj7axIdmIhXXYIIX2c8K7Up2maqNCJx\nibJ3i7bf1e3DP4orKPRngT4KFhYQRRRs9tUZziOQlhdNQ4PSsFmgKYZAaNi8CHWCUHGqaAiGJVtE\nUktc+iIucaTWPQO65BJgBar6qikqizTY67kPjWCTEHohdErC6FIg9EbsoF8FsiVSqszZ0C5iJdK0\nMbXqik9zZKkilBCoYsy6RJ6LC6tEjRw6GG7yZHJKcLdXLuaOX/+ZX+bf+/m/xZc/+Qc4/v7vY3v+\nf9Bff8rZVw3rjbwK1JaxSWl9IdfFcTg6FdnEnpl9Sgy+OszRHY2tEWLAV43i329diq/6FiFFF0jV\npkSNy8q3Lm128PTsy8DYVfqU3Flq9Pe164R4CW/2HyNUJexXpFNjorI6v8b7Rx/wso1Mt76d82sb\n7Ku/TPjkPeSdNwhHQre5wcXDU8LNj/Dg0cShXSMeWuonmAAAIABJREFUHhBl4ngWHptydxbijQG9\ntWIzb+leEA6vC8c3lPVaibgZylgriiEVdFyISVmoxYtCmd2ev++FflCGtZFXvhbXGpzDUYQyK3VU\nWg1udqss96Ti3A2hVluIU36YqXr3kUIGom8R2sLpAAxnkqoqOZm7XhEJkojBNRthISSZVir4yFsV\nrDrbtilCpMnvQeNWUchbnOwRE5a9nWtWmdSrMjkgBaQsnJnRnLegTv5z1DtgGmjNUWBEnSWm8szR\nl/BsueMNxpVpyGIylLsOaUordRECLS47Ztjk608FcoHchBUVicnn8FiJSUnBUeZz3UOKzEEWs8+C\nNHMaMM7Lb62hTdjXsmAgRtGG1sAmranXXqQU2NYLbhXh4sZH+PL33GFjb7H9wT/IRx+OvLqd4GEj\nSqKt1jRGZJ8JHUi6xKaF3nsFPi3fvhOOlhurNTcDUSObg1h1MtwjVzzLojTE0rNxpEviAimzxbfQ\n2X7j3nMh2jRBbwwSqBKoVaiH0DTxQXoBnl5wWKB/PPHr20dcX0HSJ4TpHu+99CLxtdcYDg45f/eU\nvLnJdPGIO2+NvDE+4biv9L/2APtE4tH717nWP8eNe4c8boqmQLsWeOnV++xff8JwFFgdGP260XVC\nkkQqhoVG83xXShSUwLhvy4nuhDNnxwqrjbLeGN0Kuu4q0k+pox8WrRrWlo5Vcbl48CLgW4GvB0Vc\nEalYMALfJngx8W3YMkosmx0xJca0MDGvHJach2DLTS3mXhpNr/wsGu7goNg/CvLS7/YlCut9ZG3Z\ng1JyJfZCnBMaG5NVdG7kqoQKcxVkMnJV9Mq7qjm7sTZxbrI4lXlv3kmo2KJXcAUlQRdGmkHxMSPE\nzr3ygpByQ+alC8EzDVQdmAs5QGvPboIl8Zuu891xC4BkTi8vkABNokts1TArhODZAaIu6Z1bo5Q9\nbUzuIk0lth7bXKetnyPOyjZENvszziyyuX7IC/M1vta9wDdf+3lOrLKvPXK5x4ZjTCa6EWo34bKb\nhGklxYyI0loj5kggUSbHDmqrToOORpsqmI8ytuRF1hm/CW1R3V2xP+vstunNH4QhBfbqeY65wrSv\nDBeJFgNaZuL5MRJnzgbQuiLIxO7iCbfWhzzWws331ozHN3myfUTcv0FMt7i/h/0HbzJdNN6LWw4/\n9gr94ze5vHPGR/g47eGW828VLtpE7TouCDx3MXN2bQ8XkT40uqQ+RsZIjh1iE534JkojhE6Y1dAt\ngFOb0UTXGTk01xhEo0u+WaqtknslD5AHYZ7Ee1oTD8QxJS9OzyUHV5A2kCTuxoJzEFyE52NxjCyi\nrbD4J0TQylQhxkbOAQ2KWiReCaiMZ8WitoY2Z8kqRhPvlFFnN37Y6xuiKAQTVnNiaE5H1RLQ0phw\nIJDm7DGtHtrBLCR1ZFfjFUC52Jabr18Ep4CqNLcQc9o7cVntCC7wCSKoRFT9TWvaCNFntbBU+hD8\n7+BDxCL2WQCcpdPwRGKjRV28DYOLa/COp5o6AxMjiPsohAUHKbUyVnPWWysMnSdfl8016uYG20no\nVh3nT0batcDzm56D7THdcx/jR9/7y4SLmVNdI9LYrLagjaYTsSgpBO/qcfej2pp/TzFhxWm5YrLs\ntBNRnJ8xjZUgkZQzba5ueovfxJVGU//ezJlPHkePE6AGBJ1dF0FVntYGo9PBp/EJtRnT/inDeyti\nf5cPinH08vPc/urr9HHH2/1DhgeNk5P7rN97yPmNFfKgcetgza/ef4kbxxM53ubkm+7x+ukZL4Yj\nwuqI21t4TXds96BPnnLSrSi3Dsn2mD4m0OYYCQ2i3z+5g97E8Z6gDAohKnOBNlUkBfIQSCGiTaml\nEmKH1oTWEZFGSt4JlCUbA3MPxii4HiEsBiiLtPwZw/D/dngH8XWvOzEtq0j1lbc2RasS5oYkJaeA\nxbT4NXoGhbb2f8UODLBAiOn3XqcQLXAwZboaaQjEBkHZJ/fD72JEzIjNGXZdTVQxYkxcMjGhbq6y\n5PvZ0sY2HKNo6nz0xRkM4OuGFRYJFolASIKGRlzEJxLM3Z0WKTZmaDPPKSxKnd0QtitGnKF2BtRn\nD50W51AYXk6auLORmhctUYG2iLJS+D+pe7NY27LrPO+b3Vprt6e559xzm2pYxVYkRYmkWhsSFDWA\nhRhwrERKjPRIYPkxL0EQwECAvAd5yEsgpLNfHCOWrcSWY6eRlFiiLFOmTEpikcVitbfvTrPbtWYz\n8jDm3rfEGGapSUCti4u6de65p9lnrTnHHOP/vx/bjimSMKFn22/JYQSjOTlCI5ZYPEPb0qYRqw+f\n8pH5O/zgG69TDmDybIUcGtqDDWVQI5NL7B2Ru+9pbwbL1XhVZ+JlgJIiJWspSkabn86S642ehlzH\nlxrh54KtWZIZaxwlZ3JKmCRVLFZwUXUPo4UBX1iMoSwdp5MzolzywHeMXzjh/tUjPjVseDovjN58\nQP/Rm6yuzjk7vcZieIQ5usmT0RVh3HE4mpC7U/rzRJzM2KwNA4VuNsVc3mE0nXAxbWhxHBweIlfP\nMMVodIDXSq4US+5rHoVVV61thLbbNZ2FJaojyBiMS2rwqv6GGBMxUhmP7CniRvcD7dNYU09nVRJn\nqDZ1nWKw9zOUveJwNyFTMchOQ9OTYiKKipSsS2TvSS7jnAcMph5xn1+mNiOthi196wr0L7i+IxYF\ni8EXHeU5ICDkZBmjTRhblNnvdz8AHNEK2UKwSZ1wHtWv1o6soswrhUmgdn8APd+rY48a7SWUWHDB\nQhCCUI0qOiHSTaaGgBSDpEIZ1CgUeyEO6mcYBsWPifQYVGhlRM02YlSdJmgnyVlfFw+nkmFXcDYg\nRZOR1yUzDZaAowmFrhdyHjEky8xFXvvcT/PzF7/K2eXX2d5wmNcDzScb2nnPauvrKM4qShwwzlWB\nUm06JSGnXJOcwDhDjsJmFRmNrMbKlaKQ0gRERY65HctjbyWor3HWdGYpkQSUkoi5YKOnSx6z7vFB\n6CYdfQgc9YnTzwbM1xpeeOMx5rsDV29csBoL7qWblH7gVrzkYeMwywYftlyOb3KjW3DOKe7Zlu5j\nJ4zeeo3zO5fc+MzH+ebmimlomU/HPLt1HQbLZDzm7mWhHRdcq5kPQ8yK8B9QeXN92D27H7gjdzpK\nTCmxWWdmUyr7ELKozT0l0RyJWi0iKu221c0o9fXZ9RKo96K1Zm/G0539eSNw9/PZ9SBSDYKRospF\nUMOeJD0uOyf1GUKdkiqLxFpXjwwWa3aGtQ92fUcsChiICKl2vKNRT/8ohwrBqDtQ0Qcs2wEkU0pE\nXMa4gjgl3+74ANa4ql/g+SKxw1LVxUG5erogZKNnaleqwMRTtf36A8pJBUtSz855UE18SgpgtVZt\n287J3sJNUebCzv3mvd9bW40FXzvIWk5uMFknE37UsVj2nE4PAXAmcdhYHi+XbPrHHH7mp3jpKPEX\nf+2v4cOIlbesN2uaZce4zTg5RNq1IuK8wfaqf9jbb4t+z6nXMJSAKKw1Cx6DMx7jEzkrrSqjY1pT\nRB14dSZUAJ+URJXJiAXXeGLOuFR9LEYIwEUQDttAXhlSv+Kl86+wnb/CaLXg7gtHjFZL7NkRzZMr\nRsFiEnB8wMGzC+zQce/EwgvHzMsFbz+8y4svfgR7fsWT3/99Xjx7hbk4HubEaBzoi2Amh+S1pbl5\nzGIQ/EWhbXaRgsovoBhGIxhPhK41NEbNZDEnTAJXPDEZ1gjLkcbKN42WAkOPumAHS+pro1Fs9SmA\ntV7VuEY1JgVTQSnwvJKXWiHsRou70aHsK1q9d2sGx24hyXr4LUbPxMbqEdpLwTsPOJzzyt6kHvs+\n+JrwnbEoJIRlG9EDth4RnA9Iycx6z1gaxFuyj/RlTRZHb4XYOmKwFK+lrncqRdVqrfLpRLXf1tmq\n1KsR8EZf3JKUyZ8AmwpmKLSTgA1VWGJEGwd+V304NdQUIW2EHsEXi8meYaOS4KZt1Z7serwVjUC3\nAZs9FiFYy8gHWq/8Ao9D3E1S+yZTc8LWHnO0/ionn/4xLoBV2lCmB/R3/hmLG59m/umXuf0P/jq/\n8/tv8Mnvy8go4bsJbekpxy/BnStc3tQRVkOMW1x02KxO1OQzNIYmq/OxOBA3EAKkYBjKQOkh4JGk\nZ+4kmZgAZ7HZqOgKYZsykxA0fDXo7N23wmAcfmlhDXaU6RAWMjAvhaejhp/7wr/JF/3f4n97fMLy\n2hyaU6627zGdH3L54AHTccAOQu8C905v4W+cER6tuHsr8OEXTzC/+N+z/ex3c/1jn+DpdktLy8m4\nx66PaSaRo9PP8o33Vpx9z6c5vvU65f5dnqaWknqMtXQTg++ENlhaCk1RAZokz3rrlJ+w7hk2BYvn\n8YXlmU90E4v1Wh3k4hjiQOx3olHLyFmMz3pqKAaPY44umpFClALJIsaRq6BoB3hVWlJCJGOcVhBW\nLN41mKwNQ9F/AGRMKWA9ri4CqnJUrYkxYOokzOBx5k9Z6jTWkBt92CyCqYTdgLK9DBq+op5yT/QD\nyQvZ5TpB2Km1bB3H6J9LKex+mQLkmiAlquQzdVxkimrIsyp/2W4TNqkc1tXMv1K00fn+Y9tuppyi\nilxcqHN6IkJUe61TCIbzqkn3FgS9KYzzqhh0FusDIZzQmUNMaCiTCdP5GRdAY1tiFHzc8N0feZW3\nt0/5J8OH4O7L/Oz3fwV3NMHejNBYQCsqvIVoiJue1qGxcEkJSDoeFVzSI5YzmktIlcbayvnLph6x\nshKFvdWjk3EOHxokR2IsFAOBwGo5IE3BFmiKRZKjT702Ixt1T6at2n9zMyGGGWuTWG8uuHF9zjZm\n+rigbQ1h1PCkz7jDM8ILx5iHX6Ck7yKvb/LkN/5rZtMRxx//SaYPf5eLzQr6QkwDpmzZpsyWLdFs\nVDcyP2L94C7NSEtqawpdK7Rjy7RzNLaqNYdMXAhxK8QVpMFUGDCUbcR6IVWqV5Y6ns46VQhGvTbW\n7HoDKhyyah3FiK1K251g+rlq8XmVoOIlY+rGZow+6MYgNiG2dsuxtYJQko11rqLbdv0Iwy4JTGq1\n+4e5viMWBesd3fEMlgNsInmbKFGFF8jzJpkxqlIcbGGwhexyZRTofCxnzSGohj2o2gSR3WtZufpU\nbRQ7HTqU3cKTdVhcKvh1pw4tlcFQagPJ1mg7yZkcc70JtDElAoVMippPWLxBWgvB6czDqNrN24wV\nV6cbGcsISqO+DOvxozPVM0jg8cMF/dOH3O+f4IcxL3RHPLsWWQAnj0cEiZRmRZE1khKmc/q195nc\nGJzU6mg3/84aLEIqimnLVo++g75uOe6gIaIZk6K3uI69CmI8bRtYyUBJEKxDBlXfuSLEXiAachGa\nkcdbcMVgVurCJEEa1Kp+fP0am6sVsY9ka2nHLalEVu2ccHzC9M7XeLQacGdj2t/5TVy/YfqjP4Ec\nnPLgtUecvniDmweWdCH0RAIOGQdiUlHR9MYtVm/8Hm0Ho5la7CedIfjCpNM0q35VuLoS8rKo0Gqj\nmwCVWSlUYRJVFyM7LJrX3AWySpV9tWdXc5Iet+rCYFTUpFgETdZCdg7T534cdoxFY7U3YBXMKnan\neLS1L2F1ga5uSMzuuGyq47I+A6XsHogPdH1HLArGGHzjoPE1h1M1BdsYsbJjAxaEjPHqbsOJehi8\nSkGtMSpFzlmdZ1VPLth98/f5y/K8QVMy+/NeEZVca4inJfeFaLW5lvNuYlFXmZo0nJPqGjQpyZGT\nweaKihchkatkVScNrjiKeJ0IGINtjE432BLqpMR0SeGe3QkFuFxnHl9seHk65o59xuHtH+bG3f+O\nFw5fQxYtQXoubGQyNeR+rR4f78kla1p2a3HBQ0qsV1HtvcZBUvFOkVxFMLIHqUjM6o+oDVltqOto\nNosgMTOZT+hCoQxFSdj1/FpyUuFTSRQPttNej8SMx0CKmNwiG0cqPZeLJfNwwGaZcPMDBhIHs4Ap\nI2bxkvLWVxl/z8+xuXyHycUX8N/1Z1i++ikmqwcs/MCNG7cI6TGuUQXq2HseOQ1xsVtD7BxFoOsy\n7bwwbg3TIHgvjFvBCzjj2fSFmFERVwaRHXnHAAp+zdmpYVmK5mPYgKXi00ohYGqgS50kVEaFcics\nnupMrX0urQxKrRhsHYVrn0n/rce6otBc+35DlK2wGK0UrK3ZDvXh3zGgpUJg/jDFwh819+FvAh+v\n73IIXIjI91bq82vA1+vf/WMR+Svf/ssQJRxV6rI2HguRnoCnsfqNZhPB6Yy2CYYULL4NOmKyllIG\n8qCz3cKO1W/qD8DWMM68D+Q0Vf0hInVsWF9Tcc8XJyskXzvI6KwdV6cRUerDUs0wQ6LEqhR0FuO1\nwpHU65FCDD4HSmmQEnT0V2rX2S31BshAV4i9gXbGgsIqOUo7Z3pwyOG1a/TlnP/UfpFXvw6/8Vue\nf+U/6pn2HWGaKXmDJyAu0A8JF71+Y7nsZqOkLGB11GpF/ypF/fvGa9VQ6sxdE421ohER9UE4R5HM\nELNyKJIG4hiv1vMomVjqQu6NYqpSVo9FE5A6qj0YHzI7WDCeX+edr95l9Tjyyoc/xNP+gqebntOT\nMU+/8VuYlz9FiAZz+RWWN29x9IkfZCxwef89jq+fsDTH9NHS4CjW02SHmERHotluGLpC28BkYvAj\noRkZgimEJtC0ptK1wDSW5AyDVXhP2T387JSx1Bmk03tVir42Rva8xV0T+w/c3bUktUaPkbYMUOX8\nuagPw1bAirV6nHQuYI0jZwtEdKJg9ouC2+VP1sXBoE1Nqai2938Jen//yVYK/wPfkvsgIv/67s/G\nmP8CuHzf+39TRL73A38F6EiyMZZUx1tJMkOJ9DKQRar7TkdBRiBYS2M9xRckWIo3RGvYDokyKFbs\n+WtQyy1jamCnYxekIRSs1eOAq9qG1Nezdw3k0ILDgi21vDPsDmtll/BTIEbt6Bejc2prLc3YA7WR\nGXN1E+qcH0kYHFI0xMb6AWlHpBRxnaFf9tx78oBy/ArbfokNHefrNV9OC36+eZefad7gr33kgP/q\n7474c6+smD6aYPyijmSfj8OMMfRDTzCyL1mVLKyiJTFasRTRo1MWVFZXtFryXnc5yRpLX5I2r6QY\nNquNCqCiVkw+GNUvOENzEIhDUfZgWy3EIpSxoxNDf5W4yAu62YTj+RFvL97k1vFtHr+bWE8jU5/Z\nvv4m9oVrXN3+IWa/9avg7tP8wL/DmsDpo7s8tC3Xx3NaN6FMp5hFZL0Z2IZM4xzBZrYXd5m+eEQz\ngfHY4xrLqHO0xqBARJ0ORCna/HNWgT2AUKnWpeyPmXqWZ1+ai8T9a77vBfD8odR9qY4JjfYUvHUq\nPa73nWCrwEm1C7v7E7RPIe+7l43VY5weMVxV3O4ezDq+1K9sP23S6vlP0CX5L8p9MPqV/xzw4x/4\nM/5zPwkEabDWsyorVnFgnXttdpEQE/fn+yZ7oNBYrze/MWSvo8BxZ3XUVkk4xrYYE7GuoKcTFR3k\nLGAyoSmMpkalrN4RN4XV0rJYCXGj522DVXclAr4gtYlbES36oMSiuQY7D0b1F5QSlbln9aFJRROE\nyBFCpCSh31raBprg6c0EVy6ZbwLrbabt7/DWJcx9ZHM15u7VE84+8yr3v/YV3nq05Cd+8jprG/Hv\nZBb5nInaivC2RzYJ74SNbGmyUntSdTemQR+anU7eGQc5a+kftQJqcKo9MKoBySIoWDeTNkDQXU+S\nMKyEpmmQ0uMcZCfIFEzyNDmTck8zntE/2LAeCSPJuFHHZuQxJbD0S6Yfilx/6ni0esDEDFzzK8pp\npG8/i3vnd0npLnzPjzF2AzkuefKsJ1y/hpnPaJcXrA46fN4SBss37TmHdo5tx8jyDgeTF7maGHIj\njAZHGHtsF8k5shn0eJSLpU+ZWBd56u9cDFKcVpQUdJaV9xuErUnPxoOlar+rVBlsNZdpTqezFof+\nLijaLdmgMnSqN4XnUfI7Wb2xHjFl30z0GIp1OijeaaBMrWicrcfm6sfKolWeWqY+0PXH7Sn8CPBQ\nRL7xvre9Yoz5HeAK+Ksi8o++3QcxAo1pGGRgiIVNzGwzFCN6fqs5fngQL9rRH3ncxJCD4tIIhhGO\nkiPbbWIrEWym64TxJDAaqWch5sSmV2jp4ZHj9KanG6uhZ31VaLpAIlGiahEM2gRkh27Te0LDbUVt\nx64i4HYJork2MJKIjj0r1KWgOy5Z0eGNVxRXSdDbHolP6WyipMLlw8Sr3TViEtpuxPLeJR+Z3+Tw\n1sf49b/9yzw+nvADs2f8/A9khnMh+DkuRO3AY9SVuUl4PCEb4qDn/FFwSpuuITCuqpFSLorycobt\nNhNTwRurmQO93pxpOzD0FaHvgmo8cn1BzABW3ZDbNZzenvP08VaFad4wrKsidIiEriFfaTO1rDcs\nh/cojedxuMvxS0KYHlIe3ubOy5aD175J+Or/jPzbP0OIh8Tzu3Byk404Tr/8NsuP38SHS2arGcv1\nQ6btdRYXrYrZRjAziYbC0FhsziSb2QyOCNpErJCUzQZWW8t2UFiKFHVKKgFc9Emp7STVDNTRXy37\nd+W5VMOcKaUSwe1+SoUxGF8x+6JVo6kYfFVA6s/Ce78XN5VKVHLO7I+a6sjZ5UDArizeg1jqWzWz\nsuCl7BvsH+T64y4Kfwn4G+/7//vASyLy1BjzeeCXjDGfEpGrb/2Hxpi/DPxlgLFv2Kw3XK03XKzX\nrJPCLuvRF1sy2Vrt0tuEVIeYCw7XGWwHuSrASlbKksuR0ApHJ54bp3MODhuExGK75WKxpuTC8anh\n2hm0jd60kgp9HGhay9YZtVAX1UDgXRVGPQ/l2Jvd6rh0P+KsK7eiuSvdyGqPgVLHWEZDYqwYIuBs\nps+RbEGy8OyJoY+e1bCmN2tm8wlP7j7ma3/n7xFPruPlJcqXX+PZyRnJrTl4sqRpWrIXTFFIq7dC\nG1rKkLSnYnLd3Zw6MQsaV14KMemxRwdwu36VwWb1W4vRaYuvLAIphdSDEau2YJ8YBaeLwkKPU1Jv\nShsatquIr0fDdYm0BFLKbC8Tp/0n+Madr+GOX+Fa28HD11meXefwzpwnw29y+K/+a/T3PLcPb/Hu\nR88or32N67/zDm/mGaMXl3zqpZaYA4MsmLYnzNI10voeMhrw2wu6fotvQVKiN0JZikraMypcGwzb\njWO5FNabzDBoshMJTC5qLspm//BrUpMeq5ythrtS+1KiIi9T8ycLXjeQGsenWAB9bRPaxFYltFTD\nmdQwF7Xs57Q7ruhRD6mqSYQqwAZ5rpI07FSS7HtAe73NB7z+yIuCMcYDPwN8fve2GhfX1z//U2PM\nN4GPAb/9rf9eRH4B+AWAeejk3uVjlkNiWwZitTy3NuiLb20NUgGx2kyJccBlw8gHfOOITohF8G3B\nx0IX4ODQcvOFES/cmDAZQy6FWd8xWUIsA9040zRZY7ubQOqEISYO5hYTGxZJSLWzLvVFd6bCPr0h\nBIsNPGdt1jOdsxZjY236SA0KpTb80B9wrrp7Z8lisY0lJ0dfeiRZlguIJbBcrzk48rhWKdS2LJDv\n+gz/y1ff5LvOX2PmV6wk8dB2vBAF4xpyjkhVf8bUk03RKYeFpDY8BataqfQerYZKEmKW/a6WRanM\neRCGlBiPPF2jqVEmGWLKmFxoRxa8fq/etTQuc/7ogpOTI67uP2Pdq7M1WENoHNt1pnOeqQu4JCy/\n8ZjD41usGFg/fsTBzc8wlHO2D/4Or37qp7j33rs0n36Vu00k/JO7xPvvcXl8yLg74faNOdPDWzxK\nK07nh4hJnM4N97/5Lm7U4SLk9RZpA+VqYFOEYaGoszhUVFmEFGGzhX6rUmgdR9Z7vfoXjNH+l6Wq\nVK3FO32HJJmdx2nX0ypSG96YSl9GxV9SjwnCvgewQ7IDtWIQcqq7Yv2oGv6iTUPJRiXn9Uih4w4t\nB553GUwlPv+BN37b649TKfwk8DURubP/Eow5BZ6JSDbGvIrmPrz57T5QIvNMlkRvKTqkx6aCx7PT\nKRcrVXmnTZ9YhFAMrQu4NiCm0IiCMIZiCCLMTgpnt1uuXXN40xNTxI88pm1YrQfdzYshOEc3b2i8\n0DQ6Q7Y20wTdQdbRUoaK0PIO77SpFloPLuFxqlMQqVHshVy8ZjZS9pWFL426DSvRybFj70GOhmQb\ntWMXS58SgUCTe8JW5dFZIna65cPhir/pZ/xLTeD77Yb2saF9Etj2QjANxieMKzhbGGJSn4JR0q9J\nViPos4bkSNKbTKPjdUcsVW7ravMxDkI/CF2T640rNK4hbTd4r2rNKInttkBOOGdovWGzuKxOQc+Q\nelqNVcZqW4i+X7OICx4//CLf/2d/hG984S3Ozz5Nb1/HvPlFYM3T1X1OukQrU570PfbqKwTT8ThO\n+Mj3H9FMWi7KAfcuvsTHbnyMu/2GGZn0zrsYN8E1M2Jf6NuAiT3bZOgXmdjDZiuVnKQbxpD056Ca\nDa10jNNnrRiLs7Lne+rxQWisVyBsPTZI0WYzpUroJWtfymn/yzgVh2GMqhSNRQw1ALdK4I1Bga3K\nVVBZvGCyLjIigthCMdrT2jW9bSVnF1RwZoU6mVAGwwe9/ki5DyLy36Lp0n/jW979R4H/3BgT9cfO\nXxGRZ9/uc4iFOFYEO0nPuT4FZNAfTqHsGY6JhM1CLkIsFp8dLjvoLLOmU72DiySJjCfQtIl2VHAU\nBbQkwfYRa3euMkvXOkadIQQoYplsE3no8WLxnYOtoV8ELYX3Z8T6y3qCCwTX7j0NO9S5kYyQqr5d\ncFKPPbaSkSsa3bgeKUp8tmScb/QGXG3J046xCSwdpGGNjB3HZz9K/8/+d96+F/mhz17j4tUNk1ww\noSFlXbAQBc86b4i90RtVwGZ1C0rthZSK/EJQAC4qaipQ8xp0JDmeGlzjq6uzxsxvhHDUkrda0nrr\n9fOmTGMcfVKrOUl5hcUmJl3HeiiYTV+JyIl4uaIgAAAgAElEQVSD8QnvLiMysUyG30Yu1/jREYdp\nzkPpGY9fpt2siZf3ONg23G8mHN4449AWwvwW31g+5IY9wNkWa7Z4M9DGDb1tKeOOTYrEpJLtHA3S\nG8qgjWVJ2k/KYuuCXFWDdXc1hmql16jAJuiRIXjB73bmqtGQuuhBnQLUxbVU0R27Er9qCkr9BLtq\n2NWFQclMhuJy1THsdAfPfRL/Lyu07I4NRjcn2Ynz7HOpxQe8/qi5D4jIv/fPedsvAr/4wT+9XsUa\nXRRiwVBwIkgRfeHF0oglS2ZVBnobFRxiDUMu+L7Q5MisDdw4PWAoPau4ZYgWL1u8bLFhynQyojNT\ntn0hlUG78UmnAc4pBjsOBWs9Z5OWSR+56JMKgTqlPq2XEUkGb1u1WhuLr2TdXS6hqzFdZHU7WmvI\nFazZWOUWGKM7hDMGkzNiAiaMSJtLxr4huwkHRO7ffYfmkz/M082CnC12POe42yC+589935J/9IvX\n+DMLzyuna/LxDDcSNtuMuDV207Jymblu3hovJpD7jEuGqNuf7ihO8fOStdgNtBSjY+HGt/jgcSMd\n3W5WEVMcOWe8say3HUdjWG22jFvL8hK6yRRvtlxsHIHMkbMU70hzh0mQnIBxmLLFd56DF055Z2vp\nnl5hPjfCxyk8uWBz3DAZtZhrI9beMdx/wLMtNDfPOD4UnjWGW1jk/kO2Y8+VN5iLBePZKedzw3zr\nyLdnLNOC/h1YRMEPQukNfXFISrW4N7ik37tFQHajZbM3IwWvqdzBq1itcdr8E7uzJqs7MonGthVR\neE3ZTQUMYPV+kQphxYCxCvttvNMA4/qwZ7GIMQw7YVltcptcKtpDMDbXNOn3VQG5aB/OVGaDsP+e\nPuj1HaFoFAOxg+JUaSc7FYhRxSFFo7qyyWQpDM6QJVNixqbM3E1oJ5bbL7a40LBOHYvFmn5tySzo\nt5ecHB5wNG1ZbnqOkidMppQUCQ66rsWmjEuJ4Ax0lmbqMVHzIOJWpaLGCNYXjXpyur1qeCq6KMjz\n3y5oB9k5h69NnmAh+MAOiFYjCDBlhLhE4zMj67jcXHJyDX737dd5sV/ySAbG9pD75ZLuSeHpta/x\n+N1jfufqX+aXHv0K//Foxv2N5drFgvHZK7DVSsgYiEMDflvl3mZfahop+vlTZQbk6j1J8jyqXp9d\nXDTYtsWIZ7XcMu3aXfsE6QeydZAd62WmGIsJA9lHhnOhm1tiO2CD0G4ci17oJg0mCm2Kqtr0E7on\njxnfnHPVdlw8fZfJxCHjU9pR4Oio4c7X7tNsIsOtT3A269keXHH78Pt4cu8d0sWCdnSD++tC3D7h\nu3iVd33hRzYzJtdPeOvtN3j6YMUg0Bqw27zPC8lF9u5b7fWUSv9mT1G2ThuyKiqC4IwuEM6T66gw\niyiOvdSmYt2ad1boXZMyiWBrRLdzCkDxvtHwll3vCSgp1eagAmEklVrEmMrbrD0pUROgADnlvdLR\n7FS9GASPNR/8Uf9DDCr+v7sKwtYXUiikDmTsYOTJQdianlXZsMwbeomYAIldqGeGknG2ZzLJXDuE\no8PEybHh5LhlNm3J1rAeBjbbgeVqwXq9oOssJ8djrp/OOTqeMh+3HB/MuHV2wvHBiOnEMRpB1+mN\nkfpM328pkik2I7bqfmuTZ3dkkNoMKrIjcO7O5xYq1ltbJK5aawPBt4oCt5EuBCwdzjSMuwyXK2YP\nHzOVhsOmcP14wnxreeu1e4ThGuYs8HcfjSmHYG9Fcim45oRURlqSioXBay6hM89H6EYrMAaDVFfq\nLuEpi+Y7GFtoWh3xxj6R+lTR7nrDFjJDjoxCYb0Y8KalH4TRqNHELDG4Hnx0bIYejGP7WIiLgdAC\nbWIUL7h99BJJPM8u3uNiLoSV0EZDPzXM+i2zk5e4c5mwj94gjc5orlk2/Tnu6BphFFg/fsakEYar\nh1wtI82J4xhhs10QsFw7/TBPFz2rKyHHwLZ3xFRxZ/Xal+NSEf47V53q3qqhKGNE3U/WQnBOk8CC\n03wHI9ScvWrSM/vq0Tg1w5layu80CbusxxACrtrqYWe62/l9qhitftydjHnX93lut959L6bKq6v3\nwmgVY+SDnx++IyoFDGSTEacFXBKvEVylkEVfjCFrRp+xz+e8TjwtjnHjOZi1TCaBIhEjliE4bUgm\ny3I5sGjXdLkjF6FYy7grdKORTgay0DpHMIoke/pgxSr3XPWGq3XifJHZbDSmHCd7UrQpgrN+r1+w\nplKjRbFuITR6Qwl7YUoWwRRd0TVUtIBcYhjUVLTumUxaUm9xacHWgCTLo2nBecdX773B9R//Mb6v\n/xIXlwuehldJv/c6x7OA+Wwgj5yW53EgtJbgG4a8UoxdUqy9GChbV/XNCW8N1hel9wSjKV0W2tYS\ns6GYhJVESTBttAk2noyIJRI8iDMsrnpGx4E+ZUIXKEuHzcKwzYTRiCcPesa55cAmlpsMB5lpvqQJ\nhWd5y9gKftSx3ayYNS3rYhnmY6au4fKNL9K4l5l1Dr7+f9B99idp/ItIesr26YKzjx0wjhtGk45p\nN6XDcPt8yUV+xIfGP8KQA5t1pjUe2zjEFGIsdEGBvtbUhzE/f7hqraqjPldHjLDXDDhnNUAIT0Hv\nU/13sgepgKlcg4D3Huu06UetQHwIOB8U3mIdpkglWelC5Yyl4OvDrUcZnUDUiqQapPT97X4jclY9\nKMaq1LxIwZg/ZccHI5opkKWQTQGbKdZhmtrv8Q5JjmSSRs3bgnOBtmlommaPvXLO4qQlpoLYiHWZ\nqTc0zjKzhcPGI9axiAmLMg2c84p6M4WcesQmNjHz9Fnk/sPIo8dweSWkooGiphSiDFCKEniyxRe/\n7xx77/F7dl7BGouzFjEeKwpGtTtgrNHsSuMi1nhyztjRmtQZupHDLN/l3WfnnH30Zd5pPO2ycPDi\nDcbyiL/7f97h1RsntD/+08h/+dsML18R/kJiGB7RjTNpEcEZiixJfXV9ZjQF2RdSSJr+VHTXUdit\naKx5MPRbLV/LAKmvPyTU4SigUw2EYjLtuGE99Fjv6CUz8zOevnWJ2DHOC23uKOuBvotMm8BmZcD0\nmCcX9J82pLsXTIvHlzEXzRUpRTr3IunkJudvv0l33hOun+FWX6a1Lf7wiOl0xOqbd1n2F8TmlJOD\n62waS7ee83QO43cfIukp93xH2Sgnw7ZRk7lM1Y1Yg2NH4NKGoKkPlvoQBFOPD64mizlvCU4XdG+r\nA7JopeCMr4G9pS4MluC9VgLOa+9GUOdj8PhdlWA9TpwmjcWsO3utNIQBK0oAT1KUtWCqBLtQj6Iq\neTZWJ2BARcmj3ggJIB/8Uf/OWBTYacB1ypCtVcJusWSrnfsk1RYdHMUIIXhC09E0nkxhsdLgWWeE\nlAuGTDe23PQjjiZzjkeWWXDY0DAtgYucGTY9xiVC8MSS6fuB9TqyWmUur4TLC9is1f0IBVMZZCWr\n5VdHkCqUslWaqtMF3aGjG3BGdwHnAsF5Gm/V0OW0nFNTjULosvTYdkOfCzO3ZZqfsXi6xa4eUfJt\nTsOUN56Bv/ObvNm23PnmOZ/78/DscwNHzQgbL0nDOdamfYlKk3F9QHJSr0N1zbkA3tZ07kEfdh8C\nw5AYW4+JprIHNEYNyRjjKZLwwdFvNA7PBEe/GpgeBTKJ2WzCsEiY3uEOE5EElx0v3LzO49UjLu3A\nmJsM7j7+6TMWtsc+uWD04nXuLx/RyCWYjgss0ycDm7trNvEFzsrXeVjOaT7yeY6DQYZnPHnzKd3x\niJOjG6xXsB4WvCLHPAA2D59x2nkeuYbVgytaDK0xbJN6PloXqoZAq7dcO3/Wuh06cQ9c1VJ89/+6\nK5u6IEg9txtj6xRB7dA55+ebhN8BUBylaMK090pG8k6TnkxSc1oxupkoAqDC7mp/Q6cQ2ujZ6xWA\nHW7QUN9eUDanMTrao6m/P9j1nbEoCLjBkk3AOMhWMWDOZnJIlJQpO3dSAj/1dE0DeSDnjMkt22dw\n//EC1ySMS4gIoxA4mAROpyOmNmFL1m4vlvV2zXvPLpEwYTR2GLGst4Hzp5E7DwbunxcWMWiepI1Y\nVx1uoipEU1S/butYcwfezEZX8sEWQqMloxUhOEdwmgTctR4RDwIuGByOwgbjNiQyXU5cuhXWb7j3\n9uv81Pd9lC92cP3FNR/62A/yxS/f5eHwu8znL/GlX/l1vnRtw08XRYx1FHqvraKwgtK1hD7T90Lw\nltUyYoonGM3XsCS88aw2Pc5bRp1B1hFfJngjLMqaZFtaC8lEGEM78pjLgi2Ovk+stonD+YhuVJDN\nlqt7QjKek9Zwvw/Mbn+Yrn+X2UOQiaXtD9mG+8wnG+StJYw7ro4zsnwAjybk5ha+61kt3yJeNRzc\n6lm5nvH0jOnZdbrxCds793hy9RYf+eRnONjCe52Q0hXzyQHviRDWPfOjEW9FyE97bAcQaH1BiMiO\ny1+qyMgobKdgFaVn0l6PoNWe2Z/Xi61KV6NScbF6L2DMXrDmvaNpWtp2RAgdaoXSaYT3GivovU5/\nStH0aptN/RjKZkxSyAy6SO1AucUjounfuaTq/OW5D6NCWnf8TF3o/oBt6tte3xGLAhn8ymn2YIBI\nwqSMuEFNSPuVHDWeWBURBd9gJLNcrHEW7t9dEdqBw4PAbNbRBMe1ScfxJDAznrQZWC56tutMWjtW\nT4THaUMzzkxGhm3ccv/+lsfnA4s+s8mQMbhGffPBqYjEWqOLBEIp8X2zZ9n3DxxCzlE5DEUUd95o\n51hMpjCQjCGIIRSLD1quihQKEZwnrB+wfeNdHrsR18yax+4mPzt6jb81/iwfevYF5JNXPH37u3nn\n8BPY8e+C1Qaat0ISbXKSC32O++OVKQqFseiMPkewXvX/wzLhvGezHHAScUk1DcEqQahIwgVLaANb\nP7C46gkJZtOW0FrEOoZVIa4Lk3mhRM9LLx1xnt5lsX5KXnmGdSHeepuz+4bff+kjlHZgfDBh+3jL\nqNwmN2vW5gFszpDLEd3kDuOpY8DTHRzj3YxWLL/3+utMrx1xeHqT86uITMZ0feHZJtPPlO6c+p7+\n/D7b/oLxHHyo9oEagpNzpuxdC3VTLXnvgjT1YTMVq6BKVZUfxxRrBaFhDcYarHf4LMpVCJ7JZEzb\njAihxeBIKVFypm1agveYWhWoJVtIqn/Xr0U0Yo7i9gI3ax3WlZokZd73W3sVOzHcjrS026jct2oa\nvs31HbEoGDE0W0fxhVxQ8jCFVAyUymC0YI3Heo+YhBGLsw2ILiDeeJbPNji/4nh8yPF4zGjkOGgN\nB5PA1Dui9WwuC3nRky4K/bnn4WVmsL02KYtwedmyXjkkZ02fEmUqOLeL+tZS0ltt5JSy053X3r7Z\nzYad4syk6hVqYEcdImuuo9OuMpXdsNNLW+PANJTymJev3uYbS8PxdcPT6z/E57/492k//imOvvEm\nt2/+JR4f3ePZ//0IPhuwPlPSltAYknhKTogMWmXVTx+sxeF1Fh+1eWidJl/bYggmsOgHUhlwjdPk\np6LsySSKdRtixDaO0VQYiWc1DPRDgmxYXGRGjJj5wIN0yZm1dEthcSX0444OmNy+4vff+iz/4NrP\nci7varVykXFiOe8ek4ylO78N6wsmJz1Pnwx0JyeIG3N8dMqDb7yGi1vCh15kWGXMtWtsr845aY+4\nw5aXTIefeMy2J33zdRrb041197RVlZQq9r9UoU+RqjisqkXj2MvZrdWxX/Aa1mPqVKnUqkDqRkDd\nLKxzjEZjJuMZ1gasC4q7Q/FqwQU8TulXSVQfUrM4bSWQl1LIKe3j/XZA192UxNSPpf0EizM1WK6O\nI/fmrSpw+FOX+2CxdKklpYGYEqUpeAfWjdiWnmyiZkmaLcVYihj6uKHkiJ9Yxo3ncDphs13gO5j4\njqPpjNkkMG4GfGs1gAQh4ekHx7OHlyyXLZdP4dlqIDQqzinJk3IgFPs8kp1CdnFfDSgcRfsLzrZ7\nrz1oFYExNWBFV3Jf7bXeKDYrBE8TDMEJjVWwSTGp7gYe4zJ5XUgHnstf/x8J9/4TRh/9OI9PEzfe\nfZ0/+8NTfuX4J7DrR1w8eMRrl9dJs0dqvkqxjiNbrFdDTBMcsZRapj43yvigC1wWPZzlnAjR4Y3K\nt4P3FGuRmEkJ2rYhm0TfD1CnskPMWAdE2CwUm96GwPJJT3/LkRiI70FwAV7MHC4Mfm34+9/7Fzm/\ndpPhQeZkMmZb/jH33rsLN844PLuNW19wvv462zziYP4q6zxlNJ7z8NED0uUTjg8mxMMpTZlwd73k\nehyYN4UH88whBTdtsOJIb7/NqNUHXFJhpwRQjpfs/5sNIIp718WACkFVjUIbtGHovdu7Y4sUUkmq\nAUGwXicNTdMwGc9p25E2AKkMD3HqnalehZIVPJNiJtXYwFJbh6kUYsrE2JNzIpVMKTVfcufJMDvw\nit2zHKuombIXK+06jv8/GKL+JC9vHEcc0Q8rtmmLLwPORdZeR0a+E9oDz3js6Dw0fkoaCv1yQwiW\ng8MJB0fCuLQcTgLXDlpak2i9Y9R2tJ2nDJFihG0aeHa54XLVsl0FZC3Ei0h0YBpH41Xs7qxG1uMM\nhkKoUIxUYbBK21HhilRk0/MznM6HvdebIDiPw+ClKuCsx6NHBye6yBixekNIwZSC9Ykhez46X7N+\n9CVulQ/xhfEBVzdW/OR77/DLt36AN7/5y2zPX+aVo8hD+1WuG4tkS14NrNdjRp0hb8FKqYI2g7Eq\nb/ajluBhux1Yr3pw0LQWSsEZj+8E7y2rbUZi0aSolBlKISZhVK2860FogjCWjjhEkk1ku0G8MLUz\n1s82eOdopkJjBDOfUHLir6efYvLoLQ6uHXL/3n1Myhy+8BKja59nc3nB+upLdPMA5hopZmaHY7Yb\ncKbH+QHbNlybnfHkqmCHHjuLnOcF8uCSwxsfZrowPG4PiR+6jf9ilf8apSztF0F26kDqwm5ofc13\nCHZPQQpBF4WdTBl9Vw0ZUkG4Lsil4L1nNBrTtSPVovigR68CeFOzSISUM1mEIUf6IWJqI9iws7Jn\nUo7EvNbFJxWyZDXSaeDk+9SM9b6jVqT12h0tkFqRftDn8Y/5PP+JXN4EDu01NtIQ8gqX1li2rPMG\n1wrTA8/Zy1POTkdMxgZjZiwutlw8OWc2EU7PWk6uWUbTaxxO4XgesKXHJsGmGaUXlos15xcbLq56\nLq56LjcTlisgGboQME2LazuwSbUEu/qr1O6vVGJuFnLJYFTBBlQJanVRYpQNaB2N1xlzcBYngkfh\nm6Yobt3UKeBQosa4Ycg5VfS3ZbIsPLMJ9yv/EPMX/i1aP+YfHn2GH/vKLzD+nr/K7E5HW57yewfX\naVctoRSG3lHMgMgEj0HsimETscVibKEUZUqUXph5r8eCBsDSdAHZJPo+4VshD0m5D8aSsko3rTO0\nzhCslr/OGhhge1HwxjEdW/p+CyNDu/aM3YzhWk+Ja7a5oymP+KXFv8/do++lPPo6fjLgmitWlydk\nd0y62rJ8ch+fLUenp6z8hCg9VlakOGHuDSubmZydMiHwbop8qAmUsMZI4PqVYUBoLwvDjRt0n/gw\n0lPHgWafebmbPJRSTWyodmDUWXxwdbRsVEti1a+Sa/m+Fw0VUBiwCsWMsWqY80Fl3Bg9ZmKrOU4n\nHSKa+RiHzNAP9NuhKkxrZ0AgZmVjZGKtREpFBOY6hKwtRbMDy/I+f8PzxcuY9x0jPujz+Md+ov8E\nLms88/YIFxUjM9hEkZ5gPOPjwM1XA6+8esD16yOaiaYWX15k+ltHjFrh7KgwnwgHp2PmE8/IOths\nCYMBkyjJkXrh8mrFs0VimT1rWXEZPVvT0s09zShQaLGhNoSKAmPNruwW3f2DGGJEE32NIxrBZiUV\nqwMy4KzD4+jMCFNBKso+8qqlqEIUSr25rAbbase4IDIQS6EZlmymgdGXfo3x6i7jo9v86s0/z3/4\nf/09Pvfihq8cnZAvCi9NF6xWcEyEc8gvGMbthNVloj28oN8YDlyDd5Fl6rCyVqpSX/C20BjoU2HY\nCu2m2oBbx7DWvorvnC4kUehGrZa9FNJQsBthWHmiTYSZYFyiMZZmA+ePljzyDYcfjfgLh5sMhMsx\n/5P9dzl3hZO2Qc4HhqdbcInGf4y4uY9pHjOZf4RkE8mtGJ+9zDrPGNmBtmzZdAf44wP64YopgcVy\npaj26YzmcMMIVL896ZhIpBiNfO/NWvM4CPh9eW3ZkcKdhzAC7w2j1tM0geBdDSV2iKiSNtcHU9Wr\nbq8o9F59DPZ9ydCmlL3mAXTxGWImp0i/7hlWGYlCYsC5oIrHkkmxJ5bEYISYNJ0r1VQvZ5Xo5I32\nMJQha9kVMdY6xchVxa/+xZ+2RcEa2q4jl4Eh93gCwTRMJgOnt8a89MqIF1+acnI8ITSGIW2YjD05\nCqMW5hNh1GbmRxOCFc0x8CokcShP3+AJbcdoKkzmDW7ZUxaJnBKh8XQdFBOVWei0gQgg2eGLqRJm\nVTGKMVC00eSophkLxgWMTWAKxmaKmPcJmwyhCky0Vi2Yqk5zsSj5OaVaomr46xPXMZ2dcH55wbO/\n/d/w6n/wn/He4Q3CwYYfeOvX+L3P/zjy3m+wWK64mLW8tCmIs1xuWqaL+ywfZEajQDdNrC4SUxdI\nccPIKLDGiGUoleSTDGmtgiY1AHkGIkNR+rEvTg1r2TKse4J3SFI8eiwaRutiw+I8MRpPcW1G+hXT\nT32SaX/B03KHF2Lky90P8hvLV5k/vMP2dMlB7jiXLcbeIuYrNv0zghtDa7kynom7Tt8csL5YcPNk\nxGK7xDUBOGC17MnSs7x6xujwJutt4siOSBgWRpj0wtU2Et7XA0aUzbmHmZo6zXIQgtC2DU0TGHdj\n2rZVChKWPOj5n5IQURq4F6mU74pjN37fP6AqG3PdpaVYvXeKNnjjdiD2A3EbNWrQVPS9UV9Pzokk\nCTFF/5yokYR1z6/4d2+cTpaM+wPuSRE93gpGE6r/EKnT3xHeB0FZCQQDXv32TWOZzizHpx2Hx5bZ\nLDMbC5PGMR3NOJ7NODyaMp1PGE/nTKenWJ9ZbVcstz2ElmY6pxtPsbbF2YbxeMZsPmV8MKGdzvGj\ngAQhlkRMG6QsQDYY0yNmoMiWwpZiozIK7IBxEd8q39G6gcbp28UNmBAxIVKs3qwiAyIRU2qajySQ\nhOQMlRClubWlIuy1nI1FyBIpA5gnnvWtnq//6i/zue0lb0++n986/BQ/tXyd9k7P5LrnSfu9/NPz\n25jHQWnFm4wbLZk+aSgPrjM9bhGfScC401GkLxBTYd1nUrF4aTHRkJPQ+oDNFikG4ww2oKSimInr\nRF4J9CAR0tYSWo91QrAwDIaNGPpt4aVbR/Rv3eDeWx1HLxfc+ib/q/s3eDy1dJMLTLlOdku66RRv\njzF2YDz3jA9PKa4gXYf7f6h701jptrS+7/esYQ9VdeZ3uPO9PdADQzM0aQIoboKjNGArmJAQQmxM\n1FYs5MQ4IYktEjtRomA+WMRKpBBbISgOdmzSYDGDDTbNYLoxQzfdTdPdd+x77zufqaa99xrzYa06\n70Uy4SLx4bKlUp23Tp1z6q3a+1nr+T//YXaC30S6RpgdgDaOZr7Hcil4p3Buyf6iZ94d4nOAGnM3\nsEHlADliNZRLu3oVpMKe3cmSjc20raLrDV1j6NuWruto2462m9G1M7q2wzT2ioQk2oC21bZNriLk\nry7GusOMFUxMoYCTbpyYthPTZsJtS3BsDJHoS26ncx4fIi491KGEGAkhlhFqSqD01euwSmO1phFd\nPSALDT2lUJ4fXz+WsDveEEUhkdjqNYMZGcyW0HrUnrA46en2GmxXJgHGKmZzy96+YbFvaxFYshnW\nxcpMIGpNVAaXhSFlom7IpqHtFyzmc5q25DZqHF1bphzT6Bm3xRsxpuLFkNKEjyMxjyCenDxQqNNW\nB1ob6S1Y67CNQzcTYgfEDuhmAOPRjUebCaU9OU+4sGZyK5xb4dyGFFwZfeqEbgrQ1zRgddlp2OyI\nTeSRdp87H/0o069/iNljR/zEo1/H229/lM/91Y9w5+QGZrbm/957Bnc5olOk21gihj0FZy8tievM\n/rWO1XZk/7BDdWXMGmPC+2LvHnMsJisBjDT4bQCXaU0xuhFNCdRdB5RTZAcqaiYPySpcToQYaOYG\naScUHpHP4+7t93AWj+hU4PxC8YGLr0WPmfO9J4hL4cHFmu15wGhNCNuysnZzpjTSWiE2DZxvuHbY\nsM6X6Ajd/JjNZsRIxG3OeermTVrRhLhlPu9wfoP2K8wssH7xZZIU3Cbm3eodizpSBKWL+YxtNLYx\nGGNpmloQ2o626Wi7Htv22KbDNA3KFPt1JaWnT9WmHXYTgkCqF3NMkRACPnqCd4zjWG9ljBu8J4b6\n3HofXgOGFku24sicKz/BKINW5kqLYeqoXHIBPHOKV8UoVDu5Pwx76Q8sCiLypIj8cxH5HRH5hIh8\nR338WET+qYh8pt4f1cdFRP4XEXlWRH5bRL7kD/obkcAyX7Axa8ZmIPQOvZ8xi0yQiTFGXArlIpWB\nrAc8I9tpYLlas1wvWQ8rpiAo1SG6ZYqZ7Thy6SYCiqbtmfUde73meF9z/SBy80RxeKBRCNPWMw6O\naetwW884TEzDwOQGfBwJ3pN8KEEmyWMItCbQ2Im29djGoZpSEEw3YWcjZrbB9GuUvUTMJUlvCWzw\ncUWMW5SaaJSnEcVMG/asZb9pWBhFryCqkaRGFkG4Fh3P/fyP8q4OfuqxP81L9oj3nn6Kg/MV60eW\nfHz9DPdXLQyBmAzblZAej3TthsvnXUHTpUxKdCeo1mDaAqxZK4hO0GS0UXgXcNtIHEtbkVys4q1i\natPRkbZSwNIE3gdaY4kb6IylWWiGLpJmTxIei9x53hOfFV6YvZkXjhf0vAIhMEyfxfoTWnODcXuf\nxf6MbnbCcjuSWkXXdwX49I62U/gQkFs+6vwAACAASURBVNkN1ueevssEd4pyI8fdgiaV1HBrG+7d\nvUW4dRsz0/jnb5MsuBjxIRNSrgKi0o/v9AdN29G2PX0zo+t6mrajaRpMY9DWYNuWpumwumBGiV0G\nQxnlphyIKRCTJ6VACAMhDDg/lds0XBWEYZwYJ4/zobwe8lV7mlLx3kixtBMpqmK4EoVUM9k1prBq\n465F4Iq+Ti7tRoyhiP8S+BQJ+Y8WUwjAd+acf1NE9oDfEJF/Cnwb8PM55+8Rkb8G/DXgrwJfS7Fh\n+xzgy4Dvq/e//x9IJQNAVMRZT+oiMtOkZmJIkc2gWa4DjQ64bBicYr3xLJcjrgRQY4xnGy+xytCZ\nQKOE1BtSgr3G0htF1xiOjxYoNPNmpLuccGpgWAVWa8dmcmjTFh+CVNBfawujrEm6JlGBkmIpL2on\nUEmIKh+s0pVAYgJiXKXJFbBK5x5EkbJC5YTB0hqFzQqTVSEQKUiqobMJIy3DxpMOPMf9Ect/8o/4\n19//V/jQl3weP/RDX8lTn/kkN9/qSe/6HEy/5KN39nj8HRvMcUSdR8aTib3JcrbN+MuB44N9NreX\n6A58LKSYvjEkH3E+oBqhyQ2rtcNYTR4jIUWkyTRNRKXiWZliWfmUNqgU8CPYvZ71xqEsxMvAvj9i\nDL/G0Z1Pcuvoy5kPn+B/Pfx3WC0XHO/NyLfPCdqQNxN6ccCUbxeOiMxIMoAGnxQMgW6/SuCXQtfs\nMXrFntpyfv4yj52cgIZhtWFx7YgBIa9H1BA5m7bE+6e0c1WoyFdtWkkm11KETl3TMKstw/5ij3bW\n03RtmQjlonUw0gBCCAEXIkqVgBaqcpGQiEZXcpcjxZK5iXiIQnKlPZgmh/Me70NN5aogjgLyVa5T\ndRyL1WK+eGGoXHY2uhLoHrIfc9FlpZrodcVlKOdkzDuXsT+iopBzvk1xaSbnvBKRTwKPA19PsWkD\n+L+AX6AUha8H/l4u+6kPicihiDxaf8+/8nA5cC+f0SpBtQHVBbJyoCMmZYblxN00MgwztGiGccs4\nDYDB2o4QAutpALHs9TMO2kQ3a/CiORIhGAeSMSZytGdpJdFhkC6yWke254aoFHdWK2Q7oLUhpVTA\nnRTJ2ZMoWoYC2JQQGWNLkXCSMTZV15REo0A1hctgsikxciRIHpU7cm7QIWOToc1dCU/RmU5FWqPJ\npiM6xX7XcOkyei9yyozjl54j/OQ/5J1/8W/wg098Kf/hvR/jmZ87xH3Zv8WLb3uJf/wbT/N1F7cZ\nn4oszg1hiqQbgX5jGFYJpdYkr+m7YhwTXCgxfDmDLuYrEwEtkRkzhrQFBdlZ3DpgfFH+jZKQRqOA\ntlM0VrHcbsh9A3oq7s/2zcwOHE8cfAH544rbFz2/8ZY/Q7PKDMtEGs6ZH+/hksJ2jqP+OlHBdlii\nesvczBlc8XB4dOaZzhw+L2hCQj1yA//Sb6NZcnLwds66iNg9WMPdmfD45YbuiWe4/eCczp1im2Lf\nF7PgU2F3GmuKXF4b9ruOru1otKFtO/q2p7EtKEOM1ZpfxatV+UrnEmPJBElFwahDxPtCe49aEF/M\nakhC8LkUAxeIvhQnKumoODLHGpdYs0yIpByqwW8xf7Ba0+nCzDTVxSntHOCgvjYo9rKJmHYqq3T1\nml/P8YeaPtRQmC8GPgzcfM2Ffge4Wb9+HHj5NT/2Sn3s9y0KmAhHF+iuRTeKKJ6BkbyVK0rwMEXW\nl8uC0CcgO5TWdNaQ0YzOE01gPkscz1quXxMwHXsmMSXHlFZ0kujNnL5v6fcGcrYsT/bwm4SLax5c\nJs4vU7VCL5XVOZi0p9WBto3Fz7Et7juCwtpi5CqtpiTCVAm3KaQklXzhNqhExkBQ4HKRz4pHaUer\n+8Js1IrONBgxJNMyKJBJ8PGCm6aheWqPzS/8JF/0Z/8Sn3nfv8Hv/p0ed/cOj7+55aUXZ7x6+TRM\nH0KnQrYJacvQdhAnTGvwy0LC2o4esmBR+KF8BNoqsk5FvblXZeBZIc6XkNlQDFkarZlZwQWH92B6\nSz+fcXm25ZHjntN7G/ZvWrw8YOki28ef452bF/nh5r3cGjr0YsSc7TH2n6Vt9tmGLco0nHTXWKmJ\nvD7H+B6v92h9IOXINin0gw3ebQhPPUI3XLCe7jGfHaIWj7IeDMluuRwcj7ubsDrn06+8wlufeJzV\nOCIzQ3TlQtS6aBSU0bRNQ9t1tP2s4Am2LDJaWrRqizhJlc/R58IzuFIn5qJxCMGXfj9nvA+v8VGo\nsXIACULIBbvxhda+01SUWL4ypShXd9W/1MnFFVFJNEbbEienavapypWyJHWSIlVLsStg9Rx8Lenq\ndRyvuyiIyILiv/hXcs7L1/6RnHOWP4yxfPl9V7kP3ULztncvaFSLiGUzbFmuItthy2qTCbmAikYF\ncvTsdTOUVuTR4YwjxhmnZxE3s/S9YtmMbMbEECCuNCeLRLOXaTtBJUOnOuZ9JgfL5XxkucjcnQkz\nK5xFiw8lBEGbGslOhnYXu5awuvj7QwnzaFqN6kqSkqhUDTJeQztNmeQjYxSiK4kxWjKKiNHQ6lwR\nZIPNBUGO2dIQ6Bdzzs9nGPMK+498PuPzz2J+8R9w+LX/Gefv/Sb0P/i7vOnjr3Bw84jN8SHjHGbT\ngtGuafcirC2xG4ueX0FjNJ4ycXFjxuoeELabLV0nmE6zdh7dRJIWgi9mH6ITfpsJcSR3Zedqoma7\nCtg+owxMLiAqk8QwcEpcNmxPf432scAL6Ys5Xx7RTs+Tp0R/coxOhoPDA8K84TQn/N1L2rmBa4fk\nbUPYrDG6Iame+TCivCdkIZzfoekibXvAhhlxCNBNBO+5YYSzzRlp5Yj9PmpyhE7hfAHurFLYxhbj\nk66hnfXYvi0AY9cy7xfFOFebeqE6Uko45wghEEIgpgIgxhgJoQiacqZI6n2C7Ek6XBmipOrXUIYh\nO4KbqnqYVMlF+urrhxOMKud+DSlKa1Oj5EqLoVTZOeSUSBRS1M6VqfAjdsnVr3+m8LqeKSKWUhD+\nfs75R+rDd0Xk0fr9R4F79fFXgSdf8+NP1Md+z5Fz/rs55y/NOX/p/lHDO995xDvefszb33rMW58+\n5MlHFuwfdEQfODvdcPZg5PzMsVwHhu2EjtBkMC6hJ8F4zXYpXFwq7t2DF55f86lPnfLxT5/x4isT\np5eC9x0pVVqoglnbcdD17LfQt9B1lq5pC5eAkhCUYkkNjlHwEVxIuBTxKeKl+ipowWiFNYUmXWTS\nPdb0GNNiTEGtrSnSaamCG5QqQq+WK/Rbm6KpiNFho6dVHbPZHNvcJDQn9Ec3WXzoF/jC9Yqzf/v9\ndK3B/MBPcOOJR9genLF82eJVYrRb4mSxjIguqr4kkWnrIGo0Zdu7XU1EF9FoVNb4tbC5yEzbEirr\nveBdJIdUIs9EY4zQaIMEjVtGpu3A3nFg6QbaR4RsDHtK0RrNfANumPHSzaegs3QxIptbeL/AuUyQ\njmY2wwp4HQgxIGPCKIsfHSKZcRNITQsGNucr9ucLQm4wsxukpqyskhOLuWWh4N7pOYdvfSvb0zNc\njISori6SXRJ00zT0XUvXWhrT0JiG1vZY02BU5RtkqdFxpS3wIeBjwNfisBsn7lZzqdv5EOIVbuCc\nL2NGFwk+lXF0Tmiliq37jtgsFEGcRJDAznZNZUFXEZVGrvImdKUwq51SkocWbanaw3PVWlxxHl/X\n8Xos3gX4fuCTOefvfc23fgz488D31Psffc3j/6mI/EMKwHj5/4cnADRW86bHr2FMS06G5bKlbzNj\nzJw/WLNZekQ0bV8iyCbtoGkxWaN8ojFgD/Z5/rlTRkk0orHiuTiH0+OJ5flE3s7p3tzg5hOLbqpv\nYgPSVIsthdIW2wouUNWPmUxJX44hE1TCm8wYQVcyCjGiMZiKBisKUSmRC6BIpbZGhSKV7aIueoQU\nPWMa6WiKdh+BpGt2gCf6gAsal5bg5ygfsCcnHP3WSzz9wr/kw9/wJ3jp+9/H4Ud+g69+fsvP6wWb\n5yL7X5FoYyZOB5j+giZB1grpFZu7E3Gt2Nvr6PvI2k8I6cqVOo9ggpC2HjtvsI0mpEhrhaA0kwu0\nZEwWvNN0tjpBm4Q1gk4J4hpJieXlxCz2PNh/ht/sn4b7Z0x5TedHgpoxaYc3lulyZJa3pD4y6w7J\n28SQT9FdR1SB6/01zpYvQO9pg2bloWlvovoTQh4wonGna67PFrAfOb8cUKpHLl4lG3CusPqsrear\nStNaS9+2tLal0RZrGzpjUfqhwnA3CcgpVJu93YSgjAhDDIWDEKt1WoKcIzHurp0C+KVQbPEhYRLF\n9UkXH42sVFnpJdQ2JFTwugQS51SNe8RUZ6VynWtVafdUHnO9L+Y6AEKWwmhUKaP+iDGFrwT+HPAx\nEflIfey7ajH4IRF5P/ASJWgW4KeArwOeBbbAf/wHvghtuHnjBG0bYixWV+M0sH8WMfqC6COZQjRJ\nOhM6obcdR40hbMob12nFeDlyMWZm830UDeMUcWSm9QSjw2Z46kTY6zN9O0OJZrkeWU8BF1Jxx1UR\nY0vF3SnQyqRHQBU1XUgZH0FCRsVMEyDogg4bKpFFAkkVsYykykKLJctYaYOkRE6ekLdsvCHmiM8O\nkzQ5FDRbUkWWBcbhlDZktoeBLkf2fvwHeOq73svtv/iduO/+dn7pL38v4194L7dTw5vOImPqkKOA\nTz1tXuOkGNV0XcPgYTNMGGC+Z5GsOT8daQbFTAudVcQxEEzGVNm6NoasVUHs0ZAM4zbQ7RvC5PGT\nsLdvSNuE0pHLwZBdoPOezXu/mIvTt2LCBTmOrBEWAnGxh+o72sEzzjbkl1e0eyfk1rK9fYo6nDPr\nGsbVmmAUYgwHds42TATXssccYVO25puRp2bX6DKcnS8ZX34ZN9ylz8KZC7S2uCIppWiMKeNGXXZ1\nRmta22BNV6zakDq6jMToC5dgVwRCwHuPc0XRW3fx5FR4H7vlWanCICzFBUiVPJUzUmNmrxyfr1bx\n+vPykBKdyaV9U2WXsOMyiyq0eqkErJTTFY4AOzs5XW5wpQ59PcfrmT78Mr8/9eFP/iuen4G/9Lpf\nAYVWvH/UolTDNEY2jWAMiAmgEyGlklcoAhYSZZt/dGCYegHXENYjTx8eEe8EcrTormGzPkPIuE6z\nXY8M21NWTyy41mV661Bqw8Um8cpF4t5ZZJoikqp7r4Ay1WgzC9F4RFdha9TkqNGhfJ2CIhopCVY1\n8l2yLbkCOZVRUy55D6JLmGsWQRHwfsLnyBg7WlpssqhUQGPBonQ5iUJWnMkpetmw6i955IO/yFf+\nBy/xfe95K+/7im9A3fokn/johp976k/znlsfoL15wGW8wKauxKpL2aVErVGzyHAZ6ZTCLBRDgpMT\nxeqWxbUbZvuGMCW8S2QL7cLiB02YBtooxJXCqQLA7nU9aWpoZgmngQbS2qK3Cd/C+tqjzPIdjlev\n8qJJzGxiXFzn5PCQV3/zZfTnHbLf91xsbtPYfWJq8eMFtlWo5FG5YeXPsWJQ24ZLt0aRmJ0cMUwN\nNm0Qd8ZRChwv9rkbA9cuHC+/8hFuHnWE0aAXCaVzUWtWQlJjDdb2NE2L1orGNljboYjE2lWnWLIw\nSyZmmYSUliHgXSBHCIErE5QUa0o0VKt4rvwfVa5SzGqIUi7mzFViMalmhFRbtyAEH8hSpg6Sdgay\n5TrYRRhKLpOPUAlUUmncxeex7IpQapdN+7qON4T2IedMnjxRHNMYiH4s47wmstiH649oUgZtNSkL\np6uB5+5EFotHePL6grnRaBboReTRWyOffPGUu8stymhWa8XZBcTc8txzjl9t7nO4b7DaY4wpadNO\n2EbNlIRGNXSmLWQeYgkFQWFpEOVQqjg4S4aYigmGmzKSU/HoSgqtM4FY5LCUbIGYKGQTEXwQYhKI\nqpi/rrdlPJUthrYo7pLQSfHVU6IhCb1tEdnSaMULj3ScfMsX8Y1//1f4/m/9er72O36dd3/kf+P7\nvv3v8VXLFV8RfpZmtodBEyePEdBB2IyRk2ee5MBccPvTG/rlxKzf497ac/DEFqRMJ1rVlMDdIZBU\noDOK3FtEN7hhi+4CN59uGdeRKTiOuhnTFBguA7NgmTxMep++P2ObXySsG6K5ZJOPmC/2ee6f/TMO\n3v4Wxslx7l6ldUJ+y2P4MwjbEWkCmiO2d25hekW2M7wbubaYoQ8Ny2mF0Q0Hpw9Y3b/P/ts/n48Z\nzZNuw71f/2X2yKzCSDtraWzG2IxuFW3X0c06mralb3qMKg5eVreQIuvRkfJECInBTQzjFucnhko8\n2kwD2+3AdhjwoQSviJRkp+LfWdiS5DIG3X1+pWhQdDBZI0ld+SGILtTkWBW5OZaYAFEUyrlSRVtC\nZTBqfaWOjNVJOqarnqUUlbJVeJgD8Ye4Ht8QRSGGzGrpUDqxGUc224FhmPB+ojGJeZsJyWMaS9PM\nGDq43G65HCfePrvGXgPBeY724KnHOoI9onmgmaIAkfUmsN5EhnXgchPYZsGahOSpVG2lESMYW9wS\nrVWIUTVAJb9mFlz7tjpiwlE8GEWqujEXebFKJClCFMmF/RUjkArg5UNxmIqhhLqqLMRq4xWyLxLf\nlBlxiEgBvyhqOImJcZcPodfM/+fv5m1//Qf4zFueILzwQbYvfIQff9e38RWf+CfktzRIPEXvhDlR\nyK5nOo2Ypxz6umCchilickfebkk20qjCXFyvPSQwneDyRDaGyU3EnDk8nNHudyyXl7QzIaeI30TS\nKGSVcG3D/NxxLI7fedc7uNU8Rdt8hn6RGYcE8Rj1yGMYeYXpzjnqxr9GyHPU+aeQ7Jn6A/y0YR4C\nJM1oDdCyPT1ntneCF+GJrGlt5v6eBd2xyonh8pTLF57FtsUE1diyShpjaJqWpjqAa20BTbkEap5n\nCsWuPUZciLjg8aEChd4zVZAxxliFVJTdqwZUBflIxCwQ5MpCEJ3rtAHyLpyyHjsmY+E1pqtHkdK+\nlhah4pCyCyusLgrVzHWHdeyOXRBMphSEauL4uq/HN0RRyBnGwZHUlu00MnlHyBPWJJ5+4jrdWxqc\n27AdHCkZfI5IPuTxa4cc9orHD1q03qe3Sw7WE/s3eh6fetY+M04jl8stp6cD9+/C6Sl4V+bJGYOW\nIkiy2WMlok3GtAZjFKJLpkPwkVxNMUJKpBhLYnEMCKbOhosCbhfnlTG09QNMUogzwRXfhRggo9C5\n0IRTCMV2LiliDOXiF2FMI1prOg1ZWxBBRaHZDqjgODu5zsVHf4L3nP02v/T57+HmB3+Sy+Eu/6/5\nZv7qqmN+a014osH4ULQLOtOQuHzpPns2MNtvaKRh2m6wRzOUEyafsEoVvv2U6bpipR/Es8ahDOwd\nCboV7l4scTGx2DfFXNdDoxQpanoTiNs5y3aPa+NLPLH5MKePfDHb4SPI8xvk8RuM2w3XT1ru9SeE\n5oD9IbIaHW3XYZRls90wGM/e3oJ5njGmLUvlWZge/9KrcOOAsZno9+ZsJs9ep8nRoUJiajSdGHTy\n0JgiYRddrdZtcURS1dJMbGnpciBJmTRM3uPcxOQdU/CFKhx8sUiL4TWY00NT1Fy1FSU1TF09FnOq\nFm+amCsIrYVU29Ti7lUmBLv8Tp0EMTvF5UNwUYlcjS0jOyemEhSRa2DEzqZ+N4X8w+wS4A1SFAB8\n8IxxzWZak0TTzTU31R4z23H9+BhRkdVqxXo9MY0eozputpYbC82TxwfYtmPWZI5Hy0kQzqJiUpaN\nC6xWA2cPtrzyypJPf+aMO7dGwpixjUGshuzIJEQU1mZsk2mbIr9OIkQvJK8IEXzUxCjVyUbhXECk\nZEeUbjCiS1kHbQt7lWLkKqIr8SrXhKLivGRVV0NAhEAgUizadWOuTEJTjCSJpChc9prG3ecoPEFa\nn3P/Z/82737v/8gr/8f/jrrzsyzyf8LfSn+K73npAyyP5lXenUFlWp0YN45wy6KawGYwzPcMm7Rh\n/9Ai3rBZOfwkqEbIGrbjQFSZdmawPWifGEeHnxJ7i31EXCmQGZIv29hsDXa1xCwym/BFMLydYG7B\n2SFHacXiMc/5+tNs01NMsxvomIh3b+OD49riMS4ubrOwc7Zqg7eK2Xpks12hnzlgc7bFvhLp39Jy\n5h2z9pjcKtxyA34qV0HT4sPAwlicqcVAPbRaF10zG+rIzsdAShOZzOQd4zQxOcfoyn3wHj+5qmIs\nuoKrceDv4ewIO/3RLn5uhzcoiptz2gXMyq6gPHSGUtRRoylth+TiMs1unFq2J3UyUnkN9W/vnL+u\nvv49u5I/ZjsFcrFk0yj8NGJtX7joxrBY9Fy/NmPWd2xWLavLNQ/OVzRZuDlrOZhZrLLs2RntNUPn\nBprJM8PgdYNPmc028GC+pTVdkduGB5zdHutbmBATEStIW7abjVa0JiPKE8nopli34wURi5MCAJXJ\nRNlmpryT0CoaldFk6AxZBJMNTZYSKJM1jdJVrFKzAWiKh4IY1AxCdIzThhBGplzUm1klovIFVQ49\ny8YS9CX93nUuf/wnee+//93c+bJ38WfHj3Iaf5cfn/95/vPxpzkZHCsd6UKGilXMW7j/sufpZ65x\nt72kU5q9nFl6mCkhjYJKMDtsIITSKjWGWa+I40Tw5eRsU0anwDhGxq2nURpty/QlIsT1PpNa06QV\nD87vcvPnRq6ZX+TZp76ZWWqR8Yx4fYZRC8zlANMW488J6RlGDdY/oNs/wDcd0727HBztsTIKfSFo\nd0zzmBBunzD0R2QvqKUjjxfk4OlR+LlCcoNRGaMsxhRb9ZIdVDQpMe3iA3ZEo4B3xetgmkacm4i+\ntg+TI/hY2J05F6u+YtJw5cYENR0q1fZBdLkci0a+mK3ojMNhqMQwKvtJgU+ZJKCsKROKtLNfq4au\n+aHxT6yzT5GSNC1al+fmMvYsGSSajECyr/tyfGMUBQHTWaxvKnlE03YdWhnms469vQWL2YzWlLGR\nbTtkihz1HfuNpmtaOtvQNpocDck5NMKkLN4n+rZHMgzjwLXrM+6fWrYXJTOCnNG2JCc1TYmjNw2Y\nRqHVLluwFA/IhbFH7R1TYSfmWLaInuoYbMoqEb1UIpQG0dhkyFkjYlH6YXyYaI22HQpLlkSIjkb3\nhDywHrZsxw0h+tI7GuhywG4Mow3szz33Xlzy4k9/gGe+9dv48H/5TXwb9/iZo6/gE3wN/6b7YfSs\nR9KAdxEJCrLGj7A6jdx8MnP26YZHHmmYtkuSNCU2PkHTKZRq2awHJCSImjAKYYDGJtwUGDeBpin0\n5+wS45BpraEZE5v5yPCk8E55np9P38Dp6TX+8ud+J/FNj8PdX6VNwvzRx9h85EW0cmzsGSbewDXQ\nqo7B3efo+DH8cEFoilpwvz/kcnzA3pM9l9OSs1Vg8dge8eXbPLF/xGef+yzTsOFEGtaNKS1Q02C1\nrknMRZAWoyD4cq2WdZucS4vgnGN0Dh98ISnFWPCeWFiMOT3s/VOq06bXeDfuMkV3HhmSC+wgInUx\nSWUBkTKtKm7bZYqQUqFMaykXtFRfz2IWG0tOZQ3ELXbz6cosJuf6daY4O+fKlUjFAu71Hm+IoiBK\naPqOqFqMaRFRdG2LtZaus2hK/zaf9cUV2Sbi1jNve3qt6JWlMQYUNLkg5V3OoBNGaYwW1k2mbRLz\nudD30LaaYRvIgDWathXaVqF0RDeKti2PJynOuH5KOB3RoSoiq9rRh2LgmatMNSYhBIUSSzKanC0o\nW1J/q2+flhoVVmmrxrY1MMQWM1ATiMYT0gbLGoNhcGumMBavh5zYi3tc9COT91y7bvn1v/M/8b6f\nOeVNf+ZbePPtAY4HPnzrbXz1UuhOhDhZVJcYgNm85fhY8dzHznnX+/aYXc8M3tNQVpzZrGMdB7Z+\npOtsyUxxkdxYUtBIgka3zLtqw59zmZioYgxLUlx6Q1RbDrzwwss3OP7y+zx2R7h2O5DHkeGwJ5x5\nHEJ4+Rb68UDqtuT9J/ASCH6k7feJXvCbNWYxJ89nuGlNCJ5rJ49z7k4Ro7BOuDx3XH9mzrP/8uM0\nRKSB0U0c6hlaPYxRS3XHJlqhUgEXc2UAZhLeVxzBe5x3FWyMBB8KXbnu1dXv2Y2/5h+5BgrvjlRx\nBtndds5JiUy1TJOdnrEYrJatP3WKoF7DViyFSyOIqdwESv4qQqVFc4UpiCoM1JIH8setfZDi7CPO\ngjQMo8M2sc6SG2xrsW0hYiSVmLwmmUis2YfaGLQWfIoQIjqVEWGMCaeKDflQTS1iLA7Mup4lkisP\nXeniF9AqGqtp2nJDICTKGGgKiE+FKSZCzEX8FJIU4ko9YVIu8+iYVA3iMKU9sFS5a2WeKUFrS2d7\nGtujaIpEVhVl3DBZTGqK0WtS6KxxeSLFwvBMQ2SVJmaLnuH2Bc9+4Hv5km95Pw/+8Y/w+Z/zMX6Z\nL2f0x4R8hu1nIJHFYw3jHU+3N7K/Nayej+w/OTKeWuIA7UwTvJBUkRfXyRa77lekgK3eu+JyFCNt\n05Cr4Ecpgx88bQup38dEz/7JOZf3BdOsUE/MyLmnubgD+49y8Zsfp2k90YzM5tcYugV9XrH1jhlz\n9LbFTpl4aND9HCVrWjSrVx3Lk4nOBsydSwYzhwZmH/4kWwMXXeZ4IzDTZBWvsjlURfBJ4CmOySnu\nzN4To5vwvsibXQy4Kzpzqgj/DsCT6gKtKxOVMuKJQM6FbZjrG5jSDkqqo8JaoUiI0lfCKaMKDhBT\nnS7kWPAPqY3ujosggg/56t9al4lYyrGAkUrXENxqrJt1ScR6nccboijknJjGkWkKhCCsto6Q1ijl\naWctURJJIsoI2ETWFi+e1bhlFQz7M1V7xDIBCC4yuIlLHzhzEe+F5XpiMwTWy8CwjiVhOAmqxgbl\nVN48cqquvRmtq+8/4AEo7r7KlKFQzEJKujjcBE2MoHJGkclqtzKU8aYyDSIlHkxTUoG1GKyy9LYt\n6rfclL6/UqR1e4jJFvEZJKIE0p8H0wAAFO9JREFUbLJ4NbKOa2QrDG2kEcvBieFjf/u/w/7Y1xFu\nfjXv+eh/y48+9dd54D+fR9oPMk1lK6v0AI1gbcMjU+TBZyf6m5bRZ/Z7Q4hllRRdTv6USvYiNbnK\ntplkMt57qECZKFBWMQ2BWAk3UQfaANlkttvEI2PD+JjBfvpp0rU1YbiDe+It2Ffv49KS470TxnQd\nmUZme5b1NJEPjghbjWwjBIMeFmS3pIszzldLhudv0T55DR8c8wb2JHJ2ec5CII+BtGjQJZ4ZeEgL\nlpiIlCwF7z0x+jpBCvg04ZwrxSDW1iEmYlJXF3Y1P6hn72vcnUupL20CBXfZ0aOl/li+EiTIw7vd\nSLus+RUjKApKLYWaDdQE9vKGZx7uOgoPJhGSo9Ulm0JqgI0S8CG/puX5g483RFEgZ7xzDFvHZuN5\n8GCFsQ5hhrENykDKjr5rcTEwec92nNisNxir6bPQy8SiNzgfWK83nC63PJgcd31keek4Px94cLrl\n7t2R1TpSQPIqO01S0nry1cvBxYgJO/AoIwpMo9E5YZuWlIUYEj6WnUEIdbdQbbNK2pAgVlBWFXOM\nZMmqBNUaih5eiRCSL6i4LglNIAQ/koNgsfS6JZo5JenaMhqLH89AlXCWs/Mls4MZT98dePl7/3va\n7/ibPPrDh0yP/Q7/Qr6Eb+KDjNHR7x2wuTjHNAa/tuS4RW01cWkJeYPzBk9CjKLVhuBKaK/RmkAu\nMvFOCMNE2GY0oFvF5F0Nz9UEnwvIqCI5T+g2sOkaLk88Vs25N+whw6fI176AfOpJcYaxZ3RyyJD2\nmG/vc+om1LBi8da3c+8Td7HZYaaO6DPhdsDYjrh/waHWpKnhNCSefvyAs/svce/+HU5O9hECjQFH\nLlJ0VQC7EENZBGLEx1hxA1cpzZGQa1GIxdE7Vp8DqdyRnS+BUjuSMuwU0pmKG6Cu+gxVFwZVpc07\nUnOq06orxyQRMpEdyVFXNqJUXU6JHizu0DGG6jW5k3BnQvS1rS2v5SoDQnav4Y/bToHEan3J6cWG\n88uRu3dLKk6OBtSSqDzIQem3/cSwdazXE+MmIh10ZuRIB6Tt2frIcvBcrCfurUfujJl7d9bcubvm\n/GxkuQxcnE9IaNCSEWJJe8LiY8L4QBZFMJlJit23VuXN1boAh0YghFTShEJBfK0qadQ+UOLiYiab\nRFIRn8pKpFUDJEQiPilcmtBxyyZ3dMlz0Bm0MeB3OIUnRU+IoaQVxzL6bFNgkRcEG3EhoxpDGEe2\nTx8z/6kfpf+v/wc+/swXIr/0m/zGVz7Gv3dLMXvrjO16w7yf44aRpANT1LRrYfPqwOIdhnRbUG3p\nl0RFaBTBBUiBqECMEBVEW1KTVABpCgtvzJG5UvgO7CZhvHCBY+401+cNt7aBay+PdN0lWo4wtuXA\n3WW1foX5Y8dsUmS4vM+1bsEUtsTZHiJztP40+03H6XLk8Po5Vo7ZbALs3yPNZsxn+2xXFtX1rD/z\nHOMrt7HXOgiOtYLDrOooOBLCVFZWgRgSLgRSTIS02ynEksoUEr6gy8RM2VVmX9H+2hLkck6klNhR\nikoKeTmjdZ0w5VRahCKVrzkNeUeFf7gjKEhBxqgMWaN14WpQQ4eizoXqjBQX8MqalAwSI5ICSqkS\nCyhFgalsYexSd76v93hDFIWUEg/O7nOx9JxdTty6c4qfBK0dpj3AtrGg2ymTCVxuRtZjYBo8cbtB\ntlvc/h70C7wStqZlqz1bIqvzCy7PRs7vjty7t2HYCj5YelvkzmJ0CXwNkehSybOsUeLTFImxZAhq\nA0YX4CYLaKPBGJKR6tJUTU8VBJXxIRJz2TmkFErlzmU3IFDUsclRMgh85ccrvHOYejamWNDwECLE\n4u2vxBRykO0ryDRQMNWEax3bUTH89D/i+rd+I5/+9u/idz/PcnG2z7FtiW5F2pY4+aQSXdsSZ54H\nLx2w/6aBtD8Q1z0xu4onRKxRkKHfg4jHTyVKPevCrW+VYUiuTl3KjohYXKqaHJhIxfH1gacncTj+\nPOHOf0XubrHMd7HX9nGHe8z2NOqVDWfmABM86ea7ON9coA7nbG69yuJznig29B2MacWi28PM93FK\no4JjvicMz34WezGgbjakRlA5luU7FVAv5gQ5lv9HTLV1iBVsLCNJ51xNb6rahcpoFSopqWJBldxa\ntQ5ypVAs9m11l7jjEKRYJkxa2AXDiYDSGV2Tx0qDUHgFSgoArUWTySXUiFh1MIlAupJJ70aZtTFC\nK4WtvpNaCgYXatzc6z3eEEUhxsjl5ZKz88TpqcdPipRbRpeJXshBcFvPhg05e8ZNZNhWL/wEd+KI\nR9Ece8RoYmPJtiFph1KG6BXjFsY15NBgpSXnqYwEZcdCK9v6XQpwrLHgBk2u4bHlba9zYGrYrC56\nBqGy1thhSBmXAzEqwLHz32uyKVz4IOTkETQquaLT955edTQ1gFRni0++5gLmKqJTNBgymShlpp2U\nwqnAE+OG2zcUL/7g/8mf/JW/wT9/+gv4rV/5GC+8+Z0cLT+E6RV4hYjFXzZIjBzcCDz4rUi4E2if\nnLE5A5thImFbIdkyZy+jr9IaaaNxEgkq0dQ07uI6nEimgLXExKK1YBMsPCfXO6xq+Y9e+WE+9eIe\ny7e8g8V8y7ZVLDvF9PI+c7YE9Vu4CQ7297gcHpDu3UcOZqiTluGOZ7bxNMeZ3Fpsd8QyOW4sZrQa\nXvrob7FnMrFJhByZiUGHTNSFVk5UBFWSplMoqscQYk1d2s3+axtZC0CqnzepKGaLanVnYlJ2DKVl\nyFekpYpgs1M/CqXdKC1HDYeR8nOiFVpLydokVZ5BXTgyiNKoyk8RCraWVB2Hp0jOD9sYU0VSu6BZ\no4v6VjSUDIXXd7whikJKmfPLgeUyoaXn5Pga3sH+zNJqi7hI3I61904Ynwibke1I0Sk0GlzkaFzR\nzTqSoTgVt4autaV3CwqiLuMzqSqyKlNVKpVUJ23KXDeWkA9jNQlFSGXKkCotGYAsZCnwUKnYit1Q\nutDNy1w/5d3Jkkkx4ZKgSKRQcAyyRlQos3EZ2aiGVhmMMphc0phyyBBDmXvX/IgUExiFVQarMo1o\nkjdcnihmL7zKsz/zE7z7a76ID33n/8MPf9WX8O53GLAt+jDj7mW0COspsegVjctcfspz400t0viS\nHJUVKmnCVKLriWCyYGrsHTqRJOGTB13UgMElslHMFwum8w3btaNfWrJJqJnn3nnma04+xZct/iar\nWwP/Yv6N/IWv+i8wbkPYPoueHWLEMewdIy6iponZbEHz1OOcmky3SXTbieUTBnu4Tzebc/v+A9pF\nx+Q3DHfukvchmoSKgnYZlcFL2fanGMmqIPUxlhU0Vu5BOQ9jcTdMu/khVxe/oFC5woRJrrbjO1BQ\n8sMJTflOpITAFX2MNrvzK5WQIlXEUVprjNHVJLackzmWXNJdypTWGptKbFysSlsqeamoLRUKwZqa\nGkWquZRSqdFVc/E6jzdGUciJ7bRhmiI5RGbNjHZ/xrzVGFIxSpSAiEUboY8TzTRyfukYrCIedESd\nOXVbZjrigxBi6cG8K22BVLchLRQxlDEonRBbglStLR86KRcKrMiVao0kBSvI+coMZffx78gju0CQ\nAjgKKUIMqn7AO5W7rrPuOsdOEHMoQGv0TExY0RhlCxgZTHU7EkzWxchFim4/huLgo2zJrEwuM0pD\nPvEcP5cYf+4Heer9/w2vvuML+JnnD/j2V0944sY5g/LYCDFv0LOGlRcOFpnnPraP+dLA4c3M5m5G\nTxoJFoaAzgCGNITSOiQwvZCk6kJ8pXJnYQoJT0B3ikBL/GzEbCzLyxF1sc9ZcmzUirfNHR+0N2hX\nn8a6z2U053htmZmnsVYIG0/ebBhbQw49PHDsLxXrPBLaQ3TTs5oG2hjRRx1qdUF69hVSCzqDziVs\n12lFTrGan6giQqsZFbuAlZ0rU0oZk3U9J6XyAB6Sh1MCcil8uyCZlAtPYPecvAP2EuQU0drQ2MKj\nKdFuhjKKrMVCa0SZK/KTiHro2KwUWWlsruzX6EtYsKSCSagqnxaNpSwQWquHY9Kqh8gpX4Ghr+d4\nQxSF4CNuk7l2dIRWDcMwknPA6n0aoBVNg0L5gKREmxwzlVHel1RkgYxm6T2OjHfC5TpwsQpsLj3T\nkEm+RnIaaBqD6FDSqLTC2BJBjuQrMdKOVlpG0xofExIzeic4y5TtGzXKq/LQYyzhHSlBmMrJISnX\n7aQuwJTkGvNVUOqQYr3IwUvZLpLAJo3KBTyyYjCY6pAkJcGY2lImKWzK5pJ3Xgin1yzbD/0a/Z8b\nePSbv5W36Ylf/exz/LvmDmqmUdEgOXJ0bFjenegOJl592fDqL2X+1Pt7xju+tD0VBe8bxXYqRK0i\n2kklkl2XtyGYSItFh4wbI+txS3esmB/tk+9tUacGuRQOUlOs9BAihgMHs8sNk29Q6U0kuyLOetiu\nMWpL2wqDdBjT093Zks4c7smO7miGJOH84oKbex3tcUN+dcv6d55lcWOGuFTs0BuNk4zOlFSoKmsO\n1XA15Z0xSr4SHuX8EMGvlZycc/FilIIHqJQreaMCfbuxYr2vv6jKnEuPb7Sp7YSqfImM2uVW1SlU\nqjsFTZVKS3Fmyrr4hapIMeeRclO6FD8tDyPur6zaKOddYclUncfrPN4QRaGROfl+z517l3R7cHBt\nTtMptGxplGamG6wETIQ2CgHYk8wBivU2svGR7CLnh4muD7h1YH2ROT0bOD91bJaB6HzhwDcGrRLK\nZJTNaCsgBQ8wrUFUrqCSVOGTEHKxs9KiCu9AydVMOoWy7QRVJNChqCAjijhVgOfKJiuwk74mKS5M\nRdhSJ9RJakR6QEkurLcEPipamzASUVnRiEEbgViKUIiQVEvEoSeNefSQ+7/9El/4ynN8+qmbzH/8\nR3jxy76GQX8SmwOq60luiz/dYJYK/a6G+QPPB37a8O4/YTlpWrKDe9GxaDU+TeT/r73zibGrquP4\n53vufe/NtDNtoTVYoCmtdAELIw3BLghLFTbVhQkrWJiYGE1g4aKGDQkrQFyYGBOMJGCMxESNqCHx\nH4luqKKWtlhLqxClFkrbaWc678+8e8/PxTn38d7QSac29N6XnE/y5t137s3M9+ac+b3f+Z3f/Z2W\nyIFyxWhlYacoKQtFbF1JPlNSDIOxu6HIGRQF7Q19itk2/UXI+xmDwQLdzTn5wgznlrp8cuUXLLYe\nIc/+i9ciPjfobIfFOcgvILdExlZwy7jBkN7y+2Qf30M7H9AatmkPZpndGaphdc+ewy6eJd8xT29g\nbJwt8cUwTAHLLBZZHeLNYT54Wl5uVDkprArFfAxveIWpQjW1cBaWBaMvjkob5Qw4wpjwobwmYS9Z\nkWcKO45jVVQyGIRq+hBTmVvxm7208HdDMl0eSrY58EXYLiDLQizE5FHm414iYY/SKvPRWWij9Fjm\n4z6ZYUyul0YYhVtvvo1vPvE0B4+8wu9f/SXnLrzD7BzMzazgfTus37fAlR6HaK842t6YkeiYo3+p\nz4XlPsNOQWvGGHYLuotiYWHI+fPLXFoqWRmGtNFMoDy6bi54CMrinoku7DAkF62xGcWwAFeSk8Vo\nf/DDQqjA4iAKrmIwChaKr3gYxjJybjQmwlzRVd8mPuZA4EKFn7LadchGEcv4VCxlEWv2mWfoDFwG\nFjLbChceYJqxjNPWZ1Pp2NkWx17+MTu/8gwHn/gHN2/NKD99B/3eETaWF5ndnDG4uIl8LqOzbZkN\n28SJfw/446+MLz4k+ks95ue2oG6fkrBPghQKpIowPaIsUSd6Rb4kczmddgvD48yjmVkuacCwHLJx\nxuHPFcz7FRa0hS2bOtx+9iRzfztMd99ubHEJXwwplnuUcvTMyMzI2hm9Xpdhr8vmDW02bN1MmV2i\n6PXIXTtkVXro95ZwLaolAqwMfWzehYee4kNE3sJyr/eeIj6fACHT0GIlo6qEe/Wq0o6rbFRGP6uJ\nYfQwPKP85zC+4hdINDJZXK6UXFx9cKO4QpXnqhhoHC/IOgpeM9ZW/Q5p9MqUjTybKmEqjLcsZtau\nD1VPdtWJpPeBZeBs3VqugW1Mt36Y/nuYdv3w0d7DTjP72JUuaoRRAJD0mpndXbeO/5dp1w/Tfw/T\nrh+acQ+N2HU6kUg0h2QUEonEBE0yCs/WLeAamXb9MP33MO36oQH30JiYQiKRaAZN8hQSiUQDqN0o\nSPqcpOOSTko6ULee9SLpbUlHJB2S9Fpsu1HSbySdiO831K1zHEnPSToj6ehY22U1K/Dt2C+HJe2t\nT/lI6+X0Py7pVOyHQ5IeGDv3jaj/uKTP1qP6AyTtkPSKpL9LekPSI7G9WX0wnqRxvV+Eepb/BHYD\nbeB14M46NV2F9reBbavangIOxOMDwJN161yl7z5gL3D0SpoJ+4G+TMib2QccbKj+x4GvX+baO+N4\n6gC74jjLata/Hdgbj+eBN6PORvVB3Z7CPcBJM/uXma0ALwL7a9Z0LewHno/HzwOfr1HLhzCzPwDn\nVzWvpXk/8IIFXgW2SNp+fZRenjX0r8V+4EUzG5jZW4QNj+/5yMStAzM7bWZ/jcdLwDHgFhrWB3Ub\nhVuA/4x9fie2TQMG/FrSXyR9ObbdZGan4/G7wE31SLsq1tI8TX3ztehePzc2ZWu0fkm3AXcBB2lY\nH9RtFKaZe81sL3A/8FVJ942ftOD/TdXSzjRqBr4LfAL4FHAaeKZeOVdG0hzwE+BRM1scP9eEPqjb\nKJwCdox9vjW2NR4zOxXfzwA/I7im71XuXXw/U5/CdbOW5qnoGzN7z8xKC3XSv8cHU4RG6pfUIhiE\nH5rZT2Nzo/qgbqPwZ2CPpF2S2sCDwEs1a7oikjZKmq+Ogc8ARwnaH46XPQz8vB6FV8Vaml8CHooR\n8H3AxTEXtzGsmmN/gdAPEPQ/KKkjaRewB/jT9dY3jkKxhe8Dx8zsW2OnmtUHdUZjxyKsbxKiw4/V\nrWedmncTItuvA29UuoGtwO+AE8BvgRvr1rpK948ILvaQMD/90lqaCRHv78R+OQLc3VD9P4j6DhP+\nibaPXf9Y1H8cuL8B+u8lTA0OA4fi64Gm9UHKaEwkEhPUPX1IJBINIxmFRCIxQTIKiURigmQUEonE\nBMkoJBKJCZJRSCQSEySjkEgkJkhGIZFITPA/Jg8bDDozAckAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c1825ae80>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "79.02% : macaw\n",
+      " 6.61% : bubble\n",
+      " 3.64% : vine_snake\n",
+      " 1.90% : pinwheel\n",
+      " 1.22% : knot\n"
+     ]
+    }
+   ],
+   "source": [
+    "predict(image_path='images/parrot_cropped1.jpg')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then use the VGG16 model to predict the class of one of the images in our new training-set. The VGG16 model is very confused about this image and cannot make a good classification."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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9/iEAP8XM3wXgp9Lvm6kMhBc5QvkCaQd5EDzsngYpS2Hu9SlByhCqwrd7/sv6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zAAAg\nAElEQVTEpL4vQBPeHaJwVf/fKaLRUfBLQrDVM6OT0hvdv69IV2Q5BEDo+RVaH0wtMGDTG4csT3s3\nbmIuYGJ6j55rXFM8RyXbIjApyPaU2qM5+MLE5/jYSONGvc+OggcJaNNHE3RaP4bvpBnWLo8Hzi87\nG7XNh/Q4i7iBoioR/RU60TGU3bo+znuYXFEvT41V2QdVO3Cq5kO/V4y50ByVCdMh4/Wr1zgej3j1\n6qUemybM0wRhNU8SAedlAYs6QnnpO68zoefouJSqaoMDkUxeDzOhrAXrNGPKGdOcQUmQJyUu52XF\nsq6oFWDO7T3Y3BhVgkbDqLKpq8hpu4Xe2N4dogCgybLxCJGl9HNO1R09Ru5MF9eNNv6EWPrNmwSO\nIeE+g42bAKrUrA6ex1GNP6ovXJrSosNUByMvwb9usdi+g24S5yjuu+DPqeHzpbOV+3Q4AejOVaGP\nJgmIbbRxU49OY1vdfvvsa+bIeL/tuEe34WEuxDMoK+YQC+e4bKVgWlQ/wv0l/rlVJYOKMxD4cQ05\nIJluCGl6D/M0I6WEly9fNhfpOU84HA6Y5lnXiZwBvEKtFbe3t0NR5GnKWNdiFcn1OU4YBIatsJYn\nWLN6SM5zVs02MZazqiFS3SLhUk4y70p2FtBeziEXuqSgb2zvHlEIL+UEoU+ecRLs+87rZfsht9t6\nehHEarooYM5DZmGAB0BBwTfbwL3yUyQAMmAGPU9i98e/ton1nGxStXNIhnDp9w7v65V/VPqJmzWA\naO0Z8Znjsz3gJ2ZPir9j803sHPBtRCGO/TgPvHvNRdIZbLNIda4eehU+q1oxqgKXzlU9otXNqX2z\nSAOEMKwbEsLhcIP333/fci68wvl8xsPDA47HI+7u7vD06VNQUsBvWTXs+unTpyZteFVuW8wGDjbi\nZ5gPmx8HDHNYFrF0eBWlCuoKs7yQv67OY0rd/yOR5tFkV9Xi+DyuvVNEoS0UQNFlUj2rZyk2h5lw\nDcFxg9GEuE2s4l5m+hx1LtmG5wJ9MWj2naIeYcyoRd1M3aVVwSQzPxXNNNxEdXJVvKd573Uwtdce\nh9GJmJibqpqapBSA3adeANLjZV1wAaxdcAHFO/R7tUjEYK1+lm023vy9Qxz8WbVa2DnxcDyK+V1N\noAbGbv0EfIzjpvfrtol7O8FQHd+lxc4/opqo78NVNGMR9lUZvXccqz50RGRl6owpJU1++vTpU9zd\n3aGUD7AsC15+rolaXr16hWVZ8Oy994CUUUvBw8MDXr58idvb2yY1pESY8oSUpmatur29BdcVy3nF\nshSsa9X0cmXViE/WrFK6EDOEM0oh1EqAJBBmxVrmXksVRM2qBmQFV3+TMi99xS2i3Qif1Y+8/b1l\nDnaWWtccf7gstTambe8eYJEpurQwXIu+MB2sGsTZRvF7MU+3Z+811yudODS9PqxKYatfseXYgwgf\nRmyXMLRLTFx1P4sdjCCqPNgnNO28ILbrcUL303eiGwgQdzHXN3NUGyKR2GZyjs/dU0HiOZcOYQDY\nQ46toK509nrtXu4El/MEiKDwagyqe6h6gtfJvCU958Lr+9cQ0aI4Nzc3ENGKVSKCm5sbTFNGnuYm\nsWksxgHLWVDWaqoAG5brhWEr1qVARHMs1JVQSzJAMYNoBSEjyWzbQwCug+Vq1/PzDe2dIAq+8YCu\nQBBR8yhzs85gtzYbe7J5Zksq2J0/TKSimMBlywk7RuAFTVyk80VW11UxBGEDeLoHnuu7Uiog0lQP\nf0YitYF7/kaQovKRU3aXW9j9GBxK1rkIWGuFpKx+FCY9CMswJs2pCozJSrUxuzmuv7PnlxhBPNj4\nBxNjI1BmhUlkyVxingDf3O6TAXhUX3uHpJJOXJxRAtiqDcAYGLVVP7YEoo/B6PMgEKQEI+amCgzE\nbkfdEZcWVXpwi8SIN+i5T58+xTRNuLu7w4sXLxVvWNQ9OueMm5sb1FpbdqcpZ8w3N5jnm6HfKblF\nyzY7VrAoQShrMctHAmFCKYSyrChFUKvjVQlynDBNui6IgZvDjDzdqMgq1GpwPKa9E0QBGCe/Lx5f\nLLWZ5fqmByDqByhmh2kYQFs0rttvuYMM92r6NggSEPCccw9jNVHTF0irJxE4LaFzO39+eJzlfowm\ntujb0PM9iInescX4eiObcB145KZe/s02qTl4+TP6O+Oy/21sTUcTdO+9pHUpZVMAp++VUeIYRDqm\nLhTR2F+PZNxiEnG+olT2ptbfMUgL4uvDwNpWs3F83+0zWt7J7Nah+D03on9zc2OSYQYlAn/+Esui\nBWuixLAsCxYRHJhR62bMxSVXJ6xkWZ3W1hddOxW1AqUwVsvl4IytQKWbnAjugHpzmCFZzdbp8drD\nl6778J8D+LvslA8AfC4iP0lEvw3A3wTwf9p3vygiP/vWZ6BT/pSzZUxA4GI+0ToIOU+AofGd6/ag\nmou7u1gWRPXxvEBo4KaobESBDS9QTpNSrC/hvduoNeibfywP138gYzBQ3xTkRgFEi0B8QNw7kXN6\nyjgYgWmvhm33/F2vWwwaIZNOpIW3J+3jMVsdvun/aTzu/d9iI29KHXbNyuSYQ3uePUojCI0oCUE9\nXWlDFFIjJN3ykoy0OUa0o74YCD3PM54/f45pPiBPMz7//HMsy4JXr14hZ3VlTiljXRc83D/gfNZy\nd80Xo6qE6NW1FcuwMOnKhke5ROsSa7Wx036f1qLBXaSZn3Im1HIA51lren7FmMJ/jE3dBxH558Ok\n/EkAL8L5vyIiP/noHmyau+rWHdG2LzbVESszPKnElhaMkzjiFfvEY7w2udUAAMAqQRAg0iUBT/2F\nAOLt5xZ0VaXXE9DnCNjdtBvH7/30NN5cuUsZDDBJ0xn9GY0omFSQmzQgkKzYzCUC3YnDBQrffvdn\n5Bxdka+dj+GaOBZEWl0qXhd/tgTybfO03/qG97mIKdG0H72OQ2zNDJlSlxRIgCRNrYjvHvtLRHj2\n9BmSmSlfvHiB+/t7vHjxAk+fPlVAkTOOxxOWtWCe5xaWncwkWUsPcPL+eP8rVGJTILqvIxaGsIZ5\ncy0Q0dTuh1l9KHK6jBh6W/uB6j6QjtA/B+Af/YLP3bubglEOFopu+JZfEUHF0NO9h2EzXfQdvuCV\n2hbvd/sdiYdiFf1anSjT85lbeXmg4xC1Vo1fD/1zyUP7z/bZYiAC2q4LgFtIdCsE4v8Hk1rb4OKk\n4ErmIomDIzaO0qSOLcdjVglsm3w2irfbzR1Vo32xH8P32lSsFbounVyVWnBJyPc4t3/vUmOMwNRp\nIUA8K7KXfXP1oUsO8doWfU/xGSOhakQsJdzd3WGalDAcDodWq9KlxmmamvPSuq6KK1mody3VKlOp\nBKBzA3i1arWqmHkdhqtJReWiTIAFXKqWp2O2FLAw57rHtx8UU/iHAHwqIn8rHPvtRPTXALwE8EdE\n5C8/5kaeg0BdM10M7tGGb1sw2zbq7mTc+vrzXT935FdEQEwoNnnMFSlT2NCjDZ3ifdpG9ghPPz7q\n8KoOpRgKDw/uslXaXK5bP+FmRl+cHdnvf/um6bH6TaLeEAb/Lg7h3kbfs0Zsx3lLOC7mpRG0y/tc\ne8bbJDr/vadW+G8nYkpo0dSBAHS099/FL3ak0Pg+zqj88zzPeO+993BzcwMiwqtXr/DixQvknPHk\niVbILqW0H7W2uxVHWoIXVScMczCTvONAgFb9VumggDDZ9wWaBr4ChqeJ0CDNvq39oEThXwTw58Lf\n3wHwW0Xk+0T0UwD+AhH9hIi83F5IsRiMOYVEnbKXTCOIjGXbWQRUt4VmLzsXN6063ShIZM+/EF9d\nUIjIdy1aSpzBiMDcqAaMPhJE3VkqLnqR3qdY8+ECUIPVFQTgnpi68AOI2bhcQjT3xf70547fXb53\nW9I7qsB1otvmI4xDvOaCUJjqFyW/7XP2rtv7PLzrBVHwdTMSwOHaRghHgtDwkyschBzsQVc3munP\nvBWJqGEGn3zyCaZpwqeffmqp3FgjMW9vsSwLXt+/Rj35yEC9GqumdHermaqpWkRWx6w2r9rKRfM0\ncHdES6SRfW1+mSE7++Na+9JEgTSdyz8D4Kf8mKif59k+/xIR/QqAH4dWkRqabIrBxGw4/sI5Z1tI\ndZhY5mrAVRpExJEL723K/aQgcZNrpekuBYi5j+p5aP1rrs6kYcqRmziBGReW1Vbg0VfgkiN7hql4\nLDeAk6Aij5e9G58pzQKjB03SeAP0rLdRiaUzwB1CRRS+H8c6Zq0axzoF4m6vlEaC1e99DSj+Yq1f\n7x6N+6rH22pB7kkK/Z2lHadkgWt6AkCj+nF7e4uvfe1rYBZ873vfbRmYD4eDWl5AKHVBrX3dKHZQ\nUblqGrZioOKON2j1tVpL66PBbGqFEGnWiMe2H0RS+McA/B8i8qtt7Ig+BvCZiFQi+h3Qug9/+zE3\n61yCh3x6ahsfxVP9is1j7tIrMbZLfdcXROeMzjn8/D0O5qTWfRP8JyXPBAUr3tMJiN+vcyAZju19\ndk5qR1o/iXrOBl+AYuJrkn5fgWwWTj83ir3tp6kddLVfEaxrAxXGN0oLsen5wReB0IukDuegSU9b\nrOCxRGLbb/UB8WItPGzU4bq33hhQKezyq2VZepKVWrFWzY8xT5rLQkQDoW5vb/GjP/oxiBjf+c6n\nOB4fMM8T5sMBh8OM4+uzEQHNxThKc2ymx2CyJ4/jKXDPUvezYanINA1ENl1592vtS9V9EJGfg1aX\n/nOb038XgD9KRCtUTv9ZEfns7d3Q3AbMjLUUjV03oC6xT3AHrGB2dHIp2p1sLPefL1LFu8icj7qz\nzJwnM2fqDdZSsVZuAD1XQ/BzApImWGHSDedOUESEnDXxi7uUqsRAqMJg9GSdUtnSmhOmw0GzB5mU\nQSpq6KuJBmOXWpGJMOUn9oKClG9QU4ZbQghixUWAU6lAtRJhlkdhrQA4gSE4iyCbBFJYIFy0VkTV\nJC05T7Dcn1q4diNtpZSG93apx0FIjU/pKet6HIcTXsVVPI252HsnKwTcskUZAUtWpzGK8nqpGG3u\nYN+WKWw/pzTB3dqdMOj6kKaOddmaLqmEeWqOh3WDTXkCBCirAJLUItRUR7Y8FzoeN4cnuLt7jrsn\nR7x48RKvXjxgnoua1+G+ELr5Pay6FiUUmkY+WBzaT4LIDOEKxopkoKR61lZYBgeszF+t85Ls132A\niPzMzrGfB/Dzj366t74nmoOOcmc4eqOnmfNJFEnFOJ462AQ1IvYLfYErx9J7s3h0YPAKZPSKU1kX\niXQMz5K7bAApIkhyDq4v1M1aGsYLOy/ljERazMOpfiN3pHRJzUyk/uotg5EmPhFTHTwVjffJAUl3\n53X1hSFAZUiCpTJzdFsR7om0YIzqxaT3kkv32Dh+fcO3F25cSb1Qczs+XOefbc67dBiBO2kSkV/v\n/SBQGKuukuypHS4laV/35AEajpPPc3ifeO72WsBMxhIsAdCIU7ZqTX4uV48Zybg53OIwa1WnWs7I\nuaAUbtKqE+D+I01SUGnCM3oZ4Mz9/UQBDs3q7CAj9X312PZueDSKg1D74lxM89UWm3+S/vc1Eakt\nMPu/64W+APQ4m/7lHL6ZEZ14XEn6wszItqHhxWzTxt5u/RBmsKlJYOoVyL1HrgKwYJXV8goqJ4Yn\nCmHlAWhELaoH+l5i8R/NIzP1CtttQxvD9feOBu0hHpHUzKdBmD5DffN0ySkP7s9R4tB3d2yoc2Qa\nCIAXWB1NxT6WGmQ45tfYYhGjuqjxKjEWI4LPMRDKOWyTQAaiMKqE/jcTdcsWpIn/usFV2vGNvCwr\nyrogpYx5PmBdC5Z1bVYGoLu9T9PUXei36myb7yAR2/s5Q01E6ucjmveT8MNIFID2sgDceKSHTSRN\nwY6ukIJtalvUCIMGXAG/2HBiO91pjbuR9s8G+JCHO/vvtFl0vaknmiVw0261tFtxwe7b/MNnf64Q\nkrhzli4+lvi+7uJqCwFbjimNs1apALRGYVzqCejhtrYZE2XEGAIATX1zAGs7b23Okm+SUQJoRAHO\nvYMjewAG1fGmC+utaCssjgQhFN1L8V3BHPpYR1+PS6/J+Pe1ebnaSIxRqInYXcBFpK1b9UcoOJ8W\nHB+OGvGIhGk6oFbBUlZ4Eh3HXZyokiQ1O5p0MKoO3TwZ+6quL4zKFVWUNXS57XHtnSAKYtxYf0zn\ntAHSrR8jJUf354Qg4uudjMpqzoOcc6OSJkzbb9/sxqGcw0YugtRDTpuE24f3YhG1RKhJReEAnjXQ\n5zGAD8f7uyOLhk6n5ATBnzvWTehidcjolBQbUdBJ++gyRUpJcwv686wuYUJXtVyT05NspMTlNo35\n91Rj5HiAbVgP2iIiICUbIp2wBpr24e1wwa7EHw7u04ImYXhwmRbFBeK22G6kx7Y90LOtJ3MQi88H\nGKfTGcuy4nQ6q4vzsihWljIO8y3EAuZ8owMd1KQU42i6FNmfHMBdl6xY0SyXUKqIMZTfPD+Fr6yp\nuMNo+WNcV28KaBCtuyKg54Es27Ku1MorqhTjJj0Hg7Stz0EPtL/JxLCgK1MnFV1ycWlmR491NchB\nURcHo9nUi4d41Gdsih57sI2nMx/FxHEtd5WrEwX0zSaCnBVsI7gFQdr53kcAza2bE6MF6JCJ624R\nCoRRAB371OepDh6Zdm4XBOyZWp9gq/451xe7xt/B39BpCcL99thfFLeZK2pNhnOMmyue72P/RQmF\nox1ay2G8p3u8nk5nnM9nnE5nnJYFZdUCsY51zNNBvWahZkfNAyE2cG/rD2FnCUJEpdS1FHCtkEB8\nH9PeGaIgLrbzHucbHX32JjeK6Cq+xXP3J/zaItAFYuvVxbl0ySneZC6LJqS95w1c3QGroT9iG9hd\npI0LJyDxDJBHP2YkkmZ2arZ5vbECm/PUoLrQAUuh71KOvWtbjMkOdceoYdyHW9nYsyCmSIuZklw+\nobB9tuMv4tJh57pxLNtj436Ry03eiYLW/oyP2a6d7TP25irO0RZrGKNXVXJb1xWn06J5Fc9nnI4O\nLNb2HmVR3CfnqSVgWVdVFRDeIZppu7TZQ+2JrNSALdZk5QpqZSzLAuYKj9d5bHsniELnhHHTALH8\n2h5R6OdegkNbjr5HAIbrhkUyRi8S0Kr5EGmEmuu2bo/2Fj0V44T6OZ6rIXpw7hGbJroDyJkwz1r7\nImWCJCtLRrrgE6kFwQlovB9ljyfR1lQvEUsxhyaZbAkrwS4NNRXa2AoBOUoo4xjr56Aq+dwF/X67\nMRVQCarj5n6uBsiGEGCz6TtRYHhk6z4Qeb1dWy+RMBQuhiO4KKqORufzGcfjCefzamXvVYUACIlm\nk5Rq2NgaFel5eVbP4eFBWUnxGUrqeh+zkmlfHbtSwusZwNlUCGG+ir3stXeCKADjZGpLbeP59/G3\n/mH6O7qOeq1d24CXLbguE6n60f4Gtp5wPaimPydGtwHd4Wmr9+/2K3IEUv8NTeI5Ny84TgUsBU24\nJoJWYmA0otDUD8EaAMbobzAQ0c3GbkQB0IAaE/mHAhahxflTaWXETsh0OPf+08dczpmCkR6nsGUA\noX8mTdgfQz9if4CddfOIdikVRInFfldTIUhFl8pKFJazEobltGhl6FKUCFeBUEFKE6ZptnXR50Kj\nUIF1LUYwfH5N7SN3p4d53gZHLZKmfhHQwEauFTJtBukt7Z0hCrUW9TXIkxXD8PJbuklzzs2DMFFu\nIlJz/yVCqUVTZK9ruybmM/DBj1aByNVFWCe6LSwg5YSUZgAE5l4b0O+t55lwTJHy903hiUQi0h2x\nhrjYGIoWu2Si48CaGdicrgB1rVb8oZo0TbbRQiRoSlptSzomEhf6fj6HUbVh8VThmnsQkIHYOddW\nrqUcrVliqD9PAIjNsUtA3dEmuEKTRWUajqSicTXnr4Rs3NEVEVcV47v5+/h6MRrZxnwrlW6v3Tu+\nZVrOMMQyYHGtWBYtUPvw6oTT6UGzI5UCYSAhW75P6DFTT51Aeli6M4B1Xdo60pRuuCis7OtK16St\njFqtJJ2Wt1vPZ9T5gHl6vArxzhAFd7iJnHZPV/Qir2ozDym7oAMeA5W8vV06aGc2IqIbw5B1q11I\n5FWEY9/IxL4El9KuqThbLrZ9x6g2ZEpWjEQ3WtuIwbmoc03VZbE5BvPqHISb7bWP4KBi140yUR+z\nbuPv+AOZ8t8/JyNcXkBnRAy3qdlYuBEATYRN3fPzov/777AlCm9SIbbzsf3c3nazljy9XikF51PB\ncl6xLmd1SKqi0I+9ZxagijsW6TuRvZo4ZkSEnD2n5GL9jgFyhs1QX0MpJcwTkCqhiubbIBB4tShM\nccPk49o7QxSAZKWyepXntnD8bwQgLRGShMhKCLJ0s9/ehPrf1zeCcWHn4hSiIpvephvV07y7j70S\ntHGxRskgPr89bdPHAUvI6h1or299UFdsVV/djBqBsnBfEUhKjROFh6qY6c/WB4+WAO9rGBXhSBLs\nt6t3DaaocPWlKR8S1dlL9UmaOhI4cSSsfQko5NDMdsNLXYx53ORxTlpY/CMYxfacrTm5ckGtjHVZ\nsJwXnE8L1qWgsrjxRvGooOkY6gM1nvux1D8lgkiGe+8yK96gOBbZeDim4EQ3KxMhRk1JzfGVwVLA\nXHYyZr25vTNEISeNIRhE8mHyNENNc3ndLC6ge211lPaaT8BmcYcmm2fCDJieQUlVhE6ldeH1AjEa\n0WhmvkHM1r55Ci5XYbbv0sRBSpv+SyMMzGJSgEky8FgRFdu9gnZzvdro5U1u9Q3nRMvexcrV6kIm\n0oArNnk3dY9CTVZCqOZy1Aq5wgiF6bmKl7FJKZsxF7PLU+hXIwCMHLJmsTCSBCe2RjjiXERswyNe\nqUW/+nxs18YeAbgmLfizmYG1MM6nVTMqLQvW84paWOdHbCyCJEOipu7OQKxup6kGKZsyGGqT9tif\nDECdkoQTUvIxAFKagGy1MnlCrQUpJ1svPcfpY9o7QxQoZ8tSrIvDvRS7OtHDk7cCI5HmpROUYRJT\nos2ZeqXPL1G8my5YJ0zU8DSr8ZguPePGbMxKOOZ5avjHAEoFIuIFVUZMYmdMnINDFwcbeCRVXZzF\n+0yAn8metg1oQVIyjEHY7HaVE2A4J2Ktft0ebJtVVRGBmwvFsAZBbSMYwUByAgR0zhnnUNwrJU4T\nt++TKYh8TXV5u+Zzte0RhsgQ9iwq8VoRQakVy1pwOi84nxesywq24DTA1LbmqNG9XRwDylaoVn3d\nUlvHSAiYWm3YAddOKPoAqCqRiQCacEharb1qLDYSJZMYfujUB+PqNiF1I+IJ0GozNk4QVwQlUM7g\n9QwRR/n9SjulUebtJAeiQN2Jh5IvQ2omLQ+camAY0bDR+3M22ZICQej92XF+Cuc3kdcCYwCygtGa\nwr3L0zp+ki5FZDRpU52ifDQlKZETsTXrq0zE/BRGYqrOeu583lUDaT4ISsRrkwRs8QsNRCDvxI5w\niDdQyhNUou2/jerV18G+7k+dsn/htiXq8f4+xst5xXI+Y11WlHUFr0WTm4R3D974RnepLTl10HOp\nQDc3iECSDcgmlMItI3RNtamM6uzkI6v3SYkwHyZMhxmoAuHaMLAfOklBGbEusG6fdRGum7e2Ovqw\nCOBivTG8HXHv+vM7V2gcpOmhl5vc7xdxBb+PutbqRPdELW9atJd9bO8ZQr5FClJWb0h3qW2bd4Nl\nRHOccuEYOVpBkpEsdkDsJfuCdz62wT5Eruau0K9p4IpoT++EXbWE7mfQLQdd45Yg3cV3aT/kG+yS\nKDwWK/AxfpMFYgsW+3c15NM4nxcsR5MQamdTJB51EskdGRlV5UwJB2yxBqJgV+U0q0qAdQC/4ZcA\nWFd1pW4jTirpztOMfEjdWpejy9jb2ztBFByA2uqDETwDxkmLv7VdTqJz9O2xqwRCpJVXaykOAud1\nVWFbWGZ07HGHkzwsrEgE9p4/vJMvQCMKOrkCrlZktnFkM6eG+zZiwAIhRSW9hgQjhDDbOyYTNrYb\n6pouvek13AR5bUPGV20cX/q4beenp4bbSExBmhFcJwqXbfwurrEvknjEr6m1YlkWc2E+YVnObZ5A\nbVZ0PIL64F74Tf401ZSA5qqv4ycAlDHlNLVx2c4NMzAZEKlSIUNQwaIZnSlNmD3u5gu8J7D1MNlp\nRPRjRPTfE9HfIKK/TkT/ph3/GhH9AhH9Lfv9oR0nIvoPieiXieh/JaK/9629CJLCyOm6jrpdPFs7\nf+Q+P2hzdWCachDt+jM1VVwy99RxCLc+DPG6LQaxx406hkLqfBKi4lpK78078mbzeLbfmCdSRDDk\n7Yt5E9p+e/PY9cXpeS2ucPM2H1FNGFWHKEVduy6e77/jT+UYNbhNirvfr/gub1ovXvcjzhkzo1gt\n0dP5hMUiIPeyTtlq6O8AmAJmc7wZ162W4+uoq73j8di3ZEl+YH1kqRBoomHPFblXku9ae4ykUAD8\nARH5q0T0HoBfIqJfAPAzAP47EfkTRPQHAfxBAP8OgH8CmobtdwL4+wH8aft9vYmAy0kzzlTlgqnZ\nZt0xBmAumr0oO0WtoFRVPNaSvGbyATJyF+BY9fEpT823PFt0INeKlbUgB0HvTSJqY04JGQkiWTeo\nSS4TTQgMysKW9VOy3yVIF6D+43n7U8qAJCR3FTZOwiRWlamgrOdGHCkBqhaaYJoAogxYSjqFFtiC\nlCZILRbkpdl+dZwJSTQJi3MqICPBagmIjmkkajo9W2lJrSy+GT1TkG+yvpg1TRgADQRDUq+/qolI\nABOrSXNGMMTwEzHuZiHJpJlmLJ+xVVZWqanWChLRLEgWnAXS6MzKFaiENCXMKTfVVASYD8G6oMxZ\nVfPJCIDvUvK8mLpO6wKsx4rTccF6r4WGMyVkYVDl/gyLidCQ70nXoAgEGvwkqND8VwKSGdmYT+UE\nShmHmxs8eVJxPC7IdKtzbFIg5YokFVlWUD2bs1cCZVVRyroigZFvD0i575/HtkgT9TcAABzmSURB\nVLdKCiLyHRH5q/b5FbQC1LcA/DSAP2On/RkA/5R9/mkA/4lo+0UAHxDRN97ylIAldFCuwU1NlN2K\nsxEU2/oCSNu0IDRswtPIt3Ty0gEgrwpkjx1yRba/7RhXS6jBAq/O5n11DqzXkT3P1Bl7ke63zu1N\nHBtQz8rIAfvPCKDpItN6j0As9tp/rPPDmG1H39f8pdg+nCdeeWofC2lSgW28DsT2J1VW7IdNeuhq\nADd1wMfIVak45yyuhEC9Cd+oOoyid1RJm0OUdO49SA8bSaWWgvN5xfmsrsvrsuhmNAekpK6jIBak\nquuEDPtJMHqVSP1rrD/qzmXRuTSCo0RJy8DlST0UU9Z0fykDaULKkxHvntgmkUkXgFY2q2yewhV7\nuNi19oUwBSL6bQD+HgB/BcAnIvId++rvAPjEPn8LwP8bLvtVO/YdXGsG5rVcfilE/FF3/3RzWrJN\nzxFsc52MAEIyMMcn1zMVm95rrN1dbB0HoARI3eigiPqr9uBCtCVXc5RSx3iIuOB04sYwVpU8bbOb\nFBDB1stNHeIbdBTAYsbF1i8XO8T6tDPg8JgRbht0OCMQ4r5HfONQI9CuajnOon0XHA5K9FRsdYxI\n3bL3iA6zi9cKRiYjnETjHBCkO1J5kZtAjH3MARO1U+7VvqSbkkXQYgd87MnmhlkL9BARxCSbclpw\nPJ5x/3CP5bxgXWsHCz27VZgqAlrmIwDdeuZ5J8z7MwEo9ryUkgapGSFtqoFd74l0kFSiLJIBmpBK\nAteqEbQG1FIeCxd/kfZookBEz6D5F/8tEXm5AT6E3pYz+/J+re7D+++9Z1yxSwJOFJQD+ku55bo9\nOBAUG2xNJ9QWStucW7DGrw+3ah9sMUjYEdQe5y6mDSYyeWUkAs7/KY1b0hdaf3DAFwBNwsncqLu/\ng+vbg94CWBKTfs6V0YZvaOfcYiIxIxKE0bow3m90pLqUOEacoNYaiu32cF+9z84ilS4V6IbISBau\nHpOPCFjLQaKPsY9Hi6Gwrqp/SQdu22g0iYAB2hetVeKpkCpYzwWn8xnH4xHL0XIiMOB+7UmoZ9EX\n00QGiSp4LJIm01WfM0KBcnUdUmNMJuTmnDFPs6pMsAhcImTJICHIJMgEVCr6t1QjDjreecqWv+PS\n9f9N7VFEgYhmKEH4syLyX9jhT4noGyLyHVMPft2OfxvAj4XLf4sdG5qEug9f//onw/q72LztePzO\nKa8KnPrOCQ3CYffFdymhJ1Ntui9FLmoprtCpvBMEsYc7jYAZlvRRrsf2vguSiY1mTk2daDBzS5kV\nAywVSKzqlmqLYgyAuRhBvViMI3U3jwYGNolBsNnHfSP1rwgxxNqP+rx0ZNy+lTE9WCdaTgD698qd\nXeXpfYtehr0RWuSrnyuAulD3UoJwxYG0702SoHDPPmGtz/67j5EFjNmxlvVY0IoLezn45byAC1uA\nGbXxh01/A2w9C5MwKAuSVf0iUyEgCWBdQ8Ff0+Q3d023MnPz1AKoYH1WYifIwp7bF5iszmTtsS2q\nTswgql8oR+NjrA8E4OcA/E0R+VPhq78I4Pfa598L4L8Mx3+PWSH+AQAvgprxtmfBc/xpE4C6y+le\nUxdk5xLubuuGKrnAIS50RqLGFWotmteONY2V57hT/dVAL0BVE5MGLIWquRRTO58sDTORb7gu3sak\nnL6g/Vg/vtciQi9NqvHjPob9JxDJ7VgjSAlG6PowUdxLG1wAAzHwAjcdvOwtZiWOKfT0nh3juZA6\nGiFLgKibtOI2/q48zmGY14hrNIK1sXS4M5jK4Y5xdOLmBJCrYF0KzsvJzJCaEg9MBhxSS0sPUpaU\n+50BYVBbHYFoB+KaFEjS5EJijulOZJIlcZXu1enZrihlUNaflCbkaULKMyhNEAHWylhKAUvFdDjg\n7unT3XWw1x4jKfyDAP4lAP8bEf0vduwPA/gTAP48Ef0+AP8PtNAsAPwlAP8kgF8G8ADgX35MR4gS\ncurUu6Hu6OLe3uZW0E9NdZMHENm/CPABGLIxuQelT093OhJsaaq7PjdPwaaWjAu9X+C+7aGvcI4G\ndVMmaFp4W1B9Ifd0brF1YgDAE3v4s0mgpfWcAAYw0hKARLCtj28nMi6q96bc3KUsokBQd+agzRft\nHfdjzv3Hee9zMoJ93avQQ7R9vjYEELh4luICMUFP7zPgeILHJ+h6SehSRGU2CUETpiznReuRGBHw\nvLGJlOwm+xukhAFigKkax6A6j7vK67MzaYlHgkoqXAuQDSBms3R5SL/l/SQnOaT5NikBBYKpFYAx\nMLdWnE9nJAIONzPm6eZiTV1rj6n78D9czGRvv3vnfAHw+x/dA2uKrHYRk21Q8rQJo5aElmNfYMh7\n14tFXBDr/gG+SFzvboTCN2OtUADMQhxCi74Dfv/YF3IkzPEDcv0wbjIXgb2vpoA0Mdexg6AbQ1pJ\nsjC6fRGLivstb6MARLmlQ3NpQtpCGlUvGXCK/v0w1uhSSFS7RsKCcP6bI0L3sg+Pf3dhum1sUwca\nUQyYigO3ThS2rflvhLnoxLAT1m7NUQmgihhBOGmZt4cz6lqNzdj4tczT5gRGQAY1l3A/V2NFKkC5\nMQaCYhAsQBZ0wld1UxPQ3JJz1mApIQZSNmzB9ghyCzFPjm0RQFVUqqkF5zNwPh++cj+F34Rm+j7E\nODZhaj7bYyakQdSv6r2VUsaU5rZRctjIIqLgzDRhXVfM84xs9ymlYFkWLGVt0sOovvTFtE3Xvv3s\nnDDR1ETirWPT6lWGRYnYzUHNSY5fRAJQTWYm0jDtlJVrKABJbSHV6sVzfUMmgHqKr8orhHVRIlks\nP7uqNjW9vnlppjGuQ0S5Dnjc+JGjewGTuIndxdbPd4IY8z70MdfziiVxIQqgYXimni/KKJrHn5pv\nt2vE/xbREu+U+7PIRHAR0rXiCL+oBLGsK16+fIXj8YzzWXMrJmgmamFBEvVVkVqQEjClDJLafGCm\nhh0QCq/gQqBpNkkCIC8YbER3kqq+GFyAIkjTDCSgrAVSF9T1hCndYs4HCPR9QCqlTNMNIIzEZyju\nxWC5wbqesK5nsDBevXiJ1y9fPXo3viNEQZtzE7pAhAlEafeadgZRE+kgDMqTio+2ELuJT4nEIN4a\niaU8EgQ//7KPly69ri74hu3XdnXkgpu1PljEo/fL9GDniFtx3KWA4VZgENS1miQB2TaXCKqwBp1z\nAqAb3Dd8CkljPK5g+66eVDcSgi1BdB8T79s1aWL7LlE1dILvJmmf1/iubt3JXppug1P6uTG1/kUz\nKCabNJ+atCdakWmtKIVRiih+IAGwJp83aEi5mJm8zZYDkUCyIDR1fmLAgvVc9UxwK5biDhptTiBh\nTCIQaA5Iomqh2AzLIKzrFSpZgAhkUZaaJ6siJ4LMGWV128Xj2ztBFMJYDyKt243jmVoZiVxRgy/j\nvtDY7Nv2HfWqPY1zsMW7u5MNDLx5C0EAjGPpl/AUZB1TiJum28IFaH833QJWl1I/AU6cxGMR0M67\nIAr2D4OrsZrXGpeMY0TU/OtRAS1KqoCUJmtRn46hUK2MRMBrWjrGcNkux2oAjNHntA+zhPM6IOfH\nGjDX8JAESibFeNGZ3M3P7gLsRKoRhrTNTYEmrRE0fgCswOL/1975hFqXHAX8V93nfbPQgMZIGGLQ\niWSTlQ4hZBGyjCab0V1WZiG4UdCFi5FsslXQhSCCYiCKmE0SzEbwD4Iro1Emk4lhkqgBHcaMIvgn\nM99793SXi6rq7nPuvd97XyYz9zw89Xi8++4993Sd7ur6X9XXDw9cX8+UQ/WDjY0+kpFSf0qNqkN3\nyjpTHVQOwBjHSJvmG2hUawyuRmamfz9FGbWXRKOgVoEpWcnWUsjNJ/vSlDtTVa2WISkTabJneGQg\nawWbYAqx+lo9vKZwLjCiza5uX6YvVfgLjlN0wVJtwTd2tU63Ueif/BQqCU9+LDTHTixV9YM6BhNF\nuz8ALM5ePedAsfLrvtHDmyydOL2JyUKDoWs5i9Cfv48uaz+ayh0bV5ucarao1kg8GnL6g82spPr4\nOqKvnbH5avjYYw7EalkNB4n7LRk/9GcVYaElhHQ24VA742zMRRYDjdpJrHv8Fnq4MpzGtbpZINki\nWIfKq68dvINSsX6dkVSl0fK+BhW2aVB6FmZoC62vknfLsgdRtNRIG3Ot1kRdNuKnilq40s+qyMnO\n+7TuzLO36Ztcq/M0aqV1c7LvZNOaRSFN1NY3826wDaYAgwJFE0Trx1B1MUo4E9snREPQsJMVFmGm\nxVhRXNRGcRdQSEbashOOPHP+BVOSlqnWhKZz+djk4Ujs4+dGHy1ENeJkg3jLNT/JqlpEpD07UexU\nvQ+ftruYCdKPi2+PvGZYGgVeDPiLaxYrpKDfZ/Gguno9/grrJKh2h2FD4y3OV1c0M8zAQoeR8w/a\nzMGuydTWc2LdmFVEmq9jXqFTmX1Nc6tDKTdqNQ3XB+YSSPTEI0ZtwWlRpaIZ64btlxUNA6E2Pqbu\ny4F+rQJZIKuFRM3Ms+5SWixjQZ0x1LlS5xsrp860vAob0qIXFrybgOIHK4FqIqnAiYjWOdgGU3Cp\njKtqkoYwE8cSQN2hYxI9+LRncXlYsrRoQ20e2lEdtoVdHRRCMIPxxxcXbSqYSGoWTCNX6YwEBi/8\nKPmDuEU6l3e1Xmv1/gn1aEN1CQ60Jo1KD3OtpjOkcNy7fd+7JLen9WvakWfJKX6lfWFRmZEVNC1E\nYl36OQUxvmqUj5vJEunFXZU2og2I0LLNMa30e6m5WCZIa6DrbcxDAxjNhNAMarXw3wKSz7VmcrpC\nSN59uTYNDroTcp2F2YUGqB8U3GgizDmN+auIpt7eXkCT1U0gaiFMqSSKmTJltrVIJnxyglkLlAOq\nM1ozRAFUpNa7qRFmcyV74ZULy6MJOA+bYAqhugqYbe9c2aTf2megi8YcnWCWKm/VgpQU67IgLFPb\nutraNJO17b4aT92sGc3TBcEOzU/imezf0CrUkl7AEwNSaJVNw4CulZybrSay2v/ruehJQZIni4gA\n7dCSYSJEjJGOZz5qUcc5ugJZPV/XpIwZ6TCvcSJRtMq3fhKjgzciEb1S0aT5OJdg6WIDs15pL/N8\nAzCUrZuUjO+P8xAmxChcQoMwGqu2od0kC6YmkpvRlQcmGp2om6/QxzTNMMwcv5ZoU+80EOno4SMY\nEmIjE94S54zBhptFcuZqytzcFEotpDKjaaKxpenKnkeNJCQ5U3UBGzbKuSS2U7AJpgDulxGT9ikS\nWqqZCeE8Gn97dz+zk5XKJIO93gjDWPhi8/oGt7JcbI3UdIJ1yGy07wHkxG4NkwL1833DBFnpx30j\nWIh0tKmD9qPTkkXNYmMGFfazFIKwexJThzEfIYnYEfT+oGFbhjQrRZofJe7b8ydsnkqZ0Tq3z5oz\nU6SpxNfX1xwOvUtQSmWhysf7vXy5j+kU4Gds5DYnp56r1UE07tbnKMLQY3r1ek5i3qzAKDsd1OF4\nAM+g9JJ0u36pUYJnIhLMzcdwbao6DaDazTKUKhVNwWhcY1RrUxebWLS0FH1rgqNMkry+Lapye7Qq\nuGZK2TXHNR10oXpX2AZTaGq5dM9yc8UsNYBjD3xstC5lq3t5o1++qpyowfEU6LYx+6Zdj7XGYx0P\njwy0xeOsNZPhGUDIyePeWrsU82FC5c7TGHMPSSdHBLqETvxtzIERlFKd+eCJNXPrbRDfWTAFYD5c\nU8sNi/b7gbOqH3BSmw8n7jEmjq1V++PVOGbA43zH3+jVMLVQqqnpMW4pPQ17ZBC1+TJsHrKAqDRh\nUAteO4A7Yz0xSrKnQh+8KiGQWpsTSxIzzdc1RtcYus4x5pMkkIzUmdYxQitCMS4j1ZKVxHCstSLV\n/Edj5msakIj9kJKtzUjXd4FtMAURqgplLkx5Il1lkEQZkn2myRqkzPNsW1QS1Q9pISXrBA1+vZcg\nM7s9LF5Ge8X1w1fttWTmcm3OvdlOCL66ykS78GYuFG3ag9mYUXblkrr2VGwYCRLfBOJ2ZjUiSDqo\n/j03P3mhTCRJ9TRsLzCq2AEjLoXqwZqXxJHj1Q+MmSbLXrs+4OcPzFAPdj7B6JDLkxX/DAxN1Iiw\nRQPUVNu53lBqQbBuUGN2Z3stUdXpj6ZQBy2m1EKp9jw9QpOIRrtWKm3pvwGqSsZ6CTSGUc1cUJ2b\nve/brqnQySVnss4tUCvJNbPGtG7cVNArSs3MM8xVzXyRYn65arUOQiLrEwgKWkj1gOjkzXCVzERm\nQqiQMyVPzPU1qDfkCbKYh1kqmKM3+yndhSLFWIEImq8sCqFK8oxeLTMihTxV8nyDXs+gD5jSxFXN\nPFBru3alFheRJGgWkEQlc6Ay17H25HbYBlNYQdiWa1UeQv3D89pp9mTKy9BgnOo06vshtWLTR+Zd\n9FQoRZiuulRKAsXdzQJN5C8TY0aNoUu6fg5gDzsutY9+vTXrWEYrircPV7X4dc6ZaKAjCge7ebu2\nqPkGSlFytuPiTCtQslQOh5lD6b0MrHTa6v3XIdzlWuhCcJ+OKshqbs/Aoz5bweNItkfdI6IZS1OF\nhU/AtJ04QuDuXY+7IHC/UxIg0w5G9lBqq6lMkVfiKdZVkBRu8hP394lPIahiX8zFMuezUqSScuZK\nJn+eTpM6LNwj12UFm2EKzSbMy9OYQ21ehvcwgrYPu6TWTqDt+9CcfaOjyTyZLE7kVdRCPjihiOUv\njD4aERbhr1E160zG1MAmRVk5EUU8gmKaz1xuoNSWvt3Cbdi9TjEF04BSS5MezZ+2n3xHjPH6pVlR\nqZK6Wqw6bBZlwVN9HdZ7ZhkZePRGlibT+/Xt9hIWl7Y5C0fL0X1FThL5qfe6OTKMC+54k6N5s1tk\nR+bYlDkxABbhKnZiGYMZ7M0Rjmgunt2sCuy0UNv8VdTP3XHh4fOeHNGCZTxKwX0WZt5M03A6teMR\nFvg6K/Q22ARTUNXWyy8msTLmFyybkMZ1ffJPOFOih0G7vn80+gRq8yhLs+fjXtXtVfVGqMacCofD\n3A7oCKICmnlj3neaBNYmrQZbtxS0Fg6HA3O5QVo/hdLMpUfVsDT79MRiNydkUivDc0KstS4Ouz31\n3ZPE4/b3en8cSd8VDqurT17X59sGipZzC+a0QGX5mZxhEOM3TtvUXpYdpdmqJrklc6dz1oZmGKOW\nFLRkNSVmHi246+CeWmhhLe8kbt2jPMt8hGJFW2HKYMLFqsqTZXhWWmVfnD+xzg1+FGyCKQA2by3V\nuDOBNYgMG53l5pjnuTOIYfaDmdzciIXNEEhYMdTNDaCtIKhGk1OwrrhFvKe/LphAZwruyMQ0iCjq\nefDgCkvQ0Z7PEKnVQx+95ohzIR0e9JxT82906dOfOfINmvYkefGszVWbon5uNYdux98uCO9ui962\nObllvHEsWRdiQFOzkxwzpIUGtPhscHIsbujNWc1N4f4pGa45h2h/PyXc+We+kFg7yx3IpFTMr7Og\n47S4h+JJezXGdu3ECiEwSg6GYfdSz8SNnh4ZpcxiVZTuWGn5CUmW6dl3gE0wBRG8E23y9GEW5kKE\noiJ0p167MB5OorUyXx9a1584YGOUJofDgYcPHxJTZH37HzaToKJMZeWDKL12HkJlz9QqA179+lM+\nAx1ej34AxjZZLt2Tq50issrafNT8yZG93oKcJzaOqsf21xrWOfNBx3sew2iuncTtMa5f4L/exwN+\nZ793widypG0Ipr7V5IlbCXUfgKws/GCuhor2RijQ7bjBBOnCzM0HiUiPPZUxtTiWL/o+jKO5Rgl2\nYLIRjzs5LXSqEnUS5oyuFYoekElhzn6tQs79+29U49Y3ClSVw/yQxGSZczN2Nt98aNw3JrpqxGlZ\nHkhbK/P1TSe08PwPDr885UHFVw7zYXAyWm+7OhBqK/VVqGpc+Fh76TZr4Brvj8whcIj/Z1XSkIb9\nOJy8j7vM/1+o0oJHR6Lwp0P19GlNnejHtTgNA3dYXX9nE+Ix7Nq4tw7zyJmx1mbk2pxchzpt43l+\niwqWy+JdqtRL04HoG3mCO63G7iaQG77Ob3v0KdZAxOpmLDeEptUZ+NlRbj74CF1LrPEda7tG8lC8\nWolUEXH/hHobOMNftDaH/F1gE0yhlMq3//dVpilTvEfhaw9vmOfD6iALMx3McWdMoR3E6TZ6SFmt\n3nIrEpcE89qGz6KWpW2HuhnWF9+0jihfSS7FQ43XVkOh2puz9NyIgShPbKbRVNDq51xgocXoYt0E\n0kDsXYLagkcT2B7ntwScpiEMdms4bM05aXUQ4h4pDbtopSnUcHal21T/u0Uf1o7JI8/DYzKOfutz\nGsmgHQ2XNIXcW+Hb93t/ROAIt6Mx3b+xYEIm0GHQ+qpGJC258zo0Av9OVETbgwBhZJhxkaT1I7P1\nVTGtYRa0JsgzNT2wXpBJ0Wqaj50MNnYyuxtsgimADoeGhNJcjKtKz7KLfdI57BIWEsOJfVza8OQb\nsVteuCxvcFryuROoMRxV1CVKaBOq0ZY+NkivszgyA0S8JLbj7dNgREVFaxqed6lxtGvPSO52nag3\nM/YuVNp9J4oX0CBHBHOagI61nVNjn4eQiEubuuP83WUIt4HWcATikYhs64/3nFiPQRfelgsBsWC2\nTua0FI28FnUfmWW0WPqURRpGnFuJt3sOEtUP8VGk9mQ+sOhEChOiYIxBC4VMxRyQNdKpQ9AhLZpx\n5/n8Thfiuwki8u/At4H/uDQurwPexv3GH+7/M9x3/OGNfYYfVtUfvO2iTTAFABH5oqq+99J4fKdw\n3/GH+/8M9x1/2MYz3L10aocddvh/ATtT2GGHHRawJabwO5dG4HXCfccf7v8z3Hf8YQPPsBmfwg47\n7LAN2JKmsMMOO2wALs4UROQnReRFEfmGiDx7aXzuCiLyTRH5sog8JyJf9PfeKiJ/JiJf97/ff2k8\nRxCRT4rIKyLywvDeSZzF4Dd9XZ4Xkacvh3nD9RT+nxCRl3wdnhORjwyf/Yrj/6KI/MRlsO4gIu8U\nkb8UkX8Qka+IyC/6+9tagzFf/83+xXI5/hF4F/AA+BLwnkvi9Bi4fxN42+q9XwOe9dfPAr96aTxX\n+H0QeBp44TacsfNA/wTL23k/8IWN4v8J4JdPXPsep6cngKeczvKF8X8SeNpfvwX4muO5qTW4tKbw\nPuAbqvpPqnoDfBp45sI4vR54BviUv/4U8FMXxOUIVPWvgP9cvX0O52eA31eDvwa+T0SefHMwPQ1n\n8D8HzwCfVtVrVf1n7MDj971hyN0BVPVlVf17f/0/wFeBd7CxNbg0U3gH8C/D///q790HUOBPReTv\nROTn/L23q+rL/vrfgLdfBrXHgnM436e1+QVXrz85mGybxl9EfgT4ceALbGwNLs0U7jN8QFWfBj4M\n/LyIfHD8UE3/u1ehnfuIM/DbwI8CPwa8DPz6ZdG5HUTke4HPAL+kqv89fraFNbg0U3gJeOfw/w/5\ne5sHVX3J/74CfA5TTb8V6p3/feVyGN4ZzuF8L9ZGVb+lqkWtCul36SbCJvEXkSuMIfyhqn7W397U\nGlyaKfwt8G4ReUpEHgAfBT5/YZxuBRH5HhF5S7wGPgS8gOH+Mb/sY8AfXwbDx4JzOH8e+Bn3gL8f\n+K9Bxd0MrGzsn8bWAQz/j4rIEyLyFPBu4G/ebPxGECuN/D3gq6r6G8NH21qDS3pjBw/r1zDv8Mcv\njc8dcX4X5tn+EvCVwBv4AeAvgK8Dfw689dK4rvD+I0zFPmD26c+ewxnzeP+Wr8uXgfduFP8/cPye\nxzbRk8P1H3f8XwQ+vAH8P4CZBs8Dz/nvR7a2BntG4w477LCAS5sPO+yww8ZgZwo77LDDAnamsMMO\nOyxgZwo77LDDAnamsMMOOyxgZwo77LDDAnamsMMOOyxgZwo77LDDAv4Pi31ZyHUBWRAAAAAASUVO\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c19727f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "31.03% : mosquito_net\n",
+      " 8.75% : shower_curtain\n",
+      " 4.29% : ladle\n",
+      " 2.84% : lab_coat\n",
+      " 2.69% : window_shade\n"
+     ]
+    }
+   ],
+   "source": [
+    "predict(image_path=image_paths_train[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can try it for another image in our new training-set and the VGG16 model is still confused."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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WZVspGeDq6jX+r7/7Q7x4eQPfd1HX+3fNe4qiCKenpxgOh+Ilm6ZBv99Hv9+H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hhKKYRBAF3XSBrTnu+bk3axWMB3XXS7PTjKQ3raISeeU1ZQcFDXQHrKUJU1sixHlubwfB8XF5dC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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c180b4c18>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 9.71% : quill\n",
+      " 7.01% : ladle\n",
+      " 6.18% : screwdriver\n",
+      " 4.81% : broom\n",
+      " 4.26% : nail\n"
+     ]
+    }
+   ],
+   "source": [
+    "predict(image_path=image_paths_train[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also try an image from our new test-set, and again the VGG16 model is very confused."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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YcUvPHl+0zVtCtIbAsdfNXICwBFmaMr58wcuXjymcOZHjY2RNVi2YLyfUpqDT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HAAAg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7lru7Ozbbf4kGs3+L78N/AfwHwH3/Zf+5MeZ/6//vPwP+faAD/hNjzP/+dz6KRzfo47ehhw1/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\nRAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c1825add8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "26.50% : orangutan\n",
+      " 9.93% : spider_monkey\n",
+      " 4.35% : siamang\n",
+      " 3.27% : howler_monkey\n",
+      " 2.88% : capuchin\n"
+     ]
+    }
+   ],
+   "source": [
+    "predict(image_path=image_paths_test[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Transfer Learning\n",
+    "\n",
+    "The pre-trained VGG16 model was unable to classify images from the Knifey-Spoony dataset. The reason is perhaps that the VGG16 model was trained on the so-called ImageNet dataset which may not have contained many images of cutlery.\n",
+    "\n",
+    "The lower layers of a Convolutional Neural Network can recognize many different shapes or features in an image. It is the last few fully-connected layers that combine these featuers into classification of a whole image. So we can try and re-route the output of the last convolutional layer of the VGG16 model to a new fully-connected neural network that we create for doing classification on the Knifey-Spoony dataset.\n",
+    "\n",
+    "First we print a summary of the VGG16 model so we can see the names and types of its layers, as well as the shapes of the tensors flowing between the layers. This is one of the major reasons we are using the VGG16 model in this tutorial, because the Inception v3 model has so many layers that it is confusing when printed out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "input_1 (InputLayer)         (None, 224, 224, 3)       0         \n",
+      "_________________________________________________________________\n",
+      "block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      \n",
+      "_________________________________________________________________\n",
+      "block1_conv2 (Conv2D)        (None, 224, 224, 64)      36928     \n",
+      "_________________________________________________________________\n",
+      "block1_pool (MaxPooling2D)   (None, 112, 112, 64)      0         \n",
+      "_________________________________________________________________\n",
+      "block2_conv1 (Conv2D)        (None, 112, 112, 128)     73856     \n",
+      "_________________________________________________________________\n",
+      "block2_conv2 (Conv2D)        (None, 112, 112, 128)     147584    \n",
+      "_________________________________________________________________\n",
+      "block2_pool (MaxPooling2D)   (None, 56, 56, 128)       0         \n",
+      "_________________________________________________________________\n",
+      "block3_conv1 (Conv2D)        (None, 56, 56, 256)       295168    \n",
+      "_________________________________________________________________\n",
+      "block3_conv2 (Conv2D)        (None, 56, 56, 256)       590080    \n",
+      "_________________________________________________________________\n",
+      "block3_conv3 (Conv2D)        (None, 56, 56, 256)       590080    \n",
+      "_________________________________________________________________\n",
+      "block3_pool (MaxPooling2D)   (None, 28, 28, 256)       0         \n",
+      "_________________________________________________________________\n",
+      "block4_conv1 (Conv2D)        (None, 28, 28, 512)       1180160   \n",
+      "_________________________________________________________________\n",
+      "block4_conv2 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block4_conv3 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block4_pool (MaxPooling2D)   (None, 14, 14, 512)       0         \n",
+      "_________________________________________________________________\n",
+      "block5_conv1 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_conv2 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_conv3 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_pool (MaxPooling2D)   (None, 7, 7, 512)         0         \n",
+      "_________________________________________________________________\n",
+      "flatten (Flatten)            (None, 25088)             0         \n",
+      "_________________________________________________________________\n",
+      "fc1 (Dense)                  (None, 4096)              102764544 \n",
+      "_________________________________________________________________\n",
+      "fc2 (Dense)                  (None, 4096)              16781312  \n",
+      "_________________________________________________________________\n",
+      "predictions (Dense)          (None, 1000)              4097000   \n",
+      "=================================================================\n",
+      "Total params: 138,357,544\n",
+      "Trainable params: 138,357,544\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see that the last convolutional layer is called 'block5_pool' so we use Keras to get a reference to that layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transfer_layer = model.get_layer('block5_pool')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We refer to this layer as the Transfer Layer because its output will be re-routed to our new fully-connected neural network which will do the classification for the Knifey-Spoony dataset.\n",
+    "\n",
+    "The output of the transfer layer has the following shape:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tf.Tensor 'block5_pool/MaxPool:0' shape=(?, 7, 7, 512) dtype=float32>"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "transfer_layer.output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using the Keras API it is very simple to create a new model. First we take the part of the VGG16 model from its input-layer to the output of the transfer-layer. We may call this the convolutional model, because it consists of all the convolutional layers from the VGG16 model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conv_model = Model(inputs=model.input,\n",
+    "                   outputs=transfer_layer.output)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then use Keras to build a new model on top of this."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Start a new Keras Sequential model.\n",
+    "new_model = Sequential()\n",
+    "\n",
+    "# Add the convolutional part of the VGG16 model from above.\n",
+    "new_model.add(conv_model)\n",
+    "\n",
+    "# Flatten the output of the VGG16 model because it is from a\n",
+    "# convolutional layer.\n",
+    "new_model.add(Flatten())\n",
+    "\n",
+    "# Add a dense (aka. fully-connected) layer.\n",
+    "# This is for combining features that the VGG16 model has\n",
+    "# recognized in the image.\n",
+    "new_model.add(Dense(1024, activation='relu'))\n",
+    "\n",
+    "# Add a dropout-layer which may prevent overfitting and\n",
+    "# improve generalization ability to unseen data e.g. the test-set.\n",
+    "new_model.add(Dropout(0.5))\n",
+    "\n",
+    "# Add the final layer for the actual classification.\n",
+    "new_model.add(Dense(num_classes, activation='softmax'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We use the Adam optimizer with a fairly low learning-rate. The learning-rate could perhaps be larger. But if you try and train more layers of the original VGG16 model, then the learning-rate should be quite low otherwise the pre-trained weights of the VGG16 model will be distorted and it will be unable to learn."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer = Adam(lr=1e-5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We have 3 classes in the Knifey-Spoony dataset so Keras needs to use this loss-function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "loss = 'categorical_crossentropy'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The only performance metric we are interested in is the classification accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "metrics = ['categorical_accuracy']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Helper-function for printing whether a layer in the VGG16 model should be trained."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_layer_trainable():\n",
+    "    for layer in conv_model.layers:\n",
+    "        print(\"{0}:\\t{1}\".format(layer.trainable, layer.name))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "By default all the layers of the VGG16 model are trainable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True:\tinput_1\n",
+      "True:\tblock1_conv1\n",
+      "True:\tblock1_conv2\n",
+      "True:\tblock1_pool\n",
+      "True:\tblock2_conv1\n",
+      "True:\tblock2_conv2\n",
+      "True:\tblock2_pool\n",
+      "True:\tblock3_conv1\n",
+      "True:\tblock3_conv2\n",
+      "True:\tblock3_conv3\n",
+      "True:\tblock3_pool\n",
+      "True:\tblock4_conv1\n",
+      "True:\tblock4_conv2\n",
+      "True:\tblock4_conv3\n",
+      "True:\tblock4_pool\n",
+      "True:\tblock5_conv1\n",
+      "True:\tblock5_conv2\n",
+      "True:\tblock5_conv3\n",
+      "True:\tblock5_pool\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_layer_trainable()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In Transfer Learning we are initially only interested in reusing the pre-trained VGG16 model as it is, so we will disable training for all its layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conv_model.trainable = False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for layer in conv_model.layers:\n",
+    "    layer.trainable = False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "False:\tinput_1\n",
+      "False:\tblock1_conv1\n",
+      "False:\tblock1_conv2\n",
+      "False:\tblock1_pool\n",
+      "False:\tblock2_conv1\n",
+      "False:\tblock2_conv2\n",
+      "False:\tblock2_pool\n",
+      "False:\tblock3_conv1\n",
+      "False:\tblock3_conv2\n",
+      "False:\tblock3_conv3\n",
+      "False:\tblock3_pool\n",
+      "False:\tblock4_conv1\n",
+      "False:\tblock4_conv2\n",
+      "False:\tblock4_conv3\n",
+      "False:\tblock4_pool\n",
+      "False:\tblock5_conv1\n",
+      "False:\tblock5_conv2\n",
+      "False:\tblock5_conv3\n",
+      "False:\tblock5_pool\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_layer_trainable()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once we have changed whether the model's layers are trainable, we need to compile the model for the changes to take effect."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_model.compile(optimizer=optimizer, loss=loss, metrics=metrics)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An epoch normally means one full processing of the training-set. But the data-generator that we created above, will produce batches of training-data for eternity. So we need to define the number of steps we want to run for each \"epoch\" and this number gets multiplied by the batch-size defined above. In this case we have 100 steps per epoch and a batch-size of 20, so the \"epoch\" consists of 2000 random images from the training-set. We run 20 such \"epochs\".\n",
+    "\n",
+    "The reason these particular numbers were chosen, was because they seemed to be sufficient for training with this particular model and dataset, and it didn't take too much time, and resulted in 20 data-points (one for each \"epoch\") which can be plotted afterwards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "epochs = 20\n",
+    "steps_per_epoch = 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Training the new model is just a single function call in the Keras API. This takes about 6-7 minutes on a GTX 1070 GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "100/100 [==============================] - 20s - loss: 1.0910 - categorical_accuracy: 0.4575 - val_loss: 0.8024 - val_categorical_accuracy: 0.7472\n",
+      "Epoch 2/20\n",
+      "100/100 [==============================] - 22s - loss: 0.9378 - categorical_accuracy: 0.5600 - val_loss: 0.7077 - val_categorical_accuracy: 0.7566\n",
+      "Epoch 3/20\n",
+      "100/100 [==============================] - 19s - loss: 0.8551 - categorical_accuracy: 0.6130 - val_loss: 0.6477 - val_categorical_accuracy: 0.7717\n",
+      "Epoch 4/20\n",
+      "100/100 [==============================] - 19s - loss: 0.7747 - categorical_accuracy: 0.6410 - val_loss: 0.7183 - val_categorical_accuracy: 0.6547\n",
+      "Epoch 5/20\n",
+      "100/100 [==============================] - 19s - loss: 0.7438 - categorical_accuracy: 0.6645 - val_loss: 0.5706 - val_categorical_accuracy: 0.8113\n",
+      "Epoch 6/20\n",
+      "100/100 [==============================] - 19s - loss: 0.6836 - categorical_accuracy: 0.7040 - val_loss: 0.5912 - val_categorical_accuracy: 0.7962\n",
+      "Epoch 7/20\n",
+      "100/100 [==============================] - 19s - loss: 0.6527 - categorical_accuracy: 0.7130 - val_loss: 0.5509 - val_categorical_accuracy: 0.8094\n",
+      "Epoch 8/20\n",
+      "100/100 [==============================] - 19s - loss: 0.6310 - categorical_accuracy: 0.7275 - val_loss: 0.6414 - val_categorical_accuracy: 0.7038\n",
+      "Epoch 9/20\n",
+      "100/100 [==============================] - 19s - loss: 0.6072 - categorical_accuracy: 0.7455 - val_loss: 0.6630 - val_categorical_accuracy: 0.6887\n",
+      "Epoch 10/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5986 - categorical_accuracy: 0.7525 - val_loss: 0.6142 - val_categorical_accuracy: 0.7340\n",
+      "Epoch 11/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5831 - categorical_accuracy: 0.7525 - val_loss: 0.5202 - val_categorical_accuracy: 0.8057\n",
+      "Epoch 12/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5747 - categorical_accuracy: 0.7480 - val_loss: 0.5289 - val_categorical_accuracy: 0.7943\n",
+      "Epoch 13/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5735 - categorical_accuracy: 0.7570 - val_loss: 0.6357 - val_categorical_accuracy: 0.6981\n",
+      "Epoch 14/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5377 - categorical_accuracy: 0.7760 - val_loss: 0.5130 - val_categorical_accuracy: 0.8113\n",
+      "Epoch 15/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5507 - categorical_accuracy: 0.7740 - val_loss: 0.6038 - val_categorical_accuracy: 0.7340\n",
+      "Epoch 16/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5228 - categorical_accuracy: 0.7865 - val_loss: 0.5141 - val_categorical_accuracy: 0.7943\n",
+      "Epoch 17/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5058 - categorical_accuracy: 0.7855 - val_loss: 0.5561 - val_categorical_accuracy: 0.7698\n",
+      "Epoch 18/20\n",
+      "100/100 [==============================] - 19s - loss: 0.4775 - categorical_accuracy: 0.8080 - val_loss: 0.4904 - val_categorical_accuracy: 0.8057\n",
+      "Epoch 19/20\n",
+      "100/100 [==============================] - 19s - loss: 0.5360 - categorical_accuracy: 0.7755 - val_loss: 0.6344 - val_categorical_accuracy: 0.7189\n",
+      "Epoch 20/20\n",
+      "100/100 [==============================] - 19s - loss: 0.4882 - categorical_accuracy: 0.8100 - val_loss: 0.7323 - val_categorical_accuracy: 0.6660\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = new_model.fit_generator(generator=generator_train,\n",
+    "                                  epochs=epochs,\n",
+    "                                  steps_per_epoch=steps_per_epoch,\n",
+    "                                  class_weight=class_weight,\n",
+    "                                  validation_data=generator_test,\n",
+    "                                  validation_steps=steps_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Keras records the performance metrics at the end of each \"epoch\" so they can be plotted later. This shows that the loss-value for the training-set generally decreased during training, but the loss-values for the test-set were a bit more erratic. Similarly, the classification accuracy generally improved on the training-set while it was a bit more erratic on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ESflbFOeee+6haJwlS5awceNGTjrpJFatWsVJJ53E/fffT/fu3VmwYAEbNmygZs2a9O7d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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c13e05978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_training_history(history)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "After training we can also evaluate the new model's performance on the test-set using a single function call in the Keras API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "result = new_model.evaluate_generator(generator_test, steps=steps_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test-set classification accuracy: 66.60%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test-set classification accuracy: {0:.2%}\".format(result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can plot some examples of mis-classified images from the test-set. Some of these images are also difficult for a human to classify.\n",
+    "\n",
+    "The confusion matrix shows that the new model is especially having problems classifying the forky-class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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jI4oyp7vWJ0gT8rwgSSOyWuZnv/BFPN1iRc7VecrFYoGiSDimSVmajfBCVXF5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IJNvF7x8vSMd955h9FgwCoKkf++DjtREvE8rwnJTVNEqQntyLLGYDMvcnq9PoIA682a5yfPifOk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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c18175550>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Confusion matrix:\n",
+      "[[151   0   0]\n",
+      " [102  32   3]\n",
+      " [ 71   1 170]]\n",
+      "(0) forky\n",
+      "(1) knifey\n",
+      "(2) spoony\n"
+     ]
+    }
+   ],
+   "source": [
+    "example_errors()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fine-Tuning\n",
+    "\n",
+    "In Transfer Learning the original pre-trained model is locked or frozen during training of the new classifier. This ensures that the weights of the original VGG16 model will not change. One advantage of this, is that the training of the new classifier will not propagate large gradients back through the VGG16 model that may either distort its weights or cause overfitting to the new dataset.\n",
+    "\n",
+    "But once the new classifier has been trained we can try and gently fine-tune some of the deeper layers in the VGG16 model as well. We call this Fine-Tuning.\n",
+    "\n",
+    "It is a bit unclear whether Keras uses the `trainable` boolean in each layer of the original VGG16 model or if it is overrided by the `trainable` boolean in the \"meta-layer\" we call `conv_layer`. So we will enable the `trainable` boolean for both `conv_layer` and all the relevant layers in the original VGG16 model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conv_model.trainable = True"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We want to train the last two convolutional layers whose names contain 'block5' or 'block4'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for layer in conv_model.layers:\n",
+    "    # Boolean whether this layer is trainable.\n",
+    "    trainable = ('block5' in layer.name or 'block4' in layer.name)\n",
+    "    \n",
+    "    # Set the layer's bool.\n",
+    "    layer.trainable = trainable"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can check that this has updated the `trainable` boolean for the relevant layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "False:\tinput_1\n",
+      "False:\tblock1_conv1\n",
+      "False:\tblock1_conv2\n",
+      "False:\tblock1_pool\n",
+      "False:\tblock2_conv1\n",
+      "False:\tblock2_conv2\n",
+      "False:\tblock2_pool\n",
+      "False:\tblock3_conv1\n",
+      "False:\tblock3_conv2\n",
+      "False:\tblock3_conv3\n",
+      "False:\tblock3_pool\n",
+      "True:\tblock4_conv1\n",
+      "True:\tblock4_conv2\n",
+      "True:\tblock4_conv3\n",
+      "True:\tblock4_pool\n",
+      "True:\tblock5_conv1\n",
+      "True:\tblock5_conv2\n",
+      "True:\tblock5_conv3\n",
+      "True:\tblock5_pool\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_layer_trainable()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use a lower learning-rate for the fine-tuning so the weights of the original VGG16 model only get changed slowly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer_fine = Adam(lr=1e-7)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Because we have defined a new optimizer and have changed the `trainable` boolean for many of the layers in the model, we need to recompile the model so the changes can take effect before we continue training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_model.compile(optimizer=optimizer_fine, loss=loss, metrics=metrics)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The training can then be continued so as to fine-tune the VGG16 model along with the new classifier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "100/100 [==============================] - 28s - loss: 0.4756 - categorical_accuracy: 0.8065 - val_loss: 0.5877 - val_categorical_accuracy: 0.7340\n",
+      "Epoch 2/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4781 - categorical_accuracy: 0.8035 - val_loss: 0.5577 - val_categorical_accuracy: 0.7717\n",
+      "Epoch 3/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4530 - categorical_accuracy: 0.8150 - val_loss: 0.5464 - val_categorical_accuracy: 0.7774\n",
+      "Epoch 4/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4440 - categorical_accuracy: 0.8275 - val_loss: 0.5442 - val_categorical_accuracy: 0.7811\n",
+      "Epoch 5/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4463 - categorical_accuracy: 0.8345 - val_loss: 0.5536 - val_categorical_accuracy: 0.7811\n",
+      "Epoch 6/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4446 - categorical_accuracy: 0.8290 - val_loss: 0.5497 - val_categorical_accuracy: 0.7849\n",
+      "Epoch 7/20\n",
+      "100/100 [==============================] - 26s - loss: 0.4474 - categorical_accuracy: 0.8150 - val_loss: 0.5345 - val_categorical_accuracy: 0.7868\n",
+      "Epoch 8/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4330 - categorical_accuracy: 0.8305 - val_loss: 0.5437 - val_categorical_accuracy: 0.7811\n",
+      "Epoch 9/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4136 - categorical_accuracy: 0.8345 - val_loss: 0.5489 - val_categorical_accuracy: 0.7792\n",
+      "Epoch 10/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4262 - categorical_accuracy: 0.8330 - val_loss: 0.5403 - val_categorical_accuracy: 0.7849\n",
+      "Epoch 11/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4228 - categorical_accuracy: 0.8320 - val_loss: 0.5425 - val_categorical_accuracy: 0.7811\n",
+      "Epoch 12/20\n",
+      "100/100 [==============================] - 26s - loss: 0.4026 - categorical_accuracy: 0.8365 - val_loss: 0.5432 - val_categorical_accuracy: 0.7792\n",
+      "Epoch 13/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4248 - categorical_accuracy: 0.8280 - val_loss: 0.5269 - val_categorical_accuracy: 0.7943\n",
+      "Epoch 14/20\n",
+      "100/100 [==============================] - 26s - loss: 0.4297 - categorical_accuracy: 0.8305 - val_loss: 0.5288 - val_categorical_accuracy: 0.7925\n",
+      "Epoch 15/20\n",
+      "100/100 [==============================] - 26s - loss: 0.3989 - categorical_accuracy: 0.8415 - val_loss: 0.5270 - val_categorical_accuracy: 0.7925\n",
+      "Epoch 16/20\n",
+      "100/100 [==============================] - 26s - loss: 0.3801 - categorical_accuracy: 0.8430 - val_loss: 0.5251 - val_categorical_accuracy: 0.7925\n",
+      "Epoch 17/20\n",
+      "100/100 [==============================] - 27s - loss: 0.4224 - categorical_accuracy: 0.8315 - val_loss: 0.5336 - val_categorical_accuracy: 0.7830\n",
+      "Epoch 18/20\n",
+      "100/100 [==============================] - 26s - loss: 0.4073 - categorical_accuracy: 0.8340 - val_loss: 0.5246 - val_categorical_accuracy: 0.7906\n",
+      "Epoch 19/20\n",
+      "100/100 [==============================] - 27s - loss: 0.3952 - categorical_accuracy: 0.8480 - val_loss: 0.5292 - val_categorical_accuracy: 0.7830\n",
+      "Epoch 20/20\n",
+      "100/100 [==============================] - 26s - loss: 0.3984 - categorical_accuracy: 0.8425 - val_loss: 0.5220 - val_categorical_accuracy: 0.7925\n"
+     ]
+    }
+   ],
+   "source": [
+    "history = new_model.fit_generator(generator=generator_train,\n",
+    "                                  epochs=epochs,\n",
+    "                                  steps_per_epoch=steps_per_epoch,\n",
+    "                                  class_weight=class_weight,\n",
+    "                                  validation_data=generator_test,\n",
+    "                                  validation_steps=steps_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then plot the loss-values and classification accuracy from the training. Depending on the dataset, the original model, the new classifier, and hyper-parameters such as the learning-rate, this may improve the classification accuracies on both training- and test-set, or it may improve on the training-set but worsen it for the test-set in case of overfitting. It may require some experimentation with the parameters to get this right."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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gao9jx9r8eEv2IX8r2717N2PGjKFfv37k5eXx9ttvAzaMwYknnkhubi79+/dn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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c10259710>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_training_history(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = new_model.evaluate_generator(generator_test, steps=steps_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test-set classification accuracy: 79.25%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test-set classification accuracy: {0:.2%}\".format(result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can plot some examples of mis-classified images again, and we can also see from the confusion matrix that the model is still having problems classifying forks correctly.\n",
+    "\n",
+    "A part of the reason might be that the training-set contains only 994 images of forks, while it contains 1210 images of knives and 1966 images of spoons. Even though we have weighted the classes to compensate for this imbalance, and we have also augmented the training-set by randomly transforming the images in different ways during training, it may not be enough for the model to properly learn to recognize forks."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ijI3SHaN6JntbCW/90Q8QlBG9Yo6iS2zcf4x74OPkBQgFZE1GcHKO+vuEcYDt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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f0c10690e80>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Confusion matrix:\n",
+      "[[141   3   7]\n",
+      " [ 65  70   2]\n",
+      " [ 32   1 209]]\n",
+      "(0) forky\n",
+      "(1) knifey\n",
+      "(2) spoony\n"
+     ]
+    }
+   ],
+   "source": [
+    "example_errors()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use the Keras API for TensorFlow to do both Transfer Learning and Fine-Tuning of the pre-trained VGG16 model on a new dataset. It is much easier to implement this using the Keras API rather than directly in TensorFlow.\n",
+    "\n",
+    "Whether Fine-Tuning improves the classification accuracy over just using Transfer Learning depends on the pre-trained model, the transfer-layer you choose, your dataset, and how you train the new model. You may experience improved performance from the fine-tuning, or you may experience worse performance if the fine-tuned model is overfitting your training-data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook and the other files before making any changes.\n",
+    "\n",
+    "* Try using other layers in the VGG16 model as the transfer layer. How does it affect the training and classification accuracy?\n",
+    "* Change the new classification layers we added. Can you improve the classification accuracy by either increasing or decreasing the number of nodes in the fully-connected / dense layer?\n",
+    "* What happens if you remove the Dropout-layer in the new classifier?\n",
+    "* Change the learning-rates for both Transfer Learning and Fine-Tuning.\n",
+    "* Try fine-tuning on the whole VGG16 model instead of just the last few layers. How does it affect the classification accuracy on the training- and test-sets? Why?\n",
+    "* Try doing the fine-tuning from the beginning so the new classification layers are trained from scratch along with all the convolutional layers of the VGG16 model. You may need to lower the learning-rate for the optimizer.\n",
+    "* Add a few images from the test-set to the training-set. Does that improve performance?\n",
+    "* Try deleting some of the knifey and spoony images from the training-set so the classes all have the same number of images. Does that improve the numbers in the confusion-matrix?\n",
+    "* Use another dataset.\n",
+    "* Use another pre-trained model available from Keras.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2017 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/README.md b/README.md
index 63dd275..fde06a3 100644
--- a/README.md
+++ b/README.md
@@ -41,7 +41,7 @@ Even a few dollars are appreciated. Thanks!
 
 9. Video Data ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
 
-10. Not available yet. Please [support this issue](https://github.com/tensorflow/tensorflow/issues/5036) on GitHub so we can get it done!
+10. Fine-Tuning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
 
 11. Adversarial Examples ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
 
diff --git a/dataset.py b/dataset.py
index 545c190..a4a04ee 100644
--- a/dataset.py
+++ b/dataset.py
@@ -20,6 +20,7 @@
 
 import numpy as np
 import os
+import shutil
 from cache import cache
 
 ########################################################################
@@ -254,6 +255,75 @@ def get_test_set(self):
                one_hot_encoded(class_numbers=self.class_numbers_test,
                                num_classes=self.num_classes)
 
+    def copy_files(self, train_dir, test_dir):
+        """
+        Copy all the files in the training-set to train_dir
+        and copy all the files in the test-set to test_dir.
+
+        For example, the normal directory structure for the
+        different classes in the training-set is:
+
+        knifey-spoony/forky/
+        knifey-spoony/knifey/
+        knifey-spoony/spoony/
+
+        Normally the test-set is a sub-dir of the training-set:
+
+        knifey-spoony/forky/test/
+        knifey-spoony/knifey/test/
+        knifey-spoony/spoony/test/
+
+        But some APIs use another dir-structure for the training-set:
+        
+        knifey-spoony/train/forky/
+        knifey-spoony/train/knifey/
+        knifey-spoony/train/spoony/
+
+        and for the test-set:
+        
+        knifey-spoony/test/forky/
+        knifey-spoony/test/knifey/
+        knifey-spoony/test/spoony/
+
+        :param train_dir: Directory for the training-set e.g. 'knifey-spoony/train/'
+        :param test_dir: Directory for the test-set e.g. 'knifey-spoony/test/'
+        :return: Nothing. 
+        """
+
+        # Helper-function for actually copying the files.
+        def _copy_files(src_paths, dst_dir, class_numbers):
+
+            # Create a list of dirs for each class, e.g.:
+            # ['knifey-spoony/test/forky/',
+            #  'knifey-spoony/test/knifey/',
+            #  'knifey-spoony/test/spoony/']
+            class_dirs = [os.path.join(dst_dir, class_name + "/")
+                          for class_name in self.class_names]
+
+            # Check if each class-directory exists, otherwise create it.
+            for dir in class_dirs:
+                if not os.path.exists(dir):
+                    os.makedirs(dir)
+
+            # For all the file-paths and associated class-numbers,
+            # copy the file to the destination dir for that class.
+            for src, cls in zip(src_paths, class_numbers):
+                shutil.copy(src=src, dst=class_dirs[cls])
+
+        # Copy the files for the training-set.
+        _copy_files(src_paths=self.get_paths(test=False),
+                    dst_dir=train_dir,
+                    class_numbers=self.class_numbers)
+
+        print("- Copied training-set to:", train_dir)
+
+        # Copy the files for the test-set.
+        _copy_files(src_paths=self.get_paths(test=True),
+                    dst_dir=test_dir,
+                    class_numbers=self.class_numbers_test)
+
+        print("- Copied test-set to:", test_dir)
+
 
 ########################################################################
 
diff --git a/images/10_transfer_learning_flowchart.png b/images/10_transfer_learning_flowchart.png
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diff --git a/knifey.py b/knifey.py
index 0845fb1..6079529 100644
--- a/knifey.py
+++ b/knifey.py
@@ -28,6 +28,12 @@
 # Set this before you start calling any of the functions below.
 data_dir = "data/knifey-spoony/"
 
+# Directory for the training-set after copying the files using copy_files().
+train_dir = os.path.join(data_dir, "train/")
+
+# Directory for the test-set after copying the files using copy_files().
+test_dir = os.path.join(data_dir, "test/")
+
 # URL for the data-set on the internet.
 data_url = "https://github.com/Hvass-Labs/knifey-spoony/raw/master/knifey-spoony.tar.gz"
 
@@ -91,6 +97,27 @@ def load():
     return dataset
 
 
+def copy_files():
+    """
+    Copy all the files in the training-set to train_dir
+    and copy all the files in the test-set to test_dir.
+
+    This creates the directories if they don't already exist,
+    and it overwrites the images if they already exist.
+
+    The images are originally stored in a directory-structure
+    that is incompatible with e.g. the Keras API. This function
+    copies the files to a dir-structure that works with e.g. Keras.
+    """
+
+    # Load the Knifey-Spoony dataset.
+    # This is very fast as it only gathers lists of the files
+    # and does not actually load the images into memory.
+    dataset = load()
+
+    # Copy the files to separate training- and test-dirs.
+    dataset.copy_files(train_dir=train_dir, test_dir=test_dir)
+
 ########################################################################
 
 if __name__ == '__main__':

From 025fcfaef7d63df5d6b1f0c56db7b06c0180eaa5 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 14 Dec 2017 14:16:56 +0100
Subject: [PATCH 30/61] Added plt.show()

---
 01_Simple_Linear_Model.ipynb | 307 ++++++++++++++---------------------
 1 file changed, 121 insertions(+), 186 deletions(-)

diff --git a/01_Simple_Linear_Model.ipynb b/01_Simple_Linear_Model.ipynb
index d6dacad..00ae48b 100644
--- a/01_Simple_Linear_Model.ipynb
+++ b/01_Simple_Linear_Model.ipynb
@@ -32,10 +32,17 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -48,20 +55,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
+    "This was developed using Python 3.6.1 (Anaconda) and TensorFlow version:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.12.0-rc1'"
+       "'1.4.0'"
       ]
      },
      "execution_count": 2,
@@ -90,9 +95,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -120,9 +123,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -159,9 +160,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -192,9 +191,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "data.test.cls = np.array([label.argmax() for label in data.test.labels])"
@@ -210,9 +207,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -246,9 +241,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# We know that MNIST images are 28 pixels in each dimension.\n",
@@ -281,9 +274,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -307,7 +298,11 @@
     "        \n",
     "        # Remove ticks from the plot.\n",
     "        ax.set_xticks([])\n",
-    "        ax.set_yticks([])"
+    "        ax.set_yticks([])\n",
+    "        \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
    ]
   },
   {
@@ -320,15 +315,13 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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ANzuvq96Vd4EErN/vzxz4UwG4NbuSQkvW2jq6z6u7OhK5eDyOSCSCQCDA7vIE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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3765ecd390>"
+       "<matplotlib.figure.Figure at 0x7f025779c550>"
       ]
      },
      "metadata": {},
@@ -388,9 +381,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = tf.placeholder(tf.float32, [None, img_size_flat])"
@@ -406,9 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true = tf.placeholder(tf.float32, [None, num_classes])"
@@ -424,9 +413,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true_cls = tf.placeholder(tf.int64, [None])"
@@ -451,9 +438,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weights = tf.Variable(tf.zeros([img_size_flat, num_classes]))"
@@ -469,9 +454,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "biases = tf.Variable(tf.zeros([num_classes]))"
@@ -498,9 +481,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "logits = tf.matmul(x, weights) + biases"
@@ -518,9 +499,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = tf.nn.softmax(logits)"
@@ -536,10 +515,18 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-18-1b869074280b>:1: calling argmax (from tensorflow.python.ops.math_ops) with dimension is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use the `axis` argument instead\n"
+     ]
+    }
+   ],
    "source": [
     "y_pred_cls = tf.argmax(y_pred, dimension=1)"
    ]
@@ -565,9 +552,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=logits,\n",
@@ -584,9 +569,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cost = tf.reduce_mean(cross_entropy)"
@@ -611,9 +594,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.5).minimize(cost)"
@@ -638,9 +619,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -656,9 +635,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
@@ -683,9 +660,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session = tf.Session()"
@@ -703,9 +678,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -728,9 +701,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "batch_size = 100"
@@ -746,9 +717,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize(num_iterations):\n",
@@ -788,9 +757,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "feed_dict_test = {x: data.test.images,\n",
@@ -808,9 +775,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def print_accuracy():\n",
@@ -831,9 +796,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def print_confusion_matrix():\n",
@@ -860,7 +823,11 @@
     "    plt.xticks(tick_marks, range(num_classes))\n",
     "    plt.yticks(tick_marks, range(num_classes))\n",
     "    plt.xlabel('Predicted')\n",
-    "    plt.ylabel('True')"
+    "    plt.ylabel('True')\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
    ]
   },
   {
@@ -873,9 +840,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors():\n",
@@ -921,9 +886,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_weights():\n",
@@ -956,7 +919,11 @@
     "\n",
     "        # Remove ticks from each sub-plot.\n",
     "        ax.set_xticks([])\n",
-    "        ax.set_yticks([])"
+    "        ax.set_yticks([])\n",
+    "        \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
    ]
   },
   {
@@ -971,9 +938,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -990,15 +955,13 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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K2bTbllyxL3PbAp/HPI1C2u12uZaJNjfKgAwEAohGo9yCzePxLN3CEWbHcDhEu93mAx5l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\nAElFTkSuQmCC\n",
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0u7Vqxaodn61WpnyGGX4L7IQTTgDg3nvvBaBp06aRYk+XMk0RkQhUaYqIRGBR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\nQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763c277b8>"
+       "<matplotlib.figure.Figure at 0x7f024ecaacc0>"
       ]
      },
      "metadata": {},
@@ -1021,9 +984,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimize(num_iterations=1)"
@@ -1032,15 +993,13 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 40.7%\n"
+      "Accuracy on test-set: 43.1%\n"
      ]
     }
    ],
@@ -1051,15 +1010,13 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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pyExyyUy3NkVROCZ+dHTE4avJZAK73Q6n0wmn0zkzA7bf76PdbrMAG5/XOImqVqsBmNpj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PWgDfpJHHB4CPgQUishgYhRdtjwdWA0uBR4FZukOCtpBewGI/rB9J/O1iVZWRMnbO/QL8\nEZiK9zsf45xb7n98CLAujTzeAtQRr6vLErynxQD3AQ1FZBlwEzBfd0jSptkbeCaN/BSaTF3HjYG3\nReQDYA4w0Tn3mv9ZPl3HBwNL/WcTHYGrk528oIZRisgrwBnOuV9znReTeX7k/qpzzlZbq8IK/Tou\nqErTGGNyzYZRGmNMBFZpGmNMBFZpGmNMBFZpGmNMBOl0bqeoqMgVFxdnKCuFYd68eRvcdjSrt5Vx\n1WdlHE1alWZxcTFz56YyAqvqEJHtalkAK+Oqz8o4Grs9N8aYCKzSNMaYCKzSNMaYCKzSNMaYCNJ6\nEGRMRW3ZsgWAo47y5omdP9+bP+P0008H4IUXXshNxoxJwiJNY4yJIK8jzTfffBMIopHly73Zw15+\n+eVYmldeeQWAU0+NX5zwyCOPBODYY4/Nej5N6jTC/NOf/gTAggULgGCS4MMPPzw3GTMmRRZpGmNM\nBHkVaX7//fcA9OnTB4DXX/dms69duzYAv/zyCwA//PBDqX1nzpwZ91r3qVOnTuy9UaNGAdCzZ89M\nZttEMHKkNxn/Aw88AEDHjh0BuPXWWwFo3z6rixyaHNq4cSMQtF9Pnjw59tnw4cOB4I7jrLPOAqBZ\ns2YA/PnPf46l3W233bKf2QQs0jTGmAjyKtK87rrrgPg2S4Aff/wRgBYtWgDQqFGj2Gf16tWLS7tt\nm7dgoLZ16r4AF13krY21//77A3DIIYdkLO8mNV9++WXc606dOgEWYVZFemd41113AXDfffcBpf8G\nIIgw9d/x48fHfb5hw4bY9iOPPJL5zEZgkaYxxkSQ80hz8eLFse2S3y577eWt8vrEE08AsO+++wKw\n8847x9LUrVs3bh+NNLWN7Lbbbot9pm2mN998MwAPP/wwALvsskt6/wmTsk2bvCXsa9asCQSRpql6\ntN36xhvLW3I8cPzxxwMwY8aMMj9//PHHY9sWaRpjTAHJeaSpkQcE7RbarjFo0CAg+BZKRbVq3veA\nRpM//xysbf/3v/8dgIkTJwJw4YUXAnDaaadVIOcmVV988UVs+6GHHgKCvreHHXZYTvJkskfvHsN3\neWW58847Y9tXXnklAIMHDwZg2LBhWcpd+izSNMaYCKzSNMaYCHJ+e67D6sIuuOACAAYOHJj28W+/\n/fbY9jPPPAPAp59+CsCECRMAuz3PtiFDhmTluLNmzQJgzZo1pT479NBDgaB7mcmu8APdG264AYD1\n69cDQXObdlSfNGkSAC1btozto81q+gD3zDPPBIIJXPRYEHQVXLhwYYb/F6mxSNMYYyLIeaR50003\nlXqvXbt2WTlXly5dgGA45bvvvpuV85h4OtAgrF+/fpGPc/nll8cdT4fl/e9//yuVVgc9XH311UDZ\nf2cmc3RoJASDU5xzANSoUQOAAQMGAHDQQQeVexxN27ZtWyC469QO8gCLFi0C4JJLLgFg9OjRaec/\nCos0jTEmgpxFmitXrgRg7dq1sfe00/rBBx+clXOecMIJQBBpmuzSCFCH0wHsueeeQBBBlPTrr78C\n8P7778fe69atGwDr1q0Dgghm1129FVjDHeR1v9WrVwNBB+vzzjsPCNrVTGa9+uqrsW1tw1TaZTA8\n6Uaq7rjjjlLH10jzvffei3y8TLBI0xhjIshZpDlmzBggiDghmLJNOz6bwqYd2b/66qvYe5deemmZ\nabUDvLZPldUxukmTJgCce+65APTv3x8Iotcwfeqq7Z86SYRFmpn1zTffADB79uxy02h5pSN8DB30\nkisWaRpjTAQ5izSffvppIH7yDR1KZaqG8BNVtd9++5WZVvty3n///UB8u5hOVDxixAgg8dNXpZO7\nmOyaN28eAJ999lmpz4477jig9FI0mfLtt98CwV1E48aNs3KekizSNMaYCHLeT/OAAw6IbR9zzDE5\nzInJtPBEHeX56KOPgGC0ltI+eAD33nsvEEwnF4Uu1GYTg2TH3Llzy/3slltuAbI39aL2kNDRSBZp\nGmNMHrJK0xhjIqj02/PNmzcDQSdmU3XpTPnaGb3kNsA//vEPIGjU15VI0x2AoPO0Vq/u/YlX5Nbe\nJKcDGEqWK0CHDh2ycs6yzlWZLNI0xpgIKj3SfPbZZwH45JNPACgqKqq0c+uUVEonBzDZUXKFwZLb\nEDws0vdTeXiUiO6vHet79OiR1vFMYvogqGS5ZlNZf1eVySJNY4yJIOddjrJNO98CvPTSS3GfDR06\ntLKzY0rQYZPvvPNO3L/hyaN16GXDhg2THq979+4A7LjjjkDFJokwhWGnnXYCUvu7yCSLNI0xJoIq\nG2lqhBmevFSf0Gonep2U2GSWtivq8LZENErQKd10oo3wpMFTpkwBgsltNcLQ1+HlNHTo5l/+8hcA\n2rdvX8H/hcknTzzxRKn3dMXZyh64YJGmMcZEUOmRZnFxMRAsR5BpW7duBYI1zsPD83QKMf1M+/CZ\nzNpjjz2AYFGzVatWxT6bNm0aELRTatujDoHTiWU1igRo0aIFENwpaDulPiHXY0AQYdryFpVDJwle\nsGBB7D1dBO3CCy8E4JFHHkn7POGF1Ro1agTAZZddlvZxK8IiTWOMicAqTWOMiaDS7091nR69hfvu\nu+9in23YsAGI1uFd1z7+17/+BQQPFMpaP0Rni8/Wapcm3sMPPwzEz6eoM6l37twZCFaLLDlDTXgm\ncO1+pO/pMLrmzZvHfQ7BetmmcrRq1QqA4cOHx947//zzAXjuuecAGDhwIFCxBzYXX3wxED/7f69e\nvQCoVatWBXKcPos0jTEmgpw/CVm2bFls+6STTgKizYun0YdGqUpXKuzatWvsvSOOOKLC+TTR6YO3\nyZMnx9773e9+B8CsWbMAOOuss+L20Sgy0RC5vn37AjBs2DCg8js3m9KOPvro2PY555wDwFNPPQXA\njBkzgGiRpj4wnDBhAgC77bZb7LPBgwenl9k0WaRpjDER5CzS1Hao8KqD4bWuo6pWzav/NerQtrLr\nr7++wsc0mRG+c3j33XeB0hO3PPjggwBcdNFFQFCeYfpZeLZ/kx9++9vfxrZ1sMHbb78NBDO4a7eh\ncBu00hn858yZAwTXr3Yzu+aaa2JpW7ZsmdG8R2WRpjHGRCDpTOjZpk0bl2iNkFSEpwLTYY2LFi1K\neX9dS6Z169ZA9ju8isg851ybrJ4kj2SijAuNlXFm6DBavSa1bXPvvfeOex+CdsqSzyb0mUR4OPQ+\n++yTdt7SKWOLNI0xJoKcPz3X/poQ9Lk0xhQ+bcvWyTaWL18OBM8x+vfvH0sbbrOEYPJofeKeT0Oe\nLdI0xpgI8qf6NsZUSfXr1wegbdu2QOnJwAuNRZrGGBOBVZrGGBOBVZrGGBOBVZrGGBOBVZrGGBOB\nVZrGGBNBWsMoRWQ9sCppwqqlmXNu11xnorJYGVd9VsbRpFVpGmPM9sZuz40xJgKrNI0xJgKrNI0x\nJoKElaaINBSRBf7POhFZG3pdM1uZEpFTRGS5iHwiItemkH5IKG+LROTUZPskOd5bItIqSZqBIrLQ\nP+ebIlKQ04nnsIwbiMgEEflQRJaJSNsk6fuJyHo/X8tE5MI0zz9GRLqlmPZIEdmaavp8Y9dxwjTF\nIjLNv5bfEJE9EqUHvIWsUvkBbgauKeN9AaqlepwUzlMDWAk0A3YAFgH7J9lnCHCVv30QsB7/IVco\nTfUIeXgLaJUkTb3Qdnfg5Uz9DnL1U1ll7B9zLHCBv10TqJ8kfT/gHn97d2ADUJRGGY8BuqWQrjrw\nBjA5lfT5/mPXcak0E4E+/nZn4NFkx63Q7bmI7CsiS0VkLLAE2EtEvg193ltEHvK3d/MjirkiMkdE\n2ic5fHtgmXNulXNuC/AccEaqeXPOLcb7A9jFjyZGicgc4HYRqSsij/n5mC8iXf087igi4/wI5nkg\n6YLKzrnvQy/rAFWqG0I2y1hEGgDtnHOPATjnfnbOfZdq3pxz64DPgKZ+dPKEiLwNPCYi1UVkhJ+P\nhSLSzz9nNRH5lx/ZTgWKUjzdVcAzeJV0lWLXMQAtgWn+9ut4AVBC6bRpHgDc7ZxrCaxNkG4kMMx5\nU8v3ArQQ2onI/WWkbwJ8Hnq9xn8vJSJyFPCTc+6//luNgfbOuUHAYGCyc64tcAJwl4jUAgYCG51z\nLfC+7VqHjvdoeSG+iPxRRFYAQ/EurqomW2X8W2C9X9nNF5HRIrJjqpkSkX3xIpiVoXx2dM79AbgE\n+Nov4yOAASLSFOgJ7I13kfQFjgodb6iInFLGeZoCpwIPppq3ArS9X8cfEFSUPYB6IlI/Ud7SmU9z\nhXMulYVFOgHNJVjHehcRqe2cmw3MTuP8JV0rIhcAPwBnh94f55zb5m93Bk4WEV2ishbQFDgOGAbg\nnJsvIkt0Z+dc3/JO6JwbCYwUkfOAG4CLMvR/yRfZKuPqQBvgCmAe8A/gWuCWJOfpIyLHA1uAfs65\nb/1zvuic+8lP0xloISK9/df1gf3wyvhp/29hjYhM14M6524s53z3AIOcc9skwTrsBW57v47/BNwn\nIhcBM4B1wNZEGUyn0twc2t6GF0qrcFgsQFvn3M8pHnctsFfo9Z4k/gZUw51z9yTJp+C1S60IJ8jA\nBfEUcC9Vr9LMVhmvAVbrxerfSqUSqY91zpWVrmQZ93fOvR5OICJnppi3sDbAOP/vowjoLCJbnXOF\nPYtuvO36OnbOrQXO9PevB/Rwzm1KtE9Guhz53wAbRWQ/EammmfC9BgzQF+Xd6oa8C7QUkWYisgPe\nrcAkf99h2n5RQVPwohvNi4bvM4Fz/PcOBQ5MdiAR2S/0siuwPI185b1MlrFzbg3wlX+bDdARWOrv\ne6WIpLOk6BSgv4hU94/XXERq45Xx2X7bZhOgQ7IDOeeaOueKnXPFwAvAJVWswoyznV7HRRLUtjfg\nNzskksl+mtfh/WfewYsk1ADgaL9RfilwsZ/ZMttCnHO/AH8EpuJdSGOcc1ohHYIXPlfULUAd8boz\nLMF7kghwH9BQRJYBNwHzdYcEbSFXicgSEVmA15ZS7m18FZKRMvZdATwrIgvx/rjv8N9vAXyTRh4f\nAD4GFojIYmAU3h3VeGA13t/Uo8As3aG8Ns3t1PZ2HXcElovIR0ADgr/DchXM2HP/2+BV51yXXOfF\nZI+IvAKc4Zz7Ndd5MZlXFa7jgqk0jTEmH9gwSmOMicAqTWOMicAqTWOMiSCdfpoUFRW54uLiDGWl\nMMybN2+D245m9bYyrvqsjKNJq9IsLi5m7txUBhNUHSKyXS0LYGVc9VkZR2O358YYE4FVmsYYE4FV\nmsYYE4FVmsYYE4FVmsYYE0FaT8+NMSZV8+d782fcdNNNAPz73/+Ofbbjjt4c1DNnzgTgsMMOq+Tc\npc4iTWOMicAiTZNxmzZ5c7h+/rm32sGoUaNKpbnwQm8xyVatkk3LaKqK//u//wNg6tSpQPykwXXr\n1gVgxIgRAIwZM6aSc5c6izSNMSYCizRNxmiEOXz4cABuu+22ctPef783b+3ZZ3vLwNx7770ANGjQ\nIJtZNDkwbZq32OP7778f9/611wZLoeudx3//+1/ynUWaxhgTQV5HmtOnTwdgwoQJAIwfPx6AL7/8\nMpamdWtveZBevXoBcP3112Ny4/bbbwfgjjuSrhjAr796E7OPHTsWgNdf99ZBe+yxxwDo3LlzFnJo\nKtM333irlpx11lkAfPutt6R6167e8kBDhgyJpa1ePa+rojgWaRpjTAR5Vb2vW+ettXTmmd4ieHPm\nzAFAl+TYay9vRdDmzZvH9tEntDfe6C1d3axZMwB+//vfV0KOTdjee+8d91qfjg4cODD23oEHegsE\n/vyztxLs4MGDgaDszzjjDACuu+662D6DBg0Cgr58pjDMmuWtXacRptK7wUKKLsMs0jTGmAhyXtVv\n2LAhtn3KKd4qqgsWLACCqPGBBx4AoF27dgDUr18/to9GmqeffjoA48aNA4KnsvoagvbP/fbzliyv\nyOLypnwTJ06Me63tzPpkvCyHHnooAN27dweCdrBbb701lmbFihUAPPLIIwDUqFEjQzk22TRjxgwg\nuFPs1q0bAO3bt89ZnjLBIk1jjInAKk1jjIkg57fn2hEagtvyJk2aALB8+XIAatasWe7++nBIuyPt\nsMMOQDDeVW5wAAAMj0lEQVQZQFkPhDZv3gxA7dq108q7iffqq68CQbOHPpxL5NhjjwXgxRdfBIKh\ndm+++WYsjXZL0ts87ZZUqA8Sqrqvv/4aKP33cPnll+csT5lkkaYxxkSQs6/qZ555BggG6AM0bNgQ\ngGXLlgGJI8yS9tlnHwCWLl0KwLnnnlsqjTZE16pVqwI5Nsl06tQJCDqq6yQMqTjqqKMAGDZsGBA8\nFATYuHEjAE899RQQPPTTB00mvzzxxBNAcC3Wq1cPCK7vQmeRpjHGRJCzSHPhwoUAbN26NfaednyO\nEqGUtOeee5b72U477QRYV6NsadGiBRBEmmV56KGHgCBqvPTSS8tMd84558S2//nPf8Z99tFHH6WV\nT5NdGmEqHfSQzxMLR2GRpjHGRJCzSFM7LIfpcLl0TJkyBYCffvqp1Gc6cYDJjjZt2sS91ruJcFno\nkEodRqmTskTx8MMPA3DAAQcAcOKJJ8Y+Cw98MLmhT81VVXlqrizSNMaYCCo90vzf//4HlB5yB0H/\nzIrQyOWGG24AYMuWLUDQjglw8MEHV/j4JjntnaBPT0844QQAvvrqq1ga7bmg5VURq1atAoKn5+GJ\nPB588EEgmPjDJvnIHe1XO2nSJAA++eQTIGjzDC+spmn1eYMOodYJXc4777xY2t/85jfZzHZSFmka\nY0wEOWvT1Elo0/XLL78AwZT6JdtKdRp9CL69THZof7w//OEPce+He0Poglk6kYoub/DKK69U+Lx6\n9wLQp08fILir0NFEBx10UIWPbypGo0Zt4yzZ1hnuxaI9ZzQKXb16NQD9+vUD4if2CS+TkQsWaRpj\nTARWaRpjTASVfnuukywUFxcD8Nlnn8U++89//gMEcyyWJ7xG0JNPPgmUvzbQBRdcUMGcmmw47bTT\n4v7VwQ0//PBDXLrwwyO9jWvUqFFcmr/+9a9AMM8mBJOxLFq0CIA///nPANx5552ArbOeC/ow9sgj\njwSChzpFRUWxNMcddxwAM2fOBGD06NFAsD5Y+PrWuiNXXQgt0jTGmAgqPdLUSTj0G6Vly5axz7Rz\nu0acPXr0AILGYY1GdF8IIhLt1KzrkehDH506zuQHbdDXoZA6UcfOO+8cl67k67LojPA6Sz8EHak1\n0pw6dSoA1ap58UHJhxEm8/TuTqN7LR9dgSERHaigs7svXrwYiB86q13OcsUiTWOMiSBnXY50Yg3t\nggIwdOhQIJjwQf/V6FQH/h9//PGxfXRiB20j0/Yv7VjdoEGDrOTfpO6ll16KbV955ZVA0C6tUwRq\nZ/SK0GgV4K233gKCySG0C5qujDh58mQAunTpUuHzmcRKTgGnq8pGoe2gxxxzDJBfk7RYpGmMMRHk\nfL0AnVAW4OSTTwZg3rx5cWk00ixrain9BtJhk6pnz54ZzaepuPCTcY0wtbx0FUqNEPUJa0VphKJT\nz2kU+v333wNBO5tFmtmjQ1d1aKQOZNEy1yVpEpk/fz4QDMHUY+UDizSNMSaCnEeaYbqedZR1kdes\nWVPm+4W+tnJVEp5Q+IsvvgCCnhIaQYQno84EnZZu27Ztce8fcsghGT2PKa1///4AvPfee0AwgcsV\nV1wBBL0eylrYUIdPDhgwAAh6W4SHXO66667ZyHbKLNI0xpgIrNI0xpgI8ur2vCJ0vXNTGC655BIg\n6GT+xhtvAMHQOu1OFh42t//++yc8pt7uQbAGkc7dmE8PELY3utLsa6+9BgQz7qvww1od/qq38PrA\ncI899gCgb9++sbTnn39+lnKcGos0jTEmAknnm7hNmzZu7ty5GcxOarSxGILJPb777jsAOnToAATD\n53SCkEwRkXnOuTbJU1YN2SrjTZs2AcGDmZJdkcKzc+sQyPLonKqJtG3bFgjm7Uy0BreVcWa9//77\nQDCAQR8GhpWcub1Tp04A/O1vfwMyv5JlOmVskaYxxkRQkG2a2l4FQYSp9Nss0xGmySydzX3lypUA\nPP7440AwrFIn3ICyI5Nkjj76aABOOukkAC6++GIgcYRpskOjRB1Oe9NNNwHxawRpW7YOcNHhtjqw\nJZ9YpGmMMREUZDi2fv36Uu/p0C19+mYKiz4R1X/XrVsX+0yHYepKkxqVaDtc+On64YcfDkDTpk2B\n1IbsmcqhE0CHJ3ApRBZpGmNMBAUZaT7//POl3tPVB3O9JrLJjN13373U9rBhw+LSnHLKKZWaJ2PA\nIk1jjImkICNNXTMbgn5drVu3zlV2jDHbEYs0jTEmAqs0jTEmgoK8PbdJGIwxuWKRpjHGRGCVpjHG\nRGCVpjHGRJDW1HAish5YlbnsFIRmzrncLlJSiayMqz4r42jSqjSNMWZ7Y7fnxhgTgVWaxhgTQcJK\nU0QaisgC/2ediKwNvc7a7KAicrWILPF/ks71JiL9RGS9n69lInJhmucfIyLdkqS5PvS7WCIiv4pI\n/XTOmwu5KGMRqSMic/xzLBWRwSnsMySUt0UicmqaeXhLRFolSVMsItNEZKGIvCEie6RzzlzJ4XXc\nQEQmiMiH/nXZNkn6XFzHDURkkl/Gs0WkZdIDO+dS+gFuBq4p430BqqV6nBTO0wr4AKgN1ADeAPZO\nsk8/4B5/e3dgA1BUIk31CHkYA3SLkP5M4D+Z+h3k6qcSy7gaUMffrgHMBdok2WcIcJW/fRCwHr9N\nvoJl/BbQKkmaiUAff7sz8Giuy6hQytg/5ljgAn+7JlA/SfpKv46Bu4Eb/e0DganJjluh23MR2deP\nEMYCS4C9ROTb0Oe9ReQhf3s3/9tmrh9dtE9y+BbAu865H51zvwAz8SqllDjn1gGfAU396OQJEXkb\neExEqovICD8fC0Wkn5/HaiLyL/8bcSpQFOHXAfB74OmI++S1bJaxc26bc26z/7ImXsWZ8hNJ59xi\nvIt8Fz+aGCUic4DbRaSuiDzm52O+iHT187ijiIzzI5jngVopnKolMM3ffh3onmoeC0E2y1hEGgDt\nnHOPATjnfnbOfZdon7BKvI5jZeycWwLsLyIJ10RJp03zAOBu51xLYG2CdCOBYc5b+a0XoIXQTkTu\nLyP9IqCDHzbXAU4G9ko1UyKyL9AMWBnKZ0fn3B+AS4CvnXNtgSOAASLSFOgJ7I33C+wLHBU63lAR\nKXfiRhGpC3QCJqSaxwKSrTJGRGqKyALgK+Bl59y8VDMlIkcBPznn/uu/1Rho75wbBAwGJvtlfAJw\nl4jUAgYCG51zLfCi1tah4z1azq36BwQVZQ+gnhRgE0wS2Srj3wLr/cpuvoiMFpEdU81UJV7HsTIW\nkSOBPf2fcqUz9nyFcy6VdT87Ac3Fn8INLzqo7ZybDcwumdg5t1hERgCvAZuA+cDWFM7TR0SOB7YA\n/Zxz3/rnfNE595OfpjPQQkR6+6/rA/sBxwFPO+e2AWtEZHooPzcmOe8ZwIwo36IFJCtlDF7kAbQS\nkV2AiSLSwjm3LMl5rhWRC4AfgLND74/zyw68Mj5ZRK73X9cCmuKV8TD/3PNFZEkoL33LOd+fgPtE\n5CJgBrCO1P4WC0m2yrg60Aa4ApgH/AO4FrglyXkq+zoeCoz0v8A/8H8SlnE6lebm0PY2vNslFb71\nEaCtf5GkxDk3GhgNICLDgE8S7wHAWOfcVUnyKUB/59zr4QQikvLtfxl6A0+msX8+y1oZK+fcRhGZ\nCZwEJKs0hzvn7kmST8Frx1oRThC62KPkbS1+05CI1AN6OOc2RT5QfstWGa8BVmuF7DeJlHV9llSp\n17Ef7Jzv718Nr0ng00T7ZKTLkV+zbxSR/fwThzP/GjBAX5RzGxRHRBr5/xYDpwPP+K+vFJHL0sjq\nFKC/iFT3j9dcRGrjtZue7beJNAE6pHIwP0o6CijslaJSkMkyFpFGepvr37J1Aj70Xw/TdsgKmoIX\n3ei59DZ8JnCO/96heI3+CYlIkQS17Q34t6RVVSbL2Dm3BvjKv80G6Ags9ffNm+tYRHYWkRr+y0uB\n10Lt7WXKZD/N6/D+M+/gfcuoAcDRfoPtUuBiP7PltncBL/hpXwAuc85977/fAvgmjTw+AHwMLBCR\nxcAovGh7PLAar1AfBWbpDknaNHsArzrnfkwjT4UkU2W8BzBDRD4A5gCvOOcm+58dgncbXFG3AHXE\n65a0BO9pMcB9QEMRWQbchNfsg5/P8to0OwLLReQjoAFwRxr5KhSZvI6vAJ4VkYV4X1L6+8un6/hg\nYKmILMcr76uTnbyghlGKyCvAGc65X3OdF5N5flT3qnOuS67zYrKn0K/jgqo0jTEm12wYpTHGRGCV\npjHGRGCVpjHGRGCVpjHGRGCVpjHGRGCVpjHGRGCVpjHGRPD/2VR0AzzFcB8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763336390>"
+       "<matplotlib.figure.Figure at 0x7f024ecaa3c8>"
       ]
      },
      "metadata": {},
@@ -1086,15 +1043,13 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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u2daehCMp8ZRPzxlg10PkXDR3liG0BaTp1P7f+MCSALIUGZYI422M724K7u9d\nSX8p1ru/1/6fwZgKY9bYDXjRWd22k4CuAU6SxgCHGfHsHO+bp3B53VJZw9DW/j/9FHEIfpUQe4Ik\n8VksWgOsdU1d68bIujqjM8Btz2lrhBWWES1wY0edgn5sWMMvx9vdk+4saMc0ns3ayYNXVxXLZYYx\nC2y069LNAou5h007q2aNgPvAfYLgiIODPg8fDnjyJOHJk4BPPvE4Pm6xcIQaN9vbGd9up4JzBpZL\ns6ll1rXYGAFXHnP3wSXFPja8f41u73YWOGbxxUVbE+4enrNNvGyJcW4GRHcymduK3RjRwaAdK+uw\ncNdQSA+UoBaKwPiEWqBcb9lmpoPcFHxdZdFFwo585z7j+9DtX52C/j7g3gZU9/+g/WC+b9NGx8dw\nPK45Op9xdP6Sw+l/o3r5F6q//pXqr3/BlCWeMbb5YDDYjMUSBwdwYCOe+uhLlif/nsuT/8DTxUP+\n+S+Cf/5nO+TKzncXHB7aawkC6MUCr6/oDXxIIutiuWHTNzd2TKWLgJ3L5HoYplP73tMJZCmyXyKN\nQKK2PKdu7evvVX4N1j+k3Na4uejXrTl2I3biarMZnpeTJJrx2DAM1sSzc1T2FxAvNru86PUsPr6P\nDBL8ShD7wWYsJTgD3I2AncF1eamuQbZG2BrgNgJ28rFhDb8O7y6h0o31hbah4PzcRkVpWpGm644B\nLmgjXmd8g846Bp4Aj/H9Iw4PPR4/9vnqK8Xnn9tWxZOT7TNiuxFw91onE/va7UN3U9dss4PYREbQ\nRmFd0s7Hgvevwbrb1bBet1N85/Pt32nO1iBJLC5u+A60hGXXp+3Ib10nyPPeHgG7Ht2qEuApaqmo\nCKD2UbUgqDrj7LpHNtEaYJcVc5//fer2O21D2vWgYDs15byiONSM/RUH9YrRdE508Q36+V9ZPv8L\n1elrqtmUSmsC3ycKQ1QY2ki1mdBRHNxnPX7AevSA6+gznqcPePEq5ttbwcWFnaZkPR2B50myTG4m\nI93cQIxPL0zoA76o8WSJp5QldIX2ZJaqqijznLIskXWNLwS+lMiiQDhmdLREFgkKhed5G9A+pjTV\nrnwf1m9TVNfF5VqrbcpJU5Yl1sDu9nq6fs8I6ANjwnDI0VHE48eSz3qaw1VKkE5hfdOSLvp9S4XN\nc2w6sfXO3UjKqyuYzyuyLMMSflzNubsL2euQUiGEh+97+L4kCMQmneY2j7uANfw0vLubcl23J1Yt\nFobFwuqTLGKYAAAgAElEQVRjmhryvGqcIBfx9mjvv2WhCxGhVGJn+4Zjer0jkiTh5MTjyy8VX3wh\n+OQTwXhsN+Tue2fZdvq7W8vrziZvyVai4Vy2qWe3b99FvH+JbruDUCYT05Aqc4zJWS5rwtCuohDk\nuSDPJUJY/VLK8i2qyqMsPUDheYLRSHB0CF88MXz1leHJJxXHvYwjkzFeloheguzHiDhqAlyDkoYg\nkqjQpjxMGGGiBBMm5CJiVfjM5mKTLneGfPfgjveB9XthQe+mnZ1HOhw2bOe4pp8u6KcX9GZn1Odf\no59/zfwvf6Gaz9HzObquSeIYbzAgHA4Rh4eIoyM4OqIYfcJs+Dm3o8851Q94Ojng2STiu0vD5aVt\nNdHaUFWqAb89JefmVpCEPoMBDPGIRUkkMjyp2oNnk4Qqy8jKklRrPK2JpUTVNdKxOBYLRLRA5hJF\ntFVucKB9jEoKb8d6V0HdxtidzTyfG7Ksbgxwho04nQFWnRUDA+CAKLIG+MkTxeOg4uDVmuBmZj0p\nl8NyjI2isN6xtieZOaZma4BL8jzDGGeAnQMAzvgKoZoNwsPzFEFgDfCuot4VrOHH8d6kBJvZNc4A\nz+c0xrdivdZUlaaqDC27GZzhdVGvlAm+PyQIBoxGfU5OepycJDx86PHkieTxY8HDh2wM8O7M8e6g\njW4asTtO2AYHYpPOBLYM8Ns25ruC98/RbWeA5/OuAZ6h9RzPK/E8jedVaC2pKkVVWcdWCB8hfIyJ\nqOuIuo4JQxiPJeOx5NEjwRefG/7hq5ovHhYk+YykmBAtM0R0BP4RYhAhhUHaAyhRocCLfIhCTORG\nW/YoZMCq8JjNBavV9jnfDt/3ifU7N8BdSrdTADeP9ejITrU66tdEp3OixRnB7bcszr5m8d1fWf7l\nL+i6tssYRBAQDQaIkxNrfJtu+2L0GbPBV5z3/8Dz+SFPV5K/vpC8em2YTGpWqwqt6+YhkeS5YrWy\nEfD1DfT7PqMjjzERiDWeXGJ2I+DVinWastAav6pQUhK5wR3NUyfiBaIIUegtz+ljSFP9kLwN691/\nu5rObgSstW6mHLkI2G3ILg3pyDgDYEwUDTk+juzmKzSHN2vCrDHAjknjdoGigE4E3Hrntga5WLgI\neIGNfp0DAG7KUtcA2wh4+7D5XS/5Y8cafhxvaNPOsE24WSysPqZpgTEVFm+BNcAO6wDX9y3lAN8/\nIIoOGI0iHj0SfP654PFjwaNH8OiR3UccLi6t6LpQuqdsOazcEYPOaHSZ2+6zdCciuW3gLuL9c3W7\nGwFrnaH1lLq+BAqEKLB6pjDGOVohFusQmwGpAcVoJDk+pjHAhi8+r/mHrzRf3i8Q5zPE2bk9HekA\njN+DAYjmYkVdIyIBkY30TBRTRwlV1CMXilUumM7aCW3ubIjumQPvC+tfZYC/72J2RxA6z9Lz2kL6\nqFcxMgsGkwXx7YT6xTekL75h+fxbVi+es7y9YVWWBIAvBLGUxAcHeF9+Cb//A1n/iNQbknpDrnjA\naXrC67zHq1ufs0vD9Y1hOtWbObLGGLRWlKXZmkO8WAhubiGMBEIa7gcRIhiQHGiIEwQC1mv0ek1W\nlizrGt8YZF0jpSSqKrwsw1utYLVElgMk+qNLTf1UrB3eXfJKNy1oD1uoKUtDVVXUte3DbVnPzgBL\nulOPpAwQIib0fQZhzXGy5kAvifQCs5qTz+eY9Zq66S/x8hyVZZgsp1qX5KlNe7oDHhYLzXpdNM9G\n1/A64+8MMEgpUMquLinjY2TCOvk1eDuHxxi7Kd8202Fvb60BzrIS23Pt8FZ073m7KccI0UPKCKV8\ngsAjjjunoHXIOEK0xnR7vGnbctQtf83n7dAQz2tLCrAd6XQ/48eK97vQ7bKssANuNMZ0dctvljW6\nnhcShiFBEBHHMUkSkSQex2PNp0drPj0u+XyQ8Wm+ZnS6JpgvNr1KJs+hF2EOxlAcIHQFujkdqSo3\ns4zXIma5CliuJReXkttJO104iuyrI3TB+8X6V0fAb7uwrtHtThhxQzYODuAgLhktb0gmr/GnL1g9\n+4bl029YPX9KfnPDejYjA8ZC0JOSsRCER0eEX32F+E//ibU84moecjmPuEiHnC3HnGc+r68NFxc1\nNzc187kd7K+1VXStPaA1wC41dnNjry/Pgfsh8YMRR0cBIrGd/GKxoEpT8qJgaQz2WGeQdY3WmijL\nrDfWXyGKHGk+PgMMP4717tewnZ5qo5K6Mb4lxjiveNcAu/SzhxAeUgZIGRD5kkFQchCUjIo5XjWn\nXs3JFwt0VVE1u3BUFIR5jlmvqdIeeaqbKVia5bJkuSwpy6IZ8l/TRmLd2vObG3AX17f938ckvxTv\n7qjHNN2MZmcyMSwWmqJwGY+34a2wBjjBGuAYKX2Uktsn8HROrHM1XWf4l8t2ilL36MtuLa97hKVL\nOTqCnvucXew/drzfjW53Mxy2rsumpz8BegRByGAQMhwGHB0F3Lvnc+9ewP1BzqNowcNwwoNgysly\nSu/bKdSztokYYDRC3LtvG/2LAsqGVu2K98Mh62XM9czncik4PbWOYJq25bAsa6e0dT/3+8D6b5KC\n3r24LlDdB9j1ch0cwHFY0ptck1x8i/fsT5TffsPsm6+5efaMUmvKqqIC+kIQCMFIKbyjI8RXv0f8\n9/8D6fqAq+eSZ98JTheKi5ni8kZxfgEXFzW3t5rFQmOM9cTAUNd2frCU7XF4i4W91iyzSplEEUcP\nA/TRAJX0wIBYLtGrFVlVsTTG+uvGsrFNVSHznGC1QqxWCFMgTf3RKaiTH8K663S5r7sEjW0vuUJr\nZ3i7ETA4w+uUVggbAXteSOQpBv6aw2DFSC+oqjllOqNaLimMoWxCMFGWeFmGSddUaUmW6qb/ULNa\nlU37i0s7a9qNwg7gALH1Ge+a8XXyS/CuqrbE4Ayhm5e/XmvyvFvz7xpgFx25DToBQoQIkFJspQvd\nec8u+q3rdqiGqzdPJu2xpo7p6q7VpacdwcoZ4W50142E7wLef3vd7maWnHMlsYTKATBsDHDAyUnA\nZ59JvvxS8MUXgk/7KferOffLc0arM7ybC7ybC5hP2rpCGNoa5nxuDbDrgcrztq81SUhXAdfzgOev\n2DLArqM0z9s6sPvc7wvrd5KCdkSG7oMrBCShpidzemVOUt6grl9RvXxK+e3XLF+/Zn5zwzRNt9Vx\nMMAfj/HGY1bHXzKtHjJ9OeZ0NeTVK3h5BpeXhutruL423NxUzOcZWZZ1HoKquS4D2IcjTX2mUxtd\nLRbufGhBkgiiRBL2YHztM0g9Bki0lJRCkLnPTvNoaY2fZcQuBe3nSE9v6gW76+9VfgrW3f9zytnt\nDXQtH1mmm8jTGd23pX/dU2CNsDF2LKSpDbLWeHWJqgvKurQMda03XcNSCGo/oE766GTEYhJzOfF5\n9cpwfV02px454pUbcUjnfdth/0L4KKXwffFWUsauUf4YsIZfh7fLLtkT6AzzuWa1suSrsszQ2g1W\ncbO+M+w9dwzodrM2xs4Kz/OaNPVYLhWzmeL2Vm4IXmG4fciCG+Xujvl2q0uscfVLF1U3XMtNilXr\n7Rrgx4z331a3Xf1f2LnMXh+lbPeJW1GUkCQJcRxzOJQcjypORiUPD3I+DVI+WafcKycclJeMywuS\nRdM4fnHRnh8KiH6/meTRAN5cmJGKXHtkqU9WhLy+8Hj+UvLtMxsBz+ctwc5lbFzr0w9lu94F1u98\ngJqUrXfZCyt69YJkNSNcv6Y6/Y7su6dkT58ym82YpykLrN/rY0vy4eEh3hdfIL74gtvhH/j69h5/\n/b89LpfWk7m9bdNbNsVVkqYpVeWmKXXTiwV2wH5ImiYIkZBlajO71I0oBPtwPX4u+XThkfgRte9T\nGUOuNdoY6uavCa2J85zhcmkj4CRDKr3lOf09K+fPFUfacJ6xS/e7XsvFwuwYYNds6fo+3zTCzvgC\n6MpQVxpTVRit0XW96dbdVI+lQiQ96rFtUZu+TDi9Cvj2W9NMX0qx84bXzfu7wa7uvd1JOxFShg0B\n6/sN8K6C3iX5KXivVhXrdUGe2xOntHYHbXRffdpsRN28lmgdkucRdV0yn4fc3gZcXoaA5Pq6HbDR\nnZzkoppuX+ps1hwS0ETPDrtuVN2doFVVb2fB3mW8fxxrZ4Ct7vp+TBz7xHGPOBbEsSSKBCcnPvfu\nhdy7F3AY5Rx4KQfeinF1wzg/Z/T8gkE5ITYrvHoJaUOyvL62lt5Nb3JjtVw/qfOk4ohVHnG7Cpjk\nPk9fSL59Jvn6r3Bxaa/XYQltK1o32n9fWL8XA+xOOOr7Fb16SbK8JJy8pDx9zvq7p8yfPmVeVcyq\nijlWFRXWEEcHB6jf/Q7+6Z+4mXzJX05P+L/+1eNm2ebvbbrLNG0tFXW9QusZVrG7m7r9WmufNK3J\nc4/ZLNq0lbg5zm5ovz6XJAufR15IHQSUWuPOy3FJNFXXjPIc3RzTIbwcGdUf5WD2H5NdxqRT0u65\nv/ZIwN0IGLZTVNsRsDFu+pSNhuqq8XQbA1was4ljJaCkhDjBjA8pDu4xrSWvbxRPn8JyWbBarbAG\n2G34XRKQpDXAMUK0Brh7ok93Ks7HEgn9XPkpeM/nNG1HOUWRYkyKnXzmDK9bPrvGF3K0DjGmpCwr\nZjPN7a2g3/c3Bz907/nuvdfaGt7ra+uoDwbtaVZuOlM3AnbjcN10pj3erfw03Ras14KqEtgZ3TG9\nnmQ4VAyH9v4Ph4LPPxd8+aVNNx+qjGG+YlDcEJ0/x3v2Nd7zr1GLKUoapDBQZC2RIM/b0zKiqO0n\nvb21vWiNl5WmIdfzgFc3Hs9eCL59Kvj6m3b6lhBtzdcx4l2K/X1i/c4MsLtYT2oSr2IUVIzNhGj6\nCjF7SnH2V7KXz1lfX7FarTaxqgT8ICAJAkZBgBg/YNX/jCL5Ha+u7/N80ufZc8N0VTW9vTVZZtsa\n0rRoIt/rZqW0xX/ZWUHjLdtNvywlRSHJc8l8rpjPJYuFJE1tTd8YgwF0s9G7eT0aKOqaStuITJQl\nQmukqO+MYsKbKSqXnmrJboY0pVnu6EE3darb+9tNAbu0sGm+X2OMxugaUxYb78uUJbqubfOClPhC\nIKVPUYakq4jbacDltOL6NmMyKSiKJWXpIi/Yrvs6J8AdfRg2tWePMBSbOpEj/zjl7BJT7gLuPw/v\nmjyvKMucuu6ecNV1ZZ0T5jCvaDkAmrq2z0SWhUynNWFoWK0MxtRWN02NEAYhaqQ02MM6BMYIplPJ\ndCqZzSRKtTOh3dCN3c3VRcXAHm9+GGuXaXCpfHtvBb6vKEu4d09x/77HvXuKYU8zSDTDRPPpw4on\nhyVPkpJhdUuiL4jXl3jpK8guoZhCsWjf2HlE7Qku7cPWkA3MfE4dJtQDgRYRizzkdu5xcSm5vIKr\naxskZ5nZfBal7IdzRrfbpva+sH6nEbCU4EvNQKYcq5RRdoa6+Ibi6b+Qf/dnlqenrOZzMlz3F8RC\n0E8SRqMRB+Mx8+GnXItHzOcPeTodcTqJuJnULNKCutbUtaYs1xTFAjvUfYo9zs4daecMsKsqu7Nl\nwW6+ZjOBxRiPug4QIsDzApQwiFpDWWGqirpJd1ad33Y+O3Vt+9BoRmU2YLk6yscuLp3TJWW4+lDX\n+K7XhqrSDTO9S4LqTsDqGmBNexxdBbqE3CqeyVNMUWCa4o2nFKFSGBkwXypuTwWvlOHsbM10uiLP\nl1TVDK1X2I2/y7z12SYBuT7UAN9XGwPcbdp3HrSLDj72zbgrPw9vR8rZNb7O+XJOlmOkd2dAC5y+\n2tOsrGENQwPohmlrlxAVQmiEUAhhcU1TjzT1yTKf4dAaCEfe2iUTuaEcUrYDGvZ4vx1rZ/9ce1e/\n78aOyiaaFHz+ueSLLwRffAE9VZHIjERlHPhLDs2S0dWSaHmNP71ATi5hPrUPjpsb2h1V5uoEzjK6\nNGXnfNGqX1IUkkJHzDOPyVxxc2Mz1IuFaZx/C5oQYsPTcSS8bn//+8L6nRjgrkfpC01frTlSU4bV\nOdnlt2R/+v9Y//nfWGUZqyzbVOI8WgM8PD5m/OABs9EnXPMJ380f8nQacjqFm0lNuu4OyZ9R1zfU\n9TX2KLtbYEKTJKbdYANcarHd7KGuA4zxqesArRNAWgMsa6SxPWXOALso2MVrmiZCdk3gnc9/F4zv\nbmpmdxDC9mYMWeYOQGjnLLsI14ozwE52TiuqC5uSSldQ2Mntpq4RjQEOggAtA1Yrj7MzybOq5uws\nYzabkmUTjFljjDvmTtA6aG3dtzXAIVL6eJ4gDMXWUPm3KeldkF+Od0FLuOqy3h3uzgA7rF22ysO5\nvM4ApylI6QywK2UUCOH+piVXGuOjddSULzzKUmyMq2tfcp/BtdO4aM4NwbvLeP8Y1o5J7oYrWYdG\nYoxASsk//IPgH//RrqgsCcuUsFwSzG8IFtcEl9fI2yvk9SXi6tKmG90fU6r16Fwd06UvHGvK5b+X\nS8xiSTUqyQtBWscsMsG0mfFguUHWAJelQUq5eQ6cAf4xZ+tdyTszwC6NE4mcOL2mt35JdPlXstfP\nyE9fsby8JMWqo1O3GFBCEPdGqJNPqT//PTM+53V2wp9f93h+IbmcVKTrijx3EVSOneU7wxrdW2wU\nPG2+55i0boN1R5656Ss24jEmpq4VYVBxMCh5eFxwsCgJ/RJdWaatrusNncslLpWUCM9DRBFEIcL3\nEEpu2JRwN5TVSXcUYHfZ5nx79m8b1TrD2+3Bdb2CXRFNylAgdYVYLeHmGgo7/UpUFQiB9Dy8MET7\nEau1z8Wl5MW65upqzXI5Resr2iMHXdXYdXV3nbQAKX2E8FBKvTELuDsV565EQd8nPw1vF6V2ce9i\n3GWhd58Dt1ymSpPnBXnueAL2gA6r025VtJkMjavpuyiuezBDl0jkhnW4Ddlhvse7FYd1d7yn1l0D\nJpoasY0uDw7gwQN4/BiCVOOvCvxVikhnkN/A9AJmE0iXrfHt96Hfx3SL8a7YvF7bufvO8EJ7uLfy\nKGqPZe4xW3jcTOHm1s7smE5rVquaonDlDJoMyXb6eXfi1fvA+p0YYOeweB7E2Zrg6hR5/a/Up/9G\n+fIl6+WSFW0iStMesx0JSTQ4onzw77j93X/k9OwhT8/G/Pm85uzSMJ3WzfB0x0Nes93O0E1vVTtX\n1jWd3TYIr3l3n1EPPr1f8Y9frDlJM5KXOZkuyJsIWDaDONywvFApvDhGDId2uHUSIzx1p6JgJ90+\nUMckdWWburY13O20I2xvuK4Q0f0e2EEcthdYVQvkdIZ4fYooTxHTKbIsMVIifB8Rx+gwYVmEXN0o\nTheGyWRNlk2By50rds6Zez97HXb0pNgMaHc1oV025MfSYvZL5W+Ld9foto6Q1cug+Rm3W+TNv7v6\n7lgZdL6usXOGa6QUW2NEXf2yO73U9QV32bB7vK3sYu1w7hKXPK/NIrjlgjFJbSdVuVqF61Orqnaq\nShzbwwFGozaklsr+TrfdyDWXV5W18CcnmINDMtVjlgbNUZftsZezme28MKbCjpYVKGU2Ot4lXb1v\nrN+JAXbn/EYRJNma4Oo18k//inn+L5S3t6yXy83hY+701QAYAiMhqfqHFPf/HemX/5HTecizecCf\n/qKZL6zSWAPsmJLrndU1wF2F7Maukm0DHG9ux6gPn90r+ccvS4LrNSQFuS437UeOI+uS2YFSeFFk\nj0ccDhFhjPDVnVXS7ikz7cHaphlH5zbkTeWcLju9bQei8z2B7cW1y9MaOZvB69dQnSJnM2RRYKRE\nNkqsg4RFEXB5qzit6x0D7LIhboXsRuBCyM3kpW4v6C6md3lDhr813rscDeeSu/8zWN2m+VrT1pRd\nDs397TbStpO06qYXtc1kuuMKZzMbTLl0qvtcb8P1LuP9NqydAXZG1s3Ybp2w9ntK1Mh6xwAvl/YH\n7BAGa3gPD+0aDCDpYeLEDta5ubZZr+vOStPWAI8PyHSP2drnctEaX2eA12trgKU0uBOYdtuNPgTW\n78gAG6Koof2vcvz1hPrsFfmLF+RFQZ7nmw7QGpt2DnyfXhAwTPpMBvdZJZ8wCZ5wXlWcL0ouLkvy\nvEvY6JI6XBrKpRe76U3Yjaiskuab31VKN/NgfUbhmhM/5aFcUzBhYVYs64p1Q8ByScsezSwXpYiS\nBDUaoUdjEDEIe1vvQvTrPmO3TaGrpNsKaUlqVto2o5b1uvmrW+/heYIokkSRoudr/GwBVxfUxQWm\nGeor3BnOh4fo3hHrVchkWXK1mrFczigKV5ZwDGfD9hQscBu4VVCxmRHcTU3ttiXctU35bXi7/lu3\nGXfvlz2vVWCMwhjn/DjGR9cY70a9vWbZCFkIq/dtVF1guxx2CXVuwL8A/E2fr6vhuwi3e3JPlm33\n/sKb7Sh3Ee8f022Xhs5ze69cD/Z6bX92sei06K4EYa4IjI+SIdKPkHGMcEfLjseY8UEzp/gA3RtS\nRgPKaIAua2CIYIQUI3yvjx8meOulPQD68BAzGFCtYvLC32qBm07bsZNvYzt/aN1+JwbY86CXGA7H\nhv66RgUlWZ1TFAXrqqJo2kYcBcaTkmA8Jjg8JDi+TzF+xG024OULuLqqWa10M07SrZK2id8Z3zdP\nsnG1o+1N1r2zI24UxHFNv68Y9EMO1A3RzRniT2eUL16wnEy40Zo5rZ+dAAfAEXDgeQySBO/gAD0e\nY4qEuvDQ5d0wwPDmqSi7I+rcsXT23FfnwrgcgsNH7/zVNooJQ814XHNwYDiRJUmxwsxvKdcTqjSl\n1hriGHN4CJ99Rj18TP4qJF1Om+EAF017mj2JxbW3tM/Ltjgj8jYF3VXSbkP/XZEu3t0TkFzK3jLG\nVRNpGrSOGia00z1ocXeOsnse3BxoOyvYpgwdwUc3M4bLRrccmS6lbSVzEbOHEAlxHGz6UPt9+87d\n6Vhp2h4c0Z38tMfbytt0u3vcY5q2mQQpW+MM8OpVe0zkQRBy4A8Z+5JoDKHwCHsJIgps6a4ByCQ9\nTNIjI2aWhswmknUqYNmDhSHIFGNfMT4KGLBsfzeOEVWALNSGf+ScLNuX7BEEAqUkvi83zvX3HTf4\nvrB+JwbY96CfGI4ODHGqyYOStS5I85y0GZzgqj8Sm8YNRiPCzz4j+OxLiugRN/mA58/h6sqeYGM9\nX0e6ymgb+HcNcDfCcga47ixH6rBMTCFK4thwcKA4Pgo5kGvimzP4079RvHjBcjrltq43KXNHFhsD\nD4Ch5xEkCf54TDYeUy8SdOlt0jMfu+xGQt2WDuclWwMsmmlWXQPcHbywa4AdllVjgA2PHsFJUZFc\nNgZ4OaEqS3RVIYIAc3iIefwYM/6MYhGyejllPp+h9QVau8loLtXZJYBti1O+rrf8Q0b4Y4+EurI7\nkKH7nLupd1FEk7GwB68XhT0VR2t3r7tOscPAMdAjnPFtDbBoejYrtM6pqu4ENVeGcvoeNL/rIURM\nHAccHnqcnNjrgnZyk+ti6Y4g7G68dx3v79Pt7rGiy+X2FDInnmcNsG1Ngk/uh3xyT8L9mOEoQPQS\ngntjiEPrGQ0GmCDEKJ/a88lXittbj7NLxWxmoEwwRUBMxKdJQJhEDOLlhr4s/BhZBKhcbrIc7rCF\nupYoZfuTbRnizfLSh8L63ZCw0ISioC9KQpYU9ZqiykmrakOjcNFvKASx5xGPx4SffIL3u99RLB8w\nW/Y5n9gUQpa5mpJLPXUZj7ss2vYIu3Zz7yp6l6xhD1zv9TyOj30ef+pxVKcks3OYfE159pp0NmOu\n9VatOpGSgVKMlaLf6zXnK44xwxGmiDFS3Qnj66S7IXejom6aSmvRiYC7zHQfu4m6Op/DSOGelDiC\n46OaJ59pHi0KBrM1Jl+Sr1abwoP0PPRohHn4EHP4iOp5SiZSsmyFTT2vsM9MwJuGt5sxkZZtLd+M\ngHcV9S6OI4RtvJ044qWtFdqZ6s7x8rwApWry3N0rx2o3TU3OGmBjurVfu2ytzhpgrSvyXDTPmWsx\n7DrZXYZriOfFJEnAaKQ4OWmv2RGw3PQjd/0/lJp8G+7d+/Gx6vvbdHu799t0WpJMc58Mvg/n5/Y+\n2WmFiqxSlJ7gIFKMvYhxNEBFASJMwE9AerZcUcDtUnB+Ay9f2wFYdW331H4YEMWSg76PPuzZs3+N\nhqrEoyLyKvphSeQLpLAjbIWQGwKew7Z7CtbbjPD70u13M4gjz+F2AnqCefWSejKhKoqNKbSzqKDf\nGLJBGDIYjQjv38c8fow+OyZfJ5v0hhvu/SZTso2StlnPboMPaGvDzug6L7kPHCLlfYbDEZ98EvKH\nP8DD8zX9sxvM+Uuq2yv0amVP2KFNkPWDgHAwQA4G8OgT6uN7mMGYOupRByFG7pKJPl7Z9ZC7G5Ej\nbrzte9uEOIepc46ce2anUvWTiM/uCf7973I+m+Qc3JTUviGl7Sj1lCKOY+rRCA7GTRDk+kK7PcfO\nWfM779G9Bq+JuuQb9aKu8nan5dwl6eLtGLBBYP/dTdm5qDIIoCwVZRlQlgKlFEqFSJng+6ZZYEeO\n+hgTbBbYntK6FhjjZjsLplPRTLGLsHoMLYYhSg1RqkcYRsSxR68n6fffPBvYkW7tVCR77UmyfSB7\nF2/XihYE25tzd4jHxyQ/Rbctx8OgdY3WNcbUSGlfZzPRGGDBYiE5O5N8843kaCA57AUc9cCPPUTk\nIyKJ9MSG+LxYWAN+dtYenmAMDHuSgyTk/r0+mSfwFreo+QSxXNDz1hx7JXII3w0Cjgb2pCV4c6yo\nIwo7nD+Ubr87A3xzC7NXmNf/P3tvHmPblt93fX5r7fGMNd7xve73+tndbWNsMLTtDOA2VjAkkgNI\nmGACAWGTP0BEgByGP2gjICQKRDiOhJSQGKMYMcaOFCEMhnYbIYaAoySS247b3W++705VdeY9L/5Y\nZ529zrl137u3+9a79ar2V9qqqlNn2Gd/91q/+fd7h+bkhDrPtxrOaREGWnOgNftxTDgeE62LxqrV\nIae37KEAACAASURBVPn9HouNAN62UFoB7Md1nRtzE1nGClpXqlB6z/cF8A3G4zGvvBLzuc/DnWzJ\n4O1HNO++Q72YUWUZVdNs8mWHQD+Oiff3UTduYO7cxRweU4/2qNMBJtTXK0jE+Qt1t8OQ27AtxPvp\nW8SubnO7DnTYS3jlpvBd35Zz42GGeauiiZpNACLHhjEGaUqzt2cTOfo5hK7fsy+EnQro7hHtfaaL\nHToBLE8Vvn7SxnWD49YXwOf10bU94IW6DqhrRdMEhGFMENSEYU2aOnc1gKytHLVO2FIYoyhL2Vhb\nZ2f2PloshCyzwtau4zaD2vbu3iOK+iRJQq+n6PcVw6F1N7t7MQjaxkp+1rM7nyh6MmHHF8K+slEU\nT3oErgqeZW1XlZ2LbjsT2o5kVVVzdiasVoqTE+HePU2SBKSp5nBfcXwQceMgJEoUKtSoUBE4BSeE\nVdYO25nP2+u7P1bcOo6ZNZo8FEz2CHl4QvjoHr2DEn0I/VHIrVGfg6FiOIgwPMmba8SxaxV/3Gv7\nYgRwUUB+BsX7mHv3aCYT6qLYmgwZitAPAsZxzH6/b6P1R0cUN29Rv9+n1MnarSGe+9LfqKHdNOF8\nARx6v1snsnV9pWi9j1KH9HtHHI4j7h4a3ri5YJhMSPPH1A/uU5ftObsuXSOlGPR6VgDfuYO5fZv6\n4Ii6N6IKU2oNjTzdJXXVNuynLdDdWOHT3XS7VrCN5YlEiMSIxAzSiFvjmjeO54zrOWe9jFPdxuUL\nwIgi0zFZNCSLx5TBhEa5GtNm52DzOecpdrbuWG1py7uNGfwFel24hic5dQkvLgGrLFsrMU1t9yor\nUO21dXW48Tr01+/bn7txZXc/uUSf5RK0FmYzIQwVttNViuXTNdSx94xSA4KgRxRFWw1UXF2+azfp\nZgr78b42hs1GQXAbtd+e0sWK/ezgqwhf2TpvbRtjaBo3a92VhlqvY1UpFgs/NGiz3w8PNcfHihs3\nbI91V5frstXj2F5Pf8JSez8oHs8iplXEUgxkDfpsSnT/A9IoJN1PGSV9jvuKo3HE4UGPqpGt2L5b\nu07R2m2y83Gu7YsRwHUNeQaLeTsksmm2HH+R1kTDIdq1Szk8tP6f9UrwiW43Safp2oSMbZel21z9\n0gZXktBfZzam64U5YDy+yWh0zOF+whv7M+7k99h/c0rw8OuY+SnLdaJYjE246gUB+3HMfhQxODgg\nvnkTdfcu5sZNqt6Iogk32b7nJWBdxc3YYbccxbd4bWzNWjEijkc/nr+bvW45DsOUOO4TxwNGQU4y\nnaHenGEevE15ekpelpu4fACYUjg7C1i8F/Ioi7n/OGGZuaSeiHbGlqEtYXFtSX3fjLWKbSlSK1h8\nF9ZHxf+uMtcOjlu/p7JfouLm87qpRQ5OqKWpm45jf0IrfF1pS1Fseu0TBNbyTdNg00qyaYSmCbFt\nTa3nQiQEEprGDgSYz23JqFJt7a9zQbtN1+8D7ISvmw/slIRerx1lGIbtGnd5DlfN6eVnAvv3vBOE\n4JRSWV+D3bXtarbdYmjrtO3QG7tHB0GAUvYIw4Ak0cRxQF3LRvHys9TD0N4Pk4nty8EKQnePFYV9\nwXTCUEfcPurx2c/CbNH2KHffxw3mcArWy1rbFyeAs3WbmcVi0z3DiUWF7SAVDgaoGzfglVe2BPAm\nFadxNYS+heJ+dy5ol3zhJ1z5WpeFSEwQ7BPHB/T7e9y82ePOnT6v3Ar5tvQD7mZvc/DWNygefoNy\nccrSNNTYrXsMDIKA/SRhfzAgOTggvHEDfecO1fFNqnRI0QTkedsl5jzN6SpuzLuW7m5GZHvDy1oA\nQ5sF69dsQ8uxIQwT+v0hw+E+o/AR8WyGeustmkfvUJ2eUhTFpvozAOpSmEw0i/cj7i1i7j+OPQEc\n07qbDW3pSs87B3ffuI3cJmPtJmz4i3RbSdzGVeTawX1n58Zz9bU+904Ar7uEAm2M1R2u6dHenv2/\nE2pus3ST5lxf3slESFNNFFkr2A5QSbDTkBxnCmMC6jqgLK0FpXWrCLhzcYLUzQF2owp7vVZB8PsD\n+7OEXccnq1Q+uXF/0rFbhuOsQl/Rdg02osh6Kdu13eBGSbZJlX72O+S57emd5wqlbPmZSEIYxsRx\nRBzbhCunMLm9xHkoNgJ4CuES+hVsiruXS2Q6ZRj0uXNU8tnA8GA9StgpDs7i/TAB/HGt7RcmgLdO\ntK7tlXN5/uuZVc4CDoFEa6J+H314CLdv25W4Vi3FGJT4AXNbv9VmPAY7n61op6LAdlKPxvb07ZMk\nt+j3b7G3d8Dd24Y3Xm94427G69MJt6ZvMf7gbzJ7+BbF4pSVsSMIYxECYBhF7PX7jMdjwqMjuHkT\n7tzBHN2gSofkTUjuNXS/ym7J3e/mC1+/+YYfF7SL2mnJTgCfVzoWAIo4ThmNhhwd7bGfnNFbzVHv\nvYt5/D71ZEJRVZv2HSHQ1IrpNODevZC3ZhEPT2NWmUubCzfv224Qrmta6Z2DVQDsZi5bpUhu0T7r\nIoWrwTU8/fs5K2I4tJuYfx84AeUEsNvM161+GQys4HWH7x72GylYS9cK9F5PkSRqLRTtxt40Zh3D\nta5Md82tJW02ZUbL5fYwDbB8uuiXa8DU7xvSBJK1gNbrpKDIDWdIQCnZZHS75LOrwrUvfKFtXOIS\nk9y94GYmJAkbC9iWGhqMqbDDN3ZDP1bZtveGMJ+D9UD1gIYgMESRrSEXae+fll/ronYCeDKB3spY\n5coTwAQhA7XHzcOS4hDCxN4D9vO2PR67wzY+7rX9wi1gY8DU1jdj8hzJc6SqkKZB0/a56WG3Rg1s\n2qbcv480mmF2zK0RfNu39RgOFYNBQK9n09zbVnftxSnLhjzvr4v+Q5xlY11kAWEYMhgk3L494vbt\niDs3al4ZnvFqf8Ir2SNunP0WvQdfo3nwJjx8iFosCIwhCEPbXziKSA8OiI+OkONja7HfuQO3b1Pv\nHZKbAfNMM/fmY+4SdBXLVfxMSD/D1P30N2GbybqbROe8GO5oY7J7e0PeeCPm858XvjOE2xVE1bZ/\nI1SKVGuGQcAySpE6ZLlQTGrX/ca3uNsNoLW4W7j5sLZn8Pb0o6dZv/Z114NraL+z25SjyFqM/X5b\n71mWrSB194JTpJ3rFuxm7vR0tzE6Ae7uH6fIOqEOlo/RyP5/tRJWqyfd3H58sqpk4zZ1Vlsct+7l\n0cg6327etEc/NURBTaQbAm0QbQU7SmiMoiqFqrafa6c9+ZUan3w4nlxoAez17PVavup603RubWcJ\ni4ViPtdMpwGTScR8HvNk6ae//oz3vwKbhFdR1xlFYZXlpjFrRV4hEtE0MUURsFhozs40jx8bBlPD\nYd60bpfVCnRA1MsYpBUHPVjm2zz5SYJ+EtbLWNsvVABvtIamwZQV5G0bJDEGl7fYx4rICE8Az+fw\n4AGyKhmUcHvUZ55Cv6/W7iDZNEwvCrOVGLBa2XmP1v3riLcN2OM4otcLOTqKeP31hM99LuKNVypu\nZKcc5+9wtHiL/tlv0fvgazRvvwmLBWq5RBtDGASEvR5hr0d0eEh46xbq9m149VUrgG/dok4OyWcJ\n83nAfN5uHOcRd5Xgu579hhtu8/Q7YNkN8Lw6YNdkn/VPZ6mG7O8nvPFGzBe+oHithFsPIL5vbVb3\nDkqEXhgyimNUnCJNxGqhmBbCaiXepugW+q7F3cK6EmVdsC8bDdkfyO674j5qkV41uO/sXK7O/ewL\n4Cyzz3V5EG4/dBu6s3LBvt7V5O4mYDkvyu49Bq0AriqXWCWb99jORTBrBdGsxxG2AtiP7zoBfOuW\nXda9uEE3FYGpUGJACaIVZa2YrwIWmWaxat3kWdbe41cBLqu919tOTEpTV89rr3HbZtR6F1YrYTbT\nvPdeQF1HzOeu5G/b+t3uD+4es14oY/KNsg52xKs9QkT6wICiSJnPQ05PhccjOMwMReYJ4CwDUURJ\nziCpKfYNq/W+5HILnNFwXubzx722L0YA18YK4MI68aWutyzgHrZ4wNk71LW1gPMcOZ0w3O9xa/8Y\ns2fLGOJYE4YBi3UwfbXazrqdzRRVJSwWmrKsN++stSaOIwaDmKMjzWc+A9/zPfBdry8Zv3vK+N03\nGTz+DZqz36K59zWaN98EvPStMKSXpvTGY5S3Ss0rr8Ddu1YAMyZbCfN1VxgngK9aUsYudjfHj7aA\neYoA9pFsjr09zRtvKL7v+4TjCURfhejUCuDNuyhFL4oY9XoQp0gTslxoJmI3xzYxxLm83YJ/ugC2\nLepky0Xlb0TnZUdeda5he2NyGcUuLtrvtz2UnVD190Pf6vW7TlmLylAWUHvuawu3Ccu5FrAx1mPh\n3ruNP7usXOct27aA3ei8bQFsWgEcGqSo7E1szGZnXuYBRSFMSsVi0WZm5y7X6IrAuZZ7PeilhtjL\nCF/MrdvXGOj3oNe390KeWyVoMtHUdcjZmety5wSwv/5cqaE/wcqSa4wtZ6prpyi7I8Y2/xWKQrNY\nCGdnmpMBzGtD0TTQ1G3vycYQHWQMkgr2oajNRklaLGQzz9jR648gtOfRXo9PTCtKd9LGgNGBZWj/\nAMkPCGYzoiDYXPoaKOsavVqhz862Ug+lNyAdztgP5jCcUw4DslHAYh7gxke5hecuWBQJQRDQ6xmq\nqiEIbP1mv685Pg44OhLu3qz59jtz7sqC0ckZ6fQ+wXIKRbFxkQugg4AoDFFhSHh4SHB0BEdHG5cz\nN25QDfbJmx75RDOpbazKZev53XWuKnyun1YbuDuezm2YSrmyFGf9tu6o4VAzHCpGI8Vrn4KjvYZE\nNzb+lMYwHhEMh/SShD2lUIMB6WuvoV97jWbweYrFGywXI+YTQ54364XsGnD4WfI2U7Zt+j9A65Qw\ntGURLknIZb+6coVdbfkqxf4+DD7ffmasS45yeQ9uyI3zVLm14GpuXbLTaGRTPhQ1igZFY++fdcJl\nVQtVoyhr2bj/XV2ua/jvTzBybm9os+6dte0E7brbIaORjfm6BLDRyD4nCu2kM0wDjb2hTQM1Qm0C\nVmXAstAsPbf3Vaz7dQ0q3ICiJDYksUFXFcUoI9jPWYYNcT8kHgQQhJzNNKdzq6AMBprRKGJvD8qy\npiiatVEE265n/3CP+/X6/sUNNs9RytDrGfb34fjIMJqWxNOV1Q5cllYUEUSKJKwhzBkmIYueZjFS\nT2TuQ+vVeRlr+2Is4CDA9PrQ7KPyfYJHj4iDgBK7/dVA2TSY1Qp1emq/7bogUBpDWs0hnJEMZ2Sj\nlMUiYbIMkJ36LHehej1Fr6fZ27Pt7dxw6L094e5dxd27wu2Dkhtmyg0eMHz8AZEngJ2JJkAQhqg0\nJez10AcH6Js3kVu3Ni5nbt6kHOwzNz2mk4BJIRsB7JTmq7gwd7FbD7jrPtwVwNAmyhgTYOfF+i6q\nhuFQc/eu5s4dzac/1XC0X5PohjAA1YuR8dgK4DhGtEbSlPT119Ff+ALN4DspvvYqy68NWSwMeV57\nAthp2S7RyhfAtu+w1glhGJIkstl8dgWw30nnughfB98F7bdt9MuPVp5rtihaq9VlnDoB6A5tGnRT\n2jF1CEYEI4q81KxKyAq9NcNX6ycFvXMt+jWeTggrZej3ZVNr7D7XF76jkR0cE4cGhUGaxgphY2ga\noTKKsrFtFFe52gjg3d7HVwVOQNk1YEiihjRqSOqcYDhjvD+hTCqCQYoeppQ6JQpiGiPMlyH9fsBo\nBPv7msXCCtSydAqwc0v7YSffCnaliU4AOw+WqyFu0Nps4s/Hx4ZhWRKdrkcbugLtKCIIFUnUoMOC\nYSIs+rDM2tJCl0DnZ/S/jLV9MQJYWwFsogMk30f3ekRBsHEdNkDRNMhySXN21mZerFMm02pGEszZ\nG85tHeBCc7J0I8baz2k3Addth7Xla4/jY/jMZ+D11+HmoCJ6b0L07nuEJ+8gkzPwBLA0DQbQYUjQ\n6yGjEeKyM155xVq/60yNUu+zKPucTDRny3aqiitLuKpJOD584btrATvhu20BO3eOoq5tvaZ1SbeL\nbzSyAvjzn1d8+tWGo72GVBe22YOzgEcjeklCvE6pDT7zGfT3fz/N4Lso8oTFN2Lm84Is27WAnfvZ\nF8Cu6f8ApRKiKNhyq54ngP2Feh14dvBd0H6fbCeAnWXqC0YXt3UW8HC4bQHrqkHXFUGVgxKbbqwV\ny9ygMqFBEUWyicOfZwE7Aezc4n7vZq1lYwG7z3bC1z/6PZtVrWiFL02DMYrKKDKsBbzKYblWMq4q\nXAw4Te11ScKGJKwJTM7eaILJHmLyAhlZIpfKVossi4DHs5B+XzMea/b2DFBSFDbByq5BPynSCWEn\ngN0oWTfP3SnLGj90ZAWwYX/fcOPIMDotieuV3YRdQXlsLeAgrImjnFWsGPWFVRkg60x5l2Xthyde\nxtq+kCxo+y1sn1a1t0d4dERy86Ydpr5aobIMVdeYoqBaLq0lVJaY9QrWSWK7oxQZw+oGN8tj6sEN\n5lqzTIXFyGZT6DhExwGVUeSFkBeyWXS9HuyPao56OaOmoLecoFdn6GyBylawskEcs1wCIGmKOjhA\n1gcHB8jNm9b9PB6TxyNyGZPlYyYMOM1jznLFPJNNIoZP5K4b2pF5lTbsrbDDjoXk9wS2N3mzTqiw\nk63sdKuGMLRTSsJQMx6H7O1ZT8YwrYklR61WSF3ZXWE8Rl55BZVlSJpS9PeY3vwcq/KYdx6n3D8T\nzmY1y2VOnhfUtWv0YVj3MsMK3SG2vcoIkSEiA8IwJUlC+n3ZCF0//vu05uzneTyuItewfU/vfken\n+LqfTgET0zCOV+xFK/aKjNFS0ZsKgSh0U6FMhTQV4jVaVgiB0oRe3H231WNr6dq/Wze1bJ2jc6n6\nNZ9+cl0UgV4nczUoaqMxBDQCpVHkTUDRCEUhWxu2j6vEt998JtAN2tSoqkAt53DyCO692wq70Ygg\n2iNaHdND0e+nG8W137ddq7IsWHsMzLpxisv/cLPlNimVWMW4h3U1u31B0e8nHByMODjocfem5rte\nX/KZ5IzDxYRhdUoUNG1xeZoiSQKBBtMgeUZoFEmg6fehrNq8hNYz9/LW9sU04lAawhjCAVLuER4f\nI9MpTdPA6Snm9NSqsGVJtVxSrYWvmc/h7IywaQgXC9SjR/QPXuPm/muk+w15L6KsFUWtIYmRfg/V\nT8nrkPlSMV8KeMkhw7hiL1qSrqYE1QkymyCrta/YqdHLJWIMptdrLd4bN+yxHg7NYEAeDThrhpyt\nRkzrAdMsZJopsqJ1R7kN6rwsaLgaC/Rp2I2nOIFl3dLbgtceDSINUaTp9QL6fc3enmY8VjYuF9eE\nTY4sF0Bld4Tx2Lqxh0PMa69RmQGnw8/waHHAmyeaDx40nJ2VLBYZVZWvBbALfIRYATwARsAeImOU\ncgI4IkkCBgPrsvTjvv73ccd1qQH+MPjXw9VKOyPE/V81Df1sTi8/oZ+dEWtN0miCXK9fayw9TkKK\nIEajpSEMzCbO7Le/3K3Pdlab65DlZ1E7l+puSZl/6EBAgZ2WqKmN0KApEPI6IK/UVkjlPM6vCt9u\n/YYhhNp6KKQorNB9+BDeftuOJ1p3LpH+IWEMSTTc6hrW60GWKVargCRxPb01TePKDzNa4VvR9m6w\nLUW1tn2jez3FzZshn/1swrd/e8Jn7jTcVqfc0Y84mj4gKU8JQ2PPx3dbOXfJaoU2AXEQ0+8ZVlmb\nDOgaiuweH+favhgB7FLp0gGKfcLjY8LViqauaYyhWSyo53PqsrTzXMXGfxrH/mKBfvQI3n2Xwefm\n9KKa41djTJxY97YKrF9pDDIOWJSK0xmcToW6kY2Wm1IzXC1IsxOC+UOYncFq0aZnunY7gLgxKDdv\n2gznO3e2CM31gEkz5IPlmGmZsFwJy5VsdWmBD8+auyqLdBe77kk/QcclZdkyA38ggnUpRZFmMAjY\n24vY35eNW7AX10QmtwpT0LR+sf195LXXEBGqRcLpwz7vPBjw5nuaDx7mnJ6VLJcZxuTYZgCuFmlX\nAO8jMkbETs6JIk2SyFPjvk+LC11nAezgxw2dHN0MLzAN4f0F0f0HhNN7SBOi8hBZrC9soBGtW391\nGKJUjRZD4NVe+0qunzTjSmL8jlyuFt81yfhIAawBERojNKKoMVQSUhjIa9kqqXtak52rwrd/bQNl\nUGWJFPm2AH7woM3ZGU8Jbw5Ib9zaxNrdtrlaKdJUkSQG0DRNQ1k2tE1xWP90AtgN1xigdUySaEYj\nxZ07iu/+bsXv+l3Cd7yyIH53Tvzue4T33kaVcyQw263M0nRLAAdhTBxU9GOYL9t/1fWHu5s/cQJ4\n434MNdJLkeEQCfeQddsSmc2QorCJDnEMqxVmtcLkedvCu66p5nObC1cU6DS1N0Rt3Y4Sx0gUIUdH\n0NyEuMaoAUWQUPUSagNJWBMHNUm5ICmmBLNT5PTEjlOZTu3NtM6YEr/eJElaC/jmTTLdJ1cpmfR4\nXO9zUg6YmpB5obeaBfjJH26DOA8f9r9PGnxX82493e70mCBwzdqrtRC2ric7pzMgTRXDoW1+IbLO\nbG00tY5pkh6ZYC2RIiCvA9v2s9ZMlyEPpyHzPKSqoTEaUQFK2bF2TZNgTI92cdfAEXAMHBKGI5Ik\nIY5by3s4bAWw33zDuaN8jq8L19Dy7b6TS7hzj7nrFMe2fCVUNYGqCasMLSsCk6GrDKQGsUl3TdKj\n0TFNkpI1PVbTlOUsYlUHLCrFsoL76z3/nXfggw9qHj6smUwqlstmMynJGGtJGaPQWm8yo5tGtkrh\n3O+uVM7p4CKy+T7WayNb3bzca55m/cLV4dsl002nQCKkaESHKD8WUBQbrUg1miT+gHGyTyUhjQ4J\nDyLGhEyOQibLkMkiZJUpVishyxR2aIax95SEKKnQUoIJsNNsDHFYMuyXDPvC3Vs1nx3k3C0K9k8m\nqNN30Gf3UfMzex79FIb9NqXd1Zqtkzl0EBPpgDRok/ngSRfzy1jbL0wA+wtURRrVWw/bjFd2plTf\nXiARQa0HccrDh6iHD1F5ToENvy+NoShLisWCqKqI3n6beLEgfv99dL+P6vWstfrqq3YFKYUarMcF\nhhFGIJGclJyonhGuJqjJqT2HszPrPpmuk6/cSBTXh+7gwLqc1z9XZZ/TrMdJ3mNS9ZlUfWaV2rSc\ndEr7VVh4zwOf6/Pmpfp/uzhbVTVUlctMjnANN8JQrQWwfb6t1YPVKKQI+9Qju6GeTTVnU8XZTDFZ\nH3mpaZTGiKzdZsH681KqqocxfYwZYuNKrj78FlYAHxPHCcNhzGgkHBzY8hTnyXICeHe+7XXjGnbW\n9nqTcu47aK1QV1cZhYagKQnqgqBYosoMqcrW5FibkXUQUSVDquE+J/OIh5OIR2chk2XAfBUwWwkP\nHsL779vj5KRhNsuYzzOyrFoLSlvWVhQxQRCjlNo0fhFpBe1qZTldrewmvFi0IYaybIWx34xht7Xm\nefHfqwY3wEJrqIaKvV5I2DOEadq6D0Q27gBtzugl95AoIiJnoIbcOBwwOxiyVH2WMmCpwnWzDnv9\nRcK1l0wT6opAlYSqQtUNFAaKFYFpiIOaWDfsxRl31IS9exP0B6fIyWM4PbEkuhozZ367Zt1JYh8b\nj1E6IRI7xNlx7rua/Vjwx40XbgGLgAoDpJfaKQZJZjWTdR2ApCmyv4/s76MAs1ggZ2ebGTULoCgK\nsqoiXK3oLxaYe/dQYbh5DzUc2rtknQmrTESQRsRpH7Sh1xSkZklUzZDVBJmeWsF7dmaP+bw92TS1\niVavvmqznb1mtatpn8enPd5b9ZkXAVmhWRXaWluei+s6NGLYhbt8u72Sd4WxFcJmU2Tviu5tz+WI\nIBDSVBgOZVsAVyFFoKmHCas5nFTC+xO4f1/44L5w/wGAsH8A+wduaIJN2ogim2zVNAOaJnNnjL3d\nbwA3EDkijhXDoeLwsK0NHY22XZW7Avg6cg1PxsicNegsxy13cNigiwpdZ+higZQ5VOV2INcYGh1R\npkOK4REn84B3zoQ331I8PhEmU5hMhUePrMfz/n2Yz2uqKqcs5zRNge0Bb+P79txs33eQzb3pGvo7\nIewnYTl+3RAdl2ntf18Hvy/xVYYTwFUFplZEQchwpFofvstIXAfEVVnRi+8RhzUjNed479COZ907\nohw2lMOQcthfNy4RlkvXbU4TBIY4qEh0RRyU6LKwg4CXGVLkSFWiqoJgOSM6vU/0/gfo6YklM1un\nojvhe3y83bbOzbscj9ESgFEoZPMVfOXR4WWs7RdqATs0oiglJANWwQA92Cc4Oka59jfrzldSVZiy\nRBtDlOckRUFRFOimQTUNqq7toRRKKVsV5gKM0yk8fgwffICUEPZWxL05ohVRsyJoluj5GTx6YK3f\n6dTeXVpbYtaZWqbfx9y+g7l9F3PrNoVKKFRCWSQ8zlNO8oSzLCUr1okYO2U1fnLO0zJln5Zl90mF\n/z1cwobz4NsZsK3bzloOAgh1ragqTRAogkATRXozdSZaN8Vy/dTnS8U8U8xzOJnB+w/hG+9YS8ht\nyFEEomE4cknSwq1bUNcBs1mf2Wyf5VKtsy8VTaMJggPCcEAQxFt1oc7ydRv0bvLVdeUanvwuT8sg\ndbNXQi0EhaBLjcpClOkh0R7SF2oVUklIXYcsliOW9FhkMW+/q/nG2/CNN62lO53WTKcNk0nN6WnN\n2VlFlmU0zRxj5rA1igO0rlDKbHlkXPazM7r9JjFuzrCblLTb7czn28mb8wTwVePb9XtuGggDIY4U\nQSjkq4Q4HBMf3iRYLKxBc3oKsxmmrmA1h+lja1hNbPKqGo6Jh3uY4R79DMpcKPJ1x7lQEURCpBvi\noCLSNbr25lC6jLd1HJflCSzOrOAVaRfr0RHcuIG5cWOdfBLYDOjBEJOkEESUlc1iz9etUf3JWH7u\nzstY2xeShFU3QlYFzApBqz5J/xC5WaGGg/ZOns9tDFZrVJqSnJ1hzs6IJhPMegc3TWOnJgUBNudV\nLQAAIABJREFUQRCgk8SmmKepXQmzGbz/Pnq2JEweIPEAtCI0BcqUNuHq5MQey6VdYU747u/bJrD7\n+5jxPvXogGa8x2wRMlmFTJchJ7OQ01nIciWUXm9a3xLyW5n5MbKrsiA/Ci4DNo7bDc533bVNOjRF\nEVIUQhTZuK9rduHiMsa04aX53OpMZ2dW4L7zDvz2b8O9e3bdn5xYoXlw0DaHPzy0n9XraR486PPg\nAYj0KUtZx/A0SdKn10vo9+0t4AvfD+t45SeXXVeuYbv2e7cBi7t2VSHoJkQ1oGtFgEb3emh9wKrU\nZIUmKzVnpwMmj3pMKuHd9+Hddy3Pk0nNYlGwWBQslznLZUZZrtbeDHcYbFIdKBUShm0DHtdMxS89\ncufuDw/JslYAO853G3r4uR2u49ZV9oK4awQwX4BgWzeOqoT94JC9258mYK3FPHiAefSIajajePiQ\nIkkoej2KXo8y7REkKTpJCeIUVQthrYhrQQUaHWpUqAg0aG0Q7dUG+5l2Tnty2nwUtVbvaGTzdY6P\n7eJX9vlG2ebVJooxCFkmTGdWXJyeWiG8a0C9rLV9MQLYKLJKmOcaHfdhcEiYasJqvFFBZT7HrOsH\nVJqSvP8+oQiDoqASoWoaqrIkUoooDAmiCEkSxA3lBHtFAXVyShjGBGEESiE0KNNAWbQziZvG7raD\ngd21795d93O+TRMm1EFCFaRMC+HBqXD/kS1rWiwVC48wXzve3Zivkib8rHBZpvCka9IJ4KqyPVyX\nywARRRQF9Ps26ckJYFca4Fr87Qrgt9+Gr30NPvjA0u76bt+5Yz/HKcM27KOJogF1nZDnNauVbNph\n2sxKvRmD5wSw27D90iNfAG83eLieXEPLsTuca7YoWgFWFIKWECWaQCJCnRL19tD9htlMmDUwWwmP\nzgIenWkenQn37llu792zruYsK8iyFWU5p65n1PUUYzLadoVrXzEakYYwNOvuTbJJiO33dzxznrJQ\nFC2PPt9P49x996uSbPU0OOVqM9c5FyYzYaFjJDiid7uiF1rhS1liHj+mNIbMGJbASmuWWpNrTaw0\nidYkSpGKJhFFikLCwE6ZCwNEK9vhUMmTiSO+BuViBuu47kbwutydvT1QCiMKlMYohRFNY1yfajsT\n+OxsWwDv8v1xr+2LEcC1kOXCdAGmjqhVn0oLke7R1BWGCqMGSKqRvRRdjYj0mCgdkeztUc1mNhN6\nPieIIoIoQkWRTb5yOe5RtNm1pSrRGDDV1moyeu1/6vUwStOM9qlHezT7hzR7t6kHt6njm+S1Js8C\n8irgwRk8OIOHZ74LdVsj2l2gvmC+bvA3KCd0/To6K4yFqlLrMWMNg4FmOJSNAHZuaAdnCc/nVmN9\n9MhWQNy/b6MOzkvlkn7iuBWiVWVbk5aloizDjaNkNrMLz++A5DKe/fW9K3x3f15nrs+Dv1m1Axhs\nT+emUVvPMWZ7mPqjR5ZP+7NeHw2r1YqyXFIUS4xZYi1eV1LmWhRqlApRKiKKYgaDkNFIMR7LJpt9\nMNgeCLI7Ys/31LjH/I3Z/b47XOUqC2DYXbcgOagoYtAf0o8bVH9B2Dsk7A0hijCrFfVqRZ3nm55z\nTkVy6lKzXjxKKfQ6OUSiyFahOKHrxlRBW9g9HFL3BlRBShWm1L0hanyMjI+Q0REmHWKCEZg+TW1b\nmZpabZVGTmf2nnPpP65j4WVY2xckgFsto1gpFioiUaCbiDKvqfKGJuuhsxit9ohGN9jv3WL/zquE\nxUPU6Sn69BQ5PUVpbVPgnXrtrpZr2Ot2UKc9+cHIMLRuCaVodEgR9Ml1jyLsk4djitWI7EHAYqVY\nLIX5qt2sp9Pt2tYPs4SeViN6XeC+/9M6x9j/CaCIY2EwsGVHLt/Nle7t9pdeLq2r2SWuu+oxV+7i\nvFDOmnVaexS1fbmjaCtctYn7OoHt3N9Ps3w6rp+Ev1FtuiYFbecw2C71cXNzV976Wvfc2QxWn80q\n5vOcLMsoy4y6XgEr2raELnPenUNEEIwIwxG93oC9vZjDw4CDg7btpG0G0R7Ow9Hx/XwwxpYFTsuU\nIIeyPmKY3GB4eJvo9glycoJqGnSeE9GqSK7atwEaY6ibhsoYjNZoYxDXT9g16vYzmg8ONg2R6nTM\nooiYFxG5SggGQ4J4gJYBTZHQzCOaXNkGKo3Q7MTpT0/tPeb2D1du5rueXxbXFyKAXS1ZUcBCKQIV\nEUhA0xjylSHPDFXREMqYSFX0hjn1YEI8mDBKz1APHiAPHmAePmxHFkKb2VMUdjU5wlzNSBDYVed2\n2cEA0h4mTWl0Qp5rlnnAoghYFiGLZcT8NGAyEc4mNvPS15j9bN7zFujTgvXXCedpjO4a+d4CUIhI\nO+qsJ1uNa9J0O6ZojL2HXAjfLaCiaHUs1+N3PLbxXCeAk8S+Pgztez982Hqz/FZ5zvI9j9eO6/Ox\nm//g4ASwyzB1HozJpOXQNcBzh4sOLRZQFBVluaIo5jTNat1IJaPdziPsdm4VOZGYMBwTxyP6/R7j\nseb4WHN83G4Ladq+v5+d3/H97HBGSFFrZlWPqojI6xUmuUF8eJt4+Ripa9RiseljBdb6dXu3wQrg\nyhgqEeu1bBqUW6SDAZtSBJcVeeMGfOpT8Oqr1OkBi1PN47OARa6J+yFRHBBIQF1q6kJTo6i80IjP\nnfO6zOett8NXIF8m1xcigF2DdlsnaxsuiLSN1F3vZCczU10TRCN07xAzmEN2gMkPoTjC1IamNpjG\nIGRIvULUCqVjdNBHRX1U6NrbBEjUQ+IRkoww6ZAmHdD0+pQqYWlgUcKihkXWbgBOC59Ot7/HboDe\nt4Q77djiw7IF20QH+wSlZKvDlLOYXJKLn6nq7pXJxArQyaSdA61tjsVWk/3hsH1tELSNE3w3o3Oc\nOGG8Wzp1Xuy343obu3y76+JfR18Bc+u+KNpJSa4Bnfu5WDjODXVtYDO2JVi/R7A+9PpxRRjG64S6\nlOEw2Rr04BSsJLHn6LwqPq8d38+H2ihWlaKSENOMiNObpEevoZucWqVIEBOlKbquCZqGqK7tdCvW\nndjXI14JApogogoiah1h9vYxh8eYo2Oa4Zi6P6LpDzHDY0z/VUzvFbJkj9NcMSmElVIUIcQCYdMK\nXBfb9zumucMN7vCT6C4L1xfTivIc7E5ScagqWNTCvTJkOkl4WwtmCs0kxkz3qEqzOVRT2gJ/UxJL\nQBxFJEVMIAHSaKTWKCKUStFNilkmVDqmVNp22iq2XWP+4ZQxnwg/I9YnrNOMnw6nsIThdsa4S3bZ\ndTVXVetW9jsP+Yk+Dx5Y5aiq2piv3/bOWdCuysxNxXKcuZJA55J2pUZ+4k3H9TcP35pw0aJ+v+XK\n74swmzmXs7WIlXKlL3ZYRtMIxqSIVIhUKCVobTtcKSVrZd5m0g8GCYNBsHE3u/Xrx3edcpAk27x2\nfD8f3DUtS8hMzKx3k0BqynREdPAq8adfJ5k/pFmt7LFe1EYEoxThaEQ4HhOORlQmIqs1VR1QRn2q\ndEiVDCmCHpkk5CRUyyHNgwOaPKFOlJ0RXcsmQcyfAQ3tvuPuRZe/4/Z7v1nMZeL6YxHA/oXyBfBm\nZF0lTIuQqlDURUSTJzT5Hk1ekmetwAx1QxQ0REHNQCuGsWZUKkKlUI2gKkE3iqAJCHON0Zq8tCUP\nZb2d4efPrHXn5xawO3wLyX/8ZZN2WeG7nP0Yi9voXCciFw/M8+26Q9c0YVdBch4KV6/pBLArH3Kt\nI91nu7ISJxCcAHYZ235YwbfgOq6fD7vXyQlh59Z3Xgr3czxu+/j7wtfmiwQYk1JVNopoWxU266YN\nEIaynvEra6VKMRxqhkPNaNSmfDi+nMBwit96zsPmPDu+nw9u32wayCVmmt6i6Y8oju6wz2NiHpPW\nJ5jJBDOd2vpgL8iubt1C3b6N3LpFWYTkS8ViqcjqgLwOyZuQRR4wX2nmK02+CKnymPpRjI6FXk9I\n1+vcdSB0yXG79fouidP1FHClkU4AXyauPzYL2MFtytAm7FS1sMg087leu6PSjTvBbdhZ1ibLxcCo\ngr0axiXECtTaxRg0EFQQrK1at5n7gfd1GGIjkP34kDtHt3B368L879FhG/5NfZ4AdtbnYtFaKu6n\nH973+/Qu18OrlGqtXudqTNNW4GZZu+jcjFinXGndCmjf3eyfZ8f1tw7f8vSvtVvnfq6AMa0iZhti\n2JGUbm9we7dfleK7il3mu8t2/igB7N634/ubh/NaFSpEojF1PKaKjwjiI5JoSqImmLMzOD2zglhs\nOVAjGu7exdyxpZ/zLGA2F2YzmzHvlO45MCtg6sbDL9qkyoMD0Os8A59b2ObLnaOzkl0ypnveZeP6\npQhgtxD95Ca3WUdRuwm7ds1u8/Y3c7+fp+/z95uq+1obPN1l0Q4NaJ/nF9z7BHZ4dnwU13HseUHW\nC80PVTjX4WjUuqPXbcQZj+3/Z7N2QppTqFwC0GzWWtd+nLLj+sVgd825OasupODWoOsB7E8UAsv/\naLTdZ6Esn1SUfFexg8u3dG0B/HwC3w3t1rcvmDu+vzW4fbUoQBrFaRVT5QMmojDLmKYc0phDWwpY\nK8paaDigWQwwDxRZaWtzV9l23wDXHMW/R3wLd7caxVm0vkXsDhfzdUlXcL7Aftn42AWwcxG4zblp\ntssY0rTVilerVvi62i33Oreo/NpTX9C6zXjX3bBbWuTile7wLWN/E3G4TORddnwU17uu5vOEr+9m\ncgqa3y5yNoO33lq3pTzHBeV7PnbH0HVcf+twQs5tmk6AQns9nWfjaQLY9QB3fLj7w8VpHf+7sV2/\nftuP5/tr3Y9Ld3y/GDih1zQ2fFgVETPRBCTU+ZC6rKibilUhrDJYZUI9T6gfxDSBomqgrmxbX1/Z\n8g0mf/jJeWEtdzjl3U/AcmEtl4gJT8qBy8L1xyqAn/bl3UJxm6u/iMJwexC2e9xfnLsuCP/552nP\nPom7gwPOuwGe9j06PB3PwzW0pQNuQe5y7UqP/OxaF2JYLjuuXybcxuncfrv/8zdJ37Jx83t7vWfn\n+1nX9q6y3vH9YrHpKobCVv9u81OyrjYpYLHa9nQ9C9eOO8en77FwSpPvanbC1n2GPz7yaZxeBq4/\ndgv4aXCWi7N4dzUav7bLWUjOEvI1bt8NAU9qxe55vjvDb8K+exOcF9e8DMR9ktFxfb3Q8X198KK4\ndj+d5wraMIerdhBphe5uD3oneHdzPfzfLwPXl0YA+wvEkeK7JFwdp1t0fnLGbnzH15L8xbj7eedp\nW7t/+88/7/cOz4+O6+uFju/rgxfFtf9+jq/dKUZOKfNDjrv3h3u+/37n/f6ycCkEsK+NOK3IaTC+\n28i5EXfjtj4R5733eZmOHV4OOq6vFzq+rw8ukmvYTqh9FpynnF02XAoBvAtHDGxrN7sZcLuxn/PQ\nLc7LjY7r64WO7+uDjuuPxqUUwC524+IJ8GRGs+9WgutH3FVBx/X1Qsf39UHH9Ufj0glgF0PwG70/\nz2s7fHLQcX290PF9fdBx/Wx4VgGcANy799ULPJXrB+96Ji/zPHbQcX0BuKRcQ8f3heCS8t1xfQH4\nlrg2xnzkAfw4bAZbdMeLP378WXj4OI6O6+vDdcf39eK74/rycS3GOec/BCJyCPwI8CaQfeQLOjwr\nEuA14JeNMY9f8rkAHdcXiEvHNXR8XyAuHd8d1xeGb5rrZxLAHTp06NChQ4cXi0teJdWhQ4cOHTpc\nTXQCuEOHDh06dHgJ6ARwhw4dOnTo8BLQCeAOHTp06NDhJaATwB06dOjQocNLwKUWwCLyJRH59ed8\nzZdF5M9c1Dl1uBh0XF8vdHxfH3RcPx3fsgAWkT8qIlMRUd5jfREpReR/3XnuD4lIIyKvPePb/2ng\nh7/Vc9zF+hx+9ALe97tF5NdEZCUib4nIT73oz3iZ6LjevGcsIj8nIn9r/d3/yot8/8uCju/Ne/6g\niPySiLwvInMR+XUR+fEX+RkvGx3Xm/f8rIj8byLywXof/x0R+fdF5ELaNr8IC/jLQB/4+73H/gHg\nHvADIhJ5j/8g8JYx5s1neWNjzNIYc/oCzvHCISJD4JeBbwDfC/wU8NMi8hMv9cReLDquLTSwBH4G\n+F9e8rlcJDq+LX438DeBfwL4u4GfA/5LEfkDL/WsXiw6ri1K4OeB3wd8FvhjwE8CP30RH/YtC2Bj\nzN/BkvRF7+EvAr+EFUY/sPP4l90fIjIWkf9cRB6IyEREfkVEvtv7/5dE5G94f2sR+bMicioiD0Xk\nT4rIfyEiv7j7vUTkT4nIYxG5JyJf8t7jG9i2Yb+01qC+vn78e9aaz3R9Ln9dRL73OS7FHwZC4F80\nxnzVGPPfAn8W+Nef4z0uNTquN9dhaYz5l40xfxG4/6yv+6Sh43tzHf4jY8yXjDH/lzHmG8aYnwX+\nJ+Aff9b3uOzouN5ch28YY37eGPO3jTHvGGP+GvALWGXkheNFxYB/Ffgh7+8fWj/2Ffe4iMTA9+MR\nB/z3gGuP9r3ArwO/IiJ73nP8Vl3/FvBPA38E+D3ACPjHdp7D+v9z4PuAPw78uyLiXCBfAGT9nFvr\nvwH+MvAO8Petz+VPYrUh1uffiMg/9yHX4AeAXzPGVN5jvwx8TkTGH/K6Txp+lY7r64RfpeP7PIyB\nk+d8zWXHr9JxvQUR+TbgH1lfhxePF9Tk+yeAKVagD4EcOAL+EPDl9XP+IaAGXln//XuBUyDcea/f\nBn5i/fuXgF/3/ncP+Ne8vxW2r+lf8R77MvCVnff8v4E/4f3dAD+685wJ8M9+yHf8DeAPfsj/fxn4\nz3Ye+471d/7cRTVY/7iPjusnnvtz/jldtaPj+9zn/xiwAj7/svnpuL4YroH/Y81xzc6+/iKPFxVY\ndvGDLwAHwN8xxjwSka8Af0ls/OCLwO8YY95dv+a7sSSfyPYAyAR4Y/cDRGQE3AT+unvMGNOIyP+H\n1YR8/K2dv+8BNz7iO/wZ4C+utaNfAf47Y8zXvc/6zo94/Xlw53WVGm53XF8vdHxvn+sPAX8JK1x+\n81lf9wlBx3WLH8N+r+8B/rSI/JQx5k8/42ufGS9EABtjfkdE3sO6KQ6wLguMMfdE5B2sm+GLbLst\nBsD72ID+7oU/+7CP2/n7vPHN5c7fho9wtxtj/j0R+QXgDwC/H5tA9YeMMX/1w17n4QPsjeXD3SxX\nJk7YcX290PHtnYzIDwJ/FfhjxphfeJ7XfhLQcb31Pu+tf/1NsRnQf15E/mOzNo9fFF5kHfCXscR9\nkW1/+a8B/yjWj+8T9+tY331tjPn6zvFEbMUYM8UKsu9zj4lNmf97v4lzLbGZrLuf8TVjzM8YY34E\n+EXgX3iO9/w/gX9QRPz3/YeB3zLGTL6Jc7zMuO5cXzdce75F5IvAXwP+uLHJd1cV157rc6Cxxup5\nSsK3hBctgH8v1mT/ivf4rwF/FJsh/KvuQWPMr2CF1i+JyO8TkU+LyO8Wkf/gQ7LWfhb4d0TkR0Xk\ns9gykD2e38X7JvDDInJTRPZEJBGRnxVb7/cpEfk9WDfMb7gXiMhvisgf/JD3/K+AAuuq+U4R+aeA\nfxX4T57z3D4JuO5cIyLfISJ/D9ZSGK+zL7/nOc/tk4JrzbcnfH8G+MX1e98Ukf3nPLdPAq471z8u\nIv+kiHxeRF4XkR8D/gTwXxtjmuc8v4/Eiywu/jLW7/9VY8xD7/GvYN0Uv2mM+WDnNb8f+A+xMZVj\nrBv313i6y/ZPYd28P48Njv954H8G/MzjZyHx38AKxn8JeBdb73W4ft+bwCPgf2C79uvbsZmP58IY\nMxWRHwH+HPD/rt/jp6+otnytuV7jfwQ+5f39N9bn84RGfgVw3fn+I0AK/Nvrw+Er2KSkq4TrznUF\n/Jvr5wnwFrac9D99hvN5bsgLdml/rBAb9f8q8N8YY770ss+nw8Wh4/p6oeP7+uA6c30h7bUuCiLy\nKWxc9StYLe1fAV7Dun87XCF0XF8vdHxfH3Rct7jUwxjOQQP888D/A/zvwN8F/LAx5rde5kl1uBB0\nXF8vdHxfH3Rcr/GJdkF36NChQ4cOn1R80izgDh06dOjQ4UqgE8AdOnTo0KHDS8AzJWGJiGu0/SaQ\nXeQJXTMk2OSDXzbGPH7J5wJ0XF8gLh3X0PF9gbh0fHdcXxi+aa6fNQv6R7AjmTpcDP4ZLk8GYMf1\nxeIycQ0d3xeNy8R3x/XF4rm5flYB/CbAT/7kX+b27e94znPq8DTcu/dV/sJf+MOwvr6XBG9Cx/WL\nxiXlGjq+LwSXlO83oeP6ReNb4fpZBXAGcPv2d/DpTz/PjPoOz4jL5A7quL5YXCauoeP7onGZ+O64\nvlg8N9ddElaHDh06dOjwEvCJ6oT1rcAvd/5mSp/9UZfbYy87XDZ0XF8PiNhDKQhDCALQGprGHo57\n91Nr+1yl7GPuqKr2aF54u/0OLxJXbW1fGwEMTy7I58VlIKzDs6Hj+urDCdMwhF7PHlHUCtO63r4P\nosg+NwytoK1re2QZrFb2+Fbvmw4Xj6u0tq+VAIZW6/1mcZnI6/Dh6Li+uti1fns92NuzP4vCHmW5\nbekmCaSp/VlV9v9VBbOZFch5bt+zE76XH1dlbV8JAexrRLuHc0e5w9eKoV3E/k93uP8/7XD/99+r\nw8Wi4/ryYPf6OA5e9Gc4SzdQNaHUhKoiqHL0ao5ezQmbFf1HNb1eRRw1qBJUCboCpQOU0igdEI8i\n4mFEPIyp0VQEVEYTKE0Ua5KBpqg1ldFURlHVaiOkO9f0xeM6ru0rIYChjfk4ctzPsmw1XeeWqutt\nAoKgjSG5xe6O8wj1H3foNuSPDx3XLxfu+/vXDtpN8UVakM7CDUNIg4ZhkDHQK5LlCfL4HdR776JO\nHqDI0CZDTEFTQ1iDMkKUpERJQpSkBIfjzdHEKU2UUEcJicQMo5g8ismIyYnJTcwyh+USFotOAH9c\nuG5r+0oIYLfoHSl13bqYssweziXlCPQJiOP20NoePolab5NmTEuae48OHw86ri8H3PVx18/BcfOi\n4ARwksAwqjmKVhyGU/r1fWT5m/Du38Z84+sUyznFYkaZLQkMiAEtit5oRH84JB2NkNu3ULduIotb\nmOEIBgPMYEjT69OkA5pen0w1LBAWhEyXGmPsPVWWL+47dTgf13Ftf6wCWGQ7W3EXTnN2Gk5Vbbsg\ndl0SvqbkSHGaUlnamM5q5cgzm/87zckSI6Qpm8Np2+483eFnUDpyHbqN+Uk8b6KEH3s7z/30fFy3\n90/TtMk3UbTtxvI15I7rZ8fTXHfw7G7oD+Pb/4woMiQxjIaGvaBk3MwZlSek83s0p+9iHr5J+cHX\nyeZzsvmcVZZhNp8hsByjV2OSfAzkUC0hn8PxsT0igVRDEEGSEIQNWgyBgkbZeyoIutiwj5e7tq/W\nPv6xCmCtbZJEv281Wh8+KauVdf2sVu0m6jZUXzNyR1FYcvK8PdxjLrsxz93zzXrzlQ0J/X57xLHd\nqJ0m5X73SdyFu8Gu+8a8C3+BPQ1uo91dlLta8PNy7d5HKRgOYTDYdpfubvhR1HH9zcC/hj5vT8Oz\n8C3SbpT9HqSp4XDfsEdO//GU4OQ+5t496gcPqE9PWc1mTPOc07pmDuj1EQKxMVRNY2+e6dR+wHRq\n/45jODiwJ7beDHSkiQIFAeRNez84i6lzRVu8zLV9lfbxlyKA9/ftpuiwS9Bksp2V6NZPWbYuiKJo\nCVqtbJzGCW1nBTnSHHF1bdZxBbMmTQgCey7DIYxGVjFwh9Om6tqSd97i810aHbaxW495HvyYjG+d\nfitcF0X73mFo7x2lWqXP3wjc4nd8d1w/H56WKPM0PAvfziMRhiBi6CWGg/2GvbIgeDAheLwWwA8f\nUjgB3DSc1DVnQLw+EqBnDLUjejq1Kc/WtLYbUVW1JxYE6FATxYogEvJ6WwA3TWcJO7ystX3V9vGP\nVQC7hZUkVhD7moa/KWaZXR9aW2KqqiXDaUbudxcXaLUls15nhsWiJstKsqykKKr1DWDWvn+FUoog\nUFSVoiw1RaFIEnukqaLfF8qyJcy5KJzrIgzb3118Ydey2sV1sZx8l9N5TRF2XY1ug/Ovn794y9Iu\nwNnMKmjTKSwWhixryHNDlrVHVRnPhQlBIASB5TuOhTgWoki23FzOavMXoJ/AEQStlex4f9r39jeb\nq2g17boTdzNUP4xvaHl1VpDj1ynZLlwQhnbDdBtpbBqkKZF8hVksNpuCFAUK29YvECEIQ8IwJIoi\ngtEINR7bXdlPoR0MNq4R0+tDkmLCiEaHGNEY5Il17H9f9z18XPe1Ddv7ob+W/UQq38J13k4rdBsW\ni5rlsiHLmvXabn/PMkNRGJrGbD73WffxomjPwdWK+25qf885DxfF9UtJwvK/rNvwnHYJ7QLVuhXI\ns9mTmpA7wG6Q/b79fT63xC0WGVV1RlVNaJrl+kYRQGGMpmk0da3JsgSIKcuEOI6Ioog4jhiP2405\nCKzSEMfbMQY/s85XIp628VwnnBfn8Tds/x7YLQ1wbqIksX+7ms48t1ry6anluSwryrKmKCqqqqGq\nauq6QaRBxFAUwmwWYkzIahUyGCgGA81goDcbQlFsZ1H68SEnCPp9y78TBue5sNx39rV79xlXDefx\n6oTph/G9u3k7Iew/PwjsGhuPYTAUwggaoygbhRaN1iEShmitibSmUYo9Y1DGMFKKsN8nGo+Jx2MG\nR0fER0dweLid9vrqq/Daa3D3LmYwwqQ9mrhHpSLKSlOUwmLRujz9jNxd5dH9fp1w3tp2Cm+a2n1y\nV8HdtWZXK5jPW8fEalWTZRl5nlMUBVVVUJYFZVlSVfZomhpjFM+zjw+HLY+7Lmn/iKL2u+3yelFc\nf6wC+GnJFi6+4tAG1ltX9HxuD6ct+ZZvHNvFagWwQamGPK9ZLjOa5oSmeR9jTtfEKUBjTACEVFWI\nMUPKcsByOSAM+4ShIgyjTRKYc51DK4CdNeRbbn7ij/993Xe6btjVgHdLC+p6W/i6JAn3hhp2AAAg\nAElEQVQ/TuO6Fi0WrXCbz50ANlRVRV0XNE1B01Q0TYUxFWCFcF3DbJayWiVMJoaDg5C6FpTSWwLS\neTScy9E9Bq0AHg7tz8HAPnYemqZ1oTk32lW1gP3fdwXt0/jefY57zF/zbr3t7dlrHkZCbaBqNEiA\nCgJUGKKDwFpAIiggNYZSKcLBgODGDYJbtwhv3SK4fRtu325N6yiyAnmdiGWihEaF1DqkrDSrQshy\nK4BdBrT/XfzzhW5t+xxqbffHwaBdA37HsdmsdTMvl3B2ZtfyyQlkWUVZZlTVnLpe0DQrjFnSNCua\nJqNpMoypMMZF+Z9tH8/zlsMkaYWtH3Zy97HP6W7Jknv8ReJjt4B9V4SfbOE2O5c44764cz/PZq0W\n42J77vWDgV1PR0etoD47gzyvyPMZRfGQqnqA05rsEWGMjRZVVUZVFUCF1vV689eEoSZJFP2+oixl\n7fJo3ZEu3d2/EYvCPmd30cL1Xahu03KWhHM31vU2/07gJsl29uJq5VzJrcLjkjPasIJZW701StUo\n1awP0LpGKYNShiAwG0EL7Xn5oQVfCXAavRXAhuHAHk5bBjAIdS2W/1I2rlT/Pr6K8AXxruV7Ht9+\nDadf4eCs3jbu264zpYTG2OsalApMgA4idJKg+33Y20OvVmgREhHqKMbcepXm9qs0N19heXSLcnyL\nqndry9xR6QClhqhqACbAiGBEkeeycYvO/n/23qtJkiTJ1vvMnIYHT1asu4fszgJ7Lx7wBPz/XwDB\nFazs7LDuLpo8OHFiZngw13CL6KyZ2Zmuubeq1kRcMitJZYSrmx0l56iu/FkSHuDyep8KGr62dWpr\nuQeSuQqZzeB/Ruq84TktAFyWBmN2WLvEuQWwBFbABj9oaA80dDQ7D77OpfhzfEfTlEBNFDXEsSWO\nFc7FOKexNjp0QvMRujpyjkOgDZMln9LW/1AAllrPduuNJBtP6qehJOS09rde+805mfgDMdR3DQae\nTzGZeOP2+4rRKOLtW8XNjeHmpmS53AAGkDveCy4L1MAO50qMqXHOYEyOMRnWZhijDmlFiXJFoxjW\nPMLUeJiG/Fo36FOEp7BVYKjbKwqfyRiPO9sLkKWpt/Ng4MGw14OqUhgTY4zDOU0UJWhtiGNLmlrS\n1JFlUBQpvV5KUaRMJhGTiWYy6VJfq1VH3hiPj1PN43EX+Ra5o0gbisiQRl2RujGadanZ7jTbnTqK\nfsP68pe+/pK95RK+RigDE4coiro9v1yeRB6lRrmYJMm8UV688H/s/ByV5+gsw+Z9VsVLVsULlr3n\nzOsJ8w9jFh/GqCSBJEYlCdkoIx1nZOOINFMkmU91h3yTMFUqIBJGReG/v7b1lK2lri8pXCnhWNs5\nVgLIZdllMsUZ8+C6A+bAAzBrLzm7DeDwgZQEUxmQth9roMKf4zuM2eNcyW7nz/m67tHr6YMSJwyM\nQvyBY4nSp7T1PxyAq8rfeIkyiuIYwCQqkpqqiLDXa68YGI/9vhsMuhRCv+8Pz9EI1mvFaKSZTh3j\nsSaODet1yXK5xhunwgNuHxjgjebBFzZY68HXWkfTDLFW4Vx68PLCHrMSiYtHBd3GlcjtL8kyvtR1\nStSRTSoHsJQQ5B5q7W05mcCzZ90BLACcZR3LUeqxVaWo65im0TiXEMc+ws0yR7/vDuliD7gR47Fm\nOFQMh4rBAO7v4eHB22ow+CkA93r+a/I3+z1LkRp6cUUW2cOO3RPhmojdRrFYHUsowgzIl7z+GnvL\n3pCP4XAEObBPnfSjw9EqEpvQS7KOVJXnUFXo0Qg1HNIUE9bNFdf1M95XF7y7S/11n6EjhYo0Ktb0\nRxGDsb/6A/889AedEy2OtkTscMwNCCOlr219zNZwnM4VAA4zlpIl3O+9jSVQ6QB4CyyAe+CuvTb4\niFeylw5/his811047yX+HF+36es91pbsduP2mUpbQpb6iaNw2qxDOB6nUfHPvf4hABx6EKGkKLwJ\n8v3w3yFp0Rh/U0Yjf0BPpx2RUSKiXg9WK3+Dq8p//v69I0kaPPCW+DSGoVMKJnhDilFzYI9zFUo1\nbUQFSeIOJaQsg6xtENDLoNdT5D1QSh1tUHnYvkQSzl+zwhRj6CmHer807ersWdY5U0p102lCslYc\nuyBVrHDOe8JaqwNoFkUXLY9G3nE7O/PPTFF0z4q8pqrqQD0U83tP2R20hUVm6UU1OXtSa0HHoCKM\nAqyiqtxBBnU6DOBrWB+ztwBwWBuXqDLLOi6AHIAhaGeJoYoNjTZY9riy6rz0Vm/idISdnGOmF+zy\ncx4ep7yenfHH3YQfV44frh0//uglTVo7lHKHjMdo1DAaead9NNJo7QLQVYe9LOlxAZKvxaYfW09x\neRSOSFliLCmOOAKjwEYwyDWDQjMYKPZ7dVC6SC3Wm9TRNBZjDNY2eEBuANPWfX0q2Tn7hFPr2p8t\n8ed5inMJzsVUVUpV9YAGY+S80D9RsIQAHJ45n9LWnxyAxcOQBzg85ITIIimIsGYgXqcQYKbTLjqR\neqCkr43p0hkPD/D2LXz/Pfz4o+LhIaIsY7yXFLUfoYuA+3QeVI7WE6LIX/1+wWSScnGheP7cEye/\n/RbGQ0sv81eaKqJEEyUaiwcB8ZQk2v8a1ymJQZZzx5puOXwlCpYsSUiQ2u99NLxYePsuFpb12rHf\ncwDgkFczHneHpWxyY3x5InQCJEMh3q7UqISQFTI7iwKK2JBWe/R+BZhDnlo5z85NE3fQGZ5O4vnS\n18fsLQ63SE7kvkh6r0s/dntfa3+/kwSKqGRYL5msFoyqe3rzd0SL976bVWtkk+Ss3JBVOeG+OuN3\n7wv+/U3M794a7u8Nd3eG1cqiVH24/N5ULBbQ62XtlRPH0cEZEGc71JRCd1D/JenKl7pCO4uDkmUQ\na8e0V3Ie77igxCmwWuG0Ij7PGOQ5l1c5d/dwd+evxaIrA223ObvdGfu9w5gBSj1HqSXOVRgT0zQR\nTaOoa0tdG5rG4iEsCj7KJWe7nO8G2LTZzAxjUspSHQD2VLkidf5TSdVnl4IONZRhylg2GPy0w1UY\nHYcAPBp1AHw6gFvqbdfX8OYN/OlPAsCa/T6hk+dL7aDAG6dAwBd6RNGEJPFXv58wHidcXChevIDv\nvoN/+pVjWFhiZYjxhQ+jYoz2TE3xlqFLtX+t6/RQPnWyyvIY5CRDEgKwgOJy6VPG9/eO+dyyXts2\n1a+JIq/tPT+HX/zCk/FOpU7ipMnzlaYdAIdgsN93bGip86cJ9AtHj4Z4t0NvVmDNAUmUToi0JW0B\nX2r+Xwv4ynrK3uJwSUQr90M4IGGaVzIjcu+TBApdMqwemJYfGG4+EN/fED1eQ1P5esVkQhPnLN2A\nm/2UN9UZv3sf8f/9Lubff2/Y7er28vVFpXbAns1G9OEQxwPieEgcJ2SZbkFXURRd2UMCgtA5CzWw\nXysIh6TFXmqZFnvOkiUXyjc8cfhrcDbk8kqxjTJu7xU3N3Bz48lXQsRaLjNWqzNWqx5Nc4nWFUpV\nOGeoKk1VqbZ2bLDW0DRS25Obb9vL0Z3pefC9TVteVDRNcuiYJ+dM+N7CrMentPUnAeBTxljIGg69\nyfDgCyMTAWDZhFIwFwAW4pMw1aRmtF7D3Z3j/Xt4/RrevYPlMoyAE4Q5d0zC6qGUv7JsTFGM6PWG\nnJ9rLi99yvvlc8s3LxzfvrL0s47KXVtN6RSli2icOxws0JGLugfky1sfA5hTj/EpuUrY4ETqfSEJ\nRq7NxjGfewB+fLQsFobttqGqFBATRT4CHo/h+XPPEXiqpZ3U9era/71QCgWd0xc+f75+5cjSthGE\nq2G/65T8WYZKGmIVkcUNvVRR7RWR9lrFLy1d+Z+xt9ha7nlZHhOvQma0ZLSaBkxl0MbS04aBXTLc\n3TLa/Uh/8b4r3IPfYJMJJs5YmT63zYjXqzHf3xj+8IPl9783+LSklJ/W7bVpX7WQeSSSKsgyzWDg\nmzeMx13ELs+opMzDZ/hLlCOF7+X089P3mWeOLIdB5pgmO6ZqzrR6OPLGJkNDM40xkx5nE8104Jj2\n4WECjzPF40Qxn0fMF0PmixFV3Z3x1kK58012dlvLOjOsE8N215JqlQVMK0Gssa7B2qRNQSetRLHE\nuT3OaYzJMMYdzgMJ4sJMrTjhn9rWnzQCPtX6huQFeTOnNaNww0o6qtfren2KRyJetVKdNtR3SXIs\nl5bl0rJaNW1j/hBwu2hX/p2mPZKkR5r2ePlywIsXGS9eKF694nC9uDCMs4poW0LVdQ5QxCgdoxVE\nGrRyvqJsHFniOy495UV9aStMt57WAEP5hkS7Yst+v9NTC/gq5T3j21t/3dw4rq8NNzeW2axhu/Wi\nfKU0SmUo5T258NkJsypwTKYQoH2q/3DYHUfS4sYoysoRq4hYp0S9AtXUh4dPN5CXJaMmQpFAnGHS\nHGPTIxLPl7T+nL1PNb9wnBmCLk0v9V4hVY7HcNXf8Nw+8nIx47J5z2D5I9HyNWweuy48WXb4T41O\n2O01s43i7hGWS9U6Z9ApHPbBtWu/JwDcZcis7VFVCVqnpGnEYPBTedWp7OZ0ItTnvE6JZk9dEO4b\n57kSBfQTw9liRT6/gdWbIwBW52ui7Q5VlvRXcL6xRLVllMRcThLWRcr2KmVTJWzrhMZpVOS5Hbax\nNJuSelNSbWv2pWNfOqraQaRAK5xSrPcR651ms8/YbmN2u4jdLmazUWy3is3GE2qNiY5kpeJLh2fV\nP8rWn+yxOS3Qh8Xu8PvhBg4JVxINK9URYrKsaxsWSnuEJb1cwnLpWC4Ny6VhvW5oGi9V8WA7AIb4\n1LMHYaVykqRHUfTo93t8913Kv/5rwr/+q09lnp352uIwaRjqHfFuCyroIBGBVoYocqgIIuWItMMZ\nyFJIE3Uw7peaknzKjqEt5TAOAVgE+1JSkDSxDOB4fPQpqnfv4PbWcndnuL1t2GwqyrLCmBKtY0Cj\nlBflngJwuKFCMsVpUwWpA4dpJ4nIlAJjPeM6iTToFJ0X0LQt2KoKbSvyRhMZRexiTDSkyiIq0gPA\nfEnrr7V36ADJvQ1/Xur7u11HpDw7g6tiw3P7gZeL75lu3pI/vCN+eAfl9li31P6nVidsy4j5QnF/\n7x1x3w9c4Wt/FR3wygW+FBUCcIK1jqoqcC4hy46Z7OH7PI2Awl4Gn/M6JZyFmnj5XEpFEkQNB14j\n39eG3nZFvryBH384uklqu0NXFcoair0j2tQUdUOVZNRFnyrpUyc96rigjsFGCUSgtMbVBrvcY5dr\nzHaPsYrGgkFebIRRMXeLmNtFwt08ZjZTzGaa2Uzz8KC4v9fsdhprE4yJD7pueZzCrNc/0tZ/FwD/\nOTAJN2kIwOJBhZsXjt9wGAGHDbWjyDNgFcdEl91OHVLQq5VEwDWbjYQeEgEPgQkwRohXWvsIuN/v\nMZnkfPcd/B//Hf7v/8sxGnnvruhDtGvQ6xK9XncskjhGJRoVWbRy6AjiCBLtcMaRppo0da0Y/Pj9\nfm7rr7F1CGxPgS/4ZyHLuog0BGABzd0OHh8dt7fw/r0H4IeHhoeHiqoq8enEEq19pCINN+D4NZxm\nYE6/f5qVkMNHDhopHxgD+xLiJELplDgv0I1CtegaNQ2Rc+TOkeqYMorZpj22qqtzfm7r77V3+Dl0\n91acolMuADiKnuPiDK70imf7dzyf/ZbB7LUndtze4oyBwQA1HPqRg23KwkYpuzpmvtI8Pvpz4OkI\nWFQQ+/Z7AsAxXksaY21EXccYk7Pfu4CPoo7ec6jcOI3uP+clhMg8P5aJnWaF5F6IMmU8hL6yqDcb\nWN17JmywlLX+niURhTEUZQmmgkzE/xUMG39Ej2JcqkE7nAaqGmZb1GyO2myOu/e0tc1Gp7y+j3h9\nF/HmPufDteL6WnF949UpZalZLiN8N8QYa70BpcwUAvDp8/0pbf2z/Ff/magufHNhClo2o0QMQtoQ\nAB6NvPQnjR1JbIMCvz4i0jhnETG233DCiEvw4DtBqSFpmpKmCVmWcnaWcnYWcX4Oz8Yl07hkUFb0\ndorUKbTV6KZC2ab7Q63rpLSXKngSnp/OgfZpEf89dag3fgk1olNbn2Yynrqg85zDxufinEnkGl6+\nO47j/h4WC8N+X2HtDpGQKdUnTRMGg4zxOOLqytfqnz2Dq6vj/0ucudMUUwgaktAQdvST86oLT41N\nU0ecRbi08jXgMMdsItymj9smuOrzz3j8LfY+5YCEDRkEhKX2Jnv7u6s9vz7b8b+NdnyzfsN08QPR\n9R/g8T1usfBMnSQ5ylW7s3Pc5XNM8Qy3HOMSaU/ma4IeeBvoJgTTMWbDNyY/72uI0GBtjbUaYxTW\n6icdujBN+znvbSm9SI1bukWFEfDpew33blXCWisap0lVn3R8QfLNN8fEj+fP/cY8P/ebTPpRSvi5\nXnfpMYms9i0QrFYoz8CE1fIYJdvwXEUpfTPh0kzRZkqSDkimA+J4QJr6/u/TKdS1xhiNtepo/0t7\nYcnShtentPXfDcAfS6v+JbLGU/Wj00kZkrqTXs9F5sgTQ54YjFNUJqZqo5OulaVrN5EAsKZjO/vo\nV6khWRbR70cMhzGXlxGXlxFXl3A1qThLVgyrFdlOE9mYyES+WuQsRHFbOlIHANZaoSKHi723pbwo\nDh3ozML0++e6nrL1aSpSPj89jGWTw3F6GI5r+kK8ms89AD88ONbrhrIsWwBWLWEuJ0lSBoOEszN9\nBMDPnh23QQwnaYWv+XQWqTx/oQ79CEycJo1TTKpxaYJqsvaNBAjeRECKq5Kj+/A5rr/V3qe/d2p7\nOdRF1qMUfHdV8uuzOf8ymnG+ecNg8QPxj3/EPd7i9nvcfg/DIRpa1B5jp+fYy2eY4hn2tgdpBgc9\nf4MH4JaoA9D2gffOuHzdtr8jhK0QhKXRv8I35OkO5FC3/LkDcAi8Ar5ht8GnpIQhy12k2aWL6Ks+\nanRO8urV8cPw7JnXCF5cdMAb1iJkZmhRdJtyPkfN5p50d3MDtzfeMw8lEu0LVFFCf/wcNXpOf/SC\nOH1GPH1ONOozGCrOziKePfN14N1OH2SrgjPhlLNT8P2Utv67U9B/ywFzCr6SfgwjYDk0nfMPx2gE\no8LRTw39rKFqNJtKsyk1m606sI+dszhX4dweHwkLACf41PMErfukqe+INJ0qLi9b9uxzuBqXTOMV\nw/KByEXQJFD53ItKEpwo8dultEKHMjTAoUCD0h6Epbn/57xJP2brjx3Ap+AjdaWw0YI0KBEHzDOe\nZdiC4/ERHh4c+70wWbcolaJUH60LkiQ79AGXyPfZM29L8Wzr2v+f4nCHK5zWslp1QBySL8L3mySa\n/lBjsgQKB6YFXylJaA2NxlUKt1KfLfDC32fv8PckApaPodMjTfHTFL4937cA/IHiwxuY/wA//hH3\n8HCASJUkPm5tRyW5swvs5XNM7zl2BC6FYwCu2o8CwGEELEtAWADYg69zdQvAXQQsK4yKvgTHWjIR\ng8Fxn4YwCyRZytO0rLXtee1AG+0zU+MLyE7yuRcXHQAvl8Ev7juJgtZe89U+IGo28zWoDx9w79/7\nz+/vj0fitf+/iiL6v/wl/V/+EtfbEPcgygdEvWdMd0LC0iwWHsPn867X92bT6b5PyWef2tafpHIR\nvuDDLM/suH4gRpQ3JGPmViv/M5OJfxieT0vO4pLBviJXjtg6lANcgmsUzkVHGkLRAzvn6Oo7MUql\nJElGkkRkmabf5zAXVtpb/vpXjme5YZDVqHKPcpE/YIOuIEoKAO0Jb6sGE1mslrNY4fB16dDDCiO+\nL2mFWaY/FxmFnaHClHAoKwvrr2mqKArHaKTIsqSNeh29XsJwmDMc+ozFq288S/35c8fFhUw36fp2\nh8+F2CGsNQsJKJwzLF25pP+0tKM8P1fc3Xlm9nDgiLUmVqC1Q0eetdlYxXyuWC47J+NLYkH/tfZ+\n6t9SgpCa/3RkmIwsk7HlF/Uj56sfiO//A/v9H2jubmk8k+rQgFAnCW4yQb18SXnxiodqysOPGe9q\nxX/8B/z4I1xfOxYLX/PrJIcZHchWeJAOL1kK3yUpQqmYJIlJEn1QMoTkvFOm8OcMwlLXPI0CT20c\npmy7q6uNa6fJVEFeTElzjTUOYxzWOBo1otkOMfcpqemTx5b8LIaqwtU1tmpweYFNJzjTQ7uGOBsS\nTc+JjPFlHnF0Hx/BGJ8VqSpc1dZ6lkvUaoXarOnxyFk0gCxj3yso+z32z3rcP2p6+U9B9lDLbqfq\nCWZ9alt/MgAOh2nLfMiw/vfnADjPPQDnOZwlJWfJisF+Seo0sY1RxP4gsDHOugMAhy3uPNhpZANq\nnZNlGUURt16eOrymAwD/E5yXlkFVo6o92Kh70sLpEfIGmgZrFY221MphmvZhdMc61i8ZgOHjZYXQ\n1iG7PZyvKs9EOIJQ0pNei6mo67T1RBOmU82LFykvXmhevoRXL+HlS8d47FtT6ui43aW0QBSgFae7\nLS0dprJImXGx6EpR0rlNWp5Opx58Ly9hPFKkqSZLFEni/N+Ovaxlv+/KVyER6UtZf8neT30uSyLe\nJIEXV5aXVw2vrmrO3jww/eMPxH/4H5h3P1Le37Ov68MOTgGdpv5gePmS8uIbbjZT/vh9xh/ufeOd\nH37wfK31WlOWEukmdGlmyYjBTwHYg69SEVpHRFFMHEctkVIdEZKeqol+qQB8undPpWZhVKzR5HmP\nXX5GmhbUtaOuoK4de3LKbcZ+mzHMNZNeTDQsUMbQ1BZTWUyUYNMe1vaIXEPeG5NpiGLdvVBJXbfd\neVxd47ZbXF2jlktYr1HrNb1oxjTNyIyi6Z/TjM5oxhmDoSbSULfESHmfSeL399mZ3/MHkcsT4PtZ\nALB0vpLG9uJNhMaT8F6yEcJkLgp/M66uYLAvGeyWDHb3KJugyEH1QEU4Ul+9MV2ru3B+ZycxyNG6\nR5alDAYRw6E6eOIhAP/TryG7N+T3NWpVQqO7J0wKVqKlaIuIDkWjLCVQR92hEzael45Pn3NK8s+t\nU0/5VEsn9pFsk3wN/G0VAA6jYN8X2mcnmiYhimK0hpcv4Te/UfzmN74z2csXvnSQZTBfOBbLLvo8\n7T8cprg3Gw+4cklaajbzr0scgbBz23TaZdF8W1RFUShy8ZTj47Tdl7r+kr1PPz+NgIvCXy+eW/75\nu5rffFeSLh/Qy+/R//Y/qO5uqXY7tlXl5/zS0qbS1Bvh1Sv2F6+4fhzx2+8z/u1PXq7mJWuqlR5K\nvVeIWQrPC4l4OgL2zlMIwD4C7poIPRUBfwkp6KcAGI7ijCNt/eloya5pjSLPC/Jej3TkKMUR3cO6\n1eFutorz85RoWNA/cwcGcl1BY6AxCmMVCQ0qdyT9BIq0Q0Pwm7ndqK6usdstbrtFr1Y+Al5vyNNH\nshwmTQ09i7tK4dWErHA0jWKz7foBWOvfu+zvPO/enwTd/0umoD/2YsLG+pJiFBYsHMuNfKOMbrZr\nHFmyZkux3jCKtuSrO9LVHXp1h5pOPCr3+xgVU1WabQXzueXuzvH2reXDh4bFwrPdCGZGKpW0830V\ng4E61DlGQ8s02zGqdhSPO+L5LdFqDtsNThiXoxFuMMLlBU6nGGtprKMxngi2Nwllpanp0jHiUEgU\nBJ83AH/M1qeMwdCpgm4ThxNQTvtAy7MiTpkPdHxdfzyWg9v/+9ml4RffNPziueHZVDEdaHp5hGoH\nM1RlN3M0nDvq+806VivDatW0OnHDZuM/rteW7dZRVQ6IMCaiaWTgd4y1CUnSjTLL807fbVpOj6MD\nmlD69Dmuv8fe8nko25DzU4YgDIcwZkn/8Y6suoMf/0B9e41ZLih3O+q2XqGTBJ3n6F6PavKcjbtg\n/TjlbTnk928y/vSj4s0by+MjbDaqfYYUcRwFchFfqvLMZj/pzBM0ZXydlyD5CBh0q16IIvWTJhRf\nSto5XHIOe/lWBzayb0PO01NRcKcJbu9ZDE53e3CzOR5DmeWK5Rrywv/9p/5GrDT9OGUdQ2Yc2hp0\nGhONE9IXmlSnxIMB6uYGdX3tCVvDYdupyaBN49uVNnuod/6j2ZNYR0SEVvGhxCTSyMnEP5dp6u8H\nHCskPsX6uyPgp16YsOpEXB+2FIND8PiThvvOQZo48mpFb35Dsb4hmd8Rz+9gdg/ffevvWJJgbMq+\niVhvFbOZ75T0+rXh3buG5dJRVaHGL0Epn1LKc9UOV28n5YwdZ+ma/uaB5N090XqJXi9hs23fQIG7\nuMTmBTbJsDqldI69jdg1KWWtqUgpnaYJPH8ZxNBF4x+/X5/Leuq1yyEbMkTlc+icLQFgIUNtt/5r\nEhHJdDkB4OnUXxBMoMpgOrQ8m9RcjkvGfUUvS4m0ojaxL0Psu00vTd4fH73DPJs5FouaxWLPYlFS\nVSVlWVGWJVVlKUuLl7ElWJvinC9dVFWB1hFlqY/0gvDTWtKXtP5We0vkK+ArV5J4O8vs7uF2Tvbh\nB9j+nub3v2d/fc1+u8XUNcYYlHNEaUo0maDPztidveS6ueTdhzF/UgX/8UPED68VHz4YtlvdHpqK\nKNJtlKrw03MinEuoa0vTKKxN6Bpy7OmmoumDiuEUeE8ZsV+SvYUPIRkKyUSJMuGp8YxPaelDp8za\nboDKYnH897Zb/z3pECjZqjDK1mjyJCZPFBmKuNEkUY98NGAQFwwnE+LnF6jXr9FFgbu+Rk2nqDw/\njvDE25eUZKWgScFFxLFquUCd0mYw6IYvSIT8vzQAw09fnJCvJAI+bXggDNPdrqvPyf+RJY68WlJs\n3tMv/4i+v0M93MP9HSSxz0EmCaZJKRvfZmw2s1xfG378seb9+wZrXZuCCklYMUmiDgAs+f7LqeUs\nWTPY3JC+e40qSy9sqypwl7iigItLXJxhrMZYxd7ByqasjGNfKapGUdeKxvw0ug8jvS9hw56+h6cO\nYzmgJBoKpw9tNtKxzNteZu6enXWet7SqlNqrpCyLAvqJZRRVDKMdaaYgVaAS9iudNdQAACAASURB\nVMbr9cM0sxCrRMVwdwfzec1stmc+X2PtFuf85fvIGpwzQIYxBVCg1Kgl5eQHUlVYz//SDuPT9bfY\nO4yAg14JB83vdOqZ66PvZ2Qfvkd9///QvPmR/fU167aeFznnhQVZRjSdEr18STl9xY255LfXY367\nKfjD95Y/vXbc3Pg/6FzU/k1FmkbtqEuH7wfsUErhXExd5/h+0Akc5szG7cevC3zBP88SLIQOk5xh\nMmLzlL9xWu8P740x3vH1Soau9p9l3axnrY/JkPI3JIuRJr4MkCUpWVKQpZbBsITphDx6Rq98Dv0+\nKopQWndko9PcuYTfux2UERjPLBCeUsgCHwz8PZGg4VP3b/gkKWj5esikE2OFDsl26w9J6QU7HMKo\n55h8WNJ7fEf04T9QUqRbLLAvX+F2FdZFbMqYx7nm/Xu4u/PaLq01g0FCmjqSxOtzIcO5iF5P8+IF\nvHypeH5lOe/vOR/suci3XLlbBrs79PbhyK1zznotURLTkFC2D+RqBYvWu9vvj73C0/cqUd3nvj72\nHkK5Sfi1MPINhyGcRpBhmrJfWPo9R7+wDHJDv2cY9Ay9uCHTDXldk7uGXtyQuwbrErZNwnZjmW0V\nHz54Ek6oVAglSL4eHFFVMU2TtaBb4WeNGjjMFG1Fq+3hrLX6SfoxJGSEh3QYBXzO62+xd9hQJZSr\ndEDs6GcNo7ThLG0YVI8kj9fY168xtzfUqxWVMURxTJLnpHmOunjB9uqf2Vz9mvfZv/B694I/Lvr8\nMI+4f1DsdhalHHmu2khGHYGIdLByzlFVSfsM6jYSjjAmaTW+XvMbxz3SNCFN9ZOEq1NQ/hLsHUru\nBLdCAJZ9e8pjOSVZgt9r4H9HwPfh4XgIT9j3QXpybDadasBLNtWB/Oadt4gsg2EvYtezlEXEloio\nXxNdRUSMSdK2936qujFWwyHNYIKJ+zRNymoXs1j6jmm16V5TSLgSQBZylrzeMMr/udYnIWGFkU+Y\nqginomy3XZqwqnz4P5nAywvH4M4DML/9bcei2e9xixXNrsaYiNUu4vZe88Nrxe0tNE3EaAS9nmY4\njBgMUtJUtd5vTJ7Dixd+rOCzc8O5WnHGI2c8Mtlf09/fwX5+vNsO7p0nCIRyFSHtSOo8JJqE0UCY\nnvsaVrgpxdZCRAslOaeRUZ7DdGy5mBoup4ZclWSUpG5P0uxItlviauOZqL0E1UuodJ9Z3eOudtyu\nOIw4m8+7QyFMofkG7DFa90gS32BBrq5FoU9Bd61Ks5aQoz56IJ8exl/TCh3OsKmJfE2ccO39WHpR\nzSjach7tyKoHksUt9voDZj7DbLc01qL7feKzM7KzM+rLX7F69t9YXP43vm9+wZ/mz/j+Q4+3D7TN\n9TVF4RiPNeOxOkQwoVxKPvoOSDHGKKpKU5YJZdlrzylN02i0TkiSlCT5OAB/afYO6/YhCItNT7M9\noYMdnu/G+ONaPkoEPJt1apg8784FcZIlIyYqBWmGI+Td8IwYFIrVMGM1gmmuybUiOx+R979hkFYM\n0pIkqbpwdjCgSUfs0hH7ps/jNuVuHnNzqzDWZ2TgePyolMWSpAsWw74FP+f6pAAshjyNiCStIWlC\naWgymcCrl5b435bEsxaAAwvb5Rqzr6ltxHoXcXuveP3aMx/rWjMcarIs5uLCcX7uDe6F9H5e7PPn\nvknDs6nlbLvmbHPLZPuO2DwS7x5guehQIU29nqjdwZIqWS6lnugfLnlYTgXbQsD5UjbpX7NO2bHh\nRhMplgCwpKBkg2WZB+BXVw3fvqhJqi16u0HvNqjdArWcoxZzVBKhxyOUHVERMVvVvFtZ3s29ROju\nzj9TYgdhpMsGci5B64gkydqUpGpfk4JD32AB4B5KdQAcskTDrjhfSiT0n11P6UQlggnTkl092FHE\nlQdgvcBVD7jFHfbmmma7pTGGxlqSPCc6OyN/9Yr66p9ZXvx33p3/n3y/eM4P+5Tvb1Le39BmJjyh\ncjr1TVgmk2PWbhexKXwLU59u3m5TtltPvPPPhmqHvyjiWBPH+quxdxhAnDbZeIrvAF1ZDbroWBxs\nITDJOTmfe/AsS38mlydESfm5zaZLRyvVAXZ4Dfqa1VnKap8wH/cYZCP65y8ZpBU2XZEkSwbJytew\n2qtucnZ1zqrKmW009zPF9Y06vM807UqlSh1LIWUinzgjP/f6ZAAc0tUlEvxJPbzN+dvGondbsuWO\n4mGOe/iAe7ynmc+9Ok8pP1F3t0WtlqjZI3mpmWQpz85T8lT5JhjWkfdgMtVMzhS93H/NOUcaG87H\nhvNJw1m2YbS5Y7R7z3D2xp/YrYaMweBQsHBRjFW+b2hddw+NMGtPWYNCXhDqujygnzMb9q9Zp+nI\nMPUcSoDCmrg86EXhD82rKzgfVEyiNcNyQ1xuYL/1s3f3SyhXUG1wOscphYkzSpOz2ic8zDT3Dz4z\nIaksqe1IG0Qvi/NSE1/rc5RlijENXfqZ9vtFe+VonRLHMVmmjjo3hW36wizHl3Ag/6X1lL1Pu9iF\nYCWkzKLnyN2WfPNAam9oZnfUqznNboera+Ioopem5IMB6cUF8TffUA5fcaee8cfFBX+8n3Czgo0Q\nNtOOQyDd7M7PjyOzo9KB6q7dDnZbzW7r2JeKfaXZl4q6UQcAF96BSCi/dHufZg3C+q6kaOV8O9Xa\nh0623D+JbBcLnw2Wc1H+76qC5dJyf++v9doFEbAjy2x7KdI0Jk1jBoOIfRlRG6hdTDXJcAUkQ0ud\npdg8gSzFicyl16NeJ2x3CfN1zHKj2Oy6wCnsuijvQyRZ4oDJGf8pbP3JU9CSjnLu+FCW2qlSEKuG\naPGI/vEaHt5hfvwRM3ukqWvfbai99H5HNH9AXb/mPKn558sx/f6YXR3jjMNZR5Qo8iIiKyKSFJSz\naGdJVU1fbenrHf1yTr78QHL7Hm7eHSOEnNxFgc1yjIoxQSr1VFcq9RJ5aMXjDx/cr2GFnvGpoyWe\nrciyJHKQ3vqXl17TO212FOUj6v0d1GVXfJKdrTU2zTG9AWY4Zb+fsnE9ltvowCUQTbFMdNHaO8Ki\nPz5uNKBpmoSyzNp3ESOpZxlZqXXadk9Th0j9Kb3k12Rr+Km9w/1RlseTc5LEn4WDvqNXrYkfb6D8\nHntzQ7NeU1mLiiLyNCVLEtLJhPzyEv3NN2ztcz7cjvjtTcwf7n3WSQUlvsHAE/ikB/jl5bFDLLZK\nU0eEJVKWCENdOarSUpeOXRWxqWK2ZcRypQ7acKVoy1pft73F8ZB9JcGVZDBDEJN9LpfwL8RhGgy6\nKNkDsGE2q7m7q9lu7QHAwRDHDUlSE8eaKCqI44J+Pzo48GJfKTtI2Or67pBWc0lKZWPWO81s7l+z\nRLXQ1bmlB4XMJhdOl5xTnyqI+qQRsPQ/PgVgMdahHoghWsxQ6x9Q7rfY1z9SPz5SNg1ZFPm0EKDL\nHWrxgLt+w/lzRf8Cvpn2MJECa3DG4pTGRWAjPyghUZZYNcRNSbxeE28WRJs7ouU1+u6dH5sVCtsm\nE2/Zfh+X5hiVUDfqiDgWlKWPivOSqhDP+3PW/f616zQNF6aeT++XZD3CvtACwN9+C/ntlvz2AX3z\n1vdZhuP6hda4NMP0htTDM0o1ZuuiAwBL6jOsLyfJcToy9GSbJqIsY5TKWiJWho98U7oasJcrZJk6\nqkk9dSB/Desv2VsiIejutaT4hn1Hvt0QP97C7ffY21sPwM4RtwCc9npE4zHR5SX61Su2i2d8+NOI\n3/4x5oe7bp9JZ7LJxDdGef686wceBD+H2mOvBzGOGENMgzMW2xhsY9lWCatKsS4jrm99Q483b/yz\nKr/7Ndo7tLVEv+FQDWlmE06vk45y0gxHriTpouAwQ7FcWmazioeHPdutCe5tg1J7lNqjddzaPaUo\nsoMzIMzluvYvVsWt193XkKS+b3+SUDnNpu3dIeeEnM/CE9luj8cvFsUxI/yzBOCwmC8paLmsdV2z\nDizj+ZL88T3M/oS7ucGu1xhrMUphjMEohdpuUI/36Pdv6EXQi2sYGUh7kHg3zeiEOsqooxxQJLYk\ntiVxvYbtnZczXV/DzVu4v/VPi7h4cnL7xr+Y/ohSZex36qihg3RSEs8OjtMzX/MSmwvr+fSq6+OH\nPGz+nsSWyLRaIq0OuWOL7urKxZQqHVGqPntybARxm2KGY6ambGZpDCN1nu41aqoqbmtXMX6Qh0O0\n487FB03paRvCcGrK17xO24uG6cqwG57X3jt6dzuS1Qw+vMc9PuJ2O6xzKK2J45g8TdGiYRwOoe5D\n5sMSiaTl4J1M/HV+7nh+5Xhx5bi6sBRRSS+qKKKKXBl6xpBXhjhyRNoRa4fSBiIDGLYqZRPnbLIe\nPZMRVSmYlPUuOkRDYvev1d6hH3yq7JGzUEi1cj5KKvpUEWSMpaocZel4fCxZLjdsNivKssGXgMCr\nEYQYmeD3ZI7Xc2uU0r4VbDvFqeg50sRnN2garIp9f34d0RgvEZWMa5b5R8uYrhVuKK36R65PnoIW\nUfapRCGOWy3uFM5Sw+XvNwxuH+HDB9RshtrtfKXOOay11E1DtF6j7+6IxD0VkedweNiZqlcQ5X3I\n+qAU0X6N3m1g0U7WePcOPnzwvyejrSSvKE2oLy/h1Svq9Iyd6rNc6aNewYtF96DJBvWaQ//+vySC\nxn9mhXYPRfWngv049ufraNTJ9nY7cMJCzXPIs0Oe0biYqlZUtaJM+pR6TLWND571dOr/jpTypftY\nqC0UwpccAj5F7aUoWiuaxjeObxqHb96gca5jPp9Kj+DYzl+breGn7GeJdpOk03FL1yv52Isq4v0a\nHh9R6zW6qoic8zwP8WKDgmuvB1eXvk3s4LLbqtKjezCAs6nj+ZXlxZXh2bgkWT+SLh9INzMSsyex\nJYnZo7MEnSWQJT7D0iJDrHPyuEDFfc6aMWV2hn0+ZVlGhwjuVOf6tdlbGmaE89plbwvjeT7v9nme\ndwAnrfQlat7vbduBrmG12rBezzFmhu9KJjfW4AmRNT4b5TNSURTR7ydcXPh+8M+e+QzIdAJ9V5KW\na9ivMPmIuqeo84ymUQfgHQy6Z1VaBBtz7KTnedcJ7JSI9nOvTwLA0L1w+TxkyVnr3+B0Ct9953g1\ntD79WD54cGwFtgpw1mKcw1mL22yI7++JksSjn3RYEFd4MkGNxkTDEj30KUy1XKAWc7i79d3av//e\nA7GEZDIXTU6NAICbsmC7yQ51oTC9IgAc1kVC7+lr3KSn5LvTpu1ieyFfjced47LbgW4iEp3gsgw1\nHvuddXGBsSnlXrPdK/ZNwt6llLvkAMBnZ939Pu3aA93BmWX+ex4kFHnuNb5Jotvo3LXPqGrZ88e9\nf09t+l8AfFy9EUdU6u6i7RcAHg0cuS6JyzU8zlDrNaos/aQjrX0zhVD3A+Q9uLyCXxuY7LpMRDjo\nZTyCF1eGl5c1V/0denOHXvyIfv8WvV2jNyv0do3q91GDPvSLLpRrGqKsR94fkhZDbPEc29PE0yGz\nuusVLkScrxmAZQ+LqkD+LQB8f38sNwrBK467n10uLfN5w2xWsd9vqOsFxtzh24PKjXVwGBUZAnBM\nv19wfh7x4kXC1VULwFNHtqpIVitYP2L6mspk7N2xczgYdGdBWKs+EAWLrnujnOmnY0l/zvVJADiU\nHIkUJCjjeVZh5Jj0Ki57Nc/SObg5bGe42exQLBQT4DyTWe/3uNXKH9DSJ00Ki21opZIElYqXa+Dx\n3utT3r/388pev/YpaAltJPIdDnHTKWY0xRRTmnTCukxZlZrFSh20vw8PHnxDzlYIvqeH8pe+UU/T\nvWFEFIIwHIvcJYKJIm/G+RzqTUJVFZR2Am6Cs2c4e862SVmVitVGs9urI5CVenuWdXWdEICF/CHM\nZehSpL5pgydXiT2VOnYWQhnK6QH8tdkaPm5vkXAIQB5qr7mjyCxFYiiiPanZEm+WMJ9hNxtsVdE4\nR9Tu8dNcYJp6gH1mIA/KF2li6WWWPLWMexWX8ZppuWZcz+D+B7j+Ht6+PtBw3XIJgwFuMMD1+yjn\nUO3BFPV6RG04PbhosFmPqH9GZBNMFbHbaozRP4mAv3R7H2uoO+c2HKoCnURTmnDIsSoMdH+vLGXp\ns0yLRc18XjGflxhT4SPfGh/1arxcTKGURmtHHHsiZJLA1ZXj+TPLi+c+43ExapgkDX1TE9ktkfUv\nrKksu41jbbouX1I7lqxbyFU6HboRniOfcqToJwNgIcSckpEOmq6oYeSWpA8zuG1bGC2XUFXYpsFY\nSw0y4x7w6Wj3lDpcLC6ulzTzLEuPmm/feuC9ufFhrIROLfBydubZG5dX7IszNk2fzX3EfK2Yt+nm\n+dx7eDc3nc4Nnj6EQ73c17BCBytM20i6V1LAvV5XYpeZm8Z4s19fQ7rPSXZT0l2EqQvMqk9zG7He\nKRZLxWLpp6sIuEZRVz+W8YIie5A0mbXdzwjQBv7a0UEhPAXoSien4Ht6AH9ttoan7S1Rjsi+ukDW\nkdiStNyTbZfE6xlq5QGx3u3Y1TVr57BNQ7zfkyvVzRTFa33jRJFm0Iu7Q7KXWkZpySjbM2bJ+OE9\n+Zv3sHzvxeB3d37DBjMn7WqFSRJMmhIlCTpJfDZNWvJlGVGt6OVDODun1pqVykl0ThTpI2nV17LC\n8qG0kz1SsJwQlUR371xXLkhTaBpDWTbUdcN2W7HfVzhX4iPdHGgbv5MCKVrrw+/2+wnTaZ/pdMA3\nr3r87/8S88tv4PlZyZA1veWKaLlB67aMMT2jrAesypSHNWx2HQlUzgXRLkvWRl6rDA6R+QTy8bMD\nYCHchMJ1IVH0ejCMDaP9gvT+Pcx/8CfwYuEj3xaAG47VmQcPOQyrQqGh0FSFrliWPjfy5o1PPUsO\nWXpf5rnPg56fewrlixfs++csqoKHu4jVVrNa/xSAm6bz8P9cRPQ1rDASCsE31APWded4FcUxAFvr\n76+1QN1D1RGqHlAtYioSKhezXHkJgZTs5VDo973pLi78awgBWFJLTdPVCoviODKWx0YIXLLZoLPh\nnxvA/rXZGj5ubyFfSUnmcM+0I7YlabUi385gM0et5tjFgrpp2BnDCsAYsrL0DvZud6gfqMgDcJYp\njAsaMmSWi3TPebZmtL8je/gD6Z/+Hd58/7QOZrvF4qk9DeD6feLBgGg4PKovxGh6Z2ck9TOqLKMH\nJDr9SSesr2GdZjkEgMWxFXuHY0RD7gV0AFyWhs2mYrUqqeuKpqmxtqIDYE989CqEHlrHpKkf93l2\npvnuu5hvv0341S80//wrx6++c7w4q0jmc5LZHdFmjppOUC01vnzMWa5T7mbqqMVlSAgNyyYS+SZJ\nB8BPNRD6udcnA+CQUdY9uI40dowHjmlSMdyvSJcPR+B7sGp7ZxT4dASgZLxSWAASimVbdHIhfxz8\n/7le+2HNu10X1rQJfzcawfQMd3mFe/aSvTlj0RTcPWhWm479LJyt2axzKgSAP9Yj+GtZp92Qws/D\n+mA4ojLsmy7a0bpO28sTNXY7x37vWCyathbnqGu5sYrRSLHf+3ptFPk5wP68dQfGejjmrK5Dfag6\nOARF0aWcZCpMSM44vb5mW8OxvcM9Hsc/jSZi7YhtTVzviHdL7HaF3W2w2y0VnuO6ARJraeoaF+Y6\njSFSPs08GDhiLL3UkqeGUbpnmmw4S5aM9jPY3MLte5/tkhcJXTpuv8fWNU1VUVUVbjRC1zXO+SEN\n8oai4ZBoMyOtl/SSCanKibX5auu/obMVykjle6LJlYTiqUMmGRGAurat1MiitSXLHB50U3zqOUep\nAqUKsixhNPJ7/Pkz+MW3lt/8k+WfftHwzUXF817J1G2gmvnS5XJBnRZURUxthjzsYt9y8ua4N3l4\nQXcupenxFKSwBaXcg0+xPjkLOnzhyjkY1PSoGUZbcvbEpuxOul4PJhPiJCGLY1QcEymFVopIKaJ+\nn2gwQIn6/vzcX5eXPoI9P+8KizqCummp1udwEQjWnPNfH4+h6GNHY8z4AnP2nO1yxGrRY76Ex1kH\nutLi8LQuGHqAYbecr2WdRkNhuSFsSAKd4xJ2p5Lv1/VRtpDNxnvMm03dtgy0bDYO37fZD0moqhjn\nYsoyJk0jNptTjZ+XOiilDlmZ8VgduHahThQ6h0E8eNEsh9fXbGs4tjd0vqwQ60L9rf+6I1IG3fjZ\nu7ZpqNvy0p5uKGDhHI21PuMlwuLNhrS/Y1zU1BNHQ0NqtmRmR89uGFRrknrtDZamPhVibSfWjiJP\n6nz/Hq6vMZsNjXOUbRollr8jOeUww1bXKNOgnSE6qmX+T7jp/5NWaOvwCqNISVbkuT9+xTGD7lnw\ne0a3tVxFHKfkuSHPG6QdLCi0TtA6JYoiikIxmSjGY0+w+/WLkl+d7fkm23K2mZPvF6BWhxdliyGP\n+4Lb9xl3HxLuHjV3D5rbh84hkNgrzNIcOAVpx+iOoi7N/qk135+8EUcYEUVYVFPTU3uG0YaYnQdg\nKegVBUynxEWB6vdJigLVsiOV1uheDy1Rr8wTFCC+uPAfi8I3bFARNAY1bb+/Wh53ZJC8ZL+PHU5o\nJufU58/Z7VNWTcpsrg69hW9uPDhsNl3q5SnwDb3kr2n9NSAsSyIleeglNSSdde7v/bVcNqxWJev1\nlrJsaBpLXRuc04gucLtNKcuc9VqT59FRStg5LymqKtcCsWK3E5mB4vLyuGohbEeJkqWe9THw/Vpt\nDZ29Q401HGc3Dk0N4nbfmxpMiWkBuOQYgEvnMHDsBW02ZGbHeFyRnFmsbkhWG+L1jHS/8kM6zK5j\nQ15c+BcxHnvadZ7D737nDdXqjeu6ptxu0daS1jVuv+8Kf0od1U6UadBYosgdqlpf2zoFYUlFS4ZJ\nomFxukKn+9h5jdqBJjFFYRkOHaORCzoH+jnOnmylGQzU4Xh/cW751dWeX56veJk/ks+uyebXsFt4\nT3o8xvYnPM4L/jTL+MM89sTZpWK56hwC5/zrFIa+vDZ5XgWAhYh5GkB+ivXJe0GHQuxUO0xlUKYm\ndjUaz9KySYoa+OYXSmui0YhoNILRCKsjnI5wKsImGSbNsGmGG45xkwluPMX2J9hkgnNjMDkKjYo0\nUVwS96ck03Oizfq4ANi6Z24wpO6P2eVn7JJzFhYeWyC4vXWHEXdh7VHG053Wu8ID+WNe05d2YJ+C\nr6yQoBT2ZD69V2EnmtnMcXfnuL72TMnVas9yucFaYUg2dO0iM/Z7RVUlbLfuaGaw39QWa00rLVKA\npix9n980hdFIHQGw1H+lShGy+E+95q/V1nBsbyFZSkZIUvq93kltEIM2DZjqCIDl2tPyYFsQtlWF\naqe2J7slA7Wh6O9Aa6JqSbSZoc0SmsB7y/OODDCd+qvX67y6fh+729FEERU+5W0lAhahquQgxbtw\nDo3z/aNPWsw+tb40e/+5CLg1z8GpFf3s6e/LxySJSNPoqInKdNqpZPzPdPtxPHJcnDsuzi0vJiXf\nDde86j1y6W5h/R6u3+IWS99kI5+wG4y4WRf88CHj39/Gh+57AqiyZ8XUkvWSc1y+J+Thv7R+Llt/\nMh1wWCeSG1w3mvk24cMsx5kRPd1QXKTk/QnR8xXRdkm02xyFJrWJKdtr38TsTcKuiSm3BWXVp3zo\ns9MFO9VjS4zONEVfUQxg7GKuFkMui0vGL6ouv1nXh6fAjc9Yqgl3Dxm3O8/VErnw/b3Ufh3OqaPo\nRyK4sLdw+N5Pjfilbc5whWdWSPXv9/2t7vW6oGQ08t+vqk5jKRNTZrOa2axmsajZbjdU1Rbndnjg\ntXgQlhsZATFaH8/r9WeoRWupMDb4iNl3tjImoqo0EvjAcZvBMIUW1rD+y9bdCvc2dMHjaVlGSFhK\nOXAWZy3WWhrnDsKTGm+hCg/GO4D9nujxkfjtW4hidO1PRpWmqO0adhuoK39qCitLgFiu+3v/NeGX\nCJtGXrQgCXQaNmEMHZiCA6zJsHsdYvJP1pds76ci4PBjGBWHMrQkOQ7ApPmO1sekyKD8fhClDIdw\nPjY8n5Y8m5Y8yxaclddkm2vY3x74Qo1KuNsU3N2MuV2e8f1tn+vHlPX6mIMnhE/Rpcu/tfavcbv9\n68m0P7etP1kEfArA1kLVKBbbhA9zTe1ipnnK9HyMyp6T2ArlSiJXde9SKap9wrpMWO8TFmvNYqVZ\nriNWm5hVmfixVJuE2SrhcZ0QJYqLC8X5BXwzjvmX/oCif8W4bzyaCsuyrSPb82csd2PePeZ8/9ZL\nheXyHa8cq5VrWyeqI8/+qUP5z3nJX+JGDW39FABLNkSaMfR9g7IDmeP62qf4r69ht2vY7XZstzua\nZkvT7FoANni2pKMTpkUoFbVaQXVEjgKLUiVKbfDHeg/PtPSzf+vaMyNlEHdow1Ni0X/Z+nid7m2x\n+Wm240BYizy9RrW/5JzDOHcEvk37uQCwKkuy2Yzo3TvfpKNuUHUJRYGyFmUNxIEGTU57QQLx6mYz\nXwMW5UNL8nLgyV7QsYhEjyZyxuEQV/Rxu+zQCvXPRUZfor1PbX0KwvJ14V2EqgEpS4SdDyVKlh4A\nReF/Rv5fmYx2dgbPJoZX4x2vxmsu3AO9u/dk929geXf4hVpl3G0Kfr8f8UfOuFsk3C+Sw8Q6AWDZ\nu+Nx93fF5xInQSLh0/nPT62f09Y/GwCfPpyn4OscNEaz3GqMSti7nPrZEAYQXfi+0CZ12MQzclxb\nHFyvU2brhNk65d7C/Rbua8fj8pggdX2tuLnxN/qbb+DVK9h8GzH6ZY9vp2MYtFz07dZLHQZe62cu\nnrF4M+bdfcbv3jrevPGqpbdvaVm4Hij6/Q6Ew5Tkf+ZQhi9jo37M1iHzUeqqkmISrzfPu6YX263v\nkfL2rb/nxjQYU2Ltmq4P7J5OjEb7uSdiKeUj4ChSRwxlz2ytgS1tTIUH7hRrLXWtD5nHkHQPx6n0\nsNb/tdoa/vze/hjJ7qhxiXMegJ075DGak6vCW2oD6P0ePZuRaI1qGlRViuC0bAAAIABJREFUocod\najQ67nUp+cpe7xABO/AO9u2tf6jaHomuLHF17QEcfBMOeWCF2JEkuCzH9QpcMcD2+tg4xTp9IJ39\nOZt+Cfb+mK1PO9yFz4B8T7JIsv+lE51wbLtShSPPu4YXEmnmueraMkwNL4d7vh0ume4eoLqF+3e4\n+3tfOsx71HGP+12fP2xH/L/bUatRVux27kiJNp36Wd7jsQdf2cun0bucWeF9+NQg/LNHwGH9N2zC\nIAeX6K9ajgV3d34vxRHEsSLSYKoIUzlMpZivYxZrzXwFy5VhtWpYrRrWa8dm41ivHculZrWKqOuY\nNPVNugcDxTCvyLePRG9fQ37t/3CeQ39Ac3aJGZ6zSSbc7/q8uYn53e8cDw+Wx0fHbie1Q98tKUmO\nJ+J8LCKCj6cuvoQNGq5TW4u4XYArHJAgBIewNrNe++BktzslcCmk+bownrsOOTlRNEDrnDxPKIqI\nwUAdRod5dqajLC3G+KNeKYdum/1HUUQU6YCsdczaDwX6T40f/FptDT+1d8iLkK0V0iysBR0pTJxg\n0xzSASrLUHGMxhcVhA29wlvcAdu6ZrjZMFKK3FqS3Y5kNvO8EPHkplN/k8Xw0njj7g53fY29vsbd\n3mJXK9xqhV2vcfs9SV0zcI48y0jyHJXnPjXTtrKtJxeU8Zj9vs+jzVjtY8paH6R0X4u9T20d9oEO\nJ4vJHpFKgMgLw8Y2u90xsMexJUks/z97bx5r2Zbfd33W2uOZ71zjG/q9dlvdFnHbxsGKA/FAsAi2\ngxQJmWBiwA5Bgj+AEASRSAeJIVGkiDh/gOSM0EZAEAmQSCRyaDtRArZxRwR1P3e/fmO9elV1685n\n2GePiz/W/p29zql761W9V7du1b37Ky2de849Z5+99++s9V2/2fdLPE/Xw1tEH5cltrNdlkEyX6r8\nYeIu2WiHfH2bo+AaDz/a4eP7Hh9+PCHPPbLMDt9XhKGm01Gsr1sLnFi8JOZk+ZxOz9o4b1k/UwI+\nbTEryyZ4RRZIeX1vbyWfEgBFlmry1CdLPU7GmpOJ4mQC83lJmmZkWUqWlWRZRZZVpKnPfB6S5xFa\n+3XRbc0gyi0Bjz8A//5ikpn1DYr1bbLeJrNwnf3E56P7AW+/bfPUkqQiSUrs4u/heT5BoJZyHCXP\nsdG6PllwlwmnyVoCGESrhGUzz3TaRFDKEAK25Gs3PA0BW621SdKXNIWIIIiIY59u1262bLK/W520\nIWCtDbarkV9XNFJLO1t3F+8SsNuY+yrLGk6Xt1sPWILp3MwHrcEzijL0MVEHPKu16pqADQ0BUz/P\ngHmek0+nVHlOP0noHh7i3btnCXhz06pIed5kQ4D1Y3znO/D++1QHB1QHB5RHR5RZRpmmlLU2EBSF\n/SWFIf5ggHLqyLO2Rj7aYuKtcTzvcpBFTOaaNFcLawlcfnmfJmuXhGWei+VoNf3MzakVAnZ9xs3W\nqyCKNHEc0Olo4lgtflOmqiDLQSWQzhfFBKq4S7a2w+zaGxxFt3n4IODjscedOxPKMqAsQ6oqYG3N\nq2PxPNbW7J5NDCV1htvC/SSKwpMS8LPEuRKw7JBdE1+aNu2qxBTZdKVQlKVhPtf1WG4BWFUl1lM0\no6kdWmIX6S5g21RFkWIwsBpw5+EB/t6HGPMxfP7zcP06ZucaRX+beX+TiVrjYWK486Di7bcr55hF\nbTbRCw1YCFiqpqy2KHN3VJe9XN1pshZfiutDkUkou06pViUNLaREXJMq4BKw1XqtfGMgQikf3/cI\nQ00ca6emtFksFLOZ1YCrqkCp0iHgYCl/d1UDdqMgxezcytriNHnLYikmSbfoiZijc6BUAVUUQ9Sz\nGrDnLQi4wBKwzRK2Jui0KKikdQ72FxADZjCAGzfsUMqS5rVr9sTu34dvfQvzjW9gplPKyYRiNlvy\nM0c0nZ61NPzY3sasb9h2OuvrloD9EQfzLgcmYjKH1KmaJL/ty4yzZC2PUq5VzMqS2uOad7W2gat5\nbhYVpRoNuqIoCvI8pdfzGQ41o5HPYND8pkxZYfIcUyWYbA6lTeKt4oh0bYfJtTc5jF/nYTjh45Mx\nd+6MqX8lgKpTizSbmyxpwNJC4OjInn+v1ygL7rULzlvWz9wHvBLFv4gyE9OzaD6zWUO+Vqg2bzPP\nDVlWked2JElFUVQYU9FkDs6xuyiBTTMBTRQYNkcFr10r+NxGypaBOAuh6FMO1qiGW6S9bQ7yAfu7\nIfemsLtbMpnYqdoE9AQEgVcnkDeh9vJDk53eaY77y7YjXsVZsl71nYr2KAGnk8lyyrfnWfKUnbH1\n6cZobSeRUlauReFTFAF57lFVGtGSJW1TUg0mk4rptGI2K8gyTVnawCvPixcpEG7xNPFBuc0djFmO\nxbnqsoaz5S2upPl8OUdaLMOdDsQdRdAL0L0uVWeIibsY35ZGkq1Vh8azL/5hNypatmJxUeBPJgQP\nH1oTdllijo4ofZ/s3XfJ790jn82sv1dKWdYjAPw6vVGNRrZkYZ1oWq1vWZfU+jbTzk3G4SbHs5CJ\nEyh9VeT9uLnt+oGh2WTJPZH41tnMvvfwsGI8tgV08rykKAqKoqQsszq1MMfzQuLYYzAIWV+3+6lX\nXoGbvZLRZE44HWPSOVV3QBkPOTF93k1v8t5bXd6elLz1VsLBwTFwAqxhJS0Bmmrh4pc0Q7cO/Gqf\n74uY2+eiAbuRc6KVyA55Om3Kswr5NrujauG7q6qCsrTFu4sixxh3WkrfSI/GR2gX6yiArWHB69cL\nXt/MGKYQT0JM2qfsj8iHmyS9bfb3Yj7ai/jgPjx4UDKd2jhMzwsIAhka328agZ9GwG5VrKswQQWn\nydrNAxb/UL9v3zOZ2HvjFj2TUp5N4I6P79uen1ZDtSScph5JokkSj/nclp9MUxYEbH1Mpq6eVZAk\nBUVhCVipoDZZ+09EwGKxkWyUVtYWp8lb6mWIbFcLlvT7loD9bojqK0zHYCRqGTtrA6zeInXfSxpt\nWAh4oS3nOZ3xGK8oUElCdXREeecOudZMDg6YHhwwn07ReY4uSzyaRnYB4I9G6Nu30bdvW+23blJc\nrl8j27hBunGDidlgnIw4TgImWUM2V0neZ81tNwhL5oBrFRI3hGzKDg8rTk5KptOKqkqpqpSyTDGm\noKqsXcL3DXEc0u8bG/18zQbR3ghK+nlCsH+CmacU6ztka9scV1u89501fvM7Xf7xeyX37yfs758A\nB1gp95EtmxCwawoXC9dqcOVFze1zM0G7GrCQrAReSSCOa5ZIEkOSVMznJcZIkoJ0zJDp6BqUfOz+\n2WNZA4bNYcHr11M+t5OiJwZ1EFLNepT9NfLhFrPeFvv3FHd2Fe+8Y2oCtnmjnqcIgpA4DurKLctm\nltMI2I38vIwBGafhNFmvasFRZE0/WtsMMCFM0YylE6SMMPQJAp8giBwzsVok/cs4PraP4ne2i4MQ\ncE6SFEhtWSubZQ1Y5CjnKztjt73hWQR8FWUNZ89tIeBVrUIqwna6iqAXovoBVdf68E7TgGWWuylJ\nc5qksxIwRYGeTIgmE7y9PSqtKZUiBSZVxaExTI0hMKaOGLAIgUApvNEI75VXUN/zPY1TsNOhXLtB\nuvkKs41XmEw6nNzXHB/YymnuBvGqyPs0WbsuGnExuGQl70kS18VkGI9LZrMCY6Tq9wwrzQqo8DxN\nHHcYDCwBX79uNeBrpkTvzdHJCWWaU3QGZLfe4Li6zTvfgN98C379N+aUZUJVHQP7QA/YhEU7Q7Wo\naOd2NXJdTO64iLl9LlHQ8ihCcX2A06n1/c1mpi4vaMjzijQtyfOy9vPKHlge3X6RrunZADaizkbi\nKba2bOPvyC/xQw821+H11zDzgmzjOjPdYzz1mDqbAKU8Op2A9XVDtxvS6Xh1upFaTECxWG1v27nr\nRsjK4iz+xdOKNZx3X8mLwKqsxXwrAUxx3GiaGxtNLW139yn5wYMBtcnZPrrdS9zqO7KLdQu+22F/\nC8ZYv6+NrLRuhH4/YDj0GI3s+UiQyKpfSxpsuLWMXbmeNindTYfgrGCdlx2nyVvgugIkEt6aqVWt\nRSrINaaM0fGQ3tYWszQlyTKSNAXszM5g0YZdojEqGn9xagwTwDe2drS7UiggVIooioiDgDiK6AwG\nRIOBbbLw5puoN9+Ez32O1O+REjEnZmo2mU6HTKqQ48RnMjt7nl4VeZ8ma9fk3MRbNA04tLab4Mmk\nYjIpSZKcPHetlxVNfAeAIghiej2f9XXFaFDS9XKCrMDzclS/AzeuM58Y7uWb3P+wy9vHivc/nHJw\nOCPLxsAxVvp+bUGTCGiF1mopXQ6ajYNrer7IuX1ulbDgUUe+aMA2qMpQVdbcXJbWN2DJt2SZfN2U\nfZmKcvVCwLau6NqaWhCk79W2xK0t6HSockUWbjOlt6jrLNHtvu/R70dsbXn0ej69nkevt3wd6+v2\nUNvby12QRDuWvLbTkrjLsgnFv0wE7EJ+4O59EQLudOy9S9Pl3aXWTVDr5maj0eZ5E3znpqxJtyMJ\n1IDmOHZUKFWiVInve0RRQBwHDAY+o5Fmbc2eTxQ15nA5dpY1EZ2rfl93p78avOWSkIvLtBifBve6\n5X5IrIdoGm6kNIAuFJ08ptMZ0dnZITk5IRmPSbJsUR0LGgKW2W6c11OaemhuHrHkLHSUohtFdPt9\nusMhwe3bBLdu4d++jbp+HXX9Oly/Tpp1OEoiDpOISdZlkvUZH3kkTnBZK2+LVfKSVB6Rs2ymtTYk\nSUmSZMznlnyLQtZvKabjLQ1LwAHr64q1fkFHzfGTBBVl0OvD7dvMjzw+3t3iGx/FfPOjgvffH3Ny\nsoc1O8svIiIIAqLII45tyqhov6vnL3+/CHP7XEtRugQs6SGTSRMBKxqLNTkXGCMhGKeRb+2Mwb16\nS8BhWDEcws6OJeBh3xDo2s5Q9/qtTEg2jpiN41oDb3LafN+n37cGsX7fRlD3+8vVX4QkdnaawKKy\nlIbRzcJ+mgYsfiTRti4bVkP3XQKWtE2JdI+iZX/x9evW73P9+nL7Vmg2SGLmPD5uIqbFVAyS8mBq\n8rUacBAo4jig348ZDGxXFSFgKXokBDweN34t2TCs+n3P8gtd1QV5VeYS41EUdn4LESd1HRTPgxDF\nZh7T64zo71wjUYokz0nGY1JjFiVT7Kxe1n6p/56v/N9d1n0g1Jp+HDMYjehtb6M+/3nUl76E+tKX\nGnPLcMj8KORwP+ReHnIy9xhPNeOppjKNrE+LgL1q8nblvFrPYTKx8nV9p1lWkGUZWTbHmMxxJ0ou\nf5NSCCFBEC4IeNQv6eo53mwCuoB+D9ZGzOOIux91+f/ejvl/3yp4+PCEk5P7wO7iWEpF+H5AHHv0\nemqRi3xayVS5lhdhbj9TAna1EbcmrBtV1mgrVgN2Cbgh2/yM4Wq/0kPSIwg8hkPNtWuK7R3orwf4\n/Yg88EnKkCQLmWYBJ1Ofk6m3yEuzfkrrqI9jm7At9YqHw6XGKKytWS1uOLSCE8GKqVXMlc31Ld+b\nx5U2exlxmqzFTLVqsrLND+zn4rgJxJMNkJCgRFBKutLRUdOH+eTETnjpJmnN3daCkuc2qMPm/npo\n7dHp+IxGHuvretG1cmOjKUMn5nKxYLil9dxUM1lwZDMpqVXy2lmT8XH/exlxmrzdms9iUbAbLYMx\nNqByOq2YzxXHx7D7ccGtgxG3ys8x256Rm/fR1fusFyVqnqDyHJXnBMYwwIbTdHGCqJSyndHqRaX0\nfapa/fK6XfxOh6DfJ9rYwtvcotraIbv1BtnGG+TeTfKsQ37UIR/HHEwC9o99Dk4CZon196a1Ci7X\nBFdT3o+T9arWaLuOlZSlXcuLYk5RzKmqOc0WCdygWaVsPr9S0WKebm0p1jY0cd/m/s1MwHQaMslC\n3v844L27Ph/dg93dgvHY1oCwfBAAPZTqEwRdul3pI2z3W+LqF7eTXJsEYl303H5mBOz6B1yhrYZ5\nS+JzGEo+WElZNkFXyxqv+A5kuAYpgxRpCEPr49vZgZ3rmsFGSDCEPDQcHfo8PPQ4nnhkuSYr1GIR\nl/Sifr/5wY1GzXBz4Hq9xlfp5o2t1hB1TRnuvbkskxPOlrX4/sRyIDtPiYiVqOiHDxsz82Ri3+NG\nxKepdKOy9RXqaoILU3GjeZVoneJ5KVVVkqaasgzwfZ9uN2B93eP6dbtx2tqyBCyQzZO4E9ym3ZL/\n6+avy7VdJjk+KZ5kbkvhBTtnDHluK9bt7xfs7Snu3NGM+hWfi9d5o/PdjLfWGZo1BsZj0ySEJ4cE\nkwlhUeAbQxdLviHSfBICrRcZCjqKqOIYU1fw1zs76O1t9PYO3voWZn2bdG2LcbjJSbDJeLrBNA2Y\nZAHT1CfJPJLMY55C4Wy+5PfrXvtVwpOu482aZ+oSslmdXjSvA65SWCSBiX3Car9ah/h+iO8H9Hoe\no5G2BLzpEQ1iTF8zTg13Dz0+fuDxzvuadz6A+w9Kjo5y0tRQFBq7NesBI2BEEAzodEKGQxYWr/X1\nZiMt67ar0cPFzu1nrgG7gjuNfJsGyHaXLNWKllOMSmfI6ymNQarCCtXugIJACFixfU0z2AwJhj65\nZzica+7uKvb2FdpTaK/Z8QgBS+CNFAMXwQn5pumypvs4x/1pQryMC/dpsl6tDys/dEnr8bzGonB8\nbP8WUh2Pl3sD7+9bot7dteQrxVjEnG93oRK2MwMqqqqDMRFhGNHpaNbXNdeuWb/9zo4lYCn8IaYz\n2R27Rebda1qdpJfJivE0+KS5LffFpoVZrSjPM6oqW5QbjELF3hvrTN5cI3vlC7xhPAbVjE2zS6wq\ngrIkrHv1xjSFSMEu44FSdIKAOI4Jul1bmGMwsLurz30O9cYbmFdepVjbplzbIettcHIU8PAo4OGR\nz8Gh4vBIcXCooY6wV07kq7tAX2V5f5KsVwnYpoym5HkCpHXmSkqzdWrI1xJwgO8HhGFAt6sZjWzw\n7PqWT9zRmDhkksLdQ8U331V8+9sV73xQcP9BwfFxUctHksx6wBpKbRAEMd3uowQMy6Z013UCFyvr\nZ6oBC8QHKDVCpQSYRM7ZKFa7OypLXe9moMkCdD1AbjhG89z3DWHoEYYR6+sho5FXlyRU5KXieKKo\nDOwdKPYO4eBILTRvMaGIeUICb6RtnqQIun4s+UG6k3NV22uqOS3fG/GBX5YArLNkLRqQEJmkJEi0\nuLzHrZgEzT0EKxfX/Lv6vcv5hwpjrBvCdkXy0dpnMLCbsWvXFDs7Vpby3W5KhXyfO6Ti0aqpzXWj\nuFrCaRuwy7bhepq57eZUSxCWBFB6XsXdYUg0DDH9iCrZRntvEI+mmOAW+eiQ4NoRgSqINXQ80KJE\nAVXlMyljjsuIQnXIgh4ZPYp0AzN5BXPwClV0k2q+RpWsU/ZGHB3ZzZ7tbFaPyXIkrCy8rlyvqryf\ndh2XCPc81xgjNRnOGlYTjiKf4dC6Dbe2NKORPb4BponHbO7x8QPDB3fhnffgvQ8Muw8N40lJUYjl\nc4hSIUGwRhD0ieMOa2tNCUrpvNbpLOcww7K8L1rW5xKEJRFmUbRcqm6VrKrKI8sC0lRKTEKTku8S\nr1oZEEUeo1HAaBRz7VrEaGTriVbGTrDKKPLMalHHR1Z7kvMRIpaAHPH5iYlUCooLoYh5Va7FJQK3\n2Iir9bkkXFWNv/OywZU1ND5aqXr28KG9N5Lrq3UTTLXaqMPND04S+75er7l3UgKv2UiJGUqhtSEM\nA4LAZzRS3LqluHnTar5CrOJDdqNc5RrcHfBqN5/lYiGPBm5clsX3SfBkc1tRVZos8+u5bSs+V1XK\n8XHInTshs1lI3u2Sdt8gHQzpb03pRAmdcEYYVfgRBBH4kuYPTKeah7sBD3d99o8DTuYRx7OQ6axr\nCXd3nWq4hj/o4A9CdG/ZsiGPq9rdaVWQWnk/jax9siwiTZ3dEtCQbuP/BVu/fWtLcfOm4sYNa8Tw\nvCYGZDq1jazefdfw/vuGu3crTk6q2u+rsM4JH60rOp0ug0GX4TBkZ8dja0uzsdG0HZROlauBWMvx\nSBcn63MhYAlugWYxdjUPuyNRZJnHbOYW1DCw1PvVjYHUzusQRZrRKOD6dUvAa2u2mLcxtW+xDurZ\n24ej46Y8mjjQe71G23VNKmKODsNm5+QSbJ43whOTqlR+EUGvasCrWtdlgitrCV6Q+zCdNo9iYfD9\nhoDdDkg2IK6Jmp5Om13sfN5oUyI7W1BJJrdfy07R6WjW1hS3bsHNm9Y66bYmc8vpre583QV4lYBd\nzfsqFWVYxZPNbcgyzWwmvr8SSDBmzPFxSJKEPHgQkd3ukt5+g/nOF7h5veLatZJr10r0ALweBHUO\nudzrk114+Nua3/5txfsfKB7sau4nmsMTj2I3oFAhlefT7Xt0+h6d/mqhl2aIlcP1YbfyXsaTr+M+\ns5mQrLtuK3CqFAoJdzoe29uaV1+1Zb2HQ/td83njenr3XXjvPUvA9+5Vdc0Il4AH2PoNPmtrPtvb\nHtvbis1NG0zrZjLA8oZ71ep1kbI+NwIW86HrD3RHVSmKwu6Si8JQliFFEdcBWa7JWaKiRbgWvd6A\nGzc6fOELPrdve9y4DttbEMVQ5JAXkOVNn9hV34VUYep03P8b4gii0BAFkGdgKlUTsFq0YINGaG75\nNaklfFb4+mWEK2uZpLJRKcsmN1Q2MUFg79VqQQ43b1i6w21sWP+v79td8vq6/YyQudaKovAoCg+t\nG3eCuBCE8CW60SX71XN2A09WJ6X7+LgUlauAp5vbHkXhU5b+4tHOIWuSvtfr4PcDymHISQ+OehXH\n/YqBtp69rrGtQJWyZQUfTjTfmiq+nWg+SDS7icfuzON4qqkqTVUptNb0UujNoT9vNnRy7qsVj1bJ\nt5V3gyeTtXUn5rlfa8MRZWmoKlWvg/ZRrFNB4HHjhuaVVxRvvmnTD3s9FlW0JN1wPG7WWtsIR9PU\ndw5RKiQMfba3FVtbdtSlvRmNGpmu5gGvRnhftKzPLQ+4CVM/vZqI/Z/dGWntM5t1ag0lYDkIy62G\nJdpywGDQ57XXenzflz1u34bh0NTarK28kxdNjdqqahZ4t2elmJBl1+N54HuG0KuIfMPUKPJMM5mo\nRbUktxOILOxSDvEqEa+L02Tt+8tkPK97zokZUKwNrvnfDYYbjaz2Op/bFCI37Usi6SWISzRtkW+/\n35ie3JQzqf0sY7W2rVvJ7KydsWueuqr49HPbp0kpzJhMCh48GJPnsLeX8+GHOcNhThwbokgThgrP\nswE8SgWMxz737/s8eOCxvx8yHsdMpzFFEeH7PmFo+4FLXr6UjXW1oU/Sdlt5L+OTZG3/Ly4gcTvE\nZJmHMWqxLg6HNt1oOPR4803Nm29aAh4M7Lx0myXIfOz3FTs7qnZdGTxP4XkGz7NtRaNIsbamWFtr\nNt1S7c5tkSkbh0/Sei9C1ufmA17dRbi+PrkJ1AWztdZo3aUofObzmKYnSkFTFdbHVo3tAT2Gw4jX\nXg348pc1t2+ZhRaFMrb8XWkDgKSModZNFLM8CgG7Oau+Zwj8ijgo0cYjz2A69RYa7qoJGpa1q6uG\nx8navWfQkJ7rg3NLesZxExA3GjXFO6B5n5Ck1pZc9/dtmlKWLZO5S8ASNBeGyz562TzJ+bnHXp2g\nZwVmXDV89rk9BiZAwXSakOdzDg8TgsCOMEzq42m01ijVtKIsiogkCZnPQ7KsQ54PyfPBwn0h7SmF\neE8jYLf4wlmabytviyeRtdwrKf84mwVMpx6zWbiUFbG2prh+3dZqePNNxec/b7vDKtW4h2wf74aA\nBwMJopRWon69ztvvCkNbMKnXezSgdjZr3IPutbxosj43Aj4rgqzZidg32PZ/Bs8L0NrD80KgxNYP\nLagqn6ryMSYkCDqEYZ8w7PPqLcWrN0pe3c64vsHiDldGURhNUbetG42shqS1oRNDXGtdjQlKLX5Q\nsOzjcEtoSiCQ+BKEvK/yBIWzZQ3NPVxNXHfT0lzSlCIZoh0Ph01ermg0Eokuvn457nzeLLDuIrtq\nMlsNvHKfn+b7dc1SV13W8Onmtta2RZwxgdPpLKMsc2Yz20Zy2eoFOPWvbIlROyQ4UymD1qbOhoB+\n3yzMzW5qoZCvlIpdTadp5X02nkTWUi9f3HqzmUe36y1K78p4ZSfl9k7C7a2UN9c1rww017seaeVj\nUp8EH2P0YnMex1aztQFgarFJX01rFdm6ddtdt5O4l1ZNzS+KrM+1FrRAbqqYAN2LFi2o21UMh5rp\nVMxXCmM8sswjzwOyrGBtLWRzM2JzU/NPfCHn1vqcMEngiMWdN16AIaCqe6F0OiwE2e1C14lwNsb1\nKtfpQpk1nVUVzOaaLNdLRSXOIxT9MuE0WYvJWYZLuq5VQlLEJFjNLqzL9bbleJKvK3JdjWp1LRSu\nD9olXFlEJDDHnbzurriV9dn4pLlt760iijS9nsd8HjOfG+Zznyzrkecjskzy/2UAdeqK1n6t/QRo\n7aOUHb4fEoYxYdghjiP6fZ/BQC9Kwrq/KXnuRrq28n56nCVrIeA4ZhEnk+fLfvbb0QmvxA+57T/k\nWuGzPYmJ92Lw+kTFgMgf0Olo5nM7n5VqeoVLfIdsotzNtDvnRXlabdZyGgG/KLI+dwJ2b4AbbSo/\nfgm8GY1UHU3sYYzNKTPGkCQBs1lMklTcuuXx+uvajq2CW+szotmxDYxb2B5jKg2VZ5syx7El4H7f\nlhbt9QxRBHmuyJzi/5LTlqIoK01eaKZzS8inEXCLR3GWrMXPLpN3VTuRR9c3KyZjmWRC1GI2llJy\n0jbQ1WZcApbjiSvCnXhu60FXO3Lf08r6bDzJ3LbaqKLbhcHAZzyOOTkJGI97JImt/57nUgdeNGFV\nD2uGDgJNGGp8X0zaiiCwmla369HrefT7mn5fLbpvnTbcc23l/XQ4S9ZyH6OoSUEE++hutF/Jjnkl\nvcPt7B16eURnMiTeG1B1togCRRx2ieOATsceRzZIcmwxLQdBQ/JOoiAdAAAgAElEQVSrmQySjSL/\nEwJ2f5cvmqyfCwGvmv3cSRqGdoJaEpTWZY0gJchmNoNXX4U334QvfAF2OrChSwJyyjkUpUeR+RRB\nRRkYyrDukOLZBR5gUJuoohCSuUEnarGgW3+hIq1NaFrDZApzx4m/el0tlnGWrBtz1fKkdct3wnKK\nkPjUXZ8TNGYlIdVVrcuVixupKW6F1YXE1dZWcwDd62rxKJ5kbkeRqv37qu4yFS5cBEFgahO1wSwm\nmMFGulofchCoU/3/Yh05LeDqtIpNUuVKzrOV99PhcbKWOS0bYcko6UalHWHJjeNjbh7vceP4Y/yy\nLgi/PyUdavxBnyCuFtaKTgcwhm4Pel3odg29jqHbNXgezBJNMlfMU7U0xyWWw81Gcef7iyjr52KC\ndiE3BJpdqUxWWVTdGzYYNDuba9eaZghe5KPDDgQVaQHHScjxcUihQ/xuQNDVKKeAhhCB2JzLErLc\nOv6nU+tPnE6Xz1MCA9xArRZPDpG1ECk0lbCMsTvdsyaGeww38lm67mRZk7YwnS6bvFZz+SSH290E\nuAF0q+cn39vi6XDa3HYzDESrkYVWqszN58rZ4D6aOrhasQqajbXbu3nVR+h+3i0z2cr7s+M0WRvj\nWLdiQ4+EvpnQY8qad0TXS9G+1+QcGQNqCKGNttS68et6GkbDitHA0OtURH5J6FvflPF8St+nrPyl\nTAa3rgAsm53hxZT1cydgEZQIUFKE3Ig5V0MS7TTPbR7oaFT7CiMf3e1C12c+UeyfeHy871MYj/5I\n0y8VUdzc7EVADo0W5fYoPjmxw41oFqG6BTReJOG96JB7LhC/q/hjYTkV6LTAmNUcbrfymLQplBrR\nrvl51dcri667KLvNut3gEvd8Wzw5zprb4ve3xVMa/6ybX2/jPuzNt1Guj/ZjhuWmCfIe0ajdsUre\nrbyfLU6TtdZON7k+DNKE/vyAQbpH5B0S+SnKq98ska3+GvRTMMsEHAWGtaFhc72kH5d4VY5X5ZSF\nofRicl+TrxR/WS0JLBu/F1nWz5WA3UXRxWqkquuTc6uuSOlIY6AwHpmOSP2QCXA41+yeaPJCkQGV\ngm65HA0rtWpNtVyUX8zck8myEM/yF7wownuR8ThZu6UBxbqRpsudss4yIwoBS95gkrDI0ZbcY1dT\nkkl42qJ8mqzPuo4Wj8fj5C3arwRCCQkXhVpxJdgPy3vj+NEF1H2/G0Tlnocrb5eAW3k/G5wla8+j\n9vXDaGgYTTNGTBlWR6gwgaCE0KkNWZaYoqQqKsoCTK1JL4rydA2DnqEXVZishLTAGIOmRCuz+E24\nhX/cXGX5XbzIsn7uGvBZcG+GGzQjN1U0UVm0Z1PF+ERx2IXZTHEyVou2YtJfVvJ/RfOZTqwvyvcN\ns5li5pCwm5+6Sryrvo8XQXAvM2RDtKqNyutn1cx2tVmRldSgdgO9VjdLrkvD9Tu3sn4+cOXtuprc\nIfdaFmDx+7qLqGslg1beLxpEyZlObQx7WPl0/Y5lZHcRd3ZHZXydeThknHiLfsxKAQryUjFLPavh\nzqFINVkKsyJglmtm+fIGXnj9ZZL1C0PA0NyQ1ckpk27JZBxBHGniyJAXloRLh4BLR/tdnYy2hOGy\neVsI2F0IztJ6XwTBvcyQCSKL7erOdbVmtisTF+LXkxQEV9anfX5Vtq2snw/cBdHtnOVurleD9MQS\nIvd/1UoGrbxfNIh7aTYDUyq6UcAw7kA0WF7QJfWl36eoNpjnA8Yzn9xJCQRFXmhmqSHLFelck819\n20yl8Mhyj7RoyNdthvMyyfqFIODVGyHar6sBCwGnqUxStaiKIrtjmZhuzeZGCJ98t1cncotnD3fn\nKeZJye1bNRG6i7P4mUQLdk2N7rEvMqm+xaNw5S0bLjc/XOS9GlErY3Vurx67lfeLAyHgqoIyh5n2\nSTsxRTyATgWZsWPQrxuvr5PN+iSHfaZzj1I1m7TKKNJcoepKVjZYr9F0Zbh5x4KXaR1/IQh4FTIJ\nYTkoyk2odgMz4OxJ2E7OFxutrK8WWnlfboglK0cxTgIeqC55oWDmwTyGcmgfx12oehynHY6TgLxU\nVDS5xBLjMZvZ47m5v67lxG01+DLihSRgMRe7UbRnmRbOCggQtJP0xUYr66uFVt6XG7KpKgyczAPy\nwhIxeQfyoVWNU99GXKUh89InyTyKUmFoNFxJURQLl+uOXM3vbwn4GeI00+LTfLbFy4NW1lcLrbwv\nPxbkiGJSBkzqksBLcCuOruAy9kx/HJ6UgGOAe/feOsdTuXpw7md8keexglbW54AXVNbQyvtc8ILK\nu5X1OeAzydoY84kD+IPUNSzacS7jDz6JHJ7HaGV9dWTdyvtqybuV9Ysna9XUYD0bSqlN4CeA97HN\neVs8G8TA68DfNsbsX/C5AK2szxEvnKyhlfc54oWTdyvrc8OnlvUTEXCLFi1atGjR4tniJcqYatGi\nRYsWLS4PWgJu0aJFixYtLgAtAbdo0aJFixYXgJaAW7Ro0aJFiwtAS8AtWrRo0aLFBeCFJmCl1FeU\nUl9/ys98TSn1Z8/rnFqcD1pZXy208r46aGV9Nj4zASul/ohS6kQppZ3XekqpXCn1d1fe+6NKqUop\n9foTHv7PAD/+Wc9xFfU5/PSzPq5z/M8rpcZKqYPz+o6LQCvrxTFfq4/rjlIp9Tuf5fdcNFp5P3Ls\n/0Ap9S2l1FwpdUcp9R+fx/dcBFpZL475FWc+u/N7/Cy/R/AsNOCvAT3gn3Re+6eBe8APKaVC5/Xf\nA3xgjHn/SQ5sjJkZYw6fwTk+NyilfOC/B37tos/lHNDKuoEBfgy4Xo8bwG9d6Bk9e7TyrqGU+kXg\n3wD+feC7gZ8GfuNCT+rZopW1xZ+hmc8yt78J/E/n8WWfmYCNMd/GCulHnJd/BPgbwHvAD628/jV5\nopQaKaX+glJqVyl1rJT6FaXU73D+/xWl1D9ynntKqV9USh0qpR4qpf6UUuqvKKX++up1KaX+tFJq\nXyl1Tyn1FecY72EXz79R72zerV//XqXU/1nvAo+VUr+plPr+T3FL/nPgLeCvfYrPvtBoZb0EBRwY\nY3adcalKybfyXhz3i8C/Bfy0MeZvGWM+MMb8I2PM3/2kz74saGW9uA8zd05jifhLwF980mM8DZ6V\nD/hXgR91nv9o/dqvyetKqQj4p3AEB/zPgJRH+37g68CvKKXWnPe4pbr+I+BfBn4O+GFgCPyLK++h\n/v8E+J3Afwj8CaWUmEB+ELt4/hx2d/OD9etfBe4AP1Cfy58CFm2eayH/ocfdBKXUjwF/APi3H/e+\nlxy/Sitrwf+mlHqglPr7SqmfeoL3v4z4VVp5/yTwDvDTSql3lVLvKaV+SSm1/pjPvIz4VVpZr+IX\ngG8ZY/7hU3zmyfGMinz/AnCCJfQBkAJbwM8AX6vf82NACdyun/9u4BAIVo71NvAL9d9fAb7u/O8e\n8O85zzW2run/4rz2NeDXVo7568B/4TyvsLtZ9z3HwL/6mGv8JvD7H/P/TeAD4Ifr5z+H1ZAuvAj7\nsxytrBey/nexk/4HgP+yvt6fvGj5tPI+F3n/10AC/EPgdwH/DDXJXLR8Wlk/W1mvvDcE9oE/el73\n/Fn1Axb/wQ8CG8C3jTF7SqlfA/6Ssv6DHwHeMcZ8VH/md9RCPlDLzT5j4M3VL1BKDYFrwG/Ka8aY\nSin1W9idkIt/vPL8HrDzCdfwZ4G/WO+OfgX4a8aYd53v+tInfP6XgF82xvwDOeVPeP/Liisva2ML\nrv9Xzku/pZS6Cfwx4G9+wne/bLjy8sYSRIhd2N+pz/nnsXL/LmPM25/w+ZcFrayX8QeAPvDfPcVn\nngrPhICNMe8ope5izRQb1AFIxph7Sqk7WDPDj7BstugDH2Md+qs3/uhxX7fy/DSiy1eeGz7B3G6M\n+U+VUr8M/AvA7wP+pFLqZ4wx/+vjPufgR4GfVEr9Mee8tFIqA/5NY8xfecLjvNBoZX0mfh34Zz/D\n519ItPIG7MJfCPnWkCawr2K1vZcerawfwc8Df9NYX/C54FnmAX8NK7gfwfoNBH8P+OexdnxXcF/H\n2u5LY8y7K+OR9B1jzAnwoD4OAMqGzH/fpzjXHPBO+Y7vGGP+nDHmJ4C/DvzrT3HMHwK+DHxvPf4E\n1pzzvfWxLhOuuqxPw/dhF+rLiKsu738A+EqpzzmvfTeWED74FOf4IuOqy1rO6XXsffgLn+K8nhjP\nmoB/N5Zw3BScvwf8ESDAEagx5leA/wsbxfZ7lc2t/F1Kqf/sMVFrfx7440qpn1ZKfQH4c8Aaj+6m\nPgnvAz+ulLqmlFpTSsVKqT+vlPo9SqlXlVI/jDXDfFM+oJT6baXU7z/rgMaYbxljvikDuAtUxpi3\njDHHT3l+LzqutKyVUn9IKfUzSqnvrscfB/414Bef8txeFlxpeWNNmV/HmmG/rJT6AeC/Af6OMeY7\nT3l+LzquuqwFP4/V7P+Ppzynp8KzJuAYeNsY89B5/dewZorfNsbcX/nM78MK9i8B38Lmz76K3SGd\nhj9dv+evYgMixsDfYbm59JMI8Y8CvxcbLfd1oMAG1vzV+jz+B+BvAX/S+cx3AaMnOPZVQCtr+E+A\n/wf4v4GfAv4lY8x/+wTn8zLiSsvb2IicnwL2sNf8vwPfwEbyXjZcaVkDKOvM/jngL9eyPzeocz7+\nuaK+UW8B/6Mx5isXfT4tzg+trK8WWnlfHVxlWT+rKOjnAqXUq8A/h92NxcC/A7yO3U21uERoZX21\n0Mr76qCVdYMXuhnDKaiwvrbfAP4+8D3AjxtjvnWRJ9XiXNDK+mqhlffVQSvrGi+1CbpFixYtWrR4\nWfGyacAtWrRo0aLFpUBLwC1atGjRosUF4ImCsJRSUmj7fZZDxVt8NsTY4IO/XZc3vHC0sj43XLis\nW9leKJ67/Ft5XyieSN5PGgX9E8AvP4OTanE6/hVenAjAVtbni4uUdSvbi8fzlH8r74vHY+X9pAT8\nPsAf/sNf5caNLz6Dc2oBcO/eW/zSL/0s1Pf3BcH70Mr6WeMFkfX7AF/96lf54hdb2T5PvPXWW/zs\nzz53+b8PrbwvAk8q7ycl4DnAjRtf5LXXPk2P+hafgBfJPNTK+nxxkbKeA3zxi1/k+7+/le0F4XnK\nv5X3xeOx8m6DsFq0aNGiRYsLwEtVCeuzwE13/jSpz26ry+W2ly1eNLSybtGixcuAK0PA0CzGn7b2\nSLsYvzxoZd2iRYsXHVeKgMEuyJ+l+Fe7ML88aGXdokWLFxmXgoBdbWd1VNXyKMvlRVkp0Hr5UYb8\n/6wh/3eP1eJ80cq6RYsWlwWXgoDBLriyCJdl85jndhSFHWVph7u4+j4EgX3Uenmctli7rwvaBfn5\noZV1ixYtLgMuBQGLBiQLblnaBTjPYT63I8uWF2d3cY2iZnieHe4C7XnLC7IxzYIsx2jxfNDKukWL\nFpcFz5WAnzQw5nEaiHzWXTChMTvmuV2A07TRlLIMZrNGQ8rzZbNiHDcLtizKsjC7j+53ykIt59Mu\nzMt42iAo916eZlp2NV6RlSvPNIUkERI2i/+LBmxlp+h0WIwgaIbvN+M0WQtaEm7RosWzwnPXgN0F\n9TQ0i2VDfjLk88bYRVM0GVkQhWynU0u4WtsF2ZiGmEU7EsKGxlxZVcvkH4bNWD0PpZbf3+JRfJKs\nobl/q4S7quHKyDIr0zRthryWJHakqbzfUFWWeOX31Os1I4qsbOV3JH+vynr1fI1pZd6iRYvPjudO\nwEJ8j1uUXa03CJqF0V2k47hZSH2/WRDnczg5geNjuwifnDxKwFnWLOiuH9GNmpXviGP7/zBsCNvV\nzsVM2S7Kj+JJZO1ueNwAKpGXa9HIMkuwssFqNN6GfIWAy9LUcjU1+Sp8HwYDO4bDRr5x3GjFZWl/\nayLr087V9Qe3aNGixafFhZmgT1uY3cXY8yz5ijkQGrKDJpjGkrNZaCzZtMCfz/FNisozyrTEzEvC\nxJAVirzQ5EZTeD659qm0R6fnEfc0nZ5nyRSFMRB2NFHHI+5qPF8tzJFitgzDR4ljFaukfFVI+ixZ\nn2aaFpm7Wq+r4SaJJVxLuhXTaclsVjGf25Gmzd/zuSHLDFVlFt+rtUZrje9rikKT5x5ZpoljOzod\nTa+nyLLGxB2GdoPmmqk/aaN1VWXdokWLT4cLMUGv+vXg0UjUILCaCZwdzZqmjfbr+xAGEHgJ3vwB\n8dEuvYdHjA4Trh8nzKYFhQoolU8ZhJSdHlXco+r2CPox4SAiGEQY7EkYpfC6EX43wu9FlEYtzKGe\n15imiwImE6uVScAPPJra4r52VXCarN10oVWLg9zfslzWaicTa8kYjyFJSubzOWmakmUZRZGR5xl5\nnlMUdlRViTEaUIDGGI+q8ihLj/k8BiLyPCaKQsIwJIpCBoPGdL1qknZHGDbn28q6RYsWnwUXRsCy\n4MpCLIEurpYZx8t+W9c3LIE3WtckDISBIdAJcfqAweG3KfY+Jj84Jjs+pphmmDCyI+hihpuYjQ3M\n+gZ62EePBuhhv94FaIzW0OuhBgr6IfM6kGs6tW8RAk4Sew2zWUPAq0FkcDUX5NNk7T7K3/IbcH29\novHOZnB0BIeHcHAA83lBns8pigllOaWqEoyZUVUJVTWnquYYU2CMB9hhjA8EFEWAMQPyvM9s1icI\negSBJghC0rSJDYjjhmzFPO3mFLsybWXdokWLT4sLSUNytSBZ2Nz8S1mwxfwoQxbEOAZjjNVvlMGr\nSrwsw59lRJN9opN7cHQHc/QBHO3B8b5dyeXDqgfFDqhrqGAbojXorENvrWF4ran6KVW/wPQrpnnA\nJPCYBB4oCHxDGBjGKKaRR+BrlNKL65NrWjW1XjWsylo03NVHl5DFDOw+l0Cr+RyqqqKqylrTzTEm\nR+sM38/wvBSlioXWW1U+UAFWEFrnaF2gdYXWFcaYRXCX+JrlN+j6/AUu0boWm1bWLVq0eFpcqAbs\nmiDF7yumZdEsXQIeDmFjo9ZQQkO/axgNK3pmQuf4AO/BIezdg/v3xV5p7ZfHx/a5OPM6Hfsls5l9\nfWPDPop6Ww/V7aF6fej1Cf0eXa+H9rqgFH5V4KclZe7RVR26UWz9y3kT3HWaafIqYbVC1WpUs1s8\nQywc4k7odq0W2u/bjZf8NuZzD2M69SYtpCi6FEWG1hndbkankxMEJWmqyTJNnjcmaPCJ45g47hBF\nMUURURQ+RWF/U93uoxHv4psWYpafByynKF11Wbdo0eLpcWFBWKsELKbkILBcKEOiXZMErl2zC+Xm\npvX39roV68OKzmSKf3Qf794deHAPHj60TsOagM3xsbVjyuoZhqjp1H7B8bF972xm1Ss3+bjTRXe7\nmG6XcLiOHm4QrW2AUug8QxUZRRbSVdCNAtIyWJhSbfpLc21XDauyPo18RfOUCOfVlC8huDhuXssy\nD2NijPEpii5pWpGmJb5fsr5esb5eEUWG6VQxnapaY9ZUlQIU/b7PcOjR7/vMZh6zmWY2Ww6uc3OD\nlWrOV6wakgPupqRdZVm3aNHi0+FCNWB41I9mjOXC/X3Lo26u56BXUeWGUFd0/YK+V9DXOXF5ApMD\n2L1vP5gkTdkjceLNl/simzxHTSb2iYQ0B8ESAaskgekEFcfossAPNZgIlIYqhWxOVnXoejH9TkVK\noy19UvrNZYerEa4G2LnVptwIcgl6Eh/sam5uEAgBexgTLqpfpan937VrsL0N3a5hMrHGj2RWk39t\nTh6NYG0NRkM4cTZ6cq7u+Wptz0s2DbBMzBKItWp+btGiRYsnwXMl4NWAldWgFdGGjo5gbw/u3Vuu\nStUNC9ajlGtxykY1pztO8OYJjA/tB6MI1tftMMa+9tprqONjzGy2ZA9V4mCE5jODwbINUdQwaFbi\nLLOvlSVg/+z4MOxCETYBRIKrmiMsGqJolmHY+HRdQpaKVY+rQiYaaa/HIlhKfMRyzDiGnR07Bn3I\nc0Oe2ceyUpSlojLQ70G/Z+h1DbNEMU3UkrzAfsdqfrH8fIT0XcuNnPNVlXWLFi0+HZ67BnyaliEL\nsWi6QsD371sf4GBQF96IctajGdeiCSMzJjwZo9MxpElDwOLM63TsqliHUCs32ke+5PDQqklSnaHf\nb05S4NpQpSqE7y9skp4HnQhGEZShXahXq3ZdxXKVQsBuCVHxi4tWK8VNVguhrGqTUnRlteRkWTZ5\n4r1eQ8CjEXgKtKpQGIpSU1RQVYooMsRhRRQa0kyT5pBmaul7j4+tIWV/3/5MZC8nmwXR2F23yWrR\nkask6xYtWnw6nAsBn2WOczUEN+jK1YRmsyZu6uAAAr9ibWDodwxrnYz1eMZmOKZXHMPclrwyZYXx\nPEzcxXR7MFrDjNYw3W7N8laLNUUBRYmZJaj7H8PH92DvIapjzdSqE9vNgbJWZuUWHYZml1BrvyiF\n5yviWKF6kPuW093awUI8lzVF5bRiKtCQk2tEkI1Xp2P3SHG8fD/cNCTXT+wSs8TOiUYqZD4YGHa2\nYXsH1tdskF4cGHzfUFSGolSUBnxtCLTB9yryEvJCk5Vq6TsePrTnJjKTvGT5v9QSlzxwN53qMsu6\nRYsWzxbnqgGvBlu5qSgS0CILlvs+CbwZDODmVsbnb6V8/pWUz12fsd1L8Exdqmh9HYZDq9QWHlmp\nyXVEbnrksy5lGmF1IG0tyHlFmZVU8wh9YvDKGB1u4YcBXhjihwHdjqETG7pxBZmjbmltT/74uNG0\n4xjCAOV7KK+pNyyk4+a/yuuXFe7GSsjX1XTPanDhDpfMV2s7i/FBtN5+nbItxx/0od83dGOIAlt+\nsjQKUyprgq5UfXwDpgRTkqces0yRpFCtVO7qdq0/2W1fOJk0bhLXhSLeCSHcyy7rFi1aPBuc2zKx\nSryrqSjwqNlRhu87BLyZ8YVbE77vjTFbg4y1XoZvcghC+4ZOh7L0mSeKWaKZZR5JETCbBmSlT2Wg\nrJR136aGbG4ospKgiPCrNYIoJYw8osgjjDQbgwrWKjqjCjWrI3kmkyYabDZrzNu9HioIwPdQTsF/\nGXKtq/7Cy4ZVM7sQsMS/uYUtfP/RwCvx8brEPJk0ex4hXomjc4Oz5LHXtf7dblwR1mUjK6MoC+v7\ntSVGwVQVhgqqgiJVJLOKk5mHWbmeTqcJBJNziuOm6llZNhtHqdLm4rLKukWLFs8On4mAHxf5uar1\nrna4gUfbCcrxfN8ugIMBXN/K+a4bU7782iGxXy4ObHxramZrk6KImJ8oxsdwMlacpDCeWu3J7aKT\nJIYkkVq/w3oBV3Q09TCYTkk4KhnulHjTE1R0jApC1NGhJd+TE3sB/X5dk9JqwNJxR8jHJWDXX/iy\n4klkvVrHO4qsJtnrmQURh2ETuZxldcWz0BBFhjBSRJEijGwHozxvAtqLwv4tv41ut8nbDUPodiCO\nDUFg8LQhKzRZoShKq6YqBQpDicFTJZUpSeces6nhZLJcDCaOzeI7ZK9ly6PaeuBVZc/ftXKsRn2/\nzLJu0aLF88EzWSZWF+fTtNrThmg3UuxAzM/dbmNqHPVLYp2h5gmELNTLCk1RKIpEMU7h8Mj6jKXm\nxmRiH6WG8GRiavOhcYrsqwVRiCZ164bi5nXNreuwEUeshT3WBwo/S+3BJQTXCedVWtnh+LVdTQ8u\nTx/ZxxGxm2YUhpa8JIjOzfH1lCH0oQgrgmxGMJnhH8yg1yXr9ci6PcZjtUgRmk4taUvk83TalP8U\n83DgQ+ArwkChlCLN7CirldQmTxNqn8hTnMx8xolmnCxHM/vaoGND5FWoWFGOFFppgqBxm0ynp1+3\nG1jYokWLFo/DZybg06JWV03P8vcqAUsACzRE5Xl24ZZgnYaA56CaCgil0WS5Zp4oxlPF0VETtSpW\n48NDePDAjsND2x82zw1lafB9vVTxyPr6FPdvKR7c1OzeUnzuZsTrNxWjzQCSsT0pqRhRh/Qqre1w\nFmE3MtbV9l/2Rfk0WcvrAjcy2CVgIUmtDZVvKAtDVVR4BxP0ZA/vcI90uE2aQVZ2Fxsol4AlF9fV\nQOWeGwNVqSjramTz1I6qshXURiN7HlGgiUOfKPCYZ5p5pphny4U44tCgTEmkS8KOQmuPKFb4gVps\nGuHRAh0uCb/ssm7RosX54zOboM8i4NMI131t9f+u+VJ6s4Il4MjLrQbshYvclhJNmitmiWI8URwd\nGfb3m8yiycRGs77/vh27u7ZHrG1TZ/C8pk9skxZluP+q5sGuYXcfKhMz2Ax5ddiB6WHTBUKckkqB\np6HWgFcJ2DW3v+wL8lmydrGqAcexJeDh0EaWa2VQSn4ABooSDsYw2YV7d8hSQ152GautJSuGG4gl\n5LuKPFdMJ4bJVNXV09SinOn2tk1P2txUixaE0ufZbpLUQkOPIhh0DKoqiTxbfCWKFQM8/KDpSSwB\n8ZIO5WrQL7usW7Ro8XxwrmlIj9OEJXJ0tdWgdBpadKPp+wT9OiLLMwvbo2cCQh1hwpi5XzHoeCQD\nj/lcLRbv42OrPTWZQ5ZsRTvrdBRx7BbCUty4ATduKLa3YRjPibMZ6mHdkkfCX50+dZUfUuCT5TbQ\ny/dtTmpV2e+QTk5urutlg8hNOlh1u9DtGOLQ4KsKXVSoIocyR2Vpo9pKRNN0WqvHnu3FXDUpaeOx\nvfUnJ3ZkmcEYO+yGTaG1LbQxmwn5GtLULIha7rnNA1aL4Co3PqHXs8MYyNOKap5j5ikKjedH4OuF\nmTvwbeyA60oRv39rgm7RosWT4rlEQZ+lAUtwlORVugEsQWC1p7gf4A86qOEQirn9wGyGVj5hGKGJ\n6fuKpBOSjjSTOj90MrEL93Rqj2+1bFWbGhX9vi1JOBw2GnenY7WlrS071uI5cXqM2j2E48OGgIWx\n4xgTRBS5R1qoRTWnXk/qFjcKs6TViPnyskCsFnJbJPCq2zVEQVkTsI2mUvM6yfvePTt2d5duvvF9\njNKLXNsksQS8t2ffurtrybUsDWVZ1Zq2Jggs20nGmJir80WDHe0AACAASURBVNw4RKgWUdcy3M3h\n2pp9HgRQpCXlPIdkjtIentKowCfwFL6n8evYASF20YBd8m0JuEWLFp+EcydgN+Vk9blUNpJOM7KY\nC4H1ehD1ffxhB4YDmBq7us5meFrjdWNCOpSBR9pVFPgcHntLBDybWdKrKrFe28VzMLBNHba3Gz+l\nkPJieCmd9Bi9ex9mx43j0dWAg5Ai12TZsgbc6TQR2Gkdv+X6Dy8LTjM7Ww0YoqDCp0AVGSR184v9\nfXjvPXj7bfjwQ7h9247BADwPozSVQ8AnJ9aV8NFH8MEHVq5FUVEUVe2uUHQ6Bq3VUt1wcTfYKHvL\nhlW1XPbb3RCKFtvpWA24nOeYZI4KfFTgo1WI73kEvrFacGCvX1Kl3PvRkm+LFi2eBJ+JgM9aaFYb\nLMgiLYFWsuBJXd3ZbLm+r2isngcDL2DY6TDCEFUpfqEIstw2ShifoDyNHxgiFN04YjBogm7W1xtz\nc5Y1fr5eD27cgOvX4dqOoRek9IKMnp/ZR5PRm2ZsmD261R7KPIQsWewWTFFiKoMxmqLUpJliOlNk\n+XL1J1mYXZP8y4rHyVoe3SjwwKvwyhydJKiidsjv7dmIuHv3rLNeylnFMayvM8l63D8IuXtf8eHd\nijt3Kj78sOL+/ZL9/ZLptGA+r2oN2JIu+FSVh1K6/g2ZpcpUoChLn7L0KEtvsfFz/fW+L9W07KZs\nNDR04gpNCZW2CcTKRldrJ8/b3Uy2aNGixdPiM2vApy3MboeY1b9huem625Z3MmkCXCSytBv49Hsd\nRpVHv5rQKTR+lqNMtWB1rwtRN6Tb6TMYWO11c9MeezRqegtLXudgADdvwq1bloA7+ZxOPibOT4jS\nMWE6JpyO6RYndMsxujyBqlio8CbPqYqKqlLkpWae1qbuuq+sBOLIRuOy+H/PkrX7+iIPWlXoPEWV\nUxvAdv8+3L1rx8FBk08tJo/1dU7uD/hoN+Ste4o7dyvu3i24ezfn+DhjPE5J05SyLOt7qTBGk+cB\nxgQopRdar41M1hijAI+aQTHGW5KH5PiK1WJ93W7KNjrQ9W3QmFToMEpSzliQsMQuuJXcWrRo0eJJ\n8UxM0KdVAVolX/GPrfp/53NLXgcHVkE6Pm6K9vs+DPo+ow2P9SpClYd4hSbOciiyRUisLj3CaEAn\nKpcI2O0/q3Vjal5bs+T7yitwfccQHc8JT44Ijx+i9/dQkz3UwR46m6OLFJWnS8WNTV5QFRVlpcgL\nRTKHybT5nihyUmOq5XSVlx2rsnYJ2DVHe7pCpxkqmVpfwP37Nhz9ww8bR634BXo92Nzk+OMud3Yj\nvvFN+Ohuxf37OffvZ6TpjKqaUpZTjCkBjfXp+hgTURQhSmmMqTCLm+zVw8eaoD0gWGz6sqxJdZNO\nS+vrtqXhmg/dwuDlBjCYhRlHoVbSjVYtOy1atGjxpDgXE7RbltB9TTRfNyhpOoXx2DCdlsxmJUlS\ncXSkiCKNUvYxihWdnqZKFP6kop8XePPJwm6tB7v4146Jd44ZsMG1oku+1mE9CKnqkoQaQzfI6QYZ\n/Shnp8jYPshYy1KC8QH+ySHB+MDuBA4P7XBti72etW0Ph6jtLVS/h/YUpqzIUsVsqpinzXUGQbPQ\nSxGJl9lU+aR+zUXQXVlh5nPMeGzv6f6+3WHt7TWWBD9glnok44hkv8tHuwEf3Td89FHG7sM5R0dz\nZrOEskyAGZAAJZZQrfnZmAIoMEY0XVP/L8BqvY0fXtoOSpDf+nrTQenGDbtpGwygozVB5qO8iNQE\nzMYes6nmJFGLYPjTNlSr5vgWLVq0eByeS8E8N9DFbSnXFFswJElBnqeUZcZ47KOUR5L4+L5HENha\nzZ4x9NKSKiuanoUPH6I6PfzrH6OufcRoeIMq3KE7ukayMcAo24xBVSVhNiHIJsT5hP7uCf0HJ4Tl\nGG8+RScTGygkqTGTCUtlsrpdu1Lfvo3a3kGvj1C+gllBPveYTjXTWVM+UfKARfsV//ZlxlLgXW67\nTnF80mxqDg6s3GoGrLyA8cxjdy9g98MO735Ucefjgvv3M45PZiTJDGOmQApk9ShZ2IXx6udV/bdA\n18OaorNMMZ2qRZU1STm6ebOJAbt50xJwtwsBGs8Lwe+QTH12DwIenCjGyXL/YpeEW8Jt0aLF0+Lc\nCXg1Gtr1+06nDQHPZjl5PqcsEyaTkCQJ2N+vCMOAOFZ0Oh79wLClKipV2oX8gw/gO99BBwHq+l28\n6zfwb79G57XPs7MN1UaJkXaERY4+3EcdHqBne3gHD/EPHuId7UFe2DzVos4ZkiE2a7FRXrsGb7wB\na2voMARfQVmQpzCbKo5PGpP6ai3gq+IjbGRdYWZzjBCwkPDR0aKQswk7nEw9Pt4LeTeMee9uyp2P\nc+4/mDOfT6mqMVU1BnIaonUf/frvCqvxgmjGtm6pWRDwbCZ1nu3Y2LD+3tdegzfftNrwaGRN0r7x\n0H6ICv7/9t48xrZsv+v7/Nba45mqTlXdqjv17X5+zzwICIjBGIXBzzjYsiPZSEgIUIxBIkICpAgF\nhUGCB1KUgBIhOUT8YwhBYpRITIRIlODwMAlYgHhGScSz39j9erhDzXXGPa3FH+uss3edvrf79uuq\ne7tvrY+0VVWnzrDPWUfru3+zsJgqnpzGfOPbwmzRXo89Le4bRDgQCHwUrk2AN93P3vXsrd/53K7n\nus7nlrKsqesCWFDXFXUdUxQRx8c5774LURSxta24uxXRbKUuLrdcYs/OMMZQNw3NcgHlEm0KcjtD\nTfeQLEPSFLEWJhcwv4DiHMoLKGdOdJVAEmPThCodurGGtWDyAU1vgMkHWH0f0xxgFrso3UdHbhbw\n2bliOhOWS1mXGLUlT21c9FXGu9a9pV+WUFpLWjRY3y7Kxxvm83WQ3OY95k3G0XnM21bz+BDOzhsW\ni5K6LoEaJ67erdz9IC2tpatwFrD7XamIOE5IkoQ0jchzTZ4r+n3nxLh7F+7etby2X3JnULCvSvpE\n5DYmsq7AtzIK08TMCsVkrjg7F+aLtmzZlyF13c7dn4FAIPBhXKsF3B1ovtmQoiu+i4WlrhuapgKW\n+CQbUEynDQ8fKooi5dbrms9mOaY3xPb72CTBAkVRsDg/Z7kK9mUXF2TvvEM8HqO3tlCjEZJll/3B\nSjnrtjsrL0lY1H0u6h4XTY9SUkqVUUlKbXeoT/aobI+oF5PlQpa58qOzC0VRXq537rbYfJXpvtfu\nGqfWkpUGU3Uy7rwYg2u8MdpiIT1OJzHvzeDkxLBY1Fhb4YTXW7Nd4e1awRrIVke6um+E1jHDYcbW\nVsZolNLva/p9xWDQupzv34eDeMa+nDE8OSWlR6yHqGxIaSKKUrEsNdOlYlFoqkrWXxtg3XSl2/v5\nVb/QCgQCV8u1CPBmEkrX9ezrflvxheXSYEyNtSUu3mfxls9k4sT3+HjA62nE+Z2Mpj9yLsw4pgHK\nsmR2fs7FbAanpwzffRdJEmQ4hFu3kP19l/rsexD6sTzevTwYOBfzYMCi3uW03uFJvcu8jFgUikWp\nKGxCeZpQnKYkudvMhwOoG+d6Lkp5X9ORm+Jy9u+zu8aZhap0AxcuZd75/pBZBqMtFtMep9OYh1M4\nPTUsFs2GAMe0FrDwbAHOcG7nBK0TBoOY/f2EW7ciBgPFcCiMRvDggTteew1GkzmjySHD03dRaoxK\nG6Qf09iMZREzWcZMFopFIVSr2C+0me1+eIOfknQTLrgCgcDV8UKSsHwyUje86to0WqrKdTWCTbVy\nO5mzPMTlRS0jCt3DjrawwyFNmtKIOPdz09CUJYLbnmugyXPUfI6dzy/1mLS9PnXap0l71GmfZTyg\niPos6wEPix0eFju8V+6wWCqKQlguXSMP31qy33cxxGJlES2Ltnb5JojuJptJdsslLEWobISJUy4N\n1/WF2OOxy3qSIVQpzEBrRZJE5HlMVSmMiWka0/lMhfbizCCiEUlQKkXrBKWc+Pb7MeNxxM5OxK1b\nip0x7OxYdncMd/Yb7u413B40ZMWUjClJMcWWOaasXQ/qUjidKk4miqNjxflF21PcX1x126be1HUP\nBAIfjxeShOUthm726DpRx3q5tDiLJuVybK+PSIKIIGmC9PswrjFHQ5oso1QKu3oj/dVrepupbhr0\nYoE9O3NW794ebG1h7t5nGQ2ZRyNmasjRRcrhacrRJOXRpMejacLjaUNVuwb+TaMuWbc7O6smIauB\n8JvZsN3jJuFLfsoSCq2p4xwz2oJmz10A3b7t7nT7tktoOzggi7cYRSn7GkRiIMcYxWJhWC4NReG6\nXrnn9yrnyo1EnGDHcUySRGRZRJZpBgPN3p5ma8tZvQf7lvt3DXcOGrbTJVvxkt58QVRO0baGSFNL\nRGVjqiblbBbz5Ejz8BCeHF6uT4c2we4mr3UgEPj4vBAB7jbEaCcgWaz17sTVoFc03o3oZDRGJEck\nRUQ5t/JgAGPBjkY0aUqlFGb1RnwhireTmqbBzOdu50xT98+tLezdeyxlzAVjjpstvnWq+eah4ltv\naZ6ciDtOm5WVo98X56sqJ75eiLv1vTd5U+7W3Baxoo5yTLoNes9lP52duTvevg23byMH+6TRFls6\nY1+DJcYYRV2nRJET26pyk4+M8TW+La6vtyLPNb2eMBwqBgNha0vY3nY/R0M42De88cDwxv2GZLkg\nXl6QzCeoaooyFWhNo2IKm7CoU05nCU+OhbffEY6Pnfien7cWb5a517/Jax0IBD4+L2wcYVeAu1aw\nn1Ik4kpHRBRKJSvXYkKSOOsmSYTxqCHXJWq5wC6XNHVNYy1Wa6I4RsfxqqG/uAiiiMt+NqadyCBC\no2OmdZ/H9TbvLnf5+gl89SF87S04OWk4PW04OWnQ2hJFZlW2qlY/hX5f1i0zuy0mn9YD+1XfmLtr\n7ddZBCqlqfMc09/C9peurnq5RPLctSHb20O2R+Q2Z1tFHMSgtF7VfTutznN33VQUhrq2VJXtxNdl\nNf5QyHOh15NLNb6Dga8iM4z7FXu9goN8CWYG5QJrlhig1ilNopgxYFpkTCYRJ+eao1XvkNNT535e\nLFpvB9zMtQ4EAlfLtVnA3l3b7b17qUylFJpGd2a6KrSO0LohjiPiOCJJNNvbmu1txfY2fPfBhL3F\n2+ivvA3f+DocHmKrCrIMPR4Tb2+j8hyrFFZrVF0Tzeeo+dztnmUJp6c0bz/kZJHw5nyLX5q67ojv\nvGM5PLSr6Ulq1ejfYoyhqprVhYFvb/h+NgdP3KSM2G7imRehKtE0SY4dWefMqFd9n/f2XELc1hYS\nReQDzY5W3F2FiEcjFxo+P3cifH4O06msxwa7SUcuNKC1E2CfyC7SJoL5mt9hz5CZGdH5GahJe9J5\nTiE9FiIsEM6bERcXfc4vFE+O/ezhNrzwLMG9aWsdCASujmuzgLutJ/1Pb/36yUfGuHIjrTVRFBFF\nljg25LlajZlT3Lsn3L0r3LsH320v2Fu+TfSV/w/77a9jj44wVYXOMvTuLslrr6FHI4hjbBQhRYE6\nPESOjtpM3JMTannIydkW3zpf8v+fwePHlidPnAC7c1WrrNaapmmwtkYpvUq48SVSLTfZGuqudfe2\n2jgBNqMYO0yQKIJB3ymbn4CgI3KtGOdCbZz47u05ofVu37Mz3xlUODlxngf//RG5nNQO7QWeyCrf\nq2/ImxnR2TEsjtqM9/6AgpQJKWc24XSWcjKNOZ0JZ+etAG8mXd3ktQ4EAlfLtc4D7lrB3d9dMpYr\nK/Ebp7di8twyGsJoZNkaWh7cNzy41/DafcO9JyfsvPMO+u2vYp+8i8xmrgvW1hh7cA/z2mdhvIuN\nVgK8XKKzITrNXZvJJIHFAnt4zPJ8ysV5ydEZnJ5azs4Mk0mDUmp9gEsUM6ahaQRr2wHv/v113c83\ndSB797Pwv1eNolYpJkuxI9c6SrIMu7VFUzQ0ZU1dGmqVIKKJcUl0fiZv2kmezjLnbhZpp2X5SUR+\nnKBI+/3y4wV7Pej3DKmp0MUMW04gTrCDIWQ5Rd3jouxxbHscL4WTC+d29i5nL8BwedCEX+ebuNaB\nQODquDYLuCu83RKN7mbdraFczTlgawsO9hp37Dbs9ubs5nP2ZMF4+Tb9s3dQj97DLmYkWQb371Pf\nukdx/5czv/srqId71FZTGU2UFQx7B4zuPSAvL9bzfFVVMMwqDhLD61sAhtms4vi4xlq1sswV1jar\nzNvVLFjVjhr0tc3eEvMJOn5TvilsrrUXJF+yVVWuVlqh0Vpjo4R5KcxqYboQjhZ9DucJR4vLrmxf\nT+xrb303UN+FahXuv/R5+3BHmjpLejiENBNiG6FsDqqP6fUxWR+T9plfJJxPI46O4HTt7m7Llbvu\n57XR3pkhfNPWOhAIXC3XbgF3RbhrFVu7bj5FlrVluvu34PW7hjfuVbxxtyJbXpAvTsgWp6SLt8lW\nAkykYDxG7+wwv/NZZq/9ciZ3fxXz/BbLQliWQioVB/0JaX9C3pzA22/DO++g5wuG/YrbPcPrEczn\nDUdHNVCuXMyKpnHTdS4LsKw3fS/Add1uyJuCcFPorrXHC7C3VrGuRaSJUuZEHNcJR8uIxycxj45j\nHp90Rhnqy98VcN+Tft/9HA7bHir+4q479jGO3ffJNToTIonRZKAH2N6AJh9QJ33mjeZ8pjk8ci5n\nP5N6s1zOC3BXfG/qWgcCgavjhVnAm5nCUeRchIMBbG1Z7tx2x93bhs/dK/jcvQWfvbdEDk/gyROY\nPIHlQ5gcwtmJG4gwHMJrrzG/8zlmtz7Hk8HnONW7zGuYGeglNXqnYHh3yUAfI0aQyRSZ1vRHEXu7\nivs5HB5aBgNDFLmxdsbY1fnK6py9W1rWFrBvvehnAHdjhP4zeBqv2obdXetuM5K22YoLNwgKqzQ2\niliSc9FkHJUZhzN4cgqPHztx9c3KutZmntu1a7qXw+7YsDO2JCkYn2NghLoRaiNoLQyHzqOS5kIs\nMUrloGuarE+lcwpypiWcTVydr29TvVg8/TvrRxg+TXxvyloHAoGr5YVYwN3NOY5XM1fz1uq9tWe5\nvVNye1xye7zkQJ0zOD2HxXk7m/f01O2Q3l99cOBG2Xz+88zzN3hvscsvfj3h0RxmM8NsZhn2LaZU\nZGlCsjMk2b5P8lnB3poQZ28wzLbYAfb2NLduxRwcwGKhWC4Vy6WsyqNcvWkUKaLIZ0dfFp2uJebf\n+7Nmxb6KbK5107RuXD8TWSzo1Wfi3fXeqh2P3eN9zNc3OPGuZv8a1kKmKgZxwSAuiFSDtYJBMBLR\nRAkmSiCK12KZxkIcxaioh9XixH8eM5nB4arJxvGxO1+fIAiXY/r+8G7vzUEjN2mtA4HA1XHtWdDd\njdm7nQcDtzneu+d68t67Yznol+z3p+znU/qzJ/ROD2F+2PoFp9P3C/CDB/D5zzNbvsbDr+3ylW/E\nvPXYMp1aptOGnbElzxQ7txJGWyP620J/tEVkShKzxcCM2FnA7q7m1i3h1i3NxYVwfi6Upaw3Xq1d\nHbArl2ot4G6J1eZ7f5pV9CpuzJsZ7z7umySt+JYlaIFY3E+lQHcEuGna2Rj+SNM2MU9r0Aq0skR1\nRVLMiYsJqqlAFFYUNk4wvQG2p2niuHV9GyFOElTSw+qI5Sx3cd/pZQGu6/Y9eXcztBcL7jtwWYBv\n2loHAoGr5coEeHMT2hRfHx/0ZSP9vuX+Xct3vWH5zGs1e9GCW9GEXXUKsydw9h68995lU6oo3C44\nHmMPbmPuP8C+8Vmmjw54b5Hw1W/FfO2blunUZTTv78P+QcSDz2j272WY7QF6+w55DmoK2RRGZ7C9\nrdnd1ezvxyjlNuPFonU9at2WunRd0N3s7s3mI6+yW/JZa93t9x1F7jN0wzac4MZaENxFTLzKVB4M\n3Gea5y4U4RPxXPazuz1JIIksSWxR8xpO5nByji0rrNagNDbLsFsxdpRRJ+286aoUojRGUqHRKYtp\nxPk04skTVqVnToRFuha3XAor+PX/KAIMr8ZaBwKB6+PKLeBu68mybDsjJYnbvLwAbw0M97bn3I4W\n7BVTRrNTkuYUqtXQdq+APk3ap8HeugXWsjj4DBN9m8lhn7ceRjw+grPzmvncdU4yxlDXwmTiNtlH\nj9pzqevWq+3LTrR2rlClWsvMW7bWtjHAOG7fw9M2ZHh6acqrWK6yudbdUZNF0YYarBG2cs12L6GX\naWoVk/U1e/nlbOleDr3c0utZkkRIUkgSIZIa7f3Dvg5JxLWPJKUwKVWZ01xkNEWEidvPO80EK4pl\npVkshaMzzaMninfftTx8aHj0yPL4sSHPhcFAEce+/KwdOdhNwrqpax0IBK6eKxXgzdaTPkmpK8Cj\nkduYd4cNdwczbkcn7BUnpLMTkukxzE5bM8oLcJK4F8iytVm0yO5yFB3w6LDPtx9GPDoynJ1XzGZt\ni8i6dp7royMnwP48rHXi+/ixc0N2Bbgbl/QXEN24oH+OrkXsR9F92Kb8KvG0tV4u3Wc5mbT1vHEM\nphEW2xHVWNjGEqWKPFMMktZ6NgbiyJJEljiy6MiiI0FHoOoGVRZIuYRlK8C1RCzImdgBizKnLGOq\nCw1R24oyS6GuFMsSlgvF8ani8aHw7rvw3nuWR49qnjyp2d7WxHHEcNgKcPdnd/bvTVvrQCBwPVyr\nAPtWfkq1Mb3dXZd4dbDVcNfOOOCYveI9OD9um+/6Wo8owq7rPiLYWY2w291jsdzh6HSXN4/6vPVQ\n8fioXFnABj9Jqa4106nl6Mi5NePYuTZF4GSVXP3okTtnrV2HxH6/tcq8RbdYXHalp+nljNinZcO+\n6u0Jn7bWXoAvLlr3PbiRkmUVYVQECWxnrinWaLTRXcq6JxZf++ObjtUN1AXMZ1h/VQQ0Kmbe9Dhr\nRkzq3I1BXLZrMhhAkgpVLSwqxfkMjs/g8RM6FnDNkyfV6v7q0vvrxve7NeD+/55Xfa0DgcD1cOUx\nYN+4wMf3/H7p3XnrbkIYVFUg5QQWZ23j38nEmZ/DIWxv08QZdZTRRBmmN6DpDzF6yAVD5jajbtSq\nbMgPcvfDCRXGuGSq6dSJwnTqBCLL2ozsXq9tX9htO+jjft4I75am5Ll7b75cpmsJ34Ta0M0BDJuJ\nWH69T07c5zqZtMf5ubsYGo+dAHvLsk20ErQoqtr1Cy8qwRYaKVJYWqRua49mRczhPONwrplV7efv\npxXVtVt3fz7dVAI329f1H3eOFb1qgdpmXkObCOY9HjdtrQOBwPVxLRawt3i1bi2jotho5ScWKQtk\nOoWL07b572TiTNHBAO7epYkHFFGfIh5Q64xKJdQ65YKUhUmpjMKYmvfPFRaMURSFrK0yn0g9GKxc\nnisBns/bxgvdvr8+ztttR+hd0L5doo8D37TGDN0EpK4b2YudjwOfnTnHxmTi1uDszC3vah7DOq4e\nxxBHsvoJ87kwmbpBDKaKkCaDWiPWINYiGCZzzeOThMenimXVtnkeDttwsc+419qdn/8ulqWbqKR1\nRJqq1VAHRZa1EQ9o65K7Mf+bttaBQOB6uFYBzrI2lGvM5U5HemUBM524XdlbwLOZe7LhEO7coU7G\nFPEW83ibolYUpbNqL4CFFeoGjLEY0wCrYC0xToCFohCmU7kkwMvlZQu4rt1tXaHtWjmbv3c85OuW\nhN0knZuwMXfF92mlSItFpwZY2uur01Nn/XoR9s03fEe0NBWyTDg7cxb08TE0tUZEI5K4i6PVZ3wx\ngfceCg8fujW8dcsdReFefzJpxxP2+26turXJxqjVfF9NnrM+ugLsz6/bNvWmrXUgELgeriULuitU\nfoC9HxEHKzdlZWmKGrss2iBrFGHzHNsbYPpbmMGYRTNgUuWcLyPOL9R6I5/P285FVeVmCKepIU0t\nTRPTNK51ZJI4kR0O3SbsZ8Z6F/lqmuE6ptvNyu26GVuBaJv/P2vz3ZwOBO19X6UN+2mlV92OYMb4\nnspurnLTWOZzy+mpXVmr7vY4dlOwksQSx5YkMeuwwWRiV2Mro9UBIgYRw3xuODlpOD42GCPUdcJi\nkXBxEXXmAcPOjjs3f7HlLhpknXDn4/9bW20Ncre/t/8uP23Nb8paBwKBq+daGnH4BJzEDcFZl+96\na8lZSR0BLorWJE0STH9I3R/R9LaZTVPOFzHHU+HxY5c09eiRew5vidS1QiRZDWeHohCsVWtLfDh0\nm6vPwB4OLyfTdJOq/NxZP23H461lnzi02W7Tu69val1oNyu428/ZxV4tYFguGy4uGpLEkqaWJLFo\nXaNUg9bdw1CWluXSrrwVCSIZkK0+wxqRirKsmc8r5vMK0BTFgMlEcXoarYd7jMdtA5goagUY2tt6\nPSfSXoCzrPVuwOWe1F6Eb/JaBwKBq+FaBNhbDj4O7ONnvttQ00BtLE1ZY5erILEPuiYpZjCi7m1R\n9cfMZ8LFUjg+hnfegTffhG9+0z2ft1qqSqOUIsti8txiraGuzWpgu+837TZkbxn5c9psMdhtxAHt\nRhpFzlra3m7v45O33Gzjyxbh03hVN+WuEHVd9l6AXTMOg4gTThGLUs6KdWGDCpEKJ6w1UGOtwVo/\nDKMH+Ox2gAI3OKPAmCXWFohETCZCHGfkuVun8dh9teLYrblPuPNJ1t3EqvG4/Y6sm38kbXiiG6LY\nfO9P41Vd60AgcHVcqQB3Owf5xhVe4Hxm6TpuKoLS6vIdlYJII1qhVjWgUeSa60edTd1bp+04QKHf\nl9UEHLOyWIRRv+a77pV85nbF68Oag8iyW1kGM4htQhzFiI5JlUaLwiVvtdZt933keduZSeu2JKko\nnCu8O3jig1zTr8rG3O2VvDklaDNGrrXFGEPT1KtM9aZzOOF1P0u8uLr6I7U6NO6rKrgku0Xnfl64\nE6wtqOsF1mri2B1pqteDFpZLdz6jEdy5c7nPsxdgn93uPSJ+tCK0eQx+HW/KWgcCgevhygS4G/t7\nlgB32/3FIug0QmWrlOJOENHpsEXphiSCLBWyXK37lwt+vAAAE29JREFUcGRZu7n5aUSjkbNwtJZV\nOYll3LPcG0y5N7jgoD9nKA3DWUNPBN0M0WqAUQNUFWOqhKrSVFUrrt6N7oXXx4C7ZSo+fL1cXtUn\n+cnnaWvd7RTW/bu1JA113dA0XcH1v/sM9sXqWOK+msnqKHFCbDbuV+NE2YUcjCmAmas7LlOWy5TF\nQl/KF4hjV0o+HF4OIXhvymBw+Xqw67XxlnMgEAhcBVduAT+3ACsnwJKt0qW96omglEWUAdWQxpCl\nbZaqF2BvBde1E0VfFjQawd6euCM33Grm7DVHbJlTtKnR8wpdCqg9JG1oUo3UFrsSX19G4zdbH/v1\nr+0FuZsNu1y6DOubxNPWelN8/ZEkLizQNF5ovfVa4ETVW8MLYAZMgYzW7ewtX28lz1f3sziBjgGN\nMQXW6nVoYLmM1o1UvAXsk++SpG24VpasxxcOBm1jDd+gxSeUeQs4EAgEroIrtYC7v3c3aF83W1Wt\nEBsEG/umy6N1136pKpjPkbNTePyQdJ7SLxLGEnN7mFDdiVAS0xjVjpyTkowFmV0wSpbs1AU7kyXj\n+YRRechWeUivnmwU+CrIYkySoipB2aQz+agVWj+zuNe7XPe7OaqumzH9rN7Ar4r11H0f/vPyZWd+\nnbvx8aZxVmrTKOraK5i3grvu6JrLout/trFiJ9pznFgLzj2dABFKuUzpKIpIEkWvJ5eyob2XxB9+\nUMRi0ZYq5bk7u67g+u+Fdyt3PQCv+loHAoHr49rmAXt8JrJv0uBjaJVRNHGGGYwgGrfBtrp2dUYP\nH4JSpPQYkRPTI9oaMMyH3LkfYTrZtvF8QXx2SHz6hGx2RP/0mN7ymF55TlZPiZopSNXWIY1Ga7NZ\n0j6qitHkayHJc3ca/X6btOUF2McFu12f1p0TO80ZbsoG7DPe0/Ty59F177pDU5YxRdHgRBQuu599\nE5UIZ/22lq273d93uXp8Qfv1jRFJ0TpH6wF53mM0itnZ0ezvu8mVt2+7o1vv6zPefYzfr7FPHvOZ\n9t2M6Kc14rgpax0IBK6WFyLAvhyp6+KtjaKJU2w8hGy77VlYVa4A9OFDWC5J+yOi/oh+f8hoVHN7\nGFEMexDp1vI8XKLefIIqvok+fgv93lvod7+NPj9B2QZta0jithF1XbfFwb0RqsyJqNcC7DdfL8B+\nqo/P6obLArxZ/3qT8CEGaBPkNku06looS8187uO6XlS7SVh+IG+EE17/U9OKrxdeL8J2/RgnwD2S\npE+W9RgOhfFYceuWE2Avwj6E4TtceS9KHLchhm62c7dVpndJhyYcgUDgKrgWAe426e/WhUZRW85h\njGCTFJsMgG0nvj69eLFYZ8Do+Rw9n8C8T1pOGNRnGHsMSiFYlDVwdIgcvwWn30bO34GL92B6CPNJ\np4t+sjZ1bH9AnfZpJKc0KRURKL3ehME9xFu+vi7U2rZntL+QWC7dNYNvQHLT8B8vPL0e2n0XhLpW\nlGVEXVuaJqGus1VCVkwrwD7jWdNmQLfZ6Q7vdk6JopQ0HZGmA7KsT55n5HnCYBC7mR27rOuBt7bc\n0W0t2S2f8q70OG5nV0M3jv1+93MgEAh8HK5FgL1AFStPo8+E9cJcVSDa+aalPwC1aOt7/B18v8jl\n0rmktUZiVyesYmemSFNDXSGzKZydw/mZy4ZqGqee3mz13Thu34Y7dzD7tymG+yyG+yyiPRa2jyEh\nkTbxqpv5HMfuVFxXp8sDB7qDHG4qXpCe1RXK/c/FdJWKmM/zVemWF18fA45WLScjrDWAWfX4boAU\n76b2z5llMbu7PXZ2emxv5wyHKcNhRL/fCuemxeu/i77FZDeE4F3LXboCDM+u+w0EAoGPyrVZwL58\nY91fI2lrd7UGrELSxM2liwqndt7M9Cbl2l+98glXNVK7g7Iz1qZrsnhTZjBwO6+P+25vw927cOcO\ndu+AQu8wVWMu1DaF1RgiYmlPAdqN17eoLEvf+vLyaXU7Jd00vEXYpTu6z4cJQCEiKKVQqkddRyyX\nOU5cndi27SYjoMJa73I2q8MN2nA9oZOVAGsePIi4fVszHivGY5cx75Orun3JuwLsww3dXtbd9ySd\ni7HuBWS33jsQCAQ+DtdqAfuYmbc0lGotSNsIizrhouoRS00Sj4lHt4j3p4jvuK8UMputzWnxBZ2+\nqNO3KPKCOxi4NpaDLZr+FnU+pE77zt08GCG9fSTdp4n2ODcDzsshE9O/FK/suhnbtpltg//5nHWt\ncNiIPzgT2LvllXJ3UErQ2qJUjIhGKdM57Nr6VSrCmBJrNcaoVUcs3600Jk0z0jRlby/i9dfh9ded\nc8N3sooi5zQ5O3NrlSSXE6f84ZPH4HJL0e53oGsx+4usD2pBGQgEAs/LtSVhefEqy7a3MrS6aWrh\niIhimXIWD9iWu4zvabZu7SIYlDUIxo3P8YcfZzSbtXPlisJZuXt7sLdHPRgzi8fMkm1mDJiUKZMy\npZjlqJMhyoxgOmBhM5Y2YrmxkW5aPz5Bxw+d9+7mIL5Px7tyvdu+GzP1gpfnwmCgmE4hSYQ0VSSJ\nF2C1yjJXWJtgjGCMXV+49fua3d2InR1hd9dNP9rbcxGG7vhIf9Hkcw+8Y8Xj18537/KlU/49KNWO\nrPQC7OPbXYdLIBAIfKdcaxKW/73bKcpvdE0tLJcRpyjSOOL+boS+O2YwXqJMhTQVYio3eeHxY7dz\nTyZOhN3EhVYRx2O4fx/u36caHjC1Y07Z4WjR58mx5vBEMZlGRCYmWsToNKYRjUFjOu0zNy2kbjOJ\nbmZvl5CM09J1OW826nBj/3xmubC9DYuFpt+36wlVIOvP01qNtYIxeh1rryrY2REePFA8eKDY3W1L\niqKoDQ0sFu5r0Z1BvSnA0F5c+TGFvrysO6ijadp4cadXTCAQCHxsrtUChnbT8re1rj6haTR1rdE6\npr+TMeqPGe1bdF2imwLdlFDFSBVDGUE8gXTmjlXNsK0qGO9gbj/A3n6NaW+fk3rMYTXmUHIeXcBj\n4KKGaA5x1dbyrttPd/oWw2UXZbeLlydkwj6drjv6aQLsGrK45hhlKdR1m6U8GrnHtd8blzntPQ8+\n2e3gVsPnPtPwuTdKxtsWFbme4rURpnPFdKYoS7V+vW7/Zp+X4F7HogTiyJLEYA2YRmhi99r+gqt7\nQRZKjwKBwFVy7XXAm3STdroiWJYuZqcViFEoE6OMINNtpAFJc8QuXcJWVmDrGls3UDfU+YCaXarJ\nLvP5iLMy56zSnK/aEIq0NbzdRgqbgyO8APsYX7cloT/fwPPTXetuW9Jer/3/9nZ7dKdJzefO2eEb\nZfgLuVFW0q+mpGdT4rpBJTGSRDQ2oZ5nzOcZs7la5+ZtWrPd37UYYmWRyKAR4khhUWvB72a5e4eL\nz20IBAKBj8sLF+DuNBn/uxfg01MolgAasYJYjaq2USZHpbsQ1ZC7ndg2FmsstjGUxCzJWF5kLOqE\nWRkzKzTLqt2Eu0PWN2uTu67mbny3m0zkCSL8/GyudXcOr3fr7uy0R7d2+PQUjo8vW67Wwigu6dfn\nZKeHJIsK8gzJMkrpUc0ti0XEdBFTFJfdyd119d+JWFmMbiCu0Whi7crjvLvaW98+1SAIcCAQuEpe\nqAB/UOu+qvI5VrKuGXXinKDUwJUuKSBuRdEf3Qzlbm6WMZ3xh+ryeTxLgLtlRc9yOQYR/nCetdYi\n7XCLft8J7+7u+wXYGLemvouaPzJr0HWBmcyoFiUUDeSWQmmWy4r50rAoLtf3btalg2vnEWGJrSHG\ngBaM0hjdWr5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xsSlgwzCMjKi4D5jKN1ZTAPD441rS5/j001omKneXL8N24jlf0nE7HQBw2WU6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\nSUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763332eb8>"
+       "<matplotlib.figure.Figure at 0x7f024e9ba358>"
       ]
      },
      "metadata": {},
@@ -1115,9 +1070,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# We have already performed 1 iteration.\n",
@@ -1127,15 +1080,13 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 78.2%\n"
+      "Accuracy on test-set: 73.8%\n"
      ]
     }
    ],
@@ -1146,15 +1097,13 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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v1wshBDY3N9Hv9yGE4N1Qp9Ph7DGDwYBEIoG9vT08ePAA6XQa0WiUS13ow6Pd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\n1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AQYMGATByZOqMU3379gXghhtuSO7b3Drl1hQXX3wxAPfccw8AvXsnZl174IEH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\nGFRoiojEoEJTRCSG/wftSC5FFuLBNAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763332e48>"
+       "<matplotlib.figure.Figure at 0x7f024e9b3e48>"
       ]
      },
      "metadata": {},
@@ -1168,15 +1117,13 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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UHlgBfz1bf51DZhAhfLp5coCbHLC6E9x2a+3mppuPVMJs09MCpAxBl+DkxPGZ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CyxdsR2W9O2012p0mYDnQHbOXxn8LmLBv0JntyzXMvwcNXiCeS9xON3APxcN+pTAHwYfjokXuXW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\nLkHK/8ynkaZ77j8+7xw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iVAh8uwDp2ztWvBQIO3eWfh9CVbZgQen/oeqlOok76Cgq2KGxpyApxXt6E2d1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\nSUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763399d30>"
+       "<matplotlib.figure.Figure at 0x7f024e845cc0>"
       ]
      },
      "metadata": {},
@@ -1199,9 +1146,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# We have already performed 10 iterations.\n",
@@ -1211,15 +1156,13 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 91.7%\n"
+      "Accuracy on test-set: 92.0%\n"
      ]
     }
    ],
@@ -1230,15 +1173,13 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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1J9L5JIzP84aRaJK7Api6PKjTEbnjPB4P4vH4bf06hAWDsrDp5FkqlVCtVrmH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\nTkSuQmCC\n",
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KOC7Yvw6JJoEPatonK12Ogpp9pZltFZw4mvnngaH+haV4YhlxBJVuzc3sbDOr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\n8P+WVeJogJBJeAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763d02208>"
+       "<matplotlib.figure.Figure at 0x7f024e83e0f0>"
       ]
      },
      "metadata": {},
@@ -1259,15 +1200,13 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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r4X4rrNfCag11LVxfJxtMUx1aqJsbAnm2Ile0efYCJl0TQjqn3Ep+bB4RnF+b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gBTjvv0l4dHPZfbyZGLnDw3DF+iHDlZTklwdbZprAQsASue3hvawaarnUpHYZpDSEb99lY47AyL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\ndg3rtMMAAAAASUVORK5CYII=\n",
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HsdONbTmndsdgMgMX36XJgepxfI9AOt75TFZvljBIjr0adg4G2dVX12SOS4cQHaah+s3U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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763db19b0>"
+       "<matplotlib.figure.Figure at 0x7f024ec81ba8>"
       ]
      },
      "metadata": {},
@@ -1288,31 +1227,29 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 957    0    3    2    0    5   11    1    1    0]\n",
-      " [   0 1108    2    2    1    2    4    2   14    0]\n",
-      " [   4    9  914   19   15    5   13   14   35    4]\n",
-      " [   1    0   16  928    0   28    2   14   13    8]\n",
-      " [   1    1    3    2  939    0   10    2    6   18]\n",
-      " [  10    3    3   33   10  784   17    6   19    7]\n",
-      " [   8    3    3    2   11   14  915    1    1    0]\n",
-      " [   3    9   21    9    7    1    0  959    2   17]\n",
-      " [   8    8    8   38   11   40   14   18  825    4]\n",
-      " [  11    7    1   13   75   13    1   39    4  845]]\n"
+      "[[ 959    0    2    4    0    4    9    1    1    0]\n",
+      " [   0 1109    2    2    0    2    4    2   14    0]\n",
+      " [   6    8  914   20   12    2   14   14   36    6]\n",
+      " [   0    1   13  950    1   15    1   10   13    6]\n",
+      " [   1    2    3    2  919    0   15    2    7   31]\n",
+      " [  10    4    3   56   10  750   16    7   29    7]\n",
+      " [   9    3    4    2   10   13  914    1    2    0]\n",
+      " [   2   10   20   10    7    1    0  950    2   26]\n",
+      " [   6    9    7   42    9   25    9   13  843   11]\n",
+      " [  11    6    2   16   41    6    0   30    5  892]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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BgW1mZpY5FrgxIhZ3LYiIi6vWPyxpMXCbpA9FxKJ+jlfXk9cd2GZmlq5BdGu/dP9tvPzg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\nm5mZNYD/Dy0JOPxBG9Q8AAAAAElFTkSuQmCC\n",
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cgM2sUdwFYWZWF8FgSyKwA7CZNYpbwGZmNWpJF7ADsJk1jRjwOGCry+w98n7bRkfzp+T4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\n/wfJ8CJtZ+lFxQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3763c9c6d8>"
+       "<matplotlib.figure.Figure at 0x7f024e942470>"
       ]
      },
      "metadata": {},
@@ -1333,9 +1270,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -1384,9 +1319,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1398,9 +1333,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

From 92d3b3cbc95c540f657230163055a1bc0da6d9f1 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 14 Dec 2017 14:25:39 +0100
Subject: [PATCH 31/61] Minor fixes.

---
 01_Simple_Linear_Model.ipynb          |   72 +-
 02_Convolutional_Neural_Network.ipynb | 1265 +++++++------------------
 2 files changed, 382 insertions(+), 955 deletions(-)

diff --git a/01_Simple_Linear_Model.ipynb b/01_Simple_Linear_Model.ipynb
index 00ae48b..a5cf611 100644
--- a/01_Simple_Linear_Model.ipynb
+++ b/01_Simple_Linear_Model.ipynb
@@ -321,7 +321,7 @@
      "data": {
       "image/png": 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zh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f025779c550>"
+       "<matplotlib.figure.Figure at 0x7f3cdbdd6080>"
       ]
      },
      "metadata": {},
@@ -516,19 +516,9 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From <ipython-input-18-1b869074280b>:1: calling argmax (from tensorflow.python.ops.math_ops) with dimension is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "Use the `axis` argument instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "y_pred_cls = tf.argmax(y_pred, dimension=1)"
+    "y_pred_cls = tf.argmax(y_pred, axis=1)"
    ]
   },
   {
@@ -961,7 +951,7 @@
      "data": {
       "image/png": 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0u7Vqxaodn61WpnyGGX4L7IQTTgDg3nvvBaBp06aRYk+XMk0RkQhUaYqIRGBR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\nQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024ecaacc0>"
+       "<matplotlib.figure.Figure at 0x7f3cdbdb5748>"
       ]
      },
      "metadata": {},
@@ -999,7 +989,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 43.1%\n"
+      "Accuracy on test-set: 21.4%\n"
      ]
     }
    ],
@@ -1014,9 +1004,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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PWgDfpJHHB4CPgQUishgYhRdtjwdWA0uBR4FZukOCtpBewGI/rB9J/O1iVZWRMnbO/QL8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\nEaCtf5GkxDk3GhgNICLDgE8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v3x+Ap59OzErRqlUrAFauXAnAl19+WWffF154IeN12GfttddOvnfzzTcDcPjh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\nb8i0bzekTQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024ecaa3c8>"
+       "<matplotlib.figure.Figure at 0x7f3cd33d82e8>"
       ]
      },
      "metadata": {},
@@ -1047,9 +1037,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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xsSlgwzCMjKi4D5jKN1ZTAPD441rS5/j001omKneXL8N24jlf0nE7HQBw2WU6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\nSUVORK5CYII=\n",
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IrtiYPloq39Xqqkxq+fvvf9vvOSw4s/4wixZRFqsz+MwztaypSfek34w+4KE+\nfTZtm2cbx/ZlnwJbBgCADd7AfJi9A3fH/E8DAJ55RldPmZIewt+nqWlS+/MB+P3i9DNbdLQ5lVt/\nsC/QvfcEW7D19fxH/r0vvQQumGdXDdLcfIQvJ/hjPwoAqKvr2GB9aWNTwIZhGBnR6wo47sWMazb6\ncwBg5crCbQAdP6zJqM5Cx+JyAGmtOHWqKmG64kKl8Uq9Kl/2JFMtU7WxpsubeujMxiFhby8AHHOM\nloMGadnQoFNutYZOYGzypcrk2bNV+c6b1/78VCVUwIycoPLOo407si+VUPgMj+MHSn/vbF+2rPCY\nh4OJzOnX5TNLf6dz2gKcOrUy2TeMuAiX82xfoPNnOFTAfMbS/gV+mBIth/8AXPdhAMB0P+qF5339\n9XTPSm9u9nH0pY1NARuGYWREjxRw2OMdx9exVqdaaG7WMoxEaG6m6vLOtUTxstr3cgphnouBvlR1\nRjVL5Rv2bv7KT7O5fn3hvcUxgqz5ypHu2HhzkYlZ6OtlT/GZZ2pJRZbaK+yJH+1L/V1WrdIl9hKH\nNl6zRksqXyqY+F7L1cbdsS+//4ogz8wFY/xGOtevuEKP8SqXzx5bYeHxzvmNSV+Hjmtety6VvRMn\nqmH5O+bNvkAaPw2kUTeMdeb/4gk+J9OkkRpX/cLqwckxbDHwu65fr31C/J/fvPl4AMDw4ccnx1Dp\nstV2ySVaDm7TuOw3th2W7Du59gMAwH0PqB6l374vbGwK2DAMIyN6pICLjVahaqDSZU1E1bR1a3gG\n+myogGuicocvRwTH6L4i6rtkLZjWhumeCxdq+ac/ackajKo59o+WI92xMZepMsJ17Glf7HvYm5q0\n9VFZqbYeOzb1OzY10f6H+Otqy+TnP1e5UlOTRkxw9Bbvia7kvNi4K/blMvedMSM4wQov5Wh0/6Bz\nkWoqbDXQ1wus5JV9STk+NdmXzzPVd97sCxRGecw5QSOT3vct2YE//L+64WH/T3r33bpfEGw957LL\n9AONwGbXrbdqyYdwQtABxH6kr98LAHj7z7UJzrbF5MsvT3f1zYvP3nILAGDzZr23OMS7FJgCNgzD\nyAh7ARuGYWREj1wQYbOKn/f41lVHQcyhnK+r0w6G+np1qs+dO6zgmKefZpMs6MHwbgnn1BUxY4Ye\ne2718wCAl8acluz56quF9xA2zeP7L1e6Y+NiYWiEzehVq+ju+cCfS228eXMYY/OeL+kCYlggQ9YG\nJXuuWKHWZB6CAAAgAElEQVSuCzYzqwtH1Za9jbtiXy6zI4wdRQDSWCX2KiW9zMcBSFvNdIcp1D38\nLejSoevn8GRP/t/QzZQ3+wJpiCIAfDDLd6LHzfrvfhcA8Ibf+TC6GQAMuO22gkPYZclf4ajnntNj\ngtMN9D1/r/nef0YOnsYkzOwdBVI/j+9tnTVLgwvpgiiljU0BG4ZhZESP3u1hYDLVAgP8mfwiDKgG\nChOZcNvGjaoAOJyYam3RInYChQMxCjuILrzQLy7W6mrzhFQBNzbqcUOH6r4UK3FANTvpgPIL5+mO\njdkRGaokKlMqsKFDOaxby5072aIIe0e3+JLhf23RclOy5549qig2b9abyZuNu2JftiySZzeMKaOS\nYu/mqadqGT33hQMqaM/zAQATJ6riZchU+D/CVls6DLfwnki52hcoDD195BEtk//bc87R8sUXAQCT\nuQM73oB2maMOo63ZJJk/X8sRQWf9L38JAKi9/34AafBqYjjGvQFJZq8PxqjyPcQr9r54hk0BG4Zh\nZESveTdYW7BSYqXF9VQVoTpjgPvNN2t5XMuzAICfbdNk1ml6uffSgxK/pKq0aVVeHXvZ8N2rw7tS\nVbdrlyoM+p/jYZB58KMBnduY60PxwO9IFUKbM51nba22PhYsSEPLmhKBy4EylALUEe8Hd6XNlV27\nRhRcL4827si+VKSJaHoyUMCPP65llMGFixRnYShWdbW2Pq68ckjB9diCYSsCAAav92ktK/RmPrhS\nW3j3anRVgSszD3BA0EMPaTlokKbevIAjJfxAluerzkqO8ZFpOMPb/9grtaQN1vgBV6HS/t73PgcA\nOMu/XKawKcFmdjg23P9I/L1fflnLvniGTQEbhmFkRK+/02O/SWVl8f0A4Etf0vIzYzWCAafOAwBc\nfAhV7nJfNgVHsQ/UR8M3aL6+5ytUNYc9roBePPbX5EmVFaMjG7PHPWxlMCkMlS/TdV55pZbsvL86\naDmsXq0JTBYu1LK1lWn/+DuMTXf2Q5j7k41p31jFjqv2z2WYjSfMHA4kknTWqepP5BD8sC/kuuu0\nnDNLI1HSER9M6h44eBct0tI7IAfs3AkAmDfvPACpS7PYMPRyhiloyZbPXQAgTfl5y7XpNg7d5kzT\nNBcHCAGMmEj/Mc4+ey4A4JprNOUnf7L7ZkSZlYCkyUEb0sXfF8+wKWDDMIyM6PV3O3sK415aqrKw\nhzdRvr6K+curWR8wITt9kGEyHg3KvPRSr8L2au23y19v7tx0z337NGKCtV9HNVneVFpHNo6HzgLp\n0FW6wFiyI5nqgr45IB0uTtU2caKmWKyr0/Lpp99Od/YxrPTx9wcb075UQGxZtBurDKRNCibj8WEK\nA7zC2lJ1EoBCv+6cGT6CdXNhqMSOMUcBKLTVYF78xhu19D/yJJ9V6dhjB7Y7hqq7HGFrjT5xCtHR\no7Q18NpWfQeE9mpq2u1LOrzjJF4+NAR1yTFVVaqG+bMk/SJrG7QsMrMsW4Nx+gRiPmDDMIx+RK+9\n0+OpRTh6iLUGe5A/W/tCetDdvhvTV0/paCHG+rKGOzq4kvaO/uRe3xP/pF7w3Pm6vG1bEvGXqDsK\nlr6o0UpJZzZmzf3tb6fHMBUgbcB9qHjT+NIwDlgTsn/4wxrjyw5qJqE5/fR0pBbzofAe8mzj2L7x\nSEOs9xIpnLWRBvS+2WTZB7pu9gqM4cEA2s0L9WKrKl8/XyQmTwiiTGhAyjM2Yfw5qrzC3t8oyHKC\npouTnW9pVi3IOGcGlyjse+CIzNZoPVvI6RgATuHEPD1fmedb1Q2+KU7HPpCEnzzjo7Foy3jihlJg\nCtgwDCMj7AVsGIaREb0mruPs8YRNr6QJtnBZupHtYt/GY2hUY6O6HHbv1jKc5y05z83/qGWUnSQe\n+hycvsNmWl7m0+rIxjFhzuX6eg7jVn/F8uVsvjGU6n5fbkkPgjZz33xTO9tWrz4dQDpUNpx5eos/\njE3GPNs4ti/7v9j6n8zmf13a2ZP4uehW8Mletjh107DJPXhX0HHp/XHv7lV32cm13uXg3Rfv7j0q\n2XUwzx/3ENGH9BF1QdADUu7wfzl+Tp56SkuORG5tDdMPMCy1soPyFABAVdWJyRF0ef7gDm/bO/y0\nGkfoLMnhNB1PLNM0PjQ1TVyQ9xk2J5xhGEa/omTuZWZ945DXJHadK4BUAfvq8O+u3ISQFxs1mD1M\ngnHaLF+jNR2p5Yla6722XtUE548CgFWr9LwzZ1YVXC6OnQ/nBcuDUiPxUElSqIbYJKDCfdOX7Oih\nigg6lpL0iPqjcXALh3760aIAUkXDlgmHxsYKJ482pl0Z1jV5gu85CqXRAw8ASGczPPzppwEAo/fp\nszxoij7Db7SkHZeL/TN6vubiweDhhf+Gg5/7Zbpw111ashn3pv/9/JTiFdN1yG1e7BvfWzxEnoMh\nGEYGAG1t7JTnM8sZRbyahb4DZs5Mz+uzW6ZjnvlgUt7ecEOy75N+dDI7AGnqvnhPmAI2DMPIiF5T\nwAzViIfvMbSM/rT3581JDzpBP9N/uPpOLak4HnxQS/oeAaD6elW6tedozc8a0wuRglGi06dXFazj\nPVEh5m24bGxjQjc4Q3vCmjr19TKEhzFVTN1Hn3AoWbmPNmMYNE9Vy+QoQPvhz6F7NLzXPNg4ti/F\nEn3qW1r12Rs1KlWzA7zR3/HL7/sHcoKfDO69s78AoDCsihFQh1VT0UUxfD41I4C0+UGpGE1NTddw\nXqAt+VX5v0n/a5zMSaGd6Avm86nNrzPPVN982Lie3PJb/bBkiT/EH+N3emlX6mdny46Kl67+vnhP\nmAI2DMPIiF5/p8cqgqqJncRhyjjuE+a3BtJJT1tb1/jt09udn0NpWbHFQxsBYOnSwoTsFA8cDhlP\nl5QXaAPeN2tstgb2cISG7hWVVdEy9w2llKqEoUOnAUh98K+/rmWowDm0PBw6qvfgr5ZDG8cDW1gy\nUUwYZTLm+n8FAAz20+YwJ86Em24CAIz2jsW/vjbNLvN8PdOjqqKeNtz3ffjk4R8EI2kShfTJT2pJ\ng/rRMRv8/1Ve7EvFy//FOJlQd57hsWM1SorPf5hQCsuiKaJO0UiJty78awDAV4OUra2t+sNysgL+\n/n3xnjAFbBiGkRG9npCdtQd7FFlS5TY1hb7GOL6PbC3YHiazZg3JeEH6HukLoy9J0Vp05849/jxa\nlbH2zYtqILGNCdVnkjSmKEwhyeHdHMbJ3yDIYoSpAICdO7UFUV+vF6btw9Dr+JrcRmWTJxt3ZF8+\nw1Raodrnc32al0sbvHJ7yR90vPcF46qrkmPGjFEFfNQYb/vVvofeZwL/ILj2gI9/XD/wn+DkkwEA\nr/ghyEy2lBfYmohbTHGLmYn+FfqAGZ2jLYePflSXGE0yblUQPUKHrle++MY3AACP+H6mpUvfTPf1\ninrnTn0A+vI9YQrYMAwjI+wFbBiGkRG93gnXURBz2qzbHaz9Y+FOyTJLbQqH816x842hI4yJLz4E\nVpsulZXadGErjsNDGeqSp2YykNqYnQS0NUPA5s9PXTrbt2uoDjskgbd8yWbd8b5Ms8jFc8E1NWnI\nmojaMZxzjs1yuoA4nxyzUeXRxvEzvHx54fYw1C7p9PVxkLUXXwwA+INfvcMfPCwI/D/q7LP1w0c+\noiX9aT7krCKMp6KBfSzms8MvAgAs9ofEHbLlznt+ekd2yrNTrl3muQJHTPjOABhaOVVfD+kMy99v\nSHcZ611u3/wmAOALVw4ouG7qegPoAq2s1Iv35XvCFLBhGEZG9LoCjgcJ0NnOsrExiBNLVBdDoFjT\nMQSlcIZZIB1ZuGePHrN8udZ0J56o1VOYuKelRRUbRcT48Sg4X7GkNnlQEvF9UzUwAUnYSZbGn+sX\n27ZN53l7+GEtd+6MhybHn4G6OrUjh3rGgy2ANNpniEby5NrG8T0PHaol1VM4/xo7amZcqcp08m9+\nAwAY91d/pRvYNEuTXafS6tFHtWRiHf5Yl1+e7uvl3ZZDdW6zZ76nq/c3KKDc7Qv09D2hQ4/Z+Tbg\n+r/TD+xwA7Bjrs6ZN8//T6xape+UUaPYOkzPX1mpLwj+//Tle8IUsGEYRkaUzAccl/SrtLQMSfZt\namIsCpPw0E/Jmkx9j+vWhQ5eDq3VkB3WXnSbsfYKYcpE3ks8tDAPiiEkti195PS/hmF7VGhsGcQ2\nuOceKoIwLkgNMnWqKt/ZswvPFQ73pnijqOsPNu7oGaaY5UzTQPq8sW9iwwadnbvBz9ZN/6R3DQNI\n8kdhcpU+9zuqNWEPQyjDCTdWPMPzFt5jnu0LHOh7Qt8Pt96qYXxn7fFhZ2yaJM5g4A6fYGfVKjXc\n9On6nmAY3NCh6Sw7VNJ8vvvyGTYFbBiGkRElS5FCXw5rEybYCX1Xv/qVppNra6Pvd5wvWTtplTN3\nbtqrv3691mS7dmnJ5OD034TJwumX5FDa2G+WN9UQQ9821S2VaZi+k2otHqjS2MjBLirr2JIAUiXA\npDFcpnoIFTDVWkfzZ+XZxl17hrVsa+NM3ozg0ebIQw+N9WWY7pNJfXQkAVN58rzhcPo42VE0/0Cu\n7Qt0zcaLF+t74owztPzaqT7RzsleutJJHzQd+NzPnKnPNVOoUiyHUVP8P8riGTYFbBiGkRG9roDj\n2oK1CeNCQ845R8uGhmkF66lceWwYd8rO5HjmWvo/Q4XA3upDD+3SreeGeMgsoxLoswpjsFnjc8gs\n7TVqlPrXq6u1DHOMU1FPSEUxgFT5hj5KKpi8K7GQnjzDq1b54NQkAb6erKpqbHIMw39pX54/jgQI\nP/cn+wLds/F112mZjOY++c8BAM/6xck+b2RtEJ4yf/5kAOnzzv8Rvh/CsQVZ2tgUsGEYRkaUPE02\n1Wcx/xZrO/Z8xok6wgFBJO6p5Hnp92TiFKD/qYYYJoxeulTLYlMUsaVAhZv2Mhcuh7G9I3yu9u3b\nC/fl7xL6yPq7jYHuPcMzZmh/RUPDhIJjBw1Kj2ELIrZn/EwDB4d9gf3b2GfexLCFv9AP/kGnepzE\nHQNZ+5XzCzMnvdKgET1sHYatjCxtbArYMAwjI+wFbBiGkRF9NlMXZX4xuR83O9gcYVM6DELvKFSk\nv3W0HQgHYmMuhzbm59jGQ4bgoOZA7MsIqWJDh+0Zbk8xG7NTfvi8CwAAw57UWNN511+vG9g7F/Yk\nRyM86HLgRBvl4toxBWwYhpERmc5VyxqfJTuR4s6IsLYq1tFkdIzZuLSYfUsPO5kZUjl6tIaYjb36\nPgBpJ3HD3ekx7BSNZ/QuN0wBG4ZhZIQ457q+s0gz2mdR788c4Zwb1ZcXNBuXloPQvoDZuC84IBt3\n6wVsGIZh9B7mgjAMw8gIewEbhmFkhL2ADcMwMuKAX8AicpuIXBssPyUiC4LlW0Xka52c44UuXKdB\nREYWWT9PROZ0976LnOcXIrK2p+cpBXm3sYgsFJHfi8hq/3f4gZ6rVPQDGw8UkR+IyB9EpF5ELu78\nqL4lzzYWkaHB87taRFpE5LsHcq5i9EQBLwEwBwBEZACAkQCOCbbPAbBfoznnevICncfrHygichGA\nXZ3umB25tzGAzznnZvi/t3t4rlKQdxv/PYC3nXNHAZgG4P/14FylIrc2ds7tDJ7fGdDojp/14F7a\nXeCA/qDTVzT6z9MB/BjArwHUADgUwDYAA/32bwBYDuAVAN8KzrHLlwMA/DuAegBPA3gCwCV+WwOA\nbwF4CcAaAHUAagFsBrARwGoAcwFcCmAtdLK457tw/9UAFkMf2rUHaodS/vUDGy8EcELWduznNm4E\nMCRrO/ZnGwf3cJS3t/SWbQ54JJxzbpOI7BWRSdDaZSmA8QBmA9gOYI1z7n0ROQvAVAAnARAAvxCR\n05xzzwenu8gbahqAwwH8DsB/BttbnHPHi8hXAHzdOXeViNzpf5RbAEBE1gA42zm3UUSG+3XjACxw\nzp1b5Ct8G8CtAN49UBuUmn5gYwD4kYjsA/BTADc6/ySXC3m2MbcD+LaIzAPwOoCvOue2oIzIs40j\nLgPwYG8+wz3thHsBalAadWmwvMTvc5b/WwWtmeqgRg45FcBDzrkPnHObATwXbafkXwk1fjGWALhb\nRL4IPw2Bc25TMYOKyAwARzrnft61r5kpubSx53POuelQ1TEXwOf3+02zI682rgAwAcALzrnj/X3f\n0tmXzYi82jjkMgD3d7JPt+hpLgj6dqZDJX0jgL8BsAPAj/w+AuAm59xdPbgOp5nchw7u2Tl3tYic\nDOA8ACtF5GPOua3F9oXWvCeISIM/3+EistA5N68H91gq8mpjOOc2+nKniNwHVTb/1YN7LBV5tfFW\naAuOL52HAPyPHtxfKcmrjfXGRD4KoMI5t7IH99aO3lDA5wN4xzm3zzn3DoDh0BccnepPAfgLEakG\nABEZX6Q3fAmAi0VkgIiMhjrNO2MngKFcEJEjnXMvOuf+AUAzgIkdHeic+75zbpxzrhZao/6hTF++\nQE5tLCIV7JEWkUr/Hcoy2gQ5tbFvCj8WXOd0AK91tH/G5NLGAZejl9Uv0PMX8Bpoj+ayaN1251wL\nADjnfg3gPgBLve/lYQTG8PwUwAbow3MvtPmxvZNrPwbgUz40ZC6A74jIGtGQshcAvCwi40TkiR59\nw+zJq40PBfCUiLwC7fzYCOCHXf3SfUxebQwAfwvgBm/nz0NVZTmSZxsDwKdRghdw2eSCEJFq59wu\nERkB4LcATvE+HqOXMBuXHrNx6elPNs40H3DE475HciCAb+fVoGWO2bj0mI1LT7+xcdkoYMMwjIMN\nywVhGIaREfYCNgzDyIhu+YCHDBnpampqS3Qr5UdrawN2726Rvrym2bh3GTlypKvlxGAGAGDlypUt\nrhdnyDAbt6erNu7WC7imphbXXLPiwO8qZ9x++wl9fk2zce9SW1uLFSsOHnt2BRHp1emCzMbt6aqN\nzQVhGIaREfYCNgzDyIhM44D37dNyl8/IW1Wl5aGHFm4POeSQ4ts6Wh9uOxgxGxtG+WIK2DAMIyPs\nBWwYhpERfeaCYLN17950XVtb8ZLNZC6HcBvPU1FRuByen/tWV2vZ35vJZmPDyBemgA3DMDKizxQw\nVdOuYArMlhYtqcLq6grXx+oKSNXYmDFajvRzoC7zSe7WrEn3rakpvi/pb2qtKzZubdVy40Yt163j\n9lAKq2FGjaoEAIwYAb+sZUXw1NC2B4uNDaM3MQVsGIaRESVTwPRHxr7HbdvSfTh6keWFF2pJxTvg\nbj/XXijpFiwAALzlpS7dkRfceKOuv+vvk13vuEPL88/XcsIELZcv15IqcM+eLn6pMqMrNm5q0rKh\nQcstfrrG1lZ+ado2zJM9EADQ3DzBlzopwcaN2qQYP77je6I6ZuuFpSlhw2iPKWDDMIyM6HUFHPfE\n70+dHXuslpddpuXA1b/VDw88oOX9OgPIG5vTfMvxpGLe9YjJL78MAJg09SfJtuuu+zQA4LC2TbrC\nO0RrLz0OAPDII7qaftC80JmN6fcFAG+WZFvamOBoCirhWckx8+er0mXLZKWfhpC/04YN6fmpeOm/\n5zIVN+/RFLBhtMcUsGEYRkb0SAGHQ1LjGFEqrdB9C6T+WAD4wvnv6IdHntHyttsAAK/5kAZ2qB8W\nHD/Nl1Moz6iOi4QAUAkOnzIOADDAOyQHtL0LABg/fjCA8lbAXbExvydNESamam3dDQAYNWoIgFSJ\n1tWpLWbMYJkeQ594pQZBYOrUwuvRlx6u4/G8B6pkKm8OfTYMI8UUsGEYRkb0SAEXG3FFGMnAkr7B\ngv0WLtTSOwzbvPKdNnGirp83T8vrr08OGU4nMgNP775byx/9SMuvfrXdPQ3Y+75+WL1aSy/Ppl/y\nhYLbKEeK2Ziqk35WmmStd5BT9QJATY0q3ylTUFDO8i7fnTu1DNzsWL+++L28956WQ4OJwnnc0Udr\nOXZs4T1VlNO0r4ZRZpgCNgzDyAh7ARuGYWREjxqIYfOSn485Rsvt27WMO4oKXBBR7FLVv/xLwfq3\nZlwAAHj44fQQnsePu8AA3+5+17fHB9M1AeC4Wu1sw9PPafnoowXnD5v35UoxG7OTLB7sQHN+6END\nkmPYiXfqqVrSBUE3Azvswt+F7gO6F844Q0t2vhULQ/vNb7QcPrzwHMHPYRhGhClgwzCMjOiRAg6D\n66nCmACHIUxUwKtWaXnmmcEJKLs48ILy6YTCiRrr69PPcZjTJH/MYF7wuefSndmZF48K8D1GVG+X\nXpoe8vjjWrLDKWuK2XjQIC2ZJIeqlpF5xTq+aLdFiwrXs0URDt448sjCdexIpfIOWw78fal4+ZMO\nSUU4AOBPf0o/W0iaYSimgA3DMDKi14KEqNSodKnGyPTpWoZDkRPoiORBN9wAANh15ycApL5NII0y\nm7TiZwCAlh/+EAAwksfedVe6M7P7XHKJlhxL6xncpgNB9u5Nh3qUc9gUbcyUj2wwsKSdqJQBYPFi\nLdkIYGsiDlljuBqQ+noZBcjzUREvC/L2xOqb+8Zhh+VsV8PIClPAhmEYGVEyXcIELgz0j2fnBZBI\nuQ/8WOB6X07ym6et1cQ6bfM+nRxy3AN/BwBYcdNNeqxfP8xLvIF04gLYMfc8AKkq47XpDy2qxnMA\nlTCVKkv6ao+q3pTsu6FWh2Hfcosur1unkrSmhjK5zZ8jVcCMXKCy5m9IFRuqWbrruY7qnLY25WsY\nHWMK2DAMIyN6XZ+wt5u+PyY9p/+QvkgAuG+xat3P+kwuq/1Q4df89vM/8xkAwDR8JjnmWV9S+Z5B\neftP/wQAeGf2ecm+y7z/kzGvcTIZ9uaHw3DzkDaRw32pLplM6MQT/Q7BWOKzZqksvuSSYQCAzZvV\nXukQcQ2lCBPsUPkykoEBJvQfh0OVqZZ5vngYM89lStgw2mMK2DAMIyN6TZfE0+MwZjSe0rypKU0U\ns2CBSqzP+siFcSefDABY6LdT5QYCFXN8ecLll+uH87zi9cG8d9yc7kvVTeVLNdbYqGWsJMsd2phx\ntLTp1q1aMuJh8hlT0oO8bP3nG7SV8dp6nW6Ifl2OYGNyeiD16zKIhPC3jSfeDK8dT0lUbF/DMBRT\nwIZhGBlhL2DDMIyM6LXGdzxbQwybpPPnp+FOs2dr+c6UkwAA3kPg5+RNO+MmB+c5gb0+V18NAPhB\n/WkAgIf9TBuz0qnNEpcDx3nw3jgXHclDxxuQ3j9dEQyjozuB3LdwXPL5yCP9Zz9A5tVXtXzySS0f\neoiZdZqSY445Rnvz4gEfz/iJS0KXDXMpx+6JcDAIkB8bG0ZfYgrYMAwjI0rW/USVRkXEIathesKv\nXeu72XxvD0PMhvmS05SdGk5Yds45Wnr5RzXLEKkwVSJpbdWSIXLxPHXhvGt5VGpLlmhJGzMkDADu\nuUdLdrbt2fO238IvzU7RtJ3BYePThuuAjufXq4puP7NyGnbGjsFigzWA/NvYMEqBKWDDMIyM6DUF\nHIebUeUwIyRVGRODA0iyxzwTTUt8ri8TTcZ4MaBdysq96wvPG56KAwh4TwyVos+U6/MShsb7pO+X\n6SjHj9eS3y/0v3IavFT56saaGm1ntLaqNP3mN0ckxzAJz7P1qnzp+2UrI0ze3pHPP682Noy+xBSw\nYRhGRvS6LqHSYXrC0PcHAMf/7r+Tz//l5SpHwTLuv4JTE5EwW7jPhfja+f8bQJpAvdjUN/QPU7Ex\njSKVMZVi3nySHM5NW7OV8frrWjLVJADs3MkfwM8MDY1CYYvkiivU+mFkCCeapn1oN/p+Q4VN21KN\n857ybmPD6AtMARuGYWRErydkjxUwVVkyJPX2O5Jj6Eo8jTfj5ewTosOLqapO/vDbyTG49loAwLRn\n/g0AUF//177UzaGSo8qj25jLVMt5U2Wxjal06RPm9wuH/7a26kFtbepHP/FEXaZvlseGE5+GCZPC\n63HfMNl+c3ObP59K3alTdX1ebWwYfYkpYMMwjIywF7BhGEZG9HonXDxzL8PD/ETEwCMTk31rfe8O\nXRHVvseuzTePH3xQy4WjD0+O+dszztAPvj3M5nY81xmQTgVHFwQPZZOaHYR5ayZ3NMMHbdDYGMSJ\n4Y++VEMtX669Y6NGDSs4R+h22LNHhyXX1Iwt2Ie2DvtEgVa/Tfel64H75tXGhtEXmAI2DMPIiF5X\nwOzcoQKiItq+XcvRQS/ZhIceApDm+53iRw1Uz7oAQPtZefUgn23HT79c4VUfZwRmLlsgVb6c7YGd\nSFSMxQYR5EGpxfcdz47c2BjG/vGzbqys1C/I32XNGirkre2u09pKqTvSHzO23T6VlbqOo8XjWZHz\namPD6AtMARuGYWREyXzAVD6xvxLBrMVUvpzDd8odGqJ2FuUZp2mg8xYAHvFjj72MveGOzwEAxlXv\nKLwggE0tAwuuHd8bFSNn78gL/B5xyfCwlpY05Wdb2zQA6XdlsqLU58vsRelMJQCVrob/TZyo2Xno\nzw+HFbPlwURAcVpS7muq1zDaYwrYMAwjI0qWIoWJYZp8nm8OTa1d/Ntkn08cKgAAny8d65ubAQBV\nX/oSgHTw7OG/+lVyDOeJG+zLcR/T2ZDxqU8BAN6qnpbsGyeP8acvSNeYZ6hqqYD5/cKBEvwcz9nG\nNJKVlacUnAMI5/VTVXzFFbpMBRwm4+Ew5XguOGLK1zA6xhSwYRhGRvS6Ao4VD4ciE0YiAMCFWx0A\n4ISHf6ArOHcQIyUo8Yok40nmHvJDk99o0LqkPogDpr+TCdnje8yb75fENqb65DDgcDg2fbPx9EJU\ns3HcLpD+RuvXqy95/vzC84ax1jyfKV3D6D6mgA3DMDKi5GmyqYw4IiqcMuiWW7Rsa/tLAMC2vVo2\n+OAHTnPDUXVAoOR8CEXF9VrG8afhtfs7tFOcdAhIox3oi2dM9Hma7wgbN7Y/H5Pa039MRUyfetiK\nOVhsbBilwBSwYRhGRtgL2DAMIyP6bKYuNlWLNVnjECY2qYcOLdxe7BjCYw5mGIbGEkhngo4HSHDW\ni/ULZuYAAAQKSURBVK7YmH2jQ4a038cwjAPHFLBhGEZGZDpXLVUrS3bUxR1qoWrmPh3NxmsUYjY2\njPLFFLBhGEZGiHOu6zuLNCPN8H0wcIRzblRfXtBs3LschPbsCr1qc7NxUbpk4269gA3DMIzew1wQ\nhmEYGWEvYMMwjIw44BewiNwmItcGy0+JyIJg+VYR+Von53ihC9dpEJGRRdbPE5E53b3v4PjLRWSN\niLwiIk8Wu0bW9AMbf8bb91UR+ZcDPY9h9Fd6ooCXAJgDACIyADpx2DHB9jkA9vvP75w74H9uAPN4\n/e4iIhUAvgfg48654wC8AuCrPbiXUpFnG48A8B0ApzvnjgEwRkRO78G9GEa/oycv4BcAzPafjwGw\nFsBOEakRkUMBfATASwAgIt8QkeVeDX2LJxCRXb4cICL/LiL1IvK0iDwhIpcE17pGRF7yirVORGoB\nXA3gf4nIahGZKyKXishaEXlZRJ7v5N7F/w0REQEwDOnMSOVEnm08GcA65xzH5T0D4OIeWcMw+hkH\nPBDDObdJRPaKyCSoSloKYDz0hbEdwBrn3PsichaAqQBOgr70fiEipznnwn/giwDUApgG4HAAvwPw\nn8H2Fufc8SLyFQBfd85dJSJ3AtjlnLsFAERkDYCznXMbRWS4XzcOwALn3LnRve8RkS8DWAOdDG0d\ngL86UFuUijzbGMB6AEf7F/kGABcCGNgrhjGMfkJPO+FegL4Y+HJYGiwv8fuc5f9WQdVaHfRlEXIq\ngIeccx845zYDeC7a/jNfroS+RIqxBMDdIvJFAIcA+gIr8mKAiFQC+DKAmQDGQV0Q3+z862ZCLm3s\nnGuF2vhBAIsANADY1+m3NYyDiJ4ORaaPcjq0edwI4G8A7ADwI7+PALjJOXdXD67jU8pgHzq4Z+fc\n1SJyMoDzAKwUkY8557Z2cL4Z/pjXAUBEfgLguh7cXynJq43hnHsMwGMAICJ/CXsBG0YBvaGAzwfw\njnNun3PuHQDDoU1kdg49BeAvRKQaAERkvIgcHp1nCYCLvZ9yNLTzpzN2AhjKBRE50jn3onPuHwA0\nA5i4n2M3ApgmIhypcia0SV6O5NXG4D2ISA2ArwBYsL/9DeNgo6cv4DXQnvll0brtzrkWAHDO/RrA\nfQCWeh/iwwj+qT0/hfoJXwNwL7QZvb2Taz8G4FPsIALwHd+BtBb6YnpZRMaJyBPxgc65TQC+BeB5\nEXkFqoj/uRvfuy/JpY093xOR16Av/5udc3/o2lc2jIODshmKLCLVzrldPnzptwBO8b5Ko5cwGxtG\neZFpOsqIx33P+kAA37YXQ0kwGxtGGVE2CtgwDONgw3JBGIZhZIS9gA3DMDLCXsCGYRgZYS9gwzCM\njLAXsGEYRkbYC9gwDCMj/j851a+AX8ScCwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024e9ba358>"
+       "<matplotlib.figure.Figure at 0x7f3cd3192eb8>"
       ]
      },
      "metadata": {},
@@ -1086,7 +1076,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 73.8%\n"
+      "Accuracy on test-set: 79.3%\n"
      ]
     }
    ],
@@ -1101,9 +1091,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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AQYMGATByZOqMU3379gXghhtuSO7b3Drl1hQXX3wxAPfccw8AvXsnZl174IEH\nAKhbt25hEiZSBUWaIiIxFDzS9NElQLdu3QBYuHAhAJH1SAAYN24cAGeffXZynyLN0vLZZ58B8Pzz\nzwNhHj/66KMA9O/fH4CuXbsWIHUiVVOkKSISQ8EjzWuvvTa5/dFHHwFwwQUXANCoUSMAhg8fDsAP\nPyTWdBo2bFjyHB+dSmnYZZddANh5552BMM+9m266CYAOHTok922zzTZ5Sp1UxNcQli5dmrJ/0qRJ\nADz1VLrrpoU2btyY3G7VqhUAv/tdYtWYpk2bAsVZk1SkKSISQ8EjzW233Ta5ff/99wNw6qmnphzz\nySefADB+/HgA1q9fn3zPR5916tTJaToluw499FAAZs2albL/xRdfBODpp59O7jvjjDPylzApV8+e\nPQGyOhtSdKkd/xzjiScSaynus88+ADz33HNAGHkWA0WaIiIxFDzSvPXWW6s85t577wXggw8+AGDG\njBnJ9+bOnQtAp06dsp84yZkePRKrud55550A/PjjjynvRyMaRZqF98YbbwCb9mjJFR95DhgwAKhe\nm2muKNIUEYlBhaaISAwFr56nw1fBX3nllQKnRLKle/fuQNisUjZv//nPfya3L7zwQgBat26dp9RJ\nWWPHjgXCQQjp8A+PfF6X9dJLLyW3L7nkEgC++eab6iYxbxRpiojEUBKR5ueff57yer/99ktut2zZ\nMt/JkSzygxuOPfbYlP3R4bW+C9rbb7+dv4RJCj9Zjv+ZDdEuRxVp3Lhx1u6XLYo0RURiKIlIc9So\nUSmvd9ppp+T29ttvn+/kSBYddthhQBhRfPnll5sc8/XXXwNhe1d0QISUjuXLlwNw++23A+GQWai4\nK1N0GshioUhTRCSGoo40lyxZAmw6dMtHHgCvvfYaAPvuuy8A9evXz1PqJBvq1asHhBM1RCdw8ZYt\nWwaET1tPPPHEPKVO0uWHOkPqU3EI8/a7774DYM2aNWlf1w+r3H333ZP7evXqVe10ZoMiTRGRGIo6\n0vRtWGWfnkcnefATP/iJia+88koA2rRpk48kSpb8/ve/B+DZZ58F4NVXX93kmMGDBwNhnqs9u/B8\n/81bbrkluW/RokVZu/6ll14KwFZbbZXc59s5ff/Pn/3sZ0D+apmKNEVEYijqSNNPPnvMMccA8Oab\nbwLwxRdfbHLsmDFjAPjwww8BmDhxIhC2mUlx81P7+Z/RPnx+208a4SfEVaRZeL4tM5vRZXmi00H6\n2qT/OXAgxdfzAAAId0lEQVTgQADuuOOOnKbBU6QpIhKDCk0RkRiKunru1w3x65AsXrwYgHnz5iWP\nGTFiBBBW3aZPnw6Enab9zM8Qrksjxat58+ZA+Z2d/T4/q3u7du3ylzApl286qWxIZL9+/YAwb8vr\nVlaWX63Uz6PpHxBC2ATn/f3vfwegbdu2AFx88cVppb26FGmKiMRQ1JFmWb4bUbQ70fHHHw9A586d\nAXj33XcBeOutt4BwDSEpDb7jsn+wVx5f87jiiisAqF27pP6MaxQfRVY24MB/XrfYYou0r+sncPE/\n/fSQEP6NfPzxxynnvP/++2lfPxOKNEVEYij5r+iGDRsCULdu3QKnRLLB1xyitYmy3VlefvllIGzP\nvvzyy/OUOilrhx12SPmZKwceeGBy+8knnwSgS5cuQDg80683NmzYsJymRZGmiEgMJRlpfvrpp8nt\ne+65BwifrHv5Hlol2eHbJ/v375/c99vf/rbcY/0ABkWaxcU/+S47sXS2rF69GoANGzak7M/V/cpS\npCkiEkNJRZq+r9agQYOS+8pOG+cjTH+shtqVpnQWUfM9JKL99nxfQMmvqVOnJrd79+4NwDnnnAOE\nbY2Z9HLw0StAnz59gNShlQAnnXRSta8fhyJNEZEYVGiKiMRQ1NXzBx98EICrr74aCBuAy4blAKed\ndhoQzrXnh2BKaYo26nfs2BEIh8p6fr5Vv+YMhFVBya9169Ylt7/99lsgnHXov//9L7Bp9dx3GQLo\n0KEDAMOHDy/3+tG89/neoEEDIFyd9rjjjqv+LxCDIk0RkRiKMtIcPXo0EA68r2wo5HXXXZfyU0Pq\nap4TTjgB2DTS9GbOnJnP5Eg59t577+S2f4jnhzT7Ya9l+S5jUPFqlJXp2bMnEM4eny+KNEVEYijK\nsMx/M1UUYUanlrr++uuBeJMBSGk588wzgdSuZlGnnHJKHlMj5WnZsmVye86cOQBMmDABgMmTJwPh\nM4mVK1cC8Prrr1d53aZNmwJw5JFHbvJetC07nxRpiojEUJSRpp9A+F//+hcQfttMmTIFSP1Wq1VL\n5X5N59e89k9WhwwZAoQTNXTt2rUwCZNy+XW5zjrrrJSfa9euBcKn60uWLEmes3TpUiCMRg8++GAA\nGjduDIQTDBcDlTgiIjFYZdPUV6V9+/au7DDGms7M5jjn2hc6HfmiPK75lMfxKNIUEYlBhaaISAwq\nNEVEYlChKSISgwpNEZEYVGiKiMSgQlNEJAYVmiIiMWTUud3MVgIfVnlgzdLcOZfbRZ6LiPK45lMe\nx5NRoSkisrlR9VxEJAYVmiIiMVRaaJrZ9mY2L/i33Mw+ibyuk4sEmVl9M5sV3GORmV2fxjmDI2l7\n28xOyDANr5jZAVUc08/MVkb+P87N5J6FUog8Du47xv//pXl89P97sZmdl+H9HzazXlUc083Mvo78\nf1yTyT0LRZ/jSo+J/TmudD5N59wXwAHBxQcBa5xzfy1zUyPRNrqxqpulaR3wc+fcWjPbEphpZs86\n56qahmWYc26EmbUDppnZji7SYGtmtZ1zP2Upjd4459xlWb5mXhUojwEeAO4ERsU4Z5xz7jIz2xlY\nYGZPOedWRdKZizye5pyrtHAtdvocVynW57ha1XMzaxl8e4wDFgK7m9nqyPt9zOy+YHsnM3vczGYH\n3zydK7u2c26jc25t8LIOsCWQ9tMq59wCwIBGQTRxt5nNAm40swZmNjpIx1wzOzFIYz0zGx9EMI8B\nW8f476iRcpnHAM65l4Avq5M259xy4AOgWRCdPGRm/wFGm1ltM7stSMd8M+sXpLGWmd1lZu+Y2WSg\nSXXuXZPoc1w9mbRp7g0Md861BT6p5LjbgaHB3HWnAT4TOpnZyPJOMLM6lqi2rQAmOufmpJsoMzsU\n+N455z+QuwCdnXNXAtcDzzvnOgJdgVvNbGvgEuAr51wbYDBwYOR6D1YS4p8WfDAfNbPd0k1jCclZ\nHmfCzFoCzYH3I+k82jnXF7gA+DzI4w7AQDNrBpwK7AG0Bc4FDo1cb4iZHV/B7bqY2Vtm9qyZFc/0\n4dmjz3HMz3Emy10sTSPUBugGtLZwic5GZlbXOfc6UO7KSs65H4ADzKwR8G8za+OcW1zFfa4ws3OA\nb4Hekf3jI1WO7sBxZvaH4PXWQDPgCGBocO+5ZrYwkpaK2jieAMY659ab2UDgweD6NUnO8riazjSz\no4D1QD/n3Orgnk86574PjukOtDGzPsHrhkArEnn8SPC3sMzMpvuLOucqaqt8A2jhnFsTRDOPkyhk\nahJ9jmN+jjMpNNdGtjeSCKW9aFhsQMfgPzAW59xXZjYD6AFU9Z89zDk3oop0GtDLObc0eoBVY83l\naFsaiXa5wbEvUvxynscxVdT2VDaPBzjnpkYPMLOT497MOfd1ZPvpoIq4nXNudWXnlRh9jkNpfY6z\n0uUo+Ab4ysxamVktIPoHOgUY6F9UEiL793c0s4bBdj0S33DvBK+H+vaLapoE/DpyLx++zwDOCPbt\nD+xT1YXMbJfIy14k2oRqrGzmcWXM7FIzu6j6KWUSMMDMagfXa21mdUnkce+gbXM3YNM1YTdNy86R\n7c7ATzWswEyhz3F6n+Ns9tO8isQv8yqwLLJ/IHBY0GawCOgPlbaF7Aq8ZGZvAbOAZ5xzzwfv7Qcs\nzyCNfwbqW6I7w0JgULD/78D2ZrYYuA6Y60+opC3kd2a2IEjnRcD5GaSrVGQrjzGz8cDLQFszWxZU\nyQDaAF9kkMZ7gPeAeWa2ALibRI1qAvARsIhEFWxmJC0VtWn2MbOFQbvccFKrizWVPsdVKJlhlJaI\nvZ9zzh1b6LRI7pjZM0DPHHQrkSJQEz7HJVNoiogUAw2jFBGJQYWmiEgMKjRFRGJQoSkiEoMKTRGR\nGFRoiojEoEJTRCSG/wftSC5FFuLBNAAAAABJRU5ErkJggg==\n",
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SS5m5Xy+88MLstrvuuguAp59+GoABAwaUP2EiEZVGIiIpVGWk+etf/xqAZZdd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\nmiIiKajQFBFJ4f8B5DaVvKWqiOwAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024e9b3e48>"
+       "<matplotlib.figure.Figure at 0x7f3cd2fe0b00>"
       ]
      },
      "metadata": {},
@@ -1121,9 +1111,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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iVAh8uwDp2ztWvBQIO3eWfh9CVbZgQen/oeqlOok76Cgq2KGxpyApxXt6E2d1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\nSUVORK5CYII=\n",
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XZnWtbe1+duzQ8qWXsnWaVbXxuFMlxGvAe5XXgsu3RLF7xcpM1VYMyxtw48b8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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024e845cc0>"
+       "<matplotlib.figure.Figure at 0x7f3cd2f1b860>"
       ]
      },
      "metadata": {},
@@ -1162,7 +1152,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 92.0%\n"
+      "Accuracy on test-set: 91.8%\n"
      ]
     }
    ],
@@ -1177,9 +1167,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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KOC7Yvw6JJoEPatonK12Ogpp9pZltFZw4mvnngaH+haV4YhlxBJVuzc3sbDOr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\nsx4kHkqUU4VZQTbL2Mw2teA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piohEkNaMoFz55ZfYsnt+D49tttkmn9kRka2YIk0RkQgKOtIcPXo0AL///e8B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\nAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024e83e0f0>"
+       "<matplotlib.figure.Figure at 0x7f3cd3018b70>"
       ]
      },
      "metadata": {},
@@ -1204,9 +1194,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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sBjCWH5xzU7z3z3jvvwNgO4A+aq0B3vu3AOxyzs3V6If/AOChAZyzCFSkjCsM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\nQxgm9s47TOPepq14Ld96S8w+bW0nZvYFUrnzPHS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2ADllyQXe+zcA7HTOLdLohz8D8P/245xFoCJlXGGoWBk7574N4GgA147WrwxQ\nkTJ2ztU7547T/6shL+2c5T/HhvG+gDdCPJqPRdve8d73AoD3fhWAXwB4VG0vtyMQhuJfIXbYZwHc\nDFE/3tnHue8CcIlzbr1z7mwA/+AkrGwT5IE+7Zxrdc79ZoT9vwxgJYAuAC9BbDvliIqVsXPufznn\ntgCoc85tcc59Y7/venJRkTJ2zrUB+G8Qe+hTeowvHsiNTyIqUsYAjoTYojdAnHhvArhxf296Xyib\nVGTnXL33vt85Nw3A7wGcpTYeQ4lgMp54mIwnHgeTjMupRPnd6pGsAfCtShVomcNkPPEwGU88DhoZ\nlw0DNhgMhkMNVgvCYDAYCoK9gA0Gg6Eg2AvYYDAYCsIBOeGmTZvu29o6JuhSyg9btnTjrbd6J7VK\nmsl4YjHZ8mWNvSJdLRs2rO31k7gixqE2hoGxy/iAXsBtbR1YterJAzoBF8LMW56by0Bz2Xn24Wcu\nMZ+3nHy8/PdoS86PddG95csXjm3HcWAsMq5kTLaMxyLfKVOk5fLlo41l9qka2A0AGKqtA5BdMn0s\nGGlp9v1BS4ub1OWBJmsM891S5KKaxFhlbCYIg8FgKAiTFgfMGTycycl0e3ryP5NNTA9KLMdMoK0t\n25esGUhZSbwcfTnMmJOF+N7j55D3XCg3ypKyJUL29f772e9iTeRgkDXvqa52SP7hQAWAvj5pu7qk\npSDfeAMAUKUPoKGlJd2HAt21S9qpU7PbQyE2NkrLh6HtHtQASJn1gTDiSsVo2vT+otzGozFgg8Fg\nKAj2AjYYDIaCMOEmiFjF7e1Nv6OpgdvYbtZaQ9u3S3vcccOPR9MDW2p4nZ1p39iJR/WDTpVKVdt4\n/aEmDOSbE2J1LXYG8RihmeF4LU1/xBHSNmCn/BPbhoBUyKoq7+yvynSl7KlJA+Uvd8qXSG439hID\nqQmC29gec0z2e7YhaFt75RVpu7ulpeABoLlZ2nfflVYfTo3+KJo6OgAA29A07PrLXc55yDMzxGJn\nO5rjnRjJSR+b1cI+k2mmMAZsMBgMBaHkDDhmD7GTJpzZSArIeGOyQCJAYhDuH/o0gHS2D7c31e7O\nduKB388eZEd/zbDjlDNiZyVvi+w2lBdBBsqWfbbowkwf/Wjad8HMndkvQ7UFAJYsSf59oUvm8FnY\nAQBo0Itp6O/LnHCocUayD6+33GUdM676ehknDaGnlyqXMtGXe+qy++jX4bgn+2qtFZkl8j1KKy+G\nbJnPgNsCijt6AAAgAElEQVT0PJg3T9qZMwEARwS/5Pfekzb+LZYjYidxLHMgFU88zuP3RajdxWGB\n8fgPHfuRfzPZJ/aJTgQzNgZsMBgMBWHCbMDxLMIZ7eij0z6czDnDcLKnXZcM74wz0n1O0Nr1S5dK\ny1lvVsce+YfhQOHJST+eeELat3T1kYsvlra+PdmlnIK7Y/DayAgoH7ac3SlXICFIiUwbakVOL3QL\nm9u0SbaHNrKnuhp039myT/2r8kWODXTWgMq7S7etXi0tH+YppwAAqs45J9mnsVOO29eXZoqVA2I2\nFtuxKfeOjlRj4rb+fmG+t94qn8mwyPLnz0+PmzJqsdsuuuhPAQB163VhCD4UOZm0fLhU8SLj5mDA\nGCuB+RJknbGvIrTRUl4a2ZdozHH74ovDjx9H+MU+o/B/KjPsQ/M7zfnhNZXq/WAM2GAwGApCyRgw\n2QPttnVQ+6tObXW1cqrdmpoJpDM1J/cnNXuRMx7tlHfemZ6HM+acOdn26KOFlVxyyeykL1nB7Mat\n8s8aXXyV1GbRIgBA7ZyUARPlaJ+krSu2iVF+lEVo32pq1OQB3jM1hpky7Xd0yBxc0/1Css/W+lkA\nUiLW2SnyaapW23CeUZ4PhuchEyYlDOyaVVfLBVbXHltWDDiOIuEY4C1NmyZtePtUuOKxS7yuS72G\n7JqM67nnpKWc6+sXAwBO/cjipC8jgEZKnKlWRSPUYPj/4YejLBAy8lgp5eeafrWH9+vgDoTcqgN8\nwYm64XQZP88OiF/h5ptlM5UuINX84jyWvGAUyovMN44Uit9T4XWPlwkbAzYYDIaCUDIGzJkgsZP0\nRvRMQTYBpDMWmQC/u/fe7LG2b9+Y7LN9uxz3lVdkOuztlWmL9psHHkiPz1mv88pWAEAVqUfkGo1Z\nSzkhZE68zvXrpeVMzdmezLepN2Wz2KI7vfZa9oAaydDdK3bIWYFnn6xOzbdo0ggH9EXuZyB9vqQR\npOErVwIAXtV023bSFAD43OekrY0XvC0PkJ0xgocZw7zV8Pb5P2+fdsPYQx/+DDju+Rx5vpDBEQx2\n4OMhK6dp+OyzpQ3tk6EGVA4I2XmiGatGnPzoKQyO01DIfBBkxXqDs3Ws/c9rLgAAvDrYmuzS3qI+\noYcflpYvmTY16HKcAolwd08XTY/Pm66ivCiLvDjiscAYsMFgMBSEktuAOZvX6Cy1c6Amsz0MUiAh\nZfhjOCkB6eS4fXtokBVDnKzIne6j5tyMd5Pn5HFaV6yQf3RK29kits6+KMwVAI48cvi2okH2Q28v\nbVO8ZzKopr5AzSD1IouIKNvbb8vHnz+WsgeSEbKsjg5hybW10i5ZktrM67qfzZ5csVVpBNcgP5au\nagC1SuUHB4utkzsSqGmQ8TAJLU56A1J2R9ZJcdOuy2MEt5+Iir+F7dv1BNAoHR3j0uc0AGl2Ip/5\ntm3S0ueSQ+gKtwEnmZT1Q+nGzd3SUjBxMDuN5rxhIH1BUL14/nlpKUBlxu09wYr3jz2W7RPXvmUE\nFJA8tLqL5IdUd5S8ON5/vy5ziNDey3eL2YANBoOhQmEvYIPBYCgI4zJBhA6iOESqtlZMD3GSQGgi\n4DaGf9CZxCQLhp899NAbwVlPBwDcdJN8WrYse02heshiPtR2nuo/Vq9R2nV3yPYwcSEMmC8HhCoO\n5R2HJlFuc9vUWbY5MEGwE3VihocpTr74CwCAf/u3dBsjx7grM4/5XEIsWyZhf1Xr1skGdXq8qd+r\ngQJBjSTM1QdSXV1eiRhxiFdcqChOfwdSc0Lka07MANSamUAEpCae7du5iMJT2vJhNyR9OXb57GlJ\n4jXxdxc6t2kOCZOeikDifAt/lBQYWwqKg5iDLfQk8qXCvnTGUZC0EYQeeH63UR34NGPwhcHvw3Pe\nfbe0Cxfqadsz9xGG0+VtGwuMARsMBkNBGBcDzlvdgi0nLbJQMgQyAgBofkfCpdqXKQXmdK5sbWXv\ncu25Ndnn858X9vpnl2k4i85+L9fPBZAND3nmGWnpUHvnHWlpnyfzjVNQywnhtfHedIJOZLp4kTo5\nHtBsgMcCZwTZQlyP7/bbASApYnjddV9IvqJGQrJMckvSQrICpE68s8+5AgDQeuaZAIB5mpnQqwwk\nTb9BMkjKwQmX9+zjJAG2HC9hLR6ChI1kjDK86CJpVdwAgBdfjLN8FmjLA6cMmIQtzkhm8SQ6CPNW\nNCmbcZ1XJYe/dVYOirKIXuhJZTBzpvxf1bcj25cxej/5ybDzDOi469bPnXwx5cUFMouGUGHHDDgv\n9Gy8CVvGgA0Gg6EgjIkBc2bNW+mV2zhbfPjD0nLSqnry92nn+++XlqEnUaXlO+8kA04tiN/+tv5z\n5ZXSXnWVnLdDGHCYJkr2HQe6xyXpyFaAfHZTLuBMTDaUMFHSK07H4Q2RKvGhkaLRBvbd7wIA6oJK\n9h0dkgobFrcHUq3mllt2JttuuYX2eal6MmWKpIeuXLkBAPBnLavka2bX5B24QOSFEXHsUr783NT3\nsvxTndonF/AZ6MBpaRFOc+7MbAGj63vScpyACPLEEz8EYLgPJPRJMBmG9vfmKbTzS1zbVn1WoUmz\nVCFS40XCGLsCA3WcocJKW/xR6gvk6KNTBlzVpYlFUSLGzpmiOTRcckn2GABqVW07lvswj5wqG98f\nQMrCGTenF04bOn86pUq+CGEM2GAwGApCyRIxyHzZclafXaus4YZ7pGVBnABDt9wCAFDOgA6dya67\n7scAgBtvPDvp294fBf7rdE/2EJIrmojIHOkpJgmkV7vcUjdHQlxYJClgEudS00gMYM+ij0vfm38q\nG0iVyAwoBAoLQI8San0sSUk/MoITT0zZySuvMIngQQDA3r3CMP7Tf5LMmJvPFy3m9tuXJ/vweezd\nVbwNOA9MRWW0STtHJmUWpslS9qri1VAbobpw+eUAstripz4lB77sMvkca13h4cmGm9/Scc8QFfWT\ntF57rZyu7ePJPvuzVE9hoCCYJcKwDl603ldzdZCxpVEKGwYkcYoi+M53lM1CftgrVlyR7HKDaspN\nX/+6/EMGzLKoYSIGr0lfBLvVY3FElMMRR7qUAsaADQaDoSCMa67MW5uRhGoW1G5z/Y3SMhfzjSCm\nV6kVyQEzgjtOl1hf2o1/8IPgpKGHH0hq0dXlrFXURMai7K5BaTlTankpeYyhXDzIoR2P8k4YU6+y\nL+ZhM9Y3oPQ1XcqcyHxjl67a0Dd0pXEK3/mOtJs3C8M4/3x5TrRDspYOAPT2Cpv7yU8u030oOLFH\nkzWEmcrT0kzbsgSffSLGOx6S9kSth5gXcvCQ9qE9UXd+eVA86WG8+peu2pM5zqqHRfYcrh/5SNqX\n2gc2R3Uv+az5u1qUMmBeXtFjmMpBXeiTiFXkuECWjuVXe9PxuEndB3Qj/PM/P63f6ECFaGE33pjW\nrf3GN4QNN5Nhk3HHQfThheqzHMgS4mFLE4W7WxSEwWAwVCjGxICHlZ5EWjujeZt4v5PpigZXBpMy\nLAJIDFwNylAXvvSSbFe6ELNqAEl1lwFdXmiPtg3xTAqkBuFo1b0BpdqMocwrM1d0IZPRkNjbtfxe\ntd5e68VqCA+XtGF2EKdsFiTirK+09rl70l1OPlnad98V+kWbJBlVaHImK6b4u7tlcPT2SkvbfLhP\nuS77xGc/LLonNr6HaWcMtWHQOTUNlTO7ZrIISXX1hN3dwpIpozC7Khn7m6LgZNrslaaF7IzHKVq+\nSSZhY1OyrYpqbVQcZ9t74legaB5/PD0OhzArS6b5lVwaSgoWnX56esMsJdlM1eOuu6T90Y+k5XMD\n0ogIlWkTB6i+n3bPlAgr+gZKCWPABoPBUBDsBWwwGAwFoWROuOT/dyO7AY3t1C1C4zf/ZzwO9QYN\nO5muh0pC2YAkBkUTkdHEJUvjpU2BRO/b5nXlBY1aoUOIlxTW/qX6XY5rwsV1aqmS8frffVfm02XL\n5ib7tC9U+wFVVqrTKvsH14vqx+JGQBoZxGg2mhEYuRMmu/BaKPbYEhS35Yw4jZ5tO8cYbzy0p9CO\nRecwPbuqry5eoqGCqf6cCGnHzI+FHxOtPCyF29CnIXC0iWlYW5wXPhHq8XjB31DWxCfjjT/97p66\nzGeW+g1rRvFW336bXkVmv3xa2/MAZGsiJ8ksgzref/hD+ajFtKv5QwfSIjx/0OJIfGfpAfm4+bsA\nSmeiNAZsMBgMBWFcDDhkiWQL/f2ScrngYo3hoOOCHUIHBqepr30NALB7UIzqdT3CeOd2/1a+v+Yb\nyS47NdwnMeuz2gmnP5aWC87Z3CnX8pt7qzKXQFaWV1azHFfEoFOFTInXyJmZLFaXYwMAdHRIeNIF\nsmwWBruljQvuhAhyMgCkIu3rG/49Q3Uo03jfvHKJoRJUTiBTi0urtlNriEMggTQMTNccG9AbrT3t\ntGy/kKLqWKW/jgzvy1ftzm4Akt/IUJs46qr6d2YvTh/k+8Gl8SdXdBgawci8+H9g+CrFeUW70hwN\n+QHs3SuD7uSTJVz1PCHA0OhVAMFKLa+8Iq0OzGq+L0JaThWPP6hPfQoAsLVanaM5KykbAzYYDIYK\nR8mSFqPMYDzYL7aeJRdfCgCo4jQWLgqnQdc7+oX5cjacQbqkSRZ9DHIH0EiDGcPZaJhUI+RvN6Ur\n7XZ2yv8D3dlrZEotw33KuZRfeB1kNqwZ8tkz1T6ozKzvsj8FkC19GNdhJ2PlunI8VpgoQPbBGiez\n2pSZJWX7gnqUZInThbrs6BObHldSbtKL3jJYk+xCGRcdJhWD4yCqioqZF0sKbEOj0kyu3BvsNKhj\nNln9jGP2k5+UNrA57mkTLbFfj5/UhaGdODCY7+mQc9cgWFctOAavMWRk3L3c5AsMD0FkywoFvB8S\nfCAlq3v3ys7z50tCTFSPC00DadlaQMbj0CcvBABUkR7ToBvWH1CBbdsufJRla3kNfOWEWjHfHZaI\nYTAYDBWKkjFgzrqcNeKVRxYuFI9ly9J0H363Ugtn0JP+pcv0HzU+NoaZGOlSvQCAXw9IkZd+JWch\nOeHMyWuiuY7m4tj7DJR3AgYZWlO/Ml8y0v/xPwAA/+XrMrtfduufJfvQwRs78GkKi1eCCZGUu9zS\nm+0ULvFLKNMl802EryesrW0dvk+ZgzZa2svPjZftBpIoiOqzpWBUNZfAYd1Uqhg0wgOoGRA77qc7\numXDnXoiDtSgVGIyNvW7oemi1fXob4diDn8ieb6NcgMDnph7RfN66ktK+3Lcd3YKXWZ0Dl8FTYNv\nIsbLAzLenrhNPn/wwbGZ78OonPg9EUfs8Dzh4x/vUkSEMWCDwWAoCCVblJPeS84iUXW5JJ0wNAGT\nlZEJk2DdeqvEOHziE7JMztVfTfchg6OZuOfJ7OcwRJPnop2Gtj3OqLSpVko5Ss7UTbxJupRpD1dm\n2vrYl5N9vsQY68vTEpUA0gelD24oSBeNsaNevMFNtEOGdItC5TXFzoCkANKIhy87cCxTm+I4Oveq\nKI0WGObG36mfk4KdHOR33JF2In2KSzNS5QgCrauiBSl5uriQFOuMAwDDlstRmxtp6TKC9xeKmGMn\nrt+TxEvzhxyk4Hf3CwPmYrPxecNYa8Yex1E+bHne8JpKlSdgDNhgMBgKgr2ADQaDoSCMywQxWphL\n7IxjGNRrrwW6UhJaIzrf9OlyQGoUVB9YwhNIDeI0G9BxFy+2GvalukB/CPelqlnWKwjkYGimhCZV\nUbiMRJ8/X9owDo2Cpx7HfSJBhqYhyodhPU0U0BbV38KlAeLlgGlrYo1i1Rfrg+dSjmneQE69ZQV9\nnUuWSChd55w01bsqqmzWoANyj5qDav75n+V7piwDqQeUOi7j/mjzCE08ejHbDhcz0POqZcdlncNr\nLjdzT2iqjE0PtFTFK1GHZkFaauLnctRRyO6Us6oLj0u/cbwQDJCK/YQTssfnMJ9IeRoDNhgMhoJQ\nMu7HGZkzF/1DtIunK79OTfbhbMjECCYDcNbKY6g8Dme0eEXZsPh+tNBqMvvF5V0rBZRDVZ+Eeg0t\nPVc+xwWPwuKzeZQiB7M69qQfqEZEDyBJFR9MV0VO4ofi1Ti4vtZAVebagfJnwLwFal4MR2NJ2fBe\nZtFzTBr17/8ufXSA7lBZpmkoQD0HJAc6VwU/9VRpg3inrZrY0q3hWhyzvAZ+DllauSVg5NXfIjjE\nqMnmObzihIh4uG/eLGNsYCCVMt8tXF0kTIUHsmFudFryuHz+k/F+MAZsMBgMBaHkDJizBmcVEgTO\nLnmFWGL2ytmKAdfh7M6ZLa4+WTOo6bK/+13aWS+iSQ9QrZXtOftVmu03ZjZJKF6/2IQ7l0hbN7Aj\n7aQC310vgejJSlukdbQR02YLpMIl9VBKUJcX68cHznA3YpQlZEuVxllqxOFOrJ/D8cKkge9/P91n\n/nwJ35sz/z8DAKafL+2s78qaiE15mRLcpnb4F7qFudGMPvhA2jVel4yij5lwubHeEHkhZRQHXRH8\nrdMcTlkDwxYQSbTfOIEiWAw8eS+wb5xDFA5hKnyxNj0ZPiJjwAaDwVAQSp6KHM8WMasIESdCkB3H\nXs+8NMvZHcp4e3X6IvMNcwTpfg2LtAfg+cqx9CSRx2yYNNGqUSR9fTKPkkHNbQnUDJ3e62ijpQB5\n00mdypyKRBED3tYsGkTzMUFhGH1YO9PUAwCB/Wxg+OHLFZQ1xyMrSlKbI3sKM7GZ6n2jLv7N+56p\nkSpkeGFSBMuHxp5/9g2Vh/j5x575StPieL2J5tqrBXS6dXyuFy3riIvTdHr2jZM06Gei3EIlrrVx\nt/YVnS+274aLCvC4fM/QJ0VM5Ng1BmwwGAwFoWTz50gzdRyvGNr9pk7NfhcvuTOayXFgoC7Tdl5y\nBQCgrv/NYZ336CxYG612WwmsLATJfSqXbIQBZ/A99WnhkRpGKVBwcc3FtWuz3wOpEYytPpDmRo2G\nGEjTlgcGG/Ra5HOszRDlZu8dDRzLMdvkvSVFipCGVXORXQY0xN+Hvw/Go8esjOcLGXAS64rstZRz\nyckY4TXy3mr69HcaR9HoQGq49cfpTkpxGY8+oy0Kb+IPYnMQ6aP0eC7LgC5s0/NrVEl32jUuwjM1\nDdTKIBzTpZK7MWCDwWAoCCW3IHFmiDNcOMuEGVfJRehVxJMhGUIYBRGXqyNxO+kkaTs6UvZHG960\nadLSlsfzVZr9jKA8RpJxGOPYzuBqbiQlO1GKWidCCe3k7BulWe2pV+abozmQxdVUi314SOf2StMy\nQnAsx/bWcDzG0T1syfhp7w3HGo9LjSY+bth3pLFaCcw3D8l91OoPN64tSWoaLmIavxDipaHyAnY5\nhhlTfcYZAFJG3HzGrKTrM89Im6eBABPrIzIGbDAYDAXBXsAGg8FQECZMCWfYTUznQ1WK2jAdONQw\nqFFQjeMaTcDwUJ3YURKGrNH0EDv7KlV9ix1ZcfJL7MQEgBfUSVlbK23jzOzKAHE5XwA4WuWWFFFR\ntXpAn1eogg9zoA5W5V5rJSNevywMKdvXqhN5Jph9mb4qdXzuDxg69h5TgrTI0BEzpa2ftwAAUBUu\n0RKuEg2k8WbxOpNhvjHtcczsYDEkHfDNM9NQync7ZMzGhY3iFZwnAsaADQaDoSBMuBuKbCGq0QIg\n9fuQJXBCi1lDyM72VRouz9lxsCK+PzoLRnMaxE4iPp88VjbS8UPwOAcT4z0Q7GuMHexjcLyIVyZn\nON+UKYGmpo71eIzycx0deaN5fKOslz2DKfcc6fcyGSnzxoANBoOhIDjv/f53dm47gD9M3OWUHT7k\nvT9mMk9oMp5YHILyBUzGk4ExyfiAXsAGg8FgKB3MBGEwGAwFwV7ABoPBUBDsBWwwGAwFYcwvYOfc\n951z1waf73POrQw+/6Nz7iv7OMYj+3GebufcsAXNnHNLnXOLD/S6c47za+fcpvEeZyJQ6TJ2zq12\nzj3vnFuvf8fue6/JxUEg4xrn3I+dcy845zY75z4z1mNNFCpZxs65o4Lxu9451+uc+8FYjpWH8TDg\nNQAWA4BzrgrAdACnBt8vBjCq0Lz343mBLuX5xwrn3KUA+vfZsThUvIwBXOG9n6d/b+67+6Sj0mX8\n3wC86b2fBWA2gP8Yx7EmChUrY+/9rmD8zoNEd/xqHNcy7ARj+gPQCuA1/f80AP8HwCoAUwEcDqAP\nQI1+/zUATwDYAOCbwTH6ta0C8C8ANgO4H8BvAFym33UD+CaApwBsBNAJoANAD4DXAawHcDaAPwGw\nCcDTAB7cj+uvB/AwZNBuGqscJvLvIJDxagALi5bjQS7j1wAcWbQcD2YZB9cwS+XtSiWbMWfCee+3\nOucGnXPtkNnlUQDHAzgTwDsANnrv9zjnlgM4GcDHADgAv3bOfdx7/2BwuEtVULMBHAvgOQA/Db7v\n9d4vcM59GcBXvfdfdM7dqA/lewDgnNsI4BPe+9edc426rRXASu/9H+XcwrcA/COA3WOVwUTjIJAx\nAPzMOfcBgH8F8G2vI7lcUMky5vcAvuWcWwrgJQDXeO+3lUY6pUElyzjC5QB+WcoxPF4n3CMQgVKo\njwaf12if5fq3DjIzdUKEHGIJgNu890Pe+x4Av4u+J+VfCxF+HtYAuMk5dzWAwwB58HkCdc7NA3CS\n9/6O/bvNQlGRMlZc4b0/DcI6zgbw+VHvtDhUqoyrAbQBeMR7v0Cv+3v7utmCUKkyDnE5gFv20eeA\nMN5aELTtnAah9K8B+FsAOwH8TPs4AN/x3v9oHOfRstb4ACNcs/d+hXPuDAAXAljrnPuo9/6tEY53\nJoCFzrluPd6xzrnV3vul47jGiUKlyhje+9e13eWc+wWE2fx8HNc4UahUGb8F0eD40rkNwF+M4/om\nEpUqY7kw5z4CoNp7v3Yc1zYMpWDAFwHY4b3/wHu/A0Aj5AVHo/p9AL7gnKsHAOfc8Tne8DUAPuOc\nq3LONUOM5vvCLgDJilnOuZO894977/8OwHYAJ4y0o/f+Bu99q/e+AzKjvlCmL1+gQmXsnKumR9o5\nN0XvoSyjTVChMlZV+K7gPOcBeHY/zlkEKlLGAT6HErNfYPwv4I0Qj+Zj0bZ3vPe9AOC9XwXgFwAe\nVdvL7QiEofhXAFsgg+dmiPrxDkbHXQAu0dCQswH8g3Nuo5OQskcAPO2ca3XO/WZcd1g8KlXGhwO4\nzzm3AeL8eB3AT/b3picZlSpjAPivAL6hcv48hFWWIypZxgDwp5iAF3DZ1IJwztV77/udc9MA/B7A\nWWrjMZQIJuOJh8l44nEwybiclqW8Wz2SNQC+VakCLXOYjCceJuOJx0Ej47JhwAaDwXCowWpBGAwG\nQ0GwF7DBYDAUhAOyAU+bNt23tXVM0KWUH7Zs6cZbb/W6yTynybi0mD59uu/gUtoGAMDatWt7fQlX\nyDAZD8f+yviAXsBtbR1YterJsV9VhWH58oWTfk6TcWnR0dGBJ588dOS5P3DOlXS5IJPxcOyvjM0E\nYRgRH3wgfwaDYWJgL2CDwWAoCIXGAZNdDQ5mt/NzvD0P1XoHtbXD9+F3hx029musdIzEYEeTbSz/\nWMYhDmXZGgzjhTFgg8FgKAj2AjYYDIaCMGkmiDxzA/8fGJB21y5p331X2v7+bBvvDwD19dK2tAz/\nvrEx28YmCV7TwaZGh2aH2JwQy/y996R9//10H35HeR15pLRHHZXdHv4fmycONpkaDBMBY8AGg8FQ\nECaMAZOFkU2N5vQhizpZa9839WhJ095eabvXp53b2qRduhQAsGFLEwCgR8txkBGHx920KXstZMQz\nZ0qb51zau3fk6y1XkMXyPgHg7bez31GkL74o7TtayG/LlnQfypIsls+F8qL8AGC6rkFLGcZaB7cb\nIzYYhsMYsMFgMBSEkjHg2MZLuy3tulOmDN+H7IiMbVavFsa/915pDz88e3AgNfY+8AAAYG53t7Qr\nVox8AtQAANYrkSbbi9kakNpEyxmxrPv6pCW73b497btNl2ckU50zR1qKkff+8MPpPvz/ttukfeYZ\naal8hFoGj8Pj83innCIt2TO/B9LHajAc6jAGbDAYDAWhZAx4XxEN9KQfd1y6D9lSwjo/6JD24osB\nAHvmLMgcEwAabv2x/ENKddFFAIBX+xoAAO09v087K92bNk0Y8KJFspl1Q3jc0AZM5l6ONksyX16j\nkv+E0Xd1SUu7LwCcoKtd8Z7ndu7J7rRyJQBg9qZ0ubYvqX3952coVZ0/X1qV+YaBWUlfnpOsefXq\n7LXx+c+bl14TH50xYcOhDmPABoPBUBAmLApi6lRpj9GCbLQf1mx5Oe1UKxvr64Wh/nZ1KwBgYEDa\nXeqpJ5sCgP96yVLoTgCAB7uk7xy1RW6o/VjSV532aP5gq+6jt3vT3QCAuuZmAMDucy48kFsrDDHz\nZQEqRi2Q1NLOCwBLlkjLCIbEUHz99dLecAMAoCtQMwbuugsA0KGf6//yL+Wfs84CAMw9PzWaz50j\ndLa2VuZy2tl5jWTeyfmRaj7GgA2HOowBGwwGQ0EYFwPOK/Ry9NHSNk9VW+PmzdI+rMyLbnMgMRhW\nKU2bPr0OADC3Z5V8/2Hp+0vMTXb51SaxP1568RAAoE2JW1OfMOum/mB9voFOaUnH1q2T9vXXpVXj\nc5jZRQ//4CDgJrUUexZxHDUwnOnyu069Tdqy1YQOIAil7pZ2sE00Blz7vwEA7UqXZ954Y7oTaesf\n/7G0n/uc7iyG/he6a5Ku/RHrXqjlfWkbrs4ZYXnbDIZDEcaADQaDoSDYC9hgMBgKQsnD0BILA3VQ\nmiCoL3M7kOrSmvc7l9VeFENzxPTw79en25ijcf/9Mnd8/vPyeUZn48jHp87LfFx6gc45J9MtvP7+\nfsD74fc52QhNEPyfiRY0PZx3nrRMulDfIoA05Ksdr8o/lAVtLVdeKW3oEVM57b7kCgBATzePJaaH\nvIJHjz4qLeUXh/iZ2cFgGA5jwAaDwVAQSs6AawZ2Zr9g7BRpZpj1QLbKXFrmr2r2QFXfDgDARRc1\nJYBE9z4AAA2RSURBVLuQUDPgn6mui+uzbBpAGvvEnQjNChnqnC2nXz/sK9TWFuuEG21VECZXXHCB\ntE2bJYW7mXR3TZpUkVBgxqyR6Z55JgDgF5sl2eWCT16R7MLHcaQm08yAhg4OCt2tr0+fR3uLOFsb\nG4Ud0+lHkfcEPlGDwZCFMWCDwWAoCCVjwDQpDtVLSnBVXE09SHVNQHrHGCayNcZM3XwzAODTAWvu\nuP7nAIBbb83u8nK92Is7PpmGrFUNaigcmTazBJQZV63+LQBg3tJzh10aWWDRCIsDUQwJ833g/8o/\nvK/jj5f2P/4j3Yn516SimhHzFLJp3mGBnaZND8o/pLOarsx84vawetHPfib7qD29SS+udt6nAaSP\nPa/kp8FwqMMYsMFgMBSEcTHgsGANy02S8DaQmpKB0T3OIH8gDeyfvjhz3FnVv5av//qv5SL//M+T\n7+bWiz1y7rflOLsHZA4haa7qD2zQjz0mLQ3GPDcvXM9fhaFkl539cry9e8sjCiIs43nEEdI2dWnB\nIS3JmWgSvD8tUAQgZccMmdAsjXuV1F53nbRV1/6XdJ+4uj1pMulsmBv+0kvSkhWfeioAoP2CPbqL\n2IYtCsJgGA5jwAaDwVAQSs5LSJ76amcAAAana9soRXJC8kTCRoL6pavUZnuzeOyrWcOQNA0A7rlH\n2vPPBwA82SOpySTaQGBs1BPs+Pa/AEhJGm3De7RQe39g7y2XpYjicF0gsKPerrUfqW4w/zevzuMX\nv5j57sHNxwIIZPGYFsEPA4550jvukJbsmQ8sXCVVS1cm16DP5bcPi2w5HsIMdIPBIDAGbDAYDAWh\nZAyYBIqOc0YR0ARJlht6w0lw6dVP0txCNgakIQ9AwrieHRTmy9DhNKQ4LRRz993Sh4QtXcJe+jD4\nggQvRNEF2Xn+UF5J8AHjm5nyRuMwGWqw/s+2w9sBAO9HIk3umapDWDFdo0+S4kWsKcoqP6HA+ICX\nLQMArHpSYoT5vHkpeUvZGwyHOowBGwwGQ0GwF7DBYDAUhAlTBjdulJZON6rUYRTahboQRRJqRVsE\nw8eof4dZEZpIwMUt4jXI1q5NuzIdliov/UQE1WOu1hGesmgTRB6YlNHAZS7UVDPUIjV+qwZ2y/ZA\nXu+8I218r+zy45UyB/f31yX7fOUCPf7tt0tL242aK3bWHpte1AVi5mFEHNeG47XyvGFKNf8vRxkb\nDJMJY8AGg8FQEErOgOnw4mq4DD9iycTPnr8j7UyKerI6dbo0ZomOHSYUXH11uo+yvvZ6Oc4bHeL0\n+eUvs7sCGV8UgJT1kUCS2IWrCIerNpcbWE1zz1S557c1ZO55ZZ0LFwqLretJiw9VNwo7bhqQdfGa\nVHV4pEdYLJlrGsaHVHDUSNTTSebLSEAgfc70n06bJi2ZN7UPc8IZDMNhDNhgMBgKQsnD0OJC3CRT\nn71Ekyx+cku60+OPS7tihbSkUSxdqcbhoempzZHZsHPbJH2Yy7vxPNdemx6eUVosVE52ztA1giyu\n3EEGT3s3Q/6YPJKErAVZDzNqVePoUplqCBvtryS5oR08eQ7XXAMA2NEvYXsPr5bN4VqAcSF+XlPM\nfI31GgzDYQzYYDAYCkLJeAnZGVNPTzpJWq37nX4RLjtEKkrXOVNouUyOptHefXe6C1ntT2+SuYOM\n+6qrpA0rJcapzvxu6lRk9g0ZXbkxtfB6yODfeENaMnveF/NV6utbk32YMzFLKe7O6myiBGW0vPPV\n9EQzxUj+81uF+fKx0AbNPBAglSEfb6wB0SYc3odFPxgMAmPABoPBUBDGxfdC5kjmQ6ZD5tteLd53\n9KhxMKccJXOCHxz4WPgxWUUnXGeT7CtOH148b3f2AoCEli1aJOm4TbXSZ0+1RAswCKNSioXzOpl5\nzCgOmszJkMNlgCi76mphxdRUaDNnRMivj2hP9mGfcLFSILXzhlpGXLietuS4+milyNhgmEwYAzYY\nDIaCYC9gg8FgKAglXxWZqwqnBc1UL6ajLVitYc+ij0sP7XL3d6Wl04fmhjwTBLNkqeI+2y1mhTCc\nqkFjopoYt6V692CHroYcqePlDlpXaAKgWs/bYwZ3WK73iScYY/emtsz7lgc1Z454JOmUC48f1iIG\ngO3bpQ3NDjR3cB+2fA5MbAmPVS41lw2GomEM2GAwGApCyVdFpoMoYcCDSscYjxQkCdQMyPptPT2y\nkjKTAujcm9EiTrMrr0wLxZBxkbXyPGTg4SrCDTEdUwpJ5xL3CR1E5RwiFSc18Pp5m9QOwsI3LS3C\ndPv6TgSQ3jvlR3mFDlVuO+EEaeOCSnzGQCpaOk6pAZH5xs/JYDCkMAZsMBgMBaHkDJjsi/bIxgsW\nAADazxYqNFSbslmyMZLi2fWaDMD4s+vF+NsQUNQGrRrTtkxC1mjvZJfQXnxEm6xH1wBh2q/2NWSu\nkeetlBCpWMavvSZtvH5cGOnHxBUyUjJR9mVqd2ij5bOLtQviuefS/+NVRVqn78nsvKe6YfSbMhgO\nYRgDNhgMhoIwLgYc2ktjFskyh0wjXrpUAv3DYjnDinX3ROUob7tN2pNPTndSilulebcNl12WuYDZ\n4UX0qnFUKeHhatsk2wujBcoVoYz5PxlvXDqTtuCw8PyuXdJ++MPSMoKBLWUR2mjjQkqxphAuH8f/\nk9WVN+uB1DhcM1NOsHevzfUGQwz7VRgMBkNBKHnpGbIw2gSZ7kuzblhYJykUM1NKSyaU9IwzpGWF\nnRAMWGVFGp6QJwoNlhpWsW27zDMsO1kpNt8YjFTgLTOwhNEPif2VYQsA9syXJYPImililo3MW32Z\ntZBoP25+9+XsTl3p8XF3lM996qkIT7ijrypz7eE5DYZDHcaADQaDoSCUjAEze432wmXLpOVSN7Q5\nhksG8f+ZM2UeqK09F0CaKTVlffYYANB6cVAJBkgZr2bY7R6sSb6i/ZNlFMkCycAqjYnF19s8VRkv\nae2mbmmpHQCoiepEtqra0VqrIShTdd9MepvK+AENkeAxYgMyMHzFUzU2D3VIBMre7fnXbjAYjAEb\nDAZDYbAXsMFgMBSEkjvh6BiKkwaoqYbmBIY+0VRAhA4bIJtc0QVZ0YEmDy6wUd2XPU/4f2x6qHQw\nFXgPxNxSQ2HTGxcW7KX5gHaduMgyH0IYk8ciwYwx4/HYJ3R0RnnQOwY18SKqE2wwGIbDGLDBYDAU\nhAlbAY0MlW28HUgLt5A1G/YPLJaTFh4SJnzEEdIONgbpv40z8g+yVBqS2jAVOU5QSVY7icpgZv5X\nUmylJg2G/YcxYIPBYCgIznu//52d2w7gDxN3OWWHD3nvj5nME5qMS4tDUJ77g5LK3GSci/2S8QG9\ngA0Gg8FQOpgJwmAwGAqCvYANBoOhIIz5Beyc+75z7trg833OuZXB5390zn1lH8d4ZD/O0+2cG7Zs\npnNuqXNu8YFed7D/55xzG51zG5xz9+ado2gcBDL+rMr3Gefc34/1OAbDwYrxMOA1ABYDgHOuCsB0\nAKcG3y8GMOqP33s/5h83JJBqTPs756oB/BDAOd77uQA2ALhmHNcyUahkGU8D8A8AzvPenwqgxTl3\n3jiuxWA46DCeF/AjAM7U/08FsAnALufcVOfc4QA+DOApAHDOfc0594SyoW/yAM65fm2rnHP/4pzb\n7Jy73zn3G+fcZcG5/so595Qy1k7nXAeAFQD+xjm33jl3tnPuT5xzm5xzTzvnHtzHtTv9O9I55wA0\nANg6DllMFCpZxjMAvOi913I8eADAZ8YlDYPhIMOYEzG891udc4POuXYIS3oUwPGQF8Y7ADZ67/c4\n55YDOBnAxyAvvV875z7uvQ9/wJcC6IAsaHEsgOcA/DT4vtd7v8A592UAX/Xef9E5dyOAfu/99wDA\nObcRwCe896875xp1WyuAld77P4qufa9z7i8BbATwLoAXAfznscpiolDJMgbQBeAUfZFvAXAxmDFi\nMBgAjN8J9wjkxcCXw6PB5zXaZ7n+rYOwtU7IyyLEEgC3ee+HvPc9AH4Xff8rbddCXiJ5WAPgJufc\n1QAOA+QFlvNigHNuCoC/BDAfQCvEBPH1fd9uIahIGXvv34bI+JcAHgLQDeCDuJ/BcChjvKnItFGe\nBlGPXwPwtwB2AviZ9nEAvuO9/9E4zqMVffEBRrhm7/0K59wZAC4EsNY591Hv/VsjHG+e7vMSADjn\n/i+A68ZxfROJSpUxvPd3AbgLAJxzX4K9gA2GDErBgC8CsMN7/4H3fgeARoiKTOfQfQC+4JyrBwDn\n3PHOuWOj46wB8Bm1UzYjqVQwKnYBOIofnHMnee8f997/HYDtAE4YZd/XAcx2zjFT5XyISl6OqFQZ\ng9fgnJsK4MsAVo7W32A41DDeF/BGiGf+sWjbO977XgDw3q8C8AsAj6oN8XYEP2rFv0LshM8CuBmi\nRr+zj3PfBeASOogA/IM6kDZBXkxPO+danXO/iXf03m8F8E0ADzrnNkAY8f88gPueTFSkjBU/dM49\nC3n5f9d7/8L+3bLBcGigbFKRnXP13vt+DV/6PYCz1FZpKBFMxgZDeWHCylGOAXerZ70GwLfsxTAh\nMBkbDGWEsmHABoPBcKjBakEYDAZDQbAXsMFgMBQEewEbDAZDQbAXsMFgMBQEewEbDAZDQbAXsMFg\nMBSE/x+WxwZbwb8SZwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024ec81ba8>"
+       "<matplotlib.figure.Figure at 0x7f3cd35f6ef0>"
       ]
      },
      "metadata": {},
@@ -1233,23 +1223,23 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 959    0    2    4    0    4    9    1    1    0]\n",
-      " [   0 1109    2    2    0    2    4    2   14    0]\n",
-      " [   6    8  914   20   12    2   14   14   36    6]\n",
-      " [   0    1   13  950    1   15    1   10   13    6]\n",
-      " [   1    2    3    2  919    0   15    2    7   31]\n",
-      " [  10    4    3   56   10  750   16    7   29    7]\n",
-      " [   9    3    4    2   10   13  914    1    2    0]\n",
-      " [   2   10   20   10    7    1    0  950    2   26]\n",
-      " [   6    9    7   42    9   25    9   13  843   11]\n",
-      " [  11    6    2   16   41    6    0   30    5  892]]\n"
+      "[[ 952    0    0    1    0   10   13    2    2    0]\n",
+      " [   0 1109    2    2    1    2    4    2   13    0]\n",
+      " [   6   11  889   16   16    7   17   18   46    6]\n",
+      " [   3    1   14  901    1   36    5   15   19   15]\n",
+      " [   1    1    2    1  918    0   16    2    9   32]\n",
+      " [   8    3    1   27    7  784   20    8   26    8]\n",
+      " [   7    3    2    2    9   12  920    2    1    0]\n",
+      " [   2   10   19    8    6    1    0  952    2   28]\n",
+      " [   5    6    4   17    9   37   13   13  859   11]\n",
+      " [  10    6    1    9   42    8    1   31    7  894]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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4LvB6igQxjwCkJD2TpZM8CXg/FNnbgGdTdq/xTknbvWl/P4qAvD9wY0S8kOpo\nXE4Q628OwLY7Px9rhY5JQfb58Ycocg2fM+G8V3xuhgT8dUT83wl1eFkcazT3AdtM3QWcIOlw+GUG\ns9+gyLy2UNKvp/PO2cXnbwf+OH12IK1Q8RxF63bMLcAfjutbnpcyc90JnCVp75Q17XcqvjezrByA\nbUYiYitwHnCNpPtI3Q8R8SJFl8M/p4dwW3ZRxEXA2yXdT9F/e1RE/ISiS+MBSX+TVne4GvhuOm8l\nsH9a0ulainUB/4UiValZYzgbmplZTdwCNjOriQOwmVlNHIDNzGriAGxmVhMHYDOzmjgAm5nVxAHY\nzKwm/x/MpSRMRu0M9AAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f024e942470>"
+       "<matplotlib.figure.Figure at 0x7f3cd3314b70>"
       ]
      },
      "metadata": {},
diff --git a/02_Convolutional_Neural_Network.ipynb b/02_Convolutional_Neural_Network.ipynb
index ee6f239..78218b3 100644
--- a/02_Convolutional_Neural_Network.ipynb
+++ b/02_Convolutional_Neural_Network.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #02\n",
     "# Convolutional Neural Network\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -34,57 +28,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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fRQSBVwVeQjwfexAl5q9q6WsOcDDx/E0F/gZ8OOtzHvF87pLsB/g89WtrjyZ3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\n+y1Eps78iraSJI02M4D9iWV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q8jjjI4AO8HeiBP47gQOAB3s7HEmSJElj2F4UVcyuJSbr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/lzD2OJXvT2WbN7e0sGLFChKJxBHZeqIT9HeCutaDg4NhH7GhoSEUa7XWOI5Da2trxW968Lqr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\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4gVqtxunTp3WAweTkJBMTE3iex86dO7njjjuwbZuJiQmy2SywPdvm+pCEnjyRz6hVng1+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\n4DgO+4+kSaWEtmfs7CJ79v1TY8Q5MB8b5mRul3ZckBKef97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VBHUqlaKvr49cLqdT6S5X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kfRi+pvPPHx8N2taA24BbgIlg2TeZeZDehftnnyrwZ8BJuIcg+ma4nzR8GHceb1uAY8+XNbj7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\nRERERERERERERERERERERERERBar/w89lh7LUZYtOQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "metadata": {},
    "source": [
-    "from IPython.display import Image\n",
-    "Image('images/02_network_flowchart.png')"
+    "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below.\n",
+    "\n",
+    "![Flowchart](images/02_network_flowchart.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled so the image resolution is decreased from 28x28 to 14x14.\n",
     "\n",
@@ -101,59 +61,27 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Convolutional Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows the basic idea of processing an image in the first convolutional layer. The input image depicts the number 7 and four copies of the image are shown here, so we can see more clearly how the filter is being moved to different positions of the image. For each position of the filter, the dot-product is being calculated between the filter and the image pixels under the filter, which results in a single pixel in the output image. So moving the filter across the entire input image results in a new image being generated.\n",
     "\n",
     "The red filter-weights means that the filter has a positive reaction to black pixels in the input image, while blue pixels means the filter has a negative reaction to black pixels.\n",
     "\n",
-    "In this case it appears that the filter recognizes the horizontal line of the 7-digit, as can be seen from its stronger reaction to that line in the output image."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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Ybeb5b6i68weoCYmXUYrZY6h9QnFU3XkTqu60oPbsTSZfQQngn0W1ic+iVljv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\nAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "Image('images/02_convolution.png')"
+    "In this case it appears that the filter recognizes the horizontal line of the 7-digit, as can be seen from its stronger reaction to that line in the output image.\n",
+    "\n",
+    "![Convolution example](images/02_convolution.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The step-size for moving the filter across the input is called the stride. There is a stride for moving the filter horizontally (x-axis) and another stride for moving vertically (y-axis).\n",
     "\n",
@@ -168,23 +96,25 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [],
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -198,30 +128,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
+    "This was developed using Python 3.6.1 (Anaconda) and TensorFlow version:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.1.0'"
+       "'1.4.0'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -232,10 +155,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Configuration of Neural Network\n",
     "\n",
@@ -244,12 +164,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Convolutional Layer 1.\n",
@@ -266,32 +182,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -311,22 +217,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 5,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -348,22 +247,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [],
    "source": [
     "data.test.cls = np.argmax(data.test.labels, axis=1)"
@@ -371,32 +263,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# We know that MNIST images are 28 pixels in each dimension.\n",
@@ -417,32 +299,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -476,28 +348,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210fe38c50>"
+       "<matplotlib.figure.Figure at 0x7f5d6c822588>"
       ]
      },
      "metadata": {},
@@ -517,10 +382,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -543,32 +405,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-functions for creating new variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Functions for creating new TensorFlow variables in the given shape and initializing them with random values. Note that the initialization is not actually done at this point, it is merely being defined in the TensorFlow graph."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def new_weights(shape):\n",
@@ -577,12 +429,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def new_biases(length):\n",
@@ -591,20 +439,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for creating a new Convolutional Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function creates a new convolutional layer in the computational graph for TensorFlow. Nothing is actually calculated here, we are just adding the mathematical formulas to the TensorFlow graph.\n",
     "\n",
@@ -627,12 +469,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def new_conv_layer(input,              # The previous layer.\n",
@@ -696,10 +534,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for flattening a layer\n",
     "\n",
@@ -708,12 +543,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def flatten_layer(layer):\n",
@@ -743,20 +574,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for creating a new Fully-Connected Layer"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function creates a new fully-connected layer in the computational graph for TensorFlow. Nothing is actually calculated here, we are just adding the mathematical formulas to the TensorFlow graph.\n",
     "\n",
@@ -765,12 +590,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def new_fc_layer(input,          # The previous layer.\n",
@@ -795,20 +616,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
     "\n",
@@ -817,12 +632,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')"
@@ -830,22 +641,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])"
@@ -853,22 +657,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
@@ -876,33 +673,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_true_cls = tf.argmax(y_true, dimension=1)"
+    "y_true_cls = tf.argmax(y_true, axis=1)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolutional Layer 1\n",
     "\n",
@@ -911,12 +698,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_conv1, weights_conv1 = \\\n",
@@ -929,22 +712,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Check the shape of the tensor that will be output by the convolutional layer. It is (?, 14, 14, 16) which means that there is an arbitrary number of images (this is the ?), each image is 14 pixels wide and 14 pixels high, and there are 16 different channels, one channel for each of the filters."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 20,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -952,7 +728,7 @@
        "<tf.Tensor 'Relu:0' shape=(?, 14, 14, 16) dtype=float32>"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -963,10 +739,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolutional Layer 2\n",
     "\n",
@@ -975,12 +748,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 21,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_conv2, weights_conv2 = \\\n",
@@ -993,22 +762,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Check the shape of the tensor that will be output from this convolutional layer. The shape is (?, 7, 7, 36) where the ? again means that there is an arbitrary number of images, with each image having width and height of 7 pixels, and there are 36 channels, one for each filter."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 22,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1016,7 +778,7 @@
        "<tf.Tensor 'Relu_1:0' shape=(?, 7, 7, 36) dtype=float32>"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1027,10 +789,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Flatten Layer\n",
     "\n",
@@ -1039,12 +798,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_flat, num_features = flatten_layer(layer_conv2)"
@@ -1052,22 +807,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Check that the tensors now have shape (?, 1764) which means there's an arbitrary number of images which have been flattened to vectors of length 1764 each. Note that 1764 = 7 x 7 x 36."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1075,7 +823,7 @@
        "<tf.Tensor 'Reshape_1:0' shape=(?, 1764) dtype=float32>"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1086,12 +834,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 25,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1099,7 +843,7 @@
        "1764"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1110,10 +854,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Fully-Connected Layer 1\n",
     "\n",
@@ -1122,12 +863,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_fc1 = new_fc_layer(input=layer_flat,\n",
@@ -1138,22 +875,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Check that the output of the fully-connected layer is a tensor with shape (?, 128) where the ? means there is an arbitrary number of images and `fc_size` == 128."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1161,7 +891,7 @@
        "<tf.Tensor 'Relu_2:0' shape=(?, 128) dtype=float32>"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1172,10 +902,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Fully-Connected Layer 2\n",
     "\n",
@@ -1184,12 +911,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 28,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_fc2 = new_fc_layer(input=layer_fc1,\n",
@@ -1200,12 +923,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1213,7 +932,7 @@
        "<tf.Tensor 'add_3:0' shape=(?, 10) dtype=float32>"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1224,32 +943,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predicted Class"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The second fully-connected layer estimates how likely it is that the input image belongs to each of the 10 classes. However, these estimates are a bit rough and difficult to interpret because the numbers may be very small or large, so we want to normalize them so that each element is limited between zero and one and the 10 elements sum to one. This is calculated using the so-called softmax function and the result is stored in `y_pred`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 30,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = tf.nn.softmax(layer_fc2)"
@@ -1257,43 +966,30 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-number is the index of the largest element."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 31,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_pred_cls = tf.argmax(y_pred, dimension=1)"
+    "y_pred_cls = tf.argmax(y_pred, axis=1)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Cost-function to be optimized"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "To make the model better at classifying the input images, we must somehow change the variables for all the network layers. To do this we first need to know how well the model currently performs by comparing the predicted output of the model `y_pred` to the desired output `y_true`.\n",
     "\n",
@@ -1304,12 +1000,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 32,
+   "metadata": {},
    "outputs": [],
    "source": [
     "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=layer_fc2,\n",
@@ -1318,22 +1010,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [],
    "source": [
     "cost = tf.reduce_mean(cross_entropy)"
@@ -1341,20 +1026,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Optimization Method"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now that we have a cost measure that must be minimized, we can then create an optimizer. In this case it is the `AdamOptimizer` which is an advanced form of Gradient Descent.\n",
     "\n",
@@ -1363,12 +1042,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(cost)"
@@ -1376,20 +1051,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Performance Measures"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We need a few more performance measures to display the progress to the user.\n",
     "\n",
@@ -1398,12 +1067,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -1411,22 +1076,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This calculates the classification accuracy by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then calculating the average of these numbers."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 36,
+   "metadata": {},
    "outputs": [],
    "source": [
     "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
@@ -1434,20 +1092,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Run"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -1456,12 +1108,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 37,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session = tf.Session()"
@@ -1469,10 +1117,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1481,12 +1126,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 38,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1494,20 +1135,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1516,12 +1151,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 39,
+   "metadata": {},
    "outputs": [],
    "source": [
     "train_batch_size = 64"
@@ -1529,22 +1160,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for performing a number of optimization iterations so as to gradually improve the variables of the network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Counter for total number of iterations performed so far.\n",
@@ -1601,32 +1225,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred, correct):\n",
@@ -1659,22 +1273,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_confusion_matrix(cls_pred):\n",
@@ -1711,20 +1318,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1735,12 +1336,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 43,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Split the test-set into smaller batches of this size.\n",
@@ -1815,10 +1412,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance before any optimization\n",
     "\n",
@@ -1827,18 +1421,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 44,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.1% (1009 / 10000)\n"
+      "Accuracy on Test-Set: 10.4% (1036 / 10000)\n"
      ]
     }
    ],
@@ -1848,10 +1438,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
@@ -1860,18 +1447,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 45,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:      1, Training Accuracy:  10.9%\n",
       "Time usage: 0:00:00\n"
      ]
     }
@@ -1882,11 +1465,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 46,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1894,7 +1474,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 8.3% (834 / 10000)\n"
+      "Accuracy on Test-Set: 10.9% (1090 / 10000)\n"
      ]
     }
    ],
@@ -1904,10 +1484,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 100 optimization iterations\n",
     "\n",
@@ -1916,11 +1493,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 47,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1938,26 +1512,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 48,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 70.2% (7019 / 10000)\n",
+      "Accuracy on Test-Set: 66.3% (6634 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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KOB01z0VEUlClKSKSgipNEZEUVGmKiKSgSlNEJAVVmlJRw4YNY9iwYZgZZsak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\njdGXqwAAAABJRU5ErkJggg==\n",
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2VC0LoDJu+1TG6ej2XEQkBVWaIiIpqNIUEUlBlaaISAqqNEVEUlClKSKSgipN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\nRURSUKUpIpKCKk0RkRT+HzFENlh4BVlyAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210fe38d68>"
+       "<matplotlib.figure.Figure at 0x7f5d69ee22e8>"
       ]
      },
      "metadata": {},
@@ -1970,10 +1540,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1000 optimization iterations\n",
     "\n",
@@ -1982,11 +1549,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 49,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1994,15 +1558,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    201, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    301, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    101, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    201, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    301, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    401, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    601, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    701, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    901, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    601, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    701, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    801, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    901, Training Accuracy:  96.9%\n",
       "Time usage: 0:00:03\n"
      ]
     }
@@ -2013,11 +1577,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 50,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2025,15 +1586,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 93.0% (9303 / 10000)\n",
+      "Accuracy on Test-Set: 93.3% (9329 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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vwTFLlmSWKw/P/oqEJZYnT57c4O9g7bXXzm6ffvrpVJIiTRGRFCoWaf75z38G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\nNEVEUlChKSKSggpNEZEUVGiKiKTw/wFYhGeufg/ivgAAAABJRU5ErkJggg==\n",
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EiUhebNqUnBDJd4+aM2dOyuPFixcD0K5dOwAuvDC5+OV++yVWsMmaIk0RkRhqVKTpI8xr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\nIiIxqNAUEYlBhaaISAwqNEVEYvh/h7Uqj5EaReEAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210fe38400>"
+       "<matplotlib.figure.Figure at 0x7f5d6a4b4c88>"
       ]
      },
      "metadata": {},
@@ -2046,10 +1607,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 10,000 optimization iterations\n",
     "\n",
@@ -2058,11 +1616,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 51,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2072,95 +1627,95 @@
      "text": [
       "Optimization Iteration:   1001, Training Accuracy:  93.8%\n",
       "Optimization Iteration:   1101, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1201, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1401, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1501, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1701, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   1801, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1901, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   2101, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2301, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2401, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   2501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2301, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2501, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   3401, Training Accuracy:  93.8%\n",
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+      "Optimization Iteration:   8301, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   8501, Training Accuracy:  95.3%\n",
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-      "Optimization Iteration:   8801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8801, Training Accuracy:  93.8%\n",
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-      "Optimization Iteration:   9001, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   9001, Training Accuracy: 100.0%\n",
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-      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9301, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9401, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9901, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:25\n"
+      "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:27\n"
      ]
     }
    ],
@@ -2170,11 +1725,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 52,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2182,15 +1734,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.6% (9859 / 10000)\n",
+      "Accuracy on Test-Set: 98.5% (9852 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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KcM011yS3fU3AR5rvv/8+ENYUfC0iOjm233fPPfekvJ4+fToAzz77bPLYFi1y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\nYII=\n",
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gjE8K+722BbJZuetx4NTwOPsDHzvnGlPTPE0+yzj87N4DzApbZPHXyqmMCbvq9gOeyCZ9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\nAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210fe38cf8>"
+       "<matplotlib.figure.Figure at 0x7f5d6a553a58>"
       ]
      },
      "metadata": {},
@@ -2201,23 +1753,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 975    0    0    0    0    1    1    1    2    0]\n",
-      " [   0 1128    1    2    1    0    1    1    1    0]\n",
-      " [   5    5 1002    7    1    0    0    6    5    1]\n",
-      " [   1    0    0 1008    0    0    0    0    1    0]\n",
-      " [   0    0    1    0  981    0    0    0    0    0]\n",
-      " [   1    0    0   17    0  870    1    1    1    1]\n",
-      " [   7    2    0    0    4    4  940    0    1    0]\n",
-      " [   1    2    3    3    0    0    0 1017    1    1]\n",
-      " [   3    1    1    6    1    1    0    2  957    2]\n",
-      " [   2    4    0    5    9    2    0    4    2  981]]\n"
+      "[[ 970    0    1    0    0    2    2    1    4    0]\n",
+      " [   0 1127    3    0    2    0    1    1    1    0]\n",
+      " [   0    2 1022    1    2    0    0    4    1    0]\n",
+      " [   0    0    2  999    0    3    0    4    2    0]\n",
+      " [   0    0    0    0  982    0    0    0    0    0]\n",
+      " [   1    0    1    7    1  879    1    1    0    1]\n",
+      " [   4    2    1    0   12    8  931    0    0    0]\n",
+      " [   0    1    5    0    1    0    0 1018    1    2]\n",
+      " [   3    1    3    3    4    3    0    3  950    4]\n",
+      " [   1    4    0    1   18    3    0    6    2  974]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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2Ext9CLhU0g7AfcAHKalOJZ0B3A+8pxz7XeAEYDXwTDm2J9sMJJL+ni00vmxv3j+LiB7U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\nYwkkEdFYAklENPb/ASgZ5rtZMyYUAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210d4ea710>"
+       "<matplotlib.figure.Figure at 0x7f5d69c24668>"
       ]
      },
      "metadata": {},
@@ -2231,10 +1783,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Visualization of Weights and Layers\n",
     "\n",
@@ -2243,22 +1792,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 53,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_conv_weights(weights, input_channel=0):\n",
@@ -2309,22 +1851,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting the output of a convolutional layer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 54,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_conv_layer(layer, image):\n",
@@ -2374,32 +1909,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Input Images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Helper-function for plotting an image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 55,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_image(image):\n",
@@ -2412,28 +1937,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot an image from the test-set which will be used as an example below."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 56,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2101cde400>"
+       "<matplotlib.figure.Figure at 0x7f5d69ee2630>"
       ]
      },
      "metadata": {},
@@ -2447,28 +1965,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot another example image from the test-set."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 57,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f21019c4828>"
+       "<matplotlib.figure.Figure at 0x7f5d6a483dd8>"
       ]
      },
      "metadata": {},
@@ -2482,20 +1993,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 1"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the first convolutional layer.\n",
     "\n",
@@ -2504,19 +2009,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 58,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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GljY06LUWL/bNbG7Wmc2bdebQId+8qLS1md19t4wdcDziXD9f/qLbqqtlZl6TfrhveUw/\nKT1KTVN77NC6n+tg9fUysv+6z7lmOva3W7vjBoNxoabG7K67dG7VKhnpmOo40cDMpt7xcZnpdDwt\nfcQ1jW+UACBRlAAgUJQAIFCUACBQlAAgUJQAIFCUACBQlAAgUJQAIOR3Z04sZnbNNTrnuONg9Omn\nXSOLSkp06J13dGZw0DUvMkFg5vi3LnDchZTZsME303HEwOsVFTLje5h+hMLQzHP0yD33yIjjcAEz\nM8s4MvW33OJb7NVXnVOjcaSrwSY+/W8yN3C1zkx9ZJFrZm9GX+FOxzq+A2n4RgkAEkUJAAJFCQAC\nRQkAAkUJAAJFCQACRQkAAkUJAEJ+G85ra83uv1/nHBt3i4p9o3+R1o+G9+w374gdcc2LymjTtdZ/\nICVz5Uf1kRa1X/yia2Zm+3aZmelYp8w1LUJnzvg+tw88ICP1I77DA2odm8R7C3wjudeMGWYPP+wI\njkzRmRdecM3s/PSnZeb6JUtkZuLBg655fKMEAIGiBACBogQAgaIEAIGiBACBogQAgaIEAIGiBACB\nogQAIQjD0B8Ogi4zaxu7lzOmpodhWBP1i7gUru3YGefX1ozrO5Zc1zavogSADyN+egOAQFECgEBR\nAoBAUQKAQFECgEBRAoBAUQKAQFECgEBRAoDwP5HkrDa+mXUKAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2101d870f0>"
+       "<matplotlib.figure.Figure at 0x7f5d69bff710>"
       ]
      },
      "metadata": {},
@@ -2529,29 +2031,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Applying each of these convolutional filters to the first input image gives the following output images, which are then used as input to the second convolutional layer. Note that these images are down-sampled to 14 x 14 pixels which is half the resolution of the original input image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 59,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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R2bhxY11zLjgv5v6tra2V+vr66Gc3rUSZSCRk1apVmd9VAY0fP77Qt5BSIpGQlStXFvo2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\n2gAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210889c2e8>"
+       "<matplotlib.figure.Figure at 0x7f5d6a55c780>"
       ]
      },
      "metadata": {},
@@ -2564,29 +2060,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following images are the results of applying the convolutional filters to the second image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 60,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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9+rTqZDbtjp5XIYSQBENHSQghAegoCSEkQFJilH62Mc7X9QOGMObQsGFD1Rh3FLGdcXwa\nB8Y9o5AO5MH0IGzAK2JjYD/60Y+MDeM3GIvzFTyYVrRp0yZjw88uivFfTDfxHauKAxsa4z08bdo0\ns664DkFYEXXu3Dlji+J97Odu16lTR7WPd+O+Yfrftm3bzDofl0dwuB6myon8b4ezENG78wkhJMHQ\nURJCSICEPd9fuHBBtW+u+b3vfU/1jh07jA1nY2Bz1Ly8PLMO0y5w1oiIyKBBg1SX9pE6FcBjnk+B\n2L9/v+rly5cbG+4L/h2+n0j8Bg8itvlpFGemd+/eXbUP9xQHNneZNGmSamwwLfK/c+yRy5XaUpHg\nLCDf0AVT2/zROzMzU/WiRYtU+8ocBJswi9j7vLx+gU+UhBASgI6SEEIC0FESQkiAhMUoMXXEx1se\neeQR1cuWLTM2HD6Uk5OjGmeBi9iyxWHDhhlb06ZNy3DFqQM22vXdlzAGtmDBAmPDtJWbb75Z9aOP\nPmrWYazs2muvNbbrrruuDFecOuB9i3F2Ebt/vrwRY+29e/dWPXbsWLMOm1H79Bj/34si+HsCftdF\nbAPuW265xdgwVev++++P+/67d+9W7fe3QYMGpbvYYuATJSGEBKCjJISQAElJ/69WrZp5jZU07dq1\nMzac841Z9z5VA4+Et912m7FFsYohHn7uSH5+vuqNGzca28yZM1U/88wzqn0KEDZF7tatm7H5GUdR\nxlceYbqJP3rjPvk9Q7CyyXfVikL3pdLg0waxM9VPfvITY5szZ45q3EPftBtTD8eMGWNsiQzJ8YmS\nEEIC0FESQkgAOkpCCAlwWYJ7GKMcMGCAseFwJ+wedMMNN5h12JGouI4sUcfHYzFe67vH+xnTF/Hd\nnWKxmGpf3pjOYJwcO/2UBuwK5Dvzpxu+axWmUmG8UsSW5mLp40033WTWjR49WjWW2yYaPlESQkgA\nOkpCCAmQUZqOKRkZGfkikhNcWDmJFRUVNQwvqxi4t8kjxfdWhPubTEq0t6VylIQQko7w6E0IIQHo\nKAkhJAAdJSGEBKCjJISQAHSUhBASgI6SEEIC0FESQkiAUtV6Z2VlFWFdcCqRk5MjBQUFGRV9HfHg\n3iaPzMzMIl/fnkqsW7euoDInnGdmZqb0vVtYWBi8d0vlKGOxmKxYsaLsV1WBVPbZL9zb5JGdnS1L\nliyp6MsoM3Xr1q3UVS+xWCxl99fPoIoHj96EEBLgss9QOHv2rHmdm5urGlsrYXsqEZFmzZqpbtmy\npbGxNdh/8SMeDhw4oHrv3r1x/w6PTb59vh/rka6cOnXKvF63bp1qnB7qWwB26tRJtT+eptOYjRD+\n3v38889V41TXirof+URJCCEB6CgJISQAHSUhhAS4LDFKjOHMnz/f2KZPn656y5Ytqn0sc8iQIar9\naMthw4Yl5DpTERxR8Pbbbxvbu+++qxpjaseOHTPr+vTpo/rJJ580toEDBybkOlMRzEJ45ZVXjG3u\n3LmqceRykyZNzDocpzpy5Ehj6969eyIuM2XJy8tT7X+TwLEOflRwScHPpbzwiZIQQgLQURJCSICk\nHL1xapqIyLx581T/6le/MjZMA7jiiq/8dvPmzc26L774Iu774+sGDRqU4YpTh+PHj5vXq1evVu0n\n2R09elQ1VqYcPHjQrFu7dq3qN99809h69eqlGtM0osiePXvM66efflr1tm3bjO3ChQuqMeHep6q1\nb99edf369Y0NPx9viyI+5HP48GHVPmSBx+2JEyeq3rBhg1n3/PPPq+7SpUtCrvNS8ImSEEIC0FES\nQkgAOkpCCAmQlBilj+dgCpAvBbvhhhtUv/jii6o/+OADs27Xrl1x32PTpk2XfL8o4ksRcS8aN25s\nbG3atFF95513qvZxngkTJqieMWOGsX3jG99Q3a9fv9JfcAoxa9Ys83rz5s2qr776amPDe65Vq1aq\nMe4mItKw4VdNf3yMbseOHarTIUaJ32ERkcLCQtU+Rjl16lTVixYtUv3JJ5+YdWPGjIlrw3hxeVOF\n+ERJCCEB6CgJISRAwo7eWEnj01QwpQW7AImITJkyRTV2BfIpQJjFf/78+bjvj2kbIjblKFXBqgX/\n78nPz1d98uRJY4vXcclXhGBK0MqVK43t/fffV923b19jy8iotL16SwyGLjCNTcR2qnnqqaeMDY/b\nmLqGx3UR+13wFWWNGjVSHcX7VsT6BawOExG58sqv3E/Pnj2NDUMRjz/+uGofHsEQyIIFC4zt5ptv\nLsMVX5pofBqEEJJE6CgJISQAHSUhhARIWIwSYz0YNxCxP/2PGDHC2K655hrVp0+fVu07hmzfvl11\nlSpVjA1jbmfOnDE2n9aRiuC/yXfQxjI4/2/H8jncB9xnEZHHHntM9fjx440NU718F2p/LakIdoE/\nceKEsQ0YMEA1dgHy4L74WCOWh6IWseWhPq0oKuWiuKe+/La4GC3G1zHNzYMxUL+HiYRPlIQQEoCO\nkhBCAiTs6I2pKT61p0aNGqpHjx5tbL5B70X8sQ6PNz7LPt57RAUMNfjjNaajtGvXztgwnae4VB78\nfHzqFXZ38sejKICNj/1x14eJEF8ddhEfFsLvwqFDh+K+XxTCGJcC0/q8X8CwW926dY0N1+L9icPa\nROzxPZlhNj5REkJIADpKQggJkLCjd3G//NWpU+eS60RsowBc5482mMXvj0jYDCIKv3J78N/rj8Y4\nj8g3LS7pL6dYgeKbE+BnEpVqEQQzAPAYJyLyta99Le7f4X2LzRf88Rr3zM9Mj7cuSuD3vbhfpbF5\niEj8/fBhN8yO8d99/G7UrFnT2Eo7Hzyanw4hhCQQOkpCCAlAR0kIIQESFqPEWEHnzp2NDeM5mI4h\nYuOZ+NP/1q1bzTrs0OKrdnCokK86iRpdu3Y1rzFdyO9Zbm6u6tatW6vevXu3WYepGP79ceZ31apV\ny3DFlZtYLKYa/60ixf97seksxs9nz54dd53vkJMOYGqP/91h5syZqrEBr4hIrVq1Lvl3WEklYud/\nd+vWzdhwiB5+zmWBT5SEEBKAjpIQQgIk7OiNKRK33nqrseER0M8NwcazH374oWp8LBexj9+TJk0y\nNl+tEmXwSCIiMmTIENWrVq0ytmnTpqnG8IRvToApHHiMFBEZNGiQ6ig06vVgSMJX4mAqlq/+Wrhw\noWpsSOs/A/x8POWd45IKNG/eXDU2OxaxjW5+97vfGdvkyZNV4xEaj9oitrEI+hIRmwJU3rRBPlES\nQkgAOkpCCAlAR0kIIQESFqPEVIoOHToYG8YKfDxx7ty5qgsKClTjQC0R22kEZ02LRD8lCPEloC+/\n/LJqn2KBaUD4GWRnZ5t1WC7mZ3dnZWWV/WJTAExf8fuCKWnFdbPCDjl+trofSoYUFRWV7mJTEOwK\n5L+3b7zxhmofr/3nP/+peuzYsao//fRTs27Lli2qfcmuT1MsD3yiJISQAHSUhBASIGFHbwRThURs\nWoDvLIRpAMuWLVONc6hF7Fwcf/xMJ3z3IDy+zZgxw9gw3QqPmP44jR1v/NExiilB8fDNYzGlxIeM\n8L5FXRx4lE9HevToYV7jMXrNmjXGhvPl8RiemZlp1mH60dChQ43Nd9MqD3yiJISQAHSUhBASgI6S\nEEICJCVG6eNaGLP08UWMsQ0bNizue6ZTClBpwJiv3yMsW0R8vA3nJvsSxnTC37fFpbWlU9lsovBd\ny7Fk1KelffTRR6pxwJ3vhN6xY0fViYxJevhESQghAegoCSEkQEZpqgMyMjLyRSQnuLByEisqKmoY\nXlYxcG+TR4rvrQj3N5mUaG9L5SgJISQd4dGbEEIC0FESQkgAOkpCCAlAR0kIIQHoKAkhJAAdJSGE\nBKCjJISQAKUq7M3KyiryIydThb1790pBQUGlba6YlZVVFIvFKvoyykROTg73NomsXbu2oDInnKfy\n/pb03i2Vo2zVqpVpBptK9O7du6IvoVhisZisXr26oi+jTPiGBpWNWCxmGsGmGtWrV6/UVS+pvL8D\nBw4s0bqUaRWDFUTp1HW7NPiONvv27VONw5tq1apl1uHTgB+iRf6L31scKHb06FHV/t5s1KiRat+d\nGzuopzu+qxh2Pz958qRq34W+adOmyb2w/4cxSkIICUBHSQghAegoCSEkwGWPURYWFprXGATOyfkq\nZn3u3DmzDqcD9u3b19jatm2byEtMKTZv3qwap1iK2P3EH4qOHz9u1o0cOVL1ww8/bGw45S7d2L17\nt+p58+YZ27///W/Ve/bsUe3jjnfccYfqe++919jat2+fkOtMVXbs2KF60aJFxnbkyBHVuKc4TVRE\nZNCgQap79eplbInsQs8nSkIICUBHSQghAS7L0Ts3N1f1s88+a2yvv/666hMnTqj2g7KaNGmi+he/\n+IWxTZgwISHXmQpg2oSIHcK0YsUKY8OhTHjMOXTokFl39uxZ1X369DG2dDp6+7DQq6++qvq5554z\nNhw8hgPZ/AAtTMuqWrVqXBsO4IsqeJwWEfnHP/6hGlPZRGxa1bp161TPnj3brBs1apTq559/3tgw\nXFde+ERJCCEB6CgJISQAHSUhhARISozSxxdnzJih+m9/+5uxnT9/XnWzZs1UX7hwwazDEqc5c+YY\n2/Dhw1VHPeUC04FERLZt26a6fv36xtauXTvVP/vZz1RjaouI3c/ly5cbG6ZctGjRogxXnDqsWrXK\nvP7Tn/6k+tSpU8aGKWq4t1OnTjXr8O8w3UjE3tPpEKNcuHCheb1161bV1atXNza8lzE9qGFD2xtk\n06ZNqvH3DhGRyZMnqy5vqhCfKAkhJAAdJSGEBEjK0dsfD9966y3VPn2ic+fOqidNmqTaH3VeeOEF\n1fv37ze2xYsXq47i0RtDGf4IUVz6CVYtDBgwQHWPHj3Mui1btqg+duyYse3cuVN1FI/euJ8+pIPp\nVa1btza2l19+WTWGjHwbwnfeeUc1prmIiFxzzTWqfajJf09SFUw983uDNgwTidhqu/79+6vu1KmT\nWffmm2+qxmO4iPUT/sheWqLxaRBCSBKhoySEkAB0lIQQEiBhMUrsQI4liyIiBw8eVF2zZk1ju/PO\nO1VjpxVf7oQdWnx6C8Z+fNchLC9LVbDbz4EDB4wNYy8+RonxHNyX4mKZGK8UselbUdxb7E7uY2iY\nsvPDH/7Q2DBmiXFO3EsRWwbpuzs99NBDqv3eRqXTfH5+vmr/ncY4bMeOHY0N4+E9e/ZU7bvzz58/\nXzX6IBGRw4cPq2aMkhBCkgwdJSGEBEjY2QlTKfCoLWKz7n1Hj9GjR6vGjiz+iI6P4r7yp6CgQLVP\nn4nC8RCPFHiUEbHpQTfeeKOxYdoKgmkZIjY1xe8tdnTCY7hINPYWj2eoRezgqvvuu8/Y/B5exFdH\n4ZEa99LbonLU9mC3K9+dCX2B/75nZWWpxlCRX1evXj3VPsUKfVJ54RMlIYQEoKMkhJAACTs74S+z\n/oiBRzY/36ZDhw6XfD9fmYAVI/7XLTzC+MfvKIAhCT//GCtnRowYUaL380egOnXqqPaNen2zgqhR\nXNUTHr39rBasHEObn0eE4Qn/HtjswWciRAUMUfh7F7/HOFv+Uq8v4vcX708/8xvf3x/D/WcRgk+U\nhBASgI6SEEIC0FESQkiApOR3VKlSxf5HIE6D6SwiNt0FY0InT5406/DvfBwNs/oxnhcVMOXEx25w\nLvr69euNrWvXrqoxfoNVTiI2RpmdnW1s2NUlinuL+9KmTRtjy8jIUI0Nkv3fYXwRh72J2PQV/DxE\nbOVPImdQVyYyMzNVY8qPiE3H8vfutddeqxpjm36AHt6vfq433q/eJ5UWPlESQkgAOkpCCAmQsKM3\nHt98c008KvuKBjyq4IzeN954w6zDlCNf3XPXXXepjmqFw0XGjRtnXq9evVo1ziAREXn77bdV41HR\nN0XG6gl/tG/VqlWZrzUVwHDPd77zHWPbsGGDagxxiNi0tvfee0/13//+d7MOw0633nqrsUX1uI3g\n/TN48GBjw0bJS5YsMTYMg2AYzldP4dHbh04wBai8YSM+URJCSAA6SkIICUBHSQghARIWo8SGmn36\n9DE27BC0YMECY5s1a5bqNWvWqPZldhij9HEz3/QzyvhSt4kTJ6qePn26sWHKBTaa9eVbmDqBTVIv\n9d+LGhiKBzA5AAABm0lEQVRb9yWgxaWU5OXlqcaGv77kExv5Dh061NjSIUaJ98/tt99ubPidxv0U\nsU2OMa3Ip69hQ15fpojD28oLnygJISQAHSUhhARISmWOn0+Bs3D8Uc7POr6IPx5ihv83v/lNY/Nz\nNKKMb56Lx4vf/OY3xoZHQpxX4rus4Cz0Ro0aJeQ6UxGfGjVs2DDVflYRdv7B4zumuImI3Hbbbap9\n95x0A7/DIiJjx45VvXTpUmPDLkFY3eT3EI/bLVu2NDbf5Lc88ImSEEIC0FESQkgAOkpCCAmQlBil\n706OJYff+ta3jG348OGq9+3bp9rHHXG4GMYs0h3s6O6HffXv3/9yX05K4+9bTKnycXfsjI5xYoxd\niqRHClBZadKkiWosQxaxAwqxhNGXImIJqt/7RMInSkIICUBHSQghATL8oK5iF2dk5ItITvIuJ6nE\nioqKGoaXVQzc2+SR4nsrwv1NJiXa21I5SkIISUd49CaEkAB0lIQQEoCOkhBCAtBREkJIADpKQggJ\nQEdJCCEB6CgJISQAHSUhhASgoySEkAD/B7Xpsh8LsAMyAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f210b123438>"
+       "<matplotlib.figure.Figure at 0x7f5d704ca048>"
       ]
      },
      "metadata": {},
@@ -2599,30 +2089,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "It is difficult to see from these images what the purpose of the convolutional filters might be. It appears that they have merely created several variations of the input image, as if light was shining from different angles and casting shadows in the image."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 2"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the second convolutional layer.\n",
     "\n",
@@ -2633,19 +2114,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 61,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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RR0Q+7MfTzBpr4Z6tW+3j9Fm9UmQlDz4YdXwA/8wnInKCzZSIyAE2UyIiB2K6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\n+G+SXKUoMYZfOgAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2101c042b0>"
+       "<matplotlib.figure.Figure at 0x7f5d6a510828>"
       ]
      },
      "metadata": {},
@@ -2658,28 +2136,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 62,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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EEyEPzaiYGPFZz1sP36+WjHLLufZoIhFRVRXPnnsuyNgMueIKoh07hAP7B6g1JybcK+Z5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\nKQCAAWimAAAGoJkCABiAZgoAYMD/AM6smdqQb8ZdAAAAAElFTkSuQmCC\n",
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kfjAtjWcJ8bnGnh6id6v5ub4xln+P+mfC3uxE9GB5SC9RNmhf7nEWSxkdF2ly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\nYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2101cbfeb8>"
+       "<matplotlib.figure.Figure at 0x7f5d6820d860>"
       ]
      },
      "metadata": {},
@@ -2692,10 +2163,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "It can be difficult to understand and keep track of how these filters are applied because of the high dimensionality.\n",
     "\n",
@@ -2706,19 +2174,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 63,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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PZPSZX1JSYvKgf/DBB0qjf1FEZNGiRUpXV1ebOpMmTVJ67NixSkcV7qukpESOOeYYVYZh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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f21014f8160>"
+       "<matplotlib.figure.Figure at 0x7f5d6820db38>"
       ]
      },
      "metadata": {},
@@ -2731,29 +2196,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "And these are the results of applying the filter-weights to the second image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 64,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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OO+00pXGBQsQuSnXvnkhVCydBEJjg+q5duyr9t7/9zYxbs2aN0h999JHpM3Pm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\ngg==\n",
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5scE8C5jMpaHBBDR33nmnsWnXrp3SuFAsYg/h4MJa2MMJfDIlhBAP0JkSQogH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\nMyWEEA/QmRJCiAfoTAkhxAP/DxkSP5EwP1q5AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f21019781d0>"
+       "<matplotlib.figure.Figure at 0x7f5d6a510320>"
       ]
      },
      "metadata": {},
@@ -2766,10 +2225,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "From these images, it looks like the second convolutional layer might detect lines and patterns in the input images, which are less sensitive to local variations in the original input images.\n",
     "\n",
@@ -2778,32 +2234,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 65,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2813,10 +2259,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2829,10 +2272,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2857,10 +2297,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2895,5 +2332,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

From ce5b79251bd12689fa4a39a9920a3eb4c58978f0 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 4 Jan 2018 08:32:16 +0100
Subject: [PATCH 32/61] Tutorial 16, added note about compatibility issues.

---
 16_Reinforcement_Learning.ipynb | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index 21fef0d..505f087 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -533,6 +533,10 @@
     "\n",
     "You can download a TensorFlow checkpoint which holds all the pre-trained variables for the Neural Network. Two checkpoints are provided, one for Breakout and one for Space Invaders. They were both trained for about 150 hours on a laptop with 2.6 GHz CPU and a GTX 1070 GPU.\n",
     "\n",
+    "#### COMPATIBILITY ISSUES\n",
+    "\n",
+    "These TensorFlow checkpoints were developed with OpenAI gym v. 0.8.1 and atari-py v. 0.0.19 which had unused / redundant actions as noted above. There appears to have been a change in the gym API since then, as the unused actions are no longer present. This means the vectors with actions and Q-values now only contain 4 elements instead of the 6 shown here. This also means that the TensorFlow checkpoints cannot be used with newer versions of gym and atari-py, so in order to use these pre-trained checkpoints you need to install the older versions of gym and atari-py - or you can just train a new model yourself so you get a new TensorFlow checkpoint.\n",
+    "\n",
     "#### WARNING!\n",
     "\n",
     "These checkpoints are 280-360 MB each. They are currently hosted on the webserver I use for [www.hvass-labs.org](www.hvass-labs.org) because it is awkward to automatically download large files on Google Drive. To lower the traffic on my webserver, this line has been commented out, so you have to activate it manually. You are welcome to download it, I just don't want it to download automatically for everyone who only  wants to run this Notebook briefly."
@@ -4874,7 +4878,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

From 395c4eed813b10d5b7ec8b76b0d7665e34e69795 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 11 Jan 2018 22:04:10 +0100
Subject: [PATCH 33/61] Added Tutorial 19

---
 19_Hyper-Parameters.ipynb                     | 2215 +++++++++++++++++
 README.md                                     |    2 +
 images/19_flowchart_bayesian_optimization.png |  Bin 0 -> 314040 bytes
 images/19_flowchart_bayesian_optimization.svg |  971 ++++++++
 4 files changed, 3188 insertions(+)
 create mode 100644 19_Hyper-Parameters.ipynb
 create mode 100644 images/19_flowchart_bayesian_optimization.png
 create mode 100644 images/19_flowchart_bayesian_optimization.svg

diff --git a/19_Hyper-Parameters.ipynb b/19_Hyper-Parameters.ipynb
new file mode 100644
index 0000000..ca10b25
--- /dev/null
+++ b/19_Hyper-Parameters.ipynb
@@ -0,0 +1,2215 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #19\n",
+    "# Hyper-Parameter Optimization\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "There are many parameters you can select when building and training a Neural Network in TensorFlow. These are often called Hyper-Parameters. For example, there is a hyper-parameter for how many layers the network should have, and another hyper-parameter for how many nodes per layer, and another hyper-parameter for the activation function to use, etc. The optimization method also has one or more hyper-parameters you can select, such as the learning-rate.\n",
+    "\n",
+    "One way of searching for good hyper-parameters is by hand-tuning, where you try one set of parameters and see how they perform, and then you try another set of parameters and see if they improve the performance. You try and build an intuition for what works well and guide your parameter-search accordingly. Not only is this extremely time-consuming for a human researcher, but the optimal parameters are often counter-intuitive to humans so you will not find them!\n",
+    "\n",
+    "Another way of searching for good hyper-parameters is to divide each parameter's valid range into evenly spaced values, and then simply have the computer try all combinations of parameter-values. This is called Grid Search. Although it is run entirely by the computer, it quickly becomes extremely time-consuming because the number of parameter-combinations increases exponentially as you add more hyper-parameters. This problem is known as the Curse of Dimensionality. For example, if you have just 4 hyper-parameters to tune and each of them is allowed 10 possible values, then there is a total of 10^4 parameter-combinations. If you add just one more hyper-parameter then there are 10^5 parameter-combinations, and so on.\n",
+    "\n",
+    "Yet another way of searching for good hyper-parameters is by random search. Instead of systematically trying every single parameter-combination as in Grid Search, we now try a number of parameter-combinations completely at random. This is like searching for \"a needle in a haystack\" and as the number of parameters increases, the probability of finding the optimal parameter-combinations by random sampling decreases to zero.\n",
+    "\n",
+    "This tutorial uses a clever method for finding good hyper-parameters known as Bayesian Optimization. You should be familiar with TensorFlow, Keras and Convolutional Neural Networks, see Tutorials #01, #02 and #03-C."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "The problem with hyper-parameter optimization is that it is extremely costly to assess the performance of a set of parameters. This is because we first have to build the corresponding neural network, then we have to train it, and finally we have to measure its performance on a test-set. In this tutorial we will use the small MNIST problem so this training can be done very quickly, but on more realistic problems the training may take hours, days or even weeks on a very fast computer. So we need an optimization method that can search for hyper-parameters as efficiently as possible, by only evaluating the actual performance when absolutely necessary.\n",
+    "\n",
+    "The idea with Bayesian optimization is to construct another model of the search-space for hyper-parameters. One kind of model is known as a Gaussian Process. This gives us an estimate of how the performance varies with changes to the hyper-parameters. Whenever we evaluate the actual performance for a set of hyper-parameters, we know for a fact what the performance is - except perhaps for some noise. We can then ask the Bayesian optimizer to give us a new suggestion for hyper-parameters in a region of the search-space that we haven't explored yet, or hyper-parameters that the Bayesian optimizer thinks will bring us most improvement. We then repeat this process a number of times until the Bayesian optimizer has built a good model of how the performance varies with different hyper-parameters, so we can choose the best parameters.\n",
+    "\n",
+    "The flowchart of the algorithm is roughly:\n",
+    "\n",
+    "![Flowchart](images/19_flowchart_bayesian_optimization.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-test/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need to import several things from Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Sequential  # This does not work!\n",
+    "from tensorflow.python.keras import backend as K\n",
+    "from tensorflow.python.keras.models import Sequential\n",
+    "from tensorflow.python.keras.layers import InputLayer, Input\n",
+    "from tensorflow.python.keras.layers import Reshape, MaxPooling2D\n",
+    "from tensorflow.python.keras.layers import Conv2D, Dense, Flatten\n",
+    "from tensorflow.python.keras.callbacks import TensorBoard\n",
+    "from tensorflow.python.keras.optimizers import Adam\n",
+    "from tensorflow.python.keras.models import load_model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**NOTE:** We will save and load models using Keras so you need to have [h5py](http://docs.h5py.org/en/latest/build.html#install) installed. You also need to have [scikit-optimize](https://scikit-optimize.github.io/) installed for doing the hyper-parameter optimization.\n",
+    "\n",
+    "You should be able to run the following command in a terminal to install them both:\n",
+    "\n",
+    "`pip install h5py scikit-optimize`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**NOTE:** This Notebook requires features in `scikit-optimize` that have not been merged into the official release at the time of this writing. If this Notebook cannot run with the version of `scikit-optimize` installed by the command above, you may have to install `scikit-optimize` from a development branch by running the following command instead:\n",
+    "\n",
+    "`pip install git+git://github.com/Hvass-Labs/scikit-optimize.git@610ce8d3e3e82d76f798ad90984c5888a204884e`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import skopt\n",
+    "from skopt import gp_minimize, forest_minimize\n",
+    "from skopt.space import Real, Categorical, Integer\n",
+    "from skopt.plots import plot_convergence\n",
+    "from skopt.plots import plot_objective, plot_evaluations\n",
+    "from skopt.plots import plot_histogram, plot_objective_2D\n",
+    "from skopt.utils import use_named_args"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.4.0'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.0.8-tf'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.4'"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "skopt.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hyper-Parameters\n",
+    "\n",
+    "In this tutorial we want to find the hyper-parametes that makes a simple Convolutional Neural Network perform best at classifying the MNIST dataset for hand-written digits.\n",
+    "\n",
+    "For this demonstration we want to find the following hyper-parameters:\n",
+    "\n",
+    "* The learning-rate of the optimizer.\n",
+    "* The number of fully-connected / dense layers.\n",
+    "* The number of nodes for each of the dense layers.\n",
+    "* Whether to use 'sigmoid' or 'relu' activation in all the layers.\n",
+    "\n",
+    "We will use the Python package `scikit-optimize` (or `skopt`) for finding the best choices of these hyper-parameters. Before we begin with the actual search for hyper-parameters, we first need to define the valid search-ranges or search-dimensions for each of these parameters.\n",
+    "\n",
+    "This is the search-dimension for the learning-rate. It is a real number (floating-point) with a lower bound of `1e-6` and an upper bound of `1e-2`. But instead of searching between these bounds directly, we use a logarithmic transformation, so we will search for the number `k` in `1ek` which is only bounded between -6 and -2. This is better than searching the entire exponential range."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dim_learning_rate = Real(low=1e-6, high=1e-2, prior='log-uniform',\n",
+    "                         name='learning_rate')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the search-dimension for the number of dense layers in the neural network. This is an integer and we want at least 1 dense layer and at most 5 dense layers in the neural network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dim_num_dense_layers = Integer(low=1, high=5, name='num_dense_layers')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the search-dimension for the number of nodes for each dense layer. This is also an integer and we want at least 5 and at most 512 nodes in each layer of the neural network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dim_num_dense_nodes = Integer(low=5, high=512, name='num_dense_nodes')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the search-dimension for the activation-function. This is a combinatorial or categorical parameter which can be either 'relu' or 'sigmoid'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dim_activation = Categorical(categories=['relu', 'sigmoid'],\n",
+    "                             name='activation')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We then combine all these search-dimensions into a list."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dimensions = [dim_learning_rate,\n",
+    "              dim_num_dense_layers,\n",
+    "              dim_num_dense_nodes,\n",
+    "              dim_activation]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is helpful to start the search for hyper-parameters with a decent choice that we have found by hand-tuning. But we will use the following parameters that do not perform so well, so as to better demonstrate the usefulness of hyper-parameter optimization: A learning-rate of 1e-5, a single dense layer with 16 nodes, and relu activation-functions.\n",
+    "\n",
+    "Note that these hyper-parameters are packed in a single list. This is how `skopt` works internally on hyper-parameters. You therefore need to ensure that the order of the dimensions are consistent with the order given in `dimensions` above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "default_parameters = [1e-5, 1, 16, 'relu']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for log-dir-name\n",
+    "\n",
+    "We will log the training-progress for all parameter-combinations so they can be viewed and compared using TensorBoard. This is done by setting a common parent-dir and then have a sub-dir for each parameter-combination with an appropriate name."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_dir_name(learning_rate, num_dense_layers,\n",
+    "                 num_dense_nodes, activation):\n",
+    "\n",
+    "    # The dir-name for the TensorBoard log-dir.\n",
+    "    s = \"./19_logs/lr_{0:.0e}_layers_{1}_nodes_{2}_{3}/\"\n",
+    "\n",
+    "    # Insert all the hyper-parameters in the dir-name.\n",
+    "    log_dir = s.format(learning_rate,\n",
+    "                       num_dense_layers,\n",
+    "                       num_dense_nodes,\n",
+    "                       activation)\n",
+    "\n",
+    "    return log_dir"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
+      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tensorflow.examples.tutorials.mnist import input_data\n",
+    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of:\n",
+      "- Training-set:\t\t55000\n",
+      "- Test-set:\t\t10000\n",
+      "- Validation-set:\t5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Size of:\")\n",
+    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
+    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We use the performance on the validation-set as an indication of which choice of hyper-parameters performs the best on previously unseen data. The Keras API needs the validation-set as a tuple."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "validation_data = (data.validation.images, data.validation.labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# We know that MNIST images are 28 pixels in each dimension.\n",
+    "img_size = 28\n",
+    "\n",
+    "# Images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = img_size * img_size\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "# This is used for plotting the images.\n",
+    "img_shape = (img_size, img_size)\n",
+    "\n",
+    "# Tuple with height, width and depth used to reshape arrays.\n",
+    "# This is used for reshaping in Keras.\n",
+    "img_shape_full = (img_size, img_size, 1)\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = 1\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function for plotting images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_images(images, cls_true, cls_pred=None):\n",
+    "    assert len(images) == len(cls_true) == 9\n",
+    "    \n",
+    "    # Create figure with 3x3 sub-plots.\n",
+    "    fig, axes = plt.subplots(3, 3)\n",
+    "    fig.subplots_adjust(hspace=0.3, wspace=0.3)\n",
+    "\n",
+    "    for i, ax in enumerate(axes.flat):\n",
+    "        # Plot image.\n",
+    "        ax.imshow(images[i].reshape(img_shape), cmap='binary')\n",
+    "\n",
+    "        # Show true and predicted classes.\n",
+    "        if cls_pred is None:\n",
+    "            xlabel = \"True: {0}\".format(cls_true[i])\n",
+    "        else:\n",
+    "            xlabel = \"True: {0}, Pred: {1}\".format(cls_true[i], cls_pred[i])\n",
+    "\n",
+    "        # Show the classes as the label on the x-axis.\n",
+    "        ax.set_xlabel(xlabel)\n",
+    "        \n",
+    "        # Remove ticks from the plot.\n",
+    "        ax.set_xticks([])\n",
+    "        ax.set_yticks([])\n",
+    "    \n",
+    "    # Ensure the plot is shown correctly with multiple plots\n",
+    "    # in a single Notebook cell.\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot a few images to see if data is correct"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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zh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc289fca7f0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the first images from the test-set.\n",
+    "images = data.test.images[0:9]\n",
+    "\n",
+    "# Get the true classes for those images.\n",
+    "cls_true = data.test.cls[0:9]\n",
+    "\n",
+    "# Plot the images and labels using our helper-function above.\n",
+    "plot_images(images=images, cls_true=cls_true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-function to plot example errors\n",
+    "\n",
+    "Function for plotting examples of images from the test-set that have been mis-classified."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_example_errors(cls_pred):\n",
+    "    # cls_pred is an array of the predicted class-number for\n",
+    "    # all images in the test-set.\n",
+    "\n",
+    "    # Boolean array whether the predicted class is incorrect.\n",
+    "    incorrect = (cls_pred != data.test.cls)\n",
+    "\n",
+    "    # Get the images from the test-set that have been\n",
+    "    # incorrectly classified.\n",
+    "    images = data.test.images[incorrect]\n",
+    "    \n",
+    "    # Get the predicted classes for those images.\n",
+    "    cls_pred = cls_pred[incorrect]\n",
+    "\n",
+    "    # Get the true classes for those images.\n",
+    "    cls_true = data.test.cls[incorrect]\n",
+    "    \n",
+    "    # Plot the first 9 images.\n",
+    "    plot_images(images=images[0:9],\n",
+    "                cls_true=cls_true[0:9],\n",
+    "                cls_pred=cls_pred[0:9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hyper-Parameter Optimization\n",
+    "\n",
+    "There are several steps required to do hyper-parameter optimization.\n",
+    "\n",
+    "### Create the Model\n",
+    "\n",
+    "We first need a function that takes a set of hyper-parameters and creates the Convolutional Neural Network corresponding to those parameters. We use Keras to build the neural network in TensorFlow, see Tutorial #03-C for more details."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "def create_model(learning_rate, num_dense_layers,\n",
+    "                 num_dense_nodes, activation):\n",
+    "    \"\"\"\n",
+    "    Hyper-parameters:\n",
+    "    learning_rate:     Learning-rate for the optimizer.\n",
+    "    num_dense_layers:  Number of dense layers.\n",
+    "    num_dense_nodes:   Number of nodes in each dense layer.\n",
+    "    activation:        Activation function for all layers.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Start construction of a Keras Sequential model.\n",
+    "    model = Sequential()\n",
+    "\n",
+    "    # Add an input layer which is similar to a feed_dict in TensorFlow.\n",
+    "    # Note that the input-shape must be a tuple containing the image-size.\n",
+    "    model.add(InputLayer(input_shape=(img_size_flat,)))\n",
+    "\n",
+    "    # The input from MNIST is a flattened array with 784 elements,\n",
+    "    # but the convolutional layers expect images with shape (28, 28, 1)\n",
+    "    model.add(Reshape(img_shape_full))\n",
+    "\n",
+    "    # First convolutional layer.\n",
+    "    # There are many hyper-parameters in this layer, but we only\n",
+    "    # want to optimize the activation-function in this example.\n",
+    "    model.add(Conv2D(kernel_size=5, strides=1, filters=16, padding='same',\n",
+    "                     activation=activation, name='layer_conv1'))\n",
+    "    model.add(MaxPooling2D(pool_size=2, strides=2))\n",
+    "\n",
+    "    # Second convolutional layer.\n",
+    "    # Again, we only want to optimize the activation-function here.\n",
+    "    model.add(Conv2D(kernel_size=5, strides=1, filters=36, padding='same',\n",
+    "                     activation=activation, name='layer_conv2'))\n",
+    "    model.add(MaxPooling2D(pool_size=2, strides=2))\n",
+    "\n",
+    "    # Flatten the 4-rank output of the convolutional layers\n",
+    "    # to 2-rank that can be input to a fully-connected / dense layer.\n",
+    "    model.add(Flatten())\n",
+    "\n",
+    "    # Add fully-connected / dense layers.\n",
+    "    # The number of layers is a hyper-parameter we want to optimize.\n",
+    "    for i in range(num_dense_layers):\n",
+    "        # Name of the layer. This is not really necessary\n",
+    "        # because Keras should give them unique names.\n",
+    "        name = 'layer_dense_{0}'.format(i+1)\n",
+    "\n",
+    "        # Add the dense / fully-connected layer to the model.\n",
+    "        # This has two hyper-parameters we want to optimize:\n",
+    "        # The number of nodes and the activation function.\n",
+    "        model.add(Dense(num_dense_nodes,\n",
+    "                        activation=activation,\n",
+    "                        name=name))\n",
+    "\n",
+    "    # Last fully-connected / dense layer with softmax-activation\n",
+    "    # for use in classification.\n",
+    "    model.add(Dense(num_classes, activation='softmax'))\n",
+    "    \n",
+    "    # Use the Adam method for training the network.\n",
+    "    # We want to find the best learning-rate for the Adam method.\n",
+    "    optimizer = Adam(lr=learning_rate)\n",
+    "    \n",
+    "    # In Keras we need to compile the model so it can be trained.\n",
+    "    model.compile(optimizer=optimizer,\n",
+    "                  loss='categorical_crossentropy',\n",
+    "                  metrics=['accuracy'])\n",
+    "    \n",
+    "    return model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Train and Evaluate the Model\n",
+    "\n",
+    "The neural network with the best hyper-parameters is saved to disk so it can be reloaded later. This is the filename for the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path_best_model = '19_best_model.keras'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the classification accuracy for the model saved to disk. It is a global variable which will be updated during optimization of the hyper-parameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "best_accuracy = 0.0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the function that creates and trains a neural network with the given hyper-parameters, and then evaluates its performance on the validation-set. The function then returns the so-called fitness value (aka. objective value), which is the negative classification accuracy on the validation-set. It is negative because `skopt` performs minimization instead of maximization.\n",
+    "\n",
+    "Note the function decorator `@use_named_args` which wraps the fitness function so that it can be called with all the parameters as a single list, for example: `fitness(x=[1e-4, 3, 256, 'relu'])`. This is the calling-style `skopt` uses internally."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@use_named_args(dimensions=dimensions)\n",
+    "def fitness(learning_rate, num_dense_layers,\n",
+    "            num_dense_nodes, activation):\n",
+    "    \"\"\"\n",
+    "    Hyper-parameters:\n",
+    "    learning_rate:     Learning-rate for the optimizer.\n",
+    "    num_dense_layers:  Number of dense layers.\n",
+    "    num_dense_nodes:   Number of nodes in each dense layer.\n",
+    "    activation:        Activation function for all layers.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Print the hyper-parameters.\n",
+    "    print('learning rate: {0:.1e}'.format(learning_rate))\n",
+    "    print('num_dense_layers:', num_dense_layers)\n",
+    "    print('num_dense_nodes:', num_dense_nodes)\n",
+    "    print('activation:', activation)\n",
+    "    print()\n",
+    "    \n",
+    "    # Create the neural network with these hyper-parameters.\n",
+    "    model = create_model(learning_rate=learning_rate,\n",
+    "                         num_dense_layers=num_dense_layers,\n",
+    "                         num_dense_nodes=num_dense_nodes,\n",
+    "                         activation=activation)\n",
+    "\n",
+    "    # Dir-name for the TensorBoard log-files.\n",
+    "    log_dir = log_dir_name(learning_rate, num_dense_layers,\n",
+    "                           num_dense_nodes, activation)\n",
+    "    \n",
+    "    # Create a callback-function for Keras which will be\n",
+    "    # run after each epoch has ended during training.\n",
+    "    # This saves the log-files for TensorBoard.\n",
+    "    # Note that there are complications when histogram_freq=1.\n",
+    "    # It might give strange errors and it also does not properly\n",
+    "    # support Keras data-generators for the validation-set.\n",
+    "    callback_log = TensorBoard(\n",
+    "        log_dir=log_dir,\n",
+    "        histogram_freq=0,\n",
+    "        batch_size=32,\n",
+    "        write_graph=True,\n",
+    "        write_grads=False,\n",
+    "        write_images=False)\n",
+    "   \n",
+    "    # Use Keras to train the model.\n",
+    "    history = model.fit(x=data.train.images,\n",
+    "                        y=data.train.labels,\n",
+    "                        epochs=3,\n",
+    "                        batch_size=128,\n",
+    "                        validation_data=validation_data,\n",
+    "                        callbacks=[callback_log])\n",
+    "\n",
+    "    # Get the classification accuracy on the validation-set\n",
+    "    # after the last training-epoch.\n",
+    "    accuracy = history.history['val_acc'][-1]\n",
+    "\n",
+    "    # Print the classification accuracy.\n",
+    "    print()\n",
+    "    print(\"Accuracy: {0:.2%}\".format(accuracy))\n",
+    "    print()\n",
+    "\n",
+    "    # Save the model if it improves on the best-found performance.\n",
+    "    # We use the global keyword so we update the variable outside\n",
+    "    # of this function.\n",
+    "    global best_accuracy\n",
+    "\n",
+    "    # If the classification accuracy of the saved model is improved ...\n",
+    "    if accuracy > best_accuracy:\n",
+    "        # Save the new model to harddisk.\n",
+    "        model.save(path_best_model)\n",
+    "        \n",
+    "        # Update the classification accuracy.\n",
+    "        best_accuracy = accuracy\n",
+    "\n",
+    "    # Delete the Keras model with these hyper-parameters from memory.\n",
+    "    del model\n",
+    "    \n",
+    "    # Clear the Keras session, otherwise it will keep adding new\n",
+    "    # models to the same TensorFlow graph each time we create\n",
+    "    # a model with a different set of hyper-parameters.\n",
+    "    K.clear_session()\n",
+    "    \n",
+    "    # NOTE: Scikit-optimize does minimization so it tries to\n",
+    "    # find a set of hyper-parameters with the LOWEST fitness-value.\n",
+    "    # Because we are interested in the HIGHEST classification\n",
+    "    # accuracy, we need to negate this number so it can be minimized.\n",
+    "    return -accuracy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Test Run\n",
+    "\n",
+    "Before we run the hyper-parameter optimization, let us first check that the various functions above actually work, when we pass the default hyper-parameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "learning rate: 1.0e-05\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 16\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.2525 - acc: 0.1995 - val_loss: 2.1754 - val_acc: 0.3578\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.0279 - acc: 0.4612 - val_loss: 1.8432 - val_acc: 0.5558\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 4s - loss: 1.6227 - acc: 0.5998 - val_loss: 1.3877 - val_acc: 0.6654\n",
+      "\n",
+      "Accuracy: 66.54%\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "-0.66539999999999999"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fitness(x=default_parameters)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Run the Hyper-Parameter Optimization\n",
+    "\n",
+    "Now we are ready to run the actual hyper-parameter optimization using Bayesian optimization from the scikit-optimize package. Note that it first calls `fitness()` with `default_parameters` as the starting point we have found by hand-tuning, which should help the optimizer locate better hyper-parameters faster.\n",
+    "\n",
+    "There are many more parameters you can experiment with here, including the number of calls to the `fitness()` function which we have set to 40. But `fitness()` is very expensive to evaluate so it should not be run too many times, especially for larger neural networks and datasets.\n",
+    "\n",
+    "You can also experiment with the so-called acquisition function which determines how to find a new set of hyper-parameters from the internal model of the Bayesian optimizer. You can also try using another Bayesian optimizer such as Random Forests."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "learning rate: 1.0e-05\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 16\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.2287 - acc: 0.1868 - val_loss: 2.1264 - val_acc: 0.3182\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 1.9607 - acc: 0.4438 - val_loss: 1.7713 - val_acc: 0.5082\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 5s - loss: 1.5763 - acc: 0.5579 - val_loss: 1.3832 - val_acc: 0.6166\n",
+      "\n",
+      "Accuracy: 61.66%\n",
+      "\n",
+      "learning rate: 6.1e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 474\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.3354 - acc: 0.5258 - val_loss: 0.3002 - val_acc: 0.9112\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.2336 - acc: 0.9269 - val_loss: 0.1626 - val_acc: 0.9538\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.1403 - acc: 0.9563 - val_loss: 0.1113 - val_acc: 0.9692\n",
+      "\n",
+      "Accuracy: 96.92%\n",
+      "\n",
+      "learning rate: 6.1e-06\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 333\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.1702 - acc: 0.5067 - val_loss: 1.9186 - val_acc: 0.6892\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.4878 - acc: 0.7480 - val_loss: 1.0546 - val_acc: 0.7940\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.8226 - acc: 0.8264 - val_loss: 0.6324 - val_acc: 0.8514\n",
+      "\n",
+      "Accuracy: 85.14%\n",
+      "\n",
+      "learning rate: 1.7e-04\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 252\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3075 - acc: 0.1058 - val_loss: 2.2968 - val_acc: 0.1126\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 1.5272 - acc: 0.4944 - val_loss: 0.8210 - val_acc: 0.7386\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.6595 - acc: 0.7967 - val_loss: 0.4940 - val_acc: 0.8544\n",
+      "\n",
+      "Accuracy: 85.44%\n",
+      "\n",
+      "learning rate: 7.3e-03\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 166\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1821 - acc: 0.9431 - val_loss: 0.0705 - val_acc: 0.9808\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.0605 - acc: 0.9829 - val_loss: 0.0678 - val_acc: 0.9848\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0549 - acc: 0.9855 - val_loss: 0.0736 - val_acc: 0.9846\n",
+      "\n",
+      "Accuracy: 98.46%\n",
+      "\n",
+      "learning rate: 6.1e-05\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 209\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.3187 - acc: 0.1073 - val_loss: 2.3030 - val_acc: 0.0924\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.3016 - acc: 0.1121 - val_loss: 2.2993 - val_acc: 0.1126\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 5s - loss: 2.2858 - acc: 0.1573 - val_loss: 2.2243 - val_acc: 0.2898\n",
+      "\n",
+      "Accuracy: 28.98%\n",
+      "\n",
+      "learning rate: 1.8e-04\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 453\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.3601 - acc: 0.8920 - val_loss: 0.1234 - val_acc: 0.9640\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.0850 - acc: 0.9741 - val_loss: 0.0576 - val_acc: 0.9830\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0566 - acc: 0.9824 - val_loss: 0.0535 - val_acc: 0.9856\n",
+      "\n",
+      "Accuracy: 98.56%\n",
+      "\n",
+      "learning rate: 5.5e-06\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 186\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3129 - acc: 0.1039 - val_loss: 2.3025 - val_acc: 0.1100\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 2.3016 - acc: 0.1106 - val_loss: 2.3010 - val_acc: 0.1126\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 2.3013 - acc: 0.1123 - val_loss: 2.3011 - val_acc: 0.1126\n",
+      "\n",
+      "Accuracy: 11.26%\n",
+      "\n",
+      "learning rate: 3.1e-05\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 427\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3132 - acc: 0.1070 - val_loss: 2.3007 - val_acc: 0.1126\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 2.3029 - acc: 0.1080 - val_loss: 2.3020 - val_acc: 0.1126\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 2.3021 - acc: 0.1093 - val_loss: 2.3016 - val_acc: 0.1126\n",
+      "\n",
+      "Accuracy: 11.26%\n",
+      "\n",
+      "learning rate: 1.4e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 29\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.8474 - acc: 0.7524 - val_loss: 0.2954 - val_acc: 0.9190\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.2392 - acc: 0.9315 - val_loss: 0.1741 - val_acc: 0.9512\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.1643 - acc: 0.9517 - val_loss: 0.1346 - val_acc: 0.9612\n",
+      "\n",
+      "Accuracy: 96.12%\n",
+      "\n",
+      "learning rate: 3.7e-04\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 338\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.1610 - acc: 0.1844 - val_loss: 1.0813 - val_acc: 0.6678\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.5982 - acc: 0.8131 - val_loss: 0.3252 - val_acc: 0.9100\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.2712 - acc: 0.9201 - val_loss: 0.1858 - val_acc: 0.9468\n",
+      "\n",
+      "Accuracy: 94.68%\n",
+      "\n",
+      "learning rate: 1.7e-06\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.2568 - acc: 0.3895 - val_loss: 2.1984 - val_acc: 0.6048\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 2.0854 - acc: 0.6719 - val_loss: 1.9276 - val_acc: 0.7052\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 1.7106 - acc: 0.7158 - val_loss: 1.4589 - val_acc: 0.7290\n",
+      "\n",
+      "Accuracy: 72.90%\n",
+      "\n",
+      "learning rate: 1.4e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 62\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.2396 - acc: 0.9249 - val_loss: 0.0643 - val_acc: 0.9822\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.0587 - acc: 0.9819 - val_loss: 0.0536 - val_acc: 0.9838\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.0427 - acc: 0.9867 - val_loss: 0.0480 - val_acc: 0.9842\n",
+      "\n",
+      "Accuracy: 98.42%\n",
+      "\n",
+      "learning rate: 2.7e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 364\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.3014 - acc: 0.5223 - val_loss: 0.2531 - val_acc: 0.9232\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1956 - acc: 0.9386 - val_loss: 0.1221 - val_acc: 0.9650\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.1138 - acc: 0.9646 - val_loss: 0.0846 - val_acc: 0.9758\n",
+      "\n",
+      "Accuracy: 97.58%\n",
+      "\n",
+      "learning rate: 5.6e-04\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 13\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.9357 - acc: 0.6775 - val_loss: 0.3024 - val_acc: 0.9184\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.2416 - acc: 0.9338 - val_loss: 0.1749 - val_acc: 0.9520\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.1685 - acc: 0.9525 - val_loss: 0.1541 - val_acc: 0.9570\n",
+      "\n",
+      "Accuracy: 95.70%\n",
+      "\n",
+      "learning rate: 1.0e-02\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 352\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "55000/55000 [==============================] - 3s - loss: 2.3316 - acc: 0.1049 - val_loss: 2.3019 - val_acc: 0.1070\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3024 - acc: 0.1090 - val_loss: 2.3017 - val_acc: 0.1126\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 2.3020 - acc: 0.1104 - val_loss: 2.3014 - val_acc: 0.1126\n",
+      "\n",
+      "Accuracy: 11.26%\n",
+      "\n",
+      "learning rate: 1.5e-03\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 5\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 1.7072 - acc: 0.4784 - val_loss: 1.2153 - val_acc: 0.6980\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.9949 - acc: 0.7914 - val_loss: 0.7749 - val_acc: 0.8564\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.6663 - acc: 0.8663 - val_loss: 0.5469 - val_acc: 0.9014\n",
+      "\n",
+      "Accuracy: 90.14%\n",
+      "\n",
+      "learning rate: 1.0e-03\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 496\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1843 - acc: 0.9426 - val_loss: 0.0483 - val_acc: 0.9852\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.0506 - acc: 0.9840 - val_loss: 0.0471 - val_acc: 0.9856\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0347 - acc: 0.9889 - val_loss: 0.0451 - val_acc: 0.9856\n",
+      "\n",
+      "Accuracy: 98.56%\n",
+      "\n",
+      "learning rate: 3.7e-03\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.2060 - acc: 0.9377 - val_loss: 0.0739 - val_acc: 0.9832\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.0781 - acc: 0.9814 - val_loss: 0.0765 - val_acc: 0.9842\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.0908 - acc: 0.9818 - val_loss: 0.1368 - val_acc: 0.9766\n",
+      "\n",
+      "Accuracy: 97.66%\n",
+      "\n",
+      "learning rate: 1.0e-02\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3199 - acc: 0.1105 - val_loss: 2.3015 - val_acc: 0.1126\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 2.3020 - acc: 0.1104 - val_loss: 2.3011 - val_acc: 0.1126\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 2.3018 - acc: 0.1110 - val_loss: 2.3013 - val_acc: 0.1126\n",
+      "\n",
+      "Accuracy: 11.26%\n",
+      "\n",
+      "learning rate: 1.9e-04\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 418\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.3595 - acc: 0.8999 - val_loss: 0.0888 - val_acc: 0.9732\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.0868 - acc: 0.9738 - val_loss: 0.0686 - val_acc: 0.9782\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.0584 - acc: 0.9821 - val_loss: 0.0478 - val_acc: 0.9850\n",
+      "\n",
+      "Accuracy: 98.50%\n",
+      "\n",
+      "learning rate: 2.4e-03\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 144\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1906 - acc: 0.9390 - val_loss: 0.0576 - val_acc: 0.9834\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.0550 - acc: 0.9840 - val_loss: 0.0402 - val_acc: 0.9890\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0380 - acc: 0.9885 - val_loss: 0.0459 - val_acc: 0.9880\n",
+      "\n",
+      "Accuracy: 98.80%\n",
+      "\n",
+      "learning rate: 6.8e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 105\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.1552 - acc: 0.9507 - val_loss: 0.0498 - val_acc: 0.9860\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.0485 - acc: 0.9853 - val_loss: 0.0534 - val_acc: 0.9836\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.0417 - acc: 0.9875 - val_loss: 0.0496 - val_acc: 0.9852\n",
+      "\n",
+      "Accuracy: 98.52%\n",
+      "\n",
+      "learning rate: 2.5e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 435\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.3258 - acc: 0.9131 - val_loss: 0.1024 - val_acc: 0.9676\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0856 - acc: 0.9742 - val_loss: 0.0603 - val_acc: 0.9812\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0601 - acc: 0.9819 - val_loss: 0.0477 - val_acc: 0.9868\n",
+      "\n",
+      "Accuracy: 98.68%\n",
+      "\n",
+      "learning rate: 2.5e-06\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 409\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.2504 - acc: 0.3689 - val_loss: 2.1796 - val_acc: 0.5498\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.0835 - acc: 0.6384 - val_loss: 1.9688 - val_acc: 0.6812\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 1.8409 - acc: 0.7098 - val_loss: 1.6977 - val_acc: 0.7404\n",
+      "\n",
+      "Accuracy: 74.04%\n",
+      "\n",
+      "learning rate: 4.4e-03\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 311\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1504 - acc: 0.9523 - val_loss: 0.0746 - val_acc: 0.9800\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0559 - acc: 0.9842 - val_loss: 0.0751 - val_acc: 0.9812\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0431 - acc: 0.9884 - val_loss: 0.0500 - val_acc: 0.9870\n",
+      "\n",
+      "Accuracy: 98.70%\n",
+      "\n",
+      "learning rate: 2.1e-03\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 436\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1884 - acc: 0.9418 - val_loss: 0.0664 - val_acc: 0.9840\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0598 - acc: 0.9837 - val_loss: 0.0454 - val_acc: 0.9880\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.0435 - acc: 0.9887 - val_loss: 0.0553 - val_acc: 0.9864\n",
+      "\n",
+      "Accuracy: 98.64%\n",
+      "\n",
+      "learning rate: 1.9e-04\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 441\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.3664 - acc: 0.8989 - val_loss: 0.1076 - val_acc: 0.9698\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0872 - acc: 0.9736 - val_loss: 0.0626 - val_acc: 0.9816\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.0583 - acc: 0.9824 - val_loss: 0.0504 - val_acc: 0.9856\n",
+      "\n",
+      "Accuracy: 98.56%\n",
+      "\n",
+      "learning rate: 1.7e-03\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 512\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.2528 - acc: 0.5598 - val_loss: 0.2764 - val_acc: 0.9186\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.2010 - acc: 0.9369 - val_loss: 0.1251 - val_acc: 0.9592\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.1203 - acc: 0.9629 - val_loss: 0.0916 - val_acc: 0.9734\n",
+      "\n",
+      "Accuracy: 97.34%\n",
+      "\n",
+      "learning rate: 1.5e-03\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 285\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.1378 - acc: 0.1588 - val_loss: 1.2723 - val_acc: 0.4116\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.5670 - acc: 0.7991 - val_loss: 0.2616 - val_acc: 0.9266\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.1877 - acc: 0.9460 - val_loss: 0.1365 - val_acc: 0.9618\n",
+      "\n",
+      "Accuracy: 96.18%\n",
+      "\n",
+      "learning rate: 3.3e-04\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 5\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3570 - acc: 0.0907 - val_loss: 2.3175 - val_acc: 0.0868\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.3074 - acc: 0.0952 - val_loss: 2.3029 - val_acc: 0.1126\n",
+      "Epoch 3/3\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "55000/55000 [==============================] - 8s - loss: 2.3019 - acc: 0.1123 - val_loss: 2.3013 - val_acc: 0.1126\n",
+      "\n",
+      "Accuracy: 11.26%\n",
+      "\n",
+      "learning rate: 2.3e-04\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 512\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 2.1591 - acc: 0.1861 - val_loss: 1.0381 - val_acc: 0.6422\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.6686 - acc: 0.7868 - val_loss: 0.4403 - val_acc: 0.8662\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.3814 - acc: 0.8831 - val_loss: 0.2920 - val_acc: 0.9090\n",
+      "\n",
+      "Accuracy: 90.90%\n",
+      "\n",
+      "learning rate: 2.6e-03\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 126\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 1.1633 - acc: 0.5922 - val_loss: 0.1928 - val_acc: 0.9422\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.1490 - acc: 0.9550 - val_loss: 0.0859 - val_acc: 0.9778\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 5s - loss: 0.0885 - acc: 0.9729 - val_loss: 0.0735 - val_acc: 0.9786\n",
+      "\n",
+      "Accuracy: 97.86%\n",
+      "\n",
+      "learning rate: 5.7e-04\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 246\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.2579 - acc: 0.9261 - val_loss: 0.0748 - val_acc: 0.9782\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.0691 - acc: 0.9787 - val_loss: 0.0502 - val_acc: 0.9858\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.0465 - acc: 0.9854 - val_loss: 0.0423 - val_acc: 0.9880\n",
+      "\n",
+      "Accuracy: 98.80%\n",
+      "\n",
+      "learning rate: 2.4e-04\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 164\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.4321 - acc: 0.8849 - val_loss: 0.1429 - val_acc: 0.9608\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.1163 - acc: 0.9654 - val_loss: 0.0821 - val_acc: 0.9766\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0794 - acc: 0.9762 - val_loss: 0.0679 - val_acc: 0.9796\n",
+      "\n",
+      "Accuracy: 97.96%\n",
+      "\n",
+      "learning rate: 1.0e-06\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 5\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.3000 - acc: 0.1046 - val_loss: 2.2987 - val_acc: 0.1122\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 2.2981 - acc: 0.1124 - val_loss: 2.2965 - val_acc: 0.1224\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 4s - loss: 2.2959 - acc: 0.1221 - val_loss: 2.2941 - val_acc: 0.1290\n",
+      "\n",
+      "Accuracy: 12.90%\n",
+      "\n",
+      "learning rate: 1.3e-05\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.6243 - acc: 0.6472 - val_loss: 0.7587 - val_acc: 0.8260\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.5184 - acc: 0.8724 - val_loss: 0.3656 - val_acc: 0.9038\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 7s - loss: 0.3292 - acc: 0.9091 - val_loss: 0.2724 - val_acc: 0.9268\n",
+      "\n",
+      "Accuracy: 92.68%\n",
+      "\n",
+      "learning rate: 7.6e-05\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 241\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.7636 - acc: 0.8233 - val_loss: 0.2393 - val_acc: 0.9368\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 2s - loss: 0.1961 - acc: 0.9448 - val_loss: 0.1449 - val_acc: 0.9612\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.1309 - acc: 0.9617 - val_loss: 0.1068 - val_acc: 0.9688\n",
+      "\n",
+      "Accuracy: 96.88%\n",
+      "\n",
+      "learning rate: 2.0e-03\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1668 - acc: 0.9474 - val_loss: 0.0605 - val_acc: 0.9832\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 4s - loss: 0.0548 - acc: 0.9845 - val_loss: 0.0419 - val_acc: 0.9902\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 8s - loss: 0.0408 - acc: 0.9890 - val_loss: 0.0596 - val_acc: 0.9844\n",
+      "\n",
+      "Accuracy: 98.44%\n",
+      "\n",
+      "learning rate: 2.2e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 326\n",
+      "activation: sigmoid\n",
+      "\n",
+      "Train on 55000 samples, validate on 5000 samples\n",
+      "Epoch 1/3\n",
+      "55000/55000 [==============================] - 3s - loss: 1.1358 - acc: 0.5865 - val_loss: 0.2104 - val_acc: 0.9356\n",
+      "Epoch 2/3\n",
+      "55000/55000 [==============================] - 3s - loss: 0.1576 - acc: 0.9505 - val_loss: 0.0999 - val_acc: 0.9712\n",
+      "Epoch 3/3\n",
+      "55000/55000 [==============================] - 6s - loss: 0.1011 - acc: 0.9679 - val_loss: 0.0856 - val_acc: 0.9726\n",
+      "\n",
+      "Accuracy: 97.26%\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "search_result = gp_minimize(func=fitness,\n",
+    "                            dimensions=dimensions,\n",
+    "                            acq_func='EI', # Expected Improvement.\n",
+    "                            n_calls=40,\n",
+    "                            x0=default_parameters)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Optimization Progress\n",
+    "\n",
+    "The progress of the hyper-parameter optimization can be easily plotted. The best fitness value found is plotted on the y-axis, remember that this is the negated classification accuracy on the validation-set.\n",
+    "\n",
+    "Note how few hyper-parameters had to be tried before substantial improvements were found."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2830202e8>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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2zZs3r2BMnZ2dtLS0lPV73PyfT/LQk2s4a+aBHDZlfFnXlqOS2AaLY6uMY6uM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\nAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc285dc5cf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_convergence(search_result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Best Hyper-Parameters\n",
+    "\n",
+    "The best hyper-parameters found by the Bayesian optimizer are packed as a list because that is what it uses internally."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[0.0023584457378584664, 4, 144, 'relu']"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_result.x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can convert these parameters to a dict with proper names for the search-space dimensions.\n",
+    "\n",
+    "First we need a reference to the search-space object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "space = search_result.space"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we can use it to create a dict where the hyper-parameters have the proper names of the search-space dimensions. This is a bit awkward."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'activation': 'relu',\n",
+       " 'learning_rate': 0.0023584457378584664,\n",
+       " 'num_dense_layers': 4,\n",
+       " 'num_dense_nodes': 144}"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "space.point_to_dict(search_result.x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the fitness value associated with these hyper-parameters. This is a negative number because the Bayesian optimizer performs minimization, so we had to negate the classification accuracy which is posed as a maximization problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.98799999999999999"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_result.fun"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also see all the hyper-parameters tried by the Bayesian optimizer and their associated fitness values (the negated classification accuracies). These are sorted so the highest classification accuracies are shown first.\n",
+    "\n",
+    "It appears that 'relu' activation was generally better than 'sigmoid'. Otherwise it can be difficult to see a pattern of which parameter choices are good. We really need to plot these results."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(-0.98799999999999999, [0.00057102338020535671, 1, 246, 'relu']),\n",
+       " (-0.98799999999999999, [0.0023584457378584664, 4, 144, 'relu']),\n",
+       " (-0.98699999999999999, [0.0043924439217142824, 3, 311, 'relu']),\n",
+       " (-0.98680000000000001, [0.00025070302453255417, 2, 435, 'relu']),\n",
+       " (-0.98640000000000005, [0.0020904801989242469, 5, 436, 'relu']),\n",
+       " (-0.98560000000000003, [0.00017567744133971055, 4, 453, 'relu']),\n",
+       " (-0.98560000000000003, [0.00018871091218374878, 3, 441, 'relu']),\n",
+       " (-0.98560000000000003, [0.0010013922052631494, 3, 496, 'relu']),\n",
+       " (-0.98519999999999996, [0.006752254693985822, 2, 105, 'relu']),\n",
+       " (-0.98499999999999999, [0.0001905308801138268, 4, 418, 'relu']),\n",
+       " (-0.98460000000000003, [0.0073224617473678331, 3, 166, 'relu']),\n",
+       " (-0.98440000000000005, [0.0020143982003767271, 4, 512, 'relu']),\n",
+       " (-0.98419999999999996, [0.0014193250864683331, 2, 62, 'relu']),\n",
+       " (-0.97960000000000003, [0.00023735076383216567, 1, 164, 'relu']),\n",
+       " (-0.97860000000000003, [0.0026064900033469073, 1, 126, 'sigmoid']),\n",
+       " (-0.97660000000000002, [0.0037123587226393501, 5, 512, 'relu']),\n",
+       " (-0.9758, [0.0027230837381696737, 2, 364, 'sigmoid']),\n",
+       " (-0.97340000000000004, [0.0016597651372777609, 1, 512, 'sigmoid']),\n",
+       " (-0.97260000000000002, [0.0022460993827137423, 2, 326, 'sigmoid']),\n",
+       " (-0.96919999999999995, [0.00060563429543890952, 2, 474, 'sigmoid']),\n",
+       " (-0.96879999999999999, [7.5808558985641429e-05, 1, 241, 'relu']),\n",
+       " (-0.96179999999999999, [0.0014963322170155162, 5, 285, 'sigmoid']),\n",
+       " (-0.96120000000000005, [0.00013559943302194881, 2, 29, 'relu']),\n",
+       " (-0.95699999999999996, [0.00056441093780360571, 5, 13, 'relu']),\n",
+       " (-0.94679999999999997, [0.00036704404112128516, 4, 338, 'sigmoid']),\n",
+       " (-0.92679999999999996, [1.3066947342663859e-05, 2, 512, 'relu']),\n",
+       " (-0.90900000000000003, [0.00023277413216549582, 4, 512, 'sigmoid']),\n",
+       " (-0.90139999999999998, [0.001544493082361837, 1, 5, 'sigmoid']),\n",
+       " (-0.85440000000000005, [0.00016937303683800523, 4, 252, 'sigmoid']),\n",
+       " (-0.85140000000000005, [6.1458838378363633e-06, 2, 333, 'relu']),\n",
+       " (-0.74039999999999995, [2.4847514577863683e-06, 1, 409, 'relu']),\n",
+       " (-0.72899999999999998, [1.7068698743151031e-06, 4, 512, 'relu']),\n",
+       " (-0.61660000000000004, [1e-05, 1, 16, 'relu']),\n",
+       " (-0.2898, [6.1011365846453456e-05, 2, 209, 'sigmoid']),\n",
+       " (-0.129, [9.9999999999999995e-07, 2, 5, 'relu']),\n",
+       " (-0.11260000000000001, [5.4599879082087208e-06, 4, 186, 'sigmoid']),\n",
+       " (-0.11260000000000001, [3.1218037895598157e-05, 3, 427, 'sigmoid']),\n",
+       " (-0.11260000000000001, [0.00033099542158994725, 5, 5, 'sigmoid']),\n",
+       " (-0.11260000000000001, [0.01, 5, 352, 'sigmoid']),\n",
+       " (-0.11260000000000001, [0.01, 5, 512, 'relu'])]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted(zip(search_result.func_vals, search_result.x_iters))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plots\n",
+    "\n",
+    "There are several plotting functions available in the `skopt` library. For example, we can plot a histogram for the `activation` parameter, which shows the distribution of samples during the hyper-parameter optimization."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+q6qeWlVPAr44+UGSRwLvAvYB9gWesMG22wNPB97G4J6i44EnAk9Osnu3/bHAc4Ddgb2S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\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc2704bb860>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_histogram(result=search_result,\n",
+    "                         dimension_name='activation')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also make a landscape-plot of the estimated fitness values for two dimensions of the search-space, here taken to be `learning_rate` and `num_dense_layers`.\n",
+    "\n",
+    "The Bayesian optimizer works by building a surrogate model of the search-space and then searching this model instead of the real search-space, because it is much faster. The plot shows the last surrogate model built by the Bayesian optimizer where yellow regions are better and blue regions are worse. The black dots show where the optimizer has sampled the search-space and the red star shows the best parameters found.\n",
+    "\n",
+    "Several things should be noted here. Firstly, this surrogate model of the search-space may not be accurate. It is built from only 40 samples of calls to the `fitness()` function for training a neural network with a given choice of hyper-parameters. The modelled fitness landscape may differ significantly from its true values especially in regions of the search-space with few samples. Secondly, the plot may change each time the hyper-parameter optimization is run because of random noise in the training process of the neural network. Thirdly, this plot shows the effect of changing these two parameters `num_dense_layers` and `learning_rate` when averaged over all other dimensions in the search-space, this is also called a Partial Dependence plot and is a way of visualizing high-dimensional spaces in only 2-dimensions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JiMbc65uBSkmT+6l7dUTMjYi5lVSPaJxmZvuToiYGSYdIUu71ybl4dhYzJjOz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\nicHMzPL8fy6cRQja3MY6AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc270556320>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plot_objective_2D(result=search_result,\n",
+    "                        dimension_name1='learning_rate',\n",
+    "                        dimension_name2='num_dense_layers',\n",
+    "                        levels=50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We cannot make a landscape plot for the `activation` hyper-parameter because it is a categorical variable that can be one of two strings `relu` or `sigmoid`. How this is encoded depends on the Bayesian optimizer, for example, whether it is using Gaussian Processes or Random Forests. But it cannot currently be plotted using the built-in functions of `skopt`.\n",
+    "\n",
+    "Instead we only want to use the real- and integer-valued dimensions of the search-space which we identify by their names."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dim_names = ['learning_rate', 'num_dense_nodes', 'num_dense_layers']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then make a matrix-plot of all combinations of these dimensions.\n",
+    "\n",
+    "The diagonal shows the influence of a single dimension on the fitness. This is a so-called Partial Dependence plot for that dimension. It shows how the approximated fitness value changes with different values in that dimension.\n",
+    "\n",
+    "The plots below the diagonal show the Partial Dependence for two dimensions. This shows how the approximated fitness value changes when we are varying two dimensions simultaneously.\n",
+    "\n",
+    "These Partial Dependence plots are only approximations of the modelled fitness function - which in turn is only an approximation of the true fitness function in `fitness()`. This may be a bit difficult to understand. For example, the Partial Dependence is calculated by fixing one value for the `learning_rate` and then taking a large number of random samples for the remaining dimensions in the search-space. The estimated fitness for all these points is then averaged. This process is then repeated for other values of the `learning_rate` to show how it affects the fitness on average. A similar procedure is done for the plots that show the Partial Dependence plots for two dimensions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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UN95Jqlof4n33uHYYsacB1ao6vv0TqnqRiHwLOBaYJyITVHVrGPcwKcjaNEyq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\nAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc27c3010b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_objective(result=search_result, dimension_names=dim_names)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also show another type of matrix-plot. Here the diagonal shows histograms of the sample distributions for each of the hyper-parameters during the Bayesian optimization. The plots below the diagonal show the location of samples in the search-space and the colour-coding shows the order in which the samples were taken. For larger numbers of samples you will likely see that the samples eventually become concentrated in a certain region of the search-space."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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OGsyND5/PxH99zK5te+jWtxPX/O0cOnaLvt5iAVKSE7jv1nHcfvVYyspctG+b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\nRTV5kc06i7IAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc28784fa58>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_evaluations(result=search_result, dimension_names=dim_names)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Evaluate Best Model on Test-Set\n",
+    "\n",
+    "We can now use the best model on the test-set. It is very easy to reload the model using Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = load_model(path_best_model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We then evaluate its performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " 8960/10000 [=========================>....] - ETA: 0s"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(x=data.test.images,\n",
+    "                        y=data.test.labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can print all the performance metrics for the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loss 0.0363312054525\n",
+      "acc 0.9888\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, value in zip(model.metrics_names, result):\n",
+    "    print(name, value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Or we can just print the classification accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "acc: 98.88%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"{0}: {1:.2%}\".format(model.metrics_names[1], result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Predict on New Data\n",
+    "\n",
+    "We can also predict the classification for new images. We will just use some images from the test-set but you could load your own images into numpy arrays and use those instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "images = data.test.images[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the true class-number for those images. This is only used when plotting the images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_true = data.test.cls[0:9]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the predicted classes as One-Hot encoded arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_pred = model.predict(x=images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the predicted classes as integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred,axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Dz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaj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\nIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc287ae2fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_images(images=images,\n",
+    "            cls_true=cls_true,\n",
+    "            cls_pred=cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Examples of Mis-Classified Images\n",
+    "\n",
+    "We can plot some examples of mis-classified images from the test-set.\n",
+    "\n",
+    "First we get the predicted classes for all the images in the test-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_pred = model.predict(x=data.test.images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we convert the predicted class-numbers from One-Hot encoded arrays to integers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_pred = np.argmax(y_pred,axis=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot some of the mis-classified images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fc285c98128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_example_errors(cls_pred)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to optimize the hyper-parameters of a neural network using Bayesian optimization. We used the scikit-optimize (`skopt`) library which is still under development, but it is already an extremely powerful tool. It was able to substantially improve on hand-tuned hyper-parameters in a small number of iterations. This is vastly superior to Grid Search and Random Search of the hyper-parameters, which would require far more computational time, and would most likely find inferior hyper-parameters, especially for more difficult problems."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Try and run 100 or 200 iterations of the optimization instead of just 40 iterations. What happens to the plotted landscapes?\n",
+    "* Try some of the other optimization methods from scikit-optimize such as `forest_minimize` instead of `gp_minimize`. How do they perform?\n",
+    "* Try using another acquisition function for the optimizer e.g. Probability of Improvement.\n",
+    "* Try optimizing more hyper-parameters with the Bayesian optimization. For example, the kernel-size and number of filters in the convolutional-layers, or the batch-size used in training.\n",
+    "* Add a hyper-parameter for the number of convolutional layers and implement it in `create_model()`. Note that if you have pooling-layers after the convolution then the images are downsampled, so there is a limit to the number of layers you can have before the images become too small.\n",
+    "* Look at the plots. Do you think that some of the hyper-parameters may be irrelevant? Try and remove these parameters and redo the optimization of the remaining hyper-parameters.\n",
+    "* Use another and more difficult dataset with image-files.\n",
+    "* Train for more epochs. Does it improve the classification accuracy on the validiation- and test-sets? How does it affect the time-usage?\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2016-2018 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/README.md b/README.md
index fde06a3..d665168 100644
--- a/README.md
+++ b/README.md
@@ -61,6 +61,8 @@ Even a few dollars are appreciated. Thanks!
 
 18. TFRecords & Dataset API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb)) 
 
+19. Hyper-Parameter Optimization ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/images/19_flowchart_bayesian_optimization.png b/images/19_flowchart_bayesian_optimization.png
new file mode 100644
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From c68d9601a3a5d1a955e9ecf7d05a18fc2e5f56a6 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 5 Feb 2018 12:04:34 +0100
Subject: [PATCH 34/61] Removed donation-text.

---
 README.md | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/README.md b/README.md
index d665168..5814592 100644
--- a/README.md
+++ b/README.md
@@ -4,12 +4,6 @@
 
 Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
-##  Donations
-
-All this was made by a single person who did not receive any money for doing the work.
-If you find it useful then [please donate securely using PayPal](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=PY9EUURN7GRUW).
-Even a few dollars are appreciated. Thanks!
-
 ## Introduction
 
 * These tutorials are intended for beginners in Deep Learning and TensorFlow.

From 1284750b1c47fe5c376f249e206350b36a7eb3c8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 9 Feb 2018 18:36:43 +0100
Subject: [PATCH 35/61] Added Tutorial 20

---
 20_Natural_Language_Processing.ipynb     | 3115 ++++++++++++++++++++++
 README.md                                |    2 +
 images/20_natural_language_flowchart.png |  Bin 0 -> 88420 bytes
 images/20_natural_language_flowchart.svg |  440 +++
 images/20_recurrent_unit.png             |  Bin 0 -> 22028 bytes
 images/20_recurrent_unit.svg             |  336 +++
 images/20_unrolled_3layers_flowchart.png |  Bin 0 -> 85051 bytes
 images/20_unrolled_3layers_flowchart.svg | 1847 +++++++++++++
 images/20_unrolled_flowchart.png         |  Bin 0 -> 48400 bytes
 images/20_unrolled_flowchart.svg         |  849 ++++++
 imdb.py                                  |  121 +
 11 files changed, 6710 insertions(+)
 create mode 100644 20_Natural_Language_Processing.ipynb
 create mode 100644 images/20_natural_language_flowchart.png
 create mode 100644 images/20_natural_language_flowchart.svg
 create mode 100644 images/20_recurrent_unit.png
 create mode 100644 images/20_recurrent_unit.svg
 create mode 100644 images/20_unrolled_3layers_flowchart.png
 create mode 100644 images/20_unrolled_3layers_flowchart.svg
 create mode 100644 images/20_unrolled_flowchart.png
 create mode 100644 images/20_unrolled_flowchart.svg
 create mode 100644 imdb.py

diff --git a/20_Natural_Language_Processing.ipynb b/20_Natural_Language_Processing.ipynb
new file mode 100644
index 0000000..076fb73
--- /dev/null
+++ b/20_Natural_Language_Processing.ipynb
@@ -0,0 +1,3115 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #20\n",
+    "# Natural Language Processing\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "This tutorial is about a basic form of Natural Language Processing (NLP) called Sentiment Analysis, in which we will try and classify a movie review as either positive or negative.\n",
+    "\n",
+    "Consider a simple example: \"This movie is not very good.\" This text ends with the words \"very good\" which indicates a very positive sentiment, but it is negated because it is preceded by the word \"not\", so the text should be classified as having a negative sentiment. How can we teach a Neural Network to do this classification?\n",
+    "\n",
+    "Another problem is that neural networks cannot work directly on text-data, so we need to convert text into numbers that are compatible with a neural network.\n",
+    "\n",
+    "Yet another problem is that a text may be arbitrarily long. The neural networks we have worked with in previous tutorials use fixed data-shapes - except for the first dimension of the data which varies with the batch-size. Now we need a type of neural network that can work on both short and long sequences of text.\n",
+    "\n",
+    "You should be familiar with TensorFlow and Keras in general, see Tutorials #01 and #03-C."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "To solve this problem we need several processing steps. First we need to convert the raw text-words into so-called tokens which are integer values. These tokens are really just indices into a list of the entire vocabulary. Then we convert these integer-tokens into so-called embeddings which are real-valued vectors, whose mapping will be trained along with the neural network, so as to map words with similar meanings to similar embedding-vectors. Then we input these embedding-vectors to a Recurrent Neural Network which can take sequences of arbitrary length as input and output a kind of summary of what it has seen in the input. This output is then squashed using a Sigmoid-function to give us a value between 0.0 and 1.0, where 0.0 is taken to mean a negative sentiment and 1.0 means a positive sentiment. This whole process allows us to classify input-text as either having a negative or positive sentiment.\n",
+    "\n",
+    "The flowchart of the algorithm is roughly:\n",
+    "\n",
+    "<img src=\"images/20_natural_language_flowchart.png\" alt=\"Flowchart NLP\" style=\"width: 300px;\"/>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Recurrent Neural Network\n",
+    "\n",
+    "The basic building block in a Recurrent Neural Network (RNN) is a Recurrent Unit (RU). There are many different variants of recurrent units such as the rather clunky LSTM (Long-Short-Term-Memory) and the somewhat simpler GRU (Gated Recurrent Unit) which we will use in this tutorial. Experiments in the literature suggest that the LSTM and GRU have roughly similar performance. Even simpler variants also exist and the literature suggests that they may perform even better than both LSTM and GRU, but they are not implemented in Keras which we will use in this tutorial.\n",
+    "\n",
+    "The following figure shows the abstract idea of a recurrent unit, which has an internal state that is being updated every time the unit receives a new input. This internal state serves as a kind of memory. However, it is not a traditional kind of computer memory which stores bits that are either on or off. Instead the recurrent unit stores floating-point values in its memory-state, which are read and written using matrix-operations so the operations are all differentiable. This means the memory-state can store arbitrary floating-point values (although typically limited between -1.0 and 1.0) and the network can be trained like a normal neural network using Gradient Descent.\n",
+    "\n",
+    "The new state-value depends on both the old state-value and the current input. For example, if the state-value has memorized that we have recently seen the word \"not\" and the current input is \"good\" then we need to store a new state-value that memorizes \"not good\" which indicates a negative sentiment.\n",
+    "\n",
+    "The part of the recurrent unit that is responsible for mapping old state-values and inputs to the new state-value is called a gate, but it is really just a type of matrix-operation. There is another gate for calculating the output-values of the recurrent unit. The implementation of these gates vary for different types of recurrent units. This figure merely shows the abstract idea of a recurrent unit. The LSTM has more gates than the GRU but some of them are apparently redundant so they can be omitted.\n",
+    "\n",
+    "In order to train the recurrent unit, we must gradually change the weight-matrices of the gates so the recurrent unit gives the desired output for an input sequence. This is done automatically in TensorFlow.\n",
+    "\n",
+    "![Recurrent unit](images/20_recurrent_unit.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Unrolled Network\n",
+    "\n",
+    "Another way to visualize and understand a Recurrent Neural Network is to \"unroll\" the recursion. In this figure there is only a single recurrent unit denoted RU, which will receive a text-word from the input sequence in a series of time-steps.\n",
+    "\n",
+    "The initial memory-state of the RU is reset to zero internally by Keras / TensorFlow every time a new sequence begins.\n",
+    "\n",
+    "In the first time-step the word \"this\" is input to the RU which uses its internal state (initialized to zero) and its gate to calculate the new state. The RU also uses its other gate to calculate the output but it is ignored here because it is only needed at the end of the sequence to output a kind of summary.\n",
+    "\n",
+    "In the second time-step the word \"is\" is input to the RU which now uses the internal state that was just updated from seeing the previous word \"this\".\n",
+    "\n",
+    "There is not much meaning in the words \"this is\" so the RU probably doesn't save anything important in its internal state from seeing these words. But when it sees the third word \"not\" the RU has learned that it may be important for determining the overall sentiment of the input-text, so it needs to be stored in the memory-state of the RU, which can be used later when the RU sees the word \"good\" in time-step 6.\n",
+    "\n",
+    "Finally when the entire sequence has been processed, the RU outputs a vector of values that summarizes what it has seen in the input sequence. We then use a fully-connected layer with a Sigmoid activation to get a single value between 0.0 and 1.0 which we interpret as the sentiment either being negative (values close to 0.0) or positive (values close to 1.0).\n",
+    "\n",
+    "Note that for the sake of clarity, this figure doesn't show the mapping from text-words to integer-tokens and embedding-vectors, as well as the fully-connected Sigmoid layer on the output.\n",
+    "\n",
+    "![Unrolled network](images/20_unrolled_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3-Layer Unrolled Network\n",
+    "\n",
+    "In this tutorial we will use a Recurrent Neural Network with 3 recurrent units (or layers) denoted RU1, RU2 and RU3 in the \"unrolled\" figure below.\n",
+    "\n",
+    "The first layer is much like the unrolled figure above for a single-layer RNN. First the recurrent unit RU1 has its internal state initialized to zero by Keras / TensorFlow. Then the word \"this\" is input to RU1 and it updates its internal state. Then it processes the next word \"is\", and so forth. But instead of outputting a single summary value at the end of the sequence, we use the output of RU1 for every time-step. This creates a new sequence that can then be used as input for the next recurrent unit RU2. The same process is repeated for the second layer and this creates a new output sequence which is then input to the third layer's recurrent unit RU3, whose final output is passed to a fully-connected Sigmoid layer that outputs a value between 0.0 (negative sentiment) and 1.0 (positive sentiment).\n",
+    "\n",
+    "Note that for the sake of clarity, the mapping of text-words to integer-tokens and embedding-vectors has been omitted from this figure.\n",
+    "\n",
+    "![Unrolled 3-layer network](images/20_unrolled_3layers_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exploding & Vanishing Gradients\n",
+    "\n",
+    "In order to train the weights for the gates inside the recurrent unit, we need to minimize some loss-function which measures the difference between the actual output of the network relative to the desired output.\n",
+    "\n",
+    "From the \"unrolled\" figures above we see that the reccurent units are applied recursively for each word in the input sequence. This means the recurrent gate is applied once for each time-step. The gradient-signals have to flow back from the loss-function all the way to the first time the recurrent gate is used. If the gradient of the recurrent gate is multiplicative, then we essentially have an exponential function.\n",
+    "\n",
+    "In this tutorial we will use texts that have more than 500 words. This means the RU's gate for updating its internal memory-state is applied recursively more than 500 times. If a gradient of just 1.01 is multiplied with itself 500 times then it gives a value of about 145. If a gradient of just 0.99 is multiplied with itself 500 times then it gives a value of about 0.007. These are called exploding and vanishing gradients. The only gradients that can survive recurrent multiplication are 0 and 1.\n",
+    "\n",
+    "To avoid these so-called exploding and vanishing gradients, care must be made when designing the recurrent unit and its gates. That is why the actual implementation of the GRU is more complicated, because it tries to send the gradient back through the gates without this distortion."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from scipy.spatial.distance import cdist"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need to import several things from Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Sequential  # This does not work!\n",
+    "from tensorflow.python.keras.models import Sequential\n",
+    "from tensorflow.python.keras.layers import Dense, GRU, Embedding\n",
+    "from tensorflow.python.keras.optimizers import Adam\n",
+    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.5.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.1.2-tf'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data\n",
+    "\n",
+    "We will use a data-set consisting of 50000 reviews of movies from IMDB. Keras has a built-in function for downloading a similar data-set (but apparently half the size). However, Keras' version has already converted the text in the data-set to integer-tokens, which is a crucial part of working with natural languages that will also be demonstrated in this tutorial, so we download the actual text-data.\n",
+    "\n",
+    "NOTE: The data-set is 84 MB and will be downloaded automatically."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import imdb"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Change this if you want the files saved in another directory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imdb.data_dir = \"data/IMDB/\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Automatically download and extract the files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "imdb.maybe_download_and_extract()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load the training- and test-sets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train_text, y_train = imdb.load_data(train=True)\n",
+    "x_test_text, y_test = imdb.load_data(train=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train-set size:  25000\n",
+      "Test-set size:   25000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Train-set size: \", len(x_train_text))\n",
+    "print(\"Test-set size:  \", len(x_test_text))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Combine into one data-set for some uses below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_text = x_train_text + x_test_text"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Print an example from the training-set to see that the data looks correct."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train_text[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The true \"class\" is a sentiment of the movie-review. It is a value of 0.0 for a negative sentiment and 1.0 for a positive sentiment. In this case the review is positive."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_train[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tokenizer\n",
+    "\n",
+    "A neural network cannot work directly on text-strings so we must convert it somehow. There are two steps in this conversion, the first step is called the \"tokenizer\" which converts words to integers and is done on the data-set before it is input to the neural network. The second step is an integrated part of the neural network itself and is called the \"embedding\"-layer, which is described further below.\n",
+    "\n",
+    "We may instruct the tokenizer to only use e.g. the 10000 most popular words from the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_words = 10000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "tokenizer = Tokenizer(num_words=num_words)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The tokenizer can then be \"fitted\" to the data-set. This scans through all the text and strips it from unwanted characters such as punctuation, and also converts it to lower-case characters. The tokenizer then builds a vocabulary of all unique words along with various data-structures for accessing the data.\n",
+    "\n",
+    "Note that we fit the tokenizer on the entire data-set so it gathers words from both the training- and test-data. This is OK as we are merely building a vocabulary and want it to be as complete as possible. The actual neural network will of course only be trained on the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 10.6 s, sys: 16 ms, total: 10.6 s\n",
+      "Wall time: 10.6 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "tokenizer.fit_on_texts(data_text)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you want to use the entire vocabulary then set `num_words=None` above, and then it will automatically be set to the vocabulary-size here. (This is because of Keras' somewhat awkward implementation.)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if num_words is None:\n",
+    "    num_words = len(tokenizer.word_index)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then inspect the vocabulary that has been gathered by the tokenizer. This is ordered by the number of occurrences of the words in the data-set. These integer-numbers are called word indices or \"tokens\" because they uniquely identify each word in the vocabulary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'the': 1,\n",
+       " 'and': 2,\n",
+       " 'a': 3,\n",
+       " 'of': 4,\n",
+       " 'to': 5,\n",
+       " 'is': 6,\n",
+       " 'br': 7,\n",
+       " 'in': 8,\n",
+       " 'it': 9,\n",
+       " 'i': 10,\n",
+       " 'this': 11,\n",
+       " 'that': 12,\n",
+       " 'was': 13,\n",
+       " 'as': 14,\n",
+       " 'for': 15,\n",
+       " 'with': 16,\n",
+       " 'movie': 17,\n",
+       " 'but': 18,\n",
+       " 'film': 19,\n",
+       " 'on': 20,\n",
+       " 'not': 21,\n",
+       " 'you': 22,\n",
+       " 'are': 23,\n",
+       " 'his': 24,\n",
+       " 'have': 25,\n",
+       " 'be': 26,\n",
+       " 'one': 27,\n",
+       " 'he': 28,\n",
+       " 'all': 29,\n",
+       " 'at': 30,\n",
+       " 'by': 31,\n",
+       " 'an': 32,\n",
+       " 'they': 33,\n",
+       " 'so': 34,\n",
+       " 'who': 35,\n",
+       " 'from': 36,\n",
+       " 'like': 37,\n",
+       " 'or': 38,\n",
+       " 'just': 39,\n",
+       " 'her': 40,\n",
+       " 'out': 41,\n",
+       " 'about': 42,\n",
+       " 'if': 43,\n",
+       " \"it's\": 44,\n",
+       " 'has': 45,\n",
+       " 'there': 46,\n",
+       " 'some': 47,\n",
+       " 'what': 48,\n",
+       " 'good': 49,\n",
+       " 'when': 50,\n",
+       " 'more': 51,\n",
+       " 'very': 52,\n",
+       " 'up': 53,\n",
+       " 'no': 54,\n",
+       " 'time': 55,\n",
+       " 'my': 56,\n",
+       " 'even': 57,\n",
+       " 'would': 58,\n",
+       " 'she': 59,\n",
+       " 'which': 60,\n",
+       " 'only': 61,\n",
+       " 'really': 62,\n",
+       " 'see': 63,\n",
+       " 'story': 64,\n",
+       " 'their': 65,\n",
+       " 'had': 66,\n",
+       " 'can': 67,\n",
+       " 'me': 68,\n",
+       " 'well': 69,\n",
+       " 'were': 70,\n",
+       " 'than': 71,\n",
+       " 'much': 72,\n",
+       " 'we': 73,\n",
+       " 'bad': 74,\n",
+       " 'been': 75,\n",
+       " 'get': 76,\n",
+       " 'do': 77,\n",
+       " 'great': 78,\n",
+       " 'other': 79,\n",
+       " 'will': 80,\n",
+       " 'also': 81,\n",
+       " 'into': 82,\n",
+       " 'people': 83,\n",
+       " 'because': 84,\n",
+       " 'how': 85,\n",
+       " 'first': 86,\n",
+       " 'him': 87,\n",
+       " 'most': 88,\n",
+       " \"don't\": 89,\n",
+       " 'made': 90,\n",
+       " 'then': 91,\n",
+       " 'its': 92,\n",
+       " 'them': 93,\n",
+       " 'make': 94,\n",
+       " 'way': 95,\n",
+       " 'too': 96,\n",
+       " 'movies': 97,\n",
+       " 'could': 98,\n",
+       " 'any': 99,\n",
+       " 'after': 100,\n",
+       " 'think': 101,\n",
+       " 'characters': 102,\n",
+       " 'watch': 103,\n",
+       " 'films': 104,\n",
+       " 'two': 105,\n",
+       " 'many': 106,\n",
+       " 'seen': 107,\n",
+       " 'character': 108,\n",
+       " 'being': 109,\n",
+       " 'never': 110,\n",
+       " 'plot': 111,\n",
+       " 'love': 112,\n",
+       " 'acting': 113,\n",
+       " 'life': 114,\n",
+       " 'did': 115,\n",
+       " 'best': 116,\n",
+       " 'where': 117,\n",
+       " 'know': 118,\n",
+       " 'show': 119,\n",
+       " 'little': 120,\n",
+       " 'over': 121,\n",
+       " 'off': 122,\n",
+       " 'ever': 123,\n",
+       " 'does': 124,\n",
+       " 'your': 125,\n",
+       " 'better': 126,\n",
+       " 'end': 127,\n",
+       " 'man': 128,\n",
+       " 'scene': 129,\n",
+       " 'still': 130,\n",
+       " 'say': 131,\n",
+       " 'these': 132,\n",
+       " 'here': 133,\n",
+       " 'why': 134,\n",
+       " 'scenes': 135,\n",
+       " 'while': 136,\n",
+       " 'something': 137,\n",
+       " 'such': 138,\n",
+       " 'go': 139,\n",
+       " 'through': 140,\n",
+       " 'back': 141,\n",
+       " 'should': 142,\n",
+       " 'those': 143,\n",
+       " 'real': 144,\n",
+       " \"i'm\": 145,\n",
+       " 'now': 146,\n",
+       " 'watching': 147,\n",
+       " 'thing': 148,\n",
+       " \"doesn't\": 149,\n",
+       " 'actors': 150,\n",
+       " 'though': 151,\n",
+       " 'funny': 152,\n",
+       " 'years': 153,\n",
+       " \"didn't\": 154,\n",
+       " 'old': 155,\n",
+       " 'another': 156,\n",
+       " '10': 157,\n",
+       " 'work': 158,\n",
+       " 'before': 159,\n",
+       " 'actually': 160,\n",
+       " 'nothing': 161,\n",
+       " 'makes': 162,\n",
+       " 'look': 163,\n",
+       " 'director': 164,\n",
+       " 'find': 165,\n",
+       " 'going': 166,\n",
+       " 'same': 167,\n",
+       " 'new': 168,\n",
+       " 'lot': 169,\n",
+       " 'every': 170,\n",
+       " 'few': 171,\n",
+       " 'again': 172,\n",
+       " 'part': 173,\n",
+       " 'cast': 174,\n",
+       " 'down': 175,\n",
+       " 'us': 176,\n",
+       " 'things': 177,\n",
+       " 'want': 178,\n",
+       " 'quite': 179,\n",
+       " 'pretty': 180,\n",
+       " 'world': 181,\n",
+       " 'horror': 182,\n",
+       " 'around': 183,\n",
+       " 'seems': 184,\n",
+       " \"can't\": 185,\n",
+       " 'young': 186,\n",
+       " 'take': 187,\n",
+       " 'however': 188,\n",
+       " 'got': 189,\n",
+       " 'thought': 190,\n",
+       " 'big': 191,\n",
+       " 'fact': 192,\n",
+       " 'enough': 193,\n",
+       " 'long': 194,\n",
+       " 'both': 195,\n",
+       " \"that's\": 196,\n",
+       " 'give': 197,\n",
+       " \"i've\": 198,\n",
+       " 'own': 199,\n",
+       " 'may': 200,\n",
+       " 'between': 201,\n",
+       " 'comedy': 202,\n",
+       " 'right': 203,\n",
+       " 'series': 204,\n",
+       " 'action': 205,\n",
+       " 'must': 206,\n",
+       " 'music': 207,\n",
+       " 'without': 208,\n",
+       " 'times': 209,\n",
+       " 'saw': 210,\n",
+       " 'always': 211,\n",
+       " 'original': 212,\n",
+       " \"isn't\": 213,\n",
+       " 'role': 214,\n",
+       " 'come': 215,\n",
+       " 'almost': 216,\n",
+       " 'gets': 217,\n",
+       " 'interesting': 218,\n",
+       " 'guy': 219,\n",
+       " 'point': 220,\n",
+       " 'done': 221,\n",
+       " \"there's\": 222,\n",
+       " 'whole': 223,\n",
+       " 'least': 224,\n",
+       " 'far': 225,\n",
+       " 'bit': 226,\n",
+       " 'script': 227,\n",
+       " 'minutes': 228,\n",
+       " 'feel': 229,\n",
+       " '2': 230,\n",
+       " 'anything': 231,\n",
+       " 'making': 232,\n",
+       " 'might': 233,\n",
+       " 'since': 234,\n",
+       " 'am': 235,\n",
+       " 'family': 236,\n",
+       " \"he's\": 237,\n",
+       " 'last': 238,\n",
+       " 'probably': 239,\n",
+       " 'tv': 240,\n",
+       " 'performance': 241,\n",
+       " 'kind': 242,\n",
+       " 'away': 243,\n",
+       " 'yet': 244,\n",
+       " 'fun': 245,\n",
+       " 'worst': 246,\n",
+       " 'sure': 247,\n",
+       " 'rather': 248,\n",
+       " 'hard': 249,\n",
+       " 'girl': 250,\n",
+       " 'anyone': 251,\n",
+       " 'each': 252,\n",
+       " 'played': 253,\n",
+       " 'day': 254,\n",
+       " 'found': 255,\n",
+       " 'looking': 256,\n",
+       " 'woman': 257,\n",
+       " 'screen': 258,\n",
+       " 'although': 259,\n",
+       " 'our': 260,\n",
+       " 'especially': 261,\n",
+       " 'believe': 262,\n",
+       " 'having': 263,\n",
+       " 'trying': 264,\n",
+       " 'course': 265,\n",
+       " 'dvd': 266,\n",
+       " 'everything': 267,\n",
+       " 'set': 268,\n",
+       " 'goes': 269,\n",
+       " 'comes': 270,\n",
+       " 'put': 271,\n",
+       " 'ending': 272,\n",
+       " 'maybe': 273,\n",
+       " 'place': 274,\n",
+       " 'book': 275,\n",
+       " 'shows': 276,\n",
+       " 'three': 277,\n",
+       " 'worth': 278,\n",
+       " 'different': 279,\n",
+       " 'main': 280,\n",
+       " 'once': 281,\n",
+       " 'sense': 282,\n",
+       " 'american': 283,\n",
+       " 'reason': 284,\n",
+       " 'looks': 285,\n",
+       " 'effects': 286,\n",
+       " 'watched': 287,\n",
+       " 'play': 288,\n",
+       " 'true': 289,\n",
+       " 'money': 290,\n",
+       " 'actor': 291,\n",
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+       " 'male': 910,\n",
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+       " 'superb': 916,\n",
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+       " 'whom': 924,\n",
+       " 'laughs': 925,\n",
+       " 'stage': 926,\n",
+       " 'nature': 927,\n",
+       " 'effect': 928,\n",
+       " 'comment': 929,\n",
+       " 'forward': 930,\n",
+       " 'nor': 931,\n",
+       " 'badly': 932,\n",
+       " 'sounds': 933,\n",
+       " 'previous': 934,\n",
+       " 'e': 935,\n",
+       " 'japanese': 936,\n",
+       " 'weird': 937,\n",
+       " 'island': 938,\n",
+       " 'inside': 939,\n",
+       " 'personal': 940,\n",
+       " 'quickly': 941,\n",
+       " 'total': 942,\n",
+       " 'keeps': 943,\n",
+       " 'towards': 944,\n",
+       " 'result': 945,\n",
+       " 'america': 946,\n",
+       " 'battle': 947,\n",
+       " 'crazy': 948,\n",
+       " 'worked': 949,\n",
+       " 'setting': 950,\n",
+       " 'incredibly': 951,\n",
+       " 'earlier': 952,\n",
+       " 'background': 953,\n",
+       " 'mess': 954,\n",
+       " 'cop': 955,\n",
+       " 'writers': 956,\n",
+       " 'fire': 957,\n",
+       " 'copy': 958,\n",
+       " 'unique': 959,\n",
+       " 'dumb': 960,\n",
+       " 'realize': 961,\n",
+       " 'powerful': 962,\n",
+       " 'mark': 963,\n",
+       " 'lee': 964,\n",
+       " 'business': 965,\n",
+       " 'rate': 966,\n",
+       " 'dramatic': 967,\n",
+       " 'older': 968,\n",
+       " 'pay': 969,\n",
+       " 'following': 970,\n",
+       " 'directors': 971,\n",
+       " 'girlfriend': 972,\n",
+       " 'joke': 973,\n",
+       " 'plenty': 974,\n",
+       " 'directing': 975,\n",
+       " 'various': 976,\n",
+       " 'creepy': 977,\n",
+       " 'baby': 978,\n",
+       " 'development': 979,\n",
+       " 'appear': 980,\n",
+       " 'brings': 981,\n",
+       " 'front': 982,\n",
+       " 'ask': 983,\n",
+       " 'dream': 984,\n",
+       " 'water': 985,\n",
+       " 'admit': 986,\n",
+       " 'bill': 987,\n",
+       " 'rich': 988,\n",
+       " 'apart': 989,\n",
+       " 'joe': 990,\n",
+       " 'political': 991,\n",
+       " 'fairly': 992,\n",
+       " 'reasons': 993,\n",
+       " 'leading': 994,\n",
+       " 'portrayed': 995,\n",
+       " 'spent': 996,\n",
+       " 'telling': 997,\n",
+       " 'cover': 998,\n",
+       " 'outside': 999,\n",
+       " 'wasted': 1000,\n",
+       " ...}"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer.word_index"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then use the tokenizer to convert all texts in the training-set to lists of these tokens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train_tokens = tokenizer.texts_to_sequences(x_train_text)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, here is a text from the training-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train_text[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This text corresponds to the following list of tokens:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   3,  591,  929,    7,    7,   48,   67,   10,  131,   11,    6,\n",
+       "          3,  393,   19,   12,   10,   67,  103,  121,    2,  121,    9,\n",
+       "          6,  406,   27,    4,    1,  342,  713, 1317,   90,   16,    3,\n",
+       "         78,  174,  694, 4910,    2, 2556, 3599,    3,  399,  227,   31,\n",
+       "       4033, 2628,  441,   20,   24,  288,    7,    7,    9,    6,  144,\n",
+       "          5,  114,  871,  221,  922,   43,   22,   25, 3639, 1897,   27,\n",
+       "        217,    1, 9206,   20, 1306,    4,  258,    5,  197,   48,    6,\n",
+       "         20,    9,  631,  411,   11,   19,  405,   18,    8,  614,    9,\n",
+       "       1003,  405,   43,   22,   62,  103,   11,   19,   27,   67,  380,\n",
+       "         12,    9,   80,   26,   14,  152,    2, 1451,    3, 2997,  153,\n",
+       "         36,  146])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(x_train_tokens[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We also need to convert the texts in the test-set to tokens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_test_tokens = tokenizer.texts_to_sequences(x_test_text)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Padding and Truncating Data\n",
+    "\n",
+    "The Recurrent Neural Network can take sequences of arbitrary length as input, but in order to use a whole batch of data, the sequences need to have the same length. There are two ways of achieving this: (A) Either we ensure that all sequences in the entire data-set have the same length, or (B) we write a custom data-generator that ensures the sequences have the same length within each batch.\n",
+    "\n",
+    "Solution (A) is simpler but if we use the length of the longest sequence in the data-set, then we are wasting a lot of memory. This is particularly important for larger data-sets.\n",
+    "\n",
+    "So in order to make a compromise, we will use a sequence-length that covers most sequences in the data-set, and we will then truncate longer sequences and pad shorter sequences.\n",
+    "\n",
+    "First we count the number of tokens in all the sequences in the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_tokens = [len(tokens) for tokens in x_train_tokens + x_test_tokens]\n",
+    "num_tokens = np.array(num_tokens)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The average number of tokens in a sequence is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "221.27716"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.mean(num_tokens)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The maximum number of tokens in a sequence is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2209"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.max(num_tokens)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The max number of tokens we will allow is set to the average plus 2 standard deviations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "544"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max_tokens = np.mean(num_tokens) + 2 * np.std(num_tokens)\n",
+    "max_tokens = int(max_tokens)\n",
+    "max_tokens"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This covers about 95% of the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.94534"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(num_tokens < max_tokens) / len(num_tokens)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When padding or truncating the sequences that have a different length, we need to determine if we want to do this padding or truncating 'pre' or 'post'. If a sequence is truncated, it means that a part of the sequence is simply thrown away. If a sequence is padded, it means that zeros are added to the sequence.\n",
+    "\n",
+    "So the choice of 'pre' or 'post' can be important because it determines whether we throw away the first or last part of a sequence when truncating, and it determines whether we add zeros to the beginning or end of the sequence when padding. This may confuse the Recurrent Neural Network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pad = 'pre'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train_pad = pad_sequences(x_train_tokens, maxlen=max_tokens,\n",
+    "                            padding=pad, truncating=pad)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_test_pad = pad_sequences(x_test_tokens, maxlen=max_tokens,\n",
+    "                           padding=pad, truncating=pad)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We have now transformed the training-set into one big matrix of integers (tokens) with this shape:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(25000, 544)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train_pad.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The matrix for the test-set has the same shape:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(25000, 544)"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_test_pad.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, we had the following sequence of tokens above:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   3,  591,  929,    7,    7,   48,   67,   10,  131,   11,    6,\n",
+       "          3,  393,   19,   12,   10,   67,  103,  121,    2,  121,    9,\n",
+       "          6,  406,   27,    4,    1,  342,  713, 1317,   90,   16,    3,\n",
+       "         78,  174,  694, 4910,    2, 2556, 3599,    3,  399,  227,   31,\n",
+       "       4033, 2628,  441,   20,   24,  288,    7,    7,    9,    6,  144,\n",
+       "          5,  114,  871,  221,  922,   43,   22,   25, 3639, 1897,   27,\n",
+       "        217,    1, 9206,   20, 1306,    4,  258,    5,  197,   48,    6,\n",
+       "         20,    9,  631,  411,   11,   19,  405,   18,    8,  614,    9,\n",
+       "       1003,  405,   43,   22,   62,  103,   11,   19,   27,   67,  380,\n",
+       "         12,    9,   80,   26,   14,  152,    2, 1451,    3, 2997,  153,\n",
+       "         36,  146])"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(x_train_tokens[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This has simply been padded to create the following sequence. Note that when this is input to the Recurrent Neural Network, then it first inputs a lot of zeros. If we had padded 'post' then it would input the integer-tokens first and then a lot of zeros. This may confuse the Recurrent Neural Network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    3,  591,  929,    7,    7,   48,   67,   10,\n",
+       "        131,   11,    6,    3,  393,   19,   12,   10,   67,  103,  121,\n",
+       "          2,  121,    9,    6,  406,   27,    4,    1,  342,  713, 1317,\n",
+       "         90,   16,    3,   78,  174,  694, 4910,    2, 2556, 3599,    3,\n",
+       "        399,  227,   31, 4033, 2628,  441,   20,   24,  288,    7,    7,\n",
+       "          9,    6,  144,    5,  114,  871,  221,  922,   43,   22,   25,\n",
+       "       3639, 1897,   27,  217,    1, 9206,   20, 1306,    4,  258,    5,\n",
+       "        197,   48,    6,   20,    9,  631,  411,   11,   19,  405,   18,\n",
+       "          8,  614,    9, 1003,  405,   43,   22,   62,  103,   11,   19,\n",
+       "         27,   67,  380,   12,    9,   80,   26,   14,  152,    2, 1451,\n",
+       "          3, 2997,  153,   36,  146], dtype=int32)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train_pad[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tokenizer Inverse Map\n",
+    "\n",
+    "For some strange reason, the Keras implementation of a tokenizer does not seem to have the inverse mapping from integer-tokens back to words, which is needed to reconstruct text-strings from lists of tokens. So we make that mapping here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = tokenizer.word_index\n",
+    "inverse_map = dict(zip(idx.values(), idx.keys()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Helper-function for converting a list of tokens back to a string of words."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def tokens_to_string(tokens):\n",
+    "    # Map from tokens back to words.\n",
+    "    words = [inverse_map[token] for token in tokens if token != 0]\n",
+    "    \n",
+    "    # Concatenate all words.\n",
+    "    text = \" \".join(words)\n",
+    "\n",
+    "    return text"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, this is the original text from the data-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train_text[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can recreate this text except for punctuation and other symbols, by converting the list of tokens back to words:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'a simple comment br br what can i say this is a wonderful film that i can watch over and over it is definitely one of the top ten comedies made with a great cast jack lemmon and walter matthau a perfect script by neil simon based on his play br br it is real to life situation done perfectly if you have digital cable one gets the menu on bottom of screen to give what is on it usually gives this film stars but in reality it deserves stars if you really watch this film one can tell that it will be as funny and fresh a hundred years from now'"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokens_to_string(x_train_tokens[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create the Recurrent Neural Network\n",
+    "\n",
+    "We are now ready to create the Recurrent Neural Network (RNN). We will use the Keras API for this because of its simplicity. See Tutorial #03-C for a tutorial on Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = Sequential()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The first layer in the RNN is a so-called Embedding-layer which converts each integer-token into a vector of values. This is necessary because the integer-tokens may take on values between 0 and 10000 for a vocabulary of 10000 words. The RNN cannot work on values in such a wide range. The embedding-layer is trained as a part of the RNN and will learn to map words with similar semantic meanings to similar embedding-vectors, as will be shown further below.\n",
+    "\n",
+    "First we define the size of the embedding-vector for each integer-token. In this case we have set it to 8, so that each integer-token will be converted to a vector of length 8. The values of the embedding-vector will generally fall roughly between -1.0 and 1.0, although they may exceed these values somewhat.\n",
+    "\n",
+    "The size of the embedding-vector is typically selected between 100-300, but it seems to work reasonably well with small values for Sentiment Analysis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embedding_size = 8"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The embedding-layer also needs to know the number of words in the vocabulary (`num_words`) and the length of the padded token-sequences (`max_tokens`). We also give this layer a name because we need to retrieve its weights further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.add(Embedding(input_dim=num_words,\n",
+    "                    output_dim=embedding_size,\n",
+    "                    input_length=max_tokens,\n",
+    "                    name='layer_embedding'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now add the first Gated Recurrent Unit (GRU) to the network. This will have 16 outputs. Because we will add a second GRU after this one, we need to return sequences of data because the next GRU expects sequences as its input."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.add(GRU(units=16, return_sequences=True))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This adds the second GRU with 8 output units. This will be followed by another GRU so it must also return sequences."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.add(GRU(units=8, return_sequences=True))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This adds the third and final GRU with 4 output units. This will be followed by a dense-layer, so it should only give the final output of the GRU and not a whole sequence of outputs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.add(GRU(units=4))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Add a fully-connected / dense layer which computes a value between 0.0 and 1.0 that will be used as the classification output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.add(Dense(1, activation='sigmoid'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Use the Adam optimizer with the given learning-rate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer = Adam(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compile the Keras model so it is ready for training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.compile(loss='binary_crossentropy',\n",
+    "              optimizer=optimizer,\n",
+    "              metrics=['accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "layer_embedding (Embedding)  (None, 544, 8)            80000     \n",
+      "_________________________________________________________________\n",
+      "gru_1 (GRU)                  (None, None, 16)          1200      \n",
+      "_________________________________________________________________\n",
+      "gru_2 (GRU)                  (None, None, 8)           600       \n",
+      "_________________________________________________________________\n",
+      "gru_3 (GRU)                  (None, 4)                 156       \n",
+      "_________________________________________________________________\n",
+      "dense_1 (Dense)              (None, 1)                 5         \n",
+      "=================================================================\n",
+      "Total params: 81,961\n",
+      "Trainable params: 81,961\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Train the Recurrent Neural Network\n",
+    "\n",
+    "We can now train the model. Note that we are using the data-set with the padded sequences. We use 5% of the training-set as a small validation-set, so we have a rough idea whether the model is generalizing well or if it is perhaps over-fitting to the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train on 23750 samples, validate on 1250 samples\n",
+      "Epoch 1/3\n",
+      "23750/23750 [==============================]23750/23750 [==============================] - 464s 20ms/step - loss: 0.6517 - acc: 0.6002 - val_loss: 0.6218 - val_acc: 0.6752\n",
+      "\n",
+      "Epoch 2/3\n",
+      "23750/23750 [==============================]23750/23750 [==============================] - 447s 19ms/step - loss: 0.4292 - acc: 0.8102 - val_loss: 0.6701 - val_acc: 0.6512\n",
+      "\n",
+      "Epoch 3/3\n",
+      "23750/23750 [==============================]23750/23750 [==============================] - 445s 19ms/step - loss: 0.3092 - acc: 0.8765 - val_loss: 0.3182 - val_acc: 0.8752\n",
+      "\n",
+      "CPU times: user 35min 19s, sys: 2min 41s, total: 38min\n",
+      "Wall time: 22min 37s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7ff79f0d6cf8>"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "model.fit(x_train_pad, y_train,\n",
+    "          validation_split=0.05, epochs=3, batch_size=64)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Performance on Test-Set\n",
+    "\n",
+    "Now that the model has been trained we can calculate its classification accuracy on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "25000/25000 [==============================]25000/25000 [==============================] - 175s 7ms/step\n",
+      "\n",
+      "CPU times: user 2min 59s, sys: 340 ms, total: 2min 59s\n",
+      "Wall time: 2min 55s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "result = model.evaluate(x_test_pad, y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 86.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Accuracy: {0:.2%}\".format(result[1]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example of Mis-Classified Text\n",
+    "\n",
+    "In order to show an example of mis-classified text, we first calculate the predicted sentiment for the first 1000 texts in the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 7.01 s, sys: 0 ns, total: 7.01 s\n",
+      "Wall time: 6.88 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "y_pred = model.predict(x=x_test_pad[0:1000])\n",
+    "y_pred = y_pred.T[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These predicted numbers fall between 0.0 and 1.0. We use a cutoff / threshold and say that all values above 0.5 are taken to be 1.0 and all values below 0.5 are taken to be 0.0. This gives us a predicted \"class\" of either 0.0 or 1.0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_pred = np.array([1.0 if p>0.5 else 0.0 for p in y_pred])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The true \"class\" for the first 1000 texts in the test-set are needed for comparison."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cls_true = np.array(y_test[0:1000])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then get indices for all the texts that were incorrectly classified by comparing all the \"classes\" of these two arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "incorrect = np.where(cls_pred != cls_true)\n",
+    "incorrect = incorrect[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Of the 1000 texts used, how many were mis-classified?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "121"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(incorrect)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us look at the first mis-classified text. We will use its index several times."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "13"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idx = incorrect[0]\n",
+    "idx"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The mis-classified text is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'I would like to start by saying I can only hope that the makers of this movie and it\\'s sister film The Intruder (directed by the great unheralded stylist auteur that is Jopi Burnama) know in their hearts just how much pleasure they have brought to me and my friends in the sleepy north eastern town of Jarrow.<br /><br />From the opening pre credit sequence which manages to drag ever so slightly despite containing a man crashing through a window on a motorbike, the pitiless destruction of a silence lab, the introduction of one of the most simultaneously annoying and anaemic bad guys in movie history and costume design that Jean Paul Gautier would find ott and garish. Make no mistake; this is a truly unique experience. Early highlight - an explosion (get used to it, plenty more where that came from!) followed by a close up of our chubby heroine and the most hilarious line reading of the word \"dad\" in living memory. And then... the theme song...<br /><br />Yeah, this deserves its own paragraph. Sung by AJ, written by people who really should wish to remain anonymous, it makes the songs written for the Rocky films sound like Schubert. This is crap 80\\'s hero motivation narcissism at an all time high, with choice lyrics such as \"its only me and you, its come down to the wire\" and much talk of having to \"cross the line\" (it\\'ll make sense in time - our hero cares little for the boundaries of bona fida police work) abounding. Not to mention the Indonesian Supremes cooing the film\\'s title seductively. At this point anyone wishing to switch off officially has no pulse.<br /><br />Our hero is Semitic cop Peter Goldson (essayed brilliantly by Intruder star Peter O\\'Brien), the \"stabilizer\" of the title. The man\\'s bull in a china shop approach to crime fighting and particularly his less than inconspicuous undercover work truly leaves much to be desired, but he is without question an entertaining guide through the mean streets of downtown Jakarta, with local sleaze ball connection Captain Johnny in tow, as well as Peter\\'s own waste of space partner in fashion crime Sylvia Nash, who does little. So many highlights, so little time - the \"slide please\" arrogance of Peter\\'s not all too convincingly argued case against chief baddie Greg Rainmaker (Intruder fans will know hirsute slimy bastard Craig Gavin as the monstrous John White - helluva name eh? No! Oh well...), the x marks the spot location map stupidity, our hero taking horrible advantage of heroine Tina Probost during a moment of weakness on her behalf, the latter turning up at a sting operation dressed like a member of a particularly flamboyant dancing troop. And believe me that barely covers it.<br /><br />There wasn\\'t even time to go into the plot revolving around the hunt for a drug detection system and a kidnapped professor with an alarming but commendable amount of national pride. Or our hero turning up at a funeral dressed as if an extra on Boogie Nights. Or the absolutely hysterical craic between Captain Johnny and Goldson - two guys have never made more heavy weather of buddy buddy shtick than these clowns. The trowel was possibly too subtle me thinks.<br /><br />Ah it tails off people, and you never thought scenes of wanton destruction and general mayhem could be so unbelievably boring, but the character interaction is stupendous, the dialogue truly priceless and the incompetence on show somehow endearing. Oh and the shoes people - watch out for the shoes!'"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "text = x_test_text[idx]\n",
+    "text"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the predicted and true classes for the text:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.08332923"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_pred[idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cls_true[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## New Data\n",
+    "\n",
+    "Let us try and classify new texts that we make up. Some of these are obvious, while others use negation and sarcasm to try and confuse the model into mis-classifying the text."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text1 = \"This movie is fantastic! I really like it because it is so good!\"\n",
+    "text2 = \"Good movie!\"\n",
+    "text3 = \"Maybe I like this movie.\"\n",
+    "text4 = \"Meh ...\"\n",
+    "text5 = \"If I were a drunk teenager then this movie might be good.\"\n",
+    "text6 = \"Bad movie!\"\n",
+    "text7 = \"Not a good movie!\"\n",
+    "text8 = \"This movie really sucks! Can I get my money back please?\"\n",
+    "texts = [text1, text2, text3, text4, text5, text6, text7, text8]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We first convert these texts to arrays of integer-tokens because that is needed by the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tokens = tokenizer.texts_to_sequences(texts)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To input texts with different lengths into the model, we also need to pad and truncate them."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8, 544)"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokens_pad = pad_sequences(tokens, maxlen=max_tokens,\n",
+    "                           padding=pad, truncating=pad)\n",
+    "tokens_pad.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now use the trained model to predict the sentiment for these texts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.868934  ],\n",
+       "       [0.72526425],\n",
+       "       [0.33099633],\n",
+       "       [0.49190348],\n",
+       "       [0.3054021 ],\n",
+       "       [0.14959489],\n",
+       "       [0.5235635 ],\n",
+       "       [0.21565402]], dtype=float32)"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.predict(tokens_pad)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A value close to 0.0 means a negative sentiment and a value close to 1.0 means a positive sentiment. These numbers will vary every time you train the model."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Embeddings\n",
+    "\n",
+    "The model cannot work on integer-tokens directly, because they are integer values that may range between 0 and the number of words in our vocabulary, e.g. 10000. So we need to convert the integer-tokens into vectors of values that are roughly between -1.0 and 1.0 which can be used as input to a neural network.\n",
+    "\n",
+    "This mapping from integer-tokens to real-valued vectors is also called an \"embedding\". It is essentially just a matrix where each row contains the vector-mapping of a single token. This means we can quickly lookup the mapping of each integer-token by simply using the token as an index into the matrix. The embeddings are learned along with the rest of the model during training.\n",
+    "\n",
+    "Ideally the embedding would learn a mapping where words that are similar in meaning also have similar embedding-values. Let us investigate if that has happened here.\n",
+    "\n",
+    "First we need to get the embedding-layer from the model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "layer_embedding = model.get_layer('layer_embedding')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then get the weights used for the mapping done by the embedding-layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weights_embedding = layer_embedding.get_weights()[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that the weights are actually just a matrix with the number of words in the vocabulary times the vector length for each embedding. That's because it is basically just a lookup-matrix."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10000, 8)"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_embedding.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us get the integer-token for the word 'good', which is just an index into the vocabulary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "49"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_good = tokenizer.word_index['good']\n",
+    "token_good"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us also get the integer-token for the word 'great'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "78"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_great = tokenizer.word_index['great']\n",
+    "token_great"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These integertokens may be far apart and will depend on the frequency of those words in the data-set.\n",
+    "\n",
+    "Now let us compare the vector-embeddings for the words 'good' and 'great'. Several of these values are similar, although some values are quite different. Note that these values will change every time you train the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.86528164, 0.6867993 , 0.4362397 , 0.66128314, 0.11546915,\n",
+       "       0.94507647, 0.32628497, 0.535881  ], dtype=float32)"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_embedding[token_good]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.0691622 ,  1.124244  , -0.04477464, -0.05861434,  0.16965319,\n",
+       "        1.2626944 ,  0.76136374, -0.00998422], dtype=float32)"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_embedding[token_great]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Similarly, we can compare the embeddings for the words 'bad' and 'horrible'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "token_bad = tokenizer.word_index['bad']\n",
+    "token_horrible = tokenizer.word_index['horrible']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 0.31903917,  0.53934103,  1.3727672 ,  1.4083829 ,  0.8475107 ,\n",
+       "       -0.22946651,  0.0251075 ,  0.77032244], dtype=float32)"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_embedding[token_bad]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 0.47915924,  0.12226178,  0.90192014,  0.742338  ,  0.58730644,\n",
+       "        0.32736972, -0.17633988,  1.3744307 ], dtype=float32)"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights_embedding[token_horrible]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Sorted Words\n",
+    "\n",
+    "We can also sort all the words in the vocabulary according to their \"similarity\" in the embedding-space. We want to see if words that have similar embedding-vectors also have similar meanings.\n",
+    "\n",
+    "Similarity of embedding-vectors can be measured by different metrics, e.g. Euclidean distance or cosine distance.\n",
+    "\n",
+    "We have a helper-function for calculating these distances and printing the words in sorted order."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_sorted_words(word, metric='cosine'):\n",
+    "    \"\"\"\n",
+    "    Print the words in the vocabulary sorted according to their\n",
+    "    embedding-distance to the given word.\n",
+    "    Different metrics can be used, e.g. 'cosine' or 'euclidean'.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Get the token (i.e. integer ID) for the given word.\n",
+    "    token = tokenizer.word_index[word]\n",
+    "\n",
+    "    # Get the embedding for the given word. Note that the\n",
+    "    # embedding-weight-matrix is indexed by the word-tokens\n",
+    "    # which are integer IDs.\n",
+    "    embedding = weights_embedding[token]\n",
+    "\n",
+    "    # Calculate the distance between the embeddings for\n",
+    "    # this word and all other words in the vocabulary.\n",
+    "    distances = cdist(weights_embedding, [embedding],\n",
+    "                      metric=metric).T[0]\n",
+    "    \n",
+    "    # Get an index sorted according to the embedding-distances.\n",
+    "    # These are the tokens (integer IDs) for words in the vocabulary.\n",
+    "    sorted_index = np.argsort(distances)\n",
+    "    \n",
+    "    # Sort the embedding-distances.\n",
+    "    sorted_distances = distances[sorted_index]\n",
+    "    \n",
+    "    # Sort all the words in the vocabulary according to their\n",
+    "    # embedding-distance. This is a bit excessive because we\n",
+    "    # will only print the top and bottom words.\n",
+    "    sorted_words = [inverse_map[token] for token in sorted_index\n",
+    "                    if token != 0]\n",
+    "\n",
+    "    # Helper-function for printing words and embedding-distances.\n",
+    "    def _print_words(words, distances):\n",
+    "        for word, distance in zip(words, distances):\n",
+    "            print(\"{0:.3f} - {1}\".format(distance, word))\n",
+    "\n",
+    "    # Number of words to print from the top and bottom of the list.\n",
+    "    k = 10\n",
+    "\n",
+    "    print(\"Distance from '{0}':\".format(word))\n",
+    "\n",
+    "    # Print the words with smallest embedding-distance.\n",
+    "    _print_words(sorted_words[0:k], sorted_distances[0:k])\n",
+    "\n",
+    "    print(\"...\")\n",
+    "\n",
+    "    # Print the words with highest embedding-distance.\n",
+    "    _print_words(sorted_words[-k:], sorted_distances[-k:])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then print the words that are near and far from the word 'great' in terms of their vector-embeddings. Note that these may change each time you train the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Distance from 'great':\n",
+      "0.000 - great\n",
+      "0.016 - touching\n",
+      "0.017 - arguments\n",
+      "0.025 - nevertheless\n",
+      "0.031 - elmer\n",
+      "0.032 - 8\n",
+      "0.036 - ritter\n",
+      "0.037 - juliet\n",
+      "0.041 - randy\n",
+      "0.045 - afterward\n",
+      "...\n",
+      "1.057 - rubbish\n",
+      "1.060 - dull\n",
+      "1.064 - disappointing\n",
+      "1.069 - unlikeable\n",
+      "1.078 - uninspired\n",
+      "1.083 - lacks\n",
+      "1.188 - worst\n",
+      "1.225 - waste\n",
+      "1.247 - awful\n",
+      "1.282 - terrible\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_sorted_words('great', metric='cosine')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Similarly, we can print the words that are near and far from the word 'worst' in terms of their vector-embeddings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Distance from 'worst':\n",
+      "0.000 - worst\n",
+      "0.047 - embarrassingly\n",
+      "0.053 - terrible\n",
+      "0.094 - retarded\n",
+      "0.095 - poor\n",
+      "0.095 - stereotyping\n",
+      "0.096 - uninspired\n",
+      "0.099 - awful\n",
+      "0.100 - severed\n",
+      "0.108 - lacks\n",
+      "...\n",
+      "1.167 - restraint\n",
+      "1.168 - available\n",
+      "1.176 - foremost\n",
+      "1.188 - great\n",
+      "1.193 - mesmerizing\n",
+      "1.222 - highly\n",
+      "1.229 - exploration\n",
+      "1.239 - delightful\n",
+      "1.268 - wonderfully\n",
+      "1.323 - 7\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_sorted_words('worst', metric='cosine')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed the basic methods for doing Natural Language Processing (NLP) using a Recurrent Neural Network with integer-tokens and an embedding layer. This was used to do sentiment analysis of movie reviews from IMDB. It works reasonably well if the hyper-parameters are chosen properly. But it is important to understand that this is not human-like comprehension of text. The system does not have any real understanding of the text. It is just a clever way of doing pattern-recognition."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Run more training-epochs. Does it improve performance?\n",
+    "* If your model overfits the training-data, try using dropout-layers and dropout inside the GRU.\n",
+    "* Increase or decrease the number of words in the vocabulary. This is done when the `Tokenizer` is initialized. Does it affect performance?\n",
+    "* Increase the size of the embedding-vectors to e.g. 200. Does it affect performance?\n",
+    "* Try varying all the different hyper-parameters for the Recurrent Neural Network.\n",
+    "* Use Bayesian Optimization from Tutorial #19 to find the best choice of hyper-parameters.\n",
+    "* Use 'post' for padding and truncating in `pad_sequences()`. Does it affect the performance?\n",
+    "* Use individual characters instead of tokenized words as the vocabulary. You can then use one-hot encoded vectors for each character instead of using the embedding-layer.\n",
+    "* Use `model.fit_generator()` instead of `model.fit()` and make your own data-generator, which creates a batch of data using a random subset of `x_train_tokens`. The sequences must be padded so they all match the length of the longest sequence.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2018 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/README.md b/README.md
index 5814592..277cf5a 100644
--- a/README.md
+++ b/README.md
@@ -57,6 +57,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 19. Hyper-Parameter Optimization ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
 
+20. Natural Language Processing ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/images/20_natural_language_flowchart.png b/images/20_natural_language_flowchart.png
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new file mode 100644
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+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#Arrow1Lend-49-9)"
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+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#marker24391)"
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+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#marker24787)"
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+       xml:space="preserve"
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+         sodipodi:role="line"
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+         x="295.15445"
+         y="1225.3796">(Output)</tspan></text>
+    <text
+       xml:space="preserve"
+       style="font-style:normal;font-weight:normal;font-size:30px;line-height:125%;font-family:sans-serif;letter-spacing:0px;word-spacing:0px;fill:#000000;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
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+         sodipodi:role="line"
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+         y="1267.5446">(States)</tspan></text>
+    <path
+       style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#marker5441)"
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+       inkscape:connector-curvature="0" />
+  </g>
+</svg>
diff --git a/imdb.py b/imdb.py
new file mode 100644
index 0000000..3121899
--- /dev/null
+++ b/imdb.py
@@ -0,0 +1,121 @@
+########################################################################
+#
+# Functions for downloading the IMDB Review data-set from the internet
+# and loading it into memory.
+#
+# Implemented in Python 3.6
+#
+# Usage:
+# 1) Set the variable data_dir with the desired storage directory.
+# 2) Call maybe_download_and_extract() to download the data-set
+#    if it is not already located in the given data_dir.
+# 3) Call load_data(train=True) to load the training-set.
+# 4) Call load_data(train=False) to load the test-set.
+# 5) Use the returned data in your own program.
+#
+# Format:
+# The IMDB Review data-set consists of 50000 reviews of movies
+# that are split into 25000 reviews for the training- and test-set,
+# and each of those is split into 12500 positive and 12500 negative reviews.
+# These are returned as lists of strings by the load_data() function.
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2018 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import os
+import download
+import glob
+
+########################################################################
+
+# Directory where you want to download and save the data-set.
+# Set this before you start calling any of the functions below.
+data_dir = "data/IMDB/"
+
+# URL for the data-set on the internet.
+data_url = "http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz"
+
+
+########################################################################
+# Private helper-functions.
+
+def _read_text_file(path):
+    """
+    Read and return all the contents of the text-file with the given path.
+    It is returned as a single string where all lines are concatenated.
+    """
+
+    with open(path, 'rt') as file:
+        # Read a list of strings.
+        lines = file.readlines()
+
+        # Concatenate to a single string.
+        text = " ".join(lines)
+
+    return text
+
+
+########################################################################
+# Public functions that you may call to download the data-set from
+# the internet and load the data into memory.
+
+
+def maybe_download_and_extract():
+    """
+    Download and extract the IMDB Review data-set if it doesn't already exist
+    in data_dir (set this variable first to the desired directory).
+    """
+
+    download.maybe_download_and_extract(url=data_url, download_dir=data_dir)
+
+
+def load_data(train=True):
+    """
+    Load all the data from the IMDB Review data-set for sentiment analysis.
+
+    :param train: Boolean whether to load the training-set (True)
+                  or the test-set (False).
+
+    :return:      A list of all the reviews as text-strings,
+                  and a list of the corresponding sentiments
+                  where 1.0 is positive and 0.0 is negative.
+    """
+
+    # Part of the path-name for either training or test-set.
+    train_test_path = "train" if train else "test"
+
+    # Base-directory where the extracted data is located.
+    dir_base = os.path.join(data_dir, "aclImdb", train_test_path)
+
+    # Filename-patterns for the data-files.
+    path_pattern_pos = os.path.join(dir_base, "pos", "*.txt")
+    path_pattern_neg = os.path.join(dir_base, "neg", "*.txt")
+
+    # Get lists of all the file-paths for the data.
+    paths_pos = glob.glob(path_pattern_pos)
+    paths_neg = glob.glob(path_pattern_neg)
+
+    # Read all the text-files.
+    data_pos = [_read_text_file(path) for path in paths_pos]
+    data_neg = [_read_text_file(path) for path in paths_neg]
+
+    # Concatenate the positive and negative data.
+    x = data_pos + data_neg
+
+    # Create a list of the sentiments for the text-data.
+    # 1.0 is a positive sentiment, 0.0 is a negative sentiment.
+    y = [1.0] * len(data_pos) + [0.0] * len(data_neg)
+
+    return x, y
+
+
+########################################################################

From 35139f01d0a50df4b86eb5b6284e269aca96ed73 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 7 Mar 2018 16:26:37 +0100
Subject: [PATCH 36/61] Fixed link to dev-branch on Github.

---
 19_Hyper-Parameters.ipynb | 186 +++++++++++++++++++++++++++-----------
 1 file changed, 131 insertions(+), 55 deletions(-)

diff --git a/19_Hyper-Parameters.ipynb b/19_Hyper-Parameters.ipynb
index ca10b25..abcbcd5 100644
--- a/19_Hyper-Parameters.ipynb
+++ b/19_Hyper-Parameters.ipynb
@@ -53,7 +53,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -82,7 +84,9 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# from tf.keras.models import Sequential  # This does not work!\n",
@@ -111,15 +115,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**NOTE:** This Notebook requires features in `scikit-optimize` that have not been merged into the official release at the time of this writing. If this Notebook cannot run with the version of `scikit-optimize` installed by the command above, you may have to install `scikit-optimize` from a development branch by running the following command instead:\n",
+    "**NOTE:** This Notebook requires plotting functions in `scikit-optimize` that have not been merged into the official release at the time of this writing. If this Notebook cannot run with the version of `scikit-optimize` installed by the command above, you may have to install `scikit-optimize` from a development branch by running the following command instead:\n",
     "\n",
-    "`pip install git+git://github.com/Hvass-Labs/scikit-optimize.git@610ce8d3e3e82d76f798ad90984c5888a204884e`"
+    "`pip install git+git://github.com/Hvass-Labs/scikit-optimize.git@dd7433da068b5a2509ef4ea4e5195458393e6555`"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import skopt\n",
@@ -142,6 +148,7 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
+    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -163,7 +170,9 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -184,6 +193,7 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -225,7 +235,9 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dim_learning_rate = Real(low=1e-6, high=1e-2, prior='log-uniform',\n",
@@ -242,7 +254,9 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dim_num_dense_layers = Integer(low=1, high=5, name='num_dense_layers')"
@@ -258,7 +272,9 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dim_num_dense_nodes = Integer(low=5, high=512, name='num_dense_nodes')"
@@ -274,7 +290,9 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dim_activation = Categorical(categories=['relu', 'sigmoid'],\n",
@@ -291,7 +309,9 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dimensions = [dim_learning_rate,\n",
@@ -312,7 +332,9 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "default_parameters = [1e-5, 1, 16, 'relu']"
@@ -330,7 +352,9 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def log_dir_name(learning_rate, num_dense_layers,\n",
@@ -365,7 +389,9 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -393,7 +419,9 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -423,7 +451,9 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "data.test.cls = np.argmax(data.test.labels, axis=1)"
@@ -439,7 +469,9 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "validation_data = (data.validation.images, data.validation.labels)"
@@ -462,7 +494,9 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# We know that MNIST images are 28 pixels in each dimension.\n",
@@ -503,7 +537,9 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -545,7 +581,9 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -581,7 +619,9 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred):\n",
@@ -624,6 +664,7 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
+    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
@@ -708,7 +749,9 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "path_best_model = '19_best_model.keras'"
@@ -724,7 +767,9 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "best_accuracy = 0.0"
@@ -742,7 +787,9 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "@use_named_args(dimensions=dimensions)\n",
@@ -845,6 +892,7 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
+    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -900,7 +948,9 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1137,13 +1187,7 @@
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
-      "Epoch 1/3\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "Epoch 1/3\n",
       "55000/55000 [==============================] - 3s - loss: 2.3316 - acc: 0.1049 - val_loss: 2.3019 - val_acc: 0.1070\n",
       "Epoch 2/3\n",
       "55000/55000 [==============================] - 3s - loss: 2.3024 - acc: 0.1090 - val_loss: 2.3017 - val_acc: 0.1126\n",
@@ -1372,13 +1416,7 @@
       "55000/55000 [==============================] - 3s - loss: 2.3570 - acc: 0.0907 - val_loss: 2.3175 - val_acc: 0.0868\n",
       "Epoch 2/3\n",
       "55000/55000 [==============================] - 3s - loss: 2.3074 - acc: 0.0952 - val_loss: 2.3029 - val_acc: 0.1126\n",
-      "Epoch 3/3\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "Epoch 3/3\n",
       "55000/55000 [==============================] - 8s - loss: 2.3019 - acc: 0.1123 - val_loss: 2.3013 - val_acc: 0.1126\n",
       "\n",
       "Accuracy: 11.26%\n",
@@ -1544,6 +1582,7 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1585,6 +1624,7 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1615,7 +1655,9 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "space = search_result.space"
@@ -1631,7 +1673,9 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -1662,6 +1706,7 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1693,6 +1738,7 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1763,6 +1809,7 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1797,6 +1844,7 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1830,7 +1878,9 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dim_names = ['learning_rate', 'num_dense_nodes', 'num_dense_layers']"
@@ -1853,6 +1903,7 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1882,6 +1933,7 @@
    "cell_type": "code",
    "execution_count": 38,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1912,7 +1964,9 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "model = load_model(path_best_model)"
@@ -1928,7 +1982,9 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1953,7 +2009,9 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1979,7 +2037,9 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2005,7 +2065,9 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "images = data.test.images[0:9]"
@@ -2021,7 +2083,9 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "cls_true = data.test.cls[0:9]"
@@ -2037,7 +2101,9 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "y_pred = model.predict(x=images)"
@@ -2053,7 +2119,9 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred,axis=1)"
@@ -2062,7 +2130,9 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -2095,7 +2165,9 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "y_pred = model.predict(x=data.test.images)"
@@ -2111,7 +2183,9 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred,axis=1)"
@@ -2127,7 +2201,9 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -2207,7 +2283,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

From e3c7934920e72c3a8a7f59c5fee68af78988d004 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 14 Mar 2018 12:11:00 +0100
Subject: [PATCH 37/61] Added Tutorial 21

---
 21_Machine_Translation.ipynb | 2170 ++++++++++++++++++++++++++++++++++
 README.md                    |    2 +
 europarl.py                  |  136 +++
 3 files changed, 2308 insertions(+)
 create mode 100644 21_Machine_Translation.ipynb
 create mode 100644 europarl.py

diff --git a/21_Machine_Translation.ipynb b/21_Machine_Translation.ipynb
new file mode 100644
index 0000000..21acd5a
--- /dev/null
+++ b/21_Machine_Translation.ipynb
@@ -0,0 +1,2170 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #21\n",
+    "# Machine Translation\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "Tutorial #20 showed how to use a Recurrent Neural Network (RNN) to do so-called sentiment analysis on texts of movie reviews. This tutorial will extend that idea to do Machine Translation of human languages by combining two RNN's.\n",
+    "\n",
+    "You should be familiar with TensorFlow, Keras and the basics of Natural Language Processing, see Tutorials #01, #03-C and #20."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "The following flowchart shows roughly how the neural network is constructed. It is split into two parts: An encoder which maps the source-text to a \"thought vector\" that summarizes the text's contents, which is then input to the second part of the neural network that decodes the \"thought vector\" to the destination-text.\n",
+    "\n",
+    "The neural network cannot work directly on text so first we need to convert each word to an integer-token using a tokenizer. But the neural network cannot work on integers either, so we use a so-called Embedding Layer to convert each integer-token to a vector of floating-point values. The embedding is trained alongside the rest of the neural network to map words with similar semantic meaning to similar vectors of floating-point values.\n",
+    "\n",
+    "For example, consider the Danish text \"der var engang\" which is the beginning of any fairytale and literally means \"there was once\" but is commonly translated into English as \"once upon a time\". We first convert the entire data-set to integer-tokens so the text \"der var engang\" becomes [12, 54, 1097]. Each of these integer-tokens is then mapped to an embedding-vector with e.g. 128 elements, so the integer-token 12 could for example become [0.12, -0.56, ..., 1.19] and the integer-token 54 could for example become [0.39, 0.09, ..., -0.12]. These embedding-vectors can then be input to the Recurrent Neural Network, which has 3 GRU-layers. See Tutorial #20 for a more detailed explanation.\n",
+    "\n",
+    "The last GRU-layer outputs a single vector - the \"thought vector\" that summarizes the contents of the source-text - which is then used as the initial state of the GRU-units in the decoder-part.\n",
+    "\n",
+    "The destination-text \"once upon a time\" is padded with special markers \"ssss\" and \"eeee\" to indicate its beginning and end, so the sequence of integer-tokens becomes [2, 337, 640, 9, 79, 3]. During training, the decoder will be given this entire sequence as input and  the desired output sequence is [337, 640, 9, 79, 3] which is the same sequence but time-shifted one step. We are trying to teach the decoder to map the \"thought vector\" and the start-token \"ssss\" (integer 2) to the next word \"once\" (integer 337), and then map the word \"once\" to the word \"upon\" (integer 640), and so forth.\n",
+    "\n",
+    "This flow-chart depicts the main idea but does not show all the necessary details e.g. regarding the loss function which is also somewhat complicated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Flowchart](images/21_machine_translation_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import math\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need to import several things from Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Model  # This does not work!\n",
+    "from tensorflow.python.keras.models import Model\n",
+    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.python.keras.optimizers import RMSprop\n",
+    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\n",
+    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.5.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.1.2-tf'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data\n",
+    "\n",
+    "We will use the Europarl data-set which has sentence-pairs in most European languages. The data was created by the European Union which translates a lot of their communications to the languages of the member-countries of the European Union.\n",
+    "\n",
+    "http://www.statmt.org/europarl/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import europarl"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this tutorial I have used the English-Danish data-set which contains about 2 million sentence-pairs. You can use another language by changing this language-code, see `europarl.py` for a list of available language-codes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "language_code='da'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order for the decoder to know when to begin and end a sentence, we need to mark the start and end of each sentence with words that most likely don't occur in the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mark_start = 'ssss '\n",
+    "mark_end = ' eeee'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can change the directory for the data-files if you like."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# data_dir = \"data/europarl/\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This will automatically download and extract the data-files if you don't have them already.\n",
+    "\n",
+    "**WARNING: The file for the English-Danish data-set is about 587 MB!**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "europarl.maybe_download_and_extract(language_code=language_code)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load the texts for the source-language, here we use Danish."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "data_src = europarl.load_data(english=False,\n",
+    "                              language_code=language_code)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load the texts for the destination-language, here we use English."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_dest = europarl.load_data(english=True,\n",
+    "                               language_code=language_code,\n",
+    "                               start=mark_start,\n",
+    "                               end=mark_end)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will build a model to translate from the source language (Danish) to the destination language (English). If you want to make the inverse translation you can merely exchange the source and destination data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example Data\n",
+    "\n",
+    "The data is just a list of texts that is ordered so the source and destination texts match. I can confirm that this example is an accurate translation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Som De kan se, indfandt det store \"år 2000-problem\" sig ikke. Til gengæld har borgerne i en del af medlemslandene været ramt af meget forfærdelige naturkatastrofer.'"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_src[idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"ssss Although, as you will have seen, the dreaded 'millennium bug' failed to materialise, still the people in a number of countries suffered a series of natural disasters that truly were dreadful. eeee\""
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_dest[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Error in Data\n",
+    "\n",
+    "The data-set contains about 2 million sentence-pairs. Some of the data is incorrect. This example appears to be French (or some other weird language I don't understand), although the Danish text is also included."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = 8002"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\"Car il savait ce que cette foule en joie ignorait, et qu\\'on peut lire dans les livres, que le bacille de la peste ne meurt ni ne disparaît jamais, qu\\'il peut rester pendant des dizaines d\\'années endormi dans les meubles et le linge, qu\\'il attend patiemment dans les chambres, les caves, les malles, les mouchoirs et les paperasses, et que, peut-être, le jour viendrait où, pour le malheur et l\\'enseignement des hommes, la peste réveillerait ses rats et les enverrait mourir dans une cité heureuse.\" (Thi han vidste det, som denne glade forsamling ikke vidste, og som man kan læse i bøger, at pestens bacille aldrig dør og aldrig forsvinder, at den kan sove i mange år i møbler og linned, at den venter tålmodigt i kamre, kældre, kufferter, lommetørklæder og papirer, og at den dag måske kommer, hvor pesten til menneskenes skade og oplysning vågner sine rotter og sender dem ud for at dø i en lykkelig by.)'"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_src[idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'ssss \"He knew what those jubilant crowds did not know but could have learned from books: that the plague bacillus never dies or disappears for good; that it can lie dormant for years and years in furniture and linen-chests; that it bides its time in bedrooms, cellars, trunks, and bookshelves; and that perhaps the day would come when, for the bane and the enlightening of men, it would rouse up its rats again and send them forth to die in a happy city.\" eeee'"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_dest[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tokenizer\n",
+    "\n",
+    "Neural Networks cannot work directly on text-data. We use a two-step process to convert text into numbers that can be used in a neural network. The first step is to convert text-words into so-called integer-tokens. The second step is to convert integer-tokens into vectors of floating-point numbers using a so-called embedding-layer. See Tutorial #20 for a more detailed explanation.\n",
+    "\n",
+    "Set the maximum number of words in our vocabulary. This means that we will only use e.g. the 10000 most frequent words in the data-set. We use the same number for both the source and destination languages, but these could be different."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_words = 10000"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need a few more functions than provided by Keras' Tokenizer-class so we wrap it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class TokenizerWrap(Tokenizer):\n",
+    "    \"\"\"Wrap the Tokenizer-class from Keras with more functionality.\"\"\"\n",
+    "    \n",
+    "    def __init__(self, texts, padding,\n",
+    "                 reverse=False, num_words=None):\n",
+    "        \"\"\"\n",
+    "        :param texts: List of strings. This is the data-set.\n",
+    "        :param padding: Either 'post' or 'pre' padding.\n",
+    "        :param reverse: Boolean whether to reverse token-lists.\n",
+    "        :param num_words: Max number of words to use.\n",
+    "        \"\"\"\n",
+    "\n",
+    "        Tokenizer.__init__(self, num_words=num_words)\n",
+    "\n",
+    "        # Create the vocabulary from the texts.\n",
+    "        self.fit_on_texts(texts)\n",
+    "\n",
+    "        # Create inverse lookup from integer-tokens to words.\n",
+    "        self.index_to_word = dict(zip(self.word_index.values(),\n",
+    "                                      self.word_index.keys()))\n",
+    "\n",
+    "        # Convert all texts to lists of integer-tokens.\n",
+    "        # Note that the sequences may have different lengths.\n",
+    "        self.tokens = self.texts_to_sequences(texts)\n",
+    "\n",
+    "        if reverse:\n",
+    "            # Reverse the token-sequences.\n",
+    "            self.tokens = [list(reversed(x)) for x in self.tokens]\n",
+    "        \n",
+    "            # Sequences that are too long should now be truncated\n",
+    "            # at the beginning, which corresponds to the end of\n",
+    "            # the original sequences.\n",
+    "            truncating = 'pre'\n",
+    "        else:\n",
+    "            # Sequences that are too long should be truncated\n",
+    "            # at the end.\n",
+    "            truncating = 'post'\n",
+    "\n",
+    "        # The number of integer-tokens in each sequence.\n",
+    "        self.num_tokens = [len(x) for x in self.tokens]\n",
+    "\n",
+    "        # Max number of tokens to use in all sequences.\n",
+    "        # We will pad / truncate all sequences to this length.\n",
+    "        # This is a compromise so we save a lot of memory and\n",
+    "        # only have to truncate maybe 5% of all the sequences.\n",
+    "        self.max_tokens = np.mean(self.num_tokens) \\\n",
+    "                          + 2 * np.std(self.num_tokens)\n",
+    "        self.max_tokens = int(self.max_tokens)\n",
+    "\n",
+    "        # Pad / truncate all token-sequences to the given length.\n",
+    "        # This creates a 2-dim numpy matrix that is easier to use.\n",
+    "        self.tokens_padded = pad_sequences(self.tokens,\n",
+    "                                           maxlen=self.max_tokens,\n",
+    "                                           padding=padding,\n",
+    "                                           truncating=truncating)\n",
+    "\n",
+    "    def token_to_word(self, token):\n",
+    "        \"\"\"Lookup a single word from an integer-token.\"\"\"\n",
+    "\n",
+    "        word = \" \" if token == 0 else self.index_to_word[token]\n",
+    "        return word \n",
+    "\n",
+    "    def tokens_to_string(self, tokens):\n",
+    "        \"\"\"Convert a list of integer-tokens to a string.\"\"\"\n",
+    "\n",
+    "        # Create a list of the individual words.\n",
+    "        words = [self.index_to_word[token]\n",
+    "                 for token in tokens\n",
+    "                 if token != 0]\n",
+    "        \n",
+    "        # Concatenate the words to a single string\n",
+    "        # with space between all the words.\n",
+    "        text = \" \".join(words)\n",
+    "\n",
+    "        return text\n",
+    "    \n",
+    "    def text_to_tokens(self, text, reverse=False, padding=False):\n",
+    "        \"\"\"\n",
+    "        Convert a single text-string to tokens with optional\n",
+    "        reversal and padding.\n",
+    "        \"\"\"\n",
+    "\n",
+    "        # Convert to tokens. Note that we assume there is only\n",
+    "        # a single text-string so we wrap it in a list.\n",
+    "        tokens = self.texts_to_sequences([text])\n",
+    "        tokens = np.array(tokens)\n",
+    "\n",
+    "        if reverse:\n",
+    "            # Reverse the tokens.\n",
+    "            tokens = np.flip(tokens, axis=1)\n",
+    "\n",
+    "            # Sequences that are too long should now be truncated\n",
+    "            # at the beginning, which corresponds to the end of\n",
+    "            # the original sequences.\n",
+    "            truncating = 'pre'\n",
+    "        else:\n",
+    "            # Sequences that are too long should be truncated\n",
+    "            # at the end.\n",
+    "            truncating = 'post'\n",
+    "\n",
+    "        if padding:\n",
+    "            # Pad and truncate sequences to the given length.\n",
+    "            tokens = pad_sequences(tokens,\n",
+    "                                   maxlen=self.max_tokens,\n",
+    "                                   padding='pre',\n",
+    "                                   truncating=truncating)\n",
+    "\n",
+    "        return tokens"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now create a tokenizer for the source-language. Note that we pad zeros at the beginning ('pre') of the sequences. We also reverse the sequences of tokens because the research literature suggests that this might improve performance, because the last words seen by the encoder match the first words produced by the decoder, so short-term dependencies are supposedly modelled more accurately."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 2min 17s, sys: 608 ms, total: 2min 17s\n",
+      "Wall time: 2min 17s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "tokenizer_src = TokenizerWrap(texts=data_src,\n",
+    "                              padding='pre',\n",
+    "                              reverse=True,\n",
+    "                              num_words=num_words)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now create the tokenizer for the destination language. We need a tokenizer for both the source- and destination-languages because their vocabularies are different. Note that this tokenizer does not reverse the sequences and it pads zeros at the end ('post') of the arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 1min 42s, sys: 492 ms, total: 1min 42s\n",
+      "Wall time: 1min 42s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "tokenizer_dest = TokenizerWrap(texts=data_dest,\n",
+    "                               padding='post',\n",
+    "                               reverse=False,\n",
+    "                               num_words=num_words)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Define convenience variables for the padded token sequences. These are just 2-dimensional numpy arrays of integer-tokens.\n",
+    "\n",
+    "Note that the sequence-lengths are different for the source and destination languages. This is because texts with the same meaning may have different numbers of words in the two languages. \n",
+    "\n",
+    "Furthermore, we have made a compromise when tokenizing the original texts in order to save a lot of memory. This means we only truncate about 5% of the texts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1968800, 47)\n",
+      "(1968800, 55)\n"
+     ]
+    }
+   ],
+   "source": [
+    "tokens_src = tokenizer_src.tokens_padded\n",
+    "tokens_dest = tokenizer_dest.tokens_padded\n",
+    "print(tokens_src.shape)\n",
+    "print(tokens_dest.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the integer-token used to mark the beginning of a text in the destination-language."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_start = tokenizer_dest.word_index[mark_start.strip()]\n",
+    "token_start"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the integer-token used to mark the end of a text in the destination-language."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_end = tokenizer_dest.word_index[mark_end.strip()]\n",
+    "token_end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example of Token Sequences"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the output of the tokenizer. Note how it is padded with zeros at the beginning (pre-padding)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0, 3069,\n",
+       "       3374,   43,    7, 1386,  108, 1995,    7,  178,    9,    3,  302,\n",
+       "         19, 2076,    8,   20,   39,  285,  499,   69,  136,    5,  166,\n",
+       "         24,   10,   13], dtype=int32)"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokens_src[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can reconstruct the original text by converting each integer-token back to its corresponding word:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'naturkatastrofer forfærdelige meget af ramt været medlemslandene af del en i borgerne har gengæld til ikke sig problem 2000 år store det se kan de som'"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer_src.tokens_to_string(tokens_src[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This text is actually reversed, as can be seen when compared to the original text from the data-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Som De kan se, indfandt det store \"år 2000-problem\" sig ikke. Til gengæld har borgerne i en del af medlemslandene været ramt af meget forfærdelige naturkatastrofer.'"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_src[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the sequence of integer-tokens for the corresponding text in the destination-language. Note how it is padded with zeros at the end (post-padding)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   2,  404,   19,   43,   26,   20,  618,    1, 1451,    5, 9785,\n",
+       "        174,    1,   81,    7,    9,  214,    4,   67, 2200,    9, 1596,\n",
+       "          4,  892, 1762,    8, 1480,  107, 5494,    3,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0],\n",
+       "      dtype=int32)"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokens_dest[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can reconstruct the original text by converting each integer-token back to its corresponding word:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'ssss although as you will have seen the failed to materialise still the people in a number of countries suffered a series of natural disasters that truly were dreadful eeee'"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer_dest.tokens_to_string(tokens_dest[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Compare this to the original text from the data-set, which is almost identical except for punctuation marks and a few words such as \"dreaded millennium bug\". This is because we only use a vocabulary of the 10000 most frequent words in the data-set and those 3 words were apparently not used frequently enough to be included in the vocabulary, so they are merely skipped."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"ssss Although, as you will have seen, the dreaded 'millennium bug' failed to materialise, still the people in a number of countries suffered a series of natural disasters that truly were dreadful. eeee\""
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_dest[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Training Data\n",
+    "\n",
+    "Now that the data-set has been converted to sequences of integer-tokens that are padded and truncated and saved in numpy arrays, we can easily prepare the data for use in training the neural network.\n",
+    "\n",
+    "The input to the encoder is merely the numpy array for the padded and truncated sequences of integer-tokens produced by the tokenizer:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encoder_input_data = tokens_src"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The input and output data for the decoder is identical, except shifted one time-step. We can use the same numpy array to save memory by slicing it, which merely creates different 'views' of the same data in memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1968800, 54)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decoder_input_data = tokens_dest[:, :-1]\n",
+    "decoder_input_data.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1968800, 54)"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decoder_output_data = tokens_dest[:, 1:]\n",
+    "decoder_output_data.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, these token-sequences are identical except they are shifted one time-step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "idx = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   2,  404,   19,   43,   26,   20,  618,    1, 1451,    5, 9785,\n",
+       "        174,    1,   81,    7,    9,  214,    4,   67, 2200,    9, 1596,\n",
+       "          4,  892, 1762,    8, 1480,  107, 5494,    3,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0],\n",
+       "      dtype=int32)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decoder_input_data[idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 404,   19,   43,   26,   20,  618,    1, 1451,    5, 9785,  174,\n",
+       "          1,   81,    7,    9,  214,    4,   67, 2200,    9, 1596,    4,\n",
+       "        892, 1762,    8, 1480,  107, 5494,    3,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
+       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0],\n",
+       "      dtype=int32)"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "decoder_output_data[idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we use the tokenizer to convert these sequences back into text, we see that they are identical except for the first word which is 'ssss' that marks the beginning of a text."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'ssss although as you will have seen the failed to materialise still the people in a number of countries suffered a series of natural disasters that truly were dreadful eeee'"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer_dest.tokens_to_string(decoder_input_data[idx])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'although as you will have seen the failed to materialise still the people in a number of countries suffered a series of natural disasters that truly were dreadful eeee'"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer_dest.tokens_to_string(decoder_output_data[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create the Neural Network\n",
+    "\n",
+    "### Create the Encoder\n",
+    "\n",
+    "First we create the encoder-part of the neural network which maps a sequence of integer-tokens to a \"thought vector\". We will use the so-called functional API of Keras for this, where we first create the objects for all the layers of the neural network and then we connect them later, this allows for more flexibility than the so-called sequential API in Keras, which is useful when experimenting with more complicated architectures and ways of connecting the encoder and decoder."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the input for the encoder which takes batches of integer-token sequences. The `None` indicates that the sequences can have arbitrary length."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encoder_input = Input(shape=(None, ), name='encoder_input')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the length of the vectors output by the embedding-layer, which maps integer-tokens to vectors of values roughly between -1 and 1, so that words that have similar semantic meanings are mapped to vectors that are similar. See Tutorial #20 for a more detailed explanation of this."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embedding_size = 128"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the embedding-layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encoder_embedding = Embedding(input_dim=num_words,\n",
+    "                              output_dim=embedding_size,\n",
+    "                              name='encoder_embedding')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the size of the internal states of the Gated Recurrent Units (GRU). The same size is used in both the encoder and decoder."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "state_size = 512"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This creates the 3 GRU layers that will map from a sequence of embedding-vectors to a single \"thought vector\" which summarizes the contents of the input-text. Note that the last GRU-layer does not return a sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "encoder_gru1 = GRU(state_size, name='encoder_gru1',\n",
+    "                   return_sequences=True)\n",
+    "encoder_gru2 = GRU(state_size, name='encoder_gru2',\n",
+    "                   return_sequences=True)\n",
+    "encoder_gru3 = GRU(state_size, name='encoder_gru3',\n",
+    "                   return_sequences=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This helper-function connects all the layers of the encoder."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def connect_encoder():\n",
+    "    # Start the neural network with its input-layer.\n",
+    "    net = encoder_input\n",
+    "    \n",
+    "    # Connect the embedding-layer.\n",
+    "    net = encoder_embedding(net)\n",
+    "\n",
+    "    # Connect all the GRU-layers.\n",
+    "    net = encoder_gru1(net)\n",
+    "    net = encoder_gru2(net)\n",
+    "    net = encoder_gru3(net)\n",
+    "\n",
+    "    # This is the output of the encoder.\n",
+    "    encoder_output = net\n",
+    "    \n",
+    "    return encoder_output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note how the encoder uses the normal output from its last GRU-layer as the \"thought vector\". Research papers often use the internal state of the encoder's last recurrent layer as the \"thought vector\". But this makes the implementation more complicated and is not necessary when using the GRU. But if you were using the LSTM instead then it is necessary to use the LSTM's internal states as the \"thought vector\" because it actually has two internal vectors, which we would need to initialize the two internal states of the decoder's LSTM units.\n",
+    "\n",
+    "We can now use this function to connect all the layers in the encoder so it can be connected to the decoder further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "encoder_output = connect_encoder()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create the Decoder\n",
+    "\n",
+    "Create the decoder-part which maps the \"thought vector\" to a sequence of integer-tokens.\n",
+    "\n",
+    "The decoder takes two inputs. First it needs the \"thought vector\" produced by the encoder which summarizes the contents of the input-text."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_initial_state = Input(shape=(state_size,),\n",
+    "                              name='decoder_initial_state')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The decoder also needs a sequence of integer-tokens as inputs. During training we will supply this with a full sequence of integer-tokens e.g. corresponding to the text \"ssss once upon a time eeee\". \n",
+    "\n",
+    "During inference when we are translating new input-texts, we will start by feeding a sequence with just one integer-token for \"ssss\" which marks the beginning of a text, and combined with the \"thought vector\" from the encoder, the decoder will hopefully be able to produce the correct next word e.g. \"once\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_input = Input(shape=(None, ), name='decoder_input')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the embedding-layer which converts integer-tokens to vectors of real-valued numbers roughly between -1 and 1. Note that we have different embedding-layers for the encoder and decoder because we have two different vocabularies and two different tokenizers for the source and destination languages."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_embedding = Embedding(input_dim=num_words,\n",
+    "                              output_dim=embedding_size,\n",
+    "                              name='decoder_embedding')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This creates the 3 GRU layers of the decoder. Note that they all return sequences because we ultimately want to output a sequence of integer-tokens that can be converted into a text-sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_gru1 = GRU(state_size, name='decoder_gru1',\n",
+    "                   return_sequences=True)\n",
+    "decoder_gru2 = GRU(state_size, name='decoder_gru2',\n",
+    "                   return_sequences=True)\n",
+    "decoder_gru3 = GRU(state_size, name='decoder_gru3',\n",
+    "                   return_sequences=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The GRU layers output a tensor with shape `[batch_size, sequence_length, state_size]`, where each \"word\" is encoded as a vector of length `state_size`. We need to convert this into sequences of integer-tokens that can be interpreted as words from our vocabulary.\n",
+    "\n",
+    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token.\n",
+    "\n",
+    "Note that the activation-function is set to `linear` instead of `softmax` as we would normally use for one-hot encoded outputs, because there is apparently a bug in Keras so we need to make our own loss-function, as described in detail further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_dense = Dense(num_words,\n",
+    "                      activation='linear',\n",
+    "                      name='decoder_output')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The decoder is built using the functional API of Keras, which allows more flexibility in connecting the layers e.g. to route different inputs to the decoder. This is useful because we have to connect the decoder directly to the encoder, but we will also connect the decoder to another input so we can run it separately.\n",
+    "\n",
+    "This function connects all the layers of the decoder to some input of the initial-state values for the GRU layers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def connect_decoder(initial_state):\n",
+    "    # Start the decoder-network with its input-layer.\n",
+    "    net = decoder_input\n",
+    "\n",
+    "    # Connect the embedding-layer.\n",
+    "    net = decoder_embedding(net)\n",
+    "    \n",
+    "    # Connect all the GRU-layers.\n",
+    "    net = decoder_gru1(net, initial_state=initial_state)\n",
+    "    net = decoder_gru2(net, initial_state=initial_state)\n",
+    "    net = decoder_gru3(net, initial_state=initial_state)\n",
+    "\n",
+    "    # Connect the final dense layer that converts to\n",
+    "    # one-hot encoded arrays.\n",
+    "    decoder_output = decoder_dense(net)\n",
+    "    \n",
+    "    return decoder_output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Connect and Create the Models\n",
+    "\n",
+    "We can now connect the encoder and decoder in different ways.\n",
+    "\n",
+    "First we connect the encoder directly to the decoder so it is one whole model that can be trained end-to-end. This means the initial-state of the decoder's GRU units are set to the output of the encoder."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_output = connect_decoder(initial_state=encoder_output)\n",
+    "\n",
+    "model_train = Model(inputs=[encoder_input, decoder_input],\n",
+    "                    outputs=[decoder_output])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we create a model for just the encoder alone. This is useful for mapping a sequence of integer-tokens to a \"thought-vector\" summarizing its contents."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_encoder = Model(inputs=[encoder_input],\n",
+    "                      outputs=[encoder_output])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we create a model for just the decoder alone. This allows us to directly input the initial state for the decoder's GRU units."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_output = connect_decoder(initial_state=decoder_initial_state)\n",
+    "\n",
+    "model_decoder = Model(inputs=[decoder_input, decoder_initial_state],\n",
+    "                      outputs=[decoder_output])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that all these models use the same weights and variables of the encoder and decoder. We are merely changing how they are connected. So once the entire model has been trained, we can run the encoder and decoder models separately with the trained weights."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Loss Function\n",
+    "\n",
+    "The output of the decoder is a sequence of one-hot encoded arrays. In order to train the decoder we need to supply the one-hot encoded arrays that we desire to see on the decoder's output, and then use a loss-function like cross-entropy to train the decoder to produce this desired output.\n",
+    "\n",
+    "However, our data-set contains integer-tokens instead of one-hot encoded arrays. Each one-hot encoded array has 10000 elements so it would be extremely wasteful to convert the entire data-set to one-hot encoded arrays.\n",
+    "\n",
+    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays. Unfortunately, there seems to be a bug in Keras when using this with Recurrent Neural Networks, so the following does not work:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# model_train.compile(optimizer=optimizer,\n",
+    "#                     loss='sparse_categorical_crossentropy')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The decoder outputs a 3-rank tensor with shape `[batch_size, sequence_length, num_words]` which contains batches of sequences of one-hot encoded arrays of length `num_words`. We will compare this to a 2-rank tensor with shape `[batch_size, sequence_length]` containing sequences of integer-tokens.\n",
+    "\n",
+    "This comparison is done with a sparse-cross-entropy function directly from TensorFlow. There are several things to note here.\n",
+    "\n",
+    "Firstly, the loss-function calculates the softmax internally to improve numerical stability - this is why we used a linear activation function in the last dense-layer of the decoder-network above.\n",
+    "\n",
+    "Secondly, the loss-function from TensorFlow will output a 2-rank tensor of shape `[batch_size, sequence_length]` given these inputs. But this must ultimately be reduced to a single scalar-value whose gradient can be derived by TensorFlow so it can be optimized using gradient descent. Keras supports some weighting of loss-values across the batch but the semantics are unclear so to be sure that we calculate the loss-function across the entire batch and across the entire sequences, we manually calculate the loss average."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sparse_cross_entropy(y_true, y_pred):\n",
+    "    \"\"\"\n",
+    "    Calculate the cross-entropy loss between y_true and y_pred.\n",
+    "    \n",
+    "    y_true is a 2-rank tensor with the desired output.\n",
+    "    The shape is [batch_size, sequence_length] and it\n",
+    "    contains sequences of integer-tokens.\n",
+    "\n",
+    "    y_pred is the decoder's output which is a 3-rank tensor\n",
+    "    with shape [batch_size, sequence_length, num_words]\n",
+    "    so that for each sequence in the batch there is a one-hot\n",
+    "    encoded array of length num_words.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Calculate the loss. This outputs a\n",
+    "    # 2-rank tensor of shape [batch_size, sequence_length]\n",
+    "    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y_true,\n",
+    "                                                          logits=y_pred)\n",
+    "\n",
+    "    # Keras may reduce this across the first axis (the batch)\n",
+    "    # but the semantics are unclear, so to be sure we use\n",
+    "    # the loss across the entire 2-rank tensor, we reduce it\n",
+    "    # to a single scalar with the mean function.\n",
+    "    loss_mean = tf.reduce_mean(loss)\n",
+    "\n",
+    "    return loss_mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Compile the Training Model\n",
+    "\n",
+    "We have used the Adam optimizer in many of the previous tutorials, but it seems to diverge in some of these experiments with Recurrent Neural Networks. RMSprop seems to work much better for these."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "optimizer = RMSprop(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There seems to be another bug in Keras so it cannot automatically deduce the correct shape of the decoder's output data. We therefore need to manually create a placeholder variable for the decoder's output. The shape is set to `(None, None)` which means the batch can have an arbitrary number of sequences, which can have an arbitrary number of integer-tokens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_target = tf.placeholder(dtype='int32', shape=(None, None))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now compile the model using our custom loss-function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "model_train.compile(optimizer=optimizer,\n",
+    "                    loss=sparse_cross_entropy,\n",
+    "                    target_tensors=[decoder_target])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Callback Functions\n",
+    "\n",
+    "During training we want to save checkpoints and log the progress to TensorBoard so we create the appropriate callbacks for Keras.\n",
+    "\n",
+    "This is the callback for writing checkpoints during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path_checkpoint = '21_checkpoint.keras'\n",
+    "callback_checkpoint = ModelCheckpoint(filepath=path_checkpoint,\n",
+    "                                      monitor='val_loss',\n",
+    "                                      verbose=1,\n",
+    "                                      save_weights_only=True,\n",
+    "                                      save_best_only=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the callback for stopping the optimization when performance worsens on the validation-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callback_early_stopping = EarlyStopping(monitor='val_loss',\n",
+    "                                        patience=3, verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the callback for writing the TensorBoard log during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callback_tensorboard = TensorBoard(log_dir='./21_logs/',\n",
+    "                                   histogram_freq=0,\n",
+    "                                   write_graph=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callbacks = [callback_early_stopping,\n",
+    "             callback_checkpoint,\n",
+    "             callback_tensorboard]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load Checkpoint\n",
+    "\n",
+    "You can reload the last saved checkpoint so you don't have to train the model every time you want to use it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    model_train.load_weights(path_checkpoint)\n",
+    "except Exception as error:\n",
+    "    print(\"Error trying to load checkpoint.\")\n",
+    "    print(error)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Train the Model\n",
+    "\n",
+    "We wrap the data in named dicts so we are sure the data is assigned correctly to the inputs and outputs of the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_data = \\\n",
+    "{\n",
+    "    'encoder_input': encoder_input_data,\n",
+    "    'decoder_input': decoder_input_data\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_data = \\\n",
+    "{\n",
+    "    'decoder_output': decoder_output_data\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We want a validation-set of 10000 sequences but Keras needs this number as a fraction."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0050792360828931325"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "validation_split = 10000 / len(encoder_input_data)\n",
+    "validation_split"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can train the model. One epoch of training took about 1 hour on a GTX 1070 GPU. You probably need to run 10 epochs or more during training. After 10 epochs the loss was about 1.10 on the training-set and about 1.15 on the validation-set.\n",
+    "\n",
+    "Note the strange batch-size of 640 (512 + 128) which was chosen because it kept the GPU running at nearly 100% while being within the memory limits of 8GB for this GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "model_train.fit(x=x_data,\n",
+    "                y=y_data,\n",
+    "                batch_size=640,\n",
+    "                epochs=10,\n",
+    "                validation_split=validation_split,\n",
+    "                callbacks=callbacks)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Translate Texts\n",
+    "\n",
+    "This function translates a text from the source-language to the destination-language and optionally prints a true translation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def translate(input_text, true_output_text=None):\n",
+    "    \"\"\"Translate a single text-string.\"\"\"\n",
+    "\n",
+    "    # Convert the input-text to integer-tokens.\n",
+    "    # Note the sequence of tokens has to be reversed.\n",
+    "    # Padding is probably not necessary.\n",
+    "    input_tokens = tokenizer_src.text_to_tokens(text=input_text,\n",
+    "                                                reverse=True,\n",
+    "                                                padding=True)\n",
+    "    \n",
+    "    # Get the output of the encoder's GRU which will be\n",
+    "    # used as the initial state in the decoder's GRU.\n",
+    "    # This could also have been the encoder's final state\n",
+    "    # but that is really only necessary if the encoder\n",
+    "    # and decoder use the LSTM instead of GRU because\n",
+    "    # the LSTM has two internal states.\n",
+    "    initial_state = model_encoder.predict(input_tokens)\n",
+    "\n",
+    "    # Max number of tokens / words in the output sequence.\n",
+    "    max_tokens = tokenizer_dest.max_tokens\n",
+    "\n",
+    "    # Pre-allocate the 2-dim array used as input to the decoder.\n",
+    "    # This holds just a single sequence of integer-tokens,\n",
+    "    # but the decoder-model expects a batch of sequences.\n",
+    "    shape = (1, max_tokens)\n",
+    "    decoder_input_data = np.zeros(shape=shape, dtype=np.int)\n",
+    "\n",
+    "    # The first input-token is the special start-token for 'ssss '.\n",
+    "    token_int = token_start\n",
+    "\n",
+    "    # Initialize an empty output-text.\n",
+    "    output_text = ''\n",
+    "\n",
+    "    # Initialize the number of tokens we have processed.\n",
+    "    count_tokens = 0\n",
+    "\n",
+    "    # While we haven't sampled the special end-token for ' eeee'\n",
+    "    # and we haven't processed the max number of tokens.\n",
+    "    while token_int != token_end and count_tokens < max_tokens:\n",
+    "        # Update the input-sequence to the decoder\n",
+    "        # with the last token that was sampled.\n",
+    "        # In the first iteration this will set the\n",
+    "        # first element to the start-token.\n",
+    "        decoder_input_data[0, count_tokens] = token_int\n",
+    "\n",
+    "        # Wrap the input-data in a dict for clarity and safety,\n",
+    "        # so we are sure we input the data in the right order.\n",
+    "        x_data = \\\n",
+    "        {\n",
+    "            'decoder_initial_state': initial_state,\n",
+    "            'decoder_input': decoder_input_data\n",
+    "        }\n",
+    "\n",
+    "        # Note that we input the entire sequence of tokens\n",
+    "        # to the decoder. This wastes a lot of computation\n",
+    "        # because we are only interested in the last input\n",
+    "        # and output. We could modify the code to return\n",
+    "        # the GRU-states when calling predict() and then\n",
+    "        # feeding these GRU-states as well the next time\n",
+    "        # we call predict(), but it would make the code\n",
+    "        # much more complicated.\n",
+    "\n",
+    "        # Input this data to the decoder and get the predicted output.\n",
+    "        decoder_output = model_decoder.predict(x_data)\n",
+    "\n",
+    "        # Get the last predicted token as a one-hot encoded array.\n",
+    "        token_onehot = decoder_output[0, count_tokens, :]\n",
+    "        \n",
+    "        # Convert to an integer-token.\n",
+    "        token_int = np.argmax(token_onehot)\n",
+    "\n",
+    "        # Lookup the word corresponding to this integer-token.\n",
+    "        sampled_word = tokenizer_dest.token_to_word(token_int)\n",
+    "\n",
+    "        # Append the word to the output-text.\n",
+    "        output_text += \" \" + sampled_word\n",
+    "\n",
+    "        # Increment the token-counter.\n",
+    "        count_tokens += 1\n",
+    "\n",
+    "    # Sequence of tokens output by the decoder.\n",
+    "    output_tokens = decoder_input_data[0]\n",
+    "    \n",
+    "    # Print the input-text.\n",
+    "    print(\"Input text:\")\n",
+    "    print(input_text)\n",
+    "    print()\n",
+    "\n",
+    "    # Print the translated output-text.\n",
+    "    print(\"Translated text:\")\n",
+    "    print(output_text)\n",
+    "    print()\n",
+    "\n",
+    "    # Optionally print the true translated text.\n",
+    "    if true_output_text is not None:\n",
+    "        print(\"True output text:\")\n",
+    "        print(true_output_text)\n",
+    "        print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Examples\n",
+    "\n",
+    "Translate a text from the training-data. This translation is quite good. Note how it is not identical to the translation from the training-data, but the actual meaning is similar."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.\n",
+      "\n",
+      "Translated text:\n",
+      " you have expressed a wish for a debate on this matter during the part session eeee\n",
+      "\n",
+      "True output text:\n",
+      "ssss You have requested a debate on this subject in the course of the next few days, during this part-session. eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "idx = 3\n",
+    "translate(input_text=data_src[idx],\n",
+    "          true_output_text=data_dest[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here is another example which is also a reasonable translation, although it has incorrectly translated the natural disasters. Note \"countries of the European Union\" has instead been translated as \"member states\" which are synonyms in this context."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.\n",
+      "\n",
+      "Translated text:\n",
+      " in the meantime i also asked for a minute's silence on the memory of victims of the atrocities that have been committed in the member states eeee\n",
+      "\n",
+      "True output text:\n",
+      "ssss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "idx = 4\n",
+    "translate(input_text=data_src[idx],\n",
+    "          true_output_text=data_dest[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this example we join two texts from the training-set. The model first sends this combined text through the encoder, which produces a \"thought-vector\" that seems to summarize both texts reasonably well so the decoder can produce a reasonable translation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.\n",
+      "\n",
+      "Translated text:\n",
+      " you have expressed a wish for a vote on this question during the vote on thursday and in the end i would also like to ask you to pay tribute to the memory of a tragedy in the case of the victims of the various member states eeee\n",
+      "\n",
+      "True output text:\n",
+      "ssss You have requested a debate on this subject in the course of the next few days, during this part-session. eeeessss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "idx = 3\n",
+    "translate(input_text=data_src[idx] + data_src[idx+1],\n",
+    "          true_output_text=data_dest[idx] + data_dest[idx+1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we reverse the order of these two texts then the meaning is not quite so clear for the latter text."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.\n",
+      "\n",
+      "Translated text:\n",
+      " in the meantime i would also like to ask you to remember that we have received a silence on the victims of the floods in the member states of the european union which have been particularly sensitive to this debate in the house eeee\n",
+      "\n",
+      "True output text:\n",
+      "ssss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeeessss You have requested a debate on this subject in the course of the next few days, during this part-session. eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "idx = 3\n",
+    "translate(input_text=data_src[idx+1] + data_src[idx],\n",
+    "          true_output_text=data_dest[idx+1] + data_dest[idx])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is an example I made up. It is a quite broken translation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "der var engang et land der hed Danmark\n",
+      "\n",
+      "Translated text:\n",
+      " there was a country that denmark was once again eeee\n",
+      "\n",
+      "True output text:\n",
+      "Once there was a country named Denmark\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "translate(input_text=\"der var engang et land der hed Danmark\",\n",
+    "          true_output_text='Once there was a country named Denmark')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is another example I made up. This is a better translation even though it is perhaps a more complicated text."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "Idag kan man læse i avisen at Danmark er blevet fornuftigt\n",
+      "\n",
+      "Translated text:\n",
+      " can you read in the newspapers that denmark has been sensible eeee\n",
+      "\n",
+      "True output text:\n",
+      "Today you can read in the newspaper that Denmark has become sensible.\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "translate(input_text=\"Idag kan man læse i avisen at Danmark er blevet fornuftigt\",\n",
+    "          true_output_text=\"Today you can read in the newspaper that Denmark has become sensible.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a text from a Danish song. It doesn't even make much sense in Danish. However the translation is probably so broken because several of the words are not in the vocabulary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input text:\n",
+      "Hvem spæner ud af en butik og tygger de stærkeste bolcher?\n",
+      "\n",
+      "Translated text:\n",
+      " who is by a and by the powerful eeee\n",
+      "\n",
+      "True output text:\n",
+      "Who runs out of a shop and chews the strongest bon-bons?\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "translate(input_text=\"Hvem spæner ud af en butik og tygger de stærkeste bolcher?\",\n",
+    "          true_output_text=\"Who runs out of a shop and chews the strongest bon-bons?\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed the basic idea of using two Recurrent Neural Networks in a so-called encoder/decoder model to do Machine Translation of human languages. It was demonstrated on the very large Europarl data-set from the European Union.\n",
+    "\n",
+    "The model could produce reasonable translations for some texts but not for others. It is possible that a better architecture for the neural network and more training epochs could improve performance. There are also more advanced models that are known to improve quality of the translations.\n",
+    "\n",
+    "However, it is important to note that these models do not really understand human language. The models have no knowledge of the actual meaning of the words. The models are merely very advanced function approximators that can map between sequences of integer-tokens."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Train for more than 10 epochs. Does it improve the translations?\n",
+    "* Increase the size of the vocabulary. Does it improve the translations? Would it make sense to have different sizes for the vocabularies of the source and destination languages?\n",
+    "* Find another data-set and use it together with Europarl.\n",
+    "* Change the architectures of the neural network, for example change the state-size for the GRU layers, the number of GRU layers, the embedding-size, etc. Does it improve the translations?\n",
+    "* Use hyper-parameter optimization from Tutorial #19 to automatically find the best hyper-parameters.\n",
+    "* When translating texts, instead of using `np.argmax()` to sample the next integer-token, could you sample the decoder's output as if it was a probability distribution instead? Note that the decoder's output is not softmax-limited so you have to do that first to turn it into a probability-distribution.\n",
+    "* Can you generate multiple sequences by doing this sampling? Can you find a way to select the best of these different sequences?\n",
+    "* Disable the reversal of words for the source-language. Does it improve the translations?\n",
+    "* What is a Bi-Directional GRU and can you use it here?\n",
+    "* We use the **output** of the encoder's GRU as the initial state of the decoder's GRU. The research literature often uses an LSTM instead of the GRU, so they used the encoder's **state** instead of its output as the initial state of the decoder. Can you rewrite this code to use the encoder's state as the decoder's initial state? Is there a reason to do this, or is the encoder's output sufficient to use as the decoder's initial state?\n",
+    "* Is it possible to connect multiple encoders and decoders in a single neural network, so that you can train it on different languages and allow for direct translation e.g. from Danish to Polish, German and French?\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2018 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/README.md b/README.md
index 277cf5a..4c51279 100644
--- a/README.md
+++ b/README.md
@@ -59,6 +59,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 20. Natural Language Processing ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
 
+21. Machine Translation ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/europarl.py b/europarl.py
new file mode 100644
index 0000000..de0852b
--- /dev/null
+++ b/europarl.py
@@ -0,0 +1,136 @@
+########################################################################
+#
+# Functions for downloading the Europarl data-set from the internet
+# and loading it into memory. This data-set is used for translation
+# between English and most European languages.
+#
+# http://www.statmt.org/europarl/
+#
+# Implemented in Python 3.6
+#
+# Usage:
+# 1) Set the variable data_dir with the desired storage directory.
+# 2) Determine the language-code to use e.g. "da" for Danish.
+# 3) Call maybe_download_and_extract() to download the data-set
+#    if it is not already located in the given data_dir.
+# 4) Call load_data(english=True) and load_data(english=False)
+#    to load the two data-files.
+# 5) Use the returned data in your own program.
+#
+# Format:
+# The Europarl data-set contains millions of text-pairs between English
+# and most European languages. The data is stored in two text-files.
+# The data is returned as lists of strings by the load_data() function.
+#
+# The list of currently supported languages and their codes are as follows:
+#
+# bg - Bulgarian
+# cs - Czech
+# da - Danish
+# de - German
+# el - Greek
+# es - Spanish
+# et - Estonian
+# fi - Finnish
+# fr - French
+# hu - Hungarian
+# it - Italian
+# lt - Lithuanian
+# lv - Latvian
+# nl - Dutch
+# pl - Polish
+# pt - Portuguese
+# ro - Romanian
+# sk - Slovak
+# sl - Slovene
+# sv - Swedish
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2018 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import os
+import download
+
+########################################################################
+
+# Directory where you want to download and save the data-set.
+# Set this before you start calling any of the functions below.
+data_dir = "data/europarl/"
+
+# Base-URL for the data-sets on the internet.
+data_url = "http://www.statmt.org/europarl/v7/"
+
+
+########################################################################
+# Public functions that you may call to download the data-set from
+# the internet and load the data into memory.
+
+
+def maybe_download_and_extract(language_code="da"):
+    """
+    Download and extract the Europarl data-set if the data-file doesn't
+    already exist in data_dir. The data-set is for translating between
+    English and the given language-code (e.g. 'da' for Danish, see the
+    list of available language-codes above).
+    """
+
+    # Create the full URL for the file with this data-set.
+    url = data_url + language_code + "-en.tgz"
+
+    download.maybe_download_and_extract(url=url, download_dir=data_dir)
+
+
+def load_data(english=True, language_code="da", start="", end=""):
+    """
+    Load the data-file for either the English-language texts or
+    for the other language (e.g. "da" for Danish).
+
+    All lines of the data-file are returned as a list of strings.
+
+    :param english:
+      Boolean whether to load the data-file for
+      English (True) or the other language (False).
+
+    :param language_code:
+      Two-char code for the other language e.g. "da" for Danish.
+      See list of available codes above.
+
+    :param start:
+      Prepend each line with this text e.g. "ssss " to indicate start of line.
+
+    :param end:
+      Append each line with this text e.g. " eeee" to indicate end of line.
+
+    :return:
+      List of strings with all the lines of the data-file.
+    """
+
+    if english:
+        # Load the English data.
+        filename = "europarl-v7.{0}-en.en".format(language_code)
+    else:
+        # Load the other language.
+        filename = "europarl-v7.{0}-en.{0}".format(language_code)
+
+    # Full path for the data-file.
+    path = os.path.join(data_dir, filename)
+
+    # Open and read all the contents of the data-file.
+    with open(path, encoding="utf-8") as file:
+        # Read the line from file, strip leading and trailing whitespace,
+        # prepend the start-text and append the end-text.
+        texts = [start + line.strip() + end for line in file]
+
+    return texts
+
+
+########################################################################

From 04acc34173a4536e4e03ff85af9347b4aa56f154 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 15 Mar 2018 17:57:33 +0100
Subject: [PATCH 38/61] Added Tutorial 21

---
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 images/21_machine_translation_flowchart.svg | 4475 +++++++++++++++++++
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From 26761865021a2631a58403390e0ae78c43dc321c Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 17 Mar 2018 12:16:46 +0100
Subject: [PATCH 39/61] Added Tutorial 22

---
 22_Image_Captioning.ipynb                | 2460 +++++++++++++
 coco.py                                  |  205 ++
 images/22_image_captioning_flowchart.png |  Bin 0 -> 322911 bytes
 images/22_image_captioning_flowchart.svg | 4209 ++++++++++++++++++++++
 4 files changed, 6874 insertions(+)
 create mode 100644 22_Image_Captioning.ipynb
 create mode 100644 coco.py
 create mode 100644 images/22_image_captioning_flowchart.png
 create mode 100644 images/22_image_captioning_flowchart.svg

diff --git a/22_Image_Captioning.ipynb b/22_Image_Captioning.ipynb
new file mode 100644
index 0000000..28eaf6d
--- /dev/null
+++ b/22_Image_Captioning.ipynb
@@ -0,0 +1,2460 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #22\n",
+    "# Image Captioning\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "Tutorial #21 on Machine Translation showed how to translate text from one human language to another. It worked by having two Recurrent Neural Networks (RNN), the first called an encoder and the second called a decoder. The first RNN encodes the source-text as a single vector of numbers and the second RNN decodes this vector into the destination-text. The intermediate vector between the encoder and decoder is a kind of summary of the source-text, which is sometimes called a \"thought-vector\". The reason for using this intermediate summary-vector is to understand the whole source-text before it is being translated. This also allows for the source- and destination-texts to have different lengths.\n",
+    "\n",
+    "In this tutorial we will replace the encoder with an image-recognition model similar to Transfer Learning and Fine-Tuning in Tutorials #08 and #10. The image-model recognizes what the image contains and outputs that as a vector of numbers - the \"thought-vector\" or summary-vector, which is then input to a Recurrent Neural Network that decodes this vector into text.\n",
+    "\n",
+    "This is a somewhat advanced tutorial and you should be familiar with TensorFlow, Keras, Transfer Learning and Natural Language Processing, see Tutorials #01, #03-C, #08, #10, #20, and #21."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "We will use the VGG16 model that has been pre-trained for classifying images. But instead of using the last classification layer, we will redirect the output of the previous layer. This gives us a vector with 4096 elements that summarizes the image-contents - similar to how a \"thought-vector\" summarized the contents of an input-text in Tutorial #21 on language translation. We will use this vector as the initial state of the Gated Recurrent Units (GRU). However, the internal state-size of the GRU is only 512, so we need an intermediate fully-connected (dense) layer to map the vector with 4096 elements down to a vector with only 512 elements.\n",
+    "\n",
+    "The decoder then uses this initial-state together with a start-marker \"ssss\" to begin producing output words. In the first iteration it will hopefully output the word \"big\". Then we input this word into the decoder and hopefully we get the word \"brown\" out, and so on. Finally we have generated the text \"big brown bear sitting eeee\" where \"eeee\" marks the end of the text.\n",
+    "\n",
+    "The flowchart of the algorithm is roughly:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Flowchart](images/22_image_captioning_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import os\n",
+    "from PIL import Image\n",
+    "from cache import cache"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need to import several things from Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Model  # This does not work!\n",
+    "from tensorflow.python.keras import backend as K\n",
+    "from tensorflow.python.keras.models import Model\n",
+    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.python.keras.applications import VGG16\n",
+    "from tensorflow.python.keras.optimizers import RMSprop\n",
+    "from tensorflow.python.keras.callbacks import ModelCheckpoint, TensorBoard\n",
+    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.5.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.1.2-tf'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data\n",
+    "\n",
+    "We will use the COCO data-set which contains many images with text-captions.\n",
+    "\n",
+    "http://cocodataset.org/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import coco"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can change the data-directory if you want to save the data-files somewhere else."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# coco.set_data_dir(\"data/coco/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Automatically download and extract the data-files if you don't have them already.\n",
+    "\n",
+    "**WARNING! These data-files are VERY large! The file for the training-data is 19 GB and the file for the validation-data is 816 MB! **"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading http://images.cocodataset.org/zips/train2017.zip\n",
+      "Data has apparently already been downloaded and unpacked.\n",
+      "Downloading http://images.cocodataset.org/zips/val2017.zip\n",
+      "Data has apparently already been downloaded and unpacked.\n",
+      "Downloading http://images.cocodataset.org/annotations/annotations_trainval2017.zip\n",
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "coco.maybe_download_and_extract()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the filenames and captions for the images in the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "- Data loaded from cache-file: data/coco/records_train.pkl\n"
+     ]
+    }
+   ],
+   "source": [
+    "_, filenames_train, captions_train = coco.load_records(train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Number of images in the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "118287"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_images_train = len(filenames_train)\n",
+    "num_images_train"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the filenames and captions for the images in the validation-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "- Data loaded from cache-file: data/coco/records_val.pkl\n"
+     ]
+    }
+   ],
+   "source": [
+    "_, filenames_val, captions_val = coco.load_records(train=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper-Functions for Loading and Showing Images\n",
+    "\n",
+    "This is a helper-function for loading and resizing an image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_image(path, size=None):\n",
+    "    \"\"\"\n",
+    "    Load the image from the given file-path and resize it\n",
+    "    to the given size if not None.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Load the image using PIL.\n",
+    "    img = Image.open(path)\n",
+    "\n",
+    "    # Resize image if desired.\n",
+    "    if not size is None:\n",
+    "        img = img.resize(size=size, resample=Image.LANCZOS)\n",
+    "\n",
+    "    # Convert image to numpy array.\n",
+    "    img = np.array(img)\n",
+    "\n",
+    "    # Scale image-pixels so they fall between 0.0 and 1.0\n",
+    "    img = img / 255.0\n",
+    "\n",
+    "    # Convert 2-dim gray-scale array to 3-dim RGB array.\n",
+    "    if (len(img.shape) == 2):\n",
+    "        img = np.repeat(img[:, :, np.newaxis], 3, axis=2)\n",
+    "\n",
+    "    return img"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a helper-function for showing an image from the data-set along with its captions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def show_image(idx, train):\n",
+    "    \"\"\"\n",
+    "    Load and plot an image from the training- or validation-set\n",
+    "    with the given index.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    if train:\n",
+    "        # Use an image from the training-set.\n",
+    "        dir = coco.train_dir\n",
+    "        filename = filenames_train[idx]\n",
+    "        captions = captions_train[idx]\n",
+    "    else:\n",
+    "        # Use an image from the validation-set.\n",
+    "        dir = coco.val_dir\n",
+    "        filename = filenames_val[idx]\n",
+    "        captions = captions_val[idx]\n",
+    "\n",
+    "    # Path for the image-file.\n",
+    "    path = os.path.join(dir, filename)\n",
+    "\n",
+    "    # Print the captions for this image.\n",
+    "    for caption in captions:\n",
+    "        print(caption)\n",
+    "    \n",
+    "    # Load the image and plot it.\n",
+    "    img = load_image(path)\n",
+    "    plt.imshow(img)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example Image\n",
+    "\n",
+    "Show an example image and captions from the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A giraffe eating food from the top of the tree.\n",
+      "A giraffe standing up nearby a tree \n",
+      "A giraffe mother with its baby in the forest.\n",
+      "Two giraffes standing in a tree filled area.\n",
+      "A giraffe standing next to a forest filled with trees.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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vHSajsrxw8AQvuzvPZ798hqsG9tFdPMrR0VaWb9zO7mcf5ZrN/fipgDCQXHfNK3j4oa/wyrtfz759X+fwVIaOFsPY+QoyHSL9Vq5b38pPvvtmPvS3/8xwpcjJXV9i9YocoRzBtwExDt+LMEiktCipiWOD0pZcJk/nkm4iC0Ud0Nm9gRtecSN9q9bR1dVJNtdKHHeQTnlMTo0SBAHFfIrxkTqR0XR29LFl81o6uzto7VjK+NgomWwaJyyB51OnTtrLUS8btmzcRKa9jfOnT3Hh7ClcLUYUPDJeCnyfWqWK82LCaonzZ8+R9nyG7FlEHCGkxPM8wnoNgcbThtkZidQFpJ8inc5QCPLItI/UjthZNApjHKgkZeIBSjociXThkIDEisUjdudco+NokEEBotHmnEvyLFKSSDwLpM05yVWKBKqFRCCIjcM5M4c9iXybEELhQEqNscloQ6umguAQIiFrxsZIpeY0dCEUaJPIS8IhMN815n7PNHLn3H3Aff8P9m9sSS9vrWuwU0dYdw0NrPlQkiRbM7n4beeyEblMDu0E9WqNtJ/CxOG3Dfvmrzmvr1ubaOpSeAiRfGdih1wgbST6rKNWKyO1IEgrzhzM8+535Ti8J2ImGiHO5VjaqRgdmyaSCmFc0gsrwelzF4lju2g00QxrHalUCqpV0roNlapSrwuUroP1UUJSyAeEoUUEmno9apTNYl0MBmZnZ6lUKhhjSQWaF3ef5ZZbryMa2c3YJPQMDDA0NoWuFzkzXqVMjdWd7bTlLPtP1ymVKghfUrAp1q7IkK5rNvZuYbp0HCVaePSJA5w6O0o6amN8OiRIpbAmRLg0QkaExlCKKlTDDt71/l9mfPLrnC8cJQxThGGdajVh1cY5iplO0mKS3qJHhw/fPHiW1nyOk+csTlhESpKOqvS3riGv21i3aphtW1p45PmIo6fSpAsB9fo0vnREkaDY2k1HkOGFC+dZl2/j0NFLiH7YWPUZ9XNksnUcWYSYpaU9RSAucWhngdWbUkR2Oe+6q8qv/dwdfPhX/p53vvVmZqan6O9ax/pNm3jwGw9y2y2vZvTxkKP1s/SPVyh2zeAYZt+eEq95w9v54j88RLHwMFadpxK/gvTqdogcy5atIwodVesxPlHjheeepKN7OV/7+rPsOwjl6BxtNkMqKyiZmMpEiZHJHJ+8fyet+eU88cRjqKs3k+uu4kc+k6UhPK8H30sTVxVKG4yNCDyNsSkymZCuzm5+5dd/m2/efz+vf/uPsHL9IJ29PbS3FbFOYW06IQdxgY7Odm65/Q6+8A+fwldZrtu2nXXrV9O3bAmpTJaJiWEkybtpnUWV0nSvXMHdP/42lgz0kW9pwfd9yqVp4qjO4b17qJZLyLTH0JmzPPbwg3h+QL1aIqoKjJBIk+SFpHNI6/ACDyFjTFinXgYhfYRQeIHfaLc6YcU4cAJhHEY4kAKbUN9EcnMxzoJdoFUno1eHMW6+DTfwwxiTaOdS4ozFCoFsJNab5G0OoyTJ36DB3JsuioTFW+sQrtkJzAPxwnzcQsnp22RSkUhkUki0/HZs+07xH5bsXBRuYc/XqIwFFaykR2wNzQx3E+y1L7FWzDHTZnhS4WlBxvPJZnwujM3ge95LassLwT1Jigq01kRRREpK4tiidBZrq8C8nBFHIQmvTRFWHFJP84V/KbN6o8dAdz8np0Y5ujuDkhDTirWTGJNIAbV6jO95c9dLHnLyLkipsdawrC+gXo+xnia2ikyQxVQFURyipaAa1pPGICVK+dTr9UYHaBEikZSU1pTLEZlsigce3M2m/jb+y89s55++cD+mHpFGoHyf2dhycXKSq9eu4okXjiXDzlgyI0Lufy6i2Ffgv/3+X+D5S8h3CbZc7bO0Zxt/+Mm9KD9LLayjhEUrCS4m5aWxyvLioSne89P38Obbr+Fld97Og099gTB0Sd5AJZ3Y8NQ46bYsKs5w1Y41XKg9z4kD5zCuACZCaomzAS8cPcqr33kTo4/WCTIBd29Jkb65k//16UOonA9xhLM+lclLdOV76Wyf4sfeeyMf++x/ZeOyn2DVB1Yy9OxZ8q0wOeqzpitHhzGIoI3Vmyb48hdmGL34OX7xp9/LzGyWu37mOGcPCm7cuJn9Bw7R3dNJZ3cX509dZIXyGRYXeHJ3O13+SkYnfcZKj3PwdyTXrk1zeKKCHhvkutW3MnnqIMYLmQ0jLo5McG7oEqlCgQPH9rLSrub5gwdQfYI71tzBoacfpdCaZuRSTOD5+GHEHduuI8Ry6zbHh/90N12tO9ByGlsXFHQBE4U4Mw1elnQmoFqZRpMmlarT2tHOitUbeVtHPz0rl9C1ZCmtra0Jo5QSKR1SWgI/TUtrKy97xe1MT0yyd9cRNmxaT29fJ4V8C0pL2tI5bL6FjpYubtixg01bt7N8YDleyqOzu4Nca55qtYq1fVSrVZYtW0a9WuXcyBAdrR088sD9eM5DIHBOYuKIjvZOcu05juw7QC6Vwrp5X1UhnSfwM/heCq/hFhMuccc0k93OQewcxpGQLrNYiojtAoOKbeSf3DyQ+422PJ8rE3P4kpzfzOnsALrpQplrrImcsjCsFVjhcBaMs3PJ02ZIBM46nE1cP66pqSMaHRLIBhZa/oOllf+dWNhzuqZG5ZJhCMLirJvTvJOs9LzZ6HJWHhlHXK8hrCOKYrxUGmET3bwpo8Bl9kaX2NeaZWlrz+IRYqzHxExt7oHMsXeVlKUelsmmwMu10RcIyiPTnI5LrF1V5JS7yPCRNsJoDC0F2leARQk51/nM694mYRMG0BBP1+laAhcvCOxsicCkKSlJDMyUQ8JYkc2liGNDHBusTVg5iEZ2XGBMhPaS0Qs4Dp2b5GOf+CrVWZ9YdFB3U+SigFxg6e/2Gbw2Q/2LmjCSaJUn449jI011cpbeDs1g/wxP7HX8wSOjDI0fpR4FyLiMkI44crS1hLQWMpwdlhhlmC5b2nNFQo5x8nSR7t4CqXPTSCmpG4MUEIWW2UqIM5JPf/6LbF2zHdEX88KpixRSAeVKjXQ+g6j77H7oDPd+5C/Y89xuTo3vZ2aolTddF3Lf4XNYHaCArM7wwBMX+OPf+xFMuJwfe88v83d//Wr+7islSufP84/3/Cx3vvcjvPsD7+Blm1axef1qzp2/yPhszLbtq9j74gOoaIjq8HF2vrCHjWt+lN7+HoYuzdLf1c7yrnbODB3mqrbXErXvp39NL6+Jl/KRPzzLf/vt1zJxPmLq9EFu2nEbQ0MXKYkZujsGOXn6NKfOnWJ6epqJowe5485X8OL+45hMxGtf9985ffAB4qpienacVl1kKqozVBvnM/f/K3feuJVjx/p452sDdp0+SU9bG3t2f4m1s5sYOvMsddvCjtvfR916KE+jYoEnUqTTaQbXryYKHflCmly2gBMSJxXOJCNa60Brj2wqR/+addz11rezfvMFOpe2kyqkSOe6qZenKXQuJZPr4rd+/yMIX5NvbSefz1DIZcik0gjPp5AtEkV1dLuiHlaZnp4maMlRnyyjlJdIBkhioVixbIBNmzZR7GvndXe/iS/+8+cYOn+WegjL+7ppLWqKhTS5bPJctVKJG5bm6Nkl7BmHweJscvbE2dVwuikxD+TMs+Kmu9CYxc6bQDf2b7Ql19DYm6NmKyyigUlSCPRlPkTnHFIIYidAC1QT8BfiW8NmPEfgknE6iMQVg0jK5AkxJ+98N/F9A+RKSYyxgMX3PaIoIp/PUS6Xca5x4ySJBqUlNtLUozpBKoMlnNe/AEgecg2FlClSUhJFYk4+WdjrNkNKhXOW1tYWZsszgKO9o8j48CiaNIh4QU+dWNeU9EgFIVdvSpP360wPdXC0XEKOSo4fu4h1EiWrBFo1OooGY268cLFxKKkwcYh0aYyuoLAQdlJLV5ic9igW4dqr1vHME7uJ06kkoRknrpZqNRklaO2htUYIqEch0kmcnR+lWOsSzV8ZymGRiq0SmQlUJkTVDYNrU8xegs/du4dZJ/CJsaKMrWeZFBUqNsXM6DRnRmvkii2YyFCZcqRShjoG6TyyfsjVWzrokD6nhieZtTFFP8DEdV44UuXEqeNk+ybxNdTwkM4ntlU8L6LiljAydIaP/O7v8v4f/zVKIkc+E2AkZIMMxI6O9jQ7rtvKH/3NRwlr0wws6WF5xwre8to1PPjcCeotEMV5tAtZv9wQVlNEqWF+6n1v4czsNP/yhfvZed89fO4r+9EefPwr/8S/PgX5vCLFcoxbQ/u/PsodV6+mtX07P3PXT/Az79f8xv/556xe2UladpFq04SzS1Bpj3RQp11s5szwBVZkc7zjx/4ne58u89yuv+UDb3k/zz91FOkPsTrTxfDQJZ56/FsMrBlgQkhW9C3l/MUataoh3drL6RM7mZg9i3ERYaXIpJkirdLkynnetH0HJ8uDPL7703T0esxMt7F5YDuZOOL4sc9w5PAMm29+K146SxyXcDaL88tINC26SKkSkk37pLL+vM/amgQkhEAIjZQakQevDv2D6+hctgbtDC2FYkKYUnmyUhOlIvqyg/i+JggCtPbR2sOhME4hnEHqBORSKYuxeephTCrTgkdMUGwhmqmhZZH+5WsYXL2SnsGVCM/jfT//X9j91BNMTtQYHQnJ51ppacmTz+cRgBaJhuywGGcBg/J9nHPoBoPFGkxD+pAWnGiOdBPHttAKYd2c3VA2iJtwtgGaiXfcyWa7uUyGbXjhaYwMJIslEutAKIFyjvnmJ4iFwZEkWC0KJUBLwIIRFpkcSIydI6lOCJxr4tm/H98XQN5MFDhncFZQt3W01pTLZbTWxHG8iD3bGF73xo088dh+xiYqKC3neltoZp/n3S1NCWOhLn55VlrKpCOZnZ0lDGOisqCYKrH9upXc942TyPS8NNPc3zmHRTM7q1m5togNJ+hVklwhxRmvndGRSYyJ8HyNlM0OgMYEm2Q46GxES8ZnRZcD2cOuw8NEuRLjJctMzRJHVS5OHsNl85iodplvfD5RKwQIl7hmAIIgwOIIw5A4jpFSEkaG4bFJMpkUTkCqkiLTUWX8sCHyZti0cgXxuSFwEUoJdLoMlRaOHSnzi79wJ8/vPMaDjx6mVFJIXyOUhzYevquzdoXm1dta+ctPHuPWa9Yl+/klIpVheVeeu27dypfvL7GyK8Wu8xfRPvikgYjKpUvc8mM7ODcyzh2vvJHPfGk3lUqdVC5AWINFMxMantlzkJ/7sXcxMn6SY8cmWb25Dmcz3Li9i2/tMkTBOKOyhQuzEWMzw8iZKfoGbkNOHufwI39AuVTg80/+Dh3L+ujtLPCql/czuHIJA/2dPPjonzCQW8X9+x5ByX7+x+//L7TXw/T4KO9quYm8L5m6tJkla8ZoPddCPj9EZXKSm7J5PvrgE2zduIzBNauQM9sRRjKwusiBAyV23D6IOHIegsRn3NNZAF9w7NgQUVCno6dO59pt/PqP/CmbenopFtqwtRw1r875SzOMV0fpWzLEVSs0N75ygAceWkHoDiD8GUxlJe/98XuJYoUnfVAtVOILBKoDF6WIsbS31JHCUA+TttBsT833pxlKB2gp8VSAsUnyNMiksRZ87WGVI8ikETaL0hIx51yWNF3MtvH2WUGSuPQCUqkUbZ0t3HTTnTyz60liY8mkWlkxOMiqwTX0rlxOJlugUi7Rms/jrOaZJ/aQzig8z0P7XtIBSZE4o6RstF2BcA1pEgdK4KREN25JNHJqlnnmG8UxNJiuECLR+qVEColCEC+Qu5O29e3yK4DBIR0YJKohi0oBWlpsY0qTVIlyMDfjD9mYTOQw1qKYl2VcQ/MHOSexxtYiTPxdY6i65557vuudv1fxoQ/dc08CaqKREJi3ITbBeGFlZrOKs6eHyeUD/CDbSBAsZOTNhzFvP7pcfpFy8QSk5j6uMXTSGZ9KJcXQ2XHalmSoVMyi8yTlS2b51WoR5alp7njDJo4dOse6DbDnQI3YGIRoOErmHDHN3j0JLSUiDolkzA03KM6fCqmFBl8rwlodP/ApV2oZTcJxAAAgAElEQVRExtAYFC4qd7PMUkq0cPh+gHUWs4iRNxKqQiCFwglHVA9Bx0jTyU+/tYezRyoMjU8wVPHJepLQCly9ExGNccerl7D3hcNMTQxz/hyUo05UysdI0CJiWWeGweUpepcPsn3tIPd+bidRVqGrSUd3545unt8zxIYdkpT1OX2hjjNFrJwhDqGSjinGnXQucRw/fYL9h2cAjXGWei2kpbUIwiFtibWb2tizfx+7DzzFO275AMu6B7g0Mcq+Q4fRqW5cPMWa3lZcGFGZDbh+x+2k/RnspSm+8ugBenskpelj7NjWwc/95PuYLRsmSmUeffYsz+0scdfWG+kNZmkf7OGnfupmgmKeJx7dy+YNW+ls9VEpj/yyfirDFxm48S4e/NLnue26Xu772iXe/NobeHrvQbxIMDExTpDLoEWWIFNgw9brGRsZo7enn+eeG8XqWV779tvoaOmiJwMnD+7l0Qcfo1AMiOqQySs6in1cc/0gF0d3MzBQYHREIPQ1bLmuC2xIS5Dl3Ol9TI/vRNanqI6VOX/0Bc4e2MWlczvxRczFE/vwgxw6lZ2z96oFTon5BpJIE0pIAq0RvkJKjRQaLQVSJTqykgopRAOkmu1G4gDVJGSN76xJ8lr1sA547HzmMVYNXsWKVdfS19/L4Orl9Pb10draRtr38TJZCoUWlvcP4ERIR3s7bR3tjQbdEERVI0mJQwmHFKCkSDYh0UKgaMwQbfxNyGT2r5KyIZ82LYcNvBHJ7EsrGy1MJNZAN/df8p0j2axLRExrwckmkWqCPgvwJCmDa7Zcm9yIdcl3NCyJFjCN+7NYrHVYZzAm5M/+9KMX77nnnr/6Ttg5h2f/3g7/f4WzzVcrAW/fTzLVCzWsZgXVI4khzehozFRpFmPixI/Z8LG+1EJgixl7c/78wq3B9m0im1RKVcr1SWpWMnTefFuvrLUmNgnbrdYVlybT3PuJvYxcgpMni1SqYTLRAIcxMVrLuSy2lGKuMRgglj417fPEwyWmKg6ZlYRxiJ/yKJdDtJSol5gYbM38vfq+JpMTSFfD2XjO87qwDlWjExHGkPYFb3tLJ1tXjnLNjtV84Cevpr3YStr3sDYZAbnURdKexkYdbLimlda2drqWtlAOL1GuTCGmKizJ1lnRNc3Kpe2MXTrN44dfpDWXIhP7kNUIP+SRnXXe/642Dh2JWH/VKt76+g2Es2PEkUJTpK+1wIZ17ew9OMI3Hz6OlArr6gg02Vya2dIM9fIsUblKZbaNoycOMHQaatWLBAVNZ0uRd79+C7J+iZAWJmYizk/sp+qf4E/+/MdxwzVEbjW6ME7ZG+XGV65jYP1Sfu5Xf4lybSe/9Vsfo+bqbLstT/8mQ9e29WzaYvnTv70PF1bI9M7wd1/7Gl29K4kqnXS2LaF47Y+QLvZw1699isOnW/iX3fvZ9u7/ypolXSztX8Irbr+TfL5IOp3ms19+iONHj9HV1cPx05cYmjhBKlvkTe/6Y2Sqh3B6nNgcoH8ZVEvTBL6kVvVRfoWZyRqVeopy2MXIcJmr173IM4/uZXy8jYszpxgfeZDJka9Qm32IifGPcWzf79OSuh8ZH+D8mUeoTp0g5ecXubO+U1ghMcrDKI0gwBqVAKKLUBakcWgEntB4Ws5tSloCYfGlQzcAFSlQnoevA4rFNvrWDrBm5Vounp+lva2FlSsH6ejooqWlFR34ZPI51gysIpfL0NndxTXbriVXyIOSCK0RMiFpC+eQ4GSSN7MiwQ9n0Dg0yQQ63ZwQ7RLftrKJHNKcEKRFMpPUOEssHNYkScq5baGHvJmAtBbrXMNv3yB1CGILkZNYIxudXBKm8bNssPQ58oXA2OSaMQ0gd43vEFgEYRx9x2d1eXxfSCuQyA1JctMgmLflLZyRCY3pwGGIs5Y4skipcR54nj93jFLzxv3vNN095TmMCTE2RWTiuQ5ANLLInpYIoYitQamYpkc0YeKCehSREgrPeggNxq+jy1k6emOe2zWE71mMlSB8rHOEcR18jzi0pJxHLAy6Uc7YOYqzPi9/meXY85qdkyH4mtCA5zRCxFibx9lZtNbzCWFpEU6jhSPjCXwjiLWjN5/l7EQJ6TSKpGHF1iCRaNWYOCJ9ZkYEIobOjgpV/xp6uobR54eJXB6lpulsyfLWa1sQ6Qvs2LiOp6tjPH7wKLMRtAqP972hj2BlnvGjM5w8cZbuVT3kfJgxioqq0GbTlGzM6Pgw33ws5Kd+ZDvPP3OUeijYfvNynn3qHEHrFKbuM105yJ6DU/S0L6MyPoyLfPK+IBIghaESGvz2ZRw+/FXe//a34GdKVOKAzPIO+pb1sLR3KWfdJHsem6AtzpAVvbz6ZW9kda2Xi0bw1W99FbxRLhyq4HIR0fgAy9cuYTzs5ZWvuoqTU0e5Y9sbISjQ5WDCvxHD76HNKH6mHyMq/M8/+wz/44OvgYqgW2Wh82qqhx9hx7a7+T/Oz6DVACs37iBwMWfODjEzW2Nv5TSZVJZyucwLp0/x6DM7GVzZj+5bgd+W4bbX/Dxf+8IvYC/Vae/JIWpZ6tEUJddO/9I+yqMzbLvzdRx4/kk2rs0xOmbpavNZtWQZqeJmjuz5AkZW2Lv3cbRn6eotcGnEUjEznBmZpX/gWvrLDq0cWnrYMEIUI2RFIrRqMEYSFwUNiTGZ8JC0NScQwk+4qJIJADmbJOmkayToEj+2cw6NRUiRkE+l0YFPIZuho7eDd7zvp/jsX3+Wa7espru7hWJbF4GfJTQxXpDCRCGd7R2JR9xIVKCRDqwxiSVQJMxTSIF0ggjQQqJcMnqPXNMFmFh9bYO1OxzN+fy2KZC7ONHcnUOiILZEIqkDhQBjEXLxSL6JR7hvN1i4xkjESINs5PSEdUiSKftC2IZ/IzEkWNycBk9j7SbjLMYpEDEai42/c6d7eXzfMPKFUkETbBcyyoWAPLeuRGNq7MJ1Uhbu0zzupaa1B+l04om9bBbl5TJL8+eFTEAIAZGkpqGWstioSn0mSy2Y5uxwjjCyRCIDgGfrBNKSUXlSsSYQitiPFmnzQgjGyjWmp7P86Puv5zd/+GbcbIwMI0RKILxWIl1a5Gdd+CJFxlCt1xG+pH9ZJ6+7LsCPOxdlvaVMWJJQyZTk2BoO75vm7e8Y5MV9g+x96iGu3mKx1RrGlMgKEGWBtVVW9vUzdHwMSpptPRv58M8s428/+jZue891vHbDWq5Zv4m1V62iozeFcCGpqEbWeUROoz2HkjlWrdnI4QMn6V3aQWW6TCE1ydKixY0JlhRg46Zr6O6NGbyqlZu2tYEyjKfSRHGMdYogleXsmWFqtp2//Pv7+PRn9zAzVUFVBa4uCLSHDs/x8+/r5s733sEHX95By7lhnhs+zece/Ar7Th7mk5/fxzU3X8/omSr3vXgf4lw79fIubr/9bTzz9SqHTk5w5Owpdu48xKGdX2NJtoM33X0Hv/ubP4yUFxmaPsKXHzzD+VPD4Md89d4/4eILF/j81x+g0H0D33joa9z3T39OvVJibGyMvmXLefChR+noTDFTmuLS8ATrVq9h2drrue2m1/KyLVvZ/fRhdr1whFLlEtdv287EzCWWLWnBmSmW9fVy7nyF48eOkS90Ml5yPLlrH13LX85zBz7Fc89+Ap0aY+TkDAW/TlvgMT0m2XnkcWZK09ywdYDKxDi5thROGMiEeGmJqudwupnoI0kALpDpFraDZnuJjCMyBuPsnHPEWdFYV2TBxBvXOIdTCKnxAp9sPsuKtl5WDg7y/p//IMpXtLe3k28pJJJoY/SopcL3fYJ0iiCbRut5njlXvoaManCNshusS3Rn2ZA1VMOWKxuekLlNJIxdIfDwk06ssZnG0h/N9VSatsCFdbCwHPOmicUb0ABp26gbk3zjEgNGMnM0kWWMc8Q2Ye2xTeySyQUTVh/b735C0PeJRv6hexbOpr0csC6vvDktWzJn2n+pyl74IBZ+AkRhhBTgeWlqUS3x1r6E3Wf+XPPfOefQWUWrtKzq7UbnQ8J6GSU7qLoygfbnEpNOaSKdw+kY6yye8rCRwDqzqFy+0sg4ZOWGFuJokq72KYq+o7OzldGRWXDm2zT/uZytS7LcOnKUpMeynM/eaXDVcgLeC7yszVyCEIKuwHFmfJJqZYLBawbpCHz2HTvPZDlL6DKsXzHDe9/ybkxcoyBX8eSJ4wysr5GxmtCMM3PhDCOzaR547ClWDPSx68gJquU8kyWYqdSItCCbMUSVNFuuztGabceKGt3decKZSbZuaGHttRlW9qc4uM+RbQ/QlfPs3DvBzFgBP57ECFDaB+e46dp1RHKUkclJ3vhDV+EmY/o6PFJBmlgWWFK0PHlxF791/Sqiwib+/IvPYjonOHr2MBcvltCFFp56+ABveudVhCMRT4+cZGnNsWJrmS2DLRw5XuOZx5+nMnmK6lQJnW2js2+QXTs/RVvrGs6OD3Hs7CHWDN7E8sGlTI0eZXnvMoKuDH/80b/gz/7wtzm/6wSrNq5hbHqSF/YcYNv115HyYqZLEUG2SC2a4dbbUzzy8GdY2bOFgQ2b6cwF1Etn2PPiIaolx+hYyGwcUJoZJ9NZ5JmDu5iuZHFenfZsF0PjhpQYpquwhErtAivW9aGsh3QST1YYXLaK7q40kxd30VVMIV0H1UvDFAqrGR8fp7WjQBxHiRZMwkCdXNxWFoI6JCy4mYuyiWhM0/XtXKIb0xi1JlMnBVbSYMWSjPZQqTSt3V309/eRK+TJ5XJYY+Y0e0+IxDHSsEgKaNhqG2SqOWJu/E0327hKVO9k1mWDIGEb5ZknZlomzcU6l5Qv6ZIa90Li73bzPnOYm+4zD9aNJrcQKxYTqyRPwILNCYFprq9iEueKdTScKQ3tvVGniX5usCamVqvxyb++97vSyL9vgFzpeS38clBe+LmQeTflkIUJhst1rcuZ78IKD1Ie9cgkL6lbDOKXs96mXz2RbhTUDCpIITzHsl649eZNzE6XmJksUYsM2likn8JhSNfK9Ok4Gc4FFkGEE/6idWVilWF9v0clqjMVjfJLH/w5tm5eQ09PhScfH8dmDFh12T006ovEmvW2l21h5/7jXDtYJByfZKzqsA15qalbNrQjhBBMWEFvS4EHn71AT3c3f/eFp3n5TZtJ+5a4UmbjxjZaimXKtXEOH36Cu+64nunZ89zxyh/n3n/6R0phlVduu4pbb7mZo+cOUq9Y9h+fohKGRGGyfoYzKdo7BFJMs2ppB366gozb2DDQR0Fl6V2xhO3r+zl98UVW9/Xx9WdnqIgqE+UIEbQgTIwxIbk0tAQz+OlpXnnb1SztXcXwqTrdOkumtY1y7NFXCLkuv4IzUTf3P3+QTXe0M9hRYMXypbzudTdQr53k+r4l5MUMG9e34iYr7Lj2DuLcNeSqisf2PM3pqUkmp1KsWL2Gnfufhyhi5bIbOH3hKCMTPgMr+7j/oUe4du12WvOS7mu3cuLUCMqf4pd/5V623/Ryim0Bs/WQ02eHKBTSBF6GnXuOMjIzxcWxo1y3bRlt7UVGTs9Ctc6zz97PW+66mWeffgRluzk4PoHyc3RnPGR9lCWrbuDmLWO0lVey58Qom9dr0t4YxgmuveYq4rEqobOMTEziB1mWdrUzMjKLkgFajXP+wjfwxTAn93+L+uQZZsdmaV26Ahq+7OZCT4tzSJcRIktTt0DiME0AmmtNTR91AuaCxP5nSZaZiIgI/DQpP4UfaAqFlkWTbaSUc3ZBKSTSJah7ebuHxrKwjfZvMegGk27KopKkXTVLKEXT9NIAbCGSheicaEhDDYR3SYclRDLSmEMKscCtgphbPnlhxvhy4mgbmnrsJLERRFZirMDO1VuigxvnMM7NJT0TVSf5LY7q/M1ffXdA/n0jrSRLxTaHZUkCw5okoZdIGwZj4sSD3UxwNHqx5vHzi0gJjLEYM79QlmlMgFiok8+Wo8SKZRe+wEklKjWf4ab5ACU4qzFRzOBKw5aeNLesyPH47ho5N8bszAiRNUQixlmfcmwpBFl+/v3beMNP3EpPD3RlcsR+c40XaFoHPTfF/vOGTQPLiW2Vrz7wp1g1CwZuvS2D79oTa5dsOF2EaNgsXUO7Nxw7N8za1S3sOVnmza++HhNFSJ3cQVxPtL3mSy2FxXeamamYN79hOd/4xjFygc+/PraP4bEpbrm+k97lnZSFx0zNUPV8SqmAU2dSfOUrH+ftL7uZgd5elNjBr37sj9h/4QDXXb2SlKkTmAjfaUqxQdaqVONJlrcv5dj5p9m5f5TpaolPf/kp4hWtnD05y76z+5iNDc8cPk00U+b6gT5WtRtk1SJ0TNrTbF27gg0bu3ndq97CisGbWNK6BTodqTaPYn4FgapwdDiP7NvAw7sfRqzUnNw5RX/3jbz4wGk++U9P8qa7f5pyai1P7B/nMw8c4p1vfgsfe+BLfPzez3AhmuX8IcfEdIHxepqDZ2fo68iTUVVe2P8cvsqzfmWe85Nl2noNX/j6w9QqOTg/xGDtFDsGd/D2H7qO0YsHkZ7g1MVh+pZ0kvIF1bKk7sbYf/gI27dv5lu7Jnn+oQvc+orXsXl5kbe/sZ9Pf/nTvPmNb6VmHLd2tHLnyg7axBAf+ODP8K4djvpYJ7PFZ6hVj9HWliGj2zl/aYiHv3mIDnc1L+58mrFxxQsHTzE8UWF86hTFljphrUxOtzA2cpzRM1/D1L/E5KVLOASRqyK1wEaLCdDCRejmgFS4ORnCIhsujYa917lE8hCJbc7gIJnHh0QSOgcqjfQD0pkMuXxLssYJiQVXiUYyEIESujFFpukSSzat1SKgTK7byJE1y94ceUqNEwqhFE4ILIl+HsWS2CicTTYpkpGIUwnwKpk4XgQOT4g5O68zidbtS4FurHa4+F8WaDhOnCNyltBa6sZRs5K6gThOlv0wJP82gCFZM+alFsezNkYJMZfb+m7j+4KRf/jDH77H95MqbILwQlml6UZJHuT87Mvmfc4lIWCR/HI5A5eyOctxMYNfzHAba3qLeVYipUwSONYgcbQXM1x/dTdRJLjlxo2cvDDN+PAkpy7GBKks1aomjmusXx6wLG/56iNn8KIznB8KOHOhTCoD1niL1lmxLoUJy6xepvE8WDUwwFT5NFs3bGFVr6CrfYLde8ogCiBnMSaFlPP3IoSgzcuRE45NG1uYrsxy6aJhplRNHATaT1jI3L06nG/YsiHPuVND/NC7r+Ir3zwDBn79l97E8On9pNMaG58g60uWL3kFXYUy7cU8E9MlRmYmaGnNc2H4RdZt6WX7hkF2vXCGegTTk4Z0VlGpQ9oLuX1bmvWrPGakZurCJa6/4ToujY5z7twhhoYrDC4Z4MSRmOmqYOuWbto706zdsoIXn5vFKkdLa4ZK+TxXX53Gc8N88fMPsHJjz/9N3XuHN3KeZ7+/mcGgEgAJAqxgW9btvWqrtJJWvVjNsmXLsT7FTuzkOImd5jjJSVzixMnnOMf2sRM3ybYsy+q97Wr7rnaXSy577wUkiF6nfX8A5HJXckvOua7kva4hMIOZdzjAzPM+7/3cz/3QXH09SmgGVbeiqGlm52codfl4c2iYybOdpKxhpgLD9EYXiM66eOXwS1hTo7zVbuePH9gDphGu2erk6LPj/NXHH0K02xgYaWVVcwENzYUUFlUwND3Kuo1+zpy/gMueobqkgFhKoNRpZ8f67QRmxoi5zfzz4TcxpVx09Y6yemUdoxPTbFizCotV4uS77QwFEhQUhyn3iwTjGUxZK68cuchbh8+SUuMUFiZ49rFzCIKILEBBqZls0o7Dn/MEfVV+nAXbaGheQ39vJxNjGbJ6iKaKEi6OjRAX7IwtjOHzeonOhSn0+YhGUwQWAlidIpYCiXgiSTxjJ5RuZuOmXSgqZJUsoqTlkoKumv0ub1dQXhfd12VtyVcWcsZb0I1cNiYsFf9YJD1e+Xxe9uaXf7aoq7+I1EAuaVASjSXjvqiVkqMg5pLgTKKQ83eXMPvL2ieClNctz2d/CoK05DmLiIhijlEm5J2sXAKfhiSJS+dcsj86aKq2RE2E3O+kqeQkhfVF3njuyxEud3CV/bm8npuV5A4QhJzP/t1vfeN/jkeeC1bmsSrDQDIJSKbc9MdAu+ImulrNDJYZW+HKYhTLDfmi17p8+y+7YRfla68eMXVdRzIJiJJC50iccCzLVDDGVp+VCmsxH99Xjt2UoF5OsWGjD0NQOXBDI5/62FbOnbHTUG3n1EsPI5nlpRnE4jVljCRN1fXEs0lK3ZXMBbrZsflmfv6L41Q3bEPT3OzY7EMSLhdWuBr7j6QT9AYXCGsqghglmI2AJbevmky+9/tKGHhcDrw+O9/4xil2rS2hzguv/6yd46ejrGmpoqV2PXrWyYpVAsPTAfpHpkgp4/hLy0nNxTh9qpcV1XsZngmxdt0OkHQKHFYqy+1UFlt5+K61FBaXIWk2DjTsYn3LRqxCMSbdzsqGOpJGnEBwgc3byshkwwzNpFhITWJSU9xxs4HFlMJkMlHocVFZsRFB83Ldnhs4frqVofanyBoWJJOOzWJHIMnXfvIduro7MLvcdJ3K8OJzAZKjs5y/2EFVmY+i4u38yxf3olkytM7OUF75Yb7wrXs5famTc32nsDtrOHl2lrOnu7l4epTNLTvpujCF1bmKmFLByIxGSXEps/P9TE7NUuAuY6FvjL+4+VEaW0r56N030jc6TqHLzfDgIPPBEG6Xl6oqgx2r6/E5XDRWuXDZZMwmkVhCRTVqaa7agNnkJ5uIIGMHPYPdasFXHARpnlQ6QFfPC2iZUfbu3IJcOE6lp47dm69n97YteF1ltJ2MMTUbxV64kmhM4UzrJGZ7Ay5HNalICFk2KCsuw+cZoqf9aZT4PBIyFovjivto8R65uhmGkU9ff+/ni555Dp3OvQpCjvMtCiAL4lLhicUYzS97jhdZIyYj75lKUp7rrSOS8+AlgbzXuvg/63mRKQPByM14l2deiktE7tySq8qTswcmMUdFXH7ti8+XaXkFplzVmDyP3ABRQjMEFM3I6fDroCLlqdSLS27CvwhfXW1rls/MDUPPyxDkVV5l83t+g1/W/lsYcmAJSoHLP+xyDG1x+/vdYIvt6ptkeT9ms2lJBF6SclljkiS9R9N78bhFI7sYeBXQkSQ5l3mqqMQXssSiIb75wimamvzMZCc4nTD48CMrWXt3HTgMmpoNis0iohjmx0+uw1Nq8KMf/hSrXnTFgGMymRCyNgQG8VaW4y2Nc+/d/8DYuIVN1+xnYLyPktIiKvxOFD0IhgXRlHkP7p/WDYK6hqmggHQyhMkAi2wiraiYC+zvmZqaJTOyFGbnpmpuPghuI8D+3W5uv6eWa28o4PmXj6KLAiW+On70g1NkNZn7PvgwW9b8EbK5inUtmyiv8vL2q29QKDcxODZMOK5jsqZRFAWTHGEqFEcxC2SkYl47e5TAQhjRdIK9e/0UezayaaMdQSphZGyYPTsq0eJjnHozjqu4Ev+KFVy/r5FMah5RMvHSC2c4djrBsdNnOXNqlGpDQUnr6GqCuUAAf20lGUkjFRYZDYeoXuNFsM/x95/9a77wORvdF1McO93KZNsF3K4MKxxVeIUQh39wjrODMbrOm0jEAxS77ZiNUjAymAQrW3c14bTFSURHCUenKSrKcPv9h7AXCaDM4KleQ2iwlX3778ZUqmC1mqkoK8HpLkKXLBxvO8o126v53Q/9Lj2dExw53MvEWApfSQEOexxf6TQzEzHCQhqbyUIikSIRF9GlGE5bHbHYNLFwHF+JGZMlTnB2mNsO3kM82se//fCb9A+NEosv4Hba8Dj8DI+dJDifQJcE2jva6OnuZ2Y+irugGSMzi5MJ5iZbySYiWGUrmqFe8by8n2cuGJdT0sXL9v7yfqKEIEg5mMUQUDHI6gaGYGAI+pJi4HLvm6vfL3u0RSGX2q4Leh52ydEEJSREI5dBKol5r9zISdJqeSOYS7AxcjosRh7GWPKmc7RiUTQhC+LStSz/fHGfRfho8VXTtKWaBXqeZbJ4TkMQ0fODmJ43zIuzFj0PSS0PpF7pZF5elxCR84OgLP7mKfr/LaCVv/3bv/0bq01Gz6fc5hXyl4JysPymMlB0LWeUETB0HYvVsuThZrPZ97BeJEkilc5gkkxYrBKCaEOQNDTNQFUUbLKIVdLIKBKSyYGiqphUCcwaYjKDWbCiimkQZHRJwCwY2O1p/IUtmNBpm+zDpHvoHZ+ncyJGBRqz3SlqKmycPZfg4w9uJ5OqY3o2yhvn0xh6iHlVRtZy003RVECtHMNUWkBDmZ3m+lL+6VvfQ5LN+OtKiActbFxTy9hIL9EZE4GEiEnI6U3oggNRkdDNEslolo8camHfxm28c7oDX20NPjHFTFBAF82sr7ejJmIkDTuqYmC1p2gqKUPVB3C5y7GbS1D1IJlUgj0bD1FWZiEQWiAjmrFLBYTTwwRGRfZf10Dv0BHkTBZPlZ1sJotDzhCYzxANLhDVFdJqmhZXKYY1i0uScXkVuvsmMNnNnOscpXckQEWJRHxaxldazmjfIILk4+MPHKSiNoanzEzrqW6ypnkkrZxt2zSM7FomJ9+lxN3EvpUCLV4Jw76CiWACj01lLqrwk1+cJZ00c8vBVbx7ZJxIxMxwaprCyFb8K0cxYlkGQ1GmJxWiSYFfvHGJYrkE38p5Vq3cyVz8IqvWVhMKTHP7DdegW6doPddBdZnO7z7yQRJhnWTWwuETR7hl/Qco8tfz5E8ex1W3juTYAGZ7MdNjw6xdt4pQKMjwRATRrDM8u0Cp30c0nuR81xC7KppYkB3YBJlbbmjir/7iZSwOG2nNTIQ00bkI3vpC5gLj3HrdXvrGJpkJSBQ7XPjLTYyPBnCVF5NQSni3rYPqRjMFDo0Sl8JNO/YyOBLAYjVRs8KFkhbwV+5neLqHSMiCxSRhsVWRiMfw18AOp4IAACAASURBVNSTNjmQSWPIoCsCQkYCUQfdjCHk9fsxljmZ75VgzrsIS3/FPPxi5Pnbopgv2CDkjDRLBi3P7EBA0MW855oz3oKwrM6sKKHnE+py/ecE5PKMd3RDyK3nC2vkQNAcw0bL76fpYCBhIKLrYq6q0GJijp6jNOY8biMvR5vTN9cNUA1QVQFNz5/DAARpidyYDx7kmTVCfnWZXG7eeglS7nvIxVjFXBa2mIOQTAYIUj5blVyG+be/8bX/OdAKXKbFiUuBvMtY+NUjmVmSc957vpxTJpPJBzS1pYzQxWM1TcsVYxBFNEXFbJIwSTqiLiMKYJYFzLKMIlgQzQa6EcVEGkUQUMMKj/zBPu79oBmnXIDNYuealS5shkyFt5SByBAGSfatWYmSMVNosuFKS5xrTxOQU4wOJqgpN/jqD56isFhkRYXBZz5ZR0OtjTo5TdoQwWTilrUOtu5y4bHGmRidoKh0LRu2NRHXRvjGt57kr//5p8xmHZw4P8NCNoohR0mlZcwa6EIYk01ESynohoDZlWZo/CSrG+rwijFmUlkK3RKr6wyKbWEO7qilyZlBSKVZWWintnaCD93xBbZvrqG6TOf6bZvYXL+Dtt7nOHlRYaBTp2N4ktIKO8EEHGt7lq/9278wNmbmhbNzGGGJ6iKBqWSAk6N9jIc01KRBmcdFOD2LxZSlf2aM1sEgwUgZwbEo+9fto87rIDqzQFVLGUdOv0bz+u2cu3QJh2cFd+9+BDlZxUI0zsJ8EdcfEimVq7hlvZeGiiZGgrP0KAWkikqJx0KUl5UwNDGFxW5jaiKOv6KA0YkgljI7U7Es6WCcomadm/ffwiMff5i5gTjrVjdwrmeA9fVePKX92IUWppNv0OCxctu+LWzfU8+FvqNYbTKGbmZiQmNoOIa/2WByoosD23YxNTeB5DMzNL3AG+8c5plj51Di89xw7bXIkgl/VT0zwWk6+7pQBIn//c9fJBof5aEH1nFksJPQ/DTHTnby70+8zKYdzWiiyngogpIxU1ZVSiw5QWVtEa+/3EosGWZoqpeY6mJgTGQ+nKLzfB9F9hE++7G70BYiVJd6cXltBMUpappKSScM4sFqYikPP3jyZ5zrmiMtaEyOzjM5cx5BNJEAnNkM6TSoCR271YFol0FUQUoDKgJXTvGvdq7ed5YsqJe55qpBWsmi6FqOc55/npcyJfOMlMsBRHEpqLroaWu6jm4IaOQWhfz2ZYue95A1Lac7rmjGFV6zhoCia2RUlYymkFUVFE1d4sZrGCQzaTKqgqJrpFWDjEYuYKkJKIaOYuioGGgCqIa+VPpNy3viy2fJS7P5ZR63oelLvHZD05ERc7CTIGISLh9rCNJvIWL738iQL+LRS9M7SXzPjbJEuNcvwyjLeeWL/bwn4q7reTI+yGYTSjaenw4KIJhRVTNWIYNJMshoJjSpCMGWpcwPzz/bSiLqI5vRiKfCqMk0ajaJyaWTTQqMT6UZnAkwb1YIKUlKSm0I1hSrzCV0TomQKaDM0cK3f/QKhV4bdZVFbN9uwV9qRxA19HiS1S2lyKKZuio769aX8cTPX2RurJyZKZ1wNIFuwPcfe43CYj82WwWiZkW268SzKhbJipLRKbOJmEgSDMxhs0A8OIG/zA1mBwsLKZprK5BdOmf7Rti7q4mbtpUjm5Jce90hvvwvX8ZmrQRBw2X209/5Lj63ByXVhsWiYSvyMD01ittZQvWKYlQ9wkKsE4uWZDIWJh30EZwSsCdlygsNCqwGjY2N7L1tD3NzCTTDSTYdp9idQqWA7p5hmlaXYnZmqar2oygKb75+kk0bm9GCC7x16jVmAlN86kMPkU6EKFIL8Hi8fOWHL9E2NIzD4UOdTzEzOU+R24WEhihbyahZ1jXBn356N1UeF8kZjYSS4ejpYW65roH+8QIe//mbbNxcTLHLg1WGdFajsmoHU+OjBGaC7N+7kfZLJyivcFLhcTPVMYK3FHylXo4dG6a2chcTEyHCs1FsBWaUrMRsKEY8naF/YhZZNHDYC3AWeJiZDSHKZhSytLafp6ayhdVNOzh1ohe7xUVVjZ/iEhmT5CSTVMgkEgiCjN1cQFaIc/td+4nGUpQ3WojHdWrLNtPXeYELbafJZA285T6mp8yoaSu1/iq8HplwaIF01MHsRBSbVWFoeICO7hEyiRIKijNEIhEKClTi4QkMXUc020lGkviKPbjtbsbHBsiqEQTRAuQCftlsduk5vZok8MviTDmaX85ALnrMyxOIfplUQO64PNSKkOeo545ZZHuoi8ZU1/MG3lh6XRwQFs97OfUdVEAxDLK6hmKwlISzmJSTS/O/nPKvIqAYlxN2lv7Hq2JTV1/L+zmfi01CWFoWDbeYX3/vd/mbm+f/Uoq+IAgjQIzc7EU1DGOLIAge4GdALTAC3GcYRujX9XXFxUu5aZks56hISh5Pvpw9ppBjt1w2+JqmLYlTLQ9WLPUtgCCIGJk4PrtIWMuiqgaGqqBnk8RdDgxFpaJAosAIM6sboLopcAk89UofVtmFIaQ41R7lkx+qYf9mH95bV/PYkYs8drSNrW4zjQ2NZBxR4j4QBJXv/OleHJkMfaEFfvJ8mPVrBIbe7KS2tonM/mku/D+zfPhWLxZnOR98sImnnn6GZMZOWbWDs2fewV/uw5IR2dhkZrJziGtvsZPJqlgsCqOzMpSUYU2H8FXK3HfQx8yMiGCFwGwEQ5UYmYnhsNqwyFmmpqepr3bzxU9t42NffA0RaPG7ePNwitLqUt44/ALX3baHjs4eCiprmZgOU2DEaK6pRixWiEYcrF/TxC9+oGB26OiCiXVVKzh58hgf+4M1GIMSw2NxSms1Nvv3cfrIRdQpK6oo4yoQEbMGZc6VtE53MzsQZyKtsH/Lbp74wUvcd8tNlNZ4mJ8O8uM33uGmHRtQ9CRf+tbPaKx0c+6SxqduLeXhB3egJqM881o7N926h6GJMeqqsohoKIKF2MwMjz56F+6CNbx6/B3WbXfiDbgwkiEOPfosFjHLweucFGvVGPIod9y8imjazJnuUa7Z4SR9qZiKpM6NdzzESMbgRz0/oWNklpa6ShaUCJFwlGjSy6c/vR850kBZWQkmZR67zYVqMmEYGVRN4lLPMLogMD0T58yl08xOR/DWF7Nl3WqsskBCceIUDN564yQNlWXosShKKgcUeOxmJGGO6roa+rqHaW5ez+Ejfdx+9x7i4WmKLLtobx+k3Ouiuy/KgQMNHG1/EZQiHHYXPrmQ8fYx/GUWTo2K1LeswDw9QEOTwEC/RM2aUsaik2xav4PJ0UFsx49gddgZHj9LkbeO+dkkStJMeU0BLlchkfg8kgnez6gsf8aWb4OcbkuOSrxIkZXyFL0caioJOZzmysNzNEBDy0Ev6qJhNoSlQCCwxOxYAiyW2Cs5TFxi8f8SUfUcVm0YBrokLJEqBEREYZkx1nPeuyjK+ZmEgZFnyCyeTURa5jC+T5q+katkdnnzogLisn1EYQl+WeS8L6ZWLWarGnlY6LK03q9v/19orRwwDGN+2fqfAW8ZhvEVQRD+LL/+p7+qgyXqzTJv3NByBRgWse/lo1tpRTGhUIRM9jJXXJblfD1L6T0j5SI+p6oq5cWlOC0GydEoipplwxof65rcvPxyLyHJguiWUaxJtkkegoTY3dJI/6yKkQKLYEYukTm4YROR+THe7nmFC10BKgsLaY+q3Hb/Cr71vdd44MYdbD9g5ejFLnbW340jleZPHupCzjhRmxuoarHQ0TXO41+/gZjhJjl7iddejyLKBYzPZRAVnfXNKykrK+COG6qwpFpIprsIhz1s/WiSb3ztNI31Frp60zT7MyRFiGpeqko14gUmRsYy9A7ZmdBTGOEwZpvIlmvXUVMqc6LjXR6+ewsnTrcxvJBlPtmOqAf44J0fYXy0nUpfLV5/C6/9v19DshRxZnKYXaIPu+zl1eeHqFvjYiGa5vyFGW7cbmezupe2t3tJmyM4pATvnrEzM95By5pyUoqEI20lFoziLHPzdn83a2o9+GqshAKTVPtmOKE76O+ZRfJonDszjcct88TrFwkM91Ld4OPdjhm+/nsr+PZzlxhfaCNml9EdKu++c4GVTfUEFwJkAjEsNi/pWID53gTP/ORLHLp9G6a5WQYnRyj1W7DHI2hCEK+8FYdJQDCtpP9SN6HgSZrWuxge9VG4wkSvJDPQ2kUwEKOlupgDm9fx9PNHaNxSz8o1jXz588+ybr2FD1y3n2wqxcmXXsRlsaC4XFQUwHgghqMwxcx0gGA4Q2VtAXZTivqN9YwM9tLePYAq2oham9m308RofysOl43BZIS4oVPulHELMhazi9tu3MPjP3uMpsY1aFkLwZCVlCvJhl3bGR8ZpGVFNXtXX8fs7BjxEFgsKXq7Ztm46RpWerJc7BthMtBLbDZFULex8xo/I5M2br3/SxhqkOFTx3BNHWdcC5OyrGXd5p309r/Nnq0NHD//Bg57LSuaG1F0DYxleLggLD2Py5+zK5gomPK4+iKKLaPqKpKRy8cQriqYDmCIeUOPgaDq6JKwZAgNUcCkLwoIGkvBw+VNM1gqPiECmqFdyffWjLwIWE6iVrmKlSaZzCiKkqcbixjLwA2RnHaKsHidgoC2bGxbzPp8Lx//yoBlTjQyP8vQ9TyHfjE0muPSG4aBxtUEz1/d/v+AVu4Afph//0Pgzl93gCQKZLLKko64oeZGa0VTMYRcdRt0HbPJhCxorF2T4pMfauHghhIy2VwAZLHaxyJFKpvN5oMJua9IVx1UeiVu3OlhZaPKp+9rotqjMRvOEpqb4fpby7AqGWySzMaaQirXZNmzuYD1aw1u2abz0Xv81Po0pIUEJ84G+NaL5/HX7sFtq8Fls+CT4pSZi6itLuMbz3Xy3NNHCE3qdPQ9hbt+nCNtIUbCacpKVvPyqycQzW5OdLQxOt5Fma+FuqYSTrcHMWnFvHxkiP6pEG3dbVwc1hFNZlpWbaSsqoHCAp2/+btHWVddzr1rXNQWF/N7H26mqUaj0O1g58oVSOk4Xv80JrOIYZj44w9V4WOQ7asrae1ewOM0uP6aYr7yiXW0lCZ4+IFDDI6HiaYipLM63/33b2JKFeEvz1Juj9I3NUYgOk1xWZqRkQ56Wsco9Wb5wU9bKSgycDlKsSmVHNhzLds3F1BpdTMbGKexrBzJPoq1IEGJBFIqgahrdJ2fodlXyz/+YJap2DzvXLhEQ+lWbt9zD5s2rqS6xGDn1gpqSpx8/VN34S7Yyvf+9fOsXuNjU1kNte4yxsNmQrO9YPFRVOjEWWDB7HTQF+nlups303HsHeK6yu4GL5+8dxdf+cqjNNQ38eLr7fSOJpmaTrFhwwbuuvVOWqpuQbbWcGDtffzi9S7+7btP0z8wwulLw3zr58+x4/YdxGMyVZW7KCmXmQ/L+AtKiAamcBdUYy50YzcEVq9swi6l8RWVUlvZjIJKW2cYk7mW9TV1qJZCtu/egWS4OXr2PPVNApPROLLupqK8GI+QkzReyKbpvjTMwESEEk8xu/aup739ND0DbXgLSnnsp08wOD1Bz9g0P3/rFL19abr7ZpmfzNBU4aezvZOugSkaqqzMTyfxr6nn5pu3MNk5wd4tFVw6fpjBszpbNu9CqmwikSgCwYdg8bLvwA28eORtNm89SFV9GVlFQzbnEuUWdUPgsjF/PwZKTldEzWXz6QboAoJgQ1EUDFElpag5Zock5hLodA3V0FGUvP62IZIRBdJZHUUzckk7ikgGHYWcUqGGgSFIqHpeBz2fGLQIqShGDt3XDGEJGtEMCVUXMQQp168gXrHompqTvcXIDVzLbJQhXKYRLmLiuWvLLYusnlw94RyLRZBM74VLltQQhbxSpLB0zQJS/uNcHVNJ+M1R8v+qITeA1wVBOC8IwqP5baWGYUzn388Ape93oCAIjwqCcE4QhHOGkStFpShq3nvO/aC6JqCp4lLFa1VVMUSBibYYc7NzbNilcXBHyRWwDOT2s1lldE1BEgU0FQQpyocf2ounNEuJL4GgzOL3wsJUlOEFJ4GZGI98pIrxniCG5kWNW4jMpRifXqC2vpaFVB+bNmo8+FA1Nv8Y/+tDa3n1zDtMJGZZUTXPX/z+R/nqt55kV1UNH3u4jn0rPkNCnSGhFDLeMcQ1a9dhcYlcWniK9ev24/XY2L2liliwk7nYIOHZXu6508XevXDvzWUcOzPD4bNZPnHoJiJJhZOXYgwEWlHUWiRLmN9/9I9o3JGiflsRkdAsdR4nO3a04CssZ8PqtezZvZYHNjt5+LYVjKTi+KvW8sPvPctD9+2iuszMYP8Mo2OzFJVvYSri4rlnz/L6i2O4nDXUVm7BW+am84xBgWsnPRNw7NQIwXGDQqeZ3XvLWFu7AsQM7V0jnO69QNiUZWBimO7uWVRtljJTMYUFEb78v/4Yf6WTFRVRPvRwJbIlgZYEh9nBNz57B+VSOYqi8Nkv/iuvtn0Hq57AbDHwr6qnb2COBcVB93wbxy6+wdiEQe/gCDOhIJWFJordNZQVQ0vzBuLhEIoiIXmqUEyNfOXzf44tleKGmz/MC6928dd//UNGevuob/Bw6MCdvPTKz3jx5ScoLV/Fd370OD3Dc0zOjmPoM9x0aDWhWIBk2oQglPGP//drrFlt5pOf+By+WieuAh/+cg/myjImUiqKaGJyegYRiYoyP6GYiiJaCASn0CUbUkGQl94+Ru/IGbJqCKcnzEdu3cCJswqP//19TE9OMzU5jdlsBUAyDA5dX8/UufN4BAdTfUcY6J7izu276T5/kVX1NYQXomiiyMD4FJJuZ/X6FSQ0GBqPs8JvQnKZyYQVymqKGO6K0dczys5tmxi6eIFs8B02eM4xNHIJi3cTis2MxDD9be0IJjtbtm8jmkwBtpxzpF3OeQAui2b9MiN+FcVOEARM5hiiJmI2irCYBURJQlF1ZJsdRRfJqKAJIhnFIG0ICMiYLAKybCEez6JKmSsw7EUJZwEzomQmpWWWYd56ngZ5pU+7SKBYXuLtVzXBuGq56pp+iV1bYqos37a801xfRt6I52cmYk5697cJcF5xbf/J4xbbbsMwNgE3Ab8vCMLe5R8ahnGZTHlVMwzjO4ZhbDEMY4vFLKEpKrLZunTTGEZuWmagXQ58igKyLBNQiqmptUKwgskZ0xU/mCAIFBY5cbltuN1mJFHDbLUgKBLnz7RidVVy3cHb6Z6fYf2GGoocGhc7g1g8LsSszqf/sIXjJ2KookJRkZmEYmCzJ3jggXu4duftbN7ko9bfyMBEAZXlInVlAs0lJWwumONTD2wGzYS3aBrWt7N99WoGp3tZUeWluW6Ysc5+xtt9dHWcYOeejRhGA7U1u9m+5RDltQfZsOkhnn42SuPqzexvdPB3j2ymsG4bqt5Ne1cvna1zTA54MJvKOd/1GqFYnA2VhezcdB2HLyU5frqLY+8+h0lO0P5uJ5bCEIJlDi0dx6yIrN2wlrNnOwgtJNm+ZS2+Jgetl9ro7z5HY02CBx7YhizPMh48yYWeCPGMwpEjb1NW7CQRTrNjXwHNTbu586avEUkMcecdpTzyyH6sFo0MwwzNKBRVO4lrWbZuaKarL8XgRD/zA2EslpWUuDdy655mbtxRz0c++FF+9IOjOIpmWbWxmK9/9iFu2voA40EzNaWlRIMO7rxnD1Uejf3b7iAd1bh+30b2bN/Igzdfi66Cy+NicizIxGyAxrpVzAXnuaGxhJH54/zVvz2OUVhOR/sL2IRCfF4voriKkdEZRqaf549/7wEa/St55vCTuJxVKNEYHeePsmfXjRw/OUAobkK2OZkcn+H1736B55/s5bOfuZbZeZF79z9I1mOmrK6Co6+/RYHThdUsMzo6zIW2i6ipOBVeG62D/XjNGVas8FJcIOK01NHVNY7Fa+JoG9TLZ/jmN19HFXRkmwmzTcSEQiyYIZ4soaVxJagGPacz/Me3f4giwFx0nmh6HkMyoWoK0+OzZFQfU1MTSGaNkfAkgrmc4dk4lcUyxcVbqarwEQi5OdMZ5Mb1a8AuMBFeoGFFIxfOfBctEqG3b4SLrS/x7NOv4XNVYzKZEQWYHOvHLOSey+XJQMuVA5dS45c9g1c3PaMzNdrK2aNPkJxOkMyA2eYimcgSiyWQZQuCZsZmcpDRVdBSaGmVuclhyoq97xtY1BEwCVmSsTCibuIy/1t4z7LIapMk6X3ZJELeqF65/PZtuWqicFUSUl7cIPefGwa6rubPfSXevpg8JPL+g8X7tf+SITcMYzL/GgCeAbYBs4IglAPkXwO/SV82mwNDzyXqYCwyUnRk82UJ1sWgJUKIjh4nTx2+wNTC1BW0RcMwSKeTmEQVh81EkceJruemeXabhZ7hEfqGhtm/v5Hrd29i3VoXcUWnRJVpW9AIDvaxaU2GsQ4BW6aWYpeOnHQw2HaCUt8IE929NJe6WbM+zQd2XUt9UTllG/08fe44dRsr6KONbY3bEefD7LtmB//XB2+kwF1CT28djeubuDQ4yHRS4x+++jiyL8xUdIq6irWcPfsCva1naW62sKIyQ3mxQkZ2c+zwSdr645RKQ+zbtZGMcIRTJ/sYHlG54cAdWArLGRwZpr7WQuWGVQzPyHir1nPTvTfh8Ois2VzOnz38CJLQBwmdSDBBRUkBqxrcqNEM127dT2Oln9Xr1hFWPQxNpvAWbmZlUxGrd1VSUQEfvG0PX//qp+g5M8PY2Kuca32SDas3EJqV+OY3H8NR5EBTfZTYZrHLKZq2rcFwujky0YGguPjcXR+n0BnBkTRwFVZQWi7w/CuPcS5wms7xBPVuD68e68BkNqj1uqirrmfXnk1kI2H+44k3+PJ3nuBL//48X/7OSQrNMp988A4yGYn5OQGbo5TCcjOZTIrp2X7W77ybjrZ+7j24iZHJYZ45NkckYeC16/zeI3U8+pEPUld6A1bHFt7uOs1E3xxljhj+sgQ94xGee/UsbV0ZLC4vHm8h5aUSP3v3TeZSAeayFkqEJHtvugFRSaA4nERlF12dncTiEaqr/RT6iqnx+xkcH+ejt28mEE0xORDjtoNbqanV2bV7D+5sKX762LF1O47iYkLRFKmsQTiUwGktxF7i4Pz0aQbiccImjYRb5i//7A851dNGlaeaLaWV1NjdOC0WrDY7I4E+wrMapIuoW9WIs8JHncvMRErAmhxiMCrgtkoc3L6JockwKy13MqpKHH2nn86h15iP27AUeDCyVu574DbaWl/HZrFh6EkKnWZG+saXkvMWNU7ez1j+siQXQRDISjL1K1dS11CNs0hFSSYZ7Ghj+FIrRmgGt5Gm+9yrHHv5GayqTv+ZDkoLffR3XWS0fwRRN7MIW7AMSjHLCo9//7u4ze5lbBXjilnD4mIymdA0bYmu/F9tv+zaF425+L5euY4k5OIEORun5SmY6mX7Br+FCc+1//TVCILgEATBufgeuAHoAJ4HPprf7aPAc7+uL8kkIBlJFCWeK4BgZNENAYdJ4xMPbcSu6yTUDDYkTLKMCQehwAKVlZWkktYrGC2GYZCKqQiyCUkUqa8uQjQMRKuVs6eDxGYVjp6Z58XDQV5pvUREL6LGYuLHr47xB4/cxpyqgRBGMhxMJ1VGprx4yhRmBywUOHyUFnsYGh1nQ+1Wthxcx5YbGug5PUHD5hbO9I5z07ZG3j56nucPt/LzN44yGDZzYaCN9v63qa7x8fefOoTfXsDqTet4+sWzmE06f/RPn6a5pZlQJsjZ4xcY6IEPf/R+akrKiYZMKPEQSCUMjrzL0NAQkXgbOzYqGFmJt96+QCgawGKp57mfnSUU0jl84g2CMz1cu/d+xmfDXOgcYWywjAc/eC2Hdh+ke+QM59ovcMu22+k+McuRI32I0TiJtMFCxkltdR16KoLFpHLvPY/w01+8QWvfEbL6BGpUJpzuZ3AiweTcDHVVfkSzTDphwiZEUdViTMEIoelzWBfgZNsZjsxcYrw1wWhfO63nj6FlBaotEvdtXst1mzYTDwgMjLZjc4ygalnOd13i+ce+yfd+eJFtu3fRea6N6XgUt5hAppDIvMSlgUlcpjgOUxZRcpONz+GvbSAQ7eW7X/4yoQWZe2+9jY/dtQrDOk7vYDdPPd/BcHiAVDLGT45+AZfiw9BlNNHFH15zP9vWrOLbf3Inv3P3KpKRBWrrrfzO7R/AY6rmn//y25x5rZORaZVsah49bUKZmMBfUopsNWO12ShxOdi1aRNDo6MUugq41DXNTx//O6rLJU6/NsFcQKC1Z5BgaJ6H7m3m6NkoswtxspqBxZTTCVHUBH/3+Q+xtnATsj6H22EwNjFKNJ0iE5bJzsUYa08wPzdKZamX2poWipwODJeDkKgQiVQRHgshpXXE8DweWyHbqya495ZNXLjQiblqLWqZwcxYlFLrNNs3fJ66RhMTM32UFFcRnllACyTpODlAZLaAts4LuJ1uJNGOgYTFZkbJZK8wkItc8OV1BCRJxiSLGIaILMs4LTYEq4tjp94iHHEi2eO4vWU0rm/A5V9HBDfd/U/jkWCk+wKp5NucfeEbCLFTdJ44i2Azo1KAy6nQ+uJLjF0aZ7DzEibBTnmxgWqKYJZt6HoWTVNQtQSSJGG1uBGFXO3RZCaDxYhy7p0TORtm6Fcu75lJXOlNL2Z4/iqPfbEv0POslytnBbnZjICe56GDKR8QXaz4nMPHc1DGb26e/yvDUilwXBCENuAs8JJhGK8CXwGuFwShHziYX/+VLZtVKCouvFw0WXQiKBp/9Ue3UFmoU1MuIekmMrpKKJIgnDBoHQzQ2p/g6oFVEAQsNifRWIqSIjsWMU6LX0AwpcmKGitWyTQ22IgmdIa65nDaxknZs9gcZTzx9ClSWfj0Jz+CuzaO3Z0kpIQ4cmqedRuK8evVDM9FMBxlLMTjPP79n9N2vhPJO0P/VA/pdJahs0ZRJAAAIABJREFU4SnCkw52XLOJeDTI1Ngoqq6xrmU3l3r7Odp9gcLiaiz0USHrnHxphJ1bWpiYnOLiu8Pceeca1q5sYTLewCtnznO+/2VWbttE/fa9HNh1DXLIS+/FWY6eCPDEz37MyNwktfUb+cXTz2AWFfp6ZpmYsfHWyQhPvXyGjQ3rOfLm65RuXuCxl99iMHIOD9eiJrdxtvsiqnmOzQeaOdaT4NTb73L+xPPYbUHW1ztxyFlGRt+hqDhMaG4Bq1GIx1mFPSwTi0RZsdJPMDlBmdtKoTRJxLSe1eUwNjxGefn9PPSBu/AUeOgamCCOi/FMAYVluzk/3svhUx1ECTIdChAVZyksUvnXr72DJlnZ1lTETGAd9z6wk8BMB0/+4PtUOqyUeF0kM/N8/8l/p1DSMFtEqtduwqxE0bMZGmqrEQSZ9o429MJhnj9ylCPvXGL71kNs29mCy5nhtdfbIZ1AmUjypc/t4v7bN6AVlnCmb4ALb12kdWCY/TdWUqkF6TzcQdIkkDGFePqtJzlw41qqPCpyOIG0EOH1Hz6Jouu43R7kbJJsKskrR86AJGI3iUgmO1//9hOMBGN4XSJuRebO+iYevO42ZhI11Ja76e2fBquIkjThKXCxbVcdz794mJtuKWRFcRnRBRtrG5tYtamZkkIzE9ocuO1YKqoJ9kcoL9ewFajUeKxEEn3IiUsE0qOcHNaRKlrQsjGEgi0cP3GUPXsPMTUzjSjYWLWynpQeoGPuGPaCzaSDc5jmjjBz9OvELj2HNvEynWc/g1MtYHpimNYzJ5ANiXRCx+FwvOcZXmSNLXq+kmwiq2hkFY1UJouamOTcy28gaVW4PW5MSgWKkUQXC9ClEJowwZ0f+AJD8230nX+cUGQdI/MxFMlFONKNOZ1GVmPMjp0nkDjPROQ1ZkYH+PY3P8PKNdeh627UTBRTWmdhKEjfuX5EQyGdjGC2CEzNDlHssvPi09+nrNCPIKXf1xb9Kvx7+ee/Div/tS1fpk4Trlz+s33+pw25YRhDhmGszy+rDcP4Yn570DCM6wzDaDQM46BhGAu/ri9BFJkNhJHNllzFd0ll65oKbAzjc/o4dHAlWkYAQcFuNbNmlYMav4GWUTBEZUlfZdEr14wYqbgduytFy2qdihKo8rkIxVz80z+OcvrdAOtWuSmtNfHgoXvYtkbG74shGJMUGBau27AXlyIwMR7EZSqioyfEiXcG+NdnjxJJVnL6+Is888oRAguzqFmVzfXb+fRD/8i1Byq49pZrictBnvrpOVY2VOEp0PEW+Zme6yQT0SgrXYmvWKSyeif33v+XPPK5z3D4dA+F5bU0NTWxueEAbeeeJD57HFfGS6EtxUp/FUpoAD1Vw6Zra8iay5hU+rn1/o9jtZTy3HPHCIYl5mejlBWXEZ4PUuiyMr/QgdtZz4cfuYVjby9wqH4LqAZZyyR7D5QQnr5EtduOWYekOE/F5mJq6rxYbSUYlmqGLgQwZ5zcfdODeO0VLDjNuCslXu/pwWtVyc5N4PWUMD4+SUYq5KZtDk51hhH9Hn56+F949vBRIrKJaHyaYXWIwjKBk2efwyZmCbkiRJM+vLYUD3z0FqaH4mza52R84iVCcz6236AwNNhJubWJ8Nwr1JXDmrW3ctvuj7Bryx7+46t/jmiW6OsZZ753gsJSGS0dobP9FNFQkNajIYrcKTz+LO1db2OjmA/cfB8PbdvIxd63+Ngdn+RcVw9v9fZx4fA5XhgZZDqs4RN9GJEmNt6winU7bqKsMs3hNw8zO3cSp6WI++/+BIJhMLQwTUlJCamMhk0ScRdYMYk6breTupoSZFlBTQeZHrmILheQEGVcNiehmEDUEFGDYcbD84SzKumMglUWMZvD2ItEDLeZ7gGJutUrSGhBMkkLxaY6tm48hCG56J4NEo2L6FKGvo4emgrX8JdfeIw/f/RLfOTeDzHQGyAjLxCencHn1DFFOrg4EuJ07+uMz7zEhZPfJ5108om/fQuvvJupiedoapZR4qP4bAqB+AD7dm9FjzmprhZpH3iGmjoPmFI47BY07b3BTEVRkGV5KUM7HkvkoQ+RIqeVSz0zbNlgY2h0iOB0H89+/2sEh+aYHI2yMB4nMuZCEb185JOf563Db9Nx/nsERmZQaebu3/krNE8RtmIzJ19+g2sbNvGB5gYGT/8HN2zYiJqY5vybbzI28BqvPv5vdBz/Ct3Hv0U8EGV6eJKZwQlS8wnmRzoY6Btk1aYNaO9TRm25AX0/Y3o1VPP+nvqvtZu5JCed93DMl5/jt23/LbRWvvj3f/c3oiAjSDKGqqBk4PbbZfwFLjxVTqan5zjbkcVsySIKBrffWEqhJcbYUApVMqGql4MwucQAE4acoamuisbaWkqKPVxqmyeoRjGZLYwPWaipL6KrbYxH73uYN989zcZNRbS3z2AyXDz1vV9gKXGx7wMNJKf6Wbu6jo/9/sc5fPZdLp0a4vaHt7Ha34BhDSA7deymAubVs5w/pvPCcyco9Xm51BWivXUGb3ElYWWO4+8OMD0WQVE1BgZ62bJ6Jx0dpxkP9yMkFGzpVRQ4x8CYJxJdw3RkiGBqlpmkRGGFmYWFcfrGu3D7qhke72ZT82r+/SevEgsluOsDG5mJJOkfWiCV0ckaWSQxzb4NOxmPv0kwUMD8dB/n+nq54dqb+PFrFzjTeQGHrYC5QQgER9myq5KOzhiNjgqaah24vVYWFrIYZpXTrSdIpgzUhRBlHieJ+AK9oyqxqIMd11/DaH8vpV4Hr7dPsL5O492zYZo3bGKiZ4DJ3nHMpU42lNTTMT7JSu9qFqQoe5rXkLJm+aMHb+XVN0ao8UNCnabRu4H+2VmKSqJcODeJd2UMn70Rm62Ec20BduxsZvM1+4hOjBNJTlJSWYlLSjMQKmRsuoeoksHrddPQ3MLZM+f5h89/G902Q3v/CGd7xwgvRPEUFfNixwts9u+ma2ie3/nQPTz2xGv43FXsWb+DQm8ZLmuctp52EvFVCPoQVqWS+YV55mZ1VtVVQY2HbDzF6EyKSCpDKBpBQMXuLqa80MXE9Awjo93YTUk+uu96lFSU4JBI5eYdtJ69iMMLr7xwFlWyo+k6RQ647/6tWAoLOXm6C4fDSk25n+uv30bf2AwL3TPsPnQrE+NdDIbbKfd4mQ/ouJ0yn/vY73HLnR/B73TSPXGReHyOdWt3EgxMMYsNyVSNvXQ1yUwJH/zwX3Ohc5Iiv5P+U1OMJd9hrv9VJFs5gfFWZoMZvGv2MTwzSf9YD7VNmykpvYZSfxMIEulsHLvNgqpdVSIRYalo+sLCAkpWx1VgwyQYDA92IafmeKk1iD73NpFgGxZbLf4WEy11FZx69csMtz/Fm8+/xoX2o2hmCxvqLSQkP3NTETqOfpfNvs2c+PH/5hO3bMCKSDQ6SaRngPHOAc5eeJVyl50LHReZGp1HtK+gYvUOZgfe4NSbz2GkppgZPkdvZze33vVh7BWVWGRrrkrS8mv4LbzxqzH239SLzh0v5r4xQbgsX7MoZSNcqdr47X/96v+cCkFf/Ye/+Zt0VkO1CAhxuPV2H/6qUgb7oG90hLaeYQpsGuG4HUHVUI0EZsnGZ35/Ny+/0Y+gW0CyYugpDN2CbAFBFRkdCdDVPc6aLSW0XxhHUS3ogoFOAt0scGBFOYG5SXpHAkxNKlh1B7qWYiwosnKzl+S0gCpqrNm+gqzg48Daej73uWt59E+epqlOwOdbSSo8zeri9Tz/4gyvnu9i//5KDNWPzRlDjULK0OgbCrLCX8Sd9+zmzXcuUuy2MzG7QDQ2T63HzPD4BL5CkRv3HuInP3+BVbts1FRuZ8Om7Zw59iJFup9oNoIsO/jxL9qparRw8lSAkroixFiWi32jJBIaq1aWU15RxsBMhJuvX0vrxdNsXrufQnsRO3fuYWDwAmMT42zeUY26EOTvr7+LqWwvMSmD03MHZssU/moJXZ9iaEwhbcQpKazAbktgLzTYunsFhuim3Cvxyhvz7Ni7gRdfeJ0bDt6Ow6Rx8EA5NRUHsFnNNK1wYrZF2X/gProG2xkMzlEjlSKXJnHbVRJZhfmpcbz2akaD0xSWmJkdShI3eVlX5+HchQDWohLWt+ynyKQxGZxkrE9lIaaza0sDwfAMguJkZiTBlkMHGZ3uIaqEWVd7Ded6jnPXzjt5p+9ZGgpbUMd68Ts348DFumYzjsrVWNMyQWWW/s4QrxzvwuMspKWqnr/93hOMzbRy6Ia7SKRCVJfOMz7eQyCsUV28i6Y6mQpvLZ7mZk6/+Q4900myGZ3Y/DTr1zbgdDrZvWs7bR1dRNIBnLodf9Uq+gfnWbl1NVNjg1jtZk6fPsdCMkU8Ecdf6KDY76GkysP49Gm8vtVMTMzSOfgWs2MFlOgyamiBx595hW31Rcw4XTjC0Ljq/1D3nk92XeeZ72+fnGOfzqdzRqO70Y0GGhkkQSQCDKKoRFmiojWWLHvkkuw74xpTY9Py2PJolGxZliUrJ5JiBkkQJDIaQKPROefTJ+cc9jln3w+QxpqZW/fO/XCrrnbVql3rH3jWu971vL+ngf01LfzirWe5fn2e1dV5WnYdYLhOQzjsJlPK4dDbEMU0mayWaHoOm9zGzh3DjI8+iyCbQJF24wtbGOwaQlCa2bt3J55ogpR7Ak9YyYH7Po1GUYHOUuDt86MM9vVSkonkcyKUBUrFIkWpiEppo1BMI6DAaCxiVZb5yl/+CStzE6hQoZc3MT/xMvFkFFXegVKroJCwEMqJ5LMFFhbeptpqJeC9gl60suYRWF66yR996Cy1rGMzpFlZusv0UoLnX7zI93/+PA1tzWwEYnQeeJSF2V+SjRaQZDm8wQW0sRCxTB6jukgsvsDi3Zc4drCala1qonEXMpkGjUaJXKGkjIRSUFCW/tf83t9ev7nx/2avlMsRyyVk8nsDRIpfR9RJ5RKUC8gFNaViCZVKgVgsUirdQ9XK5bJfI7XLv54Clf77EgTZPbeLcC/8+Vtf/R0S8v/8xWeerq81sccM+w5CV5eOjaUwnQNlFlZ02GwlunpbGBv3YzWbyRZl/MGHT7MdXUIeNuFPFkjkMyiUIEgylMoCuXwJrcZBNp8hl80gCQI5UU+JDDLJRlwsMuvysWu3BQdZNhNZVKUYdY01aOu0LEyGmFwN42yspMGhZGXiLvp6Pc8+/xKlVD29e5TUVg5jsXfzxguvMznvwS83I6RdnD67jxd/OoVoFakxN6JS+5ncSlOvLeMP5ZCptHS2aXH7NzHbzGRzJSqbBDb8m8QLZXpaWhFzEfy+SYSiCmdLE9vuEIH0BgePdtJQ3czQSAUzo7OY7Bqykox6Yw3+hIikFFApi2wvxXGYdShyadQqFdZGC67lGXYN9JOLlehva6Nev4tZzxxljYM7EzfRyw2EvUpWFhOUBYGEmGRmeo6aijZ62gbYXovwy1/dwtk6SJ1DwYVrE7R2W9jYXMLt2eTI3jNcuH6VZN5D0BPkzz/zF3zrh99Ak9bwwJFdxGRzeDdj7Bnah88bZN/+XUzemaSsU1NMp9CZlawur1HdWoHVaqDZlmZpYZTp+UWOnd3LC6/fxR/YZnx0g5HhLpKpALlIhGxURya3ja1CxUroFn19g9ycGqdWd4alzTkurS+hFWO8vHyFKuUQZx98mK/94Ks47I1sBJbZP9TKlGeVOnuRnl4rglRELldRKATJpvM8fOJjbKzfJSNM4Q0aONjdT8Gg5sXnz+H1hbFYqomEXVTV1PHQiSNsrK4SCaUJRX2gVBJyh1Fq5ISiKSoqq4iHg4wvuohEUgz3tKA2mwgGjFRU5+jr2cvbN87T22Wju6GDSoeOW+fv0lhj4L7de4noLXg2lmh0NhPLJ9lpsKNWW/n8Fz6L2g5za3M0VpooqbUIWRnb0RR2NVgcSnIxFVabiXg6zP4jp4gvp4lJCgRRi06VZDvfgKa8gpSrpFj2IpYENj2j1LU1cPnSr9je2sRsKyOXatCo1JQpotFpUco1oIkgLxjZXFqiqqqNn5/7Vz716T9nx3APgliiosFEo9OCw7iTxfBlnKoiyrKXcqmaZCqCw9KJtaqH40O15LMx1mI+Xvj6f2bxwkVevz7Ll//xn1mKbjPv3eDB+9oomROkxAyOpk4mtpYRy1V0dMiJr06zu62PKqcBlW+VnV0mioECzbs/i6n23Sxsj6LV1dOxcwC5UqJULiEI/+aR/n/yiP82zK8olf8H5pNYKqHX6smIZUx6OdPXL+J0tpOXJMqU0KruBbyUSqX/fjD8dqzevb/s38iRksQ/fe3vfneE/Jtf+6unH31Qz6F9VZj1bUzOrFPbaiTgUzA+uUoiqebupIuMqEFnVGDUiLz4whiBQJ5CskhZKZLIligXtcilDGVJj0wNopiko62WciaDP5qjULh3kZEriigKEic7mxjqKbO5YSKQi+IJFEgVFIgFFclEBn9CRywe5MTJTpaXJRord1CKhhje18I3vnMTc+Uezp27wsLaGmaDjrImStQP6SRoHRJjY2kqG5K01fdgsitIBtP07WwklgljKlRxecKNP5lBKMc5sGsXJr0Ck0lLIR/FtSUnk4px7Ngp4vlNlOU8YtGCa81LMqzi+ZdvUlldw6OdtQQCHjYyUaqtTqZnlmh3GtGrEnzhz36fhL/AnZmLrK4Vae/roaKqD4tZTyJW4OroOJiNvD66SG9vHzqrm+7+Njo7u+iur2NqdIvDe48zevMKoaif0dlNjh3qQyVX09DjoNFmpZAU6R8cIBrVkc8n6R8apKN5J/MzC0T8UTqautDWJLl16y5PffgTlAtQXa9lbSlFtrjAwK7HCMbv8qHTZ3nn4mUeOHOElbkFXOsJquy72fR7cMeC6HMy7I4Mm6t5yuUc+4d2Es+mWdvyU9Kug6KdVy5cJxMJcHveTTyTZ8F1Hv9ShKYmLTsa+2mqkrO+tsC/vPU6OnUtcpXEmUNP8PalV9GIVuIFiU8++R7s1WpGx69jMZXZ2fcwL7/xHAUB9o48jqOiDYdChq29hR/96FWcNgPLm1PMzbqQa+U025qJJX0YDRrWNxeRzGZQQ1GS6GrdRaXVysVLV5jfCNDd2kAqEaJnzwCe2AImVR0tHTIaG4+R8wepkDcSDi9z5thZNjc3sZgF+uwGroaWUJRkPFG3g87dfbjWvPzzc29QUCepl8W5s5kkLSYRS3oKsgTFggKrPY3FUo2hZgCFuplM3ktNxRoL01NISg91fU/ic1/ixMN/y8r5vyeUqUZZjpCPOqnbvRtdrpaOjgYa6g5ze/JFxLyE1V4BkoB3dYPliQ3mpi4yuNvCD7/zI8yKat588yJ6RQVl1zl6Kw08/9OL3J3/ARWCjnXPEulwhFXXOyTSC7g33ASj8wRdZj7ze6d5/44u3jx/mb/4l5fZ/9gn+NCnv8D+0x8h5r5KSdIx7Zqkp/EocrUVUTJx5l1PopFU1Ffqqd97FP+VV2nqrGXpjp+WjJwFRYKznzrLzYsBjp89Qb6UQCnXQlG6V1kXi/+DiP/fPWr+Zi8hoZDJkYr3QioEmYx8Lo8gZSkmfExcuUhTay+Lc5N0t/WQjpcplHOo1f8GJPufZ2D4df7Sb46W3ykh//p/febpDz/2MP/yxtsUchArxKmobiQSiaDVaKlrKFBlr2N2PkhttQ27Jk20LKEWiiRLYFKriGfl5HMFDh2yoSvHMBrM5MoSyWyCzt064gEtqVQSGUbqnWWKhgxNBiW//8H30N3az7prhom1JB0denY31jK9FCVWSKLRaVlZ3KTRsYPV7Vt4/Xa+98pVsiklouTGKrqoltcQkOWJeCSWgyUa++QcbuvgoQcquDjmJiG6Odhrw9FRjSKuIBzOcSOwTnONiZ1mLb3OPUgyA6VsliICqaKKA4dOMzY2zu7BI6x7p9nT8n7WtuexGApsrAjoqrQk4h4Mjiq0RgNnh1u4vTmFhJL+3g6isQBIKXp6d5JOQd+QipGBdxOK3MZeGqTO1kC5Io1cZUOUKYisrXPm8CNcfGcGsWxke3uTvFpBQeFBkuSYtFYyyTDNbe38+NVJlPIwwThseNYZ7D+MIEuAQsH4zbskYknaO3Zw/e7bRFIFbt3Z5sz+g6zMjpIWo8gx8tTHT6KShvAGZrkzkebm5XdQN1ZQqTQSLOmxtKzx1KPHOPeLCTKCgF6p4+KddRQGLb6QhwPd7bQ7qwl6vCgFAYdDYH1zEbPTQrvZwdjyTT6+4yRblQY+tffduNNebi+KfOEP/44f/+BfsbWoWBpP0DJioL3iFEe7mljw38ahM7N3z2NcGn2RhdspfOEQte1VXLrloa3+QeoqJTrrm8gI8MaFMQrBLZJZE70DrcQzEm21YLc1Ue2wYndYePXGFAc6asmlJRrqu1lcmWFqZpFYroxNI2Fw2ImkcywvyGnvKrI+72FsdY2O+m4GhwpMzoaobh/kkN1MJKei/VNf4KiQ49jhB9Gd2s2dX7yEpIvy0UcfZn7pLgnRSFZTRoaNvDFF0pckr84iV2pR5h0sbb5KLhCk5B8j5J/BKjRQttlQhVV07uhj6fwXkdWO0FRbwNpyhlxpEqOskbcvfY6VpSt4fSuUEu2cPHOI67fGaGut5M1XvkF4a4pQKMbinJtY4ArJohtLMcrSnZdIF3O8s+rFJPdycKCFjYwWlawOuzaNRS+Q8CZR5NN840//lGZDiTXvJr966wI/eOllho60ko+scNcVJ7j6Eusrcpr2fApdyUuxlCMY1vPBj/wHNFYrDU4nM1e+zfxCgFQxjnNLQc2+SuaXFDzyzI8Rkxok2TLW6i6MOpHJ8WUa6uuJBiMolEpkit+Kkfy/qMp/W9DL5fK9tlIuj2/bjdVqBUFALleQi29z4ZWfYzNa2TGwg4XxS7z60jkaW3ais6jxer1YLBYKhcL/0muXpN8EeNzbf+urv0NC/swzTz89OCgjE8+zuaWgVCrg2vRgNmqxKPJ85g+OUUyIfOqjDxELB9kOeHn4USfFRJFSscjpI60srG+Tksn43MeHefKhvdydzrJnr8STZwYZrlGTKW/h9RsJxePotEW66q2oVGV+9uY0NybfRKXRUd8g0l6t40+feoSrq5dw6Cv44kea+fkvM4R8Uxzacxy9PsC51yM4Ww30NpT5r3/7ZQIZNxN37vG2dcoQj9zfwNLCGEP9gywtL1BpqSAVj/PGax5EKYvbHef+Y3tZn13kiTPvZ8v/DifPvpuLUzdYXwyjUWRYWd2kqcXCr164RoWtkYnZ71BWWbg+4aO2ppHZqXnKMh06pYjHJ2FvNdBUa2FqPE887sauMzGy9wQbnsv09qqRyzuZm5ujkDXiCl2iwi4jm9nEXLWPsbGbaGjm+VfeIpRO4g0EiEWSTC4v88UnH8YnKLg0tkxCrUPcDCPXaehr7uX6zds8fGCE85fH2FoJU1VVx6mHDuF1bRMOpBnePcyNa3PkJSOL60GSigxdHZVk8gIvvHSH7eAyjTVGoqEQEVHkcG8XiXiZwHae0HqJYCBHMupDxMBG0MPZ04d56qmDeFzr6BR2SlIAlU5LOg1ajRW1scSdySVW3F52tpmo76smuLhIvqDg0sRV5lfneP7NF+jrd2DWNDO1PM/irSC/98F+nrv6GtmAnAq9yPTCOULhOIce7OHW0gLKkpJD+3vQKEJkMl7amw7w9s9fxpcMo9Ob8ZXkjHS34vau8/iDx9jZ08D5828iVxpYm79Nrqjj2MH7iAbdeH0eotEUZgWYzFbMNVXkymqy4hZpUcbgzk5O7R3i8uXzuFNaHEIFya01OpXdNDzxMHKlgK5hJ8mAF6XGQVP/Y6zfus71hUmm172EM1EO7zQxMxOgu6Of7ViaapWNdDaHz79KQ00dUsaPvhzHnStRKEBKShAIz1FlHaKjoo6J7TtsBCxEvGNQzDMx/Tx9PU/RUNtD0G3jkSeO853v/jnLs7fYXnORL4hEsyEOHXkf0zM/w6rRU4ivcaS7mbQQoRjwI0sE0WoVHL7/D/nVz5/BqMwiKQXUch2P3fcQ/Z29vPLaeZ5/7TxvvP0K/kQYm9NGCSUWjQ2zLknK4yGnSqGS3MSTa/T3HCeTlygLWTYmRpm/8xp1qgqq6yrwrMeZ206g2XEW58HD/Oo7X0Gt0rH3wAOIJShkC0zf+CXzo7fJxLdobh9GUBVBUlAqF+7ldvJvvXFJuhdBWSqVUavViKUCSlWBxOYqy3MTNHUNUiqX0GgTJP0eLJYOmnbcRyK+wcWLL/PkRz+L2monHV0mE0yjNehQqLT3hFt2j94qk//aRiiUECQJARn/+LvUI//2t770dH93O13DDlyrQfaM1JDNBHns0SY0ZTnK2C4uzZzjuQvTpOMZHFbwbmhRaEJ0tncTCE9Rb7fRVOtgeirAV75/l82wB+9Silg0wNhEnLJQJhpT07+jDaMpgFUjUhKyFOU6WurNHN3fxtbCFlNLCVajS3S3DNPYEOehTiUvTW9ydM8hsukot+fCnD5mZ3ZlnS1/nm/98Fk0ksSu3Rr+9AuNXLzo5YlTA6RLBtx+H3uHu1ibWOSJ/vdSVQMrXg+S2kBPQx3HO/q4ve1h2R3mwqUbBP1BjhxuYKT9U2yE1lGoBcKZBBlRornmIHdnrtPeWcuPfjLDQFcDiUCGR57YychBK6/+cpItt8jgSD3z4zFyGTnvjF4hlS1TZe+hp3cfWrWEN5pm9FqWmbsJNqJx3rpwg1Jmm4bWGIdPW9m9r4V0NoNSr+LU/hEuXrmFP13k6N5hfCvLTEfUHG2t4bXLNxDL99grRbWcz/3JHr7xz+dIJifZ03+MnOhmY2OTZNFPJiai08Sx2eogVklcXAXitNV04fUu4jCpELQlgmEZlTXdbIdmqbXXMzs2j8JcSTFXwqCTsNj01Ne0c/rUcX783Rfo7tFQEJqhmKSQElHojKzFAqiEHE88eIpTCsqUAAAgAElEQVR/+urzOJt6kFuMZORlHnv4JHlpnaGeQyytrpMvyGipS3P1ygRV9bWcONFPZCuN31Xm2P2HWJr0sKu7ncx2nO1VFzNbC4wtZTg2tI9vfu85/uyzv8fLF27R3NDBSy//iE8+/gEi2QiZRBCNLo88Z8dZp2Zk9xFkxSLZbIZiqcxrN+8iCXIioRCPnHmIQiZClc1ALg+UijgdKvzFNIJYZmR4hIYdvcytT7Ix8Rw1bYdQBzyoFdVsvPpjLCoBe4+J7/z0RSo7KjBYuwmFQzQ372Rs7Bq2KjXZ1CZSoYBeJ8Omq6TWkGb3SBsTiwGspi6y0TQd9QPcnPsOinyZktyJlIugVy0TzwsYZGrKpRThwE3U5UmuXf8VAf8a+cgapXgeZ+0wJlkFlY0y9u48i7j6E5Y3ApTzGWSk0ZlqKKojhN0RIusR+vYOEoh7EHJlHr3/NJfevsTFi+/w3KtXOfjoIAaHmqbKWvp3diPILFTr5ZDZJifJMSs11CjihINFotujqEoZ5LIEUnYKgzZJNhRixbWJVS1nWrRT2WThV7/8FzRSmNXlDZqd/Vy9dpOB4VYCwQ2qTXq0go7x+VWcLc2UJAmlQodSdo9AWJYkBJkMuUKOJIooVWpyhfy9QGZ5mmsvvYxJqaO5ewBJI8M7Pcf46HW83iBmR5KLr77Ojv6TmGv7MRmizIxdwbUYYv99R0jlfuNll37dfxd+jeQFfo37/dbvUmvlL//qi0+HI2tMTWwytMOBsyZJjWGA8dvjlEQ7XbVlevu68QYX2DtQRzwAmVKcct6IfzvJgYO9nDzSQ71dhrNey3NvbHF0oIUv/Luj1NUamVpbJRDWoVRo0Ck9vO9du2i1W9DLM5hNRk7d14agsiKTx/jcJz7NL9+ZxFlT5uzwYV64sURvZzcGRz35zFXs7MC+t4gVHTptHptNS9gforLKQCgUoGNHCWdNM4gSa64J2ip6efTEKb51/ocUSzrSxRz7RoZ5/s0r3PRsI8jzHOw7gcuzwYmjp5lfLvDW+PNMzfhZXV/i4Egv66suBEUEWUFDXszwpS8+wrPPXqO7xcTVMRdra34KogabyYJvIwTyIvNLCQSZEqVazdEjw/zt336NjtY+ljZXOHf5BoI5w1ZgkwdPnGJjcY2Hz5zCYt/FhTfvsLoQxOsLc8e/wup2BouoY3pjDX+8SCFVpJz0EqGORCJGcD2KxmjGtx3lwRN7Objzk7xx4b8Ri0isrcXQ6PTIzXKG23poVRvJ6wpk4mn6Oga4efUSuTTs29PH7NoytZXtrK6PkSvI2fb5qKxT0TgwiNmmIhHZoqXWyTe/+ws0WhWvvHqHQ3sGEYQSZl0FeqMSAT022xzvfeQ9RH0xTj/8BFNr81y6e5N8Jk3cn6K6qhvP+jo6XRadQoZOBa3dXdTXVuNaXkEMTTPYX8UrbywyHy9yc3qFSMFMLFOipa0d99Ym9/W+i5W1KXbuO0AwEUJZKPH4yQGivhhp8pSzcqKxFDKNyJGDx3BUVGLS3xOAmflZMskCWq0Oo6OCuJTDUlQS9HlJ5nPYq7QEIyHkKbBhoM3ZTGnSTcu+ASymPmoqY/zj018nF99i4OMfJtndyvee+i888+UvsTR+g4QsyZYvSA4ZZiVEt8Ls3NdLpVJHwh+mu6sFg77AbNRAan2dXKGM2mYjmoxz5NiHmbz7GqKYosImoizuwGwosBVOk4lPIZbSyNJWItEFhJIds1GBQpkmW9ykrJZz7dItmjqqyXiVqFNRNhMbWPRORpenCPpEBJ0KuTSFPF3P1NRV/vhTf8wLL7zBjfE7LKxv8/mnn+D2xAyhuAGbTs7qlo9iUUalRUEilWNHvYXbm4u01hgQ1Fre1ddJRiiT9XtI4SSTlaMqxXGnA9hrmtnRfYwrV75Gjd3Ju596GpVynWvvnKO5pp5sLEPWX0JMj7K5PEFjYw/RuJJiNkwhU8BktyP+2p6olCvuIWwFyBeLKGRKlCUZKEzcuvivSEUJjboemOX8L79Im9NBPuxj7tY4KpUaR10Pac8U4XSOhGcR/1YUQa1Hb65Brigj/cYtI0jIfgO1le49fP5OVeRf/29//fSf/eEuDu0ZweyAd95JsmNQyZkTwzh0dqrbykg5G3t3PIa9tgJBElh3r6PX26ipdfDWWxNcGHURzJV58GAHB3b3EEsusbWe5M3XJ+/lcEoi2UiCP/7EIWTRPG/fnOT9j38UmdaM0dzGK6++TTai4UeXXyKXTvOHJ3YQybq4tqzCWRtAVepBY5Vj6cigD9bjtOb5yNlD6GU5amurcfsS5JVyRnqHkFQGtKpt0qk2TCaRf/iHX/Lwqc8zf/tFmquH8RWukk5KKMomtCaB25dvs7oZ4zO//zhf+crP6e430Vyt5N9/9DN02Y/z7Z/+kLgSTGYZfV3VvPNOik+f3I/douH85VXqamzI5VGUJS0HDzgZvRambXeBD77vBLt2d3D7xg28rhIzy26C7kkcZi0OW5rTR3v5yY+vsOf+Hn7x4nUElYhGU6a5vgqlHEjAcrBAuVBmwx9HXbYgqXPYchKuQg5LBbRVOIglQkSSebbdSqpa/IzeWiKRFcFSoKWhEyEbQqPVspZO4w1O8Y2/+if+9DNf5vc+dhSdAWTYCGU3aaltYajJSWNrNQp5Nc1t7WzP38ThGCCdKaFVwY7mLNtLCwzsO8z6mkinM0MuXUEktY2ipCUhypjfXMBuHmJx8SrvfmAv9iqRfQN78Ka2ySsglw5z4vhJ5JowZWUVy74obvcm+4cGEBVm3KEU2/EsWR3o5CYO7K9HLQdDWsdQnYVvvnGBf/+JjzI2+jaLk8v4sLCzVksoEmVHdyOVBjm5QgEZesxmPdX1DUzdHUMsF4klknjDYZLxFDWOSqJBH1K9jqSYJpkuYlTIaGlw0NvVw64TB8nNrzK3dhd9kwGpTU1V9R8x9IkzyE1lXvjHlyku3GIrusLi4iof/5PP8fJzz6JIxbn/YDsf+6Ov8a6Pf4nv/93nsDlMZCIK6tpbuT65Sb6URC4oWIslkalF8tkgyYQWKbmNs6KKjaUAzdUabgXncUgOFNp2REFFo0Wkt0qFxiIikSWVFJHn82Qit/mDM0/xq5/+jGJpgZDHT76ilkLGC0KJkWolG4E0p08eY2dLGwcHh/jBj57lndE7FIQyu/ftJhJMoFWLhHMRhEKRglxFc3MFSwu3WA0VyZQSmPVNWFMaFoI+VGYd6XgETyhJMjRLQ3MFhniamqYmxibukssnOL6rD5tCwuW+TiEt0uosk3DP4JofheIqYm6Z9YU4Xt8q1TUWbAovF15+jaH9D1KUSigEgWK+cG/4EC1yhQyBFCuzV5l+61mkWBClpCSWiyOJaZaX0rR17yCWniTkidHX241r5RKpUonVO78kFdhCJeaxVthwOtsoK+8J9z3GuYRMkN0L0QBA+N0S8u9/52tPu9ZXEORFtlMSLk+QKk0bkdwac1NbrHjjSDYT4+M3iZeiFFICFdY6pqfnmZ0LsmukjUQQJpY8/OyVBbpa6xiujWOo6aGxRYGg06MXsjz53hF+8N0x5PYsQ3uHcAVW2dwsMzV5gf0HGnj9nWlaGho589Agt8enMVU1sLwwRzHfQ6K8TDw6jSbnxBOZpq23kSsT68iNctzeTdq7+nB75rh5ewGdpggFE3v31JJJO9DaKzHZJxjY/RgvnH+erQ0NMmSIWZFDe3sYGupASur4yg9+TtmipM0hcflihO98/xpp7TpPvf8JzBoZSkFBJhXloWO1xL0pOvccxBO4QneznMGhbho69KwvzyDmMpzat4eXzo3z9htzpDIpdLVy7t/bRcSX54kPHeKhB3+fq1cX2H+wkvHpSfQ6G0GfkoUFF5WVSRobamloaqPNWUkknKS13Ulel0YMRegdamF7y082XyafU2AwqGltceAOrHP5bQ89O9ppbq5la22L4w+c4urFGd7/4Yd54/zrGG37cc1eJVhOMpCWE1WY+PI/X+TYsdO8/MY7OOuqycjKSAUtL772MsG0Fq1ZIpgI8IlHHyCeKrLo2iRXdFDOxagyV+CNxbDbqkmn4uRlqyR8Rvp6dSDouTm1hUqnJhgI4t4KE48F6W8fYmp2g9HRBBfHVtnfIbC4XqarrYG5qTGam5pIinEiCTWKrIwKZ5n1xTQHDteTE+rZcuXIFlwMdj9Ae1cjb128yv33ddPZ3MrG2jLBgkQ2FGVoTx+N3UO4l2bIZousbbpJZXO8fWmanT2t6GvNSAoDFrWMqbs+HnnvEOFIhkgpx9C+g4z96gK9gw/w5nU33/jZGkO1XURuPY2zug5NdSeqK+fZ/dHH6DvzbhrqDUg9j1OXiPKxv3mLhj2Pkk1MMfXy91CpKklubtDZU0EpXSJZTLPtCVLpqMJiM1EuCCSSRhy2IkUEBEOeFZebolaJSWXGoC9BKcu+gd141pbobBkg5koTyaeQo6bZqWM1mCcSc+OsKnFz8g5N9Xq2fBF6mhoppYs0tdSwFS1SbarnrQsTfPuHrzPpWoRcmQ+9dzepUBiNUY1CpaWUKSHXa+lTari5Ok9tUz21lm68oQhdFiPX/FsYzErSuSyxoIxTB524EyILK5uUVEpWJtaRmUxkSinW1tdIlIsokNha22Z9M4rNbEChTBCJ5xBUMqprdmCr6cQmxIhmRSr7jmDTlRi/eZW12cvE3bd46+XnkFIB6mp3kwgVqKpKMPr2N/D78miMctRyC0qZmfd88s+4duWHFBMBDh7+C2KlWbzuRRYWrlOv0+MKazj55B+wsrpAU9tBlDoRqSRDKAkU0wKlYhaFWkmhIKCRK/jmV//md0fIv/Afv/D0Hzw1wvZ2jtlry9yYz9DakefuLQ8f+cAXef2dUfwLQYYPtFIKbuOOh6iusiNTCSQyJRJhH2lEtAoLoWSWOzM+bs0UeeXNaUKxFJ7pDLv3VFJfVaShKczI4D6CMYnXXrlBUbXJqVMDTE42kZWFsalk2AsCZe0QBSGDvbKJZOkOYsHK+GgAR5UCoWxgenGamgY7KDJU2DoIhZc5dXSQWlsFYr6DUFTGs89fxF5Zw/Z2GL2pFov+Nqf27UWuKWCpVqAzQEdnC/mcjMXQOkalkZA7j9akZHh/GzINZHIil95+k5IY4e74BsO9tczNpchothCzeQZ7a9k98CSvXHqL6mKGxa00H3/qcRbDWzx4bJiOZguFlMjSQoiV9TV29/fzxuXzLK+GyAlhpsbDeN0lHnhwhKXNORQq6G5t5ub1KWYnXDz6+F4ml25hVJrJpkSCnhQqtZpwIoUgsxKWirQbLazHE0j5NO0dlSjkCrwBF6mYglR+nr7+ShKBAn0t9+PZep317TyiWGY1XCQiZTn7rvu4fv02WlstwVSSK9dWCflWWPXm+MB793H56hhag42lGzNcGF3iyKERPvShk7z5+iyNtc001ddg1amJxJKYTUfRVk2ST+kRxTJVdVbEcga71UQsHuHg8DF0tiTf/vEdFje92CwWMhEZJ0908fq523RYWhm9M8eOw4MY1BrmvC5arFYeO72TcLZMMrIJWhWLkykKSQ+3J25ye3qRBpsNKROnvaGBdKjM4x87jWXvuyiuX0UhqLg1Pkk4mUam0iAhUeG0E82kKAkFyioZBr2ZTDJOMBBHR4rHB95H/0NtqHxbjG/MkolPs56M0zTwSSrMegyNe9m+/QMWt3X4LvwEhWjFPHSQpu6HCfiuEnnrDWr7D/Cjf/xrUkKMotZIeCvL+86044vJ2NlZhV6hQYyE6e2oxh0LQllPRVWZfNrKA3t34fO7yGRLDDS14Au62NrYwmGrY3ptmY2iyE5nPSq9glw8hkpfgVEKsxxJU19XT0dHN1I2jCuQIZ6K4YqKaAU5N67cYNoVQypG6N7RwNDeFlyby2hUZrLFHIFUAo1ORpPOQjwUxWJRseRNUF1hZG5jGYPJjjxSJKpOE01maDJUYlClcKVy1CrNzK1uETVoySajGAxW2tobiCcS5JIFBgY7yBcLNDY6kDBTSPmpNFWx7XdTJMpmII2UkEMMLM5mLJYMFfpOFMokek0b1doCE3MvYdbqmbj4DRr6P8XU2FvoFTkcBj3B+DQbK9u4tseYnypgqMgCOQoeC31DDqam/dx3/BTh7SWSwQAoK5hbXKC+uQGtOso3vvIJSFZjc9RRU1vmlZ//iNffeP13R8j//ktfevqzH3kQe0slP/zuBJU2HXPbSVo19Xzv7Z+TLyjRVgRQIOPqxSX+3ac/iFllYd/eXhbWXWjUSuwKDdOuEEd7HaxtxClqVNhtemKFLI4aO/nCFn3d/Rx78AH+8j89S06V5D99+nGKZQU/e/4W6VIU/6aPREJOCisrazeZml9CbyrQ03YceTHOwUO9zE3H8UWCHD9ynICnREdzM2ZzjsbKAZZnF+nsrMbZ1MjY/JuMHNiDXACKWa6OX2ZpNkPXQD8X7yyQj5XxbCUJRwS8kTDz19dJZSUSUpqh3m7GRzfYWAtRVVfB6eOHqDA3UtMQRk0V4VQaudaGVITlOR9RMY3BqqKi8jAlrZzX3rxBPAs3p93I5CJKjQlfJodOsLOwMUtsG47vq+etqzP09KgxW/RcvTyBSmmkXFZQFkUOHNpNqhxn4sY8gaiSslKFEFNg1OlYWQmj0Usk8hK1WhUEfSz50pTKeuLxPEK5jKPCgNOpQC2qCQdTLG/N0dBmpJjRc/LMQ6TFOJmon3BcQyC8wZ7hNibHV7EqNAz0Grky7qaUgWP7u1me89My2Ex3dyu7drfTUNVGIaWgqa0am8aJx79OtaMarcFKKp/iRz99md6BXm4v3KHeZKNUVlMUJbY8EaamExSkLXQ6JUFPnMEeFaffNcJ3f3KZMw/dx4rHj81hpaPbxLe+dZk6ZYHe5g6u355AlMWpr23n6KER9GU1G5409+/soCwU+cDxJ7GZVNitTt4cf40D736aiH+DnH8TtVyFLxRFZzEjl8lYW9sgpxLJF8pIJJEhEI37qapqopQXsVhK3LzqYmhgH6PXZgj5wsxvhGnf2cneI7sxL79J9s55LJ/7Gj19Z2lS5pmZvUhbJgpdB4heu4pMnedf/umvOLhrP8ura8z5A8iVRbx5kYW1LWZX/Wwn0rS2tfL66Du01DcRj/iI+lPU2u1MLY3TVr0Lo5DkVmCJA709eMNb1DrMZAtZjPIS9+3sRYpHCERDFHJp1EobUtyHoLBTDJbYSHowVzgo54vkUnnOHN3DuUt38AXTPLDbye49Bjz+IiaLGbPeTjSwyY6WDhr0SuazYaLqAolABoWmSF6WwSBzYDVnqJEbKckNFMnTY6/m4pofrUyiTm6hrNPhT+SpKRvISFmKMvBt+6i225AJZdzeAgZTJ3J9ExaHkhu33yEldHLs+FnGr/6E4SOPodQYCLg3EFRW7ky+wNTYOo0tNaDswFInwz1xnfn5ZRx1TvyBScLhLAYdGFUVBBY20KjChOIKhrtP4PfPkSpGURm7eOyjn+TO6HOszI2iR8bdiQWe+L1PkkoFySdEzHojt2+/QU93Oy899xKPP/Z+vvr1v//fEvL/L6Le/l9/ebFEURHlwnNzaKsEAqEMpZzIgQd6aN9RwQcfH6HSuJu+ZhOf/6Pf5874BLmUxPZWmN6+YQKpJCUxRblwz4NeabdRLJdIhzMkY3KCwTT7Rupo66hlee02n/38w/yHP/kid+fHGNx5jD07OzFIIqGYRDQjcPXyODIhRWdHO6Gwl0tvjXJnMszUnB9faJugN8no2FUWF5dIZ8tEwllKyjAVzlrG5zZYWgzS1tbG2kKR5aU5bl++y8mR92KqyBBIqshkS8hUBeTKImpZkdZ6DX/9N2dQyVM01DahUMiIh2OYjAZGr6/i8WwzM38dm6GbxeVV+vv72ViKky9HMNfA7YltRq9O8OaNBbbWYySLIsENGdGQn86WTtyrKTxrOSJxN70NXbzrsZ1YKwwM7bEyMrSPkDeMDIFkPEk8HqeQV3L50gLzswnq7LUIpQxzcy4MDhmZkp8Gp5H79rVhU8hwqOVYGirpb2rAZjeikJXIJD00VtZw/8gISnWOWETksdPvZ3Ntlu5KOP/WRcZnlvAVMgSDXoplOzeur9HQUE+8kGfTFePI7gFMFi3GCj3HjpxiacbF1SuzjN8ew7U9h8u1SVkSMRoMyNVqJJmGfF4k5NrmsbMnEUWRemcjd9eWGZ1YYGF5C7u1Hk/6Fjs7jnDi2A6anTCwv5e9bV04rFnGbrtwh4vEc2WWF4I88chhHn5wJzExyXIwQswnIBVMVNZWMb+6jUqSsNSq6elvZXZllvruGrS1Wt7/yCMUZUqKvlX05no83jCCTI1RZ8bhqMJoNJLNZ++NYpcKaOVyKqssbPv8qJUq6uvr6e3pYeKFlxna1YSush5zdSVSAfoHjmE98mFkyW2UhRqyMz8g5CtRc999bLlDJKWLfP/7L6IqK0nI0oyOjaJR2elt6KapwsLcjBc8eeLxBFV1tdwem6ShuZdoxE9PRz8qRRa1IOc9Zx/G7VlD0GjZ2VBDPhSlxlJJ3ptGm0ththiZ3diirqGdjXgSULAeDNJZ2UAiHUIhzyPks7SolMQ8UQ4PD7K9vkBBAI1SydnHRnCtpollvKxuhgmnw5jMZkLuEGqjEW1Jzc5aGxqdQGVbDXucNUhSid7eHYilHPVVVpQKAU80hMaoxRvPY9aYSJaySKk8KPX09PQQjSWprq5Do1EwtxzG68+gEGQkYncJRqM4KmtJJApsrG0gFBTkMzlK+RDlVJCV6TGkbIBUcIVMaIF0Js7d8bdIR26y7A8gJmMUS/XsGHqctv4hltcWqHQWkckEirkkHvevCEc9FEpWpKyT7Q0PIwdPUJJpKRTLDA7uIB+LM3PnAtMTl3j7wkscP/0Qk3dvcOLBU8wtTP1va+j/LyryZ555+unJ1WUG648ztr5BtixSodbwyPuO8uILUZb9Yd55NcTj7+nipXMXUdDJ7mErl8f8bIkqEovdyJ0xtMkYOpWJsGRBTAaRy8Bk1BApKFDn1VRaJYxaJ7eWp1EWtVy4GkZQSeQLWazaOsxVHnbtNvKxR08hKuoIxNxosgYCsSKz61kUhXXqGlT07TyKGM3R3JhjbG4MhaqHcjHL1at3GTmwh/npbZqcHSwujDI80M9ArxGndZ1saYiSrEyFrAWjIYRa4SArRsnEc2TKQSora4iF/Xz042e4ODpF3y4d+4Z6mF6PsbmVZXhfDaePPcY3v/1jtrJhunoriGcEiuF13vOBDxCO3kWGHoEoGruaHQ0V1JirUKVXUesFDj6wlw33Gm02G69fv8HwrjMUiytcGo0xOSVitajQ6Qusb0bI5hUMdzYRDKVxbefo7KjCH/aRlyz4YxkCvgRVUhF3ukxCVkIUBWorCtQ3lfjY2c/Q37qLr/zD1zFUammqc3LjzlXKSQ0qpRJbs5bDPbsop0ocOtXH8kYMfzRNbY0Vt8vFymqSfDrBwcO1rMzHCQc8pHJ+3v+uJ5hfewdncyezi6NIORPxqIBWyKFS6ylIChJFD9urfny+NcYm3NgdeW6Mi6iFPBPzEdLBGBVWK6lYiWg8g2e1QCAbY6B9iI3leUL+Tfp3dSLm1zi260EyShlFwUqqEKertZlrN6KMDItcv5hCLsTo7W4gtphkDSVHHz6JvPEwUz/+CS3DOxEqVORXlklky2wGfVw4fx5RFFjwujnUq+X2eBSNNUS3/SjbeReVRQlRluP+mgH+/tnvcd/OJ1lxXeb6rRWa651IqSQnPvxhhO/+DTK5Bv3wA2zOfRujvIOCa5uqR59k9Acvo27QMz5zE4XMSyiepr42gT9UIpYt0NbqJBB347A2k41s0Nbah9+9hlpVg2dzBkFtYbBLx+ZmmARmlCk38rwBuViJQqYgHMzS6mxmOebBFcvx9uhlrJYaUimJOkMN4ZicZlMBq7ObOkeS2EaeeDFLZ3M3JkOIK3fj2CpUDFVY2ErlkXQOymUv9c42alVFIjoDoiuGqSywFsySN1lRpmSsZjME/SFC7jh1VVUsxbawG2zki2o0CKx4N4mXIStPIRO0bM6toLMaWHW7Mem11DmcWE0QTbkxKwWkQgSrTIU3EcFiipPwrWC2GpmfuoYobhAKeFFL2+TDMRpqTGyuBlGVtsgl5iiWDTjsNWikKJsbUaJREZfHg6AM4Y/6iRc66OlUUoisMDa7TSHpYWZlnB1mM9FIiZKxiUJpHk16m4hnjVgiy8kP/yHJ8CIRVwGZykQu66LBbuTb3//x705r5W+feebpslCH3q5hcmoZo1JBc38jX/7qFRQE2HOwBXc4yc9/MUogIEdfU+bH37tCz44E0TtpHnxQQyy0xp/9HyeYX0zQUq9lfD4IWjOSXIW6nKFgSvPqq2u8+72D/Pnnr3DkdBN/83fnmVndYHkzTUONmzMPDOBeTSFQZm3zOpGAhCBmQFBz95qfr//1Zzn3ZhB3aR0x56WxeZBozAzqErVVRiTkKBQVyDUKvG43LU19bLnHWZiLUTJZGBzq5sq556hvVtLd+35C2VFUOBELcba2A4SiQbTqSpYWV5FJecqCk3OvzvBf/uMDnHtjgogXrt+aZmSgkyNdbVQ69KzPxbkxHaTKFKfKsQNJbWZqyoXGaGDvnkN4oy4sVTZuLXr52Kn7+fjD78Pj8XHy4AO8MbNEIBpgZH8neoWMZKyMmM+j0xsQhDwun5cqpxKXJ0O1vYGmJj1uTwhRKpMTc1RUO/DnsmSSakrZEOG4lnV/nPXANC+8fo6Hzh5mZS5EuSQQiovsOdxDqpxl4eIMqrY+HFKULd8mDrMJr28Dq9nOw0eGOLx3HyP3mfjGN+fQ1Wi4e3eNZFFNpuQmGtdS22TDamqloM2jKddgtaQoiQpkyhCykhOlXoakUBCMzLP7wP109hj47ovvOZcAACAASURBVA8n+PRH9xKhzPr2JCqVgpPHD6C1+LlyeZlAOEtHl47aRgslKcP+PUd46dw/s+WN0dvjJJtJ/5/UvXeQ5Vd17/v5nZxz6HNO5+7pMD3dPd2TNUmjNJJGEkJIIAmQCBcBBmzAGBtjG96zwZhsguEShIQIynEUR6MZSZNT55xP98k55/O7f6BX5brv3We9er5V966qXXuvb+3atf/61KpVe6+FpGwjk9/gzvcd4crIFAqZnlg8znximWq4ijMVxbVjJ56uBmJBP6pMBnJ1Rle8pJMxBJmMmdUNHC1dNJh0NO5ux5nIkkp7yecFDnY7UEvbWCytcMtVA3h9QV4bXcJq0DG+EebP778TV6+ZYn878dA6as+NqAfu4Pw/vR+5w009LvDKyC+prs/h6Grh7IVxjKZGAuE6wXwMUYQ2VyOBFS9NbhtxXwCVPIHL3oHJpqLPbSOWiqOQ12i1Ktl3lY5z3gLBeIyMNsRaKMi2fd0k8xLGVyNoDSK9ncPMzc6ye1crwWiA4Z3bUOLnrbE1XJ7NZNJF7rrzDpZXr/DSyQWSiRxDA0188mO7efzMJMVwHpvOQCTl5eysn2F9E3EhzqEDQ0wsLyARNcwvb7Dd1kaqXkSqqVAXpKz50kSzVSqyEv5gGpd5M5s8RrLZInqbmqaGLnK1KDq9BbVKS7mUY2t3JzW5BK8/QoPNQS6VJhor4LA0U5fWMRoMNDY2s7C4Qm9PPzqdhFQyit2hxON2EUt5CccKZDJxink50VgYZ6MaQe6FYgKTxEQ0rKXHXaGQrNLY1UG1JHDtoR0sLi/Q2+3iwsWnKAbTNPTczMz6ErPLEfYcvIGlyUVa2wZYXDqLthhAqRlE1rGD3/78u//7gPwfv/G1r3/nLwcJZ8bwyFwsF0pUMmnMEg/JSpSm5gZ2H7qDK1fK5AsRJmbirKVK3HDnN7g89zyrkQBrq1XGJ8e59pp+zpy/xH+5dw8XTyxSr+Yp1SykfXU8LgmvH5tlLVnh5KkNBEkdrVyO01YlEqlz7Mwyd997iOlXF+ne3sLZt7w0OPpZWlkAWSPaWo6x6VHKkhy1op1EOojOIvD26UkUUhUHrt7Km6dOcPzEJNdct4Nnnn6Se+/6FHJ9gYpGw+kTR7l52wOcuziGUjeJVjbIamSZWEZKyJfF6VZh0NXJxxL06Pt569wV2rp1OCr9RHSjbG/fiyI/D6KWEf80634Dr12Y4M4btoNCxqh3lOV5Px+75wBdbhdnL55hYy1CIFAEqlApk6rB1HKCx15/HbcjzP6rjvDIb46zHqmzua+O2aolHqsjikqKdQUtHXq6uwbwe9fwOK2EggWqdTkSmRylWkKxJkNWybJnp5abDjZQz0uZmUuwqbeVSMyLyWkknkiyb1sbakFLPutn+76bKC1MkLHaObL/dqwmKx6XlkRyGo2+HYMjyOvP+6gr0rS3dtJi05PLFUiGQoSCWXJRNYIsxMp6FLVGi0FiQyAGNS2CtEQmJzK9MsK9d3+YX/zwaabWo1y1S8fp01HysSiHDm7DH1jF4dTT17WH5blLvPeu/aQDAuuhDUwGKU5jOyqdFbNZh8NsYHWugt1hp6Ohk7n5IFJtBr+3RntHF4d3t3FpKcW1HS7ocJMIRqlEQkjDUUbWvFRKGS6ePonLbiMSjSEt1rBZi2iCSf78//wqrz67yFfuvQZn/2ZePrnGZmuBiBhnaaXG8PYOVLIG1lYv0tB9GOPFVzHt+QiKnhuJnv4e6d8/ydC3fkqDSsOlqcdxZ/XUDUpee/ZtDA4FubwAdgnNJjtypZr1YJiKVIJSJ6W9tYVMLU5F2kjEH2IjG8OfSuIo28joPDz+/Em0FS0paQVTzYK0CksbaTbia/T2OqlnchTEKhvhOHqtjUq9l6XQGg0OK5FCjUxCwc1HDjB2/jxvjpxixqvmznuGCUeTvHB6Gp3UTFFegKIBl9GB3GBArMlISgVK8TqFipR8AW45eDVjkXl0OhlypZ2llQ20BjmNegP+jQSiUkNdjBLOxkgmMgxt6yYZKeF0aFFJ1ei1ZgwqKfl8FrlKwfLGBgqZjGAxSq4iw9PQgsWsIRQKMTk3w65d13Lh0ptkUxUqlRoGo4pgKEsiGUWiFEjHRERiaHV6piemUUkMdLY4sJoFmlodvD0yikyrQiUYEaoR6sUkvZ39zC8ssPe6jzC6EOPqu2+iFvRhManxL46gzK6QynmphKdR5mpUs1PMnTvBGxfG/nNy5IIgPCgIQlgQhMl/p1kEQTgmCMLCO7P5HV0QBOFHgiAsCoIwLgjC8LsBud2goFYCc8XO1EYAkyRJMZbB6ghg0AhEQ0XmL4l84Na7qYop6qU8OkHDQz//S3LrFRKxCs12A2K2TrfDyLatHRx9epxtuyzYbGr6BnPINQrU6gqdLXn29ZugKlKrSihVJKz5atiNZtoamvnl708SdpUYnVulscfGuYlptDodReUG226VctcntjM42ESjO0WtVERWldC/xY1EbuHoyy8R9iewmMw88/wxdmzvZ2LiZQwGAw1yD3v27Wc6+jrv/8hBlOIATR0V5qe9ICa45tAurhreQ3ezkp3tg7jabWzfbiQVqdLcqyI8KWFx/RLNzXsYm1rl5Mkkr796gY6WJn7/6iJDg1sJjefod9t4+rFXWYwn2TN0gDvfcxNtrSIDzj7OT8zyyC9+z5jvFHVpimxSwdHXHuJDHxjgun1NhEJp3E2NaM0qkrkktWqKtcU04zOXQF5hZt5HMJyiVqlhtRiJBKM4bEbsjVrMlj00tNzIJx+4hn/94X3c/8Hb+eSHvkCvx83777iewHIQpFEMJhfnJ19AY8ji881yYeItnnz9MXzBME5lG/7g2xRqDWzfdRvdm5pxmho4f2oCnaFALCSjFK2QS+eYnExycO8wr596je27rkamUKNUWyiXqhTSCSKBJE+8dAa5TUVqNY1UZiWeClCXyzh7wU9Pdz86qY1P/OWPabI38cNvPsnF8XmEmoGliSh6fYRwbJXO1h5Gx8e58UgfE+OzFIsXGJ9aZXb2HCazgLtRRjy2TiyUJOfQoqKGp78bp9FKwqwgtrIKxRQDg8NEwgl2b93GTdceZuxKFrNaxsLEGl/5s+vx7BqkQVXl/gMaPvw3n+dzH/8nZpc2uPk9B/CFg3TvuJ21hT8S8IIsv0Hx+e8T3tigrKkjkZm5/Lt/Y891t/PWxTOshzI4B5oRpQbUpNAJGqbHp8llstQFiGVSpII1YusbVONO6gU1NXWFtfkYu7dvJY+PtZk3UDg2YW914mnvobXdCQqRcDnGzh19BCMK7BYtVk0Lt+w9QjwRRqW9gkJeYtkXpFKvcd2+fi6cfYVkJsbyosD1u2zEkxVK9QputZuqNIxBkFKsh0lSRF7P46/EqeRrbJSlpFIx8mKQhY0xrHIFMomayMocOr2KYklOyB9gqLMRt81MvRRHLWi4Zu8QPm+ISG6DxdUwvrCPuZUFCiL4M1mSwSDX7tsJFOkyaWn2aLkyeYZ0KobeYqAkFrg4MoZcWaW13YajQYdCK2N0doaWJjetLS3IJSK7h3bS3myhv3cTHS2N+CMZVhNFaqUsVq2etlYXorKO0uwmJ8Kyd5W1WICNlefoaMgz+vRvEasRWpo34bHBpD9Mc+sg3fvvIGMTEdx7uOMzX3o3+Hx3IAceAm7877S/AY6LorgJOP6OD3ATsOmd8QDws3dziUiqSkZVoijK+Opfb+Xrf/Uebj/czLnZFOm4mdHxFc6e/idefPErmAwG/vwzB1HqEkjqcqSUWJvLY9PHufG+I5QKQa69aRvDA1qK0TjZaIHRqQpNTRVieRXetJ1spUItX6IqykhVqmRLMjJFJ8vBEOfflDK3riKeq6OQKbn+sJvh4SyPP3gXX/+7c1wzsAe3Sc3113Wxd1szJjms+RKcHplnYa3M5YUafZtb6WqzsnXIzejsLH5fDr2inVdeOoHG2snDjz1JUebnlZcv8sH3dmGXWHl76ixnR85x8+BnGBrexenJF5meTOFs1vLQ80c5OHwVm/rkuFvtvO/WXu6+uQOLHEKTSarxJAv+Vb7zzz9k/w07+MQDn8chT+BbO8XS5Itcu+c6nr1whrnZEof3NzJ+rkyDuZPlxRQDnt34ImWypQVqZSkKrZmiWMNoNrF98GYikSTKmoRiIU1nqwe72UAuk0Yug9bWPhRijWgwwbY9g7xy9mW8SQmP/OYljp15kZWFi6QkVWo5N5YuJ/JkCU+jCo9jB6vJMg1yLdmahpIo57pdN6MwmYlEVfzhj6+gNU+we7gdi17gPffcis7soHnQQ+9AI6nsGsZKlSuXlpBKtXjXY8iUdVa8aygkRizGFu666Q5eOzFBSWFg00AvcpmT3iEPepcelVxLMljjhZNP0u1Qs/+aDj732bvYvb+XPTu6ueMjhzn2/FnigRALK36oxrh4YoVdW3exOg9qZZ57PvQVoqEyq4kxBrZv5tz5Kbr2b0Fer0O8hC8cw4iC3fv2IhHLqGolerf0UZUJTMw+i0qfJ1q18aMHn+ahZy7yk+8+xMSFFP54hPKpV8nnY4glKXNjQRQKGSf/8Ee+8KUfEtHICU9P8s2f/JRHnpvlufMnufiDX+A6PMjiP/wDH/zAEYzhCg1VDSa1ieHOw+TSGZotBtqaLMgkVVqb20kXi5QlNlYqCbbedD+FupvNBw9x5fQVtu/ax3bTFgZqJXLJGLm1CK/Nz+GvpGjU2lieXsGXjBJKFlldH2fXrhRak5NoRkOz0YJaoaNNt4mNqZNUyiIPPjnKHYeH0Kl0pP1BjAYTa5oo92zrQKox0W4wUqiKmPUFKoIRo0mkXInx3pvv44sf6aJLLiOWzpLN5nE2WGkQ1KCqUM/V8fribHh91BSNKFUCuWQeh0zGUKcG1HkMGiXNahnJYhSJtES9KjK7vsxOVyPpaJBM3kdns4lIOEElX8apNSKXpNApdSSSORbX11lcDDGwdTuBcICpK6uotAqm5qeYnl5HZbNyenIMfyhJKlXC4baiUOmIVeNseOPMzIeoa7Zz831/jajQ8NRro3gTfqYnL1DIaFlZvEIg6WJv57VEK1Vy6zPoxC3UtB1oVK53g0/gXYBcFMW3gP++Xdt7gIffWT8M3P7v9N+Kf7JzgEkQhP/wNtW6yD9/bxb9JjmCrIZOp0PfYOGhbx1BKkRwG2vYDCbypQI5UeRnv36LUllDNF1kOVHkpttMjG0YWLt4iacuBPndg88TDEdpcOtpbFIjo8zicpbhDgN2dZ1ApIDMJEOvLmNR1FGLVariAh5DO598oAmPZgOHJsu2Ph3FdJLBoWGmLyU4dMiO2WpCoxOY99q4sGLiiTcCpNIynNIMaqmWbe1Wzl+ZJB1NMn4uglqpRSoRePPyS2zZcjWRgI+N+TwjV86zta2RQjjErTfu4JDZRrvHztMXfkcm5+Ou6/6av/j8vaxHI2zb04xGM83NV32A504+zuTaGCFvmhuuHUQtz7BlUxuj584QTPh4+Y3TTK1exOTchsUzwNbd70Os+fny/Tfwhwe/SEmQojIYWPKmKWY0vHnmHO2dHmRSE8lSneOvnIB8iVqtxuXpl2jvaCcWqWIxmTk1MU+mUKTBZiToC+KP+hEF0OhUTExMcfT5OUwKF+vZDA5NKy8cv4R3yYd3/kU0NSOuzVtYm1WTyISxu4bwdPcyuLmLaq3Ir44+iaqmQ1JTUMiWefXFK+RTSo6++Cy3H+mingpRLW2w/eCHcZs285nPfx/kUpBnWNmYJx6rodcqqKpL1DQFzBYtfS3NxBYThFYXuPjWaYJzaWILZfYdcNHeo+PuWz7FX//150lllYRTBRLBKLMTizz1x8vEchpGx3JU0mb0zm5WYhucXvwVgwfd7O9vQ5Wb4xtfPUCbspnJ2TX+8m9uwHt8FUGjIrE0iVEpQyxXsVvsmC1utgwMopYpSfjjPPPsNJW8jbffvEIhmaEsT7K0EeXkxRPceu9drElt7Br+GN29Mp7/w1ECvmmsThXHHvwm88EIP/nxd5gPyEn5vQzf+CmiKgXu7X9G31MjuD/9ZYyqPBq1ka1DvUyFJ9jS1ICztZuptQCxVJZqJk+tXkKuKmHV2zh29HeUC2nGJmM4G2/jkZPnyHc14OzYTbYAdW2B/Q4zm00mVNIKMSFOo9OML1WjWhH5ya9P0q3QYpTlaXS72TWwBa0pjsTUxh+eHefInbsoSKr4gkEsWj29HgemtMirp2JIqlHsHTraLCLpTA5pzkumUqSYizI5+hKvvRQkLKrZ32YnFouQrciJVGJUczXkBiWJfBKDWU0g5sVscDA+t4bO2Ew+Lue2rbsw61J89M4DiPUi6niBbE1Cu7GDUrmORWmlw9iKS6FDJpYRxRxtbS3IVXriuRpiJobdZMSo1RNamyJTKdI/NEwyWcZua6QmNzI+uYpUVGCWC/R6rFy5PEExa+bIoW/SNtSIw9KALFth5tI4UxMrHNzzCXocW9A2tFCpLmGSi3S3Z1n3neCtZ59laXmdXHIBMV0jlan+54H8f2BOURQD76yD/KkRM4AHWP93+zbe0f5fTaxDXZbhR9+Z4ubD24n5Y3z4yH7+6m/foKO3g3A6R6kOdqsOvayCWlvFbpZg0ijQ6C0ce6GK05BgcqWGVBdi1542Oja1EwyJSCQSGh1y6gK8diGPL1VCXtQhiDVkSjkyoxrBomUmWCeZjvHWuVVKIQOnz9eplFxI5QmGe+/G1mCkp8vA488cIxSo4V8eZ1tDjnsONlOPpklWZTQ63EyshvE0uJgLJljP55ldd/NvjxwnlIixspQkk4nwxc9/lrvu+CKbe/rQ6nZgMBu477NfIVtIsqmtmUgpiS/3I5LRZ/jBn+3iA3ta+NLnv8XkxDR333orckUHN3zifbx2agqDE+YX4rgadvDggw8iVgoENoK88PLDPPHsKf7uW49waqyMZ8s+fvnE8/zmqTk6eiAQCLCpz4zJI2d2ehUkAiq1js7WZvSqP9WWyKUtLC1lKNaLWGweahIVxXdqL9dqoNIYyZckVCoq/vjYS7TalPzsicfp8vTy+tljWM0SJMUymtZm8pI0C0sh8qUNRkfnefrF13n57ROEVpZJB8pIJHWuuWoQjUKFoCig07eRyMQQBCkXjy9i00m4/647WV98hEM3NpGOnuHXv77I3GgGv9+LQq1Cr5WhrUoRqnJKNS1vvr1MUVJAqmhi595+WhxODOYqI9Nr/Pr3l5hZiXD+0tscPfYWZy6PUcrp2b/1EPHoKrsONfKRP9vKrh1KrEIb3c6tfPjm97Ozawd9vW34plKk4zHq+QV2NLazNP4KeVWVfKSIVlpCWioiFwUKhQKZdJS1UJiz0wucmV/mx7/7NnPLl7C32JicW2BtZQaDWo9aLoOyiKRS4+obd3LLng9jG2xh0+Ye3vfhD1LKJ3jstTdxdrYhqcapS6oIpTgHdsDnbznIb++8nfl//C7Otg7S3lV8xy+RECtMBTKs+jdQaAxUypBN5wgnZPhTJSq1KvXSCoXMMkblGorKMXo97YxNrvH6whnWsiH0cjv+tQJVwUVfg5WNbIVKZAOLyYDDagDRiVIpkkgmuTh2ikyqSj5a59ePPIHDrafRYSInlWNqaqJYlyJVaMnEBQb23UBW1JCPqZjyLiNKbChqZWolGeVMhdVgAFXKQDAQIxjKsbN3E2QiBOJ1mjQCUoMKc4MFvUaOp9FGupBAYdYysbRAIlfg1PkZzPoOHn7uDQxqJ70DDQw1OvEG5ynrK6xXKuREFfl0mmw8RqFaJBCOMjW9DIIUq91NHS3ejRi9vb3IVUaujJ1h376tiJIYzVaBXDREe0sTepuOQl1CJCPgai5y+uVvoc1oGOhWUktfQcyd56p+C37fy8gUSTSpWcJ5CcFClmQ6x8jGCAZDEJXWQqngZezt56jm/O8ayP+/35GLf6qM/v+5W6ggCA8IgnBJEIRLoigiF8yoNTIee/Yt/vE3b/Gvv/wVTz7yBXy+ZdIx6O2zksnWqddkqNGQy9QplmsoZEVMzgKzSwVuHNrDyoRIJqyhXMvSP9RKuZ7DojbisRtRKSuEQgqqmiQ6tYRUrkohm0NTTeOsWsjUw3Q66lx17RbuuKcHV7NIre7h77/9fWZXp6mWlahtWYKhFEvxDD99dZSfvDJN0WKiLBZ55ewUbQ1aLk8sc3DvFvbs6SeaWKFniw2dSo5cHsHj8eANzvLU4z9Hq3cTE/yMjBzn6NHH0St0SFHzyhtvkK8PUlfu4+RElsl1G48+9xqb24/w8tlFfvXwLH/3pYcwOMwIMjUVIcWZcyP44nlqgo26KMOo7yFXTmE1qXjrrWU++eV/4PJUmpoA2qITs85CoSRldKKCUiUhH9fj0Cpxu03YG4yUChnkijjZbJbOrn7eOr2IRV6jWCwjqPVoVCoQa1SrVYoVEbPDQ1nXQiok54P33cZPvvYrxjbC9HX3EJmD7W0H8BdS9A8PIJfo0WkEoqE8Y6shVBobV23p4LHXf8XH3nsL0UVobSyxdDnKbbfdQl2poLNrGGXdirXVTL4Ob7z9Bj/8+of44ffvZ3bubWymTup1H0pFnEIxTiGf4bFHPs73v/ZpzKYsb19YZNy3QSQpYX42QmunkWNvXuDy2Cp2iwOPYzOh7CTWZg3923egVBpZWZIgSLbQ0ukkW5pnY73IzPQ8E+OrrK/OUK8ZsBo6CSQC/OPXvo1CkaVamqecziLjTxBfXFvCYHNw+fIMUrFIZ5OGr37my3SaXYiFLEdu3INc0JLMbFDI1UlHs2xEamh0Bk4tPM2jP3+W6StzXDx9kXrLVm67eidiUcvwdbvZumsX3f0d1OXtfODIfnp2dyBmlVz7wJ0o6yWKehX6fB6KCd578z6q4Qj9nd2oDDoaGyX09XaiVQfR1oPIpCqEqgKzVs/I1ALRYpxEKIJOoyWUjTAmiZHKRjiVyPONvVdjNbiRl7PEylVsFitjyQwDQ7vZvqmfM2eu8MenT1CU1tm+zcny4hWkpTKFTBCJqsSJc5dp29SO3/86ZmmBYMbHR/btZD1UQGNvocdho8XTCVIdS4UImkqSeGqZQDSE2aJhT18rSdRUpFI0WhUGUUBeKpEo5IE6RUmFYDVBJBVj1uejXKxQSCZZXvATy6SIhkOMLa3Q3dlKMJaiqJBidLlIFyGeLONucNNoN5OtSTh3+gwtzgaCoTirCzHcDju+VR+JiIxMPkNLey8Gk4tErsDsSgCVsczKWopiPsTI7BnOXV4jUqwQSYSwaEyo6iLjM3Nkq1IqZTWNDgvx1QB6lYnbh65lYmIeZ1MT/T1FnnroPzdH/v9kof8rZfLOHH5H9wFN/25f4zva/81EUfyFKIrbRVHcrlBIMKiKyKVFnn15HYe8TiBX52s/+B5OnUhThwpFXkClqtLW2kWFPIVsjXIekukqfS1qEjKBdf8IpZCRRruG4U1XoZBt8PnP7eGuD/Rw3d4tOFwKcuUKO4dbaFBJMGl0SFUGMvUyhw5l2L0FpIoaNx88zPY+D/XsOtsGPOitNmYnZ5hbrtJs7+WG4RZ6LE663Wo+utfI527fj0xvRSWWyBTrFAs6Kvky2UiUz3zkRj714a9SrYSolIuEw0nkFh16t8DP/vACq6uzjAcFPE4l9Vojxy+dxdOwg425GVZmpjl3doqNyDozK2H+/mdfJpoOMjCooHeTErVCTTZVoCLR4NHbkMp0nBn3c/SlRV46tkE8rsUfVnBhJsTWrkau2avDpLUQiHox2tUEY4vcevMw0pKEUGgOqTLFqZPjeJe9XH2giVoVJBon0wsT2M11TFYXHR0mqBWoKLQUMmmy2SzZbBapWCeR9VMtyPiXbz/KfV/8e0opNVtcvXgR+fGjv6dcGebZp18lnq5Tq1fRmvWMjIxgNVWxOPVsHuwnX0nzo+9+gpFzs9x+zz7kdS+hUIDl4AiCroRWUGM0Kzh21svE+gjlmBqtI4+9yUZrcw8b/gJdjQ7yqTxyQcbx4y+Qyusp1SqU8zbKtSrJmISJK1606irRaJwDw71kSwUGOjsxawx84M4juBq76bO7MGhiXD57lgPb27jn9vdx1bY+zBYHn33/LXzzX37B0toSRqcNv/8KyVCclbOnSWXzLHsXyBZrdHf1olRp2L65D1FuZX0uzZc+eRXf/PR70ZlNrM2Pk4oUkNVVRHISfnf0Nf75h8+wurxIKJBCqwKr1cHY1GUe/deHyQtlzp0Lc/LMWSoY+PE/P8GTzz/IM8fOc/z1S6TyPkYemmH4QAMGCbRbHGi0ZX71xBskqgKDPTJMahMOUyczExdw6TuRKWxsadYhEQooJWaaPTbqFQnZao1qvYpDq2Wn04IgFCGd4mIgw3o5gM1pIJJMoqqE8K4tc7C9B1GQcm5pGqVS5NDBIaTFNNu39ZLO++lUGKFew+1pIrc+x8higX6jC6QSotUGGjwg1hTc/Z6bmbh8imwhidmuZVmnREzL6Gp0cfWBbUz51tFY7NQreZSSIlWxTp/JToUM+byESkWK0WpG39TNVnc/XT3DyDXdKDWbGF1ZRO5yEA6WOXlphnlfCYtLw9j4Kqm4iN8fxGJWsh5NcGl8juv338zq8hLeiA+troDDUiNSjeGy60hH8yjUJja8fjSlCjKxgEvThLJWIhiP4Y1Xad7URKWaJ5GR0NLvobnVweYOOyWK2FVJXruwgsoh0tLUy8VLZ5BWYxj0CmYXltDple8ayMK/bzX0P9wkCK3AUVEUt7zjfweIiaL4LUEQ/gawiKL4ZUEQjgCfBW4GdgE/EkVx5390vlIpEXVmCdm0iE1XR6fW4mqRkEzkMWo1xGMSMChRFf7UyNhq0yORlUikygwMdlBLL/Hp+z7ONx78NQ/91WcJsYpeZUFWl+HzRjAYdYytjKDSuEhmVul076OizPKFv30G2xo3CgAAIABJREFUq1WGQyvhnrt62Dq4hWeOnqTF3cZw32Yuji6yFn4Lt9WFyqxFX9mMx6pgZuoso6sVnEYpzR1bKCxPcjIY4L4Pf4Kf/vKPDA30oVElQFxhuPnTiNLLpNMyApFJ+vq7MZr6iZRLnD33Bw52v5c3z75KoyGPo9HC8nSII+99Dw89dpSr9hwkl65w4txlLo+nue5AH77oIgf3thHakGCWmhA1FV48P0XJL0WmV1Aq5OnqspGupEhESlTKkKvIsZgK6NUK1lNacqko9Rx846tHOHn5HG73Zo6+eJq/+NQB6lU5hVIcl8PJylqA3/1+hJJoI5VP0delpFGlZqMkIecvUlVVECUiGpWMXCpDV1sDo1N5iooaHa12ej0S8gWRNX+R99/QRiwXRC2qOT+1TjpfRmOw093lQKxWMOvVCGKZfT3tzM/PcyowwZ3briGclVMoFYkllziw8xOcfesoQ1t7WM+vklkW6O12YnDLyMbc5KI+nGYXuUqOaBoyxSinJldYml3D3FBlbkmC1VBArStx6LpeGmwDxDfOMxeS0dvSxfEXT/O5mw+x+eqdjC9M0qQxMxlYZbuthfZbhjn97QdZl5fo2LqT9MIEm1pbSOYKLM8tkbW0c+TwAGLcwbmRE1y+OM0d7/8YuXSMlWUvaoOaPQNu9N0WFPkSEqOKH/z0Ck/95mHec9sRln1jrCxvMNizj1QxTnNjEwvz4wiiwNK8H6PTgphLo3Fa2fCHkKGhS2/nhv2d3PWVz+L9wxMkqVPJSMj6Uxz4xhd47itfxF+UMaPwky4qqEdquDc1I2hTxFfq2BttRMJJ8uk0ar0DlaFCMhylp7WJtbUIAnXUNi0SqYpmQK7WUDJp0S36iddlzAkplFIpw81N7O7ZxfTMGK+cv8ypswH+5n2DTCSTDO9uYsobpE3tIl1PsLmtkVdHvfRYrFxc3mDfpla8yTjBVJ4DXQ5OzvmJZGI06dpQKWrUdUrIZ/FGFQx1myjEIrhbe0jGohjlFTR6GVfWE6wG0+hkMuSGCgZNA4VYloYGA06bi1ouTyKR4uqdvfhWgyQlAdR1K8vZOquTa+y8fj8zy8uUEmF2b9uCd2karUGLTKn9U8BYLpMvS1GrtZj1EEyXsGtNdPUYeOnEGFJBQn+rC280SjKSYUtfJ9V6hiW/lEq6gMuqR6Ero1aq2fCtsamtmWV/ELfVhTeRxiIoKCPS32omkqmyGtggFMqzpWsrX/nx05dFUdz+HzH03Tw//CNwFugWBGFDEISPA98CrhcEYQG47h0f4CVgGVgEfgn82X90PoBEkGN1GvjSl3+MIDSSLymYncshyI0EwgWi5RzVZJYcZa65YYB0vEKNCgaDEpfNweDgVr72yO9QFw18/XcP0e/YTbt9ExJZjZnFadoHtWQjDSyvrBELysgqUpx96wx/+N7VfPWT/ej0ImcvGFheyiETS9QKy8jVJS4ujOJ0bcYgbsY3kkMtLbGRCLFeNLJJqyEZLWOPRFitqhnaZOKpp/+Ap7WLbHKOXHyDe+78EmpnGrnVTkdnF+0d25Ap/lQ3ObA2h9vUz/TcFXZesxO5sJ+NjJGatZPL4yNcfcNV+MNreBodfOEvPsWhQ4PMrHjJlkvMTpeZXwjw0rlLPPfmRbbv2oREJ3DDbb3s2d3D5fNBmh0OdColckEkFc6i1DRRFQwo0lF2DfQzOOTmZw++yvhUluOvTWHVOPntwxf51387xnNHV/j+d17n0oSfzZvltLeKdDYr0VRkZGSgLEOaFIhK6qU624e3YXHo2Ign2DXYhlkiJx6M8uLrK5y8tIFaGyCUTPPKKzGKlTKttgGsdhV337aDsUvLnD49w+WxJY69McKJkXlOjkyiLjYzm8gzs3qegaE+brjhWt4880c8XZtJFqUUA0r8+QCJUJV0VMmpM2+CVEex+Kc67CqVCpupkT0DRTq2SHF32rjnfUa++eUHeOq//hZNtQblcYzmzewbkjA1/xLt3WVs+zpxttqxm1QU5VkcYo2fnz7KladP4xl0c/aNCUySIoc+fD8vPfM6WY2ekqKLD330ozz60E+ZWbuAx2Nn794drK4solUp8W/46HO1oHFpCF+6RDkUIXVpgaO//y0Oh5orI8fZWI+wPA/F6goWs5GLZ0dxOdrIZ3PY3RLUshpOl57ARoimpiZMjla62ly4DTZ8yQpKQaBYSKMyaNA5lJQcW6mWc9hFNUO2LjxyPRK1wHo8TdkvoLPB2csX0ZsVDA13oBciyJIplBotGnkarVFBMp0gnIiQKCTwrYYQaxJmV5coFkvMKAOU01k8Oitdnqt4/o3X+O5Db7MaLvDFz+0jqNERlKsZnfVCooY3FaWraRsLS2kK8QRIBBrdDiaXA+TzUKzXObEcQqtVYZXpyOsyBJMxjBoZSq2RVlcdqdxM/7ZDTCxMMzo/wVKuwC03HuJQj5KbuiVY9Xrctlak5QqDm5sR6hUuz0yTKWapluNcOrdINrnGojfFXDiMRa3C1GFhbuRtoguLuJsGOPryRaqiEZXKTrUgRSbTEE5nWff7yBSKTC16kctkvHX+NK++toBR3UCDpYlCWUoxX0GrtpDIFPB5M1RzIoFEkmA8ikwtxedL0NrUyfxyAJXMyOS8F2lBRk1aYsfgzYzOBJAoUuQyejZ3DdHWYnk3+PwTp99NRP4/21RKQVRIQaVW42o1UM6oicbjmG0CxUwRk1FOqVAnU8ijU0uR1ASqdQ1ylQSxVERtkGCoymjcqubL7z/I8YuXWFkosP9qF70d2zAblHz1u4+za+9hhNhZ/IFVbnlfGwbDzbx0/BXkghFbi8D51xIkS3HiiRgt7SYScSm1ogK1TKR3qIO3jp1i965O9CodbcOtDEbMzF56k7c9GU6fjXDnwS1Mjfpp7N/E2qUFmrdIUal2EsvPoDMbuHDRR7GsRKfLc+2ua8lmgzS5HDz0/Bu858ghXnnyab7x1Q/xb7+9QGeHkvbWfhy2Vs6+/TIh7wZvT0aQKMGpM1Api+zx2FmuxFiPFvDHzdTzMcpVBRprAV1OTmufHe+qjz27dvLcG2NUc9DpVjOzmsNpkVEpm1Bpgwz2tjEyHUSQ5clXpSRjAm0NCvQNbjZZpPhSCzjcMmyqRkLZIhsTOW68o58rM8uUiiDWdaytJ9g24CGczHNhZIm+XhNf+fgX+OLf/oA7DvfibNWTz4/Ts/mDnHz9UdZCdXrMal4ZWcBkdWEymdjS1UF/Xw++hXGC6Q0WZpdxuSwsrwaoSUT+8ovf5Bc//yo7tnRjtXZw9cB1rIRW+d2Tj9HZ2cpAy27UkgjJrIpEHjRaObHSBD1dPZSqMSYuJ9h9TTd1aviii3zvW2/y6U/vYX6uyFB3D/V6mt++8SIHN23m9hsO0zHUz9TRN6m6jDRlbby28Aa3HD7AhbdGGLj3AV740hfp37cJXzjLmD/Hx+/4ECeeeoR7P/lpouurWD1dPH/0VfRSFVWjmquGB1HsbGb+6Qts6pTz2ydPE4kvMztaQyJN0tDo5uE/jrBvq5PlhRAul5Le7k2cm5xlwOnhhiNtOHr2ISlM8Hc/eYM+uYP7rt+P7f0HqL9+jqpYRF6XILi3UGtWkpu6wujJEeoqBRWDhngqTDSZICVRYWo0UQxn6PToyCYipJBiN1vwBdIopc2sJ9bp6tzD3PIIVw20sXBhHJvNQow86kKFnFLO4QOHqUUinBi5yKmzK/TttrKrv4FK1syZlQ2a7Srq61kSTh36SgGHRY1aK+KUNvL2yBU8g4OElyNILRpyPj9qhwuxXmBn6xDr3jeJVxSYFTamfcv0tzkZXY1hM5lxuEwUk3UcZjuLk3NYmi2sr8ewulW0ORsRa0ly2SqrsRxGjYxiJUeyINJnaKYYX8cn0+HSyPE4ZcSqBZJ+ga6+Bh575SJ6vRaX24ZKLaFeLJOIZnA1uohni8iVBqanp9gz3IfeZKCQLxILLKFWKzFbbJRLJRw2O75ojEZ3C88dPYZaY6OnxUQikWCwbzPTi+MseIMIVTkWTwsNRjs50c/27l2cOncel9uCUamntXEYf2yWv/jGk+8qIv9f4mfn17/+j1+XCCJqqQw9KbxRBXVZnFJUw50HnIzMpakUwWgwADUazDrW42mSJVDJ6pRrRiiJFMnxnf86xr/8H59AI9cRT4TweHbiT84hi7oYGX2R0XAYlUqOSueGgoFM3sDc3AjFWBSzVUVLWyuJfJC+nh5qxXWO3NRFq6sVjbGKp0HLvC/DufFlIoEyc6kQC+oq4xMJWtvtVMUgOrmDtTU/t912J9WUj9m5ItOLC7iaXKzMlrBZS5QiRRKhDBqrlldOjLIxG+WGAzsZuRBgYu4cH/nAYcbHJpHWRC5dOEqju5sGZxWVMs3Q5i7mQyWqqSTvf+9OTs2UWU5GuO3qbSysrpBJVtnR18fCaoJgMovZpicVzZGM5+hsbGE64aeYlLN1QMt6IcyhoVYevRBhyGOht99AzFdEqjAyZE2RjGUpy+p0dWn47Ee/zYmR85BV4DBmifkLzC0l8KeypL0JEpEs/pARlTyMUatBKxb4/auvkiuUUZsznL4QY369glYnR65sI5ZYJ5hIc+3VW2g2J1n3lzl+/jKBpQnuvm0HZ8+Pct8nHuCRR49x970PYDeYeO7Fh1Epm2lvbCWZA63dDrUio5dOYzAb6WzZg6QSJpUFndGKx+UmE07SPXQQIVOgq1PC88fewKAW8M+V+OiHPsrRh19n23VmmoxStK4utqhdbBsawGJt5MoTRynq7WxtFSiVq+y89VM8+8jv8W8E0UVieAtgad/Gbx8fodFepbfFis3cyL/89HtcfdP9rM8toqiLlCRKMqsRGjrUrM+8zcS51+jd2kA5nGR8JM18IsNQt5PFWT/33X2AP5ycw23WI9REsuUsTQ4HUmMGh7uH2ZVL6BosBFYTyGoF7vsvn8LokbN+/DhmXSNlaZz2+3/AyDf/nB037ufSiQWgyERuhS5DN0IuyXI2jqXBTiyU4OBQE7GckRadAWmgQMqkpJYMkMymkejW6NL0su5fxdnWxtqMl1aHio1whZuu34UyVefEzFkef3GJ+z95AKtUiUwqoVkrI6lTcvXmPka8IcqVDEaNCqtez/RUiFgqhJ0CgVyFZDWOkAZPw2bU9Si7d7RzamKOUkmDtFJGpSiwo7cDDDoUYpG9PVcxvbaIIM+xEVhiMRBi745OkoUsh3q6yEpyFIIBGjVGFLoygbwOo7UJaTXLQt5PX7OL5Wyaw8PtSCRqJvxrFCpFIoUqpVKZRqcFtVJBouClydZHc6MJqRBFWq8xOh0in86jkKnxBdZxOHW0NTegkNYJhcJsHtiBz+djzRtmbHIFvdmJVa/GYbXhNOlJxSPI5Vr6unZSUycpZSSkUjkKZQ39zVvwRpIMbtpMuZZn1TtOMljn9OTK/z5f9L/97a9//e8+P8SVuQ1yJeiyyEhklGzflCKXlZCqlJCrZBTKFSp10Fu0VGp10skCcoUGlTxOvVojGCjxgQPDLKcX2AiGaOuUUmWDldkwT798iav7lBTSVbbuuIMXnprEaStSSCyzp3eI58/E2LZ3E4K0zPVX38rI5DqjV0qcP7+A3WmlkMmyvp4klCyh1GooFUSWl7OUM1r8gTR+HwSjOSQyDclwmQtnR5FKbYxPJWlw1ZBVMlgMLkYuBajLNOw+3MazfzxNtZxjy2Aj4fkoR96znbmlNebXg2g1IvmchDPn/ChNDaz7DczOe/FG6ji1OlaiBSKZNE0GHb2dTt6+PAV1CZVqHRkZ5LI61YpIg1lPOJKipFZgtkso+Ao0eRQszKd5+pGP46x3sBY+h6yoIBAtYvY4uG1vE9VgmJvuvYUl3xRf/uKP+dtvfJpr9+yno1Ugm/FSyTbQ71Kz9/p9XLiyQXurmUgmibFcwptVYG000tisYHCgn9ErIW46MoRRmuX5V66gUJco5UvEQgUS6RKOhn4ujU4hluro9HKKxRwGq5lSoYg/GSEQ9LE4N8INR66iy91Na1cjj770Bh5TL//22G+46967kSrMJJMhZLUcdruHbDaFWCkiVh2cn/wVjc5m5taSCBipyEV0dimh0Bl0zVXs6l5W/Q1YlF4Grhqgdfdu5i++gW9lhQPXHeJ7P30IhUzN2y/8jkCmQC6uo2hTcO7MCZSVOtv6Wpn3edkITpKtSUnlqjz6xFGUNFGRJIn41hm+sZfw3Bm0NQnpjJ9GVS9PvzBCWVanUlQwdWUed4eWTS3NTF+YpLHVjMJmppipYtLKQFWhVEtjaQarsZmxjXn+4WPf5vz0OZpde1i+9CImtxH5ah794dsJnz5NqiCSCJ4hnLUgK2VZq2YxKmTUG1qgXMXSYODK+DJ5rY6gdw1fpUg5Ueaa3j2kvEvojFZkSj2YglyYXaa9zc2GWCYcTHHDnoM8+fozPHciyF985HYykWX2btmKRFFmam2VarzIyNIijc063CotifUUClkZlVxNUWrAqDUSFGu8d/cuJvwz6KtlRIWAd2aODrcKu1KCSiNFp1BwbmWFaqLOzv2t/426+2yT7CCsff+v2pVz7Kquzmk6TvfknKOyBgRIWIABm2zAOF4csBDY2Mcc7GPfY4ONsQk2WIAI0ihLI41mRpN6pqdzTtWVc9xVtWvXPi/OF7gvr77E71nPerEWS0sruPVVVgtFjCorerNMKpzG5W3CIQukYgmKmgL9Wismv41yZYtKMU28mGPU30ewJtLnE7g2u8WoSs90JEQirTDYbWA9WOQrDx3m+q0ZAjYnS/F5lleL1OpW/E0W8ukCo0MdqOpZuvxNoGhI50qE4mmsdiuLcxOks2UCzc10tTVTSEfo7GhiaW2TVEkmW4PhbW0EY7OURB0GtYdCOUUklkPVSJKpaNncXCCRziDgRK0tcPVe6N0D+dNPP/1UX1uAQs5N/5gaGTXbO0okcy1spPPYbCaSqRy1ho6yWCcUy6NWNJjNWqr1Mo/0DNLQ6RCUPDl1DTmV4PwD7UzcjdDbuwPqY3z290bwtfdgsj7Mr974d2JSnYS4yXsefgSNUWZmaYPXXptmYHiU7/3br0gWaqTzWYwWGUGVxWbS4nM0oanJ7B/s4PU3VkEootMkOXmyC5OlRipdRKpVIK1DZxfQmBpEQls8cOYCNVOKTMJEqRykq1tDPCFCoUa3X8DbqiNULHBjfJydO0eYuFVB0FQpikkOH9vFpevTLAc3UdV1pBI5QkWJZpuaTFpibjXOnViK4RYd4VAVrUVDrapBq/ewlcxg1CmoxDrHjvQyO76CoyXAsZMOenw+Pvjhr7CyMcmZw6N89InHeOJ9R5laeQetQcY7NsDC5AyBTiM/+uF/smPXUSwqEzdnXmbnro/gbxcZGznC1NVrvO+hM1x8exWzNcV//+PXGd+aoq2tGylRI59LkIjXGBr2snk3isZtIx6uUSjG0QlutFaZ2xNBzFYnlXSB+07s5ea9uxw9upPc6iquQAf5xCLHD/SztpTG4w+QjgZxaKz85OKvKEgNIsG7nDl9EFmuYjX4qFZknBYLHe3tiOUC2WSdVC7H1TvvcHSbCoutn1euv8mhfadZnFWjtdu5/9x2fvqzW5w6/Si5mSkaJYVKXcs796Z55HAv5WiSuqkDJd/C7NYk+3b18syP7uFzuag7ygT0LayHdRzu1+JpbmLPrgPs3N5DNBpnai1OcC5Ke5eXvr4hPvvlX/DBDz/Csy/8J5lkEX/ARzGaZ/RAN6sL6zRsbrRVkS6ng3Rqg/YeP/7OLsxOPyubG2TzBdRKnuXpAp7IOgv37nLsI/eRipbo/oM/QU6FIXydlZk0Xbt7WZi6R+fIEPo6bDuym2deuUG52CCVDGIULIwNdDJ/bRbTQA+ZUp2yysDN9SQGY5Z0uozb3InTbqHd6WByaZWvfPhzXLlzhbt3pmnpdJOU4uwfO8J/vfMOqryCbPagNqrZOboTt7rCVjTBerGESmPhwM5T3F56h0q5QUOnZjkewVkxErA0Ea2XMWs8FJQqN2NptHUD+pIKldfBSf82goUQWxvrbLP4WcjXSG+l2LN/G8VYCUWlplLIUkCDLge35zbRNwRWclUqko3tfT2I6RjIaoSqkR0DAeayZZL5Io8f2UFpS2Lb7gFmZlfotJt4z4Vz/N0PrlOTtZjNKnZtH2Sbz4LRoiHQ08udmRAaSSRdLONv7cBht9Ha5ATBTFdHC3qtgqpRYiUhsr6ZZKCnD0GqcPXWDNm8hht3g3gCarpbAiAY2NZlZXUjRq0q0NRqoJAvUxEzjC9k3j2Q/+XXvvrURi5MW3OW1aBMOdcgHVeIlVO0tZtIRnPIgga1Ro1GLaFuaNEazJTFGl3tfm4ni2xlIgiKmaqQQyXC/Y+8l5dfmGN1a4JTJ0/wL9/9DqMHxlBpdZicRgqRBC2t3RRzCV68NE0wrqKmqlMpw/EzrUQ28yytZrFo1Dx69jTR8jKTS6usJUAWfDQFLISDMRSNllPHxnjoxF7s+h6mlzaoGCsYDFW2D3Vybv8I3/3eC1y6kkatj7Ctczc2t0i+UCMcFBkcayaRVhNoqfDEQ4/TFsgzOGKiJTBKrVRgbGgEozXL0mSShgBWu41qpYHDbKakL1Gv1tHIbj794A5Gt/toyEamJsKgKaFR6SiKJoSaxLauMl/+ow9jtae5+tI8u0at5DYWKGo3CW4Fee7KT9mIbPD4mc+RL7yOELEhGSoYjBYeum8b4fA4y4UVjm57P/fefo2NVAExnmUxtcyPL4a470Q3wViNYCLCSniG4ZYhAu1O1u/F6Otu4+0bdzhyXzcbmymC0TgOa4CKHEcsV9FoG2TyoKhFRoeHGe70Mb+8wWO/+SQzM0uMbm/j0KHdXLq8ztr6Bi3uHZw9uoeGCkDi1JEBalKBUEpiYzmK39eEw6ZjenoKn1fB4x1iMz+HjiqqwEH+5e/+m0/+5nv4y2//JxhdnDzUyfpSgu0HjegKNQwNKCVCJI0eGrG7XH8lS1HI09vpZXifieV3Fjj/2JNMzV/E7RPobXOST6v5xEfvp6hdYGF2hdXlDQ7sO8zFl3+JYhJx6po4ft7A7enr9HV1848/eJN6Qku5XOHaxBaDHWbsJit6c43nX1/BYlKRl7L4u120tTl46840k7MLDA0NYNXY6BsZZvn6HfwBCxuhGnv33Y9130E0liYUq5vVK7/EpDXS0+ZlcjGOXlAzk05zZ2WOeLCAxqzG522mp6sdpdAgnVnHqwOLzUA0vIleZcfd7CBSq+Cy6liJp8kWG1jMKvxaEzenr1DTOhkaa8FrN5CvhNjWZCGvFTDaq8ysx/FZdMysx4gV6lTEBjtHelgLbZIXZVpbm/E4DUSCWxTrDbQ6gUhDpGHTUohU6fT42cjmEFUNGrkyU6kw+rIet1lLLWkhLiY4cHAfl964xhPvvZ9IJIXJZSFRqaERq7i291FRSxgMKpwmmVIhTlGwY9Z7GGp34BFTGAwV9HoNpmoXA4dcXF+aYzWVwxGFiclZak0Bzp/aQyY2Qyabx6LTcPnGBC+/eRO7zcKB3cOo1Qp2s4HF+RV8TV0szc9TlySSqSRmq5U2u4TT7SWay5IqZRjo7kGuy5RKeZocPkqZFCazhWazjpIYY3SknbW1Eh63i5NHD/LfL9x890D+V9/4+lMmQU88YaTVpiMnZdh7ZJhcpkCsUMFjsSEpYLSqaPe20dGRoRAv0+y24bK5iGfTmJQavW4T2XiV42d38rW/fpZ0UURQnFx5+VV+57P38fKL88xvLHLrzgy1qsT6RopgqMJSsYDXbGCoz80r15bxWG10+8GusdM/JOPUqRnueT+VopVgPESpUGAjFOerv32BxWSaa29Osa+7hz/6pxfRyCW2dbQT2RC5thii06rw4H0H6Nuhpce7g3cWb5PN6qjXqqgqMDbYSrmwhaBXMTNXodYoQqOVen6BTtcQN5YnaXX1IQjtRAorlLMmLE1gVKuxKzUeevQsQnkZfd1GUR3jw48+wsHTLbzx/Az5vBmbJcvf/92DFKIWfvHqHA8+eoyAoEUs5MnrnIQ3k6TDBgb7HeQrAZ67/AwDrbsYanEyuRBF0OdZWa9iNjgYCmix6FRsVHUE/C5SyVUKQoE//MTjbGzNsFXMk0/YEMNR4rE0t2ZK2FrsdDSbePPNLRJbEfI1gR3Dfej0VZIJGYPGyH07j3B7eZWxvmYkk435zdsc2/0kb1x7gXw4jlJcYXFzHVfdxXvOncLshLJQZPe2ERLBtzhy4AFml+eYno1w/NhBiqEq3c12UrksarUbg0Gh2ehjZTPHfPRt/vwLn+UHL7zIZz7+ZbSNKr/6/ktslOZx1L1slIv8/V9/n0R5jUf2HmQlW+TQ3k5efnWGsZ0+Fu4mqboL/P1f/ppv/Pkn2bvzOFdmlxh25ymmavRvu8Dovvu48tYruCxNvPD2Aud238/y+lXOXPgw/+///D6H9h/nh//xJpFcmZQskBZlzpzZz5uvXefpP/9dipk19uzyk0pFeeKj7+fu6j1a7AF8Hc2YDCbujU9g11rICgo77WbyuRCHH76ALniHW9/+F5SZcfq+9G+Ib36HYFHCrBS4ESzQaRRJGR2oNVU8djPJqohIA1mapXtoCD0BVEY77QaBZDbMQ2cukEttUEGitambYqnOI/t3EImH2FiNo/X7wNpAXdHiq6coV30s5zcplAW0NT23Zufx6V0oaj0+rQWTU49LlkiUq6gUhcTGCj6rh8HBLsqNNKWcQlYsIgl6dF4d2UKJ5vZmMpUiigIrSp5iSkcDhYw+x9xKEFeLg/mVFKJBR3gzidPtxWlxUatUaNN7aB8xY5VK2B3t+LVDWBxB0pv3EAwKUk5Nz9BOYtEZOjxe9LLM/PQcm/kqWa0PRczQ5leoKRaKkkxNq+bozuO4fGpafaMUkllWQmHEWh2LXk+pMmSwAAAgAElEQVQmWabJ147JZSOdyCDl8niaOtiMRXC6/CQjEQa3tRMMxunp7WJjvYRRq6a1RUe9YaBRV6NX1VCTolgqotXqeenK/LsH8qef/upTWkFCa9Yh1WqoDAEWFzZQo0cDoK3gsDgpZsqkC1m0Sp3jJ/pYmUnRN9Sg01lGUTlJF/No9QpSo0osK5OtCaxvZRHrar77yxkyhQIOi8zyOxVSlQKC2ogsqHGURDbiBYoi2LV1MpUyckOhXMrTP7SbbFnklxef54H7Rnjt5XuUCmUOHlURvFXiYFcb1+c3+Mn4Fuq6RK1Rx6iSqVjMaCsC95Yj5OQkN24VaWtW0driZWUqT2KziNaikCrUMJg0uCw2rt9coq2tn552I77+ZpS6nouvXMas8nH0wV5efe4uOVFEUKs5cchLR5ee3tYxjh4dplDOUalVmL23wuWrl/nbv/0Sxw81E0qEuHp7mZeurbI6n6Knx0QqkWBifpWDp0dJRuy0DmwyfS/Dw2c9vPLCNHv2DvFP3/kVD544TK4goTXpWFhfx+Top5BXc+XGDLdub2JyD7I4oWEh9SYmjYXfOH2UV2+8jdrcS7lcoMtjIhlcpqbW093nRjHpaJRqpIoKq5shAn47Mnmujy+QVWsINDlockItI9M/UOaZH9/i5IGDDIye5q3r1zi2dxtpFdQKajZn03z9n77D6ZOPsBkJc/r4B2moN3jx4iuotQIqjUIxXcTb00ejKHJteoUHznUj1+s09TYjNwSSoUnkukIiEuI3P/IbHDoyzK9//FN2jJ5EdDTx3E+v897Te5hbFdl3aJC/+9k1PvbJ97M2sUF/Vx+W7jzR6RKuwirreHjx6nUqUox0Nsb1S5Ps3D3IOxOXuTFxj+4BD9t37eTOvatIWi1Wb5HHLvRwYE8nJw40Y1Ll6B7so3lbCxqtisXFFL7Odp596XUQrIiVLFXRQrmyzre++T1u3bpKOB2ip+s4H/rqnzA3uYjGZCJ4dxyNukH1+pt0/8kzbP73N9n55BOsvXYbj8vFlpLi7nwMu9PDvsEB5OAiDx/o4QevbbIZiVKIlfjqJz7GA+95gr/+x/9FR9cuquUcKn2JfCrO3t7tzCxOs5LMYXY6qRVz6BBoUzWzVS3S4rFgrlnwqCrY7U6cbj/ToU2222VCyRAus4eKSUM+nWN4aBidxoxYlcjnS/hcTmolFXptDV1Dh6AoZNNpVAjEUmn8VjtGk55GuYbH24TF56IqShhlLbl6lja7G51RS2RlnoDXTiaZZC6UoVzQEkwWaPFmWJqysK2jj6XNCJvrYHXpMTvVvHL9Hh6tnki2jGww4Ou0IqokShU11+9OE4tX2b1jkI34JjMLOUx6Ebc/RzJtQNBaMJplirU6qXyElfUSvYN7cAccuK1WcvkMSBJNThPRVA6zDTZWo7S26Dh2bCfB4AZ6gx5UVRx2J16fF7PZRC6b563x4LsH8q89/fRTLS02imKZakVBruRRqySkhkyhWmXfvjZK0Rj7R3vZisYw61p4+NEWzMY4ZpPEWxMihw5vI71axux0sDSTQBEUTDYrak2D4R2dnNrnxOPS8dYbW5icGmxGJ3q3mlQoRUXnRKWWyBVV7B8dIFtWUczX2btvjDeuvYUkG9Ea8/S2D7K8Gqeto5vPnj7Ef92aIqjepJy00+Mus5GR0Rr0yIKabX4VsXyRHUPtrC2KiFaZeKyAXp9hx45uYtEI6yEZe4uftZUEM1MSXb0O3roxz9ioF0NjmLW1VyiKJibnZ/n5y3c5vLeFZLyMz1LjwgN7OLL9E7z2yg9QSy5Gd/USTBd5/e077Bq5n8mV50Gzj/7tTq6/OM3vfeYk7/vQI/z73zzD+z/wCFVtlV+9fBNBYyCTrnDw2DDhYIqynKLF66OQkLm5OEXnqJPbd+d54L5TTM6HqNUFoqkgzS17eWd8lraWPNGoi+OH9jA82sz+/X2szs7hdBpZS2RwGUyUtDpqcRmxnGCkr4lEXqKUk2h1OFGVqugw0hyw49JWGBvqZnp6grHBXkaHdnLw6B7MuiRiQ8LRdZxsMMbk7DiYs5w9dRRbwEkwssH49C/Ys/08vSOD3JmcpMk1iNOg4BKylNTNDHToWVuDP//myxw72IG1NESoOMWzv5xkZKgVq6GbL37ju/zZZ7/KSuw6kYUFvvLUJ5mamOHaxDvcWqzR4YKp6SS6RpVERse5w2MsLG9yKS4QnLtNKl5ncHSYDn8X+eQG7V09+HydzK9u8pkvnWbq7VUGR3vZt3s35YKac2feh6AXSFdk5hajFGoy5+87wFtX76Axi6QyBRStho6Aha6WfuRSkscvPMSzP32D5ZVpDDo1Dfpod+gYf/ktWjoHWZ54E5XZgEVnIvLWS+z+xo9YfPYHhDYWKZSK2Cw+tBbwNpu5fW8aq6OFq4sx3Hoz3//mn/DgmQe5sRTGoKnx+t2rJJIVjIJEvVKjt7kDKhLJcpi6YsZoFNCjxuowUa9kocXDYjBDKD3P+lYRjdmBWCzjs5jYKlrY0d3Pcm4TW0khq22QLFSJZDJUajJmq5tgPIPerKIqGKhKWSwGM5tbIUxODzWlwfC2PkqKiMpswipr0Wg1+PUejFY9XW4PolymXKrTFughlspj0ArUjF7cXjfVRgK9RkJS19mxp4WKsZlqUaLaELk1u4FWNPDg0U4MdjeyyY7TZmB4wA/VBka9GrncYLTbxI2JIFqHilyqhVwww669nVTKYeSKjFwv0t5sR24UmZ1ZIJ0uU8jHcTmsNHs91OsiKxtF2jq68Hl0aBsGcvkohZJMS0s7a2ubRHISsXQOsZCmisCNe5F3D+RPf+3pp7QqCVlRodfpAQMqtQaNygAViXCqjEYw0t6lo71lhGI9RDJYoq+ti+GRbk6N7SVWWKShVlGIN9BaBKxuC2Wxgt1qQlAViCZFBJOZaEqD1qFFUJfJbEBNb0SvrZAM1/B5ncwFV6GaR1c3sbC2xP7DnczdXGegp4mR/aO8+vYqhXKMn16fZseAD53JQTqlYDcJaDV6FDU4zGrKGT0qVR6vu5nw+hYHBtrJFTMkcmYu31yjv7+FVKpKIllC0JkQVRJiooLF0cCg8fDTX/2C0bHtrEWd1AsqGmKJTEqDnCnxrT99koBjhIwUwdsxhGKoIle9/PqF22yFKlSKMbJpE7sHZZ772R0aDZFgyMiN8Zfxdvqo6fOU8ipOne0jOL/G/jEnp8YeoS6K7N5xH2I1CUYZpyNHuVzBoLewOBlE1zCzHFwhETOwtrSCA4Uv/sEJKpE4tyamWV6Ns7oa5POfe5xiMcj1m1sE50RUGoWlUAK7VkdgWyd1ZLKpKqGtBA2NBqfVSrEcoaPFT1Ud59ELT1LMR+noauPL/+NbTC6us2/gJA+e+zD/8K9/SHenA6Xo5dUrr/KTn92hWrah1TUxv7TGj595nnKxTCaSZWwkQKtZS0GlocnTQa6Y48H9+/nGN7/LT2av8RsHz3Pp7UW+/vVv8PNnv0uTXsXs1KvMLZT5jccOcO3uPVpcw/zixi2uXAnynjM7ia7G+fw3v8RPf36Nr3zzJY6OjLFnlwtX2y66O42sTGyi1prpatXz9tvrdLRpuXznHkeOnuDeO2+SrWZJpezcnr1ENLHI8y/eIBWJMjAwwnJ8nqqS497kLAcP7Ob40W4im2GUuopSWeTYrkPkilEmppdxtPoY7N7Oay++grsSJ78VJlxIU8zFKYl67G4TVUOd4sWXGfj9b1FZfo50TEW2mmamasaiVWOz2Dnfv43Tg9sZa3OT2IqQisxTE828du017H4vYjWDXmul0xVgsHuISCbI4kqaXduHmF68jV4w0+J2IBgtiMkYiXiDTz10H11VNyWvQptQ59yxw2xm40wvptkI1jFYNNRVZayOZqwOM+VsBp1Ki96moRAV8XX6sOAln0nQ5u+gKopYdDoWslFOOLuYCa/j9NvZWo/R2dzGTHCeelUgVa9irwh0ue005AzuNh1b+TD5ZJ2h9hG2GzuQ3Amm17IsT8xhdppx6Q1IRhuF8jKKqs5GNEFELFOtVYnGa6RzIZq7h9mKJ0FKkSoIaCUolaI47HYyuTLFfIn7zxynoZgJLi+Tz1cpFquM7RjBZtGTSaeIp4pMr2zQ0drEzOwKqViaFp8XtdJAozNRroo06nrW14Ps3DHC3sEW8qUyb97aevecL6tQIUsNlLqCVKsgaRvUlDKCINLmM7K1VaXWMLIW2mJ8fAGVRmJ1KcXGag6xLJMpX+fxc+9hpN2Hy+egISiUKnkqlRqJZBaNYEKuOqnkyvjNVerRJGtbCq6AFSWdJZqR2be/DZ1WJluEZuc2BKpY7TZuXgnzxGOnqCS6efbZ10jls1hsHto0TswmO9W1EmpjmazGh1WvQlArjA50sZmKYajDCy+u8rW//iBWjwFFa0StSuHWKeRyCmqNjBYTVUlCZzSgVaz09/Si1eXoHR5ifn2Du1ObjO2wc/qYC29nivc87mPP6AA3x58llctzd2YNUXJx9doEK3MFtNoKiQ2BtlYTr7+ySHNTG/v3tlOIbyAbteTCSeYmRC6+PstzL0S4cVtF78gICxurXFt6jReufJ9iUo1LX+HRI5+kxeVHqJuxO23UxEWMRiMafYHB/k6qGYmx3gt88be+iF5nYWzMTTyuYXzqLi77LkxY6e9xo6ZEVtTR1uvm5bduk8pmKFdKmGwWjB47DUHBZDYTTue5N7HJ1au3qEkyl15Z4K9+98uIah0//PXP+Ys/+l1O7D/P2qbEejHDtu4uPvC+B0lk5xi/vcKdiRVUKj25dIWxsTbczlaqaLGaFG5NbaHXZbkRXuQPP/04uqzMzy9eYSWfwyTmqOk8NKsUPvDIB9CZQhw58xBqbRNVeYV9vV7kosKmLPOdizMcOvUlLr4zhVGt5l+f+wn50BqFRISSIHF3fp0b70zg8klYLAb6e0Z47+MnkOoyzR1qhve18PL1f8fm8dDsG0Kjy2Bp1XDj3mW2dfWgK+iQ6xYETZ5YJEIlV8Cod+BssrO+Hmd2YRq9Rcf00gKT0/PU5QINuYLb7WB9c5Umv4+GLKAUSgjVBlZzjeLdK7j6BilLFVxaEz1tyv+duCin6RjoI5wu0OFV0dCosZiL1LMThGJJVpbXkRs1REmht7ODfDaH1JCIhoq0NHTs7O2lrjRYykR4a3aZjfAmVaoszaywEgxhqwi8770focnSRyVi5OqdaewWLSmhhMVgRIuaYi5Lk9OJUq1SSkm0NtkYvzJFtZjCbraQjMYY6OhGLpVw2Jwsr63j9Hnpc3tp6eqirKpDpUJeDdFICpvTRkyTI2jJkEpUMejtyEqOfDbKvextZucbRLbKqJu0OBwOcsUckizywQdPUKwbMZq9OF1e8qUKPpOBJpuK1NYqRlUJT2AXGoMBr93IjoF+FI0aUc5RLFd444158qUYVpsHvcaLy9lMvpBkZWWFQCCARm/C5vbi8hjxeG3s3nOMzm4/zc3NqNQNxEoBua7QHvAjKA3WFmboavf/fzb0/xeJ/GtPf/UpVCpcHjWFkhpVRYXNqGHv7m4mp0J87xvvZ2XyHnqrlmSmSiErs6PbRA2J56+uMTVfJJKMUNO4CSWKlColEpkKiqBFq9VSyIqIUgm1QYtGqmPT6vD5BZRKFqPRh8GYIxTO43FZUJQ6W2txKkYTdpuIUjdgoMALb8yitzehokgkVketdfL2a5uItQzn7zuJ014ikU5TKxdxeyx86f2P8E6oxD88dYbnn32H519fpHfAT3ilwAeePMflG/O49G5K5iI2RUOtIWG31mnptlOt67FUFZpc7bTYcvT61fTtOYJXr+LI/v0I+jbWJRWrS1O8/txNMskw12dWEVUihZKadL1GMl5jOZik1WPg0P42yukEj586TXe7hbdvTXL/g3sp5CWs7hwvPX+bheVxPvrgBby+Zt64chGTZpTv/PKnKCorF84fZ3Z2moFAO96WHlYXUvS0Gtl3NsDtl67xz//1LP2jJih4KOWy/OjHy9yZX6Uki7Q3GzCiY2h3C1ffWcei9yCXGxw9OsjyYoJcRsBmr6MoOhx+AzrFjqpRJieqefLD5/iPn3yP+0d30R3o4dV7r7MVXCXgtRFcC+Ly2JmcXuT8iZOEIklQ5TFamji8TY2idnNrYpKujnYK6SQ+bztt7S4ii2ukMxaOH9iPWd/gWJcLc+ceXvnpdzh++gz//PIveXjsIUbGtvPJL3wdIW/m0vg87V1t9NgMtJGmrbfKEw+foJDdpFFV84XP/T7/+Ysfs73jDLI2w/ETO/A0mrgyf5upyWvcvZmjatjg4M5j3JmcRFF86PRrSBWwWV2UEllauvxU0naad/YSTxUZfyeBWqOlq9NPa6ub5aBEvrhGsm6iXpcwqCHQ7MNmUVBV3QhaBZ9sY/jCUerLSxjtJiwGBxW1RP3eMv2/96dc+fb/RGsycm8zTWgzx8O7duLRWTDZFWSxjMViZm0jQt3iJ9NQUa3EaJT0yAYVjXiMVDLHvz57DUWuMrBjGKdRx+EREx84up8D245z9shBfvvUeTQmiY5t29nMpLh85Qr/8dqbtAWa2DPSTLkms1VM4LfamFzcQKyp0akVdHqBQl2gs0nLZihPQ85g0JoRpTrRRIZMRiRgMqAP+MmvRUmINaySgRZPmUyuSCaapyEWyQpw0NeKplTGorOQzhXxaox0tfqIZxqEpEUOBdrYSMmkt9bICFb2DvQyMTdPPJ1mNSMRC2dxGIz4BwaYm0rgbXJjNdhwuSSmZ0Ps7N/H9u5efu//+Rzn+od474PHeObly4RDKTLFMlaXGpvNRDadQqMzgyJjdpjpsHtJ5UIMbethfmactVCanCRTTKfpaOkkkYiiM8roNSZqqmZ0gsjFyyvvnmrlG9/4+lNWSzOKkKVWFlDrYO9hFfMzCUSVmrWFVb7wO4/z4i+n+O0PHeK5W8ssRQWWIyUCnjYyoo6V5Th3pzfoGwqgVuro9XpKhQpmo4VGHTJFkSa3E4vNzkw4xlZYRVWjJVeRiW5pcJgkOnsslJIC58720lGrkJU0SJKZUEXi05/fhUoucelalL29Xm6Or+O0qOgZ8nNvfAGzkqJWsyHKJbrbvLw6fpVPPHwGs9TOnUiQcknDwkoQm8XF/Nw0LrcRFQ3kuopCPofVLGGxeQiH49TrVbaSZWbmZ/nY4wfo6+9A7+7Ebm8hnYyj0+WpZquIaifPXbzHymaWQkVAboCkgKITyBYKjPV289rCBvF0GqvPy5627SysLdHcrqWjzYKmvMKxsUcYGe5kbT3Ihcc/wCe+8L85cradfCRLzzYX9VqeZPwW6VQee7OJWDZLV6eGSilNa2crdoeBx973cd6+foOckuNHl8J85VM7GA5oeeGmAZ1JRTBUYGYpjVVvorndgKgoJKN1XDbIiUnaOqxYDU7u3VrnkUcOIzU2SSRj3B2/zoMnH+K/XvkFZrOZM0P7ec9j76Grawe3lu4SSTdYWVBwW7W4XVpWF2McONrP9o4jZEqLLK+G6WkfoCSVKJQFGqUwTpMdQV9HbyoilDUMdFmJz6/y5PlT3J0J8diJ/dj0Aq56iKaOXh4/uReVVGU2NIevvZttA372t/ewtpIlFC2gYMJizjM1HWJ5OUi+bMHsbaNenGMjZ0KttqJ26Nm1s5ubE1Ps7d9BJBXl0J5HCIWz3Jme5ev/44/4/Kd+TqwWRFU24rCrOHnyEPOryxSyIl1tHWzFo4i1KsV8EavNisNlIBwq0N3j4frtArt6bdhMGpoHd9NIhhFrNVrHnJjDKQJ//BeE5ifxVJPcubnCnt2jfOwj78dSTiCKWTSqBnqjm7oiE682eOPONMVyBEntRWCdx4aGSOQlpuZnEQxq7j97lFavhpnVq7x6ZZPpjTw/uzbOWmSLL/zDj2jkZN6cu0bn9u1UCgUyUopipoLPauZOJIZHryNTqyFVK2hlFXa7kbJUosXfgk5Tw+HvotaosByK42xpwhdowuk0Y9Ia0GsbVColXAE/SqqOzmOkz2xmKyXSNtiPTp2hVrXQojNxM53E0tBgtBkoBecZOdDKypqLPUNmJm4v09NzgI4WGVUpTkkNY7uHiWS3iIbUtHcaeOvNe2xtRigrFm5MRWkzdXN4dx+ffvJ9OHUaapk60cgmgkHLL954kXi+xLH9+3B63JSqeZKpBiarjWopTyqdZSORYKBngFhwDYu9A5QmtIJIR2snyXSJdL7G3rExFhZmaelp5vatBe6tpN9FkP/VU0/5Anlyq/DD7x3l8uUUt8dlFLUVn11Fk0NPIb3MclbD1XuzfPwDQ9jVNkZ6Fe7ObGF31imnKzz6/v1cvnQXp1vP1lYaj6eNfLFAXSkjySoyGZFoJIveZsZrqVLM6aGU52/+7Bwzsxs0NAL7DrSysL5KQa6zsAnhdAKfy0g1F+HBB44TsDgRfMs8+dAFXr68gK/JTimbZGAggMHsZWxfK0sL61gkB23NnSzUJrh1eZJysYjZqUcQGlgt//f8YHMjQ5fbyqF9OwgHs4jU8PhsFHJ1LCYJu8NIOFNGq3XibKgQqzFW1mJcubvJkUPnCYvrHO1tpSzGSOUFzHYRo8FIKi3hMnuI5ssEvAJzCzXC8SRDowHemZlEJelIJ5N07dtJqDjN8mYItbaORnIiaSY5tP00D5//GLlSiJb2Dhz2Vnbv2o7HtYdUJkKtHEfQ2NBUfTxw/+OsBF/iuV/P8eSDO/jbT/8WczMVfvSzqwR8VVoDBkLFDLIo8759JqZXMwwOuDh40E0qtcr2sT7WlyN89DePoBTz3Lh3l0cfepJTpw/hdSsYVRJTE1FSxRLdewf4p3/7BZevTuHyW3FYmzFYcnzm46dwOerksjbmlu9w5nwvsWSMs4+c5rWLv+aB808yPjFBoVyiYbVSSsoM94msrSS5cKaXbDbFL65f5/O/9QShhoC6XuLSvXscOHGMtu4OPvbUt/nQow8jJqLI6ijN3j5iZZFYLo/ZaKNWM1CXyoz0DlGTUvzFd/4EIZPnztQstUoWm9tNn81IqVTE19pCwL2NRGYKX7OBasXEL56/wZc+d5rrd0tY5CqzkSUsmgq1bJnDO3fz0uuv47Zp0Oit5LIp3H4nsXCeUqFMvVJAFczR099Ck9OIKzBI21AfzSePUNn/KZo6msjbu9G/8m26zr2X6ctv0UCko8OGUKmAVmAzFUWp5UnmYSkaIuBxY2tpoVeX5EPHDjIfVfP8lXeIZGqE4w3sTi0qaw0pb2R41MlstEJ3cxOReIq2nmYuXDhPvZThrcsv4TGqMDe1oJKMxMNzYBZwOS1E4hXUKpnmpk5KZZG60iAVTVOvFYlECjgtZmwmMzqtllIqRbPFSSoZp1KTMVisxLa20AUE1rbU1FWbxDVG7s3M0O5vo6LOMj25Rh41g34/mZU1uq1+Xr25QMaUZ3Uzh8ns5swhPxVtlVA2RyQtMTUTJJSqQLUFm8nDzGqQHYNdmJH4009/nI9/9AK7ugdZmF8lnU+RFwtsJGN8639/n+17d7G0nqXNZWVza461xRLlcoxsXsTbFMBpNlCVCvgtWiSVhqVIidXFWZqamkmkkuzaOYTPZyG8lcZgNFColnDZmrh8512UyP/tn7/11Jmde/nuD89T2NTham/wF3+wj+P7Orj4epBEXqQQg6xSRa7UWVkuktAWyZXqfOCBk1y9uYrLrVBtCOQLGmqJKn09dtzeBnt3jzI1EeSDjx9hdWmDk/v2UE6t4fPo2crUkNBy/eocJcFFWU5jlnP4nR527u1gbbpK1SjiqGuopL00Nzl4/sZtgnN6fvzyOOqSzJCzQHOflbJKRyIRxd8moxZ8TGysULIqzF3dIlzQ4jebqckCpUKFXL6Comtgcdo5c2gX07OrWBs50JpRSzJapUSb04EFhZ3berg7u8bVO1PcXCjwwquThCMyrc4an/zji2yk13B62tnbH2B8MoJakGlttaHXpHF4FHwmNza/zGeO9RFOCtTNOno6R4lml9i9rRu3bgRJWkOQ9Pia/eQyccaGu6joNNyZfJ0f/Ndt/B0aNBot82ubpLJF/N5jpKUqq6EtLr7+DL9x9nc5e6KNChpiqXWuzyxz406cM2e7SKZr6IUCTfYWDKoaNbXEQ2cG2Tt8HpPJzcz0LPedO8e1S6/isdSo6yxotEXKpRqrS5M4/Aa2tQ9QV1RcfH0cSUrw+186TXB+i3NnR3n7yj001SR9Pd3MrE5i1zc4MHqWXSOjvHHpLcY3NzHJfXR32NHpwGiwsBJOEEqlaLOZcXuSXL8VY6h/B8XsNKtLEuH8JM6qQKAFnv7z73L2eDuFXJVtvR04DS5Gu7PcuFMhnoJEIkStXqIs6okXk/zq8hIP797JX/3VM2wEF1DUBob7xijraqwtr/LWzRvojS727D3FD5/5HumcwPEdvSwnC5wfaWKqsESbJ4C1XsKlaSEYE7F69FhUReqSHn/AzdRMDLmRx67r5vSpbpYWN3lg5zmsjTqdT5zjjX/4DqpsBeXyaxj3H8Ns6GDruf9Fbj1PuBojmwUlH2WqphCLZGlSmchVctSNTq5PrmFqlBh0mBgd7qCitPOVf/8h8aSMv7+Nsb0dmJ0NUvEq45tzlFRdJNIL+HwulkIlDgSc3JlcpaCk8Dh6Kaxl2b6ri8tvbjAw3EQhm6EgqGjztqAxSWxF4vT1dCOKOR7aexhBK5GuSYSyQfr6eohlk7S1d2HSm9CpC4iKhmKtSEeTDV2mQqIcpdTwoTaVObS7nVK2Qa0ARSQGtg0iCkW8WhNTsSJ1mxm1SYNf68KqMbGamcNvtFHemiUX0dMzNoLZbKCaj/DZ3/4gf/rZz/PY/Uc4e+AgiBWmFy6SD8WQzEX+/b8vcenGDVYjWcIxiaqcQlJUtLd5URtkHF4r9YYKt8PD3alFju7YgcNUZ1qJPvIAACAASURBVG5Z5O3rq3R09XO400xaqeP1OImHQqjrMjqbnnQmAYpCpRTnxkzq3QP5337j6099+YtHiG3WeOPqNUJRgRdfHefKjVX0ehm1BvJ1NaJcR9DqsNtFLA0ZjSpAMLlGoVQkGFEoxPP0dQpsH+qnTp1wqM7CYoRyXWB+cZFWn49qfYEPfeAMEzNZQlsFvvPVJ3n+8iwOfYOTR21UCp2EE3GafO3kpBT5WJGpdQXJlmFyTaG1WWBqrkh/h8AP//XD1Bo+Erk8D547z0Z6lduvJzl1bIRGzc21axO0d7eRjKWIVkpo9Vpq5RK/+f5zvHptidbWGh19KrZWyriaDFgMEk3+FkKhCIEWJy6fm6Wt25w6M0hDgl6fwPXrcVRVE5Obc6iFBoaGmvmkmY/sNrMYixAPa+nwKOw56OfY9m6SiS2aDWYSBYUrs2sYrTk2Vjah7GRqcQONPoRSb+L4qZOsrS/zwIExdM4+FuZmSUQ1OLwi25vbyCh6rLKXgibNL3/2Fh69kYWlTXbva+fNV1/j0P6D1CQPITEOURvF7DLRYI2ZjRQqvZOqkmHnrl0Ewxm2IlUu3XmDhVWJukrLwvQCT//xx3n9rWnSxTqFvA6zOYhU06JW2WjrCZAuLNLb4eTaHZG7E1l8zQKHdxyims2QyMlESgqbwUVcbiPVaoFUJonD6aO1zcWdicto1DbMditrq0lyuRSy4sTjq3P5moinfZhYeoN8Kc7Kch69zszcVpTW3iO8dGme9oCDgc4AOpOAxuahHpaoCFWuzSYwaRR0go1SuUytWuPCIwcRS5v8/NIED+xvJ4aE0eCgWEsSjKfJlBr8/mcf4MrMBk6nCx+wVdSTTcWYnFily9dHXS1TzTTA7yERTlOpVlF0FpL5LOPTm+zbs4PV5SgNTZ6FmRwjPS0UciXUDjddxw6x9MZrqCp5KoUC8tQ4xqNnqV57ho1UgdGTe5m7eRudxY1a0OJwd+ByF7n4VhS1Fnb2B8iKCYa3dVOrtvCn3/xHcgUdx06MMtDuoSoVSaVyjAx0Ui4JCLk8ra09aPIi3h43+UwGWVT41OOP8svXJ+jd2YbfaOLaxC3cXi9Wb4BYNEy5XKaQq6FTNVDX0pw6eoBXbo6TK5Vocrvo83vZWE3Q2tlGIh2n1ddLb28TiVwIT91IxajCJNZpkqyEcmGsNh9Wtx7iRm7MjdPT04HFbCIUTLMcSlA1m1CZjPhcXoztJsYkLXv6+/F6zdyYTRDHwtc+83scHjrAYFcPfpVCbGWW0FqQhcW7OLwqVA2R7/3qDd6c2sDf4mEjniKZSNDS6cFma2egowmVUsdgUDE/l8Lt1HFzOkS6qEOtSrEWz1Ku6+nub8FolFiJJygV6xhNAn2dXSTiG8h1mXJRxqQRyORS3F0qvHsg//a3/+apg8MB9E1r+L3386Nf3WBmMU1NU6Mu66hVaigaUOQKUlXFQKvCRz78AN//4U1kWYNFrydX0DA04KIerTG2TUW1YefO4iqSWqTJJdHQqKlVC6wvqZmLR1BTpcnsoLcrwwMntmOUwpw++wQ92yV6Ow20+tt48MxHuXHreT71O2Mklx3Ucgtkw3V27rdRVPK88PJdNJ4UC8sFrt+5iZSVcTvcvH59jVQ6g6jWsRUroBUEdFWF7i6Fhx/ax8j2IXqa4gyN7OPFV+/w1J99nOmpBdoGAqTTq/S19vCx3zpNIZ9CLAvYnUZsVoGzY+fRWK2YXWo2QzJyrYHWLLAeTPPpBw7wmU9/kVD9BvlqheWFCg2zjs2VMI+ffICiqkIkryIajiIWPGzFkuQieQb7d/Pq2zdIJ6N0NpsJSTKT964TDq+h+z/UvWeQ3Md1r/1MzjlvzrvYgF3kDCKSIAHmLFkyRUqWKFGiZdqyggOVrGxZEmWRoqlIipRIghGJJECAyGkXi805zOzM7OScZ/73g1V137p13yu9t66r3ttfurvOqdP96alTv1PdRx9ByKiITU0RLlh59+JpJgdCfOKj67j9QA9Na5R0N2+jmIhx5twoEwsB8rEILx49i1YJxhoNeqMahU5DsSCnmA0hEZfJ5tOYDWbkSIiF/JT1Ii4NzZLMJCgUZCRlMSwlNWs7W1kKF5mZnWfd2nUMXu9nU70dkczLOyfDHD99mc72OjK5CRLJMg12G6GIDLlMyeb1e3n3/YM4nU5ypDn67mVUYjsiyTLZvBejXU80UMTcaCKfSeL2+Lg0GmF41sPEwjzV9T0cOnqUoUE/KaHE7FKUWns1GW8Ek07BpD+AP5SglC+RyhaQqHVEcxlWdVn44NwwsUSFnpUNeJfy+OeWaGmrZmBgjHRGxJmrc1ikOVL+KFdDCRanQhjr7XxweYZkMo24nKbTamMoOI9FoUGttjE0NoFMpcJstbPk9aDT6jAYZUyNe2hv7+KOOz4ElLA6DVw+dgqhWKGQLSBRiqndvpfYxGlUMh1ytZpZzxI+fwyD2UQ4nebipUE6Nm2kWBFYXnSzY+ttRJaXmfCd5fKVCo3tRsr5DJFwAJPegEQQU6yYuXn3booBPyNzY4hlIoqCQKGYR6xR0WRp5MroEJFckkqxjM8vpaJKEIxk0aWipJMVVIIMg86ISKfgyvAIWzZsJJGKUxRXiMUSlArgtDUyfOkifb0tDI5NEomkKSq06KQmVAodxxaHsLlshIM+UtkSKy1t+CQpFFIZ4wvzVPIlUkoxrXYn8ZAPhVVHNhGjtBjlQlhGSanhbz/3T+xua8a7tISkMI1aHSSaKBCTKHn/6nXe65/i7bMXGZkrkEQgmZaiFIlQKETY7GIQykSjYgqFMA69HIVSYM4do62lCbUiglqnR6/XMjubIZ3JkYknyaXzWExOpKIyZoOViSk39U02EskCiXQarcnC5pVtvHJ89P8ekH/pi19+8sCuKsYmHTzz0ssIZQGTTUoiUkBakSIRVRAr5ZgUYuRyOem4gtPnhkApRSmXsWNdPblsBM9EjK4WEwaLlSnvOHq9iVwyw5q2KuamEpTyYhqq9Cy4KwQ8GT7/lQauXBETDF/k/ts+wqHT79M/NI3bGyaRWMBsLZIX8oxe9mKvFSMEoqzZfIDnXrvE8195gg3tBmqNzdQ5BVYaW2lqWM25hX6sTgdCpUCpUiGfTKHXqRALee79SBcWswu/30PD2o2c/v0h7tzaxpEzF7g86cdqVlKrVFDTWsP0vBfPUgSRXIPDVkPYW2JxPM4bZ05ztt9NOqvCJJUxF0py5gcf5kLAz8C1o8zMS7C6Utx8Swfh0QAfu+lmcgoxz7z9Dh95oIXRQR/bdtSiVYn58L3ruD7kxeMPkY8lqHU5mRibZ2hgno6V2zh9ZAipTspjX/g4v3jmZUbnTXzs4V4aalbxi+deo7F5JUfeOUepLKG5tYefH3yHUx/4ceicbN5qRKErUmWvY34+glZbIDgXJVuRURSpyGVMBHwTFCUahFiW6nob894Y0kIaW9MKmk1SCoKa81fOkoyXOXz4CjfddBemmiKrmi3sumkjfatbOXfuOANzciI+Cdo6B1/72+9xfeQYfq+P1T3byGb92Ezt7Lt5M//xq1dQSqpYDhS4NDSG3upgZDzMxGSA65Me3HExKpECi9nG1OQ4m7e0sOwOoCfP6QsR+jbt4dz4ZSRClrlwjGSyiEQiJiXkSQSjiNUOWl1aZuaCSGUpBobSmAxBlNZaFCY9gkqEoNaQ8pcZXVzCXxShyJcwmqWMTy5T7dRiVEqoq6vDYTFhsmrwez0IFTmCVIRSoyIWCWFSyhCXc+SSaswOB9lKlrbOdSgq4LBoOHn0XcQyKcVMFpEM7GoT7sVR5GUYuz6ORW8mlUiQSecpK0qIVXpCqSSVYoju2h5MhmVShTS/eek6W/d2IpaICCwHWdnbRTFbwGDUI4iSHD98hb07exnyLVDRqMiGklRb7aSXw8x64ihUabyBGA1tK1j0+NBpKiQiQZprzUhKWmLJBIJKQjibIFsuY9VZiCfTFIQiEW+ShgYnk8Pj7Fzbw/T8EHUoCVbyyBRSRiJRCjIpvXYnFaMOtVxJ2BMiLclS5zBDPEpZLkEuUyERy6BQpNFRy8TAOI6chI5t2/jsJ27HKLKSCi2hllTQGgpMu4P87shlLvSPMR92I1ZlSaeS7NyykaHhCURiyBbyhBIJXBYFLoeFXL6AxiigVYuw2eupUMAfKCCTSAi5E7iqbXi9ARrqFWxf10KVTU19o5P5pRmK+Sy5ZBytqRnP3DQihZ5NfS2cvjaCUSHmnYuL//eA/Omnv/NkhyXGq4euEk6rSacKZEsZxIIRqaiAtCLHE0hiletIphKodHmWPRJKRQlOa5YNW9uZnZ3ljnuaWPTHUNkNXDofoHuFgbsPrMeuUuALp5AZFChEWRbnxPzkG7uYvLKEWJ+nw7mBb/z0FZYDEazGHFu7N3Pq8hjhcJzrMx7U0jIhX4bdBzYwdH2Ah29VMOv2cfPuB0iV8oQKJr78y1PM+SYoFlXk4nlS2SRdrW2QzJLNlsmQ5fjbCSLxIXq6url4apwd92wmmm0h7Y2xf2c9gjZFZGkZl0GEWGmgWCzh983Q3WaFTAKTw8nv3xrEZpFQ1yDB7ynxj59YxZVhHy8dG+DBLWvI533I1WqGR5fYv+duLl8b4+T4FT66oYe+3g5QF6nkvHz03r0Mz4wzv+xm5bZ6VrVsZSkeZW1rNYF0kan4Eo98dCXDoxnmBwfYfe9d5PILzA0uMzY7x133d9Ng6CSYnuHM+9No5EWGFsIMvPoPzCwv8OKFWb7woX1896cnUah1xJIRdmxrZPueDq5eG0MlldDV6uDsFR+f/MytdK3optsm4cCdHfzqhUvcecNufvKb43S2uljRtZJwIoKrUQXpAv5MBb3KwmD/Kfp6dnD3jVs4duYMG9u6+dq/fROLvQ5btQ29WUmjvRO/9xLjwyP85aceIpIc4dzlaUoSFb5ggngkjFxSwa4vUqPJotFAKRfFrLVx3z17GB0Yw9Ju5rY7bOgNg6xfZeby9TD9k0uoxdVEInFSqQo9LhPRVIi/uLObybkAVksVQ3MLtNZokWWNqDGQCPjpbetmYHqARksdMnGMFU02NJICKkOW5aUCptpaCrkCGSFDtVbFmg1r8S6E0RhMKDVGFqfdRAUrgWCetnYt0eUUK2pMhENlak1ODDY5l8cGKOdLVNJ5pAoJpAWqe6qJRsLIBBV1NTVc6u9HorSTVJaIlUQoDAJSsYwV9e3k0iWCMR9ZrORJUVOjpig3khIKiEQQLyZRiyoUyVBV3cGQex6tXE613ILPvYhMJMVXKGPXFylX1MwFQijUZVocJrQqgYmFIilxHmd7A8uRZWq0Bmr1FkQqKFPGYFBiVVtRCVlUpQouKSiUEvTiEnVGG+YqC5KMCK1CxbR7ipmRecLBMBGpEg0CimQOjUFLR3srwxOzGPJiHC2NfOLOe3n48c+xu28NVqsZcbaC3RgjEY9xaqCft08N8fa1a+SNcM+ePhaWKpQkMXyJBPFimUwsR21NJ1UONd7FRdpX1BLyVsjlpUQSS3jGC6SECrMLk5QKakx6NbWtdRx/f46KTIxWamF0zkckECebyhCPJmhs7sGoEzMx72FdXwPe8DJVhgqRogW5YORU/8SfBfI/2SFIJBL9AjgABP4fPTufBD4BBP/o9mVBEA7/0fYl4BGgDHxOEIRjf+oSTotC+NrjDgYvSHjregi1IENaLcYiETG2KGATl4ikE1irDYQjMVY4Tbg9YnLyNPFECYe1hESsoKlGTmBJwpw/htygIBfPc/99XVw5M8GCr0Tvqib8Cx7k0gJNdUa8I3GGkgK9LfD4p7agt64nmi/y05/8iqKoTEe1Eq9Xikibw+HSsRRM0WQysaVvPU89+zIPfmwzyVyJ11+9hlhWQiGxky+GQayhqdHE4PU5Orta0JsqDPT7qTPI8cUTJOIyHDoxImkOi1OgUlZy34HdiMUiMuE4BleOq0NuSvkY29fv5dJFHzXNIuKRNKv6DvDNr/0AR1WZH3/z07z2uo8f/PI1tGoJWzZq6GrrYXE5S3W1BJ1KyZPfO01BBp+9fQ0TAR979zRhkGogXURRo+LSwADZnJbhgSkMagF0sG/jbhLZIgpthHxEz5sXrrJ6RSsGs8DU5SyzPi8ydYUqiZ3BoIcvf/xRnnj6Z+xbZ2duQsmVsUU6VzaQToaYXsggL1ew1+i4detaJpfmmJ5fwKl1sm6TnXBgDotpC9niMPPuGI994mG08hyPfuYZVAY5apsMjUjEh+6+nYAvRKoQZGnBx9YdvazsWsvffekb7NzUy6S3wOFTY9Tb4e8/+wCVihK3z8+8e4Kutip2NnZzeXQSsV1LWZTn2uASPn+CyFKSxcUUgqiENA9t7VUkC36cLhN337GV3/zmPR78+E7CkTl2bvkoB9/8DRqlAp+nyPl341RECRbDWbauqqW9ykzvutV8+HNP86Ebnbx+xs9Nu1opiyvMXk/zxb+7le8+9Swps5JsMMeDd97B8Pgpaqz13HhTLz965tdYtX3kyglaHRoMDg2KVJm0Vko6K2F0dBy93UFgXsqK+hK5JIilcsqZApWimHt33EA2L6C2xrh+cRoVZWxGLVWY6PnKhxl+/jdoU2IyOR3D7hME4npUDoGQ3UzJk6K1QYPNuBKxaJw3jo5Q01VFNqahprmOY+fPIUaGzaRHb1CRzOcpL/rIGg3Mjc/Q2t2GOCtDrhUhiNLk4yK+/KUnee7H3yKbq+CJhqltbUAhleLuH0HfYGY5HqGhtZ6RC5NQkLF6VQ9LSS86tR6rVs3w1TH27NnE0sQ4UVmG9RUXC5U8RTnY7NXsvWE3zVXVjE3MoFeoaWhpwR/2MeN2I0oVMDXUs6KxAwopFianSOezaLWg0sooS7IszMY5ce06vmUvDbV69Eoj2YUoQ7oshaVF5PY66uxOLl66jM5kR5xVsnFNK6MzI8QTYnQqM2VRkPnFCHvWryEtylFtMnBq1I3gzzCZk6AvpjDq5NS2VlFnMjDvmaG5oR5vtI3l5SNISi76uuuJ5afJRA3IFBE0ump+/bs3qKut5t3LS39Wh6A/B+TbgRTwm/8B5ClBEL7/P/h2Ai8C64Eq4D2gTRCE8v/qDJtZJDzxuVqk/hJStZF/+NkYVg08843NHH1TzZHhq+j0SQKLJW6+qYZ83MN9D36Zb3/994jVM8TzNYTTy0iR0btGyf5bbuEfvvY8RqOcVLSA0aSjqcNMIV1GLYL2ThmiVA0Hj4yzZbWc189FeP4bf8njTz1LOVBGb1fhUmoQjAIzI2HkdhWavILpUIz6BqirWonFlMPvX8a9lKRQhmKmQkOtnchyiDvu2kr/yDUqZcjkFMy7Q+zdYmNoqoBBWyYUTlMuV1BoDfz+iZ/hrxzmvcEI5987yd8/dhuHT5wlJwlS47CgVdtxL+UpRidQ29YhKvi4edtN6JVVnDjzCoJWhKOhhePvHyKXqqNltYyxES9fvPPz7PzUN/juI5v5x1+fp9VV5POP38Wkf5mBixOQTlLXaqO2voV0YZ5SUWByyEiHPUdKMYHFdRfFcIifH/uAbzxyM8+9eoKPffwe3j90FncwhFptZ3B6llv6Gnnj5BwfvaWdnEPH0PlRNqxso7mjm0OXDtFq6GZwco7B/jB93VJ8ITEamQKtVovIXCCXhpIQIhcyEk4HWN2hZ1P7KjyLUY4MLpJKx2jt1JD2Jfn7z+/j6aeOsnPXdq7MzvOlT36Y/3jpDZRqgebmVmqtTUz7r9PurGVmfhpnjY13ThymHBe4ce0tZG1pKgWBUDDBciCBwqhGLM6w7I1zx4Ebifjm8AbFbN6wicX5V+lt28K/PTXI2NIAD9y7hqaaHfgiZ1n2iKk123n1lWssBDxIpXqcFgmP3HEPdXUlvv+LD1BKvFyeKdLVVEtLSwsX+ofRkuK++3fyd989iFUP1QYtN97YiFgk5cSZAUoKI6u7rShlbQwFp3CINejFCTZuWE19dR3DZy+x9cD9fPVHP6Klqht/yEMun6asLDD9wRIP3LgHk1LCvgfv59nvf5Umuws5FVoaeqj+zF2M/Mu/YjTUsTyzjLRXzYXX+omrisxlkzhUFm7Z001erESqlTA76+fM0HUKJQXJgkCiUEAoiVDKoKejjsHLV7nnpnUsZFREI7NkBD0R9zIyRQGDzo5ckqDHaUNpqycVSzPkmyMRz1PJV7DZ9bhaGvAuuMll05REeuYXl9m8ZgUL/nlkZTEGhRiz2UZwYhKz2ISzrZ37du1EbNVTTISRF8V44lHKxRx5oYhZbyYdWyJdkKFUK9CKBCqVCjaXBqvFQKFUYHZGxszyHK8dOYpcIiUvy5NVg9VooMlRy+SlQTaonHxgzNBpqWV82U2fqxp3Lk5BpCIdDuIyukhmC+j1WiauR1DZBNqMdfgS06SSWUoiNeJyivNzMcwiMRKFGpvFhsVUYEVdE6fODuLNJGlubYGgD1u1mWQsSUN3D2fen2Xvjk5iYT/V1TIK6RJf+PGp/zMg/yOgG4C3/wyQfwlAEIRv/XF/DHhSEITz/6v49dUK4WdfW42gMPDm8+9z/5aN/MvRD/D4FFQkIoplE1UGH7/7yScJjId440KKo/1nSKfSlApa+lqquTYzgU5joVRKoVIpiKeVlIpBFFIdBpuCiDeNVC5DppCSyEbQiXSsvaHMnRt3cOlSgk2dap55bYAdm3fw4iuvMuYuc9dWFzv33sQzv/oVhgYZDpWJhioply4u07W9iTVtVtxLRV4+NEHEI0esDOMwNdGyIs6lq2KqagTmp0KoTSDkLdQ5JAzNR1jT66TJFMde38LIxAzNIg1V66qILOfwTc+zcWc35aKTU+cusaq3lYXJEY6Pws4talqaC9S51hGMxHEqVvAfL/6a1T12RCIzJ08P8tjH7ybo93FbYy3/fmUMdzbLul4n0XkR3rSHcL7C3NV5tq9ooaKTMTgyRyibQ5DAjRvrePTxj+MehBeOPsvxsTj5kQQbb2qgGC6RKUWxmxrwhpM4q3VEJmMk5Hl6WldxzX+N3voiTa4V3LdnL68e/ICTM26ceh0vvHaN6ioxgWSFne1WxIIcXzhIVqWk2dZI2DPCP39lO+dO+amUxdz58KeZH5vm8W/9iFV9FkZH0lhsaiJ+MQ9tb+J3Jy5Q0+IiJeRJL0UwuSyUCgV0JjN33noDAx9cQWdOUZIUKeWtRANxCqIo/rQMi07Guq5uJsfOIdFKyGYKdLU1oJIkSURU9Kxbh6tOyulj12lyrOXK3Et87MOPszA3RDauI5n1ksjLKCRFvHtkjtGpJWxOHQf2bERf1NK5NsvQsATP0gzv98+gE6vQm1UkchkMcgkP3r2BN89fQiYuIuST7Ny0j3Awgzc2zs0P3M71q3MMDF3gk6sf5Jy3n5033kj35n1MfXCKsiLCpQ9OMxVKkExkmHNnqDZbcBrU7F7Xye9fOMnujU3I7KtJ59xsaG5DX2ND09tDsmLGLAqS9M1w8dffZvvdn+XnT36DQEHBnEzKDZs2sdJcpq6+kbmlNG+eP0EiJ6ZAiHhGjFgws+AJ0tG7gkh4AXJlHA4ZlroO3LPDqHRWjJI4ne2dvPz7C3SuNzJ4bZ5qg4qulhZs2jra2hvwBZZJpMpYzRrkFQnVVXaiqQKCWIldo6AiBrVcRZ3DRDiaJ51JEInGkGugLMjp3bqZifNnKJRAKOcpl8soDCauD44glQnodQ68vmWqrWYMLWt48Q8vEFkOMzY5Qmuvk/Vr+8hFS1hVBvyzM/hIIdEraayqZ3FiCZfRRpA8sYk5TPVqXGYDRoeL37x2Elutk5g/jcVRhUZRYHIqSXW9DqdKT2eHAbXSyd9971l2re3j2mCR9dvkDPSHUeqlSLIJ2tqq8S5JuGungblgnHeuidm7xkI8NEtdSwdvH36L2sYWGpztpKLTtDU18LlvH/svB/lDQAK4AjwhCEJUJBI9BVwQBOH5P/o9BxwRBOGV/0nMvwL+CsBlV625/S4XfS4T+ze2cGF6nCp1LQMXRzg+nWf9Bg02a4Bc3Iyg1PHmK9dZLkpoduhQy9TIBBUXxhZApEcsjZAvGChQQiFUMOr0ZPMZItkCRpWFRNyLWuPkk4+0EJ/3ExHH+fT+G3EHEthc7bx+eohnfniRvlUV7rilioOnZvjc/j1cux6iPzDPYw/cRH5MAaZlDl67gDesYLR/ieoaLUu+DIViBYvZRKycYF1fDXqphOvXZ+naauP6oSBlUxU1xhwP3duBWFTFvR/awyOf+SKra9cwGjxOZ3c97uki9+xvwuVo4Xs/P8TaPXcw8t5FXnpziL99oguNwsnFq6M8cedtjASWkUrKTEfepV7ZikO/ht8NvMZn7n+ISKzMnO8ICukqZn0XECVtfOHR+/n+T3/J+f45QrE8eqOOcKBMc7OR2299BAnH+ekz5/jC5x/j4Ku/IhCXkE/o8RYTVKllyOTgDaWJhXLoHEqS0SwaNbTUtGGw6UBiZP+OFl574yTvjoW4e5eVD04F6Wpz8fblaTa3GqnkcjRVGZmaWaauQ8ld+2/h/XfOsRQLUaU1MVoWofKXyFQStDQ1s7KzwvpV25FowiTcVsoVA3/7/Z9jEEeJJko0tijZvcpEoazg7EiG5mo5+/bt4+r1Yd47N0KVTYNBa6MU87CYV9DXWEeDvYxYrsDrSXDT7h5+/+wFutZa6Fhl59ChMe6+51P4/Kew6LsJhWZwOW2cO3+RhcUgG7avZHoqwaWzHgJLcZRGA489sgtJMcrQVJqZ6WGyeRkzy0E0KFm52olW5qKjsZP+88f50N9s5+23D+OdNtDVK8fR14FN4UJCHt/iJGv1qxiVj6CU6RgZWqBcLpMSJOzftpNnf/Nr6pwthOKLqHQu3OOj7F69G5exyKF3z7HJtYayRuDAfQ8QycRorHaB2szQm8cwblmB1yG2QQAAIABJREFUc8OHKEsKlEjy3j37eH8pAMZqbrihnV2NYnTOCKcuJXnHHaCjeQexxASvH7pMe1cnx49fxajXsaq5gcVIgIb6ejyBWYRolp6uWm7dthNyRrp67ZiyXtL+ACmVlWgqhlmrYd6bJ50RY7XJSKSimEwmcrkYKoUGBCnBVBF7dT0KuRaRkGO0/yxLSTEao4N0YI5QKoJWpSMWDXFlZg73YhqFvEJDVyOpZByJAMv+MAq1AbIV1LoCKqkRhaDglpu38v7AO/S1tSNKSZHJVHj8C+RNBjzLUfQyNcgzxD0xFE0uatRgSGpwlzysb25gJlHgzLVlMrE8Kp2CjkYrpUKMXC6N3G5HS45X3xmjy9xOUlVh2TfHysYWWlucHDoxwq6tDYxPBFCJy7g6u4n4EpiMWqYmRrh//w4GBi9w5y0385vX30Kct9LTa0WlyvPYN07+WSCX/kmK/8/Hz4CvA8If5x8AD/9/CSAIws+BnwPYTHJBlPXS1L6ZkZgZqdlNo1KFak0X1V1eUjkT67u3k8TI7KAPsyzOhk06zl+IsuGAk/MfXOWxx9bxg2/1gwbkmjjishmxKEI4KEbIpqmtqsW95MZVpSKVS+Ge8fDWeS9funszP3z+GH/7yUfZccfXuXGfC1Otgi8/sY/nfv4e6mwjxg4j4feX+NTNa3n1xef59xdf54Unn+Cv/+IRBLWOgOcqdquGCwNZvvrDw2RTcS68+Rn2PfgiElWaQFrETQULqUYxI9Nevva1hxFpXCwsXuN8/yLZdIXjo6f44be/yHun3+LdUyNsXref555/jd41G/jpN38NEjVypYSf/nwYs2YGl8vJl37wS+766G6OvnKB9jYVi5YorvoKm1asweMeIBBSopLv5O23f0F72xZaOur5wte/i8EkZffedRy5eAb/dBJlScbStB+v7yzvHjnH1775NX74469idnZQmQ4SzPspV0zkpRGkUjNSCuy6cTPH379KNifGYtQzPDtHbUrMUkqDd+oUD9z3l7xz7TmU5SocThWJ6BKr6+wEl6MkIil0Bi0Kgxa9rIYzx2eYdycoSrN4KdFgcZB3asn4vTz80E2cPvYH2upWcPHaSRxaO0VRjBXteqIhCa4WMQ+s28Jffetl7tu2kg6DGEGUYGLkEnaVgU9//CF+/e+HsXVWKJuVNJMnnHETmFDyyY/8Jd3rJYRffQ5lncBktMLAa9dJR4tYpSqihSAyWZpE1svyiIdIOYK9oRbfwhCvHoyhkVaw61UEszm+8ne/QG2A2hUuZOUCJrUSrVyMIFUTXioRkC6wqaMGnUtCKDxHVYOZVeuquHRyEM/JRVav6qGUk7O5cxfV9Q0sDnhZCuRY172dTI2Rg0/9B2cyx6k2VhEP+clG4qyub6e2rYdMOMpCSUAqlRMqpnBKzUg1EhIzEY4PnCEyE0StkZKMj5N352i+9xYGH/s0B/7pUca/+EPyqQS+6UX6jd2kZrNUmQXisRBvn71AT7MWZ8WESARrN61keWiRvT0Gdq/ag1QeRKnoxjcfQ2s0YO3ew/jlt0jPhvAmwjTVp4gtXSScrWdpPoSgEJNKW4jFJTS2GVgMRcgnU0QTQQSpBp3BhLkuysuvvI1IomTrBhfu2VFmL18hmQ6QzymprXNicynp6mpHaw6j0AnkclkcFhNqlYqVK5rJlcUImSjuaBJLfS2RQJArC5NIZXr8iQTpdBokahQWFZ5QmI46EwMfDGOsrcbeVMeGtgZOvPMalfY+ClNi3AZ4f3iGj93QQcMKPS+84qFQiBGKRLFYXCwOT9C7podda9dw6vwc27ZU0VfTg9JSoJJOEM1nGJ9MYFVoKYjzaMUyqnpX8tLLv6K5vo7DZ4a4cWMHv3z7IKGIgXTcTzwbpr7W8Gfz9H8rI/9/s/3vSiudLQ7h7l0Stm9yIq2oKKi0ZJfn0NW4CF6vxt4zz9S0koHJ97lnzw14cma+/53DKMQqPvupPkzWRm7YfCdf+97dZJN9pHKLTC8WSCSj7Nu+iZ46FS/+4Spd243oM1IueZe5ej7Lvz62hZRZTCW5wKr6ldR0tfGHF47xi19fx9Ur5SN3rSVfXsSl3UN7+wqSxRRLnhGunrqKsaqD5sY8m9bcxx8OPcfUXIpqs4pEqpVjZy8jl8WJChlis3qqWtN4YwKqpBKpLE6xBG01Kn7y9Lf56KNfZtPWLtzuJfZsaUIkF/ODH53CZAbPHKzbZKGx2sWxN4bJi7UoFGXkciVzyzHsEhU3bLdx867VVLIlZIY04XgFJDk+eHOMpl4NH/vIFxgfmyaXhIX0JJnFGfbeupV4UuDMB+epdagZHg5ycdpLwCeh1qFjORajIlLSYtcwnQhz16otHL94ljxqFCoxLc02ijm4MuQnW6xQKeQRS6Gv04A4IuApJiiLZEgzIoxGSGUklLNlUlIVJp0cl11HOB5j3p3CoNJQW6XA4/ajN0m469YNXLg4BNIc23Zso86sZ/++z/DmWz/iP56/jEarZeuuLWxb38W9H/l7apvNOCURzM06jAo1Ol0N2YwUu1XFG++dw2HXs2Z1F2+/dYpS2UJzvRaHQ4FQ0DI82s/rX/0G3zryE7a0b2f9qpX8y4+fRmtWs6J1FSaVgliiwooaJ9djV5gbmSYn0SMU60hnPIydzyFWFiiXxKQzKRobLVApoVQVEZXlLC7HmVwusX9tDYmshtvXtzDhm0HZoObi9FlqCmY2rKznyLUFqmxdrFqlYWouQSaQwy9J8Ilb9vDy4Vc5dsjHlx+6n84qHe9cHmHVhjX45+eJh/xI5GUUeiedXd289dpvaTNuQipOcvtfP8zRH/wHRUkKaVFGUixQpVBRU9VH7WceY/jbXyKQKbDou0ze2ovPE+DA/g1UKiCW53j29bPIZHnkFhX+0QgPHdjPiuZaTEY5iXgQd2iQcrGBWCRPa5OGZFJCMOFm1Qoto1NXkdlWcuadIzTWtjPmCVNMiimLKngCCawuB95pH7F0iXQ2TlngP+tJIrBZpRTLSlTqKtb2qphfjtNS78QglnN+ZJqOznrS8TzZuIRUyUdVdS3x+DIWowxPsIJCrMTjXqC9pRp3IIFWq8duMROMBtBr1fh8Pmpra4lEQpREZdZ3rURvgAVvkFg6ScFfotGixOZs4ujSOaKLMnrrq9jR7eLcwDjBdJqMUomiIsFqNDMzO862Vas5fPwUTlsV0UIIramJ5Zll9CozFrOLk9NDOLQ6/vqhrfz6D8No5RkkKifeWI7eFiOiIgRyMVSVJEWFFqtRR9gbRis38u+vnPkvlVZcgiD4/rj+PLBBEIQHRCJRF/A7/nux8zjQ+qeKnfW1MsGuK3Hbvr00tGVIzcq4adtNnFt6hcWrJSTqBNdn57h9xw7uvHUzT/38FV74/STmRrj/9u1IpXYMujTvvjHLHY804jSsZNZToH98gNFBD52dUrLzHQwn3uHOPdUY1DupVxj46eFDNGgybN+5HXlFg0QJyWyOa4Mj5ErjrFm1g7I6QykvYNHVoKiIiJcmCQTbkErG+dd/u4yjpsKnPvoP/OhXz1JIhVgOKxFJtZQKaVpsOWR1Tqavlggk/dTb1JQEJYK0hFOnIJHJEy0mkBT1KBVifvi9rTz/yzHeO7OMTCVgNMuJhHJQzLJlYxNXB2dxNVQRjyZYCqfobWjgth0udFIFY9NXsNb3YrIrcOlaOD/4PN2NW5n0DWG0VCGRiIjE8+ypbaR6ZTcXr16htrqaRNiNxbaSj332X1GazVgNUean9EiseXIpDe01JVKREoW8Bm8mQE1DI+Gom/Wre/AveknmKhQTSYr5Eo21Uv6iZw3fOjdCIZFF0GtYXePg+tQ4a3qquTLuR6c1oVdASSLCEyqgklRQixQcuKWFSNBLS301E9ev0tO9HYWhQjQkQmHI8PQvzuFqtlNXpcVpb2Lk+gjd3W0kk8v0tNeSzwicOvUe6zq7OH1+hL17b+LCwAD5fJS/+NDjDEwdJ5YoMrMQIZssoZIoaK2zsKK3jQ01vYQyy5x6/woVlYiSzE8+X+bDd93NkaMnkWXh/OQEN2yvRydr58i1gwSHdWgEDaG8gEosoqbKTqmSJBQKYa22kI7lEJVLDLqL3LGjjqtDGf7xk7fywdXLPPz5PfzTP/+BNRu38fwLP2fXxq3Ud+vpamjjuRd/iU7ayK7dXYxfz/H4Xz+KNJSnf+AMx06/STiSo63WiVjjwmq1EJk7jdZkJxZfpsZmQhaxI5WK2fzhWzn69G+RaBVkglGychErTNUYFUba/ulH9P/17Uykc3QcWMXzPz3Mht176FvRhS94mYC/yMXAFP2Dw7z8lceRmbaQSZ9DnskTyEgZHJ6gkEzS0hJApipxfkjG6IyK2fkrpFKgs+losUsoq6uIZzPU6BRYml0szXtoqG1idHISjUVJNJIkmMihU9swKnVs2N7MWy+/R1NrFYtBP9kwyDUyRHk1ZrUSlDA24/7Pf37EFVprXDR3OLg+NE5tdQepyDSCVIzNYuXMpWF0Zi3FYhmFWIrZoicVzVGmAKIiDpuVeAk2NzVwceQqG7fsYPz6KEaRlGQpjzsSxR0oI89LWbvCTn1rMxL/EBeGPVRq1BQqFky6EqaolJK8SEudGmPHSg4d72dsOs7qjh5C0VEaLBqaO1fTpFXy1JuHKBc0rO9p5cTpU5hrjHjH0qxd18C0r0xnq4ET7wzR1lFFLBqkvX0FP/vd6f8z0opIJHoR2AFYRSKRB/hnYIdIJOrjP6WVeeCTAIIgjIhEoj8Ao0AJ+MyfgjhAIa9l21YZydnT/OEiqO05dOo0apOJ1lqB1Rs3oj5zFklFzMefeJ5Pf/g+ZhdPoXIWKOZlUBIjMoR48KFOTn7gIZQ/xUD/RZamlFTVS7hwIc13vtjG+ujNxNMT5MQBMs4ltvbq+e1bU7w78gb6VILtN7SyauNK7rvnAa7PXebgkaPIpGVu3tqGWWXipT8ksLf4qCSKnDgXxdFdQVcxMzbyDqVkhuWIkmi5gkmUoCwWMbZQ4sE+J6K2ILo5I+7lJIJJgayUQ0KZRKJCsWKloS6KOGuj2tzO2Xfe5oZ9vVw5N0UlXaBSyVIqi7nSP4scCSMjXlrqq9i2soGx8WEmx1Js2FyL3GpA4xLjXrxEQ2cTtupqBhbGcVSbGR6Y4Ka9PUwtzTLQH+DcjA9/1EMqP0U0ruTHf3MCW7MRg0FNZ3M1Ad8QElkVGrMIs6PIyp5mwhEx2kUF0/MhpGoD584NIxMrqEilNLmsaBVlgrECUZeGogBNtS4q5SRerx+5SUn/QBSrS0cslMGg1iKXC1jUMuJLQe753GaOHRukkJPT1NDDXz36CENDF+ju3cnFk9OcPD+Ho1bGzGAAu7SKQ++cRt4gZ/rFU2xbY8JvEZMN5tm88gaWl8PkxPDa4QtUuXQ8+ugTPPvLXzE+46ejqxeL0UK4LGLbRjuRkSl++/Ih1HdJef311/nWE3/D4//6HZxOJ06LgYmRixiNVrQdWtolaUyuLbivnKe5tos6Q5mJCzGKUT1mW5lCKoOj1sqs20ufRY2vJCKdy+LPpknlcoQTaU73X8EbyfH+Wye5q7eL92ZO8KNvH0RUvMgjX/oO7/3ho9Q6nmfonIeVtz3IG0M/42P372Hd+tU4tfVQFGN06Rn0JNGKg1SSOlQ6E8FwAY1RQiCapd2uZ9PGWzl74giJYhpFFkrlIvlynlA2Tl5I0yaVIJgr1EvFrHKu40fjP+GgJ8/YxkUOnzxBXXMDNcYcb37rx0SCJ4l7fky5YiaWcVHr+j1rOh/l6IWn+bffRpHpnYjEiyiqpOxacQ8L7iuI0iLQGFAiZcPmNtLZPIODEzhsLiZm5pBZLORTRZwmO7GcG4tJxuLEdX734iDVhk7yuQJWiwudzYzTVE0BDxcvz5NP5SmXdWSjCQ7sa+aVw1cZnnaRKZTwxuZoq7YjCCHa6xycPnEFa1MVoVSafLZAPp0nGi/Q1O4gHHWTzRdQiqTMz0xSMpr42StvYC9b2LKmhuWlAhqtguZyAanOTpIUJlUF+WonzYKW5YwHsSxPLJSjZ10DsmiRlEhPxjOJRm2ksdbH9auXqW2toqW2iedeepGmhgY0CQVz4RLLNW5uvvkG+q+MsHF9B5F4DouuwKVrAdb2trPg9iFVmAgsZ/8UOv87p/+cjPy/ejitUuHp7/QxNSylsXk90egEpaybrEjHXQe28+UvvY7eGuOBVd08/dtrvOWJYTLYyRUDiCUGtq4TeHD/LYSTM9isembH8xw9fRUhXeHxj+znm88c5PtfuZusEOXEqRHWrmwmnAlSa29kKHAVR3kt75weJx3L8k//chcnzryKSuXk6JvzfORjq3jgzk/xm5++gFiV5PjlSVqkrXTs0/Hsr65QymaZH02jsFVQKfRIpVLkmggzCdCWpDy8fxNvH+0nHhfhE4uo0iWJJmFDcwuD/dNg0rCiwUBLrYOwZ4mL/jTlSAGHQ8LNe2/k6WffRG51ocj7qJQUxKRSdFIBp70BxNPs2dRHKJQnWRhCq5Lzlw98nsNv/ZS6lT04jBb8sTQufRvHTv2Wj3Rs5v2Qj/ZGF6K0hAlPmClPmLG5BHOLWWoaJLRaHIzPLJGXqMmWChSLeVRiAYMSfEmBD61dwVuTi6gzZSqFPNk6ER+9YTPnhwaRCxbiiRJTM7OYjEo2bVpBMpvh+tAMubychmoTgUgYjUjLcq5Ifa0eoyrPR+7aw29fOojUWEOREPvXrKF7QzvLw4s89avDmERmdqzr5bULp/nwX91ILCbi4BsXaKrNoInK2HrLGo69dYWIXISoHENptmCsiJmeDnL/XVuZ9cRBaWN29DIBSuzbfwtWuYGJidOk4zmCERFWO9y4aQXr23qx2hr53g+/S9fqRq5eG0OqstPXs5KBgTeQ6Z3suuF2Xj74Iu6xItKChfp6C54FP8lihJYGK1u27+Xtt98EsYTXzobobpAzNpfh0/duxFXtoFwKMDg6TDBf4Otf+TZf/843WdPWRFu1g0LET0vrJl5+701WdPXiXhihobqZQNhPOiUml8+i1VqRVPIo5UVmF/xkU3nmkkkiMzm+8+m9bLzxQYYOv8lAMIxKnCceFyEppXBpNGitdlq33Yzltr9ABJQKAj97qJGJ8zEiEh3XMknuvGEV/kSB5eUB5DkTTzx8G6nEFOu2OPnqN95gMqxCoTWRyaXpqDIj04gw6IwURALdVQ0sFv34pxO0NVYz4p0nlkoizkMuG2H/tm0cH54klYwhqRioadERjsbJpQScdhXe2SxiY56uKitzfgXnLwywapUGrbqHUjFJNBzBaFIRjVdob7MwPrLMuDeJQyVn3aYmas1aZmcXsFY5uDY5SZvTRjwnxaIr4mzr4sqFEVTyEnJkaCQVXB3NFEsZivky6VSeKU+YaoOKYiFHxWCgRaZGaa0iMHGN5hqBowtJ+mqMTEwt0WJ1ohWr0NcaOTu8QO/aDl589Tw3b+rjhaPXqDYqsDntFEtl4tEY4eUk3Y1tbNjbx8GX32Xzho2Mzl9Hrdexsmklz7z0AlqxCLNTSwUFcomd98/1/1kZ+f8vXnY++eSTT+7es5bLV07Q3SPgmV0kWZShE1eYmr/I3tV2Tp+ap6gxItQq8AegmI1Tzknoa7cweDlJlWUBpaSGEwfP8IXP3sParX1k40naGq2o8gbOTh3njtvvZ8k7g91ZYSmQQaEr0eZooSIrcb7/Gjl5momhKPt2ddFhMNPsupVh3wBn33qfjCDGYoTTb42hbFYjlBdYnC0SyMXYtrkdtc5MsZQh7IGnnroNIaDC441zbWoGi85EbbcOqRDk0UduYWmxzHhoBp2tikI+S3O1k7mZcWbCRXyJAlK5AoNVTSQzw4cf2cKRt4egIMVWJaFvdTWZFCQS89RolSwk5vnQ3o1kZXJu2fcxTpw/yE03fZ6XXv0dBRLMzfg4dXWOjgYFGbGZyaFBjl+Y5rXzkwSTS6g1aoL+MFqTnHhKjNIgIZYPUSxpiBXzqAoK0qIyNqUIg0zFeElMKeAjp5eiKJSQlsxcvbRIailOTY2RcCiISq8ik00hkktZ3V3H9NQcsXgRp1nJ5FKWUCSFWKlCJ5FisRo4d3qQmupqMvEldtc24WiQUFr08ssjV1AZ7URFAXauaGBUvszc6Bi7tvXSf2mQawNZqGlm/9YD3HbrzXiWTvK5h/6BM5c+YHIqj6XaQUiW4NJ7i/inZxDXNtKkU/LKi+fZv38DekMV/Wcm8QWXaGqsxmnQUxZXyOf9mHVw9qKb6tZqgqFJfJ4p9m6/g7MXThMITXPLlgP0X7iMTKJDb1ARCEQplPLI5SKMehMTk1MUSmLmlxPkclliBQlUSpwdmGFoyEtLQw8N1TWY5P+Nuvv8kvSg7n3/rfBUzrGrurs6p+menunJeZRHGgWEZCSBEAhsIx842Bz7GJ/jA7YcMGbZYGxMsADbSMbGgJVQGGmCpMl5ejrn7urKOT/1VL4v+APueXXX1f4jPmuv/Vt7byV9IwPIcyUW5qOUlCoCoRib8Th3Hr2TYHCGRtlENJVE2WrR29nP+uptssUacxsJZtYzrEdKtKwaxLKKv/rTPyNXSzM9fZ16CSSphFYrYK43kAQRq0GPraKjlF8h9NL3ib/2Ag88+4dcufIOmmqZvV1eIrkkdlkMeU2B2DJxY32S8zcj/NsrEeQeMya7lf5uM8amHJkWig0ZBVGiVhMxK/TI1XVq1Qar/jhKTRWBJlWZkuOPHqdZqVKuVxFzdZK5CKW8DIfNy2YoiFJQ4LB1smvnEIq6QJ00TqeWPTv3sx5eYGpqje4+H9lECLXZRqWRQyxW6PA56O60UK+XuDE5i9PrZHnZT05s0u4wE43n6LTZkUopBK2GCiIOkwlZU83K2jI6tYFEMonBomdleRWlzEB3h5lMtkmv283UzDxWh4E9+wb4uLuDW5EYO8e6iUQrhCMBLk2vcmjvOG+8fZFgTMPEnk7W16PIag5W/EGkhhq1sspjxw8SaTRRUWHn6HbemzyNr38nwflZpEaZrR1aRkb7aDeVSZazqKsmVkLxD8+K/ne/89fPP3O/GXVVIJh2sbi0yY69w0zNbKBo1sk0e1iJBghHgxzduxWhHOGDqRL97Q2efdjBD//2f9CUjVEovcmhu+5iLTrDzOwa9+y4m0C8hNWX53c/+2WuXJhC3kjSKfTg9yc5f2aRqkGPvFzk6P130O56iGx2mqF+K2+cv878coN//+lVUrIUMlUdVTXAwLZDBFYW8Jo6yBdkJGJ59u/vZ2pqnoJYYnC4Hf/iJslyHLPCTD5XR27UE4yk+fwT+6kIJpZXr3H/vu1cuxZFkJVYDyf56H27mfOXyYeLdPdZKMaLVMsy5m4H0RlNOHscoCjw1INj5CtZurZ002PS8MAd93L+3Cn6+ts59d5lIlEJURYmuVng7IUoDz14GKfDSCEhZ3Jtkq3HHqKeXgeVki987jeZXZhGajSIR2toUbAWlNDrbLRaZZJJCZ1SjtdjQhKzaCQJlVlHotzCJZeza1c7TTHG3rv3EEylaIh1coUiBpMJl8uDJLYIBUM89vgDrG8sotM0yCeU/MHv7uD826sc2mNlORyiKrMgiVXuO3qQt65d4uqVDQpqN+PbtuHrMjM3v0EmAQ2Zgo/cuYefv/g6Dx+/ky/8wQOEl9+mVNPx3X97AZ1RT2hlgXAiR6mmJ5OM8vjubUzH8gwMeTje24e1ZcOoFxns7eL1t94k1KjR6dJzaOcEP339FGsLC1ye2+DaTIqmWEHZ24m2pqWQETm4f4KhLROs3l7jzqMHiKdizCwk0WsEspkiWTHL3fccpt6QEYzGiARS5MoNTGYBqaWhXMqSq8kweBzMLqwzvx7j7ZPXuK+3i6Q8RiwcQqurc3j3EVSaFvMztzHoBJKFNIeHd3LLv8imP4Lb6+HNCwvMhXPodUq2DpvJ5GRUaxo+84XHMXRvw+bRkpicRZADlQpNuwIvJuR1DaN/8fuE/vmvqNSqQJmLVzZ55lP3sTIbotyoUhQSTGw1sxmQ0VTHqaUh3GihsYtIaQ2jgzLqMj3VTIQ0Wpw6JaVsA2e7A0FmwqjVkExW0bXLSMdKdLkcFFI5rl2/ibIlINcLJINL2NyDKJsi9XqFVLbM2FAfqZSMC+dPoze46fDK6O8cIrCxRDBcxNs/iFYlZ4vbSq1Vo1grUyhIeN0q5IJErdogn0qSi5cYGOqhUpehUynIFGpY9YDShN5eZXE+gsvpRiFASyZCRYlYFlmLJunQ69ErHMiFEvq6Fae9jlELhZqKarTCxkaU9XQc9FZajQQBuRGfy8ZiQUSu0lGI50mmMjSrDVL5DEqTBYuyye987uNEsglyqTwDZi2nbl3g3sH9qGRR1pN+UsEWhnYHsfA6/b4tbPHtwttl58zFmQ8P5N/6mz9/3mwqc/iuowSXrxGoJpgY2svPfjXDXQfNUAzR7x1l6446a4lZDo4f5avPHOTRux+h0vLwxT//BjqVn4WwmrnlW1jyZfr3HuD2yjmC8Sp39HcxuTLLv/7XaR596h4Csyuks/N4e/dw6eItBvdu49qF0+itAdRKG32+O3jv/DrPPtPNJ470cOZ6hJqszIMTj/PjU6d58St/zD+9+F9UDGpM1gKn3y1RqleptozE81mSmTr+eIZ4MofeYaCciPHRx71kEgnWY3UOHxrnH184B5YW6ooZt9tIm1fB2Rt+Do124eozEZGiNAQ9Ib+MqlSkUAVtvcJCKA0aUMQi/M4fPsva9ZP4+vaxVM2TWA0wMDjOidMfUE/LKdBgenGF+PoGBx++k2azyliXh8zqTf7s67/LD7/1Q3JlJWprO2p1BZtSoqFSUq9n0Al6CtkS7k4ruc0kUs1IRFZH2VTw+U/swx8Ms5mRo9SYmJyapk/lYlUUMbqcrPpDFMqfx7rdAAAgAElEQVQSpVKTpkzAH4hA04ReaUbpSNNp0VKoiHQNDaGVKUnmCuQzMR65ZxytRo/F1MVAv53I4iRLiTgfOTaIe9CKPRwlWYG//fp3CSajfHDpZTq8u0hmYjxxaJSVjShKhYxguE5T0+Khuwe5cGmNUKyIrihjyxYvP7k4iT+r4tLUWWJRAU0ji1LVTt+4QCGa5/DBj9PtcWLW1YnmivQafOhcNbo63Jw/vcLItgFOXVkjlNtkbTlKOqhi+/Yh1tY2MTvNJBJBpEYZURKpluoIOjWVskSmpMZi1FGo1aiVaqgRqFbKqM1a/vNSGH1B5L6jx4nmchzeuZ/3L72LTKFkeiGA12Bk0p8jna6zHMrw7pQfl1bD73z8XiLpKMFqHbFVQ4GWT973MPPvvUXf3fuYfeUVzEYT2pYSr8LI7t//Mh3PPIMkM6Id7Ca+HEGSQ7OSQjB1cO7SWxg13dw/1s7wSJI4sJGwsWV0L9HYIjLJwbYdXhTqXkxVkcvBHOJmGBETh7dt4dbiVcSaksMTo2yEAyREiVhonfvvOMhmLEGnr5flW/O4bXbanV6SYoyxnmHqjQLtvWbarHpOnprigQcPML26gNmiopBrEY8oEUwa1K0ymWwGbUNGvK7AbhNYX89h1VupNvSolUq6LVaMpgrLSzW0FgUrC8u4O/vJF/2UqNCoKjHqtEhSlUq9yshYB3o5dPSoSZartNV9aIU0laaLRsuPSt1ELMpINCvIqFJq1+LVaYknA6SAagmmIgVUyRK350XuO7AFuVZi345dBGI1isUUKVHHwvxtBpxKes12zgUL7LM4yNgrGO0iHms7aSkFyRpaSy/L4dsM2WGzkOTKzciHB/Kvf/3Pnr//aDeh8DLH73uaQjDJ8soiu7YbcHhdpCQRi7ONjWiYOw8dZ3l+hfvuGOXq6lnOXLuGyexgcjZOh0/Lx57Yz4WLBVYDs+wd87B/fISXT1xhIbjOoVEjsVk5g1vdNHUebO4W9xzcw8xyhr5BF4WkkSNHRlELHn76n9eYun2RH729zN5tRnYNupClY4y73OT0Kt67co2N5SoOq5KHHxwgncwRiGsp1SoIDSU6mQyXXUdcBL3FTLNR4Nidd3Pm5BmuXFzG0+YhsJzj8MFeFv0RgokEspyRTCmLoDax7k9TLFSwOZXIaZLJldgy0kUsFEVMNBjtU3Hh7TMcOnKUW6EIHrWK2aUAseQ6tWITo73FlkENsWCVex7eQy4VxaK3sLKYYTFQ4VcvnyKa17G4LuIyq8hkc1TqNVoNORqNgVatzCMH9hKOp0mUwWWT0eZxU6lI3JxdRG/U4mrXko/XcWgaxCsioWyJnQMeqiUVKkHAorLgD29SlGTkiyVUBh3jo1sY6evgvuP38uK//YqWoEEnScgFFRvpDPMLEYx2JepGBYN8kFX/LD5fP3K0TAZEkmKBk+/9knTkFrmqCY2iQntHJ6+du0xbXzfluoLjjx6klorT19ODw+6mo0vNc59+kr/8zovUW1rK9SyVkpJDh3ewEQhjs8koZVvE4lHMPhWnP3iHuw7dx9T0LPHIDEO9Q5y/PInRaeall15Bb20w0TfOsUd3cvniJjqFikZL5OZMkC997rMkIkEcdgsFMYPbYiSaqaBo1Oj2uJEKRcr1BjqDCmRN1IIeRVNkPpKlWilgN2oZGBjh7feuUlGqUKAkI6n5+enrLGxm2NPXwUC/m9EOG3ORApVyhiOHxjApZNjUVWqFBpZslHb3IE6bgXwshNGgYfcf/gWKrl7mXvo21//hBSY+9VtsvPovyOVKVDINxWiBtq1uNqdWKOubVJUmzq+BUauhIRMZ6OsgnYsQihUp54tE8yL7dw1TlyrY3SYiiQQKux2NVObK5CR2jxGN3kZ/dx+rK5Mc7R3jzPwaTqOWq5ML6L1Wouk8hwfHScTCtGss2DRGarUWFrcZi0GPRWND1VJQbYnsmuhnbnWTnFinTdDgrGWIldP09wyBoohOaUGhUWA1GnEiUKRAoVRhy+gIankJsaVgsM9DKdvApFNQrxZJZ0SOTfRyY2aF1fAmypiD0R4LDqeFfD2FzK1nQKeh3WtlPepHr2hhUCmJxkSCFQXtag3zm0kykQqutk66XVpeuXSLrX1bkNXKbCSDaDQCMknNc5+5h2Q4QkNdQ9FsMHjoCPL4MhdvLuF1uckl87T1OOntkNPbOcLpy4sUi3kW1ov/V5DL/7+A+v+t1CqBtfUgcqOK967ewuvrwtPmwNfpxWl1sG18Fzq9h2g4R70qIlXmef319znx+ixur5xMOU29pcXmsHL14m3SpQDDfQMcu+tBRvqOMtCzn9VEBd+Ih9ffvoAZNec+OIfF4qWlrBPcDHD96jVC8SjnLt5CKqnI5TeYWYHffGqU0S2DmM09CDYZ9xzaSisSo7NDx8d+YxCXV8Ha2k1sahuVchK1UUY2k0UsKagUjMjJsh7N0qy3eOTJLzG85U68rg7qlTiDXWDSyRBrSnSKBmaLkmqjSiSRxO0YQSYX6B/xIpZrGIywHljnU597iJERgWO7n+b+Jx5maWaD91+9Sr5c4X98/tO0mR0cPdxJ96AblVBkx0QvWrXAjeu3kSQdl65dIpaH+SBUa0r0egG/P4kk1ZApVJTKNcpSFb3RQJMW6VyWklQiJxaJxf1o1WrarHY8Dj37D07QkP367ojT40WnMzC/soLTbsSsa5GMrmCxGmjWq+jUOrQqI+fOXmVpap1bl25hNViIRTOUpAY5scHcUhCVRsAfiNJhG2YudILdO8dJplMUShVGhscRNA10XVbkjR4qlQzNUgSr0El3Zxu5VAyxVubHPzjB2JYOjMZ+PnrfQRKJADKDivV8k0QqQbkiUSpILM+t4PG4EASBVCJPvSqwshTi0OF7GNq6lXg6h9jQcPrkRXy+bhQKGaNjPejUGi7P3cKkdVKuR/FvhlEqVThtOjKJOEpahPxBTEYjLqcVtbyJXC5Hq9Iga8qoN+vUGw3KUoVUOks8m0Wl0zMzk8Ric/LCz/4Zo1VNJpNhbiPCK5fmUSj09NmN9HbZ2IzN0z+4jfW1JQxmO6lUi2Q2AMoGwWAYScoSfecC9rvuRZDSKL3dFD1dLP/iJRbffpkOvYIaOuxtGgS1Crmgoaoqs6/zCC27jEq+zOStJEajEY/HSDS0iVRtYjG7qEoNErE4mUSKcCROrlxBrdaiUqioi1VUKhU6gx7qalZWZljbCKG2trGykWDc5yZWKGFt96BWSOzdOcri0hzetnZaTTkj2ycoFAoYtFqqNYnQZgi90YCrw8GlK/OkM2XEUgFJaDDm7Wagq51GrUipVGZ6ZoZWU4ZMriQvluhsc2K3GWi2KlisJkSpTCycppUrsm37KI1ajVq2xEIgilqp5oGjR7l/Ygdy6gyODpHIZQivzjGzvIagVKJV69nZ5WEzGkYqNBB0SqRoArvJwVivh2K5yO6JfkZ6zai0KkpSjc1IgpIkQyplWZldxWkz4PG4UAk1EskQSoWOzu5RIpEI20dHcBpNLMyusBFdoiip0OpM/9eG/v+iI//O3/3l84890EVKFFmcK3Nm6gp2s4M9uw4xdX0GKVnE7XPSZeslG9tkdlGDwz3K1oMlRoZKvPtWA7OlyECXE7eug86hbswKGe++Nsc/fP97HLxrgvBUkHKzzud/8w5S2TJKpZP/Ovce12+s8uixPmpSF6myn1hEQyD+Jod29VJTqEmXtPiccCNWQ9Oq8h+/OoWn3YWpU01PtxGN0cLe3XuZX7zC5x/fydMPWHngYB//cXYVlbyArtrJ956/hx6hi69/62ssbCzTUlQRW0qGR3qIBDbxJ0rYNW3U6wk+85k7WJ1e4K/+eoytA928/tI6OoMShcaFzZzn4qUUw4OdDG0Z4oWfvYijW81fPvNJ3p1doHtwmGBoiS6PFzkCLs8IE+OH0apKtFm1nDwbJxkrYjFYSKWqlMoiTqeMfF5GX78Hg8lEqVTHYrOSzmdIV7JoVRUGu7tIlFq0u8zYDA3uPTLE7m3bcdVMfP8/3sedF5lKxrFbBJqAoqlCq4b77r2HxeV5BGWDbWNdtOoZUotZNOUasVyRfK1BIlPEoFGikIs4dXqqzQZ9Pg9775ugHK9QokwwGuXyhU3cbjuVdJ2tnh5uzC8yPnAfN5czDE24WJhfZ9uW/dSzm2zZO8rtmRQffWgXy6th8skS71y4jEknMDTmY3UtzciQB7GQR5JqpFIpqpU6nV1ekvECly7O0FJCpValIAl0jW1ncXmB3k4L3W16Hjl8iNklP9mYyNT6Bo28gM1mJBzN8jdf+wrzM9cxm7QIghyTSUMqVyBRllEolanL5cjkcsoVCUGtpdkEi9lAtdTk8NHtdLpcBIJRPrjuZ3KxhpipsKvDwbH7tyAzpIgXRezqNt64cpbPf/xjTIYKrC/O43G50RpsFJKrbPMMkjYUMdScDHziY7h3HKBy5mdEL79PVq6lS+fC6PbheewJ1v/9dRRtRuqJHGeXl/jSlz7N3EU/NFR0KdSgM+LsascoyJHXa/R42nA7DZiVWpaTadBrqWXy9I90kkomcJgdXL4+g1FhwdthYHl+E63ZxfbxDm6uB2i3qamUc4z0jrG5uolWr0Mth3ytTKxYIBH7dWguazVxWuxE0wlS5TSLM1G8g06cag1UmizXKwRDZdLxJDatluFOF/lUklQqSbapQJLq6DVq6lWJRqVJsVjH6NTj0Om5uriErGah2+NjJZegy+AkcHMBtVyLb98Qv/jV65ja3Xzm8AECwQJhfwCHswuNP8GiWENptLFn0EZ9I4fTpsfWLcdqMXN+fpL79+3nxsxVooUG+0aGmZqJMdzvpM3mxdtR4uKVNZydbgy1KOdmNnnsgUcplaOo9Rr80RBNlZdsUUDKJRjtsXN+8kM0WvmTr371+f/zR/uxagfxdTfZ3nMPQjmAtk3FP730Pg8esHHu+jz9PQ4MQi9ju8YIlaeQKx1E1yyojSWOHDyKr0cgXyww3DuIUV+npi1j8giMb9Xi85kpl/K8/No59F4jbQM2fvujX8Lm8PDyu+8wPGihz7eXaHITfxDmN+MEwnk6reAe1zOicnAtPo9Qd3J8z37OzrzL8pzIoZ2DyMmxvizxiY8OU6oqyOfcHL/Tx+JchsEtEjt9h/jpu7/E1bGD2bUkFoeETtVGOJKhzdmO22vk+oUgQyPdLC6s0Gbt4rXXJ1EJbg4dq6KVW0EZwefRsb6Y5eBBAyfOn+eho0eI5CtcWQhRSMp48aevE8uJfOSRwwRWI9y8epuVVZFX3jrP5HQGg0qHd8jAxmIKmVxHS6kGqUi5Ucdp11EpZxEUamq1Xz9MaDMrcXd2kUgV6OuwEgjHsdqs6I1GZpdC/Pzt87S7NIzs7uUbf/0Mr/70AyqoqLfkFKQE1+bmUcgdaA1aEqko6WwGvUGPwWZhIx5Cq1czPtaNViOjShmtys7+o/s5f/YG/s05dDod2UoFfyjFrp2j3Lx8i+N33U22quL01A0ef2Q/doeF2MwGn3nkYVKpDTydE4T8mzh1TkqVAjduTvHGxSmqySIVmYxMJM3BI1uZnVnC7lFTLhbx+Two5AKhYAiPw0Gj1cJoNuLz2FkLBqgU8gz19pOL5tk3cQe/eu9Ndg/u4ic/f5O/+Kvf4/q5NRqtMk1Bj05dp79rCFGME41FUApmlHIZC4ECrWYLmVxGqy6HFiiUKpqNOqIoodPKubmwwsUrN9golnj6sREOb9Hg22IiIqQoR+IMmrpIFPPo9BpMdiM3rgWwa7MolVbkTQm5TkUqkGLE3Y5QKlEJBWg7/hQtWYpXvv2PmJRG6pkEFZuZ0uQMuns/xfqbf4/c4ESvtDCqq2J77svE33+JYKVJOFzCaaqwHiugUzdw2nV42/VUlXVqejmJQJpBTweCTUckkafD04ZULmGwmvG2tzM7N82uHSPIVHqu+wNYmyXkJiduu53QZhi7xUJRXoN6i/VElPYOB/lSFSVVju46yLXJS9RaDRLxAqP9LpryGgYRukYHKIkp/GsB+ge6yacbyOUanHYr/kAQUa7AoWyitFsw2XQ0mqDQ6bA7bMyFNjAIRozKFuPD7ajqFaxWI2LFjLxQJdEqcXjLLsLpNIsbMSqyKpWWGntKZLbapFCRiIeDOA1aYuEUw/t3cvnGClIJNDI30wurREUDE/Ymu3c4mLq1SEZqcPSB/bzy8jn6ejzYDHpiRSX9HT6QJVGqNZx45yoVSYU/lMfrNDI4ZCIaanJ7JfrhgfwnP/m759v0Au9cW+SOeyxcPX8Lq3Erm8sXODqxl527hnnhxevcd/c2CoUgcrOSVEhJrhpldbXEpx6+g2/+68+RG8v4r2Yw6dTES0pOX7nM1M0qBptEsVJiYVNkx4E2KvU6+UyOa1NrbJ0Y48rZC5y73OD20mX0igaWpodMRs7QYJ3pmSr5ZJl5/xpPHX+cQwdsfPvv/4N7Hj9OaDKG3lzm+i0/Tz74EfIqGZuJZYIbMqJShcOjPj738ceYWUrwrZdXKZaS+DeyDG0fIbwaRJRkSFKWWLrC731+Dyden8NihngGivoSm6tNdOoCJ94I8YUvHuW731rguz94ipd+dhmvx8ev3rxKJFBiajWA3aggkGlSKyhIFxcJJjXcufNhfnHmLN0mLcEc2GwyEgtREvUqCj20mgVcFoHffuIwl24uoxPUaOUyskINXbmF2WtnY36dYk4iUahg0ln51DN3cOmD24RTEZyU6DB2cHDfMK+/+ip/838eY2NjlnuP7SGZCFEuttAb5OQLRcqSEqXajlgVEWt11IYW1ZoOs0nDHft6SKUr3NzI0qzHePYTu4nFMgQLeVQqNWIujddTwmmy05DHGPCZ+caffpsf/+iPuXx+lpGtOzlx7g2sdi1qXYLjdz9HqbaOSq8gk85iN5o4cPdOVhcjGGRFwtECxx8ZJB2sofaWCCyW6e3WM9A1jD9TxGAyENzYoM3dxtbRdg7vHefEyRM88NARljZT7BgeJZets/NgH6shP5fOzaBWm6iW8xi1TRSCkUA0gUZQUq23UMnlRMIZxJqAoJVQVOu0FFCrNOjrtBFfSZAoSvR51Dz0yTuQqlG69S7mVwKYjE7mpjZxmZ00G2WUFhuNQh2zSYtfqrCjd5RIcJ7dO3bTLMZoaVX0GTpQK9VoDXLc49tI/vsLtMQKEgo0JjvKRh0aFXp7t9Pz6TtY/+U5xp9+Gt2RJ3jti4+itO9kaEBPNJmm4q/iNcpRWcykBR2dQoVktkVZaiDodRQrNXKpNIVcjmJTpFzIYXW5EBVl+jq6qSlkpOKb1HMy6vImgkxGOJxgYv8EgTU/8VyUjq4etPIirZpALSbn8Sce5Mzp01SyEm12JzKhiV4nIKtKxBNZCvkSA54e8sUUBpOZdCFPrirx2M5hFmIiNl8Zo6edZKqJVVUGvYxySWQlXMBh0lMvV3h0yz7izTmmV9boddjIZ1NsP3QHr737PkkK9Lb3kSxLjLTZWMmWSCSi5IxqugZ9lJJBjm8dx6c0sRbK0z7oINsc4OLkRT771HGSm5u4Ow2o5D66t/io1pp0uIzIqznsLhuz67OUcyVKtQonzrxPp3eciUENC4EsWrkGrcXGjakljC43s/OBDw/kf/onX3n++39+NwaFmhd/fpVwtIiobLGeyLK6meba3HWe/shdvH/lNlen5xnusFGpbmLVj+DfvMm1gIyP723Dqe6ic1s7G/FV3j6xRiZVQtGscPiQh0TUilwlp9GoMtB7D02FxK4dB/mt5/4Co8uNxZKn0yRnZFcbb1xa41PHjDx+6FmmQzcY7mgjGo9y/uotCk0jWw8d4cXvv4pYlbhxM0Gn10RRGeGnP71OOZvj2KFj+Kw2vvOTX3A7dZFkfJ0Hj2/jgX33IpeC3LqdpKXUU69lKIsq2tu0nHp1iZy5gUIUcFo1hKMlVKoWm/4ado+eG2fX6Rxw8s8vXMZstxKNBdAaveTLGXZu6eLxY+3cWt+gr9uJvCKnkK+QjyTYSMaJiAqQC8QSJXQ2DWKxiRo58qaChKTj9KVFuj3tLETShLNldluHObHgp1kqE041KLcMVGp1osEk+WySo3ftIpJMEpJqRMQ8N+ZWkWms3PZH+OBWglg0Q6slo0kdj8uK061jYIuT2ek0SqGG2SSjISqpliRUoojc7WZmfpM//uL9xKNx3rs0x75DB7j2wSw2m5Xh8Q7mF0KI1QKnTsWYms3wi1++hLLloq1Xxvpammg6hs3dD00Vl27/nGbDjCTJcLlUZAurDPcdIle+yl0P7yVXqJAOp2iRwa3r5Dc/8zE0phYtQYlJISGvF7j/7iNcvnANo8mE2ixHVhUx1uDOPWOcOn2SQ3v2sLIyTTy6SSamQWjK2LlzGz0dPmanbqNUtBAEEKsiHR4PJTFEIllEoRDA2km9CUJLTTyc4pvf+SwOUwZvexvJ5Xl0RjM6rZFekxW1UGDHiJtEsUa+BkJLQvDasSgabCwuoOswsjATIRBOoTdpqDQbdOvN2Kx68tksXffuY/PCOapiA6nRoFgqIpdBoqmgdus9PPuepmf3dn7x3a+hCl7AoOulqilR2RR47otPcX35CjVRTyDsx9pQoTNpSRQrWDxWZMUasUKRDncbOr0alV6DsqFg2R+hS+8g1awSWtvAarCg0SnRauUkkzl8XT1sTt3mmafHKZfb0ejlrC6t0ea2EcmmWdqYJ+rf4L6j+ylbdcxNryA0dWSrElJNhiRrkcymkWpNlE0Z8lYThaJBpJik325GzOWZTiZwqyHeUFIplJGkKh6bGpNaTU0hsLR8DVVLQ7auIFssYDWYuRVfpamWkUptMuDV4NMUmV5aZExr5J2YH7PFwaitnR3dw7x19TLJogyZLoXRqGEjsoTFYqC7zYxGI6AztGiiYGVlE61GztryCm3mYdRmGbkkHLrjAJdnV9Gq+imJWVqtKlMrC6jlKsrlEmLOit1mZGZx48MD+d/9zZ89v3dnH6+cvopSoyW00UJtVLK4nKWQb6IyKrBKCS5cy3P03iPY1O0M7+wmMDfHJx+9H5sUJmFycP3WacwGDU7PMGtrAZydagZGx3n93Wk8DjftnQPYHQI//OGvaNYaWM1Kzp1eBXUWs8vBzEYGk8HJxu0k+k4JhUZFI1qloWqg09Rod9tJh7PMz17m3mO/QUaeYHBoFKe7QSsHBw/sZHxkF5HiJC7vEZ555hnsmmHS1U2aqTX+6Jvvo7QqiOagKctjkIyUVRXcGgePPdtJOWQm3YBEMca+XV62jw8TS2YpVkqYdFCWGjgsJpSqLF6XmunFDEq1QCnXwNpmY+Z8mHwFwpEsoXwLdVNCrpVTlSR67AKipEKmV6BrqZGVSgh18HUZGBnu5fp8kHxOhVamYzUb4a7uLlK5CnU0lKQqVERMCti9z0O1pCOTWqPD60RMyvnUx/fwwNEJ+nsGuHbhBjvHetn0h+gYcvDRR45za3KZ6Sk/doeAUW7E6dQTSRXo6O8gGEhQaZUJhmTMrC0Q8EuEExVKoTIP7urBoC2gaslocxnp72kjW8ohFyRUqiZSMcNX/ujvcNqdDA1NMDO3jsGhYff2p7h+8wojW0YR1FZ6uwc4ffINjt37MGdOXiQeLnDXvp10uCxY2jWgcGI0KlifDWDw6LE4rSi1Om7ObTDnD/Gxez9KOpih29vNmXPvo3X5mF2+TUswEAgU0OpsxCN55NoW16/N0d/dziefeZYz755ErdXhdnpo1RV84snH8bbJWL40ybDPTLvLzJ5dI7z66lUee/gAq+El+lxmgvE4JqOFZqKEQW/m+sY6gyPDvw4dFTqqmTKbkSht3T7KkoTJYsbt6cJk0rK2Gefu4X2UC3HMggOjS8PUhWlaLRAlCUkqUS4VcMlFGro20lfO0faRTxJ7/zUMrTbSzSxWgwmnRk7Q4UEoF3CZ9fR5nGQ316mka3hR4tQ7WBbTqGsVUBWolJuk0lnkVSV1pZxxbxvT8RU63U6y2SxqjRy73U4uJyKKZSa2b6VZcrLiv4FeLjA+4CORr2J0WVAKKtqtZtbEEquz8zRUkG9VqZcqGPVaZPI61CS0eh0WtYIdE4Mk0yHMgp4uu5mL8RD7xw4zN3+b7vY+ju1qJ1EosrBewmHTolGDtiijZ6wLtdSioKgTqKQxVH/99NjQ0kDOwdDWUdrMSjpUHnxjfZjkGqKxIEuRDdRWK1adjO0+Nza9nGvzAboGB/HZnczPL9E72MPqRpyBfid2m45awYFMs8zN6Qp9PSAvNahW82yu+zl6YBipKNLT5yQciqBWKtm61UIulWZ+LfXhgfxHP/jW84lQlas3EpRLBTLlCh0eK3azmlg8DYKepdUkTz53hFMnJtk1IuPNUzfRa0CnH+Ir330Hn8mA2ipgNw/yXz97g889ezctUeLwnkOYdAZy1WX6Bvt4+/UbuH1Ozr+f462zN3B7HHR6NXQ7R3HaG5z4eYj/9dXj7GgfZWpqmSOPbaMUi5HM5DFaTOQqBepNNdWwgFqnYO7qNJmokq69+/nFK6fp31JiYuQ5orHL/Nt//jP/9c5pzi1VWZ1rcLBLhbyupCiX0WqI2MoCMXmLvVu2sHhjk/UNP11OHWaXlrvunsBsUBILxNj0V/mb7/43fvGf51AolKBRUK2YUSqVqJsSbZY6/qjI1//k95hbvsyg3UZbW5lsSUlFp8NjVhFIi8hbImK+yp2jPu7dv5WOLomWQeD8hTVqlSZqjZZ0OkNHu4e11Q1KcgX1ZgWrSYui2aKYb3Ls0bv4lxffZMeubWjMWmKZDOVmk7feuUhLzHD0wBFUCoGOji4u3ohhsmqJRrNY7To2FhukCmmsFisut5Kerg4WN3Lo9AayuTxt7i7EQgFdq8yRfU5uTs6yb/8+Vvxpxnb2YDb24XC62bNjO+V8nZwk0lLqEMq/ymkAACAASURBVNQ1evsGMFqtfOe7P2du8SqH9z3EyuIs//7Kq2ysJBgaNKFQqOns9dC3fZQ3TrxP36CeVLTGiTNnkCn0OGxOxjtNiNEQFFLUknG+9j+/yBf+8G/ZtWs3+w51c3MhyNXZRZY2gqxt5ijW5bTZteSiSj75md/g/IUr3HHnbl588ac8+6mn8AfWiKeyqAxm+n0+7j24lUMT27kxPc/iRhybFvZuH2bJH+Hg7qNMr0VR6OSMdXRSbEgE8r/OLfyRBCq1gNmgoVYHQdfGykKArQPDbKwuQ11BKZ9CIQiMOV3YTSo69xwis3yd2Rt+NGYdTVmTqligzWKlarfRoVLgfeIJCi49/tNncFtBoTPiiCgY+PpfIbz2AvmggKQsQEDNYE8vH//7byLPrnL95Eke3XeEq7FlHtq6k/n1MDt37iYWCOAb9lKV1Rjp7WF+bRWppiC2EaPeaJFIpujqdROP1PC4vIQzUXQGNevr65SqGpKJNdxOJ8GNSeKFGh0eNxWpQq3RolVrYbdY0KpU9Hl95DJJBnxdBCNh6lolu9q6yIVS/Pl/f4jXb7yLydyOUashL8o4tsNOJi9hUDYwmlU4DBX0ThMriTBdWjdGhZaBHh23ogWePLqPW1dukJbJyGRr6HqszF6/xVwoiUwj0JBDRaqh1RnJRm6Ry6sRLS3kLQORQBCZQkUyk0ImmJByMlRCHoPRRCASo97IIdVM5AplTE4DWwe6SEUTKAzQ1zuE3W5iYmwL1UoWu9XOuesfoo78a3/51ecfemice49KdLftJeRf5/r1DJ/8+DjlbBOlXs+uPT6k1TqXri9Tl21yz0OfplFw8+Vv/ISPPuhj74HtzM+F+PGPrnP4wQFee/U2NpeNfDXGO6enWVrIcvniDBHRwvrNDTyGFnd1dDHepWcyJuf6zBL1jIISAq+cmaQZtCMfVnHytZPsPPAIvW1eLK4aF68lSMSrxMubKBQqYjkRraxAKBUhGSgxHalTFDd4852T/Mn/fIHhrjwXX1kg16zhcFs5F85jacoRgJLCQCSRx6wSODu/SY9bT0WS2AhX6bAqsdhCPPPkxyhX5njxn+bROVsM9JoJrRUwKJTkxAxmjZsdE2rGd3czd+s9snkFsqaaPmeTuw/sQRDCdLp6CIRT1DJ1PvjF5zh5dpGpoJ9/O5UguJrnVy99jb//4UnMdjMtYw1dvU64pkIvVDEY1LRq0KJGS6Nj5uYqqayEy21GIxcQ60o0iiyFcoNQPEJLyuAds4Muj6Pa4szNTdwOF82GhXA+iE5uRGNQ0tnl4cb169RqcppSBYvBQCIeolptoNAIKGUKDt+5jzOXLrLnjo9w4o0pipkUSlmdSCzC1cl5th/dywv/8jYnTk3y6s8/4MK1y8SL4LIqSGXTRDNxfvvp5zC1dXDlxhw2pYZg6iZaUcHf/uFz/ORnb2Cza/lvv/UFllb8vHXmPMb+UXbv2onSbGV4Wy///uoJHnvySYa2bOftU2eZnJ6iXpdw2AyM9vm4fXuDrs4xNv0RYsFVzFoj8uYGzVaDT37l+5x69V9xezw06iVS2RbBlMTU3AqzAT+d9h4scjg87qQQ8WMQkjy0e5xqucjS5gr2Dg+hDT+CzYhRqWaozcPj9x9h+uplMv51ztx6lRe+9036RwaoZ/L4fD46ezoxq820uwfoe/IBkFWYvHSDQDyKtiGn1RKROwy4jJ2MfvUf0TjHkK7+kq37x0gvrCJhY+zhzxJ6+XukxSqtYoJkNIxTrUfdN4b3vo8Q+N7f8/gff5lb75zl8NYJrkbWmTDaiKgTmNR63r12m92HtnPm/cv4OnpJhFIY7X0YTA1aMh09HT4sNjDUqkTiMZLJAlqTG5nBhNMl0JR0CBYDbpuJRiFDJiehMnowGjQUSxVywTiKphabx4Rbq6ZYjtPTa6MWEbkV2iS4UETt7kJTLCCXN6iIJUzedpb8AVRONxsrUSb0bbwZTrNT1UfJUKCiqdJqeVA2qly+scanP/s052+foc/ewXxwiYJeQFVXURFzGI2diPEQdpMDvUKHVmNHY20QyjQoVHOMbp/g+q0IRl0Znc6J2yOwFpLISTX27TnA5MwsUq2KsqZELDYY27aV4eGtJJJhmlUFmdwmdVGF1+Pg7bMLHx7I/+kH//D8ju125m+HSeTTWPRjHH1ATTYdRaw2iUTiBMNpGkUZOnudVlKLbD2EvrPCA8fttDtdbB0boHfAx09+co1kso6rw0M6K7K2usHESB/XpiuEcw005SyllpxIUcWWLgWmpJWXV+LUGhL5KsiFJlKgSrk3w3a3EjGtYyO1CLIap06GKFabWGxVJkY7UdfBZMtCxou+q8LvfPqzvPyLs9iddbZ1j/LW5ZM8euQevvMvV3G6lMijBQpNPYVCDl1dT0MuoVEqGffIqDY9BMMxNE4VDz64lfOn47R1OsmXonzv22tYnXJK+RZWq5FIOk0sKmfHqBeHrwKZMj16NXqFnumVAO4uB7v2dtDbu5sV/wr+5Qze7g4ev383/uUSWXENp0PgK8+N0eOx85VvvMODh+x4bSYKuRQmjYDYKKJsqWk1m0iVJjK5kkK1iNVio1Qu4l9L4F+K0pAnOHpgD/7VBdIVMw/fNYrL1E00lSJUzuOxKGmV5aRSi4gpJSprhVZDxcL0KgMdPooyA3JBjkCNNr2eyZUc41s9HD1yiNdOnuWe++/jzJkzVDJVZi8tU83kyGfj/MEf/A6VVIFkNoLH2YPZLFFr1bnzzgcI+yPEkwlCm3luLtzk9oVpRnpGeemNixy7cy/PHP9tvvHCj/H62tm18z5+8IOfMDwyQKVZYdw6zFsXZ1lanufYrqO8PxdAzCdQq1S89cYreDxuZA09/UMj9HV28L+//CV+9E8/wKxrp6PdTTIZYmTYhVmv4+1fvouaEladGaXKQCySYd/ObVx57wxGk5l0IsATv7GDrXu2ohH0PPb7v0czUSOdkmExeKlLajrsfTy26wC7B7vp9zkIbSRQtax89tm9ZNcq9PdP8P0fnCCagKszIa5NbnLs8FPcfXwfVaGOlM2RXD6LpqxEpVOjkWkZ2XknW5/9DEv/8QLrP/omUMNx7+9TFxfo7hmmuO9B9E4T3nsexH14N9uf/CxNWZ6R5/4XisVrREOLFJaKbN29C8++Lsrr68y1FugwjzMzH2J8pJ9MNIGvzcf0zRs4HRZK+XUMKgs1mYJMPo9DL7AWLdPRbqJglNOqyKgkClibIrlcDpNCxup6FKtBzd7dY1SKSaLhTeSyJgaNknQmg3u4n8DqMqVqHWQGSjUJu9OFyeNiaW4Od5uDlWAat7ONRjpIXmWkN11C02kklK+yHoji0HTiHLfTmKyymk3icrhxuZ28/u5ryJpNgvkMY109JCJpagYth7oMnFr206U0kqoUiCcEBJuAP1ojHlnHYDCSTeWJBeoM9prQCCXEnESulCGbKJNKF6hLAv0dDu69awSZusBKYJlqo0Aiuk4sXsLn82I06mnJRd75YP3DA/m3v/1nz1eKfnQGFflqjCN3j9Lf7ePN124xMGonMNfCppPx0M5ODgxp+NIXPkpMoWHCO06k3OKeHf2kwml++uMrJHNpgtE6La2KG9NBqFvYsa2NS6dWUMsFqugQxQq1ag1zSU/8/6HuPYPkKq+939/u7t05p5menKWZkUZZIwlJICSBJEASNsmAbcAG4+MEOGFzbGNjbGNwDhifY2OSARFMRggJIZSzNNJoNHmme0LnHHbHfT+YW3XuW/e+xx/Oh/uuqlXP2v9nPXvtT/9ataqe/W+ZYsaXQiOUKVVEuhs8PPXQfQgqL/t2+piNh1nZ1cL7+8aJJONUlGXUJQcGB9x391VU5DoaWxOMTCbIJuJcu20pTpeD0RlQRYNcd91nOXHkHN3ODD1LO5iamuTfP3s1u0+dB0ORRLbEDVf0Mj0zjc0hIogqZofHufkzqxk4P8CkN0DPgno2X1VPJBYjGk2QSKmx2PN84bMrqTZPc+VV23njwAfcddu3qG4wYLaJ9NRdzsN/fYx8Xod/JsCYv8DszAhXr13Nsb4LJMsphqa1yEIWsUHB8eMhjKKVVA4KUhx1QYfeqKdUzFKpKNDqDRjECgq5CHKRz91yNaf6B5GyIjOBCGtX9XDXzdfijUzwyrsHGBkvM9Q/SbFUxujQMLezg0gkSKPbhkpdJhJSEEqF0OSTKColliyez8BFL+vXtGIzwOJ53ZRlBbOBIQ4e9pKSclx6zUKmpyNMBPPsOzmIy2XjgQe+wetvP881V20lHB1EU0xTY1dhswl8YsuV9MxdwNlzfYgaGVMxw8aFl3D9lx9m1ao6Tp7oZ+M1m8hk4oyO9hMKxTjad44L3hgOnciu4wehaOH8kI/Dx/pYuGQFiQRIZZiamqau3s0Lr77EXbd/npEhPw31DWQyISwWFWadgnxejUIu4vUHSBYqxJMJ/LMzPPSDW9m560Oaa9ppbenitVf3Es1rMBVV/P6pvxMMZQjFMsTiWTLpHBf905wfi3G0bxavP4HdbiBfaaSv7128A3rylRSJbB5Rr0MGKiW45pMLee8Xf2TRdZ9mZt+7TBQyWNMKVn/t81TVtbDjh18l6Z9Bq62gKZjI7n8J9+0PIehM+P/zC0hTGXKjw0ztfY/BN/YgW92M7X4Vx9ZryB58CovNQdWcVSja5zNv2TJWRBr45c4/s3zBIiYHBvCFoog6NR2dTQhqGbVJTXA2h8lioJSOcdEbRFHU0murYzIXQ6dQU+1wUcrlEC1qxFIJe62NskpmyudHVVGhUZZweTxEY2EczirOjo1jNhpQ63U47FUUkNGhJlkpsLi+hRMDk6xf3UsiPst0rkS3Xcn5kTCpkkhZBYpchbHUCLGgis+sd3M6IiGWBcSiRGdLKzZZRqeSyadzRMQKvRY7/UEf6+e3odJJnLyYQLQY2He8n9qGRjZfthG9uUI6JZCWfLjNdbS3thGZzaA2FlFUZNy11azqdVPlFJgYn0QuyOSyEA6EKKQFFHolUk6BQjCQSubYf3zy/xwi/9EPv//gFeuqOHEiiLtGzcBAkjee6qNlro1cXMNNt3axfduVvPDMLprXLeP+x56hUpmmZIHJkQAzE5PMbb2FC74PWbZ+BReGfUQiWTIZgWy+zLFTXtT1DigWycezJFVqFJKBcVWErto5RNIhIlMmfvH1GrZfs4BfPvksu0/5KIhaal1ujl4cxuNUotGpKZSLXHGlhx07Jlm7VEFNXSc739jJyhVNlFVxnJZWLEYVNl0WITWX0xc/olzxI5aNvHE0wPI6N28cHCMgKcnn1DhcVgYveBnwR1g8rw6NbEZljqMRZYplAVlZjUSWi/1Zliyew/DFDCXizJtjxK2VqShtXJw4RavZw+v7djCntpunn9mJwaqiEi9w9cpu1i5upO90gEtX63j4V8e4/Z7NHPvwDJ/YtIGm2iqcQoKfPngbE4MXiKfCXLVtAS6jhEbvQqOVSSSTaLUacuksGrUWQVkhFYkSmMqwdIkLZ62Z5lqBYkrAO5UmHAswOBgkL8BMsEgik+Fiv5fVaxy4HXVI2SSt7SqWLqqlq76BnsZ6mhuszPgDKM1a3js8yogvwuFTfTQ4aylk87Q1tXPoozM0d3eRLWqIJZOkpAR/+es/0Bns1FWbsNlyqDMaahvUJFJqilKCRHwas05BjV1Lz7xW/rxrJ3//wcPc/4dXcbtNvL/nIzZcto6gf4oqTwORXIIqs4GpyRQ6Ocv5gQCpbJmmhkaGBy8SDSQoqcqsWTAX3+go50dD3HjdDbyzcx/RYJIal51sPk5LvZ0Rb5pMIY/GoKWuxkOxVGZwyMuGy7fQ1z+FQiwTiAZJpwrECjBw8iw6l5tKqYzeZCCdTqLXaTAqdFTKMdRiHkVJgcVqZ+ehf/DNe+7jxRefw5tKIJXKpJNxtFolZ8eGaKGAVYZcKsuyG7aReOcQl3zrXhx6DX/84XcxF3UolAawCRg0WpRIiGu3MfKnL1DJm8lLaRIzR5gdmyYtBxD9AYSZOM3z2jBufwB1z2I0hjoEUy2SYz5it5HtHg9P7nkPqVhi+crVTPm8FAtx8rksavRYrUoKJRWFgkBHrZV954aIiAk0WhWhUJJsIUg4pyaVjqAol3Ba9EzORrCaPSSCWYSSQFk0Ek9K2F31NLfYCU6HyMsVVKJALltBJYjki0Vi6SSeWhszsTSiXktBKpFMhkga3IhaEcEXIWtXc8vW7xIPHmAomiYbmkYUVTS01XPy+ACSUKHVYGaoWEITLyPXFbFH45wOV8j4Mtiba4AsHk8tyWyWifHzBAIhBLEKNDZOHD2DSlRhd4uoVHbkQgaTVU8+HSYSkyhU7ITjGS5fs4qxmWGCWRWVcp7gbIbR0SG65rXy/kfD/+cQ+SM/f/jBhT0OJr0JfBMi9c0lGrqa6T87g1Jb5LWdE4RSZ7jpU6shn8Jmc9Nc3UJ3UyPnz/WxeOFN7B9+nCr3Sn7+8E5UFpFCoUilrESrqyCXRYzFAossEj/45jpW9zrZuGYVgcAInjkiS+et5qqrLXzi+k2883aI69au5f03B/nE2hq8vlHuuPuTFEtKRmeiaEULk1NTaFVaBn0JRsdHaanTsGnVHcTkAEZZR0u1h57WzTTOVaLSN7HjveOEA3lMTg1HpqIYNWpUBhGlFKNcVGDSG9Bk0oznMqjKSYoKNd7pWQoVHQMXR2losDHlm+Ts2CQVNGy71InJpmNOaz3Xr74Vu3IK2dVEOpzgb2+dY9u6NZw4fojFq4zkdHFM2YXMX12D09HC7bfO4ciePaRTKtwuLXI+S3Wtmrf37CebEFBpKqSjIhMTcZJSju5FzYQCM9TXOmlvtVIoFQgEs9TUu2mbY6GtxkgqOILdbKGh1UB4cpZUpEhttRlZVaFYkinmSphNZlQaG1PhEFJWpCLFaPXMZXA8iEEjs2zefG6/8QYimRGGxrIk0yE+teVajp85ik6h4K7PbmNpbzuHj5+itclGJFxCmc6QVWgplXKkwoNIKRW9S6vwhmeZDWdpbG7klivWkw6PY2+Zi9KcZ3Z8ih3vncJTSnMuWmZeWyu7d39EQipzcTzGicEYckZJMieRjZSw1NahFypkSwU2dlQxWdSztrcJ33QAvSpPOmlm96G92DRWgr4EGqOMIBcQyzly+ShanY1sIY9GZSCfzrLh0sv4aP9HzEyNYzAYCAVjTKezGIUCyWKJqUAUoyAyG00hajMUsyaMYoSkyk50OshEMIRaqUbI5Qj6g7y+5yxJhUCdaKKs0+NP5CkrKuSycRrMKir+GVo2fJ726zegzSf48Ze/itPiIKsAvbJCRWOkWquDSgXjutuJ/v23BFQ5AsEglUiJlJRGV9ZRMIM2raT28z9l9Bs9jOzaS/rYcTLv7cK9aSsn7rqa5qtv58rlc9mz/yzHTp7F7WnCZVFi0hvQmwQsspOa6gpj8Sw2g5mvbtvI6PQksgKsahXNdVV0NmgRUFAxmIlHE9SULCQlicmwH4veRt/YKN2N9cTkNCpUaBQV1l7ZRXxsjIloFK3JwujERToc1cxbXsN0IEUqVaDKoKDKsxCjkEaUDJTUJewOM2b9JPVuC7W2GmYiYUKRBLlMDHVZxmOpRyHlSAGFEkSnApxOaqnWqSlXigQSKaw1RgSVgErWkRMTiHon+Uo1heQsMxk93R1GItEQgZCIrFRjqdJyakLF2b4JmhuaCAejZMQqBEWM7upqWtpbOH2ij41XzKeSU7LnyOj/zL9WBEGoFwRhryAIFwRB6BcE4Wsf43ZBEN4XBGH449X2MS4IgvBbQRBGBEHoEwRh8X9XI5et0DVvJXXNRkwmExfP6zh4YIyWLj1KFWzdWEt341zWbdhEpdgEYp44R5nyVWFxW3j/8JNMTxl45fUdXPtZPbdsXkK1SWJBl5V0OA/qHNMZFSfi8OT7o/zst0eJFmcY92UZHSgyPHKB/uNDnD4VZ+fx13jx0C7u+PplBOQ06UILh/ftZffR02STBQyVCqWESGdnLXUuEyuWNtHUsZzDoy9DVsfpyQGOjA7z1qFXmY6meOnVv1DlSrN+6zKyiRA2tUheU0AUJGobnCiUFfwRPw4b6OUCyrwKTVlEq3JQyifZvGUpJ45NsGpNF/ObHLhsGfTN3Xx0xIunaOc3v/46mXIXJ3a/ydBYkc7WWtasaOLJHY9zx42PcnGfiahznKefeZXjJ4/zlyd3cO2my7hqYxUrG3pp8cyhuqqbhW2XsXLVfGIRkZI2TyqVwmySePO143iqG4mGw2RSFYYH4jz22Oe4eGGcnjlGKoKWvFKFvcGCXJTYvO1y3PVG9EZocmoRsiWMGic1VaBMRbmqdx5NNQLzunqpaa6md3UTqzYs4L0jb/Dq7teZGghxwxVuLu1qoaIcpaaxFkkt8NeX3+U7P3kOh7XMqt42tPoIOqsNq6BmSZeLmzbdgTQtkcgXiUynaXDkUGb8DIQidC1fj9ut5dyZJHpzA3qLgmxFi8NuZmRwgnSqTDycI+ANM7/aRkdHNRlJZgY1d2+Yj0lnwO1QsHjhPMq5cQ4fOkCdsQqzRY+hJg/qEpG0F7VZicboRq81oNIbsLsaMGqtlHN5JifGyBfzxFNRVly2HpvViVljQG80YRREZvwZvN4o6XCcsYkw3kCMQLzIyPAkB4dSDJ8bIJIuMHR+BoNNwYenvDzy1AckBTvJtIGZfIJGXYVFbhFtXuL8wDjpnJ5MReL484+SD0zx8L334bK6SEoSslKmXFKhEzTkNFo0LZ2YGSdb0pCZiBD3x0hJGbLaMhpRQfVwhdYvfY/I69+noliIUlZQ0YJs1oAgkamzM/z8k2RPR/nDU3/BWWVEaYnjNJjxeidZ3tONohLBrhOY3+omlAzzWv8BOhZ3YDKqEQwQS2TxT0bIJMokc2VKQEGZI51PYnFamQwEaG1uQqMRMWv1FNRJrJ5qkqMxnFVNGKx6envmoLboGZQyDEzMUiqVqGuso6QTiQpZzk6FuBC9QEYrMFuQSfnifHQhgiIn43G002LXojLZCaaCSLpRhhUiCSFErlxhJF9GlRLRiBZ6jQ7M1nakjJpSUQJVjFymClWhDqc5y6W9NXRUF6hzNGES9eiVCRqrlUz2+7Gqinxy0xpiwSHcLiUJ/2Gi3goVTZJMPkxRoePkYIQ/PL/rv6POf53I+adk29dlWe4CVgBfEgShC7gf2CPLcjv/1Oa8/+P8zUD7x34X8Ph/V0CthoHB3dgstaRSQVz1YexON2plA+FwjHI5xI6Xj/HVr3+faCHL4OAQ+94xEFftxeasxmwz43BauHxjO7EZgV/+5QNq2jxcOB8kk4FKTsGa+RXsbg8mZ4G//u5enn3hA5oa6xg4N8M939pERC7ywI+fZcIn89SLI+zd/zrVOiPX3thOcCbFF65fxqJmPffeu4xt1zeyttfN5kt7yccqqBQVonFYtXAlUspB33kvf3/7PQ6dvkBwWsRcspMKDeBwW4hlYxiLAjkpTSiZQ6XV4KirRumso6TUUtYZSAsF6mptxEJZEpESc1vree2ZC4wPFYmNCVw8fZ42s4Fbf/8Ks9E8P9vxEkcjNgTBQDbiZ/LcNI//9LfcetMt7B8Z5uln96ExmDE59Nxw/e1EQ1m2r/8StXNqUTm6SJYVXLF6AZ+89i4uXggwNDnO579wHT+6/8soihBPpCmWZVq71CzvreKRHzyHxWripbf72XXYTzwmUM7qeeP9MQZnciTLVo6e8WMw17NykZ3vf2cN7dVqVDGBExcH2LV3Ck9bgeMnPqSx1oPeYGbJqsX4AjkmQ2HKaZHmxhJHL0bJxIp0t7WwuMPKV25ayiPfeJgNy9biUgusWFvHxvXziIcytM1x0dimYkvvp/ni527nyquuRzKbeWffbnKiml8+8ioVMgyMhJgJqCg5lBRyJWSFkkxFQLS6UGp1jPgSjE/76DAVEMt5RmcDeCcDqGQlrS1zaGt0sXxRN3vPDzKeFimlyjitLupb6jDajLy04wOSqQKhWJxgKIUgC9z26c9QLBaREZmeneGFl17DXV2H2WqnAgwHwrx+ZoJTgTgnvCFOhPNcnAwyOphgIJxiJpzlwniEqqZq1i6bx4KeLpxVVVSZVdSrU6yy5dGbQRaLrF5Tx7fuXsldX1zDseGzZCQF4VMTaNQyLVYT2XSRsqBAWdFQNIk49QLB4RHqb70HKgJBxQQmjQurRkuhmEWbLeJUWZj/7DtYV6zCeO4UFUeBhtqGfyoD1blBTqIbjjGRDVNKj5J//B889eI7lIZCfHh6gI2XrWfgwghXbVlNz9w51LmsfGpVN0vmeBg9dx4KKqLhLAa1At/QKGRzlLMp4ukM7kYHRYWeqlo7Rr2BpfM7SSslItkEqkSZifFpygJcDI+iV9kZPXGaa9euoMmmw+9NIxRgemQSu8lJaPY8ix21bGprQCxkWdXg5shsBGsuw3vDA0TLY6SFOqwRHxZNAxfPzFBQgls00Faj4K9330VNnUi7yUmuoxoNEao8BtRqCxTnUMyV0VgKnD4+ic8rsmheI0ePf0BWylDXVE9F0NI1t44mt4yylMJsNdMxt4bO1ipWr+5Ao7UiFiXmdhg4fmSAQlrzP0fksizPyrJ86uM4BQwAtcA24KmP054Ctn8cbwOelv9pRwCrIAie/10Nl9PCqoWbUCgUKFTQUbUcKZ0hXRigvraVwaEKcxc1cvxogiNHz2EUzKzf7OH40fOc2O+lvb4O79BpmqrbWb92Dd/+6kbWzm/lred/zF9+fTfzW+xozXrcmiDeiQh3/+RXKMoaitk4bS0wOzWKplDi07fOQZoFi11GVFe4auUalFIL5/qLbF2/Do1ah1DJUKObx0vPn2DHW7uJFiSqPB0cO5zgiR2vc2z3MYrRMl++qQu7Us29D80npfNx+MI0xbwKm2CoagAAIABJREFUl1WHP5ekzWlBlnKUolHqzEoyxQwdzWZCIT9Wo52+c+PUNTQwMnyGVHSWereW+398Jc2L3Ox+I8y7J808fNN6FO09XNiXQldRc3psmp7L5zIzK7B00WJ+8+/dONVKpmJGQgmBt3f288HJAxzuP0MgP8bTu/chZY7hLCt44sW/8P0v38DfHtrI3Zs/hSpTYmHHElqadaSlPIWSwLHDFQDWbaojGk+RlyCZCVDrtPDaOx9x6ESYx//4AhfOTpGXtLyx5yxzls/l2adfw1O1FM98PQsbdWzbUEXoXI47tnwCpCB6bQJRFli6yEpRraCYKPHVjTfylU3NTE56SRd0FAQbdW2dPPLCz3h53y7u+vQNWCtGUqnT3PftW3hz514a5vTw/Jt/4Y/P/oPfPvEmhZiCb9x5K4889ns239BFOuFnyyUtmEpxhHKJYijKv33+ViwGAwOD41isDqrdeua1NFPfYuXLm1bwxpF+XPVWRJWdg6cPkokXyeVyqCSJTDJHY2sjuXiM0OwsJpPAFRtX0dq9DL1ag8VgJFWMsO/QflRaHY1NXahEA8VsAV8gwJmL/UjpFAvqa5njttJi1OIwmLEbplm7UMld1/Ywb26GLRuaePKh2zh++hR6p8Rzb7/M6nYda65czbXraqldkGb78kau2bqcbCnN2EgcXcaM0mOhkIuSKCchkaZMiWwJjBoD5XwBk6BEKqjY8OtnOfabB9hz101s/90R0pk+lMU4MhKtuhpsyy5BVkYY+sENTGnMKFVWUMqYtAqMajXR4DRinRabTktoJke0NEz05z/jyeeeoba9mrMD/URzOnYdOMKJs16UaitH+k4jhBK01NfgdJhxm/QEo37aly4gXcrT3tzElC+Mz1cikQ4xMRRFW2UhmQhSW2Ol3VOFTszjNOo4NTLL9PkKKjnPRDLFUCBCTU0t/kCW6WCE0UkfUqjM0qZmBiIjnMxmQaPj4OE+RLI4XDb0ZJgeSnM+cZ693jS+Ypn2S1ahKuRpa61nYCzG/X9/AqMqx6HgeZxFDY6SwMxogY+OXERtlXBbRKJTMdx2NdPBCLFYjI3r1+KwV5HKlShhZiYSoKmxHaPbwHQ+y9lzQXZ9MMjRo33E/SVAZv3qxdz/pfX8x69v+J8j8v9qgiA0AYuAo0CVLMuzH2/5gaqP41rA91+OTX2M/X9aJJrk7NAgnpoUpYyaswNHUGmyhJJqUnkNCy5xcPRQgs4VTvZ/MMppX5CiWCIvm1i8tJsXdwygEROU8kmeenkHTmeYuQuX8aX7fs/fX/sHl1xuQJF387mvLaC9oRtdQeD9935DLJVmfns7kVE/WzZ0Mq+5nTfffICXf7OVJQ21PPYfO1Aqd/LYg1v5twceJyHEaLC10ep2MTleZNib5q2d53jrw3dIZyLsOzjEmitXsWVDL0fOjOBNf4ROpeahb36DH37xVrRmBUUpxzfvuhKTtoU6vRunx87keAyXFtpqqtm0cA2bF89Fo1CRDHm56ZPrqKrRc9mVHpS5MJ/ZcAlf/kwL1yzMsnvwMKnELAtWupktJFjVUcWn5n2SV88fx5x3EgnVYMzCwze38ew9N/PNO3tZaHeztGE5J/d6sUoH0Oth7/g+DE4bNd0entk3zZPPvkU4dZDf/e1BzEY1JWUJnUGiTJxQOIHd08pVW+bgsboxKT0EJRNSXo9BlKjz2JmcTVFWCjS6Hez86DhLlvbgqnMSSvtA5cHRaMHRkqcvGKS9aR7eUR/zOroYHQ3w9Tvv4MXTI5ydPcODjx/kkXtvYHzyAuW8knu+9wze02U+eOtDLk55CURncXrm03/oJKWUnxq7jY3rL6fWs5RErIzeZuT3v/89j/3kV/S0Lcc7I9FWq+dTt7fhqTFitOh45a1nWdDRhaUESV8Cuawgmc2xcu0GXt13lJxcwVZtpXu+h527x/FYRLIlLQsXdNJZ50YUROwWB5tWr8Vhl3B4rOzbfQ6lVqacT5MuZpkJRLHbXBw8vJtpv490KUGxJKNQqNAYtSjzeQrZOPGKTCItcu1la1FqcpwdHcVRW481nuCnzz1BV2s9eRWYdW5Ep45kaJKIEjRVDWSKeWqrVDToDUTKBdIaEx21VcxkZdIZNQWNGr2sRmMSSCRimO0K9OZaXB1doBpFFw2QUCt592t3sv2ZMTKzs+hNNrRmE/V3fo+jv/8uSr0BnaxALEgUcnnkksCsswp7PE3J5KIYCBHODZEsVsg4tYw++mf+9MvHiacKpGYiGGU7Z+MBLhzrR2VrwVNfQywRZSoYRmcyo9d5mM0lsal0nB0cZPWqHs6NTqIz1tNU5wFDiXg+TiFaoCxlmQ7GGQ8HSKYlXHUG2qoslKut9J33cXE2iqapmhoXiG4L3/hMG6dHkyxqbMNq0DATjmK0uVg3Zy6mSgJ9SU9MLdFmraetbj6CIs60N0l4YoRdZ2ZxeGoIFG3kZCNKiuwenKTZrSapi7Bx1VxODw3TO/9KFi1vwlxtJhjxo1eZmZ0JMhvNM3zxNL6oH99UitNn+ihJGWo0El3NCtZd2knPokbau2opKSSefeEwwXSOoePn/3Vu/lfFlwVBMAL7gIdlWX5VEIS4LMvW/7Ifk2XZJgjCW8DPZFk+8DG+B/i2LMsn/pf33cU/Ry+oRZb0dAtIOR3bt3ey85UBTLYcK9d0cGh/FJM6S/scHYNDYZTKJhrqlPijfoZGMtx1SxdpRIbPxWlorMEf62dsGJq6ZS7fcBX7do7TNjfF4JEgG9fP59DhUQLREkltAu8FLRvXZlm7YguitkSlpKWiyFJKhQiFylQUZkxWkWxa4NnX3sWgsyEqYzz984f5/q+eIizloSJgtYiEZstUN7s5ve8I//nYNwnGxgnkRkklSsSjdvYdC3HHdie796V4dnc/FrVAnd1FIhWnvqaK2eAoNlGPUGvApSiybuVqjh75kIpSxuBuwjc1QqPFQ0OLnumkF7fHzFJXL15viXannrJS5MDFo7Q2V3Ptli5+8NgTZItqfvbNRxkYPkZd4yZK+QmOjh2kViUhK+y8PXiAQsJCIjDFzdtvY2TXKNW9Hsr6DKqMk/3HdnLDxiux1Dv5+R9e5NzMFC01nRw9fhqLTkVGVpOLiZgsamSlhMVgoJzx09PVSEdrDX1H+rn2zk9xZOcTzO9eiyiaeWX/ISyiyIWRAF+883riyTxvvvYGnoYlvH9sgO6GLFsWbOSlU324ShL5vMSySzqZCae45ebldMztoVIw88zf/4he7+T06dNcv2kbl6/bzMEje3hv90F2H7tIXW09sbiPH95/D4/++tes6b2EUe8YLqOOq65eSuecjdx295089LXv8/CTP+LwcR0ep4DbbSZXSrHqkqVcODNBMJZCUSoRDSa57JJ5nDt1gbm9K7AbJDLJEhVNkJlAASp5atwGYjMivpEi27e6KcQVRMsFFGUFoWCc79z/AP/4xz+QZJlMQqKQS5LP54ikk8RCEsdCBRQakfUdDcjSCGsXrmQ06UOOlhjJ5BHURQqSgp65tcwtpog5SqRmLDR3CQxMF5DKcVq0blIRmYAyhs1Sz5mdJ7lh2QJufuRbvHL/A0RlLcVCAbvGwNLuDjq/9wcOfncbqoqaIZ+XKkxULd1My2cvI/qThzAt24pcayH64TsYtAZSpQKIaoRSEqPeQU3nKhKLOhn89c9Il6JY5SwIVdgkN7W/foqSFOLAy9/j6IVhxs76cDQ6KJaCRKZLLOus58TAKPbqakw6DWF/kLyQY1ltB32BSfwxFS5rmXxGYEl3E/tODNPZoSUTV6MzaIhkE8gCpFN5mlvnUEmG8UkJqvRO0qk8gWSCtno7KtmBVjGEmKnHpIePpgdpNrkx1VtpMZvJJlP0jQXRu2WMChNnRuNoMjliYoF5ze2cn5ihyWpDQQStuZpAuoRBm6GqJGJtbMIXnsVsqGb3oaNM+YrYBRuXb+2gBj+vnPGxfH4XuWSYHBaqzDakXAQZ0OqsRFIZupr1XDg9SEdXLYPjGbLkqDVYWbSyidu/9Ma/JL78L3XkgiCIwCvAc7Isv/oxHPi/RyYfr8GP8Wmg/r8cr/sY+3+YLMt/lmV5qSzLS1UKAblspCwoeOXlkxRUBaScjrGhFBaHjsmUhpK6mt6VFmrcCfzBSXxjEg1tdqZmKuzfdQ5J9tPSKdNddTlj42n278xy3+dewDfVx5v/GGLTpzajsNpZu/USRKeJhFdmdY8Fq9XOvd97BZNJiaDIUkjpCSbLtM5dzqHTJzjRF2XH6weoZEBKKFFpPUzMjHLoQASlmKFjTj3n+mbpanAz6x/jurs38onbfs+fn3+X13f4MYlKFs9pxF4zRH/fNK3ti3BUCmg1ebpbLPTUGohnxnHUGBn1ZzEVBaYDZcamTnLTzdvobOlkZmyYnvYWNi9ZzJp5y/n8td9h4oRAcmKE+jlmosYMTx17FpVDQU6l43fPv4HSbKG+08Evnvkrbx98DpVwipfefYkqgwNvskxeIzPXsZAbN23h3pu+gq6kYH8xxlsnjxAMF3jinSf4aHSG197bhT6TZqJ/FLVCw8kj/WhEPTW1DhY01LF1o4Jvf2khn7upi8Kknztu7GLxwm72HznMmq1NLG8t8/377sBsd/LMazvp6ViHubmaRpObbz36Ers+Ok1jUy1G0YdDLLBm/rW8f7yPaDiAdyrBZAbUWgsHjo8ycGGUr977II//7SeMjM/w0uv7WNS7hMaOTh5/+gnyQppAXEFZgKnpGKEA/PuPf4vTUc/pgVO4bMvpG5pCKep5eccTfOPrP+FHj/8Cs66Rq9e2oS3oMFQqrFrUy+RkhFQ0jj4vUMmXWdDTwqkzY6xZv4bh8+c4ceACrbVudCULIgpWrFgBRZnbbtqMLMpUBAtGqx25pESpELntts/yhz/+jkKhQC6TQgBEUcRiNtLsqeY7d95MKSahzEvMmduCQWPh+PkBhqcjzMo5wuEI1VYD1Ro3gWkfPqUVrzdJdauDTLpCo6Dkwes+gVBOcFwKoFBWiOYKCBYralsVSo0OfyyGRlDitFpoqHeg0tpJRYdpsdfiDwYoF/JMhiaYPP4WivxC3D99CNP191He+RqiVkGymCWvVIAskxXtlASR9MgpjI4ejNIo81VatGUbSkcTtl8/ReDuecQe+Qbreq+mwemgvamGdDrJRwf99CxsJyaVMZotRKJ+EpkIJZUapcnD3jN95GQBhzGHTlnDurXLOdbXR73HilS0MV0uMpyeRWMwUVfrQadX453yoXG6UBWKJKNhUAiIUoJQJo3VAGNlLQfODeDVlVAWVei1OuzKBOcOnWR0yItSUBBMKBjxp0mW8rR0teGyeDg5PIVOAUZdgaxahS8axpnLIacV6PQqrCbwiKDXqdmwbCHXb2tl/ScsrDAKxMsablt/KfNcAqJcQCioQJZJZ2MkpSjB+Aw6XZ5CHlrnt7Hn6ABanZpsOMOR80kO7534V+j5nxz933XkgiAI/HMGHpVl+Z7/gj8KRGRZ/pkgCPcDdlmWvyUIwlXAl4EtQC/wW1mWl//vaui0gnzNFRai8TRjEzJiQcG8ZU4shg6Gxj5ifqOFb373uzz1yu84eXwGd1UP6dgkerOO6dEZ2poaufuLN3Du3GFUapE33zrEgnlt+Hw+ZqZlNLYyeoueYtyKtVoklMiglUxMxgepNjSSSY3S2N6G3z+D1aRi594k/37fdrxTGd55Zw/ZbIWVq5o5PxrHoMyyclU3s+EAr70wzXe+v56R4fOM+UJcPFhhcbeB2oUWjnw0Q32NgSuXbSQiHaB7mRN1aSUzgVNMDWcYOjXC3NWLOHz0PL6QGpVSQq11kZH8LKlzcOMtzSSCBY4emUa2W/EFfbS1VxEI+pi3qIWJcxLZnBaLO05vVxOn+mNsubqXdFwini1RykiYDEr8sTRmdYhFjYs4NVogn5/l8LEjXLf9MlRxHUnDFPbyAkKRJEpTmfdODTAbmaC5xsWntlzBLfe/wNz6Iv6LSqq7lYydLYAabrxxHiu6W8nmBNweM8HgBO09K/n2tx8hFNPjdpa4Zm0jJYWeYmSKUKFM75o7+fNff8Nntm5kz9khJH8YrdmITqtHLIkUVaOM+1SUShVaalsZCAyTCMm4THbWX9HM3188iEoNl13aRGdbLwcO9nPg2HkuWdTBug3dKCpxnvjbXrKSifo6CwUpzXSoyKIuLafOpP+pMtRgwGJW0btqBS++fASrNkVJX0sonKVZUyKWzxGKF3DWuljS3cS50/0sWraSsdEL1Dd4OH3iFFUuD+Vijs6uDiqyxNlz/XR1zSWeDNDc3MDrr/Sx9apVlJIpikUBWSFTV1eHzzdLqVhBrQJ/ME5tnYuKJGG2W1Gq07y6Z4jxiJp5tUo0ZLG67dhtNsqlBKlECIvTQzgiY7IoyEopmuoaabGVCeUihFJuVIUk6xbP4VTfUdK6drTqPKUi1OqXccNtl/L0N+/BZamiVM7TVtXIgru/xJnXH0UTKNI3PY0iU0BrNlKtVWLAzZK/fUjwsWuoGGWkiAqlSkumIqAXlehlNaVSmOob7kNoWYtSkknrlBgpUZYr9H1vMblKHTaNFmfFgGLrVfzqh1+hT7DToLKgs2QRDWbS8RgoBMqyQDYeoqB2ohfLGC1aMkUdNbUmJs4NYHI7IJzC6dISycg0WuyMBv0k8gU8Hg/ZTBpfIkyXq4ZwPIGs19BdX4cvlsBqVDHojVDdshCDOIndmydpMSEUw8xcTCA6NERzUNKUqXK5aCzrODpzgTqthpDOQYvRRDrixZeVsclQUKtocFgpF7WsWjqXD44cRMaB3Qjb13+SV/Y/TSZkIWAcJ5sEI2bKAth0MpmChrbWZsbHx1HpRHQqNYlUEFFho7Pbg3dqEqmoQIol8SUk3tsV/B/ryC8BPg1cLgjCmY99C/AzYKMgCMPAho+fAd4BxoAR4D+Af/vvChQK8Jlbv8iFizpktYKAZOKKq5fz9nvn8TS6SWDmE7c+xN+ei2K1NxIKe5mdNjI7HaNraQM5IYNL1NDvHWHgWISuJWZOnfPRs+wyrvrkBnJJLfPq6mmsa+fKjfPRxhtIlSu4HNUEUn5+/u2vcOZoANGsw+h009SiJVvWsfPNg9S6XRhFDcdPTCGXJXzBPG+8e4Hz56a5+pNGPjxyhKHRKHp9hV/9cgV3fuV6euqWUtJqmRrL8MTLryFru3nupWke/cOTNM5v4MoNN7Fo83VUd8jcefNn2PPMVykXykwFYvz1d1tprVeTCWoZ841x+dbVXL6sl3yswMxUjG1blmOXqujp0PKrhz6LWVPPe3sH2XB5NzPTGU4dHePkwbc4PznL3r1nWWgzMO0fYsf7R+k79wYUo3TPcXH2wiSvnzhEPKTjj2+/yuHhi7y85xDZSIyG6kWcPJ3ir8+9iVujYmFPB1df18yGNZ0YTLBojopLFjRz/MRuTg8cZXB8kON9QXxBL1dfuplqC6Tjap59ZZh8WaKxYQ2LPN1UMl6WLW/jkcd3s23eQpZ2wJJV6xmY9DKTmSE4o2Hp/FqWLvYw7hvFpmqip1NHcDbAB+8fpNGjxaBx88yOCR7/8z84fmoSq1PHvjOz/OZPb3L8wBjXbF6MyaIkkggRjkk4tBVmZqOs6LJQ1ln5zb13MDSe5vlXDqIWK4QlNYGAj3Ipy1i+gqSzo7SYSeVzDHhnKGtVLOgok/QFKYgC6hJI5Ry5SoUPdx0jXSnSPseDd8rHrx79HcVclJ4lzUhpHeQTaAwKzp4fZ273EvQaPbl8lnylgNHopFJWYDab0QgKcgklly9xI6TjFItKcoU0pior6Xyano4a/nTbFVSmx+l0KjBblVS7Gpjwejl66jzRiAFfaIJgJMapCz6GRCPz3EbGI1nkQoQdB95k/2sfceePfo5UDkFeiZTXYJqzHu30IImSBgNmzA4dDQYRq9VKja4BlZwnqMlSk7CjEjUIlRyiTk9JraJYVFL3lScpuhoZ+ekGZn5zI8PfuYzxe69DMXAEe+9qbAIUUhIBVRxp92v86MEHqEmFCc1ESChkKikFJa2KZEwiI+noXbiAZpeMMjdNyJ/n3strSA3N0G41cHNPI3q9ke56O+VinuB0AL3eiM5iY2JknDqNmQadjaJOj9lswWYyMTzoxSSUOXm+HwGwT12kTu1EZylSyE+z66ifKUnNxWkYmtGgE624SmXyg1PcuKmTy9wttLkFzoczNBqrkZMijVYX2y9tIxwIYjYYGZ4NsXrZInQmiEtR/rLrXdY3rcXVqONqm4nO6ibmOGrwGGAmrqG+QcOxEz4UOhux6SjachiLoZP2Rh0vvdtPZMZEtJzmwqwOpzH3L9Dzv0jksiwfkGVZkGW5R5blhR/7O7IsR2RZXi/LcrssyxtkWY5+nC/LsvwlWZZbZVme/7/Oxv9fP0Kp4EeP/hKlukghq0RviPHLn+3CYo8xNZlm7EKIcgb0GgG5bCaXjdM2p8T2qy8DyUTCV+KBX/yBswMyuugoIxfMpDIlXnjpDf78pz1UN5vxByV2vX2A7z24g9Gcn2MjA9w018jKBQt49Lnfcem6VqITEfSlEpaKh/986hUUVpFIOY7GbUdv0ZCT8ixb2onHrWbb1hVYzVYqUgmdqCWXhcHRJH/f8TeWzW9ifkOZlMrEqsUuomcjdNX18MdHPk/eL3G4/32y02fZ984ERuMMHluUnhV1LJibR7S1klHmmdO0gBu334BW6yUY83HD7VfgHUszO6vjlX2HGYsn+cI3fkzSHySeELh4pB/flJdyWYOlpp1NczuZDKb54X/uomfBJiaSfoz2GgZ9Xtq6e+mc387GDUuobW+jrd5EKBUkEtEQDBfx+XyYTDLbr72a5as89C5bjtmhwmKu8I0HNlApqnDVFNh45QYc7jn85Zmj9I/6CYz52LHzPYJlBZYqN1vWL2DHS7NciMi8duI4x4fOMafGTmNdkf2+i2hr2hk4dYAFHc1EA1EWLGgnmixzoW+ExfM7Ge0f4JKVl7LlWoHP376Ne790K8lEELNajc2soVJIYTcYqNKkaDAbkRRqgiEN8ahEPqmjxq3H4VZSKC3g5HAQRyzFG+8folyCSDRNUVaiUitxuRwolQKCXEYulqBURi2IVPIyQlGJ11ti69XLifoC2Ko7KGcL6IwGDDYLQh4UGhGTRWRgYIBrt36WzRtWMR30Y3DUkk2nefrpJ3n++ecpl2RMBisiaswmHSaThXypTCLrB0GgLBn45NZ5BDJK2hc0UymWMWkTHB0aZmQqT/dcG4Jopdemot6cR+syUTTUEEjHqHW5SavLoBFpCJVIpWI49SpODfi5cpGD19/dT9IXp2x1Y3FZaJ1bR0Y5xcLf9NPTW4PRXsJdBEfnehb/4h2M3/w8jA2jVBSJGcxkizHUZRWSHEMT1OL5zn+Q63uKwp/uwaVpQimIGOx2NHYdMf80FnMrWreGgkWHNlqi9rJbUHTdwy8+iKGUJqgxVJM25ElNRPG4TXSaiwQHT6MruFnQsJxLqvW8f2YcR5USUTTx7N4x6mqrGJmSyAdCzHG50CkgHQxgczmJizJTmTi5Qo5yKY8ik6LWowJFlMXzerCbTUSENOXzKWakDBfG/DS2NZKspOkfzDK/q5qBkXEa6uvo3t7JsWNhnjp7lld3+dn3QT+RnAJzqx67UstzH57j0pZ5TPQNEcmVeePgcZJSgUW1NQQm+zk4eRBNLMLRqQlq66oYDU2hqaigXMA7DeligvHJIKK6GpN1IWKNiWi8gLkcZDIe5Zr2lWxZoEDA+S8T+f8vbnb+9Kc/elAom4lMp+lsFmn2tOOqiaKhjFmn47N3dzDcP01FUaBStKDRWxkfDdDffxG0GbI5BbFUAilXweN2EpfCBKbg3+5ZT3VdheefmKZ/ehajXkEmo2bSm8OtUWDrMdBQ4+DeL3yfh37xBiq1Hr8/jcrhJxYroyjbqMglBIWCWCKNQtaQjMVRlitkkmrGR4OIGJFyGay2VqKhi2y5ajO+IR8r1y1m/eImnnj2FNde1UxzQ5JARMm030E+GOQr99+MuxhnSedVfO4nT5HKSqyYZ+Gx337E+GiaFz48zpAvwuIFl1BRTFPfupJLljXiG9nDpitvo15VwdliYf/+UbpajEyMSjQvquXX/3GEZl2ce772RZ7/v6i77y85D/Lu/++7zD29z+zO9l1pV6vVqlcXyZKb3I0xsU3oBgIYkjg8lMcpfGMcAyGQhxIMCTx001yxwXKXLVm9111t7zu70/vcc9fvD/wD+eF7vidcf8TrXOdzzvW5njvERNLAIZTJlQSGhmpoWAxfWWR2oYCspbn+5vv43Y+fw+tvZXo5j9/nYWo6RUeihZmpCdK5Oe68/Q7iMReybaCZCnfecjuHj/8Rn3AVf9h/AFX3kU3XMCQDlySRnyyyfnAVSX2C6wavoWosIjlrVDKLvP89D1MsnObiaJJt6zYwNDyEw3Yz2N9GPO6hkk9z1fYtHDpyiuvvupbejmZu3vUA4+NvsXXDRras6eUv33MdXe0Z7rjpJt5/63vYvaOTgVWDvHjwMOPDC1yzJ8Le69fgdjRx32138+Kx53n+377CQ5/9KEdOjHLmwjieoB/bAWq1Qk2t43b50dUGjUaFdev7mZuboaUpRLmQR3TA0vwy6YUkYthDSBYxRYuaqhP2OED24vOIhINuZubGaYtH+f0Lb+D0+gm6PLz+9huIggO/24tumnS1duJwSCwuLWFaFqZmIjtciGKDWCjO2UtjtLepTM7W6ehvZ2lSpVhI4Y81ozrdnM6ViQR8NLIFAsEgWzoSVGpZdvf00WPLXFycoj3awZVijpjHQWfUy1xqmSunh/jIZ/6aV158mXf927d565EHGP3Vk1SmZfZ+9Xs03fM+nEKJqa8/jE8dQTX66LrnK7DRjfjmRTzdNuJZkbZv/YKj1lmyAAAgAElEQVTRf96KmBIpmQa2Q2DS9hG2dRz+CN5wnOT5tykmLxNLt5D43gsM/+QfyL7xBNIzz/PhX76O09I5eOYwPk+MtS0xSlIRxdGErMB0Kcm27k68kSaOjY4yNZ2ma0UboWyV8YrGao+XmiFQUsv4AyE0wWKhkMNhKCgOF5WGSr5YwheRSWWDJHMVsoV5vEorulBhsdjAdHoZGx1n++YdaGYKp9RgJiPS2yvxjZ8eJp+vM5Lzc21HnJF0BocnzDrTwevnhnjopjV858gcSrWCFfUTbgpSK9focis0r2xjuZBiUXMR8fg5d+UKgjeA1+mibhucPDmHwx1gYqLIjXtbmR+dJu60uTSRw6NI1DJJDo2kOTu8SL6sklzW/r+57Pz/Y0zDolLP8cmHrqE5pJDPzmKprTS3QS7T4KUXZxBlk57uKKFYg2J5mkQbDKxtYnZGR7PLlKs2jVqNYFcPlhalqSnO0WMnefd911Gp2pRrICgy5UINp+RAkWIcPTQNRpLfPT3O5k1+ppdSuMPNqDq4nTJ6XQNLoFqu4FRcAFQqKuWSgWpnae2OUannESUXolzD6/STySY5ePwsVTNLzOflwU/uxBeQcVrrWN0/wC9+9Wt6VzUxdu4CV2aKzA6fZ3xmGbVUYDlpMdDfhiwGCAQlLo3Mcst7/4Z3jgxTKiS5cPltbr7xTirFY6zs2cNLb13hYx+6ga51MdrbKjRHfFyzvpWBFh8EBOIxD5Koc2XU5OqrN1BrlBmb0LEVgVypSKFSZd++Fxnc2o8l1pAdNpFokFDQQ7miUak1qJbhpT/8Hr83hKkmqKpzvPLa6zTqQVb0+SiVs1hmjXjMYmQ4ydx0lttuWMncxHG0eoANm2JctXkV69auYdPaAeZSF/n0p7/I6bdVxmeTlKoGfatWkM1m2f/2UdYMrEKvqzQn4hw+dJCX//gmp8++zPK8iCyL3HrT3cQ9PnwOP+v71lMszqCqVQJhmaCoc99927jr5vuI+Vbx7NMH+dHPfs1f3rub44df5q8+80me338Ab9CLQxKpFUt0tDZTq4Bt20QjcWqqzdLyMr6Ak2qtTEtrgoWlHHVLIuz3sLIvQbVaoau9hUajRn9vH0tzSerlCmNjYxSLOU4cO0J3azPhUJRCvoJDElBkmUZdxa0oYEsYpoamaciygiL7sQRABF01aQ6K7NqyhYBHYWExR3dHE8liiYWlPJcmh4gLbq66aiMlu45q2dTTWVZFm1m3qo/pfIpBbxOnZ6doCQZZqpdo8gQIeCWmUjmW59M0gLq3TG9TE8tmjaMzR3nnq1/lwpc+w6nf/RixYxWV2QbS3q2UGcPjuR7rmlaWLxRp+uB7mD39G6JEqKIRkJ00RIGWahLD56U2OoJn6/X47vwI3bd8ls5v/juZJx4irjmphgbx3buLxbELbG63idbTSM4aiwspSlmDXKGBLVQoVopM5wu8fvgIFFV62lbgT3hYMGqIIjR1drAwkaKnuw+HomAYBm5ZIewPolbrGAh0dHYxOlHAGXIiOCpUyjqqXiFruti56ypikRDX7thGUDHZuqENy9DQayXKukClJuH1exhosxiaXWL3pjVUtRrpuQZBS2P//DKrO1fRUGA5tUh2aQ6nQ2E2m+fNA4doGAo4bAzRhcfhxG7oSG43PreMVtWwzTrhYDtDF8pMJxu8dn6E2WSOnlAb69btYO3gDQx0riEzXflvG/o/YiN//PEvP1ppBLlyfpzetlaGJ/IU6k523+JnfNxiLlmgNR5mad7J6NASfa0RPvaxDbz69BxOd4zOuM5sWsQwBe68eSMvvXWa+eUy507J/J9vHGbH3gBaWqRWU7DdGho13IESgz1+2sI3sn3jCLnJJPd94G/4w/Mvo5cEMgUHzW1OBgZbSS0ZqGoFn1/GNixcjgBVzU0mnwXbxh+IUC4X2LYmQKkkE+/cxltH3+HI6Yts6FfIjqRZNmfQskX++Z8+w0N//zu61srsGtzJWPY8u9bcimZf4sOfeITzl55l7HyDvhWt+Fwyr+/7BckFBxcWTrGma5D/+8ODXE4vMri5j1f+cIF39i9z9+1ruPmuB3j2t0/x//zjXtrbW2n2N3N2egq1JnFiMklqbhqPW8Ljj7GUtHC5fBgOgeWFCq+dXCKbUpFkBV2to1s2uqaysr8d2wqxsssi7AuQK4/g9nYSCSYQrV5S43my9SzDQzlCTpNbd2ygo7eL86dH6F/ZgtmY48rMRc6eHqanfwOyZGPZnTz48cdpbocDE3kCbhdTY7P09vZQ0+qMTaW56bqb8csuNq7tIRYL4HaFCDeplMsypw6+waXzZ9iz516S2STJM8eIdazh+Td+T8IfZMf2OH4lxvTUeaKtXjKiza3repkoZxlcM8irB0fwOSTcHoX29jB6TWPlqi7Gp5Zo1HUM3aKu6oRDAUzDwCEpDI/UaF7h5CP33s/ZoVNoaoNNawZYs34Dl86dIBr10Nbcgtaw+cRDnyLo8vLWvtfxBZvwuwOIioCq6ridTnSjgWEI5MspXIofRZZxu2R0QcXSXNTUDOGARMIPtmnQEUsg185ieFaypM8TaG6lbujUFy4h11SWCxXclkxzdxeHDh2j39PCucUl8pJJ27oI2SmRplAFlxTn128O02HrbN2zicBEivHFaYbGp1nZkaA76qFm2bj8IVpcHujZQ6Mxj++Z37J8+I+0ffjbKLc+iFY8Ds/8kUWvgte2qPvcKFUTpxlDjrlp+sKTnHtkN45zI4gBH54tO7n0my8hZ+tEt13FwuUzNC7so6o38d5/eIz0xGWGzl1mINaP5THwlauojjCTkzP0dm5FbLI4PT1PcTmL2TAh6mRqehrJ3UVDL6A5RBqNBj5BAa+A2yHhcjsozi3gCTaTK+Xp61xNayzESwcusWltO5Pj0/S0tWDU66xINFiezlPVbbaujTN8pcaOTR1YtTxSqJ2WVoNyrUoyKdK63gDdwalFD03+KWo+HxsGuogIKpqtIMej9K0MkVlWUUsWoXCQoCVA0aQkafTGQ/SsdmJaXrKVJH6fyjXXdNEkuRnLV5i+NMurpwucmT2OqCls3tPKpYuZP5/SrC9/+bFHP3DbGuZSGUYWs+y9oYNaIc/URA5TdeJwWxTqdWKRCLmiRlGrMzuepVQxcAYrmKIXh+mmtc3J8y+fozPiY3Gxxhfu28K7dm6kN+5HFOfQk1U+89mdVE2D7335bwgGYvz4yV9RaxRx+1fyy6d/h8sV4YabV3L8+DytnTH27x/HsP/U+qdqAr6AE81s4HPJLKQKGA0Pn7x9NREzTSXcx46eDva9cZD1q5q54dp+Tp86y/ve/1EGu0NsCCgUprJcs7OD7z03zMzlkzz/5iRvvHOG//vtzzB8epRctcyzv/5XnvjRG0xM5hAkFzXRBuKMDF8Cbxd9K1Syi1BIzzGa1OlpqyMaZRJ9rbz02yMcOpDmzvvv4uc/+R2D21dTyqTYsWkXpUqGwdXd5AsZTKNEbtlBQa1TzFYIeHy43B7KmTJuRGq2gSTYGKaGN+AjOTvHlVEHR04d55697+I7330CZ0LhndNjdEQCbN60jqm5ArKc55ZdW1jRleDaq6+iYcd5+1CSj75/LfufeosXXjrBRz6zkWOHqtTrblQ1i2mHmLk8R6y7C6dRZ2bkEm0rO5iYmGPt2jVcHL5IpSgQDSbwt7QQDHTyyOefoG/Agy++ialUEndQ5ZrtV5PKJVm4dBKP4mD35g0cOXie558/x9bBrRi5DO/91F+TWxzi5p1bePPwBTwBP6VGHguT99xzK3YtTzAgM5bMkCs3WBH38Mjnr2PyQpIfPHuEbiwmcgJvnBpmc38b67e0ILhdLC4VscwCbc1eXnrrGW7ZewPJ5Sj9rRHqZg3RstmxcROz05NEw0FqVQ3FJWNqdWqmjt2QkB0mNVVHcXiZLydxyW4kFNpDBu3tq0kml7i6v5cmGnj8QSIdIW66ZReXiilOXxpDkAIsNIYpeuIEA14unZnGE5JZmC6QqZWwqhI93X78sRj15UnGxuaIBpvpbk2gpmq4Yg7CTgkxXaf9kYdx/PpfyWg2DaNB7uwpWpqaWFw6gq5ZOKp1LLcbwyggL0m0P/5DMq/9F5l3fotTcKNJEg1bon7sDN3//FUcukJx9CSBFdfR9/B3WDr1PRZ/+kcqmfNsa1/LwsUDLEyniXbEaO1s4u1iHgUBvdhAsgza/X48bS0sTEzj8QSIxzwYZhlNsIkIDky7QS6vs7onSFc0QjDazExyjiZvDFXTSKXmWFw2SAhert/m5crQGF63TW2pyvtvHqTYyFLRTFyWTiaXRQ4GaZSS+P09NAUdjC8uMzqeJmP7kIwKoWCEtavXkJq5iIJEPN6BWjeoNSqklk3i3jKa4MTj9bGoaazpaKKWV7HKGnrQyz07t9EVlZlZmqduepmZXmJZt9ixuZdrVrvwhnTmppeZX9T/fCD/l8e//Gg2V0UTdWQBpucL3HrnDiZmZsEjkc9bpNNeOtpNujsc5PMitYKGLxommVFZ0+MjOVNk7Zou5kaXWZhoEGzvZnTuMq+cG2F4tkCyKNDXKvCz/XnePejBVJY5sP84DUvg8IEyZSHN7IhO52CQI2+NkeiIMDWxRCzswiN5KdVrSIKNiwatwSCVXI5QKEatVCU/OcXThxp89O67+ekrr5CrC7x9eJ6/enAnZ0amOXd6FCOoc3q2wZNvnebbT53lx49fx3OHhqiWIrS1mzzyrfNEOzK0Oru4/6H/xO82cCkmboeO07Ix8g0WChoWFXo6g0xOzPChv1zPBx/s4el9w9RKCqnZOnm7ynOvprllTxdPvXgcU5JJLmQZHp4g1gS1skylmsGyDErlOullJ26/C5dbYXJ+Ga9Hol6v4xAVMmqRzoRGe8RFQRUZG51CLXuZS04QS3Sy//R5btq+nYujk/S0+0m06qzduJbunvUEogme+OnT7N5+M0uVEfb/cYZHP/cpWptrbNh0D20JBwfODNGaiFFeThFPOBlZmKe9uQ1VWKCrazuaWWdkfBqf6KKlrYt0vcFrL72BrQhcf4eH4VNTBNrDpBZrdHQO8MXHf8y73n0jadXN9586Qr2wxA27O3GFnEzkljh5bpLl+YtYgsCbR05jItJQKyQSzZSzOSrZRRrlKjVTRvG5WNceZGJB4+H3Xc/8zDyzOYuvP/5ejl64zNrNbVx/zQCvHX6LStXEkOo0Gl4OH75CIL4Sh73I2HgGp7PGcrrAli07OHLgAA6HgMfpYHF5iXCsGafi5qPvv5uR8TnquoFbFpFFgZ03bsHK1xmenGZVU4IJtUGz7ePOj91Di1hnPl0juVBleW4JRy1IV2eE3u5W1vUNkMql0eo5PK4W4vEgltlg3cYONvd7+e3Px9lzxzakfJLUYoqV3W24BBstHMLjdNHIqPR/+1XG/+EvKAoJlq0UDsWDUlqikcvRsfsaCu8coio0iPu8BKQW7L3XMfdfD1HVBTwLCuWWCqGaj47WHdTv30HjXx5lNrVMvV7ALC4z9vxzbLzzi/g+8j627LyDjvUbGNiym3v/+mGOnHib84V5PtRxPVdmLmP4fGh1C3dzkJHJGdo7Ogh7PAxYXorlPCcWZ1k1uIaipBL3ttDXJOO164zMLxJyRlClOqpRJeqM0hmOMFGZZ7C3n/PzM6iWhGZ6mE6lqOoe0qkquwebWKxoeJwBlnSVHr8fzW8yfnaegW3tzE6b/OuXPs6Jw28x2N/GHXu24rEsTo1O4HA6kamCK8LM/BTrzDi6B6IxP5nFeeo1kaJPJk6dodQI+4ZSLM81QHFQrXqpqwWWs1kUSWRqwk+sqYmJ6dSfEeSPPfqo7JbR9AZBt4d62Ul+foL/+s5f8eQTx2npcOLyuDl9MsvKtZ3MTGQJhEyqqotSrcjYTIW6ZHB5NMu9713H2fNplEaJaHsLWwcUZAos5oOodQ9eb5bN1+8Gh86dd93IO8fPo5sebt+7jVePTKMXg4hOG121uGpbP1s2r6FYnsfldiE5bBwYBFwubL9ExO9DkEvg70N05jhy8hzJlMDkeAHR44ZkleGkwvxEmkBIJT1UpNsTZKFU5fU3rhAW3fhbnSyUa3gcLs5druB2Wlhlm5xdJ9G9krlljYYhMZsqs3VjFz0rnNxw3S5++dMRbt7tZNvmO9i0bg1qvU5FnmVsyMTr8XPgtdPYSpiJiSRej8DqFatI5fIszuURHAF8vgCa3qBUskHSsIwG0XCIWNzNhz98M6v6vGQX6tx8Yy9Xb9+JaEnML+dolIsoPpH//flPsiKocGH0HCHZpG/lCpoTG/nRz5/j5VeP8MJLR5ictBjYmODW6+/nJ888z6nLM8geg+7OHk4Nv8r0JQNNLyM2PNRNA63mZ35+gZW9/UzMDlHL6gyPTbK6bxUTswscOXuR1ev6Ma00H7zlRlpXr+PEyQs4HCZvH32FkTEDn1XhkU99gctX3mJ4OE97RxftHSFOHp4hGkvgC/gQXEFsyUmxVKajM8H4yTmOvf47Xj/4CpZPolwtcs91O2hrNRncvoonv/8Srh4vVdXi9OFL4DAoZvMcHxlH1l0kmkLEgmtIpmdYWJrn1tt2k/C3cm54ipDTR6GuMTO/zN889BD3338vO67ayYFDx5AVheTCPA29wexsElmWcMgSTlHnrQun0Ms2PWtWQNGN6CsQFG2efecMFydLLOcqJBQHkyOz9LU3M5zMcvT8GE5XGaEWJVNXiXdEMEt1Vva7Gb84xvquZl55O8k979qLqOUJuoJIgoZoyVSMAiGxwbp7H+PiC1/EQkAv1jGdThTbieIPUCgbxG/5OxzP/pT4puvwfPBrjDz5eUy9SDqtscLjI+2M0rNtBy2f/h7y6jj2yBTFseexNCeWqwu5nCIYbUbasoPU9/+O8+dPwpV5TgxfZuy1ffRIGn1tTbxw7hhKwMHU2DyBYIREa5Cp6VkSNTBLVcI1jYHtW+iMKoxfPEeHHsTyS+TKdSZmG3Q00vg7Oyk3yqzu6qAtJJMqZFkV7eTc2BROKUTIkhjsaqZc9+KIKAiml43r+7gyk0cUXMScJjm1hYSZpeSK0tESYW1bkP1nD9PV00HYqREWQjx36Cy+YAKsFEMTNVoicbYNepkxVEzRZiGdxR32sdyAVZEI3kQEryWzOeIkpducPptBtQx060//dfu6/axZH8CsFbg0Vvzzgfxrjz/+qNun4fdEqRSKyCEn3asM/vDyKeaMP2WFhaoDSRDIZ7IgSHgUJzUjh9sl4TP9uCSFaEBl7K0aA10mhlugXCsyXq7jNeIUzByJNps77rieLz2+j6FLSVLZM5w+6mf14Er2vX6UuNdP3mkTrhVQDSe6vsjYUI5qvUhQsvE63TSHQxjlBi78vHM+SUMR8OBEdqhYdZG/2L2Rv31ggF+9OsLjD9/IHw9PYZlFbr/+Dn726knmGhWyRQfJusTKFQoXp/KYmhO/S6NWbKDZZXJ1B7KjgaJo9HaLUCqxpsnJg5/eztjIWVxKjIMnJlm36Ro+//hPmBka5tJUAYE867tWMT49zbzVoF6s4Pc6wGrgcGhkcjqR5hCzyRq6aeJxuTDtKl6PG4cl4JANWhIhatUcqbkkO1a7OXZyjqXyBW7btR3JMYNQjoLbxkbixIXXeN+7P8zBS4u8/M5lcqWLbLv6dnK5BrpRprnFx+RMju/8+EVsTPaucjM0lKNWO0G8KpIPS6iFKnXVZuu1gyQnZ3B4fAg4WVpeYvO6NvoGBjh6/CCx1jhLy0vMTVaZWZjjzKljNLW08eK+4wyNlplO1qmU3Xz8/t3kp8Z4/flz2AWRp87MkE2WGeiO4xBNhieWUAQBs15h/cBKSpMlak6Bp956gd1bt3FmeJSWQJTCbI6JZIH37LmZ3Xft4ulnD3P/u9aSrYh87gMP8MaFKbZ3xLl241bGrlxB1ec4f3KZN159hS/83Re5bvdGVu9oJeHsZnz0MkZD5aMP3Mv02GW+9h8/QnT8KS+/87a97Dt4GEVWiEf8VGoaAYfJogA97QOkCjOMFh3kU9P0dAywkErREpJR2jsZn5ynvz3B2dwibR0BVne1MTebYxYDR62Iip9KvcBMxmTnqnWYJY3h5RRu1YGs1FEsJ4pTQFNhRzAKvXdgxKfwzMyxmCuTFR10qi7KjgKyWCZWtfFe+xeIt93J/G9/Ruym2yn85nH8sV5iW29EWbeF9ge+RPbYU6R/+RUyh35HYaTGyq++TvuNe2ndfBORnmaKtkbH9vcz9cxXsbMlinqNaLGELHsJbb2aDYN38J5/+g4HfvYtOnvXIjZM+uayrLplF2dPnCIcC3N9rJszU1eoJNqJ2x76e1t49tWDtHX00tnUSmTdjQT8VY6dmqZWkZjJLqBakNV0TKWOppbQRAc9HR1UpAyTC3Wcss7lxUWWl7KE4iG87hgPXFdkbj7ODTuWqRT9nJyfozMWQ8jq1G03yzPTtDgDnEwtsHlwM0ItTcBX5+TlEi2eGIpgIOke3B4vRV2nqKiUFya4MGMQ6WtjbUuEthUSx97J4w+5WdUismP9etLzWe7eey2/e+ncnw/kjz32z4/GQ150U6NhgUOSySR1JMmFZHoRZBcBRUfxWjQMD6alU9Nt1JoH27SRvC4Wk0W62n3cuq2PleuinLxc5toNq+l0u4k2VUlEO3nnwBKp7DRBxc/iYp10QSHolwg6dUplg7qh4bRVJJ+LcqVKPBanVCghOWRUS0Gv1VEtg2XVRDdrqJKXSski5KkgeyOUNJVLowucGpom4bL5+aFpesI1MkCb38HQaAHN0DEaOoIgYYk2ek0nV7Xw+UM4HBqC7cBrVrl+wyBL08vIQZlKVUPQTW7fu4OfvjjCq68tsmdzK3984xQiYSqajqlqnB8y8IVEok3djI2mcIgiIU8AzRJplA18XgWP208k6EURbfw+6OoIY1RMbER2bXcjinUkfwsNcty+eTPVqML9N+7FsJ0EHR4c4QC//s1FKlqRgGclf9i3n3pJx7QNAkqE2clFpqaSROIR0sU8yaRBokvlqR8+gK9NYtcuP/PTUR7+i/X8/VfOsX1TgsmpGsGwzcSiyUBPEMmusZSukmiJcujwBVb1ryYS8HFhZJrbbt1GZnmWrVuu59WX9rF55RZuu2oTN964lT1bLX747BtUai7OZpM0iRFqoSZuv7aXe+9az3K1ilWwuJAromoSk5MLNAwVX8hFk8dLKrlEtS4Rdvpo8rlYzC6zWE6yZ+smMuUlzh1NE3DaHDx+lg4hQ67uo7vXT7XkQK3muWbHeoxGmS3bV/PKa6/w8msXaPf0slTI89EH7mZ0fJzjF6+QLdUplgqUKxXuueceCpkcqWQSSXKiNlQUb4haMYcS91LNpFjOp+gMBXC7PZiCm5Kpk5ybJd7cwkI2wz89eA8nDp1kZXuUU1NLlBbSrFu3kenZaUL+Zhbnp9m5agsHJi7SFQkT7tiBMHQMf3sMTJEV3S1MDk+w7kv/ztjPniCV0ShVqshmFVcgSDjsp26EiX3uX1l68XGWjzzNihtuJxNcT2hgM675CZLz44T7d2MOvc3S8EGyNRtJEgh6ZJKv/pgL+/5A+jfP0v2JzzJ//i3OPfl11m68jdV/+zVa3/03dN72AZLTR6gdP8zMqbeZfv5p3n33w0Sv6mHu9Zc43bCwHBnmNBmvLrB/Oc+CqGJhMbGcolVy42zpwSnXGB0dplrM0JfooVJdIB7zUazZrOlyguqjUJtBr7hZ1dFOKT+HKIeRDZvugIdyUaM90Ua9XOX6jQl++MxBujvjyGaAAhJKfpGuHh/ZUpZ0xSYQDrBQLLF1cy+5fJ1EwEVL7xac2hJStc5Spcr2bf3MzaWomCbNDgtbCFKo1nnrnQt0dnWwubcFl0fDrFWZW1JZ3deDIU5z9Ox5Lo02/owg/5cvP+rzSQiYOCSBcDSIpdfp6PYioLCYKtLTHaJUFBAkA8nhoa6XaOvwYjR0LBMwNGLRAF2JCHrNJGKpvHM5x2QmhSD7OHFuHtEtY6JQa4hEo348Lie5YpnZVANRAt0wkUUJ29ZxOX3UVBVbcrGUU8nnNGSXQlnVyRZArRkUKw18Xg9mQwWHjWbZSJqI0+2m6oOo6GHJlun1hThyboHtm9o4O17B4XIgCTL1Ro1bbt/LqePjVBsNYkEvIZfM2hUtvHV4DG/IzZWpCrGmNhqWyo9/dY6P37ubRn0MzVdlVc9K5hcWEKQQZbVMMQ/pqQqVWgpTcFLXbdSGis/rwRZtHC4PyeUUkgCiJZKaL+GRnXS2NpFIqPgaIp/45IP8r88/g9NXpxHwsbV7kO8+8SRd/R76u3YimCn+9nMf4d/+zwtkF3RSJZVizeZTn7gHJZRlfqZCIuGlUa/jdVkoboU2WyOVLNAWc1PXVnD12iYcTV2s2xGjr8fPRz6zixefP4xlOWnUcuQKOpIloVfriLbC6MwihmawdfMmvLKLns4OiuUlZLmDb/z0JCdnLtHZqjDQfR3HXzrMxZSNgQ66jtupYgg1vvufh3js8x9kMZ/kfeu7GOgxGBqrotl1kF3kcxl279rN9FKaVDaN6VbwJZqZGprk/tvv5eTRc+TrGVYk+hmvTPKPn/gsE5UFNq/dwatHnqG/dyNf+Nyj7Hv5l1yeTpKbbNAbFsnoHdi1Ah/4y71847s/oVyXsaw6pmXyyN9/kc8+/HfUNJOA348oCEiyhNetoFsWk0uzxFpb8SMgiCplEabmC8iyiNaw8ThFFMXJ8PnLWEKIuZllFismV1+1laFL47g9CjNjM2RyNbLlAhs2b+XUxBAf3HUHk/OncKrQ1dGEms6w5fsvMfmlPdScTorFAoGIn8FIDN0HxoLFwKM/pHTh11SvzNH0kQdAtjH+9QvkM0cxCgreeoDwzfdSze1HmSliulQmyx7ymsTGD/4dKz70IayeIKnuwUcAACAASURBVKe/9AFKOQ3ZtlCyNXLH3iaydQWiowe9WsJpT2Nn53D7wtSmZsnPXuHjH3iIz3zveW4e2MLs0jx9LUEqyLh8Mn5JJqUYRAxwJXw06hmafC2UXQoTY+PEO1YQEATKWoNyRWZdV5l8OYHPYyI4AqhmiW45wlBuEocJoYBIW9zJubFpKm4vrc2rEfQSl8Yy6LbEAzffiNOCSqFCJC6ynF5kbGYZwe1BrVUpNGx8jgYJb5Dtm/o5P1UkmcoSCPkRHDIrehzMLgl4HAZ3XXstZ8ZG8cohetpD9K9qYs/OOFNT8xTqFkePC+RKlT8fyB9//LFH/T4ZQQC/x0MuryPYKmvXR7hwZgm3x0U85COfyeOQQFfLRHwxcqkSgq0hSjrYHuZzCufHJkllS3T1beLsZBI8MsWCBkiEYwFSS2WqlQb+sIhtmeTzKjdevZLpuRyKK0hD1QgFgmhWARD+lBUaHpAdVCoqmgkWLjRDw+PxY+g1ZMWmUtLwCjZKxE2fz0kQJ++9KsqJC0tcWigSD3qZmFgkEAkiCSai1sAWnJw+PcL63nbqjQYOS6Oq24wsFRF9IQpaCafLzVK6RDJtsOOqOBcvDfOhj97AXXft5PkX9uP1BCiUdGqWF9syiUYSyE4LW5fRzQY+nxe9UqNmmjgcHrRGlbBPppwt4AoGKJayzM1laG7u4uDUDIWFIT73wHY+vOdD7AomOH1lio/efSvVkok/5mQ4pdMaVDh25AyLaRCdAppusGZ9gm98bQxFKTI4EGJ+Ko9acvCR961n7103cmb6EL/+wzKmvIhLD2CHqpiZKm+cWuSV3x/ksYffx8fffQMHjg0zNldFsi1csoNKtUw0GmcpmWRkbAFN1QmHXfT1JrjjznvoaT5DxHIiqDOEV+7AG6jQHBfIzi6zqJkUGzK9rZ2YusEvnnmdO2/eQef6BJ/92/30rnURj3hIZVXcbonhSyOEAz662ptJZZOs6u+jK+Tn9eOvcerCOFdtuJnTmcPE/BFaPM0cPfYy4dYWrtuygTf2v0W0tYMf/epZWhItbHKEibvc1AIBYj4Pr77yGg1HiIauEg74EGWJl19+hVgshqqZOGQZy7aQJBFRNMES0akjyBJSRUORTRSvn3JNoNGoIuKgf1UnQxdHiQ8OMJvOEgh68SfamR6dIN4Zw65UuGPnLvZcs5ZLYzNMz6dY19PDvfc9QPqlPyA3edk0sArdDuFMT6AqNewliYbfBQ0B2+khmNbp+MYTZAQd79I8iTvfjeC6mvp//D2TYg2BQRqVZbq+9mvmj/yQ1p1fwrnOTf5nR9jzzcdYfPU5Zl97kew7x1m36V5W3HsDxokTVGsNXP4yLiNM9O6PsXjwm7hHj9LS+W6aH/kenbd+lMQdd1JceA79wBL/8uZxXvjmF4ndcBNXrVhNQ6hjSSIuv5OY4qc5HieSE6gJOWamk1wTaWKpXOTc7Cwt4WZml2dpjvrxNLw0+6JYYReipXDbYB/5Wo1ozEGh4aJWUamVq7jCcZZTE9hFJ41KkpIgEgv5OH7xIsPzWe7ftZFctYiMzTW7VjA2VsTnhSaHzEyxjLBc5PeTOS5NjlJRLQSxQWtrJ2ouzdRSibppkSlPMDpmYAsOFtMTTCUNHJKbw8cu0TO4gqm5DJlM7c/nIEiwweVQMBoaqm6Ao4QiNXH+xCJej4QtO7k8nMUfDZLNm7SFAohGma2b23EIIsWqF6ffxCaNbLlY3RXgmZcOcO2mNuRaDaetYTVMDLVA2OtnZZeThMfC7fazarVIrrCAw2lgmHUkp0C2mKVUBIfsQRDqYFbRzQpOpx/DEhElG8WrUKvV/oTYul7CMT81l4iRr3MpW+TKXBrL18T3H7mf3Ds/h3oJ292Kx6yioGGIMqW6F9kd4tKVeQTLi2W4KeQaqKpIqqCi6qCYHm67aQX//t1dpBcNwl0ufvbz0zx4zzO0RzvR8w0GVvrxiODxKmT0DMvZOmgGimCj12u4HC5kxcnSUpqQ1wdGhcFV3aQzYDu82E4XlydSBBrQ2ruCTFMCZaCPb559ky3X9pKz3Hzoq79nbGaRmOLl3o99k8WygeBUEGwLl+TlBz98lZa4zrZ1nWSulLhqdRtP/MfVeJQy6eVZvnDTbj6xpYlb9uxEtRWefPIIwfB6mqUqA11Bpicz/OOXv4VDbOCP+OgfiOJwG/j9fiS9jlNUQAkzt5hkzfp1/PKnLyOaEroY4f0fuJtLFTdXTu3j9PgMxVKGNYOr2LFWxuusMJnMMZrPoLt9/Md/7ucLX3+GzbdG8biC3HDtFgy1QTDoR1YcFEtpDLWCzykwPnaBaIuXD7z3Y6zt6OK5wy+hLbTRnujg5aNHeOwfH+GV068xsHEP9VKIn/3gu6zt9jG9kCWtlLiSt7l0eB8Nw8Gtd9+ArZjYMlSrNSREotEYAiKqpmMhoqoq1WqVilrDKTtRMAl5XZR0WLN+A63tLajoVASNZC7LmaGLdK4ewEpn8Zol9MIkjfIi69euRq0XWEplKZkN/njsJfoSLeQqNUJ5cPa1oIU0VnS300hJrHzk2wSu7iOUc1H0qNSmiiSUIJqkE//bx6keHab2xEMsvbQf5AATj99ASTNRXD2EKNP29eepf3YP1vg5Zv/p3dj1Nax7+r+Y/N/3QixOMBZENkzGfvIVzMhtmOIcTleNar6Hnk9/msk3f4q178fos2VOXX6K9OMPMvnovUz948dZ3/NZgt/5BTgWeHjrRoqnD/Hs2+fp8TlYGY7THI4ytTTH8LlLuLtc5K0qUs3Fvslp1iRitHQ2MTqXomtlL4vJNItlmdHzZ5gv6cwtZnjp4Fv4vREkQ2CusEjBEHF4YsiCRpOzk9bWOum8n7Kt0+RrpcnvYkVbNyfOFRBdK1m9diWLswXWDK5kIaWRr1hUFsfxOn1IdoUV/StobesiFogwdmaYmYqEIWgIqkJfZzPZcoUrI2lWtUe5dkuUdw6fRHEIDB9dYKDD8d829H/ERv7Vrz72qCjq2IITbJBRMGhQ10RU1SAe8BNrcdDsjdO7wkVLLMbEfInx8TSmEEU2LcqmgWSa6Aos5WpIXoXx2SW8Xg92QwNJQtcMwhGRclnFI4uYqopgxrAdArViDUVxYJkGiiJTLJmEQ37K5SrBoJ+62kDXVaJeD6YhADahsAvN1lhOVwl7vQTkKpbgQhJlSg6bV44t88c3zjM6up8XfvF9fvXjJ0lnPdghnUxOQjCqNMfctPQHERs1ykUVQfHilBzUizUGV3Ywm1xiZKZGwAfdrSsI+gwOnczRvyHElYsFcnqd1U0OilYVvWYRjvrI5jQkt4XH6WJ9bx8jC/MIVRlZFnH53AhWDbVhoVsSxWKJaDiCT69hKS4GB6Js7Gvjued/wtYN1+JtFljdvpbnnt7Pr14bZmj8Iqt71zIymqZhGNimiaKo+Bw+bElm7EoWd9BBWdd46tlRarbOvbddyz9943nyVR9vnhziqnWbkPwibx/Zz4kTf+qgfu8dH2ffqVO4wyYfe/AONgwkKKg6IyNJLFtA1Z0obhmXS+HC+WE8kRBbr97ID771NM+/M0RbopNrdq3iyqUC+bxFrpTE1CMYtpP+QT99PS0sTFcwbQuQKGR1ymWZodFx3G4vVR1CPidtPid1zcIX8jPQt4Zjo+NcGD7H1m07uG/vLs6NvsZD7/kwObvI668fIDu7zPD4HD5ZwFAUmoLtuNwWlyczaJaM7jTxhxKcOHqGWNBLoZBBEmVs20I3DCzbxiFLuDweBNlEtEXcriC2WqLukMjkK9hCg6BH58T5ObqjUSRfCFMtsL21n0plgWAkTKUs051YyWS2imBVmEkXuOu6LRw5epRPvuuDvD11nIF4P1d3d9J7y18hP/8LEu/5W2K37UD9wfcoyn7M63ahnnsL298METCGsjR/8JNUXvwyITykazrx3XeRefPnpG0XTaZB59//F9Nfu5+CP4TPFhmazuBUxwm5Bwh87Du0W3O4tQU8mhtLsoj0raTuSRFKJhhYtx7h+vtY+tXnsRxRKraMUKmgyQq1gJfw+j0Eb7+H+tNfwym1YN16LbeXdH526gDR+Hrm5y6zmG/Qt7IFUPBkVIYUHXGxTnhNC6lSgRXBJgy9QEZd5KrWVSQbBeIBPzmhQba4xJZVW5mfHCdrygx091GYTeMOO9gYjjOvz/PRvVdxZO4cG6MdlIwc74zMIedh9aoEG9f1ceTsJZq7epldWCTi93Hm0iTdm9dxYnwcSfdx8M00sqDhDjWztFxnOTOL29XD6OQ8l0cWsZ0iWjXElVSVA2/McfN1vXzg/e9iaXqOSFc/x0/9954v/4+A/F8e+/KjTkVEFEXARBQFREFAFAVM3aCk17hmk4Jlq3SGQ8yn0iwuV1ixKkEun2Xrzi5yUzm8fi9/eU8/5y7lyJdMdENCEBWCQReSaLGys5uBfgmrptG6she1UcfhN0nmVSRkBMXE5ZIRkfB4FZYzRfwhP0uZCpLDTdztwWVryG6JYr1GyBdgcE0b5WSO5GKdbTt70KsVBFMhX/ZgOaqIXouxWfjq95/l6//rPfzg0fdzfv95TKFAwCeTqSvo6Qx5Q6egihQLda65bgX5epGJqRwen5vVvTbtcYN77/oLXn9jFEtIk0s26F0T4FMf/xD79l+mkVYxZRnBApfiRHGB2+FkenaOnmiYrFnDIbjwyDJBt4dC0aBQ0Qh6ZaJOuDJTQfFYXLm8wIMf/jAvvPg275wa41vfGeHJF55iOSvR6tfQNRcXh5YgGEQyLdxOBVtQESQBraGjuARCATdut5N4zMdyTsXr8nDg+DTjWYlNgzFWtzWx5/odDLYluOqaG7kyO8/Pf/MHRCVGcrlOPVtlw9VNPPEf50i0+ak3VDTdgapCIu4itZQik/Ny6PTbzKV1btu7h4tnL9G/phOfv8GrB6bRxGY0u0hLxEutlGFj/yoCUhl/xGJ0tEiuKlPXCyhOPw3doqFpOBUP5YyNbtewLA9Xxi6jlR20xHopqTY/e+4Frh/cwL7Dh1jKZpEdCl/7zOc5NDZEqFjHJdnIfgeVus7ofJneHpHxqTytLV0U83ls28Tj8yCLDjRNRQIUQcbjcWOZNpqpgyAQ8LpRFIlUKYNqOTCw8ds2LiWAooAjm6SvcwC/x6SlPUy6UGO5YJBItNPR1M1MboqwGGFoZh634OXwxCKl2RwOy+SajjDB1TcSe98jUD1L+ZXfUIrJFBcmCfj7Kc/NgM/EGpti+49e5fy/3UcuaSHpUC5Doi9E6uwS/oZN51ee4+zn1uIwoqghJxf2z7PufTdQmB5FXZ4lGu5EW3c94q6/wnXze2m+8d0IwW6kgdtxnHma+me+yamHAjj5f6l7z2g9zvLu9zd95ullP7tqb+0taWury6qWLdvCveFuYxsbQoAAiWkJJeQFYkNCCD0hJKGamA7GBmyD3Jtk2ZKs3ncvz+5Pr9Pn/YDPOqx3nZPkrMWHk/l0r//Mf13z6Tcz13XNfXVSbCSJGD6+6mE0Oln3iX8lGs2T++pfo/iLmMeHsM+eor4uRVyO8tjBg1x92U6saplYVGdsZgYrrFI+PYuf6CBvT3HDhs0sTIyzXI8SWxqnNppDjIbpW9nL6aFzJGIh5vM16oGPFAsxMpNnaU8K2atxNFdk29oL+e2zr7NlVQeyLSGEwqzPKLw4Pk48pTJ4fIh4MsJcdpLC/CKiK+MIHhODPhvPW0FdgIE+nbtuW8PZU8fYsAGi0W5m5xbo729lcdonk25jupLjzguXs3nHUhTPZ2pmkmSry6O/20++yP8ckH/2gQceaOuI07RMIMBxXRRFQpMVBEnljut62NoaQ0wuwa4XmZ6RqVl1Vq3TOHO4RqOaZ8PGMEt7FPJzHmenSniBgKprVGo1JEUjGlUp1YuoRhdN12Vph0x3yqC7tZepkQVqpo/VsOnu6qJeLFKq2hjhBLWGiYSCKhlYzRqK5KAY8NY713N43yRmo0EqHKZJnVyhyaU713LyVA5RLaARwqzKv88ja0leOHyanz/2O37zg/s5cvIc4+NF6g2LN79rEytkn//1D5vpjBkcPHCWmCxjaDFqps+SzjSDgw5C2OLoyeO0xDsYmrCpSzYH9u3HtCzShoLrB7i+SLNeRWy6hEMqrRGV8VyZpKaz4FikFI1qw6OIhFn3QNNIqRILpopspGlb6vPIr3dz/CTMzlURRQFfjCMrFRbysGubQs4UkUwPPVxHEGx0TcZDw7EUVE2jWLLI5xs0GnVMP2DfviyVikcNh3RIYnYuz1Xb2/iPnz/B4RPHGR5yydswt1gm1iKg6g6zBQdJtjhzroEo6/gB+JiIos311++it7+Fk8cLlPMB4yPnaF3WQf/SNkLVBd7z7ouYnZ2kkA2h+Ab1+UVUr4BkmLzrzj/l3pvWcfGlW9n32kHEQEcJbLqWtGCEdAq5EqGITqFUpKWzhQ++91Ye/OVjrE+lePQ33+XA43tQO2L4pTqu5IBn8uK+l7jrikspBw2SqkrbkuWE5SJ9qRR7Tnm8997b2L9nD5dccD7zM5MEgoQgCASAoqr4vgPI+PhIooRhaLg2pBIhzo1MoxpxKvM5cvUK8bhG15rVjAyfZmVrhFi0n8l6iTXpfkwt4OFHfstA/0qWZNKEYyn8cp5Cw+WiSwYYSKZIN2P0XXcjQx/ZTswPmBurkon62NkG4/sPUr10gA57Bes/9QDYLvV9j+I6LqeGcmy6+Gq8rjDdt7+Tll2388qnrsM2urB9mYlFm9u+9RlGHv8p9SBGe9VDve1ecv9wM5nxPah7noDjjxK89jBm3kd+x/1I37wVq6JhxQwEYZ54PYOUCLHy099j9KG3M7//ILMNi4ojYahN6m6GpW/7J9ZcPMDRHz9ELJ2hsDhFvM1jfEKjbo0jmTEOZYvcsGsjB44cJeXEqc01OOvaGNEkU8UKY3OzSHqEWNggVyjQ2dvBVDZLsjPFKkPn2OgEHXoGVZRYs6GDwdNFBuIyK9cnGR/N0pHqIhSVyaQyOE2PllQ7vi/Q0tHC+MkcesbAqZcwhDztPd0cPzRKZ28fuaLI4Mg8i4s+07N5lqzQcZpxvvW3d3Ny5BS2UuC3z4xhJNPseyZLW1eM0cn6/xyQ//3ff+YBUTRRdQXPcVE0A7PRxHUcXFdEckw2tybIUUG3bGZrLo2mQjLskwwbbNqQwBRBb2gUApeoHiEZFVm5rANV8vAsh1y5gRqJceLcHEMTEkcHZ4kldB55/AzxnhjVqovliFQqZUJhGQQV07GQRQddARkTJaKDILO4aLFurcHQaINIu83kRMA1u9oBDb9gUqrNU7JCEHhEwirFUo2mIJBJNCkuLOWfn32c3GCeQFMRUirekEnZ8vjJw4Ns2RBFUj3GcwKLzQqJdJSQuciy9GoODZ3kom1dhCQbUysyPeni2CqiqDBRFtnZ0crgYg5PgZXLl9Gwqth2gzhxFp060UBlzq7i+AL1fA3FczADn76ExnS+Tt0qgqWjyzq2LRGJyVx+WYrRkyZ6uMnnP3gbv3tpnGqjjk07UlDHMX2McAjTcQkED0G1QRQR5ABVd3BsjUAzUPFRpTiL9Qp7Xq/yhQ/fyYe+/mtOzTfwzTgVq4TkybiCw3RW5dCpSXS7hVqQx3VBCCR0Q2DFig5EweW3j72GZtQpGS5rYkny2Xn2HB6ipMj89OHjnDtRw4g3mVws8Ln7/5SDrx3gtWGbU9Pz9Hem+M53fkq15pMIw5uv2k77kjC+0KR/TZxYJIxmKPT2beH1fT/lIzf+GUdGjjJ26iwvje4hpKQoqSKN2TyJcJiP3vdBfv36XjYkeihOl9DVPHeuWM3RxQbl8Rw//NXv2LTpPDRVZW4xh2EY1OtVVEOjYdkQ+NhOgCLLGKqKZdv4vkhbS4ihsRlSegjfLJHpbaEzrdI9W6d7bZwj40VmzEkq8yUGCHNu+Ai1tiS5uQWEsE9LJMGy3jCVUo3RqSa392xk6RUXcfr5f6cz2sWILWNHaqhKgnFpkbaYgDi7FL3H4uj9n6Hv9o9w5KGPM6cuZ9PmC+l813UMf++fGXnxl7RdeivKvucw5Rq5epKrbr6M3X/7ZWLhOJVApTPZQviCayj97kEQLBZCOk0vSl2pEp6fJbykH/Pyd9B6zX10X3wb2pUfoOOamwhdeDeHv3YFyVKEou/g1xuk9BCu4OF6YeI7t3Lmbx7g8r/7WxbP7OPM2RkSLd1IWhGprjHopvn6R+/gly/uITe/SKxnCeFUFFOsM16vgSvQ19vNxNgkbW1dqKKAZxVp7+hmfq7J7EIJT4qxYlUrTnmGsmsx3ZxjsuRTd6Os3djP8akxypV2+rpCTE8XWZgv0dO/nOn8BLquUGiYrF+3FMnppLevlUTU4KnnDlCq2Uhqikq1wWLeQ5BTnB2u0brCYX5qglN7oatjAIwpbrtzFY/8aoxK3f2fU+yUZInrr9jGyqjEVTsHsIMmYeK8ZVML9y5J0x9TKdg58tML1IwIkcBi4/oUBw8X2Li1nVg6Qm/7MspBhZAf0B5xUA2JWmmWjkSaminRND1KxQCnaiH4da5dP8D+43MoYZnhoSqG28SIxiiWPUYXPSKiQM01EP2AwANFbiEsKpSLTdJakqNHyoQEl9KsTEGF48dmWNWtUZNMzs0LXLhuKYqiICoOhgaGbRKPtmEygVCUCCIJGkoAtSZlv868WaWnrYtnn6ph2j7bzkviFKFaNBmrCfzy5cMs7whxZmqe44NlliQyLMvEoWFhywrtms+hxQUQwsi+xtnsNPPFJoWmzunFEp4botgwadEiOIGInoyxc3MXnWGFklVDlxQSmTAJuUF2sYYvm0RSMD6a44LzNW65agf3f+sxSlULXwzhuAsopoFthFmYr7G+pw+z6VAtB9iOj+V4+EEMz/GJaw5qWME0SzhNmRU9IVZe9TE6Q0tIuDqKXEILRGRdwKxAoNbZtqqfZIvIhZt6aEnHMXSVZtNnYX6OUAg+8bGP8qEP3Ia1EPDQ5z+FL8Ptb9mBZ0pUqx6f//DbKXsGsXiYd/3V95m0QwRNCT1b4IsP/ZrMyh4++45bWdbjEU7FOXz4NO0JAy0QGZ/JMjQ5xx3XbmRiDsar4ygqDC1M8+n3f4YDx85x7tQ8ttHCeKXGr594AhpVQn6DXxw+zG+yTV4+PEdHQ+beK9bx57ddR9A0+djffZoV6zvxBBFDiyDJOo7lERI1ZF1G8ANkBDRRobU9zsxMiUg0RKjV4Ey9wab2bty6jNK/jLIjohsiSzIDrGjLMC2XsESVDiNEazLMJjlJrVLCmysSEQw+umYXCaNG5up3sXjiCGPlKvXcPG7OwqsVCbkZdDFF13lpvviJB9C7uhh58XvUw11oYo1w/wrK+19lseJiFaI0iwucawzTnHGJNacpywErujWOz88jN4o0mxYSszSkEBU5TYskExYE2kNL8Va1QbtO8x9vpvK3V1K6/26an7yG05+4guD7X2LTx35NfnKOZjWAaJqqKVEsybSt2YIvxgjHJRb+7Rs8tucUfYleFkZHmC1WCKJxOsVRHn7saY6cXKB9+RqUqM6E1yCW6sCrWazq6ePo4FlW9Z/Ha4ePkuxcSjSUppSfw1V8BM1geWuYqew0hhjlxIlhijmBNkGmNS6we+9phiaKNBszzC6UWZEMQaHMqcFReqM9OIFKezRNBImBFVFOD44xX7FR9CRziz4TkzVKpoSqxXHqM7z77jaa8zNISpol6+Mkuuax62mGjs3wD5+45b/P0P8/vJF/41+++MA6zWTZqgSD8yKNBih+kT1TDUYXRep2kUvP28b2HW24ix53bN/IdCHPPTv7uWpnP4X5cWqNKNElGmLdp7OtleOHxxjMywzn54krgBzCbdZQdQ1HEDg91eBr79nIWM6kWmhi44PvoEXiOFaDrT3tjJWaKI6Mp/ng6Hh+nhYVrt6SoJKzWDOwgv2LTbbZDYRElP1jVaxpl96lFrnFJqbrE1Z8kmEJWZWx7TqCpFGrN2kKPlLDoauzi8V6BQeXRr2BIHpcd+Mqzp0eYvPmdUzNLlJv6ixb2cLE5CLjEx6YFpkWjx07tzBXswhmKpSbFpIiEYoqaJJHs+4QjYYxLZNYPEHTtAgkFbPaQDFCVBoWY/kmW+MCpyoesYzJii6VuUqIFb0eXT1xhs9Uqdc90A2efmkMTwBVUbE9FwmRhuehWw5blvZyYmwIWTHA9wkbGvgBXuBTrZiEoyqBIOJ6IMkKouti+yJ5xyKTCWGILo4DtuyhxyOotoyW1skOjuEHMmWzRq1WZeWqTrxmHdN1UWMCT/3ycb72ZzcxPTtJZXaevc/NMFOqkPIkXh45jVdoUjUdutpbiEVUEEMYks756zu4eudO9gw+w8f//O85eOI5Tp7Lsmagh7C+hNm5Als2rUP2mtx47S08vedZqmaVlnQLs9k5SvkmtXqDy9cmKZULnM3W+Nx73skzp0YQnRqvv5hlma6xXDHoiagsVucw1Tr/8c2H6U4mmZwrosg2N956DS+/vJdINEYgiAiiSCoao1SuUDeb6KpKPB2hubCI0ZoiHdGZdJtMnspSFgLWRFIUcvOcv/k8Xjr8OmoihapGSYYNtITEmXMTvGnnAJWSRGuLRSy0irIxT23oHKIUIvAhbGgogoAtqORnFmjd+Wayx59FSsRorc4xMjpLNRdly/tv5OQPfsZ8voBlKXRIbWy4515OPPo0V37/txz87F8w7dSYmgtIJRUK2QbdN74ZDu1BCweIokIsZuL6neg3fobq5++kgkZVzrCgm+QVlUhJpGq4tC5dhdOdQ5maAMdFVmUiQo1SExIbzqf52NcIVnZx6/nrOD2+DzfcgaDGMWyTlrYEC45NKBBIxuIkYxEWF3KMjU/Rt6yL8bk5wvEoE0fHWLVmGbblMzk1iR6OErFCVMQpUonllBcHYEg6pQAAIABJREFUaUkvR2tvJfA86pUis9kqVVdGCSn0tiQ4NXSSC9w2Et1Rnj94jpZWjVi8lf6eNqzA5rmXDlK0U5wdmqZeb+LbAivWt7IwOcb77tnKRetTGJLM+KxDa4fM5pU9DA7PUK816elu4dDB1zg+/Efaj1wQhG5BEF4QBOG0IAinBEH40Bv6A4IgTP8f49/+L8/fCIIwLAjCOUEQrv6vYtTKTYLOACMUJxaYKG6d1lSKtK6SjpeZrmR45ug5Tg0fpFcNM3ZqlO1Rg3hM4rnHXmP1mq2k9UUa8y6pNgPBqJJo7yZsuKzqjeE7Io7vYAcSDjpi3eK9l2sIgYiu+IgoxCMaKzMabq3Mmt5W5mdn0EWb/k4NRAPNyrG6N8yO8yJs6Erx7jcNcMeWXm6JqLz/bTfj+w6txTrtGwz6o93ooSjVUpN4KEEmkQJkTEsBfNIJDceRePst28iVprFskdpiGF8AX7XY/cQUZ8c1nnrhLJ7nYIg2hpRHkX3CehRfFjh4wuKFlw6yY32Sc0WH8/t7iEsWIcnGdV30cArLslEVEcFroIsBQuChRyLUag3chklckKiIMoauE0vIHDxqYZdlhsclXts/R76mUmrqjI5UkREIyRKeZaEJIoLno4kyjiLx2vQYshGnaTmEw2F8QUSQFTxk4okUuXyNatWmaYLX8AgCgURM5JMfv57uZVFsIU2uaVGzDfCqtCQyzA2NIQuwY3uGt959Ne+45xYmzk2CrDExschrL7/ME7v3MzRZ4hM/eIyns7BhUx9y1COW0cCMI6iwZkMa12tSyOexLI9aYDE7OYtSGqFmxxibOMv5Gy9hWW8bjzw9yNMvH6Fh6jz75KtEU+1899s/hJrPBZsu4qLtl/H03qOcGlsk0x1jeHoB32xhoepy/1e/x4t7XsfUUtz0zuvRV4U5qs8T3tHKQCLGpvNa2HXFzRw4nWV5R4Kdmzfy4wcfpHdJF6brIDgefhBQrdeQJBAQqdUadLa1UY+Cb5skOlLEyiZSW5i5QoXB4gJZp8HPnvgdbijMfLFCbnYGJSxwcqzIypW9PHNgnvMFgQvv+gbLP/Z+2pZ3ojQUrGaFeq1ErdrAQaWanyasKBBJM9AmMDvnkBIlAiPE+Hwe8/ABRkbPILoaYqNBpWUS7BA3/PTL/PKyHhYrKmMVyMRVDFln4/plaDWRhg6uD4EtY3qdyNfdiz35As0WnQIJNC1PVFTJOBaFNp+WapGFnz9I/JLPUm84xKUOBu76OMvv3033LTeT2/1dkv/6OtNjEyycGGXXyhs4s5DFcGYJaTquoTE8lsWjSUerwWx2hIGVK0jEO7B9n5pp0SzVMZsOTq3G1OQkPb0raE23UAgWsUpxVrbobLxwBXtHTtKcKDJdXEB2VBZrVS7ZegGr2npxRYWeDeuRUxKLLdDVk2HSd5Eln0PHT/IvP3iJQjXBsvYIm1enWd2d4WMf3MVF/Qnec/cl/PZXLyAoBiWrxAVbV3L65Cxf+d5zREIZQkaDqamA7edv+K/Q+d8HOeACHwmCYA2wA7hPEIQ1b5z72h+Of3sD4muAu4C1wDXAvwmCIP1nAQxDoCvRyp7jR7lgk8gH3rad/gGBrSvaee8Ht/C523rZfWKeltR2Dk2ME+pskuwd4FR+lC+/OMkNH3yGzEqdkOjTkUmxkHc5OSqyc6POlZvTZLo83JpNJBRG8Er87fuv5dWDZQ6dmmTsXB5JaXL5qj5Wp5KYXpjRGYexkodlOuy8sJ/JeYcP3X0pf3vhhdzct4XstIzSrTM3M0b3ZoOXxw9wx5Y1XH1lH+VZn5dGSyxYDYJQmILlMVWuIysOpmmiqjpmxeXC1RnsbBbqIXoSMSKRJsViwMJ8GMuvE5FUmmUH1w5o2gLzRYOqpeH4DmoQ0JvsYCZrU5gWuag/zujiFDVZodAQCIcSCL6F2XSREBB9h5guk45GmM3XQJBY0hrjvNaAo4UGhqkyP6oTlURmPAu7ZhIICppQQxFNbFfClU08QcJFpOmKVKyAum8hIxHSYiyUmxjR3xeHTcumZprULA/HD1A1jUbdQRJDmIHNoumRKzXpaFHRPJ/1WxMsW9ZDVHXpjCeYL86ysk3m8it7GDt7lldf3MfZ40e4/spNRMMuTsMjX/W49Z7rWHHBetRGmJsvWsHw5Bhpt5MlvWl2ruti6/IUx47lsa0wkVCSdDKMZbvsuuxSIr0R9j49yuce+iaHT79CVMxQmK/QCGQqNR9VjfHNB39MvWHjxUQ8LeChB7+PgMzWtcswZ6p4TivV0TNozjy9a/v5ly9/Aj+wkMILrFvTwvqgn8d2n2FstsHJfU06IjV2DCQxTZMgMAikFHVHwLEsZAQcz6Vcr6EbMqZjIwoy+blF5qYLDES6qTg+C4NZSk4dw9WplH2kgoGltpEri8zO1tGECK8dOkrenOHcq3nuu/hqdnzvKYTIIM+8exf2k3ku/thNKKKLazcxPYdK0yYdkRGdOul0mi7d5oVXzzJRdonqIdb2L+WJXzyEpKkMD05z3vtuZOrhx3j8/ndi5WrIqQhEGvS3Juk0YmjhMqEghzf6KOWah2qnkHQVPRSmlu6BQz8hGWiEjCrtoQyyDylDZn2onbphEFm9EZ0wa768j84HvoVXOMbsF24l2PNzgiOHOfzhu7jir39E999/l54LV3D56jgNqZv8fJHJ+UWWx7s577zz8B2PSFjj8JFXEeU6k9OLaFoIt2pRMU2mFksERgKMGMdOD9PbtRRf1RifyvHMU6doa+kk0ZLm5tYONmzuoFMQ2bPvJfacOoFvK0hzAq860xw7nWW4vEBpHAakOLfs3MxXH7ib++5YQUdLg80bVnD1tWs5+NoxKnULLazzJ/ddS8PzWJLu5HcvvUA41s6lFywjt1BiYKCLRDuMjeT+eCAPgmA2CILDb6yrwBmg6z+x3AT8LAgCKwiCMX4/hHn7fxajUA4Yyg1z3daNjE4XSapz6HmBdW0G//T1Q+ydGOS6rSmChSJiI04XA5w7PoiZb+GTb9/MWzd4nD5gs+f4LJ/83n527y0iSbN0JzqIhh3WdfSRiKtU6g1sT+VLDz5DbKnAvz6Z45prVjCwrgNBqdPe14pvV6m6Dk1ANxJ864cHWJewWRqy2T95jpJXoKsvyjMvHmTCMglHHNwpj1+fOsqBUYv5kkm9WqVZDhCdBrVak2pTZDprEs/EETSBLiXMsclFHjk+S0EOCOketqQTDnsEmPSmWrh4SwfpVtjYCoKuI1MlZETwfZeGF2ZwvoAiybx06AyLvosshVmYcbAaBqVig/npKg1HIF+AxbrMfK2Bb1t0tyYJCTbtCZ3XFxpYtkjT8AiwQNOIKw6+pBG44ETjxGQFL+bQaiQQ/DqKLIDVJGZAJKzgBD6uVeaCTUsxa2VUXSYIBCJaGENo4uPRqDuIiopqCDSbLm1xFVnTec99PybevYQXdp+gc6nOQEYgO5mnJRNmoeGzqn0LDbuNataimC8xsTjOqkwPD33+03zinjvAVnjxyF58wQXfIhnTkZ0ZehJx3PJRLt2+mZtWp/jI+Wu5szfBh268grfesBy/PMq3fzLOn/7VNTQr0B5fhmwV+Pyn76DWrKFEFORYnFy+QUsmQTq5gqHRQ/Su6mDiZJ5oNIrhK1i4HLM8rtl2MWMj4zy+5xCnBycwFxSGCmWOVs/QuXUprzQm2J89Sv+2zbx+apj73v8XjE1PoBsKYgCGpmNL4DsumqYhoKCKEkpIxwtgy7qN7D13EL1Zx+2KkJENBrMTlAUJP6qSSMeYm5hizao+mkGDZZ0xYmKMv/7Kl2m74Xpe+/Jf8NKXPk/djbD/wOOQ3kWlVKVT10AvYzY9CoHBwVKWc88/zYwe4pXFPG39Kzg6M8Py3gzjMwUqtTpvefdb+cFnH2C2XKFQieDZVdRlfXRG+0irHZz/9S/Qvela8uhY01P0h+Io8ToyHrYIHH8KsapTkzXiKFhlk3QmRDy6ElmL0/2+r6GsbKP2D3+C/+3PoTmTiIPTVJf0kG2YaEs1Mu1xXv/W14hVS7hNn5tvvpd1PWUmykXWtXVy1ZWrKOQnyE4tcGxigbFcneUDa3BNgXo1x2JFZsn6pVjRGLWSxavP72d0NuDY4Qk60yHOleZo7VhNtVHg2MQ5zk0uMnFyjnJIxVZF1vauZDY/waRdRwsMlqZbuW3nFnadl6HVFEmJMrnsPEWzzPhcwPTgXl49MExXW4hULI7o55FtSMY8TuXKmLaC7ixgWRKmX8NzIxSnxmnrWfnf5fj/t2KnIAi9wCZg/xvS+wVBOC4IwoOCICTf0LqAqT+wZfl/AL8gCO8RBOF1QRBeVxSfSCVNazTCFmUNcTJ88L0XsW5TmiVpuPnWq5kq1Dg0M8GMX+VEdZyRXJmetM+KZREKdpORE/Pcu/V8QvU4Ed2nK2XT55gk5mI8+eIgO9YtwyzYhELQsA3GpxN0dcssaa1Rys7ymwML/ObAabRUFMVzUD3ImQVMKcIHruvn4GCON+3aycScSf5MAScdZrJQ5tiwxfMTM+w77XFyxqTpKaiRNOVmnVAiSc20qFarRDNhKDeYyxdp7e1BLDdRw128/U0rOTdSIyYrGEqSrrBPi+9w45Ze/vLWbbz9tmtZ222QFBSa1QZLUhIDbToXb+wE3yGWimAVArKORCiRpOEV8P0IQgDJcJQlcY9/+uD1VASZjauXElE81i8JY9eqBEKIsC7RdE0anojp2DiBT4CIF0gkBJOiZRLydWrVEkY0RiAKxONRQrKA5IMuCURUhdJcnuVdraiCD6JIpdHEkTRkfAhUVFXFCeoYuk6zIYOssnx1ht2PvQaiQn5ynpsvHqAzE2VkdoG+5Z386tAZEskQ2bkKq5f3IJZlvMDnmz/5FuNli8CVmZ9doH15k7MTx+lbFuKHP/8Ov/j1cb79q1cYWcxhx5M8Wh3nH1/NkkifZtfSNbQt6eXdl6zGOTnP8JyEkOriM1/9Mg99/1E+d+elXNQVoriYp6W7nzlLZHp2lJiQpjgzx7e/91csiTSIdCWwcfn6p/6K3x0+yk3X7+I3j+7myx96B/nyGQ6ezjIZUXnsycOImTA3XLqDD3/sI6zZeCUf+sDHOXVmhHAohqxKeH5ArVwipKn4vk+AhywLlMtlqpUmzWKZHeetB9dDFEWKpQabNm5E8R1mJ8coFmZJJsJMTg5TL5SICBp+Q2FZr8JTn/o4U0cOMzI/zayvYplTVNRW2m+7ifbVm0kUiyRMG90IEIs2Zx49zHWffpCNNrxwOM9d599F/z1X8Ja3vo1oWyu/ePxhJooiU5ZPSFAxPAHqKr2XXsO2D/8FL37oPsTJIsv+8nu4iRRCUsGWu7Fvuw/1po8hRpvUcoNE3RjhaAo13obRuR7pznej//kXyf/87djPP0ouJONKNQJjNXJjhHhVoS0Q8CopLNlBrS/SsFIs/vYJJp6b4sQRkcu2bMTSTF5+7hDReAt6Qqa7vYuLL9zCsTOnyc6WSKRbMHSFsCixMFomV8nTNrAUwcyzfGM/49lRDCXJeHYeLIlNa5ZRyNl0p9rp6O7DbVZp74zT17sC3aoxI1honRnGjhzn3NlhHp47xvGZKbyQSLQaUCxWGCnIvHgox2hB4+zwImazg737j/Hyy1ma8wJhQ6e9fy2vHB2mVBZY0pbmqiu3UzWzf3yQC4IQAR4BPhwEQQX4d2A5cB4wC3zlvx0VCILg20EQbA2CYKvvidRNi3/8xitY5+d4dPdx9rz2OsfHq1x1/XnsO/MqKzuXEC63smxHH02lxnhxhvFcjbOHxrig5yLu3b6aHz63j3R3g4kFm4/euIPtKzZw8cBW7rhmBa8dOc3AqiRO1SWi1bAbAeu6YSIrsGvNctpUC7lhko55CL5GToqyLEizeQP8x7PzJDplnjv1ApnuGFvWd3GVupO6medt121ny4VdbFySBrOI5pmYZoWWiIHo2iztaiMd0/GpE5MNkk0Yyp/j2vNbmM9PMzdTJZNxIKijek1u39VJ6xKVvXtPElRh8NQELbqLKIIalZjONfBjCi8fzVKxfWTRo9FoIDplrEaRVCqKoDicf8lqqg2bu7YsY7hu8eblSfadGkbAA0SGppuYroLTsKlWHZAEkECWRQTRJwg8nKaF5xu06UVu2rSaaqkOgUShXMMXZERFJQgCGjWHWCLD0GCWZKqVaqmOJCnIoowoiuiagGs3SMbiKLJLKFTHsywWRz0aZZ87bl/PXNZlasojl2sSkjRmxrIUx84xVyhwwXV9WHKTCy7cxNBcjomiyU9+t5vTI1lu37KDT917C9/4m7fygbfeTmH0BY4f/Apf+Oy7OTY2zL4zo4RFhWsuH+ArP38NpdtjxnmZrg19NOI2P/qzK2idGOQnn/8aX/i7j3LRJTspVXO0p3VC5QVqk2cRvICh8Qla2tt5+JFfMDwzw3WbVnDpmmU8/sTz9KVCPPbEHu55980sOj7Th4sMrNrGxHwBIdKku3M589kFejqWspjPEdJ1Lr1kF4HrYTXN33+tqCqB79NsWpi2iyiKGJqKIEgkjHYmx/OMTSwyV6gBMk69zkBPB/1dHdyw8QJkJ6DRcKmaAslwB2cnF1ByCyzYdaabHnM1l5Lp0KxATGwy+9JpEpfdybZvjJB5+6XYZ/ezcc0m+s5fCsYaHvjVP5MrnyI8ILD73x5HsVQ6lwywWG8QjbUj1GoURR/PEtn13vdQq4/w1P3vQXSqnJmYIv+VP0PY8jYi936Dlrd+ltjQK/DLLxHqvo3EB59i4bp3EU0nUK66F+X891F74fuUvv5e7LLCbLZJtVInv5iD/KvMNudx3CoIMguZGCuTnWz47LfxO1TW//WX6L723axZ1UHfqrV4FZmcq5CJtqBLOtPFErufew25qSIFLqePDzEzk0NRJOyGRHfbOrZuupUtq3sw89OsX7kN1bARXRtDFHh13xSTgcj+mRynzmUJmjKFXB5NC9ixYQMhKcroyDTLN6/HjIRJ9rTQtrQPIbdApilz2coYyWQSp+zSk2ggJKo8/+rrHDlrUVZFyuYiE0Nl9r96gku2LUHXmhw6Osa+A2cYOvNHTK28AXHlDYj/OAiCR98A8XwQBF4QBD7wHf7v9Mk00P0H9iVvaP+vR1gTGG42yBrw1DdnWL0jCv5ypGSJieECg2dqxDvAblaY2nMYKd9FPGxyybUbWZ7oI8cET47Nk5UcNkfj9EZ99MwiX3rqIBf+ww/48UsLtGVaqVRsbMknMGKUHY/DpxvUFwr88uURTpcSeKEYC4segWaRlB1Wb3AojSiEDIvdZ07QllhGpx9h3szzred2s62/hyd/9wJLFn0WGnUcI4LrQEtSxzZdLAfGpudxkJD9BLFMwJ9d0s2V8QyqEkLzYZ1l8qcXtWA2BC5s7+TZMzblhoXRZyBEGiRborS2aGipCG2uw/ve8ibq0xU0wWFZR5KOqIGfNACR9//FZeTmqgSCz/HTY3R0NVkMxenLC5xp2tTcgJawjI9Ipi1JqVbHMwN0JYYs+viui+vZGLqKKvkoMQlD9RmfFvjhsTOEtRC1mokSjpOvWtSaNkginT2tHD52Dl/SGBmdQdcNFERkz8V2PQJsDF2hWWmiSiFkP0RYdIiGCrhCDDtwmGnU+c3hkxi6QsSQmbM1lnYtoZ5zGR2cAz/g5eefZt3yVjoiYVZkYP2yCHn7LILoc2Zwgu8+9hCdS9fy8589wtU7t/HVv/kY3ZkWzo1M8PLr01SaMYq08MWvlXnipdN850en+NnBl7EHlrHy0qt46RePETK6uOa6O/Ecl/auFlZuW0dbS4Z0z0rmK01S6ThNO+CxIyfYO3mO8dJZwqJP19IE0vw8zz3+Iz72wT/n0OljeLU4sSXdTJ0ZYmp2hs5UFMud4AP3vY9zZ04gECAGIrquI8sykiSi6BqeH+C6LqosEgrplGtVZF3BV6DmWZyZWGByJk82u8DcYoVjRw6ws6uXy9uXYzRsZjFZ3dWNmggxkp0mO5+n0ZSolguUF2QWXnkEwRpn5kffZOjT15Pc/Odc9K05Wu66m9Uf+ASPvLkL/9Hv8PDuaTpv/RPGTzzN/uefRZUV6naVsObTkW7DshzklMbP/9d9TOx+hnjLUhY8gRWZdtJrVhBQpf6vNzH97T+B/DEwcxR2343/7bvJDD2OfcsX8MpHqf/wA5i5SQRTQoll0OIm6cDCDPnY2Vmi136EUqROztbpd2SkW2/guffcw+Tn7qfWmeLUf9zKe6+/jr978N/w0Nmxdi17h15ltFLHKzRo1zoZmcvR3RZn23mbsR2FXK1IvNUi8Ob493/5Fy7avp2ORBvnxo9w8GQWPaJzdGyBM/OLTNtJamELIxEQi4Q4engI2xQYbkzQkWrBq7uMzuYIKR2sbO3jZ08+TxOZw4U833lqiNGzJTZvCXjhQBO7qiAIFus2dXD2tEez2uSyy/vZvHkFxbkKkmjyyqFhamYMI+L98UAuCIIAfA84EwTBV/9A7/iDy24BTr6xfgy4SxAETRCEPqAfOPCfxUikVG7ftYOuDBydC3h+v8CEk8Wqp+ntiKPJZQwlRMfmFImOXlyxQkxYwvHDeylp4FShVGqScWD9+ijbNis4xTTzwSx9PSrdHZCbX6BesehKy8QJ0BIF9CDGSzmL1lCKJUYJr1pFsCyCqofgCpwebLB9mcJb71rPbVu2MDIxTkRPEnOT9PUIvDoh84t9TX45WSTuu7RZdQLPRVEFlJCC7hmIqkxaUgkWSwR+jIgj0BcSaa9n+dMdy7HiPpXZKF0Rjc6lGVSxxKZQN+sSq+np7mcxKOHULLauNKi5JtMLNrmahxIPYVke07kahmAR1XxOHBqjJwF1x0UTVHw7wdOvHeVszUQsVvEaDqM1n1DQoCUo0hfSCLfECbsNNixfSs4KiDc9StUGCB6aLVMyPRRNJaHHaToWqijjmk0MXSYqRZC8Bm3tEXwFbMVHUxRUEQLBx/FkTNPGMlXsQKLhOTQEj/mmSdEMKJs64VDAT35xgu0D7aQlCUH7fWdPVyLC7OwsYLEw02Quu8im85ZTLNpUxSbZEYOT8zaz2Sb7zo1T12FyrMajz+ymJdHBso3buPejn2FsKo+mRhCocfx4hQcfPUQy0813H36BVEgjcGzOHnmdlu4Y06LBN7/796zr0NnU0s5LJ4fQI7//acgvzhFSfaLpKKYjsyQTplEu0pVeA50dPP3MKbLji9x4/t1sW9PL/GwFUWnQyA6ipTrZuH4tE2OnUfQ2JooV1MB7A8w2MgGyLIMgEgQekUgMSZIQZRVZMpDxac2kUAWFFr2HUNQhqJss1lxWRuKsjrTRqqqogoyalGiPikxU52iWNGKqhRlIjJfqlJsSsmpQGJ/ENkVGytP4kRD6Tz8BxYO0r72NgCyhzvMptPZjyiayY1NY0Ols15geP4emGDSqDvlKjXimA298mFg0xIIo44YDGlWXXLOMteXNOI9/hUJoPZaSxl+QMG0LZTHGYkRFPlNCO/k4lfIUrirjVXUaiosu6GCLqHqEhAzaxBjKmgtJ52bpCCJoN9zC7k/dTsubNtLMq2gv7mXNhe/i1KkpVCnM/FSWhXqenmgXhckGmc4ERXsGDQNNVjjw6lm0hEd2JEdCi3J6dI6M4TCed5ier6B6cTJGiIjeilmWQAzYuj7GQtZGbxqoIYmuzhRyoDA/McPB4SksQUKPtNGZ0hgpz7FhSQur2w0GWluYmy9jLjgEYoSbLh/gmkvWs27AoC2mcc91S7jkgm5qlRlOvD5GTbTpWLoct+4hahLD48IfD+TATuBtwGX/R6vhFwVBOCEIwnHgUuAvAYIgOAX8AjgNPAncFwTBf/poaVY8vPooX37HBbznhgia4fCTZ0dobw3oWKpwy45LKBamqDkiyVCDbNXnwuvXosV7GFqY5OjZKdLLo+xaHcewA97SvpHHnjrK2y7ZykCmlUtWhPFl8MMOt2zpQkyo7EhGKCsVnFqcCadCXQ1xdW8HXbE2bt6ksH1dOw/csZ4fvbZArD6LIDi8KbOT37z6DHPaArdvupLiRB4xbCBKHsvaO3jPPdu4dEOK2fGARl1itrTANRuWE5Z97r/7anyvxGSkxr5mg+XbrubQyAjlhkE2JqPUm4ydOcuq3h5o2tSyZ6hNzrBhxUo2bezAykqsXNvFky+8QqxdoFzzibbGcSQfxQjhkeDV18dA0pAFm0ajQrXmMD7n8v3nXsH1DJJhhWa5yoQZwkimiSf4/T7mgsTrp4boSSRoahBSNRRVI1AF9JACskSpWsH2BEQVAtnDCcC0F4klYszNWwiCjuA6RFSRwHdRZBnXdYmFI3h+k4gh4pgeiiQjCAGtrS2AjyBL+ILK5HwBz1Ao1io0mi65UhVRF3FEmXDS4PBgGSm5ivmFAvWCyPIVKeKqwKHxJqcHiyxpXUEiEiUda+PAoZPceNP7aY+30dMTwqmDLMss71/Cc8/uo16tUqubuKJPNYhTqbjc/zef47kXTvLrVyze8cVf8qvhQT55903csrSHfaeOcMHAAJnudkq5IqvWthOOp2i1ZVavTHPu9BHae9McqjZ48ezrfPabP+HNa5JcsGY5otjJ8MwIY7NzbNy8nWKxyInDx9G1CILtEVdUHMcmHDJoNBposoLr2vi+D74LgU29XqdZsymVKowOTzLQuZbtF3RRzE1j1FRs1eZ4cZYtl/cwoMcxg1nee9t2HvrNbqLt2+lPCMSjAslUhFVXnE/27DlqDZOmZVKpVfE8D57/IdPf+iianaGjpYjuFjk822DoiSc4aeuItoVYKnPZVVcyVyxRFzTe/sF7GRmapyBIpFWHs8MjjOdNhIaO1tpBeWiWRmOBRqmIZ9UoSE2ahTJyTUJodSBiEO/aghJOIEcNUCQsu46mBYRDkDGi2IaCLbaQ/uSTRP/scQUQAAAgAElEQVTqHyksHmZF58WIZ8bJ9GWpHTqK1B/FwOa6pe14uo4ll8hEXWbn80RiGS560xYCucHMZIXLdm3mws3n8c63vZlV3RH+8oYd3PPOXezd/wKt7VHSbWEkXWV8Yoq1a2KkQmmGR7IYiQSzhRqaGiKsK0zODSP4aRZnciQTEaazw5wbPIO7WEYRp3ErEnMncqzpaOX2d1zG+csCnGaO5599jqf3zvHK0TrZXJFnXx5kek5nvOIzMljlyWemaO3v5pFfH6Oaa/zxQB4Ewd4gCIQgCDb8YathEARvC4Jg/Rv6jUEQzP6B53NBECwPgmAgCILd/+VNSCAYLvlpkUuuvIDV/5u69+yy7LDrdJ+dw9knnzqVY3d1dW6pg9QtybKik3CSbYzNABcud4ZwYQYYhlnDAjQY7LkMNnjdYYYBlgk2Y0ww2Ba2ZRtbVpY6qnN1deVTp8LJ+4Sd974vPOu+5iX+Es/6x98zJfHk/EF8X6a/3aRLwJHJSYYCHbOgsHB/gWu3r9K3JYySzuPvPEGhlGKkUKKwMMKrYp1HDh9mq+6gmyGLtT6xLyKKI3zu+S3+w7FhQkOjYOi8fdRiJA4pqQOe3+3TYJelOM/McIZPPHuZUTPN1283ybUVnt++wL59I5y0ZtkzW5x/s8Vj+zXuUWUmtB5ffel1Xr3V4vDJNDE2up5mrCgyMzvMj3/nW0SSxNdeaLKcmHzss9/lbl/n2qBBf7PDsUMzHDt5mJ3qHY4d3sfs7L3sm57AVAdUqjZZS0Hp27z/XQfJiwrFBGpbHXTdZKygIAk2E7N5EiFguGiRSVuoCGiKjGgq4PeRjBQ2BoNQYLPjk05pCF6IG0aYqQy+F5OkLfSgy4ceuZd+LwDXwXFDVMXAEMFIEixZQvIjRNGk1YnZ3Kkj6yGnTh7Bcx1UWYIoRBElPN9harqIQIgqyBAGGIpMp1VDkQVix0OOFGTBxPUTkkRBlNKEkYYn6MSRRy6lcP+pQ/zV33yLjh/x5Nsf5sr1O2RUg9/4pZ/k6Scf5Lkv/xVPvutxfv+P/47vXq3QiHLU7YCMJSCECZ1Wn3bXQRJ1VD0mm7EQlZi1bZHtPYd02kCQfQ7lW5zNxzw2Nsar12/z/EabXzz3Dh45dIxopUotdHDbHvVr24wdncWU27z/ofs4e3AaQ5Eo6xKBqvBDH/lxeo7Pe04dR+002d3s8O2XLxPqMYeOHacThzhBSCaXQZIEOp0WKdMgk04TRgGmaSJJAv1u6/8XSRQKBaYmZ1i8e4svfWWF0QNHETMJr1UHDJwWF6/eYU1ok8ke5TNfOM+Xnvssj7zjMWLV4choEcducfytZ7DXVsjk8pjpDLJust1sszNwSGVnSCSFe37tJYZmh7gvsfn9T3+axd0VarZHHMS0Wl267oCTjzzGL/zM/8nf/s23ePwDP4IsK2j1iCeeeIxY6tKMdklbBcy4jyEnSKVJnI0mAzmi07dBngExg7ZwGtN0yCk7mDJISUK2MIqUGUGZO476xM9jfPP3CP/nT8AXf5nCzCmO/dvfZcd/jSHVJDs/QfnYL9LN1PnokXvZELcwfY2ra12OHbUYK8lcefkG9x44THlumjeX3uS7L77B8nKdyZEpruy0WLxWYWpsCKenc+fOBu22ix8M6MsJe7s1VMVgfqpAfjyFm3hsbFYRJJMEl2PH9iMLIeXiGPnMNMcOz7K4bfHdiz3uztm8472HCNxlvnMloB+ZnD57lF/8iUfYXVvk6883ubqmcWl5k4kyqEmeg/MaXrvPz/7oU/zCz83/s0H+L+Kz8xMfe+aZh/aV2drpYt+9zcmzxwjtiDcvXGLh4HHaUZedrQ66InF9cYv902XaGzZpNcYdSKALKL0GpqEx8GO6ic22J+L0e0iSDJrCbiXAo01KlShODTM1lGXv9i4vJAMG7QKbHgT9LpaYwRQb3FmpE/nQTXlUl1KUx0POTI0QuDpxLuJ0aYFH941yNjfEv3v3k/zdcoVW18fquRyaV1ipiaQNk4vLK0zNjCNu1UGzkI2AB9MHeLWywVtmyvzTWp2+H2LXm6w2Wzzx9EOYdsRrN27y3Ndext5rEQoJcxNzCKU0X/nabSRBwjR9dhohXVcl6XeQDAM9ERCQCIOAnY5HEsdYZsyEqSLoPkLkUdRV9tou/SCm5UcYqo6sQEJIGHuYqoYoxfiew8D2ODgzjBdFGHpCsWDSbQ8IYwXdVOgMPLSMhusPECJodvpISPhhSBzHiAL4SYAiqdjdLqaVJg59TENFkmKGhnLU2wMEIYYkJoogjmPi2AEhIYlFHN8ndkWq23tImsZGs4shGxTGikgB/OGfPsvXXrrO29/3YX7r419AHoLANSiOJHS6Peam9rO6sk4mP4wfDshli8iSgyHr5HM6nXaP0HcZnR5DE6Cy0WYPkcPnjrG/oHKhchuzFbAldCgaJj/75IeQXIfzVy9x7OGTbC9VuLS5yfXNHcaHM8S+QjNuo8t5/uivvooh1Tly/H6mpsvUWj0CJPYXR1naXMbrB9RrNax0BkVWUBQJd9AFQcVxHMaGhxHFmP7AJohUyiWNi1dXsKxhAGLLJSVamKUsAylhp9PD90tceP0aGStNYaTIjRsN/uO//wXefPVlupLC/Q+/jc7KeeJExPFi9JSJaaWxnCylH/0Z/PoLNP7h1ylPvIWV5jbqkI5dbTIyNUYfgbX1LR5+4BxvXH6Nnc0mcaRz5vRpblWWadds9pXmOP3wOZLmHbT1CiUZjGweeX8Z0e5QGh6mNHeY5B3vBd3AEYZQdjeRxuZIVBNV01BE0PQ04dmjBKJIcvMviTsmg7bP7W/+dzo3K9z3+FMo1nGi9/wssbxL+LnPY73lEH/95ctsVzZwJQlJiLl5ZZdOWySVjrhwa5HAVSiVi7j9DgFwfbFFrZPwlscepbe7TXZIQdNLyMSYmQxPPXma7750FVmJIJDoeQMUK8346BCxHOB5EZ7v47kOS0tLeI7D3HCWjWzEwuhhUkHMszeWeO2lFk+fO8LzF67TtkUee+Io73nHPgpWwN3FGAmT0YMReVnm/e+Y555j49TrEV/9zvdRjO0nPv6xZ45MJ2QmR7h7YZ3rdp/u5hanDx6lsrPHTmMPK5fD7cMD90yys9ziiXMnaNQcFhvbmMqAMCVzTJ+hb3Zx90zyU9BztxgdL/PqhQrHp/OsNGPOpDz6gs5fvr5BR1dRmz4pQUGVuoSJxcDxeesphXw2SzX2OJErstntsT/TZ0GfxwoT0vkRnrvwHMP6FC9vB/z4Z/+atU5CfRBTixNuroXMZ2XEoIUpaly+vsWv/avTNNUUl69vcam+hSAnLFYSxssBomJSzsnMHZznc3/3Gjfu3OX+R45zcN88diKwU6/SEkU+89wiSRyyb26ckpZho9bHixN0ZEJVpb5rIwcxOUvixJEZ1nd6zBczREmLEJWCkcL1e9htgURVEYOArueycGgWPXAJwgAnAkEJafc8xP/tFCWICCWFnYaLZpr4gYuAhCz5RLgUMxaIBkHkEcQhUSISSzKRqFJKK7RbA1JWGtd3QVZpdBystMTYSJ7ddhPP14ljCYGETErCTKWI3R6BFzGINNq2S9o08QWBXC5LeWSIm+cv4xGDKSFJKq+9vohkpQgHIn2/R0owkTC4e3cLVdUIvYBsLsvArjEzVmJqKsVOq8tMeQRFkvFDhXKhSOiHLHcGTKjQpsap0iQ9N8JMqdyu7HBje42rWxf46JNPMhGq/N5nXuXg1DRWvoAnqOzZVYR6zHOXz/PRt95PNLKPUtTh775xjSNTJVJFk8s3FnnyzEk2tl2GShqR66BoKp4XUMjn8YMAQQCn3yMKffK5LL1BlyjR8YQudnOHQzPTDPyEXDnDkDXGnrvJ3nKNyobPwqE8CQq64HNn7TZHpqdBy1Fd2WN6eohKrU7Ud9DlhGAQIkgCiuYjD3wUt01tp0Zj4zafffZVLq7sMVcco1nvsDCRo1FvkZ8scOvCbTZaCY1OndWbt/nIr/wH9q7c4Mzpt6J+4AdRlRjt7ENEh2ZJ5BRcPI8fB7R8h0yzR9CrIt/9LsrkY/QPPkhv8l60A48R7X8C4fjbkfadxDUOI136FNFegOO02G165ErDOH5IHBdJPf04m3/wDP7VawyeeiepF1/mfz5/ifsfPIhfEZheGOLixW1Onp3BcwekUwr59AjlggVBwN6GzdNPf4QHHruHL3zhzxmayBD1Ha7cvoluZJDjPjcWq2x1fJI4x4hpstbYYn5igqliEU+PyWgCzfoek+MzHJ1SeG2xQyi7jMpZbm8voWVUGlsd/s2HHmC3u4FZKnPzzjqvXKugBBJzM+Po6Q2uvxnxrrfNc9/BUUIp4J9euMD5C+usbLnfPyD/1Kf+n2dmxzScQZe+LTDwehiTQ1TENoV0mRtLaxwojRCFG+yf24cZBTSqMrEGbcHFdEWKY2NkRZUra3dpuh3+9ktb9AOVQDa5vtqg008gcXnbwyf4wtc20HTQ+gMGiHh6iK8Y/OiJIo7v8uR7j7K0VKVvyzx4JkNWt5geUelJKlE0YMlr8cXrqyw5Bs9dfpNeKkdsN9FNHVHWEYSYeiTQ8EMaDgiWwU7XZul2nX7s4+4KHDowxNSERckSsQIFdVTB626TyhbY68HG5S4vbexwd3GNnS7sxD5mmGFuRubu7Tr7dAXfEun1+3hyxIiWwcwpyLJO3XbZ2qhTb4YcX8gS2BIpy2Gp6tH0DfwkwY8idFlATSIyUoIhx/SDGFUXiBwRw9BRRIFizqRcSLOzXSclq0iqQCqfodZokdI1QmIUScJxfCRVJw4DUqYOcYzvOhiGiCh+b4EZhzFBN8QURUxDYXu7iY6FqgBCj3Q6odWJMFWBQiZFs+fjxCLnzp1hp7qJlUvR2OtxZ3GNU/csMAh8bDtG1zU8L8DxIQHMVIrQcyjmM9geOL6HqqvYPZuxsVnWq3VETWMoW6DXaOK4IUEYsLlZYXqygJbP4nttQi+EVshbZhd44eYVyqkRahqcKM7x+RcWudjb5kPnjvGB9/4I/+NTn8UwQrTiGK6UoAQKv/ar/55//Nbfsm9khmu3lvD7A4Zzw5h5lQdPPcTaxjJR4pBJZ6k3msiygjtwcTyPYi6HpinkMxa79RpBDKIgkkmbWMVR7EaLtUqFvXqXzbU1+rGCiEm6nEI1VLqdgHTKwAsSVm7fYGZqiJfuriLWY0J7kdGRMVxnQCRKSJpC2sgyfPpB9nbW6FYrdPs2r95cw5EsJEFke7XK1NwU202HYyfmuX1zkZod4sYQOj2WX7rGO3/6/2Ly1Dyy3yJavUT/hW+h3VrCbewgmjrpkTJCs8mt2japuoNWPEh8+BjRlf9O5tv/iHPhz7DUPaLqVfrLr2DM7idKTWLUVjF1iwEu+ewQf/DZz7IwfojWS3+L426QsSOmDp2kNdgCv45XnqRea3PjzSZPPnUEP/BpNDsYcp69WhtJEZFViRP3jvDi61+m1eoxXrIYdCLK2RKDvsf8/jGWN23SRpl0SkXwt1g4M4HdMsgXYtLFCVZvreA7HvecuA/XC9msNEnJFiXd4I3VFc7MH+CllxY58+C9XL99Ay8W6bZjolDg6LTKxEyZQavBzPAYj5ybYtzy+NK373Bn2UVKl7h01cXufR85Oz/x2//5mXtOz5FSBGqDCMnMU9moM1HMU91sMb9gYNkKU2MTdO2QQb2JmlG4VanhGSELM4eovnKLtajL6NAIQlvigVNT3F5qsLxuM4g1qvUBR6bGeP5aG1vrIPsKfWSCKEQREobSEovbdd6/T2a72efQyH6uL9X4uXee48LrG5wez+CkTSTZI5ISblQ8dnf7HB2z2O3tMj5Rol5tYyo6YexgYKLJMokvkJYUXAFWVm0eP3aAwoTNREqg0RSR8lDvCMxGLcqjB/n6GytMDKlo4xFTBbjn+Bjj6QL3zs9z4+5NkEL++L/9CrvLd+juNUjSFnk9xXK7TkoSEeUE23N57L4ZDN2gsrHN4+88yaALlbqNahbJmCFqHCCmFCQhZGQozcLCHCtbNSQxISWl8HwXWdUIAoc49pken2JvZw/TVLC7LdJWikHHoTw2Ss/uYWgyrZ5LxjJQpBhdVUjiCNdLiBORKPRJIgHDSuEHAV4S4SUiiighStB1fKxcmV7Pw9IlksCnOQgRBInt3QqWLiMrIqoiIyoJ29UmtZqDHypEUUQYxYSRguf6iLKMIiQEnkO7F6CpEqKUgCTSG3j4scpg4DKc1um3O+w2ByRxhJHSsbdahK7A6GiGtCpwaP8Ql/o2zbbDRqNDLAh87otXOHnuGCU9zbdv3ODCzYscOVFGskVy+8q8cP46+wv7efHCawwa63S3Qyr9FjsDh/xYidnyQa68sUppSKbT65CyMqiKQRTFxCTImoYmy8Sei66ryIpMrlAidH00WeS1y1cZDLpMTk+z1+gzXSywsmUjxyJe3CB0Y/puTLfbRIhksoU0rYqNpsP8yEEe/eiHkbSYRmuHfmcXXXHxPB1REfF6W0h2i6btMUhC7u4OGHgDBD/EFQMOHDlKq76Mmsqxvb2LK6gkcci9RZ0H3v5W7nz9H5kydIJ9c7RXL6EkaaR+gpGbw3/HWczVdTKyiDJUQpnYjzB5DPXv/wCvGKG7BQIzheq6KK092F1EPfhBeiWHKHYYXLvC3zx/mdGZMT7zza9x/OG3sPLCdbRyDnetwdRP/zb3TcT83me+SdXb5D3vuI+NzS2CpM7kxASVjRr7F6YIhBAzq/HGpVX0jEGjHpNO6wSJzbdevEjKyLCxXWe11WXQ90EU+NAH389Xv/kqjUqTQnoCSQ2ZHSmTzlpcv3GVvmOz1w3ZNz/C3e1t6jsxW32fu6u7nL+8RaTM8I3v3kT0Btx76gSPnZ3npfNXWd9u4yNwa2eVv/o7l+NH0xw9XORrz14kjKJ/doztvwiQf/q/fvwZUe8wVhqmlfjcubpJaEtM6gqnD+9n8ZUtgqCBqeUQSOOLDmv1FkI2S73XB69Dy5foCBFGFFLtd7E0C9EKGJ000ZKQBw6InDkyz2BzE6cWYksJGdnnBw4VuFQxePuDMR+95wxThwucyhcYzuV5/HiB5751lXNvGeaNms/zN+7yQGaI8dQIu7s7DFkGW62QvpOAFxHKMYL6vUuEbs/GFwIwNARFoFRK8aFHhplaSDhaHOHY/AjbzSbX7zTotwd85KOnSOXzXHlzlYNlnYfGp9lY32PH9zh5/2E+9iff4Ylz44yNjNF7ZYUvfvc2M1NjVJo9dn2HdKShyQG5bJruYMB9E1lqu12kTMLdHYdXL2+TzRskYZ9UJGIZApIY8+jjD5GI8NI/XcXXFIQoRc7soas6TQcGASSizMCxiWWRrKqihyG5QhrTzLJV2yWbTSESksQiGUvBGXSRZIUolohFAUUGyxIxTZk48ekGAqouI/oOKUuj0+5jmSmiJMD3XJq2TzqbIYkFVDEml08hiwmuN6DZdkGS8d2ITDqLE/j4YUwiqLiuSz5t0R0MsFIWqqQhxyHZlE4YeYiSjCT4EAYM5yxir0cQiDRcgaGcTj/o01FDBsRUO3X8ME2VkGmpyPOrS8wdWGBn9Q77Do4SRAF3bm5yeO4YihJzbWkdeayAWHPJGCY7u7s0XYcvfPqTnH/pDi+ur7F/dJJ+2CKlGbTbHX7kh97HdmWAEzl0O10EQUQQJbwwYLRYQpclxsdH6TZbOEFIuVQmClzOnjqKR0zb7tO3O0yVx4kMkEQYmphElkNkVWLhwDSbK98TJlRWtwlik5/4Nx/g+ktvsFrpEpHmAz/8C5TnzjA8UcLQDdJqQHVrA0VOY+UULtzYwjAk3vfe91AqF1i6cZvQ9Yh0k6C5ixvERLFMYTxDtLlEumQxNjSMduIhpFe/QtsLKE5n8RMD9ej9tHwH0bKQlXGcx96Dcv0rCO1d/J2YHiFKIBBrInLXQ2g6COPDqPlZlL01YqFHbyfDD37857h7+Tr/9E+XePo/fpwD9x2nGEuwfx6vtsmf/r9/SS41jOfrlIZ08uYMsdtHVi28oEvP9tjerFMaGUYUZCYnS2ysrSNQZHRmCCFycWMfRbHQxABRjHnuW68RCynKQxbffvU6s2MZEuq0+j7798+jCCKKleXqpSVOnDzIhTcX2dlu4/gms9MpNrd2ODI7RiIESLLDc68ts7oSsrnUIwkGLN0RGZrpsrttsVW5xdDwFA07ot35Phqt/M7vfOyZ0wtZPEVkdbODYRqUiinSuRQb9bvUQ41DszqjY+M0tzvM7T9IQshLlyqYZYu0Bo4Q4dcdvIGJIAfs2RHDQyYZNc3sAZXDQyOMpmFGKPHRR0sYQcBQWcGvtrnRHvDb/8fjrG5u4y51ODKTJpOe5LVrbxLbKpoYkYs1jmVC1AmVhhhhN3ZwpRSDzg4HJgu0fA1/IPArH93Hc89u8Sc/epYvXqtQ0nV6qs3RYpf7D+9jLJUhspsYkkk67jBz6j6eOjvCoXyJfm2Zc4+OkUplUVZ6MJZFCQboQzrHp7JIeZGSZtHsWBTCDSRtmBcquzx58Biu4uErPnJdYCcwqbZsGt0exw8fZXOzhy+FCK6Lkk+hiQKSrLI9CFhbrPPIo8NIYYZOo4Mrwtx4jlqrTXrEIGwPGMoYlK08ld0WmhGRyasIPZHJ2THu7O4wbBr4QvQ9JZuvY1gKgdsjI4dIqoRpCniOh5WS8T0PUxNQBYWyZdJ0fKyUSU71SBBI6wIpTcEZOOiGClKC2++jGBZR6CFIoOkyYqIgJDGWIBFqkDE0iCEQBkSJTIjCwOkwOZYlajskgkhaSNCBJIkQdYGp8RK9XhfDSDF9dJTdvTqGoKCbKrKag8DHtTe5u73NUyfyvP5ynR/5wGme/U4N3+2xU2uSLllcu3KTt73jcS69dp2hkXFyowaS0KWQn+D8hTe5tvgqc3MTTE+OUWu2EWSBdCyRz4+yvnyVmxsr5BULJ3TwAw81BE+E2I3YrlYwc2mGslmcXg/ZMLHbPRTBZ88PyWTSbK7vEoYKVj7EtzVSRYWt6ha208fUSqQ1k5W9XTpeSGtjEcmvo3hNNlZvsnjtPG9895tcvXYLby+keN9+Vl++Qm/gIUshb1xfYf7AIb75te/S7gRU6mtUtzVGszFDUyN49TZz5SxLtzeYmVvgSNEAz0aZO07z8nM0UuOU1BLKSIpw8klSU+P4U2cw5vbhSxPI1/6Czk4XVenQc6DXbCLYA/RSniQXEyQgjZ7CzQ5ILrzOoX/7y6z++R9x5kM/zB99+i/5y2e/AYt1zvzYR2gO9VE+9+f8689/nt/85CcZms+RzWRYaa/S3wmQpIjtqoYr7pI1JyhkRAIBbNelvdsgp0p4IlSrq8hSjpwuIoQxRxam6doRVjyg3Rrw0MP3cHXxOoJmsLrR5MqtVRzZ4vpSlWxRhkaFvW6Gh8/NMjWWp1ltcGBK4Z1PzaNJCgQtjIxJ11Y4+9AE++ezLK1uslrV6QVtRqxxCPtUajK9/veRIeiTv/uxZ+47kkNwYlpNH91LsPt9EjFhfGyIH358nls3msyr05hSxN5Gi/GzUwR2l/NvLnHP0QdJtnbYDEDPWQwPqciKQqmcIZ1OI4YujXqTk8Nj6KHB7foGxw8dYtKwUAo+J3IpKo0B1c0GI7MidX+YTn+b5y9VGJrwOXb4LOtxjXJZpW/LTA+VOFQ8gDgUs+11ePrs29CSNkquycmpCZ58+yxXNvb44fce4+uX7/DJn3+cB0ujpPsC7b0uViaH26kxiDQ0ucNQojHoQaPusx4EdKs2dwsydd/nbWNHubW3TnlmktpmQr26y7Ov3OSxc+e4U92kJ6qs3Fzn5L0zLFd3GClmGM0nVNoe4xOz3FrbZq/WYLScYqpcIBKg3ewTCwqib9KKXZaubHL41Cy6bNAfdEnLsLDvAJdvraLoWSq1Dp4f0Ap8IjWHEhh4gg1dn63GAEEyiJEQwwTPDQn8gIyVJo4UUlkDzxkgCjrdXh9JMhDQsF2fOEnwohgE8MOIQFSIPPB8iBKRbtchjBLGR4fpNHqoko4mK+iaTuR5ZLImaSXE7g2IghjLEIgC8X/frSfcf88JlqvbkISIqsJANMikRUxTIfQCwlBnc32PodEC1UqXbjuiOD6KoRUwdVg4OkSjJlGcztPqpTi/bHPz5hZBKBI4HdKmQC6TMDYxxqBnc3PJpit02bhTYaQwit3ySOsGiqFhoBHKCngRAgN26k00Pcc7Hz3NXiukZ9vIWoKYKGimRq3TRjcM0hkLxxsQej4PP3COrY27dCOZ4dFRbt5c5APv/AGMyRRO0uKhR0+wfnOLzfUKZ+57mL3qLsOlYep7O7TdCDlOsJKQrj2g0+1T7wyo1Dp0vQQniJCHcvitLltuRKRqOG6LlhOztLmDJmo06nXGpgr0BwIP33cSQRFIggCSkMML09xZucO508eRJQOlsYuRm8B0G+jlecInfgqlt4l/7evIso6fm0cLXkWc/CHUfTqqJ5BOHNR8FjFOaHdtlFBBcmPCIR01PY9y6nFu/KefJLTG2ffBZ/j87/wWairNshPw6rPP8sH3fYDtV5+nf/UNfvVnfpVP/+kfYu/ItLo+xfGHWa43SaRdskKBnOWw/8A8UZKwvVplSLVodVyGp3LEUY7uoAZ6kYbdYxB0MNIWR0+O4EcxlZ06tT0HQ81y43qbru0j9iCfeLztzBRfPb+LGKU5fWSI+ZEUD56bo1ySqO9sMjE2QX40w83ruyzMFLFUn1I2TRTHCFJMYyNkbn+KQs4gk0lzd632/QPyX3/m15+xZJnQTdjabZIrm99bGKkwl1NpJescyJ5kvXYX1crwJ6/c5UsvXELPZkils9S2LrHv8Bj5whhpU0RNGThOBzVl0e3WSfkKiS5ya3sLo5jFcUQmrIRur8eDE/ewMWhQsXtcWmwwVtciCIAAACAASURBVCpgdHZ5qVKlbwq8++BBalGTY3oRaUTBcIsoG9vUex3sbo1Dozply+IvvnKDhw4vsJd4zMQ6WSlAHzI5kDLIpQWuDJbxMjrrdhtNV5jJ7yPODpAMmaYbUHX6rK1WmdaKbG/uMV4wKJkmg506U9kRKj2XN9+4QytykUKNV9fWqHcHxJKAoEuMD2d582adfjjAbzn01WHqOxVsXyGfVxlJK4xN5VEVmW7k4UYepYJE2ZQQzDzZsE+l6dB3fRQ9zRuX7pDVhtC1BLvhIakiJw8coNbYJGfpbLS6zGYUisUyPc+l0+rgJTKyodD3IrpuRNfzkIUIVVHodn1CFPrdAFkxqLe6pCyD2B2QT6v0+h66LBJGCREhkpSQ0kUSUUI3U8T9Psgq/Y6D50eYhoDvfe8D1bRK9LwQUY4ZLU8gih75nMHq7WXmpyeJBm0sRUSQdTwnRJEVRFFAMXVSVoGd2hqDvkixMMLmeoVeo4a906ZrKxw5kqbR2KG2I2Fl0myttKkNAhQj5ti9h+h5HRI7Jm3mWFvtks6ZFEfyVHdqJLFLcTJD3OlTMAzassfA79PebjJ2YIHOTsCJo7N86R++hRN4FPIWrhMwOzGC0xkQA4aiMrd/hnanywP338/Jo4fZ3a6ysbnOyHiJly6+Sq+hUigXcPoBN26t4aAw6AQkUYQzsGm1+kyOlUnLIg+eOMbli9eQjRRdN2IQid8LTOu5tKImReCFN1+g42bo+V1UNUe17qIKPnESMn9gH9Wtbfaqu8wfmSN0HR576yPEqsjb3/0UpugSBw5Rz8T88LuQGz2id/48XPpDoje+DvUuiqAh6TbSFz6PMKojFk7Tz2t4Ow1S4zMoUzmEpbtIQoSSGiG55zjx1iIoIpLTQ+mmMR64nycKS3z22+c5OjTOli6z+uYup996mtEP/mvi+eN8+F99mPNf/gqX1x3GRzw6vSrejsbBfWXqdoPL19fZd+AwiRATxz6hkGVyMsWLL96iPGoR9F0s1SSbMohtkcrWKm7PQ4w87jt5GMfeIzMi40UGVslDEXO8dGGLRjPi7Y/meOGVRVRT4cbGCk6UYWnR5+TpeVa3q2yse2TSNlEicufuNkMjBXL5FG85N47d7nH63nkKJXjhtcr3D8h/8zf/8zOi5DAyMUy90UYxdfpOSGOvSz4bkfRn8HobHFu4j9J0SL0lU087DNZ3GZ2aZThXJhuLlBcMBp2QxfUugdun6yd4ns2+1Dhhr83dio0sR8iCxaDT4v0ffBurF6pcXasyfHAfB6YzyEJI3/Z54vS95EQXY3yIQbdJu5ewlnTZaexhT47AwKFrCpx58gGqWy0urmzR36kzf3gY0Q8YyxdI1XvMzB3nf3316/zU2XextbtNVEyxeGeFiXKOcC9k2+4gqgJu32bh9AmWdqvc2e6zEQj0ehEuDpc275KyhnjqiYNcvbxOeljDdyLyWZmxnEgv8hm3DE4ulFisNBkZySAlEVEUUcyVsJs1sqZGtdNhd2sPNWsRE3F0bpxavUlKN2knHnt7TZyBR8eLSWUy9L0G26sOTzw0xWazjpAkbO0NMNMW7e0+U5NFkn4fRYlweyGRZJAkLor8PSu8pkPk+qQMjb2Gg5ZOIyDhDxxMyyTw+qSsDLokEAoqhpDQ8TyslIEuxsxPjNFxY/Y6XWLXAz2Dqmp4gUAmKxF5ESIyBCGhnCAgYJgGkqrR6g4QFAk5jsA0CZwAWfQZKlp4oUDPFyGJaTsDPFdB1UXuLlcxNYO0plBvO9QHAWNWlrubbbKaheM0GEQiTiTw4Y88xm5zh54T0u31sEOfyUmLuNun7zY5fPAY5+4/yo31Gxw7fg+vvPQKw7kcfpgQhxqhERLVA2YPTNFr10iVSgSOj6nLtFt1FFEhMXQC1yPyenT6Di++dp6lpRUEMeDmcgVFBFQDd+AhayLXr60yO32A5c0KiiyiSALNVp10bgLXriKmC6R0lbQhsrPXQlM1wiBAkgUifCzD5NLdO7z32DFevHiN+ePHWV+vYNsuE2NZgsBhdHiY3eommVSGw8f3cen1N4gjmfG5MeqbTQ6PzpItTVD6gfcgdmPUU+8iWfsDuNJG6/bxu7uoR+6jMzGCvnIRrxsSixry8DmUI4+TTJ7BHT2Gdu9bUSaPYh+dRL/5Bu2//SpiMYXYE1GKwxj9RegKvLG+SWZSJiMoCFKZd//yB/jUz/0M98wdxho9wtvfusAvPfMMf/EXn2e2MEw6HeIHffrtNGeOz/HGGxcYhBLp4gRv3rnNkQMj+JFPbdcmFAScKCFRYW1zi/HcMAvzBzh5co6mvUp5fJRWI2BudgKnryDrGbTY5tThNK/d2SDWh+j0fC5cillaXOEnf/JRvvXcdzh+YB/z8/uZmhhiZWObQrGMmQIpFNnZW+Wxh85y59Yt+smAC5db3z/OzrRl8L6nz9FsdNFyaZa2GvS7Mu976jD75obJmTYT+QXq9k1qOwH6aJO5xESRi1xfWcUQbV6+vsh/+9R5nF4A3ZBmIBAIWVptERsbLRB42/HjZIQyPdlGnx7iz/7+y7y2cYPZ4TJW20Nx+ly/2Gb6rIDb2qGcGaZ6c52LHYedrSoLrRI5bYzq+hbOQQO5HvLVr1zhr1++gCXFzB6c4aVv36Faa6Ae38flVoXrjQt89C1vYbm1y3hpH7XlPeaPTZEe01m0m6TFEhnVYDY1QrW+h9F0eHD/BEOqQM7KgarxK//uA9wznOfmRpt+7DE1M83pe2c4dWKcY5PTzGgpslMWb3vqER4+dYjQixkyYThtIkpt0pLK/kOzrG30OH3uNBNJiw89dJL7z57F83Sa9W12t20yZgErk0ZVVZrdOnJa593vOEwkR+RSZaDH5IhO2G0yN5tCyoyRyBr99oBCsYRLHyQDp99DiD3yeopOkGAqGilDoBeFpFQPyxCZLOZQRYW+47DZjXH9hH4sYuoqYSzjxgaXl3ap9yNkw0KUswSNBq5rk9ESfFdiTJWAmESOGE5bFDSDpt3F67WJBwF6epiqDV3foK8YYOjshSKOHBOHDpvVFkKsYjcTtBAOLMzQi0V2Oj6FbJokSfjuxQqKJ9HabbC6q3B4OI/v9NH9NuevrpATUhy+7yjjI3miYEBxpMzB2f1srS1x69YiUiwRVFc58dBbKJk6//fTP0Bx3MILu4xOpLl6a4nDR6ZYub1Lr19H1dMkcgrLgL4nEzo9MoaFoSrs7TaYO3SApcouZi6HZVmYYYA8GTKou+SI2NupM6RZlIoaaRJGzBS23OTgkSkEweHm3TrG7BGmi3k0NSQ9mkaRRKZmF5jKFQi7LqKY57/+1m8wP1kk6veYmBwlCkXuf+hh/KRGNqcxfWCSMIDC2DDr25sUpspcXd5m0G2R+eBPsvT3v0/rha/AhX9AHf4Q4uoSO90tkA0YiOh3rrK2tUnjhZdQt6tI0W1stoj7r6PRwdFN4sIkor4fwelyrXWbwbUtwtlhzLKJ147InTjF5769hCAltGo13nzxMt7NDX7pkx/nrY8/xj/87n9CkkeIvvlnfPG/fIL/8ad/xMb2HTY3+6SyTQyti67oVFd3OX/hMvfOLfCNb97l9IOHcOOI+ZkpQgQ+eP9p7j8zzHvefxLB2qNS2aCUmkBJKdRqPVJWn73aDldvvkmlHfPmTkClmuAPRBYrPmHY5p2PHSUVmTxwcp5/fOMa1dVLnN9aoTQ2iRENmJsbYdYTSatpXr94mUGkMoP1z2bov4iK/Ld/6zee2dqoYuRytFs2gmTguDGCkrC8ssnM/DSnZtPk/X0Mzw7xu5+/yNBUCrvWRTcT/MaA0+88SZA12dvYYqXZYiqdY7myRnlsiJLQZ2TfPF9+9QJJLWB0qsxivULlYo+qAwVLIFPUubO6x0OP5/iBh36Mly/ewIkH1CKJtCIydXicamWLMWsIRw54VDtJRW6TRAEdKUXsOaStLAoaRVGjcn0Duwt5fYR6vUdDDNmobjFULGH4ErKgcnFllbudFrPDM/jNAV7gM3vsCEuNPexGg6GhDPVWk7X1FtuNHS68vsSh+WmsdMTksI5lZLmydpt3Pf1WglrCCy+/yML8LLVmh626zdxEga2qy333HeTi+ev88Huf4uabL7Ewu496q8vVpVts1vqYVoZuo8/8TO57cbqKhmf7ZKwYRdRI5BBZVGjbNrYnEAkGzV7IWrtFEAdMZPM0Ww0mh3Kk0iaCLiEqAt6gS+Kn6AKJIJFDR0cmZ0hsN/eQcgb4EZoUkzZTNB0Xz/XJ50rs7dSRRAWvPyCb1lCkCCWtYiQC7sAlkiRs36PniYiqSadrY2gagucjamAVsrQbTXJZE0uNUBKXIIiJIpNYVshZGYS+TzhwyRc8dDFFvdGFOMJQoDwxRNt1GMnkmJweZ3QoZmN7jyXX5dh0nsX1VebnJrh5d49Ou8lweZhMweL23dtkkhQTxxYIBn2Evsv07DBLGyv4dsizX/4nfvYnfgyvP+CVS9eYMof5waffxbPf+AaHjj9A5LbIpNNMjYxwY2kVmZhH7j+LoQts71QIw5jhoRyrq+ukLYs4StAjnYrXRhZMHr//Xi6ub0Jg0BPb2HZAWjZwmn16ocjv/ODbkAYdzr79vVy/vkh3r87szAQjiknm8H7+y69+nIOPH8Gvd9itb3Lx0nUkTaGyvk2r2UeTVUaKJbJli2azycl7zpDLZVi/fYndhs6Hf+ajeBde4OIrz6NJZUqphP6hR1DHQ5TaFk6cIDV7SI//CMK3/piqG+IMbLKSQcqMib7wewgvvoJUeQHZEBFzBdyUyXxpmr7k0dyss97oMXP8PvwDT+L1lhkXNnn1O00KRZvLX6vw6LsPMd1e5a8uvETt+irfuLHCIz/0FL68n5/66Y9zcJ9E4/Ymf7+2wb2zWfbtG2Zhcpy24dLrO2QNjdqah2R6PHR0jhduXWHCtLizVWGv2WW4OEFuWEBLRXg9nX7Po9PViOQIL/DQApGF2XGWl9eYGcqTz8n0ogEblSr/6xt3eOyee1htNZiIBPpJl6ySYW91l0rfZmK4TDfsYCQiBRu+eaf+/TNa+dSnPvGMoqnUO32K6RI9x8VQEhq7PrOHJnCqy+x2AjbV2xjlMV4+f4s+MsN5mJ2YZmc3Ju6vk0+mCd0uvp9w5thxagpUt9tM+zIbN5YxR0fp9gfsqW38jQGpssLoeJbMTIGO59I3OjSbaf7kM1/G9rpIOYW2lDClqNSbPcYm5li9sYqvSVxbvs63ri+zXGtwbv8QWjZF1/Gwe11sOaSXTnBMkb2dHTZ2K2x2Yzq+w0B1kdIgOjYPnryXW3d3WN5rc/ye/The93sgGCvTrXYoFbMIapqVtR6KBcdPTSMrMptbbZqNBD9J2D85SWW9z/LuBl6s02ntMT87gSHFaNYMiyuruKFGEHZ49coqB4/MMT46y8raXX75xz5IvV7n7t0quWwed+CgptJUdzscmJ/D3qkRBDJZS6RZ3SWfy+D4Ee4gIokTIjug3XVoCx4jRpq0INMbuLQ6NoasIsQxvihSiiMKyYBThyfptao0BY1W32M4YxJFIbok4HoesaLgOT6ECaH/vZZfNU0iL2JmqEB7p4MrCwiqiiIKOJ5AkIg4XoAoiJAEKGGMoCbYgwG6IiEpBp43QJAVEjUNUYw9sNGImBsv0+p22NgOQBHodD18PeDBh0+xuXGDUwfHOT6kMnMow24Q0N+2efzQQWanpsmOhhSTPE1/m2K6wCuvL6FrKUJPIbDb3Nm4w9TkGKlQRZUFEs3j/6PuTYMkO8s739/Zct/Xqsra96reqrt6VbfUaglJIIFYhABjYYzxtbkec7GxGc9MjAFjG4bxFrYBb4MZsAFjdoEFQmuLVu/qraqruvbKqqzKyrVyzzx5tvtBPR9uxB3bN8Ifrp+IE/Fs8T4nTsT5nzee9z3v/8KtHPZwmIsvPc9gdx8r5SwhJcjoQD+p9BJXbm0TC77+3NRWk4FEJ/5QhNpOho5ON48//hjnL1ynO+Ynk99FlBU6Ozv4yrOzxNqwki8wEbPj1E0ivT563F2srW7ylrdNcevONj2hPo6OShwe6KUpFnjrQw/w+HvfyYgnxqMf+1XWf/A1CMaIurqZu3MbxWPj9loG2S5RrbfJFHexSU5iXX4EUSW5toFTcaI4ZCTZQX23xWPveROKJrKyOodLN+k4dBTNzGDrewRxYAh3rAPDayLF78fceQG7c4COEw8gjx2mYeSxLp2lqrhwWhZquoRtaArZEjFCduollbZsx94wEZ0SnoQD0xYkUVzmtbM/oOPeN0HMzf1npnl5eY4x30FuG02OP/gfePHVZ/jcb/46T7znIUKTBzhx5BAfe/JjfPNv/wGbqnLPPSOEPH7ecfI4rdIS/oSHwViAUlPmd3/tDNdm11nZ3MFU7RQKFo5AC5cZw+dXcXubzM8lqRRtHNnfw9HDPVy8fhNV7iDgaWC0QdVsjHS6OHV4khsL13lgoptNQyRk2WGzyrjlob8rSEt30DBU7LqMJ+vg+VTm3w+Qf/ozn/6k06mh1VTGx9wEogpiVicqGyheO8eOdIKhcOHVHdxOuD63hdhq8ZbpfeQdGrW6huIO0zlWodMVIDyRoJpfR6jK7GYrZC07aUPGqtTIlyu0ajWODY0y0BMhl69RqUCn20nIHeDmlQwOv4LDHmIuVSYcdiA37FxaWmLHUPF0ROj1Otmu5Jns6ccuWvR2xon1h5CbFqNBL1JYYlcz2B+KEnTZcQg+HE4H7YZOvWkiiQLdXSPMzi6T3DVxCBrjngilXIETHRM888oV7IKHdsvCEkWiUQ8Br49aXURttrC7nWzv7DA61svN2TvEEk7y2QL7x4e4fHMFyWYjFFC4dOUWfleY3UqRe/ZNMNQtMxgPIMst4mE3ly9dYWp6ggOTY5hCG01vkCnUkJQwPYko2N1sbJV48u0PsJ1v4ncqaKZAebdCf0+EhijQbLexY2dL1VCMBl6HE4cBdkPDLcOBoELQ4yXb0ljKFMiYMj0BeOz0cW5eX0QAFGcQGQFFaCG5bHicTsDA53ehVZvgsRMNOzCqBmVVQ9fAo2iogoJN0LErCpIo4rBLWJKMXZKJ+oI0W3XktoDscGNIMjZFQhBlLK2N3TRJl3ao1FXi3SPUaw0crhYHDvaRTy1xaHAAs6ViNy1u3tpEVWXq5i73Drj42vkZbEIL0xTYv38Sq61iCRaG1iTidnL8DQfZ43Ozms+iWk7OX7mDzeGlYrWp1GqMHpykw3IRiriYXVvi1LHTLM28horM+PBeLK1KJBJlenIYTXQx2h9lfGKI5559iVbL5PTJI8ytbGAJAhYaC9sVVBQOxuMsprfxR8JEHAFmNudQVZkTQ520FIOF1QynRgYol7M4dB2ruYu4VSPy1Nu4+Pufok0Lw96N7jbZd2AfltnkW0+/hNAuE413IIqgNZp0dUXY3tiir6uD5YXbhCIRLMtkJ59nMtbBTnGbhMdGuVzA7QLfThJhK4k+chQpMoyRuB9Z20RRFDxlA+HIMcyAG8E1hCloeBtVUvkSgb4DNCdHseZ+QmM2TUOQaBZVIlMTRKb20J65jhgN02obvPE/fphvff2bhC2FoZCbuGyjHSpwZV7FHxxgbGwPsysvc/PFl/jC736a6f2niU75eOIXf5nTP/dbJHxevv4n/8g3/ulZlqsNZudFOsNumtouCws3KObdHDvSw2hvLzdntqhrOZyYjA534nP4mBjq4sknpnFoBWRRxzKrtCsq2Wybob4Jbs5uc++BHpZy60Q8diTDi2u3TkXXoa3RqBpUs3k2iwVUDVwOJ/nVPFd3/x1tP/z4Jz7+SY9d4NCUj97uLgKOAFpZpTcYZk3NUbcE6rodV7cbS9PZu3+U+QublLw1ZNNEsTnp6VCQNRmPw4GslWmKIhFfBKgzoAuEdI1HJ2K87x0PEgkaJLdMVlMlpIBAcrlERbNI6018bovuiVFqxQYdvTKtkkp31EU4FsHEIL+aw+vzEOnooGC1cVuwWqgiLe3Qlejm+FgP9VoNj+Enp6VpbLXxDXWw3DLIZDaxJBmvw4ErrNCsNXGGw9xzoofySo1yh5fy+ha1TolYcICFtS0KlRqCVae7b5Ris4Bd13EFusg3HVy7eoeHjg+xstHk/hN7uTGzzOhQD8VinbWNGh2xLmTBQUfEzbW1BR5+4AxLmykW1tbZrerYvUFefmUed7jJYHcf8UQPSHau3VwhlSlQKtZoGw3mlrcp7qo43TbKuTRlXMiGiSBWaDRkwh47ltDGFOw0GmWcsobHLtLlcnKhIlKpVXD6AjidEqMDMWrlFrfWljEFAa8zTFlrU2+qjHiDqIpBq6DjDntp1wv0d8SoNUv0eiJUigUcbhO3XaSm27AEFafXgaS1sDsV6joYMoiSgSiYOHQ7TkFgeatIKBgEtYhWqRHr7EbLNfEFw0R93SQ37jB1bAhfwEE04UEyRObWq4i6E1UUsXlMWnYPTnuAZKWJXtcoNmUs0aSa3kSyBXHbFAY6YthlC6Ol4jZNnLLAWr5IV1cCm91A1sFuCsTCTcpWEHNnm737p7BZHnpHBklnMtycvUNALBGND+JxCDz349t0xA3mLy+ytnyFet1ioDfCreUklk1BtAyup7ME7E4sUcfhlplbzdG0dKb39XP12jrBuJ/UVh4h5CJad9ExFqWjImKLJfCNj2PagiQz55FKFtXuUaRmDbOW5cUXf0RTd1LVquS3C/R3ddBWizgdMmpNx+4OEYj4MdoV7IqdeDCM7B9hcChEdWGe1K6Gks2T350h7BtCnjiM8dknUcpzoNlp7nsr7b3HwGFHEAw0q42t6yji1EkCew9Ri8bwWho7P/0xS5dvk2mrVHWRfQeOoMmgixK6Q8XtGqQquCiun6PYbnD5Bxd545uP8fzsJb7994s0G9vk62UKZRc5bZ3rC2VevXCBKxd+wMyLl9ieuUw06OcDn/40v/R/fpAP/Yc/4m1H+rn69E38cYF6A6IdIZZncnT2+FB1jWFfHMPm4ObCKkZeI9Cj8K0XFnD5bJSLNWLRAG8/PoDN3SYRt3HyhA/RbeH22Yj4HMh2J2tGjcFQmFZYIV8qUJRt+INRoqEAc5kt0qk86w3+/Sx2CoZJX2+EpWWV2cU1JFud0KCBP1Hl+GiCsKpgV3OUs202UlVibonRUwMEFC9aukXdrFGqVmhW6pQadWqZFuVdnVR2B0/cyeHTfTx0/z5cHje7OxX8LS+y0iRUd5K7XmFsqodCfZeQRyaUAH0jRbyrRsAXRvMYPD+zSTZXIuwLsFLdZSNZ5uUXL7GYzHLh8ha5rS080QB30gusVFMMR7s43etHW/dScwt888Ub1Cs5wrFeOhIDGILF6o3rqA2Fr37rOrZdD8/Nv4az1mLXVIi6QxQzSWKhANWKxNZ2i5lLl4jbfGiGiE80KS3dZt9ohDupEk57i+fPLbCSq5EuNREFG3vGJ0hv5VgrF9ipVBgPR7G0NqnNLI88/E6KuxZXryc5ff8kpW0n5UqNc69eZ3O9zJsePkFfbwxZFkFyoeNElNvkimlOTu4loYg0HBoOt4InYENARzQ17tnbQ8vm5uT9x4l1+rlVt4gEJAIhBUEsgVCmkauiiAKGDh5XHL1ZJeSxgdWirOZp5xtYdh2xUsYmS4SdTmySzNLuFj6PhWkI2JwSsr2B1xunXG4hyQ40o40ogle0EfRJGKKDGjqG22A6EkBRDVI1HT8hbixssGHA+nqBixtLyIqbjZkMs3NZnv1xioUFg2KlSVktcvy+Q5y/mGM3k0Nq10lEoxw6PMY7zhykVaqx3Qiymc2BXSSZWaMtNGm2KlxIrrPRbCMrTpq1KvNL21SaBv2Dg9jlBE2zxU7Lx/mz53nh3KtUS2VcepN4LMKBo6cp19NsZfIkt6/iRGC3kOHIfQ8xffQgsXgcBBPBAlGQMPMqY9EwD07vR2nWGB9IUN1tcfnWMhMHxpldmGdstIdqNs3FtTuElAS9v/1bRD74UVwT9+ERc0yE99Ln9vLdv/8KW9kcNxeT3Hf/m9G1PBFPGASB2wvLuHydWJKNeLeXhYXr6JqGInteZzaSVOYWLxPrG2bkZ56kkBeZ+NiH0TSFajFPSVRp9vaRvP4a3HwRJ2XcVgvRcCInX0H4+u8hrF5AI8CupxMl3g3lHbZu32beAXfyTd5w6H5I2NBdTlxdCTw7OiWphEfe4QM/83NcfuYmtbKMGErw7NO3eNPDJ9kzEuXE1BBl9Q7NskG7qjI4lEAXNLLVRdKVW7xw7kX6PSP09U/yrvuOM3P1+3z6936W3//SVX7tt79EX9SGFgW93cLXaNEIGWR20lTbHsywnWpJ5YE+EZ/ZYMBvw+4EqaYy3OUj5gSqeUI2MHYMPJYTDZOJgBfFIVLaytCxZ4x2WycQUcgk08SENt3j/xzH/f9T/n8xI/+d3/u9Tzosnf0jDlZXm/TFbBiuTmyOMIVKBq9Pwe2N4okpeAWLjYyBIkBaaxHr9bO3L8FoVyf9ShjBMkirRWSXB7EtYGgNfLqBUm+h1dwYbYF2qU5vTw+L/U08LQtX1MnOjobbVqevN0JU9XFoaA/5ZJJC1UQKCKR3WwhuO/09g/z46jxBXx+eIQ+nHpxk6uAIhcIWAaGbZ89eRZM1tssqJxOduIZNjuwZotJQee3mMiNjHVw7n0Xym6xuVDFUhYEDPiJemVTdxiF/gK+8eJNHH3yUl1++iOTw4vALvO2NB/DqbVzREC+9/CoPPXYvlXyFlRxEAi4uv7aB0xIIuO0cOnaQv/nac/hDPhQV6qrK5P4+wkEPPf39/Nnn/5GR0X50U2J2do6DB6fZyW8zPhxlfekO0aDMbr4GspN2q4nRLLFvvIt944PMLcwQirjpC/uwrDL7J0cwy7vsnxxjbXWb0/uHeeanN1jO1OkKeXBKMmpDsGaNyQAAIABJREFUpTseRWs3aZRqaFYbxa3QrDfRJJlWvUZ3MIJPkCgJMiGbwk6uwTsfPEqtlkFotJEUg4muGKvVEk3Dhq4CoopTcWMTdQJhDxYGbUFGkkw2l4ucuecebq9uU5RbRD1++u1e1rObBGwOgrIdJIMeRaZYrlGywG73INha6M06gXCEVlXkxednmDrZQyLsQt0t4nQGmJ+/zVKmRmdPAq9Ux+8N0xH10NYaNBsqqdUC7q5uAhEfhfQWMiKVhk4oEsdpk1i9uUC+BMhNOt0ubqxt0OHx0xf3kRgcZj3VQhY11ld3OHZ8kkg4xv69g/g6e+kf7qHebHJlZgG3y0OtUeeRN99PIuDlzMlDaLSYXdlgaiKM7JDJpVfpTfSyky/hkC3i4wlKs0mirTY7M+eoXvomuws5uh97A459B/juF/4HBdMiuzrHseOn+eI/fhPDCuFygmlK5HdraBbUqioDg6MEfHZkO4iqgWIXkcw2116bpTvk59XLS5x66s0sfOe76GqQ7hPHUDLbNHJ3UPY9Sr3vKO0Ln0fqm0JTBIzr52muz+KQS7iXz6MgY7m8uKIRpHyL1EKWyQ8/gX7pHK7uXqwbl8guXycyfAi0CJX8Gh41xa49wPQ+H5ndJPaIwtDEQT77F3+NYTaJOaIcnY7ywgsXmRqYYHrvBIVGgVcuzbNVgPc9OEhHD6xsV/jxzee5/uIPiBhV3vWrv8+7nnicne/+lJJhMjE6TpMi2UwRoRbi/K3b1Csi3S43PkOiYQgEtQBvfvIoi7NJHEqAtYUiie4QqVyK3GwJW8jF6tYOnUqY2a1t3O4A2xrY83XW8zoet8TM5r+utfKvoXpzCIJwWRCEm4Ig3BYE4Xfu+gcEQbgkCMKyIAjfEATBdtdvv2sv3433/4s3YRm0JTeXl+pEAt3MLe2SLRUxxDLhsJuIEuLgRBdxXwcd/hipUomMtsmAJPHWw8NorQwbuXXW0yl0Q2Wwd4igAJ0+B4lEnG3DYDuqkAxV+Z+zz/HF2Xl+429+wuIP1ohGvMzeXKJebDI02UVYihAe8WIX6vT6I4iGRagrQbukszu3y/zcIqPBGPXWLvlUlZ88c5WfvHyRHsnD1HCAh967nxPj/bjSeeaNBslVgZev3kCra5w8M82Vc3McPtSJ2Q7htitMjMe5ef4yz8/v0NhZ5SW9QDDk44vffAbF5cHrtFBNhRdeXiCDjUtXbnD8oTO8eGWGsu7B0C2efXmZX/n5N3HsnhEymTR/+vnvoRoS/d1x2lqdUr2JW1H48Uuvsby2xZFDnewd60ORoaIH+Mr3niOXaXBtJs3JM5PIso2GqrOdK3JwNMQvvOUAWj7N0uoSPq+bR47sISA22dPfw2h/BLvdzszCInafk2RqE9MQ8boC5DIFwr4W+/f347Q1ef/73saR+/Zgt/twSn5Cdi+teh2vzUahWmXXsoi7vTRFk4/80mPsVJdwR8P8/L1H+PD0AezOBkGHD0s1GI546XWLOEUNt6Qz1hsl5nHgs9fZnC8T8onsHY+jqXaGvWGyzTo3izlaNjeCJ0Sq0SZX0wj2dGLze18/etfQ8AhOos4g+XSeSrVA54AHXZBIrqUYHhykrhc4dmCMgNjgUF+YAa9Mu1kild4kU2hQ1z0443EquRzztxYoNxWmj0/TEwnS4Q/QKNfpGh4Bp8nowDgZo0qbOn3D4+w/NM1udoNv/uCHOMUgp88c5ejUFCff8X5cIYVEdwep7Drf/N4zhEIRXE47gYCPHzz7HSJxP+ncJpVanbYh44slSG/VefyxR8ATwNPp49jpw7RFg62mQvjwNOWl2yS3U2wWVpBKO+Sfe4V/uPAT1EKGVC7PH3/+TynkLHoTQVxOJ5GoD49XYSezy/xqhouXZqirOpak4A0FEG120Oq88MI/UV9eY7uUZueZl4m94c3s+gNogon4pvcRf8MHcY734jOTeGcXMJ/5BjZrCPuZxygll5n/xtdYeHaWnddeYzuVRNBtbGhNxh86gfB3T6PsOQwNHcPjJ/7Ie2kRRHCCZ/AUT37yM2Brc+XcLHeWily7ss1LP77OUCzOZ377WYaGNTqDAd7z1GEk9y6l3TwLl+fpEGXec88Ab3zyGK6AB2e/yWD3FFubc/zo3BxXnjmLKbl58k9+h/e9421Uyxb1rRjIfubTC0yODPBwJIYgGrjCIlY1w0ojxVf//ix2T5yqUCE44iRdyxAMBajJMm0RqpUmJUXn+PQeWvUtgloOy2dn30gCrd78l6DzXw/kgAo8YFnWAWAKeKMgCMeBzwJ/YlnWMLALfPBu/geB3bv+P7mb98+LINKs5Ym43CxvrrK+VSckiji9JjHRjTsW4XtnZyg2DW7tlOnqEjnV2cODp0OoJXC4oZKrYTgNdIeLGD704i5aM48AFJIFWNGwI7K/f5LRSTtP/fw48X43xaJBu+XFbq9jKlAuViHjoGBKyAGRsrvN7VeXsEkOHFEHG1mVnqiD+UIFdXWXAAKnJscp2gJcX1kis1GhElJI90msplIIikW7GUI0JTbvrOKw+1lbXOVAbyday8JmmlhOB3qzxVjvAPlCldFEmAeHu5lMeKi1mqQzAi8tZVnKu/AEXYT1ClHLw83lO8R8Mm8+eZTRvhHUvIXu8BFJeOjrdNOo5vHGXcS8vWS2tsk2LZ5/ZRGvf4SZ28sYgo12q4Ykeqjodq7crnL5tR0mJiYQLZ14TGZ1a5fVjRxRSWFAtyG6PNxIJdkX66BRqWAUq+SqOpLip1AoMLPaep2ySythSj56I1HOnJ7i/O0Cn/nTb/KDF3fYamo4xQKbZZ2IvxOfTcVsKvSEg6xvp3HZXOQ27/Df3/sgTzzQi6ruUtzKsUcaxSuanDg0SrfkQPR4cStNnnrPE0QaLTZXsrRyTf77r70Xw1T41vefJ9/KU5LsZPO7mE0vlimwvJFEQsVpt3FnfYPunk5cDgtFEdipt8npLRx2gzIGpuRAzeQ4cXAvbbOEz+Vku5Tj3odOsVFIIfV2EYr3YNkNkgWFUiNPvVnjgccfQBcCdHTEuDB/m2ZNwmZvsm+yCytiw5EXWd5YxjQETMXP4kYaxS2RTzd54+lJ2paBITpwqjbyG1sEgwn83U76QoPsGRuhVq+/PmPVdFxuL0+/cI6nf/wiVzcKCHaFWqNN2chxZ2sdnTY767s060WMepvxU4+Q2djgxOM/SzGp4zLsmO4425tLXP2DT/HuR4+i+FwUt7L09XVSzGawLIO21sJhEwn5XSQ6AvT2h8lkC1y7vsLXf3SeH790mZvpBtHB/Xz72Ys89b5HuHrlMpWFDdxdfbSe/yrW819F3rsPPTaAqW1TVCsI2yvom68gDL2bvvf8OoNDexh7y5sIPXAMj+Th+uoMVy8mOXB4H+I+PzZBQnX5aHb0YVpOJKWN1RLQ0y+DIeHVa2RMiQN7DnH/iRPcd+8AnUqZi199O7U7JcrVbbZTaZRiPw0VPvqRn+MNR/rZfzzEf/v0X1HcrXD7/CZqYw2bM0xiyOLc1Zf4r7/4cb7+V//A2fkNVpe36OiOcHhwmiceeYTOsMQNTWCjskvyBwUGor2osoOmU8EjGCRiURKuLiZdcSpFDX+Xnd1Sk4ePTfHYGw5jtor09HRTb8osZlKcPXcHWzT0bwfk1utSu2sqdy8LeAD41l3/l4G33dXfetfmbvzBuwTO/3scR8AmelFbBvumQhw5MkKVBtnVPJY7yOrOJi1V55nvvkzQplBY1Tg4NUhysY7NBB9dNJ1uNsUWV24vsLO5jk9yIcVjrKe2EEMKzbCNSqvAyHCUg4cP0Fa9VMp2VpI5Go0ax+8/yT9+Y4aNmskPF6/w0pUFPvmt1wjoPWw3LSIxgYDXy/vfMsbtjRxvPN7DU+8/ypsePkZ2rUgunaart59S3c4ffe5ldtN1bt4qkjLrlEpFslmdZrnKgb0d9I53sZHeoScW4i0n9nJmZJKBSCebzRatjRy7pkoxmKPoAlOJEbRy/PmHHmPctcXESJzKdo3bKxk8+NjcyhAdU/jwx/+EH7w2z/aOE7Gi8yvvOkG1orORtXCIeV68to1QlxAEgecvXuWla0ssLa1wz/ETtFtVMukkwz0OTh47zAsvXqHYMMhkG/gjHcwmc6RaFjWbk83NHFrDRPR48OPFnmsiWXVG+qOEAglcrhrvfusZTk3vpSPcZHZphc/99T8x4HFzaGKAsYSXbo+DtbSHI+M6uVqFcCSI6m+xvL2NIxRkeCDAxJ5+zl6uc+PsNar2NstuB6a7wb4OL720SOZSbM7tkMwK3Lg+x0KuyaMP30Oss5M//tqz9MZceMUmfZEAuWQRyXJh2fJIgojfGwBLfJ3w2HRy8+YSpm6jUbfw4kRuCbhFL06bl/zOLo6Aj9RukoX1EuHuPkzZRq5Yx+fr4OKlGQq5PIl4P2q5TE88QbGs8f1/eIlm2SJT2qGarfOOJ/aR6AiiN1VmLl9HdWTZ0QQ6EsO43BLtdoNaqU5v5+t/h16+8irrs3P0PfUG/vxzX6CpmigVEEJuNlNp2i0NyTLxOx34nF7e986389n/+lu0dwuIusmrr95GbsfILJSwNV8/PvjC5U2ikQDt2qtcffZpvvfVv+btn/gYBz/wYUSPk2o5RRkbQU3gU//xN3jnY29AtFoIgoaumyiSDUGQMNoahmFiGALNVhu338PQ6Ah2d4yl7Rw3N1a5tJOnsFWiZphkKmm++Hd/RK0Br3zvOyx+4UvI2DD/6WnWKrtUKhXUKxeR16+h7n0b9l/4HUrHziC64vgjLhJhB7JYxqeLuEUv/OivUL73RdyVNobiom6YCAoYlRoL/+UD7PG5CQSHyC3dJtDcZO3ij/m1X34/6aad/ffupbpbJ+btYVFbZs++QW7N3iapN7ApEh/9yC/Q0+kn7NERXV7aGGTyO2zuLJNMb/Lsi+e4PreAKcuspta4c3uOrbUMiytFVneb1P0R8oej7DQN4qpBdaPAzE6K3GaRZH6HQtBCc2uEgwoHR7twmbA1m6LDFUUtFwh2ygyEEtz7M0fwmc5/OyAHEARBEgThBpAFngNWgJJlWfrdlBTwvzrzCWAT4G68DIT/ufEtC2SbgS8IdkXBaNZptVW6oz2sJ1M0jDaaYXJo3xgODCSlzSuXXsPV7WWtVKfayiCJLTweD6YQ4NaNJRy2INl6i66uLvrHelCCKr2RILZim/qdGpX6Dq1Wk7Yho6k2zp69Qu9QiGt3FslrAWbTJeKywuxGEq/bye1MjeWtFY6Nd7JnJIzHp7BWWKRKg6phMhpOsDG/xupcErVt49p8BTHoYX2jiDfewepqCodiY6AvSnJrFWfQhcfnxNCKBN12DkyMsZ7ZZqynB1/Yzb17jjHeMYzazHPszDBX52bZrLRZXSmxZpgoPi8Th/rI5RtItSAf/+g7ef8jp3C2s0wd6CNd2EQRwOXy8cA9+7B7Q+RaTSxZxC258Ut+nE4nN2/eIBT0EwqFeOdbH6bZVJk6dApRceH1+NjJFJBdAVqyg3R1h+mjB3A4BRa3VimVVYqiTLlhMb+ZI7mSxxlwcOHmDWbnF+mKhOjZN8WDh/cyPB3DF3RSLFVoSxa6VCVVaBDx2vi5k37amkXYGcRt1Ai73fzdd14h7Sxzz9gx0qU6oaiPbZvEmCdKRLDR7ZCJJGIYloP5+TtsF8qkt1N0J9x4wiHKhSKmbidvCDQUGWxOmnWRankXh2LDNE1008Bud+J0uNAMHcuyMIQKKE0kpY2dFiM9QZwukVJBx2GLkc4uUGuaJJMZlhY3cMoBdnayzM6vY7Mp5Ip1ajUT+90ahYJKaqtErVHlytXrmKZJ3B/iyLEJanUVBRnDhFyphMsbQbaJ+H0+9gwP0tnXg8vl486tW+R3irQbbfLpbQRBIhQKEfD5EYDugT42UknARBAsXG4vjoANJBGnQ6QjZqder+JwOclm0pw6Os1urUQxu83//MRnkAbizFyd5Y1/8CXGztzPgfseIpPOYlkWkixjCgLNhkqj3qbZ0F5/XwWZRqNBS2sjyBK1SoFMOoNityM5ZHSvnRdfeI4HH3ucW3cWGUnsxekNkCossbm0SW19Ed0woVIF0UKMRTD0NPbKRWRBIGAUkUvbtDJJ7txaxxKjZLcL6LEE1clxxIaKXt3BxEFAjkPbhmvkXYx95D9xMhIj087ic7pJhAMcmx7l6vWL3LPnAKsbqwj2AJFogOmJLuo7G/g7wpRKJXRE8qUyqtpk7949pLNlHC4vtWqDUikPlo6ugWFYVKtVPH4nuq6xsrSOhYtKW+XslSSdXieZ7QLpXIWeoQGCsTChrjiyAn6bk7gnQECQsdfbpFLbpHYz3J65yUSkD0O0aFk1krNzlKj+2wK5ZVmGZVlTQDdwFBj/V1f434ggCL8kCMJVQRCumpaBaFPIF0REyUs2Uybo9LOwlMbmsLNbLONx28AsYVLnrSdPMTUxhqI4qeY3cMsRwoKXECZdfQ7MyAA/vHydtqEjOUTMWp1ow4WatQh0e0jqm/T3DuHzakwe9nLoiIt3vP1eahU7Lk8HuVwW2RHEFnZwYnqEU91h9nT00NPh4uK5VYaGB3mgd4Lx/gnsloVX1CnLFlJvJ454CG+PHSE0QMRRwWX5yS6uMLq/k+HRcQrbGd548l7CMT+zm+tkxDKzWykSgx76wkH6R2N0+UTK6gaegEVPZwdORSbR6+fhkxOspXfYM7AHS2yi5Hc5tq+bTOkqz5+9QMkq8Pb3HmenmCdbDLF3ogO7ukFfzE+tUcFpWGhtnVJbpWhqiJaJoiiUqk2yxSZ/9hdf43s/OsvXv/tDVFWjVdepNZps55rkGxZVI8JzL8+R23Vy6dYubqPKen2Tp84cxDTbiDaLuK+T8sY2QYdMsViklsrwTzMzbKSbtFpFvv03P4Oa19nj9xFwH6TWbvF0MkeXy0vFsOMOB/D6INHl58L5Lf72J2fZ2zXNrqLy5R/d5pWtNILgItHThVfNE/TIWIqEbJcplxqsLrXY2qwQCAUptQoM1OocDELYWcLEYqA3Sq1aRJFk6k2Vwm4RUZEwDB3D0tAFB7LNT6lkoTdMqLZJxLrpjLuoVLao7Srs7NRQGwLF7TLtahuPx8NO1sTv97O+VUU3FIYm+qhWmghaFMOh8ML5FYKdCUzFYt94hI2bNxkOy/gUFx2RODO3r/Pa7DqXZmZ427veyemj0zxz7hxP/8anePTkUTpiXcyvbXLnwhWcDjdetxsRE5fbzfnLF5hLbvC7n/8LkoUWiytLZAp1dNNOQxW5cn2GjliYcFDEodhYWa5SV234vFFcPgfX/vgvufzVL/L3v/kUP/raM1xe2CAU7SZTKFGsNdksNqnWVEq1Bq22hWaBqjaxyXZkwYap6aA3ccsSslki7LYxPNqJ4pP45B9+gVjPXtZzy3zuG8/Qjp1Ei/horMzjGtvPnqlJbD4fLkcMqWs/Zq7AKx99lIuf+Aiff+r/wuFycOH8a6SraRbXfsrC5ZssXGrAnoOIY8ewqWWKLMHubYqWBR0PYPvPf8kev0Csu5s7Gwtka3XyrTrJ2gJtn5/J3jEOex0cslsI1RLLqW0enD7GeqqAqgs4/UG28yXadYtKPs+Byf1MHZhAa+TQ2xaNukalVEcUTBSb9DpxeUOjVtzC2G7TdNUw/G7mrTo1l4Fa3iVfbjAYjLK+uEqzppNWDbaSJUSXE58nyMTQELGYC1fDRk/CQ71lEIk7/tV4+v9p+6FlWSXgJeAEEBAEQb4b6ga27upbQM9dsJYBP1D4fxnrry3LOmxZ1mFJktF00FBJbe5StuzksiVWayWaoorX6cfUKiT6fahSi9nmPD+dKzG3PsOjJ96CvVQB2U7D5kFvmjjGHIQPBekPu8nmsyyfX+bC6iyrZY2zl67RlxgkmZzn0HQ3g+MR9u0ZZmvjGh09FnpjmwFPjH0hi8PjQVrZNRTNpKGmGBmexBFwEjVUctk7rO/skirmkNxwp7xC3TIwt2uMa3amIyb3HprAsKf51LsfJ9xtcmd5kZ3tGju31zncv5fFhRobNShYHp5+8YeMBzvZqOYI6zLRQD/DgwmG+0ScnjDppoe/+tbLHNt/mssLF7l3v5+CWWRyaopGPsw9Bycpp6qs314h6DMwlRVagsojp4fQCGB3CRhOgVarjc0y8FgaXZ3xu7MqkUpDpGlGqLQVipUGYb8bRVGQZPC5A6j1Fm2riuU02a7skBjs4dqmSG7JpFIyqAs2bN4aq8tpTt9/Lw+96T6iXX2kFZXPPnGaTtGBCnz+z35EsEvgRllmYX0GRZW4elEmZBQ5daIbv9hicWGFUt2OGUiTl02+fP1lzp5N0tYV7tt/kJ8uzpNzKBy7/wSd/jbHHzjJZF+Eek3g2s4WTTWPzRmmNzzBlWqL82slsgUnNg2mpkbx+Rw4HA4URUHXBLQ2YEk47G78loVRLuMPuPD1+Ki5qqxsLNPQBPYeGsAXCSBYLQStysRoB0G3SUBu4RTB5wBFgL17e3nh7Cxq2w7tPIh2OrvCjI+FSa+vU1bhA+/4ZXrDDTzxOu2dNMf2DRIP+5ic3Ms3vvlt7qytYJVaOO+ZJDYQRkNn7dptynYDt9tNu92i2qhT1zS64zFmFtZZSRWZmt7P1PgY8ZBENGQRjyvsmeylsJMlbOtiYnwfRWObgQP3cOpXfo17n/h5ph9/O7/wmT9CKboJDnhoJJM0qxUUNLRWA0UAU5TQDQFkBc2wcLnt1Ot1yoUypWwJwebFGwyxZ+8oxWyJ/O00mUadqqqxvrXB+N4pstVtVlNlXltcJL/UpNnrYPFyknYTBLeI4fJg+W1MDiVIKCYf+u2PsbC1TrWm4bUs/IrEl770DYb9PowDD2C2yxjyNqEXfsLqX36BUG6Wnef/krU//j/44jd+TO9IP6HuTjRFZmVjBZfNyz3xQabDDSoOFVtvD4sC5NfKvHx9hoBDoVHeRW+0CPvCnDyyjxNHxmlUMpQrG0S7PaSyO1S0FpooEvL4sDllRLtIdzzMB95+P7/+wXHcsoRNUbhnj4fc0jY3Ly1jT5rkdur0R/wIxQpGpY2yXiHSkGk0KuRbRVKZFF5BJ1luc6y7i7Vq+98OyAVBiAqCELirO4GHgPm7gP7Ou2nvB75/V3/6rs3d+IuWZVn/bA1M+jplju8Psn8yiNtpMNLXy5E9Lrq8HrRKg8PhbmgpmDL4dYHeYR8djmH+x9mnyZoWUt1C3KkjSnX6I2EOTO5lI1Ui3jVE99QYsUgPfYcSTI0eoFHViYcj7OkYoKvRQFpWiXbF2BsNM94b4/hRP7JNo16vs6+nj5lCkkeHp0nNLVH0Q7Qrxk5TI1TScDn9lOsmhwb24dAdrDcrCEWdnk43N3IlOqQObrazYAQIh2Js51JsFupUynmeeGKYcZ+ftcV1bNU+Gj4PzZRBpCfG3EKWV1+9RnePl2Jug9mZFU5NH2O3muXQ+DSxSB9O0c7GjasoLpVCocD6dpabC9uMDUyQ8B9E1jXMtptvXLiEbAYQy00O9EZ495v2MtblILm5S7VlYpcNJKmNbpaRBQf9A10UchkqlTJmW8DjEQmGOmg3ZbRSC1GwsVnIs9yoozs1XlpapUOwEbX7cDhabOXXSRd38Ec9OCU3n/vbH7JdLCCrYTZubOP2+NgT1egc8dAZs3AoOnktwq0rN9lzdIylso7W3mFrXaRbjRPyBKjlq/ziG0fxSw0euXeQY34fsy+dZ2C0H1GtcH0lTaXdZL83ijPgwmWYRIbjRBQXI10dFPQGT77tDWwsr5Ip1GnVDDRNx23Xsdo1bIpEW1Up1Jv4IyFOHhmlUStjqF1ktpsYONkttFi5tczYvj1EAnZK+SybRZWtpoxiggeDie44ZiVLf8KHIJVI9IR4+55xugU7E3oPb9z7ACc9/Vy6eY6a4ef8xVmeevJBdpJ5Xru9yOZOgVajRrlQ49SRfcw/fY7hgW7+5ivfZ+rUFNVUg5ZdxJLaFKsNDu2ZRq3lePuR+4jEorwl0cVffvZXODMwwEfe9m42N1TmriQZGt3P3NYqblcEQ23x8tnv8+0//wKXLv+UZ5/+Dl/++H/lyf/2CTq8PSi6jlO0Y7p82GUFEQFBEDB1A9kmEQ64qVWbSHY7lk1ht6FTyJdYXlwnGrZTrdpoiU3SeZ2V5DKvzafQGzWSi3nsfhG/w81Mcg7WZIYefxT/8AB0dCMaaapf+RpOoQMtcQ85bZd+j5tSXSPk7EXQwzz15BmEgSAGTYRzZ8n9ze/RWq7T8am/hvAR7O0dJt/1IT7xmz9PKldjS9tFE6M4LA2n4mZhZZ41tUbLE+U75y5jNAVsDjuCACoaqiYSDIVxOyRazSKZ9DaNhonYcBBzSnjdLnIbacJeP/ldHaddRBY0PO4gO+UG+ZrJWirLsRPTGM4+DIdM3+ED4FDJrqcRkhps6URcUepjblZbaZLrWUwrzHZbI6/LJPo68fplxsR/2x55J/CSIAi3gCvAc5Zl/RD4LeCjgiAs83oP/It3878IhO/6Pwr8p3+pgN0uMdgfJB6x47XVmBwI4ZDaDHUPIDer3D8+gn3AQbdP4cTACJroILW9xUZxEwOJhVSJ6ysZ1qt10F1Y+Qr13TJOn4fF1VU2t7ZpiwY/PX+dxYVZHLqJ3+HlpzeuIHiDbDkaOFoSvqbJ6YlJHraFeO+Ze+iLR3HZTN766DEavjr37Z8mu2jwzas/RZd4vUcpSDjqFm29yWZmjbe86zRln8yFZp6V1RRDI4N8+6VLlObTpG5vIOs+guE4C1sL9NgUEobEGx4+itGucu6VZdqSwA9/dA2XU6FRb7O5WiPqD3PP4S4URebaa7NsbNxhbjnPwZFOjk8dplBTOXtuht5Ok9/9L7/D/v2j1LV59h3aizPiRV1NMhoL0z9op6FWuHV7lf6xPro6FaanxxBFCb/0YSNdAAAgAElEQVQ3TofTh+aU6A54+M+/8jN0JUIoisLiQpp8MUmzussvf+jnCPgdPHDyJB96xyg/+9RxOnuCeAJ1IokedAFMq8Xc3C2q5Qr+aoW620feklnZzkDIx/p6irGRMVy6iac7TjJfoaAa7FQbfO0rV3nzkRMMKXE8/hjfWFqjS3Vy75lD7PM4ESp1pK0q/7A5wwd+9SnWU5sIhu31Q4YcMh0ROzSaLOXzrKwniYYdLG5kCThMZl67RLTTi9dtEoq4cUt1ooEYNruLuqqjtTQibj/lQoYbt+ZwC93kikmiCTv9w1FQWgyMx1ldWkQMejBVk0DQRSzsIRp0EA47MMU6jWqVaMjN2Gjw9Y+kUEctq9xZXqNQzDG7k0ZqK+QrFd505igLyVkmD3SSzW1hV+yIfi9lvU25WUfVdK68eh21LSDa/OR2CxyLd5GwB9jYWuPlKz/l4fHHCQVLxEWD5eVtvvrlz+OWbPzG7/8ByWKVUPcBZuZuE/R60Zs6IW8nsqRQLxbYmLmBzVLYTtd49g+/wujhe5l6z3u4c+cqx44dRFRkdN3EIUvYRAFFEGm2VPz+ILVqA8sSsDskBNmib6if556/RqLbh6UKbOfLyA4PyUKRxZUNDhw4SG/nILFoB/0jQZbvzOEZmcY8OAXxDnYtO6GP/iH2X/5Nun/xA3Q88FayTQN3WMaMaJQViYg/gdxoMPuPX6bS3UXnL30N6QO/gWwWUM05gso0re4YTsPJM2fPsb97klMJkY11jYvzV3F3dmO4O9jeLPF/U/dm0ZaeV3nu87frX32/9lpr9231pWpVJalU6izZkmXZxqaxYxgGm5BAcgYknIRcnIMOBAiNCeQkcAYBgslIbAM2WLZs2WpKXZVUvapq165du+9W37f/Wn97Lsy5PlzkAl9+87v45tUz5pzje+d7aGqOaDzE5KFpBNEGV8ajeNjd3qFvDFElkUg4hWL76PY6BGN+JKmPL5ig1m5Sq9XQ/DHCsRTdoU690UWVvMwlkjTqZUxrwLnkKK7R5WI3j7qQ5YrYwz07wzffvEZB6+H3jSNGA8TaNqKuYPphd2mdtU6fvc29/3Ugd133tuu6x13XPeq67mHXdX/t7+Mbrus+6LrunOu6P+q67vDv44O/P8/9/f3G/98bkiSyV6zg8cbJpEeZnxLJRAfsnz1IYFSma+UYtOrs7hXYKeaxDIt2rc2p84+iBFSaYoe+O8CbilLId3FaAzrdPl5fELtlcTwwxt2NBgdiGqQX2DDvkdSyDDaGrC7lmIyK9BotMn2VbHSCL118k7bf4Gg2Q7HbZG0zz6OzR3l57z5PJWL0d/vYwFY+z/17y/Q1kUKnQMIfQu60ScxksC7WUeNjbG6s4lRsAqMJIlOj5HWdrtzlvevryAOF9UoTvVkhOxVgYS7OZ37kCWLxIOWWTt+ycBSTlZUVKnt9sLscnZ9grTJg/d46slfh1Vcvcu3eNpHYFK5lcWfxNd69+DrBYIZ8roFebtOUHFIZmbA6ysdfOE+hVEHXBVZzLu9c28BEwrLqDJCICBYLUwn+4M++QqdZp6v3yE5NYOOlr8q8++YFzhxY4O9e/h4eX5ByRWP/+DS//PM/Ta60hAtkMvOcffhRYikvm2stHEWj3zbQh7BqajwwP8PFq1cpdExGsyrxKLhGl/HMFKIA//Ubr/NH3/0r3n5/m5jXz42dHN2uxUvv3+HWWp1tf5iRQJpvXPw+c/OT3L51D3/AgzcoUbbaTGk+AqaFVe/S6w9xAzYhC4Rml+t3yji6SzHfAi3J/UqNoSsgOC6OZNOqV/EH4mxt9LF6NZ7/2CF6PYdOR2Joaly9vsnEaJb11VWcSJSZ2XFc26Hf1TGGNuVam4XjR9jZqSPZLv1GD58r4jFcbMPCo6jo9Qoe0eL5qYNY2x0u3NrkzloNTQvRaXZQBgaHxsaJiAoJzYdH1FhZWeGtN9/k3/3iT3Pq2fN8/nM/yq/+/GfZF/Zw9qiXi2+tsXllm4995mMwTHJnrYIj+wgqKqvLq4xEYgzaTXZWN9hY2cYfipNvGliWQ6VY51/95v9B+lwGyV+nfe81rFqRraUlNEFAlUSCAT+RcBDBtjAGNrquEwiEUBQFRZEQbGh3K3i0BAoDGrUmstfL3m4ebyiKLkmUm1WS6XGOnDnG5EwYubzGpb/472hIOI0S2lf/kHbpHpYkouCjW7nP2P55ZFumuLHNG99+lTvba3zjK/8TZWuP8F6dtlOiTw25N4bnOxepffQZhL6ffOkGX/7Fz3Pt3b/iF7/0FSYPxpmfWEASFXaqu8SCHvqDIXqvT61QAMcll8tjGTYj8QQqIq1aH8OyUNwhk7NZtvM1FmbTVBp1wrERDixM0qy3EAQJQXCJR0YJygFsfcj2zhb0LPLNLlogiNuXMByHgtGhuVdkJhHj0CDKhSvXUEseljd3kAID2rUGI7ERnDr4H5j9B4P8H4Wy83d/99dffPrxedLxIKLZwRHGoNuiVdxgb7vKiY+fZ2elQHI4Rm+vDtEhE+MTXFu6iW40ePCJk4TVILrTw+p7aIg9LFx6dZ26YSDFI/SbBcqShFfqYJkHeOXWTaaPe3koGEdTA6RmpukIJnuNAlJW5vKtTRxrQCsssF9Ocm/3HlMhgb6q4NvvQZWCLERGiODhxz/yAjsrdzibPUU1t8PmUGd6dIz7a9sMnSaGlSEzqtDrGyTDcX7yU09wY2mFbCDIykDErFp4JtJ02lV61RqGrHJvo8bWTgW9p+DVFE6fnmevVKE7kJkbS3IvV2cgF3ny5EcQRQfvXo2xI0dIjIZZvL1KrxciX1imbdn89Cc/w63FNWr9Pd67uoGj+ri5tMPP/viTrKyvMj11kJXVIoajMzRklstFjozFOTAzhSLB2ESSu7d3OH3wQa7dWcKQ+kynIqQCcSrtFSKeKd6+eYEDBw9z8swCtlRjL7/BaGaeR56cYXouTD2/TiTjQ68WOHXmESpDh1K1wepGg2QmQbnZRlQsbEVhXyjFOXLsre3RVxxcVaDd6hOcnqSVsEgupNnptxA6Ds12l93VFkMbGt0uoZ7I+EiGorePOhRpSUFO+z2s9wYooknTFTlxYJpSrUrO6GNhEZJlDo6n2X94kmpvQLHd5vT5Q3gDOsWqi89nUa1WSGdTSB6HfqvH3OgoG70OAUmk2WkSD0TIZJIU213GAxLNskU06SM7PoFsQyYZw/JIWEChbzEZ8VOQO0TDUc49OYvRaNPsV9GCMrblEPT7CCei1Fs13IGf3/mTX2UimmX52veYeOI5pF6eeNzk3/ynv+OP//IGdcUkSAIhvEmMBGrMx1ahjis69CyXWrONP+Qjt1slFI2SyWQJp6fYN5ai17fIZGPUlm/TWS5TbVbwKgrB5AgXrt/GEwki2wICICCiKX/f8gsSoiRhWkNkQUVSHCxbwqs4+L0RdmsVosEIoizjwSQeDKOYAiePzjOSjbN36RIJf4JQLMlwPoV9/ToBy4/i1dADPpzXvo7HE+NPXn6J2ckJooksC8kop86dZObQURqnFoi6fgZqB239Ns5jn8V2NPzuHubmfd5ce5uvv1rixOnzzE0FkHo/SHuATkzIsFXPk47Fya9v4PMH8AWjNEoV4sEgxmBAMBQkEAkRVoK8/Mp7WK6XA/sneP/WDqVimZNHshQKDfr9AYLkMOjZpAISgmBQaLaJy2FWy9tUO1WmPHFaUpeDgQTF/oBQSKanqYyNj7JV3Wb/+Bg9wcQUJGQtTKnUICTCjbXmD8/SrN/53d94cXJCpdNp0dLbxGNxBKdHbscmFZe49uYVxtMHuX37JsV+mMCkB39Ao1CqMzEygZ63KHea3Lm+TnQsxnquy8REGo8nQLVchpBLp+1g1G12821y1Rzddocff+whGkaP9YpJoFxlJrufoGGzbDc5YsUJRXy4FYUr9han5hZIdwNM+6JEO2HqVNBp0x8IfFBcJTY6xfW9JWLpGMubTd6/ucXPfO4xGi0TSdAJ+uIk0n5Uv4svGMBUBWK+JKJp0FYHmPaAYccgPZri3fdKpCNhNvJtPB6YnBlFHOoQ8VDsGVx+b5EXf+aLvPTKDQKGyMLhCMPQAMv0cn/lIsmReboDg5Q3wL3tGtEQaP4+jYZGq9/m3IMHEboVzp5O8+kPPcg3v/MqyWiGrmXw8ceneebYOHu1IZJm0RsI7J8KMRq1uHk3x7GTB7h1bQPHaeOJhWg1BjTNFvGoD5w6qWSI3EaRA9PT+NU2Vj/A3laZfQenyK0XEVQfGxt7NHsDGAiEFS+7hQ4nZ2NE1S6dhklP9PPuO9eYHImz1dVZSEW5t1Gl1Wxid7tcurrCA/vn6HY6NGp9/JEwY6MpjE6LbMBLxTaptyws26LbaZLwB7C8Mk1HRJU87FW79A2T88ePIRpQrdR56Mn9FIo7bO7qhIJ+BKGFogyJBIPcvLLH1FSa/dNjdMs5RlJTNHQTo+oyPjvB2uo2wfgIq+v3EAyb3XKLqX0+ZEPGUUySip9oIIhp6SRiSfSeiTdg8t56nkqrjVccsFUu4vVFmUjO4ZVAG+qIho3luMRTCq++9DKeqJczDz/CT3zml/jGV77Kv/uDt2loMcL2gJ/7+R+hoZc4Gpui2q3x0rffx9GiCKKAJAiMJ0K4js3swhxHZsZ59a3X2dsr88T5s5x+6jEa5QonDp1GGB8hnRwlFB+DgMxrb7xPMhHBGg6QAY+oEIqFEEUVNSAjWAauITBwBszOz7C9W0KTodl36Q87yHKM6XQQo7lHvmUgOg6Pn3uelUtvMHniERKzk0gPHENqtzHPHkbbWAO/h873/xJxr4Hn2Sf4v//ob0mPCrTW25j2EL8RIHL2BGFfBsQwrlRGqVUZJjIETIl27012Xr1IVU2RiHlp1TfRhwNG9yW5ffU2R9JzeJUO6ViGamMPFB8njx0BoU+nYiKKDs1+k729HoLbJ9/Is7nbJxByMAUJe+BiDW1GUlE8PgddtwgFJATLplAfkB5L4JgSFb3M+MQk2+sFCi2LrOijMuyzupbD4/MzLHdwNZdQMsjdtW28lkIg5kUWDLRoktvLW+Tq9g8PyL/0O7/54pmjo4xEA5yYm6dbqPKpT5/nzfd32W5WefDR01y+cZ3Hj3yYfivHzfUejUGN1fU+Dx49SKteQHIFjp89we5eGZ8ks7dRoVjaJpWM062LjEzMI5bWaQaPInfK/KvHHqVZrONRRmitLeEdy9BWDb67cZ9Ph/dxpbyDqMNuv0+pOMQXCjC0etzP9Xk7d4/NnkOjLqJ5NYKCB6NbpTm0EUSIjqW4dquCgsDCtMLJk6co5W7z1JMPs7Nb5NKVqwTVAMXqLpnxOL1mG4cY6bDJpcUc/+JHP8faxlt4fH4s3UOt0SYUt4gpcQQjS722iceps1tWuLyzjuGC6Lo8cOoE12+sMD83gyg2SKRH8Wo1xrJHaOlttnaL7OR1KtUu/pjCA2NjrOQayIbJmdNpTk+k2C5sIYVj/OSnf4Srtz8gGskQ9svMTKdZy22hiCpnTo6iiV4KLZe5bIgD+8a4dWsdFQ+tWp/xzBz5nSp6z6LazNM32hS2wqQyfoKaDyGg4bdF6kaTjmVz7kCcRtuike+xMDdK1KNwYbXJW1/9Rb5/vUosZrJR6dN0XJrVAR5vkG5DBws8Po1WV8dydfYdGGWvUKM1BBeRydEYpu6y22tSr3QJR+NUm2UCwSA+1cfu6go2QyYmYjhCj35viIRJIOAhGAzSbtVRFQ/HD48xFoqydm+JI0ceYn3pKpdXO7Qbbar39sjOzZDOhIlHvCzMTDCTTVApFoiPpKk0W8zHUkxksxi2gSqq5Iu7xCM+djodYiE/yewo49MzlKs1aqU6erfPwsQEri0ADoJX4a9fu0LO0OjqJpkxL+mxGR46s8DLF9Z58Nhh1lYuYnd9PPbQYVIj8yzuFqh02qiyQLdrITg9vB4BW9CpG3V67S6K6KFb2CMd1ihs59ktNBiJhTHyRVbyZSQF3r9+i5FMClwLwXXRFBlZEfAFvKiaTLfdxhyC5RhUWi1sEwJeL6LVoOfEOD7nx9DbNAcBvBGJZnvA9EySo2ceI7x/Dml+H5bsxQnEUV+9QG2piPDcC4TyuxiKD8/+DzFcf5lcw4MrahyaPsbDT5xEnZ/HVgMYkov3yiuYQ/CMnEFXLDTvES6+/BuUehreoEC9U6fbtbl0c5nj+xaIxAx2dR2P5UXQ2txfbYFHRLAU8rkWHi1Af+jgCXnw+GSaZR+nH9xHLAitZo92x0SVfYiqxmRaQcGlWhGYGpUIh2JUyk1kxcWw2tS7A0xLolPucCyVoi0MGBsfo2sNCSWi5Eodyu02B2YWEHSLbs9mMGhjGi7nT5zj9ev3f3hA/ru/91svjqQFXNcmXyxR6Mrc215E9QTR9xzee2+JM4+d5Stfe5fTnxzn+gc7pDNphlYXv+qnajhMZiK8duEOqtFHioVYODLD1Ow4oUiMXrfHG1c2iAei3F/bZj4Twz8E02fwje9c42NnH6ThNbhx5wYTrpdiUGSvXKYe8jCdDdEqWayVOtxY28Lj9+JNBejutBEkATQIR20eOnKCA4Mwy1adfsegoZv0hi3iER/VZoN0JkYhv0OnY9DqSYTCYbarZRBkTpx6kNzuOiePnWJyfD8Rf4O7ixL+aJwDhyAUCjKd3se9uxd59sF5HEvjlYvLBDWNkt7jR55+iIA/yNK9D3jm6Se5f+8q9tClL8pUcjX6roI1tMht7/L4E0eZGnORbJnLt+8QD4kce+TDfHDzBmrCYHJkHqs/5Nd+96tMpFL0zW0cS+RvvnWdz3/8LHZvm9mpCRLpLK+/dY2HHzzKytp9Tp04x/3NFZLpCKIkMZLNcHflPobhoa8PsG2oVHOsbRawal32yg3S4STDoYuiRMm12tgBgam4h6Gg03Bc/vXP/Qif/ZX/xiPTk1QHFQQ3wNEHppClLrGUj0Q8QqVUpt226fRM7D50TBct6MN2DRLpBPVKB10W8YVHyJdyfPTMFFs7eWzF4czjB3DtPkOjSywUpVqu8PTZI4xEvKQSYWYnRxlPpcitbxAPJ+l0Nins5Rg5fJhjEzHiHoUmJqGQzJ2lJUQlQLFeIBMLkpAChMQuUz4NAS9+r4YruGBDs1FGReHAQ6ep5wv0Wg6727tguASUGD6vimjbSLJCKh3j6OE53rt0i6WVTfZNj5NSPdzYWmNEE/DKA751Y4cPP3aMVrXJ4+dP8J//nz+n0rdxEJFEF9OCsD+AoHoYDlq0LRePoGH2LdJBH0Izj2OKPPTCU9RvXqQThIMHHyRX2uHO0jqGY+L3aqiSjFdVEXGRZRklpOENBBA0L6lQku3KLvPjMWKhDM2ayNx+P7Vcns1cn+kHwtTKVQIJgd17Xj7x5GGMboGux4vP58MxXcS5owROPYAi9SB9Bvf4oyDZfOmX/nfaqRb1rRb5ao1nzj2Kb9hEqN5D7VfpJ0bQ9j2D7SqolsRALzHs9djeW6HRNvF4IpimxBOnHsMTULn9QZXDEzO8t3QZ00rQblY5PnMCUdMRsCmXmwSCYabHRml18gjugEw0hOqTUOQYxdIP/E5d2cfz54/j12x2SwZhv4hkuSiKRmJEJJnwoTcNcHzEx+IcPR2iVG1hSjZen8JoOMS+hUkqmzu4CujeIFgOT548w/Wbi8hJP1dv/xCZL//H3/71F3/l048hGzpyzIvYaGDrATZqFap6laqR4IPNZWLhFHfu5Cn1PIxPhMgXLZSQTH57k5CbxArKuGaIuODgE8vMRifJL25yOBOl1TNYzbd5ZH6Eu9tlPIEB1ZLAritgx226LYPltQrHDhzn5cUVjCBMCQH8oR4+K8ROq4PlS4LdI1/o4CigWxAfGaWwtIY8HFCVXQaNJiVXQ89t440pdGsCMg5377XwBRQSiQhLK2scnp/B4wsgmwLreys8+tgn+Iuvfp1EWODlC8v819/8v3j9wmv0OjZ3VmqIYQvZEdltr6GF99Msb9M322jBIAfSCd54b5X9B+f5/qtXcEWBgG8cr8/G644zEMsMC3UOn91Hp+7F7DU4c2oCyU3z8rtbKHKdrc0iYifK2IyCJEaYnVbwBC1y22XOHNrPT/7Ew6zv9dE8NvVanUaryf6Dx3jr7QtkJ2e5d+cW0XAQa9DHq3rZ3tojEAjT00UEySUc9jEYDBAdFSkWRxP9LJaKBAWB4qDJaChAqxkiMxvDjSrMei1KH9zmgYfnyBktdgqQHJFwBnBwIUvX6rKXa+JxFIaWSigcIaCJ2LqAXxEQBZNavYuquvgEqPd7jMVD6J0mghwBOUCvVUXzRgmFolQLZU6cGMPudUmkokhem1JtB8dyyY6mePWtm0zMjOMXp3nltSsExuOs7VV45MMHyG/UEA2JmeQYh2ciUC9wKD3HwGow7PQJBpOkR9LUWw18Hh+Vdg3NF+S7N99j0O1gug7BsJdsdoRe1yAZjqHJMsFwiNkDs9iayrUbdwknUniDfnyJUfTcMl2fF48lcnGxRNan4DLgy197DSE8iTVo4uJBFBx0Y4gqudSGLT7xsae5cv0mz547zXauwcd+9HM8/eyHicXC+CIJyoUyBw8+gzekcunSm6ys7+EJ+gkHgyiiRMgbQHAdQqofWVUoloqEozHimh9/esjB2Rghbxo33CJoKWzkOpga5HYHBDU/3baHs6fDbHdMAndXyX74SYYX3kBMBzEEjaHHQF28xvt/9jtMHTiE6PPz5S//ATvVGJ/56CGsho5XGWXyZBan1MI6/BRed56hZ4gp6MiyhK4a2L0bXL18j7XFCnFPnGdPHWLj/jW8pod4HFqyw6Dbx+iLjIzEub9yCa+cIhpLkM8VmZkeodPfRRCShKIhivktCrUq3Z5Kq90jm8lQanSYCvsZmwxxY3WXbGIC223RHFpIfpnluyXGpidwzTqlapN62SISC7BVrpIJp/A3DGrtOtG5NAgdoo7E+GSCu7k15o8doJlf4eZq/4cH5H/6R7/34hOJODfze1jtCh9//CwLMxMU+2UmRufodwp0aw6JaBRb6HPuzAF2ix3UoYRX7eCIKsVuC1cOMmxXGdUkhnWbNVenZQ1YXC9QLPdxJQ3FA4bZo9GPsysJTPt1FnWLnb0OW1s6K3ub+EYiGIU+e9t1LFtjqVpFEvxY/iGTqsKJhWkayoAvfPg4XqtHtTKkKtlsLucx0hoJr8Sh6VEOzxzi9uoq0eQUa1tl+rgsL7bQ+wK9YZeQD/r2EGMosLr0DpMzp1m6v8OJB6bpd5b5wgu/wL/84z/mwMgY127fZWZmHNeUSMQCjE+Mcfdek3goiFfr8OiJh7mxskU8M847b9zn+Nn9tIpDXrtyleeefJqtWovbNzZJjCRJpSOsrVe4eGuJH/vIIziyxCee2U928iDf/s571FsNvH6ZmYlpHjpzluuLd/hgcZnxzBi26OJoPkotLzev3yObiiI7dSZnD9Fulkmmx1he30ZUfBTzNTAcRkeSxFMajtajbwlsbRQZHY8xko1i2Da9toUiS+j9NouLOXyKSmJ2isXluzw8GuNCoU5SFhg0ZYIhkX63Tz5fxxZlbFuj2e1gqQKOYaD4bKamxyhU26iCgjfgRxEG9NsytWGbRl9BN20swWV0PEZI6uHzC4yPjhDxOIxPxrFMA9MYUqiWuL/eYmVtl0997hPcWdmi2MtxZGEG1XY4feYw9++t0mm4dAyHeMyhNdDxawrDdo3uwCCQHCOshAlHg5jmEL/Hy7Cikx+20OIaakTl0JFDbG3fRxIsbMOkX+8zPTpOt9PngcPzdAoFbt1fZSqTQQvFcdsVdBH0voGmyTzz+AxvLpaIJrw0GyKoBqYloJs6kqxgDAdk4iMEggKBuEix1GNneRs5EiP/wS0+8sLTvP/K3zGeOcDc6SkG6RCXX/kWZx55nFfffR1vIEQymkDvGoTjcaRaj1QqgaOKOEqAqCfIvv3z3Ll/A0Hyk2+2OHf0MOuFLbrmgEQ4AvQRXZexpMaN928TSczzyMnT+H0DCq99F7VRQRVtvMEMA9FBKdfxh7x0khGC7SqrxSGNUolas0c4nOTQ1AS9Bw4RlAKgyuiChs9t0t/4G+y12wzu3GKn3aPVL9Jod7H8baamR3jp7TepSnFq/Q7dvk4iqrK7toPh+sgXmkyPZBC8No1Bi0uXt3j8/Icwhh0+/clPYXRb1Oomh44cQ5OGNNsC585NICLR7bbIVQdEgwoeR8LtG0xM+ZlKJGjWSvhkH7rrEPD6GMkmkVQvSsBm6Nj4vR5G/GFscYikQL9vkE3GcR2RS7fKPzwg/81ff/HFB8dl5g8kWSvZ7Cyvsby1wr4TC5QWt/E6Ko7lUCpXGLoajfYmD5+Zod+tMLdvDjUQJeATCIR8hBMx3liqsdN3CBfrPJeaJW3JvNdt0cq1MTEJpeP4PBb3V/NIaYFZYQR/yERU44TjEieOJKks5njyzCPkBy3Wdmq0LZWE1+Lo7BgHFBFf1s+sP8PbNxY5dCCD7CoYaoj86jbHZuYxun28oSS3N+tcv3qfualpdos6jXaJiGqiBbzMTu9jbbtMMOgjGsjyP166hC1FKeW3ubO8SWp0yO6iTd5okfKFGEnFKRRXmZk+yOL9m6yt1sGVmZ8d5at//RqlbofNnTyBUIj72zXWy0UOjR7ke1fewW9m+MhHzrC9s8O1xRUKdZeBK9HcWOW5587z1a+8hiw3GJ9MMjU9x7Ura/z1d++SL+zRH0jUuw5bmytU2n5ef2eLVq9NOKBy9NAMAib3V9YJhuLcvb0KjszuXoHZgwcIZk327UuR69aQxSD2sM65h45jY7JRLOMXJBBtcFwGug9vYEgs7mFhdp5uZcAvffbjvHOjQtewKdQbNLptFM2H0bdQbZFCu4tounhEEdcZkA54kMwhRt8mGopQLVZwFIWa5fNh5JwAACAASURBVAIKvoBJMqQhYjKZieBVZI4dn2dx8SrhQIDZuXE2NrYIBEO4roymBoilA2xulfGHXBLRFPlKg0gywPWrV7F0kf7QxjT6+INewrEwchcWVxtYwSii18d4NMHCwhyiKGAOLXLbW8SCEaJKnKiYRKnDvsQCftPHQmqCQqVONBRkYAyYnh1loHfYyjWJhoOs5yrMpEcQRQfDNCg3qvhVi4sfbJKMRciX+0T9MubQRpJlBAQs0yITDREKe3EdB9GSccwBiSzotQb12zf5mf/4e/inRln65ht0Ln6HRCyI4vfznUsXCXhVlKGMGw7xT049xse++OMcPnuEa+9eJhLyc79W49ShfeCv0Mv30LQgV25fI55KgKDSandAkrFcieToKLlmi3KzzMT0FPOjcXznnkBLpCh+7xVCC3PQGRLOToEuoPklDp1/nN/+pX9PSx9w+smH2FnbIRXMspDRcHc26Y54CZoCA1HGF3kUM36G19/4O2qtBo7mo9kVuLW8SLnqJRnxMOw2aNSg19UpN3VsyUc2G8PQ4cB8loBPYHF5lVgsSa/bZmIyzbWb15mZnqdc7TGSSrG7sYKoitAYIBoujtrg5u0qsWgUj+QyHHTw+USuLH6AaPpwfUHKgzIHp2exejXCAYX60CAU8dFrNZgfnaBWb+LVPPilAEgCe6Uqt+7/w36t/KNwCJIViUbUT0cSOHV8jId+7Emmjh3i/laR7Z0m+VaHoRLEUUN0Bn3y23BgzuHhhzKEgw6dyg5RTEY9AlHZ5OOP7WfMozBI+tlKefnLtW2aJZ39h8bxqQKK22B8Ps3RY1kOJadRxBZGw6Vf67KXG/DeGyucXFjg1RvvMeVJ4lVCOLJIIhNk0Olxt12klRuyXFrm6NEYvpZKfVAjHvFy7OwRbpY2sFSJzd0lDu+bJh4VqFQLnDm5n48+c4hPfuoRMrE0WxtrNOpVlm6vc/3OCooaoNGscHe1Qyg2xr//L9/icx95FlepImgW+/eNI4keVjbuMjE9y/6Tc0hek1avy6/+5i9zfGacF84fYzwmc3Amw0hE42a+yslMjDs7t/naN7/BxJRLSPTjNHWeefgwX/ynj3Pz1jUee+gQ585+ilh4iiuXL5Idh09/4hSO4me92MZ2JLpmhHKxhKp3mY36qXa6bOWLlOs647OT6J0hiXSa808+gke1mIhZRC2ZvVtrRAU/vt06z4wdRHF0yoUickeh0BgwMAVm56bpdKq88MLDGP0er7z0Lku7OqlEkg8+WANDZv/8PBGvSqNSRbdkLLz4HYuRWIT+cEC7O8RARh8aGKZOs1MmNZHGtFzCYYVed8Czz5wik7J57KFZUgkJS3G4ufgBT3/kw4zOznP5/gbh8TE2c7tkM0mmJrxMZZLIlod0aIpWJcdg2EGSNZLJSRqVHqJtMzOaQPFq+AJ+7jaarDeb1PUio5Mq7UEf0zSpV6oEAgGC43EePrqPT52Y5wsvHOeff/YcX/ynH+MXfv7HMZw2iuLBH/SjehX6rQ4ezYfPE8I2+mxvbKAPLYzBEGtokB7J0usajMdA1PuMZlIIA/j/xNSuAMFgkGKvR65YQ9VlTk6NEQ3I9HJdRiYfZCx+DMp9vv0rn+fg53+W/f/bi8iKRnI0SbM9xLE0eqJJJhxBjqtsXn2HiiPwS3/yn8hv3ybQ6hONBVBDArFAiuxUCEGLYFoylXwdUfAQCfhRBcjt7SJLNvVel8vvX2dzp4qiO/SNIaMf/THs2hDZltAjQbpmBfOtb9P5by/y2z9zmA8/eYT1xas4MYl6oQXBNKY3QZAwhiIjrr9OnfsEbv0W9trrfO/dDXYqDW7du8fh+ZO0uyVOHT+DKPtpmU1mM1H2jcWYG4vwwKFJ7HCNr7/9OoIU4Qs/9Uk0T5ujRya4t3iDgBakXO5RKtYZDPsEAj58fhVnaNKtNNBEEY9nQKXVYy2fI99ucXlpnWx4hkw0i8CAhw5N0RiWsQWBXrNDq++gF1vMxlLsbSzjCUrs5roE4mkmA1F+/pGn/sEM/UdRkf/B7//Wi0ceiKNYJp2d9g+W/mzX2ao2absOzX6UXGOP558/Tj1f47kXDtHaqLC+UkdUQvjkIWfnDhDCgywM6A5KHJ05QGRcRh9U0IIhQlEfTclAM70Mejqp6Ay55l00N8y206JpDfFqDq4JmiHTnXLxp+PUWgVi0RRLG9vMLPjxqxHu1vJMxRUesObQjDEUqY2iBbhbyXE2kmRrt8hMZISgPKBebaLFQ8zNj9HrbNEpNsD1Yak6rhvn0tUcc/vHkIUEkYTAsKfSpc8LZ05iygl+5XOPcmP5HvV+Db9HoNtSkDw2uT2H3c0KExk/j59d4N7dy6SmUtxeusYjDz/FxctLVBo6pxdifPEn5jg1fZZ43GYyEmP/vJ9M1mFmJEh+s8fk4cPsS3r45huvIcpeel2T0ZEUfqcKspd8qcoTx2fR1D4vPHaI5z50mMm5aW7d3UC0Opx/6BSO22F+8gTL29v0+3UeOrGfw9kA3YHB/bVtCGg8NX2Qjq0zbNZIxzN8sF5C9gqMJEJkozZzkz467SH9nkWjPaQj6pydU/jaXy0i+1X2WiU0W8HvD1Oq1/F5HMKuSXc4oNAZkBnJ0O73CAaDeIJ+/BGNer+L0beIp4I4rpfl1TVmx+e58PYtxuanCftlPLJMNJRGEkVa9TLRUJjVjRy1LgRGstRKZdRwnf5AIhobp9XYQe8L5LYbWCYc2D+LPaiRGB2jlN+ltFwmG0nhqBJ317d54tgZMskEhXwOn9fPO5e2+e8XLrAu6VxZucPXXrrES699n7evXmNjtUg0lSGbSeDRZIRhn4FlsrnTwRo26BguE+OTOLaOaRgYrkuu2UaUTcaTWW7c2yQeSaKbOo4Agiyh9/t4VJFUJsToWJRESsb1doiHR7jXLPEfvvRvsbNHmNqfovnqBYTTZ4jtOwo+i6+/9DKKA4cmDxOMpnj0ifNoCQVFh8HkQZ7/+E9w5+0LBFMi33trifFYGEcbYaewh+xaOJaLqnkpVJqIkhfbNkmPJFF7LoV+mWzmALNhEUHwYrt9FNukVc4TtDU8AYdbWz2SPY1DX/wCv/x//j5js/vpVlrUJYFzD55By+xnIHuRsVHiMXzDJNb0hzhxdpprb14lEG7hWBb99oCTJ84RDch4JAlR95FIhJmbGEeVFd65epXRyBR3tjZRfR5u312iVpe5cmWJqalZEGS2tyqoWhCvV+PYyQd49/ItHpjJgGmwU9xFFyyEgZdQyPMDkZ2gEpIEZI+MLxnDbQ/Y2s7TrOuc3DdNq9fEMgx8hshUZJal23nCI7OcSE1y7tg+So09/uK1pR+e0cqXvvQbLz7xQIS1xSo1zeXOnR2CQY3VgkFY0dAtm4moQjQeZHdnh91KC1lKYNgKTxyXmM/O07cNApMam1WTpE/CbZbxTY9iOQKBbJRmucTSNR1dqPPwEwvcu5tjIpxFN/vkNoZsbnZRAhqjmQgPHBlD8mmMyR4uXt1hY6vHC588iCr1mJIjjIaTOLaH33/jbWanQ3z7zfc5/fgjqDtlKt0Ow6hGRpHYyTWxPANkJYvQrOG6EtlYgg9Wcyzf1dk37WXmYJar72+iWza9voPh2GBabBR3uL2Rx+i+x1TqE7x6/RZr62XmJseQ8BMMq0yM+whFRNZzeXLlLsVcj3Aiwu5aje18Gb/Hj1er89r7K5TqLdy2QMfoInrn2cq1iIYDrJRW8VV6ZCcfoW13uXnjIs8//xReX4KW3qHX67IwOcHhI1miwRiNboNivUW32+bIoYOUCgXqjSGNXp35kTiGsc3xo6dRZQNj0KPSaqJG45hDk6FfoKP28csi8XSEkckAsYiH3HaFYr3DxHiKaqtDq/UDa7h2a0DC8OCTPKybPWIECQdMRiJepH6L9Eia+dmDbG3n8CsKwqBDJBbCLwjonTaurNGudfEIMmo4jIDB2GiafnlAciJOZ9jk9NF57q9uY4o2m6vrxIJJCuUqswf3s3rrNgcnR1DUIPZAwLIHbO8V2NjpgSOjd8Hr8bG1sYsriZQqW5iGy4nTB2gbHWxRIx7TWEhOEI766Dd1DNPEq+j87bUdDs5HGMoOW3s6HSNAR+5gDAOMxDQSsRTdToexbBrV66Pt2EwfOk56xEO3Y3D39jIf+dxnWVu8jTMYcnu5Tj5fRrdVNNnBtmwQBGRBBNcloGnslspkEzGef/xxrt/apbW5SWs4YJ9ex7N0BzO3i/fTL6BK4zhb7yHJCl/+07/AH41QtwWmM2PMfvgInokjaGIZ991v0frgDT5oGUiuiyyKrK9ucvLQAayBQblUZ2jqCKIEA4NqTycW9NEsV4nEUwgYiKZK0G+xubTM7PQMq1feZXd1Db3fR/UHcAYOqblxhNQIy5ffZqCp4LWpDeHhzCSRA7PItsFQ0LD0TRSPD0scIHvi/Nmf/meeOnee6UyWA3Mz6E6b8lYVvWlj6w2m52eIBWNcXrlHMpxhJpsgMTKBYDvMT+wjHoygSja6pWINJVRZxB/wsLO8QrPXQexrTGWijE2lef3KBzjKCEMdwimBVsvhQCrJ4fQEdkvngdEsRrVFvlEnEY6RqA9YMhvMBKbp9UxyukkkMcZDJx6CgI9uz0CNJPjzl9754Rmt2KbFhBklHR+hp5vIwQxEfQS8STyqxcKYn0rDoFQt8bkfO87nP3qUn33ejzQ0iKemeW9xDzNY45VXbiOaP1Dvacn9GFd3Ca/XKV1apN8QePrxFAHJy6uv7LBZ6GL6BAqlJoOeyaGZBLIlsNRsoXYLhIoeclt5QnKU6KSPK+/sMqh4+dadZdaqZcSOzbGjKZywD0fyc/n1yziuj9drNVodkW2xT0sdIHuC9PQyG/Ut0uk0ebPLwbkEH/pQgLffWuSbL9/k4JE5HEXDVWX0gY2DQrEDlmXzX/6uzS/+my/gDF0UxcP0wSCuI+HVVBp6m2g2xrlHz6MKIRA8fP/bW4zOB1EVif5gyML8QTximrGZEAcfPYbpMblzb4NWt8vLb77Hiz/3h9Qdi2+9+7dIRHnmqedYu3eZw3MaZn/AVHaMqfEEly6u0B06+EP7WFovslfu8z/+9gpjMzM8ejbDg9NzLN+7jFcWCHhNQj4/AW+aZlujZ4ioqsraxn28dYmbu3lC6RFazSoSAprkMjM6SW6tgSbC/oUU4ZCAX3X487+9ycnz46S9MrbHIh0KEGz3GYsHcYUu7y1dRAwqeBMRwpMJookoW3t7iIoHBRVRlFElhfpuiUqtzp17y6zvbhONp7h7ZxckHwPJwmx1kRSZ5vYuIQHWlxdJjs3xl9+5zAd3VlA8AU6fPs3TTzxOpwIM4blnDyDR4JkT+2h2ugSEUcbjowiKgBYRsMUu/V6TaDSOruu4rotHVXFtyPrBF/BS2xGpNkRGMwKdQg/HdRkObYyhheM4iCJ4Aiob6zmS0Ri5fJmAz8YXDRHQFGxJw7E8oMv8xCc+itFzcCURRZERBZD5gROMYRuksyPc29ziyy99nd6ggzEWxuvJ4k+eJfTIKZI/9a8JDD30rv4V7toOVnofPzY+yeRcCI8ok1A98K2Xsb7zMr30U7j+DNrTz2E2B0h9mXa5wML+ObbyeyxuLBNNx9l3YJaAX8IUBFRJYyffwh+NsVsqsrdXpddv4boeGt026EMa9Tbp0SlEwUOx3kB0B1TbFr1Knf/w2/+M07OHcBtt0s0Wb1+4RPfuDYZGF1XwoKozdF79K5S738W5/xoP71O5tVlFdmUGWCTlJGeOH6PSKRKdmEVBZGV9B48QpLhX5eDCPKMRH5PpFEGPzJGD0xyYGiXuUUkm4xzbv0AkBCcfXODOzTWS01GaZpftapFQLITsDjEsE83nQxYMApEwO8U6rg12p09U9vLs0VPcW93kTr2H/57N+uaQOinicpL983MM7AGqR2MoevBFsv9ghv6jALnj2twq15h9MkKhaiAHNAYDE30vh+4YRByVkH/AzGSCnbxOqWPyN7dznDk8yncXl1ndKnDhwjaWPWB+OkTI0oh5DfSYjGdshI985lkiSZmbH9QxLZV+Vyfitbm3rGP7ZD7+0/MIARPbcAkVTYxmkqFYQe2prFcbOE0PiqAz6LsUizaXL+1xV99mYXY/lz9Y5tH9C+zpDS4Xt/jwkbMcmZpjr9IHLcKt63tU13NgR3nnzTuU7re4e6vI8rrLvgMRsmFIqTE8UoXqbhG/10ASDAy9h0+M4noUTOstwopDoy3wZ19+l91KHceRifjDrC7vsnRnFa8isLq6ztPPHud7F7YIR1OEQh0CSpjsWID7y3m+8a23eOTI4/zzZ5/nD//Fv+UXnvspfufLv8ZbSzXeub6Obq1x4a3vMjV+lr/8n9/CEeo8cCyLzyfjCl3yhXX++mvfwzQE1rby/LPPPkHCq1OrmJT6DR47/wjTY0epVIqsbG5zv7zHSCpBs9ZmKr2P/5e694qy67rOdL8dzj775Fx1KudCVaGqEAqBIMGcQYmSSCVLspVsjbblLLt93Q5tW9Z123JbbbdsWQ6SrKymRImUmECRBAEQOQMFVK46lU7O+ezUD+S9o8cdo23et/YaYz3suea/19u/5/jn3HNO77yHVxcX8SgRrpyfpzPQS6kB4XA3sc0k7lA7ugYWTrK5AkcefQDJpfLkbTu41TDIVOpcWy1wJlnhUslkabOGaHmRcFIrtygVYXtplZAv+GZyNJPFKQk0BQ2X3YbHJjMa7cfZ10ZieZFOt4u//OKPuO2O+9CWkthdMncPDzAaDNAeCHHz+gIRTxi3GmR+eYmTZ17j5sJFfuaDE9xz7zCFfIoj77if2VgMoWViSQViqQSWICDavASCvaiuIPFkGlGUEEWRer1ORW8y1t/OC6/fYDtewWY08DkVRvsncNh1Wk2DWq2BpmnYVRubS8toTZVyrcnS7CrXlrbYrsmUy1UcTg99g0GMeovf+PlP4ZdFBK2C1mogYoJgIkkCdrsNm2jw3g88TrHiRo/6cTndtMQmU5+8H9vMg+BwUi5kkS9exTy0H1nUuWFskrQUMvkMF66ex/HQI2hGCbmWxnbXY2RicRLJDUSbyc6ZCW4uJ1jPlol0RUgV02zlkkhOhapgw6CJLxSmmC3gcDlwuwJcvXaBRL5Jy6bw/OmL9N92mIbLR84QqDZ0zEqKV09cwCXK2FMKp078iMHxdg7cO8KxtVsIuTKSQ0Iyymhyhgo64s6H0Abu4smPf4Iju9uxO/PobJETY5y9fo7hgUEiag1VbqJbNSTD4ANPvBPBtLNvxwSZeBaX6kIRmxyYmUR1CkhCC0EqoOtuPAE/I4NDGJtr9PkjKKaNQDiCK6TSbDbIrtcwCxqpUpGi1aRzqItio0S6lGc9lcXV3kXTGcAaGKJrcpB9/b3c9eCdOF126vkU1cQGRrNEamHubXPo/xHSyt/85ef+qKvPS6tmoQJq0IXSNJkZHEbtilI2UrQUL3OXM3T2+8kW0zwxcyfnYtcZrdY4MLqT1JJC/5gEdonFlTjrV/J4dvrImBV+8o1ZbixWMOxecsU0UX8HkmnQ029DrOp02T0YeYlYuk7UY/JUKknfoJdbS0WiHW5KhRI2p0yqXqA9EEGyt4gtVGgETJLJIj86H0NyBslkLU7MrrKwmaajzUU8lyWZ0rhteoKVeJliQ2M01M1cporVytBhCxIKC8guG8l8g+7+IIurBVRXADdNLMOGKhWJzV5g36530RA05mez7N7lYqQ3QrWcR9ct+rvbiYRsjA8NkY0bbBaWadWKtHm9TI9HMCwnly8muHT8h/zMh3+Tklvllz73d3Td2UN1fYGr15rY7R7seHn00SeZj91gMZbFbeuiXs0hiDl+5v2fZnF+HkPYJBzYQTK1Rb6SRRFt+H11ttfrpPQs7ZFdLC5coKuti0pxmz3je7C5JQqpTarNPHsGBqmLJrJkYyOXIuAMIbQUWmYLw8qRL2pMTB3G4XBw7I3XuJlu8Vd/9nP8/b+cR1CLSLIDHHaUuokly5imjVKtjNPtpNo0UJ0GpiWi6yaKBm6HgO6QUBSJRqmEb8BHwCaCaBKyhRieGKBRXKa3aac11slu2Ue+1mC+0KRYEZgYHGY9Ns/B228nl6tTLsr0R+3EE0muXX1zPmekx8ldkz00dZW+MTc3r8+DGOba7Aa1ap6H9h0iEvKSiG0TDARYXL1OdyRMQnNQz27j9LmJbSXJVgU8LoG+SA+GpuH3u3AoFqVSkbrazyf+86/zvX/8Ku0Ok2S2SV9XgK18Fb2a4jd+80m0ynVuLSyC1o4g6AiiiNPlJF8o4HS4GB+Z4Hvf/BG33zFNs5KnVSjS8Dp4omUw+/Lf0yHbUTwdCA/9HHZXN5z4Ac+u5pCSaZpGP0fumca5Xcc5NY29Y4JG+Sqxp79FthKkM9LGwsoSW5s1HD4Y7evFbOlIWNSrGrmNJv1RP8lqEcXpRGvWEQ0B02hQqhgoLpHdYxPkchkcsoxgati9Dpob8yRKElM7ukkrNT7QF+JYXOfUzTN0h3YgiSYUmrgHoghaH/6xUTh7huZAkLa2B3nqu3+M4IrQbjixdDvRsJ+uvhAurxuvQ8MdDCFaIn1dERrNBk6biS/c9uZIvHILbzDE6cs3UHkzKr++sEIqLrFjQiTgC3Hh3AWy6Ry1Yo39w+N4TIG0BW02hcM9nbTKYLY0Ir2dvHFjjs7uftqkEKLHxXC4j/c9ci9KQMIqV2k5PAR9HnyqC5tNwK/I/MMLp/79aOSf/eyf/lHIk8HhiYAgURFM7u4eIpUyOX70NLsPRUnnGtx5YAersRjXb6U4f3YWd4+fNlcIe7CP3gMK+VIThSDXr6e4liiRzNSoZCpc3bbA1GmWm9RVg/07dCZ37+bU5VkmJjtI5Eosp6qYkkFLUGg161Ryb+pWqs9FvWXisul4nE6cLjvNZomazYfDESGfrXHbdD/udgNdcrBnJEh3dz/Hj15jfHc/uyZ6WVqNsXf/GMnNAtfjGzg9DhKVGulmE83w0aBFKVVGtEcpFYr84iceZCxq4+H7J5iamuLMuUv8/GM/j+At0t8H/R3tbGdKjPb14lUdXL7wZmQX7HOxuL2JTeoilc4w3N/LT85e4cO372PfznGe/A+/Rc0R5szpG4TCLm5cSnLxZg7V5UQQRa6trHP7lIdkKsGRh+/k1dPnsZpNKi03bkXgp2+8yrsf+STF0ia5ss6hXaMIdpO19SZtUYvsZoVmPUO0M0CxaFHR65QrVQKeKC6PRClTI10uIBgyiuzCZsrkkwXW15NsJ9LY7CECfhvnLp0mlqgRybv52P393HHnMP/XX/2UHV3d+Gw6HW4nkmjgVlW6Qx62ciX6BzqxSS3CthCtRh2/X6VjIESlZFBv1HApTvyhICMDYZRWFb1eQXXYkKwyRc0iVa1QSqa5SZ7lTJyNZIneUJiHg3Yst4vN2Bz5psZ9R3Zx9IVTJBM6IU8H5Wwev9MiU5Yw5Ca1hs5GXCNXNxjs6iCgwnC0m4BXpVWsYJMlVpMpbG6VbKNGowmyYsPQbZiYiKbAeFcHHV1tuB0yAdWJWa/TM/ZeKsUi5449xe7J3VxdXOHijQX6291Ims7ffPkFinGdgK+N7UICzbBAUcDQqDQ0OqJ+RHOTgbGdWPY8ZsWBatpZWqnysc//GWHDj7U5j373u2i99LeUhydwXjvGl378FAPDO8mnG/zKpz6Fb7INMzxAaXse3/GTFHBzfvUGwXY3N2dX+cwvf4qvf+O7GA6ZQrqIy+ulv6uLkQEvJ6/MEw0EsaEjNSUsycQf9mFXBCrlOj3dbYhameULl7HbXbRFuvGE/NiaSTaWdUYffAfS9CFe/cofYLaPcv71M3SH+lFlk+GZ/ciCQlk0UTZuobeNUilcRs9ukE9sEstpyIKLkUg7laaIxxtix44xVFmmq6ObTDpJeyhCsdFkaWmZQqFAd08n26k4czc22D01wvkbK6wtbbJvbz/LSynymRzB/giGzcmhA5PEbixSNSyKVZOgy8LjCVPWquBwoZcbBLrDSA4vsgwdQ91MTfXT0mr43T5kSSefjhPwqHQE7LiEGplmlX958cK/HyL/b3/9uT9635OHWVxbJtqlMFkQ0OR25jfjWB1O3E6Lg6NDxDbn2dU9QL6cpruzi61kFUMqMB+LUWwW6OnaweLGArcWCph2i0raQFVdDA2oRCQfm60k46Exfnplm8EOg4GBKPVsgXyiga7rKC4vmtEi4JBwttyIDgGHpFKuyyQSDfI5kcWVNJPTo4yNBrh4aY2aXsQfFjEqfhyBGqFIG3fNdHBwyo+pVfF62lAEeP3qZcLhHuw+L9VKE0lr0CwZRNtN2qMhPvaeR7k+P08wYLG5uEF0sIfc9jJtbhkcYT715BG+8I9/ztTuUcolhVCPC6cosLG1gDfoJhSJcvTFi8xMT2JW49yxJ4rcMHjtn7/ER37zv3B0fZtaXcASLJwq+Jx+qloKzVKwxBqDHW7uvy1MMVfB7olSruW5eGmN7v5xXj51jXc9cDuh0A4W1mZ56fVZ+ga8GLUMHe3jnHzjDPv37SXQ7scmOYmt3UK2CUyMTLO9nUBvVHF7FGRVpSMSYnjHBKsb22xlMuhYeBSBex+8l4uzK4TcbiybjQ+O9vHqyiLLlof/8Ik7ef30RRq5dQq1FnXNoGpYNLUyRq1JvamRKeRwqAqWt0j/YB/FzQzuhgGihcvtZnJyCJtbpFqqUd7IYBNsDIyPEK+X8Yh2AkEvbpsEhh2n6ifU3YPUMNEHeyjXc8g2ka6IH1NvIbXKHNx7iHOXL3DPoxOEfV5qrRaGYCGJMuvZKrW6iE9sIEY62N/ZjUAL2RCoVquUCjXi21lWszUku4bL7aZaq2CJIoJmsWukB4/XRbVUwOewY2g6jVA/h544gre8SjZXZPrgYXyuCBOjdo5fTnNiWAAAIABJREFUOUU+JfPYXfuJtLlYWa9Tq+WxRBAEE023GO6ws1Kp41FhbrmEKOiohsV6usSvfOgjWHuHUcIzWG98k0YyR6irG3bu4dmnfozd42BqdJJxWjD9Tiy3gShXiPv8COk6z124xEB7FFdbmKvzV2gPtaN4PSiixPJqHNXmYn5zi1LJhazo5HN5JMEgGArSajapVjLoZg2/I4DebBEIteMJtWHpGn1DnfgdNoqZNNEeL2XZzqMf+UOuHv06m+k8i9dT/MInHsdIachRFVFUKOSS2LtmUOURdux7nNGeAdKZJC4sLMmF6vGhChq5UgVZUTB0C5tNwpBb5HJVmg0Dj8uBqUpcOLfIPffcjqkbnD69yOSeKEtLSTK5KpPjA/gFqG5lEKwmm+UitbLBzoERFPPNn7UqusRaIonL4SQe2+TgzD5a9TymLhBwBVhPF3nt2DmG+/ro7+0AQ0BFJOxwIVsi//3Zk/9+kp2iIHD89St09XRgt4XoHOljpKOLnFnCJ+uI6BgNnckd7fS1h5me7CXS6cYvycxM7iPaHsbp7GRuYZvegV727B9HkjwIVotkusHqUox6LU+r5GJjbZ5HH+sm0u5BtgwK2xXklh2xBdV8GcswEZugG018ThHFqKG18ngDMp29Cofv7qZpNMlVatxzqIe94wPkSwob69tsLG2jCgHWVuZJNytIFsimhbstwP7d00xMRMhsJXBIIu977z187KNH8PvtZJN1Xj/7I6Siyd33TdHd5UJoagTdLtoifkanRslq2/R29rC4uMxWPMWrr5zgRjxHTVKpmSa6oDFzeAeGVcGt2gm5ovzepz/Nh3/7tygrTlrZPDbDQDI1TAxqjTIB1Y9bceNU3eiGhC4btPf0omsCZ05dxUSkZVn09PZy6dJFErk1lpZWsasaW4spvL4BXj91lAMHH0a0C7x87DSpYgKnI0DY20mjkKVRN4lnSmSL2pslhaUCK4vzLC/NodplujraqFMkm14lJFuUmnncVTtGuMLugXYClU1koUZ8uYAjEMauuFBsTup1DdMQMIQGdsVEkh0US00enZ6hLxDAtBmIESea0KC9s514epNKvURyIc3I5H6CQ4MYosXWZgKPx0vLtOju6aNmwrbewCvbafN6ufbTM2RTCXZOTxP0e6lVNUzLz9ryHENdPtZurZCtlvGFAhTTWdo8EZymjl+xs5XMcvHyMk6nE0EQUBQFURTRdQ3ZJhLweenqjtDQdHw+31tnOoZhUKlUcDqdtFotXD4/ieQGFjLz1y/hcNi5885DbG6tsLW9yuDgILIso+s6He0RGvUqiixjCmCaJiBw4NA+gqEIobAXdBulep5YpozHFaQZW6eJDHoO2wMfRq+lMSoNUBTeuLBNemMN1QjhnnoQWRJoaZvYl1fp63sX/nYXNsni/NXL3FyZR3E7qRlNbJJMoZjHEmSShSL+Nh+mXqWhNbApLgTJTrFQRtdNIm2d1Gs6hVIZ1e7EGw5RrlQoFXKgqKhOLzfmrtLYSuC5dQMEOyfOXKctEsThhdW1HPH1FVq5deyWSUMzMEwRQa1S0+v4xm8nfWuNSGcUTZI5f/XqmzOCMzmy2SyartPSDZxuDyPDO5jetQNvwEm1ZmPl1jznTx7jxkocpyLgsIt4vW66u9oRdGgUy7htKrIp0tvRiyyLaI0y3oAXj8/J+MQQ9953mOEdQxzYv4fE1hodHW10toWwqzJrW6ucPBPj4pUYxXIRp8+GLmmIDgHNarxtDv0/IiL/g9//gz/aPemnpYncOLPC3EqGTHWDXW09DBzqpCvsJ5nZIio4WJxboKOtj7pVZ89glELBwKnBjeVt5jeXufxGgr6hENeupenrCpCo1On029lKVxnqtHj8ozv44Ew3C5eTZLcqtOoKuBSq5QaD/WEaVgurZjG8qx+XXiZi1XjovYdIrKVp5kwqxSL5jMZ2Ms6d+/vY3krTzNfYeWCUX3jPPcRjMWYXc+TyPpbn59HkBgODQ1SzSSytRiAYxTJqlHM6mdQS7W1B7rhvF1//6nWiO1z89OgCD9w9zO179nFt9hY3YltcvXiZg3eMEJstY4lN9kyMcWjXw0y7I3zkgSd4aM9tjEXa2Te4j7GOTu4+uIejz7/AZ77wHFXVDdsZ3vPxD9LVFmF5YQVNkLAMA6Qqv/arT7Bx6wpPvnsn2/EcmUSazmCQzUyZTN5goLub9a1t9kwO8e2nz/PQ3b048XLf/n5CHR0EI+0cO/4qC7c2uOf2vbjULhTVwG73sby8yhOP3EPDphKO9lPOx1nbiINkx+1243Y6yOUKHBwexGHU2L93mnRqhaAo8PxClrrQwlIkPvKzD/LFf36NcEcYrVgnqKrYdB3Z7kDGxO1wky4bSAI4fU6wGczsHqSW2iLSF0G3BGShQXsohE030USBrVoZt8tJWHZxZXMNl+Ik16pRKueJeCNsL8VZSy4R7Ygw093D0UtXWV1eI56VKCQa2AwTr+qjXNbw+N8sFwOR9cVtuoMRMtkcTWeQEBb3TI0h2y30SgOn00mh3sCSW2xWGmQradJJjVbLANEg6HFxYOcoqkMBQ6e/M8p6MUOjJuIN9vHwmI+zV+bZypcYGO4ml8xRKerML8eZ3jFIyB/hxs3LVDULQXVgWSL1hong0mjm8wyM9VBKVBDUGrdN7ebGjQwf/asv4U5dwXDvQnR4aHUHkHvuRLr2DGvb1zHtbRzePcPII51UbR14bx2nMP1JHJf+lMVWBLINnCEb6VwJn8+NI6iQTWcIhDzMreYoNnTiWxkO7h1mK1FE10CVbcg2A4ddJJ0qUSw2CPgC7JqaQLdZrK0sMbNrHAciliWz+8HbKa1WcPQPUNTm+fieu/nKD55laLKLW4tpRqLD9I77MCQX8ctv0DYyiVb3oCoyiBKSHmdtY426LuJQoL0jimTBWmwVRIVitUGrXuOVo68zsqOXrXiFrYUVbrtjD2ubJQxD4LapIc6dvoTd5qKtzUujLpLMp/BGuqlUK3htITx+L6KsYwuodEUDtFpFusMRds1MsffgXuK5FJvpIqWqhj3oRGg5CXZpfObXP8GlUwucPHOZYl1iO14mlqzz9KlLbysil/8tB0EQVOA4YH/L//uWZf1nQRC+BtwNFN9y/ZhlWVcEQRCAvwaOALW37Jf+tTvaIn4mx/sRZImJYJRkMklTs1jT43RkA7y6tMyeiJtb2SSIUIuvEtMExjr7eOmN47g72jEFk53793HpxzeJLpc50BVkWy4z1uvjgf1t2GwaS9suqttFbipuzs+liATaaJJkLi6wIyTT0e9Gny3AoIuVlXXGQzof/uBBYnmRoX3dvPjSMtJ2i/FpldGhLtLZGJO9fg7d1c+pXJWT5xaIpco88c5d/OSVY3T2BfHZg6zeWGA2nsDvdDI1PYLHaRAOixTyAcbG93D8lWP87p98lD/4T9/h1/7jQ9STJS7OXkc37Nw2eT/FHVcJm1O862EfLaHKa6eP8dL516jlXIwtruMKN7i1cAnVcjI/V6ElgSkoOAIB0qtlPJ0SLzx/kWJ2HbtLIqAEqTVr7N45wF984Qd8+h0Pkc/WGO2bwq5I+MNhtl96g/v338fJG1eoFcq8dvYiQV8VLW3y5E4/Gj1sWhqDPS4+9N4HuHprDru3g+uzpynH6oztbnF45iG+/fRzXFzO854jB/iHb17myH2jlMo23PYiw/1DXC1vMjI0xqmVS/jSeSTs5FURX8OP4tOptmooUi+yJVMvWpiijUSujGaXKRdKhD1OWvUyjZpB3a7yo5ev8HPv2sXNc2cZG52kVG8htEr09PRxPbZJ062jaikKiSob8wu876NHSL5aoGIaOLQGY21ummaMH7ye5xd++S62Y4s8c/IsM/0uZq1x9PmbDO4bR2gWkfQWYZ+T7GYNl99JI1vE7QxyfjOLISiI1QreNgc1U8Or2yibTWySQiDgZ309htOSKOVlOoJhipkKgTaVlZUifo+KJStYNY2trS0apTrHLvyYE0df4aPv24dTUfjq3/09anSEBw8NsJpdIuKRcEkCyVyKge4woy4fp26t4rIpbBkmE6MjLNkFCtkKxZIdr+AgVlxlZiqIq3wFs20PGn5aL/0+xsO/irL1Oo3pXyDa+A2y7YM8+Mh91LMF7JFFKNZwm1Bvf4jYNz5Dzt5FqdLgyB2HqFTzpGsFgm6ZjfQmA4Pd3FpYxBvu5OWr15jwdpBpOajpcSb7u8gmtmnoFg6fjwuXzzPeM0Aw4sQbjXLhwhXGJwbxOxysnrvG4Mg0qCIexc2t9WMY9Tqm0o4sOkjmqoiuCGI9Sa1eQpx7EXHyYQwzh7U1z0TYTiHVzqkLlxgZHuXsa6f50MfeizfoZXFhhUgwyOzNG/TsGOfb3z/F3tFe7tk3xhf/6dvs2XcnEW+LQWcJfbQbwR4iky+CpDA+PEq9XqO7fwzLArluIVg2nDYbTpcXXYuzncqzFnsdQ7LT19NJwy/S0RUhnooR9XlpFIJ8/i++zO137uf+vhkkGQQknE4XfP7fYug319uRVprAfZZl7QJ2A48IgnDbW2e/bVnW7rf2lbdsjwIjb+1PAV/6ty7QGnV0o0Z6fpnZ7es8PnMH980coGeoDx2BvQMqanuI5E0PHqWNeilEu9fG2tIq6aST2HqeQs7G1RNLGEWN1XKCllUkaGvDIQv8j+8u8/KZFJSTeDF47eRxXL52itkNVrc0PvBIB598eB9eocXBXVPkG3WmPDpuVwf/8PIytmKBynICr6oRHQgyHy/S4wyxVwjxoQOHubmVQk5u00zXCEZl/uXZJe45dARBUiloFmbIw8zICOP9PaBXGNvRxdzNDURL5dTrp3EqDq5dOkEkLHLy2GmGRoe4cP4M/cNOVpLfYfVGgjMnT7JVafLZf/obDFcXdrGPUlFgafUC33/qFc6cyXN2Nk/RsJPONyhWNDQ1w/SwB3dN4rM/cz/FfAOH6sJn32b/kB1ZSDHZpvLtK0fZTGzx8slFvvPDU3z+C99leMc+fnTyDTRTY6g3Si2n0az3cXx2lv/67CWq9iJ21Ua9rjE/dwMbOpvnT3LPzC48gwqbMZ1ub5WVnM4D7zzA8y8e5+MffpR4qsj5Kxe498EPcuLiZbp3R3jx8ht4JTvn9BQHD0wjodHb7mFyqIfe7ghQwybV8DoM2sIq42O9OGQTwdTxeNop1yS8ngARW41PfvxOnn/mKqp7jOtrKzS1Bi29yXMvHKOULxDxRnDYXQz1ddPX18X189cxFIletwdnS6aQNZGsTn7t1+/n8uwtlnJQw8HNio+ov4bQ10elmEMQRSSnHVOWCUZ8tLQGwXA7m5n8mw2ljCbtIT+tegOt2cAwDCRJQpIkEHRypRKpahM1FGVte5nH3j/Jvpkp2sN2ZFnGNM3/V2apNnQ0U6O7N8LUnt10t7XR2REkGFHQjSaYEnabiqIoeD0uOtpCOCUT2TQQdR3JErl8ZZ2RyShXriR44kNjyC6BoWg/htFOwzMMGEg0Ee57N+GWSjG/jkoVR6gTqxTC7B8H9U5s+GHXIyiCjtSzh7Hdk6Tjy2ylY5y6dYUL66tslSpoehsOlx+Hq4oktnCUE/gNiVgJDo628IkqhZxGpaUiiiKqTaRqymyl03S2hWkU05QbLWbnt1jZyDGxdz8rC/OQLWAkK9gVP0OD48xdXiLkUdG1BKg29GQByRtCjHZgL93AZqRROnpwTh8Gu8XkrlGinQEk2eTpb/wLV46fYOPWHJu3FlEaPrStBO/c28fhMR+phfP85089QbSZxVU2aIt20jU8gOB3M7JnHyMjI3g8PkKhMPVCBbfNSdQpEnZa9ETdhL0yTmc7/d0DzOzZyQN3jGFpOQIeO2+cOEO1ZLGazJIuNzAlO/NLG6yvxknFC9y8vsT1Kwtvj8V5GxG59WbThspbj7a3tvWvQN4FfP0t3BlBEPyCIHRYlhX/3wEMzWJ2dpsR7wApaYOjZ9+gZ2QHKaOKwxAIVu/AUzPI2c7w5R9v8Zd/8g5+63OvYLdMCHnwFkUkyaRWyzM2HqJ7/ygDbhtnz8W4fiVDtNPD5nqBycP9LM6u0xmdYrl0lg8++T7Obl3i8MgkV469geLy0vBneM9IN3mnRSVtEvGH+OLrq1SyefKiiGFWcNhD5AtFmh1OClsXUBBoeQM0SFDe9rN32M4PnrlIz4CDZKyMK5uitz/M2fM3cYU6iUa72LX/EOl0lkCHSmIrRVdfO+PjTVpNuHzxLEhhfvLSHIpN44OP97Awt4S32uSOu2dIrc4z2RciG2+g1wo4FDe337uT1EKJillndqFAtWEiC53UfGUsh8IXf/Al0s//NT//h39H74G9nLtxjcyFAjcvvsDdh3+R8/UiimAjV9ZRFDcXLl3ELfux1eqkSCI5AkR9BXYFurmYrlIq1rk+t0xXTxeCINAeDrGhltiMpxi1jfP5Lz1Gx0P/hXKtytW5Exy5p5tSZhVBMjny2Dt58fWn2Tkzw9XjV7E7ZRbmLvKzB+/h1ZV5xnft5PLlW1jpCvWWhgh4XSq0avT2d5FMJtk11k+loRFf2yLg97CeqvLYkdtZ2izgDfrIbm1iNTXcA16KpTyPveshLl2+xcZSAl/Ai2aWcDgktuIlpm7bjS2xzbXFGP07g9RLCvHUTQYCfZTqeabvOMKg38eXv/5X+DxtKKKEzWaj2dRAgGazilOxkUgUyTehvLqK26VSL5ZQhRatRgNne4BSJo0kSThUG7ook2kZtBp5vNFOvvrNV9i7v49WS0aSJPRWk1AwiFmvkcxso5s6obCH0OQONr//AuV8C0MoUPerRHztxIwiimyjWiohCSINrYwpmrREgZYocun6Fcr6OKKkcfxojMXlbfbevZONVy6gZi5CYIRa+jVc0UeAAmZfNzRWiFdMqpqB2NqmtnkFq1LCtutjyNV1RPcgox//v1F+8AR33NXH8sIaNtlBKV3ClHP4PWHkShNVsrFVs6NZLpxik7/5pXv51F/McuLCHCNTQwTdCo1aie20iWQTsbvs5JJpqpqA12MyN79GRRulf3SQTCZFC5OGpDDU0cvkSIg2n8jdB/u5+dVvEUsm6Gnr4tT3niFVLhJbXSDikpD1FsMTU9QSKXKxDXplG5myBZJC1B9CVVTCHhWHaqNYFTi/KmIL3MGJ5QRtO/aQLBW5nlKoNV2obgmxVcPhEvH4IhQrZdwulZDPhdPdQSKdpliv0dbRQdixTcDvRzecSFqNwe5B6pqGx+VAtMukM1vs29WJandSrZWp51vojTqyZCHLbz+F+bY8BUGQBEG4AqSAly3LOvvW0ecEQbgmCMIXBEGwv2XrAjb+F/jmW7b/7zs/JQjCBUEQLlRbGr1DndzKJ7nv0D4uLK4Q9LZz9ewtUrEK88vHWFzZYGf7KEcmelg8ViesurBoMtnTT6fTpN0HM1ODyA43c4ubfP/pNxjc2c77P3k7yXiFQtnFt79ymbW5Jj996QI2ZZDzN88jC3a+8oNn0Zoezs7FScQ2Kbha7FS99NZreLQmM4PdTB7Yidff82azokYWsa3EeO8oI+29mLpKm+WlzR8ktrbOre08C7EVGg0Rh6fEXfeOkS/7mDlwH61Wi3p1m/XFWSSjimW00E2Jp394lWojj2EYuN0ODuwOc+SRu+jp6eeD7/4oO/f08OLLzxFfr5FMpkiXErzj8REeeXCSxx/Yz8Kli3hDJmtzaxze00e7vcR7HxngPe95L+2uBudXnfR/+PeY2lviz3/2l3j/6LuR7RaPfujTfPUff5bsYg6znqUt5KbVKHP33TNk9CLpaoM773sQPVNHq9TpOXiQzeUiEbuXAzMHOHfmBg5vmPWtDFH/GF/72jU6uzXce/4TitTC41CIhjyUSirVahqXPUKlmCG+XOV/fOfH9PSFmdnZzc8//iCr7hapTIMLF+Yo5So4LR9er5dWq44iC4QCDuqNMnanjcz6Go18CqesEJAEvJbJ5moMpaQy1OuiZYLucWAYdgoVjYWVFVTZhtZSKDckIgE/0WiUTLZBeX6VRiVPW1sP/Z0HiK2WWIu3uD63RDlr496BCE+8a5iOwL30DQ0imiKCJeJQFbyqHYfdSWcgTK1WQ/F5GRnZgSIKdETasIkO3E4HqmLH5/PQbDaxNB0TkWK1Rq1WoSvo4P6D00z2j5Pe2ELTNNxuN/l8HrfbTbQjRNAfpFnWKc9d5877ZrAEG7l0jumxITKJOKFAkHrjzaGUVsvCqboQRRFBEGjpGnabn9WVN4dYDPeFaVmgZCX0QhupVidUk+jh+xCKcap4Cbh2ULx5C4dUoSvgQVciBMbvwzY0iawU0aQc2a3ngQCSuMVGvITHFmS0fZiIL0A626JWrLN3qo97b7ufQbuI1arz7tsO8MivPk1dNxkaiJLeijN7Y4FiSWeiP8rx14+SKeSZj21TKJeoNfMIqo3nfnqKL33tKP/0vRd55idvMLuYRrbLhNzgVAVeeuU1ribWyBUKrKQ3WcnHackS3rYoLYePiiPIpasxai0Vp78b0dvFyM6DDIztpX/nNGP79uEa6qEV8qLZDXqjCh1Bi2ibA1EycUsKiWIO2dSY7O9Etptsbae4NrdEPF1iNZFlIbbFxVu3WFjfJFOs8YW//Sf+42e+xqG7Psm7P/Hb/PMPnia2ts6pEydYj62xvLhEabtIKVnk5tVZ0okcWquBTZbo7e5GUZS3TeT/ZkQOYFmWAewWBMEP/FAQhEngd4EEoAD/APwO8Cdv92LLsv7hLRx9bS6rMzTK6eLzfP/7F3nkgWnK5Sp37DlMs7JJpzKMv3+Y+WvnOHDvYX7nK99hcrQTWyVIOr6CK2TD7fXRNWSRXZCYGIyQTjVYmsuTjN/C7nAS6pEIOfzM7OigXM9z+fw2qreHU6cT7DwwzOLmBu7BDvYoGoblZC0Z57Y9Uzx/eZlvnJxlR7cIGTf3PDCAU2jR1zPA9dgVMhsZxuyjnMlew/CKTPSHcLW5ePzX7+bp57fJFGp879uL3HZbG5lEChsZujrvoC6IZBKr7BodZWJ0B6p5ionde1mKLeLxW2yumRTSN7ECSbSEgiW6+JXf+k2eev5ryKpCaksjFNpGtBSuzM0y0HWQTCLHzgNTnD9/nQNTbWxvrRH2qLz3Ax+m7/IxTp/Z4usv+vjmM+/hA4/v4cR3v0n4nl/mo7/7p3z7z36NP/7GV0jkaliqxMljV2lTvUjBIqcvnEGTXNR9Zcplky//9SdoxTY5fuEi8xkwz9wgp7nYjM+Rvfxf6X34y8ghEHASUEV6fApWPUvv6C4y5U22bxa5cCFOZNxHIVVhe/ESitROsNdFIVkk5Gujoy1ILh3HHuzAZvcS9Hrwy07m1rbp7enC4VcxaBLoUnHJCg8/ME5dL3Hq0jzDA300nBXyG0XOnj7DoXvuIJlM0qjm0FweFhYSzC7mmRnp5MBkkMw6VN0tbq3UmSueYKSjl+XUAv3dYc49P0fmiRrf/bsf8d3n/oz7730/kyNR6loWQ5PRadKoiNgNO4YuUCnr6PktvDaJjXwanwSmYbz5AW81UVQ7NllHrzbpDqt4VRuCo4RhGHQ4ori9QXRdx9IaREJh8sUsltvDWqbJ1ICOWxJZis8zcWACm2Xh9si0hTsoZmJ4vEHqehUsEUux4VFk8rqF01RpCQ10TaVVafD80ZcYdriIbRX5jV96P8G2frKXv09ov4+qL4ha34DVG5T2PkJ/1whPzy4j6zWQRVrBdsqvfovgfU8Qcjtg+zn0+Sy33f4Q0XCIvt4uwu1HOPbCs0huletzcWZGe3DLBu/2OBG1OuHDd1Jv2cgV30z+dgZUtGYNy66yFengJz9+mf7eDmq1CsVCHsM0Mc0aht5CEDspVvPU1/PYJIlKvUo6XUW2iSgGyJJCoWoCdgxdwy46cDgCNBoNnN1O7HYLMHGFw0gOBx6XC4fDQTaVxiXaiW+uU6vVEBoSNpeEIIhIYouaVkds1VFCnZy4chPFJiG4bOiVFs1iBbtDxe5zozdbVKtl0pk4QyP9DI3084jrIL//Z89wYbHAkcMeHHYNs6lhlywKWhW34STo82IYFiYCuiDhczlp72x/20T+/6v80LKsAvAa8IhlWXHrzdUEvgoceMttC+j5X2Ddb9n+t0uzDKrJyzyyu5uRGScdajfFZAlvpMnNRIVb1XUuLp1idPc0//jtn9DhcCPrFaZ2BDjy6CSP3LOTdo9JOe1AbRe5sblJ/2gfK4uLDA91IHobTEz0k8halFsS62sC/nYPZ3MZqo0qLx5foXuii4Dh4CVNJr9V4LlXsrykL3O9lmL/sBO9HmJif5mwz2Jndx/x7RxlPYDujLIhJAkFFUZwUMhpZAo2Zq9lMcwmA709eIN1aoaLYkXC5eznwrl50psZNleLzN7aJl3O0Dk8xvd//Cxun0oh04M/2MTpDzLkbsfpjvLiuRf53jNP0dHVBYJOtNdGcqvAiVNneOyBDyLU1xiOgFXI8id/+En8PhsjfQ7SlRhHX30Nv62X0elxyo0iTUcX//2peWYe/wiv/t29fPF3/panT77E1fUitZKFR/GhKXZUL2gtP7FbOX7xF+4Fwce52VM8/eJz3Pvuj3D06DKdcoOCHEEUG9w+EGTngc/Q1Z8kbI8Q7nTR0S4SCov83u/9OpncJvl4iV/71MNsVi4SFNsoZspEfNM0zRLXL8eRbE6aukQ8XUH1tbO+sIAQ8SIqUHCa9PW3owZt1NQGXd1R+qJR3A6V+Zu3iK1tMT3Ri97U6ekdYmBHO7cdPsDs5YuY1Qq6bOEgTSgsYdr9XFhs8drJFC17Er+vDyXSiRaH8nqKu/YeIDab5on3jPPH3/hHTi8uEH/le7zyrS9z62qciLsPp+TBK0aR5SqGWKPckFEdGjaXC10QadWaOASFRqNBtVpFkiRUVaXYrCN5JKZtt2o0AAAgAElEQVSm+pHEAkO9YabHekgnE2BZCIKAqjpBsKHYXKTXY9y8usTV+S0WYwm2cwbzS5skEwXyuQoWNUCnVqugGzVcbhMbbhwOPx6hj4+96wP85s/+Kl5Zwu7y4O0cY9mw6MZLVctjyHk8uw9Qmz+Oq3YdyVGjfvmnmD/8fULyIKMuyF56DfILlF9/lWYxR+z5vya/OU/97AVGHrudXGkbSbFomQ3WN9cZ2XmIVKpFT/cQHpeXLo+PZq5ErVgn4m9nfLiXXZMDDPS3EYgG8bUFGB7tIxhwMjY6SLNVpVTX0HSLRCINgozbIZJOrNKs5WlW89SaZbK5JIpdRlVVfE4XQY8Dt6RjVjMEXHb8TpWAx8lgTwftPWFUlx9LdFHXWtRrDWq1GrIk0NMVIRRycPDQNL39IQIhFdlmUqsXqdWLNJplVJdKMr2NzWbhtIPZrNKqVcBsoWkaW4kkmWweWZFxumxoRgXLKFDMbOPzOElmsrx67iouNYBNspPM5qgXRNaXEmQSaYxmDVXQUAWNciZOYm3xbXPz26laiQCaZVkFQRAcwIPAn/8/uvdbVSrvBm68BXkW+GVBEL4LHASK/5o+DiCKMje3s7TSfqI9VRgU6O6K8vLR13jw4Rlm52aRxDqLaytMjw8RiLho2EuYjTpXL18k2tdDZmuTvVODxBJlRieHyGZb3LtvH1vbaQY6Bwm4PCBY7Jj2Eu2WWDi7waYOgl9CLfpw2N08deUqDsmDMaaiB4K89noRsyawZ6qfYEc7Pz16Cjd1ov3LhKK9TDZEYvkEA7sOk99M8fzSNS7MFxiURHp3j9E36OLa5SsMDAywurmOgkm5UMUf6iGRXOHhR5/klZ+e5OrsSfZNz/Az778LreLF5avyxokMExP7eN+dTla2chy/GOM9jzxGs5LD1LykChp2m4M77v0gTz/7DN/60h/y7DPz9Jgb/OTl57jnzndQKcc4+fWXkTwOZreKZFMGXq9Mo5HD5bRhWv088NkfMsMP+fa3PstM/2k+/aXncekmxXIDtzuKZZR54N5BZq+9wON37CeVucFY1wSnLn6PD907w+XMFqlskXy1xS9/4kHmsjlUT4ihbrh06xrjff0EHDLf+PrXiPhChJxuxgd38PlffB+vvP5dPv3xz1BurBOIdjA83cP6xhapeIGxiVEyhRKYBlatTJek0tvdR1WvE/V6qfsjzKWSNFtVXIqKx+WlJZgolp2Ar061vown4KGlNfC73dgRcEXbWI5lqDd0bILOeL+X9o4oz/10k0pxnVS2RLS7g1S2ys1XFlAkP88eX+Tw+CT5fIbf+W/f4nOfcfHCj7/CiWOvMzHRy1PfPcpq3GJ1e4uKIdDdZ2f+Vor2iJ+ArqA3W9RqNez2KPlCBptdRTQN9h3YTbKZZ+KuGY4em2Pqvgnmt1fwOGxomkatXicQCJMtFunsDHNo/zDOYAg1FOHMU89jSTptoSCIb1ZJeF1BMGzIigiigGBCZ3iI0Tt2cdshDwNTU+w/OMH3v/My2+sxBjxteINdpDa3sDbXiJdSZK5tcfNLT6OYTeyOQfLO+v+k7r2iLbuqO+/fzmefHO45N9+6sXIplEqqkpBKASEJFMAICdpgAzKO7YChoduYNjiAcSIYbDefDQYsDBhQEyQQyrlKKqlUuereujmcnNPOe38P5X5uP3xjfGY9rzHWGOvht9ac8z//E8d0ueW6OZ589Gl4WEQkhpDxifgSneOPcGFhDdey6HZalDZ7hMNhFCmg1WqRyY4gmnVSyTEiUZVMehJBkDBsD08SUHUFWRTwgb4fENVVdsxs4/GnnmRycoKBCDhmn+nhFH4AnX4PWZHwfZdwNIorhdE1DR8FTUtjiyK6Fkamz9hEipbRw3Vtem4foX1pILfnq6QzQwiyh4SMa5n0m3UcCQJRoFjKEwQBzU4TQRJQVZlux8A0bWw3IAgCOo0GZauP67XwULAdn5ntexlIDDI+muTC/CnCIR1dj6KKInZ+Hcc16JhdVlY3mYqOMZDKMja2k4gewvUDtjYLmI5D17Tw/R5xVSeSiPx/B3JgGPi6IAgSl37w/xYEwcOCIDz175AXgBPAb/z7/p9wSXq4yCX54fv/rycIPoQyRKeg3tIxgiZ+X+fGQzv5+rd/ymXXzxFVkygu7N/mEQ1FOVOuE1bjxMZBFuH2tx7mhccWGZ2JU16rU+xWGMzm2DWYRgpDs3KSX7r7Os49dxo9nUAwwqxW1ok7Ydohg4WlPqHQAEGnyvqWiBNUiFbSpFMuhOHMmbNUmwFjY6Dqk3SXWqxYLYaGs9S2zrAmhJEC2D+7jaOLa3QbDUZGtnPvfW/nq1/9KYHZ4v3vu5vvPvQIJ85tYNh9itWnEIMmO6YT+EENRcgh6HXOnmuRHd+GYJURkoc4f2qddBT6jRJvPHyIz/79wxy7sMpnPvQrDKeGeab8Y77w6QeZL29xxb4buGZuD09+9/uMb5/iwI07iEUnOfLSadIzMqtrFaKRFL1eD0PZYrCe4UTEZcft/5N9o9B5+etc/+bf54Y3X8ajL17Et3qMT+TIxseIRzO0hTFObGzwk+eLPPqlv+Zdn/g80+M5EpLCzff+BSO7pmmtnabpCxzavY1YOE5UFxnQE4i2i5aK8MnP/jVJVeblh7/G3/3jn/De+z+Eaxpk0gFnTxXZMb2drtWlWisRnRojECWcTISN8hbXTM/wxPHjnNys8vu/9B5eP/06rhAwkMtQa7cJsCnmO0T0GHLUoVxrEI9EMTpdgkqTK6cGKL26Qb7tkhvqcPqJNqZaI6IPgCkzbHc5fON+HjnyEik9w4c/8rv8+NkfUe1G6JTgn/7xu7zn/Sohqce/fOW7vOWtb+DISxobxS5awoaeQFoXUVSfuB7CNx1CoRDhcBhd13EcB88LeO3sSYKIwvDUFYRzA8wvLBBNDuK5RQLhUjHVw0NUBSQhQ6daodXs8I9fdwnpcQZzMtFwDM8T8LoB11x5JaoQIISi9Goib7nrHmZ3ppF0hWrDZuv4Es1mnTccHEW6aRi/LGEGFq2yxXe+8AWsRpOOFEaVFeamJzHMJtX1Kjdfu5e1sxXGJ7NoIzFOP/MarbZLTJLxY2EqrSWu3XsQ0xgiHIkhSj6pZITh4cuIRUc4dfY4uiYyOTmBFtZxXR9FUSjlt2i36piNBkbPpFqq8nqzgtHrMzUxTrvTIR3W0DTIV0v0XfDFMPFYEkkNIWlxYmEZy7Pp9fsUVps4jsPktjECx0ZRJGRZBsFHEAQUScaxHUIxlVqzRDgaxzVbJKMRrJ6PpKsEkoAqibTNPgEujm1QrzWIRpMoqkAqJlGuVRkcTKNIUTwnTCBK9CyXxcVTjI9PEhXb2N0+W+tFUqkBKpUitWYJQfQvgTxfxjk4w1q9ilizGR4ao28aLK5uki8W2L1rFt91MQCv9h/mOML/mSTy/+dKx7XgV355N9/48TkOzEaYHZrllquv5HvfeYjpud34OR9aInEpxozeZ6vbZrO8ihb2cVJZvGILXInEbJbFYpdep4geTTExMcGrz5/hLW+6CqNdoxdyqS5VUaIjlE8UOds0afpNer5MTEnRcWoMBDkCv4ggDoFdRY3JDGU0zm8YxMIpbn2DyvTYCOFmhXh2mtMb6wzmEhR8g1PPr7Fed9G7Ch3fJJ2K4dktHnjgXVy8ME9meJL81iJPPHcRTwqwuyHe+/7drF7YYv8VV/LiC6+SGdPZqjXZObKNV19/lYf/6qt87AsPsu1AjbVzEtbmIt34VXzzJ8/wh791Hd36AGOTIziV02hSlKkrriI/P09GaLPaL/HPj7zOdTfs4eKpKvHhcV45XsIN1omF4oj4DGSGaZptirUWibBMKmrxifsPkUjfwO2f+AxTUZ1m02Y4BbOTMXbummFx9SSR+JW868Asicxe/vSLf8iX//yL/OanPk2tVCbwYzR6feKDaXaOJNg1kcZ3QRX7pDODFKodPM+l3S5z281v5I1XH+QbPzjFidZZRjVotEzCgk2jD6cunuLpp/+F33vvX9CQmyTiaZKdBqqvcd7XCffq2IqAhkJps8jATArJlxkcyNDulLBcyOpZ8oUWZq+CKAtcrGjMd3pMpkXCosTFgkEqCnEUVjsiqurjYWB0PXIq7J7dRaW6iS5qPPX8v/Kx9/wGf/a5T/OhD3+Cq6+aZc9Vs2wUovz2J77E0KRGIugRzUSxLIl2o8e7D13NoSt3UqqWQFVpty7yVw8e4fI77+Chhx7l7QeuISrLhASZcqPB7YcPomkeO6ZG2Fzd4sknLqCnUnTsDqoCd7z1MK8cO4kWijE8PMj4RA6r5VOrlhkaSdDvyeTSKUzP5LLxGQi3Mdt9fFfBdXp02wVKXRNVDdHu9lhf36TdEjBMk23bhomGFBq9NqIo0ey00fUQ0VCCSr3CxOQ22r0+pY0ysq7gBzYjQ1kS8SjpeJpyoUi30cYJ64TCMrosMZrWyZ94nXy1hqNopIZGkCSLWDRN4fw8e/ZfTbndpdDuEpIFlJBOq92l2aqj6zrr+S02S1sofoyJsSl2bB+nmM/Td5tUG00EQUYhhCiLiKKE63t4QUAqkiAcDuET4Ps+shQmHA5huxaSpJBKZkGw2TEyRlj32aiWEDUBD4NOs0KhWCcSTtNqmmiqji01kVyJ1maJMJCYSBCSUnT7Bh3fouM4bB+dot3t0mk1MLsdpJCELKt89TunEEdHyCku9xycobi6RG50hvHRAQzPIxbL8NLzT5FMzaDKXVKJEGEtzHs/+8RrQRAc+L8x9D8FyDMDepCNubzzjVdQLQgUzHO87/a7aa5b1JoGF1ubdM11srkrMJ1lIlHIKRmCgRhbjQ7BVp5UZoSz+TXWVnrs26OSb2Xw5HVmRoaYDGXwegZ10Wdw907q+SpHjy5QaKgEpkfHMPml917GuZdOYqiDdNpN6hstPvq+w9Tyi6wRplJoMrdviD0zcY4+tcK+xDAb7QaaEmJ9o85Ft0SlFcM2Qhi2wV13H+SJx5+l03ZpNuHgwVGWFnoculpn947rMPsNUkmNc2cX2L1rB7ZZIhRKI2gRvv71IwzNwPVzE3ziI5/iv3/mw+yKjbJ49EkO3PPr4G/xw9db6FKPXTv2cPToK7z/vjexUemB1WPnzlm+9e1nmJpx2ejFePyJx/ijT36YD/3mX3H41jnOLJYwzBDNTpOQqhDTL/l2R7UUxWYNw2zy3sNZbjv0AL/yd1/k6j0DJJJpZAVG4wqPvHCeEX2CWbvEXfffw9zV+/nGQz/g5eNnqDZ7bBa6xGIxFM1m+3CW8YEo0VgYXRHQQyEaHZvM4CCrG4uYZp/rZqZ4yzvfwbGzJj9+7EdEpU3y7S7jg8OYYsAf/859vPvef+Lg/QMINQNXFDl79jy/fNc9PHx0HhwLzRZQ4hlOnponFgsYH8thWSqCIPGee++mWmvx2GOPUe5Uubjep2g5pEIK0ztHeOX1ArZtI+kKkhegazKm7RELxYn4dZxYwNjgOF65xZc+9UFi2RG++Nd/zcc/9mH+7m++R2ZaZv+eA1x+zWEGdt7CwVt3ct3B3SyfWqZRaHLTgZ1cs2cHVsfAdQLQAnwxiRt0CEkibVlFFQVCqsbgyChLiwtoioqu63RbXQJ3hTfdeS+Wr/Kdb/0A0YthOw6yAgNpFVUTyCWHCGkqhtVHC2eQfZvdN9/Iyvx5amdP4QJzM0OXooFjZ+naHoZlE4pGsS2XWDpOv28yPTlBtVIkHoni+B6u66JpGooauiT9c/pomk69aiArUK+VCWybPTsmSCTToKp4skzYFUESwAuQsQiARqNFuVrn9ZOnuO3m21ivlqg1GzR7JpnBQRKSxJmTx1E0FdOyiITDLK+sgawwOjHOQG4boqAgiiaaJHDh4iJ9y6JRM+h3TQJJRAspRHWdeDyOpvtIgkgQBEiShCh4qCEFQZBwXNDVGLlcEsGHWDJMOgPLS6uUy3UkX8B0RHo9g4FMjlg8QiaW5YWXjzA6NUHHaVMptDl+YplEKsr4+CCtap0D+2cIST6KFCYQdSy7Ta1W59xqj1OFPoOKxX2HL0NRdf7hX58hFoZIPExc07jhuj1sbq5Tb3q0uh7r+RJnWsF/COT/KVr0P/4H//OTSkxhaXGDO66ZYCg9SSYUpVQ38KIWHj2mts2Ry07w8M9OcceBWUrAhddPEdIFdsWHaHX6jGyf5ty5Itk9WSKyhO6JDKSnqFBGE3UUJcZSYYvRWJxBNcz64io3Xb+d2V06xvx59u26nB88co7PfPANvP+GHThun325Azj2IqmxYToNi4yQYP3kFnnP5rrte8hXq7y4us6N11zJet2gXW2jJWWq+TY9AwJBZnhkgJXVPKGIzEAkxvM/eZm5uRSSaDE+nqBeq6CHYXA4y4Vzq2RyZZJmiFioya13v4eFb/2Ay0fCvO+PPs+nP/VFvvvqBaKuwcp6gVZtg1+89218+9++hxbL8vG/+Ra7909z5KXnKG60URMdrjlwI3/9ua8Qz8HHPvgRHv/RS7TrNR64/ybkoIEkaDTaJo0gQHYadIQwq0s1/uQ37+bYKwuM7Juit3mR0xsKP3n8BEYoQVpT6Le2+B/feQhn9QhnVjdZ32jR6hnIaphYPIrgmYwOjqKJPqLsI4kyE2NjaOEotVabQrlBcjiEbqU4t3KMyZFBPvBrv8sDv/Y5Ji8b5v5DO7hYNdgRH+bFF5+gWLdITs+y1SijBBpnt0pcv20bFyvLOBGBTrfFxOQ4K6sVLENh584ZJkcmaOQvct99d/Gdhx4mNTJIs2PgSAKeL7Oy1mEgqbF/Ksdocoh8o4EoiLT7Hh3D4PCNl6HISZx6l7e94WoSbhdBbtLMd1heLPLrH3wbJ17r8+SrT6P3G/zxn/wWa0cXCdsWM7kprth1ObnMEK6gYWlhOoKCnknT6rWxXIdG3yEhSgiOg0RAo1Zls1BAFWXsvk2v38VvOVw4s8raUhHHDAiFbNSQhCQKNCpVMqkcjWqeVr1Cp9OBwCcc9shmM6Smcshdm2QyRjYxROC47Nm/h2q9RSydRNRUPCGgXs0TUUXMXpt0IknXNBEEDy/wCQJwvABZVXBtF8/zcf2ASEQmEdWQZYl636VUayEJCiePncCy6mwV18gXyxiuwcrqKp1eHwKJvXv2stlqUm2s06zVGVBCbJ0/j+HAVfuvZtu2SQICXDFAi4XpWTam5fLykeOcX9mk021iGX0QBFrNFq7nI6kqru9jWSZu4GHYFrIqYloWpmNhWxau72GaNrVaC8Py6UtRdk1PMDo+gC5dMswayY1itru0W02KBYtms0MgK2h6jOePHaXa6rNZ7PHysVWajRquHKfWMTH7Jmatw2alx7aJbZRqFbbKFcq1FtV6E8d3qTZ7uGKUeEhlZWUdZIGIqlCr9EnF4sRUgWbfodvqMzoaI5tyOblh//y4H375S3/5yQPpXcx3mrz2wioPvP1OJF3hqVfOkMtqiMkRnnzuUfZNX4+rrSFbYVbW8+y5Yie+5bNSNphfXKPabWBYKglZIrDgDTdchmPb1MoN0FXUaBir3ufE+SUiEZm3v/UqNi+cYGo0zqR+GaPDFrfs3kNja512w2Th/Caj01FUI6BolwhUmWQ8RbXR5PxymSdPLLHRddE9n9VSEcsI0AcTKC7Uyl1a3T7ReIJKsYQuDtLt2xw6PMibbn0zX/v2T7nulu0EToyxkRE28gGNTh3TLhPxd2K7JW66+Xae/sI/c/k1O7jsnl9EGxvk7TdcxbHTJea2jyLrHpnYIHOjAzRNj2wsya++791cOFlndHiYG667ns2tJebmJjl5dpOerfH1bz7CrW+5nma3zurKEjffepinXziJJ2sY/SoKUWTZZ3BskB89/X1++MW/4CMfexAx6fD2g3tZ3dqitdzngx/YxUZN4rWvfJ5EYgeHbr+Oz33px6iqQEiVaTSbeILM5maJkWwWWbVJ6EnWixuEdJ2lpXVSqUEiusI9b7yeJ1/dBKVOY/EMX/iHL/DK42d47Jnn6MtRMnYPw3XoemE0u8twPEPFN0hrUU7k17jy4M2sLZYYmRiiWGviOj5X7trBrok0dqvIaMxnOJ3g4HXX8/xTz1JsWrQkDbNrs3s6Q63Zo1C2adgNrjwwxdUHtjOSCLN/fJZb5nbwofvv4Lf+y53s3TOCOpDC7gtM7Zug02pRuFjj7R99P0Phab76k39jAo073nYLg0NjeHKYQJcZHBxifHycjK4yEJZp5ctkEmnyG3XSySSSHJDKZWh1OoiCTCqzjbDskdQs4hpMjOTQdZXMQBLb69Jt9+h0DLxABEnk4uIad99zGFnxCKmQHVbZ3Nji8UefIB2SWVhe48yZRRrVBS5cXGRhuYYn+diOS7PRpG/0ETwBMQhQBAHHdfCRaXebBAEIKIQ0GaPfI55K0u1bGIZNJCwhKT5906FnuughhbXleVyrRTgRwTANREHF8Sw8u0WxWqAfOPQCm8d+dhynUwMtQcsXsCSIhrPkC1U6vT6xZAKjb1Br1/B8l3a7h+erNM2AdqcDto/t2niug6pJGM6laOdSztqh07NoNDp4voDRN5AkEUnVsBwXQdGRlRjD2RxSr0qxuo7nONRKZU4cO04uk8VxoWP0CCSBjhvwgyePEwaiEYWBrMrIkMLuuWmCQMQ0+vTNPmgSRtfjyMllCvUOjXqX1U0D1wbb6KKpaUxs5pfz1Hv2JRM11aHtujiiy4kLRQqNFrW+zbnFOutVm6bNzw/Iv/hXn/nkvW/ew+KpKnbC5dq9MRqbfaYmkqCOs7pwgfD2IWb0KOgVarbF8aOrxCeirJ8qU2uWufbtt3J2YZW9s9Msrbfo1IpoMZleyyfu9oiIMRqiw42pCGSz1Ps1un2L8ZFBLDFC08ujRAISQcA4o1SVLv5agBS2qKGTywxSXthk03XJOSFOrnYhpZNId5nNzNALbKqtAKtj4jgCckhCUSL0PIOQLBCNWNiuxPmLBc7On+TaPZfx1CPzRNI9piZ3c/yZn+JGklxYC2h1TvJr7/o9Tv/0W1x/8xvIzO2i/NR3yV5/mGcf+hoLK+c4fOudbC22mD/3NGFxkrXiOu1WmQd+7R3c+bY7eOGh56m7VXZPjlDbbPDI8TNIXghfMKmUunh2hK1mk1eObzCUG8Tt9blqzyyNVp1+36bX93GtNKayxud/5df58wd/RK3ps1KpMDWZ44dHF1FFeCUfRXFeYW7PXvbMvpGLi/N0rA0SegarbeGEIKEopDSF9KCOGGSplsskUjK5kUGWi20ODA/yuX/9NxaPlSnkt0hJTW66/gCHb7qDV55aYSwNy2e32PT72H6fZm2JlA/5hsuOXTsoFtbZfcU2llfq7B4dxjNq9CsFUqMJ5tIqA5ksFxeX2bVnO7MzeyGAuBShXipyzcwMe0eG+cgH3sm9Nx1gIjPE/m3TzAyPMDScYmZUo1yvsLK8TKlUR1Ij/Oj5V/jZo6/SM7oMTwwQMruIQpu7Dt/DB379j0gOKyhegzddf4DLbrqS8QM7GNg1i97rIwQ24YhEPBNm/8E9dNslem6A6fjooRChwGRzvUip0UcSRLKpBEo0iaSEcJDIN7oEaohex0AGmt0ynmBy8vVjGI7B2QsnOPvq65TrVRKJKOlYBtNtgw/xcIS+a6NoEr16hV6nRyqRYmX+ApIAyWQISRGRQyGa7Q6SLKGqKq1GA7OXR8Liwql5ND2CILoYVp/8ZglN9ml0y4hOg6GszuDYIIbRgcCj129i2RaVcofBrEapZFLOl1i6uMabf+FtGJ5Fs2EQj+dIJkcZG82RToeJRC5JCnMDKTbXV7AsKDVNXCQEKUAQbVw3wPJsVC2CZbkYpk/X8rEDkX7fwBIlDMemZ7o0mw6lcodivUup0aHd7vHud17Ntssn+dI/PM/yxkXiokosHqHa7mJ4LuVGk5alspZvMZ6LYZldpmZnOHpikX7T5+RCjbZhIQoC4ZCOZ7uIIYlEXKXSMvEUjRHdwpQgpsWwpQ5ZRWLntoCLCzY13aLdCxjSk5SrXcxwCIQwbVsgpAn0RJ2e6fyHQP6fIkeejInB5x+4Faej86fP/oRIEOGTH7yfUz+9QHagSSI5i6m2kJQ0Lyw8SzKUwvJNVi6sEwrncHoebkygVG8wns1SLlTZvy9FKDmMLXSIhocwW3mmRwc5fXKVq/fv42KxzKHdY5w9Nk96LonsemTMBCElxPPHX6DQs8mlJ8jtTXNxvUymZzA0Pgi2ytpWkxPn1umEBQ4cmuTcsUUOXL6TY2fqNFoGiUCkJATIvkirayH6CoEIXtAlImr8wi17MIU2ucEBfEsjnOoRFqY59sJRnlla57279mB1HG6/MkosPY4ndZnv9Xn/3zzCxiNPcOrMizz4oy/wG+/5EKmUxvBYjJ8+sUZPlJjSK9xyy108+9oj/PTRPJcP+xy69k7e8MAfIMajIHTQtDiW5yP6Gn3TRw276IqAYwpomka/1yKiCHiSjtZs8OCX3sVY7ja+8vjn+PYPNwk8cFoNIiMyCVPmqolBtHSbd7/nA/w//7DAQn4BWyzh4uA2u+zYPsUdt9/A5uYizVqdiB6jXG+xtFojOiJx39W38o0f/BBHjjA+l6FXXOcdt97NrukpQtowxcJpnnv+LOfqmyQSw9RaBhcWt3jDzTsQZQPfkiiubXDD1bdQOblAPK4yNj1Ep7/BkOgxPDTE8MgItZ5FEFIJZI1ypYkiC8hynGhigM1ClUCW6fYsZPHSPahhFfpVEokYamSAJ545ysWLi0yMz3HowG6GcgqB5zOSzNK1WvSNBoNDaT72x99AVXSu2pdmbNsVpLMaB268jaXjp5mfP08kEsNwbRRZo1AooOs6kViMQiHPWDaJqGgYnkBECXCsPgIqgqbRMUwq+RI+AYrgoWoSW9UyF7c26JZauB4YaCyt1rnhiiFGUnMogH4AACAASURBVFGufcNNrNZK7BgeQTC7VBp1VDVEELjUWh1isQTJWBzTNPFcA13TaLTahEIhIrHIpQYV16fr9HEti0qxgSsERGMhTKeNbTpIWJQKTUZHx4lEdFrtGrIco9lpIwgCfcMkHIaBeBpJ1wl8ActQ6Dt9HN/D6AfMze6CQCMd00jEdUzboLC+gmH0mV9ZpttXubBaQFMVvMAlkEXCsoDnO0iiCoh0HYe+7eL7IATgShqe6SBLIiHFxXQcZDVKEAQo2HSrDmPjYXyvT60aZTArs2ffNJv5EggSW7Uu9WYXQRDQJR9JU+l3eyDJjKdTSP0ahg+WF9D3JQRRxXcv5eP7Lji2STYmMj48xOl8kYgXJSR4TA5r7D80yd997QKJAQ1FqpLJZMjnQdI9krrAZEpFVWW+/MTmz0+xc3wwETzwph3MzaTxPYlcZIC15Sa23KbqCkgYTCTCdI0wEdFjuVSjE65T36xi6gqVEoi+QKXn0262ycQ8rrzicrr9FQZzo1hYHBoc4uJmiVAiw+PPLBPJ9LlsKEomPU3BWSAVTROXJVobbUaTkzz21CuEMmE8SSIb1VBiMjFNQbcVXt7c4tRaB08GkTARIco9d4zw8BMXKQYCaVGmaSgoWDS7XQbTUeJanGLNo9UvcGD/GLvmpvn2Pz/HvfdP0+iZ5Btt0oOT5Ko2k16Bj3/vWxjpMV75+CfRhQg7f+FOXn/xXyid8djzrjfz+sOvcaG/TrOwymXbthOL7UCMOnznu48xtT2JIAvccctd1No2a2svMj54Pa+eOsLffOHL/Ozb32J+fom7bjyIIOsoYQVVE/mDf3yQI8dexfQDOp0OYljmjkPbOPrsAq999y/5oy8+xPdfPILhqSjhCNPxFAcyIt1Ap+q0uWn7DPf/ykE+/aeneObIUYJQjxtvOEShXEAXfN5+x+1YQY+1pWWa3R4vvHSSoekc/VKb9//iPZyorSOaAcsLFwmLCnOTOYajaW5982306l2G4gGSKtGql9gsbkFikma3gx7LMH9xi0a9wG9/9L/SP7PM8uoazQsneOOd19KslS5psz2ZgBiOoHF6cY2l1U32vvEwsizjGH1UWcPqGwiyhONYWLZJrd3l6IkVPNthYiDNntlpYgNJBmICjtVlcmI3ndYa84ubKHKEft/AVwIWVjc58dpx3v0Lh5jetYtQOEV1s048niBQNJaXl9nKlxgeGiWVjLOxvoWoCOQGBqjW8sjhKIFlIEo6jmVjBB7lcpmsHsZ1AhKpEJ1ei/V8ka7lUt1oIsg6y+0OXd/j0FiGiZjA+K5d+IpMyIOhdIyObeKYHq4voIQ0Go0Gsqhg4WF2OuQGs3SNPjgOtmfRMfrE40kCQcLoNS4VhWURzw6w6aOHYrSbdaJqGFULI0sqpt1CFDxcPBx8FEFHCks08hbp4QT9Xg/PDRAUlVq9g2l44AvcfO0hVMFhbW0FTxTp9ToYXQPLC7i4VsX3Q0RUgXK7T19QEAWH/6OKdl0X/9+bqTwvQJQUAs9Ak3VEAtJpmZAmsZFvEI0k0BWH2SvHOXckz3AuQaGzRa0kE44K9Hs2sqRhoRAELpLgEBElNMklHA6zlu8Si0QQPBcnELF8l0Q0RkgREQMbxxdwRZmxgQRX7huhUtxgIDbMVl9gdy5EyA/jsoAYHeZPv/IcUiSGINmEJJW+1SEW0oiFY7RqVc5W+PkB+dCgGnz293+Z+bPHGBrfxvrSRSaGskSEYcIJAVFxWd8o0KrJ7BiOs7D0Konp7dTjDvmLRVqWhljrcmGjRDqTYPdghmOrK+zcN4oiSHR7LqGOiRoVcLCxB8bZkfSxSx1cWSASg8su3011bQvRl3n11eP0mGa5mscJItx4cIj1foVtdZWTvRJXX76HR55cY2x0kJHtIj/7/kX2X6VTXHcp+x66rdPvdTE8h+zYDtJSnVTQIDoyxsmlHslsgjOvLXDvm28jkzF4+eQqhcUab9k7Ra++wJce/jH/9tGPosw63P4nZ7Cosf7Q11g78SBDO9/JSifKn/zh71GqwS++Y5aZwQhOfy83vTHM9tn/wte+9TWeeO0Iv/rWm6nUTC7my3z4v/8yLz/+HL/zP/4XuTGIRSCSG+OxxzcRJXA9GVlySWbCRONxyuUyYSlMOD6MqBS5cgI+ce9v847PfBVZl6m0miQVnxsv28bzT69QjVo8/vef5cf/+3tcd+1u0uk0lqlS6ZfB8UglothWD11P0W40MG0LPZJDVqJYRpH5+Yskh4YYGoixPH+R7Zddxf/6l69w363XMTA0wmBuFK1dYnGtzHKhRmZ0iPvuv4+HHvw+pVYRQYoSj8hMjYQ5NH0Fwq4dPPu3X0YZUnCMLv2uRaHSJzE1RjI9gC9pBFIIs+kReAayImBZFrXiBrmRcQzHJRKO88UHHyEdH2T7sEYmoZJMZUln04wPxGg3CqTSg6ytLlJtlRkYzJCMZbAdn28+9Ah1U0J16lx+5R5uuPog3b7NYCYHssD68hqW5WG6Hgg22ewA8XiCSqVCr2uhhFVwerQ7NqVyk27XJPAFAiziSRWjbyOKMiFdptPtUir1yFfblLo94mGd0bhKRhaIjQ0yPTxAPKxj2xaGINGq9xBUHV9wcCwbSZDpdFpMTU1RrVdw8PA8H8exURQFwzCRPBdB9LAdgXq9iyAGKCGRvg2yqJNNJ4gLAcmwSsfp0+w7FBplXFFidbHC6GAWwbM4Od9mYjrF7EyWU2cWUNUERs8mHL5kKrVzegjEgNViFaPjIjk+iUyCUrNPWJHp9W3atgeygiz6mKaJJInICni2QEhVsDwPV5DxHRtNkYAAWRLIxVRcQabd7zOQTBFOK7x6ZAPRU4glI2g6GFaTbdumOT+/ihf4qIoKvnBJYlzoI3kG22fn8Pp1bt0/STw3yNLyMjOT43j9NpZjsFarE8lkSGgOkhSl2qoRkcN0upceiPHZAcqVHufzC+hKlqdfOk8/UHAcmWgoimlWEUMy27cleOyl6s+PauVzf/nnnww7LSKhHJJdQfKjLKyeYmZoJ82eQbW4SiyRxmh36Xo6g2mH1YstzvYuYBZshoYSJOI6M9uHuOGWyzi3tMjI6BBJNcLIUJxXXtvEUW3UeJjJ0Rzjvs+1mQjZSAYn2+bubXv46dPPc2BgnFbLYeyaMV6/sIHZlvHCNql0mk6xTtDRCGsBCzWPYsEgX+5z/nyBvXvCXLkrA6bF/KqEGjgMqCGyuUGKtRq+4fA77zvE0Wc2WKu3yK+U+adP3cvq8gIvrTXYKJS5b/cko0rA+z/5i/zsi3+BTJrJ3cMc/+a/0n/qb+nlR3nkuSd510c+xh997KPc89breMtNOcb2XMPKkbO0kjb581WM7iKLG+fIxrIM5kZZubBOtW3z6FNHqJUqRIIBVmSXnt/n9JpHIhxCTOoMDERQtBhmt0dIkojHYzhig3BEo9frcHre57a3+Hz8vt/kD//+u2SGUoyMJqHeZ7lh4IghhiZ0jjz5M3KpOKFInFKjxebyEhFdZ2tjHT2ksbF4ltGhGOXSJlEZgqCN32oxOj5KYjDDenmL4+t5fvLsC2RzcVqNCrv2TjKcjLBQa5DMjTMwOkQkk+LFl48SHVCZPzfP3K5ZHvnpU9SKa6wuFDj50+/zpruvZf7CBSQ1iR8aYPeBa1HR8P2AxkYdu9un3a3ieAaqLqFoEhIqgeATjofQ5BTLry3xS/ffwGhKxfFl9FgUQYsSi42QlnU6ZoGm2cXyDcKSjukamHaI186dxbIERFFAkcMMD2do1FtIioiCRK1Zomu0aLebqLqHFIDddzAMA0WWeeXllzH6LqqggQhzs9vIDSZIJsJ06zWK9Qp+ENDum3huj0bLp1prEY7oSLKAIEQg0SO/YSJHPFaaNcJKiDPzCzSNLpsbRSyrj2W5dHs2nu9y/vwSq5UW9VaTzdIGZl/E9Rv0ejKu6dFzLOYLW/iKRkIT0CMxqo0Oa2t5Wu02fVvnhiv2ENgWj720Qsfo0AVGZ9IUKh0O7pkhXy/R6piMxCPkch7ttstWFRqGC45Fo9Blo6Ei2C6bxR6+mqDQrdN1ZMx+l74rYrku4ZCEKvroqoiuBWRzIl6gEZZFXNNGEGwcU8P1fRzLIZtMYtgWMU3l8l1TjE6lqC7lecd9NzIyGKPX75NM6cxsG0Exe7TrbcZGIwxmdQbTYey+wdyYyJ037+WK2STbZ0bpeA650RRW0GW9skEok0EJyQS6R3QoiuPLlHodLt+3m3q7yvjMGFutDfKNPq+cukAiMcJV+6ZwhB6psEZSsQhpDrlMCMF0ScZDLGz0f36KnZ/58z/75JXTYWJqn5GpMWyrzeEb7uLF515gfFuGJ86cRU6E2LFzN8Vil2WhzLPHS7g1hWXfxy6UcFxYLeWpVSuMZpJsrbRIRyQyiQkM0wLZIxFLkRM1ipUVBDOEpfs0jDanzxsEisRz585zplRDiEfwvTCpGY92vovjeMjtOqbkMXftHhYvtJBCAZbTIxodwLcMhgNIxNPcevMM869v0VVFemaPjmujR3VGcz4La00QVUTb4dsnF1k6X2YqkWHE7PJ7D9zOnZ//O05+/jFMR2ZwaopDt/4qWxdOMHLVCM1zGxSlEM+9eITd+0AVBji52OL8ybM8vNFl4/wqAk1Wtrb4oz/4BFfNaFzzpl+jq8g49TJOrcR1V4+wc2KUlUKd9lqPB976Nl48cxzV8kmkkvT7ecKpGH1XwDAN7JqHHvFZXzeJZzQe/OEWt9wU4zfe/DY+/+CjBLJPWktRLLQwegb3HJ7l4BW7mJubpdVq0y61GB4cJhQKkcqkkTURUZbY3NhCjcaIRuN02n1s0UfMJPmbr3yVjmwSzYBgubz7/uvJDcY4vrCAHSikBwZpt2rkN5fp9moUGuusFgqgunzjX5+g3ulh2ia3v3ka12tTaPuI0SRaNEUiM0Cn2yIQLHzJJp5MIOgCkYiGpHhYRoe4puEHBrIcXHIg1B0OXj1ESLsEjUqjwVX79zM7NMbOA5eRyGosLl1EEGy6Zg/TtPAElW9+71G0WBrfF4lHY2SGVAQc+t0O9WqJpY11RBkEUUCUBFz30k+73StTruXp9mvYnkUkFuf466d4y21volmvceyVIwR4bG4WCUejJONJPNejVOqyUWqiRsOkdBHN6hKOy8SjaYqFBufPF6l1XZbmF/GlBB2zSzFfpWuoFJsV+kKLQqlCrW7S6LpoWoQTZ+rUmxaGJXHidJGFcpPNags9nqK82iKeSGLYAu1OH1UN0RMEpiamSOkWZzaWiYRVzpSbzE4lQBDx3YBauU1qaIjhrM/ZlTKT2/YyNguyLNEsGvRknZYoYJoNNmoWl105xdpagcF4Br/TRgvFQHTRNBlZlPFcn27Hw3A8dl0xQ3Wjz/a5FL7rkcuOMTqqs31biit2j6JHTea2T5JNh9g+PYwueezaM4es9di/axsH9o4ztyNHLBtw1YFp4hGPobEJdM1l3+XjZAYgNzbOQC5BZjRDoVGhY7cIJVVcxaPSrdO2TWRFo2V2WasU0TSdQnGdfq/N3n27afVaBIFGJpslGg0R0gNsq4nptRgYjDE1k2TX9hFmxnNInksuHubYQvPnB+R/+7lPffKNt8xRrPfZPTULoo4eAV/JcWrhKHddew9z0xMcefZ54vEJXriwSdfuUnM7XLt9mrnZbZhOj+17Jtk5N4bgq8xsH+X5Z15jYCTJUy+dotC1cZsWlXaL8d3jdNQeq5U2g8koK5tN9m+fJDY3TL1RJBOPcWj7dsbUEPfedA1bnTI7ZvYjV4ucL1rkN/P4LrgVm16jyYc+egvLzRqmLlE4XyGeSnF2s8xoMobiupQaLVY2DE4sd3B6DqGIwuFQkm3pHm+Ib+fyq0ZpLp7hxD/9GXd/8yi7r7+JiTtu5+QrL9FYOc61//WzfPozX+aG+27ltRMvYpgKxVKFfCHPIyfzqFs95h/6Mg3f5X8//Tr/8u2HGcuZ7LvjJsR1n2bhCY68VmVx/hj/8wNv5vxCl7e853qePX0Sv2/jqSH6nS7X79tLudBEDnxu2D/Jxz/8Tq69aheHr72ap548Siii8o3vHud333UNY9kBmrbIjqk4xaUqX/3yH9LcXGXvzp1cftU+Gq0qb7njZk6eOk2tWSE9kqRnXxp2G4mEKbYayGGd9fwm5/I1Xjm/gRGE2DWRZmt9nmuuHWdzs4zj+1T6PeSkzvLyac4snMPEYqWyhCEZdAyTaFqlUId0Nk52LMXa1iqpgctpBQHZbI5e1yAe0SEwkAORertOLBJlPb+Jq/RwMDGtLmavg+WC5ZkMDOlsrucxWwqdfg3LdpCkEDdffwjTsolccQX9pMyE53Hi7DwXN9bomwZHj53jzne8nZdePk4qFaLXsYgnJJY21uh1HDqGRSwexuwaaJpMp9vEdG2W1uYRZIVG06Ve7+IKMj3L5sA1V7CxtAqCRyKdwDRNqvUWfcuhmC9Sr7ewTJGG6dF3A8rtNpKWpus2WN6ss/PAGI6oslFqMj6WptysI4om4+M7OXVxjZHJSY4dr2BZAoNDE+SrVUTZJaSLpNIqkiIgyAHDI2GiEahUeuzYM4YatskNxUgkRZIZ8MUAyYMrd+zk3GqTh49e5K479nFxfYXh4QxTu8aYX62ysVVj5+wYHdPHFtdZOBmQikS47bY5KkvL3LF3nN9/zw04WosdkxmyOTD6oMdUOq0OqaTK+MQAtUaVXC6MHtZIZXViGQnDEtBTBpbv0Gh1MUyfiBpDEFXkkEbLKqGGodUqk82maXXqyAmdV06dJz02welTp4hkMxSqVQZHJpDjTdSoj+UYpLJpUANEzafeq+JrkBuM4wU2elQjm8tgOT3GhzMoasDgyACpeIj9B69AVgTaRou5XVNsFtZQdB/Ha5BOS8ihgLGxERwnQJRE0loMTQvYt3OMHVMjfOeJiz8/qpXp4UTwO7dNMz02SzieYGNzjd07r+TpU8cwnRJjkWna/QaqrLO41CAYsggP53j64Vd4w4E4kaEMY4kczZZBvdUllYShoWlePfoKqpokO5ukeqFBxTY4fWQNOaZS79r8t98/zHPPLRCVJRJKCCsKCclnz1VXo57ehHGV9ZqD0CjQE1LsyGZ56rk8G26ZhOPzqV99B54T4qsPP8xl02OYhDh/4TSnBYH1tU3uu+YKeq0OTU1nX2qIp14/QtYLI2o++/bOcc3eAWztZmpnf4YWj5DYUaF6QSMsS2QiLfb9wUsc/+IDrGshPvTf/oE777mceqNAvRFjINHmxoO3cdv+Ozny6qO863PfICmF2Dn6/1L3ZtGWZVWd92/3Z+/T97dvIuJG32ffkSSYkCYiqZmiRaMopZ/KJ2gVhZaWit8oCxULyw4sG8CmkEJEOiFBIHvIyMiMyGgymhs3btz+nnNPf/Y+u2/qIfLheymLGsMX19Nea82x1h5jjzH3Wv855/9fYKUhseM0+PdvOsF2ss373vwO1rvb/MCjP8qHf+tnePG8yDevXOPk7jFaOzar7SFT89Nc39wkq2lM5DXuvn03rrNCUd/NI4+9nne9+7fwFQULmUdvH+fHHvphPvQXHyYvTjFWlXnk0bcTi9tYzS4hEUPnJtufrvhUxye4euMajm8hiToaMlYSMDk9zTPPnqdvq5y89QDFXESjtcLW5joL+4/ihH18N8ZzR3gxHJ07yPXFRVpmHwwNwoCJeoV0Ok1r6KCh4NsjbEcgm8vgWNvMFKvU8jWyqSxG3qDRaBIKIflMlaWNVVZa15AkkXqpjpqoRPiIcopeP0IRdaxun93TM8xMjbF/3x6G28scXDhEYHgs3ljF7EdImstXn3qKbCrD41+8yGM//iBPP3GedBauXdrh7W97iCdffAHPF9EUBVUTiF2fJPCZmK3RbfZJRIH6eB1raPKhX/t1fuO3P0J/6KBLEtPlGhcvX2B8coKNjTZJGLHZbpNN5fEi6Do+A9NFlmUUXSaMFGI/IvBDDp+s8dKpLeRCSFnWeNePP8Df/eXjZKbKVGopen2HZiNg354KzQ0L09PwRhbNTp8TJ8fp9EYY6TSO2ccfKeRqHnfeu4vLZ65w4ugRdEOjUC7QG/TZWAu5/9hhPv7Zv2d2zwybPZcj9SK+a3Fle42sMUkpqxEmLr2Wi6LojE+b6FToNmBuT5bl5iZmP2EuW0UvRfiBxNVriwhiDilRGfS6GIUU6XwKECiXsoiywsDqECcSYeBBqCAJIqblgiIhJDHj1Ry7p6s4zoDpmRq2ZVPMFTl/4yqT9fmbdBpywpkLZzEUDSdKSIkGY+NVwmBEoZgm9GRsd4SgigRhTKVUxRoMyWazxIGPZVnksiWG3R5W6FCvVEmEkJHt4rouvX4bWdcIYwFD0cnoBu32DppiYJoRfbPLqOuSLRrouoDoG/zaxy7/68HI/9uHf+eDr71ngZXuOsV0BcHSWF97GdGo4rp9BNXAJ2bUt7jllru4cuMVOsE2s0aJ+q4aCUWuX1hElkIi2Sb2YLuxxPTYHmy3zXa7w6DrYmQrbHV1Nrdcbr2ljCqKrPddcrmQlDHGRmOLernI2cuLHNEmWaJNnBeRlkEtirhhwPWzW/Qii8/89kco1X1kPURojTFVyRIPEu4+McVaN2KukuVoPk0JcD2P9sYWpm9xcv4wkzNzlCUJtbnNiUd/ju0Xn6av9dl79ATus6eJhQn2PXg/3djj7P/4FK9/w9t4ZnuTo7PjyLLI1OwCW9fPce+tD/DcM5/lPX/wFfZHFb733hNosYzdGlJybH7jP/wSf/F7X8bZ3qKQ2ocQb/Frv/4Vntxo4XjwwR99G6cuXyGfLmGFHnEUo/geP/HoWwgHfZbWTSZn8ly+tM7QbbLSAEFJcFoD3vWuY6RTUxTSOVKyQjav4QUK4+UaptsllZcRUw6BbYMk4EYOtucgKyqTtTEGns315essrbXYanRZWKghxpvs2DaKlGViKk9rxwc5pFrIo6XzlI0xMoqIqGl4QkJBz6Nq0OsOkDWwBl3ymQIbzRai4WAP2miKTK1SY2BZDHyLze1NVpprIAi0h11IQZjEWJaJJCoIosHOjoMozpGgc99rb2d2cgpBCInCEWI44Kmz59hpDXCaA5574dt8+9sruEnC5vp1bj1xL3sOjrO+tsPtdxzBNWNuu2U/rZGJ5bgIooAbR/Q6PeoTdeSMQkoyyJdLTE5NoGoR991zK+uNBoqWZmTZxL5/kxSs2ycRFPqdDqqRxrI8/FigYY6QEMikVGQhwHUdSqU0UewhiCa+rZKp6Owa24OqtREcUAtTPPP0NV5z3+2UilmmxuqcPvUK1YkiubyIl/jUJlQUXWWz2WBipkQ6H5LOZIhGMpVymvFaDUmUWN1Yx4tGnH15kVJJJz+W5dpmi/lqll7P4sihMTY3h1RLZbKaT6GaRVcT8qUATSlSLVXIFWAwHIE7JDNWQaKHH8qQKBipiEImR5Qk5HM5UmkZJJc4EglCi1w2SxwlaFqMKqUo5srEgUUSi4iKRr6QR/R9enZIc9CnZQ5p9kd07BCtUsGLImQJkhiiIMBQDLLFErlMiGUOmKiNs7XWQpFFXN8hm0kzNAc4fogkSwRhiO+5JHFEb2AjihKCKjMcDshmDXZaOyiqTL6QRUqpNBstcpkStmmjahq+a9PrdhG0mMD3ETQBRVPwbIlnz3b+9ZzIa3kl+bV338dLL17k4Pxxrqy8wvE7p/FbKTy/zYGF17DdusJ632Vx6Rx3vvYWYruJHYrUtQprbotaocBUZZI/+MTneODkPlKViDl1gv7A44K9hqYb/PnHr7N7Msvt++dYXt2g6/Z405uO4fZsLp5ZYrJuMH/fSc6fucxrFo4y2lzj6djn4d0ZvnBKZGd1mx99SOAnPnYa/3+eonCXgjZ1K83RRQZfWkRxLjD1fY9x9o+/Ti07YPp1D7J96gpLfZPl/gVqxl4y4cuMJXdhqkNy73wb+c/9V+L3f4a/fe0xfvbJZ/jGv3uU4c6It//Zc/Sf+hLv/8B7+OSFIcdvzXN0doKVpav89Dvehde1eMeP3c/1lSWGQ4uNtS6r518kndYRFAm328Gol8hoGQ4fOkS1XsFIBaRmdwEhBAHBjWXWWhWiTp8nvvEcVzcSrLDH2miDvXecpN1uc3D/Xn71j/6RsfEKd+0Z5/T5C+yaHOPBewocOXyCV5Yu88gDb2DfgUN8+cknuePYAZ556WlOnz9DpVYnsGxSooSYTpHP5BAEiWHPZWW9yeT8LKdfPMXbHnuM7Z0bSIbI5maDQjaLGos8/PqH+daLz3BjZYOimmVoOkRKTK/fZtf+PSSDADmlsdxoEjg2d99zC8888xy7p2eRUzqhH0Cvz6HDBzBNEz+OkEWNkW0jJCJhWmXodLh4boNdB6oM1kfcf/ubOHn0JDMTc+D1efb5bzIIBsi+i65rbDh92utdQjdkZXubTKVMEAeYQ5vj+xcoZXWG/ohYiFFUCU3MUc1lubG+zlZnALHAncdOcmHxHP1uk3QxS7agc2NpG00SMQwDM4iZLk7heBbpVJFXXrjO7rkaihZi1KssLl/CHwm8cmEFo1SgNZLYWG1xYM8cvZ0mUk7jlsN1Fq91qVQy6MaQG+sDbjl5hLyiMlWVWB94XLh8nXLuJpNiIqbpdHwWds/iul3OXb2C7SVMTU4iJz6XFtcZq5Up5FR0I0MhJ6MpCiIxrhNQqOq4PR1Nj0kkEduJyWUNdrZWObp3P5IkYQ5HdAdDqtUytu9RyRbZaTSpTtTYaTcp1oqkNZVLly4yu2eOtaVtJEmmMxjiRSFJKBL5MogRckpARmFqosrs5BT/9PVvMjY7Qac9xLE9giBAlnQ8N7mpCarLKCrkcxlsewhygizHFAoFstk0+VyGttUh9BPESCCJfZSURl7L4CURceIjRDHICqMgIEokDEVDlWTiKEKSiFq9uAAAIABJREFUBDQ9xXA4RJJuFlJZloUkSfixjeUkBGFI5Ln0LRtVSrN3ocKgbzIamkyNj+HaNr2hi5oxiOKAlKTw3l99+V9P+mEtryXvf/RO0qkUrVaA6ZvYos29Rx/gyumnKNRmOHRyjM89fp69R2N2GhZWV0QZU7m2coWjE2X8bYlsLmR+/1E+9a2v8+Mn7yYu5HEtn29uLPKGe4/ztT/7JpXpCZ660mJ5y2RmOs1dd1UppIr0V4dcXNomKUZ8zwOHWf32GcSZCoNll131KpqsENddPviHX6L33/6E+mMHsKfeTH7gsvH4n1H/4bfw8Uc/wNbGt/nVv/gdzLE3otXnMUYbdBYDnv/4R8iNOdz3S7+Kqwj80//zXtLpgO1IwV7/Fj/5ua/w9C//HUG/wb2/+pu0G8/ylc9f5InnHme1O2TYD7jv9lv58Hvfz8/9yr8lqIxTzZUZKwr4ccRff/YJJifHMR2X1bWEvK6j6g7ldJrtnR4OCpUkxYrqoTYHxH6CWq1QcnvkMgI6CffcfyfTdY27T04zO5EnM7EHyOEs30DPKfzJl77N9PQsp88+z9zheaLQwfEtOt0GU3PjmIFMY+U6Y7PjqCmdra0G1VyVgqHRGvYpZYv0LZtEFBBIyKgymWoOTdHodrsgCuTSRUzTpN/rkdHS+IJPZ63B4YVDNEcD9h86wNLiFcZ3zeKPPNZXFtFzRVRERBJq03WunH+FcmWMufoMFUnh+soNZvfMcPnGEqEzQlLypOQsvaCHZXuomsB2Z8TsRJXTX79p88vv/SkW115hy+oQyz55VaeUr9J0RhRzGTY21kjlDdabW4xVi0iqgSpKOIMeE5OzWJ0e2ZzGRrNLvZSl1dkh1iTiOEELRQqVMu1mm0a3y549c3gWhL5PIghc29xi99g8GxsrTJYnGFgmqqBw6OB+nnvpaSbmx0kpBmGcEGsiN15cpDBTQlFFfNuhWKxz6eoGew/UOfPCJW6/az9h5LK+3qFenECXBcIkpDJZxnNj0prCRmOHodNnfHwcy7IoZgts7rQpFApsb23i2Q6VUhldU8ik8wycFtP5GSIXknSCZbaQxAyqIWF7Nhklj+3aaIrKqG9Sq1SwXZ98Pk9/0MEPYjKazuT4BM32JpmsQbvfI45DauM1Wp02KaVAp9chiiKskc2g72C7EYgRQeKT1jJkUim6nRYpQ8OPBVKiQRTEjEYmngsjO7hZoOO75HMZdEUll9XRNJme1SKfzZJOyxRKOSRFxLZtBqZzU9zDMIi9gEQWEQHX91D1FJqmoEoyhq5BFAMilu1iuw7FQu4m06IgMhqY+FFM1x6g60U67QYzYxW0tIzrBGhaGtu20XWdVquJICTMTs3SbDdJqRJj1QqP/eQT/3qgld//3d/64P17xxiZfUS1QqmU0Nxep1pOsdVuUaxUmN81zo1ra0yXIvbV9zNXy/FKc4tieg4FmeZOD2M6T6/VYK86RyM22QlWsJKQTz/fYOnUEostuLDTxhXyPHzbBJIbkjVKfOfsyyytDIhTClGQ4vlnVnD9EjPVhObqiEPlOpPBOK+ZnSBXuMqFr14k292hsruGXS5w7fNPc/nP/5g73/kz3Ni8SjBYZP+bfpFvvO11PPH4XzJfvMiJn/8pgu0BFz/511z+wp/w+g99jt6TX8bZEShP3EpqaZED//6n2fV9b+W333yCT33pWUqlAvlChkgI+OWffAd5KeTf/u5/4pVGls3VDeamFcr5HJlcja9+7SKH5iUcU+Td/+4IS5eaRImD66rIBtx+7278/jaBFvHoD9xDc2eFH3zzfuRwi65rcNuDJ5idV6numuZ/PnmKhjbJtU7C1Z7N9eYmj184Ra5k4XldDp+sYcYu+XqWhd278RA5fOA4L718mvvuuoNM1sAcDNk7OUcurRNHPsVclnImjSgEVHIFaoUq/c7g1UrCHkkgMFmeQEoSZqanyaUMSnmD/mBIJV+gkMsQiBEZRUGKEwhDht0OmqajpTTKuQydXhslEVAzOulclsHSGv3IRpBF7MBH1jSyepZEVhElAStwmBqvYfZbjI2PkZJBkkUOH9/L2cunsGIbQRdRZZlc7qYUlyAr+IGDqAiohoKR1UlraSzbJp/OIosyg76FnjJYW72BKAiMEgiCAI8YL05A0bCDCHtgMz81R8Yok9FzBKGN7fV404m7mK2NkSkZZKtp0vkU1bESI98knddx/YByqQhEjFwTcRAiKxKu5ZIvllna2mJ+eppCTmbXzAKqkuB6UKrWqY1ncT2HgpImVyvSGY1oDHrMTk2jZ1SiKCSfyVEqa6TTCmlDJp9LUauXEcWYrGFAAplMCiESCfwQRVcxNA1ZkzHSGbKZHKbZJ2Nk6Tfb7BqfxB9aaEaKltmnPjuOmzjYkYegSwy9IbGSkM2mcQKXRADP9ej1R7ihTxhBHIrIKOhqClWUSEsqcRSRTacJQu/mO8ga7mCErmqQRPhCTJwIqLpKLEbwat55WtcZOX18QQEEVFkjRCKMJLp9k0QUGVgOtnuzGjQkIfFjVDVFBHieT0JMJMR4vofruTcFs8OAyPZu3j4GQ0r5PLIQkc6l0WWRsgFeFJI2NILIoW86FLJFojhEVSXy+TyECZl0ClEScb0RX/x6419P1srv/e6HPnjv/mmMfIFnz21hhjsEjsnB6Qkm6gcRoojIh61uAz9O2J/TsFZHbCciVXlIWpSZnEvTjUIOVqaZHdNZd2I+8/gSW17CHdM21zdDlvsyeipiT1ZBHDfIVPo88ZSFmCvixODaAVLgMjFfZjCSOHVmgFPNcLw6wRsfiVl4w69RvvUElz//HKpyg+HZRfQr32LPj3yAV55Y4cTDPkvPjBCaKeYeu4PvfPxvSWQYDTq0z79AONzNSmJRz4Xsuf82Tn3haUqzNdZWn+WOH/wVXvqj/8zM4Une9POf4YfecpIvfnWFVFnmD973fj7yp3/In3zxBYoi3HXwbu55aIzr569z1z338O3nn2Tfwhj7js2ycGAS2zKZq+fZv7fG4VvGOH5oN1eeP8+bf/gu5soutx4t8shDd+L6Fre88TYe+J7jSHGf0rSO6TY5eHgSa7SKRI/xgomkQRyMUMdyZItTrG0tkk9XWO9uE7s+SAnesEN9dg7HGjK0hlQqZUa9IegJiD6qIaFKAiMrIPFClJSEmL2ZQqZmNEQJSsUckiZh2zbbjXVkKaaYyZPK6IiSgCJLZMt5NEXG811iIaGQr0KSEPoeA9fEVWWKgsZ4ucKi10ZSJUzPJooEXC+k2/XQcikSMUQ2dFbbm6SzNUahRafjMDuhI6cS2qMRmWyOeqnI9MQs280GlWIRL7xZEh5GMTvtDoIgEfoBYeBhdruoCDTdPpnxCrXZCn7gEEUiuVQWQU5hWh5ZH0rZIsVcgSAJEaQA1w0pFooIks7O6jbtns0gcAnjCMez8YIRQ6eHoKTQswZx6GOZJmkjS2GhgCgrpHUDtztk/6Hd5Es6sZvQ2GrRG+wwv7Abx4sQpABFMgi1iKHjkElnyackdjqtmyIHlkWtlKfZHSIikzVyaGoaL/KRRJlysUJ1fJzIDQjiCDWjAwr9fh8/8IkikSQQqRRytDpdcpUKPdckSskMYp9IETAHXbQUtHttSCIkCVzXwXRGmI5NStNIKRrmqEsouPR7PVRRIYg9vNhnrFYhCT0KuRy+42HoGoKYEEcx9XKVnjXASQLUjEoiioRRgK4pgEoSC/hhSJCEoGnEUUTgx3SHJt2ejSRLOI5LSjcAAVkWGdkjUnIKXZbRVI0IyObzFFSdnJZGDmNSCNQLeQhi1FQKWZGJw5B0Mc/y1haFjEHJEAjEAoqQZ+SNUPQchUwWz7GoVAq0Gtuoiorn+iCCktL5wlfW/2Ux8lcVgl4ENpMk+T5BEOaBTwNl4CXgnUmS+IIgaMBfAbcAHeCHkyRZ+efW3lXNJr/5E2/AxeRvvnie+dkJinoPPa6QzuWZmJnh2qXz9BULoySycv0qx4/cx7XmIpovU5ib48rzL6Or02TmbS6+0kNJBmSK06TyEe5Q5dJil3S6ihK5XF7ZxPU0Ds0qtFwPQoNQ9KlkNGxHJA5CHDvEtAz8x/8Lz++c467v/zEQdhGFI55/7y8hHNiAYYbQC7n7/fez/fttPnfqE7zvqe/Q2DzFmHE3X3jPT9AWbRI1pqbqfP8f/yFf/sCvE4Uib/rlt3DtVIFcNmTynhN8+j+8h9XmEld3Qu69/0Ec1qnkyzx414P8zh/+PoX5AjO1KfqWSSorUVQSuqMA07e45eARhsMhQ9vF0GW2NltUJirstJuoqoQoioRhhCYnaFIWXc/i2n1SasRmt0kkRcyOzzJoDlEKN6+mfgA7zS0KhRKGqNLs9ynVUtx1+ASvLK3gJDIts0vajrAin1ShgOglBM4ImYR773kNTz7xHFJaQTcUlpYWyeUKVOs14jgkCgU8L2Df/nla7QYZQ6fTahEJIhktTa/TpT5WJRZkQi/ED1xc20bSUwiCQKFQIJ026LR3cCyXvXv3srq5jmX2MNIFclkDu2vR7Q/J5/NEUYSupyGMyGZ1Op0OhVKZgT0kEWMERaCQLSOKCt12i0qpBEGIhICEiOxFZNM5eoM+sQFW5OOObAauTS6dQ5IEPMdHTASMXJHt1g6qlOCFInt3zdJeXUVTU4zPTLG5uYGayt6EIRyLdCZPEAS4rsveg4d4/jvPUs1UGboDclqOxHbwNFAlGVWScJwRmpjmyqVVFo5NYTsWuUyeTDrLemMLKaXc5EqRNEQ/ouOPSGKBXCoDsoUfSUwWKzh+xFZ7iyCyqZbHiHwPFIlypkhnOKTVaHJ4zwGGXpcovCmxZjsWlXyZoWujyQq9dgslpSCJaTRJpNXrMlkZR8vptFsDBDXGcmykMMEjIiYirar4UUiUxMRxTC5bQpZVrFEfiHEdi3w+j4TIaDTCtT0URcGzQwbDEfvnp2kMB+AlIMpEgUuATBR7EEWYtktazZHWU4ysISnNIEHi2uYGvh+iaTqWNQRZBW5i6AgxeV2jWMxjOyMERcG0RxixiJrVUQWBcS2LLQRMV+oU02m2B42bvOeagu06yKqENTJBS3N9bQ1NFNFzOYJYQExC5Nhn6AdksmUyho6U+Bhyiih0MQOHXDbNsDMgEm7i7bIo8rafffq7glb+b8SX3wdc/v/1fxv4vSRJ9gA94N2vjr8b6L06/nuv2v2zrePZbPa2yIsab3/Dg6hJi6Hl8JoHbkcxIwRzyLEThzk4OUNVy1OYqDMzWWVqbJa52Wle+MqzvObYHib0daaKVQ5O7WF2fJa5gs2EEjE9LlPE5tZ9FXY2Njk8NcNcFfK1PKGvo0dp0lKOlJ9ie6PLW4/t4vzffISv/uxenv3On3Ls0R/Ejsdh+xJnPvbjnPjr3+fuve9EifMQm1z6vW9Q+JkfYt+uh3DPv8A3fvOvIOhjzI1hpFLEZohk5Fj9+j+wb3o/6arK6EpEfP3DXDr9CZyLf409ITP5+tv5kXd+P2plwKGDY0zOZPiHZz7N/nsnyJdFxqdSzM/kyaiQy2TJ6jcDsDvrLQIvQunbTKRLFFNZmje2IE6QEbGHJoQh85UFxnN1OqstAisidlPMl46wdnabzXN9dpWOsnFpQMWYJbBjioUxglGAnM0g6TpOR+H8yze4cW2JXmOZyijiLXe+lrnyBKN2DyER0VMZcvkq516+hCiquEGA58Lx4/cShCniJGFjc5t8LkcpW8BsD9je3KDTaxNEETIRuVwONZWiP7AYmSahIjMcBcS+wKDVwez16XTarKyt0mxvUKikuXj5HCuri0iyQKe7xXpjmeXmBqY5wvMCNE3HNAf0+n0se4SXeIx8E1FJUFIQhS7bjVUE16WcyRLYDp57E/eMhYS+P2Jn1KNh99hpDRjZHgLSzcCWrOJ5AdVigayqYJk9CuUMSjohURx2llfIZHN4usj59UWCJMCNHRq9HVQ9w9rqElosE3dtll96hmjUY2DuIEoRfr/Hmw/fgWaHjFyHoWkROvDVLy6SLcyj6QUcOySKJDoDC9cLiKKIaOQhhD6ZbBolFihmVFI5GUVM4fWGrDXW2GyskpIFVGRGLZPYcwkCk5WNS4yXUhw6MMfI7JHVdSLPJol9JDFhOLwpMNEftknEhDgGxzWp1Uvs2T1FxoBuew03GGJ7FkoYUdR1UomILupUc3UcO6JSquOPAuzBCLPbJ5/KghejIJLVVYKRxXixTFHTGMvkyOYL6Hqa5a0tBCTkrEEiWBjpmHTRIJYAOSZVMBibHcey2uQyKVx7SLezQykjU0wrCJFPuVgh8WOIRaIgIgkFRiOBXmtEIV3A7gxRXIEkgtByiByPWEtQNAmkBES488BhRBHWWw1sIcALA/RsFsmJODF/gGqhRiqUyUcJdT2HqmSYLk6QQiC2HTRBQfJ8VEHBcRws2ySRRFzfuxn47La/a+f8XTlyQRCmgDcBf/5qXwBeB3z2VZO/5KYAM8BbXu3z6vzrX7X/37bQTWiRsGY7rK4tocRQKGRZbTeQJwWkaISmJ2QTWFzfIMMEq8svUWrn+dbp03zPoVmeOnuZpLaHrfYO943luXrdpDa7jxtXFC6dM1k4cJC/+8Jp9Kk9bHtrFDIx5qrHbFpk1/wIwXF5/2PfS/vK1/ip/+8X+MSHP8X3/PpvcdcvfgbD9jGuXeaZr/4mtx39FaTo2ziPvZXZPbcj25NM7JoiM30EMely+flF3vHR/4HjDOm3TbYim6hk4ERDxmf38cpYh+ot+/jmhb/hbxyHaLbIZ86fQ9QC0pKIrvkUxITGRp+LLy8TWCGaGyH3BMzWgI3LKzRXu2zcGLC26LB/4jhhM8G9EZJEElcurdLe9FC8IlpvnJUX+iRNFRrQudFltDmgolRoLvVZPNtjIl3gkbv+DQemTrKzbLJv7Dae/PxLZP0KmpVlobyA2Ryg+wl5NaE2XiKvGUzmJ5F31fmDz36Sy5vLlMdq2M6AVrdNf2TSGQ0xsga+m1Ayily/skg6r7O1NkSJDAbrLYxRyOrSGq2tDmbHY3ttwOKVdSw7uAlDjBxajS6NpQ3ikYckyESOh9npEplDCrFMMV3nlRev0tscMl/fQ3enj90NyKlliKFSLGGbDr12H13TUBUJ3/fQdZ0oirh4+QrdjoU1cBBRCCITzzdRFQFFkQjDkCQWEWSNUEjQdR1BEMgYaRRZRkFGkyRKhRL97gDXGpExNBzHwTY9qrkaA88lbZSwVnuMJVmyRpFhb4QiqZh9E71cobHTIhiNEJ0BVT1DynYJG9sUlITFxUXi0CNvyChKgirJfM9Du1FTq8SDFicW9qKEPsnIZr4+hrPTJi9pSM6IzfVrHJidR4wj/E4LwYoZz5XQRZFqwWBirM7M9By+b1LO5xlZDomgcGHpElfXrhLg0em0yOVSpHQFSQE7diincxSzGRRVZG56hvnpcRaXr7HSafLS8hUSIURXBdQ4oFTM4nkeiiKRy6RZvb6MoQkknsOemRkWZuYYK5appDX2Tc4yV6yTCQSma2O41ojaWJ2dfofeTptDCwtMTlRQIw+336OQy5FKqQy7O2TTGfbv3YeEwLUrV6kVamytNtAkjdj38MMIUZKIoojtrR3ctovbd/HMiNCKcG2B7Y0u21cb1JUyUigjiClkX0JLFKKWxZhWIBuIKF7MK1eXGQxufkdDVlHCmKgXYKARDF3qmSIlKcVCaTc1uURNzCENIO0IlEgxkapQy1aJ7Ahd0FA9EEIPGRHLcshli9+1I/+uoBVBED4LfAjIAu8H3gU8/+qpG0EQpoGvJklyWBCEi8BDSZJsvDp3HbgjSZL/7e+lmE0nP/eGBZqyyaySZ3ymiGsWefiRI3z0jz7L1KEF6nbCVb/HP37lKU4cmmBrUWTqARl/OyLURJ59ccDdxxKeeNLjp952kK9cuMIBdYrm6nW+dj1CMHSMtMpgNOANd1RZv9bFzeuY1yzOP/5XjCcQ33+Atf/+afKPvIP4xmlaZ9bwBy8zftd7cF98P+MfuMjyZ36a9AshhdsGpH74k0jnrjNKr6EGZYQDM1z6/Y8yiJ7h2B3v4svf/DKpakKSl6lIFdba64iqT6ok0V5x2VWc5Or2FU7sugVN0yjFOteaayyfXSZfMNBTBYLYg7zPqXMrLNT3IkUScq6MFyZ4O5s0u4vkc2keestjfPEzT5DILjOTU+zdM82NrSZiouBYNoosEUkJtVKZbj/ECQIO3zrD6sUNbrtlL8+dvUA6a1Cf2k1zrYFtt4kiiT1TZS51LrOzuszC7j0IOQ272aex3cGYKhG0htTnd3HmzMvsmp0iimF2djeD/pBaqcqlizeQ/YBsWaM6V0eLYKvVZdj3qebqZLMStjckm6mQkvP0nBZXbiySzmpEoUuchMjeTYmuhtkmW0wzOTVGt9kEM8SVJcbK4zS3G2gpBc+ySII0I9ukPpUjUW8STCVJgp4WyWQyNHYaZLJZnCBCyug0NxpEns/Y5Bi9zg67d++m3ewyOzGHaVoQhoShj6be5MhudZoY+SyGonF9fZVyJoOoG6RTOhlJodFcI1WokhY0XEcgN5bl0sVVVEPFDWyqmTybO1vkiilkKcVk0SAcJJRzY5x55Qxjc1XWL1yjMp5H1Q0unFnhxP0nqY8VaPf6yGJIoZKmve5yYmGWa801VD3DwBzheR66ptBZ3WH/Qh3yBoKn0vVtcnGC3YuZnK/j9No0BtvkqxMsrWwwtaeONRzRshyiWEaTQFRh0hinXi7RazW4fG2JETFjkzXEkUd1qkIiQ2O7zbXVG1QrY0zNziFYNmo2TVErYfW7bFt9iqX8TUWfwYD58Uka7dWbAtNuTL0yTeBHBHLMoDkkraVIpyQQPHbMPr4sEolQTdVprm8wNl9EsT0GfRc7pTHoN8jnCwhyhk6zQRALeFaIP7RRRAVFkfBCl4EdYpomMzO7GLRtzK5H1x4iqDKKLFJXNNJZFSklMXBMJDXPMLCYMDL4jsnkeJVCpUzgOIiKjGykyOUMotBDjEakUyqtzpDxXfM0Ww1KpQJu28MdpShkc1iDLfqjAflKilw+gyYbRG6MqKYYegMiZwB6zHbXwg1BQOIX/vOFfxloRRCE7wN2kiR56f/o8f8vmiAIPyUIwouCILzoBi5aschMZoGG1ebqy5tMlxU+/6kXePHqRbrbLTw81GHMQ8dO8gP3P8Lp7Q0unRPYcmUivY7nxmwMs2z3XXZkl7okcWp9jW9tgGyAlHIIrIiZ/CRnXhgxGKo8MHGUjWf/irG9C5w99yJr7/sJJn7mP/Lt3/hPPPWx36AsXOfA+z7Gyuc/RnjPb9H6m+9l4a2/Qel3P4pi/Ajf+X/vILa+gbz7AaSNRZY/+vPcaGxzaX3E4xf/no7bo5ZNcVitsX31ChnVYPnaDmyq5Icq115eJm1V2FxsE3cE/ujj/8D4xGGm9xzESJdZOHCQaxsdVGGex974IxTKY1QmphgbqzAzV+fkfXdx8pYHOX7itVw8c5Gjd5zkwNGT6PkiZigRBhAiYlTqDEMZP9FY3u6y59AeJEXilRdvEAoJz7xwAVUymKlPsX19jWZjA1XNUC8V+MbTz9NYXEd0UzQaO2w2Nhns+MxW9rAvPcfdt7wGa9tjqryXxnKDuVIJs7GG1dxkSs9xbGaKfMGg0xnx0lNX0aQ8VanIbQdvpVCpEQQpdHWMXsdhfXOL9rbNPcdeT1mfIhmV2D9xC3ccfRA5qSIOMjhdg0/+6bfYXLboNxVUZ46Xv32DzoYDbpW0eoDZ6SOcPHE/S9dNri01yeYMCBPSeokLFxaZqe1B6Krsy+3FutHHtmFCmWKw2uXk0bso6HWq6jiLL1ylpOQopHRKmRwZUaSmFmlcXSYcBaxeW+au3ceppktogoJpmgxdm5yc5/jkQV534l4GzS0e/+oTBHaAu+4yXA6IuhJVfQYprIOTobMZEzoSpj8iP1YmJaQ4fuwYh2eP4rUDHnz9HeyuzLJxqYeR5Bi0Qp5/6gKJCtd6Q9qjkOXVBoO+Ta0wRjFTZnxmip1BwrABNxYbKK5IKVtF1iM2G2tc22zio+JFAvffei/xMCa0NLoNm0MLkySOz1RhGtNzubq+xvWrayS2wLF9+zmysIdKaZqimGXz9BbDTY+jB24hcBKGW33K+SpzuRrb129w6MARsprK9evX6Ntd8hmNra0NxCDD2qbFjfN9nvinc5y9usmLLy8SRBCSMIoiLjdHLK5abF8dcunUEp3lTY7NHgQL7H6MmqnTuNFDiPOYpowWqRQyY/iWj+fGjJwAVBnLdkmJOaxuyGR1ntWlLRrbfXb6Q2I0iFT8vsf62g7bG0OWL28zaoT0rrd4zZ6TSIFCHOY5/3KLaxc3kVHAjsgIKjghUphQK08z6IVsdLqcvniVrdUWw50euiFhBy2anRtMjNWoT9ZxBZHVjQZb611efuUc164vYtkespxBdNJosUBRNTB8/bv3p/+nE7kgCB8C3gmEQArIAf8AvBEYS5IkFAThLuCDSZK8URCEr736/B1BEGSgAVSTf2ajXFpMxgoJ/+kn38FnvvZPpByb733odpRwjBdfOsPDjz7Mt77wBVQjS6GU5SN/9zS+nsexJQR5AEEaJI84jqjV5hmvb3FtcYTlSMhiltCJePCNczjOiLMvL/OLbz/AB/74U3z537yTh//7X3D2d34ZoVxlZfsC33fvWwl3v5anf/s/Uq3lWXjvO0j//cv0fnCStf/yJfa//TaMfT8LlR2wJ3F2vkFcuo3Olz7H5f6TTM2c5Hp4g+GFdSbr+2i3V6jkK7x4+gy3P/gw//it73Df8TspGTpXri2TKRbpdrvkCmly+TLg4pkmA8tDllUiJMzRiN27d7O5uc2ddxzl7IvnUZQ8ltfCUHTiKCCKfRJFZ2TaZFL6Tbw6rTIaOSDIuK7MI7a+AAAgAElEQVRLHEfUx6q0O1v4XkguW2Fo9qnX63S7XaIkIZMuoioRceRSKZdprTaQxITTF09RvXOC/uo2737wHbiBzOrKEjEhmlFm5Hnk01Uuv/QslxcvUJ+YZmZmP7LkMD65h1QmTamW59SzpxgfHyMQoGtZ6KJOnPiQiIiijOOajI9NMrJNUloO1xlgWTZiSsXs9um3O8wd2EUQJDjmkOHAZd/eXXiew+ZGG1EJyWULeO5NAqNR1Kbf3uDYof2Yro1nJtxY3kCRDebndjM7PcNqe4uKqvD8yxfQCjpHDh6jpBcoZAQuXv42iiywubXNwsIeoihip93GDnVyWR1v0CfSIkQiNFQiX6aUz9Hq21y7usShk0eQsga9tslth2+lUpvg0oWLiIqMbQ8J7SHLq2vIQUy+WqQ8VqGa0RiZFpEf8fLFy5y45RZW164zNzeHpqZZXLpKSs+QKeaJJA81lEGO8XyfbLFCpz3kxLEJFq9sYFsJiqyze7bGN775VW65+xjPn/0O+UKVXq9H2ijy/Q98L3/9l58nP5lm98FJrFWVbMFj4IzoDG0SUefQwiSxPeL81ecZhh4HJg6QyZXo90acOH6QZy5+hUy6hCboaEoKK44ZdrukUimur29wZN84hXqZ7vo2seswvTDLUmOD+469hksvXqDV3iE9Nk13u4uWEtm1b5Ktts9CcQq/02PgDGgGPfLFHFbooKs17HaPOBiS1jUuX9zENE1+6O1vZOXGBsuLqyh6jiiBjJamtd0nSEQ21pu4foKmySCmsRyLfCFNzkiRyRjYoxGFQgHHcTh4+MDNoHu1zDPPfYdiNo0mx2hSQjFfIYltMoUs6VyaielxXnzhNKbgEyg1SonEwekKq/11xsfHGbQcNCGLK26x2W5TLs0y6Jnk8wJpNYWeyeL3R6iKQvRqdpfVtfmFT575ly8IEgThtcD7X81a+Tvg75Mk+bQgCH8CnE+S5KOCILwHOJIkyU8LgvAjwA8mSfLWf25dQ5eTaqnGr/zMcf72E5s8cm+VK81VjKrG3Qfu4dyFGyhqQsttcP56wIUNizjsEIceUiwgqXkMPcayRgReSNaYZBRaHNwn88aHjnPm7DJnz9zg0HieZ89YLH7iEbzlGqU3T3PuK1fotjvkvBh9XODkg69DHr+NYPNlpNvuJhD20fmv72EzlLjjR98A1YfxUyHPvOcRXv/T7+e5s8+Rr9SpTaZZfOkJrm1tM4wtXrf/AU49d4ZSqcQ/fOFLvP7RR0nMiGKuyCAaUDBynL90iemZORRFwXX75DNVRuYAEYPEUPFdnyAIAEhndeIQ4tAhCkLanSFzU3NsNtZZXbnCO9/2Q3zpG09RypcQBAFJUpAUDcuyCMOQXC5HKV9mOLBIGQICEp1+B11P47reTUmvwYB8rkrGkGk2NrFcj4ffeDvNzS12ujae3WV21y5kMcDZGTF75Dit1jZhdPNi54UmJ/bdwdXrKySiTxgOGCvXGPYsipUyVxYvs3vXAkauwLlziwxMl727p4hijyhM6PeHGIaB43jIUoJjh9z/2jt59pnnsX2bvVOT9PptTF8mEV3iQMIeDShVykRRRByB53kMLZNKpYIsSvQHXc6dPs0Dr7mVMIKsUWZ2zy5urN5garrG2kaDoelSL+sMRhGZTI5MJkPsmURun25rgxgBQ8uxeHWF8dkqrR2XK9dWOHJkHjkOmdu3i5e+c4rJ2hQpI4sky6zsdLnztntYWr7G+fOX+IG3PoLV7ZAQ0eoPGZk2+3bPM+huEyQClVwBQVPwPA9NlClXS2xtbVEu12lu9XDcPt3uFgf27eLMlSvcdsudXD1/iaMH9+P7PmIqhWmNEGSJjKEjazI7Wy1UTSGdUUhC/3+19+bBllz3fd/n9N63776+fZ0ZDGYGA8wMAJICBJEQuEmUYm0RFStSUkoUp1xlpSqLrSRl05U4ZZVsyY6tKErFiRKblhRLlsxQ4gqCIkiQ2DEzmH3evt99633LH+9RQTGWRUuKBo/1PlVdt8+vu979fe87/bt9f6fP72BlS7x5/RqGpbFcnyEQMis7TfyewzPPPMPnn3+JxkyB9etXOX/hHPXJOe6srfHw+QuMh0OuPHKB/+GXfp7phUl6XYdabRbfGxE5NheuzKKrGe7cXsV1fbKFGeQ4RReCfNnASdr0bBc5kBER3Lhxk8VTs5DoZNUsjUqZjdZd/IHNE9/1XnabBwgpomDlyWpZXrlxndRVMPMGtWKWe+u7zE5Pockhd+7dw8rN4kdDEjmguRmSNXJ0Bl1mFuYRqWBvt4NlWazc3yRFJZMxCZLDBc8lDTRdZzgckstmyBgaJAkTjQar91bYWN0kkzOoVLNM12q0mk1MK49rD0mERLlWJZM12d/dIdYs3DhDJkmplQwG3R7z8zUyOpi6wdr2KrKks78fYRV0Jqqz7GzcItVSJssN7qytoVsFLDND7+CAX/rC/w8rBH1LIF/i8PHDMvAm8JNpmvpCCAP4p8AloAt8PE3T1X/T35VkkdarglM1kw9feoq/8xtf4NlLJs+df5qxF5CvTbKxvUYUjrjf3eb2SkrBVEn1EhutdapFk8hLyWdlKoUiG60mZlbhyYdqzM2a/MbvbKAWimwPQ/6PH5vmub//Bumnf5HYlLl38xWe+E//S1b+8W+hnKohV5vs325SCpcYj6/y6I//EOFYIei6vPj688z3A7plF7Oc4/n7N3n89HO0g3Xc7j6eWqB/bchUfg5L8bl5e4VCfZLy/DRZRWGzNaA7GPPQ1ATNXh9ZNYiiBMvUEVqKO3Q4c2aWrb0m/YGNqmjIKczPzxEkHnvbe6iyhqJI7DU3qVYm6I9dDE3HVDXSSOCHAbKqgAyGcbiUmG2PuHLlCt12k35vzNmHl7h//z6maSFLOmkqIcuCclnnxtv3uXjxAoPREAkfWdL48uff4PEri2QrMnWjRq6a5fZuC9wQoSRMTszhuDb7+0OieEymmGNp4RRb17ZRCimmJkgTQak6zb2VuwzdETOTU/S7I0xTp9fvMDk5SRJDuVoiSSOylsbqyhaqIqNrGfJZnYmMyVp7RHvYx9ALDNq7WIUippWh1elRymWRyRETM3D6ZK0M/c42BS3D9FSOdtNmdmmKuyubmFaRUr5Ae7DJZOEUquZiewk372xy5qEFBF1uvfEWhUyJ2kyG+zfXeej0Ffx4wNbODo8/+V1ce/Mam/f38EKbslVBzRocDPa5cHaRieVzNHdazM1M4SFo9vtkZIMwDOmPOrjjgKl6A0WJyBUyxF6EE4TIQgE3oDZVJU5CXvnqS+TrGZYXz1IsVtjb22bU7ZAQI2k6U1MLBARs7fXxgphqKUvsdyiVJjHkDHEY0Gru0RsM8L2QmZkqttNnZ79JoTgBZLhy5lH0usJEucx+00GWuty7t0K/E/HsB9+P7bYhSUljjTeuX2Xc7TB1qk7ixlhmQL87ptkbcmrpIVZXV8nkM4iiydn5czz/+5/i3MUqjh3gJDJaWmR/r0O326ViaThRilkoM+h1mJ8oMV0rcfPGGu2uT326SoBDwZBIkgCjbOF7Gvu31ijU6kyVTLLZLNfu38VJDaamJljb3mT9rs2p2Rpj26Y6U2PQ6zEcDvFdhU6nQ7nawHNSNEtmdmEGRZNp94dMVBrY9oh6JY+V0ejvbTAe+dRqDexgSDBwyGcsdF1nt9vl/NllWt0B8/PzXH/7KrKUMnIFy6dPcfrUIuv7G9RKk6ShRz4ns7e/ybWrN3no9MMMegpyxscIHR67dI7PfvkrVMuzhFHK3fsbzEzUOTU/ycd/4dPHZ4p+3tLT/+gDT/N7L73AX/vJp1m96fH21j4feLIM0TlGwXUUUtp9l9nJKbyB4IWVFTaGPopkI4IIPa/S3ws491iWzZsOf+XnPsgb119h/myWP/hUl0tnatx4u8cX/5e/jq9pvP7Jf8nCx34AaeNNcqVpdkyd7vY2frbH3qDPKa3Il16/xk/90A9xdWOT7yrVuOq3GO8eEBZNlquz9OwRu7vbXJo8z2e++iLnFx5nYXqRzrjHoOMi1JAwkjho9nHcAJF6/NiP/Qif+eKL+I4HIkZTDpeqsscec8tzhHFEa79HJnv4dMThCijy0ZqKEbqikKaHz74O+n1URePUuQVEmLKyto2QEmRJZXZ2jr39bb7/I+fZ3nG5eqNFISfh+hGaItAUld7IZnFxkZs3blMuV2n225RNjTASXHx0mtZBFxFZIHy63W0eu/AIduASJBr22KdSzbOz3SSMepTyJTa3PYpFDccJkBUVw9KZrOXp9fsELpTLMu1+TJpINJuHa2H6nkuSpkShy+VLj7B3sE8cCer1OgcHB4zHYxqVMrIs0+w0+Ut/6YfZ3NphZW0d33UIwxgkQalYYWt3h+lajY9+34d54Q+/xMr9DZYXppClmDT0MXQLWZbpjccIRT/8TFPI54q0WjsUsjmCwOOrX36BSxfOsrG2ztTcApokkbNMogQ6gwHF4gyvX32Ln/jxH+HVb7xEbxBhlUucO3+ag901vvrFr6GbRZ58+jKKrqHqGmGUEATR4f9Tk2mUSgw6LWRVJZfLoMgmmYyENxwQpynjUCCSkEImw3A8YndrmzgIyZfyhGHI5OQkumkwHjl4ccjk1Ay256JI0Gk1sXJZwjCmYJkUc4djFIKYa9euYZoZypUCY7vH3NwZ5hcfA8mmlLMIopDPfv4L7Gzu8dGPfZT95gFhHHP97dv0en0un55h8dQin/nc55mZaGCZWQZDh74z5slHz3Gws02i5tjvDZEliU73Jk888Qg7O1263ZhybpJB74BCqYiixowGDpZlUSuXaHXWKRWL9Htj8oUKr759H1KFudlpZiZqDHp9svkMu5v3mG9UuLnSY+AqWMUC+WKexmSGcn6G0bDJzOQcb7z6VbZ39+i0+yhqATgsjSBkKORzjF0HoSlYuRyKJNE7aFGbnKDZ3CdjaBzs7WMZCv7YI4hlUllnslIkn5EoVcvcvb+GQGd+fp56o4rvDjho7mJkckjK4ezOUnWKWsWkVMjQ6rbo725z9+4K1coEYZBQnqjzja9/HTXSmWrUGSZjnvnu9/PK177EhYcW+an/6evHZ4r+J/7WJz4xV1c5U8zwu394g498zxy1ybPY/W1qiwuEkoKSBPSbTSrFOre7G1ROFbhzrclENQe+yvnpiI/+8PdgKClmGOOFXarFCS4/dI5o2+djP/gE9ajHB3/yI3zyX3yKwiW4dW2HlrtFrZ7lxv1VttwNTEkjFTK7W7s8+f4rfOWVr+F7EQfdVTJTFYSkYZUrdFa2ibsBM6Vpbr5+jyee+BC37u2SKBJpnBKmgk7fIQh03NDjyuVHmJya4MWvfg1FNXBsjyRJOX/+EcZjh1w+x9r6OkKSKOSKdHsdqtUq47HDaDQmikI0TUPVdZIohjhCKBK5rEWEQFMBWaFUrhJFEMVQrxSJ3TK/+VufoTpdoFaq0TxooSiCjGnixwHbOzuoqorj+tQm65TyEiQWjWlobw+ZmpgjkfvMzy9ycDDgKy+9RLFUI5PROGh2GAy6aKqC73n4YYrtDEhiQRRG5HIW3XYTSVZByDiOT7s9PCxiZGhEcUDWMiiVS4ztMYNhjxgNP4xxPB/X9zEyGTTDxPUC9g/adLpDtrd3cW0bIcDxPCqVEpBQLOTo9Zs0W02GAwcrkycKRxCHjMeH1fC8KCGbKyBIKRezWKrgoNtndm6Ca19/FSn0mKrXmazWCYOIFAnLsigUq0h6gYmZh+i7Q556+knu397iy8+/zvs/8hxmzsQwFaxchlyhxtziHLNzk0S+BJqOErk0KiVM0yLCJY58RsMxrh/jRj7b62tUiyZoBu1+H9Uw8QZdDE1jNB6ytLxEoVRm7MdkrQKxJOgNBqRHM16FpNDv9Wh3B8zPzRO6DooE7niAqSvs7e+xtraBrMpIasjy0gKb6012dnex/Q6GLLG1tc2tW7fRzQylSp52q0USJ5i6yWgw4NTyPFEYce36VWanT9HrjQljKBarVItFbt+6DUJF0TIIYioNA9UyuXr1ALwcywsLTEzmkSSJasPAdx00KUupUMJ1HWJRwLEV9g48tvccZqYnmW5MMTs1gywEtZl5ttfvEvgBd9YOmJpb5vxj50gJuXj+FI3yBKPREM8fctBcp9fp4LgaAzshSCXylSz1yQopAVHskwgFM2MyHI1ACCanauxs7xzece81CaIQTbMY9j0G44jaTIPp6UkqlRKlSpEwDJiYKZJKDmcenmVtZ517b76NY7s8cuERhqMRskjIVYs49oirr76G7AXEroQzsBGpi9dtkclYFCo51GyIHMm091Z5eHmBjZUNXlgZHZ8p+n/zb3/iE9/9yDRauUCeAp/8gzf56R+9xGZXIrBvU63WcN0hZx9/kj98/XWe/d4rGLrLXEXh8kWLD15Z5OM/8iREMpcuyXzkqXPkSjGzS/OUagnV2ZR8TqNr+Lxw9WsoxAzkIvm127RyHiKToTMck8/kMQsSuSiPvFQiaraYnZilGXaJFItR2yceSnQ2hjy58Ch+oLN1MCBfW2Rzc4ep6XmGox69oUOz06dYKmM7PgkJzshmf79Nuz1EVXUq5SKdTvtwksfQpljIk83nsV0XSZLJZExs28b3ElJSSqXC4ZqSvRG6rlLI5/C8ACub5xd/8ZP8wPd/gN5gRBwd1fXwPZzAoVrPsrG9zcz0NLbjUKuUeO6572H/4ODwji2fp9PpcObMMm+8+hbD9oinn77EL//ir3Pj5l0+8oNPsbHe5KDZRUQpVy5f4c6NVcrFAr1Bn17/AFk2Ma0ycZiQK+QYDEYYhk4hp+O6PkIySdIY10uxbYcw9FlYWKDVahPFEXsHLZaXlhCpoD8cYxgmaZrgODZTExOMbJdOu8tEfQI3cJhsNFBVGS8OKRSquJ5PCpiGDqmGJFSEFBFFA4JQIQwFxXwFPZPHDz1SIRgO+shpwuaNe/y7H/8QuzsOL79yndmZaW7euscHPvhh3CBiemaOYq1KqVrGjRwkI8UPFDx/RLmR5/zlh/ja19/Ec8fUazWiMOWTv/l/sXK/TTafpe80UTWNpaVZdne2MTIauqKzcm8Dy8xhWgb2yKZem2Q4GBAnEpXaBBsb6+Q1hf12DxQDSZEIAg/NNEmERLfXR9V0qvUJFFml2WyTJKDpBq1+F8vMEPoe+WKRZqfP7Owpbt66x3AwQtdN7t5uUm9YlMo5trf2GAwcdvf2Wbm3gjMaIpCpV+vs7h9QqVQIPZ/Ti/N4scAeOYz6NqpmMjE1w8MPP0yzM2Dp7HkqkzM4XogsYhQ9j+vksXSL+bkpjEzM1bdfI0ZhZ6eHqRlM1KfI5AtkC3lUQ2VqdoZHLz+KVTYoFKusr66jaCqmlcWPQ3QjT764yN5+wPTCQ2TzBWYmp3n+s8/TcfsYpk7RKHL15W+Q6HVM02R+dpIPP/s+2oMRcRRiGgYIjXwhh+c6mLrG/v4uW9s71Gt1HMdD1XRUVSdwPLq9PvXJOqomUBUFRdfwAp/N1QOW5s4gYpU7N1YpmEUU1USWFFqdFpqps7e1zTdefIm9rV00SabVGqBncmTyGVAELResfJluawhhSqWSYzweoWcKFGvTfOq1teMTyH/57//dT9TLAeOexPnlmItPXWKze4/pSsDFpy/QKBawSgpO0uev/Ccfo1RL6TR3+Oj3XiFIfBamcowtmawV89U33mBUiNntDMlZ87z51i2qjQpxBLlMgWzbRl0ywRnzng+8j9W2xxI6m2qXaG+ftZHPbMWj6x0wHLrsOSrLWg09sPB2HE4vPEojN8VnP/8CsVVivztGI0uiBextb+F7Ht2Bg6nnGI5ajEYDQj9iZqaG63g8dO4st+5cg0QwMVlH0zVc30eSJYajEf3hiPnZOdqdJuORQxQllMsl9va3+Xd+4Ad59Y2rqJqKKgtkI8axR5x9+By23WRk+3h+iKqpJITUSxYkfdLAZ6JcoW87NPd3aHf2GY9tZibmcWybyUYdy9R48vJF/sk//j959qOL3L2m8ckv/QM+83svMxg0qddqjD2Pg26HueUzvPLaK+R1k1zRwDBqrKzvoEkqkibj2odV4GpVi053SBAKbM9m2Pep10ssn1pk5f4qpVKV8XhMoVjCD0KiIKJcKjMcDKnXK+iaQhyGtNstlhaXSIKIcjlHq7kLkiBTLOH3ukzWykxWS2RkieZgj1qtfHiHFyfE0mGJgnw+hxe7EKfIsky/30fVZKz5Ol98/jrlqkF9sszimdPMLs3R6rTQsypGVsONfXb39ohilSCQcIMeIlFx7JTuMOSxS2c4tTzF9HSD4WCAoU1y8fIyqqmysx0wM1HlrRv3CBOQhcr//Tuf5vTS2cMZps6IckHjoDOg3KhRyRvcub+Fb9vosmDkRWiZMo49xMrpJHGEphoI6XCA+eCgTRiERFFEMVeiN+rx5FPv4date8iyjKzq2EHKF1/4Bj/1038ZkSqMBwnvf/Y9bG90MPU8rfY+j11+iihJqZYK1AoZoljjxs1bPPP+Z/jt3/td/JHLnRs3OHfpSVzHwx3b1BoN5heXuXnjbQpF47AwlYjJajr16lkkM8KydNQkxYtCOu0eO7tD7q70mJx8iCR2yOVNbt25RyIpvPTiTbKZGrsHXfLFKkJVWViaJwgD3DBAjiQCVUXNaNRqeTLFLBcuLlMr55ieqKFhkcgGf/iVWzxy+b2krsO5R5YQcsRuu4lESrWcoz/sUqo1SOOYOAiZqDdoTEwgazoiPVyE28gYFLJFNtfXmZtpYGYlpDQhl8vjeyGGaTKxVKE7HHL91h2KpTzPPPMevviHL3PmzMPki3nKjRKd/Ra1TIlyvohu5ZCTEM2IgIAwCClnCiyenman2cRPBaoQpKJEZyiz1bJ5de3bK5r17siR6yL9az9+nqe+/zLtXpPOzj6PXHyYtXt3sYSFblno+cPJFJEbU5iept87IAnHdDo+jUoDVwq4u75KQW+QKGP+gw/9+3zmtZdJFA9luI3rqsSWiaKnjAcBwnXJVE0+/vj7+d03vk6kyGiqYGenTW26zNdfeJXJygLPPfkD5AyJnfUDItdldWuLSmOC0RAkVUGSBDlLJ7CHjFyPKM0RBAGqAqpuEMc+haxOv2dTKBRYXV2hWCzxyCMXsJ0er7x6h2L5sBBUnIQUikXiWDAcO4xGA0xdPaxxLBQ29za4+PCjeJ5DvpTFMjOIxGNsu2SyJQ5aO4xdyOhFagUTVc8i0phXv/EGzz77XTjBGM+3GdtdTi2fY2mpzu9/+kUK5UkuXpjg8198C1PVKOayfM+z7+PevXt0u20Wl2YZjWzu3L2PEAIhZHTTQk1T3GBALlslilMSAYHrk8tlqVZKDIYddpsDnrh0mVarSW84QFJkdEmh2+1SKJeI4wQhBEEQ0Gg0qOQNzp5f4vrV++w3W6iKjut6TE6W2NzYplQuEIUJQXi4rqahRGSzJmEYIkkK09MztHsdgiBgNHYxDA3Xdclms/z4z/7H/LN/9Kuoqkzo++i6RhSm5MpF1tY3mZuZBxHg2GOqpSKe7yBkmciNsSyLbm9IkAgUU6WcK9Af2MwsTPD2mzeoN8r4QUAYxiRJwv7ugKnpOkunJnjxyy/z6GNnaTWb5HMl0ijGtR3295tUalWiKGI07FIul0hlGS8IKWSyhGFIECecO7/M6soWzsghTjwsI4fjjjEtE8/ziaLo8CmMwKNSqdHr9UlEiqFJzE/NMBgM0HUTL/RwvYAYQS6bxzBVbrz1NvbQYWevxUd/8EPcuHoNHZNyPU+1PoEdOGRyBnIk0Wq12N3ZZ3l5GUVRSKWEVEooFXKQCFbv3Wc0GmF7Mc88+xS27dLvdEmSFFXR2drdoXkw4Knvfh/97gBdi3EcGzNbodk6TNEtzVU4c3aZV167ixf4jIY2OR36vSG1mUmGdkQSRpiGShDG9AddnnjiCuvrqwh0ioUaUw2T03OTlKtZXnrlLVbXdtna7SIJmTR1KRaqdAdDTNNkdWuDiUoN17Nx44SRPaZQKBI5Ht1uBwDLymLbhytenX/oNHaQIOKEnJVherZMo1Zna2sPy9Lp9kY4Y5fGZBFFSISuw82r98jk8px95CFc2+HmG68Tul2EFJAmBvlcgfrcEjfvtum7I06fnqWULVCvFfmh//p/Pj6DncvLxfQX//oVtra2aSwu8dWvvMh3X3kcQ2j4qUDKqMSujyorbO7v4wifKEqQpZCpmRlGTsRMvs5EbY5f/9Q/5df+zq/w1ksv8+mvP4+buFw69zCvv/02j5xdZhRINKZ0gg48//YrnK5NYU5WeWx5nq98/Sr97gZPP/oBKqJOw1pkbWObjt1k2HPQNfBCCCKDc+fPcv36NQxVI058Oq0uz330A3zhC19DlTOYpoltj1icn0I3BJ6b0Ov1ieMYRVGwfY/RaEQ+W8DQFPrDMTOzU7TabQaDEZl8gTgOSdOUbCbHYDDGT2MIQnKWjmEZ6IrOeDRAklX8MKXf6VKrlyhYGXyvQ6ZkcHp5gfX7+0iShDMIyFca+InNq6+9zMWzlxmHPrmCzFe+eJUPffg9zE7XGY96pInKoB8Qhi5RHHDhwgVu3b7LhQsXefONqyi6jjc+XOZKVTK02rtML8xgD0dkMll891Df5Ow829vb2EcF9zOFHA8tnaLZbNIdDAjCENIEXVbI5XJEkYeqQYr+R9PjM5kMihIw6NsgySiKApLCaDSikLOI4xhVlZFllThwKZVK2I5HEERIEqiqSn/QZXKyQb87IpfLMTi6SFVNJkyhUp2g1+miyRG6riOJFF1RDwtU6SZRFGFk83T7YzQjS7PZZH5+iZ2dTRKRkKYpSSrR7Q7JWRkylo6qymxt7VCwstRqNYaDFrIscJyAvJVlNOijGTr1ep3mwR69/hAtU2DkeVx85AL3bt08rJ9JkxoAABD4SURBVHktQkgFc9NzOO6I5n6TTMYkThOy2Ry2H2DbNo1G7fD9CgUq5RwgsX9wgKKoRMHhGItIBOVyFVnXWF1dJWtYZAyTci2HH6bkMiamlrKzv3eY7zYMbNvGdX2q1SoH+y0sy0KIEFmVcO0x3eYBpVydTC7L/ZU1Lj3xJIYKjuOws7PD/OwcX3/1FhPTVTJmlqn5Cjev3SKbLaLpOYajPmNnTCGTpbO/xfzCDI4rgRKSpBb2sIVVzCBiFdt2KJXz6JqEMwqRFRVdN+n1BkxMlxkPB/x7P/4hRt02n3/+ebw4QxAopGnMxtomFx45w8F+hyhJkUSMYmawdIOd3X3sKCYVCUkSszAzy+rqKqqqoioakiQRhjY5UyOWTPJmlvmpKiN3iOuFSEqelBhT00jSCCursLGxSWt9m/WVHqfOnuX8pYdwAxtdpJxanOGf//N/Rr4wSWtnQLaUQ83kWD41T7VWYHt7m2Ipw3/43/3m8Rns/Ed/77//xMc+dIrXN1YoVbLU6zUq5Sp6Nke+Uef1t99A0XScIKRQLzA9XcO2fYqVEpVKiZW3rmHLCb/xqd/nI99zhc+99lW2WpvUJxoIIaNqFlalQGtnh3HsoSUxaj5DpVTFEBKNcp679zcIxiFPXXiKujJJPE7Y2tzHjxyazR75/OFFvLnTRlJ01tZXkUnod7vomkEY+vQGQ+JUQ9MUZDlGFgm6qrO2vkPWUikWSpCAbQ8pVkv0ezaNRoVc1sR2QiQhYZgmcZwyGI1RVZUwjDANg+FwhCGnfPd7H2dvd5PJiUlse4xhGHR7fWJSTp2aRlEVfA90zeLG1TVCL4/jRLzv6fPcvLdNqWZRyWcJhzHzi9PkKnM4rT4ZU6VWaUACt2+tMj2zQLuzT2OyxnA0oNXqEUeC5kEL23awsnmCKCGOHeLYY3Fhhv1mlziK6fV6BH5ImgianTaKolCr1yjm8oRxclh4aTBCklQkCSrFIpVykeGwR6MxyX6zhSzpuL6PqRtEUYhhyLRbfTKZHN1ehyT0qZSKzEzVMHUd33NR5JRqtYLnR9i2i6xKRGHCcDgi8CNkScP3HRzHplapomoyiiKTopDNFun12mQzKkuLC/T6fWr1GpEXYvsuZibDYGSj6BmGow5WPsPa+gbVSoFxv0uaRni2QzGfZ2qmQbvdwrFD4lClXLIol/P0e11c10NVDBRZwg98KvUKB/t75PI5KrUJwhgMWeC7Y+r1CpVCjjjWURWd0XCMqmiUSgWyWYv+oIuqqqQCMpnD+QC6rmNZJoOBy/5+D1BRZAPd1BiPfeJUHNbSJkY3dLJZg2xWpTsc0e8PMUyNseegG0WCKGF7ex9ZyRAGIfv7TYrFEr7vkSQycSThuiHdZg/DsrAKJUrVKoN+l3ZnQBTHyIpCHEdkCxVUVUZIJgf7fTRZAyS8wGZiskSlaHH39n2efe5DrK5tUC7XGDsJSSwgSdhtDbAyFpViEVk6TH+USjm6vR7tbhfdMEiiiDSJkKSU23dWyJbqdHtj1te3adQrxAl4oc9es4+mqviuz8hzmZ6c5qDTYWyPiaMY13HIWNbhij5JQhBFNNstCvki5VIBL4gJPQ9VpCiGQX/k0uwcjguNxx6SgJ3tDfa2D5Ajn1whz+zCDPlSDtNSCMKIlfUDVrfajG0oFIq855krFKp5DEPQbB1gGmVsN+Gz33j7+OTIf+XX/t4nHlpMufzwY+xubuDGPt3xkFeu3+D6nbs8fHaJbKnKrdX7pMJDCm3KpQbDwYhBp8Pk4jRWQefsmYfJGQmt9ghn5FCu5ChVsrx2+yX2VpoUrCKlaQNtbNIdDfE6DkvLp1lv7mIZFcqqwtna44ybQ3ZbQ5rjAXrOJBhrxLgkIkOl2iAmRFVUNOnw+etms8XERIHxMKTT88mXDTJaBpFGlCsmVx5/GE3TWFtbQ1FkENHhoFusEQQOL371a9Sqk4xGIwzTZDxygcPiPuPREFPXWZxfBBL2mweUG5Pc39jhzOIUcRhTrpQJQp/9nQFpGmNkVfJVHV3WmFsscvPGTWqVWaYbRT77uVfZ2N7kvU89Rhz5/Ks/eIH/9r/4YVxngJCztFsjokigGwqeFxD4MXdur5FEGpomUSqVWVo6xcVHL/HiV65SKBkoEqze2SJMFCbqdfK5w1V/crkCYRKBEAyHA/LZLCPbJvQdZmdncb2QNAyRJMFwPEQ3NNrtHrIi0x86KKpCxjRIiRmPR2SMAlHkk7VM6rUS1VKBoWuzs3tAgkScxHS6LbLZLHGSkKYxsiQhSQKQSWJQ1ZSJiQZh6DEcDshkMvQHYzJWjjgKsEyN/mBAmMTY4zECUC2LMErY3WuRL1WZaNRZWd1gYf4MvXYXSdEpVet4QcTQdhi0bXw3QIiYeiN7WHdmIken1UGRTYbjEWbGRJDSG/TIWhZxHCHJMmGaQgxDe8xg7JCkEvm8BcSQBnieTRxF9PqHE1xc1yMlJWOYzEzPMB4NsO0xURyjKhqeO0bTQFZVUgSlcpkgCpAlE0nSUDWZKPAIExlZTRkMBqiayerqOoWihRd4hFFExrQwzQxxHKHrGqZu0uv3WFxcQFZVGlN1uv0hcRTh2UP0TAlZ0SgWi0RJhKkXkJWUfr+DaggKhkyhZLC8tMDBdg976DMzWeXlV9/k0UsX2drbww9SFhdqXHr0YcZOyGg8RFMkxsMhfhAShCmSrCJkFT+KaZQNHHtIu9diOA544427nLt4llwhD0gMhzaKaZIIDU3XIZFwo5Cd3R28OKTRqNBpdzh16jTNZhMhC8IoIopjrKxF4MYYuooXBOiKTBIJ9lotKrUJ2p0+sohoTFWJwhHL8xNcf+stDAwkLWVyZobNzV0kDBbmZ7DdPhceO4/j2Fy6/Aj90YCRI2M7LvV6nTgK6febfOmN1eMTyH/h7/6tTyyeSbl6f4dLD5/i1bfvM1GdpVIsMTtbJ41jwjTlzOI0m1ubFCt5Op0hk7NlkBSu31zh9FQJ1TdY3+pTq+dZmJmjN+6xvrXJRH6euUaDRAGnZ5OzihRSlUYuSyWSkJCoZwwmc4/wpc+9xnZrj0y+TEYIRkOffBF222PSMKEzsLF0BV1K8fwIIQlyOY2xH6KbBYolg6lqAT9MKRZNPDtiY2uXVDLQDUgThdv3N8lYBrNzFUxd57GLj9Md2ciqiqzIIMWHA3VxgJXLIkkq5XKG57+8wtKsxWQjT7vTw4scSopMIKVEQYqixJx/aI5ex0NKhqTENGqTLJ9a5PbddW7evcfT771CtV5j5A25e6fL4nSNkTNG1jL0hjadfgchqXRau9QqJVRFx/N8HntsiWKhTKlssThZQM9EjJ0x7XaXQsEik7fIZw16wzGOGzAYD4mCMYpskMYx9VqRdrtPksZkc0W2tnfIWDpmRmU0clBkFdM00TQZRdZRFYlKuUAY2JBKRElINpdDCJnBcIwkSXihy/ZuH8vM4nvuYUAzsyiqzHDQJfADZFUnRoY0pVzKkkYpUeAhCYEbhMR2DBpkDJXRcIieMUiTGEUkeK6LG0QYmsTIdtF1k26nRxRFqLLG9s4e2YKF7dh4Y5vAD4iFjGmoWNkcpq7w3HOXefvGbXr9GHvoYlkWmczhT3XN0EijBFlKcEMV2/aQhUwQ+sxNFyhbJSLhYOkKubxBpz3EymRIkoScVcL1bRzHw8hUWLm/SeBH+KHNzOwCB1sHJEIiFhKakWXQHaLIElEgEEJgWjrLy9Ps7u0zcjlcSUeWiHwJRVXQDJ3mwYg4DDENCyFJJGmEJFJAQlEsVDVlb29ArqCzcr+NmVEIQxlFV3BslzgJCXwfM2OyvX+A40QUizlEKoiklFZzgOckRFJMKse0emPm5+ZYX9+iVMpQL1fpdXZ5+pkr3L29hqbIRHHMzNwUQqj4nk+lXMGLPfKGjhOlDAYOtdo02zv7VKol3njlZVZu38KwcmTNLL3hEE2kjO0RQoZer8Nw4KDrOr1WB0jZ3m6haApCyEiyhCJJSELBT2IkRaZWLjIa2vT9CKFKdNsdDF0j8B12tnfRZIkb126QDFJQVCZn5yiWyqytrGGqGj3XoZDPs7a6z/TsFACuHxLHHrqmkiQpuwcdTCvLF165dXwGO4UQI+DOg/bjz4kq8O0XEn73852k50TLu5MTLX8882ma1v6kk5Q/xzf8s3Dn20noHweEEK99p2iB7yw9J1renZxo+bPzb7NC0AknnHDCCe9CTgL5CSeccMIx590SyP/EZP4x4jtJC3xn6TnR8u7kRMufkXfFYOcJJ5xwwgl/et4td+QnnHDCCSf8KXnggVwI8REhxB0hxH0hxN940P78SQgh/jchRPNokelv2spCiC8IIe4dvZaO7EII8T8eabsmhLj84Dz//yKEmBVCvCCEuCmEuCGE+Lkj+7HTI4QwhBCvCCGuHmn520f2RSHEy0c+/5YQQjuy60ft+0fHFx6k//86hBCyEOJNIcSnj9rHUosQYl0IcV0I8ZYQ4rUj27HrYwBCiKIQ4reFELeFELeEEO97N2h5oIFcCCEDvwJ8FDgH/IQQ4tyD9Onb4NeBj3yL7W8Az6dpehp4/qgNh7pOH20/C/zqX5CP3y4R8J+naXoOeC/wV48+/+OoxweeTdP0UeAx4CNCiPcCvwD8cpqmp4Ae8DNH5/8M0Duy//LRee82fg649Y72cdbygTRNH3vHo3nHsY8B/EPgs2mangUe5fD/8+C1pGn6wDbgfcDn3tH+eeDnH6RP36bfC8Db72jfASaP9ic5fC4e4NeAn/jXnfdu3IB/BXzwuOsBMsAbwHs4nJyhfGt/Az4HvO9oXzk6Tzxo39+hYYbDoPAs8GlAHGMt60D1W2zHro8BBWDtWz/bd4OWB51amQa23tHePrIdNxppmu4d7e8DjaP9Y6Pv6Of4JeBljqmeo1TEW0AT+AKwAvTTNI2OTnmnv3+k5ej4AKj8xXr8b+QfAP8VkBy1KxxfLSnweSHE60KInz2yHcc+tgi0gP/9KOX1vwohLN4FWh50IP+OIz386j1WjwIJIbLA7wD/WZqmw3ceO0560jSN0zR9jMO72SeBsw/YpT8VQoiPAc00TV9/0L78OfF0mqaXOUw1/FUhxDPvPHiM+pgCXAZ+NU3TS4DN/5tGAR6clgcdyHeA2Xe0Z45sx40DIcQkwNFr88j+rtcnhFA5DOKfTNP0Xx6Zj60egDRN+8ALHKYfikKIb5aieKe/f6Tl6HgB6PwFu/rH8RTwg0KIdeA3OUyv/EOOpxbSNN05em0Cv8vhl+xx7GPbwHaapi8ftX+bw8D+wLU86ED+KnD6aDReAz4OfOoB+/Sn4VPATx/t/zSHueZv2n/qaPT6vcDgHT/BHjhCCAH8E+BWmqa/9I5Dx06PEKImhCge7Zsc5vpvcRjQf/TotG/V8k2NPwp86ehu6oGTpunPp2k6k6bpAofXxJfSNP3LHEMtQghLCJH75j7wIeBtjmEfS9N0H9gSQjx0ZPpe4CbvBi3vggGE7wPucpjP/G8etD/fhr+/AewBIYff0D/DYT7yeeAe8EWgfHSu4PCpnBXgOvD4g/b/W7Q8zeHPwGvAW0fb9x1HPcBF4M0jLW8Df/PIvgS8AtwH/gWgH9mNo/b9o+NLD1rDH6Pr/cCnj6uWI5+vHm03vnmNH8c+duTfY8BrR/3s94DSu0HLyczOE0444YRjzoNOrZxwwgknnPBn5CSQn3DCCSccc04C+QknnHDCMeckkJ9wwgknHHNOAvkJJ5xwwjHnJJCfcMIJJxxzTgL5CSeccMIx5ySQn3DCCSccc/4fSKQmMVGbxOsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcaee67ed30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "show_image(idx=1, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pre-Trained Image Model (VGG16)\n",
+    "\n",
+    "The following creates an instance of the VGG16 model using the Keras API. This automatically downloads the required files if you don't have them already.\n",
+    "\n",
+    "The VGG16 model was pre-trained on the ImageNet data-set for classifying images. The VGG16 model contains a convolutional part and a fully-connected (or dense) part which is used for the image classification.\n",
+    "\n",
+    "If `include_top=True` then the whole VGG16 model is downloaded which is about 528 MB. If `include_top=False` then only the convolutional part of the VGG16 model is downloaded which is just 57 MB.\n",
+    "\n",
+    "We will use some of the fully-connected layers in this pre-trained model, so we have to download the full model, but if you have a slow internet connection, then you can try and modify the code below to use the smaller pre-trained model without the classification layers.\n",
+    "\n",
+    "Tutorials #08 and #10 explain more details about Transfer Learning."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image_model = VGG16(include_top=True, weights='imagenet')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Print a list of all the layers in the VGG16 model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "input_1 (InputLayer)         (None, 224, 224, 3)       0         \n",
+      "_________________________________________________________________\n",
+      "block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      \n",
+      "_________________________________________________________________\n",
+      "block1_conv2 (Conv2D)        (None, 224, 224, 64)      36928     \n",
+      "_________________________________________________________________\n",
+      "block1_pool (MaxPooling2D)   (None, 112, 112, 64)      0         \n",
+      "_________________________________________________________________\n",
+      "block2_conv1 (Conv2D)        (None, 112, 112, 128)     73856     \n",
+      "_________________________________________________________________\n",
+      "block2_conv2 (Conv2D)        (None, 112, 112, 128)     147584    \n",
+      "_________________________________________________________________\n",
+      "block2_pool (MaxPooling2D)   (None, 56, 56, 128)       0         \n",
+      "_________________________________________________________________\n",
+      "block3_conv1 (Conv2D)        (None, 56, 56, 256)       295168    \n",
+      "_________________________________________________________________\n",
+      "block3_conv2 (Conv2D)        (None, 56, 56, 256)       590080    \n",
+      "_________________________________________________________________\n",
+      "block3_conv3 (Conv2D)        (None, 56, 56, 256)       590080    \n",
+      "_________________________________________________________________\n",
+      "block3_pool (MaxPooling2D)   (None, 28, 28, 256)       0         \n",
+      "_________________________________________________________________\n",
+      "block4_conv1 (Conv2D)        (None, 28, 28, 512)       1180160   \n",
+      "_________________________________________________________________\n",
+      "block4_conv2 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block4_conv3 (Conv2D)        (None, 28, 28, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block4_pool (MaxPooling2D)   (None, 14, 14, 512)       0         \n",
+      "_________________________________________________________________\n",
+      "block5_conv1 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_conv2 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_conv3 (Conv2D)        (None, 14, 14, 512)       2359808   \n",
+      "_________________________________________________________________\n",
+      "block5_pool (MaxPooling2D)   (None, 7, 7, 512)         0         \n",
+      "_________________________________________________________________\n",
+      "flatten (Flatten)            (None, 25088)             0         \n",
+      "_________________________________________________________________\n",
+      "fc1 (Dense)                  (None, 4096)              102764544 \n",
+      "_________________________________________________________________\n",
+      "fc2 (Dense)                  (None, 4096)              16781312  \n",
+      "_________________________________________________________________\n",
+      "predictions (Dense)          (None, 1000)              4097000   \n",
+      "=================================================================\n",
+      "Total params: 138,357,544\n",
+      "Trainable params: 138,357,544\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "image_model.summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use the output of the layer prior to the final classification-layer which is named `fc2`. This is a fully-connected (or dense) layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transfer_layer = image_model.get_layer('fc2')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We call it the \"transfer-layer\" because we will transfer its output to another model that creates the image captions.\n",
+    "\n",
+    "To do this, first we need to create a new model which has the same input as the original VGG16 model but outputs the transfer-values from the `fc2` layer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image_model_transfer = Model(inputs=image_model.input,\n",
+    "                             outputs=transfer_layer.output)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The model expects input images to be of this size:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(224, 224)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "img_size = K.int_shape(image_model.input)[1:3]\n",
+    "img_size"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For each input image, the new model will output a vector of transfer-values with this length:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4096"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "transfer_values_size = K.int_shape(transfer_layer.output)[1]\n",
+    "transfer_values_size"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Process All Images\n",
+    "\n",
+    "We now make functions for processing all images in the data-set using the pre-trained image-model and saving the transfer-values in a cache-file so they can be reloaded quickly.\n",
+    "\n",
+    "We effectively create a new data-set of the transfer-values. This is because it takes a long time to process an image in the VGG16 model. We will not be changing all the parameters of the VGG16 model, so every time it processes an image, it gives the exact same result. We need the transfer-values to train the image-captioning model for many epochs, so we save a lot of time by calculating the transfer-values once and saving them in a cache-file.\n",
+    "\n",
+    "This is a helper-function for printing the progress."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_progress(count, max_count):\n",
+    "    # Percentage completion.\n",
+    "    pct_complete = count / max_count\n",
+    "\n",
+    "    # Status-message. Note the \\r which means the line should\n",
+    "    # overwrite itself.\n",
+    "    msg = \"\\r- Progress: {0:.1%}\".format(pct_complete)\n",
+    "\n",
+    "    # Print it.\n",
+    "    sys.stdout.write(msg)\n",
+    "    sys.stdout.flush()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the function for processing the given files using the VGG16-model and returning their transfer-values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def process_images(data_dir, filenames, batch_size=32):\n",
+    "    \"\"\"\n",
+    "    Process all the given files in the given data_dir using the\n",
+    "    pre-trained image-model and return their transfer-values.\n",
+    "    \n",
+    "    Note that we process the images in batches to save\n",
+    "    memory and improve efficiency on the GPU.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Number of images to process.\n",
+    "    num_images = len(filenames)\n",
+    "\n",
+    "    # Pre-allocate input-batch-array for images.\n",
+    "    shape = (batch_size,) + img_size + (3,)\n",
+    "    image_batch = np.zeros(shape=shape, dtype=np.float16)\n",
+    "\n",
+    "    # Pre-allocate output-array for transfer-values.\n",
+    "    # Note that we use 16-bit floating-points to save memory.\n",
+    "    shape = (num_images, transfer_values_size)\n",
+    "    transfer_values = np.zeros(shape=shape, dtype=np.float16)\n",
+    "\n",
+    "    # Initialize index into the filenames.\n",
+    "    start_index = 0\n",
+    "\n",
+    "    # Process batches of image-files.\n",
+    "    while start_index < num_images:\n",
+    "        # Print the percentage-progress.\n",
+    "        print_progress(count=start_index, max_count=num_images)\n",
+    "\n",
+    "        # End-index for this batch.\n",
+    "        end_index = start_index + batch_size\n",
+    "\n",
+    "        # Ensure end-index is within bounds.\n",
+    "        if end_index > num_images:\n",
+    "            end_index = num_images\n",
+    "\n",
+    "        # The last batch may have a different batch-size.\n",
+    "        current_batch_size = end_index - start_index\n",
+    "\n",
+    "        # Load all the images in the batch.\n",
+    "        for i, filename in enumerate(filenames[start_index:end_index]):\n",
+    "            # Path for the image-file.\n",
+    "            path = os.path.join(data_dir, filename)\n",
+    "\n",
+    "            # Load and resize the image.\n",
+    "            # This returns the image as a numpy-array.\n",
+    "            img = load_image(path, size=img_size)\n",
+    "\n",
+    "            # Save the image for later use.\n",
+    "            image_batch[i] = img\n",
+    "\n",
+    "        # Use the pre-trained image-model to process the image.\n",
+    "        # Note that the last batch may have a different size,\n",
+    "        # so we only use the relevant images.\n",
+    "        transfer_values_batch = \\\n",
+    "            image_model_transfer.predict(image_batch[0:current_batch_size])\n",
+    "\n",
+    "        # Save the transfer-values in the pre-allocated array.\n",
+    "        transfer_values[start_index:end_index] = \\\n",
+    "            transfer_values_batch[0:current_batch_size]\n",
+    "\n",
+    "        # Increase the index for the next loop-iteration.\n",
+    "        start_index = end_index\n",
+    "\n",
+    "    # Print newline.\n",
+    "    print()\n",
+    "\n",
+    "    return transfer_values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Helper-function for processing all images in the training-set. This saves the transfer-values in a cache-file for fast reloading."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def process_images_train():\n",
+    "    print(\"Processing {0} images in training-set ...\".format(len(filenames_train)))\n",
+    "\n",
+    "    # Path for the cache-file.\n",
+    "    cache_path = os.path.join(coco.data_dir,\n",
+    "                              \"transfer_values_train.pkl\")\n",
+    "\n",
+    "    # If the cache-file already exists then reload it,\n",
+    "    # otherwise process all images and save their transfer-values\n",
+    "    # to the cache-file so it can be reloaded quickly.\n",
+    "    transfer_values = cache(cache_path=cache_path,\n",
+    "                            fn=process_images,\n",
+    "                            data_dir=coco.train_dir,\n",
+    "                            filenames=filenames_train)\n",
+    "\n",
+    "    return transfer_values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Helper-function for processing all images in the validation-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def process_images_val():\n",
+    "    print(\"Processing {0} images in validation-set ...\".format(len(filenames_val)))\n",
+    "\n",
+    "    # Path for the cache-file.\n",
+    "    cache_path = os.path.join(coco.data_dir, \"transfer_values_val.pkl\")\n",
+    "\n",
+    "    # If the cache-file already exists then reload it,\n",
+    "    # otherwise process all images and save their transfer-values\n",
+    "    # to the cache-file so it can be reloaded quickly.\n",
+    "    transfer_values = cache(cache_path=cache_path,\n",
+    "                            fn=process_images,\n",
+    "                            data_dir=coco.val_dir,\n",
+    "                            filenames=filenames_val)\n",
+    "\n",
+    "    return transfer_values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Process all images in the training-set and save the transfer-values to a cache-file. This took about 30 minutes to process on a GTX 1070 GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing 118287 images in training-set ...\n",
+      "- Data loaded from cache-file: data/coco/transfer_values_train.pkl\n",
+      "dtype: float16\n",
+      "shape: (118287, 4096)\n",
+      "CPU times: user 116 ms, sys: 256 ms, total: 372 ms\n",
+      "Wall time: 365 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "transfer_values_train = process_images_train()\n",
+    "print(\"dtype:\", transfer_values_train.dtype)\n",
+    "print(\"shape:\", transfer_values_train.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Process all images in the validation-set and save the transfer-values to a cache-file. This took about 90 seconds to process on a GTX 1070 GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing 5000 images in validation-set ...\n",
+      "- Data loaded from cache-file: data/coco/transfer_values_val.pkl\n",
+      "dtype: float16\n",
+      "shape: (5000, 4096)\n",
+      "CPU times: user 8 ms, sys: 8 ms, total: 16 ms\n",
+      "Wall time: 16.7 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "transfer_values_val = process_images_val()\n",
+    "print(\"dtype:\", transfer_values_val.dtype)\n",
+    "print(\"shape:\", transfer_values_val.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tokenizer\n",
+    "\n",
+    "Neural Networks cannot work directly on text-data. We use a two-step process to convert text into numbers that can be used in a neural network. The first step is to convert text-words into so-called integer-tokens. The second step is to convert integer-tokens into vectors of floating-point numbers using a so-called embedding-layer. See Tutorial #20 for a more detailed explanation.\n",
+    "\n",
+    "Before we can start processing the text, we first need to mark the beginning and end of each text-sequence with unique words that most likely aren't present in the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mark_start = 'ssss '\n",
+    "mark_end = ' eeee'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This helper-function wraps all text-strings in the above markers. Note that the captions are a list of list, so we need a nested for-loop to process it. This can be done using so-called list-comprehension in Python."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def mark_captions(captions_listlist):\n",
+    "    captions_marked = [[mark_start + caption + mark_end\n",
+    "                        for caption in captions_list]\n",
+    "                        for captions_list in captions_listlist]\n",
+    "    \n",
+    "    return captions_marked"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now process all the captions in the training-set and show an example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['ssss Closeup of bins of food that include broccoli and bread. eeee',\n",
+       " 'ssss A meal is presented in brightly colored plastic trays. eeee',\n",
+       " 'ssss there are containers filled with different kinds of foods eeee',\n",
+       " 'ssss Colorful dishes holding meat, vegetables, fruit, and bread. eeee',\n",
+       " 'ssss A bunch of trays that have different food. eeee']"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "captions_train_marked = mark_captions(captions_train)\n",
+    "captions_train_marked[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is how the captions look without the start- and end-markers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Closeup of bins of food that include broccoli and bread.',\n",
+       " 'A meal is presented in brightly colored plastic trays.',\n",
+       " 'there are containers filled with different kinds of foods',\n",
+       " 'Colorful dishes holding meat, vegetables, fruit, and bread.',\n",
+       " 'A bunch of trays that have different food.']"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "captions_train[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This helper-function converts a list-of-list to a flattened list of captions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def flatten(captions_listlist):\n",
+    "    captions_list = [caption\n",
+    "                     for captions_list in captions_listlist\n",
+    "                     for caption in captions_list]\n",
+    "    \n",
+    "    return captions_list"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now use the function to convert all the marked captions from the training set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "captions_train_flat = flatten(captions_train_marked)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set the maximum number of words in our vocabulary. This means that we will only use e.g. the 10000 most frequent words in the captions from the training-data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_words = 10000"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need a few more functions than provided by Keras' Tokenizer-class so we wrap it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class TokenizerWrap(Tokenizer):\n",
+    "    \"\"\"Wrap the Tokenizer-class from Keras with more functionality.\"\"\"\n",
+    "    \n",
+    "    def __init__(self, texts, num_words=None):\n",
+    "        \"\"\"\n",
+    "        :param texts: List of strings with the data-set.\n",
+    "        :param num_words: Max number of words to use.\n",
+    "        \"\"\"\n",
+    "\n",
+    "        Tokenizer.__init__(self, num_words=num_words)\n",
+    "\n",
+    "        # Create the vocabulary from the texts.\n",
+    "        self.fit_on_texts(texts)\n",
+    "\n",
+    "        # Create inverse lookup from integer-tokens to words.\n",
+    "        self.index_to_word = dict(zip(self.word_index.values(),\n",
+    "                                      self.word_index.keys()))\n",
+    "\n",
+    "    def token_to_word(self, token):\n",
+    "        \"\"\"Lookup a single word from an integer-token.\"\"\"\n",
+    "\n",
+    "        word = \" \" if token == 0 else self.index_to_word[token]\n",
+    "        return word \n",
+    "\n",
+    "    def tokens_to_string(self, tokens):\n",
+    "        \"\"\"Convert a list of integer-tokens to a string.\"\"\"\n",
+    "\n",
+    "        # Create a list of the individual words.\n",
+    "        words = [self.index_to_word[token]\n",
+    "                 for token in tokens\n",
+    "                 if token != 0]\n",
+    "        \n",
+    "        # Concatenate the words to a single string\n",
+    "        # with space between all the words.\n",
+    "        text = \" \".join(words)\n",
+    "\n",
+    "        return text\n",
+    "    \n",
+    "    def captions_to_tokens(self, captions_listlist):\n",
+    "        \"\"\"\n",
+    "        Convert a list-of-list with text-captions to\n",
+    "        a list-of-list of integer-tokens.\n",
+    "        \"\"\"\n",
+    "        \n",
+    "        # Note that text_to_sequences() takes a list of texts.\n",
+    "        tokens = [self.texts_to_sequences(captions_list)\n",
+    "                  for captions_list in captions_listlist]\n",
+    "        \n",
+    "        return tokens"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now create a tokenizer using all the captions in the training-data. Note that we use the flattened list of captions to create the tokenizer because it cannot take a list-of-lists."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 8.75 s, sys: 32 ms, total: 8.78 s\n",
+      "Wall time: 8.7 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "tokenizer = TokenizerWrap(texts=captions_train_flat,\n",
+    "                          num_words=num_words)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the integer-token for the start-marker (the word \"ssss\"). We will need this further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_start = tokenizer.word_index[mark_start.strip()]\n",
+    "token_start"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get the integer-token for the end-marker (the word \"eeee\")."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "token_end = tokenizer.word_index[mark_end.strip()]\n",
+    "token_end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Convert all the captions from the training-set to sequences of integer-tokens. We get a list-of-list as a result."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 6.72 s, sys: 68 ms, total: 6.78 s\n",
+      "Wall time: 6.72 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "tokens_train = tokenizer.captions_to_tokens(captions_train_marked)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example of the integer-tokens for the captions of the first image in the training-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[[2, 841, 5, 2864, 5, 61, 26, 1984, 238, 9, 433, 3],\n",
+       " [2, 1, 429, 10, 3310, 7, 1025, 390, 501, 1110, 3],\n",
+       " [2, 63, 19, 993, 143, 8, 190, 958, 5, 743, 3],\n",
+       " [2, 299, 725, 25, 343, 208, 264, 9, 433, 3],\n",
+       " [2, 1, 170, 5, 1110, 26, 446, 190, 61, 3]]"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokens_train[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the corresponding text-captions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['ssss Closeup of bins of food that include broccoli and bread. eeee',\n",
+       " 'ssss A meal is presented in brightly colored plastic trays. eeee',\n",
+       " 'ssss there are containers filled with different kinds of foods eeee',\n",
+       " 'ssss Colorful dishes holding meat, vegetables, fruit, and bread. eeee',\n",
+       " 'ssss A bunch of trays that have different food. eeee']"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "captions_train_marked[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Generator\n",
+    "\n",
+    "Each image in the training-set has at least 5 captions describing the contents of the image. The neural network will be trained with batches of transfer-values for the images and sequences of integer-tokens for the captions. If we were to have matching numpy arrays for the training-set, we would either have to only use a single caption for each image and ignore the rest of this valuable data, or we would have to repeat the image transfer-values for each of the captions, which would waste a lot of memory.\n",
+    "\n",
+    "A better solution is to create a custom data-generator for Keras that will create a batch of data with randomly selected transfer-values and token-sequences.\n",
+    "\n",
+    "This helper-function returns a list of random token-sequences for the images with the given indices in the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_random_caption_tokens(idx):\n",
+    "    \"\"\"\n",
+    "    Given a list of indices for images in the training-set,\n",
+    "    select a token-sequence for a random caption,\n",
+    "    and return a list of all these token-sequences.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Initialize an empty list for the results.\n",
+    "    result = []\n",
+    "\n",
+    "    # For each of the indices.\n",
+    "    for i in idx:\n",
+    "        # The index i points to an image in the training-set.\n",
+    "        # Each image in the training-set has at least 5 captions\n",
+    "        # which have been converted to tokens in tokens_train.\n",
+    "        # We want to select one of these token-sequences at random.\n",
+    "\n",
+    "        # Get a random index for a token-sequence.\n",
+    "        j = np.random.choice(len(tokens_train[i]))\n",
+    "\n",
+    "        # Get the j'th token-sequence for image i.\n",
+    "        tokens = tokens_train[i][j]\n",
+    "\n",
+    "        # Add this token-sequence to the list of results.\n",
+    "        result.append(tokens)\n",
+    "\n",
+    "    return result"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This generator function creates random batches of training-data for use in training the neural network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def batch_generator(batch_size):\n",
+    "    \"\"\"\n",
+    "    Generator function for creating random batches of training-data.\n",
+    "    \n",
+    "    Note that it selects the data completely randomly for each\n",
+    "    batch, corresponding to sampling of the training-set with\n",
+    "    replacement. This means it is possible to sample the same\n",
+    "    data multiple times within a single epoch - and it is also\n",
+    "    possible that some data is not sampled at all within an epoch.\n",
+    "    However, all the data should be unique within a single batch.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Infinite loop.\n",
+    "    while True:\n",
+    "        # Get a list of random indices for images in the training-set.\n",
+    "        idx = np.random.randint(num_images_train,\n",
+    "                                size=batch_size)\n",
+    "        \n",
+    "        # Get the pre-computed transfer-values for those images.\n",
+    "        # These are the outputs of the pre-trained image-model.\n",
+    "        transfer_values = transfer_values_train[idx]\n",
+    "\n",
+    "        # For each of the randomly chosen images there are\n",
+    "        # at least 5 captions describing the contents of the image.\n",
+    "        # Select one of those captions at random and get the\n",
+    "        # associated sequence of integer-tokens.\n",
+    "        tokens = get_random_caption_tokens(idx)\n",
+    "\n",
+    "        # Count the number of tokens in all these token-sequences.\n",
+    "        num_tokens = [len(t) for t in tokens]\n",
+    "        \n",
+    "        # Max number of tokens.\n",
+    "        max_tokens = np.max(num_tokens)\n",
+    "        \n",
+    "        # Pad all the other token-sequences with zeros\n",
+    "        # so they all have the same length and can be\n",
+    "        # input to the neural network as a numpy array.\n",
+    "        tokens_padded = pad_sequences(tokens,\n",
+    "                                      maxlen=max_tokens,\n",
+    "                                      padding='post',\n",
+    "                                      truncating='post')\n",
+    "        \n",
+    "        # Further prepare the token-sequences.\n",
+    "        # The decoder-part of the neural network\n",
+    "        # will try to map the token-sequences to\n",
+    "        # themselves shifted one time-step.\n",
+    "        decoder_input_data = tokens_padded[:, 0:-1]\n",
+    "        decoder_output_data = tokens_padded[:, 1:]\n",
+    "\n",
+    "        # Dict for the input-data. Because we have\n",
+    "        # several inputs, we use a named dict to\n",
+    "        # ensure that the data is assigned correctly.\n",
+    "        x_data = \\\n",
+    "        {\n",
+    "            'decoder_input': decoder_input_data,\n",
+    "            'transfer_values_input': transfer_values\n",
+    "        }\n",
+    "\n",
+    "        # Dict for the output-data.\n",
+    "        y_data = \\\n",
+    "        {\n",
+    "            'decoder_output': decoder_output_data\n",
+    "        }\n",
+    "        \n",
+    "        yield (x_data, y_data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set the batch-size used during training. This is set very high so the GPU can be used maximally - but this also requires a lot of RAM on the GPU. You may have to lower this number if the training runs out of memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "batch_size = 1024"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create an instance of the data-generator."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generator = batch_generator(batch_size=batch_size)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Test the data-generator by creating a batch of data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "batch = next(generator)\n",
+    "batch_x = batch[0]\n",
+    "batch_y = batch[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example of the transfer-values for the first image in the batch."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.    , 0.    , 1.451 , ..., 0.    , 0.    , 0.6562], dtype=float16)"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "batch_x['transfer_values_input'][0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example of the token-sequence for the first image in the batch. This is the input to the decoder-part of the neural network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([  2,   1, 126,  34,   5,   1,  29,  25,   1, 247, 116,   3,   0,\n",
+       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
+       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0], dtype=int32)"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "batch_x['decoder_input'][0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the token-sequence for the output of the decoder. Note how it is the same as the sequence above, except it is shifted one time-step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([  1, 126,  34,   5,   1,  29,  25,   1, 247, 116,   3,   0,   0,\n",
+       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
+       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0], dtype=int32)"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "batch_y['decoder_output'][0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Steps Per Epoch\n",
+    "\n",
+    "One epoch is a complete processing of the training-set. We would like to process each image and caption pair only once per epoch. However, because each batch is chosen completely at random in the above batch-generator, it is possible that an image occurs in multiple batches within a single epoch, and it is possible that some images may not occur in any batch at all within a single epoch.\n",
+    "\n",
+    "Nevertheless, we still use the concept of an 'epoch' to measure approximately how many iterations of the training-data we have processed. But the data-generator will generate batches for eternity, so we need to manually calculate the approximate number of batches required per epoch.\n",
+    "\n",
+    "This is the number of captions for each image in the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_captions_train = [len(captions) for captions in captions_train]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the total number of captions in the training-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "total_num_captions_train = np.sum(num_captions_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the approximate number of batches required per epoch, if we want to process each caption and image pair once per epoch."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "577"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "steps_per_epoch = int(total_num_captions_train / batch_size)\n",
+    "steps_per_epoch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create the Recurrent Neural Network\n",
+    "\n",
+    "We will now create the Recurrent Neural Network (RNN) that will be trained to map the vectors with transfer-values from the image-recognition model into sequences of integer-tokens that can be converted into text. We call this neural network for the 'decoder' as it is almost identical to the decoder when doing Machine Translation in Tutorial #21.\n",
+    "\n",
+    "Note that we are using the functional model from Keras to build this neural network, because it allows more flexibility in how the neural network can be connected, in case you want to experiment and connect the image-model directly to the decoder (see the exercises). This means we have split the network construction into two parts: (1) Creation of all the layers that are not yet connected, and (2) a function that connects all these layers.\n",
+    "\n",
+    "The decoder consists of 3 GRU layers whose internal state-sizes are:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "state_size = 512"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The embedding-layer converts integer-tokens into vectors of this length:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embedding_size = 128"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This inputs transfer-values to the decoder:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transfer_values_input = Input(shape=(transfer_values_size,),\n",
+    "                              name='transfer_values_input')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We want to use the transfer-values to initialize the internal states of the GRU units. This informs the GRU units of the contents of the images. The transfer-values are vectors of length 4096 but the size of the internal states of the GRU units are only 512, so we use a fully-connected layer to map the vectors from 4096 to 512 elements.\n",
+    "\n",
+    "Note that we use a `tanh` activation function to limit the output of the mapping between -1 and 1, otherwise this does not seem to work."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_transfer_map = Dense(state_size,\n",
+    "                             activation='tanh',\n",
+    "                             name='decoder_transfer_map')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the input for token-sequences to the decoder. Using `None` in the shape means that the token-sequences can have arbitrary lengths."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_input = Input(shape=(None, ), name='decoder_input')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the embedding-layer which converts sequences of integer-tokens to sequences of vectors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_embedding = Embedding(input_dim=num_words,\n",
+    "                              output_dim=embedding_size,\n",
+    "                              name='decoder_embedding')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This creates the 3 GRU layers of the decoder. Note that they all return sequences because we ultimately want to output a sequence of integer-tokens that can be converted into a text-sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_gru1 = GRU(state_size, name='decoder_gru1',\n",
+    "                   return_sequences=True)\n",
+    "decoder_gru2 = GRU(state_size, name='decoder_gru2',\n",
+    "                   return_sequences=True)\n",
+    "decoder_gru3 = GRU(state_size, name='decoder_gru3',\n",
+    "                   return_sequences=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The GRU layers output a tensor with shape `[batch_size, sequence_length, state_size]`, where each \"word\" is encoded as a vector of length `state_size`. We need to convert this into sequences of integer-tokens that can be interpreted as words from our vocabulary.\n",
+    "\n",
+    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token.\n",
+    "\n",
+    "Note that the activation-function is set to `linear` instead of `softmax` as we would normally use for one-hot encoded outputs, because there is apparently a bug in Keras so we need to make our own loss-function, as described in detail further below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_dense = Dense(num_words,\n",
+    "                      activation='linear',\n",
+    "                      name='decoder_output')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Connect and Create the Training Model\n",
+    "\n",
+    "The decoder is built using the functional API of Keras, which allows more flexibility in connecting the layers e.g. to have multiple inputs. This is useful e.g. if you want to connect the image-model directly with the decoder instead of using pre-calculated transfer-values.\n",
+    "\n",
+    "This function connects all the layers of the decoder to some input of transfer-values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def connect_decoder(transfer_values):\n",
+    "    # Map the transfer-values so the dimensionality matches\n",
+    "    # the internal state of the GRU layers. This means\n",
+    "    # we can use the mapped transfer-values as the initial state\n",
+    "    # of the GRU layers.\n",
+    "    initial_state = decoder_transfer_map(transfer_values)\n",
+    "\n",
+    "    # Start the decoder-network with its input-layer.\n",
+    "    net = decoder_input\n",
+    "    \n",
+    "    # Connect the embedding-layer.\n",
+    "    net = decoder_embedding(net)\n",
+    "    \n",
+    "    # Connect all the GRU layers.\n",
+    "    net = decoder_gru1(net, initial_state=initial_state)\n",
+    "    net = decoder_gru2(net, initial_state=initial_state)\n",
+    "    net = decoder_gru3(net, initial_state=initial_state)\n",
+    "\n",
+    "    # Connect the final dense layer that converts to\n",
+    "    # one-hot encoded arrays.\n",
+    "    decoder_output = decoder_dense(net)\n",
+    "    \n",
+    "    return decoder_output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Connect and create the model used for training. This takes as input transfer-values and sequences of integer-tokens and outputs sequences of one-hot encoded arrays that can be converted into integer-tokens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_output = connect_decoder(transfer_values=transfer_values_input)\n",
+    "\n",
+    "decoder_model = Model(inputs=[transfer_values_input, decoder_input],\n",
+    "                      outputs=[decoder_output])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Loss Function\n",
+    "\n",
+    "The output of the decoder is a sequence of one-hot encoded arrays. In order to train the decoder we need to supply the one-hot encoded arrays that we desire to see on the decoder's output, and then use a loss-function like cross-entropy to train the decoder to produce this desired output.\n",
+    "\n",
+    "However, our data-set contains integer-tokens instead of one-hot encoded arrays. Each one-hot encoded array has 10000 elements so it would be extremely wasteful to convert the entire data-set to one-hot encoded arrays. We could do this conversion from integers to one-hot arrays in the `batch_generator()` above.\n",
+    "\n",
+    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays. Unfortunately, there seems to be a bug in Keras when using this with Recurrent Neural Networks, so the following does not work:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# decoder_model.compile(optimizer=optimizer,\n",
+    "#                       loss='sparse_categorical_crossentropy')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The decoder outputs a 3-rank tensor with shape `[batch_size, sequence_length, num_words]` which contains batches of sequences of one-hot encoded arrays of length `num_words`. We will compare this to a 2-rank tensor with shape `[batch_size, sequence_length]` containing sequences of integer-tokens.\n",
+    "\n",
+    "This comparison is done with a sparse-cross-entropy function directly from TensorFlow. There are several things to note here.\n",
+    "\n",
+    "Firstly, the loss-function calculates the softmax internally to improve numerical accuracy - this is why we used a linear activation function in the last dense-layer of the decoder-network above.\n",
+    "\n",
+    "Secondly, the loss-function from TensorFlow will output a 2-rank tensor of shape `[batch_size, sequence_length]` given these inputs. But this must ultimately be reduced to a single scalar-value whose gradient can be derived by TensorFlow so it can be optimized using gradient descent. Keras supports some weighting of loss-values across the batch but the semantics are unclear so to be sure that we calculate the loss-function across the entire batch and across the entire sequences, we manually calculate the loss average."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sparse_cross_entropy(y_true, y_pred):\n",
+    "    \"\"\"\n",
+    "    Calculate the cross-entropy loss between y_true and y_pred.\n",
+    "    \n",
+    "    y_true is a 2-rank tensor with the desired output.\n",
+    "    The shape is [batch_size, sequence_length] and it\n",
+    "    contains sequences of integer-tokens.\n",
+    "\n",
+    "    y_pred is the decoder's output which is a 3-rank tensor\n",
+    "    with shape [batch_size, sequence_length, num_words]\n",
+    "    so that for each sequence in the batch there is a one-hot\n",
+    "    encoded array of length num_words.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Calculate the loss. This outputs a\n",
+    "    # 2-rank tensor of shape [batch_size, sequence_length]\n",
+    "    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y_true,\n",
+    "                                                          logits=y_pred)\n",
+    "\n",
+    "    # Keras may reduce this across the first axis (the batch)\n",
+    "    # but the semantics are unclear, so to be sure we use\n",
+    "    # the loss across the entire 2-rank tensor, we reduce it\n",
+    "    # to a single scalar with the mean function.\n",
+    "    loss_mean = tf.reduce_mean(loss)\n",
+    "\n",
+    "    return loss_mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Compile the Training Model\n",
+    "\n",
+    "We have used the Adam optimizer in many of the previous tutorials, but it seems to diverge in some of these experiments with Recurrent Neural Networks. RMSprop seems to work much better for these."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "optimizer = RMSprop(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There seems to be another bug in Keras so it cannot automatically deduce the correct shape of the decoder's output data. We therefore need to manually create a placeholder variable for the decoder's output. The shape is set to `(None, None)` which means the batch can have an arbitrary number of sequences, which can have an arbitrary number of integer-tokens."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "decoder_target = tf.placeholder(dtype='int32', shape=(None, None))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now compile the model using our custom loss-function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "decoder_model.compile(optimizer=optimizer,\n",
+    "                      loss=sparse_cross_entropy,\n",
+    "                      target_tensors=[decoder_target])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Callback Functions\n",
+    "\n",
+    "During training we want to save checkpoints and log the progress to TensorBoard so we create the appropriate callbacks for Keras.\n",
+    "\n",
+    "This is the callback for writing checkpoints during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path_checkpoint = '22_checkpoint.keras'\n",
+    "callback_checkpoint = ModelCheckpoint(filepath=path_checkpoint,\n",
+    "                                      verbose=1,\n",
+    "                                      save_weights_only=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the callback for writing the TensorBoard log during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callback_tensorboard = TensorBoard(log_dir='./22_logs/',\n",
+    "                                   histogram_freq=0,\n",
+    "                                   write_graph=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callbacks = [callback_checkpoint, callback_tensorboard]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load Checkpoint\n",
+    "\n",
+    "You can reload the last saved checkpoint so you don't have to train the model every time you want to use it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    decoder_model.load_weights(path_checkpoint)\n",
+    "except Exception as error:\n",
+    "    print(\"Error trying to load checkpoint.\")\n",
+    "    print(error)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Train the Model\n",
+    "\n",
+    "Now we will train the decoder so it can map transfer-values from the image-model to sequences of integer-tokens for the captions of the images.\n",
+    "\n",
+    "One epoch of training took about 7 minutes on a GTX 1070 GPU. You probably need to run 20 epochs or more during training.\n",
+    "\n",
+    "Note that if we didn't use pre-computed transfer-values then each epoch would take maybe 40 minutes to run, because all the images would have to be processed by the VGG16 model as well."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "decoder_model.fit_generator(generator=generator,\n",
+    "                            steps_per_epoch=steps_per_epoch,\n",
+    "                            epochs=20,\n",
+    "                            callbacks=callbacks)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Generate Captions\n",
+    "\n",
+    "This function loads an image and generates a caption using the model we have trained."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_caption(image_path, max_tokens=30):\n",
+    "    \"\"\"\n",
+    "    Generate a caption for the image in the given path.\n",
+    "    The caption is limited to the given number of tokens (words).\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Load and resize the image.\n",
+    "    image = load_image(image_path, size=img_size)\n",
+    "    \n",
+    "    # Expand the 3-dim numpy array to 4-dim\n",
+    "    # because the image-model expects a whole batch as input,\n",
+    "    # so we give it a batch with just one image.\n",
+    "    image_batch = np.expand_dims(image, axis=0)\n",
+    "\n",
+    "    # Process the image with the pre-trained image-model\n",
+    "    # to get the transfer-values.\n",
+    "    transfer_values = image_model_transfer.predict(image_batch)\n",
+    "\n",
+    "    # Pre-allocate the 2-dim array used as input to the decoder.\n",
+    "    # This holds just a single sequence of integer-tokens,\n",
+    "    # but the decoder-model expects a batch of sequences.\n",
+    "    shape = (1, max_tokens)\n",
+    "    decoder_input_data = np.zeros(shape=shape, dtype=np.int)\n",
+    "\n",
+    "    # The first input-token is the special start-token for 'ssss '.\n",
+    "    token_int = token_start\n",
+    "\n",
+    "    # Initialize an empty output-text.\n",
+    "    output_text = ''\n",
+    "\n",
+    "    # Initialize the number of tokens we have processed.\n",
+    "    count_tokens = 0\n",
+    "\n",
+    "    # While we haven't sampled the special end-token for ' eeee'\n",
+    "    # and we haven't processed the max number of tokens.\n",
+    "    while token_int != token_end and count_tokens < max_tokens:\n",
+    "        # Update the input-sequence to the decoder\n",
+    "        # with the last token that was sampled.\n",
+    "        # In the first iteration this will set the\n",
+    "        # first element to the start-token.\n",
+    "        decoder_input_data[0, count_tokens] = token_int\n",
+    "\n",
+    "        # Wrap the input-data in a dict for clarity and safety,\n",
+    "        # so we are sure we input the data in the right order.\n",
+    "        x_data = \\\n",
+    "        {\n",
+    "            'transfer_values_input': transfer_values,\n",
+    "            'decoder_input': decoder_input_data\n",
+    "        }\n",
+    "\n",
+    "        # Note that we input the entire sequence of tokens\n",
+    "        # to the decoder. This wastes a lot of computation\n",
+    "        # because we are only interested in the last input\n",
+    "        # and output. We could modify the code to return\n",
+    "        # the GRU-states when calling predict() and then\n",
+    "        # feeding these GRU-states as well the next time\n",
+    "        # we call predict(), but it would make the code\n",
+    "        # much more complicated.\n",
+    "        \n",
+    "        # Input this data to the decoder and get the predicted output.\n",
+    "        decoder_output = decoder_model.predict(x_data)\n",
+    "\n",
+    "        # Get the last predicted token as a one-hot encoded array.\n",
+    "        # Note that this is not limited by softmax, but we just\n",
+    "        # need the index of the largest element so it doesn't matter.\n",
+    "        token_onehot = decoder_output[0, count_tokens, :]\n",
+    "\n",
+    "        # Convert to an integer-token.\n",
+    "        token_int = np.argmax(token_onehot)\n",
+    "\n",
+    "        # Lookup the word corresponding to this integer-token.\n",
+    "        sampled_word = tokenizer.token_to_word(token_int)\n",
+    "\n",
+    "        # Append the word to the output-text.\n",
+    "        output_text += \" \" + sampled_word\n",
+    "\n",
+    "        # Increment the token-counter.\n",
+    "        count_tokens += 1\n",
+    "\n",
+    "    # This is the sequence of tokens output by the decoder.\n",
+    "    output_tokens = decoder_input_data[0]\n",
+    "\n",
+    "    # Plot the image.\n",
+    "    plt.imshow(image)\n",
+    "    plt.show()\n",
+    "    \n",
+    "    # Print the predicted caption.\n",
+    "    print(\"Predicted caption:\")\n",
+    "    print(output_text)\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Examples\n",
+    "\n",
+    "Try this with a picture of a parrot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcacd243b70>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted caption:\n",
+      " a small bird perched on top of a tree branch eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "generate_caption(\"images/parrot_cropped1.jpg\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Try it with a picture of a person (Elon Musk). In Tutorial #07 the Inception model mis-classified this picture as being either a sweatshirt or a cowboy boot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcace1c8438>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted caption:\n",
+      " a man in a suit and a bow tie eeee\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "generate_caption(\"images/elon_musk.jpg\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Helper-function for loading an image from the COCO data-set and printing the true captions as well as the predicted caption."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_caption_coco(idx, train=False):\n",
+    "    \"\"\"\n",
+    "    Generate a caption for an image in the COCO data-set.\n",
+    "    Use the image with the given index in either the\n",
+    "    training-set (train=True) or validation-set (train=False).\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    if train:\n",
+    "        # Use image and captions from the training-set.\n",
+    "        data_dir = coco.train_dir\n",
+    "        filename = filenames_train[idx]\n",
+    "        captions = captions_train[idx]\n",
+    "    else:\n",
+    "        # Use image and captions from the validation-set.\n",
+    "        data_dir = coco.val_dir\n",
+    "        filename = filenames_val[idx]\n",
+    "        captions = captions_val[idx]\n",
+    "\n",
+    "    # Path for the image-file.\n",
+    "    path = os.path.join(data_dir, filename)\n",
+    "\n",
+    "    # Use the model to generate a caption of the image.\n",
+    "    generate_caption(image_path=path)\n",
+    "\n",
+    "    # Print the true captions from the data-set.\n",
+    "    print(\"True captions:\")\n",
+    "    for caption in captions:\n",
+    "        print(caption)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Try this on a picture from the training-set that the model has been trained on. In some cases the generated caption is actually better than the human-generated captions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcacd278470>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted caption:\n",
+      " a giraffe standing in a field next to trees eeee\n",
+      "\n",
+      "True captions:\n",
+      "A giraffe eating food from the top of the tree.\n",
+      "A giraffe standing up nearby a tree \n",
+      "A giraffe mother with its baby in the forest.\n",
+      "Two giraffes standing in a tree filled area.\n",
+      "A giraffe standing next to a forest filled with trees.\n"
+     ]
+    }
+   ],
+   "source": [
+    "generate_caption_coco(idx=1, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here is another picture of giraffes from the training-set, so this image was also used during training of the model. But the model can't produce an accurate caption. Perhaps it needs more training, or perhaps another architecture for the Recurrent Neural Network?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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xdlIiPYlwoJxFBj5VVlAiUesd3nrrAtudnKDaxB9K3rv9hPe/vU+gJGlTcTZbMOj1eXL7DD8UbN8IeO1netQVfPRw/olk99+bo/EvslguMcLjwYO7vPOnt6mtIooinj49pCzPvbk4jXAhUawoqoIubQwW7QuKZYqvwLDA2Qhdx2AlPgGhkHhNyfJ0QtSCwAcXdwgCj1YccFal2JbHoBsyO51T1BVCn0ccyrzBOkdWFWxebLO1M2AxKejGQ8azOd1OTJolNLbgB3/6IU/2jvjZr3yZh8+fYaSg020xmiQcT464uLPB1966Tl7Ad7/3Hheu9QnDNq4BjGNjbZsTHTKanHH6vEI1KVn5AfOlpd3rE7cFppb84R+8w2c/t83Xfu46edJmWUyZLkvqfIWtnR0uvbRKv9/n9/7lu/zoB8+4/vIaZwdPaYcV1z/zc+w//UN2Ll7j5LDF3TsP+OE7f8wiO2N19QLv33uPizuXefr0HrPlAb/4t36B9378EyaHR3hxRBBo8qT+OHphaUxB7UKcjqiaJSqQ1MagGodpDE4qnG2QgcQ4yOYV+bwh7oS0fYFvLbITsRil4HkIyccWgUUGkjS3qNJQ5UuUFIS+ptYCSosOBQYQoqG1GqMqh+5HTCdLZGPwtM/mepssK2isw1WOQEqUAOMk0grODmcI3xG3fFwD83HKw/sTlB/itysaf8n29ipHH5X4yqOsCqqqIq9yZvtjsr7mdDKmpuHCSyuUsmFe5vixwOYWoRR5XvL4QYbUMNzo8fDhR7z8yhVuXL/EvHrI13/hIk3RZjQ9o7ENhbN4oiSOI0xlUY3i4UczLl9YRz6qWV3XPHw85fZ7T5kvczwNntQopRFOYhrD2f6cMjeoxpCOBZNBxs9/9Tr/N48+kTyqb3zjG5+mvH8i/pd/+I++gajRYY5VhjLPCSOBVJI0L6hLA7VlMAh55fNXOTg6JJ3nxEFIqx3S7bQIAx+vJWh3Le22R1NCFHTpDVZwTrEoCha5Rao2aVkQ+TVFMqWuFWvruxRFQZpl+IGHElCUFVlaEviKy5c3uPnKBl7LUrqURbZgNmswlaCuzhWWcwoCjZXnobjZYooQcO3WBjde3mRv7xAcrK92WE5rLt3YpWhm+J5DW49WJ2TQ7xD5AaPTGUqErG616HY9TGnpt9fotjtsr29R5QmtaMjoNMMJR+0WrG9IikXN5uYmMki5cvMyj++dcnI8YbpYcnhk+Oa/+BZJknD7J8fc+/B9Pnr0I46eH3D6fEK6EEzOTnjvJ99je2eTnd0rbG/2sDbnZJShfA1aUJiKpjHUhcM5RWMbmroGW6OQ52a2kGgtkJ5AaU2DoDKGth8gnUB5kso2OCdppMU4gbCapqmRStBqeygFtbXUjYHGUFeOvDYoBdJZnLD4oSYMNN1exM7mNqPTBWkyY7jeZTFbEHohw9Uhy/mcPKlZ6beIeh22NzawAlxgicMI6Qzr65ugQ9JlitSaIplz6eI68xNDNm9QQlKZmrKuCbseO5faWF0xmuY8eHTIweMZLa/Lz3zpc+RZQ50rBqurDNeHlHmNECHrW12auuH2+0/prvg0VnJ6kNJqD7l3f597dw6R3nmU4zx0rlDaAxqsMdhK8fR+zsnTFO0qVlZXMEagFRgHzhh0oCkyy3JZ4WtFMi04PM358PYJk7P66Bvf+MZv/3Xy+FNhKXhaky4LlsuMy9dWWMxnpJMzvvDWmzx+NuNob0ljJPvPRihdsTHoMT+ZgJMEnsf2xQ1mkxFCrBLEOVlSYCYVx6fPKYoV2h0fX62cm6l1TV2WFL5BCx9jBWenIxbjGcpTaC2p0gJpwEnJYpJywCG7lyJmy4yTo5zhaogMGmaLCU0p2Byu4YoGZT3GJwn9fod+L6YxGZaatcEaV6+9xP1HT1jmhvWtIdPJKXXpqF3JbFwhhKDX6RD7LbTnsNTMx1O8oGZ1fZWqKum3WgxaHof7m3z324/5hZ//zxgvHhPKAVVZ8+zgGZNZSdwTvPzqNtdf2eH2h3tUaUUrGnLhSg/hC9IsJEkSNJJ8UbKcOB5/9IDlbITyPR7e/R16nQ5ROyDuSoxVLCcGTzlqIymWBc4awm6AUJbGVAShpiotTXE+xQgCgQ4E0nNgJdqLKKsapSSelBgl0Tgm84p21yOdGtLEskyWdHsrWCeQeDhpsEIAEiUEdZrhhyFVKaj8hpZeIS8ygos+n33tGqdPBui2x3Jasv9sTDRdsntphYOjGaXVzE9SyiRjc7eLHUeUeY2WgnYcM1kUzM4Kmqpk2PP54N0TVNOh47epqpKqLLHGkS8MFzdW8Trb/PP/63tkCexcvkInvsBHd8cI6xiueuw9P+bNL19E65jJacXDD/fROkJbn3SUoPoBH9w54P0PnoLyaXc01hlk4JOnFVm+YKM3pK4VhWdZiX3IcsI4wpQGbIXvS6aLhjQv8ZTESKiL8xyF2mmclWz219GBAdJPJI+fSprz/196/dj93b/7FlZUZNmcbNGQTufsXr5ATczjB2M0LaQQNPWUVh+CrqNOHYFqc/XmJtP5CYuFxuITeJa9x2e0ogjp+wgX0NQQxG2cbCjqOY3JibQkzwy+F1MXJcI6jLXnMffGUjUlpnEEbY9eN2CxzLDy3Fs9WGnjXM1ynrK92SeZzhmdlly4cYHZLKUVaKIW+B0fQ4kQHjWG08MpEo2HAiTLZEEoIm5cvclymiGFx+n0gLxeELcl7ajPylqXV169jlYwGj1kbXid2z9+xrB7EScC+ms+82zEg9v76Kjmyit90nnK2dGM+TTne394l163RXcQkqQVxhi0Umil6XRX8UKPV2+9yTLNOTw+YLIYMTp6htYSREPoe2ihcFiEVOdOAN8gJDRVQ2MbdKRJpgX53AEOHWpkoPAjhbUWUzl86+GsIVKaxtSsDdrcfXpKpxfhS430FPNFRacfEvYsRemwjcMikFogrSMMNI3l/IPQlphK44cW7VtMCYP2BvsHR/SHXaIg4OmjPa5d26VxguO9QzqdCOULbF3RbnewGGpjqWvHMivOE6Pykm7XozKKgb9GHLQwdUkyX+CQtPsx11/apbc65MG9U7KqIV1OSWYzRrNjbr22wxtvvsq9e/uk+ZLtnS6zRYqwgud3Z5jaMi9TLl9fIYo006RkmSfnYYTG4QeSsjbkac2w1ULrACMMRZXQDkNkFVOXgtl4RlFVWARJUeB5PkVZ4qykdo48rfjV/+gNNi+s8va3fsRH989+5Jx786+Tx58KS0F7EkeFHzUgA872l1TGMJpM8SJB1G6hXAvTNDh8TF0RqJhaZqRJxaP7x6xth3zuc5ofvL3PLNVoKYliHxn4pFlDXhUYPs6wQ9FkjtN0gVCCOLb0Bz1m4yXSKhAWL1S0Ap+iqrHAMinp9joUpcE4h6c9dndXmC9PaUzD8GKbZ89OSRddBmsxVVJQpgGiUQTdLtKHbDZhpd0lKy2LcY4pUxpTkNcTuLZJXRv8sGG42eFoNKcyOb1Bn+P9EUfPCjpdj5c/G1KbGd3VgMdP77ExvMlWsMaz549x1lEsFG9/8zEnB2csZjlBW/Gln7+CH0kWs4ZLA02n79jcuMS9D8YIz2dl7RYXrrzO5QsXeXD/Pnl9xHe+/a9ojMCLHO22xjaCPG+oCkOdV2i/prE1fjvCYWlqy3A9omhXmKrGSUmWVzS5Ia+a83CeFXTaAb6WyBKWecP6oMeiKEjLhJVui82BT1UbykTitz2qqgQc1lhCrcBZhPIwtkFqiXIGCot1jiQrmc+fEbdiGleyyAsGa12ePT8iiAP82KcyM956/TMMVvq8+84DBt2Y/eMJpRN0Bz5ns4JAQpGUqE4b05ToqIP2Y8oIatuwzBLef/fHrGysc3H3CpOs5uj5I0Q9R6J49GBEv/+EVidEeG0OT2cYveCVW7d4dP/0PLPSKnzh8dJLW3zvh3dRUiADCdph6gahFDK0zLOE7U5M2Qhiv0c2zUnnU9pxh1anjcsKRtMZntZ4QlJYeZ5xWTUo4Xh8/xlPHx1w+PjsE8vjT4WlsL7Zcb/4t69TVwU4STJvSOYJcRQidYuyjpEiBmeoyynOlayt9/E8xfh4jhCWqKP5hf+kz3wMe3sTMD3GxxWl06RFSl3VNCU0qQUDUhmcMAi/QXk+OImrQQsNCNqDznlsvLIsJgvW1lapRIVWmrgrWd8M2LgQoGWXO+8ecHq6oBXEjA7HrF/uc/HyCtNxw2yS0vJiWlEHzxcUVckyL5nORpTpGCEcvWHIy5+9wOzQw1pJ4wxht2HjQgchDNoOuHdnH41lrT/A7xi8yLL/2IMmYnU44OnThzy4e48wVnR7K6xtrZDlJRubQ3Z2IpZ5Qlo3vPH5PmtbId/71lO+/4OnWGO5efMr9Ho75MmIuqqYz6c8enQXoQW9bowxNVLF5ElDXRrqIsX33Xlac9OgQ/WxoNZIGowxmAashCjwmM8K5uOGUCi6cYhWH6dAa0GS1FhhqT+2znwl6PcjcKADRdkYKmdwssHDww8VIlAo7SNcTScKSJME10jS0uA8RVVXrAwipOewjSSZG4S0DHot+r2ARTpluNqlyDifPo5meCLAyZQsVbi8xm95aE8R1W2G3RUcHvNFSm1r4hWPwYbg6b1DIqXxVIinfKTX8OTJGK3PfR1B2MJvB6xf9hgOVth/ckJVwmw8YXq0RCgPhaaz6RMNJaY21LXDyhpbQm0anHAMZRfttfBCj3yacXQ4QghoxSHOC1ksFhRlSegr6sZirSMva4atgJcur/H40QFXb1zmm2/f+Q/HUnDOYhw0tcRV5y9Q+z61cQhjcDicdGglEL6iSBtmoynru6tcuDHA2Zqz45K9R5LlPEOYkDjq8Gi2T1GCUBakRWlL0FZUmaVqwIs1nUEICubzDJREBQGuURRZTlv4iLpECsdsMqesG+LIR9qIut/m+CBlc8tx4+VttN/F2QzUkJNHZ3RbIcZr6KxAUMNsMkLrkDiK8Y2h67dRvZArt2LiGNIm4eBswYX1GywXc6wwxIFPVZd0h5Yvfn2bzdVV7r73jGWa4fKI2x/cJlsYmmbJzu6Ar/3yZZZLQ1Urwrbj1md3efZkyY/eecbVq2us99eZHZU8+uCYp08nbO8OqcsC6T3hne//gKqoWFlbo24c7V5Mns1ZTmtwFk9VJPMK2ziUEFQ1gMNpAe58jUBV13ieBKPQssHr+bTiEOEkyXiO73kYZ7ANeMpDCEFe5QRRALKmbBpKI7BpycYwRiNZFhWNJ9CeBixVVeOMIghhfW3AhZ1r5GVOUy04OzwjLQtSE5AlNatbHUaTJY0VBMKjSB2di322Lq1ztHfGSjdmmhYAlHWBFBrXNMymJT1fIIWmqS1FmlEZQ7pIQGq8sE2ZRsSdAZ4yaOP4/Bu7+D1DLRru/PiATiuiyhpU5qFUi8V+w6WrKxin8aTH/DQnDn067RZZ0TAfVYSxZn29R9mkFIuK/YcZYd9DDhxVVdLuhszKklanjZaSRZIgake30wOxIEtShJKURYO1hpeur7O91WOwGTJPmk8sjz8lSkEwOlugpeLmleucnDwDLElaYBqJIkL5CqQlCAM0fbTWxL0WUbdhPilxUuCpmKYsiOKQvKow2tKSHkXaIJWgMTVhR4EzeE0LP/RYThb4bYPyLE4IwsgDe56zbzDEfc1wO8IY0ASk05IsNTy+e8rulXXyNiiZUhYFybKiFbXZutbi9oePWb/UJepq+oMNZvOCRbokS5c4axmur+JpRWA9fJUTxJbp4hDKM/qDmMlpzg++c58b17cY7SeUteEn+WOm05IHdw5oBxEGy83PrvFLv/KzrK62aEi5d3tEkQnSRc2g32LaWxAHQ8aTEWeTM6SRdNpdVjqXKKuE9rDPeLlkbdDBNIrZMqXTblFWlmpRARLhLEJVeEoifEFZgx/H5wu1lAAtiIIW1SQjmRUEfkCnExKoAJtDnjl04JEXBdqLSJIUpTz6gy5eELBMC3xfoYSmrmoqr6KQITY3Hy94UgilsaYg8DRZaZnZ06UqAAAgAElEQVQtRoCkaR7zt77+FZ48fsLj+TMGqyt0uiGeL5jOTjCFRWDRgQ/GY3Ka0ltt43seN29e4ve+/cesr/a5fGWDd975CIvE9zVf+PwN7tx+glASKxyNqZHaEXgaWxqSiaXV6jOdndANNZOTOa3KsboW85//5hf5/f/nPc6Op0Sxz2Q0Y227w+blAZqSWzcucuf9p3imZPf6BRbZkr2HJctlQTuOKRvLbJFgrMUsJSMSXv/sJbARd0YzwkDjRxFBFLFYpmgtGA562AaWZUHlDBLHk/0xe/MzPN/hnP+J5fGnYvqwtbXi/qt/8CU+fP8+F7e3iVuKk6NTlsuMJBU4O8A2EWvbA8KwYn46JklLGlnz0o016ioH4yNqhTGGpJ4TRB0Wi4LFZIkrFcoHoRxKgLIKa3yisEstKhb1hCBqzvPcqwhP+uer14Sj01fc+swa7YFj58KQh/enPH2aEPkdlBScjZZ4vkALn/HZHFM6VtaGTE5PKcuU0mV85tbnSOYVeZaT5QukFgghiFWb0likFjR1RZpm1DU0TXkuiLL5eIWgxlAxGLZIFjVB5DPcjhFBwMpazOamT6hbbO0ExG3HdGxQKuDhR2dUacRolDJfjEFVtGrYXr9ArdssllM+evKQ4Uof6oYsOTfrtefIshIvjCmbOdpTOGsxwqcyUCcl/ZU2hc0okoaVrT6D3ionz85YlHPyRUU3CmgPB4S+w1YBT+4/x1OCunZICb5SlLVBeB5VVVEbh6ktQVsT9wOUUCSzlHak8VuS2kJVGEzZYKVARlAXDVoIgkDQaUcMeytsbg7ZOxhRGsFoNCYOPYSo8VstBq1VBq0WhDnXrg/Rwufuo8fsbG5jGscff/9Dxkc1dVNz87UV8qSBPCSwPnVVYZzF9wNMA2VjCTs+GxdCVtZ9RvsL/Ejw7PCE116/xN5zePTuEUk6pq4rfD/Aiz02t9tgQx7eP2RzPeDqy9v4PUcctFmcFdx5/wArJGFbsrmzyp33nvEP/tufZTZOefvf3sVVmjRLzldnGskyz5HOEAURYRRTGUuSpuRZiXQNKzsx0teUZcnTR9l/ONMH0zRUacWw3yMvSyrrkVeC2tTUpUOrEqUiiiRj2I3Zz+dUjcMPfY73Zly43EZrxfi0YTmvEDLmdDxHSg8lWjgtccLgaBCuZn29y3xasFgszlOlRYQyjq31iLp2FJXDGQvCkaY53/3WA7Tn8ANL4A9o9/rMZilZtmQ+LrDOEMYRzhgcltPjBOlZVjY3WImG1GnJ6ck+iIIoblEVIHxLvNYwP5iztjpgbWWLg70pi2VBd6VDGBtG0wWbm0PW1kL8dsnV3ZdwjaC/usro6Iio2+Pe/fvcvz0CeYIVQ4SQ1LXl+f4pmyvbaA2T0QgZOZyVVC5nls14fPqUeZayWMxJ6oKuH1NMClRoEL6mO1jl1qtv8KM/eRtb1RTGIsMGYw1OW5yDyAsQLQijAfPFlP7qKjv9XVRjODk5xWsrjEt4460v8oXP/xxv/7t/TVOmFDl4nsbJirpqkM6hhMWLNJ1+i4aGpqyI2gEyAC8AlxqEUZRI0lmGXwlag5DluGIxcagdSbmcMhtP6G8NmY5TojDgi298gT95+zusbawyns85ePIRX/7y65we1uzt3+fV169QFRV7z+YEvmK5XNBf9Tk+TtBC0JY+Ugg8z0MJR50VLPOU9rCN166Rfo5xnXP/BcHHEYmc54/G7Fxss+Vf5Ox4xvhgzPKs5Ph0ce5HaocUjaAyjuP7Iy5e9rn5uV3ysuL5gyXZKCMNS3qdNh+++5zTk4KmcPRaisYGzLICi8A6SxhEZGVJVde0WxHdKMaTHo0pcEiqogGjPrE8/lQkL/3j/+1//oapDHnmqApIlhlSglKaqBXgCKgaHwe0Ik1Vl0R+xHJaEKgON29uEEaW0jYoX7Ky1aYqLPNJcp5ZZw3nFlGDlDWLyZKmEYiP16NLqbCFpSoccdRGSY3S50tTu4M2jXV02m1iP6CuaoYDzWx8xquv71KlCVuXNhludPG8gKIxlF5N1PdJmiXCkwTDEBkLdq9t0O7GvPbmKq98YRMZxWgR8dk3h+BZaled7/FgFcOVHlIpotint1bR6cYkC8ebb36ZrY1NekNNkU4xyZxf/PpXWN+VvPLKFstpweN7I77whVuUjeHJR2NMpUA5pLIkJcyzjPXtLQSO9bVVyrLCQxBFPo1oiAKfrStbZMmCs5MpzllQ4ISmKixZ6lhfXWVtsIlSIVcu7nCwt4dTFb72qIqK7iBASYuvJVurl/niz75F0PeYLMaoQCEVoARl1VBVNYGnyasSHXoYdx6dq/KSIm3AQqsTUZclHh5oSRxELBYJzoBEkixLagdFqbh65SqDbofT0Rnz0ZjjxxM+//nP8mt/51fYfz5hNj+lLCvyoubhg0PufPgYhKPTHZBkOQgo85JWFBB5Mb4KCfwArRRpUeC3Bd31mM5QcOuzQxZpdr7PRB1yfFAwO53x6md22bzq0V9v0+7BW2++iTMe0/EILRQSWGYl82nGlRs7dGJHrAdUCFwwYzDoc7Q/oi4FT55MSJc5GgU0eJ5iWViquiH2fAQO6xxlbTCNRWtJEEU45yiLAt/3qHLDIv1kyUs/FUrh//jf/8k3Xn99C+MUaZ4gZU1hK2pzbjKuDLawtSRZZsRhxGS0pN/vURU1w7UWebUgr3LWNjvUxrJMMiazMVFb0+nGSO3Iy4QojvB0hLE1ygfl+eighed7OGXIywRjHc4oysJR5pa6dKwMe0hlWNkMefXzF5FxxUuvrHO6N8X5LV794qtMlnOcg96gRVIkDDsd/MBHKMt0PObi5U3KtKQ/DLj5Wos0nyFlxOuvXWI68phNUnpbDiNK+n0fgUU0IU1t6XY72Czi8597CScMt+8ccf/OPn/y3Q+5dmOX/acHeIFkuLLCfDFnfaPN3XsnjBcZRapQso1AMZuOWV3dQQeSJ0+e8Cu//Aaba0PqhWQ5mRO2PDqdLsIP0arF6cE+jnN/TFmfT3NcI7FVzfWrl7n1yhvs7r7KeLSHFJZOv0WZ1SB8dOzR7Q/wlc9rr7yFlcesb15i7/mcvMgoTE0xy5ChQEmFH3m0h12sEkh1nueA55EnDfNRhhcKuv2AJreUecOrn93m1dcu8NHdE4q8Jgg9TAPzecLjR4eMjybYssH3fMrcsLm9yqWLl/noo3vs7R2hHPydX/86ygu5deNlut2Qo4MxQejhPEm3q7l8bZ0itbjK4gmN9AN8P2a42sGoGgrH6d6CQPtc2f0iTz/aR1Hw+S/t4Mc+T54/pht3SLIpFy5u8YW3PkPYkSxnC+rKAJK6bNh7csLVqztMThIWi5yv/9oNrt26zPs/PiLQAWWZo6SHFI6ytizTitIYQu2h1bm14GtN1VisNThbIwDfUx9vxmJodwLOxvknUgo/FT6FwSBy//GvfhZPBWjPQ2mYzE6Z5TmmatEkIXVh6Q0lr73ZZzYuGaz6+J2CG1dv4cuQP3r7XfqDLYpkiScFQQSTcYpQIT/54X2sjYhbPstFyfpaB+VVNFYgmhZF7uOkxsoMISuKokA6hSdCpFNobRlutJicTtnYbjE5zTk5mNLfauPpiLSusBhiP+Ctn9klSWuqUvB0bx/hC6SLKfKcTidiOGj4mS/u4vmwmDacLc7w1QqP7p1y9ZZkd3ud0VnJ7sUB3/03+9z54BgpPS5eWWV7t08gSrbWOhRNhd/yefDgCZ3BJhe2d3j3vfeJgza3P3yE0JrVYZdBZ4NBf4MnT/Y4m50yS6f0OhGT+RhBxM0rKywXOc+OJ6xtrvLGG1dxVnF2PCNdwOnxiCQZ0VjLcL1DkjU8f5LwlS9f5/LlFuvrFbs713n77QMePHyIEBGDQR+tG4Ro02ptsL3TZbI44cmTh3ztq1/l97/9XYQRZGVBlOXMRymN7yF6PlaCKRpEAE5Ck1tMDslZSZ6WXLuyTTpfsH1lkzA0/MZ//QqeusCd23u8+6cP+fEPnyCFj6c8KluxTHPW+jHLNGe42SaKfKLIsrGxyzIrKOoFdZLSH3R59GDBjVvbJLkh8hU3Xtvi5GDB3vtneF6IH0aAQ/qOopxw440LPLo/Ye/hAa9/boc6g7AXUQofYwuMSBifTbl57RqWCNMIxqNjLl1aYWN7hb1nE3709mMmpxPiyGOZlAx7HdY2+nz5l17l8dMR3/ydP6HfbeF/vEtYVRvSsiYKBKsbK7SiiNPRjLPTBVoJJJY4ClAf7xhmrMUCQgj2TpefyKfwU2Ep/ON/8j994+ZrfZqmRKFpDBRljbESa+L/j7o3C5b0PO/7ft++9Ndf72c/c87smA0DYAhQEMFdJLiILJEixShKpJQqKadSrlJc0k3sXMjlOI6cxLKdskqJy3Hk2CXFkiPLorkKIEECJAcAAQww+8w5c/bTfU7v376+uWg4yYVjMZGdot6rrv6q36qurufp932e5//7gzBwahaWUyDKlDAOqTcl5DIj8UOWOo8TeRClAsNQqLU0huOUyJeYXyhZP2tTa7VYOWnQmqtQdQ0qloskFeRZSZplpBmUhQJyQSnPZs9Nw0GWpNkEXFnSbHdmBCjbpNVyGR1PUEyZvCwwDQNLs7BknWZtkVZjHSFy7IpKu60xt9hC1kqiKQx7KqNxQpTA/Yc9hoclJ5bmUYyce1u7WG6TzZsTHtztsbzuMj9fRVCQpIKDwwleoHG4N2V4PKXWcNneGTAYjphMBuxudlldXUbWJY6GY5aWOyTRrB2VJDlCJJS5CppAVgSNuSZH4ylpGpNlOU7N4omrl6DM8SchW5ubZEKQJILhKEDTFaSiZM5V+czz72N/75gkC5lOBa+9dgdZlnn62gpVq+CxK09SrV1EU3Um4S6LcwtE0YiCEl3XUUSB26gwnOaMgwijoVCKgmCUIeegqCqaLc1wZ8wEU54XoAioOha9o4DNe11y4TP0fC6/5yTnLi7x6N4hiqQyDSJKCco0Q1J0dnaHRJOUTqPGwvwcH3v+wywu1bDNCg9udkkCwXMfegxBwlxziWCgYFoVJsMRWZziT0YocoFQFdy2xagXsbM54P0fuMSVy2dYXV3gYGeC7hgMvSNUxaDiKlRcmzgrcCyZS4+1WVqfI0pjHn9igcuPP84PvneT0fEE0zI4Gk6Yb9cIBwnVdpU8zYmD2QCXEJCmGZWKTr3hIAlBUaSYlkHkxWSlQBYFIhcICSRVml0tgLQoCaI/R9eH3/zbv/Hrj52bw7JM4iwmKWNMSyOKJcIp1NwatqtQFgFZlmI1NPZ3JpApfOTDn2B3t0deqJQUTMYemqFRq1Rptee4v7WNatZ5+unTnFoH20mw7TpuvUH/2GM68cgz6V0uoU6rVWNprY43GeI6TfK0RJIUplOfzuIyS2vzPNq4SzT1eOzKWYaex+OXL1AkErEfs7LYZDDYZ2GlZGnucVaWHMbTEYam441DGo0muw+OoJxx9xzdJksKBt2AVtOh3Vjk8G5A78Dn2Q+eRzMUDo8HGJZNkSt405ip5yFkmyRTUDQNVdVJopisSBl7Ee3FBk6rhirr1KoWoR/P+I6lRH96hKqbKLrCdOKjmwa6YVBkKWEYo8kSq50VorDgsDdkf/8A3TbISxlVEVSrFiUlg0lA72jAG29s8c7tPbr7U77whY9imDAdTHjmvad48aXXmEyPkeWCXMDZU0+RiYhxf4+l1iIFMPV9CkkiDFOc+ox6FAWCPC6xFA3dAFmVmR5HaIqCLKsoUkkapOiWgmUbPLw/4f6dPlsbxwyGCd2dIe2lGvVWg/FgQhynOM5M5VkgMRgGTIYe3d0+4dQj8ktG/YTe8TFrp+pYpkZzrsbN229zYrVFOIIgCDB0DdN0MTQT3XQBi8sXl6m5Vd65vc00GCOXMolXcvqxC4z6I9yWRZiUaJmOo1jUW3W2tvv85E88R73SYNyf0mh0yEXOUW+Eousc7h9zYX2Vo77PxvYucilQ1BlnsRSCRruKqs/EaKIoOH1yjaPjEUmYoKgSsqKQZSmyIqMq7/YSSvCi9N/t9UGSpFXgHwHzgAD+JyHE35Ek6deB/wT4V3OVf/ldtsL/4zpxoiG+9IUrGHaF/mhKzanSOwg47mcEXs7CYoNKUyVJJpS5hduq0G47+GMPKfFYO3WK+ZUFvvqV1zDMKmNvwtKCxdZmj4WlJg8fHdLpNDl3zqDX9UkiC7dhMR7G5GlK4MUMjnNsq41mKihmRBwNmAwCVCqosoVZUajNafijCXKes7S2SmfVYXuvj6ssMBz1OXexjWNr7x7zBtTrJl4Qcve2TxwViCKnlGR6ewMMV+PSpVNcONdEkUGIKndu7qAXdfb2N3n/80/w6P4e+1se7rzJqXMd7r85xPcnVOo6K+sdDnd6aIrC1A8ZDUbYrsnEi6l1TFYXFwmmBWk6xK3Y5FmV/f0u3cEAZJlKQydNSixTYJgmsR8xHE8wDZWq2iYICqJEppBjRJ5SlgJFlkHJEeQICTIvxDAMmvNNBoMJrabF8koLpJIzp9bY2Z7QnjuJ3VB47c1XcCybj3/0CcIw5RtffZtGfYl7929iOza7O0M6iyaKWnB4kFIWJYqk4Zo6dtVgPErIQsF4EFGUCSsdF0lVOegPmO/Msbg8x+7OHtNJiqYWnL20jKYZREFKvzdhOvCI0xRZVbB1nU6zRW8wIkpjoixHlqDm2Jw82SQrci4+M0+alkx7MfG4YLg/E2JZFRvDdJFtlfa8wsQ7JMozTCfhypPLXP/mIc9deZ5r77+KH99kHCUE4SE3bh6j5Qsszy2SY3Dz5utcvnAePx4RhDnNts53vvMmD+/t409TqqqGopuMPZ9W1UQzVMIopchL7IrK/GKTIpeQ5Ywv/Qef5zf++u8gS7NpUiFAFGI2cyNBKSSyNONwGP07b0nmwK8KId6QJKkK/FCSpG++++w3hRD/3Y+6kSwrrKy3aXUs9nYq7GyPKFIZEUkYhsHcmkKc5ETDKlW7zvg4g2xGJc6ClP7QJxdb9IZDKkZIkua8/sY+kqoj9T2eec8aQSL47itdFlodJuMZGqveqIGiIZsZlTrEvkeJjZyBpjtoRkSehJRpiao5SJmCN0oxqgpWAzrtORYX1/jOiz9k/eQqZ8/NcevWW7i1eY5GEbZVZdyXWWi6PLg3wq22cBs1pFTi6fevcursHLI8oWrL3LtRIqtVrlyrc3L6JNuP9nlwt4tmVKi4EkLxKPSAuRMurlvl9q27LC1WqDZrHN7uYlZVvGlGVkCc5GzvHnPh/Crz8y4vf+s+qhHjti32R/nsWoQgTSJ0XaFaaeNPQypOFVWyUFWXdDQlGE9QDIU4ytH0Er1qkRVQ5glOzUFWq7Rai+TYgMnOfsCgf8zly4vcvzPm/oMjfvpnHufzn/4kKikbu/f55jfe5Pzpk6i6wn73cEY9RkXTdCb9mLnFKrohZtDWKKOQFGKpAElGkyVqjkHfz9k9HHP+5Byr7Q6bh0OSJGF1fZ442qHZqbO/N+IjH32KNAmxHYVhVSeYpgyOR7QbdbI8n0mh8wJJligKFUTO6atLvPbyJq+/1OXyhQWWVi1GuuBgc0RW5sRxQqn6qFUd066ytn6WVCpQtZDByEd3Ktx++Db73j3e+xNnMfU5nFaLtnOLPK2gyTZhHLB+9gni3MLSZXKG3Lr7kDj3WV1rcrzr43kpcRji2CayPKOcp3mBaaggZA73hgRByq/86i9x8rFzKKqMXEhIskpRFqi6iiRJiLKEUqAoP7qbw//npCCEOAQO333tSZJ0hxna/f/1ShPBwVZOnKS49UWsfsx04HFwOODM5VP4nkqvl+JaDfb2dtEdDafWRkQF/jhh/VSFm+/s02jW8SZj2i2L8+dWac5V2N0bMTgOuHh1hZPrbX7w8iNUVcIPAwI/IfRTbEfHreokuYckaajqDNKiaRZpOkFRZsfzg52CsjShkHnl2/cpnnFYWGrTP+rzyY89w3y7w7CzSpSMWFqscO/+CEkKWGp3MB0dySo4OupjVWxOnVsmDXrsPMjIkipRfszKeo3ucIhbqTOehMi6zOKag+mYbO4cEosQOSqYDAMW5jo0F6DXO8S0IA8UUHPyomRwMGZh/gSHOz6DXsbC4gm6x7t0e8eUSsHYP2K9vsja5UsM+2OyUEWlynDgQ5EzEiMMo0q1ZpNFHqmUYRizUWBF05CETBILFudPoZgOB9tjjo58ilIi16u8/vqYIttmMo34b/6r/4GtB2/zC7/0BaJE4u74Jq+9+oDRsKC1ZFDELqMjBVGUpKlgZ2OM264ikgLTgkwu8Y4DrKpDnHoIIWEg4QvBw90+i02LS2ttBoHg9ev3WVlrc/HyaZK04Gtf+yHn1pqsnFpiMgi5dOU0uYAffOcGYVqgmSq2ac5wewg0VcULfT7/732Kuzd32N25y2fee5F/8sLbKLqM07IZHk8JxmNcqghc5uYdHmzfI5lkjKY+zfYSk/2UurLAo/2CWl1msDfh7NrH8WKNO7e+y/bWWzz/qZ+n0Wwy6N8jHsxOO8OjCaUQyJKKZsjEfoCuqMiKIE2yGey2KElLiSKL0VSV2+884OGDHTRF4AUplmmgKhKUJXku0FR9plItyz89EN9d/1aGlyRJWgeeBK4D7wP+oiRJvwi8zuw0Mfo3fx5KTA62YqqtLYxaQUROtdkiiUt6ezFZLhinPWzXJJcLdrd3cMoUzZD47qs3KBUdMpmsEOynIYWcYjjw2U9+io2tDTY3dynLlKzwOe5PCJMcShVbN2Z8gMSbjezKMXmqomgahtWYSa3HCZbpUBYQC4FpytRSh/Ggy/kLNWRZcG/zJj98y8c0auwfHKJZEqGnkKUx/f1NfvpzHyOMEizD5htffYWDu3B8GFNvWLznuWsUckgh+SgCsnREJtXpdWW8ccrGRpdqTWGx45JGEqMARlOBFwXkuQBZIxMlQpEwDEFaFqyeaPFge59B75hOw8apVDh/+izdyZD+4JjTJ5c5Pozpbo0pMwmhKAyOAkBFVVSS2OPChSs894lP8cJ3/yVjb4d6fdZFkUqVMrXYfdRHKFOKXEEpZ4pF1zZYWjwJRcDB0SO2ooCv/4vX+LkvfhqzVDiz2mYjHuNbAcglQZxw9+Y2C8vOzNNBk/GHCXop0GydUhHYqkQWeNiaySjwkWQwDQVKld0jn06Wc2p1mSJv0T0K2NucsrRq8MGPPcnX//l1ukcxzXqV1155C7tW4/TFRaZewr3bBxiGQpxlKJKEgsRwy+fb299Ekg2e/shJ7j/YYzIIWFqpc+ZKHcmqcOPlHerVGrbj8HDjPnliMBgfY1Vs6m4VI8s57D5gEjv8p7/0Oez3yXiTCVms8ZWvPaB31CMP98isKYPJmOvff5vFhTpFpnDv5h6yopIX5btOTSUw884oZ5M16LbGxUtnePuHD/n2n3yPa1cvE8cFQpYpihxVVZA1mSSKkFUVVVcokx9d+/BnbklKkuQALwF/XQjxv0uSNA/0mdUZ/hqwKIT45X/N5/5P3wenYl77xZ//KOE0wW4ZxGXCo4cT/LGMYWiouoAipdlx0asa0zjCG01wFZm0zOj7GaZtk0YJlq1RZhl2VSfwMy48dgIhMsIgYOPhLhVHRTctQh+KTCBKQRLlOLaOouUzDqBw0I06hqESF0Om0x6WXkGVKuRZwbX3rhH6Q+7c2OZDH7vG7uExhwc9KpaNVdE43D5GM6qMg4LTZ1xW5uZ57Qdv8onPfIRT5+d55cU3OD6I+eW/8EUScchR1+PqtWe4/+AdsmiEZWjcud8jEQlhVLCzfUirXXLufIvJELY3Ix498KjoKo892WE4CYmDjCKPkQxBkhaUuYY3ifCnY+pOhVq1QsNt0psO8MIxplxlqX2REyc7XH/lNrfvbRIlOVGUY5oG8+02Tz12gU98/MP0hkf8L7/3W+RShKFr6KrDaACBn5GXCqosYcmCmq2xOj/P0twcnXabnV4Xq6LzoQ98kCefugyygecP+No3v8H+8SGZ4vO9F28QDEJEIeOFHqkoiGKwVFg93wBNY7IXUakoOJZNgUK3P0ZRVFRZAkUmiTM6NYOKbZLkEqZVY3N7h9MXVlBUlfvvbPL4lUV+9t//IH/we6/y/Gefwm44/O2/+UfsbuzjOA5FkVOKkqXFKn/tb3ycnZ0+336hx503HuE6NlmRc+HaPO/98Elee+UhH/nwB3nl+zeYeCEiF9RbOuOhT8VocdwdMTdnUqlXaFQq1NpNVhZb3Lq5xx+98CqLrQpPP3mRB48ecXg0ReQlbrXG7ZvblKlKnqXkWYqqKJj6rC4wmoZoukLF1Jj6IYvLrVnB1StIkpJcFFAWCEkgSQLdMGZQG1XGUGfis/s7gx+ppvBnSgqSJGnAl4GvCyH+1r/m+TrwZSHE5X/TPp2OK37uSxcwlQp3bk0JY0EQ5sRhBpKMbkgYhopVtSlFRphGM4CHWiLylCQusZ0KxxMf0zApk5j19XVKcnpHR9iKTpb4GNZMh6+oJkUmM5lMyIsMy3RQJJ04DpFkgYyK6yxSsetEqYesjCmLBEWukkeCpZUWF68s8PWvvohSgYuPrzE6CqjYDhVX5WhzgB+lHPUV4nTK8sIJDrf3qFUVlk6sYagKb916xEc+/gynzjUwbBNdzun3Jhz1hvhJzO7BYKZ5yGa/z+WrbRw3Z2fPZ38LsjQni0AtVZoLOk5d47h7gF6TSTOVxC8oEgk/9FicX8QbTul1D1F0C7dR5bHzJ3nufc/R78Vc/94tXnzp+4ynProqs9zpcO7kGT7wzFNcPX+S8xfPcH9nm9/7Z7/P/Ue30QyXrUcDtnf3ifISU1FZcG0WahUabpWlhUWuXL7CmYsXWD99nqJMyXOo1hyCYMqjzUe0O0u4bQdV1pkOR8RxiF3vcOPWbd567XUebW0RSMcsrdQY7frcubuHqmp02hCE5WMAACAASURBVHX2Dw/Jc4Ghq5QAskKS5ti6TKtexW3MM/Ejer0edsWkzASNWslf/a+/yFtvHPLtF+/x8//Rp9GdmO/8yX1+53e+QcWxUYRg6ic8/VSLX/srP89v/61v4o0HvOfZczy4P2R/74hGu8L8SpvTZ1s83NwkSiQCP+Tk6aWZb4dbZWvDgyjig598L/fvdXnz7bvUag47h31026Bes/EDjzAssTUVS9OJ4pIkLQj9dFYoLFOkHMq0IMmy2fczdJK8oCgFWZ6zvNhEKQWgkpcpaZwjKzPZgKKoJGmKpqoIAbKistUd/bstNEozT7N/ANz5vycESZIW3603AHwOuPmn7dVuOzz//AU2Hh5z6+YhYCIj0JSSMs9RhUFZSHjjiDxNKChQzRy7pWI4Kg1XprPoENz0EaLEMC3SKKDqGhhCokgCZElg2TpxqJFGKUEaI5QSTYY4mZKnMpZRRVOgM9ciy0uCZIqi6MhUmO+4SEJja2/InftbYAYYDYN4GmAInSevLUJisvFwh9WTl8lERscLODoaMR1MqXWaOI7G2voZ+t4O1YbON77yKo3vK3zs009x5tQ6mhKTyRHVOqxXqiwvLLK34bG92WN3I2Aa9Km1KpSlxqlTJxkOeoTDkt0HY9bO1DB1B720IQ/xg4g0Ap0Ko+N9Kg2bJ08/hogVhkOPra0uqvIK/eOIB5s9qrYJcYCtllxcbrPYcRkPDpmMbBR5hefef43nPvYchwf7dPcOeHjzAbfeucXewS5JEkMB08GQqmNz9tQ6zXoF07Q46h9h2SaIkp3tY46PBgxHY648cQXbthl7Prs7O5w5t8DqiSqqtMJPPH6K/nDEW2/fQqtoFE8Ilk7s8PBRlxMLLquLq9y6d4/RZETFsmbUaFMnTgsG05iD4/soClRtHZScUkhsPBrywgtv8tyHz3Dnno4sbTLfaPP5LzyOW9P5h3//BSRNRjc0Xn9jwH/+n/0uthXwV//mZ9h75JEATlPn6hPnePl7b/KVL++wtNBAUgrA5NHDISvLLQ57HqYrkWku9zd2ufXwkFqtzTQMsW2HXJTEfo6lGcwtucRZgTcImA59dNukUjEYDsdohoFdNUmDlHiUosgytmuQjkNUSUIImW7fo1V3sCwJqdAhh6xMkXUVBDhuhTTLkAqBYWg/cmz/WWoK7wP+Q+AdSZLeeve9vwz8vCRJTzC7PmwBf+FP28jzUh5tmUzDKivnbPx+jcM9jzIpUdUS07JQHYssi4mKeOarmMtQ6ORpihdNOHmuTcUQFAgURSWOE3zfw3EVQr8kylPCdEKaKcRRimqomKqOXICizfgAjUYHFcFk3EdWNLJUQ2gNTLOKqspISkp7oUazuY5idKmKjA889yz7j3q889Y+l8+fQWQq/X6P+bUVVEvD9z2WW+eouW1ee+NlNjYf4DQlHruwROsn23z7az/kj//pK/zCL88hSSpFnFNzG3jTHnkc09sfcuLEPJPJiJo1T/9gRFGmlHHBQnuBw3BAFGVMpgmGlTHud7GtCq5pkSo5rbk5LjwFJ9ZM3nztgIXWWX7w/RtMDhLu3xxiuTZpnhOHIZosqKkwOdjEGx+wNt9GWjcZ7koUwSaW42BFMa0i5uQHLvPFn/044+GALEkIfJ8Xvvoiw+MhZ9YbzK2uoDo2YRwRehFH3SOSXLCz22My7vPOm3XKsiDOI3RZplG3eOW73yP0Q174xje4de8hmmmhahbLq6u855lnODrcp9/r8qnn389nfvpjvPTd7/PdV74/u0OXBVXHJi4K4iynTErCKEHTZAQqkgJf/cotnnxqhV/5i59G1QsUzWRja4uf+dwpNA3+7t/7Y5YW23jThOPjAWsn6hjyMu+8/W3QDYyawfU3blFruJQojCcBRVqiGzqWo7K718W1q/SHPonQebTfB7lAQibJUoqiRLdmhb8oLRD+mDQWpEmOWzORdSiTgoqi0O+NKasVRD7zQ20t2Bg1Cc9X8Cc+mqmjWRWiQqBkOf4kpswT1KpBpVZFFP/KS1PgOjOwMdtHP1Jg/1iMObfaVfHFn/sw1ZpJu13w6stHDI4SvJFHkWbUGg1qy01KOSbxA5IwIc+hyHJM20A1FHQTnLrJZOxz2O2xsrRAUeTML5uMeh6el5KUPg27iWnZTCdTbE0HIVFvz6EYJg82N9+FY4REkUCUGrJSpaJVsSoybitnPPU5d2qZXJownE547OwicQwvfW0TA53ltSZ2tUV/MGF5pYNVcbBVC7mUuP3wNsfjLpYrM7fYompXOXjQ443X7+O26nzoA+8nSge053Sm0YjVlQV+8OImhm1w7vI5esMj/CgkDyTuvHYfUQoMzQYp5ekPnEYoMZ3OAqpk0nBdbLeBLGm889Z1bMtnbydAKBrnz1/Cbduzf5vuhBe+/jaHO0dkYYzIfBqmzNpym9PzHS6eXeLEcoNOq47veUwmU9pLS1huE81usnj6CkKxONh4QG9/h1KSWFpZA81hZ/eA7Z0d0rykUW9h11zuPNjg+LDHhz/wDCdPLnL79tucWj/JjZsP+d3f/wqrK3NoZYakqmRIFJJB1TJZW3RIwoh+f8z8QovTp1bJS4V/8r/9Cx5u78yMYVWJWr1F4EeMJxOyYmbmWgiBbWvEUUHN0vjCz72Xx59y0WUF122z09/gqJuzu23y2uuvEsY50/Es0B6/vMiZCyvkqcDPPAbDmHrdJgoz8qykyAqiMMW0ZmxQipxEsUnzgrmGAWhMg4Q8T4jDCNU00U2NogBDk4iCiMlxgGFq1FoO0TggDQQTL2Y6DSiFYOWEg2krVCyFx64+yda9AZuPNqg1NSShk/gZ3aMJjWYVSZ2JrZI8g6LENDXcdpUsT3jr+zt/fqTTEhKqUrCzvc+ddyQiryRJcpBzZDUnCaZEAxXJEtQqLsKW6Q2PURSdRn1mjSYyqDkVarUaSAqBHyLLMuNRDqWOlMcouoaq5Jxcn2PzUYrIU1ynShZ7hMGI5aUq7fY8aST44RtvoxsCRSrw/AFRpOI4c7TrJt29KYpa0p536B8N8KcVykxGrgkeHe7TSgqyCNqNguuvvkNnbh1FmXL27GnkfQXTlIn8kOnwmCgqeeLaRexGwWF3i+0tj6tPtfj8F6/xxg830JyYz33hvfhxRq402bvep7c5QNcVltYXKZOcuQWNLIJK06VEIDQIC3jne7cY94fUqjZTHKqVJtc+ugxKyO7+BllsYFoOTz65hlvRWV5YQ1ILNrcesbnRY2+0z9ZgxJOnVynTuyzOtVhbm6fSbhEn4Lou1ZpDkoPh1phuSTRqLmalznAakWNw4uxVDLuKLKsc94/QZJ3FdpsLj19i2N1hMsnY3Rtx/dW7TKYeR2/0UESOphtkqJhOlVbVRPhVoGA8HhF4A7o7G5iqxs9+4oPcfNTl5R+8wfFkRJ7mqAhsSyeKBZKiYMiAkLEthYkf8Y/+8Ss892idn/zJx2imh4y9iGDi8NlPfZQ/+uNvsHK2AYrEwmKFME+5c3efs+srREFJEMYkWYBdcfGCYOZgXtFmGPsENK0CJZR5wVLbYWWlyreuPySOMixdIkpjXBuSQsL3E0xTpdl28CYx3b0RtZpFXCZU6xayriDIWTtTY3gcE3gJigiYX9VBq5HnKb29CFkWXL26yH7XQ1EKsrikUrVm/pdpQuAFGNKfFoX/1/qxSApIClmhokgNkniCEILWvE6aWeSxjVLmRN6YMlAIxz6KplHmAs3SSYsQVVYpC5AyG9dVOHVC57C7z2G3j11VKfKSat3FslVGkxE3b21g2RqKoRHmGYoKB7uHuM0mjWqDhblF3LqDJAmqjkat1uDokUdvZ0qtXQOh0Jl3cF2XybhPMIhwXI2zl10yEZGkGUVkc7Bf8slPfZY4SxiMHoCeULObuPUmadale3jE/tRjwZC4+vgqG1t76KbKd/7kBtuPejzxE/Oce2yN7a0DugcRr/zJAxRKOstzaFWDIo750Mcf440fboMIefz0SV785k0m44AiyShVuHJ1jdWVeVZWm9y79YigVyGVIyYDBUOBEwtriHBIq74IFJw4cZrxMGAjP2CcCfz9gIUlsBWDcpzQWZFBq3Pm8nswTJuRn6CbFXKlimq3mUYxX/vmSxSyxsnzl2gvnmBhYR5Nl2kPXHo79zh59jyLy8s8uH2Hza1jvvPKDcI44rEzq1y78hj1RoNRWBLGCb3uEQc728iaTKdTJ8lTDvf3mW9WUasuoT/kM5/6ANeeeZrf/vv/mMOjfaSyQFYkTGNmOVfmJZIMSVFi2halkHj11R4bmyMuXV7HkHJ+4Re/RO9wwtrSCUJ/QuSlVFsqTtVk2Pfp9kYItcTSBZpmIlHg1ivESU4pZHTNpkQijhKyPCCXY3a6FqomY+kSoqIRezmGrpBlBVmSYhs2bq2CJ/k0VJd+b0TgF0iqQpxmmI6ObqrolsTyKYuHN2Ne+PJ1KnUbVdNJUpmNewM6rQrzjQItz9AkCcuccR6LYoYfKEVJJv/oPIUfi6SQFyX37+wz117G0AySMke3NDJkFppr6LLE9sY+ihBU6hUq1QoHe4eYsk57ro7vTRlPY4b9EbotqFouA0nl3Ll5CqlkdFyQZQG10kQ3DcIw5vRSi42HXeIk5cLFNbZ3JXZ2BsRBQnp6ypNPLHLn7jFPXFtBxBEnFmv0ujk7mz55kVAU8Nz7foqH+UNuTV5iacnC742YbzUYx4JETah1Sm688zJZEnJqfZGijFHVY8bHKc8+9zSydJ0sUVhoLTOdBBRlyLPvv4htOXz9a3eIs5KzZ8/xvfvbHO1u8VOffor1C8vcuH5I/6DPJz/5PkpZYnD4AN1J+PIfvIooBZWqzfrji4z6Y+Y7NeJkymuv7zI3P8f9B3c5sXqGhtZkrt2hUathWSpTr0+u5DzYeJ3efg/XrdHrHbN+9hzdsUfNBE1vMAxg4eTjHBxOCIIe7fkF4sER3/3Wd9jc3GBra4uiVPjJD/0UXlhg+x6NqEIwmrJ17w5pXuJnBS998zvcv/uA3Z0d1s+eJwxD5tsOZy+eptrokAoVhMSgf8z9dyoE4yOKrMS2TRqNOrkQZJLMYDxh895N6ktrLCw2SPKQMPAJk5g0zSiQQQgMVZ6BXZCQBSiayu6+x9bOm9iqzOHB38OpOrRqVfZu9tB1ncPdENOMUCSFbj5i7WwLUegzKzre7WTl0gxeU6YzGzw5pyxzGnWTg6MBvaMplQogKZRlhohL4lzB1GeA4H5vQl4WIGdU2xWm/QBVVZFVBUWZoQp3HnnMd1yqdZOT6/OcPjfPaBrwna9vsLzcQrd1uuMUteIQpQlaWVBmJZIqoTDjK0jaj14m+LGoKVRrtrj2xEVsvYrnh+hGiVtzcBsVOp0qoT9CUxWmA5U0KsnUmDhNOe72aDVrVDSX4dDHXbBZXDY4PpxQFhJXrl7leLTPgwcbIBRsQ8ELQ5yqTKdls701prNQ48Rqg6989XVkxcZUJZrtCvOLLaajjOXFOVzNpXs8ZKfroQmHIEzIiwSVnEatTrWjgzRgPArQCzAqJkpDRpENcpHg9xUqqsWJtWXaC6uEUYxjmJi2wdb+Dvv3D+isuHSPdlElBXfeYjyJuHH9kGSSk+ceV584xX/8Kx+hKAX/8ve/wyd++goHe4Lf+Bt/yLPvP82VxxcQpFx9Yg3DPMHe3jGxJxiOh+TShDgu2e+NmZtrYBkNFpoqp06eZuIrUIBbrdBotvi7//3/zMb9A/b7A0xdo1U1GYxGIODSSodf/bW/hFmpsvFgg6eefT/f+tbL/NPf/V/pH/eQdRNkjQ995OOcu3CVPC8JJkdQpJQl5ChIso6iysSxRx4lrJy+gK7JdLfvoOYBtlkShh6FKOksdNANnSLJ8LwA3w8QRUGWpvh+iG6q2KZFpdHg4V6XV6/fptZsE3hT4iwDSWM8nYJUoqozOzokBVWXUWSJvBDEaUac5hRpxNkz83zssxe58dohN14/wK3bJGkKeY5hqaye6aDKM/fxNC+J05iinInShFyS5rNTg6YIWq7OwVFAXgoQGZapULEMdFVnMPFQZZUoSMjSfJbg0gzHtqGEyI9njMuKSpwXuLaMa2u0mw5ZCsHIp1Gr887GkFRWgAJJKihLQSkJKARFnqMZClKZo8qgGCpvXe/++akpVGyTWq2OP81xHJV6Q8V2FRqLkKV7fPD5Ze7dHXP33gEUBm7bwnZNFpUzlEnCOJii6hplUXBw4KNpCqap0usOkCST+c4c8/M1tnZ2ICyQSoU416i4Fv6wYDMeYpo6i6sd6k6do/0BB5t9lpaWGAwmdKMJ73nqGVZORdx4e4vhKEVRJBTVREgSmqoRRAqaYzONAgpvynLFACOnUtXZ3+mRyzUePgjpdcc068ucfs8pMpGjSgYHRz3s5RjNUTFklYNDn0kvYq6tcuIn1rh7d4e3bm3yW38no9mYI/ZLvvGVDb73ym1+7a98lPd/8AoL8yaet8fxscJkNOTUegtFTzno+mw+Uniw0efk6dPk5ZBaM6PbDekd3iYtc+7f7bIwv4StGkQTQZoJRFEAGl4Q4Sc5pmHhFTBOYrr3Nlk9d41v/eAWf/CHX2bjcACKitcbcfHCRRaWl5ClApFHJKFHHCfIuoNdb7G4tIqs6SBK8jSj1XRIvC51p2DnzgNGhU9RFuQoDHs75FkKRT6bzNN0JFFgmRZVS0Y3ZBRd8Ccvv8bG/hBJtVBDH1GWTCcTJEVBkQABIi/QFQndmI0yx+WM1mzpKjXXxA8Nbt895rnnE84/scDe4SwBlbKKbVeoVE2iKEdRBHEmyIoc8hxNBwWNMs2pVzWSDE6sONScKmUxZDAYohsGhiUznYQ4ZollKsRZQRzGLC512N3to0s6wSRGt3SkUkLNBYYORlVFliQaiw6aXDLxCzTDJlcthCbRsm1GUw/dMt41R46QFAmBRCFKRC5AlZHL/x+0D/92l0SSl5SiZHGxwfrpBoOgh24kjI4DdnfGHB4eUWsKFFEhiVREWaBqMrkwqVYMJFEgiYI4CZEpUAyFKJqgKS4qBpcunGcyjgkDmc58i0fbW6yfXOXerYeYkcalC6dw3Cq21kIv6hwfB2R5QbtdZ239DCuLHb7/6luM+mOCIEBRZIRuIEsyysBANRukqU80ClB1jUyp0nRUjvt92m2DZ59dodF2eeWle+we7XP9t1/k0oUnmY4jGs1l9rcOGA8nlJGCosqcv3SKi9dO051soDVXqdU73Hx9m3prTBRGHB2M+Uv/5fN89vNnkBKFyXCDaTAB5jEtm1xMqbkWZ81lQh+kq1XiMENXTGSRcjyMuHxJ4vKVOk89ucDOTs5X/vAHyKWCW3MYB1PSNKVSq7Ps1plORgjF5q033mFl7RSK2+Gf/dY/5LV33sawDMIgx9Isrlx+nEazNbNs1wROo4GaqdSa81x7+mmiICIvctyqwa233sY72qVIp8wv1Kk5l+nvbs3GeyWFOPCJgoCyLBlOAuIwYzQeoygKS8srxJnMg/1dHu1MyQqFLJwSTEFVJHRLp2FbZFlOlOYoyrsUorLA0k1yRaLm1pgOR9RrFnOrNSQJrr+4i1yRcVwYD2IkBSr1BoWSoYiSAkEuUhzHIfWnSKIkSVLIC6IwQjIt+sMITbPwojEUGUVYIMnGDOeXhbhOFU0WpKZB72BM5hVotkKWZmi6humolKQ4FQvJ0PDGKaNhMDs1pyG6WmPvqAuKIIg9ijil0GRKZdZtUQBJnrmdKZqMUCQyUfzI0fhjkRTiKCOJUuyKQRDm7B70eezKEooIaFUa+F6AbbXw7Ri1VPEmIYkH9YaEW9MZDiImns/ykk2rbnN4MGFxQaXIPcrcoTN/glt39zBthzg5JEpj1taW0PWSatVFlwyCMRhKyZmn1nhl7y7zS0soWsTOowPidJvvvXyD/e4AQ5eQtZA4yClSFVFW0VUdNdEpMXCsFo5rYuQGS4s6k1GIqel4XQnbKHnuuSu41TovvPQ2P/jmdaRCRRQSV68+zfmrNW7ce5nmnE7rhIoXjti5NaV7OEKVTa49c4rmXEHveMKo72OaCnfu7lO1XBRZsNed4Fg2rmtxuB/iTTPSJCPPDTrNOtuTLcbThOkw40tfusTCHFQqOmfPNHnp17/LdJTQqLvs7m3OsOoIKpYNMpi6wVNPXmNnd8D86iX+x9/8b3nz9ZewKzZZGiPSkOc+8hHe+55LxNGIRFLQTQdTdbFUmxOrcxRRn60HG+SFQMglg/1dFhohhpKR+Ql5klFpdEAopIlP5vsgAYVAkXLqdRerYlAqBoOgYPdoDz+Iadd1SlXGTxW8aYjnxSixSpqBa6uYioIoBI5jESYp05FPrW7yxKWTFPIi4+mYRMRcfWqN3Y1D0kQgSgCFRqtCkYfohkpRSGSJwHV0JCnBrDsEfkEQJCiqgl1xSIqC7v6UnYdHNOYbJCIl92O8IEGzdAxDZRokGJZOq+NwdOgjaRJpmtNpW/CuMa+lGIReQDKUKCWJNJPpHYxxrCqhNCUKk3edpkuKIGEYxHTWmpRyQZGlyMiQQ4mY8TmlH7398GNRU3BdRzz9xBVUrcRt6lg1nbXVdZYXbI76e0R5Qrt+hqPuFC8IGA9ijnaHKLKKbAiCNEXSS9aWbdodi9evb7KwVKMzZ3D37Qn1RofFpTnG0z5JlpFmQ06uL3Hx/CpH3Sl//Mc3kKScz/3ss7QbHb78z3+I6RhIJIDJ2zfus7BcZ25FR7NlkonC4dYIVTWQJZNiBsahoMR2oVavEocCXU3wggizopHFBXkRUZQC1zHZ3BoiSTKOJVOWOYtzJ2k4TXaO9zEqMr4/JE+gUpdp1qtUbZdCkplb0VD0kn/wm7OA/NX/4mc4cUpm61GX1VUXXWkxGggqlRZ7h8ekuY5jG6TZiH7/GDmxOHlGoj0n0LUGRVTj7Td7fOuF+0iyjiBjOB4xDRPGowHVisvEG9BsGhhqm1OnL9KsuQwHx7z9zg8xDAvLMnjPE4/x3LNPEHg+41GMXZ8jQSbPZQxDRyoTZElC103KIkEiJfKOkONjcgomkxSntsDqqRWKZEziD6HMCb0Jo0GEXhHkmczhwOPR/pCt/S52o8L8Sp00jqDUkHWDOJzBb6NA4eHdLbIk5dTyHEWeMvWmdOZaDMcRk4lHpW7y2OPLdHsjVF3FdDSO92IKqaAsCxRDo1azMDUZ3VYIo5RgnPL4Eyc53O8hSoUohEySSLIUW9dQZYWsLJiMJximQSlKAi9E12fcTR0ZzdKQNdBNBcOwKAvI4gzTkDnueYRhzNJCjUajyuB4gts2CKYpUy8mTmb+G6ZtEeaC4DhCyQSKoSHpEq2lJl4YEgcxRZyiqjJCK1A0uP3a8M9PTUGUIIoML40ZelNqtQrh5CH37ghOnGmQZTlH+SEH3S0arVWEDJqjkQaCimzw7LOLJJnH4eGUV39wG7fhcND3CDON6lyNKB5y88YBItOxqxVU0+JoL6FiBiR+QqfdQDUKvElB6G9QX/Cp1ov/g7o3i7UsPc/znn/Nw56nM586NVd3dVePHJrzEFOGZFmJk0jxVS6cwEaA3CQX0aWQIIYDyELGiyhBEsRAAsuwFJF2rIGkSIoUxe5ms5tVXXOdOvPZ895rr3n8c3HahoDAQgNKBOpqY2FhrYsN/C++9X3f+7w8/CBkNV9gqAYNo4NDwfH+OYmvkMYpUZlgmRVZLikrQX/QoreuEQYllQg4OlqiCYvIB8vRcZttQKHRNbliaRiWjqpKdvea+KHH3Xd+xNl+gqY46Jrg1Ts3eenT16nVbTpNg9///R9z790zPvf5l7jz6gs8uDfkj37/Ca99ss9wGHH//QJFTKFsUKtPiGJJrd5FDBT8OGU8zmjaFYu5TZK7nB+dEUxmeMucfreGgqDZ7GHaV1h4AcPxlOl0wWufeJG3PvdlRuc556dnbGz2EDJjb7PL5d0dXn7pBrWayuTskFUkqLUGxElEWkiKQrKcRigCWq0OyJw0HKPLFE3JCdIMqbdZu7SO6+jI3EetAnQ1p1QyWoM1ajt97j1+wHe/8y6LhUdeZuy+sI7VcrE6OkZqEs4Lpuc+jZ7G5k6XfnODq7t9KqHwzg8/pChLFKOOtwgxDYVm06az3qJRdzh4dkaj1USVoBgWaZEAJaQFggKn4RCuCkQlCWcxhS9otxs8fjTH1A0qRUGRCqvFnH6vg25r+KGKUKFmmli6RhQkGI5FmVVkhUSTCpqqUCoZWVGgWTo5FW7DQUNnNY9IwwIhdRYTSZlLeo0B0+WCMksp4pwql+iqwtpGh0bTRlM0zqYTOvU656sIw9CwLI2SAsRfselDs1GXn/jUi8RxRJGU5HGBpikotkWr49Bq2cwWcyzL5M1X3+Ro/5yz8YQ0LWjYDRptjf6gwYOHj2j1HQpZMPeXqIXLxsZlpLJAV0tm0yXnz30spUaa5KQywnJMbMel3W7SaYMfhCSxQpQkqBj0eg7TYUwcVPTXmxgNQV74RHGKKh3mkxDbbrFc+DiWiWlrDIcz9q5ZNPo6h09WbPUvUVTpRVpUq0UQxURehCI0Lu1t0OkaaG5BHCW8+51Dzg4WVFTsXr5Mq1Znd2+TVXKOpXdYTiPSNGTu+8yWHoEfoCvKRdqUoaEKyMsczdJZLCaEK/jCV99k74U1fvCjd7jV30ZXClRhsP/klNAL8PwFFYIwTMhiSae3zdbeFdZ7HdpdG6exRkaDTr+HZZpMzp5x9Ph9vPmQs5MDHNfBMF0MzWHn8mVWoU+a5Fzau4xQFebTJfVGk2arjiJK4mCOqGKELBC6xc7eNUSZkqU+svChChCiQtNthL3OxLP4F9/8BmE8w1Bc0iLlykubeIuYMkvIQkmS+qDbpH5IzXYxNY2T8ZCdK9ucHsyYDpeYlk6alogspdO2GWz1CIMQxTWZLBa0nBazVYRmqORqhX/ms7ZjDyZCOAAAIABJREFUcPX2OocPFqz8HH8cMVjv0t9ts/BiGjWH2dInSxM2B3V0U2O+iMhKiRQVulAuTEulICkulp9a/RpperFxqBsKli0xPjIulTnkUU5Zlh8F+l5wM1VdJ81yFCHRFEGZl2SFRNcvBH+t6/D5T77Bj+8+YxUsyfILy3Ve5RdRckHC/mPvr06lgBBIwySPQxRbcuPGTRzdIK8iikowmczwvBDblHzn2z9kvpijGRq9VpsijTg9VDg9i8E08X2wLB3Kkr2dy9SbdZZeSOTFWHqbzqAi8BIiP2N3c41CFBSFyuhsznKikKQ5dz7Z5MrNHv5Ch6KFXZvx47efkU1y3Fyj3ayhl3VWXoQsbcJohdtQiJYxUtrcvnOd8XhKo6ljqJLR6RTDUfFWFYtxSLvZJVrmtBouy/MAmTQJlgl+MGPQ7aNLk8nUwwCuXb3EbLZgc30T3VTouSZRUCPdjxHNGk1HRdcUDE0jyRKslsL6docrV7fodB3+9//pu/zTf/otfuHffosw9enV1siLgka9z86XXsep1XDdGmFa4K1S3EabG9evUWQJh/tPqdsGluty/+kB8/EIQxOMTw/ob+5SVArmbEWz3aQsKg6PDknzAE3VCcIIGS/Z3r3MxnqfNIsRpY9umKSAEBVUGZ3uNho+aeahUKGo1UVIqlSIc0Gj3uD89IRgOWLvxhbLWc52r40hHfzRBMuwkWqKUXdwbJNVIZlNQ0IvAl3w6INTBpst3vriVVzXwXFVjp6MmEwSnj09xdE1WorJ8jRAXbeQVUYeCzQUZCkJlzmLcYw/KwgCiVRVoiRFVhW2bWJbFZsbDU5PLsC3eVGRpQWoAk1ViKIMW1OxVY0sBVEUpF6MMFQUU0MgkKnCahljWTqKrmE4BmWZ0u7XkBhMzleIvLigKWgXfgZDE1TZBWVLqDBdxrx//wlSrciqDMPU0TWDMK1AVIj6xz/qPxOiIJHksY9b03CsJm5NYzacERce0tCwm4JGe40sK9BUgdvc5MbebUanB+RFge6oFJXOfLYimXu0OjYaNR58eJ9eb0C30+Pk6JSvfe0T7F17g/1nIzq1PqP5CX/6w/uMzlZYdRvddLEslZVXcHqaMT5Zcf5sxPZuk96gSRBGZIHGaFkhKpMsy7BME6ftYrQzugOV2VHF8GCCKkqe3vWxLYuiqHBUg267h+JWTCbHOK0G3UuQJz7Pjqfoik6jC3mWXhxsy2U2GnJ60MF1TT68+wC3qZMEGWVZUFYFeR6jSpOG06DbrRNGKbkokVXKvYf3UdD4xOducPTc4w//+bt88Wufpdm7hKZkfPDTe0znIa+99kkuX+3QHfTpDFTyLGR0+iGj8zN8P2amm1i2TbvdJgwCnj+5x8nRAaZTY2fnCr7nXRipmgZZHlGl8UXDLY4JFhPGisSywNQVskRg6TXqdkUSJkhNo2ZWyNxDEfnFevoiwFvMafXWMOsuUVLy/T/5E6aTOZ//0m0arZzZbM7ifEmjo9Ksu8w9QZZVjJ4vSdOMre0trGsWdt3m2eMz1jbrLPwZulkjDVPufOYqLbfLT9495N47jzg/ndOt1anbCqUHRs3CnwS4poE/S7k3GyKliqoIdN2kyCWGqdMdOAiZcHSyAFnS6dYYjX2KPKfp1EiqlHbdpMhyFLWk5CLzdDkLafVqFxORuCCzLhqJsix46fUtKlEi05y1jTbv/uQBdkOjylRs3SRIAmxLw3FMKi8nTQParTqVFEz9CEMT6IZFniasr3UwY4UgCLBr1sc+jz8ToiBExdZmi/FsyWi0YDKck6cVrY5Nv+MSxR6LVUaUxLQbDWzDJS7H+OUSx624cWmHg8cJ06SgrCRhELG912Q+V5CkPH/ylHAZ8od/8H1eHl/l/GjO2toxaV6hUWN7T+WN11/n/t2nHB0OGY4m1FsW22s7NJoR2AVrTov0WYkQGrPV8mKtNa/o9Wq01xr41RGaqWB1VKJZiWHWaHddFAXyMkEqCkEc8dpLt6l3VFb+kodPnqEqGnGUsr7XZlkVoGiouovbtDg4m7B/eswLt14kUVSEmrN+Y508ELS7DQ5OnvDk8VMKr6BRt9ja2CaVGWZNcjA8xq4bNNs6azs9Prv3BT731qucPf0hHz54zHd/8GPCKOaPvvvH1FyXwdoat2/fZq3dwPdmSF2nKASGYTIYbCG8ANeqaNiS2fAQx61zeWcby1Q5OTpgvd+lYRpYrTqm49Jp2KTRimsvXEdRBMv5BFXTiEofVdVQVAvdskmjKWWRoCgaYRix8la0O21QFKTUuXf/EXNvwrVbVymqlOF4hl2/4F5Oxx6jyZDRSUSRF6xv9VAUk+a6wdJfohQVtfoFHbnVdVjMQq7c2AYU7n74nEbX4MrNbT748VOWyxDbUSEqcCzJrCiwTANT1ynLijBKsRsucZqgS53ZeE6ZJ9y4foWj4zGdtoOmKihqhqrmVGWGjkbdsQmTBEW9IFrVXQ3XNEFTsCqJ58dI1UIxJUUOqqIwGi7Y3XMogaqqsCyXRVpSpDmOaSIomU0DpGYhFUFalKiKiqaqSHkBapXo7D8/xXVNhKJSfPyJ5M8G4v03fuO/+rXBWpMs1RisbZGnOZqu4loOnWabOI4JkotI8fHIAy5KtF63BTJHsyJQIqZnFY1ejY2tOu2uiWM1eOXVa8xmc9KswrRdzs/m7D8eoVoGBZJSVCAVwpXPKgjRbIWX3+zT2TDIZIZQJFFUcrg/o9fdZeXPaG/WcF2DrMjxA588z+n3TTRdpd9rYNsKudRR9BqGoZDFPkJRCJKcx/tPsOyKmtljY3MNTVOZjAJMW8U2bUy1SZbH+EGENw9YjH02twZc2rvG3t7LfO2rf5OHjx/yu1//BgKL4XSJVHIqRRJEIYah4NZczoYTkmqFa6/z1774t9nd6PH+j77N/SdHfPuP36PExKm1sRwLPwo5OTvnZHjO86MTfnL3PpNlyioqqdW6vPjy62Sxz+HjH6PLgIaj4S3mSKHQ6XXRdA1vucBbzCikwLRdxufnLGYzdFWn0zBwTIWqLNFtF8Wqo5sWvZZGmnjkuaQqJb7nY9sWtuOiqjpoTb7+f3+Ho6Mjgrjk7HxOkkU4TYvToxVnRxHBIqfdsjHrAqOuIQHVVLFdg+ODc8JViGHVAcH6Wg/TVFDRiKKM1SpBUSwME9xOjdUyYLoMKHOJrUEcZ6iKiuPoOI5FnKSoqiAJc1BKZKUwmsxR9epCBP2UfncLP4zIs5I0ychkihSSLIvJ8pI0L6iKgnQVg5AXqVuKRHcVDFclDhPiNGU5j3nhWo+NtQ7zJay8hHa7QZlVdFodigo8f4lpGlimhaYJFLXEsFXiOEJTFFRFJY4yZKURBQXTcfixEO8/E5WCY9vs7A5YTJZMJxOQOYam4QUB3sGKdrdBu91AVU3CesDulTZFrpGEPo26yfqWQjZYcfjYQFMU1jbaKEZBre5ycuwhyjp723UODk7J8pLNjQHRKicML+a3ugpCz1m/5nByMCTOdKRQyXKNaFXQbOjcvLXBypN85qtXSdOcd75/wAsvbrIal8xmPifPI+68dpX59IxGu0aplZC7GHaG3nARVUXd7lJIwcw7QVYzWu3LxJWGnvqoqyaiUgliyfVbL5CnGSI64CQb86N33uP1NwSHh894+wff5Efvvs9Ld/p8/vOvcu/DBvuHJ7gdmzJNORnuc+9DQatT59rl19jt3safTvBXS3rrlzgNWvytv/052u0aeR6xnI1450d/wmI5o9FsMhxNWV/f4zNf+RvcvP4i1y/t0GmbnFoFZXTOeP4YDJNbt64x9yKW8wlZGmHXm9RafZIkokRHmHUMoXJ0dEZVZWzu7NLZ2kYzdTQVZBmRxEvKSsVyLBbTObZjU2/VoCyotdv86KfnvPuT+zS6DpouKXOFmmOQLGEyDKmZJptXNyjwGfT7pFWEVFw838Moa/RafU5XYwIvwDJVwnrEZDmn4doES49Wa4PSXvHqZy8TrCKipMcPvnGPoixQhIZh6FimRpmVIMC1DLI8p7/RwnJ10rQikxk1xaRCYNkm25s7nJ7PyLMluiUR4iKHQQiJLktQBRUqmlDQANXUybQM27VZzX3aLQergqIs0Z0M30+YTRYYGiQrjyzJWYgS07IwNA3NUEBINEXiOjroGt5SoywvnJbdDZfFOIDir9hGY1GW9AY96k2NThc+fPiEKFry6p1XOD1d4K9m2A2V4+czXn3hKmstm9FiitSh1eqiKhV7Vwa81z7AG4e896cZ/a06W5eajKdDrLrAtlSu3ryComos53PC6CIso9lxiLKA3b1tDo/HFKXKaBygYqOhYFoaKBqKppEnMadHsFp6hGFEf63BoK8Sv5+gGjZpotDqdfBDH02o6A0PiaRhKzgNBb2ChrHL9b0rjM9GjJ+vmC0nFGrG2eIEO1cZn88YTp7TttdoNJoo6oLZYsbh4XPu3LmKYQ5oNjvcvlNy/QWX1mCNa+MmqlJgVE2eHDzBdjVq2oBirnDoP0eYJrXmOo3eGr9wewOoPmIjLMmpc/OOwmo5Iwg89i6/you33+T2i7e4eXVAd5Dw7o9+mz/+1gP+zb/57yCtt/jd3/0nyCTm+o0r3Lv/iOlkhmo02L36Aj3LpMhzbmxeIs9CstTHsW0KxSbLK1ynAhkgREacJZSVwWLmIYsCzTQps4vxWZpaPHzwnE63xo2bG+imoMhz8kiw/2DIxpbJYMNldHoMpkKjaRIlOfPpGYZu0mgYDIcHKJaCLRQSP2VysiBIPerXrmPZNexmygu3X2Y6WnE8m3DjlQ2+X1VYhkaag6JDFMdYpk2eX/ATLMvCqRks/QDLNRGpQqFIwqjCcXS+96ffJUtKFE3gOg66riEUSVWAEApVklLlGaptUJQlRVJhtQ2yOKHKJGEQYKmC9bU17r23YjL2KIqCTGhIUYGpklIR+ysc2yFNE1KRoNgWtlGn3moznRyTIwmiDHQVxdBRs79EmrMQ4gDwgRIopJRvCiE6wD8G9rigL/3yn0d0zrKUn/74Ea5RIy0r2o0ev/g3PsPh8wVrGw3eurqH568gP2Y0nTDo32B+IsjKkk4n4e0frLh6s8PWJYOdXZfTo5TIqzjdH3Pp8jqPnz2h2Wvx+lsdSgl//EdT6p0205HHYr6ikiXvvX2I6ia4NZsqEYRJimEWmI5Jniv89L0Tet1N8gDSNGXvVpelH3Hl6iXWN1dMziKOn59T62hsXVGYj1NaDRNd1zg/yMmCAsUI2Z+OWC3A9wK69QaOZTNo1nm4/5g8sWjUutx68RLjsylhOaM7aFFV8PDBA+KVzyuv3eFLX/kqz5495B//1jtkSsjLd9bZWr/Ef/vrv82bn7lF163hHUeYWp1mvYZqdrHsLk7dwVQlfpSR5QVuvcUlu8HuzjWSMCSJF4gqxbVjNgePKeR3+ODRU1773AanU4vf+O/+e/7jv/sf8Xf/w/+U//Mf/S9IxEUDchVRiJIoWFKrbdJotdAoKdMMx9RQRUaj5mBqKWnoIWVKWZSkWUWSRoDKYhWiRxGdbhe7tc3ZLKHQQxp9A2EkXLt5meFwThqDZngMetsEi5DlcomqaRxagsu7W2SJhlXTOHg+YmNrQIGk7rocP52wvrFBt3+D9U2VB0/2eXR3xmqc4ScZsZ+zWj7CbtVQKphPZ7RaNo5pkqYZUlHJy5IyDjESiyor0ZyK6TgisxKqyiVLVSp0VFNBQUFWoGsqlqOznBUXTWRTR5cVeZGjmxbTZYCwFExHQ+aCXm0d1zGxlYr2bhffX2EVCqKoKKoSVWpUErIyp5AVuqGTJSnTqUcYplxWBJYtITUgzYkWMUIxCRbpxz7T/19VCl+WUk7/zPWvAt+SUv4DIcSvfnT9n/3rHi7Lik6zRhmpbF7axLZMuvUOY2vO6XiMZtZYnQ7Z3W2ytT1grb3DcBywf3TA3Z/6bO60mc88XnpxjWeHp2hOjkTiLROODlRMs3kRxzUZkacpssg5Oz/Hdg1UoTEdrkAaNE2TOMppNuqgVBQkZHnOPFzi1G2yIkKYLrasUSWSKFC5f3dIFCbsXO6zWHj4i5SasUHraslbL/8HfPd7/4zTgx9RZCb+aoltm2iGjiIlpYAwTzh+csJ06ZFVJSgKRwcLbFtHVXQ219eJ44DeWo3h8oAnX3/E2z/+U7741hf55Cu/hFOv8fXf+5/5A/8pUV6hSot0LhidjvEWHtWhxHEbNJptLNvBsus0Wy5oGnEaU2/UWfkempqSFyPGZwt+7ueb1PoxaVExnHrYz3S+8JUBN25s8Jv/wz/k+t6bDHrbFPGE3Z09To7PmJyfIDDRNRNVVRBlhiYqDENQFSmzyTmdpotUclRVJVhm5HmJamrMFx6BF6NrHy3zLKf8+P27LOIhX/7K51nrNaiqHD9acXo6o9Vt8snPvMLd+4+YxVMkJv4yoeyoXNq8SqHE1G+tsVx6DNp1giRicLmDqZVIReV0dM7aVg2zYeGNErY3dxlPpvh5SL3t8Ok3Ps/R6VPe/tH7hLFAqBJDSGotizBMSVcBrmkSLhNkUSCEglAuOAmqolIgoCpBVpwdz2m0DaJVCTnYLRXFtMjziCrOaLRruC2TJC2ZnCeQnLG93WZtx6ZSfW683Ob99zwSP8G1FOK0pERi2w6KFEhVQRMCV9PIi5wk86nkBWDIbhggdLKsoiz/chHvB8Cbf1YUhBCPgC9JKc+FEBvAd6SUN/9171jf6Mqf+/IdwjiiOXAp4gLH7NPsKoTpFKGllErOYiapMgXbUtBNm6tXLxEsPXS7oqgqZscLzuYpaxubrOY+oacQBjm9fgPdLlAUgyKNScIUKUuiPMDQXSxhMTlfsAwiur3uhT23TMnKBN2CmlO/KCdNgUwK3JrFcLSi329z7cUad25dIY1KPrj7gGBmkGYV169f5ej5AY8fPaNICxyngWFerL1mWYKuXESbKxosJgtGsxlZUV58f6oCicqg16Vu26ySc/6TX/0axwdzvvfDB1y7foX3f7BPu97kC299hUf7z6g1TRb+mPX6Bs+fHDAcz/DjmOnCQ9Mv0pUMRaA6Ki+9uk5r4DL3AtqdJp2exvq6w2IeEoVw/ZpDvwtnk5h+6yWuXW5xdHyIn8boyjbf/tZ7HD48omb0+dSd16nXa/zub/9fJHHA3tVrIHTqdZe6o1N3BaoqSZMUVdHQNQ3NssjSgqqIma8Sjo6OLqLT7Tpbuze59/AhT57uk2UFl6/usXdlnb0bu+yf3ufpT8948ZU9psspZ0c+QurUag0OTg7Zu7ROv9ni9s1PMZxNefT0Pm++fov7+w8wahUP3j1jc6fO5Rs9krDg2rUrGGbJ4dM5hthgvBri1HPyEHyv4O67z1DKClWV1EwDkITJhcFKSoHlGkynKxpti3a/jmHqKKZCGKZYukrox5ydhjTbKlevr3O2P8F1DIIkxa7r6KpBKgqKqqBmuWSeYDYJuPPaBo7bwGiEODWNH37v9EJo1YsFKFXTAI26aVBJQQVUeUFZxdRdA90UBGGMYdqUSUGVwuHBjLNh8P8/4v0jAXgOLLgAtf6PUsrfFEIspZStj+4LYPEvr//Mc/8q96Fec9746ldeQJiCvStrOFqb4fQM9JwiKRj06qBX6Lrg+MAniiNa7R6adDGqGkkZkbMgC0Magz281QJvFtBpdkjClDzTSZMKw1JJ0iW2bdDt1GjVeiwXS8bTEWGUIrSLxk+0DNBUG8O2kKIi8AI2Nrq4TRifR0wnE4Q0sWsmb7x1iW6nThyqPH54frHOapikWUSRFJydjVGkhqlpOM0aiiLJ0wzdMGnUG9RqNdI8xq2r1GsqTx4NOT3zEbLkK1/4LHWnySg4ZHAt5eH9I2qN+sW3YmUyPl7hDWOuX73JjSuX+Oa3/4iFHyCloNVuswp8kqxCVSSIijiM+JW/81m8+QrdMFn4CxAZN29exTIKNrabuEaN1XQOIsNtbtDvX+fo9E/YXW+AqrNcQrvZwnV13nnvMR/80ZyvffUXef7sEd/8xtdZRRHbW+sMOg1UVbI26OLW7IvEH6GQZjmrIEPVDGzHJM+UCz/LKqbd20S3bR49fBtv4TEceWRZQVZK8rJEESquW0PTCizbIkgTdE1hY32AEAqj2Qm6YvDZNz9Ds9Pn+Owh7Q2D+WJKGmf4QUa747K906MIdLqdHlG8IsoTPnjvGRudbTJrgW3YHD4NOD+eESw9XMdAkxWNmoUwTcK4wlt4bO91CcKK2WRKwzFxGg6qqyOR+POQPBcXSV8SEBW6qmJbOs2eSW3gMBt72DWd1JNohuTWC5c4PvbQqOj0eyTFnCSvCBcZpqWSJJJc5jRrdVZxgoKg5lqYpkMSpwgRYWg6/UGHOCw5PjgjXcToQiGrBPefT/7SNho/J6U8FUIMgD8UQjz8szellFKI//fitZTyN4HfBOj1GlKzU65feZHpKMfZ0Oi2G8y9JUkEaQTz0CNNYWe7x9l5ycn5Kf3WLkZN54WdF/jBD/+AWKqwHKMoBbYr6PR6RPacPC+YnVbkUcnelVtsbnaJwwmL5ZAwD9BrFbYokEKgGAp620ZUNVzT4Xw4otPq0Gw2yIuEQiasbV1m5fn4YczdD055841P88arn+Ds9H8jziLSTOLWm6SKz6uvvsjJ4TmBn5KnBfWWiW5eZBbopkCoFY5mM+iZvPHpdV7/9CW+8Vv3MIUDpcTQJZ+8/RaFPWT9SwM8f05V1vjh9x6hC5frN3c4OT7jT99++wIakmYM+j10VaKrgkoT5GmBYuig2Fxa2+Qgztm90ifN6wxPV0TTgu7lFpawKbKSKAtRDIeGDkv/AMuGOPVRxQDHNlE1lbNxhKbVmS0POTmfsXvlBp//6r/BwfNnmDo0HIvlcsaj+4/RNBXN0DAMi6ysSCqVjY0tWr0O+wePcWod2hs77OzucH6yT5VLLl+7TlY9x9E0zofnzP0MQ9NxbZMwkpx7C7KyAlmiofHJT71Io25RxQWqUPCCc87OT4hyizzLCaKIzcsN+t02ZVHR3tI53D/BcQVpVGLbgkQJyDyH0WxBs91koiwoK4VlmKApGmEacvNaB9fMaRkVhgK9nTVElZPGCVlasJovabQapGFBWQpsw6Qoc6oKkqwkK0r6Vxv4QYo/S1lf73FyNiOLYT71QCZEkaTRLYhjiTfPcW0VTdOQSoguVAxdoVmqTKKEtm6jqwWzYMX6eo+KFUk6YXtvg7ywuXfuo+QVDdv82Af6LywKUsrTj37HQojfAT4JjP5l/sNHnw9/LltaVpJbV25zfOAxHAa88cqX2N//CXoJk/MndFvr5KlGb83AtnMMu+Rqt0NNrRNHBrpxkevXMAVBFBBHJTduXMa0VLLcYTw8YWNjj9UqZD6Zcbz/FKFkVJQYlkWr20TTdGRpYmgOWk3lfHhKHIckic/N/mVmC4+4itB1gV1TGXkp2DBbJoRhwg/e/W3aG5JKcRmfp4R+TFWA1YD13TbD0wWhF+B7Jf2NLVAqah2bjbUmsVeShJKfvD3Gbl2Uk4eHzxjNpxcmpXqdL3/h82C0+P63nhBGBwTLDDSVwE+ZT+dYjkscRziqTZbnzBYrVCEwDEHDqSM0nczO+Z1/9CcoChw8mJPkBa7VQFcKqtjl9EGE3XBwOhus15p8+5+/jRAqb33+Bn7i0Gq0ScMZ995/zv37PuOTBTo2QmikmWDv2gvYhoZpquiWxvh8SBwExHFEkmUkeUGRSWxbYWtjwMlwwvl4wY7dYa3dZn1zh8P9x7QHa7j9JvVFHVezeeVTr3D/w0fsPz5AVpJVuEJRFUyhIFE4Gy34/g8fcv3qLp1BnUQmDE+HuDWb+XBFva/yuS++gOflLFYhoiiZTVb4K8n5yGcxDbl8rY9m6Hz49oIyT0mzCUtvhaYJUDXyoiIvSh4/O6bXbZBHGXqSMhp7SKlgGgZVJalbdcJlDAiqqgIpcQwViU6UZGR5RplVJKuS5TgmvpJi1eqMTsZEkUIYV2RFyf6zE3q9LkZZkYqQPBYMem2ipMSPYxwV6pZKURZs77g0Gx28icfP/WKbfq9DVHjUmy3Go4jZ0Ke0P751+i8kCkIIF1A+Cph1ga8B/znwdeDfB/7BR7+/++e9R1YSVbYYdG1ODt/n/Xe/z9Kfo9ZyXnptgMjhlVf6RLnCkyeH6CaomU0Uh0RKxD/75u+wtVnnyb1TGrUBrYbO2cmYej2g0+hgaxrT5TNm3oy13g66ZnByPKbRclFFxZNHRzhNE9PQcByd2XREITNKJPVei/2zJ7x442VOhid4fkgyXmKgklUFG5u73L37Hv2BQ2+tQRKlGHpJ4GWUVcF4scS2VTavNkj9GkdPTzk/2MdprTOdLwmClPVBH93UCEPJ6NwjjRXqrRZRkiCLCqHCt77/XWbzJbPZipKKggpNaORZSBRFGLqG69bJ8wyhVFQVIEviKGKZw+ufuE5jUGd1XpBXOaNxhmVLfO8c16njPyrJkoSGXefZ4T6GpaKi8eYrdzh/2EQRKmdqym/9zrfwVxH1FrQbHWzLRpYlk/NTkDmj6YIw8Hj1tTusb13i+PA5yXJFlObIShDFGW6jRpIWTMYeL736OsvFijKN0DSF2J8TZgHBNKHecjh+coxd0/jU125j1DUe/3Qfx7yI/BOaTiFLFKlw/lF0n23pXLu2QavVJAoSojTHSms8v79gtcjobbY5n48vxAyFNFZpNjokUUlNKWjVXNrtNv1LDq16j7vvP+AC6gCqohJk4J3PGXRr5HmBLnTKsqQSJXlVUVUVtqaSlhWlDkKoGLp+AXiRFQJYLdILHkcl8McZ6+vbyLRAFheNZlkVdFs9dGGTaRFloYCANElQFBXL1amKDENayFLSbtXZuO6Q+HNkpjIchvQ2dDR3Ra1lYdoWi6n/sc/1X7RSWAN+56JtgAb8H1LK3xNCvAP8lhD79QkKAAAgAElEQVTi7wCHwC//eS8xTJODo3N0Czav9kitmCzzaLcMxjMPUUluvV5gxAaJZ9Judzk9nxNGHld2d2k7NWazOUGWYhcJw9GSJE35+V/4HKeHI0I/Jsszbl65g+/79ActykJSlpL1tQFFIUnjmKjweDgZUeYx7d4FiUdRczrtGh9+eJdmq4uiSFSpoSgqZZHSdpv0mxrD0xPKvCTPoWF2UNyI8SRkOctw92psbjgsximt9hUefPiY5fQAq9bjh3/8Ho5l8sarr9LutKiKi2xGX4YUFCz9FV44R9c1ojS5EFBFx7YdBAp+HKEaBhKBlJKyLHFtgzSOL5p7lgG6ynAWkNMkjkO+8Pk3+eCD5xQYXN5WKVJJq7bFeDjiyYPHOE2bsoxZejHf+INvU2sKmraDvyppbzT4pV95hd6my73veYRLjTjyWUxHOJZ68Z9pNqVaZ+fSFczGOnbrCH/lkWUZqq7RqDfIKoXNncvcePkO997/kE6rQxLG3L13lxuvXkJ1LFbLkI29NUbDc/jpgqwseeNzLyNkzr2fPMI7D9AMnaAqsA3jAigiFJ4+GeG4PrdubZHIkjBOkZWCTBXWW5fZ3t1jMh5CrLP18jXOJj+9yMWMwLIuxGg+Kum1HNq9NrPZElXRAYkuQOZQa+hs72zz/NEI8upiAa4QRGmBaYFtCuJSJy0LZFWSlxecSNcwiLyLkXCrY6NrNovJnDKriOMYwxFIQ6XTaWIImzicsb7WxfdCqKqLiY5pkaIQJTnteoPxeM7zp8/52tcu85O7c072l9x6scnCyygqUBQFy/j4y0s/E9bpwVpD/r2/92VUQ2U48jg6HFMWOo22RlYU6Lqk3+8xPPaoiopERgzW+nRaLn64ZHg2ozvosJqWuDUNt25TJTr33z/i5GxErWkx2KqxPujimBYgadXXWK58ZgufNBJkeYahSWxHYNcdkiSlIOWFq7eIwpggSLh0ySTPK+q1NfrbGnc/OGH/UYhZzwmjGXVlg421bQ4m98hlTDDRyLOKstTQVZ1+v4njaMThisVyxtnpFNuyGGxuoSs2m5trVKXk8PCEQuZIUdJoNnEdF0UpKUTCw/sHrGYpURohFBBS4tgmRZGjaxphlCJFyXp3nThJMS2Fay9s0Fnvsf90n/k8YjL0odTI8pQoirEsFxAkSUSn00KIkvX1JtdvrqOrkqfPzrj1eod2u8F46DM5CcmXKoNGh9F4wpXLuyhCcOvFF9m5fBnFbJKXJbZtEfse88k5s+mU2XiIAK7fuo3u1InTDInO4emEr/+T/5XdjRbPT8e4HYdf+lufJVV8nn14hqU0ePP1T7O//5ROu8vR8pD5/AxDd0mDhOx0xWyyIBMqq7ggSSWabRAEEYqq8cLNPl/64mvklcZykfPk0TOW3oL1Tp9Bp093sI2iaZycHjAeT8iLHLfdxKopPHt6zNnBBKFKECClQiWh7qpcvrRBq9MnLQO2djtcudRmc2OTD97x+c43v81iOr44jFWF5ToYbo3zyZw4ySgKSd1V2L6yRaXk5ElCVYGpVJSVxDRcLm3d4nQ8RNHmFNJE1QRJEWIKFbveYuHP2Ri4lFFFEkviHJoudLq1i2hFYTEczylFgalq/N6/eP6xGo0/E96HX/+H/+Wv9S5Z5PqSVlMjLyW64bKYhuiVSx4L0jjFqbmMJj664mKKGo8fnLCclrh2g+m5z/mhhz8uaenbzM/muI0Gjm2jSIP5JGIyCQmTiEuXB8zmC4I4IoguRpR5WaFaGu11E2EHeH5CkRacHU9QhU2RwuMnx6wNrnK8P+fpgznnZzF5mpGnBatVRhJVLIIR3S0DoZScH82g0lEVFVlJkqRCSsHVy5exHY1r164zHU2Yjc6RgIIgzyqyJGY+nVCkBWWUEgUxstLII0kal6RFQVWV6IqCoogLcVAEcRyRVyXNTg9ZVRh6ha4r/Mq/9wtcumrjNCpu3rhNs10nDHxG4znNRo/bt1+l0xmQFznL1YooDBFVye2X1rl1u02nvUle+Fj1AtSKutvAPy+oKJkvlsRphAAOD4853H9EmQS0Ol1Uo85kNGL/8SOG50OqCtZ3LmM0u8R5xcH+c0JvSbfX4/GjD1Ep8MMYocC1613iMGN9s48Xx5ydDtnc7DBdLS5YlmnBJ165hTRVVkHO9PkJHcfGNjWgQCJw6y6aqvL8cIwXRcRJjKwuwlpXQcrSW1Gr17n34D7TxRzVkKTJCt0WVFqFadfxV0uoFNK8RMgKRUgkCkmUcGlznX/3l/8tDL1Gnmb0GtsXeRpGC01XmC49lkGEqhusViGx7zPo1nDrDUxTpdtqUGtpDM9mlKGg6TqsFiFlJum3t+h3d/ADH2/lgQpCgzzJyKOUoiqJwxTDKFmFEdN5iqpWBH7MaLwk8mKWC4+abWJqBllesb+//Fjeh58JUfhv/utf/7VPfeoOw+MJs1lEr7NLr9nD1BRarkl/0CRdqZwfLykryEOYjTwstcbLt17l7OSMLCtY325TMwwQJZN4Qrfv8NKtbTqtOp1Gk43NFrruYjltBDVm4xgE6IbEMkxatRaykJimg0JGWWYYjo5SKmRpyWg05sn+Axb+lCgqKUSOn51SKQlbexaaCaWa4PkrojkYpkA3TDTdQNUVNE0lSWOSKGKx8Dg+O2GVpvS327QHDrojUY0SRYWXbu/QW7dxOhW6kzEerxgPZ1AVKKqkZju4tRpZnqOpKmEYo+k2uzs7CARpskIRFZ/+zA2665IwmrK2bjM9N7j/4XPOz6bkmUK3s0ZVlYSBRxAG5FkGqCz9hKP9Ockw5vL6Fv31AQdnJ5SpxfxJxnIR0m40SdIEXYEwDAHBaHjG04cfEnhLdrZ3qBCcnY2I4wxN12j0Bjj11r9y7p0ePqMoMqos5vH+PqqusZx7XL96m/Z2DRWVm1dvs394j8VqQXfTJvByFGlz+GyKLCRCydG1OrPpAlNAu2ZSFQVJVmDYJppqcHgwotW0eeOztwjCkPOjIWUl0QwDfxUyWc5RTAXIeOm1q9g1ndloSSUgCyNMwyErcoqiRApACCxbcHLylA/ee4/VMuT5wTHTxQTVEJTSZefKOm984nVULecrP/8ai6WHklfoms5ge43Z1KfKCih1LENnFaSgdkiLHMNyeX74DCFTdFtHqBWqoVIWBZoEW6sxaHapKQ2c+gZ5ldJwDFTDIK2ASicuC6IiI4kyzJrD/tPZXx1R+Pt//7/4tcuX+qxWK2QmCL2UOF7S31Qxa4J33nlIkicUoqDRatBqmfQ3+mzu9pjMTsjSCq2m8vN//cs8efqAQss+AmBYjM/mHJ4cc/WFOrdfa1KQcXo6IstCHEen1W0SxwVFERAEKbNJwGy0Ik0L8jxHUQSObWI5gv+HujeNlS07z/OePU81j6fOfO48dt97u9ns5kw2RUkMRYkaLNlSjDiG4gAxYASCgzhAEiKKEguW4ySIYwQO4CCCJTiRrIGkrIEiJVIi2eO9t7vvfOa5Ts1Ve55WflQr8Q9DYQIlEAuoH3sXav3aa+31fet936fW0Vg530YtaCSZSqlSodqOSSKJer1IoaBzejJiNA7JRcLq+hI5JmmmoWkayGDYc/fl1HOJs4Dl823soo0XJqCqLK/MA0laiwtImk6Q+AhF4enOEYqVc3bmEnoJqi6TJAmWZWDoBpqmsbK8hsjA80d8/oc/zk//zKtcea7K8XBAHMVUnCL/9J9+nWdPDojj+ds0jmNmsxmj8ZAwCskFqKqGppmkcQz+jKPtPfIkR9WL2GqL7ftHlCtFLl5YQ0KAEEwnYyRF5fz5S8iqznQ8QZZyJDL2tndIwxhJVqg3WxiahchzDF0njmOEyMgyGA6HSJIgSQWz0YAPfeQV9naGTP0+zYUWk36EN1Kx7AqVYh1JtiBV8Sc+y+dWaKwusrt18L7dWMVUZYIwQNN1NN1gOJpQMB0s08C0dDRLxQtmnD9/Ac/LSSOJZn0FTYSsndvADV3IUo4Oh/hRRKlUpGA6KIpMFMYgBIvLdcqlFp2FDl/4iS+gGDlr6wU+/urz1OuLrG50mI57vPTyKotri2w+GxIEkEQJORkigWqlgqoZIMkUSyVq9Q5JliIpMTkhZkXFC2IkoRBnMbZlsbS4wnA4QVdlKvUas1GPtaUFTK3IpbVrzOKUNAoRiSASOWmac3ww+95xSRqGQpR3uXn7PDtPBpwenmE5OssbHVY31pi6KWk2z0LUJJlRt8/SaoWj7iFBLrF0foX9vU2+/SdvkssKt26vUKs4vPXmFsPwDNVS2Dv0cdOUVMiUmiqD7hAVDUMqoeoSlUaRfneEHIMQGr4vUFWHZq1KJjRkKWXtXJWDvZDUmweRkhpMeiYqGfs7IeWSQ7lSRi2EeLOM45OcNMoxVB3LksnynFxO0HUD015CUVPi1GMySdD0AmSCIIxYXl/j4KhPngtkucjJcZ+ljRYiTnGnAxYWC5zujwlmCbV6kSyFcrmO67nEccTiYpsb15dZ7jTZPRL4k5jlZRPXHRN4KasbHeIoodudzTMl5HnSEUjI7/cp5DzAVHPSXBAnMne/fZ/F1UVW11RKBYVaowRAvVZB5DGCHN+bYJoGV6/dRFFl8jRmMuyxsbFCKmukKQSzgN7pexwf7xK4PlmaUqlW0QyTF26/yJt336JoJmRxyB/85td57sUPUiyUUFWLh5MTLl2uYZpFTg5OyLMMzw1Y7JyjsVBHM1N2NrdJ+gMgo1q2KZVMjnozLMPBDXK+/odvUS5VieMYSc4QyIwGD0mjnPWNVfYOD5FFFX3/mDz3yYiotxr0zoYkvs/y0hIHJ2cICbI8ZzjwUNQJL35wmddf/x2ePOzy4Rev0nxxh/a1Ig93fF7+8Dl+61dfQ5YTPvKx5zg68nn9jTeotDQUIeNPx8iyhqbIqEZAknsMByMURabaATQb09RJw3COnctS3t16ALLM8dhHHD2lahd559EzojClYu3hJglCzhGKjCyDlX/3KPq/FDuFX/zFX/zirRu3OHjW5fTojGK5wI1r5xiN+liOzUK7huePkSWJLEsZjSacHg+p1db4yEc/gllISGKX/e0TaosFNMUnSX2CMEJVBbpq4I1iTk8SWs0mWewhMonRWYCplUgzH8vUcAyZUtkiCiFNJFRJQUUmCnNySWdre8hs5pKnoCgSSTxBlqW5A04ozCYxsiRRq9UxtBIikbAMHVVRkZQUSPDCAakUEocTZm6OnymUaxadBQVZiUgklTTLqZRkgihg0I8hE+R5xnQYYtmCGy81GPQiRKbg+T65kAiDhMCboUqC5XNFli9UuXt/j29/5wFkCivrJRRlgScPDmgtVQjCjOk4RtVN8jxDZDkiz9AkgaNEFNQUW5FQJea+f93AdUNG/TPWlptoyvztpUsQuDNG0wmdhRa+P6XfG1Aul8mzmDwXGKZJlqfIkiBOAmTg8GCfs+4JnjtlNBphWzad5RVMw0REI9bWmuiOiRcHxKFPpTml2z2hWKpQKuugTNndPuWsf8aP/9hPUCgt8KUv/T6yZjA+PqFRtpEV0HUNQ1GYeh6mUyBJQDd0SiWH0XiGqsi06zUUkZEnAVHgEUQuW093GZ35TKchSwsdRCqhyAJJgok7D1sNPJ8rF8/x7/97/xYfetnhzu02BXuBJC3wm7/2GopRYmff5df/t9e4frXDf/h3v4/DPZfTs5gciYnfRdEUwijl+Hj+bKVSTJRHyKrEeDjmJ3/mA2w+7GJkMOq6RLFA11UUQ0Uocydmo7bIeDamVivQWm0z9GcsNhvIhobuyNRLbQypwLOd4++d8uG//Plf+OJie4nRYMrVa89z66XLHOzvMotS9o72ubzRxFRU3r23hWObVMslyHRCPyD0ByRRQBon3HppjWpRonsU0u9P+OCLd6hodfr9AYZZQBEKB9t9th4NiIIcTZGxiyZJmjEazUDW0fUi4/GEnAxVMYnjnDyNUYiJkgBVBUnJieKYxoLKuUsOyysmSyslkixnPBoy7rlEkYdlOGiqisgFyBKDUR+RRmiSRBSphLlEpWpQK6msrzVQVJnd/T6DQQ9JzoiTmOlogmPZSJjzB9yW8GYJhVIByZgHs4hcgBJTrlvM3ICbt5dodqpIqoqiq0QhtDvLnA17fOCVVQIv4vhogO+mkGaUqwqVhoptyzhE1OSIgq6gKpBkggxBLiRkRUPRDHr9IUEUYpoGlmWQJDGFQpFGa5Fc1kHRGJyecXS4T7VaZTrzeXjvHlEYUa41MK0CvhviTucBtaqksLyyAUgE7gRFSShXingRSLmFU9ZQ7Rx/JjEbKzRaDnv7Ozx4cEx7oc7O5hb90YRU6DiagqTITLpnOJZOGERohoamzANMkBW8wMMpaThOGYSG7ZSJkoRcmmcdDIYuk3FImub4rs9sOiWX8vfDUxIs28SxbVTFoNmoYlkGDx+esrUdcnzisrNzzNb2kK29IW++sUPspfizgK9//QHvPTjk3t33uPrcGutrq+wfnmBUNAxNoWBoKLKON0sIw5RLV1ooqsJkGHOwNyXL5HnTM0qwDWUujkLBn3oYho5QZCYDn3qpzMb6hXmqU57Q788Y9Cb0h+73zqLw3/yjv//Fi5ca3H7pDo2FBns7D+kPg3ndp4g5PaiuYcgmj+8fYJcV8tSmXDLRVAlvErL55IRGpQSpTLPRRGQWb762x+mBT6m6wNibUS0WCf0pQk7RbBPNKSOpCkkakeUa5y48z2DYJc9GICXopkaa5JDJCCFjOwUUZDR5vtWejiI0SWX9XA3b0jjtzhgMcmQtR+QpllojzwUSEnmWgUjI0pxcmEhGGUOVEbmEl4DvJ0yGKUkEWRKBpDObhggpI0x8LNPAsS1UWcGwVaIg4/KFC1x6roiqKSiSiqGbTCZTvvCTt9E0h4M9n52tQ6yS4OzsmHEv5ehgSrFcmFOs4oQ8iyiUZOqtEquXOrzy0h2CkxFp4qNrCpmAfM5oRUiCommg6QpxkjGbeCiqCZKOXayhmkVk1UTWTdIc+icnRJHH0soKvd4Qz3ORZYlCqYyiKoS+PydApRntpUWCIGDr6RNC32d5YxGjZDMYTTAcH5Gp3LxxkfUrJl7YY3vzlE9+8mW82RhJLhCkOqoUcPnCOe588AXCNOdwc4dSwWHkR8yCjGqlQZblRFGEN0uRpZRywSDyp5RLBXzPp1I1ee65i1x/7ianpwPIMgxbJxMQ+AlhHOMFPkkckZFyctzlhTtXWFq9xu/+zutcvmqzcs6gVHHIM4npwMe0obZiceVmg+devM5LL79Aua4QRTmqajEbTykVLaIwRQPKpk4uMnr9kJPDCbKqMx5HSLKEyCVCL6ZasUliwXSYIIm5dmUyDMh8BTVV2d48ZnA2RDMlNEvBLBoc7o2+d3oKiqLSqLXZO3qPhXaRTIRcuNREkQ0GvTHbW11MJ0GSdRqtJrNRytp6k8iPSH2fxIv4zA/cwXW7VBs6Y7dHuWXwyrkW914fUq0WWVpPSAlpn+8giwp/+I2HKGpOKnxaCzb9oeDJw0eoeCwutgg9l/5ghGraxJ6MKgqMzjzSJMGwADVHlmWCUOdrXzvFD1I+8rFlFEXleG9Kq9PGHWXopkqUhLjBlEQkGHaZMNdQDQudCUXNZOiO8dHRDUGhIJNpJeIgYnjQwywbqI7MafcUSy+gqDqEKdViDZmEnSeHSJnO2emY0XDGzduLhGnKa9+6z6N3+5ycjNA0G83Qcacuvj9D1zSW1yosrzRYXDaJ0wxF0omnIXc+90Gifsab3/pjFDlH0eYqvTwXFEwdQzfpj8aksoxjG4RhgiwLxt6AqbuP5TjUW4tYpQYLSzFZNESRoNPpkOUZy0vL5FlCsVDgxp2XODrYZTIcolsm01mPIIhIk4jTkxN++m99ljBNePudx1RtiaOzBww9lzSRmUx8yDNUrcBpz6PsGLQXCmAkxEnOx3/wxzjePeb0dIdWp02cBgxDj3KxSpQm+HFImqecDScokkSrs0R/MOWv/fSnWFpco9lZ5XM/9Dn+wX/1D9jf3cRySpiGhh+mqLKCJCkossx0OmP/oIfrwuVrNWynymjUIwxy+r2QlXWb0XDI8lKLj37iAsglTs9GjPdjTqcHVJpVJm4RkeUUSwaD0xEFK6dTKXE2jRn3JsiKhmOqzNwQchlFUhiOAoyiTrFkUm3Zc7hOKGGbOsV6lWDUo6rYSJk8dwUr3nc/H/8y7BR+4Rf+iy/eerGBaTpMRwmKJCNETL87wbQKhK7EtJ+xuzkkdjOGZ2MURcfQcwpFh9ZKh+Zyke7JhNksJYkkbt+6TqNRxHJC7r55zMalKoatoegaR8djskRQLyV84PY1pv2Ax/e3mc18ZFVB0sH3PQIvQlUEmj6vJQUyyDKqJiHJ8xxGN0yQVdhYr9BpWli2RvcwIo5SojjFKtjEIgIZ/MiDLAMh0CSBH83IMp9GuYQkYkxdQ6CgCJ1uz6dYKVCplZFlizTJ0OQc09TIUoE7CdHtCQurFpZhIhKFhdUyn/78ecY9D80sECU5SVhisXMOTbXRNY3ZbIpTsPjgh6+SM+Xi5QqvfuYOuexRKEiEszGHuxOSVCZN5xM+y3IkFLI8J0wTNN3AUkySOEUIQatep9loUKvW0TWdUsGkWS3gWBpr6xtoukahWKTVbpOlCYcH+/S6J8SRT6lWod5qIYTK6eEx42EfzVCZjAO8cEK5IehPT5CyiHb7IiX9OfpdjyRM0LU605lGFIOphzQXNOwC3L/3lC//2q+jGQbNzgpnBzss1G0sOWU4c2l3lpABTdUIk4wkTfnwyx+l2VygXHJYXi5hFyzyNOfCxXPIAg72D1AVsJ0isiSDmB83dxo1jo+OWVh1uHbjJvsHh3S7MUcnLk5ZQjcCCjWHatnim1/dxI9SHj/c4t7bmwRBgB/MyDII/BlS6mOqBVTNIYhiFEmAkCnWdHonc8q2rqnzZymeJz5XWgXK1QKGapBlBuOZy9ngBFmaJ4NniWA0nLF6bo3tze73Tvnwj//xP/ziT/30K2RC4vzaFRAWXhBz8dwiJUfGsQsEswBVFRhmlSuXV9nZ3OTic20+/Iklllcsnj07ZDQN6A9cVENHwad76DMaR0wmUCsscv3KAiJJ2H16iqpITKczDne7NKrzhGjTqTKazRgPXEzHQTU0fDcmiBN8z0eSZTRdJ4kyBCpRmlGsGCy2HToLJjvPDuj3QiZ9lyQRbJzbIIx9zIJJGPuQCqI4RzN1shxMvUClVcYqOYg8p1yo8GizS7fnkaURaZrhTTw0CYqlAoEbc7h7TKVaYWV1kd2tCff+9JC7b+xw55U7vPjKBfZ3uhhGib3dMTtPx3QW1pnOBkSRSxh685j6KMcy4fs+c41G0yBOZ8ikyKlG4Knsbg7I05g0TcmRSIUMkkomyRiaQatWo92sUSkVWV5ocP3yBgvNGrqc4U9HjM6OONl7hhe6XLh8nTSKCIMpuqpwdHTEe/ffZTIeM+j3GPX76IaJYVp4sym6rmJZJpXqAqQqqyvLVKsWUaCAKHHWG/H663fJSSk2NYYD8L0j6s0CSSLz+p+8x87jp9QXZZbP1+mc7+DOxoxPxpRLDkVdYzIYoJs2mRAkSUaczMsoL5jx2c/9IHtbB5y7soAfjpEVlevPb3DSHXJ6eIRhGnhhRJ4Lyo5D0TJRkJiMR+zsbJIlMqenLpqpUC0nrK4W0VQVu+QwmyV8/Q/uYRQkWgs2x8cepqEzPQkpl5tESc6wNyX0PQy7gMhVBuMhspgbzLI4J8nzeQNVUeex85pEf88lTnSCyMPSLaIgJg/nlG3bNnjxlTssrjZ549tPvqtF4S+FzLlUdMQLty9RKpsoioZjWyR5QBT5OOWUS9da9M9Cjo5mNNsVTEPj+NkRlqXyV/76yzx+fIYiTLaPTsgS0Iyc55+7hogdonTCd765Q8FoUK54JHHI8mqHb771Bm4kSKfz7DxZlghTwdnZlCyCYtVEUTOIchQDQECiINBRZQvTLjFxXSo1HdNJKVo5n/vh5/j6V5/x9JGLU65g2wqWZSFJEod7z8hSmUi1MQwFWZiYSsLqooPtFKhWazx5fMR37j6iYFkIAWQ54cylUEpZu3QdWdLZ3dpmcaVNLqB/MsTQEq7eaPP5n3yVe/cekwUa3/rTTb71p1sU7ALtdo3xeITr+vOsvyxDQkaKI1olmaWFwvzcPcmRMh0/zBG6ROwnRFlOEicA6JoCikIYxpQslYsrCywutDA0lTzPCIIQAezuHxElCYury1iFEtVShUm/z8nRMe2FBk65xttvvUOWzZOMyTOarRbLG5fQdBMhcqIkBCFhqCrVhkV71eHx3j7bT/ZZ7iyztb3D4nqb05MAFYOXP3yJB/d3eHT/AeVikZu3zlNpVqjXWzzZeoCSzHjn63fJw4x6vUwicvqzGNmp0p+6CBnCMEaWBT/6o59gY73Ntdt1apUC5XKJ0Vjn4bsn/E//5Ffwp9Hcb+GF8zBUOWE8cPmpv/E8pWaRw80p5CpH3UPOn2tSLZVwXZn9/hHLK02SQGY8mBIEHm6QYNsqUSyIgwQkidHAx++5FBwTFA0/iMnf7+fk2fwINY5iarUSzU6byXhClkSMxh7tdo04jAmjEKeoUWuU2NjYIIiGnA0O+NrvnX7vEKJyAb4nCP0QWQ1wnJRi0SFLEnTV5OKFi2jqMWEAG6sNPN+nePkKR8cHPHg4oVhapWSHtDsmIkvpDae89tp9XvnQK1ys3UBJHHZ3QibREa22Tnd4QrNeoYLGTHdBEsxcDxmJO7eW2X92ih+FyJKFIMcwVUoVg2AakcZgmCF5kmOrGomfIzJYqFb5w99/zDSM5mEurkcQR0TdHEWWEYlMEETITkbgqiDFdNaLCDFk6qa8+fou/bMZ1WKF0bCPaavU23WoqqRRwtnJCUJSySSFe/e2yOOEW1db/EZs+jwAACAASURBVMhPfQSpEHF2sIUhG2RFnaMTD1VVCZKQvYMu5JBmOUL8md8vx7FVVDKGZxN0zUDVNHIpRFdVXD8iiCBKczKyuZRaqARhgq7IWKbB1v4h959uIXJBmmUIJIq2xY0rFwl9l8PDI0bTZzTrNWqlMoGf8PjRNrdeKLK4tMj25jaKkNE1DYEEAjzPZdDrYpg6pXKZLIPe2RRdlllo1nn2ZJfZNCLy4NE7x8RByMULa9z9zg5vv/51zl9e4cKl86iazbNHmxRvV/jxz/8sdlmiXPhf+YNf/QrDqUujUqRVthjFMbauMvVDdF0jS3Kee9mhXatzdHjKcJAznSn8xq99iyxReeVjN/idX/9j3CkIRWI8C8klgSqrvP7NQ3RHZe3CAheuV3FaKU4RBCGn+zPKThF/lhCFkOOw/eyQUlGnWDBAiTAKEouLda7caLP7pM/e4wEFM0cVObMowTQN4hTyPMY0NYYjl+k0QJbBcAxkSWF4NsHQdHRVI8tkJtMQWU6o1Up4vvNdz8e/FOXDL/3S3//ilStL5BnIuQx5ShzMCMOAYT/i2aMpvdOEPKqwvzWh143ZfXpMf9hn48IyUeLzdHPA2obOcOpx994uumIym/aZTSGYFbh3710uXriAH4fcf7jFbBYjqQqKLBBSgh8l2AUDBRlLMTGNMuNxQOgnTKYZ47HH8nKHs8EYSVbRVIFuSei6xajnkyMxGqU4dgnD0ZH0BLss88GXrjAeT1BMmYnnYqo6ZdvGMBIMK8Y0C7z17X32d7qkWUQSJOiawuJiBauYkKUha+tLHO0fMx16VKtVXnhpGVmRuHCzBbJAV0pIUplRb0itYXFyPOb4cIIsawiRzb8IBBmWAqpIKas5bQNsTUZWZVRJIIA8E8giR9dUdE1ByDJRBnkOuciQydFVBT/JCDKBYZhzglSpxMsfeInrV29imRary0u0mk2Oun2SOEIVKXGc4fs+yysdRJZg20VWzl+k2V4iyzJ2d55xfHjAsDdgOpkSBj6pyNl5uofnz4+Vj4779AY9qnWdRr3F5pNnqCLjzkdu8unPfJiN9SU2LtdoLTv0+2O2Np9Qr67y/J3P8JVf/zUkkZBkMU65giRk4nCGkDUkWSKOMr7vs3coFsA0K/z+b2/zja++y2c/+0E+9pGXGQwDTFtweHiGquikAlRVwTAVkiTl1e+7QyL5iDwDDM5OxziOztnxGE12GIxDxv0x5bpDqTQPd601quimQp4Jllba3Lx5lYsXNtjd7DIdTTDUOUouSzNMXUNV5DnhPBfkuUDTNNR8vpMTCMI4plIvoCAY98ecHneRMVldXeONNza/d3oK/+1//4tf/PG/eg0/VEljgaZLFCoagpxqxSSNXRxbxZ+NmQwHdA9O0GUNd+Lz6MGQ8UlG3VllOjVI/Tbn186zsbZEuWxy6cIHONjv8/rdb2CqIYZWZDidYNkapYKFpukoisB1I3RdIU1lyqZDqVGlYDpMJj6qkZKSMBhMkWUdWVURUkC16RAEOf44YToKUHIN26gQRjG6IUEKn/vs53j26DEiypBVHUU1ME2V6zcXSEP41h8ek4Q5tm2hqypxFCKREQYJo5MpcpYy8VxWLywiKbCwqPLJH+xQb2WE4YxUypm6Y9IoQdc1hCIzHHoM+x6+FyDEXDCUZwmGSKmpOSVdUDdlDA0USUIROaYmYaoC01BQFYk8T/GiDC+McXQVWWTYuoImwSwIycR8kxkEKSKDVr3K8tIyU9cl8COWFtr8zE//JDdvXOfJoyekSYBh6Hj+jGq1zKUrV2g22+iWMy898pwsy/A8n1wIZn6AO5kRhAFJluCNQjS9QCYSzp9bJBj7HGzvUqmUcMo1VlaXGE1mzNyQ0SggGJlcv/oc05nH17/6Vd575y5f+Il/m0fvPCTxh7ipiqFpmFIM0vt9E0Xh8Ts7XL25zmuv7XB2dsYPfPYqceixvn6OK9eL3HnpOu/cO+b0tIthzvMMgiAiiROuP7/C4kqde+/ssbvdxXcFW08HLK3UsCyLJEu4cvEi0/EYSUqIM5DiOZ06iFwGXZ933n3McfeMPAdZl+l2p2iyhKKriDRHUUBRVSRlboUWyBiaiqZpJEmGLCtMZj6ymnP9+SVM02LzySH7W3364+9Op/CXoqewtFQT//F//mG6Byp7O0MCL8GdRQgE7Y5Np9Ngdb3E4wcHvPTyGnff2OHhO33uvHwO1dQ5OT7lwds7GFaFYJZx7eolyi2JK9depHc6pnd6RJqZvPDBdZ7tvQWawcl+l35vQK1WxJv5yKZBEuYc7w8oODalUoEk1BgMhkhWhDtNkFSdRtvCMnQWFx3qdZM3/qSHOwbI6CwWidOEs1OPJE65ev0CzXaR0fSM4dDH81MqJYv+0CMng1jGG3tEYYxlmqiyIIwjZE0iCjzIchYW65z1XbI85crzLW5/rIY3ifnYhxbYWG3wy7/yANUwCTyFg82Iz3z2Dt3BGU8eHvCNP9hkNktwHAlDk6nqMjY+qZ8hxSmmrWNZKlmSI8sKsiqT5oI0EwhZ4XAYoRkORVvGD1PSLEMS0GrUAJX+cMbG+iJVR8MNU3aPBkgytOoNAnfGy688zwu3b/L44VNm0wl37z9GVWFxqUOrvYCQNLa2d5h5PmtrGyBrnJ2cMRkOGE/HxGlKmgt0XSPPEmxbZ2V9iZ29HRZXirz6/S9Tqizxre884jvffofljTpJFFAu2HzuBz9JpWKxe/Rt0rjK/SebnO/cYnIQ8LV/+S8o1stkhoMejRFSTiRpjCJIhWB1rUPnXBW9GFGzipwd+wR+ynQSomgm797fQhIZyBIIlThPcaceFy+2OHetyf139rFNgzwTNJs6qi6RZyrlsokq6whJYTYb4BRsRj2XxJVYOd/hsHsM7+9cTa2EbQgc0+a9148IwxjLtslFjh+EoCooqkYcJu+b4rS5PF0WGLqJH0V89JNXWbtUpuDIvPbNbb7ylcf/3/YUJEm6zJzt8Gefc8B/BlSAnwV679//T4QQv/PnjaVpEsPTlGvX1njxpRtsbu7S63oUSmVUNWY0HnA2lJh6GdXGEu3FiD/6xmPUwhVG4zNC4bFxY5HhYMr6xQqqfsb20YzDsyGbD59ycuryiU99iKO9Jk/enVKpGAS+hOslROmQ9XMNnr53DLFFo1OmpCl0u2NGo5xiUSfHoLlUIIhCJEWQaQGprLC97SPLCsWqSRDPqNQVOgtNjpe6dE8DZrOIwSikUFIwzDkFaRTEoChEWYKqqJglC8VQkXOJIAlAFcjK3FGZ5jlbW6d85NUPUSiOqDdN3InKyuISurzKt994i/MXTU4OJXJV8KGXG9y6UeTdJwe8cOsWBV3nX33lAa/+4DXcqc905HHzToPd+yPCYcjk9BgtSjAMHUmbLwhzc5IgS1IMSeAYGnnsEYUJkZDQJXCkhE6jyAvnF6nVK1hkrJ1bY/tswq/8+lfZPdijUnJ4++4jev0JceCzsrbMYa/PresX6Sy08HyP46M+e3u7SIqCoWm0F1dYWFzAKthMHrrkIiUXAj8IcUwNJZPpn4z48MdvUVlVOBgesWhIvPLxZS5esnn9Wwfs7A8Ixzm/9eVvMuj1+fyP3+LJ3gFxJBHJB2yfnKDWanOwiiQzE/PErVyAZSiEImNz84SzwZQ8jVBzGc3IaHfqVKoqnh9Sqzj0zoZohoKsCjShUKoW2NsbECQBnaW5cGnSi1hfWMcPfWbpFNsyMRSZsZuiafYcPS/nIAuOdocsrS8zHHVZ7CwwHIWQu3zo4zd4/N4pWiIjieT9ODsb1w9JogjTUFAUjSia93XyNEdTBY5h8/tfeptrz7f5K3/tI/ydv/OzfOUrP/ddze3/14uCEOIJcAtAkiQFOAJ+A/gbwD8SQvzSdztWHMdIUZFGtc3Um+E4Ce2bVUqFGm7Qo9ko8OjBmEbbIJMDdrZ73Hz+MuvrDdpugYOTPTqtIn/0JwHnry7x5Nkh5XqV8axHa73C2pU6R8fP6J32kTOdOPCotBxUVSIMA/b3RzhFG8VQ6DRaXGnV+Y3Db1Es2ZQbRbxoQpwESGlGHmpUGkX2nviEnkyj3iDyckpOgXZrEc/3uPVSjUqpyje/0aN7AO4kQ1Ul6vUSspzOVWpSjpATRCpQdAnLsjDzMv2jLmqWopkKYSwo1U30Qsy5K5fJ0h6b+2fYlkcqSRi2ynQGd26dp1DMkSSZneNt6k2To9NTcnJ+7u/+O9x/923W1hqYNztsb/VIzCJKs8Dqgkk+neD3Q7zAR9VkLEOfK/6CDBSVUeDRcAxKZvq+DFhm52zIyWDGhZWI0egMRVEJ/ICPfv9nqHTW+M1/+RVG4zG6ZTGazDjY2+Phsx0k1eCdR5u063MI7cydkIQJsiZxsLcPkszS6gaaYXDh8iV2nz1l7LkoqkwSxRSaTVrtBXSlybTXI8hcxlaPKPY5Pj3hQ68u80M/cpP9nQnf+MZ9rILGP/9f3qKgmzhFjV0/wC4vUGrmjA8PKIgBJUPDj0MkzSHMI7IMwjjCPfDZWGvyAz/0Km76Lt//A9eQSLGUFU6OMv7ef/Q/kycxsiwjZSALCV3XySKZ69fPcffuLpouWD23xO9+/Y9ZXqkzG3m4wqXcbHJyHGKoZVw3Q9Nk1CygfzrBKqtcu36O3/vaW8i+RRiXWbvW4unbZ2RRgqUrBFGMpStkQiKMIgxdw9B1wjgBZKa+j6mqtJoNnj4c8c/+xzf4kR+xvuu5/Rd1+vAqsCWE2Hs/mu3/0UdRFPSSxDvvvkuQTvnUq8+RpxK90yGG4dOsl3j8uI9RUugN93BKOUXFQbdkZCVHmcbsHp/hlBRyJabfG1EsKxg6OHaFYBCg6FAsxAy7I3pHKRvnP07Rctjaf4JIJXJ1ris6PB6R+gk3bl7gsDshM30uX2uxe7+PkHXKpQrJLKdWLZIV4eigS6VUQ1EN9k5OqLVL+JHE8cMddN3BMCCYyliWg1XM5oh2d4CpSURZSJ4L6h0D04mIhWDpSgV/DFEsWLtgceFKBVnNee/+Jp3OAi+/cB6nFjCc7CLyKoM+9E+69HozSmWDUrnASqdCyTbxvT57uwfYVoXeyZDB0y7FqkWhlhP7gllgotQN6isKK2jsvbOD6wXkSGi2SZhIzPyMYkFicaGKBAwnHmd+yDiBu5uHVEwNRc2pV8o8eP1bfOJHPs+rn/hP+drv/BG//L9/mWmcoWs6kReQJxmJELzx9gNuP38Nz5uhajpJlmPaBrPpCH9axbaLlFoN+t1j0jRBNS3a7QVqtTqWpSIiFVNpYxclwnjGZBZydppBPEVab6BZ8IWf+ASaNvepiCxhZ+eYh+/so+Q2mRQx8T1szSbJBIYiSOIxBc1m6ifIkkShbLJ/dMab37nPZ364w/azU+LAZLEzodJoUV+ocLx7hqJKCHLyPEOWZQZDn3/xy29gFxSu3WjyxjtvQZ7hzXxqLZ0LlzqoSoWdnQnNlk6pXCIIXKJMoPgRmZLQ7Y0gBTf2ODnapFZ2WL+6wON7B+hBgqxKc4q0AEPT8YMAXdcxdI0oipH0Ofw4911UQ2Hv+JD/7n/459/1fPyLWhR+CvjVf+36b0uS9NeBN4Gf+/OQcQAIldFsTKtW5fbNDdzZGaZV5Nr1dWTpkC99aQdVE5xb7xD6PorusH90RLuboSgheztTVFlHTjWOnvkkaUKns8pkFDHq++iyTbWuY1qC5y82OD6Y8Fu//ds0W1UMU6AbCjM/xCoYhL5PdzjAsVRKZZP2goU39plMZ9TbNbrTQ86fXyOYZiSxi6llGIZKsVqgs2zS75+yvw2TsUcaSuS5gW5CkoYkYxl/FlOpN8lJUbIi0/GM8TgiDpL3SUMZrishqxLXrq2wsCixutZgoWMT+g5JnnL/4Xt0FlWCYIDvqRwfjKiUGzhWnbff2uSB2uXWnWUSkXBwfMTS6iJuFjKajHGjAFlKaTZaaJJAVjLGicvCyhWuaA0evP2A2B+hSMZcRanl+H7C1nRCraCy0mlS0GUGXsbEz4klGVNVeXx4Ord6/9aXuXxljVeeW0PLf4B3nh1wMvN58HgbXc2Qk5Te2Ofp5h6ddpuD4wFZ6JMkMbNxyrujt1ldW2d14wLLG+dpL6VUa1VkRSFPUtIkJAgDUmEQDR2CfEBrzabZLNOqmrSWJhyfTtk9PuXGtesULImDwxOMisLtl1cpFStESci/+u2Unbd2WSjr2JqCIilIUUDRLqKqCW4QYVoFvvPGA7pnPf7m3/wCtXaCUlDYP+2zfmmJ/Z0Bcfp/kZeyLEfTVMI4xvdSPFdD0TJsu0ClXGY2idh+L6GxlHHh0iL18gKH3TNeuHmLpcYlJjOPRw9fYzrJiGcaMlCyUsDh0dN9rt5eYXIyIJwlZLlgMvUoFUusrCxwfNonigN0XUKWBLmskecScRyhqxqqYTCahd/VZP6LYEnqwOeBv/f+rX8C/DxzOMzPA/8Q+Hf/Df/7P2Ew5ZJF6LssXN7g9HjG6eAM3VFYX4zxRiOms5RXP30Jw4DTbsbRTkitZmCYKnt7HlKuceHiAt1DePTeHpKm0e96uF7A4moVx7R5++1NOotNqrUStXIRW4eDwwFxKEjCEBGn9I5CDMegZJkEQcTVWy00SePB02Nu3DlHGM24/dI1skTlWX/Ku/dOqRaLBH6PIMi4emWZS5eWUeWEe3cf48chk35KpW6jqCb97pQ0ClF0HVMvIHKwdAvP9xBpShpEhH5MbUHnUz/0PF/9vfcwH1W48yIc7hboLBgUWxKS0PjD3+3Rbpa5dHWBki3huh6aCq26TrVZ4unWCbKh4ZRNev1TllcXqdRsnry7iaabzKY+pZJFIkfcuHiR6TMPx2mjWgWS6ZRI0Ylij6pjs77RwlYTKkWT3ukJsiy4tN7AC3OQdYolG89NeHdnlyjL8JOEzumY7UfbTPoDXrxzm95xl6PxhFkUoasqT/eOuFMqk0Qelq4TxQmKptGst0mShN7JEc2lVYI4IRc57niGosi40wme62IYOvVmk2hSQqppLC5BmI8YjnWq9QJLS0uUHYnZNCTLc0oO6DUHQ87ZaHbYvbXCpJfg9Yc4xnxXmU0SGnULN9HxwghVhnq9wtHJhF/4r/8Zt2+f58KFNY77+4RpTGe5xMn+CEkWSJKCyJlrLpAQucp7b+9z5Xqb5Ss255bX8ROd7e1HLGgSz19toZsdHu9YHHePKJcM1KLMzAsYP97DrkjcvLNIc7HAt77yEEnPccM+wtCRUhUlSijYDroq6DSKOMUST55sIUsCTZUIw4yEHFXTkJiXX9/1nP4LIET9MPAfCCE+82/4bR34shDixp83RqNpiR//0ee5vLbG9skhZtlhoV1hPIkQvkR5UcIPxigI6rUa+wfHFIoFag3B3uGMWmWB3umYp499Bv0eiqpgahaSlGOVDLIkQcpVbt5cobagEUYxtq2zvTlm2kvp98/IkDk78XFKUCobGJZMLikcbA1J4wSj4AA5S8slGq0m79494XB7wOLyAhuXLYKRAUKhuWhSrWrYhsPe6Rb+wEYIi8l0RhSljMYukiSQZFBQUCWVXCRIsoIma8RRyO0PdGgsmkxGIc+eDbh8YY0rVzo83drDKCg0OyqTgQeKiozBwdExgW/guzGVsoKumXR7Y2o1B0mK51oCo4gf+uw/OWPmhxRLBrphYhdKdBwTMcrJhcrdd++jO2XGgSCLAr7/0x/lyrXzjE428WdzWvd4NEaWUqqVCkcHfeI44ODwjDQTKLJEwTZplgtUnSr3H26SZhGrqxu0Vtb43T95m0QIBDkKGZ9+5RbueIakaVjFIk6pSpZm5JKMqhl4M5def0Cv20WW5joKwfzINMtTzl+4gCap2FWZD336Erk+YefoMXcu3kCSTNzUI/B8jg4GqIaGomroeoFhP+focMBbf3oPaeKyWLUxJIVRmOLLBsMwRKCSpzkoEkEYkyeCOI358KfOsbJRQ9Ec/vj37nPwdIhpmQgVwjhFEjKKKpGlMkKE/K2//UlOexPu3d1kbX0BTZKo2DalVglJ1Xjz7Qd84IUN/ADyRGFrc5fP/tgqZafNl758j5LV4qw3wJ2OiCKJJIwxFYPu0RTb0Lh6fpmxG7Gzd4SiGUiyQJH0OYQG8OMUWVE57Q7+f1M0/lX+tdLhzyAw719+AXjv/24AWVLpLCwThRmtZp3jk4RhpjKaRXj+CKtUp91osbs7pteLiPOINJDpVFcwJOaBFBOfOIkpFE1mkxChgF020I0ENAVdsej3JwxGKl44Y6HRIpoKVtaaGHbK080BugVXLreptxwEOeORYK2zRrd7ijtOGI4DBicpD9++h6ZbaCY010IaCwWeHPp0zzJct8i4oXL7g4vs/6mHqljkuQtCIop8FE0lykICd4oiy1i6ihznpKmCWiyg2wq9SU6Yw+ryKu16zlvf2eRgr8vzL65h2Sa9gymKUkJTwYtjwigC/g/q3jPGljS97/vVW7nq5NR9Oqcb5oa5E3ZmODvc2cC1aHIZxGBrZZGGYAs2BEOGAQOSYDgsCFmyIcKWCfuTZFOwCdkSLNLMJLiZu7M7Mzvh3rl3bu4cTk51Kid/ONeGYBjCGLaB3Qb6Q1cDhQZOv0+9T73P//eziaMYz9E5HY5QCz6f+fHn8T2Xb377Hnnu0O2OkEWJYrlGGE5pNkqsVNtMTjrIqo4s4Oat12nuXKbVaDHpPaVWN4gCnzA3yfUGJUtFL1RwRl2QcprNInlioquC05Meg+mceRAymbvUix6GrjKdR5yenAAZBQ3cVICskSYxjWaLZrVILssEYUaeZ0wdh5njYFk2hmFh6TpkCUEYkgsVoerkCMJM5t69+9y4doksrnD7uxe88uZVfuKNG5w8vcfUvWAyihdAlWFKrVykWF/h9OSczdUdNM2iVF3mg3fexpnOmM9cChLkYUK7WGIcZ4RBQhInlIsWkhA4fsQ73z2mXKhRXwn58S9c5xvxXc4Px1i6gqkJ8lyBLEMoEvM5fONPjrn58jaGqeP4IUok8P2U2JApmgaVcoFMytjcaGCaNhfnR5w+9bGve1y/0eTkJMQqSmSJRaGkk6YRQs5JlZzB6YyT0z4ImXazjBdnOHOfnAhJEli6iq7pzD3vEy/o/1c7hWcCmGNgJ8/z6bNr/xOLU4mchYb+3/0XisT/7dfyciX/5S8/z/baErZtUq5bPH5wjO+ArGooRoYbzdB0jSSJWF1p8t73HzOeJCytFclISZKMKIAwiFCFhl1UkGSFektDVTNmwxhdlhGSyYOHHWo1g2q9ilUJUfKUKMpZXlvm3odH9PsZlbrJq69eoVy06fRmfP2P3qVYtVndWsZzpzjjMbmW4bkBAovdnWXee2tGFgnsMgg9Yntzl/sPz9ANGU1PuTgb4sxSkDOCKMBPQ8wsRYplUHR0y0LIOYqh8Qtf+tcIoyEf3vs2N65dZtgdc3o8wi6WcWcBpi6zum3i+REHT/pcfm6L884YEoVMyjjpHlMu6fzUX3iFhw8u6PQG+K5P0axgKQU0VccwDEwvxA8liu09TNtAJsOyNEolDTmP8JwhsmqQ5jJB4OPMJiTRHCn2UaQMkacIWcIwTbyZT3804+SsT78/JE1SasXCghMYJaiKzDRMCHMFIRRySdCsF9lYbVIs2Vh6gZPTC856AybTOUtLLXZ2d/Fcn/6gz6A/IEkFKaDKCqqukkQpWRby4os3abeXaG802N3dYzA+Z+ge0HNOqFZNsiRlubXBwcGMu3cfcOPKNYSokAG/89t/xMqewWB/TGkWI2cpqVBwhYobQ5RKBHGEqmmkeUoY5gRRwosvL/OX/tIrTPwJDx/2+fafPmE8DJEUmTRdxM2RFlmFesPgS7/4Ct3RhOGJQxIluMxZXa0s2rgsoloosrvVZDr1eHynz63PrCHnKR/cuyD2M9xZiOuGoErEgUO5VCGXNE4eXaAnGr4fUK0UkWWFieMRxilJklCwLGQhuLt//v//TiHPcxeo/1+u/er/0/tEYUzoJPieQpzFePGY9e02gQdH+weYhk4cOuhKhd31LaQs5pXXrvGnX/seGSVCzyQhRgLCxMEoCyr1KqPphOE4YHlFZnldpW5ukBHRH3g8d3MJs+QhJKha61iFKnbBxrJ97n3kkSYVHn48QUl6zNw51SWT7Z0G3cE5y+tFdq7s4jgTHnzQpTuY8NIra1y6UuTseEK1qVAq1DjvnyHh4UxDZEUw8+agyqiqhio00mRhN0qzHLKU+XjM3rUN1td2ScKQpdoqvf6Qx0eHqKmgtVricH9MvVagYGkkqYwbhJQaJcbTMXNvRqmaMBtnVKwGEPFnf/YxliV4883rHD0+I410wrmCVSiTxBKZUaW90abRbpJEU8K5g2mAnAUk4Zw0mKGKxby9noWYxYzpDAZjF10TuFOXbq9HJkHJLrC7s84Lt3YZT+YcHXfpdPro6uIfNo8yknSOmiSkaUSYCwb9kCSO0BSF3e0t+oM+zmyOLGRm0wmdzhnLS6usrK6SpBnT4RhSiYwcKc/QDRVF1kmzFE0vQGIRzOaMjkaMxzG1dov1loIbR4xnfVRDYntvhwdHx5jqjPOjPlGYMh1HbNxo8fCtLnaWowY+mvCRdQtHKJAL8ixbnJRoMpph8t7bJ4g859/597+IWVDIc5Wv/d590iTHzzKeJe0xDJXhcM6jB/u8/PpNTvffIw4jMkni/HzGZOxQqdjkQUhBCgmijPHQZdLNeO6lCsajLnIsIVdMMjIiL0PRbDwnZHXbovLpdfonU/JTiX5/TqNZplwu4fo+aRQuyGGq9onX4w/FmPPf+Tv/+VduXXsBP4hYXrNZ32wRxYI0dVnf0RkMYqplA8NU+NZbt5HNACcIuHRdZXNHwrBlMhEwG8fUijUSL1+ALpMAU5cwVJ0bLzaYjEK8JOLWrR3iZEwYRBTtIpXivSqy7AAAIABJREFUBmleo9+ZkUYJkuqSZQpe4qCqGp/9/KcQIkW3Z+xt1gg8eLTfwfVDtnbrWJZNqSAYj0LW94podkav69DrevjBiCQJmPTmkEmoskwW5MgSaLlEnkEaLkJHrhtSreksL1U5Od3nG9/5A+qtElEomM48ps4AoYAfz1F06PSGdHojvDjk/GLEfO6ze2WFNI5Zqm2ys7PJYDRGzRpsb26wtbkBmAShSZIUkSSDxlKdopEQTU+QJag3VpGygMTroQgPVc0IfJ8nD57y8OEB+4cdbn/4mIODMwa9EZIkY1omSAu69Nn5Bf3eGE1RqVaLFAoGqqJi6AYJ6TNbkYypK9imQuSHKEImiFKc+RyAwI9ByAsbFymlShlVNYnjCNdzF2/Vs5wkTcjTBCFJtJotipUyk5mDFyTcvHkDXTGRfI080CgVVAyjRJwaxFHA/v0D6lWbKM05Or5AiiUsS0EyDYbjgEzO0VMJEYXYukyhXGL+bA4giVPSLEPRZI4Ox/zge09otCrotqDfdRn23WdMkAwQZGkCQiaMAlorGikKui7Q5YX1q2BbpE6OKhl0umMaS0X8MCHFAUVi/+GYck2jUNKJopD2kkWlUCMMU3R9kb8o1S12r7aZuC737p+SRBGVooksCwxTIwxjBlPvRyf78Pf/y1/7ymffuIykRNy9e0Bn2CNKYsqVnP5gzke3Z5TLDe7cO2J5ZZNhV+bp4x6SJHAcj/Mzhzy1CCYhrfYSW+sbpGlAmoWMxzHFgoaum4ymDjevr5DmJwgUTKXKoJ9ycHrCex/cXsRWfYkHD885ObsgzeDKtT3CKCbNHGpVnYJV4sGTAZ2uR+TneG5MuVQgTn3Ozqc8fjyitqwTRAF5oFOsyARxsvAHOhmhm+COPRLPR8qlhb7OX+i9imWT7b0i41kHhEDWJFw/QtFikizGCwO82AMl4crVCiW7hOeF+F6OlOWUqypSkhM5CboGn37tJ+gPxjx3uc3FRYded4Cpb5BlZaQkYqWuYuYTwnkPw7KxChVC94Jpb5/QneE6HnM3ZH//nPfffsD5eZ/hcIbnR8RIZCkEcx9VkykUbSzTplAsECYxJ6ddnj45pTcYE4UxkgSmbZBLMHV9/ChGyFApWgsXpqYvqEaqRpItwC6KKqFIOZVKBc0w0DQN3/MJI58ciJIMXVMXiLdCkUKhiCIUut0Bh4cHrK0t0e30mEw8CGooeYXAz7n1Yps3PrtBdzAil3SePDgjTWA+yfkP/uabOKnP2cQjzxV0IaMmIWoek0kKfpSiqRKQILHA/ycBPLh7gusmlGsVZlOXwIuQkMmynFxIKJLAm4ZEEYxnDoKU63vbpKHAH8aITCeMcyQ1Q5Lg/Njn0cc9lttNVtbK+G7wTBeosLOxRrlQQS1EBGEEkaBebDMdOrSXmrz5468yd2KOj87RNI0sEyiqTHf0yRDvPxRF4Tf/+//uK5//3CWWtxIyJUW1Qk4uOoyGKb2LjLPDEM3MURWQpYxcRBzvD5hP4OIson+RkYYG2xttMiXCDxcYdc2Ai/6cXneOoQgaLZk0jvB8g6XadfwQpt4UTVO5unuFKIoZjKfkyFSKS/jzlLPuObJIcRwf01zl6fE5w6GPJqsgBQhVpteb0u/7zGYgpQXOD+foqoKSlxhPHHzfZ9xfjKjmIicF4iglSTPiOEaTFVxnTnujxZVrK6iWCnJKEqhMp1NMWyVJIwQ6WZqiZgrzgaDXmeLPAxRJpmBk1Mo2y6s1gmjCzsYN0kTn0dM7xMmUOExIPZutzRew9JSqGUI4JA2dZwWhRBKOGXePiMOYMIkJw4zQTUnDDCEy8jxBEzqapoIEigp5kqJpEnbJotsdo+gKSytVcqQFVFaCMImRVZlM1QhVlUQ2iXOVTJJQ5ZRMkpg5zmIHYSjYtoUz9wEBWb5os2QZ0zbJMnCdObkkkIW8CA4JmdbSEsVymTAIOTo84eDJU7LQo1kvc+fjAx483Cf3ffY2thieRqSRQbXeRkElT1UOnh6RJLC+usSNm7fo9saYZYuDkx5JImHKAsuQCXMJL4yoVksUCxZZkpKJFCF0emdz4iSmVKngTFxkIRCytDiuJEPKBaEf8tKrGxi6gTMGUoVZb4ykSlQqdZaaFeZjnzjMmAynpFFKoaFRqZlkiYQqLDo9j/F8yPZenZdurWEWDA6PD1F1Fdsq4/lTPve5zyKExNNHJ9jFEqqqcd7/ZIzGH4qi8Gu/9ne/ohghesmgvqSQpTH9QUS3G1ApWyRpQqczJ4pTDp52GPYcGtUCsiSwiwLdUOmcDwijOWGY0xuM6I+nFKwC61sNTFuhXKySxyq+X2Nt5TmaS0Um81N6FwOKRZMkixEiIM9V4khdLOA8wpt7zGYOnp/SWmrhzTyG3RnDyZCVrQKuG5OFGu4kfNYeWJALStUCplykWqvgzX1G/RmGbpOmC8ZfLmUkUfp/YsGyLKO9VaDSMjg7HiLBIjaLgq6DrSjYlsBULerFEo1aDWcaEoUp9YZOqVxkMJ5SLJm8/uovoBsN3v3oq5BmSLmNpZTQJZud7VUS55zxxRPCcE5ruYZp6aSRiz+b8MxfRy6pBGGK67hUyqWF9EUIcjLCwCfLM+Q8QyhiwT+wbfqDIbkOWy+sUl5u0OmFrO61+JW//ku0dleorEKp1uDrX7tPa83mpS/s4aUS5foCnJNEIYE3Y7nVRFFVfM9FCBnHdYmTiGqltohpVypIQOB7yLKCIIMso1SpkZBzcnSEH/h0eyNKtsXLL93k+PSCi7M+FVtndWUZS2sQezZRbKDJFrVimVJR48P3jzH1Io1KgVa9xvbeKocXLkGeErsuDVMBCTw/Jc1ybNtCluSFt1NXcWch0/EcRZEXaHxJoCsyiiJjWRq2ZlMpFlHRGHZmxOmMl17fYandxvVCPD+hUCqytbfGoDdBGAlrO0WWl5aYjnIMQ5DJCWN3Rr8zRlM0yi2T5RWVWzcvoVspmlXma3/yFt3T4WLoK0uZzX0mzo9Q+/Drv/5rX7l6s0YUCxRFkMUSw36ChEBRUwxdZjJ2CGJBfalAFkPsx4RRil0okEQxkBPGKWke0WgU0BSZLFYYDyfkaUKe2EzHCZ4bMBidI6SEaK5SKlnE+ZwodNDMhFZbQ8gBCT5RsCAWa5ZMGEIS+8S+D5JEsWJQsZpMeyHjkY9lF2mtW9jlFFUsiDmKBJpQSSKJ0cBBQiJK0me8xxxJCCQpR5ZlhKZw5XobJI8wjKjXy/iBg0yBcJZCnFEuVbErOrqls7pcYOL4+HMXqySztbeNrS/x3M7rnJ+e8tWv/zbLayXiEIqGTRboPP/8C3izczr7d7ENQaVWQVZk8jQiCV3iNEXWFycNs2nIw/v7dM67mLoGuYRpmZTKRTRVJooCsjQHOQMyTNNCtzWcWOXp2ZRCtcrdByfU1iwqZZUwdbl8aZXROOE7X73LynqBX/orryPR5LjTwa6U2b12Gb2k4AxGbLTbuL5DFCUoqkwcRoz6Q5I0olwuUCgVCcOQNAmQyEmimGq1QrFSZTqZMhlPyCTB3PVRkohXbl1FL9icnffp9/vEYUiW+KytraLbZXIhWKq1qNbrnJ6eoRkaw9GQTDhsX1nGtMsYRovBoEvL0qjZgqnrEzybzVAWFh0QOVma48URYZwQJylBEBOEEWmcQJpDIrFzpc7KhsHSapNCqUKeafi+y8wJOTs9pdnS8aYJpi7TXK7ROZky7M6oVupEQUYwSyiqNp2zEe4Uzo9jvvOtx5wd9hCyxoO7J3jzgBdeq7O8YYOscnz8I6SN+0f/8L/6yl/7qy+zs71ESk7guoTznFRKGUyHjMZz1rdrJPEiay+pCt2ez2wUE4UpQlVw5y6mJVAkhSROUTKDKI5xHZfAzeh2h+imgm1J5KnEdBKgajrbGxuIRKFzfkbomTijBG/usVRpsdRoUqgXUfMM2zboXQxxJh5L7VWmE484hELZYOY6OH6AZUOrZWMVDYZdHwmFi5Mxvp+hKjoZkGZAnpIlKbK8eHqkaY5dVGm1bPLMYGe3jWmapJJEHKdMJwFjZ0KOTC5H9IZTTo67+GGAO/MolSwatWX6XQc3PkQxO6y2lrj33inNxgrdkzlXLt1gqd3i4Yffp1CyKNfr5IhFG5PlhAnEqcbUjTg+vuD+3UfMZg5R6CPLIFSFOErQVBXT1KiXy9gFE0PXEQJkTeasP6W4XsasaIz7Ic2lOuubJZ4enTI4iuiOZvz5995nPkjRLMFgNCbyQlQjxKoL4jhh47kVhKWQhtButpiNRuiKyvr6KrqhI8sKVrEEEpiWScEqIEkKK6trSJqMqhvoukGepNiWRRxFaLKCZet87ic+y0p7mU53wO27j3nr++8SeHNsS0OVNXqdCxQpp9VsY5olDLOEoZm014pEUcTu6nVsu8LB+TlSktAum6RRSBTnWEWbJE6I4hRdVcniGEPX0BQZIQRIEmmW4wc+k7lDoarxwq0dVpfarK5e4uDpE9xgRJBAkkoMxlM8JyKaz9i62kDSfKp1i/F0gOd53Lq+w+c+c4M4jnj8pEt/7DCZTdjdWGEwiLj9/j4/8/Of4sVXdnCCkKX1Mj/43tGPDuI9Q1AqWwRhhI7Gp1+/xYNSnz/52rtcvbWMpkbs70+Y+xGTsUOjXcIoqAhJIQgi4n6CXdS4en2FQddlMvCZhz2q1SKqqiy8ibnEbBpx9bk9zEJAnM4I4il//v1DFAkaS1sIxeXWtat8ePuM77/7hG5vxuZmjcRPkAshjVaRKFIIXA9bU1hZrdIZdcnJKFgCQ9VJY0GaJSBlJGnC2kaZJ4/6CKEAMoWSTRQoJCIkSUJIUuIwwTQWNuKDo1Pmjoc/09i43ECWzyhWTOoNA2c+QRUW1zauoCpVfucP/oBbL6+y1q7x7lv7pLKDHyvsFje5OB9TqZTxxjAfB4xHQ85PQLerJJLM3JXIpQVtiDwnDGMkSYFE4XT/mDgISJP0mcwme6Zoz7AMnSgOFjFgXWOpUcWPi0ymE0r1EiuXijSXLfoXAZOBw8lhDGhUygW0skS1XiHLZkhSzsZGnSgS+B2dcXdMq9Yki112r1/hd3/rO+y0m1y/vkccZiimgaYZZEIlyEDkAl23oSRh2T6aYaIZGnmSUioVqd16HkM3mE3HKAKKzRWmc4+rN69jWTbr7X1Gsyn3Hjzk4uSc5fVVWu11Htx5jyQMQDPR5EUBnCY1WuU9JhOH2uoyV40X+fj9u7hDh6KhPyOFeShCQZYi0iRCkWWQBLmQkAEhL06aYlkgZMGff/Mx13au8m/8ys/x9OABP/aZa7zzfoZ3PKWqVFhbqjKfSXz49lu01mvsP/VpL2vcurnLeOhyfjzkm98fk0syG5eWefLkKV9683X2P/b449/9Bq+9skOz1eSr33xAoWBSqYhPvB5/KIpCmmSkQmEezYnShLOuz/fv3CdFJ5gUaW1J1Ms53fOE5dUy01GKMw+olguIXCOYR5DIHD6YIAsgl5CRmU18MlRW12ucnV0QpyqjyQDheVRrBpVqyFKrxgc/OGV+OKLRKvCd9z9GVQSOO8EyJYTiUG9VyZOcJ4+PKdeXUW2Jl196jiCZMJ2ZrCwvE6cJrpeiqwqhl9FqV5GSnGvPtdl/fE6lXOf5a1e58/AekR9QsArEqYrIcmTFI85kHDfHtjSsoowXTMjiBopQ6Z11efP150myKnfv9WgVbFy3y6/+WzcYT1JOHsYICRrLRfwg5MG9Hi/e2EEWCndvP+UXfuEVnt494uDeMYVKHQWNx08OUHWVna01Tg+PGIwmrGxtUi+XWW7V6HY6CCknTjPGs4VROpMkgskMWcoJgsVRousFmLaBbljsvbpGbdskjVKm7gi0lEpd4uzJlOFwztOjlCxKUZScXEBCglKwaK/VmEwFpmjTO3Pw5gNuvLiD47vY1QZiFhFHMUEWkuUZaSIQKByfHpEmCbpp0jCWiKKc8UUHz3UwLZPNzS3MgoWQBI7r4bo+H3x4h5s3ry04kgePeOnmc4S5hiQrBGlOe32X0J/jTqdIWYgzmtK9OKNcKLN95RJGuUh56RqhHPH044/pXPgU5QxD5Lio1Eo2YZLiOB5hmpEJQZ6DLMlkpIvQGwJZaPyz336Ld+88YnOnRq8zp6iXMC0Zs1hGZDlBNCYMUr79h0+xNMF6sczdzgHttRrFusH+YY+djS2WVpdZWirgzWS+9Y2PeOGFTX72yzd5fP+cul2iVLexy/InXo8/FO3DP/gHf/8rO3t14lygmSof3T1mOA2pVUtYqsJ4HBH6Gp4bkaaLFFia5qytGaRBTBxLRGFMFi/Iw4ahoeoyii5TqtYXT/c4plg28LwxfpyQk9CubeDMUhwnYK1Z5vy8xw/e38d1FYQksbZaAQGDoUfkZfzkF19mfcXm5//ia1imzXjcQ1Ndrl5eQVE0ZrMMKVVYX94gCGc0WhoXJwOev/QZVleWOT4/Jc0z/LlHEocIVaAaBoZpkGYR49GUol4jilw2rhTwvZTV5ippMqdcFVxcTFjbNLh6rUx7XWfQcfjzrz9BV5ZA9jE1haJZRNNlZFWgGBpn5ydcu7rBwXv3mU2m1NvreLMZZ6cnKAJalRIP7z/ADwPmjoMicsolG1lI6IaKF0R4YUySSQRxvJDkpjkSMkEYIiugqSqBFGOsmARxSB6nlEomkZsxnDrYFR3NyCGHs6Mp87HHpWu7lFdsppMJ1UqTvc1PEYYxp2cn7D84YOtyGx+fyrK9sGyngiwHWdbwvJCzkxPG4xGz2YS5M6fZaCBkjbOTU4b9Ho4zYT6ZMhoNiMKI2XTGbDJFyiTeeettdjbahPMZp6dnWLaNXbaplU1ODw7Ispxao8b69gbLSytkUUhOjDebkc5nbK9scuOF1zHKFpIhMZl5BFMPQ1oMoSHEM4p3vtgFqhoZC1SalEMugRCC2XzG6XGfs+MxSqaRkeHNXIqaSafbp9PtIOUKW1t1FM2gP3QYzyPu33tEwSiQJiaO51Aul/nozjn/2z97H8vI2H2uzjxKODjsEngezjxA12XeffvwR6d9QIJBz0HTLeahy8Vxn7JpMh+7pGZGvVUlCD28aUi5VCRPEpqlCs4owHNSsjih3izjDCbs3lgjlWUuugO2t7fQVZtOZ0Q4CukNfFq1EhcXIwKvjojHZFFOrzfFnYSEacDKioUijyFQuffBOZVWAaSU4XhKGKV86uXLuLMcRdZZWVonixe/EzJYRoYkZIJ8QOA6NC6t8fhOj4+Ov8mgf06z1SCIEyRZkMUQzjzUskyUJRRLJRQlBS2hWm9hagauMubs7IIXr1xGNYpUqhHlWp/O+YiStcyN527hjMu8884Rqp5SLhYY9WdYNQMnSLjz0W00TTDqzvG9mEvPv8BFp0Ma+KRxhCLli+NC3ST3XKbDMbHv0WxVsWwb3wuQ4hRVaARJTJ7nxGmKKkkIQgoljZWVNo8PT9m8VadYNjg9GtJubxAGAY4bEqQSfuQSzV0svYJqgWFZTAYe/Z7Jqzcu404zHu2/j2XFzD2PTJJ4fPKUOJLQNYGCIBi4KLnM1AmQhELgTsmzDIA4jjjcf8T25avsXt7lwUc+nj+n0xmgaSru3ENC4kkUcunKJRSh8Pu//6f823/tL9P4+GO+9fXvEgudKIkolyuMhyNOj55iWDYr7RVWN3fwPI84SdF1laOTMzbUIp978ad44+abPHnyIQ8f3eNbX/0OwgkxyhaZiLF0myiKSfMEVZVxvQhZURBZhpAlCpZFFMYEQcTJ+Rm75TZrS3Wm0ymj+ZRyvYIzPOOVF94kTBK+9+E7+I5DuVjGEA0+3j/k+OyYb/3pY0ajmPayzi9/+V/l+PiYycAlSVRu3rxJr3/KZBp/4uX4Q1EUkjRCMSWOjvqsrDbY3tkgDnLKZYV2e41uv0u/26VSLeEFEYqmE8wDRiOPRqNGrawwnc0Rao3HT2cYBRndKHL0pE+hMCeMPDRNI88ywnmElABRjuOO6J473Lha59r1VR4eHVEsrfLxh09x/BGllkKhKBj25myu1yhWVH5w+4ipNydP4Lnda5Ts53hycIcgDhGpxo3rVdzZmE4o6J7POTkecnI4RJZz4pNjVN1AUnWiNCGXM5zpCNnQKZabVBoKQRKQkuJ7sLlTxJYzPnV5G8dVODzz+ePfe4wsxXjuIZefu8ZkFCDLKd2Ow+baKu22wWjqksgZqZdSUIoEM8FrX/gCJ50BcegtPBCuz06hxNwPcP2AIIzww5AoSQmjANu20DUNyzZwgxgpXczxy2mOrAjq9QLNRhHH9fH9iMZqnfnUxTBkFDnibNRnMJyjC0GhIlNcqjIdJJRKReZaxmw6R5daxImLO5sTxh7+QMYdJ2RKxvO3XuDp/QvGZ2CIjFgWxCMXQY4/myPyFNKEJIIkkxiNZugnx2zv7VFtVAlOPYQm40Ux2dxFUxQ0VeXg8ISdzQ1G4zm/+Zv/K7/yK38RKUn5R//wn+AJCbNQxi4WKFcrRFHG/QePOLvosra+QbFawbZsyvUmKDKnpwc4oympH/JTX3iTN15/iX/6T/+Ijz96hG2YpHmOQAIJdE2QRRJxEqOIxa5H1wxiP0KogjjLuffhOUd2n3LZRNdklttLLK03OOk/ZO7kJN6cN56/yfruZf75732X/cddPC8lSxehvPqyzvHBU6Yjj1K9wufffJXxtE8ulZAV/xOvxx+K9uE3fuPXv/L8SxsYloKmShzs95g4Eb6f0usOee8Hd9jcqBOGCXku8P0Mx/OJogDDVFEMHT9KUWTIQ0Gl3KRZW+aLn/8iIleoVmq0l1fJE4WCVqZklxcx7EqFy1dWqZR0fC/Bd2we3h6j5iucnAxptRsIV6dsN6mv6vRmIz786Cm7W5d48rCHLFIMc2GU1pE4O56S5zmKJFFtacSBxA/ePqJUNLBNhSzPkIREHEUkcYwkUhRJplhWuP5yFVmVqNRNRkOHfmeMZclsbhbwMpdAHmFVIopVm8a6TqGpYhdLbK9vs7ne4NGTfQbjOYWKiqHoqKpBs1phuVBBN2xQDe7d/ohKo8ZkMFi8T9jdYTIe0+31ySWJOF5AQOMkJU9imvU6GTlxmiAATUgIKaVUMqg3K7huyEWvj1IwKa41USSZa5dWGY6nTKcBibvI9q+urDIcRKho1GoFBp0JSq6yudtANn0qTZMMjVK1Qed8wN7WFk/udel2x6h6RIZAN1soWUivOyYlI0kW481ZnhNnGaqsEgU+BdumWm/gOHOiyEOSBEmak2QZ0kKDg+d5FApF+sMJB0+ecuPmVZ6/dZWzx0/pzkPmrkcGGIZBtdHC9wKC0GNjYxMhKxw/vMP4dJ96SaZctpm7Pk/uPWGt0eRnf+4n2dq7xL27j4niyeLvimNUWaZSWsx7JFlKkqWEYYAkgByEJBaqewSenxB5CeOeQxDETCdDKjUJKRYU7Arf+N67fHTnKaQhdknm0rVNihUNXRUYhkFv0Ofa8xu0GzaymLGxsUGpYPCHf3D7R4jmvFbJP/8ze3RPfTZWaxhmlelsjmFmjIYu/ZGPMxuiahp+kNOoW5SLJrouc3I0xnNSFF0lFREF26BUNKmaJoqloCkacZjR7TmMxgFpvoBdFgtFVpZsxoMxl64v8fqn36DfnfLtt98GNeczn77MeWdE5KV4/oSynWBKazz8eIqfTlB0G2c6Z3WjQR4ldHsB66slKs0qgbcYBPLnOX/w+3cwLBUpl0jiEPIMWVHJshQUCXce8ctffonPfeEm33nnMS+/fI2Pbj/hcL9DpWiytlZnPJlx8HRKfzzFsAVJnCOQ2d3Zpddz6XfO+cUv3eCtHzxC1ossNSx26+vcffcRXiKzd3kPVcl45+33efHqDvsnR6yvrVMpFTk8PeXs5BiRJwRhxNQNiVIwVYXd7TVMXaE76OK5PgVLp9lskKQ5FxcdvCgllhRu/vhV5LJMFoBmLd7YR35KFmfIqmAwdIm9lNALqTY1+h2XtZUG5xcTfvpn3+C923fpHPVot3a4f/eQYiFnZXMVsyxoLOkc3Hd48mjCG5+7QcqAD775AH/ooOoaSbgIwiV5jiJkTNPg8tXL6JbF4cE53U4XSZJIcwkhZHJJwlAUFFlCNXSuXNojGI9JE5cv/+ov8b/849/i4PACq1IjFQrFgs3W5StIikGWpIRhSOQ5eEHMeDLAyqFeL6AJhb2dNnqxwjiSqSxvYZsGH935Ad/59p9z3rlYSG3znEqhAELB9X0EYiHTkRWkfFGYsyxDUWTSfCHwMXWNLJUIYx9FaFh6ytb2EpmSk6QxplJAkTWySML1Zyi6INMkLl1eRgoUhFAplev817/xT350DFGzWUTvVGI2jHgwu0DWekydOZouqJbLzMaLpF3kpczdiDhImegJsZSiGWDVDUIvAT8lV1P6J2MiI6S8pNHpOSiyTSalhJmLlAmiAE4m55TLl3DChPfeP2Y2VlB0iZVmi+H4gvfefsx0JCPJMdvbdUx0anWTF15P0Gybg32X3oWEogbMvYjVjQKdXg/ZkpDSFLtU4c4HTxBCQpYESZaSZ/nCxJRlkC1yD4IcSc8pFEuILOKi/zFRmGLKZfbWd1hqy7jzMaZeoqiAokVkhs/+vRFnhzNuvXiDxnKd//m33+GFl67y4QdP+ck3fx4jVxDWGHyPVnuZPArY3t6ivlSjudomjX3CKGRltY2hSMwnI846F6giQ1c0yAWj8Zjd7VVMzcDSDarVCnN3zmQ8I5cEo/GEVz//GksraxwfnlFrLVGrq0yn/gIJRkAwT2k2KrjzAGO5xKs/tkS3d0GutLh995D981NqhSW6scudD++T5hlb6+usXSkRBiHOSMEJfJZWJMpmkQ/3n2C0VfJAI/djbFMmDhN0AUgZUeQzGAwoVWq0lpp4nkcQBOiyQEjiWY4lIUkWR8YXnQtarWXiqcw3/+zeYH8DAAAgAElEQVT7/Hv/4d/g7/6nfw8v8DEbTVSzwMXZBYqqUq2UmY2G+J5PgopulYCEnhMhpQ6aqfBCvUqzbtCZHvLxY4dpf8Te1hqXt1foDwYcnHU57Q0plStkSYqigm3phGGKpED6LKeQJAmqkEmynMD3EaqMJClc3qtz/aVtLjpd/Chi3vXJlQBTT6lWl2isWFhFm8dPTgiiENOUyPMSf/zV737i9fhDURTIckYnUyQUfD1eWHySlPZGkyhKiMKcPM4X02PSQk9mlwoMRkNWqy3yGI76faQkx51EVCoWVlHHmSYYuoZh5UynDoqkIusCsgiBwmg45PLODYSsMJudc+PyJYbjDoauMR4FbG+t0h+c8/jeOZquYegJSysq1aaJooZ8+jNXcZ0pjw+HeL5DY7lKsaJgqjpnZxMOngxQVIUsScnTGF3TFgUBiUzkSFKOZhpI0QYHj2G99RIFK8YrnXJ2cIFeCbGrBqvrLeorI7Jok9kkpbm0ykd2Dz/wKJdrVGuX+MIXPs37793ll770WczY4uh8RkrG5sYqQsrRbI1r1/YYdDtEoUOahti2jSokWq0GpqbQ7/VRpQDTUjF0k3qzThKHLDcbxGmKG/q48znzIGDmJeSKhrZU4KNHh1xerdHalBn2PZrVOo2lEu+8e4/WmsrqapMszqlXdUr1hGJ9m48fn7N7bYW7HxzjDGOkLGJjt0gmdPw84t7dcwpmi/FkiKYHNJZlWtsRo3dGlMuCS1/Y4/F3HlE1S/hRxGQ8wjLsRTZiPCCNE0qVCmvrbTonZ7S3NnFmc86PT8hEhqIsrFB+EKKaNk3LprVUQdLL/PW/9Tf5j/7Gf0xdGTFzA3rdPgXb5OaN59F1C98PmU0GJEmCLGSsUgEhVA46E2bex+ysNdFUmaqus/bCDc47Y/YffkyjVGFvvc3+yQVPj08ZkqMIgWUoqJJECmSZIMsThBDkEmRkaKpOmufkecCbn38Zu1ZcwG0LVd76zruYUkqYLZQFBTRC32FrfYXDp0dYho0sYmI3/MTL8RO1D5Ik/Q/AzwC9/wOtJklSjYX3YYsFTOVfz/N8LC1wzv8N8NOAB/zVPM/f/5fdf2O9kf/YK9s8fdInyFNkTYY4I1NihC7jjmLyTCLOEyzLxDYtZCWmYhWolXUODy/IZQurKBMEOUmYkMUBtXIRYRsUKyaaPmc4dMniHFmBbj9iuVnn1U89x87GGxydHLB/9C5plDEZO6imRqPeZG3L5M57j5/p5qvMpxJ+DLauUm82UHTBd9/5EHfucOXaOrVSm97ZGM8dc+f750SpRJpEGKpGliUkabJ4YacI4iCj3FL5y3/lpzk6HBDHM3RNQ9VKjAYB159fo7WSIlSBpps44xhLbZAEFv/8d36XNM24dOkaqpD4N7/806h5xtN7j/jDr36f096Q3e1N0igk8OZcvrKHaen8ye//CbIsIeU5L754C0WkzOcOcRQxn86I04RypbL4YIREMHeI4ojj8w5e4JMlME9yXDfk5itbrL78AqOL3uJNepqRSyGGESJLEHoy1bpCEEasrWxwcn6Grimkicb+01N0pcp0NmM689hab7Kz0+DgqIdttxEipmC5NOp1PnzvjOUVnWIrRdFCMreJaaxSsjP2336KkkC/10O3THTDIIhSVKNAHMdIskKSZZj2Yjz++OgEq1DAtEyiKKZSKlOo1hFSTslSuXz5Ei9+6hYf3XnM3/tP/jParQJODP3JnL2dLS5d2uP46JzpbEySJsTxMyVfnlOtVimXy9RqdarlItVqBbvapFCpcbR/SP/shGA+QWQBtarNew/3uf/kaPHgMk2CwCeMcjIJ4jQnzTKiJEEIFSFyoihlZbnCX/hXPk2eQeA7XLu1jhtNuff+Y/YfjKhVV2gtV1ndVklzg48+6DEbDaiUbX7vz976/7R9+MfAfwv8j//Ctb8NfC3P8/9CkqS//eznvwX8FHDp2fdrLECur/3Lbh7FCXtXN5BExnSWkqEwd3zC1MfzfFIyJFmmYhVpt2voukTvosdydZWpM2Tn8jqPnpzxpS/9GLc/OOMHHzziM29cY9hxqDUt5vOQerHFdP6EpfU2kpSjmhNsU+Os3+Fo/7e49dzn+Lkv/iKPn/4Ojx7qTFyT4dClPz5HllRWltZwhkOGAw+zWiGIAg6ePCLIQ2RiLEPn6OCYaTkgDgRynqBpKqGfoGgGqqIQxzmarBBEi2TkNJpxfaOGUZ2wY9QYDAN2dxt0T2Ju3zllGk2o1DNkoVG0avQGQ8qFmJdu3mR1J8W0bV77VJnN8vOUJInvffMtvv7dDxmEYOsapqZw//59MmLsosn62gozZ06hXELTDLq9PrqSYRg6ipDQdBlLsVAVjdFsxHw6o1ku4cURkpShCAUvCSAV2AWZSrXIWsPhxsYyDx7OGJ64vPb6Go1akf7Q4f7jIz7+aIF9G5oT3HmCVtcZ9CdMJzn+pE+xWKRVEWztrfDg7pBCrYrrD1lfMvmlX77B7TunyErGqz++yZODfZ5/YZ0P3xlzdPwR5VqRsJyz0Wpi2QpJnJALFTODIM5QdJvQDylYFmmWoqgq27vbz7RrMvBs6jBLKFfLeEFAmmd8+P5tNjfX/nfq3jNWtjQ7z3t2DpXzyemee27udLune7on9DAMOTSHlEiJpkQIFq3RH0OGYch/DBjwQDZNESAsm4QoiQZsywIogrRIixyS5gzDDHtS93S43Tedc+/JqXLatXP0j2oRtACBLcgGZupPbWxs7CpUYa39fWut9334z/7+f8E//sV/RLWksVTSscYWg9EEJwhwXXcuygrn7AdVVvAch8D1SKKIfKWEHYv4I4vz0zO6l2fEUUhraXEO/7WmPLdzlYVmjbfv7zIaj6nVCohSyswO5hORmYgiK0RxTIaApEqctof801/9V7z22h1u3lpjbDmY9RyVxTrNoYAT9Dg5m/LkIGM0mSEI863Ik8OnHzHU/z0Kjf+2CasgCHvA61mWtQVBWAS+mmXZNUEQ/tmHx//y377u33Xvai2f/ZUffZbPfN8zPN4fcf9+h2F3RJJmRJlHIsbkdI3exYRCvkSppGGPpqytLbOw2uD9B3uEcczqYpPu2ZBKI0exrHLt5jKOM0BRcxyfd5k5AvVGGdeb8vEXnmE4dPjaN+6jJTHNSo5XXv5pdk/+iKdn+wwHCTlTJ5gFZFGGqVXY3G7w/Meu0x0dUa2X8BwbazokyyTu37sgZzSIYxdBkvD8lOP3B0TJXJuRkSEDYRTMK+GiRJRE/MzPvoakeYwnDqYhkvkFXD+iNxmwuV1n0LcZ92OqDYOZExJFDtd3Wsw8hSgOWS7n+YFbn+Odr72NHQZcTkNmrk+rbHLRPmPY7c7hKlsbrK+s8Ftf+iNy+QKqAlkwI2coXN3ZwfdcRsMhY8tCU3PY9hRZFWmUikiKRBQGWK7HsD/B9Tw27zzDwvYS1YWE0UWImVNYWdewPBfEBo8fn+HOfMhEvDAmX1LQNB1Z9RkPbIp6k4XqDZ48fp8o9lm9eovziwNm4pCcrFE1Ze68UESRNXpDH0QRITGoVGBlPce9D9oIWUazVWLSjojbEUam4XkBSSrMTU3ilOPjC9IMqo0GhlkkCmPCyEfTcyTJXJQmSzKlcmmOXiOi1WzSPz9hZ2cNNxL4H3/hl6iWZBrNBnJ5ienMZ9C9RJXnegZJlNB1jVKpgJkzyOdL1FrLeH6Ma1u0L06ABEkSIEmpNZrs3LxBlma4ro1hqnzjO+/y9tv3WFloIskyo+mMiIw0EwijZN45EUEQ51ZvQRDQajb51Kc+xvUbO1yeDVF0AbVwwb/6tXewrZAsjpCkDEkS0HSZ3YP//41bW38h0DtA68PjZeDsL1x3/uG5f2dSSBMYjeArf/CQoZXg+yKt2jJbGxs8evIBtVqTfMHgHfttkkCmfzZFlFMOji5Y27zKp175ON98823ODmzcIGT7+S2u7ORpVqu40yp/+PtvsLixRqUQICcikZ0xtUKeefEKk1mXbifCjwV+9yu/zkKrzMsf2+Lr33zM9pUi3RMHKROoNQwqFZ3T4xP6HYvJZYiPizNzaFQLLDcrDLo2Rl6nN5iRxjpBnKKpMrqi4AYeqQBClqGQEcYRii5iGDUQPI4Oj1hdb6FJHpY9oZw36Z9HxJlImIYMuiKe52IUFLqDgPN2m4KpcbN0lQdv7zHLIJAUqq0Kq6rE6eE+o+EEVVFIohjDNLCsEfmcSRy6JIiosoQsCCRBSK/XZzgakqUQBClRlkIscHrZp1IposoShqahKDKtUoNcscLGxjUSacRJ8pSt7Rq6KfDu7phOex9VypMEAjs7V9g9fIzrRRTyBndufJLHj3cJbYEP7u9SKihsLu4wcqYoqsd6sYWm6UhKRpYsYHk2oqDRbQ+pl1TcmUj7xEcWDFzHxp9A7BSpbzawjs/JYp8kTYizkMnUwTQNzs4v8HyPhYUlVN2g3+8S+jFpCnESoagGkiyjySrXblyjOxgymbq89c13eOG56/zs3/1b/Mqv/nMUecpisY6UhcBcwKV8CHeVZBHT1CkVC6xvbaEaZS4uOoz6bRRFxPcD0gTSNOPk+Ixup8f1a1tcu3UHQcvzt7/wKs8+/y6/9Zu/RiEPiihiqBIzJyRnaPPPCyPiZF6cNg2DTqfP//mbv8+NnT2uXNnkoj+hfXGK48TIQoZuGsRxgKGJ/NAPfT+7v/IbHymw/z8pNGZZlgmC8O/V2/yL3AdFljg9ukRCIvsQiT5OUg6ePkEQQ6aDc3qDGZohQyyRpRlCJOK7Hl/+gz+lWikRRDE7N3coVCS8YEb/csrug6dsX93m+rPLXLYtQm/Gpz6xQy63Sa8z4MG9e7z+6qfx0ynvP3zAZBQw6waMewWu7azQPh4ia3maC1Veeq5FoZjn3sMDdE9lNo5JJaiW6pwdd1FyEhvbi/S7DoIUUTFqHIsCZi6PJKQoWYTjemiygh/HeL7LjRuLjKwzjo7OkBUZGR1DEbl2ZZOT0wlnZ2eEWYahGiRJOn/q2jIX/oS7126wml9g2nbZ756imhIXPYfnX3yFwBtzdn5BFIUgi0gCc2FTFhG6FpARJQKCLKCVawRRSBBE+H6ELMtzObIgzD3+InDcDpqq0mxUaC3WQFfRGnBwvkvnYsK1O1UQdJ7uB/TaKWIqIKgesRZx2H2EbKTIsoAuK/heiKEbyJJIMYi47Nxn+bbMqHPO9lqDVn2bKClQrbU4P94liFOmXpelFYFyXuf+B8e4rkd9sUipsow1MUlkeG9/l6VSAXdoY/WnRFGG7bkkyEiCiDW2mI4mrG9tsLy0zMV5h9nMIcvAc12yDAJVpdftsLK+RnVpgc7REW98/R4vvXSLn/7pn+B/++e/QcARzXqNSimPbbvkdRWjUKRSq1AsFjEMkziMKBYyFClDVVVcL5gnoDghS1NkSSaME3Yf7TMaDrn78VcZJCI3Nrf521/4O3zp975EFPQQBAFVU/HDGFEGQRRQJIEohjSNMXMaYZjw+OkTji9PEBKB9cUGQirS61mYywYbzTI312+xurjzkWPzPyQpdP+NnfuH24feh+cvgNW/cN3Kh+f+X68sy34V+FWAajWXffbzdyCD4XRKkml0TicMRymBN6G1VMLOZIQ0AzcgFgTCNCFfL9JarjDsj0iTlHvvvI+ZN7BsjzvPrfPxj/8gpVIev26Rpg8ZDlS6AwF1coZny4xmMbev5zk+foquSVy/voB8zeStb1icXtoYukJOSJkMY974szGSMuT23XUadQ9dSZk5GSf7U1bWrlKrrTHtH9BsiVx0+3hhTJIkhGlCGkck8RwYMgsCojAhX9D4/I+9TBCPiMiRM5pEQ4FxPySRHFrLZfJ1jXavR2BHOJOE6cxDV1xahQrKFC4ueuyfX1Ks6Iy6HopexXcmdM9PII1RZYk4jsjncuR0hc7lHHPmzRx0TUVQFeIswXIcxqMJSSqQZBlkKWkUE8QpQsqcS8GcVeEGKVPfoaSmxFGAHyY4jsjxyYBWfYmFRp6jsw6xGmPqBXRNZzidkVgiseNyfvIG21t1EPP0Ol0Wd0xc4YTtF/LgZRydn+LOFOL0CVHS57VPXiM3KmHkHCazAbIMn//xlzg4OuGb994lcFRai1XSKOWsHyMj0+kNUTORRBaIwoA4zkiFjCyDYa9PtVpnZWWRx7u7ZGkGggTZXKZuz2acH5+yvrVFvtLgeLDPm2+9z0/+tf8INfcFfvmX/hfSKGFlZQldL2EWa+iqgefNOL14iKno5PJ5Gs0qG5ubuN4SB0/3SJMEU9fJhIw0mW8fkzSl3R3x8K13ef4Tn+DR4yfUTfjC3/ob/F9f+RKjdpeoOyUEsihClOaK3zhN5oRpScQwNMJQwvciNHlewE7CiOWFAj/y+U+w0VqhXNjkF37pn37kwP4PSQq/A/wnwD/88P1f/4Xzf08QhF9nXmCc/mUW74VCjlxF5/Kyy9nFCMPQiEmZBTNyqoKESk7SGPkOpbKJ25siqBqOH4Eek2/l0UWN0ekQ3/EoGzqjy4A/+tLbKB8u6yx7wq1n7iBEEDGitSYhTaZ889v/GjGrsrDSQEoTZFGhUsqwxwvkmhm5vEbOqOHYM0bdCZNLDQEfpdZgdanC+cl3EGKRd976Nh/72A3CKKKkjZDTPJquQpoReP7ciYcMUZgrOJ+7sUK1aHBwlrJQXceyIzavL5BmCZKSJ/Ez+rvvI2UKhVKRQbtLJW/w+ot3KKY5MjQKGzWqq3XELOWNb31ATomJA4eioTJQJYLAnft+SBICc5CKIiuEskqSJqSJgJgJjAYjgmAODonDAEmR5qYgiTD//XSNarlEnAqcXJ6y/uxtwjBHHEm0NmD34AJvGmKaPQLP58btbUbWiCSISOOA2JYg9VHLEpWFJcIs4eDpEy4Oerzw+rNc9o/x1Cm6KNJuB/iRT6o45CsyalEhHzW5//Cb/MAPXWNhLc/e0VP2H3kU9AVqeQXL7vDi3R1kKaNzEdKov8KbX/4aUqQgSvPWo5DGJCT4QcjRwVNWNzfZ3t7m7OyUwA+JUgiTmNHEYjqdEiUx167foFyvc354xK//2m/zg5/9JD/113+c3/mdL6HIHWqLS7ihT783wrZGpMT4okMYhoSBj5gK1BdWMJ95lsOne0ipgG5IiJJEzshjFktMbYfZZMrJ/mOeffkTnO/uIk4v+Y8/+xn+5J0/ZbJW4v6b56QZpKKMZCqYgoAkzNupfhBCJiCIEmGa8PDJCS/evsoX/5v/kidPLtjd3ac7+lNGo9FHDuyPlBQEQfiXwOtAXRCEc+C//TAZ/IYgCH8HOAF+6sPLf595O3KfeUvyZ/+y+/tewqgbM7iMmHYTLNlGMWGhZVDNl5hNHWRVpyLLJGlCpVKm3x+yvNWgXC2wv39Bz7K4dXuLo0cXzIYzLGeGa9tkqYCZL9BcbnB0cI4sSZRKBmpSwVQL2MEEzxG5jGyuXC0xnnXxhQkoOXqXE1otnVlv7rhbL5U5u9zDcQOi+ydUSk0UucLG5iKKovPk6ARFEFDRmTkOaZbhux4CAmma/vlTIkp8bty6iefqfO2NfbaWNnnxpS0uOudMpz5RElGv1/FtiSQSCVKfZk3jb37uRynIFXp9m1svPMvF0/sUCnW+8c4uthNRyCU0GxVsOUY+B1WW5yuFvIYgpIiSiCiAKM6/T6lcRjcMLjoDwpT5IFUGfhCSJRmGIiPLGYWcQbVR5eD4ArVUxk0ypofnRGnKzk6RgikixzmCVGcWRDx4dEYcBVTLBsuLG4y7B2zdqCFICZPJAEdOCf2ELEqYDF1kdAYdmzvXlvFaPSaWz/pmE98Pee/tt2g0KzQXGvQvQyrVCltbEllm896bE9RCxgvXN3AtB1lRWWxVKedWMbQ8f/Cbv0fO0EmFFEEUETMBP8yIxlN07ZLN7euwsUH74hLHdknDGMdxMXSNTrtD4PtsXr3KZDalOxjw/rsf8AOvvsjR7jZW/5LAD+he9kjSuScI2VwOLtgOWZqyf3jERbuDWSixuLJCaHssLNTYvnkdQVBIMwFEmZnrcXlxymTqsLJ9k+HJQ64vaXzulc/w1XvfYrRuM+r6TFyPOEtQRIliKU8hrxHFKWPHw3P9eTgrIvf2TvnFX/4/KOdM3nu0ixMGyOpHf/5/V4w5Fwp6dmNnjSSOMTUNRVFxEodypUCSJYRxhqkUiOMAPacy7gVMemNqy3kamwZZNrdzT0MIJynNZgGzqDDuzAhtl7OzIWEiomkGiqbiOD6GJtNaWOYTr71MvpxgFDMuLs5RTI+zTod3v36JkJXJV2I0RWJ78zqlXIWL/iGWHTLoDT4cyKmxsNigkKsjqSrT8YQ33/gOnhfiRCEyIAgZSRzjRyFJAkkc8tqnnkMtxJRLGqInMmXICx9f5eLE48njc/Jmjmq5yMz3mM1cntm6wfXaNfxQ4+YzN3j84Dv0jvZQS02+9d4hrutyc2edKHDZ2Fzl5OCQ/YMj8oUct2/dRJFEhsMRw1EfazImCgOWF5eYOQ7tXh8/Toi8uc9gksYkYYyiKGiGSKvRoDOcMhjPyK21sNKE1YU59Db0U45ObMhS3MDhuTtbOB50e11iL0ESNLxgwu3n14mzANv2yfAZnYSkrsbCMzLu2COn1ag18wwGY2zL5nOf/zi+lTEe9IjTmFajSRi5HB9ZFCsShimy92hMFqdsrhmMbIvFtQVMvYo9jWjUinzz//4qJ496GKY51z8kKUkmIpCiyiLb165RqNSYTiwuzs6xbRdBkiGbbzVUVUbXDRZXFjk9OqWc09lcKFOpN/njP3uLXE7BCjJm1rzjhJCBkJIlKbIoousmiq4RRyG6abK5ucHV6zfQFJlyIY9jTfEDHz+MiRKBBInllVWqRZNJe5fr6w1yjQa//Fv/K+dPXfoXM/oTC1GGKAwxdBVNU0nmxoXMHB/bCxCylDSJkBUFRZcp5A1CP+L88qN1H74rBFH/5J/8T198+aVb3Ll1G9MwOD46pFSt8fmfvEsQh1QbJrmcwCuvNwgij0HbJo1EPC/Gdj1euPEqWRwSpSGR77O8VuDZuys4NpTqGi+8uoaWK+M7M6ajCWbOwPU8RuMx9957wMlhl8koJSFm78GY4XmANQ04PxkhIHPz9m0qtQZL9QVMVcRxIlaXNubWYEWFs9NLHj/eYzTrMhvP6JwN8aOIfM4kI0NTVaI0I8lSRFGgUFRZ3ZSpNSXypTK2kxFGEZqo4NgeaaQTewlaSSKIPNZrK9zdeYXJVKBULDAeHHBw/wHj0YTIrDAYOFzbXmI2HbK7t0+uUKRg6nTaHWqNxocglRBNValUSlQrFRZaCwShD6REUUAUhSRRShwn6IZK3tRRlLngx/cjOt0hUl5n52PbJFFEuWYgCynNhslwEiAk0KiqvHh3DduZ4voJoedRrWokqYLrJ+iagR9OKOhlrm48gyiqbF7XUAWd/rnDzAnwHB9BUJmMAs7OhiBCs97khec+x9OjfYRMYff+MZKoMxm7HBwNKZUrxIFEFCYoYgFnllIolnjhlefwxwGpN5vvvYMIRRZIspQkA9/3MTQFzTDxbB/f9/68RamqMiAQRiHWeEJzocXYsnHDhHJOJVfKM+kPKZcNIkEmVyhQyJkEYUwYxZDNazDFYpFao0mhXCFfKiErJuenFzx5/ADHGuHbLr5t4cwGdNuXnB8fUCyoLKxs0D6/pFowmdopPXvM0+NTQsejUS4iiTJxIuC6IWEQIEsZ9VoZUZKJwghTVZAlCd+P5zUsXWds2d87Ho3/4B/891+8+/J1FhcWUFQT2x1jTRz2Hp9x9doifjzFt6X5CKhsI4sCk94M13Vp1Bao5osc7h+SiSGeE1EsFPnUZ7YRJZ1Z1EaRFXZubHD37i3yBZ3T0zMajQLFnEqWhvi+zdPdfXYfnjDszxh0LGazuSFo4MScn3TptEe4Xshw4uAlNropMJvanLfbyLpEc6GIIOgknki32wNFJo1iEuYouyyLAYE4Srl2Z5mPf982YRKz96jNeDC3N2+fzrAsn1KpijuOCbyQslrmpz77E8yGCe3OGb7doWwqPLp3n9LiCpJZYXFpEc+ecP/9B0BGGgXsXL+GpiuUTIPRYMDx8RmiasxnEcZjxoMxgiiSKxbnqxjHQxQEfD+aT9EJGYW8SaFUpNMd4CcJy3fWWbqSR0Hk9KDDT/zYs1y7sciD3TatlkFKxv6TSzY3Gvh+zHDg4fsxgiQQRBGBF1MvNXBnKaqqgzSk352gKnM/yuFwSOBH5Es6ruvihQ5IMUE4Y2v1JpOJy9Qb0+/YIKnoapFSuUzMjKs3DRYWysSRx7B/Qb/dJggkSsUGpiJTrZbIshTP8UCANE3n3RlBoNZokpGSxBFpMrenS9P5lGKcJPi+jyRJlCtlhsMhSRRy65lnEDIJIfJoNhtYtst4NCVKE8hS6tUKy8vLLCyvsLS2TrlcIQ0iHGvC8uoijcYio7HNeDJmOBzjOh5eGJDEGb2LS5LQ4fmXX0LPl3jh2hUUDVrLTZ699RL3P3hIsWDO1ZeaSpyC57sfblFFkjgmr0uIpB9uUUTiNMVxve8dkxVDFylXRrhRDsudce25NQpayJ/9ySO+/bWnFMsqg8s+waxFpPgkkUAur2GNZwS+i6hArbTCjdtNSuUCX/7Kn/L+vSdkmcaLz9zi61/bw532COMUWTe4+dIa1YZCwShjWR6iAAUzx+7uAaOhjdX3GfYz8pUCkhrjegmDTo/9J4domsnCcoMTuUetUqNgVilVdLa21th9+pTZ0EdWdBIBbt28waMnuwRehKkbZHGAKKXUFg3ODx2CWGKx0aQbDeiPJ2iSTg6Dp48PqBRqTDsud7df4fBphygWONrdY2urhT2OqTQbeFHG2eND7tzcIfBsgiBE1nTSRMD1Q5bWVwlmFkHoY01HXHY6JHGERE7AmMkAACAASURBVEqWZSiKyObGJvVKhTgI6PaHaLpMnGWEQUKYpAiagmKo1BZqBGJM0VDw8yZrq2tUGyvc++CQ0dDlymYLPZiSVQ3G0xBrNKPVKDEYToCUKEhIQhdL13FsG0GImIxsCjmTc2tAq1FAajUYjm3Wt0r0exZxIBP7Ko9PJjx+71cQBI1QtLEGEV1rwtKCyfbVOtduVzBzMb3eBYsrRfLVFU7Oepx3n2CNPTaqa9TNPIIgkMvl6PV78+JikmKNR9jjPuWCSZbU6Pf7SJJEnKSkqUAWgmhoWJMJlXKFpdVVvMmYMEwptBaYTQaUpZSNsspZouNECRvr18kVCsRJyrA/5Oz4CEmS0SQZVVfw7TFrm1e4dvsGjuOw//gxrmuhyhqziYMVx4y/c5/u+QU/87N/g0At8COvvc7Nqx7/9X/3j3GSFMX3yOcMbD+aqyhlET9IcIMpZBmqrBJGMWkmzGtLafKR4/G7IilkJCiixvbGCuGKS7U1YGnJ4HN/tcK/+BeHXN1a57lna/zub7/Dow80LMclCcAw8wRhyml/n6W1JmmScX48InJkvvVli0h2aTbH2JOMt44ekc+VUFTY3G4yGXrYsk/gxAiCiGPa3Lp5h0LOQFYK/Nr//nuQaLz6fTexHIvO6Zg4kXEdj0FnQJam+LO5s7QQ53i7c0QmxniuTxhHJMxdgSQBZFFAEFICP0HPqzx/d5X+2YwnD7qMRwEv3f04gpjy1ne+wfUXX2KpNmUwGdAsNkjtkFHmIhoyw+4lz95YJhTmYJUP3t9Dz1XwfZsgnKPWBAG0fA5RkZnZIUKqUGstsuoHPN3bxwsz0iQmIUOJEgbDIcsrS1TqFdzQJ3M8ItslQ0SSIA1iSo0qwqLC2uYyhlFBVnuUmwrfeuc+QZBwdbvGo4eHbF3JU6hoXFw61Msmq+tLtPs6k7FFrzefDHVGQ6I0o9uO0RWFQqXM6NLCD0V64wlmVSbJfBaWTUa9iN0PZkzdEFl0uLW9zsnlhEpNoFLP8Z//vc9SKA95dLDL1DIolQuMuxXOjhJcr4DvJUiGQs/rkCYtNE0lZ2psXtnAsWwG/QFRktLrtlnb2qJcKSEpc8r2eNhFlhVAIklEBHnOoVheW6FkmkzsGUgaT866TCYiZr7I2vIyUqmCH8YcHu4zm0xJ4oRcbv5/ZGaOOE1Ik4yD3V2yLGX1yibX79zm9PAYx54QmQqeC0EUMLZcvv6VP+YLf/+/IhVE1osRd25c590P3kPMEsxEQNMUoiAhFQVyuk6WZsRZihPEpBkIpMTJR08I8F2yffj5n//5L96+uYUiw2Q0IfRkhj2fy4uQxdYKe4/75MsVqvV1Flpr9C76xEGIKM/9DSslDVkWuXNrg3v3PkAxdJqrGnbkkS/JKJpMPl8gsj0UFA73O5QLFVr1InldJPZiPDfEzBmMxyGzWUq9lRGHE86PRty+/iI7V7cZjnqIskxGgJkTiWIfx7KZjKeMBhNyRoFirsSgP6CQy7N/fIQfhuiKjCjNh4HyBZPt7SbuLCGXU/DCgPZFh/29E7JU5bxzTvuyh64W+Os/9uP4rsOdZ5/nj//gDymZMjdvX2UwnvDVr79LJBhIckq1XMKaTJmMhtRrFV64+zxnZ2dcnJxSKZdQdBlNFrGGI9zIJ8tSoiBCAhBTiqUShqrhey5pPLezby5U0UyTIAxY3Fkk00EUIA49crrG0kKJhaUK7917xM3bde7cbnJxPOXOMzVu3qrz8t0ldBOe7l6Qz1doNqq0T/vYdoofRoSeS6mSY2L5FAtFDg/bIAmICtjThLOTEdubN8kScCczbt9s8MM/eo2T8wH99hBT1bkcHWIWAhr1GqeHAh88aNNuO3QuO9RbMtbUJYsylpcX6HYTdEMh9h0koFDIY5oGlXoVPwoREdBkGdUw0HSDKIyQVIk0jRAFCVXVKBQLFIsF5ngsbQ7CDW02llqcjmZYYUghVyZJEhRZpJDPo6oasiJh6BqqrCAgQJIwN7ISmfRHTMdjNq7dRBI1XGuKpIjEcYIkiiRhyK07W1QXV9HVHH/1b/40Dz844NvvvEOpkCNDQJZE0jiGDBRVQRKlD52mVBRZI0syRAEcz//eqSn8w1/4H764eb2GZmTY/YxSYQHXN+l0Qg6fXNDu9NH1CoP+gHvvf4flxWWsqcto0ENT4c7tLaxxyNmRxenZkELRJJMSys0cSTJF12F5pcTLL29w5foymezx+vff5ft+4BVse4o1nXDz9jWs2SWiNCVTO0hailEyyVVlHn2wy+XpmMXmEuWqgJfYNJeaLK8sEcUuubyArgvkzCJHx6ckWcTq2iLTqYMgCCiKQhilOJ6DoRsMewNyhoxZKOFFDrlCQhRlBG4KMoSew2q1xNWr12g0F2if9yANSaIxrUaVN772bS5HPpJhIEnQrNcJAg/fc/jkpz/FeDDg8vQEWRJBiCmVKoiigKFruJMRaTwX8cxxUJAzDAxNIiGlkDPRdJ3JzOGyN8Io6mw8s4imqehCkfWlJXJKiXvvPiWMArZ3SgxHfRYXGhTzCgvLIm4wI58rkGFy2baZzGwCN0GQVIaT2XwWg5gwyfjYSx/jotOnWFRo1hr4XghyhKxrWIOU806HpZUSL720Tad/SbmS4+rOMtXFHPmSz3jq4TkZlVKFwXjK6qrJ6nKRXK4AsoDvpgy7NkEUEEkp9sylf9knTqJ5xyCdQ25kTSPNUrI4JklTCsX8nDgVpQSug2maNFrLKGoOLwjp9gYk1pBPPnuV/Yseb+6ekMUxhq4hCgKGYbC4uMTSygq1ZpOcMXeVFkQRQZIQZQlBEAnjGNfxcK0Ja1e3SVIBZzpFVkRkVSFJEp6/dYXFtVUEVcObDvn0Jz/Jn331m2xf2aBYKuM6Xar5IlGa4Ho+cRKjqSqSJCKIApChKgrTmfO9kxR+8Rd/7oulhkiUwqDf58neQ/r2JTkzY3VlgZc+8TwnF3vcfmabW3c28cMpR3uXjEcj6gs1rl1fYTi2GA2GqJpCZUHHnXgML110I8/6Vo5aVcNyRihazPUbt4hxeLz/gL29IUZOAmHCwjK88OJVfMtg3PM5Ou5TLNTZWN7ktP2UqTfjhz/9QzRXNI7bh/iuSKFcBkFASMCyLCzLY3GhwXg4RpbneoUwiIgCH1EUEWQNMpXT8w6SmVIqqmSRiCJniMTkcw3qxTIv3L7D0uo633jjTWq1AvWKzq0b6zx87wMODy9RSy1ESUITRarVKmbOYHVtHYGUpw8fIwgiXhQQhylJEJJmMYqmooigqhKNWp2lhRb1ahFZzObcQ1FkOJ5y2R4wGDr4fsjmM5uEgoCpmrz24ot8+9u7eKnEUmOb49MDaq350vr9d9uEbkK5sk6tsEFoF3n3vTaPnpwyHXrsH3WwvZA48JFEKFRKBFnKzsY2w1EbWU1I0gRRTqk1ciiSwNO9M4LYJ5Z9NFmkVKoymPZQzRhnbBFlMapkMBq7uKHPSqvJ4nKVi+6AIEzxrATXdTDzOq3lMnHkECQhUZZyftxjOrYYjYbomoIsioiqxng8Q9c1UlFAyEQ0zURWVJqtFqphMrMdjvaf0MpLPLPR4htvvcNBf0YsKIgIOI7DRbvDzJoyGg7wXJtCPsfi4gq5chl3ZpNlKWmaEoYhWQqyIuO6NqNBl52bt2guriAIAmmaoEkgehbFcoHK4ir9swPUbMLV7ZscnZ6yciXPrZcW8OKEaBqhyRKKKuL6IQIZiiIhIiKIEpPvpe7DP/qff+GLL766RZzF+HFKq75EIZdjMgo5bF9weT7jwQeHfPVrb9PtDmg2avQvR3S7FqkkohoaSZzghjad9oCV5Sqvfmqbw5NL7BmcHU7JgiLP3H6Wd99+B0Mr4VgO3U6XIJuB4rGwKiCZATPH4tF9D0UrYKoSceLT2iywtrlIIZfja3/8Pt//ic9jSiWOnx7jWlNCz0cxFBQtw7XmiPREEFGkGEkWibOEnKGhK3Ntv+tlNOurDHs2s4mHbpRYXq2wslWgfzLl6vImz71wl0KlzCsff5lavUilquHPZuw+eMjq9nVmoYDnzNA0hXqzQXNxAUmR2Xv4EMey8JOQJEkgjbGmI3zXpVDMk6QZupFHN3RkSSBO0zkE1guQJInxbE6VDuOMXMmgullBEkx297r89m+9wcHeGQ/uH/DiC69TamYEdBhciORpIYoGnaHNwdM9ehdt4ijGdcEPE5BSfDsmSzKQoFjXuHajxb37e8hChpmXcH2PRIhACikXRDa3Sly7tkEQR1RrkOCTaBmuO6Ng5ukMQ6ZDmSgNiR2T6TjlpDvFmypokoTvJeSLJcIkxg8TfC9G0RW0igmizLgzRBQEcrqKrmlkZFxctLGtGaKs4QUhIJArFkmzjNj3yGYjGpLH9z1/lb39Q84mLs2lNUzNIEvDD6HBKYooIEki1mTKaNhnOBqj6zkWV1YRRZHxeEqaQZYlQDrXnKRz1WZzcYFqa5FiqUaxVKZeLVGu19E0A5IYezqgVpBxUo+OdUyltkptscytuzucnXfwLQ9V00mzDEngz4fnvqdWCj/3cz/3xbWVFrGfIgkmUZBwcdpB0XVsN8SZWqTJHG+2vLgCosBoYjObBlgzl1Kxzt/9wud5cnLOZz79DI/fP+QrX76H54eAz42rNzg7HbD/xCZODDavVJCyhLWVJmmW0L4c4wUBsSdzduChqCFBMiIOZS7PB4wGQ8YXGe986z20asDxyRGhlXHaP8GLPZqLTTzfYzwMcTwfU9dJ4hBNFEniDBAQBRAQUaSEZ67t0D6/ZDCymU5CokhgakecHnS4s3qFl557FoSEK1dvUCqWaZ/s4VpDKtUqmzeuMQtVHjzaI01iVFViZXWZ0Ld5ureLZU1JooA4nDvtpFlKnERE4Ryd3un2GU8mzGyb/mDEeGZhOw6KoiNIEiNrhh9n+EGIXjJR6gaLiwZFM4c1tTFNBbOk8PDeI073x1g9GU3KoZQdxl4XWXSIZhn12gKinuO0fYEgRFQqRSZDDyEW0EyJQk2kXpcQlDyB58xlwUJGpVghzUTyRYP1LZFGtU63N0bONKyxz/37JyhCjrXFJu4s5s6z6wReRqu2iC8E2OOQW9duQaJTLOYRlYwgy2hfjomzhCCJ8X2fYlWnXq8x7QyoVkoUCnmSLMVxIqajCY7r4gY+1mjMHJkZs1bNkVp9sijm5PgE09DY2lyhUiqwsNBiNBgRxhGlUp4rW1tU6zXIBFRNJwgjZuMxaRqj6Sb1xiJRHBEGHrqhUixV2b5xh0K5hm1NEUSJTJQoFAusbV2hvrhIqVJD1Qym4yH+bEy1qHNwPiQg4fziBEFWWb1aR0LEnrjIHw4mZpkAacbE/mhJ4bui+2AaCoW8iKwUyCsl3n//IWQSvcs2cRyhqBqKLCMkKbuPTimUc9QqZQr5EdOxy2g85uBgyGqzwmTa49XXr5O8IVIuSXTPBhzsPiUWYvxoSG8/4OneMVd26lzZukGtdp1m0eB0/wBlsUzBMKk0ZeLQ5+HbJ/hTm9ZyjY0Vndd/+EcY2xbvv3XOcfsU3xVJI4WLp2Pi2CfwQ3zXo2AaJFFIJCgEUQiCiKjKWFObrY1V1rfW6A56aKaGkEmEfszZfp+Xrm/y45/7ATw/xhq7kMLR3mO++Ydfpr5Q4yf/05/hg3ef8K1v/S5xnCFJMgsLi+SLRXqnxwSOixDHJFFAEsU4ro+sqkgC6ErMaNhnMJoQRRFRnBKlKTlDQZVFWs0mXuAzs1ycIEPRNMxiHTmscXrg4LsuujlHqdkTn9B1aDZb+JZHjz51I0e10GLW8biytcZ33n2CpKe89ulN+sM2gauxe19A0lKqBZV8UebpwYDIE9EMA8+f8xuiYEaYRAz7NobaoFh0uHOnRerq3P/ggrt3r2PmXO6+VuRVaY3zrkVnCJe9YzI5Qs9nnPf3GQ0Drl1tokkKh50u5YqEMwkRJJkMkX7bYmWtzuq1DdqHl+SLBRRFmT+5RZHJzAHLRfxwgKmy1kIV8yQCWFFAvVhibXWBxbUlHBTGDsy2NrkYDFlYWcEwDYjn3gxhECJKMq4bEKcRSexRKpdYWVvnqWOjILK2to5i5uh2Olwc7WOaOqqmIRFTUl9EIUBMQ0rlCnK+Qb/dg9BlUdO5d/mUZqNBo1QmUjy276wSBgnd0ykIMZYdISofnRD1XZEUNF1k+SpIYsR42GZhq8L58RBNN8DPyJkGcZayvLJCu91DTGWeu3Oba6sb/MZv/AH7++f8zpe+Qqlm88LdVazpGa47xTBaVGsq+YpDrVmmmFuld5ny1pv7fP2PHvF+7oRiycQ0DazZhM55RJbN5amGpuK6HoJcwpoo3B93+MY3Txl2bOJApGDqELuUciZLq8uIOZ9+d8bgzQme75LECWEcIAgyYRggSBqqItHtT3h08JRCLUc+FimXaiiaydX1FW40dZLIY3/3lIWlTQb9Pl/9yh/RPrvks3/lB3FCgd2nRwRRiCDEaJpGvlgk9Hwsa4qmayRJQBbMnYqVTCBNMxzbJpYFrOkMN5tTkeeQ5Iw0TihWSsiKzGTkEYQRqqyg5nP4Ucqka6PqOlkmYeoKjjtDUVSe+9gVvvPOuzRKJs1cDT2rgy/gBTZjO2Rpo4KiBPTOQ5Y2rvKHv/MYfxqgabD0QoN8I8N3QqQ4AUKIUgpqjiCNUCURxw05Oh6zvBTPyd2xzSuv3WIyGbC8usT+XkKWdpiOU472hhQqJqah0KyaoPho5QQvO8ezRHTDwAocUjWjWlLQRIWenzC0xly5WqaYvwK+ANmcII0iIicSUZSRCDCbWajSAp5j4zgOaZQwGI9QpYxc0aSyvIqaM3m8e8h4MkbXDcZpQhB5GKqBIknUllZYWF7l4uwYQRAZ97sY+TxXdnaYDofEgkj37JTOxQWu7WJPZxQLOUxN4OjR+2Av4U27LK0u09rYZnHrJqOLxzy3s0l/5tEdOXjOgIuTNsvLBi9+eo1337zgcq9PpVjkst/7S+Pw37y+K5KC78cYsk4aJYiSzNC6YOtalcBNcCwNTSjgOCGqUOaTL91GEVQuDmcIRNSrVQbDE27cuEqpYuJOXRQl4VOfqCOkq6SpTaUhY5oKB3sTzs/PuHGzSaHksL5yk173lInVo1zRmDoOghCiqHMzUFHKEDOd40cDKnUTWZVQZJBVD9ebsLG9RH2xRDEvk0lFHj44R1MNkiRD1WSsmYthyigJRH44FyLFPqqZEiQRhbrG0LkkvIy5VVdZ2XiF04NLvDDlrNdjYDl8/dtv8dd+5GXe/fq3WHd13DAljBJyZo4r25vU6lXELGXzygaz0ZCL85Ao8EmSDEVREKQEQdQJvJBMAIWMTIIsS8nnNarlHPVGleF4zLA/QFMVJMNgGkqk05iuf4miqizV6+hSjvWVDabTc6zpiCs7m7z6ynM8+3yLk/YR33rrIYLpsXKlAlmZKNQ4PD7lzW/s0zmdICVzZLxWSZBNnaJZwxN9AidAySn4vk+agqZpLCxr5PIigZ1w2p2wtLTExWWfztmIP/nyQ/w4ZqG2QBD4hHFArz9FzUlItxYoFEQyMULIS1jtACM1GFgWcZKRFkI2rlZ5+WMbfLB7wNp6leLOIsfv9XCtCflCnuF4gpBmCIJAHEY0m0VkUeDk7JLeaESWZuRMk4EdcHDU5maxDprEzJrguw6nJ8fkjRy1WpmCUWBpbYXK0grD0ZTZzMGZztBkAWs6obG0yMr2FaIwxZ5MUWSRLEtI0gjLnZGkGpOJg1V2aK6sIwgFnGlAqVEjTa4iAc/urPK7X3uTTAipFYpsby4SCBGJMqO1VuB4d0heNz5yPH5XJAXT1GnVNnl0/4zl5UVyN1tUijpP9jo0V+sISYbnOYgStBZNuv0u9eU8lhXjeCHFQoF793Z5+fkNZFUmnOYYdD2WVlM65y4P3mvTHY9ZuaqzdsNkayPH/0Pdm8Vall73fb89D2ce73xv3Xurbs3V88ymOIhDJMoSLRmyEMeWAjtQgDxYCZBAiB8CB35IYgSJLSCWbMsGrNhBJJkMJYpUcxCb7GZP1V1jV9W9defxzPOehy8Pp5MQgWw2HCOgvqdzNrD3PudhLaxvfev//93gMmvL1zk5stjZ6TOaTBgPYtbWa8hSDllA47DBcBCRz9Z56oVL3H9wH8WQMLNlnIGDH4/JlOqcW6uxvdkhcBPCKAJJIU0ElmEThiGGYRD7AZHrk6/Vcfopg55HS5qQJClfevlpnrm6TrVe486btxARkApee+2bXL20iq7I3Ly9R3H1aSRZZXFxnnyhyMLC3HQoKgyQZZ36bI1cPoPjTOj3+/Q6valXoWqQGim6paCFyRRIkqSoikJ9ZhaBRKfTQ1E1TN1EMU36XkjsR2iaRhqlnLa6NFpNznOB1bUrrCxXCUKYuBE3b95FNRMQJuVymc2tHQiK5PIqM/U8t957jDcOUXWZ6kKN0VBwdjIgK9dQHJOM4jEZO7hRTCoJCoUihgH9Xp/QU1BljeaJw/Fxl3JWZ75cJFQSVB3sbI7BMKZSyGGUBI3ugPHQYuNSFisncCqwv91DL0AWi86Zx4OkgfpMxJPP5Bi0Uh5sHyElAtPKICdjDFUhTmPkWGJutsYnnruK5Hk4wyEZw0SSJeI4YuRFJAOX4NEhtZlFzFyZStWnWqsxN7dI4Iw5t7ZGsT5DGMOou0sYeCiygqKqlLJ5pEQw7DQplCpcvHwJx/Ppdtoc7e0SOhMkXaXT66OJiOrcAoVKijJ2SeKAytwCiIgnszZWJsc7792nXK8SxCp3P7yDqeaZu1FkbnGVu+8+/Njx+BORFJJYcP/OCY/utQmGWbJ2gTdvPcJNXaLgmNAdEUUe+UKG0/YOsiozNz+DrpSQJAkkgZ6JaQ0baGmBMBrixH2++8ZtDk56KJKClc/z/OpLbCwt0jxtUqip7B1vYRlZNKNNSTVZmM1hamWG/RRnMqTVGCBpMsvrJWYX8ijGVQbOgCD26Q0azNTqnDUbHJ80cUcazdYQXVEhBSHJyIpE4MfIqgaSTIyEokXosoepBciGTNnIk0dw/okrdBpdzs7OiGQbPQq5dGGW8yt1vvf9m1jVWR7v7CCrKmtr5/A8h5OjA1zPwbBsbEPH0hQM00CIZHo0WyziBx7O2GUw7OP5HkKXKeQzREFAmiSEUUyYpCArFAsZCtUy41CQiQNC38ULIoIoAgGR73Hnzgf4YcLBYZNMRqNUznHx0jVOGw6tRpdPfXKd8SRmMGwy7rXY35ogJTIyKYgYIzvle8iYqAUJew4U3UZ0JeazFU6bByAnZDJFxoMJ/mSCaRl4QYJqCVQtw/oNi1ROGIYRk4mEWVRZ27DpDWVODkYIJaEyY9M4dWmcOqSxTBwmhEEIkqAzdtg5EAw6NsgK93f3WS0v0TwNyOTz6MMeXpSQRCHVaglTVTnr96bzB6ZBxjaxMhkiWSdA56A94c72O4wnHrIis7Sos7q2jJ3LY2kyvd6UCdo9OyIOfZwwxtc0RJqSxglIU8+LYnmWg50dclmL5154iWG/T+tkH0tJ6Y08br93E8vKoy0toukZQt/DsPL0ui2ubVxma7/JvUd3ySwX6Y2GZI0sj7dOUGST0lIO7n28ePyJSAphlBJ7EnOLBp/9uQvcfP8hZklQsAoc7p4yu5InDnK4kwBNlfADh35vSK85IIxiVF1DFlnwKwhrzLWniuwehWwdgqpnCOOUaibL3fd2uXdzm3y2QK2qce58Fn8UUbRXGI9dDG2G4ajF0ck2sRcTCh8tI1FazCMbPeqLM5zecbh/b4cEn2IJnrjxBK+/fpucnUcSCUgaqqEQRTGxSKcKyShAVw2iRHDpyjLFksrBXsxC/RzB2ZDrT1+h3e7Sb3VINYNLN65TymdZXq7xv/zP/4DHp31WchXy4zGWbZNICdsPHjGYjElJsC0LXVWwbZusbaEpEiKJyWZzKJrAVGUypk4YBsQSJFFIJmcS+tMtBUrK/NwsiqYQSBJH7THjjkMuZ6LZOiXbomDZeG5Ms91l++Ft7GyGTC5L4Ma8/db7FMs1JmOP3/6H/5r6TJVXfuppnn31SX74zjvcuX+LJAFFh0REmGYRIQya/TOyZQ23l6AKhdT1kbSE0WhA66xJxswyU51HkSQCJaVYz6Ga0B2HqGQwbYtB1CBJJIJJHuGDnqb02yPeeaM5dSryNFonAxRJoBs6harBaOxysBUQzVosnFP5zM+u8OD9Mb3Ap1wsk88VGfRd1leXWahXPvKv7DPoD5AVmTgOUVWVhXPz5OoL9CcB2zv71OdU6vU6GdtiNJygagaj5pD7t24ydD1GjofrBSAp+L6H503dyov53JQAPrvI0rlV7rz3Nr1en9XzGzz94ifYvvcWvYmDNhmy//gRIDh34TxGkJIr5EkXzpHVFT756Z/i3cfvkfb7LMzMoCsyx40h43GTJPn4of4TkRTiEE7PXI7ax+jffYdBb4JQNPYOGyysaDz/1Bq3328wdAOeenGN5bkSrhfxtT98wNj1yOcyqBjEicuNi7PEYczm/WNEGuH7HlY2Q74sc+P6EqatcHQ0Yvn8EqNRDymGTvOAYiXL0Okw9gYsnltmb/sUq+5TXZTpdWKEP+Sk1WDzQYN+f0yaJjRnI+ollQsra7z/7h6aqpOmCUGQoioyXjQdd01jidHYIVfMYuczhKFPuVzFOe3xuU99gr2tQxTVYuniJZ7TiyiKRCmrcXa4y/b+EW5s0mr20KSUS1ev0m4PcQMXVQHX9RmHHookMRxIaLpOEk/df/MZG8OcbmUmE4dUJKi6jh+GSKqMMxyTzdjkSnmC0EVRMvQmPoU8zM0VKZg5UjEFw+w9PsSNZfwEZEnF9zzGjoOcShiGymTQJY1lJEnhYPeIdmvAePAZdKOGgo5II1RNpWiV6fUGCFmiUrbx+x5KaOC7MY1eF9PU0E2dIIFxiAAAIABJREFUYmGeeq2CpZmkqWBChNdLsPIKsSZzcWONdneMEjSYmcthyzUSOSZ0etSKM8RehkbvlJUVhZlnq2x+2CJrKyipwrm5GdIwYXmlysQZ0/emCMLzTyuc3jyjXC4xyGW4cvE8tiaxvXnK2PGnKkQEfhQz9gP6wzFGzqPfOCOeDPBjQTAegJBQVJVyvcziwjL15VWc3W2ygK4ZuIFHGIYEYUp/EOF6LlEYkjx6yNqV6yyvrrPz6BHD/pALF8+zunEFU90kCSLGww5Seh5vEqAZA+pzddAyDDonrK7d4Ms//yt85etf5aTb4OL6MuV8EcOw0SyFKZ7lx68fmxT+DSCY/wH4OSAEdoBfE0IMPrKBfwhsfnT720KIX/9x70jSEPQUGZPXv7VJtVZBtwTFXJlK0eLOe10Odntodo4ffGeHtXNVolBwethHEoJSuYSkJAQxvPP2gE98+jmuXHF4tHPMwsIiZ2dDFufmqJfrvPveXc6aAwaNMYsrRVB71FYUJkOXxlELQ7cIHEG5kscsmjz5/AX+4F/dYjfuMB77xLGgWDewLYXWWZ8tecTS4gKNs+FUkCRSFEXGDz1IBQkaSQpxkmLbKvlMjJsEJK7Oz/zM5xBRxA/vPODZV1/hjdffod1zeXDzLf6jX/0yncbZdIBGzeC4E3zfRIiYfr/FyHHQZEijhEQSiCBCIkWzbZAk0hS8aIAIfaI4QWbqXCyhEEQRsjS1mtMNndPTDq7rkKvJyHmTxVoGO6/T67loTp5Ba0yrPyLVDEw7OzV0TVMsSyL0/CnHwtBJiAkCF8PWcbwBX/2Dr6JqOqomoesaklApVgtMegOM1MBIM1iFHIEbknqCmVqJWCRTwVacMJj0aQU+xUKFOFLpn50wZ5/HtGbZ2R5SyGZwJzLdrkyndUzky8iSiUhKBHGMaZp4TsTVyxn6/RxyopPPmRSLFZLAZ7ZS5zS0iWSJbGZEt92jO3SYq9V55cWnCJ0BR3sNkiAkn7MhawISkm6AbtMZBTTuPCRn61y9vMGDh1t0uh0Uy8ZUVYbtFNPKMjO/wIaVARnsTIbGySn7u3uMxiMCPyBKIkaug+ilaNqTrF7Y4OT4AM91eXDnNs888SvoIqZ/fEAhnyFjyyhSROfsjEwuw+z5S6j6AoaRZb52AVPTiVOPRzvbyLGgWpulmCt/rITwsZICfz4I5lvAbwohYkmS/jvgN5mCYAB2hBBPfuxfwHS4wvcjPvXqZXoDh7sftBi3HYamhD+ATEbDzuoMOmMmbsjpcZP5+QX8IEEImVa7h+MNeeaJJ3n4YJPvfGtCqZzF0srEYsyly1n2d7bZfvSIXCHPpz9/na3NI5rtLjk9h+Jm0E145qkFnHFClITEYUilco7OqUupWKJ1NuDqpXMEUcBoNKHd7LC4UOe5p9Z4+4c7hD5ICJCYOvbKKomIQCSYqkZqxnz+Cy9wfqPOOHRZvnyBvJTw1d9/jbX1Nb72la/zeL9FbzRkbSbP4sYG3/7Ga4CBIk9xc34QEroTiHySMCZIEtJoOnUHUyWDM3IQIkVXFGRNJUkkPH+q8VdkUEWMrilkCjkKlQL9/phmc4CuGWQSGUuyaOw5DCdHLK3Nc9rbZ9gaYekGbhxPUeqaCjGsnJvB80YcH7YZjSZIikyxWMTOCMxMAXcE7WafJJFQNJMkTmifuORyNWJnhF6RmYQhdr44Hf0lJXB9LM2iYFukYYKh5WgdtTm3NIe6UOPw8Iw0PaVcN/D9DLJiIosKvV4PxQjIlDWKpZjhXhtn3GcykBgPQ0JfELuCkenh1hLaDZfHH25x7coq46FDbxiSr86h5wK8NKWQzXB4dsZ47BCngjBNsDNZCqUSmVINxcgwaLVRpRDbgFo1z9UnbvDg/gO8KCJJJCr1GQzL4uTomNFwiG7o1Ks1qjMzVObmGA2G7D7eYtDv4bsjTFXgjPqcnjTQSHBFQiQUtu7d49Nf/Gk6tQJ+v49IXTIFhVJmjTBKGDWOkBSFSeeYp65sMFddIUp9OoM29cUclWyOdvfjo+h/bFIQQnz/owrgR6+99iNf3wZ+6WO/8c9Zvh8yP5dHJAn+xGd9vUa/FzB0JiRySCpLjN0YYUa4Y5fPfPJzNI5bDIf7FCoWo4mPcGxMGRYXc2jEhKM+8dilMCdz5Ykyz708T+MkoXHWR4pkrmwscXrWwR/BWaeHmkvQKyrLy7OINCbyJFx/ACJgMDxieTXLxpWUnZ0Jqm5SyC5ytN9ke6vA9m6LMIxQ5WnDCPGRbFpVpoYeUUC5UiBTU0kUj4tLz1LWK9z8+ldYXp1HzeZ4/9YOqq4w6DepPblGIiRmls8hf3iMqirIQuAFHikJIk6JwpBUkklRSKIAQ5MB0BV5Sj0SCTJTEM3YjUkSkGUVU0nRNQUrYxHFEo3WiBgwdQ3X8/E6AYGbEgQyeWMOtVpCl9uEoWB43CYIAmYX5iFOmHQD6gtV8gWDSn6eZqvP/t4Btcoy1fkyOzuPyQY6riPwg4BsNkO7NUbqKeiKz4Url2k/ekysTXAcjwiFydAhN7eC4yk4/QEbawuMeh0GkwgnBTunkS8YtLtDwjhkdqmEqUCcBPR6XXSzRhD4xMmIOI2o12aRMdAFFMoFJHkCqiBwfdwoYOiEuJOYNJBxhjHZUp6l5XPwEYw2JUFWNDJWBtUySDWLSSgx6fUxNZmL165Qq5QIw4TZ5RyFWp3RYDzlQsYpOzu7+K5DEIZ4gc/x/iG5XJZsIc/SygobG5dQVYVRv0e/28FzBpSKGSbFIrEQjJ2QrZ09ajc/4IVPfQZ3MsBQU/KlGbKVWUaDLs54wqjfwh81eepT81w+f4W3br7JwlIZiQhDF5RL0ceOx38fPYX/mClT8v9aq5Ik3QJGwN8RQvzgz7vpR7kPuq6xOL9Ou9+kNjuPaYF+3GT7zTaWa+LnZZzxiGyuxPq5GZRU4WD3EEVLqc8XyLiC1lmfmeUqN15eZ6G+wXff+Bate/fxQovbN1Na7UfEoYxpmyB1KdU0olRGM6DVHrC6PE/zdEz7xOfgeA8hNDYuLKIbPoomkyvbROkEz3HoNnp4nkDPmXxw7y57O10sM0MU+SikyLJMLCBn6QThlCa8vlGlUo2R/IiTzSMuvXqO3d09fuaXvsy/+MPXkBWFybBNzjKQJIndnX0y1TqZXIFxEGOqKouLyySJhCRJWIZKGEMkSUiySZom5G0ZRVGw7AymaSFrCu1OhzS1mLgRcZJO0XC2TSpJnByc4rsulXqFMALdtKku5Nl6/JhKvcKdD26ToFGYyaBZCi+/+Azvv/8BznhE4Ec8+8QN5udqbG7dJrNgU5QFa4ZKtzngwdYmlZqNnTWoz1hMRjHd1oRIgJ2xCXyZN37wgF/55S/z4YNtWhxxetpGC0FKfdbPX0RT1jhpHIGZotsJllpGiBDFUPjsZ57n5OSAkbdDpa7iewm2YjEcOIyHHnFgkTOKFHJLWJJJZ3KCoeuMwph0FDBbK6DbBZrHHpGYcHH9Al4scX3ZoKIb7D56wGg0Ik0l7JyBVShgFapIeo6dnQOap2cIEdFqnLG0vES1XqNWE9TnFwl9n93HOxyeNHAcBwSkTLkNkiLR7fXo9do4wz5+GDM7M0+lVqF8qYYQgly+QLW+QKvTY3vzEc6wy+nRIYPmAcuXnyCJUsJk6lPR2XvI2qXzqFqVxuCE4dkZrz77HN/81ldQkoBxX+Hk4DH1WfNjB/T/p6QgSdJ/DcTA//rRpTNgWQjRlSTpGeCrkiRdFUKM/t/3/ij3wbZ08S9+94/J5rMUZxQ0M8QyTcysiuuELC2vcvH8MidnDeIg4O6texyfHHP5qTqlBdh7t4tumty8c8Cr9k9x843vs71/yA/fOeTpF9f5S7/wNNtbFsPBhFyuiGJJHJ+MGHZdLNVAVnVC32XihDSaAwbjmLk5md39A5bPlSkUqhzuxvRbIf3BhDiViOMUfxwxGSfIkoogIUWgIqHKMokEcTStGNww4KnrN0g7OoPjkKULRQLf4frTN+gNHfZ2DilVK/jjEeVSnvv37iOpErXFdWbmF3H39imWi8zPz+A5E2Zm5yjXSrRbXRrNNo6fUJ2po8mCUjFD1raYTFxa7RaT4YggBpEKRDo9DbFzNoPRhCRyWFiYIZU0gmCMpekszaxRKFaZOF0ypTyd7oRBa8DS+QqlSoaZuXkePNqiWCqzvbdLr9eiVptj9+gEPwmol2oUiia6HSCYVmaDjsv5jXNMxh4Tx0PEEaVynkazx82bH6CbWfq9hNgXRAn4SUhv0MMdjNne2qNcLWIqJoQB7X6XVIc48lF0icqsyvJ6Dc/NcXyyTX/gYBoyIjHww5idzUOurl6gnK9yuHNGqnuUC3m64zFf+PSn0Y08v/e7/4zlRYdCoUpeldi6d4f9x9v4no9pG2iqjKZpaIbN1t4xe3tH6KqMqsqgSLQ7HXqdDqOFESPH494Ht2g1O8RMZcsiFQghfTThKqHJCqqqMhwNSVKJ7ceP2dneolwrc/HKNdonZ6i6gp0v88nPfo73f/g6sirjBx5To2VBv3uGM/I4erTFsLPLM5/+eU4bA4aDN1h7+mVeeOFVtrbfR7diyrU83d7/DxONkiT9KtMG5GfFR5bQQogACD76/L4kSTvABnDz3/YsTdOwTA13MqFQrZLL5WieddAkE9VUOdlpoilFZM2gYM7ROdvFypRQNA0RJKwtlzm/PsPu3iHf+v4fkCbQGQwpFHS6jRG/+9t/RLWcRzMNzo4mjAYumq5gmTqJnmBmJSrVIs88e5F33rnP7t4BYd8FGWSlColD4MX0+iOyGRMrK6OoIbJksvOogWHoBKGHZuiYuobnesRxjBPERBOfv/7Lv8C1+jWc0YR7j7/Lz/21X0FNHWYWV/j6N1+nUChgGwaKLNEZjNE1hfdu3mNlmHLx6mWK1TJJHNM463B8dEAY+SwuzLC2vsrSyjyPHu0iSQozs3VUTabbbdNunYEEhm2QOgFhnKJIEpKikQgJz/OpzsxjWjlOTpvYhRKyItE7beALhfLsCnHapjRnMuqOCJOUh9tbuF5AtZwna5oMxwPWF+Zxxw5JIjAti1a3g2UrLMzPMhr6WOdm2d7a5eHDXUxVJ2eqyCrEQYhtmbz77gOK1TzuyOPipRKVWQXDzHD77U1GHY+nn3iKTM7iqHFINpNBy1VRtBhJOAy7E/qDCaFTwtBsitkKdXOF3e0tbFslTCWyBZlsSWV3a59sQSfRVVIyxHHMzbdvky/nKeTytA5bWDMRp4HPyfEhXuRh2ja6qZMoBkMn5rC1y9FZF6SETDZDtVpjaWWFQqGAYZl4k2nv5eoTT1FrNTk6OKLT6aDpKoqiIgUCCYGiKsiyTBgLwiBAlqcV7Hg4QJdl2o7D/t3HGLbF1Sef5ZXPfoFk1CVVLIIoQYkDzvZ3qM2tcOWlz3L79W+gv/U91m48yzt/+iek1j3S1KdaX2DvaJuF2QWOj5ofO7b/nZKCJElfBP5L4KeEEO6PXK8BPSFEIknSGlPy9O6Pe54QkM1b5KUM4/aEcBiSL9SIkg5BHOF5Ecf7EYYu0XRPSVOZxZU5LlycZ2kJklQniEdceuoqUWiws9Vj7eIs7XaL0cTj+eefYbZusvm4zd52l9HYR1YynBy2sG0TK6exoyk4fZnD7SamphHGgnw1z7XLOcZOyuPNPvPaCpVihkCM6PcDPvygSxQJFG0KWQGJMExIkXDCkBcuX+U//U/+OjPlArEQvPndbRbWVrhybZ1uo8sHwS2Oj46ZW1kn9D1yxSzt3hghS7iOS6fTY/UClMt5jo4bbG09JvR9kjRm09ml2+lzfn2Jc8sL+L6HpkKUpMSSiiSb+IE/nedXZeQ4JQZ0K4+iZpiZNRCSyunxKaapgSxxctxESlO29o8I4qlIqlirUCzWkMMM7qiHoStolQyWVWZt4zIXls/hui6NbpOD/R1Ou23q5TJNd4iWsUnSGE2zKJYL9NodqqUSXjDC9zwMy6aQy9JuD8jldNY35jGsCZNuhY0LdRY/UadSzOPFEZGcUi0VaQ/6xHJEvVRFHO8jJInT/X2CQEI1bebrNuUFm/EgxDIsLqwug2KyceMpVJHgJiGHO22iUNBqjNh8uI+WJlx56jyz5SwP758hSwqFYhHdMLFyBdAzNLtjjo4PkRWFudlZFpaWqc8uTNkenkevdUbgTuiIlHJ9hksXz7M4v8Dm1jZ7u3sgSWRsG5HEVGslDMPg6LiJH/iosvyRQtTGtAzmFhfYevSQxPW4c/Ndhp02s9USYWBh2Hl0TcEd++wM72Fly1x5/jPce/fbPF2dZ3bpAmmY0Ghu8vigBanAL7Yx1X+PHo3/BhDMbwIG8C1JkuD/OXr8JPB3JUmKmG6jfl0I8WPRNJIsIYkASYX67JQlcHp0hCSpREIgSTL+xMWJAgLfJVfO8sIrV0lCwclBwP7+Mf1uDz1rUi8V6bSHGLaMnVO4cfUizsDh8SDhYH9A66xFvlRgOPTRbI1cwcKLAnYftdh92MLzEpI4oTJbolZSqOYyEIf83BfW6Y81Hj8+oVpbxDZi3hu10KRpg0+WFCQh4/oO/mTC09cu849+67/HsE3SNGbz3gPu373D3/6v/ib33vgmmllD1Q2efvZJNveamLpOtVzGm4wpZC1SSeXSlcv0Wl0GvS7ZcoGrT1xn9/E2nUaLOIH9oyaD/pB6rUR9poYugZROXXcyuRLDSWM6SRnJyLKOnKbouo6u60SxxOlpA0jJZHOctgeMhmNyhRyLy3McH7donJ3R6LTIZbIYis7CwjKDQQfPjRg7DVQSyi88z1f+yT9GSgKSOOHapWtcvf4kf/qNr0MY8Qtf+hK9kcut+/dRkYmjAFlWUaUEkSTIUky9XKA36PLmt+6j2TaLiwokMYcnA86a2tQrMZWQEMyWC6i6hiKp1DfmSAVsbt0nVH3CNOCkdYwfOSRE6FmJw1aX0HXwPYfJwME0dZrtDp7rkAKhH2Ko4E7myKzNE/g+aRyTLxXJVCokis7RSYtWq0+pVMQuFKnV5yiWp7yIIHBpHB8g4hCRJqiyzMHJCY82N7ly5SrXr1+mXMixf3hEFLhY+TzLK+c43NlFlQWaqhD4MaomEJKEH3gksUTOtHAinyQMOT3cx5QjNKnOhzffplyrMze/gDfs4w97HCYRy+vXOd5v4HkBg/1jnt54lXb7LTRjyMbGDEsLFt/82tbHSgo/ETCYrG2JK1dvYJgZVA00DeZmyvieS+O0zWg8IRUJuiThBxFRmvD5LzyDVUp4+OiQztmQ688socoGg4mGF0SUs3n+0pee4rU//Sa6kuHyM1VyeY+332qxtdlFkiyG4whJgslohJLK5LISdkaleeJgSXlOm22yhRJ/5T/8LK3eJmEQkCvpjIc+3/36Af1eiGWqpFFK5Ez4G3/jl/mN3/hbfHj7Ed/807f40hdeBhL++T/6p5w7t4o3aPDicxc5/8xz5GqrbD56zP/2z3+PwShk+dwSxCM6vTbzK9eQZJV7d27huhPiOEZRVTKZDJVKlSAKuf/gAUGcogKWrqLICaqqUijmma2VUSRBCgzHLp7nM5lM0HSTUrmIpuvEQiCQOD1rc3baIZYkJCmhns+ycekiiR7huC6d5pDxaEIYwWjsYNkWpqGjKQaXNs7zyZ/+Am6vSej7bG7vkcvY7B8dTu3UPZ9Gs8X/+D/9A/7x7/xTGqdHdHodDF0ma1u4QUAhXwEZsoUix0dnCJHw6mevoJhwtN3h2pVVhuOQodunnC/RPOzRHw9I4gTLKNE62icJI+ozJbJWEV3VcIXEQbtD86yNqipoikzRUlENCWfkYOoqikjIZCxuXH+ScyuzKL6LN3HZfnhnqj6t1EjMDP2Bh+cntHtDTCtHtVoHRcG2LTqNU7qdDmkiTfUtSUwuY1PIWmRUmVze4tzFCyCpNI6PkUXC/OICuXIFw7IYNlp4gya9xin94YTTdpflS5cQss2DW++TiBTPizAsHVs3yWezZOwMiwtzdDstMqUc+UINIgddUanPlVlav8zbb/6AKA746ht3SIOU/thBSILHu3t/cWAwf+/v/bf/Tb2aQZFlECppohKGPs1Gh/5gRJomVCslNFVmOOjguC4RCj/7pc+QNSUmzoRzq2WMRBAEOv3OkJPD0+kcQsbk+tMb9PodGmcOvYHHYBDS7ozpdgekUUo4CSnmstTqJpam4I0TFpdq/OKvfJHqrM7/8Yff4/SgiSZnCV2Do4MuzdMJuqEz7g2YL2b53d/5h/zVX/4yv/8vv8IHtx5hWTLeZMyf/Mm3CP2E4+NjktDlZ//KL1JZWuPB3fv4ScL29h5nRw0M02Bx/TzF2iKGaXHr/fcQIiEIIoIwxgtDXMdl7Dpkc1kkITEeTRCyghcFCEnC0FRURUbXDTRNw/F8LNtCM1RkxcBxQ1KRkgqBpGkMRy7tVpckTaeTDh+BRPJZg0w+w+lZi1Ity9r5GsEkwdAVJClEFjKDwZDG2Qm2aVEo5FhYXCQIIh5sPebuoweEYchwOMQ0dN67+R5f/oVfYjgc/N8UJcs2IRWEaUoYC0QSkbFsuv0B3X4HzUhxJz7uKKRcNohCn0k3xQtTojhAE4JEcrDmM9y4cZ5svsbuWYfN4zOOzhpEnkfW1ImjKeTFVFOqVZtSxib0HJ596hrPP/ciXiTI2gaxM2H34UPG4yEoMrqdI5Y0wkRGN6Zlfbt5xsnxCa1WmziJWV0/T7FUQSQxvjtGJYE0JUkC5laXWLt4A8/3uP3uB3ROT1AQRK5P5+wMO2NTX5hn9dI1ltbPs3p+jayq4bROKdjT/xs4Dqau4YfBR1vBBFWBQs5mdmEOJ/Qp1mYozS0SJlAqZHH9CfNLy+yeNDk92mdhWaVS19g4X+H23aO/OCYrsgL5UsTKisXB3oDxWMb3VQzLJgsoWsr8uSqFQo5ECmketjjdO+VPv/4mhVLE+oVZYifh9odHjBwBUUQieQzHMrJs0GqX6Td8jnpDQEJSTCTJJWsZaArMri0SRDHdscSg1aVSymGYOmdHfV585ZN4zhBdF9x854i3f7BJpVYlDWHYafC5T73Kb/3W3+fhnbv82q/9BhtXr7G0usTK/CyvfeObUxGUklC0Nc5fWKG+tMZbf/YaqWITyTkW5meJPY9LVy5y895DSpUK51eXydg2vW4XP/AJI0Eipp3scOTiTHaozVYpV4p0+iOQNfwoJY0DZEVGM6bw3aOjJpquUKmWaXX6dPsj7IyNIkvomkqxVEBVFBQlRqQpQiSkKXTbPfJVm9mFDHESkEoaw6FPoajxhVd/CkOv8t7N95iMxrz+Z6/xXQH5UpnVtXWeffFFhpMRIonRSwU0Q2PkDPjGt7/KT3/y83z/zW/iRgmabJKxdTrtMYquI6PQbLVJU0Hr1EUVI86tlbj21BMk0oQgFaiaIOwEuBOJei3H8tol2sMmfiTx1rubTMYjJCnF1lRII4JgQj6vUs5VKeUL5Ksl1hcWCMc+1WqdYrXK0A2wdI2HO9sMeh30jIWqmYSxYOyOSZCpzlSomDVEnHB0fIYXphzsHzIZO8wtzDO7vEShXERiKrqqVsrUZldoNlsc7+8wmjjMz85TLJfwXQ9IeXT7Q0bzpzz30kvML6+gaCYL6xfYvH2PYNjghVee4vCswzf++NsEQYCsa1Pqt+9xeHKCH8dcff4VUkmn2zqjUi7RdXwOdx5y8coGmVqFw7MznvnMk9Tmi4z77r89CH9k/UQkBZFO9+V2VmJ+PsveTpc41fCdmFyxSJKk+BMV3Ugx7CyqOsTxPZqtIWYxS+yOWCjNUyoHWBmBIEbXJ6Rygu+mDNo9kkTG7Ut0hwOcwKeYy1BbK9BqjfCCiNFwQNHMcnlthstX5xmMIx7v3WISnfLgzglnjR6aYrK6usjB3hm6pPF3/85/wd/6m7/Kv/xXf8h3vvdDnn35RRQhONjeQZYF3d6Q9skJn3j5GnIq+Nxf/su8/kf/mm6rxVjOoWdrnL90mRdfepY/+86btFptojhh4/w5yuUy3U6bJEkJohSBhKzI8FFZ7h+dopsGSZKSJCmKouClKYmQCMKQw4MjgiDG8QRRKjH2fCRFxg8ikiikVq0QRilREn+EtAP9I3OZrJ2jUq4wiRWiJMEdhRi2gR/B9naH5SWTQrFKd+igWRYzhRJRlPLo/l32d3ax7Rxjf0wQ66gi5vmXXuTxg8f88de/xgsvPclh6x56xiBwMvS7Y0JnjFIokynkGTfbaKrKYOjjTmDn0SaZQoYgCanN5wnSARMvolybpdUcsbnZptE6I4wTbEOBRJDEPuVCgVqtxPraIguzM5RKVVrdBoVsgYnqIySV+4+2qJdM2gc79LttkMFPBL4T4I/buL6PqalkMwVUWSaXK1DKOciOQxDHjCYjov2AfrtFpVKhWK5SmymArLDzeJde8xD9IwyBpGroZo4oVUGEEEaETsjJwRGKPN16VBYWeeITn2Lc7xJHLp954jmWFub52h99h6PDIyLfI4kjKpUi2XKRKBWMhj0e3H6fnK5w5YWXufj0y8TehMUVnV/8a5/i/q1j5sY+J2d/wUxW0hRGI4m9vT7lXIkbT2xw994j4igmdEYohkXjtMt4LJNEKSgaVkan3/QJ/AgrF+MvdJiZX8IybN69dYeXn7wESpMnr6+SNYp889u7BEmALlkYeQsh4Gi/h2kqLM2XCcsZ0iAmEAK9mOXiap61y2s4wQ6StEh2y+TW2485PjjlF3/+5/nP//Z/xuLcDL/z27/Lo81d1laW2Lp1k2azybn18/RaLXZ2d1mbqTAzM8/KxYu09rb44bdfR8oWcaIGV54toWgKh/sHHB2ekLGyeK5Lu9Vi/fw67XaDwWiMpsqQCgwFkBRy1VnSVHDWaE/Zh6qCnKRohkK+UOKk0WUw9tFUFYGEHwSJ18wUAAAgAElEQVT4fkCcSijS9AhY1lREKjA1HZFMDUOLeYtKrYqqaGw/2KW8NIMXG5wejQlD6HT7CLGPnS/gJQmZbBaJkEq1wmA4ZjCOUYRPr+WAKiEnEqEf8sZ33sUPIoqlHKNxTEadR6QTFEumNFeic9JjNOghaTaFbIaMoVEoltjdbaDFEc2dE0LVoJyx+fkvL/Inf5Twne/tYeoKQRgQx1OGhUyCZirEsUqlUsa2cnQHIYPeMbP1Pi+9/AJf+/rrxFFIsVjinXff5fOvPokpIiq1CmPH5bQ1ZOS7RKgYChTn8hiGAUJCSCqKppNEIzQU4ljgpiFxGDPs96nPjMhcukqz3aLfbpI1DYRqkKYxYRDgeBOyhRIKAl3VGHbOGI0mJHHK0f4RcQiRIpMrlAh8QbMx4PTgiP/gi5+h60R88M5NVAnKsxWK1Rr+ZMzmnVvEQcRRp4d46wes3XgOjCydu7tkLIP1jXk0Q2Lh8iW+8ZW9jxWPPxFJQQiBCHXapxFRKaXfHeA5U2ussTtBjQMMRaZx6uK5PpKskC/UCMOQaOCRCJV9b4JubZPVTXonDf7Zb2/ymc9fotO4z9VrT2AXMqiGQEYjQcIdO2TNLPNLRRJfsLdzTJrCxWtLfPjgGNssEKchRwd7JEHAS8/c4GJtmWdeeYWf++IXGY0Cfv9//0M+/PAxjXafo+NjipkM6xcvcen6FR7ceQ9N19F1lYnrM5kMufXNbyBUDdswsXM2W4/uMVv/BI8+fMBw5DL2QvI5C9d1ubixwfXr10jThOOTJqkQqKqMrukUi0VOTk9QVQWBQNdUVAkKxQKqbjDu9IhQiCPQNQld1VAUhTABWZIwdJ1iLksqBGNFnnIYJBlFVqa6jv6QgqEiaSq3t84ol7I8+ew6sjLm7TcO+LPXv4dpWSwt1Hj6ySf5s+++jiT7PPeJNerzOTY/7NI8mRC4LrEbM56kyLpGEGboDlyyhoZMgVj46KaMbqkEno8QLqoyPdo9f26V4WBCox2wWC0wdkO++9oD3npPoXk2InZSPEtBpAkSKYoE1UqZxeVZJm5I4E4QRDSaLQxJ4RMv/CxvvHmX7/7gTV567inubj7m/Oo8gTMmmIxRNY2ZhUWOhzHC9bAsjVIxj5ANdN3ALlQZuWf0BmO8MMYLfFJ5WuFKhklG11CQp5VXFOG7Ppok0x1MkBUFOZXI2D6Be0oiJAQCS5Vod4c4N9/lk5/+LKkAPwiRJAk3iDndO8ALZT744RvkK1U+/zOfQ5JVBqMhSZLiuj5p7CFSj8psjUarydzglEx9nZOdHX7x176IE5vcfPsmjZO/YJWCECmj0QRNA9eZoGkacSohKwmSIqMqMsVCHlVRGSsKnp8iACtXxDA1bEsQhCHj7oDYTjFNndWLJVrdPvNKEX8Y4/ccgpHEaaNJpVRhpjJD6KU8uH1KtV4ml88jqQpWTmdp0eb2+2fIscwLV17lpz//Ka6dn6NUP0cawr0P7vLhnQ+5/8Ed9g9O0FWYq+dJFY1avYo/maChkUYxYRSRr1QhnTb3crqBUMBzJlgZm8Bz6TS6jF2XII4xtByhH7C3u89MvcqXvvRF3nrnFkPHIwwDsrbN6ekJkR+gyNNgyJo6tbk6hmFxcHSC5/kkApI0QRMKURwTxTGpSLGNLLahYhoa3d6Q4XBMmAqIQ+JoQCIEETJqHFELIuZrMziBQ7kWUp+Z4/23T9ESyGUE6ys67eY+G5fnyOZl0gRkpYxdSqnIFlE0pF6awevDw/uPcPt9fviD72FnbGTJIBETluYNMnmQZZtee4Iqy3RGLt/6/vfJZ3K4YcRRz0FRFEYTj15PYFsash4Rhj5pnKIpAjOXozY3w1m7y8hxuXZ9hYyqsLBWo7Hb4fpzL+NKd/n8Z13u3HtAEIWcnyvTHwyxkgQvDIhHAQvnVokXBZZiECYhfhCgajp+4NNsNHE8lzBOyGeyCJHiBgFJkhBG4PkOaRIzOztH5PnEkU+5XCaOE6IkRtdkSnmLZmtEu9uhXM6S9CImPcH9u3fI5jI8/8orFJeW+eCNm+x02oxHExY3nuDBnQ+4f/v3uPHis1y8doVH9x+CLLNx9ToPbt8hDAOCRGV3c5unqwt4vsT+/iYYCqHocNg4+djx+BORFFIhpgRgVUZWFIQkyNsGA8ehkM2RhCEHZw3yuSzZfA4hxsTBmDDymYyhE4XIJAhJYjIKsWyDvFkjl7WplGYQaYHT4wNaZwOSQEKOZEzNADrYWQV0ByNWyeeziDBi69EOl9cv8ld/6dd58pkXAB+32WR4Ovo/qXuzGNm2877vt/baY81jz9M53X3OPcOdeQdeXoqkRFEUZUqQYlkegiSWLRmKYwOBECDJUwBDb0lsJA8OnCiILSORTMkSNFDiIIoUeefh3Hvmqc/pubuqa67atee18lBXgoIE0g2dBMx66tpdtevp+2p/w///4/j0lGtvvs2t67fZOzqjVrZ54bnLlBtNut0hnbM25fIm1UYNw4TNi5tEUYDjNshXChwedCjX5lBpysbqCgd7ewwGE1zHYxyNaHW7TCZj4jhiebmO0prVtVWKowlBGGIIgUJTbzQwBATTKaV8bmZ7PxzhT0YYaLIsBRSmNNGGmBnSGjaWFJimjTRN6rUa40lAfzjCNE1sy2ASJmRZRigEhoYrW01wGzz77BzXb54xmSZE4ZQnLqxz+fJlhCk4ap0yHU+I0j6nRx2m+2OE5+AZOSw7ZOXZDax8ht8bs7/fJQ4jhBmglIG0KiRxD2EpciWP8SDEEfasfyLANCSj0YCcY9HM2eSqipxtkSqDw25KYGSsnK9RqVY43D1g5KeEYcrNd3ZYX27whc+/yJ33v8q7b7/JF7/4E+zu3EcIRd6zGU4Czq80cLIYOU04bfeZy5fJlaszTqnvYxoKDJt7t+9zcHRIqjTStCgW8xQLeU5bHQDSbDblSOKYIIzpdDugMgxzitKalbkm4WRKY3sdtEnetUmzEJUpFpYWGffaFHOLtDtn9EZTHMugMb/M4eH79Kf7LK5s048f8K1vfoc0mGCLiIHv01i9xAuvfpoP33wb10k47YyZjCc4BY/xNCCNM9qDFk994gJ/+LXrHysefyCSwmwcNjPoyBse0ygmsxUSsCwbJUIW6iV63TE6VaQqIY4yskRhOwLTtAiGEV61jG3akEn8gYDU5Fr7ENNqEwcKKQosLBQoFR0eH+6grYxSfY7mQgV/OCT2Q4LjkL/1c/8hf/tv/xJoGB8dYjkCnVpEyYQHt25w4/0bdEcTvLzDCy+/wJWrl3jnjbd45423KBRyXLh0gXy5wMbGGl7O4c6NGywszJPFCaA5653heUWq9QadVmtGJ/aHaEOChotPXODlV17irN3mjTfeBAzyuTxhmuLmPIrFEkESI4WB6+YJkxCdZKhUYUtz9utpStAz+/QoTUgyPeteRwphxaQZ5LwcQoAlDTzbwjLN2e6DVJim5LDVIxKwdnGZD94ZMhhqsixibaVCrWrhFis8ftBhOApYWC2hpOaNb+0TniU05quUS1WyYcCJeoiwhpy/MI9dlDx+0ELHJm7O46QdQ2bgSFBaEokYS2tMDcnUp1x0sBxJXiomwz6DSUpgaSwvT5wpzl9ZJooisjCjkStRVClDxsRhwg+/+lmMVLB94SK/8eu/yZ0Hj/nOG+8wGnQoFUsIrVma97Atl0mS4pSb3H94gGW2MF2LnBQsryyjpaLX7iCFxHAMhNLESUC1sUySpoxHPWr1OnONeWzbZDr2cR0HlUZoDdK0COOYdqfL2VmH+bUlutdu4tkm5UaFaegzP9fEzXskoU+cKcLJmKLr8syzT/HVr36Dk+NDbK9Asb7Ch7cfc361gswUBzffY37rIi9+9hXee/N9gsOILAmo1ers7h9SW8kRpoIg/f9WJfnvfDQQxxEojbKg4OaZTCJqpSKT/gSkxZSIp648y3B0iBCSB7cO8BOfSFtUygUa5QbjOCHNBLlCjkKxSBBOicKQTA1RyiCX89BZhucVWHY28OMURQA6wHYkh7sH/PI//GX++s/+PP3dI7qtFpW5OqnWBJMx7cNDdm5ew5BQn5tjbmWFWqPBv/2Nr3Dn+h0ilbGE5t23Xmd+eZkrVy6zd/8uhVKZUiFHkgimyYwKZFkpUhikKsMQirlykd7U58L5TZ587inefestHu3sMvZ9Ep1RLhSJ4oRUa5TW+EFAtVLFdVxszyaIArqjEakwCFJFkCosIQinU6Tt4LoOcarQhsF4MmHSH5BfdGk26ugso9aok2QpkzjENV3kTM3C7qMjYhHymS+8wnB0gG0pfu7vfApBxmuv/SnVYplKOWMyOaVQKPLjP3aZb3z1Dv1ehDQ1Y5WSM6bUazbD6QSrJPjEZ9fYfdjj+OGQ5fkcq6uXuXXnAa1OB9exyXSKbWuaFReylCyekqYpuaILGYyzlM0rDcqx5MHtLhKLUeKzvVqhvCzZ9NbJFebItMXuSZcgjEi05Cu/83t4RQ/DtBhMpjPX62ieUSI4bffJlOC062NKE1sa2IZmMOhzfvsi5y+cZ2fnETrL0CLDdWbA2PPn1gmThVkJ4fu0jw8olGtsX9ik3z5jOB4hpUkcBhRKJR4+eESUKCZRiNIWOx/eQWcRteoZq8fHfPIzLk9/6jPs7hxy5/oNwjDgxZde5NHuHt3BhO5gjGMq2t0YKTKMNOLBhx9QXV7jU6++xHvXbtBrt9i4eIWvf+8maZqRJinXb3/wsePxByIpgMAwLFxXsrCygD+OCeOUMIoh8lEKTjsxjfIyVl5geaCERhoWaQZKQGKAaeXAiBFSk4gAkVdYCISCMBlTrJdwLIfW2SlpkuHkXESmsXSBfv+QTz33Mj/zhZ+k8+AuhuVSW6lTrFU5uHWLIAiJ45iltXmKc+uE2iKKp3z9936Xo4MTJlFGrFIOjtocnJxQPzxlbWOF23cf8DM/++8RRSFn3T7dsY9lOSRGQLfXJwgipAELjSLzTpNP/tDL7D/a4/j4BGlKojhmNJ3gSBPTlHQ6HaJUESeKbm+AaZjMz8/TmG+C7jMajhFSYhqzJqRCUC0WMaVFfzTBUCk516NUKaMMQbPZpFatkaIJw4AojIjDENOUOJZAmgZHj7qsbzTZfmKF7377Ju3TPvOLeTa3V2i1enjGCjqMGCYHLF/JsX21xo0PR0yTKalWDAaCDNAiouBKJmNNY8kjJ22++Nkv84df+xbTIMA25Uf8QxtIGA9HDEZTCi7kiznGGFhlk7lKldpCEUu6+K2ApDvFqBoY5zxGYwPPqxAkFlGiQEqu3bpFpzdAOjZaCZIkJZz4zC1USEPN0VmLOElJ0xnO3TQEjiXJew5ZmnJ8cMDq+hrbW+cQzNiPXj7HqD9i2B8ymU4Y9XoEwRQE2LbN1tYFitUi03DM1B9h2xZJFpP4CSN/iul5xFrhVcssLdSoVCp4loUyXQ73D7Bdk6ufeJb9B4+4c+8BoT8lCMaYpmYwCQnDiCsXN7HMCqf7e/Ru32bYG/Hypz/H3sP7zNdzLK8uE6c+VauEW5HA3seKxh+MpKA1WaYxzTyTfkx/0EdKj+kk5ImL21zc3ubR7mPefe8dDMPGLnhkqUKpjAxNnCYomZL3VnC8PH4wodcdkskMyzKoVPJYQUajViAD/MjHVDCNxxga9vcS+qd9fv7LLzDutjk66iEFrJ9b4vH16/zhb/8eQZzwuS/9MFdf+gzf/ObrvPvOWwgNrVaH0WRKojQayFC4juTcxjKPHj7CcSxcS2NY5syyLO4zDULiLE+iMi5ceZLnXniecrlMqx/Q7w042N3Hti0mvk+cZghh0+mPqVaKM5yYzkiVIlIKKRWnJy1yrsfKyipBOMWfBmSomXZEGaQKSpUyUZJQLhSZm2tQLpVJ0UzDKUJp3FwO13XxHI9p4JPLuxRzHof7uxha8av//W/xn//Kf8z2hfO89qe3+LGfeB7bhfu3j1hatLlwtcLDBz7Hp1M+9SPbzC8F3LpxSLlp0FiqcrwXE4QKxwKlBU+fe5ZoyeN/+bVfZ+RPsUxJvVFlrl7l6PCQ0XDMIMuwpCCIJO1gSnWlgoFmMk45vTMm6hxTQOBtFqluLbG/63Pr3T2Kzy+QqRHm0SH+NCbTgjCJQYGRgUp8XnzqCs8+uc0H125gmg7FQoEoSUnHU/KOTc5zcFyLQrGIl/Nw3Jn7VRAE5HMl4iCifXLMYDAgzTK0YZAZFjrNCEc+9+7dZmVjjUazSVqtYFkmAoNyuUK+WCaOI7IsplTzyBcc5hYW0RoOW1364xDQLMzNM784z8nhLqQ2Co/hOECWChiGxYOHexiWRSmXp15rcHR8xgdvv8Yrn/0cQro06svce/wOzfIcBsbHDscfjKSAJp8TJMmQqQ9z9RlqS+Ry9Ls+f9p5j0I5z+LKAlkcMx6FSK3IDAGJZjSaUCjYOHZM3ixj2ymT0ZhU+0zShGFvhKESCDWpCvHy4FgGfppQnatiZCnLlzZ57uVXOTlpI01JsZhHEfP13/xt3nzzGtKxee6F5zkJz/jd3/4DcGzSJCOapiAlecfAMgTVWp7FhSaVWpXFOZ+D40NaB0csLi6AAdtbqzRX16k15hj7EWM/YHlxgU53QIbFwe4unX4PQ2vCMEapDJQGQzAYjcnSFENobDnrPwityUhpdU7ZajzB+rnzPLh7H01GJmZWd1oLbNtla2uTfL6MylI6vQHD0YjeoI+B+EgVaFGrVSjXa5BpSsUSl5+4RJTEdHpdvv2N1xiNB+RLFcqNRdr9PS49ucLSiuTikwovv8LjvRGls1POX22gPIdwNGFpOcfq0gbX3nxEOd9gobjGzt1jHu0dMZ765HIOUZhgmy7jUcjEDzE05KRBikEnSCg0PNAGZCCISdKIrefnWNxocNqJuf7eGbt3TvjcD71CpiVHh4c8/eQl4kTx2ltvkrdsoiTFkornL1/m+WefQ6mUZ19+FcstEgcTTk9OiOMDpBTU6lWq9RrVapUs0+zv73N21mI0HHJWKLB98SKlSonesI+QJnzknaDEDLmnlOZob59hacDSyjq2kyNXKpLFGYNeH61SJhOfNEsRWnH/5l2uPrGN6zkYjTrLayvky0WK1TIvWRaJUrTaPb7+tW9xvH9MojK2VhcQCtq9Pu2zLlYux95Jh8bND/nxv/FzjJTiw+tvcnd4n2Lu/2cwGNA06hb1WpX9gyF7x/s4lospTZIkpVouk0URgR+CkeCVIQvBViaaFJ2ZBBHkzClpkGNlcQ3bNjhp71HKG+g0wXGLTLKQyWiEnZic31jhfK3Mzt4RrgeLBYNkMkCriEZzkTRN6R4fcbz/mHLZYf3cGsuLFf7l//RrxMnMjVdrsB0baVtYQpHzbM5f2OKsfcaHf/Im2+dXiZIEJSXadrjy8stsbF3EDyLu3b7L9773LnEUcnx/kUJtjrlz2wyHQ/RHfYNKuYpl2kwmM2hMpVKgUMxz0u4xjRLSJCZVinx+hr5DqZkgamGOTrdDqjK0ylBZhuN4OI7D/uNHs/FVFOKHEZnS2NKk025RLhVZWprVx1EQMOglzDfqBEHAxa0LFMtVHOMx09EYt7iPMxmRxTb+KOLs2KJUy7GKRoiMm7fvoROP5lKJB3d9ynHGX//RXyCKErJMI5TN1rk1/of/7XcwDRslYTToopRGmiYoiedowkxQKhZY265zejQEYeEWTBrzi0xikxu3RnhGGSKDrUvn2Ng4x4OHj7n38CHdXgfbMDEMgTAFeUPyzKULNKsVwvEEbXoM/DEYIZ5nUS5XsM7b2KakWquSZRl7uwdMJ1Om0ylZqjFNh8FwxPHhIbVGA+f4lCTNSDI1A7kKiTAkiUowpEkwiTh49JiNzfN4+QqnR4cE/ghTSqIoIk4yEAKtUqbTKYvNGvPdM4LhgEvPPIu0bJ548SWmfkj49nucW1/juDcm6vdAJzz55CWu3bzH48d7eGmIEDX29o64+8E7bF/8BAYV0iRhMFAfOxp/IJKCaUrKtSZ37x1gYDIZjXHnXabBFAMD3x+zujDHYrmCW5C8ffMdotikkndRJPRGAVrYDLM+0jBBl/jES+u89U6fySREuwbTIEApmCYG4Uhz8+Ye0rTY3N6CdMzli1dYv3CRg/u7vPbNP2Zj4xx/9G9/E6/gMl8o8sSTV0mzGKESiq7ktDvA81wahRxJFGDaJpsXNmmfdbl16y4YDv1xiJZ5/EgyjWHl/GXCIGLn7j1e++4bjMazjvDAD1m/uoqUFnES45iSarWIUhrLhOZ8Aw2srS1y7twG731wl9EkwpCzXQTPzaG0Io4ioiRjcXWd+lyTwPdJlcKyPRAGRweHdDodtCEwDINEG2QfPaJbpo3SarY/kcszmQYk0xR/0Edrg85Zj1c+8yqXL17irL9H3nHoHyfsPxySk+e5duZzMnrMxUs1xq0zTFXg5Rcb+BOL4UHEIApZ3+gy6repVeoI0+b05AQDgygMZlRuoTCEQhOTSIOJNol1RhIk7D/sYDsuOtOkiU2vC5PpmOF4SJq08RyLZqHCtQ/exZ+GXL5ylWkYIEiRYUDBqXPl8hU822Dcn9AbZzw6fMh4MkSnCaYUlAsF1ra3aLW6nBy3USoFrTGlJE0V/jQGaaKMmfy6Wq+ysrZC6/SM8WSCNAQqUyghMQyHLM1wcxaWJTFtCzeXRwioFPOgIWfbJJkiSWK0cPA/UpUm0zEIzbXXxjTn53BdD2E6KJUxvzjH/P4ROokIw5SBH7I0P0c8jTjttBmO+niWwcHuMU99wuPzr36ef/Fr/wqvUPj48fj/SpT/3zyGMBieDdDhFMvIWCq7TKdjskRQbzb5wuc/y3JznmajgZPP8fKrr/LP/tl/R7czorlQZeKHxGEEUjM2hjzc2ccPy8Rjh85pj3xRYEqTXn9KEqYY0iAxUgypOHp8iqcl61/ept/q8t53vkttscnIb1OrOMydu8DRaZ9CweNbf/hHtE5bmI6F61jUKnlq5RyGdqnWy8zX8xw9uo8UikTFSJFiSRj0zjh8+Ig3dh+ik3imM3Bs1DDEQFNtztFYWGI4GnHx8hVsU+OYguWVFTIMwljR6/bwHItabY4LFzLefe8mQggGwyFHR6coMlaWV+i1T5n6PraXR2uF49qYtk0SRYwnY1I9oyVpMRM/oSFVCiOThHGGFhJp2iRxQq3kUc0XMKXLo6NDbn3wAa/80Kd563rM7r4kzeaJ9F1SAf3eEJ3B3oMJSeiwdd5kvnCe3/nqI66/dxe3WOTWv7jN6soSnbM+g9EELRRCZAihSbNZAM7WiS1sxwRpkEYBtjaxhY2pDQwB0+mUbm+AVinCMEmTjDgVJIzZ3j7H3umQs3afc+sLXL14kVKxSqVWRwiLu7fv0jo6IQxDtCFwDIGwLUxTzhIkgjiJGPa7SNOikC8SxAlkGa5tk2pFqDRBqtjZOaBerRFHKVK6KBUjDYGUApUl5DwPITS2NdOTlAoFtjY36R3v02zUsKTJaORj2SYqS3AdE9OQKFKiNKWA5Gj/kE998a+BEFjyIqbjEEcxjx8VSdOISrmGLkQUXJvhu2OCIGQw6HO4f8idWzd4YmuVJ84t8s612x87Hr9f7sN/BfwCcPbR2/5LrfVXP/rffwH8PSAD/rHW+mt/dVYwsJwCG5cK2GnK6KyFGaeEhuSs3eLwsMXzzzxPpVTCLRRYWb/A3/+FNv/yX/9r0iQk55iIOJsxA3RKEgacnTpIs0w5n6Eyn9PjU4SQWJbEtiwcuwDKIOoHPHN5ExGM6LWOqc2VeO6Tn+B3/udfxQ9SHuwdU6o1uH3jBtff/5DBOOJsOJ0xI9OEKEuoV2qUy1X8yYRwOsI0Zg7VhZyNCqe8+OLTpHHK0c4O0rFRQmJbHkkas75xnude/iGmUx9LGpzf3ESaYubdn2WcnZxw88MbRFFIrVohmAywLAdbaE7bXR492kGLGRHKcz3cnMfR/j6ZHJDpDKmhWp9ndXWZcrlMnPSRQpCk6exXWeqPWlAZzeY8+XyewWBIv9vlma3neWLzPLvHLab3J9y912F1dYXVxXma1SoqmmDcvU11MaK8UmFj5TzDs4BOO2Q6ELz+Jxmvfe8uhgWDwXBWOz/YIVMKx3FJkoQoTvCzFLRCGALDMLEtG4FAIhAZKGEQZZpMKnKAP56CYSGliTRBmgamZTEZT3nju9cp2y7PXlhnY2OLcrkGhkCaHg/v3ed4f5fpdEqlUEBrTX1+jkIhh2WaZNlsfDe/0KRWruCPx7iWxHMLuKYkCEKGvo9KYiJlMpwEjIe7WNLAsSwKRY9UZUgpAY1pmDi2ZGl1lVq9hs4CitUiXm6bxB+hVUq9WiRONcVCnUopD1LT7w3IFQr0+h2ac03e+c53aS42eOKZ5yjXauQLBWrNOR7eu0OtWuWkdYpSGS88/xSvvfE+QRhy7+E9CpUiTz/3FH/jyz9G5+SUncOPZ8n2/XIfAP6p1vq//osXhBCXgb8JXAGWgG8KIS5orf9SLyiBwWQ8ZevcHC+//AJf/63fZ3DYpmwbuKbB/bs32Ll6mZJlcu/BAwJlUp6DV7/wMlvnnuE7X/sGH1x7hO24Mz7CxEdlJrX5Io36EqetY7R2cV0bx7IwlIIItMxYXSzzD37x3wclKZYqmEJw+PAhb7z5Lq3uACtX5NkXniPotfGjlIE/G9uZlmQ0nJBqhT8ZYxmKubk6+ZyHMw5ILJskjqiUy+SLRd57823STBEGESkgjBTPy/H0s8/Q7XR47U+/w6c+9TIBgnt37zIaDDk9PSFVCtt1AIMgSKhVqqwsN5ifr3Hc72LbNlGUIoTBsN9lfmkRw7SI0xStZ+Pafr9HrVamWMjT63ZAgqUFBoKc5+G43owsvTSPUhn+eEKapTw8OKY/mJBohZ3Lc3I44Gvf+A6bT5wjX3+Wq1eeYWFhkcpCzGDQpb27j3QgozHRiAwAACAASURBVMTjvTPO3v82hkyRwkGLAK3VjLwdx4zCgGLJolEzyeVLtI59wkCjhSZNQ6RhoUwTYUqmfogRapTIyCo5TNtlOJhgYGB7FoWyiw5T5ktVnnzlKRarTfwgwjBzJFlCFMRMwiMKpTyLy8sM+j3maxXKlSqpKbFMB0vA3u4uJydtTNukUi5TqxaYa9RYWppHRxG9dpveOI9tu7T7A8hi3JyLZ1vkbAtDSqRlk6qZ+lSnGWvr61y4epU4yTg7PCCJQlbW1ijkGjQbDYhCRr0eSkhOe2OyOMSyJKPBkKXFeSzL4va1dyjeL9DrtLnw1POcu3yB5uoyG9ubZGnGpaef441v/BGWZfDc009x8+49+sMhQRRx2upjpRN+8ide5ZvvfjzI7PfFffhLzk8Bv/6RgetjIcRD4EXgjb/sQ8IwKFdL/OiPLnDhos+09QoPbu1z/cN3UGFIJV9G6Iz22YDDVptpDHvtEcIZ8uDuLtViiUa9zNBP0YaJlpI4nhBO+1hugVKxjJSaJAkRGrIsIUtDJuM+v/h3/w5Xn32Rt197n/7Qxy6W0IaNmS9QjCP8aYDnuOycnjEaTwmnUzzHQhiCKI7IZRKdKgSa45MTOv0hQZzh5AqkQcRLn/kknV6fg/19VpYXiLUiQ2K5eZrzS1RrVb71R1/DH485Pjoin/c4PjykNxiQJslMtDQNEEJimw6tVgeVJgyHXcrFHMNSgbQ3RCIxBNimQb6cZ9LuIRBoQyG0pN/r0GzUqOTzgKZUqVAqlXA9D9OUYEgyNRPz9PtdBIK9o0NawqZSymPYJrZjMfGnjAYjPnz3Fl/5zd/iSz/5JcrlTboHj2nthbQGAbfvnSKUIJj6WJYJRkKWZqTxrCdTrhbAiHn+lS0i5fPs86t89Su73L99iumAKQQGCsswCVSKMDSmKYkTg9EopFC1sF1Ipyl5s8yljYssNhbJ5XL0BmPev3GfwaCP0oIoikAp8p5HtVmjMbeIsCzGkxFJp8vp2Rlaa1x35gQVZhl2DINuF1so5poNwihhrtHALebJdQdopbGkYOy7eJ5DrVLEtgxKxQJSmmBaREmGZTlUanX6Z2cc7u7PSpM05v54hGWYnDW6XL66xebVK7ROO4z7DzHIULHGsuXMANjW1OtV4ihj9/59FlfPUSw3iPwxxWIe23GpNGpcvPSPefToEXz729iOzaPHj9Eyx/7hCdGgy8q5+Y8Zwv9uPYX/RAjxHzBzav5lrXUfWGYGh/mzc/jRtf/T+T9yHxzGYcIH1zq8/nqbdNTArbi89Nc+xbDd4+T+iN2dfYKpz1H3bCYr7R1y6coaWZBx2BsjtJ49Els2MxdsRbdzSrlSxbIcDGEgJWiRIUhJ0inLzQW++IUf5dG9+1hOjvriChJFFIz45Kuf5eDxI4ajDtF0wGjQxzA0nmOSz+VRaFrTALTEtWykYWAIB9uQKJUhLQvDdshXq0RRwNPPPk1zYRHfDzHdPFpJWt0uf/y1b3DaOkZKyWTYwZNVRr02aZSRZBlaGh/tcAiCYMxZt0Wne0qcpVSa83iOxdTWxEGKPxoRhXVK+TxndBGmxDYEphBkaYJGs31xmyRJUGjCIKTbHzD1fSzTZGV1Cce2qJdKdM7aZJlgrCOErzAjC8e20Ca4jsfD24/YfOIiBw8OGT86IzYjYmFx/8ERo9F0VqtrTZZl9AdDhBQ4QrO4soiVl6TxlN3HPlefXyBNcxiGQBqCLEsRhoElZ43HmUYgJUxDTASOaXFucY2FhVUsyyOLUqqVKkLafOc7r9MfDGby5jhBCYFpSVw5a6jGUYrAwHE90iikUCgwh2Y88fGnAVGcApDP5ygVCmhD8mhnn3G/TzgZsHb+HNuXt1lZWyYIQhSzMqxeq8yWk6KQLE1JtUQLSTiNcHIeoe/jmRLbMSkYHnGSoTS0Wm26rWO2N9d5+oXnaTSKdFpt0jglCmNa7TN01qNW9VhYWaTanCNfanCwu8vJo3v0O2fYtkeuXGVpbZ3myhpf+pmf4e6du1xutxmMQv74a19FkFEulT52YH+/SeGfA/+E2YbyPwH+G2ZQmI99/iL3oVAoakPZxL7BjXcf0m3fZuvCAjJvYsoSiRGSpinDaUB/MEFriIOMD6495qmnNhEqwKnksMYxnuWgtWDkD4l1gGVDuTyH61qYdh3fPyNUEZPRgP/sl34JY3DM3qMDFs8/TW1+gXHnmH/zz/8V7XFEfzRmY7mGRFAp5XEsGEuDUrmMtEyGE59pECGFIkxjCrkiruPg2hGWZZIheXB/F9t1GU9iDs92iBNNHMdYUtA6OyP0R6AyFLNxYqmYo5SziYIelXKROGVmsqI1k8mYiT/GMAyWlpdwLAOpZ8Qo9dH+otQpaRJhGoIkS1EIMlKkNFBJyu7jXaa+T6oSkighSBRCgCsEOUuwtrHCfLPMZNhjEickiaI7CJDSwJSSXM4hRaGUxjQK7OztsL5Qxynm+dPvXmcyiTGkJFEaxxIkcTgbCaYp8/N18rbFZDDBsAUnxyO8fIF3Xj9mf7c9ay6ms3IySVPSMMCUHp4By806i4srNJsreK7L3sExx6e7qCQm73msbp7j3OY5yq1TtGGgsgzLcnFyObIkxnFtEJLdnYckaYxWkNZT5upVzq+vkSE4ap0xGAw5a7fp9AfYtkPRc4lDHwONY9oUnzjH/OIcg/6I6WiEzDThYEoEpFmMzlJG4zH9wcyVe3V9la0Lm8wvztPefwxZhiEl4cTHFpr+RHPtxgOCKODlz36O85fmeXzvFt1uD1taZGjyXg6VaobDIVV/zLjf59HDHbqdLuVKlcJwRDQZIo2MuZU1lhZXsAyHrYtFJoMzrr//HsE0/tix+X0lBa31n3cshBD/I/D7H708Alb/wltXPrr2V90PKS3eeG13lk1LLgd7Z2AI4uARly88RWc44vSsS5Yp0jiCdGZRdufOY8rFPG5BUi6VSTJFJgSNuQad7gnjYIjtehQLVVIlMc0yfq/Di08+xU985oe4f/1tMuVgeQUO7j9k2Bvx+GTIzskZplCk0yHlcpEXP/0qR4dHPHywS6Y1nutQLhaZ+AF+arB32qNWAWXnEDIEBc+/8AnK5Qp//CffIwhDsjQiihLiBJbmaowGXZI0RWJgSYOjwyMqxU22L2zhHRywsrrE/tEJJ60eGAYIhUoVhiEp5V0MpVBJNhuDqQxD23ieB/0RpmHM1KdpSgokcYZSmvFohBBgGBIhFNLQ2KaBZWgMqdA6xZBgWhIdxciPOAVSQprGWHaOIIyxLJvW3mMiEbFz0Ofw8D5pkiIlZFGI7VizXoehydkmy80mrmmTs4u4SuDYApFMuXbtEeN2D0dKlCPxbBNTCtaWFriwvcVTzz3NSy8+j1QZxwdH3Ltxh7fevsaoN6DoFCkuzURI5WoZ07SJg4ggjmel15+VeI5LrdFkMhmjVEqWpMRxRjCNaaseYRCScx1MBBsbM47DNAgI/SlKZcQKTs4GqDBgvlFmeW2dYW/IsDtGGgbC0GRaYxgax3EoVWak7yxLmHTPWJxvsvXENusb66RJSuv4gEHrmFISM9nZZxxGXL/xiDhI+eyXvkB9aZUoiPDHI7R2GAzHDEcjNq9cprmwwMn+KWenbdJMcP/xMQXPYn5YRRkGWQoak+O9h3S6Lb78U1+iVi5x9/rHU0jC9899WNRan3z08qeBmx/9/bvA/yqE+G+ZNRq3gbf/qvtppUiUojpXx3IUUTSl2+mRL+ZpWEVM22Fnd5cwiTE0JGkyKxUwCCcZhZzB0nqD03shWRTSGQ0pVEpUik38YEDg9zGROLk6lszRKC3wj/7eL9LvniE9j367z+jda+RzNu++8RqTRBArQazh8CzAvXfIg/0uSQJ+4mI7Jq1BwDQRKMui6HqU3DxhENKsV9laXyQTBksrK8wvNrhx6wanJwGZtMmUICOjubBArDNaZ12UNkmzjMP9Fq5ls7GxTLVZQyAolCrMN8/QAjIF/W6PVAhKpRxpmqJ1ijBmPpe5vIVpS2zHQkqBzDSGlCg1U0hGSUCUJoD46H4ZQkCmNAaa0WjMQhRjmybCAJWmGAIck9kcv1lnc3uTg9Mhw9GESxcvcPP+LvunJxi2BSpFShM77yAQqCghjmJe+ewlFqrzXH/9IdWqRKWSNPRxLZN5afLln/4Rntw6R9lziJOEOE5YXV1ma+scS5vrlJpLpFHC2voCn/zUM/z0z/4U9+/v8Nrr17h27xHt4ZDpNMGyTE6Ojmd+lYkiJcWxBJ5tkSQxS6vnsM+5nJ4c4o9H2FJTKeRJlOKsO8Cf+hiORb5QwCuWGLTbxGGAaRjkci5OIY9p5ShWmmxYORxpctrq0OuOsB0L2zDJ5fIUSx71epkwDmk05yjXmliuQ6fXYzyZsLC8xsWrV8mSiJWtA+7cusvp8Sm7e4e8873XeeEzn2FhY5t7Nz9AGrMSUhgGTq6MFoK5hQbPvvQCNz+8Tac34qDTYToOOTvp4Fk2y5sXcb08ezv7fPMPfp+f+7s/T7XZgN/47Y8V398v9+GzQohnmJUPu8A/ANBa3xJC/BvgNjOc3D/8qyYPf/49GMQRRPGUxaUKw8GINElJtMuNg7sz2ao0yNAIIO/92WOsYuqHHO9NSGKNm3fwQsmk3yeyAkzLxLIkQegj7QKZMviJz/8I4WBEWycYaYTtenx4+wYP7u+g0tkjt04SEi0wDZteP8DojfGDKY7nkcY21UqRK1tPMuq1WGg2mExDPrx5G992cVfmKZVKzC8u8+2v/xFn7T5hlBFOI6TjYUoDL5/nyatP0Pv298hUgm25ZPGUdvuMzc0N+sMhYZxRLhVpzC+SZSlxkuLk8sBMPt4bDBkO+7NV2QzyhSJIk+nEJ81mlGmtMvJejrzrEgUhhhYkWpFpPfPB02AYGhAIIdFCzJKMMECnoDLmV5apN6rYpo0fpuRyLsow+N77twmjKY5jzxBqdh7XspmEU/zxiMX5KpeeOc/c8hy90xFaC/Yf7bC1vgRmgc2FRf7+P/1Pufr8FcJhh7PTQ/xRQBzGaJERKTjcOSZ9cMD82jqLK6skOkUbA57KFahWqxjAt978kN3uAULO8G5ZpgFF3rHwPBvHsgmDgDCcki+WaCRNsjTFtG0WFprk8x6tbo92Z8Dde49RaYKb92hUq6yurFAu57GloNGoUpmfJwiC2dZnlGBoDUlERoqVK2EaH9Gjli+itYHlmDimwaO7Nzi+f4ezzohpqmguLbC0usby6jLNpSVOTlsc7R2SBhM6rQ75aoPNJ58h9EcYQHVuHsfLc3rawbBMGkuLXM4ytE45Op2h9mRq8sZr73J5FDC/uspnPvMqOw/ucXx4yE/9zZ+FX/xH/88kBa313/q/uPyrf8n7fwX4lY/17X/+GUUSR5imTaZNHu+ckmYJhikYj0KSVKEFmIbx0UKOS2zEGEohTEGaaEadKflcDjOnWXSK9HsjxuOIII2BHDnPYTjqMVdbZjzK+O57d/jSFz/Hd773On7i8P6NuxyfnmABC80apor/3Bl4seGRt2Bvr0vOEmgdEfbGZHWHS09s0jvrcnp8TBAEDMcB/mjA0tIKn7MhZwomoxFxpomzlCyYjdI++PAGP/LDn+aVT77IrVt3GA+nVMtlXnr5SUxLsn9wysHRMZVKibn5Ju1Wi36vR7GY49z6MrZt4jomK8uLhHFKkiWUygWEglq9gmFq0Aa262Ga7qwXIUCjSdUsCUhDzvD0Agxmu0OGlAgDkiTGQLO2Ms/ifJ2hP2WcBbTOJly9us0T25u89tb7FKsFUII4TgmigKkQOJ7Bs5+4wNUrF5gEEXE3YbFeRW9Mee6FH+eHf+zzLCzWKBcqHB9NeP3b79A6OcG2zFmiygIcz8RxPJZXlmksLSIMk4PdI4JpwGDo0z3rMR70kZbHyuICWrbp9sdoA1zbYHF+jny5gLRsdCYgA388od/tUioVuXTlCoZp0Z+M2ds7xJ8GhFFIyRGYromhEwanRxzvPqRSKrFYryPimGqlTLHWoFSssLixwdxqwmowazAaZJimwfLmBpkyaR2dcnq8TzKdUHZACMjnbGSo6R+28Dt9dswPKJQqBJnAtFwWVy7jFMszd+00ncGKlUn7tItp9imVSzQWFqk3V5iOxlx95inS92/x8OFDgjihOxrSH/Z4+ZMvcvmZp3GKLr4f8eD2g48djz8QG41aa+IoREoby/TQWYShQ9IoYToOsY0cGkWSxkyDCNsycS0T1/HQhiCRGdIyCaOAWq7C+e0VHt7eJz2YoIUgTlLGEx9pSHRxyv7+IaEy6H/l6xzu7mAXCgRRRKNSxVAZqytLXL64zp0P3sWWsHV+ldDvc7iXMez1SYWJ1Jrr731At91ma3MDrWIcKTEMyWAypqoED27dYPfRA6r1CnGc0RtMEFJTzrt0ekPef/d9Xn7peZ5+WtLpnOFJi3KhyM7uHqcnLVSq6XV7dDqt2a+n0hRyNlJoTK0o5T3CNKNkWDi2y8gPSJOIar1KoVii0xvS7Q4Igh6FnKSUL3CmZnv3tpjVwEIYCDXbi4/imDSJcGyHpaUG5zYWsV2P01aXg6MWUZphOy6FYo16w+O9Dz5ECk2SxR9Zl6d4tRLl+TK5qsPE7zPp93j2yhU+cekF1v6jyyysnsOybYQRMxlMIItYWqixvr6I69jEUUCSTHFcD9vNUWnWCaYR7f1jpmGEUjOEsz8JOD7tMJxMqZbyPPXUpxlOply/eZ/BaObQ7bf6ICWj0ZA0SUEpLGniupLti9vUGvM4+Ry5rEqxWsWyTCzLoFAs4BiSaq1MnKQMh2MiP6DQqJNJh6OjU+4P7jHsdqjXyywuLVJu1JG2iW07IGx2bt1g5/ZNCqUiWaYIRgnzC2s0Fw0Gk4CDkzMO9g9IAx9THuLk80ynId2VdZ58/hOEozGtgx2kUEyCBLKUer1M2wT0c9TnV9l+8mn6rRaWYdCo5Lj/+IDRaIowHfZ29pCGweL6Kl7Omcm6P+b5wUgKQJalZCrFswq4rkOnl7B9YY1msc4f/ME3sFyPJM4QWmJaHp7n4Tk2QgrCICSKY6Iopn00YdyPGfsKw8ohBTjW7P5p5HNlvcLW5hp7rSn9/oALF89zfNyiUcwxHI5xcwWQDtLO8bnP/ziP79/EzrmMRgYKk4QMfxqT9xxypqB1ckyzUeWF557hrbff56jdpZR3GfUGlMoVqo0qG801bt+5jyUNDM/GtHJsrJUxbZsgTFhYWGRxaREjS1CJz+nJCYqMVKVEUQIiw5YGmdBkakaC0pbkYOeQvYNTlGFgOXnSJGb7whaalN3HB3T6Q8I0wRAmeTeH1hkSgW0oFuYbSCBOEoLpFKUVec9CZxFkJoW8Q3/oc/zoEN8PSZVgGqfMLdRpnXXwx2M82yYNYwxDUGnmKDZsKrUCZIq1gsfF1W2sjf+duvf4kSxd0/t+3/EufGakt1VZleXaVLtrZ0hhqCGlBUEtSFB/gaQF/wLttNZaELSTgSCAEglQDprR+Ll3+vbt29Vlu7LS+8zwEce7T4tTc3EFEZgWRwIuzyoyMhAnkBnve77zfs/zezzazS69Xs50+o7elc/CYpulrVWcehNjGJBECf50yuU0IPRDDK1E1TUWFhewPIcoyqg1m9hIVKXycLQ6NaSygGqbnJ9dVlyJZgddqIymPsUkeB/mqqEqCmmWo6uV/kERlcMUUVGR0iKrMjVNCxSFpu1Vqy7NxKt7dLoupmmh2ya94ZDzd+8Y3N6gazp5ltPptFheatOqO2RZwd0Huzx8+gRJwe3pKZ7nEsxCDo+PGdwO2Ds6YxQEGEKwvtABXSPNUzQVwtmI8WRKHqWMxz6hPyGIIuo1l8lsQs21cJy3lFkOaxvEpUpnaQVZFsii5PisRwFMoxlnRyf4sxG/s74Jxr91LklIsxQZ+JRSwbEcdK1D6Fv4uoJuOhQ5KIqJaWkYhkqRp4yTAFQFU7dAUdGFRhxWenhBSZaGCFVF0TTiMmBluck/+af/mFqzxeH+Kd9+84bRzCdKM1a7c3iGAEVnOh5z8O4dK8vz3N++i+vZHI7eVtRpIaokK0UhkRJN0Tk+vaLRavHo8S7Fy++4HYzQZMa9hw8xHIef/eUvCMMQXVdQlRLHNdlc38Cr11EUODs74/z8Es81ePJoh7WNTS6ve6iiACEpCyiEoCwzLF3F0FWCtKA3HFIiyXJJmE2wNJ3ZdMLS8gKmpVHIAkWzKIvsvenGwtFVVpY6LK+uomoagoKiyCnzApDESUpaSPI0Zdgb4Ps+oCCoVhRezaF3c0s0m1Cr2Vz1R6wuLPCf/LP/mMvhBRfvnrO9sIKdCeqqh27XmQ5meC2PuYU261treHWPQX/GdBhwsH+ILHI8x0LVVWzXotOu016YJ0lK9l+f4QchiqJi2no1v1ANbM9BTn1G4xmvv3vHdc1iZXmZJ08egqqwf3r26xUliqDVsLFNm2arjeWYuK5HkeVcn55yfX1FmGQoSkiBJDR9xhO90gxkCUWesbC0yL0nT0BRkUIjzUuiNMYPY8ZhjMwzmg+2aXU6nJyccHJxSWuuS1wqTK9vuffwPnmaUfc8lrpzvHl7SFKUaLpCkefULB1McFstLNMmlYKsqOIMzq5PWXyfWXrTG+BHMf3+mPb5KRv3P0DRG0SlhmIZLC61iKIQRZFVaPPcAle9gPlF93vX4m9FUxBCgMzJU59USPI0RtUtzs/7HB6e4NY75GmCSkFZpGRhRJiWKJaObXhVpHeeUbNM4iRiMBhjOzq6JSjzymijq/B3fvJ3efz5D/nn//V/i+fofPzRDn/4Z8+YRAJrGrPcbrO6vsZoPGPU73N8fEIaTvgHv/93cW0TU9fISokwc2quiWbomEIQzAJev97n008/4v7ufazjM6IwYTAcE8QZS0sr3Fxfc9sboaomd7a3abdbxJFP77rHs2+/JQ4j4iRjNvP5yY9/gIrgF19+SZqm5KqoLM66xvLKEgKF67Nz4iSlFJWDz9A1VCHp9fvMLXaxXBeEQJVVnJzj6OiqwsMH27iuy21vSH84/PVcQQB+WGHPVlaWaNVtNtdWCJMTgiSjkKCqCmkakWQlSRyzurHOba+PUpQk04LDZ9eMrgLaho67toLTnQNKuvMaC4urzC90kYrg9npIUZSkcUDdsxDAXLuGoamYno1b9wjDjJvLHqNxSFIILFtneNEjDnySMCCXOXFZYDgmaxvryGRKnsVYus6juxsYukpa5KysrWN6LrIsSZOM4WhM/7bHbXFDd2GBxZVlEJJhf0gYxRiqRl5mzMKMNM9+LZga9vpMRyOsWhOpKtV8qCwpZUEQF1xPA25//jW2YVC3dGzH5O7HOpsPn+BaJq5joGsqj55+yM//6E9x7UuCwYhQ6thCIlSVRneRVneVtJQMRiPOri5xHZvhJGI0OsCrOZi2TnhyycXZDe2mR73VorN8l8bSJp3lTYLZjNlkgK4J6rU6K9s7XN34/Kt/8b9+73r8rWgKCtWwKy9ykmhKUUgUw8YyHQwBWRJSlhlpkVXLZ11hbbOOlBo3Vwmm6aCVOsLQIE0wVAWBRugnqEJiOpIiSdjducsv/vRPuDk5ZGoZ/O7f/z1uTvdQNAU/K2h0l8lRqDc8ugsdTs5z+v0Z7/b2WVpZ5ezoBE1RKUSBgqwQWppGtzNHba5NoWkYrkOr02E6O+dnf/5zZuMJP/p3f5/ecMjx6QWN+S61ep2T43ecHR8znU2JwpAsk5RCcH51w21vxPbuYxRd8OybX3Lbm5DkBStLC8y1W5yeXXNxeY2QCkVRrYRlCYquoCqCyXhMre5R92pMZwFuzSUMQmzdpETwzYvviMKkmsfkOWWRV4rM96rCo4NjjPubGKZarSKKkiLP2d5YZme1i2PZZMU6c5051uabjKYR/9M//xf4QYZla3z17BV77w5pOzqdTpvPfvoTCqlwfTVC1xR0Va1wb6ZNo6ERhjGTWcq4d0lzoUknnWPaHzEZjEAYJNOI3mVS5XX4U9JwSjD1SUVBLjUW5udYXLrLXKuNhoKmK6zf3ebrF2/o9fr4J2dEYUAShoRxCkJgqJDGMRtbWzz56GOGwyEnR0fILAVVYTz2iaIU09BQEFiuBUBZShqtFlcXJpnvk6cpcVZwch4xX3ew6hLXdrF1AwOBZuj0R0PCaQWiTZOQly9fMQkDgigiD2NyxyIPfAaH+yxFGVtPPyEvJUKoDMczivfnTZIYy9YxDZO0yJhEAccH+3RWtynznNG4j22ZtDpNHKeOFAphnFNzNQ7evvre9fhb0RQkkiLPSbIUoVQ2Z1UUUCTkRU6epWRZRpolqHrlQb+6jtlY66AqIWlSYDs2o8kAxzYhyijSlDzLCZOEWSioeQY3R0dcJylpJvnk0w8quejxAfbSFrKQHJz1sCmIgz6tZoOoVWMwmnHbD1hc6GDbJlGWkhUlQZygjEdEukXNMmE0xvEcDEPn4PAI02lwebiHpWrsv3lNq9XBNk0211dQVUm/3+Pk+BhVVZFUUuYkK2i3mrz57h0Hh6c83F3jd378Qw72DxnPpmxurDLoj3i7f4RE/bW+QFEq45MEZJYxvL1l+/4u9XoDhEQVGtMwwTJC4jgjTTIQSmWaEkpFkRZUykPA8zwadY8kKxASmqbgsx9+xOMnDzk8vuL2so/dbOM0Frm3dI93L19iaCGaHhLHESVUBGnhYjU7KIbJaDiiyCSeW6N3e0WeSzqLq8yGQ5IsQzM0oumEIC8pFJtGo0VLURlcnpOPr0n9ENVp4Ng2iqiR5jn9q2tGozElJfOdL2i02yjA5ek5/ctLrg+PuLwdEsuiupgIBSkUFCmQmkacxJwc7EMJa9tbfPhJhz/7gz+g3qhj6QZxUeWLSFUSRDOSOMSpNxn6PrPZrAq7yUvyosA0Kh6FphsEUTUQH3/5JRvjwiuyEAAAIABJREFUKYsbO+RCIUl8wumEhe48QZiRvleiZmVJy7TQjArZF0cRiqqh6iZqnuOHIZomEFGCZerYho4UJVIoJAUcHB5xureHEk+wbZsw8rG8JoHvs/XgCfPdBT54vAP/8vvV429HU5CSJE+QskRXDSTVAMhyvPfy3glZkaJqWjVQQWE8iOjdHOG6Jo6pECdUevMkw/FckjBEFAWe5zENQuJYJfRTbq/OWV5d5d6TXb780z8mLRIWDUl/fEXimsRSwTbrDIYjFueapGnKeOaDorO4tEgYJZSOSpIlJEmC59YIk7jKYJjOqK2t8sGTR9SWtjl//hWGZfP8q1/y8Ref8eMff4ZbrxOGPrOZj2lbRFFCUhQIRUMRCv7MJwoC0iTh4vyQlYUO3bkObq1JmZcISjrtBsPpFMs2K8l3VuInGZmkYgEKlVIKOvNz2LbFwcEBKApCEbiOjWubzKIEWVQmKENTMZUqSzLPC1xPQzc1kiTmR5/e58nuDtNRwM//8jkXwxBNM1h0IC0U/KEPQmfqT8gySZZlZKVGoaiIWGIPfOIkxzItijzCD2ZYboNmp4um69i6xmgyIgxDeoMpiu0iFIM8EwizRmt5m1pzgTl/xMXJKcOrPqkUqCVYusn8XIckjohmPrquYegWURShUnB3e41MlsRZdWGRZUmW5RXu/j0XNFdzzk72iUKf7d0HbO3c5/b8DM8ysTVJWRQoisAwnYpkJSVZElKkIaqQJGWOEAJZlgzGPlEY06w5GIZGp+ny9sVz7EaT7vIGimrR6bo0Wzn9gQ/KLUIUSCST8ZS5pS52s4PMFdIooiyK94pXQEpUQyNJE9JMp91ssLy+gdXsMOoPmIz6ZGHAYHKGH0Q4ls1c3WD34T0UTUPR9e9dj78dTQEoyxIhK5MOmo5uCoRqoCkquh6TRDOkqAZ9ZV6g6yqO45DmOZPpBNvOMByXOArxBxNaNQ/NqP6plqbS8hyQBe35OShy3jx/jqZplBQ4lsqcC2Y5Q6st4Acldr3LLByxub7M6dkZ++8O2b1/j2gWEMQx0zRhNgsZjSegaqSlJLm65vDskk8+fcrdh4/wj97w3ekVt9OAhfMu6xtrTKdTdF3HNDXSLEPTdaRaaQosQ0U1FPwghVJQBglv9g44PD6jlCW7u1tsri5Tn5tnNJmRpikXVzdk0wiEiqJoFEC90yZLU06PjzENA9M0yLOcIi+xLQvH9YiKEp2SMq626kqhkJcS3VDY2liFrGRzrsHTR1u8fXvDl8+PSFWTLCugTCmkwmw6wzQtxrMp/UkIQqXICzTVRBUqskhp1z0azRp5ljEdTzFtG8vxsEyVerMGDQthSpq5h26opHlCEsxQS7MSImUZuudgCljetPE6E2bDW/zhgFjNmcQRjqbQqLkouoFp19jaeYBpmHj1FqVQuLjuEcQxQRiAUCiSlPdpIyiKhmWazMYDzg4PePjZ59i2zenb16wsdrBsm878PPPLK6DbTCYz5hYWqbke15dnTIYDykLihyFhlpMUksFkSqfmkqYGUghm0zHtxTUKRcMPfSgFbq1WyZJlySSMMOw6umXj1OoEYcjZ6RFSFqRpgqDEUtRqG95SsQytUr2rGpph4AczbgZ98jTj/OKGOKmk3WVa4+Wzb/j97Qcsrm9/73r8rWgKQghsx0ZRJEmSIYX+fttIQZY5ChJVqGRlgaqplKJ8v+8sQa0kuHkaYbu1qlEkCrMoxNIrPUGalriWjVfzcBsuNydnKEKwuLaO59TIy4KNtUUcy2Ka5Vyc90m9OjXTJZcai915jo5O0HXJw48e8+LrZ8R5UW3pxSGoGrNJhluz8HSLn3/5CzLF4+3ZFZe9IbVWk858l703e7w7eMf93V2efvQJtu3S7/UIZz4IsCy3us+PU8IsRyJRFYOsLDENjSjKkEKp0oiSnJOTC5I0I80hR4GsxNYt3HqT0+Nz0jRBEZVSUVUhl1AicWoOY38GlBiGjmOJKl255rK0NIfr1FjtNvn86WNOz25Z3b1PYtR5vXeGV2/geA6d+YUqzyBPWFhYQCtB02F+fh4UtSJTtbs0GzU0VaHTXqBVbxL6AaZTEYwtW0dRDNpKyeG7Qw7fvSMOZkyX5nn89GOyLGPQu2J0c4lpGBUyrhC4tTZZUeLEKbarkacZaTAhGE9IZjFXF1cc7O2jqwpxEjMLw9+Aq4JuaKiqgioUlFJSJClS5PRuLhBFycLaJqau8vTph9iuRxCG+NMq9+Py7BxVU5ibn+fOzj0UVaCqGuenp1xfXjAZDlGEiu06qIZJWkgmoxmD/g1pnEGWc3Z8wmQwwdB0/ChBCBXLq7O6tUuWS3rXF4T+lCiOiZMCRZbouo6qSJBU5HBFoBsqZZaTxBFhGBP5PrLIUUV1SzmNEy5u+hy922Nu9c73rsffiqagCKXCn4scT1ORUlCIsrpHUzSQ77u6qpIXBZoQlCqgSIQQaLpOUeQkSYhuWFi2QxlKwjDBNqovQ5SE+FHEq1dvefJgh9FgwMvXbxFS4lgud3Z2ETKhlebkccj1LAG9QRCFeLbFxvoqz77+hrr7Y3afPOTNqzfkRUaRlTiWgejojP2YtABZxBy/ec7NeIple6wtr1Kve+z5U/zJhBfPn9NodPj4ky+YTEecn16QhBGqXm0vRlGEpUuSNCfNBUkpkJnC6ek1i0uLtNptpOLgBxG93ohEZlgVPYHu0gKu5eEHYZWfICr+YlpWuYiKJnAdi7yojFR5UaDpLh9+9Ih6zWE6DVHLgh999pQXz/bYevSYcZTgtRO27+rsH18wmuUM/HMMVcVzHNbXltn64ce4joWt6YzGYwaDCbPBgFn/lmmvx/rdLbZ3d/AaddT3uPvezS2z8YQsiTh+9ZrJTY8sj8hin+uLc7Z371UNwHA5PTnE1nXqNY8iS1F0g4XtOzQ6TdIoZm5phVKqXFyc8erlt5weHVHzHEopsFSFsR8gFAWhKqilQGY5QhNkMsPQTRAKjmejagaeqVK/94A3r98RDG4Jwhm+X8X2yffU5tOjPdI44uGjx9Tac+w++YDHTz/l9OiI0fUV0/EIu95kZa7L3OISsyDC1Qyay1v4UWXK8jybse9zfn6B7XiYjkuSZsxGQ7I4JC9LoijFsnRQChTdxHVdbNMACbZpkWcZw9seopS/ppCHQUCRJaRKSX805pdf/5KHyb91CVGSQqkm+mmZIoQOZUoSzhC2g2YbqImKnpaUEpI0wTJNVEOjLCVZlqPoCnHoU5YVMMOy3IoGHVeBoJ32HA+fPOH08Ay3YfGrX3xJWGh8/PQDdN3kzevX5EmEqoKl6Kx3GtwGCUK3CNKM+Wabnbv3uTo7Y/3zj1EVFV03SYsYVdNZW1nkjulydHKB70/p93q4lkWa5tRaDWRZDaMUoRCHMV//8ku2tu+wsr7JvYdP0FQDWSaMBj00VUGUKcNBn95wjB9n5HmGbuq8eXvAR08/wqk1CFNJUuQYqoLt2ZimxoPdHV682idMUubcJqqgypbMCwpKmvUaeRqztNDGcWyCmU+WZVyeX8HKEo5jsmGq/O//4x8gdZ3b4ZT1nXs0Ww32351wcnJCqRgYhk6r5rHcncN1LMLplLbrcH15w83tmLwAyxB4lkEwnRKFEWUpuL28IgwjNE2nLCR5FjEeDUnSDN2xSMOMJCkgith79jXdhWXa65t0N+5Q5JLZbMpwFNFqW6ioBAlQqgwHY2zPYWlji0ZriSQJGfdu+O7Ft4RRSKKrJBLKvEreLjSFggJNUWi256h3Wmxu38GfjBmO+rRaHRzXJphILi9P0VWNIE6J4gxd1dAtjTTPefarZ9i2yf3dHRbXN1hcXmJ5dYVxf4DneRhuDT+KiGYz9o8O6a4ssrp5j7XNdcb9Hm9evWS+O4fnuURxyP7eO4LpmKIoUYWCJEVTlep2q+ZScx067SbdlVV0x6XIC4QikRRYlkGQ5ZRCVCtuJKZpcHJ0RPb/oikIKeX/f9X+PQ/HseX6aoM4LymKkiKtCMSGbmOaHlDBPaWSYRgQ+VUkfZFDWeQgBeL9/ZksAFFiaBaGaYECs5lP3TH5Z//hPwJNo7vY5r/5L/8rvvjhj/jZl19iGiYfPLnPz3/2C6IoxzQK1hbn2Nre4uXhgNKZp9PuMOnfsrE0R7OmUSZjaqbO189ekpRUmgBgrtPg8ZOHFFKlNr9AlkYEcUQWJnz95S84u+0RxIIsl3QW5kjigk6rxaeffMDP//LP0TSVtfU1HM9D1QR1z0ERgiTJ38t8c+a7XRTb5uL8grrrvXdUSuIg5PzqimffvmMyGtJs1bB0FceqYddqJFHK50/vvCcPK8z8BBAsLCww9UPapkVNV/GaLm67Th5lPH/xjudvDkmSklq7yeLSCrbrYtom4XiEkqYsLSzSbLd58OQBN9c3fPfyDZZjIWSJYeo8+fRT5pbXOD864erkiCDw8WdhFWSbzPjwg0fcXPc4PzkjjBJ8P6DpGawvz/PkRz+lvrDKi69+zpd/9H8SZSWXwzGBH5KkUUW8Ngxsy8ZQVbbvbvKTv/fv0+8NgJJ6o4Vbq3F13ePgzWvevHlOkWbUag0++PwLukurXJ6fcba/z2hww2w2JS+qWRRlxqdf/IAvfvo7vPjmGW+++SUoEKcFUz8EStr1GkkaI8nRNZW64/DxF19gN+cYXd9y+N0rVFViOTamYRNGKbahkJYlqumxsLKJ16jj2C57r15ydviOLM9QdZXpNMKf+tRqCmWRoxkatVoN17ZZ31pnfnmNPM3xZz7+bMbl+TlBEDKbzcjf395Cgee5fPDhh/xn/8V/97WU8tO/qR5/K1YKCIHm6BhpShzmlEBRgDBKZJlR8b8lUkCUJGQCFMegSEqKKKsGZVmBoarkikDKKm4tyzOEWiGwhNTRdJWvv31J96LJvQc75HmEPxkzKQX57g4bmys8//YtSJ3b/oitjTW6nsZB7wbQaTTmmAQJWTzl4vyEhzvrPLi/ydHROYquY5lmZdzSTc5OrsmPL1BNjdZiF6/msftol8FkSpLkFKrg5maIoGS+WUfTVRYWF3n1+juuh1NM00IRkt1723TnO4xHE5qdOSzHIghj1Kxgvtul3xsSnV2hG5XmwDbruLZDEfs0vRoL8w0UVArd4c2b5/zkB7sE4yrARNEM3HoHy3Ep/ICDb75FMWyWtra46zW5PLllcDOm5jXRXUGSF9wOx+wuLFJ3TJY7Lh882GFheRXNtKstUlNHc22yLEWUJaZrYzg2aZbh1lxqzTqt+RayrBp6GgVMRhM0RWVhYQ4oKlt3XpKrGoVmVmyDJCUXGkkRo+s6iqqgaQZIiVAEhSyQqobtNbk4veSv/vyPETLDtW12Hn+EN7/A3ccPabSbhNMptWadxfV1Dvb2efP1L8ji8D0fMqn4FLJEUxS+e/kt7fk2Kxvr3JwdMRgOKperoTOLY2ZpgqlqpEmBosAs9BlNJpj1Fm9ev8YPA+I4JksSbMPCcm0MXUdRVMpyxtnREZs7d3nw4VNs10U3TKQQDEZDojhFVaFWs0nTtOJARBFPHj9k/e5dgjABMmqNJp35RRaW17g8P+XkcB9/5qMqKo26y6MPPsbtzH/vcvytaAqqomBZBovLLstLdW4vfd6+GiMklLJAFTqKJkiKnCRNsS0Vy9IZ9CIaLY/Qn6EKizSOUaRCmqXohl5dRdCxdJ0il+wfn/Hm7Wvmf/wT7j/6iLOjPXRNJUtKzs7OUdSSza11To/OmAUlw1nIXNPi9PwSv1dSFMtYporh6SiqwTevDvjso/t88oOnTMezioLTaBAEAde310yHI0a9a+YWV/ng86fohkGzUWcw6SFQaHkWhqlSa9exa23cWh1dVwmijDTJ8Vyd8WhEmeX0+30ur6+xLAPLsphfXqbheiRZTJwm6JaO6TToDwLmF5ZoN12SKCEvFW5u+wRxhaETqsLy0hwIA6HraIbD6kKN5oJFW8yYYeB05tEMG6/ToDzRiKOIIC3JShXV0Ti/7rPe7XDnyQM0Z47T8yH1Vo2a53B9ecv+u0NkkSGkxNB1kq2IjXu7CMOkvbDG7ekhke8TpSn+eEIax/jBlCzLyPOUeqNGe26Btbt3cb06ke8zub1BlAWaquA6JkEYEeUSpUwRhUQqJZqm4Xh1Xr9+xcyfADmlInj+q6/QVEGt2eLO4w+5c+8+YRCSRiHJbEyahFWGRlEiAFURUAh0TSMvcq7Ojul2lxCKgqYqJEkMssBUFMoko9BLFCkp3hO10jDEcRzmuwv4xyGUCnEKWZagGxZRliGUCvpqmhbBZEqapsRRTBhFZEVBmUtUBK5rUbdtboIZju1w/8FD5hYqZ+zlyRkXZ8eYuonjeSxvbLJ17x719hyXh/s0mk3mltcxrRphHH/vevytaAplKYmTklIquI7DBx8ssr6i88u/ekEYFxhWAxRBliXkuUTRFQxNYpklmg6GY2MZdRStxJ9UVxIhqj17U9cIoxjXrdNqNmk3OyytLvO//Kv/me2NVRzHwQ/HIEr29w948vARc0/u8d3eHmWRoekulpqT+lfEQpB5TTy9Trszz+XplLPzG7Z27tLrTXjxao/VrS2WF7vUXJMkbXK3aXF5fsO7Z99yd+culmWRv7d/1+segmq/PctCVE3D8zxUNSHNUxxTQylyomCGZetVjoACumm8363RoIQky/E6c0RhztHxMa12k7OTM/yZj+PYZGlGIQUry3OEvo+p2xi2haHZLM+3ePzoLn6QgO1xOwwJ45Ik8omzkljy/t5Uw9ENlDJlfHWBGvpE0xmWqWFpFk7NxWvUuLrpcX1zjSbBVBVWVxfI4pg0nGE32gTjCbdXl8g8wfdD3NY8QlEpZEbYm1GIkuGgTxqGfPzDzzEclyROWFxdp1CUindR5MyiiFffHdLv98myGMc22NzaZNC/5fLsgLLMEYL3fwMdU7cQeYyhlBy+fUWnNYdVr1Gru6ysLtLvX6MVOlkakZclnlet1JIoQpYZQtOqzIy8qAx8sgRRVOQlITEtDUVRyaOYokhIwhA/Csjfp3FpiiTPK7euoqooQlIUOYZhoCBQhYpp6NUMyNSINYGqqjimxvbdLayazdLyGp2lFaIg4vjlK66ursiSBF1TGI1uubm9YGllg+7KBrsfPsWwHJK04PDgkMurvxGA9uvj3zT34X8A7r9/SRMYSyk/ek99fgO8ff+7v5JS/kd/0zlsy+Dv/e7HvHxxzOtXfebmAzqNJo2OgzKttlzcRgND8whmE0hhabuFYUlGg5wizSnJmF9YYWW55O2rfUBDN8C2Gxi6QatRJwgjNjbucHRyiVergZB88slTri7OqjThQvJu74CdnTt88vQJlqFzeT1gMq4UZQ0jJjN0ZplK27bpdrtEsyH9q2tEWTC4vmYympA/vM+DBw/4wz/7im5nDuv2ljyekecJ7UYTS7ui7tUwDYuF5RW2du5huTW8RoRu2BS5pN3pYFs6ipDkWYrrGihFCjkomsZsNEDoNkUJml7j/GJCFCUMR0MmsxlXNwMMQyeZznAtizAI6C4+ApSq0WoZy4uLbK2vEgQKYa6A4XB2cYofVhkaJwcnxEnIysYWne4i7WYLpcwYXl8x36qUivVmk2arTpIk9G5GjPsD0jRHmDqFplMoBje3AzJUtu5bpEVBVEqyNKfWaDKdTZFZgmPpKAtzXN0O0UyDzceP8OOC4KZH//qWg7NbuovLCCmZjUfMew12S41vopTBIEJVDVRV4+T4hGA6QzdUdEPDsTRc18Y2LdI84Ztf/IxwOqPVbrO0cYetrW227t7l7Ztv2X/+DMtUEFKgKSWOW8Ns12g3mxWLonyvodBVVKXANEw0RcG2LdI0QtV0cqGg6RoCQRYFaCpoqkJJiWYaJGmKrpsVRFhW8vQoCYnCAOc9XNUQCvVagzSLcD2D1bu7tJdXUDSDPC3wZ2OCYISuCfIUfN/HMDXMsuT88ABRlKzf/4Aoyjl6+5ab6yv6o+H/d02Bf03ug5Tyn/z1YyHEfw5MfuP1B1LKj773JwCEqhCEIWmcYFoNppOQ08O3+L7Asi2EqlPKgu5SE8vJubro8/xXF9SbFgoGulahxm6uY7bXl/j804c8f3FAkknCOMF1XSb+jMnMZ25unlevn2PkCfWGS5omrG5uo4qUJJpyeHzNy9dv2dleZ3GuydnZJVJU2z3L3QZXt5fc5DXKbhezsPDcJicH77i3s8lit0WvN+LN828oH+6y0HAZ9cfUanV6t7dcXd9Qay/QqHt88OQh7e4Sre4CmmGSJBHdbotPP/uQwc01cZIy1+0CJbdXl2i6hiwrdZvtWtSbLaSqsriyQv9myODsliCOKtNWmuPaNgiB+Z6IrCuCdr2FYTu0HJtH9zaxHJfXb445eHdMqzPHJIp58fKwWjWIgjnP4O7mNnMr22imh25orK+s0vnxD2k1XFQhMC0biSRNMg4PTkApubq8Jk1zNENnPKzMOUI3Sd/uk2UlkyBh2BtQswJ0U6Xh2GR5xixMsdwGbr2OXptjOosY3Rzy+tkLJtMJb1+9IEoSGp6DbVtMJjMMTScrVS57A9zTYzzXZdCrlJWGoaHqGlGUEoVR9d0tSyxDxZ8N2ft2RDQdcvfxJ+zsPqHdbJDnGY5lU0qJ12jhOl6FiMszPv3sY0aba1xdXzHo3ZCmKa1mE4SCKmp4NYd6p0Wj0ai0GZ0OsT9DrUGJS5mVJHlSOYJLAANN10CW6KqC1ajx8eefc/huj2zYx9YF9x4/4Rd/8Zc0mh6r23cwbIfu4jJxMKF3fYUqQApJEiUgSnS1rLgOpsXJ/msGtxekeYahqd+7Hv9WuQ9CCAH8Y+Df+d5n/NcccZzy+rtLCq3AcWDQy0hilW7XJo5zUHUURWM2hlqjxU/u17i+HnJ8OCJOcqI0JotKNE3lxesjFufatDoterdDoiBgOh1jqIIg2aHs3TKbBXTepwL9xZ/8JX5ccP/uBl98/gM6rT1evtkj8Edoyx10VcGoWXTn27iuzVwtIuoPkJlHqnlECAwikixnZ2ebKHhOfzTl7eu3/P1/8Hu8eLnHXHON1fUNzq97zM93+OKLSnWXF4LzkyMEYDoWaS5ptBeYW1ghjEI02yFPYwzXRVdVYn9MFIYIQ0O3ahSKRS5SSiFxLQMhcqzaApeXV2iKhqKULDU91tcWmYQZCJ2luTbtmktWaPzFH/2KP//Zr0gKhXrjBkHlfbCNkrpj0W23WL5zjyRVONvfRwgwyoy1jR+wvLWFpmrkeUoWJxy/O6TIElzXruS//oTW0iKWa7KwssLixl2CMGY2nVJrfohSSvzRDVqZIvMcoWusefcoCigKyei2z0QZsr6+ivtjk3Ay4vrikpkfMvUD9t4d02w1mZ9vEkURZ9cXDEeTaq5TswmCgDQKCWWOYVQhQVIWGJqOJkyEItENk7PjQ9x6nbW7D5hbXGb/5XNKJydOUga9Ppqukmc5ZSnJ84yd3Qcsbq0TjKeMhgOa7Q6G7YEs0VSFQipkaU7oT/nw4yd4jsXB2zcUQhCXJa7pYmY5WZriODaaWjDfXcYwLQoBG/fuYbouFwffUW+1CKYJV1fnpLFHq91kfqmG5lms393FcmpcnZ6SpAWarSIMDZVq9ZFLiel6CEVQFjmKEN+7Hv+2M4WfAjdSyt9kPW0JIb4BpsB/KqX887/pTQQCXRMURcks6SONnDKWTIIIw1bRyhJ/GqAqLSaDEtMSLC430FWP5y9OoBTYhs00CBCoXA18XEcjKXI0oWAaOkmccNsf42qgS0m3u4BQNNaX5nm1f8zr744YDiZ8+uEdfufHn5NmGXFSsH13izxPaTZqXF/dEPsRLVujLAJC3SLEowwz3h2esXNng48/+YDJZIQsJf1Bn/u7m5wfnWLXWvx49yF+ktOas9l7+YLT80tubq9xbRvDMJhMZ9SaddbWt1lcWcFQFDTLRTddSimxGy3qaUwpc/JSIUsyLi+vCWYzgiCqHHmDIZPpjEJCnkasPl6j3aoxi8coSkGz1mA4SXn9Zo+vnu0RSo2izPFnE+qeTZlEND2TpU6dj37yQ/rTnOM3b8jiBNc2qHku5Bk3J+c05+dxGzXyvMTrtCmESloK7pgOSZzQaDXpzM/hOB63t7ecHrxlPBhhuTZrG5s8ePSI5eWFaiJv2GRJzotvv+Ls4ABbxJSlZDwcUGvMg2KzYnoUWcL+3jt2du4AJVkS8+TDR+x++BH7e28Iw5DNrdVqJTEckacZiqIQzEIUza5AtbLAVFSQBa1mg+7yIqqu0z8/5/jtS8qyolCVskTmGUJRQVTw1IuTfe7sPmBufpG1rS2KsqygqTfX3FxcVOnUaYJlG2xs32FlYwNZpBy8fUOr4ZEkkCsaQkqETHn4+ENWNx8wGo357vUL1tbXWd++y/Ly73F5ecE3f/i/YSiCVrvJdDIkTXI63Xl0y2Hj7i6N1gJ7L18ynQ7RVY3V7R26axuUuaTMqxSyIIiqsNzvefxtm8I/Bf773/j5CliXUg6EEJ8A/1II8UhKOf1/NILfCIMxTRMhdBQRYKkWhZCYukYufSQaQVISRSoIHdczub2CwdAn9TOePnzI28NDjo8rNoBEVuz9SYSmaEhRYhomWZLT6bTp2Cpp3ebV3gE/nf+Yu/d3kZrOxdkl5D5CStqtJt9884KTsys6nTbb2+v0+0Muzq8J04JcKmysGZRpTmLOoRt1wiTm1dsDllaW2bmzRTQZ8sd/8g3NVo3dnW1e759w2RuRphlLq2vcXJ3zbv8QNI0wLtGMlCjySZMIkca4NqhqTFkKBsNJlXQ1N4+wa5iKgpaXmELBGmmI0mQ04H0RzFhsWgwnM0JRTdMvzq9RNAelKPnVqwtG04jpZESUpiSzMYYi2Vxew9IVirik3enw6U9+gtVc4uXLryjiEEXRWdtcwzat96afJsnMp0zwk5IEAAAgAElEQVRSgihA10xqnQXqCUzCE4IkYHR0ys3lLcsry5yfHREFY3RdkPhjbs8OMWSBpQu25++jGw79qyOSaYCuqtTaHcLQp+YIZDll2BuQZApBHOC0u8wvm8xmE+7d22F+aZV3+4cc7L1jf++I7burrCw7bO3sMre4QBjE7L38ltgPKEqJoKyQcKrG5u4jvMY8IAn8MZ5XJ4xC8qIAqZDnJRKBECDKKoX727/6Oe12m89/+lNMt86rvdec7O+BEMRJTJHluF6dZ998haEJdh4/ZHFtDcN2Odk/4vLiAkPJuXP/PjsPP+LFi+84OzxgPLwmmE6YjXo8ePopr1++wh/dsLjYZDb18f2IdgeODsbYrku93cX2Ojz89Asujw9I44jVu/cpEIxuhwx7F+RZjG5azOLoexf1v3FTEEJowH8AfPLXz72Pi0veP/5aCHEA3KNKkfq/Hb8ZBlOv12SS+qAKChmxszvH0dsxUrpkWU6Zq7g1QRSMUJQmti2IkhKZSRa7NTxvg/OTW4SiVgvgsiBLcxTTRBEqszBGVTWOjk/45B/+e8z61/z8q2/46suv0RWBP5mws7XF5vYimir47u0+UZSALEgiH0GBZVtYtSbTSURJZYBy1IRR7wLZWqTQPVw15NsXbxiOBzy4s8XqWheZlwz7fYTMOTw4pd1ucXpyyocffch05nN9e0MUJqSRimrplGhguBheB1VzOT/Y5+TggPZ8B00vCeMMSonXamF5TebnOwzylMgfVZmGXp1OXac5tZhNfAwK+kFOvWtzeD6hOOljmyaaXjkuDVVnfW2e7soiWZRgNBusbd2hNGrsvdkDwG00WFhcQte1imhtmJQCbEMnzaqQEcOw6F3c8ObZN5yfnTIeTcjySidwcXFOs1kjSkoUBUzdwfUahHFMuzOPYTiURUmaptTqLXTTIE5idNfDMnXiIIIsIvFDOt0lbK+BQOHBx0/xHI/e1QmuVsFhg8mAo5MT0jhmdHNN5M/YuP+Ypz/6Xd4++5LJcIiqG1BkuI5He66BqkD/6oJw1ifPczRFoGsS8pxSqT6XQFTJ1GWOqetMx316V2ds7T5GUyWlzMjykqKoXI9FFlPImNHglrU7d9ENF1V3efTxU+4/ekIYBTSa83z3/A2vv/0lRZ4hNCiyGIWM0eCWm4tjNFHJ3aezANt2mM78ykQXxGTZLU4YMTe3xPL6FnGSoqBze3XFwbvX5GlClmQUWUrNsr53bf9tVgq/B3wnpTz/6yeEEPPAUEpZCCG2qXIfDv+mNxIKfP70I/zklFHQ4/GjBZJJzotnA+y6xvy8iqE4nB6PiUIfpIOmO+hmxuHVBZvrHR7t3OH14UVFwykqEGmeV8OmPM9JJQxmPnvvDrm7tsCTh1sUWUF3vsP/8eYdcRyyvb3C4cER3313iGUZLC202Nxcxw9Chn6OO7dITY5J04wszfEaOoaS4Ic+uW2iag52vcV8dx6paGzdWScKYkzDQOgGt4MpuqYwHoyQZcEPvviM4XjAi29fMPUTUllQZBmz6ZAk8jE1hTRNUA29sk5nMBsOqdWbIIxK3l3mjG6vUIqcaZwxjmd4xhy23SQqbXJ3ieHVFbN+Qh6NeLjdJQwiylSwON9g54tHrK1tMJ7FzKYBqq7S9xOuf/Wc3mBEXlQMhH7vls+efsD6xhqqUmLZGpprYegthKIyHk7wZz5pmqKoILWKQjwOI/zk/6LuTWJky9LDvO+cO98bN+aInKc3zzX1qyqx5zZpmZa4EBekAXFBA4LBvQ1Yy7YBGd4KEGRYsBYGZBCEQYk2KVoU2XN3Nbu65vfqzS/nzMiIzJjvPHoRzzJgUFIZaAqts8lE4iJjEfjPuecfvi95JVyx8OMQxzBo1EsarQrzmUc1DNENG6da49GDB0S+h9QMqtU6bq2Fok5ZWkkpTs4Ip0OS0Fs0N6Vzdq7dYufKTQ6eP+LG1U183+P04pQ4zUjLgr3njwlmQ1a2r3Pt3ltMhwOG5z3yaE53dQXTdon8KS8efspsfI6uGczjjKIQaIpKJjJ0TVsEep6RZiVFWaLJnLPeMTtXr2KoAk0UIAsKkYEiyLKIVqvJ3bfuM7wY8fHP30fTTGqNOldu3qHa6nCwd8TnDz9G1VTiMMQyVHRdUm226J30KdMpqlpSvvKfSgmh71Nr1lFVQZHFTC58lCKntbxJIQxOj/fpnx6jlAVTb0oYRmRJgev+AnFsf5X3oSzLf8rCLv37/5/Hvwb890KIFCiA3yvL8t9bC5FCIHPBUnuZKEr5sz95iKotCM62WfL1r9zm88enaIMcEWXESYpU3cXp5QQcDXLczgb1ixikoCgESRov6suiQEqVNEsJopDhcEg0Oefu7duEUcx8OuPNu5dYXm4T+D41y8HSFRp1l6brMjg94/h8SqpVqdR1Lq12iIMJpSjJhcAxddJoSqFUmEsbx6hTrbawDEhzgWFp+EFIWmZcvbxFUpQcHZ/w4NPPGQUeb77xJm/ev890PmMynrG/t4umLWYkkjRDvurPGF4MqXWXaXY6RH5EXmTkUc7J00fEw4WKXAqD+vI6hWqTqQ5my+RsEoOqE85nbCxVWVlu0Ts95+mz59y9fYNWpUZvf58gzrn11lu0usuc94Yc7B+ihwm2pnMxGNCuOghRsrS5TqPVwXJsUFVCLyL2Q4ocKs02nZVVTo4PF92lRUKcp+SUTGYTwjgiTTI0t8APPMyZjj+fc3Z8zOalKximQaPV5GgyRM0LvKJgPhmhmw5ZLtANkzTwCCYj/HmIPx4RT0fcfP1LrO9s0WxWMJwKP3v/Q2bTMVGaoyo6/V6fwJ9x+c7rtFd3cOoNLFOhUm0ym0x59umH5KmH41j48wBNEURRSpEXaKpODouTvCxRZIoQi7t6GsVkeczqxhrHB3tMZ1MMTUVVFAQFd956ixyNJ58/wp+PkarOZDqkLFLe/eavL0JEQJykREmCjYGiGxiVOrP9z0niENtW2VzrolkGF6MZpmZQpCkpOYqho5ULX6aQBbrIUcqYIg3I0ghRZuRphGFYaPovtvrwV3kfKMvyd/+Kv/0h8Idf+NNfLUUVrF1VeO/7p+zuneFWGxgCEDmXdi6RBhm2qnL75haffXZGmcekicbeyzOklECxOL3MKpqhYxr2Aq4ReQSzIVHmIYVKEGeEaYrMUsIo4sXeMc939/gv/s7fZP/Fc/78hz/j1rXLfPMbX+bDn/2c/ckUxbTJpYkQkroeU1EhLVOGfobUVMLpkCXXwW24nM59vLLC0ZnHa9daKEAsU0xyokhneXWV4dhDiGfsnfQ4ORuy1G6xtrZKq92k1exQbzZ5+uwFQRCRFTlpEmDoGpPJhOPDQ67cuknJHEUzyQIfNZ4sTilUMiS5YmA1uziG4OikRzxPkJFPyzLZWltnMJzzcu8Az4uYjT0ePXyE5da4e/8dKvUlvFlEpd5g7aqGu9Th848/I5hOaV1ap9VuU6nWsRyXYD4lT2K86YxB/4wwLSg1l/byOhuXbvDy+WOqtQq1RgupLMpulUaDMkmp2jqGobLU7bCyfWlBXYoySkVn68Zt7IpLHkfMZmNCb4rMfaK5h67rCMWlyMuFZyKck8QmtmWwtLaBsX2J7Wt38ZKC/b2XDI5foDgmiumQITh8+pjj589Z29mhfukaaRzT231O4k3RdJUsXRCahCLQdR1VVQiCgFK8OrikitTEYgJbUYijhMlwTKPTxXQqRIFPkRdU6y5v/o130c06P/vB9zk73aWUGqBg6RZhEL2CpcRomobvL+YoyrJEt2yENJhPJ4RxSK3W4sa9m8y8kF5/hqVnqKqOoghEkS8an5SMaD6lfzZYAImyGM+fE0QhumFQr9Ww7P8w14df2MqykqODMVkCO9sraFbB+WCGoKR3MufK9Rp/6+59/uSPHiCEx5Wdbc7PcxALGnG9XiAUSRpP6Pd8Rn6daq2BqVnISgvTdCmLDKEo9GcZ13c2OZnmnM4KQtngL372krqjo1VX+GR3hOq26e7c5ODwDGm5iLxkpVWjbqZ89ugxEz+n2mhScxXKyMdoWnTaBknpMUlyXhyNsA2V1666qIqCoQhqlTpHZz55Lrlx/Qo/+vEHXNpYJgojTs+G5BSQ53Q7DW7euk5RJsRhTK1ap9fr4/sB3mRI6Ps4tTpFoVAkKWGmkthLFN6Edl2ycUvS7U741q+8zU9/avKv/s9PsdSSVqfB2PMIwpS80IjijGarwZUb19m6eQ+E4Kff+y7hzMOuN8ilwtalS1y7ewvbNLhx5zUu3bpHCcyHA0RZEscJ3iwgDGKePX3C3M/ZunmP1SvXaK9uIChQNB1/7hGFAYppkPshrZUlukstFApmMx9FKSjzEbplY5gOaSE4Pd7Hrdg02h3yrEAoOqHvM/cCLFvDcVvEYZX20jKGZaNqGgUCzTD47d/5Hf7y/U/55C9/wotHf4kuNMI0R3V1lDwinI/J0wghVUoK8jJDJlBkObW6S5KmiFJCmWNbBlmRI1kQvMsih6KglJCmKfvPntNe6lJrVNHKjO7qCu21NSYTj6c/eZ/5fLLIkUQppQBFqaDqJllWMLoYEocxRVlg2xaWaePYVZI4Yj73KJFouoHb7DIYHlB1TXRVkuUlaZFj6ZJ6p46iqTx7/JDzi3NAMPcCgjDBsW1M00JVFa7fvA7/4jtfKB5/KTYFSsmDj865fGkL11Z5cvg5mYR6o8b0IkCRJn/6/Q84OOrx279xn48fnWHZBlIYWLak21Xw/ID/5r/7DX7w3Y/4R//4x5wPfCqVGpZVwam6lPnCQhWFMSenfSq6QBEFFUtnNp1iKBVazTqtlsaz/TGqbZHoDWQusE2TVFpMM4lid5CZj111IfNRZUm1VkU3LJbaAjFOGUcmn+8NuXxDwR+HnB9PSIuS/iTF1F02l7v8p1+/zzRMeO+DBzRbbcbTOU7FwrBfJ0kSKEt0SyUvUhQWRKSV9TUQCtPpHH82Yjz1GMYGeZRQaxR86etXWV4RdJYTpBVxcjLG0lQMRcEwLU7PR8yGI37zN3+ToijoH+3z2pe/iSgUfvQXf8rFoE+SC4aetxhYyjJu33+XtZVLGJbC4PQYTYIiCrJccN4fIaXAD2akcbLoBFRBN232nj7laPcpJQXRPCSKYuaBjxSSbqfJjZvXmV2cc+nyOppc5IGuvfE2VVXHNG2cSpU8CsikitQNNNMgiCLKUlCrVPECH6disX31BvXWEqpUiYM5s+EFFAVWOmd9YwNEiH9xiFRNsjBCq+iolkmWp+iqxqWbN2h1GxRpQhiGBPM5o8EFeZpSxDmaor4C2kqEohCHBULVgJKkzCjynDgKuXH3NlIoDC9G7D7f43hvFy/wKKVEycoFes5yKJOQra11dN1iNOhTlBmmbSNFiZSCzvIyeZYh5ML1Ua+7+J6PLHPKPCWIchAKbtWm0axQr9c5Oeoxv+ijlDlpIXCsCs2mhW2aVFwH06lg23/9Kvpf6CrLEsvVePL8EVI6xHHCzqUWc11wlvR5+PCUjz9+zN/92/cJ5h6TYEqBSxhloNu4jTZ1t8Ef/LPHWBX41jdu852/+JTJOCbPYsy8iq7pqLpCnkmUoqQMZty7sspZr0+axHRdyXwyIY0zbq52yErozySxUNClwnQ4Qs1nVB2VRq2NoRv4kwl3XrtBvdXk6PCA1uoKnboG45RJZvJwNqJqKpyOhuhCR5UqSRxQyAaVaoPv/OQvyHNB4M8IfY9Wq8nDh0/xPA/DMNjeWqHbabB1+SaTKKfUG5xehERhwXw8YTyZEochrTr83d/7bU4uXmBYJnHq8wf//AH7LyKWl1pEUcpwOCGejfnmN3+V3/4v/yve++732NrcBlTe+96/ZjoeEiUxfpijqwprW5vce/sdkkLSO36JSOfIW7fotlscHe5CWlCp1BC6jpIpbF66RKbZ7B6eQp4z7B+RJRFJlhOlCWmRv2otL7CqDt58ynw6IcuWiLOI7vIaTqWGEILW8gpuvcZ0cESZL2C+hmmiGgZIBW86RUoVx3Wp1KtUqlUMXUNVFiDb+WTI5lqX3ZfPUYRkdecKusoCOiMlumnw8sljQt9jqdvFcGxM28GpN9E2dLavZYSRjz9Z9JsIKZh7M8oS0igm9H0oF6ZpXdfJsxTdqTAeXPDxez8ljkNKkaGqC1+Gpixan03DYPnSBstr2+RFgduoI2SOH4aAQNFUsrTAMAwUUeDaGp1mjSKNiPw5cRDS7XRx6g7Lq20CL+T85IyK43D59m2KUuA4TYoSDFOjLDJUVUEzDfL0P1yfwi9k5UVOlkHVNgnSCasbJstrDivLLqenY45P9/l7v/cGZ3sebtfhWrHB2VnC4f4EkZpEQcTGTkn/eM7Z6QWG4bK6tcTTRwu2oR/4WKaNYdooqsEciTTqTFKTSNoc9885H1zwK69dYXR+xnx8yhuv30Xb7bE/hkxnYf+dnFNEOdX2EjXXodPYpOrq7D56TIFAlztgZbSUAr8Xs//cYLkhUByTbJZgOgZJIjg5G5L4IyxDgzLj2tYGpYDj8wlHpxdoqsps6i2Er3qdQtVIEoOz/SFx4NGsu2iM2XJDSkdibDo8eLRLQcDwYow3kzz6OKRqmEy9FFVXSNMZ6+tr3Lh7nT/75/+Uhx9+zO0vfZXpbMZsOqK9vkl3+yqKbiKlimVaeF6MaTuvNH4lu4+fEa6tcOnadfzpjLIQRFlKGMRMxwOCQnB4eE5WpuTxnCCKCIKQvARd1RFFSaPd4cadLzE6OcBtVBkOhygUuNWEw5fPydKYZnuV1a1t1rfWmZwP8CZjosAnTcZU3CrVTpdGZ5VWo43tGJRpwmQ6QtcklWqFZrdDvOqRFBn/6v/6c04Oz5gMjrj9pdeptzq8ePKEyaCPoWtMh+eo2mKYyTQt7EoNq+KAlCglCwVfrUq3KBcm7aIkTRLyPMOtVJnOx5BnKEJiWiY379xgOhkznY6x7Qp2pYpQoFKpcen663iJJJcKtmNz7fZdPnzvRwixEOOmSU6eZdiNGu1WA5FrWM5iqKnfP+fqzSu0202EIjg6POXpk0N00+TWnbs0ui0mF0PGw3M0XeJNUxQBgR9g2C5JWnzhePyl2BQ0TSMXMB0HfOU/2eTF8RF//uNn3LqyQil9Vtbr1NolrraJpnc5OfsIP+rxtW9dxpQuSWJTrVd58uwhZ+czpsNzmm6NK9stXuwN0S2LPIiZTIeYhomiGmhLHR7tnlB1qtidbcLJgDOvWFioFIGpFFxacxmNT7mYLWb13UobU3goFKi6imnqBNMx1XoNzamSZgl5WeIYFq7p4xUN3KqGXg/pve8jpcC2TUIvZufSZa5c2WI0HC3KYEnG3tmESmMJVHNBpjYddgc+1cpCkONPzqlYJq16jcNPntPq1Nl6a5PaTp33P3iMkArBqODx4zm6YVCGPhVNx7Zdlra22d7e5MEHP2SlBSeHD6k0WjRXVmmubNDdvAwITo8OmM5GjAdnOI7D6+98BYFKFM+hjHny+RMaK5uMBiP6p0eYlkOWphwdHdFZ2eTyjSv8/Mc/WCDzkpgijVFUBVM3iIIQy7GxXJcoT5lOZ+SZhWMYHOwfMBxcYFZsTg+P6fcOuHbnDSpuFaehUWmAYlWppDm5MDg9OuTpZ5/gmjqNZh27srBQ52mMWyvJipyrN24RRQnf+/6P6Z3sc3Z8iFOpkiYJmm6ABEVRydOMKInJkoz5ZIZpLzBnAsn43GV5bZ3Z3GMyvAChkGUZWZZgmgaqprC1vU1JgWHaVOotas0mpmWi6Rqa6ZDngvk85PNHTzh8uY9hW7z7tW/RWlrGtBziOETTNRQkaRKgaHVuvfkayXyI0FWCIOPy9RvUGg5Hhz1Gkxm7B6dQKlxa7uI2uvQO9xj2jgkCj6zIEQUIsUhcxv0JWfbFYUq/FJtCluakiUSqNj/+0RFSLRFJytq2pNFa4mfvDWnUEppuRiZe8ObbHd58Y4l5eI5tavz8eyN+8t6MtasKb927yscf77O85HL39ianZ++RFDllnr/CoYeQRoyGEW9c2mR39xl2o4VmOxzPBKvNZWRwwcxPqTkOb97d4EUv5eW4wKdGo1qj2q0znPhEp6fULEGtVsELfZI0w220yPOUiqMTFAr7BzHXrm3itHLKNKPbrZA3G7zYO2ZpuU29vczgYsz5vKDS3oB0IanNkhDymKrMaRkKmisZ5oLu+hJl4JH5PuVyi+3bl3gx2CMIPG7euMrMLXn86AJF6gipkCQ+ulZFSoUnDx8hidlavULFdSiSIaPzA5a3t7noDbArNicHLxkcH9GoN8hNjTSLKRWYzeYICXMv5PjgAMM0yIqCx58/Zj730A1Jo7OMQcnO9ga6W6PmNjg7OUYqknqjzjwIqTh1/NmMOE6gKJhOp+BUcaoqpVwIfGxLJZxO+OP/7X+l3mxy/2tfp7W8QWNpk/75mE/+8j12P/s5pqHSaNU4OztibW2LNEkYnkvWNjOqdZc4Tblx8zqF1BCqIIrHpGmGYdkEr8a+syxHSNANjTIviOKYgoVxqyxygsDjYtBjMp6QRgkISZomaJrKNJhTc12EpoKQPPvkI46PjlA0DdMyUTQVRTGIgpgozsiExNAM5uMRJ/vPuXTvPmUpcN0KquGQRSGqLqk1W2RFznwyxlZtCkycisaHH3zCfBbRv5igqRqbGyusrnQwdIGpFehaQW7qzEeLHI9tGaRlwswLyfMv/qagfPvb3/7ri/YvuP7BP/gfvt1srxBHKfEsRZGCtY0lwjBBlvDk4ZCXz6ekZUKlmTMcRiRhiiISKi1o1F1cvcXUyzGUGoE34urdCoP+nCK2OTu7oERBCAUhFYqiwA9jvnRzhysrNh1b4hhw3LvAyxSkWQPNZTr16B31QTUxTBvVNFB0k944ZjyPkUmEkkyYzWa0lpexHJdSSgLPR7V1ZmVMEOYESYmuCpQ4p1KrE0uDZ7t9dntjesOA02nKLClRRImrlRiE1K2cugOubaBKEEJSazapNOo45FRsSaGUTIWKqZsoSs7e/ogf/2CX0M8Iw2jxSqzqdJoNvPliSOur33ibuTfHsUyicAp5SVEofPrznzAZnvPaO1+h0WrhzSbUmx26G9uM+j32nz9jNJtQFjlhEOLWOwjNYDoeUWQxa1s7bFy5QVYozLw5Z4fHCKnQXlnBtB0008GyHCbjMaZts7l9mWa7SxaHqKqC7ZgURYquysVYsmVw9c4dbr3+Jm59ifks4Pmjhwx6vcUbTruNlGAaCq12B7daQ1HBNHWkEJiWzfn5KVEUU63WWN25wcnpiOnkmFqjhmmaBEFIKYp/IyBCLIA/WZaiqhp5UaBqCnmeM/c88qIAShC8unIsrgzd5S6qqjPonRL4PllZMPVmzOdzojABKQjijEJIhLqQvGRJQqO1xMnhAe1Wi0Jq6JrC8voaUjHp9cd8+slnrK+vU2+vcXTYQ5YGF6MJeVby1pe+xN2716hVTcoyQtN15nOfMs/JswXs5dLlLQzLRgqVsih5ctjvffvb3/4n/754/KV4UwCIvJgg8NE0yEqD/llGcuBx6VITwzRxKjp5HHK4m2EbDkE95atfbhKkCVbVwqiHzJ/NOXo54t7r2+hGSHPFx73IMI4M/FmMYZqURQFlDorCn/38Afd3unQrCtudOv2jQ8aTkEAu8fFwSr1apaK38b0YqeWYhgpFhi0zanUT16wiyxDLVikVlTTNEIbEMg0GUcIkCug0V0iSlDNfwZVtRicx48mApFQIIg/PDxFCIsuUesdie22JNNMYj2eUApI04HT/DKnq3LxzG6VUQWSUWUp1fYWL/jnbO6s0O1v88LsfMjuPUI0CSzfQZIlqWovknLe4vpiGi6LZlKisba2jmC5FmdLutrGcBlI1WL18C6fWoF5vY9kuUHL91nXSOGbuxzQ6S0TJIpewunMF01rkdX723nuouk7/6IjQm3N+1kMzdK7fuYftuDz79BNm8wlb126RrW7gOi733v0WWTzj/PA5Fcdi++otas0mjVaLKC0Y9c94+Nn3GA4GjEdjBv1zqu1VvvTlb7C+vY0sU5aXV9FUlWrNRSqCNEkxHYt12+Hw5XPGJwdoTpW33/ky//KPdqnYKUIVrGyuYBk6k+GENI4o85wkTpGqpCgLsjwjjAqyeLHJ6oaGbpkoikKapziOTVEUgEAqkrQsEVKiCIGaL64ghRAkxaL6oKvqYiMqFLqtNkkSohvKgjCdl9Rbyzj1Jnt7e/QvZgjFZjIvMKsCxWwSTTOWVnd44/7r6ErG/pOPSKOQiluhudzFrdfxphMqlk5reYt6e5nwqE8aL2Q7X3T9koBb7XJrY5N6o8CyVEIPksLENGwEGfNgSGfZIvA9Ul1gKxqWbbO9aTI891jbsjk9nrHk3uKDjwZ0Vypk5YxGM2UySvjpjxbQFVXTybN4QXl+9YXdXG2wokdc3doky+H5/iGdRo1SSKa+wK418OKCQZBi2TXqWsZKVSVLA6ICVL1CnKVMhqdsra/SXOoSxhnncco8lfizEN/L0A1rYb0JZzStko0lF388xPNmICSmY9NsN+j1L+ifT5lOp6yud6nVazx7ukecpNy4d4dqo4kdT8hTn2Ktg9utUTMi/uhfPGXv2QWus+jAK/OSRr1GRZdsLTeQRcZ0NqfWWmZnewlETuxN6S6vYjWWSTONk4MT8hLqnVVuvfYl5rMJSRyytbVJu9WCV3KSl8+e8dknHzKfzqk3O7Q3NzBUlaeffcpgcEoa56SlQAqoWAbbl69x2h8wODlE1XWKAmxzASi5cfs2N+/dpV6toOs6tXoTgcLJ/i67jz5GKDlpmjMZzZn5IXGS4nsB7aUlvvytv8mVm9dJPJ84DAi8KYZh0F5dR1EElYpLEnoMTl/QO9zHdFsc90Z8/8/+AESCkDpV18atVzFUBU0RhPMF9cqb+/hzbyEtkYcAACAASURBVEEO1/WFl8NaSG4URaEUsLy2Qq21IEfZtsnTh484ev4SRV9c3QoU/ChD0zXq9Tpr6xtkQufpo8eQFdz/6tcpkURpQLe7glR0+v0jnj18wNl4Sup7vPvVb6CbVdzWEkf7u6y2G6ysL/PdP/1DpmdHmJak026weWUbTbWYXQwp8hTFcXn+dI+L3hlpXhAFMd99dPwfD7hVVSWNVpPlZcmVyzbe3Ofg+IKJF5ElJstLS7xqCKPqKEyGQ8gUesc6925tYVcbfOvtN/jH/8s/w49i5hON7maLas1g/8kzEj+h0jDJihzTNMiSdIHFLgT9ScTt17dQDJMnz49otDtc2V5hPrrgxo6LW61yPvb49OEZ42nAvL5M7GsUiYahL3Rho2lCWXRQvArnSUyUxgQl6FqBYxXUq4LZPCac56zUNO5cbtKs1TgpE7Y3usw9n7xUePpin6PTIXM/xLJ1dF3BCwJAIQzmTMZT3KpLGAWMZ1N+7T/7DV6envDhByeM+imNpouhGwyGY7Ikod5qIqQkC0fcunmZvd2E/YOXiHzG9s4qp4d7pP6cjatQChtvMqC5tEK702Q6ueDlo4fEcUDkz0gvX2V7e4syiViqWXTrLnsvXjKbTclFzs61W2xeuUaWRIS+z8RbqO8iKXj++BEzP6CgJIljTFUjjnzMuouhCqIgwN7cwdRNPv/wPU4On6MpC1t2gcZJ74woXEz5FWWJ6ejcuH0Hq1bl7OyMvQcf0d9/huHY6IaBW2+QRgnt1XUuXb9Jd/06zc4Gk9mIy7ffYX/3GZ++/x1UQ2c2GWOcnWPZJlW3QqXqoqsGriJQVIWyKLAsnbwoFmAUIUjTFFVKzvsXDC+mrO9sYloa9WadQcWmUqkSRjGzIKEQkjzNSeKEIIrYvLzD2uYOx0enVBsdgjjk4mhAHB5R77SJowipKJiq5PL1LZqNKlEmSIIQTUhKSvZfvKBW0VEbLpZjsnH5EnGY8eTlI7K8ZHNzgyJZVHxsyyaKI5YvLcOj439XGP6/8fjXFun/P1ZZAlIjTOD5/hC7nnD/V7ucngSMhjl6AbtPYlS9QThO2V6/Sach6K43+cb9r9E7P+L9Bz9k//iU5aUOZe5z0ZOM+zFBUOLWK6RZSolECA1VKggpUIQgSDIeHI75tTevkWYhT19eUK+YxL5Po1FlNDhje2uTriN58mSPM++AedYhKDU8z6dqqbQsyEtBGo1wNBvXLsgij0IuWoZNS2fiJygio9teot1tc9HrMx2N6A0SHj47YGtjjaPTc2bBYt7BUCSaUKEEqYLUVMbDMZsryxi6xvL2JoaV8vSTz+mdlBi2jihh0D8nF6DpGtPJlH6Wopc2k/M+zarB4VlJf+TRXVOw6m2GfkAnClGIcWyVje0dWp0ler1TzvsneKNzdFXh2o2bHOzvYusaw9EIU9dYX+ly2j9nPpowHw9xHIftGzd4+vAhxcUFAGmaLJiaMkdRdWDx9lBtNLl3/x3qzQ66ZXL4/BlnBy8ok4Ca46CaOmmS4Y1nGIqk0mown3k03BqlbpKJRVNRGoXEkY+hK8RRyMyLODzpoSC5GA452t/FrbgYusbS2ha5qPBrf+u3CLwp+y8/xjJNKAuyOGIURQwvLlClpMwLhFgwPkaUr+jRKopQkIokEWLRZCTAazq0ui2kaiAUhSiKKYSOVIE0AMUgyXJmU4/HDx+gGwavv/UVjntnfPiTH5KXMQKNq3euY5s2SZ6hyJJ61cGfjlCdGqPhGY1WFadqM+gdceXmPebThZ/C90IefP4+F4MzLMuhWgtY297m2r1VDl4+x7Zdqu0u/MlPvlA8/lJsClKU2KZClijUltbxgmNePoFgplMWKePAI45ygnlBp9ukai6zf3DASX+P/qlHf3DM2fmI165t47ZKTnsh/jTHD3Vu3r7G6kaLDz98RJalBGFEnucLLZ0oMHWN3nDG44MBm5tbbG2qGDWX8TRgNIvoLnX52c8+o7vU5fa9W+zMJzw9mjCKdLSKxVrbJA0nmJUKg0lMKmJqyw4GBhV7if2DAfODhDzVkFJj5GdczBK6Sy1qhuD57jFkGb4/J0sLKqbGWrdOo1WnVDSGZ30m0zlhKiGIiNIYTRWMph5/+sfvc3KcEocRk/EQTdPRNZVCgmUZ5HmBzCT7o5DM22Nrrc7169skuUmUG0h7meloj+9898dc3V6n0miRJT4vnn1GkeWsrC+z789Y29pm7/kLegcvuXT1Kqap4M0nbG8sM5t6PHvyiNlszDu/8lUm5+eM+ycsry1h2BUsw8SwDNI0RSoqqqqj6ovTvBCCQf+YeqNNGgZYtoVSsZmPhuDPKRdkf2zTxK5U0AyD5c0bNFe3MC2TLIPxcEzgh8zihCxOGA5nFEKCWHAoKk4FyzZY7tTxZmN2JBi1FVY3r3PRe4GmFui6TpKkZElCmRdIQDV0SlGSBhFCSChK4ihCVTVUNISUSCmgKMiSdKG3N22sSp0w8BdJS0VBSo0SSPKcyXSCKAuu3bzFeDziwUc/I4impFnGcmeJuttgMr7A0CTjwCfLfERUMh5PEbpNs76C1HVWN7eJ4ghFtyjQ2X3+jMBP0I0aUlE46w8QqklreY2rd9/C8wIeffzpF47HX4pNQdUEpfDJUofTo4wkr5Cf+igqhPOY/ukYTddR9ZDecE5/eEK33QIsXrw8J49VZFFBygXevdVSCWdz0lzj6FjSbDXZ3Nzg8OCUOJ+jSEFZLuAZWZoDkt2LGUHisNSqsvu0x1KjTqrbvDgLyK0G/fM5SRyxslLj7dcuM5jEDBPBZOwzH3vc6C4hJlOiIGd4GGFVTfZfnjIepCyvtWhtmgz6U6I84exkQvXKEnatyfJqyre+cZ/ZzCeMDknykk67jW7b7B4c0esNSAoJRU6z3kSUBcqrWYp/+d3PSBKBIgtEuRjUUY1FE44fhJSixBCSpCgZ5SbybMrtRotWs8l4PuHg6JQiL4hSODjtsykV6q7JxfCY3SdPqNYXsxGWZfKzH/9wkfT79GN+5etfo7O6xWDQp9ass0mJUBe2rnarzbtf/hrVToe8gCQI0S2TshQEcUQSRvhzn/F4D28yptlsYN6yqDg1mu0lVFMlefKQk91nhOGcNCmQQrKkmtx79xtI0+Fwd5dnnz9ga2eH9c11/MBflFRtG7deYzadEwThK2FtRDD2UZWSej3n9OCAzRsNClQsq4lTScnSGClVClWSRAvdnmqoKIqKqqrkaU6W58hCUgiIshRVUdFVhSxOybJFuS+JU4TU0AybPMtRZImiSEoEpm6hyJLllQ1Wt6/zkx//iPDVCLgsSxqtBmlRcrz/glt3rmKaBmmeoJcpo/MzVlbWkHmMZVShafPxj75Dxc7JOym1pksUt/Bmc/IiJYsjBke7WJZGtdFAKpLL1/4jc0nGSUaaBUgEQSjQ9SppnBMHMyI/wDA1NE1jZWmJBy8fkQlBkoZ03Bp+XIKiUW9UeLrbZ2XFxjIsshxK6aEZCsNRgltr0uoUXAxK4niBU1cUBUVKdN0kTOBsnjKKLkijlDSdEUcBveNDGlWL9XYDXZGoUiHPE+b9Q7JCR0gHYVQ46U9AmFQqKvPCx620ePlshO6olJrPtatXcHSL8dDnYp7jjmIc5jz46BFvvv0mFSek3ekymE5RNIsoSlCKnG6rQZoXOG6FzuoGtqWh2ZLjkf/KZqWS5xlJmpHkObqmEoQTsgIqlomqLnDkmWEzLRVePnrEldsCSxqINHg1jVmQIQmjkM8+/4QbN+5BGnG4t0vabpGnPv7snErVYnV9C9WysBtd7l+7RcUxEcDR8Rl5IQiDOZ9+/CG7u4ekSUoQBFy9dRNNU3n46adEsQ/ZogVYAW7evkUpYXB+xsneHm7dZWNjk1tvvUsQBoRzjyyJMR0XPwiZ9s/57MO/5PnDT9l7+jlXb9/mtbfeJA5jjo93QUiKHMIkQjerCCGoVCpoqkpRAIrENEwarS5BCkv1NhXnlfo9W+Q8Aj9gYSUTmIZKopbIHCQaaSHI83Jh5ApDJAVOxUGIhTE7LzNAkBUQRjGKouDYNnmasrVzhdbSKp9+8HO8yYgiz1BUSZFGlHnAYHDC6fEJ1Zogzizm0yHOxhrhpI+oa5y8TDBqHTSng5SSSr3F6dEJvdNj8qyg2WjQ6qxjWjaaKqm1ugxOjxkNL2g0ml84Hn8pNgVFCCwzRGiCYT+myHNEqWIYdRCQzX1UqWCZGo2KzsQPEDLAD0PSxMCu1EkChUatTbu1AlKjlZ5yreEwmUdkhWQ0irAch0ajSxx7FGX5b7h1QuTkeUpSGFhCod1q0Kk5LFVLNlwI5jPKZI5uVMgLOD/q4c89VMNgbaVKr0jRFA3TtRlcTGnUq3SXBKtLK5j1jOlszO7REzaXd+j3hsynHvkxvHlrnVq7zosXeyiqRlFkJFmGbgqSNKfV7ZLmGVFWMJnOOOud0bi6yeNn+zw9jdA1DSEFslCwdIGQKlEcIsTitVZXHdqdNjmQRCGel/DG9ib+RY+VzQ1cvSBPwU9gPPYWjkWeI9OUe2+9i6KAUEDX4P7feJe8BMupcXF2wfPHz+i2mxi6pN5osLJxGcussPfiEScvny7IVYrENAyOD17gVlxknqAUizq/VCQVx6He7vLy6RP6J4cE8xlZmvH04Wc4ts3y8hpO1cWtt9FUnT/7o/+dmbcYodYMjbk/45MPfkpZltx99x2UT3WOdl/gex5CVQiDkDzJybMcikV7emNpgzDJMEwTITVODi/Y2KphmQZOq0KeZWRJQlGkzOcBaZggwgBUSNMCPwoWeR4hqFZtVtfXWb+0zfHhMcPBCIqSIi8p8uKVKVtZiI4u7VBfWuOTDz8hmM+JkwSRFxiagmKYVG24mJ9TFHB+eoFTrRD4AYEX4ToWeZ5w3tuj4o2R9ohGvYbbqC/4Ev6Ms9MzTvb3mVycc+et+7iNFtOpx+Hz5/j+jP7J0ReOxy8CWdlggXdfYlFU+ydlWf5DIUQT+ANgG9gHfqssy/ErwvM/BP5zIAB+tyzLj/5dn6GpKutbdeLYor9/QSEkUjEwpIGm1NEVMNScweCAVrtCp9sgmMY0l21UaXJ+4jEdx0jZ4cmTCxzLgFIhCgvCGIoipchA5AlFHi3GYosY8aoWXVAiBeRpTKYItjc2UBUFZMbSuoEpc5I4oOpWefH8BaHvYxoWURLRLgscpcCp6BRliluzeD4OWE10pBxy9LKgVrcppQpaSaEVaKbC/lGPRrPO5pVbvHz8gCd7h2RZgihVVE0lK0tqrRaaoTGbzzk8OGJtfZ3x+JyZnzOd+UhKdF3F0HVUVZCXi+Eypcipt22SJAepkGcFZSEQpeTXf+fv8cM//n0ePXhMq9thudNkOE84u5hyMfJIs4xw9gjHdVjbvoIiNQanxxweHtHrnbG5uYGmGuw9ecCZ42LbDu2VFQq9AnKI1BR2rl9jMhwx9SakQcTg5IixrtOsNyjLjLKEZqvN+vYlvOmY/uFLhucDCqGgKJJgOGAyFBwd7JGlIatrm3zpK1+nlClnZ0e06k1u373NydERw36fx5+8T63mcvn6Hc5Oeiwvu4t8QJqSFwWVmsP1u29i15YopM7eyxfYlsEb73yFz97/AbPJhMRQGJ1fLPIHApoNl3a7RZamBN5is1J1g1oQUalWMS0bISWVapMkLdBVMPUCXeoURYlTa6NpJkVR0ugsUWLywXs/ZzZbdFXmWUK95pBnEbahooqcZkXBrer4YYJl+oi8IIjmGLokS1N03UBTFcJgRKWtcnE0JEtS7ty+xa1btxhdjEizDNOukKQF3mTMbD4hL0rSNP7FbQpABvzXZVl+JIRwgQ+FEH8O/C7wnbIs/0chxN8H/j7w3wK/zgLDdhV4B/ifXv38ty6h6Jwdu5yf9BGFhlAzBDm6npMkCoZRwXYkeRYShTFSGiAUHGOJydQjSBSEqrG1YTK+GDM4P0fVLeaBRFEEFDqqJjEUE91IkGpOli4o0mqeU5QLhHdR5Iy9CXtHp9SdKnPPwyzmdM2EpWYNw7JoL3dIwhrDiyGaoVMqkjQv0HQNqWnoFZdJ85iXh2fcubXF8Id7qFLl4rikt3tKFCSkfkwUJjx9eYy31KJS30b2E7JyDq+6LclDas0aoJLFIesrXbpLbU6OTvAyHSnBtUykri0oQZnAMgzifHGHt+wqul4wm0yYecGiG6/MCcKQO1/+VXSnzePPPmStK1jrdnAqJv2LMVmpcj6b8dmnD8jjCKlrWLbLtL+Plqec7j3myo3brG8s0T/pU1tZYvvSDv5syvlpjzBKWN7cYHX7KkLAea/H84cP8b0ZndUVrjZaRHHI0uoKqr5Iht55+x1OXr5keHFGlibEsiDNF7MH0qnQaLhITXDv/juYlkWe5rQ6XdavXGP/0ecMeseomqQ0NN7+2jdRJAh1Mb1YpOmi3Vg3OTnaxxsN6Z/uU3Fsrt+5z5tf+TWOnv2IIpsy90JUCVKVnJ2G6IaOXTFwHAOhGBS5gl11kVJlNvPwZx7J3iHVepW1jTUMQ8cLYoSQKFInDDPSLEOzXU4Oexh6gesaTCchdkVjZalOHPvoClQaLWbDIVVb5WQwosjr1GsVpuMJHVsjjeZYVZeizKi5LqNBj2AeUOYFseezc/Mul2/fI0nKV/LemGarQbNZX2gD/b/G5iUhxP/BQg7zj4BvlGXZE0KsAN8vy/K6EOJ/fvX77796/un/89y/7X+6Fbvc3lzGsuuUpUZZpqhqwtZOk0HP4/wiQdWMRbumKEjjBN+fQFnQbrew7BrTmcdv/9ZbpEWfH//gkI3NDtPxkDAu6HTaPH56TrNWJQwzpvMCTZUL5l4cE8X/N3Vv8mRZdt/3fc6dhze/zJcv58oau7qqR3SjG0MTIAZSkBukBsoOWUHJCttBD7JDXtnhv4ChhbWSF47wSrIlUQxKlAiQBEAABLsbjZ5R1VVdU1ZVzplvHu5877nHi1diQLZotRxUBHw2GXEyM+5bvN/3nvP7fYfwCYV1kSNoKXj6wgZ5WuDbOjsdi6WayXg0QdcNKv4ivMR2bXIpCcIIr1JlPJlhLa2j2j4//fAW1XqFedhH1zwK6TOfxchEYbqSJdchmOgk+sI4w5YpwXSAUCW+52DaAsu2SPKMNIuhhJWlJkk44f5pRm8SUau4JEVGGETY9iIqTygBmk4aRqxvbCA0jZOT00XIaZHzm//Tf0GpVxCG4vTxLo8//pA8TXEqPrppEmeSWBbs752y2lnimas7bF++QlkKkijg5nsfsHnuIuuXnqJ30qOx3KGQcOuDGyALZkFEGKVcuHyZ1soqtm1g6jDsndFeWabZbJGmGWenJ0CJpdvkpaLRrOE5NkVZMOqfcfBwF9c0WN0+R63dodR0hBR4tTpKCVRRkpYlmhCURYbrV9EMkyyc8+CTG2iaSSELLFOnUm/QWV3lvbfeoH+8jxIOhgDH93jlS3+RPD1jdPAeslREUUaaJsiswLIFq9vdhRpyNCcK4oXfZ16SFSVCQaVis7a5hmFYnJ2NGE0CikIt8kqArfM7LK1u8ujeLsP+Ib3+mCJLqLoWFU9nbX2FlfUVTk5HWFrJeDLjxscPqHsWL798ndPTEa4h0SgxPA/bqaILg1wWaJrOPAipVJt0t68wnyUcH+wzmQxYXlmhSCX7e7ukaUaSZvzhe3f//MlLT0JhXgB+Aqz8TKGfsrheAKwDP3uBOXyy92eCgq7Diy9u8Xi/oJA6YRCTJDFHexOGgxFlqbPcdJkGCbI0aLd0nrm2xtFRn3q9SZyWXDjX5Uc/vEWjUWMSFlxeKnj9r27znW/vYhpVzm1kgELIkn7UI8XBdl2EDoZhoSmFpoGh6SRJTBDFLFerKMPmeC45HozpHz/G1Bd6BMc2OX/hPKZl4TiA0Kh6HtMyYvfWI4JwjO0U1KpLzIKYLI3oLulcvLjK3skhm/UWwYmglxqMpxGOa9KudimkRCJACKIkYzyNKApJnmdYusn2+W1uHT9EliWZLJBpDkotXJWVwHUc5pMxr73yMsMwYTgaIYRCN7SFgWe9yb0792gsd7DcCpdf/DxHjx9x68NFCKtXrWM6JsvtOvcf7iGEweXr15nOAhqtJV78whfIpSBNMqqtJQQ6g9NDJqNTSilJUokwTG7f/hhufcxSvcnV56+zffkieZIwGvTZvXefk8NDTGvhvl3kGdV6nZ3zl1hZX6XVXmKp1cC0HQzDRirF3qMHPLpzh9byKlmxcD0u0pjN7XPsXHuONIk4Ozrg0b3bpFHELJhSygLP1FjqrNJq1Fjb3GDcP6Usy4XvYh5x+PA21196CUucgSo4fnyEkjFOxWOp08awbWRRousGCIEsFUEQoGsGnZU2rXaDIpecnhwTBilxmhOFGa7rsba5YKR+cuMGxyeHhLMJQma0Gj7Vis3GRhdNN9l7fMLxWZ+1TouNzRV6/R7j0ZxP7j5ka3MF19YxNB1Mk4rnYvs1UAZRGKEZDo12lziKGBzvk4dTzDKjLBIct0mr1WJtbZ3RaMwfvnf3zyrBf2N9alAQQlRY+C/+XaXUTPxM4oxSSgkh/r2OHD+b++A4FpNALjz2y5ytDZ8rTy/hWj4fvN9gb++Yzc0m3SJnNMmotTW2Ly6jhM7u3jGddotKNSaczxj2UzqtCrNpwk9vn7C63uStP77DhZ3LzIYJFy820MyU995/hF+00CjRNX3BPMsUaArNsAjznEoWEc1DSs3B0mz0+gpGmSE1hd9qEyQlvUePcC2DlbUVqo027378CamZcm5nC8+weLA3QxgF57YbbKzD17/yNDc+Edx665S15W2MxEbJEpmnxGlCmkYYukZWlJyNA6RuovBQukVYGDw8mBOlGb7rLxKztXzRcS9LdCEIgpCdrTWWVla48857yCzHsUxKUZJLnaOjI1SZYdgGDlWiOKW1eZ7nbY97N95j3BviVhxqrQZPXdrm8eEB3/uDH3D16S1GgxHdzQu8/+OfMDgdsra1zcbOORrtZV5+7YskQcD+4yNmszntloPjuSx3lqnUFhT1LM2JphMMQ6FpBWmckxUZQkB2FhKNezjO52m0lwnDiPnpGXmWUWQZRwePiWZTRoMzkJJGs8Hzr36O5lKHLJqhWQaNuodlKOZJgKEJ0qwgMwwGZ4dMBwdUXJ+KpROEMUqCadm4rsZoOGA2mFKru7i+RaW5gud5ZJliMgpI43iRG2nqOLaH75uYlkW9VkMWkmAWUiTxwlA1jKhXqqxsdCmU4N2fvMu4dwYUVB2D9dV1NrY2MO0F2N29+4jhKEQoyWw2p1axWOt2iZOCwWiGX3Gp+zZr6yvYtkNRZKThnDQXGLZHrdOmKATheIQmCqrNGq6zzsrWDo7fZDPYQQGr5wX8o9/9VLX5qUBBCGE+AYT/Qyn1O0+2z4QQqz9zfeg92T8CNn/m3zee7P0b62dzHzzPVXu7MZohWOs4NGoKv2VxeHpCmKYYps6jvUc8/8JT5EwY9VPavk4eGzSbDdrdDLee8+q5p0jzgA/efcDuruDu7YLPXL2AZ7js3r/J9rlzfHTrDCEE9XqD8XSG73tomvnE8TklDKcIAb3c4IWdqwxOegRKQxgutreCJxR5ETKJNSZRTC4tNNPjdBKy4tQZjxM6a13KxEY12qyveDz38iqzYEAYTjg9U1h2nZ1LgqJn4ghrwa+QOWdHJ+haxrnNFZZaNYLZiMFsSi4FpabR8FqMJhF+tYFnukglKZXC0CxknpLlCRXfY3Vtk9t3dplN5riuhWVbaHmGKhWVWhPLMhHo6KLEQJGUBc3OEl/6xte48e779PYPyMKAWrPN+c0V9vceUa3ZXLp0ifm4z8WdNdIo5Oj4kL3Hu6yvrXPlmeu49QZXrjdRpcKwFv6Hs2COEhLP8egdHPDT9z9AN3VUWQAK11CURY7vuXRW21SrDpZpcDLsc/fmDaSUSEDTF6GtzbrP+avXaDTbTKYhjx+8g2XAleefp1JxefqZa9x4/11G/T4aijzNMTTFqH9Ed2MDU5doRYxlO1SrFaajIYPjYxrVhNyR1OrVhe5lFDCfxURZgioyKp7Esi1M16bm+oDBeBaTpTkg8KoVXF/S6iyhGTb9wYCzkx4yT1ntVui0ariejePXmYU5/YMeZVkSBDGua7LSbmGZijxNcU2NZ5++wKO9Pm+/e4+vvPYs83nIbBIhKag36+iGDSxSoJIoRTcEzc4KjeVNvEoLWUrCyRSJZO/BA5Jg+n8vwf/voPBkmvC/A58opf6Xn/nVvwT+FvCbT37+7s/s/x0hxD9h0WCc/r/1E548BV3XCZM59brLcDQheD+iXne4ctnljR/scu3z2zx8dJcs9Oh0lrn61POI8ibT3QesL1+iEAOiJOFzz76EJXU+2XtId/U8R/sh42HC2tYa/WHMxup5dFMymUQwmZOmCbrQsXQD23HQNJBZSpxL0DWqdglZxCDMGM81PE2ilxGubVKtVnG8GoNJghIQMSeUNo7fJM0ypkcJr335ec6GD4hmGpORw1vxIeNpQjIcc/1cjUIqirwgD+a0q4JatYVleCQFnLtwgepwzKA/YDIdsdTostcLSJISmRfIMsNzfcyqTRgFiNkMzzUJ0xyFwnEWuv5SFmgsRr/t5Q73bp1QDKe4tRqm59H2G+R5gKGnfOaLr3L6qMPD2w84eHRAISW1dp27d+8jlM7VZ69RqApJIRCqYKnVoN1qkOc5tqYRhxGf3LpPFIcIoaDM2dzqcuXqNVpNj6tXt+mf9cgTRVHmPPf8M8zGE1Y3N/FqlUVycxYSByNEmaHpBkWSURYp2+e32N65zCzIeP/tdwiCEM80qNZtekeP6K5vYNmKa88+xScf5cznIVGcomka0XSGc05ndW2VeDYjSSNG/R6yP8BzHJaXm4yGY5pLLcqyoJQxuqGomD6m4eM65oISofdawwAAIABJREFULQSzacBwMCWIUmRZIoSGaxu0mg10vWQ6GRDO5gujVdOjyBOULshL2LvzgFmYIEuBoQksw0AAp6cDHFsDoXF00kcBW1tdXnzuMm+9+wnXrp5jqVVlPBxTqzXI8gTT1XE9HSEq2F4Fw/bICzg+eMjw5IDhoE9nZZVgNubx7oM/P1AAvgD8OnBTCPHRk73/+QkY/JYQ4j8H9lgEzQJ8m8U48gGLkeTf/nc9QABJFmE4Gv1xQnejildJcHTBKAooTEmR26x2mmRpiall/PTGW9gVk1e/eJlmfZW7d2f0533i+UMunr/O9J1d+sdHDCcjVjvLPHp4Qqu5jmdpZGGCbRrohoahGcg8I1cgNA3TtP5U737/eMazq23cKGNyMkdXOp7j4OpgqZTVmoVd8bDOEtAMpAaD4ZT+aMD25ip6JHjzx2/z+N4hS80lrj5zkcf7R8zHAQ3bZu9oSJgbWAbUl+tc2djk9uMj7u6dkumCmuNQqVbobm7QbleRCIaTgLwsiWVJpVoljCMoQ/I0oN1sYdgmcZITJAVupY4mJDJf5CJqGqRpQavdJgxDhKEh84K8LMiyhKpvkuQBy+c2We4s8/jhIx7cPWRwNmap0+Inb79Do9XEcRsUsyHPvfA0zeVVhuOAD37yDtWqT7fbpnf2mGAe49g63eUmnaU6QitxfZ+NnYtsntsGlYMCr+LT2dhkPJ4zPR2hKclSu87m1ioyTTjcP8QxFN31Nc5dOIdhCaKTPo5eYlS8heqyyJj2z1judtE0gyROKbKMPMvIpUTXNILJhHA2pdaqIXQNleWkwRTdselubCG0EqUEeZZRPmkmpklOWaZoFRsldApVLJqIaYFhGLRbFp7vIkuxCM9NM/QSoiQljFOSJEWUOSvLTYIgZTQ8hlLhWTqlhCSLORnNSeIEoQSObSIMnaJcuFY9uDWn1ayxtd6gd3KKZ+usrraYjkdUalV0zQClYdrOnxrtlmmG59joa1vEwZxoNmT7/AWi+Ry49+cDCkqpN57U7b9tffXf8vcK+G8/1dP/9YcwdF7+7Ap/8u4n7J3G7Jx/mi+8vEkq9xnMSkaTZf75v3iX3/zN13G9kEe7Ce+8e0jYD3n90heIJ33e/OFNnn35WVrdZSaRYOfy8/zhd36fV165zLlzHb7/R/e4u/sYUy1EPZsXOsyDEYNhjGPbyKJAlRI9XxBbTNPiqD/hqc0rVJol1XmBrTQ816Rmu3iGWHhL5jHrq20q1Qp3jseMx0POjm12dlZ55Qstbu/dx9GWIalx/84uspSsdHy8UlExBJZVEqcGurQ57s05PjkjDFMKKYnyHNe3MR2TRr3KtD8CTcfWBIWCPEkoZIkSJU9tb9BdWeXje7ukcYblWAhpUeQ5huNjl+D5Pp/cvcdz1y6gaQZSE0x6ffIipVrz0HWBrhmE4zGeb3Pp2gXOXd7m3u1HPHzwmCzOeOP7b/BX/9O/wle++Q3iKOPu7h6nx2cEsxlBMGNze5VXP/8Su3d3sXTB5asXaK0sMZlMeHjnESenx/jVCutrXdY31hgNRjzefcTZaZ8kjjF1jVa7zvaFLS4++xSt5Ranh0esnzuH5XoLSzfPxrZNgv6QbJLTqtdRaU6RpDSXVpkZQ3QdlCqRWUZhmpSqYHh6zKXnP8PK1ibDgz1cv0lzbR3b0ZhNTtAMHVnIRdSaKvEqBrZpoOkGcVYwHMzIsxxNaDiOTamxGIlHCYoS3/UIk5heb4yGRsUzqVYqVKsOSZxSrznMZwFJIpFSUipJo+rgLDcRQifJUkoFqiwRyiVPM6I45pnnvkpUzAiy+0xngobjU9ONRQBumZMmEXmSkkYJsgCEhl2pcuHqNRACw3R5+vmX4Fv/zqznRT3++xTvf6hVlpKHjw4QMqVq++w9us/tmzexDJ/nrl/iy8+/yOQ05/s/6lGttOmPIafN0f6Mf/Xdm1iGzle/+SKdZQ1dDXn3px8zn0gsr8LNuwcUquAXvvgUcWyi603+5I9/wNlpgOu5eJkkCSVCkyglEDInLxJMXUNU6vzg42OWfJOn1psU8z6D0wNKy8BoNWjU65i6wfH+Ma2lZQ4OJjQbdTRhcffGPvNeQbX2LKZ2Suei4vjtAXFY4lkaw8lChXlue4NiOOXwZITQBbVaDZn00XSLTFkoAY5toaFIopgsf5LQLSBJUyzLouFX2T885fB4QJBFuJaDoMA2dco8IskzEJAnknffu4mta0zHI7xGC892sW2N/F+TYxyHptNASkWSxKgSti9tcfHqeQxLIwkTbn/4EZtPPYOuGVhC8vSVc9RbLbI0xXZNhKazc+k848GA2zfu0W6dYZkaeTTE00tckZEFQ1RWp1SQhCFSFihNA10nS3JUaSD0Cqs7TZrdTXTDQDMcRGaQF3OStMByXEqhSNIZYjxjcmzTqBloKkZlCQ3f5vkXnmJja4soCvEbFVQZcfHqeS5cvcho1GM8GZKFEmGZnPSmRI/PsGwTiYGpWWiGQ2mUmEKgcoVpuViWQyQFOhqGa1B15EJQpRlUHYNut0NZzMjTYsHILQpqdQeZO5imsQiv1QyyosS2TTzXR+gaSZoThTm6blBtdmmuXUEzdO6+/xbD4YwLF69jdDIenzxCSyO6ZZcoSqktddEND79uUJRPmJRelarfJk5T4nD+pyP3T7N+LkDBrxj8yq9cIs6f4TvfesjLX1pnODjjje/1efvGA+pHJxQIqm6TZrPBt77/LzA1ByELklRDqDanvRnVlk6ZhjQ3bLylkiKr012vYzZ1+vMZWlrhxo23KKVkNB0zjRcxc6aro5SGTAtKWaLrOqVQyCwhEzrjwuDA0LiwuszVegPXBsd10Eybg8Mj+r0+raUO/ekMoWlUqzU+9+orPHp8g8HkjGvPvchgeMj6Th2EpKpM5pmOoRtkWYnj2FiOzWl/RKvqsLS5g2Ppf8pEE7rBaDhAUeJaDqkscUwLWy8wTZM4jVGqxLd0XGEhSgl5juFYTJKEUkkkElvTmAcBa+ur1GsW0/Fi9o6AslTEacR8PsY0JBXPxUAgn4xqizxDSoFSkuWNZYTh49ZW2PI7aOLJ283OcS3BfDri6PEBs8mULEuYTIZsndvg6rWnKEVJvdlC03SytMB16lx/ocHJ0RFn/TN0ITh3/hJLG9tIYdDv9xmcnlDIku7mNpZr4zVbbHoepAnD3j4ymdOoODTaNWQRU6+7PPfKdaTScf0qRwcHzEYj8jSl3qqyvL5CJksM06C7tro4GZQwnJQ82r1Dd22N6lIX3XLJswxdMyiKHE3YFKWBqUwMvaREUmKi6ya2I8glZEA0DHF1qDSrFGnEE9Y5SihqrTpFKun3R5RKoNkORflEOKU03IqP69dxq02SNKHpLnN2fEgpJcf7Bk+dX+J6t8KLz/0it9/8kOhIIesFumahlEA3bBQaCJOzo2Mgx/R8+r3+p67HnwtQCKOM73xvF9N2KJTin//WLQx9Me9O0pjJwzmub7F/dMRHt27QqLusdauEvZi15RUOj0YcBkN08wIqE9y5f8LGTpPXf/UlskRiWRZ+RfDOO3coxIRnXnoKv1rhzTc/Yh4lZEWJaQjSOEOw6HLLoqQ0S3StwDMVJ6ennA5cVpc9Lq5USE4O6XSWyOKY1nITy/eZzEOKTDEYDvi93/8Wf/PvvMC9+w/5gz/4AfVajXoz59r1DVQvg1GJ7pr0zoYI3SDJc4Rp0ptFqGGBbgoc1wWVU6t5KMDQBQYGo9kYPIeaXyVLEpI4plWrP/GMUIsAliJldDzBEBqaUECJ4bhMZ1Nmoz6bWx08R2M0HGIYJqUQhHGChiQKEvI4x/FshAaGJtCETh4niLJE+Nv4yzvc/uAdTvce47gWlqlRrVbZ3N7A9UxWNzqkaYiuWxi6RmNpGbfZRiA4ORvS7w8IpiHbF65Sa9bZuHSF1fOX0DUDt1JjPBxy8vgh/UEfpUoMUZLOJ9TrHsIoqTRbWK5LvXUevSwwHYM8TLn/09sYpkm11aC10qZ/3OP+x7eYBAmDecL65hovd5oIrUQrDaIwZDSac3La5/Swt6CMmwaakgx6ZwA0atVFSLBlY9o2QhMgNExNoeuCLI3RdYGGQJIj84JHj/ap1FzW1zpINLI0w9AEpSaxPJeV9S5JnJGn2ROvBgvdd9F0HdPyEFIw7R2SRSG66ZPEfbIkRotrvPhcjdVqk/Lqc7zXv0+RRsznPfI4RpYlmm6week60+kY29AZjYdo2qevx58LUJCFYj4RDCd9ZCoppQQNllZ9NMsizmZkRc7JWZ9GrYahuVRMm6VzPsNZTKlrXH/6Ag/vDynzhJ3OEr/8+a/Tbtf4yXs/5fNfuIrST/jaVzb5lV/r4LibCFXhS193+d1/dpsHdwWnoxMMy6DIBLomSLKCTBoUYUDba/DilTVu7J5wErg4vsFaawPdNVnugOO5hKVYCGhkySgPqTdqfPj2KZOh4PBhH7me8x99/Rv4/pzpbE5YKSgdizBKabWqTMYDKp5HYAiKWUSapWiGjWW7ZNLArrSwqzXisykVz0LKgiJPiJIIqRRJnqPpglIumHZJmiAoF56UmoZp20Rxzmq9gq3rHB2fUfMsNFVQFgVuxafi++QNmyRJiKN40fAqIExLyrLE0H1yzePozhGfbW3huC5hHBFGAbqukWQZhqlTbyxk0PVajdODI1zPYXNri3mYcLJ/zGlvwHA0XAiH8pIrz1xDExUsy8NyXPIspixCkmiGKCVJlpArSZnGRNMBvqtTzCbUmxWsdg3TtDm4/5hRb0oSxRSyYHVrg0p9mdFgQlpazIqSWZphjzM+unmKZUkm4xkHj08IwhBZlBiUXHn2MrbrMxtPSZKMVruFY+tohr4ggQEgFlJxFmrJUinSIIRSYtgmXsWj2mgSzieMpiGNdgtLMxAyJ01y4jBHN82FaYuuI3QdqSRCacRRwnQ8I8s0SikZD07YPH+R3bshuqVIgjp7Hzd49lfr5C2wzH3SNEQTJaZtYgidxtIKllNlfavK6cExooQo+vPVPvwHX46jc3Y6QBguhiUoSg3dEqSlYHg6RhWSjbUOpq4YhiMa1QaHBxM0X2N74ylsb8r2RpM7d/r8whe2ee7yU3x8e5c335mDmvOPf+uAy9fP87lXLnDSO+HO3dvMwymWp/jFL34Bpzzh4R/eQ7MsdOGQ5RIpQeY5pm0TRAndtkcRedw7mXJ4ClFaJ9csVustgtkAqXuEaUypBE3HZXtrg/u3BuxcXOZX/8rzNJdMVnfamIVNsJujmxlSGZQiX1jD+x7JNMbQbKyqRk2r4DoWtm8RpwWnZ1OQKbZtokcGiByhFu7DtmMhKZGFQAh9kUKchHi2SVrkFFIRpwWqgEbNIwhT1i6dI5qcLmLVn3w50yhYjDLthbqvLArKLCOMMuLcpjfMkVpKUUju3/0EW9ewLJvpuI9jW8wnOWk0o+r7rG10aXdabF++BAJOjo7Zvb/LZDzFNB0219ZxPJfRyRn3PrmF59qcu3iJdnWDeDJmeHSILgo8Sy0aiWVONJ+jI1FFRhHHOMselgbHjw84PeyRJSmZlGiGieO6WBUHr72CPsooJydUfI/28hLRPKEfThkM+sxmIYrFFMq1FLpmPRFnGdRbbWq16kK1W+bopkAXUKocUSp0zaREYds+lDA+PaIsC/xGg0a7TbXVRsqC06MBpgm+75BnEiULijxDNy1sz0WWkjzLQRWUaqFM1bQc0FFZwcrGNkk4x7Gh2qjx8e2H3Lr9PktbBkmQ4pn2AtQbHVA68+mUwccf0Flfp7HUQimTj2/d+dT1+HMBCvWqx5e++AI//skd8hJMb5H4m0chFUsnNRSTYEqtVkW3KhyfDflLf+F1/tHv/BPSWFCxPb7zvRGWbPPwQcHOhmQwifjOt3/Ab/z3r9PdXOYf/sPfJ40VuiH57h/8FKVsxr2Yg5eWWd1o8ktf/xw/+fAOulDEscTQNWxTp9NuUcYxutC5dmkV3zilF6UMZmP2i5zRSMPWElY32kgpQZjoloFha7zyuUvYjscz11/ijXf/mH/17T/hUmeLw0cDRtMIw05IcwiiiDicEeeKNJe0GhVsA2wDwvkYr1pDLxOm8ymdzjKmpdGqdojCcPGmQVCWBWkUo5s6aaxwPQehFmO2QomF6Yeh03BMHu8+ZP3ieSy7Rq21yMIolQ7CeHK3FUiZI2RBnsf4zS5GUae25JCmCe8dPuBwfsa1689w5coFsrSL77uoIsdyzMWITJbIXKK7AAKhFL7r0mjW2dzeobu+SZYXfHLzJnEYUKu4OJZOmcywzYxWy0T6VcJIp1rxF+NjvQNKIsjRkCyvd5mNpkRRgFf1Fg1Z08aybKyKj1E3kYbA8RvsXKgSJSFoEqVJdFPgV3yyNFtEzuuKRqvOeDJENwxayyvYtkvJE/Mac3G0R9cwhE4ezyk0MG2PXIIwdPxmgyJOKGWB0gSGrpPMYnr9HpamEVUquJ6D5TlouoamaRSlIk8z4jBCKYFpu7i1BqZpoNBodrsoJdm5/CxpFjAdjYkmAx7c+ZhzSZvt1S4q1Zic9ciCBNP1ODs4pN1cplJfAtvn+PEBZRZ/6nr8uQCFKMkZpkMaKxBMHVxHZzwfcu3KNW7cekBpLmbDWgSiLNBNHakEn3/2ee7eucMkmIKS7Oy0iKYGN+/1eDjcxao5fOd7j/i7/+NrfPNXTb71u9/m7/4Pv0Bn5Xm+90d7pInirfd+woXxKl997TNIu2Cp4/Pw4THzoUaeJCgUWZEwiQJW6nXO73RZjTMO+hN68zGn/YWevLKksbrSoTeakhaKWqOOYzW5c+sBf/L9m2iOhSgK4v2APF+Mn8512iwvrTCdTTg7zenvHZJLgWebHA57yDRFqYKt82u0l2sofUFIMmPBcDhG1xYeiDIpFndGHdIsQxYSTbdwXBuRaxRZgigVZZKw2m2RZoJH9+/RXe1i2wtyk2maIHiiLMzQlFzEvdV22Lz8CmEQYAgYj3pcf/YqphC0l9skSUSS2BRSMg0T8llIMB5R5hkXn75ArV4nz3May206a1sUcnHcHvRHxGHI8ckxep6h5T7aWgddahi2Qloah0dnzGYz+nmOAjzfw3UMfN9mudthMpmTxgU1v0npa1iuy/HBMco18c/7SE2hK4tWp0OWFTCE2bRPUeQURYFuCGp1Dw2BaS/clkzbobOyTYmObagn/QKFafoIzcI0bYRmkKUxMo/RzQKUopQ5ru9T2Daa0CiyjMm0jxCwvr6KECbTIGAe5fhKEIRTXNekUqlSSoWgfOIBCUkQLKTxhk2l3sR2lhC2CZrBw9sfMp32aLerJGcKc6uCTBdq0CyOqC0ts3XpCrPxmDgK8cwKSTTj6etPwQ/f+VT1+HMBCtNpxHA4xvddMglPXbnAw3suJ0cTBv0prW4DwzBo+g2icPGFe/fdH2PrJqbhMw6H/PIvf4FRkHLlcovT0R1m44TPvPosg7Mpf//v/W9g6WRC46P7e6BSOmsedq3GfKpxaa1LEOWLYqKFYQZ88uAmKivZ6C7x0sUtVJrR60+xfZ/xLESTGZfX24yChEdnc+7ee0yt3maegaHr3Lmzz3BwwsVL65QiZDKecHVnjddf+zwPdvvcvH2f7soyhuGT5GM8x2FzZYkkzXBcjcjSKdDxXJeq63HSHzE4G+CYOq6uE5Kimw5aIVhZ6TKfB4ymYwB8z6WQObMgQ+g2UkoMpTi/2cSuNoknAUIHKQuicEY4H6CZFp7vkyULF+Y8zak0NtnYeZH5eMywt0+j0cQwcs6d30RmCXEUMR4OePjgIVE4BwF+xWNtpc3aape0hDu370GWYlccLjz9DEUc88ntW8wnYygkQkhsU6CkoH/0mM7G4tRh2zpLK3UMfRHlplSJpjJsw6BWq6B0ndNHR4yHM4Iopl6tUW02WNps0XnmGl/7xtfYu/+Q4Z6iDAWz6RHz+YzTk2NKWeC4FkVZoBkaKA2h6SA0mq0u6AaiKJiPxziei0AnTSP8ikMSBzjWgqdQGDpKlERJwHQ4wvcr6Jqg3+sTh3MsTVBtLZEXJYPRKVJBMM/wbJ319TrRKIUUvLpPpVEny3LmsxCUhlZKKBQySZB5TDCfsbSySmdtk17viE5njWZzhTxrIOgTpwllqZj2e7TXN1htXQRhgSbZvnSZo4P/h9Lgz1w/F6AgpaJeczntz5gMCvb8Y2zfpOYEfLa5xt7eHK3QOTs6o9X2qbZdqr5OMMno9SZs7qyx0l3j9NaHvHtrn7/x117h3OaU3ZMZHbODSmJkDssbm3zvjTs4zYhKucKN90dcuGDw9As7/PjdfaZByZbloqTBMy9s4VcNxnen/OVfeo0ffve7TJWk43kMhn2khKXWEpe32zTbDT66c0o0m2CwGN/F84DrX3mJXv+MZqeOLGJ+/T9+nfXOFtPgPbrjZaI4I836zCdDlpo1ShQ1BH7FodWsEkYRuZRowsAWOqsrbRzLwrF1gjilKBTLnVVyWRBlOUIJTNNACIFuupQlhMEUxxC8/NkNnn1+i1vfu41brbBz5RK65aKlMWVWUGYJkYypVGu4Xpswgkpzg9l0zMcfvMl0OMB2ffyKxVp3hel8SqXq0m552FfPEYYReZZjOQ5KCB7tn3B2doZr6mxvb9FZ3Vj0KjSNl1/9DEk0o0hi7t28QbXqY+oaRRbTPznlOElpNhs0O0s0lurEsynBPMS2HVzPZz4PUHFMd2MZr2IRTmPcdpeiAsvn2yjDR0mTXm9CnMSEkWB/b4+zoz1m0z6WaVGWHqalUZYSTVuMf/USCqFhCg3X8wmCOUYJtWYboSkM0yHLUgpVIpQiKQoMTS0au2G8sNVv1onDOUVW4DarhGnKaDyhdzZB0wSGqfHql5/j1/7a13jzrR/x4PYEIWySKEGgMA1BIcGvVpFS4lY9hoMT8jQlmk/RTIN6vclZrw+ahdto4toe7ZUOuq5juS5oGuSS8fCQKC0wDJdbP735qevx5wIUqlWXcCQJZyYKjXieUuoR7brL9Wvr/Ce/9iI//OF7fP+P3mR1pYVjQFnqHJ6cUYgMqStu3d3l6rNLmOY6vrfC1WstltsZb/7JTc5dWOLZ6xfpjaY8evQQMbUZpor1rXVyNeEP33jE6f6McxvbvPX2j9l9cEi9blGt2Px3f/NvMBv2GE1iNjba+LZGo1KhPxxjmYr5JCJJCpZaLnHqI/sTCl0Aimk8o1V38fySjrdJzazw9//eP2Cpu0acF6R5huea6BqkacRkOGQaZQRhQpZnCE1h6tCq1fEqVbQsZjab4dg2rYrL0XBOXrgEwRwdsC0b1zNJ4gypBNPxgF/83FWuPr2GcGM21rvcFbskkcJyKvi1FpQZeb2JUIru5g7t1YukuUYSJ0xHPT754A1GZ0fEacp0PMDSFLPeKeP5wnbu/Plt0jRk/+CY6TRE18G2LCqey+Z6l7X1NVa3t9ENB1uHx0cHBPM5zUaFar3KZz7/Gcq8IBxP2L37gOn8ECE0BicnWPd02p0225d3cHyf/vGY4/1dijSi3arT2Vyje36bQZDzow9v8eJnn+Fgb4KQI36oTahbDlGYcHRwxvH+A4TMqNUq+FV/IdmWOUWhSLMI0zQoi5zW2jmC2ZzC8bCcKpZtkZcmy60WWRJg6CaySEjjkGGvT6VWxa9UabSblDInKwqW19aZTaaEWYKuLTggpqljunU+940VNi8vs3sU8+yXLlBdOeC7//QRLdtBIRDGwkoeQ1uMioucaB6SJimUY0zb5dz5i+w9vIdhgGVZyGLhpaFrYDouqlQUSEzTIO71ODlZBMR82vVzAQquY1Oxa8yHj6lVXbqdVZIk5+ygT5n0efEa3Lr3MSudJqYWo0qLwckUlaW8cH2TOIHx9IybdwziXLG0tsXho2NWWqt88y//RT75+C6/970fM5vHvPbKS6xvtvk/f+dNMkrWVi/zyccfs9GpYZo5woQr184RTgJW3BZf++ov8I//139Abzyj1q4QJjml0Fnb3iIpBHt7xxiWxXK7jVipY5g2x6MIpStcveTLX3qGUitYrWzRP56xubOJsB0en04xKx6H+4fs3nvIxlaX7lKT8OCANA0wDAPHcdA0heEYTKdTzk7PcH2HRqOGK3SGUcpsNkfTBfVGg3A6JY1S4qxEyZC//be+xte/9hqfPPiI/nBOMlW0Vlbo9XqoomA+OMUg5+LTr2DYPnsP97i3+zZJNKPiW7TaDVqdKmlsI0YJyhGsrC6TFiXDmWIyD0hziedV0ZTC1ASuY9OoV7j6zDM02isEswlnRyfMZjM828R1Lfbu3eVRltFcqnLl6UsUWUqlWeWZz15n1Bsy6I2YTae4lQrtlQZJlNI7PGQ6HGGYBm61QqJKJnlOoo64vd8jiOc8uHeTyzvr2G6FUvYZjk2SWOPx7i627dBuLqFQSFUQzAOUUJRKEAYxAvA8mySMUUqhlKLMCxrNC9SaDZSSKFUwnQwQqqBSrVCrVZlORqg8x7BsUlkSBiHT6YxgNlswExt1vEoLy/Z4+cvb7Fyr89EHjzn0J1R7IV/78uuUVDl+cMzZ3QLLVIRxQRHEuK5HLiNEmSFUjl+r4fgNqq02V6qvLOIDS40sLslGAwxLEE5CTNtmaXWTWmsZx2/SPSeZBwm//YP/H/UU0rSg1l7i9b9UpVNd4/e++yZhkFCtSSw740dvfx9Xs8ktjb/+17/C/tEJv/1b77F9vslnv3iB9z94zPpqm7c+usdwkvNbv/0ttFxgewfwA/jGV15kbaXDpYsOb731U8Z/kCFUTKQkpQy4vNHh9W++wsODPjfu3sX16symEd947TUe379LmRd0agtT19OzIePJjPVqlVwWWLaxaDQ6Oq7lkWU5s8wnkjqXLlxgOo84PokY+wb0F2/5WbhIwc6TGaaQbK7VsbWC+WxI07Ow9DqjeUIuZNHUAAAUSElEQVQUp9QqziKjUlMsrzRxXIfZZIDn+Rg6BEFKrVYlnE1xLEEUgywifuO//iIvfvYakohaVVGprHN475Q4mLGxtk6308GpVIiDhME4JUsnvPf2jwhmA3zXQHQ7OGZOo1GhXrlKKRVZJjF9hwd3dvG8Gq3lBu3lLrPZnJXVDtumiVep0mi3qdRqJNGM/Qf3mI8npGmK5+qsrnXZXu8wm4zprC5z5/0bJEWG67o0lxp0Oku0mw3QFbMgJowzzo6O6Y8zSsPGtCzyUtE7neKME35p81ka9YirTpMkKPj1/+wb/NN/9l0++uiITmWDOHKxbIvR8JQgnOA6LoahocoCTdcpcokmBIahU2+3sKzF9afMUky/TnW5CzKjd/II39Oo1X2SOGY4HON5Hs32EkWeI4E4TTk9OSMJQyzHxrAd8tykuWJw7bUaz79qUaQzvvlrGzx6XLC25vLG29/DpMor31jhXeOQu2+MMTQNzZFgm+R5iVtxqS+1sZwWmm4vekmmRpYkC4WtLHDcCrJMGY/6rHTXUEoSBVN000M3TVzv07OXfi5AIU5TlEjQRQOpafyXv/HLi2OybzIZD3nzjftMBgm5yClFDV0qeoMhG5d83nj7Jo3qCvvHQxzT4OJ2A1VaC6FRHIIeI62Y9nKXd370IXop+cyzLV74zArHpwWN5kWCIOD+gyPybMZXXl3jW99+yOl+yFs/fJvW6BiZplzcWkM3NITh0Gw2yPMCXTdo1qucDaZomkEw6+OVIYbSQXn88Q/u8dW/sEOeFlRbHsPoFJTG4OyULI2pOiaNeoVG1aCQGsenfZQyUJpGxRP4PmR5wWAwQSnw3IV7s+dV0DUNWeYITZAkCSiJ6dbIx3P+m//qG3TP6/zko/eo2+tMjwZU/DW2Ny7y0tVfpr22xf7+Efc++pjjw33m0yHPXb/G9maLk6OA9lILw3HZ3z8hTRPsao1ac4X20ioAW+ef5uJTCiEgjQtMp8aFp69TcSyyNCeMEsbDIa1WneufuU42nzMaDnAtE0VJvdZBsYbpWFgGhNGcYBaSBAH3pxOcdgvN9RjPptw5/L/aO7cYuc76gP++c585c9/b7K7X3rW93tiJY2InJIEQEBWQQJOQSm2hVKVq1VYI1PahD1S88FSJSu1DpbZSqyJRhEBtubaiCBJIgSQ2cYhjO74k6/Xae537fc6c69eHmRQ7TRRHKN1ZdX7S6Jz5znn4Hf3P+c93vjnn+2+wcGSC5y6UIIghgggrJrjzzmnuv/cEodJmZt8k0ovhuw4//MkpVMvh1371IU7+cJliucjioUU0JWJz4xqdVgtN14gnYkhFYBgaupkmkUiRyGYJA49W10NTYP/Rw/0ycW6bXreLKlSEAoEf9KtvbW+TzWVQNR2NEIBUOkXCTmKlUnQ7HsR6zN5tE8/7rG9dJxWbJvRiNDrXcFdmOfn0BocWXZZun2LPCVgvZgi2PVLJNJ1Wl263zuTcIhEKIopQDUG33e+JOM0WqiqYmM4TSyposkc8lSUCKoUCuak5CuvXKW2XEKp5y9fjUCQFw9DJjMdZu9ZgMyzQbGaYm99DqdDBqcfI6XkWH7qdZmuLtY11vvPvZzlyZIr3PXCY7333HNJU8RwNBZUwUKhVW+hCZSJlkj+Uo9A8i61bJFMJHnr3YfbMJ4jbGeb2lnnpbJUnnzjNvffewW8+/gDl6iqXL1QoFnyubpU5nwDV65FMJ0kmk6hSUG838XoeY7kMumUxkUvRKBeRUUAmbVN9ZR1XT7J8xUN9MuLoPVk26yvoUtJ2HVptl67jE7Nc3ABWNrapN3s4AfT8AEWG2JaOnYzj+hEhKhDRbncQkYdtx4kn4gTbLaSUhESYsRjVepsTx+fJJqcIuz2OLiUorkmM9CFkpEA0yfX1Aitr63SaNcpb69iaIJNPs3z1EoqiELdtpFRZXdlgfaOKMGPY8Qiz4JBJlBifmmR6dprS5nWurS7TqTcBEKoknbRREZRLJdKZOEePHUFRVTRVkp/Kcm1lBbfTReYnqdfr1Eo18rNTZMamMFIhxVoHkTJoW4LxTIaPfuRx/uILf8fKhTKeGyFch4lUHCVuYptpNtYbXFp+iQ8/+jiNQpML506zVqqzeMcStY5BKDQq5RqpdJqxyUmiyMNze/0p4MOoP/BnGujxOLFYColKz3EoFLfZN3cYicLW2iqW6pLM9H+JA89F1TWyuQzVSoSAQS0Qia5ZJFI6bhBRLJSIJxTueu8k6UkF3cthqiaVWhPUNdLpJE6nzsd/N42mCWYn7iebfJ7ee6/z/a/3iIkUbruNiCSh26PrNKi5RSbm5onbaXy3R7tRJZRef1rBtI7wugihUt7exLZT2JlJNq+vUymVEUbslq/HoUgKruvxxI+eJ+oJpvMTHM8fQkPw8vk1YmnBwtI0Ap3QyXBgzySG0sPQM7zwfIHZ/CxSDeg0qqiBTbleIcRhemqBcqkB11pMj+1lbjbDlReu0Y32kpiYp1EDzYhYWIpx51aelOXzrW+8QHavxoceOcwzzzxJoxVS7vS4b36SthtRa3UoFcvEdQ3L0mj3OgTtNpVSlVw2yfT0JKW2T6nVIZ5QUdUc19ddqu1V0gkD09FRuz5TU1lSqRi9TpdOp4uphKSSFp1KD6koREKlHUSogUQ1LAwR4oUeaLJfuMXrn9yKqvbnonB6lLeKLC6N84EH7yauxRlPH6TTbNEurlMv12nUyjRbz5FLqGTGUxi6STJlIBGsrm6ztlEgiEJ0I8Zttx8jP3+M7IyLbhiYqoJl6pgxE8s2IfKxLI2lpXl6jSblwjZSSgQhmgKL+/Nksyma5SLVUgXT0shPT7B3fppIQNTzadYlqq6wVWpx9vIafqSwVuvwyMd+A0XV+Mkz36VcU0km4tRLNSZzNpV1h3anx3g6y8UXNkjnG4yP5Tl18idcfmmLuG2DH7L1s58xl5kiE0wym89TqVQxdIVEOk23268YHfoefhCioWAGoJsxWvUGuqlx2+ETTM0cpNmooxFSLRVJJy0cp0ujUSNhx0mnM0zPzuD7Ib7v4/s+1UqNWrWBK0PyczHued8RDhxeQFFqGFaRdCLJRq1CpVFlcrJHJqNx+coa+/ZMsHr9aRqtHgdnb2P+jya5eLbE5Z5DY7tBp15GU0067TZWxcQyTCbzU/iuS6NapNtuYppZnGIFXRPsXZjHsnO4XkQmlSIIQwrlyi1fj0ORFGQkmZ7I4vdUCltlfK9GJ1Q4cfwop188x8X6y5S3XTTFol6HpdsOI4RDfjpJMpWhWL/OxMxBNi81UYXLo4/+FlsrJc7wFB9//H4qlQ1MM817P/AOCsUWP/jeKabzNs+ePE9iIsX6dpP77r+L82eW+Y9vnuS3P/EelpbmOHP2Cmt1n19fPMCLz59FkYLJbIKxXI64beL5EeV6h0RuDE8ILq2VaLsRsVgCqai0O210V6PTDCmrPQw74I50inffc5Dl5Q3W3TZp2yZpW2xWu3ibVexkcvAOvI5lasgoRDFVVGIEgYZt26QsCKKIWq1JQoejC3ne9a6HefjR95NKjHH50jqrV1cpbG+yeuUKhc0NDEtBCIGenaXb8Vmv1/AjiWYl6EmTA7fdSdNx0VQDz1dRjRgzU1NEfo9Oo0GlVCAIQnRdoAqfTMoilYozls0zu2ccTdNwuh0Cz+1P0+70aLda6KrA0lUkIVIIAj/AkwpKKkcUGawuX8ftdklm0mQzabqtgE99+o955tmn+NH3vk+3FpJNm+TmkjQ2PZJ2/69CKxZnZu8Cxe0CYdshO5YgQEXVQEYhKWOclJVmYo+F1arTqBSIwhDXdYlkhBdJWi0HlS6xWAoRSdxOk9m9Rzl89D2sXF/G7TawVEkUhnTaHXpdB7frYcdtQOD0emxvF3Edl7gdB03FTKRIjWssHpvGUm3OnVsnigxq5TbJyS5S9MBPYBk9FudV7rnrQQqraQJTJWkLhKKixl4hlh1j5tCdKOoVok4DIx4nrQk0DbrtOo2Gg6ILEukEvusQhjlmDyzSqRUIo/6Tl2bM4La772bj+jp2chOeu7VHnYciKSAUdDVFpDtEkc/2Rpt9B6Y4f2mZfTNjeO0U5dUVXrh4DkXTmZxJYlkqi0dOYCdanNi/H0XRSJ6YRuAxNrWf/2qf5uPHHkDSZGpPDjsbUr3aY2rc5szpVaLQ5vDRWS6erVFdL9Ju1cnnLe65+yDJZJq7js1x9twK6+UmZ16+BlH/FeepsTF6PZ9Oo00oJbgOlqGxvl0maVv4QYSUIYoSw1R9ICQMIJlJcmApS+DV0ZR+4ZFqucLBg/N0I59mq8bkWBzDEoRehK6DFBGBGkHgo8kQO5FAhj5CsagXK3zwnUv8we99giNHjxGpOudeuMBXv/wVXvz5zwm9NinbRCCJmRCzbSKhsLxepdp0aTbbKEJhbGyc8fw00kgwMzGLZsaIGyaqjFi5dHkw4aqD63SIAhcROiRMaMV18rOTTM3kicVjREFA4Hcpl0sEPQ+v20PTBHHbQtUNGnWXtc1VqvU2lWoDDJ2YnSFmZ+h2PLquR6TY/Ns3/5Unn3kCKy45cc8dmIrBxrVrbK51mJnLYxg6G5tV4sk4l64u0/WapMwcpm7iCw/pKKg+VDZrjC1MEYQ9et02fugSBC5B4ON7br9mQiBRTY1gUJQ1l00zf+B2qq1t2u0WXrdJoEkUTcXxu1gxi2Q6SRj5bG8XCMKIdrOF67h4fkB2MsfMTJaOG/LsU6tMzzXI5Uz27DGYORRnvVLDdQ3uOGFTrJfwL0xQ3VKYGg/J7h3Hc1Va7hhW/AjPn/ohl89cYm52hrhq0Gw10TSNKAwIfAenUSQ9McHEvv14XRczkSbAxUok+k+6ev1p+6VU2DO/xOzcIvzLd2/pchyKpKAIlY21OjE7ZP7AHKVSyKEDKZ59+tvsX5znkY/cz7FjB9hYu5ennv4Z49MWsaTB17/1U/YvzfArDx1j62qJMV2yuP8IT//0NHN748SSGjWnSTIlUCJBSoftjas88ugCP372Mi/+tMy+yYN84P3vol4P2Dc7i+83KRSvMjObIJOO0XEjLr68yb0HxzETNiFQqtYpFisYhiBrGownsqjjcWLxOFeW62i6gUJEMpUkDALGMlkCVSXwE9SbTYrdDjFDI5dJYugqhhERj2sYHgREKLqKqmrUWg5oCroqcN0eTq9HOh5D8QM+9J538KnPfJpCo8up58/y0ovnePbkKdY21vF6HjohjqsRi9tohkXgSbquS6XiMjuZ4v479zM+Nk4UaThBRKDpFEoVyqUq8USc/Xv3sGfvbP8hnVaB0uZ1em0HU1FJpSwSmTSqYVKvtShuFbBMjVQ2ydz8DHJQibnneLSaLjXHxfNDolCiGwbZsTHcKCKMItxA0O2FWPEYrusReBHdRgMXjdW1Ve5YupOGE6IIiRMFNNsOlqWTTmo4mkut1EFaer8yky7wPR8rJohnVerVBmsrr9CsFTASBq7vI0MIgwgkCAGxeJxCpcVWscLx2/bSaTuUmzXa7SY6EsfpodOfeiwIA6TfnxSo0+nQbrSIZIRqGsTTCkfuSZAaG+PSxTbJyQx2zmN2KsNEPMHCgmDWM3np5RpeUGdqMkGlWCQ9vk0sOcNmpc0rL1/ggeMf5foVydq1S9gxSbG8RcrQ8JolpO+TyqXJT+8lmbAQUqKrKvpYjkhCbbuGdDaYmJlDFRrNapnaVgnXh0azdcvX41suBvN2IIQoAR2gvNMuvwTj7G5/2P3HsNv94e09hn1Syok322kokgKAEOL0rVSvGVZ2uz/s/mPY7f4wHMfwFuZjGTFixP8HRklhxIgRNzFMSeEfdlrgl2S3+8PuP4bd7g9DcAxDM6YwYsSI4WCYegojRowYAnY8KQghHhJCXBZCLAshPrvTPreKEGJVCHFOCHFGCHF60JYTQvxACPHKYJndac8bEUJ8UQhRFEKcv6HtdZ1Fn78ZxOWsEOL4zpn/j+vr+X9eCLExiMMZIcSHb9j25wP/y0KID+2M9S8QQswJIX4khLgghHhJCPEng/bhisGr747vxAdQgSvAfsAAXgSO7KTTW3BfBcZf0/aXwGcH658FvrDTnq/xexA4Dpx/M2f69UD/k/5zO/cBp4bU//PAn73OvkcG55MJLAzOM3WH/aeB44P1JP3ijkeGLQY73VN4J7AspVyRUnrA14DHdtjpl+Ex4EuD9S8BH91Bl/+FlPLHQPU1zW/k/Bjwz7LPSSAjhJj+vzF9fd7A/414DPialNKVUl6lX/D4nW+b3C0gpdySUv58sN4CLgKzDFkMdjopzAJrN3xfH7TtBiTwfSHE80KIPxy0TUkptwbr28DUzqi9Jd7IeTfF5jOD7vUXb7hlG2p/IcQ8cBdwiiGLwU4nhd3MA1LK48DDwKeFEA/euFH2+3+76q+d3egM/D1wAHgHsAX81c7qvDlCiATwdeBPpZTNG7cNQwx2OilsAHM3fN8zaBt6pJQbg2UR+Cb9rmnh1e7dYFncOcNb5o2cd0VspJQFKWUopYyAf+QXtwhD6S+E0OknhK9IKb8xaB6qGOx0UngOWBRCLAghDOBjwHd22OlNEULYQojkq+vAB4Hz9N0/Odjtk8C3d8bwLfFGzt8BfmcwAn4f0Lihizs0vOYe+3H6cYC+/8eEEKYQYgFYBG5t5tK3CSGEAP4JuCil/OsbNg1XDHZyNPaGEdaX6Y8Of26nfW7ReT/9ke0XgZde9QbGgCeBV4AngNxOu77G+6v0u9g+/fvT338jZ/oj3n87iMs54O4h9f/ywO8s/Yto+ob9Pzfwvww8PAT+D9C/NTgLnBl8PjxsMRg90ThixIib2OnbhxEjRgwZo6QwYsSImxglhREjRtzEKCmMGDHiJkZJYcSIETcxSgojRoy4iVFSGDFixE2MksKIESNu4r8BkXOq3RuftUQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcace0e6cf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted caption:\n",
+      " a bird is standing in the grass near trees eeee\n",
+      "\n",
+      "True captions:\n",
+      "A couple of giraffe snuggling each other in a forest.\n",
+      "A couple of giraffe standing next to some trees.\n",
+      "Two Zebras seem to be embracing in the wild. \n",
+      "Two giraffes hang out near trees and nuzzle up to each other.\n",
+      "The two giraffes appear to be hugging each other.\n"
+     ]
+    }
+   ],
+   "source": [
+    "generate_caption_coco(idx=10, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here is a picture from the validation-set which was not used during training of the model. Sometimes the model can produce good captions for images it hasn't seen during training and sometimes it can't. Can you make a better model?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fcace068748>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Predicted caption:\n",
+      " a brown bear is sitting in a grassy field eeee\n",
+      "\n",
+      "True captions:\n",
+      "A big burly grizzly bear is show with grass in the background.\n",
+      "The large brown bear has a black nose.\n",
+      "Closeup of a brown bear sitting in a grassy area.\n",
+      "A large bear that is sitting on grass. \n",
+      "A close up picture of a brown bear's face.\n"
+     ]
+    }
+   ],
+   "source": [
+    "generate_caption_coco(idx=1, train=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to generate captions for images. We used a pre-trained image-model (VGG16) to generate a \"thought-vector\" of what the image contains, and then we trained a Recurrent Neural Network to map this \"thought-vector\" to a sequence of words.\n",
+    "\n",
+    "This works reasonably well, although it is easy to find examples both in the training- and validation-sets where the captions are incorrect.\n",
+    "\n",
+    "It is also important to understand that this model doesn't have a human-like understanding of what the images contain. If it sees an image of a giraffe and correctly produces a caption stating that, it doesn't mean that the model has a deep understanding of what a giraffe is; the model doesn't know that it's a tall animal that lives in Africa and Zoos.\n",
+    "\n",
+    "The model is merely a clever way of mapping pixels in an image to a vector of floating-point numbers that summarize the contents of the image, and then map these numbers to a sequence of integers-tokens representing words. So the model is basically just a very advanced function approximator rather than human-like intelligence."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Train the model for more epochs. Does it improve the quality of the generated captions?\n",
+    "* Try another architecture for the Recurrent Neural Network, e.g. change the number of GRU layers, their internal state-size, the embedding-size, etc. Can you improve the quality of the generated captions?\n",
+    "* Use another transfer-layer from the VGG16-model, for example the flattened output of the last convolutional layer.\n",
+    "* Try adding more dense-layers to the mapping between the transfer-values and the initial-state in the decoder.\n",
+    "* When generating captions, instead of using `np.argmax()` to sample the next integer-token, could you sample the decoder's output as if it was a probability distribution instead? Note that the decoder's output is not softmax-limited so you have to do that first to turn it into a probability-distribution.\n",
+    "* Can you generate multiple sequences by doing this sampling? Can you find a way to select the best of these different sequences?\n",
+    "* Connect the image-model directly to the decoder so you can fine-tune the weights of the image-model. See Tutorial #10 on Fine-Tuning.\n",
+    "* Can you train a Machine Translation model from Tutorial #21 and then connect its decoder to a pre-trained image-model to make an image captioning model? Perhaps you need an intermediate fully-connected layer that you will train.\n",
+    "* Can you measure the quality of the generated captions using some mathematical formula?\n",
+    "* Modify the decoder so it also returns the states of the GRU-units. Then change `generate_caption()` so it only inputs and outputs one integer-token in each iteration. You need to get the GRU-states out of `decoder_model.predict()` and feed them back in next time you call it. Now you compute less in each iteration, but there is still a lot of overhead, so it may not be much faster when using a GPU?\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2018 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/coco.py b/coco.py
new file mode 100644
index 0000000..42cecf9
--- /dev/null
+++ b/coco.py
@@ -0,0 +1,205 @@
+########################################################################
+#
+# Functions for downloading the COCO data-set from the internet
+# and loading it into memory. This data-set contains images and
+# various associated data such as text-captions describing the images.
+#
+# http://cocodataset.org
+#
+# Implemented in Python 3.6
+#
+# Usage:
+# 1) Call set_data_dir() to set the desired storage directory.
+# 2) Call maybe_download_and_extract() to download the data-set
+#    if it is not already located in the given data_dir.
+# 3) Call load_records(train=True) and load_records(train=False)
+#    to load the data-records for the training- and validation sets.
+# 5) Use the returned data in your own program.
+#
+# Format:
+# The COCO data-set contains a large number of images and various
+# data for each image stored in a JSON-file.
+# Functionality is provided for getting a list of image-filenames
+# (but not actually loading the images) along with their associated
+# data such as text-captions describing the contents of the images.
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2018 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import json
+import os
+import download
+from cache import cache
+
+########################################################################
+
+# Directory where you want to download and save the data-set.
+# Set this before you start calling any of the functions below.
+# Use the function set_data_dir() to also update train_dir and val_dir.
+data_dir = "data/coco/"
+
+# Sub-directories for the training- and validation-sets.
+train_dir = "data/coco/train2017"
+val_dir = "data/coco/val2017"
+
+# Base-URL for the data-sets on the internet.
+data_url = "http://images.cocodataset.org/"
+
+
+########################################################################
+# Private helper-functions.
+
+def _load_records(train=True):
+    """
+    Load the image-filenames and captions
+    for either the training-set or the validation-set.
+    """
+
+    if train:
+        # Training-set.
+        filename = "captions_train2017.json"
+    else:
+        # Validation-set.
+        filename = "captions_val2017.json"
+
+    # Full path for the data-file.
+    path = os.path.join(data_dir, "annotations", filename)
+
+    # Load the file.
+    with open(path, "r", encoding="utf-8") as file:
+        data_raw = json.load(file)
+
+    # Convenience variables.
+    images = data_raw['images']
+    annotations = data_raw['annotations']
+
+    # Initialize the dict for holding our data.
+    # The lookup-key is the image-id.
+    records = dict()
+
+    # Collect all the filenames for the images.
+    for image in images:
+        # Get the id and filename for this image.
+        image_id = image['id']
+        filename = image['file_name']
+
+        # Initialize a new data-record.
+        record = dict()
+
+        # Set the image-filename in the data-record.
+        record['filename'] = filename
+
+        # Initialize an empty list of image-captions
+        # which will be filled further below.
+        record['captions'] = list()
+
+        # Save the record using the the image-id as the lookup-key.
+        records[image_id] = record
+
+    # Collect all the captions for the images.
+    for ann in annotations:
+        # Get the id and caption for an image.
+        image_id = ann['image_id']
+        caption = ann['caption']
+
+        # Lookup the data-record for this image-id.
+        # This data-record should already exist from the loop above.
+        record = records[image_id]
+
+        # Append the current caption to the list of captions in the
+        # data-record that was initialized in the loop above.
+        record['captions'].append(caption)
+
+    # Convert the records-dict to a list of tuples.
+    records_list = [(key, record['filename'], record['captions'])
+                    for key, record in sorted(records.items())]
+
+    # Convert the list of tuples to separate tuples with the data.
+    ids, filenames, captions = zip(*records_list)
+
+    return ids, filenames, captions
+
+
+########################################################################
+# Public functions that you may call to download the data-set from
+# the internet and load the data into memory.
+
+
+def set_data_dir(new_data_dir):
+    """
+    Set the base-directory for data-files and then
+    set the sub-dirs for training and validation data.
+    """
+
+    # Ensure we update the global variables.
+    global data_dir, train_dir, val_dir
+
+    data_dir = new_data_dir
+    train_dir = os.path.join(new_data_dir, "train2017")
+    val_dir = os.path.join(new_data_dir, "val2017")
+
+
+def maybe_download_and_extract():
+    """
+    Download and extract the COCO data-set if the data-files don't
+    already exist in data_dir.
+    """
+
+    # Filenames to download from the internet.
+    filenames = ["zips/train2017.zip", "zips/val2017.zip",
+                 "annotations/annotations_trainval2017.zip"]
+
+    # Download these files.
+    for filename in filenames:
+        # Create the full URL for the given file.
+        url = data_url + filename
+
+        print("Downloading " + url)
+
+        download.maybe_download_and_extract(url=url, download_dir=data_dir)
+
+
+def load_records(train=True):
+    """
+    Load the data-records for the data-set. This returns the image ids,
+    filenames and text-captions for either the training-set or validation-set.
+    
+    This wraps _load_records() above with a cache, so if the cache-file already
+    exists then it is loaded instead of processing the original data-file.
+    
+    :param train:
+        Bool whether to load the training-set (True) or validation-set (False).
+
+    :return: 
+        ids, filenames, captions for the images in the data-set.
+    """
+
+    if train:
+        # Cache-file for the training-set data.
+        cache_filename = "records_train.pkl"
+    else:
+        # Cache-file for the validation-set data.
+        cache_filename = "records_val.pkl"
+
+    # Path for the cache-file.
+    cache_path = os.path.join(data_dir, cache_filename)
+
+    # If the data-records already exist in a cache-file then load it,
+    # otherwise call the _load_records() function and save its
+    # return-values to the cache-file so it can be loaded the next time.
+    records = cache(cache_path=cache_path,
+                    fn=_load_records,
+                    train=train)
+
+    return records
+
+########################################################################
diff --git a/images/22_image_captioning_flowchart.png b/images/22_image_captioning_flowchart.png
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diff --git a/images/22_image_captioning_flowchart.svg b/images/22_image_captioning_flowchart.svg
new file mode 100644
index 0000000..2df11f7
--- /dev/null
+++ b/images/22_image_captioning_flowchart.svg
@@ -0,0 +1,4209 @@
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From 9a5ee2615752453eab549f603fc3a63eed2b7bd0 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 17 Mar 2018 12:20:21 +0100
Subject: [PATCH 40/61] Added Tutorial 22

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 4c51279..9e4ee47 100644
--- a/README.md
+++ b/README.md
@@ -61,6 +61,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 21. Machine Translation ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
 
+22. Image Captioning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).

From 8f668109f9c395af0d8f0c09a9e509723b46eadb Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 26 Mar 2018 13:29:21 +0200
Subject: [PATCH 41/61] Added Tutorial 23

---
 23_Time-Series-Prediction.ipynb     | 2576 ++++++++++++++++++++++++
 README.md                           |    2 +
 images/23_time_series_flowchart.png |  Bin 0 -> 165046 bytes
 images/23_time_series_flowchart.svg | 2842 +++++++++++++++++++++++++++
 images/Denmark.jpg                  |  Bin 0 -> 253626 bytes
 images/Europe.jpg                   |  Bin 0 -> 207611 bytes
 weather.py                          |  255 +++
 7 files changed, 5675 insertions(+)
 create mode 100644 23_Time-Series-Prediction.ipynb
 create mode 100644 images/23_time_series_flowchart.png
 create mode 100644 images/23_time_series_flowchart.svg
 create mode 100644 images/Denmark.jpg
 create mode 100644 images/Europe.jpg
 create mode 100644 weather.py

diff --git a/23_Time-Series-Prediction.ipynb b/23_Time-Series-Prediction.ipynb
new file mode 100644
index 0000000..a5844dc
--- /dev/null
+++ b/23_Time-Series-Prediction.ipynb
@@ -0,0 +1,2576 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TensorFlow Tutorial #23\n",
+    "# Time-Series Prediction\n",
+    "\n",
+    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Introduction\n",
+    "\n",
+    "This tutorial tries to predict the future weather of a city using weather-data from several other cities.\n",
+    "\n",
+    "Because we will be working with sequences of arbitrary length, we will use a Recurrent Neural Network (RNN).\n",
+    "\n",
+    "You should be familiar with TensorFlow and Keras in general, see Tutorials #01 and #03-C, and the basics of Recurrent Neural Networks as explained in Tutorial #20."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Location\n",
+    "\n",
+    "We will use weather-data from the period 1980-2018 for five cities in [Denmark](https://en.wikipedia.org/wiki/Denmark):\n",
+    "\n",
+    "* **[Aalborg](https://en.wikipedia.org/wiki/Aalborg)** The weather-data is actually from an airforce base which is also home to [The Hunter Corps (Jægerkorps)](https://en.wikipedia.org/wiki/Jaeger_Corps_(Denmark).\n",
+    "* **[Aarhus](https://en.wikipedia.org/wiki/Aarhus)** is the city where [the inventor of C++](https://en.wikipedia.org/wiki/Bjarne_Stroustrup) studied and the [Google V8 JavaScript Engine](https://en.wikipedia.org/wiki/Chrome_V8) was developed.\n",
+    "* **[Esbjerg](https://en.wikipedia.org/wiki/Esbjerg)** has a large fishing-port.\n",
+    "* **[Odense](https://en.wikipedia.org/wiki/Odense)** is the birth-city of the fairytale author [H. C. Andersen](https://en.wikipedia.org/wiki/Hans_Christian_Andersen).\n",
+    "* **[Roskilde](https://en.wikipedia.org/wiki/Roskilde)** has an old cathedral housing the tombs of the Danish royal family."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following map shows the location of the cities in Denmark:\n",
+    "\n",
+    "![Map of Denmark](images/Denmark.jpg)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following map shows the location of Denmark within Europe:\n",
+    "\n",
+    "![Map of Europe](images/Europe.jpg)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Flowchart\n",
+    "\n",
+    "In this tutorial, we are trying to predict the weather for the Danish city \"Odense\" 24 hours into the future, given the current and past weather-data from 5 cities (although the flowchart below only shows 2 cities).\n",
+    "\n",
+    "We use a Recurrent Neural Network (RNN) because it can work on sequences of arbitrary length. During training we will use sequences of 100 data-points from the training-set, with each data-point or observation having 20 input-signals for the temperature, pressure, etc. for each of the 5 cities. We then want to train the neural network so it outputs the 3 signals for tomorrow's temperature, pressure and wind-speed."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Flowchart](images/23_time_series_flowchart.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "from sklearn.preprocessing import MinMaxScaler"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We need to import several things from Keras."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from tf.keras.models import Sequential  # This does not work!\n",
+    "from tensorflow.python.keras.models import Sequential\n",
+    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.python.keras.optimizers import RMSprop\n",
+    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 (Anaconda) and package versions:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.5.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.1.2-tf'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.keras.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.22.0'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load Data\n",
+    "\n",
+    "Weather-data for 5 cities in Denmark will be downloaded automatically below.\n",
+    "\n",
+    "The raw weather-data was originally obtained from the [National Climatic Data Center (NCDC), USA](https://www7.ncdc.noaa.gov/CDO/cdoselect.cmd). Their web-site and database-access is very confusing and may change soon. Furthermore, the raw data-file had to be manually edited before it could be read. So you should expect some challenges if you want to download weather-data for another region. The following Python-module provides some functionality that may be helpful if you want to use new weather-data, but you will have to modify the source-code to fit your data-format."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import weather"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download the data-set if you don't have it already. It is about 35 MB."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data has apparently already been downloaded and unpacked.\n"
+     ]
+    }
+   ],
+   "source": [
+    "weather.maybe_download_and_extract()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "List of the cities used in the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Aalborg', 'Aarhus', 'Esbjerg', 'Odense', 'Roskilde']"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cities = weather.cities\n",
+    "cities"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load and resample the data so it has observations at regular time-intervals for every 60 minutes. Missing data-points are linearly interpolated. This takes about 30 seconds to run the first time but uses a cache-file so it loads very quickly the next time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 8 ms, sys: 24 ms, total: 32 ms\n",
+      "Wall time: 130 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "df = weather.load_resampled_data()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the top rows of the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Aalborg</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Aarhus</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Esbjerg</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Odense</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Roskilde</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DateTime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 11:00:00</th>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>1007.766667</td>\n",
+       "      <td>10.2</td>\n",
+       "      <td>280.000000</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.300000</td>\n",
+       "      <td>15.4</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>6.083333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.383333</td>\n",
+       "      <td>310.000000</td>\n",
+       "      <td>6.142857</td>\n",
+       "      <td>1011.066667</td>\n",
+       "      <td>12.585714</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11.466667</td>\n",
+       "      <td>280.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 12:00:00</th>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>1008.000000</td>\n",
+       "      <td>10.3</td>\n",
+       "      <td>290.000000</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.600000</td>\n",
+       "      <td>13.4</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>6.583333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.883333</td>\n",
+       "      <td>310.000000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>1011.200000</td>\n",
+       "      <td>11.300000</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.466667</td>\n",
+       "      <td>280.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 13:00:00</th>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>1008.066667</td>\n",
+       "      <td>9.7</td>\n",
+       "      <td>290.000000</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.433333</td>\n",
+       "      <td>15.4</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>6.888889</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13.244444</td>\n",
+       "      <td>309.444444</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>1011.300000</td>\n",
+       "      <td>12.118182</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.166667</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13.133333</td>\n",
+       "      <td>278.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 14:00:00</th>\n",
+       "      <td>4.333333</td>\n",
+       "      <td>1008.133333</td>\n",
+       "      <td>11.1</td>\n",
+       "      <td>283.333333</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.266667</td>\n",
+       "      <td>14.9</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>6.222222</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.911111</td>\n",
+       "      <td>306.111111</td>\n",
+       "      <td>6.857143</td>\n",
+       "      <td>1011.400000</td>\n",
+       "      <td>12.742857</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.833333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.300000</td>\n",
+       "      <td>270.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 15:00:00</th>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>1008.200000</td>\n",
+       "      <td>11.3</td>\n",
+       "      <td>280.000000</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.100000</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.555556</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.577778</td>\n",
+       "      <td>302.777778</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>1011.500000</td>\n",
+       "      <td>12.400000</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>4.833333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>12.300000</td>\n",
+       "      <td>270.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Aalborg                                    Aarhus  \\\n",
+       "                         Temp     Pressure WindSpeed     WindDir   Temp   \n",
+       "DateTime                                                                  \n",
+       "1980-03-01 11:00:00  5.000000  1007.766667      10.2  280.000000    5.0   \n",
+       "1980-03-01 12:00:00  5.000000  1008.000000      10.3  290.000000    5.0   \n",
+       "1980-03-01 13:00:00  5.000000  1008.066667       9.7  290.000000    5.0   \n",
+       "1980-03-01 14:00:00  4.333333  1008.133333      11.1  283.333333    5.0   \n",
+       "1980-03-01 15:00:00  4.000000  1008.200000      11.3  280.000000    5.0   \n",
+       "\n",
+       "                                                     Esbjerg           \\\n",
+       "                        Pressure WindSpeed WindDir      Temp Pressure   \n",
+       "DateTime                                                                \n",
+       "1980-03-01 11:00:00  1008.300000      15.4   290.0  6.083333      NaN   \n",
+       "1980-03-01 12:00:00  1008.600000      13.4   280.0  6.583333      NaN   \n",
+       "1980-03-01 13:00:00  1008.433333      15.4   280.0  6.888889      NaN   \n",
+       "1980-03-01 14:00:00  1008.266667      14.9   300.0  6.222222      NaN   \n",
+       "1980-03-01 15:00:00  1008.100000      17.0   290.0  5.555556      NaN   \n",
+       "\n",
+       "                                              Odense                          \\\n",
+       "                     WindSpeed     WindDir      Temp     Pressure  WindSpeed   \n",
+       "DateTime                                                                       \n",
+       "1980-03-01 11:00:00  12.383333  310.000000  6.142857  1011.066667  12.585714   \n",
+       "1980-03-01 12:00:00  12.883333  310.000000  7.000000  1011.200000  11.300000   \n",
+       "1980-03-01 13:00:00  13.244444  309.444444  7.000000  1011.300000  12.118182   \n",
+       "1980-03-01 14:00:00  12.911111  306.111111  6.857143  1011.400000  12.742857   \n",
+       "1980-03-01 15:00:00  12.577778  302.777778  6.000000  1011.500000  12.400000   \n",
+       "\n",
+       "                             Roskilde                                  \n",
+       "                    WindDir      Temp Pressure  WindSpeed     WindDir  \n",
+       "DateTime                                                               \n",
+       "1980-03-01 11:00:00   290.0  5.000000      NaN  11.466667  280.000000  \n",
+       "1980-03-01 12:00:00   290.0  5.000000      NaN  12.466667  280.000000  \n",
+       "1980-03-01 13:00:00   290.0  5.166667      NaN  13.133333  278.333333  \n",
+       "1980-03-01 14:00:00   290.0  5.833333      NaN  12.300000  270.000000  \n",
+       "1980-03-01 15:00:00   290.0  4.833333      NaN  12.300000  270.000000  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Missing Data\n",
+    "\n",
+    "The two cities Esbjerg and Roskilde have missing data for the atmospheric pressure, as can be seen in the following two plots. \n",
+    "\n",
+    "Because we are using resampled data, we have filled in the missing values with new values that are linearly interpolated from the neighbouring values, which appears as long straight lines in these plots.\n",
+    "\n",
+    "This may confuse the neural network. For simplicity, we will simply remove these two signals from the data.\n",
+    "\n",
+    "But it is only short periods of data that are missing, so you could actually generate this data by creating a predictive model that generates the missing data from all the other input signals. Then you could add these generated values back into the data-set to fill the gaps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb464ab7ba8>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb464b19780>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Esbjerg']['Pressure'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb46057fa20>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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Zpz+mnWcJgK3Zyuz1e7FoS80aEMdduqFGfhOnz/Kod+fhoa+WYa1i/cUolYYyTfzBY+Yut9FrEvr7/XdmtUvzzzZjJj4s3mIYt7B1/9GoBerINkko/fN2a5ll6fpuutEr/j0T//zeeMFfK2V5BCeL/ErT5N+/NC4clAA6gpWEGyK/f5mOj3pZhTcurpWVAiPfnIN7bFade2fWRluV5dw06O0+V7D73b9/1dxutULgsbIK0xQXTojEVig70X5P/oglW6MV2tWvz0L/J6MHEnZqMwTFR8Wbcea4H0JVRU25iL5u92G88INzU9nuQydwy//m1hjgRJ8g+u2Pilnbh8XhTTfvFawkbGJnHWLeJuMqX1b5enGJ5nazqez9ny7BDW8XawY8HS+zNgK3YgarqBSWEs3tUcU5eDHKshqVOm/TPkxdWTNuwquRnvo8G1Wziemrd2ODSbI+PSorBR6fuKJGenkv0fuZIwOT2R6lYLFjVdWLc7Gb1NCwrsXBY/h2yXbc+s5cy+f7IAkUgxJWEm6QW59eR/Pw19H5fpz2R3p5oKx4mOw5dALPTakZ5ORl5bunvl8Ztdinh9oeHos0giPHz5ZMeTqX2utyncNvN0sCYf7m/Xh56lr8n04yPy9w6lVk9Td08lvrlUnVMu26xc5gQSsFuZ/ZEYKGlYQLzBp+pFSj/vGWL6TJoKeteYLYtVHbRWuEboVYPDc/rtyF137Wj2QuengyFmusddhFnYxNnTLEDZEOZv4m/0p++uGxY3WNSwiBNTu1Y2qspt12yifzpKjrnTbinNTfyyiluNU2Xnq0DKc+OhlPfheulBwAKwnbKH9zu52cen+jvDeRi5nu4yFai8BWvmM8j5IAYKUPvvlPfrcSt79nPPJPhPyDRj/91JW7qmpSRLKqHtTxCBz0tHbG2lv+Z80MZCWti1b6baVJS72OVHWc4vWWfUewZGv04K/HQ5Nc/5bzNu3DjgPH8a8fvfV+8wJWEh5g1ECMPFjMps3fLd2Otvd9E+U5YxchhKkdWO26qoXed5yyfIfjbJV+Fsyxw6FjZTjnqamen/fLhds8P2fYiLiBqwsoAZLHlVFNighGQwyrbf+ZSfopQSKKof9TU9Hm3m90n8kLXvjZ9Dqz12s/K+o8YhHMarfEA6wkbBIVTKexTc3NFkdCWkyRvSi0XD8j6E3TI1gZ4//iwhx1/VvOa1P8d+ZGz+MGnHDoeDm2BaCw4nwCBgBVgXlmLtxOsXpeK55iEWcC9dqYFa5+fRZGvDFbd7D08lTtdvy3L5eZ1l35fMFWlLv0hPQTVhIu+NOHC0yTlC0vUebg974hbNprbvs2mwobFUgSAF6Ystq3TsAoweC2/UdRMOZrTJjnrzeJm87aTc7/GWt3Y+ISbc81RiJibS09UoaCMV9j/C/rNfczKpWqxkmK9+mrd2Paql147Bv7awb7j5QZPvlPTFyJ+R55QvoBKwkX/Ghhwfa4BVupGUadvLlXhfn5jUwCi7bsxz8nrdKdTvvJanmWZCWls5u1Gz/HcK8ZpP9+9JsVuPl/8wyPJ0qMtQu3lByQgvf+/uUynT1ic5PsLHBHMPv9tu4/itrpqQ4l8h9WEjbRmg0YuZMq+y4/6sL4XbPCbUBgBLP0BVrYWRD/2EGuqQhuzG1mqN2g7bJxzxHD3zgs+sONHF6Y3bTcUqvO7/70rrCi5LtYjE4PgrSgBUgEDhvkcFI2kJenGkeG+oWVNNh6C3JeuSDeN8F+wkE7GMn572nr0CKrtu7ns3S+u1dYuYfqJHJWMVuTShbczLYZY5JuJvHlwm0Y7SIoSavBvWiSQROQ7KDP66QPOHrCuUnKrFjOjgPWpsd6aS+84gNV3ikrXDveWmK292dvwk+rjU1/D34RXFqJs8bp56+KsPew/u9k1AEeOFaOrxYF60X1+ET/ffsnLzP2EjIaCLkd6Hjh4m22MB2LwFKnJJ2SuP29+fh8gbcPlZWMmHd9qF9P1yy76T4Dzw0nNtJYY6VqnxFGyecAYMyExVG1IcKGXmyAEleL5yXB1mB4eepaHHEx0LGCWdU7I3NT0BAIJ4+daLhPmGc7SackgsLInJBi0gkaRW7/9bMlGGmWuC7gB2i6ic3fbKSmF+QUK8IeLGiUV+nm/86tKjXqJ//9daP5Tj5iNpAIO2FuYkm7JlFZKZASw+GH0Uhr1np3tZKteFkFyTQT+d6cscHwcztFY/xgYsgr7OmtJwHAxKXbUfIf/2NAjPKIOV1vsYPZQMsodUYYCLGOSN6ZhF56b685cqIC5RWVuh3d8pID+MdXem593hD0GMtMCXyjk+U2LChrQPjBmp0HDYMS3QZa+VXUxyoX/esX369hNpHo8VBwZWhHvmm+thbm2WrSziTKKgRqOfj2Tn5LI3OLOjFcMjJnQ3gDiWKBWaLGWCwMu8VJuVurDH5GO6+TEj8HQrHovsNcEjWpZhLKHEVOoi6d8tXCcI+UGWOCNnfP8zH7azwQSQ5ohJ+/kV/ZBpQE6X1nRlIpicteqXbzLHPocePEVS1o97agO7l4Jx4qyCU7flprZqx1t2YY7ySVklDidCbhRe2BWHP4uL/uiYmOlTgYhklUkldJOJxJ6JUSNWLCPPPcQ36yOGAXUobxG7+LEyUzSaMktu2P9lBxbG4KrxMCwyQtv65LbpOQnySFknhn1kacoUqNEMuFa4ZhmHglKZTE/Z8uqbHN6UyCYRgmmUgKJaHFiXK2GzFMouB3wGMyY6okiOgNItpJREsU2xoS0SQiWi3/z5G3X0VEi4hoMRHNIKLuimOGENFKIlpDRGP8+TrWcbpwHbQ7K8MwTCyxMpN4E8AQ1bYxAKYIIToAmCK/B4D1AM4WQnQF8A8ArwIAEaUC+BeA8wF0BnAlEXV2Lb0LynhNgmEYxhRTJSGE+AmAOoPYcABvya/fAnCRvO8MIUQkx8JMAK3k130ArBFCrBNCnADwvnyOmNAgs2b+DcczCZ5IMAyTRDjN3dRUCBEJGNgOoKnGPtcD+FZ+3RKAsurMFgCnOry2ZeZu3IcXfliNco3Smc4jrhmGYZIH1wn+hBCCiKL6TiIaAElJnGX3fER0E4CbACAvL8+VbKPfn6+7oOXUBZZnEgzDJBNOvZt2EFFzAJD/74x8QETdALwGYLgQIhLhshVAa8XxreRtNRBCvCqEKBJCFDVu3NiheBKVGjOICE7NTQzDMMmEUyXxBYAR8usRAD4HACLKAzABwNVCCGW9wTkAOhBRGyLKAHCFfA5fMar/zAvXDMMw5piam4joPQD9AeQS0RYADwIYB+BDIroewEYAv5N3HwugEYCX5HKC5fKsoJyIbgPwHYBUAG8IIXzPjWswkUCZ40IubG9iGCZ5MFUSQogrdT4aqLHvDQBu0DnPNwC+sSWdS9jcxDAM446Ejrg2MjfxwjXDMIw5Ca0keCbBMAzjjsRWEkZrEjyTYBiGMSXBlYSBd5PDmYTRORmGYRKNhFYSFWxuYhiGcUVCKwmjUb/TVOE8j2AYJplIcCWh/xnPJBiGYcxJaCVhZG7ihWuGYRhzXCf4CyMnyisx06QwOpcvZRiGMSchZxIHj5XhmjdmG+7D5iaGYRhzElJJWMFxxDUvXTMMk0QkrZJwbG5iHcEwTBKRkEpCzkBriOPypY6OYhiGiU8SUklYYcnWAzhwrCxoMRiGYUJN0ioJAPhsvmZxPEME+8AyDJNEJKSS0DI21auVkN6+DMMwvpKQSkJrrD/w5CY1tpmvXFg7N8MwTKKSkEqiTkYqAOCyXq2Md7SwwK2GrU0MwyQTCakkMtNTsf6xofjj2W2rtjmZNTAMwyQ7CakkAMkNNkUxU9Byi2VzE8MwjDEJqyQAIDVFoSQ8Oid7NzEMk0wktJJIcbDmwDAMw1ST2EoixVhJsA5hGIYxJqGVRKpSC2goBCeWIzY2MQyTTCS0kkhRfDvS0BKOkvyxlmAYJolIaCWRGuXdVPPz4w7ThTMMwyQLia0kTNYkjpVV2D4n15NgGCaZSGgloVy4zqqdXuPzTXuOxFIchmFCSl05SwNTk4RWEkpz092DT6rx+fzN+22fk8MkGIZJJhJbSShmErUzUtGhSb2oz9fvPoxym4vXzbIyPZGNYZjwwGM/fRJaSaiD6So1pgErdxy0dc5+HRq7kolhmPDBFgJ9ElpJqBeutRrCvE32TU4MwzDJQkIrCbVzk9ZMYv7GfTGShmEYJv5IaCWhzvxaoVISRfk5mLeJlQTDMIweCa0k1FSq1qh7FeRgw54j2HPoeDACMQwTCvyOf5p4R1/0Pyk+1zOTSkmo03wX5TcEAMzndQmGYXwku3YGGmTWjNWKB0yVBBG9QUQ7iWiJYltDIppERKvl/znydiKi54loDREtIqJCxTEj5P1XE9EIf76OMZWqwUL31llISyHMZZOTrzSsmxG0CAwTKPGccdrKTOJNAENU28YAmCKE6ABgivweAM4H0EH+uwnAy4CkVAA8COBUAH0APBhRLLHkzet645rT85GeKv1idTLS0LlFA8yzsXjNaTnsUzudo1mTlb4dcoMWwZSs2unsAmuAqZIQQvwEYK9q83AAb8mv3wJwkWL720JiJoBsImoO4DwAk4QQe4UQ+wBMQk3F4zudmjXAQ8O7VGWEJQCFeTlYtKXUdlAdwzDmmOVPCwP1M9MMh35ezALIo/MEgdM1iaZCiBL59XYATeXXLQFsVuy3Rd6mt913smqn48a+baK2RWYDKUTomZeNo2UVWLHdXlAdY5201Dh9OhjXJEJ1yEt6tvLkPPF6J1wvXAtpNdizyRoR3URExURUvGvXLtfnW/jgYNw/rHPUtsjUkkiaSQBw7Ap7SosGruRLBsZf2ztoEUJNr/yYW16rGHN+J1/PHwcTidgQx/fBqZLYIZuRIP/fKW/fCqC1Yr9W8ja97TUQQrwqhCgSQhQ1buyPy1gkqC6FCK1yaqNJ/Vq21iWUNOdcTqa0bVzPfCcdOjdPfCVcx0IG0r9e0Nl0nzDi90ziv9f3cX2OWKxHaBU9ixecKokvAEQ8lEYA+Fyx/RrZy+k0AKWyWeo7AIOJKEdesB4sbwuESJsgkgLuCvNyHHs48YKXv/xnRFHQIoSCVjm1gxbBEX4rib5e5VLz8Tm+Y1AH5NbLqBHcCwD3DfV3JucFVlxg3wPwK4CTiGgLEV0PYByAc4loNYBB8nsA+AbAOgBrAPwHwK0AIITYC+AfAObIfw/J2wIh0rFHGnBhfjY27z2KXQftB9U1z+aZhJ80rMPuswBQK82fkCa/BzlWFq4n3HqGv0IEzB2DOoJIey4RD4NMK95NVwohmgsh0oUQrYQQrwsh9gghBgohOgghBkU6fNmraZQQop0QoqsQolhxnjeEEO3lv/F+fimrRNqvm3WJB4bFpxkgXqidkWoaqZroJr8N44YhLcW/uNevbj8Lfx5Ss96KF9TPTDPdJ/L8hRWv3N7jQB9oklQR1xFGD+wAoDq3U5eWWUhPJUtKQq35MzkGwJBh3Zq7PsfZHY2VxO+KWht+zuhDJLX/W/u39+X8owd18OW8dvjujn5454ZTDfdxqgiGnNLM0XER4sH5KymVxJ3ndsSGccOq3memp6JziyzM38jpObzm4eFdArv2PeedhH9e1h0vXVVovnOAaNmq7fDRzac7PtZvc0dmWvCDqJOa1UfPvGzdz63MdrwgDvSBJrG5O3FAr7wcvDNrI8oqKpGempS60zH5jepgo0698CCn2KMGSKPjHQeOBSiF//QuaBi0CACAjNQUnFAFpZrpv1f+0MtHiaqpk1Gzq3vpqkJs238Uw7o1R78nfvRfiDjVEtwbyhTmZ+N4eSWWbTsQtCie0q1Vlm/nXjD2XGwYNwzT7hng6PhPbjkdV/R2bypyq4gu7eU8WKooRjEO8WCWcEL31v61TzNqp6fihr5t0TyrtvGMKl4XEzyClYSM26A6NVZ8363S3aSj/+FPZ+t+9sVtZxkee+0ZBU5EAgBkW/A8MurbeuU3xNCu5msWpiYRlzaTpy7r7vjYK/vkRZmZitxHAAAgAElEQVQu/cLNV1z69/O8E8QmZvEBZp8/cWm30JsL3RAP8ROsJGRaZNdGswaZjsqZavmwD+vaHH+70BvPpwm3nmmYJM/MF91Ijo5N6zuWywpmfVu/jo3x3R39fL1G+B9Df6lby51V+ca+bXD1afkeSRONmYfs74pao52LYExDFNd2M8xoYdG7Lh4UghasJBQU5mc7irx+94bTNLc3aeCNaybB2PtC75OW2ZLyuqJPnuk1zmofXLbOk5rV93Xx0E0HMLBTE8/k0KJDk3r483n+uJ9awcp9z2tUF/+4yNgB4fNRZ2p/YNYvWug3w555+YvbjWfrEcL+PfRgJaGgMC8HW/cfxU6bC515jer4JJGE06blRZrmT10GOqkLPTk6h+szOMertYAGOp3xpLvORpeWwdnlr7QwgLBCi2xnEeFuRtf3qvJOXWZ3bcliw6qVbtxN5tarhdYNzb//Xed2rLGtc4sGnqzL+QkrCQWF+d6tSwjELppSryO2c/0cncJAPUMe6ATER9SqW/xauPYqlbfTUbKVy2v9vrPvH4g/nt0uatuTLtaW9J6hW/q3w99+cwruHNQRTRvU0j1eT9l9rHBPblS35vEpRBj32242pY0trCQUnNKiATJSUzDXwOTkdYfkZ7SwlY4l8nDXq5WKt69znizNT3OR2dcw66DcdINCeFRPIEHdk3Lr6XecgPm9i9wXu+2nSf3q52bmvQMx+76BpseoU5tY+Un+MqQTaqWlYvSgDmhmYD5u17iu5vYihXuyXUV6SWFMqimYwkpCQa20VHRp2cDR4rUaq52LmalhcOempqM9vaZnN9+Pq35MR4is2u7r+vrs3BQTtH7CeE3aF427mx+5L5EsCJpXMLlEs6xM3fW/p39nbXYxwoKXn5EYz1/ZE89cbn8mY/TMDbPg+RcLWEmoKMzLweKtpThR7r5SnZXOy2y6/eo1RabnytbpiP0MCvzkFmtrFWkeyJDX0N2aj5turF5mmm8+KV/f3tenM8ceAmlO2czXrc3vbm49Z0kebzirDS4prF6nMGoHY12mYq+fme4qI22YBwysJFQU5ufgRHkllm4rdXUeq1NLL1IpNzKZ8lvDnhyxLJTTxySi2M+JRFcfF5Wz6rifZTWU15Lc5hACgL//5hR3J3DyQ1hodk0aZGLmvebmpBqntmjqUr92SjzMaJ3ASkJFdVBdbPI4uV04TDM4PkHbrG2s3OEuLf0tbqQeDHym5zKqwihtxeS7+mHyXVIgpRfBm03qOx9s6A2KiAiT7uyHRjqOEZHma9ZJN8vKxKCTmxru4zV23Z/NBoZGSiTMS1asJFQ0y8pEy+zajivV2SXoQvGRIL16tYJPxOYUL0Zwfgc6qTsBq1cb0qWZ7v7tm9SvmkmY8U8Hnj85lmY6xt+k9GgZOjStr5sNOMgF/XomQYbndYmenZmur5m0Q62Pjb59WBQHKwkNeuZlu3eDtdhxpQbcEob3aIm/DOmEu851F9Dltp92eheevbyH70FK40fqe32Z/XxP/647Tmvb0LsKag45o30j033Ud9H2XdW4F2ZxMlUzCSunD7jTfPbyHoafJ+rMnZWEBoV5OSgpPYaS0qOWj/n+zujUElYbTIrFmYTe+dw2zNQUwi3926G2gbnCyKRllcYuTBlm5DfUdj+MUMtCumo9RdMyuzbOaKffwRo6FNRJxyWFrfD+TafXuL+x7vCszJTU3+XUNu6zy5rNFJzM4BxnjnX5sNhd+ztTpZgzbDpx9GgdjhglVhIaVAXVadSX0Gtn6hxIBKBfx1z0aK2fxx6Ij6pqMy34oAfJlX1aGxaVyaqTjvdu1E6dYkTXllkY0qWZ41nOwE76NvR4WOQ0i4GogcZ3MvVuouj/XuLWlGX3aPVvekqLaKeHjLQULHtIO9miVnuwakr0G1YSGnRu3gC10lJcmZwEJLe4z0adWZVDScnCsYPx4939MWpAe2upEXQ6FUObpiVJ9bmkpxTMY8WV1sys4EUfoJfagohwpknuKaOiM3qc0a6RVJvYoLMx6oeUsxO33z/dJObFTOdYCVZzbbbT+JJ15ToOes3DySw1aLOTHpUWNL9WXYuww0pCg4y0FHRtmeVZ2nCtDjQlBWiTWxeZ6al47JKujr1TIv7V/3eO9+UnnzaxwSoxG7WFvZCT04XrWM0I3NatqFsrzdRt2Y/vYmTGnPKns6viaOzc/bDOwkIqlmvC/eQGSK/8HCzZWopjZRUxuZ7WQ9JWJ9RfyQd/lHLD3DXYfSZRvYfPi5GbWZK0oB8wo1F0GAau5rZ9c8y8edS0loMY3bjGGqGUJ8PCulGsf4dYel6FdXYEsJLQpWdeDsoqhOugOsB5B1jXwtS0qUE+mVh2vF5ke41HDB9uxS0Z7EGwmxFe3H31OW7s2xbjr+2NwZ2dxycYrTk0yKx2Kb2sqBVu93g2POAk4ziHTJOBi12cPAPxkNOLlYQOhfmSDVtr8doKpjZ6VeMIcxfrSf/vwTnsnCLfw/TtRs+x1TiXszsG6wJrBXWbTU0hDOjUxFpHZrJmptWGlKao9NQU/MmD2bCS01VeaZHZ4pz7B+GJS7vVWFh2i5PnpGPTeo6PjRWsJHRoUj8TrXJqe7IucdWpznL2K59NN4uKeq53/U8Kf8flFLt1t43WJPQ6yaFdm1UlYbuwewtb14sVSiWmF/XshqhbE+KOTklW7XT8rsi8hoNb7yYrWCkBHDSsJAwozMvBvE37dGcFVssWjhrQHusfGxq1zUoD9Gp0oReL0TbXWllIFwNJy59bksODc+hhVQkr7ej3nNepauH1+St64AlVXYBY9plaHnQAsOaR86teP2RSXe48ByYxszbqjznF/M62zTVfz/MadRtKFBMsKwkDeuXnYMeB49hWql2pbqDFXDJmbpR+EX5rZzV+y+rk9ttJo0CknQU1Vowe1EEzyEzZ7swWrjMN6qibQsA1p+vXwfamJof1fZsYFAjyi+ZZ4c3k6gZWEgZEkv0pixBZHR3YHUNcrfGAxcGaVhUelDJOKtS/7SRVxL5d0lNTqvI8BYIA7h92co3N6jUJtym5Y4nd5y+jRlEj7RPcPbhmGdMww0rCgE7N6yMzPUU32Z+XnXhOCGyTeorNi6+ZGBNveKbt1CnIO6gi9sPI5LvOxt8ujO7klc+AVqeo3pSWGpvhgtZYzq71x+uF7Qi3naNfYCmMsJIwID01Bd1aZWO+zuK1UaPzInhMeX7la7sV51zLEdOr+YveIr7WwrVy1jj7fvPUJFa7v+IHBml2qI//tqvFMwRD+yb1LJtYw4yVwd2KfwzBSc3cKW5ek0gSCvNysHTbAdtBdVZz1kSw055+Y9GTJpZNNOz+3hmpKRjWrTneHNlb83OzhWst5aL+xjXcmnV+VL2cSJf3duYFF0ta26wSGKZ2YScXkqv1mQQj/hKJxJjCvGyUVwos3lqK3iYV0pSYddDqTkerk4p2ga25PeBSFFGYjZqCHlUREf71+0Jbx2iJ7GeuLMYaTpvSJ7ecgRlrd4c+RUzYYCVhQnVG2H32lIRBQ94wbphbsSzhVafFnV81YRoZ+8G3o/tiy76jltcOxl7QGfd9ujgm/v5uC0O1blgHlzcM/2wtbLCSMCG3Xi3kN6oT5eEUIZb9RVTMUmKYOgPntgHtMUhOOWHWAVm55zVMiE4Fk+ldEPt6Aic3b4CTm1sv5Xph9xahDSQMgtx6tbD70PGgxfAUnndZQAqq2++rycSsroQfVx490JqXhZVrm9lwL+jmT0fippjRkC7Nqup9aJn7hMbrRJpIDO0aO5fZSOGmLi2NPYZeusqeSTBsFD8wCPcN7RS0GJ7CSsIChXnZ2H3oOLbsO+rbYnCmhSyYEbySIctSDWOL5zKp/3vXuf74hpvVkfAapY4ISmG8e8OpeH1EkevzjL3gFA+kscb5XZtj4YODq2KP9BjaVbsWdqJjVP0waFhJWKCn3LDt5HHyuu5yLBZ+9YqmeNEXqlODqNOgD+/R0vY5rSbXU2PVnGJ2y80+f2CYP4FjZ7TPjUtXVLOBhFWsPAnxZpF9+KLwuj+7UhJENJqIlhDRUiK6Q97Wg4hmEtECIiomoj7ydiKi54loDREtIqK4mVd2alYfdTJSdYPqvMBOo/ZrADtz3R6fzlyTfh2ikwv+7TenYOSZBZr7RrKFjjyzjaVzm6WAdnL/nChpt3W9k9UNc4BO4slEMvWpyUhL0c2/FTSOlQQRdQFwI4A+ALoDuICI2gN4AsDfhRA9AIyV3wPA+QA6yH83AXjZhdwxJS01Bd1bZWPepui04UG1WavdVZHNhc+ychfjL5c3IzWFouoLKMlIS8GGccNwp0WT1a9jvK/JXb0m4ayUKQC8fV0fW+k3ureyX3LVjHjI/Dt+ZB/Dz9lxI7a4mUmcDGCWEOKIEKIcwDQAl0B6niLz+SwA2+TXwwG8LSRmAsgmorgxQBbmZ2NZyQEcPRGbSnVqXrTp41/8wCAM6WLv9jb1OCnabwtbeXo+NXp9co4HKbGJgMt710wnTaiuVWG3r+rXsbGt9Bt+jJxfvdr9WkYyY6dNJ4oyc6MklgDoS0SNiKgOgKEAWgO4A8CTRLQZwFMA7pX3bwlgs+L4LfK2uKAwLwcVlQKLtlisVGezgZj1B0O7Nse4SyS7pV7jU3qG6EX1GtGhqbXU4X5h95ny8xlc/9iwqLQMynuumwnW47mlk07msUuMbdvqJHTxSJBmp6cu62a7DGy847jFCCGWA3gcwPcAJgJYAKACwC0A7hRCtAZwJ4DX7ZyXiG6S1zKKd+3a5VQ8z3GyeO01Zg+HW8+QXvnWgwXVRES7uGdL3Nq/nbQtAW3IRNUKOC1MIe8ydlJPhB09hRbkCJ3I+lAgUdq/K5UohHgdshIgokchzQ4eAzBa3uUjAK/Jr7dCmmlEaCVvU5/zVQCvAkBRUVFoJmwN62agTW5dLNgsrUs0z8rEqAHe1uQNmqza6bi1fzu8NHWt43OMGtCuxtqNFloBWA0yo5tjEAt5L1zZ03Sfl//QC1OW76iRx8jrTiFROhknvPj7nuiiysJq536E4daxuQkAETWR/+dBWo94F9IaxNnyLucAWC2//gLANbKX02kASoUQJW6uH2t65lUvJL42oghNGlirTBfhwu4tcP1Z2h46VtpTN3kh85xOxgXevcZpKgq9h+St6/qgV37NRXX1yFHtJltDLkdSGVPQqK6mAlO6NDeuXwtX9PE/vYP6/j1ycRd8dPPplo6plZaCZy7v7pNk/nNBtxYocFFdzkn//NmoM23tn5pCuEWeNStxanYM6yzQrXHtEyJqBKAMwCghxH4iuhHAc0SUBuAYJE8mAPgG0rrFGgBHAIx0ee2Y0ys/BxPm1Zj8aKLVSK2MUo04uXkDrHx4CNJSpM40rInK3HbeeQ3rYNPeI57I4hlVP2hwY9SrTtWv/KamX8fGuLinv44DiUYk+t4q8/56rmbsh5UYqVev7oWWOdEz5ddHFKHPo1NsyRAL3Jqb+mps+xlAjTqKQnI0H+XmekGjjBb1epFSC60r1JIjs+8e3LEq71DYMHtE9Bd+Jbq3zsaeQ8dxm4k5L+JlFEvCbgIKu3zJhNFvMVijnniTBpm4c1BHPDN5lY9S2Se5luld0jFE1cOcVreaeEdfDHl2uq1j0hUZQcec36lGIJySKC8ghx1WVu00LH1oiOE+Detm4L2bTova9vHNp2P7Ae165G6JF/NyotjBjfA6m4FTzNq3k9/i/wa2ZyURzzhNA+EUPx6FTs2sZ/iMUCstFb+MOQe59TKqZjJqvEihbef7DuzUBE3qR68JFdlI5e6UWLaAsHSGYcHK7P0vQzrh8YkrYiCNvhJwY2UgIrTIysQtIXKKYSVhk45N62HVjkM4cqLccL+gi+yoKczLxo4DzlMYe+lpZKZPrDxksTarWEsVHl+2njgT1xJK5xLf8Pm+zbjX+4wBbmAlYZMOTetj1Y5D2Lr/KLyMXbVbBc0uE2615rnhVrWFSzV6T2xriLgYkXooB6PCpJH3kBXVqW3Dm9nVDuF0jwkxqYk4/PIA5V0paCS5LnZpYc+01TZXivjubHBcJOrcTQcayQKrzBXVKltaBK+doRPAFYD6c3NNoyObuEw8GBcEOFrpXdAQCx8cjHND6lhiF55JhIRE0j192jTE93f2Q4cm0Wk+Rpyej7d+3Yjs2tr+4Gd1yNU8zmseubgLLu/dGnkK76gnL+uG4T1aoH0TbeeEyEwvFl5tjDFGpj+3v86Xt52FsspK450sXMSrtOhhgGcSNrE6QEl0s4ua358qBZc1lReTOzatX8NGf9+wk/Hf6/ugayv96mRax3lNZnoq+rSJXuSun5mO8y2kNYkXZR4nYtojBl+qa6ss08JIB49J65EVlcnxlLOSYDxh5JltsGHcMMNqd7XSUtHXwH02zESiYY0q7Hndh4XM94GRuU6ua1I/MzkMMcnxLQOgs41i8l4TxsRzXhFUv5mZnooN44YZ7pNsffpFPfypW67HKS0a4OtFJWgRcHGesRd2xtgL/ak6GEZYSfjEjX3b2trfq1Hj9D8PQJ2MxK9oFnazz/hrewctgi5eKbNnr3CWZubXe89xFHN0c7926NehMbq01DdXMt7DSsIn1DWdrVK/VhoOHjeOwTBCnZnULmzicM8F3ZpjQIyTMEY4ubm08G4lbXxQerZ5lrOZQEoKmSoIbr7ew2sSIaNvx1zb2SiTCVZixuQ3qos1j5yPi3oGX88rga2eSQUrCZvEot0HGa0ddjNOhHiRMwjSQpodOBZws/Ce5G1N8QD3hDVIpnxGyfNNmTDDSiLMBDCjiB9zTmIq0Kl398fAgNYzvKRldm08cWn8Fj1iquGF65AQqY1QmJcTd4niGO8oyK2LwvwcTFmxM2hRXPHLmHOCFoHxCFYSHlIrLQXHy01C+nXo0jIL0+7pj7yGdarqaDM1ObNdLgDg4hAszMYrfs8W27ooO8qED1YSHrL4b+eh4wPfOj4+v5Hq4QpgRhF2m39Bbl3ToLZ45/LerfH9sh0YcXqBvxfyoXl9dftZnqaVZ4KHlYSHZKTxEk8y45VXWm69Wvg8Tt2gwxLoFvbBTjzBvZpDYrLAG8AqMmc5dQ+vKQUH33vv4ZmETcza4MtXFWLfkbLYCMMwDOMzrCQ8xkq6acvwmgTDMAHD5iaGYRhGF1YSIaRRXam8ZM/WMSjqziQhPFtkrMPmphCS16gOvh3dF+19LuPJJDfspMBYgWcSIeXk5g2QHkCitrPjtHIcwzD+wDMJJooz2ucGLQLDOKZH62wM7doMd517UtCiJAysJGzSIFOq4ZyZzpMwJppIWc2TmrKZMCgy0lLw0lW9ghYjoWAlYZN7h3ZCfqM6GNy5WdCiMCGjd0FDfHLLGejBDgdMAsFKwiZ1MtJwg8361Uzy0Cs/J2gRGMZT2GbCMElG/5OkehW1M1IDloSJB3gmwTBJxqMXd8UdgzqgXi1nj39Bozq4xu8MtUxoYCXBMElGRloKWuXUcXz81HsGeCgNE3bY3MQwDMPowjOJJGTcJV0xe/3eoMVgGCYOYCWRhFzRJw9X9MkLWgyGYeIAV+YmIhpNREuIaCkR3aHYfjsRrZC3P6HYfi8RrSGilUR0nptrMwzDMP7jeCZBRF0A3AigD4ATACYS0VcAWgMYDqC7EOI4ETWR9+8M4AoApwBoAWAyEXUUQlS4/A4MwzCMT7iZSZwMYJYQ4ogQohzANACXALgFwDghxHEAEELslPcfDuB9IcRxIcR6AGsgKRiGYRgmpLhREksA9CWiRkRUB8BQSLOIjvL2WUQ0jYh6y/u3BLBZcfwWeVsURHQTERUTUfGuXbtciMcwDMO4xbG5SQixnIgeB/A9gMMAFgCokM/ZEMBpAHoD+JCILOexEEK8CuBVACgqKuLqKAHw+agzsXhradBiMAwTAlwtXAshXhdC9BJC9AOwD8AqSDOECUJiNoBKALkAtkKaaURoJW9jQkb31tn4w2n5QYvBMEwIcOvdFFmUzoO0HvEugM8ADJC3dwSQAWA3gC8AXEFEtYioDYAOAGa7uT7DMAzjL27jJD4hokYAygCMEkLsJ6I3ALxBREsgeT2NEEIIAEuJ6EMAywCUy/uzZxPDMEyIcaUkhBB9NbadAPAHnf0fAfCIm2syDMMwsYNzNzEMwzC6sJJgGIZhdGElwTAMw+jCSoJhGIbRhZUEwzAMowtJ3qnhhIgOAlip8VEWAKOQ4DwAmww+Nzve789ZPpaP5dPHTL5YyBDv97CbECLD4HPrCCFC+wegWGf7qybH7TL53Ox4vz9n+Vg+ls+hfPEgYwjkKzO7h1b/4tXc9KXJ5/tdHu/35yyfu89ZPnefx7t8sZAh3u+hZ4HKYTc3FQshimJ1XKxg+dzB8rmD5XNP2GUkosNCiLpenCvsM4lXY3xcrGD53MHyuYPlc0/YZZzg1YlCPZNgGIZhgiXsMwmGYRgmQOJCSRDRG0S0U84sG9nWnYh+JaLFRPQlETWQt6cT0Vvy9uVEdK/imCFEtJKI1hDRmBDKt0HevoCIigOSL4OIxsvbFxJRf8UxveTta4joeSKikMk3Vf59F8h/TTySrzUR/UhEy4hoKRGNlrc3JKJJRLRa/p8jbyf5/qwhokVEVKg41wh5/9VENCKE8lUo7t8XXsjnUMZO8u9/nIjuVp3L8+fYY/k8f44dyHeV/NsuJqIZRNRdcS57988rNyk//wD0A1AIYIli2xwAZ8uvrwPwD/n17yHV0gaAOgA2ACgAkApgLYC2kGpcLATQOSzyye83AMgN+P6NAjBeft0EwFwAKfL72ZAqDhKAbwGcHzL5pgIo8uH+NQdQKL+uD6m4VmcATwAYI28fA+Bx+fVQ+f6QfL9mydsbAlgn/8+RX+eERT75s0Ne3z+HMjaBVNnyEQB3K87jy3PslXzyZxvg8XPsQL4zIm0LwPmKNmj7/sXFTEII8ROAvarNHQH8JL+eBOC3kd0B1CWiNAC1IdW0OACgD4A1Qoh1Qkpn/j6A4SGSzzdsytcZwA/ycTshufoVEVFzAA2EEDOF1NreBnBRWOTzQg4D+UqEEPPk1wcBLIdUn304gLfk3d5C9f0YDuBtITETQLZ8/84DMEkIsVcIsU/+XkNCJJ9v2JVRCLFTCDEHUq0aJb48xx7K5wsO5JshtzEAmAmpEijg4P7FhZLQYSmqv9xlqC6N+jGkmtslkCIinxJC7IV0Qzcrjt8ibwuLfICkQL4norlEdJOPshnJtxDAb4gojaQKgr3kz1pCumcRgrp/evJFGC9P8/9K5I05TAkRFQDoCWAWgKZCiBL5o+0Amsqv9dqa723QpXwAkElExUQ0k4g8GQQ4lFGPsNxDI3x9jh3Idz2kmSPg4P7Fs5K4DsCtRDQX0vTrhLy9D6RAkhYA2gD4ExG1jRP5zhJCFEKaHo4ion4ByPcGpIZTDOBZADPgYWCOz/JdJYToCqCv/He1lwIRUT0AnwC4QwgRNfuTZ1eBugp6JF++kPz/fw/gWSJqF0IZfcMj+Xx7ju3KR0QDICmJvzi9ZtwqCSHECiHEYCFELwDvQbKzAVLjniiEKJPNEb9AMkdsRfSIs5W8LSzyQQixVf6/E8CnkBRKTOUTQpQLIe4UQvQQQgwHkA3J/rkV1VNWIKD7ZyCf8v4dhFRv3bP7R0TpkB7Od4QQER/0HREzjfx/p7xdr6351gY9kk95D9dBWuPp6YV8DmTUIyz3UBe/nmO78hFRNwCvARguhNgjb7Z9/+JWSZDsuUJEKQAeAPCK/NEmAOfIn9WFtDC3AtJCaAciakNEGQCuAOCZ94Zb+YioLhHVV2wfDGCJ+rx+y0dEdeTrg4jOBVAuhFgmT2kPENFpshnnGgCfh0U+2fyUK29PB3ABPLp/8vd9HcByIcTTio++ABDxUBqB6vvxBYBrSOI0AKXy/fsOwGAiypG9UAbL20IhnyxXLfmcuQDOhFST3jUOZNTDl+fYK/n8eo7tykdEeZAC6q4WQqxS7G///qlXssP4B2kkWQJpkWgLpOnTaEgjyFUAxqE6MLAegI8g2bSXAbhHcZ6h8v5rAdwfJvkgeRsslP+WBihfAaTMu8sBTIZkfoicpwhSg18L4MXIMWGQD0BdSJ5Oi+T79xyAVI/kOwvSNH4RgAXy31AAjQBMAbBalqWhvD8B+Jd8nxZD4XEFyYy2Rv4bGSb5IHnELJbb4GIA13vYBu3K2ExuCwcgOSdsgeQ4AfjwHHslH3x6jh3I9xqAfYp9ixXnsnX/OOKaYRiG0SVuzU0MwzCM/7CSYBiGYXRhJcEwDMPowkqCYRiG0YWVBMMwDKMLKwkmoaHqrKZLScoa+yc59sLomAIi+r3JPl2pOlvqXiJaL7+eTEQtiOhjb78JwwQDu8AyCQ0RHRJC1JNfN4EUif2LEOJBg2P6Q8rseYHFa7wJ4CshBCsGJuHgmQSTNAgpTcJNAG6To40LiGg6Ec2T/86Qdx0HoK88M7iTiFKJ6EkimkNSjv4/Gl1HPu8S+fW1RPQZSbn+NxDRbUR0FxHNJymJXkN5v3ZENJGkpHDTiaiTn/eCYazCSoJJKoSUkygVUj2AnQDOFVIytssBPC/vNgbAdCHlh3oGUgR4qRCiN6QaAjeSlIHWKl0AXILq+gNHhBA9AfwKKb0JINVMvl1IuaruBvCSi6/JMJ6RFrQADBMg6QBeJKIekDLJdtTZbzCAbkR0qfw+C0AHAOstXudHISUdPEhEpQC+lLcvls9bD1JKjI+oOrt5LVvfhGF8gpUEk1SQlJa9AtIs4kEAOwB0hzSrPqZ3GKRRvtNkfMcVrysV7yshPYMpAPYLIXo4PD/D+Aabm5ikgYgaQ8om+6KQPDayAJQIISoh1Z5IlXc9CKmGRYTvANwiZ5cFEXWMZKL1AiHVBVhPRJfJ5ydS1CRmmCBhJcEkOrUjLrCQslHa3CkAAAB8SURBVGR+D+Dv8mcvARhBRAsBdIJUMRCQMm1WyC6zd0LKqLkMwDx5Qfrf8H4WfhWA62VZlFX5GCZQ2AWWYRiG0YVnEgzDMIwurCQYhmEYXVhJMAzDMLqwkmAYhmF0YSXBMAzD6MJKgmEYhtGFlQTDMAyjCysJhmEYRpf/B4lza1fEWs2QAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb4604e6cf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Roskilde']['Pressure'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before removing these two signals, there are 20 input-signals in the data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(333109, 20)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.values.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we remove the two signals that have missing data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.drop(('Esbjerg', 'Pressure'), axis=1, inplace=True)\n",
+    "df.drop(('Roskilde', 'Pressure'), axis=1, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now there are only 18 input-signals in the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(333109, 18)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.values.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can verify that these two data-columns have indeed been removed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Aalborg</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Aarhus</th>\n",
+       "      <th colspan=\"3\" halign=\"left\">Esbjerg</th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Odense</th>\n",
+       "      <th colspan=\"3\" halign=\"left\">Roskilde</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>WindDir</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DateTime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 11:00:00</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1007.766667</td>\n",
+       "      <td>10.2</td>\n",
+       "      <td>280.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1008.3</td>\n",
+       "      <td>15.4</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>6.083333</td>\n",
+       "      <td>12.383333</td>\n",
+       "      <td>310.0</td>\n",
+       "      <td>6.142857</td>\n",
+       "      <td>1011.066667</td>\n",
+       "      <td>12.585714</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>11.466667</td>\n",
+       "      <td>280.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    Aalborg                                Aarhus           \\\n",
+       "                       Temp     Pressure WindSpeed WindDir   Temp Pressure   \n",
+       "DateTime                                                                     \n",
+       "1980-03-01 11:00:00     5.0  1007.766667      10.2   280.0    5.0   1008.3   \n",
+       "\n",
+       "                                        Esbjerg                       Odense  \\\n",
+       "                    WindSpeed WindDir      Temp  WindSpeed WindDir      Temp   \n",
+       "DateTime                                                                       \n",
+       "1980-03-01 11:00:00      15.4   290.0  6.083333  12.383333   310.0  6.142857   \n",
+       "\n",
+       "                                                    Roskilde             \\\n",
+       "                        Pressure  WindSpeed WindDir     Temp  WindSpeed   \n",
+       "DateTime                                                                  \n",
+       "1980-03-01 11:00:00  1011.066667  12.585714   290.0      5.0  11.466667   \n",
+       "\n",
+       "                             \n",
+       "                    WindDir  \n",
+       "DateTime                     \n",
+       "1980-03-01 11:00:00   280.0  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head(1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Data Errors\n",
+    "\n",
+    "There are some errors in this data. As shown in the plot below, the temperature in the city of Odense suddenly jumped to almost 50 degrees C. But the highest temperature ever measured in Denmark was only 36.4 degrees Celcius and the lowest was -31.2 C. So this is clearly a data error. However, we will not correct any data-errors in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45af285c0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb460548a58>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Odense']['Temp']['2006-05':'2006-07'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This can also be confirmed to be an error by considering the temperatures in some of the other cities in Denmark for that period, which was only around 10 degrees. Because the country is so small, it is not possible for one city in Denmark to have 50 degrees while another city only has 10 degrees."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45d098080>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb45af37fd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Aarhus']['Temp']['2006-05':'2006-07'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45cf808d0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb4605762e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Roskilde']['Temp']['2006-05':'2006-07'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Add Data\n",
+    "\n",
+    "We can add some input-signals to the data that may help our model in making predictions.\n",
+    "\n",
+    "For example, given just a temperature of 10 degrees Celcius the model wouldn't know whether that temperature was measured during the day or the night, or during summer or winter. The model would have to infer this from the surrounding data-points which might not be very accurate for determining whether it's an abnormally warm winter, or an abnormally cold summer, or whether it's day or night. So having this information could make a big difference in how accurately the model can predict the next output.\n",
+    "\n",
+    "Although the data-set does contain the date and time information for each observation, it is only used in the index so as to order the data. We will therefore add separate input-signals to the data-set for the day-of-year (between 1 and 366) and the hour-of-day (between 0 and 23)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df['Various', 'Day'] = df.index.dayofyear\n",
+    "df['Various', 'Hour'] = df.index.hour"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Target Data for Prediction\n",
+    "\n",
+    "We will try and predict the future weather-data for this city."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_city = 'Odense'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will try and predict these signals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "target_names = ['Temp', 'WindSpeed', 'Pressure']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following is the number of time-steps that we will shift the target-data. Our data-set is resampled to have an observation for each hour, so there are 24 observations for 24 hours.\n",
+    "\n",
+    "If we want to predict the weather 24 hours into the future, we shift the data 24 time-steps. If we want to predict the weather 7 days into the future, we shift the data 7 * 24 time-steps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "shift_days = 1\n",
+    "shift_steps = shift_days * 24  # Number of hours."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a new data-frame with the time-shifted data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_targets = df[target_city][target_names].shift(shift_steps)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The time-shifted data-frame has the same length as the original data-frame, but the first observations are `NaN` (not a number) because the data is not available, as it would have to be taken from before the beginning of the original data-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>Pressure</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DateTime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 11:00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 12:00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 13:00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 14:00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 15:00:00</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     Temp  WindSpeed  Pressure\n",
+       "DateTime                                      \n",
+       "1980-03-01 11:00:00   NaN        NaN       NaN\n",
+       "1980-03-01 12:00:00   NaN        NaN       NaN\n",
+       "1980-03-01 13:00:00   NaN        NaN       NaN\n",
+       "1980-03-01 14:00:00   NaN        NaN       NaN\n",
+       "1980-03-01 15:00:00   NaN        NaN       NaN"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_targets.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>Pressure</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DateTime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2018-03-01 19:00:00</th>\n",
+       "      <td>-6.3</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>1032.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2018-03-01 20:00:00</th>\n",
+       "      <td>-6.6</td>\n",
+       "      <td>10.8</td>\n",
+       "      <td>1032.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2018-03-01 21:00:00</th>\n",
+       "      <td>-6.9</td>\n",
+       "      <td>9.8</td>\n",
+       "      <td>1032.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2018-03-01 22:00:00</th>\n",
+       "      <td>-7.0</td>\n",
+       "      <td>9.3</td>\n",
+       "      <td>1032.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2018-03-01 23:00:00</th>\n",
+       "      <td>-7.0</td>\n",
+       "      <td>10.3</td>\n",
+       "      <td>1031.9</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     Temp  WindSpeed  Pressure\n",
+       "DateTime                                      \n",
+       "2018-03-01 19:00:00  -6.3        9.3    1032.8\n",
+       "2018-03-01 20:00:00  -6.6       10.8    1032.6\n",
+       "2018-03-01 21:00:00  -6.9        9.8    1032.4\n",
+       "2018-03-01 22:00:00  -7.0        9.3    1032.3\n",
+       "2018-03-01 23:00:00  -7.0       10.3    1031.9"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_targets.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### NumPy Arrays\n",
+    "\n",
+    "We now convert the Pandas data-frames to NumPy arrays that can be input to the neural network. We also remove the first part of the numpy arrays, because the target-data has `NaN` for the shifted period, and we only want to have valid data and we need the same array-shapes for the input- and output-data.\n",
+    "\n",
+    "These are the input-signals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_data = df.values[shift_steps:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'numpy.ndarray'>\n",
+      "Shape: (333085, 20)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(type(x_data))\n",
+    "print(\"Shape:\", x_data.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the output-signals (or target-signals):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_data = df_targets.values[shift_steps:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'numpy.ndarray'>\n",
+      "Shape: (333085, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(type(y_data))\n",
+    "print(\"Shape:\", y_data.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the number of observations (aka. data-points or samples) in the data-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "333085"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_data= len(x_data)\n",
+    "num_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the fraction of the data-set that will be used for the training-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_split = 0.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the number of observations in the training-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "299776"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_train = int(train_split * num_data)\n",
+    "num_train"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the number of observations in the test-set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "33309"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_test = num_data - num_train\n",
+    "num_test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the input-signals for the training- and test-sets:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "333085"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x_train = x_data[0:num_train]\n",
+    "x_test = x_data[num_train:]\n",
+    "len(x_train) + len(x_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are the output-signals for the training- and test-sets:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "333085"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_train = y_data[0:num_train]\n",
+    "y_test = y_data[num_train:]\n",
+    "len(y_train) + len(y_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the number of input-signals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "20"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_x_signals = x_data.shape[1]\n",
+    "num_x_signals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the number of output-signals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_y_signals = y_data.shape[1]\n",
+    "num_y_signals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Scaled Data\n",
+    "\n",
+    "The data-set contains a wide range of values:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min: -27.0\n",
+      "Max: 1050.8\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Min:\", np.min(x_train))\n",
+    "print(\"Max:\", np.max(x_train))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The neural network works best on values roughly between -1 and 1, so we need to scale the data before it is being input to the neural network. We can use `scikit-learn` for this.\n",
+    "\n",
+    "We first create a scaler-object for the input-signals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_scaler = MinMaxScaler()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We then detect the range of values from the training-data and scale the training-data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train_scaled = x_scaler.fit_transform(x_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Apart from a small rounding-error, the data has been scaled to be between 0 and 1."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Min: 0.0\n",
+      "Max: 1.0000000000000002\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Min:\", np.min(x_train_scaled))\n",
+    "print(\"Max:\", np.max(x_train_scaled))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We use the same scaler-object for the input-signals in the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_test_scaled = x_scaler.transform(x_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The target-data comes from the same data-set as the input-signals, because it is the weather-data for one of the cities that is merely time-shifted. But the target-data could be from a different source with different value-ranges, so we create a separate scaler-object for the target-data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_scaler = MinMaxScaler()\n",
+    "y_train_scaled = y_scaler.fit_transform(y_train)\n",
+    "y_test_scaled = y_scaler.transform(y_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Generator\n",
+    "\n",
+    "The data-set has now been prepared as 2-dimensional numpy arrays. The training-data has almost 300k observations, consisting of 20 input-signals and 3 output-signals.\n",
+    "\n",
+    "These are the array-shapes of the input and output data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(299776, 20)\n",
+      "(299776, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(x_train_scaled.shape)\n",
+    "print(y_train_scaled.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "But the Recurrent Neural Network cannot be trained on sequences with 300k observations. It is only trained on small sequences of e.g. 100 observations. Furthermore, in order to improve the training-efficiency when using a GPU, we will use batches of training-data.\n",
+    "\n",
+    "For example, we may want a random batch of 1024 sequences, with each sequence having 100 observations, and each observation having 20 input-signals and 3 output-signals.\n",
+    "\n",
+    "This function generates such random batches of data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def batch_generator(batch_size, sequence_length):\n",
+    "    \"\"\"\n",
+    "    Generator function for creating random batches of training-data.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Infinite loop.\n",
+    "    while True:\n",
+    "        # Allocate a new array for the batch of input-signals.\n",
+    "        x_shape = (batch_size, sequence_length, num_x_signals)\n",
+    "        x_batch = np.zeros(shape=x_shape)\n",
+    "\n",
+    "        # Allocate a new array for the batch of output-signals.\n",
+    "        y_shape = (batch_size, sequence_length, num_y_signals)\n",
+    "        y_batch = np.zeros(shape=y_shape)\n",
+    "\n",
+    "        # Fill the batch with random sequences of data.\n",
+    "        for i in range(batch_size):\n",
+    "            # Get a random start-index.\n",
+    "            # This points somewhere into the training-data.\n",
+    "            idx = np.random.randint(num_train-sequence_length)\n",
+    "            \n",
+    "            # Copy the sequences of data starting at this index.\n",
+    "            x_batch[i] = x_train_scaled[idx:idx+sequence_length]\n",
+    "            y_batch[i] = y_train_scaled[idx:idx+sequence_length]\n",
+    "        \n",
+    "        yield (x_batch, y_batch)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use a large batch-size so as to keep the GPU near 100% work-load."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "batch_size = 1024"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use a sequence-length of 100, which means that each random sequence contains observations for 4 days and 4 hours (100 time-steps = 4 * 24 + 4 hours)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sequence_length = 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We then create the batch-generator."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generator = batch_generator(batch_size=batch_size,\n",
+    "                            sequence_length=sequence_length)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can then test the batch-generator to see if it works."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_batch, y_batch = next(generator)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This gives us a random batch of 1024 sequences, each sequence having 100 observations, and each observation having 20 input-signals and 3 output-signals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1024, 100, 20)\n",
+      "(1024, 100, 3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(x_batch.shape)\n",
+    "print(y_batch.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can plot one of the 20 input-signals as an example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fb45ce08d68>]"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb45ce8b5c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "batch = 0   # First sequence in the batch.\n",
+    "signal = 0  # First signal out of the 20 input-signals.\n",
+    "seq = x_batch[batch, :, signal]\n",
+    "plt.plot(seq)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also plot one of the output-signals that we want the model to learn how to predict given all those 20 input signals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fb45cd21630>]"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb45cfd4be0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "seq = y_batch[batch, :, signal]\n",
+    "plt.plot(seq)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Validation Set\n",
+    "\n",
+    "The neural network trains quickly so we can easily run many training epochs. But then there is a risk of overfitting the model to the training-set so it does not generalize well to unseen data. We will therefore monitor the model's performance on the test-set after each epoch and only save the model's weights if the performance is improved on the test-set.\n",
+    "\n",
+    "The batch-generator randomly selects a batch of short sequences from the training-data and uses that during training. But for the validation-data we will instead run through the entire sequence from the test-set and measure the prediction accuracy on that entire sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "validation_data = (np.expand_dims(x_test_scaled, axis=0),\n",
+    "                   np.expand_dims(y_test_scaled, axis=0))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create the Recurrent Neural Network\n",
+    "\n",
+    "We are now ready to create the Recurrent Neural Network (RNN). We will use the Keras API for this because of its simplicity. See Tutorial #03-C for a tutorial on Keras and Tutorial #20 for more information on Recurrent Neural Networks."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = Sequential()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now add a Gated Recurrent Unit (GRU) to the network. This will have 256 outputs for each time-step in the sequence.\n",
+    "\n",
+    "Note that because this is the first layer in the model, Keras needs to know the shape of its input, which is a batch of sequences of arbitrary length (indicated by `None`), where each observation has a number of input-signals (`num_x_signals`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.add(GRU(units=256,\n",
+    "              return_sequences=True,\n",
+    "              input_shape=(None, num_x_signals,)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The GRU outputs a batch of sequences of 256 values. We want to predict 3 output-signals, so we add a fully-connected (or dense) layer which maps 256 values down to only 3 values.\n",
+    "\n",
+    "The output-signals in the data-set have been limited to be between 0 and 1 using a scaler-object. So we also limit the output of the neural network using the Sigmoid activation function, which squashes the output to be between 0 and 1."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.add(Dense(num_y_signals, activation='sigmoid'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A problem with using the Sigmoid activation function, is that we can now only output values in the same range as the training-data.\n",
+    "\n",
+    "For example, if the training-data only has temperatures between -20 and +30 degrees, then the scaler-object will map -20 to 0 and +30 to 1. So if we limit the output of the neural network to be between 0 and 1 using the Sigmoid function, this can only be mapped back to temperature values between -20 and +30.\n",
+    "\n",
+    "We can use a linear activation function on the output instead. This allows for the output to take on arbitrary values. It might work with the standard initialization for a simple network architecture, but for more complicated network architectures e.g. with more layers, it might be necessary to initialize the weights with smaller values to avoid `NaN` values during training. You may need to experiment with this to get it working."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if False:\n",
+    "    from tensorflow.python.keras.initializers import RandomUniform\n",
+    "    init = RandomUniform(minval=-0.05, maxval=0.05)\n",
+    "    model.add(Dense(num_y_signals,\n",
+    "                    activation='linear',\n",
+    "                    kernel_initializer=init))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the optimizer and learning-rate we will use."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer = RMSprop(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use Mean Squared Error (MSE) as the loss-function that will be minimized. This measures how closely the model's output matches the true output signals.\n",
+    "\n",
+    "We then compile the Keras model so it is ready for training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "keep_dims is deprecated, use keepdims instead\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.compile(loss='mean_squared_error',\n",
+    "              optimizer=optimizer,\n",
+    "              metrics=['mae'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a very small model with only two layers. The output shape of `(None, None, 3)` means that the model will output a batch with an arbitrary number of sequences, each of which has an arbitrary number of observations, and each observation has 3 signals. This corresponds to the 3 target signals we want to predict."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "gru_1 (GRU)                  (None, None, 256)         212736    \n",
+      "_________________________________________________________________\n",
+      "dense_1 (Dense)              (None, None, 3)           771       \n",
+      "=================================================================\n",
+      "Total params: 213,507\n",
+      "Trainable params: 213,507\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Callback Functions\n",
+    "\n",
+    "During training we want to save checkpoints and log the progress to TensorBoard so we create the appropriate callbacks for Keras.\n",
+    "\n",
+    "This is the callback for writing checkpoints during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path_checkpoint = '23_checkpoint.keras'\n",
+    "callback_checkpoint = ModelCheckpoint(filepath=path_checkpoint,\n",
+    "                                      monitor='val_loss',\n",
+    "                                      verbose=1,\n",
+    "                                      save_weights_only=True,\n",
+    "                                      save_best_only=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the callback for stopping the optimization when performance worsens on the validation-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callback_early_stopping = EarlyStopping(monitor='val_loss',\n",
+    "                                        patience=5, verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the callback for writing the TensorBoard log during training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callback_tensorboard = TensorBoard(log_dir='./23_logs/',\n",
+    "                                   histogram_freq=0,\n",
+    "                                   write_graph=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "callbacks = [callback_early_stopping,\n",
+    "             callback_checkpoint,\n",
+    "             callback_tensorboard]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Train the Recurrent Neural Network\n",
+    "\n",
+    "We need an approximate number of training-steps to perform per epoch of the training-data, because we use a batch-generator function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "292"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "steps_per_epoch = int(num_train / batch_size)\n",
+    "steps_per_epoch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now train the neural network. Each epoch takes less than a minute on a GTX 1070."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0041 - mean_absolute_error: 0.0465Epoch 00001: val_loss improved from inf to 0.00166, saving model to 23_checkpoint.keras\n",
+      "292/292 [==============================]292/292 [==============================] - 44s 152ms/step - loss: 0.0041 - mean_absolute_error: 0.0465 - val_loss: 0.0017 - val_mean_absolute_error: 0.0319\n",
+      "\n",
+      "Epoch 2/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0016 - mean_absolute_error: 0.0296Epoch 00002: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 44s 151ms/step - loss: 0.0016 - mean_absolute_error: 0.0296 - val_loss: 0.0036 - val_mean_absolute_error: 0.0425\n",
+      "\n",
+      "Epoch 3/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0012 - mean_absolute_error: 0.0253Epoch 00003: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0012 - mean_absolute_error: 0.0253 - val_loss: 0.0022 - val_mean_absolute_error: 0.0327\n",
+      "\n",
+      "Epoch 4/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 9.9865e-04 - mean_absolute_error: 0.0234Epoch 00004: val_loss improved from 0.00166 to 0.00088, saving model to 23_checkpoint.keras\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 155ms/step - loss: 9.9820e-04 - mean_absolute_error: 0.0234 - val_loss: 8.8447e-04 - val_mean_absolute_error: 0.0233\n",
+      "\n",
+      "Epoch 5/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 9.0360e-04 - mean_absolute_error: 0.0219Epoch 00005: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 154ms/step - loss: 9.0283e-04 - mean_absolute_error: 0.0219 - val_loss: 0.0013 - val_mean_absolute_error: 0.0272\n",
+      "\n",
+      "Epoch 6/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 8.5867e-04 - mean_absolute_error: 0.0212Epoch 00006: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 8.5956e-04 - mean_absolute_error: 0.0212 - val_loss: 0.0021 - val_mean_absolute_error: 0.0366\n",
+      "\n",
+      "Epoch 7/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0018 - mean_absolute_error: 0.0298Epoch 00007: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 44s 152ms/step - loss: 0.0018 - mean_absolute_error: 0.0298 - val_loss: 0.0018 - val_mean_absolute_error: 0.0300\n",
+      "\n",
+      "Epoch 8/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0013 - mean_absolute_error: 0.0262Epoch 00008: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0013 - mean_absolute_error: 0.0262 - val_loss: 0.0029 - val_mean_absolute_error: 0.0403\n",
+      "\n",
+      "Epoch 9/20\n",
+      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0011 - mean_absolute_error: 0.0239Epoch 00009: val_loss did not improve\n",
+      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0011 - mean_absolute_error: 0.0239 - val_loss: 0.0014 - val_mean_absolute_error: 0.0274\n",
+      "\n",
+      "Epoch 00009: early stopping\n",
+      "CPU times: user 8min 5s, sys: 53.2 s, total: 8min 58s\n",
+      "Wall time: 6min 44s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fb453a609e8>"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "model.fit_generator(generator=generator,\n",
+    "                    epochs=20,\n",
+    "                    steps_per_epoch=steps_per_epoch,\n",
+    "                    validation_data=validation_data,\n",
+    "                    callbacks=callbacks)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load Checkpoint\n",
+    "\n",
+    "Because we use early-stopping when training the model, it is possible that the model's performance has worsened on the test-set for several epochs before training was stopped. We therefore reload the last saved checkpoint, which should have the best performance on the test-set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    model.load_weights(path_checkpoint)\n",
+    "except Exception as error:\n",
+    "    print(\"Error trying to load checkpoint.\")\n",
+    "    print(error)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Performance on Test-Set\n",
+    "\n",
+    "We can now evaluate the model's performance on the test-set. This function expects a batch of data, but we will just use one long time-series for the test-set, so we just expand the array-dimensionality to create a batch with that one sequence."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================]1/1 [==============================] - 4s 4s/step\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.evaluate(x=np.expand_dims(x_test_scaled, axis=0),\n",
+    "                        y=np.expand_dims(y_test_scaled, axis=0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loss: 8.845e-04\n",
+      "mean_absolute_error: 2.328e-02\n"
+     ]
+    }
+   ],
+   "source": [
+    "for res, metric in zip(result, model.metrics_names):\n",
+    "    print(\"{0}: {1:.3e}\".format(metric, res))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Generate Predictions\n",
+    "\n",
+    "This helper-function plots the predicted and true output-signals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_comparison(start_idx, length=100, train=True):\n",
+    "    \"\"\"\n",
+    "    Plot the predicted and true output-signals.\n",
+    "    \n",
+    "    :param start_idx: Start-index for the time-series.\n",
+    "    :param length: Sequence-length to process and plot.\n",
+    "    :param train: Boolean whether to use training- or test-set.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    if train:\n",
+    "        # Use training-data.\n",
+    "        x = x_train_scaled\n",
+    "        y_true = y_train\n",
+    "    else:\n",
+    "        # Use test-data.\n",
+    "        x = x_test_scaled\n",
+    "        y_true = y_test\n",
+    "    \n",
+    "    # End-index for the sequences.\n",
+    "    end_idx = start_idx + length\n",
+    "    \n",
+    "    # Select the sequences from the given start-index and\n",
+    "    # of the given length.\n",
+    "    x = x[start_idx:end_idx]\n",
+    "    y_true = y_true[start_idx:end_idx]\n",
+    "    \n",
+    "    # Input-signals for the model.\n",
+    "    x = np.expand_dims(x, axis=0)\n",
+    "\n",
+    "    # Use the model to predict the output-signals.\n",
+    "    y_pred = model.predict(x)\n",
+    "    \n",
+    "    # The output of the model is between 0 and 1.\n",
+    "    # Do an inverse map to get it back to the scale\n",
+    "    # of the original data-set.\n",
+    "    y_pred_rescaled = y_scaler.inverse_transform(y_pred[0])\n",
+    "    \n",
+    "    # For each output-signal.\n",
+    "    for signal in range(len(target_names)):\n",
+    "        # Get the output-signal predicted by the model.\n",
+    "        signal_pred = y_pred_rescaled[:, signal]\n",
+    "        \n",
+    "        # Get the true output-signal from the data-set.\n",
+    "        signal_true = y_true[:, signal]\n",
+    "\n",
+    "        # Plot and compare the two signals.\n",
+    "        plt.plot(signal_true, label='true')\n",
+    "        plt.plot(signal_pred, label='pred')\n",
+    "        plt.ylabel(target_names[signal])\n",
+    "        plt.legend()\n",
+    "        plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now plot an example of predicted output-signals. It is important to understand what these plots show, as they are actually a bit more complicated than you might think.\n",
+    "\n",
+    "These plots only show the output-signals and not the 20 input-signals used to predict the output-signals. The time-shift between the input-signals and the output-signals is held fixed in these plots. The model **always** predicts the output-signals e.g. 24 hours into the future (as defined in the `shift_steps` variable above). So the plot's x-axis merely shows how many time-steps of the input-signals have been seen by the predictive model so far.\n",
+    "\n",
+    "The prediction is not very accurate for the first 20 time-steps because the model has seen very little input-data at this point. The model generates a single time-step of output data for each time-step of the input-data, so when the model has only run for a few time-steps, it knows very little of the history of the input-signals and cannot make an accurate prediction. The model needs to \"warm up\" by processing perhaps 30-50 time-steps before its predicted output-signals can be used. Note, however, that we can process as many time-steps as we want, as we are not limited to the 100 time-steps that we used during training.\n",
+    "\n",
+    "Let us start with an example from the training-data. This is data that the model has seen during training so it should perform reasonably well on this data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb4ec520080>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb45cd30a20>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb44d2a5f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_comparison(start_idx=200000, length=300, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now consider an example from the test-set, so the model has not seen this data during training. The temperature is predicted quite well after the \"warm-up\" period of 50 time-steps. But the \"high-frequency component\" of the wind-speed is not predicted very well. This may be because the model needs more training epochs, or maybe the model needs another architecture, or maybe it is simply because the wind-speed cannot be predicted any more accurately 24 hours into the future using the 20 input-signals we have used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb45cf3c358>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb44c0f1048>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fb44c044128>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_comparison(start_idx=200, length=300, train=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusion\n",
+    "\n",
+    "This tutorial showed how to use a Recurrent Neural Network to predict several time-series from a number of input-signals. We used weather-data for 5 cities to predict tomorrow's weather for one of the cities. It worked reasonably well.\n",
+    "\n",
+    "You can use this method with different time-series but you should be careful to distinguish between *causation and correlation* in the data. The neural network may easily discover patterns in the data that are only temporary correlations which do not generalize well to unseen data.\n",
+    "\n",
+    "You should select input- and output-data where a *causal* relationship probably exists. You should have a lot of data available for training, and you should try and reduce the risk of over-fitting the model to the training-data, e.g. using early-stopping as we did in this tutorial."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exercises\n",
+    "\n",
+    "These are a few suggestions for exercises that may help improve your skills with TensorFlow. It is important to get hands-on experience with TensorFlow in order to learn how to use it properly.\n",
+    "\n",
+    "You may want to backup this Notebook before making any changes.\n",
+    "\n",
+    "* Train for more epochs. Does it improve the performance on the test-set?\n",
+    "* Try a different architecture for the neural network, e.g. higher or lower state-size for the GRU layer, more GRU layers, dense layers before and after the GRU layers, etc.\n",
+    "* Use hyper-parameter optimization from Tutorial #19.\n",
+    "* Try using longer and shorter sequences for the batch-generator.\n",
+    "* Try and remove the city \"Odense\" from the input-signals.\n",
+    "* Try and add last year's weather-data to the input-signals.\n",
+    "* How good is the model at predicting the weather 3 or 7 days into the future?\n",
+    "* Can you train a single model with the output-signals for multiple time-shifts, so that a single model predicts the weather in e.g. 1, 3 and 7 days.\n",
+    "* Explain to a friend how the program works."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## License (MIT)\n",
+    "\n",
+    "Copyright (c) 2018 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
+    "\n",
+    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
+    "\n",
+    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
+    "\n",
+    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/README.md b/README.md
index 9e4ee47..43ac0b4 100644
--- a/README.md
+++ b/README.md
@@ -63,6 +63,8 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 22. Image Captioning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
 
+23. Time-Series Prediction ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
+
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
diff --git a/images/23_time_series_flowchart.png b/images/23_time_series_flowchart.png
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diff --git a/weather.py b/weather.py
new file mode 100644
index 0000000..524766d
--- /dev/null
+++ b/weather.py
@@ -0,0 +1,255 @@
+########################################################################
+#
+# Functions for downloading and re-sampling weather-data
+# for 5 cities in Denmark between 1980-2018.
+#
+# The raw data was obtained from:
+#
+#   National Climatic Data Center (NCDC) in USA
+#   https://www7.ncdc.noaa.gov/CDO/cdoselect.cmd
+#
+# Note that the NCDC's database functionality may change soon, and
+# that the CSV-file needed some manual editing before it could be read.
+# See the function _convert_raw_data() below for inspiration if you
+# want to convert a new data-file from NCDC's database.
+#
+# Implemented in Python 3.6
+#
+# Usage:
+# 1) Set the desired storage directory in the data_dir variable.
+# 2) Call maybe_download_and_extract() to download the data-set
+#    if it is not already located in the given data_dir.
+# 3) Either call load_original_data() or load_resampled_data()
+#    to load the original or resampled data for use in your program.
+#
+# Format:
+# The raw data-file from NCDC is not included in the downloaded archive,
+# which instead contains a cleaned-up version of the raw data-file
+# referred to as the "original data". This data has not yet been resampled.
+# The original data-file is available as a pickled file for fast reloading
+# with Pandas, and as a CSV-file for broad compatibility.
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2018 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import pandas as pd
+import os
+import download
+
+########################################################################
+
+# Directory where you want to download and save the data-set.
+# Set this before you start calling any of the functions below.
+data_dir = "data/weather-denmark/"
+
+
+# Full path for the pickled data-file. (Original data).
+def path_original_data_pickle():
+    return os.path.join(data_dir, "weather-denmark.pkl")
+
+
+# Full path for the comma-separated text-file. (Original data).
+def path_original_data_csv():
+    return os.path.join(data_dir, "weather-denmark.csv")
+
+
+# Full path for the resampled data as a pickled file.
+def path_resampled_data_pickle():
+    return os.path.join(data_dir, "weather-denmark-resampled.pkl")
+
+
+# URL for the data-set on the internet.
+data_url = "https://github.com/Hvass-Labs/weather-denmark/raw/master/weather-denmark.tar.gz"
+
+
+# List of the cities in this data-set. These are cities in Denmark.
+cities = ['Aalborg', 'Aarhus', 'Esbjerg', 'Odense', 'Roskilde']
+
+
+########################################################################
+# Private helper-functions.
+
+
+def _date_string(x):
+    """Convert two integers to a string for the date and time."""
+
+    date = x[0]  # Date. Example: 19801231
+    time = x[1]  # Time. Example: 1230
+
+    return "{0}{1:04d}".format(date, time)
+
+
+def _usaf_to_city(usaf):
+    """
+    The raw data-file uses USAF-codes to identify weather-stations.
+    If you download another data-set from NCDC then you will have to
+    change this function to use the USAF-codes in your new data-file.
+    """
+
+    table = \
+        {
+            60300: 'Aalborg',
+            60700: 'Aarhus',
+            60800: 'Esbjerg',
+            61200: 'Odense',
+            61700: 'Roskilde'
+        }
+
+    return table[usaf]
+
+
+def _convert_raw_data(path):
+    """
+    This converts a raw data-file obtained from the NCDC database.
+    This function may be useful as an inspiration if you want to
+    download another raw data-file from NCDC, but you will have
+    to modify this function to match the data you have downloaded.
+
+    Note that you may also have to manually edit the raw data-file,
+    e.g. because the header is not in a proper comma-separated format.
+    """
+
+    # The raw CSV-file uses various markers for "not-available" (NA).
+    # (This is one of several oddities with NCDC's file-format.)
+    na_values = ['999', '999.0', '999.9', '9999.9']
+
+    # Use Pandas to load the comma-separated file.
+    # Note that you may have to manually edit the file's header
+    # to get this to load correctly.
+    df_raw = pd.read_csv(path, sep=',', header=1,
+                         index_col=False, na_values=na_values)
+
+    # Create a new data-frame containing only the data
+    # we are interested in.
+    df = pd.DataFrame()
+
+    # Get the city-name / weather-station name from the USAF code.
+    df['City'] = df_raw['USAF  '].apply(_usaf_to_city)
+
+    # Convert the integer date-time to a proper date-time object.
+    datestr = df_raw[['Date    ', 'HrMn']].apply(_date_string, axis=1)
+    df['DateTime'] = pd.to_datetime(datestr, format='%Y%m%d%H%M')
+
+    # Get the data we are interested in.
+    df['Temp'] = df_raw['Temp  ']
+    df['Pressure'] = df_raw['Slp   ']
+    df['WindSpeed'] = df_raw['Spd  ']
+    df['WindDir'] = df_raw['Dir']
+
+    # Set the city-name and date-time as the index.
+    df.set_index(['City', 'DateTime'], inplace=True)
+
+    # Save the new data-frame as a pickle for fast reloading.
+    df.to_pickle(path_original_data_pickle())
+
+    # Save the new data-frame as a CSV-file for general readability.
+    df.to_csv(path_original_data_csv())
+
+    return df
+
+
+def _resample(df):
+    """
+    Resample the contents of a Pandas data-frame by first
+    removing empty rows and columns, then up-sampling and
+    interpolating the data for 1-minute intervals, and
+    finally down-sampling to 60-minute intervals.
+    """
+
+    # Remove all empty rows and columns.
+    df_res = df.dropna(axis=[0, 1], how='all')
+
+    # Upsample so the time-series has data for every minute.
+    df_res = df_res.resample('1T')
+
+    # Fill in missing values.
+    df_res = df_res.interpolate(method='time')
+
+    # Downsample so the time-series has data for every hour.
+    df_res = df_res.resample('60T')
+
+    # Finalize the resampling. (Is this really necessary?)
+    df_res = df_res.interpolate()
+
+    # Remove all empty rows.
+    df_res = df_res.dropna(how='all')
+
+    return df_res
+
+
+########################################################################
+# Public functions that you may call to download the data-set from
+# the internet and load the data into memory.
+
+
+def maybe_download_and_extract():
+    """
+    Download and extract the weather-data if the data-files don't
+    already exist in the data_dir.
+    """
+
+    download.maybe_download_and_extract(url=data_url, download_dir=data_dir)
+
+
+def load_original_data():
+    """
+    Load and return the original data that has not been resampled.
+    
+    Note that this is not the raw data obtained from NCDC.
+    It is a cleaned-up version of that data, as written by the
+    function _convert_raw_data() above.
+    """
+
+    return pd.read_pickle(path_original_data_pickle())
+
+
+def load_resampled_data():
+    """
+    Load and return the resampled weather-data.
+
+    This has data-points at regular 60-minute intervals where
+    missing data has been linearly interpolated.
+
+    This uses a cache-file for saving and quickly reloading the data,
+    so the original data is only resampled once.
+    """
+
+    # Path for the cache-file with the resampled data.
+    path = path_resampled_data_pickle()
+
+    # If the cache-file exists ...
+    if os.path.exists(path):
+        # Reload the cache-file.
+        df = pd.read_pickle(path)
+    else:
+        # Otherwise resample the original data and save it in a cache-file.
+
+        # Load the original data.
+        df_org = load_original_data()
+
+        # Split the original data into separate data-frames for each city.
+        df_cities = [df_org.xs(city) for city in cities]
+
+        # Resample the data for each city.
+        df_resampled = [_resample(df_city) for df_city in df_cities]
+
+        # Join the resampled data into a single data-frame.
+        df = pd.concat(df_resampled, keys=cities,
+                       axis=1, join='inner')
+
+        # Save the resampled data in a cache-file for quick reloading.
+        df.to_pickle(path)
+
+    return df
+
+
+########################################################################

From e686db8f90669350087d6e0879d9d9dda390b4e4 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 30 Mar 2018 08:59:09 +0200
Subject: [PATCH 42/61] Fixed bug in Tutorial 23.

---
 23_Time-Series-Prediction.ipynb     |  990 +++++++++----
 images/23_time_series_flowchart.png |  Bin 165046 -> 164470 bytes
 images/23_time_series_flowchart.svg | 2105 +--------------------------
 3 files changed, 741 insertions(+), 2354 deletions(-)

diff --git a/23_Time-Series-Prediction.ipynb b/23_Time-Series-Prediction.ipynb
index a5844dc..69a35b5 100644
--- a/23_Time-Series-Prediction.ipynb
+++ b/23_Time-Series-Prediction.ipynb
@@ -65,7 +65,7 @@
     "\n",
     "In this tutorial, we are trying to predict the weather for the Danish city \"Odense\" 24 hours into the future, given the current and past weather-data from 5 cities (although the flowchart below only shows 2 cities).\n",
     "\n",
-    "We use a Recurrent Neural Network (RNN) because it can work on sequences of arbitrary length. During training we will use sequences of 100 data-points from the training-set, with each data-point or observation having 20 input-signals for the temperature, pressure, etc. for each of the 5 cities. We then want to train the neural network so it outputs the 3 signals for tomorrow's temperature, pressure and wind-speed."
+    "We use a Recurrent Neural Network (RNN) because it can work on sequences of arbitrary length. During training we will use sub-sequences of 1344 data-points (8 weeks) from the training-set, with each data-point or observation having 20 input-signals for the temperature, pressure, etc. for each of the 5 cities. We then want to train the neural network so it outputs the 3 signals for tomorrow's temperature, pressure and wind-speed."
    ]
   },
   {
@@ -123,7 +123,7 @@
     "from tensorflow.python.keras.models import Sequential\n",
     "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
     "from tensorflow.python.keras.optimizers import RMSprop\n",
-    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard"
+    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard, ReduceLROnPlateau"
    ]
   },
   {
@@ -285,8 +285,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 8 ms, sys: 24 ms, total: 32 ms\n",
-      "Wall time: 130 ms\n"
+      "CPU times: user 16 ms, sys: 16 ms, total: 32 ms\n",
+      "Wall time: 30.1 ms\n"
      ]
     }
    ],
@@ -575,7 +575,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb464ab7ba8>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a507cee10>"
       ]
      },
      "execution_count": 11,
@@ -586,7 +586,7 @@
      "data": {
       "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb464b19780>"
+       "<matplotlib.figure.Figure at 0x7f6ab00579b0>"
       ]
      },
      "metadata": {},
@@ -607,7 +607,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb46057fa20>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a4c19cc18>"
       ]
      },
      "execution_count": 12,
@@ -618,7 +618,7 @@
      "data": {
       "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb4604e6cf8>"
+       "<matplotlib.figure.Figure at 0x7f6a507d9e80>"
       ]
      },
      "metadata": {},
@@ -860,7 +860,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45af285c0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46be8a58>"
       ]
      },
      "execution_count": 17,
@@ -871,7 +871,7 @@
      "data": {
       "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb460548a58>"
+       "<matplotlib.figure.Figure at 0x7f6a507d9358>"
       ]
      },
      "metadata": {},
@@ -899,7 +899,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45d098080>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46b8dc88>"
       ]
      },
      "execution_count": 18,
@@ -910,7 +910,7 @@
      "data": {
       "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb45af37fd0>"
+       "<matplotlib.figure.Figure at 0x7f6a48d91f98>"
       ]
      },
      "metadata": {},
@@ -929,7 +929,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb45cf808d0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46b8d7f0>"
       ]
      },
      "execution_count": 19,
@@ -940,7 +940,7 @@
      "data": {
       "image/png": 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10K3MUOOuNfb74d/1hl1DohEG/4zWGtv2NrJzaebxp942rSSiJDG0jxuLSRI5CfDxEVZu2FN6veMJb9A9ZgS451bW13Esqf8f/9+H8Sf/efuoP1+GgUaEVVv78b0Vz4z7sV289Rtpedxr7lwrEobq7N6de8xCAGmhKq1lALBVUJRz21wG6aIVh07Y3GeVNolGRrmQQZcNS2hMcaxFVyE+qW/vr7MaLVIGuWfQjnUo4tRTknno6TGbsUZXJVWzuHy4mXyySYAmqyTRRknjSh07BW/QPWYEuOEp49M7VZxr856hUWcDTqSy7ZKTl5hzlnno+/VUAaQlYROtS9VDHFprNOJ8NmdRmj0dryxTFQD2DkW26qFOVS5E0bjfLfe2ywKzO/Y2Cjl0QBrxIVH3RyOOtZBXUpEv+vyWPUNIGIUTZZRLNaNpEq3NvZ0oxYs36B4zAtwDKip7mm6PP4f+8IY9eM7lN+KaO9eO6vMT2aZsv97UWG/ZMyQzHxv50sNhoKDRXtPjOJG1w1vJQ+l4v3mkPOGmrx5ZLXyWOl8poFzS1Hq7zT3nRiSvqayZNDfifJKxHLqdlboygx4nGo9t6sOZl9+Ib9/xtLneRKe/MRrriqd3ijFMBLxB95gR4A96qeKlAyqXxzan3OhdBVK+djARcjZq6mAqBjrBO1fbDaQcd+rJD++hR4mWcQvy0Av2LSo/60J46FmCD1E0wlBn16BUynFHSVLItTcTjUbMPfniUgKcekoNv1TjkOcdJ9q07rtzzU45kcSJ8eQHWsQfOgVv0D1mBErT/ZO8ARjxsZ3PPbR+Nx5cl5ZMJYNA/OpI0ekHfell1+HcK2/Cwxv2WOVIJA36YDNPlxQGIUuczChxu/vIa3pmxwD+5tr7sWeo2bKwFaFvKBJeb6xtIpKbKQoAtTDIvGPLX7uTOunLozgRHZD4BCPuQ5Kpawool1hrqIxP0lpOEPVmYgw//V90TzoFr0P3mBHgziM96IFyPfTRLXtduePL/u13AKwWGxg+87EME5VMuGuwYSa0ZpyIe8GVLEYnnhkj7r2X0UNxrFEv6RgFpD07f3jPOpx40Fyz36ELenLHqYYKzVhjb72Z6w9KE0x/I0+t1SoB6lHaA7QaBhhqJsKANmOb0p963iUeemS5/yTJ6BP2vZK3HifWaLvJV/XIvldhBj2eIMnsPu2hr9nWj+1t9Jl8cksfdrMMOo+phyIPPQyUoFlG6yW1omroWW6l2miFTtT7WLt9AFv6hsRrabs2Sn+XFQd3DTTMNhm+aoFHXEYPRUki6AqaFGh3aiARMS67qJYL3Yo+RrnQmMiY0nM4u6tiaJRaaAOmdlvSJ3RdbrIU99BpbF2VIFPQSKPMs0ZVRihd9+DG3PGqRhlTvmrpFPZpg/78z9yMt2VSrjJEcYIXfe4WvP9797Xcz2Ny4WaHBgpQSjmNDkbpobfw7On4QZGkow10gnK58Iu34HX/9Qfx2kA9RiPiCTD2mshIKmUNDxncoWaM7qpUd7jjjhItDD/f3rh7EAF5tkw104p66a/HUm6aaKNyIUnknO6KoVGqJvnH8tcNx5jyhCE+WXCqyBr00GShSg49kyM6NEtS4qHzVZDn0DsMkpndv253y/2296fey28f3dLxMXmMHvx5ieIEgVIIlKVLqqFqqb5ohVbeFXnYU8mgDzRirN7WL16LksR4o25GIxm1WhgUeuikpW6W0CpRonOqEvNerBEqq8vmahMO3h0pTiQlFPEEH0azcMolPa+VDEoOPTEGPnECvdzw0/2pVVLJZqylQbdJRnZSOGBOF6JEG4km59DLEtw6iX3WoLsV08a6n8fkwk09Tw26pVwqma56NGj1MJJhCkf5JPExDTTGN/nELVJGNVuasfRSG7H1dPNB0RjdBQZdeOuxLi29oLU9VqKt917U7JleShydfJwkxsvndBrFBDjFYYKiQq6qBYfeLDDi6balXMhDrxZQLglTylBfU5I0csqFVkQ0honAPmvQW2Wzcfga2tMDkkNPoJRsUVYJValKYzi00rKTgRkPD/0PT20f1TE4+MTWcJb8Q9xDd7zoQKVBZEO5ZMar3uQeuj32jr2Md08SR/poj61hMzhj5qG7iVhuDRRXbmoDkjRBq0LKpchDjxJZRVHQQ4WUS5BVcpQ6dDLUEZNBap3+TSonTrmUTYCdxD5r0PfW2wtyul7dnqGmaN/lMTXAnxdq4ss59Go4eg+dP5hDDvdbb9GOrB3wce8/q2tMxwLcImWOQW8m5nUu4UzrfqvU6yXVTmZAh6IYXZlB50ZyD+t45BpJwS8LD93q1V1HyW3yLWrwMJWL9dDzlEs9shz6tayUQpQkgkMX32dByYiuSmjrtjPKhXj8lIcnJZVCkmgTZ+Bj8AZ9AtFfb+9BdH94r/3y7XjR5/6vE0PyGAOEh55RLmnCiV2ij55ysZ9z1U5kBEarYti8x6pRxkPxUkZ9RMyQpZSLNMBB4Bp066GTsSozhFGsxcTGz8trmXMPPVexkH8mSYOYtOjh2Zd2grZjLfLQd/Rz5Q6bSLRU+IiEtAJ+nquXaqEdA403yH5jREtxmqbTWcpF2GcNetsNb539Ht3UByC/ZPSYXJRTLtlDH6hRa765IdvglEElwzba1O6tfVY2Ox5eXF0Y2uLkGjcoSqqgQKlcvfKyoOh2ZjC39A2Jmij8vFrDJOFwlYt7qXKsjmFkHjpXFbledJMlFnGIkrvZxFZWSgCQk4WQLQZ2PBRsDwIlOHT6POAGRb2H3lG43tDVt63B32TF+zn4bvyHsWH3UG5fj8kD58ebcWoAAtbwuDIGyoV7Wqscuo0Mwh2rR8d/c+qiGY3diyvyOAGZnt+ME9zxlCw1G2ZBZMuh26BoTwHl8iBTh33iukdKM0W1tjVWksQmILnfhUu5NGOrKeeJRQAM358kcqxuEJMgGnhkkwpd02Ob+9h9sF65KYHAKZfsPJ++/jFDX6VNtRORKVxxOPRaGHgPvdNwPe+P/WwlfnjPuvx+7IfHl8dexji14HrogVIFQdGxq1zciZwMKFUpHCmEIRwHL04Wm5LlYDndwcfLOXS6VsOhNxNDJ3DlyPZ+u7I45+iFwkOXQVE7aSUa7VEuWfIPr25IMlQAVsFkPHSWnu8YdKVkSj9x6EsXzgJQXG+lKN3fPfamrOa71ul1CQ/dqTvTVQm8h95p8Ie71YPOf3icdz9gztgDWB7jB5n6bykEepDScrCjOzb3OPdkHLrpcZkZskSn3uitT2wdER0XC+4/NQD3rN2JvqHRZSbXReDSGqsokck1jTgxv2Hi0IOgQOUSxegq4NC5SqwZJ46HLr3tnQNNu5+5X67KRVIfcaKNAaVmzaSWyRv0fAEtQnclNB56dzVItfBxggP3S9vB8Weax1sI3KBzMmdLRpUZo121+1Hw9IlsNddVDbxssdPgD1KrEqZlOuHx1gx7jA3CMCY2KBqzh3Q8KBcy6FUm6wPS83zvrmfwpq/diZ/ct779cbNZphlrDDVjvOpLt+Gd37p7VGPlXjk3ujELDJKnTEaIDGbIpJecYyYPnXu6vP5L31AkOXThLNmJyi1jy8E12ybYWbHKFpUZcSD1uoPAHldICyuOQa8GJpekuxqmQdFIY253ukJx1Tr82gFZdE0phavedAaANPOWj5Xv57I+XZXQZ4p2GjIlvIVBdx44+3pnxuUxOiRaZhOmBl2JQNdoHypenIuMAxn0IeZxbt6Tem2rt/ajXWiHKiJjeO/aXaMa65DoHGSNVSO2TZSJoyYjREHHgBkyMpJap1RDoOxkBkiqaG89Eud1dej02NSjpDwoyisWRpZ7BuyEoxzKhY7RinLproZmIuqphkiSdHy9tRDVUIkVFzkFRTXQgfT8NLkNNNMJja6nm3nobk5CVyWYsH62wxp0pdShSqmblFIPK6VWKqXel72+QCl1g1Lqiez/+Z0f7vjB7QpeBu758YfPa1ymFhIN0S4sUHKJXAmDUXcH4h46GQcTNGQeOj3URT06y8BjZU1mdEfb+IJnPu5lHvqQwyM3IitHjOLUA+YeOm/i3FUJECglKJxGbPnhvUMR6lFsjGkkgqLWKeLyQaDcWbJ9R4lDT6CgGOVCdFpeWsi9a3pvkHnoUWKrMnZXQnNNXZXQ/D4q4tqZh87G9ND6tB46BXm72X6BM4ZaJZhSHnoE4G+01icCeC6A9yilTgRwGYAbtdbHALgx+3vagD9IrQIWfGLlu3WiSp7H6KFZ7WrihLmjVBkT5ZLPJiTjV2cUAq8p0i644W7Gsov9aMCVKH3CoFuvl7IbhSwwC4oSqg6PHARKeOjkhc/tqWLPUBNDzQQ9tby8kZeXbUSxrLEirr04YxNIn8EggAiKcjqNe9ShI1tUSk4+RDdVKwrdtdBQR92CA+cUDlfXKNQq8vhFHLpbeLOrGk6daota641a63uy7T4AjwA4GMDLAVyd7XY1gFd0apCdQLt1snkH88Tx1vuGmrh2xTMT1l7KQyJOND7604ewpW9IpGmTaoMvfathMGqvl6tPeA0PAHhkY+qpaW2X2u0ERW9+bAt2DzaFlxrFNkNyJAZ9Z38D7/zWCvz+yW3CA17PNPNEFXVVg6xPpxb1vak6JYEbxjBIvXde8IsM2dzuCh7d1Id6M8asWr5EABW5os80osTcuzjRuHftTjyzY0BWQCzy0F0OXXFpIdeKS2vKj0t0ST0rs8vpFHrPPQancJTKB10J3JMvolymZD10pdRSAKcBuAPAYq31xuytTQAWl3zmUqXUCqXUiq1bt45hqOMLGewsXyL/7Q8eKPxMolPt+od+8AB+9dCmzgzSoyW+c+dafPP2p3HmJ29MKReWHp6nXNQYKJcijbVMRU+72KTvDGeLt/QN4c+/fhfe9917nWBuMirP/I//43e4fuVm/OlX7xDG9ClmgInrpwAdL5oVJTrLFLXHdI2k63U2WYAVSBU1hR46wGgkqntimyi/8ku34dwrbxIcs0u5JNp65QBMViuBTz7zemsArCHeyGSm3AuvhgG2s3o0s7tsrx/hoTsGffHcbhSBTw5FBn3KqVyUUrMB/BDAX2ut9/D3dOqSFI5Ya32V1nq51nr5okWLxjTY8QR/cLhXs61Fwwtp0K0cy80e9JgYbGFZloJyMan/kluNE4299UgoG9qBSOFmHrorfTVtyYaJsJBUbvW2/hyPPJoH/5kd9vcn6Y4iXtquYtz7JVQuzEgGLGA6r7eKOV0V88ycc/RCs19vrWKOTUhYoS2aGGmy4HMXT6oiXrpWkTQGjYFr0gHpUffWQqy54hI8/smLsOaKS8DBvfBqGOCMw+eLv4uuXRp0VW7Qq1wNk94n8x6rDdNptGXQlVJVpMb821rrH2Uvb1ZKLcneXwJgymfa7BlqYull1+FXD20SxtnNgLt91XYc+/e/zBl3vmrSGpiVzeojNRAe44MTDpwDAFh26LyUQmBlVPMcepopuvwTN+CUj/96ROfh3iMZ3K19dfF6rLVZEQz37Bq5XSCVNzwoOloU1Syvhqow0GgaTxSqXBinzPj17kqIMFRoZjJDXjOlt0YJSHJSoWfNZu1m53VqzRCofEHN8Xp5UFRO1uWUCwcPXFZDhd89uc0en1lCfjxeSsA98uuWH2q2XQ/9L59/lD1vdQpliqr0zn0NwCNa68+xt34G4C3Z9lsA/HT8hze+IDnZl25+slS2WKsE+OKNj6MRJ4YfJbgcOj0wXLLlMXEgwzGvt1pIuQSOx6n16L4rtx0aYYAlpSSMchmO2uFdgRINpjaRnYRGA1E2lrVos7VJrBLI3q+U1+Yees3h0Ole1ipBWro2O94hrDcoGXRX5eIGek33oXo+yFoNlS2S5dAdZKuV66GXeNQuWkkL+d9CNcMNumPR959dM9t8rO5vb6p56GcDeBOAFyil7sv+XQzgCgAvVko9AeBF2d9TDjv6G/jB3etygSrXMyJUmbzN/XFIlQuP3nuDPhmg4FklSNP6K0K3LD30ajhy6dhda3bgkY17Ssug8mSaJIHpM1n9dvbeAAAgAElEQVQWFE2Df4n5XCVMlTdkDJqxHvOD3yjw0GuVwHrozPvkjSdCJT10/tvnBr0apt46neeMwyxt0ZutWN3yueQYmazdzEjyypW8/Rttux46+ci5yTooNsYuOOXi7ufSc+Z1KDNedxIoyygNlOT4u6oTl/pfGW4HrfXvkF9tEF44vsMZf/znzU/iK7euxiHze8QXyr1tHkjqqgQiCs/hcujkiXiDPjmgpTllgdYC+VCJoKgjW9ywaxAHzct3nud4zZdvBwBcdtHx5jWhSWfB9GacGO68SB65cfcgzr3yJrzz/CNx/jGLzJjibCKiOipjDZ41o/zvmpeDFRI/ZqBcDp3z8iELmNYqISrNBM24aY5NIJULfx6o2TIgi18B0qDvGrDHa0R5D50KctFYBT3UQofO0cqg8z9DxyunYl3ukfkkIEoEOAbdF+caI5JEGy/p4cw7aESJ8JyEDt2JyhNcQy1rVNjSrI0J+rL2ZRR515QU0luriMQigHTLcunMD0Ea7Xa89qjA6wUsfROoNFuSjlXkoG/rS7nmWx7fxjz0VEIYKIVKkLbLGwuHzqkQPtZqGJjCWoIbzwU+021ObwDSQ++pBqgwTp4bMgqKitR/pqbhzUYAmXm625RUsNcgxic4dOVQJMzwtzDonOcOA4U3PucwAMBfvfCYUo9fKWVWNcr10NnfRDel45O/vbH0sx0pZqRBf91Vt+Nd/5PWwiCPJdba1DKPEy2TGhw+nd6q5wy6w6F7ymVC8LlfP4YzPnFDzsuhpBDy0CuOhw7HKHHPebAZ48F1u3HCR3+FWx7Py2nf9917zXazhEO/bVUaVJvfW8NAI86ltT+2qc84ETTpKwA/vW8DAODup3dmpWHJ6CZ4/VV/MMcfaXXIWOtCeij1erNAY1hsuLgRCpUShjpkBrS3VsnuJbLj5SsTukob+t7cYlr3sPIGZNArQZDbD3A5dDnhVBzDXwb3mg5f0AsAOGrRLOF98wlCwU4s7qHvfWan2ebql9AJyIfBFJQtTifctWYnrl+5Of0ju7GNyCoIDpnf4yR0yOpwBNfzzmXAxRS99wa9k/jX3z6JXQPNXEo9UR5JNglLAyVVEaFSTh/NBLc8sRWNKMHvmdqBQEYXkN8v97QeXJ/WBCf9NeUzaGjc+MhmvPQLt5hCXWTsm1mdGUIzq0VeDVMPnV9juyu/ud2pZ6x1cQu6ahCIQCxBpvpbmiAIlFipct13dzWUiTfMSB69aLa5JkI9Tozx54XSADlh8ZIKvIkFQTEZaj5pTE5MHG4chV/v2885Av/+xtPwx6ce1MJDt/eMSLyfvOdsXPOO5+Dmx6wjQMW+aKznHm0l2qmH7imXcQF92bwwkBsgkx3Gi+WM7t9UszndHv9xe+Thfh9UnyRK8g19eWIR9Rd1Gz6029hZthKz24fvn9bUJm7W1EvRwKqtaelUqvlhFFFO+ns9iqGUQiUMcg99uwadSsGmx5Mql0BBUCSuvpzAa7mESiZh8cSinlooPFhu0Of22JAcNZAYasTmutyWcSLA3LRFz4rK2KY6dLvtesB2W36nRSsI2q8SBnjZKQdlkwW7XiFVVMbA0z7LDp2H5zH9PWAndRrfQfPsd0JqptHW4x8JZrxBp4e2ESV22avk8ltE5RMrP2uXQ5+IL8ojb+DICFAqezWUlItNFVeivRqQUWuQ+ugyuJQLGQ0qfuUW5Uq0Fg2F6XNA+psSXeej9HjVQMGt99FuByOZNs/L2KbH5ty6SKDh6hBljWEYKJEcxTXqPdVAJvJUrRHnyTWzumzJXXq8XA+dP09cseTuB+Q59KJSv0Ce5/7kK08227Ww3PC39NCNygWl6KnK1H/Rui77/ETw6DPeoBOSxPYz1FoGn/gDwbn1RiSX+Lk2WcZD9wZ9IuBOsGRA41iL4BsAkViUJsY4mYlx0rYm3eWluyuydC7V8SCjpJEaSMD+NshYKyhhdMmgVwqUEO166A3HMJLhakSJkdC5vUIB6aEHShmDHCgZ2OUGtKcaOvXH7TZP3KEA6VAzYR66lC0W1W/hlEuZQadaLgR3Zcbx8mUHsbG2MOgliUWBAvPQ2+Pn3TFwvX+nsc8YdN6g1g2K8geirCQAICVhgOXQJyjesc8jT7nYYJtmxaYAmU3oqg6A9HsmwzpccbUoScSxuxyKhTz0IeOhA6FDKxRVE0y3Y0OL5D309n5YwjA2Y6PmoDrnlSAw6fTcqLnGnSaCkG3TfkblUqvkYhUEnrhDqo/BZsw4dClblIqhjEMv4fgVo1lS2aK9/rLxuO91OSs4jrIJArDetmvO//FlJ5ptV7bIwWvmdBozzqCXJXVEieW8G1EiaBK39gT92Yw1XnD8AewYkpqh442k5ZjH6OE+EJziiAtULvRYBYHKPWS8bspwKqVmrMUDS5wy1UInz9RQQGwCcAPnSsnf21AzMQbUnVgacXt11V0pJU04zThBmPHDto6KDIQSAmWNUiUM8KazDrfvMQqmpxo6wUo7Dl5xkMpi9NdlGzzA0j5cXWYrLJavIDjlUpb6nw+KFq8mWunV+X1RLTz0l5xo6xFWC5Q2t37oAvzmA+fZmMEEeH4zzqCX6XjjOBG68TIdepzIVGWuXW2UcOgTVbx+JuOprXvxrdvXtNwnTjRuemwLrr5tDbTWuHN12rk+SnSWKSofKu7RuRnha7b3m+9tuO5AUZzkNMzVMGAeemrIfvFgWnWTlCuApfDI21Zw6pZktMia7f349cObxXlvfmwrHlq/G99f8UzL8UkuOjaecjPWRqFCp3RrtPBromusBgrd1RDPOniu2Y/iBRo6R4UQuIfeXU0T9PoLmjAbj5WPmyWJ2WNDbPPg5Khki2GrxKISDp0d3z00/01QVyc+7kMX9OLoA+YwD73zlMuwmaLTDa5WnJAqIdLtepQ48kTprXODLtQwkfTkI7afx9jwmi/fju39DbzhzMOE0eFItMZbv34XAOCiZx1oXo+TBFrLgF/AaAKeGEMYasaFDRKK0Ix15n1Su7LUozYcelWON2KBU1MeokQaG8UJapWgkM//xHWPmO3XsEJQReOrBGnySoNx6ED+2rkn6Sbu0MRAVUTN/QsVNmRlaH90z3ocvn+v+NzbzzkC1Szblb/eVQlEaerIkU42Czj0sqBtq6Bo2QTjQvDcOYNut92VnpUtlh/PyCp1Xj1VFDPoFGach84r4DVjW9I0LeNplQayBZ0T7Iyt5+0G0giapf57xmXs6Ms8uaEW9EdcsESn11Nlicuh8235kEWsbspwHPpQM5YdaYKUiyYjzFPKActd8zGTN6qUcsrxpgaAT1AjRTO2jZyjAvmmTJMvN5inHjIvO0ZiXgNSD/3grEzChy88Pnef//FlJ+Kyi47PFbiqBIGgs+i4ZOCKOfRiyiWVdmYGPSivthi0sGj8vriUSxmHzikX11Bzgw5Yg+/OKa7iqZOYcQadPyyNODE32eXQW+nQTfBUaxTVlAbcwv3eoo8VxO0Otmg2wifhu5+2WXo08bo8pirx6ID0t5Gw30Mr1F2vV6VSQEO5VKRBb8bWYbCyxfJchyBQuOC4AzAaUCyHlv9pKVynUBS79GoJ5RIoyzHTWLmMke7tQfO6nWBlOecdBlLRQ5ddREHQBB22CIqGzLCWrTpaKVHc2jUcoi6LU+WxnHKR37tRVTmTRdEE1inMOMpF1N3gXpzTr7Gsn2GibSNb8vzK9qMfpJctjh3VSgA0YtHM2AV/Hu5as8NsR8kwQVGV77jTiBIxwbdC3kNPOXQyQt05ysU6D5FT7ycMVK5LUahkwO6oRbOwams/2gGtSLtY2v0sp/tOKeXiJORUHPeWDGBq1LKAaRA4hju/f/p6OukVSS/J4+WT3JDh0NnxnPPw4KQ4b5uUC39KXZqN898iKIpyyiUMFC4970jTFSn9xeUpF3e11knMOIPOI+fNJDFfYsw5b61zvRwJcWKplCiWlIsbFDWZop5DHzPIc6QH+9YntuLUQ+eJlOqykscxyRZdqoF5TC5n2mBe9HB6b9dDT5sF54OifGzWeUhfu+nRLWYscaKzIlTpby1Nu7fHP+WQeTmDrrUu9D7JKJKyhZpV8LHKxhVl1ILCdqehCx2Hl1UIgnKZIJ8PyDDWC2IDFaP6yCdYldUld0s5lJX6bSFeEavtMtlioFSu7dxTWdZv0f3/yMUnmG36HeV16PmYQacwAykXmfqs2dI3YQaYP8Oi80xiP5No7QSwnKBoTPuN/3Xsa6gZg55gR38Db/ranXjvNfeKffh3QYa+mtUUT3Te0CjmYboPMPfQi4wOx2AzFstrqr1CHHqXw6UONmMWME/3WcEooihJWA30xHizhPm9NbgoMwa0CuXac7c+ODcwbjYtv6btWfehpVnQM2K6cdGAu8Sgu4HKSqBEBqgdA1EuthZ8WsMepQZdcOiq3PC71BoHX0jn66Hb63HPSwHhdlfiruG3zbi9QR8x3DRtE5RKHA+9haGmJfGugUYp5VLUicUjxfa99RG35aOHvL8R4dpMpvfgOiknJM8WsAqNShAgSWS6PZDVb8m2iygXPsHXh/HQ++tpA2Tz0GceNbUodD30jbuGzLHpN/fiTLMcJxpxbJtxUACVGxGe3cjHWwT6TRqDHkvqyT22q6cnBAFwQZZz8e9vPB0AsF9POmkumFUTXqbLbfNzmeMphTC0HLpUr6TbVGGRPufWVBHev7IUUeh8n61S/zl4OYPYkRCa5CHlrFzYPu0a9FxyE3HoPlN05IgclQuXFpbJEfM69HR75YY9oo8oX1Jpz6GX4iWfvwVvYGVg2wEZmvuf2YXPXP8YgHzHqJgpWcirpsYVWrvBMabSKJAtphO8VT21Sg7bW4/QXQ2MIQsURHtCl0Pvq0fG2zW0TmR/KzGrO0OUi9vo2EWZMSCKsauFyqUs4Oca4NMPm481V1yCZx28HwDgylefiitffQqOXTwHZx21PwBg/1m1FpSL3K4ylYvk7tPtp7cPoBEndpJu4XnzVUwQyPeozABdbxl4QxP390DlHLhMEZATVrt+m+vMVLzKZfTgWvEosUqGmD3AiRsU5VmjTNnSVQ2yOtsySk3V0+gL8gZdYnt/Ays37Bl+R4bDstrUXZUAl5yyBADw/OMWiX2SxHqHRhXBGiKU1UNXDucKpB5amdLJRX89QjfLkHSX69xDP2JhWoGReFc3GzXJnAnyqBtxkutwU6TDL9Mwu5RLnCTC03UVPm7FQUJRMHHBrBpem+nfP/iS4/CbD5yPpQtntRkUzTj0gkYY3Lgv2a/bTG487lF2PBor/67ndFfM8Vs1uDj+wLlmmySahG5Wx6YsUandWNkAS6YCeB9X76GPGEKHHrkeevp6PigqU/rJ2O8ZjETCSsTkXKle3XPo442YB5ud+8oDfrSUrwS2FHIYSO25CYoWUC5ud6BGnOCbt6/B8k/cgGd2DAAADs0aICc6feBt+VZ5MM6vH5g1OiD55R2rd6BvqIk7M1UOBdNlKzg5tqK09KIWZn/877/D//ede8UY3AbZLuXiJl+ZMbRybbP3jz5gdjbeEg/d4dN5UTB+Xl6Z8MD9us2qweXGS8v7Mk4/fQ84Ycnc7BgtL6Pw2IBdZbnxDAXgzKULAIzew55IDn3GqVxEh/bEKhmixKb+8/R+9zOcjokyJUQ1VBhscg9dCQ7dq1zGDlrkaFZEzTViPHmIB9toAqAyubFOA3fEoruGgkq08hT8RpTgoz9dCQD4wLX3AcgbIa6y4OCSRpIM8kYVa3cMoBYGGExixDrl0N1mCw+s293y/hQVduKfqfKgZWb8YuSbZbtFtwgtqOcc3J6bBK5yoSDmnsE8hz6725qdSsAThpQzybBjZ5y8OXbJ6qKIQ//nl5+E7XsbLa+pyjh0Mbkp4CUnLcada3YM67idd+wi3PL41lxMZr+eKp69dD5md3Xe3M44D91VuXDe3Hp+5ZQL8bHpNkSdbSoREGQeOj+eR4qxeiE8savpHCtOkOPQSQYIyOAnr8jnGoquStpEgX9vPAGGvmdu/DiHnqNcKvk64DzlnSYZICvdrHVOBunSSy5cysW9z7yiX8qb29fboVxaqUNccH06N6BS5ZIGMfuz+9BTzRfuojEQfZKjXErK2IaO0eU5B0V481lL8f4XH9v6mgI7qQjZIqwzMNxzft4xadMLN6/hmMVz8P13PQ+nHTa/5efHAzPOoAsdutADS+NeRrnw/VLDb2dvqo8eGg/dZpR6pGiVGFSGp7f348ZMpx1rW9bW9dBFUNQ0WrZlZznVECgwD10aiu5qiChJZFax6PSTmGObz1RCwUt/7I9s6VQ3KArIolRKQZRujhKdq8193IFzzN9ce09wg6Jf/r9V4m9Tczvj5M19cALCbl9NQquEHBecyy56nd6rBMpQT90s0Durxj30QFBZZTJI7jmHjtHl3+1wj+LJWcDXham1nruO9hODyGCfdFDxOSYCM86gx0LlkpilL5ctpjy59WJEkgqTNCY69ahMD0Rtdb1Ch975WMe0gdtYux3c8ZTN+uSNSNwHqCgomlIu1lvn3DH3UmVVwDBLGisz6OnrQmoX2gzJQCksP3yBOB7htEPTYNvmPUPmNX4d5DDwZs28FjkA7NdbxVfevFxcu+uh38N07ek1pp9PtDRCoZJ8MR+rmLAKJqUy0L10uX4ejK2EGYeePVs9BbXS03EzDz2QZXFzlItZGagcLdLufPT9d52Fe/7xxbnXTRIV0h6s/JoC8/y3NuhnHD4ft132ArzqtIPbG0wHMOMMuuDQY42dmXyMe+UUFK0WZHAlbCmuM+MukioUtbCDp1wKMBIP/ebHtuAdV9/lJHZZeWjTCVzGiTY8qq39oUzNcf6g86bCPKAGpJy3y6Fv3mOzJG0RKe5FQ1AuZXru3oxO2DPE6oCLPAfS00tP2eV+SSbojonuA61o+PgInDd3E4t4EhSf5Ehm2Q7oeXBlpYC9R7VQNpN2JxKiYCqBwupt/dl4pLethIduuXZK7Cq6Dpngn0d3NcSCWfnELZ4V68YIaEztPOcHzetpqbTpNGacQXfTw6mKH3+AqamwzVgrroeeaI0kkUsulfF1vI2dTyyyGImH/oFr78dvHtmCrX3WmPLOUlGS5FZP5jym9odtKsy545RySRE6HlxXJTS/AcJDG2yAkV53eW5T7CtQhbpqQHLFBJqgeBOLIsrgsouOx0/fczYAYHZXBTd/8PlmHz4p7BrIG99cQS42sfHxuXXdCT9/YGPumGUgA7rXkecBdjVQrcjz8jiDUnZCLEvvB9zMX0m5uNc7VtAxtNaiCYiCnaSmw3M+4ww697r6hpqGUxPceCZNJL2vqITHOhZRcS7eE5B4Wlmcq9NXVY5fPLgR96zdOfyOEwTuoRcl61y/chO2ZHTEjswrjJwVkgmKOh56kmhDbzUKKBduELhU0U3n7s489DjRZvnPOW+39yVARoSOJx9umeSSN+iGR65ygy4pFwB41/lH4dRDrT566cJZuPptZ6b3iDkdRbVnSpOqHCPJJZbckfz8607NHbMMJeXqzfmAtN1bxbnnZnyQxtmOR64m3BIDpkiWcitr8hGMzrjLYGzxvZwG9nzmGXT+oFFqMQDhkRnKpaBIEOfgtU7/BWyGph9dnNgveDIpl7/89j1441dGlpXZSXCD7no0T23di3d+626cefmNgrMWlIuWHLrbwJvuNW8q3GTqoyLKxVUukMqFG/Q+TpEUUi5ysjhkvmzyQCjy0CmO01MLzW+mrIytC/IWmyUB3KIxiInNiR9wiSWnNBbP6S4dgwvuHbug9Pq04QVXCfGJxH5P3Gi7BcjKEotcbb2kq0b3LHIOnSd28bjAdKBWZ5xB5x76rgFr0LmHrjP+mxcJMp8vqOtSYfvR0tstpTuZaLd7/USAUy6udnoXm2Cf2rbXbMfOPScPNIoTYewT9h3axCL50AvZIqNfqqE0LlGmgOrJDDqnD0xQ1OGbuXKkxwnsEXoKPPSimi9CMtiCc7WVCVsb9NL7wFYWQDmH7jZraIVWE5Chqyquh+4YdKNGYgbd+ds12j0mmzOfnj9W0sWcV+db0BlRxDRw0Yf9FpVS/62U2qKUeoi99nGl1Hql1H3Zv4s7O8z2wT1s7qG7NdCjJGEpuexhcUrk8qJPcayzNHL5UE0Hbm2iwD1016Bz9QBXBvH9kkQbjTlv5AzIDlJDTIdO4Dx3asSs0eBL9K4Ko1yq5c2M3SScgFEuHGGgTKCtyKD//Y/TR4fzyGWdeVzwZhCPb+7DtSueKWyo7LaTs6sJaSQ55cLP2t+isUh+TOXv0bNQDQOhohH15Lm3zQahtTy2+93SvXUrSopJYZSPonEU4iRXVtjE0KbBY97OtPwNABcWvP55rfWy7N8vxndYowc3zoPO8p/PsM2omHJxPXSt7bLXeOhQgtOcLAe9VUGpyQJPqImdJ4CvZBJncjWfSWz1w3xQlBW7KqzfAuH50TPv6pZTHXo6wXcXeOh0X12j26qWi5XyBTk5n9mvxpUebVIurB/lSz5/Cz70gwfMPRHKEUfGx+kJPmHwSYon+Cw/vP2kl1aUCz1irofe5dAYXMt+1pH7Z5/VpR56oOz11ptxrgDZWPGN29YASB014f2DlfwYh/N0GsMadK31LQB2DLffVEFZwaUoSYSH3ogT4zFG4jMyvZ+nm1MtEaVk4KwTHrrWGr9/cpuZhG5btS13Hm7PJ6LwTzvYW8BFEz71q0fNtohvuJSLSf3PB0XdHp1uISV6uLnMrRknwqBXwwBrdwxg4+4h9FbzBp0kh1UnCaeIJgBSRUqFGdCiNH1A0h0uRVIGW7bW3suBRr6xhqv6sGofe094mj0AzJ9lE5iKgrlloFvZqg9qzeHQJS8tMzNfclJaWljDaWnnbNdMAbJ8d6qxgv8e3ZWBUSmNgJaaLIxlhO9VSj2QUTKl07tS6lKl1Aql1IqtW7eO4XTtQRhntjR1S+Y244T1UMwrCCqmcYIWy15SuTSZFK0THPpvH92CP/3qHfjv36/Gbau24Y1fuQP/cdOTYh9+3k/98lH3EOOOa+5Yi5UbWtcc6W/kqQvCg6z2yNu+cVfhfi4HHzkBU570BRR0hjeeH7Bu5yAA4A9P7cDcHuuN3pupghpRYpbx/QUSPLfULNd2A8AbzjzU/P1nzz0MADCvxxrJ+b0y47NMMtiKcqllv9H1uwbNaxQb4sqRmuOxigAim4jCEm+9VR1xFyarssVHqhVZbyVXK91QLnZbazm5idui7DUmWjvBXeBVpx8CwFbtHCledXpxMpBSll6dyQb9PwEcBWAZgI0APlu2o9b6Kq31cq318kWLWterGA9wDp2MQS0M8pRLbJdWvIoibaclcqUOPdEwOvQmm7U7YdApkPbYpj6j035iy16xD7eX9zvNIDqBj/z4QVzyr79ruY8oeuYY9OccmWZXnrBkrjDcZa3lojjJNVd2A1PSMELQIv/88meZ9445wKbW8yJJ1qCnXu/xB84x3qorLaRzUXDu8leejFWXp+Gj91xwNB76p5diPkta2T3YRKDSHqGA9KjbVbnQZ3iAf2emQ+ecPL8mzqH3VENjrBtxUloPfSQwSqIWochaGApeP6cpNwFmntQjKRfXCzd1xTWwcHaXeU9B4U+fcxhWXX4xDpjbvlqH481nLS1972WnLMEJS+bi0nOPGtWxJxKjMuha681a61hrnQD4CoAzx3dYo4eooEdFlir5zMBmnE8sqvLa2qEyQVH3x8gpl9SgAz+7fwMu+MzN4xYJpwd5sBmbH/L/3r9B7MMnkoERBLVGg3b5epHZ6XDoptxw4r6eFG87skW3jj0gl/Ju1b1D5tuGBty74oFLolyoKcEh83tMYNc1uht2pfp5mmzdzFS3ml6igTnd1cJWddyYbtg9iDJQ8wZOCVBiEZ8g5rKVgVIKGzKPfsPuwdLVwGgNOn0nLT30sNxDT4UFbNVAST1wPHSR/QoMZKu/FWt2YFYtFO/lygGMEGWlD5QC9p/dhV++71wctv/ovP+JxKgMulJqCfvzlQAeKtt3osGNSJMtldzqeo3I8qqGDw8Cs827jOT5SQWe8RcnGn/1nXuxels/NrEaHmOBy9sXgdu2TgtthmukTJBVLOVn6J65RlmWa5Aeep5ykecLHSNO3HqgpKoGAK589Sn44uuXocY8WzKKZMRndVWKteKB5dl/84hMu2+FtMlDeuyuEpXLLx7cVPp5Wi08trnPvFZEuUhZoKWu/vDUjtLfz2gN4JPZSrEVvVGrBOL4bi/TCjfozEOXtVwkTXPP2nQVOtCIS3ujjhZFZQzG69gTiXZki98BcDuA45RS65RSbwdwpVLqQaXUAwAuAPD+Do+zbRQFOMnocuPYjJNc9/FKaNUrvCh9jqdVknLh+OJvnhiX66DlrMsrcvAJqtOKl8E2VwDc+3aDuGS43ddFsFp0nNI5SaPr3QsvUCmcfMh+ZrviyBJeu/xQvHzZwcJT5pN6oGRiUK1Esz3SQlYkw+Sfc8dWhq5KAKWAO1dbXcJOY9BLZJCOEXKbWBNGa9Bpcj9y0ezSfWpOpqib9Ul/82YVOR26mKzls+02uBgrygz3NLPnwze40Fq/oeDlr3VgLOOCIj62xnTHFCBtxokJslDJ3SqrtcGTidxiPQpK1OfgOGHJHIwH6PevoUsf/olMaFq1VfL3a7cPYFt/Hac7NZ65I+9WCCSPPWfQBe/OVlWxztVycb17V9pGkzTnvF28/tmH4oaHN2efzwp8ZZnDZa3SZGXCkSlChgo8dL7qK2oKTaCEGk6pEeVSNDEBeQeg1KCP0lpF5nlpFcy1Khee6JT+rYwEUCleR6U8BT9QChc/60BDO1ZHGdAtQ5nUtHWl9amHqR+2HSEKOXQKimrpkXFvHcgMeiQ1yEUeumIeOj0sx2f1rA/cb3RBGRd0FYm2hsBdDXC72GnbTmnzBZMAACAASURBVHb1oOz6zvv0TXjVl27L71eiLwcY5eIYdFEGgN1Xt2Z5FOvcdbpp2pQzoFT5MvqFJyzGc7MAbcBUILUwEBN02bKeByOL8OozDjHbobKlCbgyg/+mPviS41oez5UUUsZtV0kpXNfAlakzRs+h55O6XFSZh+4W3VLKUpohC3bqrNNU0fgCpfDcTK/eUw1LDfBoUaY0mm4e+owz6HGSmB8w99Cpdgc9sI0oMVI0MhLVUBkv0tAxSZJL0065WuvVA7b+9Vjk4AONCM+9/EZ87661Zuy81Z2b8s1pFj3KGhbtgozzht1D2MiCeNeueAaNKMHSy67D91c846iMNLbtrWPpZdfh909us/XjHavMuwXRhNpVCdNMUXa8okqO+Yp81lDQ9+bKB+n47n61ivTQ+WTBJ5bhgmOfeY0tdOV2SrLHtq8PJ4dzVwQksZSZp8WTz8LZXaUe7GgNOmXF7teTv6+EtJaL/G74+Hg3KbrNvG4S7cc/b8pY6/K40mhRNkGM82k6jhln0CNmtKMCDp0enkacCM+BIu88sSg9hs5xeQr5Ak4ke3O90pFg+94GNu0Zwqevf4wZEJ3zaAkT6aHzy/rDU9vN9od/+IChAK68/jExocWJxv3PpIGsq255ytZoSTTOzdp1AdJQ0z7EN/M6NUUG3Z1siQag7/XLf3YGfv5X5+Y+x8u30jFcyoVru7f32xK/n33N8JUJv/7nz8bNH3y+U7o2LNwuW0kQXA+dgrPc4y+rPvjF1y/DQftZtQ9HGCj87L1n44fvPqvl+V38/SUn4FN/cjLOOXph6T48UzSXMBTYCSgNigZmP6lykasOuk9u8HQ8UD5BTC+LPuMMeloPQmZzEuUS63xzXtO0IJNPuZ6326GdvAsyshWW7MD/f2rrXty2atuIxh4xT5wXEnMN+g0Pb8aWPUMyKDrMsQcbMX587zrj1f/g7nWGF//1yk3Y0tdancMnKs7/vuwUy/9SZi2BZ2hy+sQNbBZRLhSc5Ak/3JMnuHQYnZ6e9wufdSAOnpc3aGS4ucqiWpElAnpYqzTOpc4vaJDg4oLjD8DShbNkYw02WXAj3YqLdscBWIMuPHROD7F7Mq+3ikVzUs32cYtlfCcMFE45ZB7OYN2X2kFvrYLXPfuwlka1FgZmTG5Kv5sAZgy/43mX1UPvhPNSZtA95TLJoK5CoZOyGzkeOoCsU0y6TUG0hhMUBfL1QtJaLtLwkyEjo/WCz/4f3viVO0Y4dltfvWm2nYbWcYK/+OYKvPGrd4xI5fJP/7sS7//e/bhrzU4MNCJ88Pv34z3fvgfNOMGl37obf/bV1mPl5+JG6qSD5gonxu0wRLtqbVdMbmBTeOjZNmnFeTCwXlBV0k0p/96KZwAAv165ueX1FGVP1sJAGl1OdbBrdAPhrSAoF+ZR95QkGRWhx1HVUHmF7hJOntugMFCY051OCG58p9KiJstYITx0LYtu8aAorzWTxouKtfoqkzq+6/yj8KO/fN64j7csQDzN7PnwKpfpBuLXOH1SywJsgBPoClhJVAVs2DVo63gExT8sCooaD539GNP/R+8+NBnHTBODRnG/y7U7BgQNMtxZSR+/t94053l0U5859tPbB1p+3q23Yl+XRtbNFKWJphoGJkgdO/086wUVGok35qUE2vHQCUXddDhsGj8E5VLmRfMbPJxHzcENRVmW5nAG3ZUnmmqQDvdO77k1xQ+a14Mv/9npJqhYNIbxRjVUuefGbrNsU6ZJ19Cl1SApeeiyi47vyHjLg6LTy6TPGIP+2V8/hpMP3s+kD4dK2cSiMLD1GEL5Y+c1JXgfyLJ61dQ4waVcCGMJitIxh5oxPvazlQBS74ZXjaQVRKiUnDyGsehcGsYpD7ovw/1u+bnI4wPy6f3CoDPZYTW0k2qstZiM6m1SLkV138uMxqyu1koU2jMIrEGpVQLh8XOLkmiNxXO7sHlPfUQPua0qmC8kVnQNRaBJRqn0vvTVo7T4VRGNka1QzSVk+1z4rCWYSKT3Uj43BFHmmMWxtM434MguacISfJY4qxgfFJ0k/Ntvn8Sl37rbdBUKAysXq1UCVkNaKg045UI1N+g9gqvxVeAeuryF8RiComTMEsdO86Qe3npNlqDNW/Sf3LseSy+7Djv6G8Y2UXMPAt2X4R4Y/hl+plZJQnGSsDR6JRKLuCqHrmnx3C6zDxkxMuK0ggJk3RJZbwX4l5efBAA4sCQQSOAGZePudPWyta8uvGhe/+UVpx2Mn733HFzzjue0PK4LMtaVIMh5qe2CPPRZtYrpkVsNlRM0lDQSTYhjCdKPBbO7Ki1VLoq9zhOLZAMOGzyeCHv+7Xc8x/R0JXgd+iQjzoppBcp6s7zErdutnddlPoPVhOZGvOYGRZU1XK7c6abHZEXJkdR2KVKzaK1x6xNpcJXr3/vq0bDlc795+xoAaYDWHA/S2zYe+gjGxieYZqyxeTcpQLSTKWoNckq5WB06v9R6lGB2VwWHzu+1Hn32PRHN0l0NzQqKy+XcDMT9etOA5XAxBWtQ7Oc37h4Sv4+Fs23ws7saYvHcbjyvhbKjCDwj0q010y7IyImJrOLKAnnJXODYxWkWZ6dr/JSBUynpmOTkwx0p3qBZUi7y+ew0zj56Ya641zRjXGaeQU+TE8o5Shl0sV5TmoJczHFWXA+dqSlcyuW3j8o6H6u397c99mZcZNCB3zySBvjSWjPWcEtFicZNj27BB79/v3mNjEYqG6PjSRlk2zVa2GdEE4skwVu+fieAtMaIm/VJHnolVCIoyg1uKiFNH24aDzVE4IWtrHEvDgZyz6/dUEYQKLyCZWqedVTKM5937KJx4U/p58Gdh3Ss7R+DPHROdQ3UYxkIVWxSVgp/+9Lj0VsLcfQB+fT8v3rhMVjGmlGPJ9581uG4+OS0TnroiAnMdqCM58vrumgnKApVPPESXnbKErz17KXjOv7pjhnDoRNirQU3DkivvJd5OZVQdoaXWYJK7EcJSEEgO5NXhglouenvLcde4KHzJXOinVR4x3i+Nasx/pkCnTQ37nEBhz7cQkIadFnzfEd/w2xLykWbtPeU84e5j+61VjJO2K2RU2cF1vr70wxJ2c/TnWyRXecwF0RBUQX89YuOxU/uS1PKF87uwporLjG78e3RwMRoQuVQLu1bdDLos7sr+P9fdTL+7kcPZrX5iyeIUCmcc8xCPPzPRY3GgA+8+Fh84MXHjuQy2gYvWSwnHDnWoqC0hsuhQ6w6XPz7G08fv4E7qFXSuFurWvVTETPOQycOvawB7iynue+2vakx4npYQHLjoeD8lODVqsN84SPpJORWJ0w/zwyk1qJ41c9YOd253ZaGINrj7qfTRg5aw9QuueyHDwhjSioSHngtgvhMPS58nc5tG4Jo42HTXqSddjl/SvDhcQ/AVkHsqoQ26ahSrOHmnt9wHjrtFwaqZcbjWGFb0ynHS23/GJxyodVJovPBerrkEagqO4pylYvsqMSrLXLKhQdPJ1ptwvNTphOmyFc/NogU+MyLFjRLSR9Ft15ztVK8lOf8Z6AgCOei/oqtKg62gls/HEgnhAOyxBCtJUXy/RXrzDa/Lndi4Pdn50BTeNG8ZVwrRCUeuksT8UzdtOFzapDJ0yaD5JYxqGRSUxPrCKVB55OybL2Wj28AbRh0Rf8rce/GG6JzUInHOhzoersqodCvi6Ao7DVPFaldWZs9PjxBuUBSLop9bqId5S+8fhmWHz4fi+d2Db/zFMKMMOhuV5tQyS7v3LjzwJJrDLi3LROLeIkA6WkVaZKHoryuuh0UKRLW7xzE/F4bnBtinvQClrHI9eDNWHLU7ggoVR+AUU0MB87XSw89ye1HxndvPcJ/3fKUGDd5YO5EFzoerKFcmklu9VTOoY+AcmHnHYmufKQoU7mM5Ixk5GoVJQpyubJFuuZO6stHgpYeuuHQ7cSUcugsKKrs5DTR1MdLTzoQP3j386bM5NguZgSHzg1orHWu0p6gXEo89CBwJY2McgkDweVxyqWotG0f83pH4qEXGf/t/Q1BCXBq5PTD5uHB9btTSaDQfyeIEjt+11v9AqvZXtRLs3BscbGHXqRDp/v9nTvXmtfJIyeO1KWiKoGSSThEuURxyq+z76q3Jtut8e3jD5wLIE35bwVLoXXWo+XNo11FzvtfdKyRYrYCGfFKEAgPXUjmlf2ep4g9d0rc2tcDFsENA6mGERw6WNPvjo505mBaG/ShZtq5ZA9rz0X1IPhDyn9Ys0oCamlDhBLKxeH8+I+zKH2agoRAPpOyFcoCqLz92BBTmJBxr4WBaCLcjLVI1nG91TOXLjBSSJf6cNGMk1yNFlK5dGU1yznixNIl/N40WJIXjZHDNXjcQ3cVIjTBBSrvBS5dOAuPf+KiYSsYujb8JScuxotOWNzyM6MBjSPHoSuF973omPaOkTkN1TBwOhOVe8BTAWUeOo9JKSfeJSgXNtlON095sjCtDfrx//grvPjExcKzo65EdGHuQ8+9OzegJpQtgTTulkOXBr1ouc4b+o6EcikLoG7vb5gmDHw1QgFHpRQa7PU12/txFO8m4wyBe0HcoD+6aY/xcAkv/Oz/Ye2OAZFyTR56V9Y4hCPR2qhQeNs0khzS5OrKJUPXQw+tDr0SKEE1UUq+G/ymr6yd7uxu8PSqNy8f9jOjAbW7c69vJF40lUwIFDC3u5gyBOzXPFUMeqkOnX09vGMRUEC5mM93bJgzCtOeQ7/h4c341UrbkzHWstSmG4yqhArPXpomELleDffkq5XioKhSeS27C05jjCgo6uzLS8xSTW+e/k5GzuXe99ajUs/7RScc4DQBsfs98Mzu3P5rdwzkxkYcenc1zJ17qBljVlcl1zDZVa+4k1d/PS6Umg4104qNFC+Y220zEN3JdSSGzHLtnUWN/Q7dcrDt4sylaTXEPzr1IBy5aDaufPUp+PX7z5MecKDMxUwV49cyU5SpSMokxinlYr9rj+Ex7Q26C601Qsah8yg6kHreJx+cJlW4RaZEuj/30FmJgDBQYtlb5KFznntkskVpXp5zhC1rSp4L91SHStL2681YGHR+1LJaLkDea+aNLIp06F3VvIe+ta+OUNkOTkBatjVHuTgTTpRIzS99fymHrnDwvLSpxOH7z2KFncqNxlSBoVxyOvT2j3HcgXOw6vKLcd6xiwCkvVGPXTwnF2SdakHR8loudh935SKVQBBUp8fwmLYGnas4Lj3vSAApt2ool7A4GBUGlnKoR4nxgpuxhlvnxX5G6tDLmvMSuEEfmWxRGjkewKVVAT82GXd3BEPNBI3Y7seDoomWafdliUoARNYpr3TY37CKFZcL7xuKEAbKGLLZXRVUwnzCkPu5OLFZlQCjXJoJKkFgAoDuimu06fTGQ++wi07fW8iuARi5aqPISLv3YarJFsOg+HlyC5OVUWRuAxqP4TFtDTo3PuQlU1cipWzWZ6jyNSVIKTDYiPHSk1I1RNqMoTiQGipZkF92b7fbp2Yd53mtk5HJFuW+3QUd6EUHHzLozq99qBmL/fhKJNHFmaJF5+cBT67cGaiXc+j1KBb01ZzuCiqBYsXR0rG6q4HE6ScpVS72weZqmFxT4RE99dkxOky6dLGgaJmXOlq49VEIU8ZD5+oVJ9jJt8uabpdN3B7lmLYGnRuf/7hpFYDUSGiNTIeeUS6ORxcGzKA3Y/Nj4t11gPLEorToULEkkmiRQVHfO8Gm3UNYetl1uGftzravCZBNEEi6RkY8UCwoWnCchzfsMX9zo7tzoCGLczHDOsfhvfnn9tYjE5Dr5yoX1sMVsL1ayXDP7qqIGi1l3hhl+BJoP62lMQwDhTC0xvjxzbbw2Kg49A576KLV3ShXE2Vw6QkbFB3zoccFZe333O+pVT14W09/ilzUFMe0NehFRaWacWIaXFTZg1RxmlV0s2445DlEsZbKFod+4Rlr0ojnjbvw0GONa+54GgDw7T9YXXYRXIkjr1lC2a6Uqj+3p2omDtcm8U5BgKw3vnuwmWsTZ7adAOeKp+0EFMXaBDoHGeUSxRrLDrGFnoaMQc8ol8xDNxx6pdgbSxJdqEMH0gee7n+V1QFPNPDQehvInYpOHK8PNN7SQlm6XRnjN1Uol0rBigsop8lohcthyxlMjWua6pi2Bn39znxChtbApt1DaWIRo0j4D78SBKa1WL1pDXojTlBjypaq4NADU/MlTrSzlMzTIi6H/q+/fVK8z/HB79+PpZddhz1DzZyHXtQl/n+ySWFud9Vy6M5v/WM/WymMOOe/U1oK7L18+7cixFqb1QxNpg+t340VT+8UEwHFMGhs63cOIlDWoJd5WkpJXpmXa+ArJM6ha61xySm2ccNIeGnac7gyu2PF41vSFcSdq3eI+i3jTbkwkcuUqT8iPXRu0O19p/9vu+wFuOYvnps7Bn09w3V18kgxbe/SP/zkocLX1+8aFB5ioBTmsMJVlVDhklOW4FWnH4wPX3S8oTKaceJozyWHTrhz9Q7hvQsPPSzw0BONeZnk8IiFvbnx/uDutB7LXat35JJ0ZC9T+ZD2VEMzcbzvhccgDBTedvYR5v0tfbZLvUgy0tKIFTVoLkK9Gee8JCob4I47VAoPrNttxtHNxlrWjzOlxuzffPJLGFdeYZmFiQaevdQqgUZiyJbunzYz6bShuPTcNGD/6VefMu6c8MLZts4IL+ncwVahI0JZtnbRCuKgeT2FNXWmmnJnqmOKfPUjBzc+pzhLtVApoyMPAyWa41Yy2eHnXrsMi+d2ozv7oSXaqd/iqFwItUooGl4UUS4DgnJJcMZh87Nzl9/uRBdXIHzX+UcBAP6Y1eymc9F5TjtsPlZdfjE+dOFx5n0ub+QGPXHrobfpobs6cY5GlOSaTpx4UJqg9C8vPwmzWTJMK0VDGeXy0pMWi0YRrTrDt4u3nXMEPvUnJ+NPzjik/Q+NAicfsh/WXHEJXrP80HGnXHi7NFfnPRVQ1ocAaD8DlCYpb9Dbw7Q16FJDLg0hTyxydejuD4MXO2pVD51Qz2qLmM8U8OlDTemh04+2VTOJwWac49ArYdoU99YPXYAXO2npNaYwobHy6+RjaLCa4m7Ncj4xNlrUbl+zvb/0oRpoRrLGiFL4i8wzvejkJZgtsnOLf3IKKNSh0/GMyiVUsmTDKJN1wkDhdc8+bEKX8iPpI9oOeIyF1xeaOga9eILmGI7yonenxhVNfUxfg85sn5utGAYyQ0/WaJGXLHnqEsolUPjm285k7xX/UMs49KJtFwP1qNBDB4BDF/TmHgjppQa51zjtQxx6TzVEkmih7DBNp1ngsnB8jbyH/jdZk4SBeizKCYSBwnnHLsKaKy7BwtldpSsfDuV46MKgs6C0q+eWtFTp8KcEZELN2I/H68LLks5T40ZUC+hIQr1plVKtoL1FHxGG/Vkppf5bKbVFKfUQe22BUuoGpdQT2f/zWx2jE2jVIJlz6G41N/fHXpb1Keu6KFuqVhdLFQFOuRRXI2xl0PfWo9zEVDZxAJIvJiPJPVQ+qdQzeWNPNUw9dIdyUQrorgQtOfRmnOQ8v3nZPelvROKBde+xaAdYQjsFblC0UuKhB46HXkKNTUWMN4celPyup8pt4L8Jd/VEai0e3yrCla8+GccfOAcLWAlpj3K04yd8A4Dby+oyADdqrY8BcGP294Ti/OPSNOiFs2uIYo1nHWyLSnHKxU0Pdz1EbjhELRdHblbkEbuftzp0lqzDapO7Ew9Pwe+vx4U1wu055bjdeu0uijj07ixVP3aCotUgMC23ytCMkzxdxfp+uh566XU49//vLz4BQL7QFp/AePXM0AmelrU5m4ooq5Q4Hhhvjft4oBWd9YlXnIyXLzsIy5e29gVfcPxi/Oqvzxu21aNHimHvktb6FgA7nJdfDuDqbPtqAK8Y53ENi8Vz0oDQyQfvhzjROGyBVZDwoCh0PkmIox2DzjMVNaRRKqJcHtvEk3oS3Jg1jnabQXBOfaAR5dLh+cThPqRBCT3x2uVpkE9klJrmyiHiRDa/qEdpDZtqmHroT27Zi18+uBFaS3lmM9a5e1crWVK7xqpSMjG96/yjcPrh87LPSBqiJugvJVQuZRz6VPFMy1DWXGU8EATAkQtT5c5UlC0CtsAcAByxcBa++PrTxAqXcM1fPAeffOWzcq97DI/Rls9drLXemG1vAlBaSFopdSmASwHgsMMOG+Xp8iBvNlBpnZCeqnxYTBs0rVt6ul0ldVlaecC1kqBoUUXEhzda4+566HW239561NJDB9Ja7v2NGC87ZYngyHk3+JeceCCuXbFOUi6Z591TC015BEIj87zJQ3/R5/4PAPDDdz8PS+Z145kdVu/vGopaSfzBdaZKg52BVDuI8rIlmbqV0KHQxlk50kn0siDmeHfgEX06p6gze/37z8Pa7QPD7ve8oxbieUctHHY/jzzG/NXr1N0rJYe11ldprZdrrZcvWrRorKcziFlWXJxoUV/F7VPopv5zdBd42IBreAJjeLTWTv1mu99+PVWcfpjNmqyFNiEJyPcMFQWv6hGacWK8rKKx/u7DL8Af/u6F+MLrlgkZ3zzGLxKnLIKigkNPRHGuejNBdzVMDTpbMWztq+OAOVYWR+f61tttcLhIg180bjlROlQWK75UxgmHQWCv16G/3C5AUxl8lTXeXjSPM0zV+3DAnG4sZ3kDHuOP0Rr0zUqpJQCQ/b9l/IbUHsjLDANbh4WMSqBshF1r2dTCVbmUdSlyg3Ihp1xKarkESmHJfj0AbN10/n7OQ2ecdX8jzrjo8kqO82fVcOB+3WlLtmw8+8+SwSL6jJAtxtagJ0753CHKltXAzx/YaF5/1//cjTjRwvsPAlUYBAacZiGOQZHqFbkfr6YXlhi8MAAWZKufXYPN0mzTMgXNVMR400NKYcobdI/OY7QG/WcA3pJtvwXAT8dnOO2DUy6Ujs8LIZGHTQ0aCK0eei6zErpqp5a1UMMIntt6ltXMq0xaqFxcD32gETkt8srHSp64W6mOJhtu0B/ekGZtmrLBzBMfbMaoVQI8ta0/dw6ttfS8law3UyuLOeSCosXeexrsTLcD5fTcZL/MMAgwP5u43IxejqLg8FTFeFMuSsma/R77Jobl0JVS3wHwfAALlVLrAHwMwBUArlVKvR3A0wBe28lBFoG8XaXSxhBhaCv8BYxDd9HqoefG2a15zgOJrZrf0vGJ6623KE/Lufbdg02s3LAnFwwsA3mwPa5BN+Vp7blWbU2NNXnXvLnEYDMuvVfb+xs56olfgfDQ+UqlhSKn6ujGuVfp9p2ktnuV7H8gvfdl92WqqDvaQScCl7zxh8e+iWENutb6DSVvvXCcxzIikOers/re1SBg2aHlmWll3stZR+5fyo2HgUKiiwOmssa15XcrQepxysJYUuVCxr4SKKzOPGTOY7fytMioddekQafPFGnK6Zr4e1qX36t1OweleiiQq4wylYtrrMoyJINAGU9cOSoXKsEbJ2md9KG6TUSZCRK28fbQgalJufzbG07DwfN7JnsY+wymbZNo8napNgnvfBIqZYKkvI0bUFxPZdXlF0NBejacK049xPTNWiUo1dcGnHLJeO5WDSTovdndFexlDSRajdWciwy6Y4zJ0Bdpysu6BbUyAHN7pHqIa9hHFxSVXrjh0J1x8ImyEsh66tOJKy/DcBmSo4HNpp069+ePTj1o+J08xg3T1qCTt0t1XKqhpVmCQJm06OGkgGWv8UQZV3ZXWo+Ee+ihyqXT06rin/53JfrrES4+OS39Orurgl0DzYIDFp4mPT4Z9BIOvchDp/vj1pQJVNYgoUCrNK+nxvZTgjLhkx5vqu16n+WyRasvP3RBb6khCpT9bhf01kqzTacTymiuMWEKeugeE4tp+2SQTbK1SDjlomxZ3MyIHrkolQOW0QsuXC6bNzku43ADZQ1t2gezmEP/+u/X4NoV68x7POHk3994mtnmFQxz5wrsioGDvNco0Tj6gNnymqj2eyTb7bmG9IA5tizrCUvmiP3OPnp/87csm1BOuZQlFimlcMTC2XjfC4/Bx/7opNw4aIKpBAp/csYh+PCFx+MvLzh6RnjonaBcKM4znYLDHuOLae+hkydaDV2VS2bYsvd/8K7noW+owAsugauJJpXF2845ogXlYrMYq2Gars499LzKJW/QqbP7cLATh6sokZTGK5YdhJ/ctwEAp1xSpUgzpnZ29jNffP0yHLt4Di764q0AgJ5aBUcunIWntvWLFHwAmNVVXKnSNczlVRTTfd+fFfn6/ZPbCq+VVEvvfv5Rhdd8y99eIOSV+ypMPXTvoe+zmL4eOtVHiW0BfKNyUbbtHL2/YFYNh+8/q+BIw6MSBJjdVcGaKy7B2885IuchkkcbBDawVwnLPXQCVZzjhf2p1OyyQ+ehFXgHHzlW7gE7bewyimTlhj0ik5Qf4/TD5gt+t7tqOWvX8+4p89Bdg/v41sL3Wo2dI7efM6Eetn+vmXCnOl6x7CCzWhwPUKkHwBas8/Z838W0dWvI2yUPvcK47TRwmak9kjyXPFK4dsblcOkBUrAeeip1tJQQKTY4higlPzOM1FD5wY+/BEkBn81Bxq9VIaxAyUSg3lq+bob7ma5KAFn1MCwszwvIwGUrg76j32bLlimEABm3AGz6ca4w2TSmFD7/umUtq26OFFe++lRc+epTAcD8ZrxB33cxrQz6n3/9Tiyc3YXPvOZU81CQ3jot2pTxyqFCb+b1cj64Hdz7jy/OBRRdw+N66DzbkYxNNQyER95dCXMeOlFAZGiJehmupChgjaZrPEWVyEB66GUG3TXMQcDGXQ2Evt/Fs5fOx11rdsqgaE62aLfdOvMcRYWais47nftLKqU6FgM4cG4XHtmYD5R77DuYVgb95sfSpftnXnOqMY6NTOfNvbZqGODgeT34wuuW4dxjRlbkp52le5lB5zr0fGekIKdD357VeSGjQeZ6iwAAEp1JREFUOxIemOvdi16n8fAmCEU9G4GUyyZUKwEqWk5EdMzeAkNhJ9Hy4lyihonD8XO4Uj4K8rkGfCrJ8qYSPv+6ZbjxkS04atHs4Xf2mJGYVgad43dPpAG07dlyXnbFSQ3AK047uCPndvXhPH2dDKxbbKqrEiKKNXYy+uFrv1sNgFEuozDooVubxlGR9NTs++1QLtVQQbHQSlc1MBNW0fj2Zo2iZfKQHBO3v6KWyzAeOq3CXIlfWS2XfR3zemsd75HqMbUxbdeu1NWe9NuVwDZN3ra3Xvq5keDUQ+fhJSfmKwO7Hro16I46hu1GPUBP+5cbcscjioeX0x0OdlUgX29VH7xsKR4oZRpN1MJAGMzuSoj1u9ISurNqeYP+0Pq0PPDmviE7Bue8b3ruUrPdqmVct8OhE0OVl2ZO25+th0dHMWOejEqgcOGzDgQg29ONBT99z9m46s3Lc6+7QVHLobOyvTrf2cjl0AHg/GMXmddH4l2VBQbdTkvHH2g7OZVlJ4aBwjvOPRJrrrgkK/LEVhbVwJQ8beUZ89LALiVyDqO9WjV5cD30Yw4opg6mc1DUw6OTmLaUi4tKGBRmOnbmXGUculurxO7TVQkKJxqlUhkhkBboan8MWXlg53XXQ5d0Srl+vgwieSibEK5951m5YDMvCeBSKZwyWThHZp5yuCoXGq8bpPYG3cOjGDPKQzc63A63CHcNCv0VBLKxhls3PYo1Fs7OB13ve2YXgPLEmiKQt6ydScLtLVnWp/O9FxxttltlLXZVAnN9ZGDPPGIBlmaNOJbslzbB4Hr7XKYomwB7WvTVdFcQlHB0+P694nUfFPXwKMbMMehC39zZc7kyRs6hl3XTqYYBHt64B9v2NnDJyUtMWj+3xyMpqVpafoDVRwlUeSu9ow5gnZFanJaX+C2iXMjo8ozYXPlcJ1Brzuv8+lzK5cUnLsaaKy7JyTinU5lcD4+JxIwx6NyQTvTjzvtitgqKEnpqIf72pccBkE0uRmKnDOVSQDPRysCtMc4pl1rYXn/L4xbbWi5FKx/yqrmHnlvBlFyYqxbqRAVCD499CdOGQ+fUgkszALLxwUQnnpD9UrBetoKU73GTtmrrXqzbmXZS+sNTO+w+IzHoLPiaey9UaMRSFw/I+9LL6rC0Whns19s6yYna+wUq5cqp6XQ76HFklC6H7uHhMTJMmyeIp0sXpU6HgcKbz1qKd5xzBN55/pETOTTZdScophSeZt3O7127C0dkHPScroqhMrgiZTiQDdYF/bl55xpurDn90tuCyx4JLjhuEd55/pH46MtOFLV02oErUyzLFC3DrBJdvYfHvopp46FzFYXboAFIpYQ9tRD/8LITJ3JYACylwLvYA+WFqO78yAsxr7eGWhjgLy84Gr21EP958yp8IOOj2zonWnjoxqArobQRfT+z6pSNKCmkXH7zgfPb8rQrYYC/u+gEsw3EbXvori5+JMHOn733bBw4t7vt/T089gVMG4PODVdRN57JVD7QmXmT6HTbGtCD5/fgiS178dU3L8cBmSH6p5c/y7z/oQuPH9k5s5MW1XmiMQRK8tQiS1MpdGUGvYihcmuptwNej74djKXmyCmHtK5G6eGxL2JaUi5DLJBImMx0cJJL5igXNqQTl6R0ysIRFgsrA60K/l97dx9kV13fcfz92WzIM3kiRAiJSyAh0EASEmhkgkJ4aLXMQDtUpQ9AS0lpxUEqdpzq6NCnqbWtMwzaEmkrtqIDolYtg4ADA7ZqSZBHgdpCFChCIAobAoHsfvvH+Z27Z+/u3n26D+fe/bxmdu65557zu7+7Z/d7fvd3fuf7G67L5cWUI6Y6WFdnRMwDar0mLM6PwVjHiVdPcG1mk9M2LfRil8vrKZd33mUArb0dPK/PzOldg4JjV6G1fuVZq3n76iWj5jmvp9fe7BvUWi4G2q7CvKv1mj2nkjd9gl0uZjY5bdNC7y+00POcLcVhbq28ezDPYjhnRnelRaxCnaYpm3Fn88rFI5QwfvlMTLU+d9ZCH2kM+ECu9NG6SI55SzZ08S3za/dZ5ykRxnqCcAvdrL7apoVeHOfc+3qW4W/ujO7KcivnmfzshZu487HnWXrwzKqsg+Mb9TEeef6XWt9M9h/oH/G9sy6X4SeuqHbZO45i88rFbHzrwprb5V06Y+3CqR7lAnD3VacNGlJpZmPXNgG9OI3Z3v2DJ4aA1l4UPXzBLC58W8+QelSGMzbge9BYWuivv9k34omumCt9tBPOtC6NGswBZqbjMdbPO9wNR3lKATMbv7YJ6B/68kOV5bxVXpywoToDYqt0FYYMdjewhX7ehmXc+vBPuewdRw157bRjlnD3E7vZf6B/xNbyoIuidfrVXXHG0Xz6rv8ddoTMVWev5mcp1fFH3nUsu156tT5vamYVbRPQi/KAPqiF3uQuly9t2zzst4LhLorWaxRJ0YLZB3HTZW8b9rX3bz06C+hv9o3Ynz0tDVusZ/22rlnK1jVD88cDXL51VWX50rc398Yvs6miLQN6PktOccKFZrfQR7rAWQzylRZ6k7uD8pZ3rRZ6V9fArfZOdmXWGcrRTzFOlcmVa0yW0CqVyS4YCOTNrlp+M1HE0JPJsgWzKq9VLmKW5HdnZpMzqRa6pF1AL9AHHIiIodP7NMDeyiiXgS6Xskx6MNwkyM0OmPn79UcM+b3kX2T6IxzQzTpMPbpcTo+Isc/MUAe9qctl4ezC7DclDErFnCrNlAfoYGiwzk8yff0x7lv1zazc2qbLZd6MbtYuy26fz1voxYBeFpU0AF0DaQCaHS4HUuvGkGB9/UWb+K3NK+hZPKdyq77nXDbrDJP9Vw7gdkk7JW0bbgNJ2yTtkLRj9+7dw20yqv0H+ujdf6CSoCu/KLqkTnlR6mkgr0tjRreMRVely2UguJ+x5lAAjj50Hn9+3vF0danpeePNrLEm2+WyJSKelXQocIekxyPinuIGEbEd2A6wadOmCU3j/MprWQA/qWcRj/7fK5VhiycduWgydW+I/KQjVBlK2aS5qysG5WzpEvd86HQWDzOXaT6L0nDpiM2s/UwqoEfEs+nxBUlfBU4G7qm91/jlLfJ8hEb+fO6Mbq48czVbVh1S77ecsDygd3UNtNCHy1neSNXdLCuqJlnOTU+B/82+oemIzaz9TDigS5oDdEVEb1o+G/jTutWsIB+muGhO1sp8+bXs+azp07jizFUj7tcKxVS6rRo9MnAxtvZ2eZeLA7pZZ5hMC30p8NU0gqMbuDEibqtLrarkF0GLAX16mnGnbPoLzfGBgN7cJnrehz5zlCndprvLxayjTDigR8STwLo61mVElWGKKaD39QdzZpbzJteexVlyqTOPXTow72fTu1yyx3XL59fcrttdLmYdpZxRsUpvZZjiwAz0sw8qZ9V7DpnDgx87m4NndfOF7/8EaP5F0Xkzp3Pj7/0ia4+oHdDfSIH8II92MesI5YyKVfI+9LmFW/1nl3jG9/npxJO3gPe8+kbT63DK0aNfKF6+MLtYetzhBze6OmbWBG0R0H/80j5mHzRt0I1Es0oc0HN5F1FZnXPCYRyxcFZTp8Uzs8Zpi4B+7vrDWbts/qDb++eUtMul6KglQ/OCl4kkNqwYfeIKM2sPbdF5umHFQs7feAQA7zs9m9ChHVroczyVmpk1UVsE9KJ8KF4ZhyxWmzHKsEEzs3oqf1Sskk+K3A4jM9rhpGNmnaPtIs5P9uwDYHfv/hbXZHTtcNIxs87RdhHnph1PA/Bfu/a0uCajm97keU7NbGpru4D+x790DAAfKFkOl+HkE1tcsuXIFtfEzKYCRRPvS9+0aVPs2LFj0uW8caDf/dNmNmVI2jmWKT7bMio6mJuZDeXIaGbWIRzQzcw6hAO6mVmHcEA3M+sQDuhmZh3CAd3MrEM4oJuZdYim3lgkqRd4YoK7HwK8WMfqFM0HXm5Q2Y0uvwxlT+TYlKHeZSu7HuXXOhbt+nvplLInE8OOiYh5o24VEU37AXa0Yt8xlL29wZ+7YeWXoeyJHJsy1LtsZdej/FrHol1/L51SdjPin7tcMt9o4/JddueU3ejyXXbnlD2sZne57Igx5COo977WWD425eFjUV7NiH/NbqFvb9G+1lg+NuXhY1FeDY9/TW2hm5lZ47gP3cysQzigm5l1iFIEdEkh6V8Lz7sl7Zb0zVbWywZI2tvqOthQox0XSXdL8kXSJpB0Xopla1pVh1IEdOBVYK2kWen5WcCzLayPmdl4XQB8Jz22RFkCOsCtwK+k5QuAL+YvSDpZ0ncl/UDSf0o6Jq2/R9L6wnbfkbSuqbWeQiSdVvzWJOlaSRen5V2SrpZ0v6SHW9lKmWpqHRdrDklzgS3AJcB707pa/y/vkvS4pJ2SrqlXb0SZAvqXgPdKmgmcAHy/8NrjwKkRsQH4GPCXaf0/AhcDSFoNzIyIB5tWY6v2YkScCPw9cFWrK2PWROcCt0XEfwMvSdo40oYpxl0HvDMiNgJL6lWJ0gT0iHgI6CFrnd9a9fJ84GZJjwCfAn4hrb8ZOEfSdOB3gc81pbI2kq+kx51kx9JsqriArFFKeqzV7bIGeDIinkrPv1hj23HprldBdfJ14G+A04DFhfV/BtwVEb8qqQe4GyAi9km6g+zs+G5gxLOi1cUBBjcCZla9vj899lG+v61ONtpxsQaStAjYChwvKYBpQAD/RpOPS2la6Mk/AVdHxMNV6+czcJH04qrXrgeuAe6LiJ81tnpT3o+B4yTNkLQAOKPVFTLAx6XVzgf+JSLeGhE9EbEceIosvg53XJ4AVqbGKcB76lWRUrWiIuIZsuBc7a+BGyR9FPj3qn12SnoF+OcmVHFKktQN7I+IpyXdBDxC9gf7g9bWbGrzcSmNC4BPVK27hezi6JDjEhGvSfpD4DZJrwL31asibX/rv6TDybpg1kREf4ur05HSyKHPRsTJra6LDfBxaV+S5kbEXkkCPg38KCI+Ndlyy9blMi6SLiQbDfMRB/PGkHQZ2UWbj7a6LjbAx6XtXSrpAeBRsi7l6+pRaNu30M3MLNPWLXQzMxvQsoAuabmkuyT9UNKjkq5I6xdJukPSj9LjwrRe6Y6q/5H0kKQTC2WtkHS7pMdSeT2t+VRmZq3Tyhb6AeCDEXEcsBl4n6TjgA8D346IVcC303OAdwKr0s82srsRc58HPhkRxwInAy805yOYmZVHywJ6RDwXEfen5V7gMWAZ2U1CN6TNbgDOS8vnAp+PzPeABZIOSyeB7oi4I5W1NyL2NfOzmJmVQSn60FMXyQayEStLI+K59NJPgaVpeRnwdGG3Z9K61cDPJX0lJe/6pKRpTam4mVmJtDygpyxltwAfiIhXiq9FNgRntGE43cCpZMmgTgJWMvRuUjOzjtfSgJ6Sat0CfCEi8sROz0s6LL1+GAP94c8Cywu7H5HWPQM8EBFPRsQB4GvAiZiZTTGtHOUisvS3j0XE3xVe+jpwUVq+iCzBTb7+wjTaZTPwcuqauY+sPz1PQbkV+GHDP4CZWcm07MYiSVuAe4GHgfwuzz8h60e/CVhBlnTo3RGxJ50ArgV+GdgH/E5E7EhlnQX8LSCy1K3bIuKNJn4cM7OW852iZmYdouUXRc3MrD4c0M3MOoQDuplZh3BANzPrEA7oZmYdwgHd2oakPkkPpOycD0r6oKSaf8OSeiT9xijbHJ/KfUDSHklPpeU7JR0u6cv1/SRmjeFhi9Y2JO2NiLlp+VDgRuA/IuLjNfY5DbgqIs4Z43t8DvhmRDiIW9txC93aUkS8QJZG+fJ093CPpHsl3Z9+Tkmb/hVwampxXylpWkrgdl/Kq//7td4nlftIWr5Y0tdSnv5dki6X9EcpKdz3JC1K2x0l6TZJO1Od1jTyd2GWc0C3thURTwLTgEPJcv6cFREnAu8BrkmbfRi4NyLWp0l4LyFLG3ESWTK3SyUdOY63XQv8Wtr3L4B9EbEB+C5wYdpmO/D+iNhIljTuM5P4mGZj1t3qCpjVyXTgWknrgT6ytMrDORs4QdL56fl8sklTnhrj+9yV8vf3SnoZ+EZa/3Aqdy5wCnBzlq0CgBnj+iRmE+SAbm1L0kqy4P0C8HHgeWAd2TfP10fajaz1/K0Jvu3+wnJ/4Xk/2f9TF/DziFg/wfLNJsxdLtaWUnbNfwCuTXnz5wPPRUQ/8NtkXTEAvcC8wq7fAv4gpW5G0mpJc+pVr5TT/ylJv57Kl6R19SrfrBYHdGsns/Jhi8CdwO3A1em1zwAXSXoQWAO8mtY/BPSlYY5XAteTpVe+P13svI76f1P9TeCSVJdHyaZPNGs4D1s0M+sQbqGbmXUIB3Qzsw7hgG5m1iEc0M3MOoQDuplZh3BANzPrEA7oZmYd4v8BrTt7A+891kUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb4605762e8>"
+       "<matplotlib.figure.Figure at 0x7f6a48d3a828>"
       ]
      },
      "metadata": {},
@@ -1031,7 +1031,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Create a new data-frame with the time-shifted data."
+    "Create a new data-frame with the time-shifted data.\n",
+    "\n",
+    "**Note the negative time-shift!**"
    ]
   },
   {
@@ -1040,14 +1042,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_targets = df[target_city][target_names].shift(shift_steps)"
+    "df_targets = df[target_city][target_names].shift(-shift_steps)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The time-shifted data-frame has the same length as the original data-frame, but the first observations are `NaN` (not a number) because the data is not available, as it would have to be taken from before the beginning of the original data-set."
+    "**WARNING!** You should double-check that you have shifted the data in the right direction! We want to predict the future, not the past!\n",
+    "\n",
+    "The shifted data-frame is confusing because Pandas keeps the original time-stamps even though we have shifted the data. You can check the time-shift is correct by comparing the original and time-shifted data-frames.\n",
+    "\n",
+    "This is the first `shift_steps + 5` rows of the original data-frame:"
    ]
   },
   {
@@ -1090,46 +1096,214 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1980-03-01 11:00:00</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.142857</td>\n",
+       "      <td>12.585714</td>\n",
+       "      <td>1011.066667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1980-03-01 12:00:00</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>11.300000</td>\n",
+       "      <td>1011.200000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1980-03-01 13:00:00</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>12.118182</td>\n",
+       "      <td>1011.300000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1980-03-01 14:00:00</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.857143</td>\n",
+       "      <td>12.742857</td>\n",
+       "      <td>1011.400000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1980-03-01 15:00:00</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>12.400000</td>\n",
+       "      <td>1011.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 16:00:00</th>\n",
+       "      <td>4.909091</td>\n",
+       "      <td>12.618182</td>\n",
+       "      <td>1011.688889</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 17:00:00</th>\n",
+       "      <td>3.953488</td>\n",
+       "      <td>12.646512</td>\n",
+       "      <td>1011.877778</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 18:00:00</th>\n",
+       "      <td>3.674419</td>\n",
+       "      <td>11.725581</td>\n",
+       "      <td>1012.066667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 19:00:00</th>\n",
+       "      <td>3.395349</td>\n",
+       "      <td>10.804651</td>\n",
+       "      <td>1012.255556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 20:00:00</th>\n",
+       "      <td>3.116279</td>\n",
+       "      <td>9.883721</td>\n",
+       "      <td>1012.444444</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 21:00:00</th>\n",
+       "      <td>2.837209</td>\n",
+       "      <td>8.962791</td>\n",
+       "      <td>1012.633333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 22:00:00</th>\n",
+       "      <td>2.558140</td>\n",
+       "      <td>8.041860</td>\n",
+       "      <td>1012.822222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 23:00:00</th>\n",
+       "      <td>2.279070</td>\n",
+       "      <td>7.120930</td>\n",
+       "      <td>1013.011111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 00:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>6.200000</td>\n",
+       "      <td>1013.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 01:00:00</th>\n",
+       "      <td>2.076923</td>\n",
+       "      <td>7.738462</td>\n",
+       "      <td>1012.366667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 02:00:00</th>\n",
+       "      <td>2.538462</td>\n",
+       "      <td>7.969231</td>\n",
+       "      <td>1011.533333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 03:00:00</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>8.200000</td>\n",
+       "      <td>1010.700000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 04:00:00</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>7.927273</td>\n",
+       "      <td>1010.100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 05:00:00</th>\n",
+       "      <td>2.916667</td>\n",
+       "      <td>7.658333</td>\n",
+       "      <td>1009.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 06:00:00</th>\n",
+       "      <td>2.416667</td>\n",
+       "      <td>7.408333</td>\n",
+       "      <td>1008.900000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 07:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>7.100000</td>\n",
+       "      <td>1008.300000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 08:00:00</th>\n",
+       "      <td>2.142857</td>\n",
+       "      <td>6.542857</td>\n",
+       "      <td>1007.700000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 09:00:00</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>6.200000</td>\n",
+       "      <td>1007.100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 10:00:00</th>\n",
+       "      <td>2.833333</td>\n",
+       "      <td>8.350000</td>\n",
+       "      <td>1006.466667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 11:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>6.828571</td>\n",
+       "      <td>1005.833333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 12:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>8.200000</td>\n",
+       "      <td>1005.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 13:00:00</th>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>9.216667</td>\n",
+       "      <td>1004.766667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 14:00:00</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>11.885714</td>\n",
+       "      <td>1004.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-02 15:00:00</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>12.400000</td>\n",
+       "      <td>1003.900000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                     Temp  WindSpeed  Pressure\n",
-       "DateTime                                      \n",
-       "1980-03-01 11:00:00   NaN        NaN       NaN\n",
-       "1980-03-01 12:00:00   NaN        NaN       NaN\n",
-       "1980-03-01 13:00:00   NaN        NaN       NaN\n",
-       "1980-03-01 14:00:00   NaN        NaN       NaN\n",
-       "1980-03-01 15:00:00   NaN        NaN       NaN"
+       "                         Temp  WindSpeed     Pressure\n",
+       "DateTime                                             \n",
+       "1980-03-01 11:00:00  6.142857  12.585714  1011.066667\n",
+       "1980-03-01 12:00:00  7.000000  11.300000  1011.200000\n",
+       "1980-03-01 13:00:00  7.000000  12.118182  1011.300000\n",
+       "1980-03-01 14:00:00  6.857143  12.742857  1011.400000\n",
+       "1980-03-01 15:00:00  6.000000  12.400000  1011.500000\n",
+       "1980-03-01 16:00:00  4.909091  12.618182  1011.688889\n",
+       "1980-03-01 17:00:00  3.953488  12.646512  1011.877778\n",
+       "1980-03-01 18:00:00  3.674419  11.725581  1012.066667\n",
+       "1980-03-01 19:00:00  3.395349  10.804651  1012.255556\n",
+       "1980-03-01 20:00:00  3.116279   9.883721  1012.444444\n",
+       "1980-03-01 21:00:00  2.837209   8.962791  1012.633333\n",
+       "1980-03-01 22:00:00  2.558140   8.041860  1012.822222\n",
+       "1980-03-01 23:00:00  2.279070   7.120930  1013.011111\n",
+       "1980-03-02 00:00:00  2.000000   6.200000  1013.200000\n",
+       "1980-03-02 01:00:00  2.076923   7.738462  1012.366667\n",
+       "1980-03-02 02:00:00  2.538462   7.969231  1011.533333\n",
+       "1980-03-02 03:00:00  3.000000   8.200000  1010.700000\n",
+       "1980-03-02 04:00:00  3.000000   7.927273  1010.100000\n",
+       "1980-03-02 05:00:00  2.916667   7.658333  1009.500000\n",
+       "1980-03-02 06:00:00  2.416667   7.408333  1008.900000\n",
+       "1980-03-02 07:00:00  2.000000   7.100000  1008.300000\n",
+       "1980-03-02 08:00:00  2.142857   6.542857  1007.700000\n",
+       "1980-03-02 09:00:00  3.000000   6.200000  1007.100000\n",
+       "1980-03-02 10:00:00  2.833333   8.350000  1006.466667\n",
+       "1980-03-02 11:00:00  2.000000   6.828571  1005.833333\n",
+       "1980-03-02 12:00:00  2.000000   8.200000  1005.200000\n",
+       "1980-03-02 13:00:00  0.166667   9.216667  1004.766667\n",
+       "1980-03-02 14:00:00  1.000000  11.885714  1004.333333\n",
+       "1980-03-02 15:00:00  1.000000  12.400000  1003.900000"
       ]
      },
      "execution_count": 25,
@@ -1138,12 +1312,119 @@
     }
    ],
    "source": [
-    "df_targets.head()"
+    "df[target_city][target_names].head(shift_steps + 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The following is the first 5 rows of the time-shifted data-frame. This should be identical to the last 5 rows shown above from the original data, except for the time-stamp."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 26,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Temp</th>\n",
+       "      <th>WindSpeed</th>\n",
+       "      <th>Pressure</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DateTime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 11:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>6.828571</td>\n",
+       "      <td>1005.833333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 12:00:00</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>8.200000</td>\n",
+       "      <td>1005.200000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 13:00:00</th>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>9.216667</td>\n",
+       "      <td>1004.766667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 14:00:00</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>11.885714</td>\n",
+       "      <td>1004.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980-03-01 15:00:00</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>12.400000</td>\n",
+       "      <td>1003.900000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         Temp  WindSpeed     Pressure\n",
+       "DateTime                                             \n",
+       "1980-03-01 11:00:00  2.000000   6.828571  1005.833333\n",
+       "1980-03-01 12:00:00  2.000000   8.200000  1005.200000\n",
+       "1980-03-01 13:00:00  0.166667   9.216667  1004.766667\n",
+       "1980-03-01 14:00:00  1.000000  11.885714  1004.333333\n",
+       "1980-03-01 15:00:00  1.000000  12.400000  1003.900000"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_targets.head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The time-shifted data-frame has the same length as the original data-frame, but the last observations are `NaN` (not a number) because the data has been shifted backwards so we are trying to shift data that does not exist in the original data-frame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -1181,33 +1462,33 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2018-03-01 19:00:00</th>\n",
-       "      <td>-6.3</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>1032.8</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2018-03-01 20:00:00</th>\n",
-       "      <td>-6.6</td>\n",
-       "      <td>10.8</td>\n",
-       "      <td>1032.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2018-03-01 21:00:00</th>\n",
-       "      <td>-6.9</td>\n",
-       "      <td>9.8</td>\n",
-       "      <td>1032.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2018-03-01 22:00:00</th>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>9.3</td>\n",
-       "      <td>1032.3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2018-03-01 23:00:00</th>\n",
-       "      <td>-7.0</td>\n",
-       "      <td>10.3</td>\n",
-       "      <td>1031.9</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1216,14 +1497,14 @@
       "text/plain": [
        "                     Temp  WindSpeed  Pressure\n",
        "DateTime                                      \n",
-       "2018-03-01 19:00:00  -6.3        9.3    1032.8\n",
-       "2018-03-01 20:00:00  -6.6       10.8    1032.6\n",
-       "2018-03-01 21:00:00  -6.9        9.8    1032.4\n",
-       "2018-03-01 22:00:00  -7.0        9.3    1032.3\n",
-       "2018-03-01 23:00:00  -7.0       10.3    1031.9"
+       "2018-03-01 19:00:00   NaN        NaN       NaN\n",
+       "2018-03-01 20:00:00   NaN        NaN       NaN\n",
+       "2018-03-01 21:00:00   NaN        NaN       NaN\n",
+       "2018-03-01 22:00:00   NaN        NaN       NaN\n",
+       "2018-03-01 23:00:00   NaN        NaN       NaN"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1238,23 +1519,23 @@
    "source": [
     "### NumPy Arrays\n",
     "\n",
-    "We now convert the Pandas data-frames to NumPy arrays that can be input to the neural network. We also remove the first part of the numpy arrays, because the target-data has `NaN` for the shifted period, and we only want to have valid data and we need the same array-shapes for the input- and output-data.\n",
+    "We now convert the Pandas data-frames to NumPy arrays that can be input to the neural network. We also remove the last part of the numpy arrays, because the target-data has `NaN` for the shifted period, and we only want to have valid data and we need the same array-shapes for the input- and output-data.\n",
     "\n",
     "These are the input-signals:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
-    "x_data = df.values[shift_steps:]"
+    "x_data = df.values[0:-shift_steps]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1280,16 +1561,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
-    "y_data = df_targets.values[shift_steps:]"
+    "y_data = df_targets.values[:-shift_steps]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "scrolled": true
    },
@@ -1317,7 +1598,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -1326,13 +1607,13 @@
        "333085"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "num_data= len(x_data)\n",
+    "num_data = len(x_data)\n",
     "num_data"
    ]
   },
@@ -1345,7 +1626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1361,7 +1642,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1370,7 +1651,7 @@
        "299776"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1389,7 +1670,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -1398,7 +1679,7 @@
        "33309"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1417,7 +1698,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -1426,7 +1707,7 @@
        "333085"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1446,7 +1727,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -1455,7 +1736,7 @@
        "333085"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1475,7 +1756,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -1484,7 +1765,7 @@
        "20"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1503,7 +1784,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "scrolled": true
    },
@@ -1514,7 +1795,7 @@
        "3"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1535,7 +1816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1563,7 +1844,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1579,7 +1860,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1595,7 +1876,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
@@ -1621,7 +1902,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1637,7 +1918,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1659,7 +1940,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -1680,16 +1961,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "But the Recurrent Neural Network cannot be trained on sequences with 300k observations. It is only trained on small sequences of e.g. 100 observations. Furthermore, in order to improve the training-efficiency when using a GPU, we will use batches of training-data.\n",
-    "\n",
-    "For example, we may want a random batch of 1024 sequences, with each sequence having 100 observations, and each observation having 20 input-signals and 3 output-signals.\n",
-    "\n",
-    "This function generates such random batches of data."
+    "Instead of training the Recurrent Neural Network on the complete sequences of almost 300k observations, we will use the following function to create a batch of shorter sub-sequences picked at random from the training-data."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1702,17 +1979,17 @@
     "    while True:\n",
     "        # Allocate a new array for the batch of input-signals.\n",
     "        x_shape = (batch_size, sequence_length, num_x_signals)\n",
-    "        x_batch = np.zeros(shape=x_shape)\n",
+    "        x_batch = np.zeros(shape=x_shape, dtype=np.float16)\n",
     "\n",
     "        # Allocate a new array for the batch of output-signals.\n",
     "        y_shape = (batch_size, sequence_length, num_y_signals)\n",
-    "        y_batch = np.zeros(shape=y_shape)\n",
+    "        y_batch = np.zeros(shape=y_shape, dtype=np.float16)\n",
     "\n",
     "        # Fill the batch with random sequences of data.\n",
     "        for i in range(batch_size):\n",
     "            # Get a random start-index.\n",
     "            # This points somewhere into the training-data.\n",
-    "            idx = np.random.randint(num_train-sequence_length)\n",
+    "            idx = np.random.randint(num_train - sequence_length)\n",
     "            \n",
     "            # Copy the sequences of data starting at this index.\n",
     "            x_batch[i] = x_train_scaled[idx:idx+sequence_length]\n",
@@ -1725,32 +2002,44 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will use a large batch-size so as to keep the GPU near 100% work-load."
+    "We will use a large batch-size so as to keep the GPU near 100% work-load. You may have to adjust this number depending on your GPU, its RAM and your choice of `sequence_length` below."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
-    "batch_size = 1024"
+    "batch_size = 256"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will use a sequence-length of 100, which means that each random sequence contains observations for 4 days and 4 hours (100 time-steps = 4 * 24 + 4 hours)."
+    "We will use a sequence-length of 1344, which means that each random sequence contains observations for 8 weeks. One time-step corresponds to one hour, so 24 x 7 time-steps corresponds to a week, and 24 x 7 x 8 corresponds to 8 weeks."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1344"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "sequence_length = 100"
+    "sequence_length = 24 * 7 * 8\n",
+    "sequence_length"
    ]
   },
   {
@@ -1762,7 +2051,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1779,7 +2068,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1790,20 +2079,20 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This gives us a random batch of 1024 sequences, each sequence having 100 observations, and each observation having 20 input-signals and 3 output-signals."
+    "This gives us a random batch of 256 sequences, each sequence having 1344 observations, and each observation having 20 input-signals and 3 output-signals."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(1024, 100, 20)\n",
-      "(1024, 100, 3)\n"
+      "(256, 1344, 20)\n",
+      "(256, 1344, 3)\n"
      ]
     }
    ],
@@ -1821,24 +2110,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fb45ce08d68>]"
+       "[<matplotlib.lines.Line2D at 0x7f6a48b09be0>]"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 53,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb45ce8b5c0>"
+       "<matplotlib.figure.Figure at 0x7f6a48b722b0>"
       ]
      },
      "metadata": {},
@@ -1847,7 +2136,7 @@
    ],
    "source": [
     "batch = 0   # First sequence in the batch.\n",
-    "signal = 0  # First signal out of the 20 input-signals.\n",
+    "signal = 0  # First signal from the 20 input-signals.\n",
     "seq = x_batch[batch, :, signal]\n",
     "plt.plot(seq)"
    ]
@@ -1861,24 +2150,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fb45cd21630>]"
+       "[<matplotlib.lines.Line2D at 0x7f6a48a1ce48>]"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb45cfd4be0>"
+       "<matplotlib.figure.Figure at 0x7f6a48bf3d30>"
       ]
      },
      "metadata": {},
@@ -1903,7 +2192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1922,7 +2211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1933,14 +2222,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can now add a Gated Recurrent Unit (GRU) to the network. This will have 256 outputs for each time-step in the sequence.\n",
+    "We can now add a Gated Recurrent Unit (GRU) to the network. This will have 512 outputs for each time-step in the sequence.\n",
     "\n",
     "Note that because this is the first layer in the model, Keras needs to know the shape of its input, which is a batch of sequences of arbitrary length (indicated by `None`), where each observation has a number of input-signals (`num_x_signals`)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
@@ -1954,7 +2243,7 @@
     }
    ],
    "source": [
-    "model.add(GRU(units=256,\n",
+    "model.add(GRU(units=512,\n",
     "              return_sequences=True,\n",
     "              input_shape=(None, num_x_signals,)))"
    ]
@@ -1963,14 +2252,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The GRU outputs a batch of sequences of 256 values. We want to predict 3 output-signals, so we add a fully-connected (or dense) layer which maps 256 values down to only 3 values.\n",
+    "The GRU outputs a batch of sequences of 512 values. We want to predict 3 output-signals, so we add a fully-connected (or dense) layer which maps 512 values down to only 3 values.\n",
     "\n",
     "The output-signals in the data-set have been limited to be between 0 and 1 using a scaler-object. So we also limit the output of the neural network using the Sigmoid activation function, which squashes the output to be between 0 and 1."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1990,13 +2279,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
     "if False:\n",
     "    from tensorflow.python.keras.initializers import RandomUniform\n",
+    "\n",
+    "    # Maybe use lower init-ranges.\n",
     "    init = RandomUniform(minval=-0.05, maxval=0.05)\n",
+    "\n",
     "    model.add(Dense(num_y_signals,\n",
     "                    activation='linear',\n",
     "                    kernel_initializer=init))"
@@ -2006,30 +2298,90 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This is the optimizer and learning-rate we will use."
+    "### Loss Function\n",
+    "\n",
+    "We will use Mean Squared Error (MSE) as the loss-function that will be minimized. This measures how closely the model's output matches the true output signals.\n",
+    "\n",
+    "However, at the beginning of a sequence, the model has only seen input-signals for a few time-steps, so its generated output may be very inaccurate. Using the loss-value for the early time-steps may cause the model to distort its later output. We therefore give the model a \"warmup-period\" of 50 time-steps where we don't use its accuracy in the loss-function, in hope of improving the accuracy for later time-steps."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
-    "optimizer = RMSprop(lr=1e-3)"
+    "warmup_steps = 50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def loss_mse_warmup(y_true, y_pred):\n",
+    "    \"\"\"\n",
+    "    Calculate the Mean Squared Error between y_true and y_pred,\n",
+    "    but ignore the beginning \"warmup\" part of the sequences.\n",
+    "    \n",
+    "    y_true is the desired output.\n",
+    "    y_pred is the model's output.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # The shape of both input tensors are:\n",
+    "    # [batch_size, sequence_length, num_y_signals].\n",
+    "\n",
+    "    # Ignore the \"warmup\" parts of the sequences\n",
+    "    # by taking slices of the tensors.\n",
+    "    y_true_slice = y_true[:, warmup_steps:, :]\n",
+    "    y_pred_slice = y_pred[:, warmup_steps:, :]\n",
+    "\n",
+    "    # These sliced tensors both have this shape:\n",
+    "    # [batch_size, sequence_length - warmup_steps, num_y_signals]\n",
+    "\n",
+    "    # Calculate the MSE loss for each value in these tensors.\n",
+    "    # This outputs a 3-rank tensor of the same shape.\n",
+    "    loss = tf.losses.mean_squared_error(labels=y_true_slice,\n",
+    "                                        predictions=y_pred_slice)\n",
+    "\n",
+    "    # Keras may reduce this across the first axis (the batch)\n",
+    "    # but the semantics are unclear, so to be sure we use\n",
+    "    # the loss across the entire tensor, we reduce it to a\n",
+    "    # single scalar with the mean function.\n",
+    "    loss_mean = tf.reduce_mean(loss)\n",
+    "\n",
+    "    return loss_mean"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will use Mean Squared Error (MSE) as the loss-function that will be minimized. This measures how closely the model's output matches the true output signals.\n",
+    "### Compile Model\n",
     "\n",
+    "This is the optimizer and the beginning learning-rate that we will use."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer = RMSprop(lr=1e-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "We then compile the Keras model so it is ready for training."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -2043,9 +2395,7 @@
     }
    ],
    "source": [
-    "model.compile(loss='mean_squared_error',\n",
-    "              optimizer=optimizer,\n",
-    "              metrics=['mae'])"
+    "model.compile(loss=loss_mse_warmup, optimizer=optimizer)"
    ]
   },
   {
@@ -2057,7 +2407,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -2067,12 +2417,12 @@
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "gru_1 (GRU)                  (None, None, 256)         212736    \n",
+      "gru_1 (GRU)                  (None, None, 512)         818688    \n",
       "_________________________________________________________________\n",
-      "dense_1 (Dense)              (None, None, 3)           771       \n",
+      "dense_1 (Dense)              (None, None, 3)           1539      \n",
       "=================================================================\n",
-      "Total params: 213,507\n",
-      "Trainable params: 213,507\n",
+      "Total params: 820,227\n",
+      "Trainable params: 820,227\n",
       "Non-trainable params: 0\n",
       "_________________________________________________________________\n"
      ]
@@ -2095,7 +2445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2116,7 +2466,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2133,7 +2483,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2143,121 +2493,62 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 65,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "callbacks = [callback_early_stopping,\n",
-    "             callback_checkpoint,\n",
-    "             callback_tensorboard]"
+    "This callback reduces the learning-rate for the optimizer if the validation-loss has not improved since the last epoch (as indicated by `patience=0`). The learning-rate will be reduced by multiplying it with the given factor. We set a start learning-rate of 1e-3 above, so multiplying it by 0.1 gives a learning-rate of 1e-4. We don't want the learning-rate to go any lower than this."
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 68,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "## Train the Recurrent Neural Network\n",
-    "\n",
-    "We need an approximate number of training-steps to perform per epoch of the training-data, because we use a batch-generator function."
+    "callback_reduce_lr = ReduceLROnPlateau(monitor='val_loss',\n",
+    "                                       factor=0.1,\n",
+    "                                       min_lr=1e-4,\n",
+    "                                       patience=0,\n",
+    "                                       verbose=1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 69,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "292"
-      ]
-     },
-     "execution_count": 66,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "steps_per_epoch = int(num_train / batch_size)\n",
-    "steps_per_epoch"
+    "callbacks = [callback_early_stopping,\n",
+    "             callback_checkpoint,\n",
+    "             callback_tensorboard,\n",
+    "             callback_reduce_lr]"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can now train the neural network. Each epoch takes less than a minute on a GTX 1070."
+    "## Train the Recurrent Neural Network\n",
+    "\n",
+    "We can now train the neural network.\n",
+    "\n",
+    "Note that a single \"epoch\" does not correspond to a single processing of the training-set, because of how the batch-generator randomly selects sub-sequences from the training-set. Instead we have selected `steps_per_epoch` so that one \"epoch\" is processed in a few minutes.\n",
+    "\n",
+    "With these settings, each \"epoch\" took about 2.5 minutes to process on a GTX 1070. After 14 \"epochs\" the optimization was stopped because the validation-loss had not decreased for 5 \"epochs\". This optimization took about 35 minutes to finish.\n",
+    "\n",
+    "Also note that the loss sometimes becomes `NaN` (not-a-number). This is often resolved by restarting and running the Notebook again. But it may also be caused by your neural network architecture, learning-rate, batch-size, sequence-length, etc. in which case you may have to modify those settings."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch 1/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0041 - mean_absolute_error: 0.0465Epoch 00001: val_loss improved from inf to 0.00166, saving model to 23_checkpoint.keras\n",
-      "292/292 [==============================]292/292 [==============================] - 44s 152ms/step - loss: 0.0041 - mean_absolute_error: 0.0465 - val_loss: 0.0017 - val_mean_absolute_error: 0.0319\n",
-      "\n",
-      "Epoch 2/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0016 - mean_absolute_error: 0.0296Epoch 00002: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 44s 151ms/step - loss: 0.0016 - mean_absolute_error: 0.0296 - val_loss: 0.0036 - val_mean_absolute_error: 0.0425\n",
-      "\n",
-      "Epoch 3/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0012 - mean_absolute_error: 0.0253Epoch 00003: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0012 - mean_absolute_error: 0.0253 - val_loss: 0.0022 - val_mean_absolute_error: 0.0327\n",
-      "\n",
-      "Epoch 4/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 9.9865e-04 - mean_absolute_error: 0.0234Epoch 00004: val_loss improved from 0.00166 to 0.00088, saving model to 23_checkpoint.keras\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 155ms/step - loss: 9.9820e-04 - mean_absolute_error: 0.0234 - val_loss: 8.8447e-04 - val_mean_absolute_error: 0.0233\n",
-      "\n",
-      "Epoch 5/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 9.0360e-04 - mean_absolute_error: 0.0219Epoch 00005: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 154ms/step - loss: 9.0283e-04 - mean_absolute_error: 0.0219 - val_loss: 0.0013 - val_mean_absolute_error: 0.0272\n",
-      "\n",
-      "Epoch 6/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 8.5867e-04 - mean_absolute_error: 0.0212Epoch 00006: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 8.5956e-04 - mean_absolute_error: 0.0212 - val_loss: 0.0021 - val_mean_absolute_error: 0.0366\n",
-      "\n",
-      "Epoch 7/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0018 - mean_absolute_error: 0.0298Epoch 00007: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 44s 152ms/step - loss: 0.0018 - mean_absolute_error: 0.0298 - val_loss: 0.0018 - val_mean_absolute_error: 0.0300\n",
-      "\n",
-      "Epoch 8/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0013 - mean_absolute_error: 0.0262Epoch 00008: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0013 - mean_absolute_error: 0.0262 - val_loss: 0.0029 - val_mean_absolute_error: 0.0403\n",
-      "\n",
-      "Epoch 9/20\n",
-      "291/292 [============================>.]291/292 [============================>.] - ETA: 0s - loss: 0.0011 - mean_absolute_error: 0.0239Epoch 00009: val_loss did not improve\n",
-      "292/292 [==============================]292/292 [==============================] - 45s 153ms/step - loss: 0.0011 - mean_absolute_error: 0.0239 - val_loss: 0.0014 - val_mean_absolute_error: 0.0274\n",
-      "\n",
-      "Epoch 00009: early stopping\n",
-      "CPU times: user 8min 5s, sys: 53.2 s, total: 8min 58s\n",
-      "Wall time: 6min 44s\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fb453a609e8>"
-      ]
-     },
-     "execution_count": 67,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "%%time\n",
     "model.fit_generator(generator=generator,\n",
     "                    epochs=20,\n",
-    "                    steps_per_epoch=steps_per_epoch,\n",
+    "                    steps_per_epoch=100,\n",
     "                    validation_data=validation_data,\n",
     "                    callbacks=callbacks)"
    ]
@@ -2273,7 +2564,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2295,7 +2586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -2314,21 +2605,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss: 8.845e-04\n",
-      "mean_absolute_error: 2.328e-02\n"
+      "loss (test-set): 0.0021468019112944603\n"
      ]
     }
    ],
    "source": [
-    "for res, metric in zip(result, model.metrics_names):\n",
-    "    print(\"{0}: {1:.3e}\".format(metric, res))"
+    "print(\"loss (test-set):\", result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# If you have several metrics you can use this instead.\n",
+    "if False:\n",
+    "    for res, metric in zip(result, model.metrics_names):\n",
+    "        print(\"{0}: {1:.3e}\".format(metric, res))"
    ]
   },
   {
@@ -2342,7 +2643,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2391,9 +2692,17 @@
     "        # Get the true output-signal from the data-set.\n",
     "        signal_true = y_true[:, signal]\n",
     "\n",
+    "        # Make the plotting-canvas bigger.\n",
+    "        plt.figure(figsize=(15,5))\n",
+    "        \n",
     "        # Plot and compare the two signals.\n",
     "        plt.plot(signal_true, label='true')\n",
     "        plt.plot(signal_pred, label='pred')\n",
+    "        \n",
+    "        # Plot grey box for warmup-period.\n",
+    "        p = plt.axvspan(0, warmup_steps, facecolor='black', alpha=0.15)\n",
+    "        \n",
+    "        # Plot labels etc.\n",
     "        plt.ylabel(target_names[signal])\n",
     "        plt.legend()\n",
     "        plt.show()"
@@ -2407,21 +2716,84 @@
     "\n",
     "These plots only show the output-signals and not the 20 input-signals used to predict the output-signals. The time-shift between the input-signals and the output-signals is held fixed in these plots. The model **always** predicts the output-signals e.g. 24 hours into the future (as defined in the `shift_steps` variable above). So the plot's x-axis merely shows how many time-steps of the input-signals have been seen by the predictive model so far.\n",
     "\n",
-    "The prediction is not very accurate for the first 20 time-steps because the model has seen very little input-data at this point. The model generates a single time-step of output data for each time-step of the input-data, so when the model has only run for a few time-steps, it knows very little of the history of the input-signals and cannot make an accurate prediction. The model needs to \"warm up\" by processing perhaps 30-50 time-steps before its predicted output-signals can be used. Note, however, that we can process as many time-steps as we want, as we are not limited to the 100 time-steps that we used during training.\n",
+    "The prediction is not very accurate for the first 30-50 time-steps because the model has seen very little input-data at this point.\n",
+    "The model generates a single time-step of output data for each time-step of the input-data, so when the model has only run for a few time-steps, it knows very little of the history of the input-signals and cannot make an accurate prediction. The model needs to \"warm up\" by processing perhaps 30-50 time-steps before its predicted output-signals can be used.\n",
+    "\n",
+    "That is why we ignore this \"warmup-period\" of 50 time-steps when calculating the mean-squared-error in the loss-function. The \"warmup-period\" is shown as a grey box in these plots.\n",
     "\n",
     "Let us start with an example from the training-data. This is data that the model has seen during training so it should perform reasonably well on this data."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 75,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6a180459e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f6a48abdbe0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f69fc02f710>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_comparison(start_idx=100000, length=1000, train=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The model was able to predict the overall oscillations of the temperature quite well but the peaks were sometimes inaccurate. For the wind-speed, the overall oscillations are predicted reasonably well but the peaks are quite inaccurate. For the atmospheric pressure, the overall curve-shape has been predicted although there seems to be a slight lag and the predicted curve has a lot of noise compared to the smoothness of the original signal."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Strange Example\n",
+    "\n",
+    "The following is another example from the training-set.\n",
+    "\n",
+    "Note how the temperature does not oscillate very much within each day (this plot shows almost 42 days). The temperature normally oscillates within each day, see e.g. the plot above where the daily temperature-oscillation is very clear. It is unclear whether this period had unusually stable temperature, or if perhaps there's a data-error."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb4ec520080>"
+       "<matplotlib.figure.Figure at 0x7f69f54a59b0>"
       ]
      },
      "metadata": {},
@@ -2429,9 +2801,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb45cd30a20>"
+       "<matplotlib.figure.Figure at 0x7f69e014c7b8>"
       ]
      },
      "metadata": {},
@@ -2439,9 +2811,9 @@
     },
     {
      "data": {
-      "image/png": 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rpvL/lqZyw6wYwvw8eX5jNrtPDyN/Y8qNEDkNvvq1cnBqRh/GsNmkJT2Gy+ta2JNXNWhux2BcPllZgNeb7j7iF0FLjfo/1misjM12HkKId1HO8VAhRCHwJPAc8IEQ4n7gDHCzYfovgBDgJUO0SLvB/NQuhPgBsB5wBV6TUtrnk9DaoCKqXFxVKK6hz3TgOA9mx/etU9XU2sGSP3zFk58c5bMfLsbVZQjRUy4ucNFj8P4dkP2F9VqTapyHvG8gIFaVDjHhi2MlSMmQQnTNERs8jslR/qw/Wtpd8yre6PfYrpJVNRorYrOdh5TyNilllJTSXUoZI6V8VUpZKaVcIqVMkVJeJqWsMsz9jpQySEo5w/DIMLnOGillqpQySUr5rK3k7cO+ldBQBje9oZq3DIK3hyv/c8UkjhfX8t6eYXRyS10OvpGw/83B52pGFlKqCgQJi/uEZK/LLCEhZBwTI/3O+22WpUeyP/8cZXXNaiAgBgLjlNNco7EyOsPcHFLCjhdVVFXcfIuXXTE1inmJwfx+fRbVja1De09XN5hxu9p51JUMPl8zcijPgsaKPv07zjW0sj23kuVToqzSf2HZlAikhA3HSrsH4xepnccoTXjTOA6tPMxRmgm1hTDjtiEtE0Lw1NXp1DS18dv1WUN/32m3qBLux1YPfa3Geck3RDwZzUgGNhwvpaNT8q2p52eyMpIW4Ud8yDjWH+2lPBoroOJk/ws1mmGglYc5cjaqY9KlQ146Kcqf+xYl8s6ufF76Kmdoi8MnqrISmf8e8vtqnJjCvTAuVBXKNGFdZgnRgd5MNeZmnCdCCJalR7Ijt4LaZkPgRbxJvodGY0W08jBH7kYInwz+44e1/GffmsQ1M8bz23VZ/PObU0NbPOV61aa0ehh+E41zUrgHYub08HfUNbexNbuC5VMirdoydFl6BG0dks0nDFHwwROUL03ne2isjFYe5ijcp5ybw8TVRfCHm6ZzxdQonvn8OC9/nUtHp4U25/Tr1dFcUynNyKPpnDIZ9coq33mqitaOTpZONldkYfjMjA0izM+zO2RXCLX7yNum/R4aq6KVR2/amqGtAXzP70Pt5urCn2+dwbL0CP5v7Qku/9PXfHroLJ2DKZHgRIierU1Xo4WifeoY07NEyIH8c7i6CKbHBFr17VxcBEsnR/BVVjnNbYaKBfELoe6sKsqo0VgJrTx602RI8rNCz3F3Vxf+dsds/nbHLFxdBD989wDf+ss3rD9aMnC55yk3QPEhqBiiz0TjfBTuBUSf5k8HC6qZFOWHt4f1M7+XpUfS2NrB1uwKNWCM8srTfg+N9dDKozeNhsoo3uevPEDdCa6YGsXaRy7k+Vtn0NLeyYP/2sfVL2xjW06F+UXp1wECjn5kFRk0DqRwj/KfeXbncXR0Sg4X1jAj1rq7DiMLJoTg5+XWbboKmwjeQdrvobEqWnn0ptF6Ow9TXF0E18yIZsN/XcjvbpxGdVMrd7+2m4Kqxr6T/ccrU8ORD7WdeiTT2Wlwlvf0d+SU1VPf0s7M2CCbvK2HmwuXTgzny+OltHd0qgoGcQt1xJXGqmjl0Zsus1WITS7v5urCTRmxfPDgAgTwxvY88xOnXA8VWVBms9YlGltTmQPNNRA7t8fwwYJzAMyIs83OA5Tp6lxjG3vPqPcifiGcOw21Z232npqxhVYevTHuPKxktuqPqABvrpwWxft7Crpj8k2ZdA0IV+04H8kU7lHHPs7yagK83Uns3aHSilyUGoaHm0u36SrB4PfQpiuNldDKozdWdJgPxv2LJ1Df0s4Hewr6nvQNU70fMv+tTVcjlcI94BkAIT2bfB0sqGZ6bCAuQymeOUR8PN3IiA9iv3HnETEVPPy08tBYDa08etN4TnV769WwxxZMjQlgXmIwr2/LU7bp3qRfD+fy4Oz+vuc0zk/hXoiZrXwOBupb2skqrWOmjZzlpqRF+nGytF6Fh7u6Qdw8rTysTWOVusE7/im0D7Ge3QhHK4/eNFbaZddh5P7FiRRVN7HuqJliiJOuBBd3yNRRVyOOlnooO9rHZHW4sBopbevvMJIW4UdTWweF55rUQPxCKD8ODZUDL9QMTkc7bH8B/jARPrwP3r8TPrgb2lscLZnd0MqjN01VdlUeSyZFkBAyjn9+c7rvSe8gSL5MZZt3mtmZaJyXswdUkcteyuNgQTUAM6ycHGiOVEOZ96zSOjVgzPfI17uPYdPWBN/8AV6cC1/8LyQvge9sguW/gZNrYcvvHC2h3dDKozeNVTZ3lpvi6iK4b3EiBwuq2We0T5sy5QaoLVL1rjQjB6OpMXp2j+ED+dUkhvoQ5ONhcxFSwlVb25NG5TF+Jrh5adPVcJES/vMQbPwV+ITBLW/Bre8o0+T878G0W2Hrn6HshKMltQtaefTGzjsPgBtnxxDg7c6rW80UUUxbAW7eOupqpFFyBPxjevwvSSk5WFBtF38HgJ+XO9GB3mSVGJSHm6faCWnlMTyOfKisAJf9Eu5fD5Ou6tnca9mz4OkLn/14TFgKbKY8hBCvCSHKhBCZJmPBQogNQohswzHIMD5RCLFDCNEihHi013XyhBBHhBAHhRB7bSVvF3beeQCM83Dj9nlxrMss6Zs06OkLqcvg2H+UnVUzMig+3Kf1a1F1E+V1LXbxdxhRTvO67oGYDNWvpq3ZbjKMCqSEHX+F0FRY+CPzc3xC4fJnIH/HmKgOYcudxxvA8l5jjwMbpZQpwEbDa4Aq4EfA7/u51iW929PaBClVeOz4mTZ9G3PcsyABFyF4fVte35NTboCGctUHW+P8tDZCZXaf9sVGf4etMsvNkRrhR255PW3GaL7o2dDZrnZGGss5s13Vm5v/UI/ouT5Mvx2Ck2DX3+0nm4OwZQ/zLSilYMo1wErD85XAtYa5ZVLKPYCZbDk7IgTc/CbMvMPubx0Z4MVV08fz/p78vkmDKUtVjL42XY0Myo4rZ3kv5XEgvxpPNxcmRp1/v3JLSYv0pa1DklfRoAaMPhhjtV+NZex8SQWwTLt14HkuLjDvQZXjU+SAEPvyLEOwhu1zw+zt84iQUhYbnpcAltQ9l8AXQoh9QogHBpoohHhACLFXCLG3vLz8fGW1O/cvTqShtYP3d/dKGnT3holXwPFPxlws+Yik5JA6RvY0Wx0sqGZqdADurvb72KVG9Iq48h8PflFaeQyFqtNw4nPIuA88xg0+f9otqjpE1hrby9abHS/AWzfY5a0c5jCXqia5JepxsZRyFrAC+L4Q4sIBrvmKlDJDSpkRFhZmLVHtxpToAOZPCOb1baf7Jg1OuUHVScrd5BjhNJZTcgS8AiAwrmuotb2TzCLbVdLtj6QwX1wEnCwx8XtEz9bKYygc/QiQkHG/ZfO9A5Xp+7QDzMwlR9SO14rdKfvD3sqjVAgRBWA4lg22QEpZZDiWAR8DcwdeMbL5zuIJnK1pZm1mr6TBCRerbbM2XTk/JUfUrsPkA3yipJaW9k5mxtnP3wHg5e5KQqgPJ3ooj1lQldtdx00zMNlfqr9nQLTlaxIvgKK9KlnUXnS0Q+kxiJhil7ezt/L4BLjH8PweYPVAk4UQPkIIP+Nz4HIgc6A1I51LJ4aTGOrDP7851bNhlJsHTLpabYVbzZRx1zgHnR1QerRfZ7k9I62MpEX0irgy+j3OHrC7LCOO5hqVY5WydGjrEi9UgQn5O20jlzkqc6CjhbqgSXZ5O1uG6r4L7ADShBCFQoj7geeApUKIbOAyw2uEEJFCiELgJ8DPDfP9UT6RrUKIQ8Bu4HMp5TpbyewMuBiSBg8V1rA/v1fSYPp10FqvTVfOTGUutDWadZaH+3kyPsDL7iKlRvhxpqqRplZDW1pjNKEjHLojjZyNIDtUpYdB6GFqjp2n/B75O2woXC8MEXR3r2kauFOplbBltNVtUsooKaW7lDJGSvmqlLJSSrlESpkipbxMSlllmFtimOMvpQw0PK+VUp6SUk43PNKllM/aSl5n4vqZ0fh5ufHG9l49p+MXqairnA2OEUwzOCWH1dGMs3xGbCDCDrbo3qRF+iGlakIFKH9MaKr2e1jC4fdVgEHsvAGnvbkjjylPre/uDurhAxHp3WX57UHJYdpwwztyol3+z3SGuRPi4+nGLRmxrD1STGmtSTKXmwckXaxssLpMu3NSchhcPSAsrWvoXEMrpysa7O7vMNIn4grU7qP4oEPkGTHUlUL2Bph+K7iY7zXf0Sl56pOj/GL1UZrbOnvmacXOVQq6s8Mu4sriw5yUsaRF2yfJWSsPJ+XuBQl0SMnbO3vtPpKXQm2hyiXQOB8lRyB8Eri6dw0dLDT4O+wcaWUkIWQcHm4uPf0eEVOgrlg7zQfiyAfKZDX9drOnG1raeeDNvbyxPY/7Fyfy4IUT2JxV1n3DFzNHmZnt8VmVks7iQxzpiGdylL/t3w+tPJyWuJBxLJkYzju782lpN7lzMTrusr9wjGCa/pFSlSXp7SzPr8ZFwLSYAIeI5ebqQnKYb3eNK1AmFVDOfU1fpISD7ygFEJba53RxTRM3/X0Hm7PKePraKTxx5WRunRtHR6fkw32FapKxorI9TFe1Rbg2nyNTJpI+3j7/Z1p5ODH3Lkykor6Vzw8Xdw/6j1dd4XK+dJxgGvPUlUBjRR9/x4GCalIj/PDxdHOQYGZqXBnDObXyMM/ZA1B2DGb0rTaRWVTDtS9uI7+qkdfuncNd8+MBSAz1Yf6EYD7YW6AacAVPgHEh9lEexcrXliUSSDZUU7Y1Wnk4MYuSQ0gO9+WN7Xk9oydSLlNRHM01jhNO0xdjvSgT5dHZKTlUUO0wf4eR1Ag/imuaqWkylL7xDYdxoVCqa1yZ5ejHqhFb+nU9hjOLarj55R24CsGHDy3g4rTwHudvnRPHmcpGdp6uVHk+MXPspDwO0YmgPTQdDzf7fK1r5eHECCG4Z2ECh3uH7aZcrmLIT33lMNk0ZjCWJTGahIDTlQ3UNLXZrQx7f6RFqrvRbOPuQwglp955mCdrjUr08+7+u3V0Sn720RF8PN34z/cXMTGyr29h+ZRI/LzceH+PocRQzByoOGl731LJYc4wnqTo8MHnWgmtPJycG2ZFE+Dtzj+2mHQajJkLngHa7+FslBxRpgqv7i8VY4OvmQ5IDjTFbMRV5FTlzLVTNNCIoSJbJdylfavH8Fs7z3CkqIZfXDmZcH/z+Tpe7q5cNzOatZklVDe2dvs9bBwW3XH2EIc74kkfbx9nOWjl4fSM83DjjnlxrD9WwplKQ2VUVzdIvlSH7DobxrpCJuzMrSTEx8Nuduj+iA70xsfDtWeNq4h0aG+GKjNNyMYyJz5Xx7QVXUNltc38fn0WF6SEcuW0qAGX35wRS2t7J+uPlqhSMAjbKo/GKlzrisjsTLBbpBVo5TEiuGdhAm4ugle3muw+kpdCfYnuy+AsNNeqL2ET5SGlZMepSuZPCHFIcqApQghSI/167jy6Iq5GdcWfoZO1BqKmQ0BM19DTnx+npaOTX10zZdC/Zfp4f4LGubM37xx4+kFoSpdD2yYUK3PpUZnAJL3z0JgS4e/F1dOjWbW3UG2FobtcgjZdOQdG30Hk9K6hM5WNFNc0Mz8pxEFC9SQtwo+skrru4IvQNFVCQ/s9uqkvh4LdPUxWW06W8+mhszx8cRKJoT6DXkIIwez4oC6TJVHTu77gbYLh2jUBk/D3ch9ksvXQymOEcOf8OJraOvj6pKFPiV8ERM1QGbAax9NVlqR757HjVCUACyY4h/JIjfDjXGMbFfWGGxB3L3VXrJVHNyfXAbJLeTS3dfCL1ZkkhvrwvYuSLL7MrPggTlU0UNXQqpRHbSE0VNhG5pLDlIgwYscPoeqvFdDKY4QwNToAP083dp4yidpIuRwKd0PTuf4XauzD2YPgGwF+kV1D23MrifD3JCls8LtVe5AWqZzmJ3ubrrTZqpusNRAQ23UT8LevcsmrbOTpa6bg5W6+RIk5MuJViZB9Z84p5QE22310nj3E4fY4JtvRZAVaeYwY3FxdmJsYzE7D3Sygss1lp6r8qXEsZ/erelFhOa3MAAAgAElEQVQGe7iUkh25FSxMCnW4v8NIV8RVb6d5db7OGQLV6iB3s3KUC8Gp8nr+9lUuV08fz+KU0CFdalpMAO6uQikPY96PLZRHSz2iKpfMzkS7OstBK48RxfwJIZyuaKCkxlA7J3q2ahCls80dS0u96h1tLHUOZJfVU1HfygIn8XcAhPp6EOzjYT7TXNdKU3lT7U2QtgIpJU+szsTT3YWfXzn0/hhe7q6kjw9g35kqlSsSlGCbQpSlRxFIjsp40qO18tD0w3yD7XzXacPuw8UVkpYo5dHZOcBKjU0pOQzIHsrDWJp7oRMpDyEEqRG+OuKqP06uBU9/iF/Ml8fL2JZTyU+XpRHuN7weLLPjgzhUWENre6ftnOaGaxZ6phDZT+6JrdDKYwQxebw/fl5u7Mg1NV1dDg3lUKy7wjkMY0c+E+WxPbeSuOBxxASNc5BQ5kmL8OOkacSVf7Tq7zHWneadnXDyC0i6FNw82HCshABvd26fGzf42n7IiA9SvevP1ijlcS7P+v7JkkPUugTgFxZnd/OoVh4jCFcXwTxzfg8XNzj6H8cJNtY5ewD8Y1S9KFQZi52nKp1q12EkNdKPhtYOiqqb1IAQynQ11pVHySGVN5W6HCklW7MrWJgUgpvr8L8iZ8eremb7TZ3m1s7Lyt/FEZKJsyCE2NrYsg3ta0KIMiFEpslYsBBigxAi23AMMoxPFELsEEK0CCEe7XWd5UKILCFEjhDicVvJO1KYPyGEvMpGimsMH/5xwSph8MgqXWbCURTth/Ezul4ePVtDXXO7U/k7jKRF9BdxdWxsVys4uR4QkHI5eZWNnK1pZlHy0JzkvQn39yI22FslC0baIOKqvgwqs9nSmkp8sJMqDyFEhBDiVSHEWsPryYae5APxBrC819jjwEYpZQqw0fAaoAr4EfD7Xu/rCrwIrAAmA7cJISZbIvNoxej36LH7mHazauyT942DpBrDNFVDVW4fkxXglMojpSviqr57MGwitNZBTaGDpHICTq5Tnf98Qthq8FctPk/lATA7Loh9+eeQPqHKRGhN5WHoj767YyLxIfY3j1q683gDWA+MN7w+Cfx4oAVSyi0opWDKNcBKw/OVwLWGuWVSyj1AW6/5c4EcQy/zVuA9wzXGLJOi/PH3cmNnrsmvNm2FcvQd/sBxgo1VjF8GvZRHSrjvsB2ttiTA252oAK+eO49wQzRR+QnHCOVo6kqU6TF1GQBbs8uJDvS2yhfy7IRgyutaKDzXZH2n+ZntdLh6kykTiQ12XuURKqX8AOgEkFK2A8OxkURIKY2djUqAiEHmRwMFJq8LDWNjFlcXwdzEENUvwIi7N0y+Go6tVrHqGvtxdr86GpRHa3sne05XOaW/w0hapF/PXI+wieo4VsN1T65Xx9TldHRKtudWsjjZOvk5sw19XPaeqVLKoyJbhXZbg8I9lPmn04abU+88GoQQIYAEEELMB84rq0iqcA+rGlmFEA8IIfYKIfaWl5db89JOxYKkEM5UNnLW6PQEmHaL6pectcZxgo1FCvZAcJLyPQGHCqtpautgQdL5mzxsRVqEHznl9bR3GMK7xwWr7PixuvM4/D6EJEP4ZI4UKX/VoiEmBfZHWqQfvp5uJpnm0jph0e2tUJLJKfc0fDxcCfHxOP9rDhFLlcdPgE+AJCHENuBN4IfDeL9SIUQUgOFYNsj8IiDW5HWMYcwsUspXpJQZUsqMsLCwYYg3Mpg/QX1R9fB7xC9WNlVturIfUkLBLoid1zW0LacCIbr/Rs5IaoQfre2dnKky2aWGTVRtV8calblwZhvMvBOEsHp+jquLYGZcoHKaGyOuzlohrL7sGHS0cFgmEhfi45AqBoMqDyGEC+AFXAQsBB4E0qWUw6kx/Alwj+H5PcDqQebvAVKEEIlCCA/gVsM1xjSTIv0J8HbvqTxcXGDqTSphsH707rqciqpTqmd57Nyuoe25lUwZH0DgOPvfCVpKV42rkl5+j/KssZdseuAtVVl4+m0AbM2uYFKUP6G+nlZ7i9nxQWSV1lHnbnCa5+88/4saFNC2xljiHeDvAAuUh5SyE3hRStkupTwqpcyUUvZ2bPdBCPEusANIE0IUGqKzngOWCiGygcsMrxFCRAohClE7nJ8b5vsbfCs/QDnrjwMfSCnHeEA6uHTle/SKR5h2C8gOOPSOYwQbaxTsVkfDzqOxtZ0D+eec2t8BkBzuixBworffo60RavIdJ5i96WiHQ++qXCm/SJpaO9h35hyLk63795sdH4SUcKCgBuIXwZnt5x8WffYA0iuQ3TX+DvF3gOVmq41CiBvEEPZGUsrbpJRRUkp3KWWMlPJVKWWllHKJlDJFSnmZlLLKMLfEMMdfShloeF5rOLdGSpkqpUySUj47jJ9xVDJ/Qgj5VY3dyV4AEZMh8ULY+Tdob3GccGOFgl0qys3gcN6bd462DslCK4R42hIvd1cSQnx6RVwZIuDLxpDfI3eTCnGfeScAe/KqaO3oPO/8jt7MiA3ERRgq7MYvhIYyZS47H84eoCV8Oq3t0iGRVmC58ngQWAW0CCFqhRB1QohaG8qlGYSufA/TUiUAix5RH4gjqxwg1RijYLfqUe2iPkbbcitwdxXMSQhysGCDkxLeq8ZVWJo6lo+hiKsDb4JPGKSqdLRtOervNzfRuv4qPy930iL9DcpjkRo8s234F2xrhrJjVPgrhe/UOw8ppZ+U0kVK6WHYHfhJKe1bwlHTg4mRfgSO6+X3AFUoMXIqbHt+7Nmv7UlzrXJamjjLd+RWMjM2iHEebg4UzDKSw33Jr2ykzRhx5R0IfuPHTrhuQwVkrVWmXlfVfW9rTgWz4mzz98uID+JA/jk6gpOVwjqzffgXKz0Kne2c8UgFcEh2OVieYX6huYethdP0j9HvsaO38hACFv0YKk7Cic8cI9xYoGgvILuc5TWNbRwpqmGhle3ltiI53Jf2TsmZSpOIq/CJY0d5HH4fOtth5l0AVDW0cvRsrVWyys0xOz6IhtYOTpTWKdPV+ew8DLlFR5iAm4tgfKBjklEtNVv91OTxBPAp8JSNZNJYyPwJIRSea6Kgqldi4ORrVX/qDb9QW1yN9SnYDcJF9VRBtZyVEhY6cX6HKUlhvgDklJkkrIVPVjcdo71GmpSw/1/K5Biu/FXGEN2hNn2yFGORxC7TVU2BasI1HM4ehHGhZNb5ER3kfV7FG88HS81WV5k8lgJTAN371MEYayftOt0r6srVDVb8Bs6dhh0vOECyMUDBLghPBy9lvd2RW4G3uyszYgMdLJhlJIUr5ZFb3kt5tDerEOTRTNF+5dsxOMpBKQ8/LzemRgfY5C1jgryJ8PdU+R7xC9XgcExXnR2QswHi5pN/rok4BznLYfhVdQuBobfX0liV1HA/gsa59+zvYSTpEph0FXzzh7Fd8M4WdHZA4V6IndM1tC23kjmJwXi4jYwuB76ebkT6e/VUHhGGiKvR3hjqwL/AzRvSrwdUy+BvsitYMOH8SrAPhBCCjIRg9uZVGW46AoZnujqzDepLYcoNnKlsdH7lIYT4qxDiL4bHC8A3wH7biqYZDOX3COnrNDdy+bOqx/ma/x7b5batTfkJaKntcpaX1TaTU1bPIifP7+hNcrgvuWW9qusKF1WefbTS2giZ/4b0a7t2jcaQd1uZrIzMiQ/ibE0zRbUtELdweDuPI6vAw5ea2CXUNLU5LNIKLN957AX2GR47gMeklHcOvERjDxYkhVBUbcbvARAUD5f8D2R9Dsd0syirUbBLHQ3OcmMJ9pHi7zCSFOZDbnlDd1dBd29Vp2s0lyk5/olS/AZHOdBVgt3a+R29yUhQIcB7Tlcp01VljqroaymNVXB4FUy+lnxDlHWcgyKtwHKfx0rjA1gD1A22RmMfzPb36DHh+xA1A9b8VP3zac6fgt0q3DIoEYDtuRUEeLszefzIil5PDvelvqWd0lqThNKI9NFttjrwFgRP6PY7oPwdUQFeTLBxNz5V9sSDz48Um+R7DGH3sedVaG+ChT/gTFUD4LgcD7DcbPWVEMJfCBGMMlf9QwjxJ9uKprGElHBfgn08+obsGnF1g2teVL2T1/3MvsKNVozFEIVASsm2nEoWTAjB1cX+xenOB2PEVU+/R7rqtW2tsuHORNUp1TBtxh0qpB26SrAvslIJ9oFwdRHcODuWTSfKKPFJAw8/OLXZssVtzbD7ZdU1NHxSV4i10/s8gABDuZDrgTellPOAJbYTS2MpLi6C+ROC2XWqqtv80JvIKbD4J3D4Pcj+0r4Cjjbqy9SXkMHfUVDVRFF104jJ7zAlOdxMuG5EujqOxnyPA28rn86M27uGjp2tpbqxzWb5Hb25bW4sHZ2SD/YXq5paJ9ZYFhp9+D1oKIdFPwIgv7KRUF8PfDwdl5BqqfJwM5RQvxnQmWdOxvwJyu9ReK6p/0kXPqrMLJuf1c7z86FXMcRtucYS3iPL3wEQ5ueJn6db33BdgLJRVn+0swMOvgPJl4H/+K7hb3JUBWp7Kf/4EB8WJ4fy/p4COideqaoyG31o/dFcA1//TpV0T7gAgGPFtV07R0dhqfL4FaqybY6Uco8QYgKQbTuxNEPB6PfYbvgiM4ubp6p7dXY/nN5iJ8lGIQU7wdUDxs8AVAnvSH8vksIc57gcLkIIJoT79tx5BMaDu8/oi7jK3Qx1Z3vkdgB8eayU9PH+dm0ZfNvcOIqqm9jKTHD1VJV9B2LDL5TsV/wRhOBcQyuZZ2ts7uAfDEsd5quklNOklA8bXp+SUt5gW9E0lpIS7kuYnydbc/rxexiZfhv4hMO2P9tHsNFIwW7VctbNk45OybbcChan2N5ebiuSw3x77jxcXFS+R+ko23kcege8gyF1RddQeV0LBwqqWTp5sG7Y1mXp5AhCfT3414EqmHWX2hGdO2N+cnsrHPlQmdpiMoDuagYjQnkIIX5rcJi7CyE2CiHKhRA6VNdJEEKwODmU7TkVdHYOYJJy94IFD6tS1GcP2k/A0UJ7i2rCYwjRzSyqobqxjQtsnB9gS5LCfSitbaG22aRFT/hkZbYaLebN1kbIWgeTrwG37iZdm06UIiV2Vx4ebi5djvOy6d9XfpiNvzI/uWCXai+d9q2uoa05Ffh6ujE9xjbZ8JZiqdnqcoPD/EogD0hG1bnSOAmLkkOpbGjt2eDHHBn3gWcAbPmdfQQbTZw9CB2tEDsfgG+ylb3cXs5WW5BssJufKm/oHoyYoqLz6oodJJWVydkAbQ2Qfl2P4Q3HSokO9GZylP1DrI2O8/eyOlQwS+aHcPKLvhNzvgQXN9Wnx8C2nArm2zAb3lIsdpgbjlcAq6SUNTaSRzNMFhkcfsYCb/3iFQALvq8q7hbpIgFDoldy4DfZFaSP9yfEii1L7U2S2YgrY5mSUeL3OPqxyssx5laguj5+k13B0skRDjE5mjrOOxb9lypkuva/ezZx62iDY6shbgF4qtbBBVWNnKlstHq3w+FgqfL4TAhxApiN6ioYBgxYrlUI8ZoQokwIkWkyFiyE2CCEyDYcgwzjwlD6JEcIcVgIMctkTYcQ4qDhMeb7l/dHVIA3SWE+XdmyA7LgYRgXovI+dM8PyyncA0EJ4BtOfUs7+/PPcUFKmKOlOi/igsfh7ipGb8RVayOcXK/qvLl2h7V+k11BS3un3U1Wphgd51tO1cLyX6tCpp//BPa+rnxre/6pxhb8oGuNrav/DgVLHeaPAwuBDEP/8kbgmkGWvQEs7zX2OLBRSpkCbDS8BlgBpBgeDwB/M1nTJKWcYXhcbYm8Y5XFyaHsPl1FS/sgceOefrD0Vypy6OBb9hFuNFC0v6sE+65TlbR1SC50gg/x+eDu6kJ8iE/PGlfjglVjqNHgNM/+QvVmN2Oy8vNys3rXwKGgHOeevLkjT4UQz39Y5aJ89mN4dSmsexwSL4LUZV1rtuZUEOHv6fAwXbDcYT4OeJjuL/XxQMZAa6SUW4De9TCuAVYanq8ErjUZf1MqdgKBhrwSzRBYlBxKU1sH+89UDz55+u2qONuGX6iuapqBqSuF2sIu5fFNdgVe7i7MHgEtZwcjOcyXnPJeGeURk0eH2cqMyaqjU7LpRBmXpIXj7kC/gYebC7fPi2NzVjmnKxpg+f/BI4fg+3tgyS/g8mfg1re7suE77ZgNbwmW/uZeB1pRuw+AIuCZYbxfhJTS6IUrAYx7xmigwGReoWEMwEsIsVcIsVMIcS2aflmQFIKPhytv7+on7M8UFxe48o/QUqfLlliCoXsb45VF9ZvscuYlhuDp5upAoaxDUrhPz5a0oDLNK7KU3X2k0tqgdh6TrgaX7r/T/vxzVDW0OtRkZeTO+XG4uwpWbs9TA0HxEJYKF/w/WPjDLl8HqMTAqoZWpwnQsFR5JEkpfwu0AUgpG4HzUn1S1dKwJBYwXkqZAdwO/FkIkdTfRCHEAwZFs7e8vPx8xBuR+Hm5c9eCBD4/UtzTht0f4ZPggkfhyAfKMafpn6J9IFwhahpnq5vILW8Y0SG6pnS3pDWJuApPV5FllTmOE+x8GcBk5e4quDjN8f6qcD8vrpw2nlV7C3qGS5thm52q/1qKpcqjVQjhjeHL3vAF3jLwErOUGs1RhmOZYbwIiDWZF2MYQ0ppPJ4CvgJm9ndxKeUrUsoMKWVGWJjj/zEcwXcuSMTTzYUXN1v4ob/wUVV199Mfq7pNGvNkrVUmKw8ftmarD/FId5Yb6W5Jaxqua6hxNZL9Hkc/VkmxJhV0pZRsOFbK/Akh+Hm5O1C4br69KIGG1g5W7e2/aVtLewerD54lJdyXCH/H9CzvjaXK40lgHRArhHgb5ez+72G83yfAPYbn9wCrTcbvNkRdzQdqpJTFQoggIYQngBAiFFgEjAJDrO0I9fXk9rnxrD54lvxKMz0+euPqDte9rLb4nz4yehLDrEnZCVWmfOqNAGzJLifcz5PUCMc7La2B2eq6oakqv2CkKo/WBpU3MbmnySq3vJ7TFQ1c7gQmKyPTYgKZHR/Eyu15dJhJ8pVS8rOPjnCsuJb/WprqAAnNM6jyEMozcwJVUfde4F1U1NVXg6x7F9U4Kk0IUSiEuB94DlgqhMgGLjO8BtUj5BSQA/wD5ZwH1ep2rxDiELAZeE5KqZXHIDx40QRcXQR/+9rC3Uf4ROWgy1ozeJ2dsUjmv1UW8ORr6eyUbMsZ2SVJeuPj6UZUgFfPiCs3D6VARmpjqJPrVe+LPiYrtbu+zImUB6jdR35VI5tO9N39v7zlFB/tL+LHl6XwranOE0c0aD1fKaUUQqyRUk4FPrf0wlLK2/o51aeUu8H/8X0z49uBqZa+p0YR4e/FLRmxvLcnnx9cmkJ0oPfgi+Y/rLqsbXhSlXHwGHmF/mxCR7tqIDThEvCL4GhhDeca27hwlJisjCSZi7gKn9xdRXikcWy1MlnFLegxvOFYCVOjA4gKsOAzYUeWpUcSFeDF69tO93Dkf3G0hN+sO8GV06J4ZEmKAyXsi6Vmq/1CiDk2lURjVb53sYor+OMXJy1b4OICS5+GhjLY+bfB548VsteriqYZ9wHKZAXO47S0FsZ+5j16wkROgZr8kdeBsrNDNVlKvbyHycpYCPGySc616wCVb3PXgni251ZyoqQWUL1Gfvz+QaZFB/D7m6Y73U7XUuUxD9gphMg1ZIAfEUIctqVgmvMjOtCb+xdP4N/7CzmQf86yRXHzVNXRbX8ZeV8YtmLPqyphLlXlu35xtIRpMQGE+Y3ckiTmSArzoaG1g5Jak8IR4w2xKcUjrIjm2QOqB8aES3oMbzzumEKIlnLbnDi83F14Y1se5XUtfPfNvfh7ufPK3Rl4uTtfSLilymMZMAG4FLgKVSDxKlsJpbEOP7g0mXA/T5765OjA1XZNWfIEtNTCVt1lmKrTkLsRZt8Drm4UVTdxqLCG5VMiHS2Z1THWuMo1jbiKUj1LOHvAARKdB7mbANFHeRgLIU6K8jO/zsEE+Xhw3cxoPj5QxHdW7qGyoYV/3pPhNNFVvRlQeQghvIQQP0ZV0F0OFEkpzxgfdpFQM2x8Pd14fMVEDhXW8OH+/sMAexCRDtNvhV0vQ3XB4PNHM/teV7kds+4GYF1mCQArpjiP09JaJJuLuPIOhOCkkVdAM3ez6rrn0108sLG1na05jiuEaCn3Lkykpb2TQ4U1/OnmGUyJdmzZ9YEYbOexElWG5Aiq/tQfbC6RxqpcOyOaWXGB/HZd1qBJSF1c8r/quPnXthPM2WlvUY7ytBVdbUvXZRYzMdKPxNDRF0wQ5ueJn5dbz+q6oExXI6n3S3MtFO6GpEt7DBsLITpTiK450iL9+MElyfz6uqmscKLIKnMMpjwmSynvlFK+DNwIXGAHmTRWxMVF8NTV6VQ2tPDXjRZ2Dg6MhXkPqrDdkszB549Gjn8KjZVdjvKy2mb2njk3KncdoBqKJfXuKghKedQWjpwE0ryt0NneR3mszyzB38uNOQ4shGgpjy5L4/Z5cY4WY1AGUx5dt6pSynYby6KxEdNiArklI5bXt+X1vbPsjwt+onp/fPmkbYVzRqSE7X+FoMQuu/n6oyVICSumjj5/h5Hk3v3ModtpPlL8HrmbVA92Q88VUCardUdL+NbUKIcWQhxtDPabnC6EqDU86oBpxudCiFp7CKixDo8uS8Pbw5VffXasZzhmf3gHKQWS86W6mxtpnDsD5/KgMhdqiobWt+TE5yrC6MKfqhBmYG1mCRPCfEgJHx1Z5eZICBlHWV0LTa0mJf2jpgNiZCiPlnrVkS/5UnDrjoZbf7SExtYOrp8V40DhRh8DKg8ppauU0t/w8JNSupk8t3/vRs2wCfX15MeXpbLlZDkbj1togpj7gApT/fKpkVG2pLMT9r8J/1gCz0+D56fDX2fBnybDCxmw+x+qbMVANNfA+p9BSApMuwWAqoZWdp2u4ltTopza2Xq+xAaPA6DwnElZG09fCEsbGU7z/StV+9yFj/QY/mh/ETFB3mTEj/zy+c6E3sONIe5eEE9yuC+/+uwYzW2DNIwCcPeGix9XHfROWFxcwP40VMD2F+CfS+CTH0Jbk0p4vPoFuPbvsOJ3ygS35lH44yTVw6Su1Py1Pn9U7VSufamr89yGYyV0dMpRGaJrSpxBeeRX9aqJNn6mKknvzDcQZw/ApmdVr+/Y7nzm0tpmtuVUcP3MaFxcRq/idwRaeYwh3F1dePKqyeRXNfK3r3ItWzTjDnUXvvlZ52xZm7NR7TC++F9ob4ZrXoSHtsGiH8Gsu2DGbTDvAfjuJrhvPUy4WPkz/r4YTn/T81qHV6ny9Bc91sNmvuZICbHB3qSPH92b7X6VR/RsaCiH6nwHSGUhn/xQmVqv/0eP4dUHi+iUcJ02WVkdrTzGGBekhHHtjPG8sDmHPXkWZJG7uinbf9kxOLnO9gJaQlszrP9f+MtMeOt6CIyHh3fBwztg5p1dndd6IATEzYeb34SHtqvaXSuvhH9/VzXEam1UCig6QzXiMVDT1Mb23ApWjHKTFUCwjwc+Hq59lYdRkTprnavSY1ByRN0w+HXvDqWU/HtfETPjAkdleLWj0cpjDPL0tVOICfLmkXcPUN3YOviCKTdAUAJseAIaKm0u34B0dsCqe2HHCxCSDMufg/vWqsrAlhI+Se1OLnpMOVj/MBFeXw71pbD0l13mKlAlLdo6Rr/JClS4bmzwOAp6K4/wdPDwVT3vnZHD76tkzvTrewwfK64lq7ROO8pthFYeYxA/L3f+cutMyupaeOzfhwePvnJ1g2tegppCeOdmdefvKHb/A06uVX6MO1bB/IeUP2OoePjAJf8D930B026GxnMw6SpIWNxj2trMEqICvJgRE2ilH8C5iQse13fn4eoGMXMgf5djhBqIQ+8pM2TqcvDtWen4w32FuLsKrnTyZLuRilYeY5TpsYH89/I01h8t5a1dFtiyExYpe3LRXuV4doTz9PQ3sOlpSL4M5n7XOteMnQNX/gn+6wjc8laPU/Ut7Xx9spxl6ZFjxtlqVB59biji5quGWE0WFtm0By11sOanEDsPrutZCbqstpl3d+dz5bTxBPl4OEjA0Y1WHmOY7yyewIWpYTz92TGOF1uQtjP5atXz/MC/VN0ne1KeBf+6TpUKuep5834NK7P5RBmt7Z2sGAMmKyNxIeNobuukvL5Xl+mkSwGp6kY5CwffVUU8L3+6z+7z+Y3ZtHdI/usy5+m8N9rQymMM4+Ii+OPN0wnwdueH7x6gsdWCIgKX/A8kL4U1/21fM8a251Vb1HvXQIB9bNjrMksI9fUgI8H5S1pYC2OuRx+/R/RsFc2UvcEBUvXDvjeUXDEZPYZPVzTw3p4Cbp8XR1zIOMfINgawqfIQQrwmhCgTQmSajAULITYIIbINxyDDuBBC/EUIkWPoGTLLZM09hvnZQoh7zL2XZniE+nryp5tnkFtez68+taDlqIsr3PAP9QX+/p32Cd+sKYLDH6jqtr726eDX3NbB5qwyLk+PxHWMmKxggHBdF1dIWgI5G5wjZLumEMqO9mkzC/DHDSfxcHXhB5cmO0CwsYOtdx5voEq5m/I4sFFKmQJsNLwGVbU3xfB4APgbKGUDPIlqSDUXeNKocDTWYXFKKN+7KIn39hTw+eHiwRd4B8Ft76nKs2/frLKybcnOl0B2woI+nYptxtcny2ls7eBbo7QQYn9EB3ojBORXNvU9mXyZyvcoPWJ/wXpj3AElL+0xnFlUw6eHznL/4kTC/ZyzD8ZowabKQ0q5BeidTHANqtQ7huO1JuNvSsVOIFAIEYVqRLVBSlklpTwHbKCvQtKcJz9ZmsqkKH/+/OVJy2pfhU+EW96Eymz46AHbCVZXqswTU26AoHibvU1FfQsbj5fyhy+yuOvVXTz6wSECx7kzb8LYMVkBeLm7EunvxZkqM2VcJlysjs7g98j5EgJiVekUE/785UkCx7nzwEUTHCTY2MFt8ClWJ0JKaby9LQGMBZFHy0gAABoSSURBVPajAdPuQ4WGsf7GNVbE3dWFexfG89i/j7A/v5rZltQBmnCx6v2x8ZfqTtAntLsKqzVob1Wmsc4OuPBRq122ua2DzKIaDhZUdz0Kz6k7bVcXQVqEH1dOH8+Ns2PGZBVWs7keAP5REDZJ9Qdf/GP7C2akvRVOfQVTb+oROHG6ooEvj5fxyJIU/L3cHSffGMERyqMLKaUUQlgt5lMI8QDK5EVcnPPXw3c2rpg2nl9+eoz39+RbpjxA9bvY8jt4+0bl0P7uJkMlViuQvV419rnulT53mENl04lSNh4v41BhNSeK62g3tOWNDvRmRmwg9yxIYHpsIFOi/Rnn4dCPhcOJCx7HN9nl5k8mXaL6urc1qdpnjqBgJ7TWQ0pPk9XK7Xm4uwrumK8/+/bAEZ+SUiFElJSy2GCWMpZ4LQJiTebFGMaKgIt7jX9l7sJSyleAVwAyMjKcuIqbc+Lr6cZV08bzyaGzPHHlZPwsuXvzDlTVd498CJ1t8PFD8OCWHlnaw+b4p8q/MuWGYV/iXEMrP1+dyeeHi/HzdGN6bCAPXjSBGbFBTI8N0HZxM8QFj6O0toXmtg683F17npxwifJB5e9UisQRZG8AF3dVBNFAbXMbq/YWcNW08fpvaiccoTw+Ae4BnjMcV5uM/0AI8R7KOV5jUDDrgV+bOMkvB35mZ5nHDLfMjeX9vQV8driY2+ZaeAd32VOw5EnI+lyZmfa9fv5JfO0tkLVOZX1bqIjaOjr5zsq9NLV2kBrpy/hAb17flkd1Yys/XZbGgxdOwG0MmqGGSpxJafbkcL+eJ+MXqi/uU5sdpzxyvlRJi57dsq3aW0hDawffXpToGJnGILYO1X0X2AGkCSEKhRD3o5TGUiFENnCZ4TXAGuAUkAP8A3gYQEpZBTwN7DE8fmUY09iAmbGBpEb48t6egsEnGxFCNU2aeKW6G9z87PllIteVwCsXQ0sNTLV817H64Fm+PllOfUs7qw+e5bfrsgjx8WD19xfz/UuSteKwkNj+wnVB9feInes4p3lNoSrSaWKy6uiUrNyeR0Z8EFNjhlGqRjMsbLrzkFLe1s+pJWbmSsBsLKaU8jXgNSuKpukHIQS3zInj6c+OcaKklomRQyhDLgQs+z94+QL46jew4rnB15jjiydUB8Bb3urTi7o/OjolL23OYXKUP5//SNWnqqhvJWicu1YaQyTekFiXX2lGeYAyXW1+RvVR8Qm1o2SoEvzQI0R304ky8qsaeWz5EIpjas4b/anS9OG6mdG4uwreH8ruw0jkFJh1D+x+GU5+MfT1uZtVT42FP1QmKwv57PBZTlU08MNLkxFCIIQgzM9TK45hEOLjwTgPV/KrzOR6QLe56vTX9hPKSM4G8I9WlZENvL7tNOMDvFiWHjHAQo210Z8sTR+CfTy4PD2Sjw8UWdZxsDeXPwMRU+DDb0NJ5uDzjdQWw0ffhbCJqn+6hXR2Sl7cnENqhC/L0sdOHSpbIYQwX13XSNQM8Aywv+mqow1Ofa2SFQ0huidKatmeW8ldCxL0jYKd0b9tjVlunRNLdWMbXxzrp13rQHj6wu3vK4fm2zdC3tbB13S0w4f3qaZMN7+pSqZbyBfHSjhZWs/3L0keM9VvbU2/uR6gAhgSL1C5FvasrlywSxVCNPF3vLEtDy93F26bGzvAQo0t0MpDY5ZFSaFEB3rz/p5h1q7yHw93fAhuXvDGFfDeHVDfT+4AwKZfQf52VTF3CDkdUkr+uimHxFAfrpw2fniyavrQb2l2I0mXQE2BqnZsL7I3qFyixIsAqGpo5eMDRVw3M5rAcbrsur3RykNjFhcXwS1zYtmWU9m/43QwIqfA97bCJT9X4ZWvXKycrEY6O9Xd68ffU1VzM+6DaTcN6S02nSjj6NlaHr44aUwVMLQ1ccHjaGrroKK+n06TaVcAAo79x35C5XwJcQvASwVxvLs7n5b2Tu5dqMNzHYFWHpp+uXF2DELAB3uH4Tg34ukLF/0Uvr0GGspUHawDb8G+lfDSPHjzGji2GuY9pCK1hoCUkr9syiEmyJtrZ+qKNdak3+q6RvyjIH4RZH5kH9NV7VnVjCr5MkDl9PxrxxkWJYeQFuk3yGKNLdDKQ9Mv4wO9uSg1jA/3FdLecZ5luKNnw6VPQO7G/9/enYdXVZ8JHP++2YGEQEJYDASSsMu+hB2ttqjoUwTqSG3VyrQWpa08rXRo68zY1k5rny5jtYpWa7FT96VuLSMiI7UhREBW2bIQtiBwQ4jsSe47f5wTCJgb7k1y77lX38/z3CfnnntyzvvjJLw5vxVenQ+vfwfik2DW47Cw1OnWmxjayOD3Sg6zYU81d17e9zM5B1U4BVzXo7EhM+HwdmfcRbiVvO18dds7lm4+wIGaU9xmTx2esd8406w5Y3txoOYUKwPNdRSKSd9xEsW31zlzYM17z6mmSmrZgj0PLi+hR3oKs0fbU0db69nZmbcq4JMHwKAvgsTBllfCH9DOZZB2CXQdDMCfiyrondmeKwZ2Df+1TZMseZhmXTGwG11Sk3j8H+X4/W1QPdGhC2TmO08irVhKtqjMR/GuKuZdlk9yQvzFv8GEpGFq9maTR2pX6DMl/FVX9bVO21jfK0GEY6frWFtxhOuG9bDedR6y5GGalZQQx11X9qOw1Mfv3tnpdThAQw+rnXRJTebGsdZFM1yaHevRYMgsqCqFvWvCF8ie4vO66K7ZVUW9Xxmflxm+a5qLsuRhLuqr43sza1Q2//32Tpa1ZNxHG6qr93PPXzfzzxIf8y7L++Ssr6bNNDvWo8GQ2ZCUBsWPhS+QEreLbt7lAKwuryIhToJfNsCEhSUPc1Eiwn/NHMqQ7I5897n1lB465kkcNadque1P7/OX1bu54/J85toMqmGVk9GeAzWnmp9lIDkNRn7Fafeo2R+eQHa+Db3GQYoz6WFRmY/hvTp95tdd8ZolDxOUlMR4Hr15DIkJcdz+1Bo+PlUb0evvPXKCLz1SyKpSH/fPHsq/XT3Q6rvDLCezHaqwrzrAHFcNxt8BKPzj120fRFW5s2Z6f2fl6eOn69i49yjjP2PLA0cjSx4maNmd2vHQTSPZ5TvB957f0DYN6EFYv6ea639fSOXRUyyZW8CNY22luEg4O9bjYoNEO/eBkTc7Y3eOVLRtEA2DEAfPAGBtxRHq/cq4XGvv8JolDxOSifld+OH0Qbz14Uf8fkVJ2K/3t02V3PjoKlIS43j5jolM6hvhKcA/w5pd1+NCUxc63Xbf/WXbBaDq9OTKHg2dewNOlZW1d0QHSx4mZHMn9eH6EZfwm7d38M628DWgb9p7lPlPr2PwJR356/xJ9OtmI4kjKSs1mZTEuOCSR3o2jP06bHgaDm5tmwDKVsCBjTD83LJARWU+hvVMp0OytXd4zZKHCZmI8PNZwxjUvSN3Pbue8sPHw3KdJwvLaZ8Yz5K5BXRJTQ7LNUxgF52a/UJTvuc0ar95d+vHffj9sPynkN4LRt0CwIkzDe0dVmUVDTxJHiJyl4hsFpEtIrLA3TdcRFaJyCYReV1EOrr7+4jISRFZ774WexGzOV+7pHgevXk0CXHC7U+t4djpujY9f9XxM7yxsZKZo7LpmJLYpuc2wcsJprtugw6Zznr2Fe/B6lb+mq79I+xfB1fcAwnOHw5rK45Q51fGWfKIChFPHiIyBPgGUAAMB64Tkb7A48AiVR0KvAIsbPRtpao6wn3Ni3TMpmm9Mtrz0E2jKD10jLuf3xB4+u4WeO79PZyp83PLhD5tdk4TupyMDs1PzX6hUbdC/2ucpYRbOnCwZj8su9cZ1zHsxrO7i8p8xMcJY6y9Iyp48eQxCFitqidUtQ54F5gF9AdWuscsA2Z7EJsJ0aS+XfjBNYNYuuUAD/9faZucs96v/E9RBeNyM+hv7Ryeyslox4kz9fiOB5ia/UIiMPMRZ9bdF74GJ6pCu6CqU+3lr4PrfnveFDZFZVXW3hFFvEgem4EpIpIpIu2B6UAvYAswwz3mBndfg1wR+UBE3hWRKZEN11zM16fkcu2wHvx22Q4qfK1v/1ix7SD7qk/aU0cUyMkMocdVg3ad4YYlcOwjeOFWZ5XIYPjr4R+/gu1vwud+CBl5Zz9y2juqrb0jikQ8eajqVuB+4C1gKbAeqAfmAneKyFogDWj4U6cSyFHVkcB3gacb2kMuJCK3i8gaEVlz6FAbzAJrgiIi/Od1g0mIF36zbEerz/dUUQXdOiYz7dJubRCdaY2cYKZmb0r2KGdVyPKVsOzfmz+27gy8cBv8Mg/euc8Z0zHx2+cdsq6imtp6ZVyuDQ6MFp40mKvqE6o6WlWnAkeAHaq6TVWnqepo4Bmg1D32tKr63O217v7+Ac77mKqOUdUxWVlZkSmMAaBrxxTmTsrl1fX72bL/aIvPU374OCt3HOLLBTm2RkcU6Nk5yIGCTRlxk7PIV9HDzviPQO0m65bAlpedUeQ3LIHZT3xixuWz7R19LHlEC696W3V1v+bgtHc83WhfHHAPsNh9nyUi8e52HtAPKPMibtO8b16WT3q7RH71vy1f1/ovRRUkxAk3Fdgo8miQkhhPt47JoVVbNTbtPhg2B1b8zFk1cvtSZy17vx+K/wCPTHIa13tPgpmL4dLrIf6TveuKynwMzU4n1do7ooZXd+IlEckEaoH5qlrtdt+d737+MvCkuz0V+ImI1AJ+YJ6qhtgKZyIhvV0id1yezy/+vo3VZb6Qu1SePFPP82v2cNWQ7nTtGNqqgiZ8QhrrcaH4BCcp9BzjJJBn3N5TnXpDdQX0HAsDp8Pk7wZc3+XEmTo27K1m7mSbCDOaeJI8VPUTjd6q+gDwQBP7XwJeikRcpvW+NrEPT/6znPuXbuPFeRNDmrzwtQ37qDlVxy3je4cxQhOqXhntKSr1tfwEIlDwDWew3+5Vzvocm16E6b9yRqVfZFGwNbuOUFuvTMq3qWmiiVUqmzaVkhjP96YNYN3uap59f0/Q36eqPLWqggHd0iiwRtGo0jujA5U1pzje2oGgCcnO2I3Lvg/fKnYSShCrSRaW+kiMF8b0sfEd0cSSh2lzN4zuycT8TH7+t61UHr3IdN6udbur2bK/hpsn9EZasTytaXvDe6WjCh/srvbk+qtKDzPC1u+IOpY8TJsTEX4xaxi1fj/3vLI5qNHJf161i7TkBGaOzA5/gCYko3t3Jk6guLwVVVctVHOqlk37jjLBqqyijqVyExY5me25e9oA7ntzK6+u38+Vg7py7HQdH59qeNWefV9zspa/bTrATeNybPRwFEpLSWRIdjpF5ZHvp1JcVoVfYWK+DQ6MNvabasLmtkm5vLGxkgXPrb/osanJCdw6sU/4gzItUtAng6eKKjhVWx/RdeMLS30kJ8QxMqdTxK5pgmPJw4RNfJyw+KujeXHtHpIS4khLSSQtJYHU5ATSUhLpmJJAaoqz3T4x3paVjWLj8jJ5/L1yNuypjuistoWlhxnbJ4PkhMglLBMcSx4mrLqnp/CtK/p5HYZppbFuT6fi8qqIJQ/fsdNsO/AxC6+6JCLXM6GxBnNjzEV1ap/EwO5pFO+KXLtHUZlzrQnW3hGVLHkYY4IyLjeDtRVHqK33R+R6haWHSU1OYFh2ekSuZ0JjycMYE5SC3ExOnKln876WT3wZilVlPgpyM0iwCTKjkt0VY0xQGkb+F0egy+6Bo6coO3TcuuhGMUsexpigZKUlk5fVgdURSB6ryg4D1t4RzSx5GGOCNi43g/d3VVHvb7v16ptSWOKjU/tEBnVvct03EwUseRhjgjYuN5OPT9WxtbImbNdQVQpLfYzPzbSxP1HMkocxJmiRaPfYU3WSfdUnmdjXqqyimSUPY0zQLunUjl4Z7cKaPBraO6yxPLpZ8jDGhKSgTybFu6qCmi25JQpLfWSlJZOflRqW85u24dUa5neJyGYR2SIiC9x9w0VklYhsEpHXRaRjo+N/ICIlIrJdRK7yImZjjGNcXgZVx89QcvBYm5+7ob1jYn6mresS5SKePERkCPANoAAYDlwnIn2Bx4FFqjoUeAVY6B4/GJgDXApcDTwsIjZLmjEeGee2ewSaor223k9xecueTEoPHePQx6eZEMHJF03LePHkMQhYraonVLUOeBeYBfQHVrrHLANmu9szgGdV9bSqlgMlOInHGOOBnIz2dOuY3GS7R129nwXPredfHl3FC2v3hnzuQnet9Im2+FPU8yJ5bAamiEimiLQHpgO9gC04iQLgBncfQDbQeDHsve4+Y4wHRIRxuZkUl/vOe7qo9ysLX9zImxsr6dQ+kYdXlFAX4jxYhSU+st1GeRPdIp48VHUrcD/wFrAUWA/UA3OBO0VkLZAGnAn13CJyu4isEZE1hw4dasOojTGNFeRm8FHNaSp8JwDw+5VFL23klQ/2sfCqAfxi1lB2+U7wxsbKoM/p9ytF5dbeESs8aTBX1SdUdbSqTgWOADtUdZuqTlPV0cAzQKl7+D7OPYUA9HT3NXXex1R1jKqOycrKCmcRjPlMG593bryHqnLPq5t5Ye1e7rqyH/M/15dpg7szoFsaD60owR/kaPStB2qoPlFr4ztihFe9rbq6X3Nw2juebrQvDrgHWOwe/howR0SSRSQX6AcURz5qY0yD/KxUMjokUVTu48evf8jTq3dzx+X5LPi8s/BXXJww/4q+lBw8xtItB4I65yq3vWNCnrV3xAKvxnm8JCIfAq8D81W1GviyiOwAtgH7gScBVHUL8DzwIU4113xVrfcmbGMMOO0eBX0y+OsH+/hT4S6+PjmX71814LzqpmuH9iCvSwcefKckqJ5XhaU+8rp0oHt6SjhDN23Eq2qrKao6WFWHq+pyd98DqtrffS3SRj9tqvozVc1X1QGq+ncvYjbGnG9i30z8CrdO6M2Prh30iXaK+Djhzs/1ZWtlDW9vPdjsuWrr/awu89ksujHE1jA3xrTIlwtyyOuSyqS+gRu4Z4y4hAeW7+Chd3by+UFdAx63ad9Rjp+pty66McSmJzHGtEhifByT+3VptmdUYnwcd17elw17j7Jy5+GAxzW0dzQ0xJvoZ8nDGBNWs0f1pEd6Cg8u3xmw7WNVqY+B3dPITE2OcHSmpSx5GGPCKikhjnmX5bOm4girynxn96sqH+w+wk/f+JDi8ipr74gx1uZhjAm7G8f24qEVJTy4vIT0dom8vqGSNzbuZ++RkyTFxzG1fxa3T83zOkwTAksexpiwS0mM55tT87jvza1c+7v3iI8TJvftwoLP9+cLg7uR3i7R6xBNiCx5GGMi4ivjerP3yEn6d0vj6iHdyeiQ5HVIphUseRhjIqJdUjz3fvFSr8MwbcQazI0xxoTMkocxxpiQWfIwxhgTMksexhhjQmbJwxhjTMgseRhjjAmZJQ9jjDEhs+RhjDEmZBLMCl+xSEQOARUt/PYuQOD5o2OLlSX6fFrKAVaWaNXSsvRW1axgDvzUJo/WEJE1qjrG6zjagpUl+nxaygFWlmgVibJYtZUxxpiQWfIwxhgTMkseTXvM6wDakJUl+nxaygFWlmgV9rJYm4cxxpiQ2ZOHMcaYkFnyaERErhaR7SJSIiKLvI4nVCKyS0Q2ich6EVnj7ssQkWUistP92tnrOJsiIn8UkYMisrnRviZjF8fv3Pu0UURGeRf5JwUoy70iss+9N+tFZHqjz37glmW7iFzlTdRNE5FeIrJCRD4UkS0icpe7P+buTTNlibl7IyIpIlIsIhvcsvzY3Z8rIqvdmJ8TkSR3f7L7vsT9vE+rg1BVezlVd/FAKZAHJAEbgMFexxViGXYBXS7Y90tgkbu9CLjf6zgDxD4VGAVsvljswHTg74AA44HVXscfRFnuBe5u4tjB7s9aMpDr/gzGe12GRvH1AEa522nADjfmmLs3zZQl5u6N+++b6m4nAqvdf+/ngTnu/sXAHe72ncBid3sO8FxrY7Anj3MKgBJVLVPVM8CzwAyPY2oLM4Al7vYS4HoPYwlIVVcCVRfsDhT7DOApdRQBnUSkR2QivbgAZQlkBvCsqp5W1XKgBOdnMSqoaqWqrnO3Pwa2AtnE4L1ppiyBRO29cf99j7lvE92XAlcAL7r7L7wvDffrReBKEZHWxGDJ45xsYE+j93tp/gcrGinwloisFZHb3X3dVLXS3T4AdPMmtBYJFHus3qtvuVU5f2xUfRgzZXGrOkbi/JUb0/fmgrJADN4bEYkXkfXAQWAZzpNRtarWuYc0jvdsWdzPjwKZrbm+JY9Pl8mqOgq4BpgvIlMbf6jOM2tMdq+L5dhdjwD5wAigEvi1t+GERkRSgZeABapa0/izWLs3TZQlJu+Nqtar6gigJ84T0cBIXt+Sxzn7gF6N3vd098UMVd3nfj0IvILzA/VRQ7WB+/WgdxGGLFDsMXevVPUj95fdD/yBc9UfUV8WEUnE+c/2L6r6srs7Ju9NU2WJ5XsDoKrVwApgAk41YYL7UeN4z5bF/Twd8LXmupY8znkf6Of2VkjCaVR6zeOYgiYiHUQkrWEbmAZsxinDre5htwKvehNhiwSK/TXgFrdnz3jgaKMqlKh0Qb3/TJx7A05Z5ri9YXKBfkBxpOMLxK0XfwLYqqq/afRRzN2bQGWJxXsjIlki0sndbgd8AacNZwXwJfewC+9Lw/36EvCO+8TYcl73GoimF05PkR04dYc/8jqeEGPPw+kZsgHY0hA/Tr3mcmAn8DaQ4XWsAeJ/BqfKoBanrvZfA8WO09Pk9+592gSM8Tr+IMryZzfWje4vco9Gx//ILct24Bqv47+gLJNxqqQ2Auvd1/RYvDfNlCXm7g0wDPjAjXkz8B/u/jycBFcCvAAku/tT3Pcl7ud5rY3BRpgbY4wJmVVbGWOMCZklD2OMMSGz5GGMMSZkljyMMcaEzJKHMcaYkFnyMMYYEzJLHsYYY0JmycMYY0zI/h/M9b9Ks2/zVQAAAABJRU5ErkJggg==\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb44d2a5f28>"
+       "<matplotlib.figure.Figure at 0x7f69e00a7c88>"
       ]
      },
      "metadata": {},
@@ -2449,28 +2821,113 @@
     }
    ],
    "source": [
-    "plot_comparison(start_idx=200000, length=300, train=True)"
+    "plot_comparison(start_idx=200000, length=1000, train=True)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now consider an example from the test-set, so the model has not seen this data during training. The temperature is predicted quite well after the \"warm-up\" period of 50 time-steps. But the \"high-frequency component\" of the wind-speed is not predicted very well. This may be because the model needs more training epochs, or maybe the model needs another architecture, or maybe it is simply because the wind-speed cannot be predicted any more accurately 24 hours into the future using the 20 input-signals we have used."
+    "As a check, we can plot this signal directly from the resampled data-set, which looks similar."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f69f54d37f0>"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f69dbd9c588>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df['Odense']['Temp'][200000:200000+1000].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can plot the same period from the original data that has not been resampled. It also looks similar.\n",
+    "\n",
+    "So either the temperature was unusually stable for a part of this period, or there is a data-error in the raw data that was obtained from the internet weather-database."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f69db165860>"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f69db106860>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_org = weather.load_original_data()\n",
+    "df_org.xs('Odense')['Temp']['2002-12-23':'2003-02-04'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example from Test-Set\n",
+    "\n",
+    "Now consider an example from the test-set. The model has not seen this data during training.\n",
+    "\n",
+    "The temperature is predicted reasonably well, although the peaks are sometimes inaccurate.\n",
+    "\n",
+    "The wind-speed has not been predicted so well. The daily oscillation-frequency seems to match, but the center-level and the peaks are quite inaccurate. A guess would be that the wind-speed is difficult to predict from the given input data, so the model has merely learnt to output sinusoidal oscillations in the daily frequency and approximately at the right center-level.\n",
+    "\n",
+    "The atmospheric pressure is predicted reasonably well, except for a lag and a more noisy signal than the true time-series."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb45cf3c358>"
+       "<matplotlib.figure.Figure at 0x7f69fc054198>"
       ]
      },
      "metadata": {},
@@ -2478,9 +2935,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb44c0f1048>"
+       "<matplotlib.figure.Figure at 0x7f69db1866d8>"
       ]
      },
      "metadata": {},
@@ -2488,9 +2945,9 @@
     },
     {
      "data": {
-      "image/png": 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9FrL3qk6LligRcPWEK/4CRcmQ+Ln587UT7Tw0HYsT8Upgb9pL5/WROJZXxg/7c7hiUAiebs4M7tWFN28Zxpu3xOLkdPEfbFyfbuSX1ZBa0MQ336kvqG2x+Let+ZPYju+fUB8yEx47myJqb8LHq4SH1PX2tsTyVJ+GL26F/86Hn56Fbv1UEeqYByx3j5iroddIiP+35eZsIzrmoelYHF6hpMDHPnTmUFVtA7d/uB1PN2cev7zPmePXDW++3mViH1WIFZ9SRJ/uvuef7DtdZQT98ldVODjpacv+DLakLA8SvlDZUtP/ZG9rzuLsApGXQepGpenUGYp2y/LUe+b4ZlVwOeUPSsdq8u9VEaolEULJ8vz4NBSmQLc+rV9jYbTz0HQcDAYl7dB3htqvN7L+aB6F5bUsmz+WqCAfk6YKC/AiLMCTramF3D0h4uIB172vdLM2vKLSgUe3UcvJUdi/HGSDqi1wtA/oqClqFVmc5jgrIlOprwUnFyhJV/GHvENqtVFRoLL2rnnT+nUsfa9Qj8lrtPPQaFrk+EZVZDVo7nmHVyRkE+znzvjothX2DQ31Z39mSdMnXdxh7rtKi2n1c+qD4IIAvcMjJSR8pmJDQf3tbc3FRF+uHlN+7ljOY/9X8N2DKvup6pRKPT76A7j7wfy1qkWALejaW4lUHlutightjI55aDoOuz8GzwCVWmqkvKaejUn5XDO0J85NxDZaIibYl4ziKsprmslYcXaB2f8GZzdY9RQ01Jljve3J2qMqw4ffYW9LmiYwGoKHQOKX9rbEdPKPwIpHlYPoMwP6XqlWd4F9VEMyWzmORqKnKjXo+lrb3hftPDQdhbJc9e1u+B3npZXuSCuirkEybUD3Nk/ZP0TFOo7ltSAR7tdDFc+l/WLclrCjsmldtRIuTPqp9ZauR1YpeW8XTxh0vW3saw+xt6lMpPwj9rbENHYtUnGwO76BGz5UooU3fwr3/qTeK7YmbKzKWss9YPNba+eh6Rjs+1Tt3Y+897zD8SlFuLs4MSK87TIlMSGqo11Sbiv9JUbdB9e8pQKhi6bZp+eHoQGWXQ8b/66c2LLrlUheU06kplxtq+TuV61iHblz35Cb1YfxwW/tbUnr1FWr9rsDrj2rfOvsqmov3LxavtZahI1Vjxk7bH5r7Tw0jo+hAfYsVVLpF+yNx6cUMjoiAA9X5zZPG9rVEy8359adB8Coe+HWz+FUunJktubgtypN+ep/wcx/qC2pxdNh8xsXjz30LdSWw10rYIYDZVg1hU+Qiskkr7G3Ja1zdJVqAzD8Tntbcha/HtAlXDsPjaZJUtZD6cmLVh35ZdUk5ZUR16d9zaCcnAQxIb4czCo17YI+01V9wpY3bVvZKyX8+gZ0H6h+B+Megt8cVNk22/5zfpW2lLBrMXTrf/ZbqaPT70rISVSNkhyZfcvAP1zVbDgSvccriXsbF7Vq56FxbKRUPRC8g84LlANsSy0CIK5P++XTx0YFkpBRQkVzQfNzEQLGPwansyBlXbvv2Way96rA9/hHz4rqefjBpGfVN+Hdi+HYGlj7/2DNC5CToMbaMDW3tt7ArvTi9nWybGzodewnyxplSUpOKn2q2Dscr4nVkJtV1peNhSYd7Leg0ZxDTiL8PVT9UQy/E1zczju9JbmQLp6uDOrZpd23iIvuRr1BsvN4ceuDQX3Q+QQrZVpbceR7VVMQc/X5x8NGq2yfn1+Gz2+GbQth+0II7Ks+5GxEVW0DDyzdzU3vbeMP3x7AYGijA+k+UKWc7v649UQAe7H9PRWbib3d3pZcTPRU8AuFbe8o4UsboZ2HxjExGFR6rKsnjHkQxp2fxy6lJD6lkPFRgW1O0T2XURFdcXNxIj7FxCwqZ1f1wZy8Bk5nt/u+JiMlHF6p4j1N9S65/gMVMxh5L7yQA7d9qTKA2tFjPKukis92nGBraiGnKmrZnlbU6jWVtfXc/fFONicXMLV/EF/uymDTsTZ26hRCSXfk7rfL3n2rVBQqYcOhN6ttK0fDyRmm/B4yd8HSuTZzwNp5aByT5DWQtRtm/BlmvaYCq+eQeaqK7NJqJpixZQXg4erMiHB/th9v/YPyDCPmqaZR+z4z694mUZSqZNP7z2r6vKc/zF8Ds99SKcz9r2pXQeCRnNPM+b8tvPDdQe5avJN7Pt7JrR9s552NKS1et2z7CXYeL+atW2J5f94ouni6siIhq833Z9ityjk2lQBgbw7+F+qrIO439rakeUbcBVf9AzJ3QuZum9xSOw+NY7JvmYpzDLmpydOJxsrw4WHmdxIcHt6VozllVNc1mHZBQBREToZ9S9UKydKU5UHyzyqekfaLOtZnmuXvg3Ia/1mfzK0fbMfV2Yll88fi4ixIzCwlLMCT11YntZhQsCIhm2Fh/syJ7YWbixOzhoSw9nBe84WXzeHmDXFPqljSuV0OHYG0TaoDYHcz5dSbYdOxAtIKyll/JI9jeWX8kpTPwl9SWPhLiunJHKC0rly9bJYNqOVJNI5Heb6SXBj3cLMNihIzSnBzcTpT6GcOw0L9qTdIDuecNr1eZOTd8M196sPdkh/sWXvh46tU4Zd3kMqg8Q9X+kkWZktyIQ8s3U1VXQN9uvvw8T2jCQvw4tEpffguIYsvF4zjijc384/VR/nr3CHsPlHMdcN7IYyB+GN5ZRzKPs1L1ww8M+dNo8L4clcG8z/ZxZL7xrQthXrMg7BzEax4DB7crFqv2puGekj/FQZbttBSSsl3+7LwcnPmkc/24u7iTFVdAx6uTlTXnf1C8uWuk6x/agpuLiZ8z/fwU4Keh/8Hs964KEZoafTKQ+N4bH5d7duOuKfZIYkZpQzq6WfaH1UrxIb5G+dsRueqKWKuUVIpe5eaff8zNNQp6QvPrnDrF2r+mtPQO86imVPxKYW8vPIQ932yi96BXmz7w+Ws/c0kwgJUodvj0/qy4XdT6O7rwZPT+vJrciHT/7WJp75KZPmuDAByS6u5f8lufNxduGbY2crqEeFdef3GYew4Xsyq/W1MvXXzguvfh1PHlSClI5D0g/o/iDS/Y1+DQfLptnSS88p4acUhnvoqkYeW7cXLzYXegV5cP7wX0UE+XDe8F4f+dCUf3TOKjOIqvtx10vSbTP49PLzN6o4D9MpD42gcW6PqFEbe06xSaH2DgQNZpdwyOswitwzp4kGwn3vbnIeLu5JK2fYOJK9TSr/mcnwT5B9WLWFjZkHoaFj7gkVF777dm8kz3+zHWQhG9u7Ku3eOwN+r+Q+aeyZEcLqqnh8P5ODt7syfVx1mXFQgb/18jPyyar54YBzdfc9vJnXDiF68vf4YKxKyuHFk87L4TRIxEUbcrWRARs2HoH7t+TEtw/Z3lSimX6jZCrlSSn67PIGVidm4OAnqDZI7x4VzILOUG0eGMm98xEXXTO3fnRHh/izZms68cb3PrPhapGtvs+xsC9p5aByHpJ+U9EbwENWQqRkOZZ+mqq6B4eH+Frv1oJ5dOGpKpfm5TP69yv1fPg/mLoTBN5hnRNJqpUXVGBz3CVLZVBbimz2ZPP11InF9Avlg3ii83Vv/8xdC8OT0vjw5vS85pVVc+eZm7vtkF8eLKnhocjTDm9jmE0IwZ1gv3tmYQn5Z9UXOpVWmPq8q6j+6Um0J+vVSv9seQ9s2jzmc3AFrX1T/FzcsNlt+ZH9mKSsTs5k3rjf7s0q5clAwD0+ObtEhCCG4cWQYz393gEPZpxncq/0p6dZAb1tpHIOKItWuM3gw3L8OvJvPoopPVWm1E6LbV1neFOEBXmQUV7atyM3dF+78TimpfjNfOb/2IqWK80RPVenJFqbBIHl9zVFG9e7K4rtHm+Q4LqRHF0/evCWWBikZ1NOPhyY1L6N+g3HFsejX42031qc73P+z+r1m7oJt/wcfTIYv74Djv8JPv7euEm9FEXx9D3QJVbL8FtCtWpmYjZuzE09f0Z8Vj8bxyJQ+Jq0krhocgquzYGWiDdLC24heeWjsT0kGLL0WKouUflQrH57xKYXEhPgS5Ove4ri2EB7gRUVtA8UVtQT6tGFenyCY950Kcn8zH25ZqmRM2krWXijNgMnPtv1aE9hxvIi80zX8v2sGtksHrJFpA4KZNiC41XGR3by5bngoS7amc+voMJObdJ0hqB/c9T/1vKoEfv2nkj4/ukod8wmGwTe2q56lVXZ9CGU5sGCjSoU2k7LqOr5PzGZK/yC6eDWdANIcXb3dmNwviJUJ2Tw3M6bJlsr2Qq88NPalptwodV4Ed6+CXiNaHF5V28Du9FMWXXUAZ4LFGaeq2n6xmxfcvlyl8H5+i4qBtJVdi8DVGwbOafu1rfDptnSe//YA3m7OTItp/YPfUvx2Rl+83V246b1t3PXRTu5fsosTRe2ogPb0V7L4j+2CYbfDwLmqKVjyWssbDWoFGTYGesaaPdWpilruXLSD4opa7omLaNccs4f1JPd0NTvTTVRBsBHaeWjsy/Z3Ie8g3PQRhLcu5Ld0Wzo19QZmDQmxqBnhRudxsriyfRP4hsC9Pyqpja/ualuhVkWRKkQbdovqTmdBqusa+MfqJGrqDTw5vS+ebu1fdbSV0K5efPXgOAb29ON0VR1bUgp59aej7Z/Qowtc9y7csAi8u6suiZbmdI7SBmvU2zKDqtoGbvtwO0dyy3jvzpHt/sIzY2Awnq7OfLe3HcWXVkQ7D439qKuGne+rjmwmbPVkFFfy7qZUJvcLYlREgEVNCQvwPHOPduPhp5oE+XSHZTcoWRFT2PcpNNTA6Afaf+9m2HA0n/Kael6/cRgLWohRWIs+3X35dP5Y/vdoHA9Oiuang7ltK3xrCmdXtUJLWW95LafGbbF+M02+JDmvjPuX7GbvyVPnHV+yLZ2juWW8e8cIpg9s/4rPy82FucN78t2+LDJPmfH+tDDaeWjsx9FVUFEAEx5vdWhqQTk3v78Ng0HywtUDLG6Kl5sL3XzcOVlk5h+nbzDM+58q7PtqHhz4puXxhgalitt7IgQPbHlsO/g+MZsg37b3d7cG8y+LxN3Fia92Z5g/2cBrlWRIys/mz9WIwQA73oeQoWoFaQIHs0q5+f1t/HwkjzsX7WCrUSOttKqOdzemMqV/kEkxotZ4/PK+IGDhLy3LxdgS7Tw09iNtI3j4t9ofobiillve30Zdg4HlD46nX7D5VeVNERbg2f5tq3MJiIT710PYOFj5OOQebH5s8lol9z3mfvPvewFSSranFTGlX5BZ4pGWws/DlekDg/lhfw51DWbKuoRPAK/A1p1zW0hYBkXJMPE3JhVlphdWcNsH2/Fyc+Hrh8YT2tWTez7Zxb/WJvHmumOUVtXx9BVt1xlrip7+nswYGMympDaKTloRqzkPIcRHQoh8IcTBc44FCCHWCSGSjY9djcfvEELsF0IcEEJsFUIMO+eamUKIJCFEihDiOWvZq7ED6b+q6ulW+iN8n5hNYXktH90zmgE9rNdSNaqbDykF5a0PNAUXN7h5Cbj7wfI7oPp00+N2fgi+PS7qVWIJMoqrOFVZR6wF62HMZc6wnhRV1JquYtwczi4wfJ6Sqy+0wLfxxC+Vow+fAANMS1p4fW0SDVKy/MFxjI4I4MsF47m8f3f+vSGFT7amM3tYT4vWZgwP8ye7tJr8Mju0QW4Ca648PgEu3Dh8DlgvpewLrDe+BjgOTJZSDgFeAT4AEEI4AwuBq4CBwG1CCMuv7TW2pyRDtXSNbL0r24qELGJCfBkaat0PwZgQXwrKaiiuqLXMhL4hcNMncOoEbPjLxefzj0LqelVN34yGlzkkGMUjh1n599YWJvcPws/DhZUJFqhbGP+oqvRf+bhavV1IbSV8uwDeHKIkb5qj+Dj88Dv1RWbedyal/x7MKuWH/TnMnxhJaFeVbBHg7cZ780ay7reTeGRKNC/Msuz2aqOMzv4MM2NGFsJqzkNKuRm4MLdsDtDYRWcJMNc4dquUsjHatB1o1DQYA6RIKdOklLXAl8Y5NB0RKVWDp+wE2PiqOtaCZtDGpHxG//Vn9p4sYU5sL6ub1yiyeDS3mVWOHTdkAAAgAElEQVRCe+g9HkbfDzs/gMw9559b+6JamYy2/JYVKK0udwuJR1oKdxdnZg3pwZpDuVTVmqhi3Bw+3VVP95xE+GCKSpGurVAaYT8+A69Fwf6vVCLDL39XfTkupLJYNdISznDd++BqWjX862uS8Pdy5YFJURed6xvsy7MzYwjp0sbK+lYY1LMLzk7ijKK0vbF1zCNYStmolpYLNBVJmg80lur2As6NrmUaj2k6IutegvcnqWrhhGUw6Zlmg8Q/HcjhgaW7CfR24/HL+3D7WOs34YkxfsgmtVWmpDWmvaRWId8/CaWZynlufkPJj09+FrwtW7PSyP7MEgb19MPV2bFCm9fG9qSitoFfkvLNn2z4HUqB180HPrsR/tYTXummnPXg61X69Nx3QTbA0R/Ov7amHD67Sa0Mb/sC/E3TStt38hSbjhXw8ORo/Dwsv2JsDk83Z/oH+5re9dLK2K3CXEophRDnaUEIIaainMfE9swphFgALAAID3fAjl+XMtn7lMzEkJtg0PXq22DvuCaH/ndPJs98k0hsmD8f3zuGLp62+QMN8nWnq5er5Z2Hhx9c/U8lr/HmoLPHB10HYx+27L2MSCk5mlPG3OGO911rTEQAvh4u/JpcwKwhPVq/oDW69YFHtkHqBtU8q6ZMFfgNmK3OS6n6cRxeoaT0QWVWfbtA9Ye/ZRlENP1ebIpv92bh4erEHeNsJ0LYyMzBIfxr3THSCsrbXrVvYWztPPKEED2klDlCiB7Ama8eQoihwCLgKillY1u3LODcrwOhxmNNIqX8AGO8ZNSoUQ7aDPkSJfFLcHZTH6ItFMJtSy3id18nMiE6kA/vMk28z1IIIYgJ8eNwjgW3rRqJuRoe3aGql7v2Vt+Uo6aaLa9RU9+Am7PTRTpJWSVVlNXUO9SWVSMuzk6Miwpki7lB83Nx8z7rLC5ECJWQsPMDFQdx84JN/1By6zP/cXFv+BaoazDww4EcZgwMwceG781Gbh0Txn82JPPp9hP8cfag1i+wIrZez64EjK6fu4EVAEKIcOBbYJ6U8tg543cBfYUQkUIIN+BW4xyajsbxXyFsbIuOQ0rJq6uP0qOLR7vF+8xldERXDmaVcrq6jgaD5ERRBSeKKqhoa2e8pgjqr9JAB12nJNzNdBwHs0qJe3UD936y66L4QePqKcYBnQfAxD7dyCiuMr+uxlSiL4eGWjiyEta/ApteVb3oxz7Ypml2pBVTXFHLtcN6WsnQlunu68GsIT34ZnemZd6TZmDNVN0vgG1AfyFEphBiPvAqMEMIkQxMN74GeAkIBN4RQiQIIXYDSCnrgceANcAR4Csp5SFr2ayxEhWFkH+o1cyqbWlFJGaU8OQ028ponMuEPt0wSFh9MJfr34ln8usbmfz6Rmb/3xa72NMcu9OLue2D7YBg87ECXvzf+bUkjfLy/RzUecQZe883KiRbnd4TwNkdvntQiSz2m6mC7W1ssrXnxCmEwK5Fl3eNj6Cspp7v9tlXrsSa2Va3SSl7SCldpZShUsrFUsoiKeU0KWVfKeV0KWWxcez9UsquUspY479R58zzo5Syn5QyWkr5V2vZq7Ei6cYP3ohJLQ7bdKwAV2fBbDt9qwMYHu6Pp6szv//vfo7klvHi1QO4aWQoaQUV5J12jPz6LcmFzFu8kyBfd1Y+Fsf9l0Xx7b7M82I1Sbll9PL3tGlAty1EB/kQ7Odufr2Hqbh6qsw3UOnTty83ObPqXBIzS+jb3ccuW1aNjAj3Z3AvPz7acpx6c4stzcCx0jA0nZO9S1Q/7lYUc7emFDE8rKtdtqsacXdxJq5PNzxdnfnkntHcf1kUt45RYbc2dRq0EmsP5Z5pH7v8wfH09Pfk4cnR+Li58M+1SYDaztqYlM+gntYrqDQXIQRx0d3YmlqEwWCj8OSU5+Gq12HQ3HZdLqUkMaPE7nUzQggem9qXtMIKvrWjWKJ2Hhrrkp2gsmDGPdJiIVxJZS0Hs0uJ62OdtNW28MZNQ/nl6SlMMNriKPn1KxKyePizvQzo6ceXC8ad6WfS1duNByZFsfZwHu9vSuW2D7bj6+HK8xYuUrM0E/p0o7iiliOWrKtpifCxMHZBuy/PPFVFUUUtw8LsX3R55aBghoV24d1NqW1rYGZBtPPQWJf4t4yFcPNbHLYttQgpz+6F2xN/LzeC/c5uaXi4OhMT4kuiHSt7C8pqePrrREb27spn94+9qO/4/ImRdPNx5+8/HSXI152vHxpPRDdvO1lrGhP7dMPZSfDKqsN2D/6awrrDeQAWbX/cXoQQ3DG2N8cLK9ifaZ/3pXYeGutRlKpy60fd12qfivjUQrzdnB3iW11TDAvzJzGzxHZbLBfw44Ec6hokf5k7uMn9dm93F354YiL/fXg8q56YSE9/y7eytTQhXTx446ahbE8rZum2E/Y2p0Uqaup5Z2MK46ICGGhFfbW2MHNICG4uTry3KZWVidkcsUaKeQto56GxHvFvg5Or2rJqbWhKEWOjAh2uGrqR2FB/yqrrOd6eTngWoFHfqyVF4WA/D0b2DsDLreN0l75ueCgDevjxa7LjqMU2xcfxxyksr+XZmTEm9R63BX4erlw5KISfDubyxBf7mP2fLfywP6f1Cy2EY/6lajo+p3Mg8QslH+Hbcj+DrJIqjhdWOES8ozkaV0T7rRT3aDBI1hzKpay6jh/25/DFzpOUG7dyThZV2kzfyx7ERQey+8QpquvM1LqyEiWVtby/OY3pA4IZEd7V3uacxxs3DeXnpyaz5jeTGB7uz+Nf7LVMvxQT6DhfUTQdiz0fg6EeJjzR6tC9J5Qm5thIy3YHtCR9uvvg5eZMYkYp1w0Pbf2CNtBgkPxmeQLfJ2bj7+VKSWUdoBoKPTQ5mu/3KwXa2cMsIOXhgMT17caiLcfZnX6KiX0d7wvEu5tSKa+p55krLdObw5K4uzjTp7uSKVly3xge/HQP/1ybxKwhPayeTqxXHhrrcGQVhI9XjZFaIa2gAiE480fgiDg7CYb06kKCFdJ1Nx3L5/vEbObG9qTBIHlqRj/6dvchPqUQKSUrErIYHdH1jPR3Z2NMRABuLk78fCTPrnZkl1Tx3b5MckurWbU/Gykleaer+SQ+nbmxvRxS6uVcvNxcWHT3KL5+cIJN6lD0ykNjeU6lq4ryK0yr6UwrLKdnF088XO1TVW4qw8O7snhLGpW19RaNK6xIUCuO124chouTwMlJcKqyls93nGT9kXyO5ZXzt+uGWOx+joa3uwvTYrqzan8OL149ABc7xL1S8su5c9EOck9X4+HqRHWdAY+7nPklKZ8Gg+S30/vZ3Kb24O7iTHigbb5k6JWHxvIcXqEeY2aZNPx4YQVRQY6dVgowITqQugbZoiR2bmk1f//xCK+sOszCX1JoaCE7q7bewJvrjrH2UB6zhvTAzcUJJ2O72LjobtTUG/jd14mEdvXkhpGdM97RyJzYnhSW17A1tajJ8ysSsjiYZZ2U1JT8Mm55fxv1Bsk9EyLo7utBL39P/rTqEMt3ZXDbmHCbfSB3JLTz0FiW6tMQ/2/Vlzzg4kY5FyKlJK2ggigHr0kAGB0RgJuzU7MfcADvb07l/c1pfL7jJK+vSWpRfmNXejFvr0/G3dWJ20af30JgXHQgUd28kVLy/KwBuLs49qrMXKb0706AtxsfbE676NzR3NP8ZnkCT3y5zypyHP/ZkEJtg4GvHhzHy9cOYvOzU3n52kGcrqqnh78Hj1/ex+L37AyY5DyEEMFCiMVCiJ+MrwcahQ41mvOJfxsqC+GKV0waXlBeQ3lNvd17E5iCp5szI3r7syW5aYfQYJB8n5jDzEEh7HtpBr4eLqxood3qyWKlKLvq8YkMCT2/DsbH3YUNT09h/8tXWqbnhYPj4erMI1Oi2ZJSyNZzxBIbDJJXfzqKsxCkFVTwxc4m2s2aQWVtPWsP5TF7WM/z3oMzBgaT+Mcr+PXZy+nuZ9mOgJ0FU1cen6CUbRsV644Bv7GGQZoOTNUp2PE+DJwLPYebdElagaqbiOwAKw+AcVGBHMk9fSaN9ly2pRZRWF7DnNieeLg6M2twy+1WTxZX4uIk6NHF8Qv6bMGd43oT6O3GZzvOOojnvz3AxqQC/jBrABOiA/njykP8eMBytQzrDudRVdfAHDuKcXZUTHUe3aSUXwEGOCOV7phJ2Rr7sXMR1Jap9rImsiW5ECcBAx1YxO9cYsP8kRIONCEJsSIhC193F6bGdAfg5tGhlNfU8+n29CbnyiiuJLSrJ85OjlF0Zm88XJ25ZmgPfj6cR3lNPUXlNSzfncHd43szf2IkH941iiG9uvDSikNU1lpGziQ+pZCuXq6MjnDcNHFHxVTnUSGECAQkgBBiHGA/oR+N49FQB7sWQfQ0CBls0iVSSlYkZhHXpxvdfNytbKBlaFRUvVAksbqugdUHc7lycMiZrLGRvQOY3C+IdzamNrlSySiuJCxAB2LP5drYXtTUG/jpQM6Z2FJjK11vdxdemj2QwvIaPo5Pt8j9EjNKiQ3zP5OooDEdU53HU6gOftFCiHhgKfC41azSdDyOfA/luW3qzJaQUUJGcZXdurK1h67ebvQO9DpPnn3PiVPc/P42ymrqmRN7/s/y4OQoSirrmgycn9TO4yJGhPvTL9iHdzelsvlYAb7uLgzpdTYeNLJ3ANNiuvP+plRKjcWU7aW8pp5j+WUOq6fm6LTqPIQQToAHMBmYADwIDJJS7reybZqOQnUprHsJAvtCn+kmX7Y7XVWWN27zdBSGhfqz72TJGSnsz3ecJDmvnOtH9GJ81PmqwKN6B+Dp6szWC5xHWXUdpyrrCNfO4zyEEDw1oz9pBRX8d28m46IDL6r7ePrK/pTV1PPBr6lm3etgVilSop1HO2nVeUgpDcBCKWW9lPKQlPKglNI8l6/pXPz4LJzOhuveAyfTU0qP5pbRzce9w2xZNTIhOpDc09UczDqNlJL4lEIuH9Cdf90ce9EHnZuLE2MiA9hygfNozLTSzuNirhwUzH1xkUzt3535Ey9WKBjQw49pMcF8vTuzxTqa1mhUC7B3c6eOiqnbVuuFEDcIR5GT1NiX8gI4dQKK0+Dnl2H/lzD5WQgd1eql55KUd5oYB5d8aIqrBvfA1VmwIiGLtMIKck9XExfdvCZTXJ9AUgsqzpM2adTzGuAg8t6OhBCCl2YPZPE9oxkX1XR/l+uG9yK/rIYdac3X3LTG9rQiooK8CfB2a32w5iJM1Vh4EBX3qBdCVAMCkFJK/c6/lGioh7UvqMC4oR7j2wD6XQWXPd22qQyS5Lxy7hzX2yqmWpMuXq5M6d+d/yVkUWlUgp3YgiLw3OG9WLL1BPMW7WDtU5Po0cWT+JQievl7EqErl9vFtAHd8XZz5oNf0xgdGdBmKf/aegM7jxdzwwjLilxeSpj0G5dS+kopnaSUblJKP+Nr7TguJWorYPkdsOM9GD4PZvwZpj4Pvz0Mt38Jzm3TekovqqCm3tAhVx4Aj1/eh5o6A5/vOMl1w3u1KF/R3deDpfPHUFZTz3f7smgwSLalFRHXJ9BhekN0NDxcnXnqiv5sTCrglVWHzxyvrmvgt8sTePrrxBavT8goobK2waHbADg6Jv3FCyEmNXVcSrnZsuZoHBIp4au7VC/yq/8Jo+83e8rD2arrWUxIx/wOMjTUn68eGs+OtCLmjY9odXx0kA8je3dlxb5sevl7UlpVpz+4zGT+xEiO5Jzmmz2Z/OGqAbzw3QFWJmZTb4yDXD+iFxOa2U6MT1H1RRcmOGhMx9S13jPn/Pt/wPfAy1aySeNo7FsGKT/DVa9ZxHEArD6YS6C3GzE9OubKA1S84p64SJOL/ObE9iQpr4wnv0xgRLg/VwwMsbKFnZ8bRoRSWdvAP1Yf5dt9WUyN6c57d46gRxcP3vo5udnrtqYWMqRXF7p4udrQ2s6FSSsPKeXsc18LIcKAt6xikcaxkBI2vw6hY2CUZeTMyqrr+PlIHreMDnPYtrPW4KaRYVTWNuDiJLhtTDiebp1b7NAWjI0MIMTPg0+2ptPNx523b43Fy82FtMIKXlud1GQhZkVNPftOlvDApNaFOzXN096mBJnAAEsaonFQTm6HkhMqvuFk/ge9lJJ/rTtGTb3hooK6zo6nmzMPTY62txmdCicnwcI7RrArvZhxUYFn+qzMHtqT11YnsTIxm0ennq+Ku/N4MfUG2WKGnKZ1TI15/AejNAlqqysW2GstozQOxP7l4OoFMde063KDQZJ5qooGKfH3dGXV/mw+jk9n3rjeDtcPWtMxGdm7KyN7n/9eCgvwYlTvrizZms64qEACvN2QUvViWbgxBQ9XJ0ZF6PefOZi68th9zvN64AspZbwV7NE4EvU1cOg75Tjc2yeZvmhLGn/78SgAbs5OeLg6MTYygD/PGaQzjTRW5ZW5g7lz0Q5ueHfreceHhnbh79cNdfjOlY6OqTGPJY3PhRBdgTCrWaRxHJLXQnUJDL2lXZdLKflqdyYDe/ixYFIUn24/wZ4Tp3h2Zn/tODRWZ0APP1Y9MZEdaWc7P/b092R0RFf9/rMApm5bbQSuNY7fA+QLIbZKKX9rRds09mb/cvDuDlFT2nX5kZwyUvLLeWXuYOYO78XMwSGkF1V02PRcTcejRxfPM6q8GstiagS0i5TyNHA9sFRKORaYZj2zNHan6hQcWwNDbmxzAWAj6w7nIQTMGqxSUj1cnbXj0Gg6CaY6DxchRA/gZmCVFe3pOBQcU9pOnZVD/4OGWhh6c7unOJJzmohAbwI7mPChRqNpHVOdx59RbWhTpJS7hBBRQPMVOJ0dQwMsux5WPGZvS6xHwufQrT/0iG33FEl5ZfQP7rhFgBqNpnlM1bb6Wko5VEr5iPF1mpTyBuua5sCk/gKlGZCdoBxJZyNrD2TuhJF3QzsDi1W1DaQXVdC/g2pXaTSaljHJeQghXhNC+AkhXIUQ64UQBUKIO61tnMOyb6l6rKuAohT72mJpilJh7Uvg5qsEENtJcn4ZUtJhhQ81Gk3LmLptdYUxYH4NkA70QelcdU42vQ5pG5s+ZzBA2iboZexdkZ0AxcehsBM4EUMDLJ0LWbth2kvg0f7g9tHcMgBidL8KjaZTYnLA3Ph4NfC1lLLUSvbYn9pK+OUvsHQOVBZffL4oRdU+DL8TXDzh2GpYNB2WXAP1tba315Kk/QKlJ1VHwLELWhx6ILOUt39OZt3hvCbP70grxtfDRXfK02g6KabmYK4SQhwFqoCHhRBBQLX1zLIjRefkAWx8FWa9dv75zF3qsfcE6DUCDn0LwgmkAQ7+F2Jvs52tluT7J+HoD+AZAP1nNTlk78lTlFaqDsQPLdtDTb0BgBevHsD9l50Vmauua2DNoVxmDQkxWXFWo9F0LEwNmD8HTABGGfuXVwJzrGmY3ShIUo+ho2HvEpWOW5iipDo2/BVWPAJOrhDYF276BK55E+78FroPhN0f2dX0dlNZDHuWgJMLTHoaXC5Ora2srWfB0j3c+8kuHli6mz7dfdjx/DQuj+nOG2uTqKk/mziw4Wg+5TX1XDtMF2dpNJ0VUyvMvYBHgHBgAdAT6E9nrPkoOKo+RGe/De/Gwb+Hq+NegVBp7JccPVUpzPp0h1H3qWN9r4BtC6GuGlw97GN7ezm+GZBw0xIIH9vkkI/j0yksr2FSvyAE8J/bh+Pn4cptY8LZcDSfvSdKGB+tGutsSSnE18PlzGuNRtP5MHXb6mOULMkE4+ss4GtacB5CiI9QAfZ8KeVg47EAYDkQgQq83yylPCWEiDHeYwTwgpTyjXPmSQfKgAagXko5ykSb20dBEgREQ/AgmP0WVBSAVzfY8iZEXKakyT38L76u10gw1EHuAQgbbVUTLU7aL+Dup36GZvh2byYTogNZet+Y846PjQrA2UkQn1J4xlkk5ZYRE+Krt6w0mk6MqQHzaCnla0AdgJSyEmjtk+ETYOYFx54D1ksp+wLrja8BioEngDdomqlSylirOw6A/CMQ1F89H3kPTHoGRt0LTyaqbaqg/uAbfPF1oUbTsnZffM6RaaiDY2uVY2xGhiS3tJrUggqm9u9+0Tk/D1eGhnZhS0ohoMQQj+WWaRkSjaaTY6rzqBVCeGLs6SGEiAZqWrrA2N/8wnSlOUCjQu8SYK5xbL6UchdG52Q3GuqgqhiCYi4+J0TLBXN+PcG3J2R2MOdx8Fsoy4YRdzU7JN7oGCb0aXobakq/7iRmlpBTWkVWSRVlNfW6OFCj6eSY6jz+CKwGwoQQn6FWDc+2437BUsoc4/NcoImv8BchgbVCiD1CiJbzR83F2RWePa5WG+0hdGTHWnlICfFvqWB/3yuaHRafUkiAtxsDmllNXBvbEylhVWIOSY31Hdp5aDSdmladh1DC90dRirr3AF+gsq42mnNjKaXkbHfClpgopRwBXAU8KoSY1IKtC4QQu4UQuwsKCtpnmBDg4ta+a3uNglPpUFHYvuttTeoGyD8M4x9rtsWslJL41EImRAfi1EwMI7KbN8NCu/DdviwOZ58GoJ92HhpNp6ZV52H8kP9RSlkkpfxBSrlKStneT8c8ozovxsd8E+6fZXzMB74DxrQw9gMp5Sgp5aigoKB2mmgGZ+Iee2x/7/aw7f/AJ1jJrjdDakE5eadriOvTcr/nW8eEczjnNO9uSmVEuD9+Hq6Wtlaj0TgQpm5b7RVCWCKFaCVwt/H53cCKlgYLIbyFEL6Nz4ErgIMWsMM69IhVBYNZe2DfMvh4Fqx8XG0PORp5h9XKY8yCJus6GolPUenJE1txHjeODCUi0IvK2gaevrK/RU3VaDSOh6mpumOBO41psxWoTCsppRza3AVCiC+AKUA3IUQmKm7yKvCVEGI+cALVHwQhRAiqT7ofYBBC/AYYCHQDvjO2jHQBPpdSrm7jz2g73H1U/GDHe1BdCl3C4ES8iicMmG1v685n+0Ilr9JYp9IMvyYXEhbgSVgrMiOuzk68duMwdp8oZkJ0y45Go9F0fEx1Hle2dWIpZXM6HRd1IJRS5gKhTYw9DQxr673tysh71Koj8jKY+iJ8MAU2/MWxnEd5Puz/SqnmegU0O+x0dR2bkwu4fUy4SdOOiQxgTGTz82k0ms5Di85DCOEBPIRS0T0ALJZS1tvCsA7LmAfUv0aG3QI/v6wkQFr4oLYpuxapLoHjHmlx2JqDudTWG5gT29NGhmk0mo5CazGPJcAolOO4Cvin1S3qbPQwLpxy99vXjkbqqpTz6HcVdOvT4tBV+3MID/AiNqyJinqNRnNJ09q21UAp5RAAIcRiYKf1TepkhBidR04iRE2xpyWK/cuVRtf4R1scZjBI9p44xZzhPRHt7Cao0Wg6L62tPM5UfOvtqnbiHagC5zmJkH8UkuwY75cStr+rVkMRE1scmlZYQVlNPcNC9apDo9FcTGsrj2FCiNPG5wLwNL5uzLbSAkam0GMYHFsDR1ZBQw3cv0FVo9uaU+lKNfiq11vtTZ6YUQKgt6w0Gk2TtOg8pJTOtjKkUzNmgeoH4tMdUn6G1b+H+eta/QC3OOlb1GPkZa0OTcwswcfdhaggHysbpdFoOiKmpupqzCFqsvoHsGsx/PAUnNymuhHakhPxqi9JU8KPF5CYWcrgXn5aVl2j0TSJqRXmGksx7DbVD2THe7a9r5Rq5RExsdUVj8GgZNUH9NC7khqNpmm087A1bl4w/E4V/6gpt919T8RDaUaL6rmNnCyupKquQSvjajSaZtHOwx5ETgbZADkJtrvnzg/VimfQ9S0OyyqpYnua0rPqrxs6aTSaZtAxD3vQqL6buavVlFmLcDobjnwP4x9RK58WiHt1w5nn/YJ1sFyj0TSNXnmcQ32DgbWHcjmYVWrdG3kFqD7ptuo6uPtjkAYYNb/FYVW1Dee99nLT3y00Gk3TaOdxDvUGye++TuSj+OPWv1noaMjYaX259qpTsOdj6HclBES2ODQl/2wM5spBpjR51Gg0lyraeZyDh6szVw0OYc3BXKrrGlq/wBzCx0FFPhQes949pIRvH4SqEpjcetfgo7mqHvSnJy9j4e0jrGeXRqPp8GjncQFzYntRUdvAn74/xLsbU0nJL2NjUj7vbEzhWF6Z5W4Ufbl6TN3Q8jhzOLYaktfAjD9Dr9Yr2pNyy/BwdaJfsC8uzvqtodFomkdval/AuKhAooO8+WJnBgD/Xp9MlXEVEp9SyGf3j7PMjbr2hsA+kLIexj1smTnPxWCADX+FgKjzJeKbYEtyIQHebhzJPU3f7r66MFCj0bSKdh4X4OwkWPfbydQ2GCgoq2HBp3voH+yDr4cry3dnUF3XgIerhVRboqfB3qVQUwbuFq6p2LcU8g7ADYvBufl+4mXVdcxfsgsJ1NYbWDApyrJ2aDSaTonem2gCJyeBh6szYQFe/PTkZbx163CmxgRRW29gz4lTlrvR0Fugvkp1HrQkmbtVA6recTD4hhaHrj2UR029gfAAL24cGcozuv+4RqMxAe08TGRMZCAuToJfjuZbbtLQkRA2VkmVGAyWmfPYGvj4KrWSmf3vVqVIViRmE9rVk3W/ncQbNw3DVcc6NBqNCehPChPxcXfhikHBLI4/zv/2ZVlu4tH3K6n0zF3mzWMwwM9/gi9vh+4DYcGmVjsFNhgkO9KKmDEwWDd80mg0bUI7jzbwr5tjGRrqzz/XJSEtVZ/RbyY4u8GRlebNc3wTbPmXkh+5a4VJ/dLTiyqoqTcwUAsgajSaNqKdRxvwcHVm3rjeZBRXsc/YLMn8Sf1Ue9oj35tXMLh/Obh3gWv/A56mNXBKylWpxzFaw0qj0bQR7TzayJWDgnFzcWLZthOWW33EXAMlJyD3QPuurz6tnM+gOeDqYfJlR3PLcBLQV2tYaTSaNqKdRxvx9XDl7vG9+XZfFv/ZkGKZSfvPAuGkHEBbkRJW/RbqKmHkvW26NCn3NBGB3pZLPdZoNJcM2nm0g+dnDWD6gGAWbzlOTeqbhOIAAA+2SURBVL0FZEx8giB8QvucR8ZOOPgNTH4OerVNUiQpt4z+umeHRqNpB9p5tAMhBHeMDae0qo7NxwotM+nAa6HgCOTsb9t1B74CF08lt94GSqvqSC+q1MFyjUbTLrTzaCcT+3ajq5cr3ydmW2bCoTcrJ7BrkenXNNTBoe+g/8w2V6gfyFSy87HhpgXXNRqN5ly082gnrs5OjI0M5GC2hXp/eHaFITfC/q/g8AqorWz9mp0fQmWR6oveRhIzVbbY0F7aeWg0mrajta3MIDLIm5+P5FHfYLCMCu3kZyFrL3x1F7h4KGkRN28Y/ygkLodxD4FHFzW2OA3W/1n1JDehL/mFJGSUENXNmy5ezeteaTQaTXNo52EGUd28qTdIMk5VEdnN2/wJ/cNhwS9KaffISjj0P6irUDUc1aVK6PDmT8HQACseV4KH17zVqgTJhUgpScgoIS460HybNRrNJYnetjKDqCDlMI4Xlrcysg24uEPMLLjuPXghG0bcpRxHj1iVjbX2RfhwCpzYAlf+Dbr0avMtUgsqKCirYWyUdh4ajaZ9aOdhBlHdVHFdWkGF9W5y5d9gzjswf62qB9n2f1CWBzd9AiPmtWvK+BSVIRYX3c2Chmo0mksJvW1lBl293ejq5UpaoRWdh7svDL9DPZ/7Luz+CGLvAN/29xiPTykkLMCT8EAvCxmp0WguNbTzMJOoIB+O5Jy2zc08/eGyp8yeZmd6MVcODLGAQRqN5lJFb1uZydT+Qew7WUJWSZW9TTGJqtoGSirr9KpDo9GYhXYeZnLtMBWwtlixoJUpLK8BIMjH3c6WaDSajox2HmYSHujFsDB/1hzKtbcpJlFUUQtAoI+bnS3RaDQdGe08LMDwMH+ScsswGCwk0W5FCsvUyqObXnloNBoz0M7DAsSE+FJZ20DGKRMkRexMUYVyHnrlodFozEE7DwvQKGt+1NiZz5EpLFfbVnrlodFozMFqzkMI8ZEQIl8IcfCcYwFCiHVCiGTjY1fj8RghxDYhRI0Q4ukL5pkphEgSQqQIIZ6zlr3m0C9YOY+kDuE8avBxd9ENoDQajVlYc+XxCTDzgmPPAeullH2B9cbXAMXAE8Ab5w4WQjgDC4GrgIHAbUKIgVa0uV14u7sQHuDVQZxHLd30lpVGozETqzkPKeVmlFM4lznAEuPzJcBc49h8KeUuoO6C8WOAFCllmpSyFvjSOIfDMain3xmZc0emqLyGQL1lpdFozMTWMY9gKWWO8Xku0JrGRi8g45zXmcZjTSKEWCCE2C2E2F1QUGCepW1kfHQgmaeqOFnk2EHzwvIavfLQaDRmY7eAuZRSAhbNbZVSfiClHCWlHBUUFGTJqVtlglFkMD7VQm1prURRea1eeWg0GrOxtfPIE0L0ADA+5rcyPgsIO+d1qPGYwxEd5E2InwdbUhzXeVTU1FNUUUsPPw97m6LRaDo4tnYeK4G7jc/vBla0Mn4X0FcIESmEcANuNc7hcAghmNAnkG2pRQ5bLHgsTwX0+4W0rd+5RqPRXIg1U3W/ALYB/YUQmUKI+cCrwAwhRDIw3fgaIUSIECITeAp40TjeT0pZDzwGrAGOAF9JKQ9Zy2ZzmdinG8UVtRzJNU9lN6ukild/Okpp5YX5A+bRmA0Wo52HRqMxE6tJskspb2vm1LQmxuaitqSamudH4EcLmmY14vqouMfWlCIG9ezS7nle+f4wqw/lsjEpnz/OHsQPB7J5YdZAPN3Mq804mluGl5szYV21oq5GozEPXWFuQYL9POjT3YdfjXGPX47m887GlDbNsTW1kNWHcrliYDDpRRXc9uF2lm0/yb6MU2bbdyyvjL7Bvjg5ta3nuUaj0VyIdh4WZmr/ILalFlJaWceiLWm8viaJvNPVF41LzCjhD9/up7Tq7NbUluRC5n+ym6hu3vz/9u48uK6yjOP498l2m9x0u0laQpou6WKtBdpausgig1MQdCw4CLWDoqAsiqPDqIOD4+A/MjoDfzg6gixaRKGAOnbGwQGhM0qhtAXbUmgDaZvSQps2C81Gliavf5w37W3IbXqynZz295m5k3PPOTd5nrw3ffo+9ywP3LCAJ25ZyrzScQAcqB/4/UKcc/z42W28vq+BuZPVshKRwVPxGGJfuqCMzi7HP988yPb9R3Gu73t9PPLyXp7ctJ/VD2+krrmdTXvrufmPm5lWVMDa25ZTmMhh8fQU6+68iOws4736gZ8/Ul3XytNbDjCjOMmXF2U8TUZE5LTpNrRDbH7ZOCqKk9z/fCVN7ccwg3XbPuBbl1Qc36e72/FKVS3zSsdRdbiZ6x96ldzsLErGJnjq1mVMKDhxEl9OdhbnThgzqOKxuTo40f83qxcya5JmHiIyeJp5DDEzY/XSqcdvunTFvMm89UEjbZ1dx/eprGmirqWDb140nTU3L+HQ0TZ2HWrirhVzTiocPaamCgZ1ufct1fVMLMhlZknhgL+HiEg6FY9hcOOyaceXv3D+uXR1O6oONwPwzJagVQXB0VnLKopYe9ty7loxh2sW9t1SmpoqYH/Imcfe2hZueOhVNu2tZ3N1A5+elsJMH5SLyNBQ22oYjMnNZu2ty/jg6EfMKz1xufbpxUnue24XxYUJbv/sTM6dkA/A/LLxzC/LfGjvlIkF1DZ30NJ+jGSi/yHbebCRrz26idrmdh757x721raw6sLyfl8nInK6VDyGydKKIgCOdXWTl5PFrkONbK6up76lgz9840IuKJ9w2t9raio4L+O9+lY+6Y++yqSxrZPVD28kkZPN3HPG8sLOGgAWT08NMBMRkY9T8RhmOdlZzCopZM0r++jo6uaOy2aGKhwAM4qTAOyra+m3eLy6u46G1k7+8u1FbKiqZdehJhI5WcwvO/XrRETCUPEYAXNLx/L2wUbuWjGH710+K/Trp/visftIS7/7vlJVS35uNounpWhuOwbABeUTSOTozoEiMnRUPEbAj678BNcuLOOS2QO7THxhIofJ4xLsre2/eLxcVcvSihR5OVks8DOcJWpZicgQU/EYAaXj8ykdnz+o7zGjOMmeI82n3OfQ0TZ2H2lh1YVTAZg0bgyP37wkdJtMRKQ/OlQ3JipKCvudeWzw19TquUAjwKVzShifnzussYnI2UfFIyYqipM0tHbS4E8+TFfT2IZzjg1VtaSSebrkuogMOxWPmOg54qq67uTZx/76Vpbf9yIv7TrMht21fGZmka6aKyLDTsUjJkrGBvcdr20+eeZReaiJbgdPbNxHTWP7SS0rEZHhouIRE6lkcM2r3m2rngsmrq88AgR3MxQRGW4qHjFRlAxmHnUZigdAeSqf8pTuEigiw0/FIyby87IZk5tFfUv7SevTL5ioWYeIjBQVjxgpSiaoa+mgq9vxrx0Haevs4r36Vs4rG08iJ4srPnVO1CGKyFlCJwnGSCqZR31LB1v3N3D7E2+wrCLF/oZWblw6jWduX86YXF2CRERGhopHjPQUj5rGoHW1cU9wh8DyVIEKh4iMKLWtYqQomUddcwe1zUHx+MW155FK5h2/hpWIyEjRzCNGJibzaGjtoLapHTO4fvEUvrqkXHcIFJERp+IRI6lkHq0dXRz48CNSBXnkZGviKCLR0L8+MVLkTxR8t6aZosK8iKMRkbOZikeM9JxlXlnTRHFhIuJoRORspuIRI2UTg3uCdBzrpkjFQ0QipOIRI3MmjyWREwxZsdpWIhIhFY8Yyc3OYtakQgC1rUQkUioeMTPFt650d0ARiZKKR8zMnhTcJbCzqzviSETkbKbzPGLmjstm0tbZxVcWl0cdioicxVQ8YiaZyOGnX5wXdRgicpZT20pEREJT8RARkdBUPEREJDQVDxERCU3FQ0REQlPxEBGR0FQ8REQkNBUPEREJzZxzUccwLMzsCLBvgC8vBmqHMJwoKZfR50zJA5TLaDXQXKY550pOZ8cztngMhpltcc4tjjqOoaBcRp8zJQ9QLqPVSOSitpWIiISm4iEiIqGpePTt91EHMISUy+hzpuQBymW0GvZc9JmHiIiEppmHiIiEpuKRxsw+b2aVZlZlZndHHU9YZlZtZm+a2VYz2+LXpczsBTN713+dGHWcfTGzx8zssJntSFvXZ+wW+LUfp+1mtii6yD8uQy73mtn7fmy2mtnVadt+4nOpNLMro4m6b2ZWbmbrzextM3vLzL7v18dubE6RS+zGxszGmNkmM9vmc/m5Xz/DzF7zMa81szy/PuGfV/nt0wcdhHNOj6B1lw3sBiqAPGAbMC/quELmUA0U91r3K+Buv3w38Muo48wQ+6XAImBHf7EDVwPPAQYsA16LOv7TyOVe4Id97DvPv9cSwAz/HsyOOoe0+EqBRX55LPCOjzl2Y3OKXGI3Nv73W+iXc4HX/O/7aWCVX/8gcIdf/g7woF9eBawdbAyaeZywBKhyzu1xznUATwErI45pKKwE1vjlNcA1EcaSkXPuP0B9r9WZYl8JPO4CG4EJZlY6MpH2L0MumawEnnLOtTvn9gJVBO/FUcE5d9A594ZfbgJ2AmXEcGxOkUsmo3Zs/O+32T/N9Q8HXA4869f3Hpee8XoW+JyZ2WBiUPE4oQzYn/b8AKd+Y41GDnjezF43s1v9usnOuYN++RAwOZrQBiRT7HEdqzt9K+extPZhbHLxrY6FBP/LjfXY9MoFYjg2ZpZtZluBw8ALBDOjD51zx/wu6fEez8VvPwoUDebnq3icWS52zi0CrgK+a2aXpm90wZw1lofXxTl273fATGABcBC4P9pwwjGzQuCvwA+cc43p2+I2Nn3kEsuxcc51OecWAFMIZkRzR/Lnq3ic8D5QnvZ8il8XG8659/3Xw8DfCd5QNT1tA//1cHQRhpYp9tiNlXOuxv+xdwMPc6L9MepzMbNcgn9s/+yc+5tfHcux6SuXOI8NgHPuQ2A9sJygTZjjN6XHezwXv308UDeYn6viccJmYLY/WiGP4EOldRHHdNrMLGlmY3uWgSuAHQQ53OR3uwn4RzQRDkim2NcBX/dH9iwDjqa1UEalXn3/awnGBoJcVvmjYWYAs4FNIx1fJr4v/iiw0zn3QNqm2I1NplziODZmVmJmE/xyPrCC4DOc9cB1frfe49IzXtcBL/kZ48BFfdTAaHoQHCnyDkHv8J6o4wkZewXBkSHbgLd64ifoa74IvAv8G0hFHWuG+J8kaBl0EvRqb8kUO8GRJr/14/QmsDjq+E8jlz/5WLf7P+TStP3v8blUAldFHX+vXC4maEltB7b6x9VxHJtT5BK7sQHOB/7nY94B/MyvryAocFXAM0DCrx/jn1f57RWDjUFnmIuISGhqW4mISGgqHiIiEpqKh4iIhKbiISIioal4iIhIaCoeIiISmoqHiIiEpuIhIiKh/R9rzEZDS/Y97AAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fb44c044128>"
+       "<matplotlib.figure.Figure at 0x7f69db1e2f98>"
       ]
      },
      "metadata": {},
@@ -2498,7 +2955,7 @@
     }
    ],
    "source": [
-    "plot_comparison(start_idx=200, length=300, train=False)"
+    "plot_comparison(start_idx=200, length=1000, train=False)"
    ]
   },
   {
@@ -2507,7 +2964,9 @@
    "source": [
     "## Conclusion\n",
     "\n",
-    "This tutorial showed how to use a Recurrent Neural Network to predict several time-series from a number of input-signals. We used weather-data for 5 cities to predict tomorrow's weather for one of the cities. It worked reasonably well.\n",
+    "This tutorial showed how to use a Recurrent Neural Network to predict several time-series from a number of input-signals. We used weather-data for 5 cities to predict tomorrow's weather for one of the cities.\n",
+    "\n",
+    "It worked reasonably well for predicting the temperature where the daily oscillations were predicted well, but the peaks were sometimes not predicted so accurately. The atmospheric pressure was also predicted reasonably well, although the predicted signal was more noisy and had a short lag. The wind-speed could not be predicted very well.\n",
     "\n",
     "You can use this method with different time-series but you should be careful to distinguish between *causation and correlation* in the data. The neural network may easily discover patterns in the data that are only temporary correlations which do not generalize well to unseen data.\n",
     "\n",
@@ -2524,7 +2983,8 @@
     "\n",
     "You may want to backup this Notebook before making any changes.\n",
     "\n",
-    "* Train for more epochs. Does it improve the performance on the test-set?\n",
+    "* Remove the wind-speed from the target-data. Does it improve prediction for the temperature and pressure?\n",
+    "* Train for more epochs, possibly with a lower learning-rate. Does it improve the performance on the test-set?\n",
     "* Try a different architecture for the neural network, e.g. higher or lower state-size for the GRU layer, more GRU layers, dense layers before and after the GRU layers, etc.\n",
     "* Use hyper-parameter optimization from Tutorial #19.\n",
     "* Try using longer and shorter sequences for the batch-generator.\n",
diff --git a/images/23_time_series_flowchart.png b/images/23_time_series_flowchart.png
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From 1fad0403b09ff09abdfabe7a5a364db2bd2e05d0 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 12 Apr 2018 08:21:55 +0200
Subject: [PATCH 43/61] Tiny fix for Tutorial #03-C

---
 03C_Keras_API.ipynb | 707 +++++++++-----------------------------------
 1 file changed, 136 insertions(+), 571 deletions(-)

diff --git a/03C_Keras_API.ipynb b/03C_Keras_API.ipynb
index a87cf6f..5c505c9 100644
--- a/03C_Keras_API.ipynb
+++ b/03C_Keras_API.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #03-C\n",
     "# Keras API\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -34,20 +28,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See Tutorial #02 for a more detailed description of convolution.\n",
     "\n",
@@ -56,20 +44,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Flowchart](images/02_network_flowchart.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -77,11 +59,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
@@ -102,10 +80,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We need to import several things from Keras. Note the long import-statements. This might be a bug. Hopefully it will be possible to write shorter and more elegant lines in the future."
    ]
@@ -113,11 +88,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# from tf.keras.models import Sequential  # This does not work!\n",
@@ -129,10 +100,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
@@ -141,9 +109,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -165,11 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -188,20 +149,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -209,11 +164,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -233,10 +184,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
@@ -244,11 +192,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -270,10 +214,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
@@ -282,9 +223,7 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -293,20 +232,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
@@ -315,9 +248,7 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -344,20 +275,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -366,9 +291,7 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -403,10 +326,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -414,11 +334,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -444,10 +360,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot example errors\n",
     "\n",
@@ -458,9 +371,7 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -489,10 +400,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## PrettyTensor API\n",
     "\n",
@@ -503,9 +411,7 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -525,10 +431,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Sequential Model\n",
     "\n",
@@ -539,9 +442,6 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -581,10 +481,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Model Compilation\n",
     "\n",
@@ -597,9 +494,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -610,10 +505,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "For a classification-problem such as MNIST which has 10 possible classes, we need to use the loss-function called `categorical_crossentropy`. The performance metric we are interested in is the classification accuracy."
    ]
@@ -621,11 +513,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model.compile(optimizer=optimizer,\n",
@@ -635,10 +523,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -648,11 +533,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -681,10 +562,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -694,11 +572,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -715,10 +589,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can print all the performance metrics for the test-set."
    ]
@@ -726,11 +597,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -748,10 +615,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Or we can just print the classification accuracy."
    ]
@@ -759,11 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -779,10 +639,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Prediction\n",
     "\n",
@@ -793,9 +650,7 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -804,10 +659,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "These are the true class-number for those images. This is only used when plotting the images."
    ]
@@ -816,9 +668,7 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -827,10 +677,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the predicted classes as One-Hot encoded arrays."
    ]
@@ -838,11 +685,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = model.predict(x=images)"
@@ -850,10 +693,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the predicted classes as integers."
    ]
@@ -861,11 +701,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred,axis=1)"
@@ -874,11 +710,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -899,10 +731,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Examples of Mis-Classified Images\n",
     "\n",
@@ -915,9 +744,7 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -926,10 +753,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Then we convert the predicted class-numbers from One-Hot encoded arrays to integers."
    ]
@@ -938,9 +762,7 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -949,10 +771,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot some of the mis-classified images."
    ]
@@ -960,11 +779,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -983,10 +798,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Functional Model\n",
     "\n",
@@ -996,11 +808,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Create an input layer which is similar to a feed_dict in TensorFlow.\n",
@@ -1040,10 +848,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Model Compilation\n",
     "\n",
@@ -1054,9 +859,7 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1065,10 +868,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Create a new instance of the Keras Functional Model. We give it the inputs and outputs of the Convolutional Neural Network that we constructed above."
    ]
@@ -1076,11 +876,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model2 = Model(inputs=inputs, outputs=outputs)"
@@ -1088,10 +884,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Compile the Keras model using the `rmsprop` optimizer and with a loss-function for multiple categories. The only performance metric we are interested in is the classification accuracy, but you could use a list of metrics here."
    ]
@@ -1100,9 +893,7 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1113,10 +904,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -1126,11 +914,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1159,10 +943,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -1172,11 +953,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1193,10 +970,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The result is a list of values, containing the loss-value and all the metrics we defined when we compiled the model. Note that 'accuracy' is now called 'acc' which is a small inconsistency."
    ]
@@ -1205,9 +979,6 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1221,16 +992,13 @@
     }
    ],
    "source": [
-    "for name, value in zip(model.metrics_names, result):\n",
+    "for name, value in zip(model2.metrics_names, result):\n",
     "    print(name, value)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can also print the classification accuracy as a percentage:"
    ]
@@ -1238,11 +1006,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1253,15 +1017,12 @@
     }
    ],
    "source": [
-    "print(\"{0}: {1:.2%}\".format(model.metrics_names[1], result[1]))"
+    "print(\"{0}: {1:.2%}\".format(model2.metrics_names[1], result[1]))"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Examples of Mis-Classified Images\n",
     "\n",
@@ -1274,9 +1035,7 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1285,10 +1044,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Then we convert the predicted class-numbers from One-Hot encoded arrays to integers."
    ]
@@ -1297,9 +1053,7 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1308,10 +1062,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot some of the mis-classified images."
    ]
@@ -1319,11 +1070,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1342,10 +1089,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Save & Load Model\n",
     "\n",
@@ -1360,9 +1104,7 @@
    "cell_type": "code",
    "execution_count": 39,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1371,10 +1113,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Saving a Keras model with the trained weights is then just a single function call, as it should be."
    ]
@@ -1383,9 +1122,6 @@
    "cell_type": "code",
    "execution_count": 40,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -1395,10 +1131,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Delete the model from memory so we are sure it is no longer used."
    ]
@@ -1407,9 +1140,7 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1418,10 +1149,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We need to import this Keras function for loading the model."
    ]
@@ -1429,11 +1157,7 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from tensorflow.python.keras.models import load_model"
@@ -1441,10 +1165,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Loading the model is then just a single function-call, as it should be."
    ]
@@ -1453,9 +1174,7 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1464,10 +1183,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then use the model again e.g. to make predictions. We get the first 9 images from the test-set and their true class-numbers."
    ]
@@ -1476,9 +1192,7 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1489,9 +1203,7 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1500,10 +1212,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We then use the restored model to predict the class-numbers for those images."
    ]
@@ -1511,11 +1220,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = model3.predict(x=images)"
@@ -1523,10 +1228,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the class-numbers as integers."
    ]
@@ -1535,9 +1237,7 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1546,10 +1246,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot the images with their true and predicted class-numbers."
    ]
@@ -1557,11 +1254,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1582,20 +1275,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Visualization of Layer Weights and Outputs"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
@@ -1604,9 +1291,7 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1651,10 +1336,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Get Layers\n",
     "\n",
@@ -1664,11 +1346,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1708,10 +1386,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We count the indices to get the layers we want.\n",
     "\n",
@@ -1722,9 +1397,7 @@
    "cell_type": "code",
    "execution_count": 51,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1733,10 +1406,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The first convolutional layer has index 2."
    ]
@@ -1745,9 +1415,6 @@
    "cell_type": "code",
    "execution_count": 52,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1769,10 +1436,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The second convolutional layer has index 4."
    ]
@@ -1781,9 +1445,7 @@
    "cell_type": "code",
    "execution_count": 53,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1792,10 +1454,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolutional Weights\n",
     "\n",
@@ -1805,11 +1464,7 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weights_conv1 = layer_conv1.get_weights()[0]"
@@ -1817,10 +1472,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This gives us a 4-rank tensor."
    ]
@@ -1829,9 +1481,6 @@
    "cell_type": "code",
    "execution_count": 55,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1852,10 +1501,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot the weights using the helper-function from above."
    ]
@@ -1864,9 +1510,6 @@
    "cell_type": "code",
    "execution_count": 56,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1887,10 +1530,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can also get the weights for the second convolutional layer and plot them."
    ]
@@ -1899,9 +1539,7 @@
    "cell_type": "code",
    "execution_count": 57,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1911,11 +1549,7 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1934,10 +1568,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting the output of a convolutional layer"
    ]
@@ -1946,9 +1577,7 @@
    "cell_type": "code",
    "execution_count": 59,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1984,10 +1613,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Input Image\n",
     "\n",
@@ -1998,9 +1624,7 @@
    "cell_type": "code",
    "execution_count": 60,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2014,10 +1638,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot an image from the test-set which will be used as an example below."
    ]
@@ -2026,9 +1647,6 @@
    "cell_type": "code",
    "execution_count": 61,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2050,10 +1668,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Output of Convolutional Layer - Method 1\n",
     "\n",
@@ -2063,11 +1678,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from tensorflow.python.keras import backend as K"
@@ -2076,11 +1687,7 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "output_conv1 = K.function(inputs=[layer_input.input],\n",
@@ -2089,10 +1696,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then call this function with the input image. Note that the image is wrapped in two lists because the function expects an array of that dimensionality. Likewise, the function returns an array with one more dimensionality than we want so we just take the first element."
    ]
@@ -2100,11 +1704,7 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2124,10 +1724,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then plot the output of all 16 channels of the convolutional layer."
    ]
@@ -2136,9 +1733,6 @@
    "cell_type": "code",
    "execution_count": 65,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2159,10 +1753,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Output of Convolutional Layer - Method 2\n",
     "\n",
@@ -2173,9 +1764,6 @@
    "cell_type": "code",
    "execution_count": 66,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -2186,10 +1774,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This creates a new model-object where we can call the typical Keras functions. To get the output of the convoloutional layer we call the `predict()` function with the input image."
    ]
@@ -2197,11 +1782,7 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2221,10 +1802,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then plot the images for all 36 channels."
    ]
@@ -2232,11 +1810,7 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2255,10 +1829,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2271,10 +1842,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2298,10 +1866,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2336,5 +1901,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

From 5e5266b13d7b1bdfdef19a4bf8d8a0458817bdf4 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 13 Apr 2018 08:12:58 +0200
Subject: [PATCH 44/61] Updated github issue-template.

---
 .github/ISSUE_TEMPLATE.md | 13 ++++++++++---
 1 file changed, 10 insertions(+), 3 deletions(-)

diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
index 22726d5..5072075 100644
--- a/.github/ISSUE_TEMPLATE.md
+++ b/.github/ISSUE_TEMPLATE.md
@@ -1,15 +1,16 @@
 # STOP!
 
+**Please don't waste my time!**
+
 Most of the problems people are having are already described in the [installation instructions](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/README.md).
 
 You should first make a serious attempt to solve your problem.
 If you ask a question that has already been answered elsewhere, or if you do not
 give enough details about your problem, then your issue may be closed immediately. 
-Please don't waste my time!
 
-## Python 3.5
+## Python 3
 
-These tutorials were developed in **Python 3.5** and may give strange errors in Python 2.7
+These tutorials were developed in **Python 3.5** (and higher) and may give strange errors in Python 2.7
 
 ## Missing Files
 
@@ -19,6 +20,12 @@ You need to **download the whole repository**, either using `git clone` or as a
 
 General questions about TensorFlow should either be asked on [StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow) or the [official TensorFlow repository](https://github.com/tensorflow/tensorflow/issues).
 
+## Modifications
+
+Questions about modifications or how to use these tutorials on your own data-set should also be asked on [StackOverflow](http://stackoverflow.com/questions/tagged/tensorflow).
+
+Thousands of people are using these tutorials. It is impossible for me to give individual support for your project.
+
 ## Suggestions for Changes
 
 The tutorials cannot change too much because it would make the [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ) too different from the source-code.

From 3129d5a67c16cffe22d3ab7580fc87a8de4521e7 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 16 Jul 2018 15:13:19 +0200
Subject: [PATCH 45/61] Updated to TensorFlow 1.9

---
 01_Simple_Linear_Model.ipynb          |  305 +++----
 02_Convolutional_Neural_Network.ipynb |  509 ++++++------
 03B_Layers_API.ipynb                  |  736 ++++-------------
 03C_Keras_API.ipynb                   |  463 ++++-------
 03_PrettyTensor.ipynb                 |  580 +++----------
 04_Save_Restore.ipynb                 |   89 +-
 05_Ensemble_Learning.ipynb            |  137 +--
 06_CIFAR-10.ipynb                     |   94 +--
 08_Transfer_Learning.ipynb            |  124 +--
 09_Video_Data.ipynb                   |  126 +--
 10_Fine-Tuning.ipynb                  |  343 ++++----
 13B_Visual_Analysis_MNIST.ipynb       | 1097 ++++++++-----------------
 16_Reinforcement_Learning.ipynb       |  648 +++------------
 17_Estimator_API.ipynb                |  899 +++++++-------------
 README.md                             |   10 +-
 download.py                           |   32 +
 reinforcement_learning.py             |  230 ++----
 requirements.txt                      |   16 +-
 18 files changed, 2033 insertions(+), 4405 deletions(-)

diff --git a/01_Simple_Linear_Model.ipynb b/01_Simple_Linear_Model.ipynb
index a5cf611..e7598f1 100644
--- a/01_Simple_Linear_Model.ipynb
+++ b/01_Simple_Linear_Model.ipynb
@@ -38,8 +38,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
      ]
     }
    ],
@@ -55,7 +55,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This was developed using Python 3.6.1 (Anaconda) and TensorFlow version:"
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
   },
   {
@@ -66,7 +66,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.4.0'"
+       "'1.9.0'"
       ]
      },
      "execution_count": 2,
@@ -96,28 +96,17 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets(\"data/MNIST/\", one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70.000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
@@ -131,77 +120,84 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### One-Hot Encoding"
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "The data-set has been loaded as so-called One-Hot encoding. This means the labels have been converted from a single number to a vector whose length equals the number of possible classes. All elements of the vector are zero except for the $i$'th element which is one and means the class is $i$. For example, the One-Hot encoded labels for the first 5 images in the test-set are:"
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "img_shape = data.img_shape\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = data.num_classes"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 5,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.],\n",
-       "       [ 0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.]])"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
-    "data.test.labels[0:5, :]"
+    "### One-Hot Encoding"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We also need the classes as single numbers for various comparisons and performance measures, so we convert the One-Hot encoded vectors to a single number by taking the index of the highest element. Note that the word 'class' is a keyword used in Python so we need to use the name 'cls' instead."
+    "The output-data is loaded as both integer class-numbers and so-called One-Hot encoded arrays. This means the class-numbers have been converted from a single integer to a vector whose length equals the number of possible classes. All elements of the vector are zero except for the $i$'th element which is 1 and means the class is $i$. For example, the One-Hot encoded labels for the first 5 images in the test-set are:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0., 0., 0., 0., 0., 0., 0., 1., 0., 0.],\n",
+       "       [0., 0., 1., 0., 0., 0., 0., 0., 0., 0.],\n",
+       "       [0., 1., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
+       "       [1., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
+       "       [0., 0., 0., 0., 1., 0., 0., 0., 0., 0.]])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "data.test.cls = np.array([label.argmax() for label in data.test.labels])"
+    "data.y_test[0:5, :]"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can now see the class for the first five images in the test-set. Compare these to the One-Hot encoded vectors above. For example, the class for the first image is 7, which corresponds to a One-Hot encoded vector where all elements are zero except for the element with index 7."
+    "We also need the classes as integers for various comparisons and performance measures. These can be found from the One-Hot encoded arrays by taking the index of the highest element using the `np.argmax()` function. But this has already been done for us when the data-set was loaded, so we can see the class-number for the first five images in the test-set. Compare these to the One-Hot encoded arrays above."
    ]
   },
   {
@@ -221,40 +217,7 @@
     }
    ],
    "source": [
-    "data.test.cls[0:5]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Data dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The data dimensions are used in several places in the source-code below. In computer programming it is generally best to use variables and constants rather than having to hard-code specific numbers every time that number is used. This means the numbers only have to be changed in one single place. Ideally these would be inferred from the data that has been read, but here we just write the numbers."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
-    "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
-    "\n",
-    "# Tuple with height and width of images used to reshape arrays.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "data.y_test_cls[0:5]"
    ]
   },
   {
@@ -273,7 +236,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -314,14 +277,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUMAAAD5CAYAAAC9FVegAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAHihJREFUeJzt3XmUFNXZx/HvA0LYVQQFFWdOwAVCFBWDu0aBKCogccG4EGM0osEtAaNx1xglKBzRE7YD4QQNigKCUVFAEV8EJIIi4wYiCsRlhLggIsJ9/5i5XdUzPXtXVU/7+5zjmequ6qpnvPSdp27dxZxziIj80DVIOgARkVygylBEBFWGIiKAKkMREUCVoYgIoMpQRARQZSgiAqgyFBEBVBmKiACwS00ObtOmjSssLIwolNzzwQcfUFxcbEnHESeVcf5TGWdWo8qwsLCQZcuW1T6qeqZ79+5JhxA7lXH+UxlnpttkERFUGYqIAKoMRUQAVYYiIoAqQxERoIZPk0Vqa8SIEQBs3boVgDfeeAOAxx9/vNyxgwcPBuCoo44C4MILL4wjRPmBU2YoIoIyQ4nYueeeC8C0adMy7jcr3xd2zJgxAMydOxeAE044AYD99tsvihAlQe+++y4ABx54IAAPPPAAAEOGDIk9FmWGIiIoM5QI+GwQKs4IDzroIABOOeUUAN5///3UvlmzZgGwevVqAKZMmQLAjTfemP1gJVHLly8HoEGDkrxsn332SSwWZYYiIigzlCzy411nzJhRbl/Xrl2BIOtr06YNAC1atADgu+++Sx3bo0cPAF5//XUAPv/884gilqStWLECCP4dDBgwILFYlBmKiBBDZuj7kY0fPx6AvffeO7WvSZMmAJx//vkAtGvXDoBOnTpFHZZE4L///S8AzrnUez4jnDNnDgDt27fP+FnfDxHgrbfeStt3+umnZzVOSd7KlSsBGD16NAAXXXRRkuEAygxFRIAYMsOhQ4cCJRMsVsT3K2vVqhUAXbp0ycq1O3ToAMCwYcOAH+bcdXE644wzgOApMEDLli0BaN26daWfffTRR1Pb4fZDyU/vvPMOAFu2bAHSeyAkRZmhiAiqDEVEgBhukydMmAAE3STCt8BFRUVA0PHyxRdfBGDx4sVAMPzqww8/rPD8jRo1AoKuGr4RP3wef7us2+R4FBQUVPvYv/3tb0AwLCvMd7HxPyV/DB8+HChZggBy47upzFBEhBgyw5NPPjntZ5gfiuVt3rwZCDJF/9fi1VdfrfD8P/rRj4BgoLcf5gWwadMmADp27Fir2CU6Tz31FAC33HILANu2bUvt22uvvQC45557AGjWrFnM0UkUwg9R/Xfaf2+bN2+eREhplBmKiJBjw/F23313AE466aS09zNllWU98cQTQJBdAhx88MEADBw4MFshSpb4oXvhjNDz3Sz81F2SHxYsWFDuvbZt2yYQSWbKDEVEyLHMsDY+/fRTAK644gogfSiYb4+qqsOvxKd///5AMDzPGzRoUGr7rrvuijUmiYdf6iHMD4jIBcoMRUTIg8zwoYceAoIMcbfddkvt80+qJHm+/+eiRYuAoK3QtxnddNNNqWP9dE6SH1555RUAJk2alHrv0EMPBaBXr16JxJSJMkMREepxZvjyyy8DQV8078knn0xt++mjJHl+0s7i4uK09/30beoLmr/mzZsHpPf08H2M/TR+uUCZoYgIqgxFRIB6fJv89NNPA8Hcdz179gTgqKOOSiwmKc+veeKHWHonnngiAHfccUfcIUnM/CQtYWeffXYCkVROmaGICPUwM9y6dSsAzz77LBBM1HD77bcDwZRekpzwanZ33303UH726m7dugHqRpPPPv74YwAWLlwIpE+icuaZZyYSU2WUGYqIUA8zQz8ZqG+DOvXUUwE4+uijE4tJ0t13332p7aVLl6bt88Px1FaY//7xj38A8MknnwDBdzVXKTMUEaGeZIZ+IlCAO++8E4Bdd90VgJtvvjmRmKRi999/f4X7/PBJtRXmv3Xr1qW99lP05SplhiIi5Hhm6J9KXnXVVan3vv/+ewD69OkDqF9hfePLtDpP/X3274/dvn07AF988UW5Y/1Qr5EjR2Y8V8OGDVPb9957L6DlBKI2e/bstNenn356QpFUjzJDERFUGYqIADl6m7xjxw4gmNli7dq1qX2dOnUCggcpUr/4dWmq45xzzgGgffv2QNBFY+rUqXWKwa++F55DUbLHd7L25VVfKDMUESFHM8M1a9YAwQpqYb7bhua/y13+4RbAzJkza32exx57rMpj/MOVBg3S/6737dsXCNbeDjv22GNrHZNUbcaMGUDwsNPPap3rqx0qMxQRIccyQ99Js3fv3mnvjxgxIrWd64/nBaZPn57aHj58OFB+ogavqKgIqLwd8JJLLgGgoKCg3L5f/vKXAHTu3Ll2wUrWfPPNNwA888wzae/76brC3ZtykTJDERFyLDMcO3YsUH4YT7itwcxijUnqprrr4j7yyCMRRyJR8+23foXKfv36AXD11VcnFlNNKDMUESFHMkPfL+nBBx9MOBIRqS2fGfp1kusbZYYiIuRIZujXQP7qq6/S3vejTTTdk4hETZmhiAiqDEVEgBy5TS7Lr5w2b948AFq3bp1kOCLyA6DMUESEHMkMb7jhhrSfIiJxU2YoIgKYc676B5t9Bqyr8sD8UeCca5t0EHFSGec/lXFmNaoMRUTylW6TRURQZSgiAkT8NNnM9gDmlb5sB+wAPit9/TPnXOYZP+t2zS5AeD6ojsANzjnNAhGBhMq4AJgM7Ak44O8q3+gkUcal150M9AE2OOe6RXGNtOvF1WZoZrcBXzvnRpR530rj2BnBNRsBG4DDnHPrs31+SRdXGZvZ3sCezrkVZtYKWA6c6px7Nxvnl4rF+T02sxOArcC4OCrDRG6TzayTmRWZ2cPAKqCDmf0vtH+gmU0o3d7LzKab2TIzW2pmR9bgUr2At1QRxi/KMnbObXTOrSjd/hJ4G9gnut9GMon6e+ycWwBsiuwXKCPJNsODgJHOuS6UZG8VeQAY7pzrDpwD+P+5PcxsTBXXGAj8KxvBSq1EXsZm9mOgK/BqdkKWGorjexyLJEegrHHOlV8LtLyewIGh6f53N7OmzrklwJKKPmRmTYDTgOvqHKnUVtRl3Ap4AhjinPu6ztFKbURaxnFKsjLcEtreCYQXN2kS2jZq10h7GrDEOVdcy/ik7iIrYzNrDEwHJjnnZtUpSqmLqL/HscmJrjWlja6bzWx/M2sAnBnaPRe40r8ws+o2pJ6HbpFzRjbLuLSx/h/ACufcAxGEK7UQ0fc4NjlRGZa6HpgDLALCDzyuBI4xszfMrAi4FCpvazCzlsDPgZnRhiw1lK0yPoGSP3a9zGxF6X+/iDh2qZ5sfo+nAQuBLma23sx+HWXgGo4nIkJuZYYiIolRZSgigipDERFAlaGICKDKUEQEqGGn6zZt2rjCwsKIQsk9H3zwAcXFxVb1kflDZZz/VMaZ1agyLCwsZNmy6oy8yQ/du3dPOoTYqYzzn8o4M90mi4igylBEBFBlKCICqDIUEQFUGYqIAKoMRUSAZCd3rdCWLSXzRQ4dOhSAMWOCGX78Y/Jp06YBUFBQEHN0IpKPlBmKiJCjmeHGjRsBGD9+PAANGzZM7fOdRWfPng3A73//+5ijk9p47bXXABgwYABQMiqgtp577rnUdufOnQHo0KFD7YOTxPjvcd++fQEYPXo0AIMHD04dE/7+R0mZoYgIOZYZfvbZZwAMGjQo4Ugk2+bMmQPAtm3b6nyuWbOC9Z8mTpwIwNSpU+t8XonP559/DqRngABDhgwB4JJLLkm917Rp01hiUmYoIkKOZIYPPFCywNnMmSXrN736atXrgS9cuBAAv4bLIYccAsDxxx8fRYhSS99//z0ATz/9dNbOGR54f//99wNBD4TmzZtn7ToSnZdeegmADRvS150/77zzAGjSpEm5z0RNmaGICDmSGV5zzTVAzZ4aTZ8+Pe3nfvvtB8Bjjz2WOubwww/PVohSSy+88AIAixYtAuD666+v8zk3bdqU2l61ahUA33zzDaDMMJeF24vvuuuujMdceOGFAJQsjR0vZYYiIqgyFBEBEr5N7tOnDxA8BNmxY0eVn2nTpg0Q3A6tW7cOgLVr1wJwxBFHpI7duXNn9oKValu5cmVqe+DAgQB06tQJgBtvvLHO5w93rZH644033kht+0743i67lFRFp556aqwxhSkzFBEhgcxwwYIFqe23334bCBpLK3qAcvnll6e2e/fuDcCuu+4KwPz58wH4y1/+Uu5zf//734HyHTslWuGy8A82pkyZAkCLFi1qfV7/4CT8byiJhnapHf+wM5NevXrFGElmygxFRIgxM/QD830bEkBxcXHGY303mbPOOguAW2+9NbWvWbNmacf6KbzGjh1b7pzDhg0D4NtvvwWCSR0aNWpUu19CKvX4448D6R2sfVthuC23tnx3jHA2eOKJJwKw22671fn8Eq1wRu81btwYgLvvvjvucMpRZigiQoyZ4fbt24GKs0EIhtI9+uijQPDkuDI+M/RPKa+77rrUPj9Ey2eIfpqgjh071ih2qR4/4a7//w7Zaa/1dxWPPPIIEDx5BLjpppsAZfu5zHe4f+WVV8rt83d63bp1izWmTJQZioiQI8PxfHvSpEmTgOplhGX5rO/hhx9Ovbd06dIsRCdV+eKLLwBYvHhxuX1XXHFFnc8/btw4IJjirUuXLql9J510Up3PL9GqbOKVXOrpocxQRIQEMsNMo0yWLFlS5/P6USzhUSdlR7b4p9K+z5tkhx+Av379eiCYhilb1qxZk/a6a9euWT2/RCtTZuif/mfjziFblBmKiKDKUEQEiPE22a99HNVKV36VreXLl6feKzvM7/bbb4/k2j90LVu2BILuEeGJGvwQutatW9f4vJ9++ikQdNnxjjnmmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VHHXOj4Vcv80Pv/LA8gNNOOw1I7wyfyZtvvpna9g9M/PRsZSdjaNBAf8PrA78Cnn+QGZYLEzOUpX9VIiLkSKfr2vDTRD300EMVHlNYWAjA5MmTgWACCInGbbfdBqRnAv6OIDxBRyZt27ZNbftMsKKhmxdffHFdwpSYlG3rDU+mcdlll8UdTpWUGYqIUA8zQ79UgJ8YtjJ+2NZxxx0XaUxSonPnzkD6CoX+6X7ZjtNl+enawgYNGgSU7yTv2yglN/nO92WfIoefHGdjSrdsU2YoIkKMmWFliz4988wzaa8vvfRSADZu3Fjheaoz3Xu2n2BLzR166KFpP2vixz/+ccb3w/0Yf/rTn9YuMImMn7Kr7FPkfv36JRFOtSkzFBFBlaGICBDjbbKft8zPOh3mO+aWHaqXaeiev82uzkp6Ur/526yyt1u6Nc5tvrO15wc9XHPNNUmEU23KDEVEiDEzHDBgAADDhw9PvVfZeihV8X9tfHeO8ePHA9C+fftan1Nyi39IprWR65c5c+akve7QoQMQTM6Qq5QZiogQY2boV7HzK98BzJw5E4BRo0bV+Hx//vOfgWAtZMk/fr1rT52tc5tfAXP16tVp7zdp0gTI/YlSlBmKiJDAcDy/NnJ4u3fv3kCwCpqfqPWMM84A4He/+13qM/7JYniFNMlPfrVEP8D/lltuSTIcqYKfWs0PtVu1ahUA+++/f2Ix1YQyQxERcmSihlNOOSXtpwgEGca1114LaI3kXOf7/vrp9XwvgMMOOyyxmGpCmaGICDmSGYpk4tuOpX7Ze++9AZg4cWLCkdSMMkMREVQZiogAqgxFRABVhiIigCpDERFAlaGICACWabX7Cg82+wxYF104OafAOde26sPyh8o4/6mMM6tRZSgikq90mywigipDERFAlaGICBDx2GQz2wOYV/qyHbAD+Kz09c+cc99FdN0+wEigITDWOfe3KK4jyZVx6bV3AV4D3nfO9Y/qOj90CX6PJwN9gA3OuW5RXCPtenE9QDGz24CvnXMjyrxvpXHszNJ1GgHvAD8HPgaWAb90zr2bjfNLxeIq49B5hwHdgGaqDOMRZxmb2QnAVmBcHJVhIrfJZtbJzIrM7GFgFdDBzP4X2j/QzCaUbu9lZtPNbJmZLTWzI6s4/ZHAW865dc65bcBjQL+ofhfJLOIyxswKgF7ApKh+B6lc1GXsnFsAbIrsFygjyTbDg4CRzrkuwIZKjnsAGO6c6w6cA/j/uT3MbEyG4/cBPgq9Xl/6nsQvqjIGGAUMBdQ3LFlRlnGskpzPcI1zblk1jusJHBhaO3d3M2vqnFsCLIksOsmGSMrYzPoDHznnVphZz+yFK7WQN9/jJCvDLaHtnUB4pfAmoW2jZo20G4AOodf7UvlfLIlOVGV8NDDAzPqWnqeVmU12zg2qU7RSG1GVcexyomtNaaPrZjPb38waAGeGds8FrvQvzKyqhtTFQBczKzCzH1GSks/KdsxSM9ksY+fcMOfcvs65QuAC4DlVhMnL8vc4djlRGZa6HpgDLKKknc+7EjjGzN4wsyLgUqi4rcE5tx24CngeKAKmOOfeiTp4qZaslLHktKyVsZlNAxZSktysN7NfRxm4xiaLiJBbmaGISGJUGYqIoMpQRARQZSgiAtSwn2GbNm1cYWFhRKHkng8++IDi4mKr+sj8oTLOfyrjzGpUGRYWFrJsWXU6m+eH7t27Jx1C7FTG+U9lnJluk0VEUGUoIgKoMhQRAVQZiogAqgxFRABVhiIigCpDEREg2cldRUQA2Lx5MwAffvhhhccUFBQAMHLkSAC6du0KwAEHHADAIYccUqcYlBmKiJBwZvjpp58CcM455wBw9NFHA3DZZZcBJT3ls+GLL74A4KWXXgLglFNOAaBRo0ZZOb+I1MxTTz0FwOzZswF48cUXAXjvvfcq/MyBBx4IlAyvA9i2bVva/p0767ZKqTJDERESyAx92wDAT37yEyDI3Pbaay8g+xnhYYcdBkBxcTFAalzm/vvvn5XrSPV9+eWXAPzpT38CYNWqVQDMnTs3dYwy9vywZs0aAB566CEAxo0bl9q3detWAGoy0/4770S7eocyQxERYswMfVbm2wcBPv/8cwCuvLJk0azRo0dn9Zp33XUXAGvXrgWCv0zKCOM3ZcoUAG666Sag/FNDnzEC7LHHHvEFJpFZv75kPahRo0bV6TwHHXQQEDw9jooyQxERYswMX3vtNSB4ahR2yy23ZO06b775Zmp7xIgRAJx5Zsnyreeee27WriPV47ODa6+9FgjuEMzS59ocMmRIavvBBx8EoHXr1nGEKLXgyxGCzO/YY48Fgt4ajRs3BmDXXXcFoEWLFqnPfP311wD84he/AIKsr0ePHgAceuihqWObNm0KQPPmzbP8W6RTZigigipDEREghttk37H6iSeeKLdv4sSJALRt27bO1/G3x7169Sq3b8CAAQC0bNmyzteRmvFNFf5hWUWmTp2a2n7mmWeA4GGLv4X2t12SnC1btgDp37PXX38dgJkzZ6Yde9RRRwGwfPlyIL3LnH+Atu+++wLQoEHyeVnyEYiI5IDIM8M//OEPQNC1wneABjj77LOzdp2XX34ZgI8//jj13sUXXwzABRdckLXrSNXWrVuX2p40aVLaPj+Y3newf/7558t93neW91nl+eefD0C7du2yH6xUy3fffQfAr371KyDIBgFuvPFGAHr27Jnxs5kGUey3335ZjrDulBmKiBBDZui7UPif++yzT2pfXdqA/HCeu+++GwiG/IS7bPg2SYnXihUrUtu+M/Xxxx8PwIIFCwD49ttvAXjkkUcA+Otf/5r6zOrVq4Egy+/Xrx8QtCWqy018fBcY/z3zEyuE2/mHDh0KQLNmzWKOLruUGYqIkMBEDX7qHoDevXsDsNtuuwEwePDgKj/vO237n4sXL07bn812SKmd8NRKPlP3na69Jk2aAPCb3/wGgMcffzy1zw/w94P4fcahp8nx80+I77nnHiCYYHXhwoWpY3yn6vpOmaGICDFkhldffTUA8+fPB2Djxo2pfb79yGcATz75ZJXn88eWHc7VsWNHIGjbkOT861//Kvfev//9bwD69++f8TN+WrVMjjzySCB9OJfEY9GiRWmv/TA53z8wnygzFBEhhszw8MMPB2DlypVA+pPGZ599FoDhw4cDsOeeewIwaNCgCs934YUXAnDwwQenve+XDPAZoiTnvPPOS237bP/VV18F4O233waCfw8zZswA0if99W3I/j0/9Zov+y5dukQWu6QLt+VC8ET/9ttvT73Xt29fIH1yhfpImaGICKoMRUQAsJqsQdC9e3dXWUN3HN5//30guB3u1q0bAM899xyQnUkfvO7du7Ns2TKr+sj8kY0y3rRpU2rbl5MfYlfRA7DwwH/fgf70008H4N133wWCVRPHjBlTp/jCVMaVKztoIpOGDRsCcPnllwPBnIQfffQRAJ06dQKCNY/C/Bo4flKHKB7MVLeMlRmKiJDwusm1cccddwDBXyr/8CWbGaHUTXi43LRp0wA466yzgPIZ4lVXXQXAvffem/qM75Dtp17zQ/XmzJkDBJ2yQQ/MovbHP/4RgPvuu6/CY3bs2AEEGb3/WRP+4emJJ54IpE/pFhdlhiIi1JPM0GcXAJMnTwagVatWgFZSy3V+WiffRcNPzOC7z/hM32eDYTfffDMAb731FhB00/GfgeDfg0TDD8Pzq1r66dS2b9+eOsavc+MzxNrwk0D773p4JTw/yW/UlBmKiFBPMkPf0TPstNNOA9Ini5Xc5TPEiiYAzcSviuZXNfSZ4QsvvJA6xj+51rRe0fBPio844gggeLIfNm/ePCDIFm+77TYAli5dWuPr+bbk//znPzX+bF0pMxQRoR5mhn7tVP+US/Kfb6+aNWsWkP6k0a+xnM21t6VmTj755LTXfsitzwwbNWoEBMtwAFx66aUAjBw5EgjakpOkzFBEBFWGIiJAjt8m+2FX4RXv/KpqenDyw+HX1B02bBiQvj6vb6wfOHAgAAcccEC8wUk5fgZ7v2qef7DiZx8CeO+994BgxvqywmslxUWZoYgI9SQzDA8S79OnT9oxX331FRDMfZeL67FKdvhJOe68887Ue/5B2g033AAE63P7bjkSv86dOwNBl6hHH3203DHh7lEAu+xSUhX5LnPh4ZlxUWYoIkKOZ4aZ+L8gPgPwj+b98B0Nz8p/F110UWp77NixAEyfPh0I2qLKzoQu8fFZ+ahRo4Dg7i3ckfqTTz4BoLCwEAjK1LcBJ0GZoYgI9TAzHD9+PAATJkwA4Le//S0QDOqX/Beerm3u3LlAsJ6vn1ggFzrx/tD5nh9+rfR//vOfqX2vvPIKEGSCfgqvJCkzFBEhxzPD0aNHA3Drrbem3jv++OMBGDx4MAC77747AI0bN445OskFvveAXzbAD9krKioCtJJeLvGrG5bdzhXKDEVEyPHM8LjjjgNg/vz5CUciuc5PHnvIIYcAsHr1akCZoVSfMkMREVQZiogAOX6bLFJdfk2ctWvXJhyJ1FfKDEVEUGUoIgKoMhQRAcD8alTVOtjsM2BddOHknALnXNuqD8sfKuP8pzLOrEaVoYhIvtJtsogIqgxFRICI+xma2R7AvNKX7YAdwGelr3/mnPsuwmvvArwGvO+c6x/VdX7okipjM7sOuKT05Rjn3OgoriOJlvF6YHPp9bY553pEcZ3U9eJqMzSz24CvnXMjyrxvpXHszPL1hgHdgGaqDOMRVxmbWTdgMnAk8D3wHPAb55x6XEcszu9xaWXY1Tn3v2ydszKJ3CabWSczKzKzh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY7Jzb6pzbDrwEnBnV7yKZRf09jluSbYYHASOdc12ADZUc9wAw3DnXHTgH8P9ze5jZmAo+MwoYCuhRebKiKuOVwAlm1trMmgOnAh2yG7pUU5TfYwfMN7P/mNklFRyTNUmOTV7jnFtWjeN6AgeGlgvd3cyaOueWAEvKHmxm/YGPnHMrzKxn9sKVWoikjJ1zb5rZ/cBc4GtgOSXtShK/SMq41JHOuQ1m1g543szecs4tykLMGSVZGW4Jbe8ELPS6SWjbqFkj7dHAADPrW3qeVmY22Tk3qE7RSm1EVcY458YB4wDMbDiwug5xSu1FWcYbSn9+bGZPAj8DIqsMc6JrTWmj62Yz29/MGpDe/jMXuNK/KG08r+xcw5xz+zrnCoELgOdUESYvm2VcesyepT8Lgb7A1GzGKzWXzTI2sxZm1qJ0uzklzwDezH7UgZyoDEtdD8yhpOZfH3r/SuAYM3vDzIqAS6HKtgbJTdks45mlx84ELnfOfRlh3FJ92Srj9sD/mdnrwFJghnNubpSBazieiAi5lRmKiCRGlaGICKoMRUQAVYYiIoAqQxERQJWhiAigylBEBFBlKCICwP8D3P5bzM0W5d8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cdbdd6080>"
+       "<matplotlib.figure.Figure at 0x7fd2aa71fb38>"
       ]
      },
      "metadata": {},
@@ -330,10 +293,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -349,11 +312,11 @@
     "\n",
     "TensorFlow can also automatically calculate the gradients that are needed to optimize the variables of the graph so as to make the model perform better. This is because the graph is a combination of simple mathematical expressions so the gradient of the entire graph can be calculated using the chain-rule for derivatives.\n",
     "\n",
-    "TensorFlow can also take advantage of multi-core CPUs as well as GPUs - and Google has even built special chips just for TensorFlow which are called TPUs (Tensor Processing Units) and are even faster than GPUs.\n",
+    "TensorFlow can also take advantage of multi-core CPUs as well as GPUs - and Google has even built special chips just for TensorFlow which are called TPUs (Tensor Processing Units) that are even faster than GPUs.\n",
     "\n",
     "A TensorFlow graph consists of the following parts which will be detailed below:\n",
     "\n",
-    "* Placeholder variables used to change the input to the graph.\n",
+    "* Placeholder variables used to feed input into the graph.\n",
     "* Model variables that are going to be optimized so as to make the model perform better.\n",
     "* The model which is essentially just a mathematical function that calculates some output given the input in the placeholder variables and the model variables.\n",
     "* A cost measure that can be used to guide the optimization of the variables.\n",
@@ -380,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -396,7 +359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -412,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -437,7 +400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -453,7 +416,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -480,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -498,7 +461,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -514,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -541,12 +504,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
-    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=logits,\n",
-    "                                                        labels=y_true)"
+    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits,\n",
+    "                                                           labels=y_true)"
    ]
   },
   {
@@ -558,7 +521,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -583,7 +546,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -608,7 +571,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -624,7 +587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -649,7 +612,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -667,7 +630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -685,12 +648,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There are 50.000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore use Stochastic Gradient Descent which only uses a small batch of images in each iteration of the optimizer."
+    "There are 55.000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore use Stochastic Gradient Descent which only uses a small batch of images in each iteration of the optimizer."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -706,7 +669,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -715,7 +678,7 @@
     "        # Get a batch of training examples.\n",
     "        # x_batch now holds a batch of images and\n",
     "        # y_true_batch are the true labels for those images.\n",
-    "        x_batch, y_true_batch = data.train.next_batch(batch_size)\n",
+    "        x_batch, y_true_batch, _ = data.random_batch(batch_size=batch_size)\n",
     "        \n",
     "        # Put the batch into a dict with the proper names\n",
     "        # for placeholder variables in the TensorFlow graph.\n",
@@ -746,13 +709,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
-    "feed_dict_test = {x: data.test.images,\n",
-    "                  y_true: data.test.labels,\n",
-    "                  y_true_cls: data.test.cls}"
+    "feed_dict_test = {x: data.x_test,\n",
+    "                  y_true: data.y_test,\n",
+    "                  y_true_cls: data.y_test_cls}"
    ]
   },
   {
@@ -764,7 +727,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -785,13 +748,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
     "def print_confusion_matrix():\n",
     "    # Get the true classifications for the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "    \n",
     "    # Get the predicted classifications for the test-set.\n",
     "    cls_pred = session.run(y_pred_cls, feed_dict=feed_dict_test)\n",
@@ -829,7 +792,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -845,13 +808,13 @@
     "    \n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "    \n",
     "    # Plot the first 9 images.\n",
     "    plot_images(images=images[0:9],\n",
@@ -875,7 +838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -927,7 +890,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -944,14 +907,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "data": {
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0u7Vqxaodn61WpnyGGX4L7IQTTgDg3nvvBaBp06aRYk+XMk0RkQhUaYqIRGBR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\nQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cdbdb5748>"
+       "<matplotlib.figure.Figure at 0x7fd2a7fad1d0>"
       ]
      },
      "metadata": {},
@@ -968,12 +931,12 @@
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
-    "Already after a single optimization iteration, the model has increased its accuracy on the test-set to 40.7% up from 9.8%. This means that it mis-classifies the images about 6 out of 10 times, as demonstrated on a few examples below."
+    "Already after a single optimization iteration, the model has increased its accuracy on the test-set significantly."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -982,14 +945,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 21.4%\n"
+      "Accuracy on test-set: 15.9%\n"
      ]
     }
    ],
@@ -999,14 +962,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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v3x+Ap59OzErRqlUrAFauXAnAl19+WWffF154IeN12GfttddOvnfzzTcDcPjh\nhxcy7Jwp0xQRiaEqMs358xNzZN14440AjBw5Mrnum2++ASDOYMrhnoqIFN75558PZN6zhNRntVu3\nbgBstNFGyXXrrrtuxrbhai/c6wz7ApxwwglA6hlEjx49ChZ7LpRpiojEUBWZ5sKFifmdrruuvtlb\nc7fVVlsBqaflUnnmzUvM8rp06dLkew888ACQul/drFniu/6UUxITGoansgBdu3YtRZhSy6xZs5LL\n9913X8a6zTffHIB//OMfAHTp0gWA9dZbL7lNmzZtMvYJmeall14KwGWXXZZcF+6ZDh06FIC///3v\nALRr1y6//0SOlGmKiMRQ9kwzPaMImeTuu+8OwL77JiYlXHPNNQFo27YtkPmt9NVXXwHwm9/8Bkhl\nkbvssgsA22+/fXLb+p7ESXnNnDkTSN2vHjduHACffPJJ1n0nTZoEQIsWLZLvhZYR4W/o+uuvB1J/\nQ1Ic4XMIqc90YnJRGDx4MAB77bVXzscLVxMhm/zuu++S666++mogdQVy/PHHA3DggQc2IvL4lGmK\niMSgSlNEJIayXZ5//fXXAOyzzz7J9958800Axo8fn7Ft6Eo1bdo0IDE8fxC6S2622WZAKq2XyjRj\nxgwgdTn+r3/9C4DPP/88Y7tQnpDqQhfK/aqrrgJghx12AGDy5MnJbT/99FMAHn30USDVJTY8NJLi\nqN1BBOC4444D4PTTT8/7+JdffnlyecyYMQC89957QOqWji7PRUQqUMkzzXBD93e/+x2Qyi4B/vjH\nPwKw995717tvfTPmderUqcARSqH9/ve/Ty6Hm/e1H/SEMt92222BzMyiZcuWGdu++uqrQKo73YAB\nA5Lrpk+fDsDGG28MwMCBAwH47W9/C8CGG642k0yW1EUXXVTnvfAwttDCA+JQ/uGBYKko0xQRiaFk\nmWZokhAyiDDARvo3/3nnnQdA69atSxWWFMGKFSsAGDFiBAC33XZbcl3o7hq60J166qlAquxzaQ4W\n7lt+//33AFxyySXJdaHpWRiMRYprwYIFACxatCj5Xmi0Hq4aCu1Xv/oVkMo0S02ZpohIDCXLNMMT\n8SuuuAJIDQQcBiiFVON1qW6hu2N4yp0+mMqmm24KpJ547rzzzlmP98MPPwDw0UcfAXDMMccAqQFr\nw8DT9Tn66KOBzC57UjijR48GUhknpIZsS+/e2pQo0xQRiaFkmeYrr7yS8Tp0b0xvjydNQ7jXuMYa\na9RZF7o8PZQHAAAJ90lEQVQ8hraVYXCHt956K2O70OUVYO7cuRk/27dvD8CSJUsajKFDhw4AXHjh\nhRnnlcK69957gcxM/qyzzipXOCWhTFNEJIaSZZq1h4t67LHHgMwnnwcffDCQOciGVJ9f//rXAPzy\nl78E4Kmnnkqu++CDDwA488wz6923efPEn2TIVutTO8NM7wV22GGHAXDDDTcA0LFjx1ixS+OEYRch\nNVhKU6VMU0QkBlWaIiIxlOzyPHSbC2PshQ7+6Zfnw4YNA1KDK4RuWKGpSRjxeZtttqlz/NmzZwOp\nwT30gKl8wkOc0GXys88+S64LTc5efvllADbYYAMg1R02/F2kd69NH5CjPundNEPnCTUxKq4w4M6q\nbqM0Vco0RURiKFmmee655wLwl7/8pcFtQiPmMGxY+BlH6J4XRokOw0hJ+aRnfSHTzCY0YIe6mWaY\nufCaa64BUkOQQf3NnKTwwpB+YU6n0AysFB566KGM16VuTqZMU0QkhpJlmiHD6Nu3LwD9+/cHYOXK\nlcltwqyTIeNsjI8//hiAsWPHApkzT4aGzlK5wiAfq7pCCAM1hOEFpel7/fXXk8thsJ9g+PDhJY1F\nmaaISAwlyzTDvaaddtoJgHfeeafONk8//TSQyj7DTHRTpkyJfb4wSET6N5RUrttvvx1ItaBIvwIJ\nwlVDGFBYmr7w+U1/FhJaY9SetbZUlGmKiMRQ9nnP04Xud0GYuiBkmuEpWfr0BieddBIA1157LQD3\n3HNP0eOUwgll+4c//AGAL7/8ss4266yzDpC6l7nWWmuVKDppSJh6JrRkKLTwXCPMcZ5+jzu0wQ7r\nQtfbUlGmKSISgypNEZEYKuryvLbevXsDqVkqw8OBkSNHJrd59913gdRo4bWFkcKlMoXmI1988UXG\n++lzBYXGzE199JxqEubp2WSTTYDMeeuXLl0KxGvwPmPGDABuuukmAN544w0AXnvttTrbhtHiizXb\nZTbKNEVEYqjoTLNbt24A9OvXD0h13Ur37LPPZrwON4XD/DFXXnllMUOURgoPfEJj9tqOOuqo5HLo\nEiuVK4yqD6kZQeOMZRq6yoYsNQiz1R500EHJ90KzxXJRpikiEkNFZ5phiLHrrrsOSGUn6Q3W//Of\n/wCpJhBhoIfQMF4qy1dffQWkriK+++67jPU9e/YEUmUulS0MxXfZZZcl3wv3IxsjjMIfhgw855xz\nALjgggsafcxCU6YpIhJDRWeaQZhZcMKECQD885//TK579dVXgVRmGYaGk8r0zDPPALBo0aJ614fh\n3lq2bFmymKTxDj30UCDzSXbo1jhz5sycj3PyyScDqfnBwkDklUiZpohIDFWRadZ29NFH17ssle+i\niy6q9/3BgwcDqfZ/Ul1Ce01ItblsqpRpiojEUJWZplSvZcuWZbwO96DPPvvscoQjEpsyTRGRGFRp\niojEoMtzKanQWDn8DA+G4nS5EyknZZoiIjEo05SSGjRoUMZPkWqjTFNEJAYLszY2amezT4APChdO\nVejs7huWO4hSURk3fSrjePKqNEVEVje6PBcRiUGVpohIDKusNM1sAzObHv1bYmaL0l6vWaygzGyh\nmc2MzjM5h+1PNLNPou3nmtnxeZ5/tJn1ybJNOzN7xMzeNLPZZnZMPucslzKW8TnR7222mZ2Rw/Yq\n40YqYxnvb2Zvm9k8Mzsvh+2HpcU208wOyPP8L5nZdlm2qTGz581sWlTO+2Y9sLvn9A8YCpxbz/sG\nNMv1ODmeayGwXoztTwSui5Y3BpYC7Wtt0zzG8UYDfbJsMwQYHi13AJbHOUcl/itVGQPbAW8CrYAW\nwLPAT1TGTaqMWwALgM7AWsBMYIss+wwDzo6WuwOfED13aWQZvwRsl2WbO4CTouUewLxsx23U5bmZ\ndTGzOWZ2NzAb2NzMPktbf4SZ3R4tdzCzcWY21cymmNmujTlnrtx9CfA+0Cn65vqHmb0M3Glmzc3s\nmiiOGWZ2YhRjMzO7yczeMrOngFzmHnVgnWi5DYkP8Q+F/x+VR5HLuBswyd2/cfeVwAvAobnGpjIu\njCKX8a7AXHf/wN2/Bf4NHJJrbO4+i0RF3i66KrjZzKYAl5tZGzO7M4pjmpkdFMXY2szGRlci9wO5\njGTtwLrRcltgcbYd8mncvhVwjLtPNbNVHecGYIS7TzKzGmAC0N3MdgEGuHt9QzQ78IyZOXCTu/89\n16DMrAuJb7cFaXH2cvcVZjYQ+NjddzaztYBJZvYkiQL+CbA1sAkwB7glOt5w4GV3f7TWqa4HJpjZ\nYhK/9MM9+rpqQopVxjOBi81sfeBbYD/g5VyDUhkXVLHKeFPgo7TXC4GeuQZlZrsBK9x9mZkBdAR2\ndfcfzWwE8Li7H2dm7YDJ0Rfh6cByd+9mZtsDU9OONwq43t2n1zrVEOBJMxsEtAZ+nS22fCrN+e4+\nNftm7A1sGf3HIfHN0crdJwMN3a/c1d0XmdnGwFNmNtfdX8lynv5mtheJD+GJ7v5ZdM4H3X1FtE1v\noJuZHRG9bgt0BXoB97r7j8BCM3suHNTd/9TA+fYHpgB7AlsAj5vZtu7+VZY4q0lRytjdZ5nZNcBE\n4CtgGrllcCrjwivm57gxzjOz44AvgX5p74+Nyg4SZbyfmYXZ1loCnUiU8QgAd59mZrPDzu4+oIHz\n9QdGuvv1ZrY78M+ojBv8csyn0vw6bflHEql0kJ4WG7Czu2dOO7gK7r4o+rnEzB4EdgayVZp3u3t9\ngzKmx2nAQHd/On0DM8v50jDNAGBo9Mt928w+IvHBavxUfJWnmGU8EhgJEGUO83LYTWVceMUq40XA\n5mmvN4vey+Yqd69vKtLaZdzH3eenb5BWocdxArAXgLu/ZGbrAu2AZQ3tUJAmR9E3wHIz62pmzci8\nPzUROC28sOxPs9qYWZtoeW1gH2BW9PosM8tnxqUngIHhMsTMtjSzViTuqfWL7nttSiKzyOZDolTe\nzDoCXYD38oitohWyjKNtNop+1gAHA2Oi1yrjMilwGU8CtjazztFtkr7AQ9G+I8J9yEZ6Aki2uIgu\nxSFRxr+L3usJbJPDsdLLeBsSD8MarDChsO00zyfxn3mFxP2L4DTgF5a4KT8HOCkKcBczu6We43QE\nXjazN0lcGj3g7hOjdd2AT/OI8VbgXWC6mc0CbiaRbd9H4pc3BxgFvBp2MLPhZrZ/PccaCuxpZjOA\np0g8kVyeR2zVoFBlDDA+2nY8cIq7fxG9rzIur4KUcfSA70wSv7c5wGh3fzta3QNYkkeMlwBrW6JZ\n0mwS5QTwN2ADM5sLXETitg9RnKMaqOgHkfiSfZNEi4rjsp28qrpRmtkjwCHu/n25Y5HiUBk3bZa4\nhn7M3bO3h6xQVVVpioiUm7pRiojEoEpTRCQGVZoiIjGo0hQRiUGVpohIDKo0RURiUKUpIhLD/wOv\nb8i0bzekTQAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd33d82e8>"
+       "<matplotlib.figure.Figure at 0x7fd2a7fa7cc0>"
       ]
      },
      "metadata": {},
@@ -1032,14 +995,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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IrtiYPloq39Xqqkxq+fvvf9vvOSw4s/4wixZRFqsz+MwztaypSfek34w+4KE+\nfTZtm2cbx/ZlnwJbBgCADd7AfJi9A3fH/E8DAJ55RldPmZIewt+nqWlS+/MB+P3i9DNbdLQ5lVt/\nsC/QvfcEW7D19fxH/r0vvQQumGdXDdLcfIQvJ/hjPwoAqKvr2GB9aWNTwIZhGBnR6wo47sWMazb6\ncwBg5crCbQAdP6zJqM5Cx+JyAGmtOHWqKmG64kKl8Uq9Kl/2JFMtU7WxpsubeujMxiFhby8AHHOM\nloMGadnQoFNutYZOYGzypcrk2bNV+c6b1/78VCVUwIycoPLOo407si+VUPgMj+MHSn/vbF+2rPCY\nh4OJzOnX5TNLf6dz2gKcOrUy2TeMuAiX82xfoPNnOFTAfMbS/gV+mBIth/8AXPdhAMB0P+qF5339\n9XTPSm9u9nH0pY1NARuGYWREjxRw2OMdx9exVqdaaG7WMoxEaG6m6vLOtUTxstr3cgphnouBvlR1\nRjVL5Rv2bv7KT7O5fn3hvcUxgqz5ypHu2HhzkYlZ6OtlT/GZZ2pJRZbaK+yJH+1L/V1WrdIl9hKH\nNl6zRksqXyqY+F7L1cbdsS+//4ogz8wFY/xGOtevuEKP8SqXzx5bYeHxzvmNSV+Hjmtety6VvRMn\nqmH5O+bNvkAaPw2kUTeMdeb/4gk+J9OkkRpX/cLqwckxbDHwu65fr31C/J/fvPl4AMDw4ccnx1Dp\nstV2ySVaDm7TuOw3th2W7Du59gMAwH0PqB6l374vbGwK2DAMIyN6pICLjVahaqDSZU1E1bR1a3gG\n+myogGuicocvRwTH6L4i6rtkLZjWhumeCxdq+ac/ackajKo59o+WI92xMZepMsJ17Glf7HvYm5q0\n9VFZqbYeOzb1OzY10f6H+Otqy+TnP1e5UlOTRkxw9Bbvia7kvNi4K/blMvedMSM4wQov5Wh0/6Bz\nkWoqbDXQ1wus5JV9STk+NdmXzzPVd97sCxRGecw5QSOT3vct2YE//L+64WH/T3r33bpfEGw957LL\n9AONwGbXrbdqyYdwQtABxH6kr98LAHj7z7UJzrbF5MsvT3f1zYvP3nILAGDzZr23OMS7FJgCNgzD\nyAh7ARuGYWREj1wQYbOKn/f41lVHQcyhnK+r0w6G+np1qs+dO6zgmKefZpMs6MHwbgnn1BUxY4Ye\ne2718wCAl8acluz56quF9xA2zeP7L1e6Y+NiYWiEzehVq+ju+cCfS228eXMYY/OeL+kCYlggQ9YG\nJXuuWKHWZB6CAAAgAElEQVSuCzYzqwtH1Za9jbtiXy6zI4wdRQDSWCX2KiW9zMcBSFvNdIcp1D38\nLejSoevn8GRP/t/QzZQ3+wJpiCIAfDDLd6LHzfrvfhcA8Ibf+TC6GQAMuO22gkPYZclf4ajnntNj\ngtMN9D1/r/nef0YOnsYkzOwdBVI/j+9tnTVLgwvpgiiljU0BG4ZhZESP3u1hYDLVAgP8mfwiDKgG\nChOZcNvGjaoAOJyYam3RInYChQMxCjuILrzQLy7W6mrzhFQBNzbqcUOH6r4UK3FANTvpgPIL5+mO\njdkRGaokKlMqsKFDOaxby5072aIIe0e3+JLhf23RclOy5549qig2b9abyZuNu2JftiySZzeMKaOS\nYu/mqadqGT33hQMqaM/zAQATJ6riZchU+D/CVls6DLfwnki52hcoDD195BEtk//bc87R8sUXAQCT\nuQM73oB2maMOo63ZJJk/X8sRQWf9L38JAKi9/34AafBqYjjGvQFJZq8PxqjyPcQr9r54hk0BG4Zh\nZESveTdYW7BSYqXF9VQVoTpjgPvNN2t5XMuzAICfbdNk1ml6uffSgxK/pKq0aVVeHXvZ8N2rw7tS\nVbdrlyoM+p/jYZB58KMBnduY60PxwO9IFUKbM51nba22PhYsSEPLmhKBy4EylALUEe8Hd6XNlV27\nRhRcL4827si+VKSJaHoyUMCPP65llMGFixRnYShWdbW2Pq68ckjB9diCYSsCAAav92ktK/RmPrhS\nW3j3anRVgSszD3BA0EMPaTlokKbevIAjJfxAluerzkqO8ZFpOMPb/9grtaQN1vgBV6HS/t73PgcA\nOMu/XKawKcFmdjg23P9I/L1fflnLvniGTQEbhmFkRK+/02O/SWVl8f0A4Etf0vIzYzWCAafOAwBc\nfAhV7nJfNgVHsQ/UR8M3aL6+5ytUNYc9roBePPbX5EmVFaMjG7PHPWxlMCkMlS/TdV55pZbsvL86\naDmsXq0JTBYu1LK1lWn/+DuMTXf2Q5j7k41p31jFjqv2z2WYjSfMHA4kknTWqepP5BD8sC/kuuu0\nnDNLI1HSER9M6h44eBct0tI7IAfs3AkAmDfvPACpS7PYMPRyhiloyZbPXQAgTfl5y7XpNg7d5kzT\nNBcHCAGMmEj/Mc4+ey4A4JprNOUnf7L7ZkSZlYCkyUEb0sXfF8+wKWDDMIyM6PV3O3sK415aqrKw\nhzdRvr6K+curWR8wITt9kGEyHg3KvPRSr8L2au23y19v7tx0z337NGKCtV9HNVneVFpHNo6HzgLp\n0FW6wFiyI5nqgr45IB0uTtU2caKmWKyr0/Lpp99Od/YxrPTx9wcb075UQGxZtBurDKRNCibj8WEK\nA7zC2lJ1EoBCv+6cGT6CdXNhqMSOMUcBKLTVYF78xhu19D/yJJ9V6dhjB7Y7hqq7HGFrjT5xCtHR\no7Q18NpWfQeE9mpq2u1LOrzjJF4+NAR1yTFVVaqG+bMk/SJrG7QsMrMsW4Nx+gRiPmDDMIx+RK+9\n0+OpRTh6iLUGe5A/W/tCetDdvhvTV0/paCHG+rKGOzq4kvaO/uRe3xP/pF7w3Pm6vG1bEvGXqDsK\nlr6o0UpJZzZmzf3tb6fHMBUgbcB9qHjT+NIwDlgTsn/4wxrjyw5qJqE5/fR0pBbzofAe8mzj2L7x\nSEOs9xIpnLWRBvS+2WTZB7pu9gqM4cEA2s0L9WKrKl8/XyQmTwiiTGhAyjM2Yfw5qrzC3t8oyHKC\npouTnW9pVi3IOGcGlyjse+CIzNZoPVvI6RgATuHEPD1fmedb1Q2+KU7HPpCEnzzjo7Foy3jihlJg\nCtgwDCMj7AVsGIaREb0mruPs8YRNr6QJtnBZupHtYt/GY2hUY6O6HHbv1jKc5y05z83/qGWUnSQe\n+hycvsNmWl7m0+rIxjFhzuX6eg7jVn/F8uVsvjGU6n5fbkkPgjZz33xTO9tWrz4dQDpUNpx5eos/\njE3GPNs4ti/7v9j6n8zmf13a2ZP4uehW8Mletjh107DJPXhX0HHp/XHv7lV32cm13uXg3Rfv7j0q\n2XUwzx/3ENGH9BF1QdADUu7wfzl+Tp56SkuORG5tDdMPMCy1soPyFABAVdWJyRF0ef7gDm/bO/y0\nGkfoLMnhNB1PLNM0PjQ1TVyQ9xk2J5xhGEa/omTuZWZ945DXJHadK4BUAfvq8O+u3ISQFxs1mD1M\ngnHaLF+jNR2p5Yla6722XtUE548CgFWr9LwzZ1YVXC6OnQ/nBcuDUiPxUElSqIbYJKDCfdOX7Oih\nigg6lpL0iPqjcXALh3760aIAUkXDlgmHxsYKJ482pl0Z1jV5gu85CqXRAw8ASGczPPzppwEAo/fp\nszxoij7Db7SkHZeL/TN6vubiweDhhf+Gg5/7Zbpw111ashn3pv/9/JTiFdN1yG1e7BvfWzxEnoMh\nGEYGAG1t7JTnM8sZRbyahb4DZs5Mz+uzW6ZjnvlgUt7ecEOy75N+dDI7AGnqvnhPmAI2DMPIiF5T\nwAzViIfvMbSM/rT3581JDzpBP9N/uPpOLak4HnxQS/oeAaD6elW6tedozc8a0wuRglGi06dXFazj\nPVEh5m24bGxjQjc4Q3vCmjr19TKEhzFVTN1Hn3AoWbmPNmMYNE9Vy+QoQPvhz6F7NLzXPNg4ti/F\nEn3qW1r12Rs1KlWzA7zR3/HL7/sHcoKfDO69s78AoDCsihFQh1VT0UUxfD41I4C0+UGpGE1NTddw\nXqAt+VX5v0n/a5zMSaGd6Avm86nNrzPPVN982Lie3PJb/bBkiT/EH+N3emlX6mdny46Kl67+vnhP\nmAI2DMPIiF5/p8cqgqqJncRhyjjuE+a3BtJJT1tb1/jt09udn0NpWbHFQxsBYOnSwoTsFA8cDhlP\nl5QXaAPeN2tstgb2cISG7hWVVdEy9w2llKqEoUOnAUh98K+/rmWowDm0PBw6qvfgr5ZDG8cDW1gy\nUUwYZTLm+n8FAAz20+YwJ86Em24CAIz2jsW/vjbNLvN8PdOjqqKeNtz3ffjk4R8EI2kShfTJT2pJ\ng/rRMRv8/1Ve7EvFy//FOJlQd57hsWM1SorPf5hQCsuiKaJO0UiJty78awDAV4OUra2t+sNysgL+\n/n3xnjAFbBiGkRG9npCdtQd7FFlS5TY1hb7GOL6PbC3YHiazZg3JeEH6HukLoy9J0Vp05849/jxa\nlbH2zYtqILGNCdVnkjSmKEwhyeHdHMbJ3yDIYoSpAICdO7UFUV+vF6btw9Dr+JrcRmWTJxt3ZF8+\nw1Raodrnc32al0sbvHJ7yR90vPcF46qrkmPGjFEFfNQYb/vVvofeZwL/ILj2gI9/XD/wn+DkkwEA\nr/ghyEy2lBfYmohbTHGLmYn+FfqAGZ2jLYePflSXGE0yblUQPUKHrle++MY3AACP+H6mpUvfTPf1\ninrnTn0A+vI9YQrYMAwjI+wFbBiGkRG93gnXURBz2qzbHaz9Y+FOyTJLbQqH816x842hI4yJLz4E\nVpsulZXadGErjsNDGeqSp2YykNqYnQS0NUPA5s9PXTrbt2uoDjskgbd8yWbd8b5Ms8jFc8E1NWnI\nmojaMZxzjs1yuoA4nxyzUeXRxvEzvHx54fYw1C7p9PVxkLUXXwwA+INfvcMfPCwI/D/q7LP1w0c+\noiX9aT7krCKMp6KBfSzms8MvAgAs9ofEHbLlznt+ekd2yrNTrl3muQJHTPjOABhaOVVfD+kMy99v\nSHcZ611u3/wmAOALVw4ouG7qegPoAq2s1Iv35XvCFLBhGEZG9LoCjgcJ0NnOsrExiBNLVBdDoFjT\nMQSlcIZZIB1ZuGePHrN8udZ0J56o1VOYuKelRRUbRcT48Sg4X7GkNnlQEvF9UzUwAUnYSZbGn+sX\n27ZN53l7+GEtd+6MhybHn4G6OrUjh3rGgy2ANNpniEby5NrG8T0PHaol1VM4/xo7amZcqcp08m9+\nAwAY91d/pRvYNEuTXafS6tFHtWRiHf5Yl1+e7uvl3ZZDdW6zZ76nq/c3KKDc7Qv09D2hQ4/Z+Tbg\n+r/TD+xwA7Bjrs6ZN8//T6xape+UUaPYOkzPX1mpLwj+//Tle8IUsGEYRkaUzAccl/SrtLQMSfZt\namIsCpPw0E/Jmkx9j+vWhQ5eDq3VkB3WXnSbsfYKYcpE3ks8tDAPiiEkti195PS/hmF7VGhsGcQ2\nuOceKoIwLkgNMnWqKt/ZswvPFQ73pnijqOsPNu7oGaaY5UzTQPq8sW9iwwadnbvBz9ZN/6R3DQNI\n8kdhcpU+9zuqNWEPQyjDCTdWPMPzFt5jnu0LHOh7Qt8Pt96qYXxn7fFhZ2yaJM5g4A6fYGfVKjXc\n9On6nmAY3NCh6Sw7VNJ8vvvyGTYFbBiGkRElS5FCXw5rEybYCX1Xv/qVppNra6Pvd5wvWTtplTN3\nbtqrv3691mS7dmnJ5OD034TJwumX5FDa2G+WN9UQQ9821S2VaZi+k2otHqjS2MjBLirr2JIAUiXA\npDFcpnoIFTDVWkfzZ+XZxl17hrVsa+NM3ozg0ebIQw+N9WWY7pNJfXQkAVN58rzhcPo42VE0/0Cu\n7Qt0zcaLF+t74owztPzaqT7RzsleutJJHzQd+NzPnKnPNVOoUiyHUVP8P8riGTYFbBiGkRG9roDj\n2oK1CeNCQ845R8uGhmkF66lceWwYd8rO5HjmWvo/Q4XA3upDD+3SreeGeMgsoxLoswpjsFnjc8gs\n7TVqlPrXq6u1DHOMU1FPSEUxgFT5hj5KKpi8K7GQnjzDq1b54NQkAb6erKpqbHIMw39pX54/jgQI\nP/cn+wLds/F112mZjOY++c8BAM/6xck+b2RtEJ4yf/5kAOnzzv8Rvh/CsQVZ2tgUsGEYRkaUPE02\n1Wcx/xZrO/Z8xok6wgFBJO6p5Hnp92TiFKD/qYYYJoxeulTLYlMUsaVAhZv2Mhcuh7G9I3yu9u3b\nC/fl7xL6yPq7jYHuPcMzZmh/RUPDhIJjBw1Kj2ELIrZn/EwDB4d9gf3b2GfexLCFv9AP/kGnepzE\nHQNZ+5XzCzMnvdKgET1sHYatjCxtbArYMAwjI+wFbBiGkRF9NlMXZX4xuR83O9gcYVM6DELvKFSk\nv3W0HQgHYmMuhzbm59jGQ4bgoOZA7MsIqWJDh+0Zbk8xG7NTfvi8CwAAw57UWNN511+vG9g7F/Yk\nRyM86HLgRBvl4toxBWwYhpERmc5VyxqfJTuR4s6IsLYq1tFkdIzZuLSYfUsPO5kZUjl6tIaYjb36\nPgBpJ3HD3ekx7BSNZ/QuN0wBG4ZhZIQ457q+s0gz2mdR788c4Zwb1ZcXNBuXloPQvoDZuC84IBt3\n6wVsGIZh9B7mgjAMw8gIewEbhmFkhL2ADcMwMuKAX8AicpuIXBssPyUiC4LlW0Xka52c44UuXKdB\nREYWWT9PROZ0976LnOcXIrK2p+cpBXm3sYgsFJHfi8hq/3f4gZ6rVPQDGw8UkR+IyB9EpF5ELu78\nqL4lzzYWkaHB87taRFpE5LsHcq5i9EQBLwEwBwBEZACAkQCOCbbPAbBfoznnevICncfrHygichGA\nXZ3umB25tzGAzznnZvi/t3t4rlKQdxv/PYC3nXNHAZgG4P/14FylIrc2ds7tDJ7fGdDojp/14F7a\nXeCA/qDTVzT6z9MB/BjArwHUADgUwDYAA/32bwBYDuAVAN8KzrHLlwMA/DuAegBPA3gCwCV+WwOA\nbwF4CcAaAHUAagFsBrARwGoAcwFcCmAtdLK457tw/9UAFkMf2rUHaodS/vUDGy8EcELWduznNm4E\nMCRrO/ZnGwf3cJS3t/SWbQ54JJxzbpOI7BWRSdDaZSmA8QBmA9gOYI1z7n0ROQvAVAAnARAAvxCR\n05xzzwenu8gbahqAwwH8DsB/BttbnHPHi8hXAHzdOXeViNzpf5RbAEBE1gA42zm3UUSG+3XjACxw\nzp1b5Ct8G8CtAN49UBuUmn5gYwD4kYjsA/BTADc6/ySXC3m2MbcD+LaIzAPwOoCvOue2oIzIs40j\nLgPwYG8+wz3thHsBalAadWmwvMTvc5b/WwWtmeqgRg45FcBDzrkPnHObATwXbafkXwk1fjGWALhb\nRL4IPw2Bc25TMYOKyAwARzrnft61r5kpubSx53POuelQ1TEXwOf3+02zI682rgAwAcALzrnj/X3f\n0tmXzYi82jjkMgD3d7JPt+hpLgj6dqZDJX0jgL8BsAPAj/w+AuAm59xdPbgOp5nchw7u2Tl3tYic\nDOA8ACtF5GPOua3F9oXWvCeISIM/3+EistA5N68H91gq8mpjOOc2+nKniNwHVTb/1YN7LBV5tfFW\naAuOL52HAPyPHtxfKcmrjfXGRD4KoMI5t7IH99aO3lDA5wN4xzm3zzn3DoDh0BccnepPAfgLEakG\nABEZX6Q3fAmAi0VkgIiMhjrNO2MngKFcEJEjnXMvOuf+AUAzgIkdHeic+75zbpxzrhZao/6hTF++\nQE5tLCIV7JEWkUr/Hcoy2gQ5tbFvCj8WXOd0AK91tH/G5NLGAZejl9Uv0PMX8Bpoj+ayaN1251wL\nADjnfg3gPgBLve/lYQTG8PwUwAbow3MvtPmxvZNrPwbgUz40ZC6A74jIGtGQshcAvCwi40TkiR59\nw+zJq40PBfCUiLwC7fzYCOCHXf3SfUxebQwAfwvgBm/nz0NVZTmSZxsDwKdRghdw2eSCEJFq59wu\nERkB4LcATvE+HqOXMBuXHrNx6elPNs40H3DE475HciCAb+fVoGWO2bj0mI1LT7+xcdkoYMMwjIMN\nywVhGIaREfYCNgzDyIhu+YCHDBnpampqS3Qr5UdrawN2726Rvrym2bh3GTlypKvlxGAGAGDlypUt\nrhdnyDAbt6erNu7WC7imphbXXLPiwO8qZ9x++wl9fk2zce9SW1uLFSsOHnt2BRHp1emCzMbt6aqN\nzQVhGIaREfYCNgzDyIhM44D37dNyl8/IW1Wl5aGHFm4POeSQ4ts6Wh9uOxgxGxtG+WIK2DAMIyPs\nBWwYhpERfeaCYLN17950XVtb8ZLNZC6HcBvPU1FRuByen/tWV2vZ35vJZmPDyBemgA3DMDKizxQw\nVdOuYArMlhYtqcLq6grXx+oKSNXYmDFajvRzoC7zSe7WrEn3rakpvi/pb2qtKzZubdVy40Yt163j\n9lAKq2FGjaoEAIwYAb+sZUXw1NC2B4uNDaM3MQVsGIaRESVTwPRHxr7HbdvSfTh6keWFF2pJxTvg\nbj/XXijpFiwAALzlpS7dkRfceKOuv+vvk13vuEPL88/XcsIELZcv15IqcM+eLn6pMqMrNm5q0rKh\nQcstfrrG1lZ+ado2zJM9EADQ3DzBlzopwcaN2qQYP77je6I6ZuuFpSlhw2iPKWDDMIyM6HUFHPfE\n70+dHXuslpddpuXA1b/VDw88oOX9OgPIG5vTfMvxpGLe9YjJL78MAJg09SfJtuuu+zQA4LC2TbrC\nO0RrLz0OAPDII7qaftC80JmN6fcFAG+WZFvamOBoCirhWckx8+er0mXLZKWfhpC/04YN6fmpeOm/\n5zIVN+/RFLBhtMcUsGEYRkb0SAGHQ1LjGFEqrdB9C6T+WAD4wvnv6IdHntHyttsAAK/5kAZ2qB8W\nHD/Nl1Moz6iOi4QAUAkOnzIOADDAOyQHtL0LABg/fjCA8lbAXbExvydNESamam3dDQAYNWoIgFSJ\n1tWpLWbMYJkeQ594pQZBYOrUwuvRlx6u4/G8B6pkKm8OfTYMI8UUsGEYRkb0SAEXG3FFGMnAkr7B\ngv0WLtTSOwzbvPKdNnGirp83T8vrr08OGU4nMgNP775byx/9SMuvfrXdPQ3Y+75+WL1aSy/Ppl/y\nhYLbKEeK2Ziqk35WmmStd5BT9QJATY0q3ylTUFDO8i7fnTu1DNzsWL+++L28956WQ4OJwnnc0Udr\nOXZs4T1VlNO0r4ZRZpgCNgzDyAh7ARuGYWREjxqIYfOSn485Rsvt27WMO4oKXBBR7FLVv/xLwfq3\nZlwAAHj44fQQnsePu8AA3+5+17fHB9M1AeC4Wu1sw9PPafnoowXnD5v35UoxG7OTLB7sQHN+6END\nkmPYiXfqqVrSBUE3Azvswt+F7gO6F844Q0t2vhULQ/vNb7QcPrzwHMHPYRhGhClgwzCMjOiRAg6D\n66nCmACHIUxUwKtWaXnmmcEJKLs48ILy6YTCiRrr69PPcZjTJH/MYF7wuefSndmZF48K8D1GVG+X\nXpoe8vjjWrLDKWuK2XjQIC2ZJIeqlpF5xTq+aLdFiwrXs0URDt448sjCdexIpfIOWw78fal4+ZMO\nSUU4AOBPf0o/W0iaYSimgA3DMDKi14KEqNSodKnGyPTpWoZDkRPoiORBN9wAANh15ycApL5NII0y\nm7TiZwCAlh/+EAAwksfedVe6M7P7XHKJlhxL6xncpgNB9u5Nh3qUc9gUbcyUj2wwsKSdqJQBYPFi\nLdkIYGsiDlljuBqQ+noZBcjzUREvC/L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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd3192eb8>"
+       "<matplotlib.figure.Figure at 0x7fd216e500b8>"
       ]
      },
      "metadata": {},
@@ -1059,7 +1022,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1069,14 +1032,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 79.3%\n"
+      "Accuracy on test-set: 66.2%\n"
      ]
     }
    ],
@@ -1086,14 +1049,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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SS5m5Xy+88MLstrvuuguAp59+GoABAwaUP2EiEZVGIiIpVGWk+etf/xqAZZdd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\nmiIiKajQFBFJ4f8B5DaVvKWqiOwAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd2fe0b00>"
+       "<matplotlib.figure.Figure at 0x7fd258064908>"
       ]
      },
      "metadata": {},
@@ -1106,14 +1069,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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XZnWtbe1+duzQ8qWXsnWaVbXxuFMlxGvAe5XXgsu3RLF7xcpM1VYMyxtw48b8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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd2f1b860>"
+       "<matplotlib.figure.Figure at 0x7fd2a827ccc0>"
       ]
      },
      "metadata": {},
@@ -1135,7 +1098,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1145,14 +1108,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 91.8%\n"
+      "Accuracy on test-set: 91.5%\n"
      ]
     }
    ],
@@ -1162,14 +1125,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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piohEkNaMoFz55ZfYsnt+D49tttkmn9kRka2YIk0RkQgKOtIcPXo0AL///e8B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\nAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd3018b70>"
+       "<matplotlib.figure.Figure at 0x7fd2580646d8>"
       ]
      },
      "metadata": {},
@@ -1189,14 +1152,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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2ADllyQXe+zcA7HTOLdLohz8D8P/245xFoCJlXGGoWBk7574N4GgA147WrwxQ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\nMBSE/x+WxwZbwb8SZwAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd35f6ef0>"
+       "<matplotlib.figure.Figure at 0x7fd216ee2cf8>"
       ]
      },
      "metadata": {},
@@ -1211,35 +1174,35 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can also print and plot the so-called confusion matrix which lets us see more details about the mis-classifications. For example, it shows that images actually depicting a 5 have sometimes been mis-classified as all other possible digits, but mostly either 3, 6 or 8."
+    "We can also print and plot the so-called confusion matrix which lets us see more details about the mis-classifications. For example, it shows that images actually depicting a 5 have sometimes been mis-classified as all other possible digits, but mostly as 6 or 8."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 952    0    0    1    0   10   13    2    2    0]\n",
-      " [   0 1109    2    2    1    2    4    2   13    0]\n",
-      " [   6   11  889   16   16    7   17   18   46    6]\n",
-      " [   3    1   14  901    1   36    5   15   19   15]\n",
-      " [   1    1    2    1  918    0   16    2    9   32]\n",
-      " [   8    3    1   27    7  784   20    8   26    8]\n",
-      " [   7    3    2    2    9   12  920    2    1    0]\n",
-      " [   2   10   19    8    6    1    0  952    2   28]\n",
-      " [   5    6    4   17    9   37   13   13  859   11]\n",
-      " [  10    6    1    9   42    8    1   31    7  894]]\n"
+      "[[ 956    0    3    1    1    4   11    3    1    0]\n",
+      " [   0 1114    2    2    1    2    4    2    8    0]\n",
+      " [   6    8  925   23   11    3   13   12   26    5]\n",
+      " [   3    1   19  928    0   34    2   10    5    8]\n",
+      " [   1    3    4    2  918    2   11    2    6   33]\n",
+      " [   8    3    7   36    8  781   15    6   20    8]\n",
+      " [   9    3    5    1   14   12  912    1    1    0]\n",
+      " [   2   11   24   10    6    1    0  941    1   32]\n",
+      " [   8   13   11   44   11   52   13   14  797   11]\n",
+      " [  11    7    2   14   50   10    0   30    4  881]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f3cd3314b70>"
+       "<matplotlib.figure.Figure at 0x7fd216ee29b0>"
       ]
      },
      "metadata": {},
@@ -1259,7 +1222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/02_Convolutional_Neural_Network.ipynb b/02_Convolutional_Neural_Network.ipynb
index 78218b3..80f82d8 100644
--- a/02_Convolutional_Neural_Network.ipynb
+++ b/02_Convolutional_Neural_Network.ipynb
@@ -110,8 +110,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
      ]
     }
    ],
@@ -130,7 +130,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This was developed using Python 3.6.1 (Anaconda) and TensorFlow version:"
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
   },
   {
@@ -141,7 +141,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.4.0'"
+       "'1.9.0'"
       ]
      },
      "execution_count": 2,
@@ -198,34 +198,25 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)\n"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -233,23 +224,23 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
@@ -258,43 +249,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
     "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
     "\n",
     "# Tuple with height and width of images used to reshape arrays.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
+    "img_shape = data.img_shape\n",
     "\n",
     "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
@@ -313,7 +281,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -355,14 +323,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH\nHXOj4Vcv80Pv/LA8gNNOOw1I7wyfyZtvvpna9g9M/PRsZSdjaNBAf8PrA78Cnn+QGZYLEzOUpX9V\nIiLkSKfr2vDTRD300EMVHlNYWAjA5MmTgWACCInGbbfdBqRnAv6OIDxBRyZt27ZNbftMsKKhmxdf\nfHFdwpSYlG3rDU+mcdlll8UdTpWUGYqIUA8zQ79UgJ8YtjJ+2NZxxx0XaUxSonPnzkD6CoX+6X7Z\njtNl+enawgYNGgSU7yTv2yglN/nO92WfIoefHGdjSrdsU2YoIkKMmWFliz4988wzaa8vvfRSADZu\n3Fjheaoz3Xu2n2BLzR166KFpP2vixz/+ccb3w/0Yf/rTn9YuMImMn7Kr7FPkfv36JRFOtSkzFBFB\nlaGICBDjbbKft8zPOh3mO+aWHaqXaeiev82uzkp6Ur/526yyt1u6Nc5tvrO15wc9XHPNNUmEU23K\nDEVEiDEzHDBgAADDhw9PvVfZeihV8X9tfHeO8ePHA9C+fftan1Nyi39IprWR65c5c+akve7QoQMQ\nTM6Qq5QZiogQY2boV7HzK98BzJw5E4BRo0bV+Hx//vOfgWAtZMk/fr1rT52tc5tfAXP16tVp7zdp\n0gTI/YlSlBmKiJDAcDy/NnJ4u3fv3kCwCpqfqPWMM84A4He/+13qM/7JYniFNMlPfrVEP8D/lltu\nSTIcqYKfWs0PtVu1ahUA+++/f2Ix1YQyQxERcmSihlNOOSXtpwgEGca1114LaI3kXOf7/vrp9Xwv\ngMMOOyyxmGpCmaGICDmSGYpk4tuOpX7Ze++9AZg4cWLCkdSMMkMREVQZiogAqgxFRABVhiIigCpD\nERFAlaGICACWabX7Cg82+wxYF104OafAOde26sPyh8o4/6mMM6tRZSgikq90mywigipDERFAlaGI\nCBDx2GQz2wOYV/qyHbAD+Kz09c+cc99FdN0+wEigITDWOfe3KK4jyZVx6bV3AV4D3nfO9Y/qOj90\nCX6PJwN9gA3OuW5RXCPtenE9QDGz24CvnXMjyrxvpXHszNJ1GgHvAD8HPgaWAb90zr2bjfNLxeIq\n49B5hwHdgGaqDOMRZxmb2QnAVmBcHJVhIrfJZtbJzIrM7GFgFdDBzP4X2j/QzCaUbu9lZtPNbJmZ\nLTWzI6s4/ZHAW865dc65bcBjQL+ofhfJLOIyxswKgF7ApKh+B6lc1GXsnFsAbIrsFygjyTbDg4CR\nzrkuwIZKjnsAGO6c6w6cA/j/uT3MbEyG4/cBPgq9Xl/6nsQvqjIGGAUMBdQ3LFlRlnGskpzPcI1z\nblk1jusJHBhaO3d3M2vqnFsCLIksOsmGSMrYzPoDHznnVphZz+yFK7WQN9/jJCvDLaHtnUB4pfAm\noW2jZo20G4AOodf7UvlfLIlOVGV8NDDAzPqWnqeVmU12zg2qU7RSG1GVcexyomtNaaPrZjPb38wa\nAGeGds8FrvQvzKyqhtTFQBczKzCzH1GSks/KdsxSM9ksY+fcMOfcvs65QuAC4DlVhMnL8vc4djlR\nGZa6HpgDLKKknc+7EjjGzN4wsyLgUqi4rcE5tx24CngeKAKmOOfeiTp4qZaslLHktKyVsZlNAxZS\nktysN7NfRxm4xiaLiJBbmaGISGJUGYqIoMpQRARQZSgiAtSwn2GbNm1cYWFhRKHkng8++IDi4mKr\n+sj8oTLOfyrjzGpUGRYWFrJsWXU6m+eH7t27Jx1C7FTG+U9lnJluk0VEUGUoIgKoMhQRAVQZiogA\nqgxFRABVhiIigCpDEREg2cldRUQA2Lx5MwAffvhhhccUFBQAMHLkSAC6du0KwAEHHADAIYccUqcY\nlBmKiJBwZvjpp58CcM455wBw9NFHA3DZZZcBJT3ls+GLL74A4KWXXgLglFNOAaBRo0ZZOb+I1MxT\nTz0FwOzZswF48cUXAXjvvfcq/MyBBx4IlAyvA9i2bVva/p0767ZKqTJDERESyAx92wDAT37yEyDI\n3Pbaay8g+xnhYYcdBkBxcTFAalzm/vvvn5XrSPV9+eWXAPzpT38CYNWqVQDMnTs3dYwy9vywZs0a\nAB566CEAxo0bl9q3detWAGoy0/4770S7eocyQxERYswMfVbm2wcBPv/8cwCuvLJk0azRo0dn9Zp3\n3XUXAGvXrgWCv0zKCOM3ZcoUAG666Sag/FNDnzEC7LHHHvEFJpFZv75kPahRo0bV6TwHHXQQEDw9\njooyQxERYswMX3vtNSB4ahR2yy23ZO06b775Zmp7xIgRAJx5Zsnyreeee27WriPV47ODa6+9Fgju\nEMzS59ocMmRIavvBBx8EoHXr1nGEKLXgyxGCzO/YY48Fgt4ajRs3BmDXXXcFoEWLFqnPfP311wD8\n4he/AIKsr0ePHgAceuihqWObNm0KQPPmzbP8W6RTZigigipDEREghttk37H6iSeeKLdv4sSJALRt\n27bO1/G3x7169Sq3b8CAAQC0bNmyzteRmvFNFf5hWUWmTp2a2n7mmWeA4GGLv4X2t12SnC1btgDp\n37PXX38dgJkzZ6Yde9RRRwGwfPlyIL3LnH+Atu+++wLQoEHyeVnyEYiI5IDIM8M//OEPQNC1wneA\nBjj77LOzdp2XX34ZgI8//jj13sUXXwzABRdckLXrSNXWrVuX2p40aVLaPj+Y3newf/7558t93neW\n91nl+eefD0C7du2yH6xUy3fffQfAr371KyDIBgFuvPFGAHr27Jnxs5kGUey3335ZjrDulBmKiBBD\nZui7UPif++yzT2pfXdqA/HCeu+++GwiG/IS7bPg2SYnXihUrUtu+M/Xxxx8PwIIFCwD49ttvAXjk\nkUcA+Otf/5r6zOrVq4Egy+/Xrx8QtCWqy018fBcY/z3zEyuE2/mHDh0KQLNmzWKOLruUGYqIkMBE\nDX7qHoDevXsDsNtuuwEwePDgKj/vO237n4sXL07bn812SKmd8NRKPlP3na69Jk2aAPCb3/wGgMcf\nfzy1zw/w94P4fcahp8nx80+I77nnHiCYYHXhwoWpY3yn6vpOmaGICDFkhldffTUA8+fPB2Djxo2p\nfb79yGcATz75ZJXn88eWHc7VsWNHIGjbkOT861//Kvfev//9bwD69++f8TN+WrVMjjzySCB9OJfE\nY9GiRWmv/TA53z8wnygzFBEhhszw8MMPB2DlypVA+pPGZ599FoDhw4cDsOeeewIwaNCgCs934YUX\nAnDwwQenve+XDPAZoiTnvPPOS237bP/VV18F4O233waCfw8zZswA0if99W3I/j0/9Zov+y5dukQW\nu6QLt+VC8ET/9ttvT73Xt29fIH1yhfpImaGICKoMRUQAsJqsQdC9e3dXWUN3HN5//30guB3u1q0b\nAM899xyQnUkfvO7du7Ns2TKr+sj8kY0y3rRpU2rbl5MfYlfRA7DwwH/fgf70008H4N133wWCVRPH\njBlTp/jCVMaVKztoIpOGDRsCcPnllwPBnIQfffQRAJ06dQKCNY/C/Bo4flKHKB7MVLeMlRmKiJDw\nusm1cccddwDBXyr/8CWbGaHUTXi43LRp0wA466yzgPIZ4lVXXQXAvffem/qM75Dtp17zQ/XmzJkD\nBJ2yQQ/MovbHP/4RgPvuu6/CY3bs2AEEGb3/WRP+4emJJ54IpE/pFhdlhiIi1JPM0GcXAJMnTwag\nVatWgFZSy3V+WiffRcNPzOC7z/hM32eDYTfffDMAb731FhB00/GfgeDfg0TDD8Pzq1r66dS2b9+e\nOsavc+MzxNrwk0D773p4JTw/yW/UlBmKiFBPMkPf0TPstNNOA9Ini5Xc5TPEiiYAzcSviuZXNfSZ\n4QsvvJA6xj+51rRe0fBPio844gggeLIfNm/ePCDIFm+77TYAli5dWuPr+bbk//znPzX+bF0pMxQR\noR5mhn7tVP+US/Kfb6+aNWsWkP6k0a+xnM21t6VmTj755LTXfsitzwwbNWoEBMtwAFx66aUAjBw5\nEgjakpOkzFBEBFWGIiJAjt8m+2FX4RXv/KpqenDyw+HX1B02bBiQvj6vb6wfOHAgAAcccEC8wUk5\nfgZ7v2qef7DiZx8CeO+994BgxvqywmslxUWZoYgI9SQzDA8S79OnT9oxX331FRDMfZeL67FKdvhJ\nOe68887Ue/5B2g033AAE63P7bjkSv86dOwNBl6hHH3203DHh7lEAu+xSUhX5LnPh4ZlxUWYoIkKO\nZ4aZ+L8gPgPwj+b98B0Nz8p/F110UWp77NixAEyfPh0I2qLKzoQu8fFZ+ahRo4Dg7i3ckfqTTz4B\noLCwEAjK1LcBJ0GZoYgI9TAzHD9+PAATJkwA4Le//S0QDOqX/Beerm3u3LlAsJ6vn1ggFzrx/tD5\nnh9+rfR//vOfqX2vvPIKEGSCfgqvJCkzFBEhxzPD0aNHA3Drrbem3jv++OMBGDx4MAC77747AI0b\nN445OskFvveAXzbAD9krKioCtJJeLvGrG5bdzhXKDEVEyPHM8LjjjgNg/vz5CUciuc5PHnvIIYcA\nsHr1akCZoVSfMkMREVQZiogAOX6bLFJdfk2ctWvXJhyJ1FfKDEVEUGUoIgKoMhQRAcD8alTVOtjs\nM2BddOHknALnXNuqD8sfKuP8pzLOrEaVoYhIvtJtsogIqgxFRICI+xma2R7AvNKX7YAdwGelr3/m\nnPsuwmvvArwGvO+c6x/VdX7okipjM7sOuKT05Rjn3OgoriOJlvF6YHPp9bY553pEcZ3U9eJqMzSz\n24CvnXMjyrxvpXHszPL1hgHdgGaqDOMRVxmbWTdgMnAk8D3wHPAb55x6XEcszu9xaWXY1Tn3v2yd\nszKJ3CabWSczKzK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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6c822588>"
+       "<matplotlib.figure.Figure at 0x7f894a0bd7b8>"
       ]
      },
      "metadata": {},
@@ -371,10 +339,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -419,7 +387,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -429,7 +397,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -469,7 +437,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -543,7 +511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -590,7 +558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -632,7 +600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -648,7 +616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -664,7 +632,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -680,7 +648,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -698,7 +666,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -719,7 +687,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -728,7 +696,7 @@
        "<tf.Tensor 'Relu:0' shape=(?, 14, 14, 16) dtype=float32>"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -748,7 +716,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -769,7 +737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -778,7 +746,7 @@
        "<tf.Tensor 'Relu_1:0' shape=(?, 7, 7, 36) dtype=float32>"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -798,7 +766,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -814,7 +782,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -823,7 +791,7 @@
        "<tf.Tensor 'Reshape_1:0' shape=(?, 1764) dtype=float32>"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -834,7 +802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -843,7 +811,7 @@
        "1764"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -863,7 +831,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -882,7 +850,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -891,7 +859,7 @@
        "<tf.Tensor 'Relu_2:0' shape=(?, 128) dtype=float32>"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -911,7 +879,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -923,7 +891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -932,7 +900,7 @@
        "<tf.Tensor 'add_3:0' shape=(?, 10) dtype=float32>"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -957,7 +925,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -973,7 +941,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1000,9 +968,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-31-2dd067a7547b>:2: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "\n",
+      "Future major versions of TensorFlow will allow gradients to flow\n",
+      "into the labels input on backprop by default.\n",
+      "\n",
+      "See @{tf.nn.softmax_cross_entropy_with_logits_v2}.\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=layer_fc2,\n",
     "                                                        labels=y_true)"
@@ -1017,7 +1000,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1042,7 +1025,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1067,7 +1050,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1083,7 +1066,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1108,7 +1091,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1126,7 +1109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1151,7 +1134,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1167,7 +1150,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1187,7 +1170,7 @@
     "        # Get a batch of training examples.\n",
     "        # x_batch now holds a batch of images and\n",
     "        # y_true_batch are the true labels for those images.\n",
-    "        x_batch, y_true_batch = data.train.next_batch(train_batch_size)\n",
+    "        x_batch, y_true_batch, _ = data.random_batch(batch_size=train_batch_size)\n",
     "\n",
     "        # Put the batch into a dict with the proper names\n",
     "        # for placeholder variables in the TensorFlow graph.\n",
@@ -1239,7 +1222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1257,13 +1240,13 @@
     "    \n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "    \n",
     "    # Plot the first 9 images.\n",
     "    plot_images(images=images[0:9],\n",
@@ -1280,7 +1263,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1291,7 +1274,7 @@
     "    # all images in the test-set.\n",
     "\n",
     "    # Get the true classifications for the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "    \n",
     "    # Get the confusion matrix using sklearn.\n",
     "    cm = confusion_matrix(y_true=cls_true,\n",
@@ -1336,7 +1319,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1347,7 +1330,7 @@
     "                        show_confusion_matrix=False):\n",
     "\n",
     "    # Number of images in the test-set.\n",
-    "    num_test = len(data.test.images)\n",
+    "    num_test = data.num_test\n",
     "\n",
     "    # Allocate an array for the predicted classes which\n",
     "    # will be calculated in batches and filled into this array.\n",
@@ -1365,10 +1348,10 @@
     "        j = min(i + test_batch_size, num_test)\n",
     "\n",
     "        # Get the images from the test-set between index i and j.\n",
-    "        images = data.test.images[i:j, :]\n",
+    "        images = data.x_test[i:j, :]\n",
     "\n",
     "        # Get the associated labels.\n",
-    "        labels = data.test.labels[i:j, :]\n",
+    "        labels = data.y_test[i:j, :]\n",
     "\n",
     "        # Create a feed-dict with these images and labels.\n",
     "        feed_dict = {x: images,\n",
@@ -1382,7 +1365,7 @@
     "        i = j\n",
     "\n",
     "    # Convenience variable for the true class-numbers of the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "\n",
     "    # Create a boolean array whether each image is correctly classified.\n",
     "    correct = (cls_true == cls_pred)\n",
@@ -1421,14 +1404,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.4% (1036 / 10000)\n"
+      "Accuracy on Test-Set: 10.6% (1059 / 10000)\n"
      ]
     }
    ],
@@ -1447,14 +1430,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:      1, Training Accuracy:   4.7%\n",
       "Time usage: 0:00:00\n"
      ]
     }
@@ -1465,7 +1448,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 45,
    "metadata": {
     "scrolled": true
    },
@@ -1474,7 +1457,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.9% (1090 / 10000)\n"
+      "Accuracy on Test-Set: 11.2% (1123 / 10000)\n"
      ]
     }
    ],
@@ -1493,7 +1476,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 46,
    "metadata": {
     "scrolled": true
    },
@@ -1512,22 +1495,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 66.3% (6634 / 10000)\n",
+      "Accuracy on Test-Set: 67.3% (6729 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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2VC0LoDJu+1TG6ej2XEQkBVWaIiIpqNIUEUlBlaaISAqqNEVEUlClKSKSgipN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\nRURSUKUpIpKCKk0RkRT+HzFENlh4BVlyAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d69ee22e8>"
+       "<matplotlib.figure.Figure at 0x7f8947975550>"
       ]
      },
      "metadata": {},
@@ -1549,7 +1532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 48,
    "metadata": {
     "scrolled": false
    },
@@ -1558,16 +1541,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    201, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    301, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    401, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    601, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    701, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    801, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    901, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:03\n"
+      "Optimization Iteration:    101, Training Accuracy:  70.3%\n",
+      "Optimization Iteration:    201, Training Accuracy:  79.7%\n",
+      "Optimization Iteration:    301, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    401, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    601, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    801, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    901, Training Accuracy:  87.5%\n",
+      "Time usage: 0:00:02\n"
      ]
     }
    ],
@@ -1577,7 +1560,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 49,
    "metadata": {
     "scrolled": true
    },
@@ -1586,15 +1569,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 93.3% (9329 / 10000)\n",
+      "Accuracy on Test-Set: 93.0% (9298 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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EiUhebNqUnBDJd4+aM2dOyuPFixcD0K5dOwAuvDC5+OV++yVWsMmaIk0RkRhqVKTpI8xr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\nadYZM2ak/PYaN26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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a4b4c88>"
+       "<matplotlib.figure.Figure at 0x7f8947d4b5f8>"
       ]
      },
      "metadata": {},
@@ -1616,7 +1599,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 50,
    "metadata": {
     "scrolled": true
    },
@@ -1625,97 +1608,97 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:   1001, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   1101, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1201, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1501, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1301, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  93.8%\n",
       "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   1901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2101, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2201, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2401, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2701, Training Accuracy:  93.8%\n",
       "Optimization Iteration:   2801, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   2901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3001, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3201, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3301, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3401, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   3501, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   3701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3001, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3101, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3301, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   3401, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3701, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   3801, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   3901, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4001, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4201, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4401, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   4501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   4801, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4901, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   4001, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   5201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5301, Training Accuracy:  95.3%\n",
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-      "Optimization Iteration:   8301, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   8301, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   8501, Training Accuracy:  95.3%\n",
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-      "Optimization Iteration:   8801, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   8501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8601, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   9101, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   9101, Training Accuracy:  96.9%\n",
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       "Optimization Iteration:   9301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9501, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9801, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   9901, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:27\n"
+      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:24\n"
      ]
     }
    ],
@@ -1725,7 +1708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 51,
    "metadata": {
     "scrolled": true
    },
@@ -1734,15 +1717,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.5% (9852 / 10000)\n",
+      "Accuracy on Test-Set: 98.7% (9868 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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gjE8K+722BbJZuetx4NTwOPsDHzvnGlPTPE0+yzj87N4DzApbZPHXyqmMCbvq9gOeyCZ9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\nfBw2swF6APPCfcu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KUaYpIpJCw2eaDzyQWTI7ZJoPPvggADvvnJmwO2SiUl8+/zyzesH8+fMB+M1vfpPz/kcffZR9HMr45JNPztkmZC577bVXxeKU4iSzyzXWWCPnvdGjRwOwYsUKAPr37w/AnnvuWZ3gykyZpohICg2ZaU6Y0HJ2/YsuugiApUszS7n8/Oc/B5Rp1oPLL788+zi0BEKmuWDBAiBuKYRWRHJy7PDar3/965znM2bMAODRR+OVdXv1KrjUtdTI2LFjgfi6w80335x97/vf/35NYmoPZZoiIik0ZKbZvG8L4NVXXwVa9o1J9YUrqeeccw6Q2z/ZPJPs168fAH369AFg2LCWq7A2HyExYMAAgOwkEwsXLsxuq0yzNsIVcoj7MNsS+rHDT1CmKSLSYTVkpplPyEYa9cpcRxD6lcPPH/+45RLXJ510EgDbbrstAN26dSt43Hnz5uUcNzmKQmqrb9++2cfffPNNq9usWrUq5/kpp5ySfRzKvxHGcirTFBFJQZWmiEgKHaZ5PnnyZCBusrV2QUGqY9y4cTk/y2XlypVAPFwpXPTRxZ/a22CDeOWIQYMGAfDcc8+1um3zwe8QXzxS81xEpIPpMJlmyCzDAGhdCOp4mrcmdCGofoQhYxAPWg+D2dvKOBuVMk0RkRQaMtNcsmRJ9nG4XTJkIWEyAOl45s6dC8TDynr37p3zszXvvZdZdDAMUwrbJvvgpLzCMLJtttkGUKYpIrJaa4hMM2QLITtITng6fvx4IB4c+8wzz1Q5OqmWMEVc6MsM/dahHzsptDzC7bXNM81f/vKX2W010qIybrnlFiC+3bWYtdXDbbVTpkwBcvtK64UyTRGRFBoi0wwTNFx33XUAXHXVVdn3QtZxwQUXAHF/inQcYWq55HRxANdffz2QexW9+UQgm222GQD7778/AD/72c9y3pfKCxOuhKy/tXGawZtvvgnAL37xCyB3+rh6oUxTRCSFus4077//fiCeWuzKK6/MeQ5xxhAyTekYjj322Ozj5n2Z4WdY5iKZNbZnIhCprJDdh4nCG50yTRGRFFRpioikUFfN8zBf4qRJk4C4Mzg0x4444ggA5syZk90nNN3CxYKO0gRYXYQumAsvvBBouWYQxOUfmtphlnANFeq4wpCxwYMHAzB06NBahpNDmaaISAo1zzTDwHWIs43wLROmmHr33XeBeNqoMDUYxLdNXnzxxQA0NTUBMGrUqMoFLe0WMstQxqGlEMp0+PDhQNzagDjTDENXlGE2puYzt+fbJlzsDTcl1BNlmiIiKdQ80zzuuOOyj8ON/RtuuCEQ3+oWbn0Lk82GyWghHm4Sso8rrrgCiPu/tO557YSJVUIrAOIMM2SWoXyaDzpvbdq3RlqxUGKhddGpUyZHyze4PQjbhDoh2adZ60mnlWmKiKRQs0wzZCHPPvts9rXQh/n000/n3be1Acu77LILEPeFhWw19HEmt5HKCqMgDjroICC33zr0QU+YMAFo2T8Z9k1mms37NKWxJG97Tuv3v/89AGeeeWb2NWWaIiINpGaZZvOlC6C8V0XDWL4wcS0o06yWkBGGDDNklcn32soWwq2yyXGaYVRFrTMMaZ+JEycCsN1229U4kvJQpikikoIqTRGRFGrWPG9tzepbb70VgM033xxoX8d/GN4QBkknm/8a8F4d4VbI8H+fLOO2mtih3JrPaAQazN7owoxTffv2BeI5M1tTzAD4WlOmKSKSQs0yzZBFLly4MPvabbfdBsDxxx8PwPz584Hi5soME3Y0n+RDE3hUXxgyFrLGcCEH4vII5R/mvwzrPoVB7+PGjcvuowt4HUMo4z322KPgtmFwe7ihoZ4uAirTFBFJwZqvu5LGrrvu6sWsMFesMLD5wAMPBOLV6/J9y4QZvkNWGm7wD+sJlXtAtJnNcPddy3rQOlaOMk7e9hrKKfQvf/LJJ0A8QUNoIfztb3/L7lPtLENlXBnhs3nuuecC8cD1pG+++QaIM82wRtCYMWPKGkspZaxMU0QkhZpP2JEUJmsIA9PbEjJSiPvNwoQPJ598MlBffSCru+Rtr6F/Mtx0cPbZZwPxypJh3R+VX8cTynTgwIFA65lmI1CmKSKSQl1lmsGee+6Z9/3k6oMrVqyodDhSQWEMX+jL1JjMji+0BsPPRqNMU0QkhbrMNGX10ehZh6x+lGmKiKSgSlNEJAVVmiIiKajSFBFJQZWmiEgKqjRFRFIoacIOM1sCvFdww46lj7tvUOsgqkVl3PGpjNMpqdIUEVndqHkuIpKCKk0RkRRUaYqIpJC30jSz9c1sZvRvsZktSjxfs1JBmdm5ZjbHzGab2d1mtlaB7S9PxPaGmR1c4vmfM7OdCmxznpnNM7PXzewJM9u8lHPWSi3K2Mz6mNnTZjY3KufTithnjJktieKaZ2Y/KjGGu8xsaIFtzk/8X8wxs6/NbN1SzlsLNfwc3xnKrMjta1HGPc3skehzPMfMjit4YHcv6h9wCXBuK68b0KnY4xRxnj7AX4Au0bEnAaMK7HM5MC56vD2whOgiV2KbzilieA7YqcA2+wBdo8enA3eX6/+gVv+qWMabhP9fYB3gbaBvgX3GAOOjx98ClgK9Sijju4ChKbYfBjxe6zJqlDKOjjkIGADMLHL7qpcx8B/AFdHjjYBlhc7Rrua5mW0VZQl3A3OAzc1seeL9kWZ2W/R4IzO738ymm9nLZrZ7Eaf4P2Qqzc5AN+DDYmNz99lk/gB6Rt80t5jZy8CVZtbDzO6I4njNzA6NYuxmZvdG326TonMXOs80d/8ievpnYLNiY2wElSxjd//Q3WdGjz8F5gObFhubuy8G3gV6R62MiWb2PHCHmXU2s19GccwyszFRjJ3M7GYzm29mTwBpp4b/N+CelPvUtUp/jt39GeCT9sRWxTJ2YO3ocQ8yFfU3+XYoZWq4bYHj3H26meU7zo3A1e7+ZzNrAv4AbG9muwEnuPuPkxu7+3tmdgPwPvAV8Ii7Tys2KDMbCHzp7p9YZmLbjYHd3X2VmV0NTHH30WbWE3gp+s89DVjm7v3MbGdgeuJ4twM3hA95G04EHi02xgZSkTJOMrMtybQOXik2KDPbikyL5J1EnHu5+5dmNhb4yN0HWKZb589m9jiwO7AF0J9MpjsXmBAd7wrgeXf/Yxvn6wHsB5xUbIwNpOJl3B5VLOMbgD+Y2YdkWj1HeJR2tqWUSvNtdy9mCbv9gG2iCgwyGWBXd38JeKn5xma2PnAImV/+U2CSmY109/9X4Dw/MbPRwApgROL1e919VfR4MHCgmZ0fPe8C9Ab2Aq4GcPfXzGxO2NndT8h30uicOwBnFIivEVWkjAMzW4dM98vp7v5ZEec5xsx+QObLdIy7L4/O+aC7fxltMxjoZ2Yjo+frAluTKeN7or+FD8zs6XBQd48XZm/dYcAz7v73ImJsNBUt43aodhkfBLxMpiuhLzDFzHbI9/dYSqX5eeLxKjJN4iDZvDVggLv/o8jjDgbecvelAGY2GRgIFKo0r3H38QXiNDJ9HG8nN0j8IaRiZgcAPwEGpfj9GkmlyhjLXIC4H7jd3R8qcre73X1cgTgNGOvuTzY7XynraIwE8q/217gqVsbtVO0yPgG4JMouF5jZ+2Qqz1fb2qEsQ46imn2ZmW1tZp3IdJoHU4FTwxMrcFUaWAjsYWZdLVOb7QvMi/a9OvRDttNjZC7ahFh2jh4+CxwdvfZtYLtCBzKzXYFfAUNCBd+RlbOMo3K9g8wFghubvXemmZXS1HsMGBuamma2jZl1JVPGI6J+r03JZBYFRd04A4GHS4ipIZT5c9ymOivjhWTqGMxsY2Ar4K/5dijnOM2fkvllXgA+SLx+KvC9qMN2LlG/kJntZmYTmh/E3Z8HHgJeA94AvgZ+G729I7C4hBgvBbpbZljSHDJXEgFuAtY3s3nAxdG5ieK8vY0/kGuB7mS6D2ZGGXFHV5YyJvPH/G/ADy0e+rJ/9F4/4OMSYrwVeAuYaWazgVvItKjuI/MBmQvcDrwYdjCzK8zsoDaONxx4NHHRr6MrVxljZvcCfwL6m9kHUVcW1FcZXwIMMrNZwBNkRhYsy3fyhrn3PMpOHnX3A2odi1SOmT0CHObuX9c6FqmMRi/jhqk0RUTqgW6jFBFJQZWmiEgKqjRFRFIoZZwmvXr18qampjKF0hhmzJix1FejWb1Vxh2fyjidkirNpqYmpk8v5maCjsPMVqtlAVTGHZ/KOB01z0VEUlClKSKSgipNEZEUVGmKiKSgSlNEJAVVmiIiKajSFBFJoaRxmiL5PPvsswCccsop2dcWLFgAwJ577glAv379cvaZN29ezr4QTxIdJpf53e8y8wGPGjWqEmGL5KVMU0QkhYplmv/85z8B+PjjzFyjc+fOBWDp0swk56+8kllH69FH4/XIPv88M6P9kUcemXOss88+G4B1180sOd21a9dKhS1lNH/+fCDOLiHOGv/0pz8B8NxzzwFxFhneTy5BMnz4cAC23XZbAA4//PBKhi2SlzJNEZEUypppfvhhvDz5jTdmln655pprWt22eWaRdN111+U8v/baawH4/ve/D8Cll16afW/vvfcuIWKppNBv2dpE1xMmtLpCQot9oWW/pzS2v/89s6jnIYcc0uK90aNHA3DiiSdWM6RUlGmKiKRQ1kxz/Ph4Bd2QLfbq1QuAXXbZJWfbkH189lm8vPCLL75IPs8//zwAP/3pT7OvPflkZhXPtddeu71hS4WEDDHZmgiPw9+F+ic7vhUrVgDxZ3WnnTLrFIbPM8T1wcsvvwzAHnvsAUD//v2rFmexlGmKiKRQ1kzzrLPOyj4+9thjAejRowcAW2yxRav7fPFFvDLq1KlTgbgfNPlNlDRjxozs40ceeQSAkSNHtjdsqbBk/2S4av7zn/8cUKbZkc2ePRuAIUOGAPE1j5BN7r777tltQyszjLqZNWsWoExTRKThqdIUEUmhrM3zjTfeuNXH+SQHqh966KEA7LfffgAcddRRQNwEb82YMWOAeOD7gQcemCJiqYYLLrgg+/iggw4C4oHv4WcYuC6Nb9myZQAcc8wxAPz1r38F4gtAO+64IwBDhw7N7tP8IvCkSZOA+ux2U6YpIpJCXU7YEbLPhx9+GIizkylTprTYduXKlQAcfPDBQDy8oXv37hWPU4qz//77Zx+HoWdhIa/33susb6VMs7G9+eab2cennnoqEF/M2WGHHQB44YUXcvY54ogjso/DMMIw9GjRokWVC7ZEyjRFRFKoy0yzuf/+7/8GYNNNNy24begXnTZtWkVjkvYJA97DsLEw9CiZjUrjeOmllwA444wzsq+FyXjCjQzDhg0DoHPn3Opmyy23bHG8sE8YrhQy2L59+5Yz7JIo0xQRSaEhMs2ePXsCsO+++wLx7VitCRlMmIquHgfHrs5+9rOfAfFEwmGy4fBzr732anPf0Kf9wAMPAHDrrbcCubdphtszw5SD3/nOd8oWu7QUbpcO2WVr/uu//guAp556CohHxYQbYFoTbq8Ofd7KNEVEGlRDZJprrbUWAPvssw+QP9Ps1CnzPdClS5fKByapNZ/EI/wM4zU32GADIB6nB/Dggw8CcSui+b7JTDNMch1GU4TsRtPLVUbylubm/vVf/xWAgQMHArB8+XIg7v+86qqrKhxdZSjTFBFJoSEyzeCcc84B4jsOIJ6gOAgTnB533HFAvJyC1JcwiUeYwCMsvtZ8EbXWXgtXY8MdJ8ksMkwAEpbYGDRoEBCPC+3du3e5f5XVWii/ZOsvXEdoqz85ZKcHHHBAi/dam7C63ijTFBFJQZWmiEgKDdE8X7x4MRAPIwkTAEDLdD48D830r776KvteuKAktRcm8Qi3yAahKR4uCEHc5D7ppJOA+JbLbt26tThuaPqF4SyTJ08G4rlekxeYpHSbbLIJkH/4UHOh2Z689XK99dYDWl8zrN4o0xQRSaGuMs133nkHiG/NCoOZw0Do1r6F2vpmCoPbw22VEA9xaL5ekVRfKJ/QMgg/L7zwQgAuu+yydh03ZJ8howx/HyHjXLLgDjuKAAAItElEQVRkCZCbyUpthJtWALbffnsA5syZU6twiqZMU0QkhZpnmmEqN4ARI0YA8Oqrr5bt+MmhEIcddhgQT1mV/KaT6gpDgpr3YYZ+y3JpPgA+ZJwnn3xyWc8jpQmtv+aZZmh91hNlmiIiKdQ800wOVA9X0JoLV9u22267Fu+FiYrDLVrNhat7EE90usYaa7QvWCmbwYMHA/DYY48BcOKJJwLlG3weJgBpPrpCGWZ9CuucT5w4Mef1MHFxuPmhHijTFBFJoeaZZjKzeOihh4B4jGUQlq5obQmLMD3Y2LFjWz1+uCoHcNppp5UWrLTLvHnzso/D7a1hKrEwFVyY0q1cwuTGoS9TUwTWt+9973tAvNTNl19+CdTnSBdlmiIiKajSFBFJoebN86Rwm+OGG25Y9D4hre/RowcAn376ac77YZ5GgP/93/8Fil+TXcojuYpouM2xmJna2+Oiiy4C4gtM4ULQ+eefX9bzSHmFz2ZolgfJW6brhTJNEZEU6irTbI9woaepqQmAN954A4gvACSHNIV1R6S6wkB2iMslzI3a1mD25DroobUQXku2HiAesA5xhtl8JcQw6YfUpzCsMNxwEj635bzRpVyUaYqIpNDwmWYQpqY677zzcl5PrmIXZnHfeuutqxeY5AwnCn2MYSb10McZXi9m5va2nkM8YUeYei78lPq2/vrrA7DmmmsCcdmGmeHriTJNEZEUOkymefzxxwNw5513AvHUY8nV8s4991wAhgwZAsTfblJZyWwvZIVh1cggOQAectf9Ce999NFHQHw7bWsD4s8880wgt09UGk89T0asTFNEJIUOk2mGqcXC7XP3338/ACtXrsxuEzIVLXtRXcllKdo7ubCsHo488kgAbrrpphpH0jZlmiIiKXSYTDM45JBDcn6KSOO44oorANh0000BuO2222oZTquUaYqIpKBKU0QkhQ7XPBeRxrX22msD8SoL4Wc9UaYpIpKCKk0RkRRUaYqIpGDNV+tLtbPZEuC98oXTEPq4+wa1DqJaVMYdn8o4nZIqTRGR1Y2a5yIiKajSFBFJIW+laWbrm9nM6N9iM1uUeL5mJQIys/6Jc8w0sxVmlnfBcjMbY2ZLou3nmdmPSozhLjMbWmCbw81sVnTOV8xsYCnnrJValHF03g/M7I3oPC8VsX0tyrinmT1iZq+b2RwzO66Uc9ZKrco4Onfn6HPyQBHbXp6I7Q0zO7jEcz9nZjsV2KbJzKZFMT5lZpsUOm7ewe3u/jGwU3TwS4DP3P3aZic1Mn2jqwqdrBjuPjdxzv8DLAIK/ocDd7v7ODP7FjDbzB5y9+ykjWbW2d2/LkeMkceBye7uZrYLMBHYvozHr4palHHCnu6+PMX21S7j04GZ7n6wmW0EzDez35f5HBVX4zI+G5gNdCu0YeQadx9vZtsDT5nZhp648FKBMr4e+K27321mg4ErgBPy7dCu5rmZbWVmc83sbmAOsLmZLU+8P9LMboseb2Rm95vZdDN72cx2T3GqHwLz3P2DYndw98XAu0Dv6Jtropk9D9wRfev9MopjlpmNiWLsZGY3m9l8M3sCaDm7bcvzfJYozO5Ah7qiVsUyTq1aZUymTNeOHvcAlgLflP83qo1Kl7GZ9SHzGb49bWzuPhswoGfUKrjFzF4GrjSzHmZ2RxTHa2Z2aHS+bmZ2b9QSmQR0KeJU/YFp0eMngYIr8JXSp7ktcL279yeTDbblRuBqd98VOAoIhbCbmU0ocI6RwD1pgjKzrYA+wDuJOPd191HAycBH7j4A+C5wqpn1Bo4AtiDzH3gCMDBxvCvM7KA2znWEmS0gkwmPSRNng6hkGTswzcxmmNmJaYKqYhnfAOxkZh8CrwOnJ7OeDqKSZTwe+AntSCgs0931pbt/Er20MbC7u58H/AcwJSrjfYDrzKwLcBqwzN37AZcDOyeOd3sbTfXXiSvK4cA6ZrZuvthKuff8bXefXsR2+wHbWDx9fU8z6+ruLwFt9mVF/wkHk0nvi3GMmf0A+AoY4+7Lo3M+6O5hBfrBQD8zGxk9XxfYGtgLuCdqmnxgZk+Hg7r7hW2d0N3vA+4zs72By6LjdySVLOPd3X1R1NR+wszmufsLBc5T7TI+CHgZGAT0BaaY2Q7u3pHWgq5IGVumv/h9d59pZvuliOcnZjYaWAGMSLx+b6LrYDBwoJmdHz3vAvQmU8ZXA7j7a2Y2J+zs7m01uc8Cboq+uJ8BFlOgNVFKpfl54vEqMql0kEyLDRjg7v9IefyDgZeSfVYF3O3u41p5PRmnAWPd/cnkBmY2LGVsOdz9KTO708z+JWUfXb2rWBm7+6Lo52IzexAYABSqNKtdxicAl0TZ5QIze59M5Vl/i3G3X6XKeCBwuJkNiY6zjpnd6e7HF9jvGncfXyBOA4a6+9vJDawd6wpFf4fDov3XAYYX+lIsy5Cj6BtgmZltbWadQhCRqcCp4UkbKXJr/o1mTXMzO9PMflxCqI8BY82sc3S8bcysK/AsMCLq99qUTGaRV9QfZNHjXcl0onekCjNHOcs46pPqET3uTqbfa3b0vG7KGFgI7BsdZ2NgK+CvJcRW18pZxu5+nrtv5u5NwCjg8VBhmtnVoR+ynR4jc5EuxBKa4c8CR0evfRvYrtCBzKxX+BwDFxB1O+RTznGaPyXzy7wAJC/cnAp8L+qUnwucFAXbZl+Ima0N7E3Lq+b9gI9LiPFW4C1gppnNBm4hk23fR+YDMpdMp/WLiVja6u86iswV3Jlk+ntGtLJNR1OuMt4YeN7MXifT/J3s7lOj9+qpjC8BBpnZLOAJ4Fx3X1ZCbI2gbJ/jPHYk0wxur0uB7pYZljSHTDkB3ASsb2bzgIuB18IOefo09yXTingTWA+4qtDJG+o2SjN7BDis0YZ8SPFUxh1blNU96u4H1DqW9mqoSlNEpNZ0G6WISAqqNEVEUlClKSKSgipNEZEUVGmKiKSgSlNEJAVVmiIiKfx/XUGar1bBMx4AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a553a58>"
+       "<matplotlib.figure.Figure at 0x7f8947975748>"
       ]
      },
      "metadata": {},
@@ -1753,23 +1736,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 970    0    1    0    0    2    2    1    4    0]\n",
-      " [   0 1127    3    0    2    0    1    1    1    0]\n",
-      " [   0    2 1022    1    2    0    0    4    1    0]\n",
-      " [   0    0    2  999    0    3    0    4    2    0]\n",
-      " [   0    0    0    0  982    0    0    0    0    0]\n",
-      " [   1    0    1    7    1  879    1    1    0    1]\n",
-      " [   4    2    1    0   12    8  931    0    0    0]\n",
-      " [   0    1    5    0    1    0    0 1018    1    2]\n",
-      " [   3    1    3    3    4    3    0    3  950    4]\n",
-      " [   1    4    0    1   18    3    0    6    2  974]]\n"
+      "[[ 972    0    1    0    0    0    3    1    3    0]\n",
+      " [   0 1128    3    1    0    0    2    0    1    0]\n",
+      " [   1    0 1021    2    1    0    0    2    5    0]\n",
+      " [   0    0    0 1007    0    1    0    0    2    0]\n",
+      " [   0    0    2    0  969    0    2    0    0    9]\n",
+      " [   1    0    1   13    0  871    3    0    1    2]\n",
+      " [   1    2    0    0    2    3  948    0    2    0]\n",
+      " [   0    2   11    6    0    0    0 1003    1    5]\n",
+      " [   1    0    4    4    0    2    0    4  954    5]\n",
+      " [   0    3    0    4    2    4    0    1    0  995]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d69c24668>"
+       "<matplotlib.figure.Figure at 0x7f88a807ee48>"
       ]
      },
      "metadata": {},
@@ -1799,7 +1782,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1858,7 +1841,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1923,7 +1906,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1944,14 +1927,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
      "data": {
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+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAADV5JREFUeJzt3X+oXPWZx/HPUzeNYKrmNtMYbextc0UJwabLEFYra1dtuAmB6D+SICUFaQoqrlB0xaKr+E9YbYqgVG80NC6tbTGVBAmubqhooJaMJv6Ku+uvG5twzZ0YoSkIadJn/5iTcqv3fGecc2bO3DzvF1xm5jznzHlyyOeemfmeO19zdwGI5wtVNwCgGoQfCIrwA0ERfiAowg8ERfiBoAg/EBThB4Ii/EBQ/9DPnc2bN8+Hh4f7uUsglPHxcR0+fNg6WbdQ+M1sVNIDkk6T9Ki7b0itPzw8rEajUWSXABLq9XrH63b9st/MTpP0kKQVkhZLWmtmi7t9PgD9VeQ9/zJJ77j7e+5+TNKvJK0upy0AvVYk/OdJ+uOUxweyZX/HzNabWcPMGs1ms8DuAJSp55/2u/uYu9fdvV6r1Xq9OwAdKhL+g5IWTnn81WwZgBmgSPh3S7rAzL5uZl+UtEbS9nLaAtBrXQ/1uftxM7tJ0n+pNdS32d3fLK0zAD1VaJzf3XdI2lFSLwD6iMt7gaAIPxAU4QeCIvxAUIQfCIrwA0ERfiAowg8ERfiBoAg/EBThB4Ii/EBQhB8IivADQRF+ICjCDwRF+IGgCD8QFOEHgiL8QFCEHwiK8ANBEX4gKMIPBEX4gaAIPxAU4QeCIvxAUIQfCKrQLL1mNi7pqKQTko67e72MpgD0XqHwZ/7F3Q+X8DwA+oiX/UBQRcPvkp41s5fNbH0ZDQHoj6Iv+y9z94Nm9hVJz5nZ/7j7C1NXyH4prJek888/v+DuAJSl0Jnf3Q9mt5OSnpK0bJp1xty97u71Wq1WZHcAStR1+M3sDDP70sn7kpZLeqOsxgD0VpGX/fMlPWVmJ5/nl+7+TCldAei5rsPv7u9J+maJvQDoI4b6gKAIPxAU4QeCIvxAUIQfCIrwA0GV8Vd9ITz55JO5tU2bNiW3Pffcc5P1008/PVm/7rrrkvVzzjkntzYyMpLcFnFx5geCIvxAUIQfCIrwA0ERfiAowg8ERfiBoBjn79Ctt96aWxsfH+/pvh9++OFk/cwzz8ytLV68uOx2ZoyFCxfm1m677bbktvX6qf8t9Jz5gaAIPxAU4QeCIvxAUIQfCIrwA0ERfiAoxvk79Oijj+bWXn311eS27cba9+3bl6zv2bMnWX/++edzay+99FJy23ZTqH3wwQfJehGzZs1K1ufNm5esT0xMJOupf3vqGgCJcX4ApzDCDwRF+IGgCD8QFOEHgiL8QFCEHwiq7Ti/mW2WtErSpLsvyZYNSfq1pGFJ45KudfePe9dm9a688squap0YHR0ttP3HH+cf+nbXCLQbz969e3dXPXVi9uzZyfqFF16YrF900UXJ+pEjR3JrixYtSm4bQSdn/p9L+vT/ztsl7XT3CyTtzB4DmEHaht/dX5D06V+hqyVtye5vkXR1yX0B6LFu3/PPd/eT11Z+KGl+Sf0A6JPCH/i5u0vyvLqZrTezhpk1ms1m0d0BKEm34T9kZgskKbudzFvR3cfcve7u9Vqt1uXuAJSt2/Bvl7Quu79O0rZy2gHQL23Db2ZPSPq9pAvN7ICZXS9pg6Tvmtnbkq7KHgOYQdqO87v72pxSscFtlGbu3Lm5tSuuuKLQcxe9hqGIrVu3Juup6xsk6eKLL86trVmzpqueTiVc4QcERfiBoAg/EBThB4Ii/EBQhB8Iiq/uRmUmJ3MvDJUk3XDDDcl668ryfHfddVdubWhoKLltBJz5gaAIPxAU4QeCIvxAUIQfCIrwA0ERfiAoxvlRmYceeihZb3cdwNlnn52st/vq7+g48wNBEX4gKMIPBEX4gaAIPxAU4QeCIvxAUIzzo6d27dqVW9uwodh0D9u2peeKWbJkSaHnP9Vx5geCIvxAUIQfCIrwA0ERfiAowg8ERfiBoNqO85vZZkmrJE26+5Js2d2SfiCpma12h7vv6FWTmLl27Mj/b3Hs2LHktldddVWyfskll3TVE1o6OfP/XNLoNMt/6u5Lsx+CD8wwbcPv7i9IOtKHXgD0UZH3/DeZ2WtmttnM5pbWEYC+6Db8P5O0SNJSSROSfpK3opmtN7OGmTWazWbeagD6rKvwu/shdz/h7n+VtEnSssS6Y+5ed/d6rVbrtk8AJesq/Ga2YMrDayS9UU47APqlk6G+JyR9R9I8Mzsg6d8lfcfMlkpySeOSftjDHgH0QNvwu/vaaRY/1oNeMAN98sknyfozzzyTW5s9e3Zy23vuuSdZnzVrVrKONK7wA4Ii/EBQhB8IivADQRF+ICjCDwTFV3ejkPvuuy9Z37NnT25txYoVyW0vvfTSrnpCZzjzA0ERfiAowg8ERfiBoAg/EBThB4Ii/EBQjPMj6emnn07W77333mT9rLPOyq3deeedXfWEcnDmB4Ii/EBQhB8IivADQRF+ICjCDwRF+IGgGOcP7qOPPkrWb7755mT9+PHjyfrKlStza0yxXS3O/EBQhB8IivADQRF+ICjCDwRF+IGgCD8QVNtxfjNbKOlxSfMluaQxd3/AzIYk/VrSsKRxSde6+8e9axXdOHHiRLI+OjqarL///vvJ+sjISLLe7u/9UZ1OzvzHJf3I3RdL+idJN5rZYkm3S9rp7hdI2pk9BjBDtA2/u0+4+yvZ/aOS3pJ0nqTVkrZkq22RdHWvmgRQvs/1nt/MhiV9S9IfJM1394ms9KFabwsAzBAdh9/M5kjaKukWd//T1Jq7u1qfB0y33Xoza5hZo9lsFmoWQHk6Cr+ZzVIr+L9w999miw+Z2YKsvkDS5HTbuvuYu9fdvV6r1croGUAJ2obfzEzSY5LecveNU0rbJa3L7q+TtK389gD0Sid/0vttSd+T9LqZ7c2W3SFpg6TfmNn1kvZLurY3LaKId999N1lvNBqFnn/jxo3J+qJFiwo9P3qnbfjdfZckyylfWW47APqFK/yAoAg/EBThB4Ii/EBQhB8IivADQfHV3aeA/fv359aWL19e6Lnvv//+ZH3VqlWFnh/V4cwPBEX4gaAIPxAU4QeCIvxAUIQfCIrwA0Exzn8KeOSRR3JrqWsAOnH55Zcn663vesFMxJkfCIrwA0ERfiAowg8ERfiBoAg/EBThB4JinH8GePHFF5P1Bx98sE+d4FTCmR8IivADQRF+ICjCDwRF+IGgCD8QFOEHgmo7zm9mCyU9Lmm+JJc05u4PmNndkn4gqZmteoe77+hVo5Ht2rUrWT969GjXzz0yMpKsz5kzp+vnxmDr5CKf45J+5O6vmNmXJL1sZs9ltZ+6e3pWBwADqW343X1C0kR2/6iZvSXpvF43BqC3Ptd7fjMblvQtSX/IFt1kZq+Z2WYzm5uzzXoza5hZo9lsTrcKgAp0HH4zmyNpq6Rb3P1Pkn4maZGkpWq9MvjJdNu5+5i71929XqvVSmgZQBk6Cr+ZzVIr+L9w999KkrsfcvcT7v5XSZskLetdmwDK1jb81vp61sckveXuG6csXzBltWskvVF+ewB6pZNP+78t6XuSXjezvdmyOyStNbOlag3/jUv6YU86RCFLly5N1nfu3JmsDw0NldkOBkgnn/bvkjTdl7Mzpg/MYFzhBwRF+IGgCD8QFOEHgiL8QFCEHwjK3L1vO6vX695oNPq2PyCaer2uRqPR0bzpnPmBoAg/EBThB4Ii/EBQhB8IivADQRF+IKi+jvObWVPS/imL5kk63LcGPp9B7W1Q+5LorVtl9vY1d+/o+/L6Gv7P7Nys4e71yhpIGNTeBrUvid66VVVvvOwHgiL8QFBVh3+s4v2nDGpvg9qXRG/dqqS3St/zA6hO1Wd+ABWpJPxmNmpm/2tm75jZ7VX0kMfMxs3sdTPba2aV/v1xNg3apJm9MWXZkJk9Z2ZvZ7fTTpNWUW93m9nB7NjtNbOVFfW20Mx+Z2b7zOxNM/vXbHmlxy7RVyXHre8v+83sNEn/J+m7kg5I2i1prbvv62sjOcxsXFLd3SsfEzazf5b0Z0mPu/uSbNl/SDri7huyX5xz3f3fBqS3uyX9ueqZm7MJZRZMnVla0tWSvq8Kj12ir2tVwXGr4sy/TNI77v6eux+T9CtJqyvoY+C5+wuSjnxq8WpJW7L7W9T6z9N3Ob0NBHefcPdXsvtHJZ2cWbrSY5foqxJVhP88SX+c8viABmvKb5f0rJm9bGbrq25mGvOzadMl6UNJ86tsZhptZ27up0/NLD0wx66bGa/Lxgd+n3WZu/+jpBWSbsxe3g4kb71nG6Thmo5mbu6XaWaW/psqj123M16XrYrwH5S0cMrjr2bLBoK7H8xuJyU9pcGbffjQyUlSs9vJivv5m0GauXm6maU1AMdukGa8riL8uyVdYGZfN7MvSlojaXsFfXyGmZ2RfRAjMztD0nIN3uzD2yWty+6vk7Stwl7+zqDM3Jw3s7QqPnYDN+O1u/f9R9JKtT7xf1fSj6voIaevb0h6Nft5s+reJD2h1svAv6j12cj1kr4saaektyX9t6ShAertPyW9Luk1tYK2oKLeLlPrJf1rkvZmPyurPnaJvio5blzhBwTFB35AUIQfCIrwA0ERfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d69ee2630>"
+       "<matplotlib.figure.Figure at 0x7f8947e53518>"
       ]
      },
      "metadata": {},
@@ -1959,7 +1942,7 @@
     }
    ],
    "source": [
-    "image1 = data.test.images[0]\n",
+    "image1 = data.x_test[0]\n",
     "plot_image(image1)"
    ]
   },
@@ -1972,14 +1955,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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q+tgl+irkuPEOPyAoLvgBQRF+ICjCDwRF+IGgCD8QFOEHgiL8QFCEHwjq/wHi31d/HSnF\nFwAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a483dd8>"
+       "<matplotlib.figure.Figure at 0x7f8947e1fba8>"
       ]
      },
      "metadata": {},
@@ -1987,7 +1970,7 @@
     }
    ],
    "source": [
-    "image2 = data.test.images[13]\n",
+    "image2 = data.x_test[13]\n",
     "plot_image(image2)"
    ]
   },
@@ -2009,16 +1992,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 57,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d69bff710>"
+       "<matplotlib.figure.Figure at 0x7f89e12f7f28>"
       ]
      },
      "metadata": {},
@@ -2038,16 +2021,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 58,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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R2bhxY11zLjgv5v6tra2V+vr66Gc3rUSZSCRk1apVmd9VAY0fP77Qt5BSIpGQlStXFvo2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\n2gAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a55c780>"
+       "<matplotlib.figure.Figure at 0x7f88e80d2208>"
       ]
      },
      "metadata": {},
@@ -2067,16 +2050,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 59,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d704ca048>"
+       "<matplotlib.figure.Figure at 0x7f88a0c82400>"
       ]
      },
      "metadata": {},
@@ -2114,16 +2097,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 60,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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RR0Q+7MfTzBpr4Z6tW+3j9Fm9UmQlDz4YdXwA/8wnInKCzZSIyAE2UyIiB2K6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\n+G+SXKUoMYZfOgAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a510828>"
+       "<matplotlib.figure.Figure at 0x7f8947e92e80>"
       ]
      },
      "metadata": {},
@@ -2143,14 +2126,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Svgf9+u15LLvYOCTyAK0kJREF+fjm3lmkluyYM0fMz3z722rNmNde4+HLL0ceH+GTKQCA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\nm1lcPUX/zlQzsu+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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6820d860>"
+       "<matplotlib.figure.Figure at 0x7f8947e11ef0>"
       ]
      },
      "metadata": {},
@@ -2174,16 +2157,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 62,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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PZPSZX1JSYvKgf/DBB0qjf1FEZNGiRUpXV1ebOpMmTVJ67NixSkcV7qukpESOOeYYVYZh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\nFm6+cC3IvvDCC5V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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6820db38>"
+       "<matplotlib.figure.Figure at 0x7f887be39d30>"
       ]
      },
      "metadata": {},
@@ -2203,16 +2186,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 63,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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5scE8C5jMpaHBBDR33nmnsWnXrp3SuFAsYg/h4MJa2MMJfDIlhBAP0JkSQogH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\nMyWEEA/QmRJCiAfoTAkhxAP/DxkSP5EwP1q5AAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f5d6a510320>"
+       "<matplotlib.figure.Figure at 0x7f892c044dd8>"
       ]
      },
      "metadata": {},
@@ -2248,7 +2231,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/03B_Layers_API.ipynb b/03B_Layers_API.ipynb
index dcc8f72..58d8fbc 100644
--- a/03B_Layers_API.ipynb
+++ b/03B_Layers_API.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #03-B\n",
     "# Layers API\n",
@@ -16,10 +13,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**The Layers API was intended to be a basic builder API for creating Neural Networks in TensorFlow, but the Layers API was never fully completed. Although it still works in TensorFlow v. 1.9, it seems quite possible that it may be deprecated in the future. It is recommended that you use the more complete _Keras API_ instead, see Tutorial #03-C.**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -34,40 +37,28 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See Tutorial #02 for a more detailed description of convolution."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Flowchart](images/02_network_flowchart.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled using max-pooling so the image resolution is decreased from 28x28 to 14x14.\n",
     "\n",
@@ -84,10 +75,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -96,9 +84,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -112,10 +98,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
@@ -123,11 +106,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -146,20 +125,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -167,11 +140,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -191,10 +160,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
@@ -202,11 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -228,10 +190,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
@@ -240,9 +199,7 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -251,20 +208,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
@@ -273,9 +224,7 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -297,20 +246,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -319,9 +262,7 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -356,10 +297,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -367,11 +305,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -397,10 +331,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -423,20 +354,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
     "\n",
@@ -447,9 +372,7 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -458,10 +381,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
@@ -470,9 +390,7 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -481,10 +399,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
@@ -492,11 +407,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
@@ -504,10 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
@@ -516,9 +424,7 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -527,10 +433,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## PrettyTensor Implementation\n",
     "\n",
@@ -543,9 +446,6 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -566,10 +466,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Layers Implementation\n",
     "\n",
@@ -582,9 +479,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -593,10 +488,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The input image is then input to the first convolutional layer, which has 16 filters each of size 5x5 pixels. The activation-function is the Rectified Linear Unit (ReLU) described in more detail in Tutorial #02."
    ]
@@ -605,9 +497,7 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -617,10 +507,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "One of the advantages of constructing neural networks in this fashion, is that we can now easily pull out a reference to a layer. This was more complicated in PrettyTensor.\n",
     "\n",
@@ -631,9 +518,7 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -642,10 +527,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We now do the max-pooling on the output of the convolutional layer. This was also described in more detail in Tutorial #02."
    ]
@@ -654,9 +536,7 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -665,10 +545,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We now add the second convolutional layer which has 36 filters each with 5x5 pixels, and a ReLU activation function again."
    ]
@@ -677,9 +554,7 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -689,10 +564,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We also want to plot the output of this convolutional layer, so we keep a reference for later use."
    ]
@@ -701,9 +573,7 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -712,10 +582,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The output of the second convolutional layer is also max-pooled for down-sampling the images."
    ]
@@ -723,11 +590,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
@@ -735,10 +598,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The tensors that are being output by this max-pooling are 4-rank, as can be seen from this:"
    ]
@@ -746,11 +606,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -769,10 +625,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Next we want to add fully-connected layers to the Neural Network, but these require 2-rank tensors as input, so we must first flatten the tensors.\n",
     "\n",
@@ -783,9 +636,7 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -797,10 +648,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This has now flattened the data to a 2-rank tensor, as can be seen from this:"
    ]
@@ -808,11 +656,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -831,10 +675,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now add fully-connected layers to the neural network. These are called *dense* layers in the Layers API."
    ]
@@ -843,9 +684,7 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -855,10 +694,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We need the neural network to classify the input images into 10 different classes. So the final fully-connected layer has `num_classes=10` output neurons."
    ]
@@ -867,9 +703,7 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -879,10 +713,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The output of the final fully-connected layer are sometimes called logits, so we have a convenience variable with that name."
    ]
@@ -891,9 +722,7 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -902,10 +731,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We use the softmax function to 'squash' the outputs so they are between zero and one, and so they sum to one."
    ]
@@ -914,9 +740,7 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -925,10 +749,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This tells us how likely the neural network thinks the input image is of each possible class. The one that has the highest value is considered the most likely so its index is taken to be the class-number."
    ]
@@ -937,9 +758,7 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -948,10 +767,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We have now created the exact same Convolutional Neural Network in a few lines of code that required many complex lines of code in the direct TensorFlow implementation.\n",
     "\n",
@@ -960,20 +776,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Loss-Function to be Optimized"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "To make the model better at classifying the input images, we must somehow change the variables of the Convolutional Neural Network.\n",
     "\n",
@@ -985,11 +795,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_true, logits=logits)"
@@ -997,10 +803,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
    ]
@@ -1009,9 +812,7 @@
    "cell_type": "code",
    "execution_count": 30,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1020,10 +821,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Optimization Method\n",
     "\n",
@@ -1035,11 +833,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -1047,10 +841,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Classification Accuracy\n",
     "\n",
@@ -1063,9 +854,7 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1074,10 +863,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
    ]
@@ -1086,9 +872,7 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1097,10 +881,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Getting the Weights\n",
     "\n",
@@ -1112,11 +893,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1158,10 +935,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Each of the convolutional layers has two variables. For the first convolutional layer they are named `layer_conv1/kernel:0` and `layer_conv1/bias:0`. The `kernel` variables are the ones we want to plot further below.\n",
     "\n",
@@ -1172,9 +946,7 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1192,10 +964,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Using this helper-function we can retrieve the variables. These are TensorFlow objects. In order to get the contents of the variables, you must do something like: `contents = session.run(weights_conv1)` as demonstrated further below."
    ]
@@ -1204,9 +973,6 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -1217,20 +983,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Run"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -1241,9 +1001,7 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1252,10 +1010,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1265,11 +1020,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1277,20 +1028,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1301,9 +1046,7 @@
    "cell_type": "code",
    "execution_count": 39,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1312,10 +1055,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function performs a number of optimization iterations so as to gradually improve the variables of the neural network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
@@ -1323,11 +1063,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Counter for total number of iterations performed so far.\n",
@@ -1372,20 +1108,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
@@ -1394,9 +1124,7 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1430,10 +1158,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
@@ -1442,9 +1167,7 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1482,20 +1205,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Below is a function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1507,11 +1224,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Split the test-set into smaller batches of this size.\n",
@@ -1586,10 +1299,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance before any optimization\n",
     "\n",
@@ -1599,11 +1309,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1619,10 +1325,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
@@ -1632,11 +1335,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1654,9 +1353,6 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1674,10 +1370,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 100 optimization iterations\n",
     "\n",
@@ -1688,9 +1381,6 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1711,11 +1401,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1742,10 +1428,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1000 optimization iterations\n",
     "\n",
@@ -1756,9 +1439,6 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1789,9 +1469,6 @@
    "cell_type": "code",
    "execution_count": 50,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1820,10 +1497,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 10,000 optimization iterations\n",
     "\n",
@@ -1834,9 +1508,6 @@
    "cell_type": "code",
    "execution_count": 51,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1948,9 +1619,6 @@
    "cell_type": "code",
    "execution_count": 52,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2007,20 +1675,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Visualization of Weights and Layers"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
@@ -2029,9 +1691,7 @@
    "cell_type": "code",
    "execution_count": 53,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2083,10 +1743,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting the output of a convolutional layer"
    ]
@@ -2095,9 +1752,7 @@
    "cell_type": "code",
    "execution_count": 54,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2146,10 +1801,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Input Images\n",
     "\n",
@@ -2160,9 +1812,7 @@
    "cell_type": "code",
    "execution_count": 55,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2176,10 +1826,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot an image from the test-set which will be used as an example below."
    ]
@@ -2187,11 +1834,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2211,10 +1854,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Plot another example image from the test-set."
    ]
@@ -2222,11 +1862,7 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2246,20 +1882,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 1"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the first convolutional layer.\n",
     "\n",
@@ -2270,9 +1900,6 @@
    "cell_type": "code",
    "execution_count": 58,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2293,10 +1920,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Applying each of these convolutional filters to the first input image gives the following output images, which are then used as input to the second convolutional layer."
    ]
@@ -2304,11 +1928,7 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2327,10 +1947,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following images are the results of applying the convolutional filters to the second image."
    ]
@@ -2338,11 +1955,7 @@
   {
    "cell_type": "code",
    "execution_count": 60,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2361,20 +1974,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 2"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the second convolutional layer.\n",
     "\n",
@@ -2387,9 +1994,6 @@
    "cell_type": "code",
    "execution_count": 61,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2410,10 +2014,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
    ]
@@ -2421,11 +2022,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2444,10 +2041,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "It can be difficult to understand and keep track of how these filters are applied because of the high dimensionality.\n",
     "\n",
@@ -2459,11 +2053,7 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2482,10 +2072,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "And these are the results of applying the filter-weights to the second image."
    ]
@@ -2493,11 +2080,7 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2516,20 +2099,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
@@ -2537,11 +2114,7 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2551,10 +2124,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2565,10 +2135,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2591,10 +2158,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2629,5 +2193,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/03C_Keras_API.ipynb b/03C_Keras_API.ipynb
index 5c505c9..e55a7b7 100644
--- a/03C_Keras_API.ipynb
+++ b/03C_Keras_API.ipynb
@@ -65,8 +65,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
      ]
     }
    ],
@@ -115,7 +115,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.4.0'"
+       "'1.9.0'"
       ]
      },
      "execution_count": 3,
@@ -127,26 +127,6 @@
     "tf.__version__"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'2.0.8-tf'"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tf.keras.__version__"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -163,35 +143,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -200,77 +169,49 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 6,
    "metadata": {},
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": true
-   },
    "outputs": [],
    "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
     "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
     "\n",
     "# Tuple with height and width of images used to reshape arrays.\n",
-    "# This is used for plotting the images.\n",
-    "img_shape = (img_size, img_size)\n",
+    "img_shape = data.img_shape\n",
     "\n",
     "# Tuple with height, width and depth used to reshape arrays.\n",
     "# This is used for reshaping in Keras.\n",
-    "img_shape_full = (img_size, img_size, 1)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
+    "img_shape_full = data.img_shape_full\n",
     "\n",
     "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
@@ -289,10 +230,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -333,14 +272,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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zh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY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\nRK5CYII=\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc310557978>"
+       "<matplotlib.figure.Figure at 0x7fab44735a20>"
       ]
      },
      "metadata": {},
@@ -349,10 +288,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -369,10 +308,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred):\n",
@@ -380,17 +317,17 @@
     "    # all images in the test-set.\n",
     "\n",
     "    # Boolean array whether the predicted class is incorrect.\n",
-    "    incorrect = (cls_pred != data.test.cls)\n",
+    "    incorrect = (cls_pred != data.y_test_cls)\n",
     "\n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "    \n",
     "    # Plot the first 9 images.\n",
     "    plot_images(images=images[0:9],\n",
@@ -409,10 +346,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "if False:\n",
@@ -440,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "metadata": {
     "scrolled": true
    },
@@ -492,10 +427,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from tensorflow.python.keras.optimizers import Adam\n",
@@ -512,7 +445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -532,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -540,23 +473,23 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/1\n",
-      "55000/55000 [==============================] - 5s - loss: 0.2261 - acc: 0.9335        \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n"
+      "55000/55000 [==============================] - 3s 59us/step - loss: 0.2201 - acc: 0.9341\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fc30e732f98>"
+       "<tensorflow.python.keras.callbacks.History at 0x7fab41f81ef0>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "model.fit(x=data.train.images,\n",
-    "          y=data.train.labels,\n",
+    "model.fit(x=data.x_train,\n",
+    "          y=data.y_train,\n",
     "          epochs=1, batch_size=128)"
    ]
   },
@@ -571,20 +504,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " 9152/10000 [==========================>...] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b"
+      "10000/10000 [==============================] - 0s 35us/step\n"
      ]
     }
    ],
    "source": [
-    "result = model.evaluate(x=data.test.images,\n",
-    "                        y=data.test.labels)"
+    "result = model.evaluate(x=data.x_test,\n",
+    "                        y=data.y_test)"
    ]
   },
   {
@@ -596,15 +529,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss 0.0618685603024\n",
-      "acc 0.9801\n"
+      "loss 0.05883921128492802\n",
+      "acc 0.9807\n"
      ]
     }
    ],
@@ -622,14 +555,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "acc: 98.01%\n"
+      "acc: 98.07%\n"
      ]
     }
    ],
@@ -648,13 +581,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "images = data.test.images[0:9]"
+    "images = data.x_test[0:9]"
    ]
   },
   {
@@ -666,13 +597,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cls_true = data.test.cls[0:9]"
+    "cls_true = data.y_test_cls[0:9]"
    ]
   },
   {
@@ -684,7 +613,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -700,23 +629,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
-    "cls_pred = np.argmax(y_pred,axis=1)"
+    "cls_pred = np.argmax(y_pred, axis=1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc30d870dd8>"
+       "<matplotlib.figure.Figure at 0x7fab423855c0>"
       ]
      },
      "metadata": {},
@@ -742,13 +671,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_pred = model.predict(x=data.test.images)"
+    "y_pred = model.predict(x=data.x_test)"
    ]
   },
   {
@@ -760,13 +687,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cls_pred = np.argmax(y_pred,axis=1)"
+    "cls_pred = np.argmax(y_pred, axis=1)"
    ]
   },
   {
@@ -778,14 +703,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc30d870d30>"
+       "<matplotlib.figure.Figure at 0x7fab42330208>"
       ]
      },
      "metadata": {},
@@ -807,7 +732,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -857,10 +782,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from tensorflow.python.keras.models import Model"
@@ -875,7 +798,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -886,15 +809,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Compile the Keras model using the `rmsprop` optimizer and with a loss-function for multiple categories. The only performance metric we are interested in is the classification accuracy, but you could use a list of metrics here."
+    "Compile the Keras model using the RMSprop optimizer and with a loss-function for multiple categories. The only performance metric we are interested in is the classification accuracy, but you could use a list of metrics here."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [],
    "source": [
     "model2.compile(optimizer='rmsprop',\n",
@@ -913,7 +834,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -921,23 +842,23 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/1\n",
-      "55000/55000 [==============================] - 2s - loss: 0.1924 - acc: 0.9409       \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\n"
+      "55000/55000 [==============================] - 2s 37us/step - loss: 0.1958 - acc: 0.9394\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7fc30c02ceb8>"
+       "<tensorflow.python.keras.callbacks.History at 0x7faac4a441d0>"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "model2.fit(x=data.train.images,\n",
-    "           y=data.train.labels,\n",
+    "model2.fit(x=data.x_train,\n",
+    "           y=data.y_train,\n",
     "           epochs=1, batch_size=128)"
    ]
   },
@@ -952,20 +873,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " 8992/10000 [=========================>....] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b"
+      "10000/10000 [==============================] - 0s 36us/step\n"
      ]
     }
    ],
    "source": [
-    "result = model2.evaluate(x=data.test.images,\n",
-    "                         y=data.test.labels)"
+    "result = model2.evaluate(x=data.x_test,\n",
+    "                         y=data.y_test)"
    ]
   },
   {
@@ -977,7 +898,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 32,
    "metadata": {
     "scrolled": true
    },
@@ -986,8 +907,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss 0.0654281976447\n",
-      "acc 0.9786\n"
+      "loss 0.061494892170466484\n",
+      "acc 0.9811\n"
      ]
     }
    ],
@@ -1005,14 +926,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "acc: 97.86%\n"
+      "acc: 98.11%\n"
      ]
     }
    ],
@@ -1033,13 +954,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_pred = model2.predict(x=data.test.images)"
+    "y_pred = model2.predict(x=data.x_test)"
    ]
   },
   {
@@ -1051,10 +970,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred, axis=1)"
@@ -1069,14 +986,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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0Br5wzq3MILails0yBpYCvzazuhbUZl2BReG2xfQ5bhJ52IOgbbdK2eyneSXB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\nQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc310343470>"
+       "<matplotlib.figure.Figure at 0x7faae86bb080>"
       ]
      },
      "metadata": {},
@@ -1102,10 +1019,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 37,
+   "metadata": {},
    "outputs": [],
    "source": [
     "path_model = 'model.keras'"
@@ -1120,7 +1035,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 38,
    "metadata": {
     "scrolled": true
    },
@@ -1138,10 +1053,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 39,
+   "metadata": {},
    "outputs": [],
    "source": [
     "del model2"
@@ -1156,7 +1069,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1172,10 +1085,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [],
    "source": [
     "model3 = load_model(path_model)"
@@ -1190,24 +1101,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "images = data.test.images[0:9]"
+    "images = data.x_test[0:9]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 43,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cls_true = data.test.cls[0:9]"
+    "cls_true = data.y_test_cls[0:9]"
    ]
   },
   {
@@ -1219,7 +1126,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1235,10 +1142,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 45,
+   "metadata": {},
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred, axis=1)"
@@ -1253,14 +1158,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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BmU7fhm4EnXXWWentvn37AtC+fXsAnnzySQAuu+yyOsfdeOONQN0BtFJc8bIIN2jGjRsHwAYbbNDs84YbQPHfoUq6YSCNCzdt63PIIYeUMJJklGmKiCRQtkwzTNAQ+rgAVq5cWe++YfjQscceC8Af//jH9Gdt27bN2jdMDTdmzJg65xw6dCgAX375JZCZ3KN169bN+4+QRk2YMAHIHsge+jLjfc3NFYapxLPLAw88EIAOHTrkfX4prngLIVhvvfUAGDlyZKnDyZkyTRGRBMqWaX799ddAw9klZB6BvPfee4HMnfLGhEwz3JW98MIL05+FR+tCxhmmn9pmm20SxS65CRNDh//vUJj+5NBKueuuu4DMnVaAiy++GFDroZKFBxtmzJhR57PQcuzVq1dJY0pCmaaISAJlv3ten9DfNXbsWCC3DLO2kEXeeeed6fdmzZpVgOikKZ9++ikAM2fOrPPZ4MGD8z7/zTffDGSmDuzZs2f6s4MOOijv80txNTYBTzWMbFGmKSKSQNkzzfqe+nnxxRfzPm94qij+FFDtJ43CXfgwZlAKI0zEsGzZMiAzvVehLFmyJOv1TjvtVNDzS3HVl2mG0Q6FaIkUmzJNEZEEVGmKiCRQtuZ5WLu8WCvLhVXt5s6dm36v9uOZl156aVGuvbbbcMMNgcywkfiEHeHRx44dOyY+74oVK4DMUKZgn332aVacUlrPP/88kBkqFhceg+7cuXNJY2oOZZoiIgmULdOcMmVKQc8Xhp8sXLgQaPwxrDCESQOgiyOsFhgemQyPUwIcfvjhQPZDB/WZP39+ejvc+AnT/tWelKNVK/3trwZhxclwQzaukifoqE2/bSIiCZR9yFGhhOnHbrjhhgb3qampAeCOO+4AMhOBSHEMHz4cyM4sQgsjPlFLfTbddNP0dsgsG3rk9tRTT80nTCmR2n3R8UlVzjzzzFKH02zKNEVEEqj6TDMskREmMG5MeNxuv/32K2pMktKjRw8ge0XQMJqh9gD12sI0gHGDBg0C6j6MEPpQpTKFhxxq3zWP3ykvxFSBpaJMU0QkgbJlmo0tnvbII49kvT7jjDMAeP/99xs8Ty7LHBT6jr0kt+uuu2b9TOL73/9+ve/Hx4H+4Ac/aF5gUjRhKrjad8379+9fjnDypkxTRCQBVZoiIgmUrXke5s0Ls6jHhQHQtR+xrO+Ry9C8z2XlSqluoXlXu5mnJnllC4Pag/BwyQUXXFCOcPKmTFNEJIGyZZoDBgwAYNSoUen3GlsvqCnhr1cY5nLLLbcAsOWWWzb7nFJZws0+rW1eXaZOnZr1ukuXLkBmko5qo0xTRCSBsmWaYdXIsNIkwKRJkwAYPXp04vP94Q9/ADJrmUvLE9arDzSovbKFFWcXL16c9X6bNm2A6p0wR5mmiEgCZX+MMqxtHt/u27cvkFl1MEwofOSRRwLwy1/+Mn1MuJMaX5FQWqawOmmY6GHYsGHlDEeaEKbsC49ILliwAIBtt922bDEVgjJNEZEEyp5p1ufQQw/N+ikCmYzl17/+NaA1zitdGDsdpm0Mox5++MMfli2mQlCmKSKSQEVmmiL1CX3bUl222morAG677bYyR1IYyjRFRBJQpSkikoAqTRGRBFRpiogkoEpTRCQBVZoiIglY7QldEx1s9iHwTuHCqQrd3H3TpndrGVTGLZ/KOJm8Kk0RkbWNmuciIgmo0hQRSUCVpohIAo1Wmma2iZnNi/4tN7P3Yq/XK1ZQZtbPzF43s8VmNiSH/UfEYnvVzA7P8/rPm1mvJvZpY2YTohhnmFnXfK5ZLuUq4+ja65rZK2Y2KYd9S17GsX2PNzPPdf9KU8bv8R1m9qGZzctx/9PD/ma2yMx+kef1x5nZ0U3ss2P0/V1jZjktj9nohB3u/hHQKzr5cOBzd7+y1kWN1A2l73K5YFPMrDVwPfDfwHJgtpk96O5vNHHoFe4+2sx2Ap4ys808dpfLzNZ1928KEWPkTGC5u3c3s5OAvwAnFvD8JVGOMo65EJgPtM1x/1KXMWa2ETAYmF3I85ZSGcv4NuAG4OYEx9zp7heY2RbAfDOb7O7pFReLUMYrgXOBY3M9oFnNczPrbmYLzexOYAHQxcw+iX0+0MxujbY3N7OJZjbbzGaZ2Z5NnH5PYJG7v+Pua4D7gP65xubu8wEDNo7+0txoZrOAkWa2gZndHsUx18yOjGJsa2bjo79u9wNtcrhUf+COaPs+4Me5xlgNilzGmFk34BBgbNLYSljGACOjf2uSxlnpil3G7v4MsKo5sbn7cmAp0DVqZfzNzF4Abo9aKFdHcbxiZqdHMbYys/81s9fM7HGgUw7X+cDdZwM5V8T59GnuAFzj7j2B9xrZ71pglLv3Bo4DQiHsYWY31bP/1sC/Yq+XRe/lxMz2Br5091BYWwJ7uvtQYBjwqLvvDhwEXGVmbYBfAR+7ew9gBLBr7HxjG2iWpeN096+A1WbWIdc4q0SxyhhgNDAESDzmrVRlbGa7AZu5+9Tan7UgxSzjZjOz7kA34K1YnAe7+0mkWnkrojLeDTjHUt1jxwL/BfQETgX2jp3vMjPrV4jY8plPc0lUQzelD7C9Zdaq3tjM1nf3F4EX87h+bUPM7OfAZ8DxsffHx5ocfYHDzOx30es2QFdgf2AUgLvPNbMF4WB3P7WAMVabopRx1M/0L3efZ2Z9EsRTsjI2s1bAVVRhl0tClfY9PtHMDiSV2Z/u7p9E13zQ3cNypH2BHmY2MHrdHtiWVBnfHf0uLDOzp8NJ3f0PhQown0pzdWz7O1LNpSDe9DFg9ygby8V7QJfY6840/hcwuMLd61v7Nx6nAUe7+5L4DrFfhCRCnMst1Znezt0/aeKYalOsMt4bGGBmR0Xn2cjM7nD3QU0cV8oy7kAqY3kuOnYL4GEzO9zd5yY9WQUrVhk3153uXt8NmdplPNjdn4jvYGbHFDWySEGGHEU1+8dmtm30Fzoe/DTgnPCigaZu3Eygp5l1M7PvkWoKTI6OHRX6qJppKqlO3xBLaKI9C/wsem8XYMcczjUZCF/y44DH8oir4hWyjN19qLt3dvca4CTgsVBhVkoZu/sqd+/k7jVRnLOBfi2swsxS4O9xg8zsfDM7q/mRMhUYbGbrRufb3szWJ1XGx0d9m1sDB+RxjQYVcpzmb0n9x0wn1Q8ZnAPsE3XYLgTOgIb7Qtz9a+A84HFgITDO3V+PPt6Z1B315roUaGepISsLgOHR+9cDm5jZIuASIP3FaKRP82ZgSzNbTKq/7KI84qoWBSnjJlRSGa+NClbGZjYeeI5UErQs6loB6AF8lEeMY4A3gXlmNh+4kVSreQLwLql6YywwIxZLvX2aZtbZzJaRqnOGR3E2Opqjap49t1Qb6RF31xKVLZTKeO1gZv8A+hd6eFipVE2lKSJSCfQYpYhIAqo0RUQSUKUpIpJAPuM06dSpk9fU1BQolOowZ86clWvTrN4q45ZPZZxMXpVmTU0Ns2dX7TwGzWJma9WyACrjlk9lnIya5yIiCajSFBFJQJWmiEgCqjRFRBJQpSkikoAqTRGRBFRpiogkkNc4TRGRYvj4448BePfddxvcp1u3bgBcc801AOy0004AbLfddgDssssuRYlNmaaISAIVlWmuWLECgOOOOw6AvfdOrYt05plnAqknFwrh008/BeDZZ58F4NBDU9M3tm7duiDnF5FkpkyZAsBDDz0EwNNPPw3Am2++2eAx22+/PQBLly4FYM2a7AVDv/uu0CtOpyjTFBFJoOyZZui7ANhxx9SyLSET3HzzzYHCZ5g//OEPAVi5MrUGfXjudtttty3IdSR3//73vwH43e9Si0cuWJBaJHLatGnpfdQCaBmWLEmtdXfDDTcAcPPNN6c/++KLLwBIMin666+/3vRORaBMU0QkgbJlmiHLC/2XAB99lFpr6ZxzUoveXXfddQW95ogRIwB4++23gcxfOmWYpTdu3DgALr74YqDuXdKQgQJssskmpQtMimbZstQ6baNH17cKc+522GEHIHO3vNSUaYqIJFC2TPOf//wnkLlLFjds2LCCXWf+/Pnp7SuvvBKAY45JLed8/PHHF+w6kpuQbfz6178GMi2O1EKUGeeem166nOuvvx6Ajh07liJEaYZQjpDJJPfdd18gMzplvfXWA6B9+/YAbLDBBuljPv/8cwB+/OMfA5ksco899gBg1113Te+7/vrrA9CuXbsC/1fkRpmmiEgCqjRFRBIoefM8DGC///7763x22223AbDppvkvzxKa5YccckidzwYMGADAhhtumPd1JJnQRRJu+jXknnvuSW8/8sgjQOamUWi6h+aelM/q1auB7O/Zyy+/DMCkSZOy9t1rr70AmDt3LpA9lDDcCOzcuTMArVpVbj5XuZGJiFSgkmea//M//wNkhpyEgeYAP/3pTwt2neeffx6A5cuXp9879dRTATjppJMKdh1p2jvvZNawGjt2bNZnYVKF8CDD448/Xuf48FBCyFJPPPFEALbYYovCBys5+eqrrwD42c9+BmSyS4CLLroIgD59+tR7bH0Pq3Tt2rXAERaPMk0RkQRKnmmGoSXh59Zbb53+LJ8+qvAY1siRI4HMo1rxoSyhz1RKa968eentMGh9//33B+CZZ54B4MsvvwTgrrvuAuAvf/lL+pjFixcDmVZD//79gUxfp4YilU4YGhS+Z2GCjfh9iCFDhgDQtm3bEkdXGso0RUQSKPuEHWFKKIC+ffsC0KFDBwDOPvvsJo8Pg+PDz5kzZ2Z9Xsh+Umme+JRdIfMPg9uDNm3aAPCLX/wCgAkTJqQ/CxM9hMkcQgaju+elF+6IX3755UBmIuDnnnsuvU8YvN5SKdMUEUmg5Jnm+eefD8CTTz4JwPvvv5/+LPRvhYziwQcfbPJ8Yd/aj+Fts802QKbvRcrn7rvvrvPeP/7xDwCOPvroeo8J0/XVZ8899wSyH8OT0pg+fXrW6/B4YxhfuTZQpikikkDJM80f/ehHALz66qtA9p3VRx99FIBRo0YBsNlmmwEwaNCgBs938sknA7DzzjtnvR+WyggZp5TPCSeckN4OrYeXXnoJgNdeew3I/D488MADQPbk1KGPO7wXpvQLZd+zZ8+ixS7Z4n3NkBnBcOmll6bfO+qoo4DsSTZaEmWaIiIJqNIUEUnAkqzJUVvv3r29sQ77UnjrrbeATDO8V69eADz22GNAYSb/iDOzOe7eu6AnrWCFKONVq1alt0M5hUcjG7qRF58AIjyocMQRRwDwxhtvAJlVSm+66aa84qtNZdyw2g+n1GedddYB4KyzzgIyc2L+61//AqB79+5AZk2wuLBGVJjco1g3mPIpY2WaIiIJlH1we77+9Kc/AZm/fOEmUqEzTGm++GOO48ePB+DYY48F6mac5513HgB//etf08eEge9hSr/wiOXUqVOBzOB30I2/YvvNb34DwFVXXdXgPt9++y2QaSGEn0mEm8AHHnggkD1VYLkp0xQRSaAqM82QrQDccccdAGy00UaAVi6sdGG6sDB0JUzQEYYVhZZDyC7jLrnkEgAWLVoEZIYvhWMg8/sgxREenwyryIZp+r7++uv0PmEdqJBxNkeYrDx81+MrT4bJqMtFmaaISAJVmWmGAbVxhx9+OJA9qbFUrpBxNjRRbX3CKoRhFdGQaT711FPpfcKdek0XVxzhzvhuu+0GZEYyxD3xxBNAJvscPnw4ALNmzUp8vdDXPWfOnMTHFosyTRGRBKo+0wxrH4e7etLyhf60yZMnA9l3VsMa6cOGDSt9YALAwQcfnPU6PCodMs3WrVsDmeVnAM444wwArrnmGiDT112JlGmKiCSgSlNEJIGqap6Hx+XiK0yGVQx1A2jtEdbEHjp0KJC9vna46TBw4EAAtttuu9IGJ3WEFRnCKpXhBlGYrQrgzTffBDIrMNQWX0us3JRpiogkUJWZZnyygH79+mXt89lnnwGZuReraT1lSSZMzvLnP/85/V64Ifj73/8egHHjxgGZ4UpSej169AAyQ8XuvffeOvvEh40BrLtuqmoKQwnjj9XY76NRAAAG3klEQVSWmzJNEZEEqirTrE/4ixQyijBkITx2pcfqWr5TTjklvT1mzBgAJk6cCGT6ymrP7C+lE7L80aNHA5nWYHzA+gcffABATU0NkCnT0EddSZRpiogkUPWZ5i233ALArbfeCsDpp58OZCZ3kJYvPg3gtGnTgMx63GGCiUoeLL22CCNdpkyZAsDf//739GczZswAMpllmBquEinTFBFJoKoyzeuuuw6AP/7xj+n39t9/fwDOPvtsADbeeGMA1ltvvRJHJ5UgjJYIy2WERy0XLlwIaOXKShJWE629XemUaYqIJFBVmeZ+++0HwJNPPlnmSKTShUmOd9llFwAWL14MKNOU/CnTFBFJQJWmiEgCVdU8F8lVWDPq7bffLnMk0tIo0xQRSUCVpohIAqo0RUQSsLDaW7MONvsQeKdw4VSFbu6+adO7tQwq45ZPZZxMXpWmiMjaRs1zEZEEVGmKiCTQaKVpZpuY2bzo33Izey/2uqgzYpjZumb2iplNymHfEbHYXjWzw/O89vNm1ivHfY83M891/0pTrjI2swvNbEH079wc9j/dzD6M4lpkZr/I8/rjzOzoJvbpaGaTo9/DF82sKp/BLGMZL4u+j/PM7MUc9i9HGfcxs09j/z/+0NR5Gx3c7u4fAb2ikw8HPnf3K2td1Ej1jX7X1MUSuhCYD7TNcf8r3H20me0EPGVmm3msw9bM1nX3bwoZoJltBAwGZhfyvKVUjjKO/sAMAnoD3wCPmdkUd29qJPqd7n6BmW0BzDezye6+MnbeQpfxJcCL7n6Ume0I/D/gkAKevyTK/D3ez90/SbB/qcsY4Cl3b7RyjWtW89zMupvZQjO7E1gAdDGzT2KfDzSzW6Ptzc1sopnNNrNZZrZnDufvRuqXc2zS2Nx9PmDAxtFfmhvNbBYw0sw2MLPbozjmmtmR0fXamtn46K/b/UCbHC83Mvq3Jmmcla7IZdwDmOnuX7j718CzwDG5xubuy4GlQNeolfE3M3sBuD1qoVwdxfGKmZ0exdjKzP7XzF4zs8eBTjlcqifwZHTNBcB2ZrZJrnFWumJ/j/NRwjJOLJ8+zR2Aa9y9J/BeI/tdC4xy997AcUAohD3M7KYGjhkNDAES39o3s72BL919VfTWlsCe7j4UGAY86u67AwcBV5lZG+BXwMfu3gMYAewaO99Yq6fpbWa7AZu5+9SkMVaRYpXxq8ABlmr+tgMOA7rkGpSZdQe6AW/F4jzY3U8CzgRWRGW8G3COmXUFjgX+i1RFeCqwd+x8l5lZ9rKmKS8DA6J99gI6R/9akmJ+jx140szmmNlpSYIqYRkD7GtmL5vZw5ZDF0w+z54vcfdcmqV9gO0ts+zuxma2vru/CNTp54j6IP7l7vPMrE+CeIaY2c+Bz4DjY++PjzU5+gKHmdnvotdtgK7A/sAoAHefa2YLwsHufmo9MbYCrgJOTBBfNSpKGbv7fDO7GpgGfA7MBb7N4TonmtmBpDL70939k+iaD7r7l9E+fYEeZjYwet0e2JZUGd8d/S4sM7OnY/E01I91GXCtmc0jVYG+nGOc1aQoZRzZ093fi5raj5vZInef3sR1Sl3GLwE17v551PKcSKqCblA+lebq2PZ3pJrEQbx5a8Du7v5VjufdGxhgZkdF59nIzO5w90FNHHeFu49uIk4Djnb3JfEdYr8IuepA6q/Zc9GxWwAPm9nh7j436ckqWLHKGHe/GbgZwMxGAYtzOOxOd7+giTgNGOzuT8R3MLOcm/+xGD8l1fca/lAuBVraDCDFLOP3op/LzexBYHegqUqzHGUcth+KuvM6NNYPW5AhR1HN/rGZbRv9csWDnwacE17U19Stda6h7t7Z3WuAk4DHQoVpZqNCP2QzTQXSd2rNLDTDnwV+Fr23C7BjEzGucvdO7l4TxTkb6NfCKswshSzjaJ/Nop81wFHAPdHr883srDxCnQoMNrN1o/Ntb2brkyrj46N+r62BA3KIsYOZtY5e/hKY5u6rGzummhWyjC11/2CDaLsdqXsU86PXlVTGW8S29wS+aerGVSHHaf6W1H/MdGBZ7P1zgH2iDtuFwBlRgI31hTRkZ2B5HjFeCrSz1DCIBcDw6P3rgU3MbBGpO6bpyq+hPs21VCHLeFK07yTgLHf/d/R+D+CjPGIcA7wJzDOz+cCNpFpUE4B3gYWkbjDOCAc00t/1A2Chmb0OHExqREdLV6gy3hJ4wcxeBmYBD7j7tOizSirjgZYa9jYPuIbsrr16Vc1jlJZqBz/i7oeWOxYpHjP7B9C/CMNKpEJUexlXTaUpIlIJ9BiliEgCqjRFRBJQpSkikoAqTRGRBFRpiogkoEpTRCQBVZoiIgn8f6S1hmwDdPmXAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc310396ac8>"
+       "<matplotlib.figure.Figure at 0x7fab0c040dd8>"
       ]
      },
      "metadata": {},
@@ -1289,10 +1194,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 47,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_conv_weights(weights, input_channel=0):\n",
@@ -1345,7 +1248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -1357,21 +1260,21 @@
       "=================================================================\n",
       "input_2 (InputLayer)         (None, 784)               0         \n",
       "_________________________________________________________________\n",
-      "reshape_2 (Reshape)          (None, 28, 28, 1)         0         \n",
+      "reshape_1 (Reshape)          (None, 28, 28, 1)         0         \n",
       "_________________________________________________________________\n",
       "layer_conv1 (Conv2D)         (None, 28, 28, 16)        416       \n",
       "_________________________________________________________________\n",
-      "max_pooling2d_3 (MaxPooling2 (None, 14, 14, 16)        0         \n",
+      "max_pooling2d_2 (MaxPooling2 (None, 14, 14, 16)        0         \n",
       "_________________________________________________________________\n",
       "layer_conv2 (Conv2D)         (None, 14, 14, 36)        14436     \n",
       "_________________________________________________________________\n",
-      "max_pooling2d_4 (MaxPooling2 (None, 7, 7, 36)          0         \n",
+      "max_pooling2d_3 (MaxPooling2 (None, 7, 7, 36)          0         \n",
       "_________________________________________________________________\n",
-      "flatten_2 (Flatten)          (None, 1764)              0         \n",
+      "flatten_1 (Flatten)          (None, 1764)              0         \n",
       "_________________________________________________________________\n",
-      "dense_3 (Dense)              (None, 128)               225920    \n",
+      "dense_2 (Dense)              (None, 128)               225920    \n",
       "_________________________________________________________________\n",
-      "dense_4 (Dense)              (None, 10)                1290      \n",
+      "dense_3 (Dense)              (None, 10)                1290      \n",
       "=================================================================\n",
       "Total params: 242,062\n",
       "Trainable params: 242,062\n",
@@ -1395,10 +1298,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 49,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_input = model3.layers[0]"
@@ -1413,7 +1314,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 50,
    "metadata": {
     "scrolled": true
    },
@@ -1421,10 +1322,10 @@
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras._impl.keras.layers.convolutional.Conv2D at 0x7fc30c26cb70>"
+       "<tensorflow.python.keras.layers.convolutional.Conv2D at 0x7fab0c052d30>"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1443,10 +1344,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 51,
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_conv2 = model3.layers[4]"
@@ -1463,7 +1362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1479,7 +1378,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 53,
    "metadata": {
     "scrolled": true
    },
@@ -1490,7 +1389,7 @@
        "(5, 5, 1, 16)"
       ]
      },
-     "execution_count": 55,
+     "execution_count": 53,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1508,16 +1407,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 54,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc302a554a8>"
+       "<matplotlib.figure.Figure at 0x7faa856a42e8>"
       ]
      },
      "metadata": {},
@@ -1537,10 +1436,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 55,
+   "metadata": {},
    "outputs": [],
    "source": [
     "weights_conv2 = layer_conv2.get_weights()[0]"
@@ -1548,14 +1445,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc2cc6bde10>"
+       "<matplotlib.figure.Figure at 0x7faa8529c240>"
       ]
      },
      "metadata": {},
@@ -1575,10 +1472,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 57,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_conv_output(values):\n",
@@ -1622,10 +1517,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 58,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_image(image):\n",
@@ -1645,16 +1538,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 59,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfiAowg8ERfiBoAg/EBThB4L6f6yMEem39pFEAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc2cc21aac8>"
+       "<matplotlib.figure.Figure at 0x7faa84ab9208>"
       ]
      },
      "metadata": {},
@@ -1662,7 +1555,7 @@
     }
    ],
    "source": [
-    "image1 = data.test.images[0]\n",
+    "image1 = data.x_test[0]\n",
     "plot_image(image1)"
    ]
   },
@@ -1677,7 +1570,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1686,7 +1579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1703,7 +1596,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -1712,7 +1605,7 @@
        "(1, 28, 28, 16)"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1731,16 +1624,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 63,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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4cnIyoRrHbaa3YRiGByHTKIeKOMDFxJPH4SBaaUFBwaAnfDwgp3J6erqmPogJ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\nwxvRzOVkraqq8qtJglNyKil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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc2cc21a2e8>"
+       "<matplotlib.figure.Figure at 0x7faa847ac1d0>"
       ]
      },
      "metadata": {},
@@ -1762,7 +1655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 64,
    "metadata": {
     "scrolled": true
    },
@@ -1781,7 +1674,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
@@ -1790,7 +1683,7 @@
        "(1, 14, 14, 36)"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1809,14 +1702,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Y4OqjY4O4VcydOxeAIUOG5PQ+CduUWjpxROxp6VUFpK5Oroh9Lu4VF2R8QeeX/v4gjv1RIeGU8pwWGqYs2kYxgi7CROzl4rJnZ8PLB5VMFUVRHFDwX42Elorzs+R7tJMDFNux2RUiYUpChWySqWTcB38IW1wRe9i4ceMAGDZsWF6fE3dbqZCvXUyI87MskqnUcMolyCYbIpnGMeiiELbaaivAe2YLtX+rZKooiuIAXUwVRVEcULCaL+U5bFeodETtEHebqqoqc07yDWZypo0bUup2jz32AOD+++835wYPHuw7d9JJJ0U8usKQTYpc1F/ZiLPjnOX+lcJ9tBH3IcmsBJ4KL5mk7CxZEvcuZWriSM+ePZ18jqj3peYGlQkpT2/nM5XfbJBy0Nko/W9JURQlBiSCZH9JJBLfAXPCG05WBqdSqY3DvojOMRLWh3nqHB1SCvMMtJgqiqIomVE1X1EUxQG6mCqKojhAF1NFURQH6GKqKIrigEB+pjU1Nam6urqQhpKdhoYGGhsbQ49nyzZHCZEV31obCUmT13xC76Keoz0Pu9Y4ePMII2FJfX19YxS7wOv78xo2Uc0RvHnaz6kkdU5PRG6Hz7oIb851noEW07q6OqZOnZr/qAogSDG3QpA5ijM3eBmVJAuPlNKVfATg5SgQh2k7W7csSJIvsX///gAMGjTI9Nl0001NXoOwyTRHKYD4/PPPA55z84Ybbmj6yJzkYbXj03fddVcAjj32WMDL3Zop01AikYjExWV9el4zITkxXDnxpxPVHMGbp11mfsqUKQDcfvvtALz66quA/5mT/pLT1X6eDz74YMAroLjXXnsBa2d3y3WequYriqI4QBdTRVEUBzjP9ir1x+2kudtvvz2QW5JaSU5s164OS03JRCqVYs2aNSxdutQck9RcUntbXmfMmGH6SLmPhoYGwG+DFLVDbDyieqxatcr06dWrV0ZbbJjYORIuvPBC36vw/fffm7ao/qJW2rXm5fuSz8yk3merWa64J8rfTVTY9tCxY8f6XnNh9uzZpi2/R/meCk0xqJKpoiiKA/KSTL/++mvT/vTTTwFPEhMDr13q+U9/+hPgZd+R94CXkeaAAw4AYJ999gFg//33N31qa2sjk9oSiQTl5eW+zaHOGDp0aMZ2vsSxLIRkTgI48MADfa9BKbWMUkp8aGtr44cffvB5l+QjeUvC7EzIJpVs3AW9hkqmiqIoDshLFLKTo4wfPx5Y259rzz33NO0zzjgjn8v4iLocxvvvv2/aYscdOXIk4OVgLVVWrlzJlClTjBsUwBVXXOH0GldeeSUAV111ldPPDUIqlaK5udnnTiO2fLF3P/nkkwAsXrzY9BkwYADg5d99+OGHzbltt90WgMcffxzw8psq4bJmzRoWLFjgyzt7wgknOL3GRRddBMCRRx5pjgUpOaSSqaIoigPykkyz2R1KnZaWFubMmcNnn31mjk2ePBmAe++9F/Cc9aVUrH3s/PPPB+Dyyy835yRDf1xoa2tj6dKlfPDBB+bY/PnzgcLL3Qp2QcVikUgkqKyszFhQbsSIEQD069cP8HtffPTRRwC88MILgF/6fOihh9Y6lk5LSwtxSm357bffAviCNBobGwFvrldffbU5J8EpUi1CnNbPPPNM06fQIn1BKS8vZ8CAAcycOTO0a0yaNAnwvI+gw/Mm13upkqmiKIoDdDFVFEVxQFF8cV5++WXTFleodGyVxHYuD5uKigoGDx7MKaecYo7ZbfBUwjlzvBBzqcEdBNuJvbW11SRsCJsePXowfPhwjj76aHNM1D5Xav6ECROcfE7YSJ4EG3GLExOA5B3IlYqKishrzNvuPGKyWbJkCQCjR49eq7+4GEmeiXPPPdecE3c4cYYXtz97I2/58uWRBpkkEgnKysqMoz3Aa6+9Bngx9YVy+umnA/7fcmVlZc73UiVTRVEUBxRFMu1MGrWx/2krKipiZdCXf/V8pFEbKT8LHVJQVCV1y8rK6N27t88h+amnngI8l5/NN98cgKOOOsr0EWd9CSvNdk/EhaiYtLe309TUxLJly8wxka4ktFnc3ObNm2f6PPLII0Buz2kcaG9v9wVEDBkypMv3iAYSRIOwN50qKysjdVdMJpP06tXLlFIHL5ubbLClZ3sKSk1NDdCRoSqvMRZ0dUVRFAWISDJ95ZVXAHjssccAuO2227p8j/1Pm0wmI7dBZUMksnzHtHz5ciD6QAQhmUzSu3dvn9Rptzujb9++QHaJNE4kk0l69uyZU0jge++9Z9qSp3XHHXcMbWwucaHRiBsYeHlro8qvGwTbzTAXl8NccrrOmjULgP322w+AnXbaKa+xqWSqKIriAF1MFUVRHBCamm/nDXz66acB+O1vf9vl+2SzwC77USx1uDMKNTlIdJAYvOPMX//6V9M+9NBDiziScJAIoGnTppljv/71r4s1nMhZsWIF4FeD46jeB+HLL7807Vw24ySbXVAXuHRUMlUURXFAaJLpxIkTTVs2XLbccssu35ctU3uxKHTDSZB8iWFU/AwLW3o++eSTiziScBCn9VGjRpljhbrYxAUJLsn2vN16662At/myLpCLNApe0I38ru1ie/mgkqmiKIoDnIt///jHPwB4/fXXzTFx8s6G2G5EMo2TK1ShY5Ew0SASelxYF6VR8EJ5xT5YW1tbzOGEQjaJ9O9//zvg/U4vvfTSSMZUbOxAGalbNm7cOCefrZKpoiiKA5xJppIDUTLs//znPw/0fpH+ogqpzAfJWWp7GuSCzKkUJNIHHngA8MIN7fC9dETSBs/RPe5IOKnYwddFiTQXRFs69thjizyS/FmwYAHg5RWWEOhsTveSk9ju52oPI74rl6IoSgmhi6miKIoDnKn5+ebBlJyIUeYsDYpsjslGWu/evQEv3yV4mWYWLVoEeJlswHMvGjhwYOhjzRfJMSsF8CQuPZuaXyqqvY2odHE2J4XFgw8+aNpvvfUW4C9FUmrIvRQ3SlH7s6n5dg6GfEuWd8b690QpiqKEQCJIBqBEIvEdMKfLjuEwOJVKhV6ZTucYCevDPHWODimFeQZaTBVFUZTMqJqvKIriAF1MFUVRHKCLqaIoigN0MVUURXGALqaKoigOCOS0X1NTk8q3DGqhNDQ00NjYGHoqqZqamtTgwYNNLkiAlpYWwItnrqioAPylb11kuYpyjsW6jwD19fWNUbjUrC/P67o+RyiNeQZaTOvq6pg6dWr+oyqAXXbZJZLr1NbW8uabb5q66gCNjY0AfPLJJwBssMEGgD/hiZRb+f777wGvkifA9ttvD3Qd5RXVHMO8jxLRJq92km+JOkokEpH4C9bW1jJ58mSToAbcJ37uLHH4unAvuyKqOUJpzFPVfEVRFAfoYqooiuKA+BRaignJZNKn4oOXqMRVRu51GakkG4eKsqlUijVr1qx1P10yY8YMADbddFNzrBgJYKRyAHgJP+R1yZIlvlfw7P9iqrKrk4ppRhL6SB7ejTf2zNylVMcsKlQyVRRFcUAgyTSVStHa2uqrSy3/cNtttx1Q+qnNmpubmTVrFnfffbc5JmnKJJO3K55++mnT7tOnj0n1FzapVIqWlhafpNLQ0ACsXRXArk5aaiQSCcrLy31Sl2tmzpwJeJuS0CHlRZXzQu6lfb0tttjC95oJSUUnlQfsypzpY+/evTsAra2t5ljUmodoGXGWiEt75VMURYkJgSTTlpYW5s6dy6RJk8yxRx99FIDZs2cDXs3qbbfd1vQRyWCfffYB4Iwzzljrs++66y7AS9g6aNCgIENzRktLC3PmzOGf//ynOXbNNdcA8Le//Q2AYcOGAbB48WLTRyQ68YXbbbfdurzWk08+adqnn356ZBVZ29vbWb16takbDjBlyhTAc/+S5MFiE7Tp378/AIcddpg5Nn78eAB22GEHwJPii2k7TSaToUmls2bNAuD5558HYPjw4eacaGtRkEgkjN9zEHJ5PuOEaBlhkG9tt3RUMlUURXFAIMm0srKSLbbYgmuvvdYck7bUo5bSHiK9AIwYMaLLzx47dixQPIlU6N27N+PGjePzzz83x+6//37Ak0TffvttwF+BVeYrNrRsTJ8+HYAxY8aYY6NHjy74nzFXysrKqK6uZtSoUeaY3bZpamoy7Xnz5gGenc2OSJF/d7H7zp8/Hyj+/QyLwYMHA/Czn/0MWLvKaVRahmBLw6IlyhhKoSpuMREt7IADDijoc1QyVRRFcYAupoqiKA5w5rTfp08fILioLO4WcSufYru6nHvuuTm/b6uttuqyj2zOyGZNnLE3cIYOHdppv84c1W31s9Td5mzuuOMOAA4//PCijqO9vZ2mpiY+++wzc+zVV18FYPLkyQB88cUXgGd6Ac/JX8wTV1xxhTlnm6/WZR5//HHAM1EWyrrzdCuKohSRooeTSkYm25VqXWXu3LnA2psVxUACMNJx7X4S9UZMJuxQS3H1ko3CF198EYCnnnrK9Jk4cSLgd/0SzjrrLAAeeughoPhSXDKZpLKy0gTNAAwcOBCAgw8+GIBvvvkG8AIzwAstld9dsSVslyxcuNC07TDfdI477jjAc28rFJVMFUVRHFB0ydR2oYo7kqMzqCP6okWLALj11lsB+Mtf/uJ2YHkQphN0+nWKjYRDguemJ+GT3377LQAnn3yy6bP77rt3+ll33nkn0BFkkf7ZxaKsrMxn25a2SGUita5atcr0kWfSdYh0MRGbcLbENqNHjzZtCTDae++9nVxfJVNFURQH6GKqKIrigEjVfKmrZEfViEtVKZBvnPkNN9wAwHXXXedyOLFGXKLi5g4l9bymTZsGeLkIzj777E7fc+GFF5q2RHTdcsstYQ0xNGyTy7qk3ktEnkR+7bHHHmv1ETcxidAE/4acC+L1pCuKopQokUqmK1euBPwO8esqL7zwgmln+qdcV8l3ky4qxCVI3GdyCci4+eabTfsPf/gDQKg5Ul0hLmGSN6GUc9Nm46uvvgKy/85OO+003yt4+RVcoZKpoiiKAyKVTEtdIn3jjTcAL8NVNiSbEHjln0sB0R7E5SeohBlXiVSQeYmTejZpTRz07dpfdthlXBF7tczVdolal5A9mGxh2Q8//DDglfi+5557QhuPSqaKoigOKFgylXBQSa7Qr18/wJ/Ju7KyEvD+SeJcxyUTkn9U8h5KYoRDDjlkrb6SsKWUpFHw7GsS8io2RdkptamqqgJg6623Nsfknz/ukmnfvn1z7it5a3/xi1+ENZxQSPegCDLnUiKXPZirr74agIsvvjj08ahkqiiK4gBdTBVFURxQsJovBvxjjjmm0z4S/yyqYKkhBm4p/5CuCoMXBx2HWPR8kM0KySKUKYuXuNhItim7kFvc1fsgvPbaawAceuihQLB8tkp0dKbev/7666Ytv9kJEyaEPh6VTBVFURyQCJLhPpFIfAfM6bJjOAxOpVIbh30RnWMkrA/z1Dk6pBTmGWgxVRRFUTKjar6iKIoDdDFVFEVxgC6miqIoDtDFVFEUxQGB/ExrampSdXV1IQ0lOw0NDTQ2NobuxKlz7ECSZdh+s658aOvr6xuj2AXWexkuUc0RSmOegRbTuro6pk6dmv+oCmCXXXaJ5Drr+xznzZsHePkU7KxKssCmO++Dl5NAjknBOvkcu08ymYzExSWXezlnTsdQ7CJsLoJL4nAvwyaqOULmea5YsQLwcmVsttlmoVw713mqmq8oiuIAXUwVRVEcEGlyaCW+SMrAjTbaCMhclkNSu+Wb5DuOeQtcl65QoqN3796+12KjkqmiKIoDVDJNI5VKsWbNGlMSGOCzzz4DvCxJIr3Jhgx4mxaSfUkKt9n944YkhAZvo8jeiFHiT0tLC/PmzeOpp54yx7744gsANt64w2HivPPOA9bdJNH58tJLLwFeIT47C5rQ0tJCriH3KpkqiqI4oGDJVCS4TKt6Loi7Q21tLVD8nKdNTU1MnTrVlGEBz32mf//+gJfPtL6+3vTZd999ARg6dCgAQ4YMMeckp+J3330HeGWgzz77bNMnymKDbW1tLF++3Heou94WAAALbElEQVSsuro68OfMnj3btLfYYouMfeS7g7XLaRQTKaEzf/58ADbffPO8PmfatGkADBs2zM3AApJMJunZsycjR440x0STkrLUUn5l0qRJpo+UF1qfkd9sNioqKnK29cfn6VYURSlhCpZM85VIBZEQii2RChUVFdTW1vqKqGUrB5zO4sWLAfj444/NMZFI77vvPgBuueUWwMvOD3DqqafmPeZ8aG9vL1gaHjRoUKfnROJ77LHHzLFcJIGwmTVrFuBpQvlKpEKxJFKhW7dubLTRRj67vBSzPP/88wF49tlnAfjggw9Mn/Hjx0c4yniybNkywJ0tWSVTRVEUB+hiqiiK4oCiuEZdcsklpj127NhiDKFTysvLGThwYN7vF8P+/vvvv9a5nXfeGYATTzwRgOHDh+d9nUIoKysrSMW/9tprAbj00ks77fPwww8DsGrVKnNM4vWLiWwG5ovEgYujeJw21dKRzVB5VfyBIzfeeCMAF1xwgZPPju+ToCiKUkJEKpnKP8BNN91kjsWtjG57ezsrV640G0ngZacZMGAA4DlD54tsEJQCdmDCYYcdBsCxxx7baX9xcBb3nMMPP9ycK/R7c8nSpUsBbwO1V69enfYdMWKEaX/yyScAOTtyK/Fg+vTpABx//PHmmCuJVFDJVFEUxQGRSKYi3bz11lsA3HHHHeZcWDkI8yWZTFJVVdWpE3o+NDQ0AB05GUuNyy+/3LTff/99wHO1ycStt94KeK5utlRn5zYtNkHst3Zo8TPPPBPGcJSQETv/Aw88EOh9QTQQlUwVRVEcoIupoiiKAyJR8yW6R2LbzzrrrCguGxskyquUkPwBoh4BPP/88532lygvibI56qijAHxuZnHMZ5oNcf2SaCmAQw45pFjDUfLg+uuvB+C4447L6/1BnlmVTBVFURwQmmT6xhtvmLZsXEj+wFJHcpXaWaPSnfT/+9//mvZBBx0UzcAcsGDBAsDbJBw1apQ5lykQQbj99tsBz31s1113BTpix0sVkbKvu+66Io9ECcLkyZNNe+LEiQB89dVXoV9XJVNFURQHhCY2PPLII6Ytmb4LCdOMA1InSSTSTJmuxMHfzghVSog0Jraid955p9O+M2bMMG2xmZ5wwglAvBz0g/Kf//wHgEcffRSAPn36FHM4eSMaVFwrPYSFnbHtz3/+c2TXVclUURTFAc4l03fffRfwJ1ewM8qXIosWLQK8UELJg5jJhiiZ13ffffeIRucGSeAhDuoPPvhgl+/53e9+Z9qS6X2bbbYBSm/n3g6Rfe655wCvokKpIRqU3NP1TTI95phjTFs8iKJAJVNFURQH6GKqKIriAOdqvhjrJcPQuoCo9bvssguQPa671NR7QVRCmWO2cjSiBtsbigceeCAQbWFAF0ggQlNTkzmWXmyw1JB7kO1eiCtbqZvgMhFUtZfcIYXmplXJVFEUxQGJIFlREonEd8CcLjuGw+BUKhW6v43OMRLWh3nqHB1SCvMMtJgqiqIomVE1X1EUxQG6mCqKojhAF1NFURQH6GKqKIrigEB+pjU1Nan0OkbioyUbWWVlZW5GlkZDQwONjY2hxyhmmmNURD3HtrY2c0za6RuStu+d3NtC/fHq6+sbo9gFznYvZZ5hhb3q8+qWUphnoMW0rq6OqVOnZjwnTt/i8Gw7zpaXlwPewmtnnpcfpvTpDHEmDxuZ4xNPPGGOidP+6aefHuq1o56jzAu8bFeSh+Cjjz4CYP78+abPjz/+CHg5Squrq825QYMGAZhChOLQbz8HPXv2BCCRSETi4iLzlHGD96cRdiaoKO/le++95/uDiyovQlRzhMxrz5QpUwDYeeedAXeCnF3mvVevXowdOzan96maryiK4gBdTBVFURzgLDZf1KZs6pOoInGqn94ZRx55pGlLguQXX3wRgP32268oY3JN375912pL8TgpO7Iu0KtXr2IPITTa2tpYuXIlq1atMsdEzZ81axbgmWdsU1q/fv0AWLlyJQDDhw8359LzMkhKv7jlXQjrGbVTFjY1Na21j9AZKpkqiqI4IDbVzmQzxJaW4sLo0aMBb4zyzy+lgAGuueYa33suu+wy0z7ggAMA2HPPPUMdp7L+0d7ezo8//ujbnPn6668Br7jh4MGDAU/CBE9qlWfaLjMj/QXZaBQpFjo2e9bVUHS7CGR1dXXOG1sqmSqKojggNpLp0qVLgXhKpoKMLds/srgSTZo0yRx7+eWXAXjvvfdCHF1wbJchKYB48803AzBnTof3ku3GJpKJ2Nv23Xfftc6J7e34448HvDImxaC9vZ0VK1Ywe/Zsc0xK/sp4xdZouxOJTb+1tRWA8ePHm3OdFYW0n4kVK1b4fHjDpKWlhblz5/LCCy+YYyJ1iuuS7FU0NjaaPiK9ih11n332MedmzpwJwFZbbeV7/+rVq02f1tZW8/0oHahkqiiK4oCiS6ZiWxSJZssttyzmcApms802A/zO7nGjra2N5cuXs3DhQnNsjz32AGDChAlA5iAKkUy6d+8ewSgLp62tjaamJqP1gGc3lGJ5Ymv89NNPTR85J1K1HXggngE9evTw9bXtif379zcBKmFTVVXFqFGjGDVqVOjXsne529raugy0iZpnn30WgMcee8wcEwlcypI/8MAD5ty4ceO6/MwVK1bkfC9VMlUURXGALqaKoigOKLqaLy5FH3zwQZFHsv5QVlZGdXW1L7Y+F0pFvRfKy8vp16+f2TAD2HvvvZ1eQ3JR2O4zVVVVoSX8iQtxnN8hhxziew2KbLraa9HIkSNz3mhTyVRRFMUBRZFM7ZVf3IZ+8pOfFGMonTJt2jTTloxKYZZxXr16dSycoGWuCxYsADqy9QjpYcB33323aR9++OEA1NTU+PrYGXji7PaWL9tuuy2Ab5Oiqqqq4DSFuZJKpVizZg1Lliwxxz7//HMA3nrrLcDbmLFd88QV7OSTTwb8ASjFdGcrJhKsYIfEb7DBBlnLntuoZKooiuKASCXTpqYmAP7973+bYzfccEOUQ8iZYcOGRXq97t27R5aHMhu9e/cGYOjQoV32PeOMM7rsY4fmxUHyFsSpXoIS7LGJ21M2WlpaAM92mMt7wiCRSFBeXu5z35L2mDFjALjooosAv2aRz7OWnkwlTvezENITheeb0EUlU0VRFAfoYqooiuKASNV8UQsffPDBKC+rOEZU40wRMKL+SnSVnUs0Dnls01VTmYuYN3KlubkZiMec0pE5yhjFtadQ1zbbHSqqDbYocGVeW3e+EUVRlCISiWR65ZVXAvicp5XSJVtMtkhBIunFNcu9SFlBxycSt2xS5Oo2EyWyUSTubZKzdLfddsvr8yQwwZZGe/XqFYsN00J45ZVXAC8fSHoe16CoZKooiuKASCRTCdO67777oricUkTE/U2k17hJbunSVFDpShy64zYvG5EkpRTySSedVNDnSYnudQ0pEe1Ke1LJVFEUxQGRSKZ2pvJ1HclrWVVVVeSR5IeERT700EOA3zFfKrb+6le/AvzOzZLrVOoOZatSGwfEjijO++lhsODNya6dJDk945ToI5VK+bwUvvnmG8A/7iDIdyOeDuIFEFf7dxAk1Ba8UGBXqGSqKIriAF1MFUVRHBCJmu9anI4zparey6aFlPEQ95qPPvrI9MkWry+qocSox62khSDuQpIVTFTYkSNHmj5S5kRMNnYZZHH9itP80jfRJDb/nHPOyevzJLuXPBPyTJeio/706dMBL9fGYYcdZs7dddddAGyyySZOrlV6346iKEoMSQTJ/JJIJL4D5oQ3nKwMTqVSG3fdrTB0jpGwPsxT5+iQUphnoMVUURRFyYyq+YqiKA7QxVRRFMUBupgqiqI4QBdTRVEUB+hiqiiK4gBdTBVFURygi6miKIoDdDFVFEVxgC6miqIoDvh/KEq7GTrHoFYAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc2a94760f0>"
+       "<matplotlib.figure.Figure at 0x7faa849ed048>"
       ]
      },
      "metadata": {},
diff --git a/03_PrettyTensor.ipynb b/03_PrettyTensor.ipynb
index bb3fbb8..a23fe03 100644
--- a/03_PrettyTensor.ipynb
+++ b/03_PrettyTensor.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #03\n",
     "# PrettyTensor\n",
@@ -16,10 +13,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It is recommended that you use the _Keras API_ instead, see Tutorial #03-C.**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -34,20 +37,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. See the previous tutorial for a more detailed description of convolution."
    ]
@@ -56,9 +53,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -81,10 +75,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The input image is processed in the first convolutional layer using the filter-weights. This results in 16 new images, one for each filter in the convolutional layer. The images are also down-sampled so the image resolution is decreased from 28x28 to 14x14.\n",
     "\n",
@@ -101,10 +92,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -113,9 +101,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -134,10 +120,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
    ]
@@ -145,11 +128,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -168,10 +147,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "PrettyTensor version:"
    ]
@@ -179,11 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -202,20 +174,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -223,11 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -247,10 +209,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
@@ -258,11 +217,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -284,10 +239,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
    ]
@@ -296,9 +248,7 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -307,20 +257,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Data Dimensions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
    ]
@@ -329,9 +273,7 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -353,20 +295,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -375,9 +311,7 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -412,10 +346,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -423,11 +354,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -453,10 +380,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -479,20 +403,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph. We call this feeding the placeholder variables and it is demonstrated further below.\n",
     "\n",
@@ -503,9 +421,7 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -514,10 +430,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-dim tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
@@ -526,9 +439,7 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -537,10 +448,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
@@ -549,9 +457,7 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -560,10 +466,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
@@ -572,9 +475,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -583,20 +484,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Implementation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This section shows the original source-code from Tutorial #02 which implements the Convolutional Neural Network directly in TensorFlow. The code is not actually used in this Notebook and is only meant for easy comparison to the PrettyTensor implementation below.\n",
     "\n",
@@ -605,20 +500,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-functions"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In the direct TensorFlow implementation, we first make some helper-functions which will be used several times in the graph construction.\n",
     "\n",
@@ -629,9 +518,7 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -643,9 +530,7 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -655,10 +540,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following helper-function creates a new convolutional network. The input and output are 4-dimensional tensors (aka. 4-rank tensors). Note the low-level details of the TensorFlow API, such as the shape of the weights-variable. It is easy to make a mistake somewhere which may result in strange error-messages that are difficult to debug."
    ]
@@ -667,9 +549,7 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -734,10 +614,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following helper-function flattens a 4-dim tensor to 2-dim so we can add fully-connected layers after the convolutional layers."
    ]
@@ -746,9 +623,7 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -779,10 +654,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following helper-function creates a fully-connected layer."
    ]
@@ -791,9 +663,7 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -819,10 +689,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Graph Construction\n",
     "\n",
@@ -837,9 +704,7 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -890,20 +755,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## PrettyTensor Implementation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This section shows how to make the exact same implementation of a Convolutional Neural Network using PrettyTensor.\n",
     "\n",
@@ -914,9 +773,7 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -925,10 +782,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now that we have wrapped the input image in a PrettyTensor object, we can add the convolutional and fully-connected layers in just a few lines of source-code.\n",
     "\n",
@@ -939,9 +793,6 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -959,10 +810,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "That's it! We have now created the exact same Convolutional Neural Network in a few simple lines of code that required many complex lines of code in the direct TensorFlow implementation.\n",
     "\n",
@@ -971,20 +819,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Getting the Weights"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Unfortunately, not everything is pretty when using PrettyTensor.\n",
     "\n",
@@ -999,9 +841,7 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1019,10 +859,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Using this helper-function we can retrieve the variables. These are TensorFlow objects. In order to get the contents of the variables, you must do something like: `contents = session.run(weights_conv1)` as demonstrated further below."
    ]
@@ -1031,9 +868,7 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1043,20 +878,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Optimization Method"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "PrettyTensor gave us the predicted class-label (`y_pred`) as well as a loss-measure that must be minimized, so as to improve the ability of the Neural Network to classify the input images.\n",
     "\n",
@@ -1068,11 +897,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -1080,10 +905,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Performance Measures\n",
     "\n",
@@ -1096,9 +918,7 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1107,10 +927,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Then we create a vector of booleans telling us whether the predicted class equals the true class of each image."
    ]
@@ -1119,9 +936,7 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1130,10 +945,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
    ]
@@ -1142,9 +954,7 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1153,20 +963,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Run"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -1177,9 +981,7 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1188,10 +990,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1201,11 +1000,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1213,20 +1008,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1237,9 +1026,7 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1248,10 +1035,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for performing a number of optimization iterations so as to gradually improve the variables of the network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
@@ -1259,11 +1043,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Counter for total number of iterations performed so far.\n",
@@ -1320,20 +1100,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
@@ -1342,9 +1116,7 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1378,10 +1150,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
@@ -1390,9 +1159,7 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1430,20 +1197,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1455,11 +1216,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Split the test-set into smaller batches of this size.\n",
@@ -1534,10 +1291,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance before any optimization\n",
     "\n",
@@ -1547,11 +1301,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1567,10 +1317,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1 optimization iteration\n",
     "\n",
@@ -1580,11 +1327,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1603,9 +1346,6 @@
    "cell_type": "code",
    "execution_count": 38,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1623,10 +1363,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 100 optimization iterations\n",
     "\n",
@@ -1637,9 +1374,6 @@
    "cell_type": "code",
    "execution_count": 39,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1658,11 +1392,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1689,10 +1419,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 1000 optimization iterations\n",
     "\n",
@@ -1703,9 +1430,6 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1734,9 +1458,6 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1765,10 +1486,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Performance after 10,000 optimization iterations\n",
     "\n",
@@ -1779,9 +1497,6 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1891,9 +1606,6 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1950,10 +1662,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Visualization of Weights and Layers\n",
     "\n",
@@ -1962,10 +1671,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting convolutional weights"
    ]
@@ -1974,9 +1680,7 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2028,20 +1732,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 1"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the first convolutional layer.\n",
     "\n",
@@ -2052,9 +1750,6 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2075,20 +1770,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Convolution Layer 2"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the filter-weights for the second convolutional layer.\n",
     "\n",
@@ -2101,9 +1790,6 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2124,10 +1810,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 16 input channels to the second convolutional layer, so we can make another 15 plots of filter-weights like this. We just make one more with the filter-weights for the second channel. "
    ]
@@ -2135,11 +1818,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2158,20 +1837,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
@@ -2179,11 +1852,7 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2193,10 +1862,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2209,10 +1875,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2236,10 +1899,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2274,5 +1934,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/04_Save_Restore.ipynb b/04_Save_Restore.ipynb
index 523cdba..4491afd 100644
--- a/04_Save_Restore.ipynb
+++ b/04_Save_Restore.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It is recommended that you use the _Keras API_ instead, which also makes it much easier to save and load a model, see Tutorial #03-C.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -44,7 +53,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -104,9 +112,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -133,9 +139,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -169,9 +173,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -199,9 +201,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -231,9 +231,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "data.test.cls = np.argmax(data.test.labels, axis=1)\n",
@@ -339,9 +337,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -572,9 +568,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weights_conv1 = get_weights_variable(layer_name='layer_conv1')\n",
@@ -602,9 +596,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -737,9 +729,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "save_path = os.path.join(save_dir, 'best_validation')"
@@ -803,9 +793,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "init_variables()"
@@ -873,9 +861,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Counter for total number of iterations performed so far.\n",
@@ -1234,9 +1220,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def print_test_accuracy(show_example_errors=False,\n",
@@ -1344,7 +1328,6 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1371,7 +1354,6 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1412,7 +1394,6 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1491,7 +1472,6 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1560,9 +1540,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1598,9 +1576,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "init_variables()"
@@ -1616,9 +1592,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1643,7 +1617,6 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1702,7 +1675,6 @@
    "cell_type": "code",
    "execution_count": 51,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1768,7 +1740,6 @@
    "cell_type": "code",
    "execution_count": 52,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1811,9 +1782,7 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -1875,9 +1844,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1889,9 +1858,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/05_Ensemble_Learning.ipynb b/05_Ensemble_Learning.ipynb
index 60d1ccf..6afc6cf 100644
--- a/05_Ensemble_Learning.ipynb
+++ b/05_Ensemble_Learning.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It is recommended that you use the _Keras API_ instead, which also makes it much easier to train or load multiple models to create an ensemble, see e.g. Tutorial #10 for inspiration on how to load and use pre-trained models using Keras.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -44,7 +53,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -105,7 +113,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -134,9 +141,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -170,9 +175,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -200,9 +203,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -234,9 +235,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "data.test.cls = np.argmax(data.test.labels, axis=1)\n",
@@ -274,9 +273,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -303,7 +300,6 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -333,9 +329,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -363,9 +357,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -534,9 +526,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -740,9 +730,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -1008,9 +996,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize(num_iterations, x_train, y_train):\n",
@@ -1111,9 +1097,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1928,7 +1912,6 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1958,9 +1941,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1989,7 +1970,6 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2027,9 +2007,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2057,9 +2035,7 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2105,9 +2081,7 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ensemble_incorrect = np.logical_not(ensemble_correct)"
@@ -2127,9 +2101,7 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2156,9 +2128,7 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2186,9 +2156,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2215,9 +2183,7 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "best_net_pred_labels = pred_labels[best_net, :, :]"
@@ -2294,9 +2260,7 @@
   {
    "cell_type": "code",
    "execution_count": 61,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2323,9 +2287,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2352,9 +2314,7 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ensemble_better = np.logical_and(best_net_incorrect,\n",
@@ -2372,7 +2332,6 @@
    "cell_type": "code",
    "execution_count": 64,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2421,7 +2380,6 @@
    "cell_type": "code",
    "execution_count": 66,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2457,9 +2415,7 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images_comparison(idx):\n",
@@ -2569,7 +2525,6 @@
    "cell_type": "code",
    "execution_count": 72,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2598,9 +2553,7 @@
   {
    "cell_type": "code",
    "execution_count": 73,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2624,9 +2577,7 @@
   {
    "cell_type": "code",
    "execution_count": 74,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2651,7 +2602,6 @@
    "cell_type": "code",
    "execution_count": 75,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2684,7 +2634,6 @@
    "cell_type": "code",
    "execution_count": 76,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2714,7 +2663,6 @@
    "cell_type": "code",
    "execution_count": 77,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2741,7 +2689,6 @@
    "cell_type": "code",
    "execution_count": 78,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2767,9 +2714,7 @@
   {
    "cell_type": "code",
    "execution_count": 79,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2804,9 +2749,7 @@
   {
    "cell_type": "code",
    "execution_count": 80,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2867,9 +2810,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2881,9 +2824,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/06_CIFAR-10.ipynb b/06_CIFAR-10.ipynb
index 8a145e4..9e45d12 100644
--- a/06_CIFAR-10.ipynb
+++ b/06_CIFAR-10.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It would take too much effort to update this tutorial to use e.g. the Keras API, especially because there is already a short [Keras tutorial on CIFAR-10](https://github.com/keras-team/keras/blob/master/examples/cifar10_cnn.py) which does the same.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -42,7 +51,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -103,7 +111,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -132,9 +139,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -198,7 +203,6 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -224,9 +228,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -270,9 +272,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -300,9 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -327,7 +325,6 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -472,7 +469,6 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -508,9 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -712,9 +706,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "distorted_images = pre_process(images=x, training=True)"
@@ -1021,9 +1013,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "weights_conv1 = get_weights_variable(layer_name='layer_conv1')\n",
@@ -1049,9 +1039,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def get_layer_output(layer_name):\n",
@@ -1075,9 +1063,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "output_conv1 = get_layer_output(layer_name='layer_conv1')\n",
@@ -1182,9 +1168,7 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1559,9 +1543,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def print_test_accuracy(show_example_errors=False,\n",
@@ -1808,7 +1790,6 @@
    "cell_type": "code",
    "execution_count": 56,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1847,7 +1828,6 @@
    "cell_type": "code",
    "execution_count": 57,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [],
@@ -1869,7 +1849,6 @@
    "cell_type": "code",
    "execution_count": 58,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1930,7 +1909,6 @@
    "cell_type": "code",
    "execution_count": 59,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1968,7 +1946,6 @@
    "cell_type": "code",
    "execution_count": 60,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -2048,9 +2025,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2079,7 +2054,6 @@
    "cell_type": "code",
    "execution_count": 63,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2109,7 +2083,6 @@
    "cell_type": "code",
    "execution_count": 64,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2145,9 +2118,7 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "label_pred, cls_pred = session.run([y_pred, y_pred_cls],\n",
@@ -2165,7 +2136,6 @@
    "cell_type": "code",
    "execution_count": 66,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2197,9 +2167,7 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2219,9 +2187,7 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2255,9 +2221,7 @@
   {
    "cell_type": "code",
    "execution_count": 69,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2315,9 +2279,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2329,9 +2293,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/08_Transfer_Learning.ipynb b/08_Transfer_Learning.ipynb
index e90922e..c3caab2 100644
--- a/08_Transfer_Learning.ipynb
+++ b/08_Transfer_Learning.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It would take too much effort to update this tutorial to use e.g. the Keras API, especially because Tutorial #10 is a similar but more advanced version of Transfer Learning using the Keras builder API. However, you may still want to watch the video for this Tutorial #08 as it explains more details about Transfer Learning than Tutorial #10 does.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -52,7 +61,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -114,7 +122,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -143,9 +150,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -226,9 +231,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -252,9 +255,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -298,9 +299,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -328,9 +327,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -354,9 +351,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -457,9 +452,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -521,7 +514,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -558,7 +550,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [],
@@ -585,9 +576,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from inception import transfer_values_cache"
@@ -603,9 +592,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "file_path_cache_train = os.path.join(cifar10.data_path, 'inception_cifar10_train.pkl')\n",
@@ -615,9 +602,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -645,9 +630,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -682,9 +665,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -711,9 +692,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -740,9 +719,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_transfer_values(i):\n",
@@ -767,7 +744,6 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -814,7 +790,6 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -892,9 +867,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "pca = PCA(n_components=2)"
@@ -910,9 +883,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "transfer_values = transfer_values_train[0:3000]"
@@ -947,7 +918,6 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -995,7 +965,6 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1024,9 +993,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_scatter(values, cls):\n",
@@ -1057,7 +1024,6 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1141,9 +1107,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "transfer_values_reduced = tsne.fit_transform(transfer_values_50d) "
@@ -1160,7 +1124,6 @@
    "cell_type": "code",
    "execution_count": 40,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1191,9 +1154,7 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1324,9 +1285,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Wrap the transfer-values as a Pretty Tensor object.\n",
@@ -1417,9 +1376,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -1492,9 +1449,7 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1905,7 +1860,6 @@
    "cell_type": "code",
    "execution_count": 63,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1939,9 +1893,7 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2058,9 +2010,7 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2185,9 +2135,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2199,9 +2149,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/09_Video_Data.ipynb b/09_Video_Data.ipynb
index f0e39d7..44117d1 100644
--- a/09_Video_Data.ipynb
+++ b/09_Video_Data.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It would take too much effort to update this tutorial to use e.g. the Keras API, especially because Tutorial #10 is a similar but more advanced version of Transfer Learning using the Keras builder API. However, you may still want to watch the video for Tutorials #08 and #09 as they explain more details about Transfer Learning than Tutorial #10 does.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -50,7 +59,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -112,7 +120,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -141,9 +148,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -243,7 +248,6 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -272,7 +276,6 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -303,9 +306,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This is the code you would run to load your own image-files.\n",
@@ -333,9 +334,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -363,9 +362,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "image_paths_train, cls_train, labels_train = dataset.get_training_set()"
@@ -381,9 +378,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -410,9 +405,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "image_paths_test, cls_test, labels_test = dataset.get_test_set()"
@@ -428,9 +421,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -458,7 +449,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -593,9 +583,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -657,7 +645,6 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -694,7 +681,6 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [],
@@ -721,9 +707,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from inception import transfer_values_cache"
@@ -739,9 +723,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "file_path_cache_train = os.path.join(data_dir, 'inception-knifey-train.pkl')\n",
@@ -751,9 +733,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -777,9 +757,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -810,9 +788,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -839,9 +815,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -868,9 +842,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_transfer_values(i):\n",
@@ -896,7 +868,6 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -943,7 +914,6 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1021,9 +991,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "pca = PCA(n_components=2)"
@@ -1039,9 +1007,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# transfer_values = transfer_values_train[0:3000]\n",
@@ -1078,7 +1044,6 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1126,7 +1091,6 @@
    "cell_type": "code",
    "execution_count": 39,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1155,9 +1119,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_scatter(values, cls):\n",
@@ -1191,7 +1153,6 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1275,9 +1236,7 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "transfer_values_reduced = tsne.fit_transform(transfer_values_50d) "
@@ -1294,7 +1253,6 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1326,7 +1284,6 @@
    "cell_type": "code",
    "execution_count": 47,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1459,9 +1416,7 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Wrap the transfer-values as a Pretty Tensor object.\n",
@@ -1552,9 +1507,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -1627,9 +1580,7 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1782,9 +1733,7 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred, correct):\n",
@@ -2050,7 +1999,6 @@
    "cell_type": "code",
    "execution_count": 69,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -2090,7 +2038,6 @@
    "cell_type": "code",
    "execution_count": 70,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2120,7 +2067,6 @@
    "cell_type": "code",
    "execution_count": 71,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -2239,9 +2185,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2253,9 +2199,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/10_Fine-Tuning.ipynb b/10_Fine-Tuning.ipynb
index 924ca7c..1f385fc 100644
--- a/10_Fine-Tuning.ipynb
+++ b/10_Fine-Tuning.ipynb
@@ -60,8 +60,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
      ]
     }
    ],
@@ -95,6 +95,35 @@
     "from tensorflow.python.keras.optimizers import Adam, RMSprop"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This was developed using Python 3.6 and TensorFlow version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.9.0'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.__version__"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -111,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -135,7 +164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -199,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -235,7 +264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -274,7 +303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -314,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -337,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -378,7 +407,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -394,7 +423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "scrolled": true
    },
@@ -420,7 +449,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "scrolled": true
    },
@@ -449,7 +478,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -472,7 +501,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "scrolled": true
    },
@@ -494,7 +523,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -503,7 +532,7 @@
        "(224, 224)"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -524,7 +553,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -549,7 +578,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -565,7 +594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -581,7 +610,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -602,7 +631,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "scrolled": true
    },
@@ -611,7 +640,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Found 4170 images belonging to 3 classes.\n"
+      "Found 4173 images belonging to 3 classes.\n"
      ]
     }
    ],
@@ -632,7 +661,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -661,7 +690,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -670,7 +699,7 @@
        "26.5"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -689,7 +718,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -706,7 +735,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -723,7 +752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -732,7 +761,7 @@
        "['forky', 'knifey', 'spoony']"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -751,7 +780,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -760,13 +789,13 @@
        "3"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "num_classes = generator_train.num_class\n",
+    "num_classes = generator_train.num_classes\n",
     "num_classes"
    ]
   },
@@ -779,16 +808,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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9TojWc7Q4AkW20rtfPT4YDB8WQwB8ZonTG0GYJF9bzByApdfrEScJFt9MCpjP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\njx495smzE0bDEUmS0u32SVttBgPH8fEzwDeT398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p4UZU3bGCNAM6qtHHoLmfDj0bfAvD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lDXQimfs7A9HmlKRr2c/aMHpMMxx6cnnB4fk3h459EjZodHZIMJpfT47Pic849/m3f6S4ajEZ5N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\nGudAm4TpbE6SpOR5wXq9wRhDY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h0gk8e4YjmpFYGwMOEclvMCJd1hsT/F798v9DLLublr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\nkhDypiTjk+zRNjZ0MFTBYdhKpA8RW/oitYwHTFLSLCFJC+rJHQeHB1xcX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SHjjKif3UaLX+/7mz/9msTjF6WgGWhQmilLKh2tBhqG4kfcEPRQpaImxVJOGOcJTMe8Y+cY4lY9aSHj1kmFsjSnDBRDmfjdYaImM6TG29x/zc8/nM1M+1payHCS8nxjaB3SPHif1pjjD/E9bzlSG9IoFIdkCCq6Eow81ey2uESHmryqKhddHyQdJ1C6XmlpiOJ7yeG9msBQGYwBCkK8B+R+4s5WLaq1GIlKevfCSEBXRVcTx5Z6pBBBdR0AExQxPzeImrl0UFvSlZAmZYZtq1v+eJ7CqazRMgao01Qxp6uJLJQNctHhtBkvlWxj2fJknmts2h1CXbHbmdNZsdj45TilIs+XDeQoGrBNzMAFYWnPGlLsdzfwT1VHDWApsNLkyckYUNIps9W8//MJRQiGHJkA7wei/dtDxXwpZ+rN3BkZLnNSqCRLKBh6zNQdx/mOfVMlA8OKzeYbDUt6KKGXitWG2fjAv/J5TjGeIRz4fKiYPS78aR6FTT2uI9iERbn22Lrqg8sVCknf5ggEZlg1jDS1mymvQMs83QwhPsdapkVtI9mO6W7rl3kDzxQEExOueJ/DeVtzeaGYVoN6Uv+KBECUBk3F0kcFRvm0QGafwsDSBAS+8984fpTbbWgteXe24WCslpqDXIpFUzS89EEatxQE0WA9tpW5AgvHVAfaXUdHqGk9Sr+EtCQZqBWBq9AfF5PZAvbDm5bwjoiMiwKENvIWRH8ow1vHtg6ViIREeaKIooWYHSoFXcWtLeCk5NGGrALWTc3CkqYWwTUukep5NVSWRE0uGWjziFUZ4pCYRp6gZLx8xpqRAjccYnOzXPUoY9/d21tsP6oG6+3oYsZp5hry7YRFdSbptaYFU661w7RwnCHfekdPTwybc9CVf3OQBT3XzfM0p5QAkqSLjg8dvaPQsLhr2H+5OkzZeHJwmrjHs4FMoN6KFyGsG1CqC/RxZcJ34e2cVOnBV9mtnroXff5m03ki3tpkMtC5eM7ePx9NkLQ5uVDB2e6bLPCokhXMqFmPvSVsdWIfbGzOiQsLsvFF/gKYfP+1lKbw/BrWYFSo/YPs5Kdcwvvg4d0M9xp14lLLP5va3y62d5qUTqhOy2bcaQxHu3SKLk1ewZZ/jZLbxCqZV8uCU9srWES1Uz0WEL8N43fuvJ9a97JUvu1aJM+7XwqFuMHwtIWbFF7XyyLXt+c7edrrFUy3QgdrPpsKlcWAW5tg97YSuzspHVZ8F3e8iydoDxzR71Bq6rt+6b52Il97J5ff1I94AlFnKv6BMl9wTXcl96622vv8h+efjX5Iq7RnZ840GmPnyRSzZ4cJdnP6P959349KogYPP+bjChZ+W7ExNJDxa8sGONuGc/jk6j6YZvIxNfHat4zf/gc+AZRXS/P5ZCRgMBu/Rijk83eM8vx8snqFeAbB/KXj1Qa6c2JP3ZWbCnXpHSM9LIR380mw3rXkf+UeGkZCZ5gyFthQRxgHtKv6hGM4k8NMMwJFGUVUl+ZMyesX8/zpV/fE8gNevh0SrjKG/rybCS2eWtRe84XuJ1voakTw+fJM7UQzdSIXeAvmeqn2Y8VyUdybyy+b7L+Mkz+LFE+0F5oUuQjIpskav5SozeGp3Y67XyrDM1whi2PEsZkS3/WV8LrWmLh77KuGN8YUyfGDX6NZ7Ku+PFawVb6gAPzDJEqgGZ+RJLftJ6JmYoIBp4YIJHi1L0tlScrPWBCa5nKychqkg6QRaPlL05DBn3mzfEO0YlCehuGkCKZlWXZ61k9zZ/aFWWcv3sbdZ7KHb5SHKd4nLRkj4A3QIvtAIl0O2S4UXIqLXKQnC2qEXtuCxAqwYaeK2KpKIMSkynZVRzRhQvhnuNzGFPrEkkY0hAHykLRtwjhtUbkeXwQry9EVCKEaG4enopahgWj028O/4vEdK/ZBl7MjZaM7SMeGZknX4m1+7TImAtOIXd01vKbJVMrBmtRfMGKdEYIzzy6EQjIsHqyM/oVSoRZHSMcTVaaxWaLJ/bZa6q2VGpN/7wbKokmRgNnZA8g0+OAJ6nDEVBCpb8MqsBrFq6re4W3EMrVG8L7hPKcWBJk+c2WJYCkXNQzCqIoOziIfaKyEDzLMBO8NyzTVBYqI4NrZvVvdXYjJrYhGAWB3bBv7DISJkCNcD8JQHwQg+KpDJsc4YkgFsoR1nxo3iYe2LEYl9zb80b0muBW4bFmlUBHnie+kgYv4pTUsbRWSaMa0nsxxaMqXsr2yJ+2+DT/fYt5Rc010jsiJUlERcjUuRZeNKPaolAGZY2ama+eFW19cYLnqWXilkN7F+3+HsqNsusfnRviLPpDbxivgtP0GucNmtrchMBHYjIr3eqedpYJRJua8/MJYJUxRDMg34X95tt4qisfRM6Zvhpcn5eAiWc63B3rT59ELMnmopi0tstSbSZy0OQsVZYetaNFRW8xYFaodReE7m2burZJvdgNppbHEiJP2W3UYYiZBY0Pja4iN1LHaK3Ii3LIB2yHXyyw2kvFDPcSsAXb3+Vcdiu4Ag2wuMuRRccsCfBOjTScUAVRTJjj6ypjeAVbnAqViI+pBwkvDszYRzHJ4dlm0gJJRqUrM4z7TQgY/N3ZPDUXqoyJBNdPSNvYbw6hSa8sQhJQ8ZrSOoJW/W0R8f/PT01JRNT/Vkgz6NulFmPCm3FkclzHEnVkd7Rvt/LFo7r5xUvGFFeG8yU/jNfPNCu8D9lPdMzXL2u2iq7oZfMdOC8ENUmU3oItnCXNGP7tfvTmqhwc2pr4VVK73EXXDcdViwwodEIZfukOwnSd8euAl/Id2cCoGeiEKH1rhkoJtHcVbXXWW4A2JepC4G0Bxke9xCj72NwygqtTYvXH8TZyEhqWmxhJdF3wLu1hqtSFnw3ZEwhgfdQrqHoJMKnNHhR/14WGfcz1Z+9BU8Cao+40eUaQcTYHJilicgLXLIqs2i+G47GU9y9N+/NvSa9NOlzZnqSVNIYhgPSWsi6FKdoocGqKDsmmMJbaHNmEcFpOFSw4oTxPORt52sO4cSI0qxF5tiTrN/pP6kTn3OOn5lAiTB3rnMAqb4mUNZuM5KKOYH25B01a08GwzirYu0x/qr1P5Ic6RWK49I9hW4BtpkxzXA4Q7m8FyUJnxZhV7SHAsvOx0V9AexLz37JR1mVF7TMjLnWJ5U7nSe4tERLR79Z9gpkzS77xm/ofNNunrftwfraVkAgUVmiCqL5cBsIoYQX0vXyxD9dQnRpjmcPXAZES/DNWA9U/5yXKWJZKGZWk54iycj0tYChR2HuRN/CJQG69d77fCIWWlrMOpEnn7cowKevLh5kHFlFJJuy6JDvWFXUkyoYjNpq8lZL/k7qBPH1t55xjp9Nul7CJhlX7W6JIaUSNO9k29gwDaiRDT7aPdkMp3oq3CnuScCVDFsVMUHS1Y4KVcvwKWtYdUAIV7o1w3wmOuBAjAUNoZKZ46EY8wzNCiaF4i1xKcPEoqRoPc8vbrnN2aRhCBlbw5OEDYHDmIQitBodTEQF05D1OiJA1jkVvUOQG2qxzx0wV0p4FjkNTSigeei6x58Z67D2LUdIbjpcw5KVFoWixlyFaoprtK3X9DI7eTs4qS9PyALR4b3VKIuTxPm6V69Z6ujxvtpm3CulE/GXRBfpfGQF2uKOgasthjA6nY9oov7Loe/t/CVKc2MIWVkKKtzaolh7tBh4dJCpB4G5CVXW9oC9wMM1chdbFsN/bD1PGXqmL5KWoqq01i2+LBnkPme1a/Ytb4kUhCffz9OzwJyAovoYR2LDjWwK2YJRnkC8Q1SrSFRJmFWmqbHbrdP7rA+07t6lR7F+1EeH4M0HhIr6HAq49CMmn4w1/LhWpkJUKDomDhc/0e75m+FzxWs0VQgMaQNnpFEMgUUT0JaVRioSiq5jT+lRuHnixkYpG4wo+06GVxGzd4eFWB8JkgDMM3mS+KCIB/xhAoyINIrX5dlxyJD5H2CL/8FXYvhCJLaW7DqIC+18DiVZCnObYvaMg5ekOwXgECWakB1qOqndovsNSbrf4rsp4xgoFaV65j0qHAKnFqfOU5x9WjTykNVoLRFka2jqotYIj9JnoNESu4SNw/UJ6z+hhdf6AEWqXJYRgOEl9jkoedOJM6ypciLc7fSavGwnX5t5NNGlV7L060XbJ8sGrtI7bdDv5YzKGH9St/jS+VC+sRAOjKi26Jziu7BGnDEU9T1bnOKlrfSt6Nn0JQG1yDhKKDsQLl0LiSzQSY8AzJ3Sh7kbDKVEJtCyn2CqJbOWHmQaMQtKjJSyPiPAXI9EKdgu3utrCRcJlvcowF1RrfEeC66jecV6Oy+Ml8oY8GXve9WHIOl01Mcj9e4dMk/YYaS8ugyD1pJu1uULGf0a4gO90EKz9Zab4SU+TDLKizkpqYi73PoQMCcw/fkMgzIMYyQ8gc1/4v6zwgjx6H8qBWsFtGUn7obosIwX/tT17AoUxxdFtewIPVxey2O2BFkRoZQxPYs1Nt626xdZSb4/+Dz3DV60uuc9U9mxrbUUbF1b8DUaNOwoJUL8cTCKTgG0y5Ag+waIfYFug3z8nfdXO+E6vKuGQ8k2bj3JkjNv4lcdsJzN26/QxztCupNJs/AcEBVY0UKw3SjCPrRL9D8skx6+qQzL8zYUQ6Xi3ism6rNCpx/n8sVJEA0ainthPjemxwnmitYz8u4d/rvfw+MjKhkxbLH9NHRFB0oJAyPa5xwnS0BkySQvfUSXs5vPxVKm6zgVEVuMax9hCizXcIKqVUqhqDCWMMqGZtluKkv+qMrQUyvHd63ZosC692XJL1xVni+lXd0y1Dqn++ypyDaArJDt5Hu2L0NrVqB9KQmDHAjlCxrx5F63lkG6HXSQliF4NAINTuM+eVU9o/xCM42wwfoESxnH4emZ44afJnxqS0VUb7XfH9ha53y4bckwuq+1oh1LeiKj7qXIU1l37xRL/phkCC62/lpf4qBZ3mdjdsGZ0wssEVZrj1RepsEDWBJeubdzdaZjg2yPZmIM6ujpiH7/Dnn7FqYz6LB4lrXOWXanSx/LRdDSceN+DtfP7k5NvCXrkyXxQO9E+yyjXGbsbJ2s7HWAgEUOQXQOjnAAooRiBuTTZfxs0nUZLyllZBx3tDbRqjOMe5pZuKwV/HyPmVF2B6SMNBFsjsHdZhVpjqlQzQKXcmWyGpPWLNs5tYaJUpx0wWuOjizZ1KGCKON44PLymvn4gNkp5vaq0ttz4fnw9/mqhLBiQlpNbClT8Jk46Q1GX2SsLIoOOwax6DXpHrhNGcENqTPt/oy9f0udj9TdyPj6NW1XsBr4krXsRFTCWBUp0X+6TUgpAdK36IbSRNGSZtMC7zNruDSKjqFYzZGi7MYDQLZ4h1ULdi6qZ1gcz0ytE+I1p/2BeUAt0JMFzwCUfkRLRBlEMR2gKbU6bRKYK2KBnSNDeP9WGWtjOE4wVabTRL29yQxzZRyE2mZKC8yv2ozowOCC10qrNRo4DIH1r81/K+4x76YS2H8pguuI50gH6O0CtzBXRimiNHGqVYQo5FCPSpReA235TH2qjJ+lDMswcHP7BdjEUAam6RGVqzgoFNTg+9/+Fvv9e6w+IIcrrn/yE/zqFcyN4o3a0vrryMXFJReHA3VSXJxhGLCckue1ghRUd9QquFes5fgAGtfXB958+RXzrPz2t99yerjnsIddKZtC7q0liUoVWcD3HFifUKvRENeoa/EZs/+kJuD/xa9SBm5vX+PthOrIXM8M5si4p1a4/+576rFRzBms0T5M+GlmfH2D3t4yXlwwzwCVIgPj/sDlxYE2H6Mb8rjDiZ7GrjtAEd3RZE4GgiTHTWnzxOFiz+31FyAHWj0zn+4jEaO6RA7uHZdOGoVrRiHpaXjPghu9oD++Hl6iLqSUgZvbN3ht3N898OHunmLg9UyzGSE4gnM9oXNDqmG1sSsFef8QGf7Xr9hxgHFgGAr7/UUUnlij7A4xU1kV9QHc0KFkokOya1SU7O0vLtjtL0BHWhNqrXibonVbErEjQeZZUZQepwSjpGWD5hhwZUvBRRAmK/jZAAAgAElEQVQPDHP9ZBk/O5ucaaHMFAlaRpo7gw7cvfvA44eJooURx+/fcTqfGN98xf7NG8r+QPHeQKFwcXHBfj9ipSFDyZpDYygD3hLjKzumKTYcQoldHJQ/+/Of8/btO373298ynY7sdiOvbi65uT7QCbd9PSkiF2WaG4/jLgYViVAtMlcdV2qutDosVJKXtDqG04FyR5Axet7Nx5nH+4qitKJoK4zqcJ7Qt2+Raca++ILDzTVDCfldXFxxOOywWZES9AnzxlAGrIaXr3LBNJ0YdyljE2o98l//xZ+zP4z87rs7fv2b7/FW2Q1wfX3NOKTnjz3Bmh1AR8a5cSxj1q9Lkn9r0mk8Bkb5yjx4UUsE0R2znXl8ODGfjpFMnI8ZcoZyERfqXJkt6CzzMMB55vCbb9lfHxjfvAGD/f7A9fUlbR4CLhlGJL15b7t4psrAPM+oKrWeAeOv/uqfcPXqmr/77Xf87ts7TuczmDOqcH11lZAWsMHve8jtKpFg6+R8yFLainvv0B7UvI95rf+h9Xz3RyKM9RYKp3l4a9Oxcf/uHvWGq9CyE62cH+F3v+H87h36+kt2X39BG5WiQcNpdSZmkQj0jLHV2MzBMIsOOBDZ69ombl9d8e3v/o7zeWYclHEkroGzG/dLSVbPQm1bFXVW/W7nSyXE3DzanGcXD3RHq0MMJXphq+d0zSwJ7tAQzo9nHj8co+lun3erwuyOmDFWR+7umN7eM7+55frP/4Qy7CKcanOyCkqGOkF6F89uyl6Jtv+RdTyeHvnJT265urrib/7mb/j993dBkXHh6vKSw36XVQ/Qp6bBmlQzNIF8zZGWSvPorhLFAYll1nXm9staTq3G3fsHHj7cw3zE2xzUo05md5BSOJ7OnI6PwQQQgVb5RkB+8WvwwuHrrwMzzP4BK6F47XTUGyoASyecn/2jr3j16oJf/OIXfPf7e5oVeiu3q6srrq8uWboYJSVqhUUcijKc52W8hBDFbmXIjDdKY2au5ZPP8bOVYcsZIkOJbE61YPrfvTvhreJ2CvKsKrODmtIchnbEHn7FdPcdN3/5F4lBeWcsBQdJIk9pksTcFq+dz2fO54n7+zuQxuubPV98+QWt3THND5mxYqmRpeMLC3On182uexn1qgLekjQ+olozSZYM/Be6LLsSqzpDKcznM+9+9wGZKj4/oDZB4rfVBDVoDxMyDDGk61f3zLsdw5/+yQpXaGcGhAJbO81XXKDWmePxxOl0pBRntyu8f/sdr64ueTiemO6PFAp3d3dc7JWLw+EpNWZLvxBbEnQGWRPdgAGRqIYqZaQML1ERxvrw4QP3H+7xeYY6YT5Twowg5gtj4Fwr7+4+RLbYYCfC+1K4qJVprqgODD/5BtwX+lU4FdmQxaPUtllkrntn9GFUptPE1eHA/Krx9t0Du7JDUM6nE7VeoBIprqUJW2/7t8EeO5e4JItPbUQ0Cj50GBiGP5pn6Hh9xLxR3SnqYM7b775nuj/D9AD1iLbg+Yhnb8P5TB0EWmO4f+A8DOz+9Occbm4Tt7MsCwpQNd5qtBmaC19+9SX39w/86le/pBTh7aGwG6OR5CCCSeHisKfkRkF4K9uJbp3XZlhUxFgy34vSfKJVRYYYQ4qH1/IC4STAadMJqQaD4bLn8f6R+XhPmc9QTxg1s/PhgT2e7mmniXEYmacTh1IYfvm3lNY4/OM/Q3SPNqF5w4rn3JS6zLaZ5xPDsOdP//Tn/PVf/zWPjw+cHk5cvrnhu9//HTRjJ4rZzO3tDft9JOziYHQqDysTiATRLag4/evqzpBRiXjJ7uYvb5kZDx9O1PMZ2hGpxxhzoZtWLBbd5Sd3HutMPZ4pwM3FBcfTkcvDgb3A4y9/yfjqwFkvwRvVZso0xwgBb7Q2oSg/+9nP+It//Jf8y3/5f/Hr3/wN79/u+Mmb17x/d8eHhyOIcDwfoc18cXuzYH5KlPouDK8ldA7inbZgD1DCyE6Ts9spMjjI82CQ52OG3f3VgrlwPjUePzyi8xmZ7xGLubpGyYNyZnp4ZDfuOE9HLsYR/c23TPdHDn/1l+y/vMTaMbJCs0BzTkaEruPIV19+wcXFjn//N79gv49pWu/evme/22Ee3uNhv6MPnHra8mdDyO0zFTIEsMRBJBXieZ7x6qgrQ+mthZ61Oz+O5b3zd6PInunUePhwps4ntB0RC1qURNNAUOHxfObx7o5xGDk9PvLF5SUKHP/dLzA789O/+ovocNQqmDC3mWOrTPOEmXBx2PPzn3/NNJ35/u13fPjwgdPDHX/+53/Kbr/j/u4d4sLV5S6qShISibUmQTwjqTg4nehbkSKUEt7nPId8hyIvky0AWDOOd3fY6UOM1RTP2SUJLyTNzUXYHQ7c3t5Szydanbg47Pj66y/Z7y8YDzvKvlDribfvT0znidqMQQcuDgegcvf+HYfDAfPGr/72V/zu2285nR55+HBHaxNXl1fI8Ug9H7k87NnvXrEfSnKWczzplmu4/EcywrPsfxrDqY7HKWvRh3hG/1jZ5MALg75QdOR0nPnw/his8fkDpR4Dqs4wVFSYW+Pth3sGKdh8wi72eJ25nE78/v8x6l/+DNkpc2vU5uCFy5tbbm+uef/9d/zql3/NPE+ICF999TqSIc04nyvjKAxjTLrrHuF2StqaXVx2cKlfJfmQZhrEYY3sspnTpHfSeJmHJWq0QWXg7v0H6nkCm6nzAwNGQRHr1SbCaZ757t17igj7YeDxdGQYCm+uXnP+/Vv+/t//kt2bG6Y6U81xUfYXl7jv+PD+9zw+wHff/pZaG5cXe8ainM+VX/7t33N5GLk47LnY75HirNSY8BiWNki5kquQib6UsQtaBGlhHKOE1NZ5uy9sWTPa8T0y3SNqmWMoSwnbwg8U4fb2FjXjQ628fnXNm9trht3I7LZ0F/2zP/sTHlvl7u6e++OJ+fHM/f09iHF1dcXV5SX4TK2Vi8MFQylYm/j1b75jHN+zGyKyG7VXmVXMZ7bzUYAnBOo16ks4pAlDGShD4pKzMYy28pc/YT3TM8waUhQz5f7+yHw6Iu2Ine9CEYoGbSLL8BrO+w93uDV2Y2Ecldv9DRe3NxRzpseJ3as3DK4MDCjCw/0d77/7ewZpXN9c47uRuc6oB5eI0uth1y4pC0Qr0LuZrGWBfUYK4D2wytGEyV1HKhBVC9HZ+eUut6AknM/G/HjE5w9QAws2ogFrSc9BgHG34/r6mvn0iNG4fHXFF1++QXcjZTdy8eqWi6+/oh4njtNMM+fD3XtOj3dcHeDq4iooF7VFQuNinwkTZxhyhm9Zyzd770TocNBK0O6yF/cFt4JCkGpahE4aMtZPZ138qJabUeyEUum1BdLJ7u4MWmjZ+qyUwpdffsnt9SWtzoyHIUyRCXNt1Fr53d9/y3B1wcOHe75/945iyqvrKw77OO/DoCiR6LAG4yAIQyhhFQbtrbksCx9glcxTz67XRi9VcP2g5u+UIpgVQKlzDpn/Y3iGvbpAdMfjw4nHh2NYmPkBYaLXhEpZqz8ur1/x1TdfcfzwDkX44s0XvLq9oSU6cfPqln/y3/y3fPjwwN/+7W/463/7r9lReX1zwcXlJWUcAz9cxhWuTUShtyOPprmy8RAXa2K2cJVSRdJrmtdOKhHxWc2u2QnAv0Svwd2hGsbA+7sPnB/v4PQ9xYKH6Xj2ZuhVAcIXX7yhNOd0L1xeXfH69Q2tRGca5srry2u++fmf8Ktf/S3Ht+94+91vOezgy5sDh4sD47jHmjH1ygGEsYTnqdlBpbkz0IeHbXvVZEOQwDzyNVlGPHhv8+WaRf0NI8YSRPXoy5Mx3nA7R/YWRZPDpyU5ty2b4iKLl7i7OGBtwCX7j9bG+XhEDgO/+OWvkGHAzhOvXl1z8/qWoShSooplkN7cVSgDFJckRZPzT4Q+gEN7d6kODALbvpPxyPXSWt3ogkiUhIyDQxrVT/WP4xmGNi7UJnz4cMd0/y3l+D3BsxnT0wrWeFFo5lxeHPjZz/8Rpw+voFUub66pGLhQp8rV/pp92fGv/u2/4td/8+/YFefLN68ZdyXLaTo+lGGv5KZlK6HYG6c1R7UFcEufdVGWO4c+TDqbQQjUlt2aLfhRZidcIhFjORPipS13o4lwPBnnhzs4/x5p5/C9M/GgTg7Vir0cxoE3P/2adn4VpXq7bCnfjGbOr//+t/z6/J63v/uWVk/cXB+4uX3FMBS0KKvtVqJnJSC9zXyGvZbFc9nZaG3RwWLQVoWYVxOoZjSv8b0K1s54NgOx9jJlDEZJGCvKFaPFWa/MaRIQhKR3Hq28oqX/1OaAs1qlns9RaHS65PLiiptXl+wv95ShoiXlp4Jr0NhUGuJz3IJCoQ+Zyn9ioA2oZ1le9/hTA7iv0YEFDKI4tQWsY+YMRXGbaFg0e2jzE2X6/7We6RlGDePxeGR+uEOnB7DQvD2BIbrWDQuCuTHudly8eYPVGg07W6NNjVYnZq/87//H/8a//zf/mturC17f3lKGPi8luYV19QxFA7PsafveNkzEU6G1xaYsYbSvHLRI+8viYQa+6kjpk1mijX13xV/acnceTjMP797D8Q5tczx4mqEUKyaXAWnWliq7wyEHRkVPy/o446LcHx94ePw9oxuvb19xdXVBKSX5+zFYvLUs5C9xgMwsS7FYDkA08nTsMC5NHGzDM4x7keS9pUexGMx+nfBShtKLuF6ejGNDsp0aoXRK1vo6nvXmIZOelIxIyrmfJk7ThJwn5OHI5eWei2ZcXYyM+8IwCH1npbd3s+hh3nsZqGZfxNa7UJEFDuGFzjTMdksTX9syqDx5wz1w21DpFkI2oYiL9vZzf4wECvD4cOLD2w/46Y5hegTPOL8/uD2Bs6T4oga0JkeoWh/QDnWa+b//z3/JfFN488Urrq+v0GGditUFFw0dYiPLEGFSrypZZyM4MzG5rx+UBXVIpRneZIjfspdasyCL9k4pc4vyo/3uZVYnuMP93T3T3VvG6RGxSu8wHF5CN3ZCDD+0VFI9dBamNmPzDLVxvnvP1I68+vOvuHp9xX63NgXetnDrZFxzj9AN2SjBLmOQ3vhB15/1tW0L76kM3aF5jjWVqHKa5hkVZRz7qPGXtjxJeboQlvv57Zvnts5MXmSD83CaeHf3nvbwwJ/c3HKpO3bN2Y2CjoJ2r84AbQuKYS7ZYb4rQFlk7IRRBBbuaIS6cS/tI2WmEl2s3FcF2J2lkl2PplpRUXbjCJ8o42cpQzPnfP+Inz9g5wfEY9RjZ3spfe5pPqjNs2OJU3M4z3meOJ/P+DTjHx64nHd8/c2fsL+8QIZeJdKpMev3fWN6Ef7Hcy86btQtQ7y0utlLhjmlIxLufymFaW7UuaFDWUKzl7rcDPtwh0xHrE3L7Ok+x6JIttaSVDYW2cnAX+MBfjieOT0+Mn145A0DV1W4HPeUIR7M/gD34fTQH+p1gJAvMFCEUllSTJ+94U8aaXhH1vMavsEP4z21zgiNMmhy2DIMe4Gy7mEpznJeLT2sZJ5hDrXWRRHNdeZ4OvLtt99xf3/P9cUFJ4P93Ci9h6CXdN8d692MtEdlq4whfmYe5O5SygJ7QYTA4dX3tl7bBEpv4RAOUy+4EHfmuaJiUeKp8SH97H/Kel6YbMbx7j0yPaBeY1SfxXhQFdBsqtorDcw8GyxGB9xqxuPpzIf7e87v7/j5zS1j2TFPlV332jpW4P2BluWPjt54Tp+1sh1dqFoo6gx9SBX09hVrqEQmUkQowxCjTkUYiiZTvSvwcNVf4rLWaPfvEeramr8bHvq4HtJr2LRbI3oS1tb4cH/P99+/5eBKeX3J7E6dK4MfWH3IWN4hlm64UkFqwhrb/ndh/BwtvcTKnz7pnS2Q3c9LUQxj0AJuWS+d4VMzZuk48gtcfbZJGg8j4Xj3pbN439tpmpjqzLfff8/p8ZHXl9egwv0UoyEu9iPNGtpa1JNlljjOcQTfZcMV7DNolC181c9zjmgohZL151t0eFGAEYjH8+HGWIIfWUpcO+Y32jIc7FPW85Rhq/j5AbWZkp6VS7ZD9Sjm6eOoDKGSc1i9RbZwnvn+7Xt+//vvuDnsOVbQybmQ6DYzFE2trunoSX7vjKMkzhTlNxAPez8Bfc6KlC2VZgEvw1tYsvSyYCHuhteGlwFrnoOiBHup7qFVhLSwgVEEBiMSSS8PKEQ8mh9UoFrDvVLNef/+nt/99u9prbG/vOHDaeJiFF4NhTII46AM47h8nGrwPIcBWCIL0BwN0OdHRRPRzBKXIbOTxg/KJtP4Qf89i9nNZsi4i7kcrWEo8xrEvLC1GdVqGS0FFB9myjNMlegVaGKcgJMe2F0oN/sdZRjxV1cMNyOH2yuGIRq8DkUywiqZxOwGKAznbreD9AIH7bJemz5HYq4s4wiANHzr2JCOW3csOPoZpIylxL1nhH5e3/QfXc9MoBgidWGs9yFQrVlwzvLh60oSCTC8zsbcZt69f8+777/nerdHEe6mI7Jzvrk8IIVo9d43RaKDjbqw7UwSmKqxjhTt27N6KiJrKLy8I3EqsgGBd56haOBPPUxLcLa1+dNNyo9siSTqDcQ86Rj+JESvQEkia5+bLaq06kzTzLt37xgZ+PrmNbM3HoaZi9c37K8OkZjSqP4JLy9k2zOFKy+0b32MEIpC/84myDBuGTSVibU8dGHkwmNcQ+H4vY49qgRm/HJlnJMBe69AOs7fsT2j1kqw9Qy0MFzf8Hr/Bad3bzlPJ65vrrj45g2X1wPjfhehbsq3Z3/pFLYlNblmA/qokHibL/e15Y32My+WiZ5+hgXwIOOQzWF7ILnIOOczxWiSP0ICJRootswg9xAlR4biWY/Y3x1cpB5i1Vp5+/YduzLy1avX7IbC/c7Y/+w1u8t9ZJYkMlDbe2/WluSJWaOUjhMaG+w8XrPAKDsW9bSLct/iEEfHnsKC9XGHnkqyLMPHX+bqmE3H9TTGX0vHc/r7lJZKScvI43TPcT5zc7jgsDtwcSHsvrri5uvXcUiMkLG05ffjmiHfANh7B6EEXHpWEyCNpbXAqred0JfZ3YurJ1kgEAYu3p+zW9h2MXp5MnYCDorCg16CQDoTxnk6B/yBUMQ46wCHWy6v9uwOV2g7sX91YH+9ZyzRd7T5kNnjFs+KslBrejRmhINDC48/KIXpnabYWsq2tZaRH6zD7cNwal7NJQxrcJ+HlW7nq5fZJ+19ynp2bbLS5yd0RdjhhWiM2nI61lwbrVaKhAc2WeNkM9e7i2V+xk//q59w9eVV/lHBY4sh5AINtMQQmpwznV1pIosZ1iCEqSK05jlnt2cSu8XYWBQWWIkYMLXNWsf74jrGMAwvNISKbN2yWx6yWYB2VsRvms9RzUBwA62AXu2YUO618frmFW9++hXjULA4A6gFZucW1ypagkNoNeGqPqnN8rNsSZK11rLTTVTB9FRl9yRDxL6RcaYKZD1QIpl5lPBkXupqqYBUYmZxVCo6p9OJqUa36yF7Wtr1FeVwRSkj+4sDu1HY7ZRRKtqOaNlHl3oRnAkHCtFCTVyWGSeWSZMhR7cu1CfJsb4C0LPY63iRdZicLPh/vLNDYkYfD9E9yFYjWz48o0Xb87vWtMjoKjlIpntaebuuSm3O6Twh3nCJWt9ZndtvvsTmmQeM8Xrg+vUlhyFafluynMxzzF+G4IjQPJNUIuEW5x+sJTYxmDrRLPzJAPloVdNh1wyViPvtSpNw2dMTZxhKkLJhrdV8UcuxFhw/6ftkKzCdvjO1VaYpSMtFnOoNGwpvfvo1uHAxjFx8ec142DOqQim0VGqSMo5Z10CUm69KtxlLoneJuWJ1FZi0gpzj2+1WFmW6Lc+j4dEbs7MOPGbyGOt42xe3Nli/JYVmrs40TxzPp2idn9GS7C7RwyukDIy7ER0GCjVwvKTnxHztHegSdIOMIQvNhr0S5XbujSjn7TStPMM9u91NoNPrK3qF5eZRWKc3xvzrbBEma9iv2e+yiH6yjJ/pGQqYhFclGi1/FuUSHl0z4+F8ps2V4pUmwlmcpsLrr24z5a28enPDeNiDCq4lqhukt+oJZSgiWCrKtvHiOt0DiTDNPYa/CAMuZQFoxbUbm8VLMA2F6yLxPhEoA2XxGDalXM/anB/JShdPuqJwVqWYVnu2xsN0hjnItZM6tj9wuPqGQRv7URgHGMfM9g0FGfaQA9xNBtCkMREVLw0NhZp8QiUmn60y7rNswuNw1vZsAL05bJe3E3MyAqDK+yDwsODWOYOuv/7SllKYaqO2Rm3G3IzH8yNTPVGkMKSDMO6/5LC/QHUADe9PsoO0uEMxXII1gowpg4prichuKQBPHFegCbiHDHtdsuUIWumzUPpZhiUBstQjJxjSIBoQ9xBZDSgLVNajw09dzyZdF+1J67gpJFzfVkM7H89nHo5HigiDOM0drm44XH9DkZldMXaDMu5jxnEENQXzLNQuGSZns9ecD75w07YhkXt3jQM/6phTLwtEdFVozkbRygLG11oRdAnBcdAiUORFHhSRgCd6I82+v61FP8BqxsPxyHGaGQUGr0xlZH/9VTTcwNgNDW8fQLOvZXadXrooJ/XFnmxwPvAdHyf72C1Ybgg98PA/JJiPr7XK2NzAss45/551Qt7LXHM1prlynmfm2ji3ylxnrFaaTdgwsrt5TdntUe3nI/D7UgZER8zO1GrU2ijqS5bXrJdSRnu17djOfna3hPvt6gUWWz7iVrRLk440fME26M1euwGPkHxN0n3aerYyFO3Tx2RxZafWONfoeH3/+MhcZ7w1xkHxcc/N7Vfsrt4waKX4GbEzqNMsvDtJZRh/bMl6RXJIU8d9Il0fQ8NtAXshsESRgm83nMQ305KsxmkdA7BmAno1BU9rnp+7OT+SFfiOULvX35xznZnNmFrj8XTiPFfONA6DwOEa2V8H1FFirgmWmeNIuyEyghaqTQyq9E4y3WtXaTnruLPeVlkC2WOSzesrjrSKspfsbxSdW9JHNJ+XBPVXVPTFLXc4zTVkOM2cp4nJW8wSEY0u52Vkd/MFlCFb+lesWmBwOuDeqHZmFA9KWqugIftmFvPtvHvvXbn1sPjp653iVtJ7tyXR1RWmLApwTYZ0QnXyJa2hlEzK6DIwbMnzfsJ6dj/DGOcIqEaWtxqnaeY0V07zTLUAvmudMQrj1Q3HWpmPd4wCSkX7JLTZKarobrfMwijjGHMrcGCKbrtTpbVo5xSb1jc0HurIePqSmQyyZlAoOi0jvXRKcVwG5nlimmtO45PFGg3DgLsxDMq21OslLc8u4ebR+89q43yunNscMnYDojmrlwv240UM/mozTZxJG+qVuTSsTQxlZNwHd7DOR8Zxvw6XN0MkOqJHs40ExEnu78JFWwd7iSpDyhi6l9Gx4sCJKMo0TZynKZMpPVzL6Xs4Q1VeYjbZiHb+0zxz7ue2RgOLshs5vPqCcnHJuYH4hB0/UKeYg9LKSJMjp1LxemSnBrXxWIRxf8FYBub6yDhOlOGQ3viEYNS50lpdZbcEYAF1Db2xQ1a2jWPMu+7ltUgn6cTvuRZqrRxPp/y5bGQcz8oyCuQT1jOpNbGRzQNfa+a0Wplq5VijgNstx/aVgg8jMu5prVLqEevVBUNSGzSGVZccFNRaRVpieRb0C6UtLbzMQum1RQHGXYWFCKtfkrn+seXo7rVmmNZa4zzN4Q2WmM1gbkxzuBkq8mKVYfPAgJoHoXqaK1OrPJzPTPMMGIMQU9AO16ADNp9pRFKruSM5QCjAbSiZeGs1hkAtiS5rwERrlVo71tM2RRCdexYshV6ZUoaMJHqyDDK1w2Ioa4sD37mQbmHMe+ikRdca2Be2anOqw1RjHrlXx0vhcPslt1/9hNM8kzmNHADWcIlO81YEqTUTjJrzi4KuU70xzxWYMY/3u00INZuuVErV5JoGs4CERiYNfnFkh4/hmJDKMh0al1CGmgOS4xyHwQvF28s6I7opRT5Zxs/uZ9hwztawDF/PVpncOM4Vs5k2nZi8cPH6Nbq/CNfZGoMUBnGGEn+clAFKAamZkRqRNufDHsmZqHqo0XrJw7oHLpE8tdCbgfNp/imyLdcxtgTt8CAiDHdVVBot62sTqMrsqSAvlHYRIYcwE00Tqhnn1jjVmcdaYZ6wOmGHKw5vvkSHXWTerTLKyAABiouF1ZddKCsXREtiPYrKgNMy6xe8m07RIr2F/n0HwUUiDFoxwWA1dLuvaFRR9FAJkJpT23oiiDB63YP4AWj1Apa5c64WLeysImZcvXrDxZdfs7t9HSM+5w9E3bDgZuiwRmHa5UJm/TOZ2SGPBf8Vy6x9AYIW1TPOkq+Zy1Ke5zgUjRpnGUCGSNJoTM1bWQOxVsxQsyoq7skyPPZUiJ8q42dihpLeQmjf2oxTizIsrw2rRqWwf/0V4+0XWH2kiC31wkha4zoHyZaoMTW6lQ9wXLOvHT0JIpEZXOcYh1utUhKQJ2IqoFPgA0Lqgtn86yt+iEe3He8hlkgWXmze9wJXtegy5AjTNNPcOFfD6xy0m901hy9/wnhxSZ0fQY0y7J7I2NqMqeCUYAxssvMdrev8MfOsZklZS46MDQw3+aCbQ9YHF0m/Dixh16rkoGtGSe9lkbH3oPplLjdnqjOtBf1tGAeuf/ITdte3NClBfC4D9OFpOV88SNSkE6KBFSbCG3mLZGmwNuOAjM4svMhe3R7tubKZr5SPcL1EfpcssjxNuuSrjqRyjTO8FPVJB0w2z8wnrGc2d4W5RSZqzj6Dkzl1OqM+42Xg5st/RLl+RRNBmZISwVJ6FYTZHNzkEG2Tw/r0TFPC3KEILTOAxqIM3RslK0eWkiJbS3l6txvR7NDWsdieoNqAsKGAWQ5WvNyJv8/ZnR/HcmA249wqtTWmqVIBWmNsjr66ZffmG2TcU3Nmtvc2brLKuJlRrHcjzr52Hg9wM1tGKMeMigmWX1kAACAASURBVFRYbunhO96zljl20l2yY3k+4JI8uCdwSAjyKUaU8neJbJ+wGElfsuUvazlO80xEmlOuL9HLa6a0OUvSQTpe+xR3i7ZtMWxLdVU60rF3sizWWDz5nvA0i4IGEaFZjKJdiyLCMKrLcrZ94w4+afvGD/9vS8VRnt2MMj5Vxs9r4eXOcZo41xkHmlvgAxZdInbXV5RXt5g6xaNEC6sMmz/GzBIYJ7w51fQIskNK/CD1fjaB7PGwrF6dSxKlFz8j3u8iS6872WSkFrpRsurTnYSlOajkGUvr5i8zTDZ3TtPEbBYeYnPmZgxWGYaB4fUb2hChbxGn6ADeEM0ElmcVUgJBvUbdYGkP1WUSvQsjfG610uubfJV+Euq3B66T7EmRPZVTJ9evz/9mlja99llZIuUXaPHCAXCohpQ9l1//lFJGvIV31Xzt8Sma3aisD4nP7K/lnKD05tFVdk88Mhectom6uvMTjmH3JCGiwiWWzvsUtgRriJO+yj++Tp6ie0brQi9pMf/0GODZna5P5yna9oswzxM4DO5MTRkvbmkYoxTc5tjghSZRY9Cze7b8yk4UizaPW+7WnizTWcJVCZJmCEQj/BKFj/oV9zLB7T0vhyO/jgPT3ezMagaalAIpTwrJX9Jyd061pbELgrW60GpFL1+hl69o1RhUU8YD1rqMGyWL5qOl2oCL0GyxZYsi6/SlLuOQTSfvr2FXf21pxEBQdZySyreD47IqX2RVvJ6lX9r7nOTniAa551N5Fz+i5e7RDr85Nz/5hv3/y967xFq3ZfddvzHnXGufs8/je9xn3euyy8YuXIiHGyiACA1ECAEkJCRAQYAQktMgUdKABo0g5AAthAikAw1LRBFuIAQSiA6PDkKOFHAjihS7gu2yY1e5btV9fY/z2HutOcegMcZca5+vquzvmLo2/vaZ0nfveeyzH2usOeYY//Ef/3HxCLFESl1zwP95cSP4psHd9YmCzXHERWHKmQdVNUQwvFMI62ryKSL/ng3IguO6Zo7vY8O7UnzmzToPpcNYLPa3dT9HliBBy+ltfl5C6Xjz69n43gWUWZvf4LVi6jJe87SnnD+inD2l6S6ykaC/5N4REjTtaPyXkPvyG957sry7QLE2xyYoPc72NDgmXaWUIQ3utGzGG//7ZkmYOt6wChXF+w/H3CPDrrm2uFKNhnUSSY6zyqjmaTK4/JoLcFRUCudvfwkbTnx+cndCAqn4wWSBZ0jKLrPlXCfHe6U7IyfXayhoG0vHvkcKlhCat1Hhumwp5ud2rEokYZLDdj5Tw31aUG96hmEE58wxSZeKb0sxbtWOP76lqpw/fcr5W2/TzHUfTbzS700IedEhILi5SRLWQt5NEjnlaMtlFV1OeRFb6epEJjlsHCMEzB8r/bCLA7F3CS2YbqS5GrNZBLmjtrMWRj2C9QfbkjlGXPna1+ReueChBPg8Tf6hqtFy5uKd98hD8WggQAcBSuktOv4BV7FODk57WFKYg7cvsjqqRd3Cv6MD6B3zY/l/B+b7Iw8vhiz4xKG6xd338brnyJu5eko5zzO1zmBKm2dOL59w8ugpZj6Q3W9mACPnshDl79pYlqTJb/DVxh1D7Da2JZ3xv3Ala/9nC4bbU6ZDmdkUmGOOxPqg62h53juJ28GHPV5LX771Dk8++IA0jIv0/yKoK2lRjOlGzdmnJK96k70K7A9bMEX3byx0J+vCLt0WPwDzC2xPD/Zmd4oSdYUIsVjsThdtie6xNYE+WK9vY7kP6VREPgb+7mv/wR/99WNm9s4f9pv4g1wPNn7z14ONv/+6lzN8WA/rYT2sN3UdZ8n0YT2sh/WwXlkPzvBhPayH9bD4/+AMReQtEfmb8e8jEfnWwffjD/NNvvK6/46I/IqI/LV7/M3Pish//kW9pzd1Pdj4zV4P9r277i3h1ZeZfQr8DICI/BxwZWb/6eFjJIhhtpLBfhjrzwJ/3Mw+ep0Hi8jv+zMe+3qw8Zu9Hux7d/3Q02QR+UkR+WUR+QXgbwNfFpFnB7//0yLy8/H1eyLyP4jIL4nI/yUi/+jv8dw/D/wo8L+JyF8QkbdF5H8Skb8lIn9dRP7+eNx/LCJ/TUR+EfirrzzHvyAivygiPyYi3+gXWkSeHH7/sH7werDxm72O1b5fFGb408BfNrO/D/jW7/K4vwL8J2b2DwP/CtAv8D8iIv/Vqw82s58Fvgv8E2b2V4D/CPgbZvYPAj/H3Yv208A/ZWb/ev+BiPxLwL8L/HNm9neBXwT+VPz6XwX+OzOr9/+4R7kebPxmr6Oz7xd1Qv66mf3SazzuTwB/r6yE5ycicmpmfwP4G6/x938c+OcBzOx/FZG/KiJn8bv/0cx2B4/9p4E/BvxJM7uKn/088BeA/xn4t4B/4zVe82H5erDxm72Ozr5fVGR4ffB1Vwvs6+TgawH+mJn9TPz70Mxuv4D3APBrwCPgp/oPzOz/AL4qIv8kMJvZ139Ir30M68HGb/Y6Ovt+4dSaAF4/F5GfEu+T+xcPfv2/A3+ufyMiP3PPp/8/gX8t/vZPAN8ys1cvYF+/AfzLwC+IyNcOfv7fAL8A/Nf3fO2HFevBxm/2Ohb7/kHxDP894H8B/jrwzYOf/zngHw/w9JeBPwM/GG/4Pus/AP4xEflbwH+Ih8k/cJnZL+Nh9H8vIj8eP/4F/LT5b+/xeR7W964HG7/Z642379G344nInwb+GTP7XY3wsP7orgcbv9nrh2Xfo6YYiMh/iQPAf+r3euzD+qO5Hmz8Zq8fpn2PPjJ8WA/rYT0seOhNflgP62E9LODBGT6sh/WwHhbw4Awf1sN6WA8LuGcB5exsa08eP4q5EqsffXWmTv9Wl6lkBw+8M8DH55r4rIWGEfMtXpleYuaDv7t8fMz+eeWphZQPBgG9+sZiAJHGfI8+UcYnBQwxhGrGB2sVEPj4k894+fL6qLThu41BSKnPs7XlWr4q2r5MWrN1Ltrym5jyJSnHWGufRCiSY/gPBzbyqXoHOvL9z1eDCuT0g85vvylMFdU+ecj/+MHGd9f29NQeP75c5sn4Xl6HZcH3iuX3sQyH+49DGX+J+4U+VOpw9Mb6MI2RwIt9FjuxfLHed99vyTJ+xF6V+I+WZLF5eR4QPv709Wx8L2f45PFj/vyf/VmGccP59gyhxtDvg39AFr940zTRWgtHJiQRmu5jQuiISmY4veBsqKT5czSNpHyGzyXx4UEi0Frl5vYm5iD4xKt1pkJ8kKFwtj1dhkyZ+MzkgzYhWmvc3Nwgy2jBhiLY+B5JJ3L9CMnCZvMISYW/+HP/2X0uzxuxHj9+xJ//t/8MOQ9st6c+C0N0mY8rMb8m4wdQrZV5ntFwZkUSag2sknMBCmk84+wkk+pnPrWsnPkISsWnE5qhNnN9ewvWByprzL2JQWIiSBbOt1skhkwZwjL9zHzAeWuV65tb+qYxKrUB4/sUJqR+REmJsrkkpcJf/Et/+Q/pSv/hrUdnW/7Nf/ZPkk82PH7vXS7ffjuGpflyJwk5ZsxpzMRR9b1sMdzL2kxOiZRGTDLbs0sGniPtFkunSNogNPpkSxFjt79lnmZEMuC+d7UxIMp2e07OMUGPvMxTIYZVqTWub259JpL4kK/aGlLegZwo9Ttglc3pBSmN/Pt/6b94retyT2qNIKn4cO+ceFXUxx3POsBpHcYTk/JiYDiwnPwpSQSJspwe0AdBqQ/56cOF+hA7XQe/qMamMfMxpIfP9erBEY5RVSM6kJhS6SeZByZtiUyPsc4uS0SYlsFOh6c8fRiX2J3hWhwcPBb28bnI8Rd9ENQrS838do8Jet2eIkJrbflZSsnHSB7aRtbsYBk6xN1D0iNcn47XR5LqD1WN6o/gMiPtZ9puz6e7HdYal++9C6yxnNvKR6keDnSSPtFOLca6GlhDYlqhHNwn9JnIyyD4wyFhdsdH9AFQOacl6KEPHeuDoYhscxlMZYv9Ux8sRjy/rtnK66578wx9VmrGTOMm7R6+j/mzZd/owQWUlN0IZJ9UljKSYpwjBxetZ1eR4kiSJRV7dQKWiByk6zEpVXojZb+Kd54wjNHHCVpMVrPYsMnnwn7Phjqu5Y6wX1tdPM/q0A7mz/VJZuDzsJFlTm6/pu7cUjjVA0cUo0URd77+Ix8bu07L8/fRX8PUYsSrv6fD5+ub0R2pxv7z+y8d3A6q7e77OMJlNBJKe3nFd3/112gp89a77y77Ue6aOdLS9fqKCCQQ8VnJ9ImIy4DRdSphuK9Ifdc9rHrgH+IF1aA1oxQ/hHsQJMvzrcGTHezpHtgogpog2sKfvP4+vlcBRcDvXQStithB1BBjHUUBM7T7aREg0wxmq2jggkTe7x4800j+3OZjpcXUh0gvJ7874dRnx0tEltmxQgyPHMzNUfAJvf48SoygX6KXFapSslYfRyiZZCDW/D3c5+K8MSucUIqoTyvdcYi4IwJdnKBjQP2UT6iGLci+SaQ/BxB/K9ZI/hIRyYfDNceQ+0rZnXI/9ARIlgDHmYuFTZlJ+L2URTx1C1gmiZAMik6kHu2axmZpf6BX9v9PywJqygnS/obnv/nrtP3kQUrfHHJoYzwSRLCmWKS2SbJH261h4g7TR7rGQUc/S+O+Wg7WhMSB2+2bUl7uLyJA8r2rYbO+nx2KoztS86dPVDKZFCLdqg7XvG6Od7+5ydhyyt/5P4dplAag7hGGbxoFdIkUAZo2mtbAISxS3zXN+n6R2as4oeN+3WBtNZzePREOccO+ef35CPvYARi7YmPHuhxuiIHs0lOWOJsD5jBbnaB/b0jYWjWiOFNam2mtYmpos8U2GpnFklQdzK5es4tDuxD484GN++rQi7BkJ9YzAmSxbyTz/njpjz/Otc419n2qz1/y2W/9Biq64Hmv7jciuMAsbOEz21Vb/NNlT/a/dxvL97y244SGh01K92gdP2zawsbdOSopERjx94vqVwvfeaWeqr/G+n1SayxOkORYwUFFcE0xHTNwZ6lxEXFszvzDwmGIvAbC6wdJS6WyXzzpHzxwnx4Jp3DMOeeoPtuCaa7OUhcDqa3vtbXqz28softxIoa+xEO7sO/Bwed50ZoaG0BaojasYbTlvvCDJ0CLOzelRMq6Hkrrc/ZB82GnqBoe4nxe1OHgPfTNW+9sYNP+HI3WZgfcSWF7jvrAu4v3uiO4+uY3ufrmNzHxSr8dFK9SSr7HXoGozJSmbYFQemDUbdPhrlcdqyxUAV+qSmttwX1zyouN4y9i/7Zl7y/BUNwrrbbYx3HsiSyO/XXW/Z2hGCnloDgc0mscE1i9s0cUPVw200hTiv9W1mhgiSytO0AWfKdvFP/g3+vYsI73Hd7YEY53rGqNCVbne2AoD7cjwmyGtn6Rj2+JCIpjwZ16sR5S3T5RyFicZQRhYbiUMhbP04tkcliEeaVQdnhI9Yje7e0HoMbB6RXtg4je1vusH5A9e+kZyXqwBZKloE2Xw+94oeE1EDBTmhlZjee/8Q1uPv4OktJy/y8wxYFzkmBsqBmSDiN7WWwgPbo37tjYFhu3ZS+vNv5el2SWcRunxV53o8/V2R4esNpelWH83df9CigRIi8XxQ4xgIOT373OcsOaKSKJnAMvTAFy0rG7OIGScww7QBovuhRn5nmmlESvGHZAtoPvS+lEOuWi//wgjeoOOEW65DFI/DJB8tDfDvDKY1pJhDbPSwRAL4X0a41jsd0uRKSlrTlOl4QkGZU4/KIYQ2QGEsUStV4p7MwBf/7WKnLowMRiI+YlK1hutSiMrbd7wDOLvaPgsxTeBGSNOI7QvMuyyIL20+z2NCilwDTx2a//Ovlkw8n51mu68VjV5tGiJHLOkPxg7IyP/ryQFuzX9xqs+1IWaKwHIOuBudLzJKLT/hxrhNlNn5bnBMEOKz5xQC+c4tdc93KGrVVePv+MpkYSBzZT2SB5IKdMoqFtIhdBsjFNO2g1Igcjm2BUv/mtue8JB5sASRlLfoN7vOcXSpzVRkoG5KhgtyXCS+H3FC+ESAD37hzX0yRJoqSCptk3koJVRUpwE1PBUgss6fXD6zdptVa5fv45bZ4YNycMZWAcN0guiGRKElR3voHGgalWamskayiZrAmTGcccBKUhZiSap19SQAIob4pGBHGIOwuJlFMcop4erVF9RI+CPx/EpvJCnQhkySA1bCzQDKP5vSUJS/34O94GLCNjktjvZ99/CcZhwFIi3dzy+a/9Ghc/+mOUsxF0YNpNGF6EyhEwSGqYuWMrKWAnBFJZCzEaEO2SwbEcfjkPcXgZ0KJgKogqSSsEpzFJpjs6/3sl5xyptBdjPUloiBhqCRXI3K9Adi9naKbM88S03yHSHAdMM5IHP4F1xmz2mzaPzNOEzhOg5FxIKaNNPaymUcpA1cSQFWk3pOGEVCbASZnZBMlO/ZznCUmgdSYVJ3AmHBcSASpYy1BSDzdZowuPYHpEaAYp+ZVNSbyyJkZOiWYexUjqIP5xrVYb7eqGm+c33CYhDYXh4pxyfkZhRExp7ElmlGFiP8+0ugNTPxBTxtRIOSE0UoZmCdM91JfkPCBDwm9+Q7I7xiwlOIawRgApInyWTeSRRF7SNDnEGTu2mWThr1rnQwZAnyTRjCXqOEYbQ8folNoqNGUshf1+QpKwGQbmz57zef0Gmw8/RFJhmm6wNoMkSh6iQGVIcpsNQ6WZkmxHtooMG4dazCALiUTKhWmeQRWyoOq8AJYGGFnwYbXgOKYD0jWd7hXBU49GezFMPNqUlH3nL2nz6+UA9+YZ9pBW1e7yiyQ4g5LIqSw+2c8Kx39ai/S6KVj158gTmhs635BmRUrDdAIgaQruReL29spPd0ukHO061jwNi4u12w0Mw+jRR1S1U2xQiS6K3b6xn2dSzmDVqT0l01pC6i2ZxjxPlGHFr45pmRmyn0nVI+uGMt3ecJ7fo5yPWIOkQsrZ64BaMVWnz5jRmttamhc0wGha0Jax+SVCQQYvtCT85Mc8Srjd3aBaHaMSxyy9IGOkNIAZ835gMw5IKh6FmAYtw6O8lDLzPDPPMymnAAkVSYq22Q9jEnpAGTq2ZQZz9a4NVUCNVpXJJmqrbKSw2QzIy2vasyvk7UdBxfF4uhc6EMN8U3tnWcnQbqBNSKluE22RwkLOhXmeaNMOFYcsSi44vKFkSZgIY85M+8G5ySkj5hGlw2zuEmY19tNEzhlBo/OsoW2GVh1+WQ7X1zvx7u0MrbfELf5aMIVUnMmXIhLzgk9PgSRO7x6peUqccyaX4tVmWTlHFniepO5s1+4EryoBHXRNGriFUJe2yOA4mgI1/sY35n5Wpuq8N9PZW8LKRMt7ik6IXkGauNlVaj3CiZJqtNZLJg5n2NWe3UeJzZfPYBzAnDCveMePLmlsfxLHb1JEaTkXPyAlk4jURjT6yB3Lc5saqjOQPI0VpelEypFGAWKVOs8gnuZhLXDstYi2n6sfeMlJ9EkVyo6W9mTdk+2K293Mbq+0I7Sx4dSYaXaIw5pyfXPNJg2IGLthR0U5rTP127/D9vLUr3X/+8NqvIWNUyHnwXmmIpTi0BZYdP94TaDDHo6iCNUaqtW7hEz8eMqeObiNxfnM4SN6tldVudnNDplpRaxhecTSTNJGspcgMFWHfl5n3S9NBpDOESNOXkFNSQso6tQZjxb6CUJEWboEWzkX0gEovtIkenVQD3CkjjIIqZOtJQXhUwNsDXJujhQKcCL4IXgupAyp9U4ZwYJBn1OU4S1j2pAjJuQ6IO0RoBgMItjzl1yVb7N5/23KMKKBBTXzroEsKXpFdTn4PCovaweJ2SElkO4wLQDv/hsRJ0+7wENBbUZEeynHIw7pnQ5u6/4afo8kz7xadUoNIBE5GFBrQ+sNkBeazVEtc2rbPM20pux3O+Zpz9R2bE823O535Dqjkhh3e+ZPP4PHlx38Q60ueL0XRoelmLWyAXrpzQtrthSzcLuJkRBy7FmzCmLkgEBS4IFGb+EzeqeaRfEtpxSVZAVtjieL+n3ZoLWJVG5f28b3jwzFwWiSYClHxU5RneJNB+VGq7PSFY8E7uTt7vCaGtoq4OV9bUbOyUvpbfLnV0Wt0VTDeTZEZ5Di0SMCot7xYtEf2XlIqhHJ+h3QI+b1ZDvoWVULML8gNiFHmkJ12/hVU6zh3Tk6oc8+YbKZ9O57pO0ZakpTW0gFnVbVUyikYOYncxY8hcl5sQ9aERkcJ2IOzDBFkaRGWR8/6JZXkOV+cj5kr2LasmFyOEN/qNA64wHPNMiF1DwaOUbI0CKyMvP0eLffU3d7pv0+cPVElkSVzNPLc9qnnyFnG0TyAX2px/RDVKZ9v/t+NodTUoqOLkVSRlujNUXFU9tkCuqHn6m5IzNBu7ADq31MW9g6d3iR5X8iaJIouQY2nEaSVgI6fq11L2fopOYBSCHJtL6hQxDbL1jwxHpUKOtz9JTXzMLJdc5afz5h6W+UXvBwwmdPp0QiZY7Hc7ARD8FT/1uJiy0h8dRWsF0Ew9U4MCUb8ZpHGDHcWW6z3u1hqpw0RZ6/ZDLgg/dhM2Ct9ltwWR65BYxhirSMpvXWXugQkSYH3Hzn52p6sB0OHN4Bl+zwZ3dayOgkfY1bz9Ms1YbSQnEnvS6u/uYtW2knTRv7aWaeZqap8vL6lmmuJDPONhvOTzecvtihNzvs4gxrne/Zi1tBuUGc12exx2FhANC7hYImldR/q6ED4MyNziPsBY+eKR4WQnqWGJWIhbPoaYpJ56QS9Kz7HXX35BY4sO2N/N6T2NOTw2Zr70fV5UN5WtsFHfzGNOvAeMcKvQrco4Mu3+UO9bDtKy7IEt0dVIrjMYf8opVXmA423GHKLnc2mZlXqI8yfQI/aJZID6Za2e32zPvK3LyFMl1dU7/9HabrK6JZHZXudPqSg/7VUMKJroI1AoxC2FIx7lvogCgv3cavvs1XW8X8Z50P5/+Mjm/392KR1vtfHqmNMUSNUgqKcXN7w/bsjLfefotprjx//oLdNDO1SttP1GlP+fQl0prbMNJdIS8HlwfdbtO+p159zd45gvk+7u11XofNC0vgcC8TUWjvJun715++d6T4IzuBmzVbX+z+OuveRCsvVuSll7i3vvUP2VuoWquuLiIHN/mS1axRnFcBhVWRhiVi873lmF6P+NaL1b8OR4rcuZB3G8BXUqh/z533pdbCQrJ8pmOsJPd1eDioNuq0o7bGbmrsdxWtFXv+Av2d7yKtoZk7VId4ltV+uXcYxWNElvbJvkk6hWbBdpdD69DGfI+NgcXGvUtiPWAPokrVg40RUekR27hfv+3ZmQssi7AZRy4vzzk9PaFr1EzzxG7eo89fkl7eehHk4Pr1LqEUdjUNbC9uhS6ttd4P69YS0mJb/3O78/76/7uzTKnEwbru6/UxjllaZHZ+v90vw7u3nmFKrhCsrZJSodW6SHkpgQEGhpdxLpFKryTLcnKnlBzoVE9Ppd+c1lALibDWIKUDZwWuGxQX4Q4O+EqVi9WputGEJAULYH9t1fJSvR2k5KGbc79L8yatpffTK3ytKnPgS/vmkeM4COV2woYC7zxGVZae1qVtAZzMHtFDNWEwwBrNPAk2VSQPSx/xUl1eAPc1U0hL21dghiL0DpXFlik5cThnTCu9fd8LbBZUHq9W6pH6QkEoKaM0Ls7Pee/td3jx7Dl1njkZR959911evHhGFmPSxtX1DbUpFx+fkC7PaO731kzKlByOsVlE8/0wlYRqC51CvN4QQY+yYvwi6lzEO1oHvVW3w239/khB/s5oalEsJTLQnkzTz9/XXvfDDBFSLo7JtMZ+N1F3O1qdyUNmc7YlDTnkkzJVFdQxa+soYOQoqgY5UmwSFpJRaKNJI2FBhxm8YrSc6gmT4s41bvZ+5HQMoadLvfVnufjmNepeVBHRAOkFkwYU3yCSUDtU4jmyFX3gakZVmBWm3Q7ndbpk2j7BicH4iZAvzmjDGGlG2HRhEUSfMQkTT6tojbaA6w1jCEUjXTBgI2wcUaOFUIQqi7jvq72uEN0HHRIBVILlwODQzBIxHG+JDHGZM8xhqh/58AO+kwvPnn3OZjNyfr7lyeNzTsQYk8th1Tpj19dwfY09uiA1aMwLyc4DGUVyBupaEMFHPPQim7fiNS/K5YKHNPN66AVU5nhiomlkDQadHqcmITHXs42DUR7W6C2ihh/mr7vuTa3JqWBNmW4n5psd6fYW6o6Jyvxyw8V77yNn58i8942Qu9JFb7DrUeyqXC0pQQu8MEXIjW9G1yg8fA+rgk3vle7ae6WUZYPEMy/OMYnf/JYGopXFHS5KM+erWT9KYsMeK6a0NNK3Fny0mdv9jnm/ZzMGjaJVzsaBJ+NI+eyK/P7TuL4LBNiz3CV1SqkX1yQqxH7TpsURhpNDQAdnLmjgQknxpgQJnMiWF1hk4yH+xjeM9Wihg/ypy8jH6xxpaLgWFhOmypALH37wPo8vzsAam7FwMg6MYiR1NevL8wuojfn5FVxcYNaVg7xXeYWhugp28ywylkZP8yKkAKAH0nAo1Zxj6pL/BnQ7++OWfS3efWRB48sG0fiJhTP0um0UWV7zuty7mqwK025ivp3QfUW0UkwZtDG9eMltNbZf+hLzkL3FTdfN5Y48OhRSb42L31knT69prqkhmTtKFhLVaQuUVLUF9uAAbJcV4uB5wB1uEWFapL/Ed21gFX4RD4jkR4snrdGWqtJU2U8Tt/s9u5tr5nlkmrxvlO2Gy/EE+/wFdn6CnZ1gZLIZ0gRLXQy2QyBRJRYnYScztGqINvTHdVzZIRUxV1ah80BZO6B8rc/vfLVwpymhmkCVLB49tMAnO6TiVdDjXH0PrgVQODvbgjXn3GK06BpLJTOcnIAp035GbyfaZiS3aJmTXpjyA8ZaQ1JZsDyLoCXntTAS25illGXq4i0CUMLWGiyqtUiboiOtWVekCcjEIIkFpNbTb+FwRMjvCDPKvQAAIABJREFUte7NM7y92VHnCZ0b0pzr5XrDmWIVrl8y/XZzkubZSXC8HKsxUvQld4PYku9rRG+vasx1zKBjf118QWKz9M95OLPDCzPEY7u6jVeZkhmtVjdEzmRJ5MA4RbzJv2kLcvBxpsmLI2xOU9jPM02V8eSUab9nt99zOmyYS+Z2d+udRB8PpPFdKmCWaB3TW6K+PvUwsFm644tDicD0+k0eTffWNNKqHMD5YYRpgf+xFkzEIN67GpRUfLuI0vkN/fXhOC1sZtTaSMnTZYuKvYnvLS94KXVuaGuMw8DNPGPaKE8fIWNmr5WuWNMPUA4q/N3Z/cCgQgSRtqTYqkqRIYokhZQGzGbUnCu4FoUjYFLPWqp2cj4kaQv+L9ax5bWI9nutewo1wO3VFckUq3VJLTUIlWKJZEqe9uTPnlFvR6bzUxgHMjkcoYe9ZuIjApoz2lHDoo2ub4jllEdAvawRbEOPXsQxzBTsWaProvXo73tbiDJGTsZclabFK5fMZMsos7cd9e6GI9wpZh3XMRBjHIcFlD47O2cqhXk/oXXGdORmPyNyy+mnwnC2gXeerGoyUTxzmwa9JaIItDqWqID6puwjH5INjjdFmJjL4FSukI1qgQkjKxkbWDhmSYwixl7NIZCU4t6pIDmglXSnxey4llFbRVRo4oLIBSEj1OqBgc+yMao26n5Pw9BaefT+e3z45Q/51rd+h2ly4rpZdvvaGnkTttTO0HDAPgj8zYssyZZxwlkGkhTHHJPjg71OsMi9wfL8KQlD8t75ZsV9QXShGM3T6M4aec2rcj9nqEq7dSBd4mTpb6yqonOlOPJOEWO8VnQ/095+hJ0MrBieQhLvC+7pigaFRhtNQ9EkQmxrjl9hSsoFpC0OsyswmyjTtEMYcTxIIiW/S8dAo0fGv3RBCYNkLgJhyfEUPVLIcKEsBR6Xc+bJkyd8tPuI/e6WlDJPnzwmtZntuOH89JRNKV4tfHaFPD7HhhFRRVOi0xu0hSIy0b1wR6AXkhKjASoixX2WOnTRp/UhxlxnumKR12c83jM7yCr6wRkdDVUTWSAxR8EOTxT09aOGN2lZFDD79U+5UQZlMGOujVaVLN4hMs972M3M0eMrL1/yYycb3nnnLT7++GPqNIFASmVRFe+WcdHW0CUgDjB1u/bJC0QBVRauMbQ2M8+rjqmkQ15xj/hYZug0CCp9Iln1ImjyOdn30a28X5qsBvPkdAh1h2Y50lYR9tMEkqj7iTJlbByxKx/sZF/eUlMmL9FBo4swelElVJVtFXW0bjnPbcKQRuvKJmmI187Ueb8oIXfSzaEa7tKlYH6RPRPwyMREaDZjDC41oW0B849xJfGKKyI0GpeXjwD49JNPGHNmuz3h8vSSkzL4sKWc2ZxsmGtj9+KG9HQAcKXrOIwsugTykJfIPnVxTyzGQHTnFGo45pvMMeFCnW8BQ0ruwOJBGrb+vx+AWTwyUR1cMspm1DIl9DCPt5yMt8J2KKQKQ1UmUVezmRrKxCAZH8Zk6O0Nc1Lef3LB1c0VTSuXjy548ewF+6mRS6/wx1gGvGji6lB4feCg8i+wqNe7D3TvaLXS2sQ4dmWqu/j9IhZNZG/Jh0apSUAx1XNPG+Pxr39N7q1naFrpXSFeCUwRznoscX1zg9TG6XjCPDVSrWxVkUfnyJPHdF1iaYqMDuA2hdw1yAj8p639DJ2c3Qsj63hSf4xLCqlvnAVblMU53u1IcYkx0wrSHFTHSadBioxq9+tXod6o1XG8WCnGuT558oTTzYY67TkZB8rgN3xTJUtBhgLZBUKbqneqKEgZ/XpbiK0utKaFDcbqwPpcHQkMq2OKnpWg1SWbXsWVFy7pCrK7QISSBFdmsZXI7ZtJgvJzfFY2M+ZQcmkBVYgZlcpumtDdzE2tbJJwlhLjsGFPZfPeIxhHvvvdTyjFdStzHjjdjk7A0EbfxF4oA1ibNfv/e6NFCtX77jusKcZMWs+6dXaXrE6xB1CpFHKn3Zk5LGYu30fnJsvr2/f+eobq1aZkq2bICrgbVze3tP3EfOpcxGyNocD43Y9Jw8h0WrBp9hs2ZLiiXztC9vD+0cki6e7Jv3QVLMWWfnN3rlHA9CK9pfuAhO2bcZEUC2Wa1npHgw8zcrWb49QzjDuZFOC3iBDTP9luT7GxkDNgbm9XrBGmaWai8ta7b7HPic8/+wS1Rko5iPU1Di710a6sEfsS/S/FMLDA9jqTYNUf7KjxatO7IL1XGEUSaEZkIslMs+IhCBWkEFIO0cN6XMuAafZ7f+kYy6DpjJuauX7xMe30baxckG4+5iRNbMYTZHPKx8+eMUTgMg4DCaGMI6fbUzbjwDw1ag1pLREXb1B3TpLKsqcWjQIzHyEQRdSlkYI1IVx4jMsKeT+VkHozklWqZYSRJHs8cRbcMX4R1eRwIGLeDYAR4JoDpLU2bm8nrq5esptmVBtnJXN+MlLkJUk/Qr78Fip40UVdDJQEc/WQWsxQnbBQwUjim1ObhgKu66OlXMjWEPzUt6Xg4pfRSdudcEscNZ4mqzVqnYAaElIFtUISP03UDtVujmuZQW31INIKFSI/ngGhRbO+JqVao+0mdlXZ256n1nj06BGY8uLlC+ZamfY7NmMJ4VafrW3NgdlWlZwcsq8RpUzNo8icUwws6imYsM5nA7fnqmfoq3MOHU4BB9QhY1pIafZEXPSgR/n4lqvWzzTcGZ6MFwxvfYX542tudr/FkJTzn/gaF58oF7JHTBiGkTRe0toerRPX+1sP9K9vOb3dc3Fxxtn2JKT6Qz2qNqwaWnxPNgxVb4HtKtmtdbgED2oW6T0Wa9/tLnMHlyx5O6jOWMiKNRz2SpHxtXtAIffkGYLjOS3GBnr60hVmWq2eOo+FFzdXJDE2+Yyr6xtUG5cN8jZz8uH72DBShpGz8zPU9mirDMMp0uXBKrQqSBmxptR59jDa8G6RRFR9HYNap7lJRBrBZ+QgerAeTrfAsEL/QqCZY0heY6morXMXjmkZLPJOPvPWuX6WDEs+T8ZaQ6W6tNrc0Dq5vzzdMDeDm1tUjaFskOSFk9Y8vd1sTiglk4KWkZOShhEloa0yV98YJZW7eKBZcM/COfOKTVkzhRb8yD6b2ftYfdiUA9SG0jALleUjXJaAZLRqjNtHvPsTXyVfvMP1/tvUi0dQ97TdC1oa2N28ZMiZ07xhsz0HO1mI0ZI8S9uUgVonnj1/AdYopfDo8oKz0w37nVHGE1Ie2d3eMAUm3AVguyN0KwZfWEo4nA6NrYRtNS+g0cf7tj6e1vexWec+NtTSa1v43mkyS1ocnSK2AtbDMCA5cXlyTh394gxjYfvogsuzM07Hwrzbk3cz5fIRwzBydnZGU6dV5LLxPsWcsDb6qZ821GnGmkd0jy/P+fDDt3n+4jOub2eev5y4ub0m58LJySmXlxcsobH1+cgs0UUC9nMjl2FJt7yyVlH1iLfZHJv3WKkXQp+R0eWRqvqMGG2NNs/MdU9jpljxQlRTtk8uuZompo9vQc1l5TGGXMg5M5bMNE1IGjg5OaNko1YYxnOEzBVw+vScx48fsbu94eXVFX3QUz/gc0qcbbfBY3MaVceEzZZOZGrVSNG7EKl4O2ZzPLKxp7Xjbbns3MLT03Pe/Xu+xnj5BMmZx4/Pud2cIu0Tdp/+JuNmi9WZU53Z6uKavOU2J3JJlJw5324Zx8I83zLtJ66urvn882c8efxlvvrVr/Bbv/1t5rlxtj3h4nzk8eNzEOPTTz9DVUhp9CqwVlLKnJ2dk3Mfz7C22iKyyPlrc9rVXMcg2TeaNX8+jKYztPTaFv59OEMi21S6Epnhoen5xQW73Y6rZ58xlsw777zN+XbL+cnWxVdPNwwipCFR5x37aQdWyUUZhxGXgvcP6m2pxn7aY9UvxHY78A/8Q1/ldDNyc/uS+cVtCEXgQgIG42b0nuXeXrdYf0GTkNxo6pQgkUStzSf6eeMWhjLXtFTFjmu5JHytXpQSkeXrnBPzPLO7vWU/TTRtDAbbnNgMA8Nwwu3UAkt0sqyJQErs9xPz7A7rxcvGi+Gar3zlQ7761Z/km7/9bZ4/f87FxchXfvx9vvKVL/ONb3yD73yk3NzOXN/OGIXNuGEome126w6YA3rOwfsHqNUjSRXISdCqiJzGY4TGKa36Rj625ew3gbTh4u0vsXn0xENFhUdvPeH52++z/+3POT8pbJ484vbFdyhDwTYbWg3l6ph+15qrkvs94wHH9vyMy8sn7HY3vHhxxeefvwSDzz79hLOzDU+fXPC1r/0kanu+/vU91zcz02SgiTRswHwmTikJ1V4XOIRC3D80NZoZxUaSCLXOwSl1hW2jMlcfL/I6657O0Oj9JkTFL4vjhc2MVDLvvv8eZ2cj9faW07Mtw2ZkpgZlxQsl7733Nm078uzZSz7//DOQxpBHttsLgvnHZkxcnJ/xlS9/wKff/YTv7q44Odlyc/OSX/mV3+R216hVyckYy0BtHsm4EKlHDB3WlO9zNnh0i1eUmysup9wr5cUb2Y9wGTA3jQpsFFCs+iQ1FeZp5vOrl1zvJk5OLjiVmUcnG07KCVkSw3DC2XaDSmUoiWEcOT3dkiNtMYM6V+b9xPPnL7nd7SlDZre/YbPZksj80v/9N3nx7AW1+TyT3W5mP19xtr3k8uLc7RZqR/Y91cLeydI5ZhIV00bOBUkNbR41UvJRBoZmSh5GHr37AdvH76IKuRR0npGSeO+rP831ycCjtx5Tzs55uSlsTwfYbqm1xdA1r/Y7XeYun1dbo4lS8sjJ+YaPPvqUq5cv+fzz56AXvPX0EV//+t/h9uYlw7hhKAO1zeymHcNwSpYofUZtrXNfO+3q0GQdptMoxiYZIK1Qnqfir7fuHRn6jOLQNINoYwsHmbxb5PGTJ7Tzc1ewTkKrvplsqlStXN/e8PjtS072E9qMWidqU3b7CdPGze0VQ0kuETY39nPl6uaWk5PMOIx8+OEHfPSdz3j27CVNZ3L2qOH0ZOPRZYcN+z6RznULKoH4dDZMyAlSMmqtDJJ8GI31NrL7Xp03YBm0GsrB6p0K1WaqVvJ4wX54zPV8S51eoNu3KCdbEjOpKlZ9DrIPHYeqlZIySSFlwaikcsI4bJDTU2qd+JWv/wbaZl68vEaykcvAO0+fMk2Nly9vwDJJGkUSt7fXlASX51sQuxMRrpslIsUUoqAkjyJspqpQxEVFkeKV5GO0cco8/pGf4Pzx2x5dRQDSNYO25+dsf+prztmrlcsPf8RJ01YpSYIyo14Y0UY10BGw5O2T3TM0n58tpfDWO+9DFl68+BR4j6ePLvmd3Y7Pn10zzxVSoc6NVifOTreLw3PBmkM6liy/cLxfEHXhhpQC504jKWmk9OUV9/mD1z2ryQdv0FmT1OD0xW9WqkTKaKiLNIV5qth+RrPw7Y8/5UaMm+sdu9s9TSvDMFLONmw2p94wjjHPxt/+5V9hrsZub/zOtz/h6dNvMdc9Vy93aPM30rQy7/eYTlxcbFh5GracLinK+E16caV5c58R6Z8z1/NQgod4nAOhLApMIi7VVRWmWZHhlPP3f5zMltPbHcIttBuqXfByPyFSyQFtzFZpNlME8jTRRi9cNJ0Z8KKKWKXV5unQkHiS3+GTT7/Ddz/5mOn2iuvbPSpG1erVbSxmb0fjP12s43s+wfr7RRIskbL4zF7LlJz67HGOkWdYxg2P3/mQqU40ncjlZMFbEwmtrhSeQwpNq3MGx6EEe0O9m6TFdU4hu9UaWiuSe/Grdwxlqs48fvwO19fXfP7sc3Ka2W635LLh+YtrdvtKncFsIifh7HSzjBjta1W8icJZJ/dZgzSQcqJNk8MfybtaVl/wGtflXldROnGVpXDi+IOuw9x7pUecNtNapdYG1aj7iXx+wu2+sf/2Z6QsnJ+fM24GhjIyDqeOM8X4wJIzQ/E2n6FsUIW/86u/wVtPz2lNmKaJ1pzTNG4Gxk0O+gYhC7WW4xfKjTkqiBpGQ/Gxhik7daNVhTRHWHl8G8WvSnMengBJKWVg+85XOH3rPQrCzYv3mW4/obQbTs4vmXYD1zpzcXbuRZecEEvLdXcMtkWqGsUtdVFgkmJzRRg4PX3E//Orv81bT7dUdQrGMG7IZaC1usxkdmd3lzPRlVfsIKLvVCyyk/tzCAM0NRKhfH18JvaUWAp4XZdSNtTWMTlX/BGNzM9wIdWSkGTkHG15kryfPERUJEPTilZXkTJRRJ2mlnIo45vy+PG7PHv+GcNQaM/2NPMgRdUoYyFLCdm4iaGsQBccckplgXB8Hnv1sSKpIHKLy4SMkVTX17bxPcVdO3GZcIYelmqQpIGoQPqrz/PM7e6Wea7IXBlUOc0Jq4YNme32lM3Gm/Jbq1huQb6uMUHNwdqShVwgWyalDc9f7ClpZBg2nJxs3CjiEkFYXWa7HeIMzjcMCXFwo/fpehiSDLEMYYz0Shp2LMvMfGMQ7ZYGZXvJ5uk7pDRQZOby3bf47PlbDPWUt3/kK7Qk0G7Jj879pi5CJpNFgoKhtBDjaC3aMVsLJfPszQJSKYNjv9/9+IpcvNxVZ2/qzzmx2WwYx9Fl21Kn27yK7Xbbg7t25zAikKUr4mRvQ7NjjAuDPlWnoB0NLmoQ2QC480MkpmAkhiH7AHebMTTmYUdFORWnKjUfLarm+tVmUQFWCxpbAmmkUijDBR9/+oJHj88pw0jMkWJ3u2dfr6OD6HIp1Iocuinxe3PJmLvGIUgaPWMBV8jXg6F0r7F+H0Pk7Y4z7D2OqwS4d56YGdc3tzx/+YJ5mtgAH1w+4sQSQ8owFKyG+II4bcOru94qJSHzPmT/eW17TKGkEclRFklg2lCUXjDqElHrcWDrz+lCsT78vFlXVHFHOu+bdz7gWNkxLjOYa/BITcgnp2ze/oA0FhpCUzjdnvD2T34N5lvk8oITMXLaYtIYcnQHFZdVaq1iMURBUloko1yl2GXXWvSaKo2UM7k8JuXuBHt2MTG9vKIIGKehcLN2F32/5ayEFThOEmotkj0q1fXgPqbl/OCdB/5lw36ePBMwb4vt0Rxx/Qy86CQhtZXXlsmcM7Xt3OHhDI2c+zhPga45gLfLaptJpXBS3uL66gpkIuWBkkfOzpzD2HSOzrTvharWrX0wLEzc36h5q20NGp61yD6+iMjQzIKicFCcIPg9rYUzVFqduJ1mPv3sGdfPPyefnHB2duapdFNyUx8RL+bqGOJadcZMVzURcZxPBkHUGJJrIqbUN0GfmyKLxL/Q0ygHzpEVZ/Dfe9nHxHuRm7W4cEQE42lDziW4h8e3UQxo84ymjJyccfbkS2wePyWVAWzyjiNJnJ6dY7pBW0WTk2iHUZBUltO8tUoRxXQOm5Zor1K3o6qnq324zxS0qqwk80Nw3BRS2gAXFAFhhjaRiguAWnAGOk7oEf9BW5f6V9UGRGZUZ6QNIeKwP0obAxGpJVpzYj0po7kwlIS1GclOes4CNu8W1kXKLpDQGkgRJ9zbhA9GcXEEDaFkI+TAFi6yobPL/uehcHpyiapSa+V2v+OqXlNK4ez8BJ9RMyMysA6L6xQbj/D7vncIcVVKb+0aSUMclPMXNETevDG/5+vSK4eGK79oY54mjMZtTdzuE6cnZ0gRdpZ4fjv5oJ+cGGSMdpwYGRiDXfx9e2ircRE1Ch4LYBpfdUkgl4RKzqhvSpd2t15ZpDvD/jEOI8floInHOS/tUIX7mJaZMZn3i148fsp48WiJApbxrjljQWWSGNyVs7LJLtIASkvNWytlxfN6V4C3XGlUhF2m3V9bl/+3JQHpaW+KNq+Gtuz0iUUM9qBjRkIuqgPa4Rj9OQREPQ2TDrAf3/IsznHUOs8Mw+AFqpiLAl1NXKl1RutERhEa5NGFcyMFzSlRZAx5fY/kfJzCgXYlvUkjZqW3Fu28vieHsVCGhKmx209cXV1xurlY6FEufNoVyjWyRyNksAlpJO99ro4bIk6t8yzyC3CGBlS1g5tbQghUl3kKBrThjHJ2ySmnjFefsLEdcnZOTSP1yRlpe05KA5LbMk7Uc3/fMWoatAcLVQu/8Gru6FLnIcW78nS9uchx66NFl7Nkcd5JlthwiWwNbyOU4jfH3BSRysk48LtkYG/sMjNkGDh7/DaXb72LlSHktqKRPg7BGi1vOa7vmAta3Q6uoGyUkpFIm1fB3bZgODmlKGGto19bmzHw6W1dewMjS8ZHBLlARM19k0DvQjEzp3NJrzV3GEQxdU1mh1xmSoJhOD7CNYSDSrII+EoSl+rvOGtrSClondDmdLdGYwzOnh86Eo4p1KlTC+fn7ZK9eOY+whZ6W/+7eVaspGB5eJdQKYVtPqHrIKpKxJddXNRt6WfYqsfYD0GtSoq++arV8c6cXnsf398ZWsd7vIWNVuMEj8pRGWjbp8jmhDMRZplhnzh75x3Gp+8xnBTMXDMwlYJJn9AqYFF9VGe1I32Ogb+mkPF+ZMB6VNk/rEQq1iejyaKT5qcL8Rr+WVw1RyJVqM6kzymULjq2eHzeUFLi8u33OXv0lOHklF2LExbni+ZSvB+1z8owcxWj5IdYTk50lUilhmGkC2x2NWTvpZKYa+InvC3Rf9T9Q17LseMUunjqVepU1qjA33Wo20SaTFe78wwhpUJV70pJyXExjyD1KA88AmvbTxNlHOKH3l7bajApLCLBsLNj9CkcD5Tifd21zQgFo1BrJaUU6WtzGbcky2HWiypur9jbts5GSVnct2ihZFe+dqx3TZNjR/t/AzZL0mJUsRfmnNlX4jWV79d08f3W/Qso8a9Fri+6NkmbGrY5JZ2eMoiRT0fGD75MahNyfkbejAylkKTSROnTsvyj5figeN+wCDn0zlp8uNTnnDikS5+bCy7UkMXbeJY2ulfHtOGAsCKkXBHFJc/NudaYpwpNjakeJ8+wjBsu330fKSMthZhC3FQpOWDudV4jF5c7KwmKDzWmZK88mjZUiUqhREqUMI3yWHKnmiLt9l5ib4GUZOS4p1LuKuX4rAuDUkZKkSjMeMGrC2/4tnUnWErw5XLxtjxGkBnSEJP/jJ6iH9PyqM3YbMYlenO7ejo1DD7qIWEMOXu3jrptS8yAWLRCzYc2lXyCyOTKUyRShrz0gPl9Y+aCC2MeHW6RmF2SA+oyfy+pZMowxrRLIjtcMUNwPiQpUyuk5P3MagrJKGmDpQFtiru4L8AZ9ha2qsoU3SSJXnk0ZLOlPHmXUjZgDSvFm7nljJwTQ0nkUqD416fbM8Y8k/H2qJRTzNvt+VGGLE6MHpQcuJ8XWZauaAAf7LSIei6M2nCIHRCEFlQMteQST1bR5hiZxgY2QOVAYfKIVi4Dm/On1E5CzyUEORrD4PYUwRv0k4FmhmTeMRS4niRBsnd7nG9P2W4Am0jJUyrMsOD8uaCrYeJtlT7PxpZL3wfH+8/czcmiTtRT8A61GC7IELwLSajNWJ2pql6EU6HZBJaRfMJRRv8IwzgiWtnv98jJFiT7Xg7xhSEDLaHkBXoo2fH0qGCGrQrbzZaT0xP60eKiraHuF99L8vpCGfJyuAGRGRh93GgfNq+Yj43QdbiTRXHVnaJ3kEGvHO+pCjltMJ2obQcM5LJ57ety7zR5P89M0+Rs/gQpKVkNSYXNo8dszh6hrS4pUck+B7XkxGYzUspIysZmdOyPkOzSwH26BFdKXo5HE4R0k/UythwC4izlkGaN2kF4NOgCevDuLXBH3OFGWu38RIvBM46LtI7gH9nqE8Vqa5Rx9LRYldqMMg7k7JX/NtviqDqd0yQi9FyQBMNCmp9DyVxp0aKFmG8akzBxdgJ2vA/TFqlvWl6jY4A+IyfT6V3AslFEopppHac0wKNDt//eN37KNO0qN0e4RJhrJeVMyn4I6XTjkV1EgyJ7DgWUzbpDSpTI3vx+aczzDSkn1ynU/nd+cFmyUKbxKE3VlsiyCzr3x7fmIsC1CU0zosEltbXA5tPy5giaeoGmkvKIkGntGvKAiNNsXtfC9xwIZVzdXLOfJkyNYci01JjV2D5+wvadD8CcS5Rziob4RBkKJSfKMFBSQaRhtTLtGzJmsITqBGKUXPwCdh+WcmyEHFhE8v5oC/HBiBq6g/SCjrgg7CuO0LBo7F+jAbdlL6isWGFPJY5tGfgmScmhiVxQ3fmsiZxJZXBlIQcblr+R6FfP2fEeSU7E3d/ODGOCUlDdu2PMJci6INLAfPOZzrg2pW+MdVxDhz1C6KHW5QBbB5N3x3Yg5d9vD2wRCV5koFDUeqfRcS3fPg5TSUpIcjzWMIclUvEARR1mKCnhxHXPlnIeliFdqo397oa8HTE59evZJpJBLpu1kKksKbQeDITSfqBlgIQkL5bWBtpKbOtuox7ohJ1tbc0U6VhzPxgl2Ar1i3GGzZTr3a1L8rdGaw56jueP2b7/owybC26uX1JbJWWPIiQ2UYlxjx7eVqre0lJBhy20XiRxReJCRn3CI6TiU9Ms5pRYp9oIy9xXCC6bP0+fpyxRug9Ox+IMhaBW0KvLfkGTOKalYqR8fJvEl7dj9XDPDGpTL4qIFy/avHe8OMdUPDEsRDlzGvwGVaVOO9KglHFLbeKqRaF2nXohLMod4GnUsrSxtNb11j4xxHyIUWveV+5FmB7ZHzjBg+f1KrXP1BVJrme0VCWPc3nBIniaKaFzP6RGhxcwl8QSIqLLIBmTwce1Np9JV+uezIRpoVI9jY46AJJZGJ8xTqMXQzGJnvO2FD5zlnheI1ufsRTRY+plsSjU9siTEFaJAh7mWKQXaSs5VeQ13eG9nKGqetQQlJrWlLPTJzz98McYLp5iTdA204f6IAnJEljR6LMRUISJZDNCCtn/HG/FW6fUvJ2LcFyqjlVKDjrA0o2TQsnWVSdz8glZxEUjVLB7V4qD7MTXji0JXSE5fpVjIlj3B0e3XLSz1ebVww5Y5+JtW+pUpERe5pO4zLUVcsFaAAAgAElEQVRHkd6RVElSMZvcianzDUXKyhoIHOhwFkZTDZpH7w6JGD75PdCsUnLnJHZoPu6JBU02OrIMKWa0ZFIy0BnIC25JsAyOblnv62Xh0y76n1K8B5wa0Z8y14mc/DpKKi6XVyslE4PVogNNXX1mcbC9UJbxeSXBMQRiaqEGtOsNEi2KWqVriyqOQXc4hQ6J5AhgvGWwF2BTTj7Pm+zFNnrk+Hrr3gUUb90RNicbTi8ecfn2lzl9+gGqiVnnuNCZOjsYW9KImTBXb4wfCmRTl4xXJbWKSUFSIensQ6bFQ3cxxZotfayO2/qt3iuP3hvdnCZD8dAZryj6Xu2IInTxVscyMuTi81VlxkdH9tPGQeMjzJIBgkjfZ4j495VIS1UXJ9enEm42JyA+w0Srn+yDuIRTawWtFQrkNMRJHgPcUwbxjgSP6L3zxGtcngn0wlZrDUnuI1USlsLZ0QsugpPta1SVE5pcUcXyiKgXT6R40caBp8Avj22JILmQ5upR2bz3mTRDCdxcPCJTd4q1VU5Oz733eJ4P6FEGrdHE2yVTUixlTAo1epRJKZTQa8yd8cJcSQWLGSgSRbO5ziSDVg3NftS5ck30SluQ8JKhzCQXYvQsNBWcvl+xYRN1BvGRxl9EB0o/TE8vLnjy3odcvPMlhpMzn18ReJHzhOboShjJ4lifykwWcF4fgd/0OSXq1SI1LPmFdhKti7Q658kizQHHk1zee+mGgbUPseMUy6kfDtFsdYspk6m0WhcJdEiefktM2TjGqAEi1QCtdYmW1ZzULtk3TNN9QLZOf6rqwgcJSDlRq6JNGfQQw5NlAlr/euk/7YwEWdVIjOhu6kUzYWmTXO/vrlbjlclOIHBBgZD4jx7VJEaSE8xcCZn0ugy0N2uZGTc310it2OzdKLl4RjTVyYucNHa7q1CbNlptDiGpknP2bhWtzLWSB+jdIh3Vw2yNOhfMPuCoFJqSLWYpS6NFkN4Pv3UIWDd0fy4QdcDR4US3/zxPaBJEIeURI3ip6fW5pPdyhjkn3vvRr3D2+B3yuGVWmG9vItwulDKyv74iJY/i6pTZA1ijDOKlcsvU/Z4slf3eMYSkTs71UyctvcMxCNBnaeiqkiNxUXvI7cUmJ3G6w5ZwiJ3UKweb5/9l721iLNuyO6/f2nufcz/iKyMzX+Z79fWqnl1lN7KNEch8NQNEAy2QkJAa1AgYIDUTWuoBDBgBVtNMEBJgIcHAEq0WHiAEEogJHxPUuCW3eoBawm663GBXV9Wr9/IrIjMi7r3n7L0Xg7X2OTeyqvwywOWS88Z+ipeRN2/ce+Oss9de67/+678a7WK6M+ykxPAw20xlAmQPbZWSuXpzOfEEJUZil6zbJEaGtGTcvUHHa8ds7RaqRV0oNxBSoo4bQs3sRFG9gdSx6AXGTAhKwmg6QVuaFWxmhSQfedt64P34cixKYLoPDOcVg00Cs5NUASkeHUAeR0vpg3hBSGkiwIeYJ9dauLm+gnE0BkDsnPBcjMiceqQWdlc2FjRIZBjyHvzlAq+aoWwZO3y2TaJbFISRWkb6RUFiJAlQbDzwdjBbhBBRDM9rXWghiEuLVXdw1o0UnA43iXI42VrU9ApMxsu0Kg3fip7BZJpy/rusuznDlDh9/BSVhfGA8g7VAKWgEhi7gWHYEKSSYkS5YRw3pADjGLyyJ0jdkUKBalXn0I10XU/ZvTFCbb+wW1SLYVS1mBJ117luos1TniSHohCd1JvzzvocVVzt2KvNLbR3WF1V2W22Fp1Ed4bSeYGnkKRtuMNbZRygViQlhEodd6gWSgZyYRy3MA7EKFQZ/UY0ArU4GVbLli4WagkM44DGxNArdffanODOsOegGVX7+WEoTrS1Gzm6Ogo4PBJsYwzjjr6PHuEFx3dbe5iPK5KByoKb7Q1aCiksLWWLxYszIyHkg7SxwU12IMQYvGXS1OotA/CJk05BsgNnsNCkzTgGgmdsVY17TM12fXWgjAOKFVvEeYABYRgt27Bpd9aGZ+eU+Hsm4zT68LBWN5hwfd/HJilmafluuyOPA7FbAglNI1p2SM2EaP7jXdadnGGICcRAVavCeiVX1cjRHhVEirfCNZwPG/aS0pRGxcmZtZ5hT21dkLNVCE3otaC1TqNIRSqWTdsFKlWpEhEqMQdKy48D08Hfhhuhrnao2JgBUaSagbWO1JrnG+MANwpgsEUMzvX03m7nfsYItUTUlYZAUecRilpLo0oldt4pJI4BO39RxdKuiEOQ6pQXKrXmaagQZI/sm0NUokYqlTzOY1yFSJM0bK1XgoCMKMKwG0ArNSRUoOiGWgbfhAdsYzW9Sryjq80yEdSwOBGyeFAhUP1wqqqkaC18USLVx6+29jjE5hkXzB5BzTghGKe4SefZ9p7J18YndZtOBc0ZUsGzhAa51Fp9NIdOzRJSFSVTh0zJN1ZrrtGFI7543VHpuvGNGgnSsZzgZEi1Mrxqsepjze7xg3eiJBsxoqMBtRhdQ4siyX9JL6dXLArQYARaFZ/R4PplRtxMVsoPjl2JV59ik5GaW3zaprIN5hc2WOnfHGRGPCrU2Fkt5WBXhZBsvo2ryrSZxV6+8k0ULRVxagMxOA3D7odaMsTOHGcj7IZorQnuCI3iFFAdDWDH6FhT2UuCq8xY1NCGD6EtItxLn9iPJBdTTRlJNpdcK1KLpVDJCnuHuOyeN4mMKBG0eOeXXbHomL11mARTHqpm/SCRQOvtVhu94Zgtri9q3zhuiMnrqhdcWgulul4pkmkcxhZkteWW3MMNWwbgblLDRNxvNB50sINbTe0afXcxjjszrVrUZlFc+4B2w5o8koGgLSQ04Dq40ox1fdgUO6ZCXpMCU1qv8i3LMUu8hzka8UjFDNHEZR3/kxZW/6ivt06J9nPaRL/sIqOHS0Ir3ow/HXjsS2UVmkjGbYDb7egpSS02J8OpX3boKVOkWW8pEDvNw/+LTuid+GXSsOD5/cIdSIJG+6jOPGjCIO+uZvK+LQGjR4XG72zUpPkJbZbRHDEyUWHwrCnn7La0XdVUx634yY+Nuvf3rgU1gdY5ZBMU694H2cf7f/yyzMJZCdO0vrB3UH7xuvvcZHdy1rhv00kNBG0pbrHk2UPgphrT9PByLtNFbdGfuDhCc7D7v7yJt7bqkr1WKYUUHbh3IL1KdSET00572+m1Tf02YK44XQS8Y8WoFzaT985X571Y+2lFEJkG8xjOs7dR/DniN3VKJuOWnQoVG06hfk191zQ5eJmzXX8cF2DwzerN/dXVbLSWyYG1d2/FlOYcp/a8PeOpVlMzEZh0MSWiNd963iGt9murMwCgHVjVD8HqxQuZnlyKDfCymSV5GvXhoB/G3WUiSrcozgcvzA7VBRwawdoc6lxznj+j7h263H6c2R+0x7S2UQ4z+bodtO+y7hT+tL5Ev3ITENoirlY6n1KVKSW1v7cJWnb94tTpUFp9AyaCpdY5jWqn09xvOl8U1dtub3Z69us1ykyjzbTP0T6nqilmt7xYvB/2YD0hamrGfm7YhsDtaCNW58NpPrzMgYpjvH4yu4K1TFSp/Rsc23TMsmt2G4nPzdj7RG+dbW30xH5xZT9q3P8exAc/ta1W/b6LHKqF8crt1PO9dy1b1F73DsQW4U30mTqr2lthywTTaq3eIDFH/e11LPKb7VLa4BN7Zebv6pQ9qN8Ub9t3+iVojhGYBoWZozW6XbzTNr77qNCWnrgTigIap5yKJqvVwNCmcFvqiMWRdZLiAqPWCNWpE60gY6d3nZyfOzGtRqK0WPTWKEH1aNQuuBmI6YLubQyP/lr4HYL1SxrvEcPG5F0beN7DpSaDJp4OTbCFzI4GaW2OddKjRJSai0cLrYofHPqwFCb6QdcOoWbaChNs0jZe61S5DW84PjXFD3OHwTw5rcX/9nMKRuCXMGHISMM+D3OZuGvwy+qjMnBgsCF1jcjue7mlneCCJmA8zRYMtR+d0tPoEbu4r3CtQlpRzusMRLwx+fZnnKy8Z39tDhAXfDU/UsF7rAMBn/tNcB2Cd9/JdwPGvDLYvLSdJnXaHEHaxVGaOrU0AU8nUEto0j9Wa65+wuC4HYqlL7V42N0iilm7UNommxyiTFFMixRVw3RK6VtOsUWLIt6aFaJfCX+tdlIe6H6RkDyaM7VgYIriGuRhXQB2uFW8kDFpTJoYqzgAr6g5zmk2hph9a6bixGpmgq5OB14A3yx2e+jUfqXTJuHW/ThFD9OBFm0eht+H0jZU3RP6OLAlYIRox4DtMsyqP3YNDTeuxSZVKtaoEPBAR9S1B/yA03Zeen6oe4K9xQKbqtZqW13C36689TwDbhtpx557ERx3tiDn7eDQNAzDJOgCmeCft9LS6Xdbd3KGlsaKzbnYC63xx5vy9H4424BS7DpNz5svRnM8sodH6q3XtO+ZwnCTd9+/iXXaEPuO70fd5/sh91yZak5W3jqRDnC1DPbHFCoaDcrST3/OFOn7S4jswSezadvrtvuoGWiiw3ik12w4vZMfeAazzPfAu6RA8+Zmmu3dcOxDXg1rnSX8ubV3FAsaWqQexIQd9lPdW4fPW2tOu+3VghOrjd62f4DtfSbwFL3NLpozk1uFur33tnEe871XHa6xQLfO8Ms7LLnLTSEiz4Dff+cf+OO/PlbVD37aH+KPct3b+P1f9zb+0etOzvB+3a/7db/e13W4ZLr7db/u1/3aW/fO8H7dr/t1v7h3hvfrft2v+wX8/3CGIvJIRP4P//qBiHxv7+/9H+aHfOt9/00R+R0R+St3+Jk/JyL/yU/qM72v697G7/e6t+/tdfd2PF+q+gL4ZQAR+VXgSlX/o/3niHMi9C7a21+8/g3gT6rqD97lySLy//l3PPR1b+P3e93b9/b6Q0+TReRnReS3ReQ3gP8T+KqIXOz9+58VkV/375+KyH8nIn9DRP66iPxDX/Davw58DfhfROQviMhjEfkfRORvishfE5Ff8Of9JRH5KyLym8Bffus1/jkR+U0R+VhE/u92oUXkfP/v9+vHr3sbv9/rUO37k8IMfx74j1X17wG+9wc879eA/1BV/wHgXwTaBf4HReS/ePvJqvrngM+Bf0xVfw3494HfUtVfAn6V2xft54F/QlX/lfaAiPwZ4N8C/hlV/X3gN4E/7f/8LwH/jZo87v364nVv4/d7HZx9f1In5N9R1b/xDs/7U8DPyUxDPxeRlar+FvBb7/DzfxL4ZwFU9X8Wkb8sIkf+b/+9qm73nvtPAr8C/FOqeuWP/TrwF4D/EfjXgH/1Hd7zftm6t/H7vQ7Ovj+pyPB67/u5+9vWcu97AX5FVX/Zv76sqpufwGcA+F3gDPhme0BV/zfgWyLyjwOjqv6tP6T3PoR1b+P3ex2cfX/i1BoHXl+JyDfFFBL++b1//l+BP9/+IiK/fMeX/6vAv+w/+6eA76nq2xewrf8H+BeA3xCRP7H3+H8F/AbwX97xve+Xr3sbv9/rUOz7R8Uz/LeB/wn4a8B39x7/88A/6uDpbwP/Ovx4vOFHrH8X+IdF5G8CfxELk3/sUtXfxsLo/1ZEvuEP/wZ22vzXd/h97tcPr3sbv9/rvbfvwfcmi8ifBf5pVf0DjXC//viuexu/3+sPy74HTTEQkf8cA4D/9Bc993798Vz3Nn6/1x+mfQ8+Mrxf9+t+3S+4702+X/frft0v4N4Z3q/7db/uF3BHzHC1WOjpaunS3W3WhEnDp+WSkKJP49kb1DTJhM9jevaGTAI2lCmIzePFx/vZpIt5gkF1Ofi98eJvLZln7E5vPr2U/6nTtK5b89ck2ZPq6JL19hmevXjJmzfXB6X/38eo3TT0y2X9o8n6B9poByGIEGOkPz6CGG6NF51s7MOjABs+LopSENrQLZ1GCNjbmaS/yO27ZP9151m4P/oeALPx9NPTfeo21tFmtASbjvf8xavDs3FKuux7wMZnTCM0fJyG+NiGaSxHCHTrFfhIDwGT1W/y//5/CWZjtGBzivasuzduQ/Vt2uLt1fbxj1vqo0XZm2tk8v4JqFCzT2W02SrPX7zizdUX2/hOzvDsaM2f+Ud+xWagaiWIsFz0JAmkx2c8+hPfYtmvkb1xkMMwULTYRC21AeE5D8QANsEqsT46pQ9vkHyDpCMIPdRiN6zPW94NW3IuCMEH0/ucA5+nIAHW6yUpxWmA1P6MBREhl8zNzc73hznXXEdC9yEiFRm/RwiB1eocCZF/5y/+p3e5PO/FWqTEtx48IKAkgSGPhBg4WqxY9z1dSqyWCx6eHLFar/nyr/y9HH34IcNuRKlIVbNbzUBGJFGJLFfHrFNGy2tEVoS0pDDabGVJIJVh3LHb7RCSDROTedZFm9WxWi1JnTm2eTQk0zyMWiubzdbHjVab41wzsviAIIqMnxJCYrk6A0n8e3/p136al/unshZdzy99/evErmcZM50IQStSlFXXsVr0LBYLuqqUPnD24RMefeMbdA/OqGNGFGIM1DIC5ryqJpbrY5bdAPmaEBZI6ClUEjawSTEbD8OI+NTE5ieajUMIrI/WxGiD5ew58/Q8ESHnzM3Nje1jVRs+D0j/GOqWML6g63q65RmI8Kv/wX/2TtflztXkMRdqHkk+GKjveiQqu5cXvPnuD+i/8XXi215fZZp8V9tMSIUQBZV50Di0qWU2q1dVfdzfPMTHNohP1/MZzC1Q0GnUpDBFoarTsKI2uKiWuhexhOk1LSKsVK0EbVP+DmupAiEQg9ClBDGy2265LjfUnFl2vU2mXS+RUhhevebo6RPa8J62qtp8MhuEaPZA2vSz6jPU2n3SBFH8PpB5PnetbUhRG1Op/ni9NUxIRKavIEJ1m5q7FAgeVYZEGxYkBwoSVYSbYWDRnSPsyLs3RJQuBMZSkGGkKuSqVIk8PjsmxNCmxQL7GZ/vnbaP2uTCeUjhPABqitbx22F2hMA8TG5v/jXMg5/aY83O0+vQpubJNKcbacPkf3gM6Y9bdxsir8qYC9vtjt0wstuNlDyyKSNRhc33PmN3cenjQqcfsl9qb3KezWkttyZkybRR2mqhe5uwJ9Nr2RzXMv3Z1IV0uoi3X2J6xb33mAwZWkoHqPj39dbGPqQVQiCl3kaoKsQYWXQ9VZXtbsc4ZmqplDwitTK8ek3NGZ9DRghvDfxuA9zFgA9801j4Pt8P0I4vaIMibVh5YRo5SbsN9Ids3Gw7OV6Y7q32mVCZJ+MdVGL89hJ2Nzu2LKnrL5GrHV61CqUqw5i53my52G0Za2V1fETqemrOEyzG3nTDdkCJT6VrJmiP3tpvbznANg2xTcS7BXNxC3H7od8BZlTOpja2ewB3Au3r3dYdnSHkksmlMo6WFu3GHdthtLHIY+bN3/0ueRhsKDxQahu8OZ/abYC8iBBj8+TzaMnbF2HGfqpvAhtxWOzCh3m8ZxtrOF2qacdoy6en7xuOObtHH5fokemhjpHvuo6T42NStBM1inB8tObs7IwQIzEGYow2k3os7F6/YXN1PWM8e9FZkICE2caG97Vbbh73uh8xNEdqqU8B1CO4NlNZJ9xSRG5FK23ibhsrq3ses6FXk41bhnKAS0KkjplCZHX+MbFbEkMgxUDwUcDbnNl2gXS0JqREWs1aryKT2zEsWYToDlL29rGA21hnJ8rsCG2u+ewk9x2kSBsgK7f+bXr/hll6HaHdVw1KrD6n/S7rTmmyogyj4QS1KAQYdhmtA7uQWIcF4/NXXH7nO5x/8o3pwrQB4ahhOELbFJayaq3orTm7Lf5tnj25g4oEseHiDUewaFlpu0IkGUiu9s6qitQ54kgRSq4EbEYvKsSQqSFAEKQYAEt69/D6fVohCk+fnHPxEsbdji5E1sslIQWuU0QUuhSmG1m3A+Or1yzWxxQVigao1c2R0Bocu7ObuGjxW1wJUintjc1gfqNHA+FDAB9Mj0S0FV3E0ukIfm+VqbAWUEIUGBXBf14DSStVAkgk1J1tuJYRHNgKqUP7BNtrutVDtDthmUf6FCm5QN/Tnx2RUZYPzqlF6YIwSEE1eDHT9m0MASoUMqFUNEZUDR+MWpEaqO68gAkOC0G8WGZObD5MFVEIjvsLUG7BKPYatu/rPK+7ig27l4gSqDXbfRje3cB3c4aq5JyJWDEijzsWi45aKn2XCBg4e/3dz1k+OOfo8WNzb7VM3rzUaqdKglIKig2NrqgVXryw0dIugrRy1PQZmpNsoLr4aaaq1NKiiT9gwHX7c4o+61wRe+s5h7YEOD05gaqMux1JhGXX0fcdJ+sVZRwJpRJLIddCrYXh5QX1w6f2822jKKgoWgtVfQB8VfahjFKLcQbC7as9wyftT0/HfOi5RX2VJHEqou2v6llE9H+zH2/ftK+7pVDv0+r7jtXJY4bda0SEfrmiv0l0ISIJ0vERZ1/+Ctvdhm7Rk/PIOI70XWKzHVF3ZIqllrVWqkKslVqZojX83/St6nCL9PZt21bx4KgUO+CCBDs8tQU++3Hn3hK7X6xqLbPN77Du5gyrUrKd2LvtFq2FnDNBhN0wEkMECfS5cvn9T1k9fkRp8IID4a1sbxcqE2JvoXaIUJsDU8OaPBzXOqc088X4kZ/QKpkT5jdHFuppUdtMIRp9RmtBJXvkGfY21qG6Q6sUrtdrSkpEUfoYWCwXoAsoBSmVOBayY3njq0t0GAmrJVrKhBEroGWE1HkE4ICJ7GN3MqXH0Apes8NqtlMVrxAzgeelFuZqMrRUukEi4odoLZnKgLIkqUypWZD9A/FwVuoSH//Mz/Hy098l6IbardACSiGlyPHpKU+/9CU2myuuLl+x2W55c/WGh48fs9uN084ITnOqJYPDJyEotVjWEMJMntoPTPbxw327TzCkGFZdirNQpGH5QK2WIUw0nT26Ts0W+UvwqPNu9r1jNVnRWhlzNgpEgO12y9FyxTCMoJBLZSWCfv6cvNkhMaKlCc/KhA9aAaQ91nhtwYF7462FOHt5rXPpXdnDg9Qu+C3gfLrgc3qsOleQFSbqhVF+qhVqEAeSK4eZJGPXs1ZiEGKXSAJddNxPLeIOQYmSWMaA1pHx5obx6op+tZzwHg3JbBxm52evP1cb7bwS1FOjhvPtf81SeoY/hn0bTlGfOE64Vxjxv6t4pEr1Hwp+LxUONTLsuo6f+4Vv8d3uElkNXMQ1Y1WomSTKerXmwYOHpD4w7m7YbDaEN4njkxNSDIzZaG/GOzT7NGwPnYMeM4oVribzt/0V462iyVwAm5+3b54W6BnP8bZjnZyhFofJxGGcSgzvngHcuYBSSmHMmbEU3ry55s2bK8ZiFeabmxuu3lyx3Q3o1Q2b5y8JBGi4oCoxREKIvqlaiuS/EHuFFLENYM4OjyAsfDZyrkeLXkmycNpwwuDP3wfN/TeYDDdFKH6VrRLWosXDrSYDnuYwVWJjDFMUVT0byLWQYmS1XpNiZPvyAq3FDpVmD4HQOPRTpcOdmfEw3Fn6v/iJX3L2Wpd6duuvFcKe9fxr/+jX+XU81HeMagb8JUR3lJW39ttBrdVKOHmw5uxY6ZfHZBI5F2rO9F1P33X0fc/x8QkQ2NxsuXh1Qdd1Ey4RHN6QCcpyOgszFjht5T1YQlUpZVbm36/uS8MFpzpAC3rmwKZlDFNRjvmwFfchwpwtvOu6U2TYKjg3W6sgo5GqI1fXN2itpBBtg8SE5MrNp59STo+RPE43M0ERqaiOqGQizhp3lLAGIQbHi6ROBO4JDI8BCZHYUigqUoHg4DmjH0YKIRBoNAy7WClF8mhFnDn0ViRB1WB0SN2LVg9sqQpShSiBooWiiiF7VgAruSIFQoyEvmO5WqEB6uUlw/UVxESoCSGDFFRHYhIgewFXIQmkYFFDUKQRa4OAGKFeQuefqKXTdsiZX7XIfQbd5w0lQAqJECwqpRRUBSqEoBSCUxlboeancJF/6ksZri+ptbCKlbOzFZ8tTsl5w0IiVeDVyxfUOqIa6FdHDLsdF6/esFofEUNkt9sgu+A84EqMipYdWRVRD2TE7UmlemQvweKducvFU16Hs8KE51bzEwRE9rM6+z7GQMl2R1QVquL3UbBCGSBqRdp3hbzu6AyFRb/g2fPnqMLp0Smw4s3lJbvdwHLRs+p7hsWCvFyyfXlJfv6cmgRxnK5VAiVUJFRiyuQiBN0QZST0o0WOtRBSJEpAYmXMo6VgKpSSiSEx8YlkPnEsO7YIYD4x/AI3h2xXaqLi2LWzCzkjkwe5S4wxkAtBvNjlrW1V7LYqWqEqsUvUIKgIIfXs8kB59Yq6XBBDMJw3gFAJcWTMwiZUKNeEbkHsFmgthBiIAiF2lDJj0FLU2rsiINXsWJVaMqppD25p6XKj7lg0OgWMLWjxEqXUMLMbDtTGqDJsd0hNBCoPznu2T56we5VZrjviasFYMlqtPpBSotTCMO548eIZT59+yGZ7w7AbrOKvSkwdORdSUChbYuoIqUOoRAkQIxIDJWeGYbAOEzWcsXF9VWz/hqDUak4shD1DYliiRZszaV+kNWkYQyBIcFLWT7CAAsLx8TFd6silEEIgpsj6aM32ZkOphsvUkhnySNxsCK9fow/PvMrDXNyoChRqHUlpQHQHeYuMjkfU4lCDICFZRWu3QQNI6EgSHQfKREkQAn0K7JZGGFbM8QZRZ6VbOD8WZcwDMUTrhmmUH82oV7BqLci7HSbv3VJVduNokXktoMpYhKyVLlorZMkGmLPdUmohl4wsOqRmJCyMLN34Y6pUzeScEclo3pmjy4rWPB1oIomild32GkERiW5Hs02MHREr7ux2CzswJbojVC/CWcSQq7WB2katiFrfey0DlOL1uXxngP19WarKOFwjZMvokvLoy4/ZHgf6qMTVEWDdWCkFYgiMYybGxPXVNduzLcfHay7yAJ55ad3jAOdswJNiNlZQCYQYyCWz3W78uocJOxSHu0Sh6yKLhRP/PZAxewdCUEIM7MbCbjpbssEAACAASURBVDcSY0SdUygxsRs2iI6gQqn5Tg7uzmnyar3ioy99ie9/+im7YSBlZblY8ODkhMuLC6IIpRZ2u4FF38GrC+TkGProSXzDFIQQOqtAxYAUQYO457e0WD2gmwQYtFiVSANZQDWDZirF2vqK3fxIRJ2FhlY/XSwUz1XZbrM5PbL1QKclNZhDTlwRw46xMLX7HdJSVSuGUbwDxHDWOAqrZQdjIQ8DVaGIRWpFCw+enFNTQov3C4vhsCEEQkzEED11FrN3cHRXzGFaPzN4JcWjNyfPSqFkK7ppDQzBIn/FUu3Wx2z3lbWRbXYDBg4WRBW6nioDUguRK4IIQxbygdp4LFtau5oCy/WCZf+UFApdl6ilTIWtmBLRo0MR5eWLV3z1q19l0W/Z7naklAghWZTn+y06b1etamDBSQxEZwtYMXTG7VUr1R1oLfjhOTNCaLGeWrPFbrTGD/t9MqqVEHdoWBIYoN6w3e1YLEZyebfJoXdzhpjQwtMPPiCK8OyzzwmqHC2XnJ4csewC5EKKgSGPXG+3xMs3pOsbSCcWdguOD9jJ76GB3fSqxqgJAXGiZQNIW4HFThDFoueIXUKrchIEnLxt+EPD/4T96nIQcQC9GLWm2oYThJwrQ9mgpImCcUirqjLkwfiatVI0U5TpkIuq6DiQczUybNcx1sxH52ek02MuLt5YBde3QYzJydLVC1/FCLJuHyvWtP70VnmUiV5qEXxB3D5WeAuoF8gkhilNnpSNvIDT1GtUq0WE0fqRa8YEOnY7p20d3io5gyQHhJSAELqeELLtxVq88UApTUlIhJR6ttuBN2+uOHvwgN3nn9O0AqpW+7mqlOptkHgS6DitVXkd1nDMPohjfszvYzoBkdbi13D/BmXFaNoETYvAGjksSxACRZVxHIlxnAo+X7TunCYLQpLAlz54yqrryNstq75jueo5P12TgFjtIuSxsN0NHF1cEo7XFFGi5bktO6WqRyA1IxW0GrBd6wgoeGqmVa3JHr/gEgx7JKAyWoUKobaqshSjcXgp36LyxlzXKXLBpakazVtcaiqFeJApFBhHrHZrhhoZN88p44hIx1BvWMRIrJUUCgw7dMxsysjVbsfPPP6YzW7HbrelERVqxdKVYlE8zhkEl4Py7iOtlVosXYZqqjcyEiQhGhHJVKJhftrkpdQIwF55tv0SHPL1+qIENOhUMKuq9pqOEb8ruP5eLa1QFIkdhOpiKVCpoBaJBZTQxFVKpZZKipFcKzH1vHh1wemDU45PTrh+c4MolJIJatmEqCBE31fFC5mKqhCCXX+t2Q+y4M9vvNEApNmmiHWUYA6TMAc4VkSL02Er2oRe7m7ju5VMxU/gaif/yckxZ2cnLNdLUhfpukiXrH81hMDR8ZqjkyN0s0GHnd24MpfiWxo2eXdpp8B+w/ZcIJkoE3r78UbBaV/2mnPztz/bcQ2dqDn7hM9a1dLiFkkeKrgugW615PjJR+jjn+VN7nl9syX3j9nJks12w845oGNVXmyuYb1i8I6U8/Nzj+zNGdVJRAPaye5mdgfFRKGYHhfBhDwKTd1GNc52nzaWUmu25zkuiFZ3etX6mz0jaPdZdVx7rlL/UV/gn/5S9WgvJMucCCa24PtL2yXau85tr0RvkBCEly9f8fDhQ4u2a2HKvFw5Zp9DeEuD0ouctlcd7xMBEqqtKGZ2bJzi6QscPpnt2Qqn2n63onvu4N0j/7s5Q50rsHhqErtE13d0fQ8hkGuxjVEKsUscnx3TBUF325mXNKVNdmNP4KiEKaTdv4DtPSeKjLRfsm2gOLmu/VYf9h6bHe3cLta25JxeGTnHgOBykO4wpY7uwYrT8yMenj8l65rNzQ1l9ZDF428SJNHHMN0Lq8fnHD95zPrklOurK9brNYt+4U5tvt7WnRAJYqmXUSRaX+r+TSt+b7XIvOkaNsKiL2WvImw4VPDIfxKHnaCRQOO/AcwH5CFa2H7vsRSyynS/l1IRojkZ5mJIq/CDJ6MhEmMkxsTVmxtqqZydnXoS1+w722lqi91jbwAuuBEmrNefPf+czJVi+zPM8lyeXu8vEXfiTQrQ74+7sAburlqT80xJkUDBNAlrMJRvVBhKRboO6TpIiRJBtzurMKpMqiH7AgszPucXIUxAgeEAItPvZGx3nR4XcWyB2fFFv3BWZQzT4yHI3t8dj6x2cYXGZ8Q3z+Gt2HUsVqcslkuOjwJpdWRYqhZOHn6dk6OHnKzWrPoF6/Waj77+MWdPPuDNmzdshx3jOHB+fk6KDsJrdXuFPW1Cd2CTaGc71KzjyAK2ODnE2dZMNkVaBGLYs4SESDI6Tgiuo2jpsdCikL17zFPAQ/SHU++/t89WL1hV1IjXvhdLLobLleoCKdA6jEqxiP3Vq1ecn58SU/CIc5Zsm99vPrimKE4Bt7EZwQsqbq9WWGkB1Nv7uKknzUHTvvObM8h3hAvtPe50ETE9wyFnxpopquSq7HJmGDJjhazKUCtDUa43Oy7fXLNVJa2X1qfq7VFUT3GqVQ9r9XqRNoaQ9RjjF88knZo3jBjcuc8z8suocsup7fc/GgetSRUx7YlJX5YZ8G0nzKEtCSaAqiGxWlZOHj2k648oVy8IEkjSGem6CkfLFalfsFwtyaq8fPWaFy9eEUPk+HgNlMluWlyoAWuH01Ipaq1/tWYQpUwpL7ONVab7oKXeU3orzdJeVa5GwI8ipBjdaTo+HMSLbsHU0wX0LjvlfVqeEndpCSFMqWaDq0q1gGasXp4MYswB9cYIKiFaan11fcPNZuTo6NiKkareO9yUbWSCLywIbHBG61KJNDdkhVB8W8/Os63pMFUXkzXJfWzn7neUTa/mf3+3vXxn1ZpdHik1UNT6hGstDFWJCF0qFCo1j5RiWoZRBF1EvvH1j3l5fcnNdmwHARrcvalaiE5GagGpVixxiS2lGcyMVSWaErUWkDxBrtOGUKU2LTzHOMGizephe8CUNiayJwWpMispHyKYBBaxi9FNFkn56KOnbL//hHF3yfbmFZ0G2O6QIHSnx0gIjJuBbtEz7AoX9Q21Vk5Pjun7nt04TNiQSLTr7JuhumyXOue0aLZ/R6hEA/D3UyeMCF5dxKNooSk0TamvCEVlPsykcUm9px1Tv27Y9CGaWbUaZugd+ApQrRVPa3VKiwUJEhM5mw0xtgyeRkGA7ZB5/uKSR+cP2MkNw87pLrWgEglOcTPpPhNGEYc+tEn1edGmlopK0zlMe5j+HPlNfe5uPyvO+IcBv8+cWN9w4XcM/+/uDMeREoKFwwJaCju1EvdRrBAXMGZKHljWTB8im01GBT766Ev83u9/10mZdiGaJ7c5Ct6W43iktmLNXnTXmvcncFQcQEUI0TaV0uSB4hQ6G5jvGIlvSuOpN05bZg6U5WApF1PjvURKHjg9iXz0ySfk6+esOuU6rQn5OZlsOnUhIQp5N1JFKUW4vHxDkMjZg4c8f/GMGfrAIkQFCX5QIj4ioKVHbuNap7RMKZOKUWAPnFfDHfdvd1W8A8vS8ii2LbIaA0GmYht7xZTDWobXmT5kKcV6wUtG0kxLazoC0NSClBCsIDZjd5ZtXd9cs1x0HK1X7HbXfvhV34/+njpDYmCxnNMA7GDUbH8Ntw/AhuW3NfeiWwik6tE/FoWKs0Jaq+1duMJ3FHfFNOy0kv2GyuOWsSp5rAwysliMJCJBTQj2zXhDd3rM65sNxw8f8OjRQz77/vcnrG+q6vkv3qZzAT6nwoH3EOZfbCp+OPCrgjh+EFxJoxVI2mliJNDAqFbeLypEWsdzJYh1OjSQodYfBmkPYZmEVkfRiuYRzTsefXBGfXxKlCOGqyO2F5FaM+tFb2UJ9fJEVcaSiSny4uUFy8WSh+ePeHXx2mwcZkxH/P/tEofJdkwOsZ3q5rSsXzmE5M8rloLtHZQhWN96VvU+aKP7KsXxw7niaS99gAbGDpgUF5ag1UoeLdKvokj1lnFpHWNmL1XDE6d2VpiKklUrl69fA5XUdeRdnirOb+sYTt/TtpeAmL0M+YhebAuU0rqE5n1sytqBsVS3safDPm+n3TPSsr6fJGY4lMxQK7lWigq7eMz1YDyzC13xejNws9kiKmipaN/x4ScfE1Lk9evXrNcrPvjg8aR0uy/b5Ffsh94V2buQboBWT9GJV+RAuiS4pUvoF9M3YPTNVapSvZk8ClgzuGvg/XBx62CWokhKFvnVQikZTUJa9vQL5ezJE+ThY9LTxywfPjQ5rDJan7EEQrKK5FiVz589J8XE6empvbLbqpmytiJaGxi29yls3VYjMTzTQXR7heknpkiFSnAV5lqEgvFaQyvChFlQdO9MPailarSaxqIw/G4urOhewGyUs8o45onkXG9lTeagdsPAy5evrLuoYYZTzK6zM9vf341L5d/ORZL9cbC3MzTDNq1Jwr63NFucLTzVD6bmC/uM77LuXE0eS2XcZUqB5cMnhEe/wNVuzauLN/QPf55w+k2iBHpRehEePH3M4vSYl68uef7ykhcvL1Cx0ZEoLpeV7cvJ1aZ+XfzkUpf0xlrnqhE4jV9WibEnhA6806FM8l5vK107+VptBKaoUjSS6S0FqIXgJE2ZWgIPb1nAbylmBgpixQytDHnL8mTB02/+LA8/+Vm69RElu6S/n+whdsS0IBDY7nb84PPPWSyXLBcL6lgopZrYA0B1xsAkxiuWDtdikYNUslYIidB1U8eSbUpFa5NnmxNl9agmRQhSqSpk0kTMxiNGIR1i4A949KTitlOQiIjtn6rqqmeBSqTUSh4HL2L6YdmqHFXdVkrf9+Ra+cEPnqESJkEPLdrqJea8pCmWO3bszlVCRBs1R421ohPm0drxmmyfub4UBRFrsS3atBXzlOFZV5K884F3tw4UNQZ/t1zx8MMvs3r4mLx9QOqODMjWwIMPv8mqPucoGmDOcsnV1RWLfsFuyAzrQhQ4Xq85PU1sNht3grMKhVYvf1Rr2zPdRmes+yBSa99pJF5LkXPJjKNDRhKmqWi3pcWN6huDkFWoam0/QTOqXkmlOYUDdIeuGUmuhM6KWIL4YC9F6ki/WhIlUctgh1Uw5Rlp1fwQiVGpCtvdyKtXF3zw6CHj5ppa7d9rcaDelYgswvQZOVLR6FCHeViIvkmGgVHMfmjjpTZV69ZYNkeB9isFlIQyQg2WPUjLkg/Pxuo2DkVRt1Mk0iRCDccVtCjibADD8Juqk4EcBqmIq08Hjo6OefH8GTebLevVci/jExqFzUYyVC98ydSqZ+mdHcJjHpDQ7ynWNB6wOcfmzAU7+PwT2s6uDSOM0z5+11PvjmkyHB2d8PRr32D1+AmaIqtloV8tOVok8psfUPJIHZVxM1CHkSSBvuvJPmL04uKC66sbXr26QIGT0zPbHN6TDN614HmwVYPLdONOALvupUYiaMnUcbTTZjL6jEXe+hLDD0PwoUC1906J0sy8F3Ec1lI18QVTrWlFLosEDAQPTN0cLa2aKncN/LZNkkKEqlxdXXN9c8NyvSLEMKVQ+4gErdAljRdoD7eUWABqdhxJp2rmbZ4ZTtWxopiNJW1hiSlvV7U2zzaq9jBtbB0cMuGC7gCLdaZAwOiC6hhu8OLTnJJOh4jbLYRgc3KOj/jss8+5urqZCmItrGhMjf0CTHO0/mKUmsGLNTK/xd73rRPF7sXgM75xB9l+n1aYuQt96k7OUEQ4/+Aj1mcPqQRKgUVfOH74gEW/pFx+l+2bz9nUwPVmYBit9zAXJcTE8fEJfbdgt93x+vINn3/2gu1u4Pj0mG5hkkEzJ/D2xW6YgohhR8Gll415XtGSXY1Z3togeuvzI1ZsCSGQohDEFG8Ma9Tp1DlUDpqdOeZparWoodRKLsUyWNXp8Wl0a3ustrvWG6lq8Yig8vryDWOurI+Ogbl4ovtS/bj9JmL8TLKtnj3EuFcA4YcPPH8ViMlUUgLEYD2vIsmji6ZsziH6QjtHQkS8YIUYp8IGfHkbnLb0tnH7sMPOD7xaLIzM2frNg1r2tl6t6bsl3/723+H6ejNV9avuk9Xmxofwto19HjrMNr512LUHg6kfWUGFKWqcK89v8w6/eN3JGcbU0T16xBgTQpuXKjx49IDF2VNWqwXLtTD0Cza1MlalNjktDZRSCSGyXNos1iHvePb551xevGa5PGLmBc3zMBobfv8Ubz3GDTJXx50mTGFvydtXw085Uz2pwGDVRl14rWaWrD/IjSKBxWpNt1iRFiu6fkXqekt9UyLFNBUyGrw9RRdqaig5WwSX8wDYOMnq0mnjmEnJ0Jk2wsEG/+zZWa0dstSZFmGb0p6PRwa1HXpv26kdkoAN9N65jfu9w7JxCQ5vSQwcnxxzdHzM+mjNen3M0fqI5XLFcrVmuVjRLxZ0fTcxOebDKZJzOxx9DIcXQs1BwqNHjxiGzO/8zt9iu9kA8362pV6ca62xe3oBND7xj9p8e8Uv4ZYDbQIg0xiAMFeh37Xt8k6YYew6js/OibE3blKtTmmBo7/v70frluMHj3jWwcXmktPHH9CfnJMjSExz3i+ZRd8Rk4G2ry5fs9luWS0TfWfPCz6sXlMiWFJDriCap17mVkQBiGrabNRgArB7YTU0p6iIupZhLq6MU5DQGdAarMwvWqn1MMUaQggsVycsjs6s2pg7oo9zSF2iTR/rpFDGa3LNdm2dUgMmsSZkNAYbPJ961utjKIWXL15wenZEnyJCJWvA5mEHkEpByEWRFAnSbORKRHvpkuGTrXHf0y8x+029tcUVjtTwQztOzQEGrHXsEG0sCLFb0y9PUC2kkq2dDlj0C8+aIqIjY07UskLEBHGTqwqJ2F7SxYIQE/2i52i1RPNAWK/4pV/8RX7zr/7vfPt3/zY//61PWK2P7QAbdmQRqgafUOkDP9o+pe3VFuXJW87RB44VT+tzpVQXmsagHUEw0SpFy484LH/MulsBRSCK8f4qGYmJqoXURZbrYxClTx0ffu1rnJ+f0B0tkS6xFCUlE3dNKYCONn0tJharFavVgqvXF1xevoIKT58+ZtV3JuiZFjaadLO1sFiVGDtKGa1q1ObYaSVIIqZuGjIF++nTHrPJow+TBYsOwppiTVU38l3Vzd6jpQQD0P3ULqV18ARKVbrUUUshxGR0GhFCc5bqeA+ZlGzaYbdYcHp8RM0jfQ/Pnn3O+fk5j88fUHUFao3/w27LJnWGI4VIrgOqxRSvtUKpBAksFouJk2gCAPrWp8coUzFSavDPGMg+I8NSwEIlHWT0bydKpF02VYxDSDSIqIKk4EWuBs5CnER6rZsnSSBEIaSOxaJntVqi2XiCZw8e8p3f/w7f+f3f4/T4iG/+3Lc4Pjlmu71ht1v4xwiU7OWPhvvVQhBhtTpyGys4vjt/gU1LtN7p0NrzFEqZU+w2LvRd1531DBtFQVBKGSkKEqLNJUnJFWqhPzmhoEQiWsepo6NWJflFjbEjxkQQODlZcXx0xMsXl/zgB8/42lc+YrFaImlhRFuElBLRcYZcBpMAD032x3huR0fHxGSk4DmMngm84pFH6jbUvEKCUFRdU9FulFog1+6HU+yDWLfbmGoxorLESFGdpPhR7ycvSuwjWq2TwVo0ISWryhtOZ22bVTProzVP5ENevHiBAA/Ojuk7S19jSvR9bz2nIRKLpT1N2j14GnS0PqLr0zRhbR/fVe+fLSr0/YI8DqQQKUUpCkgxScw8kEm3SMSHtlrpq9Q8BTmqOIzhSuPFDsMUPIqr2aJ4rM9//zSpHoWbZqTwi7/4i3z6/e/zd7/zPYZx4OlHTzk/P7P5J1hGgI+hbYW1oMZFPDo6JsVkzAYp7GPDACKRIRe6rqcJvmipzB0pSh6NfWKf84vXncOflpbUWii5QOq9GmUT50zAs5BzMZVjxbhiRS30npxZhWj9y8YltGEvX/ryl7l4teDZ85d8/eOPuHhzRd97md1b73KdxwYEx6MkmPOKsSM2EVetEz4FHoKrEGJlLBX6JSEExrwjhsQcTfZk7W0EwQGu4Dd+yaMNaOrMadSihM7wwkr1lkxzNBG73q04FVMyYY69E71VL09OH1ArfO973+HVxUu+9pWvsV6tJijDKpnWHinT0CcFokEhLtKh6ATA72+S1vIaY0BkSRQBCil2SJu4SE+WfkrVDmqpRXlaIZfB5qB0nTvDWaKvVbbsMLIHixaDPmKwCXVe/QUftqaGt5eSOT8/5ytf/Qqffu+7XFxcsB02PH+x5mc++YQYTYTDIC9v+fMCXCsGGym/iTr8cGAyKU+J+YZSlT6tUEwQJqUO6Cbn/UXrzseiSKDmTMkjU1P0XmWxAd3e1uG0GCdZSqNpzE3VdpUDQZJ3hmROTs948uQjnj274NnnL/i93/s9Li5eUcqO1FVOHyzp+7nTpOpo/cveb+nB64+4gOJjDPH3l0miSGvy16rOk5tVcQ5pKXh6Wcjj6BiOqUe3SrOdu+odP9YU3wjtrUCh2D1RysjUh06gFAPbT8/OePz4CZ9++gO+/e1v8/r160mAgfZ8EYR5I2rjuk3Sca3g8paIqDQeHP5nk41rUS9+MoaDTZPt/vZGBGGypbXIhimFDt6fLBOvMPghM+sgjmO+VSCpNVM1A5WvfvUrE9wCcH11xWeffeYC0HvOjLdMIVN5jln9unGKmw6icwsbpQYTWJkQxhBuNzZ9wbojZmiV2Fp2Bj6HnkCCOhKSNexrKTamszkWVVJKrm5tOMXoEvCSK1J7pLZNAxI6tGZiUNbHJ1xc3/Dy2efUXDk7PeXsK0d88vGXePnyFc9fXDMM2kI+S920dSpWIo107bwogRrURwsIpVZSDMRgUY50HbADOoIeKp4UqCFOk/GqBGLsqWVAoh02tWSCRDSC5oxosQJZU9wHyljMpjGQcrXU1GXejZVRePLkMZcXH/Hd732XXEeePH5E3/d0faDv15Qq1Gg0ajRZ+qwZ1YGgHaIBFSfLT9y3uXoYiOSKDxpz2oj0BNlRg936B1lAccqJULBM14Z2FR/dWl2zyfZxMNvXapBWbFe4Mha1uTjOJ8XV4kV81GdQHjx6QFx0lFzoQqLvE8N2Sx0HQlp4t1i8VSUGS88nvqnMoyJEZtww+Gx1VUimAkIed2iKrjtg9+u7rrvxDBuZRYxvFGLyk0P95KhTqoqask1r7QnRqDVG1vXBQFhJXb0HFphObZtoJXz8tY95+PAhm+0OVWVzs+Fv/1+/y247sD5KLNfBJjZoI9IWwCaizThDS+29FcxTaMOxsOFBujO6gEZQ5xwe6EaxqM9tHYLPrBBXqnbqQozeniUgCQm99bs63cKGwbfB74ZLWQ+zKw6h5Dzy9W98g7MH51xeXvLs2ec8f/6My8tLkBELXmYraAv5G5Wi1r1WLyZeXJmU0b1QovZ71Lqzz0FENdEmqRzcchtbEK4mkhrFJLUEL0Di9vT4K5pwrrj+YbvGyCyg1drsWlRZa2W5XHByesp2t2O5WvHkww/p+p7rzQ1z77JF8m3Ql+3lfbn/Vmye7oR5b1efoeRFGGvrBa3Ri4DvvovvOANF555hVVLqDCt0SoNVD005pAqEmOi63oskBoKrV/RaVU9c1DOXPDWFlzJ3P9RS+PhrXyfEyG7csFxaW9/nzy7ZbgupTywXRsexVh8b/zk3eDvR2v+zlKphn14ljQlh8Kl7SxTHQvTwnCEwaduhEFOPJR+WksRggLSCd/JEYlqYoozMUMM818KcYS3Zla/V+4orpdg4gE8++WRKbVRhyJlh3LBcWkZhqTq3NsZMt2gpVEuTG8+siQVY7yzSAQMpFELooXZo0YO0cZO/aAFISskLkLDf3NDCtBgTKXaOCTYVIUCgi9EVboqlx9XmUrfgI4TAhx9+CCJstluWqxWL1YrNdrAKdmwye7NoBDSMeL6PJh1D/2r/bzUMg8UixlQJhLjw9PnHcRZ/eN1xBoqB6iUXYupcb7DszZ9wxrfTGlJnXEKmdBVCNIeUnAJTa/H0qTVo4WAqUzUrpSUPH33Azc01V6/f8OTpI46OV7x6dcXlqwFlAT5QXJsIbGVyujMYLEwdCJ5aW8WzAesW/VR3rIeIGQKu+JIJMUEIlLxFxOXVwAHZ4FGE0SxqzXutVFZRjjFNrIOmat6yi315rgfn55ydPeB6s6ViONV2MzIMIyk5hqjNfjJtHlMZarNzLNppuNakjYgrSNCbzb2PtqqSq2Ufh7gatm9FBnExhjpd36r7YzV8JtAU9beOEYsqa3FIpGbHjZt97c8Pnz7l0ePHfOlLX+b16zecnZ6hqgzDzoANbfqkYBGi02ymI1ImGKQ9p3Fm5m6zgISFMUz8ZyYh4Hc87+7YjjffxDGlqYNAnDPYAHBx2oxImGYqWPdJ628V5xjlvU3EBNJWd4ziQDgaOH/4mK5fsNtlPvv0EiRwenbKMFYuL6/ImUlkwSpa+/2T8+duDzQowYDfQBSrrpVqU95yOUxxV3ByjSghRk+HMiI2KrKNZWhUjBgErZlaB0oZ/OfF5d6FPBZPZ5sKiR+ALQXye+aDD55wc3NDqZWzB+cIC25udsQEXZ9uHU7TgQfTJtmHhlqaZUVE9YjUnGYthVJHSh3JtYkMH+hyn1J8YHzbFy1w8ZOPqpVSR8ZxIBfr36/eujdmi/hrLdSSp6pwk/vKOXN6dsbJyQndYkG/WJBLZbleMwwm9NGq2G1aZinWfWTO+Q+yT3O4LslXDFMsOdvPi73/TyZNBqTayVtqJuhIIrvogRhoExKEZKfJOCAlk4edYwA2pF2rkocMpaJ5h5TqF7hODnYs5pBKsdYuauTk9Ak3oxL6I16/Hrm62pnT1cB2O1CsTdK6FqROGBKiPp85Txpuc+Ubsho5V/MVWqpr322m0+2QlgdPEDtUlKgmjNBkzZQRgqAhQYWyG6jjSN5tLb2uyjha99A4AthgqDYcqjR5+aJU9SFi48DD86es1w8Yz3DozAAAGwpJREFU8oDWwvHJCbtdZrsthNijIVA020HVZm1UmfpeDYfO/jVO3UlTO1b08RFlS1AhBkXqcIhZMgC5ZmLsvIBhbY/iUl5Nr7Ai5FoZhh3DODAOA7iDG4Zs85CGiopLfdViclp1Hs9QC8SQePLkCS+fv2C5WHFzvWG1WFOqsh12SAqMtfhAqsxYrFWvqnWqlGp902MtjLkw1kr28bCBmU2gQUzKq4wEKSSpNuThHY18Rz1Dw3tCsgu2j8G1oS9BbM5BHofpyyakBXKulFwZx0JR0JAc5MTSl1rQXLwyBXnMjMNAKZlh3JFiR4wdL19e0PULlMDV1RWjE72H3cB2u9sTDqgT2Ds1oDc+08QV2Q+129Ahk4s/xHJyE1hIXU+tNowb2jjVak7NgfJxHMh5nGwMxjnM2W7mXIEQnfIUKH5jm10aPlwZh5Gu63j69EMW/ZJxLIxjZr1e8fryDbvdjn6xQFXtgGyKOdNrFT8094UGpl/IWARVgEQIinEYIXVtBNgBLgW8z7h1b1CVoNbC2GzcpmFWV5kXhJxL2+4+PM1EMFQjTQuTyT7KOI6cnz8idT2bzZYYE2+urun7pWOHc2dQafeGGt+0VnusuBPO3gttv0LrkgLUDkabuDja51Uh3YEhd2dx1xCTe21Agg+WYVKOQS1crtmkkko1NZl2YabiCQGVBGExK6AUS52mDddubq8455xJqQcCL19eULWyXC6RGBh9TKVFluxtujpFJdXliXSqfxmmlHMBjSiWDhgZ9G6KF+/NUussyGP2bqJInQoNlZozUtUk04pxyZA6tccZjmRCrE3xWkMil0BWnFHgqVCx5v5alFwy5+cPQU2xfLfbAYGu73n9+g3b7cA8ZFz8vJwJ3bXWPQfYDNf4rOrvixfrBgxj4jAhQzU8N+dCcMEKLa2YOVJKtuxIrfDl3sYxflAVUjIba1XGsVJqYByriThka8jI41wUjTHx5MmHXF9vWCzXjGPxe0S4utlinUpG/G4wWqvoGHVUZo6jz0mxNsvokJhO91/FuK1B0p4m4hevO/IMxftTs1WSHawOIVLzgM000ymKiMHK9FZ9VFIUa+avdtGNNN0xlmJKKKoEtbat6L3MEwG4jM4zC/SLnlIyN9dbQjIVnEWX2G62VFVi1yG1OTz1PdEwEW/x8s8dU4dqExtl6lWu9TB3SusQUky9WLX63JFILZkU7Nrh1cfYJah1qkSmFIjRW7lqcX28zgQ9xXu/a5Nks7gsOiUnxsTpyUOurzY8evSQzWZD6npiCFxfX7NeH9N1iZisF9pat5Kl87HRLbwIEAIpKjlWYtejahFLSj2hX7nSSsdBKte4rbqULArU6tVirKgSHV+lGjlaTOg1BitKGunaozMvoqVuQZRCEJ32FoKTq40sfXJyxsXlJZvNjtOTM643G1brIzbbHV2qdGkW7EjJskB89jUwHXxt9krE+6XV7h3jskb6bgkpkseKRCsQvcu6kzM07xzp+sQwDpO8T7uxU0x2MQT6ZA3b1mYXkJimWEyiQIW+61iu1qjz+trgplqjV51944mSumTVXk9p0yKxWC4YxpGb62v6FFmtlqzXvQ+REkRDKyLj02MQCVQJhJCdhuGDpkKmkxVVArkOiPTvfBHfp2U9wj0xCbvdDSqQ0sImnVUT3AjO/u9SNDghmL2C7zI7JM1hdV3i6OgIqQWRQvBuIytcWOQpe1H4gwcPub6+4Pr6hpPTU25utiYCkRK77cDR+shawVIiqBdQpKnXmFp6EKFKQCR7plEpdUCwSKjk6m1ly4nBcEgriNB1CRUYhoEudda26j3AMXlEVW3+tPiIVZup1tgAvucJ9H3PerUGHREpxH0x4H0GAHB+/pDPn33OyemJ9Y6XSt8vGcaRRd87PGWzdNpwt7eHSs3dJxbiVC/yjbnQx2jR6PD/tnc2obJsVx3/rb2r+nzdRIOKA9EgGI0ikoFExTgQowYFQVCJaAZCnBjIQAfOJKgjEZRMdBAwBN9AREFx4sdEJIFIBhIwOvCDgIGghCTv3XtOd9XeezlYa+2qPrkv93bybkJO17ocbnd1dVV1rdp7r4//+q8ZYzS/4nnH8cnZ5HE3gla0HGx1HgZED4gUGIyWJyW3EDC+w5wg62w4vpTI48DF5TVX19eMY2YcduzGgTGHE2uKMFSMImQG2ZEkOwo++cSZub684tHNJaUq+70z2zicphqwwsrCMFxcZDAtgVKpdUJ1RtKOqVbK/JiqguTXnWc0SQxg22qFahAq2e1INHKbaSkh42ATkoi14nTas+TNmIacGYeB3bjjYrywckfvZVzrRKl7qrcMaDRLeJmJQaNyc/N65qo8vr3j6ua68xpmyRafbNYsvrXGrIWiBqavivXBaeZ6d548r6CQfMFcG7XeGjSIkXOMC9uCJRbyEEGGHck9PTSD+Lj2FgpZLDtf1bsgYobPMIykwbyEw+HOKlJqZZrumKY7Sj0Yr2Wr1FYQlN048ujmEa+88pjrqytaLUbYK4nSSZUbtUyWBHPcsYVVavc66zwxlUiIGkJgHDKKMhUzdFI2Apnn1fCJPVDo6XIrsbMVpE53ZjHkHTnvKPPedhbDmyU19xOSx5Nsdi9l4kBhyBm0UuvBdOUVD+bqiiVsHJPWMIhOWCc5J4Zx4ObRSJ0PlHmm7UZoobgVjY+A1oqmhVVb20TOl6hmar1jGHYMaaTN00m35sGIerOtVnu3QYOkWB/dlAbjfywF2kRNRveVcJdEnPXE4zjTdAeaGdIISWnekDzlnYdYrD1lTjZAS60MaeD1r/96Xn7lZVI6cHV1bYF3qaSmlHmmDOaRNGkrCwQLpNfqD52FRlQrOY82AbTKMF5avLtMnOVkGMBpnFzBK1Jaa05YYkB2S5LNRs5hbIFE/XLKGcEMi/10h1xekLlAEtTZLPJxZ4B9ImSVhFqV6+sbJ26Y2F1cst/vubi4pMwTeRBEC3NSd+Md/CTBQm+x4mgFaj9n1QPH3WhBOoLkebPJJ7LW2EqbRXqbzU6m6Gl5AzsWap0Z80Uvric5XVfKWO3iTK17xnzlmT4sLigwpCjO97qR5A2jvWYSxX8oKGaJopCHZPHFUqw22ifB5BZmq2bBWAkZ/mfxS8HhQSRPBp3pQEHBYzAlFjEPomseSG67z3VmLnuGixuE7NZ3Mq5Df2i1FlrZo8OFTZg6eDLMAN0GkjdFRBOi5mNHBG5ubnj8+DEiwsXFBYe7PSiMIx7vs1rzwMc1B92zgossWLoJRRzTZnhDYaGGOiexQgNPoswzSVJPPEboyBhtZs/WBgFGQrGFbfZkqdYZaQV0QFuh+nfNffUYbstet77AoK5ubnhye8ejR488wVVIafTqpMrQrOxPdE3+Gn1zAhoXLrR5nKWU7n0G2Dp/UZzisZwcPU7gTZ7tj2Y3M6WdDQgt3lDIWUVEaJJBRpCRWjzjNE8OxG3OOLyUzNkgAZpT9AeaXNXdoNphFHhQtXZs2dKL2awFT4ToEsMI/LW1DsiOTbRufoLYanKu0Bqlx2g0/tXZyqyc6r/W2Ug1hxHV2fSQdqiMVE0cZsOD1TJjlG6l60ZWDMbW5N3KN5XseDIcj2oQiqvLK/Z3e0qpjOPAXGe6Va8QvU3ASAWiNC+aU9kzEhnHigHyBZHWcQXnJoG9jKqv1rQjNwBqxSEslSFng7QU6yODZEpT5rk6vKlaBz2tXopnhlFQq+U09JYBtRk0qjSzGpXEfn/g8vKSMs+gjdmZkiAKIjzit9RP2KhcLWL2XHniTxeLNyX3WJ5zHJ8MrcHJUG3mL1Qt9uBp8nKdmSi5mubJV5WMIkylcvB0u1UhRD2jsZlICsvRmFLyMBAErdUBvVG5QFiMIj2eABCceTEBogscAMlEYTkYo29Kg8N1rC2p5EQa5EtYJh6GCBibseCQqOILhfMGNrPOVb0n8TTZQyvWOmGeK6UujaSqQ3A6tEmWyTCK/01HxSFZ3vvEdTiOO25uHvH4lceUMnN5uTOzRrD/HWOGBnogdR33euq8I+UdYI3JxBma3a/+6tzor6IEVCVcyiBPyUPuVqORlzQ3PEpHGTSHzphlJhYTdB33yiJk8Q5ggVIV+7yWSqvK1eUl0zShqlzsdtTZYXhRXeR6dqhoxwMLC+QmOd1eh0lJ6mWkFgJY3Olnycm0/839/iRQyh7BMEdNmyVPnOwTqsdnXgeMzKVYcD4J0CjzTE6V1iZriSs7kExtM3kwGimaky6kRtJCVUXaaDcnJsJmlmZOzopT6ZMxsLIeolZ1IqnSUjK3XTOVqKvOloUEksxunp6XqCp3d08QjH6tTgVJO8Yxw352BptkVUVqLNjZq0HrPHfEgWThMFUGd3+zeAxPRmo5kMhUMZBvag3RStKZLPZsBYyiev3rxcXIYX9LTpfoMBi+NVVEh6NsI9i8mFRBMjntbDFVzHLMpmNjlDu/iRAMg/vy5z9vb3zyyuPIMGRauyWnzDiOPHn8CkIhA02FqtDq7KW29n6aC2Myiy8z03wh1WaM40XVWnXgteStMoqQPc53OQ5Md3uur69REaPlCsC2AjTPD7h14otkLx8kISqU6WDsVSLktLPP1ZN7L2IybK3x8uc+05vsqCSGcWRyssU8jKSk3D75vLd0tDR5yZOn4jM5C6141cFQmadMGwSbkryJeLPm1eKZyubbDb8UpDQrYkqfZKN9YcQRIqawvIfIpsTkOM8HNFv3vpSMegzxmsgz9KGaNp7cvmKx1dbQlBnyjsMez8gOpJy5e/JZiy0mIY870v4WrZaoMKiMUqZbxlRpdbbs486SX2W+ZbcbSA7hyM1wppPV79Fa8jYRllzRWhmGxJiviSA5EoHz4wXLHnvp+0jCysiGjDCQ0oVbjl67eYY67kkyDUB0hhlqJ2tITAfh9vYVhMaQBEkTIEbEYKSG7hpP7LJS5xlV2F1ek0Qo856Ly0tkMLYbqZWcE9M0+Txgde6ShHmeuX1SSDnThuTJu8TglqqF4e67atrB12HBShKSjGTJVCqq5aiP+rPkxGxyVB7MNk/ngVpwt0YRZ8/d728Zk9P7z8VNWjdtsYbv0mZ2I5R5QtLAeNGgzdR6YHcxIWkki20TEaZ5tjhlNuJR++EePM3GkhMcdxGSx+nru+Ug4qwWoN63xdicd2Zek9ylm9FUTro1D0lSSmithisbLOGFU7BrtfpzpdmDpoKWiRlDAtRmg0ZRpBUkNSZpzFIYm1kN83TLPGdkMFYbqZZhLs1xgtkK95c+2ICoow6Uw2Fk9gonCavfzxneR1KFNHCYJqZpT96NJC6QajRPtJmUIjB/fhKEDDlHtZUlO6KHjEgiD8nZnyCosAz7V91VVesvssrot7AISyHNM6KumWLjePYFzwD31V3dRCm2gA2O9JimA/uDoVJCx+tOl4vLnLjb39G0MOwuQSeLT6o1E8uy4l58hpzeAs4vIufkuL2GSENxbI8j1A1cC5GdFMc2KWIA3WRgzhCLO6qzilREM4rBN1A19hPBMl3ebiBZeMiszmyYqDLP1GKYJvVrNUDuQkeUtKF5YL/f00oh765okkns0bq3lSnT45DnJUs8Ljm1O84eYhOU02MBqJCdpzJ5bCeJ+KqvhqZgduC8LUjJFzH7vgXyk0SG0EvqklmDYdnZQx+9b5R5hnwwsHUfKH68WHBFzao9HCZqmUmeYa56h9Y7kuNYz1PHAAsFF2DM5j4hBueAJbisz8zcZjM+FLKkjvBY37/OX5mkv+5tXJ2ZxrabRW7Ol7g7u2Kpsi/2YOFxwy/tH1ucH8cSGu+B6sEJXyzOWaX1WuZnyemToarhtdTd4FW6JxrxRBCbJLRmg8EaMVndYQJaqV5CGtm/ujRucfdH4ya22QYjAklJbXF7MxnJ9EHQLxM6dEZ8gFsscBV78HiiBYMLpc20cgcISfPZWg00q9rI4wjgjXqCi1DcMvfifklm6Se1zKEkpPlqXycqjaaJnAaiJlxJ/aGW0AFe5+yDw7wih3VgAyytBpkrd/lPIDgP4y/CIwRcRAvW2G9GdUAYzlbFqnh5ousiCER9YKwp0ppPWoE0MOJX289CVW5NJt8H6ZZnOLfBfxiky5EECRKXsO5t0ZVl/N4Ty6msdO+Ih8gfiPMYWHnn7gX2QEGQGpm+jNSyTGjxUFdrF6kIlYUfLcWq4VGd5t+1Cc5NZscuoorQaILhGQGVZlAbtyzNVB88U10WCndVsyBFFoW6JWJQAodzeJpK1ZpRK0ZPZKShOyA7POP8RAi3x+I3sqwsllWOTKEoRWtf5VGnf9cGTr6QxIr4U/bESwMjW4ip0eFTWuyJcfQBYl5CShZbDB5FDUhUtzxWgyveS/JgfAwVtTaSWKLGrt3NzjOV1r4w1rqe8ILkxIMPPl4alYaQPQNtlSUkq/ayemQje7X+40pWpYlnl/t5k/OfTnZsZ06PnknLXCF9sTrGg6qjjpcrj37ntq8x3RvG+fl5iU62DGurFovrKetlwrAmS073vbLUeoE17pboir49bjQBlIw6UxYTebVwWdbYQMDDsLAeNzdLNcdEt1xbB41G8P3otuoSJ/FzScpnPFC8053//sUKoL9fU7QvlprPhoJDKBwj5sFyYeXKYvd99eRgzZvmblnUqp50c0oorPnQ0/scax/Edor1wHMLJijIHLuW8sDzh9YfngQlfyc9jhCDj5OO1TUrAkJfK4uwuVVnTPfRcjVSWNKJOULREfezIonAOa7GpB87wloh61jhepsevXasssb+nlTt1u6z5cQeKHbcHhtwi2v9gAbo2V43N8etYUvzh7G1YnNNNlxf2Iudkqm1/n/UrMYPNJd6uYEL+FaP8FOLm3Q8QJbv9FvpWDi7TsBBwKGW8xKRGCjr1Vn7fe20aEEAeqRrw5MZkW/EdY3xfN3nIkCyy8Lnd9onwtYWLKk6hlD1C/Uewfe19XB/sYtzx+COoL2Iue3nqOP77met7ei+Hu+6jPXQU62tT2LJSzRBnJ+ydmt9MWS0T37r5yiOe79VaOhxifMfX/B6IuytaXX5aZYYOma6fx45uQdKgC9jkCCLad2DpasVWlYri5nPnnkWrzxQ8Z4jhJnop9JuWtvNtPPUutzE9YTW//VVJPUFL/7Qpw0Y7+2xsoQiAH+OTnI8gNEUqK36YogH0IG+8PS4HBYYX7KR4lUA1iy8qXrpJizWhy7egFpHvdCjrewe3F8t7uuBEi7z037D/cFt1ksi4pKq6RynwS4pHcNV7lvcob+48TbxJbeHdHUMg6Wt1bBgehfrL47R9RbHeWpc8DgEstZ5vI8TxteDKmzx6E4fvSfXJqfsPU7XKPH+Y31bbx9qDZ0kDWFy+HV6I+iICSg4mhCL1VkAHxE0R48ssx9jtZG0FFNpd8KimbRlrcNiXK4+TFvfKlbFYteiFIWF9PV8h8rSvdDojA1XthTDC0Ly/tbiWksyGO8dgAbPpQfEY3oTixfR9e7xPSM+CYfWz0vfdzUHQwTesfCHsgyMJSK9vDY3LoDZscDZa1ahlLOS1biwMdtADJpmUREzWJIkh6XE5JeP7nfKDuVYL4ziLNUksuRwXgk0AcQ49udGj3lDuzeppq0+hsNjj3/u9UW9eW3NWa7q6lgrc/E55EuE1kSbwXBbPQvok5WkAS17q/RArIaV5oRAqafZtQHRVY9wbUc/TuuU8wuGPAYTWFWJTbqQaFqNgTl5vsqMVrQrOMp44rLFYp8asZDqvyDiHGdKCC+xkKzcWsCCGM0at6/KLwXrNifD6EkxX/Y9KaIKTQZ3t3xyFWczBkJRKhlNuVOHiSSfK01nAj12KM36p/QmDar+bNmOBgExDJqIw3xEHa0fcCsD9Z+rRMECTs+lKgvQXSK05S6tVmMdIhndWogOxmSfEqqBBWw2HYn11Q5bKSYvifadS/0cPeWrpmMVp2UOHWvMAj4mk9B8hbQFOPk4NpNqWWyfbnm+mpycJajeCatfPRGzW8zZeHCbquOR6D1zzUJgCdBy/N318UyO435hfcb7uIyj4vNVDfN9V0pW31u/XtzrMMOXeMm5ibZ1zGb9ga/MDqxtHiPsg6BanXlIq0urxogTRZjj2N3t7oEzjkuPWa5JN+IizHOIRNzKWzi+VOA4nHJcL9uWhfAM5X78VryKLJAf62dA1dirSykeE1ysSr0XPz4ex9r1bpbgsq33Zub+s9DutfyIcf1099h/DUjUwrejc58icsoXROT/gE+edIavbXmjqn7TV/sivpKy6fjhy6bjp8tJk+Emm2yyyUOVcwXTbbLJJpscyTYZbrLJJpvwZUyGIvINIvIv/vdpEfnU6v3utbzIe+f9dRH5NxH50AnfebeI/OGLuqaHKpuOH7Zs+j2W06E1Lqr6GeAtACLyPuCxqv7+eh/xEhBdp4C/fPk14G2q+unn2VmME36TL0E2HT9s2fR7LK+5mywi3yEinxCRl4B/Bb5VRD63+vydIvIBf/3NIvKXIvIxEflnEfnBZxz7A8C3AX8vIu8VkW8Ukb8WkY+LyEdE5Ht9v98VkQ+JyIeBD947xs+IyIdF5I0i8l9xo0XkDev3m7y6bDp+2HKu+n1RMcM3A3+gqt8DfOqL7Pd+4PdU9fuBXwDiBv+AiPzx/Z1V9d3A/wI/oqrvB34H+Kiqfh/wPo5v2puBH1PVX44NIvJzwG8AP6WqnwQ+DLzDP/5F4M9V9XxZXU+TTccPW85Ovy9qhfxPVf3Yc+z3duC7ZEH2vkFErlT1o8BHn+P7bwN+GkBV/05EPigiN/7ZX6nqfrXvjwNvBX5CVR/7tg8A7wX+BvgV4F3Pcc5NTDYdP2w5O/2+KMvwyep11OqFXK5eC/BWVX2L/32Lqt69gGsA+A/g64A3xQZV/UfgO0XkR4FZVf/9NTr3Ocim44ctZ6ffFw6t8cDrZ0XkTWLUMD+7+vgfgPfEGxF5y4mH/yfgl/y7bwc+par3b2DIfwM/D7wkIt+92v6nwEvAn5x47k1cNh0/bDkX/X6lcIa/Cfwt8BHgf1bb3wP8sAdPPwH8Krx6vOEp8lvAD4nIx4HfxszkVxVV/QRmRv+FiHy7b34JW23+7ITfs8kXyqbjhy0PXr9nX44nIu8EflJVv6gSNvnalU3HD1teK/2eNcRARP4ICwC/41n7bvK1KZuOH7a8lvo9e8twk0022QS22uRNNtlkE2CbDDfZZJNNgG0y3GSTTTYBtslwk0022QTYJsNNNtlkE2CbDDfZZJNNAPh/+kiRYNF/y8oAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c185f6320>"
+       "<matplotlib.figure.Figure at 0x7fc0e8042ef0>"
       ]
      },
      "metadata": {},
@@ -819,7 +848,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -828,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -846,16 +875,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([ 1.39839034,  1.14876033,  0.70701933])"
+       "array([1.39798995, 1.14863749, 0.70716828])"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -866,7 +895,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -875,7 +904,7 @@
        "['forky', 'knifey', 'spoony']"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -897,7 +926,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -935,16 +964,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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IRzi+V6ajk6dAzZno0IkyJGc7GP1YiUNAkkCqjEMl9lAIPBwKXTV6E3bJebaF6xGGXpAk\nFBFOK6902htHh93JGEaj64TNRhiSgBVuNj28gMEMzcLDYkxeORwbAGibNjAXjjlwWuAuKOMiHMTY\nbSIvdoZR0RSJ1xvmsedhWcgyUWrBEIzAMRsPWbgrcFSYB0Us04UZxoW4cfpB6IbK7gr64ZeT9mf7\n7QCF1QwuyT2Rc7SwsuCXBS0GPw+oi1cAmJzlH4/WUo3WwoCzJ7Km1qoLXqV5BLW5+Y9hypplkAvK\nPDnOczqDlUY/A8cjgEhQ/Lze5Zj8Aip+iakfOSi0sfRBW+waENwruYLW9r1S88qFOLlmyiqwkpWb\ncKzpGBwQw7xBoZhgHi5pShejestYmAU8Nk6hZScSIXQA5FIIMdOFQi6FaQGzhTVMJ8QW9qlyEc8E\n7QgpsUnGRhcGN7o1nu9C5boLVOm46YTlTUeYM1EDYorlzNvTwh+/LTxXoV6BZeO0GONWEIW5CqXA\ncjIOe+HhTjkcYF4a0TmidK4MoTCZMAaI68Ri1ekBV2W2yCFX7k7OIUMpwqubyC5Vtj0MCSQISzGW\nCqI9X72r6H3lZqdsemHsnavO2Ea43lZ2veLXzrIId7PzgPNmCweDOrXJSVWbOA4n0zJbp6zs50q1\nyqaHm9sNm1cvmEPk/qfvWOzM4YAtxn6BQ4kcq7OoQOxIMTHGie1g3G6VZ1dwMxhXoxK6ixv+S+23\nAxQaSY+bIP44lC784TqVnh0Ct68RfNpuxrN2QNbhqLYOYHdM17SbKZjgtZFQZ4pAVrBob85suZ61\nOm2AAr6q2B7R6+ytPH63MflhDVlWcv/J+npOR15QQTCspadU2zWohbq0MD7XFUQKZCvYqntoANb4\nA6uNCwB7JDAv+GjNo8ltUNQQoELQSgwtbJAms0FpA121eSkxNMGXpZYr7+aO43SilIKZr+BUWujj\nECSx6Xo2AW5H56Z3NhgdmYiRTPDe0GTsx8D7Y+HU9QQvROkIuaOWyoM5dzmwWYwxAtrSkRpgocOy\n87DPvLsz3j4Ih5OSvTIE8CTgSkqCDE7cBgjCXCsPC9Q5MDscT5UvT5Gfnpx31Xg3K70Wxk4YohHW\nLJGrU4GHqfLmqMwmbI7O9SZy3Ud2/cKLsWAiPBsDV1vn2Zz5wRw4mPJmNB4muJ8dD83LkjV1K9LS\nc4Kw5IoKbDaB/nrE+ivyvOFuMo7THpkqbpFpOjJZx8l79sDJhS6MXI3wYlQ+3RQ+ue55vivsuolN\nr7RU2nez3w5QoCGorXwArIPsCbP9FAVUzwE7F7dcFApPBh9wZhcAal3FMgbS1EycZcs4nKc+Oac3\nz/7HKjw4ZzjOmYTzr+k4rusxil1Yd6dN7SFIG+hNftayF0ATFbV1NSpiEFYFnnulVKBULEY8JowW\nNhTPVLWWgMbWbEGbxfGKma0cQ+MuVNfwQh1XW8OKigRrLntsWRgAs0iMK0fjjpqiQdAYMYGu60gp\nEbtEzjPFKqU6yZvuQ0vjUjZd4rOh8PI68NlNz+0w0NUZsUqelOyGS+H5VcebsuFHD0aZDkiFKJGU\nBnSE2RemCktVBlNKFmzJzF4xg+PiPMzOvkQOKIUCAUpniAS6QRivYdxou8YL3O8r707CV/vCaXLe\nlZE3U+aLgzGZ8MkWrsbE1VCIUlu2IQkmyo++LHyxV+4XiMG43cLzUbjpjbJzOirRhU2njL3w+fXA\nwxL48XHhzehMuZCltrCvNMWhuGImzEvBHPqhY3u9wbsNB29CqFOtHHLBlkKpxnFRTibMHthXZQk9\nwzBwc/XAy2vjsx18uoPnV0YfHU2h3R9f86K/zX47QMFbbrt5B48ueJAnKzwxO8fy60e+uvKP0tl1\nm+KsDkJLhbnjZi2nb6FlEOAi0mnS45XGlCcJRRHcS0ttCqvQSh7Dh3X9D4hIcUTXga+r93EWMXHm\nQVZ4kDMhuq6jgQoEE0o1zBe0WhMKqTFrix9FKmYVc6WWVR9Qm7TVvYmXRFtQ0fZbcddG4SjEmKnJ\niDFgnjHrm55DIMbYpjBrUvCw/jYpJUIIlK5v/IxlqLTj7BZGVa4C3O46Pr0VPt0Yv7Pb8qLf09c3\nHGZnP3cc5sjeOn74YgSrfCHOw9TCmy50TMGYWNgbHKsxViOUxgkttYnMDjh32rOXDfQLURJdzOgA\nYVPpOqMfoRsz4yYxFJjNeVcqkzlvTsJPZud+qsyLcDRnuhJCL/RdYKvNY1B3FhOqKm9n4ctDm+Ff\nnwrbrvB8aKKhnTqjLNRtxEUI44mrjfNqVN4sUKV5Kl2NVDcmKosIuXaUCMNVZXwWmPqRSTZEGZmi\n4qe35EWZl8CcYV8jb3NhDgY6kNQZe9hsO65uCtfbwnUnXHWRYaitVsQTMH+n4fjbAQrfYq7yOMKf\nLn8qf74IhuQyQNeVeBq5uz2Jp9weC51WQPGLX9G2cakhOI9/B0EvyrBzGtK0pQWfDnJgFSI9EQtd\nAGMFGeGiJISwztZnNWDTYWRzajlLAK3VUQShaGiRwpqHl1UbU0pdv9+2Wuuj83JWYDYNAmSBEBaW\nuWU3SjFqD13XlIUhBGKMdF1CNay8ahNExRRJQwfSWPq6VErOSBy47SM3Sfm8O/Cim7mRia0Jz8LC\ny+sONPH+BO/3cDfDnQn73LG3zGExilUmN/ZZeU2EUOmzoRk2qiDGNDvZIpMnJnbM0pE6YeyEXZd4\nuYNnW+d6PLG7cjapECOE4FztlG0OhPfG+8n56UPl7YNzNCVLpNjCbAtZwZJSNTKXhYdiTUFaYSkw\nmbJflLd7590oKMJV56TY9BhXnRPFuRmFT3bCfWn3V0HRamzGyOjCu2NlyidiJ1y/2pJuN8yp496U\ncKocDicOD8790Xk4QJbIocKxVFyMlCqdCtuusgsQzTCrZBFOUpsuJwv7+bdAvPSr24eD6rzk/Oeb\n+j58ODO3ghNY+QCFphF4ChQ8bqdJ755s6+l+mzT5HLo4K5l4Ppwn/z891g8rLx+r7OCJN7KCVxMS\npSefOWa1EXV+hrKOilCtXvYt7hS8EY9BVlAwSn0qLV7hzWWtd5CVY/ALWRvCquSsjSuoZSHnStdF\n+r4yDP2FFA3BILRMRxRHQiSsYBdiYJMG3CuqlV2n3A6RXdeRuEetcsoLhwVeXfc862aG0LyJ7XHh\nJ4cjz7cjX+5BtTJr5lid97l5fi5KEkHEuPLG1ZxmmErPFLY81A2zKsM28GxjfLapfP/Kub2ujJvE\ndlNJXgBFZmdYnC6067uY8Pak/OwANUZil5ipHAo8lKZzmN1ZZtoMH4XPrxpB9HqGuSrZA+8m4x/c\nOc9G4dngXCXlKmS6KFx38GKsHGcniGKayMeZfgA0sAnGMgqf/Y7y6lWHbpScIkcTpvcP7N/es5+c\n+6K8rcIiCY+JIBlRIenC2Bl9KNgyU5eFOWb2qpQAsUJeGvh8V/vtAQWXS90AK1n4OLfLZba+LHnC\nHTwFhotefx0A31Y+IWudRMtXnrmCxtBemA3h8fX5MC+7PRMXj67/023Do67hEdDWPKq342tEU+Md\ncKG6EFaG0KRxBedq2Ipfio0qRpRGBJ4rF3NthUbNGdHLoZmt1Yqr6QW4ZFUjOrVCrYWcK6WU5jXU\nQtd11JrouoR0aZU/N7F3cxMghEiMEdGA2bymVSMxCr0ObLSyFSFpXfkUY+gCKoZo5eZ95boau1EY\nx0Q2w7Iwa+Agmb07+yqMdRUmhcBdVo5TYg6wr0qMkc1gvNoVXm4qL3eZ211l3MIwKqX21BopNVN1\nIYtQiZgYSy7MGao7VWb2JfH2VIgi0EdGEdSMgcinI1xL4eVgvCmwt8p9rbw/Gh2Ou1Ky4x4YNz27\nIZD6hZe1YCZc9comGqcESKFQ+bxzxqvA888rrzYHohoiWx5OM+/fv2d6yLw/TrxbnAdRjp7ZpZ6r\nEIm+4J4ZMUYJSCxoSJgpp1NtGZOk3BXj9f0/gUSjr1mCcxELNNa3vXgcpI/rnzlA/0DufB6EYucU\nQlg//Pl0TCMH1yGuT0iKp/u5FGdddtK4Cb0c5gfrigjm/nWcWD+XS30ErFqB9fxCCERVAo5kQ8wp\nK1nZ6hn8AlC+hg1qgWrShF3eBvnqDnH2FFhz4+dtNOJRVsCwlaRdZdj4Cggncs7EeKLrEuM4UvoB\nVSV1ic5AXHEV3JYmBRdAnSFFigdsWdC+ErUyBui8Uk8Ti0ZCAiXTKVz1Hek004VI6iBVZZFKkYDF\nSEmRk8JddZaSwCL7HDhlWKhIqAwx0ofKkJw+VTQthKSkEOhUWNzJS8cpG8fFOJbEsSqTZ/Ll524S\n+Pe5oCdDXZBSuemNHuMGIwbntodPOqgRZoGvlsr7GQLKP7WDV1ew2zSJ8vOtkjdCRYgi3EzwYmtM\nizAviakY47by8rPA5rkybgPbm4Fiwpv3e+7uZ6ZjCx3mKuQYyBjInisRemZIxvMEt6GyUUeKkN2p\nEcyE6aS8PsDrB+WfrJQk8M3hw/nn+tpy+dqIO2PGk7qTxiY8Hd0rSKy7kbWI5/LRY6zywVdYdfqa\nn5CP52oqbR6NyKM6wmpz00whED7YXuMWuAzEc4ZgHAZSSvQpkkQhV+o8czjsqSZkg+BNCu2AaNtH\nNWtKOW3FMnq5FmfkOZ8slzRlreesxznt8gimsuo8ZK2szKVQa6HWSs6FEAJ96bHOqMVIKdJLxylP\njbsJji0LS5yZN5FjFuZe8aGDOBCWjDAzjgVlITgES60a1VYCNDnRA25QQiCLcyRBMY4WcFHMEjkY\nxEKXhG2ETipWm5pzAo5mhEURAierHPfO+33lbhLuZ+N+gn0RZjtfU8WCMjGTJWApEYbIsC1sw8z1\n4gyaSMUJtV3z4saL6Dz0Cup8emV8uoOX186uq1z3hkRpYrJSee+FjcKUlYejsavCy08Tn/1OxDtH\nNh0WI3/8+j0/+dk9S47cv6nMJaGpx6SiIbPpKtviXOGkbeS2g+e9s0uypq2dXJwHh7tT5Wfv4GeH\n75Z5gN8WUBBAbWX11xTfkwH6dRC4zN5PYnizVlb6yOKfPQD7MIQ4g0Y4qxnOhGITN4k+dmbSVQwE\n4PExDJCvAdillwA8egJKK1pSbX0dvGVCgkprDOKwHTbc3Fyz3Y70fU+fAsGcYIaXyjQdOZwmpmVh\nzoVSa1Ngx0z1FuZIbNuvVvDFKKUpA2uFWhoxVvNZ5i2rchG8ttoNDa18mfBInqraOQLBXclLppSC\niLLfHzmDWUqJvu+Jq3CmFXs1j8aq0PuRMRq3Hfze1cLv7Qq/d5N5eZ2Jaxn0/iQc88y75cBDMVyE\nYdO1rWTjHudkCTHoq3MbjZt+z21IBIzgP+PZAC+3ypCOLFU5nAxfjPuuYyLysMDruz1f3Ff++EH4\nozfGj18X/tG7VmdRk9L1mauN8y/9cMfnr+CTTWRblF2qXI/CS5TrTrnSSr9qTOas3J8i+9L6KQxd\n4JPryLOtcjNWtkMgBuPFrfLJq543d4X3byv73O6h1BfiCN0uoje3/MFb4//8g9e8vnPevDPevT+i\nBb73IpA0c5MiFeE2OM9fVH7Qw6uo3G5g7CpelLsTvHuovDnC6wxvc+D1e+fLN3/2/RR+ZTuz94+A\n8JTW+67b4OIqPCX8vik/27iLduefOwedW16BIEGAgFtdFXve3PEPsiErd/CE2D3H60ZdxUWPfk49\nE4xi9H3Ps5sbttsruhQZu4EhKF2AJALmzOPI9S5znE7sjydKLRAUS4J5wUMb2EvJnOaJKoVFSmuI\nIrB4K/hq4UL4xmt6pj8f3a0nIdWZd1nl1LLWgNdqlGzMc+Hh7kBKHanriElRbedYCHjNECJfqjMf\nC7IYz2OHpEporQw43S0sJ8gzl4KsVichhBRAjAWwogRXajBinBhDZbCFkcKLKDyLQsKQ2lqn7TMs\nC9wtlZ8eFl4/OD+5h9cH5f2hYyqOaGFIlWEM3G4rL26Vv/BcuL12rsKCitGF2uJ8d5Am4RagD0Kv\nSvTMWI3ZnJBgTDCmwDhCl5TogRQVDUoXnF4y20UhKAXIanh03hwn/uHrzB++Nt7uO372+sR+D9fb\nxCe1sqWFRxKE26Fw1cFmbI1prjtn7JwSYMpO18GQhVhb8FhFca3fOA6+yX5rQOFSEQlc0nbfBgrf\nxh5+sM4aMAHGAAAgAElEQVT6/7fhysWTaJmGM6XQxoQ/vl5rG85ZA7+EZWe6sVH0Z3FT26w/hvZP\nQMFXbUMMgc1mYDMODH3PZtgwdJFetUmBY0BlTUciTPPM3fhALhlUmc1bpiUUTCrHaUZMKFYIGFmM\nUqHWDDavl+spL9Okth/0dXBaeHXxnFYHrjESjY+QtbaBlumo1ahmLGWC40SMgdhpK24SW1WIA+bO\nhJMlsrfEUGdCbnnR6TDD1DEU4RkBtBI9tz6GXeNdiiemJobApNVU7IJzq85NUp4PsItOCD1VWzny\n/ZJ5qMabGb64h589BL64h/cHp+ZKWISXHvhko7y87Xh+lXl5o/zgJrEdK5sY8MEptlw4mqk4pRZ8\nbnUffYoEZohKF4QuGonmmU414DidKp1EAo2M3O1Sa/Yiyr44J5RJe/7R6wN/9JXx9jTwswfhyz1U\nD3gNHEtlJ3DTGTdXyvMx8GyjjAn6zulSayTTwgtIQdp+sxBOgtfIGHtg+uXjhj8BKIjID4D/Dvh0\nveN+393/SxH5j4F/H3i9rvrX194Kv2SD51n2iZxZvmXw61lg1EbhZfzb2TfmAhznlNyT415rKdqA\ndnHODTg1nOPrx+/LejwXmm8lGGX1aNr2/XL8sqZCoyilnBFknY8rWKh0Q8e4GQhdJMTAMHaMqaPX\nQGykfhMfua1pp8qYeoIoxSqmK/EoiqkzxoQmOJQTGkrbT2mhRKltSJ97PJ6P51ykhVnTXpzl3mvP\nNaXVkuCtBkRC41Cw1kylJUwabORcqMXJ1dHSUrFdMlQcK5nQtbLpnIX9HNjmhauciJYIsXATlM9U\nGBG6vqKd4zHThwIqzBXembCsLdj6ZFwPxqvgPOvgZqDJm1U4FudhMe4OzvtSeTsp+31ivw8c95V6\nWtiFyhiUuBFuxoHPX3S8uA7cjvD5bcfV1rjatHvxMAvLImhWaqlMBR6mwml2ogpDVIYhMiZnS6uW\nXBbHtOIdEL01YLWIS4SYaYkkR0NPtsj7WfnR28rrO+NwNN7fLUy5hVKH48K7wXi1g2fJ+Z2xsuuF\nMSh9cEIwQlgrh00o2Tktwv1ReP8g3B0gz5lR/xRAgaYq/g/d/f8QkR3wd0Tkf10/+y/c/T/9VTb2\nSH7BZRb+OqG4mj9xby8io3Ve+yYv4pwVOJuqYjztfdD+nesmLsKnpylQPcue121I+GD5GRA+OCbP\nLYX4ZENuRtQmABJtLrlh9H3HzeYKMWc+HpinCS0NGGt1VAMhtGPqU9PiVzdwa52aUiSWltZcijWF\nopeVX30EBFlLUN3XPpUryJ01CeathqEta7O9A66GSes3icQmaxbFltxk0UHXGoxKyUKpgS4UgjhD\nSKToFKtkHEUYY6IPW7Y4zzVyKoUhF7apEDaGda3PYJDIqTipwj61LshDV9ltlJso3ETjehMYEyy+\nMB2MYq3zs9HjHilzpeaImnLbKd+/HnmWhEEqN9uRFzt4sRNutsL1WNl2zq5zNBh5UKbacbefOE4Z\n84ClyP0+M00zKsL16NxsWs+EPihdCeiScZX1d6iobhk0EEKlFpgdoiYsC3dT5n5Sag1tVJVMjEou\nTWS3WERVuR0rL8fKbYTQtSrQTTL6BKEoZVL2x8JX752fvKv86CHw/mioOeP1dx/q/9ig4O5fAF+s\nrx9E5O/RWrv/427vUUB0qU9+MqDXvL4GhTVVd8m3O2tXYm3sf/FHfDn3bRO/SJHbzb72R+Q8G3Lx\nAD4USq2sfDVc9bGl2mqqdpFGnzsbhRDwapBWpWJ1Sm0DMsVEipGkSicQveKlrlVzLUSZTkcOxwe6\nkBCJCIJKQKQiUTBp1XTVK1VbmTMYoUuQz9mCRkYi4EEfC3BYeyX62iTmaVs6F+IKrysegIBGQVND\nzUBEW+sRJDgW/LHpjQhSmgfiwFRhC2yScR0K25hJobDVa6665k28tC1ahNpP3ElFNHAVhE1/7i2R\nmdXZRrhbnC5EXo3Qd0bcOn1y+mj0MRIzzMGY+tYHYdq3mgnxjCzO8+GKV2Plz91GXkplDMLVlbMd\na+tfsHUkVGLoWnGXV8xaDUjJYAuUXHCJZCJ3S6Vk52BCRdkqWOiYFiduFC2V0DslZaZ4oN/0WNKW\nzs2K+IAfF/L+yI7Ay6DcSeZ2K+yKkwgUhauU6F1IFLYd3AyBPhWiV0ZpPRv21Xi/RL56UL64V/74\nWHhbMjPwYkh8/+ZPOfsgIr8L/AvA/w78JeCvisi/C/xtmjfx7hdv4BzL/wJi8eJIrLJiztjROh9f\nlq49/C+c2vmREnrujnQGnDYI9dxXQFri4oPqQj/rHqSlJtdU3fk5Esja5gy/nEMj2owQ1yMyXQuT\nwGtFxYldR4wJrw2oljkznWb2dqCWmYeHe/IywyB4zThQMYoX5rpQpOAUqjRXtNBKqnNemJeJaZko\ntfERIbYsxFnw3dKwa09F1dbfUs8p0vYZ67WUVZ6tIoRzdmblWUJUxCFphJzbdXUQUYIJVZwIbdZN\nhZu+ti7NI1wNsOudsQtoDQRXpLR4vEpm68bGIPZGEqemSheE69w6Hl8lYZeMXTR2HVwFJ0rl5EaP\nkow2a+6N+4OxFOF2jNxulO9tnd+7qjwPzvU2cLUJ9B2klJHozFawaszzjNfCKRsPM5wKzDOcFnhY\nKkciJSlLXmAqnICTGUdboBc6b/UQlsE7x0NuqdZdosRA7TrmCZZc6V15kZRZCp8kZ3Oj7TEELtRQ\nuNbC81C4FudZEj7rE6kDrxNuTpky89F5P8HirSK064xbCXQ3kR9ujU833y10gF8DKIjIFfA/An/N\n3e9F5L8C/gZtWP4N4D8D/r1v+N7jcx/0Q0C4pBnPI1Q+VCaeawca6yfr7N2aZLZk95lRlwuB+Zi+\nP/vRT0JsbYCwOiTNLp1VVvbeznJnA2s9D1o4Ycja97B50Wt1YlCChzbTFCeoU0IgBqHvOmJs5b+1\ntt4Gp9MJaqEumcPxiFttYU4F80rxymyZbIXa+sVRfcZolYpzzpymlrp0bH0yCq3b07m/gnOpPIWW\nirx0qFqVnRfi8SJ68CcA3Po7WCMWAIiDQFQkN52AeBPNqMMgcNPBTapcB+O2h90Gbq7huleSGJI7\noiaoBamBaVlIxUgFxk6J0ohNkQYAMTqpj1xF5yrC2Al9ULwYS4HTJBz2gft75c1eeXNUSk08753v\nbyZ+d1v4p3fCs0G42q4PffFMVaiu3JXAyYz9khuZKgG3yCZVxI1jaQ1si8Fkxj6DFkg5Mp4yYapc\nj9DtOuoQKFOhBiP0TpDK0kVOtMYoD9NCOS5samuxt3hGklM6YeiECGStbBO8Ss6rEW6Dc8VCkoSH\nwOytca6IErvIdtfxMir9tnm8V33gs3HiOny3Yij4E4KCiCQaIPz37v4/Abj7z558/l8D//M3ffeD\n5z6kb2MUf8G+1yfBNM99beddLvttsxxCvbi2fuEOzrHFxTsR/5qnstKKXwOGc2djwSlrfULyx33q\nmvcPQS8eRgMaA28DJaiSQkcfE27rcYszLxNWFyxn9qcDVgrTfEI1YAZTnpjqglFZpBBCxWTGaYRU\nKZWyNlNVbdJpW+XUsva/POf+W8X42np+Dc/Ojpg9AUc/+xe+CnbWEMyt9QRApLWFU0HjCmDnJyMV\nuA5w24W1erCRgV1y+tHoN4rVgk4wxsCQO8IpUxZhWiBLQDTRJyN6pVNj7ITtCF0vdBrogxDXitLF\nmuT5y73x43fGFw/w9uAcsrRsxVC57WeeD8ZucLZXyrhRUlCsVKoFjkWZThN3CPvacG8zdmy2I7Ge\ncDGG4gyDEk5GLpV3EywHmELAOyPReiJspXJlPahTY6tYjaKcJHDywDHDPBXCYuw8EG3mkw5uOkXG\n1jFq7CJTUjqEG018du1c9c7QGyHWFvKJYAhbnFcaUYGhE5aNobXQh8xu61x1a9j9HexPkn0Q4L8B\n/p67/+dPln++8g0A/ybwf/+q236M6f1r79elsnoIYZ3Jzu78upoHXzlHa1k2PcfrcHaPde2RKLq+\n13Oo0N6fH+Jx5hxMfG2y1Po+YOdnJDVmX6WJr1qVYm1PXZKmhgxr2rM1UUkIjXfQrpVvV6+YGxkj\nzxP74z21VIa+R1CWXNif9pyWGZOKjErqhJiMEFv9gWhsacBayW7rMwW0PS1L6iUrUs8dqd2fZCBX\n/QTKGnW05qtnL4JVMRnWMEmd9RJTvTUIUzHk/PgzUVJybiI82yq7zkip9YjszAkrqAQRQhTmpcm2\nFxfeL84+OzEbh2Xh2UYYeyNGY9vDdQrshkoMSnBBpak056VymJT3E7zPwv2y4Ag3g/DZlfLptfG8\nX9iMQugqYRDCZiQqlKzMk/BmcX70sPDlCRaJdJ3xzBY8Brapb3dD5+gCIRZQ4+TGVxneHDJsK5/c\nJm6Bw1LZa6UGJ6SIDMLUBw4hMhEppwqHQj8bWgTRiHYV75V4VbnaOFeDoQOwOFtVPtlGbrbG0LV+\noOZCMMArbsZcJ05BoQ94tzAUow8wbpXdn1KPxr8E/DvA3xWR/2td9teBvywif3EdUf8Q+A/+BPv4\nZntMpz/RFbSb2i79DerKQzS2rIUcdvnio1egT3QJ5ydGrc8y8HVn8mFW4WmR07noqNqZz6irhxAJ\nCoiiJoTQXPUYI+dUR+tLmGEtblIF89Jy4d5kzK1QqVxCIwfcKhBaiBLXugVvbeFDMIIKVVbnyJum\nQdZUrai26MDl0lzF1wspT8Mrl0shlZ/rT0VIoV2HJOuTpSKNawFab8ZAEGX0heso7EbooyOhsfmD\nBzxXfBE0dq3hdm3l4cWVY4ncL40x7ynsNk2z0akzBNgm41adGFu3KTPaE5lqa1MW+55hF7hGuZHA\n7bjhBzvhqp8YfWEchGEUNldK7ANiRpmNuRiHLPydt5E//LJwQtmNysurzPdOE787Oh469pNzdxSm\n0nolmsJJnMUqz905kJm8ZQwepkyNTr8LTX5tmYMPLMWYjgvlYUYOqzw7O1RvLeivItc753aMbMYK\ntWUydzEzrES4uKEkVJRebJ0ImkfSBaWLiV2A66SMXWndq76j/UmyD//b4x30gf0Kz3p4tCcJwq/t\n6Bv20p6pdnmrtBbirq2QqN3rT2SG52pJkTVbAA0ozqnKp2nE9j1VafWSq1pppTYbCJ27tbpjnJ+1\n0Aahe5s9e6+UtVXnmZ1r4GOoFFpnYJDUinbWoyDGjn4YyHPrYhxWPoO8tA7MIeChrI+To7m/4q1v\nwvrshhCcUJsa8fyQ0yCgQSjqFLf1kWNcrsu5lopLDN9IyLPDZEpDv5U3ERz1M9diaBCiGiEU+iRs\nCIzB6EJhE51dL/RrtiMTmUqk88BES1OaCH0auB4ciwGJzjBkNlvh5cbYdZnt1tn2zjaAhkg1o+B4\nUMLoDFeR204IY+DTZxvUZsaw56Y3tp38/9S9O48sWZLn9zM757h7PDLvo7qr54XF7CxWpkJQokCC\nAFVqq1Lgh+DKlPYrUKRCgFQWpESQILA6vwAl7i44PTNdVV11b2ZGhPt5mFEwj7y3qmu6azHDQY0L\n92ZGRnp6RPixY4//g3MWjto5LCG6I7YrUUsKyX8fXG6Df7sJf1kXzjf409X4dnO+KYn5KHRrPN+c\nj1vmqSs3ybzIxnzMnN8EnqMJ1Aw37ejB0ZPDfKKasplSR+VyvXB7cdpzpq0DzFkm4Qw8uvO2GA9L\n5biEhsW4VWjOaBrS++L4WCFlhgvbEG49MtJFBw9l8LAIy6zMqfMfUqD/bBCNP3bR/iMh586m/DxQ\nBIBohxVzlzS71/P+2pD8bBNE1b/nu3gvG+62azFmtJ1pCPfxx6s03D043CccsnMd9tHqNm5k3e3e\ndq3HgVAImHCtlaLReLz/3ZIzPs8cD0eabmRRxjCatUAg3tsjOnacQMSbrMHSICVydnJJmEffgxHl\nCzteX/dpjPQIfG53luSeIRHvob9OcuLo+F0KM5y27hbPu3R5ViEjpOSUrBwscSjCvChpFuzgtBmq\nCpfu6NZZdr/MrGFa8ss3UCbjbc+YGufD4JdH+PLgvElwPjjzDGmZSCljzbHmSO80G7w9CCULS4bR\nG0Wc0wSH2ZhTjDUPWZl2gZq7/J+JICWTS6KlxsC5bhcuV6PewvHp1yXzsCpJZm7N+FiV55tz6x2y\nc5qc0xnKYyYdFEs9FK3PSnmYsFOox6qMEKW5Cdt1cH0erKszKUyJgCjP4dWQ9zl5yhlNA2lhgJzv\nCmMWMoNbC5OZ7DHGTCmQsWEWHOViYGX+MZnB/L5Dfvit7O2vT1Ekmuce2cJeA8s+loxgI9xt5F5B\nUq+/HlC+ew9B5FOw+DxSfW9cuvcjdN+J74AgNBaIJpgXIS+JJBn1BOb0Lsx5Ik8BfBqj4wZFMpqE\nlBLLvDCOnaYJt3Cu0t5fMQOIkVIYpKgS4qLxCsOFiQAzSSLk4PIdaLWrAe8DGc+E3ZywDyvvGVHA\nyz9XiQJeCVg4pBG9GE1hgJtkDwjilL0/Y9lCQHXJ+CR4MVpyXjzk2RvGMcEDsUizDs6z88WbRLNM\nBUQ23s2dd/PgcecVSBF6EkyjT1KS0IeQ3Zl1YGqkMvA8WLRzXpzTIcJcSTDlDCI4ITc/hkEzpGQ8\nG6sUrDTIyuqZv+nOtxf4xdR5HMJRoZnxsTVeqmOeOR/hywfj7Tvl4b1yPhXO6pxFOD9m5Jy5LEAB\neqVvnX51thdhvTnbiBFvysaywOFgLEWCO1GEYWELkEbCGrQea2CYUV24DqhdEUm7QrlzqcbWnCTG\nXH7IM/79x88jKNzv1h8cr9Jo96ftI7XPGcn3Udt9R3eX1zReXgcI8v1g8Dp6g3tP4ZM02v0H+yKR\nzzQaNCC/kUJHYEj5btFmiN4XbGKeM8txIadCIiMeQCb1xHGZmacJbx0bHVEh5eD/a8okhFpmeqtc\nrzdSb6G3YLo3AANEFbf2biyLUZJhKYgxak7OSmAf5d44CLyGE1oNn30Adw3tTz0adij3fjvpPfjs\n2ZftUeruRnbHOwigwjUPlqzccA4IzcNU5Vt31iFUjSzrMVk4VknslEkBzQwUGQfmvHLKULIwcg8X\nrhb9omiyxTw/i0Ywc2MuynHKoa+QB0uy1wmrdUPShGrB70rYkVCF/w9ToDLdMM/UbrysRlvgaR2c\nJsWscxuGifJ+hn/yduafv8/8+fvEHz3Au9l51MxDhvMxUw9hQmNZ8G5Ib0gzrAvVoIpSNO1Kz+HB\nWUTJGhvOdUvU1fGLkGtoTjgRHFYzbiMQki8YNw8h4JIcemS6WccrwO6nHD+PoAD8aCh7Xbn3FD/6\nB6917n5f+10QwYnOut2z+ogKLh6qRclf6dn3896DwGt28IOLubP+HAuD05xwDdOVlAUmI2eJCYCM\nmAZkZUmJ0+PMVCayFLIUIDwAp3RgSjM+Cm6DRKKkQs453KHIFM3UlGhtkLYVTQIjhGfpAiWk5oQI\nUNggORR1bAdOCVEa9BHIPEyjP6E7IequoSSfxG1E0muAlM/eC9lNYjVY1iRjN5qJ57iAqTM8IQTk\nOcaETunCNGmUGN7pJvhITAKeOzLBnBNHhSkrUmLMlnugJ9Ukpj09Yc4eHHdR3gE+QEiI9xj9ZWdZ\nYJkSczYmUuAnRmRrYgFM6aNipvQxGCMzTMg+SBJirVNeKeYhB78lhjnb7jSmIjwuE3+yGP/0MfNP\n3x3508fCl4fKu1R5cziyzBKkqsko+0rzmzJjHLIzTUK7wubOpMaQe5Zm5KKUrNTaeN4y33001m+N\nXJWj7I5Xw6nmVAnNzecBNUFZjEOJB0cX+uCTYNFPOH4+QeFHe5Z/ywsx2eflP9jd9y58RIz73nf3\nadD94YDPjsFudXYPCvfJQqQZEV+ikZiS79ZqKZh7SclFyVnR2ShTPK7JyDn8Bg5FOT0cg1asU/g5\njsLoCR8ZPIzXsiqFEualpL1uj2sY1qPud3+Vbh8WMNuyq9TLfu2ugtkgJWVJSp4KqQmlF6oNRjNG\njxr8VZVagOQkTWgOBGOSmJzA7k3wOueN91SEvc0qoW5FXEcTZ3TwZkgzioe69Ao8JVDPqGQeJUx9\ni0F1B+lIMabpwJSUkghClDfQQRqGuqFDYYQQy9hNW809QEtDGA4J24Vyd8DEMFCnEQHUmtM7mN0i\ncKXYNLbNuK3CeoMijfNR+GXOZMlkH9RbY70YFJDseIdTEX55Fv5syXw5waPASRPvyswvinA4TqRT\nYi0Vzw2V6L9MKHMWzgs8L4oWaM3YLFy2u2lku/u9mBSeLp2vPg4uH2Ee8OaO4HUYKjDpXsr1sCjY\nN0H2pvu4Tzd+4vGzCQo/Jsy6I2jixtzXfUiQ3xfwJ84BwJD7gvr8JHsRvY8txdjTzNesNxpnHqmy\n7tm2qMYY0BzyvlNOTlqcXDpTycxLIR8yZUrMczT5yu77WLJwPsyUNDOVBUiITRHd10GrnSSFnApi\nShal+O78kqI/sZlxo3Kj0lql1UFNidIhD2HeJxqJQSrxBsg+TSgJpuH04Qwp1K2xDWdcO14HjNBX\nSEkoE2gK6SZJisp+c8EeORQdsaDEAwhlNhAZ+zQGXIM5Obkwd8GT0zTSC7OwYx8t4VPirIMinRdV\nrhmKOGpbGOAWwaUF3oIV3Q1/W6sEnSS8Pw2FrowhbOZcrbON6NbpHvxacl5UUVdEGuZQV6gt0vSU\nFW3C0+b8zbbyzQs8WyaXwZdqvCH+Xj0l8tu0A7OMPhqnonx5UP6sJH6Vj7xX5V3pvMnOmynhs2PH\nQVVnWICKhA3xzikl+mzkg8MsbGtkWh9MeXGhu++o0cTwxOXF+O0LvKzCWRNL6ZyWFCVUSuQcHSUR\nQQeMobQWVoBDBg3hYsoruu8PHD+boPCjx31Mtn/9WTURD7l/qvfvgYJoEH6Sctvv2v3ufR1H8olC\nbe6I7VqPtjcl936EZMg5kaZOmZRpVsqkHI4TyzJTjsI0FeY5MxVhmhJTSeQMD4cHSpqZyxHxHPbh\nbbBqpaUe7EcCiCJue7of5bpL6CGM3mm1UnunWjToJMku1W6v0OokQE7h9YhBNqa5RHddna0qUw9F\npa2CNYvdQzyakbup6v3/lD693+4GfTfNNmCEHuSn93pvfOZ9DCoWoiy2B5ABozvbcJ48JNJUnKlH\no+zeb2g4OhzvzmgdNsEugtZEXYPDMZVEykLH6c2wEXDjC8LFhL42chIOKXoufUeTSopLv92E6wZD\nYzOwBs8bfNfhN6uyXQY+C1JAzDi48D4HEzKRGQPWTTgm+KOj8kdT4v0x82ZJ/HJSHosxF6Hp7lW6\nG/zgFhotougkpAV0jjKwa3SHVldeWufaobqgfdDa4OtL5quXQb04FOPdSThOmZwNT0YqiZLCJ4QO\nLzfntg7WTVg9cR3w7fWn6TPCzyko+Oer/v7YH37Kp5/5j441Pz/ugSKAPLLvYpFBsKeStpvG3LUW\niiZyTsyzMS0wzTEWO50yx9NEOQSX4TBPTFOiFGWaMiXDYT4y5wNTPuKeoREy6imz5UqvI4RKBqRh\nZBTRFDe8NFrfGK3ScZoKQ6NU0BL16GHKnAqc5kzKIdzRhgW0uwRiUlUYHk7HtSuSodZE3Yy6Ob3H\nmxblUXTAS4Z8t6nfJ7o+AuVpw2EINvS1f+O+k6vcqGbYEKbNUM8kz5g41RJY0KFnUWZRmkaNXuvg\nYooOyKvTd4RiuwryDKzOdgPpwpKFMkcz9Q7r7klYk7Kp0F0wFTIZbLC2Qa2DnJUumQ834bfXSNfH\nUOoQLtV56c63TfnQegi5ZDjr4IssPM7KmzQ45GhY9uwcgPfJeF+cc4JHKbxxpfQNz4Z5ornRPFzO\nqQOujb6F3mXDaFnoOYftfcpUUa6jUw2aB2emVeerF/juFlnNKSU2nK6JaUnoBCUPlqQccybVQbfB\ny4vx8QZPFX67KV/9Y1Rz/vHVLj/47ncbgd877tyEH/nx7zAwxbhrJH/ecEQiwLjGDirZkAKpCKk4\nWqDMwnzMHM8TywLTFDLoOQslp+imJ/b6fO992NhVm8bei5ioUmkNcNubhBpCGd3ZRg+uw/6aeooG\nYUnwcBTOx5nHQ+LxmHg4HkhZqeJ0HzQJpVeZAybpkjGTMKotja122mqsq1K3kHQXkVBMyoOSYS4x\nWQnfQ+g9AFI27qpLgg3Bm9D2PoWZMjxcvVFDidclmhmWMEuMEZZvXhSZhOo32uhcHWw1UoPaYqF+\nfAG5gF+dUZ3ZnIe9iXgXMNEsaE6krJhtlAnmBEUGwy1MYAz6cG518O2z8NebcTNn24yLJa4tUevg\nQ+t8m5VDNd6jvF+E02TM0+CY4JyMc0lMh8JUheMYnJhYBhx6YqnKwFm1U9vg1owN2BpwaXDr2OZs\nFa5VuA2hSaalwH1cRLl64mrOSw3LuNYINecOM2H48/wMk3RKWTgsiVRCWk6LMtHDB2ISkjptGNeb\n8vHye1ff946fT1AAPocRA68Th8+esK/dTw9+T8T1FZb76Xz3WcP31JacnTLtr/qM96BkMpDkUW9m\nJ09CXiDPyjRnDqeJwykzHzPTEiCTkolGkkWKixnWgL4yEiTpuCWsxyRAPLErpUZ548GITBoCtMMH\nncFtGMNCOGXIQLNxnjLnOfM4L7yZC+epcJ6PlGnGyqB5j2CjA0uGJ8hJcNdwqE4eykA1sd7CHTlk\n3cdrUNV9NFjSbtIqd/xXSMTdg8JoRl13lGKPyYjsQcEQxoid23E0GyLG5sYmyqZwS8qzQHGJKcUK\n8gwvV+FDDek0uQm5JSbvvMmQSvQgpAh5EUp20hQ9guMQcoZZnckHpjClhKjwdO20Ovhwha9WeBJ4\nrs53HW5V8c15HvBRnUcRlnnisSiP02DKjuYeAXkW3uTEvBn5auRm2Ih6xFHseKXnznVTbtm5DOF6\nNfS5kreOd2fdErcrbC0zSNRkfOcKm/OwFv76xRliTEVpFt6V6wBlcBvw3VMA4LZhHNvM4aAsEyxL\n3GaZ98cAACAASURBVMMlwdtj9Cpu3XleneM/BMz57/v4YUCAT6P1T0/623//HkA+Twh+tHn5ei5/\nFVyVe4Py/ngKqfE0CWWGUmCaZw6HieNx4nCIZqLIfSogrwvCd4iwuFLTYEod8Yyb0LrRmoFr0IXR\nfSLQGJ5BOjaE21ZZtzWEV7kbzAvzpDwcF96eZ96dT7w9zZwPC6fTiTJNtLRSrZF8RXyl5wHJyDle\n6ywJSqI3p94GZVJac0YXWjNa7/jQ1wCKGW5Kysp0KAhGGy2w+iNSeBJIFbIpNmTPBKKsGAa1hzzc\nwBg2SJa4JWFKkMV5Et1ny4rcYDzBdx+Fr1fh+TYoFU4qPObMPBs2ZWQalEUoi5HTCNi3KCctQKMA\n047JaEDXwVSEVDIjwwXj22781pyvTbh20KGsArdn5ykbL7nyDMgGxzlxOTqH7Fhq5NRZJAR21Qa1\nbQF0SIJONxxjWGGrxjPGy8eKfuzMDXwv427XQt0mbAjNB7/1hK3GeUo8PA9qCxLZhrB1wTQm0avF\nOexmvPSKXhrLCU6TsCgcj86pOMc58cVbpWJcNuP58JOWIfBzCQpCDMB3qIF8lsp/frwuXPPvURs+\ne8JrlqCugAaVxyXQDRJ8h8gYdsHWvdawe+28pxalOHmO/6fJKRPkAmmnwYo7dd3omkis0TCUve52\nIUmJxp067nWXoN/HgiOymrzbvyOJjrKaYKasV6PeGr2tbP3G6JUJY86F+TCH+9D5gcfDiYdl4nQ8\nkEo4EItuoc/oHet7kMoelm8pMZ9mahO2STjMcNsUc9iqs60jEHM1moPR5x07KCvGXkULw5zajNSU\n1JW8dKxHL8Gr4i3SVq+hrQCK14SIsDq8zIFFcBt8TBNNQIYwboPnl8FzLXyzGd9W49ATb1SwCc5F\nuKVBn40yCVIMy7zK6BVqEMP2EhCH7BYZWInp0LzA0YVjFS43x1qYp8zzYALWpDx1eHqC7cU5LsJ0\nVr7YhOVUeOmddz04KbRO6isP40DPnXVszCq8iPPRKr9Zla+vg/WvOuUZpIOL0LpGJjSctYOkRGvC\nN5syXwoHyTzfIJeGW6Pt2IayOy5bN765FdaXRNPG4XFwPgpngTer8pgGv3ijnGfly1Pn+ezcfrqc\nws8kKMAOKoK7sUpQef+W5+6jsB9GjVf9AIjGwmeUh+iV32fu8feSRl6843n2AbyQiwf2YHbmJbMc\nZubFKZMDIW3et8hMkoYFvOyZyui2S68JKRWS5uAVWICzx3BsBAswiwapSTJKgiGh37c5t62ztY0+\nesiqaVjal1w4lAOn6cD5cOJhCUVoLQnvM2u/UYfhY8Oshmw6Ri5OykKZp+hW10bP4ajUamcCijtj\ncmoxeruXXGF3X1uniDKXmWlJTLuaM8NYK9Q+GE0ZRRgNWCcGGR8pxikWFOWrDHztSEkowndtsHrF\nOvRqXIEPZnw9nA8GZ+uIdh4TkCEdQB+E6ZSYFwEZjAFthMrVK8JVJcBN4lgKbkieOo8LfCkxXTEL\n96gHd44SzdKvUA4tHKjHcL5KzlEHhwEvY7CasXWhq5IlBHCQTvVOaxu1Ch+r8JvufN2Fbz44l6/A\nnzPWYcqhIfncKpfk3HKMxMqYed46fzViBPumDHQCJJPa4DE7S3JKFl488/WT8tWzsDbh+Jx5cxbe\nHDrvFuH9RACwTolZlC8WoZ3i3v0px88mKACg8tr2+zEy1P24C6j8Tjlhjtgd/SgEdXDfSXZa8F0H\nUXfcguun06QkpALTrEyzkItQJqGUgCHjkWa7DZQWu/+wGM9ZZAmtG/0+0di9FV8vM4dgiriRFZac\nIo32QtYd196c1pytGW0MmkUJ4bIHThFmmTiUA+flwHFZmOdl13sTvAtprNALva80h9E6eQ5ZpOkQ\nblS5xDRg3gbb1shZyFno3il50Cq0PmgjzGXqGJhZ0LOzMmVBciAFpzmzVqVWoWWhbuAUTAS7pWCe\nDsCVipJXoc6ZWoQn27hVobXQ3dyy8FSEj2VwcQmDnEVZzsb5ofPwIExnODwIhzno3bU5vjm96asR\njniMe18RmQKHAzwivBONvsgxFlqdnHNKlJy4XTtXzzxX4bpWkgTYrYrRUZoF1dtSQnKG3ul9sHZj\nqOGb8JuL8GuU726Dj98K1w/CdstUg6NG8/g2nJo725xoZOhw6c6HzXipcM6ClIKo8Be58n52zgtk\ndS46eHoa/L9X+O7qTKvyuCpvJ/jlOfGnR6UgTD44Z+FUnHen37OgfnD8vILC3hR47QT47iL9O5OJ\n3204xmF88or4JCb6qjsoOwYB2Sv1z85YiMbiHMy+ada9fAhnZSyHQ7N1zCKt673TazANRwvSSrew\n7RIKcscSOGHtltghssF5X0pIiU0yMZXIFFo16nBqgzqM7jvNyUNubth4hXtnTeHBKPvCI7F5Ri1j\nNbGtxEiubOQtdrVlEdIyxzQlR0mgO8YgTYleryRVkg5k3ScKOMON1pz11hARlqVQpkzSxCTKXGCd\n4LY5aGeY4L3TdDA8wYiUOw/YkjNnp2riWRW/BRQ37ya7mwodUBGWqXA+zTyeOsfDyjI7hxmm7MzJ\ncHV8QBOhewipjm2vSAnS2sQIJWoPcljRzCEbv9DKmxziN+cpmIX1aDTrvKzC08WpFs3W9yXx7qA8\nJmMqAWArJZE0029GZ9CzcvPCby7Gb4bysjqXq3GtzsU7N5xTNTRDc6hd6DJRCWDU8MxtOPTBNTkk\nKAL/7J0ylRzTL4fUM6N1rtX55ubUGyxX4zE5374x+hcTx8k5l0Gao2Q+LP8IEY2J+NBcPssA7nwG\n9rLi9evPUU2fHTuab08GYMcawJ55fHZq37uYQsLTIGeY5sR0EJYlMR9i1FOmREqABJBk2zpuzmjG\nuhm9ZkYb9LaLonj0nJyNtP+9xCctg4AJCz05IxmbCLN2NCliu/uSKXVEiBsj0JZDnDYGtXdu68at\nrtR6YEwZHxlRYUrOlDRm9D1Rr4mX1ah5oxwgTY5tUc5gjubMlIQ8hbltSUpTJaVGkoH7FkhPNSC8\nHcygbj1GmDlTFmUqEz6E0oQ8OSlXkhgu0XQcZrThtG5kS/hm5Msu78agb6H4dEiBMB1AzrCYcC6Z\nQ87BM0mOp4FI/zRVUsc00dTYPHFrRr2BekJTKGLlDutQPjTj2o2M8TjBWy0ka8wqHJfMJMZ2UFpX\nnlbnwyTUkcma+VIbvzxlfrU4b3VwTkZRGNuubGXQk/IyhO/WwaUOLiMs7C8VPvZBRSjTkZwSfXRq\nFzabaGQOufDG4GjOkUZOg6GQrfOQgxy1joFV4eUCdOGsykEH2xpakTfgZQuRjFNSHrIxJeM8O/P0\nD5gpiMi/A56Jz7K7+38sIu+B/wn4c0J96V/8IUVn9R0NB/vKjSDwSWX4Ez8B/Hs9hdex5C459ukn\n0Zz8rJsQ9aZEtn1n9clOcCpFKVMEh1ICqhsAp0a3G9vqrLcg5oymXG9C20K1d3RwVywRswLVIC29\nwjKDyHW/bkMwT3Q1vPdQkh4xyjPJEQwITEDfVZJaDx2GzSptVLpXzKYgKO0ZUSbSXfWMN6WtwkUr\nswiHpgFxloa0gZdOKjmyBA2b93w4gm64N4YR/RG1IGPJjiAcjTEscBhzCtxFSkyS7mouZE24xnth\nHm7WrTt1GNYMWQ0TY2ijtiBm2SIcVNBJWSRzLoVlZ1NW4IaElBlOF8dUGQQZqCJ8rPByda4vDj2o\n3NFTCKv5dYCJU6bGMilFJiY6s8IigyIDaRIEJTeSOBcfeDXeLINfzIkvHwqPRZg1cC51sgB+NWe1\noK+PBhioJiQJPQ2szwxmqh8AxVMjJWHWKZSrhvCFKJKdR5mYloFnZ0qDN+VCYrBVuLVBnQfnB/iz\nnFjOwndXeOqJb2+FW7vx3XXw7Wo89WBgzpMjy37z/4Tj7ytT+M/d/ZvPvv+XwP/p7v9KRP7l/v1/\n+7f9cigA70KU6p9lC3evAn6nsfgqlQb7KJDXsuC+6Hj9PXY6dTTs7urPEN6VST/pE2jWUCfOuk/l\nogzZNmVboTVCSmsT6qr0Lf5i+E3GH0yaduHUvlOJwZJQyHs/YhdlkZg8NO+k1z5QKD61YYgJTX03\nfYFmcO2VdV0jKNgGLCR1sirumeQ1ypEUWpCjDzacps703LDjjU5DszIk0egIRsoLqSRkGFmnoDAT\nQWrdBqk56hEUeg+A1W0z9DlMcZeDME2hpjSlwkVubM2ptTNOO76hg2zB/XBzTEp4HFp4JK4ZpkPi\noPBgiaNm0nC6wjXnHco82JoiK1TbMB2sLfFSlQ+18k1TPq6OVCft5ahlpZkhRVkmZSGAUIyKeGKa\nnESnJEfmiboNZESpo32wdbhMkLQyTSBLZJjTiFLpJo6vBOOywTEL25I4dg/1qVPYym3dQY11FLoX\nkEQaSmrwhsoxD9JkTClAWie9oXNoQVYLWLz1xMGVh6PzRer8ySJc3sHTMH57rdxqCNW+XZxjgSkZ\np0U4nwvw00YQ/3+VD/8V8J/tX/8PwL/h9wSFABd9giq/qia9lhF3puO+9O/KzPsv+655cBcZhXuJ\nETvsq6biKz14V1wSRzA07YIlJTKELNHpFwllm1Y7dRtBprk525Vg3LXYBePei36FStCS75qK9/CD\nO6YW16USrLYcPy97p9w1FHLc7vDhAFgFIjvO5B5+hlvrtF3B2XbSVtJBmZy5C1N2klbwCiR6G9St\nYw0sD64VpCVkmWIa3CHnmZQmSklIKiRtpNIoa2O9gdFpxFRneKc2Q68N3RWkSkrkvVdiMtFH9DlU\nG9ZCTmw1p7VBa4bcRrzPNigz+2cF81Q4lMKyzEh1ZGS6OlsKi/mXLdCCuXQoxnUYH1fn6xW+2oTv\ntphkCOHwnbdQj8hDOAzj1J2SIws77/eKJOFqSn2aWbtxXQdrHUg3JjcKzkwiE7RDu4PgLJElGsc6\nwkznkAZZQabEinBOmTfTzKUl1lr4sGYua3BEDiVxKJk3k3DKnUUrcxo85s6iHSnOixvP6vHeAwcG\ni7B7dirDJ27D+XgMW7tpKnx5Mv7kUHm/wPtT4nz6hw0KDvzvEqvwv9+l23/1maLz3xB+k987fuj7\nYHekku/iGexEPtht4j8hk1z5Xib0ySnq3m2+DzP3fsJnIKZPNnOhJxBZgpCnXR9hOJ56cPSVGJVt\nTr9BuznbTWhb2K6F0Yu9XtM9wTELxmFSxTU0GSBUoFUiGEQgimwl7WWSSwQDI6YMdzzmvQgZI/AB\nW++stVL7oO+4iHgfhZwKJWWWklmmTMmC9kyzaGC25mwS2PuxQRkW7M88OBwSIguaM8uco7QohVK2\nUFPyDQsZWEaHOpxUhfUWaL+sQloCDTorcM4RbDG8J8QHqonrtTJ6MDhvq+9knvi43AwtynKeOSxz\nYDsqbLXzgvLiiQ+1kWyQk8EsPA3jw7Pz8qQ8XeC7VVjXvW+dlCGBWViasOTBMYffQ06JLVhKPHfn\n42Z89eGZsd8uhwRvinDOypJjZKkW1OnhMXp2d1oXeofRBkWdtzNgcW9VUR5K4mFOPN8S36pwGxmp\nSnLjIWe+mAtvJuUhj9CQTBuPubJoQ9Lguxyl2VWDXv+2b0zA0p2CgTeudfBhC+2HaRHenuDLI7w7\nwTKHk9ZPPf4+gsJ/6u6/FpEvgf9DRP7vz3/o7i53KZ/vP/7J9yHLfY3es3pet1nxfZAouyeiYMM/\nJQWvgKdPpcIP57Gfqy9/Hk2ClRgch1TugiqhtTi6M1T2ESExoqshWvF6Kvl0qa/S8Pv5s6Rd5+CT\nM5PLne+/a0TuDdOiwSgcGqChOyLQDUaKV+8uMX0YoRxcx6CP8HZwglAzTTNmmaUYh3nldDhyOi2s\nm8XOzuC5Ca6ZlhutDtJopALzLKgO3AZZc4xlc4YDAVFOMdeV1JBb6Fn00TBJ1Gpcry3g4UkQLeEF\nMRXUBbGODQ0rPQs9hd4TvYedniYHzYAxGCEVN4Veo81Co/Fx20gjFsG6XikdjhnSInzsxjcv8HV3\n/qYbvxVh3acS0egUkgeV/DBCk2AxZ5LBVRM3V9be+PWT85eXmCAVhfeT82cH+OMFHrNxXZ3rBIdD\nQd3Z+qA24eNmfLjBbYAc4TQLiVBTqhnmSZiKoGlwS40jhQcyyeCXxfhibjwsztvcOWvjmI1TFo4i\nJO0clkRGeBFYsvNHnkLT0Tt5F7hYm/DuFga7ZGeZjONZOJwT07FQDuUnL+i/c1Bw91/v/38lIv8a\n+E+A39z9H0Tkj4Gvfu9J9sWNOm7yuqSjrbCrMu4OzLiRPdJz4xMC0e/gI/YdW/dgcW88yl2sZE8X\nUUSidMi7DJbr3oFUYhRYYdsGtcYO21ssQiOab58r32m4y8a592AxfBc73XsNqhqSbipkdfIuCpPv\ntm1daGZhJzegjRhDWtI4v4de39ajfOjmeHCd0ZRQKbtw6cRpnjifMw9VGUvwEeokPPmgW8Ka0Btw\nG5Qk+NkR6fQpDGNFM9OcWJZEnqbQEJS4TouZAV6jd1OHIVXQm6EycBJlTpSkSCn4YUc7ekd8wwmm\npmywtcB1DARXxbNjxYPwtAioU924tIGtlVYbh9WZNnhwmBbl4plv6uDfDuNvRvAaeon3H+uIxcRn\ndmVyYRFYkjADH03Qm/PNxfn1R/hmCzn2Y8n8kUVkLhJaCd9d4ZCF5okZRSt8bMrXl8GHW6BH551t\nOmdjLsaSYJ4GkjcqxskKy9o5z4WEM2chF+U0d97Mlce0MYmT3RAZTDlRMBYS3SsLneNSWCZlkpg2\npZzoQ1heOmvr9OSUDG8flMdzCa2P+TMNwz9w/F0dok6A7gazJ+C/BP474H8F/mvgX+3//y9/8GRK\nzC/k01K7J/p8hj6Ip967d7uN+j7mu2fRd06DCvt8+vuJyv37+6RD99mhE9TfRGALRg/yUK0EK1D2\ntD7vgUc8lF32c7o4uuctd9+Ivbh4RVneg0YSpewdbLXdtOY+RXm9zn1M61FSSIywd1DReKV9y35d\nLoGrOBwyD2nmrRx4scx2W3ksUA+F9aUGVt8jCFGdWZ1S9qAwVpIaKc/kArOWV2WpnDMuuguJdthT\naLMgPm3VSdJfG746zYgIU86cDopbQzyyFlXBRszwcYlJi0S6L1nwHCPbnsEOgo3E1Y1eBwcv5Bq9\nhXlzas4898StVm6r01B8xNjY/a4nEzV5xqgEFiKPKL/WCl9v8C0ZmTsjBQluZMfLgNnpKlSBy+a0\n1pgM2JzfXIRvV1h79IlM957U2VhEkAWKdEwHt62xWGEeg+yJVBJjSXhWDkvluBjH1GE4oxqtEdLt\nBUyVUiZSMi77/WTmjN4pNdS9zyn8Oy05ucApW/Q3cpDyfurxd80UfgX8671Oz8D/6O7/m4j8X8D/\nLCL/DfDvgX/xe89yb8jtJYTstbW/7rryGWRBaDL2CUUAEmJn2xWZXhWdx/3Ur5yGQBfuzTss5M4V\nBo7ezVx81xjw4CjUJrQGZmVXa94zFburOPOaMejey4zhoL9qEUSi4Eh3JAvqobKbk6JuIdTaRtjL\na5BfGEKyFAi6buQSQaKPqF9dHfLAdcO1gRizZLQEM7LNwttS+Dgy12Mh62BL8OEaPRF8VyCSXRTl\ntsIQcg8wUp0ynkHVOFhGZkOOe4WnBckde2rQBnUjpiXuJAwk9AZDFSiTEszZsGnQD4NjE1w6m3XG\ni+DV2TZnO4QcmdmuL5mcMgpHVWreuIrSJKTd2wZyDak8K4MVuK0hCTdSjHEHsSnI3ghuO9ltzE5N\ngysxfnwRuE4wlwEW06j38+BXyfhVgl9MzvuD81ASE45sxlYTz8+DXz/BdzXTveHnzMNVgIFME4el\noqfCkiGnwaUJx9vguHROCrkkHhfnYW48nJVlEtSNNuDDFdbLIKlQtaGPwuHwgM4JsZW6Na5DubVO\n7s6JElLwc4JR0dzBEqPCUEet/uRF/XcKCu7+/wD/0Y88/lvgv/gPOlkidl3ZpxD7MOF12e2LGgnD\nDZwA4eCway0G8jB2Lpd4aS4jZufxC9HM4z7ISPvih7Y5bQtNv3uZ0buHBfkAsxrAo89KFFVg8vh7\n+xTCQ1sd6J8clu7XySeXatkbjGqQXEniscMIyB50+m4HFlqRLchYkyIPjuZKlpVD7qQy6OlGsxvU\nhGeHdEXnD/zyjyvJBx/XxrfPzpwTp4eJtTfyUPrq9OZcbdDqE9N1xeuR221jecyMtwfWAuVoLMuB\nt+eJ82nh3eOB58cjH186z5cbl1ul18alRb9jroEVOJ4XDoeZecqkBbzEhKV5p1Qnaeb2YmxtUFv4\nXOQslElDb3LOTAmWSQMxKYOnJtwajJ5ghIuWa6gdrbOE2tGeeZg7Oef4SMogPxTySTBrLAg6nNmF\nd6aBpVhhKc6fHOGfzc4/n+GfHIRfFPhC4TiEek08PyfGdeBT4qlN/GYdfLsN5ovwF4/OX0ydeYYH\nn3jIE3mCmyoXb1zZ8C0z5Zl3S+LNZDwunVNO3K6Dv37q/OU3g4/PiTEOpLcX/vxd5i/eNN6eGtqF\nywWer4XrOvOb7zrPTw3Vzi+OYZ7zxVmQAWuDx1pJ5fNc+/cfPxtE4+fHD6aL3/uB72Aj7G6Htk8a\nxRF6lAMijHtvYtf2ll1p6d6DYM8aRO4MyVjYSixIG76DkjyINtgrNftVLv71+PzrkNW2XXA1O4j5\nDrza7d3YPaY8mp2hrklciOln5c2eG3m8jCRQdhp0p7PZhet44jAWMGPKZRc6MTbfqKPS6EFZJpHV\n8WE0HwhOzgOmkGjzJlw246Vv9A5lzcxDcWmcT5kjBdXGNIWXxWHKcDrgctdoM24yqJvR3cjdWde2\ni8Eq01wQCbXmOWtwPjSyLDPHq9C2TNtg3eC2deaaWYJhHurZU2bkxuqdyxDaSDge72dSqo7QmfRd\npTqBWqTzIkbJwnFySjLIQs4z0oJw5ibkJkxJOU/w/pR5Pwtvy+C8CMc9FZ9HgNRSc2QGrp2bOx+6\n8bUJiwjvm3AZzk2EI0Lfoe4OyAhfBsbem+mhcdFqZW3Ky63z8Tb4sCnfVnixlS810VwZmzDEqVvj\n1gZbVxrCluApObKCurG48JCUoYPRhXoIXY6fevxsgoLfV/c+fZDP4M4OoOxGsvsUwn3HHrC7LIe7\nTnLijdh5CE5YpL2OJyTKEtR3oNTO2pZYoLYDdEYP8RHbS4r7tYSCsu8qSp+Cl7xea5Qu937AJ6Na\nUA+MhMr+9X7akDDfF4cZmAbZyu9YhShNEjEWKwLDBy925cMeFNSdZxIk6Fa52kdu/cpzq7xU59aU\ndU1c1w3vlVJgPsL8EHyA2yXxfKtcnp3bpXI6wHFk0BtmE2hCysAFlqkwTVNgMmQFa+AjyikH6yPE\ncIfTK9i0l3PiMBy94wdEwljGI1tp6twuxuW5cz47p2PGhoS3hUYpIjlT58EtwSpBRDsozGWX2NcI\nwq5OymCEQK0kYzkm5hnKNF4NeVKR3UBFGFnpfXCchIej8VCMYzGOB+XNIajJs4Gos7oxV8gtQGwf\nML5uMJnztsCfbM61OssmFDGyCJdNeGnwvDkfVwuOiO8+Hpa4Ac9X4Zs18der8/XNqTL45ZzoVC43\nZRqKeqcNuNXGdhu7d0QwRbkK0yhMBqU1ZDFSVdrh0334h46fTVD4fO/9sSQB9p7Avkvfn6t7UMhZ\nKCl25rFPCGK2vz8PZV+NwGCI44m9n/FJ6JVdc9B2eWw333sRu63aYI8Adwn5H4xD5d4Y/UT8FuQH\n2YW8/nsf1sq+bkIpOZiX0T6VVzcq1bjp1ZWBcbGNl/bCpR0oXVklFJZbX9n8yq1euFxvPN3gsnZe\nbnGd8yHzcMzMx4HmhqFsTcNtaBVebsZ1aby1gN1OqqTS97EkYWKboGQlHeYYTdpO3BpORxAP9eTR\njbZ2pAb2t/vAe0fMSYC4k5NQNw+16jXUnOoaSkljBPgsPuNCnjp92qgFbho7Y07CnCFrxlUYfSDZ\nkZToovQ2QqZ/UfLsOxNWcKukPVPsLYJanuAwwTIbh8lZJjgclcMMBzGKxetbhlJuRn9Rrqo8OzwP\nIZnysRovK1yuyrwQFn0YHzfj23XwzXXwzRoTrObKICFdKO68rPDNTfjqNvjqCuWoHJfEYRbmJYWC\nuEM3ZXPjssa909157oN1U7wK2eDQIVUndaX2+8z/Dx8/m6DwymZUQYbfi/79Z/vC2h8yG7EY736K\nOLJDgc0DNFRcqRbnc3fGjkEIZ17dNQQFRoB/7pMO8RwApv6pS3jHItgr4vLupBRjOuc18ryCo/Q+\nJt2bj/cQEYbRkRGNEdqGyRJ0R5tD33EKKmRXRmjFYOoBvdaMFQsyld94qeFr6KlTPNLk1lZuduNa\nb9xqZb3CdlOsJ949dk5n4/wwKCFBw9M6oINuwlJ3deOdm0A23FcoM6KhV5BkJnllnjNlVt7ocUel\nCm6dZxrDE14N88Z6G7TRgYGUQvJOplFUSHkwacamO8ej0G1wvQ3qOtj6CCj6yMzdOIhwTIkXDX3G\n0K1wpuKMFBiQkZxeoqErLYx8pxmmMljmEDxFg5JeJOSjVDuig0Q4VZWkqEQ3f8I45ih9dHRmIFeB\nJUNqWDZAMR90dV6Y+LY1/uo5sfqKT4bqRK3Cr79z/vIp8VUVMo1aM3kUZFpJ1risxtc35Xk4rSjz\naeJRG0ctzCWR54DLT1sPz8nHAmunNfiwKbcn+NoaYygPCnNSijhX/2k+kvBzCgrmCGkvHfbVf+8I\nOvvOGQtVNcZi7D2BKQtTVg5zCmLPULQZq7dQH773ECQ+aNlVmu+7+t1Y9T41uEugiWuUKkRWoXuX\n0ffSJcaO+ZXfENHDXzMakXAyconBxqwJdcf6YOxd7iyBgDSiUx7Vxi4WoiMwXboboQ4wawh5/2NK\ndeN5vdE9bvBSnCE3VjYuVrkOY5MU9fYED28nTmfhODveJBSTzF8DnZWQebcq3J42vkuOaWE+JSD0\nYQAAIABJREFUVHKO1LmkHs5NGnoQKScOhyWQjkTwvG4dywMbzjYGVqPEmOQTbV00dmykBHBrM3rr\nUXIMZauddQu37aI5MqYEUymUEoQiISjgaZpCBEcCKJUtuA97+ykUqncznzzHZy9maEqBIt1hshvC\nOozNQ+h2pMCgiCRU8276CyqFpEZWQ3YCnGSnS4wMf9uFdDFeeoCxXCu1dv7di/PvnzpfVZg0fExU\n4OXWKQ6XVfnm6twsZOazbHy9ZvgYm+G22f9H3ZtH65aX9Z2f5zftvd/3PcM9994aoIqpgGKGSgRp\ncUDF4NAYiZqIhl4ap9WIbSedNtGk07qMplcSNdq2Q1hGJaC0iiTEuARNiGJAxKIQZSjmGqjhTmd6\n33cPv6n/ePa5kLSrrU6nXfCudVbVnc499z17//YzfL+fL8vWUqRhSJHtMJEqYA2xFk5j5mSo7PnM\nyQ5cNJ6xVPr4mXYofLJlB0Sn75VZ+yqfrBRk/nXOWgk1AjXesPDCcrFQbFgChsg2RdUXzHtdM3sT\nRApulhVrr6uFSkHmHo951z4P+uaNyFmPICLqeRBmc9MnRUtnHYKGc6g8u1Kv5wMGK5p8DNiaNbmo\n5ut5hnX+YowIqZylSxtqKbpuG2DsE7HxTEnoR/AhIsHSD1uW3uCbhClQsiWpyFiBpzYr4NMbqHlO\nDzLaz8+T/z5XcgFyZcoQj3Tv7d0pYlvEtnir03zrVRHqnKdtnLZrJZNiUD0FQpVCyjp8VFZd0aew\ntfggLFeCnQxZNFcxTpXYa3DMMCb6YdI4Pa9J2NYo/0HTkxQGa5zHeYcNs67DgiNjZo9CU6BrZkZG\nMIhRfUvjA2a2MefK7GMxDGNlOxZGRVyQUaVgEEHEkkphrJlYKlM1Sp2SggSF424qHFaBCJuiX3cs\nwulYuHeo3N8bDqPQ2kxjIQxZK58EKVo2GUyoLIKup979QGThIo/Zd9yy4zi3qjRty6aHwy1skmUC\nRpPYGMAXxmAYbKYXcPNM6pG+Pj0OBc4ERfPU/XrmufZAYuaP62Gw8+TeGk1n8oYmaECrehkMwWlw\nyJg0F/DMXCRGh1x6vlTOwkyM0SlALZUyP5H0MBC0aimzbmI+KmYzk7V646raVA+Ls9aAs2Hi7HOw\nRfvfIJaFtThxCJUxRb3gS8VScTXPfBlBrKWK0YCXUpmiRbaRNkC/MHiXWO4I7U5gb2/Fzo7H2sTp\nZss4nnIis5/eGZrWsNMWvK2kCilbhtGyWVfWJ5V+A9NYld5UBTGGHAunRxVnM9b3uADOGdUQBJVz\nO6uBOW2AlAOpayil0E8wUDSyzuiAEWuxwROsxfjKfrWst5CqYujGqBEJKVqmqOKxOMuhNeFbMXra\nMmgYa2gMJliss9RSsVbbAxMndAJQ6RaWbuFoGqMMBtH0JzGZlCcQXWvLVIgjnIyZq1SudLBnC3SQ\nm0wnhT4ljiIci2FtDakB2xlcKUisJMmcxEwCNgVMEtZT5vK2cqmHk9EyVYulsp4Kh1boTIVJZ1HF\nCt4X2qYSxfOxY70Gr1XH1WQ42AqLViiTZZOE42S4NsA6TUSpLDpDt+8JO47cFMZSaD7jaM4y998U\nsGcVAddDMcXOoiCTFcbC2dRfEGfw3tF4h6mCFYMzhmALYXbtlVzUfYhWAKp+VCOMtXaWPc8Hhctk\nEbLMvf3Zk3/OpjxLcLJzO+H8LIKaD6qa55UmIFkv4iCa6dBYR+eMhrgET+ssDsMmbhlTwoWIy5lQ\nVKKbq1KPkPlGmQqlFqZY6fuJcfTIOdjZ9Vy4oePi+Y5lF6AmmsZSpGJ9JRXFlK86TbIq1XC6zWxP\nCuvjwrXLkcOrsDkR8lAwxajj0xhsFfI2cRo0hKVpIsElnE2EUGhMUsWjg+ANyxIoiwQkxBR9qppE\nNfN8x1RMMIQCzivSzYbKlGActFrJBbZDJowzgj4yh9YYrHEYm3R70ugA1oWMdUV1KrUSGqdmMylq\nO/cZ3ymA1/nKWeq4Fa3SpCYNMhdNiJq2Qhk1tGYxCRKFoausAyyCZmBei5bDajm0makTbAEXK24E\nVyu9MRpnlyomCkeT4aExczKgQbZSMbXSZ8vhZJm8KmmDV8l6YyuNc2AdvYHTqXB6PHEtCjcsGhZb\nZWQMqXA0Fk6nxDQmXBAurCw37Ft2dqBpKsFa2lCB4RHdjp8eh8LZS7QsNAawhmLPfAKzQ+2skqii\n/nxmspIxWOtYtJ2WpgipGsKUcSYyGY05+0+G/1YFQ0YUxnHGZ3CiBh1BVC5btfy3Zy0D8yzA68bD\n+Tk+XXem1KRJzBldLxrAiaE1GtqyCp69rmHl/fzmV0yAkCK2VWpvmluOIjAVHQZOWff3KVYkGcQW\nxCS6xrPcEZargl9EFamUwmJpOHANfpXZbEZqGmjaRPAt/VSYxsLpceTyQ5GHHyycHgnpVNezBCFJ\nxRvwGCQa+q3h5DgRQsS5CSMOZyO+6pyhisN7p8TnYFhUS8wGOzG7T3UVa50G9dpZK952HmxmvTZs\nWg2CKbkwxsI4CVMq5OQoeXaWWov3nqbx1JqwpuIbg/UVFzJGhMXCqH2dSDGGxlnCzNu0ts6bHM13\nzLnq4WAMJcM4WjZD5eR4jn07rWybSmorO01hGVR6fWwq6wxrm0mdwYmjmWDpK13RrceYI0OqEA1H\nxXJSlb5kDDhJQGVAgbMUT+crrvHoDKvBOIcrkVwUGDvUROxhPUZ2GsPKB6ZcOZ4qsULrhAurBY+9\nEHjUBcP+IrMKhuXCcK41fGYdCnXu4VXZQ/Wa/dcYg/ca2yZG/QQpJWrVIE0zl/RZBJwlLFqCWASh\nw7KKiX6qDGmiljMokCGZii+KbD+bUyhyLWqKb5q1D0DNBTMfCFJnIIuF1sOic2ruE1FzUlGYisRK\nkzIbMfPWpNA4Ydl4Dla77LqOZeP1ieWE5ZTp85FuTIzmA+J0ElKIxBzpYyFGTz9qTkTjDE0nhM7R\nLNS9aI1O0ZGCKRlrBecDnRf63FNKZJgix6cjl44iVw4t66uO8Wqk9nAdDVVgzm4HC8ZVTLX0feLw\npOLbhHVrgksEt4OL4KaKM9r7t51FTKAfEwvbkmxmsOp38HNWZesDzjllP1ZhsQo0m4HNRqGxlI4U\nsx4ONdGVQPAeciQYi/eFlDPWOkLQwaERy6KzLLoGxDKlCC6CtzTe0rQOZzKVrOwJ44nW4KqQKKTe\nUgYYR1hPsFlXpiKsjbBdWM6tdDNBI5SVY7SJddHh4tBkmrahjYEyjKRpxIllMwpjyWAqe74yVc23\nLEYw4hQ/FyOTDXiEKSWaAD40eGMxMpFzwiVDKp7TWJjIbHpD01pSmahM7Laem3Y8TzjvecLFlpvP\neS42iR07sOoa9pfhEd+Onx6HAvPW32ir4OYsw2A9zhslJYkqyUQEyQXj574dXdM519DYRv3unA2/\nOsx6wlqLyapSjNNMHXKVWKoyAGY7swqm1C15nRA/7xWNURGTt4bQWrrO07UeJFMo2KyKx1QEIVGT\nxYzqsrPG0oWGZbti2e6wGxZ0bdAWxBpSN+FSJhjPaCJFEratGFMo0pBroh8Tw2TYbiPTpAyCvV3L\ncgXe6YTeUTElqUQ7RtI0kcdIihlvLUaEWISTk5HjIzg5KWw3qrCz87bkLH5GpFJNUYDNrJGoWTMd\nT4+jHnKtoxsTIeh03zqnrj7niDHjrMOaqF+bddoaGtUcWGdp2kAqiS4Ki6ahbRLeF4Y+M44TbZq5\nFbXOZC7dQHiv8udCxZqA9wFnNcezaR2hcZSiWD1bAzhovSc4QceGQuMsrXNsp0IU0apMhOk0EbeG\nzbpyfFpZ58oVC9e2hr3BsggW085CspUlS2UwFWsri3n+ExOUaKk4WpsRlxUYWzUINtVCQeYVrqLy\nhzJgij4ovFScSQSj/pD9zrDTBPU7TIkeqETIFUeltY6LvuGWVcPNi44busD51nKxc+wEg1t62u4z\n7VCYn+DWCa6BpjO44PRQsP76CjCn+YJFy36NJisKNRFH4xokJ6aoq8gKeGcxk64GS63oeEcoRrUK\naj5grhTm9adUijqodUjJ7MJEd+NN42nagAsOJwFqJbs4exQq0arWYmtHTIG2CSyXK3a6XXa7XXaa\nhQa4WHVcjnlNjRPBGoIZKTIQFoAUtWfYoPmPUdgOlmH0WIns7Xp2dtTcldLIlOr8hIRrJwOHJ6f0\nQyJgNeYutAybhpIb0lSJQyIlgZqxM40K9IA++z9gHs7O25kBtidwaguLLuHdqMNWq393NUa3ElU0\neXp2spUqagc3kIpKtYM31GRoHLStpe0cTZtYbzNTSXOQDDAH+1hrEWNwMRMaS0bbAGe1NfGu0jSG\n4HVz0xQBE7CmEIJHjA5wnTg673Qqby3et2xrJdlEjo5pm8kbSxwglsLGwMYmFmTaIMhUaX1ldyF4\nGyg+0nilao9JGItBssMYTzAWsUkZFaLJ4RlLQTcVU5ppXKJrWgXxFFqJtALZFW7abWlsixAYomOb\nsqLiaiXnxMoHbly1PKoTbmyFc8aworLywl5rdQjaGR7p69PjUEDty95bQmNoGoWoWquhp1x3JQq5\nZBxerbFSKDlfz0JMU8LqVApXVYCy7Bo2aWTIutqz1sww2DrzE/TCO6uctZvQoaNl9lp+0qKJd2gk\nfXAaQW891IKOiQoxJ0rJGNH9tTVC5z3LpmXZLli0S5bdimXb6LtvK5REdh3JzsMvm+kW+p4YbxFT\nde1VhWGIrLcDUi2LhSAS2awHYqwcHlnaVSFXz/FR5vTUQA2s5tWuiOPSg1vWh0LcCmnQf6CyIKDM\ngq4ida6adGBqVLuMNYqznwY4PSm0i0xwSbMxQkJMpIrBZcMntTJ1phMVcqkYoyu9M1ydYtjLTNNW\n3YKxqkQ9U5UKOhA2xmFMJnhD2wQyETEWLxapldDCotP5wZSEKlYDaDE4L2Rd4BCcU2R6ygrDUZME\na6lYb6gl4WqhWKcPlwLHxtBPlXbme+xMgs2O4C2tNQQXsNkyxEgaEylX7BmOizMeSMUb3T5hLFMF\n6woxWUh6CDRUOhFaUQdtxShDofQ0vupwN6tep5RMKpVVKNywEm5aLrjYWg6csDSGzlU6bzEUkvlM\n0ykA4qqGuAarCDFndAZgQG/VmVhkHRSZeYdRCcO1zvvxESlFlXJWaUZjSTSTxReVJpp5OGmNYK+v\nQFHlILMSsdbrvgM7P+1K1YrCzco2Hyyh8XhxKMNXJ9may6AnuDD/Xm8JztO2LYtFR9cutMQlUyRB\nMTjnKLN5yAdLEwq+sTjvcE4YUyIXaF3BGTuX0QWxhZgM/enINCUKmZgNY58hCwvfII2w6TNuM7A9\nsoxrS9wMEOssQqqKKY9CrXamSDEnXp9N/c0nveFVGMfC6amlbROhga4zOKukaJctMt/4KuAypDPE\nu9dNQs5lDtudU6N9UaR+o+9x/JTWAZkHzUYFRt7osNHNUF1n1N/SNo6mtVijYrPqFKBrZq1Lmk9+\nbUeNPp1Loaj3m8ZqonW3mKMhh0ydMgZDqgHvswqKvCW4gEQhy0Aylm2uyJQY+0RNquSkVgqGWCLJ\nxFnP4q9bfKTqLsxYvS4bU+hMwYlhSur2XYvGC7Yms+cKi1DYk4yfZz85wq6tHNjMPoXzWPaMY897\ndh0EmRglMshnWqUguvv2XteLzql82Zj5hiyKIUspk3MiJ0uJalzShldmTLtT5akIkcqUR7wV2jaw\nkKKR67ViZgmrnVUdRQxFCoIhS9b2QqOTEYweDEan7HYmM6EyBFJN1JkhUJizH3LWVsOCD57Ge7xz\n8w2uGQYaJacJUGk2P5WCxt4bwUghWMEHME7bm1RUw982rW4ZTEVcJFXPOBam08qVo1P6TUKqZ2ED\ngUAplkrPsE40YY+BkeASTSikVp2G/RShVGxxlBrnAayllKy4OlFjUq1FU7Aj9NvKyfGAs4YmKCi1\nObM+z0rCMx9HLoWUPqk50LDdjJvTt3XWoBJ0b4VqZ4EaSsd23mOtHhLOBXypuJLn1aJWdV0XaILD\n2IotgiuipqOU1UYd83WLe8qJcZywsVJT0YeJhWUL4z6YztBvKzUaGiOUHAle2zlnhTboGemiHkDD\nVJAJalEYimuUXpWTUeGWzE1otRjcDM1R7YZUQbzDSsTbqhmbKatJywg7ndB6Qxcqna90FpbeEBDs\nWNmvDeesp5XKvhhW1bIsBjslMpGtq2zPwJOP4PVffCiIyO1otsPZ6wnAPwD2gW8FLs8//7211t/4\nf/xcaEnn5zj2M4hppGCSftOmaWKIWWPaoiMnSClhG6cmpqxPC+dUAlzipPVFLTRWWHUNKc/5h4L2\n64DYohWDaMOQpeC8KhFT0t+HNfofLxjnELSNKUUn/WeDsFKZTT0aDhOC0AXLIrQsfIezHmM0mSGW\nQikwjomJwrjNTHXC7ZUZ892wt2ppz+0omXnsWQ+Ra2OmrSPtrsd2mVgNsXqOjq6yPUr0JTGUSpcr\nq/2AW7Q0sgfllCEWrpxapO0wklgtHKYkNptjfOsZayZvJpwTpikTGoeIVbaDZEhGn361IE7YrhVh\nb13GNxMiljxlHaa1DuOcvkdUajLqLM3M05nMFAeadh+bC1bUUF5rwnpLjXMbZsE5zeRUbH7FFINz\n4DNKnUYrkKa1WFtwXrBJsf25ZDCZVDKJiVwSZko4DCVGJOnWAjt7MnYTe15o+sLQQsqzvyIXfNMC\nCSQqyUg8Yh3WdORJmHpVbDpnCcESfGDKieo0DKcUQ0qWXCwlZnKJiPPYVGkU9UPKDomRMUNfLdHA\nM1ZJh+8S2bdwwQoLX+lMoQuWEGdsvUSIO9Bbqgxsa09ZjPTekdwjv9X/iw+FWuvdwHMARMQCnwDe\nAHwT8KO11n/6SD+XGCGEBuuUBVBTVmPLTEHKo0Zzx0lLTkq5blm2s7CplkxOcbZXF6RmpCrjrrWe\nKiqKSTGTauXMDlmAWpPqAvIMWKnKijRnLMeqaUfWWIwUUppUZjuTfHSuoVCVcZuIU6FU1VW4ORS2\n8Q2uqt6+loIRry6LWNisNXR2IpNCT7sDe+c6unOOnZ09SjGcpkP2LlbC9gpmBdv1hKkNnYPNlYE9\neSzLGzc0yxHDioU07O62bMqayT5Af0kIpdCNN7Jwx5QLhWtXhe1xJSwbrl2ZMKWhWVamccRbR07a\nhxojxKwYc1HgJHlS+bIxMLbC2BXWDEjnyEH5E6E1GNQ0ZsXo98NYrFjimDG10LkEdTaxOavcBFdw\nzuBcxRp7fQCqVYGhzpVLUxwF3aq0jdWcyxnXn2cHpVidD8U4D6uzsJkipKr6l1iRGe4zVdhZBRoP\nXWdJyc7W6wJpoqI2a6kGUx0lakWZUiElYcoTNVeK13ZrYlKqlTd4p4yPKSbGWLVnRZCcdKZkElOq\njDVjSmXKwiaqzuFy1+CsZcfrZm0wQlMyjRXOhaDai5hgCJQ4UVKl2IESJkpISFH36SN9/ddqH74Y\n+Eit9Z7/e+7jn/0yYrDOKSw1ZXxRTHgwgSlPOikfixKVo5b81gouBBZdRxcc3nrC7AgzFIpkkhQ6\n64locKrUTLEFyZWc86c85c9MUYIxnpw/6YLUOZEi05zVC5yqB0BMKCeyFE2bnipTr4nUqUDjwIuu\nvoLzdC7gjeCq6Dc+JsZhJG0i/bAlhw2r/QlsYpgSN+cb4eo9sOsw51qONpmlOcfxZuRRF1oOmp6l\nVC7cdoFlU2lll8FYdlbncdUzpYmpHND3T0M45cqx8PO/8T4++MEtJ1cyQx0pPuNo2FkKaejpJ6vt\ni1HvgTFW+4CzFRpzW6BvC9MW+gC9L9gEZizkTt8nb8EbR+sb2pCRCo21OLEk5aOT2kgVVZUaWzFO\nE7KbYBSxN0NykDOPCVC1PQjBKWadjPeWxulA0Rg1YhWrh4gUqCmSp8wwZt0uTJXWofMJ63BWV5yL\nRcQHQ06iXpSZE2FFIb4pZ6xYarKkHnJuIFskG0rQttF7Ico0b10KWQylWnJRDsaUC956pERcUTt8\n9sImZ1JW+3+qllEMg0TeeyVydZMZdzJlCXst4Cq7TjCLiK0RoiEkwdoRKxOkEWqkGuhr4bj/c8Kx\nfcrr64Bf+pQfv1JE/jvgD4H/6c+MjENwxRDnJ/sieDpnNZ8xR+XsxzqvH/XPeOtoQsuiW7AMjqVr\nWXUtKyMwD/nEJEbjGavQx0SazU/qg8z6TSt5hptctz9dt53Lmetx3tvbGaVWS4VcKEQSyg2o2TCN\nMIzKdSwIzlka51n4htboDt8ZjWCnVPKUGPuR7XZNvz2mLk8JKTHFkcyKkyisfIAp4tIhj95puGAy\nj96HNjzAcHhIf2zZSS1hZ6JkS7tccuXSBzGxUo2hLBY0e49lr60crALf94rn8/H7r/J7f3jKW373\nKg/ed5mHHjrCi2F/saJtMpv1QGgE7xwpn7EdKqmcYWhVU1IFMoZhXRicTuanolqJFBy1qZrhYD3L\nJsw+CQ3DLUXzGLLqwdUnAjgpGtQSzrwnmTOdiLH6dxtjCM7jqhBTJpeknhKn+g2MkJwSrlSZoEnR\nOelcIxVIiAJSKTAH1WINuyEwJVEkvTCnc2l1aqxWGt44arTEKqQpqLvCVbIXimRMY2aGqF4nNUNN\nQs3aqq5ay8KDK4WWghHDca5MVgVy3hg6DG2xSBROtwkD7FhLZwRKZre1DKUwmYKzc1VU19iq6VtD\n7DVbo3iuTJaHtvER38z/NbIkA/CVwPfMP/VTwA+gA9YfAH4Y+Bt/yp+7HgbjgsUWQ0HoGs+ub2mA\nUSrFJAaJ2hJIuZ6WvFgEdvYadnYCO8GzGzqWoWFRhVJmHJp4Zf5V9SFQQK6zEGbLclHrcJ5pLLnO\n0+rKLDzSJ5SzVvMuFb2kw7OqqDNtSypDX1VxmBRB71pHYx3eeZ2eyxwQM2suhnFkGEc2/YacEyVO\nrE97wm5FcExdYS2ZXbNgdQwcXeHB8QGu+hXBVNpFR20rf3T/hmxbzLCmPYBpGFiI59wNF7j34w9x\nU3OF84t92mXhUvMRWG75qq96NC/5qsfz7vc8kbvuCvzKr7yHd7/jYxjg4OYFglBSxoghpvQpDlC5\nnsFZ5zuuTJB7IRmNwqsO0pBhWXDeY5wjhaICqApTTCTAzVsdqdqqeWfwjSU0elifEbPEaOVojJBy\nQaydLcwZcYZcrQJoJKKQX91U1az0rPV2pO8j05jmzE8dNmNRebOziDdzMpUhpVmEZqHUyBQTNSny\nLUUwutrQrNCkMgrvreL/pRLaigstzupMI06FcQCqQl52vbDnRlqJePTaWcXKzvz+NQYaSZSUOB4N\nV0LVlqBAH4XJVcYqbEtlyJVGdLNd60hMZwnbmW0RNlPm4REe2P75tg9fBryr1vowwNl/AUTkVcCv\n/2l/6FPDYLpFqDZlbHDsLlYcLDpCgd5FBOhjZEjqG3dScU2laSG04BsFbLRtpXUeN2lmA3Nke5r0\naZ6zUnw0yTkrLSjrVqPMKDQ1NhTEuDmwVS9+7W+9CpzOQDCiF5cg1KROwBg1Z7FWR82TKvx8oHGe\nYDzGWNUEFJjSxDBNbMeBKSfGacSYQt3C5jRzcq3nhnMPsXPDAjckPvjee3nqU57Ghw8n2oPIEx63\nS9x6PvC+DR95cM0Nt6oAKG9H2hA4vnLKzZPjgcPK+0rh1nOHXFgueeyTLlCHc3ziIxv2b/wgz3oW\nPOFZj+dFf/mVvP2tHb/1K7/G2/7g9zl8cM3eTQ22UXjIOCi+3hqVbl93mM6HRY2VaZtwRkv/mpVH\nEYyjOiHmBiQypMQYI3HewZdacWIQo5untgkMbmSyBTfD/PUm1x681jo7Zit5TpyyYrFmfqLX2fIu\nulKdUmY76EyqzBoDM2+rqqk0bWBnsaBxXjdgRnBO06uqqeSSZlGag2oRCmVUX4SpQIlINVg0jata\nja6HhLFWN1I1M8VMnCouQefgwCX2WsFYy7hVUlRvPGJQS3Up83VS+UQPx71K8xdWCMEgNpMsZA84\nDbtxVZiiYvBigatj4VqKXC6ZK3/OM4WX8Smtw1kIzPzDlwJ/8md/ikpjDTcenOPGiwe0zkBJbKcB\n79UIUyWTTja6vjT6pZdqyCnSNp494+hcRzMn7ZqYyXFgk7acTGui1QMhzWVwzWelpFCrwcyORmIB\nLypsKoBxeNsgtlLyQHBWh0wkxBVyMVSnAS7ioMWQY0ZsVZVe2+JNg5cGKw5TK+TMNPSM40g/Tmym\nY4Z8zPnqyNvA0QZW1474yLTloXcZ7n37wE37u9z90INcWz/MYy4e8Na3rHn0lDGP85y76GhMZbPN\nXL3kuOFx5+lubnn3h65hpxvZrXCVwtV+4Nq5E/YOFqRrcHh1w8HNwvs2v8fubTs88yVfwAtf8jO8\n/d2XeONrfo7/+Etv5Pieh9i5tWG5sGw2vbIQcyLFig2CsQq4jNUqEzMmyqDkqhwj4DFi6bynJKGX\nQkxpBsvMgjInWCytS+w6x+BGTmtWzXv1lOpJKZHm7InghCRKdM150koCYSzQJoFcoCbilNhuB6Zc\nlHtABq8YOIfavTvvWDjHwgeyU3WnoeKN6k4oEIxnqoYSM2UU4gBjP1AyVNNoGI8pBFOuH2BVRrZj\nYTsV+nWmbCpuUvjJjZ3lpi7QBRW4lUXFVat6i1zpvK5lY64MCYoTdkLBRzjnAzd3hoN25CDoAdx4\nQ1uhmIxFD4WpGk6j4+GYuZIqQ//nhGObA2C+BPj2T/npfywiz0Gfux//z37tT30ZY7j53HluPjjg\nws4ubp7wt16n9lkMh9tTvGdGaxlCkHk/XfHO0rUdC9/gS2HaDoxxpB82nAzHbMvE5A2JylRhLIUy\nZmK6DlJTUrJ1M7hV2QfaxzplJxiw1inExViMFS2Nq/aa+oG2DlFVeHu7S3YWLV0TNMnHqBItp0SM\ncf4ae9b9gPiWIU9UuyVNhSvXLCdXHs3zP/tbeeBtf8DRWLh29zHPf/qLGbaVi+eO+OhgD5msAAAg\nAElEQVQ7f5fje495wRctsA1gF9z6pMjHP3I/H/71wvmFw4ZLfHin4eJUufmmgaO7e9b9FXZyx623\nLLj7/Wt2bj3Pffc9wMa9ERt+ld2n/EO+/n/7Z3zZV7+cN/70j/CW1/8r3NJycLDiaNowuULrDI1e\nBBgLU4yYqiKmalXCm2d9gsNjvcdnQx221ARR1/bkqlsAcQbrnTIanMPbUYVmzOq9qpTsM9+ERtyr\n7wRJ1JlapTCXxJQSwxgZ40RK8yp73tVLVQHSovM0rX4EZ0lGN0mqjTGUpGnZMarCMk+aNzFNQpwc\nKaXrMF6nVl6KZKwTEhYGbQF8qXhr6RrD+UZnA02ttEUVjtYbvCvYKgRj6EJHrZXNMKpZzKgPpbGw\nazK7Hm7YDVxcZnZdZccITc2MQcBVSjRUN1/vsTL2hTg98gXA/9fchw1w/j/7uZf/v/08zhguLFcc\nhI5l1RLRi5AVOUGMPaVGmlaoZo55k4TUiSAtnfO03mufWRMxR7bDltN+Qz9tibaSi9Vw1iwatNqX\nWeGmDyRxqjvX4ClFhRsLtgHXGqyteBcI1gIG8QYXKrZEVTr6jPcFipBiQXDs73TsLFva4AhBKcym\nVpJoCzNMA33cMubEdihMaaDdy/im4/LVwrd97ct42Uu+m29+6VUmt0NOmZ1kGPPIan+XO9/yVl77\nKz/IpXt+n3/3BuFzvqTlTx7YcOvNX8gLnvoF/M5vv41u0fO8F76A3/iPb+Tt5pRbHv8xnnvHivM3\nZ3q3YKyRfDSSzl2l3bvAVjreMT7Eg8OHuf15d/Atz/01nvXi1/Bz3//3eeij9/DYJ+xz5LaUEkmx\naLXgHDUbEplsDBPQWUsSBYpSim4RFPhEjIVY8tw+aE6DdRWPJ41VdQYejc8j6ewmZ2CWfc8HBZL0\nQEA5jBX9+3IaGYbEZsz0Y9JouiTUbHT2YA0hBELraNqgkmejGypjzvwWqGIw6fezJKMD0myUMG0b\ngpEZWluIJVHrqNsP5zDiCNWwKg4vovOSmFmUhJkiNauatGmt3oRTxEkluIItvSLfcmJRYKlyGHwF\nlxOuZFbBs7+wLHyiNQUPmAaysUwTVLHkKUGBpWkIVvgMs05XnZpOE8VWbKMnXSmR0+GEk+0JmUjT\nnoVkapnkga4JdE2jT5UUlYdoYSKznvoZlaW92ThVUjZMuVKiZkgYp/r0Sp2Tr7VnxelBId5gG+0T\nG6fVgqCUH/EFyaqzSDkTkuZLlpgR8RqA4sDYgnEV7JwNifo2phyJZWSIidO+kGrioFo2h5EXPu0l\nvOxLv5Oar9K6nhjXHCwey/3v/F2+7RWv4Lu+6x/xope+mGC+kT/8k9t4xTd9M6/76X/GK/7yN3DP\n5S1f/te+kE9sT3n51/0V3vSqn+f//Kdv5Hf++EP89p/8Mr/42tdw/qDnOV8ycPvjFqzvm7APV4b7\n3srixht55q0fYsc40vhO3nn6Jdz+9X+dH/2c5/OT//Pf4Q9+7de46TELytIR3aQ3JqK5jdUwFs1q\nTKIu1CEVgk1YZmx9hpKKHpx1/t5jFYpiK262VpuzwB8+RWwmWkVYr1LsPCd5nWV6pFJIUyROkc0Q\n6YfKMOpHTJaSNQZA/FztGauzCpEZjFNhxvqfzZrq3GrWolmmpeZ5Za3zADH6dQgF48B5h2+8mumk\nzKxIwar8lZgN21TwTk2A2aj6U5KjdTpML0nJ2FihLapePLsuzXy/6KxFK904/1qVQg1CqUZ1NkYz\nMzvrKeYz7VBAn84xjUxFBTJDHLk2HXOlv8Y6rylWsxTUsMP1gBRXBVuL7qGLR6wlz4fCxExRKpVU\nz8JlZRYQ6b69ipYLZ/JXY9Qe7YPBNwbfGnxrCbMARSm/GtdeRVObXFBbakwJqWrSkuJpmgZjhWQy\n02wWKikxpUw/jYyxZ0qDGrokEXOFtOThSyd86Steyl1v+zgPT5f40i/6cvx4wmTvpzt3C3v7F3n1\na36A5770OZTNis9+9hdz5eSI21/8Ih6ukdiO/OJrf4YL9ph//QuvY7rpHO/+0J3c+du/xd/65m/l\nS5/6+bztP7yPD77+g7z5vtfzrBfCHf9NQ38tcLB3yNX3/Bjnb/s8HvJQDz6LdwyWR128yLe89l/y\n1H/+hfzKD30/dntMe3NLMZs511L1H9ukiUt9qviUMFEJUMEJJaH5FglKrOoITIKvatlGCsZUhdcE\nh5gyw2xmXJ4xODsj+YBKUWVpVbGYpMQUB8Y4MQyFTS9sB42kS+O8pl6ojiWGRBwN1ESdKq5o7kQw\nDSlncs7EOFHKBBSsBKoRQlBgcK2RzEjJShY3Ihiv4N84E6RL1pWtdQ3FC8kZUl80+CUXTgAfM8FA\nK4Y2w6oKPjmmVBgmBcyMUWG3Yc4wtXY+UGdtfM4QpSDVkHCknClEOi8cWIM5U/E+wtenxaFQaqGf\nRhaNxRYhToWT8ZRL/RWOhlOSBcRSJjUPpVpxtqjScRgZhoHRWpahpZZKn0ZGJkxj8CkQUXWjsUA1\nWAvVntGYdb1YzbynlKJ4t8YSWkNoAqFRvLafKwVnG6xzKm4pFWMcYixTnDjLkC+T2r+Ns1RTiWRK\nraSove5m3LCdtozTxBgT6yEhXcPhNah9oGGH93z0d3j73XeTt4/mK77ySYxxQ3PzeT73hd/J+vRe\nNily/lE385a3vIF3fvC9fPVL/xav/7ev44lPeSLbjce3T6ZKzxd81l/k537mJ/gf/+Yref/dH+Zr\nv/ZlfN3XCpvDY97xrr/L777/rfzm63+cZ97xII95huf+y4/mI+b9rJ76JO6553V0576RD7YHfGJM\nfO4rX8ntj38CP/TKb2Jz9Sr7tzjiGHX4airTmNXMgyWXQkzKPqyk+emrZKqaBbJgimDmyHC1Ws+O\nWWdmBqfX6mBmXpwlbdWqc4JSVFmZUUr2ME7EGJkmGAbDdgtjD3HU9bKbP/9ooz79+wmPsiiqN/iZ\n522sOjO7rqM0BZKnVku3aBFjKaUwxcg2Jvo+qQ+HCkV1GFLAGIt3BiOBlCp9mUiTw4wTQaDJGeug\nsZWFySwMDFkfWidrONzACbCskVVTOb8Qlk5t+SYVlWgz2/0LRAxDn1n3mQGtuFfe0joVcj3S1yO3\nTv3/+CqlshlHDuOW+44vcfcDH+XDD9zLJ64csR4zaRKmHuJgGLb6pIlDZtxktieZzQaGDH0ZOIkb\nRgrZVvAj2U6IT7QNrFqDswUfKraZHXxF9fy1FnCVEDxt61gsG1bdkmXT0bmgkJTFDm3X4VtwTSG0\njuVij8WyoVnBat/RrTyhDbRLh2kiSRLVCplInwa2dU3ujjEXjtm/rXLh9padx4BddVydlnzivpGX\nvfjbed8f92yGFrPxfN8P/m0uXRkx9oBF2/DEpxt+8Zd/go/93vu48elP50MPrvniF/1VPnHpPl74\nuV/E1QcO+cavfxn33/MBvvzLv5Cf+Rc/y9/+nu/nZ1/9ixyuB+752HvoL93HsjvHF33eZ/F9r3wl\nv/AP/z0fvesL+Nc/suYx7THnD6+Q73oz5z7wKh6+/HIw76Szl/iNq8fUv/Ri/uYbX8fu8onYhyqL\n6mgniHFBGpyyJasjR2E8nSijxrINMTFViFEoOSA0jDqJ0Fi7GqhVORfeJ3ynsFljdAjsrZrIKipi\ny6kgRUvrlCYkZwXOToLtjVKioyGNDVI9zgghCBf2WvZXAesTqUycjCNHQ6FfC6enPcM2I8nS2QUL\n19IYoWlHdvci5w4GLpyP3HSD4zGP3uGmiwv2dx1N53BhocSkJtC0C7pFx2q3wXUZ6wu4wGCXXKPj\n4dRwaQgcRs/R5DnshWvFce9kufNq4feuwe+fON5zWHjH1vBHG+HeE8NRb9kmw3ZqGPtAnCy5OLaT\nod8Kxxu4sobjwWCyY1cMnR051z2y1gE+TSqFSuXa9oirU2UoA32OjEVnAanMCfVoOIomUs8Mvlzo\n+4ntZmC0DadDZjtObKaoxiejWG+xmvYs2WB9oQ6JNKlsl3JGFgJnLU1rCJ3GuXdtQ7cItK3FB0cT\nvH4eOUvBVmt1ES1ltQOuGn1ezhR/hb5uGVLGucRyz7JcVS6GDmk6prLk5Og8H7kP/uDOD/OCZ3wx\nz3zSF3P+YMFd7/wod73rA+zv38j//mM/yXf/3W9hZ9Xxgs//XL73f/k73Pbkx3Hp3g/z1V/9Vbzn\n/XezHfTdvP/++3nve9/L05/2dH7kh3+E53/OC/itN72FF33Ri9hZnecJT346v/VL/4673v9DrG4c\nuecuzzd813fzyz//Wr7nH387b33Tv+K2J+8Qljex9+hbCN3I+KG/x0f3ns75m7+Xj5/Cbc/8Qv76\nr76Wf/5XXoI7eQh7Q0O3mThdVM71lW2v5XoXIGSHJDu3VWcBGWfOUPUOWCmk6ywKCMEBRjMdLBhX\nsFa1ImeYAh0OqvPQmgopzglbuvngbLMhmSbA3r5w/hzsHxga54hZmZDrdWE4yYzDiPEW06gGJZdI\nZcJIZrkIhOCoUvBG16G1qoFpCqLqQZE5dxQkF0QUI2hcRYLohshHksAYC5OBaCvJV6ZSOZlgkyoP\nHlWO+8KQADGsfKGplbVkNi5zKHB57DGlsHKwdI44wVGfONnCeqrYFpqgn9t5oQ0eGB/R/fhpUSkg\nsMkTD6+PeXgzcC1mNhj6ZJmKJRajT5isoA5w1OpIUVivJ46Pe05Oey5fO+XK4Qmn254IYCyutbSd\nYdEJq5VhZwldpwAWa0XfAQs+KER0sQwsFp5u6ekWnhAszlus0xtf5uGXyOzZEA10ccZiRY0wziig\nNEqi+EJvB3q/xe/0rG4YuXBL5dbbVjzhSTs87akX+At3nOc5d1zjb3zdV/Ci530jN92cue+eK/z6\nv/0PPPkpz0DwpGr5xde9nrvv/hihafhrL/96umXDwQ0XuP/BB+i6wJ+854+ZponFYsFzn/dc7nzX\nnXzN13wNcTNy222P4+lPezpf8ZIv5yd/9Af5zTe/hvfdfRd33PE8XvxlL+XVP/UvWBbhB/77X8Ad\nfS533zmwPjzlzrfdxfaj+1wN38DwiR0efO9bOK5b3rueKM/4i3zLq17NtWmHcDiRJcGQ2RRhM8J2\nzApenXtflY0r/drMANWSFauXc5nXhhlvDV3wtI1RqI1TnLz1OsyzTlWtPni1ss+Hi8p6VVBljOpZ\nugD7e5XzB8JNN3rOn4dFOxD8lqWP7AXYteByYVon+pPIuE1MQ2QYB2KO2k6USOuEzglOIuQtpDWN\nJBaNZdFYDa4VRcrrv0/zPsSCaQymE+yqYpYe6RaktqN3nhNruYbnvkm4dxSuiiEvGvyqwXYN7dLT\nLRVI2y4cvtPWasqw7uHqUeGhS5X7LlceuFy5dmQ4OhWO15H1NjLFisgjf/5/WhwKBoNjFqNUTVNC\nNNjDWId1DpnNOCKOWoSShDFVNkPk6HTgyuGGh443XN30nMTIUDJRZpx40ByI1icWbWW5qHSdqiBD\nV/AdNJ3QdoZ2zusLweOsU0NQ1Yt3miLDMDL0kTRmjZcrgqkWL55gWpwEBXKKIcbENo6s4ylRerq9\nzM75wu5Fx8Ubz3Hx/EUuHFzgwgXLU24/x6O7/5aleRSNNfzwP/kRXBN43vOfz7PveDbve/8HeNQt\nj+Vnf/41/Js3vRnEMcZMHAaedcdf4NKVqzz7Oc/m4Ycf5ju+4zv48R/7cW6//Xa6bsGb3/SbPPG2\nJ/Kqn30V//4338yyFZbn1vzCL3+An/7B9/HCr3wcjzp3hYfv/yj7+8I/+Ed/n3svt1y9fMKzn7yk\n/+23cvhHr6W55XNY7T2Gj8g9XJ5GLh8dsf/5L+Kbf/gnWF+FIB07xTNaTxyFcfhk2nEtyoF0VvBO\n5sHt/N4WJSnXojLw4C1tGwiNVQpXU7FO9SCKm55DYIzOIFLKxJgZp0lZFqIDycYLy9awvw/nzzvO\nH1jO7Vt2dxV57mrElIEghSCWOgjbk8SwTmw2E8M2Mo2FnA0iAedbrPPkolLtYZrIOeK9pWsbrLOz\nlF0PBDtj7JwFF8C3hm7H0e44/MpiO4/pWkrTsm1aeuMozrNYWna6xE4YWLVb9v3EhbZyECrnLBy4\nyp4XVsHinGfIhqOhcrSFK6NwJQUuD47La+FoK/RRK6pH+vq0aB+cWC40B1RjqPGEvqjd04o+ARAF\nnRigViFNhVoSMSqN6MiMpJhn3XvGJUPxowpCjMM1nmAqoaolNxtLTmCcsM1QnaFthbYVfGjU+FRl\n7lvnr6FGTWyafRDZqbzaW91xi1O8uRVHNZZSM7UmUszkNLBoHd3Cs9oTVvuG3Z1GGQISuXDxPPED\nz+VD92c+78tu5ZXf+T9wy6MPePbzn8Pv/+FbefyjnsKTn/x4Do+PWe7s85rX/iqPufUW7njG7dQU\n+Te//ibuu+cBPucFTybGyBve8AaWyyWPe+zj+IWf/zl+4v/4Me77+IM84bYn8q5338kNey3P/exv\n4AWf/xG+5tueyZXLlYfuWXD44CXazWVuffyjePVP/RT/69/7l3zo5t/myY9fcfHet3MlfyPbG76e\n/Wd+AdPOEzmJmTuPt3zFX305H3jH73Pnq3+Ki4/foZz2lCokUanumcpPKnhXCMFSqlK6UyrEKWFR\nCbFzjkaURFQQgkeNTk7bgFryzOZU6XqKmThFUozqWEVBvNbrsLL1ggue1crRhERw0FhHnOP8YsrE\n4f+i7s3DbD3LMt/fO37DWjXXrj1lJzszJCEBMoGJEiAEkgOiDEqjKKfB7lawj5524KB2c7qbQaFB\nFBygUUFsAdFuQECQAAIiMyQhIeNOsrPnXXtX1Rq/73un/uNdFdE+rfHS0xf9XVclVWvXsHet9b3v\n+zzPff9uT9cqGpfR91PpsjAgSWIypKiZFAo/6Egpuw1DkPlk4h0uGryQSJUpW4gsz86YuAzMUUJC\nBQJLTA1JBFJQCGXzCWlGaqpMIgWVg3plpJKwuiDYWUl2WdhRCvpFoqcDlRC4LkvrpRIEJRgQ2QqR\n2ASWJUSrqGto/CPvNH5nLApSsaO3BF6QmohuxvmXpqD1ubuchCQlRddFcJlL4H3ORkhtR9t0CCVB\nBKwX6DrQ6+WdxGiVuXwxW6CDEPh+ysnTPidSZc5gpvyQMs8vxYBzMYeahJYY4sO5hlpHvElYndBK\n5iOuVgiTPRMgMKrKHW6lKKxFSU9RWPo9RdULaCRF3eHaZW77/ApPu+EKPvzhD7N+Yp1rn/IU9pyx\ni2a6yYH77+KMM3YRQmRt5072n3MB7/z9P4Qfeh6PvfQSnvl9z0GaP+Ptb38bV151FVddeTU33/wJ\nOtfxlt/8Dd72tt9mOvL8wr/9Ob51+5382pteyYt++Bze9fb30IhNnnvT87nxpmfy2CuvhsmIziyy\nduZZ/OsfWOMX3/NVFi4aMrl0Lxv+Mnavfw172y08eFHB8bUnc5azfM5Nef5rfpkjt97G4O7PMbfX\nEF0kGUgiR8QpIRFWEbzDaEVMGiGzHiD4rONXKs1KOpmnCzBLg9pO7Mpw0xAiznc4F3A+Lw4pJYzW\ns4BhRaFmcBRrKGpNr5aURUNVGkpT0gZPch2taPAx4pzPvoko6dqIMCBNxgKmJJm0Q4LvQEb6/RJj\nTJ4mhUTXBVywCPJoWsnMAtUoRAQRFV4okiH3sFLMdmkvcJ3Ed2AKTZM8nfPZF6INUSqkSPQXJL2i\npS4CvTrRrxU2guoiJGYnrwyVaQWccj5ne0RJXUETEtPwv56n8I+6lFLUZcW8D/joUW2eP7sU0XR0\nBNoQadv8S8x4tiw0EELiY2LsI8oGpMnRXz2TKLqIiA0qJqRPBJlrUCOnlEbjqxbRJbxUIC0paYLz\naGkJThCEw4cuy2lDxrlJJFqpTJu2jp4ticYQyOIjRc44TEGiRYWLDmNrkIIgRnRdwWCro66OYuS5\nzBUFn/7sEDeYZ3BqyLvf8wGefOP1dM6xWC7zxMufxAf++I+QqWOhX/OYyx7PkaOnOXF0zG/81u/y\n6v/4S+zZu5+n33g9k3bKHbffwX96/Rv59//x/+Xrt9/C9z73+3jOs76fK5/0ON7x9nfxf/3Uy/ix\nf/MqfvcNr2HVLnD85Cle+vKXccONN/Frv/kOltZW2bn3TC65ZD/PeNZTsf038vr3/Qhzi5vU49tx\nl/8kh/dr5k5/ih2h4sTitajxFl+qV3n5W97B6579FNrREXqFxZWaZAyQI3GNgmQ8pZW0PnMhvTf4\nmJDCkTTY2eKZuhZkDtONyZKSmt20HZ5MUupiIKQZOSvl/A+rctCMMgpkwliNtpak2gxJCZJONKBa\nYoozjUWWNCeXiNoySS0uJUKUNGOPGEemTWA89mgtKYqALT1KRqSwEECJjl6l0EpQz1mUNcTOo9S2\ndiAhi4QWiUKUCFngm0BLDnIJ0uODoQsB/BThJhg8qbQ5t8FG+qWkKgWL1lNrUC6hNExaAUUiBejG\nhqZxnA4SFzSLLrDmBdN/AOdEvepVr/r/615/xNebfuVXXnXlBecipSI6j2s6cJFo8q7hBbQh0c6c\niFkZMjuaJjJlc4Z0R8isHSAHt1QFWJshHikJggiEWThoyi3s/P8ZKzClMOPxk1OPpw3TSUfTepqm\no2tcBqTGOFPcpYeFT9sBqnFm0yZkVJzWUBaJujSYcoxAIYshLozo2OLY7Tfyguf9Sz71Fx9ic3Cc\niy6+iAcOHmF1eZlzzt7Puefs5/jxY9iq5vTmAKTk3HPOwTnPB//bh3j84x/PwuISr3nNa9l/1jm8\n9CUv4bfe+pvc9IwbueryK7j55k9y6NAhrDGMxkOe/KSn8l3X38COld088clP4WjT8ZbffgdHDq9z\n94FTfOzmj/Bf33cze3fu4qlP+16Gmx0nb/kEsrfBQ4NPcPaCpCzXEYOK+bVz6bWrTIYP0Z1zPuef\neQG3/MH7WV3S2CXNjiIiKuhVBUZmN2TnBU3nQSYKq2eE7IQ2Em1yeG2IXXZBKjlzqWbnoY/u4TTq\n1mVbs/Muw0zSNmw2K1W1UVRVQWE0WgfAk3xmHAQP04lgOIoMh4nRCJoOAgFbK8pejtgLITCdNEyn\ngeAVvtUMNjtGw8h0mBhtOro2S6fLqkQXBdaWmT4tMphH5BhiEDlgSAqV+04qcxy3+2Q+KoLL9Ois\nYBRIYzh/2bCzhB21YqmyrNSa+V6B1RCRdEHQxsjJkDg6NpwYRzaCYJoCPRHZ3Vf0i4L3/mVz9FWv\netXb/r778TvipCCEoC8LkoxEO0enJmzFQAzZV9CFAC4QHbPmXtqG8WTXYZrBgVBkdorCx0TjoJkG\niiJAqUjC5/g3ORtRkogh9yUABAqBousc02nOj8iYtYD3jjT7mUJC0TqcywTpylbYwlIYRVkYlBKz\nEJUM0FBkS+94NKE3SSi9gVyfo1o8wIEHe3zyA6dZLD/PyVMbXP1dVzAcDbnwggvYOL3BH7z7D7j2\nmqu5/oan08XIF7/4ZXpzc3zj1kPsWdvFkeO38ar/8Bre8fbf4A1veiMv/tEXc/+D9/Pil7yYP/vo\nRzh9eoMbb3wGwQWuuOJy3vjmX+W9730v/ZVlYtvx0MEHefRjHsP/83Ov4PEXP5qtdkg3jdzy1Vv5\nxVf+LPsf9Tv8+A+/mmc+6nI+9iev5MHmQe65+eMMnnAu7a672Zx+HRHPw9o1ugfu53u+95lc8dM/\nzS1v/xUuWu7TznsWTZ2P8kYijaVymuG0nfVdEgmXWYuz7I2UslxcCJn5ieRwm+A8IXq6CNO2y4g+\nn/s2sI17yCRlnQSl1GidBURGZzKXlhpJJESPMh5tQBcBVecMz6VaYXoFogBdGEQqmAwVpzc8oy2H\n9wbhe/gWWu8ReHpzkq6QTCfbQJhEmSJ6ttdIBQaBiJmXkBW0gSgSOmb+h2sFWki0MCCzHyTJgLIS\nKz1WiRwpUGoK7XJqGoGQwHqQzhHGiU4k2qQY+VxubfrEcJzYHP1vVj4gEqKI6BRzpkJtwSmKGPEu\nERykTqDaLLX3QjzM7YvbydR6ZmSagUDaacZp+SgYdIGyDhRWYSuQNqF1R1KzgFol8Z2gGY2ZNBLv\nIj7kejGG7IlQQoDMcl2tBSRHCB7fKia6yTHzWlBVBmsUaEnf9DJsVCYKkQgENrbGdEEyHCimB0bc\n8mdX8fjH7ObTn/0ET3/60/jgBz7G2edewMHDDzEdT1lcWeahw0dpXeD2b93J4tISxw4dQ2nBt+65\ng9ZPeP/7/5jnff+zuf57LucPfutN7LvgUXz1G7fz2S9+hisfdxUv+uEX8cUvfYHXvf51HDp8hDPP\nOJO5cp5B2EQbxcE7b+eXfvrlbI1HrK6chWDEf/vQR3nWM27ga+9/M5+8/0+5+uINXnBej8FCYg9n\nML33Ad537HbedOIW3L5fYNdizdLeeT5/+D5ufOXrWNy1l8+89V9z3Vk70FGhS4tMLSHkiDetFT4F\nhMhKx4xzl8SQCCkSXMI7EDbQtoE2RTofcCEyjoG2C3gvMvcg5s66NWBKRV1rSDbDYltyXV4WzPcL\nCmvxeDrfUJiGUivmS8/qfEvXdPTnFboHQUWSdsikaJ1gY6TZOiUYbig2T4NrJTGWTKeOmAzjsaYd\nB3rzjqqE+Z6h17eIKtugJQpD1q1IkxAyIWNCGlCFRhtFMRUUCppJw6SBiEM1kQeOeewyLBaKtbkK\nUZYkI1CywCLRNntQRGzzSNzmPAgnYVMIbm8CR06OH/Ht+B2xKIQUGLkRk27K1njAVjNkEltC5xhF\nz9QHXMxx5TGmvJLO6shtTfdsLXg4GzKSoa+TThCnES9mXgeVE3+Z+dXzC1I9fOwPIeG6gPMz5orK\nKdZylmUptmnTBFKMeEfuN6RI0BIhPDEohFXZ1aYlpcxj1aJU9HoGlSqKYgvXrHDuvus4euxBetUc\nZRm59nuuoO0UR44d5ejxo+zdvZu6X7O2Ywe33fZNlDRceO6j+fyXPs2hQwd44PxLAAoAACAASURB\nVIED7Nq7i4sufDTi8GEWReLIgdt59IX7+NAH/pTXvea1fNeVV/Crb/113v37f8A3brmF2775Lb5y\ny12s7j6TG256FjsXlxApYYwktC3rmwN+/MdeyePOv5fhHW/ANTWyGqN6m6xtJQ73T7N4RuRHN/rs\nevCb/Lu5/5ut1VcT/A08tFBx3mCLa57/Qj77yXfiDt6G27MbZRVFC60uiGE8y+qUhOCRpZ11Hbb7\nRWEW/iOJXaKd+RBaF3AJJinSuoQPghD+OvaOMhOVfBA4l2h9QAdHVVRZip5yklZSEWMEIhZ4Q+Zh\nqIQQkbrQKCOJRhDV7CUmJNZ22CJR9SUpGdqpwnWeILLRKXpJEALXJpJvUeTGn9IGpTLARQgBQaGJ\n2dUZyH4XGTBW50a7TbgZJzN7RDzr0TNPYEUFFvH0g2Khl+lk0Ql8ByEo2iRxdESbUAnaCBNgIwjc\n9H+zk0JMiaGbMuomDPyYNnYEAq0MdCGju+LsF4nO3L3MDWS70f/w+wnysV0KEjKnKrUBoQAViQ5K\nk+WvuQaJCEKm5yiBMYLQiKy2U9nRL6InKZDKZjN3imR4XMa8iSQz8EVIfJBEIlaANznmXKRAqQVF\n6VicmyP5yOJyn2as+eo37uSaKx/FDU95ImVRcPjQt1jbuZvhqZM85rwLWF5a4KFDD2GkZTTxuGMD\n3FRxev04J449xEUXXsyjL72MT3/xc5zTdVz2xEvZs3OJVkxppx2vfs2r+dz1N/DSl/5L9u3by4c/\n8lEee9llvOiH/taTkGKui8hEpOc9+3tZmJzix683tGadkRuw50jBKVNRLLQ0ckqztMDTNiZsPniQ\n9wzeSXjcPnZMd3FAzNHtXOapL/oFDr7leez3LcqN0PVOtrYC0kIloGk8Siqi8MRUZOmq9JCyJdrH\nhG/ztMn5xDQkXEqZnxgDYjbmDCkb3HzIZiTTShpyJmgInmIKc7XG2YCRfhaBB0kGtI4oETK5SBmM\nyEE7qpKZu+gjRkhcUeGrjDsrk0YID3jmtMU7STNuAfWwG3MwbkmziLwFJKrWIBMyZqAtKSPflUio\nWTygtECdaJ3IZOYEwXWkLguajunEqtQsBoVvPVoGXDIMgueUiowLTVu2BFFQaAddJEjDJHrcI18T\nHtmiIIT4HeCZwImU0iWzx5bJuQ/7yTCVH0gpbYh8rn8zcBN5oXpxSulrf9f39zFwuhkyaaeMXEsb\nfA4PyU7WbHxJWX0oRZYmb58WMi8w26BTtkHmen72OsepTKKRKcudjUA4Sak91mStQgY7z4AgPo/A\nOifwIUeaIUAGQMS8OEjQ0mCVQIgGKeJsS8kiGhlACY13LYUWlFZS2kivLqhrh2We/Wcb7vp6x8b6\nmDvvvodLL7qQfq9i7+59rK9v0gwnjOMpLjrvPJbnF/jM5/6K/XvPYjTuuOuOW7j3zrs4vbnOJY+6\ngs994lN87IN/zI//8A9xJLZceMkFLC8usHfnHo7f+y2uetK1fOrTn+E//847uPEZ17PvjDN47nOf\ny1n7z0YpRa/XY8+eM0jdFN9sYeaXec0b/wPv+eM38Np3foofu1xxwwssndcU6w12GBg6g5GR8Qr8\n4Ehw7Ct/xgeXJ5idf0jTh7u7da69/hnEL16POvwZdlx2Jg+NJ4CkKC1TN0Zplce5RubaXgsiOdkr\nRYVrHLENxCbm8BgSQkukkMgZiTvnSMosWU+51JyMHN3YzSLoJQowIpKipK7BiBzk6qPMp8VIxsHZ\nWZNaZMBuUgk8BJFQKmIsFKXI2Y8p5umGE3QSFJbos+AuJDDBkLwhtNBOPEblVCsxG88mEj4FjAbI\nG0pKoIOhqCW2jbS+w8VI5zwbk8AxJVigQTeKuaHAykCSgVGKbLTQCoEoLErKzBdxEZCMU46g+ydd\nFIDfA94CvOvbHnsFcHNK6XVCiFfMPv55MrPx/Nnb1WSQ69V/1zd3KXC83aTzjjY5OhEIKod7upTp\nu5kyLmYTgu1GVBZtPLwIIL+tosj/lbN6NYa/5jBKoDBgrUSrbNXuTD6xtFP/sMouxCyxrYtMCg7S\nE2bJ2FZZCiUR2pLI8lwQD2vufRuwdUGhFVWh6dcF/UpizCYL5Rq7d1iazUX6xTJzCyV333MfXTPh\nmmuu49iho8z1C4ydYoop3/U938UFF5/NYDjm1978Vm75+u1sjU5y8cWX8JhLL2M8HHDHt77O4r49\n3PT8F9I2YwoNLjSs7F1guHGAqlrj53/239CvNB/50w/x22/7bQ4fPc7G6THWaM4/9yyMcvSnc4wW\nIt/31Ofz7176bzn+Izcz/I2j3PnROVbPCqhKMdKKpSjp/IToFCeXJC959G7uXP8Mn7/4d9nb/Tzy\nxAYP7FnlnB/6GW7/1S8zcGOiUdTWMhgP6PVLQvAQE1VtKAuF0YrOz6ZISUGIOQS3mZV+UiCNzPmi\nUuXoBJn1K/k1n9mQbetwMRFMIhiFTF1ODfOKqicwhQMlCL6jHTaEqUeE3DeK2/Bmn18vroOui1md\nGXI5WZTZnNWrwbeJ6TgSCk3bSZomIDBU5Tx1YdE6kULAd1mQpa3OAGLh0TKrO32IILdPCxJdSHQB\nshUko+k6zUYTUSFB52jGgcUSKhHBRrpSMAQGaEKmw1EjMy3KQfI6j/CZPqKb/REtCimlzwgh9v+t\nh58NXDd7/53Ap8mLwrOBd6WUEvAFIcTi3+I2/g+XT4FTfpgZBzMASRARR+4jhFn7ALaNR/nOT3I7\nDJXZIqGyEm12CRFnx+I84VAKtE4UNlEVEmtAy7zbdErgW0+roVMZ+2UFzBWCHT3NfJ2IMuKZHWGV\nQ6gsqgohkWZQkO0MgUpnTUSKCWIGeyoZ6PUKykJTC8t4Y45DDz3EZVc/lsFoxL133oEyBXNzPfbs\nXSUgWB91fPoLX2PH2k6+8IUvc911T0YYTVVAO2n48Ic+yMZgg595xc/w1Cc9hYMHD3L2OftRNgNH\nfLuF7QYYWzLZirzs5T/By17+kwAMxlMefPAw9959F/fddxfRt0Rfc8f93+Tf/6fX8nv/+SwuWTnO\nzzzzPIodR5k/GRlUnqVJZBwMmzsSF0TJg2NDXW3wrw5fzoO3P4B6zOdo9CUc6ToWzr6WHZc9hUP3\nfYA95+2BJtIrDR7PtMu4dqUyaUnKiNh2QYaE97n0Cy7DVpE5tk4isFpkTYpWgMD5SNtCcJGYm0+Z\nPiShaRJbm46m9ehBQuqZmrGb4mep3L2ioDAShcJ3ETGKBARtF2k7mHaK1kliNChlqeoSIxTReyaF\np2klzRSkSrNoAo+PFhk1ISbaNieKVTJ7PkgzSTci80NDJAmBNAlVCEwhKApB22mGW4lxlxj5wEAF\nTtewXEt6OiFLj5jThEIwTYLOaKSKVDITohz51J3S/xoc285vu9GPATtn7+8FHvq2zzs0e+x/uijE\nFBi7KUJohJSzkNRAl/JJIacU5lqdNCsZIGcpyu1TQiLJPH2QIoH468/ZPtLFmP30VuXkpsooChWz\nJj/NxkpFpJmmjBxXgoVKsKOG5blEoQVSCxoR2CIxFp5pl4Nd5CwoRkuFtQVzxiJihzaAiLjoQEiC\nU9RLlkmKHD64hdQl0yawd88OjOnx0KHjLC71OHTwAPv2PZrbbn+QIAS94j4uvfBRnDx6iNWVFR64\n82toH1l/4BCXX/ckrnny03jlz/9b2hR57gueww1PfwpLi4tsDMfIaaJeKUjAcOsECk1UBi01F190\nJpdctB/Bs2bPhqcD7nvoLg4eirziX2xS//pt/NC1O1nfdYA9WGLfkmhYiX1OtwPmbI2ctly2eC+7\nj7+QD8qDXH7BHgKWe7cUF1zzI4yPfp54agtbr7DYL9kYDzAyzTrE28lcnhA6vOvyODjkTSJHOeUb\nxlqVd9hKZ0yeUfiQaBpP23kgsyJzCC8zQhNMmkgTQDUpuywl+E7j2kRdGIQqSFKgkkTMrLlthGYK\nncs8385nDYE1CUvmbti6pNCJSZPt3tJYphPHeDAgjBoKW1OXZnaqzVZ9rVVOCYsOIyWF0kQTt3ly\naC2oS0PyEecipyKM28RwKpgmmLSSE05QmojtoFYz16eQoDTG5teib2aah9DNGhaTR3Rj/5M0GlNK\nSQiR/iFf8+25D9KCFzndV4rcb/LfFrwqZix/ZhMH8bf6CVmnzuzPt3/ADD8uZYaexGyVFuR5sEyR\nympKlUVNIon8cZ1oJoFGCwolmLOCOZvoqcBCJZmrCxqTWBeeUynCWEDKuDUtMj/Q6EhlAqUp6fUM\ni0sZ2pJiJEXLeDxEih04N2FxqebokVMMjo9ZXd3DfQfu5eu3rrO4UHDBRYLPfuHLXPeUp+OaAWft\nq7nr1nv52he/xBMuOptLzjmHE5c2VHv38fpffiNHDxymN1/zrt//Q4bDEf/8R17E4twe5Pwupikx\n9RMsLUZWIDVJtkTXsHV6E6sKpqMpWkGsepy51OPR+/bzlWdcwet+7bNctgJXlX165/UIC46yaUkj\nT9n2ie2Ipp6jckMet/MveWf5y8wd+hZbu+Zpyppj530Pe/adgz54B3a1oGlGFEaidUXTdDN8+wyY\n4j2ta2k7h/OSJCVCqVmupMAWhspqbG0wpQCVG5a+y6g1nIAksMYgVc6tKKteTtVW5Bg5lTcZrSGE\nKVEqfLK0QVCkDEqJItF0gWmncQ4iOd8jpUQKHoImSk+KCmsNiNz4lDpHHjoXcG1LbEDrHpWqUVqj\nVUVRGBAJ57epTRnyEqUg5vUPbcAahZ2dNlPI/Yo2ak41kpEAqR3WJRYLWCglttQoaaiMhhhxzuG7\nRIjZk/NIr3/MonB8uywQQuwGTswePwzs+7bPO2P22N+4vj33wfREElGhiESf05udzN1ZCBmAIsS3\nxZfNJhFCPDx5kLN6PqeM/7Uzj5Sz/PIISGXjVEoU0iDJtGYlC5RINKbFakNhIkYGCqUoBVQq0heC\nnoz0FZRWkUSH8AWxEFmOax3SeGQKaBFYnZ9jcWEBJRPzC4a6kBA7NifrdCGxeNoxHQc2tyL7zl7l\nzrvvQx5wHD9xD/t2P5qLLrmAW275Kjdcfz2f/MQX+cmffD73HDjCr/32O3jhDzyfn/rRl3Drrbfw\nYHcP733ff2Gy0aAKxcbh06yfOsZ555zJzZ/YyU03PYNuepokJPP1AtE3tL6hZxUiKdrJkKX5BbzP\nv1MjJdLWeJk4fORuLn7cY1lc28+v336Yd16SmNgp8ydrRtogZcDNO6yoSdMJ64XhhSf/hE8uP5d7\n6v+Ds6YTYulJtkfz6B8kHP0lKBzSO6KPtF6iDBgZiN7hUsjuQ5cj+byQJJV1C8oKTGXRdUFVQ1UZ\ntMmjYq00IuVdcRQCXuWRtNaa0haoMmPk0TE3+2QeWUad8fzEiEsghWYyUUjlCamh6Tq6lmzTxxC6\nQBKJVkVE8gSRIyGtjmhh6FcGJbscMqsWGA07BhsNbeuRoqa0C0ihiRGqKkfeTV1DSC2KhJU5YjzN\n8hyk9pSFpjCRZPPJJfiYDXcYhNB0sqUl0iEpyOa8GALMCNTZU6ogPfKEqH+MdfqDwI/O3v9R4APf\n9viPiHw9Adj6u/oJkDd3l3weLck8XIhxBtOMkGbThW8fP0q5DTvJC0NKuVabCcYeXjSS0NmW6yLe\nhVm9mZmMUuRoN6NEBlEUmvnCUZcRa3PgR/CRUpf0C0NVgDGR0jiqIlIZR1F06DpQLhiqBcHicuSc\ns0vOv2CF1R2GxQXJXC8xN5+lvK7TjCYDNjaGs0aZQMY5otigcSfxzTIXPepiTh4xjE7Dp2/+CzY3\nH6SyPd7+W+9mvr/AcH3AnXffy8H147z/Qx+iS4755Tl0Siz2+4TW88mPfYJbv3YLMiRCswkxk40l\nBX09RzMd4tsRzrdMp2OG4xHOezAGFyPGWOpezfe98IXs3bWDL48Uf/Fgn0Vv6ZgQbEMtO5x3nMZj\ndcTVid5Y8xtf+inmxQE27TLdScf61pjm0uezuHoGbJ2iX9X4KJApB+AEEei8o2kck6nPJ7Um4TqP\ndz6PH0WmZVsTsDrSrxXL85aFecPivGFpsWRpoaRXK0yRkNojbURXiaqOzM0rej2J1gGlRE6FtgZr\nLNoUCFPQRcnWOLI1kozGFc2kZjwSbG46tk4nhoPEZAjTcWI6cUzGHZNJR9tlZoRAUpUFC/MVi3MF\nS3Mlc72ClALjyZhpM81hxC6TqKyxuT+iDFLpXAKniJBphgS02Eozv1gzt1zRX6zoLxYUcxbd05g5\nQ9kr0bbKC4T3TKctk0mbexjZeInWOe3qkV6PaFEQQvwh8FfAhUKIQ0KIlwCvA54mhLgHuH72McBH\ngAPAvcDbgZ/4+39AXhjCbNoYYRbaOvMU/A3q5MP1wcOqxof/MbNFIjGzR0iytnz7K2LO9QtBzCzN\nEZlyerQiUFrJXCkorEAZTRcVG6PE1ijReTmbggSEyouG1VCVkbqvUbXElJHlFdi3V7O2q2R5QbK0\npOn1JUUNykjaTrK5CfcfPEpdrzGZTFjfuI8zzzyPq668lnrec9sdX6cNdwIThGhYXerxX979PtZW\nK0JsuP2uezmytclbfu/3OHn6FDJGCiWxpc3W4yK79e64826++c3bKU0fKQpS1BAD48EGw411hIZe\nv8IFR+MauhhoXERqQwyZPRmj4OU/8VKcLHnjp/aw8XVDfZZG+z6uLunNLyDnp8hCMNeu0FYlu8qT\nvOLrv8j9g4bRWoUYtozZycrlP4w7PcR5CSHnXnTOMZ46hqOOrS3HYCswGUqascY1gq4F181EZjFj\n/Ust6JeG+dqyVFtW5grWlkrWVkvWVkrm+gJtA6qMFHOKhXlYmIN+DVUJhQkUKqJFnHkvLDEpOi8Z\nTSVbA8XmpmU4KBkMFFubgdEgMh4mppNE20SaxtNMPaORZzpxeeLhWxARayWlicz3NcvLPcpKMZmO\nWD99ktFkjHc5BVpiKXR+01LNXr9ZLGV0HpEWpWRhtcfijpqlXSXLu0qWd2gWlgSLC4L5eU1Z5LJb\nqhyQ5J2k6wQBmRPKSkVZ/hOXDymlf/Y/+aOn/n98bgJe9oj/BrNL6ryURS+y2YjZxGFmDknMKEmJ\n/2ExAB7WKmyvGSJXGvk0ISVaJQqTS4/gEsFFfOeJ3iBE5uajJF1hkToijaZLiRMTMOsebQWrFjob\nKJMgqHy8FVKiTUEbG9BQ1wpbJqRqKcsKJTVIQSRkwGgSDIdztH6dlZVVBEOiF2wNNlhcmuPSxzyR\nU+v3I9qzmI4OsLqzppkIumnk/oN3MxpHLnvCuey96FFEJVmcX6JGQ9PhVaIqC2ToOL01YOeZ+/jC\nLbdx3v7vp3URXRtaP8TUgsXeDprWQ0ooW9IveoQoKMperj+Tpy4rXJjwxGuvQ+iGB+bX+eUPdrzh\nYkuth7imz3DFUafENChQY0iG0C5ySflNrjj5ce7b8VxW05TNyYT1C19IvPmtbA4mqBRpokQ0Hu8U\nzTQwmQSaSaJtBN6TX51JUhQSVSSMspTW0u/V9OqSXmVQMs+juqAoLRhdI2TglMjP2UJPsdjXVHWJ\nVDnkZTrNEBVvEwg9Q8FngE/XJlzI4SkparwrcF3M49Pk0T4Dd2IA57IwLXQCVwXKQmMrjTF65k1Q\nzM0ZIoKtrYbheAtrNXVdEoJESoMQhuDz0T4H5+bg2uQTgoQ2iv6cxRaS1oXMZ/AtITiU2I7QcxkY\nGytkVDgX8W2HQFBYg7Kz/tojvL4jFI0CgZkFr7oQyEHDArkta05pNl7Md7zQs0j02eIhZitAklnA\nwrYeQQiiyBRfYzIBh5i/ZwoS1waSjwidSxAtBUoIeiaPe4Y6MkhwdJqoG4gIvBL0RAQJE5log0R5\njzSeaqZ9SCLRuAl9bSjLHkEEpm3Ah4at8YD1TUXdgewdZ+++XXR+RJKee+59kPPOO4O1pavZcf77\nuOu9I7720YoLLuwzPz/g3gOHsUXBNddeg7SWyx5/JV/+7OeZho6p8Exiy8apU8z1asbDEbfcciuL\nyyucHHVonajMZBaqWuKajq7pMr8AmR2K1qK0RiZF6gLONxRVxcnNk/zSS57LJ756kHd/7au89B7B\n+c9cZnpkTJ08U9+jDD1EPIGTPU7ONazYlsfI+/mrQaQu56n8Fof1Ev1zb0Ld8U5CPUcIU/w00LZ5\n122midDl8jd68DkkHDUTHhklMw+hlBiTcilhs05FuwzrEbLAhZDTyoWisoqFomRurkddFyAFk8Yz\nHI6Ztg7vBEpEtJjtrmWuv4XI8mEhi9mItCX4lP+uymONwFiJ1plQTSxmG1ZubEtbILRCJUHdKzIu\nLnVsjE5TFCUL9QIIjZZVxv/7bgbokWg5A9SkiJIiL4pKYco8MhUhZcGd8LNciqzViCE7sIQQ+NQh\nyKdgGbdH+Y/s+g5ZFGZag8QMuy7QyCxvTnG7vzj7pW9/1XZpwd/wP2yfFuTDo66YexUzsRMz13UI\n4mGMVzR5BJnhsIm+kcxbz0BFJhqCFmwpWCoUVRkRNguYGhGYBtBdy1wp6JVZjCKUJBEIqaVx0AXH\n5mCTza1NNrc8UmusnqeJ96D1VaTYcfpUYu/eFR586DYO3jXi9c95Apde/hCf/K/w5x84zUMPDTjj\nzGVe8IP/nCsvfgyv+Nmfw5iCpaVVTFnRRU89Tvgk8NOOsih54N77OfOMs7jtwJ3ccN21DDaO45JG\n64rRdILVlqKsCMGjjUVrC0mSQg5dCV0OrznnrHO5+8ExDxy4n653Lq//o7v41Uss9WKLi4tUtmVQ\nbNFjnrlhS7Tn05vcxXfzh3zMPofD9X72H6+Z2B69c78bc+vbmLCGkSN8Enk8J6G2EmE1Ikp8gK3O\nEVycWdNngSsykegQ0iCNRRcapWJuWJoCoQKdzyh9HwWlycnfVuUAWFto6tLQqzXD8YjJJDeyrVZM\nx9D4hKjy89jKROcyVSu1nhA8braDd23EGCjKDmLKgS4iO3iNj/hgKCuDMoJSSkLQtM4wmjpODTYg\nKXqhpCwVSpksq58J74T86yOvQmBUtv5nPL0ixRIVs8mKlLIC1GtcozL+LiV8DCAculBZO+G3AxL/\n/us7YlHIdyq5azvLF8skXI8W+R+aUoZyJJF1CJa84zfbOvas6MyNO5FNMiiyl90L2iBmKcGCyShR\nykRdGRrXYZpIvyjJ1oqIVI6ilBRW0OuBnQ+UOyRyTqDmInbOEJLFi5Zx6+kpMUuqyuIlSR5/Dt2I\n0IzomnxcHYwDRi3RNgOinLD//CU+/8eOfWdV+PGIkye+hPSrLFWL/OQLvsDKqmFlZRcXXr7GC//P\nl7NQznHivttYP3WQ9WNHWFjZQ29plWOHDlIQMVVJtVgzHA6xhebU5ia/+853sXbuOVxzzRPooqAu\nLcloFpfWCG0LKSPlIgrnIUSXZ96xwxQa7zynN0d84M+/wPxKhyx28f4H1nj+R49y079aZXTqFOV6\njakVg7JlKhXV5Cgj2eP6h77BPcWr+dUzfp3xSkPbzNPbfR5dtRMjG4pykWl7gspbahUxvXyUi84h\nUZSNYmsYaFpop4LxJDCeTOmXmrl5S5IWdHYYStMhtSPIiGkitjA5pblWqCoijc98AiUxZYHoYvZb\nMCUAadLRRo9s8oYEBh/BWIcJLe0k4Hw3m3obmtbRNInoFDIpphogNxHroBDRo0WLMWq22wt6tcUH\ncE3H1nAT5yp6saCqDIiCrumwtkAJyTTEmUwvIITKnEctEDoiZEfyeYqmpYGocG2WZ3sHMXq0TQij\nKKuMwIvhkSsGviMWBYFAzDqMKoJIkRQTQuQdPEqBJJcX0ieKqChkHu1MYsSrnB6UooWQiCHQRkcT\nPSk6IBI7aBJ4DcFGKgtNFymdpzOzHEExi/6yII2nrGG+EtRLhvlFnXMCEngELmXwCzFRFYperbEq\nj1SbScDYDBEV5J2g11coVXD8ZMPSYgliyN5zG/rLpzlxvEMZydqOHRy/f56l1QG79jfc+sWdmGLA\noW9s8ZXPf4zzzrqCwckRX/rczYSmQwfPxvpRxsNT7DxjL7q/yMmTJzHGMNoaIlPknN17GB8/zpGH\nDrNvz15GW+uEyZj5xQWcD0zbKdZoLBaRRGYGigxDnbRjYkjUVcWu884jDe5FdvcxWKz52Y8u0q5O\n+d7nao7UNXuamsngOH4poSdbDBYrUrvIP7vrT7i/fxNf2fUUJltbjFbPY8fex3F8/c+x7KJUlnox\nPdxsC87RTBzt1FEai7ciN4ddZDxqmYwiYSFDcUMIKDmTuscscQ/OzRY6SRBgjaaylkJuk7cFBkGU\nkrKIOC+wHRQaOgvWBlwXQAhsEnRFxPqILTzTsaPrBCmqHBUnoAMEAZkEMihSofKoG0eKgbJXYK2l\nUAY9b4g0bLkJ3rW0QgGJznWk5FE6xyJ67yEFRNqeauSjr9ICazXKlHjniD5Ays3gjFuZKXGtRmgD\nyueELRtRqnjE9+N3BM1ZiFkmQ5AoBBaBiQEVPSpFihSpEMwFQT8I5lvJwkSx0has+R674wJ7WOQM\ntcweucianGNOlRn1GmPu6sbMwsuSVRhMEqOpZ+oyFjwpUIXC2mxvXlhULK3C6m7B6p5Ef3FKb76j\nmgdTeoSdIkxgeRl276rYtVazOF9QGENK0HUtSkjKwjLXr1lenGNhrmDn6iJa5GCS1bWKi68+TTvJ\n3W8fA4PpcR7/RMU7P3gBT/+BU5w8PuSCsxb4xAfew59/6P0cOXyIG2+6gbPP3MfG6VOELrBjZRfT\nsacbT9FJYKVmx+oKCcFoPOIvPv5xbv/mHUx9wiNx3nNiY4NxcLRS4qQkiFx1ehKtd7QhKwSLssep\nE4c4dPhrRAzlhmJVdzxYef7yI5LumwV1bwunDqFTm8eHYQXVBg5XicXhkEvGd9L4FTSnuG9aIi69\nETMyRLXF2lzNyqJmbcWysihZmtfM9yxllRFnRiesVigkImrAZg1DiDgXY7tHMAAAIABJREFUspKx\ndbNFQuB9yr2olLmLzjlm2dVokTE6MjFjfLak0BBDh0gOowNGe4xxKN1gi46yzOg1W3aYMm9ghOyX\nkUGSfMI3iek4MBp4RsPAZBQZDjom45BDbVM+5isB/drS7xVYq0gp0XWe6aTN7NGUQy2k2D7VZjhP\nFuJlmrWxOYNSCkWMgs4F2jbStpGuc7lpKXwuqRQgAj54Ov/IdQrfMScFjc6Nw5AQKQEZqrotWzYi\nYaRCR6gwFEFjY0FfFwhpMMIgZUUgMBUNAkGDYxx9xsOHPN1IJJxUGenVgQsSFyFKibaGUkoKBJiE\nqBL0EtVyoD+fWJ639Hv5SRs0AV12CCfYudOytlxn2W7MIJC2dXkXk9lvYbVBzWVBlguKxCKnj1uu\nvn6LOz55PqqY8sChuzh2ytG219KFyKvecCaXPXbCJ3//UajTSxxKX+R5z7uOM3ZfwFn79xGFYdhG\nusYjkIxPbzEYD9mxc43xZETZK2jahnEz5o677uTK7/5uopDML60yan2mTYcpUStCmkWrS0c7zV31\nfm+e6OGn/sXLWPIVp+udsLTOvNCE8YC9l3YU4xZ1qGQy3yGXEzYIRnaLXmeQPpFsYn50HyM15sJ6\nD3d1jvWzf5D54tW4asIyDbJYoLIKkSKtCgQnmHYRbQPChSzxm9lYvM+chK6DZuKIYUJRa6QGEQ1g\nCbGhbTybgzGtdyghmA8JISVITxcSbWhxIdJ0iWmTG8Gdz9Z5iAjpcTKhjaMsIr5O9J1CBEE7Ad9k\ngVQ+N1qiT7TEWX8i17JaKXyr6GQG0iopsErQry0iRToXQWiEysFGwZMp1MripCfFrLRNs0BZSc7H\nwOfTTNMGgs/cheDzz8zhM/nEoEwGyLYu4Rv/iO/H74hFgQQqSUJUJB8zes3n3SvMnA9x5pCUUmCi\nohKGKlaI1mBFHqlZs8wkdkzSBBUNXeeYiGmuA10EmSWuKSRcyPbozoOLEh8VSVmsVTldukzMSYNd\niJSLHf2eYa5XYpTIAaIk4rwgtIlCR1RUOfNQR5KbklKFFD7nHKiUtQ9KY9tI0XWMx4ajRyfsOaPh\njLOG3HJrQ3/PIsiWRp5gq7EcvP8I17+45ILLj/LO1x3jrm+cyWc+epBj3/wj7rzvbi67+ipO0nBi\nvJWzLYd9zjlnDw8cuI92OkWEbMLZe9FFXPn4x3Lq6EOsLq+xtZVty7VSlFFz9L6DLK+tUFQ1Ugh2\n79zFdNrSTYf8yqtfy4F7jrD/jPP52qm76LUQeo7+Us2bvpFlyT/xbEf0hulijWpPU9ga7Tv6XWIq\nJWcf/zzF6DhH+vtZmDQcK3Yyf86VzJ/+PHXPE2wFKaCFJEaJMA5ZGAgSNw0EmYgyy4LbNuJcRdcl\nJpNA9LkxLaxESk3nHE2Xk58mTWDYDLKCdNKw4lp6tUUriY+epvMMR47ByDNtAm0AK4o8GpQCJROp\nUKSkcT4RXAc+oISkSdA1CUnO+BDJzMaCGtdlxFpVFXSdzFMAvf2msdrijKN1jpQ8cpZ5Mpk0YLML\nNLp8MorRZ1yAyEj5RB4juw58l9OlY5TE2eg9EZhZIBAmIY3EyoL0DygKvjMWBZipljJJJ2vMs1jI\npZTHMwTEzGvvu4BCU2PR0dCLNTvMKr3ePk65EVt+gPCSURpzVJ/OgIntzu7Met35ROeg85IQJAmN\nUtnqWvYrFssSXQnsvMP0JtS2QklBaHMknUmKShXEuss5EEGAE9mVN+1oO5ifsxSFoSoMpVW0rqQs\nHbLtaDYCvptw6DCc8agpt91h0cUmwRf01k5zZD2wvtlw8huJXbuP8ROvXWH9wTk++eG7OHj3KQZV\n4Atf+QqLcwU9OWFpoce9osfuXWs8dPddrNUVbjjhyquu4RsHDxKmE/atLuO6SH9hkY0TRzh84jgb\nx4/hfItvxyyvrbFr79m8+c1v5eMf/Ri711b4+J9+mKgN4wXDmlslHR2yp1fzrCec5u4Haz58sOU5\n9ynOfozklJwg+gIaGJSCvheIWOZTHAWHJqd5oqwY2S02z3wui4c/ilo+g6QUzWSE35406YQqNN04\n0IX80sh8xzBTsuaaPric4eG8ntliAl0X6LqEkBZlCqbTCadHLa0PjNsphc3J4hkTr2aahUjrsmlu\nqVKYUmOtRmtIQiKkgRRIcfDfqXvTWFuz9L7rt8Z32MPZZ7pT3bo19+xqD90esNvzJBIHWwEigWdE\nsOEDH1BAJkBMIhnC8CWKQEgWiTIokJAGMqDgbhKwg+0ebHenu92u7q7uqq5bt+69Z9pn7/1Oa+TD\n2mVZyOACdaL2++XqHt1z9rlnn3e9az3P//n9kDnT2IpeSXrpyalQo4Sw++9L4J3C2hrvBNfrAVNF\n5nNLLRUyZ4w2VLVg8plunAgxoqkYB0/2I0ppwhTJvzvKI1CU+Y/kihQ5BLH3oJa5IK3KjiJmQCQi\nsbTqRXFgWGHe8q341bEovDnCEAvDYMyCKUeIoqC2FXQqMROSWZTolElIaqFY6Iq5nHOqb3BibgHX\nZCQpD5haob3A5UgyAqly2SmgiiI+Q0iGlCwkjRGaqvK0C8nsUKOsR1lNUxVUmg+ZQVGchzEybyuU\naNBIMj1TLufL3cbTjSOz+RFCQmMV1mQCAR97xrHhquu4PAuInLGHX+bo7nOc3c9UCUKX+MLL9xn7\nFfras3u4QaoeYb7Me3/4mtmL8Mpv1Zy/JImPPP6sIl42fFN8DGeXfF1KvHx2jrMa31j+oz/3c7zj\n+ef41Q/9MtJUXF5fc7xYcH7+mNPjY5YHBzAJ4i7wb/xrP8sH/+bf4onTm3xsvebo1gmPLx5y/6XP\nMj9a0dWK5Cp2ZxVfP+/4Ey9WtHJDyi36PDA7qRjkiFaKSQZaBLemM16In+WXmm/FqJ4becmvVV/L\nTZXxSZO6HpIj+b6EiSbF+toxbsq0olQRZaCdSeq2QiuNVotSPJOaGBVxKh6HhEYmi5aOeTtDKcMU\nAs5HLq49xhRSt5sCY5L0u4QbZGGmCIFcTLRpb6AyGqMVWmqsTGgig3JMg0YIga4MsVdlN5ALco0M\nKSq810VyoyPGxnJE1ro8wVVC60IZHyfFNEZ0k1ksD/BTKtAXXWY5cshkU3YYiIJvS75kI5QqhcqU\nCr4uEykcuNJ+V1mhhSEBWv1hyylk0LGcq4iSEFRZKVEoWdoykcxIAuGxWrLLjm2YsMqymjXMVyuW\nbcvKRYKecNRUriJTJJ9FN1ZKTtJmUBYfHc4FnJPEPSSlqi3LZcVsUUZskSMITxKqBJxUxazVKJOR\npirnRlcmOicf6IfA+VVks5HMlhFyaa9VRrPuPN2o2GwFU18xDZKhi9Ryy923X3L1xglVE3n06oIX\n8xVDZ4n5MVoKBA3BHdOtn0Zd77jZeGYvdKzvdPTdDJkaUrwB6QrjDE/HF6kPbvMt/9y38clPfJb/\n6r/8i3zh058i1y3rfkdlKm7dvMX3fe/30LQNv/qRXyOEwMuf/zIvvue9XJ1fMj9YMTlPVc2p7SE6\nOQ4PNZ89e8xLH58zP5jzgXtvUD9r+cZssEIwrkdEaxiSp5kSvmlY+XO+67UP87H3fi8fyQPf2Hue\nPrzNun0XVTci+4HGVohs6cbI+fXA+eXE9noPtKk0xoK1ogwzRQoiHkEdEzqWQl7pCAgyorA1lcBq\nSUIVbHyMBJcJMTFMkWGM9B24Ie7DQGD3fX4pBLYGo8s0pcrAXJfWoCq8Ra0FSWuGXhDDngglNVJY\nxt6V1nktMFrhJ+h2vqD6LBT/scAYwzRFgvO08wV2XiMipBDp2TFOI4o3EYOgtCLqSM2e+Sgy3peJ\nyBjLnNDenEPKCecjUpW8yVu9vioWhZxKUVHlIg5pMChdg1REAl0eGPE4mUkmU4nExk0scs3RomJ2\numJxeoQ1NY312MGAlySpyCKTRS4/KCwxeiQlUFSJiKk0dW3220UFMqJ12VUkERAykWRkjAmRDbaa\nYW1F40udYxx7gncMU6QbRq42nrMzR7cR1PMN216w2RqkgC4ktl3mepOJUbNarFi1FmXXPPWNZ4zr\nG/z6/2ro+x2L+RFD32LUDYLfcrXestvu2I2PcI1gnGAMnuQ9bTojTGvORcO83rBYHjA8CHz8V36L\nz3zk0zw82zLXkaeevM3rV1uOjm+ybBuQil/8y3+Z5fKQ2bKl73pu37gFOaOt5brbIStZbkC95oAj\nhvXI8XyJj0uMueLqXNJeZuZdzzWBvMzIZKijwMoKqIlq5Ntf/yAffPaneaRfoN++yu27T9Gdfh/D\nG3+bgymxGzPDlNkMkcsuse3BezBSkPO+NmNLUMn5QDeOe8CrpsHuxb4VmYxWmZjL+5iRaGNABLyX\nxWAeMyE6vMwo6ZGiwHxCEAxdCUiJ7IhOQSuQldiLbk3ZOZi9QLgS+FEjtGAcMsGLQu4UZTQbMikk\n3ASQSntcZARm/4DRVFYwSsE4DJC2HB/OmC/nhBAx1uz9Fx3aSKwttYKUM0qB2WPfpWwJKTD0jm0X\nmFwmRglopASpQoHUvMXrq2JRSLkALNS+aFMrQy3KFi1mj4qSGDa45IkKRg1DDMRa0d5asbx1jF21\ngEJMEJxnyAO9GMgqlhRcVkjVktOAVJ7FKnD3Ts0LzxxxczWnNQJUJuSEcw4TMuiSUEsZxslDgkZH\njIScBVJIGtsisyWlgfV2oB8828Gz2SYuLzUxasZhIiWPF4quKxOApmo4PLTMqpZZe8itux3HP6X5\n+P+ReXD/ihuHL+LjNWHQRDFDHFiyeEQImpmf4wx0M88kJwY7kLrESW/QUdGfRz7+0S9imieZZODm\nzVssbGa3ueD09JRmeUQce0KEe3ee4uTGKbtuAz6ymM+5uLpgcg7bGDbbDmsMOgcer89RpqLKGeEG\njnzHH3//ivr4DH/nCFkFkutIMdE6ibea1I8MuuFufJV3rf8R4uQ5rpcrKiGYZk9wcGVxSdINA9ud\nZztFBp/wocTZ61oxa2GxKHMExQTeoPaEbUShHIFCyAiikLSEsmgj9pIYgdjzBZIAF1P5N9khUnGB\nqFEwTYJxCKU1GxQxls6XEglTKZTRJdEqyk7CGQjWFrWdlkyDZ5pyyU/sBcnOU1yXQUE2KLOP3O+V\ndNaWMfBxmFivL5k3Sw6XR8WhaTQpOi6u+wKOMQKlA0IlZpXBKjAGlNGEJNGq+CwSEhUVQuj9z0iV\nMYG3eH1VLAoZCCGhcqbKFVa1CGH35l6YJwMus00dQmdqYN7MOZwfc/zEKe3hkmwkMmY0mSx6endJ\n77elSKQ82XtC7hDGsTjJvO15ydueXfHcU6cczZaQoNvtCH7HervDi4iuIAhPFIEpptIrr0DW+y6I\nUVSmpa0TdWv3e8yKGDvS1NNtJH4EVRW9mZuKgai2isWB5WCROFxkDlcVJtzmHd/s+VN//j7/8b95\nh4vzNU893fLoy4lUTVS1wblbhCowqQ1alvpD8oYkJabJ9NExswe8/orDNKc0bUsM5+zGnh0RLQW3\nTY0OkbOzR1xtBharQ3a7HcM0gmAPCw0IU8bR5/MZxhj85FBmR3VoObvYce/JG2zTCZ84O+O77hj0\ndkNaGWgE8toTRA3SkVDoLDCrOUcpsh63bISjHgLtjaeoNrCtZEmtikzOxeIkI9RtZnWgWS01y6Xm\nYFVjjaGyurghKKlWkcqZ/U1QizZlWlZKhdQaIcu8QHKGKDIhByojaK2ibyRdn9luE1fJ48ZMHD0h\npX3tKRRocBI0QiOVorYCLQSjzHhlkG/i9lAkP+FCJApFDJGcSqcKCc5lVB+xpgBZirZeUNWGtjVM\n/cTFxTmz5oDlYkGKGWNqlLLFaRITKM+sVhwsLFaUydGYJ1IGY8vXiqkUMWNwgCzzLP+MICtfsUtk\nEEFgsmRpKlq5QESLMInKGpxoUF6xDoakAjrDcXXMyeqUxdEBpjGknBA5o2UkpYlx2jK6DckohIlQ\nBaoqsjzJPP/uive+85Cn7p5yumyYVTWCit3Wsl5nNv2a7nxLlhGXAhiQRrJoFKvGUFU1VkuM1Rhd\nk9J+MIdA8AI3JqYu8vh1R4gO3ZYMSreNmEpw80aDURajChqu0oGqus/68oAf/def5aP/2xWvfj7w\n9NsblBwQsiVFhxQTVaMIQ0UMI9KCaSUuerJwtDbh+wrDnNbUCCaECaWXnSVZKvp+Yn44w9YtdfTY\npmb0npgiLjim/Rj1arlgu+lwk6O2h1DXnJ7WLNqaJozcvrdF0XA7Zea2Yb3eUR9aplzaat5IGh3x\nZsZqvWXwcy78EjdbcjOeMVtf0T777bxy+SXa5RwhEtpKqgRKGrS22EVgdVCxbAUHi4rFvKaqDJUB\nH4scxvkiqE1xr+8jI5JG6FJT0FYXkE7MZCULhk0YqkoyOEVdCao6YUwik7h0grjHoI1TQOwK/5EI\noKhqiTEaVRWwixYWokTuvRV+SqQYmLxnCp6UEkoAPu/bhQpbebS1QESqgpdr6pppluh3PX23YzGf\nE2NB11tdkXNHjAGVM9YIrAaTEz4GSBKJ2KMGNd6WGsKbwCGF+cN3fJBJ0riKBstKNhyZA5Su8dKh\njMbrFq0lzQDCRnSlOVkcc3TzBoujY1q9wERNWgum2NEPHd2YmPJEVJm6lRwfGU5uap59vuJtb694\n4akTTpY3qESFluX8JZRlNwncWtH3Bp9CqfxW0LQS2dp9oSlSNwXeqZQmusQ0RVqVWFSZtKgYB8n6\nYc96fY0aJYOD0Qlmc8F8npkcpKxAKFL22HpOZVc8fn3Gz/9Fw/VVZnuhyWzwKTFOgpw1QnRIkYq5\n2WSCTehKIkRVbnwvOTpa0l0Hzq6uyTahZIUR4N1EaODhZsf52qGbCa0EwyAYJ4exFaNzVLZl7MtT\nzFgYp2uMWjKkTHdxn+bgmrs3JdWkeOcUWawmuucE9ThgtGTKApxjyom8SMS5gavEwv51hlsV78rf\nysHsiEurybuEbDzeZYZGIhDYOrNYVuhGoNSAVAZtW6Qu8BSELgNsOSBzYPJly5xxSGFIQaJyQhmJ\nCBEZZcm7FEs8VgisqqiloFYKJUak8CgtcINkmgTOCVxUCC9LGjIGpJjIGEAVybCRCJWJOZAE6CRQ\nlUS4RPQTKRVLecITk8J5Re490oKuoZIFt5Zi/N2io7UlT+B9REiNRGOEJYSRODpUXYzc4zQS32yt\n+mJfjzGRo0HlhDEOITUpmhLvln/IVPQCsE6gc5kpr2cVbb1EqQhG4lWkChmjAlWjaFvLwWLF8WrJ\nbNliVIUKmrwJjM7TDxNhKufAWRu5c0/w5POKJ+7OuXtnxZN3Dzi9NWdRzcm+TGlmBDoUIrRzkutN\nYnARVUN7ILAm4UbH6AbabMlC43NGRrGnPXmUzjSVpqsydb2HbdiKXRfZdZluTOw2iRhHNAkrR7QK\nVPUtTHdEElseXb3OYr5E6ZH+/IgwwjRE3C4Rxkwcc1GZa4VNmmQjviqWLTdWUPcs74zcEoaHv+Ho\nN4K2GUiyRsoF2mguLl5njIFZPKEfE8N0jVSGnCt0KJVuVUmElUzeMKbEvM4o3/LAXfHeeye87ynN\n5vqCt9kZixs9eSXJu4DQUAuBH2ACDrvI+iASZ1f84Cu/zf35ms+865qjaYkIBs8C5TKqd1xUkcOo\nyBGu+pFDCfOq3kta2adbE5pESAHvHaNLTFMoC6Io3SolE0ppTICki/6tuIQFWUKWJbSiraXVkJFI\nHFpqhqPIduPYxKKzC1NJ2dokUGMuDEYREVUR2ShZbFMxCXQFpkrIMZKHkm78XRhQLqKamCJ2UExN\neXortaeNywwUKpTWZfxZ7HcJnbSkaHE50Q8QcUjhsVZgtS4u45QKNm7PesgU0YxWhUim1FdwIOr/\nQQTznwM/RJkHeRn4qZzzeo+B/yzw0v7Tfz3n/DN/0GvILDjOC6qkqYOlETWn8yOMlqAzUWcWoabt\nM6rOtIuW+XzJvK6prabWGmUsQ3ZMY8RPZZy0UobqRubZZxc8/7aKk+Oak0PD0VyxqDWNlQgNiEw/\nTHjXMbiR3TCy2TlCkiwaSaUtVhfr1OQdm26NjztUBzMraaoZQkSsyVSVQitPbTVNkzk8rPbtJElM\nnn4YWV9GlBhI0TF6z+gS8/kW53csDw547f5jlE4o7wjBM/SRsS84uRA9yoiisqsEKekSxAqFY+jC\nxLZ/yI1bz/DsM8c8fBBo5zOGcUAbTdfvCEGxqGdkPJuriYTn6LghxeJSkDLQzi2jL7vmWb2gD5Y2\ne04rwSJauq4mpx1zuWZICURDtAJSREuJaYGidUCHxEpHvnzjgtfuvJOdeYF2/TLP1i/wStCM00il\nFakbGfZcQRUTA4J5Kws0JAZSzLix8Dp9jHgfcGNi1zmmAEIYtMkYlbC6MBi1gmhK8TEQkW+OOJNQ\nGqTUaFF+F3IUrBYJnRXCT2x2vqjhnEQGWeCviP2QnaSqTBlnlrJkKbTaq+JAiEhInpR04UNSNIbZ\nZ3rtqeuAVLKM2YtYwLQabK3RtuxElDbIWnE9rhGiZvCRTd8TfI/3I0pn5rO61LNEGRoT+1al0QL7\npmTH7ulEX6lFgd9fBPMh4OdyzkEI8eeBn6M4HwBezjl/7Vv+DgCRBafMqTEwVdSp4sgeUM9nZAle\nONpYYWQmyhFtLZWpkQhIAZ0SJiU2Y0Ikg5U1ta5pqor6yHHjdMHxcsm8klRGYrQnu4ksLEopYsr0\nfc/V1SXn6zM2/YasEvOZ4fiw4eio5mChaWcV2kLCMboRMQWSK0kyJWUZZlEKay3zVtG2m31LM1DP\nNLaVXKxLRXq9BjdFtuvI6wcPWSzOMGqOVg5rE1qsiPEMCHiXICmkzGiTmNm6AFYRZfEwGdsIZHa4\nrhiMh7jjHW+/w/bqC+R8jLGeEDcoY2jaW+Ru5PTugPcN5480MgeaxpBrg/M9u3EkRY9MiWF7RdAr\nlni06NjOWy7EI/7le4I7yYCdiDsPWWJE6e2nOJGtwitJlhopKm4eeH7ylZ/lf59+gVef/FZ2ec3q\nzoqz118j3Zlx+HhgqyVuSjQ6ss1g7UiMGmszSiac8gxSME6eXefphsz11uN8RuAw1hfic1WoxkZL\npLVYVToJUmSMlAU54iM5lm26kBorDJWckE2NmGuin9gNHp+gGxJJxD2PozAeUkq0VQPI/VNfFFiN\nkRhbitEppDJBqTSCiJsSHQ5baVDFWyJlmfURsoSl5P4GripLXdXo64zLiWHsub6+JsfMMDpiTGgb\nymsJgZKStja0TU3bVtTWlhaqEF9ZyMrvJ4LJOf/S7/nrrwP/4lt+xd/nEgna0TDLNd4YZqrlpF3R\nNEckkenDllYrDJFuvCJMueC9Qyb4yIgnxIxOmpmZsWiWLGYLTg4PMceB5dLQthSghQGfIv04MUyB\n0UfGaeL6auThww2Pzy4JKbA8rFkdNNw6mXFyNGcx09imIhLxYSBFj3cwJkeMA1Dipy5UhKTJObCY\nzzHGoSqFDxlbT+hKsd4m+i1crzPbq0BGMptn5rOBeV0Wreh7slBkAkpk2rqmqgoZ2piMMbn4D1JB\nm7uU6HxAmhmzleHs/mPMjYa7zy55+QsXNE2DjHMGP4KeECbTNifceBtk7VhfJA6PLeMUGbYDy8MV\nyjgm37G0mfToVV5tb3F67ybvtomvJ/NCq2gqGBZgpS24cgqXIC0NNpQ6Q1SS0RuetId8Z/w0nzQf\n5TP+h/Dbz3H83n+V8Xf+E/zgOPQwJEtyuUBNhOSCMuPgJkdTZYyKJCPpu/IknzwMXYHmVCojq4Cp\nE00daffWKWMTldEo0j7Q9OZwXCKEMhtqjS27AC9RUWCFprHgAgQXcBHUlOlEJMZAJu0VA6UjkXNZ\ntK3JxX5tFdpE/F6Uq5QkqQL9GceRzaYsCMgWY8s0LwQUghD8PkAlkTJjdEBFj1IOrQIxKuSe9+AG\nwdhFUgxII4gLkKLCaIMPGpsLZ0H8fyC3fiVqCj9NcUq+eT0jhPgtYAP8BznnX/n9Pun3eh9qNMIl\nZE7UxnDQLFi1S7SsyQK0jIQMOe9KuCQGhDVQJ1wOjNmjEjS6ZdEsmNdzlrM54WhBbjtsFdHVQDXP\n6Kpsi6921+wGx+V6S9+P9ENit4lMXlC3ltPTFSdHLbeOF9w4mlPXpaIdcmDylmkYyVEwBU+YPDkX\nBqMbI5MzhJBYLo6xNmD9hAsBbTJVY9DWca0S22tFd+2ZgmDsJJdi4qCVaCqU9ITkgERdKdIqk+fQ\nVoKpiszbcu40JqKHhBIZYxdc9w6VRqojw4PrN3j63rvYbDa8+uULYmio2oQUF6j5jIcXmideHLn9\ntOSN1wOPLx/TJM1caKwUDFmi54rcRCpX82xzxJ1bZ/zA26/5rsOOg1oSmoRXIImEHFASXIy0kybq\nzKaNJdv/KBF0wB01WJ6ndTDmOaff8kd56b/7C/Rf3nCdBCEGrGi4DpG88xwsBHoO68uOuRbI/et5\nlxkmSI7yZ8q0BqRNqDpg68jMSowuuw1rNDKnUqG3eu8EEfs6RenxK4rDchodwQkUJY+QUgHHDmPA\neYlzEYRB6oION5UGFBKFlAmlCj9RqQIjBvb2alGKhKMj5kgkIBRUjcUqSQwOTSbOSi1CiWLPms0M\nQoM2M2aNYn02ECNFZhwkOQb8BDJ4fJWZpoTRseQaVMHUGfvPqCUphPjTQAD++v5DbwD3cs4XQohv\nAP4nIcS7c86b//vn/l7vw1zafO2vEQRO58ccHMxRewuQSJJKHzB6Re83WFcxho5tFZgWAZcSJhsa\nNEElslbM5wcc6gPc7DFBKOI4MnQt9SwS08DVWebR5Zr1ZuJiMzK4UgASGmotmZuK1cxw43jF0emM\n1bKiqWoQFk9g9B2dFJAlqfd0Q4cLgZAUfkx458ixoakTVW2pPLigkNZgq4RSZW6/skVzP+2g7yJT\nrzjbCSrtqYymtKwMOUpqK2gaRQ4agqILaw7qE8QETSUILuL0SHd9OhllAAAgAElEQVQUcfcNIimG\nMLKdrrl5R3J2XrFZb/GTwAjB0VM3GQdBP11i6znGlJH1MWRWtaZ3r7FWlnc8syBtAk88qfjpF17j\nSXPGwgduWYkwgXUWKC/JjUOoDEFgssAJj/JFkJO8oKslzeg43MwI4h6hjrgR5s98A83Xfz/xl/4H\ndu0B8WLN/WFCzSIzDHq0yEGxHRzjUrOjIydFsIowBGyGOCYmCWMrqCzYSRL7RK7BGEFjAz3hdyHA\nkgmpFFKXKUOtChHZaoFUET8FnE+MUTClYijTsrxHAU8bNdkkgiqglyZBXQsk5YhjtKAyRQfgpyJj\niTHuOZgZMYLvAx1grCYUEQQ5F6ZoEoXJaK1F5UTbAsYzV4rlqi2hrEdjyT5MCa10YYZoTc4G76AX\nA1JUkBpEzCwO3vp9/f97URBC/CSlAPk9e4IzOeeJUnQm5/wbQoiXgbcBH/9/+1qRxLWZmFULxEKj\nFhq1tNTtAiUNMmbUYNkNO4xaM/pzwujotx4nI/WsRklN1czJMaNrzbJe0S+WbMQZ2+sdskpMuWLX\n7XjtlY6ra88wwnYscVptBW2r0fOAWihmdcVy3rBsZiyamqotkV2/V8SlEAghoKaKcdxyvRvIyZCD\nJQWFJLBcmX0VXBKix5pDxjph1ECmR0pBTpGNGIvhWEIcihMghYBSghgiTmSGSTC5YkrOGaRX5PoK\n5BPEtEVULbg1sxF6KaikZZYFyV1z5s9IQ8vJ8YyzSbGcaVpVs7q3ZX0RSNtI00qQB2SxIZ9WLKoG\nu3C8/7sPGD59xr1XJu6sJO/9loqsJYMTTEbju4lUgrulWyRyweaHXJ7oVYRa00jBPEV+8847+GT7\nNAz/iGU+5UqcYJ58GukUuu4581CLgNoecHG55sHOQwvyCZg9hDtVg1sGuuCohaDPmTZJVFvjuh7X\nRyoL3oKvoalL317JMmXop0BKIEXYT1aClqVo2NQWWRtEBh8yu8nRh71y0AdijoSQ6LpIQpOjQAVB\nymUC0ShNzoWSpJVEa1GKmfFNdDs0TcPQOXbDgE8JZVQJR0VQqhQYnXelnakUgkjbGDCKkAYintky\ncOBLdmYcKDRpp/EpkUPAubJjG8dISgMyK2z1T/n4IIT4QeDfBb4j59z/no+fApc55yiEeJZinv7i\nH/T1ksi4OTA3mAODXRiqlUFUlH5wKoquqm5o6hlKtHRxw9hv6GWPlQbdKJb1ESJ45JQxSVKbmsFW\nhCS4vBp5fD2y3uw4fyy4vrL0U8D7jFTQziW1NpgsabSlshqtEkaUYw05IVURgkZjS9tIZlwskpXN\n1pU3FoUSmtrK0joUibYSJEoRqTbljJkyKFXy8DF5pC5V4yln8ggCDckXzXqSeJ8Zx8humOAgceyf\ngOst4eAhOpyQNy9xvh3or2A8m/NgK5kLg1573vtD7+AHvvub+Tsf+ifc+s1XGPOc+8PneO9tyeUX\nKq4fn+DUObMDqLQmzRzveu4u3p7T7tZ84Mjy7XcystqxCxWdjwUvrgJ2Vc7SQhU4buFiQo7F2FcQ\n9wqhygi8fvw7bJ+7Tz++nfctJi76gRff917+/njIlK9RuiVe9Fyfrbn7vq/hhXd9Ky88ecjV9Dof\n/cwnef2Tn2a2zcxXLS5Npf3ZWqaNo2kMPgTylAkGXJ/xdUKaXDIFwpCiLIXCIg0ABCkFROexFqrW\no5QmpczgpvJ+iAIySblYqcO4l7akhM4RpXXZaanCdlAS0LEwRWUixoJDs5XFWk23m9huBrzLbDaO\nmAUpZGylsMYyjhPe+zK3IBQz2yC0ZYwdWXqMm2hnipgLEi6qUrOQQeFFLMNhUeylM9ALsM1XENy6\nF8F8J3AihLgP/BlKt6ECPrR3MLzZevx24M8KIQoYEX4m53z5B72GlIJUZZgJ5qcts0NLagNi4UEa\nCAqSxM4r5qs5y+kGQw50akeXOrZhzVy0OLNBLgKWhB4iTSPZWc2YBf0u0AXP9Taz3hjOzwzDEEAK\n2hkYW7b9foA4CeKUcINnbCbGKoMHIzQpZ3IaCdExDAP9NBZ6cFD4MaNlwsgEKRLbUgTUtiTplBQY\nJYhkQnDkHEku451Fksg+k8Z9HDomhCrWIe8D05hxkyZNGjFMbKtEy4LFuOb1y09g23fzPe/5SS7n\nI7vfqRgv/yq//dmX+Mj/fMiP/vw5x29/mV8d7nNDnPHJccbUB8Q3PIl56jVWX9xx+1JyevoKi3fe\nxBrPvemcqulo3I6vfW7FSXOBsopr6TAR2pXCrRIVieQh+gxZFsS5kgypvAdmiGQFkxAkbXn+wTW3\nHvwSn7/5M3zx/A10dQv59u+geteT8PFLzq89t06+iZ/8+R/l+3/ie5mLgS/dV2xu3Obu5nNcf+oz\n/P0//efYvP6Y+qbF+onHjadRihSAVBbckMuIcfCJLBJSJbRWKC33MtuEqErXIMmyUPRjoMkRKUu9\nxqdMIBYbehQIFFJKQoz4CUbAyEBVWYwJJFlkFTkX+rJUJbYdowRdU9VtiUlvaqQyDN4TpoA0CqtL\nIlIL9olKT4gRoTImV1jVIIwHpai9JrhiUcsx4PeAFZUz1tqiXgwZ7yM5C6Ypsd28NQ09gMj5rfcv\n/2ldjTX5A+95J8/fvsdzt+9y996THJyeMNdH1GaBjjPSLjNc7hiut1xMZzzkNR7pV7lKZ2hgZuc8\ne/QMUQZ8F5h8zyP7Klf2PkFuuNh0bIZIPyTOH0keve4IrjzJtILaRA4PDPdODMtGYptEeyR5+m1z\nnnluyeFSUFsF0pFlph8Ul1eBB2eex4+u2VxHpKgLoFNqpJQcLhtmM8VsYdBWoLRAUeN8Ztf1bPvE\nZuPYbhzrdc/VpWN9FVhfjPRbX5J52pJipNKR1UpxcjpnttK87Thx6S44ff+f5Id/5L/hU49+k3sX\n/4DZ63d4fPAK1w803zX/a8jTx3z64U1+8Ik5D375c6yaiYcBnpEAZYs6zDQfDYZ/Mq447q95dxq4\nHeHwJOJzxUiHmGXEUhFbSe0itc1cSRBOIh1ILwqq32YQER0VEUVEkH1CREGTQI+Wy2PJf3j7v+DT\nz/0Rmocj737qFpcf/EXeef0l+n/hF/jY/d/h0D2k7b9MtA1+dsrCDZyEis892nGxEtx5/ID/8d/+\n9zm+p2gmz1VVXs1aWWYOKJOMOYIio3Tp2UtD0d4ryg1XSawt25sQMn4SOA/DEAs3UZRBJDvbo9YR\nTIPDTyWU1LaZdq45WFUsZjVaW1IAlwLDkLi6cpw92iKT5fT4JscnS3LWPHhwzitfep0kEqYqu9Sm\nrTg+WnDn1i2OD445OjykXbQYOTCFM5Lt6MYNPk4M436vI0BlTQgCFxTeRfw+qxP3yrWmqVgu5/yV\nP/Nrv5Fzft8fdD9+VSQapRAYYbBKo4QkhEQ/jMjZgEqalCI5S6JKOCURQlP5ikU6xMvITp6xNedc\n2xVWarIZmfwanQNVFZDMaJNkCluij9w89bSNKpVnJG4IuCEjZWTYQQgQd5G2l3ShZztdcXra0La5\nxEdRxDCj6wRTl8nJomThGpIV0SecjEzOYrREmYDJApsqlMnUIqIai5ShiEeyAm+JITH4Ceskzmlc\nSHsQakJoCdmSRoNSli90l7x480/ws9/zU/zDL36Kv/ZQE1/9Tp63r1I/rvgOPs+9p1/C6Sf4wQ+s\nmX7rEUe3A/aW4pkBhqPMbuWZm8Tstcj7v+R4XjrEsUCFkcMnDNMskbsdC2d52HlmPlP7hEuRrEsC\nFRVLOCcWTJDShXkZbESlGV46FjvPS9UKHRx3dcdH7nwj3eoDnE0zDtvP8Dgc8/1/7EUefPmSs9/4\nC7x7/GVesz/B/8mO0+FT1A/+CB8Nb/A1dy1P3T1gcVbx/Nd/G5//9m/jM7/2D7lzQxF9eWLnWLbd\nGVVsSrqwDYWJCAuq0sgqofeWcGUDto1IIQhekYTHCMvkDMiwN1UXVZmUmuALAUxKgXeRfoQsMkI6\npMzMqoAQuojQY0AridWG3dZxcXFJUxvmiyV1JWlaXXarXpFzIrnEsHHkU0lGcn6xYT5FpJ7oRkeQ\nAz4XMlPhR5T/s60qZo0h5cw4TgwmExrJOCS6bU+3t4m/1eurYlEAgXQJMWWCS4y7EaEVRmqEj4jJ\nkgdFGEUZfx0FwUmCEmQtiUrge0+/uCC1FVpGlB2pdcbOVwx+QhiHrWq0aEq4hh6lKtwIFxdbrteJ\nGCJVigXkmmHrEhevZB6vE6tTz+rAsFwkrA0FopkKLFShqfctHxEFMWdyLCPYk0qlyg0QQZORWmCk\nYi5sKXYlTw77rMHkCS4gRsk2esbBY43FaI2M0Ioa+UaDfGbBB37qF/hE+wof+9yHOXzpk7zx6gU/\n+R7Do5NHzB6Ukdmr84fUjWDWVvCkIq4gdonOe2aPG6bO44ykfSZyOnQMuqaVGjMXBKMYRCYPmXqw\n5FTkOapWZQKRRJZ7P0HK5dytCimLDCZ1ZK24vNUgNwOfHjKv+WM+d/Eid9OH+ZXLf4nN4U0epgM+\n9iV4/RNrUvsCn89vx3zpDVTqGJ5o0OGK56Pm4gE8nCWepmd6PPJNP/yv8Ou/+iGmXtK2GoKEAj9C\nqhIKEiSEVChdoChKZaQSGAO1VmibqSpQShL205WjKpHkkEKJDVN2lGlvfS6O01I8DC7jhGc0knEq\nNSQlIwhd8gxJ7o8cme224+LyCqktQkhqawk+E0IqZObJMypF3w20zYhAMU0RIT0X6ytGv8G0iXpW\nHJhSyL2MFmqjsSoXxmgVGKeElJ6cDP3Ose22b/lu/KpYFEQG0wtUL8hdYjA9OZfzoKYjOwtOw2jA\nC6bO0/WOLRN9FZiqSAgTl+6SxV7KoipH02aEncFYqsUHBy2LuqIxBiWOqeo5k8ucX255fHnF9aZD\nycTkPT5Khl7jrgKPzjIPzxOHK8/JoWI+z7Stp6oUtc7U1tLUhhQD3kWmCaSyxFhoTGoqs/VYiZEC\nKd78JYXKZqoqEhrBzAnmC0lwijxmUlKEFPYkX6iEATfwurvPj3/ff814fJtf/MwFa/Vu3n+84cee\n+Ac8etTwI6fX7A4z4cGSmbnG1hXZBSAy5sg0ZupeMUex6R3XRw51V1EJkDkhksKPjjAklIM8RarD\nCmUlwoBuFV4EUihtPlNJ5MyQY0JoGDLkSRBNpJ7AMKNpt9x5Y8HfO+j4vFX8xEsf5En3j/lP3/1j\nvP/yb/LaNvJZc4eFOaZ130b93Cm5ijx844ucL1esvvglzM1T0gjrGxWf+MKX+O63P8c//71/jH/8\nS3+XanZEM04kFUgiIKvSBZBKoCuJtgJpEuiM1mCq8vPXFmyVUaowFkoxMWHrAvTFv2klE3uoS4Gc\nkApKHqnKYuFz2WHGRE4FQx6jL/QwLVFSMA6Jq/WWdnZQCrBCFII2GiEkIUS6vufi8hpja+qqoet7\nckxcrgfGacI2mWYVWMwabCVAJIwJGOewGqQ2NE1hjRY0vEUKwzC89ZrCV8WiIJOkGSr0WjGowDR2\nmHUHTU3eU3JFNBhqFAa/m7jsrjh3a7pqg5sP5JnDTJnYaEDT6Eyly5SZTILGGuYLy6JtMEJRywV1\nMyORWc4XzBeas4sIuoBjh9HTDYF2aXn8cGB7CW6T2IaMnAQmQiM1yhgqW2GsIkUYhCDFTIiZfnT4\nKIgpY53A2VL1TkJjRcKaQo9uG4mIEh80vVNEB2mIRJcIUeKGoshrdUW36bnxte/h4Tf/AH/l6jHD\nZs75+n38O0f/PSc1/PjfPua7viYxM9cM1xOL2xXRzkh2RxgnZIRFq8itxSeHPYjcmmm0NHgEJnpS\nKMUpkNQrRZ4nRONQlQGZycpjyKgkSEPGKFBCEEMZ1U1JkKRGiUQicWEGZjKweCrxI0x86xsf5t6D\njq976qPcWf0lXutv83enh7z7qOGMjvWjl5jOHjBbzBH1iHvjJeTtp2iev4H49Y/S6RfYPmF56cEX\n+P4/+W/x4b/x90BFRJ3LrkyBsqULoLRAaElWgaQSUglKFrt0vdCQNShbeAQxGpKFUKUycr4PLsW4\nl7vm4mssR9ry+1uKeongJaku1KUU0+8mGUuRU6IkbK4dWp1zfHJMXc+QciyyY0RBrYXI1dUahGKx\nWBCzY7fpGfrANDridU8zKIZ5oJ0ZFge2BLm6QG0EdVPTzmvquiqTl1pjVEKIP2TaOIlg7mfIa0kX\nJuKmB+FwtiSjfAYhNFYbrLT4kNmMV1xMa7ZiSxh3CNczzB2HtqGazamyLXJaRDln6uILbOqK2jbM\nbIM1hiwEpvYgaqya0TtXAiCtYfQ944Gg0ZZzEZj6CB7wGhksMpkiBWHvErTFBiUkhcDU++JKzALv\nKPFU7cgykkTasyMFdVV8AmNINM7gnMQ3kewkPpYIrwyClMFvtzRf8+P42VN8w8u/zRe/9Hf49+xf\n5Y/OfpsP/i8rngs9SnaISeJmgatackCGHLFK4gVUM8voPdIqdNYEFwh9QhmNHQUuFseCnRv0gSZK\njxGigE1iwo8Jq/bAMVmerDE7vC9MxQygEyorRAXIQHtVc9ls0a7mVv4Cr74DDs5OeeH+z/Kndj/G\nofodtq9vWLfvoGsPSa+8zElzh1xP3BnP6MScYRdYmEw7jazjyGYl+PKNr+Pn/uwf57/9z/4Wj+Kc\n2UzsE8OCqBMIicwJKSJG7hcIDZ6EFMUiFXMJKEkDVaXIKRJiQbS5lIhTYThKdKkniFyy+SKX6UQh\nC8XZp/JeaVnCcKIAgpUShQYoM84Jzs42kBVV1VCbmt3UMYVQaM8S+mlifPSIbdfRtg3rzZYwZvw4\n4vxEDC2xD4xNZthltPXl4VJnZrPA6iixPBTYyjCfGYz05UjzFq+vikVBZEmTZsjBMKSEi4EUBzpG\nRtz/Rd27x1qWZ/ddn/V77L3POfdV76ru6p7unpkez8P22PHblmLHIsQkxJBEgkD4A0EgEoi/+INE\nIIEgEpFCEAoImcgIOcIgkFCw4kCQBbFDHOI4kT3jmbHH0zP9rK7u6rpV93HO2Xv/fr+1+GPtW2Mw\n2I1lovGWSl11+9Ste8/de/3W+q7vg9EKzVwP36VMyBv2beR8vuS0PmFuFySb2LzckzslZXNrLrua\nDWdMC3ObaRj9kMld55zwEOhqzzofEI6MVTlD1Vu73RzY7qq3kCXx+L0tbW+04q1g6ioxR0r2RJ5u\nCHSxo6q7UNtC+VXDxVwsFm8h+FybKinHBRl3VdtqyJRVoG4MZthtd5TkQqv9xY6YD3j5B76Nr7bK\n+vAE09v8mP6b/MTP/23+zPa/4S9/95bDSYhdInyQOL9vtDK6diBF0joxpXk5OYwqgdIFpFZybeyC\nOKYSA7kPxFQgVFpNjuq3iBUjtIwuYauIIGYIDTF/dEQrOxEGEw5r4DxvsD20dxLMicOzA+Ro4uzy\nb/Et1z9N98HH+cUXX2aV9uy+/GUOX/4E5ZVPUT//kOH2Ad2Nwvtfe8CTO9/J3Xs7+PJj3nr/NvHF\nx/zw7/+jfO1//+/5ib9jDAeBVn17ECWgonTiYbA5elFQaYgaDShVXbYsjayNIQZSVvreKAZzdXdl\nN6pZ3LfEQ34wlyyYudP3PBpT36CLtKqo2BIbuFiE4gxGbZUPPnjKZj3TxUxOPaV4qrUl12To1Ght\nS62BOhulGK1CCj0694wK+13h/OnsI1JnbNbGweHAbjeyHydOrh+wGgb6nLDVh4+N+8YoCgi9JqQK\nzRpFlGJQSGzrlllGpnrJru1IQ6YfVpwlYV93XIYzymrHvesDr37iFrduDERpEBslzExNmBWmvWJs\nWeWBg3zEyja0NFHZMtY9sxRaVKJkDoaOWio5HxKkMu6Uw42wT5FdE3QvlFgYu4k8RLpVJVhAtKNL\n0IXGOis5KWOtjBPMIlR1amoKA3NUpuh4QUwdIRdyX1kNwjQEhoPETpWTbYJd5PFxo3try3P/xD/H\n9uPfzUff/kV+9p0HTA9/lqP5VT5x+5RjRj6WA48MrsVAjVuO7p1A3SNdouVEJ4F6MRMC6BCQLKTW\nHGhDyWMgBcWSIVSsZawGZHS3uaZKErfNJ4JpcwMPDQQVpPqD0BQ6aVQiNjVyOWWoAXJjbpW8G5mH\njqdH/yL/2/6P8DF5hzsvv8zugy9zctRYn9znwaMzbm0O4blPkW6uWZ+fcvDCLc4u3+XBw/cZXrjG\n/Te+yP90dp3Pvvo8//XPPGGmMShIHVAFmSbIQhwCWCOnhcZYhRKU2nx1p9WwTujyvFCMI50Kw+A4\nwn4fqaUiFA89xlBz7oJqQxRqDUx73zioOPdBa1ncliB15jqQEJe4u5EwBGSJj7emSMgIguTkHdt2\nSzDvds3MM1PDzFybJ6r5UYMAZdcxbRv7i8K0HdmfCUfHRkqZpr/HAmYDgSCeYiMqQPI+lMkDMWqF\noug8sy8zl3Xisg8UZuTQuH5/w/0Xj7l5+5CTg4BpYy4j+8kz+s4vR87OLgmxUUsgpSOknhG7QCmF\nqTSqKftpT98nJGRSl0GUNE5OWpFKTp4B2SpMoyC7gMULTApDS2x0RVolYlwkrOsB1Yl9bUyznyZq\nShA3AkniztKDRFIUR6P7ShmUtlYuaqEdDmwm4amdA5k7f+hPYLZhjh13Pvj7jPu/yR//+E/ysUvh\n1nNr9vcjR6vCNCrjEdwYlOlcyclFQKXNEAwJQorBrcDVocwcnCWn6hhGLQoUVBSr7g505TcIXsyz\nLEEsCqiz6IJWdPbYdCygkzmAXJW5iwzm41HZnvO/vPg9XP/1Pc9vlDfPXmP7a68xdiO32nvsv/Ql\n3oq3ubX+DO2559jND+FLf4dy7WXWhzcgjTz5oOeFf/w7ee8f/BBSf5JBBqrNxABlrIQDUNx8V8wJ\nP4hvS8roXUCORukFWQsHJ85HTjGw7gKhJaS5UE4qtObtgaqPKUZ7ZiCrzZhnpZsrIWeaeriNGaSU\n6VZGGRtVjWGVCNKYxh2QMVNMPDHa8E4yYJR58XAovgYRgWdgBuYMy+oKXS3KuJ/YbSu7XeXp6cT6\nYE9etiof9vrGKAoS6eIGAXoJNCuYdEjbk2ZAI0kzQVaMVtnSQBoSC+sj49bdjlt3M5t1Y732PJ3d\nPrCfG9vpKfvZ2E6NUiZCfEpKPXpS2WxWoIH9VJjqJWO9ZCqZos5+0xaZSqFVRaqHgkQR5mLMCJIF\nlS0hFixCTpXWX8lwlcN1j6kjzKXOzM2QSTw0NVRiqG7eKdB1mZwCfRcYOphWkYPSowHqceXwQcVu\nvUr6tu/mI23P6w/v8/P6R7j96jfxU/Uv8NlffZd/5w83Tq83bsxGeZoJuWFsMTVSl6hasabE5FFm\ntqRi05ZTzxPJUIWYEoLQikJ08o8ET9fSK+TdzE/IYujU3FuiCrUZQWXRFhjWxD+/Koem9HPHxX5C\ntvDu9DJyqKQJ3p3POR5XDAf34XpC1485GBK7N77EeZ/pj044/dwvc1sHLj5+n5MdPNoaT8oFz/3g\nv4D+hZ8kt8A4w2gzJ9cGN0QxD1dVkwU8dDpytcA8GYUAzcii2FFyQ02ULgakj7Rm9FNAi7j1WQMr\ngi2VJkbfLlkzWoFSZFlZ+2ubNqckB/PAGCDHgKlSRN3jIbrnQViyHFyK7xFwVp1ExYJliAFEH4+W\nf0MbSFxA7mKUubLfwuoCUueg54e9viGKQsTz7oL6KdUmqBT6lrAyuHkJmTl2jLESuaTpTEnGyTp7\n8OtKybHQdW5y0SQT94IGb+GnUn3WHBuXF4XLvKfNlRR6trsdF+MlFisyNbbb4o44TdhdFi4vZsqU\nEe2ICGKKlkbdgwYhZCN00OXKPk+ERfK6XnU0i14QypKCXAvjGLiMkZAhRCfFhBiJUehyYugq+yFw\nslsTB2Pbn3P4q5B+6Pvpbt7hg90X+Xz7ArcuvoK+BT9z9w/zH37nf0qwEfaBJoHdI1hdTzQrfi9J\n/Lq5be4o80ydKikqVj0opRVz12MgRY8jC8v6LS3egXXCTyzCs9PJZkMLUCHWhZMRm+/0m2JNIMkz\ngddl6FDt2IfCwbDhiW753KMdq6ND9q9+gu37j+kvG7uTF9mcdOQ33wGrHBzd5FQinZ5z/e5LDLvb\ntOMHnIbEt33mU7z6Ld/CV7/yS6xu9gRpzNuZdBjpxY1VtTXqLL4lMEODUhc7vmlJhZ72QFhcoYOQ\nQqRPkdVglNkoAbS6MZCYISF6dFvz1NNiMI0QauVZLKyKt1LqkbQiQi0zIUJKAWvN16cS3G0s4AI5\n8ZQofDpDLLoaUtRP/oUDEcVXk6qVZhD067yHWuuiEP+9Nj6I0AVvobMKyQLRcO659QSdEZnZ6o5L\n2TPqxCTCXkeiQN8Fj2aLV9FwRpXGaIXdPnC5bex2DjyFtqGTG9S5Y1cKwSZqCUg9pNXMbn/JVPaU\nUtEKZfI2k12gTokomS5BMX/DmTqv4EHBCkkmUsx0Q8fQJVQDtRjzNFNaoBVhmoUQg7smJQ+gnTul\nD4GUI8MgrCq0sGM4DpTLkRgH7v3Aj9BC5N3Tv82d/cxb/Uv8sed+gu+RPbdFmTRx0CAUZXwsbD5+\nA7VTos1ug25+M4k5cObFIiCqSFW3VhchJZ+HRSCgjrCrEIiIGm5A5GCaFU/1WmwPnbi1jBI6q59g\nCtIghEgqsN2NhJi5zkCbK23bOD58ifdPOsbHpxw/2TK+dMj0lffZvPKdHDyG984vCB+cMQ+J7fGK\n8NYlh6/cIxye8PrZKeH+bT75/d/Jl3/pl7BDiJ3z//UgEZpgxb0NWvEkKTU3OWlqqDWKQJkD1w8q\nwyq7KUnKhJjIVlnpxH4PUwQV8UfMPP/DQVYvNKW4f6RnVjooaSIEFZIEcvSRouFaGCGg+Bo8ihdO\nkiwms0orLIYrXhmu8lBFAiauGwohfH09qk7EEhGaNmpphKjLJu7DXd8QRQEzKDNiiaTCKna41AyM\nFaKFxuiefw2Ou0bpC838tC+ze/THmFE1pnHP0/NzHp9d8F739uIAACAASURBVPQCdnuYZ4hq7INx\n3hdsDHTBLeH7PBCl42LXON02LvYju93kp18JxJZIrZAskSSTO88eLKbM80JmyYWQI9PkBCaS0nfi\nBKcSWa0zY4GxNlQzdY5MkzIOiaE24lxIqfN9dgqkVOk3gadlpNtX9MZ9rn3y23jrfM/bb/4hPjPP\nfBd/hT9992d5VQs7PaG2PbEo07YitYO798G2SJuBpQPFsOrquRgDUcISdW6k6KEmIbqZjJmv3aju\n/wf+/uvsJJ0yO4ofQyRY8JOquUIyWSC04HH0FrDmtux1J6yzcFYK/YWxX/V0+0vOzy6Zzy9gMzKF\nLatffYubH32OtUTeO3uPs7ff4NZnv4Pp3ivE29d56+13KW9+gU986tOcv/mAz11/zKd++A/w1/6z\nH/fYuBBRrYyl0M1GiA1tDRNoFTDBYkLNW/upQonC+VnDUIZhWRcsNulDF+n6QNwrVfQ3tO0OvMbg\nasra/FTOeNER8aDXq2IZY0AVkrhWRBcpvkh4ZqMYcOwgRX/gdVYnTYmCCQH/mTkI4TCjSECWgJyc\nk+dKmGdghPjh15HwDVIUTBWb9lQ6mgoEGMSIljAxahRKhGgTG/yHuzew4YBx3HL6sHC4ntmslbya\n2Zc9H5zteHxWOD2LXuEnIWtgjo3zs3PscsOqz6xXHda75dsHTx7zaDuy2wuXu8g4KqsmnMRETD0p\n9/TZ3XPFAtYSrQQ0FPY7JXaJi73SrycO+kSzSuoSw5DY1IF5CszTnlILWpzKPOTEVjwPIEcDqxjO\ndJy6nrYW7r1VePCtL3Hv5Zf45Ydn2IEh8z9g9cH/QJvWXBxAvPGErgkSN9iJspLCVBJ916N6QRQH\ns+KyQotBiWERDzU3/MxJ0FCxeKV6FHIMaPY5tulSFJphk5OXUEfNqynW8OO4QF1MThFBFxvyGD3n\nsZZG1I56zengwzTy8L3HHNxq3H35Ppfvv8PBk0L57D2evPeUJ0+ecu3xUy4evU3+fd/Be3XkY6++\nwu7pO5x+6YsctMgXX/saP/I938mnvuUzfOntz3Oy6cGMaXJvhRAiMisaDAue7RDwh01IUIy9wuPo\nzsvdbUUYvUOSSBcThwe24EOVOi8s1arUEikKLTqAC1BzIAZ33q7VAe4mgSZuANxmv4cIUGvxQSN4\npmkIkaDuJ2lBGBesQYJh6rhOsyVxOkY3ozVZTGW9w+v74B2fNVqz33u5DyrKuW5JOhElEVpATMix\n8/lKoMa6vDGJGg2iEvFU3qdPd/DWnm0B4kgVZWqw3Sn7J7LIjr21vWBHiL5yqzpQ2oxeKue7Cz44\nO+N0LJRJGMfAPDuHvg4QhoGYB3LuvIoTSW1GrbIvxlwmCEZMldVqYrXOWPPupU+JdS/M68jF5cx+\nLJgIZYJdKuQuMk/G1JVFYp0Y+p7zeMbNvvBaWPHSR17lQhL9XPjWo1/gyw92/MIb/zw/8skf55uG\np+y7jqYeRd4TaQ+UuH2NIJWWwKSSu4DObk2eLGJt8RVIHoEnJtASWoWmSsiBMHR0qLfYc6MVPwnd\nqNYw8ZMP9VHBmm8uZInVu8pUtFbRJiSM/WIjf5yVCwbW6wvqjUMO710jvdM4f/UVNp9/nd2ZcXZ6\nwUlR2seuMb33GvrFRvr0K2zf33Pn+oYHv/ZV7ly7zzZG+pNj7t1/mS988XNsrkceM3OcVlzutsvX\n7N4ZjvIvmVJLzstclKrG5QWsD5RpXqLdguMROQp9CgxDYLUK1Elx/E+w6mSn1pw+fWXhJmYoRlWj\ntOY5lvBsDLBlC6Lqs5eZIQFvtcw/JlI9Ut4Es/BsZHFAMgA+upn5v4e4RXxKzo8QswXH+PDP4zdE\nUWjWeFQf0VnHJg30NhBrRFMHQWhAC0aNypwKmgOWcQWcBKYRHp3O7FUg+P68EdjthenMqAVa9eTh\nUSt73TL3wkGbGUqktsbFfsf5WD3qWxO1OGnEBiHFiMRMzB0pJVIIdJKJNVKsLlyEgu2NbqzsRmWe\nO0oJ5NyRQmRIkb6HzaajNGGeK2NVwmgMfSBHmLOvx7ohUqgcrFf0Y+W8z3zXp/8xfqEo8eIJ64tX\n+MLZz/PZo7/OD15/TCuDC382M/N5QfbQHmVyO0X0+OpOJHauz5AciAp12XHllHwFOS+77xg8VXsI\nyOCBNVIMqc3nZ8MLyjLvYj4iiBm2ZBhEvDC0pmgTb3vVU6HpBufp70YejL07Em16wsoobz0mP/cS\n78+N7umesr1gddLxFiMfu3Wdp2885GHIPPfKCxw9d5/333rE7vYBwQJfnUe+95/6o/zdn/1p9rUS\nYmTejsTDzqnEz1KT/EGpQG1eAEv1j7UhshuVy10jd+LAn/kIEGmsO6Ou/d7YiyHV8ZfW/O+nEBaJ\ntXcEbk3gYS21qlPDlwKK+YrX4NmY4n9yjEJUCXbl5wBYcBOX5bkRCSDuo6BmXjzE2ZO2rJadyn3l\nD/3hrt9p7sO/C/xp4NHysj9nZn9j+X9/FviX8AL8b5jZ3/zt/o1C5UF9yGAdx3LEIRt666F1pNBR\nRJmiMqfGlJRtmth1E9I1pI9UE8qlu9yqq/oxYByNuQZqC4uyV9lWY1eg9JecjyNDF0CUqVVmMzQI\nitG00PD1Xegaqct0XSbFRApLWwwMdHRTxCaj1Mo4Gdu9sN83NmujK8Vdl4OwWgWODgemaoxz9TZa\nIhc7RZKQOyXnRgyFGIwcVpzqGS+uOp580/dSxqe0rvG53RtcqzN/9pXXuRU3vP/WOfnmik4LQ1wj\nrVFQYt+e6f6bKcmMkCIEPyVDcjSbGLBSadKIGaRrxCyEDsxmtDnQKOYZiuDKQVVzpqkFULy1vWI4\nirfoc1WoV8al4RmqnjLQweNiXA93yHnPRXjC6mDH4Zfe5r3bh4zhkiMmjJnn8nXawTWsFe5tXmZ7\n5w6//uiceO0m3e1rHL9+wa9dbvln/sgfZPXnjhjtklidWi4W0OrZC2aeQm54R9PUqOrjfO7dEGec\nG+fnHt66WTXS1RpQoE/GZgjMG6Oq81tSAusgGOSkpCUROohQVanLe+dmNO7boD6Duq8DoEkcoBX1\nda6ydFrmHYG5MvPq2BdxMNGBx4CFpXFYujMzo9aGifqG7Hd5fPiv+M25DwD/sZn9xd/4ARH5FPDP\nAp8GngN+RkReNbPfEumo1nhkTxgkU0ypqmxEaTowGDRpjKKMQRljY58q+74g60qJlWKVNivnxSum\nmptrCAGNAV8EqSPNI+gcKKPSdzOrHlL2E66JEA1kceoZBPrBsyNjHwlDJOAjjODgWrLi3UAMlFbZ\njpC3wsVl5eBISbmyTsHNQWNkLELeBefHF2Vuxr40cvGNQ1eFWJUhJ0qthHDBrRvPcXFwHZsKjIHX\nxzv86K0f43vnM06/kslhRT4U7EKIF8Z0UdltGu1goJMJFW/rdXH5uWptQ7pqYw2LEPqw2Kz5rtxa\nQ4uTmMwEmUGqOxxpWQhBBKwpWh1zsKXttRycpFXdY0GbkUwYZyMyUVSgDwyxcX24xa+Pb7ImMk9O\n/b1264g3L77G3Qang/DRw+d5nAfsYGB7tufa1LOzme7Obbb7id1GuN0d8dYg3PvMZ/j8L/4cN+8d\nYhS229HDVWKAYDRtKNDF6LLqAMRKt16MvppwscU1Cyqsej8AklRihj4LfWfsO38fUicE3FGr64xV\navQWaeLbGd9+RHQ05jFQ1YuqE8h8gyBBlr3jMmTowgtxZAbwsYFlm8HSgbh8xqnz/iIfXZyw1Xzz\nYe4t8WGv31Huw29x/Sjw3y4Grl8Tka8A3wX83d/y3xBllgmkMcrIxJpO1E87UZooRStTK+wZmbuZ\nUWYqO5pVmjldeGrm8WHN29ucAylAEsWCc8frDFaF8znST66X73oXwxAEkejZe523wF2XiSkD3p6J\nkwAx8x9OSityt/jst+aKtV3g8rIwzZU+BWYCQwoI7vS7XnVsNsa2QZ2MsVSGGfZjoM/QJWW0QuoT\nt46Ei4P7kDrOp0j3/oi89gFfXN/mP4if4fF+4N/+ltd5/nTLXHv01BHxgxdX9NcGrG4JBq0aNVS6\nLqNavV3FGZam7vWX8xJEC4g6Wm7LBkbNiM3XjHVS6uhzeeqc5afLZihElvHN2+fQL6u2BkxO0+03\nQp2hBqWfC1qfMNaOMN7iOCX2h4eMZeLWPlEE9nePeFQDJ8N1Ts/PON3sSK99EXrh8NWX2TyZefuw\n5yPDAW/LJS9986f50t/7OdcslEruM5hvXEAghAX594cxiEESQlAnIFmibY2zpmQU2XiHo1Hp/Lkk\nRiMnsAGPbkuCaqHrYRUhF/fbqM0nWimGFRfGVXWAEPy9j8G5L95kCRb9ZyPBNwoux7ZlSxSeAQRy\n9SsIon7v+pgQlns1+tpSorNLP+T14WlOv/n610XkcyLyX4rIteVjzwNv/YbXvL187DddIvKviMgv\nisgvVjO66Pp2v6kCleAyteCee63MtGlmP42MOiFa2OvEto5orbQopOAV20ydGJLdEKUPxgZhExN9\nEkKoyHxlvRVoFtHmKPlehSk06AzNoFKxWAAjhUSKA4I75QQxYoaUA33uMY20AvNc2e49DWiegoNQ\nQCeBVYJ1Z2x6YUiBoJVQjDJWSoVSQasStXGYN2z0gDsvfy+0QMo7km2RX/k5Pm+vkJ7c5JY84MTO\naIeRcQdyKWxPYXN7Q96MhP6AkBIaXNFowb5urrrMoVdRasQFu1Fd1oiBUpp3Fs38vVUDFZcgY1DU\nW+Oly40JUhDvTBqEIVC7Bj6lYVPjAkiWSRUYjnhf33UHoXc63n8ycXrjgNQCUQqnQ+Z4c4/1wT3e\nLRPzbsdHbhzTjQ8Zv/p5milTf51b117g9PKU09Zh10/QCnFX3d5ThVKNas2BVTNPTZLliXX9m2cy\nFt/GlOLWfWdb42wUdrOyLzBWoZoHya4OhGEt9Csj97p0EYH1kozdReiTOOGtCTQ3gDXcDy5Uc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GrYGpOUkpp0AguvBt77b5tQTXiYh3Y+4jLb5RUCdWEWxZ7Pi6PMjy81vuyRiyKyklPnudagMt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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c1825ae80>"
+       "<matplotlib.figure.Figure at 0x7fc1178db860>"
       ]
      },
      "metadata": {},
@@ -975,14 +1004,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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9/iEAP8XM3wXgp9Lvm6kMhBc5QvkCaQd5EDzsngYpS2Hu9SlByhCqwrd7/sv6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zAAAg\nAElEQVTEpL4vQBPeHaJwVf/fKaLRUfBLQrDVM6OT0hvdv69IV2Q5BEDo+RVaH0wtMGDTG4csT3s3\nbmIuYGJ6j55rXFM8RyXbIjApyPaU2qM5+MLE5/jYSONGvc+OggcJaNNHE3RaP4bvpBnWLo8Hzi87\nG7XNh/Q4i7iBoioR/RU60TGU3bo+znuYXFEvT41V2QdVO3Cq5kO/V4y50ByVCdMh4/Wr1zgej3j1\n6qUemybM0wRhNU8SAedlAYs6QnnpO68zoefouJSqaoMDkUxeDzOhrAXrNGPKGdOcQUmQJyUu52XF\nsq6oFWDO7T3Y3BhVgkbDqLKpq8hpu4Xe2N4dogCgybLxCJGl9HNO1R09Ru5MF9eNNv6EWPrNmwSO\nIeE+g42bAKrUrA6ex1GNP6ovXJrSosNUByMvwb9usdi+g24S5yjuu+DPqeHzpbOV+3Q4AejOVaGP\nJgmIbbRxU49OY1vdfvvsa+bIeL/tuEe34WEuxDMoK+YQC+e4bKVgWlQ/wv0l/rlVJYOKMxD4cQ05\nIJluCGl6D/M0I6WEly9fNhfpOU84HA6Y5lnXiZwBvEKtFbe3t0NR5GnKWNdiFcn1OU4YBIatsJYn\nWLN6SM5zVs02MZazqiFS3SLhUk4y70p2FtBeziEXuqSgb2zvHlEIL+UEoU+ecRLs+87rZfsht9t6\nehHEarooYM5DZmGAB0BBwTfbwL3yUyQAMmAGPU9i98e/ton1nGxStXNIhnDp9w7v65V/VPqJmzWA\naO0Z8Znjsz3gJ2ZPir9j803sHPBtRCGO/TgPvHvNRdIZbLNIda4eehU+q1oxqgKXzlU9otXNqX2z\nSAOEMKwbEsLhcIP333/fci68wvl8xsPDA47HI+7u7vD06VNQUsBvWTXs+unTpyZteFVuW8wGDjbi\nZ5gPmx8HDHNYFrF0eBWlCuoKs7yQv67OY0rd/yOR5tFkV9Xi+DyuvVNEoS0UQNFlUj2rZyk2h5lw\nDcFxg9GEuE2s4l5m+hx1LtmG5wJ9MWj2naIeYcyoRd1M3aVVwSQzPxXNNNxEdXJVvKd573Uwtdce\nh9GJmJibqpqapBSA3adeANLjZV1wAaxdcAHFO/R7tUjEYK1+lm023vy9Qxz8WbVa2DnxcDyK+V1N\noAbGbv0EfIzjpvfrtol7O8FQHd+lxc4/opqo78NVNGMR9lUZvXccqz50RGRl6owpJU1++vTpU9zd\n3aGUD7AsC15+rolaXr16hWVZ8Oy994CUUUvBw8MDXr58idvb2yY1pESY8oSUpmatur29BdcVy3nF\nshSsa9X0cmXViE/WrFK6EDOEM0oh1EqAJBBmxVrmXksVRM2qBmQFV3+TMi99xS2i3Qif1Y+8/b1l\nDnaWWtccf7gstTambe8eYJEpurQwXIu+MB2sGsTZRvF7MU+3Z+811yudODS9PqxKYatfseXYgwgf\nRmyXMLRLTFx1P4sdjCCqPNgnNO28ILbrcUL303eiGwgQdzHXN3NUGyKR2GZyjs/dU0HiOZcOYQDY\nQ46toK509nrtXu4El/MEiKDwagyqe6h6gtfJvCU958Lr+9cQ0aI4Nzc3ENGKVSKCm5sbTFNGnuYm\nsWksxgHLWVDWaqoAG5brhWEr1qVARHMs1JVQSzJAMYNoBSEjyWzbQwCug+Vq1/PzDe2dIAq+8YCu\nQBBR8yhzs85gtzYbe7J5Zksq2J0/TKSimMBlywk7RuAFTVyk80VW11UxBGEDeLoHnuu7Uiog0lQP\nf0YitYF7/kaQovKRU3aXW9j9GBxK1rkIWGuFpKx+FCY9CMswJs2pCozJSrUxuzmuv7PnlxhBPNj4\nBxNjI1BmhUlkyVxingDf3O6TAXhUX3uHpJJOXJxRAtiqDcAYGLVVP7YEoo/B6PMgEKQEI+amCgzE\nbkfdEZcWVXpwi8SIN+i5T58+xTRNuLu7w4sXLxVvWNQ9OueMm5sb1FpbdqcpZ8w3N5jnm6HfKblF\nyzY7VrAoQShrMctHAmFCKYSyrChFUKvjVQlynDBNui6IgZvDjDzdqMgq1GpwPKa9E0QBGCe/Lx5f\nLLWZ5fqmByDqByhmh2kYQFs0rttvuYMM92r6NggSEPCccw9jNVHTF0irJxE4LaFzO39+eJzlfowm\ntujb0PM9iInescX4eiObcB145KZe/s02qTl4+TP6O+Oy/21sTUcTdO+9pHUpZVMAp++VUeIYRDqm\nLhTR2F+PZNxiEnG+olT2ptbfMUgL4uvDwNpWs3F83+0zWt7J7Nah+D03on9zc2OSYQYlAn/+Esui\nBWuixLAsCxYRHJhR62bMxSVXJ6xkWZ3W1hddOxW1AqUwVsvl4IytQKWbnAjugHpzmCFZzdbp8drD\nl6778J8D+LvslA8AfC4iP0lEvw3A3wTwf9p3vygiP/vWZ6BT/pSzZUxA4GI+0ToIOU+AofGd6/ag\nmou7u1gWRPXxvEBo4KaobESBDS9QTpNSrC/hvduoNeibfywP138gYzBQ3xTkRgFEi0B8QNw7kXN6\nyjgYgWmvhm33/F2vWwwaIZNOpIW3J+3jMVsdvun/aTzu/d9iI29KHXbNyuSYQ3uePUojCI0oCUE9\nXWlDFFIjJN3ykoy0OUa0o74YCD3PM54/f45pPiBPMz7//HMsy4JXr14hZ3VlTiljXRc83D/gfNZy\nd80Xo6qE6NW1FcuwMOnKhke5ROsSa7Wx036f1qLBXaSZn3Im1HIA51lren7FmMJ/jE3dBxH558Ok\n/EkAL8L5vyIiP/noHmyau+rWHdG2LzbVESszPKnElhaMkzjiFfvEY7w2udUAAMAqQRAg0iUBT/2F\nAOLt5xZ0VaXXE9DnCNjdtBvH7/30NN5cuUsZDDBJ0xn9GY0omFSQmzQgkKzYzCUC3YnDBQrffvdn\n5Bxdka+dj+GaOBZEWl0qXhd/tgTybfO03/qG97mIKdG0H72OQ2zNDJlSlxRIgCRNrYjvHvtLRHj2\n9BmSmSlfvHiB+/t7vHjxAk+fPlVAkTOOxxOWtWCe5xaWncwkWUsPcPL+eP8rVGJTILqvIxaGsIZ5\ncy0Q0dTuh1l9KHK6jBh6W/uB6j6QjtA/B+Af/YLP3bubglEOFopu+JZfEUHF0NO9h2EzXfQdvuCV\n2hbvd/sdiYdiFf1anSjT85lbeXmg4xC1Vo1fD/1zyUP7z/bZYiAC2q4LgFtIdCsE4v8Hk1rb4OKk\n4ErmIomDIzaO0qSOLcdjVglsm3w2irfbzR1Vo32xH8P32lSsFbounVyVWnBJyPc4t3/vUmOMwNRp\nIUA8K7KXfXP1oUsO8doWfU/xGSOhakQsJdzd3WGalDAcDodWq9KlxmmamvPSuq6KK1mody3VKlOp\nBKBzA3i1arWqmHkdhqtJReWiTIAFXKqWp2O2FLAw57rHtx8UU/iHAHwqIn8rHPvtRPTXALwE8EdE\n5C8/5kaeg0BdM10M7tGGb1sw2zbq7mTc+vrzXT935FdEQEwoNnnMFSlT2NCjDZ3ifdpG9ghPPz7q\n8KoOpRgKDw/uslXaXK5bP+FmRl+cHdnvf/um6bH6TaLeEAb/Lg7h3kbfs0Zsx3lLOC7mpRG0y/tc\ne8bbJDr/vadW+G8nYkpo0dSBAHS099/FL3ak0Pg+zqj88zzPeO+993BzcwMiwqtXr/DixQvknPHk\niVbILqW0H7W2uxVHWoIXVScMczCTvONAgFb9VumggDDZ9wWaBr4ChqeJ0CDNvq39oEThXwTw58Lf\n3wHwW0Xk+0T0UwD+AhH9hIi83F5IsRiMOYVEnbKXTCOIjGXbWQRUt4VmLzsXN6063ShIZM+/EF9d\nUIjIdy1aSpzBiMDcqAaMPhJE3VkqLnqR3qdY8+ECUIPVFQTgnpi68AOI2bhcQjT3xf70547fXb53\nW9I7qsB1otvmI4xDvOaCUJjqFyW/7XP2rtv7PLzrBVHwdTMSwOHaRghHgtDwkyschBzsQVc3munP\nvBWJqGEGn3zyCaZpwqeffmqp3FgjMW9vsSwLXt+/Rj35yEC9GqumdHermaqpWkRWx6w2r9rKRfM0\ncHdES6SRfW1+mSE7++Na+9JEgTSdyz8D4Kf8mKif59k+/xIR/QqAH4dWkRqabIrBxGw4/sI5Z1tI\ndZhY5mrAVRpExJEL723K/aQgcZNrpekuBYi5j+p5aP1rrs6kYcqRmziBGReW1Vbg0VfgkiN7hql4\nLDeAk6Aij5e9G58pzQKjB03SeAP0rLdRiaUzwB1CRRS+H8c6Zq0axzoF4m6vlEaC1e99DSj+Yq1f\n7x6N+6rH22pB7kkK/Z2lHadkgWt6AkCj+nF7e4uvfe1rYBZ873vfbRmYD4eDWl5AKHVBrX3dKHZQ\nUblqGrZioOKON2j1tVpL66PBbGqFEGnWiMe2H0RS+McA/B8i8qtt7Ig+BvCZiFQi+h3Qug9/+zE3\n61yCh3x6ahsfxVP9is1j7tIrMbZLfdcXROeMzjn8/D0O5qTWfRP8JyXPBAUr3tMJiN+vcyAZju19\ndk5qR1o/iXrOBl+AYuJrkn5fgWwWTj83ir3tp6kddLVfEaxrAxXGN0oLsen5wReB0IukDuegSU9b\nrOCxRGLbb/UB8WItPGzU4bq33hhQKezyq2VZepKVWrFWzY8xT5rLQkQDoW5vb/GjP/oxiBjf+c6n\nOB4fMM8T5sMBh8OM4+uzEQHNxThKc2ymx2CyJ4/jKXDPUvezYanINA1ENl1592vtS9V9EJGfg1aX\n/nOb038XgD9KRCtUTv9ZEfns7d3Q3AbMjLUUjV03oC6xT3AHrGB2dHIp2p1sLPefL1LFu8icj7qz\nzJwnM2fqDdZSsVZuAD1XQ/BzApImWGHSDedOUESEnDXxi7uUqsRAqMJg9GSdUtnSmhOmw0GzB5mU\nQSpq6KuJBmOXWpGJMOUn9oKClG9QU4ZbQghixUWAU6lAtRJhlkdhrQA4gSE4iyCbBFJYIFy0VkTV\nJC05T7Dcn1q4diNtpZSG93apx0FIjU/pKet6HIcTXsVVPI252HsnKwTcskUZAUtWpzGK8nqpGG3u\nYN+WKWw/pzTB3dqdMOj6kKaOddmaLqmEeWqOh3WDTXkCBCirAJLUItRUR7Y8FzoeN4cnuLt7jrsn\nR7x48RKvXjxgnoua1+G+ELr5Pay6FiUUmkY+WBzaT4LIDOEKxopkoKR61lZYBgeszF+t85Ls132A\niPzMzrGfB/Dzj366t74nmoOOcmc4eqOnmfNJFEnFOJ462AQ1IvYLfYErx9J7s3h0YPAKZPSKU1kX\niXQMz5K7bAApIkhyDq4v1M1aGsYLOy/ljERazMOpfiN3pHRJzUyk/uotg5EmPhFTHTwVjffJAUl3\n53X1hSFAZUiCpTJzdFsR7om0YIzqxaT3kkv32Dh+fcO3F25cSb1Qczs+XOefbc67dBiBO2kSkV/v\n/SBQGKuukuypHS4laV/35AEajpPPc3ifeO72WsBMxhIsAdCIU7ZqTX4uV48Zybg53OIwa1WnWs7I\nuaAUbtKqE+D+I01SUGnCM3oZ4Mz9/UQBDs3q7CAj9X312PZueDSKg1D74lxM89UWm3+S/vc1Eakt\nMPu/64W+APQ4m/7lHL6ZEZ14XEn6wszItqHhxWzTxt5u/RBmsKlJYOoVyL1HrgKwYJXV8goqJ4Yn\nCmHlAWhELaoH+l5i8R/NIzP1CtttQxvD9feOBu0hHpHUzKdBmD5DffN0ySkP7s9R4tB3d2yoc2Qa\nCIAXWB1NxT6WGmQ45tfYYhGjuqjxKjEWI4LPMRDKOWyTQAaiMKqE/jcTdcsWpIn/usFV2vGNvCwr\nyrogpYx5PmBdC5Z1bVYGoLu9T9PUXei36myb7yAR2/s5Q01E6ucjmveT8MNIFID2sgDceKSHTSRN\nwY6ukIJtalvUCIMGXAG/2HBiO91pjbuR9s8G+JCHO/vvtFl0vaknmiVw0261tFtxwe7b/MNnf64Q\nkrhzli4+lvi+7uJqCwFbjimNs1apALRGYVzqCejhtrYZE2XEGAIATX1zAGs7b23Okm+SUQJoRAHO\nvYMjewAG1fGmC+utaCssjgQhFN1L8V3BHPpYR1+PS6/J+Pe1ebnaSIxRqInYXcBFpK1b9UcoOJ8W\nHB+OGvGIhGk6oFbBUlZ4Eh3HXZyokiQ1O5p0MKoO3TwZ+6quL4zKFVWUNXS57XHtnSAKYtxYf0zn\ntAHSrR8jJUf354Qg4uudjMpqzoOcc6OSJkzbb9/sxqGcw0YugtRDTpuE24f3YhG1RKhJReEAnjXQ\n5zGAD8f7uyOLhk6n5ATBnzvWTehidcjolBQbUdBJ++gyRUpJcwv686wuYUJXtVyT05NspMTlNo35\n91Rj5HiAbVgP2iIiICUbIp2wBpr24e1wwa7EHw7u04ImYXhwmRbFBeK22G6kx7Y90LOtJ3MQi88H\nGKfTGcuy4nQ6q4vzsihWljIO8y3EAuZ8owMd1KQU42i6FNmfHMBdl6xY0SyXUKqIMZTfPD+Fr6yp\nuMNo+WNcV28KaBCtuyKg54Es27Ku1MorqhTjJj0Hg7Stz0EPtL/JxLCgK1MnFV1ycWlmR491NchB\nURcHo9nUi4d41Gdsih57sI2nMx/FxHEtd5WrEwX0zSaCnBVsI7gFQdr53kcAza2bE6MF6JCJ624R\nCoRRAB371OepDh6Zdm4XBOyZWp9gq/451xe7xt/B39BpCcL99thfFLeZK2pNhnOMmyue72P/RQmF\nox1ay2G8p3u8nk5nnM9nnE5nnJYFZdUCsY51zNNBvWahZkfNAyE2cG/rD2FnCUJEpdS1FHCtkEB8\nH9PeGaIgLrbzHucbHX32JjeK6Cq+xXP3J/zaItAFYuvVxbl0ySneZC6LJqS95w1c3QGroT9iG9hd\npI0LJyDxDJBHP2YkkmZ2arZ5vbECm/PUoLrQAUuh71KOvWtbjMkOdceoYdyHW9nYsyCmSIuZklw+\nobB9tuMv4tJh57pxLNtj436Ry03eiYLW/oyP2a6d7TP25irO0RZrGKNXVXJb1xWn06J5Fc9nnI4O\nLNb2HmVR3CfnqSVgWVdVFRDeIZppu7TZQ+2JrNSALdZk5QpqZSzLAuYKj9d5bHsniELnhHHTALH8\n2h5R6OdegkNbjr5HAIbrhkUyRi8S0Kr5EGmEmuu2bo/2Fj0V44T6OZ6rIXpw7hGbJroDyJkwz1r7\nImWCJCtLRrrgE6kFwQlovB9ljyfR1lQvEUsxhyaZbAkrwS4NNRXa2AoBOUoo4xjr56Aq+dwF/X67\nMRVQCarj5n6uBsiGEGCz6TtRYHhk6z4Qeb1dWy+RMBQuhiO4KKqORufzGcfjCefzamXvVYUACIlm\nk5Rq2NgaFel5eVbP4eFBWUnxGUrqeh+zkmlfHbtSwusZwNlUCGG+ir3stXeCKADjZGpLbeP59/G3\n/mH6O7qOeq1d24CXLbguE6n60f4Gtp5wPaimPydGtwHd4Wmr9+/2K3IEUv8NTeI5Ny84TgUsBU24\nJoJWYmA0otDUD8EaAMbobzAQ0c3GbkQB0IAaE/mHAhahxflTaWXETsh0OPf+08dczpmCkR6nsGUA\noX8mTdgfQz9if4CddfOIdikVRInFfldTIUhFl8pKFJazEobltGhl6FKUCFeBUEFKE6ZptnXR50Kj\nUIF1LUYwfH5N7SN3p4d53gZHLZKmfhHQwEauFTJtBukt7Z0hCrUW9TXIkxXD8PJbuklzzs2DMFFu\nIlJz/yVCqUVTZK9ruybmM/DBj1aByNVFWCe6LSwg5YSUZgAE5l4b0O+t55lwTJHy903hiUQi0h2x\nhrjYGIoWu2Si48CaGdicrgB1rVb8oZo0TbbRQiRoSlptSzomEhf6fj6HUbVh8VThmnsQkIHYOddW\nrqUcrVliqD9PAIjNsUtA3dEmuEKTRWUajqSicTXnr4Rs3NEVEVcV47v5+/h6MRrZxnwrlW6v3Tu+\nZVrOMMQyYHGtWBYtUPvw6oTT6UGzI5UCYSAhW75P6DFTT51Aeli6M4B1Xdo60pRuuCis7OtK16St\njFqtJJ2Wt1vPZ9T5gHl6vArxzhAFd7iJnHZPV/Qir2ozDym7oAMeA5W8vV06aGc2IqIbw5B1q11I\n5FWEY9/IxL4El9KuqThbLrZ9x6g2ZEpWjEQ3WtuIwbmoc03VZbE5BvPqHISb7bWP4KBi140yUR+z\nbuPv+AOZ8t8/JyNcXkBnRAy3qdlYuBEATYRN3fPzov/777AlCm9SIbbzsf3c3nazljy9XikF51PB\ncl6xLmd1SKqi0I+9ZxagijsW6TuRvZo4ZkSEnD2n5GL9jgFyhs1QX0MpJcwTkCqhiubbIBB4tShM\nccPk49o7QxSAZKWyepXntnD8bwQgLRGShMhKCLJ0s9/ehPrf1zeCcWHn4hSiIpvephvV07y7j70S\ntHGxRskgPr89bdPHAUvI6h1or299UFdsVV/djBqBsnBfEUhKjROFh6qY6c/WB4+WAO9rGBXhSBLs\nt6t3DaaocPWlKR8S1dlL9UmaOhI4cSSsfQko5NDMdsNLXYx53ORxTlpY/CMYxfacrTm5ckGtjHVZ\nsJwXnE8L1qWgsrjxRvGooOkY6gM1nvux1D8lgkiGe+8yK96gOBbZeDim4EQ3KxMhRk1JzfGVwVLA\nXHYyZr25vTNEISeNIRhE8mHyNENNc3ndLC6ge211lPaaT8BmcYcmm2fCDJieQUlVhE6ldeH1AjEa\n0WhmvkHM1r55Ci5XYbbv0sRBSpv+SyMMzGJSgEky8FgRFdu9gnZzvdro5U1u9Q3nRMvexcrV6kIm\n0oArNnk3dY9CTVZCqOZy1Aq5wgiF6bmKl7FJKZsxF7PLU+hXIwCMHLJmsTCSBCe2RjjiXERswyNe\nqUW/+nxs18YeAbgmLfizmYG1MM6nVTMqLQvW84paWOdHbCyCJEOipu7OQKxup6kGKZsyGGqT9tif\nDECdkoQTUvIxAFKagGy1MnlCrQUpJ1svPcfpY9o7QxQoZ8tSrIvDvRS7OtHDk7cCI5HmpROUYRJT\nos2ZeqXPL1G8my5YJ0zU8DSr8ZguPePGbMxKOOZ5avjHAEoFIuIFVUZMYmdMnINDFwcbeCRVXZzF\n+0yAn8metg1oQVIyjEHY7HaVE2A4J2Ktft0ebJtVVRGBmwvFsAZBbSMYwUByAgR0zhnnUNwrJU4T\nt++TKYh8TXV5u+Zzte0RhsgQ9iwq8VoRQakVy1pwOi84nxesywq24DTA1LbmqNG9XRwDylaoVn3d\nUlvHSAiYWm3YAddOKPoAqCqRiQCacEharb1qLDYSJZMYfujUB+PqNiF1I+IJ0GozNk4QVwQlUM7g\n9QwRR/n9SjulUebtJAeiQN2Jh5IvQ2omLQ+camAY0bDR+3M22ZICQej92XF+Cuc3kdcCYwCygtGa\nwr3L0zp+ki5FZDRpU52ifDQlKZETsTXrq0zE/BRGYqrOeu583lUDaT4ISsRrkwRs8QsNRCDvxI5w\niDdQyhNUou2/jerV18G+7k+dsn/htiXq8f4+xst5xXI+Y11WlHUFr0WTm4R3D974RnepLTl10HOp\nQDc3iECSDcgmlMItI3RNtamM6uzkI6v3SYkwHyZMhxmoAuHaMLAfOklBGbEusG6fdRGum7e2Ovqw\nCOBivTG8HXHv+vM7V2gcpOmhl5vc7xdxBb+PutbqRPdELW9atJd9bO8ZQr5FClJWb0h3qW2bd4Nl\nRHOccuEYOVpBkpEsdkDsJfuCdz62wT5Eruau0K9p4IpoT++EXbWE7mfQLQdd45Yg3cV3aT/kG+yS\nKDwWK/AxfpMFYgsW+3c15NM4nxcsR5MQamdTJB51EskdGRlV5UwJB2yxBqJgV+U0q0qAdQC/4ZcA\nWFd1pW4jTirpztOMfEjdWpejy9jb2ztBFByA2uqDETwDxkmLv7VdTqJz9O2xqwRCpJVXaykOAud1\nVWFbWGZ07HGHkzwsrEgE9p4/vJMvQCMKOrkCrlZktnFkM6eG+zZiwAIhRSW9hgQjhDDbOyYTNrYb\n6pouvek13AR5bUPGV20cX/q4beenp4bbSExBmhFcJwqXbfwurrEvknjEr6m1YlkWc2E+YVnObZ5A\nbVZ0PIL64F74Tf401ZSA5qqv4ycAlDHlNLVx2c4NMzAZEKlSIUNQwaIZnSlNmD3u5gu8J7D1MNlp\nRPRjRPTfE9HfIKK/TkT/ph3/GhH9AhH9Lfv9oR0nIvoPieiXieh/JaK/9629CJLCyOm6jrpdPFs7\nf+Q+P2hzdWCachDt+jM1VVwy99RxCLc+DPG6LQaxx406hkLqfBKi4lpK78078mbzeLbfmCdSRDDk\n7Yt5E9p+e/PY9cXpeS2ucPM2H1FNGFWHKEVduy6e77/jT+UYNbhNirvfr/gub1ovXvcjzhkzo1gt\n0dP5hMUiIPeyTtlq6O8AmAJmc7wZ162W4+uoq73j8di3ZEl+YH1kqRBoomHPFblXku9ae4ykUAD8\nARH5q0T0HoBfIqJfAPAzAP47EfkTRPQHAfxBAP8OgH8CmobtdwL4+wH8aft9vYmAy0kzzlTlgqnZ\nZt0xBmAumr0oO0WtoFRVPNaSvGbyATJyF+BY9fEpT823PFt0INeKlbUgB0HvTSJqY04JGQkiWTeo\nSS4TTQgMysKW9VOy3yVIF6D+43n7U8qAJCR3FTZOwiRWlamgrOdGHCkBqhaaYJoAogxYSjqFFtiC\nlCZILRbkpdl+dZwJSTQJi3MqICPBagmIjmkkajo9W2lJrSy+GT1TkG+yvpg1TRgADQRDUq+/qolI\nABOrSXNGMMTwEzHuZiHJpJlmLJ+xVVZWqanWChLRLEgWnAXS6MzKFaiENCXMKTfVVASYD8G6oMxZ\nVfPJCIDvUvK8mLpO6wKsx4rTccF6r4WGMyVkYVDl/gyLidCQ70nXoAgEGvwkqND8VwKSGdmYT+UE\nShmHmxs8eVJxPC7IdKtzbFIg5YokFVlWUD2bs1cCZVVRyroigZFvD0i575/HtkgT9TcAABzmSURB\nVLdKCiLyHRH5q/b5FbQC1LcA/DSAP2On/RkA/5R9/mkA/4lo+0UAHxDRN97ylIAldFCuwU1NlN2K\nsxEU2/oCSNu0IDRswtPIt3Ty0gEgrwpkjx1yRba/7RhXS6jBAq/O5n11DqzXkT3P1Bl7ke63zu1N\nHBtQz8rIAfvPCKDpItN6j0As9tp/rPPDmG1H39f8pdg+nCdeeWofC2lSgW28DsT2J1VW7IdNeuhq\nADd1wMfIVak45yyuhEC9Cd+oOoyid1RJm0OUdO49SA8bSaWWgvN5xfmsrsvrsuhmNAekpK6jIBak\nquuEDPtJMHqVSP1rrD/qzmXRuTSCo0RJy8DlST0UU9Z0fykDaULKkxHvntgmkUkXgFY2q2yewhV7\nuNi19oUwBSL6bQD+HgB/BcAnIvId++rvAPjEPn8LwP8bLvtVO/YdXGsG5rVcfilE/FF3/3RzWrJN\nzxFsc52MAEIyMMcn1zMVm95rrN1dbB0HoARI3eigiPqr9uBCtCVXc5RSx3iIuOB04sYwVpU8bbOb\nFBDB1stNHeIbdBTAYsbF1i8XO8T6tDPg8JgRbht0OCMQ4r5HfONQI9CuajnOon0XHA5K9FRsdYxI\n3bL3iA6zi9cKRiYjnETjHBCkO1J5kZtAjH3MARO1U+7VvqSbkkXQYgd87MnmhlkL9BARxCSbclpw\nPJ5x/3CP5bxgXWsHCz27VZgqAlrmIwDdeuZ5J8z7MwEo9ryUkgapGSFtqoFd74l0kFSiLJIBmpBK\nAteqEbQG1FIeCxd/kfZookBEz6D5F/8tEXm5AT6E3pYz+/J+re7D+++9Z1yxSwJOFJQD+ku55bo9\nOBAUG2xNJ9QWStucW7DGrw+3ah9sMUjYEdQe5y6mDSYyeWUkAs7/KY1b0hdaf3DAFwBNwsncqLu/\ng+vbg94CWBKTfs6V0YZvaOfcYiIxIxKE0bow3m90pLqUOEacoNYaiu32cF+9z84ilS4V6IbISBau\nHpOPCFjLQaKPsY9Hi6Gwrqp/SQdu22g0iYAB2hetVeKpkCpYzwWn8xnH4xHL0XIiMOB+7UmoZ9EX\n00QGiSp4LJIm01WfM0KBcnUdUmNMJuTmnDFPs6pMsAhcImTJICHIJMgEVCr6t1QjDjreecqWv+PS\n9f9N7VFEgYhmKEH4syLyX9jhT4noGyLyHVMPft2OfxvAj4XLf4sdG5qEug9f//onw/q72LztePzO\nKa8KnPrOCQ3CYffFdymhJ1Ntui9FLmoprtCpvBMEsYc7jYAZlvRRrsf2vguSiY1mTk2daDBzS5kV\nAywVSKzqlmqLYgyAuRhBvViMI3U3jwYGNolBsNnHfSP1rwgxxNqP+rx0ZNy+lTE9WCdaTgD698qd\nXeXpfYtehr0RWuSrnyuAulD3UoJwxYG0702SoHDPPmGtz/67j5EFjNmxlvVY0IoLezn45byAC1uA\nGbXxh01/A2w9C5MwKAuSVf0iUyEgCWBdQ8Ff0+Q3d023MnPz1AKoYH1WYifIwp7bF5iszmTtsS2q\nTswgql8oR+NjrA8E4OcA/E0R+VPhq78I4Pfa598L4L8Mx3+PWSH+AQAvgprxtmfBc/xpE4C6y+le\nUxdk5xLubuuGKrnAIS50RqLGFWotmteONY2V57hT/dVAL0BVE5MGLIWquRRTO58sDTORb7gu3sak\nnL6g/Vg/vtciQi9NqvHjPob9JxDJ7VgjSAlG6PowUdxLG1wAAzHwAjcdvOwtZiWOKfT0nh3juZA6\nGiFLgKibtOI2/q48zmGY14hrNIK1sXS4M5jK4Y5xdOLmBJCrYF0KzsvJzJCaEg9MBhxSS0sPUpaU\n+50BYVBbHYFoB+KaFEjS5EJijulOZJIlcZXu1enZrihlUNaflCbkaULKMyhNEAHWylhKAUvFdDjg\n7unT3XWw1x4jKfyDAP4lAP8bEf0vduwPA/gTAP48Ef0+AP8PtNAsAPwlAP8kgF8G8ADgX35MR4gS\ncurUu6Hu6OLe3uZW0E9NdZMHENm/CPABGLIxuQelT093OhJsaaq7PjdPwaaWjAu9X+C+7aGvcI4G\ndVMmaFp4W1B9Ifd0brF1YgDAE3v4s0mgpfWcAAYw0hKARLCtj28nMi6q96bc3KUsokBQd+agzRft\nHfdjzv3Hee9zMoJ93avQQ7R9vjYEELh4luICMUFP7zPgeILHJ+h6SehSRGU2CUETpiznReuRGBHw\nvLGJlOwm+xukhAFigKkax6A6j7vK67MzaYlHgkoqXAuQDSBms3R5SL/l/SQnOaT5NikBBYKpFYAx\nMLdWnE9nJAIONzPm6eZiTV1rj6n78D9czGRvv3vnfAHw+x/dA2uKrHYRk21Q8rQJo5aElmNfYMh7\n14tFXBDr/gG+SFzvboTCN2OtUADMQhxCi74Dfv/YF3IkzPEDcv0wbjIXgb2vpoA0Mdexg6AbQ1pJ\nsjC6fRGLivstb6MARLmlQ3NpQtpCGlUvGXCK/v0w1uhSSFS7RsKCcP6bI0L3sg+Pf3dhum1sUwca\nUQyYigO3ThS2rflvhLnoxLAT1m7NUQmgihhBOGmZt4cz6lqNzdj4tczT5gRGQAY1l3A/V2NFKkC5\nMQaCYhAsQBZ0wld1UxPQ3JJz1mApIQZSNmzB9ghyCzFPjm0RQFVUqqkF5zNwPh++cj+F34Rm+j7E\nODZhaj7bYyakQdSv6r2VUsaU5rZRctjIIqLgzDRhXVfM84xs9ymlYFkWLGVt0sOovvTFtE3Xvv3s\nnDDR1ETirWPT6lWGRYnYzUHNSY5fRAJQTWYm0jDtlJVrKABJbSHV6sVzfUMmgHqKr8orhHVRIlks\nP7uqNjW9vnlppjGuQ0S5Dnjc+JGjewGTuIndxdbPd4IY8z70MdfziiVxIQqgYXimni/KKJrHn5pv\nt2vE/xbREu+U+7PIRHAR0rXiCL+oBLGsK16+fIXj8YzzWXMrJmgmamFBEvVVkVqQEjClDJLafGCm\nhh0QCq/gQqBpNkkCIC8YbER3kqq+GFyAIkjTDCSgrAVSF9T1hCndYs4HCPR9QCqlTNMNIIzEZyju\nxWC5wbqesK5nsDBevXiJ1y9fPXo3viNEQZtzE7pAhAlEafeadgZRE+kgDMqTio+2ELuJT4nEIN4a\niaU8EgQ//7KPly69ri74hu3XdnXkgpu1PljEo/fL9GDniFtx3KWA4VZgENS1miQB2TaXCKqwBp1z\nAqAb3Dd8CkljPK5g+66eVDcSgi1BdB8T79s1aWL7LlE1dILvJmmf1/iubt3JXppug1P6uTG1/kUz\nKCabNJ+atCdakWmtKIVRiih+IAGwJp83aEi5mJm8zZYDkUCyIDR1fmLAgvVc9UxwK5biDhptTiBh\nTCIQaA5Iomqh2AzLIKzrFSpZgAhkUZaaJ6siJ4LMGWV128Xj2ztBFMJYDyKt243jmVoZiVxRgy/j\nvtDY7Nv2HfWqPY1zsMW7u5MNDLx5C0EAjGPpl/AUZB1TiJum28IFaH833QJWl1I/AU6cxGMR0M67\nIAr2D4OrsZrXGpeMY0TU/OtRAS1KqoCUJmtRn46hUK2MRMBrWjrGcNkux2oAjNHntA+zhPM6IOfH\nGjDX8JAESibFeNGZ3M3P7gLsRKoRhrTNTYEmrRE0fgCswOL/1975hFqXHAX8V93nfbPQgMZIGGLQ\niWSTlQ4hZBGyjCab0V1WZiG4UdCFi5FsslXQhSCCYiCKmE0SzEbwD4Iro1Emk4lhkqgBHcaMIvgn\nM99793SXi6rq7nPuvd97XyYz9zw89Xi8++4993Sd7ur6X9XXDw9cX8+UQ/WDjY0+kpFSf0qNqkN3\nyjpTHVQOwBjHSJvmG2hUawyuRmamfz9FGbWXRKOgVoEpWcnWUsjNJ/vSlDtTVa2WISkTabJneGQg\nawWbYAqx+lo9vKZwLjCiza5uX6YvVfgLjlN0wVJtwTd2tU63Ueif/BQqCU9+LDTHTixV9YM6BhNF\nuz8ALM5ePedAsfLrvtHDmyydOL2JyUKDoWs5i9Cfv48uaz+ayh0bV5ucarao1kg8GnL6g82spPr4\nOqKvnbH5avjYYw7EalkNB4n7LRk/9GcVYaElhHQ24VA742zMRRYDjdpJrHv8Fnq4MpzGtbpZINki\nWIfKq68dvINSsX6dkVSl0fK+BhW2aVB6FmZoC62vknfLsgdRtNRIG3Ot1kRdNuKnilq40s+qyMnO\n+7TuzLO36Ztcq/M0aqV1c7LvZNOaRSFN1NY3826wDaYAgwJFE0Trx1B1MUo4E9snREPQsJMVFmGm\nxVhRXNRGcRdQSEbashOOPHP+BVOSlqnWhKZz+djk4Ujs4+dGHy1ENeJkg3jLNT/JqlpEpD07UexU\nvQ+ftruYCdKPi2+PvGZYGgVeDPiLaxYrpKDfZ/Gguno9/grrJKh2h2FD4y3OV1c0M8zAQoeR8w/a\nzMGuydTWc2LdmFVEmq9jXqFTmX1Nc6tDKTdqNQ3XB+YSSPTEI0ZtwWlRpaIZ64btlxUNA6E2Pqbu\ny4F+rQJZIKuFRM3Ms+5SWixjQZ0x1LlS5xsrp860vAob0qIXFrybgOIHK4FqIqnAiYjWOdgGU3Cp\njKtqkoYwE8cSQN2hYxI9+LRncXlYsrRoQ20e2lEdtoVdHRRCMIPxxxcXbSqYSGoWTCNX6YwEBi/8\nKPmDuEU6l3e1Xmv1/gn1aEN1CQ60Jo1KD3OtpjOkcNy7fd+7JLen9WvakWfJKX6lfWFRmZEVNC1E\nYl36OQUxvmqUj5vJEunFXZU2og2I0LLNMa30e6m5WCZIa6DrbcxDAxjNhNAMarXw3wKSz7VmcrpC\nSN59uTYNDroTcp2F2YUGqB8U3GgizDmN+auIpt7eXkCT1U0gaiFMqSSKmTJltrVIJnxyglkLlAOq\nM1ozRAFUpNa7qRFmcyV74ZULy6MJOA+bYAqhugqYbe9c2aTf2megi8YcnWCWKm/VgpQU67IgLFPb\nutraNJO17b4aT92sGc3TBcEOzU/imezf0CrUkl7AEwNSaJVNw4CulZybrSay2v/ruehJQZIni4gA\n7dCSYSJEjJGOZz5qUcc5ugJZPV/XpIwZ6TCvcSJRtMq3fhKjgzciEb1S0aT5OJdg6WIDs15pL/N8\nAzCUrZuUjO+P8xAmxChcQoMwGqu2od0kC6YmkpvRlQcmGp2om6/QxzTNMMwcv5ZoU+80EOno4SMY\nEmIjE94S54zBhptFcuZqytzcFEotpDKjaaKxpenKnkeNJCQ5U3UBGzbKuSS2U7AJpgDulxGT9ikS\nWqqZCeE8Gn97dz+zk5XKJIO93gjDWPhi8/oGt7JcbI3UdIJ1yGy07wHkxG4NkwL1833DBFnpx30j\nWIh0tKmD9qPTkkXNYmMGFfazFIKwexJThzEfIYnYEfT+oGFbhjQrRZofJe7b8ydsnkqZ0Tq3z5oz\nU6SpxNfX1xwOvUtQSmWhysf7vXy5j+kU4Gds5DYnp56r1UE07tbnKMLQY3r1ek5i3qzAKDsd1OF4\nAM+g9JJ0u36pUYJnIhLMzcdwbao6DaDazTKUKhVNwWhcY1RrUxebWLS0FH1rgqNMkry+Lapye7Qq\nuGZK2TXHNR10oXpX2AZTaGq5dM9yc8UsNYBjD3xstC5lq3t5o1++qpyowfEU6LYx+6Zdj7XGYx0P\njwy0xeOsNZPhGUDIyePeWrsU82FC5c7TGHMPSSdHBLqETvxtzIERlFKd+eCJNXPrbRDfWTAFYD5c\nU8sNi/b7gbOqH3BSmw8n7jEmjq1V++PVOGbA43zH3+jVMLVQqqnpMW4pPQ17ZBC1+TJsHrKAqDRh\nUAteO4A7Yz0xSrKnQh+8KiGQWpsTSxIzzdc1RtcYus4x5pMkkIzUmdYxQitCMS4j1ZKVxHCstSLV\n/Edj5msakIj9kJKtzUjXd4FtMAURqgplLkx5Il1lkEQZkn2myRqkzPNsW1QS1Q9pISXrBA1+vZcg\nM7s9LF5Ge8X1w1fttWTmcm3OvdlOCL66ykS78GYuFG3ag9mYUXblkrr2VGwYCRLfBOJ2ZjUiSDqo\n/j03P3mhTCRJ9TRsLzCq2AEjLoXqwZqXxJHj1Q+MmSbLXrs+4OcPzFAPdj7B6JDLkxX/DAxN1Iiw\nRQPUVNu53lBqQbBuUGN2Z3stUdXpj6ZQBy2m1EKp9jw9QpOIRrtWKm3pvwGqSsZ6CTSGUc1cUJ2b\nve/brqnQySVnss4tUCvJNbPGtG7cVNArSs3MM8xVzXyRYn65arUOQiLrEwgKWkj1gOjkzXCVzERm\nQqiQMyVPzPU1qDfkCbKYh1kqmKM3+yndhSLFWIEImq8sCqFK8oxeLTMihTxV8nyDXs+gD5jSxFXN\nPFBru3alFheRJGgWkEQlc6Ay17H25HbYBlNYQdiWa1UeQv3D89pp9mTKy9BgnOo06vshtWLTR+Zd\n9FQoRZiuulRKAsXdzQJN5C8TY0aNoUu6fg5gDzsutY9+vTXrWEYrircPV7X4dc6ZaKAjCge7ebu2\nqPkGSlFytuPiTCtQslQOh5lD6b0MrHTa6v3XIdzlWuhCcJ+OKshqbs/Aoz5bweNItkfdI6IZS1OF\nhU/AtJ04QuDuXY+7IHC/UxIg0w5G9lBqq6lMkVfiKdZVkBRu8hP394lPIahiX8zFMuezUqSScuZK\nJn+eTpM6LNwj12UFm2EKzSbMy9OYQ21ehvcwgrYPu6TWTqDt+9CcfaOjyTyZLE7kVdRCPjihiOUv\njD4aERbhr1E160zG1MAmRVk5EUU8gmKaz1xuoNSWvt3Cbdi9TjEF04BSS5MezZ+2n3xHjPH6pVlR\nqZK6Wqw6bBZlwVN9HdZ7ZhkZePRGlibT+/Xt9hIWl7Y5C0fL0X1FThL5qfe6OTKMC+54k6N5s1tk\nR+bYlDkxABbhKnZiGYMZ7M0Rjmgunt2sCuy0UNv8VdTP3XHh4fOeHNGCZTxKwX0WZt5M03A6teMR\nFvg6K/Q22ARTUNXWyy8msTLmFyybkMZ1ffJPOFOih0G7vn80+gRq8yhLs+fjXtXtVfVGqMacCofD\n3A7oCKICmnlj3neaBNYmrQZbtxS0Fg6HA3O5QVo/hdLMpUfVsDT79MRiNydkUivDc0KstS4Ouz31\n3ZPE4/b3en8cSd8VDqurT17X59sGipZzC+a0QGX5mZxhEOM3TtvUXpYdpdmqJrklc6dz1oZmGKOW\nFLRkNSVmHi246+CeWmhhLe8kbt2jPMt8hGJFW2HKYMLFqsqTZXhWWmVfnD+xzg1+FGyCKQA2by3V\nuDOBNYgMG53l5pjnuTOIYfaDmdzciIXNEEhYMdTNDaCtIKhGk1OwrrhFvKe/LphAZwruyMQ0iCjq\nefDgCkvQ0Z7PEKnVQx+95ohzIR0e9JxT82906dOfOfINmvYkefGszVWbon5uNYdux98uCO9ui962\nObllvHEsWRdiQFOzkxwzpIUGtPhscHIsbujNWc1N4f4pGa45h2h/PyXc+We+kFg7yx3IpFTMr7Og\n47S4h+JJezXGdu3ECiEwSg6GYfdSz8SNnh4ZpcxiVZTuWGn5CUmW6dl3gE0wBRG8E23y9GEW5kKE\noiJ0p167MB5OorUyXx9a1584YGOUJofDgYcPHxJTZH37HzaToKJMZeWDKL12HkJlz9QqA179+lM+\nAx1ej34AxjZZLt2Tq50issrafNT8yZG93oKcJzaOqsf21xrWOfNBx3sew2iuncTtMa5f4L/exwN+\nZ793widypG0Ipr7V5IlbCXUfgKws/GCuhor2RijQ7bjBBOnCzM0HiUiPPZUxtTiWL/o+jKO5Rgl2\nYLIRjzs5LXSqEnUS5oyuFYoekElhzn6tQs79+29U49Y3ClSVw/yQxGSZczN2Nt98aNw3JrpqxGlZ\nHkhbK/P1TSe08PwPDr885UHFVw7zYXAyWm+7OhBqK/VVqGpc+Fh76TZr4Brvj8whcIj/Z1XSkIb9\nOJy8j7vM/1+o0oJHR6Lwp0P19GlNnejHtTgNA3dYXX9nE+Ix7Nq4tw7zyJmx1mbk2pxchzpt43l+\niwqWy+JdqtRL04HoG3mCO63G7iaQG77Ob3v0KdZAxOpmLDeEptUZ+NlRbj74CF1LrPEda7tG8lC8\nWolUEXH/hHobOMNftDaH/F1gE0yhlMq3//dVpilTvEfhaw9vmOfD6iALMx3McWdMoR3E6TZ6SFmt\n3nIrEpcE89qGz6KWpW2HuhnWF9+0jihfSS7FQ43XVkOh2puz9NyIgShPbKbRVNDq51xgocXoYt0E\n0kDsXYLagkcT2B7ntwScpiEMdms4bM05aXUQ4h4pDbtopSnUcHal21T/u0Uf1o7JI8/DYzKOfutz\nGsmgHQ2XNIXcW+Hb93t/ROAIt6Mx3b+xYEIm0GHQ+qpGJC258zo0Av9OVETbgwBhZJhxkaT1I7P1\nVTGtYRa0JsgzNT2wXpBJ0Wqaj50MNnYyuxtsgimADoeGhNJcjKtKz7KLfdI57BIWEsOJfVza8OQb\nsVteuCxvcFryuROoMRxV1CVKaBOq0ZY+NkivszgyA0S8JLbj7dNgREVFaxqed6lxtGvPSO52nag3\nM/YuVNp9J4oX0CBHBHOagI61n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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c19727f28>"
+       "<matplotlib.figure.Figure at 0x7fc0e8079908>"
       ]
      },
      "metadata": {},
@@ -992,11 +1021,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "31.03% : mosquito_net\n",
-      " 8.75% : shower_curtain\n",
-      " 4.29% : ladle\n",
-      " 2.84% : lab_coat\n",
-      " 2.69% : window_shade\n"
+      "50.31% : shower_curtain\n",
+      "17.08% : handkerchief\n",
+      "12.75% : mosquito_net\n",
+      " 2.87% : window_shade\n",
+      " 1.32% : toilet_tissue\n"
      ]
     }
    ],
@@ -1013,14 +1042,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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WZVspGeDq6jX+r7/7Q7x4eQPfd1HX+3fNe4qiCKenpxgOh+Ilm6ZBv99Hv9+H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hhKKYRBAF3XSBrTnu+bk3axWMB3XXS7PTjKQ3raISeeU1ZQcFDXQHrKUJU1sixHlubwfB8XF5dC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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c180b4c18>"
+       "<matplotlib.figure.Figure at 0x7fc1178eccf8>"
       ]
      },
      "metadata": {},
@@ -1030,11 +1059,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " 9.71% : quill\n",
-      " 7.01% : ladle\n",
-      " 6.18% : screwdriver\n",
-      " 4.81% : broom\n",
-      " 4.26% : nail\n"
+      "45.08% : shower_curtain\n",
+      "21.84% : mosquito_net\n",
+      "11.55% : handkerchief\n",
+      " 2.02% : window_shade\n",
+      " 0.91% : Windsor_tie\n"
      ]
     }
    ],
@@ -1051,14 +1080,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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YcUvPHl+0zVtCtIbAsdfNXICwBFmaMr58wcuXjymcOZHjY2RNVi2YLyfUpqDT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HAAAg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7lru7Ozbbf4kGs3+L78N/AfwHwH3/Zf+5MeZ/6//vPwP+faAD/hNjzP/+dz6KRzfo47ehhw1/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\nY5mfn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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c1825add8>"
+       "<matplotlib.figure.Figure at 0x7fc0f001ed68>"
       ]
      },
      "metadata": {},
@@ -1068,11 +1097,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "26.50% : orangutan\n",
-      " 9.93% : spider_monkey\n",
-      " 4.35% : siamang\n",
-      " 3.27% : howler_monkey\n",
-      " 2.88% : capuchin\n"
+      "26.75% : spoonbill\n",
+      " 7.06% : black_stork\n",
+      " 7.04% : wooden_spoon\n",
+      " 4.21% : limpkin\n",
+      " 3.72% : paddle\n"
      ]
     }
    ],
@@ -1095,7 +1124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "scrolled": true
    },
@@ -1173,7 +1202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1191,7 +1220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -1200,7 +1229,7 @@
        "<tf.Tensor 'block5_pool/MaxPool:0' shape=(?, 7, 7, 512) dtype=float32>"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1218,7 +1247,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1235,7 +1264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {
     "scrolled": true
    },
@@ -1273,7 +1302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1289,7 +1318,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1305,7 +1334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1321,7 +1350,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1339,7 +1368,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "scrolled": true
    },
@@ -1383,7 +1412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1392,7 +1421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1402,7 +1431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
@@ -1444,7 +1473,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1462,7 +1491,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1479,7 +1508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {
     "scrolled": true
    },
@@ -1489,45 +1518,45 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/20\n",
-      "100/100 [==============================] - 20s - loss: 1.0910 - categorical_accuracy: 0.4575 - val_loss: 0.8024 - val_categorical_accuracy: 0.7472\n",
+      "100/100 [==============================] - 27s 265ms/step - loss: 1.1149 - categorical_accuracy: 0.4407 - val_loss: 0.8443 - val_categorical_accuracy: 0.6642\n",
       "Epoch 2/20\n",
-      "100/100 [==============================] - 22s - loss: 0.9378 - categorical_accuracy: 0.5600 - val_loss: 0.7077 - val_categorical_accuracy: 0.7566\n",
+      "100/100 [==============================] - 22s 219ms/step - loss: 0.9529 - categorical_accuracy: 0.5500 - val_loss: 0.7798 - val_categorical_accuracy: 0.6377\n",
       "Epoch 3/20\n",
-      "100/100 [==============================] - 19s - loss: 0.8551 - categorical_accuracy: 0.6130 - val_loss: 0.6477 - val_categorical_accuracy: 0.7717\n",
+      "100/100 [==============================] - 24s 238ms/step - loss: 0.8422 - categorical_accuracy: 0.6164 - val_loss: 0.6778 - val_categorical_accuracy: 0.7566\n",
       "Epoch 4/20\n",
-      "100/100 [==============================] - 19s - loss: 0.7747 - categorical_accuracy: 0.6410 - val_loss: 0.7183 - val_categorical_accuracy: 0.6547\n",
+      "100/100 [==============================] - 22s 218ms/step - loss: 0.7591 - categorical_accuracy: 0.6635 - val_loss: 0.6562 - val_categorical_accuracy: 0.7396\n",
       "Epoch 5/20\n",
-      "100/100 [==============================] - 19s - loss: 0.7438 - categorical_accuracy: 0.6645 - val_loss: 0.5706 - val_categorical_accuracy: 0.8113\n",
+      "100/100 [==============================] - 23s 226ms/step - loss: 0.7246 - categorical_accuracy: 0.6816 - val_loss: 0.5812 - val_categorical_accuracy: 0.7943\n",
       "Epoch 6/20\n",
-      "100/100 [==============================] - 19s - loss: 0.6836 - categorical_accuracy: 0.7040 - val_loss: 0.5912 - val_categorical_accuracy: 0.7962\n",
+      "100/100 [==============================] - 23s 226ms/step - loss: 0.6968 - categorical_accuracy: 0.6960 - val_loss: 0.5351 - val_categorical_accuracy: 0.8264\n",
       "Epoch 7/20\n",
-      "100/100 [==============================] - 19s - loss: 0.6527 - categorical_accuracy: 0.7130 - val_loss: 0.5509 - val_categorical_accuracy: 0.8094\n",
+      "100/100 [==============================] - 22s 220ms/step - loss: 0.6622 - categorical_accuracy: 0.7205 - val_loss: 0.5208 - val_categorical_accuracy: 0.8340\n",
       "Epoch 8/20\n",
-      "100/100 [==============================] - 19s - loss: 0.6310 - categorical_accuracy: 0.7275 - val_loss: 0.6414 - val_categorical_accuracy: 0.7038\n",
+      "100/100 [==============================] - 22s 218ms/step - loss: 0.6430 - categorical_accuracy: 0.7307 - val_loss: 0.5173 - val_categorical_accuracy: 0.8321\n",
       "Epoch 9/20\n",
-      "100/100 [==============================] - 19s - loss: 0.6072 - categorical_accuracy: 0.7455 - val_loss: 0.6630 - val_categorical_accuracy: 0.6887\n",
+      "100/100 [==============================] - 23s 232ms/step - loss: 0.6026 - categorical_accuracy: 0.7515 - val_loss: 0.5157 - val_categorical_accuracy: 0.8170\n",
       "Epoch 10/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5986 - categorical_accuracy: 0.7525 - val_loss: 0.6142 - val_categorical_accuracy: 0.7340\n",
+      "100/100 [==============================] - 22s 221ms/step - loss: 0.5615 - categorical_accuracy: 0.7782 - val_loss: 0.5412 - val_categorical_accuracy: 0.7792\n",
       "Epoch 11/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5831 - categorical_accuracy: 0.7525 - val_loss: 0.5202 - val_categorical_accuracy: 0.8057\n",
+      "100/100 [==============================] - 22s 220ms/step - loss: 0.5924 - categorical_accuracy: 0.7460 - val_loss: 0.4885 - val_categorical_accuracy: 0.8113\n",
       "Epoch 12/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5747 - categorical_accuracy: 0.7480 - val_loss: 0.5289 - val_categorical_accuracy: 0.7943\n",
+      "100/100 [==============================] - 22s 223ms/step - loss: 0.5770 - categorical_accuracy: 0.7555 - val_loss: 0.4831 - val_categorical_accuracy: 0.8094\n",
       "Epoch 13/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5735 - categorical_accuracy: 0.7570 - val_loss: 0.6357 - val_categorical_accuracy: 0.6981\n",
+      "100/100 [==============================] - 24s 236ms/step - loss: 0.5387 - categorical_accuracy: 0.7822 - val_loss: 0.5934 - val_categorical_accuracy: 0.7377\n",
       "Epoch 14/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5377 - categorical_accuracy: 0.7760 - val_loss: 0.5130 - val_categorical_accuracy: 0.8113\n",
+      "100/100 [==============================] - 23s 234ms/step - loss: 0.5414 - categorical_accuracy: 0.7745 - val_loss: 0.5325 - val_categorical_accuracy: 0.7660\n",
       "Epoch 15/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5507 - categorical_accuracy: 0.7740 - val_loss: 0.6038 - val_categorical_accuracy: 0.7340\n",
+      "100/100 [==============================] - 22s 223ms/step - loss: 0.5296 - categorical_accuracy: 0.7785 - val_loss: 0.4925 - val_categorical_accuracy: 0.7887\n",
       "Epoch 16/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5228 - categorical_accuracy: 0.7865 - val_loss: 0.5141 - val_categorical_accuracy: 0.7943\n",
+      "100/100 [==============================] - 23s 226ms/step - loss: 0.5278 - categorical_accuracy: 0.7810 - val_loss: 0.5659 - val_categorical_accuracy: 0.7415\n",
       "Epoch 17/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5058 - categorical_accuracy: 0.7855 - val_loss: 0.5561 - val_categorical_accuracy: 0.7698\n",
+      "100/100 [==============================] - 23s 228ms/step - loss: 0.4814 - categorical_accuracy: 0.8142 - val_loss: 0.6115 - val_categorical_accuracy: 0.7226\n",
       "Epoch 18/20\n",
-      "100/100 [==============================] - 19s - loss: 0.4775 - categorical_accuracy: 0.8080 - val_loss: 0.4904 - val_categorical_accuracy: 0.8057\n",
+      "100/100 [==============================] - 23s 228ms/step - loss: 0.4861 - categorical_accuracy: 0.8150 - val_loss: 0.4783 - val_categorical_accuracy: 0.8038\n",
       "Epoch 19/20\n",
-      "100/100 [==============================] - 19s - loss: 0.5360 - categorical_accuracy: 0.7755 - val_loss: 0.6344 - val_categorical_accuracy: 0.7189\n",
+      "100/100 [==============================] - 23s 226ms/step - loss: 0.4632 - categorical_accuracy: 0.8187 - val_loss: 0.5041 - val_categorical_accuracy: 0.7868\n",
       "Epoch 20/20\n",
-      "100/100 [==============================] - 19s - loss: 0.4882 - categorical_accuracy: 0.8100 - val_loss: 0.7323 - val_categorical_accuracy: 0.6660\n"
+      "100/100 [==============================] - 22s 224ms/step - loss: 0.4987 - categorical_accuracy: 0.7935 - val_loss: 0.5093 - val_categorical_accuracy: 0.7868\n"
      ]
     }
    ],
@@ -1549,16 +1578,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
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ESflbFOeee+6haJwlS5awceNGTjrpJFatWsVJJ53E/fffT/fu3VmwYAEbNmygZs2a9O7d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\nbuGcweCefMK8QcZb/ETBywHV9sAKVV2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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c13e05978>"
+       "<matplotlib.figure.Figure at 0x7fc1179fd080>"
       ]
      },
      "metadata": {},
@@ -1578,7 +1607,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {
     "scrolled": true
    },
@@ -1589,7 +1618,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {
     "scrolled": true
    },
@@ -1598,7 +1627,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test-set classification accuracy: 66.60%\n"
+      "Test-set classification accuracy: 78.68%\n"
      ]
     }
    ],
@@ -1617,14 +1646,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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CGEZ88Rces1wtMVsWRVQhFRESNVuDPuPTEXJriOs56K5NmiaEdYHuKWiliSQqRCWjdmxs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IJNvF7x8vSMd955h9FgwCoKkf++DjtREvE8rwnJTVNEqQntyLLGYDMvcnq9PoIA682a5yfPifOk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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c18175550>"
+       "<matplotlib.figure.Figure at 0x7fc1179c8860>"
       ]
      },
      "metadata": {},
@@ -1635,9 +1664,9 @@
      "output_type": "stream",
      "text": [
       "Confusion matrix:\n",
-      "[[151   0   0]\n",
-      " [102  32   3]\n",
-      " [ 71   1 170]]\n",
+      "[[140   5   6]\n",
+      " [ 47  86   4]\n",
+      " [ 36  15 191]]\n",
       "(0) forky\n",
       "(1) knifey\n",
       "(2) spoony\n"
@@ -1663,7 +1692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1679,7 +1708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1700,7 +1729,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
@@ -1742,7 +1771,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1758,7 +1787,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1774,7 +1803,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "scrolled": true
    },
@@ -1784,45 +1813,45 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/20\n",
-      "100/100 [==============================] - 28s - loss: 0.4756 - categorical_accuracy: 0.8065 - val_loss: 0.5877 - val_categorical_accuracy: 0.7340\n",
+      "100/100 [==============================] - 27s 273ms/step - loss: 0.4715 - categorical_accuracy: 0.8105 - val_loss: 0.5107 - val_categorical_accuracy: 0.7717\n",
       "Epoch 2/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4781 - categorical_accuracy: 0.8035 - val_loss: 0.5577 - val_categorical_accuracy: 0.7717\n",
+      "100/100 [==============================] - 24s 241ms/step - loss: 0.4656 - categorical_accuracy: 0.8067 - val_loss: 0.5141 - val_categorical_accuracy: 0.7717\n",
       "Epoch 3/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4530 - categorical_accuracy: 0.8150 - val_loss: 0.5464 - val_categorical_accuracy: 0.7774\n",
+      "100/100 [==============================] - 25s 252ms/step - loss: 0.4359 - categorical_accuracy: 0.8210 - val_loss: 0.5059 - val_categorical_accuracy: 0.7717\n",
       "Epoch 4/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4440 - categorical_accuracy: 0.8275 - val_loss: 0.5442 - val_categorical_accuracy: 0.7811\n",
+      "100/100 [==============================] - 24s 237ms/step - loss: 0.4324 - categorical_accuracy: 0.8355 - val_loss: 0.5057 - val_categorical_accuracy: 0.7736\n",
       "Epoch 5/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4463 - categorical_accuracy: 0.8345 - val_loss: 0.5536 - val_categorical_accuracy: 0.7811\n",
+      "100/100 [==============================] - 25s 248ms/step - loss: 0.4243 - categorical_accuracy: 0.8340 - val_loss: 0.4981 - val_categorical_accuracy: 0.7792\n",
       "Epoch 6/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4446 - categorical_accuracy: 0.8290 - val_loss: 0.5497 - val_categorical_accuracy: 0.7849\n",
+      "100/100 [==============================] - 24s 241ms/step - loss: 0.4224 - categorical_accuracy: 0.8395 - val_loss: 0.5045 - val_categorical_accuracy: 0.7849\n",
       "Epoch 7/20\n",
-      "100/100 [==============================] - 26s - loss: 0.4474 - categorical_accuracy: 0.8150 - val_loss: 0.5345 - val_categorical_accuracy: 0.7868\n",
+      "100/100 [==============================] - 25s 251ms/step - loss: 0.4374 - categorical_accuracy: 0.8310 - val_loss: 0.4943 - val_categorical_accuracy: 0.7849\n",
       "Epoch 8/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4330 - categorical_accuracy: 0.8305 - val_loss: 0.5437 - val_categorical_accuracy: 0.7811\n",
+      "100/100 [==============================] - 24s 238ms/step - loss: 0.4261 - categorical_accuracy: 0.8305 - val_loss: 0.4832 - val_categorical_accuracy: 0.7925\n",
       "Epoch 9/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4136 - categorical_accuracy: 0.8345 - val_loss: 0.5489 - val_categorical_accuracy: 0.7792\n",
+      "100/100 [==============================] - 25s 248ms/step - loss: 0.4408 - categorical_accuracy: 0.8215 - val_loss: 0.4927 - val_categorical_accuracy: 0.7925\n",
       "Epoch 10/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4262 - categorical_accuracy: 0.8330 - val_loss: 0.5403 - val_categorical_accuracy: 0.7849\n",
+      "100/100 [==============================] - 24s 243ms/step - loss: 0.3978 - categorical_accuracy: 0.8475 - val_loss: 0.4873 - val_categorical_accuracy: 0.7906\n",
       "Epoch 11/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4228 - categorical_accuracy: 0.8320 - val_loss: 0.5425 - val_categorical_accuracy: 0.7811\n",
+      "100/100 [==============================] - 25s 248ms/step - loss: 0.3889 - categorical_accuracy: 0.8615 - val_loss: 0.4834 - val_categorical_accuracy: 0.7925\n",
       "Epoch 12/20\n",
-      "100/100 [==============================] - 26s - loss: 0.4026 - categorical_accuracy: 0.8365 - val_loss: 0.5432 - val_categorical_accuracy: 0.7792\n",
+      "100/100 [==============================] - 25s 246ms/step - loss: 0.4017 - categorical_accuracy: 0.8442 - val_loss: 0.4758 - val_categorical_accuracy: 0.7981\n",
       "Epoch 13/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4248 - categorical_accuracy: 0.8280 - val_loss: 0.5269 - val_categorical_accuracy: 0.7943\n",
+      "100/100 [==============================] - 25s 249ms/step - loss: 0.3988 - categorical_accuracy: 0.8450 - val_loss: 0.4816 - val_categorical_accuracy: 0.7943\n",
       "Epoch 14/20\n",
-      "100/100 [==============================] - 26s - loss: 0.4297 - categorical_accuracy: 0.8305 - val_loss: 0.5288 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 23s 232ms/step - loss: 0.4129 - categorical_accuracy: 0.8340 - val_loss: 0.4706 - val_categorical_accuracy: 0.8019\n",
       "Epoch 15/20\n",
-      "100/100 [==============================] - 26s - loss: 0.3989 - categorical_accuracy: 0.8415 - val_loss: 0.5270 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 24s 238ms/step - loss: 0.3944 - categorical_accuracy: 0.8375 - val_loss: 0.4621 - val_categorical_accuracy: 0.8038\n",
       "Epoch 16/20\n",
-      "100/100 [==============================] - 26s - loss: 0.3801 - categorical_accuracy: 0.8430 - val_loss: 0.5251 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 24s 238ms/step - loss: 0.4034 - categorical_accuracy: 0.8365 - val_loss: 0.4675 - val_categorical_accuracy: 0.8000\n",
       "Epoch 17/20\n",
-      "100/100 [==============================] - 27s - loss: 0.4224 - categorical_accuracy: 0.8315 - val_loss: 0.5336 - val_categorical_accuracy: 0.7830\n",
+      "100/100 [==============================] - 23s 230ms/step - loss: 0.3984 - categorical_accuracy: 0.8337 - val_loss: 0.4655 - val_categorical_accuracy: 0.8038\n",
       "Epoch 18/20\n",
-      "100/100 [==============================] - 26s - loss: 0.4073 - categorical_accuracy: 0.8340 - val_loss: 0.5246 - val_categorical_accuracy: 0.7906\n",
+      "100/100 [==============================] - 23s 225ms/step - loss: 0.3851 - categorical_accuracy: 0.8375 - val_loss: 0.4719 - val_categorical_accuracy: 0.8019\n",
       "Epoch 19/20\n",
-      "100/100 [==============================] - 27s - loss: 0.3952 - categorical_accuracy: 0.8480 - val_loss: 0.5292 - val_categorical_accuracy: 0.7830\n",
+      "100/100 [==============================] - 23s 230ms/step - loss: 0.4070 - categorical_accuracy: 0.8397 - val_loss: 0.4731 - val_categorical_accuracy: 0.8038\n",
       "Epoch 20/20\n",
-      "100/100 [==============================] - 26s - loss: 0.3984 - categorical_accuracy: 0.8425 - val_loss: 0.5220 - val_categorical_accuracy: 0.7925\n"
+      "100/100 [==============================] - 23s 227ms/step - loss: 0.3797 - categorical_accuracy: 0.8477 - val_loss: 0.4569 - val_categorical_accuracy: 0.8132\n"
      ]
     }
    ],
@@ -1844,14 +1873,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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gao9jx9r8eEv2IX8r2717N2PGjKFfv37k5eXx9ttvAzaMwYknnkhubi79+/dn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\nUPkqa7CzNx/6OrV4nbtLKkF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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c10259710>"
+       "<matplotlib.figure.Figure at 0x7fc0e80bcf60>"
       ]
      },
      "metadata": {},
@@ -1864,7 +1893,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1873,14 +1902,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test-set classification accuracy: 79.25%\n"
+      "Test-set classification accuracy: 81.32%\n"
      ]
     }
    ],
@@ -1899,16 +1928,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 67,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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ijI3SHaN6JntbCW/90Q8QlBG9Yo6iS2zcf4x74OPkBQgFZE1GcHKO+vuEcYDt\nqDRKVb7xR3+JP5LINZMnFZ1hOuHJ5hGL8xfYG+9iNWymatNI3SGGoKHVVpFVBd10ftFy/tLxN4Eh\nPzzJxd1af0K726ZSrhBGEZEbIgvgeR5CbpGmKbVaA0mS+au/+gZhPMa0U1793Oe4/uFHbD55xNJK\nQjDqc7y2w9s37lGbL/LKF19HcyxwDFZWrrEwM00u+Lj+MQuv1DjY9qib87SLm4gl0CSVoTcgSmMs\n3aR1+RJpmBB6W2AaeHHGzbu3Wd/fYlkto1YqJ/nIp+DUBpimCVmeYpo6o1EfSRCIswx/MkFTFHTV\nIIxDZEEm9EJMxUBNZOJcRQQuLsyjSTIHB7u05urUX1rhqJay8e2PkQUFKxM4Hj3FUZssX16l2igQ\nBHB8PCROYpJkwPqjbdwsQqkLqFWTRnWB3wx/gzgdUqwoPLyziZBq1FrTmIbB6uULJI7Axu467e4W\nU606w3abLD+LAn8agiBQKDqMRyPGkzFBP2Z6bubkuGMyIclj0ihl2BsiCxL1So3dwyekocrY88g0\nA7toc7R1xPHBAWIeE+/5CPsps4UZpGIJ0akw6B1jFVTml5fYuLtJGAas339IVoDL114kDkKGR4e0\nO0NMo0rZdkhE2Hn0lPpikcdrXbpbj6iXWviHAuVCFSlMMIs6amMaRXVAPJvkfpY8z4nDiCSK6Xe6\nKIJKtVAnjzP8UUAeQJ7l2LZGnggYhkBrqcZkMEaIbbZ3B3QPRvzbf/1vQZERVB2tqLK1scPjR0+J\nvQxLNSg5JeLIxYsDNNMkzjkJcgoie4873PlggxcuOhgNnepSlcuff4Gbf3YLT9eQDRtEFdFSkeOQ\nZNjm441HFFWbuUqLVqHB5s4xw657Kg1OHwWWRBxHZzTuEYYhpmkiZhlimpIkCSECOQKplyKKIo5s\nko9jpMxAUmSKep39QRe/aKLWygQLCt7RJvdv3MGmgFmV8SsD3KHPdz74a5xii6Rr0O1EmJbN2tod\nOgFUZpbIyyKSqhAQ01xtkAoWpbLKXu+ArfUnmJZBsbXM2v5NrJLOxx/f5urVq+TImHYZUTxLkfg0\n8jwDIQUxJYg8KtNNojhGkk8a1QpRTjyJyJXsZJUoJJTNBkFkEAVjHMPBVIp4vSGTdo9Jp4eBxNXp\nJXRDZ390RHyUEVo9/KyHPdeg5pYoNxwSP2cyivn8K1doj58ymWyThRLPfenzaLrGe9//IckoIRvI\nKIpGeORCcpoBAAAgAElEQVQz6nTohH2kPZmrooFW0pGyHhW9inhWCPL3yUEVZPr9Pqogo+gqtmow\nHo0R4ow8kknilFEwoF5v0G3vMXS3qGgW8tBFbbtIOwHnynXaYo6gVznqDBiHIXq5QL/vcdybIIgK\nQiahywZjbUwmxxQq06zdu8fD769h6Rofxx9QP1flw/W7fPnlRWYvvIoYWiDokEpE4zZh94COA2vH\nR6ieQEUuIBfLVAcqqnK6RczPEQSBJEmJ4wRFOSk2z/OcIAwRBAE/GqGZJggwHA4RlAwlFlE1FU2W\n6EyGBMMxmRQQzIjcfus9bt+6TdKH3Iox5ZwgiJmqlll78D4769t84co/wzHqdDsReztDFpebqCUf\nX5SZbPSQrJDtvW36g31SJoTehGefm2c4GlGqpry49Dw339tgcuCRzUFlukZeFRGkswPyTyPPYTKZ\nkKYZuqZj6DqKrnF4eEgURcRRSKlcQlVVPM8jikKiJKZgmZQ0A2/o4oUD6oUShVxCrjSYhC6tl2fx\nRh7KQ4P2YECrbGIaFqO+B/nJ1mx+aYkPbt8iiQ8wgyFOkDIQuxTqdRrFWYxykSzJaS20cLMh6ThD\njmAyHlKqViiXLxCNPOIwQDcMzprB/H2yLCNNUwRBQNd1oiwmCRNkRUY3DLIMkFIM00TTVcKJSedg\nwk5nn7A/oiYrPKdXsZ0quRYSRxHD4Zg8z5ifn4UgR1JT9vf32Tw+4PNf/RKLjSZpFLOzsw2Ch1JR\nqdVmOGofUC6q5GEBedzg2pVL3Pv+O6wd7qBNN9n96AOaWcLHowFHmYcrZcRJxmgwQHIUwiw4lQan\nPwPMQdd1wjA8aZaZ50RRhG7oTMZjRFmD/JOW+JLEaDRiutjAsm2iKKI9GcDYxUsGHGcV7v7kFrsP\nRyyXzzM1X2P2aoOP7u4woY8uJaw/2uDCXB1JWWH/IOD5Fy5TnXLww4SbHw+4uXaLsDyitFihXCnj\n+Qkl26HX9QnCBEV2MKQi56orfBhep7c1IKrFDI480vDMAD8NURQYDoekSYpTcEjShNBNCIKAnJMU\nCkmSPhlEkMQxsnySx6cIEmkcszq3xFxjiqMn28i5QvnyLNIzKd//5tscHQ5wrpbp9/vIkoTrnlQS\n2ZaNJMuUy2Uera+RPOmz9u4axVenmbpqUSjX+fJv/QZeZ0StobNzsMbWgz00TWZxYYrW7AwXn/sq\no7X7HGzeZPncq79oKX8pObmKQKDZbBIEAVEWE8cxiqIQBAFVx4EkxQ8Cur0elmZT023SgkiGiWJI\nlC/MYaUC6t4T/O4QY14jFhOyNCPPcqqVMo7jEO0+xTBNqjWJ3e0nqGZCfcrk6n/2Ozy8vcNgGNLf\nivjiF3+bi403EIcG00uXub53jzvfO2JlGJCVDNb0Lj0NnNkm2cExxwcHOHMNMiE8lQanNsAsSxmP\nx2iahq7rjMcTAj8kzzMKTpEozZAEEd/1CAIfORERZImJ5zGZTNBNk7oqUSsXaY/buO6EpblVNGxS\nWQFRR1NNwjigUiyxerXFk4N3OejcI8/KbB7f4jLPc+3Sb1B7eo7Z0hJdfQPbMnjm6hWGkx433r+N\n1xHZfHJEpXie5y42mT9X4tVXX8Mf+rzzzfeIXAH3lOcHvwoYho5uGCRJTKfdBlFEVRQ8zyNPUyI/\noFQq4UUuMhJZnKEoGpPhGFPXyeOQ3lGX0cRlenYWo2by8eMP2NnfYzzMkH0LXTsJsiwuzNFT28iy\nwKjX48qlS7SP9rn13gbz9YtcuvYSyAWSMELVJQJDRNRlgiRk5A9I8Fmo15hvnmfhfIkRC/zff/XH\nVEs3IT1rePGpZDlRGKEpKv44QFVVwiCk6BQhziAVyWNotaZZaDYZHBwS2DJqw2L+9asM6zrHP75P\nnmSoo4TxIKJcqLB3eECcR4iKiGEaNBsNnjx8xNSL55mMXCRUHFugsVBnMEh5dGOHr7z6Fb547eu4\nvoKqWSxcuIpYE/nu9/8SUy5iFm2UxRa/vvI6Rcng6Z2HfPDjdwnkhIP9vVP9+z93geTfXF4iZCKK\npOF5HrKko8sicRxTMhzEOKNUrWNVqmxtb1OqVLBVGVHy6ScjhoddCueKvHbtGvfXnmA4Do9+eohW\nNlAMma3+Ls1Gk86DkFrdYu6qyv7uGutpG8VVOMxylHKNuhZR0E3qhXMkQoVK3aduxkRxxqMHT9h/\n9RC5kTL7/Dzuw5D9tT6KH5MlZ0GQTyMnBzknzkIQIQlDSqUSQRAgpAlpkJLGGcOwj6Io5EFE5IWE\neg4o2FWHTEjodn2O05TA7nFv/QEff/M6clwAzcQwyqRxhKQliFJK2x/R6veoFwp4gyPaj4dULi1Q\nvzZHRSvRWfPxS0d0gsc8OTigfWOIU1G4/MorBAOPucorXJt/HUcA68I05Ze+wB//8f9Gv326jsGf\nafKcLEyIwgSzpJEFKUkEeZKjqgpSnBOMPDRBR08NJE8jHUsohSJ2y8aYFukdPeLu+kPSnsfiSp0j\nP8BPPUQbpCrIjkJGTKPoEA76PFl7zI+/9YDW1DlWrxSQtYzLz17ipdaXuGi8yHiQohRBEEc8fHSX\nw9Ejnv21GcbjgDvzGX4pw7E26btQem2al5d+jet/+l2KmnEqCX6OIIiEJEknhvdJobkgiGiaRhLH\nZAiI4snP9Xodyyqd/L57Ug5nVyr4gwgEDUMrs7pcx7IlWjNlusd9XHdEbcakXCsyGU/I8gx34lGu\nZMzMzBDKAWppn2H8FpHYQDenkfJrKBOR9tMeE+EhinKMYlR45dVn+PM//Qv+/V/9GVMX6iyaK7hu\nQBAE6GdlcP9BRPGkKaVlWRQLBVz3ZLWcJifBLUE+KaeKooggCHFdlzRNWVo6R69zSBTLGBQJojFW\nKrG9vU2306VqmjRmG6ysrLLf9tjZXWdpsYEqVbH0Kr3+AbLe496D+8yunkNRc/qDY37ww5+gF2RK\nMyrLF66xoqV0ew/ZXNtnyrjGq2/8Fq0ZEIQcWRD4z//FP+FPjjeIPvr+L1jJXz5OStpOzs5GoxGG\nbuD5PnmW0+50MDMFVZAplUrIikKn02EwGOJYNrZjs3Zjnf3tA3rHLlKe0A2GSI4FgsB0q4UoCNi2\nTb/fx7ZtZmdn+d533sYPx8wvVWhNNchdlWa5yWztAsPNIaFkE0YeP3r3DxiFt6nO2YwDgYqqc/OD\nD1n63DUOEg1DLzMej5lqNjEqReLjw1NpcGoDTJIEWZZPkqDDEEVRSJIUz/OwLIE4ToijCNd1qdVq\nTMZjHEfhlZdfYWdvhywTyRIdq6DzzHNLyGaKJnh4nkuxUGL/QELUJ2RpRhiGHB8dI6ITBiE//vE7\n+JJHoRYQe7uUsgvYSh0tKCO6KVtrd+ikD1BsWFpextB1ylWVS5eXqC/P0LnX53vffptyXsOyzLNe\ncf8Boij+20EifnJdYRzHjMdjClYR23ZIkpgwDMmyDFmSsSwL15sgiRqSoCMh02gUccMBw8GAxYUF\nHKVJrKh0Om3SNEHTNKIwYn6pwnB8BFGEJjTRNA0/6BOEQ0Z+giiFTLwBM9YKlXKLSqWMe9yjItu8\n8ew/4eLcPIp2ksIT5/C9771FPvKxdP0XrOQvH5Io/W0GhyRJuH5AkqYEQYDrTqjUZ7FVkyRJTs71\nw+zk2Y9GHLclfvzdnzLey5D0KkZVprk6z17vmMlggmWajMdj5FzCtm0kSWRvbx8hc3j+hRmm53Wy\nXMZOqySDlHcev8PV1Vfo9B9x8+6PySvHyPEAY6bMdP0a7/7RX0KaIvsZoiOi6zqqquL6Hpdeep6O\nNz6VBqdukysrCmmWgSCcXFySZeRZBp/cwGXbFrIsU6lU0HWdj65fxws8NFNnOBggpGAZJXa2j/no\ng7s8Wn/K7tEWT/cecffBdcZBF0QBRBhPPDY3nzC12KJULyFJAqqicLRlQzhPsVTk4jMLWIUIMZ9g\nCUXsZIl0bJNkHkghiyvTNKeb2KbDhQsXmZ6fwy4XkNSzFJj/L/I8R9VUlE+S2/VPuqrkef53wQ9A\n0zRM08SyLZyCQ7PZ5Pj4mNHYQ9UL6I6JF40ZjNqYBYdLz15lbmkezZB5uvkEPwgpV2uM3AGox6RC\nn9Ewpl5+ka/9o69z+eoSS+dajN0eM/M1Vs8vkqZgWiUUsYIjrfDs6ptcXr6EBAgCeEnE2z95m1vX\nP4LdDllydgb4s2RZRqs1jaKoiKJEEAR4rkuWpkiiRJwkKJpGr9+jPxzgBwGiLKKbGmN3jDsK0LMC\numxTnWpRa7XQdZ3J5GTHZhgGBcciiiIOD454+uQp7c4AVZfIs4g00BgfRrz3/fdxCg5dr8v9g7cJ\ntLt4HCGoJoY1R6GyglNYxB/oHD1xqTg1FDRs3SFwA2RD5Qtf+dKpNPg5EqEzhmOfLM/Ic9DFDNeb\noCjSSZL0JxEm13UxDYPX33wNT8kQmyYLsw38g10k02Z+ehpfzDk6HjAxXS6+8RxxlLCxuUlsSUSB\nx8Fej8urM2iv1FB9CDc7bG9vEyY5ZfsColGicaVAJ3zK+HGG7E/Rooyb7zLudvGSPXaHLq/aq0zZ\nMnq5yNRzS+w9OaSll1F+dJYk+2mkWcpgMsR2HMghimPSNEcUZTTNQJVUojBE0zSyJEVSZBRDJ1cE\nnGqRwAOxUeRgtIVsidSsJlMX6kiJhJ6IFLaGJEcJYSZQmKoyTrYYTUAby8SeiGXVGMS7FMoScXhI\n41wZY6GEY1b44M4GB4MDttv3KBQbrEy/iecZ5CLsjCf8wV//AQcHT1lsTfH4gwPc5HRRws8yaZYh\noWCoJuQCuqiCkJHnOZVqiVKxSnswZGphnn6/j+k0yNIhY3mfo/aY3Na5eGGGbs/HjE0Gj3PiNEQ3\nFfzQxSno2EbEuLvPdHOZjt8nkvaJgkUK4YtMKc+weXiDlcVlMlJixceoFthYj/A7LgePtlluvIS5\nOGH1tSu4usxknLH2F4cIgsjsbMrG44c83fmY3/7df3oqDX6ObjAnt61mnxSZh2GAYRh/t10SRbxP\nIr6SJNGoN7CKDoZlMI58ovGQoqyQy5BIoKgKBbWMJRfoj3oIsYiUKKRhyrmZFi9deRF/lNN9vI/m\nZ9TtKfb6e9y8+RHlUot333uXtZv3UMI65xufh0RARSdydYbumHicYBmg6zDsH5PgMbMwRbB70sL/\njL+PIAgkWcZgOKBcKpOnACcRWwSBOIrRjJMZvtPpUKpWiIKAJElYWlri+GBA6LrIgkw8EbB1i1Zt\nHlUSeLx+n37YoTpToieFkEnIiYK738aSSkiizOMPfsRAP6bUEjg+7hKFIitzNarTM6zEfbaPrpNO\nirz+uf+CeKRhz8H97af8+OM/Jy+7XJmb561//T2isE/A2QrwZ5EEEd/3kUQJURIoFovYlkWcJDiO\ngyIrPNl6iuu5TE1NkaYpQRjQ93p4SUJztsnMapPw8T6qKPFw8yFSM2RqaoowikjTFEmwGY+GpDWJ\n11/9IrWnDc4vPIuiqoTCkNb/w957BkuSXfedv5u2Mst787xpb2amxwAYAAQIMyBBkKAoakkExd2V\ngtqQVhEMhTZW2ojVbii0+rKSNqSlPmiXIoMgghDdgjAE4Wdgx/V0j2n7uvt5V+aVd1mZWZm5H17P\nqDkYmHkECbKnfhEZL+vWrcyqc17evHnvOf+7lODm1iuoIsqJ4wniIspUaY6h2mZY6bCzvcWpR0+T\nyWUoTHWpbTRYv3wbRVU52CzT6bVY3bnDzl+1GEIQBLiu+1qjNxwOMQ0DVVVRVeW1ccFoNMZ4PKa6\nucOJxDkGvT5aKk4mlKCytocqByyeO8Od7dvsr5Q5WGsgSzJrNzf4iSfeR7tzgOhLlG9V6TaH+Ac9\n8AO0+Tz9zpCQqfPii5d58dIt5qaTLOZPUz0oMptYwPMknAOJ0ThGRs+wcuWb1AtxAi/E4nKRbKzE\nS5XLqBO14DdEURQUWcYwDXzfxx65DAcWsizjOg6apOIHPpqmEY/HmSpNceXaNXq9HnPzc9iDAYHr\nkc1l6DkSg/KAO+M1hObiKwPGpsNWa5NoqUjgBLj1MZWVHXKP5Zg+PU9rd59wTKZSHpBOFIhFfeLZ\nPK4syOTCvHy5ywcf/FX0wQJ6eMR+b43PffG3ieZ7FDMlwrEIZx69wNXeVbxrk3He70Ic+ti2bTSh\nUSmXicfjxOPx18bFT586hW3bZLNZyls1ImGDdCjNfL6ANfIw0waZIMOgF+BYI6KKQiQSIej16LRa\n9EWEZn1E+uEZEvES56bSaJKBi0V1fAehdGkHe4TkJBVrDSsYQADRaIQHH3qA5y49g28KCrkFZudm\n6e71UB2PiGYgOx5pI8L5c+cYHzHM6S8cByjfDWBV744FRqNRHMch8HltnEjVdSKy4GB7F1+MmDu+\nSHYc4mCzQjqdBgEPPfgQl59r0Kl3ME2Tc4vnSRlpGv0qrb02z69USI4N0oqJYoYYNl3yuRKRuIEq\nxXjnu9KkkmPE0EcKXMaeiybpiJ5B0sxhm3VatQ1cEkTCGXLZefAciqXiZNHs78Gr40Ku6x5eEGMJ\nWZLRNO1ugLt2KHIZBAwGA6qVyuEF4ziYpsny0hIbL6/TqjSJx5IoUoRqu0K8ZFA8kWNOzbOxsoaN\nghhL9A4GJAp5ph49DSGFqDRks7bFdtVGWyghKz7xTJy+M+TrT76AOjjJAzMfwW4HvHjr27Sky2w2\nLrKYOkE0VcIwS2SLYczIOoo6ucm9nsPFxw8Vf3zfR5JldF1nb2+PIAiYm1tgaWmJF198kVa7RUjX\nGY/7WEOLY4UiThAQScDNrXUkLUJ+PoftHoA4lE/r9wb0vRQhLcbmxj79jsxy/DRjx2avs0nV2uPs\n+WmOPzTD1fU71FcrjIcKMRHj2NIS/XIdRZEJOBTkWF9bZ+32KmlZQx2D8HyE7DOzPIPj/BWLIYgA\n8okUvu8TljVs28EIRyBQcByLpB6n02vhMKR4fIaQEiOkxViv3iKZLPHSxcsMNIeTx5I0xnts7DRo\nt/u8933vxvP7GDGdVXuDcWqTxZMx6leyKGNBZK6An5FZfGSZE6cexLYG9Ab7rG9fZdSAuFFEltus\ntb/DqcV3kI8tMgo2sA/ytHdNHMoMYjZ1qUO9tcPW1h3G3tHUZO97AvAsUEPq4TifEuA4LoOBhWGE\nkQOBrqo4to3j2HjNLv32ADkbJ1lMc/3WGhW3S84L4Y8dIvkUhivTbdRI9APsoIPoORCCQLGIFhTi\nc0sIxaP37CrW0EVLp0gYbW5du8jysVk2X6hw6/pVvGGWv/+xf0F7MObmzjfZqH+JcNJi2Oshy1Hy\n+jSq0Hmp+QLheRVZmyyL+V0Ige1Yd+XOBFIQMFUsMej2KO+XSUwnMXwDT/Jxeh7T6RTNxpDAzXDt\nuT1ExMPM2AyGXUajBs7YIlUyGFg9/G6I5qpHflbnzEKJRKzETOo9NJwGltikMXqFTDqOkdIIJ6OU\n7DaXX3oRxdeJZQSu1MeP+5QeKrLw6DTTkXmuP7OF3XJBi2F5YyQkelafarNJyDnaLP9fSA9QV1Q8\nz8MORkhCIribx5lKpmlu1wjpKmo0TrvTIFOKIMcUdl7YpF2Z4fb1FWJakb3qLn25y+ziDMdLy0RT\nJr1+j/aoxmDYxDRNQqUwva0OshiRmQsxiDpYlNmvj5nKzbC106XbMJnOztJtNjESPumkRsve5kTh\nUXbKgnR8BlWM2NmpcNDfoDq4zDt/8ieYKU7jjSdjgG+E4ziMXQ8HF9tyUPXDnt+rQx/+yEFwGBKV\nSaUZd/vYfoDd7dBst/DkgLe//3GqL69QLVconp1HGoeo9yTWb9Twsdi8vsvpd70NVdfo9tbxVlq4\na2PEtTqeatI/Bo7wCBsGgSfzhc99mmAk+N/+l/+IrqT5wjc+x0i+QSSpU9nfIRGP0bO2uHL1G2iq\nipl0yWZP8WX9Sz9uc/415L9Knb2q+bi/t0c8HufkiZNs9raZWZjB6wXUN1rUKhVSqRimnqY26DEY\nNIjkFE6fPo2madxeXUHTZJRRFNvS0d0wp8/FmM69jYh2huFgzNOXnkJLVEhmbVLJJZyBjyTZbNzY\nxG27yLrMcNBlaPVxPJfBYIgSKEiS4NHHH6G+1cTdGR6GR1kjGrUm6VyKTC59JAv8hdRgAsC+2/XU\nQ4cBxcvLy2i6xpXGgHa7SbGU58b2VWbOHmPqWJHijSLf+eKzWDWbd334HCIaoAmFQARs1NfoigiB\nGNAfNhjV2vhDndpendzJMPKeQqddQ46E2NmtIWtNGvUNxsMic6WH8YIxfriHkQsh1D50G/QHu5w+\n/jgH1T6+u8+J0LtJhstEB9vMJmfYWL0N3mR86I3w/cMLxB27ry0s/urj8NjzCJsG1mj0mhiCFDPJ\nzkzR6LZZX1snkkuTnUtz+4UWs6emGSkjksUcm5fXGQ5c8pks589liKUKDKwhniNRvrJLI9BZlvJI\nsTj4EoVSHkMPYRgmyYejfOgd/4CI/BgXX3yS7YNPYcQljEgJ19EIGRqN1iah/cNGOp3KIYeLTHJ9\nvhuBQFGUw8mN0QjrbhD0q+tuzJ6awfd9ut0utm1zqI7gEJg6vgRCkRBCoOsanW4XU48iDUM8dvq9\nPPqR92L/0pjcTJQ7K0Oefe6rtO2ncYMO/WaTTm/A+dPvwWq43HzxFb7zhReYn58hUtRw7saZNpoN\nRm2Hufgi0Xia8kEbN2oTmz6MK+yUWxSWs2RLKQzzrzgTJAigVquhh0JIkoQkyQgh0Ww0CRkhBnfj\nifL5HG23RHY2S3mwh6zIWAcjTs+dZXFpkX7QQXKh1q6SXUgTMgT11gFaXIINm0vfWSeRTpKdcRjc\nlnG68MCDZyjkVMywi2ePSc7O47smjb6NHUohxaDn1ImYKi9++1s8+uAiqdQMnUYPuxUhEsDJmSjb\nN7dYv7KBCCYN4BshSYdZHp7nEQ6HCThUh5EkCVXTGFkjNFnGdV3GrksknUbNxEkYKq1mC0kR7Lf3\n2KptMn9ilqpVodUsY3llfuLxtyOcMWZa5WZ9jzEjpueidLsJ6gddorkw2nSewpkplo4tHsaYSmMy\nxhTLxSf49Oe+RqX3OVD3yU/NMFtcJJXKEoo5fP3i12jUh8RiCpGIYHVnC8s+mlrI/Y4syziOcziU\nFQ7j3l1cqNfrMW8sHio5IZidnsFqNqkd7DJ36gSxWJg75QaVap1er4/ne9y5vkE6WCD5QIlibB7Z\nlDASBp+78//yzec/QSSqYSTT9No9FAK+8dRFNm7eIRbVObd0mka9gVrUmJ6ZYmSNGAwGRLUIw+oI\nz2tT69dIzMZJdsNcfOEFJEmwNL+IGTGOLIj6FwiEPswBtts9dNsj8Bw8HOrtGnc2blGvt1GlCGu3\nd8mmpknJEb748T9le61BeCqJk7AYGwrheJGQFmKqECWZTqJqJtFokZEV5uZKh3qnR7oYw5dUyJjI\nKZN+2+J86TxWW6E/FJixEKG4gzeu4PT2iUY1ZN1gz6niTtk8fe2zyN4ei+l50nkJ23axe3lkPSBz\nbBnFmKTDvREC8Mcegefjj8f4IwcNCQ0ZPZAoLS6gRWMMukOUSJRGvcbt7RtklnOMrCbDapmDl27i\nOw6uP6ZZr7N0fIlTD59iHLVp6y2qowbOsIU0bBGPCyJzBnpMx89FGMYtqp1rrO49Sbl1nVTiFDPF\nj/Llp19gb/QlfHPA/MIyeiygZ1vcunaToVJm/ngRPJfq6j5f/YMvc/3ZF5Am2T7fhSzLDPsWnuuh\nSAqKoeCrHnpMY4TFyvUbbG9tkz8zTeYn5ujEIJqbxlIDpJTCAw+dI+VkqV1rYm97eA0fTYdaxcJ3\nZYYDuPj1b/LVT/wOoa5Puy1x0BqhhfLkCouM/CbJQpRssUAsFSeVTzPoDggGJo1tCbejISsqV1df\n4fqNy/jDOktzKSJzYc6/4xzz8wvsb1XpNx10IkeywZEbwLHvkZ0q0ul2GA0tEAGKJhOJhgnwsOwR\nI88lXchy4txpRv0h/XIX3xX4GgzlHr42RtYMouEEgevRrfc52GvTrlg0yw6drkdhOoumS6iKQXwm\nhm86NLpVmgdlHNumUCpSrlZQQyqFbIK5UhZZEvT6FrIeIpyOMQrqfOmrv89MaY5INE65+TJD5wBE\nmhPvOY8WnTSAb4Tn+8SiUXRNQ9d0XNvBUHVkBOlEklQmQz6TI7DHqKpOJplAC8mkiilOnFhi/fYt\n7rx8nYcffZTS3AzZfAFr6LJXrlDtNhjJNh2nwtgdMmp7rN/uEBgapekZmr0RYxdGVoX+oEzgxkhr\n72J1fZ+G/RyuGBKJzRCOZujaHdZ3bmF1+8RiBobhMj+X4tSpEtlsiOPLJ1HkySzw6wmCu6rfsTi2\n7WA5QxKZBMdOHWNheYG52VmajQahiE7LqnNr8xYLJ5eIZ2O48pAXr7zA9voOjz70KOlYmofOn8WM\nCW6vrmLZHgHw5a98lvHAIhFNkCjonH7gGMdPnuTEqdOcOLPIzHyJUNggmU0xuzBHJpMiEU0wnV9g\ntjSHpIzZrNymN2gSjFykAHpul629LTqdLvOleVaffoXu6tHELo7+XyFJFJbm0FSVbq1BuVElF8rh\nui6tZptzj50lkUlQPJFnIPdo7O/Q7fVoNDY5n1wkGjVod/eYK+VY2+iwsbWPPRgzHAzJ5fMISxD4\nPtlMhmQqRSgkWN+rkJnNYdsOv/+FP+TnfvGjpNMZ6gcrPPfc8+TiKc6eO8NOaxPbHmFKGk7NIx3P\nslu7w7M3vs07H3sfz974DG3rBqo4SWd9azIJ8j0QHK7Dats2Ozs7REJhZO1QBKPX7yPKVfqVBk6n\nT2xex8Flbm4OgWBzY5NAFow1ienlBbR4hMLcDLXaPjPT06SzESq1bfzARpZVLl6+QdKYhpCP5Xu4\n7TGFqQynT55AsMzjD/4CiVTAytYXiaRaDEZhUvEMYypgSIheH7dvc/viHuXGOkvLywQRn/x8mpKS\nZjvRiN8AACAASURBVDw82iPS/UxwN4azXq9jmia+PybwA+zRYV6363uMXZewL7N/axt6XYRssbp2\nheximtJcmuK5k5imQSdQ8X2f5maV3rhKp9cioitc3biClBRkFlOYBYXZJRMzFCIeT7K6OmRk1cml\nC9QPDkin0pgRlUzOQFMljHCJ7KzNCy89z/6+xLAP7moNSZOxRzaabLC3u4t10KTsrR3JBkefBNFU\nxpqMEgszbrV49LHH+Na3voGQJAr5Ao+862H0hMbK7g26/Q69xgHv+8BPcv3KHu9+57up96+zsXkV\nZxgmGskw6HpcffolTp06S8g12dvex/M80pkMIV0HYXMwrKBndBzJoXA8Tb1dR9F0wuEwoZDO7Ws3\n2S/v4Ic99JyK3Xa4/fwdkpkiM8eneOrSZ0nFIvzCz/wTPv/8b5LKZqne1glGk8ejN0IIcTj+Z4bp\nh3qMLAt/7BGJRPA9H3/ksLe6geZDa7+KmdFJJpO8+OJLfOPr3+SJD/80m7e3sAIPxR+jRUymwlMg\nHCTZIxqNYfXibO7doF5vkF5MM5R9CtPz4EbI6FOcm/oIx088jKpavHTjTxHyBqqI0my1mJqNoIaG\nbPf6hE2VqGrw/FdWOHZulpcv7tLz2xSnp5DiaYSY5Hy/Hl0PsbAwz+XLL2KNLEJRnUajjjW0+NAT\nT7BdL9Nuttm+fpv1Sy9RjITxGTC0GswtnKLWrNK0Dmi5Ald3aTYqSIpNv33A1tY68bBG3aoxnQ3R\nDVpUOkPszV0ieoRkfIZqtUMsGiekaaSSSSLhKIE6xnY63FndJZVTyc9KzM5n2NsacfP6OkPL4z1P\nPEYwgFsv3Obs0lnCswUCXTuSDY7cAEoErNy8SnVnD0PTmQtlCKfCdDpDEkWTrt8hKpIMnR6Vg3UG\ntR6Gm+QDP/dOlIyOomRIywqK5PEHv/17rFxZYX76GNl0kt2tNTbu7GNEVQq5LOFwiI3NVWYKpylm\ni+zvb1DKFen1ugS+wskTZ6kfdFm9/Q1u3brOhfdeYDk9T7W+S/F0HsfVmT3zNkbSFp957vf5pyf/\nGR95/Oe5sb5GP+ggJlOE34OAkTtCC5vEpnLcuXadXCTLIBiRiiXRDJlIKIwiyYRScRbfvkwkHsd+\neQVlqFBe3+XAqTKWXSLxGIbvcuXKNSLhCOFQmJGl0+51aHW66KZMIhViJnyGX/rQrzITXSAZT2JG\nDFp2j6+++GnWq1t4apRCPsp0LkzYDLEzWAVPxnMC8gt5dqsNWqtjdutd4jNxPCvCgdRBDU+GOV6P\nJEkIoWDKOv1Gh6npORzfwkjEULJhEqEY2ZkkL195Bc1RefR97yG9WGBqVKXfH1DeqyBLCtlcDuF5\nSJLC2FcZ0ecz3/o4Zthj/lgRZ2+A3w4xk0vT7G4Tyxu02x3SmQQhLcSgO0YWERKlBK3hAfXBHtX6\nBgtTb8dUdISxx8lzi8TjFmE1Q8xJMrA8hKOyur7FAx949FC78rfefKjTkRtA13HoN+s8/MiD5PI5\n1tdewBEuiWwGy+uwU9vEsNqMrCGj7oB2rcXAd3CkPj1UwpkiU7E0veqA8voGST3DyROPkc0qdHtN\nPvCBD7Ky/QLW8HBqfnOtwvzsw8TVKdyYR0gYHDT3aLUsivllpqdOcG7xAo3b+5T0HO6+jWfbaNND\nknoaRxsRn41Tb2/wh3/8n/j1X/ufqRh9bo2vI+RJD/CNCIIASZUJJaLMzpQwwzrlvT361oBxx2Ov\nvoNsarz3/U9QNzp4OZVG84ButYFnB/RaXRYuzNHqN8ha02iqwqjdo7XfptO0mZ6Zox8cgO9ihuLk\nU0v8o4/+M04vLr4WtmKPA556+ss0qGEbPpu7Fe7c3uI9D7ybsZqk2bNAgtHAR/KGFPIFOgd9DBHG\na/vIQ4lerYLvT3KBX48zHlOt1Og3uuiBRCoeo9KrUlqcxtHhledeZjQaMHAsUtlZ4qUp2s6IdKFE\ntbJDMT9FIpHEsiyGgxGRcJKuLLG2s0bI3CKVB82NIDkGWCHOzp1hFFui2WoSiYQxDANrPGDoKqh6\nBF/1EGbAaDwgZMhcevoq8VwEOz5AzY1xPQs9IrG3UmN1dQ0jFObMg+eYP3aMwbB/JBscfRJkPOYd\njz/OwsIiY3dMKpnCNExSyRSSkInFNRTVxTBMVCVOt2vT7XYYDUfgBwz6fdrtw3gxL/AoTWdpd/f5\nzjevEI+WWD5eImToXL16jdXVVRzHZn19l2bTQlWiNA6GOI5PrVplf38PVVN5+PRZUoHCtz7zRV5+\n6mniqkzIdNHNDpt7T1FtXKLT6vLk157idz/xuzz62KOcPvkImjrpHbwRQRAQi8aIxaLs7+1RLldI\nJpKcOH6CtdU1Bu6A4+99AOPBEpGFFHdWr1OubGJmDC488RjHHznNqRMnqdUOuHV7hc3bm5iDKJee\nusywP8TxRnSrXXqVEcXoMX7hg3+PE4uLtAcjHC9AAC9vXOeF9Ys0Bg0USaGYLWAYJs8/f5FLlw5D\nIXzfp91ucfH5i5jRCJFcikAGzx7RP2ihKREUeaL4890ErKysICuHKaura2tIQiKbybJy8yZf/v++\nRsSPMjVVwlL69Nw2ETOMaZrMzEyTTCVfk0JLJOIQBOzu7tDt9oiYUWLRGNmFDHICyv1drm69QiwR\noVIp47qH4TZhM8zIGtHv9QiFDAig0+mSyWQZjgYMagPYU7j41ct0Wz3MuMH8+VnOv+ssxy4skZlL\nIgloNVtHssDRw2AUhVQ6RSaXIVfIsb6xztrqGqqqMjU1haSMCJmHgpqKFKVe69Mf9BkMB7jjMb1+\nn6E15Jlnn2V56Tgzs0VanX221tsYWoahVUPTZCRJEArpFEsFSsUlTp64wLGlB3BGCqOhQ6PRoNPt\nEgDRXJrFh89jFDMESQMpnCBuTtPr2shywNr6TUwzTCwa508+9Sc8/Z2n+eD7fxYhJjOEb4Qf+Iwc\nm263x43rNw4HxA2TVrNFNpMjZ4YYOz1WK+sMO3VGzQoHjR2265vEFlIkZjMoksL8/Bz5QpGbV1f4\nzG9+Hq8dsDS/RL15QHO/gT+QeOcDH+T9D7+H5y+9zDe/9QyaLHBs+Por36YpDqj3ayQSSVLJFOXy\nHk8+9TWefOopBtaQwWCAEIJcJkc0FufMIw+TyeUIqyG2bt5h0PeQJusCfxeqokIA3XYXTVExQyYP\nPXQBXdMYe2N0V0e2VNrdNo7pgHk4c1wqFel02vR7XRrNBrZj4/ketjPCHbuEQgbxWAIEWPIAKQZ6\nRmOkDtnd36WQL6BpGs1GAyEEiWSKhcUlBoMB/UEfVVUIh01K0yUG1SG1Sw3knoJt2VTaZVzDYupU\ngdyxNER8fD9AUY7m3yNf+Y5l880/ewrDMDh27BimnmBt7dssLJygNHMMCQlZGvPtrz+DNVSQAgVT\nj1De3aPvW2TTKW69coeDSp1jsyaDUZ+QpJOIG4yCBrXOiOpmA9sfYztjpJGCpsoMmh0SeQUjpjDq\n9dENwe0bVzg+vYymaQRZg9nwMbIzGfrWgP29Lp7vo6iC2dl5nLqgcLxItXGdP/rUJ1mcm0dVJgPk\nb4QqVMwgxPraBsvHFikUcoRUaFwpoxkSilDY398gn9Lo7dZRRjKtfpd6tU4+06Uwn8OTJTKxNCIk\nI4ZjwrLGudOPETXSlFtV3v/On6FTEXzog7/I1dv7PPfMRX7lV34ZD1jZXKfc2MZXXMqVA1Q5yezs\nSc6deztrL2yzOLVEYhxls1slJCtMn8qTLIXwQ2Pmzs5RvT2m02oyqjbxJpJn34XtjPA0jwfefQHc\nMcceWSQwJFq9Jutrd3Bdj5srt4hN66RjMRyrhRZO4juC7Y0G4bBBpbyDaYZJJpMEtorngBGR0RMS\n4XSCrtXG0T1ypSxru6uUy3U+9MGfIhwOs1eusFXZJqYnOT23wEbVxXU8TFWnfdBDlxJkU3N07DoN\nt8G47+IORgxMG6Fo9IYWnU6VMycTxOJHe4o7cgOoINNaq7HWaLCUmMFU0xw7eYxOr4EQD5CMJpHN\nOngShhJFjQ2I6nH6nQ6OOmAmF+Pi1y7Rbw3xFtusrtY4mX+EQlHF0ba5/MIOfkWmcL5AYSpP7cUW\nO5VbzBTjqJEIjcE6vtJHM3wONtb41Md/k0d+4nGE6pJNJEkrCYzpPDYDhCSxtrZGITuFZESoeXXm\nHppj0Knyyd//9xzx5nH/40HYC1FIZDj/wAM03D7tzhb9cY1QKIyeKqCkRqSLEgcdlan8SXa3nmHc\n8qDtgOTR8VzkXp9Rv0V1c4vEYoqB7XP5yRfJTYWYSh9nNlVk6Ao+/YU/4Nd+/ud58mtP87b3vo3L\nq89Sq20jzCGdZpM9b4OZqePMTp9ndvoqt7/zMturKom3JUlPZ3FDHbbtq/RrOoHlsrO7w6A1wOgM\n8I6YKXA/M3JGZBYzLD9+EsdxqVg1Rg0LezQipMH5x89T2drjfR94L9XaOvvrt/GGY2LRAidnH+P5\n559ld6fKiRMn8FSFTs3GHUA0qyAnXKS4QWezgxDgyGFCaKTzUxw029hjj3A8gRbTGezsc/Frn2Fg\nKigJHbvvsbVWxXRdTh2/QNNzGVYO0Go2dsJi+vzyYZ66LrNa2eLza3/I0vLikWxw5EdgIQk830PR\nVCRFptls8vjj7yAajWLbI9bWVrl58yayInPsxHHmF+YPF2GxDgUzW+02i0uLGEYIgSAcDtNo1CkW\ni2hqCHtk0Wq3WFpaQtM01jfWEJKEEBKbW4dBkJqmE41EMUyTSq3G+voGrjum1+uxX9ln7AYEvkF5\nr40sIoT0OEbIwHVcspksoZBJtzOg2+kc1Qz3NZIiM3Bt3JHNsN4ipSWIywkONhusX9siEgoTjUQY\nDg/zgSvlfYbWkG6vR6ffZdwd0+80sO0ee5d3GIz75M4fw9dk7GYHtTPEdXuETPjK1z7PQw+d4TuX\nXkCJ6HRGQ/abdVKZDP27aZWNRgN35AABy+dOEp7JMTY1XEeQzUyjiDD+SMKv9+ltV5kJJ9GsMd3e\nAG8yCfJdCCGYm53Dcz3MkIE9stne2qbd7tDt9ijMZXj0vY8w1hTUWA7fjNEYDXjhhUt84VOf5qVn\nniMSDaOoCp1uh/3yPu54TCKRJBaLIwsZSYRJxadRpBgCk1g0xtA6XP85m8kgYXDr5i6f/vST3Lqx\nSyDr1Ec9krNx9OyY7FKYuTMzFEp5nLbL1o0dxmMXIQ6XbJ2bmyMajXLzxsqRbHB0OSwh0DQNgeDZ\nZ54lfSLL/t4+mXSGVDLFjbUdDrp3mJmeI58v0PI67K3tUm1UuHD8QWRF5pc/9jE+/ru/S7N1m0Rs\nmbScxw8C7JFFsZDHszVkSWZ9a4dOt8tsKc5+eZ92sMfQHyL5HoV0gXQ6wGm6yIqMH/is3FrBtR1q\n9SZyKEo0FuXc2UcOB/O3tg4v2qrF7s4uD37ww/QHf3ZUM9zXeIGPE/hs3FmlvL9J3YYPfPAdaK5B\nrdpg0B1QPJHB9iwGgwFPPvkkqWwS0zQQkuDG5RskT8WwxjK3v3mDcFJmWGsyaMpEM2kCUyApY26v\nXiUSjVKtbxPYgife+7f4z//lvyBFJGRVxR7ZeL6P1e+zv7dHePEYhDQiswWmcmHUqEd5/1CvbjRy\nCacTNMotzHiU/OwMu7tl3EkP8LtQVZWxO6bRaKIqCo7rYo0sbNumWq0ST0co5qcIwiF0qUQ8oaFr\nMDiwufnCy5w+d4rlE8dIxpLcuXOHpaUl2kYNXdeRJMFOuUy341LMpfDHAbnMPL4PnUYTx3ZYXFxE\nkUyK+UVamy2OLZ2j2e/Tdi0KaZN0KcxArxObiRCrxPHDBdq9Pju7u4yGFtFYjJBhsHzsGEFwtFi2\no/cAhUQ4FiGeSzB9YoaTD5wlkkriKzKFmSmisRj53Axjb0y5vEWlWqFcqSAFglgoRiFZZHPtDvag\nj+TJeLbD3tYuQkhEEgWCkMHi2SV0UyERi7G0dIyomSQRTZNKJikUMwysHru7++ys7+H1IOj7mJLG\nXGmWVCaLqkc5cfICJ08+QDqXx/MDBn2bSDxBcW4aQhIr69dR1IlW3BshKTKZYgY9FKJVbyGGDoVE\nnlQ6x5lzZzioNZAlnUgkhmEYKMqhAriuaggP+gctjEBi58425fV9TFVB6vQJrCHJmTRBUWe/usX2\n5hZCjGg36/z0Ez/D//1//QYrN1+h73Q5aO5jRhQkJcBzRnz9a1/i8kvP0B92CMVNYokEqUQOVQqh\nq2EkRaU8arBw4SRyPoxWiqOHTXxvEuz5eoQQbOys4uHQ7NZpVOtYXYtus8uoa2GNbFAkHN8lUAIk\nVcXzBZvrGyQiYYrJDIO6RXWvRqk4xblzZ5EUib3dXRqVJo39Fm7fo98eEY9lGHvyayvObWys0+93\nyRdmOHn2YVxf4wuf/iq3rqwhyRK+7OLrDtvVO+yXN2g1qhyUq+hCw/fG7B5ss1/bpbyzxxc/+2cs\nzC4cyQZH7wFKEpgKQcQlfCKMko1yIvIQvu/R8hyyxSLdWy3W1y8Rj8foN3oYUR1VUWittfnmpeew\nahaD4YBEMkPUDNMaO+imyqm3fxQr/jzlOzeIyCnmSkX6WZl2pUG9t4MX6xKb0ZBkHeHIaFaY2dAi\nxSCN1ephYpJZmmL53AVCkSTl6iora1v4rgsYFBcKIARL1hztvW1QJhfHG6EqEt1GBUPVaY0lcobE\n5UsX8eJRElkDVQ5Trw2pbm1gV/oUpoqcOfsAVy5eor/fQov6+B2HbGiO7Ol9+iObcDSKYjkoco/4\ntM72+ioqZ1hde4UP//RH+dTvfJrLX/wScw/mKVfaDN0yI2ooUYmiFeH61i1u3BhQzM4TV8OMexZa\nLMPcwiKD/oBWq4UiWbh0kWM+IimYT53k+sVrP25z/rXDZ0y8aGCkJUaSw5QoIPoBK7dWMD0T6wD0\n5TjS2GI42sGQphg2JOq7FRZOlMALaF7r0XAOeOIXP4AvAkJxDdGTaGy1SCopPFmgugJF0jDiCcrV\na4QMmUG/R7VSRjWmiRanycwvYl2/g71TJ7IYZSYzRaVWwRRhNq++QiFeohFy6Azr1HZ2aQdlnEGP\ncCvMcL+F0z2a2s/RM0EkCU3TUKMGQgi61TpGKMLIHmEmZQaSzJWrV4hEIkiyjBk2eeDUOe7cWeXq\ntatYDZ+Z+DmS0RK9Vo9oKMzbf+oUesSn16wTQeOVcoViUmV/d5/V1X2yRZXZ+XkSqVM89fVLGLko\n6UwUNWFh6CHW6lvIvsTUzCwnT53BExardy4hS2BZXWRZATQU/XDhl+m5MON2+KgmuP8Z+4QGY6Ku\nYDacZChcyu0G6YUZ1lZu865H34OtjmjsNpCGHmfPnsGxbVRFZWdvm+R8jJ4acOr0Mo8nonz9y59D\nGngU8jPgywz7PrIRptnd5/jJJa6vX+KP/uSLzKZyeK5PZb2GnPSwJA8zEiKVzFOM9kiIBFElTr3d\n5eUbV1k4uUS5XGZkjVBCMnMnlwjLUaqdGrrmU94u4x1xzYj7GVVTX1vTJxyOMGhbSLJEvz+g2+li\nZFMMh0M0z2U4sojJNrdfXkUIQWlpAb8vQbOLLEt4nsfBwQHjsUcymcTzPPRQCEyZaDSKoqrEwzqV\nA0Gn02E8HmNZI3KxMAqCmfkssYiCmvAOlZ67LsI3kI0w8UIOa+AxdXyRW1dXOdjZRy8J/P6IwFKZ\nmiod2b9HXxPE88nlcviRQwGDseNjix5rG+tc/sYzbFXX6FltSqUpNE0jG0sTBAGmaXD8+DGqm21G\nzS6GKeG6Q+qdPdqygMBFD0pU7+wwdlw8z6fZbFAsFrFCB8wcn+PE9CM8++WXGFfGmKkolj6m4dZY\nfuwMjUGbhx66QHV7j9sbLzN3Js/u9gG7uwc8+tg72Khssrq6zdLSEq1mn263y3gihvCG+IFPZ9jH\nl0ALG+iJJJkHj6FlkwyHQzK5LB2pRSKZQNclNtc3icWTNBoNggDSqRTZZBJnaHHr2nUMNUQw0jio\n9ohrEY5nltjv7aGlfcKZJGvb32b2fIFQTyWXyiMFcZTciBuVBp32CLtRpbszIiWrJKaT2BGfVDbJ\naGTdjU8rIYdUZqaO09xv4doSqUSBUXVv0gC+AYLDtZ4PJxUkvvjFLxEPxxFCQlGUw0fkjQ3SGYNo\nQqG2tcedl64Sy6cp91r0KkMKRhFkj8APaDYbDAZ9PO9wTWDPH9OsN9HjUXQrTigUIxKJ4DhDQqEQ\nK7dWKIRzTJdmUI0xbtgmlswQj8UY9h3McJbd8h7ZuSIh12DvVoXi7AxiYCPZAW5/RKc8YuAOsUbW\nkWxwdEFUApLJJC2vwebmJm7VJpvIsrO2zvbWDkbB5KHHHkZCMByMCGkGu1s7dLtdItEIWgiC6BAn\nsImmVE4/uIgddBjZJt966hvcvL5GeFpH1VTmFhawIiZq/gSub3Lt2kucO1tia8clHckxDFt0ek1c\nxeGRxx/FHVps3bqJNA7o7ntYNRWvFiUmLZIKK3zlS19m98SAfq9NRNYJgsmySG9EIEuEpnP06xJj\n18VIhZE0BUVXePhtj4AjoSs6uVSeje1bVCplGs0mXuARS8Vo7DewvnqRUfNFBs0OkbBOIplm6Ni4\n44CZmWXikQzb27fYKm8Sy+r4cxEObhzwyo2X8U2DmKxjiji272DZLlE9SVxO0a536dOnNFUimcqQ\nziQxTR3Xg8rePp2DPoqqk0xmMCWd76iTWM/XEwQBmXSWkT0iCAK63SFRMw74qJqCKivUymUgSnH6\nOM9+5Rmsbp/8/BSVVgN7MObEzElSyRjdYYubN1YYtposHl+iNFWgttvAc33wQVdVGvUDBv0+WkjF\nx6O63+dLn/0cD194CFsTxDNRFFUnm55CVRXa7Q5+IONJEpIRwtcVSgsz9Cr7iMCjXG8zqrkkFtMc\nNczz6GowksSw38dTxri2g2pKoHv4iosWlTh+4QHiU0l65SqZ0AzYY6q7O8zNLyAJgTBB6CFUVSGZ\nTNKuD2FfUB5tUx9YZGZyZEt9tJDCrcYOshzmZCzFsN9jNIL08bNo6TSe1yeWNhhLcOvGMxj6kCfe\n8R6Mx4/R3xvTtBJU2zfI9kf09+qktBCGG+C7bfTQGKMXw5+sifSGCEmibVn4mgqyjBRX8d0B4/oY\ny3EgMDl16jSvXLzEzuouiXSMkWMzc2oaSZbYubaLe90jEC75fJHGQZP2sMrShRPEF9K0+x3Cpszm\n1jqxhE4gm6xcaxEyPUSuy8kH57jz/CrBLqRPJxkWesjjCA1vgFWpES2YHJtbJJaaojfcYL+6QlSb\nYdTfwUzk6JoQWZjCDvfRI5Ngz9fj+wG2FRDS47iugx4KoWohcvkolWoV3RKMeh0i0xEatTFWYOLo\nAs/3SWth+qEhO90yDz00T81dI1BDuHUJ87EsiuFQvzXAb2u47TEHW7v0vA6234WUSyQSZvlgno47\nwB6pGEGIrTvbYNQJLBdd0+n3+5QyRfLJaRzbIZwJU9us0Nxu8pEHPoK19gw1pc75C08QMk3gU2/a\nBkcPhFYUFEWh2Wzi+z5CUtkv75NMJRmPx0xPzxBNqpTvrOK7fdaur7O326LX9YhGIywvHsPUojiO\nzcbGJo7lwkCgxHW0qEI0rhKPR2nUG/QGPbLpOJY1QJEMZFkmZISJTk1RLa8hbEEkEiaSilCrVnj6\nmW9zam6eSq/C2kYTRZZxxmO2trfQ0wYf/oWfZau1gWaq5J0i8mefO6oZ7mt838c0TYJBQDwdZ0CH\n23duk4gn6Pd77N2u8NRnvkjHOiCaNpBVhYRpkEgmqNfrpPJJjLDJxuoG3ig4XOheHjGwWmT0FJ4/\n4uCgT6vZJJ2ZotPpkEqlafd2SUQMHrzwAP3tPjdeWSGvp2n16wjbp5CdwrNdlhZOki3kWd3axZe7\nRKNhurU+VsclljJoNvexRn00/VCrbsKfRxISu7t7dLtdfN+nUChw5tRZxmOXwWBAZb+CGhqjaSrW\ncMTP/txHefLTn2U0GiEE5PM5PNvAGds4Y5tUKkV8RiMSjtDr7eDYDpl0HvyA/b09lLjMKBjhD0eo\nQsX3FIZ9C1lWSSRS3LyxQv2gjav4FPIFEok4yWQSgXS49K6qUCwVqb24x62bt4hGYszMzfPsN77z\n2po1bxZx1Mc/IcQBsHWkD//1Yy4IguyP+0v8dWPi4/ub+8y/cAQfH7kBnDBhwoS/6UwigCdMmPCW\nZdIATpgw4S3Lm24AhRBpIcTLd7eKEGLvntdHE+b/4c77T4UQN4UQn3gTn/k1IcR/+Mv6TvcrEx/f\n/0x8fMibngUOgqABPAgghPiXQD8Ign93bx0hhOBwfPFHOfX2PwLvCoKg8sNUFhOV0yMz8fH9z8TH\nh/zIHoGFEMtCiBtCiE8C14EZIUT7nvd/WQjxW3f380KIPxFCXBJCXBRCvP0HHPu3gFngq0KIXxdC\nZIQQnxNCXBFCPCOEOHu33r8WQnxCCPE08PHXHePnhBBPCyHmhBDrrxpWCJG89/WE783Ex/c/bzUf\n/6jHAE8C/z4IgtPA3vep9xvAvwmC4BHgvwFeNejbhBD/z+srB0Hwa0ANeHcQBL8B/B/A80EQnAf+\nJX/eSCeB9wdB8HdfLRBC/CLwPwEfDoJgC3ga+Km7b38M+OMgCCb5cD8cEx/f/7xlfPyjviOuBUFw\n6Yeo9wHgxGEPG4CkEMIIguB54Pkf4vPvAn4GIAiCrwghPi6EeFXV4LNBENwrDfFB4DHgiSAIXl06\n6reAXwc+D/w94Fd/iHNOOGTi4/uft4yPf9Q9wME9+z5w73qToXv2BfBYEAQP3t2mgiA4Wjbz9/8O\nAKtAHDj2akEQBN8EjgshfhJwgyA4mpzsW5OJj+9/3jI+/ksLg7k7cNoSQhwTQkjA37rn7a8B//jV\nF0KIB9/k4b8N/Mrdz34A2AuC4PUGe5UN4O8AnxRCnLqn/PeATwK/8ybPPeEuEx/f/9zvPv7Lc74y\n8AAAIABJREFUjgP858CXgWeA3XvK/zHwzruDnzeAfwDfe+zgDfjfgXcIIa4A/4rD7u/3JAiCGxx2\njz8lhHhVOvaTHN5R/vBN/J4J383Ex/c/962P37KpcEKIXwY+FATB9zX6hL+5THx8//MX9fFbMixA\nCPGfOBzA/akfVHfC30wmPr7/+VH4+C3bA5wwYcKESS7whAkT3rL8wAZQCOGJw/zAa0KIPxZCmEc9\nmRDivUKIzx/18xP+cpj4+P5n4uM35ofpAVp3Y3zOAg7wD+99Uxwy6Un+zWbi4/ufiY/fgDf7g78N\nLAsh5oUQt8ShosM1DvMFnxBCPCuEePHuHSYCIIT4KSHEihDiReAXftAJhBBhIcSfCSFeuXu3+qW7\n5ZtCiH8jhLgqDvMOl++Wzwshnro7Ff+kEGL2B5R/XAjxG+Iw93D9bnoN4jD38Ofv+R6fFEJ89E3a\n535g4uP7n4mPXyUIgu+7cagSAYczxp8F/hEwz2GE+NvvvpcBvgWE777+5xzG+ISAHQ6jtwXwR8Dn\n79Z5BPitNzjf3wb+8z2v43f/bgL/6939//ae4/wp8N/d3f/7wGd+QPnHgT/msPE/DazeLX/PPXXi\nHAZeKj/IPvfDNvHxj98HEx//eHz8wxjOA16+u/1HQLtruI176nwEqN9T7wbw2xzK7Xzrnno/9+oP\n/j7nO37XSP8nh0nTr5ZvAot391WgcXe/Dqj3lNd/QPnHgV+557i9e/avA1kOHw/+3Y/7n/av8OKY\n+Pg+3yY+fuPth4kDtIIg+HMpLuIw+fnelBUBfDUIgo+9rt6bTY0hCILbQogLwIeBfy2EeDIIgn/1\n6tv3Vn2zx74H+96vec/+J4C/C/wyPyAq/T5j4uP7n4mP34Af1aDncxymxLz6PB8WQhwHVoB5IcTS\n3Xof+14HeBUhRAkYBkHwe8C/BS7c8/Yv3fP32bv7z3D4Q+Ewr/DbP6D8+/Fx4J/Aa2k3E/4rEx/f\n/7zlfPwjyQQJguBACPHfA78vhNDvFv+Lu3eB/wH4MyHEkMMvHwUQQjwC/MPgUCPsXs4B/1YI8f+z\n92Y/ll1Xnt6395nPuefON+Y5cuSQJMWiqJJK6iqVWKrJZaC6jHqwHwz4xTZgv/lf6Ce/2YABA3a/\nNWCjG2W7B5WksiZSJMUxmXNGZsY83rjzcObBDzcyKRWpbivobndT8QGBuIjMiLh3nTjr7r3Wb/12\nBsRMahVPqYjJ3GDIpxfhvwH+sRDivwNO+TTj/7qv/+tex4kQ4j7wf/wGL/+3gotr/OXnt/Ea/wcz\nCSKE2AZ+J8/z1r/F32EDt4Gv5Hne/7f1ey74fC6u8Zeff9+u8W+d7ufXISZ2PPeB/+HixvhycnGN\nv/z8ptf4P5gV4AUXXHDB/9dcrAAvuOCC31ouEuAFF1zwW8tFArzgggt+a7lIgBdccMFvLefWAdoF\nKy9VCggpSZIE1VTwQ/+ZrltqCkmaoaKiKRpJkk7+QYAiFbIsJYpjkiRG01VMwwCpkGcZpmURRSFR\n5OEUXHTNJM8FeZDQbXZRDR2zYjAaDyjqNRqVGpCRIYiTiKPmEaquUijaZFlCGKXkQhKHMXHk4zgO\numEwHo4ZdYdEXkSSpOLXvtjfUmzXyos1hyzLiOMYVSpkWYYQAk3ViNMYqSqkaYoiJUEQ4Y8C0jhD\n5ILPC+inJygKICfP+ewsgDj7XiHgrEmXA1IIhJQIJlMMTz8kAoRASgnkSDl5LIQ8+wyD0RjfDy6u\n8S/huFZeqrggIEszhDKJZ5Zm5ORIKUnT7FmckyRBSImuawghieOILEvJgSxNUVSFnAyJROYSVaok\nWYJUBVKV+KFHFKSYpollmwS+jxAKAkmSJggEqqKQpRmaoeMHPmEYYtsWpmUy6A9QNI2CWyIajhkN\nh0hdxS255FnG4Wazled54zeJwbkToONa/PV/9WdoqoZpmWz6j+iMO1imhaqoyIqkN+ij+ybPL73A\n4X6HDBUpJY5TYHfvMY1Zl4P9Jt4oJM1hemWG5aUl6vUG9+7fYnFNYXZ6kfXVG7z55vukhwr9+0PK\nJYeX/+oqP/3o/+YvX/iv+dOvv0GGT4jCzb0P+Nu3v4fRUFm/vETmBzy4tcV7P/uE/mDEla+s4rpF\nZmZnKDkl7v/8Ef/4H/0v5w3DlxrT1fjuf/k1fN+n4Bao6AVUodBqt7AtCy/P0SwLclBVlbHfpdM6\nYePjTVrbbZKhREk0ojh6OnYFeYaiKNi2TRRGiEwFBHEckef55IY4u+EmCMhB13U0TUPTVFRFQUqJ\noiioUqFg2Zimiaqq5HmGqgksy8KyLEzTRDcU/un/9cP/v8L47y1u2eE//W//lDRNEUKgGCoFt0C/\n35/MykpJFCcYhsF4NEYpKNx47UUq5Qq379yh3+8hFAh8H1XTSNMYnYx0lBF3UhruFG7dIrNSWn6T\nJ0ePmZqZIo4yKpUGYZCQ9GHQGSGEYG11DbNiEuUhiR/x+P4DLNNmYWkJ27YZDYe41TpZovGL/+1f\nsvt4k6WXr+Mul1m/tMY/+s/+p53fNAbnnwQRMB6NqDcaRFGE5/nMz88zGo6olCsc+rtoRoqMY05O\nd0DYqIqFpqmMR2Nm5xvYxYytzYA33vgL0kzwi1s/4a233mJtbZ31S0uMw7t8+PE+luWyuX0fMWzw\n4qUX6R8f8PYPfoSzYDM/vwj5ZEXg43M4OCDRQ6LMQy2oPNk44Mff+yGiJ1hZWMQPQn7yk3/BtatX\n+No3fo/Fb30F43+8ODTs80jTlF6vR7/fx/M89KrANiyq1QpRGFG0S6SoPPfcddxCkV/c+iGnoyc8\n99oKo6UG27eOGeynZHlGmqbPfu7TFaVhGqgY5HlOksT8siTr6eOn68jJSm7y+Onn/Gz5KPjlhPn3\nDD6erjIv+AxZlhFFEXEcA1C0SviB/2yVn6UZmqaRJAlhGGK4OsKBcTYiN1Omqw1OmseEUYBTtpFo\ndHePcdUSUZ7geR4Ns8KbH/yM3Eko1Bz22huAxigNKZdmJ6v2HPzAZzQc4qyUKFYKyFFEr+2SRbC3\nt4+Ugq9+9atkSH72/beZKVcpX9FJdYOpqQalUvlcMTh/AswzVD3j6Ggbt1ikUl5C14oI2giqlIwI\nP+7hi4BW2iX3EwhSag2DXB2SKQY/f/8J5JJxPqZ1fMR4dweRZ6TJmGq9wrXqG/zg7TdRlQKrapXq\n8iLF5QYH33tCe1/ld669SrVWIckz1Mwkjk7o9Q64/fZt4kTh8Y92GHWOCfsRSZgwHAyhb1BPy5Q1\nh1G/Q3FpGsPSzh2GLzOKVHGdBv1OSBKq4BRpBX3KRYPd9gaX5l/mxnOv0KjPk0QK9bkFfLWDzFXs\n2REUdQ5v9th/fEA+AjVXSEVODiRJgm4YSA2iMEK3FMIwgVRCLp6NtktFnG1lBUJOts1PVyxZliER\nZCInzVLSLCPLU0ScAfJsNSmRAi70rp+DEGQyRzU1EII0zYj8mDAMgRxVMRECdM2gZFWRac69Nx8w\ntTTP2urLdNpHKKMd0u6Y3cMWQua4BQvXMSiULXYfHWDMV1i8coUo69Ls7JFnGvWpGbJMZdBrIZMC\ny9evs31vh+GpZDUsUDVs9g/3CGIwDAfLMEjTkMXL6zz+4D7GfkTpxiJ5dMrlxTke3N5iuN89VwjO\n3QTRDB2nWsSuFHBrRfwgZjDwee65l6lUpvBGEe3TLkmWkSuQyQQhEwxTJ0oSHt3ZwN9pUwwFj995\nn/tvv8tsvcHi/Cy1WoUHGw9w7VkuXXqFw/0ev/jxhxQMybVX1rl0fQXTdKjZDVzLJMkzUKDdb3Lz\n4w8JRwFFo8Ktd+5S0er8/le/TcEsEfkpNbvK+uIajVqdhflZVJGhasp5w/DlRgjIJaZpMzU1yzga\nsXx5Gd0x8OKIkT/itHNCs93k4ePH5KhYVokwzig1pphemeO516+x9uIKhZqNND79c8vhbMsLTsE5\nqx/lz8qBT1dwk+0wnJX5foU8z0nShCAI8IMAz/cIgoA0zciypx/5RfL7NQhAqBKpKghFnNXyJqvz\nMAwJvBAyQZ5CEiWMWgOSXsDOg21aBy1uf3CH5kEXWy0ybPvE45zT4zbNVhvpKJTmS6RKRJiGCBSy\nWHJ57SUW5taQ5KTJiHHYozNooZsaaZxwvHtI67DJT3/8Ux4/2SJMIkxHQ9U1dnePOD5usXJlme/8\n1Z/z/OuvUi7X6O62KHA+h/9zrwDDOKITebiVIo+PD7jx1W/QmJ7BdV2SOKUf7iD1EEVRCcKAkADd\n1AmjgP3dDg13luuvXKLVbtM9bCKjlJmZGfbaTQzDQBoGrdMxEof7925jmWVOTvewd+6SZkN0K2a2\n6FJUDIJ0MlX9yYOH3PrkFq49Q6lc5LWXX8OJBPv3DknbOXbDAQndXhdzqKPrBqjqWfH8gr+PEGJS\ne1M1TNPAaegYZk6z6TEewuFBk2JxGtdpoGkqQnPR/RI3XriO7/tkwT5e94j1G6vousHOvR30sUYU\nTep9cRxj6Dp5nqMoCpqmkeWSycb3V7NdmqaTRDbJnKiqiqKqkOeEQUgYhkgpMQydXFXOttkJmhaT\npsoX8lz60jJZUBMnMbquo0gFVVPREg3bLkGmMhr62LaFVBV0kRKORsQy470f/ZQwiVBEThiMWVy4\nTBSFxLFPiGDPbzJ7dYaCrWN4Lv0e3Hjh62SmzkFzhygKULSALEwIoy4F16XX79IfJmy+e484jnFd\nl1rd5aWvXOfB3T2aRwP0QoWVK2WMRoHOBx5RNyUfSbxmcK4QnH8LLCXYBt3IwyNlMBpRa+T0ej2G\nwxFu0SXKSgyGQ6amGnTiU/B8vLGCyCzK00scdPaYubbCtHGV2x99yFtvvcXzr76C7/noikKW6kw1\nVthUdlhZvEav3+T2vfd4aeYKoySgaBpIJluj9jhm++CEN/7wDWTu4vmCcv0Sm2/dIWzFuHkR4Us6\n7TajYEy708IPPHJfkmfZucPwZSbPcqanp8myDMdxuHa9xu17tzk8bFOwG2SZpNPpYJtNSoVpdM0m\niRUCP8fQS8zMQRiOSQYZ3/zu1xn1h/i7Iaqikmbps7pdmk46gwBeEpFnkxT4NGkJIT6t6WUZeZaT\nZRlEEYpUSJQYISaNj7Nnfvb/f2kFeLEK/AwCgaqpZNmkMRUnMZqmoSiTN5AwCIiikF6vh2lZxEMP\nPc+wSwWCXoBpFVENizzPyVIFVWiUS3VkUaDWJYmd4Q/b6LpDozHL0sIVnhwd4o1iFCUnVwNyBFKJ\n8cddhIxJU4NCwUWRKrs7e+zsbmIUUoYjjZIzhem67Ib7pM0apfIMN//uJyTdlHbWPlcMzp0AVVVh\nfn6Gu3fuMBz26Pc7tDtFpqYaZFmMzG0MZYrnr7xAEIZocYmD7V2SOOT1b76K0HJ2h306ieA7f/Ad\nqrMFPvjZexQvVdi894jhls/sP1xnvXqd+ekGuV2AseTJR3v0GfD61/6Aa0svAIJcKJzkBwxn76Oo\nCVXFonW/ixnktE/baK7K0tocsZoT5wKjKdB8E+EVSEuS/HMFGxfk5EihYJk2umYQBhobDw4Z9DxW\nVy9jIOjvt7h66RqlWY27d7YoGA3K7ixRFON5bcbhiKJTRjVVFtYXeDLYIu/n6LGBzCRpFiMECAmq\npmDaOlEY/VLT5NPkl2YpIv+0m/w0pSnPJDCc1fxU0iQjUTLSNCNNL5Lf55EDIhM4uoWGwliJSXVo\nnXbw/DFVc4qyWyHLc7qtHq5tIzWJNAyqRcko8LFUHUVRiMIIwzbxlD6z0wZWRWU8TjltRuiqwurq\nEpV6lZdmpsjVkJu3mqi6hYogTFskqUthqo5ayikUijx6fwMvHzH2C/zkB7/gxouvMbtukQu4+eiA\nzuiQ3335G2j/8ev81I+IvfTf+Ho/j3MnQCklZCnDQR/ShKPjQyzbJgx9isUiRa3GaBQRBRJTLyEr\nGpGfcXJyDErC5tYGp809XEdDUxOcgsnlF18ktrtImRG1hty7+zGPt+4TxxFLy8skWkYpsRl7KQ9O\nN9BMC9CJgd2THaKsj605xGmMXbBIUsHq124wFH2cOYtR6LHz5gPygw7FWpV+y6O60vhMbemCCYpU\n6ff6SCSt0xYPd+4z7EcIoVEo2JQNk0qpgCCj3+8QRn1Cv0M9Nth4/IiUiJnZWRxcfvqvfsa3v/GH\nzE7P8v2/+SFhGKFnE60X5FiWhZQSVVOIYyBLf6Xol2XZs5og/JIOUAqkkH/v65Isy8nSjCx92g2+\n4O8jAJmBqqsgJUJmpCJHdwxikZytxCWGrmHqJoph4FRKJEnCqNUlCH08f0yeZZTLZWZnljiKI+aX\nynS7x8RDePL4iPX1SyiqxsgfsN9so6oaV6+8SK9/wqjfI4qapJmDUXQJ4iYfv3WLLM945cbLvPHt\n7/L9f/FD/LHHxsZN0jxHkRKvf8g4PObq669iiRr/5H/+J+eKwRcyRL137x55nlMqT1rQw+GIpaUl\nVFVl48kjVF2lVCqS5TmDbps0TXAchyiK8YOAhfkFisUSg8GQhw8f0u+ElHWNtbU1ggchpYrO1v4m\ngRcQpwOuvVrHmZvh6HDI7EoDYUOSQb8Pjz/ewI7n0fsafqJQLc1Rn5/nUbaNPxhQn67jSNh46yHj\nwEfxxuzu7lJ7bYrfwtMA/1+hqgpBEDzT00X9kPn5WRYWFikUCoRxl+euXkdXSrz54w/o+cdohYhK\nT0fIMXEUsNy4wu1f3GHj4RP+4X/0V6xfWyOMQ/7ub35EnOQQTFJTkiTouo6qKNiWTRAGRFE0WfWd\npa9PmyJPk99EQiHkpFapqippmhLHZzWtM73gZOt8kQI/Q5pRNGwSUyXRBNHIRxUKAsHi/AJpXxAN\nYyzbojHVwLQM9o/2MHQDKQWWbROnIaqqIaVkNPIZBRmSAnu7HY72x1QqVZIkZjAYAJ9Kb4QA27aw\nDI39gyMURTIejTja3WN84uO6BfKB5Gc/fJNur0On06FQKLCwtITqCAzDwnVL3L11h8P7PRzbOVcI\nzp0A8zxnc/MJlmUzMzODorn0+32GwyH1RgNVVUniiXJ8+/Fj0ijELRSpVCq88867FCsWv/eNb5Bm\nGa3WKYeHh1hqhUq1SiFSKZVKxNkARYso13VMO0N2FN57+yOmp1ZZu34JQ9oMPNjcaPKDf/avaJQt\nVF2S2TpT6waHow4bb95Eq6tcXm3wyYO7uCUXs1bDrVYIo4Dtne2LLuGvQwgKhQK6ppNmKdevXycl\nIUszCk6BYllhkPXY/OAhe/cPGedjQnNMqbCMZU5hWAkbjzY4bba4euUK84vzzF6d4rvqG2w83GDz\nzjaWNjEefqo9UxQVVRVIZbKqC/2E7FnyOtMG/lISfKoBnSRPlTz7VCYjhEDKX9YMXvDLqEJiCEkg\nMnxNoTcYUC2WcByHHFAUhULBQEpJwXVpd1pIIdF1nempaYbjIcXKDGEYEkcReSYIPMH21glHh13C\nwGB+YQrP89jf22NtfR3NKuAWXIIo4fKVJbY3n1AoFBh1U466R8hEoaY1WJxaZPPmFt2gy+qNFbIM\nim4JckG9Uefd999hff0KG4+6+M0c1ymcLwbnDd5oPMYuLGEYBoViGTS4ev06ZbPE9p1HHB7toTsm\nfbdLOAoJsx61uWl6x322H2zyJ3/+xyzMr+N7Pjdv3kTRdOxpDdcyKRs6dk3y/jvvsri8yJXLVzk4\nOOTnP7tP5IEzXaGYzJFgc9CCHgNWvzbFxvcfMqfNklUTeloPNc5Za8yRqAmtj48Yb7UpGEWWL12j\nF/oc7rcJPgnJk4smyOeRZxlSUdAtA4EgVHwajSk0VaPT6aDlAcN+j5sf3KakTVPUKvg4yLDAt7/9\nZ+yd3Of94TZWRVKplzCnFSLAcA1+/49/l0H/FG83JfAjIIcwIFcnW9osy1BVlUjEZFl6pgGEPBdk\nmUBRJn1iISW5gCiJJ/LBHBQpf6WGmMQX1/fzUBQVEoGSSfIgQ9dVvGBIvV5na3uLGXeOilkmGI0I\n45DYGzIzP0Pg+SiKgqsWiElRTQ3V0IiygFLFYHvzAEOr4tYcSpUquZCEYYSi6QgR0243abePCTwP\n0zJw7Aa9lsfM7BxLUzX6pz1G4xGylFO2XepmlbgYcPnGEp1+H5lZfPP1/4RaaYb5BUmoWRBK+F9/\n8xh8oS1wY2qWtbV1pBQYpZRCUSMfhTz66A4jEjJdUHUrqJkCjsbOyWNOHrcpFyzWl9aolecYKUOK\nTgPL6eJUdZRU0u/3Mes6s4MrjE9jHnx0xOLSMsq1hOHghOr8NAtLVwl8aHYT+soOy1+v07p/RLYT\nYOYmYXNElOfMzszTarV4/81bECfopZzHrQE4Ju1+m6PxPkmYfJEwfKmJ02TSxNI0puamWFlbod1u\nkwGj9iHt7RYVt0S9Vmc0DliozzLuddl//ISlSzPsHlcxVZW9/T3u79xiMXkBITOm5+u8/OpzfNR6\nQhDExElCkmWkYTbpTqoqQghURSKF+FQGgyTPM/L86YTIRCAYJwkIgSIlqqo+G52L45g8n4zbXfCr\nxEmCUywDCcGoTxZHDIMh5YpLtVaiUHCIgxiIicc+xYJFFAekeYLrOIyjgDiLCaKIJElxiiaaGjHt\nzKGqGqVSEccxWFitkWcZo9GQfntE4I1wrALzsytI1SfwQzr2IcWii+IahOMRw6BL40qZ3v6A3cdb\niBJ48ZAgGyNykxvXv8kHH/8d7f4WZfMyhXrpXDE4dwI0TZO5uTnSNMUwLBzHpNVqsfHBEzzfI9Ek\no9BnOBzy8ksvo1dV3nr/RzTqkuJzBoWiMtENJTEIqLhlXrv8EuQ5j0438IVDo7bCJzdv49oVFGrY\nTpO11SuUsjqN2hTkMPTanAw+Ji+GrL2yxmbwAC9LSQc6FbvEoN/HNE3qjTq2rpN6Y1KZ0ffGXLl6\nBc8ecvjO3nnD8KVGSEmpVKLb7RIEAeXE5e2332Z7e5upqWmIB0RJTLFUJPB9TFMjFz7IiA8+eYub\n9zN6/T3W1y8xdWWaR588xDJdGoUpOu0RraZPoVAgjlLG49GkfhfFcHZetaZp6IaByAVRHJ3pB3lm\ndqAok0kP8nxioHC2FTaMybYtSZJnP+eCz0GReElIHMfMFqv0ghNy2+b4+GRSnysVGWZjEk1imgUy\nKdE1HXIYDAaUahWiUR/btknTDEUR1Gp1up0uhqETxSFFPaFYNrAsi9Ew5YMPP8T3E+bn5wDY29tl\nMByQ5zm2bdPrdHn08BG27TA/P8+f/Od/ys7jbfb290l6KUEnhCq02k063Q5xGrN4aYqpxvS5QnDu\nBCiEpHzW/NB1nf6gTee4zePHj1lrrBMbkoY7g+d5CAGV8gyzM5cYiX28aMje/kMi3aRSLlGtVRn1\n+nz/f/8BoyTk0isvUphdpGCr3MhXqNVrRHELoY0Rqkn3pIfEIPCgNzgmVbY5Pj5FcWe58u0VFK/M\n6RMfGQh83yNOElRVoVh06QceuqZhSEG92oCpCsqFEPpzSdN0MhYlBGPPYzAa0u/3sR2bOIkZtluk\nYYimGSiqRppHFEsF5hfWGI1GPLx3l+5Bj9udu5DmWCWLvf2HJOWYD967xf5uh4peoFKZKHKDICCO\no4k4N4pRFGXSHRYSVVPP9IACVdXP6oXKJFkCnDVINE1DCEEURmdOIvZEsXCxAPwsisTPEmyhYoQZ\njVqNk2ELKWKklPQjD1kwyeKIMAXXdlB1nVarBTkYjoWmaYRhSJ7neMOA2FSZnpmm4BRYWVlm/3CL\n0Ne4f3eDTrdDp9Pn+KRJpVKh1WrR6XbRdZ3VlVWkVLl78z71eh0hJAWngDDBXXCwugbD4zFH201M\ne5flheeo12p8cvdDHuu3CKPlc4Xg3AlQ0zRe/+rX2NraZjwe0W1F+L2Q1ZU1TEz8KKJWqtM8OeHN\nn7/H/OE+p90D/H6Tb73+VT65fRdxcoipS7qdFndu3WL39jYLl1axpU1EwjjfRi2HmNUKtnRonh7w\n7kdPeGX1L5AJ7Oz7HJx+gj4LftvHrcQ0lmfxdnNG42Okp7A4M8Px8TGKMGie9jFMF8VMmZkyGOZN\n5Nj81Krrgl9BURTiOCbxQ8L+iEHbQqIwVZ2m1+8T+JD4Obkao4sAvSzxkgHHJztoUuIaFn2vyGjP\nI9QCqtcEQ3+IljVJ8ohMpMRpjFsqMA7GE0OzdDKOlSQJSZYgFDANYyKDERl5KlAU/Zk2UJ7JYICz\npsfkcZImqOrkzzuNM5SLTv/nkIOAIAqIohFW1aCkFolFilAlhtAxTZud4QFRLojjlEqpgkAwHo9w\nwgLS0p41nUzTRBMKWQSKoyJSlbCv0RkP2XnYIYxCCqbF5dVF+p0mbVvHVAxUXSHJfX72f/4EP/T4\n9n/xl0ipoEiFwWDAyekxqUhJZUp/NODw4JDhsINjFygXZzhoHpCfc5F/fh2gkHz4/k0ePHiA67oo\nYcK4GWKYBuPYBxX8cMi15y5hmCbbG3dp7m2RpCn/bPsH+JHPeggKMZuPHnNwsMs4iAmHHhUM4hRO\nSgqjIKKs6WSJDh3Bk7eb/OVrL+MN4d6TDW7e+xum2ja2rJIofcz55+gEh5hFSbXRoN/1EYaOpSr0\nm20iaeCnp1Qsn8XL0zhi6WJI4NcglImhgK3oeF5CNIwQmsqw46FJg0ppkUHcQ4YJVcdBUxWOd484\nau/gt3uEo4yGus68WEbOphyq26RCY/tgl8a8i2ub7N48ZO36dYyyxsMHDzByHTIIo3CSCLMIFANV\nkyipIAk/lcM8lbmocmKh9VQG4ycTRxNN0yAHmUoMzfg3v+DfMiQCmcR4qU8uoewZVCkzFgmDMGR0\n2CE3x+gpFAo2eQpHB0dYtoVVM3Fsh2EaUCyX8DyP0XgEYU7iw6A15sn9HWSaMRqNEGGCo+rUijMY\nps79e/fRZjR+//d+n5/d/hEPH32C40OjMsPU1CymZiCEYO9gl8HpmDiLoZxRXilRrZT0HOsVAAAg\nAElEQVR49xc/olQqU3FW2dy4w8PN7XPF4NwJMEkStre3yc7eiZunTaIwAAGqquGaAa7egwiENJgt\nOCjaDI/3HuM6BRQVFFXB83xUVZ0sl4MTxt6YVqvF/tE+L37reeZmJi4hB3sHCEfj9T/8JrOX17mz\nlXDY3McPenx8c4NaeQHVgN7+u5wen/LXf/XXGKrF8WGTufk5hsMhH7zzEb2DIZ4fYxvTrCw8j9//\n7JD9BROiMMIbj9GSnKmZKXLHYOCP8TyPQqGA7/s0GnXycUAaJeQnMK+sEsUDhBbTyo6ZnrOZa5QZ\nBUO6TUG4FmJZFieHTSQqhYbD9NoU7kyBreNN/FGIoRgYunE2I6xORq2yDCkmW+UszZ51hQWQi0k9\nECa1KUPRsG17IpMRAtd1L+qAn4OUgiRNJ36LmoaqTdKBkuUYik7gjQhDKBaL6LpO6EcTY9LBgNXV\nVYyCRed0gHJmVaYoCpqp4nljpKIggOb+IXmeo6oKMpeIvEwSqkzVr5NGZYIgw3UL1Gp12skmJV2j\nWq2gCIXhcMjxyTGj0Yh6vY7rFjna79CYKnDr9m1aHY2F2XmuXF7i8ODwXDE4dwJ8+g7bcBwGgwFx\nEpMDvu8jZMis6eIfe7S3toiSiPAgwBoZrDpzVMwKPWtMJDK63S7j8Zhiscj83GQe0TAMwiCCzOXK\ntTXuPfgIp5STS5drz7/OEMHx/j47hxtUqgaFwjIim2LYbFIt1pl5YRpn2mTnZAd92cQrDshLCb/3\nl69x559/wum9fRy7hm1N4xpMTBEu+AxCCMIoQmaCDIUkjomTGNu2GQwHGMZEH6ipCtHYZ3lmgdnq\nPEdPtrFThcZcncvfvUzTP6LzSR+1VaDf79EoTOO6RdoHHULVR7gwtzDD4tY8ozygc9wlJ4Wzed4g\nCCbmp6pKLBLCOEZRJkkvSzPSJD0T1wryLEM1rEkXWU70hAuLC2g3v5Dg4UtJlk6kRmmS4BZc8iAh\nzTOK5SK2Jjk68BmOR1SNKmEYEoYRtUoN0zTxPA8/CcmyjE63iyIlUpEEQYCma5OfrWnU6zX29vYR\nQmA7YOCzvn4Vy7rE/Xv3+P4PvkdxWaNSKU8kVprOYDCgXj2rAxYK5CLFtEycgs30bIWHjz+hVDEY\nDIboboK9kDK/6sJ//5vH4NyFkTRJJ9Y5UYymaJQKJSzdRlcNLN1CDV1KYpEiC6TdAsa4gJ7qzF9Z\nYWZhhqJaoHfURyoCu2CRJil+6E3s8W2DxeVFnmxtkiYp4cgj6I/I9BzFMWi1PY4O95hbLXLlhSsg\nJ35xy/OLzE01qFQr3H50nw8efkQnP2W3v8VQ7aHVBY31GqmR8GRnk16vj1sqYhj6ecPwpUYIQXZm\njRQmMVIoZHFKnmQkQUzBdFAyObHAR8GpOyRWSGLHyDnJ+reuYKyVaek+P/r4Q3SrhkgkvjdCUSHN\nUwxXQ3ck0oTrL13mO3/+e9SqRWSqkiAIw5jQC0milCw50/kpAiFysiwhSWKCICAIArIswzRNhJAT\nP5k0p2y5rMwvI+WF5dnfJ0lToixBs02CJEI1LTTTIolTTN1kbWmdPMoJxmc7O01hPBrieWOSJOb4\n6AhD09GkgiIEWZKSxima1EjjdPJ3oeq4pTK2XcDSLPR8RLt5j3bnLuVGSJZ63P3wLpmfsba2Qrd7\nysH+Pr3hgDRNkICiS2Zn5jCEyfLsCnEYYeoGczOzEMLBW02O3/p3bIYghIRQ4IU+lmUhIp2pYpUk\nTRiNx/htn2rVxdQ1rLrOfK2GX0ngj4q0Hu8TvRVSjir0vDaFogOnKZmMMAsuhq1QkQ6D8TYP7n3A\nxz+6CaOc6396iWqtRu9WGXXwCfVXfSiskN/fYXi6iTFToWUIquY8b/7Ld6mtVAgCj4LjUrBsOl4f\n47kq35n5LscHB7RG25in6mSk6oLPILIcGaVESUIiE+RpiqmZBH0f/Bz/ZETiJ7hFF71cwg8jhsdD\nwj4MZxMK9REPfnyXo40+8tCkr4akZYk5l6CVNBYvrdBrH+F7A5LY59q1NY6OHlKbNbHyGh91HmKn\nAifRSNKcOI9QDYFpS8IgJAgDFKGjCP1ZA0RKBalo6KhMmWVeWb5GTSvDhRb6syiC3DUwXZdut0tv\n0Md1SkRByMhrc/zwgFKxhK6oxESgZGRJhlMwSNMYVeZoKei5YDQcoWoaBctFBgp6ahD4IWNVUKzO\nEnWHmJmkMso42t6lJ7oUF2xkz6B4VGJ7b5vhcIRV03l47wGlhVlmjCJKnhLKmJnGHPrY4OCTFieb\nAceP9/mjP/4Oh7uH+NspijjfIuYL7QvyM1+2Xq+HyaQbNJm9zFhaWmR1ZpHReMTp6Sm67XDl9RWa\n5ik3j8fcufuES69eJcgzfN/HdV3SOMd2bMbemCD0uLF2lfff/ZjOsM+3vvYHrM2ukQ5VvGjAUB7R\nfHCbWES4rst6Y45TI8S6tsSKuUQ9eBPrOKbglamZNUpBldAP2dnYIcozXrj6FcZhQKfV+SIh+FKT\npimO49Dv9wFQFDk5BCfPSZKE9qDD/NTc5HyPKGI4HKJGgiAIyYYRj+61+ck//RFpoKEbZXIrY3V1\nlY3NX7C6sk4YhozHHuPxmEajQRiEbG0cMXt9jit/8jtU70zxi799Ez/2kYo4ew4GUkykLs9ODRHy\nWR03Z2LUoesGK8vLTE9PY5rmhefj56CoKsVikdFohGEYJCLEdQsMh5OafhxPzGZtpYwXjVDkxDlp\nIjfSKZVK+L4/cepJU9I0I8kmtmQTb8ecjBz8GFc1iAZjVGeammuh+j283TG2b+BQR7UUul6PU++Q\n0/YpO7u7ZIUqu4/3edzcZ7znszC9QGom3LhxAyEE/V6fUqVI0TFIkvMNM3yBLrBgMBhQcAvk5JNh\n5DOfNsM0CYLJMPvBwQGGbpLVNbqiw/Z7nzDcHeH7kk63S1z2cTSHRr1B4E9uolarTbnsMtg/Jh0H\nvPLV36G8vMBwX2Hh8hwtM2NoHuIUBfgaWpaxv7/PqeKxeHkdXdd5/pUbnB72OHinyX52TLlSIQ1D\n3vnJjyguzlL66wU6YYjf7V7Mif5r6PV6z24SXTcYDoeMRqNJlzbKUNVJB7bb7TEYJJSVAkIomJbJ\n3sEhWXcy+laqF5laqzE90+D+RkK326NYWOL0CKanp9nc2qJaqbB1/4RLrxYJF4b8/tzv0Nreodvq\ncNI8JYpCsjjBUCs4tjPx+0ueTo1MZDuaqlEqlViYmaNULqNpKqZpXCTAzyE5S3BCCOJ44qlYLJYo\nlUqTg6wGGSfHR9jTJl7iUyuX0TIVbzxGnB1u5p/pLV3XxfcDkjRlMBhgWRZhFKGrOgQxhmJQsl3q\nMyUsbY7Dx4coicb+YJOphQaKVEARHHf30DSLMAjY6exw54O7YFh4RQ9/zgNXcslZZzAYMByMQMmZ\n/Uqdk+bJuWLwhcwQVEVl2B+SZRmtUQtTN4iiiHKlQpbkDAcD8iRhHA7IEoU7H7zHrb/9MXo8R7my\nQLVWwVmd4fb9W1iuixCSKAqZatQ5OtijqOfsbG5hVmeJlAQrdpkqzPJRvIFWDrly/TJ+Hx7dvA2q\nRvfhHubLY8orJaZeu0Z6t0nv1ikPHj2kWOxg6xpTWo1eLyAJMwI/odNpkaYXo3C/jsFgQKlUolQq\nE8UTbZ0UcpJopkqYlkV/MKDeqBOGI8pWBSLw4wHt0xYz9Vnmr66x0z7GJ+Dw4Ai74JCTARmXr66y\n9eQJpmGTxhCFkk7SpqccoHoC09VYm17l63/4DfqDPp2dDqfbTaIowrAs4iCZnE+japPjEw0Dx7Sw\nDBPynDTLeGokfcGvIpXJzLTneZimSaJk7GxucnBwQKFcxCpYJGnCeDgmN3LGnoetWBSKRXzfww+D\nZxM4/V4fRVGRqk52Vm/I0wzSBDUFVQgMTQPZo3V6SKNcJ+kmvPbGVzDnTXa2ntAdHFJdKDIip9/r\nofoRi/OL3L+/S74uyNWM0XBE52jyfKv1MkLLCVQfWTyflOPcCTBNUoqawzAYkiQ5WZSSpAm1Sm2i\n48okx7vHFPKQk7RNUdFpbR6QxQ5KklOelljVIvPuPHezR4R2SqlcpVi2ON3dxMhhYJUJDAM/PiGL\nnlBw59C1MsPgY2wnwJULFCsavdmQYWHInJ/w85++jVOfoq9ETF+p07l1jFO0QMnw/IjywhqzL6u8\ne+tv8Y58XvrdVfxgdN4wfKmRQuI6Zcjks+SnGRpmbfJGVyrVEIrOxtYmS8vLzNdm8cOAHgf0TvfJ\nbI+pb15ibmmN449iPA/aDw5RF1x0R6d3sM30qkm2m6OZs6z97svkf1FGKz7m0pzOzbd30acMNFUy\nu7bEX7z6DwjTIT/8wT/n9rt3Od5sInMFWyhYtolhSrQsw4kEZiLJU/CCEC/wSc+5Rfoyk8YJ3Vab\ncrlMtVJhP+hC22Mm19jtdrCmdbSiAj2FmWuz7HV3idScVFcwCzZeGBKkkCQZaiqwVYNEaii5gtf3\nGI/GJKrN3OwsaQ5DcpxBTjRw6DsFlOmAtZcvcyi3OD7ZoixSRKlBVxwzbrao12vYC2Uqox4zMzOc\nPu6yvLpCuz6YbMMrKoPegNbPmiTxv+MEKIUk8APGo/Fk9GgcYpuT81lPTo7JMahLjTjPqUxP0QtG\ndMcjjFKRtemrdHtDkjRl8/EmqqIRpyGnnX2WanN0tpuUnQrrl69iuBqWnVKrlVm1F8kySZqGZGlK\nHPlE0YA4GVOuOlgs85O/+z7vvf8elZVZmienbG1vUaqWCMKAPBccHh3hzGsEiYdj2Zw2exN79Qs+\nl6cGo2kSYegGe3t7Z5qsAlmWkZDw/AsvkKYphUKBk34Pp1ymXC3iVGyiOKdYtlherRN7GTtbKcVC\ngVLJ4mh3QOhnRH5GkHnUG0XGogLqFAoOK2sN1hauITLB8XGbTnBMpkTMXZ6lVCyzv3HExvv3sBMV\nVdMmc+XkkH1qf5VlGb7vXVzjz0FI8Wz7u7q6xunhR4zDANMxoTdEVy3cYpHeQY+6qDA7P4c/CCcy\nlywjyycH+CmKgmk7iGxyjIJlTs6KzrMcLdeJ42RiojoaUnQckC4H/UOWVqtstn5BP+pBv0AQO1iG\njYiPiKJo4iM6GtKYbjA1NcXJyQmuU2Fl/RWOjo5otVocHvTYe7hF0a2eKwZfqAny1KEjz3N0w2Bm\nZppOp0OtVmecgqmaFNSEg+iE034fXItrl66wXF4lurdBu9Uid1LqjRqGK2kNn5DldbodH0tOUa/X\nyZWQnCG+77P63ArDtsb6+iUeHO2xtXOfdvuUHFheexFcjfW1dV566SVKi1P8fOOdyZhUPjn/QNcN\nFEOlXLJ54dLzqAMDjwBNNb9IGL7UCCFIkuTs0PEcXdfRdZ2joyM8L+b69RdYWVnh5z//OUXdQtc1\nghCyscWVa9cJkw5ZHtPpb7I0u0qWLBKp3bMbL6HTjog9MNWAd9/7O8Z5l5m5EifH+4Q+XLn8NeYX\nlmn5bR4efUhn0EbkKstLqzz3wvOc7h3ibQ/QDYmmaaipQpJOzqR1Cg5+ENDr9cku6ryfYTKAsIKq\nqvzt975HdOJTnppiLDLMvoKMUkzToBdN7r9SvcigPTpreKT4vg9SwzIM8CMURSFNJo1QTZtoAV2z\n+Gwk0TItZCbxk4DYDdljC6XZ4f5PN/H2bXRzisvPl1Dak+9vt9skcUylUGNubo5ut0un2+LajRfZ\n2X1Imo8puBrzCzNo6vn8AM9dGZZyMnheKpUwTZNKpUK90aDX6/Hw4UMUyyBUcjreiI4/JtEUVq9f\nwSgVsGpF5laWWFxYpNfroygaqiZJ8jHN5hGaYhKHCh9/9DH37t2l1+szHAwpWC6qqnL16hVeeOF5\njk/28IIOQoaMgy5ZHlOrVbEsG03TeeONP+LK1ctUahVeePEFFFWhWC7iui5BEDA3P8/S4iVU9WJK\n4PP45cPMn7qrCCGo1+sYhonv+8RxxGAwONPfQalURJUWrZOQD96/z8bjDQ4Ot4nzPnfuv4/neUg5\n8fvr9UY8erDH8vIl5hdn8MIOupXRPOnT7yYUXJNSvYzu2lx5aZ2j/hP2O1t0/Q6ZmaCVFC6/cIlK\npfIrJqhPn7vv+QS+T5ZfrP4+lxxs28bzfaQQyCCm6w3xVNCEwrg7wPMDhICd7W3GY480Tel2uoxG\nI8bjMb7nTYYgzjrBTy3ITk9PEXIyhWOaJt1uF9u2qVXqWK5FbAQE7pBWP8c/KFHOp7jxrTW0eow3\n9hgOhxiGwdLSMo7j4Ps+hmGyt/+YONshVw8oNzymFwTf/NY3J2ap5+ALrAAn3TfbthiPFUzLJshj\nGgszxElCIcsp6g7H7S7zpTXK81OUFitE/oAg6LLrbVOurjC7voJppiiazn7HxEqbLNWW8LSIcXsL\nygU2ttv81df/jFl9lqa9yWnnAf3jDr29IwpTNmEWcjzuIP2crdMDvtNYpuIusdfd4nT2mIrRYGt3\nm7gScel3V0hkjEgFvaCDbqmkaXz+MHypyUnTECktFEUQRzlpkrG7vUfJLXPlj6+z2d3kxa88h9cN\naDc7dJUuK9UZrKLOvr+P5/SpTK3zzat/wdHuAa3DfXwtojVQOdj3ef6lWZyXHKrCoHmqc7jXYdQe\nc+3aFVy9wVJpkWQcs//JYw5vP6EyP03oe3RHTVQrp2u1cW/Uad/sUkptTHRQBXGeTD5IziQyFyvA\nz5ALHt98gqIqGIlJsQgdz2duZZG2H+KfRkgkoQwZ7g4pGy1SUqpz03hZgirAzCGPEnqeh2WYGIpK\nnidYloZhaLQGLVzXZWFtAXLopILjoIkf7mMfJBw98CmvTJFnEaqV4Bo1XLuA5zdplC8z7OXoElqn\nh3j+Ca+8dJmjvSaWWqDf65HE8v9h772DLcnu+77P6Xz75vRynpxnA7C72EVYgAgiJZIiZZEQg0iX\n6JIli07lkqtku1SSymWTcplFlcu0BFkwi2AQKTGIAAECIEAsFgtgw4Sd9GZezu/mfDsf/3HfLAbL\nQdi3ABaYuZ+qW6/v6X7dfX+/e0+fPv37fX80FQXHP1yg+5uIDRiUwNzY2MQwDPpun2q9xsjYKIWR\nAvvbOxBJRkbG6LX63Lx8izu3ltne3qbVqdN2KmyXl2g7NUIZEDQd9HWHbqNJfKHA+GPHyMZS+O2A\nVqnP8YmzCAVCemztrfGpP/sUW3e20FwNS9iEDnS7LgGSZqtGv1ej0txm4dwRCpN5VEvDTsfZ3tpG\n8TS8ZsDLX3qZl59/cVgW8xtw97Y3iiLCMERVBtW/HMeh2WiysrjK6ZNn6LhtKq0S1VadMIpo1eoQ\n+YgwhuKNo4QxAr+FjFrYepKklUKNNOZmpznytmNoGWiu3SZTamALA4HgyuWrdFp9/K7C4tUtPvmH\nX2H9hoPf1EmocfyuT6vapFyp8MhTj5LKpgbCBwf5v/JA6URKcB1nWBPkPsgw4tqVa+zv7JO0U5ip\nOEYoSaOCqeEGEW7fZXxyHN/12dnYQRca5f0KvV4fXTeI/EGdH13XB4rcB1MmmUyGeNxmdW2VRDKB\nH/r0+j08QlLZNKl4ln5NkMvAxacmmDs5T6cep7YXEbNMOp1BeY3SXplms4mUEYIQkPQ7sLy4w8Zq\nmY3VEmbK5t0ffM+hbPAmcoEHQpPxeBzDMHj5lUuMjo0xNjY2KHhtWa8VvM5k0sTsFLuVEoYRMDGV\n4dn3PkXba7G7U0IoCqIlSTuS6SdPoBTTlHdLpLsGMXROTS5wfOw40oPnvvBF/vC5P6KYTGP2Jb09\nl2NH5qk7PRr1Jvl8nttLl9jZu4Wi6yzMHaO11SaVqhH1Jf1Gj5tri+TzedJalpXbd+h3DldU+cFn\nIHF0V2ig3+sTj8cHc79IemUHOoKWbJGbzTA1O8vm7duUy2XOHX870s+wubNDTW+xHawgXY/ObpLj\n757HlxuYQYRTCdi+vUj81R3cdg958RhBOBAyXVxc5LOf+B9xuiHHj53ENNK0SgEXz5zAcRy6e30s\nYshIkk6n6dbqKKh/pQaw5w+KKw15HUIwOTVJuVxmYnICaSjENYPK7XX6GQVfEwSNLlPTU5imyf7+\nPlOzkwdlTAfTGCKKcF0XTdPQtEGN4SAI6HW7FEdGeP/730+z2RyI1ZoGCpJWq4uwUrz7ne9BKLt0\nmh1qJYdquUPLK6GnXBKJBJqmMTs3Sy4dZ3X1DqNjSeqNFpsbu8TjKS488cQgmMpQ0TKHG8sdegR4\nt1i1pmmYlsnjb3sbuVwOVVWZnZklEU+wtbVFpVpF1TS63f4gRjCTJZlM0XNqNLtLtLt7aJqC0Ayy\nZ2ZJnJqh02jQeeEmq5eXCVoRP/rsj5OxRgg9uLW4SDxuk8tlOTlziniYwK+FKF0NQ8ToO32WV2/Q\n6KwSiRa1Wp2VlRUqlQox0yZqwv5yme5ej/nCAk+ffyciGsrB3I8oConFLDxvEOxqWdZApdkwKBaL\n5Mw8ty8vsXjnNuPHxpk9MUsYhszNzhF4ATNTRY7Optlb3aa2DrU1CysoIHsavXqLyuoWl/71y6x8\ncp/WVhInmGG/VEfKcKAIoqpkiyGnzqWx4n3Gp9IkTBuv7tPa71BeKzOSGWVldZkgClAOZLEkg1Gr\n4zq4roPruMOnwPdBRhEnjh/HMAw2t7bZ7zVJ6hZqq48nItpen3qtRrvdZmZmBj/wqdVrmKZJJpN5\nbd71rvK2OChdEIYhqqbR6XZpdzrIKGJhfgFFUajWKmQyedy+xuKNEu1qknzqOJalMzmn03dL2LE4\nIyMjOI5Dv9en0WhhGPqgKt3mNjtbNZLxIkgLXU+w29ql4lYOZYPDzwFKSegFNJ0Gbs/h2JF5dmVA\nYaJAP/IpRS38Tp20EDR7PUbPTBF2XZZvr0A4h+NHlBsxyuUWx2fG2Ktt09gqwSdcZNnHqGvIfIZT\no6d5z7kngADfDDl15DhyrwdaiJXLouhdzKLPeG6OBfUkPX+fF776SXbWW1SXTOrNz5OZTwKS9atr\n6MclQTtAnUrhZi32qsvYGfvQZniQGcjND57m6bqO13VxnR7Z8QyFIymadkA6n2Fx9zK64bK7fYdy\nvcQjT56hEbbo99pcfflLzM0fZXZmnjBQqFR2sT2Dd8z8TaLp32W708NsRWTmRugl4eyZxzh24nHq\ntTLC3KZVq9Guu1hmgmQqx97mbfRCgun8HLlUhbK7R+naOsluip4CnuqQYKAGoyqDsp66NInCYQf4\nevSYgZtUyORTmPttPCcimBulGUZEKzVmjDwrtFm+tcrJkyeJyyy7N2pMjR5F60n0CHTTJPADoihC\nVSNiVgwZRfi+T+T57C+t8siHnsWPQlp7ZdAEqudzLJ2n3GxzyV1mRhnh5volMkaMVDbCzJjIKI1l\nJQmDNgnDoHWtQ1eNY9p5esE6vagEZp52R/Dipz/Dk0++/VA2eFMjwNAPiMKQXrvLrevXUIQkX8yx\nXdklPpHn+LmThL5LrVFF1QSz05NcOHeBRq3N7mYDJUwzNTaPaeiEQQeTiOriLr39PnYqy+zcaX7x\nw7+EKWwkgkBEhJ6P3wkJJdS9HvnZPErMp+u0uXnzEla8y8xcgpgN/V6P0A2YHJ0kpsfYK+2z1yvx\n5AeepnBkhJJTph7VkOpwfugboWkGxeIolXINBYW4bdPqNah3q2hFQSto0Kw2kI7PzStX6bk9GmGb\n6+vXiGUMnnjnkzz+jkeQhkdkdIn0Lqpv8eG/8Ut88IM/gTcuEXkXe05h9HyCWKaOGW9x7sIxRoqT\nVMsehp6n3fZp1DtksjZmVidTyDM6Osr5x8+R0C1EH1R0AhG9JoygauogXi2KGJZG/6sEQUC916I4\nXiQTixF3BRgmftKmvd8gJg3mZ49QrzSoVxsYSoyoL/A6Pv1mFx0VVdXwfB9NH8QGIuWgnnMYMjEx\ngWarXL5xiUgNBilvCYtGs44IA3q9NiMTOcy4yuzRSYQZolghqqkSCRVFF0SKpFH26Zd1ol6Kxx9/\nN0+983GE0aXd3+PajUtUt3bpVxuHssHhM0HCkEwmQ6fTQUpJLGawv7/Pyy+/QtvrcuLiI5h1j6tL\n6xx/7AK90Gc0nub6tRv0+30uXDyHmVTxwzZB1CSWUhg5XqSV7FBaKqPlFH7yJ/4O42OThKF8Lcao\n0+kwNj6Go/UIPCgWsvSdMrvlTVAC4imIJULGxqbYMH1Go0miLcHe2j7mqMXpk49w4ew5tre3qdRK\nBL4/nCD/BgghOHLkCLph0Gg0aJfr5MdydLotlpeW+cBP/BitRgfnksPLn7/M+uImx06eJm7HUYVG\nrphjcf8qUTWk7/XxnB5O3yUzMo+qK/zwB3+ej1/5Szqbq5CSlPr7iFoLT+6zvj1B6CawYyky6RSq\nKkgkUhSyJk7QYrN8m87+HkeyR4gnErSlg2Ho6IGGCMVrCtGmbmLq5oGY6pB7kUFIp1Kn7Xjk4iZW\nP0B1Amzbphr0aS/f5sTxU8TjcV599VUsaRMEATdu3mDuzAzJYhxFG4S6nDlzhnK5zMbqGq7rMjY6\nyuzReZxkgGno3Hj1q5w+f460b3LlM88zk02RTKps3l5FTGc5duI49YkEm1u7KChomkqv30OVNt2W\nRiZdxPcjwsjFTggSms3IWAq3q9DcmyU45BzvoUeAdwsnh2FENptlemqaifEJWs3mIBjf1Fku7VDt\nd7Byadr9Hvu7+5iGyTNPv5NEwiaVNlBVj16/gmGHxEYMtIxCrGgweXyMRy48AhJUcbcE4kCdNpPJ\n4Hke2WwOpEAVA7HO7a06L355ibWVJqXdgPVSiVQ+QaZXYDo3xeSJKUYLCzhOQLm6xZ2ly9Rqtddi\nx4Z8PUIIXNel027jHqi9pFJJxsfHmZubI1YwUVIwOTHB9q0dxtLjvPtd76KQy3FkYYHt/S16oksU\nCwhMnx51YrZB0p4kHo8R1wu85+z7KcgxytcrTOjTaO5pTL1IRBPLhunpacbHJwgAaAUAACAASURB\nVNBUjUK+iGVphLLH6tpNJF2SOQvHc4jFYgOJfPVrX2lVVQflMTV9KPt9H4QE4YdEmoJvKpgRbCwu\nUe+0GDs6R6lWYWNjHTtu0+v18FwXgFarieP0AQiCQfGqbrdLOpV6TSi5Vq1x7cZ1/JyCHYP97WW2\n/RLJqRHOvu0xWr5LbnqCrD1Ct9RnbXMNx+gS6B4IgWVaOP0+nU4T3+uQiIcoeokvv/zHlCtbqLpH\nz6kyMzfKB97/Q4cWuzj0CFBVFOq1KpZpMD42goxL0rksSr9PrdNEqdTYuXUTTwtoyx7L23d4//uf\nwcyoBJpDyy3Rc7v03C5B3yfyLDZ2dhktxsC1aLYKfPXyLk89OUcYge+DH7PITOUot/ZRhU4qrqKk\nNcr1DolCAn1L59YX9xifnOLFl1awx1J0nT6ZIwYzJ07QUhqgNgmCCUwzTSypUN/r4rrDp8D3QwI7\n5V2UMKK0tYkaWqjCplra5uKxC/jVHp/87U+SVnNEBmTmbPq6g2EkyeVGqLTXmZ+bIx5PEEX7dBs2\nSfMY58+cR5FQ2fZo3WnTb3RBHSFGgR969iLl9jrtzg4T45O4PY1ut45ih4Raj5bi0vZLZHNxVi/t\n09p7Dq2mYxoGMoqwghiKUFHEIBdYRiA0MSwKdx88xyGvx4gXs/RbHcJ6h8WXX8IKmhw7f4plPcb2\nWol43EYJDcIoQlFMRBSj3XKI93tEioptm9SbXQxVJ+yG5MfzWAmD/U6JU5PncLZrSEUjGdk4zTLd\nqEFXaaFFFqbwiFkWzVKFynaNfr2PNWrjZySGHcd1JSOPF8ipCVKJDK/erqNrAY1qgNc16ZoVcqlJ\nxqbnD2WDQ48AoyjEtk0Eko2NdSr9GsnxDI1elUp1l71rN+hs7zK9MI1qqRQncphpjVJrl43SKp7a\npeFXCGXE3madK19doVGPCPFQtRjp5Gk++4Vr/N4fXabcDKh3YHkvIIwFJDIxWo06MurRDVuU/Rq+\n6HNidg6jb1Ne6hE1FYyORqfeo6RXqCf7dOizs38L13NIpfKkMzmKo4XXwjyGfD0hEZqlsbm+Rr/V\nwrJtbty5zdjUFMXxcfaWtrj2/DWyqTFy0wXqlAljIZFqks7kmJuaQZMxLCXOaG6CsdwCJxeeIpWO\nowDXrqzQrIQcfWwWJ+5xdWmNjrtFtbZLab+N74ek8jbxrMFOZZ3caIK+AY5skUzZZO056jdaJP3U\n1255MVGEgmBQMnMQG6gwrIv5V9F1AzOUyG4fqQmcpAamwuqN2/TqHWanFggcqJZaiFAnCkJARRVJ\n3H6IF7iYdoy+62LFbe7cvoMhTWKGRcdpkxtNMZ7PMXV0gbHJWfqbLb74539Gq18mMn0a1W3seIhl\nw1hmhHSYI+Wl6daaCBNc14dAkhhR6Fl1Qs1nND9Kt9MmcExCN46pp0lmi8wfO3UoG7yJOcCIIAjJ\npDNsbm0yMRUjl83y2GOP86cf/zjXb94gk81y7txZYvksvtpld3cXy7SYnpqh2tklki6GFsN3S6yv\n7XL6sQvIqE0+l2NvbwdFCdnaWmdrc5d3v/tpNnrbVDsbxG2L4yenGBsb4aX1l4hkROAHuL5HcbRA\np9uhWivTbmgUapLsTJ4wMtCEyrXVRRZv/h7j4+OgGBQLI68Vgxny9ShCkE5nMEyT0bFRjLTF0QvH\nmTg2RjOs0+gOJp63tjbY2r3JU+89iwwliZRNKAM++7lXGB+fYmN9fyBU4CkUw02yqTidjuTm7WvU\n+5AxsmRmSqhmjitXbjN3ZJTjx06ws7NDudogny/yxNufQFU1Ws0WqjEId5mcGqO3uYEUcqAnB/jG\n4ImklNFreeqDOd7hPO/rUVWFsfFxVks79CIPO62Tm8yyUS6zu7hP3i4QRSFRFA6K0KO8VpgqnU6T\niFv4YRsrZhDJLhEOQTAQzBAJybnTZ4mkxOk7xGIWL770EiMzedKpNLpuEI8nkFEb0xikWY4dG2Ht\n1g5L+yuMJJO0N8psXF5kNqEghMIrGzcYGR+n3QxoNxrELZUzp54il8sdOszp8IHQMqLX73H27Fn6\njsPM9DTJVJJr164Ts2O0vAbZsTQJO07f80gmE4QIUsk0hqETiyUIvJBO1aFS6mFbeRLxBLGYjx3G\nWNzexXG7xBNxOu0O1Wqb9DFBW12jXNrl7LnTOG6HUEpUTWVvd5/mq1tcOPl2ek6fTrtLq9lmZ3Gf\n9777R+jIAOGYZLOTeHKTxTuXkUGec2+bfO3HM+TrCaOIxcVFKqUyH3z3e9HHk4iURt2rUQ9q3Fm5\nTS6XZWNjiw986H34ep1yuUzMGEPRPTRd59q1ZWrVGkePHEWVki+9+BdkYzkeWXiGza0buFob1zuP\nmWpT82+ydL3N+NT7Brmlgc/29h7r65u8/Ym302q3CAIfRYvY2d7BbsQoForQGeQqa5pKFERIZSB+\ncVcRRtXU4RzgfZBSUqtVcRyHQJX0LY/MZJrY9Rgbr27TSnfwAx9d15ASFDGws1QUHNclZqcp5k1u\n3rxBz60Qj5ssTByj0i3hGS75fJ69/V0+/8nnmE7PkEwkOXXyFMdPHWNvbw9dN6i0muw0qrTbHXRd\nJZOf4cTEeRr+NrZQCTdcLv32LSaPzbNfkfgdn74Z0m11aCgKTk+i6Tr7e3uHssHh5bCkgoVBFARI\n4WNl0ty5scQnfvuPecd7n0GfVOgp0HQdFMskmyvS7ko63R6GEWEocaJOl9AZVBwrTuTRExFGLMPm\nnTKVThMZpHECi2Qiy+KdNjNZg/FjOTTV5OWXruF1euTmsohEiGr62JMxrPE4I3aeen8XY0/SKtXZ\nWluhpbpEpkbaslGUHN60wqsvrCDCWTR9WBTpfvR7XerNEueePM/sI0cRiQQru0usbC2ixD1S+SRP\nve9JOm2fY+dPcGfjGrulXTqNiFTCJKzBS5/4CgtnF+i7PWQo2bi1zP+19H/w9Dtegek6Sdmn3fDJ\nFS7Sbe5wZD5Hu91kp7yLmSlwIjHCq5ev8Ae/9QcUMznyJ7N0woBSfRtno8njU2dx2z1URSFi8GPQ\nFQMJaIqKpupYlv1a8fQhX0M1dDqug/RDsrEkLa+CriscOTbH7Usb7O73MS0TIVSEgFBAiEpc08kX\nM4zNFag29/AjiS8DnnjmCeZH3s6XXv5LIr2PYmpEXZv3ve9HUP2Ir7S/RNvt4AQeUlVotFtUWhVa\nvTKmaRFpCmrGJ5QecaFg5GMURkeIe2OYxiipTIKJyaOs1ZcRyQoChY/8m3/LzGyeTCZ1KBsc+luh\noRJ2Qm4t3mB0rkgYM6nuVFEbLnoPKm6XqnCJLI1ULk0qkeHFF65Q2Wlw9ZWbrN3aorfXJ+iH+NIH\n20PP+CRz09Q7Prkp0BL7ONE61dYKje4WyZxPNjMLMsPLL61x9eUb5EUKWQ2Qhkv6ZAI36xGlPQrT\nNt1Oicjp0u7us7R/mY3WDUoby/z5x/6Co0cvMJGxWbm1SbfdO6wZHmhMQ0PoLlFWcru7Qbnbpdns\nUd3bxauX2djZREmrnHxijq7oo9hxJmbGmZsb5dN/9Fn+42/8CemOxqNHztBuN6i2K/i+j2+2aSTX\n0E/1KHfX0ZJXyMQSnB/5OXL6MVqNLuvbW5ipcXQjh9P0ufr8VdqrdWJ+nEY1JD1qMHHWxswlBtXr\nZARiUOI0ZsSxjTjxWJKYmUAow6fA98OPInaqVSxFp6DaxHydhBGjOJEmdySOEhNEUgGhomoGWDa6\nlcBWdYoTOULbZ313A8VIMzkzj5pW2dM7nHjXI0ycmaUd9UnFJhkfn+fLV79KTZbJjOVwowipKQhT\np1Ach0hDYJBNj9IN9+k4K/idFj2/ReF0mm66jptpUDhpcfSRGX7qb/0iz7zjvWSyFsVRFafRplWq\nH8oGhx4BemFAfCTH6PEis6dmaMpBjV/X97n66jXCtEoqZ7FfXsOMhehkOTd3gRs3b7CyvMLU3ATZ\nQpxKpYrrOBTGR8lmcmhSBQaiim7MJQh86tU90skQ3VhAVRUmJsaZmp6kXzYolTqIdBwRSQxdpd+v\ncO1OA7fq4vQF/V6XvuPQbLTx+21SjiCejFOr1chmc+w7nWFNkG+AoqikUmmq5SrCNPB6EsdtAirl\n/Q5bG3uMjTSZnJwgiiLGx8fIZbKInobrOugJk2OPniGVHcHqdJgcy6GN9FlZXUb2BI1an83lHmJ+\ng56fJ648wUTqEe7sNNnd2mA0W+LU8TM89ujTPP/pF7BiGXo1H0UqKIZg/Mg4Zk2nJcH3fQzDeC3n\nVAiBYRhYlnkwfzXsAF9PGASMjo6iugGKpqIbOpVSFbA4Mn+Uytq1134bMorQVBXLMtENg8D30TWL\ndCpNT1h0e30+8+lPUZxeZWFhnnqjSrPVJJ3Zp962aHdqTE1M02l3KeQk8/Pz3LlzBxnGkJHF7Zvr\nzL7/BFHg4UqPTtuhXfeJaRpjEzrpokrdrbG6+UVCdZ/x0fN0Oh524mW8ahY7ljyUDQ49ArTiNoW5\nKSZPHKUtA0qVCrVanaMLCyAlH/pr7yWdVdkvL/Pq9S9z9eVLVFYbfOlTX0HvWxTsIq1Oi93dHWK2\nTSaTJRYfqEmHYYiqKqQzGsVRm7PnFojosrG+huu4JBJxHnnkIvt7Tf7973ycyy/fJpedRtVAM93B\n3EbZ4cj8WUzD4KWXXkQSEYQ+7W6HZCqJbg6KMU9OTmDFhoKo90PTVFKpJJ7nkc8XUHUPx2+hKBr1\nmoOqmbTabVRNIwwjer0+3V6P1dUVdvd2mZyfoqeGPP/CK9Q3XY5PXUTNCnpBl5e++BLV1SqIPjub\nDRrVkE63gh2MM599lFiQYWtxm8hVGBud5/iRC3zuM1/hU//hczglj0K+QCtqUHUrg5xUZZADPKhY\npr+WnK9pOqZpIJRhB/h6hKJQKBTQ1IG0/F0xA891yeVyTIxPYOrGgcCp8ZpN0+k0EkkQBSwtL6Hr\nGkhJKm0xNqlSb21QrZW5ffs21dYilcYyC0dmmJ1dwDJjVKtVKtUK165dY2u7hOep9LoSQ09jmVns\nWI64XaBecUjYIxhamu3NKqnEGLVqm5X1y9xc+jRStAlcm4Q9QhSYh7LBoUeAdiLOwrmTNII99lub\ndF1I51LMZvO4isRO6RSCIkiDREZj9YU1vvAHL5EbK3DyxGnGR8eoru7x1NPvorS3Q6tSprmrsL22\nR6ftoQdtjh2fY2lplX6/TCwjKFX2qFQmMY04E2MznDp7lonWBJmJNEFfYKZ0yuU9MrlJUufGCMoe\nuZE8ncDFiAza1QaN1RIJK0Zlq0pc6nRKJXzHO6wZHmiCIGRsfJKMEiAUSSJmoGSLGKrNlVeu02+4\ndBotfNchEhGu3yOmqlz5yhXGxsYYK44S9iK21srkMhMYEly/RT5boL25TSIWR051sbWTXLz4LI7b\noLfXo91SmSqcpOvW0DAQMYuFU0fpdEpEeohEEE/n6TTraH4EQiMMBlJJQhuEd9wNjB0EuYvhQ+D7\noCoK1VoJ3+2RsZN0+i0iAXbKxoipTM5P4PsR7WYT0zQxYjYxO4FqGFR26uTrFk47YGu9xNPveRQ9\nHaM4k2Nno0G1XMVQNKqVMslkwOTYMRKJFIEXsb29zeryGqP5MfZ292mUuxydO4kMFSw9ifQkN5au\nomo6ESquY+P1I07MP8bG/iZGqs1+9VVsYwJbnyOup2k2vse3wKEQkFKobaxTrtxAlyNsNfYRM9OM\nj42BBXZqilzqKIpdopGuY0SS8ckRPDNkbWOLrDbO9LFTlPa36W+XKfVV4qTpiDZmzMbX8sQKfbZX\nrjAymsLxWrj9Dkk7g62PEivGMEczFPJFhB8RtFRiWo79+g7jk+O40iM3P0Eq9LE8i2Cvh95OcPLE\nRaYLJ1jaWEXd8+g12oc1wwON6wb0+iGxkRhO1MaWSV75xCuUBQhPYnXA8nU2VlewizHicYXaWpf9\na1ukZkcxYxpyU5JTiiQTAsdfpr+1R2nZRVNtHOlQ7UhEtslm9ToTY3NcC76IphcJG0kmCybLdy5h\n5OJEyT6JBRt9TCNmG1xfqVCIkow3bCqKR7vbQhgKoeLjmh6pVAopJbpmoKr6MBf4PggiWt0qRsyg\npXbRUylSika320FNBOhFwYw1yeKlKpblY+kqim7QDQP8PYvODZ25wgmaPRs/UvGkT9R2SOdGeOx8\nlmapyc2N21Q6IflkhFnQ6UdtZhZm2V7c48oXr7Nxc40zF09DH65dexUFn/p2l8WbOxw5mUDLulhB\nnNKVRRZvvsJ73vshNip76KoklSzgZHK0u33a/uH8e+gO0Pf77Je26fcD+h1B221SrVYZGSkO1nsa\nhqEitBae43NjaYn0ZAJFU6is11hfWeE9H3yafq+P53sUCgW8UJJIxBFKF9M06Dt1TCsinTGx7MGk\n7aUrX0YIjWR8hCjy0XSNRCJBPpcjBDa3t7HtPJn0OEGtiqd0WV5Z58KFC9ipJOqEjhcFXPryizQ7\nDXzZxLCGT4HvhxDQbDYZPVKkGQyusOVyhYoisG0LMyUxTYubN28xFU1w/Og8n/uL59jfr5CcTXFn\nZYucM83C2RP0tD2Wd26yeGsdv5dh4cgCqTT0KjHWX11mND1Jvpij7d5AD7LY2lH6rQlaW1t0NldQ\npUFSGSNpWyRtiZUYIdEzsOoaCO9rcvhCEB3Up1YUZVCcO4qGI8D7oKgq+Xz+NbmzZq2F63okEomB\nEK70mJ2fIm0KRlMZNjcqtHptgkjFdSW3F9c4866jLG1tsLK6yMV3HccJu/jSY3Nzk/peg2arSdfp\ncerkSYIwQCAoFovMFRbIxfIELY+5uTleuf0SshmRTdo02wPp/Xw+j1QiREIycWycruxQ6++xtr5I\nEPU4Oj/NftBG0VLIQ5Y9OHwusAypVHcIPInb12k2u/i+R71eR9M0Asek3W7QdtbY3Nxmo1xi4dFZ\nxsbGoKWQJIMQgmqtBgxuVaJIvqblJlSBH7UIohaZnEEma2BaAdt7d/hPn/g9biy+iKYLavU6m5ub\nbG1vsby0Sa+jMD1xEhEl0dUExWIR0zC5cvkKiqljjxW4cv0a+2ubBI0W9qiJYQ87wPuhaTqVSoUg\n8EkmU8TtOLquYts2hXz+ID5M4jgOpmnQbLiU9zuD3FuljxqLaAY+gRkydjxJOyqztlwDqTE7N4Gm\nepSvbpMOYiihy5UbX6berFJvLSH0ErphYvpH8MtZOvttbKVF1GmSEjnyRgHdNQg6AYoiiMViaLqG\nqqoEQYDruq9VPPM8b/ig6z44jkO73abb7dLtdslmMqRSKVRVxfN80hkLP2wRsyX5vM3ImMHIuIKU\nXTzPIfAHv/vZIynshEqvI0gk4owUR/B9n+2tbVrtFvG4zfbONt1O96AOcZ9qrUalUgYgnrAZGx/D\nNE0azSatVpt0OkUykSCRjeNoXaQdUPOrfO4rn2J0PMPC7CN025KJqTSpVJJKpXooGxx6BKgZKuls\njMCxkWMaL26+QL/bo9Vo4vYdFN2i49QxLIUbr2zg+j6e5rK+uUlGmWAsP0I/6FLeaVDbr5MWEQtH\nT7K3VUeVCk7XQdcjqo0dskUTzYrIWkkmOyP026DJEDse5/KVS2ywyfz8HAtHz2HbOTLpHLv7uwRR\nQHGsyNmLZ1i8eQsjplNudNDiJuePniFwe2zqa0MxhG+AaZpMTk3RbHVYX1lG9yRCVzh9+hSJpENQ\n77O5sYWMh4SBj9N3+ekP/xx/9jt/SOD3ME2TWDFLL2iRtQR+z2Fqeh7LSBFLaiwt7xC1IhKjNvVS\nmZ7l0WmrmEaHhrpMNj1D5CnodEjERrh6ZY+N3qscO1onmR4n5cQ40k0RSTAMA9/3Bhn+DDJAEAel\nHxUxHADeB1VR0VQNz/XQVI3woPSB63n4nocQKjHdYGZsDGFFCMvFMmBETdPutYnbOUrbFehsM3/2\nFLVKm+X9FR45eYHCSIGt9C6ddo9irsDSrSViMQs7l8AQOoZr0ag30VSDz3zqc7zt2cfImmnu3L5K\nFHkoio1tJ9FMiPQuLh6u74EWkMrYFNIL3Fm6Ts93KObOUSp/jwOhIxmRzgRsXZXQdJGNLmoPTE9j\n+8Y6YnITO9uhtzFL5fkSY+ManZ5HqdwjP51nYtqmXqixc3OD5lf7JN45hV40CS63CLf6KGacrtvA\nTmRoezWarTKTmVlitSLqRkg6kyCwNE4dOY/neZw+dpqZo7Ns7a+zubOF69chGUOfnyFhxJgIMnj9\nOuefOMELz9fRjoyg+IL+S9v02kMxhPvh+g7jE0foa326bot+ucHImSMkMzH2qmv0vIhWqUNsVJKK\nq9gxhYXZ04wc+zK1vTtYWoGM7aG4Lj1nFKdskpywmJ44Q0Pus92uEY0WSU+Ok41l8HyPyGyz0l4l\nVKG78xnG7HfgiBpGYpyFkadoVVu0lZCpRIaxsSm2Xt0k1vZJZdIIoQxue0WEG7ik9BSmaeEH0TAV\n+D5ICdJRkM5A3l5agr7v0e12MC2DMXMSS7foRj6e7eFmVVz6dEcCRlMjKOtxopKKZmY4Nn+RzdYa\n159vUNv5JJZhM358Hn+nj95VSIVxau09UuMztLsrNLd6NOtAz6C9LTGdItMzEWtrn8fXKiRjRwmx\nWFveolCcwqmH1Pe2SI0V2C7XEOYaraDEzUubpOPbPPnMKf7wEDZ4EzVBBpLjX/jcl7HEQBpf1zQs\nw6TX7dEpdTg/M8r6y+vUSjXmpgePqU3TYnt7k7kTF2hpgnw+h1EYCCr2HYdGrc746Ay54igdVMxc\nRMnrUfdqg5jBpqSYGIcIOu0OUsLpU6fJZXOsrq7iyS6dXhU7LqnXq0zN+BiWSb/fp1apImLxQbxa\nIU9pt4ZtxVGGqXD3JQwCUuk0Cipx26Y4k6S81SOMKjiOQ61WQ9d18vkkcdsmk85w6dJllpeXKSQV\nTN2mvNegMJ3h9MnHcIsjfPa55zEtiyAMePqZp1jq9tnc3MRx3UHMXkKAgG6vR3Nzg7aa4/TFKdqd\nBqZhcf7E4yhZl1NHTqMJA9sF99USQghsO4aUCqEciH3WajUMw0S+mdpfDzAyGtR51vVBWdhSt45l\nmVimSavVwhMuCEG/1aVdbjFSyJNI22BGjI/Os7ZXxWmp+G6E63p0Om1y2Tx2uk/gS9KZDAUvT+Va\nBd/zkZFFMplgd32JjeVdmrtJ5lJH0ISN03fptl1M0+DkqRN0G0lu375DubKFrieJxeIoQiGKBEiL\nSrlJsTDJ+NgM166+QKtTPpQNxGHnRoQQZWD9UP/8/ceslLL4Vp/E9xtDHz/YPGD+hUP4+NAd4JAh\nQ4b8oDO8NxgyZMhDy7ADHDJkyEPLsAMcMmTIQ8sb7gCFEHkhxOWD154QYvue99+1iGIhxH8nhLgp\nhPjNN/A/f08I8WvfrXN6UBn6+MFn6OMBbzgMRkpZBS4CCCH+KdCRUv7Le7cRBxno8rD5KffnHwDP\nSCm/rYhHIcRQ5/6QDH384DP08YDv2C2wEOKoEOKGEOJjwHVgWgjRuGf9TwshPnKwPCqE+I9CiJeE\nEF8VQjz5Lfb9EWAG+LQQ4peFEAUhxJ8IIa4KIb4khDh7sN2/EEL8phDieeCjr9vHjwohnhdCzAoh\nVu4aVgiRvff9kG/M0McPPg+bj7/Tc4Angf9TSnka2P4m2/068CtSyseBvw3cNegTQojfeP3GUsq/\nB5SAd0opfx3458BXpJTngX/K1xvpJPA+KeXP3m0QQvwt4L8HflhKuQ48D3zoYPWHgd+XUgZv/OM+\nlAx9/ODz0Pj4O31FXJZSvvRtbPdDwAnxtRzcrBAiJqX8CvCVb+P/nwF+BEBK+edCiI8KIeIH6/5Y\nSnlvbtv7gbcDH5BSdg7aPgL8MvCnwC8CP/dtHHPIgKGPH3weGh9/p0eA3XuWI74+A/Ne2WUBvF1K\nefHgNSml7H8XzgFgCUgDx+42SCn/EjguhHgW8KWUt75Dx34YGPr4weeh8fF3LQzmYOK0LoQ4JoRQ\ngL95z+rPAP/w7hshxMU3uPvngJ85+N8fArallK832F1Wgf8M+JgQ4t7qyb8FfAz4d2/w2EMOGPr4\nwedB9/F3Ow7wHwOfAr4EbN3T/g+Bpw8mP28AvwTfeO7gPvwvwFNCiKvAP2Mw/P2GSClvMBge/wch\nxPxB88cYXFF+7w18niF/laGPH3weWB8/tLnAQoifBj4opfymRh/yg8vQxw8+b9bHD2VYgBDi/2Yw\ngfuhb7XtkB9Mhj5+8PlO+PihHQEOGTJkyDAXeMiQIQ8tb6gDFEKEYpAreE0I8ftCCPuwBxZCvEcI\n8affYps5IcS1N7jfTwghMgfLvywGeYcfO+x5Pgx8r/065HvP0Mf3542OAPsH8T5nAQ/4+/euFAPe\n0lGllPKHpZR3U3f+AfB+KeXPvJXn9APA971fh7xphj6+D2/mAz8HHD0YpS2KgbrDNQa5gx8QQrwg\nhHjl4GqTABBCfEgIcUsI8QrwE2/kYEKIBSHEJSHE24QQvyAGOYifFELcEUL8yj3brYlBjuFvAAvA\nnwkh/lshRFwI8f+KQc7iJSHEjx1s/4V745eEEF8UQlx4E3b5Qee77tcDX3xcCHHlYETyUwfta0KI\nXxFCvHrgp6MH7XNCiL84CLf4rBBi5lu0f1QI8etikF+6IgYpVIhBfumP33MeH7v7PXjIGPr4LlLK\nb/vFQDECBk+P/xj4L4E5BtHiTx6sKwBfAOIH7/8xg3gfC9hkEMktgH8P/OnBNo8DH7nP8eYOHHMC\nuARcOGj/BWCFQfyPxaCuwfTBujWgcJ/l/xX42YPlDHAbiAN/F/i1g/bjwEtvxCYPwust8OtPAv/m\nnvfpe/z1Tw6Wf/6e/fwn4O8eLP/nwB99i/aPAr/P4AJ/Glg6aH/3PdukGQTXam+1/Yc+fut8/EaN\nGAKXD17/CjAOjLh6zzZ/Hajcs90N4N8ykN75wj3b/ejdD/9NjjcH7AO3yRBu8QAAIABJREFUgNP3\ntP/C64z7Zwwkdu4a+H4d4EsMOtO757UBnAJsBmk2OvC/Af/VW/1lfQt+HN9rvx4/8M3/ziAx/m77\nGrBwsKwD1YPlCqDf0175Fu0fBX7mnv2271m+DhQZ3AL+y7fa9kMfv7U+fqNxgH0p5delu4hBIvS9\n6SsC+LSU8sOv2+6Npsncpcmgs3qGgUPu4t6zHPKtYxoF8JNSysW/skKITwM/xkDR4rFDnucPMt9T\nv0opbwshHgV+GPgXQojPSin/2d3V9276Rvd9D/d+P+7NZf1N4GeBn+ZbZB48YAx9fB++G5OeX2aQ\nHnP33j4uhDjOYBQ3J4Q4crDdh7/RDl6HxyD/8OeFEH/nTZzXp4B/JA68LoR45J51H2Eg7fOilLL+\nJo7xIPMd86sQYgLoSSl/C/hV4NF7Vv/UPX9fOFj+EoMvMwxyR5/7Fu3fjI8C/w28llo15Gs8dD7+\njmeCSCnLQohfAH5HCGEeNP9PB1eE/wL4uBCix+CDJAGEEI8Df18O9MLut8+uEOKvMxBS7Nxvm2+D\nfw78GnBVDJ52rTIY8iOlfFkI0WKYNP8N+Q779Rzwq0KICPAZzEfdJSsGuaEuX/uh/SPg3wkh/geg\nzNeu6t+o/Zt9jn0hxE3gj97Ax38oeBh9PMwE4bWr1eeBk/I7K/895A0ghFgDHpdSVr6Lx7CBV4FH\npZTN79Zxhtyf7zcfP3RxP69HCPHzDMQb/8mw83uwEQPJpZvAvxp2fg8mb9THwxHgkCFDHloe+hHg\nkCFDHl6GHeCQIUMeWoYd4JAhQx5aDh0GE0/HZbKYJgg8QCIEHETYEQQ+iqqiBBItVBC6jhu5KCqE\nEai6Shj5hFEAEjTFQEhtEBIpIqLIR9fjdLodDEMnDH1UVUXVDCBCiAhVE8RicTzfx+25CF8jdCLs\neAySPu1mGy1MYMYMwshF1ww03aTrdlBVFSsWQ0aSwPOo7FRwOo74ph/4IcSKW9JMGASBDxJ008Qw\nTRRlcN2MoogoitB0jSiKCIMA3/OIZIQiFAxTJwgDZBRhGAae7+M7LkIIVFVF03QUVUPXdAAcx8Ht\n9IjH49ipBI7n4bY9NFNFahFO08U0NYyEhpAq7U6PKJQQgYgkSIkMI1AVdE3H931QQLM1vI4/9PHr\nMCxDxlI2qqYghEQ3NMIwoN93MA0dTTfRDYMoipCRPPjNekRSEkXRwO5SAyRRJPF8DwToqoYCREGI\nFIAARdeIxeOoQqPXaxOPWfhOSBQpCBXCno9uq3jCQw0MdKHT93vopoZlxHADl0gJMU0DgcDzAgQq\nUSRxvR6aqlLfbleklMU3YoNDd4Cjs+P82P/8kyB8JB4J06Db6SKlpFKtEE8mSfSgv1UjTMTx4wHZ\nQoZqMyCet6j3d4hEh169QdoYJ+rZKMLEjuskM7B0s02jVedv//SPc/v2NZ7/0ufxpM773v8sk5N5\nnn/hc0zMzjKayfPqc9eZH3sUvWlQ3tpFPFIBPWJafSdbuxtUrm0ydX6MyWcm2avvks/lOXrsKJ1q\nh8u/f5n/71d/97BmeKDRLIULf+MEmqYShhFmKsPk9AzpdBrTNKm36tRbDXLZHLquE/kuzXqV3d1d\nioUidtJkafU6iqIyMTHBoxcf4dN/8mmq1Srnzp2mXK7Rd1Weffa9aLrOrZs3qd5awTAMRqcnEZZB\ndaXGyEyBUm8fZ8fnHc9epEaJl79yg0qpy9TYAqvXV7FReecjb2Px1i1q3S6KoiAQGAmDzGN5nvvX\nz7/V5vy+I5aO88iPnac4mmB0LINl6+yXSly9epV8Ps/80TPMzh8jCkNq1TpOWKcf1BEohFFIdbeO\nFSRwXIf19XWOnzxBpEN1c5deqUYmFmfh5AI1p0N6YoRAU3nX03+N9eWXMQKHVz5/h5NnHsPMa1z9\n/Su4yRaj71KZ8Kbor6e5sbVHZi7OxfMzNPp1zLTJ9NwkXstlb6fOF5+7RKvZxYr7nD9/jv/nv/7d\n9Tdqg0N3gGEYMjs7ixd0Wd9YYnllm2atgRAKvu8xPWGhJtMk5kwCQ4Kq0G3B44++k2q3xN6dMj3X\nIabpuF6HbqtDMTeH67rceeU6yzfbXDh7hpee/zJLSzewhMrYTJGtrXUunHuEp5/4cdr+Pv39Fnmj\nyNyZGbZvb7H/4h4zJ5PYIwbl1W2SwiR/4QzaZB/ptbn98VuYpklw3mNjdYMvfeIFPMc7rBkeaKIo\nwnEcisUi8XicUqtDvV7nzJkzrK6u0m53sGM2+XyeMIxo1PrIKKLX64EQNOp1arUaum4wMzNDGIYc\nPXqEbDZNGEbs7GyzX+4xMTHJiRMn0HWd9NQY+AHVUpkTR44i5iwirwv7LnPHR6h6e9xZXUbXDfKF\nGJqmcf78efrVOptbm+zu7GKkkkxNTeF7PoESYFkWqqa+1eb8vsPQVQojcVJpjdHxJFeu3sRxfNLp\nNP1ej0qlQsxOEYvFSGdSaK7AknGymSx7+3t0zYhuq0UURjz++OPkCnmu3bnBiRMnaSb2qO3us7G5\nSWokj67rCE2lWqvR7/fZ3l5nfX2D937gfUyeHKd7qUc5qJFKten+/+y9V69l23mm98yc1porx513\n5XDq5HN4GCSqm5QoqWW1ALvbMvqirbbR176yDf8F3xmGARsQDLQbtgxZtNgyJUqkmHlyncpVu6p2\nDivnNXPyRVFSizoNgUVAEtj1/IGF+WLNMcd4v/F979GM+SSj1VilcamIp824+/E9dFGnLFUYdLp8\n40++R5bopInE9sYFBrvj59LguT1AQRCo1mocHx8TxzG2UcAULXJKjtTLSBYJo8mCwJToOQM03eSN\nV7/A2spFLp5/mWZtg6JdI28XQIgxLQVFlul2u0iSxMsv38CbLXhw6zaGrPD6y69QKptUamW63Qnl\n4jZLx+fk6QlHD465cOMC517fYm1tDSvLoWgq8+MJ0/0RynUBfVXi6ONd/AVkoca/+d3/m4O9Hl/4\n8leQFOV5Zfi5RhRFwjDEMi1kScbQdSRJYjabYRgGYRiQkSEIAsPhgNFwSJqmbGxskLMsjo6OuHr1\n6l/uGBfzBePR8C+Pzvm8jaZqnJ2d8cMf/pB+v0+hVSORBbpnHT748+/jM6aYN9iw21SaFh4zKuUK\nly5d4DOfeZtWq0WhYGOYJkdHRyRJQhiGzOdzzs7O6HQ6zOYz/nqr6AsABBHSzMXKy3j+lF6vy8nJ\nCZZlUa1VcRyHJEmxbRvP8/DckF53RuCDZVRYW90mn89Tb9Rpt9ucnZ0hihJhGPDLv/zLVKpVlkuH\naq3Kyckpnu+TZRm2bTMZjykWbXb3HvD4yV2SJMNzUrKwzrArM53NuHitiFl1eXj0kLPuGbPegv/j\nf/m3/OAbPyRdZPijgJpZY3425+PvffJcGjz3DjDyfQ7uPOLswRGe51Js1DEqZcK5Q8kqkhkWxa08\nWs5j/2zCyLFpMEZa5OgPe5QLNhk1skREqowZDXrMfJ/JEi5deYkgWFBrr9E/ixh3XI4PTokaFvlS\nzETookQlommK2xnSLujc+uF38TSL0EpJhBhrWWY57/PF//QNQvuQuzcPufvBgPXVBjkzT62+Rr2x\nTqabEL+4C/lpSLLExQsXKeXLuHOX6xfXaK+ucnw4oNeZslwOEQQHd6HizrsESUC+1iQn5Pn4u58w\n6Dr84y+/TLnYp1DUODx5ysnsFFmWOb96nmJaYDHzaNdKHB0dsYhjFLeHtV2n/YU1ciMXt5fxJOmw\n0ijhOg61domePMOPxshahFUrkAR5jk93yJdrpJUITVPxkwRRAE3USBYGL+p9f5M4jok8iXE3YW9n\nwHwWIMkyhpFDVTUUfcJi2sHevsFy4hAHLpWSTamQYzyZ4PgOWZaAkDKbTTg9PSFRI2rNjLjssvXO\nNfRxjkW4oLN/RPfxGa9uvslq9TJHlSFiNmM09RD2ppgbNsqpjzwoM5kEvPmVV6Ge8uDuHo8/HLJW\nOUdBVFm6E9ZXLpJbt3n44BGJsyRIZTaamxwy+Kk1eP4FMIy4f+sukRehitpf5sdngoCRz6HZCrmi\niR+4jEYT0kymWl/ByjXRNRU3hGq5SbHQpNN/wmg8wHUdPvPOOxg5gQc779Fs13jznV/lD/7NN0iE\nlLbdpnv3gGpxi62NFdx6xrztYzpDTu5+Qv3qy5y7scF8ccJgf8jqJRWqAz7+3hNyxgqf+aUtnMmE\nht1kvbLJ7oMD7t28j5C82B18GpIsIRUEhEpKaS2Pbegs51N2HjxgMg5YxmPmSw1Lz6PKOmIckBKQ\nxAqTQZ+cnqNSamDndeJ0znDUJxMzyrUydsnG8z3SJEKRRTRVIhGf/WalWGHkzIkkkWK1xszzGMVz\n7EDF67lkgowEJH5KsHAxhBzNWoPuYsLa6jpilhDOFoh+hJBkpG5Klrz4yP0kaZqRzxUQkRkNllQr\ndcycTqFQJE0zaqU6JXudYX/MYjqn2z/j0rWr9HodRqMxMgK2nccuFNh59IhWu8UynmKXDGbehMF8\nTCwlGIaBpZsEbsTd2zcxLAtBkti8sMHT+3fod465cu0Kl66tMet7tFbKmGWZBwf3iZKAl1+5TuaG\n2JLOZz7bYNr3eLLzhMVsRrPdor2ySn/Qfy4NnnsBTNOUNEvJ5XMIgkBO0UizjGKzwWy+YHW7TELM\nwd6InFUiCkP6vQG2OcIwdGRZYzhZkjOhUmpybvsiR49H5GyFh48+YTYbsIxr5Ot53vjC64TeBH8Z\nsn/7EM+3aIhrLN1TShcKWDOdw4c7PDn6Lhdfu8751jZKeErpvMl0GVBrX8TILWm0EybHq/jdiHAa\n4fU9tgqr3Ff+o0wH/VtRBIWcYDOejbB0E2kWsv/whP2DY3JmjTiUGPY9Wo2EVrNNc6PF/ccfcdz1\nsWxYWV/HMA0qpkGn59BoNHGPjjFNkziKyedsZEXh5s2b1Ot16o0Gc8/hya19njx6THNjleqKzNWX\nr7K6ssFstuC9b7+LIRnIsoSipth2gUazQTmTEHpnZMUc9VqFj773QzrdLkUzT3LWe3b94AV/DVmS\nUFWVLIMrVy4TCg6GqVEul0nTjEZbQxaK/PC7D5kvBsz9EfXpBAGBKIoQZYWt7W0+/vhjPr55k3/5\nO78DRkKhHDEZTzg8OETJJVzZukK1WsPJXNLM4dHjR5RKJSSlRXulwHjgc3L6mDhpkAYyq+srpLg0\nmwVKDZOcVkRwFKbHDulSZDw+ffb7kkQYhpycnNDr955Pg+dWTxAoFAss5gsWiwWJ6yMqMq21VTwh\nI1eSePBgl8ePjjl3fg0jB6PRiOtXn/15J+MZpVIdQy8wHE1ZLjwMS2I6HxJES3RLwipb9KYdetMO\nihBiFXVUWyZRMr7zwddxFz3a59Ygb1B9uYjZV+nPjnH7HhdKDSZBD722Sq6xIEpmLJOETM/h+EvK\nYh0lUkgUF8VSn1uGn2fq+Sa//cq/5L2zH/B49JC+02c4GqAbOuVKGcXPIakqUajw0ktvEylnHPdv\nUVYqTFKJQtEiTVIQJAQBREkkl8/RaDRAAGfpYufzLOYL/MBHkATEfAn3yRkVihRr60ySLpNoTF3e\nxKy2MbUmO+/dRzc0JFli+7LN9PQh/XtPcEi40HgN3/dJ0gRVVUniGC2BOIr+vuX8B4iALMuIoogk\nSQhCjCAKTKdT1tbW6Q+O6HcO2dvroagJE2fE4eEh7fYKsiKTRDGdsw79fp9SscTq6iqSlRFlHT65\neYc0g2KxSKVcpmcOiLQIWU1QtJiFM6AY6qw1ytRq64zHE/r9Qyy5xGKhIBZzKHrE1B2CFGGZdSrr\nDfY/Ocb3ffK5HPVanSiO8JMQu1B4LgWe2xiRRYVkkYGfIcUpcQZGzsZdeAQzl8e3jnl694CcqmKI\nCjV7hY31dbIsYOaPGM0eI8Yh42Gf08EDcoUCF1evcvPPfsBarsUX3/4K6ysNnjzqcnDSxRMC7JZJ\ndbNNq7ECdkYkhZz1O4h5idpqEasm0l5rY9Zr7Loj4lTCH3aJliOIZFInj9uLWF/dptAs8dlff4fa\naw1E40UR5NPQZJVfqt7gv770z/ln8peIBwaqWmWtsYXgRRSKNuVaBWc04nt/8DWWJw61wjkiUsRy\nxNPuXc6On7KcTlAEE13IUVELWJmG6KYEoyU5UaNu1dm7fUb38RItEdi6uk1ps0G1mEeMRbqnPZaL\nKbPZGa++fpWCncebeCgLDffUZTZe4ssqpl1GC2X2P3hINPQoW1U0PUel2SAKXyyAP0mapWSAlcsh\nKwo3XnqFa1dewjByuI7PpOvw+O4DhMTBki1qdovMTylqeb7w5heoFPN0hzuoWkKrXcfQLeqVLbKw\nSNGuYRcE7LKJH/ustNpMh1P2H+/RrDQoWgUMWedoZ8q733lKnNqsXrzByqvnMNYtUmQGTxaUohby\nwiRzVcgM7FKN7YublFfrtF/aRmkV0GQNQ9L+1uf9NJ57BygiIqYyiiBjFUuYlSqSouA5PuV8kTD1\nKJfq1Ot11tfWWbJk/WKLdCry7tc/wY/6jNQuilEkiDwSCgz6fQanp2z9xj9ha/sqPW+XUX+GZmg0\nV1bQTIlyLcfRk3tQ9ljZaOAsE9xOxr3v3CS3orL6Rp1XP/sqxUqeYOrye//bVwGolEqMRIdixcIq\n5JkEM+5+chOl4CK98Mc/nSBg9mSX2tY5fu36r2CWLf745nc5HPdxwhAli4mDOfVKHiPLePc7P2Ap\numS4vPHWVRB22dvbwbYN8vk8kZex/+iAH337Pba3tzl/7hxKVSaNFVZXXC6ev8ooOsaVU7aunydL\nMtYbq9zducf2xvlnVUsKbFxZwV0uMRQFd7JAsBTq9RaO43Dz+x8QzxcUSyUqlQpO4DKYTkhfDP34\nVGazGUEQcPXqVdIkZeEscB2fMIgZD2aU8jZGrYIzz2g2tgizJe7cpWKXKdl5mq0ihm4R+hKSJBFH\nEZpio8o58jmP1eYqUqTiiwGSLqDKBs4iotVc4fjgmPFhgB9ENBxwZY/PvvkqhpZj95M9Hn78gPVV\ng1QKKJdMVlcMmjWF3mSKKOvUN9pEmsgHHz1Ces4q/3MvgGEUYds2jpcQJx7FYpGF42AYOqIgIukC\nm9ULRGGEn6WUVnOMnEPuf3vEYj/Ai2P21WPOXypwYestDs7ucHpywMaVVVpbq5QaTSanPWoNm7Tn\noak2nufQqBc4uLWDqRmokYWZL3D44BQzKlEvrXA6nHAxGdO0S2hSjc2Na7z/pz8gETNSIeWsNSSe\nJBw8OCL2PKpNjSR94Q99GpEfcPTwCakTUF5f54urb/F2/TIf9fb441vvcXd6i8ZWmWKpTBRFLE6n\nOAOPKIi5/d2njBcT8rWE4+NjisUi9+4/4Hh3gCSpyJJNsdSmn+6SRAmrV9vMsgle4GHaJdIkZX9/\nn5ULbXL5HL7vI4oiC6eDVlXIty2CpU8wCckneTTVQNdMeo6HpMjM5jNmsxmKoXLq9UheeIB/A1EU\nkWWZJEkYDofMjyfsH+xRLBbRdZ3lcoEmq0RxjCRrCKJA5Ed0e12+9rWvsb5VwXEcisU6x4cjHj68\nx9qFFoZuIEsmZXudslBn4owZL0YUNvIMjpYcHOxhahXqtU2szMc0DS5eP8/7D97FWyZogkmjeo5G\nrcPew2PSOGBWSUhmcHZ8zHI0ZvXCNo7jMBwMKRWL9Ht/x0UQWZYwTROEkPnCY7lYIMoKWZZhWiZx\nXieUI66cu8Hh0RHecMHwdJ/uwYx6/TyW2AZFod1e5fLLrzFyd1m7WGVpumSqyNwPARVRDtk812B7\n+zK7u8dM+o9YK62xf9DFH3TYernA6ktbeM0O2kqFYOpz+8lH5KoWaWxy5ZfOs/f4DvHjGY1KC6FS\nRkk1LCVHs7rJ2eEj/KX/vDL8XBMGAaeP91CClLyokmUZRrnIF7Y+z8vqNr+7H/Gj0QeE6YzU0pD1\njKqe4+H+IY4g4pCiV0J838dxHNIEZDFPGIT4joQi5YmNmJEzZTB1KNh1rl66wKOHD7jTu0vnrEMg\nhwRpwM7jx1y9eoXu9AxdMmlfaiL5Cs7BEnUm4gwmWIZJ2ciRb1To93uQZniBx0p7heHO870gP88k\nSUIQPovVmM1mzNwp9UYdz/UYjoaEUYiQZtj5MomgkaUZ589fQNN0Hj9+wre+dQtZn3H1ch1Jlni6\nu0OpLSLLTbJM5uP37/KDr36Xl968ilDMKG4WCBcWhlyjWl6n0+1y6fwlKrUCsRLh+R5P9+9ybstD\nzhS2LxQ5uv+Udv4SBU1GDTPkOKJWq5KRcXRyzNHJEWVFwTKfL+f9+Y/AskhGwtrqOscDCS8JsXMm\ny+WScDqmYBY5t3UOOZURExFvkeIMRZorLaI4oFisEscRH/zgh0R+SkGt40gD2u0at2/9iKtShqXY\nmHKRs3vHHHz8VaobGxTadfJmgfEso7G2jlU0GEenbL1dIvMEzmkb3H30fS6cO4cfiVhyicuvX+ZO\n7xMWqctiZ0wnsaiVmjTrDZadU+JF8Lc/8H+ExFFIb3BMoWQwGBgQiRSDEHMZYCcCv33tK3S+ecL3\nbz1mIadIC49yaLCirCJrJpmV4DpzogSG0yF5S0XZaHB6ckKKT3dwwjweU282sUwJTSnhTsf40xnT\nzoTVygaH9ztcvLbO8LhDUDuHktiIssxKY4Vw5OBlU0QMysUyk/EEgZTIGZPLNDwpIi0JNDebPNSf\nzyP6eUYSJSzZZOksWU6WZCLoloWgySymLio5EjdiGS7IWQqCGjJP+liRTrttkNc3efp0jw+/e5fl\nPGB1e5W9kwNWA5GPfvgBp7tDynIJMTWpVE068wMatRWMls1wPEDSwMpVmI18xsd9NvLbeFOPiTMk\nmIVIVYnaZZvJ3hnzs4T51CRvFikVK9x79ICp56BbJmoxTz2fhx/d/qk1eO4FMCNDFCFNUuxKncXg\nmIW3JGfnGI/H6E5Ab7/Lw0cPURUVQYhYOAkCzwYbeH5ItVFkq1zm4b0POOkcUyxnVBt5Do6eUm3U\naFUusHNnn8ffeoRmi6ysr6AUNbrOkK1XtjHyZTrTU6ycQToTeHDzFjeufoa62WTc7aPkFE4GXTBF\nGm/UqUglBvf7qHKDOIZHuw+RDQNFflEF/jS8OGSuxQwFF390RC2xIAxJ3CWKqlIIEt5Sr3Mqxyyy\niEUwwJBk6uU6Rl5jNO3jzwX8MCERPDQlw6gYTOcKxYqO588Z9RM+99abTKczet0eieNQzFvkLl0j\nDhXELIfbd1CSlPe++SG1tS3MvIJRNphOuyRpTKjC0p8TSAmeFLKczSimK6gFg/yqzDxaECUviiA/\nSZakz9I6IjBzBrGksZx5KIpCMV8mnLpkREhI5FSV+WRC92yAHguYqUC4iEmH0C438CUPeZGSSSrT\n6Rw5SSmoOr6bQqZiyBZ5Pc/h6AzbDCiWihRLBTSlwAcf3SNMpmxu1BFMkcD/8QlQgvy6RV6FRcdB\nDBUINYRApiiXCJwAPZWYuM+6i56H514ABUFguVwyGY3RaiVarRaDQZ8w/Ksjjx/52Lb9bEBCp0/s\nu6iKgKbnENUYq+EjySNWV0UEX+bszoAfucdYa0X2T85II4WDo6csXQ/ZKlDQKkiiiKapdA5Pqas6\n57eucvj4CX/8px8ynzrgWuTrGkePT7j21jUOF/sYgsHqyy2swEQciUzHoCgyWRYRBB4/WzLfzy+W\nXeCLv/mfIUoS+3u7xJMpc9fFDh0sM8d4fMx02qOUilRkC6FdYF7waF2r4px65DybUbJgMOhTa+VQ\nrBzTcUCWgWEYVCp1jro+aaRTKvsMpyP0uo1g5KlV1vj+dz9ispwiGzL5Qg4RjflgiD+Dm15Ev9fj\nl37hS6SBxOHRIdutFabOiHu3b0NksHSnKJFIrdVGU1985H6SLMtAgEqlgiAIeLGP4y7JWTn8ICBn\nGhh5G9fz8EMfmxKFsMC000f0Y0wp5cZaEwEBDxWXkCgK6U27NFttilrA00f7CGLE/v4JuXqOzZdq\nmGKe+dmCX37rV/nONz8mJWW5XDBbaATpEjmfYioqw+6AWq5O/coKe/EBoisTLiL6gz6CKNBaaSMK\nAtFshh89n431M90AjqKIIAixZJkgDCmVSni+j6IoTKZTNEPFtm2CIMTQNOLQJ3B9JCVFigQevnsP\nMxWJpwuEmUBjUae0eo6+PkdSTY6On7C5uULNFdg9OsQdBnTOTth8aY2CXsLQLYbdQ6K5izgVudy+\nwul+hy2tzbTXx84VUBMN3TJp1lt43QXz6YwosNB1jSyV8IIIUXhRBv40LM1kNb9GeWuLq5c/w7J/\nwLx7ytnpKYP+GU/6T5mXRcx8FcGPMESLlTdyDNsnjE9HDPYnWNsWgRCxWCwoSSq+5/3YP7ao16vo\nhzt8ePP7nL+wxemRiyAHmGaJdjHPlTdfI/I/5NxWCVkL6KQBBbnAsHeMvWmjl2yql9Y4PDpmtbZN\no16nENeQ2mVG7w+Y3z/lfHGNdrv9Fxm4L/j3EASBNMtYLBaYpkmSpui6QRg+G3FnmAaEMWmaIkoi\niqKgKwqakKFFGXN3QXlzHVmW6XY6HA120WZQVMrEBOi6RmvFxspr9PsjCs0WW6+uM9wf8lr1dfJJ\ngVqpTqs9IownBGGIE0zZu9tjc30LJUxY3aiTLGTCMCRZ+FRyVaazZ8m1WZbhBT6pIYP2d+wBZsmz\nGW+6aVCqlOgOTvE9F1ESydIEU1YxVBN35pCKAoaSQ7RUAiVFQ8YKLLT4OvF4SdgZo5gmG1dWCVKP\n/mKB642JApcslSg0bFaFFM2SWJxOKMg3aLzRYnf/E9Am2DWNf/rPfpOj/Q7LR0smnTFCAT7+9n0q\n9iqNZsiZe8r+zgn1ZpVrWzc4PjzF9yKq+TaZ+OLl+DTiIKL/aB/FScivrWKvbGJvrrOKiD+fE7/3\nJ3zv5Ba7sw5rjQrFfA5R15n1liynczqjU2qtNWIlQrQ0EiCXyyF8RpT5AAAgAElEQVSKIpqqcnp6\nyMa6gWUWuX/zMbduHnP+1XXKDRtUifXzaxR1lZyWMJn3GE47xFFEpVXDsA1MU+fgZI+d3QfceO1V\n9ka7aKbF9oVtSq7F4e5tNipNKuUqovRiGsxPkqYpge8j/bgaLLggZCCkAuV8mWDuISYZWQzVQo1i\nNY/jTBE0BT1TWF/fxD5f4cndPY6nQ3LFGoHnIBUkZE1iMOzjpw75gsGWucFkMKaonSPf2OC3Xv/P\nmexOePP6azjLBfu7D3Bc/9kItLMRzugp+bxFyRjjOwKZKlI/12TSHREmS8IoIgxT4jSDooSkP99S\n9vytcHFCGPpU6i2iOEQWIPBcAFRVwVZyhF4MMQTEiK5ANdcik33i8YKSpWBWqyxjmZxVxd0wKFxS\n6N4OyE8tFvMBeqlJEqp0/R7ooFQiLmxsMHo6oXVxlSSKkQSJpCKTv1Il8wa4H0ZoDYPmdpWiLqFQ\noLN/BEORJEm5/M9fIW/lcVtLtrdfY+r46L9vPK8MP9f4gcejvQdE+FzfaCDkamSKgBBn6M0Sb2Zf\nxi+Y3P3h73Mw7EDdo3+/w+EnPcSliSdJeGFEUbaIgxCpZtIyTPb39/E859n/xCwSuQnD0zMub2/y\n+mvvgCyQxRFROsdniiJZhILKPFpAKlAuVvCFEBOZP/vqH3Dh/DruqEdiSJCqhI6LUgOxlLG/d0Bu\nYw1ZftHu+DcQnnXISJrGbDpFVXQi59k77AYOaiYT+iFFu8xsuMDSNYadHuViFSNXxF61mfhP6PdP\nGB8PeenlVznxDnEFhyAN8CQHs1ZEtTRqosHuzl2S43P82jv/ipreZik5aJnLlc0LPDm4T3d5RrHc\nRlIsMsBzXR4+OmLpBnz5y1+iUqvyyQfvc+XtG6SJxt3bu4xHc4gmBH/XR2BJlilUyiync7xeH0kX\nMEwD13EJ/AA3lpBEGT8IyFQJ0zQIAp84CTFVlZXtLTzPJy17iKbC9V+6zK5wl1tfv40dVtCyPFHo\nEiUBQbCkmq8gSxp6Weesu8vRA53bX99H01RWXy2TFUPO/8JlcnqTfFtgJpxx3H9CTlWoNrbYutBC\nLUSIqs7O8S65co7d+R4hMar1ohPk00gFKDTrrFy7jNCogCpAmD3rH5LAjxOq5TW++Pnf4vjkGDEe\nsfPgI3pHQwpCiUqlTKVSob5W5d7hHRIiBKPGbDZjuVxSKNjM5ksG/RlWLsflS5cxRZnDgwPSJEVR\nVTq9U0bjIZqmsbW1iaFZeEuPjfUNsixDlTT8YYi0oVKpNEhkBV/KkCs2r/zGlzjc3ac/GJCmL3ze\nn0QURKIoQv2xP5qmCUmaEEURaZZSsUqYlokoiZiWCb6A4mssFwu0osLh8ZL7d+8xH0d4WUJnPiDR\nYgRBIJ/Lo2s6kRsQBiGL5YIbL7+MJreoFrcRMmg0awSiz4X2OV5LXuF4WkaREvYfLUAQUFSFWr1C\nudpgZa1Cv9ejvlGlfHWDMBC5tlblzkf3GHzYQ/m73gEmpERZShyECH6EbBqEUUgUR2RZhhM6qIpG\nmqYsli4CEWoqk0ig6ybj5YLJYIyIS+3lTfYGe+zsHtHbmyOQI5m45CyNYjmHJa+TBSnO0iVWK1x7\ne4sPvv4BZ0cLPvfld2i3V5ETFUyd+pZKoZqi+wv6QsJweES1ucEgOUNzFO78v1/HVzwuvrFNKqc0\n9AsI2Yvj0aeRLxT4xd/8dcRiAXQVvBgBEYIYxirdxyd8+86HXP71r/DWa/+U6SKkXv0tTs6/y+6D\n7+CHIyzLwDA0XM9BMSSKxSKlUgnLsphMpph2yv7BHqQGjfqIdq3M9LjDweEhjXqD+labi5cvMB6O\n6A/6eM4JJALnzp3DLtq0qm2SfkDv6RBZstEskAl5enKEXi5w+aXrpNNnc+he8NeJ4ohavUbgB6Rp\nQhCEBEFAmqbP4gTMjFqtxtHxEY7r4AcaemYyjHvoWwoHD/Y5/KBLrEjka3WsVol8UaHf67O5tcVi\nPsfzXbq9LtVaDUmScBY6fiCjK2AXbSpqiYPxEbN0glKWKKgK6n7M8ekppVIRUfaZzE65e2/EkydP\nuP7aDQ5Pd5AEEzvf5O13XuEbt+5TKOSeS4Pn9wCzDEECXdeI0wwv9AnDEE3WWMyXyLJEKmaQpIgJ\nOM4S3Sqh6wYKCnPPIY1j/MznODzk/p/eZ3Bzgink0JoGle06B9375ComSRQxHUyptlaQyhFHnX0E\nL+PtL73D6o1NpEDBfxrgKS6nB6fM7p4gKxNa5Q2UDZVAGrB2YQtbXOfRn/4+5U0bIxKQSzkUXSAT\nXnQJfCqiwDJ0kKcRmmkihCIgMu10mU4m3L51m3s7e4TrB0RxHdPM8earn+NzL3+O4B//a447n3Aw\n+yE7R/dRMgMxlhgNBqy02kRBQBj4VOQa7eo2ulqlXtxmOV3izHxiLyNvath2kXZ7HWfpYpgF5hOf\n7tkpUZRg6BYvXX+F6Mzj1qMHPH1yQiGfxwgDPnx0h8/8yi9iX7tMlsbPXugX/HUyyJJn9wGFTCAT\nEzRVw3WfZWwIkkin3yVfsAnjCDXV0QWFgl0gIqI3GJFXa0glDcHUaLSaKAWHxzuPWczmgMBynNC6\n3ub07IhKpcZZf8bJ3inlC5vPpsR7S77x3T/hdHrIwXgfK0uwEDh/cRPf9yiUc9Sba/zR1/4IQzVJ\nvQhBnlMq5zDFCEVXaK23Oer91NPwgZ9lAUwT3OX0mXlqPQspCcOIZJnSzLdxfQdZkAhnPjIZ/sxH\nt1SMRKUzHKKqCtVQJC3qeNkJ3tMluURGqYN1QWG7dZ6zk6d4Uw9bLRGrAmWlyuHBAwbBlNnxlMZl\nHy2XcvvP7jN+2qF8TUJfNWnULxA6jwmdPEfDDvlixgWtgCmXUcQK/nFI0rNQ7RqaID8L1HnB3yCK\nI457J/i+jyxJVDQdMc0YDIcc7u/zcP8pWrXINPE4mQ2QBmeUFxaKrJLL57Ebr3CteoPttVPeWT6l\nO7zHUeddEtclimLmvTHXV77A+eu/wuOHIxZ7JRpv5Nm+HNPabhL4Mbq2jizblKplfN8iKedxFzGP\nHh1SLq+Qq9UIJQflqYExEhFcCVfRKVgt5sM5UprQ65+SJvHft5z/4JAlGSEWUEUNURXxEg/VUFFF\nBV3XKVUq7Dx+TFkuo6oqQk4mFSGIEuYnUyRJZ+3aOpqhMZvOCIdTpv6Ekl2ELKNgFShvtxgfTpEj\ng3/yG/8Fi8cancf3eeXKCothwv/8P/2v3Dp8j+b5Ghe3NnCnM4KJgxsmCKKCXihjlBtY5grOmYc7\n0Ni81CaOYxI1YTbvcPUXXyG5IwEf/vQaPK94AgJxHD+r6GkaciqRxAm+H4ANuXyOOIswDAPHcSiU\nSxiFPMPhkFKjhpAkFOU8A3VI73hObGXcuPEKZ6MzJEHl8NERKAqpDJHo096usPdkh8pajXESEstd\nomDIYmASu2PC5RBRNCgXXmLrwi/yZCek1x8w7yac7o743I06drXK+S9dIx4uOLi9S/j+I8rFFt70\nRSvcpxGGIXfv3sV1XWazGRVVRwZG4zGdszMMu4pOwKS3g5zNUYUco3GONEmoVMsoUgExq5BmMuO5\nhbdscXHjV/Fcj/2DA8Q4z+7uPtPhE+YThdXWVcYTj5yxwsXzr/J4912iZEF/6DKd9Ugzle3zKywW\nh9y79xGIAa1KEyM2WDoOqqQhiTKICefPn6e6Ueb+/ftkWUKavdjl/yRZlpEkyV/6gFEUoSgKtm2j\n/DgmQtM0lssl6xsbxI5PEHh4+Pj4lGslNrfWmU6nLBOBo/4B0cLDylkIgshw1GG7Xmbvkc/v/Iv/\nns+9+iX+v/7XeP/Rd8g/iPjBtx/y/Q+/SWu7RLFQYn3tPAtjzNF8l8l0yt07d6i1tzl3Kcf169c4\n5pSTgzP0oooiK5gtm+7ekFSAl268xP/J7/3UGjx/K5woPLv357o/zmF4JqKcU0iTFEmWkKVnno+m\naWi6iZIzOX7QJZYFtporTGchZ8kpka+y9soWjYsbTO94BIuI6WCGfiWPookMemfYlXUWwwHlWpvP\nff7L9Bof07pYxSOCXMi5l1fwpCV57QqaWqBWeIW0eB+DkCdPJE6edtlcX2X1UpWZbbLsOkzvHZPq\nE2Lvxe7g04iiiP39fUajEZPJhJpuoIgStVqNz3/hC5hmkT/b+ZiFc8Duw1vUGquo+QqKIrM4jel2\nZsSBQaGYYz4fMRqPyVlV4jhhMU9ZLFT6nQcYWgVdWaVSrSALOVDGZISc23ydw9EBj3fv4PlDSvlz\nNFp5Wv0CRg4uX1lFw+LbX3sXz3XJaXmEBDzPY0mEf+LSm3ZYW1t9kQjyKfyFL/oXnt94PCaXy5HL\n5fA9jyhJuH7tOt1eF1mWyRQFKUuo2lU222vImoyQCNQrFQLVJRy5TCYLKpUKuXyes9mINBX4L//F\nf8sX3vkS95484N2DbxDnunzU/RZ7cZ9XPrtFFIVomk4h30b0DRq1jDg6pVbeZDp2EQRYX1tHC03u\nf3Sfj/7wFpZlsZ8/5s79O5SvlimWis+lwc+QCpfieT6SrDwbPqmoCEnMPFgQiiFuGCGrEsPBkEa9\njiBJLHyHV99+nfl8ga6ZjLKAYrXIy5tXEIyEKFVYv7SFuhB5+vAxqZFi2SrD7iEzZ4A3W5CXi2Qh\nFBt5lopHpMhsvL7Nudoat3Y+xAvP6Ex3Gc+WZELA+nqNcX/Gt7/1R0wW9yk0qlTLlxlMHWQ1T0rG\nC3/80wnDkKOTIybjCZVqhRs3XmOl0UDMMmzTYjQaocsJhuoT+hMm0xGSZKEqz/JlnWxCKmcsZxml\nUpWiHrKcPuC4c0ylXmVzo4Y/qzMdgabqqIpOEPjkjBpCYmCYS3Q3YbLfRTdSRDEkSR00QyCXqhiW\njK3luf7ydW4tbyMkArIkk4UJuXyOcq3Mldeusr//9MXEn0/hL0KvDPPZNbBKpfKXAUg3P/6Yi1ev\nsHX+HNFpRK/bpVkok2Zwdtpho7iGYRsousLp6RlTf0pttYFkKGj6s/xuWdT5yi/8V3z+9V/m9r09\nvvnu/46jnFFqS5y6u+TWbNryNuPulHmcMJ86LGYOcZxRLFQ5f17mgw8+QrFFNirnKRQLSKlMLrbR\nA50kgHZ+lZk//vHl7Z+e5z8CixKKaZMkMfPJFFWUEKIESRLJlARBVoiTlEKhgC7KfPj+h1x+8zr1\njSKnT4+JhDqmYOA9slgwQ12XsIsKHx28TxZr2OtNEnlMIhZgJDNzZlh2hcHxKXPnHm45RXaKzKdz\nmrV1lGaRi8Zn2Hm0y+H9XVx3zkr9LTZvXOPp8RNapSLFq20KZo0f/O63mez0aKzW8L2MjBcvx6fh\nRz4Hg0MEUeDVK69x/sabrJWqPHjvexw9fsJQmNNJegSGQUlsgy5z4A2xxJTWSoVLb1zkrNfh9PSU\nVA9BXhJ19tBthyufu4po6KhLg51PRsSLkGZzHSEf4/pLdN1iOHnEn//xH1Is68iZhag6jHpdOt05\nkiRRKDTRDAN9TUduyFTyFZzhAjHyqTTbqPk8omlz4ZVXee//+en9oZ930ixFUCBKg2dRsXH0bJ6f\nqvLZd95hlLn0wwmKKaFJGUIYYYomZaNJby9gOh+gFBcsFz5Ld05nMKaxvoEnDJGiEv/qt/4HXm99\nEWc45v/66v9I398lzU8REvvZVRrNYeXCZS69epWdp7c42P0u09kIQze5fPVV0ichhZ7I0j/iNMwR\nHMCgM8Qu5HCDJZIkk2/kWLne4Kxz+lwa/AxV4JTxeEycJDiOQzVfwHM9siwjzVIURSNIQtIkxTRN\nLl+6REZGlqWUiyVcZ0nOVCkXqviux/HTQ0w7ZvtCm+VMYtDxsMsSzmLJ6UmXfFngjS+9hbZQWbrH\nBF6I18nI2yVqhRpyplIrlngUO8xGPWQ5JoqWLNwZhUKeolGgUdukYqxTW+3jj1OiTIIXLVL/QeI4\nJoxD2u02iqoQ9gY8HXR5f7BDJ+gy9+bMhQQzL+GHKU7okakSsqIiSQqu5xOGMSCSZhl+khIU87Rq\nm8h2jclkhNrv0V4pMR6POVx8CyU0UaQCJ6cyj/bep3PWRdPWKRfzpImCs/RxPY92q4Whm0iqyng6\nptFu4vRdFt6SxtYqKxtrLAOfRW/MynYL4cUh+FMR/70uKN/3CfyAgm1z+fJlnMER6xsb+KbN/Q9v\nkiUhFbtKPmdDEjGbj6hX86yvN7h27TIn3WO6gx5qVuLXfuFfI3nr3D+5x0H3PkYhRY4zolShezqh\nXCpTLVUoFirIqkqxWODJ7m2SLETXNGRFoliy2dzc5sqlbczyJh88+JA4ccgEiyRLSOMUZ77E6y2Z\nzCfP9fzP3wnyYwNVFARMw8D3/R9/RZ4VRtIkJUkSZrMpUpyyee4Co3jO2toa832P3u4ZWc3C1CuM\nnYBI11ltXqDWEugPDpGkGSkiXhATI3DjnTfRKip1DKaRxMFBj2bBxI09mi+3sZUiH378I/7s332T\nl15tImUQOC6j8Rmj8YhcqUTZalM1G1z4zDmG8zPKlClrTX7wrT95Xhl+rkmSBNMwkSWZ6XTKh5MP\n6bhD4g2dvcAjjBTygcGiMyRfLlLfWCWe99h9+oiMFvpcYTqf8/TpLq+//hq+FxKnBmqWxz126Dw6\nQhwvyTdCYlvn/b2vUtKLJG6Ofn9AtRVz+fIVBv0FuQsNcrkcw2kfVVXwPI+9vV1kXcPO59munWP3\nk3002WDgjCi7DlkYE7suB86ULH7h8/4kgiA8q+4Kf1XQVBWVOEn4+OOP2Xz9KqIg0Ol0iKMYL0iY\nMydLNLRCDiU0mIxCKhUDP5oiiUuM2OS3f+2/YS33BnuP9zkrPuDO8EcoZkwhVNnrjfGjmJwpIwo2\nuVyR4XDEn3/7e7jekGLpWU/yeDxmNJoT+Bm6WsUwcrz9zg0+6syIFhqapjEcDClUCuhllTfeeoOP\n/u1Pnw38M1yDyQjDEF3XkWUZdzHHzucRRRFBEH4saoQsP2tkfvLkMedfv4Lruni+R7Fss3RHxJFC\n++I6k8EDHu58QpiVmc2HHB0fc35zGymL2b6wQaVZx9mfcPzBLvP1hGLlAuOTMXFvytP6Hj/ovM/R\n4SlSUGDaSdjcXCGnFhlPu4zHQyrNVeqlOmoccebtoLZ8rBCG+31emID/YQRRwPM9zs7OuC0HWG0b\nWY4p5E1y6+eYP+oiT11SMmIxY31tHcsSODp+TJR5uL6HrhlYlknohoQnC/Ye9ChJOnIoYOa3WAwC\nBF3EqudpFGQWfZ9iuY1iLJCEIqbWYjkPkcWMOIYgCPA9n8OjQxRdp9lcBUBRFIJ4gVktcvfhA66t\nbhFO5pzNOng/bvF6wV8hCMKzoajBs3mYuq4TR8+GHwiCwPHxMfmSDcBrr79GMHR4fP8JpUKTSrXM\nchAwmiw4O+mQiGeMBlP+k7f+O/7R679COIJx7y7/7s4fkiUB+7d2KGt57GKTRafPw/t7WEaZhw92\nuP/gLnfv3Ke1kqdStREQWCzmLBZz4hiqlVWMss3u4z1EOaLdbuO4Dsvlknq9jlQUmM1nz6XB8zdI\nZhnL8RytouD7PiDgOC6m+awEnvg+qpAhGAqSJKGKCocPn+LEDZqfb1JUy9z5vR8hWCFhXeKSfYHJ\nYMwn33sKWUQY2Zj1FmJ3n9GdLkcnOlHfAUHAdQTEGrjZnHJljfffu83JwRMubje4vn6F/vgBhbVV\nqmqFg7NdVFNn5vW5ufNtZMNE06u8/c4lju4/Quy7CNKLBfDTEEyJ2XqCUJQpr1RQxx3kUsZO5wnn\nXr6CFSccDI5pn69RrFRwEh/H8Xiy85RiqczWSglBd1FkFUFKSROfViXP1E+JFlAttVEaZbKKyqW3\nb1CxTEQmDKoDDg+OkeQihlFC0Kao+oL21gVKns0lY5Nbt99nMT+iRA1hXmWv22c8ccnSjNwiZf+w\nw8Oxw9raGi9deYsPvnHn71vOf3AIgkiWyYhChiRJ+NmChICV9Sae5yGJGaeP7yMXciiXKnTcGUot\nh1yXmcgdLl5b4/ju/9/emwfNcl2Hfb/b68z07Ou3b2/fHzaCBEiBq0xRsuRYiRZLkRWX4yh2rGyV\n8h9OUipblYplVUUlpcqqMhPTLDGyrChaLJqSKIokQAAEsTwsD2/99m2+2beent47f8wH6okCCOAD\nSJDvza9qanpu3+nlnO7Tt+8951yfzvZtfDfFD33wv+Lc9AWqG126vV1++Vf/W7S4itp1yQZpRoaM\ns7iGx4hMrszq6gZ//vmvMF0q8cDpS1T39zDCJabzBdq9VRwzRIgYzdYN0l4FX5JYePgCay/eoG87\n6NNZ8svTmHKNkTU8kgzeQYS4YGZ6ZtziQ9BqNkmn0wghEUagayph4BEEPouLC+ixGKEi2KxvUzkx\nzcHuLshw4vxxasGQwBqy9vI1Lt93Hj0m0FMqfckjCjUUOcXqtT3KsRxqPo6sKszMLlJOnUU3InRs\nTh8vI4sRcaVMriMxtCJSloZt+qiaRr25R3xbRoulmcmdIZnIkikVcIoCSZsEyr8ekQTCUIjlEwR6\nRKhFpAppqEaoQiYc2extb5PJpAh7bfqjHolMnOmZEktLS/jRCCOXxPcDTNMklY2jLSpIisLe9QO8\nmEGmEEdMpQjVOpJIYSQy3Ly1iqTIFAol6o0u2UIcJBMjFWdre5/KdJLllSVur73I1kaPZ798lcXF\nU8zOnOT6KzeopJLkiwVi8TiZcoFRaJNIHi1d0t2O7/lEETiOy8gdUShmKZYK1Ot1pmfKvHLzGkUt\ng+c57OztMJsrky1laTo1NrZus3Vzi/sfusDHfuAnKGaXeOnK1yiUSvzWH3yazqiNvesyqySZqUzR\n0cBInaAcl5BklyC0KBgXEP441jiuxnFGDv2uSbtlEvgaQrVZX79JMtEhaVQozU6jBSH7ex32djq0\nuh2MrIp6xC6Od3DnR9i2TSKRwLIsEokEijKOqU0aBnu728RjGpqm4ToOQRxiuRTtm20US6L68joj\nd0jLbDBod4nnDR79yH1UpvII4WE6XQ7sVTIVm+MP5rgd3sb14syfOYaoxJi5sEShsoJhBGzceo5b\nO3sY8QqerKAkciQzNgvHyuRnH0VN+3zlG1+gVd+lGJvFjnps1DvcunkN9yCaDIS8AbIkEwYhzUaT\nKIyIlws0Bj167Q70LXZadRzPRZEVbNtBSD4z81l6XQlZdbBHQwYDGA6H+H6A5w6xsZDSMsZUkmTJ\nALlPr99itNWhK8dIxxcIw4hiYTxlgmEYZDI6jhfQarXY29tj5fgDhNGQ+fkFhK+g+m2OHz+O58hE\nElzf3eDcufNkMhlQZRrNTYQ80fG3oqoqCwsLbG5uEoYhuVwW0zS5desWlXIFNZtit92kPDfD8KDJ\n3uomM5fKHFSrWMqQpelFSg/O8GM//DPMzRzja08/wQc+9j6++MRnaYXXWTy/wPbNHQLbIzalUcgl\nOHbpB8iXMijagK29q2xc20aSVcIwxDCSoPlMTU9RyE8hJJ8rrz5Ns+mglDOkUxLmYEB1/4DaQZeZ\nmSXWbq8zW8xh26MjyeDo2WBkGcMwsCwLcZjfzfU8Lpw/fRj90afXaVMqlVhbXef0YxfJLZVQX9B4\n+ckXaa7tce7BczjRiErKQF8o02ns47kOES7DUQdz1CTwQyxhk5xJk4okgmSLfuQzbLY5GF1lOrPC\n1qpDPn2MRCrJQafG4uwyvnybkRty7dVVTt8/y/ziDHvbq1RvrPP84zeZO3mCYqXAxtU1giP6EN3t\nREQUCgV2dnbQNY3TD53CGg3JrWXYunaLdnvA0tISxUKRXq+PLI3wgz61+gbWKEU6m0VIGoqi0Ol2\nCMKQ/bpPOVFhduUknWqXvOYTz6RxPZl0egoCwfT0FIqs0Gy1SBpxdE3CDxU67S62bVOr1+h090ln\nZQgFS0uL+H7Ayy9fp90dMHt8mRMXzxFGEZ1uC0e1CQnea3F+zyHLMvF4nGwux9bmJnIsRr5QZGN9\nndOnTpMs55k9tczttVU0LyCdSGCkkpjS2M8ym0ty8cSHOHfqPlw34P777+dLL/weL279GSJroalp\n9LyG7oTEihpD2Waz9gWawzS57DTNxoDQF0xPlalWq0xPzeCKNql0ir1Nh3RWsLhUZnO/yvr6Opsb\ndSIXikocWZYYDof0u33CpsXSwuKRZPCOXoE7zTZyEJKNG/iOhyIkOt4IOwpQBgFuZ0TpYoWOGDF9\nfJm0KjE1leDaEzeZzy1w/NH3Y9omw+EOB9VVBAniioTnD0E4+GsK7brPyJGZP7mEdd3DbFjkji3Q\nqTcpLMnUD/YpTc2TS86wW10nX8kiZSzscMRO7SbDnRqVj5yhNoyoLOfQS3HcKwOWTpxD7vVIDyLi\nTNJhvR6hFzBdmaIzHJBfmiMeqoSORDKWpHVQJ9IlygsV0pUMxAQ9y6PddUmkypSnZxj5PWxaKIqG\nGHncenGNqeIJDEPF7LcYeQojr8CZhQtESegNWuRzaYyEgTk0kXUw7Q6FdI6R0yfUIJdK8PyXnmFm\ndoreVpfe0OH42ftI53IUZotMrcyQnyqhGDLNZpOD1j7Dgflei/J7Es/3cUY2o1YXxXQolBLkMnHM\nxSLxlRye53IsWaHh9UnbIT/wkY8zd/oCVqdF1x9SPnaG9y0+imeDHJdZ23uCK6/8Po6l02n7uF6X\nqYUM4W5Eux3hFxWazQOECBkNbVwnYmp+nqHtEi8kiBUlvBEMOm02X13l7KNLZBayZKMmXmfErWd3\nOb/8QaYKOaprL+OqAcVCgr4/InEyfSQZHD0UTpaQFQV7OECNJGRFJh6PsXOwTyySsLZrZOIx2gd1\n9JhCLB7nq5//ArXdDYysQaKYxFFATSSJfJ2cliKfXcTz+zQ7bWJynM6Oydp6jRMXj9EyWzj9BOmo\nwsnFC8RLOh27jl6KoSk5bCskJCSRyKDEh4S+gxt1cC2Lbzj+9oEAACAASURBVHztGZruHrMny/hS\nQHGujB/4bD93k9OVZa7orx5VDHc1siyPR+09FyWug+PzwtPPMrSGxFMpRmaHUAoxRyY+Plo8gaTE\nSWc0FMUg9Af4hOBHDLs2o66LWpKIJ0Iy2TS7gU2t1aJYPaB0rMDm3iqJY2dJiDizc9PUGzUkTeAL\nlwAH2zeZmZrB3OpiNhzazT5yyqDe6pHNlzhz4QyO6+AR4AcOnu/QH3QZmiZBMGkBfitBELC3tzvu\nghIKnqKztr7HbLHCWanEgrJI6sQjJBYhLcWJLyzDdA5/pwXJGHY5geIJiMOzq1/j8ed/m3RSY/XV\nFrVqh5XTWcDBsSUC2+Hi+y7jKia6riFJAlWV8bw0frePFHmEsoen+nStFjElREWm1bbIGjnSWY2E\nPcOxqbM0W1WEorB3sMf9Dz3AQsXA42h9gEeeDCOMIkrzM3RHQ1rDPrYICVWJTCqNFoA1MMfJFV2P\n+y5eJgh9br+6hjzQSBdSDOQWsuSRShqUCjNk0mUcxyYeT2EkytRrDhv7DWRDoGcVZpePUzpVpu2F\n3Ni4hq4l2d5o4Tohuq6RLxhYo/5hcoYYo+EIoSskSlmef+oVklaZq3+yxbNP3CaRTZE1YpzOLPC+\nkw8R+pNIkNcjDALW19cpFYtomsbe/j4vXnmJMIiYnpqCKEIwdnnSVI1cNvtNtyfXtTGMDLJI0W07\ntJsj8sVpkjNxLMXElAbESxr5UozeoErfrLG4XKZQyLO1tcXW1jblUpnTp04xHFq4rociyxBp5HPz\nWCaEYYzRyMd1bRqNBqPRCNd1OageMBxapFJp8vkCqVTqyLOG3c0osoznefT7fbzAZ2e7z4Jxil94\n7O/xQ8WPcDHzEMvzj1A5/ijx7GkY6BBA5MW5/cQmo36IrcB6a4evvvT7eKrPcCDT7QyIxIi4EZAw\nEiSTBlEUUq1WKVfK1Os1fN+nXK4Qi8XQVBXXdUkl08gpgSn1GQ4tvvr5x6m+3KK7GbB6/YAwprPd\nr3Hl9jWGIuDMQ/dx5oHLTE9NI4uj5fR8B6FwgsJUhQceeZj9rR3avS56Io4uBK39BifOn0Utp5m+\nvAylBBv1Pfr1PoE5pEmf45fn8f0hmcwCN599hWpjFU1XEJFAUTTMgYSHxtKxLOgBje6IUHUonwIf\nnds3r3Lm9EmUWIzNjQ2mZ6Y5deoEucI8m83niMIIL/IpzFeo7lTZf6lNrxOgnynQMrsUjTIXKydI\nh6lJOqw3QJIlpsoVZo6tYEtjx3dVUzCHJhsbGziO+01fsngsTrfX5pXrL7GwsMD2zjbpfIq+PcDt\n+oR+jISRQKRBNWSGQxNXisgn4+xVN+hG+1x+9CK2M84ovrOzjapqzGgyI3uEJEs4tsv+9Q2W0seh\nHGN7axsvGrF/UGVpaZlMJoNpmtiOw9Nff5qZmVlkSZDP57+Z3WTCHQiBZY8oTZUoGWk+9b6f5LH3\nf4yknob2ENpNSDpEug5ygIgnIYLQtBhUt8kGx9js9/mzZ36HkQgImGd3+yVarS4nT08hqzaJeJpE\nNkUwshhZI0xzMB4/SCTY29tjfv4yzXYPTY8R+hF9v0cghywtLvLq869CR+X61S3Ugsvxi4uUluZR\njHGC3XQ6ja/JDNp9mo3mkURwZAOoaAqh5qEldPR4gotnZnj+yW9g7/rMlHOc/sTD6NkiW40tzPo6\n/Wadiw9f5PqVa3zsUx+nZdVY3bwJvsR8oUR/Y4erT14nfWqGYilJ0OkhSYJEIU5hOoXTVah5HWJp\nmfXaKnVnj6kz0/gRtHoDdmrbrBybR4rSiIEDCegP2hT2cxwrLtGy+xiRQtD0sSyPYb1JMizgdXqT\nGcPeAEXXmTq5hBWa9AYdqrtVEimDvYM9CqWLzJXmafXbqHENSVcQocJCfoXmZpN6vU44D5EWoss6\nSkxGjoUkdIVUYpa99VVkYJRwiBfizC3M0djvUMmWWVw6gWUNuXLlRV554WXmFrJMLedpD+oMFZm+\nXmF+YYGePUTr9tjf2CQ86xBUfNBhplRGeAG765v4gcfUbBFJmmT9/lZCO2BZzPPjP/zDnFw5wXRm\nZez7BCACBrvbCBmSywtQzENMhq4L/RamW8duHPC7f/47fGnzT8gs5whHAbYHqXyMXDmFFtMZ+R5D\nUUNfTNIYbtN9rskjjzxCNp/n+vXrbFa/wmJlijNLC2zU17GHQ9KxPEpBIzczTWO3T5YpiBza9Q7J\n9A6ZbIFkxiAIQ2zPIdIMBr5zJBkcfRBERKxu3KS6XkPyZabOpkhkNIKGS2YxQ0PqkRNpuv0u9fZ1\nwpGLH1N5349/CKOYw2z4+D4c7FTZfGmNK195jly6SOxsml63x8616+iaTqaQJ5FI0N86QCFJXK+g\nGltMHVtkp15lpnSccxcf4ObqFZ758lPo8jNUTpbwlYhuvc7Gs00u3/dhSsdLVAdfJ+w7hDdDypfv\nw1EzSGEfZTJn7OsiqSpdz6LXr4I0wgsczlw4y40bNyhUiiRyBvV2nUa3Sb3bQHdijOojrr96i9nZ\nOfx+SKg7VJt7uK5LYXqWTNwgtGOklBlmphfY695gMAwIwziKUPBcQaVYQKDQbg9oblY5v7SI148I\nPIfpEzMkDR01BnMrUzSuBwydOLXNfaS8wihymEtO4WVsAtvh6rVXKVYKaJr+Xovzew5DM/ilf/C/\nkJ+ZBx9wLcJmHSHLeOaAdrtJIh4nKSuQThKFIDojnG4PazhA2Wtx2knwvGXgtfoIRgQR+IyQNYlU\nukyn16Nq75KQ+oRSSDJRYGi70OsjFBU1IXOwt0XcTWNLA3RiBFbIlVsvUskeoxyk2Hh1DV3TiFsC\nt9fD01OEQcj29jazc3PEUzmyhe9yOizP8bC6FqfPn2JpaYmNnasQCZLpFISwt3tr3OQddjCHI/qN\nFt5QZvHEMRRZplKeoZyZIep5/D//5/9LaIc8/OhpjGSBrWqXmaWzOG6btFHGtSLaLYsTK/ehpVIM\n7BBVFGnWq6RifRbnFojHSqx9o0YiI5G5lGPU9NHlGJUP50hWlskmNDYHL2MeSCyzwvHCIzSbFnMJ\nBzGZFvN1kWUZ13ZoNhqkMuMYUVlWuHTpEqlUChQwEgaZdAYhCZ778vO0tlvIiszc3Cy+cGiaPWRZ\nJp/Po2sxZEWhXqtjDk2MpIHhFIjpWXQ1S6fTpllbJ5VMUywWmZ+fpbO+S6dtI4UC1cggSzJBaFKt\nDQmckHbnAC/wSKXTtNsdmmaLIO7w9FNP8ZGPfpSDeo1up3tkP7G7mWKpSH55HoYu0cBCIBF0BrS2\nt4gbBp7jMggCSkKA5yFkFSRBc3MHve9QUrP8rYuPUbM2eLzxdazIZLfWG/f7pVLEYnHCtk2lsEQQ\nBHRHPfK5Ap1OG0kSLCws0DEDnnzmz3jmi+vMXl5k5sI0jf06vW6fguIxv7JMo1dlYA4Y3O5xfOk0\n5XIZc2CiqirfeObrzE3lielHe8C9g2kxIy6du49UOYnlm8STcRKJOMlcmm6nzfLCHIruEkQ2sizR\n6/WJXJ0gCAgj8HyHEIvqwQ623+XYyjGs0MHeOeDE0jmypTRPfPWzrK9WCQKNZsMkaexRUqbI5AzC\nyBvPO2pCMXuGk8fuZ3rpKbxeh2BNg3hEYIxI5xUUo0noGHzyQz/CYvoCWjjN6vo2t29eJZPSJwbw\nDfA8D9f3cFyXqG/T6w1QhMbU1NQ4I3gQkM/nxxFA8ngWrzCIOHf+NJlshoHdxcBgaWmZnZ1dOp0O\nsUbA7l6N4SCkWj0gmS3RbLXotBzMIQz6HbrdLuVyiWPHVrj59HW+9tUXyC6lue9Dl4nFVQK/R7c9\nIOxHJBIKXT+i3qgj6zEsy6I5bCKk8YxniUSClnn0fHF3N4LxzegifI9gp4a7f0Brp0oYhDiew9TZ\n05DNgOeDGxA2mrRXN7lw8TwxJYWzW6WcyeFWXYxyhqVYHstuIcuCdrvF1maTCxcu0m23Segy8XiC\n/mA8yJHLZynkponpeczBLZKpEsOhjes4nD59moq2QCqTonS8gLqrcHCzzvDApjvTxfU8pmdniekq\n6y89gYiO9hZ35FFgRUhkYykKqTyVwjQHtRqr19cQjsTcygqRppJKqszmi6TUHK1aF7PTxx2NCD2b\nkdmg017n+a8/xeLMHLlykvpWg6vP3CImJ3FDh3S2wNb6PiIKiCWSRK5MPrFIjCKN/R1CAdVWG9M0\nScfyXLx0P7XtFn/x756kttkkZVRIuyWm9RgfffARPvXYz2Iox1jb79KxTJKahAhBkiahcK+H77v4\ntoUIIpyhR+AFWEMLzx3P/IccoidUCCLaey16nS6zS9OMrBG3XrnN+vUtMskySSONLIf0ug22V3dI\nKAmyiSxZI8ex5ZOUCkW2t9dwnB6uYzEYmIhIo1JcZOXMSU7ff46FpWVEqKIJg9HQI5XNYOMSn0oh\nZzTqO/swCJB9GWs0RNMVZFmQy2dZWFgiHjfea3F+zxEGAcNGG9/2IBSYrQ6u52OaFubQ4tQHH2Pu\nkQ+CLBM6Q9y9barXXkaLKUwtLBDsrjNsbLF+a52RkmLl7IPkchrDQZ+djQZ7Gz2cjk1rxySfWUSL\npbAsj26vRb2xS7PRJhnPMDO9hIRB7WqT3lYfRZVRYiGO2mavswpyQLfbxrdd7KHFbnWbRm0fyXUI\nRxazi8tUDxpHksGR73zXcfjKF75ItlykODtFQk+zcWOdhcwSuftncSQfz7Z5+k8fpzv0CW2JeFKn\nur1DEI2I5QTNzQ77r1RZOL1MUk3jDgcYikKERbt9i0HfR/EECXkI6SSzMwvMT50jMeyw27qK1+/j\n9Hys0QEDL49WzFC+uEJMlbm0cpYfuv/HOF45w2yuhBCCzTb0oxHgIAUORBqu5cJkEPh1kSWBHHhk\nYmkODg7wHR8rGuJ7HiISOMEQf2CREXlaGw1SCYP8VAbdTdBcbxNIAk1OYvZMNEWQyxhInkqMOLlk\nHj3UGZkW+XyaVEpi5NRQFJVG7QDHDoi8GBiCmKayML9IGISYTY/QS+ApMscunqfTsqi4EnrfJuyD\nH4bsH2yiKAr9XhffcRm5k1RYr0cYhmxv7pCWdYpGmnqvB56Lkklx/OJFUucujZtIdovO7irmXp2N\n69eQwxCvvoUf2viyw85Lt5Dun0ETBUTYZ6pYpLbdo5SfpqILklGeUysP0LZa3L69Sa4IfbNGrzck\nLmmsrKxwNTvF3ot7xAYSlz91EkX36Xnb9EyHqGswMof4oUsoeXTNAV7XxG+1eOLLX+WTP/vTxDK7\nQPVty+DIBlBVFPrNFmsb63z4Ex+jWCxy8uwJukEL4QvyqQJxYRGEPkHgkzQM0pkMvX6PwVqfMx88\nxVNfeg6/b9HWd6i9lGRl9gwxucfIrLK9u07MSfO+0/ehxkxeXVvjlf4m6fIWgdbHVQbgDVEdn6e/\n+Kd8+OMxThUrXPybf4eH73uUmeICihZDkiJUPyISglgEgnEaoDCMcDyX/WEHfzJhzuuiyDKarqO5\nLrZj0+v1SKcyjEYjwsMJtP0IrNBiY3ODXDmPqml4w7F7jKKGIA0JAx/XkVCkNGosHCfP6LSQ5BiJ\n6bEHfyaThYFLp93i5q0Gtu2wMHeSKArQVB0ixnHBWY2BadLtdiGMiGs6jqoSYWMkDaSehdPyuf8D\nD2KESVzLp76zwbA/eI+l+b2HEALTHDIwm6iViFHkYVkD0rk08VIeQh9GDu29Lfare4x6A9Zr+0yl\ncjgyJM9cIu4HXLjxPBvSNgOziWuPY//1hEDRHSJHIplKYlkW8/Pz9PotGvVNHM87zDjjk8nrzJ6e\nJjWVRMl6hJ5GpMZxRwGaotK2TBYW59nq7VCtVomSGp5lYUQyuUIexx6RNI7Wwn8H6bAgqcYYShaG\nrFHbqPHQBx9ko7qBM3QxdxvYuoksyczPTzNy0/RbHZyBTd7IYrYCvEBFMmx0P4WjhvS8Lg8+eIaZ\nuQUeufyjXFg4y3R5Dsvu8sUvPs4TLz6LZLUZ9HcoaQmmL3ySSnKFhcISD5y6j1K+giTABUxABnII\nEIJQgBeA6/oEQThO2BqG7JodvEmUwOsSAS9cuUIYjGUmJAlV02i127iOS3xaxUgnWF1dpd8bMDU3\nxcHBAYqlcnLlDEO/jeO12Vo/wB5BpVwhn1doNYeY5pB8PqDX79HuHWC7Dqqiks3FsEZ9tnavM3KG\npDMZGs0WAKViCdfzMC2L2ZkZCsUi+6MmsVicndoax6dLxNQ4p2fOIgYKg/6IVq1NOZ1he+Lr+dcQ\nQpBKJen1h/S6XbLTZUpLc5SXl5EVmWgwwDKHbG1tMRh22FhfxxIBD37iwyTPnAMMqPYp5Sso9hr1\nxg7tlosfBCRTOkKxGI5cNrc2MaZK6DmdmB7D8xMgebz44suUkyVy+TRhJoSURiZbRFNUhgMHx5bR\nUDl3dpHmVptcNotjO0RuROB7VKtVEok4QpKoTFWOJIN3YABDkjGNIJvjyrMvUF6eY7O6RzybJJPK\ncrt2mxvVV0nlsiwtr7Bb36B2cECzWmNqPk9kRfzkz/8Mf/zb/4qoJZOeyZDN5jl54j7OLD7C8lQF\nQwdFgoRa5Kd+7G/z2Ic+xo21XW6uNlCMEj/+qXNUUtCw4NrNOn/4Fy/RNV3cUYd8VieZiWEkdcqp\nJAEG9bZP52CfxsEOVq9NQIDpj3DcybSYb4Q79ImkEFmWSMTjxGM6CV1nOBiQnC4ReRFbW1vEEwmE\nkBChhOO4mLZJbiZNP9wBGUzL40SmiFB7DMwBoQuBE3H7xgahGCLkAWrMJ5NLM+q6jLoR+cQ4ocLV\nq1fptrpYgyGzcysszc0zNV2kb3YIfY9EUkdL61xbvUZlbpFkNsWVF16kVCzhhy7JYox4LPZei/J7\nj0hQyJfIagayH5EtpVGNOEgSke8z6NTH92yrQbdXZ+T5/MDHP05peg4cH6weoTnAjUFC19jaucXq\ny1VOn1vh5LFpdrY2CR0FX/Ww+j3qB5sE4YhEUkFVYtS3W/zRf/g9Lt53jjCEmKqTjGXIJlNIkqB6\ncIDvOOjJcfSYWJmna5r0RiMCO2Jva590MkW71kIOjvaAeweRIEAc8vkyupFl+eGTXF+7gW2NmF6Y\nZW+wSiZfQnU0avV9Wgc1+tUmGdIk40lKcxlEFCBiGfotn6KcICsX8AYKt9dvcvXGq+iGghzKPHLf\nZXKGwc7mgJeebfDq2j4kN5GMfWKKzR/99hM4/SaL57O0PZPnXn6G4lyOdCFHLJFmceEYM9OL1Hfr\nDHc6SH7I6q2b5IwUkmlhjybZgl8PgURcNxiYJjNLs1S3NlCiENcaIguBYstIyExVKvQHPcIwIqeX\nCIo+JkOSuorlB2TKJdzIJorBIOxTa9RYzJyhqJYxzQZa3EeIHqNeDaFO4+7pJPsGqUISP+axOLNA\n4Accmz/G3PwZbDfA6ps0G9vIIqI4N0OoHWNjawM97tOu7VOZTzM/V+agUcPEQ9Envp7fiiQkMkae\nkYgRRRGSJIEdgCJwTJuuWaPeWqPXb7K/V2Xu2Akq2SnEUCLsDbDaDbadA170t7AYkMjIzOXLZOUC\ncVzsZoDXSJPSIg7Wb9H3u4xSBxjJEXkjxVKqQE9yGTk2CSfJ/qt7KMcCRosWiiTT7wxYOLaAkktj\nNUxMOaDdHfDAwgVe3n2JmJ/go498gkCR2d7ZPZIMjp4SX5ZxU3F8OaS4UkTRVU6fOoUsjQPoM/Es\nkh/ywvUrRBFo/ZCUG0dLJgg6KmtP77C/8Q26jRa5WAWGHtevPc+ZS8dQCxGr1dtMR3kWyydQNBlJ\nQF7J0WutcWA9TmT0+Ldf7hH2Lax1l4uVGdSoT6gMOXupiGIoLK2cwojPo8UCtHiXUbCNSKfJJfME\nWwHbzQ3OxYooEzeY18X3PBzfoVQuUilXsPs9bGvIwDTJ5XLYtk0kwwMPPMALV17AHAzQwgR6TMf3\nPIamgx0KFCnk5MlFMtkE1YOA6elpVE8bzzligGboIDIM2x0ajTb4GvlCAUVV6Jk9oiji/PnzLMwv\n0OztYns9OrUm8YRKTEuRzeawLIt4LE5AxMKp46ytrVFZnmcQORzsrn4z7fuEOxCg6jpRGBJFESJy\nx6P7noc1HNLpdGi329RqNfqDPnkjRUJoUCwS9tpc21njye2XOIh3CVIhUQTl5XlKM3O0RjfYbzeY\nzy1QLpWpDvcItQjXEXiuTSqXx7ZdhNCQbBk9odP12wxqNhm1xOz0DOfOnSVfnqJW7xP6CWJqjG5n\nk2Z7m0RS5+zZS7xy5RZ6XDAYHK2P9x20ABWEEiOZiaEkoNVpkkmPYzErU0kWy0v8/pPP4Ac+IhbR\nU32Of/Qit669wpU/+xqSEyczVyQvpRDdkPxSjtRjedqhiWFO8cjpH0RLqhhqAs+NkOJQczboBFcx\nUg0sa4iuhKSLafpFSKQK9AdtPA3KlWWWTp5BjgmqzVcJRw6j/S6yppNeylAoaJxjns3rNvZBH6RJ\n/9DrYTsOJysVcrkcw+EQIQTWyMJxHVRVHcfYxjX0mI6qKjiWjwh8/KGP7/lcmr+fheQJzGEba9RF\n1mQSiQTJ2RL97ZDt7S1ayg6pbJxUKoEIU+SLGlFfJkaM9bV1lLkYp06fIpvL0my1qLV3CGWb4dBH\nVbK0Wn3K2cOYZN/noF3Hy2okygXkTJJAVzGSBr6//16L83uPMEJEEbKiQBQR2iNENO4bbzQaNOoN\nOp2xX6YeizGVzpFMjAethoMuj994ic+/+gS5Dy8wPTtL68AlEAaJcoFaL+LYxbNEN1R6vT5qTCWW\n0om0iF5nwN5Om25bY648gxGlsGyLqdNl9HSGs+fvI5vJMhqNxnP69A6IGxoVI4fZLdLubpPPLHKw\n71CvDikYHppyNI++oxvAMKKSLqCkwO21Gbgho+GIG9evYcTimO0Ot2+uUVkuoxgyuXgKIxOSXNFR\niznM2y7B0CGmKwwHQw42t1h6uIyu23hGg3/31T9GHlqcXX6QH/34T9D0Iz77ld/k7PsrlKrn+Pf/\n+ktc+lCRSPQYJlS66oB6a4uTF89z6vwp2h0Lq1/D8taRAwPfBi1j0DRrZPIxlJSEozrYaQlvkizz\ndZEkgSRJ9HvjeOnhcMhwaBGLxUkaSTRZwxqM2N3cpVlrkdWL5NJZ2t0WtjsCAYlEhjCy2dq5hh8l\niCkajVYTz9Yw0lk+9PD7abU7PPn408zMTKP7EIoAyzGZWZiGosqxxWVuXr9Os9WjMJ1lc7NFUi+R\nKhzn5s7X+Vr7CcIowLEdfD+kbfXRdZ391gGBHLG0sszm17fea3F+TxJF0dj4hePMPmEY0e116XRb\n9PpdWq0Wo5FNsVyikMkjgohwb5cbt15lvXuAFY+QnD7HC3NkDY3VdYuDzj6eFKKnkrgxQaNTw1FH\nCAuUXAIpTJBKJhEZjZSWZdDsI3KgJlUuX76EkciwvrmKLsdo9LaIZW2SuRJpVWPxRILddRVJldBj\nMcqVGU7MJVhbvXWk8z/6IEgA+UqSZlBjc22TgQX5VBZrt8qtG7cRlTRnH74PRRbYzoiskaK+3cTt\nBCgpGz8zQoxC+hjIMy7HL85i9U1UkSSfiPPY5b/JiemL5DM5Bnaf3/7D36Da2+Ni6iRuM6JwfJ4A\nj0A3GKmrpOeWWV75OMcKJ9k1W1z78hNUThVRM2U2P7/K+Y99jBCVrasvMSXP0a+FjHoKrj3Cn0yK\n9LooioLZ7+C6LvF4jH53gK4kIBBsbuzSrzmMejbxRJxKbA6/H9DtdZg7NUusqNF2d4mcPt1BF8f1\n8WyFCAkrdPGTI6K4Q2rmIqXKJW6+0MAIHfJqmh11F5Ie+fkllmZOEu5UUbb2yarz0C+SaLcx/JDK\nvE480uns1imUZRRimKaDkXeJGyojt0muFEPVE0STXo6/jhCEXkgUguu44EG/36XV2WPkN+mbXWq1\nJnosxsLCEpYfYvb67NfX+fKtJ7jprnPuo8ex1dbY11OtMOw8gRvrk0qmqVXrmFIfshEf+MAHaDSa\nXPmPNymeTCKSAkO3GIYdar02S9kl3nfmB9BHMrvVVQb+PnhZ9L6KHTo05B65k2WiZIyepWJkFTKz\nAZ3eAOP8JYT13X4FFgLHcfAlH4RASB5h6BJFoEoxzl48R3q6wMi0iSIZRY6xv1+lPJUjkhzSaQlV\ngyg0uHj5OAcHHdp9m7XbNa5p26ysnGK1egNdT/L1Z75MrhQyszDF9Ws3SClFPvDoB+i0X0adkhC2\nydraGp5h89DUSdqdAQ9Ultns1hmGElKoMTRdsoUUt16+itlqI8sKSTXGyLYns2K+AUEQMBpZ30yM\nmkqlWFpYolqt0uv1sS2bQX8wjgWOBJ7r47oeOzs7PHTiAYb+OA54ODSxRhapZApFGc8SmE6n8IMA\n27bR5IgPvP8Rtte+TiqZojJVYX9/n63tTbKJAo+dO8V0SuPlLYdOGNDt9IgChZs3rlOenqI0YzC0\nd5kqL5MshTStPTRVOeyndMatnAnfligCx3YYDoeMRiPq9RpbW1v4fsCxuTkMw2C/Uacf9ri9eZsr\nt65RtRtU7DLJXAJd1zEHFoN+n6zqAYIojIhEhCwLMtk0S0vL1J7v42ESBCG+65JNx7j/+AMsLiyi\nKhrPPPEUYcIiczzFy8+9yH2nHwJVYXNjE99TGPVtImB3b5dCIU++kCU6dHM7CuKoF4cQogHcLe8V\ni1EUld7rg/heY6Lju5u7TL9wBB0f2QBOmDBhwvc7R06GMGHChAnf70wM4IQJE+5ZJgZwwoQJ9yxv\n2wAKIQpCiBcPPwdCiL07fn/H4o2EEP+DEOK6EOKzb+M/f18I8WvfqWO6W5no+O5nouMxb9sNJoqi\nFnAZQAjxS4AZRdGv3llHjGcZElH0ruaZ+ofAB6MoOngrlYUQkyynR2Si47ufiY7HvGuvwEKI40KI\na0KIzwGvAvNCiO4d639KCPHpw+WKEOL/E0I8J4T4pqJznAAABqJJREFUhhDi/W+y7U8DC8AXhRC/\nKIQoCiH+SAjxshDiKSHE+cN6vyyE+KwQ4kngM9+yjR8VQjwphFgUQqy/JlghRO7O3xPemImO737u\nNR2/232Ap4H/I4qis8Det6n368CvRFH0IPATwGsCfVgI8ZvfWjmKor8P1IEPRVH068A/B56Jougi\n8Ev8VSGdBj4WRdHPvlYghPhPgf8R+FQURVvAk8AnD1f/NPC7URRN0ga/NSY6vvu5Z3T8bj8R16Io\neu4t1Ps4cEr85Xy8OSFEPIqiZ4Bn3sL/Pwj8MEAURX8mhPiMEOK1lLB/GEXRnQn+PgG8D/jBKIrM\nw7JPA78I/DHwXwD/+VvY54QxEx3f/dwzOn63W4DDO5ZDxhnoX+POjJQCeF8URZcPP7NRFL1b8xYO\nv+X3KpABTrxWEEXRV4GTQoiPAF4URTfepX3fC0x0fPdzz+j4O+YGc9hx2hFCnBBCSMB/csfqPwf+\n0Ws/hBCX3+bmnwB+5vC/Hwf2oij6VoG9xgbwnwGfE0KcuaP8t4DPAf/mbe57wiETHd/93O06/k77\nAf4T4E+Bp4A7U7b+I+DRw87Pa8B/CW/cd/A6/K/AB4QQLwP/jHHz9w2Jouga4+bx7wkhlg+LP8f4\nifI7b+N8Jvx1Jjq++7lrdXzPxgILIX4K+BtRFH1boU/4/mWi47ufd6rje9ItQAjxrxh34H7yzepO\n+P5kouO7n3dDx/dsC3DChAkTJrHAEyZMuGd5UwMohAjEOD7wqhDid4UQiaPuTAjxYSHEHx/1/xO+\nM0x0fG/x3da3EGJJCHH1bW73PwohsofLvyjG8cOfO+pxvhFvpQU4OvTxOQ+4wC98y4GKw+HxCd+/\nTHR8b/E9r+8oij4VRdFrIXj/EPhEFEU/827v5+2e5BPA8UOLflOMMzpcZRwv+INCiKeFEC8cPlWS\nAEKITwohbgghXgD+9pvtQAhhCCE+L4R46fAJ9ZOH5ZtCiF8RQrwixnGHxw/Ll4QQf3E4FP8lIcTC\nm5R/Rgjx62Ice7guxuE1iHHs4d+64zg+J4T4sbcpn7uBiY7vLb7j+r4TIcSKEOKKEOIhIcTPi3Es\n8Z8IIW4LIX7ljnqbYhwr/JvACvAFIcR/f3jt/N+H18eV1/QnhHhc3OGHKIT4mhDi0pseUBRF3/bD\nOEsEjEeM/xD4r4Elxh7i7z9cVwQeB4zD3/+EsY9PDNhh7L0tgH8P/PFhnQeBT7/O/n4c+Nd3/M4c\nfm8C//Rw+efu2M5/AP7u4fLfA/7gTco/A/wuY+N/Flg9LH/sjjoZxo6XypvJ5274THT83uvgLtf3\nEmOjegq4Alw6LP95YP1QFzHG85PM33EtFF9n+X8DfvZwOQvcAgzg7wK/dlh+EnjuLcniLQgrAF48\n/PwGoB2e0MYddX4EaN5R7xrwfzFOt/P4HfV+9DVhfZv9nTw84X/BOGj6tfJNYOVwWQVah8tNQL2j\nvPkm5Z8BfuaO7Q7uWH4VKDF+JfjV9/pC/S7eEBMd30Of90DfS0ANuAGcvaP85/mrD8IvME6V9dq1\n8HoG8DnGxvS149oGzgAJxuFyKvC/A//NW5HFW/EDHEVR9FdCXMQ4+PnOkBUBfDGKop/+lnpvNzSG\nKIpuCSHuBz4F/LIQ4ktRFP2z11bfWfXtbvsOnDsP847lzwI/C/wUb+KVfpcx0fG9xXdV34f0GBur\nDzI2pq9xp54C3tw3WQA/HkXRzb+2QogvAj/GODPNA2/loN6tjs6vMw6Jea3PxhBCnGRs8ZeEEMcO\n6/30G23gNYQQM4AVRdFvAf8SuP+O1T95x/fTh8tPMb6YYRxX+MSblH87PgP8d/DNsJsJf8lEx/cW\n75q+D3EZxxH/nBDi77yD4/pT4B+LQ4sthLjvjnWfZpyi69koijpvZWPvSiRIFEUNIcTPA78thNAP\ni//nwyf9PwA+L4SwGF+gqcMDfxD4hWicI+xOLgD/UggRAh7j/onXyIlx3KDDXwr+HwP/RgjxPwEN\n/vKp/kbl3+48akKI68AfvI3TvyeY6Pje4l3W92vbHAohfoRxQlTz9eq8Bf458GvAy2I8Ur3B+HWd\nKIqeF0L0eRuJEb5vIkGEEJvAg1EUNb+D+0gArwD3R1HU+07tZ8LrM9HxhHfC4ZvFV4DT0VtM4z/x\n7TpEjNPxXAd+Y3Jj3J1MdHz3IoT4OcZJWP/pWzV+8H3UApwwYcKEd5tJC3DChAn3LBMDOGHChHuW\niQGcMGHCPcvEAE6YMOGeZWIAJ0yYcM/y/wPWXxTHuEbFxAAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0c10690e80>"
+       "<matplotlib.figure.Figure at 0x7fc028c84d30>"
       ]
      },
      "metadata": {},
@@ -1919,9 +1948,9 @@
      "output_type": "stream",
      "text": [
       "Confusion matrix:\n",
-      "[[141   3   7]\n",
-      " [ 65  70   2]\n",
-      " [ 32   1 209]]\n",
+      "[[138   6   7]\n",
+      " [ 40  95   2]\n",
+      " [ 33  11 198]]\n",
       "(0) forky\n",
       "(1) knifey\n",
       "(2) spoony\n"
diff --git a/13B_Visual_Analysis_MNIST.ipynb b/13B_Visual_Analysis_MNIST.ipynb
index b5098dd..c600282 100644
--- a/13B_Visual_Analysis_MNIST.ipynb
+++ b/13B_Visual_Analysis_MNIST.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #13-B\n",
     "# Visual Analysis (MNIST)\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -30,20 +24,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below. Note that there are two separate optimization loops here:\n",
     "\n",
@@ -54,20 +42,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Flowchart](images/13b_visual_analysis_flowchart.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -75,12 +57,17 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -92,10 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
@@ -103,16 +87,12 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.3.0'"
+       "'1.9.0'"
       ]
      },
      "execution_count": 2,
@@ -126,20 +106,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -147,46 +121,24 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -194,115 +146,65 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [],
-   "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "## Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
     "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
     "\n",
     "# Tuple with height and width of images used to reshape arrays.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
+    "img_shape = data.img_shape\n",
     "\n",
     "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-functions for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -336,22 +238,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 10 images in a 2x5 grid."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images10(images, smooth=True):\n",
@@ -386,22 +281,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot a single image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_image(image):\n",
@@ -412,28 +300,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nRK5CYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUMAAAD5CAYAAAC9FVegAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAHihJREFUeJzt3XmUFNXZx/HvA0LYVQQFFWdOwAVCFBWDu0aBKCogccG4EGM0osEtAaNx1xglKBzRE7YD4QQNigKCUVFAEV8EJIIi4wYiCsRlhLggIsJ9/5i5XdUzPXtXVU/7+5zjmequ6qpnvPSdp27dxZxziIj80DVIOgARkVygylBEBFWGIiKAKkMREUCVoYgIoMpQRARQZSgiAqgyFBEBVBmKiACwS00ObtOmjSssLIwolNzzwQcfUFxcbEnHESeVcf5TGWdWo8qwsLCQZcuW1T6qeqZ79+5JhxA7lXH+UxlnpttkERFUGYqIAKoMRUQAVYYiIoAqQxERoIZPk0Vqa8SIEQBs3boVgDfeeAOAxx9/vNyxgwcPBuCoo44C4MILL4wjRPmBU2YoIoIyQ4nYueeeC8C0adMy7jcr3xd2zJgxAMydOxeAE044AYD99tsvihAlQe+++y4ABx54IAAPPPAAAEOGDIk9FmWGIiIoM5QI+GwQKs4IDzroIABOOeUUAN5///3UvlmzZgGwevVqAKZMmQLAjTfemP1gJVHLly8HoEGDkrxsn332SSwWZYYiIigzlCzy411nzJhRbl/Xrl2BIOtr06YNAC1atADgu+++Sx3bo0cPAF5//XUAPv/884gilqStWLECCP4dDBgwILFYlBmKiBBDZuj7kY0fPx6AvffeO7WvSZMmAJx//vkAtGvXDoBOnTpFHZZE4L///S8AzrnUez4jnDNnDgDt27fP+FnfDxHgrbfeStt3+umnZzVOSd7KlSsBGD16NAAXXXRRkuEAygxFRIAYMsOhQ4cCJRMsVsT3K2vVqhUAXbp0ycq1O3ToAMCwYcOAH+bcdXE644wzgOApMEDLli0BaN26daWfffTRR1Pb4fZDyU/vvPMOAFu2bAHSeyAkRZmhiAiqDEVEgBhukydMmAAE3STCt8BFRUVA0PHyxRdfBGDx4sVAMPzqww8/rPD8jRo1AoKuGr4RP3wef7us2+R4FBQUVPvYv/3tb0AwLCvMd7HxPyV/DB8+HChZggBy47upzFBEhBgyw5NPPjntZ5gfiuVt3rwZCDJF/9fi1VdfrfD8P/rRj4BgoLcf5gWwadMmADp27Fir2CU6Tz31FAC33HILANu2bUvt22uvvQC45557AGjWrFnM0UkUwg9R/Xfaf2+bN2+eREhplBmKiJBjw/F23313AE466aS09zNllWU98cQTQJBdAhx88MEADBw4MFshSpb4oXvhjNDz3Sz81F2SHxYsWFDuvbZt2yYQSWbKDEVEyLHMsDY+/fRTAK644gogfSiYb4+qqsOvxKd///5AMDzPGzRoUGr7rrvuijUmiYdf6iHMD4jIBcoMRUTIg8zwoYceAoIMcbfddkvt80+qJHm+/+eiRYuAoK3QtxnddNNNqWP9dE6SH1555RUAJk2alHrv0EMPBaBXr16JxJSJMkMREepxZvjyyy8DQV8078knn0xt++mjJHl+0s7i4uK09/30beoLmr/mzZsHpPf08H2M/TR+uUCZoYgIqgxFRIB6fJv89NNPA8Hcdz179gTgqKOOSiwmKc+veeKHWHonnngiAHfccUfcIUnM/CQtYWeffXYCkVROmaGICPUwM9y6dSsAzz77LBBM1HD77bcDwZRekpzwanZ33303UH726m7dugHqRpPPPv74YwAWLlwIpE+icuaZZyYSU2WUGYqIUA8zQz8ZqG+DOvXUUwE4+uijE4tJ0t13332p7aVLl6bt88Px1FaY//7xj38A8MknnwDBdzVXKTMUEaGeZIZ+IlCAO++8E4Bdd90VgJtvvjmRmKRi999/f4X7/PBJtRXmv3Xr1qW99lP05SplhiIi5Hhm6J9KXnXVVan3vv/+ewD69OkDqF9hfePLtDpP/X3274/dvn07AF988UW5Y/1Qr5EjR2Y8V8OGDVPb9957L6DlBKI2e/bstNenn356QpFUjzJDERFUGYqIADl6m7xjxw4gmNli7dq1qX2dOnUCggcpUr/4dWmq45xzzgGgffv2QNBFY+rUqXWKwa++F55DUbLHd7L25VVfKDMUESFHM8M1a9YAwQpqYb7bhua/y13+4RbAzJkza32exx57rMpj/MOVBg3S/6737dsXCNbeDjv22GNrHZNUbcaMGUDwsNPPap3rqx0qMxQRIccyQ99Js3fv3mnvjxgxIrWd64/nBaZPn57aHj58OFB+ogavqKgIqLwd8JJLLgGgoKCg3L5f/vKXAHTu3Ll2wUrWfPPNNwA888wzae/76brC3ZtykTJDERFyLDMcO3YsUH4YT7itwcxijUnqprrr4j7yyCMRRyJR8+23foXKfv36AXD11VcnFlNNKDMUESFHMkPfL+nBBx9MOBIRqS2fGfp1kusbZYYiIuRIZujXQP7qq6/S3vejTTTdk4hETZmhiAiqDEVEgBy5TS7Lr5w2b948AFq3bp1kOCLyA6DMUESEHMkMb7jhhrSfIiJxU2YoIgKYc676B5t9Bqyr8sD8UeCca5t0EHFSGec/lXFmNaoMRUTylW6TRURQZSgiAkT8NNnM9gDmlb5sB+wAPit9/TPnXOYZP+t2zS5AeD6ojsANzjnNAhGBhMq4AJgM7Ak44O8q3+gkUcal150M9AE2OOe6RXGNtOvF1WZoZrcBXzvnRpR530rj2BnBNRsBG4DDnHPrs31+SRdXGZvZ3sCezrkVZtYKWA6c6px7Nxvnl4rF+T02sxOArcC4OCrDRG6TzayTmRWZ2cPAKqCDmf0vtH+gmU0o3d7LzKab2TIzW2pmR9bgUr2At1QRxi/KMnbObXTOrSjd/hJ4G9gnut9GMon6e+ycWwBsiuwXKCPJNsODgJHOuS6UZG8VeQAY7pzrDpwD+P+5PcxsTBXXGAj8KxvBSq1EXsZm9mOgK/BqdkKWGorjexyLJEegrHHOlV8LtLyewIGh6f53N7OmzrklwJKKPmRmTYDTgOvqHKnUVtRl3Ap4AhjinPu6ztFKbURaxnFKsjLcEtreCYQXN2kS2jZq10h7GrDEOVdcy/ik7iIrYzNrDEwHJjnnZtUpSqmLqL/HscmJrjWlja6bzWx/M2sAnBnaPRe40r8ws+o2pJ6HbpFzRjbLuLSx/h/ACufcAxGEK7UQ0fc4NjlRGZa6HpgDLALCDzyuBI4xszfMrAi4FCpvazCzlsDPgZnRhiw1lK0yPoGSP3a9zGxF6X+/iDh2qZ5sfo+nAQuBLma23sx+HWXgGo4nIkJuZYYiIolRZSgigipDERFAlaGICKDKUEQEqGGn6zZt2rjCwsKIQsk9H3zwAcXFxVb1kflDZZz/VMaZ1agyLCwsZNmy6oy8yQ/du3dPOoTYqYzzn8o4M90mi4igylBEBFBlKCICqDIUEQFUGYqIAKoMRUSAZCd3rdCWLSXzRQ4dOhSAMWOCGX78Y/Jp06YBUFBQEHN0IpKPlBmKiJCjmeHGjRsBGD9+PAANGzZM7fOdRWfPng3A73//+5ijk9p47bXXABgwYABQMiqgtp577rnUdufOnQHo0KFD7YOTxPjvcd++fQEYPXo0AIMHD04dE/7+R0mZoYgIOZYZfvbZZwAMGjQo4Ugk2+bMmQPAtm3b6nyuWbOC9Z8mTpwIwNSpU+t8XonP559/DqRngABDhgwB4JJLLkm917Rp01hiUmYoIkKOZIYPPFCywNnMmSXrN736atXrgS9cuBAAv4bLIYccAsDxxx8fRYhSS99//z0ATz/9dNbOGR54f//99wNBD4TmzZtn7ToSnZdeegmADRvS150/77zzAGjSpEm5z0RNmaGICDmSGV5zzTVAzZ4aTZ8+Pe3nfvvtB8Bjjz2WOubwww/PVohSSy+88AIAixYtAuD666+v8zk3bdqU2l61ahUA33zzDaDMMJeF24vvuuuujMdceOGFAJQsjR0vZYYiIqgyFBEBEr5N7tOnDxA8BNmxY0eVn2nTpg0Q3A6tW7cOgLVr1wJwxBFHpI7duXNn9oKValu5cmVqe+DAgQB06tQJgBtvvLHO5w93rZH644033kht+0743i67lFRFp556aqwxhSkzFBEhgcxwwYIFqe23334bCBpLK3qAcvnll6e2e/fuDcCuu+4KwPz58wH4y1/+Uu5zf//734HyHTslWuGy8A82pkyZAkCLFi1qfV7/4CT8byiJhnapHf+wM5NevXrFGElmygxFRIgxM/QD830bEkBxcXHGY303mbPOOguAW2+9NbWvWbNmacf6KbzGjh1b7pzDhg0D4NtvvwWCSR0aNWpUu19CKvX4448D6R2sfVthuC23tnx3jHA2eOKJJwKw22671fn8Eq1wRu81btwYgLvvvjvucMpRZigiQoyZ4fbt24GKs0EIhtI9+uijQPDkuDI+M/RPKa+77rrUPj9Ey2eIfpqgjh071ih2qR4/4a7//w7Zaa/1dxWPPPIIEDx5BLjpppsAZfu5zHe4f+WVV8rt83d63bp1izWmTJQZioiQI8PxfHvSpEmTgOplhGX5rO/hhx9Ovbd06dIsRCdV+eKLLwBYvHhxuX1XXHFFnc8/btw4IJjirUuXLql9J510Up3PL9GqbOKVXOrpocxQRIQEMsNMo0yWLFlS5/P6USzhUSdlR7b4p9K+z5tkhx+Av379eiCYhilb1qxZk/a6a9euWT2/RCtTZuif/mfjziFblBmKiKDKUEQEiPE22a99HNVKV36VreXLl6feKzvM7/bbb4/k2j90LVu2BILuEeGJGvwQutatW9f4vJ9++ikQdNnxjjnmmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VHHXOj4Vcv80Pv/LA8gNNOOw1I7wyfyZtvvpna9g9M/PRsZSdjaNBAf8PrA78Cnn+QGZYLEzOUpX9VIiLkSKfr2vDTRD300EMVHlNYWAjA5MmTgWACCInGbbfdBqRnAv6OIDxBRyZt27ZNbftMsKKhmxdffHFdwpSYlG3rDU+mcdlll8UdTpWUGYqIUA8zQ79UgJ8YtjJ+2NZxxx0XaUxSonPnzkD6CoX+6X7ZjtNl+enawgYNGgSU7yTv2yglN/nO92WfIoefHGdjSrdsU2YoIkKMmWFliz4988wzaa8vvfRSADZu3Fjheaoz3Xu2n2BLzR166KFpP2vixz/+ccb3w/0Yf/rTn9YuMImMn7Kr7FPkfv36JRFOtSkzFBFBlaGICBDjbbKft8zPOh3mO+aWHaqXaeiev82uzkp6Ur/526yyt1u6Nc5tvrO15wc9XHPNNUmEU23KDEVEiDEzHDBgAADDhw9PvVfZeihV8X9tfHeO8ePHA9C+fftan1Nyi39IprWR65c5c+akve7QoQMQTM6Qq5QZiogQY2boV7HzK98BzJw5E4BRo0bV+Hx//vOfgWAtZMk/fr1rT52tc5tfAXP16tVp7zdp0gTI/YlSlBmKiJDAcDy/NnJ4u3fv3kCwCpqfqPWMM84A4He/+13qM/7JYniFNMlPfrVEP8D/lltuSTIcqYKfWs0PtVu1ahUA+++/f2Ix1YQyQxERcmSihlNOOSXtpwgEGca1114LaI3kXOf7/vrp9XwvgMMOOyyxmGpCmaGICDmSGYpk4tuOpX7Ze++9AZg4cWLCkdSMMkMREVQZiogAqgxFRABVhiIigCpDERFAlaGICACWabX7Cg82+wxYF104OafAOde26sPyh8o4/6mMM6tRZSgikq90mywigipDERFAlaGICBDx2GQz2wOYV/qyHbAD+Kz09c+cc99FdN0+wEigITDWOfe3KK4jyZVx6bV3AV4D3nfO9Y/qOj90CX6PJwN9gA3OuW5RXCPtenE9QDGz24CvnXMjyrxvpXHszNJ1GgHvAD8HPgaWAb90zr2bjfNLxeIq49B5hwHdgGaqDOMRZxmb2QnAVmBcHJVhIrfJZtbJzIrM7GFgFdDBzP4X2j/QzCaUbu9lZtPNbJmZLTWzI6s4/ZHAW865dc65bcBjQL+ofhfJLOIyxswKgF7ApKh+B6lc1GXsnFsAbIrsFygjyTbDg4CRzrkuwIZKjnsAGO6c6w6cA/j/uT3MbEyG4/cBPgq9Xl/6nsQvqjIGGAUMBdQ3LFlRlnGskpzPcI1zblk1jusJHBhaO3d3M2vqnFsCLIksOsmGSMrYzPoDHznnVphZz+yFK7WQN9/jJCvDLaHtnUB4pfAmoW2jZo20G4AOodf7UvlfLIlOVGV8NDDAzPqWnqeVmU12zg2qU7RSG1GVcexyomtNaaPrZjPb38waAGeGds8FrvQvzKyqhtTFQBczKzCzH1GSks/KdsxSM9ksY+fcMOfcvs65QuAC4DlVhMnL8vc4djlRGZa6HpgDLKKknc+7EjjGzN4wsyLgUqi4rcE5tx24CngeKAKmOOfeiTp4qZaslLHktKyVsZlNAxZSktysN7NfRxm4xiaLiJBbmaGISGJUGYqIoMpQRARQZSgiAtSwn2GbNm1cYWFhRKHkng8++IDi4mKr+sj8oTLOfyrjzGpUGRYWFrJsWXU6m+eH7t27Jx1C7FTG+U9lnJluk0VEUGUoIgKoMhQRAVQZiogAqgxFRABVhiIigCpDEREg2cldRUQA2Lx5MwAffvhhhccUFBQAMHLkSAC6du0KwAEHHADAIYccUqcYlBmKiJBwZvjpp58CcM455wBw9NFHA3DZZZcBJT3ls+GLL74A4KWXXgLglFNOAaBRo0ZZOb+I1MxTTz0FwOzZswF48cUXAXjvvfcq/MyBBx4IlAyvA9i2bVva/p0767ZKqTJDERESyAx92wDAT37yEyDI3Pbaay8g+xnhYYcdBkBxcTFAalzm/vvvn5XrSPV9+eWXAPzpT38CYNWqVQDMnTs3dYwy9vywZs0aAB566CEAxo0bl9q3detWAGoy0/4770S7eocyQxERYswMfVbm2wcBPv/8cwCuvLJk0azRo0dn9Zp33XUXAGvXrgWCv0zKCOM3ZcoUAG666Sag/FNDnzEC7LHHHvEFJpFZv75kPahRo0bV6TwHHXQQEDw9jooyQxERYswMX3vtNSB4ahR2yy23ZO06b775Zmp7xIgRAJx5Zsnyreeee27WriPV47ODa6+9FgjuEMzS59ocMmRIavvBBx8EoHXr1nGEKLXgyxGCzO/YY48Fgt4ajRs3BmDXXXcFoEWLFqnPfP311wD84he/AIKsr0ePHgAceuihqWObNm0KQPPmzbP8W6RTZigigipDEREghttk37H6iSeeKLdv4sSJALRt27bO1/G3x7169Sq3b8CAAQC0bNmyzteRmvFNFf5hWUWmTp2a2n7mmWeA4GGLv4X2t12SnC1btgDp37PXX38dgJkzZ6Yde9RRRwGwfPlyIL3LnH+Atu+++wLQoEHyeVnyEYiI5IDIM8M//OEPQNC1wneABjj77LOzdp2XX34ZgI8//jj13sUXXwzABRdckLXrSNXWrVuX2p40aVLaPj+Y3newf/7558t93neW91nl+eefD0C7du2yH6xUy3fffQfAr371KyDIBgFuvPFGAHr27Jnxs5kGUey3335ZjrDulBmKiBBDZui7UPif++yzT2pfXdqA/HCeu+++GwiG/IS7bPg2SYnXihUrUtu+M/Xxxx8PwIIFCwD49ttvAXjkkUcA+Otf/5r6zOrVq4Egy+/Xrx8QtCWqy018fBcY/z3zEyuE2/mHDh0KQLNmzWKOLruUGYqIkMBEDX7qHoDevXsDsNtuuwEwePDgKj/vO237n4sXL07bn812SKmd8NRKPlP3na69Jk2aAPCb3/wGgMcffzy1zw/w94P4fcahp8nx80+I77nnHiCYYHXhwoWpY3yn6vpOmaGICDFkhldffTUA8+fPB2Djxo2pfb79yGcATz75ZJXn88eWHc7VsWNHIGjbkOT861//Kvfev//9bwD69++f8TN+WrVMjjzySCB9OJfEY9GiRWmv/TA53z8wnygzFBEhhszw8MMPB2DlypVA+pPGZ599FoDhw4cDsOeeewIwaNCgCs934YUXAnDwwQenve+XDPAZoiTnvPPOS237bP/VV18F4O233waCfw8zZswA0if99W3I/j0/9Zov+y5dukQWu6QLt+VC8ET/9ttvT73Xt29fIH1yhfpImaGICKoMRUQAsJqsQdC9e3dXWUN3HN5//30guB3u1q0bAM899xyQnUkfvO7du7Ns2TKr+sj8kY0y3rRpU2rbl5MfYlfRA7DwwH/fgf70008H4N133wWCVRPHjBlTp/jCVMaVKztoIpOGDRsCcPnllwPBnIQfffQRAJ06dQKCNY/C/Bo4flKHKB7MVLeMlRmKiJDwusm1cccddwDBXyr/8CWbGaHUTXi43LRp0wA466yzgPIZ4lVXXQXAvffem/qM75Dtp17zQ/XmzJkDBJ2yQQ/MovbHP/4RgPvuu6/CY3bs2AEEGb3/WRP+4emJJ54IpE/pFhdlhiIi1JPM0GcXAJMnTwagVatWgFZSy3V+WiffRcNPzOC7z/hM32eDYTfffDMAb731FhB00/GfgeDfg0TDD8Pzq1r66dS2b9+eOsavc+MzxNrwk0D773p4JTw/yW/UlBmKiFBPMkPf0TPstNNOA9Ini5Xc5TPEiiYAzcSviuZXNfSZ4QsvvJA6xj+51rRe0fBPio844gggeLIfNm/ePCDIFm+77TYAli5dWuPr+bbk//znPzX+bF0pMxQRoR5mhn7tVP+US/Kfb6+aNWsWkP6k0a+xnM21t6VmTj755LTXfsitzwwbNWoEBMtwAFx66aUAjBw5EgjakpOkzFBEBFWGIiJAjt8m+2FX4RXv/KpqenDyw+HX1B02bBiQvj6vb6wfOHAgAAcccEC8wUk5fgZ7v2qef7DiZx8CeO+994BgxvqywmslxUWZoYgI9SQzDA8S79OnT9oxX331FRDMfZeL67FKdvhJOe68887Ue/5B2g033AAE63P7bjkSv86dOwNBl6hHH3203DHh7lEAu+xSUhX5LnPh4ZlxUWYoIkKOZ4aZ+L8gPgPwj+b98B0Nz8p/F110UWp77NixAEyfPh0I2qLKzoQu8fFZ+ahRo4Dg7i3ckfqTTz4BoLCwEAjK1LcBJ0GZoYgI9TAzHD9+PAATJkwA4Le//S0QDOqX/Beerm3u3LlAsJ6vn1ggFzrx/tD5nh9+rfR//vOfqX2vvPIKEGSCfgqvJCkzFBEhxzPD0aNHA3Drrbem3jv++OMBGDx4MAC77747AI0bN445OskFvveAXzbAD9krKioCtJJeLvGrG5bdzhXKDEVEyPHM8LjjjgNg/vz5CUciuc5PHnvIIYcAsHr1akCZoVSfMkMREVQZiogAOX6bLFJdfk2ctWvXJhyJ1FfKDEVEUGUoIgKoMhQRAcD8alTVOtjsM2BddOHknALnXNuqD8sfKuP8pzLOrEaVoYhIvtJtsogIqgxFRICI+xma2R7AvNKX7YAdwGelr3/mnPsuwmvvArwGvO+c6x/VdX7okipjM7sOuKT05Rjn3OgoriOJlvF6YHPp9bY553pEcZ3U9eJqMzSz24CvnXMjyrxvpXHszPL1hgHdgGaqDOMRVxmbWTdgMnAk8D3wHPAb55x6XEcszu9xaWXY1Tn3v2ydszKJ3CabWSczKzKzh4FVQAcz+19o/0Azm1C6vZeZTTezZWa21MyOrMb5C4BewKSofgepXMRl3BlY7Jzb6pzbDrwEnBnV7yKZRf09jluSbYYHASOdc12ADZUc9wAw3DnXHTgH8P9ze5jZmAo+MwoYCuhRebKiKuOVwAlm1trMmgOnAh2yG7pUU5TfYwfMN7P/mNklFRyTNUmOTV7jnFtWjeN6AgeGlgvd3cyaOueWAEvKHmxm/YGPnHMrzKxn9sKVWoikjJ1zb5rZ/cBc4GtgOSXtShK/SMq41JHOuQ1m1g543szecs4tykLMGSVZGW4Jbe8ELPS6SWjbqFkj7dHAADPrW3qeVmY22Tk3qE7RSm1EVcY458YB4wDMbDiwug5xSu1FWcYbSn9+bGZPAj8DIqsMc6JrTWmj62Yz29/MGpDe/jMXuNK/KG08r+xcw5xz+zrnCoELgOdUESYvm2VcesyepT8Lgb7A1GzGKzWXzTI2sxZm1qJ0uzklzwDezH7UgZyoDEtdD8yhpOZfH3r/SuAYM3vDzIqAS6HKtgbJTdks45mlx84ELnfOfRlh3FJ92Srj9sD/mdnrwFJghnNubpSBazieiAi5lRmKiCRGlaGICKoMRUQAVYYiIoAqQxERQJWhiAigylBEBFBlKCICwP8D3P5bzM0W5d8AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff410829320>"
+       "<matplotlib.figure.Figure at 0x7f76ba043860>"
       ]
      },
      "metadata": {},
@@ -442,10 +323,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -453,10 +334,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## TensorFlow Graph\n",
     "\n",
@@ -465,20 +343,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Placeholder variables"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Placeholder variables serve as the input to the TensorFlow computational graph that we may change each time we execute the graph.\n",
     "\n",
@@ -487,12 +359,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')"
@@ -500,22 +368,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The convolutional layers expect `x` to be encoded as a 4-rank tensor so we have to reshape it so its shape is instead `[num_images, img_height, img_width, num_channels]`. Note that `img_height == img_width == img_size` and `num_images` can be inferred automatically by using -1 for the size of the first dimension. So the reshape operation is:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])"
@@ -523,22 +384,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Next we have the placeholder variable for the true labels associated with the images that were input in the placeholder variable `x`. The shape of this placeholder variable is `[None, num_classes]` which means it may hold an arbitrary number of labels and each label is a vector of length `num_classes` which is 10 in this case."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
@@ -546,22 +400,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We could also have a placeholder variable for the class-number, but we will instead calculate it using argmax. Note that this is a TensorFlow operator so nothing is calculated at this point."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true_cls = tf.argmax(y_true, axis=1)"
@@ -569,10 +416,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Neural Network\n",
     "\n",
@@ -581,12 +425,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = x_image"
@@ -594,22 +434,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The input image is then input to the first convolutional layer, which has 16 filters each of size 5x5 pixels. The activation-function is the Rectified Linear Unit (ReLU) described in more detail in Tutorial #02."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.conv2d(inputs=net, name='layer_conv1', padding='same',\n",
@@ -618,22 +451,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "After the convolution we do a max-pooling which is also described in Tutorial #02."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
@@ -641,22 +467,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Then we make a second convolutional layer, also with max-pooling."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.conv2d(inputs=net, name='layer_conv2', padding='same',\n",
@@ -665,12 +484,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
@@ -678,22 +493,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The output then needs to be flattened so it can be used in fully-connected (aka. dense) layers."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.contrib.layers.flatten(net)\n",
@@ -704,22 +512,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now add fully-connected (or dense) layers to the neural network."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 20,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
@@ -728,22 +529,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We need the neural network to classify the input images into 10 different classes. So the final fully-connected layer has `num_classes=10` output neurons."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 21,
+   "metadata": {},
    "outputs": [],
    "source": [
     "net = tf.layers.dense(inputs=net, name='layer_fc_out',\n",
@@ -752,22 +546,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The outputs of the final fully-connected layer are sometimes called logits, so we have a convenience variable with that name which we will also use further below."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 22,
+   "metadata": {},
    "outputs": [],
    "source": [
     "logits = net"
@@ -775,22 +562,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We use the softmax function to 'squash' the outputs so they are between zero and one, and so they sum to one."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = tf.nn.softmax(logits=logits)"
@@ -798,22 +578,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This tells us how likely the neural network thinks the input image is of each possible class. The one that has the highest value is considered the most likely so its index is taken to be the class-number."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred_cls = tf.argmax(y_pred, axis=1)"
@@ -821,20 +594,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Loss-Function to be Optimized"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "To make the model better at classifying the input images, we must somehow change the variables of the neural network.\n",
     "\n",
@@ -845,35 +612,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 25,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_true, logits=logits)"
+    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(labels=y_true, logits=logits)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We have now calculated the cross-entropy for each of the image classifications so we have a measure of how well the model performs on each image individually. But in order to use the cross-entropy to guide the optimization of the model's variables we need a single scalar value, so we simply take the average of the cross-entropy for all the image classifications."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [],
    "source": [
     "loss = tf.reduce_mean(cross_entropy)"
@@ -881,10 +637,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Optimization Method\n",
     "\n",
@@ -895,12 +648,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -908,10 +657,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Classification Accuracy\n",
     "\n",
@@ -922,12 +668,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 28,
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -935,22 +677,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The classification accuracy is calculated by first type-casting the vector of booleans to floats, so that False becomes 0 and True becomes 1, and then taking the average of these numbers."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [],
    "source": [
     "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
@@ -958,20 +693,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Optimize the Neural Network"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create TensorFlow session\n",
     "\n",
@@ -980,12 +709,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 30,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session = tf.Session()"
@@ -993,10 +718,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Initialize variables\n",
     "\n",
@@ -1005,12 +727,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 31,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1018,20 +736,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to perform optimization iterations"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "There are 55,000 images in the training-set. It takes a long time to calculate the gradient of the model using all these images. We therefore only use a small batch of images in each iteration of the optimizer.\n",
     "\n",
@@ -1040,12 +752,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 32,
+   "metadata": {},
    "outputs": [],
    "source": [
     "train_batch_size = 64"
@@ -1053,22 +761,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function performs a number of optimization iterations so as to gradually improve the variables of the neural network layers. In each iteration, a new batch of data is selected from the training-set and then TensorFlow executes the optimizer using those training samples.  The progress is printed every 100 iterations."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Counter for total number of iterations performed so far.\n",
@@ -1084,7 +785,7 @@
     "        # Get a batch of training examples.\n",
     "        # x_batch now holds a batch of images and\n",
     "        # y_true_batch are the true labels for those images.\n",
-    "        x_batch, y_true_batch = data.train.next_batch(train_batch_size)\n",
+    "        x_batch, y_true_batch, _ = data.random_batch(batch_size=train_batch_size)\n",
     "\n",
     "        # Put the batch into a dict with the proper names\n",
     "        # for placeholder variables in the TensorFlow graph.\n",
@@ -1113,32 +814,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot example errors"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for plotting examples of images from the test-set that have been mis-classified."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred, correct):\n",
@@ -1155,13 +846,13 @@
     "    \n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "    \n",
     "    # Plot the first 9 images.\n",
     "    plot_images(images=images[0:9],\n",
@@ -1171,22 +862,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function to plot confusion matrix"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_confusion_matrix(cls_pred):\n",
@@ -1196,7 +880,7 @@
     "    # all images in the test-set.\n",
     "\n",
     "    # Get the true classifications for the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "    \n",
     "    # Get the confusion matrix using sklearn.\n",
     "    cm = confusion_matrix(y_true=cls_true,\n",
@@ -1223,20 +907,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for showing the performance"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Below is a function for printing the classification accuracy on the test-set.\n",
     "\n",
@@ -1247,12 +925,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 36,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Split the test-set into smaller batches of this size.\n",
@@ -1262,7 +936,7 @@
     "                        show_confusion_matrix=False):\n",
     "\n",
     "    # Number of images in the test-set.\n",
-    "    num_test = len(data.test.images)\n",
+    "    num_test = data.num_test\n",
     "\n",
     "    # Allocate an array for the predicted classes which\n",
     "    # will be calculated in batches and filled into this array.\n",
@@ -1280,10 +954,10 @@
     "        j = min(i + test_batch_size, num_test)\n",
     "\n",
     "        # Get the images from the test-set between index i and j.\n",
-    "        images = data.test.images[i:j, :]\n",
+    "        images = data.x_test[i:j, :]\n",
     "\n",
     "        # Get the associated labels.\n",
-    "        labels = data.test.labels[i:j, :]\n",
+    "        labels = data.y_test[i:j, :]\n",
     "\n",
     "        # Create a feed-dict with these images and labels.\n",
     "        feed_dict = {x: images,\n",
@@ -1297,7 +971,7 @@
     "        i = j\n",
     "\n",
     "    # Convenience variable for the true class-numbers of the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "\n",
     "    # Create a boolean array whether each image is correctly classified.\n",
     "    correct = (cls_true == cls_pred)\n",
@@ -1327,10 +1001,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Performance before any optimization\n",
     "\n",
@@ -1339,18 +1010,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 37,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 9.3% (933 / 10000)\n"
+      "Accuracy on Test-Set: 10.3% (1032 / 10000)\n"
      ]
     }
    ],
@@ -1360,10 +1027,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Performance after 10,000 optimization iterations\n",
     "\n",
@@ -1372,11 +1036,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1384,108 +1045,108 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    101, Training Accuracy:  73.4%\n",
-      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    301, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    401, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    501, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    701, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    801, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    901, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1001, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1101, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1201, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1301, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   1401, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   1901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2001, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      1, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    101, Training Accuracy:  79.7%\n",
+      "Optimization Iteration:    201, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    301, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    401, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    801, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    901, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   1501, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1801, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1901, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2001, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   2201, Training Accuracy:  95.3%\n",
       "Optimization Iteration:   2301, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   2501, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   2801, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   3001, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   3101, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   2401, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   2801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   3001, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   3201, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   3301, Training Accuracy: 100.0%\n",
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-      "Optimization Iteration:   3801, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   3801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3901, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   4001, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   4601, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   4101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   4301, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   4501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   4601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4701, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   5101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5301, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   5401, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   5501, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   5501, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   5601, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   5701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   6001, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   6101, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   6201, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   6201, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   6301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   6401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   6401, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   6901, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   7601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   7601, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   7901, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   8001, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   8101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   8101, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   8201, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   8301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   8401, Training Accuracy: 100.0%\n",
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-      "Optimization Iteration:   8601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8601, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   8901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   9101, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9201, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8901, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9301, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
-      "CPU times: user 38.6 s, sys: 4.3 s, total: 42.9 s\n",
-      "Wall time: 31 s\n"
+      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9701, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
+      "CPU times: user 26.8 s, sys: 3.86 s, total: 30.6 s\n",
+      "Wall time: 25 s\n"
      ]
     }
    ],
@@ -1496,11 +1157,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1508,15 +1166,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.9% (9888 / 10000)\n",
+      "Accuracy on Test-Set: 98.8% (9879 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff40bd9d8d0>"
+       "<matplotlib.figure.Figure at 0x7f76b7c59320>"
       ]
      },
      "metadata": {},
@@ -1527,23 +1185,23 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 977    0    0    0    0    0    1    0    1    1]\n",
-      " [   0 1134    0    0    0    0    0    1    0    0]\n",
-      " [   2    3 1021    0    1    0    0    4    1    0]\n",
-      " [   1    0    1  999    0    3    0    3    1    2]\n",
-      " [   0    0    0    0  981    0    0    0    0    1]\n",
-      " [   2    0    0    3    0  883    1    1    0    2]\n",
-      " [   3    3    0    0    4    2  946    0    0    0]\n",
-      " [   0    2    5    0    1    0    0 1019    1    0]\n",
-      " [   7    2    4    2    3    1    4    4  941    6]\n",
-      " [   1    5    0    0   10    3    0    2    1  987]]\n"
+      "[[ 970    0    0    0    0    0    3    0    4    3]\n",
+      " [   0 1125    4    0    0    0    2    3    1    0]\n",
+      " [   0    1 1022    0    1    0    0    5    3    0]\n",
+      " [   0    0    1 1001    0    2    0    3    2    1]\n",
+      " [   0    0    1    0  958    0    1    2    2   18]\n",
+      " [   2    0    0    4    0  881    2    0    2    1]\n",
+      " [   4    2    0    1    1    4  946    0    0    0]\n",
+      " [   0    0    6    0    0    0    0 1019    1    2]\n",
+      " [   1    0    2    3    0    2    0    3  958    5]\n",
+      " [   0    2    0    0    2    2    0    4    0  999]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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MeF+ZvVkMPDGuCzQlW22RSPoSEzSFbG/erIqIHkxhRqaODwIXSdoOuBf4ACVnsqSTgPuA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\nCSQR0VgCSUQ0lkASEY39f2GvAFCULtk9AAAAAElFTkSuQmCC\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff3ad7e4278>"
+       "<matplotlib.figure.Figure at 0x7f7690094240>"
       ]
      },
      "metadata": {},
@@ -1557,10 +1215,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Optimizing the Input Images\n",
     "\n",
@@ -1571,32 +1226,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for getting the names of convolutional layers"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function for getting the names of all the convolutional layers in the neural network. We could have made this list manually, but for larger neural networks it is easier to do this with a function."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def get_conv_layer_names():\n",
@@ -1611,12 +1256,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [],
    "source": [
     "conv_names = get_conv_layer_names()"
@@ -1624,20 +1265,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['layer_conv1/convolution', 'layer_conv2/convolution']"
+       "['layer_conv1/Conv2D', 'layer_conv2/Conv2D']"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1648,12 +1285,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 43,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1661,7 +1294,7 @@
        "2"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 43,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1672,32 +1305,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for finding the input image"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function finds the input image that maximizes a given feature in the network. It essentially just performs optimization with gradient ascent. The image is initialized with small random values and is then iteratively updated using the gradient for the given feature with regard to the image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 44,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize_image(conv_id=None, feature=0,\n",
@@ -1818,22 +1441,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This next function finds the images that maximize the first 10 features of a layer, by calling the above function 10 times."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 45,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize_images(conv_id=None, num_iterations=30):\n",
@@ -1882,10 +1498,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### First Convolutional Layer\n",
     "\n",
@@ -1894,18 +1507,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 46,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Layer: layer_conv1/convolution\n",
+      "Layer: layer_conv1/Conv2D\n",
       "Optimizing image for feature no. 0\n",
       "Optimizing image for feature no. 1\n",
       "Optimizing image for feature no. 2\n",
@@ -1920,9 +1529,9 @@
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAADFCAYAAABjLIjfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff3ad6a7a90>"
+       "<matplotlib.figure.Figure at 0x7f768803b7f0>"
       ]
      },
      "metadata": {},
@@ -1935,20 +1544,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Note how these are very simple shapes such as lines and angles. Some of these images may be completely white, which suggests that those features of the neural network are perhaps unused, so the number of features could be reduced in this layer."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Second Convolutional Layer\n",
     "\n",
@@ -1957,18 +1560,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 47,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Layer: layer_conv2/convolution\n",
+      "Layer: layer_conv2/Conv2D\n",
       "Optimizing image for feature no. 0\n",
       "Optimizing image for feature no. 1\n",
       "Optimizing image for feature no. 2\n",
@@ -1983,9 +1582,9 @@
     },
     {
      "data": {
-      "image/png": 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nIzQ0dNnzL3n58fHxbN++XRjm2traNUVEUVFRZGdns2XLFmw225oFl9ZkkO12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\nBgbocZTcP0+a3/T0NAYHByGTyShVbTdNBqFQiKNHj2JychJKpRKNjY30M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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff3aa99bf60>"
+       "<matplotlib.figure.Figure at 0x7f75f62db208>"
       ]
      },
      "metadata": {},
@@ -1998,10 +1597,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Final output layer\n",
     "\n",
@@ -2010,11 +1606,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 48,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2023,54 +1616,54 @@
      "output_type": "stream",
      "text": [
       "Iteration: 0\n",
-      "Predicted class: 1, score:  79.35%\n",
-      "Gradient min: -0.564165, max:  0.727934, stepsize:      5.89\n",
-      "Loss: 0.974301\n",
+      "Predicted class: 1, score:  65.21%\n",
+      "Gradient min: -0.754999, max:  0.602095, stepsize:      5.48\n",
+      "Loss: -0.24191949\n",
       "\n",
       "Iteration: 1\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.570292, max:  0.710277, stepsize:      5.12\n",
-      "Loss: 26.5427\n",
+      "Gradient min: -0.959483, max:  0.945845, stepsize:      3.74\n",
+      "Loss: 31.78731\n",
       "\n",
       "Iteration: 2\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.409457, max:  0.470393, stepsize:      6.22\n",
-      "Loss: 37.2067\n",
+      "Gradient min: -0.698926, max:  0.681807, stepsize:      4.26\n",
+      "Loss: 49.426582\n",
       "\n",
       "Iteration: 3\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.496705, max:  0.523132, stepsize:      5.94\n",
-      "Loss: 38.8357\n",
+      "Gradient min: -0.679672, max:  0.737549, stepsize:      4.47\n",
+      "Loss: 54.057976\n",
       "\n",
       "Iteration: 4\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.408904, max:  0.465926, stepsize:      5.98\n",
-      "Loss: 41.3122\n",
+      "Gradient min: -0.624817, max:  0.728835, stepsize:      4.41\n",
+      "Loss: 59.83038\n",
       "\n",
       "Iteration: 5\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.476362, max:  0.522812, stepsize:      5.89\n",
-      "Loss: 42.0313\n",
+      "Gradient min: -0.617483, max:  0.689194, stepsize:      4.47\n",
+      "Loss: 58.287357\n",
       "\n",
       "Iteration: 6\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.398669, max:  0.488273, stepsize:      6.10\n",
-      "Loss: 42.4584\n",
+      "Gradient min: -0.678464, max:  0.716904, stepsize:      4.35\n",
+      "Loss: 61.191967\n",
       "\n",
       "Iteration: 7\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.470078, max:  0.545729, stepsize:      5.88\n",
-      "Loss: 42.6654\n",
+      "Gradient min: -0.649330, max:  0.682045, stepsize:      4.37\n",
+      "Loss: 59.402054\n",
       "\n",
       "Iteration: 8\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.470376, max:  0.456324, stepsize:      6.17\n",
-      "Loss: 43.9691\n",
+      "Gradient min: -0.670582, max:  0.723849, stepsize:      4.29\n",
+      "Loss: 61.544674\n",
       "\n",
       "Iteration: 9\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.471091, max:  0.535464, stepsize:      5.92\n",
-      "Loss: 43.4301\n",
+      "Gradient min: -0.639827, max:  0.774844, stepsize:      4.33\n",
+      "Loss: 60.820866\n",
       "\n"
      ]
     }
@@ -2082,10 +1675,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Note how the predicted class indeed becomes 2 already within the first few iterations so the optimization is working as intended. Also note how the loss-measure is increasing rapidly until it apparently converges. This is because the loss-measure is actually just the value of the feature or neuron that we are trying to maximize. Because this is the logits-layer prior to the softmax, these values can potentially be infinitely high, but they are limited because we limit the image-values between 0 and 1.\n",
     "\n",
@@ -2094,19 +1684,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 49,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO4AAADuCAYAAAA+7jsiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff3ad6eecf8>"
+       "<matplotlib.figure.Figure at 0x7f7638092ef0>"
       ]
      },
      "metadata": {},
@@ -2119,21 +1706,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Although some of the curves do hint somewhat at the digit 2, it is hard for a human to see why the neural network believes this is the *optimal* image for the digit 2. This can only be understood when the optimal images for the remaining digits are also shown."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 50,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -2156,9 +1737,9 @@
     },
     {
      "data": {
-      "image/png": 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XsLUnz2q32+l2mnxPkvwiCbVInHGDwYBvvvkGWq0WDAYDVqsVCwsLyMjIeOBE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KxIT0/HD3/4Qzz33HNUCYxgdnYWPT09mJqaglwux8rKCsbHxwO0kO/evYtf/OIXYLPZsFqtAQHh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\n+H+odrS0zIdNqQAAAABJRU5ErkJggg==\n",
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WvaQfEZBMdSQSoUthpVIJmUxGn0sgEKBhqkgkAqPRCIPBkLAfEl91OBxwOBz08wsXLqCxsRGtra00AUoMCKFUkdyIw+HA1NQU9aBcLhfsdjusViul2hUVFUEkEiE3Nz2bSSQSoaqqClqtlh538eqI/DscDsPpdNIkGVkmkwT51NRU2mMFAgHMzMyk/N5gMECn0yEnJwd5eXmYmprChQsXcPnyZeoABAIB2O12TE5OYnZ2FiUlJQiFQjAajQgGg8jLy4NWq0Vubi60Wi2NtctkMjoJpEIwGMTExETK7/V6fUJoy263Y2ZmBiaTia7YyORCnp1UKoVWq4VUKoXP54PD4QCDwYDNZsPNmzdx4cIF9Pf3LzlWOBxe8o75fD50dnaCwWCAw+EgJycHIpEIZrMZk5OTKCwshEqlgtVqhc1mS3kdc3NzOHv2LGpra7Fx48aU2yVDVm9WOByGx+NJ6yFxOByo1WoIBIKE8IbH44Hf74dIJIJcLqcGXSqVQqfTwWazUc4rAQmOX7hwAb/85S8xPDyMX/7ylxgbG8Nrr72GPXv2ZHzuhLNJwh2jo6PweDzo6elBS0sL/uZv/ibh5mUTulgOJpMJ77//Pm7evIkXXngBBw4coB7sYiyOiadCpskkDoeTlBu5GH6/H06nE5FIhPJ8BwYGMDIygmg0ColEgsLCQkgkkoRJ816huLgY69evh8fjwdzcHNRqNVpbW1FTU0MTtk6nEzabDTweDz6fD6dOncJHH32UUeJkeHgYb7zxBuWdk1ULWXbL5XKwWCwEg0H4fD44nU5K2XQ6nQgGg1hYWKBUN4FAgImJiWVj/Lm5uXjhhRewf/9+xGIxzM/PIxqNJjwPJpMJFosFp9OJkZERWK1WFBUVobS0FMAdh+Ts2bM4dOjQXTFWgsEgzp07h9HRUQgEAmroFxYWkm5PJuRQKEQ9SWLIZmZmMDs7Cz6fD41GQ0MW2SSx+Hw+cnNzYTQaEQ6HIRQKEyZ7vV6PQ4cO4cyZM/D7/RCLxdQgBwIBRCIRVFZWYv/+/aiursbk5CRGR0chkUjA4XAwMjKy7CSWDB0dHfB6vRCLxQiHw5iYmEB/fz/KyspQU1MDo9G47CpxYGAAP/vZz5adsBcja1eHLINSgTAdkr20ZHkTPxgJAT4dWCwWjh49iuHhYfh8Phw5cgRlZWUoLy+HQqGAy+WCWCxGbm5uWsMTT4UKBALQ6/XQ6/UwGo00blRcXExn4uXA4XAgkUgoQTwVotEo5ubmcPLkSaxbty7t/TObzfB6vSkNMofDQW1tLfLz8xEIBDKicmUSLgmFQnC73TQkZbPZqDfI4XDA4/EgFAqRn5+fNX2MvHhkWUsy18CduCKXy8WWLVvw4IMPwu12w2AwQKPRYPPmzWhoaKAroWg0CqvVSg0yg8GA0WhEV1cXZXGkurc+n49SycRiMXJyciAUCiESiSAWi2lslMFggM1m01CP0+mE3W6nRTECgQBSqRTRaBShUGhZ2huDwYBIJIJOpwOfz0dVVVXa7SsqKrCwsICysjJKIyPemNFoRE9PD83kE8YHiZFmAoPBsGRVkQrBYDDBY83Ly0NRURFUKhWAOw4TWTVxOBywWKy0Y1sgEECn09H3RSwWQywWw+VywePxgMPhJLxHbrcb3d3daG9vT7nP0dFRiMVizM3NYXh4GLdv34ZEIoFCocDc3BydaLlcLmKxGKxWa1JjymAwIJfLqbH3er2YmJgAn8/H0NAQbt26BYPBQFcqXq837b1zuVzo7u5Ou00yZGWQSVx4pUvWldJXFnNKAeDzzz+HxWKhy/GHHnoIL730En15F4cuyGfJDKfBYMCHH36IiYkJPPnkk0uI3amQk5ODhx56CBcvXsx4kBOvbDEikQgsFgv6+vpgMBiSehoqlQqPPvooHn30UbS0tNxTqhFZBs7Pz2N4eBgWiwUMBgMlJSVwOp1wu93UU8y2D2NdXR0OHDiA4uJiev95PB5isRj8fj+YTCZ0Oh0KCgoQCoXgcrkgEomg1WoTwlJMJjPBGDz88MPIy8vDqVOncPjw4bTL4Xi43W5EIhHq2RGvNCcnhy7pORxOgtGNxWKUWiiTyaDT6VBZWbks93ZhYQEffvghzGYzXnjhBer1psLihCwAKBQKbN68GTKZDPPz82AwGODxeHTi/MMf/oBjx45ldO0rRVVVFVpbW7Fx40aUlJTQ9yo/Px+FhYUQCoXLruoKCwvxL//yL7h9+zZu3bqFsbExzMzMUPYPWQERpKPYEtjtdly6dAn9/f00hBUOhyGTyVBeXo4dO3agpKQEIpEIExMTOHHiRNJ8lUKhQFtbG8rKyuhEF4lE0NfXh4mJCczNzcFkMmFkZAQulyttBfDdIGuDLJVKUy637xUikQiCwSAEAgHC4TCGh4eX8Fhv3bqVwP91OBxYu3YtNmzYACA5dYaUgCbD8PAwhoeHoVarE4jd6ZYmSqUS+/btg9PphNFoXHa5xufzwWAw4PF4lpT5BgIBujRKZZClUil2796NZ555Ju1xFmMx0T0ZiBcRDAZhMBjgdrtRUlICpVIJo9GI6elpWK1WjI6OpqR6MZlMcLncBK+Rz+dj+/bteOGFF6DVarM673RgMBgoLCxEYWEhZDIZuru7MzbIBHl5eTTJZ7FYwGazkZubi4KCAvD5fNhsNvh8PjCZTBrjJjx3uVwOrVa7LMXM7XZTg8FkMvHd7343gae6GKkKWEpLS1Mac4fDga6uLszNzVGudKqQFpvNpgU/qVgwhEERz37YsmUL2trasH37dhQUFCTd93LjTCqVYuvWreBwODRpSjx7kUhE80kkXKhSqVBZWQmFQpE2Zjs4OEj/zePxaCw+Ly8Pe/bswaZNmyASiXDjxg3q4ZKwE3m+a9aswe7du7FhwwZIpVIsLCygs7MTHR0dYDAYEAgEmJ2dTTjW/UDWPGQSn7lbJPNgCXp6enDhwgU4nU4wGAwMDw+nTVYAwLVr1/A///M/ePzxx7Fv376kg57NZlOPixSoLOYRkiUsANy8eROzs7Mpj8nn87FhwwaEQiEoFApcvHgxbczK7/djdHQUN27cwJo1ayCRSOj1RyIRql3hcDiSGmSv17tkQskk1k0SNekQDochl8tRXFwMNpsNr9cLtVoNiURCqx9v3ryJ9vb2lDHHwsJC7N27F5988gnMZjNqamrwta99DXv27LmnxngxlEpl1k6CWCxGS0sLtm3bBrvdDr1eT/VAiCaByWRCfn4+ZmdnaXHA1NQUjEYjcnJyUFdXlzHjxG634+DBg/D5fNi/fz9aW1tXcqlJsW3bNgQCAXg8HvB4PAwMDODYsWNJn3lTUxMeeeQR+P1+XLt2DaOjo7Db7QnXweFwkJubi7q6OjQ3N9OkZElJCTQaTdJzIMyUdLzshYUFvPfee9Dr9ZiYmIDf74dGo0FRURHWrVuH1tZW5OTkwO/3QyAQQCKRYPPmzTCbzbh06RJGR0fT3oc1a9Zg27ZtNPTU0NCA9evXo6ioCEwmEw0NDXjuuedQX19Pk9SBQAAsFguVlZVobm6mRUAKhQIcDgcKhQJjY2MYHh5GIBBIOfbvFbL2kDNZmmSCVEbE4XDg3Llz+PnPfw69Xg82m02LQNLBarXi/fffx8zMDDQaDbZt27ZkG6lUiuLiYgQCAQgEAhpTIjxWslwMh8Mwm824ePEiBgYG0l5DeXk5ZZXEYjF88MEHac/T6XRibGwMKpUKZWVl1BsiscC5uTm4XK6kngbh1C4+h+VAYrbp4oxyuRy5ublQKBRQKBQ0qw3cCc1IJBL09PTg1KlTKY27Wq3Gt771LQwMDODSpUvYu3cvvv/97yeQ6u8HFhYWsq6Yy8nJwfr16/HMM89Q4STgz94hg8GAyWSCRqOB0Wikscjz58/DaDTC4XAkVHRlghs3bmBgYAChUAhVVVX3jHLZ1NSE2tpaGmb77LPPMDw8nLTMfMeOHfje974Hk8lEY/IkcUfAYDAgkUiwZcsWfPOb36SrgHgu7mKQZGy6MTYzM4P//M//RCwWo9xurVaLbdu2Yffu3SgrK6OrYgAQCoV48MEH6bgfHx9PuQqVSCR4/PHH8corryA/P58WsxD7AQAajQb79+/Ho48+uuT3hGlDrk8mk9Gy8dHRUVy7dg1utxszMzP3teo062Dw3ZQxhkKhJd41oYSRgWq1WhPiPNkWFnR1deG9996Dx+PB5s2bKTcXAKqrq/HMM8+gu7sbw8PDMBqNtHiAxJ30ej2OHz+OyclJnDx5ctlZmcViQaVSYc2aNXjssccgFAphs9kgEAjovSKVamKxGDU1NdDpdLQsmcBiseD27dvo7u7G9PR0gkGWSCSorq7Gtm3bUF1dndX9AO54Dq+++iquX7+OmZkZmlQhq4GysjI88sgjlHdMriseOTk5iEajy2at6+rq8JWvfAW1tbV45JFH7psxjkaj8Hq9mJ6expUrV6heSqaQy+XIycmhL2uynIFarUZtbS0KCgpokjoUCkGpVEKlUqGoqChrzmwgEMCZM2eQl5eHNWvWQCwWIxAIwGQyweFwUKYR+b9QKKTnqlKpoFKpltA9F5cXr1mzBs888wwtjBIIBHC5XJBKpdi3bx/UajWlmCZj4BDGDQkbEqRzxAgPPp19IDkDch/cbjeYTCblCIfD4QRKLVG9a2hoQEtLCwYHBzEyMoJQKETpteRZ1NfXY9euXSgqKqLnsxgMBiPrlZRAIEBjYyOEQiGsVivGxsbQ39+fMjRTVlaGjRs3Qi6XIxAIIBqNJhTDLId7TyhNARIIl0gktCwXuMPZ++ijj3Do0CG43W7w+fxll9fp4Ha78e6772J0dBQ//OEPE6hxDQ0NKCkpQVFREQ4ePAibzUZnRvIC9PX1YXR0FEajEUNDQxlrSSiVSuzevRubNm1COBxeMnhjsRiNRRIWSvygsVgsGBsbw9DQ0JJ9FxYWYv/+/di9ezdqamqyvictLS2oqqpCf38/zp49Sysj8/PzsW7dOqxfvx4FBQVpY5vAn/Uy0j0fsViMZ599Fj6fL+E530uEQiHYbDaMj4+jq6sL165dSxtjXAy5XA6FQpGRc5GXlweVSkWfp1wuR2trKzgczpJnmClu3LgBo9GIuro6unzu6+uDXq9PyHNwuVyo1WqUlZWhuroadXV1qKurQ2VlZdqVUW5uLl588UU8+eSTAO4YUrLiIUZ6fn6einslMy5k/Pf09GDz5s3LUh1JCDBb7Yb5+XkMDAzQfEVubu6Se0ocnvn5ecjlchgMBggEAtTU1NBQR01NTdYUs2xQXl6O2tpaFBcXU3nbZPdt69at+N73voeSkhK43W4EAoG/nkH2er0wm82ULhQOh8FgMBAOh+ksqFAooNPpoNFowOVy0d7ejvb2dpjNZrDZbBQXF6OmpobSj5KpPJHvQqEQZmZmoNfrEzzpcDiMCxcuoLq6GnK5HE1NTXRAicVirFu3juoS9Pb20jgxm83G6Ogo/H4/IpEI+Hw++Hx+UmEi4M+eL9E2Jsv9lYDL5UKpVEKtVi85HqksIvQmog+dLXg8HgoKCihdr6ysDGvXrk2IC6aLSZeWlmLv3r344x//mPY4pISbIN1SNxNEIhFalh+LxTA0NIQbN27AbrcjEomgqqoKsVgMZrMZTCaTskXm5uaWTKh8Ph95eXk0VrwcyLKXQC6X33UlWTgcphSqyclJhEKhlAlJkmwm//X19UGn06G4uBjV1dVLSv+BOx5zqlgvgc/ng9lsxsLCQlLqXjQaxeDgIE6cOIG5uTkUFRVBrVZDKpWCwWBQKmBBQQE0Gs2S+5QMAoEA1dXV9BmRKsqSkhKoVCqIRKKkExyPx0NlZSWCwSCUSiUmJyepQV6/fj2am5vTHvdeYGJiAtPT01TCdbHAk0wmQ0tLC/bt24c1a9bQz7LFPTXIFosFnZ2duH79OgYGBjA/P09nfFIZpVQqodPpkJeXB5FIhMnJSdjtduTl5eGpp57Ck08+CYFAALfbDRaLlUB5IzeAyWRS/u/Bgwfxf//3f0vWgIXrAAAgAElEQVRevFgsho8++giTk5P4+7//ezz++OMA7kwaQqEQ+/fvp9VKV65coefm8/kQjUZRXFyMuro65OXl4Re/+EXS641EIlR0/m6ZJzk5OdiwYQNcLhc6OzsxMjJCr3dqagqHDh2CXq/H008/jd27dy/xBtIlSScmJnDq1CkYDAaIxWIUFRWhsrISZWVlS7zYdJ7XunXroFQqs9K0vVuQSY/BYFChqI6ODnz88ccoKyvDM888g8cffxx2ux1erxd8Ph9WqxXnz5/HmTNnMDAwkFBMwePxkJubm7FBvp8gDKLlYDKZYDKZMDAwQOPbdXV1eO211/C1r31tRccm1Xfp6Fvj4+M4fPgwrl69ivz8fJSXl6Ourg4CgQB9fX0wm83Yu3cvnnrqqYyOqVKp8O1vf5u+Ky6XC5FIBCUlJairq0sIDS1Gfn4+hEIhdDoddd5IteD9xvXr13HkyBF88cUXGBgYSCpF8PTTT+Pll19Oq8mdCe6pQSYz5Pz8PK5cuZLUs1QoFAgGgwgEApBIJIhEImhsbIRGo8Gzzz6L7du3Z3XMgYGBlMbQbrfj5MmTKC0tRXl5OTgcDsbHxyGXy1FaWopoNAqfz0e9a4fDgVAoBCaTScVjamtrUxpk4rGRbiGE6J5NhR+pfiRUuMLCQoyMjCRsEwwGKe1MLpdDKBSiqKiIdlSRyWRJj0k8sWPHjlGvtq2tDVqtFhUVFRl7esQjUKvV1EtKhmAwCL1ej1AoRF+YlXrzi48f/29SsEBi8slkTUlyiBD7ie4AoTDFYjFK/CcFAaQjDaHvLdYgIYpvXq8XIpGIcqJXCjabDZVKRWOmRHsaAK3WJFQyUirs8XjgcrkwPz+/JLnk8/lgMpnAYDCgUCjAZrMTmgyQ45hMJvT09CzLXPJ4PJiYmKD3qby8HAaDASKRCN3d3TCZTBAKhSgvL0dBQQEVk08FmUyGffv2UWKAy+WiMgDL3Usul0uLyIi2CmHHECofuYepQJ4rmdRICDE+3xPfJUYgEMBqteLUqVM4cuQIhoaGlrBIuFwuWltb8cQTT2DLli3085VW+t5Tg5yfn4+2tjZ4PB50dHQkNcgajQYbNmxAdXU1jTtxuVzk5OSgvr4+62NmIrp9+vRp2O12yOVymuFlsVgwGAwJLAqSaY5Go5DJZFTqMxVYLBYkEgm6u7sxOzuLsrIyNDY2Zpz4DIfDsFqttORzcHAQ4+PjlPmxGB6PB1988QVmZ2fBZDIhl8vx2GOP4bnnnltyD4LBIB1IFy9exMzMDOrr6+kK5V4IuCyGyWTCT3/6U5jNZiiVSjz77LMJbJeVDNLFiRgmk4lNmzZRfelUceo1a9ZQcamOjg50dnZidHSUamWMj49jZGQEfD4f9fX1qK6uphoYQqEQBQUFS2heRKOgr68Pa9euxTPPPJNUTyVTlJSU4Pnnn0dNTQ38fj8cDgd8Ph/VeJHJZAki6oSf7/f7oVAolsi5DgwM4P333weLxcKePXuQk5ODq1evwmw24ytf+Qrq6uowNDSEt956C6dPn05L6VwMIgDm8XjA5XIxNzcHr9eLixcvwuv10sRhOoNMur6QCTonJydptely44TH48HhcODUqVO4desWvF4vnbiSTf6k3RRpqUZU7Hg8HioqKlBdXU0LfMbGxnDkyBH09vbS93h4eBjj4+NLjLFGo8ETTzyBxx57LGPBs+VwTwwy8SzYbDYUCgUqKiqg0Whw8+bNJduq1WqUlJSgpKQEQqEQOTk5KC4uXnE2ns/no6ysjMZ2kmnvjoyMYGRkBBqNBuXl5fB4PElnu3iQpf1ySZu5uTkMDQ1hamoKQqEQ9fX1GRnkaDRKtaNHR0fR39+P27dvY2xsLGl/vsXXQhCLxdDU1ESl/kh12e3bt3HkyBH8+te/ptuS7DSHw6EiPcQLS/cCkO/iPbhksFqtePfdd+HxeMDn86FWq9Hc3EyThSvxGEi+IP7vtWvXLqt1LJVKsXHjRmg0GqhUKhpXdrlcMJvN8Pv9GBwchNvtRnNzM7Zs2UKrJSUSCaqqqmC321FfXw+VSgW3242JiQlcvHgRZ8+ehdlsxrp169DY2Jj23JOxN8i427RpE77+9a+jvLwcwJ2QH6E8EmGlTBGNRnHp0iW8++674HK5NF/w6aefYnp6GoWFhSguLsaFCxfwm9/8JqskKAFZycVjeHgYBoOBlt6no6cSLW3SGIKcJ5AYcstknMzPz+Ps2bM4ceJExl1b2Gw2KioqoNVqaU1Cc3MzfD4fLbq5du0aDh48mFHZs1qtxv79+7Fv374l361UB+eeGGTi5ZF2Lp2dnSkJ1FNTUzh37hx6e3vB4/FQW1uLPXv2oLKyckXHbmpqwssvv0wpQ7dv38bx48eTylfKZDI0NDRgYWFhSVhgMYgoTzoYjUb8+te/hsfjgUwmy0jEhyAUCsFsNmNubg4WiwVWqxXz8/MwmUyUkpYJx/XKlSt444038MADD9AXe2RkBO3t7Th//nzCtj6fD/Pz85ienqZJy3it3Ew1KlItC0OhEH0h/X4/Dh8+jEgkgieeeALr16/PaN8rQfyEsnhyKS4uBoPBwNTUFC5fvgybzUaz9GTJPzQ0RJt62u12iMViDAwMoKOjg9KqtFotFR9iMBiYnJzE4cOHkyqJEeTn5+PVV19d8jkp8GltbaU0LeCOx0hWcdnIEwwNDeHo0aP4wx/+QA3tmTNnIJPJ0NfXB7vdTrV+Ozo6Eoxx/H1bCXw+H8RiMS2FJ1rSqRAIBPCnP/0J4+PjeOCBB/Dggw/SpD9RWEvm0Cx+rqRrUDYttIhQkN1up+XnZrMZQ0NDlPI5Nja2LNWVwOl0rqhQKx3u2iDb7XYMDAygq6sLer0eJpMJer0+pbj6xMQEZmZmaLfW5uZm8Hg8ShLPFg0NDaipqaHG5MKFC9Dr9bhw4cKSbUtKStDQ0IC5uTlKb0sGIhm6XDHK7Ows3nzzTbS2tmL79u0JlXfLweFwwGg0wmg0wm630zJVUkLK4XBgs9mWbQw6NTWFX/3qV2hvb0dbWxvEYjEuXryIy5cvL+Fwe71eDA8PQyqVoqioiMaCGQwGCgoKUFpaek+lNXt7ezE4OIhQKITKysr7pj2dTMoyHkVFRSgrK6OrMJfLlWA0PB5PQhm+3W6HzWbDjRs34Ha7IZfLsW3bNir5qtVq4XQ68cc//jHt887Ly8P3v//9JZ+TlzY+9kmwEp7/yZMn8dOf/jRBn7ejo4NqMgDAqVOncObMmSUty1ZqiAmIpgdRd4xEIjh9+nTK7cfHx/HZZ5/h+vXrNKHncrkwNjYGhUIBPp+fNEex+D47HI4V9TMMBAL0nWIwGJiZmcG1a9cSmhNkWn1JSq/TnWe2yOrtCwaDmJ2dpWpbw8PD6O/vx9DQEPR6Pebm5qgIdLpZklxwMBjE4OAgTp48CbPZDJVKRXu6kaq55TrNLibFt7S04MCBA2AymbTHGgFJZtjt9pTVNqSlPIkzLQeTyQSv15txm3LioZlMJszPz8NgMGB8fBwejweNjY3Ytm0botEoAoEAJdLr9Xr09PSkpN8Bd7Q9SCKqv78/aUGN0+lEf38/HA4HlEolRCIRotEopRsSjqtWq6XqWIFAIKHiKVMlPIJAIIBTp04hNzcX27ZtQ1FREWw2G7q6uuD1erFlyxbU1dXBYDCgv78fZrMZPp8PoVCIKguSGGAgEKCtmVpaWpblTcdDJBKlNHYMBgMymQyVlZV06Uqej9vtBo/HQyQSoW3EBAIBXd2k46mTfnPLYaVe1fj4OM6ePYvDhw8vEUtfLBYfv3oBlvblA4D169ejqamJsqIIPW1hYQFTU1Pw+XyQSCRUPkEoFKKkpASFhYVgsVg0gZjKIM/Pz+Pjjz8Gm81GU1MTbDYbra5dWFhAfX09baOUCjabDZcvX8bx48dXJK0Zj1RiY8uBy+Vi48aNd7WyT4WsDHIgEMD09DRkMhkWFhZw9OhRHD58mIqakORDJoLoBHa7HWfPnqUzulqtRltbG/bs2YO6urqsum0Ad2K/zz//POVnnjt3jn63ON6V6vd5eXk0S70ciGdOxNOXw9TUFHp6euB0OhGNRmGxWLCwsACZTIaHHnoIW7ZsgdvthtFoRG5uLuRyOS5dugS73Z7WIIfDYfT399OXKRmcTicGBgYwPj5OOd6kOkqn06GhoQHbt2/Hrl27kJ+fT5XXFuvUZouenh7Mzs7i1q1bePrpp2GxWPDLX/4SDocDUqkUdXV1mJycxKefforbt2/DYrFQUj1JZpHmCGq1Gq+88goqKyuzMsjEwCcDEfvfu3cv2traEIlE0NPTQ0VoGAwGIpEI/H4/Hdvk72wLIZJhJcY4FArh0KFD+PnPf551lSKw1DOWSCR44okn8I1vfAN8Ph/z8/NgsVgIh8O4efMmLl26BLPZDK1WS1dXEokEKpUKEokEPp8PFoslrSzlzMwMPv30U7z66qtYu3YtPv/8c3zwwQcYGhoCk8mE1+vF2rVrUV5enjKndPnyZfzkJz/B1atX/2qda+rr6/EP//AP2Lt3b1ZjMBNk9ZYRmghR0Z+YmEjbeilTxHd3mJqagk6nw9atW5doL5OEHelzFr/cIzKJpNS0ra0N09PTNHljs9mSJiUWg3TLIJSp5cDj8WhMurm5OWnvPNJrzOVyUY+T9KoTiUSoqKigAitESYvoSgDA2rVrM+LMLreEIzS/ZMlMo9EIk8kEgUCAhoYGaDQa+Hw+mmQiDASTybSiWv75+XmcPHmSisOz2WzaVgu443WQljnEI7darVSnljTYVSgUy5boJkMoFErKAJDL5dBoNNBoNNQI8Hg8ylOWy+UQCAS0w0xXVxeGh4cxPz+/7P0m8VSiGXw3IHQ/Eufu6OjAn/70pxUZ43jw+XyUlJRgx44d2Lt3L9WtiOe5y+VycDgcWK1WKrcplUppxSkRo7LZbGnvCZvNRmlpKZqamtDS0oKJiQmoVCp4vV5IJBLU1NRAq9VS5UOTyURZUVKpFG63G3/605/wxRdfpJwIORwONBoN8vLy6HMjnURIjQEpSedyufB4PFQUaTlvmclkor6+Hk8//TQNDxIsXuWQdybbkFBWBpnQREQiEcLh8BIJyXsFLpdLRcPjLzISicButyMQCEAmkyVQt7xeL0wmE6U6SSQSfP3rX0d1dTV++9vf4qOPPspoRnW73RgZGYHRaFx2W2JYSSw6GfXF6/XSmKTf7wePx0NTUxNmZmYwNTVFOdFlZWUJVVfx8VZSqXa/odfrMTQ0hOnpaRQXF8Pv91OxfI/Hg97eXly6dCmtp54ORqMRV65cQXNzM1XdIlTH8vJyWnIdCAQwOzuLyclJhMNhWiVGBGOKi4uzjkf7fL4lBlmlUqGkpIQWHZDmlwqFAnl5edDpdCgtLUV+fj6V4yRx/0xK6km8knDF7waxWAwejwc3btzAsWPHaO+2u0V5eTm+853v4Mknn0zK5wbu0Lu2bNlCubnECBOpT+COYReLxUti1PEoLi7GP/3TP6Gurg5sNhvNzc34zne+A7fbDaFQiMbGRlRXV2N6ehoffvghPvvsM9qmic1mIxKJYHJyMqUxJpN8W1sb2trakJeXB5/Ph+npadrnjoSciouLIZfLMTw8jK6uLprXSoeNGzfi9ddfR1tbW4LuC7B0lRONRhEOh7NeQWUtv0m8CLVajcbGRlRWVsJms0EsFsPj8dy1PB2J5ymVSggEAlp2SwTUfT4f3G43PRfieZBlrd/vh81mg1KphFQqxa5du3DlypWsljcejweDg4O4evUqHnjggbTnSvrfjY6Ooq+vD4ODgygrK0MwGITH46GJuZmZGfj9fuh0OhQWFtKBnZubi3Xr1i3xgEmSwe/3Y2BgIGNNjXQgNCwivk6oikQ/l2gRGAwG6PV6yGQy2heRyJQu1x0lHnK5nPKEY7EYRCIRZDIZCgoKsHv3bsoKAbCk7DwYDGJychKxWAzFxcVZdykhCIfDtPNwXl4eTehoNBrU1NSgsrISKpUKPB6P5j+I0Ver1SgoKKDHJrrXZIwXFRVBqVTixo0bKY+/XIedTEHi0U6nE5cvX057zGxAWlilK8wgXmc6ZFI6LZfLE5yWqqoqVFRU0A71AoEACwsLuHbtGk6ePImenp6srqOiogKbNm3C448/jp07d0IqlVJmRWFhIWZmZhCJRCCTyVBVVQWxWIzTp09jYGBgWcNZVFSEffv24amnnsqYe37fPeR4CAQCGmskCYLz58/jww8/XFH2k0AqldKXk8fjJehKxOsZ+Hw+2l+NSCZqNBqaJXU4HJDJZLDZbBm3t4lHT08PfvzjHy+ZCeNBigyAO4bz0qVLiEajqKqqglqtBpfLhdfrxcLCAvR6PVwuF+VCE/0LiUSSkl6n1+tx5coVnD59etmqqkwgl8tRWVkJuVxOPVHSkkggEFANWlKmu379elRVVdH43rp16yCXy3HmzJmMjrdt2zY8/fTTkEqlNFREOpGnEjknIMnVWCy2YmMM3Gnxc+rUKUxOTqK1tZXqHshkMio0RfSPvV4vfD4fBAIB8vLyoNFowOPx4HK5cObMGRw9ehSfffYZAoEAWltb8bd/+7doaWlJSenjcrnIz8+/q+KReBDP7l7GLfV6Pd58801MTEzgq1/9Ku1I/ZcCk8mE2+3GuXPnoNfr4XA4MDo6uiwtdTFEIhH27NmDb3zjG1RLArgzURQWFtLGyDwej4a+AKCvrw/hcDhlTQKHw8HDDz+Mp556Cg899FDCs0yXjCU26b56yIsPuG7duoTabalUir6+Pqp1wOfzafyUNHIk0oLhcHiJhq1CoUB9fT3KysroEo94GPFqaeR3xFhzuVyqRBYMBmGz2eB0OhGLxWAymcBmsyGXy7NSkSPNH9OV/S7OZPf29mJiYgKlpaWorq6GUqmkvdkmJyfhdruh0WjgcrlQXl6OsrIyyjtNhtHRUZw4cQJffPFF2hAKoVDFM07iW8CzWCyIxWJUVlZi/fr19BwIjzJehJ4Uq0xNTaGiooJev1AoRHV1Nb2uVOdBVg06nY6+ICvFcjF8wkYhz4C8HGScEGnXkydPAgCtECVsHsIYIGyeZLBarbh27RrefvttHD16lH5eUVGB7du3p5VDZbPZKcvMMwVJkpNJye/3J0zgAoGAsiEI4ilci3Weyf4ISFL91q1bEIvFePXVV8HhcODz+Wi7sfsZLvP5fLh69SoOHz6Mjo6OFbdG4nK5lNYKgAqbkXgxUbmLf2dJCXa61SebzcbWrVvxyiuvLPluuWKqxQywTLAig5xqZli3bh1eeeUV7Nq1CzweDx6PBzdv3sT8/Dy9WaRcsrOzE0ePHqUDRi6XY9euXdizZw8eeOABGhoh7WaAO4NKJBIlyGUSQxQKhShzgbwIPB4PCoUCO3fuBIvFwqVLl9Dd3Z22Qo+gsrISGzZsgFarxY9//OOM74vD4cCNGzcwMzNDdRy8Xi9dKofDYZSUlFAPTafTpTQGdrsdo6OjaROnYrGYet01NTVQq9VLBP1J7DQvLw9VVVXIycmhynxk4olXSiOrjpGREQQCAZokWa7cWqPR4Nvf/jZYLBa0Wi12796d0X1bKSYnJ3H8+HFMTEyAy+VSQ0U0CwKBALq7u9Hf349IJEIZALW1taipqaETdyrZxkgkgs8++wyHDh3CF198kfDd6OgoPvjgg7RNSwlL5W5yLVNTU+jt7cX09DQsFgt6enpw9uxZAMADDzyAvXv3QigU0vJh4E6uh81mY2RkhFLiqqqqsH79egwNDaGzs3PJcebn53HkyBFYrVZqtNavX48dO3bc9aSSDITm2NHRgfb2dvT3999Vnzqv14vz589TnWdCrVvcmYUwusiqvr29PW3VIpEoyBZ/US2LVAfS6XT4xje+QQ3lzMwMjh8/jqGhIWzatAl79uyhD/cPf/gDbXYI3BGPf/TRR/Hcc88lZKTj/0267cZTYsi5mM1mmEwmMJlM2mcNuONl7d69m3Icx8bGMjLIa9aswT/+4z+iubk5Y4McD7PZnLRaUCKRQK1Wo6ioCCUlJQmDnVCsFhc6JOOMxu+vsrISO3fuxL59+1BbWwsAtFcYYXe43W7akkYoFNLqqP7+flgsFhiNRlgsFipYD9zR7b1+/ToqKiqwZs0aVFRUpEz8AHcM8o9+9CMwmcyE7gv3C9evX8evfvUrWqKfzKOOJ/objUYwGAw8/PDD4PP5MJvNGBgYgN/vT1jmEhCD9sknnyz5rqenh9IMU8Hr9eL27duoqKhIG/pKh7m5OVy9ehWXLl2iSmPAHQfmK1/5Cl5//XXweDxalAGALqs7OzspI2Tjxo14/vnncebMGQwODiatEzh37hwuXrxImUCvvPIKWlpa7rlBttlsGBwcxIcffohDhw5l9D4uB7fbjcOHD+PkyZMQiUQoKSnBM888g9LSUhofHx4exnvvvYff/va3AP68gk+XX4pGoysqM/+rlk7Hn0R8vE+r1WL79u3Q6XSorq5OeLAtLS149tln0dvbC5FIhMbGRir8nclxFoN04WUymUljjlqtFlqtNmP6kVgsXrZykM/no6CggMoIkqaXbDYbPp8PXq8XHo+Hhky0Wi2qqqpQX1+PkpKSpLHA+GsrLCzEli1bIBKJsLCwAKvVSgsnCEQiETQaDXQ6XUIZbnysi8/nL/ECORwO8vPz6SRgtVpx48YNRCIRmtkmybDh4WGMjIxAq9VCpVKlHKAkVDA2Noa+vj4aNvL5fGCz2SgvL0dzc3Naj4O06pmZmUm41vilH+G9nj59OqHpZCa5CzJxT01NoaOjAxcvXkRXVxe6urpoAQjhvvf39y+RGiWTY6oGofGw2+34+OOPUVhYiIKCApo8Ky0tzVj6UyaTobq6GqFQCPn5+XC5XGCxWKitraX94wAkzUMQilZFRQUefvhhrFmzhhZwnD9/fglLI/6awuEwVbW7VzCbzfjNb35DS887OzvviTEmIGONJP6VSiVt0hqNRtHb24tr167R7TMZL+FwGFeuXMGbb76Juro6SvuLn/xnZmZw+/ZtWK1W1NfXp9U3WQ73vWNIZWVl0sRGYWEhXn75ZUqrEgqFd6VPKxKJ6KBMZXSzyXjGJ+xSQSqVYvPmzZSK8+CDD2Lr1q20fx0xonw+HzU1NaiqqqIhFxL7i8fiv4uKirBz504UFBRgcHAQg4ODlItKQBoyisXirInyLBYLRUVFyMnJwdTUFM6ePYvp6WlEo1EIhULaGWFoaAjXr1+njIt0KmFOpxPvvPMOPvjgA6oV7XA4wOPx8OSTT0Kr1aY1yDMzMzh79iyuXLmC27dv01BKvCdKKFCk7U82CIVCGB4ehtfrxenTp3Hy5EnEYjEoFAq6oiDG3+PxLBF6ymYM2e12fPDBB1TNsLS0FOvWrcPDDz+clr0Tj5L/J97e1tZG4+UMBoMydNJBKBTiwIEDeOyxxyCXy2mfvMLCQuTl5eGNN95IuoojyISHnw2MRiPeeOMNaLVaGsq7X/D7/Whvb8fAwACVW3W73VmHRUKhED7//HP09/fjgQcewK5du7Bt2zZaoWe1WtHd3Y3f//73GBwcxIsvvviXNcjBYBDj4+OYnZ1FJBJZYvxIh5BIJAK5XI76+vqkHEwOh7Nspj0bpPKMCUgZcqZZz8WlpskgkUiwc+dOKtazceNGbNq0ifYJy83NhdvtptVo2cYSSbmw1+uF1+ullWvxkMvlKC8vz8r7XwyRSIS1a9dix44duHbtGubm5mAwGBKSoJkIHXm9Xrz//vs4fvw4jXvHv/DT09PU2E1NTWF4eBixWIwmZf1+P3p7e3Hu3Dl0dXWl1EO5GzidTnR2dmJgYADd3d30GlfCxFkOJCwE3Ln22dlZOBwOOpnk5OQgGAzSSYVwVwUCAdUYJsUX6RDfwYIkc4myGpGVJGCxWKipqcHOnTsxOTmJmzdvgsvlIhKJUPkDgpmZGXz++eeoqKiA3++neiukSIXkCggbZjl9CSJXK5fLIZPJIBAIUFpaikAgsCQJRmwI6Z04MzOTdWs3p9N5T+iiwWAQU1NT9Dzdbjeqq6vB5XIxMzODzs5OfPHFF1RVj3TpJgVm2SBrg2y1WnHo0CEcO3YMgUBgSXyJdPD1+Xyora3F66+/niDcnA3uVjkpHjMzM7BYLBnfoEw8IbFYjLa2Nqo0p9FoIJPJYLVa6cMgNL6VgCjjdXZ2YnZ2llYbxiMnJwfV1dVpy00zAeFCl5eX4+23315RBaZer8dPf/rTlB60RCKBUCiE0+nEb3/7W/zxj3+k4REWi0XjdSaTKa0E6d3AZrPhypUrYLPZab3D+wGz2UzLyE+fPg0ul5vAUybc9fz8fHzrW9/CgQMHMtoveUcILTQTNDQ04PXXX6cddMbGxvDOO+/gxIkTdJvr16/DbDZDKBTSegASZltYWACXy8VXv/pVPP3004jFYrh161baoiG1Wo3XXnsNMpkMIpEIsViMOj7hcJhOzMSbJdVz09PTOHLkCC5fvpzRtd0vLCws4MKFC7h16xakUiktmLJarXQi6+jogMVioTUU9532ZjQa0d7enhCLSYWJiQmsXbsWlZWV4PP5sFgs9KaTkACRMwRAyxpJQcG9MsbT09Po6OigMouZgMfjLXt8NpsNnU5Hy03jQZaWXC6XlpaSwoxMdSEsFgtu3ryZlhlCwh93y3XlcDi0yOfgwYMr2gdpPppKpNzn8+HWrVtwu904fvx4Rpqz9xp+v39ZBb37BTLhLJck6u/vR2lpKerq6lBYWEg7a5DiGsJxT4ZM3xm5XJ7Qi660tHQJv3xubm7JvdJoNOBwOHT1Ul5eji1btoDBYNBVQCooFAo8+uijYLFYtHMHQbK+i16vF6FQCHq9Hk6nExaLBRaLhYb9yPUymUwEAgEsLCxktJJbKaLRKK3UTAXSbmulyMogh8NhTE5Opiv5DL4AACAASURBVFVyi4fL5aJZW6fTCbPZjJKSElRWVsLr9dK+ewBoTIm0eXn88cczimFl4kUPDg7i008/RXt7e0YPTKVSZSwulAw5OTnweDxwOp2046/f76dc0Ez3SzLA6bx6p9MJg8FAS3SzPefF9y9TgfBk0Ol0OHDgAA4ePIjx8fEl3/f19eF///d/qb7I/x+QjgFzNzh//jyNwQcCAXg8HoTDYTQ1NeGll15KqHJMhXR9Fhcjk21IYlahUFDBf7/fj/n5eaqHnC5syGKxUjI2knn2JFRTVlaGJ554AjU1NfD5fOBwOHR7onA4NTWFDz/8MCNH8cuMrNXesvEuOBwO1R2enZ2Fx+OhxQlOpxNXr15NGmTPzc3F3r17k+4zvghgsfEg5cDhcJjOwqTx6tmzZ2EwGJY957y8PDQ1NaGioiJj6cTFRpMIzLNYLColSWJipEAmE8NJJA6FQmHKGKfT6cT4+DgKCwtpaXI2WPwixmIxFBYWQi6XU4bIYqOdKk6oVCrx2muvwWQyJTXIpD/bvQJh9cQXw9xvEENAxIrSGWNyfumquYDEAg6CoaEhDA0NLfnN7du3UVNTQw1yfGKMnAtpT5TNxOp2u9O2XwJAhfrz8vLgcDgQjUbhcrkwMDBAV7T3ozWYRCJBa2vrEk5xPOx2O6anp9Hb2wu/359UJfIvNT4Wl8tnU7mclUEmamvpBETiEQqFsLCwQI0WAKpP4Pf7U2Y8SWXZYgSDQdolgChxxX83OzuL0dFRDAwM0BiX1+vFF198kZExBu50IHnuuefwwAMPZGTcbDYbLly4gOvXr9MigJqaGjQ3N1P+Y3xzSqfTSfv7yeXytJU8HA4ngT2yGEStanx8nPKa71bEpqCgAE8//TQaGhoQCAQo8yDeg/nVr36V8vfFxcV46aWXoFAocPbs2XumuZAMRUVFeOyxx1BaWppSze1eQygUIhgM4urVqzh27FjabVUqFZ5//nnKTlnsTZPPBgYGcOLEiYycHb1ej48//hjj4+NgsVgJBtnn84HBYKCxsZEyK1Jh8SRLVPjSgbQ+MxqNMBgMtPDL7/ejuroaVVVVKas47zfkcjn27dsHkUhE4+KkaIwoLi6u6LwfIO+L2+2G0+mE3+/Hu+++m/HvszLIJF6TzQUtfkmCwSDGxsaW9SzILLf4t6TDRjQaTRhwFosFvb29OHv2LE6dOoWhoSHEYjHw+fysMp2NjY3Yv39/xkR+u92OY8eO4e233wZw54EcOHAAWq0W+fn5NBRDZP6AO3S5WCwGsVic1iBLpVLKnyZJjvjv1Go15HI5lQy9F/qwBQUF2L9/f9pJ9/Dhw2n38dBDD6GmpgaRSOS+GuSWlhb83d/9HS2XvZec1mQgOYBYLIZ33nmHVtClglKpxMsvvwy1Wg2FQkF1lQnICuzSpUuYmZnJyCAHAgEcO3YMJ06cWGLgiSe2e/duVFVVYcOGDWmvJR5EXD4dXC4X+vr6aBguFovB6XRicnISTqcTUqn0nvKWs8XWrVuxadMmOtnEr6BXIvSzErDZbKpzbjQa4XK57p9BJoT4u/VElrsx7e3teOutt7Bjxw76sgF3QgF2ux2zs7Ngs9kQCoVQKpUIBAIYGhrChQsXcOHChaTFAnw+HyqViqrSzczMJJwHm81GXV0dSktLl6UZxUMoFCboAxN9BSJyT2rl5+bmYLPZIJPJkJOTQ8WF0qGwsBDbtm2DUqnE7du3cfPmTVqVptPp8Mgjj0Cr1UImk2V93qlAyo6X2yYZ4u9nfn4+NBrNfYmxlpSUoLW1lXZSJrhXIj7LgcFgYMOGDXjxxRfR19eH48ePp9yWx+Mt232msbERTz31FPLy8hAKhSAUCsHj8RAIBJIWpyxHybx+/Trefvtt3Lhxg0oPiMViqFQqlJeXU10H4E6oor+/HxcuXEBfX9+y156MORCLxTA4OAiBQHBPQ1KZIF7nJpniHJkAV9Ia625QUFAAhUKRtZOQtYdMOhXfTxCt19nZWXz/+9+ntLH4rtI2mw0zMzOw2WxwuVy4du0azp8/j97e3iX7EwgE0Gg0qKurQ1FREQwGA9xud0K2u6KiAi0tLVAqlVhYWKBtaTLBYk9eoVAkyE4SGU6XywWVSgWVSrVsuAIALdqor6/H7du3oVKpMDs7C6vVirq6Onzt/2PvPYPjus77/+/23rCoRO9EIYlCgCREsYpFEiVTzZZsK4ps2U5spzmeZJLMxD9PZpIXsj2xIpsexVajJUuWaFmmREisgFhBohO918U2YCu2797/C+YcY4HdxS5Aykj+9zPD0Whx99675577nOc89UtfotW5SPTKn5LlWtd6qv7FusYDDzyA7373u9i6devnUic6EsXFxfj2t7+NxcXFqALZ5/NhZmaGFt6PhkqlwhNPPIHDhw/TBqdqtRoOhwOvvvoq+vv7E4oeMJvNePvtt3Hq1ClabiA/Px81NTU4cuQIMjMzqeC6ffs2fv7zn+PMmTPrqiVht9vR0tKy6mJ+t4n1/O12O0ZGRqgz8vPW3iUSScKVChMSyAKBAFlZWcjPz8fIyEhccZwymQwKhYLafEkft/n5eVpuLxJ6vR6ffPIJSkpKcPToUaSnp9M4WbFYTG1eExMTaG1tRVNTU1TPvUqlQmFhIerq6lBRUUG3WD09PeDxeLQgOYmFJdENq0VweDwenD9/fkUYzOzsLC5duoT6+noolUpkZ2fD7/djfn4e6enptLrYagsbeZmys7MxMTEBtVqN7du3IxQK4eDBg9i2bduKxcDtdmNiYgJzc3MRE3eWnpvYtoE/Nqtcr5ZNkiFu3bqF7u7umNqxWCxGYWEhkpOTaUpzUlIS0tPTYbPZMDo6uiKih8PhICcnJ6z2xN2MV18Nci2RSLRqaj2pNBbrXMCd35SamroiiUOtVmPv3r3o7+/H4OAgxGIxtY3a7Xb09fXBbrfTolEmk4m+A1qtFlwuF2NjYzCZTNi0aRPtijI/Pw8Oh0MbjjY3N8cljPl8PrRaLW3AS/rukZIFn5dZYDnk2ev1eszNzVHfi8lkwtzcHJRKJTIyMv4k5pREldeEO4aUl5ejvr4eCwsLqzbeFAqFyMzMREVFBbZv347KykpkZWUhFArh+vXrePvtt3Hjxo2o3+/q6sJPfvITTExM4Fvf+hYyMjKQn5+P3Nxc+kNv3ryJDz/8EO3t7VFNKcnJyaioqEB9fT2qqqqQn58Pt9uN3Nxc2pVkYmICU1NTsFgsEIvF1CEYyzwzNTWFl156aUUbHeJEPHbsGF544QWaSafX6yGVSmkHhHgxmUzo6uqCyWTC4cOHsX37dhrbvZyFhQWcOnUKH3/8MW1KGW1ShEIh2Gw2SCQSPPLII/j617++boGs1+vx+uuv49SpUxgdHY15rEajwZe+9CXs2bMHly9fxsWLF1FXV4fDhw+jv78fP//5zyN2xSCdGMjv+jy15ESuJZVKaSH0tZ6LFLmy2+20K7lEIsHAwABefPFF3Lp1Czt37sR3vvMdXLp0CS+++CKSkpLwF3/xF8jMzMTJkyfR29uL/fv344tf/CIkEglGR0fR0dGBa9euob29Pa7uOMCd92jHjh1QqVTo6OhAT08PNYOQRAkej7eqs/NecfXqVZw9exZisRgFBQVQKBSQSCTQarWfu8lirSQcaJuamork5GQkJSXRGsPRhJZQKER+fj4aGhqwb98+1NTU0JdIpVLRyAer1QqXywWDwRCWuBEKhXD79m3weDyUlpbi8OHD1Ekml8sxPz+P27dvo7OzM+o9pKWlobKyErW1tSgtLaXtenbv3o28vDwarO9wOGhgORFSq0WUOByOsFKGxF5KvM+BQACbN29GWloa1XRXg3R69ng81AQxOjqKsbExuN1uVFRUYO/evVG/73K50NXVFXOhi0RhYWHc0TOxcDqdaG9vj8uZx+fzUVVVhb1798Lv92NkZARbtmzBwYMHkZSUhA8++CCiQCY7mPUUrv88EAgEa67yRjRxjUYT0TlXWFiIGzduwGq1Yv/+/Th06BCEQiGuXLmCtLQ0PPbYYyguLkYwGMTVq1dRWVlJO3J0d3ejqakJTU1NYd2qSbicXC4P6/ZOFoLi4mLcd9990Gg0kMlkUCqVSEtLQ2lpKcRiMX1fYgnkSBUN14vb7UZ3dzfOnTuHM2fOgMPhoKysDNXV1dixYwdSUlLuel2Oe0XCApk0e9TpdLTUJenKsXy7IhQKUVRUhO3bt6OwsDBMU8vOzsZjjz2GhoYGMAyD8fFxvPXWWyscGMCd+NWTJ0/i+vXrYa3pPR4POjs7o9oqc3Nz0dDQgEOHDmHHjh1ITk6mW+Dy8nIkJydjfHwcdrsd2dnZSE9PB5fLRU9PD6xWKxWka2VwcBAnTpzA1NQU/uzP/izMmRJpm03iOqempjA9PU0dbGNjY2AYBmq1es0Ot9UgL+J6iRX8vxyHw0EXUpK5FQwGsbi4SFvtEOfW8ntdKoyJk+le+zY2ElKpFE8++SSqqqpok4jy8nL87d/+LaRSKbKyssDhcPD444+jrKwMY2NjePXVV2mX88nJyTBzIZfLhVKpRF5eHnbs2IHq6mooFAraZZuUbiXtx/Lz83Hw4EFal8JkMmF0dDSm6YNk55J6zXeD2dlZ/OEPf8Ann3yCzs5O6PV6BAIBLCws0K4vhYWFCV1vNRPYvTSRram4kN/vh0AgQH5+PpRKJYaGhtDX1xfxxcnJyUFZWdmKeg5isRg7duyg/0+iJ0hc41JsNhvOnTtHmx5Ggggvoj2lp6ejoaEBR44cwX333YeioiIaNkfST3k8Hrq7u6HT6SCVSqHVaqltjpQ5TOQlX74gMQyDlpYWzM7OIjU1FS+88ALdOi1/oGShm5iYwNDQEGZmZqiH3u/3IysrC3K5HEKhkIYYRSIUCq1JG/D7/dQBtR5Ij7a0tLQw7SsSmZmZYV0+UlJSwOPxaC0QuVxOnaxLQxdJn0LS523pMwoEAmERCEufCdlSr7cD9OdBPC/8rl27wqrGpaSk4PHHHw87RqFQoLCwEOfPn8fJkyfhdruh0Wgidg4XCoVIS0tDQ0MDnnzyyZjzaHmm4OTk5KpOXJKPsHz8id9maS2O5QlgJLqD2KqBO3HRN2/exNtvv72igQDxjaSnpycs/MnYL034IslciYb9JkrCAlmhUGDXrl20kA6Hw8Hp06cxMjKyQiALBAKkpqbG9DAT1Go1nnrqKchkMpw7dw43b94Me7FWiyUuLS3FgQMHkJWVBZ/PB7FYjJKSEtpanMDj8agpwOfzoaurC83NzSgoKMC2bdtgs9lonLNAILgrBWhmZmbw61//GjabDY888ggtIr8Ui8WCM2fO4PLly3C73UhLS8PmzZtRUFAApVIJj8dDK+TF2qovLCysKbqhra0NL7/8Mnbv3o26ujoUFxevSeMMBAK0QFA0UlJScP/99+Pw4cOoqqoCcGc3c/DgQWRmZiIpKQkTExM0jGl5NualS5fA4XDw8MMP48CBA2Hnvn79OjVhCQQCLC4u0rFLTk5GWVkZduzY8b9mC7terl27hnPnzuGTTz7BxMQEAoEA7HY7rSRICIVCWFhYoB21E332qampqKioiOnoXFqRcakPgHRgF4lEtEenyWSCx+OBSqWCWCyG1WqF2WyG1+uFz+eDzWbD7Ows2tvbaSgoQSKRoLi4GGVlZWve9Xm9XjQ1NaG7uxsCgQB5eXnYsmVL1JT1u6U1JyyQlUoldu/ejd27d4PP59OurqdPn45Y4yKRm6yrq0N5eTm4XC66u7sTSnQoKSnB888/j9raWgB3IiBIOb+lKapisZhOivn5eYyMjGBgYAAikQh5eXm0Ut38/Dx4PN66CoUs5cqVKzQVtqSkZIWTwWazobm5Gb/5zW+QkpKCAwcOQKPRoLKyknrfl2sRyyH1M+ItoLQUUm+5q6sLzz//PMRiMbKyshJ2hpBtaSxve25uLv78z/8cjzzyCP0sMzMTGRkZVJuRSqWQyWQ0BX3pXOjs7ERnZyesViuKi4upbV6n0+Hs2bM4deoU3G43LWjlcDioo+fw4cNITU2NuCj+X2NiYgK//OUv8dprr4V9Hq24kc/nw8LCAkwmEwwGQ1w+D4JEIkFRUVHM504aGJCsOTKPjUYjent7acPfUCiE3t5eWK1WWg9ap9NhaGgIdrsdLpcLIyMj6OzsjJiBW1RUhD179qCiomLNYXjz8/P49NNP8d5770EsFmPnzp20nVmkaI27pTUnLJBJQ016gv+pNhZJg/V6vRgeHkZ/fz9KS0vjWnVlMhktFp4oS1uVR9KAyMPx+XxwOBywWq0oKSkBwzDIy8tDRkYGzGYzbDYbvF4vrFbrXc3+MplMOH36NBQKBQ4cOBDWIJPY4oRCIUwmEwYHB9HQ0BDWnn014UgSCtaTuHP79m00NjbCaDQiNTWV9tcjDj8OhxOzNKZIJKIhVtEyz/h8/opdE6nfS1Cr1SgtLcX09DSsVmvEc127dg0nT57E1q1bwTAM+vr60NzcjMHBwRWmLY/Hg76+PohEIggEApSVldGM0OUszUglGWlrYX5+Hr/61a/g8/mg0WjQ0NCAnJwcBAIBjI2NUVtvPAQCAUxMTNC5unTbPzIygps3b8Jms0EoFEImk0EgEKC/vx/Xr1+P+35zc3Oxc+dOlJSUrCnaJp53lozt0jFVqVTIycmBXC6HRqPBwsICrFYrzWxNTU2FRCKhkU8WiwXz8/NRQ2bJs1urkAyFQpicnKSda5ae02QyQaVSUeHc0NBwV9PF74plncQiLi8gvbi4iFu3bkGtVsPv92Pr1q2rnsvhcGB+fj7hQiCBQGDV4Hlirpifn6c2rwMHDuDw4cPg8/nwer0YGxuj2yLy8t5Nrly5gvHxcej1enzve9+jtSdEIhEKCgpQVlaGrq4uDAwMYGRkBHa7PW67LofDidlBOR4WFxfR1NSE1tbWFeYCco1YYVKkHdfk5CTa2tpWhAQCoEWXYqHValFVVQWLxULHaznj4+M4ceIE/b1ut5s26YyEx+NBd3c3JiYmaMeWpZElREgIBALweDzabIFo54m+4DqdDj/4wQ/gdDpRUFCAf/mXf0FOTg7m5ubw2Wef0WileJ6XXq/H1atXaZf1pQ7iK1eu4D//8z8xMTEBuVxOCy6RRrbxIBKJUFNTg6NHj6K6uvqeFAkiLBfc2dnZNBJCLBbTCBqxWAytVou8vDxwOBxkZ2cjGAzCbDbD4XDg2rVrEW3hXq8XTqcTLpcrYTlC4vhJr0nC+Pg4zGYzrV7p9Xqxe/duaLXauLu/xMNdEchlZWV48sknaSNGIhhJd5GWlhbI5XIwDAOpVEqriMnlchp2Rjop6HQ6dHR0rFriMycnBzk5ObQLSEVFRdjLRSqrRXqJiHNHo9EgIyMDGo2GFi4izkG/359Q7eJEmJ2dxblz51BcXIyamhqEQiEMDw9jZmaG3q/H40FHRwc+/PBDHDhwIO7tY3JyMurr62EymeD3+yGRSDA1NRWx+lo0lmoniSKXy1FVVUWzE5cKZKI9b9myZVXbnkqlQllZGWZmZqLae71eL9Vg4mVxcfGe1sxdis/no1vqjo4OnD9/HklJSRgaGkJTUxPtwJ6bm0szUJdDylr29PTgypUrNDW/pqaGho5euHCBZqjG2/lEIBDQ3nA+nw9arZY6wIgD7fOK3SWCmCCXy6HVasHn8yEWi2khMmIDdzqdmJubo4WV8vPzkZKSgqGhIVq4a/PmzcjNzU04NNJiseDGjRtoamoKq1Pi9/uxsLAQFkVy5coVNDY2UkXP7XbTBdHtdtPiQolwV6TNnj17UFpaivz8fLz00ksYGRkB8MfaE8PDwzRriGiyZOXzeDxoa2vD0NAQbWGzWj48l8vFwYMH8dRTT9EOFCQBgtRmFQgEUcNr5HI5cnNzaY6/QCCgWyKRSITU1FTa5+9eeeT7+vrw05/+FBqNhlaHIiFJhJs3b9Kedt/+9rfDtrfRnAgajQaPP/44GhoaIJPJ4PV68f777+PEiRMxJ8fdqjkhkUjo4tjW1hb2t9zcXBw5cgQHDhxAZmZmzPNwOBxotVps2rTpc0/HvVc0Njait7cXDoeDztNbt27R7hmRtDmiTVqtVjo3enp6kJSUBIFAALfbndBiS0hLS8PRo0dRVFSEQCAAm81G61qIxWKqrPwpkEgkyM7OhkKhAIfDwdDQEJqbm3Hp0iUaNjc2Nga9Xo/MzEw8//zzKCwsxGuvvYbz588jPz8fDz74ICorKxPe1SwsLODy5ctobGxcVSmxWCx45513cPXqVSiVSigUCmrz1uv16O3tXTXSaDl3Tf0j7XmWrqokNZesZqRjh9frpbVVXS4XWlpawn68UChEXl4edQAQzTcYDMLn86GoqAgHDhwIq5lsNptp6qRCoYBKpYpYbAS4ox1E2pKRmhdkst8L7Zhgs9kixlwvxefzYWBgAB988AGKi4vx2GOP0fuONNFIgfCSkhKUlJSEXYs4wpZ25ya7AtId+m5BQsuWb01TU1NRV1eH2trauBMm0tPTUVlZidHRUfj9/lW30sTMQDoPR9rS/qmYnJxcYcJZS6useEvJEkiCiVqtpiVVGxoasHfvXpSUlMDr9WJqago9PT0wm82YnJyEVquFzWaDXC6ntYXJzpIU8iFjHQgEaPOFWHZkIviJ8hMNor2r1WqEQiFMTEygpaUFp0+fRigUQkpKCu0X2NDQgIceeghZWVk4f/48AFDBuBYbssvlwtjYWNw7xOHhYQwPDwO409m+uLgYKSkptKv2PW/hFIkbN27gzJkzaG5uXtHChTTmtNvtVMiRlX1ychIul2vFS1NdXY3nnnsOmZmZWFxcpDY8Eq+o0WhoMDyBy+XC6XRicXERoVCIFttJdMuyNCxuo0ASTCYmJvCVr3wlTNjGE25TVVWFv/7rv4bRaKT1FaRSKQwGA95//32cO3furt2rx+PB2NgYbt26tcKcQGyCZMGLh/T0dHzpS19CXV0dgsFgzOdJzE0OhwO9vb1ob29HV1fXms0v/1cQi8U4fPgwjh49CqlUCrfbTRUiovQoFAoUFBRApVLB7Xbj6tWrdOcol8uhUqmgVCohl8shl8uhVCohEAioeYs821jvjsPhQEdHB0pKSiI2OPb7/bSzTmpqKkKhEKxWK20wSoSbWq1GUVERCgsLaY4BaXEF3FFA9Hp9zKbC0d6b9TgDGYahNT4MBsOaCuInLJAjtYW5fv06XnrppYj2q6W2MY/Hg/T0dOTl5dGC8nw+Hzk5OeByuZiZmYFEIsGRI0fwta99LSFh6vP5aOrm0nqoGwWhUEiLF5HCRUB8zVQZhsGtW7cwNzeHjIwMFBQUhPUUI0T7vRkZGTh+/PiKz4ldrK2tDQsLC3SxBP4Y9UA6DMcbuREIBGAymTAzMxN1PiSijSuVSuzbtw/79u2L+zsMw+Dq1at0J9DZ2blqH7t7xdJY6tXacd0rBAIB6urq8Nxzz9HPiPAwGo20PVRycjJkMhkNgXQ6neDz+bT2dlpaGi2dkJKSApFIhPn5eZjNZirYY/kGSMehaJElZAdMFlZi8jQYDHC73VQL12g0KCgoQG1tLfLy8mA2mzEyMkLNA7Ozs7h27RoCgQCys7Mj3tPSOsl+v5+WZCDCn0BC3CIJ16UdWmQyGaRSKSQSCWQyGS19cE/Lb4ZCITidTlpFjNwsCdSOh/z8fDz22GPQarUwGo3UEM7n82GxWCAQCLB///7Ey9bx+VCpVFAoFNBqtdBoNBtG0+Xz+Xj44YdRVVWF8fFx2l0ESMyBNjMzgzfeeANGoxGHDx9GXV1dTMfLatqzQCDAgQMH6MtJtqaksL9arYbT6URTUxPOnTsXl1CWy+W01c7Q0FBYjzPinLFYLHFFsKw12J7D4dB49vLycoyNjeGzzz7Dp59++rlWIxMKhaitrUVdXR1NeFrNTHUvsNvtKwQKichxOp00xJPP59MWaMv7ORIhSdKp3W43QqEQRCIRUlJSAICaI6Mhk8lQUlIS1exE/D7EaTc5OYmOjg60trair6+POhtNJhOGh4cRCoUwNDQEj8eD2dlZWvdkZGQE7777Lnp7e1FRUYGqqqqopVpHRkbQ2toKnU4Hm82Gnp4eWllv3759uO+++yAWi8M6sxDImJjNZly5cgVTU1MoLi7GgQMH0N3dTeVbIiQskF0uF23ZTQQyKRQfTwm/zZs34/HHH6cZL6TtDBAedhQvZIUj/bx4PN66Q7/uNtnZ2Xjqqadw/PhxtLS0QCwW04QTnU5HyyjGw40bN6DX62k0QyyBHI8wq62txdatW2nRFwJpL2Sz2eBwONDU1BS3liyVSrFt2zaaGk2eq8fjgdlshtlshkajWfU5r2eHk5SUhB07dqChoYHGjA4NDa3JAbZWJBIJDh06hKeffhopKSkIhUJ/EoFMSt4ux+fz0YYT5L0mi2BKSgrVLHk8Hq2ASBKrSLMKjUYDqVRKQ+xiRbDI5XJs27Ytqp2ZFDEyGo1ob2/HZ599hmvXrqG/v5/efyAQoD4pEpdNcgfIMXq9Ho2Njejr60N1dTUcDgc0Gg1ycnJWXLOnpwe/+c1v0NraGpZ3kJWVhS984Qv4xje+AR6PF2YyIZB3hJQRnpmZQW5uLg4dOgSxWIyPPvoo4Q7nCReoJ5ELS18morKvJpBFIhG0Wm1YUkAsLTaWhkRWcp/PR6ujkQlF7M5EECwPq7nXFBUVoaqqim5diouLUVdXB4lEgi1btsBqtdIdBUkBHRwcRGdnZ8S4XQJJna6pqUF2dva6iumQsSXZjJFYWFjAjRs3aI3dtLQ01NTU4ObNmxGPdzqdNDRrbGwMAwMDETVS4gu415DfJRKJsHPnTnz1q19FX18fDacC7sxpoVBIHaidnZ0rtBqJRIL6+nrk5+djcHAQbW1tcS1OarUa+/fvp0lRDz30EIxG1z19EwAAIABJREFUI65fv06dlPcSiUSCzZs34/7770ddXV3Y+2Q0GjE5OQmLxQI+n4/09HTq4FUqldBoNGH1G4jvgQhg4tgjRanIgr5aa7bVQuk4HA7sdjs6Ojpw+fLlFTXOST9OsjAQocjj8eBwOMI0dLIj6+rqgtvtRllZGU3vFggE0Ov1GB4exu3bt1fE1pPaz0vnUDRIWjWpEX/27Fn09vauyTyVkEDm8XhQKBRgGCZsYEl35NVQq9UQiUTweDxx5ZjH0pD8fj9cLhfcbjc8Hg+8Xi8dAKfTSbfepNhNol1418PWrVvxV3/1V6ioqKChZmRbp9FosG/fPiqQhEIhGIZBa2sr/uu//iumQE5KSsLx48fx2GOPoby8fF0heauNxcLCAk6ePIn3338fnZ2dCAaDaGhowPPPPx/Vy2+z2fDWW2/R7tLLtQOiaRENKxgM3rNYV1IzmXjzCwsL8c1vfpMKW7KYcblcqFQqOBwOeu/LBTLp6PHQQw/hvffeQ29vb9wCefv27fRae/bsQU5ODl555RWcOHHinjsb09LS8Oyzz+KZZ54Jy2JlGAbT09O4cuUKGIZBTU0NsrKyqPOdVHVTKpUQi8V0npHQPOIHWGofj9ZCaSnBYBBOp3NVc5XD4cDg4GDUhhPAH4smkfuem5tDV1cXxsfHIRAIkJ6eTovSj4yM4PLly8jLy8Pzzz9P+xuSTLxIz2Fp84bV8Pv9KCkpQU1NDe3rSXa8GRkZcdebBtbg1Iv0AhFjeyw4HA4kEgl4PN66tSPyMvv9fni9Xrjdbmr3Wtrzi9hCY3lb7wWbNm3Czp07I4b2cLnciDa0hoYGvP/++zHPK5FIUFZWhp07d97zWsAWiwWdnZ20ipZYLEZ2djZ27NgR9VmTcqjRSqKStPulnYDvlUAm84PULyHNEqKh0WhoXd/liEQiVFRUoLCwEKWlpXHfM0l+WkpeXh4qKys/lx0bMWstFcYAaPTC5OQkhEIh+Hw+VVoYhoFEIkFKSgp18hGlwev1wuFw0Aw48iyJA315+vtySFLLarLC6/WGxeNHgs/nQ6PRIDs7GzweD0KhkOYvCIVCWopAJBJhenoag4OD0Ov1eOCBB+Dz+WgxJZvNFnGuEmd2PDAMg+TkZGRkZODChQu0Zg0Zw0QEMicRJweHwzEBiK7C/d8ll2GYlOUfsuMRDjse4bDjEQ47HquTkEBmYWFhYbl3/P+nxQILCwvLBocVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBFYgs7CwsGwQWIHMwsLCskFgBTILCwvLBoEVyCwsLCwbBH4iBycnJzN5eXnruqDdboder4fT6QTDMPRzoVCI9PR0pKSkxPx+MBgEAHC5XHA4HHi9Xng8HgiFQkgkErhcLszOzsJutwMAOBwOMjIykJ6eDg6HE3auQCCA6elpLCws0M82bdqEjIyMsOPa2trMDMOsuLF4x8Pr9UKn04VdJx64XC5EIhGUSiW0Wi0kEsmKY8xmM2ZnZxEIBBI692qIRCJkZGRAq9Wu+NvExATMZjNn+efJyclMbm7uinGOxezsLIxGI0KhEAAgJSUF6enpEAqFUb9jsVhgsVjg9/vB4/Egk8mgVqsjjs96cLvdmJ2dhc1mW+3QiPNDKBQyPB4PHo8HXC4XmZmZSE1NjXidmZkZOmeXkpycjE2bNkEgEKx6v6FQCIFAABwOBzweD1zu3dG3HA4HpqamEAqFkJOTA5VKFfP49b4vsXA6nbDb7WAYBiKRCGKxGAKBABwOB36/H6FQCEKhECKRCADovOJwOAnNy0iEQiEEg0EwDEPPx+PxIp532XsZcTwiwjBM3P9qa2uZ9WA2m5kTJ04w9fX1jEAgYADQf0VFRcx///d/x/x+MBhknE4nY7fb6Wcmk4lpb29n9Ho9wzAMc/v2bebBBx+k55VIJMy//du/rTiX3W5nPvjgA2bfvn30WA6Hw3zzm99kbt++HXYsgNZo4xEKhZjZ2VlmcHCQMZvN9Nyjo6PMwsICwzAMMzMzwzz//PNhvzeefxKJhKmsrGS+//3vr7gnwsmTJ5nKysqEz73av+LiYuY3v/lNxGv+zzxYMR41NTVMIBCI+vw8Hg8zOTnJjI2NMXNzc8xnn33GPPvss4xYLKbX/cu//EvGaDRGPUcoFGIuXbrE/OAHP2C+853vMP/0T//EvPnmm8zw8DATCoWifm8t9Pf3M4899lg84xVxfigUCqampoZJS0tjiouLmX/7t39jpqenw67hcDiY3/72t0x9fX3Ec7/wwgvM5ORkXPfr9XoZq9XK2Gw2xu/335UxMBqNzI9//GMmMzOTSU9PZ1588UVmenqa0ev1zODgINPf388MDg6GPbNY78t66erqYn71q18xJ06cYE6fPs10dXUxMzMzjF6vZ/r7+5m2tjZmenqaCQaDDMMwjNvtZlwuV8x5GS9ut5sxm82MXq9njEYjY7PZGJ/PF/HYM2fOMI888giTmpoadTwi/UtIQ04E5n9WEcLQ0BAuXryIixcvQqfTwe/3hx0vFovB58e+HQ6HA4FAELbyJycnIykpiX4mEonA4/FWnHspMzMzePPNN3HmzBn09vaG3fPly5fB5XLx6KOP4sEHH1z1dzocDrz99ttob2/H448/jieeeAJdXV146623kJubi+9+97tITk5eVauIBMMwCAQCdFcQiaSkJBQVFcFoNMJsNlONYL1wOJwV4xbPd5aP/VImJibw+uuvo6+vDyKRCD6fD/39/fB6vfQYoVAIuVxO/5/5n10UmUscDgclJSWQy+V0Z6RWq5GamrpuDWj5teRyeVyaaSySkpKQkpICmUwGnU6Hd999FwcOHEB1dTWsVisuXryIxsZGjI2NRfx+IBAIG59Y9y4UCmPuLOI5x9Ix7O7uxuuvv45z587BYDBAIBDg1KlT6OrqApfLhc/ng9PphFQqxZEjR/Dss8+ue7xWIysrC0KhEKFQCHK5HDKZDGKxmO4mA4EAJBIJ/R3kfu7GbkEgEEAulyMUCoHD4YDL5Uad7xUVFfj2t7+NJ598Es8991zc17hnAnnpg7Varbh27Ro+/PBDdHV1YX5+fsXxxASx2jnJhPN6vXC73fS7CoUCHA4Hk5OTWFxcpN9hGAbz8/MwGAxIS0sDAFy9ehUnT57EwMDAimv09/fDYDAAuPPwt2zZEvOe+vr6cObMGVy9ehWbN2/GI488gpGREbzzzjvIyspCTU0NCgsL4XK5Yp4nEmq1Gjk5Odi0aVPU7bhYLIZKpYJSqYTNZovr5Y0Hn88Hg8EAl8sFqVQKu91OhX20BYJhGCwuLiIQCFATCofDgUajgdfrxbVr1/DOO+9gYmIi6nUXFhYwOjqKyspK+v3lbNq0CZs2bVrnL1zJ8muNj49HNCMkglwuR0ZGBuRyOXQ6HVpaWpCRkYHi4mJYrVaMj49Dr9dDIpGAz+evMD2FQqEVi6zb7YbX6wWHwwHDMLBarbDb7RCJREhKSoJCoUh4MQXCf//i4iLOnj2L119/HRaLBcCdxeHGjRu4cePGiu/6/X5UVVWhpqYm4esmQlJSEpKSkiL+LdI7EktBWA2yQAN/VDbiPV9OTg5ycnIA4N4L5OWaRCwmJiZw/fp1XLhwAV1dXZibm4t4nNPpXKE1L7/m0utdv34djY2NWFxchFwuh1gsBsMwGB0dDdM2AoEALl++DK/Xi9TUVLjdbnR0dKwqFJqbmxEMBumgRsJoNOLtt9+GXq9HamoqZDIZ7HY7XC4XAoEAenp68Itf/AKZmZlobW2NMUorSUpKQl1dHR5++GHs2rULWVlZEY8jNvPZ2dm7JoyBO4vohx9+iImJCQiFQng8Hvrcoz1Dl8uFCxcuoKenB+Pj4wgGgxAKhRCLxXQ8JicnY1736tWr+PGPf4yHH34Yx44dW5NgSZTlc8tiseDDDz/EmTNn0NPTs67zer1eeL1eSCQSqvn7fD7odDrweDxs2bIFEokElZWVGBoaQm9vL0ZGRug5/H5/2Bj4fD589NFHuH79OgKBAMRiMRXQfr8fMpkMdXV1OH78+Jp2ZQDQ0dGB3/3ud/joo4+oMF6N9vZ2vPzyyygqKlrTNTcaDMPA4/EgEAhAIBDEPQ+Xz6VESUggMwwDn8+HQCAAhmEgEAhibpGsViuuXLmC06dP49atW9Dr9VGPXVxchM/ni/r3pT/SbrejsbERP/nJT8I0MXKPSwkEArh69SquXr0a9ZhI9Pf3o7+/P+bgmkwmXLlyBcnJyaivr0dRURF14CQnJ8PpdOKDDz5Y9VrLEQqFSE5ORk1NDY4dO4bMzMyox5rNZoyMjNDdwt3CarWisbERn3zyyYq/RRs/r9eLzs5OnDt3Di0tLTEX2GiMjY1hbGwMJpMJ+fn5qK2tTfgcibL8Gd+8eRMnTpzAzZs313VeHo8HpVJJnUwajQYqlQoKhQJWqxWbNm3Crl27sH37duh0OnR0dEChUCAQCGBiYgJcLhdKpTJMKxsaGsJ7772H9957L+p19+/fj8LCQuzevTvhe/Z4PPjDH/6AH/3oR/B4PHF/b3JyEq+99tq6zUYbhVAoBJ/PR3ci8bLe35+QQA4Gg3Rb7PP5EAwG4Xa7MTU1hampKQQCASgUCqjVasjlchgMBly8eBG3bt3CzMxMTEEYaWsWiba2Nioolm7vIp2bbOliHbMasb4jFotRW1uL/Px8bN68GdXV1VAoFOvaJgF37OByuRxarZZGOVitVkxPT8Pj8YDP59Mt+8LCQkIvTqIkMmYikQhbtmwBl8tFdnY2jabh8/kQCATQ6XRh2l8s2tracPLkSXR1dSEUCoUtOCS6IjU1FQUFBcjPz48YvZAoer0e586dwwcffICOjg76OZfLpXbqoqIipKamwmQyoaenByaTCU6nM+L51Go1vvCFL0CtVkMqlcLtdiMQCECtViM5OZm+J8Cd7bZAIIBEIkFpaSmMRiP4fD7q6uoQDAYxPT2Nrq4unD9/PqLJYCnt7e149dVXYTabsWvXLqSlpUGn02FgYAA6nQ5WqxWBQCDMTMjn8yGRSGA2m3H+/Pk1z6m1vGOxCAaDWFxchMPhgMPhgMvlorsB4I4PqaioaF2280gQfxWHw1nVtxXtvv1+f0z/TyQSupLP58Pk5CQ8Hg/dJhmNRjQ1NaG5uRkulwvp6elIT0+HUqmE1+vF0NAQJiYmVn1Q8awsc3NzeOONN/Dqq6+G2Ymjcbcnx3K0Wi2eeeYZ5OTkICsri25r1vIAl0KcBT6fDwsLC9BoNBgbG8Pw8DDm5+cRCoWwadMmiMXiVRe6zxPi3Dl48CBsNhtGRkYwPT0NhUIBgUCA5uZmvPnmmzAajauey2Aw4I033oBIJKIeaILb7Qafz0dlZSX279+PvXv3YufOnZDJZOu6/88++wwvvvgibt++Hfa5QCBATk4OduzYgUOHDqG8vBy3b9/GqVOn0NvbG+YYXkpSUhKOHz8OkUiEYDAIg8EAi8UCpVKJ9PR0GpoF3BHIhYWFyMrKwsGDB8HhcBAMBuFyuTA3N4empib87ne/Q3t7+6o7D5vNhtdeew0DAwP4u7/7O+zevRudnZ34wx/+gK6uLkxOTsLlcoHL5dK5SsK4gsFg1AXmT4HH48H8/DzGxsYwPj4Oo9EIp9MJl8tFHbwSiQT5+flxnzMQCKz6jnK5XEgkkjWbIILBIDweT8K7xIQkh81mw9mzZ+mqIZfLsbi4iJmZGUxNTQG4s4UeHx+HRCKB3++PJ4YTQHSB7Pf7YbVaMTU1hUuXLuHcuXNxCePPA6lUiq1btyI5OTns8/VuW2w2G8bHx9HZ2Yn8/HwUFRWRMCqYTCbodDpMTk7C7Xajt7c3LoehWq1GKBRat5MqFhwOB1KpFACgVCqRkZEBg8FAnS18Ph9WqxUtLS2Ym5ujmlokiLMqFm1tbeByuXA4HJiYmKBO26UvgdfrBY/HQ0lJCbZt2waPx4PW1lY4nU7U1dVBq9XCaDTiwoULOHPmDEwm04rrCIVCVFRU4NChQ9i7dy+Sk5MhEAhgMBiQmpoaVSBzuVz4/X4MDAxgYWEBKSkpyMzMhFgsRigUgt/vD4tK4PP54PP5YQuLy+XCxYsX8eGHH6KlpSXmeEQan48//hhzc3MYGBjA1atXMTw8fFd9DfeCQCAAl8tFTZherxcjIyNoamqCTqejpgQAdGdeVlZGFzBiKiopKcGmTZsQDAbR1taGkZER+Hw+ujOQyWTIyMhATk4O0tLSVgjp9cQurxZxFI2EBfInn3wCmUyG5ORkFBcXQy6XQ6FQhB23uLh4V4Sm3++HwWDAtWvXcOrUKVy+fDmqQ+lPgUAggEajuSfnNpvNaGtrQ3JyMrhcLrZt20ZDuwwGAzo6OtDb2wuj0bjqC5aUlISysjK4XC709vbGtNXfTfh8fpj9u66uDmq1Glu3bsXFixfR2tqKmZmZNZ/f7Xajs7MTo6OjaGxsXJEMANyZswKBAF/5yleQlZUFi8WCX/3qV5icnMS//uu/Yt++ffj000/x//7f/wPDMKiqqoLT6URvby91aIlEIlRUVGD//v3Uw6/VarFr1y6Ulpbi5Zdfjnh/gUCAOsimpqbwxBNPoKKigj5DLpeLpKSkmKFiPT09+P3vf5+wMAbu7GgbGxtx7do1OJ1OWCyWDS+MgTsC2GAwYHFxEQqFAk6nE0NDQ2hqaoJerw9zsM3NzWFqaooe53a7qcb8zDPP4Pjx4zAYDHjzzTdx+vRphEIhyGQyeDweyOVyNDQ04OjRo6ivr4/qOF8LfD4fUqk04d1rQgKZrN4+nw/z8/PUXszj8ZCeng6DwUCdfVKpFEqlEhqNBjweD0ajEbOzs1HPHSnuVafT4dq1azhz5gwaGxvhcDjiuk+ZTAaNRgO1Wg2ZTEZtyWRwSEyix+OBzWaDxWJZVRuLds+RVsGlW8HVEAgEyM/Ph1arpbGdHo8HPB4Pubm5UCqVEIvFUKvVVPjPz8+jra0N09PTYfciFAqhUCho3HMwGASHw0FRURFKSkrg8XiQlZVFheBSQSAQCBAKhTA/P4/x8fE1OeQ8Hg+mp6eRlJQEiUQCh8NBXyqFQkFt4hqNhi5m09PTsNvtVBPR6XRhv2s17HZ7XFr/xYsXUVZWBqvVikuXLmFychLbt2+HSCTC8PAwhEIhysrKcOjQIczOzlLzAnBn3qekpISFWykUCpSVlcXMkGQYBsFgkMbICoVCOl9EIhFEIhEEAgH8fj8mJyepKUcgEECpVMLpdKK5uRnDw8Nxj8dyjEZjXCYiAMjIyEBmZib4fH5E3wuZ106nExMTE2t6Z+IxAfB4PIhEIlgsFvT392NgYABtbW00KGCpfVuv10cMFpiYmEBKSgpUKhUmJydx4cIFuotfCjF/Wa1WFBQUUKeqWCxGfn4+lEpl3L+NxCcvzeJLlIQEckpKCr74xS9iYGAAk5OTmJ+fp9vOwsJCqNVqLC4uQiaTIT8/HxUVFdi2bRsEAgFOnz6N3/72tzFf9OWG+f7+frz77rtobm6OWxgDQHFxMerr61FbW4vCwkIIBIIwzYAklxgMBrS3t6OlpQVtbW13bTvP5XLjDpPJyMjA888/j71794LD4cBut1NHgFQqpQ4gso3Nzs7Gnj170NraisbGRnoeoVCIlJQUbNmyBQcPHkR1dTUEAgE8Hg8UCgWUSiWCwSCsVis1cSwNllcoFAiFQmhubsYvfvGLiJN3NSwWCy5evIja2lqkpaVhYGAAo6OjKCoqQn19PX2+ubm5OHLkCGpra2ncskKhwOLiIt577z288sordy3BhdDb24uXXnoJXq+X7rJOnjyJvr4+VFVV4Yc//CFqa2uh1Wpx7tw5nDlzhn6XYZgV90PMC7HgcDgoLi7GV7/6VbjdbqSlpcHpdEImk4UJ96mpKbz66qv47LPPEAwGaWRFMBiEyWSiZQGWhh6ul+UObw6Hg6NHj+Lxxx+HSqWCx+NZcYxIJIJEIsHo6CheeeUVXLp0KaFrknFcLedALBYjJycHLpcLv//973Hq1KmoiTPRMJvNOHPmDPr6+rC4uBg1zHV2dhaNjY1obW2lSR8ejwelpaX41re+hYaGhriuR5x4PB5vXckxCQlklUqFQ4cO0eDz+fl5eL1epKSkoLS0FE6nEzabDUqlEps3b0ZVVRXq6uqoHS1WtozP58P4+DhmZ2fpNtdsNqO1tTXiSqxQKKDRaMDlcmnMIMMwyMrKwn333Yc9e/bg/vvvp3bFSPj9fqSlpUEqlUIgENCsMZJF5na7qcaaCAzDxKVhyuVy7N27F8eOHaOJEPHA5/NpVhYxPwiFQpqIcvjw4VUTWmLdU3d3N60XECmWNVr4ot1ux7lz52CxWJCXlweTyQSbzYasrCwEAgEqkIn2EckRY7PZ0NnZidu3b0MqlVL781Knk9VqTWiBBu5EqSyPTtDr9fj444+xc+dOfPGLX6SfL830IizXhN1uNxwOR0wTgNvtxvz8PPLy8iCTyTAzM4PW1lZIJBIkJSVBqVTC5/PhypUr+Pjjj9Hd3b3iHEKhEKmpqXTHEwqFoNFoIJfLVywU5J69Xi+1wRLlIxgMIhAIwOfzIRQKhQlasViMnTt34pFHHsGxY8dWHcstW7ZgeHiYOplVKhWEQiF9v6MJv6XaYzzI5XLMzc1haGgoruOXwjAMxsfHMT4+HvM4r9eLiYmJFffc39+PzZs3Iz8/HzKZDDabDSKRCDKZjO4glv8D1p8RmHA4QFpaGqqrq5GZmYnFxUUEg0Ea1hQIBODxeGjGUFpaGmQyGQwGw6pCzel04v3338fs7Cy+9rWvYefOnTGLxezduxfHjx+nWjl5MZRKJTIzM5GTk7NqKJRAIEB5eTnkcjm2bdsGs9lMtxmjo6Po7u6GXq9P2H63uLgY5hxSqVQrnJulpaV45plncPToUZSVlcV1Xo/Hg6GhIVy7dg2dnZ1htmCRSIS8vDyUlJSscDImQkFBAdXYyXmX88Mf/jDq/TU1NaGlpQV5eXk4cOAA9u/fj6Kiorh3DHV1dfje974Hk8lE5xUAWkTIYrHgd7/7XdjuYL0s9YHMz89jZGRkhaN0uRCZnp7GjRs3Yu4k9Ho9XnnlFTQ0NCAzMxM9PT1obW2F1+uFWCyGUCikMcfRNECfzwer1UpDvdLT0/Hggw9ix44dkEqltJgQMRUCdwTirVu3YDAYqPLkcDig1+uh0+loJioA5Ofn4+mnn8ajjz4ad5adWCzGsWPHsGnTJjgcDvD5fIjFYqrYLF3clpOIwBIIBEhNTYVGo4k7QeVuYbfb8fvf/x4jIyNU4JaXl6O2tpbKlUAgQLViYo5bb8hrwgKZhADFymBbitvtxvT0NA3XiobP50NPTw96enqQl5eHmpoautUmtmcy8dLT03H48GF8/etfT/T2V5CcnEyTMJYyMDCAjIwMjI2NJSyQxWIxUlJSsLi4iOLiYqjVaszMzGB2dhZ+vx9cLhf79+/HN77xjYRSgN1uN0ZGRtDZ2UlrCxBNPCUlBSUlJSgoKFhXTKZcLsfhw4djHvOzn/0s4ueBQIA+K5vNhmPHjmHnzp0JXT8rKwtPPfVUzGOcTifa29thMBjA4XAiLhrRIMlNRKMhtm673Q6Px4OzZ8+ira1txa5sualgfHwcn3zySVi88nLsdjvefvttzM3NIScnB319fbh582bCprGlYWgSiQTFxcXYu3cvNcctZ2JiAmq1GpOTk9i0aRO0Wi0WFhYwNjaG1tZW2Gw2qiClpKRgz5499DkttYPGorq6GtXV1QBA53Q8wiiRMDIS3XLw4EF0dnZieno6Yafk0pRn8rtIjZjVKiTevHkzLDmoqqoKFosF5eXlUKlU1KwkFoshl8vjHoNY3LNaFgSbzQa9Xg+r1Rp1G8/lcsOENSmSQ+xNGo0GR48eRXl5ObxeL5RKJfbs2XNP7zs/Px9+vx9lZWX40Y9+lNB3t2/fju9///uwWq1QKpXg8/mw2Wyw2WxwOByQyWTYvXt3mDCOJx1dKpXSaAmfzwefzwe9Xg+lUolt27ahuroamzdvXlPkRyLp8LEQCoWoqanBAw88kFCmWCIv6t69e+Hz+WA2m+MqSgXc0fQ5HA5GRkZw4cIFqpEGAgE0NzfTMq5DQ0MYGhpa1SRCIl0i1UNZis1mw40bN9Df3w+j0bhuP8XCwgLOnz8PLpeLJ554ImKqck5ODvbs2YOFhQUolUrqqJqdnYVAIIDZbKaOQp1Oh1OnTsFgMCA3NxdpaWlIT0+POociPSeyKKxWYnap03dpAaloSKVS1NfXQyaToaKiAt3d3auWPViKUChEWloaioqKsGXLFmRmZkIoFMJoNKK9vR03b95MSPPu6+sDcGeh3b17NwoLC6lzdrVomXi5pwKZxBMS04ZYLI5ouliuOSclJdFY59TUVOTl5eGFF17AgQMHANyx+9zrqlIk1GktTpSKigqUlZXR37XUxkT+GynmMZ57KisrQ3a+DAR+AAAgAElEQVR2NgQCARiGgcFggFqtRn19PSoqKtZsrrhbKa/p6ek4fvw4nn766YTCiBK5/rZt21BeXp7QIkK06MuXL4fVO/H7/WhqasLly5cB3HHOkJq3BGK31uv1NJookRCyaJEAa8Fms+HixYsYGRmhlf6Ww+VyUVlZSYUnMROUlpZibm4OLS0t0Ol0cLlcmJmZwS9/+UucPn0a+/fvx6FDh7Bz506oVKqI5oVoYz04OIjm5uaYwnJxcRF9fX2oqKiISyCLRCJqx62srKQZeWazedXkFZJdmZWVhd27d+Opp56ifpX5+Xm8++67cDqd6OnpiTtXwufzobOzEwKBACUlJaisrERubu6KsN/1cE8FMhmUnJwcVFZWYmZmBkNDQ7DZbCsEnVAoRGlpKRoaGtDQ0AA+n4+srCwcP34ccrkcW7dupccu3aKSsKJIE2W9hT7WaqC3WCwwGAxQKBSrCqW13KNcLkdVVRW4XC7sdjvkcjlyc3ORnp6+pvu9mzidTnR2diIzMxP79u2LWyjHGoflfyNhZGuhqKhoxQu02vbV4/Hgxo0b4HA4UCgUcLvdsNlsOHLkCNxuN954442Y11Sr1VCpVPR7RJCrVCoUFxcjEAhgYGAgIeexXq8Pq8a3nEhzlzj3dDrdijwBg8GATz/9FMAdhai4uHjFOSI9o6mpKfT29qKtrQ3t7e0x8wTsdjtaW1uRnp6O7OzsqMctX2hFIhFKS0uh1WohFouRlJSEiYkJhEIhai6QyWTg8Xg0e9hkMmFxcRFcLpeaWQlarRYPPvggZDIZJicnYbPZ4Ha7w6IkDAYDrly5EvH3DA4O4pNPPgGfz8fx48f/dwnkpKQkVFRUwGg0Ym5uDm63m6ZdL0WpVOKpp57C17/+dbqVz8/Px5e//GWaeROJWPauP1Whk+7ubjQ2NiI5ORlPP/10zMm31nvMz89Heno6NeuQqmp/ahYWFvDOO++gt7cXDMPg2Wefjet7n9ezstlsCSfGOJ1OWpOFxCQTH0ZlZWVMgSwUCrF9+3YUFhZibm4O/f391FyQlZWFQ4cOwe/3w+l0xl3nA7gjpEip0oqKiriVB5vNFtWsYLFYcOnSJVRXV0esBb78GYVCIdy6dQu//vWv0dXVBYvFEnNRcTgc6OjoWNWvEG0uJCcnY8+ePUhLS8PMzAwcDgcUCgWKi4uRnZ0NsVgMu92Orq4utLa24vbt27BYLFhcXITFYgmLGMrPz8emTZtosTS/308r60kkEnR1dcHj8eD06dMr7oMUN/N4PCgvL7+rpWATEsh2ux3Xr1+PmmoYDaVSCYFAALvdDofDEbHghkAgwObNm8N+HLHPEAKBAPr6+mCxWGjeP5mI8/Pz6O3tBZfLxdatWxMK6AbuTMbZ2VlYLBa4XC6qea+FqakpXL9+nW4Xq6uraTGX0tLSmAI6XtZbjPxec/v2bXz66adITk6GRqOB0+mkVQLJApKUlITCwsJVt6/kBe3r68P09DRycnLijkwxGAzo7++nYXcdHR1rMh+Q7FOlUom6ujpUV1ejpqYm5hyRy+V45JFHUF9fj5ycHGqnzcrKgk6no6m9AoEADQ0N4PF4GBsbiytkMhQKob+/Hx999BF6enqgVqsB3Nkxbtq0CZWVlRHnR05ODg4dOoSpqSnIZDJIpVLweDwYDAa0tLTAYDDQ0M9gMIjr169DKBRi27ZtK3YlXC4XVqsV/f39q4aXkXuzWCxYWFhAMBgMc4C5XC4IBIIVpsi5uTkYDAaqxNntdmo+slqtyMvLQ3Z2Ng1vValUkEqlkMlkyMzMhNlshlQqxe3bt6HT6WgbJlJSk0SIpKamhkVl7dixA1/4whdgt9vR3t4e0acwMjKC7u5ulJeX35XiVkCCAlmv1+PNN9/EQw89hPvvv59OgniYmJhAS0tLTBvTapWR5ufn8c4776CzsxPPPvssnnnmGfq37u5u/OQnP4FYLMY//MM/oK6uLu57A+4IkLNnz6K3txdzc3O0jGaiXlODwQC9Xo+ZmRlMT09jamoKarWaFl76xje+ga9+9av0+PWaVTYyFy5cwODgIPh8Po2DBf6YiVZdXY0vf/nLqKqqWvVcfr8f7733Hj7++GM8+uij+Pu///u4eujdunULL7/8MsbHxyGVSuHxeKDT6db8m/bv34+/+Zu/QX19/aoLdlZWFv7xH/8RGo0GEokEbrcbdXV1VEsmEQBqtRrHjh1DaWkpfvvb36Krq2vV+3C73WhtbcXo6CgNNyN21QceeADf+973IsZ5NzQ0IC8vD263m4YSisVidHZ24j/+4z/Q0dFBBfm1a9fw7//+78jIyMA///M/R7RX8/n8uOcvSSe2WCyYmpqi9+dyuTA5OQm5XB6mrNjtdrS0tKC5uRmjo6MwmUxUAyea765du7B169awfAONRoPq6mpUVVXB7/fTHWtvby/8fj8tWEVitJOSkrB3715amQ+4s9g8/fTTKCoqws9+9rOI5U4ZhkFnZyfS0tJQX1+fUIGjqGOUyMGk/KbJZILBYKAl+4jzjqx6JIuJNFocHh5GT09PTGHs8XjQ3t6OyspKbN68eYX27ff70dbWhkuXLlE7VFlZGQoKCjA/P4+LFy/i3LlzEIvF2L59O01FjuXVFggEEIlE0Ol0uHDhAs6fP4+enp6E6nCQOFGj0UiLIPX29mJhYYHGmBKGhoZQWFiIyspKbNu27a40XtzIrObMMpvNtKGpRCJZ0fgWAI1v7e3txfnz53Hr1i1IpVJUVVWhuLgYfr+fxuiKRCKkpKRAoVAgGAxiZGQEH330EbWNroXs7Gyo1Wo4nU5otVo89NBDNEYbiF1RUCaTYdu2bWGfkd1lXl4eLBYLQqEQtFotcnJyUFBQAIvFQpOSSCnXUCiEhYWFsLofoVAIZrMZZrN5xXVDoRC2bNmCI0eO0Fhn0lUmLS0tYrKUVqvFqVOnaG2Q9vZ2WuY2OzsbO3fuhEAgoAV85HI5LBYLhoeH47Z9y2Qy5OTk0KJYVqsVYrEYk5OTGB8fh1wuR2FhIZKSkuD3+zE6OooLFy7g0qVLGBoairhzmJmZWVEPhfiuCCqVCv39/XQeLI/qUqlUEIvF2L9/f9j3ZDIZ9u7di6mpKUxOTmJwcJBm5JF3d2ZmBn19fcjLy/v8BXJKSgqOHj0KkUhES2pqtVqYzWZMTU3RpBC5XA6VSkVz9Ds6OmLGawJ3bFvvvvsuRkdH8dxzz+HRRx+lfyPxoadPn8bExAQCgQAuXLhAs4Q8Hg/NsvN6vXjnnXfQ2toKDocT015INGBSsW56ejrhokgmkwlnz57FZ599BoPBAKfTienp6ahhU83NzeDxeHjsscfw0EMPJXSt1fjfpm2Pjo7irbfewpUrV8Dn8+H3+1cIOGLeWFhYoFXVbt++jZ/+9Kc0nIvUzMjKysKxY8eQn5+PlpYWnDlzZkUpzURQqVR46qmncOjQIQB3lILy8vK1/+D/gSRMkY4UpA2XRqPBM888g4aGhrBttcfjwcWLF/Hmm2/GVT9ifHwcv/jFL3D9+nWUlZWhrKwMlZWVMc14RHsNhUL46KOPoNfrqU1br9fjtddew/nz52l9Dj6fT7PcIi0KkVAqlaisrITL5UJraysuXrwIq9UKk8kEq9VKW7EJhUIwDAObzYaZmZmIPTiBO4tlfn4+7HY7RkZGonYrMZlMYXbz5VFdNpsNTqczqgnwyJEj0Gq1uHLlCq5fv46RkRFqgnO5XHA4HHetYFdCAlmj0WDXrl0YHBykRnWlUgmj0Yjp6WnYbDZaTSkpKQlutxs9PT3o7u5etTZCKBSihe6Tk5NRXl6OoqIi+Hw+3LhxAx999BGamprohCTHRqKzsxOdnZ2J/LQ1Y7FY0NHRgY8//jhi6cbljI2NwWq1QiAQICMjA+Xl5fD5fDFLaJKiLqTzRDTbPUktXlxchNvtvmcCei2FhyLhcDjQ3t6O9vb2hL5HYnGX43K5YDQaodFoMDo6is7OzoRSrIVCIZRKJa1jW1tbi0cffTRMI15OrPH1+/0wmUwQi8W0XT25TqS+cCKRCDU1NREz5uRyOYaGhvDpp5+uGorp9/tpjPTjjz+OgoKCVf09JpOJCqq5ubkwZ5bf74/aSy8RSOalwWCgrapmZmbW1O1GrVYjMzMTUqmUZtPNz88jPz+fmqbcbjd0Oh06OztXDW0zGo3o7++PGKmUmpqKhx56CHK5HOPj4xgbG6Np7IFAYEUq+npIOMqCrJBms5n+UGKiMBqNGBsbowWGQqEQDAZD3Csoobm5GaFQCCkpKfB6vZienkZ3dzdmZmbuaXeMtRAKhajpJl4WFhZw6dIlOJ1OpKSkhNlXl0I+I+ngxcXF2LJlS0ynoMViwZkzZ3Dt2jV4PB5IpdK70nF3KRupBCoAlJSU4L777sOuXbuwbds2KJVKyOXy/6+9Kwtu6zyvB/sOglhIguC+gasoihSpzRYl1bZsS4riJU6dROPEbrpM0y0vnelD+9hpZ5q6zrRpPGMlTRO5cu3YsmtJlKzFoWTJoiiJorjvBAmSIECQALEvfVC/PyCIlYusZnheElNYL+797rec7xwUFxfj8uXLaG9vT+m8MRqNeOmll5Cbmwu32w29Xo+ampqYj03lZjc1NYV/+qd/wvbt21FfX4/i4uI10/V27tyJv/iLv0BFRQVOnz4dsxUUSwyIRPzJeSYWaJt2M7WygYdsFcowSWx+rZnl4uIiq2gHBgZw8+ZNZGdnswUNYk4sLS1hbGws6SD3zp07+NGPfoT+/n689NJLcfn809PTLBHk8XisqvtKAnIgEIDT6WTi2qOjoxgcHEROTg6Ki4vh9XoxNTWVcFsnFfT396O/v3/Nz4/szUYfrHR89VIBifpUVlbC7/enHKz6+vqSbnkRMjMz0djYiAMHDsBgMCQMyHa7HW1tbfjlL3+Z0mtvNKKDAv0tWgJ1I6BSqVBWVobDhw/jO9/5DioqKti/VVZW4qmnnoJCoWAUpmTYu3cv3njjjZRoTKlUHlarFT/5yU9w+PBheL1ecLlclJWVrekGqVQq8cwzz8BgMGBycpJ5NUb2Q6OPbVZWFgoKClgwJiUzMuH1+/1YXl7G/Pw87t27l1KFtx4sLy/jzp07mJiYWHeMCIfDzNx3IzA3N4ePP/4YZrMZhYWFjPYXeePt7e3F8PAwew5l4XQ8NwJpZ8jkNUUXA2kiZ2VlQaPRICMjA0tLS6w8EYlEcLlcuH//ftoSemuBTCbDM888g9raWnbTuHr1KsxmM/R6PVpbW2G323HlypUNMQZVqVQoKipCaWkpJicnNyV79Hg8rA2UjGtMov5fBXJzc/H888+jvb0d/f39kEqlyM/PZ2urg4ODaGtrW3e/LS8vD3v27GHUx23btqG0tDTmY2UyWcIASDTJAwcO4NixY3GD8VrbP3a7HV988QXTEG9paUFNTU3KjtDEMyeUl5fjlVdeQXFxMWtD3Lx5k71H9Hu3tbXBZrOx9X2/388U3wKBAKOSmc3mpI7g64VIJEJOTs66thaJnkYZ8kajr68Pp06dYiwYErz3eDy4fv36ihuJx+PB2NgYsrKyNqy6WJO4EG2g6XQ6xisVCASr2BU0lDCbzXj33XcfSUAuLS3FiRMncPToUXg8HrS3t2NxcRFmsxn19fV47bXXWNkRz3onHWRkZKCkpAS1tbUYGhpCb2/vBnyLldBqtcjOzoZWq03aGuHz+TH7k48Cer0ef/InfwLgYTakVqvR3NyMo0ePorGxEZ999hn6+vrSWoCIhebmZnz3u99lfPNEbRmXy5VQ1EooFOLw4cP4y7/8y4Rc0vX04sfHx7GwsACr1cqYFXv27EkpU45+jEgkwrFjx3DkyBHIZDLYbDa89dZb6OzsXBWQLRYLTp8+jY8++ggAVmXS9L/UD92o2UA8iMViFBYWptRCiAeDwYCmpibMz89jeXl53Zl2NJxOJz744AN88sknTN40UtY0utIiwa+Nqi7SCsjEmSQOH/VPaUtMJpNBIpEgFAoxE0KNRgODwYDR0VH09fXh/v37KYuPFxUVYdu2bdBoNIxuEg3iEi4vL7NBTFNTE7hcLqRSKRoaGnDs2DFoNBrs3bsXO3bsQEFBAb7xjW/gzp07zFtLKBTC7XanJBhDoBI8NzcXDQ0NmJubw+LiInp6elbs2hP1KNb3pmqDx+MxtkA0HA4Henp6GOE/+jNEBgulUokDBw4AeHgCSaXSFTKPt2/f3tQ+/Pbt2/Hss88yAZnq6mo0NTUhJycHLS0t+OY3v4muri7weDyW7dMqNCn+xRvIFhcXY9++fXj++efR1NSUkm6Hx+NJqHtA1UdkMN6MYejS0hK6urqYdvfMzAxKSkqgUqnA4XCwvLzM3E/4fD6qqqpW2F/RuUPmmwS1Ws0ontEIh8NsM/ZxgNvtxuDg4LqkNFUqFfbu3QuRSITS0lKMj4+zoTf5K3Z1da0r+UvXgs7n82F6ehoDAwPM6YQ0r2OttSdC2hZOGo0GfD4fIpGIuQpkZGRAo9EwVwuSMwyFQsyuvbGxEdPT0+BwOCkzILZt24Y///M/R319PRPdjkakcHk4HIZcLl9xcWk0Grz44ousn0j6sK+//jqWl5eZ9RGxRX784x+nHJBJ/5laCR6PBz6fDxwOh0l2ZmRkMI5trMAglUphMBggEokwPj4e80Sw2+1ob29HMBhEc3MzKisr434mtVqNF154Ab/3e7/HAguVXOfPn4fFYlmT4Hc6OHToEJqamsDj8SCVStmuf2FhIf7wD/+Q/Y48Ho9VWCqVCg6HAydPnsTg4OCq4yAQCPDyyy/jj/7oj1BUVLShAdPr9a4IwptFHVxYWEBnZycmJiZw69YtbNu2DbW1tZBIJJiZmcHY2BjGx8chlUrxzW9+E1//+tfZcxN9po10EtlMOJ1OlqzQUgyfz2ctlFRAsaSmpgYHDx5k9l/0epOTk3jnnXceSTVOkEgkGB8fx6VLl9icLTc3F5WVlWmLfaXdsiA3Bcoow+EwlErlCqdckUjExLMpgy4tLcX+/fshFouh1+tht9shEolgt9tjXoDAw/5fXV1dwglxMnC5XOh0Ouh0uhWfLzL7IGRmZuL48eOYn59He3t7Sgac1KYh0j0R/OmGRD3J7u5uFpDJXSHSpdnr9SY9KR88eIDz589Do9GgtrYWUqk0phRi9Boo4cknn8TAwACUSiVCoRDj8VJf0ePxMNlT6i2SxRKXy4Ver0d+fj6TIYyG1+tlimixOK80AI0HtVqN1tZW9PX1obe3l51rLpcLpaWleOqpp9Im35eUlODgwYO4desWk3UFfnteNDQ0MG+8zVYQBMBuzDMzM7BarZiZmYFEIsHc3BzjwlO1KZPJmK1U9DA68ndPVcIAADNvkMlkrFWx0bh69WrMv0skEuzcuZNJCojFYgQCAQwPD2N4eJjtNVC1xOfzoVAoIJfL4XA4IJVKsWvXLnZDjnWe5+fns5bI9PQ0qxCB3+4duN1uTExMwGQyrftGxuVy4fF40NfXx1bORSIREz5K19lmTeJCYrEYIpGIbURFn8gCgQBarRahUIgdDJ1Oh5aWFpSVleG5555jgfrWrVt46623YtrXeDyeR05zO3ToEEpLS/Gzn/0M//zP/5yQv0gnDMHr9YLD4aCoqAharRZyuZwNMaamplifiex7eDweAoEAc9hNVlouLS3hF7/4Bfr7+/H9739/RQaVCkpKSvDGG2/g+PHjLKsgo1da+aYAbLFY0NPTg5GREaYD0dzcjG9/+9v427/927ifr6OjA42NjdDr9Wl9NkJ9fT1++MMfwuFwsJtWMBiEXC6PS/xPhObmZqYc+NFHH7HepUajwbe+9S288sorMBqNjyQYR8Lj8bDeI6mU0TnA4XDw/vvvo6enB6+99hq+//3vr2hJRLdU0llf3r17N06cOMHWpzfDhTqeVnlOTg7++q//mgVGmUyG5eVlfPLJJ/jkk08gEomwc+dO5hAiFApRW1vLBrbUHoxM/qLB5XJx8OBBlJaWsvVwOna0ETo1NYVf/vKXeO+999Y9YA6FQlhYWMDw8DCcTieKi4tRUlICAGx7Nx2sS+0tlhgIENtBmkw4IzNV4OHAqqurC1arFX6/n9kdkZV3tPst3dXJBWAzkJmZibKyMrS0tODOnTtxG/aR9DrKsMiQVCqVMtbJ5OQkZmZm4Pf7V3ii8fl8WK3WtMjxNpuNrbOWlpbCYDDA4XCwslUqlSIrKyvm8E8qlcb07vN6vbh//z46OzsxNzfHeuPR/a/c3Fy0tLTE5dLS7CDRkks8UJDJzMxMqkOSTo9XLpczF+7ITFImk2Hv3r1obm5O+7NuFOL1d8PhMNNxkEqlKCwsxJNPPskc1COzZTKSTZV2VVRUhKeffnrNfOj1QC6XxzQNXV5eXpEBZ2RkYHp6GgKBADt37oxJ80x0DuTm5iakLtbV1TE51bWC4p7f70cgEACPx2Nkh7KyMqhUqjUtjKwpIDudTrhcrlXlwlqGITk5OXj11Vexc+dOhEIhiEQieL1e8Hg8ttdOIKFwn88HuVyetqJbKqD9fZFIhG9961v4q7/6Kxw+fDjmY8kKhpglBoMBMpkM4XCYDTqFQiFycnKQnZ2N1tZW3Lt3DwMDA+w7Uh81XVy+fBkLCwtQKBTw+XzMV7CqqgonTpxYpaGQCKTs1dfXh7GxMYjFYrjdbnasgYcZnd1uT0jrk8lkqK6uXpNjyWahr68P7733Hq5evQqr1cr+nooz+Ea5qKwH9Du/+uqreOONN1Yc2w8//BCnTp3CrVu3Ur4JJhPw+ipA7TehUAi9Xs90iWNV3xsBYk+s51jk5uaCx+Mx78eGhga0traitrYW+fn5kEqla2oJpRWQQ6EQpqamMDIygsXFReTm5qK4uJiV32s5cXk8Hnbt2pWS91ooFGLCKxut/RsOhzE4OIhTp07hF7/4BXbv3o3nnnsOra2tcZ/j9/sxPz/PBneZmZkxg5FSqUROTg6am5vx+eef49y5czCbzWxQqVKp0qYBDQ0NxaSP3b17F6WlpSgvL4dUKmVDD5pC03cFfqsTATw07bx79y4GBwchl8vB4/FY1UKw2+0wmUxxyzyZTAaj0bimyiWdcyfRYyM94fx+P+7evYtz586tGtT6fD6MjIwwgXda+6f5SKz+fDR8Pl/Ci5qypvXAbrejq6sLhYWFaGlpYe2A/v5+fPjhhzFVyBIhFAphaWlpVaX6VYJ8LQkulwtut5tVfdFSncD6bpJOpxNerzflqoJW3+nx+fn5qKmpgUgkgslkglAoxMGDB3H48GEUFRWl5IYSD2kFZLPZjH/8x3+E1Wpl+qX5+fk4fPgwDh06lPC5sbLndDPqSLnA9XzpaIRCIVy+fBlnzpxhA4nh4WGcOnUqISOEhgNGozHl1emdO3eCz+djeHgY4+PjEIvFjKI3NzeX1JomGcxmM95//31MTk6Cw+EgEAhAr9ejuLgYGRkZLKsnyiIpfw0NDWF6ehpTU1MsW4kupwUCAWu1xAItDX1VCAQCWFhYYAsQFosFJpMJIpFolX3Y4uIi/ud//of5zJEwFQnKHzlyJCFlaXl5Gd3d3QmXcHJycvBnf/ZnLEuKtFNKFdQD9Xg8OHfuHM6ePct84a5fv57Wa5FW8Eav0q8V8a5/iUSCrKwshMPhtCR+U4VcLk9ZS1yn02Hv3r3M5Zs8PUkP3m63g8/no6KiAoWFheuOS2nrIb/55pur/h4IBFBfX5+Q4hHrwKd7l+PxeClvOKUDm82GtrY2/OxnP2MbN3Nzc/jpT3+a8DO6XC709PRAqVSm/Ln4fD5KS0sRCoXgcDiY3CKJAq03IAPApUuXcOnSJfbfVVVVaGlpQVZW1iqBbmKwdHV1wWKxIBwOx+VhCoVC5q77OCIQCMBut2NkZATj4+OYmJjA2NgYu4BmZmbYEMvhcODcuXM4d+7cqtd5+eWXUVFRkVCneWBggMlCxkNOTg5++MMfMkomDbPSWd+nY3327Fn83d/93QoX5HRASxlarXbTZi/pIpHTT/T15PP54Pf7GeV2PXA4HGwAn+g3yMzMRG1tLfOIpPeN9ZyNamttiIXT559/Do1Gg7y8PDYt9vv9bFU50s9qo0Dbd6Ojo8wXi8vlwmAwYNu2bSgqKoJAIIDL5YLZbIbFYoFAIIBarYZWq4VarQaXy2VGh9PT0zEnzol+MIfDgba2NszMzKChoQG1tbVMmGZqagp2u53R2UhHwG63Y3Z2FmNjYxgdHYXNZmMUs82YeANglCKiuSkUChQXF0OtVmN2dhYmkwnDw8NpU3QeN5CMJfAw479+/Trm5+fh9/uZXncq6OjowH/8x3+gs7MToVCIVQqU0bndbgwPD+P+/ftJ19QTDZ9TuYh9Ph/a29tx5syZuFugiQKLWq1GQUEBMjMz2Yp/sqyT+PQkmpXK56RNv42k0S0uLqKjowPd3d1wuVzsWAoEAvZeRUVFOHToEJs1OZ3OmFnq9PQ0ZmZmYLPZ0NfXh3v37sU8ZllZWWhpaUFVVRXkcjmys7NXDbI3c6awIQGZxOfJCXl5eRkulwvbt29notQbiUAggMnJSdy4cQOfffYZrl+/jomJCQgEAjQ2NuL3f//3ceDAAWRnZ8PpdLINQalUioqKCrZxSOyCjo4OOBwO5iicKtXO4/Hg7t27jPNIJpgWiwU3b97E6Ogo00r1+XzMN210dBR2u50FCPqBN2t11efzsUl8OBxGTk4OsrKyoFarMTo6ihs3bqS0i+92u2GxWDZ9xXa98Pl8GB8fZ1uJ1FNONVhMTk7i5MmTTJeXtuP4fD48Hg/LsNJZaFgrzpw5g3/4h3/ArVu34j4mXjAm6yUybNBqtUmvRdokdDqdkEgkEIlEKWXUNFjeKF1g4GFF/v777+PUqVNwOp1MsJ/D4cDhcCAQCKC1tRV6vR779u3D8sCSK6AAACAASURBVPIyhoaGkJ2dvYJ2SX34zs5ODA0NYWRkJG5lYzAY8J3vfAdHjx4Fn8+Hy+VKS8lxvdiQgOzz+WLulN+9exeffvopG5JElgp5eXmorq5eU4+IerAXLlzA559/zgZifr8fHR0dUCqV8Pv9aG1tZbxFgUAAiUQChUIBhUIBPp+PhYUFDAwM4O7du5icnEw7Q5VIJDAajWwxhvzFRkZGcO3aNQwNDWFpaYlduE6nk7nlcrlclJeXIxwOM3H/zURkELXZbJiamkIwGExLdnFwcBDnz5+Pqx9AbhJCoTDlZQXqZ6dCY6RKQqlUQiQSYWpqCj09PbDb7Wwqv7CwgP7+fgwMDLBjmq7KHLU+IqHValFWVsbojYFAgN1Ik2l9rxUOh4Nlc8nA5XJRUFAAo9EImUyGQCCAzMxM1NfXo7q6Glqtli0s3L59G0KhEBkZGWzFnUBJhUgkApfLTbk95fV6YbVak7bc0pkbkXoi/RaxVq47Ojrw8ccfw2azwWKxYHJyEmq1Gnq9ns1MxsbG0NHRgfn5eeh0OlRWVmJ5eTkmY0gkEkGv1zPSQCST61EYQGyq63Q4HMann36Kjo4OZkG+tLQELpeLQ4cO4Y033kBLS0var0tmp1euXMHc3Nyqf2tra4PD4UBxcTE7IYPBIFQqFUpLS9kgiwSsR0ZGYDKZVtC8UoFarcYrr7wCiUQCLpcLn8+Hzs5OdHV14ebNm5icnITb7WaZcCQNhjQfHA4Hzp49y5yIHwUCgQAmJiZgtVrTEmcZGhrCwsJCXC0CCmQqlSqlgEysGVo8SRaQTSYTxsfHUVhYiKysLHz55Zd4++238eDBA4hEIqbZ4XK5Nlx0Zu/evXj++echFAoxOzsLi8XCrOY3IyDT0JD4uMnOS+Lsfu9730NVVRVrldGmm0wmg9vtxrVr13Dt2jWEw2FUVlairq4OtbW1K449j8dLOyv0eDyw2WwJjzvRzVLtYZNZaSLY7XacOnUKZ8+eZdumNCRXKpVQKpUrPPxefPFF1NXV4eTJk7h9+/aqGzUNhmPhUdAfNzUgA/F91S5duoTCwkK43W7I5XJ2cRLFRSAQxFwLFovFGBsbw61bt1YE4+g+2t27dxlHMD8/H4FAYJWIDFGcRCIRAoFA2uWWXC5HS0sL+Hw+nE4nBgcHMTs7i9HRUUxOTiYU5qdJbzKbqXggrVui40SuBNPml9lsjqkXGwqFWHYQWXKTVKXf74dAIEBmZiajbbnd7hVDyFiIXNxJBdRKSOQt6Ha72TGlAFVQUACdTodLly7h8uXLSasLsVgMnU6H7Oxs+Hw+1kpKBJVKxUSnKioq8Nxzz+HQoUNM86SzsxPXrl1blRCsB+FwmK1V9/f34/bt2ynrgnu9XqhUKuzcuTOm1IDFYkF3dzcuX76Mzz//HOFwGCaTCWazGZOTk8jPz0dGRgazNCONFr1enxJzhuQ8k1HJgsEggsEg055IlIGnuoE4OTkZU4pTLBZj165d0Ol0EAgE2LZtG3bv3o3S0tK4iyNerxcLCwusEouWP91sbHpAjoepqSm8++67uHTpEus90wVNP1Z0kKUSyuVyreoBRd/pouUE9Xr9qjuzRCJBUVERKisrWcM/HfD5fGRmZrL3Ir4il8td4bDM4/FWBA2ZTAaLxYL29nZYrdY16bo++eSTOHHiBHJyctgQld5PKpViZmYG7733Ht59992YF0l00BSLxSgoKGDuxSqVCs3NzTAajQgGg2wQOTw8jO7u7pifiTKrVNsVdEOkxZpYGBgYwHvvvYcrV66wG5xUKoVYLMbMzExKwViv1+Pw4cM4fPgw5ufn8dOf/pSJP8WCSCRCfX09GhsbUVdXh7KyMhQXF7OyPyMjA11dXbh//z6++OKLlL5rKnC73bh//z5u3LiBW7duobu7GyaTKeWlj8XFxZjHw+/349y5c/jVr36F7u5uLC4ugsPhYHp6Gh0dHZDL5TAYDGhoaIBer8fg4CBMJhP27duHl19+OSUtGYFAwFoliRCZ+ND1QqAYEMmXX09Pury8HCdOnGA+fhkZGSgtLWWMpligAbDD4WA3BLFY/MiWg9IKyLR1lioo86FSNrK/5PV68eDBgw3RJI71OVtaWlbcBWMtkohEImRnZzNn4XRBspHkBqFQKKDX62EwGJCTk8NKp3A4jPn5efh8PhgMBhQVFbGNPho0En82lV5yZWUlDh8+jKNHjyZ8XE9PD8v+dTodeDweFhYW4PV6IZFIWKuFz+dDpVJBo9GwzDg/Px9NTU2oqamB2+3G6Ogok3OMl7XRIkSqHE96TqxgHAwGMTExgS+++AJnzpxZs1mpVqtFXV0d9u/fj6NHjzLvtNnZWbhcLojF4hXsCS6XC6PRiNbWVuzfvx/Nzc2rymZKIKanpxNWAxRQUj0e9HiabcS78QG/pYYplUosLi5CLBYjOzs7ZkAkp45oil/07MBqtaKiooJ5Zubl5aW8PCESiZCZmZmQkkYtC1opTlZJCQQCFBQUICcnhwVUom3SshMdM2p90Tmq1Wrx1FNP4ciRI6uWYIh0EAukPud0OiEWi1lQpqThseoh6/X6uMIyMV/8/5xsLRYL3n///ZjGlOtFdBat0+nw0ksv4bnnnotpFhn9XJIAXMuBpkUICsgajQZGoxEulwter5cN6+x2O6xWK6RSKXbs2IFnn30WOTk5rD0TCoUwMDCAjz76KKGRpEqlwoEDB3DkyJGUHKspW66ursaLL74Ih8OBM2fOYHJyEnV1ddixYweys7PB5XIxPDyMnp4eeDwelJSUoKKigg0qFxYWMD09DbPZzDQ5YoFuUNFYyzBkfn4ebW1tOHPmzJr76wKBABUVFWhtbWWZvlwux7Fjx1BdXc00CACwxAF4KDxUWFiIwsLCuD1MsViMzMxMjI6Oxn1/WhwyGAwp9WRJ3Y3P52NsbCyh+atCocCRI0dw6NAh1qIqLy+Pa06QyvGfmZmBQqGARCJhoj6pLjpIJBJotdqkDJzIjDO6FRL9GTMyMvC1r30NlZWVjDu/tLTEbkBqtZoxaiYmJlgFVVRUhIaGBrS0tMTcSIzXKqFt23A4DJfLBb/fzyryQCAAiUSS1IFmvUgrIGu1Wnz3u99N+02oUd7R0cHsvtPJooDf9iej79jRrQqj0YhXXnkloVNw5OciCcR0BKkjQScRtS/kcjkreSQSCSwWCzgcDpaWlqBQKNDQ0MBWLCMxPj6O3t7ehAFZLpejvr4eu3fvZkMayhLoOFBf2mq1YnFxkbl2HD9+HHa7HVNTU8jIyMCBAwfwzDPPMCWtCxcuwGq1IhAIoLKykimg0aCGlMh8Pl9cxoLf74fVamVqgJRR0DGKzm4AsN+UXpMqmeHhYdy5c2dN7iI04NPr9TAajSgvL4dQKMTExASkUikaGxvxxBNPpP26kVAqlaiurmaVXiy4XC709vaCy+UyBbBkUCgU2LFjB0pKSlj1FQsSiQT79u3Da6+9lvQ1+Xw+CgsLsWPHDkxOTrIs0uVyseMuEAiYv55Op0NhYSE0Gg18Pl/SwRq9R7LgHXmOJtr2JMhkMuzbtw/79u1jf3M4HLBYLJDJZGwm0N3djZ6eHradumvXLuzfvz/uTchkMmFxcXHFeaxSqVBRUYGamhomd0qblV6vl1VP6QrOp4tH0kPm8/k4dOgQwuEw7HY7KwWSge5Ey8vLrIfZ29sbc0goFotRVFSE5ubmVVxLytCiMzUOh4Oenh5cvXo1YaaTDGKxmAUfWkkWiUSQSCSMNkMUo+Li4pgnuFQqTVrCOZ1O3Lp1C36/n7Ui5HI5axNErug6HA6YzWbmSjE7OwuhUIgDBw5gz549qKqqQlVVFdPeaG5uhkAgQDAYRFFRETIzM9mNJScnB0X/JymqVCoxNjYW8/PNzMzgrbfegsFgQElJCcrLy5GXl8d+x/HxcXR3d0Mmk2HXrl2QSqW4d+8evvzySzgcDnYBcDgPHTQoUxMKhRgbG0t60xSJRGhqakJ1dTWjOtLnXV5ehk6nQ1ZWFnMrWU+mYzAYcPDgQZSXl8etGp1OJ65duwa73Y7FxcUVhqPx4PP52DmeiKpHov6pQCwWY/fu3ZBIJPB6vfD7/ejs7MTFixdXUEYXFhaYHKzNZmNmD7W1tRuywpzKII8Qr6pSKBSQSqWsshEKhSgvL4dCoUBFRQU4HA6Ki4tjPtfhcODOnTu4cuXKKiphcXExjh8/jl27djHKnEwmY60KuqYfq5bFetDY2Ij6+vq0FLQoizaZTLh16xauXLnCyuZoEDl8586dq8pmeq/o95yensbNmzcTloaJEJnVUTYTCARYK4JEerKysiCVSpGdnY28vDzmVhtZxi4tLSXlytrtdpw/fx4XL15EMBhkbZKcnBymLkULCzweD1qtFvn5+fB6vfjyyy9RUlKCpqYm5OXlQSaTrejd0uCKLhq/3w+73Q632w2lUgmBQAC9Xg+5XI7z58/H/Hxzc3P4t3/7N7S0tODAgQPIzMxcYQQwNzeHL7/8EgqFAmVlZdBqtbh9+zbee+89pn9LehJVVVVobm5GVVUVtFotBAIBRkZGEnKmtVotDh48iCNHjkCpVLKtrMHBQVaZUc/Y5XIxqdS1IDs7G7t27UJtbW3cgEwLOXRMSZI1HtxuN27fvo0rV66gp6cnYf+WdHhTAZ/PR2NjI7Zv387aBJ988glmZ2dht9vZ3CJyZX50dJTR5oLBIIxGI1QqFWNCEQMlHA7D7/enpGPi9/ths9mgUqmSZpqJ4kP0zEGhULCZTKx/J9jtdly8eBGnT59eZehKTtO0Lh99Q3gUHGTgEQRk+iLr0S/OysrCzMwMent7V0goRkOv1yMvLy/pj022521tbbhz586aPhOwUiyGynChUAi1Wo2ioiKmiUoDD1rZJj2IyB9ZLBbDaDSisrIyoYVUNLXIbDZjYWEBIpGIDTgoqFFZRhKh+fn5cWVLo5cAaHFAKpWyUpSoY4kuvKWlJWi1WpSXlyM7O3vFSWwwGLBnzx54PB6Mj49jcHAQNpsN+fn5KCwsZMeLy+WirKwM27dvh1QqZUsZMzMz7DuFw2FYrVZ2gybeeUVFBerq6iCRSLCwsMCm/3w+HwaDAWq1mlUv69F0IHphokpPLBajtLSUOagka9OZzWbcvHkTn332GQYGBhJWTNQquX79OrZt27aiXUBBk85JUvqL/H33798Pn8+HoqIiXLhwIWbVMzQ0hIsXL8JiscBoNEKr1TJmDLnM0/cn+mii42Gz2XDp0iUcPHhwxTW6EcEulazb6/VicnIy5lBaJBKt6L9Hf57HkmWxFmzEFxkcHMTFixcTDgVlMhnUajVUKlXSE//Bgwd488030dbWtm79iOi7qEgkgk6ng0wmYxt6YrEYKpWKbQgCYKU5QaFQYOfOnbDb7RAIBGmxCmI5q3i9XqbxQVNn0tNIdfJPvdjI75dsAJqfn489e/bgqaeeWlWp5OXlIS8vj13oAwMDkMvl2Lt3L4qKilBQUMDUyMRiMfv/JSUleOKJJ1i/mcvlMrbH7du30dvbi4WFBRQXFyM/P59VHiqVCrW1tSgvL2cZHJXMlCSsFW63G3NzcwmzVDKcJc/JeDrRoVCI8YSvXbuGL774Iul56Xa7cePGDcaB37t3L6RSKaxWK9uI5XK5zAoqsm8bDAahUCjwwgsvQKPRYGhoKGZAtlgsuH79OoaGhmAwGKDT6Zh5Z2lpKUs6aNiVjPI4NzeHDz74AAUFBQkF5DcLZE0WC0R3+6rxlfGQCeFwGA8ePIDJZGKZHIHu+u3t7XHXR5VKJerq6vDkk0+itraWlbeJ4PP50N/fv2FiPn6/nzkHBINBllVS4KKFlkSgDDkUCkEqlaKgoABerxcCgQAzMzPo6elZ0+elQd7CwgLzQEyndxqpTBZJLYoHqVSK/Pz8mGyLYDCIoaEh3Lhxg+mPZGVlMc/F3NzcmPrB8ahUKpUKcrkchYWFLDOPdJfgcDiM3rfRiNTmjgepVIqamhpmVhDvHJicnMT169dx6dIldHR0pPQ7UzuEFi3m5uYgFotht9uZpgRpcEgkEnZNkG0TuWoMDQ0lDEQejwcTExOw2WxMaEin08HpdLIbGrVjgMQJWCAQwK1bt/Dhhx+Cy+Vi+/btK64Tgt1ux8DAAGMmkQ5HMlpdMiRiSFAluVFYa9b/lQdkq9WK//7v/8bHH38Mt9u9oqdHwZloV7Gwd+9e/OAHP0BjYyPT8Y2+S0cfHDJh3QiQfoPL5WJroZEXQao/jEAgQG5uLjIyMlBRUYHjx4+zz/jZZ5/hRz/60ZqddEkQx+fzQSAQpGWKGfka1J9OFJBJajIWurq68NZbb6G9vZ2tuNJWYzAYREZGBiorK1Pu65JWQ3l5OdOY2Az93FiIlNOMBzKcpYw8VjBwuVzo6+vDBx98gLa2tpR1RcLhMBYXFzEwMID5+XlcvXqVLSTR5ia9J7UsSDjI6/VCLBZDoVDA7XanZOYb6Zput9uh0+lQUlKC3NxcdsNJ5dwymUw4efIk7t+/jx/84Ac4duzYqsd0d3fjnXfewZ07d6DX69Hc3Ixdu3Zhx44d0Gq1KScU0fMqqpDWiujFlc3ApgVkh8PBpsvAw/4hTe5pM41MTi9evJjSYI0WOZRKJRwOB5RKJdvAShT06N8CgQCmp6dx9+7dpAsYEomErZMmUtoCfvtDRfKaKSNJ9S7J4XCYY200l5TL5aKrq4v1FGP1gCOpZXRBEhujsLCQ9XQjg106a6GUbdLySDw4HA7cu3cPxcXFEIvFWFxcREZGBnw+H86dO4ePPvqIbUTK5XI4nU7Mzc2x9kgwGERTU1PMz+X3+9lSC7UeMjIyUtKijqRNkjAQuX9TkCLeduRFG7nIEAgE4PV64XQ6YbVak1oM0XskgtPpZEL6FIxJXjIZQqEQG8Sls+2p1WoZR5pcOVKFRCKBwWAAh8OB2WxmveT5+fmUTVNpuFZeXo6CggJkZWUxU4GlpSVcvnwZFy5cgMlkwt27d+F0OqHRaFBdXb2m6g54mPhdu3YtoQVZMszPz2NwcJDJPRCfms4NSqqo1w6kpnkdiU0JyOFwmK2VdnR0IBQK4bXXXsOzzz6LwcFB/OQnP8Hw8DAkEgkWFxdT3tZTq9X4+te/jtbWVqbuVV1dnXLQa29vx7vvvov29va41C2C0WjE66+/jqamJuzevTvu44ibGGk1vpYMNBEKCgrwve99D0899RQAxLzII286TqeTXWg0UNTr9dDr9ayPSW2WVOUVxWIxcnJyWE8yHubn53H69GncvHmTbT0RRW9kZGTFejpN9D0eD27cuIGFhQW2HBELMzMzMJvNbHsrHfj9fiwvL2NpaYnZWmVnZ0MqlWJychJmsxkajQalpaXs+xGDgNxElpeXMT09jbm5OQSDwVU99nRBQkg8Hg+FhYWwWq3weDwIhUKYnZ3d0BKaUFtbi6NHj0IikaC/vx89PT0YGhpKSQtbKBTi2LFjqKqqwtjYGBP/pwSpp6cnLW2PCxcuMIcaEkPy+XyYnp5eoTM9ODi4Ls2Q0dFR/Od//ic+/fTThAPzaERXt/39/Xj77bcxMDDA6HfAw6rQ6XQiMzMT3/72t/HCCy+seI10kFbk8Pv9mJubY4Md6l8RiNs5ODjIvOPIEqmgoABlZWX4zW9+g9OnT69JjUupVOKJJ57A8ePHV/1bKq2Bvr4+nD59OildSCaT4cknn8Q3vvGNVUau0aAsaD0XZjJIJJKUfQeBh/1F6gtSORmZWVDQ9nq9jHFAHOpIRgw9h7JEGt4k+q7Ly8vo7OxMqeKJPFm9Xi+6urpw/fp1PPHEE6ipqWFtFpFIhKWlJXR0dGBsbAylpaVoampiJgPUEoikN0azCqhk93q9WFxcBI/Hg1qtBofDgdfrZfz4aBF7qjj8fj88Hg+WlpYYe4NU1FIFrQvTsab+c2ZmJqqqqli27vF4YDKZYDKZ4HQ609afjuT70rHxeDxQqVRobW3FkSNHmAt8KBTC/Pw844HL5XIsLy8zPr1SqUQwGITP58POnTtx7Ngx1NbW4urVq8yPUCAQYHp6GlevXk0r4MXzhYwGeTtGzgLS6dEODAzg17/+dUJGVbLNwYWFBfzmN7/BmTNnVkmzRkKj0aCurg7l5eUAUmN/RCKtgDw9PY2///u/h06nYwMEKt0iyzObzYbBwcEVB/vChQuw2WwYHh5eszQin8+PW55S+Z3oR6KSOBLRq9dGoxHHjx/H888/nzQYbzbWOhhIdoMgcRW73c44pJTZUwCnhRMejweHw4HFxUUmrLOZuH37Nt566y1kZWWxlVXieJtMJrawcPbsWZSXl8NoNCIrK4s5fEcu5ERSwfh8PtRqNZsxhEIhxoctKCiAUCiETCZbNTSii1QgELAWB21ypbrgBIBxn51OJxu6kURkXl4eJicn4ff7IZfL2ban2WzGgwcP0NXVldSZhEDPF4vFUCqV0Gg0zIwgOzsbpaWlcLlcmJmZwfz8POvlZ2VloaamBtnZ2Whvb4fJZEJxcTFeffVVFBQUMJf5pqYm5ndXUFCA/Px8KBQKNgvYLPOCjIwMtgZNNym5XJ6wZUSVxsjISMIgCjy8ZuIZ0t68eRP/9V//hYsXLyZ9nXPnzsHv9+OFF16I2R9PhrQC8vz8PP71X/+VmfmZzeaUezL37t1LSWg7EXw+34rSJdJhOLLsjtd8DwQCUCqVKwYnkcFYKBTi6aefxh/8wR+wleKvEpvBfaQhpNPphM1mw9LSEtvZl0gkTIOWSnKxWIzl5WVYLBYWrDbTJYPMXyPZHBQIox06jEYj9u/fj5KSEshkMmRkZDD2QLyhLZ0vlKEmcguP5PECD6mJGo2GZYxerzctK3kSrbHZbHC73cjJyWH0r7y8PMaVzs/Ph1AohNVqRXt7OzgcDutd0lIRqaDRdwF+K8mq1WohlUqh0+lQUFCAkpISxiOmpIhU5MRiMeOnHzx4EHl5eUwCtKmpCa+//voK5gqhvr4e9fX17L9JozpZwFoL+Hw+o6VJpVI2XEw2mJ+ZmUFHRwd6enqStg48Hg/m5+dX0fEcDgc+/vhj/PjHP07pZmMymfDzn/8cXq8XRqMRRqMx6XMikXaz0+v1JjR23EyMj48zIWq6SOrr61FXV8ce4/F48MUXX2BpaQn19fUoKiqC2WzGjRs3cO3atZiOBmKxGNu3b8eBAwfwta99bUUwTrcH9DiCDFU9Hg/rpc7PzzM3k8ggRaV5pCJWOBxm2edmG2RS3zYSROGKvhGMjo5CIBCgp6cHPB4PJSUlePrpp1c50ZDwzOLiIqxWKywWCzweD6RSKXJzc1FTU5Oy1kRkkBYIBGndnEQiEZRKJdOcJiF/WvvNzc2FWq1mmTwp9Gm1WszOzrK+P/VbqYKixIRuGJHO7Gq1mq2MS6VStmaflZUFh8OBuro6LC0tQSqVorKyEpmZmeBwOGhoaEBjY2PMYBwLtbW1eP3119Hf34933nkn5WOSCvx+Py5cuIBwOIxdu3axTD4ZvXVqagptbW24cuVKzO3eSPT39+PkyZMoLy9nFRSPx4PZbMbFixfTzvxv3ryJf//3f0dVVVVaz/vKaW/pwOfz4eLFi7h//z7C4TA0Gg1eeeUVlJaWsrulyWTC5cuXMT8/D41Gg4KCAty+fRs///nPcfv27ZgBmUjyf/zHf7xKIOVRbehsJijDpZ5spC8cWVtRz5HH47Gg6HQ6WaVBtkmb2SuPBQ6HA4PBAKlUirm5uRUZmM/nQ19fHxt+zc7OoqWlZUXpaTKZ0NnZiYGBASbIbrFY4PV6IZfLUV5ezoZq6d5sUhFuj/weEomEqZRFVnACgQBFRUXsb5F/37ZtG6qqqlgABlYnCRSYI7VAIvvo1D8PhUKQy+WoqKhYYSZA7T6ix+Xl5eHIkSNpfb+qqioUFxfD7/dveEAOBAJsF+H1119HTU1NSp9tfHwcV65cSYk00N/fj7GxMdbyIaF+ajGli/Hxcbz99ttpD/jTerRGo8GBAwdgtVrh8/nYRtrg4CC6uro2zRdOr9djx44dEAqF6O7uZq0PlUqFvLw8ZGdnIzc3F4uLixgeHmY2QiqVCsFgECaTCXfu3InLt+Tz+cjLy2PB+P79+xCJRCu2vr4KBIPBFToB6Q4IyOVjcXGRLQwQl5jaFNRzpQw0ch2Y/A95PB4Lxsk+g0qlQkNDA7KystDV1YXe3l7k5+fDaDTC4XCgt7c3IddWqVRCrVZDoVBAIBCwtgktjxBdi7wJI5kICwsLcDgcmJmZgcvlwoMHDzA8PIyRkRHMzMywmcfc3ByEQiFKSkrYaz+KSihy8BiNeDcDgUCQVmBMBKLJeTweSCSSuOpsPB5vhWcgaaQQaycyyNDNIBW1t/Ui0oSB4PF42DDWYrFgfn4ecrkcHo8HPT09MR1zYoFaWGTku16Qh2a6SCsgGwwG/M3f/A36+vqwtLSEbdu2QafT4Ve/+hWGhoY2LSAbjUb86Z/+KVQqFd58802mj2u329HZ2clEfebm5iCXy9HQ0IA9e/agpKQEoVCIXYiJQL3A7u5ufPrpp4w3/VUGZHLy5fF4SdkN0QiFQrBarTCZTGyaT9kx6QBTMCYVKxIsIoPLQCDA+qyptiuys7Px2muvYceOHfiXf/kX9Pb2orq6GidOnMD4+DisVmvCgKzRaLB9+3a2lksXWjgcZpS0y5cvY3p6etX5JhAI4Ha7MTAwgKtXr+LXv/41u7ho0EnDTLqZb9u2bYUi3e8yuFwuLBYLJiYmkJGRAaPRGLMPOzExgdnZWajVahQUFCAcDmNpaQmhUAgZGRkrAvKjqiDVajVqamqYlCoANpQWiUTw+/0YGhrC3bt32XPSYXw8LkgrIAsEArbuaLPZ0NzcDOChg8VmlrJarRa7du2CSqXC6dOnV/zb9PQ0gsEgbDYb5ubmUFhYiJaWuSeo9gAAAVpJREFUFhQWFkIqlTIaUbKygzIks9nMxEc20tJ8LaDh0VpMJ2mqTx54xAWm9W7qg0YOrcLhMGtd8Pl8tmBCATuVoCWTydDQ0IDa2lomg6rT6dgmZbJBjFwuR25uLsrKyqDT6djNxO/3o6SkBFlZWejv7495c6DMjsSjooXtFQoFy7KCwSCUSiUT/vldaE2lApKy9fv97BqJRDAYhN1ux/T0NGsXETWQ5F4fNTgcDlQqFROHot/e7XavcB+x2WwYHR1l2b3Vav1/NwPipPOBORyOBcB40gf+7qEwHA6vsh7YOh4rsXU8VmLreKzE1vFIjrQC8ha2sIUtbGHz8LvfONvCFrawhf8n2ArIW9jCFrbwmGArIG9hC1vYwmOCrYC8hS1sYQuPCbYC8ha2sIUtPCbYCshb2MIWtvCYYCsgb2ELW9jCY4KtgLyFLWxhC48JtgLyFrawhS08Jvhfv0NyVch8nmwAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ff3a1f70c88>"
+       "<matplotlib.figure.Figure at 0x7f75f6c32c18>"
       ]
      },
      "metadata": {},
@@ -2171,10 +1752,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "These images may vary each time you run the optimization. Some of the images can be seen to somewhat resemble the hand-written digits. But the other images are often impossible to recognize and it is hard to understand why the neural network thinks these are the *optimal* input images for those digits.\n",
     "\n",
@@ -2187,32 +1765,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 51,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2222,10 +1790,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2236,10 +1801,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2260,10 +1822,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2298,5 +1857,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index 505f087..7dc305f 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #16\n",
     "# Reinforcement Learning (Q-Learning)\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -36,10 +30,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## The Problem\n",
     "\n",
@@ -52,40 +43,28 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Illustration of the problem](images/16_problem.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The problem is that there are 10 states between the ball going downwards and the paddle hitting the ball, and there are an additional 18 states before the reward is obtained when the ball hits the wall and smashes some bricks. How can we teach an agent to connect these three situations and generalize to similar situations? The answer is to use so-called Reinforcement Learning with a Neural Network, as shown in this tutorial."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Q-Learning"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "One of the simplest ways of doing Reinforcement Learning is called Q-learning. Here we want to estimate so-called Q-values which are also called action-values, because they map a state of the game-environment to a numerical value for each possible action that the agent may take. The Q-values indicate which action is expected to result in the highest future reward, thus telling the agent which action to take.\n",
     "\n",
@@ -108,10 +87,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Simple Example\n",
     "\n",
@@ -122,20 +98,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Q-values Simple Example](images/16_q-values-simple.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Detailed Example\n",
     "\n",
@@ -144,20 +114,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Q-values Detailed Example](images/16_q-values-details.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Q-values for the possible actions have been estimated by a Neural Network. For the action NOOP in state *t* the Q-value is estimated to be 2.900, which is the highest Q-value for that state so the agent takes that action, i.e. the agent does not do anything between state *t* and *t+1* because NOOP means \"No Operation\".\n",
     "\n",
@@ -176,10 +140,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Motion Trace\n",
     "\n",
@@ -192,20 +153,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Motion Trace](images/16_motion-trace.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Training Stability\n",
     "\n",
@@ -216,20 +171,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Training Stability](images/16_training_stability.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "If we were to train a Neural Network to estimate the Q-values for the two states $t$ and $t+1$ with Q-values 0.97 and 1.0, respectively, then the Neural Network will most likely be unable to distinguish properly between the images of these two states. As a result the Neural Network will also estimate a Q-value near 1.0 for state $t+2$ because the images are so similar. But this is clearly wrong because the Q-values for state $t+2$ should be zero as we do not know anything about future rewards at this point, and that is what the Q-values are supposed to estimate.\n",
     "\n",
@@ -238,10 +187,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart\n",
     "\n",
@@ -256,20 +202,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "![Flowchart](images/16_flowchart.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Neural Network Architecture\n",
     "\n",
@@ -286,30 +226,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Installation"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The [documentation](https://github.com/openai/gym) for OpenAI Gym currently suggests that you need to build it in order to install it. But if you just want to install the Atari games, then you only need to install a single pip-package by typing the following commands in a terminal."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "- conda create --name tf-gym --clone tf\n",
     "- source activate tf-gym\n",
@@ -318,20 +249,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This assumes you already have an Anaconda environment named `tf` which has TensorFlow installed, it will then be cloned to another environment named `tf-gym` where OpenAI Gym is also installed. This allows you to easily switch between your normal TensorFlow environment and another one which also contains OpenAI Gym."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You can also have two environments named `tf-gpu` and `tf-gpu-gym` for the GPU versions of TensorFlow."
    ]
@@ -340,8 +265,6 @@
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
-    "deletable": true,
-    "editable": true,
     "id": "xu2SVpFJjmJr"
    },
    "source": [
@@ -352,9 +275,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -368,10 +289,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The main source-code for Reinforcement Learning is located in the following module:"
    ]
@@ -380,9 +298,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -391,10 +307,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6.0 (Anaconda) with package versions:"
    ]
@@ -402,11 +315,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -428,9 +337,6 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -452,10 +358,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Game Environment\n",
     "\n",
@@ -465,11 +368,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "env_name = 'Breakout-v0'\n",
@@ -478,10 +377,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is the base-directory for the TensorFlow checkpoints as well as various log-files."
    ]
@@ -490,9 +386,7 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -501,10 +395,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Once the base-dir has been set, you need to call this function to set all the paths that will be used. This will also create the checkpoint-dir if it does not already exist."
    ]
@@ -513,9 +404,7 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -524,62 +413,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Download Pre-Trained Model\n",
     "\n",
-    "You can download a TensorFlow checkpoint which holds all the pre-trained variables for the Neural Network. Two checkpoints are provided, one for Breakout and one for Space Invaders. They were both trained for about 150 hours on a laptop with 2.6 GHz CPU and a GTX 1070 GPU.\n",
-    "\n",
-    "#### COMPATIBILITY ISSUES\n",
-    "\n",
-    "These TensorFlow checkpoints were developed with OpenAI gym v. 0.8.1 and atari-py v. 0.0.19 which had unused / redundant actions as noted above. There appears to have been a change in the gym API since then, as the unused actions are no longer present. This means the vectors with actions and Q-values now only contain 4 elements instead of the 6 shown here. This also means that the TensorFlow checkpoints cannot be used with newer versions of gym and atari-py, so in order to use these pre-trained checkpoints you need to install the older versions of gym and atari-py - or you can just train a new model yourself so you get a new TensorFlow checkpoint.\n",
-    "\n",
-    "#### WARNING!\n",
-    "\n",
-    "These checkpoints are 280-360 MB each. They are currently hosted on the webserver I use for [www.hvass-labs.org](www.hvass-labs.org) because it is awkward to automatically download large files on Google Drive. To lower the traffic on my webserver, this line has been commented out, so you have to activate it manually. You are welcome to download it, I just don't want it to download automatically for everyone who only  wants to run this Notebook briefly."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "# rl.maybe_download_checkpoint(env_name=env_name)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "I believe the webserver is located in Denmark. If you are having problems downloading the files using the automatic function above, then you can try and download the files manually in a webbrowser or using `wget` or `curl`. Or you can download from Google Drive, where you will get an anti-virus warning that is awkward to bypass automatically:\n",
-    "\n",
-    "* [Download Breakout Checkpoint from Google Drive](https://drive.google.com/uc?export=download&id=0B2aDiIly76ZvUjZTcXRuRFY0RjQ)\n",
-    "\n",
-    "* [Download Space Invaders Checkpoint from Google Drive](https://drive.google.com/uc?export=download&id=0B2aDiIly76ZvWDR4TExwdmw1RVE)\n",
-    "\n",
-    "You can use the checksum to ensure the downloaded files are complete:\n",
-    "\n",
-    "* [SHA256 Checksum](http://www.hvass-labs.org/projects/tensorflow/tutorial16/sha256sum.txt)"
+    "The original version of this tutorial provided some TensorFlow checkpoints with pre-trained models for download. But due to changes in both TensorFlow and OpenAI Gym, these pre-trained models cannot be loaded anymore so they have been deleted from the web-server. You will therefore have to train your own model further below."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Create Agent\n",
     "\n",
@@ -590,9 +433,6 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -635,10 +475,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Neural Network is automatically instantiated by the Agent-class. We will create a direct reference for convenience."
    ]
@@ -647,9 +484,7 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -658,10 +493,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Similarly, the Agent-class also allocates the replay-memory when `training==True`. The replay-memory will require more than 3 GB of RAM, so it should only be allocated when needed. We will need the replay-memory in this Notebook to record the states and Q-values we observe, so they can be plotted further below."
    ]
@@ -670,9 +502,7 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -681,10 +511,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Training\n",
     "\n",
@@ -695,9 +522,6 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -715,10 +539,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In training-mode, this function will output a line for each episode. The first counter is for the number of episodes that have been processed. The second counter is for the number of states that have been processed. These two counters are stored in the TensorFlow checkpoint along with the weights of the Neural Network, so you can restart the training e.g. if you only have one computer and need to train during the night.\n",
     "\n",
@@ -732,20 +553,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Training Progress"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Data is being logged during training so we can plot the progress afterwards. The reward for each episode and a running mean of the last 30 episodes are logged to file. Basic statistics for the Q-values in the replay-memory are also logged to file before each optimization run.\n",
     "\n",
@@ -757,11 +572,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "log_q_values = rl.LogQValues()\n",
@@ -770,10 +581,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now read the logs from file:"
    ]
@@ -782,9 +590,6 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -795,10 +600,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training Progress: Reward\n",
     "\n",
@@ -808,11 +610,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -835,10 +633,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training Progress: Q-Values\n",
     "\n",
@@ -853,9 +648,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -879,10 +671,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Testing\n",
     "\n",
@@ -894,11 +683,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -917,10 +702,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We will now instruct the agent that it should no longer perform training by setting this boolean:"
    ]
@@ -929,9 +711,7 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -940,10 +720,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We also reset the previous episode rewards."
    ]
@@ -952,9 +729,7 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -963,10 +738,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can render the game-environment to screen so we can see the agent playing the game, by setting this boolean:"
    ]
@@ -975,9 +747,7 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -986,10 +756,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now run a single episode by calling the `run()` function again. This should open a new window that shows the game being played by the agent. At the time of this writing, it was not possible to resize this tiny window, and the developers at OpenAI did not seem to care about this feature which should obviously be there."
    ]
@@ -997,11 +764,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1075,20 +838,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Mean Reward"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The game-play is slightly random, both with regard to selecting actions using the epsilon-greedy policy, but also because the OpenAI Gym environment will repeat any action between 2-4 times, with the number chosen at random. So the reward of one episode is not an accurate estimate of the reward that can be expected in general from this agent.\n",
     "\n",
@@ -1101,9 +858,7 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1112,10 +867,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We disable the screen-rendering so the game-environment runs much faster."
    ]
@@ -1124,9 +876,7 @@
    "cell_type": "code",
    "execution_count": 23,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1135,10 +885,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now run 30 episodes. This records the rewards for each episode. It might have been a good idea to disable the output so it does not print all these lines - you can do this as an exercise."
    ]
@@ -1146,11 +893,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2883,10 +2626,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can now print some statistics for the episode rewards, which vary greatly from one episode to the next."
    ]
@@ -2894,11 +2634,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2923,10 +2659,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can also plot a histogram with the episode rewards."
    ]
@@ -2934,11 +2667,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2957,10 +2686,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Example States\n",
     "\n",
@@ -2973,9 +2699,7 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -3009,10 +2733,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This helper-function plots a state from the replay-memory and optionally prints the Q-values."
    ]
@@ -3021,9 +2742,7 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -3056,10 +2775,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The replay-memory has room for 200k states but it is only partially full from the above call to `agent.run(num_episodes=1)`. This is how many states are actually used."
    ]
@@ -3067,11 +2783,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3091,10 +2803,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the Q-values from the replay-memory that are actually used."
    ]
@@ -3103,9 +2812,7 @@
    "cell_type": "code",
    "execution_count": 30,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -3114,10 +2821,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "For each state, calculate the min / max Q-values and their difference. This will be used to lookup interesting states in the following sections."
    ]
@@ -3126,9 +2830,7 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -3139,10 +2841,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Example States: Highest Reward\n",
     "\n",
@@ -3155,9 +2854,6 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -3179,10 +2875,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This state is where the ball hits the wall so the agent scores a point. \n",
     "\n",
@@ -3194,11 +2887,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3408,10 +3097,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Example: Highest Q-Value\n",
     "\n",
@@ -3421,11 +3107,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3447,9 +3129,6 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -3586,10 +3265,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Example: Loss of Life\n",
     "\n",
@@ -3599,11 +3275,7 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3625,9 +3297,6 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -3889,10 +3558,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Example: Greatest Difference in Q-Values\n",
     "\n",
@@ -3903,9 +3569,6 @@
    "cell_type": "code",
    "execution_count": 38,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -3928,11 +3591,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -4067,10 +3726,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Example: Smallest Difference in Q-Values\n",
     "\n",
@@ -4082,11 +3738,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -4107,11 +3759,7 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -4246,10 +3894,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Output of Convolutional Layers\n",
     "\n",
@@ -4262,9 +3907,7 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -4328,10 +3971,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Game State\n",
     "\n",
@@ -4342,9 +3982,6 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4366,10 +4003,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Output of Convolutional Layer 1\n",
     "\n",
@@ -4382,9 +4016,6 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -4412,10 +4043,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Output of Convolutional Layer 2\n",
     "\n",
@@ -4426,9 +4054,6 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4456,10 +4081,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Output of Convolutional Layer 3\n",
     "\n",
@@ -4476,9 +4098,6 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4508,8 +4127,6 @@
    "cell_type": "markdown",
    "metadata": {
     "colab_type": "text",
-    "deletable": true,
-    "editable": true,
     "id": "Nv2JqNLBhy1j"
    },
    "source": [
@@ -4524,11 +4141,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_conv_weights(model, layer_name, input_channel=0):\n",
@@ -4599,10 +4212,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Weights for Convolutional Layer 1\n",
     "\n",
@@ -4615,9 +4225,6 @@
    "cell_type": "code",
    "execution_count": 48,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4646,10 +4253,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can also plot the convolutional weights for the second input channel, that is, the motion-trace of the game-environment. Once again we see that the negative weights (blue) have a much greater magnitude than the positive weights (red)."
    ]
@@ -4658,9 +4262,6 @@
    "cell_type": "code",
    "execution_count": 49,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4689,10 +4290,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Weights for Convolutional Layer 2\n",
     "\n",
@@ -4704,11 +4302,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -4735,10 +4329,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Weights for Convolutional Layer 3\n",
     "\n",
@@ -4751,9 +4342,6 @@
    "cell_type": "code",
    "execution_count": 51,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -4782,10 +4370,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Discussion\n",
     "\n",
@@ -4804,10 +4389,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises & Research Ideas\n",
     "\n",
@@ -4824,8 +4406,7 @@
     "You may find it helpful to add more command-line parameters to `reinforcement_learning.py` so you don't have to edit the source-code for testing other parameters.\n",
     "\n",
     "* Change the epsilon-probability during testing to e.g. 0.001 or 0.05. Which gives the best results? Could you use this value during training? Why/not?\n",
-    "* Continue training the agent for the Breakout game using the downloaded checkpoint. Does the agent get better or worse the more you train it? Why? (You should run it in a terminal window as described above.)\n",
-    "* Try and change the game-environment to Space Invaders and re-run this Notebook. The checkpoint can be downloaded automatically. It was trained for about 150 hours, which is roughly the same as for Breakout, but note that it has processed far fewer states. The reason is that the hyper-parameters such as the learning-rate were tuned for Breakout. Can you make some kind of adaptive learning-rate that would work better for both Breakout and Space Invaders? What about the other hyper-parameters? What about other games?\n",
+    "* Try and change the game-environment to Space Invaders and re-run this Notebook. The hyper-parameters such as the learning-rate were tuned for Breakout. Can you make some kind of adaptive learning-rate that would work better for both Breakout and Space Invaders? What about the other hyper-parameters? What about other games?\n",
     "* Try different architectures for the Neural Network. You will need to restart the training because the checkpoints cannot be reused for other architectures. You will need to train the agent for several days with each new architecture so as to properly assess its performance.\n",
     "* The replay-memory throws away all data after optimization of the Neural Network. Can you make it reuse the data somehow? The ReplayMemory-class has the function `estimate_all_q_values()` which may be helpful.\n",
     "* The reward is limited to -1 and 1 in the function `ReplayMemory.add()` so as to stabilize the training. This means the agent cannot distinguish between small and large rewards. Can you use batch normalization to fix this problem, so you can use the actual reward values?\n",
@@ -4843,10 +4424,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -4878,9 +4456,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/17_Estimator_API.ipynb b/17_Estimator_API.ipynb
index e26fcbf..47117c2 100644
--- a/17_Estimator_API.ipynb
+++ b/17_Estimator_API.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #17\n",
     "# Estimator API\n",
@@ -16,10 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -38,10 +32,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -49,18 +40,14 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
      ]
     }
    ],
@@ -73,10 +60,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
@@ -84,16 +68,12 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.4.0'"
+       "'1.9.0'"
       ]
      },
      "execution_count": 2,
@@ -107,67 +87,39 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given dir."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -175,205 +127,65 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers so we calculate that now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [],
-   "source": [
-    "data.train.cls = np.argmax(data.train.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [],
-   "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "This is an example of one-hot encoded labels:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.],\n",
-       "       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.],\n",
-       "       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.],\n",
-       "       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  0.]])"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data.train.labels[0:10]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "These are the corresponding class-numbers:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([7, 3, 4, 6, 1, 8, 1, 0, 9, 8])"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data.train.cls[0:10]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "## Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
     "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
     "\n",
     "# Tuple with height and width of images used to reshape arrays.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
+    "img_shape = data.img_shape\n",
     "\n",
     "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -407,28 +219,21 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f00292a1978>"
+       "<matplotlib.figure.Figure at 0x7fcc687e6a20>"
       ]
      },
      "metadata": {},
@@ -437,10 +242,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -448,62 +253,46 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Input Functions for the Estimator"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Rather than providing raw data directly to the Estimator, we must provide functions that return the data. This allows for more flexibility in data-sources and how the data is randomly shuffled and iterated.\n",
     "\n",
-    "Note that we will create an Estimator using the `DNNClassifier` which assumes the class-numbers are integers so we use `data.train.cls` instead of `data.train.labels` which are one-hot encoded arrays.\n",
+    "Note that we will create an Estimator using the `DNNClassifier` which assumes the class-numbers are integers so we use `data.y_train_cls` instead of `data.y_train` which are one-hot encoded arrays.\n",
     "\n",
     "The function also has parameters for `batch_size`, `queue_capacity` and `num_threads` for finer control of the data reading. In our case we take the data directly from a numpy array in memory, so it is not needed."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "train_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
-    "    x={\"x\": np.array(data.train.images)},\n",
-    "    y=np.array(data.train.cls),\n",
+    "    x={\"x\": np.array(data.x_train)},\n",
+    "    y=np.array(data.y_train_cls),\n",
     "    num_epochs=None,\n",
     "    shuffle=True)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This actually returns a function:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 9,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -513,7 +302,7 @@
        "<function tensorflow.python.estimator.inputs.numpy_io.numpy_input_fn.<locals>.input_fn>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -524,31 +313,24 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Calling this function returns a tuple with TensorFlow ops for returning the input and output data:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "({'x': <tf.Tensor 'random_shuffle_queue_DequeueMany:1' shape=(128, 784) dtype=float32>},\n",
+       "({'x': <tf.Tensor 'random_shuffle_queue_DequeueMany:1' shape=(128, 784) dtype=float64>},\n",
        " <tf.Tensor 'random_shuffle_queue_DequeueMany:2' shape=(128,) dtype=int64>)"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -559,62 +341,44 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Similarly we need to create a function for reading the data for the test-set. Note that we only want to process these images once so `num_epochs=1` and we do not want the images shuffled so `shuffle=False`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
     "test_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
-    "    x={\"x\": np.array(data.test.images)},\n",
-    "    y=np.array(data.test.cls),\n",
+    "    x={\"x\": np.array(data.x_test)},\n",
+    "    y=np.array(data.y_test_cls),\n",
     "    num_epochs=1,\n",
     "    shuffle=False)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "An input-function is also needed for predicting the class of new data. As an example we just use a few images from the test-set."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "some_images = data.test.images[0:9]"
+    "some_images = data.x_test[0:9]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
     "predict_input_fn = tf.estimator.inputs.numpy_input_fn(\n",
@@ -625,33 +389,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-numbers are actually not used in the input-function as it is not needed for prediction. However, the true class-number is needed when we plot the images further below."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "some_images_cls = data.test.cls[0:9]"
+    "some_images_cls = data.y_test_cls[0:9]"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Pre-Made / Canned Estimator\n",
     "\n",
@@ -660,12 +414,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [],
    "source": [
     "feature_x = tf.feature_column.numeric_column(\"x\", shape=img_shape)"
@@ -673,22 +423,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You can have several input features which would then be combined in a list:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [],
    "source": [
     "feature_columns = [feature_x]"
@@ -696,22 +439,15 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In this example we want to use a 3-layer DNN with 512, 256 and 128 units respectively."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "num_hidden_units = [512, 256, 128]"
@@ -719,29 +455,22 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The `DNNClassifier` then constructs the neural network for us. We can also specify the activation function and various other parameters (see the docs). Here we just specify the number of classes and the directory where the checkpoints will be saved."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Using default config.\n",
-      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-1/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f0028f03198>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-1/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fcc66415240>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
      ]
     }
    ],
@@ -755,10 +484,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -769,69 +495,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
       "INFO:tensorflow:Create CheckpointSaverHook.\n",
-      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial17-1/model.ckpt.\n",
-      "INFO:tensorflow:loss = 300.688, step = 1\n",
-      "INFO:tensorflow:global_step/sec: 370.039\n",
-      "INFO:tensorflow:loss = 26.462, step = 101 (0.271 sec)\n",
-      "INFO:tensorflow:global_step/sec: 521.366\n",
-      "INFO:tensorflow:loss = 22.0528, step = 201 (0.191 sec)\n",
-      "INFO:tensorflow:global_step/sec: 549.886\n",
-      "INFO:tensorflow:loss = 32.07, step = 301 (0.182 sec)\n",
-      "INFO:tensorflow:global_step/sec: 548.856\n",
-      "INFO:tensorflow:loss = 13.8037, step = 401 (0.182 sec)\n",
-      "INFO:tensorflow:global_step/sec: 516.064\n",
-      "INFO:tensorflow:loss = 23.2653, step = 501 (0.194 sec)\n",
-      "INFO:tensorflow:global_step/sec: 552.268\n",
-      "INFO:tensorflow:loss = 17.7141, step = 601 (0.180 sec)\n",
-      "INFO:tensorflow:global_step/sec: 529.426\n",
-      "INFO:tensorflow:loss = 25.7157, step = 701 (0.189 sec)\n",
-      "INFO:tensorflow:global_step/sec: 513.375\n",
-      "INFO:tensorflow:loss = 5.08285, step = 801 (0.195 sec)\n",
-      "INFO:tensorflow:global_step/sec: 536.319\n",
-      "INFO:tensorflow:loss = 10.3937, step = 901 (0.187 sec)\n",
-      "INFO:tensorflow:global_step/sec: 534.847\n",
-      "INFO:tensorflow:loss = 3.12976, step = 1001 (0.187 sec)\n",
-      "INFO:tensorflow:global_step/sec: 540.827\n",
-      "INFO:tensorflow:loss = 5.54126, step = 1101 (0.185 sec)\n",
-      "INFO:tensorflow:global_step/sec: 483.467\n",
-      "INFO:tensorflow:loss = 10.2708, step = 1201 (0.209 sec)\n",
-      "INFO:tensorflow:global_step/sec: 527.042\n",
-      "INFO:tensorflow:loss = 7.62363, step = 1301 (0.187 sec)\n",
-      "INFO:tensorflow:global_step/sec: 557.67\n",
-      "INFO:tensorflow:loss = 2.30585, step = 1401 (0.180 sec)\n",
-      "INFO:tensorflow:global_step/sec: 547.406\n",
-      "INFO:tensorflow:loss = 7.69151, step = 1501 (0.182 sec)\n",
-      "INFO:tensorflow:global_step/sec: 557.682\n",
-      "INFO:tensorflow:loss = 10.7881, step = 1601 (0.179 sec)\n",
-      "INFO:tensorflow:global_step/sec: 547.859\n",
-      "INFO:tensorflow:loss = 7.09411, step = 1701 (0.184 sec)\n",
-      "INFO:tensorflow:global_step/sec: 544.495\n",
-      "INFO:tensorflow:loss = 2.6387, step = 1801 (0.182 sec)\n",
-      "INFO:tensorflow:global_step/sec: 549.648\n",
-      "INFO:tensorflow:loss = 0.772691, step = 1901 (0.182 sec)\n",
+      "INFO:tensorflow:Graph was finalized.\n",
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n",
+      "INFO:tensorflow:Saving checkpoints for 0 into ./checkpoints_tutorial17-1/model.ckpt.\n",
+      "INFO:tensorflow:loss = 300.61185, step = 0\n",
+      "INFO:tensorflow:global_step/sec: 453.729\n",
+      "INFO:tensorflow:loss = 33.910957, step = 100 (0.221 sec)\n",
+      "INFO:tensorflow:global_step/sec: 545.745\n",
+      "INFO:tensorflow:loss = 38.821697, step = 200 (0.183 sec)\n",
+      "INFO:tensorflow:global_step/sec: 510.96\n",
+      "INFO:tensorflow:loss = 36.428062, step = 300 (0.196 sec)\n",
+      "INFO:tensorflow:global_step/sec: 509.188\n",
+      "INFO:tensorflow:loss = 10.77646, step = 400 (0.196 sec)\n",
+      "INFO:tensorflow:global_step/sec: 525.229\n",
+      "INFO:tensorflow:loss = 20.211845, step = 500 (0.190 sec)\n",
+      "INFO:tensorflow:global_step/sec: 529.656\n",
+      "INFO:tensorflow:loss = 16.973766, step = 600 (0.189 sec)\n",
+      "INFO:tensorflow:global_step/sec: 518.829\n",
+      "INFO:tensorflow:loss = 9.104766, step = 700 (0.193 sec)\n",
+      "INFO:tensorflow:global_step/sec: 517.877\n",
+      "INFO:tensorflow:loss = 11.87432, step = 800 (0.194 sec)\n",
+      "INFO:tensorflow:global_step/sec: 513.369\n",
+      "INFO:tensorflow:loss = 7.3187075, step = 900 (0.194 sec)\n",
+      "INFO:tensorflow:global_step/sec: 531.02\n",
+      "INFO:tensorflow:loss = 5.238852, step = 1000 (0.188 sec)\n",
+      "INFO:tensorflow:global_step/sec: 493.925\n",
+      "INFO:tensorflow:loss = 6.4892335, step = 1100 (0.203 sec)\n",
+      "INFO:tensorflow:global_step/sec: 513.837\n",
+      "INFO:tensorflow:loss = 10.295633, step = 1200 (0.194 sec)\n",
+      "INFO:tensorflow:global_step/sec: 516.007\n",
+      "INFO:tensorflow:loss = 4.5178833, step = 1300 (0.194 sec)\n",
+      "INFO:tensorflow:global_step/sec: 501.485\n",
+      "INFO:tensorflow:loss = 2.4612594, step = 1400 (0.200 sec)\n",
+      "INFO:tensorflow:global_step/sec: 508.118\n",
+      "INFO:tensorflow:loss = 10.878417, step = 1500 (0.197 sec)\n",
+      "INFO:tensorflow:global_step/sec: 505.549\n",
+      "INFO:tensorflow:loss = 22.480297, step = 1600 (0.198 sec)\n",
+      "INFO:tensorflow:global_step/sec: 512.93\n",
+      "INFO:tensorflow:loss = 6.8385906, step = 1700 (0.195 sec)\n",
+      "INFO:tensorflow:global_step/sec: 520.968\n",
+      "INFO:tensorflow:loss = 1.8562572, step = 1800 (0.192 sec)\n",
+      "INFO:tensorflow:global_step/sec: 547.812\n",
+      "INFO:tensorflow:loss = 4.875979, step = 1900 (0.183 sec)\n",
       "INFO:tensorflow:Saving checkpoints for 2000 into ./checkpoints_tutorial17-1/model.ckpt.\n",
-      "INFO:tensorflow:Loss for final step: 7.35222.\n"
+      "INFO:tensorflow:Loss for final step: 2.701511.\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.estimator.canned.dnn.DNNClassifier at 0x7f0028f03a90>"
+       "<tensorflow.python.estimator.canned.dnn.DNNClassifier at 0x7fcc663a5160>"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -842,10 +569,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -854,21 +578,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 20,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INFO:tensorflow:Starting evaluation at 2017-11-17-12:07:56\n",
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
+      "INFO:tensorflow:Starting evaluation at 2018-07-16-11:23:09\n",
+      "INFO:tensorflow:Graph was finalized.\n",
       "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-1/model.ckpt-2000\n",
-      "INFO:tensorflow:Finished evaluation at 2017-11-17-12:07:56\n",
-      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9727, average_loss = 0.0934177, global_step = 2000, loss = 11.825\n"
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n",
+      "INFO:tensorflow:Finished evaluation at 2018-07-16-11:23:09\n",
+      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.972, average_loss = 0.09360652, global_step = 2000, loss = 11.848927\n",
+      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: ./checkpoints_tutorial17-1/model.ckpt-2000\n"
      ]
     }
    ],
@@ -878,23 +604,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 21,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'accuracy': 0.9727,\n",
-       " 'average_loss': 0.093417682,\n",
+       "{'accuracy': 0.972,\n",
+       " 'average_loss': 0.09360652,\n",
        " 'global_step': 2000,\n",
-       " 'loss': 11.825023}"
+       " 'loss': 11.848927}"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -905,18 +627,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 22,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Classification accuracy: 97.27%\n"
+      "Classification accuracy: 97.20%\n"
      ]
     }
    ],
@@ -926,10 +644,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions\n",
     "\n",
@@ -942,12 +657,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "predictions = model.predict(input_fn=predict_input_fn)"
@@ -955,18 +666,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-1/model.ckpt-2000\n"
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
+      "INFO:tensorflow:Graph was finalized.\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-1/model.ckpt-2000\n",
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n"
      ]
     }
    ],
@@ -976,21 +688,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 25,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([7, 2, 1, 0, 4, 1, 4, 9, 5])"
+       "array([7, 2, 1, 0, 4, 1, 4, 9, 6])"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1002,18 +711,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0026103a20>"
+       "<matplotlib.figure.Figure at 0x7fcc65d22e48>"
       ]
      },
      "metadata": {},
@@ -1028,20 +733,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# New Estimator"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "If you cannot use one of the built-in Estimators, then you can create an arbitrary TensorFlow model yourself. To do this, you first need to create a function which defines the following:\n",
     "\n",
@@ -1058,12 +757,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def model_fn(features, labels, mode, params):\n",
@@ -1166,10 +861,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create an Instance of the Estimator\n",
     "\n",
@@ -1178,12 +870,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 28,
+   "metadata": {},
    "outputs": [],
    "source": [
     "params = {\"learning_rate\": 1e-4}"
@@ -1191,10 +879,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then create an instance of the new Estimator.\n",
     "\n",
@@ -1205,11 +890,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 29,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1218,7 +900,7 @@
      "output_type": "stream",
      "text": [
       "INFO:tensorflow:Using default config.\n",
-      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-2/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f00290fac88>, '_task_type': 'worker', '_task_id': 0, '_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
+      "INFO:tensorflow:Using config: {'_model_dir': './checkpoints_tutorial17-2/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fcc665c3208>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
      ]
     }
    ],
@@ -1230,10 +912,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -1242,11 +921,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 30,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1254,58 +930,63 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
       "INFO:tensorflow:Create CheckpointSaverHook.\n",
-      "INFO:tensorflow:Saving checkpoints for 1 into ./checkpoints_tutorial17-2/model.ckpt.\n",
-      "INFO:tensorflow:loss = 2.33444, step = 1\n",
-      "INFO:tensorflow:global_step/sec: 190.454\n",
-      "INFO:tensorflow:loss = 0.810317, step = 101 (0.527 sec)\n",
-      "INFO:tensorflow:global_step/sec: 198.129\n",
-      "INFO:tensorflow:loss = 0.349305, step = 201 (0.504 sec)\n",
-      "INFO:tensorflow:global_step/sec: 184.116\n",
-      "INFO:tensorflow:loss = 0.288062, step = 301 (0.543 sec)\n",
-      "INFO:tensorflow:global_step/sec: 195.138\n",
-      "INFO:tensorflow:loss = 0.0948148, step = 401 (0.512 sec)\n",
-      "INFO:tensorflow:global_step/sec: 199.116\n",
-      "INFO:tensorflow:loss = 0.203272, step = 501 (0.502 sec)\n",
-      "INFO:tensorflow:global_step/sec: 190.777\n",
-      "INFO:tensorflow:loss = 0.22347, step = 601 (0.524 sec)\n",
-      "INFO:tensorflow:global_step/sec: 198.669\n",
-      "INFO:tensorflow:loss = 0.161297, step = 701 (0.505 sec)\n",
-      "INFO:tensorflow:global_step/sec: 192.277\n",
-      "INFO:tensorflow:loss = 0.154663, step = 801 (0.518 sec)\n",
-      "INFO:tensorflow:global_step/sec: 158.865\n",
-      "INFO:tensorflow:loss = 0.136487, step = 901 (0.634 sec)\n",
-      "INFO:tensorflow:global_step/sec: 121.05\n",
-      "INFO:tensorflow:loss = 0.144933, step = 1001 (0.826 sec)\n",
-      "INFO:tensorflow:global_step/sec: 118.257\n",
-      "INFO:tensorflow:loss = 0.103951, step = 1101 (0.848 sec)\n",
-      "INFO:tensorflow:global_step/sec: 118.136\n",
-      "INFO:tensorflow:loss = 0.133236, step = 1201 (0.845 sec)\n",
-      "INFO:tensorflow:global_step/sec: 112.046\n",
-      "INFO:tensorflow:loss = 0.060983, step = 1301 (0.896 sec)\n",
-      "INFO:tensorflow:global_step/sec: 99.9212\n",
-      "INFO:tensorflow:loss = 0.0838628, step = 1401 (0.997 sec)\n",
-      "INFO:tensorflow:global_step/sec: 115.121\n",
-      "INFO:tensorflow:loss = 0.118691, step = 1501 (0.868 sec)\n",
-      "INFO:tensorflow:global_step/sec: 96.8269\n",
-      "INFO:tensorflow:loss = 0.179758, step = 1601 (1.038 sec)\n",
-      "INFO:tensorflow:global_step/sec: 99.8103\n",
-      "INFO:tensorflow:loss = 0.0996531, step = 1701 (0.998 sec)\n",
-      "INFO:tensorflow:global_step/sec: 128.677\n",
-      "INFO:tensorflow:loss = 0.097964, step = 1801 (0.775 sec)\n",
-      "INFO:tensorflow:global_step/sec: 124.224\n",
-      "INFO:tensorflow:loss = 0.086759, step = 1901 (0.806 sec)\n",
+      "INFO:tensorflow:Graph was finalized.\n",
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n",
+      "INFO:tensorflow:Saving checkpoints for 0 into ./checkpoints_tutorial17-2/model.ckpt.\n",
+      "INFO:tensorflow:loss = 2.328683303358867, step = 0\n",
+      "INFO:tensorflow:global_step/sec: 30.0746\n",
+      "INFO:tensorflow:loss = 1.0425889833487076, step = 100 (3.326 sec)\n",
+      "INFO:tensorflow:global_step/sec: 30.7697\n",
+      "INFO:tensorflow:loss = 0.4519329631053862, step = 200 (3.250 sec)\n",
+      "INFO:tensorflow:global_step/sec: 30.5945\n",
+      "INFO:tensorflow:loss = 0.28173916577119856, step = 300 (3.269 sec)\n",
+      "INFO:tensorflow:global_step/sec: 30.3772\n",
+      "INFO:tensorflow:loss = 0.41579200542133726, step = 400 (3.292 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.44\n",
+      "INFO:tensorflow:loss = 0.2537537261934676, step = 500 (3.181 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.2734\n",
+      "INFO:tensorflow:loss = 0.2306796091927107, step = 600 (3.103 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.4727\n",
+      "INFO:tensorflow:loss = 0.16169791614095563, step = 700 (3.075 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.9575\n",
+      "INFO:tensorflow:loss = 0.24491770370504626, step = 800 (3.034 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.4056\n",
+      "INFO:tensorflow:loss = 0.1723769961825516, step = 900 (3.185 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.8268\n",
+      "INFO:tensorflow:loss = 0.0865023047044578, step = 1000 (3.142 sec)\n",
+      "INFO:tensorflow:global_step/sec: 33.1043\n",
+      "INFO:tensorflow:loss = 0.08865380930537742, step = 1100 (3.021 sec)\n",
+      "INFO:tensorflow:global_step/sec: 33.0132\n",
+      "INFO:tensorflow:loss = 0.09500106271291871, step = 1200 (3.029 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.2879\n",
+      "INFO:tensorflow:loss = 0.048251991971276796, step = 1300 (3.097 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.4468\n",
+      "INFO:tensorflow:loss = 0.0965478484811222, step = 1400 (3.082 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.0871\n",
+      "INFO:tensorflow:loss = 0.06810141978839185, step = 1500 (3.217 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.6667\n",
+      "INFO:tensorflow:loss = 0.13537004696386645, step = 1600 (3.158 sec)\n",
+      "INFO:tensorflow:global_step/sec: 31.98\n",
+      "INFO:tensorflow:loss = 0.08716099232839157, step = 1700 (3.127 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.1884\n",
+      "INFO:tensorflow:loss = 0.06138957874514458, step = 1800 (3.107 sec)\n",
+      "INFO:tensorflow:global_step/sec: 32.1328\n",
+      "INFO:tensorflow:loss = 0.11381113679326431, step = 1900 (3.113 sec)\n",
       "INFO:tensorflow:Saving checkpoints for 2000 into ./checkpoints_tutorial17-2/model.ckpt.\n",
-      "INFO:tensorflow:Loss for final step: 0.0712585.\n"
+      "INFO:tensorflow:Loss for final step: 0.09910375161965862.\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.estimator.estimator.Estimator at 0x7f0026148f98>"
+       "<tensorflow.python.estimator.estimator.Estimator at 0x7fcc665c3a58>"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1316,10 +997,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -1328,11 +1006,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 31,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1340,10 +1015,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INFO:tensorflow:Starting evaluation at 2017-11-17-12:08:18\n",
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
+      "INFO:tensorflow:Starting evaluation at 2018-07-16-11:24:18\n",
+      "INFO:tensorflow:Graph was finalized.\n",
       "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-2/model.ckpt-2000\n",
-      "INFO:tensorflow:Finished evaluation at 2017-11-17-12:08:18\n",
-      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9761, global_step = 2000, loss = 0.0760049\n"
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n",
+      "INFO:tensorflow:Finished evaluation at 2018-07-16-11:24:20\n",
+      "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9769, global_step = 2000, loss = 0.0701695\n",
+      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: ./checkpoints_tutorial17-2/model.ckpt-2000\n"
      ]
     }
    ],
@@ -1353,20 +1034,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 32,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'accuracy': 0.97610003, 'global_step': 2000, 'loss': 0.076004863}"
+       "{'accuracy': 0.9769, 'global_step': 2000, 'loss': 0.0701695}"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1377,18 +1054,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Classification accuracy: 97.61%\n"
+      "Classification accuracy: 97.69%\n"
      ]
     }
    ],
@@ -1398,10 +1071,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions\n",
     "\n",
@@ -1410,11 +1080,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 34,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -1424,18 +1091,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-2/model.ckpt-2000\n"
+      "INFO:tensorflow:Calling model_fn.\n",
+      "INFO:tensorflow:Done calling model_fn.\n",
+      "INFO:tensorflow:Graph was finalized.\n",
+      "INFO:tensorflow:Restoring parameters from ./checkpoints_tutorial17-2/model.ckpt-2000\n",
+      "INFO:tensorflow:Running local_init_op.\n",
+      "INFO:tensorflow:Done running local_init_op.\n"
      ]
     },
     {
@@ -1444,7 +1112,7 @@
        "array([7, 2, 1, 0, 4, 1, 4, 9, 5])"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1456,18 +1124,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "execution_count": 36,
+   "metadata": {},
    "outputs": [
     {
      "data": {
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0026645d68>"
+       "<matplotlib.figure.Figure at 0x7fcbfbb44a90>"
       ]
      },
      "metadata": {},
@@ -1482,10 +1146,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -1501,10 +1162,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -1526,10 +1184,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -1564,5 +1219,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/README.md b/README.md
index 43ac0b4..dbbbfde 100644
--- a/README.md
+++ b/README.md
@@ -17,7 +17,7 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 2. Convolutional Neural Network ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
 
-3. Pretty Tensor ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
+3. ~~Pretty Tensor~~ ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
 
 3-B. Layers API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
 
@@ -69,6 +69,14 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
 
+## Obsolete Tutorials
+
+Some of these tutorials use an API called PrettyTensor for creating
+Neural Networks in TensorFlow, but the PrettyTensor API is now obsolete.
+Some of the Notebooks are therefore also obsolete and they are clearly
+marked at the top of each Notebook. It is recommended that you
+instead use the Keras API for creating Neural Networks in TensorFlow.
+
 ## Translations
 
 These tutorials have been translated to the following languages:
diff --git a/download.py b/download.py
index 676abc5..57bec13 100644
--- a/download.py
+++ b/download.py
@@ -34,6 +34,9 @@ def _print_download_progress(count, block_size, total_size):
     # Percentage completion.
     pct_complete = float(count * block_size) / total_size
 
+    # Limit it because rounding errors may cause it to exceed 100%.
+    pct_complete = min(1.0, pct_complete)
+
     # Status-message. Note the \r which means the line should overwrite itself.
     msg = "\r- Download progress: {0:.1%}".format(pct_complete)
 
@@ -44,6 +47,35 @@ def _print_download_progress(count, block_size, total_size):
 
 ########################################################################
 
+def download(base_url, filename, download_dir):
+    """
+    Download the given file if it does not already exist in the download_dir.
+
+    :param base_url: The internet URL without the filename.
+    :param filename: The filename that will be added to the base_url.
+    :param download_dir: Local directory for storing the file.
+    :return: Nothing.
+    """
+
+    # Path for local file.
+    save_path = os.path.join(download_dir, filename)
+
+    # Check if the file already exists, otherwise we need to download it now.
+    if not os.path.exists(save_path):
+        # Check if the download directory exists, otherwise create it.
+        if not os.path.exists(download_dir):
+            os.makedirs(download_dir)
+
+        print("Downloading", filename, "...")
+
+        # Download the file from the internet.
+        url = base_url + filename
+        file_path, _ = urllib.request.urlretrieve(url=url,
+                                                  filename=save_path,
+                                                  reporthook=_print_download_progress)
+
+        print(" Done!")
+
 
 def maybe_download_and_extract(url, download_dir):
     """
diff --git a/reinforcement_learning.py b/reinforcement_learning.py
index 3805ab2..357ea7d 100644
--- a/reinforcement_learning.py
+++ b/reinforcement_learning.py
@@ -7,7 +7,7 @@
 # To train a Neural Network for playing the Atari game Breakout,
 # run the following command in a terminal window.
 #
-# python reinforcement-learning.py --env 'Breakout-v0' --training
+# python reinforcement_learning.py --env 'Breakout-v0' --training
 #
 # The agent should start to improve after a few hours, but a full
 # training run required 150 hours on a 2.6 GHz CPU and GTX 1070 GPU.
@@ -18,14 +18,13 @@
 # Once the Neural Network has been trained, you can test it and
 # watch it play the game by running this command in the terminal:
 #
-# python reinforcement-learning.py --env 'Breakout-v0' --render --episodes 2
+# python reinforcement_learning.py --env 'Breakout-v0' --render --episodes 2
 #
 # Requirements:
 #
 # - Python 3.6 (Python 2.7 may not work)
 # - TensorFlow 1.1.0
 # - OpenAI Gym 0.8.1
-# - PrettyTensor 0.7.4 (not required if you use tf.layers instead)
 #
 # Summary:
 #
@@ -165,7 +164,6 @@
 import time
 import csv
 import argparse
-import download
 
 ########################################################################
 # File-paths are global variables for convenience so they don't
@@ -216,29 +214,6 @@ def update_paths(env_name):
     # File-path for the log-file for Q-values.
     log_q_values_path = os.path.join(checkpoint_dir, "log_q_values.txt")
 
-########################################################################
-# Download TensorFlow checkpoints.
-
-# URL's for the checkpoint-files.
-_checkpoint_url = {
-    "Breakout-v0": "http://hvass-labs.org/projects/tensorflow/tutorial16/Breakout-v0.tar.gz",
-    "SpaceInvaders-v0": "http://hvass-labs.org/projects/tensorflow/tutorial16/SpaceInvaders-v0.tar.gz"
-}
-
-
-def maybe_download_checkpoint(env_name):
-    """
-    Download and extract the TensorFlow checkpoint for the given
-    environment-name, if it does not already exist in checkpoint_base_dir.
-    You should first set this dir and call update_paths().
-    """
-
-    # Get the url for the game-environment.
-    url = _checkpoint_url[env_name]
-
-    # Download and extract the file if it does not already exist.
-    download.maybe_download_and_extract(url=url,
-                                        download_dir=checkpoint_base_dir)
 
 ########################################################################
 # Classes used for logging data during training.
@@ -1100,23 +1075,15 @@ class NeuralNetwork:
     better at estimating the Q-values.
     """
 
-    def __init__(self, num_actions, replay_memory, use_pretty_tensor=True):
+    def __init__(self, num_actions, replay_memory):
         """
         :param num_actions:
             Number of discrete actions for the game-environment.
 
         :param replay_memory: 
             Object-instance of the ReplayMemory-class.
-
-        :param use_pretty_tensor:
-            Boolean whether to use PrettyTensor (True) which must then be
-            installed, or use the tf.layers API (False) which is already
-            built into TensorFlow.
         """
 
-        # Whether to use the PrettyTensor API (True) or tf.layers (False).
-        self.use_pretty_tensor = use_pretty_tensor
-
         # Replay-memory used for sampling random batches.
         self.replay_memory = replay_memory
 
@@ -1187,115 +1154,80 @@ def __init__(self, num_actions, replay_memory, use_pretty_tensor=True):
         # You can experiment with values between 1e-2 and 1e-3.
         init = tf.truncated_normal_initializer(mean=0.0, stddev=2e-2)
 
-        if self.use_pretty_tensor:
-            # This builds the Neural Network using the PrettyTensor API,
-            # which is a very elegant builder API, but some people are
-            # having problems installing and using it.
-
-            import prettytensor as pt
-
-            # Wrap the input to the Neural Network in a PrettyTensor object.
-            x_pretty = pt.wrap(self.x)
-
-            # Create the convolutional Neural Network using Pretty Tensor.
-            with pt.defaults_scope(activation_fn=tf.nn.relu):
-                self.q_values = x_pretty. \
-                    conv2d(kernel=3, depth=16, stride=2, name='layer_conv1', weights=init). \
-                    conv2d(kernel=3, depth=32, stride=2, name='layer_conv2', weights=init). \
-                    conv2d(kernel=3, depth=64, stride=1, name='layer_conv3', weights=init). \
-                    flatten(). \
-                    fully_connected(size=1024, name='layer_fc1', weights=init). \
-                    fully_connected(size=1024, name='layer_fc2', weights=init). \
-                    fully_connected(size=1024, name='layer_fc3', weights=init). \
-                    fully_connected(size=1024, name='layer_fc4', weights=init). \
-                    fully_connected(size=num_actions, name='layer_fc_out', weights=init,
-                                    activation_fn=None)
-
-            # Loss-function which must be optimized. This is the mean-squared
-            # error between the Q-values that are output by the Neural Network
-            # and the target Q-values.
-            self.loss = self.q_values.l2_regression(target=self.q_values_new)
-        else:
-            # This builds the Neural Network using the tf.layers API,
-            # which is very verbose and inelegant, but should work for everyone.
-
-            # Note that the checkpoints for Tutorial #16 which can be
-            # downloaded from the internet only support PrettyTensor.
-            # Although the Neural Networks appear to be identical when
-            # built using the PrettyTensor and tf.layers APIs,
-            # they actually create somewhat different TensorFlow graphs
-            # where the variables have different names, which means the
-            # checkpoints are incompatible for the two builder APIs.
-
-            # Padding used for the convolutional layers.
-            padding = 'SAME'
-
-            # Activation function for all convolutional and fully-connected
-            # layers, except the last.
-            activation = tf.nn.relu
-
-            # Reference to the lastly added layer of the Neural Network.
-            # This makes it easy to add or remove layers.
-            net = self.x
-
-            # First convolutional layer.
-            net = tf.layers.conv2d(inputs=net, name='layer_conv1',
-                                   filters=16, kernel_size=3, strides=2,
-                                   padding=padding,
-                                   kernel_initializer=init, activation=activation)
-
-            # Second convolutional layer.
-            net = tf.layers.conv2d(inputs=net, name='layer_conv2',
-                                   filters=32, kernel_size=3, strides=2,
-                                   padding=padding,
-                                   kernel_initializer=init, activation=activation)
-
-            # Third convolutional layer.
-            net = tf.layers.conv2d(inputs=net, name='layer_conv3',
-                                   filters=64, kernel_size=3, strides=1,
-                                   padding=padding,
-                                   kernel_initializer=init, activation=activation)
-
-            # Flatten output of the last convolutional layer so it can
-            # be input to a fully-connected (aka. dense) layer.
-            # TODO: For some bizarre reason, this function is not yet in tf.layers
-            # TODO: net = tf.layers.flatten(net)
-            net = tf.contrib.layers.flatten(net)
-
-            # First fully-connected (aka. dense) layer.
-            net = tf.layers.dense(inputs=net, name='layer_fc1', units=1024,
-                                  kernel_initializer=init, activation=activation)
-
-            # Second fully-connected layer.
-            net = tf.layers.dense(inputs=net, name='layer_fc2', units=1024,
-                                  kernel_initializer=init, activation=activation)
-
-            # Third fully-connected layer.
-            net = tf.layers.dense(inputs=net, name='layer_fc3', units=1024,
-                                  kernel_initializer=init, activation=activation)
-
-            # Fourth fully-connected layer.
-            net = tf.layers.dense(inputs=net, name='layer_fc4', units=1024,
-                                  kernel_initializer=init, activation=activation)
-
-            # Final fully-connected layer.
-            net = tf.layers.dense(inputs=net, name='layer_fc_out', units=num_actions,
-                                  kernel_initializer=init, activation=None)
-
-            # The output of the Neural Network is the estimated Q-values
-            # for each possible action in the game-environment.
-            self.q_values = net
-
-            # TensorFlow has a built-in loss-function for doing regression:
-            # self.loss = tf.nn.l2_loss(self.q_values - self.q_values_new)
-            # But it uses tf.reduce_sum() rather than tf.reduce_mean()
-            # which is used by PrettyTensor. This means the scale of the
-            # gradient is different and hence the hyper-parameters
-            # would have to be re-tuned. So instead we calculate the
-            # L2-loss similarly to how it is done in PrettyTensor.
-            squared_error = tf.square(self.q_values - self.q_values_new)
-            sum_squared_error = tf.reduce_sum(squared_error, axis=1)
-            self.loss = tf.reduce_mean(sum_squared_error)
+        # This builds the Neural Network using the tf.layers API,
+        # which is very verbose and inelegant, but should work for everyone.
+
+        # Padding used for the convolutional layers.
+        padding = 'SAME'
+
+        # Activation function for all convolutional and fully-connected
+        # layers, except the last.
+        activation = tf.nn.relu
+
+        # Reference to the lastly added layer of the Neural Network.
+        # This makes it easy to add or remove layers.
+        net = self.x
+
+        # First convolutional layer.
+        net = tf.layers.conv2d(inputs=net, name='layer_conv1',
+                               filters=16, kernel_size=3, strides=2,
+                               padding=padding,
+                               kernel_initializer=init, activation=activation)
+
+        # Second convolutional layer.
+        net = tf.layers.conv2d(inputs=net, name='layer_conv2',
+                               filters=32, kernel_size=3, strides=2,
+                               padding=padding,
+                               kernel_initializer=init, activation=activation)
+
+        # Third convolutional layer.
+        net = tf.layers.conv2d(inputs=net, name='layer_conv3',
+                               filters=64, kernel_size=3, strides=1,
+                               padding=padding,
+                               kernel_initializer=init, activation=activation)
+
+        # Flatten output of the last convolutional layer so it can
+        # be input to a fully-connected (aka. dense) layer.
+        # TODO: For some bizarre reason, this function is not yet in tf.layers
+        # TODO: net = tf.layers.flatten(net)
+        net = tf.contrib.layers.flatten(net)
+
+        # First fully-connected (aka. dense) layer.
+        net = tf.layers.dense(inputs=net, name='layer_fc1', units=1024,
+                              kernel_initializer=init, activation=activation)
+
+        # Second fully-connected layer.
+        net = tf.layers.dense(inputs=net, name='layer_fc2', units=1024,
+                              kernel_initializer=init, activation=activation)
+
+        # Third fully-connected layer.
+        net = tf.layers.dense(inputs=net, name='layer_fc3', units=1024,
+                              kernel_initializer=init, activation=activation)
+
+        # Fourth fully-connected layer.
+        net = tf.layers.dense(inputs=net, name='layer_fc4', units=1024,
+                              kernel_initializer=init, activation=activation)
+
+        # Final fully-connected layer.
+        net = tf.layers.dense(inputs=net, name='layer_fc_out', units=num_actions,
+                              kernel_initializer=init, activation=None)
+
+        # The output of the Neural Network is the estimated Q-values
+        # for each possible action in the game-environment.
+        self.q_values = net
+
+        # TensorFlow has a built-in loss-function for doing regression:
+        # self.loss = tf.nn.l2_loss(self.q_values - self.q_values_new)
+        # But it uses tf.reduce_sum() rather than tf.reduce_mean()
+        # which is used by PrettyTensor. This means the scale of the
+        # gradient is different and hence the hyper-parameters
+        # would have to be re-tuned, because they were tuned for
+        # the original version of this tutorial using PrettyTensor.
+        # So instead we calculate the L2-loss similarly to how it is
+        # done in PrettyTensor.
+        squared_error = tf.square(self.q_values - self.q_values_new)
+        sum_squared_error = tf.reduce_sum(squared_error, axis=1)
+        self.loss = tf.reduce_mean(sum_squared_error)
 
         # Optimizer used for minimizing the loss-function.
         # Note the learning-rate is a placeholder variable so we can
@@ -1480,12 +1412,8 @@ def get_weights_variable(self, layer_name):
         you must use the function get_variable_value() for that.
         """
 
-        if self.use_pretty_tensor:
-            # PrettyTensor uses this name for the weights in a conv-layer.
-            variable_name = 'weights'
-        else:
-            # The tf.layers API uses this name for the weights in a conv-layer.
-            variable_name = 'kernel'
+        # The tf.layers API uses this name for the weights in a conv-layer.
+        variable_name = 'kernel'
 
         with tf.variable_scope(layer_name, reuse=True):
             variable = tf.get_variable(variable_name)
diff --git a/requirements.txt b/requirements.txt
index 43c0e28..e730721 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -29,14 +29,18 @@ scikit-learn
 tensorflow		# CPU Version of TensorFlow.
 # tensorflow-gpu	# GPU version of TensorFlow.
 
-# Builder API for TensorFlow used in many of the tutorials.
-prettytensor
-
 ################################################################
-# The tutorial on Reinforcement Learning uses OpenAI Gym.
-# Uncomment this line if you want to run that tutorial.
+# Some tutorials use other individual Python packages.
+# Uncomment the relevant lines for the tutorials you want to run.
 
-# gym[atari]
+# gym[atari]  # Tutorial #16 on Reinforcement Learning.
+# pandas      # Tutorial #23 on Time-Series Prediction.
 
 ################################################################
+# PrettyTensor was used as the builder API for several of the
+# earlier tutorials. PrettyTensor is apparently no longer being
+# maintained and may not work with newer versions of TensorFlow.
+
+# prettytensor
 
+################################################################

From 60c5c46d8223ed7de669448988e06ef1278a9641 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 16 Jul 2018 15:14:02 +0200
Subject: [PATCH 46/61] Added mnist.py

---
 mnist.py | 186 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 186 insertions(+)
 create mode 100644 mnist.py

diff --git a/mnist.py b/mnist.py
new file mode 100644
index 0000000..6b7bbb4
--- /dev/null
+++ b/mnist.py
@@ -0,0 +1,186 @@
+########################################################################
+#
+# Downloads the MNIST data-set for recognizing hand-written digits.
+#
+# Implemented in Python 3.6
+#
+# Usage:
+# 1) Create a new object instance: data = MNIST(data_dir="data/MNIST/")
+#    This automatically downloads the files to the given dir.
+# 2) Use the training-set as data.x_train, data.y_train and data.y_train_cls
+# 3) Get random batches of training data using data.random_batch()
+# 4) Use the test-set as data.x_test, data.y_test and data.y_test_cls
+#
+########################################################################
+#
+# This file is part of the TensorFlow Tutorials available at:
+#
+# https://github.com/Hvass-Labs/TensorFlow-Tutorials
+#
+# Published under the MIT License. See the file LICENSE for details.
+#
+# Copyright 2016-18 by Magnus Erik Hvass Pedersen
+#
+########################################################################
+
+import numpy as np
+import gzip
+import os
+from dataset import one_hot_encoded
+from download import download
+
+########################################################################
+
+# Base URL for downloading the data-files from the internet.
+base_url = "https://storage.googleapis.com/cvdf-datasets/mnist/"
+
+# Filenames for the data-set.
+filename_x_train = "train-images-idx3-ubyte.gz"
+filename_y_train = "train-labels-idx1-ubyte.gz"
+filename_x_test = "t10k-images-idx3-ubyte.gz"
+filename_y_test = "t10k-labels-idx1-ubyte.gz"
+
+########################################################################
+
+
+class MNIST:
+    """
+    The MNIST data-set for recognizing hand-written digits.
+    This automatically downloads the data-files if they do
+    not already exist in the local data_dir.
+
+    Note: Pixel-values are floats between 0.0 and 1.0.
+    """
+
+    # The images are 28 pixels in each dimension.
+    img_size = 28
+
+    # The images are stored in one-dimensional arrays of this length.
+    img_size_flat = img_size * img_size
+
+    # Tuple with height and width of images used to reshape arrays.
+    img_shape = (img_size, img_size)
+
+    # Number of colour channels for the images: 1 channel for gray-scale.
+    num_channels = 1
+
+    # Tuple with height, width and depth used to reshape arrays.
+    # This is used for reshaping in Keras.
+    img_shape_full = (img_size, img_size, num_channels)
+
+    # Number of classes, one class for each of 10 digits.
+    num_classes = 10
+
+    def __init__(self, data_dir="data/MNIST/"):
+        """
+        Load the MNIST data-set. Automatically downloads the files
+        if they do not already exist locally.
+
+        :param data_dir: Base-directory for downloading files.
+        """
+
+        # Copy args to self.
+        self.data_dir = data_dir
+
+        # Number of images in each sub-set.
+        self.num_train = 55000
+        self.num_val = 5000
+        self.num_test = 10000
+
+        # Download / load the training-set.
+        x_train = self._load_images(filename=filename_x_train)
+        y_train_cls = self._load_cls(filename=filename_y_train)
+
+        # Split the training-set into train / validation.
+        # Pixel-values are converted from ints between 0 and 255
+        # to floats between 0.0 and 1.0.
+        self.x_train = x_train[0:self.num_train] / 255.0
+        self.x_val = x_train[self.num_train:] / 255.0
+        self.y_train_cls = y_train_cls[0:self.num_train]
+        self.y_val_cls = y_train_cls[self.num_train:]
+
+        # Download / load the test-set.
+        self.x_test = self._load_images(filename=filename_x_test) / 255.0
+        self.y_test_cls = self._load_cls(filename=filename_y_test)
+
+        # Convert the class-numbers from bytes to ints as that is needed
+        # some places in TensorFlow.
+        self.y_train_cls = self.y_train_cls.astype(np.int)
+        self.y_val_cls = self.y_val_cls.astype(np.int)
+        self.y_test_cls = self.y_test_cls.astype(np.int)
+
+        # Convert the integer class-numbers into one-hot encoded arrays.
+        self.y_train = one_hot_encoded(class_numbers=self.y_train_cls,
+                                       num_classes=self.num_classes)
+        self.y_val = one_hot_encoded(class_numbers=self.y_val_cls,
+                                     num_classes=self.num_classes)
+        self.y_test = one_hot_encoded(class_numbers=self.y_test_cls,
+                                      num_classes=self.num_classes)
+
+    def _load_data(self, filename, offset):
+        """
+        Load the data in the given file. Automatically downloads the file
+        if it does not already exist in the data_dir.
+
+        :param filename: Name of the data-file.
+        :param offset: Start offset in bytes when reading the data-file.
+        :return: The data as a numpy array.
+        """
+
+        # Download the file from the internet if it does not exist locally.
+        download(base_url=base_url, filename=filename, download_dir=self.data_dir)
+
+        # Read the data-file.
+        path = os.path.join(self.data_dir, filename)
+        with gzip.open(path, 'rb') as f:
+            data = np.frombuffer(f.read(), np.uint8, offset=offset)
+
+        return data
+
+    def _load_images(self, filename):
+        """
+        Load image-data from the given file.
+        Automatically downloads the file if it does not exist locally.
+
+        :param filename: Name of the data-file.
+        :return: Numpy array.
+        """
+
+        # Read the data as one long array of bytes.
+        data = self._load_data(filename=filename, offset=16)
+
+        # Reshape to 2-dim array with shape (num_images, img_size_flat).
+        images_flat = data.reshape(-1, self.img_size_flat)
+
+        return images_flat
+
+    def _load_cls(self, filename):
+        """
+        Load class-numbers from the given file.
+        Automatically downloads the file if it does not exist locally.
+
+        :param filename: Name of the data-file.
+        :return: Numpy array.
+        """
+        return self._load_data(filename=filename, offset=8)
+
+    def random_batch(self, batch_size=32):
+        """
+        Create a random batch of training-data.
+
+        :param batch_size: Number of images in the batch.
+        :return: 3 numpy arrays (x, y, y_cls)
+        """
+
+        # Create a random index into the training-set.
+        idx = np.random.randint(low=0, high=self.num_train, size=batch_size)
+
+        # Use the index to lookup random training-data.
+        x_batch = self.x_train[idx]
+        y_batch = self.y_train[idx]
+        y_batch_cls = self.y_train_cls[idx]
+
+        return x_batch, y_batch, y_batch_cls
+
+
+########################################################################

From 46e2d865e45c14f374a4a256947ff1062629ec68 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 16 Jul 2018 15:35:09 +0200
Subject: [PATCH 47/61] Tiny fix.

---
 requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements.txt b/requirements.txt
index e730721..9c32b92 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,6 +7,7 @@
 # Python packages by running the following commands in a shell:
 #
 #     conda create --name tf python=3
+#     source activate tf
 #     pip install -r requirements.txt
 #
 # Note that you have to edit this file to select whether you

From 8d2e0eee5c680dd028b302ee1ac74c3ae8077700 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Fri, 20 Jul 2018 18:09:21 +0200
Subject: [PATCH 48/61] Updated to TensorFlow 1.9

---
 12_Adversarial_Noise_MNIST.ipynb | 1544 +++++++++++++-----------------
 1 file changed, 678 insertions(+), 866 deletions(-)

diff --git a/12_Adversarial_Noise_MNIST.ipynb b/12_Adversarial_Noise_MNIST.ipynb
index 6a11e12..ab3473a 100644
--- a/12_Adversarial_Noise_MNIST.ipynb
+++ b/12_Adversarial_Noise_MNIST.ipynb
@@ -43,6 +43,8 @@
    "source": [
     "The following chart shows roughly how the data flows in the Convolutional Neural Network that is implemented below.\n",
     "\n",
+    "![Flowchart](images/12_adversarial_noise_flowchart.png)\n",
+    "\n",
     "This example shows an input image with a hand-written 7-digit. The adversarial noise is then added to the image. Red noise-pixels are positive and make the input image darker in those pixels, while blue noise-pixels are negative and make the input lighter in those pixels.\n",
     "\n",
     "The noisy image is then fed to the neural network which results in a predicted class-number. In this case the adversarial noise fools the network into believing that the 7-digit shows a 3-digit. The noise is clearly visible to humans, but the 7-digit is still easily identified by a human.\n",
@@ -54,31 +56,6 @@
     "The two optimization procedures are completely separate. The first procedure only modifies the variables of the neural network, while the second procedure only modifies the adversarial noise."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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OrWrYsh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\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pOIiIjEDfvn3xwQcfAAA0Gg2GDh2KrKwswamIiIiIDEtCQgLy8vJExyAiolJIrVZj4sSJ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\ndOv5sFgsHj9+SZCZmen2F+dBQUHO9yA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ARc2ox02S9u/f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\nzm0ZTjBIRI5y/vx5+Pr6OjoMIiJygOTkZEeHQEQCnDdJvF49YNQooFEjwNw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qKiqyKLNq1SoNGjRIP/30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AAAAAAApIgkcQAAAAAAAAAAAAAAAAAAgBSRJA4AAAAAAAAAAAAAAAAAAJAiksQBAAAA\nAAAAAAAAAAAAAABSRJI4AAAAAAAAAAAAAAAAAABAikgSBwAAAAAAAAAAAAAAAAAASBFJ4gAAAAAA\nAAAAAAAAAAAAACkiSRwAAAAAAAAAAAAAAAAAACBFJIkDAAAAAAAAAAAAAAAAAACkiCRxAAAAAAAA\nAAAAAAAAAACAFJEkDgAAAAAAAAAAAAAAAAAAkCKSxAEAAAAAAAAAAAAAAAAAAFJEkjgAAAAAAAAA\nAAAAAAAAAECKFEXEhnwHAQAAAAAAAAAAAAAAAAAAQI1s/T+kmVVl4pDteQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from IPython.display import Image\n",
-    "Image('images/12_adversarial_noise_flowchart.png')"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -88,11 +65,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  from ._conv import register_converters as _register_converters\n"
+     ]
+    }
+   ],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -101,68 +85,34 @@
     "from sklearn.metrics import confusion_matrix\n",
     "import time\n",
     "from datetime import timedelta\n",
-    "import math\n",
-    "\n",
-    "# We also need PrettyTensor.\n",
-    "import prettytensor as pt"
+    "import math"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
+    "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'0.12.0-rc0'"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tf.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 2,
    "metadata": {},
-   "source": [
-    "PrettyTensor version:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'0.7.1'"
+       "'1.9.0'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pt.__version__"
+    "tf.__version__"
    ]
   },
   {
@@ -181,40 +131,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -222,72 +157,45 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 5,
    "metadata": {},
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": true
-   },
    "outputs": [],
    "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
     "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
     "\n",
     "# Tuple with height and width of images used to reshape arrays.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
+    "img_shape = data.img_shape\n",
     "\n",
     "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
@@ -306,10 +214,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None, noise=0.0):\n",
@@ -360,16 +266,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2059353828>"
+       "<matplotlib.figure.Figure at 0x7f5e636b45f8>"
       ]
      },
      "metadata": {},
@@ -378,10 +282,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -421,10 +325,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')"
@@ -439,10 +341,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])"
@@ -457,10 +357,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 10,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
@@ -475,13 +373,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_true_cls = tf.argmax(y_true, dimension=1)"
+    "y_true_cls = tf.argmax(y_true, axis=1)"
    ]
   },
   {
@@ -502,10 +398,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 12,
+   "metadata": {},
    "outputs": [],
    "source": [
     "noise_limit = 0.35"
@@ -522,10 +416,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
     "noise_l2_weight = 0.02"
@@ -542,10 +434,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [],
    "source": [
     "ADVERSARY_VARIABLES = 'adversary_variables'"
@@ -560,13 +450,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 15,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "collections = [tf.GraphKeys.VARIABLES, ADVERSARY_VARIABLES]"
+    "collections = [tf.GraphKeys.GLOBAL_VARIABLES, ADVERSARY_VARIABLES]"
    ]
   },
   {
@@ -578,10 +466,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 16,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_noise = tf.Variable(tf.zeros([img_size, img_size, num_channels]),\n",
@@ -599,10 +485,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 17,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_noise_clip = tf.assign(x_noise, tf.clip_by_value(x_noise,\n",
@@ -619,10 +503,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_noisy_image = x_image + x_noise"
@@ -637,10 +519,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [],
    "source": [
     "x_noisy_image = tf.clip_by_value(x_noisy_image, 0.0, 1.0)"
@@ -657,51 +537,50 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will use PrettyTensor to construct the convolutional neural network. First we need to wrap the tensor for the noisy image in a PrettyTensor-object, which provides functions that construct the neural network."
+    "We will use the Layers API to construct the convolutional neural network, see Tutorial #03-B."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "x_pretty = pt.wrap(x_noisy_image)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 20,
    "metadata": {},
-   "source": [
-    "Now that we have wrapped the input image in a PrettyTensor object, we can add the convolutional and fully-connected layers in just a few lines of source-code."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": true
-   },
    "outputs": [],
    "source": [
-    "with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
-    "    y_pred, loss = x_pretty.\\\n",
-    "        conv2d(kernel=5, depth=16, name='layer_conv1').\\\n",
-    "        max_pool(kernel=2, stride=2).\\\n",
-    "        conv2d(kernel=5, depth=36, name='layer_conv2').\\\n",
-    "        max_pool(kernel=2, stride=2).\\\n",
-    "        flatten().\\\n",
-    "        fully_connected(size=128, name='layer_fc1').\\\n",
-    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Note that `pt.defaults_scope(activation_fn=tf.nn.relu)` makes `activation_fn=tf.nn.relu` an argument for each of the layers constructed inside the `with`-block, so that Rectified Linear Units (ReLU) are used for each of these layers. The `defaults_scope` makes it easy to change arguments for all of the layers."
+    "# Start the network with the noisy input image.\n",
+    "net = x_noisy_image\n",
+    "\n",
+    "# 1st convolutional layer.\n",
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv1', padding='same',\n",
+    "                       filters=16, kernel_size=5, activation=tf.nn.relu)\n",
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)\n",
+    "\n",
+    "# 2nd convolutional layer.\n",
+    "net = tf.layers.conv2d(inputs=net, name='layer_conv2', padding='same',\n",
+    "                       filters=36, kernel_size=5, activation=tf.nn.relu)\n",
+    "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)\n",
+    "\n",
+    "# Flatten layer.This should eventually be replaced by:\n",
+    "# net = tf.layers.flatten(net)\n",
+    "net = tf.contrib.layers.flatten(net)\n",
+    "\n",
+    "# 1st fully-connected / dense layer.\n",
+    "net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
+    "                      units=128, activation=tf.nn.relu)\n",
+    "\n",
+    "# 2nd fully-connected / dense layer.\n",
+    "net = tf.layers.dense(inputs=net, name='layer_fc_out',\n",
+    "                      units=num_classes, activation=None)\n",
+    "\n",
+    "# Unscaled output of the network.\n",
+    "logits = net\n",
+    "\n",
+    "# Softmax output of the network.\n",
+    "y_pred = tf.nn.softmax(logits=logits)\n",
+    "\n",
+    "# Loss measure to be optimized.\n",
+    "cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(labels=y_true,\n",
+    "                                                           logits=logits)\n",
+    "loss = tf.reduce_mean(cross_entropy)"
    ]
   },
   {
@@ -720,26 +599,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 21,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['layer_conv1/weights:0',\n",
+       "['layer_conv1/kernel:0',\n",
        " 'layer_conv1/bias:0',\n",
-       " 'layer_conv2/weights:0',\n",
+       " 'layer_conv2/kernel:0',\n",
        " 'layer_conv2/bias:0',\n",
-       " 'layer_fc1/weights:0',\n",
+       " 'layer_fc1/kernel:0',\n",
        " 'layer_fc1/bias:0',\n",
-       " 'fully_connected/weights:0',\n",
-       " 'fully_connected/bias:0']"
+       " 'layer_fc_out/kernel:0',\n",
+       " 'layer_fc_out/bias:0']"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -759,10 +637,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 22,
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
@@ -784,10 +660,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "adversary_variables = tf.get_collection(ADVERSARY_VARIABLES)"
@@ -802,9 +676,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 24,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -814,7 +687,7 @@
        "['x_noise:0']"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -834,10 +707,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 25,
+   "metadata": {},
    "outputs": [],
    "source": [
     "l2_loss_noise = noise_l2_weight * tf.nn.l2_loss(x_noise)"
@@ -852,10 +723,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [],
    "source": [
     "loss_adversary = loss + l2_loss_noise"
@@ -870,10 +739,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 27,
+   "metadata": {},
    "outputs": [],
    "source": [
     "optimizer_adversary = tf.train.AdamOptimizer(learning_rate=1e-2).minimize(loss_adversary, var_list=adversary_variables)"
@@ -899,13 +766,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 28,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_pred_cls = tf.argmax(y_pred, dimension=1)"
+    "y_pred_cls = tf.argmax(y_pred, axis=1)"
    ]
   },
   {
@@ -917,10 +782,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [],
    "source": [
     "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
@@ -935,10 +798,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 30,
+   "metadata": {},
    "outputs": [],
    "source": [
     "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
@@ -962,10 +823,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 31,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session = tf.Session()"
@@ -982,10 +841,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 32,
+   "metadata": {},
    "outputs": [],
    "source": [
     "session.run(tf.global_variables_initializer())"
@@ -1000,10 +857,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 33,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def init_noise():\n",
@@ -1019,10 +874,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [],
    "source": [
     "init_noise()"
@@ -1046,10 +899,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "train_batch_size = 64"
@@ -1066,10 +917,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 36,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize(num_iterations, adversary_target_cls=None):\n",
@@ -1081,7 +930,7 @@
     "        # Get a batch of training examples.\n",
     "        # x_batch now holds a batch of images and\n",
     "        # y_true_batch are the true labels for those images.\n",
-    "        x_batch, y_true_batch = data.train.next_batch(train_batch_size)\n",
+    "        x_batch, y_true_batch, _ = data.random_batch(batch_size=train_batch_size)\n",
     "\n",
     "        # If we are searching for the adversarial noise, then\n",
     "        # use the adversarial target-class instead.\n",
@@ -1155,10 +1004,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 37,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def get_noise():\n",
@@ -1178,10 +1025,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 38,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_noise():\n",
@@ -1215,10 +1060,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 39,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred, correct):\n",
@@ -1235,13 +1078,13 @@
     "    \n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "\n",
     "    # Get the adversarial noise from inside the TensorFlow graph.\n",
     "    noise = get_noise()\n",
@@ -1262,10 +1105,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_confusion_matrix(cls_pred):\n",
@@ -1275,7 +1116,7 @@
     "    # all images in the test-set.\n",
     "\n",
     "    # Get the true classifications for the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "    \n",
     "    # Get the confusion matrix using sklearn.\n",
     "    cm = confusion_matrix(y_true=cls_true,\n",
@@ -1305,10 +1146,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Split the test-set into smaller batches of this size.\n",
@@ -1318,7 +1157,7 @@
     "                        show_confusion_matrix=False):\n",
     "\n",
     "    # Number of images in the test-set.\n",
-    "    num_test = len(data.test.images)\n",
+    "    num_test = data.num_test\n",
     "\n",
     "    # Allocate an array for the predicted classes which\n",
     "    # will be calculated in batches and filled into this array.\n",
@@ -1336,10 +1175,10 @@
     "        j = min(i + test_batch_size, num_test)\n",
     "\n",
     "        # Get the images from the test-set between index i and j.\n",
-    "        images = data.test.images[i:j, :]\n",
+    "        images = data.x_test[i:j, :]\n",
     "\n",
     "        # Get the associated labels.\n",
-    "        labels = data.test.labels[i:j, :]\n",
+    "        labels = data.y_test[i:j, :]\n",
     "\n",
     "        # Create a feed-dict with these images and labels.\n",
     "        feed_dict = {x: images,\n",
@@ -1353,7 +1192,7 @@
     "        i = j\n",
     "\n",
     "    # Convenience variable for the true class-numbers of the test-set.\n",
-    "    cls_true = data.test.cls\n",
+    "    cls_true = data.y_test_cls\n",
     "\n",
     "    # Create a boolean array whether each image is correctly classified.\n",
     "    correct = (cls_true == cls_pred)\n",
@@ -1394,9 +1233,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 42,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1404,17 +1242,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  84.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  20.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
       "Optimization Iteration:    300, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    500, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    600, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    500, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    600, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    700, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    800, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    900, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    999, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    800, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    900, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    999, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:03\n"
      ]
     }
@@ -1432,9 +1270,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 43,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1442,15 +1279,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 96.3% (9633 / 10000)\n",
+      "Accuracy on Test-Set: 94.2% (9417 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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JkyZNiqaIRABCx/m0r1qdNm2ayQ8++KDJ9mkIu1vMfkyTPfBGtOzH5NmPhmrX\nrl3Y6du0aWPy+eef77w+Sl+7du3KcZratWuH/GwPXrN3716TN2zYELuCxQGPPImIiByx8SQiInKU\nlN229hVYkcatLVq0qMn2+LT2zcCR/PLLLyZnZGSEvGd3bRUowO8WlDv2Vav2YBtvvvmmyevXrzf5\n7rvvNvmzzz4zuVy5clGtzx6441//+pfJ9tW9ZcuWNXnUqFEmJ/LRaJQaLrzwQpPtx9n16tXL5NWr\nV5v82GOPmXz22WeHLOvGG2802a6fqYatAxERkSM2nkRERI6SstvWHoPTHofWZt+oe/HFFzst377i\n0b66FgDq1KnjtCyicOx69Prrr5ts1z37SvJIXa3Rsh8NZatUqZLJgwcPNrlnz57O66D0dfrpp5ts\nd9X279/f5NGjR5tsnwqwx/wGQgcNSWU88iQiInLExpOIiMhRUnbb2l1N27Zti/nyTz311LCZKGj2\nQAp2d67d/TV8+HCTo+3CtbvV7C5Ze7CGzMxMt8IShWE/3nHx4sUmL1iwwOTLL7/c5EsuuSRk/mXL\nlgVYuvjhkScREZEjNp5ERESOkrLblijd2GPK2t25diZKNvb4zPbV4y+88ILJ+aWb1o9HnkRERI7Y\neBIRETli40lEROSI5zyJiChXTjvtNJMfeughk48dO2ayPfKQX6tWrUyuX79+jEsXLB55EhEROWLj\nSURE5IjdtkRElGeVK1c2+cUXXwyb8xMeeRIRETli40lEROSIjScREZEjNp5ERESO2HgSERE5YuNJ\nRETkiI0nERGRoyDu88wAgLVr1waw6PRl/T4zElmOfID1MwCsnzHBuhmQIOqnKKVitSy9QJEOAKbG\ndKFk66iUmpboQqQq1s/AsX7mEutmXMSsfgbReJYF0BTAJgAHY7rw9JYBoCqAhUqp3xNclpTF+hkY\n1s88Yt0MVMzrZ8wbTyIiovyOFwwRERE5YuNJRETkiI0nERGRIzaeREREjth4EhEROWLjmWAiUkNE\njolI9USXhchPRIp69fPaRJeFyC+R9TPqxtMr4FHvf/+/oyIyMMiCuhKRCiKyzStbEcd5Z1jbdUhE\n1onIw0GVFUCu7hcSkdtF5CsROSgiW0TkmVgXLFWkUv3M6+cmIsOt7ToiIhtEZISIFAuqzK5EpJyI\nzBSRP0TkdxF5KZnKF2+pUj9F5FIR+VBEdnmf27sicoHjMpK+fmYRkQwRWZObAxiX4fkqWbk9gCEA\nqgMQ77UyGhKSAAAZxklEQVS9EQpXUCl11KVQMfIqgOUAmudiXgXgbQB3ACgGoCWAF0TkgFLqH/6J\nRaQAAKXieNOsiDwCoCeABwB8DuBkAGfEa/1JKCXqZww/t88BXAegCIArAEwEUBhA3wjrjfff4b8A\nFAdwpff/ZAAvAugRxzIkk6SvnyJSCsB8ANMB3A6gKIBh3mtnOi4u2etnllEANgCo4TynUsr5H4Db\nAOwI83pTAMcAXAPgSwCHADSA/jCm+aYdB2C+9XMBAAMBbASwD/qX3zKX5esLYAGAZgCOAijiOH+4\n8n4M4H0v3wlgC4DWAL4BcBhABe+9Xt5rBwB8DaCHbzmXAVjlvb8UQBuvjNUdylceegSSS3Lz+8nv\n/5K1fsbqcwMwHMD/+V57DcD3Xm4Wbju999oAWOnVv/UA+sMbLMV7/zwAS7z3/2f9zq51KF8dr05n\nWq/d6P2dlEl0/Uj0vySun5d5n1tZ67V63muV80v9tJZ1k7eumt4yot4HK6UCO+c5DMC9ADIBrIty\nniEAbgbQDcAFAMYCmCkiDbIm8Lq4HsxuISJSC8D90BU0lkeCB6C/RcFbbikAdwO4FfqXv1NEugN4\nCPqo4jzoyjxCRNp6ZSsBYA70EXEd6N/TyDDbkNN2NvPKkyki34jIjyIyTUROzftmpoVE1c8gPzd/\n/QRCt/MbEbkawHgAT3uv9YbuXXnAK38B6Pq5A3qneTeAEfD9HYnIUhEZm01ZLgGwTSllj3C+ELqn\nq34uty+dJKp+rgGwG0APESkkIicB6A5gpVJqs/tmhEim+gkROQ3AGAAdob/UOQviqSoKQH+l1MdZ\nL4hINpMDIlIcusG7VCm1ynt5gohcCd3F9V/vtfUAIo5L6PWpTwPQRym1Laf1RkP0QpoDaAz9jSpL\nEeijyu+saQcD6K2Umue99IOI1IauALMAdIE+8rhTKfUndIWpBuA532qz3U4A1aC7k++DPtLdD13h\nFohIHaXUsVxsarpIWP1EQJ+bt4O8BXrHkiXcdg4C8LhSarr30iYRGQrgEegvcS0AnA59ZLzDm2cg\ngLd8q9wIYGs2RaoEYJv9glLqoIjsQWj3JZ0oYfVTKbVTRJoAmA3gCeij2a+hj+5yLdnqp7dPnwzg\nGaXU1yJSA7k40Aqi8QR0l4GLGtAD934qoTWlMHTXJgBAKdUoh+U8C+AzpdRs72fx/e+ijYjc4JUB\n0N0Ow6z39/oaztIATgMwxVfZC+L4B3kegC+9hjPLUvhEsZ0FvHLdqZRa4q2/A4CfobtePs1h/nSX\nqPoZy8+tgdcYFfL+vQ3dKNv82/kXAHVF5AnrtYIACnnf6s8DsCFrx+RZCt/fj1Kqg0M5bYLY9gbl\nVwmpnyJyMoAJABZBdwsXBfAwgHkicolS6ohDmZK5fvbTk6nnvZ9zdZQVVOO5z/fzMZx4ZW9hK58M\n/Ud1FU78ZuTydIHGAM4RkVu9n8X7t0dEBiqlnnJY1gIA90Af0m9WXie5xb+Np3j/d4Y+p2nLaixj\ntfPY4v1vusWUUptF5A8AVWKw/PwuUfUzlp/bKhw/X/6LCn+xhdlOb6daHLqbbL5/QqXUMW+aWNTP\nrQAq2i+ISAb073Fb2DnIlqj62Rn6fOcdWS94X+52Qfe+zYk0YxjJXD8bA2gkIvaXAQGwWkQmKKV6\nRbOQoBpPv18B1Pa9VhvAdi9/Bd3AVFFKLc/DelpAf1vK0hD6G1R96G/3LvYqpTY6TP8TgN8AVLOO\nfP3WAGjpu7LsUsdyAfqEOaC/cS4FABGpBKAEgB9ysbx0F6/6GcvP7ZBL/VRKKRFZCaCGUmp0hMnW\nADhbRMpY3+4vhfsOaymAiiKSaZ33vBb6d5iX31+6ilf9PAm6obYp75/r9THJXD974vjBDqBPp7wD\nfQHRF9EuJF6N5wcA7hKRdtCF6wrgHHgfvtfX/gKA0d431KXQF+Q0BLBdKTUDAETkUwCvKqUmhFuJ\nUup7+2cRyboFYK1SKlcnhaPlffhDAAwTkf0A3oPuSmkAIEMpNQa6n30wgPGi7+2rDn3SO0QU2/mV\niCyC/n31gj4ZPxL6d7sk3DyUrXjVz0R/bkMAzBKRLdDntQC9E66ulBoC/Y3/ZwCTRd/XXA66voYQ\nkRkA1iilHg+3EqXUShH5GMBEEekNfUTxPIDXfF1uFJ241E/oi7qeEJFR0BccFQXwKIA/EJ9TQfGq\nnz/5pj8KfeT5nVIqu3P5IeIywpBSag70VVGjcLyPerpvmn7eNAOgv2G8C/1tdZM12dkAyualLHJ8\nRJ8GOU/txmsge0N/s/kfdKXvAH0CG0qp3dD3jNaHvkR7APTVuX7RbGd76G+cCwC8D2AngBZhupcp\nB3Gun9l+bnJ8xJRb8rZVJ1JKzQXQCsANAFZAN9h9cLx+HoW+paQ09BHiaOhzXn5VkPOFP22hj6Y/\nhN4RLvTWRY7iVT+VUl9BH33VB/AZ9P6rFIBmynuAdD6qnyes3rW8afcwbBFpDmASgLOVUv5zC0QJ\nJSKZ0BdS1PB/QyZKNNbP49JxbNvmAIay4aQk1RzAmHTfMVHSYv30pN2RJxERUV6l45EnERFRnrDx\nJCIicsTGk4iIyFHM7/MUkbLQYyFugtvoFpS9DABVASzMumyc3LF+Bob1M49YNwMV8/oZxCAJTQFM\nDWC5pHWEHvyecof1M1isn7nHuhm8mNXPIBrPTQAwZcoUZGZmBrD49LR27Vp06tQJCL3pmdxtAlg/\nY431MyY2AaybQQiifgbReB4EgMzMTNStWzeAxac9dufkDetnsFg/c491M3gxq5+8YIiIiMgRG08i\nIiJHbDyJiIgcsfEkIiJyxMaTiIjIERtPIiIiR2w8iYiIHLHxJCIichTEIAkxdejQIZNHjhxp8ubN\nm03+8ccfTX733XfztL7SpUub/Oijj5p87733mlywYME8rYOIiFIbjzyJiIgcsfEkIiJyxMaTiIjI\nUdKf8+zdu7fJEyZMyHF6ETH5iiuuMLlq1aomL1261ORvv/02ZP5du3aZ3K9fP5Pnz59v8uTJk00+\n7bTTciwTERHlLzzyJCIicsTGk4iIyFFSdtv26dPH5Ndff93kvn37mnzTTTeZfNFFF4VdTpEiRUwu\nVOj4ph4+fNjkP//8M2SenTt3mtyxY0eTP/nkE5OvvvpqkxctWmTyGWecEbYcROEsX77c5Jdfftnk\n9evXm3z22WeHzNO6dWuTL774YpPLly8fRBEpjdinrIDQU1rTpk0LO8+oUaNMtk+ZZadSpUom26fQ\nzjzzzKjmTxY88iQiInLExpOIiMhRUnbb2t0HZcqUMfmhhx4yuUKFCrlevt2da2cAOOmkk0z+6KOP\nTK5bt67JK1euNLl58+YmL1y40GRehUvhbNmyxeQ2bdqYbI+SZZ9isE8XAMCkSZNMrlevnsnPPfec\nyZdffnlsCkv53pQpU0weNmxYyHvr1q3LcX67q7ZWrVomHzlyxOS1a9eGzLNt2zaTt27dajK7bYmI\niPI5Np5ERESOkrLb1h6coEuXLiaXKlUqAaXR7EESGjVqZPKaNWtM7tatm8n2APV2NxyltwIFjn9f\n3bNnj8l23Z4+fbrJ/isg+/fvb/KKFStMnjNnjsnstqXs2FfO9urVy+T9+/eHTGefMrOv8ra7Z+2B\naOxuV/suBv9dCAcOHAhbFvvq8VTAI08iIiJHbDyJiIgcJWV/4l/+8pdEF+EE9o29Q4YMMblr164m\nL1682GT7KskmTZoEXDpKFRUrVjTZ7l61u13tbv727duHzN+wYUOTx44da/K4ceNM/utf/2pyq1at\n8lhiyg/sLtlXXnnFZHuAmQEDBoTMc9lll5lcrFgxp/XZXbPZDZ7Qtm1bp+UmEx55EhEROWLjSURE\n5Cgpu22Tnd2VNnXqVJPtK2ztcXHtG+OJsth1xO627d69u8mDBw8Omcee7osvvjB53759YTMREDr4\nywcffBD4+p599lmT/VfxnnvuuSZnZmYGXpag8MiTiIjIERtPIiIiR+y2zaMGDRqYbHfb/v777yZ/\n+umnJvMGdspid6XZVyTa49zaA2/4ZWRkmGxfQdmpU6dYFZEoavYj9p5++umI09kDM5QtWzbQMgWJ\nR55ERESO2HgSERE5SptuW/sROUqpqOaxb1a3xyS1tWvXzuRBgwaZbI/tuGnTJpPZbUtZWrRoYfIb\nb7xhsv3IuyeeeCJkHrvu1q9f3+TOnTsHUUSibB07dsxk+5GM9hW2JUuWDJmncePGwRcsDnjkSURE\n5IiNJxERkaN80W27e/duk2fOnGnyZ599ZvJbb70VdvrsXH/99SZXqFAh7Ov2WKP2Y6X8j5Iiyo79\nyCc7P/XUUyHT2acf2FVLiTZhwgST7dNWNn8dTsaxy3ODR55ERESO2HgSERE5YuNJRETkKGXPedrP\ny7z99ttN/vbbb2O2DnvEINukSZNMrlWrVthp7NFfrrvuupiViShL4cKFE10ESnPz5s0L+3qVKlVM\nvu222+JVnLjikScREZEjNp5ERESOUqrb9o8//jD55ptvNvnQoUMm289ItAdtt1155ZUm2yNkAMCp\np55qsn3by549e0y2L71etWpV2HUUL17c5FQe/Jjiz36oQHajYbFeUSJ8+eWXJs+dO9dk++EG/fr1\nM7lo0aLxKVic8ciTiIjIERtPIiIiRynVbdu7d2+T7a6tZs2amfz666/HbH19+vQJ+3rNmjVNtgeG\nP3jwYMzWTenL7gqzHzAAhHaB2QPLEwVp3759Jg8ePNhk+7TCVVddZfLf//73uJQrkXjkSURE5IiN\nJxERkaOU6rbdsmVLoosAIHSQePuZn7a2bdvGqziUz2zdujXie926dYtjSYg0e2AYe2CEYsWKmdy1\na9e4linReORJRETkiI0nERGRo5Tqtk2k/fv3m2xfSbZ3716Ty5cvb/KaNWviUzDKF+yrx8ePHx9x\nOp4OoHixxwl/9NFHw05jD4bQoUOHwMuUTHjkSURE5IiNJxERkaN80W175MgRk48ePWpywYIF87Tc\nXbt2mXzRRReZvHHjRpPt8UXtq9DOP//8PK2b0sv27dtN3rRpU8TpSpYsGYfSUDryj6M8fPhwk+3T\nU7Z0HqiDR55ERESO2HgSERE5Sqlu206dOpn86aefmvz++++bPHToUJPtMRijtWzZMpNbtmxp8m+/\n/RZ2+ieffNLk+vXrO6+PiCgZvPnmmyE/v/baa2Gn69Kli8npvM/jkScREZEjNp5ERESOUqrb9rbb\nbjN5ypQpJtvdtnY3qn0F40033WTy4cOHTX7nnXdC1vHGG2+YvHv3bpPtp6RPnDjR5I4dO0a/AURE\nSWr9+vVRTTdgwACn5c6cOTPkZ/sxjqmMR55ERESO2HgSERE5SqluW9vIkSNNfuSRR0xesGCByS+9\n9FLYnBv2lWf2Vb9ERPnBihUrIr732GOPmVylShWTDx06ZPJbb71lsn3Xw4svvhirIiYVHnkSERE5\nYuNJRETkKGW7bWvXrm3yjBkzTJ49e7bJb7/9tsn+q2ojefjhh01u3769yRdccEGuyklElAqWLl0a\n8b0dO3aYbD9u0b7b4IcffjDZfoRZo0aNYlXEpMIjTyIiIkdsPImIiByx8SQiInKUsuc8bSVKlDDZ\nHoXIzkTJrGLFiibXq1fPZP/tA5dddpnJDRs2NHnx4sUBlo7SQatWrUJ+Hj9+vMljxowJm+1ngPbs\n2dPkBx98MIgiJhUeeRIRETli40lEROQoX3TbEqW6MmXKmDx//nyTK1euHDKdPaJL7969gy8YpY0h\nQ4aE/LxkyRKTV69ebbJ9m6A9SHzTpk0DLF3y4ZEnERGRIzaeREREjthtS5Rkypcvb/KRI0cSWBJK\nJ3a9A4BVq1YlqCSpgUeeREREjth4EhEROWLjSURE5IiNJxERkaMgLhjKAIC1a9cGsOj0Zf0+MxJZ\njnyA9TMArJ8xwboZkCDqp9hjE8ZkgSIdAEyN6ULJ1lEpNS3RhUhVrJ+BY/3MJdbNuIhZ/Qyi8SwL\noCmATQAOxnTh6S0DQFUAC5VSvye4LCmL9TMwrJ95xLoZqJjXz5g3nkRERPkdLxgiIiJyxMaTiIjI\nERtPIiIiR2w8iYiIHLHxJCIicsTGM8FEpIaIHBOR6okuC5GfiBT16ue1iS4LkV8i959RN55eAY96\n//v/HRWRgUEWNMoy1hWRGSLyk4jsE5HVItIrF8uZYW3XIRFZJyIPB1Fmj9P9QiJSUUQWishmETko\nIj+IyPMiclJQBUx2qVA/AUBEmonIMhHZIyI/i8jQXCxjuLVdR0Rkg4iMEJFiQZTZlYg0zebzuCDR\n5UuEVKifabT/vCPC53FEREpEuxyX4fkqWbk9gCEAqgMQ77W9EQpaUCl11GE9eVEfwM8A/ub93wjA\nSyJySCk10WE5CsDbAO4AUAxASwAviMgBpdQ//BOLSAEASsXvptmjAN4A8BCA36E/h/EATgHQI05l\nSDZJXz9FpB6AOQAeBdABQBUAL4uIUkq57jw/B3AdgCIArgAwEUBhAH0jrDuef4fvI/TzAICRAOor\npb6OUxmSTdLXT6TP/vNVALN9r80AcEAp9UfUS1FKOf8DcBuAHWFebwrgGIBrAHwJ4BCABgCmA5jm\nm3YcgPnWzwUADASwEcA+6J1Dy9yUz7eeVwDMc5wnXHk/BvC+l+8EsAVAawDfADgMoIL3Xi/vtQMA\nvgbQw7ecywCs8t5fCqANdGNYPY/b2Q/Aurz+vvLDv2StnwCeBfCx77U2AHYDKOqwnOEA/s/32msA\nvvdys3Dbaa1vpVf/1gPoD2+wFO/98wAs8d7/n/U7uzYPn0dRADsA3JfoupEM/5K1fkYoa77ffwI4\nDcARAK1d5gvqnOcwAPcCyASwLsp5hgC4GUA3ABcAGAtgpog0yJpARLaIyIOOZSkJ/YebVwegv+UD\n+ptVKQB3A7gVQE0AO0WkO/TR4APQO6GBAEaISFsA8LoE5gBYDqAO9O9ppH9FrtspIqcDuAnAR7nZ\nsDSUqPpZFCcOu3YQwMkAakVZjkj89RMI3c5vRORq6B6Kp73XekMfHTzglb8AdP3cAaAedP0eAV+3\nmIgsFZGxDmVrA6A4gNedtyo9cf8Zx/0ngC7Q2zjHZYOCeKqKAtBfKfVx1gsiks3kgIgUB3A/gEuV\nUqu8lyeIyJUAegL4r/faeuhuyqh487cEcFW084RZhgBoDqAx9Df+LEWgvxV9Z007GEBvpdQ876Uf\nRKQ29A5qFvSHdBDAnUqpP6F3aNUAPOdbbVTbKSJvQR9lZEB3497lun1pKJH1cyGAniJyM3S30WnQ\nXbgAcKrbZoSUrwGAWxD6xx9uOwcBeFwpNd17aZN3zvUR6J1QCwCnA7hEKbXDm2cggLd8q9wIYKtD\nEbsBmKuU+tVhnnTF/Wec9p+WLgAme8uMWhCNJ6C7DFzUgG4APpXQmlIY+tAcAKCUahTtAkWkDvQf\nfX+l1H8cywMAbUTkBq8MgO4WG2a9v9f3wZeG3hlO8VX2gji+ozkPwJe+D2kpfBy2sxf0N8NMAE9B\nH1HcH+W86Swh9VMpNVdEBgCYAO8cC3SdagDd9eSigYjsgf4bLgR9juk+3zT+7fwLgLoi8oT1WkEA\nhbyjzvMAbMhqOD1Lcfy8XNZ2dIi2kN7O7UoA10c7D3H/aQly/wkRaQygGvTfpJOgGs99vp+P4cQr\newtb+WTob1xX4cRvDM5PFxCRWgAWARiplPJ/K4nWAgD3QPfHb1Ze57jFv42neP93hu6Tt2V92ALH\nK8Oyo5TaBmAbgPUishfAIhEZqpTaFat15FMJq59KqRHQXVGVoLuKzgfwJPTRnItVOH6+5xcV/qIS\ns53eTrU4dHfg/DDlOuZNE+uLNroD+AX6qJuiw/1nqED2n54eAJYppb5xnTGoxtPvVwC1fa/VBrDd\ny19B/4KqKKWW52VF3mH+YgCjlVLDc5o+G3uVUi47tJ8A/AagmlLKfyVXljUAWvquoLs0D2W0FfT+\nL5LtVBRO3OpnFqXUVsA8w/F75X4V6iGX+qmUUiKyEkANpdToCJOtAXC2iJSxjj4vRS53WN7RbGcA\nE8PsPCl63H9qMd1/ikhJAK2Qy9Nd8Wo8PwBwl4i0A/AFgK4AzoH34SuldorICwBGi0gG9KF4KQAN\nAWxXSs0AABH5FMCrSqmwh9jeB/8edHfDSyJS0XvrTxXwMwa9ndMQAMNEZL9XjgzoLrkMpdQYAJMB\nDAYwXkSegb5U/e4w25HTdt4A/fv5HPobXC3oc1bvKaW2h5uHshWv+lkI+iKdxd5L7aA//5ZBbZjP\nEACzRGQLjl+qXxv6SsUh0EekPwOYLPq+vHLQ9TWEiMwAsEYp9XgO62sOfS53UmyKn7a4/4zh/tPS\nCfpLx8zclDkuIwwppeZAX7U3CsfPoUz3TdPPm2YA9DeMdwFcC/1g2CxnAyibzaraASgN3VW02fr3\nadYEcnxEigbhF5F73gfcG/ok/f+gK30HeF1ySqnd0DvK+tCXog+AvrrML6ftPATg79C3FHwNfa5z\nBvTVduQojvVTQV8V/R/oizgaA2iulFqUNYEcH9HnlrxtVZiVKzUX+pv2DQBWQNefPjheP48CuBH6\nb2g5gNEAwt3cXgUn3scZTjcAHyilNuW17OmM+8+Y7z+zdAMwQym1PzflTbuHYYtIc+hvwmcrpfz9\n7kQJJSKZ0D0KNZRSPyW6PEQ27j+PS8exbZsDGJruHzwlreYAxrDhpCTF/acn7Y48iYiI8iodjzyJ\niIjyhI0nERGRIzaeREREjth4EhEROWLjSURE5IiNJxERkSM2nkRERI7YeBIRETli40lEROTo/wEt\nwtpDP97oCAAAAABJRU5ErkJggg==\n",
+      "image/png": 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f47KqNEVEik3TKEVEYlClKSISgypNEZEYVGmKiMSQ1W6ULVq0cBUVFTnKSnmYPXv28vVpVW+Vcd2nMo4nq0qzoqKCWbMymYFVd5jZerUtgMq47lMZx6PmuYhIDKo0RURiUKUpIhKDKk0RkRiyehCUb6+9llim75JLLgHg7LPPBuCII45IpmncuHHhMyYi6y1FmiIiMZR0pDls2DAA/vOf/wAwffp0AI499thkmsGDBwOw6667Fjh3IrI+UqQpIhJDSUeaXbok9kUaPz6xLfZPP/0EwJgxY5JpXnzxRQCGDBkCwBlnJLZ7qV+/pH80ESlTijRFRGIo6XDs/PPPB+DnnxMLPI8YkdhT65NPPkmmWb48sVVx376JLUcWLVqUcu7WW29dmMxKVubNmwfArbfeCsDMmTOT7739dmLrpaZNmwKwbFnqbhgDBw5Mvh46dGhe8ym58+OP4R5tt9xyCwBXX301AM2bNwfgs88+A2Dy5MnJtPvuuy8AH36YmAn5yCOPAOEom3r18hsLKtIUEYmhpCNN76KLLgJgm222AeDTTz9Nvrd4cWKn1jvuuAOAm2++GYDVq1enHJfS5KPI005L7N47Z071u+NWjjC9Z599Nvn6nHMSGya2bt06V1mUHFu7NrFF/YAB4U69Cxcm9iS87bbbAOjZM7Gtfb9+/QDYYYcdkmlXrlwJQNeuXQH4/vvvAejduzcAm2+e3wWqFGmKiMRQFpGm5//6RPm/MptuuikQRpp33nknAC1btkymvfLKK/OdRcmQjxaOP/54IOzTrEmzZs0A+PLLL1OO+ygF4MEHHwRU1qXo668TO/iefvrpAGy11VbJ9/76178C0Llz55Rz/GiYFi1aJI/tv//+QPjZf/7554H8R5ieIk0RkRhUaYqIxFBWzfOqNGzYEAgHt8+fPx+Ap59+GoCJEycm0w4aNAiAjTfeuJBZlCqMGzcOqL5Z/qc//Sn52j8w2GSTTQC49tprAbjrrrvWOW/BggU5zafkjm9G+yGDt99+e/K9aDda1H777QfACy+8kDzmhyD68i/0FGpFmiIiMZR9pFnZo48+CoRLxs2YMSP5nu+ILlSHsVRvypQpVR7v2LEjAOeee27y2C677ALAd999B8Crr75a7XXffffdXGVRcuydd94Bwgc51UWXUb7lePTRRyePNWnSBIBWrVrlOosZUaQpIhJDnY00pbRdcMEFADz++ONAOODZD3b3UQnAww8/DIRRx9y5c6u97jHHHJP7zEpW/DRXv7SjX+oxE35yim9lAIwaNQqA3XbbLVdZjEWRpohIDGUfafoBrtdddx0QDm73unfvnnztF3yQ4vN9lwcccAAAU6dOBeCbb74BUheajsP3l0nxPfbYY0DY+vP9zRtttFG15/iJC5dddhkAI0eOBMKp1FD7341cUaQpIhJDSUWa5513HhBO2vfLuvknZz5SjI6zfOaZZwB4/fXXU67Vrl07AO65557kMS1MXHr8kl++/Pz4zDfffDPja3Tq1Cn5WpFm8flxlH6pNj+GulGjRinpfD82hOMwr7nmGgA++ugjIFwO0tcNpUCRpohIDCUVevn+STMDwpkDfvEN51zK+1FbbrklEC4N5if6axHi0rbBBhsA4UINf/7znwG4+OKLk2mWLl1a5bmbbbYZAP37908eq+p3QwrLz/Ly29P4LbeXLFkCwAcffADA6NGjk+f42T2+v9PP6Is+kygVijRFRGJQpSkiEkNJNc/9AyA/QHnWrFlAOGTh888/B2DVqlXrnOvXZbziiivynk/Jn6+++goI936qiW/C+UUdpDQ0aNAAgBUrVgBwyCGHAPDGG28AUFFRAYRr4EbPad++PVCazXJPkaaISAwlFWn6oUSHHXZYytfBgwcD4YIbfsc6CIck/POf/wTCKVt+PyEpD36qpN9F9IcfflgnjX/I06tXLwD22WefAuVO4mjbti0Aw4cPB8LdIv1wIr8Yy4033pg8x0+f9TtNljJFmiIiMZRUpJmOX4T2pJNOSh67++67gbC/00ejUh7uvfdeINzTp6oI87jjjgNg7733BsLFPqS0+Z0k/VfP73F+ww03JI/5IWfR6LNUKdIUEYmhaJGmn1oVnfZWmylwfiqWH/gu5eGBBx4AoE+fPsC65RddoNYv2uAHs0t5+vjjj4Fw4kJ0AZ2xY8cCsOGGGxY+YzEp0hQRiaHgkeaTTz4JwNChQ4FwumNN3nvvPSDsC/HLiEHYB6bpc+XBR5h+PG11LQS/NzYowix3v/zyCwAHHXQQEG5fMmnSpGSa6B7opU6RpohIDKo0RURiKFjz3D+w8YOYv/32WyC149cPG/KrHd1///0pXz/88EMgtSnud530A2bbtGmTj+xLFqI7RF5++eVA9SsX+RXdL7zwwvxnTAri1ltvBeDTTz8FYPXq1cXMTtYUaYqIxFCwSNMvwOBXWveiHcDpHuYceOCBAPTo0SN5rGvXrkC4UruUnrPOOiv5Ol2E+dxzzwHQokWL/GdM8mratGlA+NDv0ksvLWJuckeRpohIDAWLNJs1awaESz5NnDix2rR//OMfgXC5qJ49ewLlMZlfQr7/eubMmdWm+dWvfgXAgAEDANh8883znzHJqwcffBAIF8/xLUNFmiIi66GCRZp+J8h//etfhbqlFMnixYuBcKGGNWvWVJu2d+/eAJx44on5z5gUxE033QSEu0/6HWHrym6wijRFRGKoG1W/lJQddtgBCHcC9QvMRnXr1g0I98aWusc/m2jYsGGRc5JbijRFRGJQpCl54zfQikaafkSEX7jD71cv5W3ZsmXJ137ver8tSV2jSFNEJAZVmiIiMah5LnkzYcKEYmdBCiQ6HbquDx9TpCkiEoMqTRGRGFRpiojEYNns4mhmXwAf5i47ZaG1c269WVVCZVz3qYzjyarSFBFZ36h5LiISgypNEZEYVGmKiMRQY6VpZs3NbG7wb5mZLY18v1E+MmRmjc1sZnCPt8xscAbnDInkbZ6ZHZ5lHl4ysz3SpBlkZgvN7A0zm2xm22Zzz2IpRhkH973QzBYE//pnkL63mX0R5Guhmf0xy/s/bGY90qS5NPJ/scDMfjazTbO5bzGojDNKu7eZ/ZJReudcRv+Aq4CLqzhuQL1Mr5PBfeoBjYPXGwKzgA5pzhkCDAhe7wp8QfCQK5Kmfow8vATskSbNQUDD4HV/YHSu/g+K9a+AZbwH8AbQMCjjqcB2ac7pDYwIXm8FLAdaZFHGDwM9YqQ/BphU7DJSGee+jEnMjJwKPJ9J+lo1z81sxyAKHA0sALY1s1WR93uZ2b3B6y3NbKyZzQoiyM41Xds5t9Y5923w7UbBf3jGj/idc/NJ/AI0Df7S3GlmM4HrzayJmd0f5GOOmR0Z5LGRmT0R/HUbAzTI4D4vOOe+D759Fdgm0zyWg3yWMdAWeNU5971z7idgOolKKSPOuWXAB0CroJXxoJm9DNxvZvXNbFiQjzfNrHeQx3pmdoeZvW1mk4G4212eADwa85ySpjJOGgA8RqKSTiubPs1dgOHOuXZA1fuyJtwCDHXOdQCOB3wh7GVmd1V1gpltZGZzgc+AZ51zszPNlJl1AdY4574MDrUEOjvnBgGDgeedc51IRIo3m1kD4FxgpXOuLYmodc/I9UZZmqY6cCZQFyda56uM5wEHmFkzM2sM/B7IuHvDzHYEWgP/i+TzYOfcyUAf4POgjDsC55hZK+BYYDugHXAG0CVyvevM7LAa7tcE6AqMzTSPZWS9LuPgvMOBezLNWzYLdix2zs3KIF1XYGcL9zRvamYNnXOvAa9VdYJz7kdgDzNrCowzs7bOuYVp7jPQzE4HvgF6Ro4/4ZxbG7zuBvzezPy2eA2AVsD+wNDg3nPMbEEkL2fUdNPgnu2B89LkrxzlpYydc/PNbBgwBVgNzAF+yeA+J5nZgcAPQG/n3Krgnk855/xGRN2AtmbmF3PcFNiJRBk/GvwuLDGzaZH8XJ7mvkcDLzrnvsogj+VmfS/jEcAg59zayM9Wo2wqzW8jr9eSaBJ70eatAZ2CijAW59xKM5sOdAfSVZo3OedGpMmnkeizWBxNkOl/VmVmdigwEDigNj9fGchbGTvnRgIjAcxsKPBeBqeNds4NSJNPA/o55/4dTWBmGTcNq9ALeCiL80vZ+l7GHYAngjqgBdDNzH5xzj1T3Qk5GXIU1OwrzWwnM6tHat/FFOAc/026pq6ZbWHBE0oza0TiL9zbwfdDfT9kLU0k8dDG38s3w6cDJwbHdgd+k+5CZtYBuB04yjmXUV9IOctlGQdptgi+VgBHkehTwszON7O+WWR1ItDPzOoH19vZzBqSKOOeQb/X1sABmVwsaO10Aar9ENUV62MZO+daOecqnHMVwHigT00VJuR2nOYlJH6YV4AlkePnAPsEHbZvAWdBjX0hvwZeNLM3gJnAc86554P3dgOWVXFOpq4GGltiWNICEk8SAW4DmpvZQuBKEk0JgnxW16f5N6AxMMYSQyTGZZGvcpGrMgYYH6QdD/R1zn0dHG8LrMgij3cDi4C5ZjYfuJNEi+pJ4CPgLWAUMMOfkKZP8/8BEyIP/eq69bGMYymbueeWiJ8nOOcOLXZeJH/M7DngaOfcz8XOi+RHuZdx2VSaIiKlQNMoRURiUKUpIhKDKk0RkRiy2o2yRYsWrqKiIkdZKQ+zZ89e7tajVb1VxnWfyjierCrNiooKZs3KZDJB3WFm69W2ACrjuk9lHI+a5yIiMajSFBGJQZWmiEgMqjRFRGJQpSkiEoMqTRGRGFRpiojEkNU4TZFS8PPP4WI5frzhnDlzUr5/5513ANh5550BOPfcc5Pn7LlncncTkbQUaYqIxFCSkeYjjzwChFHCiBFV7WKR4Je223vvvQE48sjEwu59+vQBoHnz5nnLpxTHTz/9BMDrr78OwN/+9rfke+PG1bwW9MsvvwzAf//73+QxH5WKZEKRpohIDEWPNK+44ork69tuuw2A779P7Czg+6oy2fjstddeS/k6b948IIxapfz5fsnzzz8fgIkTJ6Y9p0WLxNbX7du3Tznuf9ck/8aMGQPAu+++m3J88uTJyddTp04F1m0xeqeffnrydcuWLfORzYwp0hQRiaFokeZll10GwLBhw5LHfF+Vt+mmmwLQo0cPAI444ggANtpoo2Sao446qsrrL16c2KV3+fJwo0gfdUjpiz4Rv/LKKwG4/fbbAfjmm29S0vrfE4Czzz4bgBNOOAGALbbYAoCtttoqf5ldj7399ttAamT4xRdfpKRZsyaxXXnlz3eUb01WbjF6TZo0Sb7u378/xaRIU0QkhoJHmv/73/8AuOeee4AwEgA48cQTATjjjDOAMKLcbrvtUq7ho9SoHXbYAYCmTZsC4ZP3999/P5lGkWb5+POf/5x8HX06HtW9e/d13t91113zmzFJ8Yc//AEIP9f54usLgGOPPRYoXt+mIk0RkRhUaYqIxFDw5rl/cPPll18C4UMegBtuuCGja/Tr12+dc3yzzA8l2XfffQG48847k2k7duxY22xLnvkHP5dffjlQdZN8ww03BMIpkNdddx0ADRs2LEQWpQqrV68uyH0WLFiQfN2lSxcAzjrrLABOPvlkAFq1alWQvCjSFBGJoWCR5ieffALARx99lPW1ttlmm+RrPxzFR5y9e/dOSbt06dKs7yf55yPMoUOHrvNe69atAfjLX/4ChA8Kpfj8A9iqPme+9XfvvfcC8PXXXwPhFOcdd9wxmXa//fYDwod7nh++FG1d+jrEf/a33XZbAE455ZRsfpSMKdIUEYmhYJGm7/tYu3ZtynHfH1FbV199NQArVqwA1p1+tdNOO2V1fckP34fphxZV7sOMTmB47LHHAOjcuXOBcieZ8tOUfT8jhJGgX0zHR5R+OOCkSZOAMEqtip+U4ocXfvzxx8n3/ED3Aw88EIBDDjkkux8iJkWaIiIxFCzSbNOmDQDNmjUDwj6Qdu3a5eT6fmrVo48+CsCqVatycl3JjwcffBCofuD6lClTkq8VYZYuP8D8ggsuSB4DIO8eAAAK9klEQVQbPnw4ED7x9n3QvqyjfZmVrVy5EoDjjz8egBdffHGdNL7OeOqpp7LKe20p0hQRiaHg4zQHDRoEhMt7Pf3008n3Bg4cWOvr+qmWfsyejzSjiwT4frT69Yu+It5666WXXgLgwgsvTDnux2D6cbV+nK2Uh/POOy/5+re//S0Axx13HADPPPMMAC+88AIA999/PxBOwYzyx6ZPn55yPNpnWtU06kJSpCkiEkPBQy6/yOgmm2wCwD/+8Y/ke76/88wzz8z4etOmTQPgxhtvBODTTz9NeT/aJ+L/eh100EExcy3Z8E9RIZyx9dVXX6Wkady4MQA//PADAN99913yPd96qFdPf+PLgW8lzJ07F4BjjjkGCLcVOemkk4BwRg+ET8BfffXVlGv5Fsjf//735DEfyRaLfgtFRGJQpSkiEoNFm05xdejQwfl1K+Pyg9qr2sPHT4vq27dv2uv4TmG/8vNpp50GwKhRo4DUoSvdunUDYOzYsUDqYiGZMrPZzrkOsU8sU9mUsfftt98mX0dX4M6UH07mB8Lnex1FlXF++M96VdMdfT3kP8f/93//B8Cll14KVP3QKBvZlLEiTRGRGIoWafqhQNH9p33k9/nnn2d8Hf8XacCAAUD4F6lBgwZA6l4zgwcPBsK/an/9619j51tRSHzR4UV+4HNttG3bFgh3Ltxyyy2zyld1VMb54R/+de3aFYDZs2cn36scaS5ZsgSAX//613nJiyJNEZECKdoobz+UYK+99koee/PNNwG46667gNT9fQA23nhjIFwSCsI+Mj+EqbLoQParrroKCAfd+j3XhwwZUrsfQjIS3d/a+9WvfgXAfffdV+U5fiA0hL8PCxcuBMIpmNlMhpDC87uG+mGH0Vam5yPNUqZIU0QkhpKaT7j55psDqZFkLvnlxjbYYAMAHnroIUCRZjGcfvrpQBj1V7b99tsnX/tI06vcApHy4CeePPDAA2nT+skq0UHtpUKRpohIDCUVaRaKX5pqwoQJADz55JNAuJ+y5J+fNlkdv2ma1B3z5s0DwgXJo3vU+6nTfmlH3wr0o2L8gjylQJGmiEgMqjRFRGJYL5vnl1xyCRAOkn744YcBNc+LyU928GUzbty4ddL46ZM+jZSHDz74AAinT/rhhn5aLECvXr2AcCUrv97ujz/+WKhsZkyRpohIDGURafoo5L333lvnPb9ftueHsJxwwgnVXm/EiBFAOLhW+2jnl18oBWD+/PlAuHiDXz9xzZo1Kd9XxU979fugS3m44447gHCHSf9wx0eXUdH1dUuVIk0RkRjKItK8/fbbAbjooovWea/yRH8/NdLvdhnlp+z5Pkw/xTLd8BfJzg033JB87Vfa91G+3yO7sq222ir52keYp556ap5yKPlUuYXop9BGB677HRbeeustINzTPF8LdmRDkaaISAxlEWm2atUKCBfl+Prrr6tN27Fjx7TXa9SoEQD9+vUDwoWLJT/801IIF5YeOXIkAH5JMr/vi/8anUrry1/qhmuvvXadY5VbjO3btwfCqLSUKNIUEYmhLCJNv7Dw4YcfDoRPvyH8C3XNNdcA4W6GVfHbaEyaNAmANm3a5D6zUiO/A2F0J0IRz4+0KOVptIo0RURiKItI0/OLEFc1I8RvwCQipaV79+4APPXUU1UeB9h///2BcGsUv4xjKVKkKSISgypNEZEYyqp5LiLl509/+lPK13KnSFNEJAZVmiIiMajSFBGJwfzg8FqdbPYF8GHuslMWWjvnNi92JgpFZVz3qYzjyarSFBFZ36h5LiISgypNEZEYaqw0zay5mc0N/i0zs6WR7/M2z8nMLjSzBcG//hmk721mXwT5Wmhmf8zy/g+bWY80aU41s3lm9qaZvWxm7bO5Z7EUsYybmdlYM3s7KLNOadIXo4y7mtlXkf+Py2tKX6qKWMYXB5/h+WY22sw2TpN+SCRv88zs8Czv/5KZ7ZEmzS2R/4tFZrY83XVrHNzunFsB7BFc/CpgtXPub5VuaiT6Rtemu1kmgh/yNKAD8DMwycyedc69n+bU0c65AWa2FTDfzJ52ziX/A8ysvnPu51zkMbAY2M85t8rMjgTuAvbJ4fULohhlHLgVeNo594fgg9swg3MKXcYAU51zNVaupa5In+PWQF9gV+AH4EngOODhNKfe5JwbYWa7AlPNbAsXefCS6zJ2zp0XufYFQNt059SqeW5mO5rZW2Y2GlgAbGtmqyLv9zKze4PXWwYRxSwzm2lmndNcvi3wqnPue+fcT8B04JhM8+acWwZ8ALQK/nI9aGYvA/ebWX0zGxbk400z6x3ksZ6Z3RFEPZOBFhnc52XnnP+ZXwW2yTSP5SCfZWxmzYC9nHP3AzjnfnTOfZVp3gpVxnVdnj/HABsCDUgEZ42ATzLNm3NuPmBA06BVcKeZzQSuN7MmZnZ/kI85QdCCmTUysyeClsiY4N5xnAA8mi5RNn2auwDDnXPtgHU35AndAgx1znUAjgd8IexlZndVkX4ecIAlmm+Ngd8D22aaKTPbEWgN/C+Sz4OdcycDfYDPnXOdgI7AOWbWCjgW2A5oB5wBdIlc7zozOyzNbc8EJmSaxzKSrzLeHvgiqOzmmNlIM2uUaaYKXMb7mtkbZvYvM2uXaR7LSF7K2Dn3IfB34GPgUxJl8kKmmTKzLsAa59yXwaGWQGfn3CBgMPB8UMYHATebWQPgXGClc64tMATYM3K9UTU11c1sB2Br4MV0ectm7vli59ysDNJ1BXa2YBl7En85GjrnXgNeq5zYOTffzIYBU4DVwBzglwzuc5KZHUiiKdA7aDYDPOWcWxOk6Qa0NTO/d+imwE7A/sCjQdNkiZlNi+Snxn4sM+sKnALsm0Eey01eypjE710HoD8wm0RTfSBwdZr7FLqMXwcqnHOrg2hmLIlKpi7JSxmbWXPgCBJ/qL4GxphZL+fcY2nuM9DMTge+AXpGjj8R6TroBvzezPx6kA2AViTKeCiAc26OmS3wJzvn0u3T3Qv4ZybdE9lUmt9GXq8lEUp70bDYgE7OuR8zvbBzbiQwEsDMhgLrbni+rtHOuQFp8mlAP+fcv6MJzCzj5n+l8/YA7ga6O+dW1uYaJS5fZbwE+Mh/WIOmVFVlV1lByzjaZeCceyZoIm4W6ZapC/JVxt2ARb7P2czGkYju01WaNznnRlRxvHIZ93DOLY4miFTotdGLRIsxrZwMOQpq55VmtpOZ1SO1D3IKcI7/pqYQOZJmi+BrBXAUwX+0mZ1vZn2zyOpEoJ+Z1Q+ut7OZNSTRb9oz6PfaGjgggzxWkOjcPtE5l0mlXtZyWcbOuSXAZ0EzG+Bg4K3g3FIq460irzsDP9exCjNFjj/HHwF7m1lDS9RmBwMLg3OH+n7IWppIopXi8+Kb4dOBE4NjuwO/yeRilnjo1NA5NzOT9Lkcp3kJiR/mFRKRhHcOsE/QKf8WcFaQ0er6uwDGB2nHA32dc377ybbAiizyeDewCJhrZvOBO0lE20+SKOS3gFHADH9CDf1dVwHNgLstMVyhqmZoXZPLMu4PPG5mb5L45fabo5dSGfeyxJCZucBwUpuLdVVOytg59zLwNInutXkkRsLcF7y9G7AsizxeDTS2xLCkBSQ+iwC3Ac3NbCFwZXBvgnzW1KfZi/QRcFJZTaM0s+eAo/MwrERKhMq4bguizgnOuUOLnZfaKqtKU0Sk2DSNUkQkBlWaIiIxqNIUEYlBlaaISAyqNEVEYlClKSISgypNEZEY/j++NhxVOXnrNwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f20571306a0>"
+       "<matplotlib.figure.Figure at 0x7f5e38074128>"
       ]
      },
      "metadata": {},
@@ -1477,10 +1314,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 44,
+   "metadata": {},
    "outputs": [],
    "source": [
     "init_noise()"
@@ -1495,9 +1330,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 45,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1505,18 +1339,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
       "Optimization Iteration:    300, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    400, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    500, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    600, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    700, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    500, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    600, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    700, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    800, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    900, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    999, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:03\n"
+      "Optimization Iteration:    900, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    999, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:02\n"
      ]
     }
    ],
@@ -1533,9 +1367,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 46,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1546,14 +1379,14 @@
       "Noise:\n",
       "- Min: -0.35\n",
       "- Max: 0.35\n",
-      "- Std: 0.195455\n"
+      "- Std: 0.19540551\n"
      ]
     },
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2056bad3c8>"
+       "<matplotlib.figure.Figure at 0x7f5e38070048>"
       ]
      },
      "metadata": {},
@@ -1577,9 +1410,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 47,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1587,15 +1419,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 13.2% (1323 / 10000)\n",
+      "Accuracy on Test-Set: 13.8% (1378 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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GOwF448aNofPZicL2OuyE5ebNm4fKkeJTam8CYX9++umnqpcsWaLaTla3oyHn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\nTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2056ba3e80>"
+       "<matplotlib.figure.Figure at 0x7f5db664b940>"
       ]
      },
      "metadata": {},
@@ -1606,16 +1438,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[  85    0    0  895    0    0    0    0    0    0]\n",
+      "[[ 115    0    0  863    0    0    0    2    0    0]\n",
       " [   0    0    0 1135    0    0    0    0    0    0]\n",
-      " [   0    0   46  986    0    0    0    0    0    0]\n",
+      " [   0    0  146  886    0    0    0    0    0    0]\n",
       " [   0    0    0 1010    0    0    0    0    0    0]\n",
-      " [   0    0    0  959   20    0    0    0    3    0]\n",
-      " [   0    0    0  847    0   45    0    0    0    0]\n",
-      " [   0    0    0  914    0    1   42    0    1    0]\n",
-      " [   0    0    0  977    0    0    0   51    0    0]\n",
-      " [   0    0    0  952    0    0    0    0   22    0]\n",
-      " [   0    0    1 1006    0    0    0    0    0    2]]\n"
+      " [   0    0    0  966   16    0    0    0    0    0]\n",
+      " [   0    0    0  865    0   27    0    0    0    0]\n",
+      " [   0    0    0  946    0    1   11    0    0    0]\n",
+      " [   0    0    0  981    0    0    0   47    0    0]\n",
+      " [   0    0    0  968    0    0    0    0    6    0]\n",
+      " [   0    0    1 1008    0    0    0    0    0    0]]\n"
      ]
     }
    ],
@@ -1640,10 +1472,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 48,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def find_all_noise(num_iterations=1000):\n",
@@ -1675,83 +1505,81 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 49,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Finding adversarial noise for target-class: 0\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    299, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    299, Training Accuracy:  89.1%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 1\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    200, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    299, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  60.9%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 2\n",
       "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 3\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    200, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    299, Training Accuracy: 100.0%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 4\n",
       "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    299, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  92.2%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 5\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 6\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    299, Training Accuracy:  98.4%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 7\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    299, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    299, Training Accuracy:  87.5%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 8\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    299, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
       "Finding adversarial noise for target-class: 9\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    299, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    299, Training Accuracy:  85.9%\n",
       "Time usage: 0:00:01\n",
       "\n"
      ]
@@ -1777,10 +1605,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 50,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_all_noise(all_noise):    \n",
@@ -1812,17 +1638,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 51,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
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K1Jw/gE0F/Aj5grvEVcnly+1/52HD7F5XD7Fyb2rXNcunFMuLp9n2KxfFElSTN/bd1Sad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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f205683b2b0>"
+       "<matplotlib.figure.Figure at 0x7f5d8c8c6b70>"
       ]
      },
      "metadata": {},
@@ -1867,10 +1692,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 52,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def make_immune(target_cls, num_iterations_adversary=500,\n",
@@ -1922,10 +1745,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 53,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1933,23 +1754,23 @@
      "text": [
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   3.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:   1.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    200, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    400, Training Accuracy:  93.8%\n",
       "Optimization Iteration:    499, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:02\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 14.4% (1443 / 10000)\n",
+      "Accuracy on Test-Set: 13.3% (1326 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  42.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    199, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.3% (9529 / 10000)\n"
+      "Accuracy on Test-Set: 93.3% (9327 / 10000)\n"
      ]
     }
    ],
@@ -1966,10 +1787,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 54,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1977,23 +1796,23 @@
      "text": [
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  32.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  17.2%\n",
       "Optimization Iteration:    200, Training Accuracy:  32.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  29.7%\n",
-      "Optimization Iteration:    400, Training Accuracy:  34.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  26.6%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    300, Training Accuracy:  28.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  21.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  18.8%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 72.1% (7207 / 10000)\n",
+      "Accuracy on Test-Set: 80.0% (8002 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  75.0%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
       "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.2% (9519 / 10000)\n"
+      "Accuracy on Test-Set: 92.3% (9235 / 10000)\n"
      ]
     }
    ],
@@ -2012,10 +1831,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 55,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2023,203 +1840,203 @@
      "text": [
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  73.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  75.0%\n",
-      "Optimization Iteration:    300, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  90.6%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 23.3% (2326 / 10000)\n",
+      "Accuracy on Test-Set: 24.6% (2464 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  34.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:      0, Training Accuracy:  37.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.6% (9559 / 10000)\n",
+      "Accuracy on Test-Set: 93.9% (9387 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:  62.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  67.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  67.2%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  65.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  71.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 42.2% (4218 / 10000)\n",
+      "Accuracy on Test-Set: 32.6% (3260 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  45.3%\n",
       "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9555 / 10000)\n",
+      "Accuracy on Test-Set: 94.0% (9401 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  43.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    400, Training Accuracy:  68.8%\n",
-      "Optimization Iteration:    499, Training Accuracy:  71.9%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    499, Training Accuracy:  79.7%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 46.4% (4639 / 10000)\n",
+      "Accuracy on Test-Set: 26.2% (2620 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  59.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:      0, Training Accuracy:  37.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.5% (9545 / 10000)\n",
+      "Accuracy on Test-Set: 93.8% (9380 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  46.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    400, Training Accuracy:  50.0%\n",
-      "Optimization Iteration:    499, Training Accuracy:  48.4%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  50.0%\n",
+      "Optimization Iteration:    200, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:  64.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  59.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 56.5% (5648 / 10000)\n",
+      "Accuracy on Test-Set: 46.3% (4631 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:  46.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  90.6%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.8% (9581 / 10000)\n",
+      "Accuracy on Test-Set: 93.6% (9358 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  87.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    100, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 15.6% (1557 / 10000)\n",
+      "Accuracy on Test-Set: 16.9% (1689 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 95.6% (9557 / 10000)\n",
+      "Accuracy on Test-Set: 93.3% (9332 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  65.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  75.0%\n",
+      "Optimization Iteration:    499, Training Accuracy:  76.6%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 17.4% (1745 / 10000)\n",
+      "Accuracy on Test-Set: 26.4% (2638 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  29.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.0% (9601 / 10000)\n",
+      "Accuracy on Test-Set: 94.1% (9407 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  93.8%\n",
       "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    499, Training Accuracy:  89.1%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 17.6% (1762 / 10000)\n",
+      "Accuracy on Test-Set: 15.8% (1584 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:      0, Training Accuracy:  17.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.7% (9570 / 10000)\n",
+      "Accuracy on Test-Set: 93.8% (9385 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    200, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    300, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    300, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    400, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    499, Training Accuracy: 100.0%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    499, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 12.8% (1281 / 10000)\n",
+      "Accuracy on Test-Set: 13.2% (1319 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  23.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  90.6%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 95.9% (9587 / 10000)\n",
+      "Accuracy on Test-Set: 93.6% (9357 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  64.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  78.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  84.4%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    300, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  76.6%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 24.9% (2493 / 10000)\n",
+      "Accuracy on Test-Set: 26.9% (2694 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  25.0%\n",
+      "Optimization Iteration:      0, Training Accuracy:  23.4%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.0% (9601 / 10000)\n",
+      "Accuracy on Test-Set: 94.5% (9452 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
       "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  50.0%\n",
-      "Optimization Iteration:    300, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    400, Training Accuracy:  64.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  65.6%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    200, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  50.0%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 45.5% (4546 / 10000)\n",
+      "Accuracy on Test-Set: 46.6% (4657 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  51.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  50.0%\n",
+      "Optimization Iteration:    100, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.2% (9615 / 10000)\n",
+      "Accuracy on Test-Set: 94.6% (9462 / 10000)\n",
       "\n"
      ]
     }
@@ -2245,10 +2062,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 56,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2256,355 +2071,361 @@
      "text": [
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
-      "Optimization Iteration:    300, Training Accuracy:  79.7%\n",
-      "Optimization Iteration:    400, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  60.9%\n",
+      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:  57.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  71.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 29.2% (2921 / 10000)\n",
+      "Accuracy on Test-Set: 36.0% (3601 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  29.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  45.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.2% (9619 / 10000)\n",
+      "Accuracy on Test-Set: 94.7% (9474 / 10000)\n",
       "\n",
       "Target-class: 0\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   1.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    200, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    300, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    499, Training Accuracy:   6.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 94.4% (9437 / 10000)\n",
+      "Accuracy on Test-Set: 93.3% (9334 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.4% (9635 / 10000)\n",
+      "Accuracy on Test-Set: 95.2% (9524 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  42.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  60.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  75.0%\n",
-      "Optimization Iteration:    400, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  53.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    300, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    400, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  81.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 28.7% (2875 / 10000)\n",
+      "Accuracy on Test-Set: 25.4% (2543 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  21.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.4% (9643 / 10000)\n",
+      "Accuracy on Test-Set: 94.9% (9492 / 10000)\n",
       "\n",
       "Target-class: 1\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    499, Training Accuracy:  12.5%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  23.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 94.3% (9428 / 10000)\n",
+      "Accuracy on Test-Set: 91.9% (9188 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    199, Training Accuracy:  89.1%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.9% (9685 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9545 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  60.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  64.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  75.0%\n",
-      "Optimization Iteration:    499, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  70.3%\n",
+      "Optimization Iteration:    300, Training Accuracy:  78.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    499, Training Accuracy:  71.9%\n",
       "Time usage: 0:00:02\n",
       "\n",
-      "Accuracy on Test-Set: 34.3% (3427 / 10000)\n",
+      "Accuracy on Test-Set: 34.7% (3474 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  31.2%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.6% (9657 / 10000)\n",
+      "Accuracy on Test-Set: 95.2% (9520 / 10000)\n",
       "\n",
       "Target-class: 2\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    499, Training Accuracy:  17.2%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  14.1%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 94.3% (9435 / 10000)\n",
+      "Accuracy on Test-Set: 90.5% (9051 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.6% (9664 / 10000)\n",
+      "Accuracy on Test-Set: 95.3% (9535 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    200, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  54.7%\n",
-      "Optimization Iteration:    499, Training Accuracy:  64.1%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:  43.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  46.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  48.4%\n",
+      "Optimization Iteration:    499, Training Accuracy:  42.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 48.4% (4837 / 10000)\n",
+      "Accuracy on Test-Set: 58.3% (5833 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  54.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:      0, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.5% (9650 / 10000)\n",
+      "Accuracy on Test-Set: 95.4% (9537 / 10000)\n",
       "\n",
       "Target-class: 3\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
       "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:   1.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
       "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:02\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 95.7% (9570 / 10000)\n",
+      "Accuracy on Test-Set: 94.6% (9464 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    100, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.7% (9667 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9550 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  67.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  78.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  79.7%\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  73.4%\n",
+      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
       "Optimization Iteration:    400, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    499, Training Accuracy:  76.6%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 23.7% (2373 / 10000)\n",
+      "Accuracy on Test-Set: 26.0% (2599 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  26.6%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:      0, Training Accuracy:  34.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  92.2%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.3% (9632 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9545 / 10000)\n",
       "\n",
       "Target-class: 4\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
       "Optimization Iteration:    100, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:   7.8%\n",
       "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    499, Training Accuracy:  14.1%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:    400, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  10.9%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 92.0% (9197 / 10000)\n",
+      "Accuracy on Test-Set: 92.2% (9225 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:      0, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.3% (9632 / 10000)\n",
+      "Accuracy on Test-Set: 95.8% (9579 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  57.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  76.6%\n",
-      "Optimization Iteration:    300, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  85.9%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    100, Training Accuracy:  32.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  60.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  76.6%\n",
+      "Optimization Iteration:    499, Training Accuracy:  76.6%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 23.0% (2297 / 10000)\n",
+      "Accuracy on Test-Set: 33.0% (3295 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  28.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.6% (9663 / 10000)\n",
+      "Accuracy on Test-Set: 95.3% (9533 / 10000)\n",
       "\n",
       "Target-class: 5\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   6.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  21.9%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  18.8%\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimization Iteration:    100, Training Accuracy:   1.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    300, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    400, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  15.6%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 88.2% (8824 / 10000)\n",
+      "Accuracy on Test-Set: 91.9% (9194 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  92.2%\n",
       "Optimization Iteration:    100, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.7% (9665 / 10000)\n",
+      "Accuracy on Test-Set: 95.8% (9576 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  40.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  53.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  51.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  56.2%\n",
-      "Optimization Iteration:    499, Training Accuracy:  62.5%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  14.1%\n",
+      "Optimization Iteration:    100, Training Accuracy:  32.8%\n",
+      "Optimization Iteration:    200, Training Accuracy:  67.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    400, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  53.1%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 44.0% (4400 / 10000)\n",
+      "Accuracy on Test-Set: 40.6% (4061 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  39.1%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      0, Training Accuracy:  51.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.4% (9642 / 10000)\n",
+      "Accuracy on Test-Set: 95.8% (9579 / 10000)\n",
       "\n",
       "Target-class: 6\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  17.2%\n",
-      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    400, Training Accuracy:  20.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:   7.8%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    100, Training Accuracy:   6.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
+      "Optimization Iteration:    499, Training Accuracy:  20.3%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 94.6% (9457 / 10000)\n",
+      "Accuracy on Test-Set: 94.0% (9396 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:    100, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.8% (9682 / 10000)\n",
+      "Accuracy on Test-Set: 96.0% (9602 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   4.7%\n",
-      "Optimization Iteration:    100, Training Accuracy:  65.6%\n",
-      "Optimization Iteration:    200, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    300, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  85.9%\n",
-      "Optimization Iteration:    499, Training Accuracy:  90.6%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    100, Training Accuracy:  59.4%\n",
+      "Optimization Iteration:    200, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    300, Training Accuracy:  87.5%\n",
+      "Optimization Iteration:    400, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    499, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 18.1% (1809 / 10000)\n",
+      "Accuracy on Test-Set: 17.5% (1751 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  23.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  17.2%\n",
       "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
       "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:01\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 96.8% (9682 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9546 / 10000)\n",
       "\n",
       "Target-class: 7\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    100, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    200, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  18.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:  28.1%\n",
-      "Optimization Iteration:    499, Training Accuracy:  18.8%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  17.2%\n",
+      "Optimization Iteration:    200, Training Accuracy:  17.2%\n",
+      "Optimization Iteration:    300, Training Accuracy:  21.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  18.8%\n",
+      "Optimization Iteration:    499, Training Accuracy:  23.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 84.1% (8412 / 10000)\n",
+      "Accuracy on Test-Set: 81.5% (8149 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  84.4%\n",
-      "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:    199, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:      0, Training Accuracy:  71.9%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.0% (9699 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9550 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  46.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  71.9%\n",
-      "Optimization Iteration:    400, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  75.0%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:  26.6%\n",
+      "Optimization Iteration:    200, Training Accuracy:  43.8%\n",
+      "Optimization Iteration:    300, Training Accuracy:  60.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    499, Training Accuracy:  64.1%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 36.8% (3678 / 10000)\n",
+      "Accuracy on Test-Set: 44.9% (4493 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  48.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    199, Training Accuracy:  93.8%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  45.3%\n",
+      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 97.0% (9699 / 10000)\n",
+      "Accuracy on Test-Set: 96.2% (9616 / 10000)\n",
       "\n",
       "Target-class: 8\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    100, Training Accuracy:  14.1%\n",
-      "Optimization Iteration:    200, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    300, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    400, Training Accuracy:   4.7%\n",
+      "Optimization Iteration:    100, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    200, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
+      "Optimization Iteration:    400, Training Accuracy:   7.8%\n",
       "Optimization Iteration:    499, Training Accuracy:   9.4%\n",
-      "Time usage: 0:00:02\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 96.2% (9625 / 10000)\n",
+      "Accuracy on Test-Set: 95.5% (9555 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
@@ -2612,47 +2433,47 @@
       "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.2% (9720 / 10000)\n",
+      "Accuracy on Test-Set: 96.5% (9650 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:  23.4%\n",
-      "Optimization Iteration:    200, Training Accuracy:  43.8%\n",
-      "Optimization Iteration:    300, Training Accuracy:  37.5%\n",
-      "Optimization Iteration:    400, Training Accuracy:  45.3%\n",
-      "Optimization Iteration:    499, Training Accuracy:  39.1%\n",
-      "Time usage: 0:00:02\n",
+      "Optimization Iteration:      0, Training Accuracy:   7.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  28.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:  39.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  42.2%\n",
+      "Optimization Iteration:    400, Training Accuracy:  46.9%\n",
+      "Optimization Iteration:    499, Training Accuracy:  48.4%\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 64.9% (6494 / 10000)\n",
+      "Accuracy on Test-Set: 64.1% (6415 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  67.2%\n",
-      "Optimization Iteration:    100, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:    199, Training Accuracy:  98.4%\n",
-      "Time usage: 0:00:01\n",
+      "Optimization Iteration:      0, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    100, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:    199, Training Accuracy:  96.9%\n",
+      "Time usage: 0:00:00\n",
       "\n",
-      "Accuracy on Test-Set: 97.5% (9746 / 10000)\n",
+      "Accuracy on Test-Set: 96.3% (9629 / 10000)\n",
       "\n",
       "Target-class: 9\n",
       "Finding adversarial noise ...\n",
       "Optimization Iteration:      0, Training Accuracy:   9.4%\n",
-      "Optimization Iteration:    100, Training Accuracy:   7.8%\n",
-      "Optimization Iteration:    200, Training Accuracy:  10.9%\n",
-      "Optimization Iteration:    300, Training Accuracy:  15.6%\n",
-      "Optimization Iteration:    400, Training Accuracy:  12.5%\n",
+      "Optimization Iteration:    100, Training Accuracy:   3.1%\n",
+      "Optimization Iteration:    200, Training Accuracy:   3.1%\n",
+      "Optimization Iteration:    300, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    400, Training Accuracy:   9.4%\n",
       "Optimization Iteration:    499, Training Accuracy:   4.7%\n",
-      "Time usage: 0:00:02\n",
+      "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.1% (9709 / 10000)\n",
+      "Accuracy on Test-Set: 96.1% (9614 / 10000)\n",
       "\n",
       "Making the neural network immune to the noise ...\n",
-      "Optimization Iteration:      0, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:      0, Training Accuracy:  96.9%\n",
       "Optimization Iteration:    100, Training Accuracy: 100.0%\n",
       "Optimization Iteration:    199, Training Accuracy:  95.3%\n",
       "Time usage: 0:00:01\n",
       "\n",
-      "Accuracy on Test-Set: 97.7% (9768 / 10000)\n",
+      "Accuracy on Test-Set: 96.7% (9666 / 10000)\n",
       "\n"
      ]
     }
@@ -2686,9 +2507,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 57,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -2699,14 +2519,14 @@
       "Noise:\n",
       "- Min: -0.35\n",
       "- Max: 0.35\n",
-      "- Std: 0.270488\n"
+      "- Std: 0.27831247\n"
      ]
     },
     {
      "data": {
-      "image/png": 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wzZrsMQdOOyO7dtu27FJW/VW1qbrdN+TXVrlDbF3qmopcl8nWb2UVPpv6owqX9OXggkno\nnrAkFWQIS1JBhrAkFWQIS1JBhrAkFWQIS1JBhrAkFWQIS1JBhrAkFWQIS1JBHTNteaA1cXksO07K\nn4p88O7897/vvvzar341vxbqm4rcCXdFrstk61eTW5V/o9Ont/e93ROWpIIMYUkqyBCWpIIMYUkq\nyBCWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkqqGOmLXf9+Ed07Rp77mD3K1+VPWaVqYgbNuTXVrkz\nc52c2iuNrLu7dAd53BOWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkq\nqNK05Yj4IPBm4ETgKeC7wKUppQcG1RwG9ABvAw4D7gAuTin9dtTBd+6s77bEGbZsKfbWkmrw8pfn\n18645frs2oELLhxHNyOruid8OvAp4BTgdcAhwNcj4lmDaq4C3gj8BXAG8FzgyxNvVZKmnkp7wiml\ncwY/joh3Ar8FFgBrImIG8G5gSUppdavmXcDPIuLklNI9belakqaIiR4TngUk4LHW4wU0g/0bewpS\nSj8HHgJOneB7SdKUM+4QjoigeehhTUrpp63Fc4BdKaUnhpVvaT0nSRpkItcTXgG8GDgtozZo7jFL\nkgYZVwhHxNXAOcDpKaVNg57aDBwaETOG7Q0fRXNveETLVqxg5vTpQ5Y1XvtaGq997XhalKT9ore3\nlxtv7B2yrL+/P/v1lUO4FcBvAs5MKT007Ol7gd3AWcDNrfp5wPOB74027pUXX8z8efOqtiNJRTUa\nDRqNxpBlfX19LFy4IOv1Vc8TXgE0gMXAkxFxdOup/pTSjpTSExHxb0BPRDwO/B74JHC3Z0ZI0t6q\n7glfRPPY7l3Dlr8L2HO28zLgGWAlzckatwOXjL9FSZq6qp4nPObZFCmlncD7Wj+SpFF0zN2WB046\nmYH588es69qxPXvMHTumZdeelnOOR8v69fm1ktpn2Hf3o3rJSyoM3Luxci/t4gV8JKkgQ1iSCjKE\nJakgQ1iSCjKEJakgQ1iSCjKEJakgQ1iSCjKEJakgQ1iSCuqYacu5BrrzpyLP6s4f96ST8msrTYcE\n3v/+avWCVSzOrl3Mqho7mVyq/N7e2p3/e6tyI/TaphZT7d/p7Nn5tQMf/N/ZtV0MtKXmj7WSpGIM\nYUkqyBCWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkqyBCWpIIMYUkqqGOmLXdt/BVdMzLmO86dmz/o\n1q3ZpdOnH5VdO2tWfgsAS5fm1151VbWxc022acCd0APAqr/9bnbt4n96VT09VNh2Vdx07RPZtQ9s\nnpFdu2FDfg9/dnW1ddu+NP9zMW3pe7JrB675TH5txr5rTs0e7glLUkGGsCQVZAhLUkGGsCQVZAhL\nUkGGsCQVZAhLUkGGsCQVZAhLUkGGsCQVZAhLUkEdc+2IXFXmZDM7/3oQz9762/weZuWPC/Cnf5pf\ne/75+bVv+0I91xSo61oFVa4HUVcPVe+xvvifPppdu+ryvvxxL59fqY9aXHBBdum8CsNWqd1+Y7Vr\nhEy7pie/eNu27NL16/OHnTfXW95L0pRhCEtSQYawJBVkCEtSQYawJBVkCEtSQYawJBVkCEtSQYaw\nJBVkCEtSQZWmLUfEB4E3AycCTwHfBS5NKT0wqOYu4IxBL0vAp1NKF486+KZNcPjhY/aw4eD8SZEn\n/C5/GunAy+ubRnrkkfm1b3hDhYG/ULmVoj7+8QrF76+pidmzK5WvOu/67NqHZl+YXbtyZYUmzqtQ\nO8Vtv2h5dm13d/6489Z8O7t2YO4ZY9fUeMv704FPAacArwMOAb4eEc8aVJOAzwBHA3OA5wAfqPg+\nknRAqLQnnFI6Z/DjiHgn8FtgAbBm0FPbU0qPTLg7SZriJnpMeBbNPd/Hhi0/PyIeiYgfR8RHh+0p\nS5Jaxn0py4gI4CpgTUrpp4Oe+gLwK2AT8FLgYzSvbueRLUkaZiLXE14BvBh49eCFKaVrBz38SURs\nBu6MiONTSg9O4P0kacoZVwhHxNXAOcDpKaXfjFH+AyCAucCIIbzsmmuYOX36kGWNRYtovOY142lR\nkvaL3t5ebryxd8iy/v7+7NdXDuFWAL8JODOl9FDGS15B87jxqGF95UUXMf+FL6zajiQV1Wg0aDQa\nQ5b19fWxcOGCrNdXPU94BdAAFgNPRsTRraf6U0o7IuIE4O3ArcCjwMuAHmB1SmldlfeSpANB1T3h\ni2ju1d41bPm7gOuBXTTPH/4b4HBgI/Al4CMT6lKSpqiq5wmPekpbSunXwKKJNCRJB5LOudvyKafA\n/LGnDp9Q4S6mbJ4zgYbap9KdXNd9pb5GMv3yqvw74B57bP64czvh07Z7d7X6gw7KLj24wvo9/nh+\n7dFjl/zBwC35267r3JruaF3BtCXVeqi0fnd9M3/ga67JH/e008au8W7LkjQ5GMKSVJAhLEkFGcKS\nVJAhLEkFGcKSVJAhLEkFGcKSVJAhLEkFGcKSVFAnTCRtuvtu2LJl7LoqtyPetm38/bTRvPfXND30\n7LOzSwf+5yXZtSdUmM76xA3500irTOudll/KrpX5PezYUWFgqvU8uwP+NVVZv+4KU4CrjFt1KnIV\nVaYDDyx6bf64ixZVb6ZN3BOWpIIMYUkqyBCWpIIMYUkqqKNDuHf16tIt1Kb34YdLt1CblSt7xy6a\nxG66aequX2/v1F036Mz1M4QLMYQnry99aequ3/C7Bk81nbh+HR3CkjTVGcKSVJAhLEkFdcAcH7oB\nfrZx415P9D/5JH3D75LZ15c/8j7GHMnAE/XNruv63e/2Wtb/9NP07WN5JVXWr8LvbV/9jmTb2r3H\n7e/vZ+0+lle4ZybPqtDD0/flr9vOnfk9wL577u/v5759vGeV2XVVHFLhd/FUhd/FYYftvay/v5++\nfXxWqvzeqmy7yip8jgf2sY850vpVmYmX42f337/nP7vHqo2UUlvfvKqIeDvwhaJNSFI9zk8pfXG0\ngk4I4SOAs4ENQMWZ/ZLUkbqB44A7UkqPjlZYPIQl6UDmF3OSVJAhLEkFGcKSVJAhLEkFdWQIR8Ql\nEfFgRDwVEd+PiIWle2qHiLgsIgaG/fy0dF/jERGnR8SqiHi4tR573U4hIj4UEZsiYntE/GdEzC3R\n63iMtX4R8dl9bMtbS/WbKyI+GBH3RMQTEbElIm6OiHnDag6LiH+NiK0R8fuIWBkRR5XquYrM9btr\n2HZ7JiJWlOq540I4It4GfAK4DHgF8CPgjoiYXbSx9lkHHA3Maf2cVradcTscWAtcAux1ik1EXAq8\nF/hr4GTgSZrb8dD92eQEjLp+LbcxdFs29k9rE3I68CngFOB1wCHA1yPiWYNqrgLeCPwFcAbwXODL\n+7nP8cpZvwR8hj9uu+cAH9jPfQ7qJqWO+gG+D/zLoMcB/Br4QOne2rBulwF9pfuoYb0GgMXDlm0C\nlg16PAN4Cnhr6X7btH6fBb5Surc2rNvs1vqdNmg77QTePKjmv7dqTi7d70TXr7XsW0BP6d72/HTU\nnnBEHAIsAL6xZ1lq/tbuBE4t1VebvbD1J+4vIuKGiHhe6YbaLSKOp7mHMXg7PgH8gKmzHQEWtf7k\nvT8iVkTEs0s3NA6zaO4ZPtZ6vIDm5QwGb7ufAw8xObfd8PXb4/yIeCQifhwRHx22p7xfdcK1Iwab\nDRwEDL/t8haa/zee7L4PvBP4Oc0/gS4Hvh0RL0kpPVmwr3abQ/ODv6/tOGf/t1OL22j+if4g8ALg\nH4FbI+LU1o5Dx4uIoHnoYU1Kac93E3OAXa3/aQ426bbdCOsHzcsk/IrmX2svBT4GzAPO2+9N0nkh\nPJJg5ONyk0ZK6Y5BD9dFxD00Pwxvpfnn7VQ3JbYjQErppkEPfxIRPwZ+ASyi+efuZLACeDF530tM\nxm23Z/1ePXhhSunaQQ9/EhGbgTsj4viU0oP7s0HovC/mtgLP0DxgPthR7L1XNemllPqBB4BJc9ZA\nps00/9EeENsRoPWPdyuTZFtGxNXAOcCilNKmQU9tBg6NiBnDXjKptt2w9fvNGOU/oPl5LbLtOiqE\nU0pPA/cCZ+1Z1vqT4izgu6X6qktETKf5p+xYH5JJpRVImxm6HWfQ/MZ6ym1HgIg4FjiCSbAtWwH1\nJuA1KaWHhj19L7CbodtuHvB84Hv7rckJGGP99uUVNPfyi2y7Tjwc0QNcFxH3AvcAy4BpwOdKNtUO\nEfHPwH/QPARxDPAPND/wnXfjqzFExOE09xyiteiEiHgZ8FhKaSPNY3F/FxHraV4h78M0z3L5aoF2\nKxtt/Vo/l9E8Jry5VXcFzb9q7th7tM7ROh+2ASwGnoyIPX+t9KeUdqSUnoiIfwN6IuJx4PfAJ4G7\nU0r3lOk631jrFxEnAG8HbgUeBV5GM3NWp5TWlei5+OkZI5xWcjHNf7hP0fy/70mle2rTevXSDKKn\naH7b/EXg+NJ9jXNdzqR56s8zw37+fVDN5TS//NhOM5zmlu67HetH8zKFt9MM4B3AL4H/CxxZuu+M\n9drXOj0DXDio5jCa59pupRnCXwKOKt17O9YPOBa4C3ik9bn8Oc0vVaeX6tlLWUpSQR11TFiSDjSG\nsCQVZAhLUkGGsCQVZAhLUkGGsCQVZAhLUkGGsCQVZAhLUkGGsCQVZAhLUkGGsCQV9P8BdgJ+CcQS\nqzcAAAAASUVORK5CYII=\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2057188518>"
+       "<matplotlib.figure.Figure at 0x7f5d8c9677f0>"
       ]
      },
      "metadata": {},
@@ -2726,24 +2546,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 58,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 97.7% (9768 / 10000)\n",
+      "Accuracy on Test-Set: 96.7% (9666 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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3bq1js70333yzjs1S7y233KLj8847L1yDQ/jwww913KdPH1Srxs856ZTJ/Awj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\nd+ZJRESUqqp45klERJQSdp5ERESW2HkSERFZYud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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f20572d0080>"
+       "<matplotlib.figure.Figure at 0x7f5d8c99fb70>"
       ]
      },
      "metadata": {},
@@ -2754,16 +2572,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 972    0    1    0    0    0    2    1    3    1]\n",
-      " [   0 1119    4    0    0    2    2    0    8    0]\n",
-      " [   3    0 1006    9    1    1    1    5    4    2]\n",
-      " [   1    0    1  997    0    5    0    4    2    0]\n",
-      " [   0    1    3    0  955    0    3    1    2   17]\n",
-      " [   1    0    0    9    0  876    3    0    2    1]\n",
-      " [   6    4    0    0    3    6  934    0    5    0]\n",
-      " [   2    4   18    3    1    0    0  985    2   13]\n",
-      " [   4    0    4    3    4    1    1    3  950    4]\n",
-      " [   6    6    0    7    4    5    0    4    3  974]]\n"
+      "[[ 966    0    0    0    0    1    5    1    5    2]\n",
+      " [   0 1113    4    2    0    0    3    1   11    1]\n",
+      " [   2    1  991    8    6    0    0    7   16    1]\n",
+      " [   0    0    4  978    0   11    0    7    9    1]\n",
+      " [   0    0    4    0  946    0    6    0    3   23]\n",
+      " [   2    1    1    6    0  870    3    2    2    5]\n",
+      " [   3    3    2    0    6   11  926    1    6    0]\n",
+      " [   0    3   24    6    1    0    0  972    3   19]\n",
+      " [   4    0    3    8    5    4    3    4  939    4]\n",
+      " [   3    6    1   11    8    3    0    5    7  965]]\n"
      ]
     }
    ],
@@ -2783,10 +2601,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 59,
+   "metadata": {},
    "outputs": [],
    "source": [
     "init_noise()"
@@ -2801,24 +2617,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 60,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 92.2% (9222 / 10000)\n",
+      "Accuracy on Test-Set: 87.6% (8764 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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RFrkziMgGEbmtgGWUx4HDWu0EcCjst4ui2AH7zQTI68Zyt3OFiJwL4AkA9wfT+sMeHQwO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\nAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2056abcdd8>"
+       "<matplotlib.figure.Figure at 0x7f5dcc037c50>"
       ]
      },
      "metadata": {},
@@ -2829,16 +2643,16 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 970    0    1    0    0    1    8    0    0    0]\n",
-      " [   0 1121    5    0    0    0    9    0    0    0]\n",
-      " [   2    1 1028    0    0    0    1    0    0    0]\n",
-      " [   1    0   27  964    0   13    2    2    1    0]\n",
-      " [   0    2    3    0  957    0   20    0    0    0]\n",
-      " [   3    0    2    2    0  875   10    0    0    0]\n",
-      " [   4    1    0    0    1    1  951    0    0    0]\n",
-      " [  10   21   61    3   14    3    0  913    3    0]\n",
-      " [  29    2   91    7    7   26   70    1  741    0]\n",
-      " [  20   18   10   12  150   65   11   12    9  702]]\n"
+      "[[ 948    0    3    0    0    1   27    1    0    0]\n",
+      " [   0 1110    5    1    0    0   19    0    0    0]\n",
+      " [   5    1 1022    0    0    0    0    0    4    0]\n",
+      " [   0    1   22  955    1   23    1    5    2    0]\n",
+      " [   0    3    2    0  941    0   36    0    0    0]\n",
+      " [   1    0    1    1    0  869   20    0    0    0]\n",
+      " [   1    1    1    0    1    1  953    0    0    0]\n",
+      " [   7   32   77    2   43    4    1  855    7    0]\n",
+      " [  13    7   45    8    7   39  107    1  747    0]\n",
+      " [  11   18    6   10  465   79   32    8   16  364]]\n"
      ]
     }
    ],
@@ -2863,10 +2677,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 61,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# This has been commented out in case you want to modify and experiment\n",
@@ -2948,9 +2760,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda env:tf-gpu]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-env-tf-gpu-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2962,9 +2774,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

From 320750e142e2bf1d133570d1bb3b88fa8227dd88 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 22 Aug 2018 12:45:11 +0200
Subject: [PATCH 49/61] Added links and instructions for running on Google
 Colab

---
 README.md | 141 +++++++++++++++++++++++++++++++++++++++++++-----------
 1 file changed, 112 insertions(+), 29 deletions(-)

diff --git a/README.md b/README.md
index dbbbfde..91227f9 100644
--- a/README.md
+++ b/README.md
@@ -13,57 +13,109 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 
 ## Tutorials
 
-1. Simple Linear Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
+1. Simple Linear Model
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
 
-2. Convolutional Neural Network ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
+2. Convolutional Neural Network
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
 
-3. ~~Pretty Tensor~~ ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
+3. ~~Pretty Tensor~~
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
 
-3-B. Layers API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
+3-B. Layers API
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
 
-3-C. Keras API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
+3-C. Keras API
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
 
-4. Save & Restore ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
+4. Save & Restore
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
 
-5. Ensemble Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/05_Ensemble_Learning.ipynb))
+5. Ensemble Learning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/05_Ensemble_Learning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/05_Ensemble_Learning.ipynb))
 
-6. CIFAR-10 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/06_CIFAR-10.ipynb))
+6. CIFAR-10
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/06_CIFAR-10.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/06_CIFAR-10.ipynb))
 
-7. Inception Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/07_Inception_Model.ipynb))
+7. Inception Model
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/07_Inception_Model.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/07_Inception_Model.ipynb))
 
-8. Transfer Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/08_Transfer_Learning.ipynb))
+8. Transfer Learning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/08_Transfer_Learning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/08_Transfer_Learning.ipynb))
 
-9. Video Data ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
+9. Video Data
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
 
-10. Fine-Tuning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
+10. Fine-Tuning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
 
-11. Adversarial Examples ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
+11. Adversarial Examples
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
 
-12. Adversarial Noise for MNIST ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/12_Adversarial_Noise_MNIST.ipynb))
+12. Adversarial Noise for MNIST
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/12_Adversarial_Noise_MNIST.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/12_Adversarial_Noise_MNIST.ipynb))
 
-13. Visual Analysis ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
+13. Visual Analysis
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
 
-13-B. Visual Analysis for MNIST ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+13-B. Visual Analysis for MNIST
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
 
-14. DeepDream ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
+14. DeepDream
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
 
-15. Style Transfer ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
+15. Style Transfer
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
 
-16. Reinforcement Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
+16. Reinforcement Learning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
 
-17. Estimator API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
+17. Estimator API
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
 
-18. TFRecords & Dataset API ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb)) 
+18. TFRecords & Dataset API
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb)) 
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb))
 
-19. Hyper-Parameter Optimization ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
+19. Hyper-Parameter Optimization
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb))
 
-20. Natural Language Processing ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
+20. Natural Language Processing
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb))
 
-21. Machine Translation ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
+21. Machine Translation
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
 
-22. Image Captioning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
+22. Image Captioning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
 
-23. Time-Series Prediction ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
+23. Time-Series Prediction
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
 
 ## Videos
 
@@ -129,11 +181,18 @@ There are reports that Python 2.7 gives error messages with these tutorials. Ple
 
 ### Environment
 
-After installing [Anaconda](https://www.continuum.io/downloads), you should create a [conda environment](http://conda.pydata.org/docs/using/envs.html)
+After installing [Anaconda](https://www.continuum.io/downloads), you should create a
+[conda environment](http://conda.pydata.org/docs/using/envs.html)
 so you do not destroy your main installation in case you make a mistake somewhere:
 
     conda create --name tf python=3
 
+When Python gets updated to a new version, it takes a while before TensorFlow also
+uses the new Python version. So if the TensorFlow installation fails, then you may
+have to specify an older Python version for your new environment, such as: 
+
+    conda create --name tf python=3.6
+
 Now you can switch to the new environment by running the following (on Linux):
 
     source activate tf
@@ -154,15 +213,39 @@ in a terminal:
 Note that the GPU-version of TensorFlow also requires the installation of various
 NVIDIA drivers, which is not described here.
 
-### Testing
+## How To Run
 
-You should now be able to run the tutorials in the Python Notebooks:
+If you have followed the above installation instructions, you should
+now be able to run the tutorials in the Python Notebooks:
 
     cd ~/development/TensorFlow-Tutorials/  # Your installation directory.
     jupyter notebook
 
 This should start a web-browser that shows the list of tutorials. Click on a tutorial to load it.
 
+### Run in Google Colab
+
+If you do not want to install anything on your own computer, then the Notebooks
+can be viewed, edited and run entirely on the internet by using
+[Google Colab](https://colab.research.google.com). There is a
+[YouTube video](https://www.youtube.com/watch?v=Hs6HI2YWchM) explaining how to do this.
+You click the "Google Colab"-link next to each tutorial listed above.
+You can view the Notebook on Colab but in order to run it you need to login using
+your Google account.
+Then you need to execute the following commands at the top of the Notebook,
+which clones the contents of this repository to your work-directory on Colab.
+
+    import os
+    work_dir = "/content/TensorFlow-Tutorials/"
+    if os.getcwd() != work_dir:
+        !git clone https://github.com/Hvass-Labs/TensorFlow-Tutorials.git
+    os.chdir(work_dir)
+
+All required packages should already be installed on Colab, otherwise you
+can run the following command:
+
+    !pip install -r requirements.txt
+
 ## Older Versions
 
 Sometimes the source-code has changed from that shown in the YouTube videos. This may be due to

From 2510898a9783e8be3fd057b17080d223fd250493 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 13 Sep 2018 08:59:20 +0200
Subject: [PATCH 50/61] Tiny typo fix.

---
 16_Reinforcement_Learning.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index 7dc305f..2496b56 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -547,7 +547,7 @@
     "\n",
     "```\n",
     "source activate tf-gpu-gym  # Activate your Python environment with TF and Gym.\n",
-    "python reinforcement-learning.py --env Breakout-v0 --training\n",
+    "python reinforcement_learning.py --env Breakout-v0 --training\n",
     "```"
    ]
   },

From 24cacdc402daf8d0520176efcc208488505558d8 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 13 Sep 2018 09:06:49 +0200
Subject: [PATCH 51/61] Fix import scipy

---
 reinforcement_learning.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/reinforcement_learning.py b/reinforcement_learning.py
index 357ea7d..cef5545 100644
--- a/reinforcement_learning.py
+++ b/reinforcement_learning.py
@@ -158,7 +158,7 @@
 import numpy as np
 import tensorflow as tf
 import gym
-import scipy.ndimage
+import scipy
 import sys
 import os
 import time

From 48525854f0552a2ce8f9bf4ee58d62de96d06708 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 13 Sep 2018 09:45:57 +0200
Subject: [PATCH 52/61] Clarified installation instructions etc.

---
 README.md | 48 ++++++++++++++++++++++++++++--------------------
 1 file changed, 28 insertions(+), 20 deletions(-)

diff --git a/README.md b/README.md
index 91227f9..2dafd4a 100644
--- a/README.md
+++ b/README.md
@@ -133,15 +133,31 @@ instead use the Keras API for creating Neural Networks in TensorFlow.
 
 These tutorials have been translated to the following languages:
 
-* [Chinese](https://github.com/thrillerist/TensorFlow-Tutorials)
+* [Chinese](https://github.com/Hvass-Labs/TensorFlow-Tutorials-Chinese)
+
+### New Translations
 
 You can help by translating the remaining tutorials or reviewing the ones that have already been translated. You can also help by translating to other languages.
 
+It is a very big job to translate all the tutorials, so you should just start with Tutorials #01, #02 and #03-C which are the most important for beginners.
+
+### New Videos
+
+You are also very welcome to record your own YouTube videos in other languages. It is strongly recommended that you get a decent microphone because good sound quality is very important. I used `vokoscreen` for recording the videos and the free [DaVinci Resolve](https://www.blackmagicdesign.com/products/davinciresolve/) for editing the videos.
+
 ## Forks
 
 See the [selected list of forks](forks.md) for community modifications to these tutorials.
 
-## Downloading
+## Installation
+
+There are different ways of installing and running TensorFlow. This section describes how I did it
+for these tutorials. You may want to do it differently and you can search the internet for instructions.
+
+If you are new to using Python and Linux then this may be challenging
+to get working and you may need to do internet searches for error-messages, etc.
+It will get easier with practice. You can also run the tutorials without installing
+anything by using Google Colab, see further below.
 
 Some of the Python Notebooks use source-code located in different files to allow for easy re-use
 across multiple tutorials. It is therefore recommended that you download the whole repository
@@ -159,30 +175,16 @@ This also makes it easy to update the tutorials, simply by executing this comman
 
     git pull
 
-### Zip-File
+### Download Zip-File
 
 You can also [download](https://github.com/Hvass-Labs/TensorFlow-Tutorials/archive/master.zip)
 the contents of the GitHub repository as a Zip-file and extract it manually.
 
-## Installation
-
-There are different ways of installing and running TensorFlow. This section describes how I did it
-for these tutorials. You may want to do it differently and you can search the internet for instructions.
-
-If you are new to using Python and Linux, etc. then this may be challenging
-to get working and you may need to do internet searches for error-messages, etc.
-It will get easier with practice.
-
-### Python Version 3.5 or Later
-
-These tutorials were developed on Linux using **Python 3.5 / 3.6** (the [Anaconda](https://www.continuum.io/downloads) distribution) and [PyCharm](https://www.jetbrains.com/pycharm/).
-
-There are reports that Python 2.7 gives error messages with these tutorials. Please make sure you are using **Python 3.5** or later!
-
 ### Environment
 
-After installing [Anaconda](https://www.continuum.io/downloads), you should create a
-[conda environment](http://conda.pydata.org/docs/using/envs.html)
+I use [Anaconda](https://www.continuum.io/downloads) because it comes with many Python
+packages already installed and it is easy to work with. After installing Anaconda,
+you should create a [conda environment](http://conda.pydata.org/docs/using/envs.html)
 so you do not destroy your main installation in case you make a mistake somewhere:
 
     conda create --name tf python=3
@@ -213,6 +215,12 @@ in a terminal:
 Note that the GPU-version of TensorFlow also requires the installation of various
 NVIDIA drivers, which is not described here.
 
+### Python Version 3.5 or Later
+
+These tutorials were developed on Linux using **Python 3.5 / 3.6** (the [Anaconda](https://www.continuum.io/downloads) distribution) and [PyCharm](https://www.jetbrains.com/pycharm/).
+
+There are reports that Python 2.7 gives error messages with these tutorials. Please make sure you are using **Python 3.5** or later!
+
 ## How To Run
 
 If you have followed the above installation instructions, you should

From ddb0ab3aba35eac3f4710fe7fd12a72b2dce68c2 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 12 Jan 2019 18:04:35 +0100
Subject: [PATCH 53/61] Tiny fix.

---
 imdb.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/imdb.py b/imdb.py
index 3121899..db3094f 100644
--- a/imdb.py
+++ b/imdb.py
@@ -54,7 +54,7 @@ def _read_text_file(path):
     It is returned as a single string where all lines are concatenated.
     """
 
-    with open(path, 'rt') as file:
+    with open(path, 'rt', encoding='utf-8') as file:
         # Read a list of strings.
         lines = file.readlines()
 

From c47f4fec07ab57616d40c0a4a5fbba6436473ec5 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sat, 12 Jan 2019 18:48:02 +0100
Subject: [PATCH 54/61] Tiny fix.

---
 14_DeepDream.ipynb | 66 +++++++++++++---------------------------------
 1 file changed, 18 insertions(+), 48 deletions(-)

diff --git a/14_DeepDream.ipynb b/14_DeepDream.ipynb
index 3f8f0fb..6f031d4 100644
--- a/14_DeepDream.ipynb
+++ b/14_DeepDream.ipynb
@@ -41,7 +41,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -80,9 +79,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -140,9 +137,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -181,9 +176,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import inception5h"
@@ -217,9 +210,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -263,7 +254,6 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -671,7 +661,8 @@
     "        # Calculate the value of the gradient.\n",
     "        # This tells us how to change the image so as to\n",
     "        # maximize the mean of the given layer-tensor.\n",
-    "        grad = tiled_gradient(gradient=gradient, image=img)\n",
+    "        grad = tiled_gradient(gradient=gradient, image=img,\n",
+    "                              tile_size=tile_size)\n",
     "        \n",
     "        # Blur the gradient with different amounts and add\n",
     "        # them together. The blur amount is also increased\n",
@@ -839,9 +830,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -870,7 +859,6 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -900,9 +888,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1147,7 +1133,6 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1350,9 +1335,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[6]\n",
@@ -1371,9 +1354,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[7][:,:,:,0:3]\n",
@@ -1392,9 +1373,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[11][:,:,:,0]\n",
@@ -1413,9 +1392,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "image = load_image(filename='images/giger.jpg')\n",
@@ -1425,9 +1402,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[3]\n",
@@ -1439,9 +1414,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[5]\n",
@@ -1461,7 +1434,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [],
@@ -1473,9 +1445,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "layer_tensor = model.layer_tensors[6]\n",
@@ -1561,7 +1531,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1575,9 +1545,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

From ae4aaa1aa7b9454f530dd73901a2dba30ad3e17a Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sun, 3 Feb 2019 15:54:32 +0100
Subject: [PATCH 55/61] Tiny fix

---
 22_Image_Captioning.ipynb | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/22_Image_Captioning.ipynb b/22_Image_Captioning.ipynb
index 28eaf6d..a134116 100644
--- a/22_Image_Captioning.ipynb
+++ b/22_Image_Captioning.ipynb
@@ -70,6 +70,7 @@
     "import matplotlib.pyplot as plt\n",
     "import tensorflow as tf\n",
     "import numpy as np\n",
+    "import sys\n",
     "import os\n",
     "from PIL import Image\n",
     "from cache import cache"
@@ -1390,7 +1391,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "batch_size = 1024"
+    "batch_size = 512"
    ]
   },
   {
@@ -2452,7 +2453,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,

From aa0d6796c6bb61a4c81ab1f8d0dc425cc034095e Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sun, 3 Feb 2019 16:21:48 +0100
Subject: [PATCH 56/61] Tiny fix

---
 21_Machine_Translation.ipynb | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/21_Machine_Translation.ipynb b/21_Machine_Translation.ipynb
index 21acd5a..f0653c2 100644
--- a/21_Machine_Translation.ipynb
+++ b/21_Machine_Translation.ipynb
@@ -1719,7 +1719,7 @@
    "source": [
     "Now we can train the model. One epoch of training took about 1 hour on a GTX 1070 GPU. You probably need to run 10 epochs or more during training. After 10 epochs the loss was about 1.10 on the training-set and about 1.15 on the validation-set.\n",
     "\n",
-    "Note the strange batch-size of 640 (512 + 128) which was chosen because it kept the GPU running at nearly 100% while being within the memory limits of 8GB for this GPU."
+    "Note the batch-size of 512 which was chosen because it kept the GPU running at nearly 100% while being within the memory limits of 8GB for this GPU."
    ]
   },
   {
@@ -1732,7 +1732,7 @@
    "source": [
     "model_train.fit(x=x_data,\n",
     "                y=y_data,\n",
-    "                batch_size=640,\n",
+    "                batch_size=512,\n",
     "                epochs=10,\n",
     "                validation_split=validation_split,\n",
     "                callbacks=callbacks)"
@@ -2162,7 +2162,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,

From 7065009e8f0395605cdcab4cdf3269421e19b7c2 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 12 Jun 2019 14:08:03 +0100
Subject: [PATCH 57/61] Replaced deprecated scipy image-resize with PIL.

---
 reinforcement_learning.py | 20 +++++++++++++++-----
 1 file changed, 15 insertions(+), 5 deletions(-)

diff --git a/reinforcement_learning.py b/reinforcement_learning.py
index cef5545..de81a9b 100644
--- a/reinforcement_learning.py
+++ b/reinforcement_learning.py
@@ -158,7 +158,7 @@
 import numpy as np
 import tensorflow as tf
 import gym
-import scipy
+import PIL.Image
 import sys
 import os
 import time
@@ -405,6 +405,9 @@ def print_progress(msg):
 # Size of each image in the state.
 state_img_size = np.array([state_height, state_width])
 
+# Size of each image in the state. Reversed order used by PIL.Image.
+state_img_size_reverse = tuple(reversed(state_img_size))
+
 # Number of images in the state.
 state_channels = 2
 
@@ -435,12 +438,19 @@ def _pre_process_image(image):
     """Pre-process a raw image from the game-environment."""
 
     # Convert image to gray-scale.
-    img = _rgb_to_grayscale(image)
+    img_gray = _rgb_to_grayscale(image=image)
+
+    # Create PIL-object from numpy array.
+    img = PIL.Image.fromarray(img_gray)
+
+    # Resize the image.
+    img_resized = img.resize(size=state_img_size_reverse,
+                             resample=PIL.Image.LINEAR)
 
-    # Resize to the desired size using SciPy for convenience.
-    img = scipy.misc.imresize(img, size=state_img_size, interp='bicubic')
+    # Convert 8-bit pixel values back to floating-point.
+    img_resized = np.float32(img_resized)
 
-    return img
+    return img_resized
 
 
 class MotionTracer:

From 0495ab11a7eef74c2637a9a3fc2ca4bd1eac9022 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Wed, 12 Jun 2019 14:15:36 +0100
Subject: [PATCH 58/61] Tiny math font fix.

---
 16_Reinforcement_Learning.ipynb | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index 2496b56..849ccbb 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -123,11 +123,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The Q-values for the possible actions have been estimated by a Neural Network. For the action NOOP in state *t* the Q-value is estimated to be 2.900, which is the highest Q-value for that state so the agent takes that action, i.e. the agent does not do anything between state *t* and *t+1* because NOOP means \"No Operation\".\n",
+    "The Q-values for the possible actions have been estimated by a Neural Network. For the action NOOP in state $t$ the Q-value is estimated to be 2.900, which is the highest Q-value for that state so the agent takes that action, i.e. the agent does not do anything between state $t$ and $t+1$ because NOOP means \"No Operation\".\n",
     "\n",
-    "In state *t+1* the agent scores 4 points, but this is limited to 1 point in this implementation so as to stabilize the training. The maximum Q-value for state *t+1* is 1.830 for the action RIGHTFIRE. So if we select that action and continue to select the actions proposed by the Q-values estimated by the Neural Network, then the discounted sum of all the future rewards is expected to be 1.830.\n",
+    "In state $t+1$ the agent scores 4 points, but this is limited to 1 point in this implementation so as to stabilize the training. The maximum Q-value for state $t+1$ is 1.830 for the action RIGHTFIRE. So if we select that action and continue to select the actions proposed by the Q-values estimated by the Neural Network, then the discounted sum of all the future rewards is expected to be 1.830.\n",
     "\n",
-    "Now that we know the reward of taking the NOOP action from state *t* to *t+1*, we can update the Q-value to incorporate this new information. This uses the formula above:\n",
+    "Now that we know the reward of taking the NOOP action from state $t$ to $t+1$, we can update the Q-value to incorporate this new information. This uses the formula above:\n",
     "\n",
     "$$\n",
     "    Q(state_{t},NOOP) \\leftarrow \\underbrace{r_{t}}_{\\rm reward} + \\underbrace{\\gamma}_{\\rm discount} \\cdot \\underbrace{\\max_{a}Q(state_{t+1}, a)}_{\\rm estimate~of~future~rewards} = 1.0 + 0.97 \\cdot 1.830 \\simeq 2.775\n",
@@ -4456,7 +4456,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,

From 36229085873d0c2548fc6de5e3a4129e09fec72e Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Mon, 26 Aug 2019 13:52:15 +0100
Subject: [PATCH 59/61] Tiny fix for Google Colab.

---
 README.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 2dafd4a..475ab44 100644
--- a/README.md
+++ b/README.md
@@ -243,9 +243,10 @@ your Google account.
 Then you need to execute the following commands at the top of the Notebook,
 which clones the contents of this repository to your work-directory on Colab.
 
+    # Clone the repository from GitHub to Google Colab's temporary drive.
     import os
     work_dir = "/content/TensorFlow-Tutorials/"
-    if os.getcwd() != work_dir:
+    if not os.path.exists(work_dir):
         !git clone https://github.com/Hvass-Labs/TensorFlow-Tutorials.git
     os.chdir(work_dir)
 

From 1e901d01cb0739de29b9aea33a6b30a1b26e2414 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Thu, 2 Apr 2020 13:44:15 +0100
Subject: [PATCH 60/61] Updated to TensorFlow 2

---
 01_Simple_Linear_Model.ipynb          |  205 +-
 02_Convolutional_Neural_Network.ipynb |  437 ++--
 03C_Keras_API.ipynb                   |  196 +-
 07_Inception_Model.ipynb              |  305 +--
 08_Transfer_Learning.ipynb            |    2 +-
 10_Fine-Tuning.ipynb                  |  273 +-
 11_Adversarial_Examples.ipynb         |   29 +-
 12_Adversarial_Noise_MNIST.ipynb      |   11 +-
 13B_Visual_Analysis_MNIST.ipynb       |  444 ++--
 13_Visual_Analysis.ipynb              |  124 +-
 16_Reinforcement_Learning.ipynb       | 3348 +++++++++----------------
 17_Estimator_API.ipynb                |   11 +-
 18_TFRecords_Dataset_API.ipynb        |  610 +----
 19_Hyper-Parameters.ipynb             | 1156 ++++-----
 20_Natural_Language_Processing.ipynb  |  535 ++--
 21_Machine_Translation.ipynb          |  226 +-
 22_Image_Captioning.ipynb             |  284 +--
 23_Time-Series-Prediction.ipynb       |  443 ++--
 README.md                             |  100 +-
 reinforcement_learning.py             |   10 +-
 requirements.txt                      |    6 +-
 21 files changed, 3432 insertions(+), 5323 deletions(-)

diff --git a/01_Simple_Linear_Model.ipynb b/01_Simple_Linear_Model.ipynb
index e7598f1..6df8479 100644
--- a/01_Simple_Linear_Model.ipynb
+++ b/01_Simple_Linear_Model.ipynb
@@ -22,6 +22,15 @@
     "You should be familiar with basic linear algebra, Python and the Jupyter Notebook editor. It also helps if you have a basic understanding of Machine Learning and classification."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## TensorFlow 2\n",
+    "\n",
+    "This tutorial was developed using TensorFlow v.1 back in the year 2016. There have been significant API changes in TensorFlow v.2. This tutorial uses TF2 in \"v.1 compatibility mode\", which is still useful for learning how TensorFlow works, but you would have to implement it slightly differently in TF2 (see Tutorial 03C on the Keras API). It would be too big a job for me to keep updating these tutorials every time Google's engineers update the TensorFlow API, so this tutorial may eventually stop working."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -33,22 +42,34 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from sklearn.metrics import confusion_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/compat/v2_compat.py:88: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "non-resource variables are not supported in the long term\n"
      ]
     }
    ],
    "source": [
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "import tensorflow as tf\n",
-    "import numpy as np\n",
-    "from sklearn.metrics import confusion_matrix"
+    "# Use TensorFlow v.2 with this old v.1 code.\n",
+    "# E.g. placeholder variables and sessions have changed in TF2.\n",
+    "import tensorflow.compat.v1 as tf\n",
+    "tf.disable_v2_behavior()"
    ]
   },
   {
@@ -60,16 +81,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.9.0'"
+       "'2.1.0'"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -94,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -141,7 +162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -171,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -184,7 +205,7 @@
        "       [0., 0., 0., 0., 1., 0., 0., 0., 0., 0.]])"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -202,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -211,7 +232,7 @@
        "array([7, 2, 1, 0, 4])"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -236,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -277,14 +298,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd2aa71fb38>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -343,7 +364,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -359,7 +380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -375,7 +396,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -400,7 +421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -416,7 +437,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -443,7 +464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -461,7 +482,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -477,7 +498,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -504,7 +525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -521,7 +542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -546,7 +567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -571,7 +592,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -587,7 +608,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -612,7 +633,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -630,7 +651,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -653,7 +674,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -669,7 +690,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -709,7 +730,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -727,7 +748,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -748,7 +769,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -792,7 +813,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -838,7 +859,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -890,7 +911,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -907,14 +928,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd2a7fad1d0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -936,7 +957,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -945,14 +966,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 15.9%\n"
+      "Accuracy on test-set: 22.2%\n"
      ]
     }
    ],
@@ -962,14 +983,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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Wi/qNMplMhEIh+vv78fl8alBnH9JoNPTF62ZmZrhy5Qomk4lwOMzIyAiPPvoodrtdWZZthNls1nMzBINBEokE8/PzvPLKK8zMzDA0NMQzzzxz1zCveDyuZxJKJpMUCgU9sW88Hte309q7JpitpKViqS1clkgkiMfjZLNZpJT6W8vj8RAMBgmHwzgcjpbfLMX202g0dItSS5aiTW10Op36Cp6K9kILEg+FQiwsLGCz2ajVaiwtLWGxWJiamrrrBIJUKqUnyUilUpRKJRKJBPl8nmq1uqGt2+12PB5Py11wLRNLLbXT2bNneffdd5mYmKBSqVCr1XC73Rw5coRwOMxXvvIVxsbGCAQCrSqqYgepVCp88sknTE9PE41GWV1dpa+vj9HRUUKhkHpBtilms5nTp09z4MABurq68Hq9LC8vMzMzw+LiIufPn7/n/kajUR9d1/IB1Go1KpWKvp0QgoMHD/LMM8/gcrkezgEeKSWpVIqZmRlisdgGP4XFYtGzl4TDYbq7u9U0t32KluA5Ho/rVoXBYMDlcqnZOm2MwWCgs7MTs9lMb28vCwsLVKtVlpeX9fndd8s96Xa7dfEzmUz6ao03r6uljVt0dna2fLyipWJ55coV/uqv/opUKrXBodvZ2ckLL7zA8PAw/f39WK3Wljt3FTuD1rDWZ5bSUrLt5sp9ivtDE0uPx8PP/uzP8sQTT7C4uMj09DTFYvGWNn0zw8PDRCIRvX6np6f1cYtLly5tyIpuNBrb4lloqVRrCxHdfFPtdjujo6McOHAAt9u97TF2WsKGu7352sGh/DAgpaRcLm9I9GswGPRUfIr2RfMhajNr+vv76e3tJZ/Pb1gn63YcPnyY8fFx/e/Lly9z7tw5hBBcu3Ztw7btMBIObRJneTONRoNisUg+n8dsNm9I+nszBoNBf+toN1RLP3/zuuKaPySTyXDx4kU9+Hk9QgiEEAwNDXH8+HF95UnFzlCr1YhGo1y+fJl0Og1AKBTi6NGj9Pb2qhfWHsLlctHb20utViMcDt/VGLl5Fp7ZbKajo4PV1dUNL0kpJZlMhoWFBVwuV0tT9LWlCjQaDcrlsh5adDdzXltC12Aw6GIppdRnBGhdO1iL7crn8ywuLvLee+/pwc83YzQaqVQqjI+Pb2k2gmLz1Go1FhYWmJ6eZnV1FSEEPp+PSCRCV1eXEss9hM1m2/KItdFo3ODHXE8+nyeRSGAwGJRY3kwikeDP/uzP6OrqumcgusvlYmBgAKvVqqeZ1waLtASyGtqqgZlMhitXruhzz9ejCa7muA4EAoyNjaku4TZTrVZJJpMsLCzoIUN3eykqHg40a3S9VaplSHc6na0qFtCmYrm8vMx3v/vdTW0bCAR44okn9Jx3RqORTCZDqVTi448/5saNG7fd717rD9dqNT3l1MjIiBLLbaZSqTA3N8fs7KweX6fE8uHmTt12j8dDd3f3LpfmVloqltpN0LKMrGezDadYLDI3N6dPvRJCUCwWdQty/dRJDa3LbjQa6ejowGKx4HA4NoSqDA8PEwgEWj55f79SqVRYXFxkcXGRSqWiT3E0m836ip1ut1vde0Xb0DKxFEIQDoc5fvw4U1NTZDKZLa0JnM1m9VE07bjaSLdmPQoh9FyIN88MGB8fx+/309/fv8Hp3NPTw+joaFvEd+1HCoUCV65cYXJykmw2C6AvbTwyMsLBgwdV/sqHjNvV9c1ttpW0VAW6u7v1xY1yudwdw3m0ke1arUaxWKRQKNzym8lkwu126yEn60MN7HY7TqcTk8m0wXq02WyMj4/j8/kIh8O43W79N23d41bPGtiPaINv2rrQ2owNLcmrVo/qvj9crG//WnRLOz0DLRNLg8HAU089xWOPPcbHH3/MG2+8oUfw34yUkpWVFbLZLNeuXbslDgvA4XBw6tQp3TpZL4pDQ0OMjY3hdrsJBoO6kGphR1p40HqBNRqNuuiqXIrbR6PR2BC+NTk5ST6fx2g0MjIywvHjx+nr62uLuDrF7rHeINLQgtHbpf211LJ0uVy4XC56enqIRCLU6/Xb+iobjQYOh4NsNquHFN2Mx+MhEonoYrk+hCESiRCJRG4RS0Xr0ESzUqlgMplwOp10dXURCoVavnyAYvep1Wqsrq6Sz+eRUuo9xXaa9toWzrjh4WG6urpuGzagoeW+KxQKG7rhGkajEa/Xi9lsvsVKtNvt+kqQSihbi+Y/NpvN2O12fD4fgUAAq9XK008/zenTp1ue5FWx+6TTad577z0WFxep1+v4fD6+8IUvEIlEOHDgQKuLB7SJWDqdzpbHUCl2D00w3W43Xq9XtyB6enro6elRYVoPIZVKhWQySSaT0WOm+/r6GBkZaWkg+nraQiwVDw+aUPb29vLNb36TYrGo9waGh4exWCzK+n8Isdvt9Pf3EwwGOXHiBH6/n8cff5yenh6CwWCriwcosVS0ACEEHo+H06dPt7ooijZBi68VQvDoo4/S09PDoUOH6OrqanXRdJRYKhSKlhMOh3nxxRcBOHDgAC6Xq+VL396MEkuFQtFyAoEAzz33XKuLcVeUc0ihUCg2gRJLhUKh2ARKLBUKhWITKLFUKBSKTaDEUqFQKDaB2EpaNAAhRAyY3t7itD2DUsqHZgFzVcf7H1XHm2fLYqlQKBQPE6obrlAoFJtAiaVCoVBsAiWWCoVCsQnuKpZCiC4hxCfNz5IQYn7d35btLowQ4teEEJeEEOeFEK8KIQY3sU9UCPFpc58fCiG2vAycEOJfCSF+fRPb/aYQ4oYQ4qoQ4n/Z6vnagRbU8eeFEGeFEDUhxM9vcp9drWMhxGPr7sE5IcQLWz1fO7DbdbzuvF8TQkghxKOb2LbeLM8FIcT3hBBbnhguhPiv93q2xBrfarbj80KIk/c67l3FUkqZkFKekFKeAH4P+I/a31LKihBiu+eWfww8KqU8Dvw34Hc2ud/TzX3OAP/7+h+aN2XbLGghxGHgG8AR4GeB3xVCtEfe+y3QgjqeAf4O8Mf3ud+u1TFwgbXn8ARrdfztHbgPu0YL6hghhBv4p8D7m9yl2CzPUaAC/MpNx9vuMj4LjDY//xvwf99rh/t+wJqq/XtCiPeB37n5Td18M0Sa339RCPFB843x7XuJipTydSmllgb9PaDvPov3JnBACBFpWn3fZe3B7xdC/HMhxIfNt8hvryvvvxBCXBNCvA2MbeIczwP/r5SyLKWcAm4Aj91nOduaHa7jqJTyPHD3hdvvzI7XsZSyIKXUFoOxAfsuZGQn67jJvwH+HVDaQvHeYq2OnxJCvCWEeAm4JIQwCiH+/bo6/mazfEII8Z+az8MrwGYSYD4PfFeu8R7gE0KE77bDVt/GfcBpKeWv3WkDIcQh4OvAk803Wh34m83fvrMJ0/zvAT+4z3I9B3za/D4K/K6U8ghrDWSUNVE7ATwi1rqDj7BmJZ4AvgycWlf+XxFCbHi7NekFZtf9Pdf8v/3GbtTxVtiNOkYI8bgQ4mLzXL+yTjz3EztSx80ubb+U8n/cb4GaFuSz/KSOTwL/VEp5kDVNyEgpT7FWj78shBgCXmCt/g8Dfxs4ve54/1oI8ZXbnOq+2/FWTdvvSSlvXVlsI38NeAT4UKwtZ2kHVgCklH//bjsKIX4ReBT4wibL87oQog6cB/4l4AOmm28MgJ9pfj5u/u1irWG5ge9r1mzzDUazjL+3yXPvV3a0jrfArtaxlPJ94EhTLP5ACPEDKeVWrKR2ZtvruOkO+Q+suVruB7sQ4pPm97eA32dN9D5o9uBgrX6Pi5/4I72s1fHngT9pXsuCEOI17aBSyt+6z3Lcka2KZX7d9xobLVRtWUUB/IGU8jfv58BCiC8C/wL4gpTy1mUcb8/TUsr4umP4biqjAP6tlPLbN53rn91P2ZrMA/3r/u5r/t9+Y8fqeIvsZh3rSCkvCyFywFHW/KX7iZ2oYzdr9+rHTXHtBl4SQnxFSnm3+1dsWq46zf1vruN/IqV8+abtvrzJsq3nvtvxdjjFo6yZypr5PdT8/1eBnxdCBJu/dYp7jG4LIT4LfBv4ipRy5abfrjxAGV8G/q4QwtU8Vm+zXG8CXxVC2MWaQ/pvbOJYLwHfEEJYm12AUeCDByjbXiDKNtXx3WiXOhZCDDW7gzSvZ5y1e7CfibINdSylzEgp/VLKiJQywtrYw1eklGeadfLqA5TxZeAfCCHMzbIcFEI4Wavjrzd9mmHg6U0c6yXgbzf9nU+w1r1fvNsO2zHC9GfNk15kbeTrGoCU8pIQ4l8CP2ya5lXgHwHTQojvAL93mzfNv2et+/S95ltlRkr5FSGEn7W3ypaQUv6w2Z16t3ncHPCLUsqzQog/Bc6x1rX4UNtH82Xd3FWTUl4UQvx/wCXW3sb/aBNdmb3OttWxEOIU8H2gA/gbQojfllIeaac6Bn4a+A0hRJW1gah/uN6q3adsZzu+E2HW2sxW+Q4QAc6KtUqOAV9l7Xl6hrU2OQO8q+0ghPjXwBkp5Us3HesvWfNh3wAKwC/d6+R7Ym64EOI5YFhK+a1Wl0WxM6g63v8IIf4xawbQzcK1J9gTYqlQKBStRk13VCgUik2gxFKhUCg2gRJLhUKh2ARbHg33+/0yEolsY1Han48++ij+MGXRVnW8/1F1vHm2LJaRSIQzZ/ZbjO7dEUI8VOn3VR3vf1Qdbx7VDVcoFIpNoMRSoVAoNoESS4VCodgESiwVCoViEyixVCgUik2gxFKhUCg2gRJLhUKh2AR7dhEmjVqtRi6Xo1gsMjc3R7VaJRQK4XA48Hg8OJ3OVhdRATQaDer1Orlcjvn5tRyrDocDs9mMz+fDYrFgNpsxGB7s/S2l1M9VKKwt5+R0OjGZTFoyWYViS+x5sVxdXeXTTz9lenqa3/3d3yWZTPK1r32NQ4cO8eijjzI2NoYQQjWUFlOpVMjn85w7d47vfve7AAwPD9PR0cHp06fp7u6mo6MDh2PLK6ACUK/XKZVKrK6ucuPGDYQQHDp0CK/Xi9FoVM+BYsvsabFsNBoUCgXm5+eZnZ1lbm6OeDxONBrFbrdz8OBBtBR0qpG0BiklUkoymQzz8/NMT08zMzODEAKXy4WUklqtti3102g0yOfzLCwskM1mmZ6exmg0MjAwgNPpRAiB0bhnVy3ek2iWfi6Xo1qtUqvVaDQauN1u3G53q4t3X+xZsaxWqxSLRSYmJvijP/oj5ufnSSQSlMtlXnnlFd5//336+vo4ceIERqPxgbt3iq1RqVSoVCq8+uqr/P7v/z7JZJK5uTlcLpdu7TkcDvx+PybT1h/HarVKpVLhzJkz/Of//J9Jp9PEYjG6urro6urCYDDQ2dn5wJarYvM0Gg3K5TKrq6v88Ic/ZG5ujlgsRj6f56//9b/Os88+i8Fg2DNtc8+KpdbdymazzMzMsLS0RLVaRUpJIpEgl8uRz+dRyY1bh5SSYrFIPp9nbm6OCxcuUKlUqFar2Gw2jEYjRqMRi8WCxWJ5oHNVq1Xy+TwrKytcvHiRbDZLpVKhVqtRLBb1Z0Ox82i9hVqtRjabJZVKEY1GmZycZGlpiWw2y6OPPkqj0dhTPb49K5aZTIbr168zNTVFPB4nm81Sq9UwmUyMjY0RDAbp6enZlkEDxf1TLBapVCq8/vrrfPjhh3z88cdks1n8fj+HDx9mYGCAr33ta3R3d9PT0/PA55uYmNDPs7S0hMvl4tlnn6W/v5/R0VGCwSBWq3UbrkxxL5LJJNeuXWN5eZk33niDWCzG5cuXSaVSlEol6vU6S0tLFItFLBYLdru91UXeFHtWLEulEvF4nEQiQbFYpFxeWzXXYDAQCATo7+/H4/EoH1ULkFJSrVYplUpMTEzw3nvvMTc3R6VSwWKxEIlEGB0d5ZFHHiEQ2J5saIlEgsuXLzM9PU0ul8Pn8zE+Ps7g4CB+v19FRewihUKBmZkZotEoP/7xj4nFYrqLDNbGD3K5HJVKZU8ZMntOLDWH8ezsLK+//jrRaFSvBACj0cjw8DDHjh3btoaouD+klCSTSZLJJNPT00xMTLC6uoqUkmAwyFNPPUVvb++2+A+z2SyFQoFLly7x5ptvUq1WOXjwIMPDwxw/fpze3l4llLtEpVKhWCwyOTnJX/7lX7K0tMTS0hL5fM1TNPMAACAASURBVJ56/ScLoEopuXLlCn/+53/OyMgIp06dwmKxtL3lv+fEstFoUKvViMVifPjhhyQSCarVqv67yWRicHCQQ4cO0dHR0cKSPrw0Gg3S6TTLy8t6pIJGR0cHp06dwu/3Y7PZHvhc+XyeRCLB1NQUZ86cIRwOc/LkSUZHR3V3zF7p5u11KpUKuVyO2dlZ3nrrLVKpFNlslkajAWyMSJmamuL111+nWCxy5MgRACwWS1v7MPecWBYKBVZXV4nFYsRiMTKZzIa3ltFoJBgMMjAwsOdCE/Y6UkoqlQqlUom5uTmi0SiZTAaAgYEBRkdHOXnyJG63G6vVuuUumJSSXC5HuVzm/fff58KFC1y4cAEpJS6Xi6GhIfr6+rDb7ZjN5rZugPuJWCzGxYsXuXHjBoVCgXK5fMdBtUQiwdWrV6nX61SrVfx+P+Pj47jdbgYHB7Hb7W3XRd9zYrm6usrCwoJusazvghsMBiwWCwMDA4yPj6tGsstIKSkUCuRyOSYmJrh06RLxeByA0dFRXnzxRYaHh/H5fA/U5Wo0GqRSKdLpNC+//DL//b//d3K5HFJKvF4vR44cob+/H5fL9cCj7IrNMzc3xxtvvMH169fJZDJ3FcuFhQUWFxe5fPkyr732GpFIhOeff56+vj46Ojp0K7Od2vCeFMvFxUXS6bRu3gN6HF1XVxdWq7WtbvLDQqVSYXJyklgsxo0bN4hGo1QqFbxerz7o5vf7H3jQTUpJNpslkUiQyWTI5/PYbDa8Xi99fX309/cTCoUeKG5TsXm0YPNEIkE0GmV5eRkpJUajUbcQNQt/dXVVN3C0EKNSqUQ6nWZiYkIPAfN6vRgMhrYaoN1zT9PCwgJnzpwhGo1ueGtZrVYOHDhAT0+P6n63iNXVVV5++WWuX7/O22+/zezsLMFgUPchnzp1Crvd/sANoF6vs7CwwNTUFEtLS2QyGcbHxzlx4gSPPfYYp0+f1ueDK3aefD7P6uoq165d4+2336ZQKFCtVrFarXR3d2O32/XIlKtXr7K8vKzvq8Vjzs/P8+qrrzI8PMyXvvQlvF4vJpNJieWDUCwWSaVS5HK5DZal1WolHA7T39+vHPotQkpJqVTS/VXlchmDwYDdbsdms2G1WrfsQ9SskEwmw+rqKrOzs8zOzuqj7J2dnYyOjtLb24vNZlNCuYto8/4LhQLFYpFGo4HT6cTr9TI2Nobb7danm1YqFaxWK/l8Xm/D1WqVer3O6uoq6XSamZkZLBYLIyMj+Hw+DAZDW/QU99QTJaXUA1wXFxd1y9JkMuHz+Xj22WcZGxvbliBnxdbQ/Ezax26309HRoVt6W3Haa3GbqVSKH/7wh7oVEo1GdZ/oiRMn+OY3v4nT6VR+yl1ECxOLRqOsrKxQLBZxOp0MDg4yNjbGr/7qrxIOh6nX69RqNb1X+OGHH3L27FlWV1dJpVL6bKtoNMp3vvMdent7+eVf/mU+85nPYLfb26JO94xYaje7UCiQyWQoFou6WBoMBqxWK4FAQM3UaCOEELpFWCgUSCaTmM1mvXt1L9+yFiamTVmMx+O6Rbm0tEQ8Hqder+vdvO7u7rYbQX0Y0PyO1WqVRqOBxWLB7/cTDAbp7++np6eHarVKtVolFosBMD09jd1u3zBAq80lj8fjGI1GSqUSjUajbaap7gmxlFKytLSkT6O6du3ahhk7VqsVh8NBb28v/f392xK/p3hwpJR6gpNCocD09DRmsxmHw4HP5+PRRx/F5XLdcX8t6UYmk2Fqaop0Os0nn3xCJpPRrZGhoSHC4TCDg4O7eGWK9WiGjBbCFwqF+NKXvsTg4KA+IUB7QR4+fJihoSHi8ThXr14FYGVlZUN2MJPJhNVqxWQybbk3shPsGbHM5/Ok02nS6bQeuwdrcZVmsxmr1YrT6VSzNVqIlgJt/QOez+fJ5/NEo1GEEJjNZpxOJ4FAgO7ubrxe7x2Pt7y8zI0bN0gmk1y5coVsNsvk5KSe1NdkMuHxeOjp6cHj8bSFX+thRIuV1MYQbDYb3d3dBAIBfYBGc8v4fD68Xq8ePqblbtD21UbONXFtF38l7CGx1PJUptPpDb/5fD4ef/xxhoeHlVC2GLvdzqlTpwiHw8zNzZFOpymVSpTLZdLptJ6M12QyYbPZmJycvKsvqlgsks1mKZfLZDIZPd2bEAKPx4PdbueJJ57gc5/7HGNjY7t4pQoNKSUzMzN8+OGHzMzMAGtTUC9dukSpVOLEiRO33S+dTjM9PX1LCKDZbKa3t5eBgQG8Xi9Wq7VtRsT3jFiurq7qSTPW43Q6GRkZYWhoSPkqW4zZbGZoaAiXy0VXVxdOp5N6vU65XKZQKOgWodblun79+j2thtslb9bi97xeL8PDw5w8eRKfz9c2FsjDRjKZZGpqikQiQaPRoFQqsbCwgNPppFar3bK9NnkhkUhQKpU2+CQNBgM+n4+uri7sdntbRTW0T0nugpSSdDrN/Pw82WwW+Im53tnZyWc/+1n6+vpUYtcWYzKZ8Pv92O12XnjhBR555BHi8bjuPonH48TjcW7cuEG9XsdqtWK1WolEIrf1XXZ2dtLb28vi4iKvvPIK+XweWKv7YDCofzo6OpSfukUIIQiHwxw7doxSqaRblIuLi7hcLlZWVgD0GT3ahJJPP/1UH6S12Wz64E65XOby5cuk02meeOIJurq6cLlcbVG/e0osFxcXyeVyAHpXzu/385nPfEYPflW0DqPRiN/vp6uri69+9atUKhUWFhaIxWJEo1GuXr3KtWvXmJqaAtBHsY8fP053d/ctxxsZGeHxxx/no48+4n/+z/+5QSy7urro6+vTxVLROsLhMEePHmV2dhYhBKVSSc8pqoV2zc7Okslk+OSTT5iZmeHixYuUSiW9HdfrdT1r0ZUrV1haWmJ2dpa+vj6MRqMSy3vRaDTIZDLkcjk91VcqlQJ+Mg9cGwl3OBxtM2r2sKMN5Agh6OjowGQyYTabcbvd9PX1EQgEaDQaerD6wYMHbzvQo80R1nxWRqMRl8uF2+3m6NGjjI2NEQqFdvvyFOsQQuD1eunp6dHrS8s6NT09zV/91V/hcrlIJpMUi0Wmp6dJpVJUq1XC4TDd3d2MjY2RSCT46KOPKJfL+ioI0WhUHwhqhxdiW4ulNg1qZWWF8+fPc+bMGT08QXvbOJ1OfD4fHo+nxaVVrEfrYjscDqSUjI6O6ouXaXWo+RjvNOKZz+dJJpO6WJpMJkKhEMFgkGeeeYbHHnvsrqPpit0hGAzidrvp7e3FbrfrluXS0hKXLl3S420BfTBncHCQ0dFRHn/8cb7+9a9z+fJlEokEKysr+hTWjz/+mEwmQyAQYHh4uJWXCLS5WMLaJP1yuaxP1tewWCx0dnaqbOhtzu0yx5jN5k3tq8VmLi8vU6/X9YxSvb29+uJj7TQA8LCixUWGQiGOHj2q+6VrtdqGoHOtp+FyuRgdHeXIkSMcPHiQjo4OOjs7CQaD1Go14vE41WqVdDrNysqKPglFCylq2XW27MyboNFoUCwW9WU019PR0cHRo0cZHh5WDWafMj09zV/8xV/o2fA7Ojp49tlnGR0d5cCBAyq2sk2wWq1YLBYef/xxHA4HZ86c4b/8l//C6uoq9Xp9w7TkY8eOMTo6yjPPPMNTTz2F3W7H5XJRLBY5efIkfr+f2dlZCoWCPsL+5JNPsrKygsfjaWl3vK1VRgtG11bq0xBC6IHN2kR7xf6hUqlQLpdJJpMsLCzogwQmkwm3243X6237rNoPG0II3G43PT099Pf309fXRzqdJplMUq/XEUJgtVrp6elhcHCQ7u5uOjs79UkMDoeDcDhMtVrF6/VSLpc3TJNdXl7GYDAosbwTlUqFS5cubUgiqw3qRCIRnnnmGbq7u1V85T5jdnaWyclJ3n77bd544w3K5TJCCGw2Gy6XC5fLpXoTbYgW5qN1tWOxGGfOnKFYLOqDec899xzHjx+ns7NzwwsvEAjw3HPPMTc3x/z8PFNTU1y/fp3l5WXeeecdcrkcn//85+nr62vZS7JtnzgtAUMymSQWi1EqlYC1wQCTyYTL5dLDRpRlub8oFArEYjGSySSpVAopJU6nc0OaN1Xn7YfZbMZsNuP3+xkZGcHj8RCPx8nn8zgcDmw2G729vYTD4Vt6BhaLhUAgQLVaJRgMks1muXHjBpVKRc8RoK3n06oxirYUy3q9TjabZWVlhXPnznHmzBmSySSwFpvX1dVFd3c3Q0NDOJ1ONcCzz1haWuL8+fPMzMzQaDT0UKGhoSFGRkb0NVoU7Ynb7WZ8fJyhoSFGR0ep1+v6PO9QKITNZrvlZadNMtHibr1er54oeGlpiWq1yokTJ8jlclit1pbEXbalWGpTpnK5nL5CoIa2KLvL5dLnjir2F1q9r66uAugjrd3d3XR0dKhM+G2OFqkCawHrm0WLnQ6FQlSrVZxOJwaDQV9fScsToGUa2+3ueFuKZblcZm5ujtnZWb37rREKhThy5Ah9fX2qK7YPWZ/gOZFIYDKZCAQCPPnkkwwMDNw1pZti72Oz2RgfH8fv9/PZz34WWMs+lU6nuX79Om+99Rb9/f2cPHly1/3WbSmW1WqVeDzOysrKhjgtWMsyNDw8jN/vV6Oh+5RMJsP09DSVSgWj0YjP5+Po0aP09PS0xbQ3xc5hNpvp7+/H5/Nx4MABstks2WyWubk5FhYW+PTTT5FS8pnPfEaJJfxkLRctUzKgB6QODg7yyCOPMDg4qCzLfYSUktnZWZLJpB5nB+jJggOBAF1dXZsOaFfsXbTpsmNjYxiNRhYXF5mammJhYYF3330XKSWnT5/W1/bZLR1oS7HUgtG1xY9gzW9lt9sZGRnhySefbMtF2BVbp16vMzExoSfayGaz2Gw2PB4PTqeTcDhMMBhsdTEVu4TFYtF7Ex9//DEffPAB8/PzRKNRjEYjX/3qV/UlRXZLB9pSbbRueCwW04PRLRaLHn6gpZxX7B+klHpm9EQiAYDD4aC7u5uuri494kFbwqBUKlEsFm+bL1Gx99GC3Ds7O4lEIhw7doxgMKhnILt48SI3btzYYFDtNG2pOMVikevXrzMxMaGn5dKCXbUM2SpcaH9Rr9e5cuUKP/7xj1lcXEQIQWdnJ8eOHWNkZASTyYSUUs9KUygUqNVq+Hw+9eLchxgMBgKBAB0dHTz55JM4HA7eeustPWj9pZdeYmxsjNHRUSwWy67M6Gq7p0zLSpPP53XLQQihx2G127ociu2jVqtRqVT0rETaBIRGo0EqlaJQKLC8vLxhG6PRqJYT2adoazppSaC7urr03JfLy8t0dnaSz+dxu936mj07SVuJpSaU2nKYy8vLegINbaU37aYosdz/aC/JbDbLBx98QLFY5LXXXiOdThMKhXC5XPzcz/3cbRMHK/YHBoOBAwcOEAwGWVxc5J133qFYLHL27Fk9xNBoNOrx1ztalh09+gNgMBg2iKJ2Q5RQPjxUq1Xy+TypVIqZmRlmZ2eJxWKkUqlbQsoU+xdtvaVAIKCHFWmTVrQpsbvhu24ryxLQEyYMDAxQq9VYXl6mUCjg9Xrp7u5WQckPEYuLi7zxxht6Vhq73c7w8DDd3d188YtfZGhoiKGhoVYXU7HD2Gw2LBYLTz31FL29vbz55pt861vfIplM8sorrxCJRPQExDtJW4mllijWZDLh8/no7OzUb5TdbsfhcKg4u32M2WzGZrPpMbX1ep10Oo0Qgmw2i9fr5dixY/j9fvr6+hgYGFBTHx8CDAaDvkid1WplZmYGs9lMvV5nfn4eo9Goj4rvZBhRW4kloOes+9KXvsTy8jIAc3NzjI+PEw6H8fl8LS6hYicwmUz81E/9FF6vl7Nnz3L27Fk8Hg/d3d0EAgGOHTuG2+3WpzwODAzg8XjUy/MhQouC6enpYXx8nFwux40bN8hms8zMzOjJgXfKd9l2Yglr8XVjY2MEg0GuXLmCzWYjHA7T1dWllrvdpxgMBiKRCHa7ndXVVebn5wmFQoyOjtLf388Xv/hFXC4XTqdTH+hTvuuHC63evV4v4XCYxcVFrl69SrVaJZlMks1mcblcD5dYaqv4mUwmnnnmGTKZDG63G4fDQU9PT6uLp9gBhBD6muNPP/00Bw4cwOl06rG12sqBWi5LJZQPLwMDA7z44ovcuHGDdDqN0WjUB3u6urp27LxtKZYGg0Ff3vb06dOtLo5iF9CC0Ds7O+nv7291cRRtTG9vL8899xznzp3j5ZdfJp/Pk8/nSafTt6zVtZ20pVgqFArFndDyXobDYZ5//nnK5bI+HXIn3XRKLBUKxZ5CS/47PDzMr/7qryKl1OOvd9I9o8RSoVDsSbQww92ibWfwKBQKRTuhxFKhUCg2gZBSbm1HIWLA9PYWp+0ZlFIGWl2I3ULV8f5H1fHm2bJYKhQKxcOE6oYrFArFJlBiqVAoFJtAiaVCoVBsgruKpRCiSwjxSfOzJISYX/e3ZbsLI4T4vBDirBCiJoT4+U3uExVCfCqEOC+E+KEQYstps4UQ/0oI8ev32OaxdffgnBDiha2erx3Y7Tped96vCSGkEOLRTWxbb5bnghDie0KILU/TEEL813s9W0KI55vP0ydCiDNCiJ/e6vnagRa040EhxKvNe/hjIUTfJvZp/3YspdzUB/hXwK/f9H+mze6/yXNEgOPAd4Gf3+Q+UcDf/P5/At+66XcBGLZ6jbfZxqFdNxAGVrb7PrTqsxt13DymG3gTeA94dBPb59Z9/yPg17ZaRuC/3uvZAlz8ZPDzOHCl1XWzl+oY+B7wvza/PwP84Sb2aft2fN/d8Oab+feEEO8Dv3Ozijff/pHm918UQnzQVO9vCyHuuqKQlDIqpTwPbHVtyzeBA0KIiBDiqhDiu8AFoF8I8c+FEB8231y/va68/0IIcU0I8TYwdq8TSCkLUkoth70N2HfhBDtZx03+DfDvgNIWivcWa3X8lBDiLSHES8AlIYRRCPHv19XxN5vlE0KI/9R8Hl4B7rn4uJQyJ5utCHCi6vh+6/gw8Frz++vA8/dZvLZsx1v1WfYBp6WUv3anDYQQh4CvA09KKU8AdeBvNn/7zma6X1vgOeDT5vdR4HellEdYu3mjwGPACeARsdblfwT4RvP/vgycWlf+XxFC/Modru1xIcTF5rl+Zd1N30/sSB0LIU4C/VLK/3G/BRJCmIBn+UkdnwT+qZTyIPD3gIyU8hRr9fjLQogh4AXW6v8w8LeB0+uO96+FEF+5w7leEEJcAf4H8Hfvt6x7hJ1qx+eAn2t+fwFwCyHuJ3daW7bjrU6s/J6Usn6Pbf4a8AjwoVib3G5nzdRFSvn3t3jeO/G6EKIOnAf+JeADpqWU7zV//5nm5+Pm3y7Wbrob+L6UsgDQtFJolvH37nQyKeX7wJHmg/QHQogfSCm3YiW1M9tex0IIA/AfgL9zn2WxCyE+aX5/C/h91kTvAynlVPP/fwY4Ln7ij/SyVsefB/6keS0LQgjN4kFK+Vt3OqGU8vvA94UQn2fNEv7ifZZ5L7BT7fjXgf8khPg7rFmJ86yJ7L1o63a8VbHMr/teY6OFamv+K4A/kFL+5hbPcT88LaWMa38IIXxsLKMA/q2U8tvrdxJC/LMHOamU8rIQIgccBc48yLHakJ2oYzdr9+rHzYbXDbwkhPiKlPJu96/YtGp0mvvfXMf/REr58k3bfXmTZbstUso3hRDDQgj/+mdsn7Aj7VhKuUDTshRCuICvSSnTm9i1rdvxdoQORVnrDmldLG25vVeBnxdCBJu/dQohBrd6kmaXaKu8DPzdZsUhhOhtlutN4KtCCLsQwg38jU2UY6jZHaR5PeOs3YP9TJRtqGMpZUZK6ZdSRqSUEdYGeL4ipTzTrJNXH6CMLwP/QAhhbpbloBDCyVodf73p0wwDT9/rQEKIA6Kpxs3rtQKJByjbXiDKNrVjIYS/2YsA+E3g/1n3255tx9shln8GdDb7/v8YuAYgpbzEmin9QyHEeeBHrI063c2fdUoIMQe8CHy7eUyEEH7W3ipbQkr5Q+CPgXeFEJ8C/w1wSynPAn/Kmo/lB8CH68pyJ1/HTwPnmt3C7wP/cB9aHDezbXV8F8KsWTdb5TvAJeCsEOIC8G3Wek7fB643f/su8K62w118ll8DLjTr+P8Cvr5uwGe/sp11/BRwVQhxDQgB/0dz+z3djvfE3HAhxHPAsJTyW60ui2JnEEL8Y2BGSvnSPTdW7En2ejveE2KpUCgUrUZNd1QoFIpNoMRSoVAoNoESS4VCodgEW17tx+/3y0gkso1FaX8++uijuHyIsmirOt7/qDrePFsWy0gkwpkz+y0O++4IIR6q9Puqjvc/qo43j+qGKxQKxSZQYqlQKBSbQImlQqFQbAIllgqFQrEJtjzAo1AoFLdDSkmj0SCRSPDmm2+SSqXIZDLUajWCwSAej4fDhw9z+PDhVhf1vlBiqVAothUpJfV6neXlZf74j/+YyclJpqenKRQKHD9+nP7+fr7xjW8osWwltVqNRqNBuVymXr8116jRaMRqtVIqlVhYWKBWq+F0OjGZTNhsNsxmM3a7HavV2oLSKxR7G22tmlQqxcTEBDdu3GBpaYlUKkW5XAbA4XDg8/mw2Wz3OFr7sW/EstFoUCwWqVarJJNJisXiLds4HA46OzuJxWL86Ec/olgs0tPTg9vtJhgM4na7CYVCBAIPTUyyQrFtSCmp1WrMzMzw53/+50SjUa5fv046nabRaGCxWOjq6mJwcBCv19vq4t43e1YsK5UK+XyearVKLpejUqkQj8cpl8vE4/HbiqXT6cTv95NMJrlx4walUolsNovNZqOzsxOn08nJkyeVWCoUWyCXy5FMJpmbmyMajRKLxbBarXR2dtLV1YXb7ebgwYNEIhF8Pl+ri3vf7FmxTCQSXL16lXg8zqeffko6nebq1atks1mWl5cpFAq37KNZjpVKhfn5earVqrYsJgaDAZPJxG/8xm9w7Nix3b4chWLPMz09zTvvvMOFCxd47bW1pY4GBwfp6uriy1/+MpFIhLGxMUKh0J50dbW9WNbr9Q1d7HK5TLlcZnFxkampKeLxONFolEwmw9zcHKurqyQSiduKZS6Xo1qtUq/XSafT1Gq1DYJpNBrJ5/O37KdQKO5NuVwmk8mQzWbJ5/OYTCZcLhddXV309fUxMDCA3+/H4/G0uqhboq3FstFokEqlyOfznD17lmg0yuXLl7l69SrFYpHV1VUqlQqFQoFarUaxWKRer1Or3X51glKpxNLSEvCTwSCV/Fih2B5KpRLpdJpcLke9XsftdjM2Nsbg4CBjY2MMDAzsSYtSo63FUkpJuVymUCgwPz/P9evX+fTTTzl37hyNRmODVXg3hBAYDAaEEBusSKPReMt2N/+fYvfQRlO1741Gg3q9roeiaAghMJlMGAwGvV61j6J1SCn1nhuA2WzG5/PR0dGB2+3G6XS2uIQPRluLZaPR0LvVZ8+e5e233yadTlOtVu/LKnS5XHg8HpxOJx0dHXdsVEajke7u7u28BMV9kM1mKRaLuqtlZWWFaDRKLpdjZmaGRqMBgMVi4dixYwSDQYLBID6fD5fLhdvtbvEVPNzUajVKpRKVSgWTyYTD4eDAgQMMDw/veaGENhHLm0VPE7P1luXi4iI3bty47f7rxc9gMNzy/3a7HZ/Ph9frpaenZ8M26zEYDHvWn7KX0azIQqFANpulUCiQz+eZnZ3lwoULJBIJLl++TKVSwWAwYLPZdP+ylFLvOTgcDr3OlaW5+zQaDSqVCo1GAyEEVqsVv9+P3+/HbDa3ungPTEvFslKpUK1WmZ+fZ3JyErvdTiAQwOFw0NvbC6wJmNFoxGKxYLPZMJlMGI1GvRvudDoJh8PYbDZ8Ph9Wq5Wuri4cDgderxen04nT6cTlcmG32/F6vXdtRIcOHdqty3+oqdVqpFIpCoUC165dI5lMcv36dVZWVsjn8xSLRbLZLLFYjGKxSDKZ3NC9q1QqeL1e3ars6OjA7/fjcrn0Bnrq1CmcTucdX46K7UGzJqenp/nggw+oVquEQiH6+vro7e0lHA7vaV+lRkvFslqtUiwWmZmZ4Z133qGjo4PR0VE6OzsJBoOYTCbdj2gymbBarVgsFiwWC9VqVbcER0ZG8Hg89Pf343K5GBkZoaOjg76+Pv2tZjKZ9GMoWo8mlslkkvfee4+ZmRnOnj3LzMyMLpZ3Y3Z2FvjJy7Sjo4NAIEAgEGB0dJSRkREOHz6MzWZTVuYOU6lUyOVyLCwscOnSJVwuF6OjowSDQUKhEF1dXa0u4rbQErGs1+vU63XOnTvH5cuXuX79OufPnycSiTA4OKj7poxGI36/H6vVytNPP00oFMJut+N0OimXy6yuruLxeBgeHsZut9PR0YHVaiUQCOhdb7vdrjcoZWG0jlKpRD6fJ5vNMjs7SyaT4dKlS6TTaS5cuEA8HicWi1EqlTAajbhcLr13YDKZsNvtVCoVpqamKBaLeDwerFYruVxuQ1hZOp1menoaIQSXL18mFAoRiURwOBytvgX7EiklMzMzTExMMDMzs23RJVJK0um07r+uVqv6b1arFZfLhdlsxuFw7Fq7bolY1mo1KpUKb7/9Nt/73veIxWIsLCzwyCOP8NM//dP64I024BIMBnnxxRfJ5XK67zGfz5NKpfQpVOvFcL3fStEe5PN5PTb2tddeY2lpiXfffZdMJkOhUNgQ2eDxePQpqAcOHMDpdBIIBMhkMsTjcWq1GqFQCI/Ho1ui1WqVfD5PqVQilUqRzWYZGRmhr69Pd8soth8pJVevXuX111/nypUrt83JsBXq9TorKyukUinS6fSG+Gev10tfXx9OpxObzbY/xVKbOzoxMUEsFmNqaopEIoHZbGZoaIhIJKKPbq4P4TEYDNjtdoQQut/SZrPpbxctjESJY/uxsLBAPB5ncXGR6elpFhYWmJiYIJlMsrq6qvudesNcFAAAGvJJREFUNevRZDIxODhIf38/HR0d9Pb2YrVa8Xq9JBIJQqEQJpOJQ4cOEQwGgbVuoBBCF1yDwUCxWOTy5ctks1keffRROjo69OdEsb1ks1kWFhbIZrPA2rTi3t5euru7MZk2JzH5fJ6ZmRlKpRKZTIZSqcTc3BzZbJZcLrdhkonL5SIUCuHz+RgfH8flcunjFjvJroplvV6nUCjwgx/8gDNnznDu3Dnm5ub4zGc+w+c+9zkOHTrEsWPHcLlcWCyWDfu63W5cLpcuiJr/EpQF2a40Gg0++OAD3njjDSYnJ7lw4QL/f3vnGtvmdSbo54g3URIvkiiSEqmrdbFkS5EvtevEtR27uRVJOkmayQANusVitztogcVi0flR7PyY/bMD9OdgdtEBisXOLrC9pJPdumiDSZrGTeN6Etd2bEeyK1vWjRJFiZRIURIpitS3P6RzSsl2IjuiRHnPAxAiRX78Pn7vd97vPe95L4uLi6qwwvLyMjabjcbGRiorK/H7/bjdbp588klOnDiBxWLBZrMpn+PY2BhXr15lcnKSl19+mY6ODt544w0ApqeniUQi6rqIRqO8+eab1NbWcuLECbX4s/G60nw+DMNgfHycq1evMjc3h2EYVFdXc/z4cRobG7Hb7Zv6nnA4zE9/+lPC4TBXr14lmUyqpJONVcTMZrNa2H3mmWcIBoM8//zz1NXVFepnru63oN++xsrKCtlslpmZGeLxOOPj40xMTKi7hcPhoKGhAZ/Pp0qlbVSA93LSayVZfMjA8kQiQSqVIhQKMTo6qkp1ZbNZcrkcJpNJRT60tLRQU1ODz+fD5XJRW1tLZWWlyteXyCmXDB8qKyujpqaGYDBIJpNhcnKSXC5HJpMhm82yuLhIKpXS2VoFQoZ8ybRhWVmovLwcv9+Px+O5r2W5vLzM8vIyyWRSzTJl8Y1IJMLCwgKZTEZdKyUlJeRyObXd8vIyZrOZUChESUmJcsUUcm2i4MpS1pdMJBK88847jI2N8cEHH3Dz5k1MJhMOh4Ouri5eeOEFZT3qKfXuRQYmnz9/nqGhId566y0uXLigFmCkVeDxeHjiiSfWWQdlZWVYrVbKysruecNcWVlhYWFB5fgDHDhwgPr6en75y1/S19dHJpMhnU4rl49WkIVDrj1ks1my2ayy6pubm/nSl75EZWXlXZalvGnJBb0LFy7w4x//WBlRmUyGVCqFYRiUlZVhs9lUVEs0GiUSiaip+srKCh988AGBQIAnnniCiooKtahbCLZFWco87vHxcUZHR5VPwuPxqDChqqoqFWys2Z3IoORUKkUkElGWQjweVzMDGa3g8/loaGigrq5OxeNZrdZ7yl9aq4ZhYDabsVgsqhxYOp1WlsTKyop6SP+29HHrG/DWYhgG6XSaxcVFlpaWlFUpV6plxpxEKkkZkxmNRgmFQoyMjDA4OMj8/LxKMpAyrqysVP5Pr9eL3W7HYrEo/QGQSCQoLy8nlUqpgPhCUXBlmUwmuXbtGmNjY7z11luMjIyQyWTweDy8+uqrnD59mubmZioqKrSi3OUsLy8zNDTE1NQU7733HpcuXSISiQB/Cvfo6uri1VdfxefzsX//fhwOB9XV1co3uRHp25TT+t7eXiYnJ/nNb37D2bNnVUxmOBxeN1CcTic9PT00NDSo6b6+vraObDbL9evXGRsb49atWyQSCZqbm9m/fz8tLS3rzvXKygrz8/Ok02muXr3K2NgYFy9e5A9/+AMzMzNEo1FMJhNOp5OKigp6enqorq7myJEj1NXVqUpFy8vLZDIZPv74Y37yk58wMzPD8PAw8XhcPTYq6a2k4MpyeXlZmc9jY2OMjY1RU1ODw+GgubmZw4cPq1Vtze5G5vLPzs4yMTHB2NgYmUwGQFkLVVVV7N27F6/XS319PTabTU2Z7/V9Kysratq1uLiorJaPPvpI9XWRmWD5WK1W/H4/tbW1lJWV6ZXwLcYwDGKxGOPj4yQSCTKZjArjczqd6258hmGQSqVYWFhgYmKC27dv09/fz+XLlwFU0omcRjc2NlJbW0tvby8NDQ0qE0+Sy+U4d+6citdeWloik8nsfssynU4zMjLC6OgomUxGOfZramrwer1UVlZqRfmIIKsD5RdUzo95NZvNpNNpRkdHiUaj3LhxQ9UWlT1aAOWkT6VSKiUyEomwtLTE/Pw8S0tLyqKQAyY/FbK0tJRAIMDp06dV8VmTyaSn4VvIysoK0WiUsbExFTJkt9tV6F/+jSmdTvPhhx8yMjLC7373OwYGBtSMQ9ZrCAQCPPnkk1RXV9PZ2YnT6aS2tpby8vK7IhikKyeVSm3rbGFbLMtYLEY0GmV5eRkhhMrldTgcOlj4ESS/uEW+siwpKSGTyRCLxZidnSUWi5FKpdZFRkilajabSSQSTE5OkkwmmZiYAFYjJ0pKSkgkEusUrMRkMqlsrs7OThoaGtaFnGm2BsMwlN9YysFms+F0OlVMtGR5eZnBwUH6+/u5du0aAwMDwKqsy8vL8fl8tLW1cerUKTwej5px3A+LxaIyvOR1tR0UXFkuLi7yxz/+kVAoRDqdZmVlhXA4zOLiIpcuXcLhcFBZWYnX61XFMPSFvTuxWCwEAgFKS0tpaWkhFosRiUSYmZlRfsehoSHefvtthBAqrEcGp+eHh5lMJjV1y4+zW1hYUGEkEiEE1dXV1NTU0NDQwOHDhwkGgzQ2NuJ2uzcdGK3ZPHJqLWV3L3K5nAoNGhgYoK+vj3g8DkAgEKCuro69e/dy8uRJvF6viojYrLysVis+nw+Hw4Hf78fv9xdsJRy2SVnKvFFZyTwcDhONRrl06RJCCFpaWti3bx+VlZU4nU7tiN+lmM1m6urqcDqdNDY2Mj09rXL4s9ksiUSCeDzO0NDQPbeXMZT5U/mNbPRtSgXr8Xjo7OzkwIEDfP3rX1c3YX0tFQapLGWzwHuRzWaJx+NEIhEGBga4ceOGKpBSW1vLgQMH+OIXv8irr76KzWZ74Jua1WrF6/Wqqbzf7y+ovLcldEiGC+RXwc5ms4RCIcxmMxMTEwwNDeH1etm/fz92ux2n06n8VoZhqGB1GQ4iLZDl5WUWFxdVBSKLxXLfEBRNYZEVomw2G729vbhcLvbu3cvU1BRTU1NqdpFIJIBVS1QGmJeUlKjrI5VKsbi4SDqdJplMfuo+Zdpbb28vR44cUZEV+deIpjDIIPH8gP/8m1w6nWZwcFD5NbPZLB6PB7vdTnd3N48//jgtLS3qOtgsMhA+m82qay6/an6hKLiyzOVyLCwsqER4IYSyDj755BP6+/vVj2xqauLUqVNUV1ezZ88ezGazmsJ5PB4cDodaHJIsLCwwPj6OxWKhtbWViooKqqqqtLLcIeSq5rPPPqtibNPpNJcuXeLcuXNEo1EGBwcxDEOlH8oYWzkApHKdnp5mfn7+vlZmSUkJra2tdHV1cfz4cZ555hlKS0txOBxaURYY2UIinU6rafhGhZlMJvnwww8ZGhoiEomQyWSor6+nubmZ5557jq9+9auqItiDIFfApetGfkehx3zBlaXNZqOuro5cLsfMzMw6kz1/FVMIwdzcHKOjo8TjcdLptHLyZ7NZIpEIZWVlquqQJJ1OE41GMZvNxONxlWpVUVGB3++nqqqq0D9Rcw/yp1Rmsxm/309HR4fK/4bV9EWr1YrT6cRqtarrYWBggMXFRZLJ5Lq+SbCqIC0Wi/JVdXZ20tnZSSAQwG63Y7VataLcJu53E5PnX94sU6mUsj7z+yk9aBSMvD6SySThcJj5+XlKSkruG6O71RRcWVZVVXHmzBlGR0d55513mJ6evufnDMNgamqKc+fOrbvbyBMsrc+NuZ9ySm82m1V6VXt7Ox6Ph9dee42TJ08W+idqPgWr1YrFYmH//v20t7erKRT8yd+Y30zOMAx+8YtfqH48+cgMIIfDwVe+8hU6Ojo4evQonZ2d2Gy2gled0axHKqiNpREluVyOubk5ZfAAqpCKzMB5EKT/e3h4mPfff5+SkhIee+wx5X4rNNtiWdbX11NSUkJTUxN2u33dycrv4ienYQ+DyWRSVWzKyspIp9NEIhFisRh2u12HKO0gQghV4f7TkPUoZcrkxgFlsVioqalRpdtkdo4MgtYW5c5xrxqyZrOZqqoq5ubmVCpzJpNhYWGBeDxOLBbDZrOpUKPP8lvOzc0RCoWIRCKkUinKysqorKykqqrq0VCWXq+Xl156ifn5eY4ePcr09DQ/+9nP6OvrU6a5LI7weSrDSN/o4uIifX19qllSIpGgp6eHI0eO6MFUxORyOS5fvszt27f59a9/zfnz51WomcTtdvPyyy/T3NzMyZMnaWho2NZK2ZoHQ87uZE2IhYUFpqenmZ6e5vz585SWltLU1MTBgweVkfNpY/TixYv86Ec/IhQKYRgGXq+XM2fO0NTURGVlZcF/T8GVZf7yfi6Xo7q6mmAwSDQaJZfLsbKyonwOchqW3yXuQSxN+VnZ22dqaorx8XGampoK9Os0W4GsSDQ1NcXIyAiTk5MqO0ciV83lAoHP59uWAaK5GzlGpXFzvxRDq9VKbW0tJSUlqliOzMiKRqMMDw+rKkWy6nn+Io2sGiVLtU1OTnL79m2SyaRayPP5fHi93m2pU7ot0brSCRsIBKipqeHb3/42iURCKcfJyUlGRkbUdHxmZobz58+roOb8KsmbReauDg8P646NRczS0hLXrl0jEonwq1/9isuXLzM5ObmuvFppaSkej4fGxkZ6e3tpa2tbt8in2T5kUYz84hX3yqSC1XEvF1y/9a1vEQ6HOXv2LB9//DGhUIhQKEQwGOTSpUu0tbXx2muvrVvsu3PnDrOzs1y+fJlbt27R39/P8PAwfr+fp59+mj179tDZ2UlNTc22+Ku3LbWhpKSEiooKgLtWqEOhELW1tWq1a2Jiglu3bpHL5YjFYus+m78gsNEazZ/Cy5U4Wc5JpuBpiotsNqtaTty5c4fbt2+vi8mFVV+ly+VSmV6ytYRm+5GWnmwkJsuzbRyHcrzJULLHHnuMlpYWrl+/zsjICOFwmHA4rIr2yowu6VbJZrPEYjHC4TDXrl3j8uXLTE1NkUwmCQQC7Nmzh+bmZlWRaDsoiivO7XbT1tamTrLb7aa7uxu32004HGZubk4pyWAwSH19PTU1NbS2tpJIJOjr62Nubo7BwcGHskI1208mk2F6eppoNMq7777LzZs3uXPnzrrURhkmFAgEePHFF2lsbFTVt7WfcmeQRs/KyoqqRSsTDeLxOLdu3cJut6tCz7KddXl5ORaLhRdffJFDhw4xNDTE0NAQ1dXV1NfX4/V6EUIwNTXF9evXicViXLhwgVAoRDgcVv2Xenp66Orq4qmnnlIB7ttFUSjLiooKZXUCyo8hhFAnQ0bo+3w+urq6aG9v5/jx40xMTGAYBuFwmLGxMa0sdwnSchgfH+fy5ctcvXp1XYAzrEY4WCwWPB4Pjz/+uEql1Ipy55BFlXO5HC6XC5fLpYpeJJNJQqEQgUCATCaDzWZT1Z5sNhs2m41jx44BMDAwwMDAAG63e12aYiKR4OLFi4yMjPD+++8zOjqK1WrFbDbT2trKoUOH2LdvH1/4whc+tdhGISgKZbkRq9WqAtmlspRO5HA4rALYV1ZWmJ6eVgn6G0NNZAfI7Qpa1WyepaUlRkdHGR0dVY2p8i1Kk8lES0sLhw8fpq2tTa146nJ+xYHZbObgwYNUVFRgNptV3YehoSEsFgtvvvkmHo+HtrY21R4if/FmYmKCcDhMKBTiypUrZDIZ5ubmSCaTXL9+Xa1peDweWltbCQaD9PT0cPTo0QfqGrmlv3nb97gJbDYbTU1Nqj0q/KlW4tjYmHIOy/JdfX19LC0t3ZXpUVpaisvl0sHKRYjMGx4eHr6r3JrZbMZkMtHR0cHrr7+Oz+ejvb1dd2YsIqxWK8eOHaO7u5t4PE4oFGJmZoaBgQGi0ShTU1PU1dXx/PPPU11djdvtXie/0dFRxsbGCIfDDAwMqCl8fkM7v9+P1+vl+PHjHD16lPb2dvbt27djMbVFqSxlIzO3201tbS3BYJDZ2VmVXy5jM6enp1lYWFhXpcZkMuF2uykrK6O9vZ2enh5qa2t38udo8pA3vfn5eQYHBxkaGlJylbhcLqqrq1XvadnpUVNcSCOko6ODEydOcOPGDVVCb2ZmBsMwuHjxIg6HQ/WGl4TDYSYnJ5mZmWFqaorFxUVyuZxytZWXl9PT04PP56O7u5v6+vq7igpvN0WpLC0WC16vF5PJRE9PDyaTiStXrqwbVIlEQhVZkNM36ePas2cPfr+fp556ijNnzugKNEWE7PYZjUb57W9/y+Dg4F1pjcFgkN7eXg4dOsTevXuxWq1aWRYZctGmrKyMZ599lmPHjvHzn/+ciYkJkskko6OjjIyM8Mknn9zTEpRhgvK5HMdOp5MDBw5QV1fH1772NTo6OlRfnZ2+BopSWcoc8NLSUoLBoGpIJXNM8wPWpfPYbDarXh3t7e0Eg0F8Pt8DFRPVFA4Z6TA7O8vt27e5efMmc3NzKvQEUHL0+/20tbWpEKGdHiSaeyOVoExXDAaDdHd3Mzs7q9rIyBRmWSRYBp9vlKkMD3O5XHR2dqpgc+lGK4YxvPNHcA9kLrHL5eK5557j2LFjqp+0LN+VTqeZn59f1yRJOn9feOEFVa5NL+4UB7lcjkwmw5UrV/j+97/P5OSkCj6HVZlXVVXhdrs5efIkr7/++l1TN01xUlZWRmlpKadPn6a7u5twOMylS5dYWFhQsZG///3vmZmZ4dChQzQ1Nd01Jn0+H0ePHsXtdtPU1ERZWZkKNyqW8VvUV6L0P1qtVgKBAI2NjZhMJnK5nCr4a7fbCQQCVFZW0tjYiN/vp66uDq/Xu9OHr8kjm82SSqWIx+OqYVl+KqsQApfLhd/vp6amBo/Ho2uS7hLkTNDpdKrZQSwWY35+nvLychKJBOPj4zgcDpqammhsbARYZ136fD6amppwuVzblr74oBS1spQBsHa7nZdeeokzZ87Q39/PjRs3iMVihEIh6urq+PKXv6wWg+x2O9XV1Tt96JoNxGIxBgcHGRwcVEV985WlxWLh+PHjHDt2jAMHDhSVRaHZHBaLBZPJRDAYVLUglpeXyWazvPLKK2SzWRwOxz0DyWVdU9kyuRgpamUJqArIgUCAQCCgBCBXxhobG+nu7sblcun+PUVMKpVienqa2dnZu/p8WywWbDYbfr+f1tZWqqqqtJ9yFyItTLvdvq2ZNdtF0SvLjQSDQRwOB+l0moWFBcrLy6mpqXngPh6a7WVwcJCzZ88yMjKyTlGWlpZy6NAhamtrOXz4MHv37qW8vHwHj1SjuTe7Tlm63W7VlkCze4jFYly7do14PL6upJfFYqGhoYHW1laVI6zRFCO7TllqdifZbJZ0Ok06nSaXy6kcY7fbzWOPPUZ3d7dWlJqiRitLzbYglaUsv2Y2m1U6aldXFwcPHtQ1KjVFjVaWmm3B4/HQ3d3N+Pg4yWQSu93O/v37CQaD1NTU6OQBTdGjr07NthAMBjl16hTXr1+nv78fp9PJiRMnaG5uJhgMblsBV43mYdHKUrMtuFwuWlpaEEIwMzOD0+lUfcQfxTATzaOHVpaabaGpqUnVKP3GN76hFnhk8RONptjRylKzLchgZWBdVXyNZrcgHrZPtxBiGhjZ2sMpehoNw6jZ6YPYLrSMH320jDfPQytLjUaj+f8JnR+o0Wg0m0ArS41Go9kEWllqNBrNJvhUZSmEqBZCfLz2mBRCjOe93vLqnEKIbwohpvP28W82sc2wEOK6EOKaEOJtIYT/c+z/b4QQ393E574nhLgthPijEOKZh91fMbADMm4UQry7Jq9zQojgJrbRMv4cbLeM1/b550KIfiFEnxDif2/i88UvY9kb5bMewN8A393wP/Nmt9/kPr4J/P0DbjMMeNae/xfg7za8L4CSh/2N9/hMF3AVsAHNwCBg2srzsFOPbZLxG8C/Wnt+GvhfWsaPnIzbgCtA5dpr76Mg4weehgsh/ocQ4gdCiA+B72/U4kKIT4QQTWvPXxdCfLR2B/sHIUShK/O+D7QKIZrW7hb/E/gEqBdC/JUQ4uLanes/5x3vfxJCDAghPgA6NrGPrwI/NgxjyTCMIeA2cKQQP2anKLCMu4DfrD1/j9Xz+SBoGW8BBZbxvwX+q2EYswCGYUw94OEVpYwf1mcZBB43DOM/3u8DQohO4DXgCcMweoEc8PW1934ohDh8n01fWTsRPxNC1D/gcT0PXF973gb8N8Mw9rF68tpYPRm9wCEhxAkhxCHgL9b+9xXgC3nH/5dCiL+8xz4CwFje69Da/x41CiXjq8DLa89fAhxCiAfpA6JlvHUUSsbtQLsQ4rwQ4l+EEM8+4HEVpYwfNoPnDcMwcp/xmTPAIeCiWO2lYgemAAzDuJ8v8hfAjwzDWBJC/DvgH1mdqn0W7wkhcsA14K8BNzBiGMa/rL3/9NrjytrrClZPugP4P4ZhLAIIIc7KLzQM4web2O+jTKFk/F3g74UQ32TVghhndQB+FlrGW0+hZGxm9dyfYlUhvy+E6DYMI/4Z+ypqGT+sslzIe55lvYVauvZXAP9oGMb3NvulhmHE8l7+EPj+Jjd90jCMqHwhhHBvOEYB/K1hGP+Qv5EQ4j9s9tjyGAfyLd7g2v8eNQol4wnWLEshRAXwyiYGEWgZF4KCyJhVK+1DwzCWgSEhxACrSu3iZ2xX1DLeitChYeAggBDiIKvOUoB3ga8JIbxr71UJIRo/7YuEELV5L18EbuS9d/NzHOM/A/96bXAihAisHdf7wJ8JIexCCAfwwia+6yzwF0IImxCimdWL4KPPcWy7gWG2TsYeIYS87r4H/Pe897SMd45htkjGwP9l1apECOFhdVp+Z+31rpXxVhTS+CfgG0KIPuBDYADAMIx+IcRfA2+vDY5l4DvAiBDih8APDMP4w4bv+vdCiBdZvcvNsLo6Lk/4Q/dFNQzj7TXfy4W1qcQ88LphGJeFED9h1Y82Rd6dT/o5NprxhmH0CSF+CvSvHed3NjGV2e1spYxPAX8rhDBYvci/A1rGRcBWyvifgaeFEP2sulj+yjCM2G6X8a7IDRdCPA+0GIbxdzt9LJrCoGX86LPbZbwrlKVGo9HsNDrdUaPRaDaBVpYajUazCbSy1Gg0mk2glaVGo9FsAq0sNRqNZhNoZanRaDSb4P8Bb+qyhc5qe+UAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd2a7fa7cc0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -995,14 +1016,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd216e500b8>"
+       "<Figure size 432x288 with 12 Axes>"
       ]
      },
      "metadata": {},
@@ -1022,7 +1043,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1032,14 +1053,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 66.2%\n"
+      "Accuracy on test-set: 77.6%\n"
      ]
     }
    ],
@@ -1049,14 +1070,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd258064908>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1069,14 +1090,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd2a827ccc0>"
+       "<Figure size 432x288 with 12 Axes>"
       ]
      },
      "metadata": {},
@@ -1098,7 +1119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1108,14 +1129,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on test-set: 91.5%\n"
+      "Accuracy on test-set: 91.6%\n"
      ]
     }
    ],
@@ -1125,14 +1146,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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BZgAPu/uk6L3uwGf1SONtwFvAbDObB9xCKtoeB3wILCDVMDEt7FBdnWZUUf0MMJfU7cnNWdx6lLtc5XFNtgcW1SONVwIbWarLynzgiuj1G0nVQb8G/J6MaLGG+q7HgBXR3zQJOD9hj45ylKs8/gmp6oxwHT/m7k9G75VSHv+ZVPXag5bq6vRwbScvq2GUZvYYcGiOuxxIibDU/dUT7n5AsdMi+dEQ8risCk0RkWLTMEoRkQRUaIqIJKBCU0QkARWaIiIJ1KdzO+3atfOKioocJaU8zJo1a+mPaVZv5XHDpzxOpl6FZkVFBTNnZjMCq+Ewsx/VsgDK44ZPeZyMbs9FRBJQoSkikoAKTRGRBFRoiogkoEJTRCQBFZoiIgmo0BQRSUCFpohIAio0RUQSUKEpIpJAvYZRiuTLd9/F61uNHj0agCuvvBKAtm3bAvDpp58CMHHixPS2e+65JwAffJAaJXfvvfcCcPHFFwPQqJHihEJ5//33AXjzzTcBuOeeewB4773UMktbb711ett3302tuH3ssccCcNJJqcUjN9hgg4KkNQl9gkREEiipSPOHH1JL/4RvorFjxwLw1VdfVbvP4YcfDkCPHj0AaNWqVT6TKHm2Zk1qaevzzotXY37ttdR6dTfeeCMAgwallsM+88wzAdhmm23S2y5btgyAfv1Sy6mvWrUKgCFDhgDQvv2PZvKiovnkk08A2HvvvQH48MMPAQhL64Sldl988cV19n3hhRcAWLo0tTDk7373u7ymtS4UaYqIJFC0SHPOnDkAPPXUU+nXJkyYAMTfNtkYOXIkAF27dgXgT3/6EwADBw7MSTqlML788ksATjzxRAA222yz9HshT3fddddK+4R6r3bt2qVf22uvvYA4wnzyydSqsYowC6d169YAHH/88QAMHz4cgKZNmwJw2mmnAdCxY8f0PhdddFGlY9x6a2pV4F//+tdAaeWfIk0RkQRUaIqIJFDw2/Pbb78dgLvuuguA6dOnp98Lt2SnnHIKAJdeeikAG2+8caVjLF68OP34oYceAuLuKEcffTQARx55JAB33313bv8AyYtwGx0aEW666ab0e5tvvnmV+/zsZz8D4Jlnnkm/FhoTw+1dz549c59YqVGzZs0AuPDCCwH46KOPADjooIMAOOKIIwBYtGhRep+1b89D9co333yT38TWgSJNEZEEChZpPvfccwD89re/BeLOy5kRRYgw119//RqPlVnxH7oahQ7PQ4cOBeII9Nxzz01v+z//8z91/wMkr9544w0gbsipLrrMNG/ePAAOPfTQ9GvNmzcHKjcySHG0bNkSgDFjxlT5/n//+9/049AdqbrnpUSRpohIAgWLNA8++GAAVqxYAcAVV1wBwBlnnJGT44fOy6EOM9SVLlmyJCfHl/wIdVlTp04F4Pnnn89635tvvhmAr7/+Ov1aqCvffvvtc5VEyZPJkyenH4cO7yHCDHeioW6zlCjSFBFJoGCRZhgKGb5RQt1TrjRp0gQozQH+sq77778fgPvuuw+IJ3WoqT77888/B+JeFaEnxm9+85v0NqFlVkrfggULqn1vu+22A6BLly6FSk7WFGmKiCRQsEgz9JsLwx3DN0muvPPOOwDMnDkTgA4dOgDxVGFSGkI/yjBV29VXXw3AhhtuWGm7MHEHxP0w//jHPwLxBBCjRo0C4JxzzsljiiXXJk2aBMQ9XKpSyncMijRFRBIoWKQZBt7nS5jgNLSkhv6aua47lfqZO3cuAN9//z0QjxJZuHAhEE9cG6YFhPguJdR3PvroowDsv//++U+w5FyYpOeLL76odps99tijUMlJTJGmiEgCKjRFRBIoqZnb6+Laa68F4gk7wozf11xzTdHSJNULcyp+9tlnAPTv3x+I51etqKgA4iF4mfuExkPdlpen0O1wxowZQNz9MNP5558PQJ8+fQqXsIQUaYqIJFCWkWbm6oOho3O3bt2AuKPzeuutV/iESa26d+8OxDPuh9UiQ3eis846C4D//d//Te/z+uuvA+o+Vu7+9re/ATUPlQ1rApXyqqGlmzIRkRJUVpFmqL/861//mn4t1G/dcccdQNypXUpbWEky/A7CGuchryFeGygz+pTy8+CDD1b7XuiSGNYXKmWKNEVEEijpSDMsazFs2DAgrv8aMGBAeptHHnkEUB1muQtLIoQlEjIjjjDcLkzKIuVp7VVmW7VqlX58+eWXFzo5daZIU0QkgZKONMOg/fANtcMOOwBw6qmnprcJfb+WL18OxP38kghTjoVoJ5xH8m/16tUA7LvvvkDcC+Lpp59Ob5O5BrqUnzBBRxD6Z4aJySG75U1KhSJNEZEEVGiKiCRQUrfn4VY7dFB/+eWXK70fhtoddthh6dfat28PxPMvhlmNwiw6VQndkg444AAAbrnlFiBejySkQ/LvhhtuAOKVCcMaUlL+Vq5cCcDZZ59d5fuh0a/cKNIUEUmgpCLNEFneeeedQDykKpuGmRYtWgDwxBNPAPGqduHbDuI1tYcPHw7Al19+CUDjxo3X2Vbya8qUKUCcx5dcckkRUyP5EO7Ywpr2DYUiTRGRBEoq0txnn32AeGXC0MG5bdu2WR8jTDVWk9DVIUw/FqIc1WXmX1iXPqx3PnDgQECRZkMW7vqqe15uFGmKiCRQUpFmqFvs3LlzXs+TOcEtwKabblrpt+TPddddB8SrT4aJVkLeS8Mxbtw4IO7MHiLMQw45BIAePXoUJ2H1pEhTRCQBfb1LUZx88skANGvWrMgpkXwJy5OEobFhpdGwbn253l0o0hQRSaA8i3opK4sWLUo//u1vfwvA4MGDi5UcKZC+ffsCMHnyZCCePLxLly5FS1MuKNIUEUlAhaaISAK6PZe8y5wP85hjjiliSqQYwlyZmes+lTNFmiIiCajQFBFJQIWmiEgCVp/B82a2BPggd8kpC53cvX2xE1EoyuOGT3mcTL0KTRGRHxvdnouIJKBCU0QkARWaIiIJ1FhomllbM5sd/Swys48znq+fjwSZWSczm2JmC8xsvpmdlcU+Q8xsSZSu18zs5Hqm4R4zG1jLNpdk/C/mm9kPZtaypn1KUTHyODrvBdH/bb6ZVb1cYeXtC57HGdvuZmars92+1BTpOu6RcY7ZZvZVbddyka7jn5rZNDP71szOy+a4NY4IcvfPgF7Rwa8AVrj7n9c6qZFqUFqTzQmz8D1wnrvPNrMWwKtm9rS7v1nLfmPd/Twz2wyYZ2aPuvvSjHQ2dvcfcpRG3P1a4Nro2IcBZ7j7F7k6fqEUI4/NrBfwK6A38APwtJlNcPf3atm1oHkcjglcA0zM5XELqRh57O4LMs7ZBPgYGJ/FroXO46XA2cAR2e5Qp9tzM+scRYJjgfnAlma2POP9wWZ2Z/R4UzN7yMxmmtkMM9u1pmO7+yfuPjt6/CXwOtAh27S5+yLgfaCjmV1tZneb2YvAGDNrbGbXR+n4j5kNidLYyMxuNrPXzWwi0C7RPwSOBu5LuE9Jy2ceA92Bl919lbt/D0wFDqtln7QC5/F5wP2kLq4GJc95nKk/8Jq7L8x2h0Llsbt/6u4zSX15Z6U+Y8+7ASe4+8zo27g6o4ER7v6ymVUAE4CeZrYLcJK7n17djma2NdATeCXbRJlZZ6AT8G5GOvdy92/M7Exgsbv3MbMNgJfN7GlgV2AroAfwE2ABcGt0vOHAi+7+eDXnaw70A07NNo1lJF95PBf4g5m1Ab4Ffg68mG2iCpXHZtYROBDYD/hZtukrM3m/joHBJAwqCn0dJ1GfQvOdqISuTT+gq0XrhACtzayZu08Hple3U3Rr/iBwtruvyOI8x5rZ3qQuwiHuvjw65yPu/k20zQCgu5mFyRxbAtsCewH3RbcmC81sSjiou19Wy3kPBZ4rx1vzLOQlj919npldD0wCVgCvAquzOE+h83gUMMzd12T8bQ1Nvq/jpqS+eC7IMj3Fuo6zVp9Cc2XG4zVA5qeqacZjA/q4+3fZHthSldMPAXe5+6NZ7jbW3auqyM1MpwFnuvvktc6X9a1hFQYD/6jH/qUsb3ns7rcDtwOY2Qjg7Sx2K3Qe9wYeiC7adsAAM1vt7v+qw7FKVd7yOHIgMD2zXrIWxbqOs5aTLkdRyb7MzLY1s0ZUrp+aBAwNTyzVCFAtS31CxwCz3X30Wu+da2Y13QbU5ingzHAbYmZdzawZqTq1QVGdSAegbzYHM7PWwO5AQ7qIqpTLPI622ST6XQEcQqresKTy2N07unuFu1eQasQ4rYEVmJXkOo8j69T3l1Ie10Uu+2leTOqPeQnIrPAdCuwRVdguIKr7M7NdzOzWKo7Tl9Q/ur/F3RX2j97rDnxWjzTeBrwFzDazecAtpKLtccCHpOpA7gKmhR3MbLiZ/aKa4x0OPOHuq+qRpnKSqzwGGB9tOx44PWr0g9LL4x+bnOWxmW0M7MO6reYlk8dmtoWZLQTOAa4ws4VmtmFNJy+rsedm9hhwaK67lUjpUB43fOWex2VVaIqIFJuGUYqIJKBCU0QkARWaIiIJ1Gs1ynbt2nlFRUWOklIeZs2atfTHNKu38rjhUx4nU69Cs6KigpkzsxlM0HCY2Y9qWQDlccOnPE5Gt+ciIgmo0BQRSUCFpohIAio0RUQSUKEpIpKACk0RkQRUaIqIJKBCU0QkARWaIiIJ1GtEkEiu/PBDamrFsAbNeuutV8zkiFRLkaaISAKKNKWoJkyYAMDxxx8PQLt2qaWqL7300vQ2v/rVrwBo1Ejf8aVm2bJlAIwdOzb92rXXXgvAxx9/XOU+AwcOBOJ8zXytHOhTKCKSQN4izTPOOAOAXXbZBYATTzwxX6eSMtazZ08ATj75ZADGjRsHwCmnnJLe5q677gLgzjvvBKBLly6FTKJUYdWq1FqChx2WWrDyueeeW2ebffbZB4Dtt98egK5duwLw8MMPA3Dcccelt73nnnuA8og4FWmKiCRQr4XVevfu7dXNwxdaQTfZZBMAJk6cCMTfOsUwb948IP5Wu/jiiwFo3bp11scws1nu3jv3qStNNeVxPj399NPpx4MGDQLiFvbXX38dgA4dOuTl3Mrj2v31r38F4LzzzgNgq622Sr8XIsxbb02t7NukSZNK+65ZswaAY445Jv1aiD7vv/9+II5g86U+eaxIU0QkARWaIiIJ5K0hqGXLlgAsWbIEiMPuzp07A7Dhhhvm69QAfP755wDce++96df++Mc/ArB06VIAFi1aBMCYMWPymhZJbsCAAenHoQHoqKOOAmDu3LlA/m7PpXajR4+u9PzJJ59MP66toS50HQsNfADfffcdEFeZ7bHHHkBcvVdKFGmKiCSQt0gzNLYccsghQNzh9e233wbgkksuAWCzzTZL7/OTn/wk8Xk+/PBDAGbMmAHA448/DsRdIN57771q933xxRcTn08K7/DDDwfiCObVV18F4IADDihamqSy6dOnpx9n2yWsWbNm6cdXX301APvttx8Ahx56KADTpk3LVRJzRpGmiEgCeYs0QxQQfj/11FNA3Hk5DJ9bf/310/uExyHi/PbbbwE48sgjKx07DN0CuPvuuwH46quvEqexHDrSNjRhaN0///lPIL4jCN2+jjjiCAD23HPP9D4LFy4EYOXKlUD+u6NI7UKXo1DPPGzYsPR72223HQC9evXK+ng9evQA4JZbbgHg9NNPB+JO9JlRabEp0hQRSSBvkWbjxqlDhzrG3//+9wDcdtttQNyC/c0336yzb3gvCPUdNQnRxwsvvADErfZVpelPf/oTAKeeemqtx5W6C9H/Aw88kH7t/PPPByAMqmjbti0Aq1evBuDvf/87ULmuu2PHjkA8JLdbt275TLZk4aCDDgLgyiuvBODyyy9Pv/fzn/8ciK/10K6xtjDYBOI2jnCth8/H3/72NwDOOuusnKW9vhRpiogkULCp4a666ioAfvGLXwBxnVaILACaNm0KxNHHggULUolsXDmZJ510UvpxaG0Lfb7WrtvMHML17LPPArD77rvX50+RLIX/d6jPhnjYXZiQI0SRoZ9e2DYzOgn9aVu0aAH9eUqFAAAJJElEQVTABx98AECnTp3ylnbJzkUXXQRA9+7d068NHjwYiO/+jj76aCDuJ7311lsDsHz58vQ+jz32GBBP6nHaaacBcMEFFwCVh1y2adMmx39FMoo0RUQSKPgkxLvttlul36NGjVpnm5deegmI+2Cu/c3Sr1+/9OORI0cClaOZTOHbDRRhFkqoVw4TC2dOUBvqwtYWek6sWLFinffCZBBTp04F4rrNRx55pNJzKZ7MfH355ZeB+O4y5H/Irx133BGo3EMimD9/PhC3O4Q6zjDJRylQpCkikoAKTRGRBPI2n2Y+ZaZ57733BuD555+vtE1YayYM24S4IaE+NNdi7XbddVcgHpwQbqsBNt544yr3eeKJJ4C4gWjTTTdNvxcmgwhD9c4991wgbiAKwyohN92RlMe5Ea7T1157DYjXBFq8eDEQV79lCvPwhkakhx56CIDx48entwlDLOtD82mKiBRIWa5GGb65YN0Is1WrVkD8DZWL6FKSCVO2hRm8q4suIY42wkCD0O0sRJ4QR52hG1IYcte/f3+g8nDYMON76MokxROixpBfr7zyChAPPAnDYwEuu+wyIM73zC5MUPmaz0WkWR+KNEVEEijLSLOqYZUhmgldjKrqziCFEYbEhYlWMjuhH3zwwUA8YcuFF14IxNFkGPSQOYxybWEi67DuVIg4IZ68eNasWQBstNFG9flTJA/at29f6TfEg1RCpBm6q4XPSWa9ePh8FYsiTRGRBMoq0gxTwoXp5TKFb59SGtj/Y7XzzjsDcMIJJwCVh0T+8pe/BOJhc5tvvjkAzzzzDJBsIuq1I06AnXbaCYhXsAyThZTS1GJSu7AczhZbbAHE082VAkWaIiIJlFWkOWLECCBe/zpTWKxJSkeYmDazPuqtt94C4jWxQ+RZn14OIeKEOLIMS2SEPqNhOZQNNtigzueR4gkLNZYClTQiIgmo0BQRSaAsbs///e9/A/DnP/+52m1q6kAtxdG8eXOg8prYoRolc22oXNp///2BuCN1aBgKs/CE2bBUnVPaPv30UwAmT54MlFYXQn1yREQSKItIc5tttgHiGZ9DY0KmJCvfSWGFoZGFFIbhhTVmQmfpG2+8EYBzzjmn4GmS7L377rtAvIZYuIMoBYo0RUQSKItIM3R0Db8zhS4kPXv2LGiapDyEtWXCJBFhNcwtt9wyvY3WUS8911xzTaXnmflVbIo0RUQSKItIc/bs2QDMmTNnnfdClKAp4KQmYXht6PweVsUERZqlKFzrIcIspUEJijRFRBIoi0izJpnrIYtUZ7311gPiIZ2ltLqhrCsMmwwTuZRSP2xFmiIiCZRFpBn6Z4b1refOnZt+L0wdJZKNMBJII4JKS5j6LaxxH/plZk7GUir0yRERSUCFpohIAmVxe962bVsgnu07dFQG6Nq1a1HSJCK5E9Z2CsMnS5kiTRGRBMoi0gzatGlT6beISKEp0hQRScDcve47my0BPshdcspCJ3dvX/tmDYPyuOFTHidTr0JTROTHRrfnIiIJqNAUEUmgxkLTzNqa2ezoZ5GZfZzxPC8rY5lZj4xzzDazr8zsrFr2GWJmS6LtXzOzk+uZhnvMbGCW2+5mZquz3b7UFCmPO5nZFDNbYGbza8vfaJ+C57GZtTGzR83sP2Y23cx61OecxVKMPI7Oe0GUv/PN7Owsti9GHv8yyt/ZZvaKme1e64HdPasf4ArgwipeN6BRtsdJ8gM0ARYDW9Sy3RBgVPR4M2Ap0G6tbRonOO89wMAstmsMPAs8mc32pf5TqDwGfgL0ih63AN4BupRaHgMjgcuixz8FJhY7j8ooj3sBc4Bm0XX8LLBVCeZxc+K2nZ2AebUdt06352bWOYoSxgLzgS3NbHnG+4PN7M7o8aZm9pCZzTSzGWa2a4JT9Qdec/eF2e7g7ouA94GOZna1md1tZi8CY8yssZldH6XjP2Y2JEpjIzO72cxeN7OJQLssT3cecD+pzG1Q8pnH7v6Ju8+OHn8JvA50yDZtBczjHsAz0TnnA13MrG226Sx1eb6OuwMvu/sqd/8emApkPdtzofLY3Vd4VGICGwG1tozXp06zGzDS3XsAH9ew3WhghLv3Bo4CQibsYma31nKOwcB9SRJlZp2BTkAYj9UN2M/djwNOAxa7ex9gZ2ComXUEjgC2InWRnATsnnG84Wb2iyrO0xE4ELgjSfrKTN7z2My2BnoCr2SbqELlMalI6ZfRNrsBW0Q/DUm+8ngu0Deq4tgI+DmQ9UI/BcxjzOwIM3sDGE8q2q1RfUYEvePuM7PYrh/Q1czC89Zm1szdpwPTq9vJzJqSKpQuyDI9x5rZ3sC3wBB3Xx6d8xF3/ybaZgDQ3cwGR89bAtsCewH3ufsaYKGZTQkHdffLqjnfKGCYu6/J+NsamnzncQvgQeBsd1+RxXkKncfDgdFmNptUAToHWJ1FOstJXvLY3eeZ2fXAJGAF8CrZ/e8Knce4+zhgnJntA1wVHb9a9Sk0V2Y8XkOqTiTIXOjagD7u/l3C4x8ITHf3bG99x7r7eVW8nplOA85098mZG5hZXRaJ6Q08EGVoO2CAma1293/V4VilKm95bKkGiIeAu9z90Sx3K2geu/sXwK+i/RuRul18L+lxSlze8tjdbwduBzCzEcDbWexW6Os4zd2fNbO/m1krd19e3XY56XIUlezLzGzb6MOVmfhJwNDwxMx6ZXnYo1nr1tzMzjWz0+uR1KeAM82scXS8rmbWjFR9y6CoTqQD0Le2A7l7R3evcPcKUmH9aQ2swKwkl3lsqW+aMcBsdx+91nslk8dm1srMmkRPfw1McveVNe1TznJ9HZvZJtHvCuAQUvX/pZbHnaPPI2bWm1SjULUFJuS2n+bFpP6Yl4DMhpuhwB5Rhe0C4NQogdXWd5nZxsA+pAqjTN2Bz+qRxtuAt4DZZjYPuIVUtD0O+BBYANwFTMtIS7V1IT9CucrjvqS+FPtb3PVl/+i9Usrj7YAFUX3XfmRfVVTOcnYdA+OjbccDp0eNflBaeXwUMC+qghkNDKrt5GU1jNLMHgMOdfcfip0WyQ/lccNX7nlcVoWmiEixaRiliEgCKjRFRBJQoSkikoAKTRGRBFRoiogkoEJTRCQBFZoiIgn8f+zqJWNhd48fAAAAAElFTkSuQmCC\n",
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cLseFCxe4ePEiMzMzFAoFbVrW1dXF5z//eQYGBnC5XJrT/m5RFwdisRiLi4tawVmj0ci+ffvYt28fbrf7ro8j+XjUwjaqrNWWHqVSiUuXLmG1WrVptDotT6fTLC0tUS6XMZlMWp0Hl8vF4cOHaW9v58iRI5pV2kh2TFlOTU1pCfLVapXFxUWi0SgjIyMIIRgYGODQoUO43W5aW1vlQs8uRFEUrWr9xYsXOXnyJKFQSLMqATo7O/nyl79Me3v7R7K07oZisagpy+XlZTKZDLAWvDw4OMjRo0elstxm1MUaVVlWq1WtRUsikQA2l2LceJNsaWmhtbUVj8fD8ePH6erq4sknn6SnpweXy9UUiQQ7FjpUKBQolUraj6WmPS4sLGAwGAiHw0xPT9PW1sbhw4exWCy0trai0+nI5/MoiqIFq5vNZsxm8yYncS6X0yoQGY1GWlpapMLdYdSpcD6fJx6Pb2pH3NraitvtpqurC4/Hg9Pp3FL5fNyUWwhBS0sLJpNJhg1tM4FAQFN0LS0tZLNZrevq0tIShUJBszzVh4rZbKa7u5tAIMDw8DBdXV20tbVhs9maZj1jR5SleodR7zJCCK1HzsWLFxkbG9PM8mAwyDPPPIPX62XPnj0YDAZWV1cpl8v4fD4cDoe2OKSSzWYJhUIYjUb27t2L3W7H4/FIZbnDKIqiLbBEIhFmZ2c1Jebz+Th8+DD79++nu7sbh8OxI/JRawrYbLaG5BPfTwwODtLX18fy8jIPPvggqVSKa9eukUwmee+991heXiaVSlEoFDa5ZmDtZnr06FGCwSCf+tSn6OrqarrElB05e9Sqx9VqldXV1U2tBDbeYYQQpFIp5ubmSCQSFAoFDAYDyWSSSqXC0tKSliLndDq1zygUCkSjUQwGA4lEApvNRkdHB3a7XQt6lmwflUqFTCaj+aaXlpZIJpMoiqJZ+O3t7ezfv5/e3t6PVI35uPYganrrxtnIxv/f7EIyGo04HA58Pp9W9FnePLcXtUC3w+EgEAhoM0O1wtTq6qpWF2B5eZnl5WWy2SyxWEwLH1ILA1er1VvKeKfZEWXp8Xh4/vnnmZub47XXXmNlZeWG2ymKwvLyMm+88YZWiUb9v6Io2p3m+vABdUpvMBhwu91YLBaGhobw+Xy89NJLPP300zvxNe9bstksly9fJhKJ8P3vf5/5+XmmpqaAX/U+On78ON/61rdwOp1a9Sj4lZ/zRrUtVVlvjNtTuVXhDZvNxtGjR+nr66OnpwefzyeV5Taj1plUM7I2xl2qMlbz9d9++23eeecdxsfHeeutt0gmk4yMjBCPx1lcXMThcGhdD5qFHbMse3p60Ol0BINBLBaLZjkCWpc3tYXtx7WxvRV6vV5bVbNarRQKBZaWlojFYlgsFhmitE1UKhXi8biWeLC0tKQt6mwsp6X6lpeXlzWLsVqtEo/Hb9gzXK1qr/q8VctSp9Np/iyTyYTRaKRUKm2qZqTT6TCbzVqvcDkF3zl0Ot3HrlwXi0XK5bJWMT0SiWidHlVXndpyotlCv3bkDGpra+MrX/kKmUyG48ePs7Kywl/+5V9y6dIlbQqmOoPvpo+36hvN5XJcunQJk8mEz+cjmUxy5MgRHn300aYy6+8V0uk058+fZ25ujitXrhCJRDRXi9o2YGJigh/84Aeb2g+r5freffddotGo9nmq/F0uF4FAQGuDrFqXVquVl156iQMHDmiVz8PhMKOjo8zOzlKpVLBYLFgsFllroMloaWnBaDQyMDCAXq+nUCjwi1/8gmKxSDabJZ1Ok8vlPuLTbAZ2RFm2tLTQ1taG0+mkWq3i9Xq1nhtq+SWTyaRZG6qlqZrut2NpqtuqvX2Wl5cJhUIEg8Ft+naScrnM6uqqVqB1Y0626iJJJBLMzs5umn7D5in89bjdbu3imZub03ou2Ww2pqentcB2i8WyqVAH/KqQrM1mk6vg24TqW1TdYvW0e1D9kOraw8YqUOVyedNq+X1pWcLayWsymejq6sLv9/MP/sE/0BYBFEXRVk/V6fjq6ipvvfUWsVhM68VxuyiKQiwWY2ZmRnZs3EYymQznz59nfn5ei3hQUafG+XyecDj8EWWpKtIboU6/q9UqLpcLQFsw+sUvfsHp06fp7+8nEAiwsrKita2oVCo4nU5OnDhBMBjctBgo2RrK5TLvv/8+oVCIjo4OvF4vXq+XQCDQ6KFtGzvqyNHpdNjtdoCPrFAvLCwQCAS0u0o4HObKlStUq1VisdimbdUyTRtXS1VrdOPdSHUoq+Xg1CIOkq1FLZSiFva9/j215enH9etW5Xm9VaLK2Gg0ahaiWvNyfn6eXC5HPB7H5/Np/i61EZp6Y+7q6tq2DpL3K+psIRQKMTExoTURs1qtt7zG1GtUvc7VhT31Gm42a3IjTeP1drlcDA4Oaj+Yy+VieHgYl8vF4uIiqVRKu6i6u7vp6enB7/ezd+9ekskkly5dIpVKMTU1JYso7DBut5tnnnmG2dlZTp48ucn/qPoNTSaTFhi+scSWwWAgEAhgs9m0vt4qHo9H6x1fKpW0KTjA1NQU8XicSCRCLBYjm82SSCTQ6/UEAgE6Oztpa2vD6/XKxZ0tpFQqaX2zTp06xaVLl/B4PDz44IPYbLYbKsparUY6naZQKDAxMUEkEtGqj42Pj2sp0NDcnQ+a5iyy2+2a1Qlr063+/n6tnBf8KjShvb2dgwcPMjQ0xBNPPEE4HEZRFBYXFzWLQ7Jz2O12jh49itPp5OzZs5veU/N91QK8aqM5FbPZzKFDh/B4PPT19eH1erX3/H4/wWAQRVEoFotaVX1FURgfHycajfLmm29qK++pVAqXy4XH48Hj8eByuWhtbZXKcgspl8ssLCwQCoW4cOECo6OjfPrTn6a1tfVjLXi1rUg6nebixYuMj48zPT3NzMwMiURC65XUzIoSmkhZXk9LS4sWyK4qS/Xus7i4qAWw12o1VlZWuHTp0qZwJBW1A6S6gCTZemw2GwcPHsTv95NMJjdZlk6nE4fDsSmLZmPsnMFgoL29HZvN9pEcYLVnDqBZo0ajEUVR6OjowGaz0dbWRmtrqyZfs9lMIBCgvb1dq3AjF3i2jmKxyLVr15ieniaRSGghPnq9XotuUF1i+Xye+fl5UqkUly9fZnV1lYsXLxIKhYjFYsTjca2nu91uJxgMEgwG6ejoaMqyjU2rLE0mE8FgEIPBoClL1dcxPz/PwsICCwsLRCIR0uk0ly5d+khZLjXWzul0Sr/VNuJwOHjwwQcpFAr09PRssuxbW1s1pWe1WtHr9R8JNL5RUdhb0dXVRaVSIRAI4HK5tHPEarXS1dWlTe2bKah5t6Na+OPj40xMTBCLxbTK9zqdjkqlQjabpVqtUiqVtKl6JBLh5MmTLC4usrq6qhU5gbWboNFoxOfz8fjjj9PX10d3d3dTpis3rbJUp1xqrF13dzfxeFxbbVVjM1dWVjQBqYpSr9drYQlDQ0McOXLknl6lazSqL9loNOJ2uzcF/6s+S7W4ST3hJfWi0+kIBAIcPHgQk8mknSsPPvigVsxBsjWo5ddyuRwrKyuEw2GtwM3Y2Bg/+tGPNm1bqVRIp9OMjY1p1aByuZyWKKDWNFXr2nZ0dPDAAw/Q1taG1WpturxwaGJlaTQaaWtrQ6/Xc+TIEfR6PR9++OGm0JRkMkkmk9mUDqfX6zEajezZs4eOjg4+9alP8fzzz2+qUiTZetTQsM7Ozo+8p/7uW/3763Q6jhw5wsDAAPl8nlwuh9VqxePxaCvokq1BrU0Zj8cZHx9nbGxMW81++eWX+fGPf/yRfdS2tur1qZZibGtrY2hoiMHBQQKBAENDQ7S2tmp1AxrVY+dWNK2yVPOC1dJN+XyexcVFrajGxoB1IQQmkwmDwYDT6cRmszE0NER3d7fmu5JO/p1hp/2D6jRbTXFV21Y0o2Wy21FTV9XsKLU2rVqZXkVd1FPPBXWWaDKZGBwcpL29nb6+Pvr6+vD5fPj9fqxWa9NnWzWtBlHrEDqdTj772c/y+OOP09LSgtVq1SqWFAoFMpkMLS0teL1erWBDR0cHL774olauTS7u3LuoYUlqyNnGVqlS5luHXq/HZrPhdrvZt28ftVqNycnJGxbF8fv9HDt2DLPZrCnXhx56iLa2Nvbs2UNbW5tmQRoMBs2SbGZFCU2sLFVU/2NLSwtdXV309fVtWnlTA5W7urpwu9309fXR0dGhxdlJ7m2arYzXvYp6E1KjVHK5HMVi8YbFabq7uwkGg1qRE4vFQjAYpK2tja6urk3hYbuJpleWataPxWLhK1/5Cs8//zxjY2NcvnyZWCzGwsICnZ2dfPKTn9Qc/BaLZdcKRCJpVvR6PV6vl29961uaj/hG1aLUafjGzCy1h85ujkppemUJaJVq1PQ1tZKNy+VCp9PR19fH8PAwTqdT9u+RSLYRNVnkfmRXKMvrUdsSFAoFstksNpsNv9//kQrcEolEslXsSmXpcrm0KjQSiUSyE0gzTCKRSOpAKkuJRCKpA6ksJRKJpA6kspRIJJI6kMpSIpFI6kAqS4lEIqkDqSwlEomkDsTdNAgSQqwAs1s3nKanT1EUf6MHsVPch/IFKeP7gTuS8V0pS4lEIrlfkNNwiUQiqQOpLCUSiaQOpLKUSCSSOripshRCeIUQ59YfESFEaMPrLe8GJYT4TSHEyoZj/N069pkRQlwQQowKIX4mhOi4i+P/nhDid+vY7ogQ4h0hxKX1Y+/aIn07LeMNx/1bQghFCHGsjm2r6+O5KIT4nhDioxVn6z/ufxZCfPUW2wghxB8KIa6un1cP3enxmoEGXMe/vX5dnBNCnBZCHKxjn52W8TfXZXtBCPG2EOLoLT9YLcd/qwfwe8DvXvc/Q73713mM3wT+6Db3mQF8689/H/jD694XgO5Ov+MNtjEAo8DR9ddeQL+Vv0OjHjsh4/XPdAAngXeBY3Vsn9nw/M+B37nTMQL/GfjqLbb5HPCT9XPnMeC9RstmN8kYaN3w/IvA3zShjE8A7vXnn61Hxrc9DV/X2t8RQrwH/MH11tj6nSG4/vxvCyHeX79j/IkQYrur8p4E9gohgkKICSHEfwEuAj1CiH8qhDizfjf51xvG+y+EEJNCiNPAvjqO8WlgVFGU8wCKosQURalux5dpFDsg4/8d+D+Bwh0M7xRrMn5GCHFKCPEKMCaE0Ash/t0GGf9P6+MTQog/Wj8ffg7U02vkS8B/UdZ4F3AJIe6pXsrbKWNFUVIbXtqA2w252XYZK4rytqIo8fWX7wLdt9rnTn2W3cAJRVF+5+M2EEIcAF4CPqEoygNAFfjm+nt/epPp199a/yH+UgjRc5vj+gJwYf35IPCfFEU5xJoSHAQeBR4AHhZCPCWEeBj4xvr/Pgc8smH8vy2E+O0bHGMIUIQQPxVCfCCE+F9vc4y7hW2R8fqUtkdRlFdvd0BCCANrVoAq44eA/0VRlCHgt4CkoiiPsCbHvyeE6Ae+wpr8DwJ/hzWLQv28fyOE+OINDtUFzG94vbD+v3uNbbuOhRD/UAgxBfwB8I/rHdAOyngjv8XaTOKm3Gnx3+/VYU09DzwMnBFrDaUswDKAoigf54v8IfAXiqIU1+8afwY8V8d4fimEqLI2Pf6XgAuYXbcKYM0a/DTw4fprO2vK0wG8rChKDmD9Dsb6GL/zMccyAE+wJqwc8LoQYkRRlNfrGOduYstlLITQAf+eNXfL7WARQpxbf34K+H9YuyDeVxRlev3/nwaObPBVOVmT8VOsnVNVICyE+IX6oYqi/KvbHMe9xnZdxyiK8h+B/yiE+A3Wrslv3eI4DZGxEOJZ1pTlE7cY3x0ry+yG5xU2W6jqYocA/kxRlH9e74cqihLb8PJPWbsr1cOziqJE1RdCCNd1YxTAv1UU5U827iSE+Cf1jm0DC8BJ9XhCiB+zdve715TldsjYARwG3li/8DqAV4QQX1QU5exN9suvWzUa6/tfL+P/WVGUn1633efqHNtGQsDGWU33+v/uNbblOr6O/wb8cR3b7bSMEUIcYU3PfPY63XNDtiJ0aIY1ZaFOsdRuRq8DXxVCtK2/5xFC9N3sg67zC30RuLzhvfG7GONPgW8LIezrn9W1Pq6TwJeFEBYhhJVcyU8AACAASURBVAN4sc7PGhZCWNenDE8DY3cxtt3ADFsgY0VRkoqi+BRFCSqKEmTNV/RFRVHOrsvkbm44PwX+vhDCuD6WISGEjTUZv7Tu7woAz9bxWa8Af2fdF/YYa1O/xbsY225ghq27jgc3vPw8cGX9/00jYyFEL/B94H9QFGWynoNvRQ+ev2LtxLoEvAdMAiiKMiaE+JfAz9anX2XgHwKzQog/Bb5zA2viH6/7FyrAKuvTNSGEj7W7yh2hKMrP1n0v76zfrTLA31YU5QMhxH8HzrM2tTij7qP6K6+fjiuKEhdC/Pv1bRXgx3fif9tlbKWMP44Aa3K/U/4UCAIfiDUhrwBfBl5mzZUzBswB76g7CCH+DXBWUZRXrvusH7Pmw77Kmqvlf7yLce0WtlLG/0gI8cn1beP8agreTDL+V6xFsvyndZ1QURTlpmFsuyI3XAjxBWBAUZQ/bPRYJNuDEOIfAXM3OKkl9wi7Xca7QllKJBJJo5HpjhKJRFIHUllKJBJJHUhlKZFIJHVwV6vhPp9PCQaDWzSU5mdmZoZoNHrHq/K7jftNvgAjIyNR5T6qlC5lXD93pSyDwSBnz9YbGbL7OXbslgVy7inuN/kCCCHuqxYLUsb1sxVxlttOrVZTK4WsVf/Q6dDppAdBIpHsHE2tLBVFoVQqMTExQSKRIB6Pk8vlGB4e5vDhw40enkQiuY9oamUJUC6XmZubIxQKEQqFSCQSuN1uqSwlEsmO0rTKslKpkE6nicVinD59msnJScxmMy0tLRSLxUYPTyKR3Gc0rbKsVqvE43HC4TBvvvkmH374IcPDw/T09EhlKZFIdpymVZbpdJqzZ88yOztLIpFAURQsFgtOpxOTydTo4UkkkvuMplWW0WiUv/iLv2BqaopwOIwQArfbTSAQwOFwNHp4EonkPqOplKWiKORyOVZWVtQAcNLpNC6XC71eT29vL/39/bhcrkYPVSKR3Gc0jbJUFIVqtcr09DSvvPIKs7OzTE1NUSgUeOKJJ+ju7uZLX/oSDz/8MBaLpdHDlUgk9xlNoyzL5TL5fJ5EIsHc3BzLy8tYLBbsdjvd3d0Eg0H8fj9Op1MtNy+RSHY5pVKJfD5PuVwmm81Sq9W0hJNarQaA0+nEarViMBgwGAyaYVWr1cjn8wghtPe3k6ZRlsvLy0xNTXHmzBlef/11zGYzL774IoFAgGeffZbOzk7cbrfM3JFI7gFqtRq1Wo3Z2VnOnj3L/Pw8v/zlLykUClgsFvR6vaY8v/rVr/LUU0/h9/sJBAIUi0WSySTxeJzz58+j1+t58sknaWtr21ZDqmmUZT6fZ2VlhWg0SjQaxefz0d3dTX9/P319fbS3t9/xZ28scCyt0sajpq9WKhVuVnxap9Oh1+sRQmgPyb1BuVymWCyyurrKwsICMzMzjI+PUygUcLlcCCFYXV2lVCpx4sQJstksTqdTy+qLx+OsrKwwNzeH0WikUChoVul2nSdNoyyXlpYYGRlhdnaW1tZWAoEADzzwAMFg8K5Wv4vFIqVSCVhTlAaDAbPZfIu9JFuNoigoikKxWCSVSpFKpbh8+TK5XI5yuaxNuTbi9/vp7+/HYrHg9Xo12UmlubtRFIXR0VE++OADIpEIExMTGI1GvvjFL+JwODh06BAGg4HXXnuN+fl59u7di9/vx2QykcvlGB0d5c///M9JJBIsLS3hdrt5/PHHcbvdWCwWjEbjtoy7KZSloihkMhkWFhZIJBJaPGVHRwcdHR13FFe58eJU/RoAJpMJo9GIEEJO6XcA1XKs1WpUq1UKhQLJZJJoNMrExASpVIpCoUC1+tH21X19fdhsNhwOBxaLRZOdam1Kdh/qeRCJRDh//jypVIqlpSUCgQAHDx6kvb2dxx9/HIPBwMLCAgBerxe73Y5Op6NQKBAOh3nnnXdIpVJUq1U6OjrIZDKUy+VtjcFuuLJcWlpidXWVy5cvc/HiRVpbW3nkkUcYGBjA5XJhMpluS6lVKhVKpRKXL19mZWWFiYkJ5ubmtPddLhddXV20tbXxzDPPYLfbt+Nr3dcoikIikSCfz7O8vEw8HicWi7G4uEgymWRubo5MJkM4HKZYLFKtVm84HT937hzvvPMONpuNrq4uXC4Xjz76KF6vl+7ubhlvu4sol8uUSiXOnDnD9PQ0odBaG/auri6OHj2Kz+fjgQcewOFw4HA4UBSFwcFBbDYb3d3d2Gw2zp07x3vvvceVK1fI5XJ4vV6eeeYZurq6CAaD2Gy2bV3kaaiyVBSF1dVVpqenuXbtGtPT0wwNDXH48GH6+vqw2+23ZVKrfrBCocDY2BhXr17l5MmTjI6Oatu0tbUxNDTEwYMHefTRR6Wy3AYURSGZTJJIJJiYmGB2dpbp6WnGxsZYWVlhamqKcrlc9+dZrVYCgQCBQACLxUJfXx8ej0cqy12CoihatMvIyAhvvfUWDocDm81Ge3u7dgPcu3evdr1XKhWCwSAul4v29nbMZjMzMzP84Ac/IJPJkM/n6enp4YUXXqC3t5dAILDt7rWGW5axWIxr166RzWZxu910d3czPDx8W9Nv1eGbTCZ5//33iUajnD9/nqWlJcLhsOazBLTQJJvNpt3d3G73tvk57idKpRILCwuk02kuXbrE8vIyV69eZWFhgVQqRSKRwGAwMDQ0hNVqZWBgALPZjMFg2DStrlQqlMtl0uk0y8vL2uJfJBLh1KlTjI+PE4vF6OzsZN++fXR3dzfwW0tuRbVaZWlpSZth5HI5+vv7teu8s7MTm822aQap0+nw+XxYLBYqlQrhcJhkMkm1WsXr9XLw4EGCwSAdHR24XK4duX4bbllGIhHGxsZIp9MEAgEGBwf5xCc+QWtra91+qXw+z9zcHNPT0/yH//AfmJ6eJpPJaKutGxcPCoUCiUQCgKmpKarV6rY6he8nisUio6OjhMNhTp8+zdzcHLOzs0QiEaxWq2ZJDA8P093dzZe//GW8Xi9msxm9Xq99TjabJZfLMTs7y7lz55iamuIHP/gBy8vLzM/PYzabmZiYoKuri29+85tSWTY5apnFcDhMJBIhmUzS09PDpz71KaxWq7b6vRGdTkdHRwe1Wo2rV68SCoWIRqNUq1W6urp48cUX6ejoYGBgAKvVuiPfo+GWZSKRYH5+nmq1is1m0y6cehSlqghTqRTj4+PMzs6STCYplUo4nU6MRiNutxuHw0E0GiUSiVCtVimXy1pg68f5yyT1s7Gc3uTkJPPz80QiEa32qNfrxev10tXVhdvtpr+/H5/Ph9frxeFw0NLSoilLRVHQ6/W0tLRQKpUoFAq0tLRw5coVYrEYoVCIYrHI8vIyQgii0SjJZBKTySSjHJoUNY05k8lgMplwu920trZitVoxmUwfe63n83lKpRKTk5NcvHiRa9euUSgUUBQFm82GxWLZ0UXahluWMzMzvP322/T29rJ///7bytCp1WqUSiVCoRAvv/wyi4uLRCIRisUiBw8eJBAIcPz4cfbt28ebb77J3/zN35DJZFhZWaFWq1EulzXFKblzcrkcU1NTzM3N8eqrrzI1NUU+n6dWq/GpT32K48ePc+DAAY4dO4bRaNSUoxqVcL28VT9yIBDg0KFDLCws4HA4mJ2d5b/+1//K4uIiV65cYX5+nscee4x9+/bR1tZGIBBoxNeX3IJarUYsFmNpaQmXy4XFYqGrq+um17q6TyKR4Ec/+hF//dd/DayF/5VKJVwuF06n8/5QlurqWKlUolqt4nA46Ovro62tre4fIJ1Os7i4yNzcHNFoVAs7stvtBINBgsEgfX19WvbPRgtGr9djt9ux2WybpoCS2yefz2vKcnV1lWw2i91ux2w209nZSW9vr+Zb0uv1t/y91QtIp9NhMBhobW2lu7ubcrmMw+HQfFfFYpFisUihUKBSqezEV5XcBuVymXg8TiKR0GYAbreb9vZ2XC7XTa/zWq1GPB5neXmZ1dVVkskkPp+P9vZ22tratPPrnleWtVpN+/GKxSIWi4UHH3yQ3/qt36K1tbXuhZ2xsTG++93vMj8/z6VLl9Dr9Rw6dIiOjg6+9a1vMTw8rJn6Fy9exGKxUCwWMZlMOJ1O9u/fTzAYpKWlZZu/8b3NwsICf/zHf6zl9AM89NBD7NmzhxdeeIHHHnuMlpYWzZK8XdxuN0888QQ9PT288cYbWgxePp8nm82SSqXweDxb/bUkd8nq6iqvvPIKi4uLnD9/nlwux7e//W2eeOKJW0YylMtlPvzwQ8bGxpiZmaFcLnPw4EG+8IUvsHfvXgYGBjCZTNueD76RhihLRVFIp9Osrq5SLBYxGo2a87+euErV15hIJJidnWV5eZlKpYLRaKStrY3Ozk46OzsJBALaxWmxWLS2FGpAuvo/yd1RLBY3uUBaWlqw2Wx4PB7cbjdOp/OuPt9gMOBwOGhtbdX82kIILb9YLaogaQ5U91g6nSYUChGJRFAUBbPZjNPpxOfz3XB2oa5B5HI50uk0kUiExcVFyuUyVqsVj8ejzT7VKIqdpCHKslwu8/777zM2NqbldprN5rp/gJWVFZaWlrhw4YLW8zgQCNDZ2cnXvvY1+vv76enp2WTFtLa20tvbixBiU5C65O6p1WoUCgWKxSKKoiCEoKWlRSuIcLcIIbTpu1p5RmbwNC9qksn09DRvv/02lUqF3/zN32Tfvn309/ffUH7VapV8Pk88Huf1119nYWGBn/3sZ8zMzDAwMMDnPvc5nnvuOY4fP75l59Xt0pB8P3UaPjMzQy6Xo6WlBYPBgF6vr8sHkcvltIIbq6ur5PN5WltbtVziPXv2YLPZNu1jMBiwWq2aQpZ+yq1F9S+aTCbtsdFHvB3HU2cI9Z43kp1BTUlcXFwkFouRzWYJBoMcOXIEr9e7SVGq1mS5XCaXy5FIJJiammJycpKFhQVWVlawWq309/fT3d2N3+/H4XA05GbZsGl4NBolHA5jtVo5cODAbVUVunLlCj/96U8ZGxtDURS8Xi/PP/+8Vp3IarV+5CJVc8+r1SqHDh1i79690le5RbS3t/OVr3yFdDqN2+3GarXy4IMPaq6Qu6VcLpNMJlleXtbaIgshtNTVPXv2yOr5TYBajyEUCvGjH/2IUqnE8ePH8fl8dHR00NLSsummpqbFRiIRIpEI7777LtFolIsXL5LL5XjggQd46qmnePrppzly5AgdHR0NnVE0TFlms1kSiQQul4uOjo66Q4bUQPYLFy6wuLiIoig4HA4OHjxId3c3ra2tN1SCuVyOeDyOxWKhs7OT9vb2Hfd53Ks4HA4eeughyuUynZ2dWK1Wuru7taKtd0ulUiGTyZBMJlldXSUej2txdurqqkwqaA7UVezz589jtVp59NFH6e3txel0bjJgVMWay+VYXFxkamqKkydPkkgkiMVi6PV6jh07xp49ezh27BjDw8MN/FZrNDzOMpfLaeEm9cY7qlk4pVIJu92Ox+Oht7eXzs7OjyjKdDpNLpdjeXmZpaUl/H4/e/bsweFwyKnbFmG32zl69KgWAmY0GrWohq24IWUyGcbGxrS0WEVRtFlEe3v7RywWSWPI5XJaTYByuUxLS4u2fqAmj+RyOUqlEpFIhKWlJaanp/nggw9YXV3l2rVrmEwmTpw4gdfr1drJ3E0t262k4aZVJpPRLM16KRQKrK6uUqvVcDgceL1eent7aWtru6GyjEajLC8vs7y8jN1ux+l0aiWfJHeP3W7f1jt/Npvl8uXLzM7Okk6nqdVq9Pb2Mjg4iN/vl1Zlk6AaJYlEglqthtFoJBgM0tPTo7lSYrEYmUyG0dFRLl68yPj4OKdOnaJarWIwGOjq6uKxxx5jaGiI4eFh/H5/o7+WRsOVpdPpxO/315ULns/nKRaLZLNZyuWytqhgNBq1h/oZaniRmiqlVrqx2+0MDg7S09MjfZZNTjweJxQKMTU1xblz54jFYgQCAXp6ejh69Cj79++nra2t0cOUrKMutql1ZGOxGCdPnsTr9ZJMJrWMuWq1SjgcZmlpiUwmo13HDocDv9+v+bqbrTFhQ5WlEIK2tjYGBwdvedKrzmC190Y2m8VqtWor3GoMpYpatv7tt9/mr//6r1laWqJYLOJ2uzUzX8ZYNjehUIif//znTE5O8uqrr2I0GrWFvC984QscOHBA+p2bCJ1Op1n52WyWZDLJn/3ZnyGEYH5+nmw2i9frxWazaUkKiUQCvV6vrSV0d3ezb98+BgcHm27m1/AzLZ/Pk0wmyefzN91OvVtls1ktva2lpYWuri78fv8m57EampRIJLTis7BWy1ItPX+zBH5JY8nn8xQKBRYXF5mcnCQUCqHX67FarfT29tLX10draytGo7HpLqj7GYPBgM1mw+v1smfPHrLZrHaNeb1e3G43fX19eL1ecrmcNkMEaGlpweVyaeXWmlGuDV/gUevUDQwM3HSBRy0ou7i4SDwe1yolP/XUUx8JAyqVSnz44YdMTU0xOjrK3NwcwWCQ4eFh9u3bR2trKxaLRSrLJmV5eZnZ2VlOnTrF9773PWCtwn1PTw/PPfcce/bsob29vSkvqPsZu92O1Wrl6NGjfOMb39D6apXLZS2E6BOf+AR79+7lzJkznDlzhvHxcaanp7FYLAwMDNDf37+trSHuhoZblmpbgWKxeMttN6a21Wo1zXxXrURFUbR8YbXARjwep1wua2a+x+PR7lxSWTYX6qxhcXGRmZkZotEolUoFm81GT0+PViFdtSolzYWaaWW32+np6cFsNmsyDAaDeDwerXRipVIhm81qM8TW1lYtpK9ZZdtwyzKVSlEqlUgmk3ddKi2fzzM2NkYkEuGHP/wh586dI5lMAjAwMMDnP/95urq6sFgs0tfVZFSrVUZGRrhy5QojIyOMjIyg0+k4dOgQe/bs4aWXXsLv92t9WWQGVvPi9/t59tlnqVQqvPDCCyiKoi3WjI2NcfLkSX7605/y85//HIvFoi3Yff3rX8fv9+N2uxv8DW5MwzSGmg+ez+c3PdQ0uXpQe+5UKhVt9Xt5eVkr6rC8vKzdtXw+H4FAALfbLbsDNgkbO3AWi0UikQizs7PMz8+zuLiIz+fT4vT27NmDx+PZ9qZUkrunpaXlI1Wg1D48uVyOhYUFFhcXWV5eprOzE6/XS3t7O4FAAI/H07Q3woacdQaDgeHhYYQQnDp1ilAoxKVLl/irv/orgsEgJ06cqEthplIpZmZm0Ov1hMNh0uk0r7zyijaFs1qtvPDCCxw7dozDhw9r/hCpKBtPtVrVqsu8+eabLCws8NZbb3H16lVMJhN9fX088sgj/Nqv/ZqW1ridueaS7aNWq5FOp0mn07zxxhu89tprJBIJ7HY7Dz74IN/+9rcJBAJNnyjSEGWp0+lob28nk8lw7tw5qtUq0WiU8fFxdDodx44dw2Aw3PKHKxaLxONxLQUukUgwOTnJ9PQ0hUIBs9nM3r17OXHihJZSKX2VzUGtViOfz5NKpZiYmGBycpLLly8zMzPDnj176Orqore3l4cffvi22yHfDLUqkmTnUNcSUqkU8/PzjI+PY7FYsFgsBAIBHnroIa29SDPLpmGW5YEDB+jo6NhUMPa9995jaWmJarVKe3s7x48f19LnAC10SF0MWl1d5cMPP+TatWtcu3aNYrHI1atXKRQKHD58mI6ODh544AGtqZGcfjcPsViMl19+mVAoxOnTp1laWqJcLtPR0aG1oOjv79eCmEulkrZ4cDvWpTrNVy1ZtT+TbIG8M6i1a7///e8zOTnJ4uIiHR0dPP744zz22GPs378fj8ezK1JWG2ZZ9vT00NXVxeDgIOPj40QiEcbHx7WYyP7+fg4cOKA1MFN9HoVCgWq1CkAymdQWcEZGRjRFaLVa6evr48CBAwwMDNDR0dGIrym5CalUilOnTmnluFKpFD09PVqB14MHD9LR0UGlUtEKwqqxlrerLEulEuVymUQiQT6fx2g0SmW5Q6hW5enTpzlz5gwGgwG3280jjzzCr//6r2O1WndN//eGe8r9fj9DQ0PUajWt5/TY2BjRaFQLUlX9l6Ojo4RCIWZnZ2/6mUIIbDYbTqdTpjQ2CWrYVzQa5fLly1y7do3p6WktswrWbn6VSoWRkRHi8Thut5tAIKApPL1ej9PpxGAwaItD12MwGDCbzZhMJtra2rSU11QqRSaToVwu88ILL8g0yR1AbWQXDodZWVmhWCzy5JNPMjw8zEMPPYTNZmvaMKEb0fB0x0AgwOHDh0mlUpw/f550Os38/Dw2m00r/KleHPPz88RisVtm++h0OhwOBx6PR6Y0NglqLO3s7Cw//OEPWVhYYHJyknQ6rTUbU2cKi4uLvP3225hMJs3qqNVq6HS6j7SUuB61bJvb7ebIkSNUKhVef/11reUFrGVyPfPMMzv23e9XstksH374odY7vlAo8Nxzz/Ebv/EbN+zq2ew0XFl6PB6CwaB2oSQSCWZmZrRKRLlcTgs4LxaLGAwG/H4/JpOJWq1GpVKhXC6TSqUwGAx0d3fj8XjYs2cP3d3dcrrVJKiVotSyXIlEgt7eXmq12sf2f25padGUo16v1/yOG/u9qxarzWbDZrNRLBa1Rnhq59Barab1iVe3l2wfav+dcDjM2NgYi4uLeL1enE7nLbs6NjMNn4arJZwGBgZ45JFHmJ+f5+233yYSiXDq1CmtWomiKFoV7sHBQfbu3UupVKJQKBCPxxkfH8dut/Piiy/S09PDM888Q29vr4zJaxKSySTT09NcunSJU6dOYbPZ+OxnP4vf76enp+cjbUA2YjAYsFgs5HI5Lly4oJX1U6fnlUqFrq4ugsEgk5OT/OxnP9PidtWpuk6n026ssrnZ9pLJZLhy5QoTExO8+uqrJJNJPvnJT2qtIXYrDdckOp0OnU6H3W7H5/NRLpfZu3cvTqeTdDqt+ZkArbufmvqm9h5PpVJYLBasVqu2oGO32++49apk6zEajVitVvx+PwcOHMBqtRIMBrVkgZspS71ej8lkolAoaLMNVVmWy2UqlQrt7e10dnZSLpe1hcFgMKjVFFhdXSWdTlMqlZqqRuK9RKFQIJPJsLi4yMTEBLOzs9q13d3dTV9f366e6TVcWao4HA6sViudnZ0cOnSISqVCoVDQplDwK8Wq1q5ULxi19aZOp9NS4WShjOZCzb7p7OzkwIED6HQ6fD6f1sP9Vgtxqivm6NGjmyxD9RxQ65o+/PDDPPvss9pikNrvqVAoaFP4/v7+7f669yWhUIgLFy4wNjbGyy+/TK1Wo6enh7a2Nj7zmc+wf//+m94Um52mUZYbFWGzFf2U3D0bkwz6+voQQmiLd+rferhVTx+TyaT5QC0WC4qiYDKZtPqmlUpFNjfbJjKZDOFwmEgkwsrKChaLhba2Nrq7u/H5fFpSyG6laZSl5N5GXaSxWCxauIiaJLCVF9DGWYX6sNls2gxEUZRdFa6ym5ienuZHP/oRiURCi3T5xje+QV9fH11dXbs+VVUqS8mOotfrt/WiUZXyRuQi386g+iuLxaJWwKavr49gMHhP3KDkWSSRSLYUr9dLf38/AwMD91RF+93/DSQSSVNhs9m0kMCtLILSaKRlKZFI7opisUi5XMbv9/P000/T0dHB8ePHtbjoewWpLCUSyV1RKpW0zo3Hjx+ns7OT48eP33O1Y6WylEgkd8XGhANFUXC5XBgMhntKUYJUlhKJ5C4xm82YzWYcDgc9PT27skhGPUhlKZFItoR7VUmq3BvLVBKJRLLNSGUpkUgkdSDuple3EGIFuHnZ8nuLPkVR7puSNfehfEHK+H7gjmR8V8pSIpFI7hfkNFwikUjqQCpLiUQiqQOpLCUSiaQObqoshRBeIcS59UdECBHa8HpbeswKIb4uhBgTQlwSQny3ju1nhBAXhBCjQoifCSHuuEm4EOL3hBC/e4ttvrnhNzgnhKgJIR6402M2mp2WsRDid9blOyqEeF0I0VfHPlLGd0EDZNy3LttRIcQbQohbNt7ZaRlv2LZXCJGpa3u1LP+tHsDvAb973f8M9e5f5zEGgQ8B9/rrtjr2mQF8689/H/jD694XgO5Ov+Mtth8GprbyN2jkY4dk/CxgXX/+94H/LmV8z8n4e8C31p8/B/x/zSpj4C/Xx3vL7W97Gi6E+M9CiO8IId4D/uB6LS6EuCiECK4//9tCiPfX72B/IoS4VdXXvwf8R0VR4gCKoizf5vBOAnuFEEEhxIQQ4r8AF4EeIcQ/FUKcWb9z/esN4/0XQohJIcRpYN9tHu/Xgf92m/s0PdspY0VRfqkoSm795bvA7bb7kzLeArb5Oj4I/GL9+S+BL93m8HZExkKILwPTwKV6tr9Tn2U3cEJRlN+5yUAOAC8Bn1AU5QGgCnxz/b0/FUIcu8FuQ8CQEOItIcS7QojP3Oa4vgBcWH8+CPwnRVEOsfbjDQKPAg8ADwshnhJCPAx8Y/1/nwMe2TD+3xZC/PYtjvcS8Be3OcbdwnbJeCO/BfzkNsclZbx1bJeMzwO/tv78K4BDCOG9jXFtu4yFEHbgfwP+9fXvfRx3mhv+PUVRbtWp/nngYeCMWMsXtQDLAIqi/N2bjGcQeIY1QZ4UQgwripK4xbF+KYSoAqPAvwRcwKyiKO+uv//p9ceH66/t68dxAC+rlo4Q4hX1AxVF+c7NDiiEOA7kFEW5eIux7Va2S8bAmrUCHAOernM8UsZbz3bJ+HeBPxJC/CZrVmKINSV7K3ZSxr8H/F+KomREnfnsd6ossxueV9hsoZrX/wrgzxRF+ee38bkLwHuKopSBaSHEJGs/xplb7PesoihR9YUQwnXdGAXwbxVF+ZONOwkh/sltjO16vsG9a3HA9skYIcQngX8BPK0oSrHO3aSMt55tkbGiKGHWLct1C+5v1WHwwM7K+DjwVSHEH7CmlGtCiIKiKH/0cTtsRejQDPAQgBDiIUBtyvz6+mDa1t/ziFuvfP6ANasSIYSPtWn5zpSbWwAAIABJREFUtfXX43cxxp8C314XHEKIrvVxnQS+LISwCCEcwIv1fJgQQgd8nXvQl/UxzLBFMhZCPAj8CfDF633SUsYNZYatk7Fv/fcD+OfA/7vhvaaQsaIoTyqKElQUJQj838Dv30xRwtYoy78CPEKIS8A/AibXBzPGmin9MyHEKPAaEICb+jp+CsSEEGOsOYb/qaIosXXFece1nxRF+RnwXeAdIcQF1lbAHIqifAD8d9Z8LD9hgwV7C3/WU8C8oijX7nRMu4ytlPG/Y2369L31BYNX1reXMm4sWynjZ4CJ9ZlhO/B/rG/fbDK+LXZFbrgQ4gvAgKIof9josUi2Bynje5/dLuNdoSwlEomk0ch0R4lEIqkDqSwlEomkDqSylEgkkjq4q4ZlPp9PCQaDWzSU5mdmZoZoNHrvdmS6jvtNvgAjIyNR5T6qlC5lXD93pSyDwSBnz569m4/YVRw7dqvsvXuL+02+AEKI+6rFgpRx/chpuEQikdSBVJYSiURSB1JZSiQSSR1IZSmRSCR1IJWlRCKR1IFUlhKJRFIHUllKJBJJHUhlKZFIJHVwV0HpEolEcj2lUolUKkW1WqVQKFAul4nH4xSLH18UX6/XY7FYMBgM2O12jEYjLpcLk8mEXq+n3tYP24lUlpKGU6vV1LakCCG0h2R3srq6ygcffEAymWR+fp7V1VXeeOMNFhcXb7i9oijY7f9/e+ceHNd5Hfbft4+Lfe9iH8ACWCzefIsCBfER2qQk06KS2pL8iFLVSpOOm04z8R+tM+l00uQPp380M2nadKq4Y2cyTuv8YTdyW7NxUtshJcqWSEmUCBJ8ASABLAAC2MUCu4sFFvve2z+A+xGQSAqkuQtQvL8ZDLDYvfd+9569557vnPOd46CzsxOPx8OePXvw+/0cOnSIUCiE1Wqlrq6uxmfxUXRlqbMpVCoV8vk8pVKJVCpFPp/HYDBgMBiwWq3YbDbMZjMWi+Xjd6azqSwvL5PL5SgUCuRyOWZmZohEIlJZJpNJJiYmiEajH9lWe0g6nU5MJhMLCws4nU6WlpZob29HURQaGhp0Zanz6JLNZhkcHCQWi/GDH/yASCSCzWZDURT27dtHb28vra2t7NmzZ8tMw3Q+iqqqXLhwgYsXL3L9+nUuXLhANpsllUpRKpXIZrOUSiUWFhZuu70QAlVVyWazRCIRjEYjY2NjWK1WJicnaW1t5fOf/zyHDh2q8Zl9lKooy1KpRLFYRAghrQWTSdfLOrcol8ssLS2RSqUYGRlhaGgIi8WC2WzGbrdTX1+P2Wymra2Nuro66urq5PdJZ2tQLBYpFotEo1FGR0e5du0a/f398v+qqkrL0Wg0Sv+jJkMhBIVCgXw+L78PQgjS6TSKojA+Pk65XCadTqOq6qY/MKuiwS5dusS5c+dwOp00NDTg9XrZtWvXljCldbYGZrOZYDCI0WjkySefxOfzMT4+TiKR4IMPPuDq1auEQiHefPNNwuEwzz77LG63m/r6ev3BuwUoFoucPXuWiYkJXn/9dc6dO0cqlSKbzUoftBCCuro6FEWhu7sbj8dDW1sbPp9PGlEDAwP85Cc/oVgsrtu/qqqkUikURSGVSrG0tISiKJuqQ6ryrYtGo5w/fx6v10tnZyfZbJZt27ZtCWW5tufQZj+pHmWMRiMOh4NisUg4HEZVVZLJJIlEglgsRjqdZnp6mng8zu7du3niiScQQuByuXRluQUol8tMTExw+fJlrl27xvXr11FVlUqlsm5GqSgKDoeDlpYWGhoaeOyxx2hpaZEWZiaTkffhh+/HbDbL4uIiy8vL0qf9iVOWU1NTvPPOOzgcDgYHB+np6aGrqwufzyenV7VmeXmZxcVFEokE4+Pj2O12du/eLf1k+vSutphMJtxuNxaLhSNHjtDb28uhQ4ekkpyZmWF6epqhoSEGBgb49re/TUtLC6+88gotLS0yzUSntlQqFRYXF0mn01y+fJl3332XZDKJ3W6noaGBpqYmfD4fnZ2dmM1m6ULp6urC5XLh9/txOByMjIxw48YN5ubmUFUVRVFwOp0YjUZ5P2YyGbLZLPF4nEQigdfrxW63b9q5V82yvHjxInV1dbhcLlKpFM899xwGgwGn07kpyjKbzTI/P08kEuHs2bMEAgFaW1sxmUybMp5HHYPBgMPhwOFw4PP51r03MjLCyMgIp0+f5p133iEajXL16lU6Ojp45plncLvdKIqiK8tNoFKpsLS0RDKZ5Pr161y+fBmTyYTdbicUCrFv3z7a29s5cuQIFosFo9GI2WwmEAisy2yYmJhgenqaVCoFIPMr6+rqsNvtqKrK2NiYvG8XFhaw2WybddorY6zKTk0meWFyuRwLCwuMjo5SKBTw+XyYzeaqRziLxSLlcpnZ2VkWFha4fv06V69eJR6PMzw8jN/vx+v1EgwG6evro76+vmpj0bk33G434XCYPXv28MwzzxCNRrlw4QKFQoFkMsn8/Ly8sXRqSyaT4ec//zkTExPcvHmTfD6P0+nE5/PR09PD4cOH8fl88j43GAwYjcaPPNgaGxvZu3cvyWQSIQRmsxmv14vH46G3txdFUfjxj3/MxMQE8XicS5cuAdDS0rJp7rOqKst8Ps/S0hLz8/NcunSJhYUFtm3bht1uRwiB0WisxuFRVZV8Pk8+n2doaIgbN25w5swZTp06RTabJZPJ4PP5yOfztLe309HRoSvLLYTf78fn88kp3MDAAAMDA+RyOeLxOPX19QSDQZxO52YP9ZFjcXGREydOcOnSJaampshms7hcLlpbW+nr6+Nzn/scJpPpYxVaa2srbreb6elphBAoikJjYyNtbW382q/9Gna7nfHxcRYWFpienubtt9/G6XRuamuXqijLYDDIvn37iEajXL9+neXlZUZHR8lms1y8eJHZ2VlCoZBMRDWZTLd9+nwc5XJZpiksLy9TLBZJpVIUCgXm5ubIZDIMDg4yMTHB5OQk2WxWJkLn83nm5+dxOp0ficTpbD5CCOx2Oy0tLczOzuJyuairqyOTybCwsKDLrMaoqkqhUJDGRiaToVQqAbdWXWlBnY1YfoqiYLPZ8Pv9bNu2jUqlQjKZxGq1kk6nEUJQLpcRQpDP58lmszId6RNlWfb19aEoCm+//TZjY2PMz89z8uRJXC4XsViMpqYmjh8/Tnd3Nw6HA5vNht1uv2dLIZ/Pk0wmSafTRCIRUqkUly5dIplMMjQ0RDKZJB6Pk0qlKJfLFAoFGQ3P5XJEIhGZEKuz9fD7/dTX11MqlWhubqZcLhOPx1EURZdZjSmVSqTTaZLJJHNzcyQSCQqFwn3vz2q1YrFY2LlzJ5/73OeIRCKcPHmSRCLB2NgYfr+fXC4n789kMrnpMq+KsnQ4HDQ1NREIBHC73WQyGZaXl8lkMsRiMcrlMjdu3KBYLGK32+XyNofDgRBCWpiqqmIwGLDZbOusTi1FIZVKMTMzw+LiIhMTE1JpLi4uSl9lOp1meXn5I2M0Go3Y7XbsdnvV3AE6t6hUKnImsLy8TKlUkjeDZo1omQmKomA2m+U2lUoFQH4XdJnVHlVVKZVKlEolef9pWCwWvF4vNpvtnqw+LRWso6ODcrmMx+NBURRu3rzJwsKCXAVUKpXW1Q/YLKqiLBsbG3G73aRSKXp7e4nFYgwODpLP52X07PLly9TV1clgj5YyoEXQYeVpVldXx+OPP47X65X71/yRY2NjnD9/XvpGtem1tu64UqmsE+paHA4He/fupb29HYfDUY3LoLOGXC7H0tIS0WiUgYEBuXInn8/LQgm7du0iFArR3NxMU1MT2WyWdDpNLBYjm81isVjYvXs3XV1deDyezT6lRwrtntJW25TLZTkl7urq4siRI3R2dt7zFLm9vZ1AIMDw8DCLi4tEo1Fee+01mZ5ULBZxu91VOqt7oyrKUlOA9fX1tLS0YDAYmJmZkcml+XyeXC4ngzxaxExLOtUuTrlclsoznU7L/WvbRyIRIpHIOuGt/ftOY7NarXg8HhoaGggEAiiKUo3L8MijqirFYlEWy5idnWVmZoaJiQlSqRTj4+MUCgVpUbpcrnVL5DQFm0ql5GoQp9OJ2+3W0702Ac0nqd2v2n1ms9mor6/HarXe8z61IF4gEKC5uVnGHebm5qhUKhgMBsrlchXO5t6pirLUlOCePXv4+te/zs2bN/nRj37EzMwM58+fJ5lMksvlpIm9NoNfSx6HW9PwZDK57ubQLMbl5WWWl5dxu910d3ejqirj4+Nks1npEF47JoPBQHt7O0ePHiUUCvHss8/i8/nWWa06D4ZCoUCpVGJkZITJyUnOnz/Pz372M2ktrrX4NfkPDAygqir19fXU19ejKApWq5VCoUAwGCQYDBIKhQgGg3raUI3Rqv8sLy/jcrmw2+1yeuzxeAiFQng8nvsOvni9Xp5++mnGxsY4d+6crGR0p5nhZlDVrF6Px4PH48HlcjE4OEhdXR2jo6PSlNd8H1pUDW4trodbSxOXlpbW7VfL0dSUcl1dHT6fj0qlQiwWk/6wdSdqMqEoCl6vl56eHlpbW2lvb8ftdus3XhUolUoUCgUSiQRTU1PcuHGD/v5+KpWKdLu4XC4MBoN8+M3Pz5PJZLBarfKnvr4em81GIBDA6XRis9mwWCz6UtUaYzAYsFgs2Gw2GZzJZDIUCgVMJpN0qd0vFouF5uZmcrmcTGbfajKuyRIIn8/H8ePHSaVSdHR0kEgkGBwcZH5+nrGxMaanp9eZ91arVVZXXmt5worQwuEwbW1teDwegsGgTANKp9Pkcjnpr4RbFuWBAwd45plnCIfD7N+/H6fTKZde6ksdHyzlcpmpqSkSiQTXrl1jaGgIs9nMZz7zGbxeL9u3b5dTN206VyqVGBsbIx6P8/777/P+++/LNCG3243VapUrR1wu16atBHvUsdls/NIv/RI+n48333yTyclJpqenGRgYYNu2bTQ0NNyXktOS0pPJpKw+pe1HCy5pwb7NKg5dE2Vpt9vZtWuXzPZPJpPYbDYmJyfJZDLMzc3JXEtFUbDb7eTzeVmafm3kUwhBIBCgp6eH5uZmtm/fTiwW480335T+Si0fC275WTo7Ozl+/DgNDQ10dXXp0dQqouXMzczMyJ/6+np27NhBW1sbR48exeFw4Pf7MZlM0h1z5coVpqamiEajvPXWW3J2UKlUZHFZLcfParXqynITUBSFrq4uTCYT/f39ACSTSSYnJwkEAvedB2k0GrHZbNhsNhm/WKsstVmo5sf8xCpLeTCTSUbKzWYzCwsL9Pb2Mjc3Jy1ArX9HLpdjdnaWYrEo6+Bp7Nq1ix07dkj/19zcHKOjo6RSKZaXl9c9gbZv305rayv79u0jHA5jt9t1S7JKlEol5ubmSKfTvP766wwODhIIBHj88cdpamqivb0dj8eD1+ulrq5OykF7oGm5sJpDX0tcVhSFqakplpaW+P73v09jYyPHjh2Ts4vNLK7wqKHdw6VSCZfLhaIoRKNR+vv7EULgdrvxer20tbVtyCDRVvglk0muXbsmLdW197GW0zk+Ps74+Dgul+u+LdhfhJoqS6PRSENDAwDhcPi2n0kkEty4cYPl5WUZEdNuGI3Ozk46Ozu5cuUKr7/+OnNzc0QikXURc+14PT09HDp0iMcff5zW1tYt5wf5JFEqlYjFYsRiMU6fPs27777LK6+8wmOPPUZ7ezu7d+++7fXX3C+VSkUGhmBFWXo8HvL5PNPT00xPTzM5OYnH48Hn88kiKLqyrB1r72HNFRKNRkmn0xgMBtxuNx0dHYRCoQ0ry4mJCcbGxvjbv/1bYrEYMzMz6+IU8/PzzM/PS2UZDAbx+/01nx1uubItWhpBoVDA4XCgquo6KwTA5XLJyPnExIRMdF+Lltjc0tLCjh07CAQCuqKsMvl8nitXrjAxMUEul8PlcuHz+WhqasLtdt/2+muWw9LSEpcvX+bKlSukUinq6+vp7u7mySefJJ/PMzMzQzabZWJignK5zPvvv8/8/DxPPfWUTD/R+/VUH6PRiNvtplKp0NzcTCgUkr7lkZERzGYzo6OjzM7O4nQ6aW5uvmtq3sjICO+99x7xeJxIJEIulyMYDNLc3MyOHTvweDwsLCywvLyM2WzmH/7hH+ju7sZiseB0OmuqNLecsrTb7bS3t981W1+76ZLJJFeuXCEWi30kTchisWC1WtmxYwdHjx7Vb6QakMlkOHXqFENDQ2SzWfx+P+FwmO7u7jtmHBSLRcbGxohGo5w8eZKzZ89itVoJh8McOXKE3/md3yGbzTIyMsL09DR//dd/zfT0NCdOnEBVVYxGI8FgkPr6el3GNcBkMhEMBnG5XGzfvp10Os3FixcZHx8nHo/T39+P1WrF6/XS0NDAsWPH7ppUfv78eU6cOCFXBjmdTj71qU8RCoX46le/yp49exgeHmZqaooTJ07w6quvcvDgQVwuFy0tLTJDoibnXpOj3CMfF+0qFovSt5lIJGSPDkAW5ujo6KChoUHm5Om1D2uDVhDF7/fLBQWKonzk6a8lrC8tLTE6Osr4+DjJZJJKpUJjYyOdnZ10d3fjcrmwWCw0NTVhNBp57LHH8Pl8XLlyhWQyyc2bN7l48SJdXV2yeKwe+Kku2pLktrY2stksQgicTifxeJxoNEqpVGJpaQmTycTo6Ohd3SSzs7PU1dXJuqb19fXs2rWL5uZmvF4vFotF1gcIBoM0NTVht9tJp9M4nc6a5mE+lBoknU5LH8bQ0JBs5G40GrFYLLjdbr785S/T29vLnj17sFqt+hS8Bmg+q0AgQFdXF36/n46OjtvmRZZKJZLJJNFolB/+8IdcuHCBUqmE2Wzmqaee4uWXX5bBIIBAIEAul6OtrY14PM6rr75Kf38/b731Fv39/bzwwgsEAgHZ7EyXd3VRFIXnnnuOp59+Wra5PXnyJN/73vfI5XKkUikWFhaIRqN3lYXD4aCtrY3m5maOHTtGY2MjBw8epL6+Xrrbmpqa8Pv9MnhoMBiYmJgAWJejXW0eSmW5tLRELBYjmUxSKBRkJ0mTyYTX68Xr9dLU1ERLS4usnalTfbQlrouLiwghyGazsoCKViCjXC6Tz+fJZDJMTk4SjUZJpVLkcjm8Xi9Op5OmpiYaGhpkcrK2b4PBIH1Ura2tzM/Py1Yh0WiUSCRCIBDA5XJtyaTmTxJaCT2r1Uoul8NkMkmXSzqdZnZ2VubP3q7vld1ux2az4fF4aGlpobm5mXA4LItyr82jNZlMGAwGGWXX8m21TJhKpVKT3kwPpbK8du0aP/3pT7ly5YrMwzSbzfj9fn75l3+ZUCjE/v376e7u1td91xC73c7Ro0eJxWL88Ic/ZHh4WPaFDoVCdHZ2kkqlGB4e5ubNm5w4cYJ4PE4ymcTv9/OlL32JJ598ko6ODjwez0dSvIxGI36/H5fLxW/+5m/yK7/yK7z22mucPn2aM2fOMDw8zOHDh/na176G3W5HURRdYVYRLd9R6+Dqdrs5cOAAk5OTvPvuu1KprbX+tLbYfX199PX1yTYSVquVQCCA2WyWuZZrl0EbjUZ27NhBU1MTFy5c4G/+5m9IpVKoqkogEOC5554jGAxW9XwfOmVZqVRYWFhgcnKSRCIhnfwOhwOXy0UoFKK9vV0uk9OpHSaTiUAgAKz4JDULY2pqCkVRCAQCJJNJpqenuXnzJiMjIzLyrVXb7u7uvmO7W639gNFoJBQKyXw7l8slI7Ktra3r+rroiw+qi1blXKt07nA4sFqtzM7Osri4iMPhWKcsNZn09PSwe/duzGaz7Kf0cctY7XY7FosFl8tFsVgkn89z8+ZN2Xu82jxUyjKfz1MoFBgbG+O9995jaWmJcrlMY2MjR48epbW1lePHj0sfh05tMZlMtLS04Ha7ZQHo69evc/bsWbq6utizZw/xeJwLFy6QzWZZWFjAbrfz0ksv0dPTw86dO2lsbPzYAI3BYJDJ6C+++CJ79+7l1KlT/OhHP2JgYIC/+Iu/oKOjgy9+8YtS8eoWZvXRujJ2dnbidrtlfYC1QRhttqAFc7TFKBtZwqh9TvudyWT44IMPCAQCPP/881U9N3jIlKX2NNGK/mq5lVarlfb2dvmjJc3q1BatY6PZbKa5uZlUKsW1a9f44IMPWFhYoFAorGs+VV9fj8/nY8eOHezbt0+uAd8IWm5lT08PDQ0NDA8PUyqVZPpKNpvls5/9rFyxpVuY1UfrE64oStVqUGpTcqPRSKlUktH3fD5f9ZYTD42yLJfLXL16lbGxMUZHRz9Ss3KjTyed6mMymdi7dy/BYJB4PM78/Dw2m414PI7D4eCFF16QeXramnEtxehe0ZTzwYMHSafTzMzMcPHiRdLptOw1/oUvfIFQKLRpa4p1HixalbFcLicj74ODgyiKQjgcrlph6IdGWVYqFcbHx+nv72dmZua2Sev6jbA1MBqNdHR00NLSwvnz57l69apsiez3+zl8+DDBYJADBw7gcrmwWq33bflZLBbZy8VoNHLmzBlOnjwpo+zhcJjDhw/T1NSkP0w/IZjNZlwuF4lEQubqTk5O4nA4ZDvdarDllaUW0FlaWuLq1au89957TE1NrfuMZv6vLeuks7loAZonnngCs9ksKwv5fD527tyJw+HA4XBIP9cvitvtpr29nUKhwFe+8hVisRgXLlxgZmaGU6dOEYlEOHDgAG1tbb/wsXQ2F6/XS19fH263m4GBAfL5PJOTkwgh6O7uJhQKVeW4W15Zlstl5ubmmJubk0nIH14HrivLrYe2kurw4cPs379/XbvUashJq67e2NhIV1cXAwMDnDt3jlgsxokTJwgGgwQCAcLhsP4decgJBAJ8+tOfxufz8cYbb8hCOqlUik9/+tNVO+6WV5ZCCKxWq0xitdlsso+Phslkwu12y2Rkna3Dh5Vjtf2GWnAhGAzy+OOPMzs7y/LyMjMzM0QiEVpaWmSLXZ3aodWkzOfz61KJtFSytcuVfT6f9Evebr2/tkQ2EokwPz/P0tKSbHxWzfoAW15ZGo1GPB4PRqORQCBAIBBgfn5+nbJUFEV2BNTXBW8ttMhlrdA6RRqNRl5++WXGx8f5zne+w8jICGfOnCGfz3PgwAFdWdYYra1xMplcV37twoUL/P3f/71UoE6nk/379+P3+zlw4MBtE81jsRhvvPEGo6OjjIyMIISgubmZbdu2VbUT5JZXlnCrOMPa3xpaUqzD4ZCZ/zqPNlq/mKamJsrlMqFQiHK5zMLCAsPDw7S0tNDe3k5dXZ2+cKEGlMtlEomErB41Ozsr3xsaGmJyclIW6/Z4POu6Oq6tJra8vMzS0hJTU1NMT0/L4uBms1kmt1ezsPeWV5baqg2tXqGW7Q+3rBabzaZbljrrcDqd9PX10dXVRTqdJhKJcPr0aU6fPk2hUMBsNtPa2srOnTt1H2aVyefznDt3jsnJSf7u7/6Oixcvrnsvk8kAK/d6KBTipZdeIhgMUiwWSSQS8rODg4MMDAwwOjrKm2++STqdJp/PS73wyCtLrVlRsViUP9qKAJPJJP2Z2gXTv/g6sGJd2mw2VFWlpaWFcrmMyWQik8kQj8e5efMmdru96onMOkhfpXbtp6en5T384RTATCbD/Pw8Ho+HXC63Lvd2fHycSCTC9PS0XORgt9txOp3yp5rG0pZXluVymVgsxvz8PBMTE0xOTkrT3O/3s3PnTnbu3InT6cRisej9dXTWYbFYOHjwIDt27ODatWvSyvzud7/LCy+8wKFDh/TvTJUxGAyyar7T6ZS94NdOsTXi8Tjf/OY3sVgsstqQhjYNz+fzZLNZPB4PfX19tLS08PTTT9PZ2YnT6azaeWx5ZamqKtlsVnb100x2WHHmaxVP9Ja2OrfDaDTi8/mwWq00NjbS2NjIwsKCLPRwt4r8Og+GtRktWsGb5eVlstms/IxWDDqfzzM8PHzHfWnZFQ6HA7vdTmtrK62trbIvTzXZ8srybvh8Pvbv3097e7vuq9S5I1rA58UXX+TQoUMUCgUKhQIdHR16QLAGKIpCT08PoVAIn8/H7OwsQ0NDDA4Oys/E43HOnTtHNpu9Y0Ffq9WKzWZj165dPP/88/j9frZv3y6rrFebh0JZagnNH/YtOZ1OwuEwjY2N+pde566YTCb27NnD7t27pTWpJcnrVBeDwSBL9zU3N1Mul3nnnXewWq0y/zISiXD58mWpKG9n8SuKgt1up62tjWPHjslmeLVqGbPllaXBYMDpdFIulwkGg4TDYdLpNJlMRta203uB62wE7YGrT703D21RgtZuRJNFb28vu3btWtc3/sMoikJdXR2tra00NzfXPEax5ZWlEAKHwwFAY2OjLIhQKBRkO0ybzaZHNHU2jP5d2Tw05RYOhwmHw+vee+655zZjSBvmoVCWiqJgs9no7e1FURQSiQSJRIK+vj4CgQAOh0O3LHV0dKrKQ6EsLRYLdXV1HD9+nKNHj8qouMfjobm5WVeUOjo6VWfLK0sNzcJcW7lG91Xq6OjUiodGWQLSwtRWXuiKUkdHp1Y8VMoSuG0KkY6Ojk61Eb9IGoUQIg6MP7jhbHnaVFUNbPYgasUjKF/QZfwocF8y/oWUpY6Ojs6jgu7009HR0dkAurLU0dHR2QC6stTR0dHZAHeNhgshfMCp1ZdBoAzEV18fUFW18CAHI4T4M+CZ1Zc2oEFV1bs2ARZCRIBFQAWiwG+oqhq9z+N/A1hSVfVPN/DZMHAV+MZGPr9V2QQZ/y7wW0Bp9ThfVVX1rgGGWstYCKEA3waeBCrAv1JV9fT9HG8rsAkybgO+AwSABPDrqqre/JhtItRWxmbgL4EnWNGD31VV9Y/vtt+7Wpaqqs6rqtqrqmov8C3gz7TXqqoWhBAPNPVIVdWvrzneq8D/3uCmz6iquhd4H/h3a98QK1TDgv7PwP+rwn5rSq1lDPQDT67K6wfAn2xwu1rK+F8AqKr6GPAs8J/UOEsCAAAERElEQVSq9B2qCZsg4z9lRfnsBf49cFcltIZayvgloG5Vxn3AvxRCtN9tg3s+uBDivwshviWEeBf4EyHEN4QQv7fm/cvaQYUQvy6EeE8IcUEI8W0hxL3UUfsnwPfucXg/A7qFEO1CiCEhxHeBy0CrEOLfCCHOCSEGhBB/tGa8fyCEGBZCvAVs38hBhBBfAMaAK/c4voeCaspYVdU3VFVdXn35DhC6x+HVQsa7gNdXxzsLpFixMj8xVPk+ltcPeAN48R6HVwsZq4B99UFhBQpA+m4b3K+mDgGHVVX93Tt9QAixE/jHwKdWn2hl4JXV9/5SCHHHL9+qGd/BrQu+UT4PXFr9uwf4b6qq7mbl4vUAB4BeoE8IcVQI0Qe8vPq/fwTsXzOG3xZC/PZtxuYA/i3wRx9+7xNGVWW8yj/n3q3zqssYuAi8IIQwCSE6WLE8Wu9xnA8D1ZLxReBLq39/EXCuugI2Si1k/AMgA8wAE8CfqqqauM3nJPdrfr+mqurti87d4hgrX7JzYmXFjRWYBVBV9bc+ZtuXgR9s4BgabwghysAA8IeABxhXVfWd1fePr/70r752sHLRncD/0SwdIcT/1Xaoquq37nCsb7AyjVkSn+yVRFWVsRDi11mx1p7a4HhqKePvADtZmQ6OA2dYURKfNKol498D/lwI8c9YsRKn2Nj1q6WMD6yOqRmoB34uhDipquronQZ3v8oys+bvEustVMvqbwH8D1VVf/8+9v8y8LV7+PwzqqrOaS+EEJ4PjVEAf6yq6rfXbiSE+Nf3MbaDwK8KIf6EFWFWhBA5VVX//D72tZWpmoyFEJ8F/gB4SlXV/AY3q5mMVVUtAV9fs48zwJ0bwzy8VEXGqqpOs2pZrs7EvqyqamoDm9byPv4K8GNVVYvArBDibVYe3ndUlg/CYRphJaKEEOIJVqbPsBJ9+1UhRMPqe97V6fVdEULsYEXTn/3Q/wdvv8WG+Anw1VXBIYRoWR3Xz4AvCCGsQggn8PzH7UhV1SOqqrarqtoO/BfgP3wCFeWHifCAZCyE2MdKpPmFVX/g2ve2hIyFEDYhhH3172eBkqqqV3+BsT0MRHhwMvaLW8GY32fFUtfe2xIyZmXq/ZnV/diBQ8Bdx/YgomD/C/gNIcQV4F1Wn8Cqql4VQvwh8NPVC1dkxVocF0L8JfAtVVXfv83+Xga+r65ZhymE8LPyVLkvVFX96arv5ezqVGKJlXSG80KI/8mKj2UWOLfmmL+9uu2dzPhHiQcp4//IyvTptVVZTKiq+sIWk3ED8BMhRIWVKeQ/vd9xPUQ8SBk/DfyxEEJlRZF9DbbcffxN4K9Wz1cAf6Wq6sDdjv9QrA0XQnwe6FRV9b9u9lh0qoMu408+D7uMHwplqaOjo7PZPLSJtjo6Ojq1RFeWOjo6OhtAV5Y6Ojo6G0BXljo6OjobQFeWOjo6OhtAV5Y6Ojo6G+D/A421sFVMuOp2AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd2580646d8>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1152,14 +1173,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Zfb2lJdW76Phjy+XSqELGadLlAqqToUOQ5oRrr5WWa4XVdOk6ZjpudvakvIVDKzEP0SRAOxq/COwK09XJTNnwvLRanHJKek3PPy9t6tzL9knsQqHdieO7YB9cnsmsXznf+HopUjRvnowxio0y4G0BwFe+Ii1v65JL9AvaK9gpWDKGvw0+Bh5/rl7TtE3pihjTJvZmjtd/maSi8/mwDR3LpXIkGwM2GAyGglAyBhyTzAELlsWrGQPBTC1T9V5dISAtbM+yMGnYD/BBAMDJJwtbZpry1Ela9i+cpjZ0ZS+KFv8rrpBWaUU5J1+EiFfEoIjj1ShCBswFZJmoQoUkCfPRZ9AUpmYq5fhv13MD0zSEmtXXpww4TrQg82DBGjopQhnH4XNFII/B1KyV+xz/Ww17pEyoYmhMWUfvjKTPad3qbI7jxLjkNgUUeH0oo7peCRdbNEkL1CzU1TO6tyX7TpkijrTJ7U/Ihkn64Lr1PPTghQ+d6k1O5cXRRBzOBQTru2mBrCVLzgGQ/mzz1jWk8hCvYwhIksp81ZyfX5WmbS//++y+SYGqp5RahwMyOnCVqtNcgaNOv+/uS52apUpLNgZsMBgMBaHkxXgSAspYHm5g++EPp53ILDqZHCAf07AVGpTTeWLMGJntWD+ci6nu7hVbUl043fL/2Par0+HeRkl17g1quIcFb8q1IHtcGJwaA7cH2d4J8WLBEprLGrreznSaSuMtgI3VYgNbtoxxNyKntrZabdPjh+IGBtr9yjWxhew7c730T9DwSgFTiMqIT0NQ8IkMNM48Yfgl82cDDaPmqSey+yqD47jv7E6ZVhJuRvsmS6vyWnme0MiunYqOsuT9VKE/3cgYL11pukqvdbquncfxGSZi7NolyVccj8uWyb3Ons33QzZdGwCuV+3tHzRLuepHsrhAIqdw4QYyYGotzLlXtXFdz/jM/ZQSxoANBoOhIJRsjoy9mDO4dgqNgQxTCG2NpGw6VU9t3Km7MhmW7uB0WZcrr5SWLG9gScvUn9+iNmWepkEZHJd84bWGMxsZ8HvvAf3BxF1OoKxJ0LhkC1dc4iq7QDq58x6TKJHNepA//mNpAypLknXhhSKMxkYpKEMzfuilP0FrzUTZ5AniFZXz9ikSmWuhsFgBnGCR/3vukTapf4h0XJM1xVWJSMsCo+HmUyUKonnHm7LhF78AANSoFjKNdRYB9FfreP6g+D6SHNrbbgMA8NfUqMvoAEhUlOoykXN/wPOq8qI2AMz6vPxWWfozLPh0wgmigb3zDhOy5J2yahV/oPK+aGtLnQp/82W1NV+vIRSxHyjM/2YN3bg0gmrKK5ZDj59/f8OBMWCDwWAoCMNiwHmpeYkpao4GLsYUlbmrQEo/uCjeTZLz+r+/Lgacf1wssyInKCAlKTHjYrt9e7ov92G5v4ZxMgtyoiOTzItRLcdFOSlvmgNpMycLvUBqxWTYZly0ndmae7VkYU2LGpCpWgCYp7K8447s+Smv8PjxYpz8TBcAiUZeBnrZgYOLjDdc2wlIBcDxCgzMDebgOu88acmEqZ4AaP5dYEMG0pU29Vibt6daXPMYjYhQlsxzU4SN7BvSM30Yfdno7sIQPu+auFrTL38JAKg6+2wAwFe+IgsrUAsDUoXjoYckGoqvlHOlLnsyHjPrbXIgUi7UUDhQw1zkOLha1cR13dnC9iNhUzcGbDAYDAXBXsAGg8FQEIZFqvOC2RP1NDJkJ6pZULFoQCFULjurKsEXNJZk8wfOQoyXXpKW6gg1m7zoEpoYNqtKxn24PVQtym1F2bwwLkaM0SnGuHtqVTMbN6Y78yapCnNV2npxbDDUZm+grvaoaWNGr9ZSpa2DAg0X0dM5PE5miVdsLjokajBkzE9URcMxCqS2n3i8AmmOcJwfrss17GycmtkMAOMb1XnEwUvdWcOgAiNd+iPj0hGKapo4BiyMBuytFdW5r+AVMXLBcRjbodTx2bBYnsE54YOZJS+Vlhap2cdoMT4uOpYD32W69DTlEi/XHpqXGEqo9YS3tYh57p23sl1H4j1hDNhgMBgKQslTkZN4dAZS0wgeL4QFpLMg94k9axrC0xwYzOmgINOmsZ5dwokzThJgwZi4gEq5rtAQg+SBK+DOvHhTdockNznYHq0E8MRqYb5pGVmRJ/1OQOoTQk+0RASLJgVUYDIL1PRlg+Ep+zCsjyg3LSNBvJIul5DesEFaxveFXkg6d8iAyYj1WHns6cmnhPcsWqDMl4OYcYVhRgGdo1R3yJr5W/nIRwZcU9FrwQ0J/pZ5H4xpjMNVw9RqfWfMaZWPJKzcletRho47Fvmp4Y+Gz+634eo6Ci1N8Ey3FKzqeTH7dd4zLBWMARsMBkNBKNk7nbMEJ7aNTVpEBGqP5EyULtGQgrNgXOGC4T5B8gbZcLPaI9va5Dwk2KEtkrbeODSKYVvlUBTmYJCYzXiTXOqYN3DqqdKGIUnKHh5dLoyA7IEtnxtTN4E0eWIGaSxPTNtoUgsxXXk6iqsfsIpAuWoZoSmSttOaWqWQZ5whLY3ulEfoaCBrJQOlQHVfjsuQnbF7fb08k7l9+jyZUx4+Pz4oggySz0DVldCGH6/wUFYgbaWmEFdz0vG6uyUteFTXJxpfVZ8kZF1/vdwrZctDhhpvTaem2vN5sKV6FzzD/jZhvr3Ls5fCV9ZI+i+MARsMBkNBGNa7PZxh48D7ZIJpmgwAmDy9NrsDkNKC2GhFY21Mq4GEHfQ3CvPtVAJCYh0eit1pBo0ZQbkVCc9DeM20o1YfK3bcujOzKxsnTC3w8K5plzmWcqH4v/hFaelcD9chC9d8A5DaH9WOtq4znbf5nMl0YyJI5luWbAxZBpympk/OfFfdKp/JhDoCLWvOzUsBpPdL5SRmvuFYI7PiM9k9T6J86rhuXDiIU7osLZ+tMuHdvfosyjW5BVEiBgcg74caRJTRU5esGIB0fGvfGn0QCxbIc6la8TIAYO+kuUmXzfskYoLm+7ltuoKy2pZ3t6X7drRnr5OXxufEd1te4tlwYQzYYDAYCkLJrBtkOMw0pmeSk/mTa4Wxjh2bltrb0yiz1FgGPqoJk6a3mh5JwyTbBVJG0aGxgHFBnZBgcyYbzItZ1rayIZCQhXnCvqCMlUShO6h5T+WBjCzODKdswjROmh37+iSGtbVVW3VMkxEAA1lCjEqSbZwlS0c8tas45hxIi8fwmXD8UWmgRpBXjIj7JpEjbednzgsAbRrGWgdhcIw2eU8DUmivD30f5Sbz8NrqOOACPwKAdIDef3/2MzCwhKT+sKs+oAs1KM2tCfo0a/RIc6sIe/MueYcsf0HeOVyYAEjHcFxHKR7TI6ExGwM2GAyGgjBi/j0GNHC252ead4F0QgtnfCCtuFddLbNWXlwjZ6vjjpOWDC5kwHG8Lxkxr6XcmML+wOuNlySKCxKFTJ+zOVs60WObZQg+lziTkAhtYTFLqDSZhoiDcMhaeY8s6hS6JKjphQwXSGWWx4D5HZ8XnwEXUOUxgbTU6JgxdZm+HMssPlUpct/WK/dRPV1ssPVzpK1iGtvayKkDpC8IDvg4bpqLPISsmi8NFdQe/Ui3Sfie4GEHK841krI1BmwwGAwFwV7ABoPBUBBKboIgXaeDi+obaX1o/M7U7wwvKlphN69+bOxEis0NIeIkgEpR1wYD7ydW/2mOCVVYypix/XGRHKpfYRB7HLseyzSUZ6XLMgTvhS1NEjQ9UMMdKhzpQIoPxeM5XrowD+UeznewYEhlIotaDfWboyGAsxYl+/JdwjygwcxnYbo7nxHXe4zfF+G+ByL/kYIxYIPBYCgII+aEi2dqfj6YUI68Uowx+xiKGVRqmNn+sL/7yfs+nt0pG7K7A5HR4SrPwTDYfQ51/5WQ3FMOGEyGedou943DBIm898RgWmK5wRiwwWAwFATnvT/wnZ3bAuB3+93x8MEHvPcT979b6WAyHlkcgfIFTMajgUOS8UG9gA0Gg8FQOpgJwmAwGAqCvYANBoOhIBzyC9g59y3n3A3B50ecc3cFn293zv35fo7xzAGcp8M5N2A1ROfcYufcOQd73UH/DzvnVjnn1jrn/rtzzh3qsUYKh4GM/5tzbr1zrmwXyalkGTvn6pxz/+aca3fOveacu/VQjjPSqGQZa/+HnXMrVcZ3OudKtrzAcBjw0wDOAQDnXBWAJiT1zAD9bkihee8PWSgAFvP8h4jvALgWwMn6d/EwjjVSqHQZLwMwcEnr8kKly/ib3vs2AGcA+Ihz7qPDONZIodJl/Ife+9MBzAIwEcCnh3GsLLz3h/QHYDKA9fr/bAD/A8CjAMYBGAugG0CNfn8jgBcAvArgluAYPdpWAfhHAO0AHgPwcwBX6HcdAG4B8DKAVQDaALQC2ARgA4AVAM5VoawGsBLAk/u59hMAtAefrwLw3UOVxUj9VbKMo/voKVqWh7uM9RzfBnBt0TI9XGUMYAyEVHymVLI55EQM7/1G51yfc24qZHZ5FsCJAM4GsAPAKu/9XufcUgjDPAuAA/CvzrlF3vsng8N9UgU1E8DxAF4H8P3g+y7v/Vzn3BcAfNl7f41z7k59KN8EAOfcKgAXee83OOcaddtkAHd57z8WXf6JAIKlZ9Gp28oKFS7jisDhImPd9+OQl3BZ4XCQsXPuEb2uhwDcXwKxABi+E+4ZiEAp1GeDz1pUEkv17xXIzNQGEXKIhQDu8973e+83AfhF9P1PtH0JIvw8PA3gbufctQCOAuTBV+qLIYDJeORR0TJ2zlUD+BGA/+69f3vIOy0OFS1j7/1FEM15LIDzh7rRg8FwU5Fp25kNofTrAfwFgJ0AfqD7OADf8N5/dxjnYXmZ9zHINXvvr3POzQdwCYCXnHMf9t5vHeR4GwCEpYBadFs5olJlXEmodBl/D8Bb3vu/G8a1jTQqXcbw3vc6534G4BMQ88ewUQoGfCmAbd7797332wA0QlQLGtUfAfA551w9ADjnTnTOHR8d52kAn3LOVTnnmiFG8/1hF4Bj+cE5d5L3/nnv/VcBbAEwZbCO3vt3AOx0zi3Q6Ic/AfCzAzhnEahIGVcYKlbGzrmvAzgOwA1D7VcGqEgZO+fqnXMn6P/VkJd2+2D7HyyG+wJeBfFoPhdt2+G97wIA7/2jAP4ZwLNqe7kfgTAUP4bYYdcAuAeifuzA0FgG4HLn3Arn3LkAbnMSVrYa8kBXOucmO+d+Pkj/LwC4C8BaAL+B2HbKERUrY+fc/+uc6wRQ55zrdM7dfMB3PbqoSBk751oA/BXEHvqyHuOag7nxUURFyhjAMRBb9KsQJ97vAdx5oDe9P5RNKrJzrt573+OcmwDg1wA+ojYeQ4lgMh55mIxHHoeTjEesHOUh4EH1SNYA+FqlCrTMYTIeeZiMRx6HjYzLhgEbDAbDkQarBWEwGAwFwV7ABoPBUBDsBWwwGAwF4aCccBMmNPkpU1pH6FLKD+vXd2Dr1q5RrZJmMh5ZHGnyBYCVK1/q8qO4IobJ+MBxUC/gKVNa8cQTLx7UCbhgHhfTDBfdi5efJw5kaW9+x6XDDwYHuqjk+efPO/iDDxOHIuNKxmjLeDjyjZc2B9KxGy/GWdW3N9Npb1/VgD55C1CG5wkR7ztY3zxMmOBGdXmgkR7DeYtwAsUuFnuoMjYThMFgMBSEUYsD5oxNdhv+39WV3WfTpuz3TQNKLKcsoblZ2mOPzW4HUlYyGJM+EpZXj9lCrIlQxnmaCeVHLYPyCuUZLxF+1CClqitZ1rzfhvp++ae7O/muhv+vXSttfb20FMyWLbJfIICalrAMSQD2DR8Gt/FhNDYCAPobGzKXEj7nSpY1kcdyOXYHQ973g43HoTCa8jMGbDAYDAXBXsAGg8FQEEbdBBGqrDQ10ARBdWr16mw7aVLah5oYtbhZs7KfQ3PFccdJe/TR2Wt57z1pqeZUqso2mDMiVMViEwPb2AE6YULah/J46y1pKT/KuqojLTnbwBOoaowx8oA27xufuZZKlTEQONjy7DWDCZSd3n134AHVLIEzzpCWP4qnnpJ2U5BZS6E+xx6nAAAgAElEQVRTvvpjqNLP41tbAQDbUHeAd1PeiJ32QCp2imkwkYcYzPzIz+F2/k9zxWi+F4wBGwwGQ0EYMQYch+Ucc4y0IQPmzEX/RczSpk+XNpyt+J1O/AlB4PlCJtc8UZ0mkZevgWxCO23rrqx5iDP0Di3CR5nyNjuDxZaoVfCWKdPY4dnWlvaZ27QOADB/nFIPOoLa9WDhA2FHnrSjAwDQXN2ZOeHe6pShxY67cgXlvH27tM3j9L4DNWtnrZSrbVAVbGO33GeiGMxaBCB9NkA6Vqf2rEF2Z31IgZMvYcXsxHPPk/C9/raZeoyDubPyQW9v/udwjMQaMr9jy+3hsSguDl22fA+NG5fuS02Z2+J3FzESjLiy3jwGg8FwGKHkDDgOYaqrVRaqlGvixJpk34iIJkzj9NOl3aCLBIV2XYZEfVQX327oXpe9gM0Be3hXpz1OocrOkqlz8WI5/6RpSZd4Ri4nxGF7vJ0VK6TlbVErABKilNjRaSun1sFncGKwJOkzv5kKADhnQaRB5NHlFzXgng+ejG3XLmk/9CEAQE1wUeOVFZeb5kH50hZIDYPjc1uPjF2yKSDUNoT53nuvfKKIKLI8P0b3dGGvrfOkTTSzEPGDC08OoKpnp/7XkGwbKoGp3BDfModNyEJ5yxyz9E2sXCltu65PEWp+PM6ePdljxOIEgFNOkfbMM6Wllshry3sspWLD5fULMBgMhiMIJZ8rOXPFqZikAlUBxZzUOgNAyuTIeEm4SK448wHAnDnSPq3rqO7bJ2yNiRif+tTUZN8pypwnk0GTnTG8QllZHQ3KAPo0ZfRgUj1HC7R1xdEjvNYFC6RdsiTt09C3LXuQHtl5+nSxXdZt0oiGX6apo3sW/CEAYE27yGIm5Uc5vfJKejx68nkxpB58QN/WVdKvvz7tc42smlNdPxluVCttHBgYuDCY953DBwDeeUfa3/wmuy/b53QBnpAB8zlxOHKct7TMBQAcd/rcZN8TTpA2ZmH8WVHcYbAF9y1HJsxronzGN6qWpYM6N5ajXjpNmy6dlrbJ5zcvl9/6PffIbqH2yqHKZ8bIJ2JiULWBQSnUtKNXVnKteRFWw2XCxoANBoOhIIzcHEm6RuMLUyjrU1vV8se1XS4tZ6v7788eYvv2d5I+v/0tY1AlB/nkk8Vgc8EFsnVDsLg8WcGkxWLjraLhh1ObXlNoiyy32OBwVqc8yKooL87MtOM2rH057USKRhdvaCAGsLFWZNN4aWoHX71c2osv1g3LlfLRoBzSh9iYzO+UJq5RejHzgQfSPldfjXJBGEsdBh8AqTYXaxp5fgJ+R/HGxwrZE232FF3Mzmi3BFImp+6KAen5tDWHGhsfRblocaE9t65aNOO+PvUFxYOawg7p+zvp7x9A8uOcoUL4m0tF6HvnnJXsUtO3W/6hgZgvGRp8Z89Oj8eCSU2TM5fA58NLDO+DDHi4MAZsMBgMBaFkDDgOZeSsslutOpyMH7ov7UOWGTMKHuOii6S9885wB6a1iQ2TtrULL5Q29Obz+GQCNQsXyj90cyq96OpI+5RqZhtJ9Ebhubw/2tLnfyh4rBQChaqMoK/trEyf9evTLiQLZACzZp0PAGhRxWFGaJDkxbDVA76tB+Qa5C2kfQAalGJUN00tKxswGc5g5SLzyFlcACZmS2SwoYeecqVItm9nJIO69ZG66GfP/mDmWnhuMmA+P/pGgIExr0UjE1e7tgMAMJ5jKHZoMIwkHGOk/9RgaYSPCiDVPPZY2ueNN6TluIyZ9pVXpvvqQ+romZw5DVs+p1Bb2l9hoAOFMWCDwWAoCPYCNhgMhoIwLBNESMlDFRYAenulGEvk70rCxYCBFJ9q1Xe+Iy3VqzvvTNVX4CMAgFtuEWfeZz8rW6luhc4z9qf61tkrKkZPtbTL75TttEiE/x93HOA9CkdYz5SqXGwmodzOPls3vBjE7dGBwZgnbRs0LOwc9bT97a/SAKCf/Sx7fD5Dnvfss2ck3zGkquae78s/+jA1CBFMkwmD4RpUHezrKw8ZE1TvqbUyxIvPgH7M0GRGbThOKop9k+EYS00PqiaDiylkzWtA+huLyw3HWcuh069cnG+UZ1Xv7nQjsyhiLyVtNTfdJG0Ytxf+D6SeTv7ACcYChif/1a+kpc2AXsvQsade0BknMG9fjt/bK8+Bv688x7yFoRkMBkOFYlgMOAyXIeKs1dg5R3s6ANR1vgkAaLlBGNV48iQ9yO23k2m9kfS58cbLAQD/8T/K5+ajxYGxra8hcx4gZSe8FrIIbj/ppMHvbcwYlJWDCEgndZKFuEzk1E2/ln/Cyi/PP589CL1BjF5/+GEAwF/efHOyy+zZoiGQND+u4YLUWLZuTQ9HmV5yyecAAM1XXAEAaNP2Y+oYSTld+YMMkvKl3EnEQoY5f760TJggKeO4Z1IMfUsA8MILFCA9OVpQB0Kxp0xJvWeMluI1kElT84iz68sSIdtlbOhrr0mrN9S/ZCmANIFr8/a0ZAFUC2h+V0NQ9QFsmyd9xrc/I9vDNO07Rb1dqyrEdKreVFGYxwykLwi+nJQRbzr6EgCpbPNSkocLY8AGg8FQEA6JAdMuFTIB2sdIvjjRkDXMbNFQmweWpZ1++UsAwHiyMtpndCZbtuxvdMc0NZMZrc23fEH+UabVXnt+5hDA4GXrCE6KoYkpqnVSGAYrtg4AJ58sLUPumlc+mt0hpEOM5aO6Qllr/muXGu+bkqwLoLPrkwBSdsUSn9QcHnggiKnC77Vl6JSwt1tukWv66leeQOZgQELZy8EGHNrwKKK45CnR0Kv3GmRVzB+nKkCt0KOxpwjXXzRHx7v+ELZsCRgd5EfSpqUkY6YdnlezthPG29CzUf5R1vb8BPlthOIdai3F0UTyW9qUQ89JJzV+rgqDF+1KFgDgTSprZo7FvHnnAABqWM0LSGIpp69aJZ85iNkpTEjib4QPQtWZar3suLQlcGhrzeXBGLDBYDAUhGHZgMOA9LgoMu2FMyYpE1CbTBIIDSRTSv9DDwEAtmnbpBTvhz8UBvzlLy9Nukzt09nwF7+Q9hKx0zQqix1fvzfZd+FCmUW5cjJjs+Pg9ZApcJZ7773i2VkMkgZe4/jaKN2SOzDhBMBOTbhouF+jFMiANUW4iXSLacYAapdL+6Mfib2utlZYLevuhIkCb71FKvCktsJC/vqvJVrlxY+LZnLHHcF9MDC/TLz1gyEpFBM7E8Jahr/9rbQagtL87L/JZ1UJd88RdvZG6sZAW5ukw/7X/5o9XJz6CqREraFd7ftqs6cGM//rXwcAvDvxtKQPf5dDaVGjgSQBKqSOB1KBHdnIibchafIruqV9UV8lt94qrfci3IsvviTp89BdmhLP9w7HPVUJqhbhhVJ9V6GPDWpOAWYDNhgMhsMKh8SA82LfOOsmzLdR7WX3/lRaMt8wIFKnesaIMiGzSQ25ZAKM9QWQ0tdzz5X2b/8WADDzsjeyFwDgtMh92azMcNIksdMNSJ9G+cRQDhVzmDCzFcp86WpnXcPgJpJylJRFaCQHEs/vOqRlPBn1QEyZktk1JMvYtEnsZTffLLb4LVvo2Rf6xXERsjoW1QfKT8vIIE5fpWYRDhLaDSm0yOHQ2yYM+CtfSbssXSxaGgu8U4HJsz3zEiaTffNann1WWn3mjXNSBkyUKl32UJGUnBwqpjdaPfPNTolHD0kzb5mKyDe+oUs54TZthbk+8kjqX3r7H0Tzm3adbmDNSR3MOxvT8Z4s6hDle4c1p2KUSrswBmwwGAwFoWTFeGhHndyts9ODOm0x7YczHad7IGFjTeedJy2NYLo9x6SZblRb2O/Vi388mW9I37iNDFHpREuLMGCahcJVwHmZtbXlFwfMWbdf582+WeIBp+mq6Urxqtd0vJl2okxJIz7zGWkZj6m0NkwM4rM87zyx/cYLG4ZhxrSjMzpl7FixCW/YIC0fV1xyESi/WGuydd5f/xzJ5qwiayOlC+2Y1Mji1QP+/b/PHCssko922adelyTikOVpQo1sZptqO7/QVFMOUKY9qoMjJJZxJFLR2N2b8rw6amDRuj/PrxLmy8ikcBEG/p/6EV7QlgNR7LoMZgj7TFooTLju/v8pG26/HQDQEEZMcH0zhhXpi2Ga/jY2e3lfjIQ8jQEbDAZDQbAXsMFgMBSEYZkgQkcRfRGA6k9xpZ3XX5c2jBin7v+JT0jLmBvV16pV0wv9drhOvBkb1fQwmR4iDUfLxPuo927nJElppopJ9YSXFDo9eLhyBJ0q1ISp9dK6QNPBZz+bFsup69I0TYbfcOlXFcbmYyS057u3pufhI+Ij5HHphAtNNlSXIysPF0NO1LZ0fKT3US6rjhC0LNA0RTlMY1WeuCgvkHoUY0+aCiBxRj8YhF8quhrFBMFHQzlnVN3QZAekS79QiHqecizGQ2SuR29yb7WYHHh7HAv8zGi7sD/NXb/6lY5hUFCXAkjHHAAsXaKmGwrmi1+Ulg+Z2UxA+gOi4DmYk3i+7KGANBHDivEYDAZDhWJYDDj0RZAV7dsnhVzmL1RqRDrxUw1HCz0MpJ6f/jQAYFtTtijPHzBA7YYbki4dWtwlSVQkLeNxw0r3kdWcjJEzGVNPw3AdfhdHyxSFMNwlXrGB8ud9sb377rTP9OkSBjVpkrTTl8t2ij72Icm+2fNlwgCRXXWE2kl8TfFCBJWA+NoZuTTtg7IqRRIHFWpxVEfo+eJ3seMurNeqIZSUObsunReFDALobxGWXEVB8xrYSdWUroBg86dQdCIGETLgnVwhR2Wcl+YLZHNdeKupWKTw1uzZ4lC+7DLZGq4Kkrxv6F2+6ipp8/KzyXSZrqxBAZv3iROW74fwPkrlkDMGbDAYDAWhZGForLPMojwvt8tMN1eL5SRxSOGyxWpr2VgvzLdX2dJ46D+aZolgrafWOFaHdmONml6TlPYDOKn26Qwah+fkpRaGaZzlliTA667rFab0sRbRLj72ZaEG/7JeWC5TXIGB9uGYaVCcIePnI2P438xqDWtTFhaGFdV0Smp4jV5cZ7SuVmOkCAGlK2RSCoQsMc5IpTuh9SKRazOpcZhOr536tOgLE2gbWMuTtCxwNOxslaSJHiWzSR0kOicCG3OPJgy8956m1TOMS+ngq+1hkR9BuYSf5YGaMscho8FiLS4MdaRY2Pc//AcZXAw7+8xHNYUrVLc6dMCrcGlzrtkUJV0EF7Ot+vjMYapVQ+YYHomSn8aADQaDoSAMiwGHkwgDqDmjcbbYt0/sNeMu/E8AgBktaZGNzbtkVrrru/KZJGFam05/nO3DE5FafUSKvfzcSfRDuxKOkMnxeLwWms+iGPAMI+OyO+WWJACktsk6UgIWVdeCI5/R5Vzev/mrSR8Gr5MVxcyUDt9MsosiKfbTJZ3Xdcp8PbU+WGCIwlV6MqNNT0T/gJ6otnbgXF8OWkaeF5uyoZgps2b+w7AFIBlU1cp0G+jG/9a3pP3Sl6QNyh82dInW8Ec8THuHtLQfX311sm+tDv2GWklf7lcm190rLZliqM3xWRedikyEQSNxLR6uIkSlgppSyDbjFG2KMnl2ce1bALubRHNgkgsV8DPPlO207wPASt0nliVNwiy2n4nGKhGMARsMBkNBKFk5Ss5KJAD8jiuP0H7T0ZEu/sh9aXOhnfLBJkkfXLJE2j+9+e30RDoNvrlW5o7O5bKZs1doa6Tjmew8XsCQ5wsXCi232NQwfpbXPZ4XzpYrkqpA/6jn/076/NHdQdk9YIDbeW+9eHprelJWu7tWtj36lDyrWbOENUxlmnloC4srGvEiI8PZ2LENSRcys3JL9+aYpVg5psiW1k0XX8XUKwM1i34KvandKo86+joon1eC2oakfaR2rJdKmTF2HkCNsu7+pmwBqcROGS0kGh42LHpULuD18hrj6BkqAXlxzWSgZMe0I/dXix28qn1N0mfVLvEF0RTPUO7/83+yfYGB0VFk2gywigvzA6nvwOKADQaDoUJhL2CDwWAoCMMyQYTOK6oJVN9oXqBKQa0q0K6C5A3h8xdeKHyeWvIDD0i7YMG0pE9jZ/Y8VBO4b6iKMduQml1sRKfDrbpkwXilR15a6d4WkUcNPWf0FrCAKfUuIHXU8eb50D7+8czx2zvHJ10oj6VzNI2WDyovfo+6HL9jyCDzQlWFPvbY1ARBdbDcwFugiKjq6vJiibrZdHF6L0l1L3XG1elB9r4gFbtqNAW2P9Cpqy68UP6hM48HpmkitDtF+i8dg/GjCB8JTQ/lYk7Lq4QXr/5BWefte+qp0rJMAH/j9LlVdck43dmShqC+dr+0fN/wPcShHOZjMFeDP5/eKEmEobXh+65UsjUGbDAYDAWhZMV4QscKMPiKrGGYGGft1lY5EMkEnR+cecI0WQatc0YjQWCmYYiYCcSrI5PplTMDDhMFeJ010HXvSP/Z6pp6GeEzzowM+MEHpVVh1Gmc02nVQYUdPojurFdq81GSZHFs4MCoW62rHsfUjFCGHG6OQ5HKBZQvx13sE+P2cFGRmRyQHFS6c68y4L26vT5ksvwR0PlGgVCTCffVi+J4J0Ok5sJrDB1u5cJ8iTAcbrBCQRQJFaehGD3FQzbb3S0OyrCmNf3SYcRgiDDMjcya52S0YZySPxIwBmwwGAwFoeTcjyyCpkGyBc4iYU0SgrbaeGbjMcJZk+QuWW9KkwXG9yhtDkvpcyrTncdrsHyvptKWc8pmHigHht1QTrS3L/6oJKVUzZ6ddtKbfLtHWMI0UgLaiUmxQ8rBqZ9r9jWKzfl9JoKseCbdlw+JFVGovnC7DojwGcahSOUCMi3ePkMrSW45tLjQLgC0tYlWcOkVfw4AqL9ato/nyiMaxb9XVy8BgJpeSZ3dXd2QOS4RamR9HdKS+XIhk5FYoXekENpO47Uj42JOcZEoYKBypVnfCTjkwmQiHp8hpnxv5FXFpUy5D68hTtsfCRgDNhgMhoJQMgbMWY6zRuyp5PYgIzMxgdEGw2MweYMB8KFJjDPljCZNHFirYRGcJkNaRdqghqWNm2S+iW2+5RiwTuTZ8yhbypReYiahTA2nbq5vtUkNmVQdaCSj+hFWWY/cwGQLJMuTw4eo++5tFIYNbWv6NI1Zhd2bk1pabqCsOS7D9QGBdIiF7In+CQabULyTJok2QvN87fLwTMJ84xwWssHQhB8XgIntkpWmxXFokqE2cC30pC6q0Nm2hecnfeLoJR6Dmh+H46I5O9Od9HjTLpYvt3XLb5+KH90lQFofjM8h9l+NZGKLMWCDwWAoCCVjwDFT42zC2YMzdZhiyHBHbov3ofc0LE3HOstzdMXarm5pF12m02AYMqHUmWXmjlIGF0c/lJvXeDDwOhlHmzC2ibL8SlImsjYwELICEdUJTve8ebr4w7WYeAK1Jc/Fy/J5j9KxzoAiKCWrqe7PXmy1PEyu4BzGd5a7vHl9jBMnwyJrC9Pd+T9ZWqhIAClLC5kqWWy85FNeWjF/R+zPfeKY5XKWaXht/D9hvhyfUeJATWAYr6FA9EEs0sG0qC1aQvneQLWi6qDCHa8Ca2qS9wVX5gJSJTAuDh/LfCRgDNhgMBgKwoi928l8aTdk9ENYjz1M2AIGLoYY249DkAmTLS9YIHNJa+tZyT6tkbmTmS6c0cqpMPjBgCyCxID2LcopLJheN2+e/MPoB1I0MgQeJFzPJaR4wIAalrv70iLg7F4dFUipgjBijoNyZmj7A21/eUXtYy9+bN8m8w9jYWPWOhi7DbcNNlYrTa7JvVFO8Y+cAgsXI42N7/drmhtDrNg370URGXTP0bjt1tbjk208LGVMzZyHG8nMQmPABoPBUBDsBWwwGAwFYcRMEFT7CQZEh76eeLVTagtxSnLo2KDGwtC0WG0L1Tc6MKKcgLIrVnKwoFmHKhPNAHlrVo0dKzV9ea/VXGNMZbB1q7R9q9M+zc1TM8d4V4/bFzlLgYEqcqqCV/7cPtj4iMd2iOGsQjGUSaxSx2qMZOVpDcVDo7T7VKbjrpX18rjWIICB9p1LL5WWAzEuLB7+H8eQqdNvcphP3jo5cziiVDV/h0Ll/0oMBoOhQlFyBjxYOBpnE9YbAYCTTso/Rswi8gL3DyQ05HBxXMSIr/9g7id2ioXPYzAMxfiOJByInCt9bBWFuGAWGtMStAOKZrXOzHyuoaM5jFcdLI+YK8H0pdyzMXq/jGaikDFgg8FgKAjOH8SytM65LQB+N3KXU3b4gPd+4mie0GQ8sjgC5QuYjEcDhyTjg3oBGwwGg6F0MBOEwWAwFAR7ARsMBkNBsBewwWAwFIRDfgE7577lnLsh+PyIc+6u4PPtzrk/388xnhnqe92nwzk3YIU559xi59w5B3vdOcf5V+fc6v3vOfqodBk755Y7595wzq3Qv+P332t0cRjIuMY59z3n3JvOuXbn3KcO9VgjhUqWsXPu2GD8rnDOdTnn/u5QjpWH4TDgpwGcAwDOuSoATQBODb4/B8CQQvPeD+cFupjnP1Q45z4JICd/rGxQ8TIG8O+893P07/fDPNZIoNJl/FcAfu+9nwFgJoBfDuNYI4WKlbH3flcwfudAojt+MoxrGXCCQ/oDMBnAev1/NoD/AeBRAOMAjAXQDaBGv78RwAsAXgVwS3CMHm2rAPwjgHYAjwH4OYAr9LsOALcAeBnAKgBtAFoBbAKwAcAKAOcC+DSA1QBWAnjyAK6/HsBTkEG7+lDlMJJ/h4GMlwOYV7QcD3MZrwdwTNFyPJxlHFzDDJW3K5VsDjkTznu/0TnX55ybCpldngVwIoCzAewAsMp7v9c5txTAyQDOAuAA/KtzbpH3/sngcJ9UQc0EcDyA1wF8P/i+y3s/1zn3BQBf9t5f45y7Ux/KNwHAObcKwEXe+w3OuUbdNhnAXd77j+XcwtcA3A5g96HKYKRxGMgYAH7gnHsfwI8BfN3rSC4XVLKM+T2ArznnFgP4DYDrvfebSyOd0qCSZRzhSgD/UsoxPFwn3DMQgVKozwafn9Z9lurfK5CZqQ0i5BALAdznve/33m8C8Ivoe1L+lyDCz8PTAO52zl0L4ChAHnyeQJ1zcwCc5L1/4MBus1BUpIwV/857PxvCOs4F8MdD3mlxqFQZVwNoAfCM936uXvc393ezBaFSZRziSgA/2s8+B4Xh1oKgbWc2hNKvB/AXAHYC+IHu4wB8w3v/3WGcZ4+272OQa/beX+ecmw/gEgAvOec+7L3fOsjxzgYwzznXocc73jm33Hu/eBjXOFKoVBnDe79B213OuX+GMJv/OYxrHClUqoy3QjQ4vnTuA/B/DeP6RhKVKmO5MOdOB1DtvX9pGNc2AKVgwJcC2Oa9f997vw1AI+QFR6P6IwA+55yrBwDn3Ik53vCnAXzKOVflnGuGGM33h10AjuUH59xJ3vvnvfdfBbAFwJTBOnrvv+O9n+y9b4XMqG+W6csXqFAZO+eq6ZF2zo3ReyjLaBNUqIxVFV4WnOcCAGsO4JxFoCJlHOAqlJj9AsN/Aa+CeDSfi7bt8N53AYD3/lEA/wzgWbW93I9AGIofA+iEDJ57IOrHjv2cexmAyzU05FwAtznnVjkJKXsGwErn3GTn3M+HdYfFo1JlPBbAI865VyHOjw0A/ulAb3qUUakyBoC/BHCzyvmPIayyHFHJMgaAP8QIvIDLphaEc67ee9/jnJsA4NcAPqI2HkOJYDIeeZiMRx6Hk4xHcMHlg8aD6pGsAfC1ShVomcNkPPIwGY88DhsZlw0DNhgMhiMNVgvCYDAYCoK9gA0Gg6EgHJQNeMKEJj9lSusIXUr5Yf36Dmzd2uVG85wm49KiqanJt3IJbQMA4KWXXuryJVwhw2Q8EAcq44N6AU+Z0oonnnjx0K+qwnD++fNG/Zwm49KitbUVL7545MjzQOCcK+lyQSbjgThQGZdTFMSg4IrKIWz12eEhlqnJ02AYfZgN2GAwGApCoQw4ZmHvv5/93NeXbfNQPcQd8Lujjsr//khgfXnaA5DKmrLdsyd/P2CgjAeTJ3BkyNRgKBWMARsMBkNBsBewwWAwFIQRN0HEKnCo6lL97e2VdtcuaWP1+J130j5HHy1tfb20jVqSurZW2u7udN8mXR3quOOy10A1+XBz7uXdTyxLtj092TY08/B5UKZjx0p7rJZFCU0S/J/7EpUsR4NhtGAM2GAwGArCiDFgsqiYcYVMKWZaZLOTa7fJP6SzXSvSTrVKfZsmAQDerj8tc57w+GRnK1dKu0lLdjBmfF5OCCqvqRIwmHYR3gPlzm1dXdJSFmvXStvRkfbhPpRfS0u2nT493ZdaBuU+SR5L8izzHHbGjg0GgTFgg8FgKAglY8BkY7Q5knGRRZGhbtmS9iETIhs7f5auWv6j+6QljQrj0zo7pX3rLQDAtD2Py+drrpG2Z+Aq81uOm5w5D4k128mT+pN9d+1K56RyLRRHWZPxkrHyfkIRcBvZ66WXSkvm29Ym7f33p3347B57jJ9F/sceK3R21qx0XzJgPipqF6fqouMnn5zdL4QxYcORDmPABoPBUBBKxoBj5kswgmGzLpQd2g/JisnCEipH2kSqFVK6+5Qdf/Sj0irF3tbXAAAY39me7qsXc0Lr5Mw1nrNAGG9/zvxDVknPf9HIi2zgNZLFktmv1hXXwogGypvPpap3NwBgRr1Q4xlrHwYALGrqTDtduUTaL0ehE/qgvv/w5GRXMmwqJrwGXtO770pLRgwAJ5yQ/l+uWobBMBowBmwwGAwFYVgMOI+d0ebLlrGjtA02v78x2XdbrTCp8dU7AQAbMRMA0L5J2t4V2WMBwNILLwQArGuaCwD46U9l+/XXS/tm41nJvmR/U3vk+FOrlUl/Q1bBrpozRz6fe27Sp7FRmHRfH+BGtRBlFkMxX2oVcQQDP9PeCwALFkhLLaO/ug4AUPWDb8mGW24BALQHJ/z9X/81AEADGjCD2sZ11wEAPrdkTrn2rH8AAA94SURBVLLvtvqpAIB77pHPZMBUWmgbDm3AE7VIX7loGQZDUTAGbDAYDAWhZDZgxoGyresT1jm5UU9BI+Se1EA5vv0Z+UfpUV+tsE9GQ+yuPx4A8M1vpufpmi4M90qN4b3sMmmrXvw1AGBGGNxLGsZapWx36CrWpI5nnJH2qZdrqK4ulgEzQiA0f5P5bt0qLU2zNJVTxFdfnfZhxmBnYOIFgNb/8lcAgKozzwQAtN11V/JdGw27S9QWfOWVAIDNY4XthjHDtPHynPxuU7RM4lAFlQyGIxXGgA0Gg6Eg2AvYYDAYCkLJEzHoUEt0UOrQ9KStX592op6t+ulUaB/NZ131WzFBrAgykZcvl5aqrmrHifNtRsfb6c60h8RZALwWdejRGSjXkv5bZIgU5RmG9cWJK3Ss0ZdI68uMpm1Jn53V4wEADT3q/KQtYpLYLXYvXAoAqAttHfz/4osBAC93Hp85XxhGxut76ilp6QCk6YOiZ4oykIp/zJhizTwGQ9EwBmwwGAwFoWQMmM4Y7IjyfUmNmpsHdnrtNWlJk0jl7r4bADBf04v/8i+nJV3o7HlY8gcSBqYRUkBPjreHjC5mwkrTmP+Rt0vRyCsTydAuMt6GdnFAjie17EppcwNviGoE6bMebEX1IgDArCWfTPo895y0S7Tr3PYn9WLk+Uya1JDsW9MlzHrGYrmo1lYJc6NMSbh5zSH27bNEDMORDWPABoPBUBBKxoATpkZjX7umBNNYyxCwJO8YAyvC0GbLDIobbgAAzA/yl2+//f8DkDIrnpeMa/KsINf5oYekJRunAZl0TGn0jDBuSw+4racm5y5HD3mp3SztqKZZ1D3ww+zOlGeY4XDeedJSYO+9BwBY0yTMt7tDNtNmCwBLG4VR4w6lwsx2UQ2lJsz0+Kd/klaTWWZqRszOOadl7idv7T6zARuOdBgDNhgMhoJQMgZMBtWviQxVpGvz50tLIzGD+wHg9dcBABvPuARAyman0sBLxhrQs4/N05KVc2TnnzwnEQyJ7TbMAHjpJWlJj8nOuUYRmVwYARBSwTJAWGA+SXJZoQksvD9eP43CYR4zZUkZ3HQTAOAuTW65+WZpq274z2kfGoFDpgukduTHH0+3MSuEF6f71LZlC+WHTL7MRGwwFAZjwAaDwVAQhsWAw4LasRnyuHmXZPbJKxbecrZENzysJsbPLdYYXrK1CROkDXORWfVl8WK5gWphwMnSNxODgFO1ISfsjBdHCqaMeHdfau/dFRSML9JDz/vJW8IJr7wiLe26cS5yGHSrsc78bk23yCuJoOh4NTo40go+f//30rJYEW3nrLgDJM8Bp5wCANh9xZ8AAH6qBd7JgI85Ju8uDYYjG8aADQaDoSCUPAqC5JVBECRLJJ8h0WJwwxVX6AbafAkyrnC9nKi+4cJW+XjvvbyOdE5Zu1bs0SeeKJ/HjZMylySIPH8Yo0rmWZSH3nsx4VJzyFtkNKntefTR2c6MtQ5T1fQmd/eKXDo1LJs2883NYqvdfP33ki6ndT0h/yxbJi1twQy/4PJPwXf9c6Q86L13y2YGv1DWLEsK5C/UaTAciTAGbDAYDAXBXsAGg8FQEEq2IgZj/6kya4RZYorg9jCyibV86ZjbfMnnAADNDHOiZy8MLdNA/2c6xJlEkwdNGzwfkOYPMM9j4cLs9dMXFyYJcFtRK/Y6N/i5k2SXD31I2rPPBgDsrZeCOzV9st5bkvQSdNq0SRyNND1QXt/+trShDNpuOl+Ox53YqsPt7b6pA67t4TulDeUPZP2BBB+rrYpsONJhDNhgMBgKQslXRWa4Wbwa7pQp0pL1AkBd+8sAgHUt4sBpHrdXviDjVe9c/01fTfqQYXFl4zfXyhxyxx3ZrkDKZrdoaBmjtk4/XVoSuzLOw8jF7kkSvkdZ8L7a2qQQzoyAdr7dKcx3Wq2Wo+yQJIs1bWnxHSBbhKimV0uKfvzj0qrANlYL83384XTfuBwlNR1up7/QYDAMhDFgg8FgKAglD0Mjm2TLAPwLLpA2SaMFkrKTU1lL8utqSIwSJciqgZT1zZwuJ1y+XBjeSSfJ9tDOq7kBeOMNacnGGKVF1hcev5xBmZJtUhaMPpvRqhpEb8qAp0HZLEtUaip4ox6L9nHmcgBIbMh77/he5rwd7dk+wMBwM2YrM7SPTDgsq2lhaAaDwBiwwWAwFISSMWCyJNpgmeRAtpTYd0M3OTsxvZghEqRjl14KILuiL731P3kw69X/sz+TNrThknWR8fLwPAbZWZjsUM7sjOKiPBgBQrb5/CsikzFj0tRqJqE010pnFku6W23mfD5zZ+1N+uyFREE8+GD2GGS74cLTsRbBx0sZU+sIZWzRDwaDwBiwwWAwFIRhMWBGPgApAyLzYdXJxCFP2ha627kEkaa4/rxT0mJpx2Us8dNPDzy3kuOE5ZLJVfXsTHfS/OdpTUq/6vXcSsfWdDZkrjm8p3JkaYOxc4qW6d6hvZX24sbGbNx0vKjpihUpa6Y8qIjQhs6+YSw3n3v8HMiaeYxQM2H8eDnK2GAYTRgDNhgMhoJgL2CDwWAoCCV3wsUpxzXLH5V/qAtrKjGA1AShZolVD2X7EqHfjis4/K//Je3JJ0tLZ09dmIlBLxt1Z+rB2lJ9Dq0i5eaEC6+Hxc8Y2hcv6MEQsLywvS1bWIbuPW3F5NDZKQcLQ8t4PIqLIqUYQxMHs565L52vfB68xty6xgbDEQ5jwAaDwVAQhsWAQ3bGZdboEGI77a235B/SptAbo7To1bWSQst0ZTK5P7lY1n874abjB5xT69AkjIsMa2/rjGTf6unyf1X3tsxO67rqMscK2Vk5g9dJOREULRcQCUVMJ2hHR63uW5s5Vh4bjZlvWmtZ2lBD4f9cGIMsmccf3ygp4zt7bK43GGLYr8JgMBgKQslswEx2YHgTF7eY9vnPyz8sMRlUvnl1kzBbstjTWpSpPqTG4Hs2AwCmstYlAFx1FQBg4sLxmcORcYeFdXhcllXcXTs+c80TJ0obhqGVc2gUmSmZaGyb5bWTjQKp3ZiMdPt2aTdvzh4zBGXJZ0mWzISPsNolzfhMg57RFBmQSzfEDIbDDsaADQaDoSCUfFXkceOkJQN+6il5xy9YsBQA8KezNiZ9yKgSG+zjGinxb/8mLakXV+kFgL/7OwBAlX7XoCUrG3iwxoDSdWapW7xoMJljuUU+DAbKiYyd0RuMOCAb/YNL+5M+zzwn8idr5jPjvoyYCINHwkWPgVT8PA+TYABgRqPY6XGv1qjctUtarsasakgYOWEwGATGgA0Gg6EglLwcZVyE5bXXpGU86qOtk5M+LIxehf5sp0sukZZBvqGR9tlnpd2wQVpSN7bBEse75y0CkNoyeRimwlYC8w21jLh4EMttks02sPTkirVJn5NO0mL3e9YBAHbPk6Lqq1bJ95RNGAny2c9KSxv6zEbVWpL1n4IL/CddOXnHDmlJy3VAMPohXL6qnO3sBsNowhiwwWAwFISSMWAGKpDEMluLJJYENcxqo62xsVHmge5uKcZTWyttmzrUwyLrNUrLdqJB+2SvIyTLR6k5Mm/xzRCVwsjiuOXxtboIJ2lsjkG3md9p6EKdVt+Zv0FY8vw5TQP6YFKrtA8ul5aB2XE4BDDQIM1alZpa954uB1UpMjYYRhPGgA0Gg6Eg2AvYYDAYCkLJTBBUMWl6oJrMBA0iTH2l446aM/uEDhsAeOWV9P89e8T0EIewDWZeAFLzSHytlQZeN00q/dWSUl1F9Z9CCXOFaVqgEOhIY8uiy1zGOjwOvXu0AeWZIAi1Pe2tl2SX3p7sNRsMhoEwBmwwGAwFoeR5omQ8gzGfvNRXFpFhn5gBH8r5D2eE6dYAgGotVpT3NKdL2Nm+D2Q3j5kj676R1IaaCbUKaij8js8uDN8b8My2Z7cbDIbBYQzYYDAYCoLz3h/4zs5tAfC7kbucssMHvPcTR/OEJuPS4giU54GgpDI3GefigGR8UC9gg8FgMJQOZoIwGAyGgmAvYIPBYCgIh/wCds59yzl3Q/D5EefcXcHn251zf76fYzxzAOfpcM415Wxf7Jw752CvO+h/lXNulXPuVefcw3nnKBqHgYw/o/J9zTn3t4d6HIPhcMVwGPDTAM4BAOdcFYAmAKcG358DYMgfv/f+kH/cABbz/AcL51w1gG8DOM97fxqAVwFcP3SvQlDJMp4A4DYAF3jvTwUwyTl3wTCuxWA47DCcF/AzAHRpTJwKYDWAXc65cc65sQA+BOBlAHDO3eice0HZ0C08gHOuR9sq59w/OufanXOPOed+7py7IjjXnznnXlbG2uacawVwHYAvOedWOOfOdc592jm32jm30jn35H6u3enfMc45B6ABwMahuxSCSpbxNABvee+1HA8eB/CpYUnDYDjMcMiJGN77jc65PufcVAhLehbAiZAXxg4Aq7z3e51zSwGcDOAsyEvvX51zi7z34Q/4kwBaAcwEcDyA1wF8P/i+y3s/1zn3BQBf9t5f45y7E0CP9/6bAOCcWwXgIu/9Budco26bDOAu7/3Homvf55z7PIBVAN4F8BaA/3SoshgpVLKMAawFcIq+yDsBXAagpiSCMRgOEwzXCfcM5MXAl8OzweendZ+l+vcKhK21QV4WIRYCuM973++93wTgF9H3P9H2JchLJA9PA7jbOXctgKMAeYHlvBjgnBsD4PMAzgAwGWKC+C/7v91CUJEy9t5vh8j4XwD8CkAHgPf3e7cGwxGE4aYi00Y5G6IerwfwFwB2AviB7uMAfMN7/91hnGePtu9jkGv23l/nnJsP4BIALznnPuy93zrI8eZon98AgHPufwP4yjCubyRRqTKG934ZgGUA4Jz7U9gL2GDIoBQM+FIA27z373vvtwFohKjIdA49AuBzzrl6AHDOneicOz46ztMAPqV2ymaI82d/2AXgWH5wzp3kvX/ee/9VAFsATBmi7wYAM51zzFS5EKKSlyMqVcbgNTjnxgH4AoC7htrfYDjSMNwX8CqIZ/65aNsO730XAHjvHwXwzwCeVRvi/Qh+1IofQ+yEawDcA1Gjd+zn3MsAXE4HEYDb1IG0GvJiWumcm+yc+3nc0Xu/EcAtAJ50zr0KYcT/z0Hc92iiImWs+LZzbg3k5X+r9/7NA7tlg+HIQNmkIjvn6r33PRq+9GsAH1FbpaFEMBkbDOWFkpejHAYeVM96DYCv2YthRGAyNhjKCGXDgA0Gg+FIg9WCMBgMhoJgL2CDwWAoCPYCNhgMhoJgL2CDwWAoCPYCNhgMhoJgL2CDwWAoCP8/omE7OeYNa6kAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd216ee2cf8>"
+       "<Figure size 432x288 with 12 Axes>"
       ]
      },
      "metadata": {},
@@ -1179,33 +1200,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[ 956    0    3    1    1    4   11    3    1    0]\n",
-      " [   0 1114    2    2    1    2    4    2    8    0]\n",
-      " [   6    8  925   23   11    3   13   12   26    5]\n",
-      " [   3    1   19  928    0   34    2   10    5    8]\n",
-      " [   1    3    4    2  918    2   11    2    6   33]\n",
-      " [   8    3    7   36    8  781   15    6   20    8]\n",
-      " [   9    3    5    1   14   12  912    1    1    0]\n",
-      " [   2   11   24   10    6    1    0  941    1   32]\n",
-      " [   8   13   11   44   11   52   13   14  797   11]\n",
-      " [  11    7    2   14   50   10    0   30    4  881]]\n"
+      "[[ 958    0    1    4    0    7    5    2    3    0]\n",
+      " [   0 1103    3    5    1    1    3    2   17    0]\n",
+      " [   7    6  917   25   12    3    8   11   38    5]\n",
+      " [   1    0   12  943    0   19    1   11   17    6]\n",
+      " [   2    3    4    2  921    1    8    2    8   31]\n",
+      " [  10    2    4   53    8  754   10    8   35    8]\n",
+      " [  15    3    5    2   23   17  885    2    6    0]\n",
+      " [   3    8   20    8    7    1    0  946    4   31]\n",
+      " [   7    4    6   40    9   25    9   12  858    4]\n",
+      " [  11    5    2   12   49    8    0   31   11  880]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fd216ee29b0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1222,7 +1245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1286,7 +1309,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/02_Convolutional_Neural_Network.ipynb b/02_Convolutional_Neural_Network.ipynb
index 80f82d8..c4f3446 100644
--- a/02_Convolutional_Neural_Network.ipynb
+++ b/02_Convolutional_Neural_Network.ipynb
@@ -94,6 +94,15 @@
     "Note that the second convolutional layer is more complicated because it takes 16 input channels. We want a separate filter for each input channel, so we need 16 filters instead of just one. Furthermore, we want 36 output channels from the second convolutional layer, so in total we need 16 x 36 = 576 filters for the second convolutional layer. It can be a bit challenging to understand how this works."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## TensorFlow 2\n",
+    "\n",
+    "This tutorial was developed using TensorFlow v.1 back in the year 2016. There have been significant API changes in TensorFlow v.2. This tutorial uses TF2 in \"v.1 compatibility mode\", which is still useful for learning how TensorFlow works, but you would have to implement it slightly differently in TF2 (see Tutorial 03C on the Keras API). It would be too big a job for me to keep updating these tutorials every time Google's engineers update the TensorFlow API, so this tutorial may eventually stop working."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -105,20 +114,10 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
-    "import tensorflow as tf\n",
     "import numpy as np\n",
     "from sklearn.metrics import confusion_matrix\n",
     "import time\n",
@@ -126,6 +125,28 @@
     "import math"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/compat/v2_compat.py:88: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "non-resource variables are not supported in the long term\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Use TensorFlow v.2 with this old v.1 code.\n",
+    "# E.g. placeholder variables and sessions have changed in TF2.\n",
+    "import tensorflow.compat.v1 as tf\n",
+    "tf.disable_v2_behavior()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -135,16 +156,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.9.0'"
+       "'2.1.0'"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -164,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -196,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -213,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "scrolled": true
    },
@@ -245,7 +266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -281,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -323,14 +344,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f894a0bd7b8>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -387,7 +408,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -437,7 +458,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -511,7 +532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -558,7 +579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -600,7 +621,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -616,7 +637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -632,7 +653,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -648,7 +669,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -666,7 +687,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -687,7 +708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -696,7 +717,7 @@
        "<tf.Tensor 'Relu:0' shape=(?, 14, 14, 16) dtype=float32>"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -716,7 +737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -737,7 +758,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -746,7 +767,7 @@
        "<tf.Tensor 'Relu_1:0' shape=(?, 7, 7, 36) dtype=float32>"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -766,7 +787,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -782,7 +803,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -791,7 +812,7 @@
        "<tf.Tensor 'Reshape_1:0' shape=(?, 1764) dtype=float32>"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -802,7 +823,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -811,7 +832,7 @@
        "1764"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -831,7 +852,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -850,7 +871,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -859,7 +880,7 @@
        "<tf.Tensor 'Relu_2:0' shape=(?, 128) dtype=float32>"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -879,7 +900,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -891,7 +912,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -900,7 +921,7 @@
        "<tf.Tensor 'add_3:0' shape=(?, 10) dtype=float32>"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -925,7 +946,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -941,7 +962,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -968,20 +989,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "WARNING:tensorflow:From <ipython-input-31-2dd067a7547b>:2: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
+      "WARNING:tensorflow:From <ipython-input-32-2dd067a7547b>:2: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
       "Instructions for updating:\n",
       "\n",
       "Future major versions of TensorFlow will allow gradients to flow\n",
       "into the labels input on backprop by default.\n",
       "\n",
-      "See @{tf.nn.softmax_cross_entropy_with_logits_v2}.\n",
+      "See `tf.nn.softmax_cross_entropy_with_logits_v2`.\n",
       "\n"
      ]
     }
@@ -1000,7 +1021,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1025,7 +1046,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1050,7 +1071,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1066,7 +1087,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1091,7 +1112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1109,7 +1130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1134,7 +1155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1150,7 +1171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1222,7 +1243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1263,7 +1284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1319,7 +1340,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1404,14 +1425,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.6% (1059 / 10000)\n"
+      "Accuracy on Test-Set: 9.2% (915 / 10000)\n"
      ]
     }
    ],
@@ -1430,7 +1451,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -1448,7 +1469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {
     "scrolled": true
    },
@@ -1457,7 +1478,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 11.2% (1123 / 10000)\n"
+      "Accuracy on Test-Set: 8.7% (873 / 10000)\n"
      ]
     }
    ],
@@ -1476,7 +1497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {
     "scrolled": true
    },
@@ -1485,7 +1506,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Time usage: 0:00:00\n"
+      "Time usage: 0:00:02\n"
      ]
     }
    ],
@@ -1495,22 +1516,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 67.3% (6729 / 10000)\n",
+      "Accuracy on Test-Set: 61.2% (6117 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947975550>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1532,7 +1553,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "scrolled": false
    },
@@ -1541,16 +1562,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:    101, Training Accuracy:  70.3%\n",
-      "Optimization Iteration:    201, Training Accuracy:  79.7%\n",
-      "Optimization Iteration:    301, Training Accuracy:  81.2%\n",
-      "Optimization Iteration:    401, Training Accuracy:  82.8%\n",
-      "Optimization Iteration:    501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:    101, Training Accuracy:  62.5%\n",
+      "Optimization Iteration:    201, Training Accuracy:  68.8%\n",
+      "Optimization Iteration:    301, Training Accuracy:  85.9%\n",
+      "Optimization Iteration:    401, Training Accuracy:  81.2%\n",
+      "Optimization Iteration:    501, Training Accuracy:  89.1%\n",
       "Optimization Iteration:    601, Training Accuracy:  90.6%\n",
       "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    801, Training Accuracy:  89.1%\n",
-      "Optimization Iteration:    901, Training Accuracy:  87.5%\n",
-      "Time usage: 0:00:02\n"
+      "Optimization Iteration:    801, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    901, Training Accuracy:  92.2%\n",
+      "Time usage: 0:00:17\n"
      ]
     }
    ],
@@ -1560,7 +1581,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "scrolled": true
    },
@@ -1569,15 +1590,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 93.0% (9298 / 10000)\n",
+      "Accuracy on Test-Set: 94.1% (9409 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947d4b5f8>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1599,7 +1620,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "scrolled": true
    },
@@ -1608,97 +1629,97 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:   1001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   1101, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1201, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:   1301, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   1401, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1201, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1401, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   1501, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1601, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   1701, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   1601, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   1701, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   1801, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   1901, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   2001, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   2101, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   2101, Training Accuracy:  95.3%\n",
       "Optimization Iteration:   2201, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   2301, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   2401, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   2501, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   2601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   2701, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   2601, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   2701, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   2801, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   2901, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3001, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   3101, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3201, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3301, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   3401, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   3501, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   3101, Training Accuracy:  92.2%\n",
+      "Optimization Iteration:   3201, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3301, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3501, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   3601, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3701, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   3801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   3901, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   3701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   3901, Training Accuracy:  98.4%\n",
       "Optimization Iteration:   4001, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4101, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4101, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   4201, Training Accuracy:  93.8%\n",
       "Optimization Iteration:   4301, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   4401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4401, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   4501, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4601, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:   4701, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   4801, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   4601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   4701, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   4801, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   4901, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   5001, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   5101, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   5201, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:   5301, Training Accuracy:  95.3%\n",
-      "Optimization Iteration:   5401, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   5501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   5101, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:   5201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   5301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5401, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5501, Training Accuracy:  96.9%\n",
       "Optimization Iteration:   5601, Training Accuracy: 100.0%\n",
-      "Optimization Iteration:   5701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   5801, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   5701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   5801, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   6001, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   6001, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   6101, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   6701, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   6801, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   7201, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   8301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8101, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   8201, Training Accuracy: 100.0%\n",
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       "Optimization Iteration:   8401, Training Accuracy:  98.4%\n",
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-      "Optimization Iteration:   9501, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   8501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8601, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8801, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   8901, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9001, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9101, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   9201, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9301, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9401, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9501, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9601, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9801, Training Accuracy: 100.0%\n",
       "Optimization Iteration:   9901, Training Accuracy:  96.9%\n",
-      "Time usage: 0:00:24\n"
+      "Time usage: 0:02:51\n"
      ]
     }
    ],
@@ -1708,7 +1729,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {
     "scrolled": true
    },
@@ -1717,15 +1738,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.7% (9868 / 10000)\n",
+      "Accuracy on Test-Set: 98.7% (9867 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947975748>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1736,26 +1757,28 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 972    0    1    0    0    0    3    1    3    0]\n",
-      " [   0 1128    3    1    0    0    2    0    1    0]\n",
-      " [   1    0 1021    2    1    0    0    2    5    0]\n",
-      " [   0    0    0 1007    0    1    0    0    2    0]\n",
-      " [   0    0    2    0  969    0    2    0    0    9]\n",
-      " [   1    0    1   13    0  871    3    0    1    2]\n",
-      " [   1    2    0    0    2    3  948    0    2    0]\n",
-      " [   0    2   11    6    0    0    0 1003    1    5]\n",
-      " [   1    0    4    4    0    2    0    4  954    5]\n",
-      " [   0    3    0    4    2    4    0    1    0  995]]\n"
+      "[[ 975    0    0    0    0    0    1    1    3    0]\n",
+      " [   0 1128    3    0    0    0    2    1    1    0]\n",
+      " [   5    2 1015    1    0    0    0    6    3    0]\n",
+      " [   1    0    0 1003    0    3    0    1    2    0]\n",
+      " [   0    0    1    1  975    0    1    0    1    3]\n",
+      " [   2    0    0    8    0  879    2    0    1    0]\n",
+      " [   6    2    0    0    2    3  942    0    3    0]\n",
+      " [   1    2    5    2    0    0    0 1012    1    5]\n",
+      " [   5    0    3    1    0    0    0    2  960    3]\n",
+      " [   4    5    0    6    8    2    0    4    2  978]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f88a807ee48>"
+       "<Figure size 288x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1782,7 +1805,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1841,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1906,7 +1929,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1927,17 +1950,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947e53518>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1955,17 +1980,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947e1fba8>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1992,16 +2019,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 58,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f89e12f7f28>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -2021,16 +2048,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 59,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f88e80d2208>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -2050,16 +2077,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 60,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f88a0c82400>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -2097,16 +2124,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 61,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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B1Scs3ubwmHrdc0oTg+eOOZzpMyHW4Dg2N3V1EbUJe8drz68TEU2YIMcrK/Wc1at5rLZWfi2+eQIAGEDxBAAwgOIJAGAAxRMAwACKJwCAgajutldWEv3sZxdZfOst96g5H3ywWzkid5gnIiop4U10e8SpzKelyQ1Rl6SuUnPWpj4gH3Bocz1FaE7wz/8cYXBuSUggCgRY+Mjq99UUreHzP9IBNae8fFjUQ3NTVmIDzQn8jh+4e52a8/dK1+fm+X9Qc/K+x5uPJB06FHmALsjNJVoiLJwQmstf8cYbWld8vVt+INCfxd57z6ETscu++IIoM5PXnvb2BDUnqUT4wRDR6fnL1JxNm3hM+1nimycAgAEUTwAAAyieAAAGUDwBAAygeAIAGEDxBAAwENVSpeHDiT78kC8N0Pb0vkTeMOTRR/WMpNARFvO0C10BYiC1s5FGN77DDzgsO5qzfY58oEbPmbr9BharqIg4PFe0pPalT3/Al1eNTD2l5vzj3XK8ok1fjjRqlBzXlj25TusmIcW6SZ0hiCi1UelwQ0QvhsawWHhZfPYwCqacp1nD97L4tdP5cr9uhw/Le1W9+aa+H5XUZOP73488PrcMHEi0YgWvPUlP6MuOVgXkY+Hf6Od5rGYWi61tCYmvxTdPAAADKJ4AAAZQPAEADKB4AgAYQPEEADDgsaPY+8Hj8dQR0fHYDcfRVbZtO2wu4A7MMS6+DfPEHF30TZxnVMUTAAAuwZ/tAAAGUDwBAAygeAIAGEDxBAAwgOIJAGAgqsYgQa/Xtnw+fsCpM0i6si+KQ6MFsiwWCtXUUPjsWY/zCP98QZ/Ptvx+fqBvXzWnPSFFjHd16edpauKx+voQtbSEYz/HXr1sS5qPw8Y31WflOaam6ueRfoxERPv27QnHY4lLMCnJtlKEcQeDak5zIt/biYjo3Dn9PMJ2UHTqVIgaGmL/XiYmBm2v12LxnBw959gx+fc1PV1//3Nzeay6OkSNjbGfIxFRWlrQzsqyWDwjoP+SNTXL3w2Tk6M7d1VViOrr+TyjKp6Wz0dl113HD9TV6Um33CLH331Xz3nuORYqmjcvwujcYfn9VDZ+PD+wcKGaUxGQO9g0N+vn2b6dx3796/h04rH69qWyNWv4AYeismyzPEetcxIRUbHcUIv8fk9c1utZKSlUNno0PzB7tprzUWCiGC8t1c8zeTKP/c3fxOe99HotsqwyFv/FL/Sc6dPPiPEbb8xUc5Yu5bGZM+MzRyKirCyLSkr4PKdNPq/mbNsp/4d/9dXRnXvSJHme+LMdAMAAiicAgAEUTwAAA1Fd8zyWdA1Ny/uIxW+aoefMmSB3Jx/z5VNqTvY64dzhtIjjc0X//tT18issvHGjnqJdQ9mwQc+RrhVGeyHbVIcvnU4UjmPxgjz94ntgpxyfOVM/j9P846JHDyLpBqd0h+eynco8Kyv109x3H4+dOBFhbC7x+YiuvZbHn39ez9mzR7622a+fntO3nU/I7+2INDzXZLScpGllfPcD2q3frB73+efygT/+Uc1ZtJh/nwyH5dfimycAgAEUTwAAAyieAAAGUDwBAAygeAIAGEDxBAAwENVSpfr6Nnrtta9ZfN++a9ScuXN7ifE9e/TzTJjAY07PFrtpzx75Ee+uTn0Zz67d8v9BTo/0ZQqrRdraIgzOJUl2OxV0VrD4qtUD1JyxY+V4KKSfZ/THy6McmbtO+QbQksLfsfh8/eNKq6fI8bw8PUd6dPEBYVVNLAxMqaa3RvCfc/PixWpOauUm+UBgqJpz+3z+2fjP40mRB+iWxERxidn7RUvUlB+VCA0kiOj9rfp3xscff0GIymuV8M0TAMAAiicAgAEUTwAAAyieAAAGUDwBAAxEdbd9+HAfffghv1Xp1Bzi97+X24lfddUWNefnP7+dxV7hvTpiYkTGMSq7dRo/sFBvFHzjrbeK8c+Cz6g573/3fRbr2TPy+NxQXZ9Myzbwu6dLZjp0s1i/XgyvWvcrPeemm6Icmbuqq8/TL3+5l8VHjZIbOxPpDUAmTdLPU1jIY1I/kljoOHWKKoU769kOOY3KZAJa43Ii2iJ0Gima1B5xfG75uimHRm/nd9YLHRq2NDbKu1gUOfRwtn/Tyl+/Ul5pg2+eAAAGUDwBAAygeAIAGEDxBAAwgOIJAGAAxRMAwEBUS5USPF2Unsj3SR45Ut4fmYho5UrtiL4uR2rM4WFbzsdIr15E0r7tMxw2ajp8WI4//LCa8qOFw1hsSVV5pNG5wutVGl04dTL58Y/l+O18WdkVDs0p4iEzM4UmTuTLkpz2I9q3T45fd52eM7jtAIv5bL7kJRaShg+nvA8/ZPFZC+VlOkT6CrJ79jt0M5E2pKqvjzA69/j9RMXFPO7UmEZaQkZE1NDgypDwzRMAwASKJwCAARRPAAADKJ4AAAZQPAEADHhs2/7TX+zx1BHR8dgNx9FVtm1nxfokmGNcfBvmiTm66Js4z6iKJwAAXII/2wEADKB4AgAYQPEEADCA4gkAYCC6Z9sTgnZCgsXiXXKXeiIiGj5MOej0gGlzMwuFzp2jcFtbzJ9wD2Zm2lZ+PotXnNB/VLm5cry6Wj9P//xOFgudPEnhM2diPkefL2j7/RaL19c3qjmDBwfEeFoC73XQ7eQZuedBbe2ecHzuRGfaRPy9zM7W38t+QWVriR4O3zNqalgo1NRE4dbWmL+XGRlBOz/fYnFvi/5eHqmV30vhY39Fz3O1LBaqr6dwc3Ncuk4EExJsS2p6kZys5tT1HizGMzL087QKLQlqakLU2Bhm84yyeFqUnV3G4kKtu6Jsp/LL9cYbetLOnSxU9PbbkYbnCis/n8p27GDxu+7Vf+JLl8rxkhL9PK+u5h/GonHjIg3PFX6/RePH8/dx/fp31JznnpsoxscE+B5B3Ra8LO8V9PTTnjgtOcknon9n0Z/8JFPNeGx2hXzAaVOiJ55goaJ//ddIg3NFfr5FW7bw9zJ391tqzrjn7xTjehMfomGlT7FYkVOCy6zERCqTvqUMGqTmrJ2yTYxPnaqfZ/9+HpszR970CH+2AwAYQPEEADCA4gkAYCCqa562TdTWxuOzZ+s5H5UpjZKte9Sc0VLj4b36tTU3HS5PpBsn8Oubo0bpOUOOvSfGX53ucKK/fJDHnDq7uqi+nmj9+oss/k//JF/XJNIb6O7are+Brl1bevppp9G5Z8TQi1S26SyLH2jWr3leO57vZ09E9CuH7eknShe3P/444vjc4K2totw1i/gBy1JzhC3YiYho4MCDDmeSukHrTdBd19lJdOYMj99/v5oyc658Lytpo97Au2vLFhbTnsHEN08AAAMongAABlA8AQAMoHgCABhA8QQAMIDiCQBgIKqlSgMHEr34Io87Pbl2ffNH8gFpE+bLVq1OYrHTpyONzh15eeLTduISrStG3SyGP/P71ZQ+QqzDeWiuGfGdNip76yg/4PScban8rPSNAfk5aSKiektfxhQXR48STZ7MwsOGDlVT/uP3wptPRLR+vZpTMfRRFmvvTIg8Pjf06yc/B+zwgc3wy0t47N/8Rs3x/K+/FKJxmiMRHfFfR2OK+GOoj/9Azxn5c95zgIiI/uIv1JybUlNZLG37dvG1+OYJAGAAxRMAwACKJwCAARRPAAADKJ4AAAaiutuenHzpjvt/1ff3r6g5FaPkBiAD2prUnHCY323v5I3XY6K9Xe7PIdy0/X8OHxbDNxw6pOcI3RmS4tRAl1paiHbv5vHCQjVlbfkYMT5nrNI8mJxXYcRFSgpRkdDI1qkRdxm/o0tEtGzGETVlSdnvWCz5vMNOCS46eJBowNX8O1BJid60Y9rmzfKBTZvUnJaWBSw2alTPyAN0SWIiUTDI48XFQrOQy/LzV4jxk08uV3P69+fvZVULmiEDALgGxRMAwACKJwCAARRPAAADKJ4AAAZQPAEADES1VMnb0kh9/8j3gx69Tt+P6EGlb0RnYbqaIz23nxKn7VK6uuSeCiNH6jmbNskNMMrL9Zx7N/J9sGsadkUanjsyMsQNhjqILxHrtlLYVoqIaO5cYS/ty+z/szbqoblKW9/i9MYozVHm6j1eqKnnXSx28XF5mYzbtL4g2dl6zqwN48X4iyu/r+akLH6AxXpUnYw4PrdkZhLNnMnj69bp+1Hddpscf/JJ3sjFySJhiygifPMEADCC4gkAYADFEwDAAIonAIABFE8AAAMe27b/9Bd7PHVEdDx2w3F0lW3bWbE+CeYYF9+GeWKOLvomzjOq4gkAAJfgz3YAAAMongAABlA8AQAMoHgCABiI6tn2Hj2CdkKCxeKdnfpNp4wMj/Jv6ecJh88K0Vqy7bPyP+aijIyg3a+fxeKnTuk5Scoj4R6H0eamNLJYqLaWwk1NMZ+j3x+0e/e2WNxpq5NE5ZPS2qrnaMdaW/eE43GXNikpaPt8Fos7bQ+i3T9tb9dz/MJz72fPhuj8+XDM38tg79621a8fi1/06pNMCB0V43Xpwh47l2Wl8YYPoaoqCjc0xHyORETB5GTbSk3lBwoK1JyWtgQx7u+U6ssle8qlnhvHybb5exlV8UxIsKh3b77HS13dBTVn/HivGHf6AL/wwhYhyvdQiYV+/SzatInPcelSPScvT45rBYeIaFnROyxW9ABvvhALvXtbdP/9fI5n9O1gKFPpv+C0TdP+/XL84EFPXJac+HwWFRfzeUr7cHW7eFGOS/tadZO2SXrpJXnfG7dZ/fpR2e/4vjtNeUPUnPSZd4rxtbfxpj/d5oz6isWK7uINUWLFSk2lsltv5QeEvcC6ffofcvOhkeH31BzPhHFCtFh8Lf5sBwAwgOIJAGAAxRMAwEBU1zz79CGaP5/H8/Lk65pERH/7t5+L8Wee+Z6ac/To7Sw2aVKvyAN0QXJLPQ345LcsPnPmdDVnTOpn8gHLUnMeWjmRxSqbl0UcnxuSk+Wh3XGHnqNdWlK2rCciooMHha7ScTR4MNG2rV38wMaNetLkyfK/Vah/z1i4kMf+7d8ijc4lti3e6XviCT3lsWL5Gt7ixXpO4Rv8Gmpzp8ONC5e15/anipJXWXzpfXqOds9heVhuBk1EtFzY0v2ZZ5Sb3vqpAQBAg+IJAGAAxRMAwACKJwCAARRPAAADKJ4AAAaiWqqUk3SGFuW9wuKPVer7tr/5prwk6c6iE/qJ7r2XhZJP/GfkAbqgKTGDtmXxZUm3/lBfduP13iDG16zRz/Pwwzy2bVvE4bkiMZEoS3iyfMgGZYNqInpqirwJ9g27R6s5P/2pvJTlhRecx+eaY8eIZggbzhcW6jnS89NEdGRKqZ4T5v/ekk6HZ11d1NLVkz5tHcbis2frOZ6B/PeLiOjuu/Wc0YEDLJaa4NDYwGXl5UTjhRVGR+XH9ImI6MKFr5UjOWrOO9kPsthbHfLTxPjmCQBgAMUTAMAAiicAgAEUTwAAAyieAAAGorrbfjGQSU2T+Z31RalC84XLVq2W6/NeS+8Afb10xzNB7grttvSaIzRuJW+IepY+cMiR76xePzZDzZk792Mh2hxxfG44d46otJTHd/oeU3NKxsrxKVP086x9ol6Mx+1uu8cjd912utveyDv8ExHRa6/pOfffz2NObfld5PddpJHXNrG4p5feoPyOO+TO1kpPlEukbtBO7fVd9p2eFVT2XaH58iMT9CStAUwZb5B9ReVQHuvoEF+Kb54AAAZQPAEADKB4AgAYQPEEADCA4gkAYADFEwDAQFRLlaqriUpKeHzFbaUOWWPEqNNylXmL+T7UrYfisw/2hf6D6fR63qGj73KHfeOVDiB7F1pqyo48vuRr3jy5KYXbPB55f5fqaj2no4w3hiAiufFGtx/GZ3mZ5kCTRblbX2TxUwuVuRCpy5i+GqrvUT5k51oe7BGf7yXHTiTQPffx/clz9N4X9O67csOMpUuv0ZMSLR5LTo4wOhd1dhKFwzzutIRRWS7WFdKbEt0m9L85Ysu1B988AQAMoHgCABhA8QQAMIDiCQBgAMUTAMCAx7btP/3FHk8dEck96WPvKtu2hc0j3IU5xsW3YZ6Yo4u+ifOMqngCAMAl+LMdAMAAiicAgAEUTwAAAyieAAAGUDwBAAygeAIAGEDxBAAwgOIJAGAAxRMAwFwnX18AAAAHSURBVMD/BXX7Pot3sO1ZAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947e92e80>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -2126,14 +2153,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8947e11ef0>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -2157,16 +2184,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 63,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f887be39d30>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -2186,16 +2213,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 64,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f892c044dd8>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -2231,7 +2258,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2311,7 +2338,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/03C_Keras_API.ipynb b/03C_Keras_API.ipynb
index e55a7b7..b439d13 100644
--- a/03C_Keras_API.ipynb
+++ b/03C_Keras_API.ipynb
@@ -60,16 +60,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -82,7 +73,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We need to import several things from Keras. Note the long import-statements. This might be a bug. Hopefully it will be possible to write shorter and more elegant lines in the future."
+    "We need to import several things from Keras."
    ]
   },
   {
@@ -91,11 +82,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from tf.keras.models import Sequential  # This does not work!\n",
-    "from tensorflow.python.keras.models import Sequential\n",
-    "from tensorflow.python.keras.layers import InputLayer, Input\n",
-    "from tensorflow.python.keras.layers import Reshape, MaxPooling2D\n",
-    "from tensorflow.python.keras.layers import Conv2D, Dense, Flatten"
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import InputLayer, Input\n",
+    "from tensorflow.keras.layers import Reshape, MaxPooling2D\n",
+    "from tensorflow.keras.layers import Conv2D, Dense, Flatten"
    ]
   },
   {
@@ -115,7 +105,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.9.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -277,9 +267,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fab44735a20>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -431,7 +421,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from tensorflow.python.keras.optimizers import Adam\n",
+    "from tensorflow.keras.optimizers import Adam\n",
     "\n",
     "optimizer = Adam(lr=1e-3)"
    ]
@@ -472,14 +462,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch 1/1\n",
-      "55000/55000 [==============================] - 3s 59us/step - loss: 0.2201 - acc: 0.9341\n"
+      "Train on 55000 samples\n",
+      "55000/55000 [==============================] - 21s 375us/sample - loss: 0.2251 - accuracy: 0.9335\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras.callbacks.History at 0x7fab41f81ef0>"
+       "<tensorflow.python.keras.callbacks.History at 0x7f815cf3c630>"
       ]
      },
      "execution_count": 14,
@@ -511,7 +501,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "10000/10000 [==============================] - 0s 35us/step\n"
+      "10000/10000 [==============================] - 2s 187us/sample - loss: 0.0771 - accuracy: 0.9756\n"
      ]
     }
    ],
@@ -536,8 +526,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss 0.05883921128492802\n",
-      "acc 0.9807\n"
+      "loss 0.07707656768076122\n",
+      "accuracy 0.9756\n"
      ]
     }
    ],
@@ -562,7 +552,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "acc: 98.07%\n"
+      "accuracy: 97.56%\n"
      ]
     }
    ],
@@ -643,9 +633,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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RhkIhOjs7VVjXAaXRaOgepZYsRQiBy+XC6XTqSb1bnX3tWc7MzPDGG28wOjrKjRs3KJfLDAwMEA6HGRkZ4fDhwy27G+BBQErJlStXOHfuHG+++Sbj4+NUKhVqtRput5ujR4/S2dnJpz/9aYaHhwkGg81usuI+UKlUeO+995iamiIWi5HNZunu7mZoaIhwOLxvOsh9KZaNRoN6vU46nWZ6eprFxUW9t/L5fIRCIX0OTNE8tJIg09PTrKysUCgU9OG3xWIhFArR1dVFZ2envg1VcfDQEjxrdbeq1SoGgwGXy9Wyu3Vux74Uy8XFRebm5jh9+jQvvPACmUwGWFtZ+7mf+zkGBwdVTGULIKXk2rVrfP/732d1dXVTlcb29nY+97nPMTAwQE9Pj0pscoCp1+ukUqlNmaW0lGwWi0V5lveTbDbLwsIC09PTjI2NIaXUs2pHo1EGBwdVbZ0WIZFIMDk5+b5ytna7naGhIQ4dOoTb7d71RTgtYcPdKkMaDIZ9c6PuZ6SUlMvlTYl+taoG+2GuUmNfiWW5XKZWq/Hee+/x4osvcvPmTer1Ok6nk6GhIaLRKAMDA3oCBkXr0mg0KBaL5PN5zGbzHbPfw9qNpXkgmveplSG5ta54rVajUqmQTqe5cuWKHvy8Ea0CaH9/P8eOHdMrTyruD7VajVgsxujoKKlUCoBwOMzDDz9MV1fXvumw9tUvpFqtUiqVmJiY4I033tiU2Le7u5uenh46OzvVQsE+oNFoUC6X9dCiWz3PjWilQgwGgy6WG2s1bSyLXK1WyefzLCws8NZbb92xCqhWJnlkZASLxaLE8j5Sq9WYn59namqKbDarry1Eo1H8fr8Sy91ESkmtVuOdd95hbGyMc+fOkU6nkVLi9Xrp6uriIx/5CL29vWr4vU9IJBL8xV/8BX6//wMD0V0uF729vXr2KIPBoC8WaQlkNbSqgel0mmvXrul7zzeiCa7ZbKarq4tgMMjw8PC+GhLuB6rVKslkkvn5eT1k6G6dYquzb8SyUqnwxhtv8OKLLzI3N0cymcTj8eD3+4lGozz99NOEw2Hcbnezm6vYAktLS3zzm9/c0nuDwSBPPPEELpdL35GVTqcplUqcP3+emzdv3vY4rfDZnajVarS1tXH48GEGBweVWO4ylUqF2dlZZmZmSCQSm+Ys9yMtL5ZaVmUtEYMWfgBrK6qPPvoow8PDeuIMtaLaWng8Hjo6OshkMvp8lcZWb5xiscjs7Cw2mw2n04kQgmKxqHuQG7dOamhDdqPRSFtbGxaLBYfDsSlUZWBggGAwiMfj2TdDwf1EpVJhYWGBhYUFKpWKvsXRbDbrFTvdbve++e5bXiwbjQapVIrV1VVmZ2eJxWL6Cmd/fz/PP/88XV1ddHd3Y7PZ9s0X/yAghKCzs5Njx44xOTmpT53cK5lMhgsXLui2FUJsqjGvPaflANj4G7Db7YyMjBAIBOjp6dmU+i0SiTA0NER7e7uas7wPFAoFrl27xsTEhB7ep5U2Hhwc5PDhw/sqb0PL/kK0ecpiscjk5CQLCwv6Bnyfz6fXaeno6NB/7PvlS3+Q6Ojo4KGHHsJkMpHL5e4YzqOtbGs217JHbXzNZDLhdrv1kJONowi73Y7T6cRkMm3yHm02GyMjI/h8Pjo7OzdN0wQCAX1Eon47u4u2+JZMJlldXaVSqQBrKdk0j3K/ZcFvWbGs1Wokk0mWl5f5r//1v3L58mW9UuOxY8f46Ec/yqOPPsqJEyfUamaLYjAY+MQnPsGHP/xhzp8/z+uvv64nP7kVKSXLy8tkMhnGxsYYGxt733scDgcnT57UvZONotjf38/w8DBut5tQKKQLqRZ2pIUHbRRYo9Goi65KtrJ7NBqNTeFbExMT5PN5jEYjg4ODHDt2jO7u7n03ZdayClOv18lkMiSTSRYXF5mdndXnKt1uN5FIhEAggMPhUELZwrhcLlwuF5FIhGg0Sr1ev+1cZaPRwOFwkMlk9JCiW/F4PESjUV0sN+a9jEajRKPR94mlonloolmpVDCZTDidTvx+P+FweF8m425Zlclms7z55ptMT08Ti8VIJpNUq1WEEASDQY4cOUIkElE3xT5hYGAAv9+vD8FvNxSvVCp6QbONw3ANo9GI1+vFbDa/z0u02+16JUj1m2gu2vyx2WzGbrfj8/kIBoNYrVaefvppTp06RXt7e7Obec+0pFhqCX0XFhb0kraapyGEwGq14vV6VfGxfYTT6VQxsA8QmmC63W68Xi9ut1sfYUQikX0ZptVyYpnL5VhYWGB8fJzXX3+d2dnZ94WcKBSK1kUTyq6uLr761a9SLBb10cDAwAAWi2Vfev8tJ5ZaWduFhQUmJiaYnZ297f5ehULRuggh8Hg8nDp1qtlN2TVaTiyLxSIzMzPMzc1RKBSoVqv6/JbL5cJms+F2u9UKuEKh2FNaTm2KxSJzc3N6rRYtPmtjYSstD54SS4VCsVe0vNoYDAbcbjc2m41Tp05x6NAhjh8/js/nUzVbFArFntHyYmk0GvH7/QQCAf7W3/pbPPvss7hcLiWUCoViT2k5sXQ6nUSjUaxWK8888wyFQoFgMIjX66Wnp0ffiK+EUqFQ7CUtJ5bhcJhf/MVfpNFo8KUvfUkvmyqEwG6376uaHQqF4uDQcmJpNBr1Wt8qiFmhULQKYjsps/SDhVgBpnavOS1Pn5TygalZ8QDaF5SNHwS2ZeMdiaVCoVA8KOy/PUcKhULRBJRYKhQKxRZQYqlQKBRb4K5iKYTwCyHeW/+3KISY2/DYstuNEUL8wYbzjwkhPjDdkBAiJoS4JIS4KIR4WQjRsYPr/1shxD/7gPf8nQ1tfE8I0RBCHN/uNZtNE2z820KIq+v2elUI0beFY/baxs8KIc6uX/OsEOKZ7V6vFWiCjT8uhDgnhKgJIb6wxWP22sZ+IcRrQoicEOK/bOW8dxVLKWVCSnlcSnkc+CPgD7THUsqKEGJXQ4+klL+14Xr/L/CXWzz0aSnlMeAM8C83viDW2DUPWkr5pxva+BVgUkr53m6df6/ZaxsD54ET6/b6c+D3t3jcntkYiAO/LKV8BPhV4E928dx7ThNsPA38PeB/3ONxe2njEvBvgLuK6kbu+eJCiP8mhPgjIcTbwO/fquJCiMtCiOj6339XCPHOeg/2NSHEvRQ6+dvAt+6xeW8Ah4QQUSHEdSHEN4HLQI8Q4p8LId5d77l+b0N7/9W6F3saGL7H6/1t4H/e4zEtz/20sZTyNSmllgb9LaD7Hpt3320spTwvpZxff3gFsAshrHc7Zr9xn20ck1JeBO5euP3O7IWN81LK06yJ5pbYrlJ3A6eklL99pzcIIY4AXwI+ut6j1YG/s/7a14UQJ+5ybB/QD/zwHtv1KeDS+t9DwB9KKY+y9uUNAR8GjgOPrw8VHge+vP7cJ4GTG9rw60KIX/+A632Jexf0/cJ9tfE6/xB48R7btdc2/jxwTkr5/qJA+5+9sPF22Gsbb4ntut/fllK+v+rUZn4WeBx4V6xtT7QDywBSyn/0Acd+GfjzLVxD4zUhRB24CPxrwAdMSSnfWn/959f/nV9/7GLtS3cDf6V5OkKIF7QTSin/6G4XFEJ8BChIKS9vsY37jftqYyHE3wVOAE9tsT3NsPFR4N+vn/cgcr/v43tlz218L2xXLPMb/q6x2UPVSu4J4L9LKf/FNs7/ZeD/uIf3Py2ljGsPhBC+W9oogH8npfzaxoOEEP90G23b2MaD6lXCfbSxEOLngH8FPHUPHtue2lgI0Q38FfArUsrx7ZxjH3C/7+N7pRn38ZbZjQnTGPAYgBDiMdaGzwCvAl8QQoTWX2sXW1v5HAHagDdvef7aDtr4EvAPhBCu9XN1rbfrDeCzQgi7EMIN/PJWTrY+0fxFDuB85R2IsUs2FkJ8CPga8Gkp5fItr7WEjddv0v8F/I6U8ic7aNN+IsYu3sd3olVsvB12Qyz/AmgXQlwBfhMYA5BSXmXNlX5ZCHEReAXohA+c6/gy8D/lhn2YQogAa73KtpBSvszaytybQohLrK3CuqWU54A/Ay6wNnf27oZr3m2u4+PAjJRyYrtt2mfspo3/A2vDp2+vLxi8sP7+VrLxbwKHgN8VfxNiE9pu2/YJu2ZjIcRJIcQs8DzwtfVztpqNEULEgP8E/D0hxKwQ4qG7XX9f7A0XQnwKGJBS/udmt0Vxf1A2PvjsdxvvC7FUKBSKZqO2OyoUCsUWUGKpUCgUW0CJpUKhUGyBHe0JDQQCMhqN7lJTWp9YLEY8Hn9gCgA9aPYFOHv2bPxBypSubLx1diSW0WiUM2fO7OQU+4oTJ+7Hzq7W5UGzL4AQ4oEqsaBsvHXUMFyhUCi2gBJLhUKh2AJKLBUKhWILKLFUKBSKLaDEUqFQKLbAbqeTvy80Gg3q9TrT09Mkk0kSiQTJZBKr1YrT6cTn8zEyMoLVasVqtWIwqD5AoVDsLi0vllJKqtUqpVKJn/zkJ5w7d47z589z/vx5/H4/3d3dPPzww/zGb/wGgUCAQCCgxFKhUOw6LS+WgC6Wy8vLTE1Nsby8TC6Xw2g0YrVaWV5eJpFIYDKZ8Pl8mM3mZjdZcQfq9TqlUoliscjc3BwAAwMDuN3ubZ2vWCxSLpcxmUyYzWaMRiMm0774WSs2UKvVyOVyFItFZmdnqVarhMNhHA4HHo8Hp9PZ7Ca2vlg2Gg2y2Syrq6u89957vPbaa5TLZYQQ5PN5YrEYVquV9957j56eHsLhMHa7vdnNVtyBQqHA7Ows4+PjfP3rX6fRaPB7v/d7fOhDH7rnc0kpmZubY35+nra2Nvx+P3a7HZ/Px3oJBMU+IZvNcunSJaampvjDP/xDkskkn//85zly5AgnTpxgeHgYIURT7drSYtloNKhWq8TjcZaXl0kmk+Tza1nmDQYD9XqdWq1GuVzWPQyVcq61qVarZDIZUqkUCwsLAJTL268Fls/nSSQS1Go16vU6Pp8Pr9erxHIf0Wg0KBQKzM3NMTMzw+zsLPF4nFgsht1u5/Dhw/p9rcTyNtTrdfL5PMlkkr/8y79kdHSUGzduNLtZih2SyWS4fPkysViMfD6P2WzedgcnpWR6epqzZ8/qHeexY8f44he/iNV6oCrXHliq1SrFYpHx8XH+9E//lLm5ORKJBOVymR/84Ae8/fbbdHd3c/z4cYxGY1PXI1pOLBuNBrVajWq1qg+/Y7EY4+PjZDKZ2x4jpaRer1OtVqlUKlQqFQwGA0II/X9Fa1Aul0kmk6TTaWq12o7ml6WUlEolstks2WyWXC5HZ2cn9fpWi4Iqmo02h53JZJienmZxcZFqtYqUkkQiQS6XI5/Pt8SIseXEcmVlhYsXL5JMJrl27RqJRIKzZ8+ysLCgD8FvReuZMpkMVqsVn89HMBjE4XDQ0dFBW1vbHn8Kxa1IKZFSkk6nuXLlCktLS5TL5R3NLwsh8Pv9RKNRxsbGGBsbIx6PUyqVMJvNaqFvH5BOp7lx4waTk5PE43EymQy1Wg2TycTw8DChUIhIJILZbG56lEvLiWU+n2d8fJzFxUXOnDlDIpFgdnaWbDZ7x2MqlQqJRIJGo8HExAQej4dKpYLX68Xj8SixbAGklPrc1NLSEvF4nEajsePzOhwO2traEEKQyWTI5/P6/KXJZFKjihanVCoRj8dJJBL6ugOsrUkEg0F6enrweDwYjcYmt7QFxXJxcZEXX3yRRCLB0tISpVKJUql012Py+Tyjo6PYbDZisRg2m42Ojg48Hg/PPvssUkrcbjder3ePPoXiVtLpNMvLy0xMTBCLxWg0GoyMjBCJRLYdNgRrHWWhUCCTybC8vMzq6iqVSoVqtYrFYlFi2aJonefMzAyvvfYasVhs00Kf0WhkYGCARx55hGCwNdKLtpxYxuNxTp8+zerqqj7n+EHk83kmJib09xoMBvx+P263m0gkQldXF0IIJZZNJJfLMTMzw9zcHAsLCzgcDgYGBujr69tRDJ0Wg5vNZkkkEmQyGSqVipq3bHG0tYmVlRXeffddEokE1WpVf91kMtHX18eRI0daZmTYMmI5OTnJlStXeOedd/QJXuCuQzWj0aj/M5lMSCkpFov6cK/RaPDmm2+SSqV46qmniEQiytPYYwqFAsVikatXr2cbhO4AACAASURBVPLqq6/q4SDhcJhjx44RjUa37VlqiwCTk5Mkk8ldbrniflIoFMhms6ysrLCyskI6nd7UwRmNRkKhEL29vTsaeewmLSOWly9f5hvf+AZzc3P6sPuDVsCMRiMulwuj0YjNZtNjLiuVCplMhkwmw4svvsj3v/99DAYDv/ALv9AScx8PEplMhng8zttvv82f/MmfIITA5XLR09PDk08+STQa3fYij5SS+fl5Ll++zOLi4q7MgSr2hmw2y/z8vB5buXEIbjAYsFgs9Pb2MjIy0jIOTtPFUvM8tHCSjWECd/qSfD4fPp8Pj8eD3+/HYrFgs9moVqvMzs5SKBRYXFwkl8vpvdXq6ipTU1O43W4CgUDLGOAgI6VkeXmZmzdvsri4SLlcJhgM8vDDDzM0NITb7cZsNm/LFlqomCbGuVzuPnwCxf0im82ysLBAKpXa1MkZDAba29vx+/1YrdaWuk+bLpZLS0ssLCwwOTnJwsKCHkt5p61NBoOBQ4cO8eijjxKJRBgeHsZiseBwOPThXjwe58UXX2R8fFw/bnp6mh/+8IcMDg7ysY99TIWV7AFSSq5cucJLL73E2NgYpVKJrq4u/v7f//t0dnYSDAa3FTyuxVdqWyevXbtGo9FoiVg8xdaYn5/nzJkzxGKxTXazWq0cOnRoxwt/94OmiaUW3rG0tMSNGzdYXFykWCxSrVbf19NoISBOpxOz2Ux3dzcDAwOEw2EikQgmkwm73U6xWCSdTmM2m/X3ajdRKpViYmICs9nM0tISTqezZUISDhpSSgqFAuVyWd+qWigU9JR6gUCAtra2bSe8aDQaJJNJVldXyeVy1Go1fXRht9sxmUxNj8lT3J1isajbb+P9brVa6ezspKenp+VyPDRFLKWUZDIZcrkc3//+9/nOd77D6uoqy8vL7/MQDAYDXq8Xu93O0aNH6erq4sknn+TjH/84VqsVl8ule6HVapVQKMTy8jI//elPmZub02/a0dFR5ufneeihh3QP52Mf+xhut1sJ5i5Tr9cZGxtjYWGBM2fOcO7cOaxWK6FQiK6uLgYGBnaUHapSqfDTn/6U69evMzExAYDf76evr49oNIrL5cJutyvBbFGklKysrDA6OsrCwoJ+v2tZw5577jmGh4eJRCJNbulmmiaW2pbG1dVV5ufnKZVK1Go1vZcRQmCxWLBarQSDQdxuNz09PfT09NDV1UUwGNTTcmmYzWZ8Ph+1Wk1PqFCtVjcl2mhra2NqagqDwaDvIFFbIncXrTNcWVkhlUqRz+f1nVVutxu73Y7FYtnWubXkKisrK8zNzZHP5/VFo2AwiM/nU55lC6Pt4S8UCqTTaYrFoi6WBoNBv99DoVDL7e9v2jBci7MqFotkMpn3rWTa7Xb6+/sJBoN86UtfYnBwkGAwiMfjwev13nby12g06h7Lk08+SSAQ4Ec/+hGXLl2iXq9Tr9eZnJzk29/+NkePHuVDH/oQUkra29u3ffMq3k+tVmNsbIzz58/rK52RSISnn36ahx56aNvD73q9TiqVIplMcuHCBd566y2WlpYwGo0cPnyYz372s/T392Oz2dRooQWRUrK4uEgymdS3p27csWO1WnE4HHR1ddHT04PNZmtyizfTNLHU9grXajVqtZr+vMFgoNFoYDab8fv9dHR0cPToUR566CGcTuddexvNG5VS0tnZSalU4r333kMIoSfbyGQyZLNZPB4P+XyeSqWiFgZ2mUajQSqVYnFxkXw+T71e18OFQqHQtoVMi5/NZrPE43F9h5fBYMDn89Hf3084HFZC2aJIKcnn86RSKVKpFOl0Wn/NaDRiNpv1ee1WSPZ7K01fDb8Vu92O3++np6eHL3zhC/T09NDf368v2GwFbauU2+3m8uXLzMzMkEqlSCQS97n1DzZSSn374fz8PLFYTL8hurq6eOqpp/Rh8nYoFAqcO3dO3wmUy+VwuVz4fD56e3sZHh7G4XCoIXiLIqXU81SmUqlNr/l8Pj7ykY8wMDDQkkIJLSiWZrOZ9vZ2urq6OHnyJD09PXrM1VYxGAwEAgFsNhvhcBi/368n29DQvEnNw1XsHK1eUrlcJpVK6RmAANra2jh8+PCOSj5Uq1WmpqaYnJwklUpRLpdpb2/H6/USCATo6OhQQtnCSCn1banFYnHTa06nk8HBQfr7+1turlKjJcRy4wp4X18fv/qrv0p3dzfd3d243e5t32CaEG78p5HNZnnzzTdZWFjgmWeeabn5kf2KNhedz+fJZrO0tbURjUbp7Ozc8SKaNo2SSqWoVqsYDAbcbjfBYBCXy7VLn0Bxv9BC+Obm5vR4aoPBoDtIH/rQh+ju7sbhcDS5pbenJcRyo4j19fXxla98Zdc2z99OKLW8im+//TaLi4s8/vjjhEKhXbneg4w2L6ytduZyOQ4dOsTw8PB9EUsAl8ulF7ZStDaaWC4sLOg7rkwmEzabjUAgwKOPPkpHR0fLxVdqNEUsG42GXmhqdXX1vpx/eXlZXwSIx+MUCgX9dS3A/ciRI/p8qGLnCCEwmUxYLBY8Hg/t7e3U63WSySTZbJZSqYTFYrnnkYIWLpTL5ZidnWVqakpPBO12uwmHw3g8HhX+1aI0Gg3S6TS5XI6pqSnGx8f1+17bB66thLfynHNTxLJWqzE6OsqlS5eYn5/f9CPfjR98vV4nFosxOTnJ+Pg4s7Oz+h5xLYC9ra2Nn/3Zn6W/v5/29vYdX1PxN9EIdrtdz3CtJbtIJBJ6Jiin03lPdq7X6+RyORKJBFeuXOHq1at6ct9gMMjg4KCyYQtTq9WYm5tjeXmZixcvcubMGf1+1JLgOJ1OPd9Dq9K0oPTV1VWWlpYoFAo77km04V+9XqdcLpPP55mdnWViYoLV1dVNiTm0dG4WiwWLxbLtRA6K96PlH914A2i1cWZnZ7lw4QI+n49IJHLX8B6tllK9XtdrKqVSKWKxGIVCYVMqr421lhSti7bwV61WN4UKWiwW2tvb98XW46Z5lhMTE5w7d47l5eUdn69er+vDvIWFBRKJBK+88grvvffe+/Icmkwm3G63HopkNBqVWO4iWqxce3s7oVCIRCLB3NwcP/jBD5ienqa/v59nnnnmriue8XhczySUTCYpFAp6Yt94PK6/T7Ob2oHV2jQaDYrFIrlcblOCX1iLknj44YcZGBjYUaTEXtC01lUqFb2n2Y1zaZXgYrEYKysrevEj7fyaKLrdbrq6ugiHw9hsNlWn5T6gBYmHw2Hm5+f1XKOLi4tYLBYmJyfvumNqdXVVT7KwurpKqVQikUiQz+epVqub7GW32/F4PCqaoYXRgtG1LPYa2tqBtk211UcHrS3lW2RlZYXvfe97zM/P86Mf/YhEIkE8HtezpsNaYSuXy8WxY8f4/Oc/TyQS0ZMutLr7v98wm82cOnWKQ4cO4ff78Xq9LC0tMT09zcLCAhcvXvzA441Goz69oiVzrtVq77vZDh8+zDPPPKMnVFG0HpVKhatXr+rpEwF9UScajfLMM8/Q0dHRsvGVGvtaLLX6K6urq3rG5TuVGDAajdjtdnw+HwMDAwSDQT2dl2J30RK4ms1murq6mJ+fp1qtsrS0pO/vvttGALfbrYufyWTS0/nVarVNx2meSXt7u7Jji6JtaU4mk6ysrOibFLTUiy6Xi1AoRFtbm/Is7ydXrlzhu9/9LsvLy1y6dEnPYnI7tOJl0WiUw4cP4/F4VALg+4Qmlh6Ph1/8xV/kiSeeYGFhgampKT2P4d0Kig0MDBCNRnVPcWpqihdeeIGlpSWuXr26KSu60WhUVRxbFC0udnl5mQsXLnDmzBndkdG2NXd0dOjhe60+wmsJsbw149CtQeTajXWrN7KwsMC7776rJ224XfJgDS1FmM/no729vWUDXw8K2hyitrNGS62Xz+f1vKV34qGHHmJkZER/PDo6yoULFxBCMDY2tum9aiW8dWk0GpRKJXK5HEtLS8zNzemvaSFmLpdLzyLW6rSEWG4UwXQ6zfXr1/WytYVCgZ/85CcsLS3pYqgxMzPDpUuX9HyVWvjQ7YZ4x44d41d+5Vfo6upSHmUTcLlcdHV1UavV6OzsvOsw/NbdW2azmba2NrLZ7CbbaTux5ufncblcLR2j9yBSLpeZnZ1lZmZGH35rhMNhjh49Snd3977p7JoqlrdLYqHVVdGykqRSKb7zne9w7do1MpnMpp04tx57t6HYwMAAn/zkJ1ve1T+o2Gy2ba9YG43GTfOYG8nn8yQSCQwGgxLLFqNareplRTZWbwT0tYP9VDywKWJpNBrp7+/n+PHj+lyjxuLiIt/97nd1t7xUKjE7O0uxWNwUzAroeSq1v29FCEF3dzd+v1/VDD8AbMwUpaFlSFdbVlsPrbBcqVTSp13MZjMmk4m+vj4ef/xx+vr6lGd5N4xGI8PDwwghiMfj3LhxQ39tdnaWb33rW8DfCOCtK6C343bPm0wmBgYGOHr0KH19fUos9zF3GrZ7PB46Ojr2uDWKraAFo28M4bNardjtdgYHB/noRz+6r2olNUUstdXS7u5ufD4fdrtdDw/ZmK7tdpP3Gx9rBtCyLGtVHi0WC9FoVN8d0N/fT2dn5959QIVCoQ/DV1ZW9PhYrWy1zWbDarXuq5CvpnmWhw4dIhQK8eabb+JyuSiVSnomme2cz+VyYbPZiEQitLe385WvfIWjR4/qRbJsNpvyLPcxd5pmUTZtXYrFIjdu3GB8fFy/t10uF21tbXg8Hux2+75aQ2iKWAohsNlsNBoNIpEIhw8fJpPJ6JlpPiho+VasVqtelH1oaAi/309XVxd+vx+n07nvjKJ4PxsXA7URhxLK1kXbfZXP5/X1Bs1u2g6t/WbDpomlx+PB6XTyC7/wCwwODjI1NcW1a9eYmprixz/+8ftWz+5GIBDgueeeo6uri2eeeQa/34/b7cZisegG2U9GUWxGK1excYFPC0ZXnWDroQlluVzWc8pqIX8mk0n/t9+S2DRtwsBgMOhzl729vUgp9VjJcDhMoVCgXC7TaDSoVCp6xUetVvjGRAzhcJjOzk4ikQidnZ27lmVd0RrUajWy2Sz5fB4ppZ45yuVy7Ytg5gcZLWWfJoobO7n9JJTQAkHp4XAYn89HNBrl5MmTLCws8Nhjj7GyssLZs2dJJBJcv36dfD5PNBolHA4zMjLC8PAwsNaLtbW1cfToUdxut9qZcwBJpVK89dZbLCwsUK/X8fl8PPXUU0SjUQ4dOtTs5ilugzbV1tvbS61W03PXer1eOjo69mXNpKaLpdVqxWq16gHFTqeTSqXC4uIiy8vLWCwWlpaWEEIQCoXo6uri0KFDPPLII/oclsPhIBgMYrPZ1LDsAFKpVEgmk6TTaT30pLu7m8HBQRWI3oJo014mk0nfXmyz2fQtjg6HY1/uomu6WN6Kx+NhZGSEaDRKf3+/nlWoUqnoYUZ+v3/TUNtoNOJwOPQs6IqDhd1up6enh1AoxPHjxwkEAnzkIx8hEomoQnMtisFgoK2tjWeffZalpSVgLYZ6ZGSEzs5OfD5fk1t477ScslitVsLhMLBW6VGh0EqlCiE4ceIEkUiEI0eO4Pf7m900xV1wOBwMDw8TCoW4du0aNpuNzs5O/H7/vqzG2XJiqVDcSmdnJ88//zwAhw4dwuVy7cub7UFDi382mUw888wzpNNp3G43DoeDSCTS7ObdM0osFS1PMBjkU5/6VLObobhHDAaDXt721KlTzW7OjtkfmzIVCoWiySixVCgUii2gxFKhUCi2gBJLhUKh2AJKLBUKhWILiHvJ7vO+g4VYAaZ2rzktT5+UMtjsRuwVD6B9Qdn4QWBbNt6RWCoUCsWDghqGKxQKxRZQYqlQKBRbQImlQqFQbIG7iqUQwi+EeG/936IQYm7DY8vdjt0OQgirEOLPhBA3hRBvCyGiWzimvt6ey0KIbwshtr1pWAjx34QQX/iA9wghxH9eb+NFIcRj271eK7DXNt5w3c8LIaQQ4sQW3runNt7w3pNCiNpW39+qNOE+/rgQ4ty9fHdCiJgQ4tL6PfWyEGLbJTuFEP9WCPHPPuA9fiHEa0KInBDiv2zlvHcVSyllQkp5XEp5HPgj4A+0x1LKihBit/eW/0NgVUp5CPgD4N9v4ZjienseBirAr2988T608TlgaP3f/wb8f7t8/j2lCTZGCOEG/gnw9hYP2WsbI4Qwsvb7e3m3z73XNMHG08DfA/7HPR73tJTyGHAG+JcbX1h3UnZzJFwC/g1wV1HdyD1ffL1n/iMhxNvA79+q4uu9f3T9778rhHhnvQf72voP8G58Bvjv63//OfCz4t5yz/8YOCSE+IQQ4sdCiBeAq0IIoxDiPwgh3l3vub663j4hhPgvQojrQogfAFtJjvgZ4JtyjbcAnxDiQNXZvc82Bvi/WROi0jaatxc2BvjHwF8Ay9toY8tzP20spYxJKS8CjW027w3WbBxdt9s3gctAjxDin2+w8e9taO+/EkKMCSFOA8MfdAEpZV5KeZp7+A1uV6m7gVNSyt++0xuEEEeALwEfXe/R6sDfWX/t63cYfnUBMwBSyhqQBraUtHC9d3wOuLT+1GPAP5FSHmbNY01LKU8CJ4FfE0L0A59j7Yt9CPgV4NSG8/1fQohP362N68yuP3fQuC82FmvTFj1Syv91rw3aKxsLIbrWj9vXo4YtcL/u453yKf7GxkPAH0opj7JmxyHgw8Bx4PH1If/jwJfXn/ska/bX2v/rQohNI5Htsl33+9tSyvoHvOdngceBd9edQzvrvbSU8h9t87q3wy6EeG/97x8D32DthnhHSjm5/vzPA8c2zJ94WfvSPw58a/2zzAshfqidVEr5u7vYxv3Irtt4fRj1n1gbot0Le23j/wf4P6WUjXsb2Ow7Wuk+BnhNCFEHLgL/GvABU+sjOFiz8c8D59cfu1izsRv4KyllAWB9tMF6G/9otxq3XbHMb/i7xmYP1bb+vwD+u5TyX9zDeeeAHmB23YvwAokPOKa43uPprBt1YxsF8I+llC/d8r5P3kPbbm2jRvf6cweN+2FjN/Aw8KN1G3UALwghPi2lPHOX4/baxieA/7l+jQDwSSFETUr519s4Vytzv+7j7fK0lDKuPRBC+Hi/jf+dlPJrGw8SQvzTPWjbroQOxVgbDmlDrP71518FviCECK2/1i6E+KA6ES8Av7r+9xeAH0oppRCiSwjx6g7a+BLwvwshzOttOSyEcLI2N/Kl9fmuTuDpLZzrBeBX1ufCnmBt6Lewg7btB2Lsgo2llGkpZUBKGZVSRoG3gE9LKc+0ko2llP0b2vjnwG8cQKG8lRi7dx/fESHEtR208SXgHwghXOvn6lpv1xvAZ4UQdrG2ePjLO7jGHdkNsfwLoF0IcQX4TWAMQEp5lTVX+mUhxEXgFaAT7jrX8Q3AL4S4Cfw28Dvrz3ey1vNtl68DV4FzQojLwNdY86r/Crix/to3gTe1A+4yZ/k9YAK4Cfwx8Bs7aNd+YTdtfCdaycYPIrtmY7EWcjULPA98bf2cCCECrHmH20JK+TJrK+xvCiEusdaRuaWU54A/Ay4ALwLvbmjLHecshRAx1qeFhBCzQoiH7nb9fbE3XAjxm8C0lPKFD3yzYl+ibHzwEUJ8ChiQUv7nZrdlO+wLsVQoFIpmo7Y7KhQKxRZQYqlQKBRbQImlQqFQbIEd7QkNBAIyGo3uUlNan1gsRjweP9BRyht50OwLcPbs2fiDlCld2Xjr7Egso9EoZ87cLZb4YHHixP3Y2dW6PGj2BRBCPFAlFpSNt44ahisUCsUWUGKpUCgUW0CJpUKhUGwBJZYKhUKxBZRYKhQKxRZQYqlQKBRbYNdrlygUCsVOqNVqNBoNyuUy9fr7cxMbjUasViulUon5+XlqtRpOpxOTyYTNZsNsNmO327FarbvaLiWWCoWiZWg0GhSLRarVKslkkmKx+L73OBwO2tvbWVlZ4ZVXXqFYLBKJRHC73YRCIdxuN+FwmGBwd/cWtIxYNhoN6vU6uVyOubm1xOMOhwOz2YzP58NisWA2mzEYdjZzIKXUr1UoFAD0XumAlxBQKFqOSqVCPp+nWq2Sy+WoVCrE43HK5TLxePy2Yul0OgkEAiSTSW7evEmpVCKTyWCz2Whvb8fpdPLYY48dXLHUvrQLFy7wzW9+E4CBgQHa2to4deoUHR0dtLW14XBsu2Q0APV6nVKpRDab5ebNmwghOHLkCF6vF6PRqARTodhDEokE169fJx6Pc+nSJVKpFNevXyeTybC0tKQ7NBvRPMdKpcLc3BzVahUt1aTBYMBkMvE7v/M7PPLII7va1qaLpZQSKSXpdJq5uTmmpqaYnp5GCIHL5UJKSa1W2xURazQa5PN55ufnyWQyTE1NYTQa6e3txel0IoTAaNxKJVfFbqB5+blcjmq1qs9Vud1u3G53s5un2EXq9fqmIXa5XKZcLrOwsMDk5CTxeJxYLEY6nWZ2dpZsNksikbitWGq/l3q9TiqVolarbRJMo9FIPp9/33E7peliWalUqFQqvPrqq3zjG98gmUwyOzuLy+XSvT2Hw0EgEMBk2n5zq9UqlUqFM2fO8Md//MekUilWVlbw+/34/X4MBgPt7e079lwVW0ObwM9ms7z88svMzs6ysrJCPp/nl37pl3juuecwGAw7nnZRNJ9Go8Hq6ir5fJ5z584Ri8UYHR3l+vXrFItFstkslUqFQqFArVajWCxSr9ep1W5fZaRUKrG4uAj8zWLQXiQxb6pYSikpFovk83lmZ2e5fPkylUqFarWKzWbDaDRiNBqxWCxYLJYdXatarZLP51leXubKlStkMhkqlYpunI09k+L+oY0UarUamUyG1dVVYrEYExMTLC4ukslkOHHiBI1GQ02JHBCklJTLZQqFAnNzc9y4cYNLly5x4cIFGo3Glu89IQQGgwEhxCYv8tbR4P0aITZNLIvFIpVKhddee413332X8+fPk8lkCAQCPPTQQ/T29vL5z3+ejo4OIpHIjq83Pj6uX2dxcRGXy8Vzzz1HT08PQ0NDhEKhXQ81ULyfZDLJ2NgYS0tLvP7666ysrDA6Osrq6iqlUol6vc7i4iLFYhGLxYLdbm92kxU7pNFo6MPqc+fOcfr0aVKpFNVq9Z68QpfLhcfjwel00tbWdsfO1Gg00tHRsZsfAWiSWEopqVarlEolxsfHeeutt5idnaVSqWCxWIhGowwNDfH444/v2opWIpFgdHSUqakpcrkcPp+PkZER+vr6CAQCOJ3OXbmO4u4UCgWmp6eJxWL86Ec/YmVlhUQiQblcBta8Am1VVA3B9xe3ip4mZhs9y4WFBW7evHnb4zeK30bba8/b7XZ8Ph9er5dIJHLH34fBYMDj8ezos9yOpollMpkkmUwyNTXF+Pg42WwWKSWhUIhPfOITdHV17cr8YSaToVAocPXqVd544w2q1SqHDx9mYGCAY8eO0dXVpYRyD6hUKhSLRSYmJvje977H4uIii4uL5PP5TYHHUkquXbvGX//1XzM4OMjJkyexWCzK629htKmzubk5JiYmsNvtBINBHA4HXV1dwJqAaVNqNpsNk8mE0WjUh+FOp5POzk5sNhs+nw+r1Yrf78fhcOD1enE6nTidTlwuF3a7Ha/Xe9dpmiNHjuz652yKWDYaDVKpFEtLS8zNzTEzM6O/1tbWxsmTJwkEAthsth1fK5/Pk0gkmJyc5MyZM3R2dvLYY48xNDTE8PAwoVBIDfX2gEqlQi6XY2Zmhh//+Mesrq6SyWRoNBrAZq9icnKS1157jWKxyNGjRwGwWCxqDrNFqVarFItFpqen+elPf0pbWxtDQ0O0t7cTCoX0GGaj0YjJZMJqterrENVqVfcEBwcH8Xg89PT04HK5GBwcpK2tje7ubgKBAGazGZPJpJ9jr9lTsZRSUqlUKJVKzM7O6qECAL29vQwNDfHYY4/hdruxWq3bHoZJKcnlcpTLZd5++20uX77M5cuXkVLicrno7++nu7sbu92O2WxWN+EesLKywpUrV7h58yaFQoFyuXzHuSot9q5er1OtVgkEAoyMjOB2u+nr68Nut6shegtQr9ep1+tcuHCB0dFRbty4wcWLF4lGo/T19ekdodFoJBAIYLVaefrppwmHw9jtdpxOpx4R4fF4GBgYwG6309bWhtVqJRgM6kNvzeZGo7Fptt9zsSwUCuRyOcbHx7l69SrxeByAoaEhnn/+eQYGBnQ3fLtooQqpVIqXXnqJ7373u+RyOaSUeL1ejh49qvdeO11lV2yN2dlZXn/9dW7cuEE6nb6rWM7Pz7OwsMDo6Cg//OEPiUajfOYzn6G7u5u2tjbdy1SdXHOp1WpUKhVOnz7Nt7/9bVZWVpifn+fxxx/nYx/7mL54oy24hEIhnn/+eX3NwOv1ks/nWV1dxWKx4Pf7N4mhZt9WsfOeimWlUmFiYoKVlRVu3rxJLBajUqng9XoJBoP09PQQCAR2vOwvpSSTyZBIJEin0+TzeWw2G16vl+7ubnp6egiHwzuK21RsDS3YPJFIEIvFWFpa0m8gzVvQvPtsNqsv9GghRqVSiVQqxfj4uB7+5fV6dS9DsfdothkfH2dlZYXJyUkSiQRms5n+/n6i0SihUAifz7fJRgaDAbvdjhBCn7e02Wy4XC59iK2FBrUie6oW2WyWl156iRs3bnD69GlmZmYIhUL09fVx5MgRTp48id1u3/FNUK/XmZ+fZ3JyksXFRdLpNCMjIxw/fpwPf/jDnDp1St8Prri/5PN5stksY2NjnD59mkKhQLVaxWq10tHRgd1ux+PxYDQauX79OktLS/qxWjzm3Nwcr776KgMDAzz77LN4vV59gUCx92h5FV588UXOnDnDhQsXmJ2d5dFHH+XJJ5/kyJEjPPLII7cdubndblwuly6I2vwltI4HeSf2fBheKpX0Oatyuaz3NjabDavVuu05RK23S6fTZLNZZmZmmJmZ0VfZ29vb/3r10QAAF+dJREFUGRoaoqurS+/VFPcfbc9/oVCgWCzSaDRwOp14vV6Gh4dxu936VtNKpYLVaiWfz5PL5fSV0nq9TjabJZVKMT09jcViYXBwEJ/P19KeyEGj0WhQq9VIJpOkUinm5uaYn5/XtyS63W56e3sJh8N6qrRbbXO76ZP9Yr89Vwzty9L+aRO6mqe3nclbLW5zdXWVl19+WfdE1ut8A3D8+HG++tWv4nQ61TzlHqGFiMViMZaXlykWizidTvr6+hgeHua3fuu36Ozs1Le2nTlzhlgsxrvvvsu5c+fIZrOsrq7qO61isRhf//rX6erq4td+7dd49NFHsdvtyp57gLY9NZ1O88orrzAzM8Pp06e5du0aRqMRt9vNQw89xC//8i/r3uNB68ia6l5p25ZqtRqFQoFkMqnPXWgJPu/2ZWs9nbZlMR6P6x7l4uIi8Xicer2uD/U6OjrUKuoeo807ars1LBYLgUCAUChET08PkUiEavX/b+/cY9u8ssT+O3xJlEjxJVKkqLcl2ZtYnozzcBLPZBzbWSADTyaZ2SAFul0M2i46nX11ii2KbRdFOwU66HZRFINFOwtMO50FinaxWexOimImM5nZZDxJdhM/8pJjx7KtN0WKoknqRYmibv8gvxvJ8YN2LFGU7w8QTJrf45Dn+8537r3nUaRYLDI7OwvA2NgYbrdbz1/CxzdrOp3GbrdTKBS2LSfY8HGdyfn5eaamphgfHyeXy1EoFGhtbdVhQsFgUKcq7zZqnhs+NTWlq4uMjY3hdDppamrC7/fz0EMP4fF4bri/VXQjl8tx5coVstks77zzDrlcTnskvb29xGIxuru7t/GbGSwsr9EKPG9ra+Opp56iu7tbJwNYD8f77ruP3t5e0uk0Fy5cACCVSmmDKCI6xs6KtzMPv+1hfn6e9957j4mJCX70ox8xNjbG6uoqra2tPP/88xw9epTe3l48Hs+uNJSwzcZyY2CqdZEvLi6yuLjI6OgoIoLT6aS5uZlwOEw0GsXn893weMlkkpGRETKZDOfPnyefz3P58mU9h+JwOGhpaaG9vZ2WlpZdNSSoF6xYSSvmrrGxkWg0Sjgc1jeVNSVjhZNYoWNWsWdrX2vl3DKuu22Yt5MpFouk02mSyaQevYXDYbxeL729vdqxcTqdtRZ1y9hWY+l2u3n44YeJxWJMTk6SzWYpFAqsrKyQzWZ1MV4rpODy5cs3nY9aXl4mn8/ruRSr3JuI0NLSgtvt5tFHH+Xzn/88e/fu3cZvaoDyyGF8fJy3336b8fFxoJx+eu7cOQqFAg888MB198tms4yNjZHNZrWhBHA6ncTjcbq6uvD5fDQ0NOxaL2anUSgUdK3Z1dVV7HY74XCYcDhMJBIhEAjsakMJ22wsrTgsj8dDKBSiubmZUqmkk+wtj9Aadl28ePGWnsPGIZqFFcPn8/no6+vj4MGD+P1+44XUgEwmo+Pw1tfXdZOp5ubm69YrtBIX5ubmKBQKm+YkbTYbfr+fUCiE2+02EQ3bSLFYZG5ujnQ6TbFY1MW5A4EAXq/3nqgDu61Xm8PhoLW1FbfbzXPPPceDDz5IOp0mm82SzWZJp9Ok02lGRkYolUo0NDTQ0NBAT0/Pdecug8Eg8XicRCLBK6+8oqsj22w2IpGI/gsEAnclz9xwe4gIsViMoaEhCoWC9igTiQQej4dUKgWgM3oSiQTZbJb333+f5eVllFI0NjbqxZ2VlRU+/PBDstksjz76KKFQCI/HY3S7DSwtLXHhwgUmJyf14loikWBpaYnTp0/j9XoJBAJEIhFdDGO3OSfbaiytHNFQKMSzzz7L6uoq09PTzM7OMjo6yoULF/joo4+4cuUKgF7FPnDgwHXr0+3Zs4dDhw5x+vRpXn/99U3GMhQK0dHRoY2loTbEYjH279/PxMQEIqKrXHs8Hh3WNTExQS6X45133mF8fJzh4WEKhYKejimVSrpq0fnz55mZmWFiYoKOjg7sdrsxltvA0tISly5dYnx8XFcyTyQSpNNpTp8+jYjQ19fH/fffTyAQ0IkGu4majGOshRwRIRAI4HA4cDqdeL1eOjo6CIfDrK+v62D1wcHB6y70WHnCllLsdjsejwev18v+/fvZu3cvbW1t2/31DBVERNcetHRlVZwaGxvjxz/+MR6PR7c8HRsb4+rVqxSLRWKxGNFolL179zI3N8fp06d1H+lCocDo6KheCDIPw63HmkJZXV3VUyNW2N/k5CQOh0NnzUUiEfbv36+dHZvNtmmk4HQ6aWxspLGxUXufxWKRpaUlXYHI6XRuurd3AjWb9LGG2E1NTSilGBgY0M3LrDAT64e80arn4uIimUxG/6AOh4O2tjYikQhHjx7lkUceuelqumHrsfo4x+Nx3G639ixnZmY4d+7cphYB1mJOd3c3AwMDHDp0iBdeeIEPP/yQubk5UqmUTl89e/YsuVyOcDhMX19fLb/iPUGpVNKRK1C+N6055w8++IBz587p+7Snp4cjR44QCoXYs2cPDoeDTCajK0h5vV69OGSxuLjI1NQUTqeT/v5+PB4PwWDQGMuNXC/9qdpVNSs2M5lMUiqVcLlcdHV1EY/HdfMxswhQW6y4yLa2Nvbv36/npNfW1jYFnVujDI/Hw8DAAPfffz+Dg4MEAgEd8Ly2tqYXGLLZLKlUilwux/Lysg4pMmwNDQ0NtLe3UyqVyGQyrK6u6s+sUm1Q1mM+n2d8fFxHuzgcDnK5HGtraySTSR1HvdGRKRQKpNNpHA4H2WyW5uZmotEoHo+HaDRKMBjc9u98LXV9dY2NjfHDH/6Q0dFRVlZWCAQCPP300wwMDNDf329iK3cAVqGEQ4cO0dTUxKlTp/j+97/P/Pw8pVJJe5UOh4OhoSEGBgY4evQoR44cwe124/F4WF5e5uDBg7S2tjIxMcHS0pJeYT98+DCpVIqWlhYzHN9CgsEgx44dY3x8nJ/+9Kc62+palFKkUileffXVTZWhrFGj5X1eW5fSGtI7HA4CgQBut5vBwUFaW1t54YUX+MIXvrAt3/Nm1KWxXF1dZWVlhUwmw/T0tF4ocDgceL1efD6fqay9gxARvF4v7e3tdHZ20tHRQTabJZPJUCqVEBHtuXR3d2tPwkpgaGpqIhaLUSwW8fl8rKysbEqRTSaT2Gw2Yyy3kIaGBjo7O7HZbPT09OB2u7XnCB/3gLcytm7UxvZW2O12XZWqqamJQqFAMplkbm4Ot9td0xClujSWExMTXL58mV/+8pe89tprrKys6Bp5Ho8Hj8djhmQ7DCvMxxpqz87OcurUKZaXl/VC3okTJzhw4ADBYHDTwy4cDnPixAkmJyeZmpriypUrXLx4kWQyyRtvvMHCwgJPPPEEHR0d5gG5RUQiEZ577jkWFhY4dOgQs7OzvPjiiwwPD+sc/Y3Vou40Z9+aG11aWmJ4eJiGhgZaW1vJ5XIcOHCARx55pGY6rkuLsrS0xOzsLJlMhqtXr6KUorm5eVOZN5MzvLNwOp04nU5aW1t1r5V0Os3i4iJNTU00NjYSj8eJxWKfGBW4XC7C4TDFYpFIJEI+n2dkZITV1VVdH8Dq57OTFgR2Ey6Xi0gkgs/no1Qq6dA8q1jN+vq6LnxjDbnX19dZXV3VBW+qxdrW6u2TSqWYmpqip6dni75dddSlsZyZmeG9995jfHyc9fV1HSrU29vLnj17dJ8Ww87D6/Wyb98+ent7GRgYoFQq6fkrqw7itQ86Kyfcirn1+Xy6UPDMzAzFYpEHHniAhYUFGhoaTNzlFmGz2WhoaCAejxMOh/nGN75BLpfTxnFmZoaxsTE9HM9kMrz++uvMzc2RTCZ1ht7toJTSVfa3omPj7VCXxnJhYYFkMsn8/DyAXm2NRqM6/cqwM3G5XHplMxaLVb2fzWbD5XLR1tamW6fabDbdW8mqEWDd0GY4vjXYbDadTXftCvXk5KSuT2p1K7h48SKlUom5ublN24qIXuy51hvdOIS3SsNZ5eCUUmYYXi1KKWZnZ3XsncPhIBwOc/jwYbq6um5a0s1Q3zQ2NrJv3z5aW1v57Gc/C5QrT2WzWS5evMjJkyfp7Ozk4MGDZs66Bvj9/k3x0n6/n6GhIfx+P4lEgnw+r42k1QsrHA7T399PLpdjeHiYfD7PpUuX7sgL3Wrq8orK5XK6np7dbsfv97N//37a29vNEGwX43Q66ezsxO/309/fTz6fJ5/PMzk5yfT0NO+//z5KKT7zmc8YY1kDrMVVC5fLRW9vr+6IAGXP1Jpyue+++xgcHORzn/sc09PTKKVIJBI6PGynUTdXlFKKiYkJMpnMph/TKhYcDocJhUK7vkzUvY6VKrt3717sdjuJRIIrV64wPT3Nm2++iVKKxx9/XPf2MQt9tcPlculAdstYWllaiURCB7Cvr6/rvvIbw5EsrCiXWk+v1I2xLJVKXLp0SRfayOfzNDY20tLSQnNzM7FYjEgkUmsxDduAy+XSI4mzZ8/y1ltvMTU1xejoKHa7nWeffVbfoMZY1g6rYpjD4dDG0kpnnpiYYHJyksnJSWZmZpifn2d4ePgT/eRtNptuY13rUWPdXElKKV0Z3ZosbmpqIhqN6ubs8HEbg0KhwPLy8h0Hxxp2LlaQezAYpKenh6GhISKRCEopstksw8PDjIyM6G6ShtpgNTLz+/3EYjE6Ojp0KxFAx2bOzs4yNze3KaPLbrcTCoVob29ncHCQAwcO3NaC4FZQV57l+fPnefXVV7ULHwwGGRoa0sn6SildmWZpaYm1tTX8fr+Zv9pl2Gw2wuEwgUCAw4cP09TUxMmTJ3XQ+ksvvcTevXsZGBjA5XKZbK4a4XQ6iUQi2O12Dhw4gN1u5+zZs7oYB5TXH6yIBiu/3G6343Q62bNnD9FolKeeeopjx45tqlJUC+rKiqytrbG6uqp/VJvNhsPhYH19natXr7K0tEQymdy0jd1u3/Q0M+wOrPxiqwB0KBTStS+TySTBYJDFxUW8Xq/u2WPYXiwdNTY20tHRwfLyMolEQhfV2BiwbqW8OhwOfD4fzc3NDA4O0tHRQVtb244oilNXxvJarDCEfD7PW2+9xfLyMj//+c/JZrO0tbXh8Xj4yle+ct3CwYb6x2az0d/fTyQSIZFI8MYbb7C8vMyZM2dYWVlhcnISu92Oy+UySQo1QERwuVz4fD6efvppHnvsMVwuF01NTaRSKVKpFIVCgYWFBVwuF6FQiJaWFg4dOkQ0GuVLX/qSLtdW68UdqHNjWSwWWVxc5OrVq4yPj1MoFJidnWVhYQG/329iLu8B3G43IkI4HKazs5NUKkU6nWZhYYFMJkNLS4spAF1jrPA+l8tFPB6nu7sbu92up8tsNhtut5t4PE4gENDFVNrb23fUom1dG8tEIsFrr72mK9O43W76+vqIRqMcP36c3t5eent7ay2mYQtpbGzE5XJx5MgR4vE4v/jFL/jOd75DJpPhlVdeoaenRxcgNtQGK+vH6r117Ngxzp07pxNLJicnaW9v5/jx43oxyO12EwqFai36JurKWFrl6K1Cr6VSiWw2q+O1fD4fQ0NDtLa20tHRQVdXl7lJdjlWkHMkEqGhoYHx8XGcTielUompqSnsdrteFTdhRLXDbrdjt9uJx+PE43HdT97v92Oz2eju7mZoaAifz7dj+/fUjbF0OBw89thj+Hw+zpw5w5kzZ2hpaSEajRIOhxkaGsLr9eqUx66uLt3Lw7D7cbvd2O122tvb2bdvHwsLC4yMjOiq3VZxYDN3uTPo6OjA6/VSKBRYXFykubmZcDi8oyuG1Y2x3Fh0dH5+nqmpKdra2hgYGKCzs5Pjx4/j8Xhobm7G4XDgcDhqPiFs2D4snft8PmKxGIlEggsXLlAsFslkMuTzeT0UNNQev9+P3++vtRi3Rd0YSxHRPceffPJJ+vv7aW5u1m03re6B1pPJGMp7k66uLp5//nlGRkbIZrPY7Xa92LPT5sAM9UVdGctgMEgwGKSzs7PW4hh2KPF4nBMnTvDuu+/y8ssv646E2WyWYrFYa/EMdUzdGEuDoRqsupexWIwvf/nLrKys6HTIWvZvMdQ/xlgadhVW8d++vj6++c1vopTCbrdft+WywXA7GGNp2JWISM3T4wy7i525Rm8wGAw7DGMsDQaDoQrkTvv7AojILDB298TZ8XQrpcK1FmK7uAf1C0bH9wJ3pONPZSwNBoPhXsEMww0Gg6EKjLE0GAyGKjDG0mAwGKrgpsZSREIi8k7lb0ZEpja8d22VUCLyVRFRIvJQFduWKvJ8ICJ/ISJ3nKYhIv9TRH6tym0fFpG1arffqWy3jkWkW0R+JiLvicirItJRxT6jIvJ+ZZ+fiMgdl74XkX8rIr9/i21cIvL9yjnfFZEjd3q+nUANdPw1EZndcI5/XMU+263jHhFZ3iDjd2913JtG7Sql5oAHLAGABaXUH284oUMpdVfbJ4qIF/g94O+q3GVZKWXJ+L+ArwP/eYtltAP/EfjJ3TxuLaiBjv8Y+DOl1A9E5CjwbeAfVLHfk0qptIj8B+BfAb+7QUahvFh5t1o5/iaAUmpIRCLAj0Tk4bt4/G2lFvcx8OdKqd++zX22U8cAlyzbUQ23PQyveF/fFZG/A/7oWite8fB6Kq9/XUTeqljuP60YmVvx7ykbosKtNrwOJ4F+ETkiIidF5CXgnIjYReQ/icjblSfXP6nIJyLyJyJyQUReAaqtYf87wF8CqTuQccezxTq+D/h55fXfAF++TfF+QVnHPRW9/RnwAdApIv9ig47/3QZ5/7WIfCQivwT2VnEOLaNSKgVkgVuOcuqJbbiPPw3boePb5k7nLDuAx5VS//xGG4jIrwAvAIcr1rsE/P3KZ9+T6wyxReQg0KmU+n+3K5CIOICngfcr/3UQ+D2l1CDwj4CcUuph4GHgN0WkF3iO8g97H/AbwOMbjvctEXnmOueJV/b7b7crY52xJToG3gW+Unn9HOAVkdupnXaCj3U8APxXpdT9lPU4ADxC2Yt6UESeEJEHgb9X+b8vUta/Jf/XReTrN5DxGRFxVK6TB4HdWOpqq3QM8NWKQXtRRG73t9sOHQP0ishZEXlNRD5/K6HuNHn2L5RSpVtsc4zyRfZ22YPGTcUTU0p9Yg5DRGyUh89fu01Z3CLyTuX1SeC/UzZ6bymlrlT+/1eBA/Lx/KKP8o/+BPC/K99lWkQsjwel1L+5wfn+C/AvlVLrsrsLM9x1HVf4feBPRORrlD2IKco34K34GxEpAe8Bfwj4gTGl1N9WPv/Vyt/ZynsPZR17gb9SSi0BVEYbVGS80TzV/wB+BThFOWD7jSplrDe2Ssf/l/J9tVIZxf0AOFqFPNup4wTQpZSaqxjbvxaR+5VS+RsJd6fGcnHD6zU2e6iNlX8F+IFS6g+qPKYX2A+8WlFKFHhJRJ5RSp26yX56ztKisv9GGQX4HaXUy9ds98UqZdvIQ8D/qZyjFfiiiKwppf76Do61k9kKHaOUmqbiWYqIB/iqUipbxa5PKqXS1hsR8fNJHX9bKfWnG3cSkX9WrWwbZFwDvrnhGG8AH93uceqArdLx3Ia33wP+qMpdt1PHK8BK5fVpEbkEDFJ+QF6XuxE6NEp5yGsNo612ij8Dfk3KE+SISFBEum8ifE4p1aqU6lFK9QB/CzyjlDolInER+dmnkPFl4J+KiLMiy6CINFP2bF6Q8pxmDHjyVgdSSvVukPFF4Bu70FBeyyh3QceVbVorowiAP6DsxVmfnf8UMr4M/MOKAaZyzUQo6/hZEXFLefHwS7c6kIg0Va4PROQpYE0pde5TyFYPjHL3dBzb8PYZ4MMNn+0UHYetuVcR6aPsoV6+2T53o4bVXwK/ISLDlFewPwJQSp0TkT8EflK5OYrAbwFjIvI94Lu38Bg3EqP85LtTvgf0AGek7BLOAs8Cf0V5eHAOGAfetHYQkW8Bp5RSL33iaPced1PHR4Bvi4iifJH/FpSNKGXP4Y5QSv2kMr/2ZsXrXwB+XSl1RkT+nPI8ZAp429rHmsu6zlAtArwsIuuUpwmqWa2vd+6mjn+3Mt+/BmSoTK3tMB0/AXxLRIrAOvB1pVTmZuevi9xwEfltYNwYrt2LiJwA+pRS36m1LIatod51XBfG0mAwGGqNSXc0GAyGKjDG0mAwGKrAGEuDwWCoAmMsDQaDoQqMsTQYDIYqMMbSYDAYquD/A3+wtU+cAfewAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fab423855c0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -708,9 +698,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fab42330208>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -841,14 +831,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch 1/1\n",
-      "55000/55000 [==============================] - 2s 37us/step - loss: 0.1958 - acc: 0.9394\n"
+      "Train on 55000 samples\n",
+      "55000/55000 [==============================] - 16s 298us/sample - loss: 0.1977 - accuracy: 0.9389\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras.callbacks.History at 0x7faac4a441d0>"
+       "<tensorflow.python.keras.callbacks.History at 0x7f81307d4710>"
       ]
      },
      "execution_count": 30,
@@ -880,7 +870,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "10000/10000 [==============================] - 0s 36us/step\n"
+      "10000/10000 [==============================] - 2s 169us/sample - loss: 0.0563 - accuracy: 0.9809\n"
      ]
     }
    ],
@@ -907,8 +897,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss 0.061494892170466484\n",
-      "acc 0.9811\n"
+      "loss 0.05628199413705152\n",
+      "accuracy 0.9809\n"
      ]
     }
    ],
@@ -933,7 +923,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "acc: 98.11%\n"
+      "accuracy: 98.09%\n"
      ]
     }
    ],
@@ -991,9 +981,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faae86bb080>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1163,9 +1153,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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RhkIhOjs7VVjXAaXRaOgepZYsRQiBy+XC6XTqSb1bnX3tWc7MzPDGG28wOjrKjRs3KJfLDAwMEA6HGRkZ4fDhwy27G+BBQErJlStXOHfuHG+++Sbj4+NUKhVqtRput5ujR4/S2dnJpz/9aYaHhwkGg81usuI+UKlUeO+995iamiIWi5HNZunu7mZoaIhwOLxvOsh9KZaNRoN6vU46nWZ6eprFxUW9t/L5fIRCIX0OTNE8tJIg09PTrKysUCgU9OG3xWIhFArR1dVFZ2envg1VcfDQEjxrdbeq1SoGgwGXy9Wyu3Vux74Uy8XFRebm5jh9+jQvvPACmUwGWFtZ+7mf+zkGBwdVTGULIKXk2rVrfP/732d1dXVTlcb29nY+97nPMTAwQE9Pj0pscoCp1+ukUqlNmaW0lGwWi0V5lveTbDbLwsIC09PTjI2NIaXUs2pHo1EGBwdVbZ0WIZFIMDk5+b5ytna7naGhIQ4dOoTb7d71RTgtYcPdKkMaDIZ9c6PuZ6SUlMvlTYl+taoG+2GuUmNfiWW5XKZWq/Hee+/x4osvcvPmTer1Ok6nk6GhIaLRKAMDA3oCBkXr0mg0KBaL5PN5zGbzHbPfw9qNpXkgmveplSG5ta54rVajUqmQTqe5cuWKHvy8Ea0CaH9/P8eOHdMrTyruD7VajVgsxujoKKlUCoBwOMzDDz9MV1fXvumw9tUvpFqtUiqVmJiY4I033tiU2Le7u5uenh46OzvVQsE+oNFoUC6X9dCiWz3PjWilQgwGgy6WG2s1bSyLXK1WyefzLCws8NZbb92xCqhWJnlkZASLxaLE8j5Sq9WYn59namqKbDarry1Eo1H8fr8Sy91ESkmtVuOdd95hbGyMc+fOkU6nkVLi9Xrp6uriIx/5CL29vWr4vU9IJBL8xV/8BX6//wMD0V0uF729vXr2KIPBoC8WaQlkNbSqgel0mmvXrul7zzeiCa7ZbKarq4tgMMjw8PC+GhLuB6rVKslkkvn5eT1k6G6dYquzb8SyUqnwxhtv8OKLLzI3N0cymcTj8eD3+4lGozz99NOEw2Hcbnezm6vYAktLS3zzm9/c0nuDwSBPPPEELpdL35GVTqcplUqcP3+emzdv3vY4rfDZnajVarS1tXH48GEGBweVWO4ylUqF2dlZZmZmSCQSm+Ys9yMtL5ZaVmUtEYMWfgBrK6qPPvoow8PDeuIMtaLaWng8Hjo6OshkMvp8lcZWb5xiscjs7Cw2mw2n04kQgmKxqHuQG7dOamhDdqPRSFtbGxaLBYfDsSlUZWBggGAwiMfj2TdDwf1EpVJhYWGBhYUFKpWKvsXRbDbrFTvdbve++e5bXiwbjQapVIrV1VVmZ2eJxWL6Cmd/fz/PP/88XV1ddHd3Y7PZ9s0X/yAghKCzs5Njx44xOTmpT53cK5lMhgsXLui2FUJsqjGvPaflANj4G7Db7YyMjBAIBOjp6dmU+i0SiTA0NER7e7uas7wPFAoFrl27xsTEhB7ep5U2Hhwc5PDhw/sqb0PL/kK0ecpiscjk5CQLCwv6Bnyfz6fXaeno6NB/7PvlS3+Q6Ojo4KGHHsJkMpHL5e4YzqOtbGs217JHbXzNZDLhdrv1kJONowi73Y7T6cRkMm3yHm02GyMjI/h8Pjo7OzdN0wQCAX1Eon47u4u2+JZMJlldXaVSqQBrKdk0j3K/ZcFvWbGs1Wokk0mWl5f5r//1v3L58mW9UuOxY8f46Ec/yqOPPsqJEyfUamaLYjAY+MQnPsGHP/xhzp8/z+uvv64nP7kVKSXLy8tkMhnGxsYYGxt733scDgcnT57UvZONotjf38/w8DBut5tQKKQLqRZ2pIUHbRRYo9Goi65KtrJ7NBqNTeFbExMT5PN5jEYjg4ODHDt2jO7u7n03ZdayClOv18lkMiSTSRYXF5mdndXnKt1uN5FIhEAggMPhUELZwrhcLlwuF5FIhGg0Sr1ev+1cZaPRwOFwkMlk9JCiW/F4PESjUV0sN+a9jEajRKPR94mlonloolmpVDCZTDidTvx+P+FweF8m425Zlclms7z55ptMT08Ti8VIJpNUq1WEEASDQY4cOUIkElE3xT5hYGAAv9+vD8FvNxSvVCp6QbONw3ANo9GI1+vFbDa/z0u02+16JUj1m2gu2vyx2WzGbrfj8/kIBoNYrVaefvppTp06RXt7e7Obec+0pFhqCX0XFhb0kraapyGEwGq14vV6VfGxfYTT6VQxsA8QmmC63W68Xi9ut1sfYUQikX0ZptVyYpnL5VhYWGB8fJzXX3+d2dnZ94WcKBSK1kUTyq6uLr761a9SLBb10cDAwAAWi2Vfev8tJ5ZaWduFhQUmJiaYnZ297f5ehULRuggh8Hg8nDp1qtlN2TVaTiyLxSIzMzPMzc1RKBSoVqv6/JbL5cJms+F2u9UKuEKh2FNaTm2KxSJzc3N6rRYtPmtjYSstD54SS4VCsVe0vNoYDAbcbjc2m41Tp05x6NAhjh8/js/nUzVbFArFntHyYmk0GvH7/QQCAf7W3/pbPPvss7hcLiWUCoViT2k5sXQ6nUSjUaxWK8888wyFQoFgMIjX66Wnp0ffiK+EUqFQ7CUtJ5bhcJhf/MVfpNFo8KUvfUkvmyqEwG6376uaHQqF4uDQcmJpNBr1Wt8qiFmhULQKYjsps/SDhVgBpnavOS1Pn5TygalZ8QDaF5SNHwS2ZeMdiaVCoVA8KOy/PUcKhULRBJRYKhQKxRZQYqlQKBRb4K5iKYTwCyHeW/+3KISY2/DYstuNEUL8wYbzjwkhPjDdkBAiJoS4JIS4KIR4WQjRsYPr/1shxD/7gPf8nQ1tfE8I0RBCHN/uNZtNE2z820KIq+v2elUI0beFY/baxs8KIc6uX/OsEOKZ7V6vFWiCjT8uhDgnhKgJIb6wxWP22sZ+IcRrQoicEOK/bOW8dxVLKWVCSnlcSnkc+CPgD7THUsqKEGJXQ4+klL+14Xr/L/CXWzz0aSnlMeAM8C83viDW2DUPWkr5pxva+BVgUkr53m6df6/ZaxsD54ET6/b6c+D3t3jcntkYiAO/LKV8BPhV4E928dx7ThNsPA38PeB/3ONxe2njEvBvgLuK6kbu+eJCiP8mhPgjIcTbwO/fquJCiMtCiOj6339XCPHOeg/2NSHEvRQ6+dvAt+6xeW8Ah4QQUSHEdSHEN4HLQI8Q4p8LId5d77l+b0N7/9W6F3saGL7H6/1t4H/e4zEtz/20sZTyNSmllgb9LaD7Hpt3320spTwvpZxff3gFsAshrHc7Zr9xn20ck1JeBO5euP3O7IWN81LK06yJ5pbYrlJ3A6eklL99pzcIIY4AXwI+ut6j1YG/s/7a14UQJ+5ybB/QD/zwHtv1KeDS+t9DwB9KKY+y9uUNAR8GjgOPrw8VHge+vP7cJ4GTG9rw60KIX/+A632Jexf0/cJ9tfE6/xB48R7btdc2/jxwTkr5/qJA+5+9sPF22Gsbb4ntut/fllK+v+rUZn4WeBx4V6xtT7QDywBSyn/0Acd+GfjzLVxD4zUhRB24CPxrwAdMSSnfWn/959f/nV9/7GLtS3cDf6V5OkKIF7QTSin/6G4XFEJ8BChIKS9vsY37jftqYyHE3wVOAE9tsT3NsPFR4N+vn/cgcr/v43tlz218L2xXLPMb/q6x2UPVSu4J4L9LKf/FNs7/ZeD/uIf3Py2ljGsPhBC+W9oogH8npfzaxoOEEP90G23b2MaD6lXCfbSxEOLngH8FPHUPHtue2lgI0Q38FfArUsrx7ZxjH3C/7+N7pRn38ZbZjQnTGPAYgBDiMdaGzwCvAl8QQoTWX2sXW1v5HAHagDdvef7aDtr4EvAPhBCu9XN1rbfrDeCzQgi7EMIN/PJWTrY+0fxFDuB85R2IsUs2FkJ8CPga8Gkp5fItr7WEjddv0v8F/I6U8ic7aNN+IsYu3sd3olVsvB12Qyz/AmgXQlwBfhMYA5BSXmXNlX5ZCHEReAXohA+c6/gy8D/lhn2YQogAa73KtpBSvszaytybQohLrK3CuqWU54A/Ay6wNnf27oZr3m2u4+PAjJRyYrtt2mfspo3/A2vDp2+vLxi8sP7+VrLxbwKHgN8VfxNiE9pu2/YJu2ZjIcRJIcQs8DzwtfVztpqNEULEgP8E/D0hxKwQ4qG7XX9f7A0XQnwKGJBS/udmt0Vxf1A2PvjsdxvvC7FUKBSKZqO2OyoUCsUWUGKpUCgUW0CJpUKhUGyBHe0JDQQCMhqN7lJTWp9YLEY8Hn9gCgA9aPYFOHv2bPxBypSubLx1diSW0WiUM2fO7OQU+4oTJ+7Hzq7W5UGzL4AQ4oEqsaBsvHXUMFyhUCi2gBJLhUKh2AJKLBUKhWILKLFUKBSKLaDEUqFQKLbAbqeTvy80Gg3q9TrT09Mkk0kSiQTJZBKr1YrT6cTn8zEyMoLVasVqtWIwqD5AoVDsLi0vllJKqtUqpVKJn/zkJ5w7d47z589z/vx5/H4/3d3dPPzww/zGb/wGgUCAQCCgxFKhUOw6LS+WgC6Wy8vLTE1Nsby8TC6Xw2g0YrVaWV5eJpFIYDKZ8Pl8mM3mZjdZcQfq9TqlUoliscjc3BwAAwMDuN3ubZ2vWCxSLpcxmUyYzWaMRiMm0774WSs2UKvVyOVyFItFZmdnqVarhMNhHA4HHo8Hp9PZ7Ca2vlg2Gg2y2Syrq6u89957vPbaa5TLZYQQ5PN5YrEYVquV9957j56eHsLhMHa7vdnNVtyBQqHA7Ows4+PjfP3rX6fRaPB7v/d7fOhDH7rnc0kpmZubY35+nra2Nvx+P3a7HZ/Px3oJBMU+IZvNcunSJaampvjDP/xDkskkn//85zly5AgnTpxgeHgYIURT7drSYtloNKhWq8TjcZaXl0kmk+Tza1nmDQYD9XqdWq1GuVzWPQyVcq61qVarZDIZUqkUCwsLAJTL268Fls/nSSQS1Go16vU6Pp8Pr9erxHIf0Wg0KBQKzM3NMTMzw+zsLPF4nFgsht1u5/Dhw/p9rcTyNtTrdfL5PMlkkr/8y79kdHSUGzduNLtZih2SyWS4fPkysViMfD6P2WzedgcnpWR6epqzZ8/qHeexY8f44he/iNV6oCrXHliq1SrFYpHx8XH+9E//lLm5ORKJBOVymR/84Ae8/fbbdHd3c/z4cYxGY1PXI1pOLBuNBrVajWq1qg+/Y7EY4+PjZDKZ2x4jpaRer1OtVqlUKlQqFQwGA0II/X9Fa1Aul0kmk6TTaWq12o7ml6WUlEolstks2WyWXC5HZ2cn9fpWi4Iqmo02h53JZJienmZxcZFqtYqUkkQiQS6XI5/Pt8SIseXEcmVlhYsXL5JMJrl27RqJRIKzZ8+ysLCgD8FvReuZMpkMVqsVn89HMBjE4XDQ0dFBW1vbHn8Kxa1IKZFSkk6nuXLlCktLS5TL5R3NLwsh8Pv9RKNRxsbGGBsbIx6PUyqVMJvNaqFvH5BOp7lx4waTk5PE43EymQy1Wg2TycTw8DChUIhIJILZbG56lEvLiWU+n2d8fJzFxUXOnDlDIpFgdnaWbDZ7x2MqlQqJRIJGo8HExAQej4dKpYLX68Xj8SixbAGklPrc1NLSEvF4nEajsePzOhwO2traEEKQyWTI5/P6/KXJZFKjihanVCoRj8dJJBL6ugOsrUkEg0F6enrweDwYjcYmt7QFxXJxcZEXX3yRRCLB0tISpVKJUql012Py+Tyjo6PYbDZisRg2m42Ojg48Hg/PPvssUkrcbjder3ePPoXiVtLpNMvLy0xMTBCLxWg0GoyMjBCJRLYdNgRrHWWhUCCTybC8vMzq6iqVSoVqtYrFYlFi2aJonefMzAyvvfYasVhs00Kf0WhkYGCARx55hGCwNdKLtpxYxuNxTp8+zerqqj7n+EHk83kmJib09xoMBvx+P263m0gkQldXF0IIJZZNJJfLMTMzw9zcHAsLCzgcDgYGBujr69tRDJ0Wg5vNZkkkEmQyGSqVipq3bHG0tYmVlRXeffddEokE1WpVf91kMtHX18eRI0daZmTYMmI5OTnJlStXeOedd/QJXuCuQzWj0aj/M5lMSCkpFov6cK/RaPDmm2+SSqV46qmniEQiytPYYwqFAsVikatXr2cbhO4AACAASURBVPLqq6/q4SDhcJhjx44RjUa37VlqiwCTk5Mkk8ldbrniflIoFMhms6ysrLCyskI6nd7UwRmNRkKhEL29vTsaeewmLSOWly9f5hvf+AZzc3P6sPuDVsCMRiMulwuj0YjNZtNjLiuVCplMhkwmw4svvsj3v/99DAYDv/ALv9AScx8PEplMhng8zttvv82f/MmfIITA5XLR09PDk08+STQa3fYij5SS+fl5Ll++zOLi4q7MgSr2hmw2y/z8vB5buXEIbjAYsFgs9Pb2MjIy0jIOTtPFUvM8tHCSjWECd/qSfD4fPp8Pj8eD3+/HYrFgs9moVqvMzs5SKBRYXFwkl8vpvdXq6ipTU1O43W4CgUDLGOAgI6VkeXmZmzdvsri4SLlcJhgM8vDDDzM0NITb7cZsNm/LFlqomCbGuVzuPnwCxf0im82ysLBAKpXa1MkZDAba29vx+/1YrdaWuk+bLpZLS0ssLCwwOTnJwsKCHkt5p61NBoOBQ4cO8eijjxKJRBgeHsZiseBwOPThXjwe58UXX2R8fFw/bnp6mh/+8IcMDg7ysY99TIWV7AFSSq5cucJLL73E2NgYpVKJrq4u/v7f//t0dnYSDAa3FTyuxVdqWyevXbtGo9FoiVg8xdaYn5/nzJkzxGKxTXazWq0cOnRoxwt/94OmiaUW3rG0tMSNGzdYXFykWCxSrVbf19NoISBOpxOz2Ux3dzcDAwOEw2EikQgmkwm73U6xWCSdTmM2m/X3ajdRKpViYmICs9nM0tISTqezZUISDhpSSgqFAuVyWd+qWigU9JR6gUCAtra2bSe8aDQaJJNJVldXyeVy1Go1fXRht9sxmUxNj8lT3J1isajbb+P9brVa6ezspKenp+VyPDRFLKWUZDIZcrkc3//+9/nOd77D6uoqy8vL7/MQDAYDXq8Xu93O0aNH6erq4sknn+TjH/84VqsVl8ule6HVapVQKMTy8jI//elPmZub02/a0dFR5ufneeihh3QP52Mf+xhut1sJ5i5Tr9cZGxtjYWGBM2fOcO7cOaxWK6FQiK6uLgYGBnaUHapSqfDTn/6U69evMzExAYDf76evr49oNIrL5cJutyvBbFGklKysrDA6OsrCwoJ+v2tZw5577jmGh4eJRCJNbulmmiaW2pbG1dVV5ufnKZVK1Go1vZcRQmCxWLBarQSDQdxuNz09PfT09NDV1UUwGNTTcmmYzWZ8Ph+1Wk1PqFCtVjcl2mhra2NqagqDwaDvIFFbIncXrTNcWVkhlUqRz+f1nVVutxu73Y7FYtnWubXkKisrK8zNzZHP5/VFo2AwiM/nU55lC6Pt4S8UCqTTaYrFoi6WBoNBv99DoVDL7e9v2jBci7MqFotkMpn3rWTa7Xb6+/sJBoN86UtfYnBwkGAwiMfjwev13nby12g06h7Lk08+SSAQ4Ec/+hGXLl2iXq9Tr9eZnJzk29/+NkePHuVDH/oQUkra29u3ffMq3k+tVmNsbIzz58/rK52RSISnn36ahx56aNvD73q9TiqVIplMcuHCBd566y2WlpYwGo0cPnyYz372s/T392Oz2dRooQWRUrK4uEgymdS3p27csWO1WnE4HHR1ddHT04PNZmtyizfTNLHU9grXajVqtZr+vMFgoNFoYDab8fv9dHR0cPToUR566CGcTuddexvNG5VS0tnZSalU4r333kMIoSfbyGQyZLNZPB4P+XyeSqWiFgZ2mUajQSqVYnFxkXw+T71e18OFQqHQtoVMi5/NZrPE43F9h5fBYMDn89Hf3084HFZC2aJIKcnn86RSKVKpFOl0Wn/NaDRiNpv1ee1WSPZ7K01fDb8Vu92O3++np6eHL3zhC/T09NDf368v2GwFbauU2+3m8uXLzMzMkEqlSCQS97n1DzZSSn374fz8PLFYTL8hurq6eOqpp/Rh8nYoFAqcO3dO3wmUy+VwuVz4fD56e3sZHh7G4XCoIXiLIqXU81SmUqlNr/l8Pj7ykY8wMDDQkkIJLSiWZrOZ9vZ2urq6OHnyJD09PXrM1VYxGAwEAgFsNhvhcBi/368n29DQvEnNw1XsHK1eUrlcJpVK6RmAANra2jh8+PCOSj5Uq1WmpqaYnJwklUpRLpdpb2/H6/USCATo6OhQQtnCSCn1banFYnHTa06nk8HBQfr7+1turlKjJcRy4wp4X18fv/qrv0p3dzfd3d243e5t32CaEG78p5HNZnnzzTdZWFjgmWeeabn5kf2KNhedz+fJZrO0tbURjUbp7Ozc8SKaNo2SSqWoVqsYDAbcbjfBYBCXy7VLn0Bxv9BC+Obm5vR4aoPBoDtIH/rQh+ju7sbhcDS5pbenJcRyo4j19fXxla98Zdc2z99OKLW8im+//TaLi4s8/vjjhEKhXbneg4w2L6ytduZyOQ4dOsTw8PB9EUsAl8ulF7ZStDaaWC4sLOg7rkwmEzabjUAgwKOPPkpHR0fLxVdqNEUsG42GXmhqdXX1vpx/eXlZXwSIx+MUCgX9dS3A/ciRI/p8qGLnCCEwmUxYLBY8Hg/t7e3U63WSySTZbJZSqYTFYrnnkYIWLpTL5ZidnWVqakpPBO12uwmHw3g8HhX+1aI0Gg3S6TS5XI6pqSnGx8f1+17bB66thLfynHNTxLJWqzE6OsqlS5eYn5/f9CPfjR98vV4nFosxOTnJ+Pg4s7Oz+h5xLYC9ra2Nn/3Zn6W/v5/29vYdX1PxN9EIdrtdz3CtJbtIJBJ6Jiin03lPdq7X6+RyORKJBFeuXOHq1at6ct9gMMjg4KCyYQtTq9WYm5tjeXmZixcvcubMGf1+1JLgOJ1OPd9Dq9K0oPTV1VWWlpYoFAo77km04V+9XqdcLpPP55mdnWViYoLV1dVNiTm0dG4WiwWLxbLtRA6K96PlH914A2i1cWZnZ7lw4QI+n49IJHLX8B6tllK9XtdrKqVSKWKxGIVCYVMqr421lhSti7bwV61WN4UKWiwW2tvb98XW46Z5lhMTE5w7d47l5eUdn69er+vDvIWFBRKJBK+88grvvffe+/Icmkwm3G63HopkNBqVWO4iWqxce3s7oVCIRCLB3NwcP/jBD5ienqa/v59nnnnmriue8XhczySUTCYpFAp6Yt94PK6/T7Ob2oHV2jQaDYrFIrlcblOCX1iLknj44YcZGBjYUaTEXtC01lUqFb2n2Y1zaZXgYrEYKysrevEj7fyaKLrdbrq6ugiHw9hsNlWn5T6gBYmHw2Hm5+f1XKOLi4tYLBYmJyfvumNqdXVVT7KwurpKqVQikUiQz+epVqub7GW32/F4PCqaoYXRgtG1LPYa2tqBtk211UcHrS3lW2RlZYXvfe97zM/P86Mf/YhEIkE8HtezpsNaYSuXy8WxY8f4/Oc/TyQS0ZMutLr7v98wm82cOnWKQ4cO4ff78Xq9LC0tMT09zcLCAhcvXvzA441Goz69oiVzrtVq77vZDh8+zDPPPKMnVFG0HpVKhatXr+rpEwF9UScajfLMM8/Q0dHRsvGVGvtaLLX6K6urq3rG5TuVGDAajdjtdnw+HwMDAwSDQT2dl2J30RK4ms1murq6mJ+fp1qtsrS0pO/vvttGALfbrYufyWTS0/nVarVNx2meSXt7u7Jji6JtaU4mk6ysrOibFLTUiy6Xi1AoRFtbm/Is7ydXrlzhu9/9LsvLy1y6dEnPYnI7tOJl0WiUw4cP4/F4VALg+4Qmlh6Ph1/8xV/kiSeeYGFhgampKT2P4d0Kig0MDBCNRnVPcWpqihdeeIGlpSWuXr26KSu60WhUVRxbFC0udnl5mQsXLnDmzBndkdG2NXd0dOjhe60+wmsJsbw149CtQeTajXWrN7KwsMC7776rJ224XfJgDS1FmM/no729vWUDXw8K2hyitrNGS62Xz+f1vKV34qGHHmJkZER/PDo6yoULFxBCMDY2tum9aiW8dWk0GpRKJXK5HEtLS8zNzemvaSFmLpdLzyLW6rSEWG4UwXQ6zfXr1/WytYVCgZ/85CcsLS3pYqgxMzPDpUuX9HyVWvjQ7YZ4x44d41d+5Vfo6upSHmUTcLlcdHV1UavV6OzsvOsw/NbdW2azmba2NrLZ7CbbaTux5ufncblcLR2j9yBSLpeZnZ1lZmZGH35rhMNhjh49Snd3977p7JoqlrdLYqHVVdGykqRSKb7zne9w7do1MpnMpp04tx57t6HYwMAAn/zkJ1ve1T+o2Gy2ba9YG43GTfOYG8nn8yQSCQwGgxLLFqNareplRTZWbwT0tYP9VDywKWJpNBrp7+/n+PHj+lyjxuLiIt/97nd1t7xUKjE7O0uxWNwUzAroeSq1v29FCEF3dzd+v1/VDD8AbMwUpaFlSFdbVlsPrbBcqVTSp13MZjMmk4m+vj4ef/xx+vr6lGd5N4xGI8PDwwghiMfj3LhxQ39tdnaWb33rW8DfCOCtK6C343bPm0wmBgYGOHr0KH19fUos9zF3GrZ7PB46Ojr2uDWKraAFo28M4bNardjtdgYHB/noRz+6r2olNUUstdXS7u5ufD4fdrtdDw/ZmK7tdpP3Gx9rBtCyLGtVHi0WC9FoVN8d0N/fT2dn5959QIVCoQ/DV1ZW9PhYrWy1zWbDarXuq5CvpnmWhw4dIhQK8eabb+JyuSiVSnomme2cz+VyYbPZiEQitLe385WvfIWjR4/qRbJsNpvyLPcxd5pmUTZtXYrFIjdu3GB8fFy/t10uF21tbXg8Hux2+75aQ2iKWAohsNlsNBoNIpEIhw8fJpPJ6JlpPiho+VasVqtelH1oaAi/309XVxd+vx+n07nvjKJ4PxsXA7URhxLK1kXbfZXP5/X1Bs1u2g6t/WbDpomlx+PB6XTyC7/wCwwODjI1NcW1a9eYmprixz/+8ftWz+5GIBDgueeeo6uri2eeeQa/34/b7cZisegG2U9GUWxGK1excYFPC0ZXnWDroQlluVzWc8pqIX8mk0n/t9+S2DRtwsBgMOhzl729vUgp9VjJcDhMoVCgXC7TaDSoVCp6xUetVvjGRAzhcJjOzk4ikQidnZ27lmVd0RrUajWy2Sz5fB4ppZ45yuVy7Ytg5gcZLWWfJoobO7n9JJTQAkHp4XAYn89HNBrl5MmTLCws8Nhjj7GyssLZs2dJJBJcv36dfD5PNBolHA4zMjLC8PAwsNaLtbW1cfToUdxut9qZcwBJpVK89dZbLCwsUK/X8fl8PPXUU0SjUQ4dOtTs5ilugzbV1tvbS61W03PXer1eOjo69mXNpKaLpdVqxWq16gHFTqeTSqXC4uIiy8vLWCwWlpaWEEIQCoXo6uri0KFDPPLII/oclsPhIBgMYrPZ1LDsAFKpVEgmk6TTaT30pLu7m8HBQRWI3oJo014mk0nfXmyz2fQtjg6HY1/uomu6WN6Kx+NhZGSEaDRKf3+/nlWoUqnoYUZ+v3/TUNtoNOJwOPQs6IqDhd1up6enh1AoxPHjxwkEAnzkIx8hEomoQnMtisFgoK2tjWeffZalpSVgLYZ6ZGSEzs5OfD5fk1t477ScslitVsLhMLBW6VGh0EqlCiE4ceIEkUiEI0eO4Pf7m900xV1wOBwMDw8TCoW4du0aNpuNzs5O/H7/vqzG2XJiqVDcSmdnJ88//zwAhw4dwuVy7cub7UFDi382mUw888wzpNNp3G43DoeDSCTS7ObdM0osFS1PMBjkU5/6VLObobhHDAaDXt721KlTzW7OjtkfmzIVCoWiySixVCgUii2gxFKhUCi2gBJLhUKh2AJKLBUKhWILiHvJ7vO+g4VYAaZ2rzktT5+UMtjsRuwVD6B9Qdn4QWBbNt6RWCoUCsWDghqGKxQKxRZQYqlQKBRbQImlQqFQbIG7iqUQwi+EeG/936IQYm7DY8vdjt0OQgirEOLPhBA3hRBvCyGiWzimvt6ey0KIbwshtr1pWAjx34QQX/iA9wghxH9eb+NFIcRj271eK7DXNt5w3c8LIaQQ4sQW3runNt7w3pNCiNpW39+qNOE+/rgQ4ty9fHdCiJgQ4tL6PfWyEGLbJTuFEP9WCPHPPuA9fiHEa0KInBDiv2zlvHcVSyllQkp5XEp5HPgj4A+0x1LKihBit/eW/0NgVUp5CPgD4N9v4ZjienseBirAr2988T608TlgaP3f/wb8f7t8/j2lCTZGCOEG/gnw9hYP2WsbI4Qwsvb7e3m3z73XNMHG08DfA/7HPR73tJTyGHAG+JcbX1h3UnZzJFwC/g1wV1HdyD1ffL1n/iMhxNvA79+q4uu9f3T9778rhHhnvQf72voP8G58Bvjv63//OfCz4t5yz/8YOCSE+IQQ4sdCiBeAq0IIoxDiPwgh3l3vub663j4hhPgvQojrQogfAFtJjvgZ4JtyjbcAnxDiQNXZvc82Bvi/WROi0jaatxc2BvjHwF8Ay9toY8tzP20spYxJKS8CjW027w3WbBxdt9s3gctAjxDin2+w8e9taO+/EkKMCSFOA8MfdAEpZV5KeZp7+A1uV6m7gVNSyt++0xuEEEeALwEfXe/R6sDfWX/t63cYfnUBMwBSyhqQBraUtHC9d3wOuLT+1GPAP5FSHmbNY01LKU8CJ4FfE0L0A59j7Yt9CPgV4NSG8/1fQohP362N68yuP3fQuC82FmvTFj1Syv91rw3aKxsLIbrWj9vXo4YtcL/u453yKf7GxkPAH0opj7JmxyHgw8Bx4PH1If/jwJfXn/ska/bX2v/rQohNI5Htsl33+9tSyvoHvOdngceBd9edQzvrvbSU8h9t87q3wy6EeG/97x8D32DthnhHSjm5/vzPA8c2zJ94WfvSPw58a/2zzAshfqidVEr5u7vYxv3Irtt4fRj1n1gbot0Le23j/wf4P6WUjXsb2Ow7Wuk+BnhNCFEHLgL/GvABU+sjOFiz8c8D59cfu1izsRv4KyllAWB9tMF6G/9otxq3XbHMb/i7xmYP1bb+vwD+u5TyX9zDeeeAHmB23YvwAokPOKa43uPprBt1YxsF8I+llC/d8r5P3kPbbm2jRvf6cweN+2FjN/Aw8KN1G3UALwghPi2lPHOX4/baxieA/7l+jQDwSSFETUr519s4Vytzv+7j7fK0lDKuPRBC+Hi/jf+dlPJrGw8SQvzTPWjbroQOxVgbDmlDrP71518FviCECK2/1i6E+KA6ES8Av7r+9xeAH0oppRCiSwjx6g7a+BLwvwshzOttOSyEcLI2N/Kl9fmuTuDpLZzrBeBX1ufCnmBt6Lewg7btB2Lsgo2llGkpZUBKGZVSRoG3gE9LKc+0ko2llP0b2vjnwG8cQKG8lRi7dx/fESHEtR208SXgHwghXOvn6lpv1xvAZ4UQdrG2ePjLO7jGHdkNsfwLoF0IcQX4TWAMQEp5lTVX+mUhxEXgFaAT7jrX8Q3AL4S4Cfw28Dvrz3ey1vNtl68DV4FzQojLwNdY86r/Crix/to3gTe1A+4yZ/k9YAK4Cfwx8Bs7aNd+YTdtfCdaycYPIrtmY7EWcjULPA98bf2cCCECrHmH20JK+TJrK+xvCiEusdaRuaWU54A/Ay4ALwLvbmjLHecshRAx1qeFhBCzQoiH7nb9fbE3XAjxm8C0lPKFD3yzYl+ibHzwEUJ8ChiQUv7nZrdlO+wLsVQoFIpmo7Y7KhQKxRZQYqlQKBRbQImlQqFQbIEd7QkNBAIyGo3uUlNan1gsRjweP9BRyht50OwLcPbs2fiDlCld2Xjr7Egso9EoZ87cLZb4YHHixP3Y2dW6PGj2BRBCPFAlFpSNt44ahisUCsUWUGKpUCgUW0CJpUKhUGwBJZYKhUKxBZRYKhQKxRZQYqlQKBRbYNdrlygUCsVOqNVqNBoNyuUy9fr7cxMbjUasViulUon5+XlqtRpOpxOTyYTNZsNsNmO327FarbvaLiWWCoWiZWg0GhSLRarVKslkkmKx+L73OBwO2tvbWVlZ4ZVXXqFYLBKJRHC73YRCIdxuN+FwmGBwd/cWtIxYNhoN6vU6uVyOubm1xOMOhwOz2YzP58NisWA2mzEYdjZzIKXUr1UoFAD0XumAlxBQKFqOSqVCPp+nWq2Sy+WoVCrE43HK5TLxePy2Yul0OgkEAiSTSW7evEmpVCKTyWCz2Whvb8fpdPLYY48dXLHUvrQLFy7wzW9+E4CBgQHa2to4deoUHR0dtLW14XBsu2Q0APV6nVKpRDab5ebNmwghOHLkCF6vF6PRqARTodhDEokE169fJx6Pc+nSJVKpFNevXyeTybC0tKQ7NBvRPMdKpcLc3BzVahUt1aTBYMBkMvE7v/M7PPLII7va1qaLpZQSKSXpdJq5uTmmpqaYnp5GCIHL5UJKSa1W2xURazQa5PN55ufnyWQyTE1NYTQa6e3txel0IoTAaNxKJVfFbqB5+blcjmq1qs9Vud1u3G53s5un2EXq9fqmIXa5XKZcLrOwsMDk5CTxeJxYLEY6nWZ2dpZsNksikbitWGq/l3q9TiqVolarbRJMo9FIPp9/33E7peliWalUqFQqvPrqq3zjG98gmUwyOzuLy+XSvT2Hw0EgEMBk2n5zq9UqlUqFM2fO8Md//MekUilWVlbw+/34/X4MBgPt7e079lwVW0ObwM9ms7z88svMzs6ysrJCPp/nl37pl3juuecwGAw7nnZRNJ9Go8Hq6ir5fJ5z584Ri8UYHR3l+vXrFItFstkslUqFQqFArVajWCxSr9ep1W5fZaRUKrG4uAj8zWLQXiQxb6pYSikpFovk83lmZ2e5fPkylUqFarWKzWbDaDRiNBqxWCxYLJYdXatarZLP51leXubKlStkMhkqlYpunI09k+L+oY0UarUamUyG1dVVYrEYExMTLC4ukslkOHHiBI1GQ02JHBCklJTLZQqFAnNzc9y4cYNLly5x4cIFGo3Glu89IQQGgwEhxCYv8tbR4P0aITZNLIvFIpVKhddee413332X8+fPk8lkCAQCPPTQQ/T29vL5z3+ejo4OIpHIjq83Pj6uX2dxcRGXy8Vzzz1HT08PQ0NDhEKhXQ81ULyfZDLJ2NgYS0tLvP7666ysrDA6Osrq6iqlUol6vc7i4iLFYhGLxYLdbm92kxU7pNFo6MPqc+fOcfr0aVKpFNVq9Z68QpfLhcfjwel00tbWdsfO1Gg00tHRsZsfAWiSWEopqVarlEolxsfHeeutt5idnaVSqWCxWIhGowwNDfH444/v2opWIpFgdHSUqakpcrkcPp+PkZER+vr6CAQCOJ3OXbmO4u4UCgWmp6eJxWL86Ec/YmVlhUQiQblcBta8Am1VVA3B9xe3ip4mZhs9y4WFBW7evHnb4zeK30bba8/b7XZ8Ph9er5dIJHLH34fBYMDj8ezos9yOpollMpkkmUwyNTXF+Pg42WwWKSWhUIhPfOITdHV17cr8YSaToVAocPXqVd544w2q1SqHDx9mYGCAY8eO0dXVpYRyD6hUKhSLRSYmJvje977H4uIii4uL5PP5TYHHUkquXbvGX//1XzM4OMjJkyexWCzK629htKmzubk5JiYmsNvtBINBHA4HXV1dwJqAaVNqNpsNk8mE0WjUh+FOp5POzk5sNhs+nw+r1Yrf78fhcOD1enE6nTidTlwuF3a7Ha/Xe9dpmiNHjuz652yKWDYaDVKpFEtLS8zNzTEzM6O/1tbWxsmTJwkEAthsth1fK5/Pk0gkmJyc5MyZM3R2dvLYY48xNDTE8PAwoVBIDfX2gEqlQi6XY2Zmhh//+Mesrq6SyWRoNBrAZq9icnKS1157jWKxyNGjRwGwWCxqDrNFqVarFItFpqen+elPf0pbWxtDQ0O0t7cTCoX0GGaj0YjJZMJqterrENVqVfcEBwcH8Xg89PT04HK5GBwcpK2tje7ubgKBAGazGZPJpJ9jr9lTsZRSUqlUKJVKzM7O6qECAL29vQwNDfHYY4/hdruxWq3bHoZJKcnlcpTLZd5++20uX77M5cuXkVLicrno7++nu7sbu92O2WxWN+EesLKywpUrV7h58yaFQoFyuXzHuSot9q5er1OtVgkEAoyMjOB2u+nr68Nut6shegtQr9ep1+tcuHCB0dFRbty4wcWLF4lGo/T19ekdodFoJBAIYLVaefrppwmHw9jtdpxOpx4R4fF4GBgYwG6309bWhtVqJRgM6kNvzeZGo7Fptt9zsSwUCuRyOcbHx7l69SrxeByAoaEhnn/+eQYGBnQ3fLtooQqpVIqXXnqJ7373u+RyOaSUeL1ejh49qvdeO11lV2yN2dlZXn/9dW7cuEE6nb6rWM7Pz7OwsMDo6Cg//OEPiUajfOYzn6G7u5u2tjbdy1SdXHOp1WpUKhVOnz7Nt7/9bVZWVpifn+fxxx/nYx/7mL54oy24hEIhnn/+eX3NwOv1ks/nWV1dxWKx4Pf7N4mhZt9WsfOeimWlUmFiYoKVlRVu3rxJLBajUqng9XoJBoP09PQQCAR2vOwvpSSTyZBIJEin0+TzeWw2G16vl+7ubnp6egiHwzuK21RsDS3YPJFIEIvFWFpa0m8gzVvQvPtsNqsv9GghRqVSiVQqxfj4uB7+5fV6dS9DsfdothkfH2dlZYXJyUkSiQRms5n+/n6i0SihUAifz7fJRgaDAbvdjhBCn7e02Wy4XC59iK2FBrUie6oW2WyWl156iRs3bnD69GlmZmYIhUL09fVx5MgRTp48id1u3/FNUK/XmZ+fZ3JyksXFRdLpNCMjIxw/fpwPf/jDnDp1St8Prri/5PN5stksY2NjnD59mkKhQLVaxWq10tHRgd1ux+PxYDQauX79OktLS/qxWjzm3Nwcr776KgMDAzz77LN4vV59gUCx92h5FV588UXOnDnDhQsXmJ2d5dFHH+XJJ5/kyJEjPPLII7cdubndblwuly6I2vwltI4HeSf2fBheKpX0Oatyuaz3NjabDavVuu05RK23S6fTZLNZZmZmmJmZ0VfZ29vb/3r10QAAF+dJREFUGRoaoqurS+/VFPcfbc9/oVCgWCzSaDRwOp14vV6Gh4dxu936VtNKpYLVaiWfz5PL5fSV0nq9TjabJZVKMT09jcViYXBwEJ/P19KeyEGj0WhQq9VIJpOkUinm5uaYn5/XtyS63W56e3sJh8N6qrRbbXO76ZP9Yr89Vwzty9L+aRO6mqe3nclbLW5zdXWVl19+WfdE1ut8A3D8+HG++tWv4nQ61TzlHqGFiMViMZaXlykWizidTvr6+hgeHua3fuu36Ozs1Le2nTlzhlgsxrvvvsu5c+fIZrOsrq7qO61isRhf//rX6erq4td+7dd49NFHsdvtyp57gLY9NZ1O88orrzAzM8Pp06e5du0aRqMRt9vNQw89xC//8i/r3uNB68ia6l5p25ZqtRqFQoFkMqnPXWgJPu/2ZWs9nbZlMR6P6x7l4uIi8Xicer2uD/U6OjrUKuoeo807ars1LBYLgUCAUChET08PkUiEavX/b+/cY9u8ssT+O3xJlEjxJVKkqLcl2ZtYnozzcBLPZBzbWSADTyaZ2SAFul0M2i46nX11ii2KbRdFOwU66HZRFINFOwtMO50FinaxWexOimImM5nZZDxJdhM/8pJjx7KtN0WKoknqRYmibv8gvxvJ8YN2LFGU7w8QTJrf45Dn+8537r3nUaRYLDI7OwvA2NgYbrdbz1/CxzdrOp3GbrdTKBS2LSfY8HGdyfn5eaamphgfHyeXy1EoFGhtbdVhQsFgUKcq7zZqnhs+NTWlq4uMjY3hdDppamrC7/fz0EMP4fF4bri/VXQjl8tx5coVstks77zzDrlcTnskvb29xGIxuru7t/GbGSwsr9EKPG9ra+Opp56iu7tbJwNYD8f77ruP3t5e0uk0Fy5cACCVSmmDKCI6xs6KtzMPv+1hfn6e9957j4mJCX70ox8xNjbG6uoqra2tPP/88xw9epTe3l48Hs+uNJSwzcZyY2CqdZEvLi6yuLjI6OgoIoLT6aS5uZlwOEw0GsXn893weMlkkpGRETKZDOfPnyefz3P58mU9h+JwOGhpaaG9vZ2WlpZdNSSoF6xYSSvmrrGxkWg0Sjgc1jeVNSVjhZNYoWNWsWdrX2vl3DKuu22Yt5MpFouk02mSyaQevYXDYbxeL729vdqxcTqdtRZ1y9hWY+l2u3n44YeJxWJMTk6SzWYpFAqsrKyQzWZ1MV4rpODy5cs3nY9aXl4mn8/ruRSr3JuI0NLSgtvt5tFHH+Xzn/88e/fu3cZvaoDyyGF8fJy3336b8fFxoJx+eu7cOQqFAg888MB198tms4yNjZHNZrWhBHA6ncTjcbq6uvD5fDQ0NOxaL2anUSgUdK3Z1dVV7HY74XCYcDhMJBIhEAjsakMJ22wsrTgsj8dDKBSiubmZUqmkk+wtj9Aadl28ePGWnsPGIZqFFcPn8/no6+vj4MGD+P1+44XUgEwmo+Pw1tfXdZOp5ubm69YrtBIX5ubmKBQKm+YkbTYbfr+fUCiE2+02EQ3bSLFYZG5ujnQ6TbFY1MW5A4EAXq/3nqgDu61Xm8PhoLW1FbfbzXPPPceDDz5IOp0mm82SzWZJp9Ok02lGRkYolUo0NDTQ0NBAT0/Pdecug8Eg8XicRCLBK6+8oqsj22w2IpGI/gsEAnclz9xwe4gIsViMoaEhCoWC9igTiQQej4dUKgWgM3oSiQTZbJb333+f5eVllFI0NjbqxZ2VlRU+/PBDstksjz76KKFQCI/HY3S7DSwtLXHhwgUmJyf14loikWBpaYnTp0/j9XoJBAJEIhFdDGO3OSfbaiytHNFQKMSzzz7L6uoq09PTzM7OMjo6yoULF/joo4+4cuUKgF7FPnDgwHXr0+3Zs4dDhw5x+vRpXn/99U3GMhQK0dHRoY2loTbEYjH279/PxMQEIqKrXHs8Hh3WNTExQS6X45133mF8fJzh4WEKhYKejimVSrpq0fnz55mZmWFiYoKOjg7sdrsxltvA0tISly5dYnx8XFcyTyQSpNNpTp8+jYjQ19fH/fffTyAQ0IkGu4majGOshRwRIRAI4HA4cDqdeL1eOjo6CIfDrK+v62D1wcHB6y70WHnCllLsdjsejwev18v+/fvZu3cvbW1t2/31DBVERNcetHRlVZwaGxvjxz/+MR6PR7c8HRsb4+rVqxSLRWKxGNFolL179zI3N8fp06d1H+lCocDo6KheCDIPw63HmkJZXV3VUyNW2N/k5CQOh0NnzUUiEfbv36+dHZvNtmmk4HQ6aWxspLGxUXufxWKRpaUlXYHI6XRuurd3AjWb9LGG2E1NTSilGBgY0M3LrDAT64e80arn4uIimUxG/6AOh4O2tjYikQhHjx7lkUceuelqumHrsfo4x+Nx3G639ixnZmY4d+7cphYB1mJOd3c3AwMDHDp0iBdeeIEPP/yQubk5UqmUTl89e/YsuVyOcDhMX19fLb/iPUGpVNKRK1C+N6055w8++IBz587p+7Snp4cjR44QCoXYs2cPDoeDTCajK0h5vV69OGSxuLjI1NQUTqeT/v5+PB4PwWDQGMuNXC/9qdpVNSs2M5lMUiqVcLlcdHV1EY/HdfMxswhQW6y4yLa2Nvbv36/npNfW1jYFnVujDI/Hw8DAAPfffz+Dg4MEAgEd8Ly2tqYXGLLZLKlUilwux/Lysg4pMmwNDQ0NtLe3UyqVyGQyrK6u6s+sUm1Q1mM+n2d8fFxHuzgcDnK5HGtraySTSR1HvdGRKRQKpNNpHA4H2WyW5uZmotEoHo+HaDRKMBjc9u98LXV9dY2NjfHDH/6Q0dFRVlZWCAQCPP300wwMDNDf329iK3cAVqGEQ4cO0dTUxKlTp/j+97/P/Pw8pVJJe5UOh4OhoSEGBgY4evQoR44cwe124/F4WF5e5uDBg7S2tjIxMcHS0pJeYT98+DCpVIqWlhYzHN9CgsEgx44dY3x8nJ/+9Kc62+palFKkUileffXVTZWhrFGj5X1eW5fSGtI7HA4CgQBut5vBwUFaW1t54YUX+MIXvrAt3/Nm1KWxXF1dZWVlhUwmw/T0tF4ocDgceL1efD6fqay9gxARvF4v7e3tdHZ20tHRQTabJZPJUCqVEBHtuXR3d2tPwkpgaGpqIhaLUSwW8fl8rKysbEqRTSaT2Gw2Yyy3kIaGBjo7O7HZbPT09OB2u7XnCB/3gLcytm7UxvZW2O12XZWqqamJQqFAMplkbm4Ot9td0xClujSWExMTXL58mV/+8pe89tprrKys6Bp5Ho8Hj8djhmQ7DCvMxxpqz87OcurUKZaXl/VC3okTJzhw4ADBYHDTwy4cDnPixAkmJyeZmpriypUrXLx4kWQyyRtvvMHCwgJPPPEEHR0d5gG5RUQiEZ577jkWFhY4dOgQs7OzvPjiiwwPD+sc/Y3Vou40Z9+aG11aWmJ4eJiGhgZaW1vJ5XIcOHCARx55pGY6rkuLsrS0xOzsLJlMhqtXr6KUorm5eVOZN5MzvLNwOp04nU5aW1t1r5V0Os3i4iJNTU00NjYSj8eJxWKfGBW4XC7C4TDFYpFIJEI+n2dkZITV1VVdH8Dq57OTFgR2Ey6Xi0gkgs/no1Qq6dA8q1jN+vq6LnxjDbnX19dZXV3VBW+qxdrW6u2TSqWYmpqip6dni75dddSlsZyZmeG9995jfHyc9fV1HSrU29vLnj17dJ8Ww87D6/Wyb98+ent7GRgYoFQq6fkrqw7itQ86Kyfcirn1+Xy6UPDMzAzFYpEHHniAhYUFGhoaTNzlFmGz2WhoaCAejxMOh/nGN75BLpfTxnFmZoaxsTE9HM9kMrz++uvMzc2RTCZ1ht7toJTSVfa3omPj7VCXxnJhYYFkMsn8/DyAXm2NRqM6/cqwM3G5XHplMxaLVb2fzWbD5XLR1tamW6fabDbdW8mqEWDd0GY4vjXYbDadTXftCvXk5KSuT2p1K7h48SKlUom5ublN24qIXuy51hvdOIS3SsNZ5eCUUmYYXi1KKWZnZ3XsncPhIBwOc/jwYbq6um5a0s1Q3zQ2NrJv3z5aW1v57Gc/C5QrT2WzWS5evMjJkyfp7Ozk4MGDZs66Bvj9/k3x0n6/n6GhIfx+P4lEgnw+r42k1QsrHA7T399PLpdjeHiYfD7PpUuX7sgL3Wrq8orK5XK6np7dbsfv97N//37a29vNEGwX43Q66ezsxO/309/fTz6fJ5/PMzk5yfT0NO+//z5KKT7zmc8YY1kDrMVVC5fLRW9vr+6IAGXP1Jpyue+++xgcHORzn/sc09PTKKVIJBI6PGynUTdXlFKKiYkJMpnMph/TKhYcDocJhUK7vkzUvY6VKrt3717sdjuJRIIrV64wPT3Nm2++iVKKxx9/XPf2MQt9tcPlculAdstYWllaiURCB7Cvr6/rvvIbw5EsrCiXWk+v1I2xLJVKXLp0SRfayOfzNDY20tLSQnNzM7FYjEgkUmsxDduAy+XSI4mzZ8/y1ltvMTU1xejoKHa7nWeffVbfoMZY1g6rYpjD4dDG0kpnnpiYYHJyksnJSWZmZpifn2d4ePgT/eRtNptuY13rUWPdXElKKV0Z3ZosbmpqIhqN6ubs8HEbg0KhwPLy8h0Hxxp2LlaQezAYpKenh6GhISKRCEopstksw8PDjIyM6G6ShtpgNTLz+/3EYjE6Ojp0KxFAx2bOzs4yNze3KaPLbrcTCoVob29ncHCQAwcO3NaC4FZQV57l+fPnefXVV7ULHwwGGRoa0sn6SildmWZpaYm1tTX8fr+Zv9pl2Gw2wuEwgUCAw4cP09TUxMmTJ3XQ+ksvvcTevXsZGBjA5XKZbK4a4XQ6iUQi2O12Dhw4gN1u5+zZs7oYB5TXH6yIBiu/3G6343Q62bNnD9FolKeeeopjx45tqlJUC+rKiqytrbG6uqp/VJvNhsPhYH19natXr7K0tEQymdy0jd1u3/Q0M+wOrPxiqwB0KBTStS+TySTBYJDFxUW8Xq/u2WPYXiwdNTY20tHRwfLyMolEQhfV2BiwbqW8OhwOfD4fzc3NDA4O0tHRQVtb244oilNXxvJarDCEfD7PW2+9xfLyMj//+c/JZrO0tbXh8Xj4yle+ct3CwYb6x2az0d/fTyQSIZFI8MYbb7C8vMyZM2dYWVlhcnISu92Oy+UySQo1QERwuVz4fD6efvppHnvsMVwuF01NTaRSKVKpFIVCgYWFBVwuF6FQiJaWFg4dOkQ0GuVLX/qSLtdW68UdqHNjWSwWWVxc5OrVq4yPj1MoFJidnWVhYQG/329iLu8B3G43IkI4HKazs5NUKkU6nWZhYYFMJkNLS4spAF1jrPA+l8tFPB6nu7sbu92up8tsNhtut5t4PE4gENDFVNrb23fUom1dG8tEIsFrr72mK9O43W76+vqIRqMcP36c3t5eent7ay2mYQtpbGzE5XJx5MgR4vE4v/jFL/jOd75DJpPhlVdeoaenRxcgNtQGK+vH6r117Ngxzp07pxNLJicnaW9v5/jx43oxyO12EwqFai36JurKWFrl6K1Cr6VSiWw2q+O1fD4fQ0NDtLa20tHRQVdXl7lJdjlWkHMkEqGhoYHx8XGcTielUompqSnsdrteFTdhRLXDbrdjt9uJx+PE43HdT97v92Oz2eju7mZoaAifz7dj+/fUjbF0OBw89thj+Hw+zpw5w5kzZ2hpaSEajRIOhxkaGsLr9eqUx66uLt3Lw7D7cbvd2O122tvb2bdvHwsLC4yMjOiq3VZxYDN3uTPo6OjA6/VSKBRYXFykubmZcDi8oyuG1Y2x3Fh0dH5+nqmpKdra2hgYGKCzs5Pjx4/j8Xhobm7G4XDgcDhqPiFs2D4snft8PmKxGIlEggsXLlAsFslkMuTzeT0UNNQev9+P3++vtRi3Rd0YSxHRPceffPJJ+vv7aW5u1m03re6B1pPJGMp7k66uLp5//nlGRkbIZrPY7Xa92LPT5sAM9UVdGctgMEgwGKSzs7PW4hh2KPF4nBMnTvDuu+/y8ssv646E2WyWYrFYa/EMdUzdGEuDoRqsupexWIwvf/nLrKys6HTIWvZvMdQ/xlgadhVW8d++vj6++c1vopTCbrdft+WywXA7GGNp2JWISM3T4wy7i525Rm8wGAw7DGMsDQaDoQrkTvv7AojILDB298TZ8XQrpcK1FmK7uAf1C0bH9wJ3pONPZSwNBoPhXsEMww0Gg6EKjLE0GAyGKjDG0mAwGKrgpsZSREIi8k7lb0ZEpja8d22VUCLyVRFRIvJQFduWKvJ8ICJ/ISJ3nKYhIv9TRH6tym0fFpG1arffqWy3jkWkW0R+JiLvicirItJRxT6jIvJ+ZZ+fiMgdl74XkX8rIr9/i21cIvL9yjnfFZEjd3q+nUANdPw1EZndcI5/XMU+263jHhFZ3iDjd2913JtG7Sql5oAHLAGABaXUH284oUMpdVfbJ4qIF/g94O+q3GVZKWXJ+L+ArwP/eYtltAP/EfjJ3TxuLaiBjv8Y+DOl1A9E5CjwbeAfVLHfk0qptIj8B+BfAb+7QUahvFh5t1o5/iaAUmpIRCLAj0Tk4bt4/G2lFvcx8OdKqd++zX22U8cAlyzbUQ23PQyveF/fFZG/A/7oWite8fB6Kq9/XUTeqljuP60YmVvx7ykbosKtNrwOJ4F+ETkiIidF5CXgnIjYReQ/icjblSfXP6nIJyLyJyJyQUReAaqtYf87wF8CqTuQccezxTq+D/h55fXfAF++TfF+QVnHPRW9/RnwAdApIv9ig47/3QZ5/7WIfCQivwT2VnEOLaNSKgVkgVuOcuqJbbiPPw3boePb5k7nLDuAx5VS//xGG4jIrwAvAIcr1rsE/P3KZ9+T6wyxReQg0KmU+n+3K5CIOICngfcr/3UQ+D2l1CDwj4CcUuph4GHgN0WkF3iO8g97H/AbwOMbjvctEXnmOueJV/b7b7crY52xJToG3gW+Unn9HOAVkdupnXaCj3U8APxXpdT9lPU4ADxC2Yt6UESeEJEHgb9X+b8vUta/Jf/XReTrN5DxGRFxVK6TB4HdWOpqq3QM8NWKQXtRRG73t9sOHQP0ishZEXlNRD5/K6HuNHn2L5RSpVtsc4zyRfZ22YPGTcUTU0p9Yg5DRGyUh89fu01Z3CLyTuX1SeC/UzZ6bymlrlT+/1eBA/Lx/KKP8o/+BPC/K99lWkQsjwel1L+5wfn+C/AvlVLrsrsLM9x1HVf4feBPRORrlD2IKco34K34GxEpAe8Bfwj4gTGl1N9WPv/Vyt/ZynsPZR17gb9SSi0BVEYbVGS80TzV/wB+BThFOWD7jSplrDe2Ssf/l/J9tVIZxf0AOFqFPNup4wTQpZSaqxjbvxaR+5VS+RsJd6fGcnHD6zU2e6iNlX8F+IFS6g+qPKYX2A+8WlFKFHhJRJ5RSp26yX56ztKisv9GGQX4HaXUy9ds98UqZdvIQ8D/qZyjFfiiiKwppf76Do61k9kKHaOUmqbiWYqIB/iqUipbxa5PKqXS1hsR8fNJHX9bKfWnG3cSkX9WrWwbZFwDvrnhGG8AH93uceqArdLx3Ia33wP+qMpdt1PHK8BK5fVpEbkEDFJ+QF6XuxE6NEp5yGsNo612ij8Dfk3KE+SISFBEum8ifE4p1aqU6lFK9QB/CzyjlDolInER+dmnkPFl4J+KiLMiy6CINFP2bF6Q8pxmDHjyVgdSSvVukPFF4Bu70FBeyyh3QceVbVorowiAP6DsxVmfnf8UMr4M/MOKAaZyzUQo6/hZEXFLefHwS7c6kIg0Va4PROQpYE0pde5TyFYPjHL3dBzb8PYZ4MMNn+0UHYetuVcR6aPsoV6+2T53o4bVXwK/ISLDlFewPwJQSp0TkT8EflK5OYrAbwFjIvI94Lu38Bg3EqP85LtTvgf0AGek7BLOAs8Cf0V5eHAOGAfetHYQkW8Bp5RSL33iaPced1PHR4Bvi4iifJH/FpSNKGXP4Y5QSv2kMr/2ZsXrXwB+XSl1RkT+nPI8ZAp429rHmsu6zlAtArwsIuuUpwmqWa2vd+6mjn+3Mt+/BmSoTK3tMB0/AXxLRIrAOvB1pVTmZuevi9xwEfltYNwYrt2LiJwA+pRS36m1LIatod51XBfG0mAwGGqNSXc0GAyGKjDG0mAwGKrAGEuDwWCoAmMsDQaDoQqMsTQYDIYqMMbSYDAYquD/A3+wtU+cAfewAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fab0c040dd8>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1255,10 +1245,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Model: \"model\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "input_2 (InputLayer)         (None, 784)               0         \n",
+      "input_2 (InputLayer)         [(None, 784)]             0         \n",
       "_________________________________________________________________\n",
       "reshape_1 (Reshape)          (None, 28, 28, 1)         0         \n",
       "_________________________________________________________________\n",
@@ -1322,7 +1313,7 @@
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras.layers.convolutional.Conv2D at 0x7fab0c052d30>"
+       "<tensorflow.python.keras.layers.convolutional.Conv2D at 0x7f8145dfdf60>"
       ]
      },
      "execution_count": 50,
@@ -1414,9 +1405,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faa856a42e8>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -1450,9 +1441,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faa8529c240>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -1545,12 +1536,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faa84ab9208>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1563,99 +1556,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Output of Convolutional Layer - Method 1\n",
+    "### Output of Convolutional Layer\n",
     "\n",
-    "There are different ways of getting the output of a layer in a Keras model. This method uses a so-called K-function which turns a part of the Keras model into a function."
+    "In order to show the output of a convolutional layer, we can create another Functional Model using the same input as the original model, but the output is now taken from the convolutional layer that we are interested in."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 60,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from tensorflow.python.keras import backend as K"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "output_conv1 = K.function(inputs=[layer_input.input],\n",
-    "                          outputs=[layer_conv1.output])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can then call this function with the input image. Note that the image is wrapped in two lists because the function expects an array of that dimensionality. Likewise, the function returns an array with one more dimensionality than we want so we just take the first element."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(1, 28, 28, 16)"
-      ]
-     },
-     "execution_count": 62,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "layer_output1 = output_conv1([[image1]])[0]\n",
-    "layer_output1.shape"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can then plot the output of all 16 channels of the convolutional layer."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 63,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faa847ac1d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plot_conv_output(values=layer_output1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Output of Convolutional Layer - Method 2\n",
-    "\n",
-    "Keras also has another method for getting the output of a layer inside the model. This creates another Functional Model using the same input as the original model, but the output is now taken from the convolutional layer that we are interested in."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 64,
    "metadata": {
     "scrolled": true
    },
@@ -1674,7 +1582,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -1683,7 +1591,7 @@
        "(1, 14, 14, 36)"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1702,14 +1610,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7faa849ed048>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -1790,7 +1698,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/07_Inception_Model.ipynb b/07_Inception_Model.ipynb
index 1ae5c56..da11720 100644
--- a/07_Inception_Model.ipynb
+++ b/07_Inception_Model.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #07\n",
     "# Inception Model\n",
@@ -16,10 +13,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2. It would take too much effort to update this tutorial to use e.g. the Keras API, especially because Tutorial #10 is somewhat similar.**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -34,20 +37,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Flowchart"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The following chart shows how the data flows in the Inception v3 model, which is a Convolutional Neural Network with many layers and a complicated structure. The [research paper](http://arxiv.org/pdf/1512.00567v3.pdf) gives more details on how the Inception model is constructed and why it is designed that way. But the authors admit that they don't fully understand why it works.\n",
     "\n",
@@ -60,9 +57,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -85,10 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -97,9 +88,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -115,10 +104,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.5.2 (Anaconda) and TensorFlow version:"
    ]
@@ -126,11 +112,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -149,20 +131,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Download the Inception Model"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Inception model is downloaded from the internet. This is the default directory where you want to save the data-files. The directory will be created if it does not exist."
    ]
@@ -171,9 +147,7 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -182,10 +156,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Download the data for the Inception model if it doesn't already exist in the directory. It is 85 MB."
    ]
@@ -193,11 +164,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -214,20 +181,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load the Inception Model"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Load the Inception model so it is ready for classifying images."
    ]
@@ -235,11 +196,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model = inception.Inception()"
@@ -247,20 +204,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Helper-function for classifying and plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is a simple wrapper-function for displaying the image, then classifying it using the Inception model and finally printing the classification scores."
    ]
@@ -269,9 +220,7 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -288,20 +237,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Panda"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image of a panda is included in the Inception data-file. The Inception model is quite confident that this image shows a panda, with a classification score of about 89% and the next highest score being only about 0.8% for an indri, which is another exotic animal."
    ]
@@ -310,9 +253,6 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -350,10 +290,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Interpretation of Classification Scores\n",
     "\n",
@@ -370,20 +307,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Original Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Inception model is very confident (score about 97%) that this image shows a kind of parrot called a macaw."
    ]
@@ -392,9 +323,6 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -431,20 +359,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Resized Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Inception model works on input images that are 299 x 299 pixels in size. The above image of a parrot is actually 320 pixels wide and 785 pixels high, so it is resized automatically by the Inception model.\n",
     "\n",
@@ -457,9 +379,7 @@
    "cell_type": "code",
    "execution_count": 10,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -476,10 +396,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now plot the resized image of the parrot. This is the image that is actually input to the neural network of the Inception model. We can see that it has been squeezed so it is square, and the resolution has been reduced so the image has become more pixelated and grainy.\n",
     "\n",
@@ -490,9 +407,6 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -513,20 +427,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Cropped Image, Top)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image of the parrot has been cropped manually to 299 x 299 pixels and then input to the Inception model, which is still very confident (score about 97%) that it shows a parrot (macaw)."
    ]
@@ -535,9 +443,6 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -574,20 +479,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Cropped Image, Middle)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is another crop of the parrot image, this time showing its body without the head or tail. The Inception model is still very confident (score about 94%) that it shows a macaw parrot."
    ]
@@ -596,9 +495,6 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -635,20 +531,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Cropped Image, Bottom)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image has been cropped so it only shows the tail of the parrot. Now the Inception model is quite confused and thinks the image might show a jacamar (score about 26%) which is another exotic bird, or perhaps the image shows a grass-hopper (score about 10%).\n",
     "\n",
@@ -659,9 +549,6 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -698,20 +585,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Parrot (Padded Image)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The best way to input images to this Inception model, is to pad the image so it is square and then resize the image to 299 x 299 pixels, like this example of the parrot which is classified correctly with a score of about 97%."
    ]
@@ -720,9 +601,6 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -759,20 +637,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Elon Musk (299 x 299 pixels)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image shows the living legend and super-nerd-hero Elon Musk. But the Inception model is very confused about what the image shows, predicting that it maybe shows a sweatshirt (score about 17%) or an abaya (score about 16%). It also thinks the image might show a ping-pong ball (score about 3%) or a baseball (score about 2%). So the Inception model is confused and the classification scores are unreliable."
    ]
@@ -781,9 +653,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -820,20 +689,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Elon Musk (100 x 100 pixels)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "If we instead use a 100 x 100 pixels image of Elon Musk, then the Inception model thinks it might show a sweatshirt (score about 22%) or a cowboy boot (score about 14%). So now the Inception model has somewhat different predictions but it is still very confused."
    ]
@@ -842,9 +705,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -881,10 +741,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Inception model automatically upscales this image from 100 x 100 to 299 x 299 pixels, which is shown here. Note how pixelated and grainy it really is, although a human can easily see that this is a picture of a man with crossed arms."
    ]
@@ -893,9 +750,6 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -916,20 +770,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Willy Wonka (Gene Wilder)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image shows the actor Gene Wilder portraying Willy Wonka in the 1971 version of the movie. The Inception model is very confident that the image shows a bow tie (score about 98%), which is true but a human would probably say this image shows a person.\n",
     "\n",
@@ -940,9 +788,6 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -979,20 +824,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Willy Wonka (Johnny Depp)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This image shows the actor Johnny Depp portraying Willy Wonka in the 2005 version of the movie. The Inception model thinks that this image shows \"sunglasses\" (score about 34%) or \"sunglass\" (score about 18%). Actually, the full name of the first class is \"sunglasses, dark glasses, shades\". For some reason the Inception model has been trained to recognize two very similar classes for sunglasses. Once again, it is correct that the image shows sunglasses, but a human would probably have said that this image shows a person."
    ]
@@ -1001,9 +840,6 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1040,20 +876,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Close TensorFlow Session"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We are now done using TensorFlow, so we close the session to release its resources. Note that the TensorFlow-session is inside the model-object, so we close the session through that object."
    ]
@@ -1062,9 +892,7 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1075,10 +903,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -1091,10 +916,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -1111,10 +933,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -1145,9 +964,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/08_Transfer_Learning.ipynb b/08_Transfer_Learning.ipynb
index c3caab2..af5aede 100644
--- a/08_Transfer_Learning.ipynb
+++ b/08_Transfer_Learning.ipynb
@@ -2149,7 +2149,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/10_Fine-Tuning.ipynb b/10_Fine-Tuning.ipynb
index 1f385fc..01bc5c9 100644
--- a/10_Fine-Tuning.ipynb
+++ b/10_Fine-Tuning.ipynb
@@ -55,16 +55,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -78,7 +69,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "These are the imports from the Keras API. Note the long format which can hopefully be shortened in the future to e.g. `from tf.keras.models import Model`."
+    "These are the imports from the Keras API."
    ]
   },
   {
@@ -87,12 +78,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from tensorflow.python.keras.models import Model, Sequential\n",
-    "from tensorflow.python.keras.layers import Dense, Flatten, Dropout\n",
-    "from tensorflow.python.keras.applications import VGG16\n",
-    "from tensorflow.python.keras.applications.vgg16 import preprocess_input, decode_predictions\n",
-    "from tensorflow.python.keras.preprocessing.image import ImageDataGenerator\n",
-    "from tensorflow.python.keras.optimizers import Adam, RMSprop"
+    "from tensorflow.keras.models import Model, Sequential\n",
+    "from tensorflow.keras.layers import Dense, Flatten, Dropout\n",
+    "from tensorflow.keras.applications import VGG16\n",
+    "from tensorflow.keras.applications.vgg16 import preprocess_input, decode_predictions\n",
+    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
+    "from tensorflow.keras.optimizers import Adam, RMSprop"
    ]
   },
   {
@@ -112,7 +103,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.9.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -319,8 +310,7 @@
     "    generator_test.reset()\n",
     "    \n",
     "    # Predict the classes for all images in the test-set.\n",
-    "    y_pred = new_model.predict_generator(generator_test,\n",
-    "                                         steps=steps_test)\n",
+    "    y_pred = new_model.predict(generator_test, steps=steps_test)\n",
     "\n",
     "    # Convert the predicted classes from arrays to integers.\n",
     "    cls_pred = np.argmax(y_pred,axis=1)\n",
@@ -538,7 +528,7 @@
     }
    ],
    "source": [
-    "input_shape = model.layers[0].output_shape[1:3]\n",
+    "input_shape = model.layers[0].output_shape[0][1:3]\n",
     "input_shape"
    ]
   },
@@ -640,7 +630,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Found 4173 images belonging to 3 classes.\n"
+      "Found 4170 images belonging to 3 classes.\n"
      ]
     }
    ],
@@ -815,9 +805,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc0e8042ef0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -881,7 +871,7 @@
     {
      "data": {
       "text/plain": [
-       "array([1.39798995, 1.14863749, 0.70716828])"
+       "array([1.39839034, 1.14876033, 0.70701933])"
       ]
      },
      "execution_count": 31,
@@ -971,12 +961,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc1178db860>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -1009,12 +1001,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc0e8079908>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -1047,12 +1041,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc1178eccf8>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -1085,12 +1081,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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gfogXNGSKRFXcKxXneeRz1dMbi80s746vcG87rpqG0Y0Mw4hQEmMyhFOEYaQ9jOy2a0x1YHm2ZBwt4+gwM8N8PqPMJogo2dyuGMeRYWipqoLHj56i04yxGymLyP2LS5TOIEoQkKUpCEnfD4Cg7weOxx2rFSgtSRJD13Xs9wduru84HBru3WvIsozzizPqckY/DEzqktlMMY4DWZahtcF7z2Q6QyBY3d6xXV3TtS3Hw4Gh61FSIZOa+48FZ+mMbmzphwPO9/hocb7H+R6EwxhNnuWkScpuu+OwP5DnGYhAmhuqSU7TH+lcR4iBICK6MMwu5pgqJZ3kLBdn3PvkPpOLisY1iDSyPtwRpWe2qDGdods1tNsGexhpu471YY8UKVrn/OznBfOZRgJaacqqhGPAOY8xKWUxYds12H7E4zBaEZVCekGdZJh6ihoFYfQkMiFPChKfkqSGoWuRWO7fnyGi5vXthn0fmN+/4GyhaW9XxLbh3etXvHp3hU895fkfkAlDGhS79ZHmpkGHGZ3tEVph8ayHlgePl+SJphN7tt0dXTginSFVJd0x8vbVHu1SwjEyHCWJrNAiZbc5UKZbDs2RXbfn2xcv0BvJw88e8OSTJ9TVDKmuafqOSTLh/qMH9F1P17cEEWiOLdk0ZXE5pygnFFlFt2t4s33J6maNby3BBcqsINf5D/LvpyECMRCHAWH6E/G15sR0AZhTjiAR3+UFvh8ivE8eCnkq08U0IkuYJiVTDWgoMQyTHU2z5e3taw67I2maovPAsPNoVaKipDnsqM5SkjShqkucc8znC/K8xI2OoRuJQFGUHI9bhBCUeUXTD9ytrjGm5OLiAXk+JUlLhIBh6IkxUJUV49hxPOxpDg1tt2d5PifLUvJcIeVIWXbEKCnLijQpSUyJTBXQoI0gzwpM0nM4HHj16jUhemazKW3TstqsuX77juZwSmhmJqWuayaLKfW0AgVCBUwqCWNk6DruVjesVncIIUlNihSCzWbLerXC+1MZr57UnF8uSUpF0x84dAestySZQWqJKTS6Ujz89AFPHz1FJgIvAtYOICNhv0UHw2RecdjvefN2Tdd09MeerunJdcH2dsNf/cVfEdDk+YR6uqSlJc9LprMp7djigyNEiHiEtCg8WkaiUmQ6IStSkpmiymu01ty8vKJ1Dcuzc0wpuB7est1sefn2OWfnl8REosqcIp/Rbzp2w55CO7weWG1v+eqrr7j/6ZLLhyXrAdy2Z6JKDj7QjUeqeUUyrxB5SrkoCYlndbilHQ8gAlJK3CD45S++5bAa+PzpI86fXlLJS159+YJu3XJo93z78ius8GAEz189JySecl7x5KlkMTljOV/hGsfTh8+YZlPevHzFmzdvGHzH3e0Gh6OqJ9w/n1KXU3714obrV9cMx5EERSpT8uI0Q/wh/CREgBiJdgRrwY3gBtAKhDrtUwkfhCzwf/URRMCA0O/rxJzSDHEI4GCqJnwy+5yrm7d8c/cNu+stzllciPTWEoMiBkNqJpyfL9FGU1Ul4zggpSYi6MfTSF7VNe3xgDYGIQTbzYa319d0Y2A2v2DsLYmBoAUxBqwNKCnwIXI8tKxWG9quQ0hFkqSUZY0Q4KxDq5zgBT/72TMePXyKcyBVRGAYXUffjxzblvV2zXq3Js8yfHAIESiKlKoqGPqWtrF0oUclCbUQDG5kcA0+jggZCNHSjw1te6TtGkQUxDRidMo4rrHWUpclzlqIMF1MKKYZTdMx9h1GKyb1BGt7toc1y/tzkssH1GnNodkRZDzFp/0RJy0KTbSB6+srRCuJQdDuO7IkZ7qYcxxa9qs9f/kXvyBEyb/9p/8eap6g3ckn4IcRJywxSCQOGQa0EmRpRrd3NP3A0HZUKsekp5h5fbfh0O+Ylw+psgxnFhxcy4sXb9n2I1V9j7qekGUVwUWq8xLjW5bM+Zl9gkwyrLUkckahCpKgQWqO0XJ2b0J+lpM9XFAvK0jAhhEbLFJGlDBIkfLqxQ1/8Wdf8O/+W/+IT57+A2pTUsqaoRl4516B9VR1Rj1f0HQN/fOOrEp59uRnLKfnxEEwq2fISvHpzz9DBsHV3TvSKiWVKfvDlt3qyPXLOxblQ8Ix8vbXb9ne7ChNSpkXBDxD29EeDz9Iv5+ICHAykAwDQqkTkRMDaQVzAxkn8ht+Y0ohAO79NgIFUHEKG9T7yUKURBsRqeCivsd5eg+5V4SjRyiI0SO1oB8c0iQ8e/CQsvCkiSFE6LoB5yJ5dsoU294xdj2HpiHPMpbnZ+wPe9brDdVkgQC6riPLHbEfkFIghaYfelZ3G9brDW3bIKViebbkyeOnSCnY7/ckpuDi/DF5XlGVFTFqvIsE7+m7ERccMTrarqXIc6qnjxnGhvXm9pQ5l4rJfEIECGvatsFoQ5aljOOADwNCWBAjzlmapsV7T5kXjINDCMUwWJQL1HWJUNB1PXVdY3LFYdiDUGht6MYBGWAcRtb7DSpXVFmFDIqEDJULunDAWoeXkeW0QKead0biIyTGAOAGSxw9WhqyNGN1e8svfvHnlFXJ5z8XhDDFe8/oBnSqsePI2XSCG9bc7fcYmdJITchTdCL4wz/4I15+/S3rdkuqFWaU3PzqLd20YpCObFGRX8y42+/oj2seP7wknSTYTFMuC5QPTM4K0nnN3eqIUAopNIlIib0nek9ZpywezcgvExafPaA+K2jdjnbcYr0lekGMEtt5/uxf/IJ2N3K+uE+MknbokalkdlFjsofYsePzzz7jk0//iLYbyP/XnNevXuMGj8ZQpBWzyRyJJCroxp56OWG2nOJGz4tvn7Pf7Rl2nv/jX/+Svum4evOGsRmQOjDTNZOy5sXNFimSH6TfT0IEohT0QpBETyIiItFQ5jAxUHI6y8CJ4B/2w/vNv7+f8D5XwG9XE96LhoyShVliGoNdj6QzQ1CKTg7oTGFURsDSHQfOHi9RRhOjoGla9vsjVTlFCMGxaejHgfOLe+RFwXq3RSeG2XyK0oLdfktRLqnT8uTm45TzGIYe5xxVVTGZFDx4dI+6Lnn79h2vXr0hTQoePEjJ8yneCQY7ctz1IDzWWjb7FVWVEYKjHzuSRNF1Dcf2QGJOoVOz2xPxTBZT0jxjeXZGXuSgT44xZy0igh1HRIC6nCArhbUeOzqkUqRpSl7kODeglKAsUqQWdK4jITs5HoMgjIGm33M4bBnDgGUEAUJLnHc475EolIykZcaimtN9arn96o5m32CMwdvIbrejXsy4WJwx1wuSuuTm9i1SCf7g539MkqUcDjtUL7DBY3SLiQotEoY+AAmLiwt+9vgReZli9tesX9xyOVuQKs3V87dc391ys1uRXEz404tHnE8mvPzi17jVr7CfBNCB3u6RnAR2cn/GIAVWeCIKomYcA1mRU5YlyVQgC0c+i/R+g7V7fBgJHopkQtM4Xn71hrH3PH74GNu3HI8rlIQYR86fTDmPFda23H9yD1NrZtOUx58+4vnL53z7zbcs5xdopSnyinEceP76OQJYXMy5XF5iW0scA8/b58QOrlfXjP3AcBzAwsBIYxoynZKqDI/7Qf79JEQgCEGoc3Q1Qc7mMJ/DrIRCfZcaEHznD/gA9/5+CaTfO+5DR0QEwcmuKaPkojwn6TTN2wNClegqQ6cSlScYoWi6NUPTsJyfMV/MmFQ143gq22VpRZZkaKOZTCYkacq+ORCiZ76YUk9OP9bt7TVldUZeTLF2BALW9YTgyfOMLK+YzkrKomCz2fD8+XNWqxUXFw+IEdwYGMXJPHI8HoBAkmnatiVNJUJA2xxpWoeUkTRL0FLhR4fSmqbpcaNnNp+zPL8gyfOTBRWNIqXrBrbrPZv1jrIomdT1KbZ2DVLKEzldoG0bggiUk4ok1wx2RKBx1hFcJIyBXXOgOZxmNj46XO+QQiGFREuDVgahTuYnGxzlrOQ2veUwHNG5IUk0PkQm0wlnD88pljUiUVyvbtlsrlmtF9R1zX63ou0bIgKTjIzjka5xKFnw8N4TLi8umV8seP3qS+7GDWEiEdOTuWt3bJkVCwrleP3tHS/+6g2P/uAZplfcvHuJH+D+zy5IJxobBb0YmFQTZsyInSMEgRAJh7bHFx1n9ZSkFszu1Zh0YHV3zTj2FHlCojISmbJptvRt4B/80R9ztrwkuMD28JbBdqSF5tnlIwB8L9jaFWMXSWWOziR5mbHdb/nVF3/DbDbHJBohoe86YoxcpOdU04pRjBiVomJKtBFpBaUpmCwqovM0ux1DM9An/WkmEX64TegnIQLCaMqH99HzJcwqyA3oU3b9N1P/DwIQ+Y7kH/KHOadQ4fv4cMwH8ZCwKOdUMceuWvo8UucpRVFg0hQ3WHa3K1Z3K8q8RApJOSkps4KmO5X70izj8t59lAi07Z7b21uyPGNxNsekhrZvadqRrHhLWU2pygIfIkPTI1Xk4mJBPS2wtuPtu9e8ffuW169foFRKXVVUZY3S6pQACxCiI+LIspwiz7BuRCan3oGuP5x8DVIwjCPBR/KiwDto6aknM8qyIgpBDB6tDYO37NZ7tnd7hs6SSI+anJJqfgyMbsRZj7U9gxvJq5SiKtEmJfiADRZrLQSB847jbs/Qd9TFDC00nRsQMWJShQ2O0Q1kaYIQiq7rCDpg6uSUVJvm+A7apqMfe47tEVUrfIhEYYlC8PbqOdVxgreO65sr+n7k7N4MZGC3OzIpMy4v7vHg8oLRHXh39451tyJNJWEqmDxb0nUjYRdAGVwf+eJ//4L17Y4iidi2oVmv8PdrslrjtSSIiBeONNW43hNsQJsMU+Q4FXDKMZtNmC1rtsdb2uYWo3K0qJAyoTmO9I3j7OyC+/fvs1wuWG9WbHd32GZAl4KeA+PYgxLcNTfUIVJlU7x2PP38KWf1BbnJ6dsBoSTd0JFmKTEErq9vOK4b3NFx/eYGFRQEmFVzEqPRUiJ8YOUjfdviRkcIgXG0P8i/n4QIqDTFPHkMVXqqAghxIv+HSsD3bcP+/V5wCgE+bH9b05Hgt1yH2qSc5RMmZPghIqOiKEtUaji6EetGDtuWze2OR48DRiakSUEkIdEGow3lbIoicDhuEFIwm09P5iFh6K1HJ5oYHc51SJMTrMf5nizTnJ3NEDLw7uqG129estttT06ysqYoC9IswyiDtREfHGkC1geUcpR1yt3dFbnMkUriQ0Aohdaavj8SfMSPI1lWkKUleVGS5jnBOUTweO+4vb7j1Yu3jL1jUi2YVVPOF5csz864ubnm6vaK3rZIDVVdM1tUmOQUFgkko7WEGE4jf3Dsd3u6Y0tGwbE50Ox6siwnKs0QRlz0KK1RyuBtACPJFyVtM9CuejarPYf9kaIr0LVCHmFgQL0Pb25uX7NeG8q8ojvuGcaRY6MQWuGsgxDQRIyI3G1WRDESlGNMBHd+y2I54+wPL3n5l69YDxtMphE+srta0WX+1HgWLNUyQWYLkpkm4GgOe2ILupO4bCBawXxxhi4LsmnBdD5htCNdeyTRijzLmZQzIGG7viEiWZ7NWCynoCxJEdDWkxtFUWra8cgw9GRFjvcRaQQygfn5jCqrOJ9doknZrnaMw4jbOLIiI0tSXn79gq+ef4U9esyoWeRzhsGRJTlaCqL3KCmpq4pEKZL3M4kQf+LVAaEVTLPvRv7fPPG924rftg2/rx7+ptno+2XD75cSPyCcmgPPygmPl5es8x5jclReIpREyYa6KDmbn3E2X7KcLUl0hogjiUlQyhBCxFnHsTvS9T1n52c8evSQY9vgvCDJC6p6zrMnn6NVyuG4o2kbmmZHiI5w17Pfb3j15jnD0BGCJS9SZrMJRZ4RfKAbO4YhEoVDp46xG9gfRsaxZ7tdE/UMkyRkWU6S5GipEGKgyDOcdmhpGIbx1A0oFVKDG3pur2748pdfcnt7S1kULKcFi+kFj+8/5dHTx8ymcyKBq/U7pA4U9em8pJJ4F5BS4+xw6g0QYN3pfLpdS+pa9ne3tMeB+48fILKMoDzSSFzwtMcWYUGgUaXG68jdfs16u8WNnsmyIi+zk406BJCRiEAIf5optA3eRWJwHHYbpNZolWBMZOwPdF3Gdn2LVpDkBqct+7BHAmmdIi6gbHOW6pzElLRdT9NvCD4T6pAAACAASURBVEEw2I7tesX0oiCfzgghYNsWf7C4o2Dvc4ajZxgci0czZg9mSKXYbVYEAkanJDJFCUPbebwTLM4W5EVCH44cjztGe8TGDp0L0BHnLCiBCw5lNFJHdCLJlzUHGl68fU63H8hNwaSeUtUlAkGRltTlhDC+oj/2pLo+eUGEP3V+ag1SImMkz3MkASEi2hSo5CceDgDvyf+ete8z/L/lBfiwl79z+0My8PsJwe/PHL73mPCBMjHcWy4Rec+QFkSdg4wImTCfLrmcPObZp085my85tC3Bx5M9Uyqsc/Tblr47UpYl9+6fcXHvHHcV8FEwLybcu3zIgwcPefPqLe+uXhEJWDtyOGx5/ebA4bDFuoEsS3AiorUkzRKkFHRdyzickl0miSB7fGhZb3aMbqTtjiStoahLTJJDlPgAoJjOFiQmoTu0HI/XxChQ77sXN+s133z1De/eXOGdJ46w0Xse33/KtF4wreYgBDera/bdDrSnKHPyqsSkBiHkqUPRRpLEEIWn61v2ux1hDMhEMOwHumNH33WIAVw+YqODvkNaQUpKVhvqNKPbjdy925LXI0YYzu9fUM9qZB5RBEbXE+KAMQI7BNqmRUlNFAIxBrADYxzYuMBLLRDKsm929K5FyohUEWk8fTziVc/kccH8fIoJJd4pmmPPbp/xqEjJU8PgOrpjh1pJpI4Y7zE20mwOHLsU7w277ZGLGCmqkkO3Y+gcvbckRYZKc/ousl7t8d5z/+KSKAeuVq85thsiljTL0CbBB4jv/7whRFKjsd4RhGdwPcfuFNa8e/EORcInzz7l3tk9hqZn12zR0jCfLklcg7bq1G6cGkIIpHmGloKxbRnHU0LZ+xGT6NMI+AP4aYhAAKw4nc2H6b/nRPAPZzjynQB8EIgPlYIPQvB98sNvNx0BhIj0gSLNqEqDNxqvzKn3PUrKcsqnjz7l8sE9bDx10cGpk0tIibeO3XZPiCOff/6MepIhlCJET5qVXF5eUk9r2u7Ize0Vt3c3ZFlCiJ6+b+n7FiEiZZkRoyfiGa3lcNyz3W0pC4HRJ9eekAMujCAs+/0d3TC8rxQMhFBAhL4fTlZTFJN6hpIKozP6wSKlYhwGuuOeV89f8O7NWyTytHZCO7Db7LFjQIpTKVJJdZo5KEVWJExnU+q6wqQCLU/xdAjx1MYaAofuSNe2ZKZgUkzwUwh2Q9+NSCuJmWf0Fi0VaZJRiBKVJmR5TrwHb7+5Yiu2JJkhSROKIsdUgs5HpD21WrvRnfoZnGYcLFpnGAJ+6BldZLdZcWg2KB2I0THaHp1LVGrwYsDj0CYlX5QUsgKb0XWRapIgasPThw+p84Svv/oVN7c33NxdkaaKy8mUOmhi0xNcT15VzKYzjEno+wHrPW70gCbTFUbmJEnJYq7YHXegIi5YbOhxcUCIiNTi/TIVEmM0XgSMkad+fyXphwE/eoI4uSuHfuDdqys2uzVPHz5lbCzNfo9tLEYYirQkBEeIgUTp9+GuhuDo+o5hGIFIFAHrLf3Q/SD9fhoiACcifyA1gOV0dgnfJQW/Xx343ZH/w+Z/5/0++AkiMAZUFCRpgsp6VB7wiTstMmEUs6rm7OdL0kxz3BzJFwX91uNCQBEJAjyRECPFpCYrEwIRVCRKSzmRJIXnuDl1brX7lncv31IVBUWZUegSTIY0kdXuDk+gDwPvbt9gspTPZjX1JCF4R/Aeo0qy9GRvPoUcJ39/kpy8/d5CampSXTKvHhJ8IKaelJQ3b15wd/OGw/UN1199A5uWuSpR0tAIxaysmZQZSgW0iQgf8GEgRsd0NmMxn5NlCVqd+jOOdBACArDDKSnVt55qWiDznGKpiIcdd/s1D87PmaUVOQl5mpEmBSFIoopEI9CZQQpJ6ALBRZQzZEVFnESCs4gRUi9ItEOGFj9a+hHGCFJEvHSgAonx2OOW9etXPH74CCNLBj8QoidqQZQOISJBOpzsiGIAFQmDIw2BJD0yekU7HDkeG+zoSZUh7xxoyWglNgvMJprPFg9IlxnHbsuAZdc2lFNN1I5RNpR1zmyW4HaS/XDNMDZoDak52bv94JAClElQ731wUkOUjgxg7AneYRJLNVOYdImQjirLmS6mTPMFb/p3vHn3hmFniUNAR0kiJcKfFi4ZuoboTsk0nSp0lZ+Swwn4dgv/6m+n3k9HBDSn0T5wIvAH4n4wB8H3RnS+E4sPJP9wJfF39p7TLCMAzUB0oBKNNJGkUohK4I4DygjqRYVeSI7dgVE76umEPgSaY4c0ijTRTMQUraGclGSFQUiPyTVtv6cZtySlpO8tbnC0u5Z3z99xvlySXJyjE4NOM9rhQNeMYE4rGLVDQzsekMYR6DkcG5x1p2m492R5STYeORwbTApSjoTQoWVBohKIKZmuTyvbhIFsKrl++4J3716zef6K7maNOoKSCVmWkqYVD84uOFtOTiO9ATlGjFFkqWFS1dRVhZEaIzSeSKd6Yoxs11turq95/fwtRE2SVrTOc3AdB9/SjUcE58zLKVmRIbRitJ5uHEgSRZQRoTnV45MJctCI8cQIn3piliJ6gezBd56+7enHAWk0AY3T/rQmRFTUZUq/6Tjc3JFcPiFJK9zoUUJj8hwvBmLwKCFxfsB5S5CeUfaoENjvIoEUnUA1qemPAWEVh53Ha0uqEkYdiXmgqhL2/YpNd6TxAwOg4gjjQEgdcrAEGRlEzxh7etuBjxilECESrUNqAX5kDD1oQVCaiMaPLYkxBGkR0oH2JIVksihI4mmFpzpdcCu2jEdPHAS+9xglidEhlSBYRzP0yCjQ5tRWLgrB9NEMOTOE4++Wz36ben//+H644r/3mOc7MfiwN9877kPoIPjuShTfIX7vzS349YHu0OLdKWmWpTk6N/TdgJOnKfTQebpmRAlFdKc/q5aauq6QSnBsFfN5yWxZ048NEU+ap+ybPV07MKki3bFlv9qgfCRPEoJztIcj1bTGYVndrnEuoFEkMkMmCoWiPbSMx5HNasexaQghMp3WlHUFyiNURAjFbrdnHAfKvCREi9EOF5pTV6U4LcUViQzDgB0diUlxWMbRIuRAUVdU04qsKE7XPIzY0ZGnJVU5QavkfZ1fI6JAioAyin4YePHtr3nx/AXewqRekhcFdrTcrm6wfmQ2n55mPWXOZD7Bh8Cx6Rm9xfvhtHZMmlDVBUmqGTvP0HWnZJZJiNIjVUpwPdv+1I1JFJjEIEmxoiNqT5LmJCpl6CzH7cAooShykmREVxJSh4ieRCVoJ0+OSyHwzuLtaWmynT2i00hZFxhdcEgH+v3A4W7HgORyuUSnGUFI7jZbvn7za2Im6XDMLs4Q8mRTj9HSNgdsdFjn8CGi5GkZtsQkp6XwrD0VvLzFxYAUCh1Of+Mu9DjviSKeOuTfr6CnVQKjwI2eoALd8ZSjStMMHwVKnnpTEmlO4ioF3gWC97hgiSPUAiaTilb8/7+oyP87fCD++/X38MD4PlcQIvgI6fdKiB9E4IMz8HfDAyB6YACxtxxu1/RNBwGyNMPkOa0CKTVJkuI9HA8dMQiM1HTdgEIwn01ZLKYMrsPFI5N5hjKe9rBDKkmaJ8QIXTdibeCw3nO425AqzSQrCD6SqAQjNKvVHeubLcJIEg9SC6RQhCEwtiMojx172vaA0Ip6/oD7D+5xOFTvO/8G9ocG7x1pOoAQZCrh0NwQHaRJwnZzR9cdMcacWoMLi2tb+tHiho6UApMmKHPKJg+DZewsWVKQpxXORvre4U0kOo/QAu8Du92Oq+sbdvsD88mSJEkxiSHEwDAOmFRx7/45VVUi3/s8AgEhQSmFdS1BRkySYVKDC47RDgx9hx9GclJQKTFGDmOHs5E0K1AxMPpwWpsx1adqEhGvAt4oRjWg64x8VtMcW/5P6t4kRrMsPc97znSn//5TzJFDZVZWd3V1s0k2QYkCSEm2aArw1ksv7IUBwxsvDHinlQFtPcArAza8MeClvfLKBgwTogmJYosUm+yu6hqycozxn+48nMGLG91sCGxJtthA+wIBZEZkREb8cc+55/u+931etMeL6TYyUqOlQqJIIo0XAhVqGrHD+YkzqKPA/DhnebSiK3puNOzv9rRuxGQZdTfw1Zs3bKsDx09PSYwkSRVSeTyebuhgYOobWcdoRx608Jg0wXuBtQEhHC54nPfgAyJogve0vqcfxmkigsJZEE4S65SuCuzvCnSWEUcpi/mC2lV4o6a+UhixKmBMjCBQVQ1BOCyWtu3IuopVdEoyz37usvv/vAkIIZ4C/xNw/rDk/vsQwn8rhPgvgP8YuHv4p//ggS3w868QeLCIgXUgfsIL8DDKyTbsgPGhDhA/gx/7ySnB8pdjxJ+cAALQAYeB/nbD9u6GcRyIIsNqmdKmhmqoMCYmmcW03YA/1Bgd0dgOnCfPMuIoR2voxgGhBgZfU7UjZb0lihOSeEYIgqbuKQ8tu5st1d2e4C1D3TGOlujkHOklxaZkbNykpBs8SI8LI4aI8XRgcbxmOZ8x+gGVJayPp8593fTUzUCQfnp9RGB0HUI5BqfY7t7ibGCW5ByKHdYNWGvxHiKToLVFKEeQYNKYbD4jTiLiOEYpg1Yx82xF2/WT+m8MU/1twY09dVdhrSOKE/L5kjxfkmYzTBLRDy1SwzKbsT5eEM8Mzo80XUVAoozGOIcdp5tWyEAym+TIw9DTVBVtWXHEEoJitz9wf7tlaEeydIYRAd+24AVxEqOjBNsHRmHxUcDHApEozCzC9wLvHdKDcGJi8o0K24LQhiRNaaylqUdECCySlHSWkmYJWkbMFzOiZNogY5kg04TruxtevnnL8eM1J+eniCQwhgEXLMIrbD+AF9OpquupmwqlJGmaoJBoKRmleGDkCKQQKBQyKKRQDN7hnZtwYgjcIDBek0ZzRt/w7vUV/cyRJCmnF6dIIbFupG5KgtM4GVBaMPQDxVCTLzKOjk9paNCzCGHkBOj5Ode/yUnAAv95COGfCSHmwPeFEP/Hw8f+mxDCf/mv+4VCCBNA1AZ81yGIkFoz2egkRBqsn/4+Rn9pJPrZnoF8+Gn+xdKiHhg39xyu33DYX+NchzQCpQ37ZqCoSpJ8wSyecX99S1uUpFFKW9ckOiLWGu8s49BCGBDKsituaUZDZ2uCAq1jpJB0dc/99ZabNzcUtxuyfAY2gPW0dUvTtFT7CuEkaZRgraMbWsq2wvWei7Mdq+USYyKSOCIYRVGUfPHl19zd3WPdyPmjU1arBcXhjnHsIAIvGsrW0tUj+4eyIvjA0PcIJHk+xw+KSGeISHP55BEnF6ckswxtDEk0Q3hDHM9wPtC6lihRRLEiBNiVd9RtTZwknJ6doXWCFobZbIZSiqLcE8WC47Mj4sxMdmXhGe2INjFaKQh+okCbiXOYzGJMqnHeYocB7QW5Trkq7rh6fc3mZvNT4nAyi5nnC9rSESyISEwnKKWQMRB5qrFkKVfEaUxrR5RTGJ+hR4mvPLt3B/rBEc0yiqakLDvSLCZKEhbrCc3VNA0SQzSPOH/2iFTlKJ1QjxNoNF+uiZKYEA00dU+cGOIox+gIhSQ40K7HiukEleochcEIzyhHButACIyIkD5CuYhYpwjj6b1l6C3OM9X9UnCyXhGt52ze7thut6yyFSKCxdkcqSTyIBn2EyhnbFqGcSJu52crXnz7IwZtaUOD1+DGX8CIMIRwBVw9/LkUQvyICTX+//ry3uHaHryn6yo0KVGSwNASgkKm+bQBDAN0D/NB97Cz/aRMcExS4/AzrYBuYNhuKe7esd9d0XYF1vc4Z6l3Je83Ww70HB8/4mR5THk4cN/sH8ZlkhA8XddNAJG5IUkjqtFxt7khnkVESfwAzqyRQdK1PdX2hps311TXe9JnGUfzNb0dqYqKum+RUpFHCVmW03YN1llCB5Wr2dzuODo+Jk4nyGZZFVRly9XNFoHk/PycD599TJwKXr8O3N+/QUiH1CNdU9OPHtsHNnc7vAWcYDVbsMhzjKopohonA7PlnGw+QxqNCwIhNEk0/Z9u7kloETGYREEQHOot49gjpGCxWKJVQlMPmCSmqEruNjdkeczqaI6OJFFiUEZO83ABox3ohgGBnBDaUqASRbZIWR4tmGUz+qpnc7XhenPN7fsbhn4kjRPqriaZJyzna7ANh67AeUsUaaJYM0YSFQd25R2n4wnL+RwqR3MoqQ4N1B67H7l7d09dN8R5hsw02emC08sT5os5loBzI/VY07cjmpTF0Qnr2Rk4xQvzCY8/ekY0kzjVUrTlZDefr5nP1+RZjnKSw7akHw7QGJwLJKs5Jmi0NAzB07QFAkUUx4igkSEijRdoDUNVYGtLahK0CygfM4uXxKcJxia0ZUvTNeADs6P51HRdSdSRJskzdm9up2nA6YqTR6csL48Z5MBQWrowENQvWCwkhHgO/AbwT4DfAf5TIcR/CPwx02lh9y/7fOcdfVcRfKBuKmYEIiUZhw7vNYmdEcaBMPTIRk1kRR5KAh8I/QAIhDJ/ySa0A2O5o7x7z+72mqo8TE8iqTAmo9gX3FQ7ssdHnJ+ec7xcUhZbrl/dMbqO1XKN7XravmGz8+TLmOUyIxSBrmvx0pLPc8ZupK52+F5T7Vo2VzvKTclQ9dRFzdH5MZGIud/vCCGwmM+JogQh5ATcVBFZPKNzDWVRUxQVJ8kxUkdUxT3jIEmTnPPTxzx6/JhHl8/ohz1RPNX1Uo4431A1B5RICEIxDB111aOCIRKGLJ4kyRQ1dddMkA4c0kxdVDc6DPHUX4hzjE4YRY9S0/46DHZ6SsqIyCQcH8+RokAZzfvrtxRNQbY+xYnp9Y2SCIRntJNzse+nbIJZOidLE4KT6ESxOlsjagl94NXXr7lt72no6JoObQwozxBaXLAkWUx6uSDc9+yqmiAk3jqECGSziKY90Pc1SbQilSmv37ziqz/7knAIxKNGWqZTR+U4f37JannCbDFt0IfNDmE8VVNTFQ3r5TkXRwvyxYosnvNh+jFRpGj6gne3ryjflqwWa46PH03GnDGiOnR8+aP3vP7yFdvNhjSNOVs85nh5BNLRlI6+LBAElNUEK0hnKfnqiLJvaG7vaWrH8aMV8SpDeUMW5UQy5uRc06Q1u82GbuiQKUQLw2KxIL9YYnHU+4rVyQk6kTgs23qPM5be99gwIvQvphz4yQaQA/8L8J+FEAohxH8H/EOm5fgPgf8K+I/+is/7ae7Ao5ML2rYBAk1XIkXAaM0w9ATniAdL6AfsMKJFh4zMtBF4T/AB3/f40RKkRnqBcGC7jnJ/z+5u89PjsRAaqTPiNCPBsJoFLi6f8MHjp8wSxW6/RLyHui05Wa3RqaGtRu7ubshyQ756AkEgpUYGSapTRttw2BxQNmZ3c+Dq1RXSCpRK2O8L5usVKtVESUSQYaLFigmfpaQiiWOkXqJ7TQiSrukZbUCqCKMiTBLx9OnHfPDkm2RZTmRSimKLFIb5bM44Hhhtw2hbbBjpKkAEsiylrx3vr9/TRx3H61OCFNhgJ1upEiRpgooUbvREanrqG5VgosAkNfeE4GjbgbqsSVM9NcWSlCjpiSJDXVcT9cdb6qbEJFNXXMjpa1hrcS4QxzFxNAmSgpDoTJEuDaUJlPuKsbE0sodMIIVE6UCQw6SlsBUIx+XlOXGiCK97WlfhxxEBE4h06CkPB2zraYqOd1/csH1TktkMeocOcmrYJQPp82SSdTcdXVfhxIiIYLPfMw6WJ88WHJ2dEOuUKEqIsmTKSUhXHLmWsis5Oz9ilp3w/u01b9684+79lpvXN1Tbkfbg6UTL/qrhdKWYLXO0rRgPYgpWISU4hXOGkBtimWMLQbXpUacx89kRwkuMiVFCkS9mSBlox2pChmmPSjXr2QIZGV69eY33Himn331RFwg7MSCDBIREa/UvLsG/nk1ACGEeNoD/OYTwvwKEEG5+5uP/A/C//VWf+7O5A99+/nEoqz0CwW63oTwUjMOAFhKtFO6g6Kp2IhDhMc2kbJukkJJgR9rqwOgcymtcHxjbjrYsGFvLPJsTZyte377DNxFl2fPom5/wjRen6GPFejYjn0lW8zlpGuGHkWyWEhsD3rMvNxRVSVlW9P0IDoKT+AE0mvZQY9uGpqhx/YhRM6wUtP1I2w8o6fA8uPDsyHy5nEQdMhDpmNikLM0R6TLDC8XhUKNiiRYR69UF33zxbS5OnzJaaLuCofWkUQ5hzt4e8MGTphFjF7BjT5xE5NkRdTJwt+3oxunp39kOZMAkBi/8Q+d+0vcHDVIo8A5jJhmql5axH4ijlBCg2O9J4oy+6yfIqdFTak4syRcz0iyZ7NT3d+TzOWkyNVSlnNRy4xiIU00QFi96zEygUk+QIwrJAxQKJf1EP9YCDLTDjrorGMPIo7PHeDfw+upLrK+QWiIJ1HXHu9dX+O6arnZ0+4FMzcnFjFTExGiasWJX37O9PSA/PEKlhqrtqfuK0ffc3t+SL5aksxwdGwY74ocGHUXEcTTV9NJwdvqYfJah5Iz1/JIvD+/4iz/5MX3Zs56tOJk/xg4d+6uaT5sv+dZ3PsIdoLkbp8yAfE4azfnq81dcfXHPb/7t3+Rsfsn924K+HCmpCEEwny/RqcZog/GGbJ6SzhLKpubu9o6PPv4m3gt875nHCV99/mP2zZ715Zrnnzwjmhl2RU+axJj4FwAVEUII4H8EfhRC+K9/5v2XD/0CgH8P+PN/1dfy3lPXFQJBWRYooUjjmPghkks9SGSVkJMkQPdTjeMDCIkfBsaupe86ZIhQYRrHxYsVp+sFgZ6y3WNRtKPkvuiZrx1Pfu0D1o+WFP0t1VByvDzl8vQYLQzf/vbHXL+/Yad2XD56zHyRsdsVdL0lNjnBetpyoC07+mogUTlHyzVjMVLXliAls/kCk8RYMS1+E2vSPEUaGNxAkA6TJihtwCiiOAEJh6IhyyMeXVxydvoBy2yFDhFCSkQEy/kRLhSUNVMNqxX5fEGrRvpOoMU075/PJLqB+q6kGyZ34KPLS55/+Iz10RKhJneZkJoQPIiH2LOfZD+gUDImz+bk6YzD0DyMHZNJe1WXdGODiSX5ImW5nMAqQkyCqeqwZb5Yslwsqeua4lAglEfHAqE8i3VKfZRQ3BeThVhO0VppYgjKo4wlnmlccGw2tzw6eca+HZnPlnzjxcd89eYzRt9NkmIybq8PzOMFTdnjRoFWMX4AiSY4CV6jVMY4CIRWKBMDBh8k4wghaJJkholTghR4HKOfAm2CBBCYKMN5QfCaEDRZuuSTT36Nm683/OD7P6ALA1ESc7a6JPIJoRZs35dstnv6zUAzDtyO91yeJbSbnpvbW54+f85sNmO9OKKtW4qyIghBlBhOT45xUQLAcrlit9nx4z//MdfXN+yuD8zmcz7/8Reoqubd668Ztef88pgwWqqiJYkjVssVddP83PX3b3IS+B3gPwB+IIT404f3/QPg3xdCfI+pHPga+E/+VV/IOcdhv0cIOBwOGK1Z5DmYCGcdtutxoyWOEoQAreVDbtwkDrDW4kaH9IosykiSHKEMwgik7Oj2V+zvDmyKA5tDgyOmLAL3VyOPX5yxPF6zuX/LaD3fePaC7d2evu0RwHq1nqaVwTIMLcFKhDO0Vcl9s6erWoptiZxpZvGcKIrY+ZagDOk8I5nPkBGIRuCxaKOmn8FMJUIyS0CqKW9QCKTW3N3vIKS8+K3f4OLiBUbN6LsRpSLSKEUtj9kXb6e6XySkicBocEPDeh2j1YxIpeTpknUy581nr9nc7lislzx/8Zz1ejVJp7XEhxEJjH5EaEUQDxmMUhJ8wAiNQuOtI4kSjlZHpFnKeD/w7v0b2q7ixUfPODs7Qakpl3GWzclngc1mO7ndVISRCiMMVVEhjMX4STuvdEAZh2LqASACxhiCFigVmM9i2taz29yyvbtjFq0Zxp7zJ8d8/I1P+LMf/gUEw9gPuNZQjZZIp5xfrpCtQBwcqpW4zhKTsyAiW6yJshnSKKQ2SGFAWNIkZ54viaLJ72GDRyGwrqe3oFSE1jFGCwiCEKbf5TdefIPmbza8f3nF5v0djahZpDOW2YK2rbl+eU1R7PElDN3Izh84mz1hGa257u94/fIVn/zqt3n65DFlU1MWJSjB7e0Vm80t68WKy9NLIhR37+948+Vbbt/dUl83xHHK7d0dJ7FkOUuI1ymxFDTFATUznJ2fMJvljN0vQCwUQvgD/moX/79e1sDPXN47imLqgFflnshEdM0SIkff9rSyngQ1YQq3NNpMwgw3KYaccwinmJmcbL5GJhMqG1tT72+4uXnF7e6Kq+0NX7+7Rp0+5Sw9oj546s3IJ6crsnXE69uIs/ya+9db3nzxhtl8xsnxCaMbGceBw8HStiVZHDO2e2zoECMoJG3dIpxCGYFONV5rknlKlEZk85jZMmV72NC0NVEUYRKFjDJWqyWj8+wPB6wbSYJBhIDrRxg8qYwxOmbsLOPQEamMNJ6hg0F6xXpxRJQGynKPdYF8sUSJeAruSCWZzNmvU/b7HYvljMePzzFGMvYtepA4J1CkeCTaGFSkHlyVkjBYQhDIoPFuuvG1lBil0EZQlDuMFpyfnZIkMV3XkyYz8nxFGufEOme33TEOHiEcaRQzeI9zI4mJMYkiTROiWGO9ACNQRpEkBhMpnJAM7fhw2grcXt3yybcu2Bw2HD7f8yvf+y4fPfd8+sMv0XJCrx32PZdnSy7PLlmolPau5uarG4QQHK9OcQZm5zlxkuF1QOsIhEYEidYRWk6OO2dH7DiiIkEQjsEOKC+JTYoxCd4JpILwUFY9+uARH3/nY/7w5pa6qri9veGDywvGZqDrGhgDuZwh6QiNozt0GDSZSbh6d8XjZ4+5eHRJnBpkJKby0Q68fnXFfr5mFS9pB7h5dYsrRlZmgWonyXvaa1aLGRcXR1R09E1NstREMqGtatw4kjycJv6qnVLQvgAAIABJREFU65dCMeidoywOSCFoqhJrIqq6wA4DbdUilSRPc+I4wo4DwzhMSGfrJjuBDwivUMIQBkvXbxi6gq6+5+7+Nbe7GzZtxZv3b7m637KcHXOpIgwp7QFsJzidzxDyKbJ5zRfj19xs7qirliPrWJ2sybKM7XZD1/Qsk2n+q4Igm2X4EzjsC9q+QRrB/DhHhoyj8yPiLMKHh7LFevq2RymNjBRJGrM+XtL3I2V9IPgRJWA1nxPcwOuXrxA24dmzb7FIVlRNO0FCVEBLTZ7kzGYCL1r61uG9mBKSg2d0A2W7Q3aCYDxeOO63d5RlQbpOsH6k61oEGge44IjjCGVibHCIoKeTlvMYGZNEKU074Kxl6JqfJkPns5g0NQ8pu5rIzMizNZFO6MyAOjJ4N3J/fw3Bk8QxNgQOm5LxvsP2dkKcxQkqj7BqKkuC6/GjoCs62saifMrbl+94/uEn5MsFf/THf4RJU379u79OuR3Z3RYUsmOUAa1j8sWco/mau95yGAsUhkfnS3wkkbkCJVFqeqgIIR4CsT1dU9HVFS6f4dxIIMJ7O2UfKEFskinuDWjaktgYiq7EipGzRyfkqzlWdRTVnpuba5qihtGhpJpORF7TFB1vXr4GBE3ZcFfekPwgxnlHtsyIjMbhUUqSJQnlruTTH3zGWA7cv9swkzNULNBiUkJanXK2mqGkYqha4nzSfwzjwHCwREnKarn6uevvl2MT8J7qsEdJSdfUeDNSFQWD7mjKScGXmBhrR9qunQQXJsK6SYZJEBhraPuCqrqlbjYU5R1Nu6fqCvZ1yZvNli9evcXFCyySQ1Gysh4VDL4Dk8L5PCOOP+Ht0RXvXt9ydXXFoah46h3LoyVGayIdURc1Y+emaUOkmM+XDKNld9gRgGSRM8+WrM8XGKUp9iV393dstxsCnmwGSmuQPIzqIM+zBzqwwQ2Gvh15//I171/d0jeOX/veb7Fe5lg3YkNLHMfkszmIjq5zCBRJlDAMk1IQEaibDlt5nPBIE3j7+hX6TyR/I/2bnM7O8GEK8HAPWLF6qEjVFOUtncKNAiMVkumGM8oQXKBpGoa+nVxyaYKJJEYrrJaEIKcNUsQoOfn1YyPwY89hs0VahQiGt19d8/WffcVSzPng4ilnj8/p1ch9saMqW+pdAcEipEL4lOBjXn9xxadnn/Hhtz9Cq4gf/cWnPD5/ym/86m/w2Q+/JE+WvH//DiU1vbNc399wfXtF63uMnDr2cZZhjcUI0HIqX5Sc3InBj5SHLdv7W9arOVIqvB3pXYdzEp3GU9PUScZxpOoaUBnOWvbVHhlLnn/8Abbs2b+/5/r2CjUKlAUtI9JFyixO8LbFdiNBSIILdEPLD/75n1EWB55/8wXZIgMB6/UJ33rxMV9++jU/+sGndLuOVbrkbHVKGBxuHJHeY4NnGAf6ypPkM44vTlFpTBsG0nQKqqnKX0xP4K/tmtJnG7SYIBhKSNq6phctbd2SxhnWjvR9zzBMnLs4SfABrJukg4mV9N1AWW8p63vKesMwNgxu5GZT8OWrGw6VI10sUTrF2smDrkRAhgdnsoeT6JLf+PZv8f79LW7wE5br9h4EZOmMWO/Z3t3Tlg3BpNShRmqNMpOJY3CWKAWTAcoRJRlCwm6zZbvdk8+nMd9isaTpaorygJSCJDHksxw/WGxT0zc1u7rk6uoOP0iO12ecXjwCPDL2HK3WjPaY3eEaO3qMSZAyULcVzo3TtMANDH662RarGYf7iJcvv2J5siBeRWRqjjP+AW8ukF2FiiK6oUd4hRSGWGQoqdHKENxI0zRY1zGGnpPjFSZRaCWnaY5KyOJsMjJ5zSxdMg4NMJJnc/p9S3B+6leYNcZn9B3YUdA2PZtux/1+R99Y2v0ADpSSCAnWWfrS8+kPX7K6POPi7BEvv/6SLz77guV3l3z3O9/hsJmSl4q24H6zYX+7YX+zJY4UGCjtAWM0MlMIJRFSo7VCPdB4fuLFv7t+x+X5McvVEd6PjM4TggHCNOnwkwAqm89wwVG2FVVXsTid82/9/b9LcbXlix/8mB//yV+w1AskTBJxK0hnGVoleCQ2QO96ZmTc7W559flXOGtZnayQZkKdnz09J49yfOcnN6wSCC9IkwSvmB6a9OyqHuUllx88YnV2zBA7rBWEBwZlsL9AncBfxyWA4DxBMElMATuOBO8ZhgGjDeMw0EmNd57ODKRu0tBbP3HD7NDj6h378paq3tD3BX3fcyg6Xr87cHvXkCYnKJVjTMo8z0liwFm8fUg189N389H5x/zu3/49jr484s9f/hnb8p4oVeSzBOtG+nagaxqyRUzXddjg6VyPDRYZCaSB0bVU1QHXW3a7LW50JDolUgnL+YrVYkUQniAc3lpC8DR1QXtoaKuSpi7Z3N+CDdzfXvPjTz/lq5evGGzPt3/1Y558eAqqYbQldV8QGGnaksH1SAleWFQEKhYMnSXLUy4uLvjqq1e8fPM1R89OuEgESmu0TgheI0eDEIEQAuMwEgmJtZZYRczzJXXZ0NUNg2/QceD05Giql8cOIRSnxxecXzzGyDneKtJYo6Skqu7Z7/aEEZQw1FXHo5PnPPk7z7n64i277R196NELQxKndGWDHw31ocWO7UQ4MhGzZIXwmtRkZKuYt+oVxWbLP/7DP+D3/u1/l2dPn/D5559SNgVJlLJaHeFqi206jJ5GbDqVWGWnbAoJykx9HM+IEA7venbbW8rywGq5ntg1DxmA09tkThEPVKj3dzeUh5IoVlyeXPDi8kPe5l9z//aGWE9zfq0l42CpiwZFTJzN8FISvEebiDULlvmMMVjK3Z7DfoeJE1bpmmfnnmW6ZD1fY6UlYnK9mjQQ3IiUFkKPFZ5mGLkwimAkAyOj8DRtAy4QyV/yngBTzwlPmLDXkSEogfdhsoKJMAU79O10Uhg1IUxGI/fw2xmaA7a4o6juOLQ7BtdTVA2v3214e9vRiTmz5THR/JR8cUo6WxOZGUpPTxrvJ19ShGIMgV/54LvIWHB1f8P95p776z39MseoGCEl3guGcfI3d3agsz0+MOnIlSQ4Rz90VEXNzfUN2hiOZvOJ/ackWk9iHxcG6qpitz/QFFNE2SxJiSJNmuZ88MElcZxze3vF/d2GfVOA7Fmf/A3yWc5qdcKhKtgfdpR1QwgQZRO0I45idPBYAbJT2NqxWGTYrqe433F8ckSYJQR68JZBCgIOLRUjPZ7A4IZJlZclmCQmy3NC5+iHSYKtjEQ4wcnylJPlGTGaLEoYvGdX76iqHWW9ZbvdkQSNEorrq2tSnfOdp58Q+Zj9YZJqf/tb32Wwnj/9oz+nbG6xB/BOk6RLstmcEBkunz7i+OyM4rDFmIiyKtg09/yjf/R/8bu/+/eZL3POOOXs0QVpFPP+6A2f/fCHqEiwPM3w8Ug31szUY7SMUajJZRgCIoAUgrpp2BcFF85OSVMShLeMY0Pbl4SgUEZyu71he3tPmk45jLPFnMY2NLajDyPxKmMsPFrH6EjT95au74mzDBNJJJI85GSZ4emHT+iGjrdXb9gWO0bnMCZini8IJ4J5NqPpW5bZHCMk4zjpPqJIIjBT0rQUiDiaei5VzSgckZkazXYYfu7y+6XYBHwIjAR67wghEMUZahbhOxDCEyLoQ0fXtRA8coS+O0wnCO/x1mHqElduOQwtuyDYecNXRc/nZUlnppjq9ZPHLE9esDh/QbZ6Srq+IF0bRAqDnF4MaacIgyAV3zv/dfRvL/nfw//J568+Q0WGaCbJkgG3gLovibVGKUHsY7IonwI3BonRGh0kdVcTdCCbp0QmoSob9ocDq/WaWCbs9i3FrqLcF9RNOfkUFhHnF0+5/OATjtYLyn3BbndHlgmiJOPrz3+E1iPf+pVPMHrG0Cg+/+E7jIHZPGGVLpnJiEQZxEwyf7RAScnr9CVjXzBuepKtxd90iAuNWE6JQU25Y7WckWcntAPICAIjjhFrAlZCuloSGk1733N3fcPF6QlHizPyfsH+03veHV5zdLJGSnhz85p3t9fIyHBycQmyo+4OxGs4HG75bCO4ePSED/gO1a5mkTzGoPnSv2eF5/IoI3QS7RXCQr4wPPv4OTaT1NuBs0eXDE3Ddrznn3/+p+y7Pd/73m8yP33Gti4h1uTfWDOXS7rxwC6/JdChYs08WxHrOQMlsU3IwpxhHMBDUfe8uy25/NCSqR4ZLFJD0e5o/AZhZuSrY5S3PDs6Z75eIYyi9Q3b3S177ggnnnCq2dYlC5ExyzOUsbR+QHZbVukSLRUmCuQfPufDX/kut2/fs1xfYlLFq6uvydZzgnY42xMBwzAQRE0nPU3oWFyuIUqo7zcMzT0mjnBB0VaeME7BrrYe8INDif8flANKTPw6gkQJiUYi5DTH1VIxtt2U6OMnWgtSEfxk8GnbFru/x9Y7OqUopODVdsuru3sQGWcXT1ifPOfi0XNWx085ubzg9PE5Z5eGoxWkMRgEigfg/4Pt04XAx4+f4f/23yXS8ONXn7KvatzgsGPg7PQSN47sdpMvIDiHwzH2IFJNYEr2ydOcSEdopVmvV+T5fHLnHfa0XcswDBwdnXJ6do7349SoUjGroxXKaESnQQmGceqH9H3L9//on3J9c80HHz5lv9lS7g/ASBqdw+gp+wqXJVw8uuT4/BwlJMW25K18Q9k25G3LMROye+x7ejsSLLRNyzwXREZDcAgEbdMSwmQeqvY1QgQiFbPKj8n0nGJf8aPv/5jXX71n6D3zfM5smWDFAFpxevmISEeMdgJF5vMFIhiqsmLDPRePz1GXl6A8d3e3iEjw9MVTZmHO9maPjjU+9SSZJIojhHMczxc8OTllmef86R9/n9///d9HS0OUZnzzk084OpkjE4kHHj05p24jpOxpW4c0GmMU83xGU6aT+lQqvFeTUXVwdG1H3/bEkUSICQKCDHRdQxjDRC560Ha44BjajkO5p2pK+qoiuDDJq02HsKCYJMNCgLfQNdOTeQieNE5ZL5e8f/mGuq754OwxT8RjhBZ4GzgcSpqmQyg1NQFtT7rIeP78Q4hi+tGCranaA7dX1yzDMVaM9LYlMoZIaqrd4eeuv1+KTQBAIyZFnJTEWhJJgdMKKSB6qJ/sMDD2PW0IE1f0YRNo6gbflYzDyKaveF2WvK1aWpWyPHnK6eOPOD1/xuXTD1muzzm9POPyg4jzS8FyBbGZNiERPF6CVOJngMeB716+IPttjQqOP/mL79N1I0YmbO8qkJ6uG7DDQJ7nU0Ja59A6EEcx6/Upk7hSPDQjA13T8tX2cw7lgctHlxydXPDo0Tlt29L1LUbrKZDlJEcESG2CqWJ845AyQuIpyoKXn39Bsd8w+oGuqEAGxmacHGd1hVstePIiRSYJ3ntMloHRlF0Ld3esykecXS5whIcxWaDvW7QSGKMYBzfFkUlBHKV42zBaR55lSGdIdc7m+sCrL19y935HW43Y0VPkFYsmZ3E8KQ1NFBNFCd4P9H1BkiacnZ1xPVzz+Vc/om9qnn/wHCcCAz0h8hwOe4q6YrM9cPH0guXxkuOzJUfnp4QocD8eiKQiNRlHyxOePn7K+mhN01W8vXnJZXLJfJ7jw0CcAybGWxh6Tde7yWtiPWmSsVgeUVYlHjkJgNC0VUdxOLBYxNPr+lDuBSFwbmS33UDjWCRzhrFlX07NQSkmapU2muVszjAbCYUgOA/BT2ShwTMqTRBqQriPgd37OzbvbinKPd72iEhwenFCuTtw/e6KpmnJZAxKMA6OWWQ4e3RJiCI+/eor/Ojoio7tuxuM1sTLjND7qYdjA9dvr/4la++X4prEGUpIpFIEOz68eVTwBO8Z+wHbD4xDj7du2hTsSNc0tHVDN/bs24Z3+4LrdsDNlqzOn7K+/ICjJx/y9Nm3ePHim+TzGaujhItzwXo55Z4qAuLBl+CVnrQHIcB0KEBJyfPzJ/ze3/p7GKH5J3/6jzl0ew5VQ9MVKC04OlqQJPGkcxgCbW2JjWe1XABQFAVd1+OdoygLirKYQkmfPKW3lijOsB5UlJAkCVVf03Qt+WxGMkuZL3KMEoTB0gsm62tTcXv1niADiYrR0WRn3tzvaOqK0VnqdiDtHW4cGGwAGRGE4lCV7A57Ft3xxCZkuhnatplixb3EDgPBekxskEIjUJweHzG0PW+/uCJPE96+vOKLP3/F0DkiMz1VnQuEIImjFGNibO8pyxZrHQSNVAodT8KkXXGPVIH5OmOeL5mfzlgfVtzfvYKgIRWIWKHziGg9Q0WCotwz1B1BJuw3e9p64PnTD5kf5by++Zr3d6+IjhzMj7ChZwg1QbqpGag1bTlJzG3SIYXCRAlKJyg9w7sRgaFpWu5vbzk5zYlTiQ8OpSOUmHIYi/0W2QUioaj7hvv9ARPHXJys6WREl9XEpyluH9g3B8auJ/ISIcR0nyMgSIKFq5dvuH71lsP9gbZt+PqrL5ifzlks/hZhgOJQMAwDaRph4phYeVRsJixdGiGMIIwOOsuAoN1WGK2RDspdRVOU7K63P3f1/VJsAsEHXNeDUqAUfasQLiC8RzwQUcZuQibrB+Jv17UURUGx31OWJUXvuG9GeqN5/OG3WH34DczqlOX5Y775re/w0Tcec3mRY5QkiWE2A2MenvYPlmSkZBQBg0Ag8MGjhZyabWi++fgFyd+ZoXXMH/zTP6CqO2SiiFJFlqZI6RDKILUj4Kc0YGuJdETfdjhrp2adVJwcn3BxeYExhkNdIhtFlEYkaUKcJIhWTvmFSYYY/IPCDkbRM7Y9qVKINKasJ3bgPM/Q6ZQJ2A8dvesoKqj2NcenQFAMrUMEyWpxRNv2FEXFZrMlEQnaSIKQ2KqgKA9ARNd2SC/I0xRtDEYaYpnw9u1bXn32mt/83vcwNiEhJc9jkixHqEmcJIWcnN4e+n6kazqyfMZsvsCGjqZr0LHk9GJFniUMNOxayzxbkh2lHD85ZiZWNPsOLwL39ZbmruP50Tl9W9GWBatkTjO0VEVFlMYcnRzRiANNOBB0S9VPpYWKAuPYMw6C4BRj5yn3B06WZw/BMjGro3M8k6Go2lcMtuP6+oaT8wXHZ0uiWIEI9END3wXGwWK8pKy3dKNj6EeiOML5KVVgsVgyy+dQS9pNS1vXCB2RqITIaIwyDMMUZrN9fyB4T6oTTFDU24qub3n39Vvm8xUySLIkQ+uJ+SCVoh0HPn/5JTKJKeqKTMd0KsF5aLY1trcIKTjsdlMp0Lu/evHxS7IJTA0+B1JM4YnDwOD8T+nCwgfcOEzpMP1AW9cURUFVlLRNy+gsQSQkacZiveKDF99i/eIb+Nmcxdkll08fc3Ix5+QctPrLqAL1EwKJB8IDkOQBUyAFD7jtn36HKCH54OSCf+e3fxeB4g//+A+oXQ3GUjZbHMOUDpRBpCKSeMImS2nIkhTvPHESk0QxcZbgJbx7/5bOdWTLhNlijhcOr3tmi5i2tAx1y/Z+S7nbkSgDzuHGDjcOKPFQu0s7GXcUxCYiig0qFvR9z5effslh12Iixe3rd5SbgsykKK/BgR0sznqUZsoqsAN1VaDNjLqrUF4gOkddl9xcX/HVj17y9vM3lJuaXM4wzsCgiE1CZmYEE3Biwn5bOxBCijGaNM2Y50eoWHEob+mHgjg3XHxwgkRgRcPQV3hpibKcF996RiqWbG9KUJJNu+HQF+wPMWHo2dxvMT7m7OQCoyOcHZnNUo7lkpkUmIXDqxYhFEgxWbhDBFbTVY7NzS0fPf2IxXI9SaaTlCAU/TigjeBu855iX1AWJevTHI9gGFqqssPZiWwrtaLpS5AxZ+cX6DhmXxaEfmS1WHAUrYmsprjacrWvJjKw0SjNZFASDqkEuUqIlEZjcMbRLY65K+747M9/zMnpGZFIyLIZOkiGscfkhmyZU1QlsQg8/eApwyDp9hVeS/p+4H5/RxAB2/UMzYgRvyAr8V/nFbyf+ADOMfowBSj6aWzjradrWoZuoG0aurbDjRZjEtaXJ+SzOTLNaaSm1xoVx4ihY7Y+Yr2Yk8UKLTzBS4ScMEseMU0fCSj5sPIfmoOjBS8genjdnAsICfIh5fjx8Tm/9zt/jySK+cN/9n9zfbjGjorOBYISzBKNCf5hfOPpmpokjicS7OiJ4wR8mFKLlUXoQBAdoy+p+4q+bNHE0KW4oaepS6QMJIlBorHjjEZPwqRUB3QQdONksoriFK0i4igw9pb3X73h+ssboljR7EvMIDDRHGE92snp5hgdXjuC0ggZaIeWeZQwjANj12NFS1nsuLm+4vWP3zEcelIV41tPvW+wzYiVDhuPGG3QcUyI7UOASE/w4yRlHgVeiglUYkci5Ulyg7eWYWwZhafuAaNY5UtCN5IuDE+fPWffH/PZmy8Yhh7ftdMRubIYHdMPA9vDLeu7GfFqQqgL5VHaTwrLQaCIiHRGbzuaYuD/Ye5NmixLz/u+3zud6c55c66qrq7uZgONJggSGihZsmxJDnnpnbZe+ENYa6/0Fbz0xhH2RmEvHArbsukIh0hKIkWCJBroAVXdNWXldKczv5MXbzYEOQTaCyICZ3MzsyIy7q0873Oe4f/8/gf2tIeG6XyGzgzjzmF94Oz8gqOjBcXXksEfUMKgVE5vR4ZxwIXUJBTRI2TEY5kUU45PjwgRNve3uD5Jy71wnD86ZXGy4O3L13jnsGpAyIBSEDNBJjIKmSF8ZGwtCJgWFYe+SG5SpmY1S8xDicD1jkkx5fz8nNr1TI+OmM2WPH+5YVpNMWXG5rBjN+wJwRF9RKHSDf1Lrl+LIBBCoO06MpWwXsELgk8fgCiwg6WtG0RMyyvz2ZrlfMHR0Zrj9ZrZbI7MDU20bPqem75n0+5x+wlTpbk8MqznEhkiCX6TULSRdLijAKIgBJA+VQYIGHyCbYJEfpsexIgMgkdHp/z9v/WfEGLg9/7V73G4qVG6JMsr8jwQ+gbvBvrR0TUjZVGRm+LBMShZjulcMl3N6OyBpruj8be4OOJihwgZE3VKUWouZ0cYqVABvHNUM8MwLOiHnmG01H3Ddr/FuhHbeJr7e2LwCXp53RJt+syuGyiCwmRJM6/XAteN3A936AIWszlGGoahZ7EQCBlo+xqZ5cRg8W4kBoeMERUltnPEISC8IPiAd57KTJivSoKxBO0fti8HhmFguSqZTKfYeODu4PBDT1UqQkycQZRkdD3j4Y4+OoytmBZH5JOMZTXnuD+i221ohzE1UaOj7TuQgbfv3mD/vObTv/kBKk/vR8iE6xYuo9JTCBNu255+b6n9nturK6KGbdtwt0tWb85Fyszw7OkzDu0deVahZZH4twSMScxIpdJDREpwwbI/bIghNQ2dG9nXW+IQmB1PCcbjjMUUBmkEIcYH/HpMzISR1OMYE3BXSDg5OiEaQV5U5CY5EoeYtDNaaaaTCa4TlFlJsI7gHKfrNSbP6JqWiS5ACNq+RWmFFL/8qP9aBAHvHZvtBiVTtPPWJ/ONKFEyrbJWkyXTyYzjxZrj9QlHR2sWs3myFjcZKos4MXJwI8dtxxdX11zfXXP1xU85WRpm2TmLowytxb8Dr0pBjOnJFNL5RjtBkZHqPxfxRLRKGcBDspBKhAjH8yX/4O/+Z6gs41/8y/+d2+aeST5Bi4YxNPRtj4zJOnroBxSayWSG1JLRdkQsAocyAesGrGsxuaAsBdY7XKwR5YR8UqJipK+bZC+lQGSRXGXoPK0i4yRd3XB9dcP+fk+uTcp0DhEpJEgYdz1hjGSVopxPkEHQNz33/R0iD0TnmU8XNE2N8yM+jIToQGY4Z3F+JDqP6yxOmCS3jmk9VsiBvEqW7lIqTC4hCwSVPANm0wmX548wRcmuvSK4AHLEOoEPFqR/6MRAvdtzfX2DHiacry15VVAuqkTvdVOGfUtellTFlMfvpVHabrjj9fVX7OsTTpYzbJAwRkwsyM2MUqy4v265f7ND+xLlBZvrW4boGWVEGUllMu5u3nF9teP05Ij1+hQJtI0lr0pkbuj7JsFgjCK4RPNp25quH5HC4Gza9rzre1xpyU1GFxvypWJSFuQ6QwSJHQPjwdIONcYb+qEnExlSCKbTOevLExrXc2gahJCMQ4LsKCnw1mL7kcpkVFnO9fU9Y99yvjjCxeQmVWkNWhNdwMrwqyML/VVd1jk2m22CawQeZLySskhrs+vlmg8/+IjlfMVqecxytqIsykRc0QZtMoRyBNGzIDDp6qTqe/mKn/3oX/Hy+Rd8+sMf8t0fvMfFkxXL9QytJT6CjTERzGOqqRU89CIEuVb/zgg5ph5CdOlrbQQhwmoy4x/9x/+Qs7Mzfu9f/l98+fWXdH7AuUjX9GilqcopQ2/p2y1CSspJgVCRiKdt9+gSlEjGkrqUBCzedQzBMu63bPdv0aT/G9s5xtYxdCNCGCbZjOiAQTDuIvWbljwWHM+PUELg155qWdH1Ld90lhiSIYeRiR5EhKqa0Ic6UZuMYX/Y0rRNkgxnSX3Y1A1jP0CM6CxjosvUQxgd8SEQeBdQQnPYN0gXWJ7OUCo1wWaTOUoYuq5PHookL4Om6ZlUOYvFkqYd6EYHwG635f7lS+7e3LHdbXj/4w8IBcxnM3Kd0wyW6XTC42ePyKqMYiX5X/75FXYYiaMgBpm2NaNCkuO84MVPX/Hyi9c8On+P5XTC3bsbDkPL5UdPKRYVdVsjVWSzvaXr9rz//vsU5OzuG450jjRpgSo3JtnSBU8IDu/BjTbxBqXAxwRWVUry+s7jMsfRkzW5UighMVJDUFR9YHtTUzYVQztiR0tpSo7Wa95//32u7q/Z7vdIPPLBYDZKyfb+judfRtZnJ+RZwe7dDV3TEOdLxn5Ai1TmuTFQmhz54H78y65fiyAQI/SjJxOaIiuYzSbMpwtWizXL+ZLlfMXl+RPmsznL2RGz2YLM5In1JzSpq+Uh9HjX4T2czQbao5rN3RVfff2v1KH8AAAgAElEQVQjvnn1I/6P/7PiB3/rh/ydv/e3uLg8ReUZIivIswxETGUAPBCLBbjkGad/4X1G8W0jM6aUEFCm5Hd+4/tkXqF7+PLljxli5NBb9m1DX6bUVBtF1zW4MCCzxIoXD8abRgpkUPjeI6Sk0jmjCHg30veW0lQomYHwCbctJVoYMl1QHxrurjZs3twT68jx6oiVWtLWLbPTOWdPLri9u+Hu5p4gRjJTkOclRucUZQmlwu57iOnGtmMSPi3mc5rDgaFLuPQYI1U1YX9oE9lJKZQxTOdzut7ifSTLKvbjPZvtLWjJ6cVJMsYQyZij61pkjCymM1yM9H0geMF8tiLLLPX+LUZrjlZL9m8OtO2ew27Lq5cvyec5RuaJKqdBaMkoRqoiZ7Ges1gtkm7kMOCtp2sO2AFmeSD0A5//6CtcLxj2Pd/c3nG3veH0/UecvXeBpMAODW2zQymo6z1f/ewrHj15wklxhu0DykeMzFAq4lyyR7MhIL994roRnSmyTOJlhsigdwNOjHjjiblGZzpZiDtBvpqwOFlRbCu0UOyu90QnqfuGXb0HIcnzAo2mzHOi9QQPY9vzxV98xjfffMP5+WOG3mGiQIZAZTIW5YQwOIZg6b2jMBnr89Nfev7+KkCjL4ADD6ZhMca/LoQ4Av4H4H0SXegf/2XEYSESUXc6nbFYLFktjzheHrNaHjOfzplNFhyvT5iVcybTBaacwLdk4SDSJogdwXkUUCjHsui5WC64Xs14dT1ys71md93x/Poz/vDf/h7f+/6n/NYPf8gHH32X1XSGLKvEI5DfzgO+tTD6FmGebJ7kw06DfwgCSVoI86zkr333N1lkU/7vPz7ms+efkYsFdXlAG8VsVhGVx9qW0Q4EOzJdlIQQ6JuBtrGYTIICbRQmVwgDucwpTUluMmwfaOoR23mcBSkdu3bLu5fXbN5uCY1nNVlyujwhtI5+27C4XFHNFmRNw3yxwqvhwf5K0A4jynryZcH6+ASjBc57MlMkXoO1+Adq0zh4pNRMFhW2gaIoccLjZURmBh0F2uRJaNOMvHl1jdCS49MzJtUco3L8aMmVYrlYwGFP3TUQNc5FpCzI84Is20GU1KLHGMOnH/0mzz76mFfv3jJax5vXr5FKM53NqKYVm8OGPtTkueLi8SOuXr3k9tU9715f88VPvuLxxRO+9/GS51++YHu9Zz5d8fb1G2yzZ1/v0ZMK149kUqFkEklVk4K2PfDu6k2qwaWmzHKKZcrgvGuTKMxanBdoKfDBM44dyAxTGpQAVNprUZUmSBC5Ip/lKCkZmoEsg1wVyFEhckm1rJhlc4SU3N9vaIaOpmnIZIYykElFVVUEYRltRxg9b1+9Jtclj6cVRmu6pmdWVkyKipu7e9r7G6bTCcfro196hv+qMoG/H2O8/YXv/wnwL2KM/1QI8U8evv+vf+mb0IaTk0vms3kKAoslq8URy8Ux89mMaTljMT+iLCaYyQzyPB38nzsOPzwaVAEYdLTk0VDJnHlRMSlyVB1RuaAeDrx4+wKbRTbdjj/57EecX1zyySe/ybOzS/b5hFwZcvlQQ8UI3iN8JJoEo5BS/FxaDKlfKANUJud7H33E6viI4z+95A/+4A/IzYbpokTogIsDzhuabkfvHG/fvmN/2CRxDoFh7PDeUZVV2nU4miQxizJshi2HXU3XDoyjQ2JQIqPrRlzjmBUlPgQmKkcrwbatCT7RcTb394QYOTs/p7s/UG/2tF2PaCKmLzEYjo+PidGxv98hTcYwDMncUinsg+48ywuyrESeGRbFlFGMjNIzRIvMM3Se0w+WcQi4MbLfHOi7kUwXhAB92zJbTPGi4PpmpK37ZLklJW3tCCiCVynL0ob5csmT997jo48+oguOl9dvaLsaKRWL9YLJvEIWEic8wnsuzi959/KKH//J57x5fsfR/IhnJx9y/2rH8598TS4KqmKCMYa7psGNgXpz4HB74OziFBkFxmi0SfbhELh9d0WmNFWZU5Zn5FNFCJIQANJY2QeP9yPODwjrUcZDEGiVJdl7kTPagBcCU+QoKWiajjFaFCPODhzGPZk2VPMKrQx13xJIqDUVk4gulb8CqECGJBeOmtl0iVGRfhy5vrkGD6vlMQRBsP4B+lr+0sP7qyoH/gvgP334+r8Dfo+/JAiUZcX3P/0d8jInNzmZzsiy9JqbnDzLUTIRYL51H3uY7/2CD+GD6aB3COvQTpCLnEk+ozAVEYFTUC2WVKsZoYA3u3fcD1s2wy039Ss+Wx5zefoxlyennK1PmRVTdEzgzGSEKoguIoz497xQpUosghiSuvDs5Jjf/eHvIqPmT/7sj+hdS1kZhtCyPSRmvpIGgkLLHKkkbdNQb/okLy0zbuoNb39yhbOWPMvo2hYiLObzJGsII3kRkT4wUQXHq2PqWFOJnElZ0BhFUWTUuz1NHFgeLTg9OuUQDP0uuR7HQdB1PbrTzKmYTiaMzcA4WOpDzdFyRT+M1HWDlIIsMxg088cLqmyCHx2yEogclFToXDOMAyEksYzWkrZusQ8MiGkGRsDYdgxNT3QQvUKIjLEDh8c5hQSW62PoFYeuoR0GLh49xueG7d0dt9fv2G8cq9Mpso2UVZ6awzLj9uqOb7684WR6xN/57d/FyII/+/M/pNu1zI9WnJyfMptMKULyW3C9Z3O9pdv3SB7UfFKQl5pyyGkPLdvba94WGVp6Th8foUqZDrTJ8N5jrSPEQCSJktyhRwqJ0TlSGKTUCKVBKJQqMEZgso4iT5qRMAdhEqzl0OxYH52yOloxFyvqpuNwv0N6QSCS5TnlbEV33WEPLavVkvl0gQ4dNgYG62n3DdaS3K2DQCiNjb8CB6JfuCLwvwohIvDfPqDEz36BOHxF8iv8965f9B04X53y/U9/QJZlCdgwjjjrUELhXWAcHNaMKBRKDenU6Ye3HiP4AKEHV8PoEdYivUB6gUKTFyXFfM60qJg9XjM5ntONHW1fIzQMouPN5mt+9vpz9J98xvnpGR9/+B2+88F3uVgepzRV5+hkAUh8qBF+XjjEB7f0bynoEY5XC/7O3/5dFssp/+ZP/zX322uscHgvCEGhTcmjy6eUecY49Lx7+5apmYNP9bjtHb4RjK0DDdEqyrxgJhY/N/osVQlSoGXGVJUI4ylVnoQnQlEWJcVkiig0lTTkQRJ0xrKcJgPWpSJqhR0twziymE7I8xI7djR1y2w642675eb6Ou3ea4jRM11PKFTO0ASmRyXDuEDGnDIv8M7jvWValaictIgz9iglybTk+s1rPv/6M1q7pZhmhCjI1YTMzAjOUVQLVIS637OrayblnnromKyOeDKfMqlKdvc3tF1N19a0Y43cCU6Pj9neb2i2NY+OT/n02SfIQfDll5/Tbg5kyjCZTnj0+CJJd7uLdMC7A3dv73j94g3z8+mDb6PG5JqiNIRR4W3H/c07lHJIbTl+ckyW57hSYX2PdQ4QSAHWD9hhRAnNdBIRSlAUJUqUyAjGFGgZKfOKaTWlzEomj6Zcv3rH1eGadmxYCU+WFRAjxmiEkrRth3SO1XJCNS0QN2kdnZg8OmI01E2NLEtkH2j6gcF5rPds9zsmJ79avNjfjTG+FkKcAv+bEOInv/iPMcb4ECD4f/38574D33//k7harimLNEd3w5h86YcxCUnigMsKLAljJZVEkKc8/FsfZ9tD18IAWIhjwHYjIXhmyymPF4+pZ4G4zLBZZKxT1IxhhK4GYal3B5rba+7rezb1lhevX3O6vuTi5JL3zh9zupxT5RmZkg8dA0GMMU0PhMDL1FCMDwtOq+mE3/r0e5hS8mef/YjX16+IGhZ6RZanJ3VhNNFZTlenDHWHH0eGrk0eAr2kbfYJOho9+DRzt+OAlJLMmUT9QUPnmOiKWTElfxCgKBE5rubIiaYfB/rdHu0i6+mCMlj2sqexFmElQ9fR9wmVJYSibhsOdU3X9XRdS1Fl6EwRfETowBAa8nnG8mxOWZVEa7BN4LBLW4ZCxqQd8BYpoCwy7NDxk7/4c/70p/+GxXHF4/cfo3VOVS4Sl5DIbLVGhMDz3Rccuh5hMkxRYmMkGsPp6SmHy0u+fPUzuq7j+OKE+909h33D9n7L6cklooz4zvPy5Sv2tztymaEywWq1TM+P3FAWFZkqwDfcXN0hS82z7CnVSUZRlvS2Jsslo45pV8X3NIcd2/uC1cWScjHFKYMePdKOSCWS4YrzeDemSiFGClNQ5SsoFfhAkRuEtxhhsL1NXgUnK5arOZv8Pu3+u5H9wbOvG8bR4odAU9cUWmHyBNldLJaUxZTN/YH97oCTI7v7+yQ+ms2JLuKkwjc1h7ZlcO5XFwRijK8fXq+FEP8M+JvAu2/9B4QQF8D1X/Y7hEypUwJyaDKVoYRG0NKHFu8cbdsQnEXGQEFABZv6Aj4ZlUbfE3sLnSc6geuT2i24kaIyrKo5NqvZio7WOryO6EmBtZ5NfUAQIEp0GYkmsOsPHF79jOev37KcvuDJ6WPO1ydcHq959uic+WxCnmUpK3goU8KD3kAjkERcjFRlxfe+8z1Ojk/48c/+gj/60R/x7uYtk0lJ3/ZE71HBU2hDkRX4KNFR4KTAqfT0t13Paj7D9T3Pv/qSrrUopem6jqPVEZcnl0QXwQtKU6ax0LFkHAYmVUkfe+q2pxtHVAAlFG3XcFAdXkucCYjMU2YZIkqEFPTDgPMOk+cIJQnBJRvyILG+p+1aLs/Oma0mzCcK10qu+ztCtJhM48KYPAONIs80Wkuwnqbes9tuUXlk6C2L1YKqmqF0RmlSU81ogbRQ3zcIJRlDwABNP3BkJOfnp3z+4gtub2745Puf4KIjNzkiCpbzJa9efsP+sOPy6Bx5JLDX11w8PuP0/BTrR4wwSJWCtRsdNgb29wd29wemJ2cs5kucb3FDmyhN0aEF6IemsRIKSZrZmyzDjBanRuy37ikPJaQEjNIUefkwXgzJHn3siQH2hwO7+w3rcp0azg/7Jk3TgtS0TYtznkIXFEXOcjYDIdnXNSbLiDE5Ee/CDqcdnXWYIseYHF0oPJBVFTLLGP2vKAgIISaAfDAknQD/CPhvgP8Z+C+Bf/rw+j/9fwWBrCwfpJEShCM3imAkro8MrqPeN4xKg5uRSY90w4MZaQAXCMJhx5HQdjAGvBvAtsRxwIeRQYw4IRlcQBQGoyJGKEyhGFtB2zYYrQlFQFcSWUS6bo8f94RuYHiz4S9+2pFFxScffcz3v/sJHz37gPl0DiLBKpV4yAJiwqUpAUIJSl3w+OQJi8mU3GX8we//Ppvrew79AZ0puu5ApgVKgY6RSVkwdpY3b+5Tiqw0T9YXxFhQuILddosuJOV0wrxY8/j4KYyO3e2GSiV+4WyyoHMDY9VwaPeIPrVN2rHHR89ubBlVRHU5KteEQXFoBhZHRwxDTT9YvA/k0xKVSdrDhqKak+dT2rah63qCD8zmU25e37Hfdng8upCoEMmyktlyzcnJMUZnEATlZMrJ6SXLF6e4xrJ/1zCt1kilcAR89Div0GXF2dPHfBodz3/6JfvhjmUpwYE3OVZqttsDYh9Q33pN5CVFVTDKA8J25FFyMq9QIrIdC86fXlLNp/Rjh/MtvWswM03Z5XgfMVbjNiNhC4uzJSGzDHKkVSMegXUaFUvoc4ZbTykMzrcYIZnKAikcQjoGNyB8BJmjZYkfPKLw6X5QGpNlHPqWKCRFUWCrikPo2Q4No/MUrkAOGaAp7RRkGjLklaYoClo3MirQZQFKkM8ylHd4B5MilXNCaqxzWJLQKjMZ46H/1QQBUq3/z9K+PBr472OM/1wI8a+B/1EI8V8BXwP/+C8NAkKgVLIWkz5JJ6OIaBFReKIbsHbERpDSU2SKwmUPT7+ACGBF+gNE2yHGkeAt0fd4O9C0LYe+JZ+tyGJgtC6x+AhM5iVTs0TLZGLivEsbgKGnsy3RB0ohqV3D/e6Wdttwt33D26tv+Pqb7/Dh+x9yenzOcrmgLEukSHJSYiT6gBAKLQRjiKzKFf/gr/89Pjx6jz/64z/mz37854hM8HLbEpDgPF3fMskrVrMlN3LD/X5PuVyT65x62zMxM+R4iykKjpcXiGi4enOLbVpyEVnNZuSVZhxHbnbv2IcNGE82LygnFWG3Y98eiFEmu/cB8lCgY85oY2LfiUTTPez2LE6Pknpy6CirBU1d411qqoUQEUiurq447HpOjs5ZT1es4oyizFgsp+g8e1jwiegy4+jolPlkzbur11yHexZHx6nhqyDIiNaaICRowcXTC/aHazq7JR8ylCyRpqDzlt3ugBIe23RUWZqMBB8wWnJxskbuLWN/QBeKs2cXUCk617O5vcdEkJnk6HyJ0or9pka4SHffcv/NHTIGghRIZyizGZQ67es3gV1oUP6WYRu5a2+RGRyvVszMFGJk0x/AG6QuMbokuojtG2IQrFZrlJG0Q0eUgqIqyPMMDzTdgFQZuZlgYkF0miJopADvB1DQj8ls5vj8HJUbuv2B7fUtsesxpEwyL0pccHT9QO8HjFGIAMP+V0QbjjH+DPjBf+Dnd8A//P/7e0QEHUB/O+4LMY1gvvUYF6nx1g99SrezjElRpt0CF5AILA4XRkSwRDcS/EjvLP040LYtQ96Te48UET+MRDyDG9l4x2I+YzKf0/cdRpfstlt8jExnC4oiZ7+vqfcNKkgWqyPyvGJz2PFHf/pHfPPqJWen55yenvHsgw+4OL+g0FlaqX0YrQkhMEogYiQrM37jOx9RTiqW6xV/9pMf8fyV4+zsnGFouH53RQiBZ0+e8OTxBQTP6dkJgx+53t4yXcx5/PQ9VKbJypxde2BT33N7c8XHHz7l4uicWu257W94t/+aoGC9WlP6CcIqDk1DIEFOkrmqwluH7wLZJGdsO1azGb4ZcNbh+oFJUVKdX5JlM7744gVa51ycp5Huu7fX9INltVixmM2JHqazAusH2rYhC55xHDnUB3JTkJWKybTCx8Buv6frOpSUKC3RRpPnBi3T9KXICx49fszV2yu86FFG46gRqqecSurtnuvrK47PzpFCED3c3m+ZTSbMpzm73YFYGs6ePKINjt3uQD20COe5WF0yrWaU2RQp7tht9+wOB+JtxOcjMg8MQ48WkvlkwtAO9E1L+6Cc3G3vubm9Z7Qj3/vud/jgw2cYbxFWIXxAmEjfdCwmyzQx8elvr7QkeIfUidCcCUN/12P3IyIofIx0vidXFUoInB+xfiQS8MEzR1LpEjc47G6g2fWY+K20ndQfC+lMaKmIIqHJXfw1ZwwKQEeBCt8GgIgI3+JdUzfeRkfdtwx+RBcZQaQnbbDpAwcViHiEH/Gux7uRemyphxYbLFIns820EqwwWrHrWu4OW4QSzJYzUAqjNOMYGIaB6WSBUhl2PNB2A9OyQhqNFwG0YLAjV5trbnZ3mK8/56u3L3j63lMuj8947+IJi9ny570CLZLOPtiIEJLHjx6zOlpSzUom84rJrOTq3Wtev3rDbt/R9T2LzHB+dsLR0ZKh71FakWc53/30u7Rdz8/efMNurJmup5weP2b6eIU/hn5s6MeG499YolcFJiuRjcY3gWJWsTKSsNkxjHXqvQjJOI60h5EYHfPHT3l0doYdR6KILOdLRPDs931SBWrF+0+foaWgOdRooynLksOhpj7UrIc5zbDHBcvq+AjvEhKtGxp0oZguZ2iT0TyMD0WIaNIITESPFikQBG+ZLefs6g1BDfTBMfYCXTm+91vPePfyitubK7QxXFw+4dHlE37yxz9GCM/l00vM8QImJfPHl7zb3HN92DA5mlNKzWy5oMhK/AjT2UjTDjTdnokvCS4QZILaICDTyRtxGHrG0ZLLnGAt48Zz2HUcZi1+HVFBUzLF+gNDM/Lqm9fEc1gukmdFkWdI9UCriD6FYh9p3x3oNz3BK2RmHtyjLZKYkOdxZBgGgojsdweEf0PXdDT7A8JKVGYgePq2Sc5S2pApRcgMbhxwdnygJP+Hr1+bICADSGLiCvjUCSd4Yky1orUj7dChvKIaO3RuCN7jkpPkAzU4EPyAjyM2DGzGhs1wYMCTTyZkZQF1k/a6lU6p+wP2yzqf6MG1Y1bOKTKHRDEOFqk0i+WKSVEggqAfE+9QAplIN+32sOfqxzd8/s0XPL14jw+efMDjs0c8ffSE5XyBjOLn40P5sLm4mE/53b/xN/j4Ox9zt7/hy6+WXL2+4vk3Lxg6S5XlZKslCMF0seDR+pxXz78hL3IG77g/3BOmiuOPzvneDz/Bi47b21d0cUf2qOBsfUbrRt69vkNZg4oZ08Wck/NLpH7D0DtESBlKki9bmsPIbnPH5cklWgrGMGBDZL+t2dzXzCYLHl2+R31o6doGN3oynTMOI9u7A23TUBUG7yw6T7CV2WxKUeV4ETBFxun5OSfnN7Rf9wy9JTiPihFJxEDyAIiCiCArcopZzuFwhwsBZSRFpnn/Ny5ZL6bU+4Fx6MhNxvLJU9anZ2zevEPMKz54+h42V8j5BD/PudtvKINiXc3p65G27WnbDu8Cuclou7R9KGXKkJzWiIcH0dB1jH2P1hmZMXR9i2+AvWb7+sDr6i2mUggp8H1giCO7+kC/6/jg6fs8e/aM1XyFsw4jNONoETaw3+2prw7ELmDKCfOTNQZNs92jY6SaZ8TB0h86YoB6f2DYdklAFAXL+RGeQBybRHTyAR8d2mgKkxOLtN3Ztd0vPX+/FkEgxgjeJT97b3HO4q3DWpvWY52lG3r6sUdFRW97jE3rlaNNDUIdJUJ4vB3w0dGHntt+z02/pzaOXE6QWuK8x9kx7eebDCVnECL3d7eMQ2Bt1hTVhMHZ1KN40G9Pp4ZJWRKcpzs01HWNURovIxrPEAb6oYdM8Or2Ld+8fs0sn/A73/lNvv+d73Fxek5ZVUgtSdx6GH2gKEtOi4LpfEZZVLz65hXPX75me38gm83J84Lruy3rJ2senV1w+/qKw25La3uiCizO1nzw2x9z/PEF+2ED8g673aNLhZsLDrcNd4dbVuoYbUpsFzA+QJBIVHra2dRbUSJpHer9ln6ySPZpGpwNbG53xKh59vQDJuWUP/7jf8t6vWY+WzI2nmbfMg4DEMlyQzVdMJ2XHB0tKaqcED297ZlOch49eUJdD9ze3lLXLW6wFCYjKIlCImJS5GVZBjJgjMDRE1TAlIa2r5NQqVAs9ITZdEFyBIycPbrg5vqaTkK+XuClg8owFTPW58d0NxvywvDm+WsO2wbpNYwkuK3SaRHIeUxlcNEgoofgcc4TERRlQZbl7Os90heUquJwX/Pi829YnS2YnE6pzAQRDQfXYJuRrz9/wcnilFk2o7UdvvHsb/b0uwO7my3y3iCCIErIFkkktx/uid4yWWSoXlCaAhUzXO0QXcTIZJxgRcBLSZmXRO8YhiHZ88VIlmdUZZnKuvFXOCL8q7hijAxjj4C0smpHnBvp+i7RhPuepm0Yxg4ZJHV7QDzUjd4nArGLyYzBjj0ez25suBl27BloJdgwUmaS6XJGbCIxepSQIBR9P9AONRJDNZ+gjGZs0h9eygThLIqCrChww4jJDeEQ0ixYRDyeKCM61+kmtR2HbcM+bGluN7z4yRf84Hvf5zd/8/usT09RRpHaGan88SERZx9dPOF3/8Z/xN2+5u1Pf8pYO8pMIbykPTRs9T3HqyP2uy13Tc3yeMb7n3zAxQePuB/2WOU4eu+cUHraZsfVbkPdbJPNd66xjePNm+vk8deMiKiZTSfEyrONA9FZMIpxSPW8kJKqnJBlOSIqTk7O+eiDj/nDP/hD3r275tmzZ0zygqZo2N3uqA81k0lFVVWUE81kWqB0Iuw6Z1FZBlKhckk1TQBSO1q6tkeLBN7U0jCZLQgi4HzzMM2wCBMhWKKEMfZ0Q0NByXq5YDafsGt3bPY11WLCbL0kFoZeBAYCmRLo3HC0XvL586+5qnvevXnD9nrP6dEZ82qFHR4Yl0ISHzwdpZd47zAmSZizbEgZZGYoZjPW+pjYS3abdzR1QzHPOTJr5ssjDkPDcOjRSD7/7AvO5hfov6uwe8fLz19z+/YK13YIC+vsBF1ljIWACUzWE0J1jHAjk6Ig7iK5rZBes/cH3DAwugEHHHyHKDMmWUkYPDY4fPBoafA+gW21yZjP5r/0/P1aBIEQAu3QI2NMUAY7Yu1AN7T0Y0c3tDR9TTc0CCcxjcFHj9E6PTmEwMeAtS3t0GGj47Y7cOdqfKVQU4M1EacE508uMHea+9trwuAYh4HgHRNToqQmEinLkqbvaOqGvu/x3hFjJDdZql+VpqxS4yaE1LBRWidrtBDo+gGZSXKZs7m9Z/8ude+7puW9Dz/k9PKS2dESYx6clqVES4FE81uffMpqveZPf//3ufnxTzm0HRfnT2jqPW/fXHFxeoI2kpv+nsePHvOd3/qEfJIx7AY62zCZZkzmM5q+pj70IKCsCjZ3G+q3IzdvtxhRoEXOtJxyfnpBbxoO9YbBOcZ2QE9TuiukRjtDiJ71+oT33/8AZz1ffvGCGASzyZwwjiiZ1GshphpaG41WCuctymvKMkPagJOKIATWOVwITGYTDs09X7/4muXRkvXZGaYwrGdHmEzx4upz9vsNo+8SJSc62nbEes90OWOqZxRZgY09d/sdblDkRcnjD5+yOjlC5ebnjEhjDMvlEmdHPn/xnGEzPGQ/ktwY2pgwdoSEdnfOEEUkCDBFSVXNaeqWum4JSrJYH7FW54QmIvTAvt7SjT1N0zJZLQlDRDnF5vqed8+vuX+0Ydw4dm/2fPmnX9IdamZFydFswdHFmmw5pxGecl0wPZ+yfDxFxUAmBLP7GcPBMu4t3bal2Vk8AZkb8rJkFIFuGAh+xKmIkIogoffJxSvKJJD6ZdevRRCIMTLaHhkCw9jjXMoEmr6h7mrq7pCCgO0JDsIBBj9SFmmvQEqFDFOgG4sAACAASURBVJZ+bKhtS20HrtsdB0bEvCJflDTKUw8tRUyLFMGHB624wAVPoUq0KZJ1eG7QWiAEbLf3HA4HIoH5dEqhDS5GJkVBcJ6mbbHOplTfgB0t3jsI0I+Ovm+pyGj7hh/9+M/47MVXvPfRh3z627/Ne48ek+tkEhEjaCEQOufDR085/89XfHZ8yV/85MfMZzMOX3xOvb3n9CQiMo3KDYuzY+ZHcwY3kGWa9uBwfUDF1HBSSiFNRpSem82G+3c1Mhas16doDAqJVgaBJC8KvB4YxYg2hsGOjLajCS2TbMLF6SNWyxWvXl4hlWS33bO53zCtSrTS5HlGWRbE4GnqA0pXTKs8lQaTCvqRw2EkxI7ClMxWM84enTJ8veeLLz5HKsEPfvjXMXmFjoKZLhnHlkO9IUgHIaCkwA6RTBdMqxnSCUbX4+xIP9bYMZUz03mF1gpnPV4Ehr4mNxmEQDWtGO2AIDIpJ6gHYIfzPnk61D3qIFATgcwiRVUync+IQdAN48PSaKQocpRRSOGZnkwh8+wOW+5v75guFrTbhlwU7N/V6EFTUtFvBq6eX3H98oZJUaT19RLml0ccPTqnFx4qTawi5IoQAqP1FIsiEZ/CSDHJcSYiSsPx43PO3jtn0+w4vLhBhykrk5SIXdfSdT1Dl+5Hxa89Xswzdi3OWdrmkKg20bGv9+ybPfuuZlvvaMeOwY3IVjMdZ8ym0we4iEr73cOB1o7sbcfOd9hSITPwwuNloOsbXrw44Iae4Dy5MWgp6bo2EXsXK65vNrR9zdHxmsViyqvXFqVlqq3GMWmym5ZcGYzWzKsJMUCIaSPNZBmTaUVTN1iXqMNd33Bzf0s5Hcj8QP+zL2iCo+47nlxcsppM0eLBIhsILjKbLfjB3/6bPPn0e3z1059yfXubmkIe7vYbdl3H2WyKrnIO45ZxGJDeYeuRfqgRD2q94BR4RaYKNCPOQfSCajqlyEpCFFjrqKoJUVuMznHeE0abXvuRSTFNtvFdmzDpT97j+c+ec31zTfHokiDS+DY54Gq2ux1ZJTiulmRFhguOQMoSmrZFzxSr9ZTzds0wbvnZVxt++pPPKKoJ1WzKaBsOY8+hvqXv9mR5RKMIo6eKU1aTY6K3vHr9DUIqZvMlNnaJTWk1wfZ0/cimqRFZTlYVyFIgvOPs4hzfDdx8fkO/G6n7jn7wjNaCkkThiUR8DOR5xvrkmPl0xmF/IDysk492pAglVllUJcjJCLGgGVR6ALiIdHC2OOU6v2In71kWS8Zm5O2rtwz9yGq+wEdQucGsSvJlyaTMiYXE6YgTCRzj+45sAFsPtNue1vaEDI4fHfPxX/uEy/cvqdsDt8dvmZcziqpMjlX3d9zdb3j76i27zX0CY/yS69ciCMQY2G3vExbaDglw6XuasaO1LY1tOIwH3m3vkuinKljInl1s0E1KPWMcGMaGZhywEtSiQk4M9dji4kCxnCT6SkyeBfiQFnqcS2wAKfEiIqVn3+4puozjkxMuH13Q1g3TqsBZy9h1mCjRJmHRq7ygLCbUdc3tuztGNZDlOavVgjJqfNVD57CjYwwj08kRMtd8/epr3t1c8+H7z3j//DEfP/uA+XSC0iIh1gBfVRyVFZPJlPl0wU/+5E949c1zXl7dMDk/4fTxU6TOwQr8YLFdRwwdzjUIadEKbCvZ3jS8e3XHsI/YJvKyeUXx4ZTT4yWDbwkBrPMEIxldGkeJOFJVU/JpcinebO9wCKxNo6b1eoULlpv7O/zgyLKMxWqVdBhxYHQO5306NG6k7jqUqijKCiE9Jteszxbcbwpmy4rDoebFN19xfH7M2aMjQtvR1LfkOuLHATVGNDnuIGjbHqk9ron0bo/WmqbdI6PBh5y6tggGFtkDPEVlaSM1z8mfPWUxnzNRr3j+4xcctjUqevK85OL8MdN1SSwDqoosVhMWy0VqwvkHEG5ITtW269BL0FLhbdoCVFoghUAhkEFg9z0TU5HrAoVEIZjOZiyPl4xxwAew2tIrT8/IIitRRQY4xmATKkxppBJs7q65enGFlDnnTy+5+PA9ZmcLfOYxSrH+6IxC52ijUUeG8rxi1R6zfLzixfOfcX317peev1+LIOC95/7uBh8sITj6Me1ae+lpfcd22LMZdux9wyG0MPY0zUgeSozJkmMPlhAso/QEo5hUkmxWoi0MtqOrIz548jxLY0fvGINndBZhFKYsCCJB85ztefP2NULBbFqRGZXw2cGlnXOpMULhnSOMnt619HXH/8Pcm/xYmqV5Ws+ZvvHONvsU4TFHZGVWVs6VmVUtuukWNAiJEgtoqZFAQmzYsYIFm94hEEsW/AGIFQsKSlVFldRFU6mcKuchMjw8fLLBzezanb75+845LI5FUGpVFNDdKfKTXC6/JrsLNzvnnvO+v/d5ujJ0COI05mB/wTjKuGkv2aw37LYFSZYx54C2LVnvCuazBc+fPeHRz37Ji9ff4Ku/8yWOT46RSKz1dBIyAfk446233+VkcciPfvB9SGLG9+eMF4dUbU/Xe4bh4w2to7Utna8ZhKfeDpx9dMXZkyumao/E5EihGeVhkvD66pqajsEEcebQVLSdRSKY36bPrLUIDRcXp1xermnqjr39BUkcB7dCP6CiUK1u6xoXIA+fMBfcLSs/S3KSJGe1WdK0OxD2Nv5sGIhYbS95/4Mfc3x/xsGdCWkkqYsG1w1M4inrZcGjHzzFdZ67r58QRQllVdCWDa7tkTrEv6MoZzxeMN87IB3PUbFGKYkUFk1C5qccvy5Z7WpEEjNKp6RxymQ2ZnEyhdjSuB1RItGxpm/C9VQJjxLBmC2GgWHocdIyuCGMWutAuvIuhNgu11c47xhPJ6SjDJUp3vrsW6yHNT/9+Y8oiy1qbBikZxAeHRm0NjRdwF0bE6Ocxu5qNpsN/dBz/5UHnLz+kPHJHiqPaH2LiQXKSHb1DttZrLd4M6Cminm2YNkvOd9dfOr6+43YBIahZ1usQxXZ9tRDjZUOpz1FX7ButpS0iJEmX0zxRtHhaHxLbCDPNEponPPB+y6gsA2mlVgJzg7U24o4ijBJjBMSITQWf/ufnaAiQ2ctaR6RdhnPnz/Hup7FYp+2adms1igrOZjtM5of4Kyl7zrasqWqauq6wQ8OLTTlrqCuK2ajCc3QsdxtiCNDnMVUTYVDMHQdUhDCMQq+9a3/k5/84Id883e/we9+9Wskk4wYH+oWAMpweHLEN6Z/h7c/91merc+5rldUfUvRtlRlR9MOON/jNMhIY5SgwyD7nEhUJHrEJJ8znkwZj6f0vWPwYKWkdzL056VBSIsUYVrTDhbloelqLq+vqeqONM3JxvvsLeZUZcl2vcVbbuPWHUqFNqGODVEaY9KYcZxgZERVlVxfXwY4iHI0Q4tKFLlMMKmh6QqevnhElL+K7XtE58lVjigkT374lPP3X5KZMeWoIVvEVJuQIo3zCKNjusZzePeYg/176GiMjDO8DBN+eHBGo9KY+d2E411FOpsxzxdkSYqJFfHI4GSDRpBkCiNhaJowtRlHyKKgb1r6uKOuSpTSKO9J4pghz3E2OHSiOKK3a3SiyCYJRJ7Gtezd3eO96DPcDFcU25T9B/t4TXBOCoVtLbbpENKT6AhPy7OLC25ubjg4OODea/cYH85wEVgGJC5IY0xPVRfBjm1d2JhlqNWMj0bsV/ufuv5+IzYB6yxVXwXnm+2xBD7arixZVhtK0aJnKYqBfDEin0+ph47r9Q2ddcRjHVp1TY+Xgf7jjKRxAZDRdR3eu4AI8yGfrpVkEA4rBVKHIkxVFeSRRKrQEkySBGM0Qz+QxIFQq1RQUtVtS1vUaBG4+f0t/GM2n0Ea3Ilt39DYDhErxrMpUkiqastkMmOUjBnHhq6pbzeIiNOzF/zRH/+vPH70K377i1/gvS98EWPUbZsnXBNGsxFJnjE62uPD62d8cPEI0RlcqxlqgUVArFGRwQtBWxUwROTxHOkTvFMoGXGz2qBjQ5LlDHJgN2xodhUy1UTaYFRw9xkTB9uRdczmYw6Pcuqmp67rgFszgiiOsa3Fe0k+ysOkkpIMbgAVTE5t76jrNS+enbPcrsgmORbPaDpj/2hBclu9ruuaKInYbYNqbBzNUK3m6QenFGcNmRsR+RRbSPwowpBRrkvSJMc5QRwlTKdzstGYwQXaixQKrXVwBGqQSjIowcErd4jzLcrqYIaKNOiBpmuJc8N4luP6hrZWZOMUhaDaFjg7YG1P37doGShEkRb4UULTdDgGsmlKViZUu4qOlsaVNK4KUtIE9u4fsOdmpGlKHEdEUUTbdwxtT9d3OOlRsadvWra7FdHIcOe1u4z3J6BD6w8BTliKuqBTNYNokbFDegFa4IaODkc6T3klfuVT199vxCbg8Ox8i+1CRhoD27bkYnXJztUkeyPmx/u4aofPDWqakIiYLBpCBVQ6xNAjlA13aefJoxFpmuF2BU3XECVB4GB9ONJBOELjPVIGtl5d1YhBk8QJ+/t7jCczsizgnqSXMIQjW9u1NEWN9IIsjUAG6KUxMdlohEgE292O7W6L0objB3dw3cBmuUY7weF8j/t3TqiKmrpveX5+zma7Q3hP1VR86zvf4gc/+wnffH7K3//X/y7z2RShCRRHQGrJIs4xyWuMxmPONi94cqY4bztW2xZbWFQtcXiuX5Rsbjq60tHblqENbEFxKRjPJhzdP4JM47yibnqS23HhfDQiTzKctmA7pIK7907IRjNOX7zEiwFpBN22wTGET/1Y3U6BWqIkwuHp7cC2LGiaDlErmrJBOEMaT+hFhzID8/0xi8UIKRzb7fb25wJ12bNa7lg93XD1+AbZpBxNpjRYVjc7hsjjI8N23aJUhROOo+MJSupQiFQKrRVS6lvBTAB14jy98+TTCVoYml2Ld9ANHc73yEiTjmKkkfRduNZESYywApNGSKNuh50UWZYSS4VxIb8vIwGRI9GGfJ5ws1mSTCMmB1PUSNPJASsco/mYoWsAz2w6Jc8y2qZj8Da0V4eGbtfQlDviRLF44y77Dw5QI4kP+iy872i7hqatqG1AoUsZrFlShKtYENwaFotfL1TkX/rxAgrX0nRV0ID5MM9fiA49TckP5qixQSlN5XuudkuEVug0IksNu2KH7ztiI2nrhtVtou7kzl2iPAmDHUqhkohBOMDhLCEy6h2ZvJ39lgExPhqNQ56+t+h+QMiQrR+6gXGW0XUDZVNzMF8QpTFV25CNc6I4Zb3bIAZB2ZZstlsePnzIaDrm+vwl4JhOJsxHIxajEeurG7AD5W5L29YkUULZlDR1xbaq+NM//VOWN0u++s1v8N5775IpsIMPrnkHEx3z5t4d9mdz7s1PWN9/l9XuirLZ0dmasqpYvLvmjWmDqAWpTFBCcL2+4uL6JevNDVdXV8zuz1A6IhJJKHz1wSU4znOqvqSqGuI4BmC321HVJfPFlOl0xjB02NSiRERT9wjriJKEyV7OaJShlKLrB/rBElnF4d4xDR5MBHQMvqBuQ25AfXwSHCzaR1Rbywc/ecrN4zUTZsStYdvVXDdrbuoVJ+KEV95+hXvjCUkes9mtcU7iUYSdWQTJrOvxNkSjhbdEKLqQUyeKIzSGoRso6x1SwmQ+IZtorGtv50QkGBmuWYlG5+H3KB/nzOdT+qqgb7oQgjIpUoNJNFkbE08Nr7/2Dq+++YDGNjS7gt4PKKUouo7peMRklKG1pBEOJyxagOs71jfXlOUGry1mauhMg0ChRRRqRk1H42q8Cq4B5QXeerxzCBUKkUYqYhX//8IY/P/0OKD1ll44mr6l2O7o/cBsf87B/WPkOObxy2dUoqPXIgg4rGSSTIjiGFdu6fqWPM/JVErZ1XSup2xLojgBEwIgvgv9+FmakBhD2VQIe4spHAbUrW+gbkLoo2wbyjrGKM22KBjqjnGWEwlDZzt0FIwy/dCSyhStJFVVMNSWZJIxnc/xSmKlYLo3J49jMkIuoN4VVNstvXMcHx1ipcBZz9X5JWkcMVsc8OLlhj/6sz/jw6sLvnL6Nf7B7/8+8zjC9z7IUAQoJZmqnPkiQ8zv0zPQ+47OhiJl8VnL0EkSp0gJTLz17oar9TWPn37Ek/MnnJWnrK5X+KwjQmOHgc1yxWI8whgdLDu+42azZLUqaPueV1+7x8HBPjDQ1j3rZQhWSSFRXhLHESYyKK1ohmAMUr1klu2RmZTaCpToqHqB9S1lUyMIE3N9b1ltKs7ObqhLTyzHRHZMPMRc1UtW7RqTZ5zceYV33/ttzMhQVQWXNy+J4hglTai82yGwDZTCCBWAKbfH6EZB2w1BlGIUVdlQNzWL/RHT+RS0pao70AoVG4a+R8aS8f4Uq0NbNZ+NULHkxYtLXp6dkacZyShFRRFHWYyPBfce3uVLX/0ySZ7z4bNnbIcGk8U0bUdVVKFV2HW0sqZnYFuXaGcRfctqecH5y1PMOEHNYhI7ZiIjrHUMbR+StkONjwTGOvSt98DdErCFkETaIKXC9+5T199vyCZg2boNjW+pbE0latQoYXE8IT2ZsmlLrqsN3kgikxLpCIcLPxghGWc5nfXBoqsVk/EUJwVaB0a9cx47OKRwCCnxCLSOGI/G1FXNcAvQEM7T1Q2rm/XtSWBgfbUjT5OwdIXANh1xnpDHKUIqmq7HpCnRKKb1Ha0Osw4H80MWiz3KXUm7K5llYzplqW62LP2ScrNjs1lh0ojZYkzdWWzvGM+nJFHMbL5giCVmI7i4es6f/NmSviv5N37/X+Pw4wjox4NhzmNliCBLLxmpHKlHoMDmH9OOAgwV4IE4BDzf/Prv8vTiGd/+8bfRP9Gc7V6EdJ4Kn/i7Ysf+wQyDoi1qhBZoKTl58JCDgxOklECAoG43G8pyR5ok9K3l9PSU/eMD5gf7eAfL5YZ1UZI8mDKZjPFDR11uqKsNURKDN7jBQq9pthUvn16yudgwiSYMqaNdtmgUMlcc3L3La6+/wZufe5vF0RFSA0gW1mMSExB1fY83EqGDfckSrn5+CAJW7yTaeaQcGHxLWYcWdTY+JsszinpJb0tQFp1ohBsRKU+k8tuTQ81Ep3S7jvOn5zx6/32yPObOg7ss9vcptitAEWlFlAi2uxWPHv2Sq+2Kyd6cxd4C6xxN23K9XpKkIbMxlBXlrmB3fc2zjz5iW685ye8RxRqvHJ2rqJuevhvQRtH5nqH11LXHSEMUBfwYQqCEQusID7TDr2ETEEK8TXALfPy8BvxXwAz4T4Cr29f/S+/9//a3vdfgei6qUxp6+khgDkcwSVgvHFbtON+9pM9DX946R+IN1kK/brHacXhwhEr3ef8XP2ezXZGNRyRJgmscWT5C5RGVqEiyDO8dQ2dpXE1kIlrXsNuUxElCEiW0ZUVXVCzmR2RSM2xviGzEbJyjMkusFLQt+5Mpfd1StB17x4fkB2POV+eIuSTXKTr3KDngm4rV1RaRzhlFKcopttsdN66l7Vsm+Yz1bkXXD9RVT7GrGOcLTBqR5x3j+ZRNUWKBP/zT/wmTwNe/9HvM0pxxFGM9gVWAwIvbwaD+dsG3HhWFP38N0wwWvPVEHt46fpW37rzKlz/zNb79y7/i+4++z7PlY14UH9D1FiUV9AJfQzZN2D+Y85l3P4+ThvPzlyyvam6uN9R1g5ADUQxC9rx4/pIkzZgvjpmMRyCu+fDJC46P7nJ/b0F59Yzt9ik3NxvS+HWmx/exYuDm5ozivKA627KQY5SIaaKWPmto2jXyIOL+ew949fWHqLFh19RMJ2Mm0wUIReea0NFQIG87QK1tcD6IW6UQeO+IbIwBWlfSDyU66phkOUmeMbiewZd4UeD8QBJNGUeHNDcDzz/6kOuLc4yp6bsRfeXJhpRJNKXeVchGcm9+RN13CCyn56c8fXaEdYKL86c8fvaE+cE+0y9+mfEkBy1ZFtdEpcF0AtU5lh+94Oc//hmr3YrjV++wGO2RSIPrKrbdlqYNgh3ZG5Q29BbcEKGUwQygZPhhay2IhcTo6HbD/puff+FNwHv/PvB5ACGEAk6B/xn4j4D/znv/3/y/fa9+GKj6gWSak+QxIosRUUjQtbfJNW0MdVPgnAsDLUbTtiVtWSKkYDGdsre3wNqBNM8wcURZliRZxmx2WxSRAucCWz6Kwtf7IZhg27YljkcoqYmimDiJmU72mEyn1GXB0DV44anLimq745V7r7ItK1CGNI7RQpHomIf3XyNJIy7Pzni6fI6rBvqmY5I68vkEoQUX5+dI6SmrEiU006lBO8iFIY7H2LLh9JePKdyOOM8ghWx/yvQo50ePv8fjsw/48ntf4Wtf+AaZUJ8UDJUI8hJ6wh0nFwjlcC5o3ZXUCKlBhqEeCEXZwcNrD17l5MEdXn39Hn/x3T9nd3XNUAq6OqIdJCSa8XwGCJpmh/OK3fqKurih7yq6vkYJUEYxOEuapSSxQWMxWFTX0JYVwgkkhroOpy+pBJ4BoQZ8V+NchwcG4TB5jJeSvfyAKI5JhCJ5ZcHowQGj8YgoT0lGGfl4RNu1yFohulC/wQvcIEOVPQpgUSMV/rZjIbzBIkFEDEONwJClGbiBvnVEOoF4SlPXCKcxkWHd7nj00YfcXJ6SZXD+dMt0tMfenUPM1PD02Ue0vsMZSZZn3Nzc0PqBm82K8WTG4Z1DrncbusFhnedgukAazYvTM9bXN6je024Lrl6cUdVb0lyTjSKs71lvNiQ+RRsVUPUQZL1NS9v3ZGZOJH2A6lgYbLBMK2uRscXLX7+G7O8BH3rvnwrx6RnlT3uEliT7Y8Z7M2Rq6JWnE57WO9q2pvc9TjoGIRDeIW7vwt45qrIIo8Hec7C3x3gyDoQYATKX1HVN13cIKdHShGiulDjnqcqKrmnp+/4TeEnXdSRxglYhiZjnGbv1mpfn50Hm0bS4pudo/4g8HyFNxGq1pJcTFnsLsnGKtz3nvWV1dUMsYqQX1F3LptgG+64IIM+uG0Ktog92X+kkuYgoq5rNxRU3fUE8Szh+55j5nRSfZLTDlheba+qfFKRZytff/TLOe3wnA7jEEKB04uMpR4tXDolD+AHxsTFFSJwM9CPnPX0/kGrD11//Im+cPODO9IgfPfoxz5+f83J5xfzQMFhHmsQMtufq8oLTFx/R95bISGwUU5Y7irJknI+JVcLQDrimZb0tePSTn0OdYYjYrtbUZYFWnuk0I4mhqdf0bR9CRAyM8oyqKBhFU0SkePOVdzAehokmOZgRJQnCaLyUIe8hbivjXgQ/ogVvZMgQyOAQ7GyPGwYiaUBpbO8QMkbKmKpaE8UR88kd4lxStg6jIJEZ5ablYvmSYteQjUe07ZRiu6ReXVMPnmSesjg6QGWaot6yLNdEgyGepMzcgtYPzLOYN99+C680L6+XRHHKwcER1jq+9+yHfOcv/xK6jrGJyIzm5GSf8d6MfH+KiUOrc+h7rLNh8ElK9O3si1ECiUUph9ZR8GT4KKDttEGK0Bn5tOdf1Sbw7wP/41/7938mhPgPge8B//nfpiADiNOU+2+/jtMi5APqgqqrUaInTlPS8QjbD0HpXQQNtxIK5yxRpHHWhXqAlBweHtH2PcvVKvDjdjt6OzCfz0kIC92YUOjpuo6mqYPjQGnwsJjOWd6s2a5WMAik1PRdz2QU7rHbrieeTFBKh3kC67m6ugIDx/cOSdKY65c7lFPkSQ49OOHYlQXltkQCk/GIWCu0MkTK4HuHHAIrUUuPLSpED/t7x6iJZ7Y/oqGEyONTgdFwc3PBn3/rT2m3HV9674vM0uQTF4KXDmcbvB9wKhyBpdKhDeM/xp6FwqK/5eVnRqM8WCs5yY74g7/3B7z7zuf4X/74T7g4PWV7U1EvHLFRXL684dmzJzjnmIxHbHc7mrpBi4iYlPKm4urymuP5Adoq6nLHq8d3OXjvXaaTOW21487xMdbMuLy5Ck6GocZgePHiGa517O8fsnRbnBAsqxVvHL1FHClWfYnD42SgRDWdRyiIVMgCOA9ucAgvQjYgNiQ6wVvB0HbBG6G5/WARtE3PzWrF06cf8dFHDU17zWuv3ydONWWxY3WzZXW9Y7MqSXVCOoopygi3kxw/vM/9B68wXUzw3hLLAZeCjT2Fq0llmAkobU3RVxwcHPH622+Q5GOMDlDdOEm5d/CAH/FXFEWBnsVMxjmzxZTxYkIySYlSgzMC5wdcH2o/QmvwCiODqFQSmhhJFOoAUoRchJQavMS5X+MAkRAiAv4d4L+4fem/B/4J4Rb6T4D/FviP/4bv+0Q+Ml1MiScZPY4BhabFuZrB9rieYJfRkjxP6eqGtqpRQpFECXmS0jYdSgqapmEynfLgwQOU0Ww2G/IsAyXRWiNkIMc452iaFqUU1jmGfiDLc5wLIYyby2uybMI4n7ErNmw3K072DxllCedIIhOhTITWml2xZrcrOBRHaKm4vrjmyQcfIQZPFmVsyi191aEJivI8TUmSFGcHMBHCgXUBkCkGSdU0gRGvBDLTLE7G5POUy+YUlYBQErwhynJ+/v6P+fAXT+n/LcfvfeV3GSU61AolyFuOoPRB0+QRiNuZfethsB7vBVL6IFVxob0kfPhEXURTPv/qZ7n7j17h/ske//T7f4wZcmytwoDWriUfjWisoO080mtimSAayeWzKzarFfINheoU2kU8fOUN3nr4RQbr+eDFR/ikQo0tzrZEGtq6ouk8xaagXFWw0Eyn+1RVj84M627LKMmxBgQ9nigUfK3FGMUkm0LvWF5eg/UBuhllREkCSoZ8iLydGakaXrx8wq6sOJjtsbc34eYm56c//SWXy0d88OEBe/t71HXH6qbAWohUxP7iAG0Eo0nKbPY6r772Nnfu36eudjx59phltcbLgSTNkAzUtmEynqCMYZADTnru3r/H3uKItnHk+ZhYRuyPFhxPD9lZweFixnyek0QZWulbm3AQxQII/7HAPUhqwkiDZq580wAAIABJREFURyUijBADgwvoMuXCWHfIDvx6pwj/TeCvvPcvAT7++3ah/w/AH/5N3/TX5SNH9w79stggtEQmBh0ZUpfS9E1g0HmCzFIqjJKoOL4lwShcb+m9pW9bttstSmuO75xwcLAfuGzeM/iwuOM4pmkCetlZS5Zl9G2H7XqSOMZah+3a4AKQkshoVJ6xWym6roUsJUlThIe+7z/xoWqtaOuG50+f8eLsBZvlmnk+RQpLW7UBhmoMWZ6yN1/gHWzWO7IkJokipInQKqItWzZNgZlkHB0v2GQ9cqzx2mPbHuUVWkmUUNSbgqvlGdvTj/iTfM5iMeeLn/st9McdA6kDy84pvBOhsyEUvQ+j21IEnJfyYdgl0F5BEPj3znlSaXh1ss8//gf/iM+981v85Fc/5snLF2yHa+7cfZOjO0ecnZ3S7BxOKFxl2Wx3bE43JFGKsTF5POXh62+RjkeU14rvfPvbfOtHf869N+f89tfeIIo1TRsEH7bzRCJm3RRcni2ZvH5InOXMRjm17fCDxBgFvqe3LdYFDJnMMmJt6H3N8vSCNM2YplNkL3DlAFKijcRZqOuWtqloux0fPn6f7eyAd956kzRTTCaGotxw+mLL9fUpxmRIFZHEGXEssK7C6IjDO/scLY45eeV14jRhW28o2ppdtWOgZ3IwYjIbIboWNTLk2Qi8YFPvyPMpB0eHdJUHJ6nKjsgr7h/dox/PmeYpJpHgHbYHbyUIidGEwq8IPyMpBEKEhW+kROkUYYLfQCqNs2BReC9xfSAx/zo3gf+Av3YV+Fg6cvvPfxf46f/TGzjnKNsK1wGNoLUtymhGeUbXdUgEbd+idQQ4xMe7oA3+r0hIhPNEUYS1AxcvL4iSmDzPqeqaqiyZ7+2Rj/KweG8HWtI0Zeh7+tvNQgtBpAxJHFNsNrywnrsnd5lNp+Ea4tcoqUmTcPQuq4I0S7ib3+Xy5iVPXjwmSRP29g5IdILtLZPpPLTuHKRxOAUUxY6yLMFajDZIrZEmoitrCtdxvHfIa595i03WcbZ8wvnygmWzYh7npMmERGku15cU2xuc13z45H1+9PPv8+rDeyxGU3w/oJVEyuj2CiBB+k/8rYhQN1Qi1BFdPyBN6DHfStlR3ApfHUzSEd94++vcP3yVnzz9Bd/75V/R0LI/P6BYN9Rxh9CCpt+xvt7QbBve+fzbfObtz3J8/w7pLGNXlXzwqyf89Ec/5uzFC05eHZFEMUPfBouS1my2a7bLCm1jtMoYOsl0f45MFD0DLT3Se0Q/0AmHv9WzSx+EpO224Or0gq7qWe5dI6RExYbF4T7zvdktsaplNEo5Odrj+anhennGo0c9USR48OAe213MersEAXEiSdMQtEmTDOkVsYnI45R8nCMkICFO4kBKSiK6tkNFmnwyhkagEkWcJTgbRpB3VUWWWqIoo9jUXL9ccn1xiXaSOJogB0G9bimHCj3R3J3NSVSCEwMo+39TrIVESo3RCZGOGEiQKkxNKm1ASLz1WOuDiMf+mmoCt8KRvw/8p3/t5f9aCPF5wnXgyT/3tU97I4yJ6Iaetm1p+4ZZMmM0HrMrtvR1S1vXJKMwJDQMHb4LqTYjNdY6VARxHKOUZrlckuU5s9kMbTRt1+GsJU9zNusNfd+jdYBCRlHoo243GxbzOePxmPF4whAPDIOla1sUgjRJg5DTGKaTKbvdDmk0h0eHmDhiVdwQDzH7+/tk2ZQoyohNhPKCuqhwbU8WpaRpSpKE0dLtek3XD6HNF0fIWNMMLZ1wJLMRpSxYbtY8ufwVPm44uP8mAslqdcNuu8ZIyPOUtir5y3/2z3jtwWt8/atfR0gFCAwydAFEUKk7AUoKzl8uefTBY2IJ77zxkP29BQ73SZDGe4EUGqyAIczWoyUP5ncYj2cc7p9wdnNGMRS8tGeIRjCfLOhliuss7737Dl/56pfYO96nrEqKtuRmteLl2QtWN5eMspijw32UUrjKk0YpRdlxeXbD5rrCNpI40jSLjv1jQ2tbWt/RtQPKGzweQU+SjUgjjRKeoW1oqoa+bFhd3LC73lAUBdJo3v7se3RFxZMnj8AP/M6XPs/iwYQ7xwe8aF9gbUuWLYjMCC88KooQOhRXtdIkicYYTSwS5pMjrs+v2S4fceeh4/juHYzUjLKcxXyPpDW3bERJnmcMLowFRzohilOcFFRVTTQagZDstgVXF5csz68wXpPoBB1H9EOgYU8PB6YLBaZHJQIda4SWtyc6GG5PcwKN9ArhFYpQ3/JSovD4KETjP+35l/UOlMDeP/faP/4XeCeEEERG0w1tMNxqjesHurajbzuGYaC3NryuBqz0eB/Gg6VSCCk/Of57F5DhXdext7eP0oaqroJXwBi89/RtR6964jhmPp9TFAUQDMmTcRj2CWJJEEqRRDHiVlDivCPNM5I8xUSGNIu5c3JC09b0w8DL5ZLZnma2f4BCUFYNVRe479b25HHG8ckdxlnOy4sLtn4L3qOVZP9gH20Ez54/47Iv2K0LvBdM92ZMZhOaruH06py26xhlOaKI0L3k+YdP+PZffIuH9x5y//49vICOUCxSeLABeS4sXJ2d8X/80z9nsD0vl5/l3Xfe5LX7r4QTDg7vCBVG4fE+JM+cCO3Eqc744r33eOPOK9ysl4hVw+WHz6mKgvl8yvHdA2aLKTftmusPl4xHI0ajjGqzY7u5RKie48MDRqOMpm7AB6FqsV5RrhtsA+urHd4V5OmYfJaTzGOc7+gqh3YGnUREJsIYgbr1ORgpkNbiu54IiRoECRECydWzM06fPuXp8w+BgSRRvKIe4vqe6Sjj4OCQNB3T95b9vRwnOzpX0PZbPD1aaJRQ7M2OOZrd5fzxNY8/eMzVaodSmjQ2SAfjeITEwm20W0cxrrtNLkpLnKbkUY7yoXZjdESa5ihpKLYVelDIPMLIiFhpZJSyW7Z81L1AZT2L4xF7x/OQitSKpg+f9I0diLDh2jwMKBEK2t4NIDyR0mFC9FOe34jEIIjwH6VD0sk5y3q1CpNS0qGNQccRFk8cR+FIP4RpKef4BAL6Me/PGEM/DKzXaw6Pj3ht/zWur69pu44kSRBScH15Rdd13L93jzxJuZQhZdbULYIwzWb7ntgYkjRhsI6iKEJkWUhGk1GwxTYVSZ5gIsP1zTJAS3tPOupBStquZ1MV7Io1K2sRg2cUp7x69z5HJycUuxIlBFmSMBmPODk5ptxsuLq8ohGWeTpmdud1xvdjOuB6u2ZbFwg0kYoRBN/dIOAXP/s53/3O95gv5oxGOS0eT1BmSynRLvD29scT7p0c8eL6nB/88kf84ukv+P3f+ybvvPYmB/n+LXXXBZirEaGVSChKBSy8Z0bK3uIB+RcVrmr5/i++h4tgdDTjYvWSH//wR5wcHPK13/kdlPdcX5xR1je8+sYRi5MJQsJ6tUHHit621EWLQuMGx9A5jDJ0dc3p8yfM7JR4niKlxFqHNikmUgEWG0lMFKrjXV2xW29wjWc+n3P36C5eCy6WF2x3K0bjDKng+uoS94HDK0cSR0HSYSV5tmD/8JjOV1yvn9EMim4oGBpLmozZ37+Da2OSaEaWTrk6u+TxL95nbz7H+oFURRQtFMuSUZahpmlwG3iPuzVrRXFE5IO9WWoT2I2vvcH5Rxe06wacpNiVROOcV+6/TiMqPnr6C5yosM0B42xCNk6JkhgVObpuwDkQdsD7hq5t8S4ijpPwgWgdeEXftZ+6+n4jNgGlFUIrBu8xcUxZl+zWO7TR5OMcpMILgTIGFcUMZUGPQ8cZ3jp6EfLhQgiUlCErPQx0Xcf52Tmj6YT9/X2sdyEg1PfsiiKAOKzFdgN1U6OlYnW7+cRa0ww94AMtRqpbmCYM3rMrS/aPD5GRCHTjzYbrqyukUiTJlFwliM7TVaEQOdubI52nLWucdZwvXzKZTnjw8BVipTg+OqTvOs7PX+D6DmF7drslsztTsmmOF5b1+obVpqDuLHQeIRJG44R23VH1FVW75Uc//SFvfeYd3nv7LaQQBFB2OB1pQErB/Xt3+b1vfoOff/Q+7z99xKOPPmD9R3/I6ed+h6987gvcO7yPlhrvFUoFFLYjVJtlmF+FIRQST8ZH/Hv/8A/4/Bc+z3c/+D6nN6eMZlNeffM1jIddGchQly8vyEaKO6/exYw0LTWeMBDVVC1tO6B1TGQEeMiyhDyP2G5v2HZXHPhD9u8cYpTCCUc7tDAMLPYW5KOUelOx3m7o2w45CGbTGaPxlLKrOD45Zn48Y1evUBEkqUEqAusgMnRtgzEzFos7zOd3KNstq/IGKbYY2WL7AJIti4brF0va2nLn4AGTfMT50zOePnrK3bsnLPan9EXP5c0FF6dnfO33v0KWxVR9i/cC5wkYM9+RyJjIRIwmE975rd/m/PFLPvzZ+1gCy0FHitF4zCSZsFxesdlesbvuKZaOg3sTjI7R0oHf0dYNUvXBmyEU/VBRt4oszVDSULcF9tdVE/hX9Qgp8UoyDANGqTCf7hxxGiMjQ1U39IMLbR5jkFGMGDwmjW/bWuF9hmFAyFspqJQopdiVBReXLynLktfeeJ22banrsDCttVxdXTFKc/b29ii2Bbax5OMchUAITxQZosQwDJ6MnERI4iwhziIm8ylFuaHpmmCTLUraumUU90SdwW4rBj9ghWW8mDKbTemalovTc6quBS0xSnN5cUlRbemHnquLC7CWamhYVxdkgyJ1c+pdy3KzoSx6tM8RJvR+O2VxI08sDZPjEUW35oNH7/Pg7h0mo0mwHCuJUmFx2dui4WsPX+HwzgF7h3tU9Y6zi1P+7C/+jMdPHvH1L3+dd994l/3pXkgYQpBdAN4JhAunAgZAayKV88bdt5nt7/H+6fv8/MOf4lqLsJ6yaLh4fsbNeks6dajYEqcJbQMgbvvXmjTN6XNFXwp0LGltyUDDaGIoXcNmfclsb0RvHNvakYgcISS7Ykee5mij8c4xmUzYXm4pdgVSabb1DqctKpOMxjmz/ZzZ/pR6qII52fYMzhLHCUk8QoqELFOk6ZTd6iwU4JQKyrSbU14+3WBLy8nBEXvzBQLH5csrrs+W1NuSq6tLXrx8QdFXvPeZ91gcHuIGQT0MDL2l7wbwA3EsiOIIhUF6zb3XHnL98pK+KBASWt+EMWSbEZucmJp61bO96lH9iFm2oOg3NLZkaDpaHwCxozzMlXR9i/UxURzjW4//9JLAb8Ym4JyjHUKMNDIJWTZCSHnrFgj97sFZ2n4gdZ44TXEWvJBEkQ7VbKXRqNu0VKgdxHFMP/Qsb264vLzk6OQYYwyL+Rzpw6bR9z2d7jg8PCSNU1bcMBqNELdpxY+Tic5DkmWoOEYaxWiS09medugwxpCNc7I8o6s7ROdorjZcPnuO13B0/wg/ztBKoUc56SgjjVK8UVxcX/Phk0fkacKrrzxgcWef9fWSSGru3ztAp1DVW653a66XNzgE88mcdJrSVTV1WZEuYvYf7jOfTohtwmq75OryhkmcEyuJsISCH+CVCrJXHzHPI77w3udIk5i//N63+Pmvfs4HTx9zubriVx/+kq9/+avcPzwmiUfEZhIq0/hAz9G3LQYJIFHecBAfET9ImEQjTKv5/l99lySJECqhsR7lO1pbY6uQdNZRgrWeODHMFwlduWIbNUQjA6Ijngr2j/eohphdW2GMIs1SmiG0+ZIsp7VBVhuJiLIK0k0hBLvNBm8dRV9R+pJ0FjM9GjOa5xzfO+Tl9Rmr1ZbBWkycMB6PSeIUbwVSGvJ4QhaN6WwPwU/CttiyWi2JRYrQCuFhOlrgGqiKkmrdsVkW1JuOurOcPrngzbfeJo81bbulby2t7BAygiig67101NZycP8O+8/2uT7tUDps7utqxdEkYW9vH1v1bLdbNpcN25cVR3fuobsKVzjcrsPFEq8UdugxJmaU52RpRhQluAy6tv/U9fcbsQl4YBg8m/UaN8qZjMfgPWVdIK0i0hFZkoEPI8GRielkT9u0RIkObTYhUbc8gCiKEErivUfIYBCq65rT01OOj485OjrCaE2xK4LpqO0oioLpdEpTNLfE3SY4EIeepu1xTjKOUuIkAyNwAuqmCU4xAdFtwdELSRYnGCeColoJhn7g6uqKum+YzudM5hNmkxnL7Zpnp8/BaMw4xUWS3a5k3RaQ9pT9Et8pvNa0gyeSMUpoIhGHFGAkQsss80zupXRDTa7HiNjy+MkjpmnGycEBbvBgCL/MdghDWFojPKQ65gtvfY67J3f547/43/nuD7/L4D3vP36f588e85m3XudLn/9djvcfEsUxRkaoWGD97Tgz3LYUFQLBRE347MlnscXAd/7iO7T9wGg0ZbF3SDItcF5ws9yh05S90Qinw6JTeKK8QaWa2dGELJfsnUwxI0nmEiKRM57OyPKEftdRFgVCKZwb2O12lFXBbrvCWYsRGm/dJ4nQTb2ilzGTwwjrWopqTW+bAOFAEekYhQLnUUJirSVSKaNsj/W2RnjPeJwxlBWegXycI6MIuo6m7vBeMspmlGWBayWpyhGRYntZ0pUBGR6rGJzADRZvwm+998EU1PiGTnW0vkHElsXJAXqc0EuJk5au7vFeon1Cu+25erHi7oMWkFQXBdvllvhoEmpD3hHnilE2xRDjGjA+4W+5DfxmbAJCCNI8Z71as93tiE0o1ij0rQbMAIKu66H36EgiHdRlTecVUSqxOAZCBiAb5URRRF3fRoK1wtaWsigZhiAcaermNi8QFvF2t6WpG3KT4/AgxC3hxdJ1A0JECKVuaS0tde/IRzFeeJquQWqNuL3KqDii3XXEWUq+GKGiIDE1aUScxHRtH+LMbUuSJoz250gBre9oxEDhWlxf0ZqCrieYbmWEMRLvPH3fhMRirIikxquBVXXDKJrgdE+na55cPmY+m7OYzYhNxODA9vDi7Jzr5RUnB/scHRyEDVNIDqcH/Nt/9x/yzlvv8LP3f8KTx4/Y3Fzzre9+lycvznn77d/m3bfe4cHBfaI0xVqPEhqjJK4PLSijJdIblDK8cviQ915/j5/+6idURcHedIbPBDfrHdfXJfP9I+49WBAlMW0/4FxDMh6xONlHMMNEPSJzlH0JCoyOQ9pxcCRRhB0sVbnlarBclC8YNgNtVTMdZXS9IY/GmCimrLcMTQtekyQG73teXp4zSIdXCikj4mSMwHziohBoDCnajdB+jNTB0SBly/7RIeN0gVARSR7T1A0mctBDU/UIp8njCRExza5jebHkKL5DFuc4IdAi4Ns8YXDOe8Gge9bNDa2oSRYJiztzxocLKms5e37JdrdFR4osTWjajvMnLxn/X8y9WYxla5qe9fzDmtfaQ0wZETmeIc9cp7qqq7vKGNoYGyPPXFniChBXCORbfMetb5G4RmAujFoCCQuBwbbcuNuiPVR11ZmHzDw5RMYce17zP3Cxdp6ubnW1LTVGtaRURO7cisiIvf9v/f/3ve/zFk/IRyFXT2as5gvkqmO054iCiC7zBAcp6c6IMIhYrlbcnNz8wvX3S1EErHUEQch0MqGpKkzTY1yDs4a0KAijCNMavHDDi+E8oVA0VtBvanqnkYGks/0QGZZsA0acAyEGKo73ZFmK1pr5fD64sqKIvuto6hrnHfN2we39Y4QICKOAKI6hGWKldRBvSbAtl7MbkJbj+BbOd2Ad42LEg/sP2KwqXA0rs+bgcJeje0dcr264ml0SRCFJltC0DcYOk47pdIwONF1X0zmDjDQqDWiMQQiBwwxJPtIiggDbe5xricSYWAXgBa3pWc3npHspravZmBX4lsfXj7mzOOTOraNh5y4l12cv+Yf/+B8SJwm/+oMf8M5b7zAaTQhDzUE2ZfrO93hw6w5f3/+aT774iE8//5QvXzzjvFzw6OxrfuXtD3n4+kP20j2iJB8Oa3IQHAo3GFo8nizN+eDdd/n4ox9zdXXC0Z0DjOi4WW+YL2qKiSaOd0iyGFeuEdpT7EwpdkZoZVmuzynrC5zsiaIUITTGCpTQ7B/s0zvP+cUl5abm5uU11XVN1ARM1Jgg0hRxSpIk3Cw0zvSEShEFinKzYtOuIUmIk4I0TCmKPYp8SqwTNIP/IBApmjF57BCyoVzNQSiO7t7DtyGKnCQexNlZ0rC6WlA3Pab3JEnK7nSfTbvim8cvKHan7Bzt4yUoGRHpbY5m26JkiE4F6TTi8N4+tmkQicSFAi1CwjwmzjsirWhNS11WzM6v+KzvKIqEZrVG9ILFakV52RHokCAIKQ9q5OtD6tL1y2tefPX8F66/X44iYAxNXaOVIk8H9s5mvaRtW7I0AwNd0w5OQKURXhDpkDiMaDcVnWgIGEAjcTzM7p119P0Qbuq9J4wipJLbVJchoUUKQVs3vDw5QQjBdLrDcrXG5SlhnBMEAdYYEJIwGkZUzjqUUjR9S9O1SOXQQhBEIYdHh1RFw83Nhl4ppncO2b9zRHdmObl8SVlV3EmioUFYtQRS44xltVojhENHCXmW04xbutUGHacI1dE4gwwVYRTivMD3jiQNiIKQftWg0QQioNrUSLciicakScj55pRnZ8/Yy6dEWYSUnjQJ6buGr5484uTygi8efcOvf/8HvHnvLkWeE2jF7ckheVZwcHjI9OCIn33xe1wvX/Ls/CnG1VzPTzma3OK14wfs7h6TJwViK+JxXmCcI9SaB3cfEAfBgNSqclSugRAtPUk8ItAJziusl6ggoBiPieMAZEvjZpTdIOaaTKZoVRBHIyajiIP9Ai8USirKdUlkNZfNBbPZjEAqRuGEJI0ZT0bsNjtclBcUo4wg0Fwur+h9RxQmRFFOmkyJowmhzlEqGkCgDqSLSILREGxj1/ShIQrb4ajYB2gVEYaaQEoaGdOue/CCsqwpipz33nmPj77+iNOX59xfvMad1+4PQFuvCFWIbRnGhIEnTDR7h7uY9S2uXp7SO0PveqwcAKfUlva8xJpuy0qE5dWc+dkloyQlkZpAC2znkcrS+5LnVy9Yn5ak6RAZX237JX/U9UtRBMATRwq0GMYxUqG7hE3ZslzXFF6jVbzNF5C0TTPop4MQKyqcEjglsMYi9OCOs97gvKWqK6x1JGlKV7fU6xJhwNY9Zbem73tWsyVCCPZ3DrAi4HK+RMZ6SPCxklCHxGmKlIpchqTjmGW1YLWcE0QKHWjCrh4WaBqTJxIqiU4H7UG9rGgXHewpimxCkY45efaM2c0Nq/mQSXB864iMlFwmhEri1ZouNUQmpkAhoxCEIi1GWONQejgqWREhxZAcjBfUnWPTNqigw0l4fvGcO9Mjbuf3sMCd117nT//ZP0f+2Se8fHnC7/7u7/DNl1/yo+/9gB/92o/YP9wjCEIKlfLW3hvs/2CPN4/u8unTn/Ly8oySmk/nX/MvTn6P4quU77z+HT548D73Jq+RJ2MECuUFSobs7tzlw+/+Bi/P5nRdQNxF+LYi0IIki5GBR4QgjEarCKUkcaiom2rw8XuBRBJoyWSaDanJCZCGONMjop5pmpAXt8iLgGU55+X1Jfog587DXYIkpsgnPNi7T1RoonFC4keItiUVYyZ6n3F6TBrsokQGIkJojfAOW3uCICUUEV0XEuYJqk+4uZgjrCebKAKf4PyQYuWUoKNHJop7r9/m4NYO/U9LpBVcfnPKO2++y/ToiLIxBDofYKedxVqB7EOyeJcom2PlDXg5qP+sIHCQBAE+CqiwKGuJZYwxgroeBHSd70mShFDrrZNygOguNzPWahiZx8EveRbhoBZUeCmpqwqlAsI0Jm4G5JJHIuWQmeedx7uBJyADTZilpKMCpQW2MiCg67ut4m1LXVWKIAhQQmK6DiWDgSrUNLR1Q6hDpBiaNmEa07uWpu/RUYQTgs4Z8kASBSEDml/R9ZrKu8GQsu6Js4IwyBBSk48iRGmRrWc1X3D98hLZC9IgQ4sI5BAT/WpqYxoDBmxl6bqGMRldssuJvSFRKfl4h6wYs6460jzHyeHoo7RmPN0f8gH6QTzVd44iG5EXObFK2Nys+er5I6KdETvTXfLRhO9//9e4c/8+jx59yf/9j/4RH//sp1yfXTK7WfDBdz7g9TceMN2ZooVmL51y8M4PuHtwzOOrZ3wzf87T+Tc8vz7ly6ePOL045cnjz/nu/V/hvTe/y/7OEVGcImRAko75jd/4C1xdrviXP/5dGtFgt2rEMFTIwKNiRRpkQ4irkBjbcXl1zWy2pMiHWbjpekINUvYYCY3vMK6mcyUyCEkmCXtil2gvoVws6ApBcntEHIeM013Y9VTthmicsRcpZjdzRKeRfUiscgKRIgi2hjCHwyC1J/CagdGW0BuHchFxEOOwhFoQyADrFIia+WbJql1z5/XbvPneQxbLOYubGw4O91leLnj+9QvGk9vE4YjeKnSg6E2D8Z7QysHiHqaMdw+QwhEFIbY3tE4QBgHBdEw7r2lvKpR0pEGK7KBuO4RW0DM4Rj1ooQi24boCgZb69zkSf8T1S1MEqqrCW09ZlgghybOCNEsxvUNKQdPUOGNIkiH62pkevCNNYsJA45wlDiO0VDhjQA5OqyRJgEFE5PADpUiHhHGMdQ5tDNkoR0s5RDgpy2ic4rE0bU3bdwMmuxfkcY9EEmcp0koO9g4ou4rzq0u6rqPIxkRRio4EfR1gO8P6aoHte3amE8JAU5cl1nWESnP74VssZgu+6r/+9nfQCo+IcnQQEIsC6TR5MuJw74hx12MFdMYgO0EUx4NN1ViiJMT2FpEqRsWIyXhKGqX0ruZ8fkH+4ilJkpGEEZMsY5w9YG88wneGpu44PT3j7//OP+DzF1/y4a98yAcfvMfh8RGTfEJMwsHubca7t7i7ep3jk2PSMuazxcdsLmd8ufqam6trHl98zZuvvc3tw9c4PLhHGo147e4xf/HP/vtsrpd8dfkRYTgYtOJg2HpLpYl0iHEC5zybakNrYf/oNnkCOGUIAAAgAElEQVQmsLakyFMQQ66jkIqq3uBdh5CKtu1JohFhpEnigiwrSeMcrSJGxZQ0TRESmqsWIeQQC4+l6xt61w9sAu/oXT9Mc4zFeQPKbHURDhl4mnXJcj1nPBmxnK+4urni1u4gpNp0c5bljCSL+OA777G7u8uXn31C3bSDAzCIePrNM3YOb/PgjbeouoYwiomCQdPi6Wn6Fqk9073xsLMzBotHxSFSDIs5SlOcnNM7SyTFFqjsydIYhfpWC+AZJPX+lVTYMiDzf8H1S1EEABaLxUD9dYZ+i7xO4nRwRG1lr+tyg5KKNI6oupayKsmSmLqp6PutJNgPzkK93S6HwTAkN87RGzPMZrf23yRNSOKYJMvQUpKmKcY16EDRmob5bINEob3i/OQMU70gC1Py0YhsLyeNCop8RNV1CAFaSbI4pKcn0gFWwc2mRDiIg5Cubtgslzjfg7Hs7+5SLlaYrsdGhs46RlkMgOksWTKhXFe0ix52BLujKa01LDcbZKQJo5jWGEw/JNHUVUOSJIPk2Vn6LEd5S9XWfPFokOK+/fpD0jAG79kdT/nTP/pTJFnKP/itf8xHn3/MV+ePab/qOGtecnh0xOsPXuPh7ffYSXfRQnM8PmQ3GnFvdMyD6X0++uInXC5OuFjfcPX4mifzJ9w+uMOD44e8tvcm9w/e5L23HvLX/upf4jf//oKXy+dM96eEQYR8ldnnHaGOqJuGvnMcHd2jyCRVfUVVCsJEU3VrnHdEQU5XDnZv2xvkFhqrUsXR7TsEeszu9BZBHBNnOUE4puobLudXbKoaR0tnO7yTGO+2eDWHcg4lLMb1dLYekny3phsvHHVbsanWFEVG1ay5vrxG6J4oClg014S55J3Dhzx89yGuNd/SrYTUZElO27Q8ffSIvBiRjsd425AEIcY6OtPjfY/UoP2AfrO4gXQcRggh8WZoDAut6GpD07YIAYEOhlAdKXlF9Xq1+F99tNb+fkH4I65fiiJgnWW5WhAoTZpkQ+xVPYBA87zAGUeSRlQbTdc3VLXCmBbrDH2/fUF7g1UKKyRKK7RS2G9/8GFXEAQBxluQgihJkO0AFkmLHOkFVV1SVituHd0iixMWTxb4zrBf7LG5WHHy6DmRjAjjiGS/4N67DygOJ0RRNBQXa3CmQ2pPFqeI3HGJoK0qNIqNWnIVSMJIY/qOq6srnj99ymqxIAlj0AqthwTgclZTdT2rxYZmbUmjnHtxRhRE5DGIQCF1hKxrlAjROsB0A3/R41iublitrunnG7pZizQpdVkSSsVbD94gDIcz4s50lx/+8N8im07Zv3/Mk5PHmKDnZP6Ss/Upjy6/5sv9x7x56y1ev3ef450jiiilOHqTw8kt3rj7kM+ef8InT3/K2fwFs82a5eYzHj95woPJF7x1+33u7j1glGvG4zFXdUqSZAMcw3ikdQjjCFXIbFnRlx139m8TpR5jN1SNZLFeIAKL0iCsQjDoAASSQMc4LzEWdvb3GY8OsSbAIEANO758tENeTKiaBa1tsVgQDusdxjk6awiUQUuJdS11s8DRE0UhEkXbdYP0lp7W1EjtiRJF65Z4ApxumdwqeO3efUY7OS+fvURHIUlW0Hd26/lXPH7yGKvg7XceorRmf3cPHWh62aO0wdNhbIsKAoSWCK2JkgihhmOyQ4BWAzlKDAtfMoxnxbZh6Nwf5AYIMew2jDG/cP39UhQB59zW6ujRWhLHMdWmpm0bsjRFqYGFr5TEuf5bJV+aDHd+sbXI+m0GG3hsb3CAt24oCjqg3SoE+95gvaPpO6SVxHFE3fbMZjeEhefg1i7Tgz16a7h4foUxBi0VwkJVlgDIjaatWoKyxSs/ZBMaM1iW8xTvHIvrOX3bIhwoIejbjvn1sG10zjC/uUErzXQ6xXlHVXfUTYMOPKZ3bMqWxazEyxUCRaAj9m7fYjKZYAXUXY+znqqsyfLh5whCRaA1cSrou5bziwUnZ89Z3fQ8+vIx86sZf/43/jwfvPceWZLTe08cxfzK+x9ycPuYL59/wRfffMLJ+VPKdsPm6pLTszM+in7Cw3sP+fD1X+GN49c5HB8yzgref+Ndju/c480HD/noyc/4/OnHXJy/pGo29PMnvHh0wkSPyNMRZ9dnJFlBqEKadUO/aRilOZiWq4sLnn35NWVdsptGvPbWHcRkh6q9ZtMZAgUyEnS2QXuNQCO8QqBYLNY0G4MxEq1DnAMvBNYLOgNKx4yne/hlT7cp8VsmocPSOwN9N8ifEbR2w6a+ojMVcRcTBgl9Z/GyJxslQ8J1FhCEO4igxukOGXtSnZDvFHjlqdpyGGcrzWq1YT5bEBUJVxcX3CyuuJmfMh4VPLh/j/2DA4yUWOdYbxb0xpEHY6RWKKW2ExTPdXnDarXBOU8QBkihsG7wtojB/433v3/3f8XS/Ne5fimKgHeOIAjADRUrz8cEKmSz3tD3PUmsqaqSZrv4+77D2sErHwR6ACluQy+8tXTO4v1wJFDbrDipNOuqQm2NRgO3oB92DJVjvd7QmZ7D/QPyUU4UBhwfHdGte+anMzyeYlxQicGQEk0ymrpFlRX57mj45W9fgFeik/VqRbkpt6BHTxSGJGk6wD8BHBwdHxPHGdfXM6IoYjyZECtJ3nXUa0EcNpTVkqePT1htSu49vM/7332f8e4O55fXfPblF2zqmvsP7nJwax/vDEKqgZrUQe83nM+ecnlWobszrq9umC1nbJq/yPc+/FUm+Ri8JxCKuzu32BuNuXt4xE+//DFfP3/EzWzBRsy46k9Zf7PkfH7GG+cPef3WmxxPb7E/3mN/vMPktQ853Dni7v4DHj37mhfPnjK7uODy8orL6oz1YoUdF7z/a98jiSQn589II8VOntMuV3zz6ae8ePwYL+HrwBKFPQd3J0xHY1bVJUGkML7FdD06TJFqmBx0jWWzvMJ0ApxGSUMcFEg5AEedBe8V49EO1rc0/Ro89M5gnMFYg6dFKIE2PVU3Z11dUjdLtApIkhHCBngMYaRo2wq9vQEZ2VF3LUJDVuRkeY7FU7c1dVvTdi3GWE7Pzxn3Y6QSVPWap88eMRkXzGang9U9TQjCENM7smzEaDImChOkd2giVss1F6fnnJ+eETlNFCSYbU9MymE9aLXlRm7fg68KwKudwB93/WsVASHEfwf8FeDSe//B9rEdhtyBBwzwkL/hvZ+L4WDy3wB/CaiA/8R7/5N/1fdwzqEQdO3guy+KAtP3tN3AF2jbeuDFhxHOOrquQUqBFENWXCA1yiuss9iuw1hDXhQkcYwMwm85A0Eck2YpTdsO1mMxBGaabTMxSmJ6Y1itVggPYRjQdjUCx/RgSjbKyaY5tW3ZLBvSnZw4iNjU5SBTbYedgZaSru8Huo3WgzlKa3b3dultS1mut0GjAUE09CX2d6Yc3D6iWixweIpiig5CLq4FL05fcL2cc3J1SWctH/7g+1ycX/DZZ5+ST0bsHUxATDGmJ1HZgO1qehqzQaWeveMJos8pFyU//epnOOm5uLrih9//EfeO7xCoAOccWsU8vPU6RZpzfOseH3/6OZ88+wk2qMmnOaWs+fLmC55ePSFxEXdGR3zntfe5c3SPW6M9dt/7ER/ce4/P7zzis08+5p9d/BNu5idU65LRZMQ0z2ibksuTM2xTIe1wFDx99oRQWtJRyuz6hN/78ZzXyrsUuykKgXIC6xjGZjIkChKc0yxnFZfnV4xHuwPJ2Rvy/RFeONabFVk6YjweUYwSVOBo2xU3+op1V1L3NQ6Lt/1Ae24kVTunqme0/QqBxJiWUBcgBn5fb5sBOZYHLDcGD4wmYw4PjhmNp6zmC7RWZEVG73p666jrmmmww93bt2ldRecqtBIsN3OqtkSl8dD/UkNC1Gg0JpkWjLMC2Wsul+dcvTxnM1+hopzeK6Qbbipyy9Zkq659teBf3exeFYI/cREA/nvgvwX+zs899reAf+S9/9tCiL+1/ft/xcAcfLj980MG8OgP/7gvLrdmIds7vLOUZUmkQ4JA0zQdXdfSdh2h1gMrwHWILYCx7Rq0EMRJgfbqD9yNBzeh+rZxooMQqYdfTpoO6LKqqnDOYqzFWEPddUP33ThsP9iMm6Yh0RG7+/tUVc2mLmn6jiAe8vnaumWz3CCFohiNqbuWcr1itVkTxRFhFCCk+pZ50Fsz+MrjCOPtsMNoW3rv2NQV8+WCm+UCSzAo+Q6P6b3jZj3DOsfl1Zxvnj1jtpiTFSlHRwckWcD5xQlNu+GBukdeRLRtgxeWyd4ILaaYOuJG1zjr+eLZF3z9+BGff/EFf/nP/2U+ePt98jwd7hwojkaHjJMJ++khcaz5/OVPoJeEkwgRCVabBZ9/+Q2/tzB8/sm/5K277/D63fe4c+c19g5u8esf/CpvHNwl9TH/8nd+m4uXz9nf3UP1HefPn3F9dk5br2nbEqcco2nKaKfAa8ts1XE1e8nqZ5fce+2YOA/x1YAOr5uKq+U1YZCBV8xuVmxWJeN8iveOJA5I4hDhLb3pwEMYxoRhjB3tYvqhidw2TxHKDwRf22G8gMbQdCvqdknTDilU1lqMctheIpwcqE3S4THEUUqaTyiKXQ72DkmSnNV8hY4Cjo8POXn6nJvrgZlw++4Rxw+OWTc3rKo5YDF9QRAM4/AwiqjWLVVdMr++ISZFJ4pmU3H94oxuWRIJjbADI2A0GZMlKYvlEqEUUg46GWvtQGxyg6jt1ed/4p6A9/6fCCEe/KGH/zrw724//x+A39oWgb8O/B0/lKTfFUJM/hB38I8oAoo4Tujp8Ns4sZVcD7DPMBjmnNtq1jQNpuuG7aASWGMQSm0Z6xohJcZ7cAMroGkbhNJESUIQDLlsVV0hkOR5Ttd1XF/PscYz3imQKkCgMW03oMDdEL0VFQn5rTGqDtF1QNT0tG2Hs2aYyVpo2h4ZhDRmw9VshjU9OgpQVlOMJox3JjSmYbFYkGUJm7pCScXR0V0Wmw1lWVI/X1Nv1ngp2Gw2hDbgg7e/y+7BASfXZ6hYUUxzNmWFCjRvvf2QrIixruP58ydsyhXODfi02WzGarPBCgYCT6RIp+lgLKktZ89PuPitM66vLvkP/r2/xPc++BWOjg4IwxAtBnjl27cfsDvJufflLh89/oxVs6LpG2QgMbqj8Ru+Pv+Sr774nFHwO7z33vd58413uf/gde7dOeI//Ct/lbfv3ef//D/+HiauKJfXXF+ekaURo0mBjgPynZTD+wfIGGarK9IgoPRQ1kuuLxWH4ha6D7HOs1ysuZrNED5AygDTe+I4oS5LgjCkyNPtSM2TbcfHfTv0TpQMGY/2tltlibXh0Fw2NVJIXNPQ9Bv6vqRuVuggRKuIsl2yXrXEOmUy3UFKaPuG/f0jwiBFqYRQpSgZEgUxzjryUc7R8RHL1Rodaya7E8a7I1zZ4KJ+OKKiSJKMNB8IQ9cXc+qNJQxCbi6uuFxfUl5XnD15SWgEcThg6eIgYH9vCGBZrJZ4KQnCEGuarR/Bo5QChh2B90Oexp+oCPyC69bPLexz4Nb289vAi5973sn2sV9YBIbGXoCK1TZP4NWMU2CtReIYFQXeWdpm4AE4ZwjDIXLaGGi7ljiNidMQtMTVFdYYvJCDbbjvt81DizWDKKfr+21TUhLEmiLLaTrDZlMTeoGpOlxviOKIIA6IJymHr99GIPjm62/49GcfMx6P2ZvugJKUpqVzhjBLGO9MUQnYheHm5IrRWLC3t8eyXnE1u+Ti4oLTk1Nu375DGOfDMcdY5jeXeGs5ODxg6qCpG0aTEUEcUXmLEYYg0LjAkkQxUS5ZbW44Oz+hNy1RHLFYLjg9PWU+m7FYV6RpRJwVKJ8zncakQUq5XKK0QRnNTXfJ//J//SZfP/uCH/3wR7z1xpvsjHbQKkRLze3RATsf/lke3nmLf/Hlj3ly+Q11XyH7hL5dc7G4QZSeJjSUP/2n/OyTnzCd7vLhd77Dd7/zAfFEMb094Xw+xzrP0Z0D7sZ3SHdG+MATFIpoEtCLGtf1mKYhzBXGD0Xe9dB0PXSevoRIZkgU1kJWpEil6NuWUTFCAMZ0CN/jtMG5HmvNti8z5PMlUcrtu7epasdm7mjrEukEgejou3ooogqU8AgszvdY29FLjbUdhMEW5R0gCZEECB8ivB7ex1oRRZp0G28ephGd62lMPaQVBwNnMtQpaZohlWc0GhMGGaaGbm356tHXvPjiOW7jCPuAWCq8Gxreth8a0NY6OuNo254iVkThwOGQ26bgq37A/y8jQu+9F0L88d2HP3T9fO5AMhp4c946ojDahiYMcse6bum9IcsL+rbBGEscx1hnUJIBO26GI4QWmmm6QxKkdNbQdi2275A+QBpDHMfDmd15+q5jNpuhlGJvb5+ubri6ukJ1IcpI7u4foYWmLmuauiEuEpIsYu9oD7VVNn7+ySd472i7Fh1okmh4wfNpOoRLlNAGNc2qQYcBURITmJqyLJnP52TpkHVweXFOGMWEQcBoMqarKqIwZJLlLNcb8AzUGOdx3tN1Bq2G5uaqXFG2K+qmIopC8nyAbSwXaxaLNQ5NnE0YjfdIw/FgkhGSKIZ8HLI72aNct3z20Zf89PlPWPo5nz29w3ff+y4PHzwkj8eEIqQICt46esj+eJ9vLp/z+dMvufz8mq+fPmJ+fcXrd+/itOP05hvSOOZi8YRl85wvX/x4GAFvVhTTiN2DXVI3Zl1VlF1J13dI79hJc6KRQgYWLwxRogmDHSIZb1N2A8ajETLK6U2H956m68jywfXp8Ozu7JJlYza1oe07VNDTm57ID2M6hUL7CB84JgnEsaWvN1QXN3SmZTzVGNdiTL8l8UicG/DzcTw0mb13eD+M4UxrEcohIomzArc9LgShxvmAOInQehhZW2/pbAfJANGRkUKHww1LiOFGFMcJnXWsmyXL+YrVbEViQwIdESpN23as1yV9P7zfG2NYbdbgB++jUpJA61frazh69v3WQ/NvZkR48WqbL4Q4Ai63j78E7v7c8+5sH/sD18/nDoxvTXzb9iRhhNaaqmqoq4Y0SYfRoFQ467DGDWETYUiiYqx9NSKBpmxZbjaESUIUDyBGaYdmjvN+iPuSw/gRBmBo37boOCHSmtZYNss1aTKmqWpWyxW+tvjeMSkmTCdTwjDAWYOUAdOdCQeHt/DSc3VzSTIpyCcjwjQgyVPG+QjWlnl7TZZlxEkycN+Wjs16TRiEHB8eEWhF2xk26xl5kZImMbuHIw529uk6Q1M3LOcLluWaNE2ZZjGNq6n7kpubG64WZ8SpJowSlJIoGRDHCVGYoHVEboZcRq1jxuMpo2yE7RuU7qgai0gtCIOfOFxqmLlrrh+f8eL6G95+9hZvP3yHtw7fYSfaR0nFXrbL6N6IB3tvoDcBZ1+dY1eOUT7F+waCnmK/wAvLTXfKZrZiur8PexK9FxMfpKxXNS9OXnIzu0FIS5QrnN7nKNkljULSOB5+jqig2fRUtaWIC0SYMYkLTNfRdC1h2A2AFC1JspQkzihGE/JROHD2wowwSInCCCGHc7Fzw7nZSYvWgjCSdH3JZrMijGKsLzFdh3fb0rJ9vaNAb9+3dvtR0HUdIuzRzmOMHTr2uEHSHirCNCSMh51BXuSkWUIjN4OUXQrQEuMcQgi61iFFhFCevnfgJXGUoBsB1g4R6koi9ZARYdwgE4+jlL43wyLfqgRfFYDtOqPrun9jeLG/B/zHwN/efvxff+7x/1II8T8xNASXf1w/4NV/NIxCxuMpYTCw3DbrCmeGs00SD4EKcZzQtvXWyae30wHQUiKFpu8sm2qD8QakQodbPbgbmiad2WBdzM5kl1GWM7+6plqtwQ2xVeM8p6obgtEu5yfnNKuKSTZidzIiCmICHxAKjesMtuuYTid0raGsK+KdjKQIENrS244sSYlyTRkOJqWb62ucd5xdnFKXFZPxiHpTspkvCYIE4zz5/h5ZHJHHCZPRmLOTC54/ecrl9Q1eCd7+4H3G45y2cpimp65a6k1Dlu+QRjEqUCgZEuiEnZ0DtFaU3Yqm79A+Js8GxNmmvKGxAm8NV6tTNnVDth8QaNiYGVY6IqF4cv2Yby4f81H+Md9/84e8+cYbTPIJoQiYhgF/5c/8Bd668wZ/9zf/Rz599BNULNjZ3yXMQ2QMRRoh4oBif8xod4qXjo3sYRywc3cPFzrqco33NU8ffc3N9Qv2j/YpkpzRZJe6dHxz9oSuskT3JpRNj7Jg+w5PD4GkaSu010RIlpuKpIAiLxAyQstw8IzoV1glP2QvAr3pcA7CQBEGCoHdpiCtcbhhTi+GXo+1FmP9lgg9LEglQ3rbo2yHxwxJxk7isUg1NLvjKEQFmigKOTg8IBwp6vWaINJ4MWRqhkGE9grT++EIkSVko4Y4zbag2hblPCoYcHl5lqOiiDhJKMZTut5xenpK13Xo7UTg5xWDr4rBnziVWAjxdxmagHtCiBPgv94u/t8UQvxnwDPgb2yf/r8zjAcfMYwI/9N/9deXKBVgjaf3niCIyHKJlpqqqjCdI9oLyfMRxhgW8xvquiaMAqQUeARRnBBF27BRBEKAMYNeIIhipADXtlSbktu3jpGjMV81Lcv5HO8daZwyynPS2GK7ltOXp4ziguPbd4iSgM60hChSGbKuNzx//IybqxviNCXNInQkEcohtQUczjvquhoIxU3D7GrG6dkpxhsm4zHHB7cIlaLrejyawDtM29F7z6KssZWhWjWsr5eI3rMz3WGUpmwWC66uzyGUSCfBabJ4ynQ6obctURSxuzOhKAr6vqcIxuQCTCeJk5QwGWgzne8xsqOjBmVIC01Tb2ialiRIcLpjbZfUVcvV1ZxnJy85/uKY91/7Dh++/yE72YSRLnjvjXf5m//53+Sf/rPf4X/7h/8zs/KCuNhhdFSgc826L9n4kkjGhHm8ZTMoDu4ckKQh6/kMXENVzbi8PqNtWt569z1sK/j4p5/y1edPOdg/ZjOtUELTbhrwnnycIPCEYYSONE1r6UxHVVmCEKTyGNnTe4e2AIa+a4ZUq77GiR6tg8EFGgoQ2zCb7fvRWTe4UfHgDd4NWQ5CMDQkjUPIlkjEIB297wmcwgv37QJXoRow40XBaDzB6BYnLGmiaTs7eEjCCcoFmG6Qy6tAMp7ucHz3DquzBbPVBToKKYoRXdvjTEeaJRSjQZtirEUw7JRRA15PCP/tiPDbntef1EXovf+PfsE//bk/4rke+C/+db7uH7icoK6bwc3nIYlThPesjMF68203Pww1pm8pyw1yy4Hp+x4l9ZYlEA4ZBF1L07bD7D8dmkfOWmIdYHvLer1G4EmiGNP1VLYkL1LySLKYb1BScvv4NnmacX52TtOWJGFIHsZsyoonXz3m2ckJD99/l9duH1LsFxhaXNeT5iOiMOZqfcrZ2SnGWXZ3dsiKnDDSKDV0rm+urlkvl0BAkqTMrq5popCurpC94GByzP54j1u3D4nHGbPNjCfPH7NuayaHOzhniXRGke0wzne5ml0SBinjyR4OS9NWZHlEHEWUrsN5h5fgpad1LXVf05kGYw1N3bNZ1dD7oaMuerxo2PgOHfZsyid89bNP+frsa/7557/LB69/l3fvv8ed/WPu3b3H/t5f4+DwmN/+6P/hrDxhsr9HshtQnn1N160omyVBrkmLEcIIhHYoP0KYFttDlh7Q90NSjmng8dMTfvZPn9LYige3c9pNQ2k9oBmNR6RpTNVtiKKINC/YNAYpIzwahwKvsE4QuAFG47bRZW3fYLoWLwYEd1l2rJdz1ss5chqTZgldb6nqHqyDcNtoE0Of6pUnpS47VGRJsxhLhzUC0VlcX9PbFo/DWEuWJIONvesJIkmeZKjAIRm690KC8kNcPEJjnaAYTXj4zrt0y45mXlEkBXfu3OXmZsai3qBChdCSm8sZy/mCLEmGxGkxkLu9c99GzwvBt8j5X3T9UigGX9GATNvTNC3eQ6gH4UTXdURBBEJu5/sZUZywWq4obY1SgHfEcYZQg1PQu4HdJqVEBwHOe+rNhlCHKKU4PX2JNY7pdIer/hJnHXES0zUd2SThYG+XLMhBCp4+f8Hl6Rk4i6kbzk9eoEKN74aO88H+Pvdfu0+nWl5eXeF7iwpSupVncTXDdIYiKXjt7n0m0zHX8yvW6xnXNzc8fvSYUAbkxRjbGZI0YlwUrPqOxXzNql8zyUe8dnSHTbvm8csz5heX7N89Jg4TFtdr8nzEONtB+mDwv4cZm7LBYzHGE4mIIiwwqsQ5wbpsuLieMVsucd4MdwwPIoDRfoZ3gr63WG+QGqwQGFERFi1Sec6bF5w+OmO2WPGTf/Exb+y9ydsP3ubdd97lz/ypf4eH73+P3332MU+rR9T+Cq8EQvSYtqNpQ7KiGPIPQ8lonGHaktWipmsNOorRUrMue16eXg98wqwgJCB2Abr26CJkNB0hlaFelfQoimiK9oKud0MBkMGgs8fj5ECNdt5gfY91Pb0bioDrLVc311wvLliUc4J0zHg6xROhmoHhh/MY3+NxKDWcKqRWmNbRtkviTqLDDGeHSYQ3DZuyJNLQdS3GOZarNU+ePOH19+9QFCmL6pI8G9N1krLcsJ8WqFAjdQw+RIqY/Vtj3njYMHt+hWp65LbpJ4RktV5zenbOalEhvYJe0LYdIg4IIz30wRx474bdg7PIX3aegJKD5BepsWrIBrDGEIYhcTKgwdqu5np2TZ4mSAZdvJaSKEio64rGVSRJOgSLbsciaZqggxAvJVJJhBKUdUldVkxHE+LpmPV8Rt1VRFozLnKm4yntpqX3LevrGYEMkM5jjGO53HAzn5PkKWky4sGDnLuvPSCfjFg0c9rO0tYNSi7ZtCXL+Q1WtMRxws36mpOLF6xXS7T3rGcz2vmSvTt3mO6M0FHEweEB5XJQEu7uTGjKmjAJqSOYm47zbsNbv/49bt875vrmmvPlJdZZ+Y4AACAASURBVMYPW0zjDIcHt5DSslkv6ExDnAW4IKSip6ZkXc4x647Lm+e0ZkWWKYIoHGjEkSSJCpxTrJYlTg7zZRk66rJFSIgnCV3niBOBiZf81m//Nr/dBLz12nt899mv8vCD17n94D7/9nd/jYflMZ88/ucs3VOWbk7vWqpZiSpviHTEtJiilaSuWpbrFc41JElIoGOaqmMSp7z52jGm94PoJ/KIXHLn7mvs7Bzx/OQrLl4uENqTp7fIsh0iEZAFI0KRbAVolqarMPRoNSgOrRt2E64OeP70hI9//Dkvn58SBLAXxrhRg/MNUg54ewjxxiGcJCAidiG6h8BYVJyiwxSkx/uOtm/omxKlFKZuqNclq5sZm3VFniccHO+SjDW+SSCMiKQE9NAkdBDoQZMiTI93UExT7r99n5uzK66aFbVvmRzvY41ntp7Tezekb3nYO87Raoi86/t+2w/RmEBSlQ3231QM2f9nlwfbDnelJBqUbptyTdcP89hXlXy1Xg6dbeHJ04w40CRRgqk6yrKhikryJB2SftXgLHT4rb8goeuGbVqWxYCl73qyJEJ6SxxKpqOCtnFcnV/hq57Iaw729ijCmE3bEEQxTdcO0c/esru7x2hnghUeGYSk2YR+uUQJRRCD9RVOtRil+PLZF5ydnDOKcw7HU2h7xlHCKItJ8gAjPSKAxWrBZr3hYGePylf4saYeBdRRzmVo+fXvvsfeJGdjS6Z7I67nc6pmTSoz2tIyn10yW10hAsfe4ZhwXGGtoexqmrqjbxu87EkzgZYOydBk7XvParXB2xCphsi1pmvwokYGmqbfnjuFgcDRqRkiXzLr1ny6uOHFZ59wOL/P688e8s69d3n77kPenB5yPb5FI+ZsfI+Yt9ysL8nzgvRWTuV7Zucz5qs5o0nE3t4uGIlZrdhJRkR7CVfLBWEe4QtJO7ZMDm8xCY74bPE55y+XCOU5vtVwMC5IiimjdIz0CikUCOgtGDc0yJqyozeeUCbMTmZ8/Ftf88XPHtOsSvZvjUiPNbGVeOnp5MCnhACMJ5YReZAhjacvNygnCIIxgmTrP3D0fU1TDUdJYwT1umI1nyNVQBrFhDLHdopYRfRlR5IGJElMj0VJgbUdkdKkSQSdJ4hhcmtCazuuL64xVrJ3uI/wkpenp6i2w3pLEIQcvXFIJBVnT19yc77BOEMWToiSgrrvaOwvOXLcGEPbtuggQClBMcpx3nJ9fY3SisNb++hA4/qeum6IlGZnZ2eIC9tsEFIQhyFd27JYLkmzjCAKB+adc9htJJkzQ6FBKrq+p6trhBDkWU6cJJRlxbze4Pp+EBh5y6YqGU13GAW7SK0xveHy6pJe9AhnsG2HRhJqzbgYEShFliaYqh24BiogSzP2dvdoqhZrLLXvUXFAGBYE2eASe3l6Sl01KAtRGLLZVFR1xch6Ah2ie401lvOLMyJ1iNIB43xE33RUVwsW3RWnpyfM5pdU3YZ3P3jIeJSwmXuILX3b4ZzB0JEkIXGo6ZsGiUIQslouub5c0PWevYNDxtMJbdcMTS4psb6lt6C8RaiIalMRRBFh2JFlOVme0rLmy5NP+Or559y9fZejOwc0UYXVLb7vSHSKlxLXWy5OT9lUK0zXEciAOMrQYcq6qmiMHxiCaYBfr4dMPy+olzXfPP6Cc3PGyckjNpsbwiSgtzU6kehUYUS3Bci4/5e5N+mxLFvTtJ7V7u70xzo3d4+I21VWQgkQVSUQgqwBEybM+AEFo/oFSCkYMUP8BoYMS2KGRA2ZlASIglRW3iZuhPfW2+l2vzoG2+7NBG4ok6SQ4kguuZnMjsldttZe6/u+93lIwaH1lCsZxhHfD9SnI64b+fW/+HO+fPsRESVltUCZDFvMWSw2U1r05MFHjErTsJAQeMwkrxE9Oi9Qo2R87rGFnU4NwRN9pKkbCmlxbiJPzRY55xcXfPX1V3Rh4FDvGIZADJIYJNIalM4mGQMSawqM1vjC44eB7lSjY6KczRAx0LQ1i0WFEAvKqqLte6I0rM4vCF5y2ne0hxPORSprqPKcdnf4wfX3o9gEnPc8Pz9RlCVlOU1TZfalvaOmWoBznujclCOPicwYpBB4P/U/Z/M5Qk9H2GGYIKDihRbUdx3HwwEBLwjzjOVsTpllHNKB+njkeDoyYyIMRaEYfEfTTHosU5VUmSXLc6pScjzt0AiOhyOf332kXFfEDLRULGZzcmtou8A4OPqmY7s65+LNJY0fORwO5LM5q6rCvPg7docd9e5AljSZskTniUTc6Dgdjwxjz+Adm8sz6r7jcfeMCJ7c5hTasru54/7unvfvPzC6lvXlnLP1hovNGV41dGNL8ANCJ7IchPKEkJDSYETBUDs+f3zkw/svk5I7Kzm/vMBmlq5vgIRMkejDhBWWCec8yiiSCog8QDXSqgFbTKOzu/SF080Np+HAKTyjjWBdLSmZ83h44sOH72m6I9Wmwlb2pZbheT60eGnIy/kUGtIPnLqWw82BQbXs3tekQ2BXPxF8Q6IkhA6TSbKZJsWAzcTL6SaQkkQqQ/LTQ+T99+/48Jt3HH61o98PMIItCozICF6iRDadRlqHUhJbSkyWMTpHP9aITNNHTxxb1loRnQcdyCSIlFAvyVXvI94FtNJoY1nM16xWW2R7moJQGKySaGWR+QwtNRZFJnO6rqftPcPQs9898e77b1lWS86/+pr9/sBu/8D55RWb84tpDmA3ErRAZhloQ1IKoSwxwTD0+NEhQ/zB9fej2ASm+9tEFRrdyOhGEoKLy4vJYJMmQahIk+RjEod2ZMZMYEVjsdYizZQdkEpzqk/4GEBMI8XWmGkzGR0pRvI8p8xyhn540ZV7nPcvR/2EMRZdacpqhouBp90Tut6jUbR1TRSR3e6RQThSBqtXW6pFOQU5Gkcaw8QkzBJjikQCq8s1b37xDa+vr5Ap0R8bPv76Wz7f3TIvSpblgvpY8/y8x0iFloq+bkg+sF6t+JM/+Ud03Yn+eADvSSGwKCqWr2eoJDg+7Yii4Bd//AuuX7/B2IyURrJkp0TbOBCVp28dmShY5We4U+Ddr254/nJiZlbTIrY5uc2AOSk4gn9pl8WJ0hRjpFAZMkri6NFaklUGkXtkFUh6QM0L5uUC/9xyeorYZKEJdI9HDvf39E9HstIgxoguLV3jaZ5rkjCUizUqWZqmIy8qxtDSDx3BODLfkWKgLCzlbEUUnro50vc1q/UZUhtSDIwukJKnqCyEwMPjni/vPvL5u/c8frmlSBmb1Yan5xNKTZiz3e7A6bQiqSks5MaRPrbMqgXKSkYCaEGUkT4GkpwGdGKQEKcOltUZoy348uUzp7Zjtd2QlXMScqIBY6jyFdaUU9sagdIlJFBSI5WhOx3YPTxyenjm+fmeU/1MYfU0GyE8EY8ysD1bcffwxKmrWZ1d4UKi7Qe8T0ipsWaiDg1tj5XqB9ffj2ITgDQVM7T+feJJSsWsKshtRt9PI8UIXvjz/vepwqyssHmOyaa4cAxxwoy/EFeGYWDoB/I8n/BjxTRq/LtxX2U0m80arRRKK07HIylEjNEIa1huV9Rdz/54REuFRpDJiXgcvWP3+MhvfvlLXo9v+eO/93epipLYe/qxpm87tJ1ShPlsxtnbK4rFjJgiTd+zuNpwHb9m//TMTGfsnp/58vELJstYrM+Z2wKZl9TPe87Wb8g3K77c9Hy4ueH0/MjVdstPfvINucnIbM7j0zNXb6/4B//BP8SuLB/vPtI+78gs2FkxVY5VwKeA9BZ3gtvvdnz4l3cQBVdX56hCY4JFBUkmLdoLUpyIvwwBlSR+jOSLGb69pT854hjJVYa2Aq8cQjsGd6I+emI3UIWc3Be4g+f53RO74xPrak6xLDkMNd1xpD/1BKM5v7ogzxd0Tc+xrlFaoLxgNZuTTEA0Hm/jBKM1ijE4xtZxeNyxyLdI4yeugM5IIbD7csenj99zc3NDkVneXrwlixkndkidWChYLFfMliXDeODLlzvKpURGQ/Sepm/J1YyzV5c4EXhq90CcXBbCk2LEDdODQ8vp5AqC9+8+cjrWrFdbpM3o+4Gu7yforbVkspioRcMIIZ808GG6vmpjGN3Il/vPeDmyPp9R9zu+/fBLUpCMsacf2+mkYs2LNn1DpjLKrGSxWND5IwDDMFJ3DbPZ7AdX349iExBCMp/PWSwWZFnG4Bxd29B0NePY/x6blEKgHhzj0JFpg9QaBORFjjbTdGDXdxz2B4ZxnK4U2kAGbnSoskQKiYiJvu0mJBOJvMh/DzWJIUzcAmUnq1ChGYeAEwHvRkSA1cUFPoyURUHIJSS4u7mjmlV89dUbfDty+/mWrhvYnC3IZgX5PEOXhjYOHIcWCWipkZVhvpqzkgWh9mhrGKaUO68vLuhzze7uge3rC9qnwyRD6QdiiEQhOPQtuigpz88Q85J8syYaTeM9Y4L3v76lfXji8ucXbL5akc0zVILjQ8399194+nAg1ZKz7Tlnswu8HLBJUwiLyjLGvKYdHAMRnzwiykmlNSia3YBrEs3jSOZyZrbieXiYhGQp4UZP7ktUsDy9f+L9v/zA88cndKbIXhmcGiBBc2w4hJH162syPcOagpT/ToPu8OPAcr5AmcTxtKd3IyoprLUsqhIjNHcfH2gfHX0X+PL5gcfHx+m0mFuUhmHoeP32NUVRUJUzulUPReLqfMP52SVZpvn4peXzh8+szwtmVUFp50QjUbpks3yFV5HntkPGQBgSSQeMlrgwDZgpJXHBMQyO3e4wiU5fYLB91zAOPXk1I/qAzAqUtNOotyjRWiHSSAwdkYQwiaAdokxc/vQc1znCGBi6QC4tZVVOD8zBM7YDT7f36KhQUfDN9Vv25pHH+wfuHu4Y48irr1//4Pr7UWwC1houLy+IcUqA9W3NfrejbVuMNSwXS7Jsgon0w4B3nnk5Qyk9jUtqDTGAkGibobQmtC31OFJVFcvlkm6Y5g+GYYJUmt8x2l9ShT4ErDGsN0vadqondH7k8bAHqzl/c4WKieZpRzd0ZIWhpCDfVJTnK+6Pz/zm17+mOR2x0fDw5YG6b8jmM7wICKsY8PQpIAtFStCFkeZ0pO17CilYr1egDE9jS5KKU9/RDIHb/sTr+htstGRScH11iXr7inJe0gwDx+hIpWXz6oLZZgnaTBQeH6mfe+6/300tP2motkBKPN/WHB9a2l2HawP51rKolnjRMcaBvu1Z5JPQtE2JJCVJSAISiWT3dOK074id4HDbcP/umZ8s3vJ29YY2tMggUUFzujly/+6R+w9PDI8dRmcsqjkyKsbGI42iPznqoWO2iiQ3aeF1nlFmhrF1xKFHuoJcafYhMkSPfFGZn6+35KYgnKYW7nFX86s/+yW3N7dILdmcr7GZou5qZuUMsYGQEmdfX0BSMCiii9RdTQyBru5YzHP0PEPrjCyfs9icU8zXODxltmLwDZ3rIQR0YUlpavGREmM30jcdWZGTZRnCSKSW9GNDSg5tJKe6IQkFZnK+WzRWvqjJkqP1I33oIIt4O51qbWYo7QrfRVwbOd9eMLwYrh++3FPf16iQeHt1zU/efEVczPj46SN1d+Ls9SV/9G//a1Pg/w+8fhSbwBR7hKY5Udc1bdtMxNwQyMmw2lDmOV75CRs1SLK8QCvNGAIxQfKBUzNVQMs8J88yTqcTMUbKsmSz3rDf7WiGkfhXZqtDjLiX1FiKkcxI8jKnWszpg8cLyeXray7Ozmh3Bz56x1h3rDcbaDQ9gawseLN4w+PugbquycnwcUKIZUVBVhUklRhDT9ACXq49OsvwwdP2Lf1+xzfXP+HtN29ZW0WmLexOPN18oBk7jvWRq+Ulj7sj2iiu374iKoE7HIgy0XU9Opu6CrnNyIzhPkrwEi1yxkGye+yox+mkE/qAsQVZMeKHhro70Q8NqpI4P+m6q3nF4ajofEswGVFGiBGpDffPj5zaFlyifW755f/8K4a2483fucSrAUKieW65/fUd3eOAGA2vr75itZjTnk4E53C94zh0ICUzNcOdBoZjg1hU1IcHjrs7hvqADAP96YR0GdpaysUC3zmMKVgut2Sp4PhQT0/G2qO9pJTT126qDUl6Hh/uOex35IUlnxWcXZ1TlXNO9w2/+rNf0R6O5EawLBasqw1VVnFsOwKO68WKfLYgjT2L5YbjKVEUOUm0RD/lTibCtaFzPfv9M6vVguiZsGWZIiRHwmM0eN9P2RclCDERxmmy1cepeGsyRTOceDw+EMVIVRYTlKbIWG/mjKdIdJHnxyeeHh4Ze4dKDTjP0eZ0my2D6+hdg64sq6sV2Sr/wfX3o9gEwksU2LmRlCYwaFVWWK0nYWaaqvrr1YphGLi/v+fU1Czmc4TSDM4jJIQYUXLyyQc3WVmybHIRSCHIs8kB179sMDFOqUTn/Yvoc+RUO4qqYJ2fkZcLjsPA+fUFi+WSuj6SL+a4cUTnBjGqaSAjeKr5nDfVG57vH3Ctx5YFZjVjsV0SVaL3PeF3c+fBv8xza4a+p60baAaOzQkWJcXijPPLC/y25o6O7rDj8+6O/XCkbvZcXm2QWuKip6wqymLGPu1REd7/6reUSnH1+oynD18Yx4FX37ymPF9AIdFlhvM9SgwUOpL8CCpQrC3JekYSQ3KMOBbbFcduiTg8IizEzhNTwhjDc/OMyiRxFPghEMeRL7/8wtOXW1p/JMstrouEU2QhlqyqFYu8wg8j3akjMxbpJe2ugyJjebbC2pJ2f+DXxwf6/sgwHBn7Bin/ki+htKawFifdlOeXBiMLEh193XM81ORmshllRvP69SXKJnp/ZBgbTu0z+fyceVkhAtx8/MTdpxtmJqe0M1wKCAe+C4zdSDnXzBdrsqKicY6YmH6/CGim+ggo4uB5eL6nawZIivl8ztD32EzjQs/9/Q33958xmaA+7UkpEHBEL9BOIBgYQovME2PscMFN7kJlycoSIw3KZlTzJet5zvG+5cvxnqZpsFZjo2K5WrJYzPj0+QMPj/fU/Qk7t2SLnMOw/8H196PYBGKKU277RSeemYxynjMMA3VdY4whf0F5/T4bLQRCTjShcXQENx2bhJSTeXgcscZgtaapa04xMp/Pyayl7zq6rnthFkx+wpQSwUeOpz1RJk5DjfMtoxS0YUSNHY5IMoJ26Ng3J3RuOLu+IChwMRCd4/7+gTBGFqsNeZmhrJo494DQEiPMxNtPgmZ/5PbzF051zVwaDt2J8Wg4v1gSC4kPlsWbc1Y/fc3gBz5/+YjAU61mJJno2pbVesP12RVu10DdEw8Nn/781zR3d9zffaKcGb766VvsrGQQkagTx9NL0rEsKHLJ9nzGar1GZ4ZT3zIKz3HoGYFsViEzhcODhjR6Rt+hTGKxKhiCACLrakGpNI83dxzaA8U8Q6Ko7IzSZigBzw8PdG2DDJJqlTMrVyhV0OGJcpKQnOoTt88fKWaa+bIkhmHqFimBsIboRwKRoszJVMEYEkYE0BInEslEsmVG6Qrmi4rFpkDoyNXrLaduhw81+0Pky28LmmPPh2/foZGsF2uMlnT1kefbJ/Imw5Q5F8stq3LO2I7sH/ecDg1SC8ZxQBcaQUIkRdO0fHj3CatzLs+ueRpHlJnoV+PQ444Dnz59B8LRDiMujmR+gqMQRnovJmyeS3S+IaXIrFpMIpSkp0h0XqFURmYLbOFoXcNpOJGbDC0zbJVx/dM33N/ccvhwZEwDuVYMsaMZTj+4/n4Um4CUAp8C6SXrLRUYrWnbjtPpxPnZGfP5nL6f0FxKqalOkOcgJDJG+qbFhwnsaawhFzludLRNCyTc6LDGINXkDkwpTUlEO+UJhJQE7yirgu3VGbPlgg/3d6gq49AekWaad+/HlqgiY/JcX79l8+aKxvc0bcPndw98+vCZMi+nxeM1PjqMNFMRUiRi8AihIEROj0fq/YEUIyoz6MJSrGbMzxZEBZ+fbnk+7vmH/96/i9KSaAPP97eoXJNkJIQBIwSp7dh9uqH5cs8yKeZJ4fY1K1swv1qxuVqgswIvYF8fGdqWlDw6K1idnWGUZhwDp7rHxYixOQjFqenwQiCUInZTMXYUEde0LKqCpmvIrEIHQyEzimi4zC/Ylku8HGi6GisEwXXsjjVhiBgURV5RZRVn2wsutOHz/oGH9pm2rsF6NqsVOp8UcjYvwRiiFAyIaTCHiFGWMq+IMtDFAVEpVFDMZEkMBrs5x1qDUy0+jti54HKzBuHxIdDu97g2cXl+hhYZWkzDPovFEjecCO1IaQvMCPE00vqBft9jo8UaS2E1IU6pvhQlfTOgheH11Ws2Z2eMriOKgkREFwpjBd637A8PJCGJh5EsTFmNQR1R0uCjR+ipWG20YV4uQQi0MpRZQWFLYhTTBGD0yFJRbjKM0IRBsHcN61dnzDYz3t++p38eUEbRjz193/zg+vtRbALpZQ5AJshzS4qRrm/RWrFZrZjPZpyfn3Nzc8PoHFoZhFDENGmYQkqTminP2axWpBjZPe/o2o5ZOYE6YgjUp5o8n64HWZYRY/y9vlxLhc0z1ucLfv7zn1MsZzy1R5wWuDDiwoA2kmJWMvYz8qpktl2RLUqSU5jMsLt/pCzyKd6cItZOPrhxHFG5xqhsEqkGKGTGOER0lFRFSbVYUG0XbC43lKucKDzB9dT1Ee9HkjZILdCZpBsaYCS4kee7Wz4/fsunX3+HOzbIGElZRlFVLJZzqvM55WzChKENIniG2ZyQBjJjKMqS+WzG7vmEPzRYm7PebqmWJUSBc2BVQYiesXNkaAQGH1tEDGRWop1kbBpSMOTGoq2kcQ6b9HSi6wZO9REbMpazLdvlhvV8RWYyDkPH8+6JJrUTcDO3bLcbfBo5NCdMYTBGkqQg2Yz1uoAUaNsppTcGh8wyZCFILkz/RyhSryeQaD6iZGI1mzGvcorSIIVE9nN8r2janv2hYewd83LJzF5S7x447Z+QLtI+HnkuHjDVio1ZcwoK3/eYXPN0eqQfR0RIDO3IcrZiuznD2ozFakkUiYCjihlSRELwDF2NNJoxtIyimxBhusTojJgSShqMyZhVM+blcuogvLgFY0h4F5ACTKZZX66R2YQca3aAh5grjM6p1jOOwwmVGWw2dSd+6PWj2ARimuKaKUWUkAQSdVOjxARRqIqS6Cbqr5IapRQhvcwNSPky4/2X2UnnHD541Es/f+j7qRugNG3T4kaH0JLVaoXznqZtGMeBQudkZoKVdF1H29QU2xVFkVEWOdU8ozsceby/xRN4Ou5IM8tyvWa51Dx/uWezXDHGgMoUeWFJyTO6gNEFtph89pnSLGzJzaGhPzRYNNoavEg4Ji31Yl7xxz/7OZA47XY4ERj7Bq0lD493WC3IlOXzzTve/flvSQfP3FYYpQhEBj9idcliPWc2K2j2Lb6pUT5ytVohjSCKyHK+Zr3dIikYBtAm4+ryCpkLRILoPDpJ4hBxp45Sl1QmY9/15EZQrgtcHGAQ+Hpk93DCFoZB9KhSMLMlKsBoDVXKOVttWMzmdH3PU33i4Br62GEXlnyeIzKDyivm1Tnl0tH0PS6NRA1BgtGWZVkw5JG28wiVEUXiNBxpUoMpEiGNoCO5tRTVNH2aGU2ZZXjXc9gf8LVjPt+SLTOU6ylyy+XVNXNjuIsj+6d7/DDS7I7UxZGNXCJRPH56pndHZkvDY3+g8wMaAV6gdeLT+w+M0ZNXOd3YMfphylukwHI5Q1uJQaFzjQ+TB7EPYeI6RImImsxXVOWCMp9hZIY1E2nJjRNJKwVP29XYUnFWrAkx8OpqQ3cYqPsGA1y/fY2Pnv1pR4qO3X73g+vvR7EJSCGYz+cQ01Q1doJoXsZU04ROPh6PuH6kyIvJHjQOWJ8hQpxqAiHy8PhAU9ecbbds1mv6puOw31OfThR5wWq5nDYQ+ZdFQQCtNOGFOpNC5OnhkWPf8HB/zz/4xc84X6+RKXE67vn2N7/i6f6BpevZjd3Umrs4I/rA0/0Dp+c95XpOWWQYrSBFItN1x4WAlZMdud/XPH9+oN6fUEKiS8tmVSAzibES/Mjh8YmP333Hpy/v+dkvfkYuJKfmxNPjHV9//Zqr1xe8+813fPvuW65ml3zz5huSC7S+p1wtWZxtmK9WFJVlODWMTUuuDOvtGl1knMaBYragmq2AnGGA4Ee0TLhxYOxGUnDEFNBWs1is0CMkP5L8yGI1J1cZh3YgNgmhQVuLNTnOOca2pTv1CAnrxZKCGdpY+tExpMCAZ5SefFOi1zmitDgSSeScX/wUbTJu7m4JcqRalzycHvFNw7K6JDubcXv7SN22DP1A09ZI49EW5os5eW6RSaCExmAnIEnn+fL5ge+/f4dRc/7oj2dcXr/Czhe4MZHnFfhAuZijM8v++MTcjRibUZVz7p6O3H96wNjEuixZzy5whweGukEBVgiEfcGUez85MELEB884NCzmFbkxRBGQSjD4yaURVUQGPTEQ/MgwBAQaSYYXCe8S1kQk03BQNAKV6+lBk+fM5hVxP+OYTjSnhjRMhuf5Yk43tvT9QD12P7j+/tpN4AfEI/8N8B8DI/Bb4D9NKe1fsOR/Afzq5dv/eUrpn/z124CgaepJFCKn9J9RCqXNhA3ve7zzeB8QStF100BFUVbkRYbNEz6M0Ez48qKsKKx5cQYMNHWDkgo3jiAEPkwK89+hl5TWFEXBrCyIruHx4YHHw576cOBsveRsteJwOPB0/8CnT59YL1dU8xlmXjJbzEBKnp4e+fThM7vHHcW8wMhp2IUYJ/ILidG7yQEY4fn2ieP9MzhPFzz744niYknbN+yf7rlvHJ9++YEvXz4RCJxvVjjXcXh+QOBYLGast0uW5yvK7ZJqtmJ1fY7vPbJvuHh9xaufvsauDCH0FDOLCppcKbarKcoaO4nKC6S2ZKWinJd0zcgwHmiGA1YavHT06YhZlJwVGw6fH2naE8Uit77n2gAAIABJREFUY/1qNanea4lBc/n6FRu7Zf904N3HbyEF4nRgY71YUqoVRhUkJbBqAot40ePLRCgE5IqyWLDcXLFav8GakhgrpI3MtxmrccunX36HcCXbi9f0tSL6J0zoyM4Uq22GtQlpIpA47I8cdycyNccoxVB7pJjz9vUfs9ycszk/Q+czbKVJLiHGiBtb0JrFZoW2mrNXlywvt+SrOWcm59/g36QoJVY7+lmGvM24HT5SH/fMy4qv337D95/e8+nzJ7aX52SlhlbQjA1unH4XpIAYw3RPlwIjFZKE0pIUmcxI3hPiVOPq24EQEiL9ztYlCWHKNnjv0VqT5xWOgVNTE/sRiGTaorWlcyN5XvztNwH+sHjknwF/mlLyQoj/GvhTJucAwG9TSv/W3+B9f/9KTEU6KQRGm6lQpg3z2WySKAj5whYo6Pqevu8RaiKlWGsx1lDkhuvrS9bLFUopxq4jzzv0SyFwPpuTvYwgxxAoZxXVbEbfd7SHI0FAkVkypXDjdHxTAr58/DwFabrpVLGcz3j9+prFdkOxmlNWBfv9jqfHB06HA/X+SHuak6JHicmG7H1Ept8VBwWu8zzePfB09wRRoIzFFIa8zElExq6jyAquv7qmCR3Hwx4j4dQ0HB+fuHxzxvnZhqgSy8stf//f/3cQrWT16oJMWu4fbklGYoocU1qGtkEZyHLA9zhfI00iqzLsYgaZxYcWL0e86CE5HEekNAQx0nKizDOyVUZ4iHT0bK7XzC9KjoeB6lVBebbgTF9ie8vxyyeOXY0tJUobYph4fqrMmM836MJQh56dm+6seqFopMNUBduzK5blFUrOKbIVV+dzXKiRYuDNZUUxFOiQs6wumf/knCQjOgtE0dCNj3y6+Y7n3S1CCtrdidNuIN9uycyCQ/eMSEu+/vqaar1k+B2OzAA+UT8dqZ8eiMOJPjjyVcXZ20vybcXBN8g849VPrrFyJI4HVudXCJNjUdx8/IASYoqwh0DbtpxpNXW4mpbjsUYKWM4r5psSnxzeO6RWhJBIAjKj0VoRpq7jy5/JoRAHzziMdG1LbjRlWSCE4PHhkdPhyLppuHt3x373xGa1ZLWcY6SaJhZVxquv3gD/w99uE/hD4pGU0v/4Vz7858B/8v9m0f8/fsaLi9A5hxunWYEX2huZzSFCDNN8tvcTRqksKxbzBavVcoJHRkeeacqiJHpPe6xpmxatNWfrLSLB48MjRZEzny/IiwKlFDbLqWaBMXi6rsOnkSQElc2Z5SV/9i/+D4axxxjNfv/Mm7dv2J5vKOZzsuWCECPHQ00MiSLPCd5zOpwY+xEt5LSrjwFbJmyWoZKkOR7ZPTzSNTW5zhi9J8ZIlmfkeY5WAmUUy/M1P1U/4fbmBucc0TuKMuftV1+xWC3Zdy3lcs7Pl+fQJq6WF5ioGMVIJCCEwBNoXQ9hQApPDC2nXmGUQC9KpNV0buTp8MTt0w1+2DOfC7AjpjRAROeClAm89iQbiTZNROEs4ZQjWxrykPF0d8/z+yOPuye8iIgwUZ6tVRMC3jkCiSybJh+z4BG5xZcRjSCflS+nuwqtMiRTPgAZplZcDHzz9heUckk1L8ms4VDvuXv6SNMcODX3nJ739HWLtZbj84kP7x5IY8WbV2uCVyhhmVVbUpJ0bTP18rVDJ0l7bHm4f6I5PVBVkny15uBOdLvPKLPm1dXXyOB5uP1EphxbY5hVC87PL4hu5HR4ZuhGrl9ds73Y4kTicNgTnKM2mqZtqOuW+brCjRP5WCiFjOoFXmoQwpDC75TpfpLuKEAnVIA8NxilEQlc77i7veNwOLB8/kSoA8E7KpMx5hnaWN68fkvIJOV6/oPr719FTeA/Y3IS/u71EyHE/wYcgf8ypfQ//aFv+r94B2Y51USHBMRLBVQREcSYIEXC4Eh+RBNYL2ZcXL/i8tUZKsvxCcbR4WKgbkfi6On7RAyaRbFFpkRzOqHJmecrlLI0zUBIgeXZhmWR83Tc4RGEPmEjFIOm3Cce6wc+JUFYSNTC8OYnr5GFpliUZEVJ0zmSUOSzBauzcxabW2InefruwKI4x6wLlPbkaBZJMTweuP/lt6imY21zSIKhc6yyOWeLLVlR0TNO93Dv8Izs6md+/d0dr64uWb++ojo/J9qCODik8IgIWWFJJiIQzNczQgxIIabr0DDBVFSu6ZOiSYkiJCoPwnl8cPT9jqa/J6YTMmqs1CTmyJRj/Ix4MlOKL1cUS0UqI0loVNLoIOjqZ77c3LLbN+gih5hwY2B3OHF1fQ6ZxoUj3lmcT8TComcVYiEJqYPWUSBZaMXMBnTWEvOEEJJcCqxeoKygMCtKs8CFgZvPH7h/+sihvqMfH+ndM93YoLIMpUv2xy+8//CI1ZdcXU4Pla6vebj7hOuG6SopBKnvUZnhcjNH+yt+W9dIrShWFU184rne8frN36O6WhAG8O0jn25/y/G7b1nPtry5POPt5XoaGpstSFLjiPzFb/8CIUHbSOcqjqcjh3FgmyRCWqJrsUGgQiQJgR8VNq9ACbpxutYInSCMiOAxQFVMmYPnxwN3dzs6B80Q8YcjF/OJu7HrWg53PavzLV9/85bybMXt7uH/n01ACPFfAB74714+dQN8lVJ6EkL8feC/F0L86yml4//9e/+qd2BzuU6zsiIh6IaRiYQkGQZHEA5BQkvB2Hd455hvVmw3K8qyoHaOceoVIqSefvl8JCZYr88wSPaPT5xCQ2FLjMro+5FjfcSLRLGYI62YqunGTqAMD7Q98TCQJ0kYRpKc2i6ikiQDTnhyLcjKAtN7tBFcf/2a/njg8d0jd58emJ9vOSstILBJ448t99994OH9R7Z2yZuLS7phpO6baTrSWLwP1GEkLzSKwMPTPe8/fM/pdOD67RWbyzOyWYVLCaEVQgqa05HOR8b2SJUVaGOozJQa7GI7yVyjwxaG0RlcmgJVoW3RNkfKiBQOqQNpAmgjAoz9pO8aGof3NY2FyIgpwUtP8JF+HBmfG2LjiMaRbw2MiqQS7hhpho4+eZIUaBUItmeILYNzxHKqD0wyEYdIPdEf6UdwpkWrDCM1mcoQWBA5xzHRy4HRdTztb/EMzFcF/qTwY0SZCTSbkmW1uuT62rFcn7FebyEKHh5veffut7RPe863F9hi0rmv3lzx5voVhbF8+vgJpQXVrCDkEWJA2JHeN2T5ivXVJU/tDR+/e8ewqPn53/2Ky+sL8qLARYELkjEEiiKHU8Dmktmi4NDs2dd7mv6CxSzHCYMIU2jNR48wEZvb30+vBpsmGMzYomIikxZJ5Ljb8/HjZx6fnkEq1pszlrbievWKfmh5fH7E5hlowalrWGXnaPXDS/1vvQkIIf4xU8HwP3whDJNSGoDh5e//qxDit8DfAf6Xv+79rLWEBK5uIAqEFKQItsjxbiQEj3NTxXWSZooX03CaUllCEpwnMeUQQvQUecm8qDjsdjTt6WX4xEzE3RDwydP3LZnOKcuKqiqxIuB2NV0aSZmkKhaoqqRcr1iuz/BDREVPGzqKIpIVJUkd8d6zOl/y+ptrxnrg7vaJU30gP+bkyxJC4ubmhvfff2BseypKzlYbsuB5HmuijHz34Ts64Zldbjjfvsa6kXHo6eoj68WMPDMs5xVlrvG+JYQexEgUA13XcHgeybTl8uKS+apEF+DrgeAdxigKWxBGj3eB4AdSGlEGSAmpBMZaZPAv6b1J3RZTZIwNLvYEFNJEVJD0XUtz6nDOIY2gWFXM12uOh57n+5rclCg10jeRlEdSkQiVpptNG8joPb51BCUY4pGYBloPt0eP6C2iMUitMFJRSDOlOqVkNf8J8/krxrEFOVLkFq0VdZvhhgmvPfaBFEaur94yKy6xuuTN9VuW8wVZZvj8+ROn3YlPt7dkRcbrN6+YLVYU1RyfHog4bJaR5QqqDE3C+57D/p7tyrKY5fzsq7fcNBodJV9uv3Bodpy/upiAntKAkug8gBgJqUepF0qR63FDh15WE89i6Kj7jswalBAkH/C9Q5IwCVzb44eO6EfqmBh6z+3tM89PR2KSpDgJdc6vz8iNhc5zXVwwX8w5NjW7hzsur7aU6l8xbVgI8R8B/znwj1JK7V/5/DnwnFIKQoifMpmJv/ubvGcKCa01RpmXp4alyHPONkseHu54uHtCAEVRvowKD1MikBfvWgLvRrTUKK1BiIkpoCfU1DgM02SidxO3ME3XDOdHrMhZLFdsz9dk2vP+eKT3A8Wiws4yBi2wNiPL8he8eZrYhFogtEDlkr5uiQxkq4yz19upv+2mxKNOgtPDgc/ffmB/90wWFU47Wt3RupHV5Rnn15d8OTyw6xu2b69YL1ek057CajKjWa+XGCMoC4PW0IUB73uca4mpx6UpMOKDoRlzTr0ljZKH3QNuHJhVa7S2ZFmBwDGOnhBHEpM8AxEwRoMwCKY7eAKkgKrKiEmjZCAMA9G5SSGfBMvlhvm2QMdE3zv2w0AqYVYucMWI2IGeafJ1jlhKehMmys0IfXckSoksHFGMjDESQo8fIPiJB5FJSSEMRlhEivgk6IJjHCabtPEGoxNt2/P8dGD/vEdKzWpxzvrVgpA52mbAaMPV1SukBGMUIsD+eU9WTHMes+USlKTre7LCMl8WSB3xccClgB+ODMMJ51okkiLPefP6GhUlN48f+c33v+Fmf8vFq0vOri5BwHKbMz9Z2vsepR3LeY53EJ0jN5oxWW6+3HB33/D66hsyu0KYRIGZRl/6wNA31M0Th8Pz1AqP0HUebQza5AxDIHhPP3acdnvmRclmtWI5m9P3DTdfbvn02xxh/j9ARX5APPKnQAb8sxdb8O9agX8C/FdCiMnHBP8kpfT8N/gZE6zRB8ZhRCmDUBP8AwRN3XA81cxnJUVRYIylHwbi4UDSGmkzJCAlSCVIMVBUBVVRTU8yP6AzTZHlU9Fw7Keno51cBN55Sj0Zi4rKUswL2nKiwPbRoUxJUc4mNJktWC4XzKrZ5JfrT9hSE6PmUHeoUnH+5ozHx2eaceofh9Zx8+UTh7s9OihkFChlOPUNXRi5eP2Gq6+ukaecTRi5OD+f/u1GMysLlos5i9kMqyRFNhXL2taR4ggiEuNk5DGZREnY1U8c2h2RROcdeVlOQyl9P7WaxDSa2nRHHp4C1mr6oZ1COunFtycFKSYQicIYnIPh1BCGHoVkni3BaAwG5UFpQcAxpkC2nEAvYQyowiC0opzNiNtpYwmNRwuLjhKXAlYrhJpQZSMeLxJogdLyhZcfCNERfGDXfuHxcCAEz9n2HKtmNF1PUzecDh2fPzxycXbF5s0Vma54qO85HE48Pe14/ebVVHwtC9bbDTafJhTzqsSnxBg80kouXp2zvczRZqAL/eQ1VAUpjgTnaFpP0xwxncAkyaya83Qy/PI3v2Q/Hli9XhHwrC9nHNoZp1ajVI4RkuO+xY8drh9o25aHu0dubo9oClTIMRcluSpp65q7wyOn7onenRjDxDLMyxmb7RqrphHiphnom577mzsOD3su1lvEGFlkJYus5PS058/3/zvz5fJvvwn8gHjkv/2Br/2nwD/9697zD72kkIwuTFV1nSBA9AE/jrRNT2YybJZjsgzEi6IckFmOQUIMpOAZGUkxMS9nlLOS0/OOum2IKVEWBSlM0M0QAjKCcyOFSCgl6bqOPDfMlwva+ZFd98Cxbbl4taQoJ5fgcrNiPq8QUnJsWppxICtztJWoTDKvZpTrgg/vP3LzmxvaU03qPYfb5ynims0Z2246IZSWV5fnbN5cQibZlue8KjOqxQIRp+vObDbn8mLi/amX6ciJvjSx8K01pDxjbDt6P+KdYxhHQozYzFItF+R5RoyBcRx+n560mUEpaPsDbT9xGWOKSCmISSJSIrqIVOC7kcPjERMjy7JitVjhguLuYcdx90BhMq6vr5DKoIyekGBdYBgcSmhE0hhdICoIaaR9aiiSYLFYcPA1TdfgtUNXEpKY8iDy5UoomFTzBBwBQUsz1iihKRdXWC3Z7zq8i8zLNRfbyNdvfsZPv/ojxiFizInMOn7zm28ZfT9t8lXJ9nJL/b6hHTqqNONQn+j7fkK/X1+y3Ei8fKZuBVJOAJPMFsyKOWNyfLj5SPZ/MvcmP7ptZ57Ws7rdfn10JyJOcztf+9rY6TJQ/wZTRkwQM8SEEYyQagpiyIB/gCkSQkIqIRVCKqVUqsqyM+177dufLtqv391qGexIV0rkTVDl5O7ZiXOOYvB9691rrff9PU8fSc5x8HveP97x8LhmfrXEC48NPTmJcpYznZcoIioKkk2kELi/u6XrO5RQzKczhm7g7bevsWtPTsnmYc3D4w2t21MuM86vT5hOZsi8IM9Lcl1AGkfRH1rH5nFHbAKdaHl7fEsWFVVdUZqS1vXYbvjBtfejmBj82zeQVgKjM0iQQmQIAyJGqqKgLAx5lY8zANaRVMBUFZkxTzomT3AD3o8ATqUlXd+w3W3phw4fPM47ZIrkZnTB9d6BHdN088UC60YhRSSRJNjkkbmiqAp0pqme5vFj8EghUUYiA8TgcLYjjQFyhAZTakLytMcj5SRnXkxRFjKhyNBIJZmdLLj66AV6VuJkoJxMKapitCoNlqHryYuS0/MLmvaIzgu8Czjn0SobiTbBYZ7kLF034J1FKT1i1pVBPwlXRh3VCGa1rqeoNJPZhK5PtM1xDBQ9pTiTD6Q4bslTSpSmosdxXD9ieo0eOqyD99/ccfP+judXl7x68Qqjx8EVIQXb/R4Gjwlq3N53iUkad3Cb2zUxFyxXFxx7z3Z9TxuPrOScWTlHaDHGaIlAGLVyWqKygqASjpainJHXGtcO7PdbYkisFqesZhfIlDG0lul0yScffczX337Dv/3tv2F33PDTzz7m5HRFN7R4EehsTzO0VLYe8XQkEBEfI0FGXPCkJNC6IDcl88kSrxK2/SPvv/4O3MB399/z+vF7Lj6+4Oziktb2uNBxuH0g2JY8L0jVeAQKZSREST/0WOeYzuaYHEInaB463t1/D72gPXR0fcsQR4/A6vQEpQoiAusdQmhybUYwb56hg6Yyc6bZhP1+yx//8CWn56dcXz0nn1Xs+x95ihAEg7UQxUhjSYJMPw3XxISSMNiOoR9G9JJWGJP/O3jok5FVa0WWaaqiIkTPZr3h9vaWoe8pcoMk0R4bMqMpyxyBwotEkeeslstR7y0ct/sW7xzKaObTKdWsJq8KsmJMemktyQqDiY486jEY0jSEwdLbSOtadKn5+JOPWGQLpIVkE74LlGVGkhpPYHG2RFUZXkXINKgnmWRMpARCmZFZP5lyODZMJgu0KUhJonVGanuaQ08KAZE0ZVYzRE1e5EzmC4qqQmaCxBheMZlCZ5LBR3wYkLKmqsoxoJTGBOfQjcNYmR6DNkpo6qyiOJ3S6wnt9sAf/+Yruj7Q2YTrIlKMpKSYAiY344RkDGipsINHJQdOUdqcw90D+5sD+ckUKXPq6ZK0uaE5WvJsQAtLVudklUHlAiUiQkaiEsinzzskiw2Wfujp2zH7EXvBvD7ho1ef8tUX3/HXv/sbfvrTn/PpT39KSJ5vvvsTSSS++uZr7h7v8KFHF5JSF/TBMnjHdDpFiEjbjtpvRMC6iA0CrXLKokbrHKTEyCm7+wOHzR374chiesIvPvsVH7z8iMfdPfvmEWMiCg9P2nFRC4RQpCjoB49P4emeRpHPa46iY/t6T4xjwCykEZSbbGKk7BlQEAXY6JHBkRU59aym0QfEIJgWE2zX8vb9W0yV8fJnH1KfTsnb+gdX34+iCAjAWY8bRg05SaIzxWQ6JXhH2x5pnMdGyyTXTKsJWVVhvccNFhciSibKwqBV9jQxOHB/e8/r774lDYFXl9foBG6w9F3LVM0ppyVWRGQciw5Zjt8PbO82NMcWZQz1tKacFBST8UPpbcfZ2QljPyRglACf0EnQNY7bzQODG9BZxotXz+EIx5sjrh9IncdKTWc7nPEkJXEEXIJMa1zyCCeYFDlGG4SqqIDe96i1weTFn8+BQ+jZH4507UD0HtdaSJq6Kjk9O2O+XI2hJBydbRj6Bh9GWq3JBCF5ur5DGw1SPCm7LYKA7Vt2zUCe1UwmE4RzhENgXhW8uD5haCN//Pp79ocWpRR1XZFkwEWLKTVlPkFcKvI+4+0Xb+kbSxwEbKF/1xH2kTRV+CCoFzNOzi5Q+ZjOe/vVO6rZhLPrM2YnNUoltE5ILRiipRs82+2BR39gmi+osvk4kCSLf+cKlJI3b16zWCz49W9+xQcfvuA37a+5e3zgj19+TrY2zJY18+UMI0YjcBSg8xylYHu0xL6lzBJCKvp2YL/fc5jsaMojqSvoG8e8mqHceIH86hcf8Ktf/5q8zrhZ35KiZDFfIJLjuFvT2wMq0yyLEmc96XgkKjMKc9FMs5KFmXJiFqzf7FnfHChzKLKa6mLC2cUzynpOyEcWRIwJ/0QeLiY5ZVHQNx193yAkmMLQ2pbb9S3TbECWP3rasEAgGPqBTI9b2OAjth/QUjCdzBh8j0qayWSKyXParuPQdkQhUWqUfEavGKQiVh7bO9b3I2xxWc2oioLj7oAxhtA7urajnNVMqxIjNZnSIDV37+7Zb/YcmwPVokLmmqwee8k2eawPtEOLtw43WLTSZKZk3zzy3R++5fH9HdVZxfnzS47tkd37PeIokELiAecdyihkpYkS0COnQGcapTQhjC1PJ6ALDpFp8qpivloyBMf2sMcTGdzAsWmw/TCCP11kMV1wef6M07Nzeufo7YDKcvIsEvwwpv2kR2eCSOLYNchBkVIYZaUEyionhZqH+zVvv38gyyoMBcO2ozKa3/z8l/zqL35DOT3h//7LvwQRkYUClZDZ6FGoJgUXk2cUtmJ4dDy+e8R2nuamJW0FM7Mk1zVtO1CdlFxdXbNazDisNwy7gc37LUKMdB6lIIV+xM0TGDxIWXBs9rx/f8fzZyX1pGZRrugOjm+//ZbJtGR1tsQzUpOqacHqdMl6v+bk5JSiLimmiqwYv2tCaOrJFFOMUpVDu6cUlkoVCCWwfuBxfYeR31PpJZmf0x73JOc4X6ww85IPXn3M6eKM7bCm0DnLkysm05wUBnCBbn9kcAOmlGSlZGpKcp9zbBuwFmEsp89WqHlOu+twN45qNqGYT7j4+JrVy1PSBJwe6O0ILY0x0MeBPM+YLCfYQ8/2uCWJiMkV2/2Gz//0OdfpOecvz39w9f04ioAYL19EGu8EqqJEITlsDzg3jLBIk1HkJVJrdvs9690W6wNVPUNXaswcEBiGHi0k/bHHDQN1XjCfzkacs/MUJkcKgU2e4CJZEgx9T79viDGwudlgMMC4UGSu/yw6FRKss2w3W5SQKKkQIYENfP/FN/z+X/2eXGiKWYnWmjBE7h8fUJ3CDIo0BMq6oJ5PSZUgaYgyIY1CZQYl9YiwtgE3dGyGNfgIITBbLWibhhA9ItcMw0DTdARrWc0WPHtqK1ZZweA8jw8bTJFTlTUuOpTSJKmIclSzpRCe1O0CrUYeAoNDCDg/P8dbwcO737O5e6DQU0Sf6GLLb90f+OWvNJfXz7m8fsP9+m6ct7AdIfnxOFYWrPIF9j4wq6a0WUe0iWEfMLFkNZthTMXx0GLshIuLcxpjmKmSUtT8m9/9jnZvmeYLjHLstweisCymJbqYkl2f004PDO2As4GPP/oJucz5/e++oGss/9Fv/mNC8qPUpd9R1jW7wwYfHc9fvRhfBKInyZE0nZmSuppS1AXOa+arCeXEorJAFBFlBGWuMXlg8FuSixQTwbuHG/bJc56/IDpPsoFCZ0yLikldjmPaIlHmIwLuYAd611HXFdO6wnoHytG3FrRD1wljJHoqiYXHTDKef/whJy/OoZJ47YhqZFMiE8G6cfelFZPFlMc3DzjrkRKC82MnY7tnfXPP2dnJDy6/H0cRIJHCCGoMzuOFI0pFd2w5NDtcsCxPlxRliQ2OwQ4jgfWJCqSlpq5rUvL0qcP2lr5pyaTmfHXG+fKUXOVYlRFExEhwQ6BvB3Se0e1a3nz7PdF7dpsDWmlMlqGKDJ1nY66g71GlASTRJ6Qazcnt9si3n3/NH/7qc/rtwOp0gYoarTNOLpbs745s3u7ooiMzCl3nlPMKawJDsIihw+QC6RwyBZIdOx+9a2nkERUlZZ6xWixJKeJcT9+NLVPvBlarFT/9+FNOFyfs1jvW6w29cxwOB2ZGo5XBpAzvNTFIEuPZPcRITJIYEpAoc01UEjsMrOYrXj3/kLvvj3zdvsM3Aj1IpNDcvl1j+3/Lz379K1bLc5quRUSJ7RxDcNTTGoXi4eaBzTcHNrcbkoMiqyB5XJTkZYW1gW67Z9LOKbOCanXGoDtyMeHu2YFyNeOjDz6j2d+j+0ChApUQPARDNltxvXrGw/0jWhguzi8QQTGbzclMQVEazi5XyDwy+IbUOR7Wd+wOW6rpDJNnyBTxyf35MtCFgcF2FLXm2fUpLm3o/QZkpKhzFoua5SzHGItzW4a4IdGx2eyw30fKRcX0bEJ5koMP5EKBFChtuHn7hvXjliwTlFWGyiRSJWSCss7JK0N/cKybOyqxQM3AmQGfB559eMlktWQz7EhpFJUaocnLGi97+q4jibHt630k+oQ2CoNBR0m/H2hudrTnP/aLwQRSSaKPdF1PuSpJIdJ1LZN6wnKxxGSGECJIwerkhHKY0PYDoMjyjDzPcT4hEGweH1m/v8M2PfNyyrSoqfOS/tgwNMfxYseUGGPG+wVTcP/ujuawo+t6nHD4LDGbVhSTGmEU1nlypTBFPuK4+oH1ds3rr77nL//Pf8ntl3fMdEmd1VRPlf/87Bn+I2h2v+dhc0fKSlIm0XVBlAM+OvphAJdBN0BMyKDwzZgZmJxPydCUmWEynYwhqMc79rsjWikuXrzg2cUFeW5Yb9ZsHzZ4HwhEQgpPcoqcRKCXihgZ9Ow4AAAgAElEQVTH+PS49R/n1ZNMJAKgkErhQ2S3PbKoz3n58iPubzs26x1FrJEpsN8d+OrhWxZnl5TzCSeLc4ww2G40OFnpWfcbbv/4QFqDPQRqM2Vez2i6PX1MGAR2GOiDpT+2tLsj56crJosKEVt+/vNfs7p6xrPza+6DQHeBaa6YKEnwlk5nnJ+cMCnnbB+3hBDIVcbV9RUCyaE/EGXk9GKFziTr7QOPuwd8TOPuJ4LJsvFt+SQTbbqGzeaRuhZkRcfgDwR6pBFkypBXElMFiA2Hrufm9kukSdSTEqMVx/2Bb/70JeWmIGjH+dmMTOdIBd9985ovvvgdH3/0nPnyCkHC+3EkW0uDSwMyS7R9g3UBykB1XlJPC3SlkEZQUKARyBBxIVAoTdIKRER5RXuwjIFug4qaQkeGbqBrBwYxcPvV7Q8uvx9FEYgpEdyYPV8tV9RVTd+2PDu/4PTiFBS8vnlDMlBMK6oiJ4SIs3bsmeZj79d4RbdvOOz23L2/g86RLwRNvacTRzabcYCmmk5RatSVyydSbLc9EgZP0tC0LfViyvLijOlqicgEvfV4b5mQYQpF3zi++eNXfPHbP3Dz5p4wjKkw23v8EPFDoMhLrl895/b2gZubW/bDkaNvmTAdnfdeIuLToJMQKGMoiwIyMd6BZGk02A4D3371LUqN05HPzi+ZzKdIpbB9z+OxpTt2SMY5gmPTjOyCcoxZWy+RUgOKJPTTRGBEiLFtKAWE5ACBUQVd4yiF52RxxnQy5/GJLSCFQAbJpJxS5BV97zBZCVLQNi1eJHabI/uHW5r3HafZOVVZUehsbImRyGfTp2AY5DqnzmtSSAy9ZVJOyYrI5OmMboeAFIbj0eE7R3lyyqye4P3oEJxVU4anY99kPuXs4px3b94TRaK3HfWkoJqVvL55TdsfOFldjju/wSK8JS8lyLElWJQ1zfHAN9++Zb5KTGYJFGMeJUUGZzm2O1rXsdv3HNoHzuZzTD1DZBpEYrfdEbWlmCmSc7g2sl5veHj/QHcY6FqLbR15oYlJkDzEKGht+0RxznHBISrJ6fMTqnyOMGPqUiDY7lra7R7ve+qzFZN6BinRHXqOmyMqaPJihiThIgyyppcW21nu3j/84Pr7URQB0ogd93agWp2xedzgrOXXv/4Liirnu3ff0vc9uSnoupam7/BPUFJSGhl9Zc2h8WM+QOvx1tdbko90+4ZhGHAxUs9mKKVp+hYf/GgccoG2OVJMKmSpmOQzLj96zsWLK9Qkp+s7ut4hhaIuNJqCwnichc3DjjwzyFoTezgcW8RGc9r0hJjGPv+zc85eXGCbHgpB4xpModGZJs8zjMnITTaOSpsKYRTCSpxv6a3DdwP79YHVasF8tSCvMjo7sD1sybQepwulQAiBUoqCEj8IDu2RsqkIcTz7K5mBiKPRiUQMDiEBIXEuEHxCJEnwicNhoDI50+mMMi9wh4GyUsxmE8ysZHV2yt1xTdcM5Cqn7R1lnZEXOfdvN9STCclFAp59t6NfD8zOzjhdXmH3HS4kpvMZl6fPqMuSoRuoigpdSI67A+qQofPR4XgYWpxSvNttKZZTcqkIg8PokVAcw6ix8xHW+y1t27FvNnz04QtMrsczfV2R5TnWWpyNSD2QlRVCJA7HPWdnNecXp2x3bzg2RyaLCVJnROtxYQxKJb8FKxGi4PnLKy7SGTQCMsNstaKeleQzyZCO3L655c3tW+7vH4kWVstzjvuB9+8eefnymmk5oXE93TCgyLFDR1YqTKEJAVSpODZH9vsd54vLsQO07jm82bLbrXF3HSerEzabDdvNjmENyUcyU4xOTx/QRU5t5thkmSxmP7j8fhRFIMYRETZiv/0IEDEZ+92e1282HPoDs9kUM8lZH3Yc2iMmz2j7MT/w/PoabUaXYFlWzKcLjpM1h9YRree42xNTYnl+Tj2bsm8b2q5HCIghEpxn6Ma2nlxlXF9ecPnhC4pZRRcdLo7DInVWU5dLyqwkI+f5s5d8f/INO69JMhBSoGk6/GOibwa6bsDkgslyxsc//Qld23J/845v39xz+eKKStZj7oFRRmm0QUqJs36M0GYTtvePkOD66gVnZydkeYaNlq53VEXNdDZBISmz8mnqL1HlBt+psZ8cHCIlUhQjskoYlAxEwlgQiAghiFGQAvSN47jpiUOLSRua45Esk7TdnnZwVNMcKQ2TVY0+Lfn+7fdEEUkaqsWEy8tLjCkwvWH7ZoM/ePqmx+OZmgvKeoJyIy1Hk7Fb77FmwNSKzncILUH27A43oBqGoaGLB/Rkwh/u/kT5WHN5foWY1SBASzlagONoWT45O+V3/9e/YH/Y8sFHL3ExUlQVzy6f0R493fFIWdTkRmP7BlOMF8UxBK6fX7FY/VP2xzcEDgxhICZL9JHgBAMe6SWzScXPPrvi5nd3bDd7JrMlfr3jzfvv6cMBVQSkSbx/uEFlJc+ur2n7hjevvyJTmvrjOVfnzzkeB3bbPbteQlRINN4/Ye9Eomn2vHvzhlpM8UeP3XRkncLednz/ZsdutsG7iIsJgkGQ6IcOFy1OBEQmKMsp56czLp5f8S/+13/+966/H0URgMTxcOBsOeKvlydzog18/dXXHNo9Z5dn1NWExdmS2cmSr777hvV6TYiJ5fmCIi9JUSKlwfmI94HTkzOuFxekznHz9h3HricvK6Qx+BipJ1OkgNzk41a5HVAxMT894bOff0acKB6aLQMeYwrqoiYTJSpoZMpwwbGYnfAXf/FPuP32DaG1dOuOu/f3MKIFcc7iBdzvHnk4POK6nrvNGjdYrqWiyKsnktKT8VsqBu/Zbrc0bc9yteRk+YxJlY9wTdsjlaTINJMUick/peYGhBzHjF3wYBQYQT6tyIuMvmlx3uGiAxVIOiJ0RGd/WwQdRV0zq2ved4+sNzu6vQWr8CERkqMf9rjYkUzNaV4jS0HTdpBLBtfT42ncgCwMP/nsZ9iN5XRyit333Lx/T2sHhNEMLvLw8Mhxe6BNA18+fsPqgzmffPYKpWGxXPD85Rlv797S2B5EIOSWrdvzV9/9gVOx4mJ2Tig9bXOgrEuQ4KKnrEquX76irCukETy7vkDqNJKlplO26xtCMAipiMkiUiDhsd5yaPa07ZKqqohpyqHtEAQSBh8DKo0DUTKARKNVSUTx/vae3ZffkmU5UVqGsGeyyMgqiZCCPJ9S5zUiQW4KnA3c3j6gUs60XLGcnJFUj5CCt+/f0Qwd2pSYvGY6qzFCEFtL3DvyXlBkS5xp2DYb1EHgXBzv0vqWsihxLlLUGScnJ+z7A03qmV2dUj9b/ODq+1EUgQSoQlPOa56/eI4bLN98+RVtbMhnOa1vEJ3irHyGNgXVuuLxuKEsSs5eXqBmmsY90vc7XPeIsC2lUpzMT5hP5kwWS/7wxRc87reoKmM6n7JYzEEpWu84WktxcsLVR1fUH2nCJKPzDqQhTwYlDFpJpAg40XJse7wd0BKa7ZGHdw8YJzE+Y1msEEtDVkzJqBl2ltu/ecv7928wJqF9y2xRUFWRpDp0UVFNCzJlsF1Pf+zod0eKXHK+ylguZkip6foBpCIzJfcPdyQi89WSfbOjswNSSwYxRqOrVHIic+YiJw2j8HJR5wy+IyaLjz3Otkg5ItQSETlovI3INqNI43m/2Y8XVdpFssrQ2wGmNbPLc3o/0B525DKiiJSTkkml6Pt7jOpgKiirHNUYyqzEbxMToXHrLfevbwhDYBJrZOmQg+Vx/Y7tAGL6Eacnl9S7mm7fgkjUJue+eY/K7tBlxj5tmZZzVtNz2oPDqJrSVBgn6X3PZx98ymQ+5fLk1ciRTDnOjcWOGIluT2OPFGVGXtQYgBTxqacNgcZ1eB/AejJnMe44ymPyDJTh6BqC0EgTyDJF027xoWCxnGF3kc3bNScXS1RlsC4wna6oJytub7bEoWf73nL35o/Y5FFGgx3ou4bNdk0ELi4qzq+esfjkGVVxgvCGvT5gi5Zud6CbJ0LSNDagTE5pJL2KNMIRkidfTJi8OKGQc3b9ATlRBBN/cP39OIpASgzejeOi04LXd294vx2Fkodmy/5ux0vziigZt/x1yWQ+xeTmyY7j8P5A160JroFo6bvIPhoWi1M+/unPEGXOu5u35GWOThHbtWSTCcuLU6oyJ05mnHx0SZreszt2xACZKUbsdhy/QMl4DOrJYeg57rf86fMv+O4P31CGnGW+YrU4YbY4oa4X+F5wuD3gNhbdREweKCpJXSmQA4EOoRNKCwY3iiyFC6xmUxYnBdMJDO4AQnPsLJNqjpCK929uaI5HPvzkA0ylybKcoz3S2Z6ua4itJS/nKOlxWULlJVpLpMhIOCSRGCwpedzQc9wfaDvLcX+gOwxkMcOgCcM4RpypgrKecBSObFaTTyrapiPaHmJgkmdkxlDkAhUtg9sijKGLHUMK+CoirMJud2zf7enaPUbmJB+ZZTVhsKy3LZOi4PFwh1SGOq85duNcRJIBb4+cnuYspxVWO2RmmExP6fYbhNdMTUVioO2OXJ2uqOcrml1Pa3tSkGTS0DUNx/2esFwQtCfLTllMViht8NKjDLg4YIMlhEiwFul7VOgIKRL1iLjvYoNShu3+kRgtv/qLz1idnLDfbGFoiXlGIQvevrvl+XyB1BkaA9awebcmcyVyIrk9PrDePdLfNfh+YHWy5PT0lHm2YlmcMK2W5NWMzkVkclg1cPABt1IcO0ewnufnL0kW4uFIMamRSnCMPfvQ8uLVCyZhQe9Gge4PPT+aIlCWJZN6wjfffMtvf/vX2GEgyxTv3r8jicTLJ921UQqjNLkae+DReVzb03UdzdHSdpbN7kA8RiQ5u+OOqCXz1QJhBF3X0PY9KWqqwnB6egKzmmOEaHu6Y4t8GhRy3qKUGpN1IRKGNA5rSIHrB16/fsP68YEQPD4qrO9JBCTguo43+2+5f3tDSA5pJK1vmaock5UkqQCJt47msCcEhZGGyXzGvJ4hdeT2/p7eembzE5Q0hBjouobbuxt+97vfcr++4Zf/4S/xMnB7dzeOK6fRmUBMSKMpsmoEVQaHlOOXOM8N3iUOh4btfs1mvcYNHttZnPNIJVFagRhbt0IphIHZbMZyPqPIM6wf6F2P6zry0wVZVaANFGUJKnFsOw67BttEglUoYdj7PXu5RcxBIPF5pO0P+HXH1cUZJ/NzXOfYxAeuz16S15Kb+w2Pxxseuz2pLimLFfN6idYGGwY8La9v3qDyZ1R1RjlVRJORhKXrHNZZyjzn4vSMN5MpN2/f0TQNs9M5L69nXF5cofOMx/0DbXskyHYcyY0RFyI+SaLIiGK8IBTJo2UiyUTfD8QIP/vFL7g8v+RPn39OaQz7/Zq3t2/RUrOartCM39na5Hx1+4A97Hnxk+ecT1dUWc77/oZd9MhSk88LdKVxYmB9eKD0nqJaUJcFtusQswUTndNvGnx0XL58xna9w+0958sZeVHw/uEdzlu0Majc4Lv4NOb+9z8/iiKgtOInP/2U3XHHF198zu6w4+T0hHpSsm12IwmIxHazprQV3g5jQWBUkO23WzbbR/COtum5ubtD9oLV/ISoYdNsGWJgspqT2QIBnKyW5HWBS5623SPKgiAUNgZyPb4xXfRjEVAK68eEovSJIUa6bcP7t29pj0eMURQiRyfJ0LUcNjtc5tnerdmtN1R5Tje0DKFjbmqqyYQ8L4gp0HQNBVDkMyZlPW6dQ6A7NjzudhyOHVKXTKZzYkoMznN3d8cf/vr3dEPD8nSKKA2b/QaUJNcZIXiavmfiHBkRvCczkjzPsa6nazsOhy0PD7c0hz3eWrwN2MGhhCIrM1rTEsJoaAp4cq15fvmCF5+8pDyp2DZbkInWtvRDznRW4FPicBxlmoem4XgcSE6hU4EMCjWJLD+aYo+Ay8mzmof9A7PlCa9efEJZaZp+j7c9XbtneTrhzZ2lbXt6B/PFgml9ymR6islrkogc+x2//eJf4dIrzp8tOVmumC8WxJgxWCiLfBz+kpKXL15yd3vHm9dvmcwWzKYnTOsFIY1gjtYeEdkIffUhEqNACIMyGZEx1oxMYNLTHMIFZ8UlZ2fnWDcmSFcnZ3z33dc83D3y0WefcrE45XS6IlioRclEVxwed7wXb7n8+JKL1RnFp3MeHu+JYaAZeh73a9CGarJE5RWFSmOM2XmKPMdXJc3xSH/sqc6niFrxKv9gjNnLxPRkRsokm8OOajqyMCP/CLLQD3gH/jvgvwD+ll7436aU/venv/tvgP8cCMB/lVL6P/6/fkdZlFRFzr/+q3/N7rDl489+ws//g1+MglIt2GzWHJuG9+/fM51Nx9hwb+lDwpUFh7Zhu9tTFBmDj/R+HOE8+J5ZGNBFSVHUTE9XLBdzVIKubXn/cMO63TF/fs6z81dj7z6NA0lJpBFfpkZ6UBgC1g/kSo8ewf2Oh4ex9zqdTqlSiewFx+MRexfI4pH1w5osM8hc4nqHyjUyz4hKEYUYg08pIKSgyDXCJFrb0B0GetvR9D1D8KMYJT3tToKj6xpc7+nbnsPxSC4r6qpCZobdes1wHHDaUdYT4nbL4BJ1nVMUGcdmR98fabsDXXsgBjcOEIUw3g1Ig5KKEAJd1zE4h9GSyWzCs+tLXn74nI6Oh8MtygiiDKBhs9uwXj8itSCJETWuVUGe1YigGazFmo7prGB2OqFQcyozY3KYcn51xsuXV+y7B4J0hGDZbu65vLrmxatrnAxMxQn1asJ8dkVdn6J0QRCJZDyPhxvu94Zk9vR+y/XlKzK9QqKRUiMRaKEpsoJZPWO56FnUJ8zLJTJpjs0e23UE70jJ4nyLH+y4bJRBkiOAKCNCS6QGZGCynHJ2fsXp+QVffP4Ff/zyS2SMrB93lGVNHDzCQvd44M13N9x/f8tEVWAi0oIaFMPR0YvAZLbC+3bcwfiObbNF5hVZsDhvMSqnLEu81litefbimq5rCVWknk742dVPabqO/WGPz8ZdzKFtUKVhNp9jsuzfvwjw93sHAP7HlNJ//3d/IIT4OfCfAr8AroB/LoT4NKUU/qFfkGWG27sbmuOei6tLfvbLn/P81QuaruX5hx+QFxnbzZbj8UjXtMQU2B/2SCOp8nGIhQhNM5CS5OTiGbbpaMLAwfWcX5wwW62oZjOmqxOaw5797p77zSPv1nekRcaVfo6L3Z+lJCF4kogICZGID47g/Thm4z2Hw579bkdVVlwsnyF7cLuBaBJN17N9t6OqSj799GOiDLR+jy41uiqwMSKdo8gUSgqUgsEdaZojdohIDEJI0IY6K5DaENIoowjBojJJuVC8ePmM6+fXHIcWGy1VVfN4t8a5QHI9N3cP9M0tQ+84f3ZKWea07R5kQGsIcQSMiDQeE4w2Y7ciJJx/QmIDyNEFqIwiK3MG2xPSQJIOZaCo8pH/MFh8GwlAXpTUZUFV5GidE7xg78bwy6JUmLLGSTtqyWYTto87uqFDKU1mFFFYnBu4eHbGtj3QDJbpZMmsvqDIZogUEUJSz6esLhboCnq3p7vb0jQ9V6cfsVo8R6IRCKq8ZFJNmE5nSJVxefmS+XT5NGPwhGf3jnbY41MPKY6wGgRRyHHASYzyXKEEyMDN4wP5coUTgkPbc/vwgAoRqQoyFbFd4P7dI3dv1rz97h3N5oiJAiUUhSrBaXb3DV/v75mfTVkuJ5RViVDg0pgWDHE0bg+pJ0VJSmPOZrKYY6qMmALJCGxwTE5qimVNvt8RI1R1jRQS5wM+/iOgIn+fd+AfeP4T4H95Ao5+I4T4EvinwL/8h/5T8IHoAxeXFzz/4CVnV894c3fD69ffspjNuXz5HKUkfdNye/uOoe9BSupZTdd1I6u+KDk0LUIIFqcr/NQxnU74yS9/wqtPPkFmJSE9TYC5gdOr55hZjf0TOD/g40CeK5yQWNuPAM0nn0H823ZfGNtK0Y569CzPeH51zcdXH7K72XIf79FCY2LOze6WzGieXV1QznLOX55Rzms2xw1361t0HB0Kfd8ixPiFtkMCDNNqiTaaTJejlUkLQvD0QyIEy3RWc/38muvnzzk/O6d/95qb92uImkLmkEG0geOu5bBvx9HhGHHDyDwsq4yqzEagiB1TiEQxniGVou8Hhr5HKUWeFWhtOA49m/0O63qECuhMMQwNplDoTLNcLCmqMRTUD5bB+nEBhYTOFXmRoXXOEB0HP15ASq+p9Ywv/mh5880blvMpP/npB2SVQOUJoQUTveT59TXffv+eLBoMBcEqMJKQQCnF6mSJ0B4nI8lF7u5uGA6K+LxiNhnbtcoYqrri4tkF1no++OBDFqsZwY9Qz5TG0eGjO5DlkkwJgh+PCSEFvIhE4p8XjHeWTXOkP3xPlxybw4756ozUtVjZ8vhwT57XqCDYPh5IPeSiYOh6ApE+HNnbgfp0RqlLQpdwhacsa4xWKK1xwWPtgM16gkuIOF7uiZG6hzSSzBh61xOVH+dMkkAVApkkKhsLIGGcofih5x9zJ/BfCiH+M0aS8H+dUtoA14wykr993jz97P/1/F3vQD2tcENPYXJm8ynVpOLt7Vsed1uEluTKUE5q9pv1KAixjnpSkecZfT/gfKD1gX6wzOua5WzUTp2dn3P10XMoFNvmQJZXRGHI5wtE8sg647o70MQ9LlhU1Bil6LsG2/dkJiM4SfAe73qC92gVkUpRliXPLi/55IOPeXH6gtdecvP+juNxT2tb2qbl9NkJWZVRzkvKswnVYkp8kGy745M41dM2keAsUmuUyNDKELxDKIHONFKB9cP4hUegGLMTz66u0EaPceak6A8975t3lEVF7ALtoUOhKHVBXddoqXF+IESP94J+iHhnR4LRYJFI6lITReRwOLA/HoiMuzSjc6xPHPuGdmhJWY/UYwutqjNEltCZZnVywmSyIIZEc+w4Hps/i2aTiMSkEaIAJYkioJVkcEd2+z2b9SMP7295vL/Diw5TC37+m59x/eoFH3/yGat5S9+NhGJdpNFG7ce3eFlP6YZHikwDieXqDHtMfPnHPzGfnaCNYTKbMZnN+PiTj9BZRlXNkAJ8CCBH4KyzA1KO3RrkiLcLeDxhPCYKnkArijBELp+/Ig0VfYxcv/qQk8Upb/70JTIlgo/j9GfUuCGigkIKBbkkn+RQaAZhmc5OmNaGzWFNt++pqorJpEIZjXeJ/f6ATBlVPkMLEGIMgSUiUo+TkL6NhJQ42D3RJ4TUxJhGNbwuybIc9Q8s9X/fIvA/Af+MscX/z4D/gVFC8v/7+bvegdlqmt6++R5V5eRFQT90VJOKVx9+wMP9PaYU5IWm60ajkARcGN/G1llkChy7Hp9gtpiwWM0piozpakLjG0QXyeopvfMMQ8+8nuFtQuYFp1dXFH2BkAopJIZE6HqcHci0hhRwtse5fsSbI1BCIEiUVUE1nYxyyNLgdeLd+pa2bRBakJWGqBN9cigJNjlUnmOqkr47Ukg5voXCuB01mURLibMdLgRyVdJ1EQUURUFIUGU5i+Wc1XIxilRtGGGfTvH2zVs++eRTRCd49+VbUoLz5xdUkwpvLVIJJmVFwtMdG3wYEPBn/VtZlsj0VPR8wGhNURSU1RwbIlIbXPA0hx3NcMDHgdVyhckVLjm0zMhyjUijyk0LCMHiSFjnkSlDCJBaIbD0tkFFTTk1PLs84fb1PZvHNV4P1Cobt90icv/wnpPlkm3aIwnosW9LtIngBKen12y2Aq0Fu+OGNgbwGY+Paz7//Etc9PzyV7/gV//k19T1dAybBUc/tCgl0WaErBgjyesJLnZYZ1FKImJC/Rk7JslNRi5zbLKUVcXli58Q7MBEV9Snl0gXOaw3+PQV85MTvA/0zTC+4WXJdncgL2te/OQFg7A8Hh4plKZDsVnvKauM2WxGShGhFCGOgSGhBbkZB8sGO5BEwpiCvMhBCbbHHghILZFAcqPaTOuRt0H44fbAv1cRSCn9OZIkhPifgf/t6Y9vgRd/558+f/rZP/h473l8fGCVnZMX4yVMSpGiyimrYmTg+8B8Ocfb0VtfVBXeR+zhQD2fslzNiQKEFrjkKHVOUonWjZyAeV0T5bjFa4fxA45IirpElUtcGnC2R+IQ4/6fdr9jUBIfAykGRJJEAq4b2DcHqukEqTU2RVSdYaY5IUtU2ZRn1+ecXJ9jo8O7SFYkgoOkYTqf4YaOlBISNaqtQ8Rbh8w8Av301mHcrgrJcb+jKEqsENRlRVXWBBfRwpC6xO23tzy8e+C0PAM/3kTrzBBsoGkaisxgck2KiUQiPv0+iCgpR8+dHh0MSTCCT4REa4PSapwDKIsno84IcalMRlYZZCZARnywhAGMMHTtka++/gpjck5OTslMQWmmGOGJqcF6S/QDQkJeVZw/P2cYHNvtI9evXnL+asnyfIbIA4dmQ1VNKXNNGBq6sEEYST2bsJqf8vr9nt/+1ZdoJTlfnPHpZx/x7s09X3/zDff3t1R1wfZ4zvuH75i5FUIa9sctEsmsXoAApZ6gpsETxNPlcPx/mHuzHVu39EzrGd3fzja6FavLvfZOZ9kUKrBAQuIACdUdcALiCkDiFjitQ7gMEBwhLgFODFQZKLlLOzN3s7pY0c3ub0dbB2NmkpS8ZWzjUv5SKCLWmjGjmf/ovu993yfgwowLE0VlKIqKMAVUrahVzdO+o9gq1ttrnu+eeH7+wn5/ZBwn2vWGi5tbFsWC0qz4/P0XQhQ07fJMw1ZU1QJxeCaOE5UQGCS2d1lCLLOyNSTPodsToueoSmSSmKKgbuqztLhHSEkO5kxIKfNiFXPsm/eWGBKlaX50/P1duQMvU0qfz5/+J8CfnD/+n4H/Tgjx35ILgz8D/ve/6flSilg7czwe2O8eKZcVIQSS99RlwdT1jNNAu1wwDQPBe5rlAl0abPQ0i5bVxZp+7LF+wkXNHEa005TlEkRg9jNS1ASgnyaa+tetozDMX+0AACAASURBVCrblk89z7tn5mHH7BzWTUQSRaHRpUaIDDURRGIKOGcpqppAIipoL1Z89Y++wbTZBr3eLFhdLfAikmKAqBAYyqZiKyXD8Ui0E84GkHk1RnuC9GhpIAaO+2fsbNlutihAxICdJlRSaGGwo8P3AekUZSxY6QVyFEihuGy3aK2ZdGY4OpuLTKYQKA3xvL0VkMM0A9mFmCDEbDIy2qC1wgVP1AWmKlFa5tasAFUohMxx4zE5UlQURQUucjruOeyfkdKwWi0pijIb9kIuYrnk8wIgIkoG6rrk8vWWeqt59e6a659soAxMccDomoenz2wXVyRvGfpHdFkizhV6EQs+/bBj6Dte/9Pf491P/zHj+GeM80iSgRevt6AtP3z8BevhkqZdk8jJ1vM0sNle0CwqzKA4jIdMAjIKUoAUECJlB6XIkmGTDLunA5/+8o71dMH693/G9HzkT/+vf8nusGe1XUFZcLQTb9/+FC0rHu+P+CmChGm0vP/uPaZR1G3B08MPTH5CJ/Eb+29bFvgQ0JXBJcvz8YlCFwihKOYS9CW6NAynEe89UY4gMs0ohYwvlDKDWRSSGN3ffRL4Ee7AfyyE+EPyceA74L/Igzn9qRDifwT+jIwn+6/+ps4AnA1EbqJ/Gnl6uOf1uzdcXmwZhoLkPWM8EZxDIVitljRNA0rgYs6vFwoeHu/5cn/HZrvm+sWGJAKn7oisqjPOfKCpS0Dgo2e2gmQEiDygnQvM08zTlwe0UfjkzytEhY4QhQCRECqn6UopCdFj/YyLnqKpeP3NV1y9uqU7HLBupFoaZC0IOr/4WUteYISmrlvmmCD5859RIFGIRKYteUs3n5iGmbYsudxcYqQhhohIilWz5u7pnj/54z9DOkFNhVUNw67Du5CzErZrlm1DLCJ91xPxLJY1TVtC4rzjSoQQKExJWRREH7GzJYaILCVSqdxyVZqiKpFK4WaXGZFkcpFUkmBj/g00dIee7nSk1NnLIckpTAmJi44UM3A2CXAhkH4Ngb2s2bxsqVaaoB0Oh8YQo6A7TWw2lxR1ZP/8hB8Vtd8glKAqW64uXvIYH7i5eos2S7ZXN7z+6iecTiVf/d5rhA6cumcmb1m7iZubK6TQJOeZxo5x7AkuIBCkGDM1Q2RcuBJFNmE5T1OsMMnw5cMDh/d77udvWQvD6XAijDZzMeqa5EbG6Pju83uePz7hU6CqG6ZxxM4z3ccjVaN49eaG3fM93TTQbDckL7DTTJOW+BggCaQCoQTNqkGhsyU5OJIUOY85RYZ+pG2qfC+lfDf1xxNKaS63l3hn/+6TwN+GO3B+/D8D/tnf9Lz/rx+i0Fy/uaGfJpTJwZWmrtjtoD8dUDK/MCEllMlxX7PL2fpCSfquZ3fcsd89s1zVVFWBdZZ+GFist0QvOZ2eUZcVSpYZdEHAuoBzI86NpBQxuW+GLnPWn3MWYRNSlUghkSbTjOZ5OgdzJGZn6aeBskxIJdGNpqRCzAFda0yjCSahjCQR8XZGRokxGq80MkqUEmeGYm49xRSYvcefV+TnL8+M+4HNckNpcob9ut7wnA788T//F4TeUZ13NIf5gI+eF69fUtUlqiqYxYxzlsmOJDxSJZSG4CPhLIhyzvH0/ESwmU+glMr3U0y4ENAy0rQNQkm8z7DTUhcYo/OxRiokkqfHR+6+u2PqRjiHZkgMha5RZYEKgjhW+fiTHMHl2PRIQhWCoqnw2tFHR60NSUE/jihVse8PXNQbpHGc9gdUWWDtRIqCN6+/4vLyhrZd87g7kKTi3e99w6nL4RzTfEJpcHbguEukaFkt1izKNd46jvsDw9gjirwjSjFPzEIKUoIQEiplw5W1lrmfWciSRdTsP3zm4WnH5WbL69//hoMdUYeKi+2W7//qe+7ef+Ll8pbNxZb9UySFQLIWGxL3Hz+ijKAwmrZqUW3Nol6wbBbEKdBPPejEcrWi3S6pdIPaDyA1znukUrTlknHqECm/ZiRJ3/f85c9/wTSO/Dv/5N/l5vr6x8ff32aw/kNdi+WSf+8//A94eHygbEpO3ZHKW/bPzxyenvF2xtqJ6D1V3WCt5XTq0IWmKhsQgovNhs1mwZufvGa9XHP/+ED0EaMNIQkOfc9QHKmqJWVR5xk/5RvQu4xDVyJ78oXIRxQXHMkFhE5opXPF1ltO3RE7z2hR4IJndjOBlBHpKebV3eT8QKRAq3yUiD5gsWiRE2FCiHgfgQJJFiiJlCeLOXjiOXPx/fcf+fLhM+t6w2a5odA1N9tbpsOEO1pOT0dClavtCGhXS1YXa0xb4FNExIxNlwrcPHI8eNplnSveCUII3N/dY0dLWdSkJHNNAAkpEVNEGU3T1kBmF2htaKqGwlT4kFCAQnHadzzcP2AoSV6yWK4pZEMKGikiRSGpqHPhKqfMEwnY4DhOESctpTC0VUVMhuhyr15pzdPhiUVZc3FzgQNScgzjwKJd8/W7r4kJEoLdfo+Ugcuba0zt8PaAMSbrFayApNg/HZk7j9gaqqqhNAYzaax3KC0z7zLm+owPgeAD2oBznjhNCKBMioUuccPM85cHvrq65Jt33/CLh/cc00i7XrG5vKC7P7LarjGlYXYOqbJ0exwODN3Ei5/d4iWU9YJqtaStF6gIbVEyu5Fpns99IQ3SUFQLgotMNuZofqFpqgUpJWIMKKmwo+PLp098vvtMU5XUxT8AkPT/z0sXhs2La1KlIQkeHh5QUvLp0yfuPn1GS8XpdEJLxeXFFSLB8+45MwCMZrVaUzZL2lXLqzevqNsasz/Q1pJFvcAH6LUlek/0FkvO9Y/REsKIdzPGQFUVlKXODL7fatGF6EgiorzGx8DQ94zjgMQwjRNam/9HYy/T2dYrziKj7EHPqQG50p898DnKi6gwRUtd1ehSo41gmge8EJiyZlk2dE89vzz8kg9/fo8gUquK26s3NKYlTYllscKgcm+/UejaoJclZl0hVQAXMVJTVQWHU2CaBoxRFKUiicBxf+T77z5BDLx+9RpjSpRU+WcSCqyjrqt8DEsThEhpasqyRimD844QEk1Zcn31gv6xp38eqIsV29Ut29UNg3OMc49pwCiN8woRJcSMO8vkpBlEy2J9QaVXBAsQcpcGQEVOY8/lumF9dcHj/RFpB9rbl+iyJoWsHTCFIWKpqppxqhn6HeKcXlWqluAEOM1sHY/zM0af8MIjBRQmv5ZSQUgCnyDFgA8BfwYkeZcBsNPe8tF9QBUF4zgyDgPTPNMPI8/7He1iycvXt7hdz+npwLjvGOeRqCCKhGlKFsuS66vX+BTphhEcHB/2+OdAc9GgESgvKUSFpiaFEq1EzqAQWSfgnUWbmqHP0N26LFmtVrx5+4Z5Gvj44T2kv0dN4N/EFVLEiUCzWhBDIBKJzjNPI3YeQeV+eFE3rBYLmqrieDzw+PTEcX8gvQx8c/VTbq6vEVFwf/dE1w2sN1uqouZ4HFBI/GyJSiNIWDfnAAbbQ3Ks1gtKYwgpMU8THosqFUILYgoQskAkOHBzFtOIoChUlmMKKamaFq0VQnn8b5yb4ten/dyKQyD5NWBEYMqK9eUN280FZaWIOJ52X3Apst3ecr254Gp5zVV9wR/9L3/E48cHdDCk0TOdBtIEi6ZFSkBCMIlZOFgoLn5ygxKwu3+gG06EmHMHTToLR1IefIdDx3gKtEtJ09SEKCAK2qYBnxByoGpKFk3N7GZAUBUVhclx3SIXpimKkjevtqQTfNt/z7pdcnv7jpsXX3H//EQfJwQBiUJGCT4SZ4ezNgNPioqrzWteX32F1BoXAzHOTOMRKT1SefpxoC4d2tSUTUCR6UpKSUxVkqLCekdMAqlLpsnz7bcf2D0+oILhdvuW4AWDO6GEREbJOA1gIusXS7avNuhaoYVESIlP6RzM6okxI9J88MzzyJwSn5+faBYtPkY+393x8fNHhMnGK6UkL7bXFN/AH3/6FwhZ8Obrt3z3/lu6buDm9gUhWOwsOZ4Gvtx/QRmJxyNLuHUvMMuKylSszJZ1fQ2yxruEcx4FNKVhoicoSd+PxAQxJOqm5g/+4A9o64Jf/NWf8+H9tz86/n4nJoEEJKMQUfxm1g3OEn1AS4lA0FYFRM8w9NR1w3a9Yff4zPNuz3qxoKkyK/DLwwP3Dw8EIpvVBbvH3CseRsfr128odIYweDcx25Fp6IhxQutEWWjGeeJp/0xSkfV2gUAQk89wEmGyyu8sWPLJMY1TlrqWJaYwKFNmBaCMCJGjvxQCI/LqIn5LF6C1oa5bFssNZb1EqIgAhDZUbUu72FCYiuu3l2zUkscfHpkfZ+KYCCNoISlViYj5SLUoF+z9kVBkVHh50VAGSRhnuuHE6XjEhZmiyg7B8JvYcc9iq7jcbKmqinn2IDTaGHzwIAVFWdC0NanvKFSBNkBSJJ8BHSnANDmC6+j6Aa1Lbq5f8vLFW5bLKxIlqTswhz3EhIg5oCO5QHSO5BPL1Zrbi7es6pekHPCHdRmw0tsTPh5Q25pIQVHWXF61DKeJcehBKlISpKRwMdL1PafuibvPD3z3q0/snx65bK4Z7j9y3PdYBpQUiJCwdqJaam7jFXohMO0VsiqIMZKCw9qI9wkKiXNZxdc2NWKj4VhAoZlOni/vf2D77be8+cdfs1mtUULQVBXbd++4+8UHQPL67Rs636NPkqtXN4xdz+655/Fhx+k0AZ4kHNXC0Lcn1rpgvdiwLi9YmC3StFgFVlpisEgShQ7YSHanpsDkHCl66qrm5ctbds9f2O1+nAv8OzEJCCHQVYGf3bnyLoheUlQFzaKFkCi05nn3zKfPH7m6uqGpa9arFfM0sl6vqcqSaZx5fnri7u4zs3NZ+qsMP//5X7HdXPH1u6+QMjJPHcPcMU4D3maRhbPZKLNarzl0B6zPcWcpZN+AVhohFMFZpmEi+hypJUR+I0UgZeS5+DUuXWamHwkZ07nIlN/XTU0IiqZaU5RV7gm7GVlE6qZGFyUoyakfMEFRVhVVUSFilgSrQlLogpQii8WCd+++ghr+7MPPcVWivVgSjcAGT7WoqU4V871lGDqaVOWA0UKipGa1XFKWNW3ZopRB6axvz5VBj0gJJcCYAm0MUmmUTMQz4VgLhQ2e3cMzT5+e+PzdHdv2mrpqqeoW0KxXlxz9iv64I7qYZcpSoZUiyAJVVqyXl5l38OXIdnNN1dSoQnK1fsGnLwfmKWPBZh9YaU1hKsbeZpyXUFhrUapitz/w+PhE22hurm+53N4wHUYq03K8n7B9QFUGnGccRvppIKqK4GPG3glx7hLkgqAbXd4N1hldPk8D66s1C7dEDxWlKQilQg4dqlA5W7KoaKoWgaRdLHj15g0f3n/i8/1nhJbUiwX7/pRdgc5jZMHN5Q3T0DFOR4RNDE9HqrJm9XbBqlkhk0ZTYMqS2gSs7fF+QmGYhiMxCuqqJnnNPPdYZ0kxsliuMifzR67fiUkgxUQY5mzaqAxSRJKUVFc1qYqZyDN6WumZ+4nTcOTq4orb1y9YrhsWi5ZxmJBnLNk0drgwg9iy3DS8+fqaxWLJ5oVBaYsOniLA9OlI3+2pdI1slizrFfXbd3hr+eHDrwjjTNWUiKAoY0mdWkbrEU5RyJz0a6uChWwR55pAiALGLMCRxiCNAQ1eJYKIKAkxeCbnqOuGpqoppEYKjY0zMkgMBS6NODEQleShf6aNFc4nosuVZS0Dqo6EMtHc1qxerRBGoB8MVBJVNExJIoqe9cqwEmvqp4ZpnBDBoKkQPtHoktXNmmGYCUGgy5qyjng/I4kYbZFuJvYRmTRRGJyAsqhIyVNEjQoKu+t4eP+Z+/sds4uMKbGbLfLxyNtXL6mLhovla4ap4zTtUKqiriU+KOw0UhYLlstXhFTw9PTAOA9cXW+oKs16ueF0ekV/lOzuDuj4HYVSLJoLirIhBAhBopWBIGnEkherkuWqxPsNn6++5/TpiVYWOUIcaELBHEa8H2gbw+2ba168vUVqhZtnCi0Jw4gcZwrrsd4T1MzsHZO06KWhreGr6xdUxYLD/3HC7uHm7SuIBYWqqYpbZHGBqBuWL17x+f/+l3x4/z1f/d47rm6v+cUPv2Kan9ikgvVFDQHEbClkTYlAWYnsPMJHXJoJ7kBrFBUCEQJpmoGIi4JalhAdRTQIoym0Zr9/4Hnf0SzXTP7v0SL8N3FlqIYFAevlAkRkmHpQUC3rvENA0viGpmqoTUUiB1gYozmdjjw8PtAs885ACFhvlty8uODi5or1xZqyLmlWFTEGCoAokSrDPApZME8jQz9webmiLpo8qShBXdeIqPCTx0lH9EASCPKATsETg0eIbMcFiUq5ICDOLaZsTY6ZrguEM0W5NJLCFHnVPTfOU4yIlKvTITqkMMzOo7xgmnPrThWGGD3ISLmoaTcLNtcbDqcjKWU7cIzkoptKuHhW5hUli3bNZr2hqgvGsSMGjylKVsuKyXqS1Eit8E4S54mYEkooBDJbl/ueEAVJKJqqQfnEeMiFr+PzgeA8ZVljg+U0dCh55A0JiaAsaxbtimkccX5AyexLENJTlDV11bJarRECTv2Oh6eR1bLFhoblYsOT6jkcHtDKUZgVXBrqepO7OVGcxV81elHjy4gpE8EkXr98w+HuAX+0iDijhECliJ8nSIGbF1f85OufsLnYknQActSat4EUEzIJgrUMfSKorEpNBpJ2xGbGSY1TI7JUNKsGrVY4n6PFYlJEqVFViTCK0U14b2mXDVc3V9w/PFCKAi0N42HA2ZlSahZlRZI5V+K4e6bpbtBCYlRFURqij0zDiE2eKBPLJhcR5zCTokBJzThaDqeO65sL1tvfcQJRStm7H3wOdNA69821yG6q3aFn6sacS9e01GXN8XjM1ldj8CEyjCNBCEY7Z63BcpENNs5TlCXNYpkHhhCkmFtfiVxgGdLIPDnGyXJ1fUlZt8xTADmxXIWsB5gtkiF7zs/++6quM847eqJ3uHnElAll8uBLKsLZIZi7ziCSIPcKcutLa322sfos540BZEJLxTRnvX/ygf3zM/vDDqU1utH4mPHZ5mwVdSEwjANKa5QuUEmio4Ao8fOM7SzzaIlBUFUL2kWTY7X8iC4NSkhEkWO7XfAkAKFwVuJcdi8O48A0zESXOO4GqsuG5Dz7Q8/hNOJsQAqFMRrnHdPU4euRmEYCkmnu8N7lgqT3aC0wWlMUEq3BGNisW9plRfgwczjusPOM2h94+/Yt24sVs60Yx5HHx0eELLnRFW29JCWZi60klFa5xScCpiy4ub3l08UF399/Sz+P+edLM4PvKJqC29ev2F5cIZUCA0Kp7DMJiQh4KbApgp3QlaHQ5fkYBN3pCGFAF5LVZkFR6rP2v6I7DfT9jkolkInN5YZ3P3vHzesbikpxcbnAzj1pSIzeMboJlwJGKFz0hGCZQs56nPuBpCtGOWBSgUgS62fm4KkXNVEIZFHA5InJ51j5AEoWrFYb1pv1j46/35lJIMXcl9+fDjRVzq8vjaE/nHi+f8T2jte3b1g2C+6/PPD58x0vbm9Yrte0bp0db6VhuVyga0Hd1szOMh/3LNdrEtkpJs7bcS1F1tZHz273RAx5ddOm5vLyhrJsctz1OFGWJSlJvIsEf/bYp4QkoXXWbc9jBkhoraAwJJGdc1kr++tfNL/LE0Fe/XM7MRCSB5U9/onMwHPzjDa5Uv/9d9/y/PiIPO8spFTosiSIxHE88fnxC8E72qaln2em48DqYgtCklxiPI6cnk+IqBEolost7WKJ9xOlEYxTR7C5pjEPE7O1yADeC3yI2HmgP50QSLSusXbmdJgIo+X5qWcaPDHKTAMSAiET03Rimo90wzMxZcOOtZZpmpmmmaLMt58xBqVB6URRqUzpXS3YH555ft5RVSXOWrabDcdDy+PTHh/3aFPTLFbUTZupzmPE+QmjmvzaJjCmYrFcYYoiy4gJCKV/U0F/+fUbvvn6pxSLkkk4AhHvcnF6co7oLVGE7HxMHiEFSkhiBN0IfJoIUbG5XlGbS0SREDKyWjaURvPl8x0ieYRJvPjJC65erdhu13TDEecnknAUiwV+CmAUusqCKmctNszEEtxkCbNHISDlrAslNDF6nJ8ohabrMwpeqQKJRMpE267Yesei3Zzv07/++p2YBIAMz5AiOwUlLJqGsRu4v/vCl4934AQ/++pnbFcXfPuL7/ly98ByuWa13FBWDd3YZcG0WaCDRBrB7HPIyOIs2Q3nPn1InsKUbC82LNcL9s+fEChWqxWmaFhvr9heXHP/6HAuoTW5z59rf/ktRqI/o9Rj4HQ8UAVP2zaAIoiEFCk//LzryMocQYoii4NSxlFBdoVJJbKBJTiESIiQScEiKr771a8Yp5G1WRC8p140XL28wZEjyu4f72mbmqapeLo/8Pjxns32kqpWDCfP06dnDk9H1qtNLsiZAp8EhZI0bUGSMDqL8yPp7I+wk8uTAYl5GulOHYuLNcJkTcL+6cBw7Bl7xzxH5tn/hotXGMk0njieHvl09x3rxQVmITC6JCVBCALv8u9cGAMEZtfj3IDUBYvFgsViyenYoaTheDySoqAbesbZEpmY7MDhtKeqKtbtNnc0lECpTGISQqK1pKwa6sWCum1yNuIxT16r7Zqv3/2Ur159hVWek+8Y4oBLuSaFSMx+ysVcLRBBoaRBJI1M+fldmEkUtJslpSw4js9wnsRMkRjmA/30zM3VJa/e3TLPPcHNTPshG9Zkot1uiHMkWk8IAjFY3BzO94LAzQ4tJMumRRZFDogNAecnTsMOryxaZNl3VZaIsxitbdc475lGf5bM//XX78QkIEQW5igDIWa2oHeOL5/v+PThI0M3MJ9mvv/ld9T/qOFic8lm9YydI0IYrq62xB2chgOeeNZU5/N5UZQoo/LNmb9ZtrMqyWaz5ubmhvu7Z5TQ3L58iTE11s1cXl0zzj1KSoKHhCdqQ4wpJ/EgiD4gEwRr6fo+HzVCIIlIEGQLaoxnkX5mCySRIKTcz02J2c6EGJFGIxP46PDJoqXECJW17aeB58cHyrJg2Sw4hBNFU3Px4hqbHPOd5TR2jHZg2a6oTMnxYceXX33i8mrN6TCyuzuCTZTaoFQOXHUpsFg2lFUDMtHPI92cEWYhOnyYGaaOfuwo+4ppnFimNXM/M4wzT/cnwmzRssDZyDjOtMuGqsoejbHv6E4Hvnx5Twye6/YFhW4odIs3GeoqZNbrz27keMx0naKoUarkYnvB6XgipsTnz3d0p44oTmduQGS2I/v9E1VV0lYt8qz4TGfFp5ASIRUoRdU0LNdrhniiO3YZFzfC/suJh+UzzbZCG0GR8k5LG4k3imnIO0iSQIhs3BLJUOkSks/xagLQiTmOuH5EikQ/NUzdyDA9kEh4WVM1Jb3z7Ls9/TjgrM3dpxQpSkNVVYxqxAefj4dCEGPCWQcpk7VCigxTh7WO43jgeNphk2O9vEa4zKFQSqK1yCyEKDjsu2xK+5Hrd2ISkEpS1SUkjTEaLSWfPnzgww8/MA0jF6sNs8zmnrvFHVdXN7x6+YZD39ENE9ubFzTtkt51CARGGZLIcVjVeQb0Mf+BQkgIIiE4Cl1ycXnB5dUl0Sc26xUkmKaZ7eaS02mH8zMxeEJIzH5m6qdzYTCLf7xzWTwyTpRV1jaElAh5rCNSyvjyc1qyOCcXex8wMhcmowhorYk25xhG4VBJY5Jk6Ho+vf9ICp6Lyws2iy2TdRkkKnKM12KzYp4mutMJrWYqXbE/dHz/579it9pip4lhP7OoWpaLFqkCw3xAlRVV26CKApV8hrP0hmHqc8HUCIR2jNOJvqs4HQ9Yb/n05QEhFUpolDTEEPDeQxJUZU1VVJm+pBTO2nyzp8wVrExFU454m30SCUcSIJjPkuwDpA5jakBhzq3hfjiilGK9XeLiyDjlwqMPgdVqmQulUWGjReoCKTVGZ9NSjAJT1Zi6opgt7aLBjDVxknz7F99z/+mB1dUCsxDohWRx1dBeVDTCMGtD9NmnIs+/s0yKUjdEBqROpKSwyQIRnwI2FpyGTzw9PDO7juV6Q1QzMx4nLJObGc9oeTdZ9DSQZJGL4+QjpTCGJDWe7IE5HY8M4wBGM9qRcZjoxyNdf8SLQF0tSLEgRJfx8DLXLTiLh4z6+2UM/oNfSuZK82wnFm2LnSYe7h/Y7fdsl2tebG6YjhMPnx75+P0HClVhdEFKMI4WKQ3tcknn9gibMJXExZlIyK634DApr04xeIwWOJ9n18VqwYuXL+hPA2VZ4OzM0A+sVqsc5DG4XGWXgqEbOO6OVLoiptySspNlmie8D0Sfe+cxCkJMhAjq1yWB+JsDQfYMOEeqSnzKvgWRPLPL50BlIEaQvmLsRn75l7+gKDSbizXLxZLH3Z7jcGLfHViXW6IQFHXJVVlSCM08eLBw2h3oHzxSZESbrkSOS3cDQUpWqxqps5PPx3jGlXtCcoQ4IYzh8sWS4+nAYX/ky90XJus4DSPL5ZqXty+xbmKeZqSUGQWnJN56nh53VPWCFCNal5iiojALmnaFd4rgNSFafBzyjkrmwIzudGSec4U+hbytV1IiReLm5oJ2VfL4dEcMA9OUOzPOjqQYSCn9ptAaz3oNoSR1u+Dy+oZ2ucQNI2VTIXSAGeIY2HXPPN89IIqIagQXr9Z89W+9Yf1iSShWWacfZiAjz4gRKRIxCcCco8gdRSmJemZ0z+yOlufdEyAxZYP1RwrdErDcP97z/OWRuZuwg2VOBh0V6TCyJOc2DC4nGhWmJglBNwz0Q49uK3y0jK6nn04M0xFZwDh1FKstUQRCSKSMVEErhSxL6rL+0fH3OzEJSCkxykABUuh800qFUQWLdkVpKuZkcbPj/ukRRcHi4oL1coN1nv3xRLM2SK0xFJkBHwQ2WFAigyNSREuFSAkpstTUJkdTNFxsL7Cj4+7LZ26vWwqtCEnlFc45OYEY4AAAIABJREFUjMo7iL4beH7es6xaFm2LQJ0Hfq7CpgDzFKhFia7MmXGXGWNKyMwuCAHvPD44rJ+QqkCkwDTHHHGmcrqQ9InxMPLhu/c83d+zbpc0ixJTG65eXvH4uGcOFh8DXd+hhODl9Quut1d0zwPuFEjDgRTrc/88IILHW4e1M7qqSCLQ9Uck2VU5u5EQLFonUikwheBisaI/XfL++z1TN6KKglIbalNSFgbwyKYkWI2bJUarLJIKApk0VVmwXG5p2w1GLyj0iu3aIFLNbHvGaY87zKQwYmfP6XjPOFmKoqGpl7x+/ZamreCLxTtH33mmMce/K6WQAqYpb6Erpc6iLsnsIs57TFDUTc2LF6+4ur6h2x8wdUEqzsU2VWBQjONIGAP2NHPXW+zouHi7obmqMVUFhUIoCQSESvg0ImQOponJI0gIaSgqSfIzp3HGhSNCGp53dxTTwM3tW1LMFvf9/oDrLW5w9J2lkgVVEFSyyIXcoUdWBfVyja81NgTmkGXr3XSimw7MvifgsvhtOlFUBiUlSSnmOQfHVIUGrfn44cOPjr/fiUlAIKiLGh003jnKquby8pr36gemyXL0HY8Pzxz3J4bTyPvv33MTEm9/+o55nPn44RNvipucFHxuN+YWl8jvU8JahzbZIhxkRP6GxpBXj8PxyN3HB8w/WbNa1wyDzzFb1iELTQwxJ+qOE350tHWLdxFlJFqVRCmJAaZxRqBZLDYE5xj7nkDOrRNJEM805YhndiOqSJDEuXUGQhlSCLghsr/r+fz+I1pIikIhVMQzc/3qimqxIAaBUobLiyvcbNntj2gMrV5wvb3GHTzjpJFoYspZBdMwU9iSUhliDIzzkGXMBKbpiPMjUkWKStG2Nc2i4vWbN7ixxs6OdbOgMCWbzZLK5BCRGBRjv8OUhmW7RIqCZb2mrjcU1ZKL7QtWyyuMakihoCoMl9uKyfb0fcEwnLBuwM0dx2PHOEy0C3j18jWLRc1iWXE6PfPwcAcqsxFTimiZb/qxH/GzR7X67KXPegtnI76QhCBRuqRqFzTLJTLC+HyiG7vspIwCFXXWZyRFGAJ33+14f3fH6uWSlz+95fLVlqI1uDCjtSApj5Q5Lk0pSRIBHyylMQgpcHZEaCB4ds9PNMtEU6/pO8tqsUS/NOzunpjFnNOKvCeOgZPtkT6nPVdGsSgrFpdrNhdbyqpkCpZu7BhdjwsTAs88W7qhIuKoi5KmqhHJEZ1HJcHYT/zz/+3Hs33+rtyB/wH4/fNDNsA+pfSH51TiPwd+fv6/P0op/Zd/4yyQyAYd64kpYlNifzgxjDONaTnsD3z6+JFhP0IQdF3PZsqZf946dk+PrK9qdFMwztnJlX5dsDk/vXMOO2tCsJAURkpKk9tlzlqeHh/59MMXVuU1X3/zFh+n3JIJgXnI3YS6rBFInA3Mc1ZgSVUglUZISUqSac4AlHK0+eujIHh3puae48yjI4lEwhPijIwCJYEIbppAJuw+8fh5By6yqCtMofHJIlG0jWJVrDg9DwgE37z7hu7U8ed/8qcc7ndcLa8pQ5Er2GcBU1mVKOGwkwU0dZUhKEImuuMB63rGaYcPPUWpMLqgqVuKqub6pmU4GP7iL/6MeZ559/XXrJctRSlJQjFNGRxalPksbidPCpLN6gqhawQFQhiMrtCyzG02VWTKEYGmWXHsnvA2oVWBYCbFgBSJ/eGJ6+trmqYiJo+bXD5jyYyGm0LCiIbofp1doCAJtJB4AjGC95F+GEkothdXzLrk6SExHmemYcZPnugDQqhMhjrXcu008fHDPaGExfWaZd1S6jpPBEoR5qwhUSon6HjvsrwahcxVT2KEebRIOfH5/SemwXOxvuQnNws+VQ2HpyMMkWl35Pj8QJo9tS7y9/eBmGB7ccnty1foquB06hAmoaMkdo4QJoiJcT6e2ZItWiUkgeTzRPh4/8CnD+//7pMAfw13IKX0n/36YyHEfwMcfuvxv0wp/eH/h+f9zTXPlqeH55ziUmqeHu754fv3FFXNy9uXfP/zbzkcTqQ5YaSmLGuW7QIRU+6px8Q8T6xWNQmYrcWcU3GU0CBzldVam3FcMaGKHIZBTAQfsNPM48MTv/rLX6Jlom41wTqiC4QQqU1LaUqUUFjvGccJc55EpFIkmbPpZ+s57I/IQrNoauS5QxBDhCSw3jK7mSTCuYshstAlhxiAz1bYYRp5vtsRbERpiVSJqDypTKhaomPJ4anHjpbG1FAlSlNiu5mHh0fULNBe54FXKKpaE7REmIJle8nF9oZyZZjnjlF6Jj/gfY/Wibpp8s07ZwZeKyVNtQAkp2NHXZYYKYhhxhQS50cQkaIwxCCQybBeNLy5/Yp9N7HfHWlXF6xX6nwDgRKKJHNu33Kx4dStkDIDUDrR4YPj/uGO9XqNVoDIOzbr5txdiYEpegSK1kTwAiMLiBrOYbAhnaswOZeUomxYriIaxbCy9EtHkD2JicEecNZSNAWm0pSLkmZZM6oRhGSePUqX1KuGU7fHGE2YTyTvEVJno3iMBBUxMpvNlMqR5QRF/9zzOBxomw3Xb6+oq5rj/sDYD6ggSWpExYhO2WruU8R5xzjNObZd5l3yNPUIGSlKCdKTUoasBj9lCbYDmQJ4SyFzItLUd/hp+tHx9/fiDgghBPCfAv/0bzPo//Wr7zq+fPjC5YsbFlVJWTasNxcUW8n1i1s+fXdHSgKtc9DF9dUV69Wa/W6PE4nV5TZLdIXKfMLgUVLntFgpUVqfC3cRQm7TxZAILhJkwEhFYQoIcHze88O377m4XNKPPW522QwUElJIyqJg6KaMJFMKbTRCS7KEKHvj53HiuDsgY6RpCowSufcePd7P+OQQKuYEW5kngOA8KmoKVVJIQ+g7jk8dUXvUEpQGlMdLS5AOTQZP5DalQVOg0lmGmwRxzLCUsoZ2WeTvlyR13bBsL2jrFc4PDH1H9DNu6ghupqhrtC54ejrQ7UbqouayNchUsF6s2TtPpTUpeIbxSNEYfJhRWtLohqqokKpivXrBu7c/5f3dPX/5q1/QnU7E65irD8GByH8PoxUX2wuEdBxOJeHe5qwF73h6ukdrwTiecq9eZNl18llVmSNEcuvVzj4bbGSBTwlPQshfm7sEVdWwWq7ZTRNKFjSrLe1FpFg0uPXIIAbGrmd93bK8WlIsC9rLBbFMDH4CJMELlKho60vKokS6xDwc8CEQgydJgYiCiDwHh2jiMFNpyXF/5HB/YPl6Qy0L/OSxLuPa4pMldH0OKikKtFTZcJZg7Aa6Q0ewDnTCzRNj6ghpxrkRISKQI9pC0HgPs3fgHEWTVbL96YAdxx8df3/fmsB/BHxJKf3Vb/3b10KI/xM4Av91Sul//ZuexM6WD99+pKob3v30HS9uX9H1A1PXI6TBWkdICSMlhS7ZrDfEEHi8vydIWKwyaUUKRVM3aA+mVCAzWDKdhR2QEEISYiK6rOgTSVKYMhfPIggHD58fkCIQYm75SSOZxgmiZLFY0J06hDi/YEYTz6xEiUAbQfKO0/MzYewJl0tMkXP2fcyBp1El9Dl7P54jGEMIyPO5tD8OPN/tmEeHqiJaG3ShSNozhZ7TdKKKAjtPOW4qSaZuYugn2mbFsmzZucccqa0jqGyAmYKljC1KZsXcMPXMw4BIkeBy2KiRhuAkh+eRw67n+qIhNUVesds1p/0+qyZTxNmZKC0ppQwqKWtCgP3zie3mLVobqqpEG0k/nfB+ojDmHOcWEDIhZaIwmrqqsb5lsVjRHBu6cU8InsfHz9RtduMJcoiGTR51zuCXwkBUTL0leKirguQtnDsFGSATKYqKplnyZf5IipLFeoN1iWk+4r1iq7c0s+Lydsv6cokoIKiUk6RFVova0ZOs5HJ9S1k2VCmwD4Fjd8I7D1rnepOMGF2yXLaUweJOT/g+Mu8ndvKJh4+PmLrCO/ARuqEnjQOVzEnSKgk8gqQMfvY83T/y9OWe1csVMkaCnZjiAHi0zmndKVl8UDgHMZFj6ooaXGLqOmT8h0OT/+fAf/9bn38GfpJSehJC/PvA/ySE+LdTSsd//Qt/Gz4iC0V37NCqYNmu2XU7rPM07ZKxn/j4+VPeUotEVZYYqQjWYbQmpZCTdF0gpcw1NFGgCpHJMfOEd3mgGVmQhCd5RxQZv6WlOq+eEjd6KBXjqcOPHlUotCpJMeUWoqlZLlbsq8NZjZaTh6LIcluhJarIks3ucOSwm7F2TbssQUOUEGRO1pEyswUzXgxI4P8Vc28Oq9m652c977zW+ua9q3ZVnao659zh3NuDmzbdGFtCIiKBxJIDYofkBDgmInWEhEQACSJwSMJohCxZuN2m25e+V919xhr3/A1rfieC97vXYPXFyG6js5IqbZV2aQ/rXet9/7/f84yedj/y8d0Nt2+OOFUTcuH5CQmoTFKeMfR0J0/b9TjT8O2ff83NzS3TMPOjH/wYJzWP72/RShSk1TwyjhOzKCk0IQQpBaSCpnYMXU+OAk2FYsE4wTQptF6w2T5ls94hBoGrGlISHB/3LJdXJRRkMvNQwjQpC+5vHrh7d+Szlz/Fz4F5GlmsGhCRYTyglWCcWlKKGHP+/qWIlIpFs8SHC06ne0LqGeYT+0OL0pJFs0ZrgzOSUWX6qSNMHqk0MsvikciFTJUzxSMo87mcFrDaopVlnhMpZpqFo/aO7iHgmdg8XyCMo14ZhMsFbEMihsQ8e7wHP0Ril8AKkg9UckHt1pzaCRE8mcycPdlIrGmomoarxRXtxxPZZ0zSdPctN++uuXr1CueWPHvxGpcsvjpge8+2WhJHz5x6sjTEmLn/cM3Xf2r5VL4CU6zXMie04jzBGskSQJSRtNBwfkOIPjJ2I0r8a4gNCyE08LeA3//lx876sen8938shPgS+AnFUvT/uP7v8hG3rPIXP/iCH3/+Yx7uH/n5l7/Az5EnuxVfv7/m9v4BrRXrxYqrJ1c0TUMUmSe7HWOcySnQ9y1usCyWrsgwjUSLhI+BcZoRosRJRdaEXJ7aZEFKRWVlTGHy+6nEdAkCW1tM1TCMPcM0Igk4V4w+vyz8xBTJZ6SYUPksidCIlOhOB6oKpG6wjUVpgzSqFIxEKj0DIKWMyZrjsefdV9e8/+4W0TvWZodXM6rwxosc1SiyjOwPJ7I3xOz52R/9jNkHTO2QopSSFouGgGa5XtHNA93QgyhPXalFOcl2GiksDzcDcU5YtcSqFf0wIrKlrgxa12jtSlR1mlFCnAk2qdCJVShCjMnTH265fnNgbkUJs3QdD4/3SJXxaSaEEWMyNmXGeS6k5t6TU8bVjuVywzi3OFfhKsvoYblaAIWnL4RGKYE6byW6qSDDB+sZh4DICpk1KgfIGT/NyBSRpqKUtQxkQdv1yBq8GBjiCZ976pVCVwqvPV3oGKYJJYtUNaVMDp5+39OrFsaEEop6BWRFpRqyzUxpYvblqRxdIKeIsgpnHJVUVNIwT4lh3zPuAl5A1ax58olAb3aIfYsbPadhKucmUqLPE6+p7Tk97BGrTGBkjgN+Hsm+OCPnaSRmcNpgz4EtZyyncOJ0PL+p/GUvAsC/B/wi5/yrAaQQ4inwkHOOQogfUrwDX/2LPpFzjh9+/kO2my13p3sW9YLNboNUklPXooxGI3j2/BmfvfycxjWcupY+TmhZQi5t12F7hzYCU0mk0Bhn8TEyTR6BKmESpYtqKpfDwhA8WlgW9YKqccxzxDhNSKCVYbVcFsJMPhCCx1pL09TsD4XqK2I6R5E1UkImnm/sQiWeZ0sMGoHBaE2UJcgi8plnl2MZaebM4Xji22/f0h0mLuwzood6UbNaabAdU5oJMWFMsRPL4mxnGkaE1CVAhSoZ/ixYrzc8e/6CQ9cydhNjnKhcVQ6L+h6VAtPcM44TSlhWywsWq6eM4UBVdWil6IeR2XnyHLm7vUMiCrRTabqhIwiPLJpebq7v2T/2VGrH2zfvWe92PDzcs7xakonc319TOUO9sDTa4L3ndOroh5FLfYE2rngpUyldb5YrtpcbhmGm6wackySRUFKwXq8hws3pwOPDI8fliRQSdd2Qh0Q/F1OPrDKraonW5RBSSMnheCCFjnnumFOPMImsBV4EhCw1b6FF4T24FU8vagiSNAXyNBPPW5NjiAgjqGyDsgqGI/MUiTmdAaEjd8cbdpsNw+4pw82IUuBUXfiU/cSUB6zw7LZrZIK+veV4PDBMCaMtSmo2qyWrakHyHuZyQByDL1h4oLLmV+pxIcqbpjOWxWIBk2C92aCl4ctfHP7C++9fyjuQc/4vKfbh/+af++f/LvCfCiGK2gb+o5zzr+canS9lDPXuCXK9YZ469HLDZrPk7v17Hj/e82y7wynDD3/rR3z6+edcf7zh4XgkzwE5BkxMDDGz1xWNWlHrBidqko+INLNebEryTJfEl0Awdv25CKTIgHUKkWd47NFrRx0lC7ugsjW+TljXM40z85hR2XCx2tIYh1SZrEBYR7a2RFazwCZBlR3hmAkO8kIwh66AP0zZDmhtkRh0tMhJonrDqluyemjQNcxPH1hv1iSZUNmgZsghIcNMncHVFSYpcspUpma72HCxWXBoH9EXAlVnDukDt/0tXfXI4mqFfj3xkL9FDpk6KuI049uZ/jRzsa7QSRM6T2o9wiieXT5DC8u70xuk1dRuyXJTU9US2Wgejg/42NMsNM8/aWiMxZ8E799/Q8wzy+2CxcYgROLt3ZeM04kf/+inLJdbrDKYpzsmPzEMB77++s+523+HT0fqtcLVa+qFw6vI0O35cH3Ns92KJ5u6gDrrRMoD795/xXjy/Pbv/CbbqwXBdtzefcvd4SPNZoloPsXo51jp+GT3Iz782SOH+xukGahriWgiyYxljBsbjNnw7Okzrp5cUdmSBRjajvbUlbpuvWCKEdKMkZJ+GIkpU9ktMSqGsUcZ6PpHDmNESc3ud3fITyzXH44kKzikI6MfmAbPbr1F4WiF5MM8sCdijMUEgfIZW0uq7PBdYMozcqPQ2jGHiTl4pMwlgi0TEyPRJGTl8D7T7VvSfkQd/xVAo7/GO0DO+W//BR/7e8Df+xd9zn/+EgiENQzeM+eEWTRMc+Cbb77h5uaazWrJerni4sUlZu14fHvi4+EG6wXLqLBRMCkw3YiMEoVFJFX04rHcdChB0zQ4axFZQAA/jKSUMEpTNxXLpqE2hqkvYNJl3VBXDcZW9GPg+vqW2UdUFjjjSgJRRHyKJUqKLLotZVhUNSddIdK5gJRKY06phFIJV9fkGEmUdN3+oeV4d6LGobNmmkfkIoLJhJhQGIyQECdyjFTqvOXoW5CSmBNKqkKbXThe714yTif293d4OWC2ksWVQy0jExMqZtRsGB5bPrz9QHcK1G6Lqyf2tw8Mh45ZTNzLimZdo2vFD3/yQ8gTq4UEC8TI7DtC9CzrmstXFzSfPiGNjnff3bPfn5AqMfWLIuEUibY7cTye0GpF5cqJPTLw7v2Jh8Md3bCn2UhMZck6MPiBJCLSCOY0M4eBxC9dB4mqMehT5NTu+V/+/v9Ms1zw7NUFc+popwd8O2Cso9FLluqCi+1Tnl2+4jR6hFV4mRnyI13oCVmxrC94/uxzPnn2mkW9JCfPPHWMqkdoSRAZsicSMQLatqPrezIRZTVaGRrTMA2BoDwxZYLvaa5WfPGD3+TzSXJ/feLm/Z6VrlkvFqj5LGYRcIqeURRPhdASk0w5Kzr1KFveZtCJ0ffnLELpumSbEMrSjz17ccTSIKVkf/dI93Ainf4V1OT/f1xaKxbO0B/2pHlm2Viu37/hm2/+nJgDz19/ztPLC0ylCzU3lxP7OcyMMpOFJFuBqzXSZGKamKZIUqlINEQBlkzTVE6KtcE6SzmRE4DE2Yb15pJw5+nbiXbozo1EiZCCqqlwzjINIymFczW4LnVSP5HyRGNrjCze6CwExlmULjfoME9o4cqbAhKFIfqSWuz7gW+++YaP335gHdfUi4pAKcCklJE5l1GnEQUvFkRBmYnMOPSkc8f84eGBt+8WrC5rLjYrpIR55VGVw8uAqQ1+SqBKlHmOnof9nuuPN1ixZDgNDKdE99gyHc9ttnbg8sWWVz98xpPLJ+Q0MAxH5jBz6ifGSSBlg0hLGr3j9ZMfoOKS8eFPOT0OqKwwsiT5nj65QumK2QfGacS6ml/2WoTKaKtw1LhagpwYprkkPDNoY9hsN6QceNyfMPbM26+XPN2tqMUlf/wHf8Sr55/yO+k3SENgXa/IUnA67DnZPbquiGJkva3wJ8MQAtM8MjMhtaRxFYulRZtE1z1y2N8y9z3zPDJNM957lDJoZ5EKpiwYz2cfk/cIBU1dUS+K4DaH8wEshsPjEaeXPH/yEvusIkcYOs/Nuxv29x2fvnyFPJ/9SF1q72OaIQZ8GhjbwHZ3wdIt8IxEH0sE4uzHIGScsYTZM/gTs1wTnWMcxkLGDv/6pgN/KZdSCi0LetwJGA4H3n33LV174Or5Ez7/0WdstmuOXcvYd2wuN7zmM9q7RxgDKmb0umG1aVBGFB/hKBFaIHUpoBTIZ6JtTxilzyDNX56kKqSyaO3Y9weE1uxPRyY/c1E7Dl1HygVCMfYD4zzidJFyOO0QfiKn/Kt68f1hz+l4LGUWVfwDPnrGWWDRGGORWWO1YR4Tj7cPfHj7kYf7B6zVIFdIXYoqISUU8pyy08hzHDal0tjLLnFixrmq5A1ioj129OOJeln8gdkKnBVkFxlCCymUFmIshB9jDE5Y8lTkJKkNqFlghKISBqtBKk/MA4gZz0yYekJK2GpNmiHPlnac+er2OxgNN29vyEPAbg1WWqSQrC+fYJwjzJk5jEx+QE+Cfjhx7PcYJ6iMRciAz5FELmbizJkWtWA+nXg87mmahs1qhyKwsA1P1k95oz7ysz/4J+wf3rO81Fy+2qAXlmE48bC/IU8KPyWCGBh8GbVOqSfbiKsdrm5IOXJ7e81dvCtBstmXx4SQxUQkwxlOk4kBNpstq/UOHyMpBe4f7jh8uOPJk0u0UUxzYNFUROD+8R6jHZVuWCw1Oc8c+9syCravWe/WbJ9eFFFMEPSHnilM+JQYuom8z9hLTe0qGtvQzb7E4s+dBoVEKoHJBW0vQiTOMyKdiVW/5vpeLALzPHP94T2ffPaKaUr80z/5E/7kn/4MyLx4+Zxq1dBOA4euJaTIdrdjtVzy2NTM7YhMICtdXg21LNHjaWIaPJlEtbAslk25wVKEnIq5NWZsZantAm0qpLZMBFzteGxbhmkq6udhIGuBrm2hBZEK0ivM1KLCaFOmDwimYeDx4YG5H1mslkSR0UZia4cxGiU0RjoqXWOwtN0j+/sjOWZsbfEh0KWOJGGcAto0FL53EQsooYvpOERqpakaDfJEIvPi6hmffPKSt9ffcv3hLZfPdiwuGqII1KYqPQcUWRZLUogeaw2b1Zr2bubu/T0iaHISLGXFertkt9uwfF5hlpmue8DnCaEgKRDZUMuKfvKMp8zh7oHjx7c4aqy21NYxdxPjaeLp7jlNvUQYTYwFHXZqj2irOLYPHE63JTVXCWIu9WxlCl5OBkpPwimSn5hHi3E1UhQrj5SSMHpWbsH1m3ccDtfsXtQ87y9ZP9uitIMg8DZiaBjDkSl2BCJZK4S2CGnO0wdT6sJa47TFWUelHQJJjBCix4cJHyZi1KzWFzx//pzVesM4jnz51Z/z3bffMo4zNhtAIWQZJ1fOoZ0sYRQ5Uy8kL15eMFSJ5a6htg4fJrpjBwH293vmcSYLyaE/sj/usfeOevMcpxyjNFRuwRQ9MlPeGIXGoIjDxGkMjIcWpwyz+EtWk/9lX+Mw8O7Lr3lx9YTj9R2/+KM/5vrdG37ww8+4uLhg9DN393e/8hGGObBslmXlToJFtQBVKDwxezjrwMZhpB063KDxfma/TwiRaOqayjYIXbS8/TDSnkaktrhlxUwsKUApmFOiWjgu9AV9OzAMPeYkmIeOaZqZxrF44KVCRBiHkTCHf+byyyUVqLTCuhJKilNmmiYmH5jayKra8NmnhkfzwHzbE/qZkGEYZ5arGqXl2ZiUIZdfxugzPgcSgkjk8Xhge3nB6dhyd/fAse1ZbJfUCFRlUdagTSagCKkYinMOGKuoKsfD1JLGlkquSjHHCLaLFZ+9fIm5kgzVkSEFvI+4xoLUHI4DfgQrl+wfjpyuO5rcsDQLnK1IRtKNE8PRw6xIvkA/Ykg8Pj7Qdie0BeRMO+6JYmApHdqCNoqMKKlMkdHZkCmRZqsMVpUpizaKfj8Qpwfa/QE/DNR1Q5gGbj6+5zTuqZZLnD2xqgeerF9w7B5pp74YkbXGWo2zFVW1wppFaYQGcKbiYnvBoloi0MWzkCNzGJl9h/cCHxLjOLNcwaJZ8vrV5yAEHz68IaSIkJFh7HDWoUTmeHrEascUPM7WvP78Nf26iG0Nsox5xxm3cOjaEVNmsVjQnk589/Yt/bHneHfErMTZY2lIMSMzpDGi0cgU6U9HxoeJ4+0DWmqS+p5vBwQwnHquv/vAt1/+GYePd6xMzcurZ1xsLxn9iJKabiyMumXtCSYxjIFunKkXa7RVhDgyDANCabIQxfHuI213Yr9/pB8OZCK77ZaXz19gVMXtx3tuPj7w8cNdAZFUjux7fvybX/CDn/yEerOkUSuEkPSnDmsV99cfaQ+aeRo4DT1GG6zThHmmP7aEqQBLSlGxiE1PbUBWGWMNQ99yuOmo1ILt+pKXP/mMcRj4xnzFXb5FnBLz0JdknijbpXSOOucIyafyxJIaHyNV7ciV4t2Ht1zffmDwLXapqSrHxbNL7NKS8sw4nfB+Zpg7UhqRCKxxNKsVy2YiBYs5R5BFTOWNKQfmKRM02LomqgldlV8b7z3zCEu5Ik6CMGSW6yUVDqKgqsoZiJgV+5sOt1tTOUX0oai8xhMWuHi6RNU113f3nE4Dm4sFUisBv697AAAgAElEQVRm7wlzLPtwVc5WXF2RtWMaWlQuUe7D4ZGtNogUyMlDnlnWW9xCl979fYtSJ7hUrOsV3XhkToF61bDaWGwtEUqSUYxTIMwzOcFmpQhR4KNGYgpaTJfRsTQGhgmhClZtvz9QNxXH7sDpuC/bOR2Zh56cJdYp2n7mcDwUYrB2XOwMq8WG0LW8+/ieo6nwY2LwM7apcfWiTH5chbEGHyIfPrxjeOjZrJ4htOBuuCUnQZgTiojVJVuZ5sR0HJi7qRCt0vf8TcAYQxhn/uxnv+D69gONtNjasXAL6qphnCfmELm7e6BxNU5ZpnakPZyIKeNDIssSAw4plnSUNChVXvH6fiQxkdKIDyMxTGgBEsPd9Z6333wkZcXT7RXZKFbLLT/6jZ/yyeuXRAIBj4+eOU1UteHJ1SVawd3tzDx7lNTklJj6gdPjnjhHqrVFpPMhHJkUA8PY4wbD1Ab6dmK1u+DJxRVPr15wOh04PDkSx8Qx7wmzx1pJliX+lkUipbNJOEQWZsWyWZDjxIvPnnO5fsp3X73h5vYGIcHoIgqpmgq3ckx9IHQz0zwwTR1ChsLi0471bsN4mTkOA7FPVLVCO82cIt+8+QY7V1x+8QztQMm+KNnnuUwpdIOYBRqNlY55CIiz089KgzaGnCtimxBeEOZAuz/ixxFFPLcFE6tVzcNB0Q0HbA/GGcJZmCHyeQaeI0I4phTLSM4Yso0gItN8ZLOtCaknxB6hVkWp5vW57FVm6DF5tBHoqKjqiuViCSoxTCOznxHCoJXF1Y66XiBkqZ8XBXgm+MDsW1KaIRYrdtud6IeW3cWGYTgwhx7XKHyYWW0XZctOQmrJYrGmrpaEMZNiaZ0mEQjZ0x1GwpRY1Eua9YoQAzklDn1L+3DEollXa3LM1GqBcYa74x0yGdI4gypHzjmAnsvXyJzIsUhwft31vVgEQPDw8Mg4dAgyq3pJO3Xs7w+8mALHU8u337zh5vqa3/7pb7KqF7x/d81pf2T75CkgabuWqlHU9QJlKoZxZhoH/DwjhUBpw+xH1qsldW1BRMbRIzQs1g1SWK6eX1HTYCrH5mJHyCXr7+PMNI8MU4+QmcW6wc8Dx70pBaMsIcLcjZz2B6y0uF0ZY8V5ZrGpabYN0iamYUIkxasXL/nk6nM2mycMk6cdJ2zTsLzY8OHjDce558l2dZ7/RuTZdBR8IoVEtbQslgu0cSzsmk19gRYKZzXH7ki9sggyj/tHmrOYIqYZpQrRVygBsSQe60rz5PkT5NTSXg9Iq0CXkVzXn3iiXrLaPiHnDp8cwzTR9x1GKtarDe3HyNjOaOVYLtcYJNM8EkNkudrgFmvGFPGdp/cdN+8+0o6P6Doz+ZaH+4ntZYPRmRQ9bXvEzmUBsdZBTMQQkFIUBmMIVJWldpaYPctNzZtfvOX57iX1QrO6rKkbwzT3RGYWjWO5WJNSoD2eqLTlcnuJNJm+HZnDgA8FMGJtEcfmGMnZ4+OAEGXL5GpHjIo8jKUrEjPzOGGMZPYj3377FY+He07jEWthtVowTj2r9Yrt6gKiQAiLEhWxHGQRYvnBLhYLDo/XHB97lq83VHXDsT2eeYeWoS/15V295WH/wN3bO6oLiwqaPEt0NFSyhlEwHHpSsuQh4YdYejXye24lRsCxP2GlYhwGTuOJ1eUGZRXfvvmO64db3rx/g5OW9njkqy+/4uOHG0JMvHr9GZcXl3SzIcsZ62q0qfEerK1YLjfFOeiPLJqGqpLnPPnINHtCSGQSqMhi3fBs8wnIzHK9YvbnPHiYOJ0OjNNYZsRDWWDKrF8wjTNT7+lOLSImamuI44wXASqorKNxjqADRhm0teQRbq7vEFiSUpz6HlkbPv3i81JJ9gM5e+ZxZBgUja4YugETHQ8f71mZNevXC776+jsehgfEM9hd7LjY7vj62y/Z94+4yhKi53gaaWw5kJumniF2mEoVCKtQiKyo1xW7p47D/VsmEVkta7ZXa4ZgyNYw50zyBS2mZLFCVaZGRYnvy2unY4k25Q1IO4PPZ95d5Zj7nqHtyVXktD+wP92xe7ZEuzKR6NqAFlAZg59meu9xrkILRVUV4QY5EnDUtSbnES0ETzdbGllzuj1xffOW1WJF3RhCLIu/qywIBwKGbqAWnsYtUUTmeWK/f2CeB4yzSOkRVamZT31L2z7iTEVdr3HVGlNVVFVZKKyTDMeORMQ6weQ9Xb+nHw6EeTq/hcJiuaKqFud+iGC73FC5NZ0asXrBNE4c9x/JGfwcGaeZlAU+Rh4e94RpYuWWTN3IPPRUqkJlzdX2ivpJzfFDy/Vwh+oF+7HDoTHRIGUBymrt8HPEf99HhCkn9MIR5onjdGJzueUnv/Mb1LslQ54QjSTpRJw8wme6rqXrToyT53jYc/H0KcY6klAgNIJSH1amgEuN1vggsUYXyGgKv+prh1jMmLauMZUgjpF59pihRxqNqTQpl5k6ORLDzKkrph0ABOW1zRd3Qm0cVmrmYeI0t9hNhVKlqmytpqoa+v3IL37+c/wg+d3fFbz4/CWL9RJXW55sNtiqYn9/w9s//ROq1bZosuNZzpoE3anjdGyZx4lpGji2LatmxZPtUzbNhnfvvmPoOoZ+oF5VKFsIy1lkpC5K65gzBbkqmYJntdhw+XLLze0jfop4nejyjKgM2SpCmAu2PRWUlhEGIxx+zhweO2IQCKM5dgNaQbOwCCno547UFbfh6XGPWAhkApUFq6pB1ZEoR3IoxR6BLFVon4giEE0gm1i4+UKUV15rSoQ2eazRfPr5a5yo+epnX/Pu7Xv6oceum6I+jxppFU4X6rTIEqcqnJC4aDlOd9y/uyvVcCnR1vD0xRWbixWiYEkYSUxzSzqU/olxAm0TNltyEAy+cCZjmlFS4qymtjVG1xhpWDU7pFBlWpVUgdqYGqUsYR7oTyNGGXa7S8jmzMFQOGW5vb1mVAP4zHAamOLE61ev+ekPfkpaZm4Ot6zsmtRPhDQzDxElBBOR7tgTI2RVJii/7vpeLAJIqHYNtx8OUCt+9Fe+4Ee/9UNO84AVDU/qZzx99YzHm3uONw9Mp4HRj5zajmN3pBtPuKbGuQX6TPoxzqHDDEJgK0eWFVKWZlXK8cz4CyQyttJsNktcZWgfO7qpoKHqRY0wFSGUNpyfe+IZCkJIyKwKWDQkko/nKnF56szTRH9qkZVEi8INVM5QNxXtY8/19R1WNVRNxe7ikiAjrrI0rkJieP36NQ9vvkRqcZaeClxdc/zQ0R1Hpn4qNl6RqSvHMPTc393SihPXH244HVr2D3vsxTMaXZFTIMZAzKlgz89V3BAz8zBR12WLUW0a1Byo1g1BZ1zjcE1FFB6jcwmynIMq0+iZHgKHhxMxFgfeHCPSGOYUMFYzh579zZ6qapisREwSlSWX20sut5f04UA7dyRxBq+cn5ikoqcPk2eWCiwYKQmxGIwqXUCvfd8x+gkp4OWrVyih6KYT2jjWywVBZnyWpABKFAjMZrkjeck0DizVjtR9x8PdHiipTt/PiPCC5a4G7Ul+RhmN1CWj7+eyPRG6oT2O3D8+khHYqmG5XLNYFIy7kOX7u2wuUVIhYg/ZED0o5c7To2KE0lJhLpYFzbZcstvsEBHeffWWh9t7VrrBUMjO2/WWly8/JVjPk5u3vP/4kSnn8/cusV3uyFPiOHdI7Ygpgfie5wSElAgncJuaT37wgs+++AxVW/r+kWQEVjuUkSy3S2TOvO862tMJhMDVDiRlH7/dYa0p6bqo8X7CWMViUaH1TEjF355TwTBnfmkIdqw2C5SWeD8TY9GhBR+Q08Q4DAx9xzC15OjLq2ZW522FZ5oCMpx5AqoozmIKCCXLaywwe0+VC1xksVrwe//277JwO159/hJkLmRkWVDmq2bF5599zu03L3gYS+lDSolCMZxGdNZs6g3BF1HJerMhtIkv//TP8H0ixMSzpy+oXYUVBo1hnkdSTIzTzJxmmtUChGYcAmmGXk+IPBBtolkvuHx2RRARU1fUK4EQvxwrRmKKjHPgeH1D9zEyDBkjLCjFy1evuHi64e377/B5QhGY80htK6xWdMNIjomYPW++fcuUW3SdsEtFkvmsZytYrpgighlQxR1pDMKUqnCKEWkVfvB8+PIt92+PNGJF5RYsbKntaqoyXg0Jkc8o+hDRStGYp8xqorUHVmbLIR3o+6Gcwp8ip/uOnCNZebLKVE3Ncr0utXNAZsHhcc/h0BLmhKsWON2wXV/w5OkLrHXs949gDVatSTHgrMaakm+IITONE9YWTdg4lMnW7H2xDPmZME6okAj9TLSWyjiMK2ITbRSmMqwXG8KUYAYZdXmQVCumMOFszZyA5Ll69py3X3/zF95/34tFIJMJIvHis5f8+Mc/YHGx5jS0Rf2toRs7TocTGoWtLVOYGfzEZr2lqiu0UiyahtV2c9aMJYQvNB6lwFpNyoY4jZTglEQKew4PlZXYLWomP/L4+IiyutzIMTIPkTAXsCUUPmAIHgVkHxjGkTB7al3hpDp/NQmhBavNksV6SaRsPXSU+DBRNzX/xl/9Kxi9gJy4vb9GGkXwnqRnLpYXZVuha6wacLZCZkEOYKXj1YvXbDeXzFPEaMvl00va3PPxyztiDz/96U959tkzjtMeESDPmZgSOXMeW2q0qpj6yOGhpzEbkBKPR9YSu6qxqwqrNVWzxdoOH1tC8sQYmEJgnCfuHu5p7wM2bRCiLHz1Ysmz5y9ofcfkW2IOvP7kik9efML17QPtu7eEEDn2Jx67O+xC8PzTJwhpKd6PjBSRjCTGwJhnkLKotbLAVjVJKaZpgCCocKisON613B9P1HbB9mJVEpxyYH21Y11XxYKsV3T7EvN9+vwnNC7yjq9QwrCslsQpkSM42WCyJQyRIArJyYdATgJjRlKOSBLDUFgQ69UFdbMhJsHUA8mxXlyiRIOUChFLf6SpGpytSTHRjh37/YlF3SBVcUL248DkR/qx59tvvub6uw+M7UCtbakMK0W9W2Gcoh9bjHbFZBUyeU40pqayjtOpY+o9WUpCzly9eMFf+3f+Bn/4D/7BX3j/fS8WgZQSKWcunlzy5OppOY3PgaqpSSKVgkRKReYRM0pr1pdbFosV4zTjZ49zDmMNOaezLGQipqnk/HPZv+cza04IVaqlouDH6mqJNYZ2f+L+7o7Nblt06SGcX1ETRmtS1sQAPk4lr38O/ZAExtgysgqhkG+kxi0qXF0VBr4UFBxOgWh0Y4dTME6RYfZUVYOM0FSaMXa8+/oN1x9vcDuHMxXz7MlBYHWDbhZ0hx4VDVcvn7PbXpA7SeVqJJZ1syVMmeOhxyaJrTVZCkIoPQutHTlp+tPAcJpZ7hRWW6SUNKsaszAkVVqO1i2ReSTNIyGXmu8c5tJsdBLlZNkakQlx5Ls334CO1MuGi/WOQ7vn8y++YLfdMkW4ubujHzrWqy3bqy1Ze1yj0bbo2bIEJTI6l9+JEAPTOJ9R9II0F5gn50VRKs26ueByMbI/9shBEg7QB48yDndV07gVSZjCYDSeeRrw5wVtjBNjGAip0KhDAC0tAoOfRqRTxTEQMn03gvDILKicpXaXaFUVLH61oB9nwpSYugAXjqeXWzKZ4/GIM6rUuClcyXmKHA5HRBZFNycEtrJcVFsWVUN7d+Dw+EgcA410hNnTTS26Uhz7A+3Ysl5qErlwEqSmtmVB7IeOYZgYp5l6veT3/8Zf53f+zV+P/fxeLAJSSOqqJsyBoR+L9y0XXp8QEmcqvC3MPDJcXb3AyArvIzlmki/8uRgDiIyPE/1wYpoGcp7PJY6IFhKfBQKDVBJrK6Q+3zxScTq1tO2RqrIlM541mHx2FYCUAqnKn3EKzL7Mq9VZJS6FKEElJUlCYuoaoRSo0opTRhGh5M6zZ/QDPoI2krq2LM2CpXbcffeBn/8ff8LD3SNXq+dFlpol01gOe/w+8ZgP7D7Z8eqHrwghMfTlcCkjef/uI8ObgUkMvPzRSyqzQKiMjAZjaqQVKOGoK4vcLH71vRQyITRIK3FNc07POfIsSbMn5FAIuiRM47i42rLSmelWYiaFCJLj8Y5vv/P84De+wFQLxDyRjOGhH9DWstvtaKeO9eWKTz7/hNO457G7A5MQuZB+87lvEVJpaPqQULNHCYkfZ6wS1NJgsoIJQpuQs2WtXQF4WMecBmIr6B764vdzlmACMUaG2PHm5mtSTog6Uq0V17ctKMF6tWOxXpHIDJOnrjTGVgglUaZCCo0zNbvtjvXyBSlKElDXC7YbS0bgqpoUBfOUcZUpvY4CQmeePWEuP684RfwYsEKSpUAayWa95unukr5ZEfYDd+MtTIWCFZLnbn+Lfqe5/MEz7LYipEKe2q3XSA9h8lRV+XlKMr/xW7/Fb//V32X086+9/74Xi4DRhudPXzBOA/vHluWmOZt7Bdq5EgGWA9qYArR8vqRxK/rTgNWWpxdP0dIQgkeIRAgTw9QR4oiQGSFysfhqg549xVCu0dqiraZyNUIqhn5gaFtOxtKeTqzWS5x1JK1LyQlJ5RwpRHpf6K1KKUQU+HFiCgFrDKZxKFchtcJYg6scWmlyLtsJrTUxBPpuRpuK3eqSp5cXhC7w7tu3/Owf/jFf/emfs9g4tLAFhZ0i93d7DrctS7WhqRtAst+f4HDi/btrkhfIINnfHxnFiNtYLjZP+OTZawZ1pPKaIW+JIiKxNM/XzG3k7uMD0ziTz8013dQsFguMWkGsENLSp0ycI9pqtLNooXGXFt1UyI1huouEk8DPgojgcb+nDTNtGJEfbthtt9RGYZzBVhXKWAoJVOGqBcuLhiEceTiWgEzEIb0H5qL2ChElIyZRDjNjRiaYDhP7mwNpgJoF8ymw2V6Q68B9f8Ptu3tsP7B5ssO7gFWGMXqu3/4cqeFy6/j0x1doOzINEWfWuKqmm3pI5SBUGoV2lqZZ43RDZVdsNzteP/8tYlA8PN4TY8SqBtdUWGtQABn87H8FSPVTyTgM/Uh76LC2wZgKSQmEdeOAqw1V49hWS+a7luH6QD8MWK0J2fM47Hl3E9l+c4moFIfjgRACVjWk0ZNCQApNVTd8+uNP+P2/9vsc2xN/8Mf/5Nfef/9foCKvKbjxZ+XL4r/IOf9dIcQF8N8CnwPfAP9hzvnxTCD+u8B/APTA3845/+H/2/+htOLZ82e8+/CetuvRlUZpQ93UVHXNOA0oWrQyv9ofT0NACsPzJ8/YbncEk/BxQp3Bkr9sTWmlyEkhRCahEVrDuXuvVKHxGG3w0TP0A21/AiU4Hg/I85mEcYLaWJSs0FIQpsiQCu9dUk7vvZ8RQSAF1KrBNU1h0pvSGky/uolk4Q3GUqdthKapKoxUvPn2G/7Pf/TH3L+9p3E1tnbUdU1tHeNp4v76Abzh5WefsrvYsh8f6U4d81RO6NdsccaRVKlnu9qy3Wx4+vQpwa251Fv6fGKaJ0SSbJpLplNg7hOPhwdCDMx+pu/L4Z1SZ6yXcQg0OU8oWWCfRmsyiWWzYLndYK8axsfE3c2JYztxd39P/+EDY/Jc39zx4y++4EdXV/hhJs0BGWHqJsZ5JmvB9mJHnTTH4Y4UBCYrrDGE2eLD/M+kLeO5WYdgnAX+ZuR419OINZv1JYfpUAxVyzXZJnrZorJBnA3I24sLhNS0H284dg+EFNmtHT/+7R8x95GhSyUq3E5Eb9HWYY2hrhdsNk9o3JbKLFktN1TVjpwMs8/0/cCZjEEilb1nlkQfkRJCmvFxJifBMJaa9Hq5K6lEkRj9iI+BU3dimAbqSuNqi6sc0cbyUIwFljuOPR9vPqBqzTAVevW+e8Rlhao1KSSePnnC7/1bv8fu4oL/7n/87/nf/+Af/csvAhSvwn+cc/5DIcQK+MdCiP8B+NvA/5Rz/s+EEH8H+DvAfwL8+xSs2BfAXwf+8/Ofv/bKEqpdjWkdj49HRO2KVSdYcq+oqqcsG0P0nrpq8MFj6hlpPaLWjKIoqqKPpBjJOWF0QwyQskc6jQ8jk4iEqoghrHEYpVnYCj3D47s7ptsDqvZgJub4yO39nrt7wbOrp9RVTe5hagPH65b9/YE0eSSSdbPESF3OIlJAoXGiJuQZETLSZ3QwSG0xGMR81podB47XJ6rZEJuRj794w/131/h2QjoNdamILqXlsQ2kQbBaPeHVF1/QrBq6r0faw5HQwiZcUlFRG8vkW0Sc2cqapEb2HGlEjYhLbKpQIhFEYA4KUQu2L7ec8pH2scWHWMjFx5Zq7bDO08fAKC2mUUTREcJM3ZgCM4kerMLqFQMDfp9xjcEEiwkZNUzo2JPf3THNjnw3Ie8nDo8f6T/ek5eSvIZpOEE1I7VH+BEdEmtRsaxqunhiyiM59PjhxDRHHo+CRd6xTlsWcoFGoq2muVhwP59Yuh3PN5+R0oDWibffvqN+seSz3/wJk1BcP5S2536YcfUCVRvupweSmLG1RcaRxmhW1Ybt8orl8oLK7qiqDc1ig6sW+GSYgscLhV44dJ0RpliihExkioquqIgKvapvOx4fP5IofEGparSS+HQgCsNpnvnweMtU9bS+Q7rCkRAhUSmBk5BlYrlQCDUwhT2mnvFuxNY1zlqWdsMnT18yixP/2//6M778o5+z8hU3/7KLQM75A4UiTM75JIT4OfAS+JsU7BjAfwX8/fMi8DeB/zrnnIF/KITYCiFenD/Pr73aviOkyDCPTNNEzqLEblMuEE1jEanglFPKWGsJUZSuQAxEInOay1hPCKTUVK4hE5jzRCCisqaqqqLdEgKjFGM3cP/+lsebe7TSXF5esFyuabsjOcNisWC/33OSJ8Z+5PB4oD22jMOEApqmoVkuUELQHk7M0TNPM/7xxGk4kFRAyhcsmiU66v+LuTfZsTQ50/Qem/75jD7EkJGZnIpV7FahoLWWug5BELSUFlrrCrTSHWgpQOiFAGmhK9CmFw2ou1hNMpnMMSJ8PPM/26SFOVNsNNkFVAFCHiAQiBODh/txs2P2fd/7PDDAZC3nc8v7P7ynO7QcvzuxqdZ0hwsyKgSCeZ4RziSHoQ2M/YRWhuVqTV5VqExTNhVD13EZWnJZkpnUvhJSEJ3HW8ulO6EPD2yX2xdacDLyBCHwMoKCvKxYrtaEAPt5D0ROxz2reolWnqntiQKKqqAbO7x3WGvRUZEXJWVR0x0Gvnv/Pf1l5t3VO5QwzNNIGQxaa3a7R7r9kUxppID9fk9736HXGfXrmsVDjlw47DjjZ0+0ARklShqQCj+nlGjd1EjhOfv+hREhkpDEaZABlWkOxyP9MPD5T/6KutTsn+74eviGdn9OBqbcoJVg0dRMU2SeLH0fE6xGCyIp6FXWDdvVLevlK4pshVQV2pQomSGFpuvPzMEiVCRGxzhNGAJFqQnBcjyfyHWB1pIi15hMsD+cObdPjIOgLFesl7dMg8X7QGYygghIrUBLZCapNzXYwNyOyYIVS0IeKDKD0RLvZ6QMrK/XZJnBkJObjHa68OH7B775w3vsPCcxyz91E/jTx4uE5D8H/jXw6k8W9j3pusDLBvGnzqP3L8/9JzaByDgOZEaTmeTIS2IKgzbq5fguCCqpnhKuWkGwSRiq1X9QTIwClNHJiIPDTR4hJYUp8EJhw4BGoVAc2wsf7++JU6BZLLHRobXhfD5TliVVVRN8miJ03uNCssUKLamrms8++5xCZzzc3XNsLynUEyO2H2mPLZf+DB7CFMmrAp0bhmnk8eGJu6/vkWhKNxLbY0Kg6wxZANERJtAUTINn6C1aZRijuVzO1LJgsW5oL2f6+ZG6WbJYrDg8PzHYgdkNqFGijo+os2TVNESZ45zDBo94sQdLJVjUK8I29dKHtid6ENKjskA3nWi7PUoHQpgZ5wGjDJnKyFXOolqBV3z/zXd889V3LIoN0mjKPKdZl+gR+qnn+ekJ7STvXr+lXjWIQdJeekznWIglczczjRecTU5G5yLi5a4cSC02k2dcb99gXSR2D6gR3NzhwoBWJVF4hBIsV0uEkLTdQF1tWF/dcn3zmm8f3vPNV7+n3DTM45myUAihmeaB+CKOkdKgZEa9qNiublk2W4p8hSBHCo3OFdoIpArgR5wfiD4QhcPHmTinePc8p3ZzkeU0TUlZreiHnsPpA6ieKCWnyx11mRGcpDCS25srVB5YrxsqrcmipMpL9uaJ/d0ztndk5KhcYp3ldDqn2QajqcsaIUQCtsyWabqw3x8Z5gFtUpvyn70JCCEaEj/wf4gxntPV/2UJxxiF+E9QC/78v/eDd6C5WhCiY9FU2NkyT46uvaCW6T5ttCKQpJ1SRJRUeB+w8x+JKQGJQgmJlskLmGmDMhIXJdKZ5KlTChvBZAIlJH3b8/z4xDROLMsFVVFxvpwZ+o66rlmtVmSZwc4xzcNnhrKu6IeBoCTVYsGbT9+ho+Du7g4bPTrPiD4w9xY7TIyngeewoz+MFGWZ6hc+cHy6EC+SzdUVS7MixkiZ50xxQBY1RYyc+hNGFNh+xs8BLTRjP/Ldd99z+2bLzas1RVUijeT6zS1/9ZNf8sW/n2k/7Bn9hBss7mipxwIbBpTThEjSpvGCW9cabQxSaZxLKrGubbFh4Hh+oD0PeNHTbGTquAwtZZmR65zSNDTFktOT5f7DE107crXIE4Zdea5erRkGzfhwxquRGCVWTYQsR+YQVURnms1yjcHQnieUVshMEcSM96nPLdCApqoqFs1Vko2sHe3TGRcnisqQhxwXPUiDzgxBwPNux373zM12yy9+9jeoIqM9HtmdHxnkQNHkKBGI3jJPaYqyLHKWiw3LxYb14ppc10gyYjRok1EWBcro1L2ILZM9p41LCrJMEKKj60eGoWW2PePkQDagLuz29+yOzxR1gVSScTjQTw2V2lJXJdVqSVYpkA68JVsX6EwzuZHB98z7mcqlobbT+YQ9zWAkq/UGZVTyI/iAUp7gA2FEeAkAACAASURBVP04YL1NG777Z4BGXxasedkA/tcY4//+8vTDH4/5Qog38MOV4wPw6Z/89Xcvz/0Hjz/1Dlz/5CZ6NyOyjKrMaduW/f4ZKVQCeNY1IAjeYUxSPFnrmeYRJSGGjODiDwYdoVVi/CuZoKBZiQSCnzFIZAz0bcf9h3vuP9wjg0SvMoIQZCZjnmeWm2XyC/iEBJ+sRSDQmUFmmkzp5Lk3CqMNxbLm2t+QZTmn84n20HO5dOAFzILpaGHQOJFkGPPeUsqahV4Qp0gUkfXthiEvGMeB6D1aGIzKaC9DOhVEg+09T9MTUgRWiwotUmTa5IbPfvYOzEyoRp72AsuMKAKz7zj3exweqUti1HgP2uRkWcE8T/RdUqsBjFPH/hC4tDtETHl/IQzOjSn6C0z9RFkvkSGjP13ouyn18qXChYl+cggdiZlH11BuNEYU6KUi5J5yk7PyS5QxECOunxEzFHmJ1ppoB9ppYrSWGAWgKcsFeEWMKb3I4BjnHh1yMpvjXcQHy/pqS72qyIxmf//EN19+xS9/+TP+9j/7Wy7uxB8+/p7ZtSgVSOyfiPORrChYLjZc37ymyhZoXaFUkY7/0qBNjs4ViDQvcTh/ZA5JAON9YJwiykS8H7E2MRucn+mGmX6ynM7PoNKJUMiQ5DixRcoVq/WaZl2A9gzzhdFZXJgROiDWkso1xDxN/7ppZvf+mcmPvPrkFWWZBq2st0hlMEVG349MbkYaiZIZwf8zNoGXav//Avwmxvg//8lv/Z/Afw38Ty8//x9/8vx/L4T430gFwdM/Vg+IMRKCYxz7NATiHf0w0xcVgohWAoHC2RGlMgQCOw1MQ5847kahVJ5eKK0RSidJpBCIGMl1Qa40bu6ZfaQ7n3j++Mj+YYefHXm1ACTWObI8YyEXCVnlHDE5SpJjQEikVEmOkec0qwYbHFpqFlcrFpsV8zRzOn5Nb1vQJCqx0mS6YFmt0DGj70aU10ihsP1M7y2mzKjqBqEVk5uJMSBVAmyOw4SfI5nMyWXFbC3dvueyazHSkMmcw+GAjTM/+9XniNVE85Az+IFYjygT6cczHpByJmJQskDpLGHWnEdKSV4UPD72+GCZZo/zSf4hTWB2I5EUsrGzw/uIqjV9O/Jw94y3nqoqQSYJx9hP2Dgm9XrmqbcFhaooFznL7ZI3v3jLZ73l7sM9u/0zMViqWpEVRcKGjZK5dbTjTNWk/rwSiqEdcDZgjGSzXdE6yeRiyswLSSCy3Cy4eX2FINIej9zd3zNNA7dvb7j6ZM3VekO0M7o0DONINwikkFTVIqHQsxpEAWRIXaR5EqkIBAabcg5SSU7tPS4OZJs3SKVwzuHHZJp2dsL7CUhj1iLOlHUKtCnlkS/cArwjKyXNMl0bXLT09swUZuYwAh6XO+RSUooSEzRzOyajc4jkuUHIiHUziDRePvQdbT+gM0lR5Qinaarmn74JAP8F8F8Bfy+E+H9envsfXxb/vxJC/LfAtyQxKcD/RWoPfklqEf43/9gHEC8/nEvZ/MxonE1fSGKVJveCxXuLnSM2Bqyd8HbC2cCgJVWRIqdaG6JM3xCpZaMwMkPrjNE5DqcnvvvqWx7u7rHzTFMvyPMSpXR6BwqWsiyZXaoB6JcsgjEmtR4JZFVOUVVUqwUy0wijaNZLyqIixsg0duSFIstKwiSwfaDJV6wXVwzdxDTNL21Dn6YhJeRSkuc5c3D4mOQinmTpncYRGRW5yKlkgqrMw8TloWO1bChUQd913D194Bev3rF6W3NQFcJFvAjJeCQD49QToyXPlxTFAiFgHAeIgTzLiTFwPh8BR16WZJnAZAHnJ7wNOJ9OQ8FHMpWjhOH9dx94/917pBDJFiQ9/dQy+5YgpmRllh6ZC1y0ODPTvKr45N2nBC/xxvP0b+4ZjheEbchepgbPQ8+lbRmCo2nqZDsKSUfu54BRkqww5EWBNx5shiRnuUzDUHPomaaBdjyS1znDPPPrX/8DP53esrs8M1YjZZ7ayVJplvWS6+vX1M1VKgCqksyUaJOjjCYSGcY+0a6ZyYuc0Z3YHx6Yx5nbm09o6gXj0DGNjvgyaTpOPUIZykpRZFVySkZFVBlTlPTThDT88FpLCXaeGeeRqB02jHhlCcbhjUV5iS4M6+0a0UYQaaoSqdDGIIJgf9xzOvQUukLnimmeWS4W//RNIMb4f7+s0T/3+C//zJ+PwH/3j/27//EHCggkIXjyTKcKu53JjEHESHs5E7xnJLyEfGaGMb3Qdh5RG0OVNeAjMaYKudLmhWQsMRouzzsePtzz7VffMnQdTV1DSELUsmzIipy+O73Yhs0LqzC+JBELpnkieEfRlJgsSxkDlcaBi6bCmIw8z3jz0zeUjSLTJW4EPwiW1QYVM87dhTlMZCbDzY7ZhWSvAbROhdHLuePcnchLgXcWPztqU1KKAuY0oZhFSfd0xnYj0QYi8N2Hb9BXM1N2YdIdVo5IwGQZUku8S+qzssrJjMDZOW10L3fG4/4ZZyeyHEwmQTi8D4SgwYHzidokoyRTGWM38uUXv+dyHnh9/Q6tcqZpwE8QxEhQFhlTxDqGiPOwLNY0Nw1qKZmHmcWrhtefv+beOrrjhfFwASKXeaa1EyGXFJ9lyEIRgifLDGWmsC6NxtrgyaqS4AuEzXj19jW69Hx4/I4QZrya0YVEWMXHj/eIzDPFjna40IhFKgLWK15/8ilXN2+JJPVanlUQBEhJEInsNPmBY/dIN55RSuFjqpscd2eWzYq3N6/RMSY0nBcM3cg0T2gjURqkVqyqBUXecDqOnPYt1krGF/LyMAkinmme8MESgkunARWJxoH5o3w0sLneUjQ5wgQ8HikUwXm2qw1G5tjpjugkmTB0p4Hj5fAXl96PYmJQCIgvu9k8J2GmVpJp6JmngSIziQPgUsJvnkeGoeN8PuHcnFTkwTC3DqElRb1gfXODKQxCpXU69S1fffEVd+/vGLuRrh1S/UAYhnkgK2s2V1uGacQFT900CCVfjsoKoSU2OKRIVWqTGUJCvOKiT87DeUJNCsuMrATWW2ImqOsFmVYcdydae6ZeF2zXV9zd3aV2qPWcL2f6ticvMjKhMUKxWTXgoTv3NGqFQaV3GAQxBMZuZBg7ok5G5ufdHfm9I78VBG3RSmJETqGLdI2SgiLLKQoDISUllZTEaDmddjw+PCBETBNvUhJCTKo27wgRBCqNR8d0wnq4f+SwP1CVa25vrxmnmcuQvtmECqAiqORgSPhwSXO9pLlZEEqPCzPNbcO76R3jvuXu6czcW0SUjOPI5CbK64ZNs0LWnnZ6Zh5Hcl2kcJed8KSswexn8JHJDUzjyOHyRFkV5E2BzFTyJdqZj/f33L7bYvIC6yK6znn9yed8+tlPCWi6boKYMv/HU1LPba9X6AxcnDhcnhjmC9JI8tyxWpU8fmzp2hNaiCStKWqGy4WxHSmqAhE08+hf2BYVVbnk8DzTdyPeGc7dkWZRk1mFdUkuo5AvVKGkgcdoYhYIc6SfeuwwkeUGlQv6uac/HBN8t8h5+/odt1dv+PDtA/15RAbF0/1fFoH9KDYB4h95EWnizvs0cTXPI6fDnqaqWS4XtBfB+XSkay9YO5HnGUVu8MFxeH7meXzm0vesr2/4l3nJdrNFSsnDw0e+/OK3fPHbL4h2oqkXdJcW5yPaGGzf0Q1D6jsTsT7d49Qf2XZKpFFjKdEp3I9UaXoLJXHB0Y090zgCEe8uhDARvEAKjVcz++6Jw+VMsVTcXr+hymr2lz0+pmz+0PVcTheuzRWLskFL2NQ1GQY3JkIRMh2DpZYp4DRMKT8hFMop+tHSdgbta0yuKMrEuJ+7maEfqapFMgmHVNgq8lRUbC8XDvtnTsc9WSZQIm0YSmqInmmaCVKSKfUDRZkIx8OJsii53l6hMomfZpQBYWLKKmiB0IoQBQSoFwvWVxtEJhkZiUWkUBkbu+Hq9Q3dw4XJdUgnkFnOPO2pZE6pEwx0Dkf6S8eEBTPj3AxCYuOEDeAm+Oa7jqwGmUt0kbEstvzslw333z9yPO7weLIqw9cKURjevP2cz3/yC8pqwfPuzDR6ikyhpOLh/o7DYcev8l+y3JT004nLcCRvFHmpybXi3btX+FHibZKIZjrDyRk3OvrLxKJZYpRBqIgSGWMfmPojdx8e2e+OFPmS2U5EEjlZyowyz1N4SQR0lmMnASoichj7kafnJ54fn3nz5jWrq1XKq/hIZnKCC+R5ztu/+RwjS/79v/sNZVNydXv1F5ffj2ITiC+xXREF0XvaS4+b09hv3/c4a1ksFrThzOWSfmRGU1Ul1s2cjhdc62ESPD7vOOxPXG9vWDULLm3Lb37zD3z77VeM7cCiLtA63elNniGNTkUWwLrEAID0fQ6AFMQ/XoZEMsWaTCNkCg1HAjEGnE/3OBEDMSacN0KhDfS25dJ2RC149eoN1+s13WlEZxqpJNFFgg20pzNNXmFQTA5sa5FKUKgCGWUi12QKU+eoLMN1GtvPWG+ZbCCPNVJGiiyh00VmGHpH2yWWQFnKJEWdHcGDqTIEgbHvGNuOeRiR6MRaCCk0FQMvANeAFgKdVy8jvOmUsF6vqJfJf3i6nNC5QGVpChQpUFJBlIzWk2UFRVURiEz+BfhSllSrnPXtNe1Nx6F9JA6euiwY5hkdFcNlIFtUNPUCPwyMncXbCesHZFRkQmCqDG8th9Oe2HlefXpLVS958/ZT1r+84u+zX9P/rmO1Mphc4YqS7etX/PwXf02zWHNpB5z1aKHIlKbIDHYaeLj7wLt31yxWN0xjhw9zmhisc6SDXBW8ur1BWY0dJmSU7B+esf2cItwzKJNGrTNTE5zmeDhyf/fE5TCib2qMMSitEECR5/hQMbg+VfeRGBJ0VQnJNMw8PD5y3B1YrVfEA1SLguur6yTCiYJpmNDXmsViwe6wY+odr67f/MX196PYBJyzPD08IFC0l479/kSRVdR1g599AojESNu1iSqT50zTyH7XMU0j59MJ2zqykBOtoxvP/O7v/4G77z9yupw5nQ+ARwmFsx6lNGVdp+gxkJUFVVO9WH4UPiS6LJLUrRBpo0p1BpWKhS9OgRhCApA4h7VzGmzSKa4M4INjGid8nFmtNzTrimHu2J9ORFIUuTIlVVFy2O1TRgHP1PWEaaahRkSRUGiix+uAziPFyrBYVoQ20vUp2nt9u+b161s2qyVOBHbPF3anC1IqyqLEu0Df9S/Ico2dDX72zMNAcA6FQISYNmMXk6UoBKQ2aJk+X/WCqlJoIiCUou87zpcW5x1FnmHxKNImgU+BFonGmJLMpOq/jAqkQAiF0IZ6sWGx7WgfeqapQylDVVRMdmbqJ6Kv2G6vsO2Ry/EZrxw2OmRIOK2qNEgvmCbP/e6JWAjefv5Trm5fs6zWXH9yw4fHGlOBlZ719pZPP/sFdbPGucg8WvCROi/RURCnGTE72v2e5/uPXN2UBDcT/EyMDvEygaeEZNksGQ+Rw9MePwd+9+vfcX295XZzS10uE8HKKspsSVEYLmJAoXHWMfU9MkCYHUPXQ5nixhrNZJOFSgvzg1mq6wbKskRsQCLZPx+wU03zSUWeJZRd33Yc9nvatuV4PnHaX/j/3sn+48ePYhOY5pmvv/6auqg5HE7sdkeWiw2r5Zi0TXlJVVdk2mC0oW8vtOfE0Ld2Zp5m5mHGzTNKapTSPH74yDdffk1W5CzXC3xImrMhWPLKsL3aghBY7yirkuWyQaokuwjxBcUkJIhUgRU+FRulVi9KquT/s94SXapaB+eAiBAJXhqDJwgBIqTjY6nxYeJ5d+LxYU8mKqKAsiqRFXTdmWFsWC5LwOKHSHtuCSEyYwnRMsoRNw9s9AKZC+qyZKWvKMuCd5/dcn29xLmJ0+nMw/0TrXOsr7ZIkRwMve8hQJmXnPZHLqc2Jd2iIDcFUgSICQ2uTZra01qhMkW0aWZCaUOhaxCSbhiYx5YoRNpIjUitRC3TqSgk5LpEURYNRpfgFFqa1LWhwAaJKRasb17jLpF9vGfuB3Se008jdvSIYLjavOX0PDHbVGzLdZEoiTYi4kxWSMqFQhwDs7NkZU2+qFPPXXpCFpGloljVvP30c66uX+O8Zxpn3OwwSOosR8VIfzjS7fe0ux1PHz/yyafXTH3PPIypyGktORqFRsbET3Snj8RZ8v1X37FpVly9umG7vaVzM14ENAXegoiapl5wkGe685nz85FFsUCvlxgtU1K2qIk+BeGEEMze051HpJD89Kc/ZWgHxn7ADZaJmd3DnuxtTplXTOPMt19/w+HQst1uiU7yuHv6i+vvR7EJBB/oLi11UWNMRlM31FVJDBFrLafzGSklptacj2eenp6JwWOyZBaSUpKbDD9aRAxkWUadV5Q6SRuaekHbXzi0F5p1zdXNNSrXjNNAO3QYIajqMinDdVKViTSEj5Av3LuXOoCSChHjD1cYO82JhWcTiFRKSfABHx0xeFACYxQiCpwfabvI6XRkt9vx7nXD1fUVhcmZ+oTHRltMXVCvctxZM84TCIhSEIVnljOEmVJImnrBqmhYNDdkJkPnmtPpyKk9cOlHxs7SzQNFVbGsF6mvnOUYbRi7kQ/f33Han6nLijAHMp0T4pwgnyr+AGmVCaZAVJEYPVLlFHVNXtY8PbcIoakXSxarBpV55rkHPDIAQaaRVR/IdYEMGmHThqNDQbCa/jwzWVhfv2JhVogoef/VV8lYJDVtNyLJ2a7e8iH/SAwWpYuUNgVCnHDTmMazw8Tt7ZarTz5jtV0TVeR4OXPojxSrksVVxed/9XNev/2UiGKeZ7z1iBBREbAzMUR2H99zeXpEe0cYRlw3MLVDOvKH9E6tyclkybnv+fDdA1ns2NRb4iyZOo/0GblsWN8sGIPj3J84dzus8yyaNXV1ZGh7Hr//SJwD4dM3eLdiuV4l65FP9O1xGJhbR3CCsqypshwZJXM/kQlDHjMOT3tUOm+hTc779x+xNvKrX/0Lnq8P/Pa3v/uL6+9HsQlonUZCsyxjvcrZbm5o6oZpdIzj/CKGdDx1jzw83GOtTYEMpfA6pQuDSLv/PPZYPXN1dUu9WGK9Q4aIlmmYY7vd8urNG9q5Z3RpTFUbQ1mWGGMQUhPFTBAvgE9eaEAvgxhCiJdjsXzJiE9M48A8vUSLpSAqnY660RKDI4hECg7R0o2W8+XENFmkkly9vuJ4OHJod5gcRD7jdEexUvSTYph6go6YTGPqCoqAWUK1rrl+fUXZrLGj4Hg8cjiOmDww2ZFuckyWNEpqLVopMp2i2GM38u037/nw7Qf8HLALm+YkZJaivS9MvkwrjEldkRACmTFpMzYGnRvWmyvuH8409Yrr6xuKOkNngfN5R9ceUzfCFAgvyRQYmREsKG/ItCaMkqmLnJ4Hpi6wvL7FlJHy6RH1mONtB1FzvnSEoCnMiizPKevE0vMibb7BOsLsidYzzyPvPv05b372E8rKcBmO3D1/xGvL3/zdr1AaPvv5XxF0wenUIr0nOk+wluPDI6M21FnOx6++wnUdb7dbGq1x/YCwEeFgamc222vqLCnXdvGRqU9uylp6mmLN1DvwhnmAq9dbMgK7w5n2bGkWFavtgvP+iLQwHUe+u3zF+XTg5vUtbz/9lOVyzdBPHPZnToc9XdsiZMAoaPueaZjARbTXqDlp8LpLS3s+UzcrhkuPyUtev35NZiratuNL/v7Pr7//f5f7n38opWiaBTFKmrpODvYomfAEH/EETqcLw9DhfaCpK0JwCCmo64rgHX0YcXbGzjPBetrjkVh7qqahzHLO7YngPVmekxcFre1wMQWL8iIjL7OEelIvaOtkLE88mBh/mMZSL5uDMQZvk+6873vmOckhpICoFDLTyQbjJwgWQUChmLwlBEu9SECTrNDMYWRiYrFsiJmldT1RG1zWpBfbCGQuWV9taK5LspVgcVNSrSqmKXJqWx6fntDK88m7K/LG0D7smaylaeqXxKWnyAp2uz1/+OIPfP/19wQLi3KBmzymzDEqZ/BtanooTZFlIAJTGEEapBQYk/RmWhpub1/x/v2ePE8pxKwySGVxbmBoL8TgiHhUFFRVQ1U2uDkynEYmCTFooEbaDCMVebkgzBO6KVm/uUVkkoeHB4ZxYuo90yXVJcpVRr1c0A093ThDEMjID+3NvDA4P7E7PTE+P3D/+MD1zZbrN6/wLiJUQTeMeB9fXseZy+nMH774gutmye16w/7xkUIrtldXRA22H5EhoKLitDvx+pO3rFc3CCuwc2S9fk3uKuZuJFcV7WFk6CzbmOHn5LVsqm26ymhHYQxVXjIXI3kh+O7jB86XU7IuScVhf6FvR07HlsPugPcz26vlH6fqUou0H5EuoBBc3W6JOjINE0oOLJdrsqJM2vRpoqrrv7j+fhSbAEBV1mipWS5XWDuzez5wPvdY61kvVhhTJFmGktRVkUCTpCGZNNGXUdcNVRHBQZnnaJUGKLx1ECLRB/qhpx97gMRmE5CXOVJK5mlO5GMhUndAvLQsQ/p1AoiIxKdXKhFwBss8TVjr0EIley2R4D1aRcoyQ6Kw40QIHm0Uq/USmoK8yNK7rIjU65JmU0EOo28RokDmC4IMiEwjC021rLi+vSZbQbnWOALd0CXvgQChJGVdIk36v/sQkq9PJqHp7nnHh5cJv/OpZVGvyIryxbxTIAQJjS4lRhuMMVg7QAStJEoJjDFkWYZSmuWqRmvNOE64EMle5gGyoqSsa+ww4CdPdJGmlBRZTn/peTg8YeeZulzx9u1fsaiXuJhRVDUTgXLZ8OrdW5aLiv1xjw2erh05HFrGfiAzktVqgdQaOzlikGTCEXEYJXnePfPc9ci65nA5E0SkWZV8+dWXLJdbvFQsV6/ItEbGQHSO7nxiaC9YrTkdArkQvH71lvXVmjHOeA3t0KNRjO3E5dgyr7ccH458980dVb7manXD189fIaLifGp5uHvmzac/53zsCBrWqyuidOx37+m8AxR5lmOFw40zwQe00ljr6Ic9Y2sJllSzcAlIElykMBlWObpLz0JWrOolIpcEHTmfLoyj4/r2FUplfPfdt/S9pe26v7j2fhSbQIwByYySkefd++QO9BGVJZdfVCOeSNnkxBcOXV6UBBfo+wE7C0JQqCxPoo+sSGO+RKIW2NJT5Dk3mytiYXm+PCC1QheSXNUUeYn3QIzk0hKMQknBODmyrEKqRLlRUjBPHbnQGAzLumJA4y4TMUQqvaTOF/iyZ4gHpEgSlHlK1WSjEx9go0rGy4wXLTITFLljUa+SVmtwRF8THPT9Dqd7rm5vaVYlq09yNm8aur7jvBsRIWJPA67vOD7eI7XgFz/7KZvFNVerwOX4HewdrzfXyIPhD7/+mufjCW9zmkXJ7dtXLFZL7GQpljWNzHFyj9QzOldYMWNVRIoCHSsMJZleoERNntX84ctv+d0Xv2a1XvPqsy3Cllg/IYXg9ae/QGJwQ+Dp7pmPpw719ERVVQwDZKamWW5BSMq8QomUmzdSIA2cp0syNl1rFtGgN5Y+7rla3nBV58whcJlaNosFtswJ48TC1LjB8rvffMk0e6p1QzCR1asVLtzzsD+zOys+CZ+wLv6OOtSI2dEET/mmpJo2xG6mtJ63t7esmzXWRVplOM6QhS0LXeAzybSv+DBNKF9Rc01hM2qluDFLTLHm4/TA/vsHnt685/NFyf5wwMYlN9c32Hbg2999yTdffmBRLZh2nmknIIuIFprbHGs8uo5cup5uPqapy7ikVA2lMFwmQUHNsrgizzb0sUUZSe8OjP0z+VXFYtHQDXvuL4/c3f3l+M6PYhMgRuZpenmnDUgZ07uPNngfETJSVjlVVeJcYOrTrhgV6b7uI/0wMl96hHjRgJuMZrlgvd5Sr2sa3SDbPbpQBOHTnzOSTKWI8Q//lRAQgPeRrMgQQiN1nmCRMem3tPxjFLmjOydQRSYNi2pJVS/omNLAi5AM/cTxcKTQOVebG/IyAz/RhYEoLFluaJomfUxrsbNFS0WM4MKAyQ2bqw2rmzXVoqTtWz58/wHnAqvFku5w4cP9B46HPWVTMw2W7jxw3J257C/cVFukFewf9uzu9kQlWTQrZKlYbdesNmvGYaDIEs23KDOEjphMEWVqdWY6JzMFWmVJ7iI1p9OZ+/s7pCSl6vyMc5K276iriryqWZZrtCxQqua7r7/lckmx2xAytEpjyNpIiqwkOM3UD0z2wjxPWB8wuWZzs0Vnjs3Ngqg811c3PH/suHu4J1sYskrjXIasalyfOhohWOZxoIkli0XNoi7xrmd2FybrOJ8luL/i1c0bQjcQpomb7SvKzLF7f8/C5txmW0w0XOyExHLuBxSGQi+YBbhRooqc7WLFvBq5+/17um6PdoJ6uSCXmvVmTZgtY99TVxXepQ7S69u3fPj995yeWwY5IUdNpSu8mBgOLeOppdkuKcuCfugZxz4xC71DhYAdRmw3oYLETp7OdTz3O5rrmqpuGP3Ex7sPXLGlWpQ0Y4E+/MhbhEJKYhT0w0iWpbDPHC1KpsUskCiVkFzOB0JMs+ghJBeA1pKizJEucmkvtIeOpmlYbTcsFguaZY0VljFMqFyQ5UUScsZ0z5dCIF4CR94n628A1qsSFxOLUAuFj5FMG8TLlN/uec/++Zmpn6iqBmMyloslrm/pJ42IOrXVZoELIEVGkdUM3jEMjkJrlMwo6wY3Wy6ngfP5jBCRpl6yXm3xBNq243H3zPb6mk8/+wmr1YYYIkZo3p8ufPj+Ll0FSpGQZceO77/5nsul5fXilsvlzMePHzidTzSbFXVTQp7oyJkxaCmJbkryVinIsgQ39c4TZaLkJpS7T/URQrqrTwO/+he/wmQ5zjuG44FARDYN49iTyZxFVfDm9S2FMczTibEfIRq00czzlGbrhaXIG7LcoCfP7e0rQvAMw4W6qtlclVxfXeNc/ToMKwAAEPNJREFUoGsnvvv+jv3lyN/9/O9wYubu7j0aOO0P1KakKAqc9dRVzXqzQeeafj4nfLyAth3wPrLebLFZhwqB7fWCvNHE2dHYnLfLt0gv0H3L+bjDnk8oWVBXNbmMrG/XLMsa24/Jn3k+Mu5brhdbRIiUJucnn7yDquDh7oHXP/0EpGDsBz59+46f/eRzvv/yDxwe9uAFi6qknaf0OTwVZKUmVxXCe5QPiVjvX+YJjhfG80iYZ9r2QOvP7PIDVs1sr7as12sO5z1Pj8+8efua66sbYoAHdn92/f0oNgFiUmkfTyf6rk8MfimJMWK0BiRd1xF8R4wJ7qmkwjn7g2q6WC/xRUU/Dsw2peBW2zV5UbzwAGbqukYWKgV/ROLaS1S6T8sIUqYeuXVIrVAyeemlNmilETGiTIYWkbFruZwuXE4X5nHG28jpcKYqF2iZU5llAmOGiPIZ3guk1TTrNWMecPMjUaqUirQRITRZXqSIaaYoyho7wf5wQGaa9WbDq+s3bJZbdvs9Jks69/3uhJ8jN7dbrlc36Gh4fnxg/3AgAl3bczfes98fmKaRbM4JMQWBhrGjHzKKLGcYW+x4JgT3Ep5K7dkoNdqA0hKFTJRk17E/PBFD4Cc//xxtDL//6kt2px2bqw0QUVKgpGQYeupiwc3tDX4ueX56pu8s0zRi3UxTbyhNsqLkeU7dXFEvMoSA59095+6Rrus4Hk9k+ZIwOo77nss4MvQzWamwc8C6GSVSnWa5XJDlOYtlRVEUzHF6EX1GlILZznTDwDAlqelis6Re19RTzXK7IB5mZCnZNhvmg2Te3aevXd2gtCE3ms/evAMf+Le//ZL3336PCFCZAo0kE4pV3dBfOlbLiv605/CkuX59SykzMqG42mxpqoYxa1mUDULDsDth54lx6Dnu92RTj5sn6ipHIdAJipGSlHYiOIsbLNFBzCLTNDOOA7dvb1luF3z9/mvev3/Pz3/+c969e8e/5t/82eX3o9gEvA+pJ49kto7FIifLc2Y7Y60FBOM44Wf34gvI4MV4E2IAEVDGIHyi5FSLmutX19SLBd0wEG1A5IJls4RcvGi/0qRf8rcB8qUFGCXjMLNY1kgUJivQWY7JMoLVaAkKx9P7Dwxtj58cePCz4/7ugfOxpVkXVKtUQR/mme40EZxn3nhyWVEYC1bgJEyTYxxcKrrlFZvrG4oq/d370zMmK3n32Wf84q9/yWq15Muvvua3v/kNn3/6eSq0dRPrZsPV6oZVs0Y6RXvssb2jqCqOhxPP0w5rA0opnHc4NyExWNfR94oQctr+SLQ9RpMy6ioy2wBCoLSmLAsUiu7S0Z56jscDWhUvnsTI0+MdD4dnlusVSieV9zB1PHx45vbqLa9vXyfEW16gZEk/9AxDx+GwR9Iw9JGqKlmuCwSS29tXbK9WlDU8PX/PPE+YzFPkNevVLd8+PPDv/u1v+Zd/+9e8unrD+fgEUjNeOuqmZLleoouM4CyjG18yFvyQTdnvDzw8PbOqCqSOdOHM8bLHVIrh4nk8PiKloJtbzu2ZaZoQuQPhaRZLcpUx9Bd294lPuc2bJKiZLFoo1ouC333zFVs34gr48F2P1pqr1Ya+bTnsnmlPJ0xmuL69IisNLp8ZbIs0islN+ClNbS7WCzQCmSVk++pqjQySqTuCTk7JLDMYo4kC6qZiU625e77j6emRcRy5uvrRZwcC3kXqakFdw6JZYzLNMAz0Xc84DkmqSOqQWDfjfCL9ai2xzqfhHGC5XbLcrFltNvTDwMPzA3ld8tO/+QnNYokTDhdnQgwEEfAxvMwCpMp/DIFxmNmsDRJFXTWUZY3RJh1fu5bT8cTTwxPzkJJrWigyXdBfeu7fP1LWGa8/uWWzXeMnwdw6pnmmPY1MQ0BiEBjm0eHmtANdLi15keoDWSaRaH7y+c9YbTY0yyXtpef3X/yBr7/5lv1+hwiK7WrNsl4QPYztxG7eM3WO0+6MFhnbxQYpI/vLjoiibmp0qZEyImVASokPE103Mo4tRoZk3c1MgnZ6j1AGEMnLh+Bw3PHw8RlvBU2dM40j04susCiyF9lGhjGG4+6Z3e6Z9fLqBcuegjKL5Yr1ZsmlPXM+jlzOZ+SqZpoll7NFSIeUIGRgvVyjTWrFznNE6YKr67eYP3zJx+8feffJWz797DadzPoLbX+hKkrKKgepGOxMcBEtNbOzjNZiDJzPLfvjkWkwPDyPBD3hfMtS5zTLgmk38t3993TzTDdc6LuWUxco6i2b7Q33Hz7SHg5EFzBCMo8zwit0BOc8pSwI1nLaH1m82XDeHfjSziglyZTmm9//ASkFy6sN2aZmuV7ySQPHfg95RBhJNAo8ZKrACInIDeVqQX1TofOaS2sRyiOiZjYdQsnUMicwDAN5llOWBd3Qsgmbv7j+fhSbgBAKERR5nqF1QmopkQSSWqk0gefSXADA7CcgpaW0MYQYsZMlelisEiTE+8Du6YGP93e8evf6hdJbgE8gEoJNC1/K1D58af/Z2eOsQ7zISoq8YlEtiRGmbuTx/oGvf/8Fp/0zZZaoszG8iDRDfJl+HHm62+OniJISFXMMguEy0Z76/7e9s4mN5Kji+O919ed0z4ztGe/am0TJJsolJ1hFUQ5RjkByWbjlRA5IXECCA4egXHIFCQ5ICAlEpIAQuQAiFyQ+hMSJQED5Xm0SNpuwX/baHns8Pf3dxaF6E2tZKxui0B65f9Zoeqr78C/XzOuq16/ew3V9Aj8iSTLzVEIUSZo1j/hCHFvo+SFrq3eS5jmbm1ucO3eejY0NgsBndXSCujbTv0F/id3tXSbbE0SE/WBmHH2Ow8pwibAfgoZ5nBIN+yhfYTnSJMaEvKhMokxdYCmFJSZUVTd/N0Kky7JAa00cT5nPY/rhElG/h6UgzVJWV8eMTowYDgeEgWe2MbsOa+snGY+WEYEkSUmSOSIuw0FEP4ooMgiCgOFgYJaAVkZVVcxmc2bxLkm2DZKYACVbEQ2GDLwl4jzm4qUL7O/OmPRNhd88SSmLglyZ3APKNv4cTwVYKPKiIEli6gqqGqb7MVub+2TFFDcCLQlpL2T1jvtAXLav7JCWOShIkjnXNrYYLGWcWr+Ta+9tUNcFK8tL1HFBujOj5zh42ma2N0Xrin4QYgU+Ums8ZZPN57z/7gWzA/P6LqdOncL1PErfpvDBd/sMhhaF5KRVSlYVVAJiu9QaCBy85T5RMCSvLILxHrlboLDJa5OA1/d9qrJib7aHbSt6YY8kTZtdr7fmSBgBZSlTiUWEsjCVaF0cisKkYh4Oh6A18Xxm1n6WKbCZFSYrj9iCzo0Ty7KFoszJsubZqBKWRyPCXgS2hdRmeVHfCAhCN84uExVYFBXUUBc1ru2iawAhTzOuXbrKxbcvcPm993EsCJSDqxyquiKbZ5SlJvRDU20ordi+st0EH0EU9KEUJtsTot4Qx3IpHVMk1HEcxqsnWBoNGC4PcBzBthy2d3fY3p6QxClRrw9jqKnohT69XkgYmOCUIk0RDb7tUmc1vjgo26YX9BiPxszjhLqa0I/64EEuJoVYmeXUOPi+h+f69Dwbi5y6Nnn9LMtCKRulBKjNOr7IsR0zA7MsQSxIsoR4FhMOIwb9CC/wmc33KcuS8XiMUoo4njGdTplNY7KspigzqjInnhUE7jK1LtGVhWACeIJgRC/02dktub41MYZnOGLQH7C8NmLpxBL3XjnNhXffJJ3N8FwTFeo4iqoqyIqcQRjhhT6lpYnzOXGSIthIbSPaYne6y9bWNVAZoSgsleK7mnmZ4CsHXIFKNWXvXXQ9o0gzkv0ZWZwQDSJOnBwTqZCJfR2VlZSxecITx+bOnM4T6jpleX2MOwio0Mznc/zIZ7i8ZMrYRzaFrbGUg2dF6DJGZzlFVoJlivNUZY0ENlbgkFFT2xa95QGWk+Ngk81i0jLBdmwcxzH7Wy1TGBetse0jbgREBMfxqOqSIkuxxUIcyJOcPMlYWTtBv99nY/Mq+/E+okzK5SRLyYuUoBfg9Twc38OybOI4QZSF47oM3WXW1tdRro22NGIpc4+rQWsLTVOqV5qCpZVGW2JqDCqXqqypioo0Trhy6Qpbm9vQlEirixLX90FZJPspRVHieQG22GRFRZal1NQEvYBoFOF5AXs7U3Z3psTzFOWYPIhBGLIyWmK40md/f8LedA/RwnQnhsoicD36awPK0QgUVHXBpUuXqIqC0XDZbBN2zOaRJE1RTaBP2AtxHbPbzbIsbMcGVZNr8xi2rsyP3fcjeq5D4NnUuam1qAUcbDzfR4vpS56V5EXxQcKRPM+JImm8/Cl9q49t28znMZOdPWzLYzjso0tNmiUURcHW1hZVtcXJk2P6g8hspaamyAuTxERnKFtQyiLLY+MTEossT2G6xyuT1widIXffc4pTa+vsT69z+fKEeVMPwfEc45DVNZZyCHp9tAhlJSjLxVa+yaxca+IkIU4TlFdCVuP5NbZnszubEBQ+buQS2DZhFrK0tMzKQFMUinhvnyovcB2HMOohRU0V58yuTSiKkrDXw/V9qnxKMBwgoU00HFI5mtl0jzRN0VpTUrMyGpEGNWmVYSnItTYG2FY42txgxDJ+LGUrEMuUMC9zXN81laqVi5XauOI1UaiuqWGQ1Mbp7pr/yaG/vxt3wTYRketADGy1reUTMGax9cPi92HR9cOn24e7tdarNzceCSMAICIvaa0fbFvH/8qi64fF78Oi64d2+nD4QqGjo+NY0BmBjo5jzlEyAj9uW8AnZNH1w+L3YdH1Qwt9ODI+gY6OjnY4SjOBjo6OFmjdCIjIF0TkvIi8IyJPta3ndhGRiyLymoi8LCIvNW0rIvIHEXm7eT88VrMFRORZEdkUkdcPtN1Ssxh+0IzLqyJypj3lH2i9lf5nRORyMw4vi8jjB859u9F/XkQ+347qDxGRu0TkzyLypoi8ISLfaNrbHQPdJM1s4wUo4F/AvYALvAI80Kamj6H9IjC+qe27wFPN8VPAd9rWeZO+R4EzwOsfpRlTT/J3mLjKh4EXj6j+Z4Bv3eLaB5rvkwecbr5nqmX968CZ5rgPvNXobHUM2p4JPAS8o7W+oLXOgeeBsy1r+iScBZ5rjp8Dvtiilv9Ca/0X4OZ6VIdpPgv8TBv+Ciw1Jehb4xD9h3EWeF5rnWmt38UUyH3oUxN3G2itr2qt/9kc7wPngDtoeQzaNgJ3AP8+8PlS07YIaOD3IvIPEflq03ZSf1iG/Rpwsh1pH4vDNC/S2Hy9mS4/e2AJdqT1i8g9wGeBF2l5DNo2AovMI1rrM8BjwNdE5NGDJ7WZzy3Uo5dF1Az8CLgP+AxwFfheu3I+GhGJgF8B39RaTw+ea2MM2jYCl4G7Dny+s2k78mitLzfvm8BvMFPNjRvTteZ9sz2Ft81hmhdibLTWG1rrSmtdAz/hwyn/kdQvIg7GAPxCa/3rprnVMWjbCPwduF9ETouICzwBvNCypo9EREIR6d84Bj4HvI7R/mRz2ZPAb9tR+LE4TPMLwJcbD/XDwN6BKeuR4aY18pcw4wBG/xMi4onIaeB+4G//b30HEREBfgqc01p//8CpdsegTW/pAQ/oWxjv7dNt67lNzfdiPM+vAG/c0A2MgD8BbwN/BFba1nqT7l9ipswFZn35lcM0YzzSP2zG5TXgwSOq/+eNvlebH836geufbvSfBx47AvofwUz1XwVebl6Ptz0GXcRgR8cxp+3lQEdHR8t0RqCj45jTGYGOjmNOZwQ6Oo45nRHo6DjmdEago+OY0xmBjo5jTmcEOjqOOf8BCfyDzvyUDsIAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc0f001ed68>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -1133,10 +1131,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Model: \"vgg16\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "input_1 (InputLayer)         (None, 224, 224, 3)       0         \n",
+      "input_1 (InputLayer)         [(None, 224, 224, 3)]     0         \n",
       "_________________________________________________________________\n",
       "block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      \n",
       "_________________________________________________________________\n",
@@ -1226,7 +1225,7 @@
     {
      "data": {
       "text/plain": [
-       "<tf.Tensor 'block5_pool/MaxPool:0' shape=(?, 7, 7, 512) dtype=float32>"
+       "<tf.Tensor 'block5_pool/Identity:0' shape=(None, 7, 7, 512) dtype=float32>"
       ]
      },
      "execution_count": 40,
@@ -1517,56 +1516,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "Train for 100 steps, validate for 26.5 steps\n",
       "Epoch 1/20\n",
-      "100/100 [==============================] - 27s 265ms/step - loss: 1.1149 - categorical_accuracy: 0.4407 - val_loss: 0.8443 - val_categorical_accuracy: 0.6642\n",
+      "100/100 [==============================] - 32s 322ms/step - loss: 1.1149 - categorical_accuracy: 0.4585 - val_loss: 0.8945 - val_categorical_accuracy: 0.5604\n",
       "Epoch 2/20\n",
-      "100/100 [==============================] - 22s 219ms/step - loss: 0.9529 - categorical_accuracy: 0.5500 - val_loss: 0.7798 - val_categorical_accuracy: 0.6377\n",
+      "100/100 [==============================] - 31s 309ms/step - loss: 0.9385 - categorical_accuracy: 0.5432 - val_loss: 0.7380 - val_categorical_accuracy: 0.7717\n",
       "Epoch 3/20\n",
-      "100/100 [==============================] - 24s 238ms/step - loss: 0.8422 - categorical_accuracy: 0.6164 - val_loss: 0.6778 - val_categorical_accuracy: 0.7566\n",
+      "100/100 [==============================] - 29s 285ms/step - loss: 0.8408 - categorical_accuracy: 0.6186 - val_loss: 0.6924 - val_categorical_accuracy: 0.7321\n",
       "Epoch 4/20\n",
-      "100/100 [==============================] - 22s 218ms/step - loss: 0.7591 - categorical_accuracy: 0.6635 - val_loss: 0.6562 - val_categorical_accuracy: 0.7396\n",
+      "100/100 [==============================] - 30s 299ms/step - loss: 0.7855 - categorical_accuracy: 0.6432 - val_loss: 0.6994 - val_categorical_accuracy: 0.7057\n",
       "Epoch 5/20\n",
-      "100/100 [==============================] - 23s 226ms/step - loss: 0.7246 - categorical_accuracy: 0.6816 - val_loss: 0.5812 - val_categorical_accuracy: 0.7943\n",
+      "100/100 [==============================] - 29s 294ms/step - loss: 0.7128 - categorical_accuracy: 0.6879 - val_loss: 0.7109 - val_categorical_accuracy: 0.6698\n",
       "Epoch 6/20\n",
-      "100/100 [==============================] - 23s 226ms/step - loss: 0.6968 - categorical_accuracy: 0.6960 - val_loss: 0.5351 - val_categorical_accuracy: 0.8264\n",
+      "100/100 [==============================] - 29s 286ms/step - loss: 0.6945 - categorical_accuracy: 0.7015 - val_loss: 0.6150 - val_categorical_accuracy: 0.7604\n",
       "Epoch 7/20\n",
-      "100/100 [==============================] - 22s 220ms/step - loss: 0.6622 - categorical_accuracy: 0.7205 - val_loss: 0.5208 - val_categorical_accuracy: 0.8340\n",
+      "100/100 [==============================] - 28s 282ms/step - loss: 0.6910 - categorical_accuracy: 0.7060 - val_loss: 0.6316 - val_categorical_accuracy: 0.7321\n",
       "Epoch 8/20\n",
-      "100/100 [==============================] - 22s 218ms/step - loss: 0.6430 - categorical_accuracy: 0.7307 - val_loss: 0.5173 - val_categorical_accuracy: 0.8321\n",
+      "100/100 [==============================] - 28s 284ms/step - loss: 0.6269 - categorical_accuracy: 0.7382 - val_loss: 0.5828 - val_categorical_accuracy: 0.7868\n",
       "Epoch 9/20\n",
-      "100/100 [==============================] - 23s 232ms/step - loss: 0.6026 - categorical_accuracy: 0.7515 - val_loss: 0.5157 - val_categorical_accuracy: 0.8170\n",
+      "100/100 [==============================] - 30s 300ms/step - loss: 0.6180 - categorical_accuracy: 0.7362 - val_loss: 0.6337 - val_categorical_accuracy: 0.7377\n",
       "Epoch 10/20\n",
-      "100/100 [==============================] - 22s 221ms/step - loss: 0.5615 - categorical_accuracy: 0.7782 - val_loss: 0.5412 - val_categorical_accuracy: 0.7792\n",
+      "100/100 [==============================] - 30s 297ms/step - loss: 0.5823 - categorical_accuracy: 0.7568 - val_loss: 0.5569 - val_categorical_accuracy: 0.7868\n",
       "Epoch 11/20\n",
-      "100/100 [==============================] - 22s 220ms/step - loss: 0.5924 - categorical_accuracy: 0.7460 - val_loss: 0.4885 - val_categorical_accuracy: 0.8113\n",
+      "100/100 [==============================] - 30s 295ms/step - loss: 0.5969 - categorical_accuracy: 0.7455 - val_loss: 0.6298 - val_categorical_accuracy: 0.7340\n",
       "Epoch 12/20\n",
-      "100/100 [==============================] - 22s 223ms/step - loss: 0.5770 - categorical_accuracy: 0.7555 - val_loss: 0.4831 - val_categorical_accuracy: 0.8094\n",
+      "100/100 [==============================] - 29s 289ms/step - loss: 0.5516 - categorical_accuracy: 0.7704 - val_loss: 0.5804 - val_categorical_accuracy: 0.7566\n",
       "Epoch 13/20\n",
-      "100/100 [==============================] - 24s 236ms/step - loss: 0.5387 - categorical_accuracy: 0.7822 - val_loss: 0.5934 - val_categorical_accuracy: 0.7377\n",
+      "100/100 [==============================] - 30s 297ms/step - loss: 0.5514 - categorical_accuracy: 0.7770 - val_loss: 0.5879 - val_categorical_accuracy: 0.7453\n",
       "Epoch 14/20\n",
-      "100/100 [==============================] - 23s 234ms/step - loss: 0.5414 - categorical_accuracy: 0.7745 - val_loss: 0.5325 - val_categorical_accuracy: 0.7660\n",
+      "100/100 [==============================] - 33s 326ms/step - loss: 0.5239 - categorical_accuracy: 0.7830 - val_loss: 0.5448 - val_categorical_accuracy: 0.7849\n",
       "Epoch 15/20\n",
-      "100/100 [==============================] - 22s 223ms/step - loss: 0.5296 - categorical_accuracy: 0.7785 - val_loss: 0.4925 - val_categorical_accuracy: 0.7887\n",
+      "100/100 [==============================] - 32s 325ms/step - loss: 0.5367 - categorical_accuracy: 0.7760 - val_loss: 0.6596 - val_categorical_accuracy: 0.7226\n",
       "Epoch 16/20\n",
-      "100/100 [==============================] - 23s 226ms/step - loss: 0.5278 - categorical_accuracy: 0.7810 - val_loss: 0.5659 - val_categorical_accuracy: 0.7415\n",
+      "100/100 [==============================] - 28s 282ms/step - loss: 0.5155 - categorical_accuracy: 0.7860 - val_loss: 0.5385 - val_categorical_accuracy: 0.7755\n",
       "Epoch 17/20\n",
-      "100/100 [==============================] - 23s 228ms/step - loss: 0.4814 - categorical_accuracy: 0.8142 - val_loss: 0.6115 - val_categorical_accuracy: 0.7226\n",
+      "100/100 [==============================] - 29s 289ms/step - loss: 0.5058 - categorical_accuracy: 0.7889 - val_loss: 0.6200 - val_categorical_accuracy: 0.7340\n",
       "Epoch 18/20\n",
-      "100/100 [==============================] - 23s 228ms/step - loss: 0.4861 - categorical_accuracy: 0.8150 - val_loss: 0.4783 - val_categorical_accuracy: 0.8038\n",
+      "100/100 [==============================] - 28s 283ms/step - loss: 0.4925 - categorical_accuracy: 0.8030 - val_loss: 0.6469 - val_categorical_accuracy: 0.7151\n",
       "Epoch 19/20\n",
-      "100/100 [==============================] - 23s 226ms/step - loss: 0.4632 - categorical_accuracy: 0.8187 - val_loss: 0.5041 - val_categorical_accuracy: 0.7868\n",
+      "100/100 [==============================] - 31s 312ms/step - loss: 0.4681 - categorical_accuracy: 0.8145 - val_loss: 0.7350 - val_categorical_accuracy: 0.6906\n",
       "Epoch 20/20\n",
-      "100/100 [==============================] - 22s 224ms/step - loss: 0.4987 - categorical_accuracy: 0.7935 - val_loss: 0.5093 - val_categorical_accuracy: 0.7868\n"
+      "100/100 [==============================] - 31s 307ms/step - loss: 0.4743 - categorical_accuracy: 0.8045 - val_loss: 0.5995 - val_categorical_accuracy: 0.7377\n"
      ]
     }
    ],
    "source": [
-    "history = new_model.fit_generator(generator=generator_train,\n",
-    "                                  epochs=epochs,\n",
-    "                                  steps_per_epoch=steps_per_epoch,\n",
-    "                                  class_weight=class_weight,\n",
-    "                                  validation_data=generator_test,\n",
-    "                                  validation_steps=steps_test)"
+    "history = new_model.fit(x=generator_train,\n",
+    "                        epochs=epochs,\n",
+    "                        steps_per_epoch=steps_per_epoch,\n",
+    "                        class_weight=class_weight,\n",
+    "                        validation_data=generator_test,\n",
+    "                        validation_steps=steps_test)"
    ]
   },
   {
@@ -1585,12 +1593,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc1179fd080>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1611,9 +1621,21 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "27/26 [==============================] - 4s 156ms/step - loss: 0.5888 - categorical_accuracy: 0.7377\n"
+     ]
+    }
+   ],
    "source": [
-    "result = new_model.evaluate_generator(generator_test, steps=steps_test)"
+    "result = new_model.evaluate(generator_test, steps=steps_test)"
    ]
   },
   {
@@ -1627,7 +1649,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test-set classification accuracy: 78.68%\n"
+      "Test-set classification accuracy: 73.77%\n"
      ]
     }
    ],
@@ -1651,9 +1673,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc1179c8860>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1664,9 +1686,9 @@
      "output_type": "stream",
      "text": [
       "Confusion matrix:\n",
-      "[[140   5   6]\n",
-      " [ 47  86   4]\n",
-      " [ 36  15 191]]\n",
+      "[[137   9   5]\n",
+      " [ 56  81   0]\n",
+      " [ 56  13 173]]\n",
       "(0) forky\n",
       "(1) knifey\n",
       "(2) spoony\n"
@@ -1812,56 +1834,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "Train for 100 steps, validate for 26.5 steps\n",
       "Epoch 1/20\n",
-      "100/100 [==============================] - 27s 273ms/step - loss: 0.4715 - categorical_accuracy: 0.8105 - val_loss: 0.5107 - val_categorical_accuracy: 0.7717\n",
+      "100/100 [==============================] - 34s 339ms/step - loss: 0.4605 - categorical_accuracy: 0.8211 - val_loss: 0.5776 - val_categorical_accuracy: 0.7566\n",
       "Epoch 2/20\n",
-      "100/100 [==============================] - 24s 241ms/step - loss: 0.4656 - categorical_accuracy: 0.8067 - val_loss: 0.5141 - val_categorical_accuracy: 0.7717\n",
+      "100/100 [==============================] - 38s 384ms/step - loss: 0.4683 - categorical_accuracy: 0.8175 - val_loss: 0.5600 - val_categorical_accuracy: 0.7604\n",
       "Epoch 3/20\n",
-      "100/100 [==============================] - 25s 252ms/step - loss: 0.4359 - categorical_accuracy: 0.8210 - val_loss: 0.5059 - val_categorical_accuracy: 0.7717\n",
+      "100/100 [==============================] - 36s 357ms/step - loss: 0.4643 - categorical_accuracy: 0.8095 - val_loss: 0.5748 - val_categorical_accuracy: 0.7528\n",
       "Epoch 4/20\n",
-      "100/100 [==============================] - 24s 237ms/step - loss: 0.4324 - categorical_accuracy: 0.8355 - val_loss: 0.5057 - val_categorical_accuracy: 0.7736\n",
+      "100/100 [==============================] - 37s 371ms/step - loss: 0.4368 - categorical_accuracy: 0.8236 - val_loss: 0.5613 - val_categorical_accuracy: 0.7604\n",
       "Epoch 5/20\n",
-      "100/100 [==============================] - 25s 248ms/step - loss: 0.4243 - categorical_accuracy: 0.8340 - val_loss: 0.4981 - val_categorical_accuracy: 0.7792\n",
+      "100/100 [==============================] - 37s 367ms/step - loss: 0.4140 - categorical_accuracy: 0.8317 - val_loss: 0.5490 - val_categorical_accuracy: 0.7642\n",
       "Epoch 6/20\n",
-      "100/100 [==============================] - 24s 241ms/step - loss: 0.4224 - categorical_accuracy: 0.8395 - val_loss: 0.5045 - val_categorical_accuracy: 0.7849\n",
+      "100/100 [==============================] - 44s 439ms/step - loss: 0.4456 - categorical_accuracy: 0.8155 - val_loss: 0.5488 - val_categorical_accuracy: 0.7660\n",
       "Epoch 7/20\n",
-      "100/100 [==============================] - 25s 251ms/step - loss: 0.4374 - categorical_accuracy: 0.8310 - val_loss: 0.4943 - val_categorical_accuracy: 0.7849\n",
+      "100/100 [==============================] - 45s 454ms/step - loss: 0.4318 - categorical_accuracy: 0.8352 - val_loss: 0.5505 - val_categorical_accuracy: 0.7660\n",
       "Epoch 8/20\n",
-      "100/100 [==============================] - 24s 238ms/step - loss: 0.4261 - categorical_accuracy: 0.8305 - val_loss: 0.4832 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 41s 409ms/step - loss: 0.4283 - categorical_accuracy: 0.8265 - val_loss: 0.5580 - val_categorical_accuracy: 0.7604\n",
       "Epoch 9/20\n",
-      "100/100 [==============================] - 25s 248ms/step - loss: 0.4408 - categorical_accuracy: 0.8215 - val_loss: 0.4927 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 43s 427ms/step - loss: 0.4197 - categorical_accuracy: 0.8392 - val_loss: 0.5496 - val_categorical_accuracy: 0.7679\n",
       "Epoch 10/20\n",
-      "100/100 [==============================] - 24s 243ms/step - loss: 0.3978 - categorical_accuracy: 0.8475 - val_loss: 0.4873 - val_categorical_accuracy: 0.7906\n",
+      "100/100 [==============================] - 43s 431ms/step - loss: 0.4138 - categorical_accuracy: 0.8312 - val_loss: 0.5535 - val_categorical_accuracy: 0.7679\n",
       "Epoch 11/20\n",
-      "100/100 [==============================] - 25s 248ms/step - loss: 0.3889 - categorical_accuracy: 0.8615 - val_loss: 0.4834 - val_categorical_accuracy: 0.7925\n",
+      "100/100 [==============================] - 38s 378ms/step - loss: 0.4373 - categorical_accuracy: 0.8332 - val_loss: 0.5449 - val_categorical_accuracy: 0.7679\n",
       "Epoch 12/20\n",
-      "100/100 [==============================] - 25s 246ms/step - loss: 0.4017 - categorical_accuracy: 0.8442 - val_loss: 0.4758 - val_categorical_accuracy: 0.7981\n",
+      "100/100 [==============================] - 25s 252ms/step - loss: 0.4046 - categorical_accuracy: 0.8470 - val_loss: 0.5396 - val_categorical_accuracy: 0.7698\n",
       "Epoch 13/20\n",
-      "100/100 [==============================] - 25s 249ms/step - loss: 0.3988 - categorical_accuracy: 0.8450 - val_loss: 0.4816 - val_categorical_accuracy: 0.7943\n",
+      "100/100 [==============================] - 23s 234ms/step - loss: 0.4014 - categorical_accuracy: 0.8442 - val_loss: 0.5400 - val_categorical_accuracy: 0.7717\n",
       "Epoch 14/20\n",
-      "100/100 [==============================] - 23s 232ms/step - loss: 0.4129 - categorical_accuracy: 0.8340 - val_loss: 0.4706 - val_categorical_accuracy: 0.8019\n",
+      "100/100 [==============================] - 24s 237ms/step - loss: 0.4141 - categorical_accuracy: 0.8365 - val_loss: 0.5473 - val_categorical_accuracy: 0.7679\n",
       "Epoch 15/20\n",
-      "100/100 [==============================] - 24s 238ms/step - loss: 0.3944 - categorical_accuracy: 0.8375 - val_loss: 0.4621 - val_categorical_accuracy: 0.8038\n",
+      "100/100 [==============================] - 23s 231ms/step - loss: 0.4117 - categorical_accuracy: 0.8307 - val_loss: 0.5436 - val_categorical_accuracy: 0.7698\n",
       "Epoch 16/20\n",
-      "100/100 [==============================] - 24s 238ms/step - loss: 0.4034 - categorical_accuracy: 0.8365 - val_loss: 0.4675 - val_categorical_accuracy: 0.8000\n",
+      "100/100 [==============================] - 23s 229ms/step - loss: 0.3826 - categorical_accuracy: 0.8472 - val_loss: 0.5549 - val_categorical_accuracy: 0.7623\n",
       "Epoch 17/20\n",
-      "100/100 [==============================] - 23s 230ms/step - loss: 0.3984 - categorical_accuracy: 0.8337 - val_loss: 0.4655 - val_categorical_accuracy: 0.8038\n",
+      "100/100 [==============================] - 23s 228ms/step - loss: 0.3979 - categorical_accuracy: 0.8442 - val_loss: 0.5402 - val_categorical_accuracy: 0.7698\n",
       "Epoch 18/20\n",
-      "100/100 [==============================] - 23s 225ms/step - loss: 0.3851 - categorical_accuracy: 0.8375 - val_loss: 0.4719 - val_categorical_accuracy: 0.8019\n",
+      "100/100 [==============================] - 24s 239ms/step - loss: 0.3941 - categorical_accuracy: 0.8447 - val_loss: 0.5313 - val_categorical_accuracy: 0.7774\n",
       "Epoch 19/20\n",
-      "100/100 [==============================] - 23s 230ms/step - loss: 0.4070 - categorical_accuracy: 0.8397 - val_loss: 0.4731 - val_categorical_accuracy: 0.8038\n",
+      "100/100 [==============================] - 24s 244ms/step - loss: 0.3956 - categorical_accuracy: 0.8385 - val_loss: 0.5407 - val_categorical_accuracy: 0.7698\n",
       "Epoch 20/20\n",
-      "100/100 [==============================] - 23s 227ms/step - loss: 0.3797 - categorical_accuracy: 0.8477 - val_loss: 0.4569 - val_categorical_accuracy: 0.8132\n"
+      "100/100 [==============================] - 24s 240ms/step - loss: 0.4037 - categorical_accuracy: 0.8281 - val_loss: 0.5352 - val_categorical_accuracy: 0.7755\n"
      ]
     }
    ],
    "source": [
-    "history = new_model.fit_generator(generator=generator_train,\n",
-    "                                  epochs=epochs,\n",
-    "                                  steps_per_epoch=steps_per_epoch,\n",
-    "                                  class_weight=class_weight,\n",
-    "                                  validation_data=generator_test,\n",
-    "                                  validation_steps=steps_test)"
+    "history = new_model.fit(x=generator_train,\n",
+    "                        epochs=epochs,\n",
+    "                        steps_per_epoch=steps_per_epoch,\n",
+    "                        class_weight=class_weight,\n",
+    "                        validation_data=generator_test,\n",
+    "                        validation_steps=steps_test)"
    ]
   },
   {
@@ -1878,12 +1909,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc0e80bcf60>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1895,9 +1928,21 @@
    "cell_type": "code",
    "execution_count": 65,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "27/26 [==============================] - 3s 118ms/step - loss: 0.5256 - categorical_accuracy: 0.7755\n"
+     ]
+    }
+   ],
    "source": [
-    "result = new_model.evaluate_generator(generator_test, steps=steps_test)"
+    "result = new_model.evaluate(generator_test, steps=steps_test)"
    ]
   },
   {
@@ -1909,7 +1954,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test-set classification accuracy: 81.32%\n"
+      "Test-set classification accuracy: 77.55%\n"
      ]
     }
    ],
@@ -1935,9 +1980,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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JB5TrS+Q1mCgOHfkUo2oy+tTB1AwE4WKU/7Nq2QX+1Yv/E++fvsuTwWO68y79QQ/d0CmVSyheBklVCQOFF154g1A55ah7j5JSZpRI5AsWSZyAICEIIEoimWyGer0OAsxth1w2y2w6w/M9BElAzBZxnp5SpkChuswoPmMUDqnJq5iVJqa2wPb7m+iGhiRLrF/LMT55TPfhU+bEXK6/jOd5xEmMqqrEUYQWw/i0c64Mzl0AZVEhnqXgpUhRQiRBPpPDmbn4E4cn9+bsbO+TUVUMUaGaq1EuiKSpz8RzGUyeUMi+zLDf5aT/iFy+yFKuwrf+5D9w5+VbrNx8A6Ui8HTrhP3jM1rLFo1Gicpqk0p1EUc6JXQCTrttrjUvUzYK9FOPrFknmubZnQyoJBJe/4ww9ECWSeZZnE7IcmsdaabwxW+8yW5/G/Guct4YPtcUSSENRaIEyrkaiZAgpjKB59Ns1FAzM0q1LKV8nh+8+w5yJFMqZxiND1lkHSNTZWdnE0POYaYWmiRxEJ4gqTJJGDA661AwTLJWytwfsL23zzyak9EzlFplBscjzsbHnD07RdUFnLRGbr3A6+uXCAcJh09P0UMFez7BKhaItCGC5qGKKcnYJ4okylaKLmdRpItR/s/SZJWvVm7zQnaRj+6+yx/0/hJVrVDOZAlsn3wxh2pZTNtdfvSnf8ELb12nmr9Ed36IWArZOXvAwtEizcUaimCiCxnKaoSVariuiz+wyYgahmVw/942slugtFGifmOds6NTKoUs81GXs5MOi/UxSTrlpVducPbokHF3QlEv45w4hEqMJ6uYpoEWyOw9fEzYdylZFaI4pLxQ5/ioe64Mzv2tEBERExlFkLEKRcxyBUlRcOcepWyBIHEpFWvUajWWl5axsVm+0iAZi7z3rU/xwi4D9QzFKOCHLjF5et0uvZMT1n7nn7C2foOOu8ugO0EzNBYWF9FMiVI1w+HTh1ByWVypM7djnHbKwx/cJbOo0nq1xktffIlCOYs/dvjD//3PACgXiwzEOYWyhZXPMvInPPj0LkreQbqYHf2DZEl7vsnVj3DmLnESI0kSipiiqjKSJDPsDOke9Fist6gtVOlMO8ynE4rlJlE8BdUgTaccnzzDFWdcubbB9t0dnHHAl377K0RCn26/w/7REYqVsppdprZcw3E8MqU8kt0jSjxUQ8MSFA73DlG0DBtv3EITMthuhKgoPPjpj1ipVQlSyGolXEchL+qUcwVk+aIA/j2+z+TpLtW1S/y3t34Ts2Tx7bs/5GDYZR4EKGlE5E+plbMYacp7P3gXW3RIcXj19Rsg7PLs2Ta5nEE2myV0U/a29vnpO++zvr7OxqVLKBWZJFJoLTpc2bjBIDzCkRPWbm2QxinL9RYPth+yvrKBIEJCnpXrizi2jaEoOKMZgqVQqzWYz+fc/fGHRNMZhWKRcrnM3HfojUfEaXKuCM79rQjCkFwux9yNiWKXQqHAbD7HMHREQUTSBVYrlwmDEC9NKLYyDOYHbL4zYLbn40YRe+oRG1fzXF57nf3Tzzg53mfleovGWotifYHRSYdqPUfScdHUHK47p17Ls39vG1MzUEMLM5vn4NEJZlikVlzkpD/iSjxkIVdEk6qsrtzkg++8SyymJELCaaNPNIrZf3RI5LpUFjTi5Hzhfd6lPN8HGIYhjuMgShIpCZZl4fs+MRInRwP2nu1TyDfIlWtgqtxYusly4zKf3P2UXn+btFanowT0vT7ZfBZFUXnw2We8cucNlhdfIKDNRx//EFGEleVlLDNDUhJ4OH3Mo80HtFaXEQWR7lnA7rv3sXsjrv3Gm5wGNl/88hfJagsc7jzj2Xt/jJCDWDYIYofmpWvU0iLa32zvuPBfCj2fw8dPSeY+peVlvtJ6nTdq1/i484xv33ufB+N71NdKFIolwjBkdjJm3nMJ/Yj7P9xhOBuRrcYcHR1RKBR4uPmIo90ekqQiSzkKxSbdZJc4jGndaDJJR7i+i5krksQJe3t7LF5ukslm8DwPURSZzdtoFYVs08K3PfxRQDbOoqkGumbSmbtIisxkOmEymaAYKiduh0w2c64Mzj8FliVM0wQhYDpzsWczRFkhTVNMyyTK6gRyyPVLtzk4PMTtz+if7HG2P6FW28ASm6AoNJstrt15mYGzy9KVCrbpkKoiUy8AVEQ5YPVSnfX1a+zuHjHqbrFUXGJv/wyv12btTp7WC2u4C220xTL+2OP+04/JVCySyOT6Vzd49uQzoicT6uUGQrmEkmhYSoaFyiqnB1t4tnfeGD73LMtiMpkgSRKiKNBoLGCaJr7nocgGmpHl1s0SoiCQbxTJVRXymszgtMP2J49x4injQYp4p0K20iKwu9x7co9cLs+1qzdo1K8zcgTy+TLjkYeiyERxhK5rqKpEEPuMxkMqpSWkVEYzRLLLLQytwPHBMXb3BLMskM0ofOOf/R4//vffpppKVGolYntGxjKQZBFFuXjM8bMC3+fkyTMUPyErqqRpilEq8Pbal7ijrvP7eyE/HXxIkExILA1ZT6noGR7vHTAXROYk6OUAz/OYz+ckMchilsAP8OYSipQlMiIG8zG98Zx8rsaNq5fZevyIzzoPaJ+28eUAP/HZfvKEGzeuczY+RZdMmlcXkDyF+b6NOhGZ90ZYhknJyJCtl+l2O5CkuL7LYnMRQTzfM97zT4FlkZSYpdYyRz0JNw7IZUxs2yYYD8mbBS6tXUJOZMRYxJ0lzPsiC4sNwsinUKgQRSEfvvsTQi8hr9aYSz2azSr37/2UG1KKpeQw5QKnD4/Y/+TPqKyskG/WyJp5hpOU+tIyVsFgGJ6w9kaR1BW4pK3wYOvHXL50CS8UseQi1165xmedT5klDrPtIe3YolpcYKFWx26fEM3888bwuSZLMmftDpIkUSlXGc6GxCLEInhxhFnI4McBmqajyAquE6C7IsPJiA++fw8hFCllyvihRE5t8uLrL3Nv+9tEzEnFPFpRwZ9PkGIRGY1KpcgL115kMphy0D+kWKkyOfXZfb9D4YuLKBYUX1rAiwJylSrz97eYHByhxhFuKGEtZalfXyb+zGaeRlTmLvmaQanYQJIuCuDPisKATu+IfNGg1zMgFCn4Aabtk4sF/tXN36L9vWN+fO8JMzlBmrmUAoNFpYWsmaRWjDOfEsbQH/fJWirKSp2T42MSPM56x0yjIbWFBSxTQlOKOOMh3njCuD2iVV7hYLPNlZvL9I/a+NVLKHEOUZZZrC8SDOa46RgRg1KhxGg4QiAhnA/JpBquFJIUBRZWn9+U3+VH/+gMzl0AU1JEEZI4IVeuMesdMXNtMrkMw+EQfe7T2Tvj8dZjVEVFEEJm8xiB540NXC+gUi+wVirx+OGHHLePKJRSKvUs+4c7VOpVGuXLbH+2x5Pvb6HlRBaXF1EKGmfzPmsvrmNkS7THJ1gZg2Qi8OjuPW7f+AI1c4HhWRclo3DcOwNTpP5qjbJUpLfZRZXrRBFs7T5GNgwU+WIV+OeJo5h87vkRI1VVmUUOE8dGs0xSWcQLPEqVIgAvvvgip90e/eER7ZMTZCmlslghSkO0TInTvX3qjTrFSpWz9kNa62X2j7bI5grk8xYFq0zn5JS/+uPvUC5VKFfKLKw0qZChICyxsrDI6eQZRlEmjUUSQaJebvF0ZxupCJOhi6Jlqd+o0PEkIlWkZsdUUwktjBCTi83uP8uNAqZaRF9w8AaHVGMLgoDYsVFUlbwf87p6ixM5YpaGzPwehiRTK9UwshqDcRdvKuAFMbHgoikpRtlgPFUolHVcb8qgG/PW668xHk/onHWI53MKWYvM1ZtEgYKYZnC6c5Q44f3vfUR1aQ0zq2CUDMbjM+IkIlDB9qb4UowrBdiTCYVkETVvkG3JTMMZ0/HsXBn8Vx2Fs22b0WCIVi3SaDTo9boEwd8Nib3QI5fLPW+Q0O4SeQ6qIqDpGUQ1wqp7SPKAVktE8GROP+vxU+cIa6nA3vEpSaiwf7iD7bjIVp68VkYSRTRNpX1wQk3V2Vi7wcGTp3z7Ox8xHc/BscjWNA6fHHPz9ZsczPYwBIPWnQaWbyIORMZDUBSZNA3xfZeLc6I/X5qmiOLz6aMoiqwsLXPaaeN5Hqqi4vhz+v0+ly9f5sn2Nvsnp6SSw2Q4xDBMwjBBlEVUXcTIqNy9+30mk2MS1+PSncvsnD1lt/SUDW2ds+MOD97f5PRwwJd//cusXV5l4HWhorHeWqZvn6HrBmEfjvfabE3bvPLKDfY6H2E7Ofwoods/QcvnaXy1RWkqsXR/SgUJezaBOPpFx/lLx8rl+co3/zmiJLH3bJdoNGbqOOSCOZaZYTg8YjzuUExEyrKF0Mwzzbs0blaYn7hk3ByDeEav16XayKBYGcZDnzQFwzAol2scnnkkoU6x5NEfD9BrOQQjS7W8xI9/+DEje4xsyGTzGUQ0pr0+3gTuuiHdToevfvlrJL7EweEB641FxvMBD+/fh9DAdsYooUi10cQ0/n8+CQIQhiG+H2DJMn4QUCwWcT0PRVEYjcdohkoul8P3AwxNIwo8fMdDUhKkUODxew8xE5FoPEOYCNRnNYqtS3T1KZJqcnj0lNXVRaqOwO7hAU7fp316zOoLS+T1IoZu0T87IJw6iGORa83rnOy1WdOajDtdcpk8aqyhWyYLtQbu2YzpeELoW+i6RppIuH6IeHFK4OcSJZE0TREEgSRJ0FSDUrnEcDCkXC4TBAEze8rp6SnD4ZCZ64Hs4thTTAqYkkxMSDavkV/MoAxmqI7JyUHE9//wBwjKlGE+RdEldh7vMm+7ZNMc+AKyJiNkUzqjU/zQI5NVqRXK/NUf/kfcqUSqmeyVdCaxzd6zDqvLVzmZHWPVMtQrTaTBBEPQ0CqXkVUF3cz+ouP8pWNpJq3sEqW1NW5c+wJ2d5/p2QmnJyf0uqc87e4wLYmY2QqCF2KIFouvZug3jxmeDOjtjbDWLXwhZDabUZSeN8V4vj5gUatV0A+2+ejuj9m4vMbJoYMg+5hmkWYhy/XXXib0PuLSWhFZ82knPnk5T79zRG41h17MUbm6xMHhEa3qOvVajXxURWqWGHzQY7p5wkZhiWaziT2zz5XB+afA8fMeYLppUCwXOeud4LnO84smiTFlFUM1cSZzElHAUDKIloqvJGjIWL6FFt0iGtoE7SGKabJyvYWfuHRnMxx3SOg7pIlEvp6jJSRolsTsZERevk391Qa7e5+CNiJX1fjdf/FNDvfa2Fs2o/YQIQ+fvLNJOdeivhBw6pywt31MbaHCzbXbHB2c4LkhlWyT9JwPUD/vBEEgl88ym06Z2TO8UUhzaZFCscjMtonSkDiImQwnyIJEtVTh+GyP2FeZOQ6JZpDJZ+gcdOi224hpSHjiIpzGtHKLSPkCYrbEeNjFyqksX1pj5+EzfN9j+/ETkhzcuPMKoecz6ZzR608wjTLFTJZIhKOn+1RX8+xuDhgcPKVaaOCeCRRzZSQ/wszrqLUmipoF8eIZ4M+K/JDu1h7KPCa71CK3uEpudZkWIt50SvT+f+JHx/fYnbRZqpcpZDOIus6kY2OPp7QHJ1QbS0RKiGhpxEAmk0EURTRV5eTkgJVlA8sssHn3CffuHrHx0jKleg5UieWNJQq6SkaLGU079MdtojCk3Khi5AxMU2f/+Bnbu4+4/fJLPBvsopkW65fXKToWB7v3WSkvUC5VOG9jq/MfhYtigsCjXGsQRgGyAP7f9IpTVYWckiFwI4jAJ0J0BCqZBqnsEQ1nFC0Fs1LBjmQyVgVnxSB/VeHsvk92bDGb9tCLC8SBypnXAR2UcsjllRUGOyMaV1rEYYQkSMRlmez1Cqnbw/koRKsbLKxXKOgSCnnae4fQF4njhGv//YtkrSxOw2Z9/WXGcw/9T4zzxvC5lqYJCDGIMV7gUGouEITPO/6omooQpIR2QKokz0eJQkTRrOEFBoE3I2tkMZU8znCC3Rti94cYSNxqrqEbOqfTDmEnwbeGuMmQzFKNyrxAsZYlclPsachbr9+kN9vHtg9JfIkXv/IWmq7qAM7kAAAgAElEQVTx/l//kGgakYxlFEXD77hM+336/gjpROaWaKAVdKRkSEkvc3GP+/s832Xr2SNCPG6t1BEyVVJFQIhS9IUir6Vfx8ubPPjJn7Dfb0PNpbvZ5uDTDqJt4koSbhBSkC0iP0CqmjQMk729PVx3/rwOmAVCJ6Z/csq19VVeeflNkAXSKCRMpniMUSSLQFCZhjNIBEqFMp4QYCLz3T/7Uy5vLOMMOsSGBIlKMHdQqiAWU/ae7ZNZWaJU/kf1Qf1b5y6AkiyTL5ewx1PcThdJFzBMA2fu4Hs+TiQhiTKe75OqEqZp4PseURxgqiqL62u4rkdSchFNhVtfvcau8IB737pPLiijpVnCwCGMfXzfppItI0saeknn9GyXw0c697+1h6aptF4qkRYCNr58jYy+QLYpMBFOOeo+JaMqVOprrF1uoOZDRFVn+2iXTCnD7vQZARGqdTE6+HnSFGzbJo4TdE3H0HUUXePs7IwgCAgDn0KxgKqqOI5DEPgEUUjOMiloBs5kjuOPqeYK5FIJuVTD9uc0XmvhTB2UJwa98ZhG0cQ0LKYjB1KQJInltTU+/OweUdjG9CZkvZixOCBXrVLLtzCKeZIopbHSYJ5MiGcJcgD2bEKhXKJYvEowdQh9D90wuGgG8/clAuQXaizevIZQL4MqQJA+H0xJ4EUxldISX/nS73F0fIQYDdh+9DGdwz55oUi5XKJcLlNbqvDw4DNiQgSjymQywbZt8vkck6lNrzvBymS4dvUapihzsL9PEicoqkq7c8Jg2EfTNNbWVjE0C9d2WVleed6IV9Lw+gHSikq5XCeWFTwpRS7nePF3vsbB7h7dXo+Fev1cGZy7AMYkhGlC5AcIXohsGgRhQBiFpGnKPJijKhpJkjCzHQRC1EQmlkDXTYb2jFFviIhD9c4qz3rP2N49pPNsikCGeOSQsTQKpQyWvEzqJ8xth0gtc/ONNT781oecHs546+tv0my2kGMVTJ3amkq+kqB7M7pCTL9/SGVhhV58ijZX+OzPv4WnuFx5dZ1ETqjrlxHSi02yP48oCkwmE+IoJpvLEsUR/jzC8zxSnt8EJUkijmMEAaIwRJaf7+NTBIk4DLm8tMZSrU5n7xA5VSjeaCG9EPPX33qHztmY7K0io9EIWZKYz+fIskzGyiDJMsVikafbm0R7IzZ/ukn+jSb1Wxa5YpVf/8Zv4fSnVGo6R+1NDrZO0DSZ1ZU6jdYi1178GtPNx7Sffcql9Td+0VH+Usrm8/zaN7+BWMiDroIbISCCH8FQ5ezJMe989hHXvvFbvP7y7zKeBdQqv8fxxnvsPvoBXjDAsgwMQ8Nx5yiGRKFQoFgsYlkWo9EYM5ewt/8MEoN6bUCzWmJ81Gb/4IB6rU5trcmVa5cZ9gd0e13c+THEApcuXSJXyNGoNIm7Pp2dPrKUQ7NAJmDn+BC9lOfaC7dIxh5hdL5FrvM/A0xTBAl0XSNKUtzAIwgCNFljNrWRZYlETCFOEGOYz210q4iuGygoTN05SRThpR5HwQGb39mkd3eEKWTQFgzK6zX2zzbJlE3iMGTcG1NpLCKVQg7bewhuyhtfe5PW7VUkX8Hb8XEVh5P9EyYPjpGVEY3SCsqKii/1WLq8Rk5cZus7f0JpNYcRCsjFDIoukAoXJ0H+IYahoxsGURTS7/VAFFEVBcdxSOOYwPUoFAo4wRwZiSRMUBQNezLD1HXS0GfYGTC15zRbLYyKyf3dDzk6PWE2SZBdC117vsiyurLEUO0hywLT4ZCb16/T65xy7/0dlqvXuH7nVZBzRH6Aqkt4hoioy3iRz9QdE+GyUq2wvHCFlSsFpqzwf/3lH1EufApx/IuO8pePKGAHc+RxiGaaCIEIiIzbZ4xHI+7fu8/D7WcEy/uEUQ3TzPDaS2/x1p238H/j33DU/pT9yU/YPtxESQ3ESGLQ67HYaBL6PoHvUZarNCvr6GqFWmEde2wzn3hEbkrW1MjlCjSby8xtB8PMMx15nJ2eEIYxhm7xwq0XCU9d7m09YufpMflsFiPw+WjrM77wm79G7uY10iSi3T45VwTnL4BJjGOPkWUZwRIIgoggCInthIVsE8ebIwsSwcRDJsWbeOiWihGrtPt9VFWhEogkBR03PcbdscnEMkoNrMsK640NTo93cMcuObVIpAqUlAoH+4/o+WMmR2Pq1zy0TML9724y3GlTuimht0zqtcsE8ycE8yyH/TbZQsplLY8pl1DEMt5RQNyxUHNVNEF+/sKVC39PSgpySpj4IELk+xQKBTzPQ4gjYi8mDhMm/ghFUUi9gMDx8fUUUMiUsyRCxGDg0o1jvMyQR9tb3P/WJ8hhDjQTwygShwGSFiFKMT13SmM0pJrL4Yw79HYnlK6vUL2zREkr0N90cQsd+t4ue+02vbsTsiWFG6+/jjd2WCq9zp3lL5IVwLrapPjql/ijP/q3jHrn6xbyeRZGIUedYzzPQ5YkypqOmKT0+n0O9vZ4vLeDVikwjl2OJz2k3imlmYUiq2SyWXL1F7lZuc360glv2juc9R9y2H6P2HEIw4hpZ8itxbfZuPWbPHk8YPasSP3VLOvXIhrrC/hehK4tI8s5ipUSnmcRl7I4s4itrQNKpUUy1SqBNEfZMTAGIoIj4Sg6eavBtD9FSmI63ZPnL0g6h/PvA0QgiqLnKz6ahpxIxFGM5/mQg0w2Q5SGGIbBfD4nXypi5LP0+32K9SpCHFOQs/TUPp2jKZGVcvv2i5wOTpEElYOtQ1AUEhlC0aO5XubZ023KS1WGcUAknxH6fWY9k8gZEth9RNGglH+Btcu/xtPtgE63x/Qs5mR3wFu3a+QqFTa+dpOoP2P//i7BB1uUCg3c8cVRuH+IKAq4rotlWeRzOebzOfB8k7Qoigiy8Lx9ehDgeT7z+Zw4jllbW2fYPyMIZQzyeMEMK5Y4PDxk0B9QNk1qrRobG5c57TkcHW+ztlpDlcpYepnhqI2sD3m09ZjW5XUUNWU07vKDH/4EPSdTWFS5dPUOG1rMYPiEZ5un1I07vPH2N2gsgiCkyILAv/4fv8kfd3cIPv7rX3CSv3yCIODBgwc4jsNkMqGs6sjAYDikfXqKkaug4zPqbCOnU1Qhw2CYIYljypUSipRHTMskqcxwauHaDa6s/Dau47K3v48YZdnd3WPcf8p0pNBq3GA4cskYi1zZeIknu+8RxjO6fYfxpEOSqqxvLDKbHfDw4ccg+jTKCxiRgT2fo0oakiiDGLOxsUFlpcTm5iZpGp+72cX5j8KJwvN9f47zN336Q1RVRc4oJHGCJEvI0vNnApqmoekmSsbk6NEZkSywtrDIeBJwGp8QeipLL65Rv7LC+DMXfxYy7k3Qr2dRNJFe55RceZlZv0ep2uStL32dTv0TGlcquISQCbh0ZxFXsslq19HUPNX8iySFTQwCnj6VON45Y3W5RetqhUnOxD6bM354RKKPiNyLTbL/kCAI8bznNwhRUpBl+fnB+NmMnJUnk8kSRSG+7z9/haIkY1kWc8dGEjUkQUdCplbLM/fHTMZjVldWyCoLhIpKv98jjiM0TSPwA5bXSkxmHQgCNGEBTdNwvRGeP2HqRoiSj+2MWbQ2KBUblEpF5t0hJTnD27e/ybWlZRTt+RaeMIXvfe/7pFMXS9d/wUn+8gnDkL29PQaDAaPRiKpuoIgS1WqVL739NqZZ4LvbnzCb77P7+B7Vegs1W0ZRZGYnEWftCZFvkC9kmE4HDIZDMlaFKIqZTRNmM5Vu+xGGVkZXWpQrZWQhA8qQlIBLq69wMNjnye5nuF6fYvYS9UaWRjePkYFr11toWLzzF+/hOg4ZLYsQg+u62IR4xw6dcZulpda5G96efxEkTnBdD0lWnjcnVFSEOGLqzwjEACcIkVWJfq9PvVZDkCRm3pyX3niF6XSGrpkMUp9CpcCd1esIRkyYKCxfXUOdiew8fkJiJFg5lf7ZAZN5D3cyIysXSAMo1LPYikuoyKy8ss6l6hL3tj/CDU5pj3cZTmxSwWd5ucqwO+Gd7/8lo9km+XqFSukavfEcWc2SkJJezIB/rjRNUTWVMAwRBAFd13FdlyAI/m7xA9A0jTRNUSSFWI1ZWFhg99kusqBRyNfQFZlucMp42sPMZbm+dAXBMzkZ2ew/2yNXiyiWK0ztMVZZIHZi5hOZS8VX+Pp/02QS7bG23mDnw30WlyvIhkQcg2kVUMQSWWmDlctXuHHpOhLP30/tRAHvvv8T7n3yMcvHfZLo4hngzwqCgMPjQ0bDEeVKmdu3X2axXkdMU3KmxWAwQJdjDNUj8EaMxgMkyUJVZOI4Yp6OSOQUe5JSLFYo6AH2+BFH7SPKtQqrK1W8SY3xADRVR1V0fN8jY1QRYgPDtNGdmNHeGbqRIIoBcTJHMwQyiYphyeS0LLfu3OKefR8hFpAlmTSIyWQzlKolrr98g729Heaue64Mzj8FFiUUM0ccR0xHY1RRQghjJEkkVWIEWSGKE/L5PLoo89EHH3HttVvUVgqc7BwRCjVMwcDdspgxQV2WyBUUPt7/gDTSyC0vEMtDYjEPA5nJfIKVK9M7OmE6f4hTSpDnBabjKQvVZZSFAleML7C9tcvB5i6OM2Wx9jqrt2+yc/SURrFA4UaTvFnl3d9/h9F2h3qriuempFwsgvw8cRIztidksllIn7dAi+MUUZTRNANVUgl8H03TSKIYSZFRDJ1UEciW83gOiLU87ekBsiVSsRaoX60iRRJ6JJI7mBB1IvxEIFcvM4sOmNqgzWRCR8SyKozDY3JFidA/o7ZexFgpkDVLfPhgh/a4zWHvEbl8jY3ml3Ecg1SEo5nNH/ynP6Dd3me1UWf3wzbz6KLhxc/yQo/93gGCKPDS9ZfZuP0aS8UKj97/EYdPntIXprTjDr5hUBSboMvsu30sMaGxWObqq1c47bQ5OTkh0QOQbcL2M/TcnOtv3UA0dFTbYPvTAdEsYGFhGSEb4Xg2um7RH23x19/+DxRKOnJqIapzBp0z2mdTJEkin19AMwz0JR25LlPOlpn3Z4ihR3mhiZrNIpo5Lr/4EvbcBr77j87gv2IVOGE4HBLFMfP5nEo2j+u4pGlKkj5fCfTjgCROME2Ta1evkpKSpgmlQhFnbpMxVUr5Cp7jcrRzgJmLWL/cxJ5I9NouuZLEfGZzcnxGtiTw6tdeR5up2M4RvhvgtlOyuSLVfBU5VakWimxFcyaDDrIcEYY2M2dCPp+lYOSpV1cpG8tUW128YUKYSs+HCxd+LkEQiJKE8WRMsVAkjQGer9giCIRBiGZYBEFAv9+nUC4ReB5RFLG2tka3Pcafz5EFmdAWyOgWjcoyqiSwu/2Ykd+nvFhgKPmQSMiRwvy0hyUVkESZ3Q9/xFjvUmgIdLuD/4e99wyWLbvu+377hD7dfTrHe/vm8PKbNzlgAAgAEUiCCSJlkbJEW1RRLsuq0ge7SnKVQ6lsf1LZZZtSlVRFukSzzCDKJEQQJAACgwEwmBlMfBNefjenzvnk6A/3AR4NHgTOA0CRb+6vqut273NOn75rde+zz97rvxaeK7G+UKHcmGPdH7LXfo3QyPP0U/8F/kQjswDX93Z47s0/JC6aXFhY5Jnf+gqeO8ThZAT4boIgwAs8Go0GakLFa3fZ6LZ4qXuTpttiYk+YiJB0VsbxIkzPJk7IKGoCWVaxbAfPCwCJKI5xwgi3kGW2uoySqzIc9kl02jTmigwGA3anz6B6aVQ5z8Ghwo2tl2getdC0RUqFLFGoYhoOlm3TmJ0llUwjJxIMRgPqjRnMjsXUNqivzDO3tIDhOkzbA+ZWZ/HNv+ARYBTHhGGIJATpVArHcdA07TsLI1EYEYYh4/EIOYhYXjtFP5iwsLDAZNumvXlEXNVJJ8sMTBc/mWR+5hTVWUGnu4ssj4mQsN2AAMGlDzyOVk5QI8XIl9nZaTOTT2MFNjMPNsipBV557QW+/Mdf4YGHZ5BjcE2L/uCI/qBPplikpDeopOucemqN3uSIEiVK2gzffOaL92qG+xpFUVBkmVQ6RRRFuI6PZdrIsozveSQklSg+lkTm83nmGnO8deUK0+mUpeUlXNMk9kOqtQpTT8JsmtwONhEJn0gxCdIeu8Mdso1ZYi/G7wW0buxTe6LG/PllhgdH6DmZVtOkXJghl43IV+v4sqBS03njtQmffOiX0cwVNN3haLrJ577wf5GtT5mtNNBzGS48/ghvT98mvHJyoXs3YRiSTqVRZIXRaMQrw1doWj2CpSRbro3nq2TdFNNmj2ypQG1pnmDSZnPjBjGzJCcqo8mEjY1NHn30ERzbI4hSJOIs1r5J88Ye0sAgW/cIckle2vosxWSB0MrQ6XSpzAacPXuObmdK5lSdTCZDb9QhkVCxbZutrU2UpEYum2W1usbm5W00JUXX7FOyTGIvILAsdswRWlK7Jxv8AGEwMZ7nkUwmURQFazohl80erwwKcTx6CI4DYz3P4/btW6w/eg7LsrAdm0Iph2H1CXyVxulFht1rXL95GS8uMZ702NvfZ315FTkOWD21RHmmhrk9ZP/lTSaLIYXyKQYHA4L2iI3aFt9svsTe7iGym2fUDFleniOTKDAYtRgMepRn5qkVayQCnyP7JolZB92D3naHk0nAuyNJMo7jfGcOkEBCluTjYjRhiCQniKLoOPDdNGm3Wpw/dw7X80in06yvrbH9xhbD1oB8rogiZWiPWuQbKWbP1FhS62zf2MRFQQQS065JYabO3OPnIamQlSx2OrvstV0SKw1kJSJfyWN4Fs8+8wqqeZYHF34adxTz+s3nGEqvsdN/mdXSGbKlBql0g+qsTjqzhXJS+e+uCElgOzZHR0e8qbjojRyKEpDPpsksrjG50UIZWUTEBFLM4sIiui7Y27+FH9tYjk1SS6HraTzLwzuYsnWtTVFOoniCdHaFaddFJCX0WpZ6XmHacSiUGqipKbIokNZmMSYeihQTBOC6Lo7tsLu3i5pMMjMzD4CqqrjBlHSlwNvXr3FhfgVvOOFo3MT1/oLLYhLHGIMJWlm9s0ooME2LdFpHCInQcUiIGJFSkWWZhKSye30DM6gz86EZCokSb/2bFxC6h1eTOZM7xbA74PI3NiD28fwc6dosUmub/lst9g6S+B0ThMAyBVIVrHhCqbzAS996k4Od25xerXNx8RydwTXyC/NUEmV2jjZJpJOM7Q6v33wWJZVGS1Z48gNn2Lt6A6ljIeSTDvCuxBDaoCbV43k+JcbzfEzTJpXSkWOBpqp4rovnuYSDCcbIRK7mKc6WuXpzk5Y/oRYmiQKPTL1EypeZ9DsUjBg3HiOmHiQhVmyyMwr5pTWEEjJ9cQPb8kmUSxRSI25eeZn1U4vsvNLi5tW3Ca0qf+9v/feMzIDr+19nu/dF9KKNNZ0iy1nq2jyq0Lg8eAV9WUVOnGT8eTciLTNeDBEFhdJcmcSgiVKMudm8zdqD59CDkJ3uPo31KoVyGTN0ME2b2zc3KBRLrMwVEUkLVUkg5IgodJgtZxk5Ef4UKsUGar1EXE5w5slLlPU0EkO6lS67O/vISoFUqojQRiSSUxorpyjaOc6klnnjzZeYTvYoUkVMKmy1OgyGFnEUk5lGbO82uT4wWVhY4IFzT/DMM8/ckw1+gMuioDHbOB7xIej3euRyOYSQiGLQEipR6BOGAUtLi2jJJJEi2OnsUT81S+vgAGQ4dXGddmgSWiabb13joYcvoiUFWlZlIvnEUQJFzrJx7ZBasohaSiGrCo25JWrZ82h6jIbD2fUasrBJKTWKQwnTislaCRwjQE0k6PQOSe3JJJI5GsVzZNIF8tUybkUgJU5GB3fD8zwCP8TDx7U9VO145Of7x/GdkeMhOJ5LqpTKBBMDN4pxJ2MGoyGhHPPUx5+m/cYN2s0WsxeXkYIkvanE1rUOETY7Vw84/6EnUbUEk+kW4Y0h/maAuNIjVNMYp8ATIXoqRRzK/OnnPkvsCP6H//afoyll/vRrn8ORr5EparSO9inkc0ztXd56+2skVJV00adaPceXtJNpjncTSyB0hWQpTajFRImYbDkHzRhVyES2w+HeHvl8lmg8YGKPSedTzDaqLC8vE8Q2ejFDEIQYhkG2kCKxpCApCofXW/hJnXw5hZjJEqkdJJFFT+e5eWsDSZEpl6t0uiMK5RRIBno2xe7eEfXZDCury9zefIPd7TGvPHuFpaUzzDVOc/3tG9SzGUqVMslUinytjB05PPL0Y9z41vX3bIMf4Jcf4zgO6XQay7JIp9MoyrGmNqPrHB7skUom7lQUcwlTkCxmGdwcoFgSzbe2sD2TvtFlOhiRKul88GMPU58pIYSP4Y5oORvk6w7rjxW5Hd3G81MsnFtD1JM0HlimXF9F10O2b73Krf1D9FQdX1ZQ0kUyeYfFtRqluQ+i5gK+9vIX6HcOqCTncOIx250ht25ew2vFJwsh34MoOs4F6Af+d+Ksvn07HIQhejqF7TjfSYYg5dJUF+boT0ZsbW6RqZWpLpW59cqQxXPzOIpDcbbGzmtbWKZPvVLl0gMVcqUZTNsi9CSabx3QjzXWpTpSLg+RxEyjTkpLkkqlKT6a5cc/8PfJyE/w8uvPsNf9A1J5iVSmge8lSKYS9Ic7JI+OO+lyqYasz56s898FWZKJwohet0ccxaRqZbrTMePBECYW+/0Oru+hyAqO4yKkgMZCgfFIQlZdHNtkOgXTNAmCEN8zcbCQcjL6TIZMVQd5wnjSx94dMpKT5FKLRFFMpXxcEkPXdfJ5DdcP6ff7HB4esrr+KFFssrCwiAgU1GDA+vo6visTS3D9YJsLFy6Sz+dBlen2diiXS/dkg3vPBiPL6LqOZVmIO/m/PN/ngYtn76g/JoyHA6rVKpsbW5z9yCWKy1XU1xO89fwb9DYPufDYBdzYpp7V0RZrDLtH+J5LjIdpDzHsHmEQYQmHTCNHNpYIM30mcYDZG9CyrzCbX2V3w6WUWyOdzdAatlmaWyGQb2N7EdeubnD2kTkWlhoc7m3QvLHFa9+4yfzpU1TqZbavbBLe4/zB/Y4kHas8wjBE13VijrPDSJKEmkjg2A4JWcb3fQLfJ1Muo1byFFIqw8EQSREcjQ7Z7eywfGaRtt1iOGhih03+2tNPIbyAdFnleu+QAIf5pSyTSYFed0K2ppOYrzNzYY61U6vEUQRSQCU1x/rsp/js575Ca/o5UI+ozy2wOLtKqVQlmfN49uWv0O9Z5HIKmYxgY38X2z1R+7ybmJhyucz+/j5aIsHZx89g2SbFzTy7124xGExZXl6mUq4wHk+QJZsgnNDubGPZWXKFAkJKoCgKw9GQMIo46gTU0nXmVk8zbI4oJQJS+RyeL5PLzUB4XFhLkRV6/T4ZPYWWkAgiheFghOM4tDtthqMjcgUZIsHy8hJBEPLWW9cZjKbMra9w6tIFojhmOOrjqg5GPLknG/xAt8DD3gA5jCikdALXRxESQ9/GiUOUaYg3tKleqjMUNrPrK+RUiZmZNNeeu8lCcZH1Dz6F4RiY5j6t5gaCNClFwg9MEC7BpsKgE2C7Mgunl7Gu+xhdi+LaIsNOj/KyTKd1RHVmgWKmwUFzi1K9gJS3cCKb/fZNzP029Y+do23G1FeKaNUU3uUpy6cuII/H5KYxKU7SYd0NwXHexziKiIKAOIhIICEho8US1dVFJoMR471DEoUs/V6HsTzlkSefoPn1Tax2iLt3QOR5+FHAoNfjyUeeIJdPEWRcTGPC1JHxrCGS55DPC6KlFFPXJaplsPI29vgK8eE26WSNC2ufYaH0Mb70/CscOl9EpE2WZ9bRcg5T1+bmleuc+mtplk/PcrBxRHvjiKvPXUWvVpFORvnfReSHzNZnGJpTSsvzpCKVyJXIJDP0Wx1iTaK2WCdXz0NSMLZ8BiOPdLZGbbaBHYxx6KMoCYTtc+uNTWYqp9B1FWPSx/YVbL/MucUHiDMwnvYpFXPoaR3DNJA1MJwh5VwR250QJaCYTfPaMy/RmJthvDtibLqsn3+YXLFIea7CzGqD0kwVRZfp9Xq0+keYU4N89t4yft+7FE6WkBUFx5yixhKyIpNKJdlvHZGMJay9NvlUkkGrg5ZUSKZSfP1PvkD7YBu9oJOuZHAVUNMZ4kCjmMhSKizhBxN6wwFJOcVw32Bzq82pS2v0jT7uJE0urnN66QFSVY2h00GrJkkoRRwrIiIinc6jpEyiwMWLh3iWxcvffImed8jc6RqBFFKZrxGEAXuv3uRsfYXL2tV7NcN9TRhF5LJZbNtGS2hMzTEpVSMIQ8qFIqVKhZSUoHN7F1XVqKQKWMmA0myJM2fWeOHrz8PQ5dEnHqextMA4crAtn8NmC7eeRVEjAm9C4Fv4o5iDrTGFUoLG/AKDqUOmoOHYLQwzTUpep5z4EBtbR/Tdb+ELi1JuAT0bMnCv0mrexJ4Y5HJlJqbP8lIJaoIbgc38+lluyO99fuh+R5bl46gM30NJaeAGvP7iK5iWSSqbxTaGRFKEYRsEBCRSaSQlRS6fQFF0omBKQARBjDlysEcealUilY7IF3IchA7tfp9Ks0V1rczO4QbptfOkRYq5+Vk63TZSQhAIjxAXJzBozDQwdkcYXZdBb4Kc1en0xxRKVc49cA7Xc/EJCUIXP3CZTEeYhsF4NL4nG9zz0lgUx1QXGoxsk745wRERkSqRz+ZIhGBNDcIoxPd8Hr70EGEUcPvqJvI0Qa6cZSr3kSWfbEanWm6Qz9VwXYdUKouertFpu2wfdZF1gVZQmFtZp3qmxsCPuLF9DS2RYW+7j+dGaFqCUlnHsid3kjMksU0boSmkqwVee+FtMlaNK1/c5ZXnbpMuZCnoSc7mF3ni9ONEwckM0d0QCDRNQ5Ik9vf3CYIQhECWZaaGQb/ZprN7gDc2yCkaChJLS0sIBDvbO8SywE9IzK+vkMhnmFlaoNPpsDA/z3xjDuKYKHaRZZXLr20QOHlIathRiDkKyJvV2VcAACAASURBVEQVnjz745wu/go/9eg/Zr4eM7K/QKY0JKPrlPIVQikGXUKoBr7hcuvlQzbf2EKVVJSMRH25TEMpE1gn0xzvJgpDtra2qFYqJBIJDo+OeOPym0RhzOzMDMQxguOQtoSaoFgofCeszfMcdD2PLLKMBi6Dnk2pMkumkcJSDAxpSqqaoFRNMp42mRhtllZqlMsldnd32d3do1atcfbMGUzTwvN8FFmGOEGpuIBlQBQlse0Az3PodrvfkWG2mi1M0yKbzVEqlclms9/Rq79XfgApnKA8U+fRp5/kaHefwXiElk6hCUH/qMupi+dRazlmH1qBaprtziGTzoTQMOkxYf2hBYLAJJ9f5OYrb9PsbpDQFEQsUJQExlTCJ8HyWgG0kO7IJlJdamcgQOP2zSucO3saJZlkZ3ub2cYsZ86colheYKf3KnEU48cB5YU6zf0mR28OGA9DtHNl+saIil7jUv0UuSh7kg7reyCEOJ7/S+sYySmObRMFIZlMhiiMiByPw41tEhEMj9qkKxrFYpHXX7/M1579Op/69E+yc2sXOw5RooBEJs2cPgfCQ5JDstkc9jTPzuE1er0+5dUylhwxM78MfoaKNscDcz/N6TOPoqo2l6/9MULeRhVZBsMhc4sZ1KTF3tRAT6tk1RQv/dkNTj2wyBsvHzCNRszOzyHlywhxkvT23UiyxEytTmNtFUc6FjaoCQXDNNje3sZ1ve98B1LJFKPxgLevv8ni4iJ7+3vkSlkmzhRvFBAFSdJ6GpEDVZcxTQNPiillUhw2txnFRzz0wUs47nHG+P39PVQ1QSMhYzs2kizhOh5H17dZzq1DLcne7h5+bHPUarK8vEI+n8cwDBzX5cVvvUijMYcsCUqlEonEvU1j3XMHqCQUooRPIq2hpdJcOtfgtedfxjkIaNSKnP3kk2iFCrvdXYzOFpNeh0tPXuL65Wt8/NOfoG+12di5CYHEQrnKZHufK89fJ3emQaWaIRyOkSRBupyiPJvFHSm0/SHJnMxWe4OOe8jMuVmCGPrjKfvtPVbXFpDiHGLqQhom0wHloyJrlWX6zgQ9Vgh7AZblY3Z6ZKIy/nB8HOR7wl2IcXyHhJ4mN1fj9pWr1DJVzNihlCuSSMlkkjqKJJMs5Vl9ap1MPo/7xg0US6G5dUDXaxPIPpl8jlTk89ZbV8joGfSkjmNrjKZjhuMJWlqmUEqyoF/gF3/8l1nIrlDMF0lnUgzdKV9+/bNstXcJ1Swz9SzzNR09nWTf3IBQJvRi6it1Dtp9hhsBB70J+YU8oZ2hK41R9XtTCtzPKJrGzOllrMhgPB3SPGiSzuoctg4pVy8xX12gPxmgphJImoKIFBZLq/R2enQ6HaIFiBMRmqyhJGXkZERaU8im5zjc2kAG7LRLqpxifnGe7tGQeqHG0vIpLMvk8uU3ePv1t5hfLDCzUmIw7WAqMhOtzsLiImPHJDEac7S9Q3TeJawHoEGjWkP4IQdbOwShz8xchXy+fG82uGfriZiN7Zs0t9pIgczM+SzpfIKw65FfytOVxhRFjtFkRGdwncj2CJIqT/zCh9ErRYxuQBBAa7/JzpubXP7aqxRzFZLnc4xHY/avXUdLaOTLJdLpNJPdFgoZUlodVd9lZm2J/U6TRnWdC5ce5ebGZV569gU0+SXqp6sESsyo02H7lR4PPfxRqutVmtNvEU1copsRtYcexlXzSNEEJXFSGP1uxHGMpMokC1kWFxqkdY3m4SGGbRKMQw57+8jpBB/9+KfopcaENZX+oMuk3Sd0Y6bDCSuPLDE0+lTteRKqgjOaMjwaMR64zC8sYcRdiHzSyTz10hr/4Of+MedXV78TtuIGMV99/kv06eCmInYOWty+tctHHvwwgVpkMLVBAseMkEKLmfoM465BSuiEowjZkph2WkTRiRb43Uiqysi3GE+aINn4ocu5B85z48YNyvUK6aJOZ9ChO+rRGXXR3CR2x+b61VvMzc0TTCIizaXZO8TzPMqzc+RTOpGTJKs0aMwucji6wdQMiaLUsSbcE9QrZQQKg8GU3k6Ti8tL+JOY0HeZPdUgo2uoSZhfnaF7PcR0U7R3jpBKCnbsMp+Zwc87hI7LlWtXqdTLLC+t35MN7rkD9F0fa2Rx9uIZlpeX2d6/ArEgk8tCBIcHt7AtG8McYpg2k24f35RZOrWGIsvUaw1q+Qbx2Od3/sX/S+REPPnBs+iZMrvNEY3l87jegJxew7NiBn2LU6sPk8hmmToRqqjQ6zTJJicszS+SSlbZfLlNOi+Rf7CI3QvQ5CT1jxbJ1FcopBPsTN/CaEmssMp6+Wl6PYv5tIs4KRl2V+I4JpfNkcllOTo8pNlsUSwUWVxY5Ktf/SrlRp7HPvo4qXMNMp7M9ZvfIhlDupLikU89QblWoHqqyNbGEXF0g6yaIW1mee7ZZ5hbX8ULHSbdCdOWw2z2FD//yV/hzOrqcaW+pIYmC97YvsorWy+TqcsoyQyz1RmGfpeXXnqZOF1CmhX4UcRkNOTK5S0ePv00oUgQT5uEroPRHVJenEeRT1b6340sy3iOS6/bJZtPEIQhsqzw4IMPks1mQQE9rZPP5RGS4NVnX6O/10dWZObn5wiES88YI8sypVIJLZFEVhQ67Q6GaaBndHS3TFIroKkFhsMBvfYW2UyOSqXCwsIcw60DhgMHKRKoeh5Zkgkjg2bbJHQjBsMWfuiTzeUYDIb0jD5hyuXFF17gYz/2Y7Q6bUbDEdeu3dtC5g9QFjPmwQsPk61lsAKDVCZFOp0iU8wxGg5YWZxH0TzC2EGWJcbjCbGnEYYhUQx+4BJh0Wzt4wQj1lbXsCIXZ7/FqeULFKo5nvv6b7G10SQME/S6Bhn9kKoyQ76oE8U+3V4Hx4BK4Ryn1x5hdvkF/PGQcDMBqZhQt8mVFBS9R+Tq/MSHf5ql3AMkolk2tva4ffMK+ax20gF+D6I4wvFcosmUa9evkZEV9FSa4WBItVKjkhYE3pSN1hYp2cYZtJhGPu3emLXVCxTKJRTpOI4rk6nx2tde4dXf+TqJapK15TXagzaDoz6RKfHBJz/Jxx/9CC+9+gbd7oCf+ckfw3Ph2TefYyC6OIbEqZkFtGTMtdcOufrCFeJ0had+/ix+YCJEklqlRjaXZ/HsIsNpF2fcYff6bSpnziOd1AX+Lnzfxwt8XM8jnjiMx1MUkWBmZuY443sYUiqVjhVeskBNqERhzIWLZ8kX8kydETo6y8sr7O8fMBwOSXZDDg7bmNOIZrNFplCl1+8z7LsYJkwnQ0ajEbValbW1VW6+eJ1vfv11Css5Hv7wQyRTKmEwZjSYEk1i0mmFURDT6XaQtSSWZdEzewhJwvd90uk0fWPA/v7ePdngnleBFSFRSGYpZ0vUy7O02m02rm8iXIn51VXihEo2ozJXqpBVi/TbI4zhBM+2iXwH2+gyHGzx2rdeYKkxT7GWobPb5cpLt0jKGbzIJVcos7t1hIhDkukMsSdTSi+RpEL3aJ9IQLM/wDAMcskSlx58hPZen6/+3vO0d3pk9To5r8qsluTHHnuaT3/k76Ara2wejRhaBpmEhIhAkk6kcHdDFSrpOMne5jbrp1Z56OnHmFmrE8gmiZSEIlSOjrbx/Dad3S0UR8YY2PTaPYzJBDmrEGoqlUqdVEFBWAG6nOCR80+QTZWJfPj4B3+Kjz39GX78k3+Dt28d8a0XXuapJx4jBG7sbNHs7xFJPs3WATvbW2iqxgMPPEVSzXFhbo1CkMWcWMRywPy5MsW1JFExYOniEoVqiaSaxGkPCMOTrN/vJgg8AsdChDGu6RP6IZZp4XvHlR2RI7S0CmHM4LDPeDhibnkW27K59fZttq7vks/UyOg5ZDliPOqyt7FPWklTSBco6EXWVk5TLVfY29vEdcd4rsV0aiDiBPXKEqvnTnP2kQssLq8gIpWE0LFNn2whj4NHaiaLnE/Q2T+CaYgcyFi2SUJTkGVBsVRgcXGZhx567J5scM+/fM91+doXvkyhVqEyN0Nay7F9Y4vF/DLFR+ZwpQDfcXjxS99gZAZEjkQqo9Hc2yeMbZJFQW9nyNHbTRbPrpBRc3jmFF1RiLEYDG4xnQQoviAtm5DLMNdYZGHmAmlzyEH/Cv5kgjsOsOwWU79EopKndmmVpCrz4Op5fvKRn2O9fo65YhUhBDsDmMQ24CKFLsQJPMuDk0XguxOCHiaZKVS49OCD9H2D0XgXI+iQTOpopRmUkkN5VqI7Vpmrn+Vg9wWCYQgjD6SQcegjTw0cY0h7Z5fCagnTjXjtmdepzSWZK59msTSL5Qs++6e/x69+5jM885XnefKjT/Laxot0OnuItMV4MOAw3GZh7jSL85dYnH+bW998g70NlcKTRcrzVfzkmD33bYyORmz77B/sYw5NUmOT0D8Jg3k3siSQQ598Mker1SJwA6zYJPB9RCxwQ5NgapEXJfrbXbJpndJMHs1L09saEEqChJzBGBskFEExryP5KklSFDMltEjDNixKpRzZrITttlEUlW67heuExH4SdEEyobK4sEQURhg9n8hP4ysya5cuMuxb1D0JbeIQTSCIIo5aOyiKwmQ8InA9bC8gvsfr2z13gKqiMOn12dze4qOf/DiVSoXT508xCvuIQFDKlkkJizAKCMOAjK6Ty+cZT8ZMNyec+9AZXnjmVYKJxUDbp/1mhtW5cyTlMbbRZO9gi6Sb44mzD6MmDa5ubvL2ZIdcbZcwMcFTpuCbqG7Ai1/+Eh/9RJIzlTqXfuY/5cmHP0ijsoiSSCJJMWoQEwtBMj5WNwghiKIY1/c4MocE8Ukc4N2QFBnTd/FDF6s3pFStgjymu9PH7PT4yKfWiTIKlnWsB27tH2HZFpPplLExIZgEGOEQXRUcXt3HDAwWLz2A15VwD8eomQjfn6LnZvmzr3yehx++wDdffYVcrsrYsTga9ChVKux3rxOFx1pR3/FI6QnWHzhL+/AIVzXxPUG1Mo9pGkSOIOoZGIcjFvQiG3aHydQkPFkE+S4UWSahaSQ8D8d1GI/H5LJ5bNsmio6TXgQxWJHF9s42xVoJNZHAN4/DYxQ1AskkCgM8V0KRcqjJ6Dg5yrCPJCdJz+YAyOcLMPUYDvrcvNXFcVwW508TxyEJVYOYY11wIcHUMBiNRhDFpBIarqoS46BndKSxhdsPeOQDj6FHGTwroLO/zejo3qr+/QDpsCCjJjElC11O0N5u8/iHHmO7uY1rehgHXRzNQJZkFhZmsb0ck/4Qd+pQ0gsY/RA/VJF0By3I4qoRY3/EY4+dozG/yNMP/SwPLJ5ntjaP5Yz48pe/wXNvvIJkDZhO9qkm0sw+8BPUM6sslpd59MzDVEt1JAEeYAAyUESAEEQC/BA8LyAMo+OErVHEgTHEP6kZe1fCOMKLI7Zvb9A82qHnwic++QESfopOu485MZk9U8ENbUzT5JlnnqFULZJOpxCS4Npr1yiey2EHMre+fg29KGN1BpgDmWylTJwWSErArY23yWSztHt7xK7gUx/96/z67/wOUkZCVlVcxyWMImzD4OjwEH31FCQTZBZnmKvpqNmQ5tGQpKbhOD56uUC/OSSdz1JfXODgoIl/MgL8LmLg9cuXicLj34S4o/HuDwZ4rkdqVkXPpdnY2GAynjIzP0Or1UKxVE6vnsMMBrj+gN2tFo4N9VqdUkmh3zMxDJNSKWQ8GTMYt3A8F1VRKRSTWPaE3YPr2K5JLp+n2+sDUK1U8Xwfw7KYazQoVyoc2T2SyRT77U3WZ6sk1RRnG+cRU4XpxKbfHlDL5THM6T3Z4AfoACMyyQRhocjlV16ntjLPTvOQVCFDPlvgdvs2N5pXyRYLLK+sctDZpt1q0Wu2mVkoEVsxv/h3/zaf/91/SdyXyTXyFAolTp96mHNLT7MyU0fXQJEgrVb4pZ/7eT7y4Y9zY/OAmxtdFL3KL3z6AvUsdC24drPDH331TUaGh2cPKRU0Mvkkekajls0QotMZBAxbR3Rb+1jjASEhRmDjeidC+bshKTKV2QrabpJhr4uQdWYKdUrlGvkHZuh2+sxLc2QyKn4qQlFUstkcru0gQjC6QxpnC+zf3qO5dcS5p5YRY4PYVimurRIXTI7auxzshKyurjMaWPzSZ/4u/+f/9mvsjQ5ZfLBCd3BEOqMQGDGh5/DsV77I5PEuUSRI5tPkCgVSWRnP9dDUNF5g0rT7rDxyluneiISXR2sfZyg/4bvxzIBYipBliXQqRSqpkdY0zOmUzGyV2I/Z3d0llU4jhISIJFzXw3AMio0ck2gfZDAsn1P5CkIdMzWmRB6EbsztG9tEwkTIU9RkQL6Ywx552KOYUvo4ocKVK1cY9UdYU5O5+VWW5xeYma0wMYZEgU86o5HIaVzbuEZ9folMIcvl19+gWqkSRB6ZSpJzC2e5/JW/wHRYQgJSUCrV0PQCK0+e5vrmDRzLZnZxjsPpBvlSFdVN0O4c0W+1mTR75MmRSWWozucRcYhI5pn0AypymoJcxp8q3N66yZUbV9F0BTmSefrhhyjqOvs7U958pcvVzSPI7CDpRyQVh8/97nO4kx5LFwsMfINX33qJynyRXLlIMp1jaXGNxuwSnYMO5v4QKYjYuHWTop5FMiwc27pXM9zXqIrEpN8ipWoMA4laSuK1V18mzGcpVFOosk6vY9He3cZtGczMzXLh4oO89fKrGEdDEtmIaOxRTS5RPX+E4bjo2SyK7aHIU/LzGntbG6hcYGPzTT79kz/HH/zrz/LaF77I0kN1mq0Rlt/EoYOSlZi1M1zdvcm1ayaz1WXyqk4wtUnkKiytrGIaJsPhEEWy8Zkg5yJEUbBcOsvVl6/8xzbnXzoEEilNZ2oYNJbnaO5uo8QRnmUiC4HiyEjIzNTrTKZjoiimqFUJKwEGJhlNxQpC8rUqXuwQJ2EaTWh32yzlz1FRaxhGl0QqQIgx9riNUGfxDjUyE51sOUOQ9FlqLBIGIWsLa8wvnMPxQqyJQa+7hyxiKvMNosQa27vbaKmAQfuI+kKOhfkarW4bA58Lq/P3ZIN7T4kvy3jZFIEcUVmtoGgqZ8+cQZaOBdb5VAEpiHj9+mXiGBKTiKyXIpFJEw5VNl/c52j7ZUbdPsVkHUyf69de49yDa6jlmI3mbWbjEku1UygJGUlASSky7m/Ssr5BrI/5v58dE00srC2PS/UGajwhUkzOP1hB0RWWV8+gpxZIJEMSqRF2uIfI5ShmSoS7IXu9bS4kKygnYTB3J4hImgFZX7CoF7GET3PUp7yywOaNW3zo8Y/gqg79gz6SFXLx4gU89/hWZ/9wj+Jyjqkac+78Ok8Xsjz7pc8hmSEz9QWIZCwjQk7pDCZHnD67xtWtV/n9P/wCi6UaoR/R2uogF0NsKSSdSVIq1pnNTimIAlklT2804Y1rb7Nydo1ms4ljOyhJmaWza+hylva4g5aIaO41CU+mOb6LwPdxA5dqrUK9VseZjHEsk6lhUCwWcRyHWIZHH32U1y+/jjGdkojSaEmNwPcxDRcnEihSxOnTS+QLaZqtkNnZWVT/OHluWoeEroHIYw6GdLsDCBKUymUUVWFsjInjmIsXL7K4sEhvfIDjjxm2e6TSKslElkKhiGVZpJIpQmIWz6yzublJfWWBaezSOthga3PrnmzwA4wAFYSSJJNPoqShP+yRzx1r9eozGZZqy3z2+ZcIwgCRjBmrAes/dolb197m8p99E8lNkZ+vUJKyiFFEablI9iMlBpGBbszw9NlPkcio6Goa34uRUtB2txmGV9CzXSzLRFMicpUckwqks2Um0wF+Amr1FZZPn0NOCpq9q0S2i300Qk5o5JbzlMsJLrDAznUHpzUB6WQZ+G5EccTYMogkSOgptEKRykOnSFSPv5CVWpWxNKRQLKBpEjtbO+TyRfr9PnEM5VKJarGIZ9ncvHKVlJokdhJ021PyiQynK2scTQ9JlCP0SpHNvedYvDRDcqpSK9WR4jxKzeFaq8945OD220z2HUqySmG+iJuJKFWLOI5NHEOj0UBOqizMnWZwNMR3JUqFGZz24UkHeBcc1+V0vU6xWMQ0TYQQWLaF67moqkqpVEJNJdCSGqqq4FoBIgwIzIDAD3hw4REWM6cwzAGWPUJOyKTTaTJzVSZ7EXt7u/SVfbKFFNlsGhFlKVUSxBOZJEm2NrdQ5pOcOXuGQrFAr9+nPdgnkh1MM0BVCvT7E2qFO5rkIKA16OAXEqRrZeR8hlBT0TM6vW73nmxw7x1gFFPPlVGy4I0HTL0I27S5cf0aejKFMRhy++Ym9ZUaii5TTGXR8xGZVQ21UsS47RGaLklNwZyatHZ2WX6yhqY5+HqX3/v655FNi/Mrj/Gzn/ib9IKY3/rav+L8U3WqzQv8/q8/w4MfrhCLMWZaZaRO6fR3OX3pImcunmEwtLAmbSx/CznUCRxI5HV6Rpt8KYmSlXBVFycn4Z+UTLwrsSyRnK9h9CQC3ydV0pESCoqm8OiTj4EnoSkatVKd7b2btFpN+oMBYRySK+XoH/Wxv/wyzuB1zMGYjK5RKJaxPBc/iFlYWCefqbC3d5Pd5g65qka0lKF7rcub194gSqfIyRppkceNPGzXJ6sVycslRr0JBgaNuQbFUoVypUg6reGH0Do8Ytw1UFSNYrFCWtL4pnqSDOHdSJJAkiQm42M9vGmamKZFMpkio2dIyAmsqc3BzgG9dp+CVqGYKzAY9XE8GwSk03mi2GF3/xpBnCapJOj2e/hOAj1X4MNPPkV/MOT5b7xIozGLFkAkQizXoLE4CxWVtaUVbl6/Tq8/pjxbYGenT0arki2vc3P/W3xz8BxRHOI6LkEQMbAmaJrGUb9FKMcsr67cyVj+8nu2wb0vgoRQqmfohW12NneYWlDKFrAOmty6cRtRz3H+yYdRZIHj2hT0LJ29Ht4wRMk6BHkbYUdM0JEbHuuX5rAmBqrIUEqn+MhDP8Op2UuU8kWmzoTf/aN/TnN8yKXsabxeTHl9gRCfUNOx1Q1y8yusrH6CtfJpDow+1559jvqZCmq+xs6fbHDx4x8nQmX3ypvMyPNM2hH2WMFzbIKTokh3RUgSI9smSqggy0h5lcg3CXoBtudBnObcufO8+fKr7G8cUCjncDyXhXPzSLLE/pUD/KshsfCp12fpdweMrDZrj5whv1JmZIzR0zI7u1vkChqxnObGlSHJdIioTTj70BK3X9ogPoDy+SLWzBQ5yNAPTexWh+xMmlNLq+RKc0ytbY7aN8gmFnCMfdKFGpM0ZFbmcHUDLXOiBHk3iqJgTIZ4nkcqlWQymqIpaQgFO9sHTNou9tghlU5RT84TTEJG4yHzZ+ZIVhIMvANid8JoOsL1AnxHIUbCijyCjE2ccsk2LlGtP8jN17vokUtJzbGvHkDGp7SwzHLjNNF+E2X3iIK6AJMK6cEAPYioL2ikYo3hQYdyTUYhiWG46CWPlK5iez2K1SSqlsY0zXuzwb0aTwiB67oEUgBCICSfKPKIY1ClJOcvXSA3W8Y2HOJYRpGTHB01qc0UiSWXXE5CTUAc6Vx6aJ1Wa8hg4rB5u821xB6rq2fYaN5A0zJ866VnKVYjGoszXL92g6xS4QMf/ADDwVuoMxLCMdjc3MTXHR6fOc1gOOXR+go7ow5mJCFFCUzDo1DOcuutKxj9AbKskFGT2I5zUhXzexBFx0XtYzMmX85jMubW7VsU8gUMY8rhrRZf/XdfYGx3yZaPi1UV0qnj25lej1K9SEpPs72xTejEyIFKKDuY9pCKViKMHLpdg+FgQLkyx3g8plQqM5oeUMikeOiRBzH2DK69eYO6VmZo9BBuxEx1jtD1WVs5S3WmzsbuAZE8IZvVmXQM7LFPrpRiMDjCdgwSmnpczP2Ef48wDLFt6zuJUbPZLMuLyzSbTcbjCY7lMJ1Mj7XAscD3AjzPZ39/n8dPPYoZHOuATdPAsi2ymSyKclwFMpfLEoQhjuOQkGM+8NTT7G1+i2wmS32mztHREbt7OxTSZT5y4Qyz2QRv7boMo5DRcEwcKty8cZ3a7AzVho7pHDBTWyFTjehZhyRU5c48pUscx8fKlXtA3POBQnSB3Xs6+C8fS3EcV/9jf4i/bJz4+P7mPvMv3IOP77kDPOGEE074q85JtegTTjjhfctJB3jCCSe8b3nPHaAQoiyEeOPOoyWEOHzH6x9ZamUhxH8thLguhPit93DMrwoh/o8f1We6Xznx8f3PiY+Pec+rwHEc94GHAIQQ/xQw4jj+X9+5jzgusiHi+IeaZuW/Aj4Ux3Hrz7OzEOIkyd89cuLj+58THx/zQ7sFFkKsCyGuCSF+G7gKLAghRu/Y/ktCiN+487wuhPhDIcSrQoiXhRBPfZ/3/g1gEfiyEOIfCSEqQojPCSHeEkK8IIS4eGe//0UI8VtCiOeB33zXe/ysEOJ5IcSSEGLr24YVQhTf+fqE782Jj+9/3m8+/mHPAZ4F/vc4js8Dh/+B/X4N+GdxHD8G/E3g2wZ9Ugjxr969cxzHvwp0gA/HcfxrwP8MvBTH8SXgn/LvG+ks8PE4jv/OtxuEEH8D+G+AT8dxvAs8D/zEnc1/C/i3cXyvKRXfd5z4+P7nfePjH/YVcTOO41f/HPt9Ajgj/v9ylEUhRCqO45eAl/4cx38I+CmAOI7/TAjxm0II/c62P4rj+J35rT4JPAF8Ko5j407bbwD/CPg88CvAL/85znnCMSc+vv953/j4hz0CfKceJeI4AfO3Sb7juQCeiOP4oTuPuTiO7R/BZwDYAPLAqW83xHH8deC0EOJjgB/H8Y0f0rnfD5z4+P7nfePjH1kYzJ2J06EQ4pQQQgL++js2fwX4h99+IYR46D2+/XPA375z7CeAwziOv5cYcBv4T4DfFkKce0f7/wP8NvCv3+O5T7jDiY/vf+53H/+o4wD/CfAl4AXg4B3t/xD44J3Jz2vA34fvPXdwF/5H4ANCiLeA/4nj4e/3T7MLeQAAIABJREFUJI7jaxwPj/9ACLFyp/m3Ob6i/Jv38P+c8N2c+Pj+57718ftWCieE+CXgx+M4/g8a/YS/upz4+P7nB/Xx+zIsQAjxLzmewP2J77fvCX81OfHx/c8Pw8fv2xHgCSeccMKJFviEE0543/J9O0AhRCiO9YFXhBD/VgiRvteTCSE+KoT4/L0ef8KPhhMf3/+c+Pju/HlGgPadGJ+LHNcc/y/fuVEcczKS/KvNiY/vf058fBfe6z/8HLAuhFgWQtwUxxkdrnCsF/yUEOJFIcTrd64wGQAhxE8IIW4IIV4Hfv77nUAIoQsh/kQI8eadq9Uv3mnfEUL8MyHE2+JYd7h+p31ZCPHVO0vxzwghFr9P+28KIX5NHGsPt+7IaxDH2sPPvONz/LYQ4ufeo33uB058fP9z4uNv8+18+t/rwXGWCDheMf4j4B8AyxxHiD91Z1sF+Aag33n9TziO8UkC+xxHbwvg94HP39nnMeA37nK+XwB+/R2v83f+7gD/3Z3n/9k73uePgf/8zvO/B/y779P+m/x/7L1ZjGTpdef3u/sW+5YZGblnVlZ1V/XOXtikKK4aSPbINj1jWSMDHsCA4RUwDAz84ifbMGDIb/M8mIExhgey6TEsayRSXEbsfWF37ZVVlfsakbFH3H31QzalHrIpikmNyGnmD7iIixsXEfH9z70nvvt955wP/k/Onf+TwNZHx3/9Y+cUOQ+8lH+aPp+G7dLGv3gbXNr4F2Pjv4pwCXDzo+0fAupHwu1+7Jx/G+h97Lz7wD/ivNzO9z923m//sMF/yfdtfCTS/8J50vQPj+8Bqx/tK0D/o/0eoHzseO+nHP8nwO997HOnH9u/B9Q5fzz4X3/RF+3f4M1xaeNP+XZp40/e/ipxgF6WZf9Kiotwnvz88ZQVAfjTLMt+90fO+1lTY8iy7JEgCM8DvwX8T4IgfCfLsv/hh29//NSf9bM/RvDxn/mx/f8N+I+A/5CfEpX+KePSxp9+Lm38Cfx1DXq+zXlKzA+f5y1BEDaATWBZEIS1j8773Z/0AT9EEIQ5wM2y7J8Cvw88/7G3f+djr299tP8m5w2F87zC137K8b+MfwL8N/DnaTeX/AWXNv708ytn47+WTJAsy7qCIPx94P8QBEH76PB//9G/wH8K/JEgCC7nPz4PIAjCZ4D/LDuvEfZxngJ+XxCEFIg4H6v4IWXhPG8w4C+M8F8D/1gQhH8AdPkLj/+Tjv9l7egIgvAA+H9+hub/SnBp408/v4o2/jcmE0QQhD3gM1mW9f41focJ3AGez7Js/K/rey75ZC5t/Onnl83Gv3JxPz8J4bwczwPgH17eGJ9OLm386edntfG/MT3ASy655JK/bi57gJdccsmvLJcO8JJLLvmV5dIBXnLJJb+yXDrASy655FeWC8cBmjkjK5ZzCKJIHMfIuoQXeH8e1y0qEnGSIiOjSApxnJy/IYAkSqRpQhhFxHGEosromgaiRJam6IZBGAaEoYuVy6MqOlkmkPkxw7MhsqailzVsZ0JBrVIvV4GUFIEoDjk9O0VWZXIFkzSNCcKETBCJgogo9LAsC1XTcKYO9nBK6IbEcSL8xMb+imJYepYvWsiyRBTHyLqMH/qkSQqArEgkaQKZhKbpRGGMkJ1nGJxnGWQEYUiaJggCyLKErKgggGGYBIFPFIXouo6u62RZRhqljLsTZEnGKls4/hACBVFVEaUMTVDISPGjkEwSyRVyJGGEO7LBT0iDmDCJkHQVRIEsSREQ8IKQMIoubfwxjIKe5csWcRgjICKKEkkck2YZaZoiiSICAqqqEMcxCAKqopIkCWmaEsURqqpynlAiIMkikqaQxjGBHxD4PsVCiSyDyWRCmqbkihaidH6fIwhMxmOSKKVcriDLCt1uD1mRyOfyZFnKdGqTxAlJEpNlGaZpkgkCSZIgAFEUkaUpiqLgT4NelmX1n0WDCztAK2/wO//5v4UiK+iGzo73mIEzwNANZElGLIuMJmNUT+f64g1OjgakyIiiiGXlODjcot7Mc3x0hmsHJBnMLM+ytLhIrVbn/oPbLKxKNGcWWFt5mtdee4/kRGL8YEqpaPHs37nKn33wHb5+47/gt179GikeARI3D9/nT978Y7S6zNqVRVLPZ/P2Lu9+/xbjic3G8yvk8wVmm7MUrSIP3njMP/6f/9FFZfhUY+Z1fvvvfwnLyqFpKkfxEf1pH0M3EEUJNR8RxB7OJGOuuU48FUicDFESUVWNid0nX5LptAeIKKSCQKal5PN5ZmZm6ffPmJu3UFWFJ598ktffeB3/TCLblVFTnRu/+QSPeq8R3c9RvbrBQfshi8U6C0/N0RuPUPMWi2ureH2XO//vW4zfPcQ5HnI27CBm4CpgzDcwBYU3bt77Rcv5S0e+avG1//JzHDw4wsBitjbLeDJGEARs22a23sCeTCkUCuTzeZIkpd3uUKvWUBQF250ydoYAPPXUU+zu7dCfnFGsVVi7egVJUUm6Id/65reohDqVSpVnfv0pmgtNHNvhu9/7HqlbgUgkjhRm6kvsHexSq5cpFApUKhXu3rrNXKPJ9s42YRDyld/4KoedNmdnZ1iWhQDEjkun02Hrtf39n1WDiz8CC+DYNrIiE4YhruvRarVQVZVqtYoXTFG0BFGO6HT3QUiQZQVN03Bsh2arTqGkEoY+X/va3+ZrX/1tPNfl9ddf5/bt2ywtLeIFI37w4VuctHfZ2XvAQb/D4voaWZLw5re+i6WbtFoLkHH+L4/HyeSYWA2YphPknMzh4THf++M/xT3uslys4fkBf/iH/x+v/dn36Y2HLHzhebRC7sIyfJoRBQHf9yHLkCUZz/VoNptkWcbs7CyiFIPgE0ZThuNTkjREUVTgvBdYLucoFBUmkxFP3fgMr77yZRzH4eatmzx8uMmNp24gShHvf/AWh8fbBNGEJInZuHqVUqnEd779bbIsZX39CkEYEvg+vWBIO+0xigbs7t/HtYdsbm5yeHiIKAqkAsiiRDWSyIWQkv1cyaafZgRRIJfLIUkSjuMQhMEP84NZWFzk6sZVSsUSrusiSRL1eh1N00izFEmWiOII0zRZX18nCAJkUaSg6FSLJdS8xcr1a2xtb2OZFouLi7z8yktMp9OPro0Sc80m6+vrzMzMksvliKKI1dVVgiDg/v37HB0fE4YhvX6Per1OpVrh+PiYOI6Zm5ujUqkgyzKWZaHr+k9p7Sdz8VS4LEVWU05P98gXCpRLi6hKAYE+AhWKWogXjfAEn14yJPNi8BOqdY1MnpJKGm+8tw2ZiJM59NqnOAf7CFlKEjtUamWuVb7Gt958DVnKsSJXqCwtUFiqc/zH2/SPZD5z7QUq1TJxliKnOlHYYTQ65s6bd4hiia3v7mMP2gTjkDiImU6mMNaoJSVKioU9HlBYnEEzlAvL8Gkmy1LyBY12Z59ypUKSGiCUqdWrOG6C7alYxRlUc4QXOcSBDk7CbCtHnPUIXZ+7b22jqgZhv8Pj2+8xOTvFEkVyskj/8JgXXv4qbtxAE+dg/4Dq/BozG2scdl/DCgyKhRxH9h72icx6tYm1JCEoMbfeeo/MznjwnceoWZG6mmecjfFMSBODgZESJDH5VEaULp98P4kkylBSnbyq0/c7xHEKXohqwvyzTXzbpzs8o1QpkQgxXbtNadEgjiOmUY/iskWhWcY0DE7bbaamQ7Fcoe861COVd753k8CJ+Qf/7X/H//WNb6BJBtZAo/96m42X15h5wiDquhw/HmMZLSQ5BT9ACjIEYibBGfUrFTTNIo5jvLHPGIfVpadQFIXBoE8i+WhZxPh0dCENLuwAFU3FqhQQNIl8qUBvPCUUPJ588ll8z+dsf4/BZIiqaiiqSCrGSGKMpucZ2zF7d/fxDkfMzDTYeus9Tk+OmJ+rE6si1WqZzUebrH35t1hff46ToxHvfO8H/N3/YJVrz63h7rVx7u1SNevkDf3cAUoi/fEZNz/8AYHtUyrOc/Ot93nhxlWefuk53n73HUIvoVmpYOY06tUq860mopAiK9JFZfhUIykyhXoJ2VRQVJVSYpEmIhtXrqHrBh/ctzk4eoRlWSiaQhpnpEJAikG/P2DY7SMpOoIscv/RPU47p1x99ipxHLM438JzHEJfpNFYoN+b8PjWNs/Xllm9ssDgZJF79pDITZEUhW6vw43PPoNQEnnznbskbp712Q0+eOtDrixXqBfL7LX7oEho+RxxHKPEMaamEybxL1rKX0riKGbUH6EqCqahkyYpedNCUEMSMWHraIvMSCk1S8iSRLfTRVEVxuMxsiQzszhPpVJFkiQm48eIkoygSWiCRhJD3ixy7Wu/jlZQMUs6WwePCc8cpoc2fXuA9FyMZRqIAkRBjChCo1pBlVTqixXGyZD6XI1Go0W73aY+Vyf0E1JiWgsLuIHNYKcLgsJkPL2QBhd2gEEUMghd8uUCW+1jnn7pc9RnZsnn88RRwjjYR1QDJEnGD3wCfFRdJQh9jg4G1PNNnnhunV6/z/DkDDFMmJ2d5bB/hqZpiJpGr+sgYvHg/h0MvUSne4i5f48knaIaEc1CnoKk4SfnWdW3Nh9y+9Zt8uYsxVKBF599ESsUOLp/QtLPMOsWiDAcDdGnKqqqgXw+LnnJjxPGEYfDHtVKhc3tba5/5hUWllcol0qEQcTS4iJIHlEUE0YhkhKTKAlJHGNPUvLFJo2NKoPBAM/zyQyVOI5JkgTbdZidadI+PUEuWtzbeky5UsJu73Pnve/jRmOEKuiCycFun/WNdYymxoebm0xGEflcnUK+wec+90XscZ+TkxPiKCaJImRkTMM4r/emKIRx9IuW8peSNMswTAM1ATFIqMw00OIExczotDscdg+YqzewGSOkMHKmZH2FRmOW0WhE53DI2tIGd+7c5eZrt1ldW6aUK7C6usJ4aFOtzGDHfW5tfcjSkwssi4vcf+ch/VOPR/ePuLq4iidNqVQr5IwWmeBjjydMJhMKVo7F1iKZIjLXbFGtVImiiO3H28hqiJUXSTObna37xKUmonCxXv7F73xRBFNjGLq4JExsmzTNGI1GnLZPyRfylEpFMlIajTpWTkYQPVzHQUgNSjOLHKcu5WvLXPviK4i1Aq+//jo508JzPaI4Jk1UGvVlFKnA8sI1RuMz7tx/l5nZPHPzZQq6hoiAIAr0nYi94w5f+8rXePWVV2k0Znj2+nNIjkzQi8hnBQRPZNDvYzsO/UEPz3dxPe98RuqSHyMVoDjXwBNTPCljNJkwGU/o9wccHBwQhgGmZaKqCnNzcxTKBpnoMJ6MUaUC1558ntPpCKNW5sUvfYEnnnuamzdvUqvWCPyA+w8eYOVy1Go15uZaLC8ukRMSNm+9g1EUaazXECOJklxh/co6e/1dfKHPK5+7wpe++jSFSsDMnIVt26RJgmmYGLpBrVYlZ1nIsgyXY4A/kTiO2N3dQ5FlGo0GhUIRURDRVJXRaESqJEzTMQO/z9HwECOfZ6a+AqmOoVfwJjGd7TM62x2qap1omiBKIlkGYRihGwYH/QPu7d2hNF+ksVLnt3/v61y5fgNVKNLKXUETDfzAR5JkKpUKs7OzLMwvkCQJlpXj85//PIKQEScxYRQxmgzxgiGCFPLcC0/QbFVxXffCGly4ByjLEq3WLPfu3mU6HTEeD+gPCjQaddI0QsxMNKnB9Y0b+EGAEhU53jsgjgJe/rUXEJSMg+mYQSzw1S99lUozx/vff5fCepmd+4+Z7no0//011ipP0Jqpk5k5cES2PzhkzISXX/kS1xZvAAKZINHJjpk2HyDJMRXJoPdgiO5n9Lt9lLzM4uockZwRZQLamYDi6QhujqQoknE5RvRJKLJMrVri7t27DAdndIsVdEPFMJcxcyr+1ESX68ytVEmzjFzURxgKOJnA4o0NJt6IKB7g+CEzzWeoVZ4h8G2kWZH2nQPO7nYpFessXV0jDcbUrs7SHah0Hu+y80ff5drnX6KSqyBlNqF0hlFRaFRy2OEh1byJe2STSy2yQCLWZIoLJaQ0Q58onB2fkKWQBQkyEsKljX8MVVKol6okwNRziKITJEEgChXcQUDZqBIEU/I5iOIAgQmV+jw7OyeYeok4TNg92WESTGgsNej22mzefUj7sMt8a5nh8ADb61MsFUhwGUyGvH37A0QppFwUESQDo17Ff3SAZkrIWUShYbH27BrdQRvFENBkDV2rsPPggHsf3EJBpHhtnjvv3eGJ56/x5d/8Io/f2uNRuMvwwPlpTf4xLuwARVGENGE6GUMSc9o+wTBNgsCjUChQUKrYdkjoi+hqEbGsEHopnU4bpJid3Ud0zw7JWwqKHGPldK489RSROUQUU8LelPv3PmRr9wFRFLK4tESspBRjE8dN2Ow+QtENQCUCDjr7hOkYU7GIkggzZxAnAiuvPM1UGGPNGdiBy/5rm2THAwrVCuOeS2W5zgV7z596ZFnGd2zSOKRaLtPvd6nVanS7bVRVI2eVGI4c+l2bpeUlfE8kriWc7j6mEIxpdw+w7T6qCoIQ0u12Kdfr2Fmf2YU6g5tdup0TDg93SLOM+cUF1JLC1acXCEc2x2ePGSYW5VyOcBCQa1hM3QmKKDMa+GhmFSMs8cpLr3Iw2qO4UkRIUj785+8yHo6oqiZCmmHqxuUwxycgCgKmbhBGEU4QUJQN8sUiO50TSvkyTuxQa1RIcfCSDDcc0h0doFkikgySouKnPuvX13j06BErG6usri7xxptv8P77b7G0vMjqjUXa7TYf/uAWzbkme48fs5FfZGljjpu3b1HeiNi4sYHqSRzv75HoPk9URMLUJ7RBTBU2797nze+8gRKmXL/yBFt3dzmdnJDICQtr8zzzUpHG3AL/7IP//WfW4OcqiHr//n2yLKNYKgEwndosLi4iyzKPth8jqzLFYoE0y5gM+yRJjGVZhGGE5/vMt+YpFIpMJlMePnzIeBBQUhVWV1fxNwOKZZXdox181ydKJlx7oYY1N8vpyZTmch3BhDiF8Ri2PnyEGbVQxwpeLFEpzlFrtXic7uFNJtRmalgiPHr9IY7vIbkOBwcHVF9s8Cu4GuBfCVmW+PDmTYIgoFwuYwoaw+GQVqtFo9Hg4fYWuq5Rq9VwbJuzUY+JN2F1bZXQDvB7Y55//gXCMCIMQg72DxiOfMrrKtVKlWqtxuzMLN1Rj/Zpm9FwyPWNJbSJS2TbrC7W0fQ55Pg8UPrOu3exVJVUVEnklFK5TN6ssr21ycgbMbNRJyVGkRVM00QRFLIwRlUVpEsH+GOIksRkMkGWZUzDpD/o44UBmqah6hpRKJAlMmHko6ll4sBhNBojZAaBIJIz8+iqxtbjLdqnHZaXltje2WYymRCFEXGcYGgVrj85z+PHj8kSnZpW4MpT1xkOA6bfeZvmRglRkhgMhpTKZaqLKqIYcOvWLexJyhvfvwNxipGJEIacHR0zTSNKpSKSLCFIIuWFPKPgZ+/9wc/hALMsY2dnG8MwmZ2dRVLyjMdjptMptXodWZaJoxhBFNnb2iIJA/K5AuVymbfeeptC2eDzn/scSZrS63U5OTnBkMuUKxVyoUyxWCRKJ0hKSKmmopsp4kDi3Tc/YKaxwuoT62iiycSFnUdnfOsb/4J6yUBWRVJTpbGmcWIPePTaTZSazJWVOrc275Ev5tGrVfKVMkHos7e/x2VJsE8mCEJ8zyNOEkzTwMzVmNoOk+mUfCFPkib0+wPKlTKD/oCB51CZm6GsGvyLf/Z/kyuqPPvcMwz6Q7q9Hu12m3J5jmazRjHRqFVrHBwdEqUxKysrxEnC9qMuW2+8z5OrG1imyPNfXGexsYx76vPtP3gbxil5M48jjJjdEDmMu2zfvktlqcRoOuLBnXvkVA2tXALbJ/QDgjBElC4d4I8SRRFZlpHL5dBUDTfKKBSKOEKCG4bcuP4caZZx687bTO0QXVNRBBnfTxBESJKE/ZMD+r0BqqJy//4DhuMeV65cIc1SKtUqJ8cDXn5lg3ZuzMnhgK2b9/mtf/fvIjcE5m/tQuQg5xSGwy6LV1YpFiPevPUG41FAo/YEj+495un1ZYozC2zdvIslKRTmZ5kkYxozDQrFHKqpofQvFslx4avCdhzMXBHdzJErlDAKEs+/8AT1QpH9u4852Tlk1Bsy7g4J7ADHH2HWBVx/zN7mDq3qAvOtNRrVeYY9F0lRMWcV8oZOOW9iVkXee+tthChhY3mNxI944/sPcCZgCWUK8RwxJsc9GDFh5ZUGJ/snxHsJcTtmdDDC7oxZrc/RVCr0PjzFud9HdwTW16+hWQV6R332bm2TxZeTIJ+E4zjEqUChVEVRTUQt5tqTKzx3/TrbNzc52zvF6U+ZnI0gyEj9CaQDRqMOtufSbF2hWlhjbnYNXdEo1nOE+RBVM/DDgOJCjuPDHaQsRpUyTE2mve9jVdYR8lVGwylHRweM3D6eOOVv/e6XSZKMuCtQyPLovoQeS1xbu4ZFjsdv7jDZtRFigZJZRBM0NBSEKP35lt75lJIkKf3RlP5oQHfUxpwpcWL3Kc1UePq5p5mbW6AxO8/i0hpz8yuUyrPIqkUGCHLC1B3jxwnPvPgMtVYRsyCjpDLB1EeKRLRMxVJNRmcDNFHl9OCYem2G2++8z+BwH1VLUBIJuz+gPKtR26ixeXKKHahUaws0KnN87tnPItgpj24/Zjr2EUWDUddmsj9kcjhGkXNMvZDW8tKFNPi5HoHrjSarq2uIooBWTMgVFDI74PEHd7GJSVWBSr6MnEpgKex3tuhs9SnlDNYWV6mW5rClKQWrjmENsSoqUiIyHo/RayrNyQZON2Lzg1MWFpeQrsVMJx0qrRnmF6/ie3A2jBlL+yy9WqP34JR030fPdIIzmzDLaM626PV6vPfabYhi1GLGVm8Clk5/3OfUOSIOLuPEPglZUWi2Fpibm8O0LORcQN5SON3b5+jBLn3fZhq65BSDRqPJ9dUl2v0tdna6VOarrFx7AkOtYZk5trceYlgm5nyNSr7GWXefcTqlVpxndOZhDw65cmWDa6tLOOGUmVaBTmeHB7c/pFotkqYJbs5h+fk52u8MUWOJk3tbkIlcWb2KpVrs3z1AFw2GowGpolNWDLJMIQpDhOxyoPfHECTiTEQ1NQpFFV9M6ThDCs4Yy8+huC5n/QGpIIAoYuZK5HMSQXyC59r4Xsz6tSeY2GcYRZmVxVWcxgpvvPEGr776KqPBAGyHa+tXsOZaHO/uIco67YN9Ut9j/UYLNxjTGXVordY5tA8ZE/P8Zz+LkZhMTm0U2WK4laJredSGRSSqZEFEITbIxgmhB2EmYpoXS2a4sAPUdZ25uTmSJEHTDCxLp9fr8ej9bVzPJVZE7MBjOp3y7DPPolZkXn/vu9RrIoUnNXIFiTAMiOIIBCjnS7x45RnIMh53H+EJFvXqMrdu3iFvlpGoYlpnrK5sUExr1KsNyGDq9ulMPiQrBKw+t8qOv4mbJiQTlbJZZDIeo+s6tXoNU1VJXIdETBm7DhtXN3DNKSdvHV5Uhk81mqrRaDQIwxBJkpBMGAxGvP3NdwgHMcVmHTFS8HyfZ559mkJFpvdGl+WlHDmrh+Od0h8doOsqulaipM9SCAw6D9rEkUAhP0f+SoV333mP1uwSleIyff+QK9dWGQ4GzNTXubtzi/FoRJKkOK5Nda3MdOhiYpC1Myr5Gv1+H0VVKJZLVCslgvGAzAuRBBlN17AnNqJ46QB/FFEQmJ2ZQddFqpUK7W4f13Fot9vouoZmNVFVFQuLLMsz06jj2T5JknB6ekqtWqRWq9Hu7ILoUygVWG41GMUDpKLA0dEBneMJ+UIBy7IwLYtyo8Dh/h7vbb5La9qiWatSrVRRFBWrmCeRfVKhj2YKuOEJWlrCFVOUYo5mcxYviPBPu8RpwtSxCaMA2ZAvPIx1YQcoCCKljyY/VFVlPOkzaPfZ2tpitb5GpInU87O4rosgQLk0S3N2HVs4wg2nHB49JFR1yqUilWoFezTmm3/wLew4YP25p8g1F8iZMk9ny1RrVcKoh6A4CLLOsDNCRMN3YTRpk0h7tNtdpHyTjS8vI7klutseoi/gee55JRNZolDIM/ZdVEVBEwVqlTo0ypcD5D8BQRTY2NgAMgbDIVOvw3QwQZQkFhaaeEJCq9FCEkW++93v8OLLL1CrLbO1fYfWYpXB8JCd/TvMN9fQtRLjzg7v/MG3iTWJL/zm15A1k0R2ePb5VfK5PMPxHmo5ZmJ3ee/9W1zbeA7dyLF3sMfiwhLD4ZBMHDH3Sp1aOEv7Bz0EX0IyZbyPrjPPc8mSGFPTsBQDWTdATkn3Lp+Bf5SM84mumUYd2xnieR6GYeC6LqPRENXokiuV8VyXKI6IwvPcX8uyyLIMVVXp9rq4noesRIgSHI32idQAX3JpLNfpdVz6/QGbDx+i6zrBgknzSoNiK0cYxZy0jykWSshJQE7MSDKJIBHoDByKVovqTJN8cYmjoyOW1lbpdQfcvnkXxbeJT1IWvScplaokSXIhDS585yuKwssvvUKjPosiq/ijEG8UsLK8im7pxCkUijU8P+a1N97l7Tfe5nT/kLNOh+dffInucMBZ5wTPnTIc9Lh7+zYfvH0Td+Rjiia6pOFkh8glB72SUmpahMMJb3/zXeKxiBjD/pHHcfcWsgBe30PQIuprTfSiju2MsadTyuU6aSIgCRpn3THoeSRLZ3a9yjQ7w3HcvyjVdcm/giwpFHIlpiMHe+wSTmKmXYdqpYasyQiSgmEUCUIQBI133niXt7/3OifbhyixQDB0ONzept1rc3x8wN33P2AydMnrBRQ0TMUg1Wzak218qU9t0SALAv7kG39Ed/eMm6/fQglVHt/eIp4mmFhogkGzOQcqdP0zBt4AUhHPC1FkDcf2iWIRRbUwzCLlyiyNmXUuY91/HEWRMS2TSrXOwUGbvf1jTLNALl9iMvEwLINc3sJ2XFTVwsrl6PaVj9naAAAgAElEQVQ6TKYTZmZnMFSTez+4x8svvMyNG08RZHB364CziY1gqcwszlAumRTzOqYm4jsjFF1k6iYcn05RTY1nXn6FGy+8ypUnnuHWnYfs/qBL71bM5AhIcwxGLu+8+z7D0YQMkdPjU1rVBopqULCqTDsOaZqSXDDd8eJxgILID967yebmJvl8HimIcc4CNF3DiTyQwQumXHtyHU3X2Xt0j7PDXeIk4Rt738ILPdYCkIjYebzF8fEBjh8RTF3KaEQJdIoSth9SUlTSWIWBwPabZ3z9xWdxp3B/+xE37/9zGn0TU6wQS2P01pMM/BP0gkilXmc89BA0FUOWGJ/1CUUNL+lSNjwWrsxgCYtcTgL/ZN576wecnXUxdB05iYlGKRkJgi4gazK+N2VtdfG8xps9RrUHdPoZ3//GWwR+wNrzGoelUzLHI6cE9BQ47nUQ4gR/OEbImcxf3cAwTSaOg+hIaJ7CSnOd6ShkvD9Ckw1e/8M3KBQKzNTmCcjY2d0ht2Kx3FzjbGfAE089wWQyYWtzh2ysEQsGilFmtrmI0A/Isste/o8iCBlOMGV3/4he3yZJJax8CU3TsSwTiOh2jnAm54UuhrrNcDwkS2FldY03//QtnPaY5dYKvmJzOjzDmWYU8hUKxTykAbqUsXnnAxYWFphrlBl0BuxtnUCqk9M83LrM0spVyDJK5fvsf2eP1AfPcAiv20RRiuRlmLpKe/uY0UGHYiZjzC0TRgJHt06RSiL5Yv5CGlzYAcZxzN7eHmmWkWUZZ90zwsAHAWRZIa/75NURhCCIGs2chaTMsnW4Rd7KnQdSyhKu6yHLMsvLSxz5HRzXodfrcXR6xFNfuM7crEQQxBwfHiNYCi9/5ddoXlnj7m7MydkRnj/iw5uPqJbmkTUYHb1Nt93ld/7O76DJBu2TM+Zac0ynU95/6wNGx1NcL8LUZliev4435jIQ+icQRzFpmqJpKqIkYk9sgjBAkiSCIEJRpyiqRDCNkWQJrxPi92LGJ1Ma1Vm0hky+mMcPfOz+gIXFRTI5z9nZGWEUsvlok5d+4yVa8y263S6ubaOV87z6tS/iTOFssoMzHrKwPIPrekRxxNHxIaORjePYfP3f+zpiTkReFmnONpnYFrMvzLD/rQGjkw7zV9f40he/iKTm+P1/+j/+ouX8pSQKIx4+3CTLMhYWG1SqBoqisrQ8j4LJ977zfSaTMaqqYigyilQgxmFr+y5T55S1jTlK5QJirs7QtpmtpFg5lbwsQqKTz9VwJmf0eg5xrCBbRVoLFpKkIMs6mw/u02jOosgyzz57lcnDPpOdCZVSmWickMUZC/UZbNvm3e+/TuyHqNUGcRISKSL7xyd4eZv1K+sXav+FHWD6URXWumWdBz7GERngeR6CGNDU83htl/7uLmEcEhz7GLbGijVHWS8zMhxCIWU4HOI4DoVCgdbceY0xTdMI/BDSPBvXVrm/+QFWMSMT81y7/jJTBNpHR+yfPKJc0cjllhDSBtOzMyqFGrM3ZrBmdPY7+6hLOm5hQlaM+fzXX+TuH96ie/8Iy6xiGjPkNc6LIlzyYyRpSpZllEolbMcmiiIk6bwCeJZllI0ccpBx/OCUqT1heuJiRjmuLz+FaZjYjOkO+uRKBpIkEUc+lmkxMzODrum05loMB0OeeuZpOmcdNEMnyVLmZpYhs/jw0T7VYpX5+Xna7Q6iKBIFsLa2hmWZaJrKQfsQKiL7R/uIMszNrmJ8ZpHlxgxffvklDEUGCTTd+EXL+UuHKIrkcjlKpRJpmiKbAcWyhmkY+OGAOx/cxG73SJKISTDEayzy3OdeZjzd58Hjt6jWVZardTRNJhFMDKVKzaxQLc1SFGc4OmxjaFUadZ07d+7w/POziFgsr8qIUowmNfnB/Xc5OnmEqmjEScT604vcHmySJAn9/RE5VUedTSl+NKufLzeYTiYEYoZg6awsrRBPIs62L7bO+oUdYBInpElKFEYokkIxV8R3POIkRpZl5CBPTqgi49IZnqE5Mmoi0NpYpqAapOMOW6enNJdmMHMG7sjHC1wMw0A3NRaWFtje3WF9Y4nAdvHHNopuIlkavb7L6cmYuZUCemWDezd3EBFYai0w16iT5DPuPH7Ao9OHXHvmCsNxj3wpT6HcpL5WJdmO2d7fYfXJqywvLKBp6kVl+HSTZdhTG8MwEDmP/E/jGFlW8AOfaKKgySYVpYhueLRmIPQC5q4uYykaZx3YH58gTl10VUY0VcLRCEEEQYSFpXne2X6P5d0FDh7tsrO3z8LqOiulHJZZ4yt/+6tYok8xpzCcDJhObUwrh+0NkSR48/W36Q27PPXCkwgotBaXudq4zuoTNygpMlIGSZyBKFAsF37Rav7SIQgCURRjWfnztLiigedNkQSB0XjEw3v3mSnNoSg5NFVFjEFFo16tcdIvIKUBg0GXvb1dJLPB3uYx4/2QvjggDl3INKrVFhVLRMkKNGtNJuEEVRZxvCm2M6JWr3HaPqDVWmA8GRFmIhvPr2MleYY7E/RUIrBt4iimkith5XI4vo9hyNipz+rSHJl48TDPn2sWmEDADc5njoRQpVGoECcxtuPg9T0qlTy6qmDUVFrVKl45ht8o0Ns6Inw9oBSWGbl9cgULugmpGKLn8mimRFm0mDh7bN5/nw+/exPsjCd+a51Ktcrodgl5covaCx7klske7DPt7qDNlulpAhW9xWt/9DbV5TK+75Kz8uQMk4E7Rnuywldn/xbt42N69h56V0a4nAX+RERBRExEpoMpuq4T2VAu1ECAMAJTUKnnypTLZXb3d1krLZDOKiRfNmnf3GTn9fs0mk3GkxC9IuPjkggRZt5E0SUm/piNF6/S3dlj9/U7mPU55hfXQVXw0gmFhgRBTChF+KKDXIBEnVBebLJaXeaP33+dLBNI7YDnnn6R69deYjY3Qw4+GtfNyGSBMMnQ9Muitz9KkmbUqrOoqsry8jKaCgf7uwy6Q/odn3qjSS6fJwgCtILJtN/h3W9+E21G4VHnhCury2iyyJ0P7iGwy6BtI0/ypBjIUo4sUfD9AtVajpVyg9TzqVcEDh7us7OzTxg84tpnV9ndPaFebRGF4CUeV59YIZuInJ6cEDoClUKJTqeDn8RMR0MiVUI0oFC2mNIlDRQ07W+6IjTn6XCyLDMajdBRSJIEURTJspTFxQVWZhewHZtut4tqWmy8vMyZ3uVm2+HuvW3WX7iKn6V4nne+5kCUYVomjuvgBy5Pr17lvbc/ZDAd84VXvsRqc5VkKuOGE6biKWebd4iEkHw+z1p9jq4WYFxbZFlfpOa/htGOyLklqnqVol8h8AL2H+0TZik3rj6PE/gMeoOfR4JPPYIgYJomjuNg6DpJmpwvSCMIFAoF5udbeL6PoRuEVkZrvc7JsIPbcdk/OGOtUiEIU8xUJJezUObLBEGA67qIioiaQPvwiHK9xvorL1DJF+juHZ7POHa7HB3uIZAyMzOHoqiEiU0x30BTCuSsKlKq85Xn/x7PPPU0kiQgZvxFTJggnC+XIHA50fUJCMBoNGJubo6zszN2th8QR+cxn47rkqYpYRiSpufruKwvrzIZj9k52sHv2Dw62yQnWlhmlTQRsKQcbhIRxh6GplMu1qjXZ0kyj16/TRCOWWqW2dvfx7FtCoUC+48O0HMK995/gGka5IwSqQO+55GoEflShdHYxlosgitzcnBKQSsxDSYUjBpzrRajnovrehfS4OeYBRaYTCbk8jkyMizTgvR8NSlN1/F9nzAMOT4+RlN10prCUBiw9+4tpgc2nicyGA6JSh6WYlGv1fG9kOl0Sq/Xp1TKMzlqkzg+z730GUpL80yPJOavzNHTU6b6CVZBAE9BSVOOjo7oSi4LV9ZQVZXrzz1N92TE8VtnHKVtSuUySRDw1r/8LoWFJsXfmWcQBHjD4WUu8E9C4M8LmIZhiCpKxAh4nkcun8e2bWzb5rTdJo5i3JmYI++Id777bdxTCUkuYNtTSustRsNTcvkycRTTbndotVqIgogw9OkenTC38CRxTmd81ufd7/wZhWKRmZlZPvvCrzFxXNqnbU6P+uwePaScm2f1Wo3f+3v/CVdby8zPFEhjyJKPnJ3AR+WvsvNGIFxOdP0EHNfBts8nt6bTKaahMZlOmIzHWJpJkiSomkoQBIycLik+NTPHyNGI/AirWUANdOJIPbdBllAsllEkC93Q0TSNbr+H49hM7AHKicvqygqlUpntrW1OTg8whRrTsc04m1AxM9yD+wz9AZ/90ss0mnOMhyHz8y06Zx3Kd7cZPexjjycUigXm5uYg7jMeTy7U/p+rGIIsyUzHU9I0pWf30FWNMAwplcukccZ0MiGLY5xgQhpL3H3/XW7/yfdQozlK5Xkq1TLWyix3HtzGyOcRBJEwDGjUa5weH1JQM/Z3dtErTUIpxojyNHJNPogeoZQCNp64gjeGxzfvgKwwfHiI/qxDablI48VrJPfOGN3usvn4IYXCAFNVaChVRiOfOEjxvZjBoHfhGKJPO3F0vvRg4AeQnY/7JuF5zKTv+zSKNXzXJ41jSFM8NeDunbvcf/smWjTHbG2NmWaRmeUVvvvGA8qyipkrU62WkSWZk+NjKhWJ05NTMCvowhVUPyLxAhItoGgYFAt19JzEeBRRq6qcnZ3hjlKWW+usNVbRYyDIEEQBQUqABFKVTDh3fqIIWZIxmVysWsinnel4St7MEcURs41ZXNcmjVN03SAKIkxVRxEVup0eW9unhN6EdJDSsubJVYokgkLkJViGSaYoZIKCY/ssLyxRqzbOh8NcF9d18b2Avd0ez3zmBktLi9x/+ABdMZhvLGLbUwRRRAhkLDXH6o1lKs0y42QCJZO90T6iKfHiV17m7e7r7A/30BQVWZRYXlkmii5W9fvnmgQpKBZTf0ocZ6RhQpzEVMtVSCFIRdoHbXJZQCfpU5BUejvHpJGFFGeUZkSMSoFWvsW99DGBmVAsVSiUDLoHO2gZTIwSvqbhRR3ScJtcfg5VKTH1P8S0fPLiPIWywqgZMM1NmfNi3vizN7FqDcZSyMxGjcHtNlbBACnF9UJK86s0n5V5+/af4J56PPPZFTzfvqgMn26yDB0d13EhzZh6Nqqs0JpvYds27YGN600oygljySbLRKbdPpCnXi2T4IDeJBy6WGqOqRiDPGJxZYbewTElJY9ZrrP4okO1YTFfdHm416a8NINu6DhiQGzUUZQUPZcghkX+4y/+V3z1pVdZrs0jZoCUEcsfde8EESERkAJIVAFfhkf7j/nBze/QG57+IpX8pUREQA4FokmAqmoEkwQJg7xWQ8l8NBG0REbyJPJ6jqJvEos2Q6nNwkKZSqNC1/fZOz3FNz00vcZ64bOoiYoeaQiegD/t4ttjvLEHiUriNphMTaRSmVf+nS8wbp/SajTZ3d3l5PQU1RTQmgUm0ZTBhy4De8DKjRZCBvV6nUT1KH1mDtPf4/TgiGapSnnVYnl98UIa/FyB0L7n49gOgiAQOgGmbqLrOp1OmwyNmqgQZRnlmQYj32bo2GjFAqszVxmOpsRJws7WDrKkECUB3cERi9U5BntnlKwya1euouUVDDOhWi2xYi6QpiJJEpAmCVHoEYYTotihVLEwWOJffvubvPveu5SXm5x1uuzu7VKsFPEDnywTODk9xWop+LGLZZh0z0akl2kCn4gkSgR+QJqkiIJI9tFi2VEYocgyfiKQqgqSJqMaGb3pEC+JmFtd4qUnX+Xh5g6CILC9tUWlUkU0UibDHgWlSOAHxE7Gk8svka+a+GEfXVNYXVshW5YRRYGdnR1OT+7ihfsYUsZzT/wuv/HCl6jmIE0zBAlSPhrzE4BMQJIEMGFgu7y3eYs/e+977O/eRrgsh/VjpGmKZVgYukEQBPhhgCRK2I5NoVhEj8AdTVEyhdlmkyxQsLQSk6UZlj67wWQy4fhP3yORUmQlJhJGnLlbfPWzv4k41Xh8dwfP9/BclyzNEBBQMgm7N4Ywpl4qkTpTNEMjFVIkRQQhw8wZ1GvzvPn6h7ieyxV/kXK5TEEuEAw9ZsplvvD5zxM5HlGa4bjO33wuMJzXA8s+CoRWNY3Z2RkGgwHVag0nAV3Wyckxx2GH7ngMeYNr6xsslVYI7z+i3+uRWQm1ehUtL9KbbpNmNYYDD0NsUKvVyKSAjCme57Hy5DLTvsLa2jqb/z97bxZs2XXe9/3WHs88T3e+fW/PAxogABIEyZCiRUqiZMmRnJRlKZaVsjPYZVWcPDhVqUq5YlceXKmKy3mQH2RF5bJia6ZsauBMAiQxNdAAerzdd57OPA973isPp0FCECgRl6RJdZ9f1ak6Z+919tn7+9+z7jprf/9vVQ/Y2btDu91EAitrVyCps762ztWrV0kvlfj6vRdQhPLNdYMNw0Q1NTLpGJdPX0IbmEyw0bWT3UF62JFITNPEtm3CMMQwTOYXFuh2u7iOQ6xQQZUaoeLSdbvsdRrouRTlhTkixQyRWpLJZEJ/NGB+rkI0ZdBrVBkMhjiuS1wzGY+nhWnLcwkODg6wehFWlk+zvLyEqioc1F5Bt8/zkSu/yI9+6BJRLUSRyrfm+MJvTe6pKhzXRzx/7Rvc3L7FxBhRPlUkt/hBvvo7z/3gAvlDipQQjUW/mddpGAau65JKpfA8F0PqSBmysLAw9QhrY7SISXk1jRfVaByO2bh9yPKlCr4/Jp6RTMIdvnbjM3zw4k+gZwwm2xMsy0JVVaSURITGpNmhtrWLknI42N/jxutvUijkObV6CmsyIB6Ps7CwQDq9RbPapHswQHNMggHYE4tXX75GLJ3i6WefoTvss7W9zdkzZ04Ug++iJL5A13XS6TSO4xA34hSKRQ6PjqhWq6xceQwnlHQmIzreGD+ncurCWcwgQTSfYn51mUA6vLnzBvOVOTRd4ssxjUYVXY3gOSrXX7vOwGoyN59GUVwS0SSWpnHu3Fm0fIMXr30Dz58Qi8UZ212i0iCfzxGNxtB1g0984pO8Un0R23coFAps3tkmloyTTEaxbZuzC2u4ikDTZikS74ZAEAQBpVKJVqtFPBolkUjQ6/VoNpssVxZQI1GG/SFETQqZeRZX5zGcCFE9zdzyIplkEvZCpJyOHsMgoN1ukdazCAVu3LiBZobUqjVCaRPX5omYBpqmTtcfrn+CS+uf4skzq8gREAepT0d9ihBoGkwsaLctrr92mz/5wucY6DWWzs9jMcESEzK5NMyqwfw5pJRMJhNisRhhGOJ4Lo7jfHNQM7ZGZB98vxUhqGMxiKisRFRufPlr7N+roaoJRqMJC4tJGp1dCouL7FfHbP5elfed/Siq9q0uRgC6FEgfNl6/iZ71WDy3yqlT69TrNba3d6jXjlCualy6+BQXLl5E8TR61T53r99D0zQMTWVv+x5GNsnCuTUs3yMMQ1T1ZAVRv4sRoJiW0o5FGY9VItEYtvQoLlbwfJ9EKEkZcWrtLgvpNTILJdJLWVxrgG132Z/sksmtMre+SiQSoOoGh50I0aDBcn6Zie4ybu9AJsG93TZ/89mfZM6YoxHbptm5S7/WoXdQJVGK4YQOtXEHxZLsNI/40eIK2eQyB90dmnM1smaRnf1dvKzL6Q+u4iseIhD07A5GVCMIZssmvhuhnHZc7XaLZDJBJBqjM+5TXKyQnSswaU9IRFI0LDD9BEkzwqK6zEgfMjA6vHL/BXKjDLEFDd0USHtMtKVR69cpPZ2luBinvVMnrqXZv1NncXGNeNqgklxA9IpYh0kulJ7gwqlVzDQ4qkSTClEJriJoDmG7eY/Xt56nV+3w0peeIx6Pk1mYw3KH6ELQ3W/Sz+0RMtP4nYRhSOD6eKoLCLyxg5Bg2WN0QydAhUgcIQ0m7Qn0LIKIw06tzusvvAK9KKnKPMVSltOnz1F9dcCw65HLxrGCBo3hF3G8AvFEBMexAYmvahBmESONXGZEJlmmtHyG8eQGxTDFYCDY3u8ytEKy5SJnLkqObu1yvFlDx0QPTdZLV/HnHYJgglUdMnb7bO/cPVEMvosOcLoEpm3bzM3NYTkWfjegVCnjuA7VjX1SK6cplSq0m22qr98lPy6haS666TC0W4ybPprhYyTiyH6IvmczToyIP1kgXTrDZPs+1aHLoGlxdv7ytAw3Ew5ru3z2Tz7LoNngcvoiRiJGYIM1dvCR9AcdImaCVv+ItSvrqGOdQWNETI9zdHjEXGUex3F49farGBFltizmt0Ewvdvb7/fJ5XJsbGxgmCZXrlzBiJocbxyQM5NUKvP0uj1ah01c6TCkh5KFi8+eQXdht76HYUTQfJ1a1SdZWmRl8QK+YlHMJRn0JviOx/FelaCwQOFDz3B/o004LrO4Okc6B2YMNEUQ2LBx3+L28T1q1hFNZ49I0idbiXHlyTPY3RHd/SqFxUWikSibtzfZbx/hDt0fdDh/6BBMp7HCIHywyNn0xohlO0QjUbLFMq1aE0toGD6oCFBC6v06Y89lbf40VhhgGCbd7gBdjwEqtm1TKKUYNVtE8grdtodQUuhqBt+zkL5ECQ10Yhi6gR+6xOIRBqM+5y+c5dVr1/iPn/kDllaWKMbzNBoNZCDRNQMl1KapdjF46aUXUAYajz1zkaOjwxPF4LvwAkt0XScej2MYBq++dp1ypUKlUsHzPMxIBCklqqqSyaSJxlJUWw0Mw2d+McOPfPyDDN0B1ePG9Pb3QJK2JUvPnEMppmlWG6THBlF0LiyscbZyFunC8899jT94/tMUk2lMSzKpOZxZP0XXntDr9snn89zbvM5x7S6KrrO2eobB4ZBUqkNoSazehDu7G+TzedJalu1797FG9knD8HAjBNFolGg0SiqVQlHV6U8lxyGuxykUC7iui+dP68QtZhbpBh1cz2WtvEp6IcJBfZO4yBERJTxXYlSOWTu3gCks6jtbNI5DEvESiUiWiJHlwtrPsLOh0GuaxGNZWvUQJXSZjCSdbpMXX/kKG/sv4yebJJds4ukyhdiz9Gt16rUGugeLhTIvfPl5cvkcp9fOUDDnec26/oOO5g8diqJgGAZhGOL7Po7rIMPpd9Y0DNqtFpFIBMWTZDOpaQkytUGt0yO/usDTl59l4+49EIK7d++gp3WSyQS9ap2kojOeTMjmPH70o8/y2iv3aDZaRDQVb2LiugG9js94PKC23aDb7pLJZqiUy2xuvUmhFGNpOU91q8H9+5vMpecJ3ZDAdbBDm4ircv7cebSJQavVJhr9z+wEEUJ80wliRkyeevppxuMxqqqysrzCbt/j8PCQWCJONp1hPB7gBi6lUp5kMsnErtO3dhmOJ+Syy4SaSvbSCokLC4x6PUYvVOmMA6Jrq/z0T/0NMpES/gjubmwQj8fIpbJkI4v0un28ToAiNAwRZWj32Nq5zcqpHJlchU6ny/72Pq1Wi4XcEuPqhPpWk4gX5erjjzGXrvDCp184aRgeagQCz/OwbAspJZcuXQIgGo2yvrbO64dd+p0+qqbhOi5GysD2bFRTpdVpYwsVf+hzLvE4f/3pXwIZ4/5Ht7H7Ld742lc5vnGMFltjbuExnvz4s8yVF6nXfLa39hkM+7jehPHoDs+/eI/yXJpoTDBSbpE6VWO7foRjJXEVD7u9gZxMpncyvZB+0GKUUImlI2iLOSIORBKzG13v5K0FkTzPw3VdYtEYjuNMCyRkszS2dggMn9XSHNIO6PT7HKgN4sUMmWIeLRohGU/iKQ5BEJCOpTEMnTCUDxKrJyRzJXZrNaKVAcnoPv07EeLGGXQtjjWxODjaZ8gAa2yRTBtEorC4UmBuPks0BhcunqZ2voXb80jG0tjSAQXS6RipVJLlpVX6XodGs3GiGJz8J7CUBK5P3+7hTGzOrJ+iKn0K8wWs0KMRDvBGXdJC0J9MKF9aJBg7bN3bhmAV2wtp9qI0mwPOLleodY7oHTbgjx1k08Poash8hgvli3zsygcAH88MuLB+FlmbgBYQyWVR9DFm0WMut8qaep6JV+eFl/+U470B7U2Tbv8rZE4lAcnem7voZyX+0EddTOFkI9TaW8QysROH4WFHegHuxKHvBCi+j2rqnDr7FFv1XWphj5gWErEdRsMui8unUbQC7V4LdWxw9817PHP2U/z3v/A/UUzFqTfg9NIchgY/duHjTAYToskUyWQUXQNTg69tHPPSzdfoDPeQI4tYUseLt4lEYxRXr9JuKCyvnKNzw6LWOaZxv4a7K/jIsx9DTVa49uabRFZyLD92Fk3XmUR8msMttNjJJskfdjzHwzAMhBSYhoke0TF0A6EK9KiJF0r0eBTbGRCLJjmfuUj5dBFFF2hCR3P06dIJ6Xmk4hNRNILQp9ZrEyul6cp97L6CptroMY382QK94x6KnUTYGTp7VWRqhBYRDJwmjZ5Ku1Xn1MoZsqlVVEXDXNIIoj6JWAzr2KZQmSM/l8NyLDxVJZ1IM7JOlsv7XY0AA2/qoJgMx9y9dZNsuUC+mOOlW68Tn89TypWZ3D+kMxlR0JZYWVqgXChweHhItzfEiKVZrMQwDZ3AH2ES0t6oEvHiZArLFFYv8Ms///cxRQxJgC9CAtfDGwUoaei6E/IreZSox9gesre/wbmraZZXE/R7knF1QuD4LJQXqO+1ud/YRl+EZz75IRTiNOwm3bCDVGdWuHdDhhJFKBiaThiGhK7LxB4xnoyY+DaLF9c5n6yw9dWX8R2wAofiQgnDMLh95zbCUqndG+NbEdwUBDJAtxXMBMwVkohCkhBwJOzuHtNq1bnd2KI1vEM0KSmUktRaPYqLOTTTYad6yObeIc8snWNxrkwmI7FiLlo0RyGX5/bxLsOJg3Bs3vfkx/A8j+Goz9Af4s/cPu+CIPADXOniOi4ja0Qmm5nWdrQnrJ89Q6fdw3ZdhKbiWjajY4tEIoYfcTEyGjut+0zGEyKRKKVCHns8ptFoYzsT/trHP04+k2L/4JB6vU8oJQtzOrCBVZYAACAASURBVMtnc4yqMKpKnL5AFRqKquKMA3rdMbbt4/sQi6ToDjuYWYNiocTNl24TM5KERog7dpE+7GztEIuLE5fEP7kTJAimdeJGI6SURKMG9XqdV199jaE75tzjT2B2Xd7c3OPsk1eZBB7leJpbN29jWRZXH7+CmVTxgiF+2CeaUiidLTJIjmhsNtFyCj/3s3+bucoCQTCdlwj8gNFoRGWugq1N8F0oFrJYdpNq8wAUn3gKoomASmWRfdOjHC4QHgpqu3XMcoSL55/g6uUrHB0d0eo08D0PGc46wHdDyhDTNAmCAMdxiMVi2COP3d1dxtLn9BNXGTsBm7Ujnv7oh/FiEs9x2dreQkpJLB4lnojT7jgUyrFp+bRAoIUgCCFQuXcEr7z5HNvVTzNyb6JHzpMv6qSSKRr1Bvl8ikwWhqMWnc4IHA9lqFO712RlrUzbGKBX8uy0qmw3jiksznH16SukUimq1dq00Op4MvN7/wVIKb+Z86nrOm+++SYry8tky/PYE4uB4jGXzqOpGorUqDfrjOSQyEDl2WcfBwT3NjYQuLhOgG25nL94gUQ0RnjkEJ1EiKlpjjoNBr3Xefbxj2LZfYQaAUvD70SYqyySTMZpthokYkWOj6vEYq/ihT6rK6eIk8BpeVh9m/ZxA5F2SKXSNI6r3Gs3SSQSJ7r2k3uBYdopBSH5fI65Yo74qM+g34eIRmjqbDV2aVsjzufS1DsHUK1jGiZPvu8pQuESTUt6fZfRqIURC4iWDCaWQrRosHC2whNXnwAJ6gMnu6JAKpUiEjXY7/TIZysgHVSh4nsutWaP4MUBvWGfuWKFvUaDx88tkdjMs5RbxC4GlAtr2LZPs33I5tZtbM9BzJzy74oQAted3j0tFoucXVulM+pDMsK9wz18XeHO1i71cR9LCdne2WF9ZYGlxSX6gz6ldIbOxpDDgwbnL6wipSQIpjmkGgqHtRG/8Ye/zb3d5ykudMgUA1S1TzlbIWrGGY/SJJI6mj4EYWFEDDq1Jp/73c9Tnk9y64Vb9CY2l55coFAs8USyjKLqRGMKjuMwHo1otdqMJyP8E44QHgV0bVrJSaiCSCTC2bNnUZRpFaC1tTUauwccHx2RSWdBE/i+j2aqlOcKKJpDu91B0R0IVRAqC0slFlfm6ff7WK/V6Xsu2mKBIIxgaAOuv/EN2tsOy/nzJEUBa2JhNwWJeJRhG3xpUK/VMSMBiXSKWDRJs9ak3myQEDHm03lefvllisUi6+unmUtUePGll0907SfuAFVFodtpEzEN5iolZFySzmVRLIvOqI/S6nB89w6u5jOUE7aO7vOJT3wYM6PiazYDp8HEGTNxxviWR+hG2D+uUi5GwYnQHxR4+fUqH3xmlSAEzwMvGiGzmKM5qKMKnVRcRUlrNLsjEoUE+qHO3a/VmFtY5JVr28QqKca2RWbdYPncOQZKD9Q+vj+PaaaJJhW6tfGDHKUZ74Zr2whFwdR1Gk6HwAyYjMd0ujWM3oD9GzfQ0wa+GdIdd8jNXWG8P0aYgq2jbRwrSXt0hMIqinTwQw/COLYLv/Ebf8Ct3d/j45/6CNKQtPpNcvnY1N0hPHx1SOhHCDVo+yPikQKPnb3C7dfu0a36VI+HpOdzNDotMKPElvJYExt7PAKi5PJJioM0k6o5GwF+G4Qi8EMP13MJZECr1eLU6irj8ZhIKkq916QxbJBUDFpWm2gmQb5Q4qC6z+Fmk0Raw7Icbt8+4AMfeD+hDNg+3ubG7uuoFsTHAiciISpJplWS6SLpaI6lhThKEMM6DqCXoLUbkDN9nrx4hjALN+9d56B9QNLJcLTTJaGmMFWDVrNDJB0hWs7gRzT0fBzbGfHEx6/w2tdeec/Xf2KDZBgGxGImAsn+/h4tq0NyLkNv0qbVrlK7eZvRUZWltSXUiEpxPoeZ1mgMquw3dnDVMT2vRSBDagdd3nh5m143JMBF1aKkkxf54nM3+a1Pv06z79MdwVbNn06GZqIMel1kOGEcDGh6HTxhcW5lFcOK0dycEPYVjJHGqDuhobfoJi1GWBzX7+K4NqlUnnQmR7FcOHEW+cOO7/sk4nEMTeNgf5+d5h6LF1YoLuQQqsft557Ha7V58pn3UV4ssXp6mbEzZmgP6U/6xPMJFs7mcMIBgQumquL6KkKBz3z+i3z5hd/HDHXaxx10Q+Ogsc/E8RGaQaaQJFCHxGMGY89looa4no+pmsQiGTxLJ3CT2H2FYOyjKArWg7+Hvb37vPrqSwwGbUxTZXFpCV37rlyfDykSoUwT3l3PwXUcPMdha3MLXdPRoxpDb8j6xXVSpRTNYQNHuKRzOZbmV4lrGbbu1Bi2A5ZK5yjnV/F8H9VTcA4nyKMAXVsgX7jA6fX38eOf+Fl+5GOf4MyFC3h6iEgr2PEJbsQHqXF4b5/GziYRdcJcJUGgDOkMGty5tUEyliSiRTiu1dnrN1h74iLlc6tMDJ96cIw5f7Ku7LuYAwzx/YBMOsPB4QHzi1Fy2SxPPvkUn/mjP+LWndtkslmuXLlMNJ/FU8dUq1UiZoSlxWXaoyqhdDC0KJ7TYG+3ysUnryLD4XSR5toxihJweLjH4UGVj370Q+xPjmiP9onHIpw9v0ilUuLa3jVCGeJ7Po7nUiwXGI1HtDtNhj2NQkeSXc4ThAaaULm5s8HGnd9ibm4OlOnkqqbPvhzvhqIotNttTq+fxvd9Uqk0qWSS0A8oFAo0bx+QyqQ5tXoKRddZXlqm321hGAYXL17EmYz5xufeIM/7CEPQ9BgO8PreHV7Z/V1y6116LYf+KIXRd1ldK5FOJ9nZ3OXgABbmF1ldPMXL21+bmvRHI6r3NiiXV+kPerQ7LUI3pL7Z4onHPoSWTNKTHfxUh62tLY6PjxGKoLSYnU1zfBtUdZq4rOv6NG9X0xBCsLu7ixWFeCzOufVz3H3tDSrlCvlCkcD3kcD27iZXHl8jmUqTSqZo9hqQCCmu5em5TazqiNUlncRiBDc2oDbZpmLkGfQHICXxWAJ1MYKfCekfDWkdTxjccogVk6TzCR4/s85oAhmpYRgGtfo2AOViiQvnL2DbDr1eG9f2GA8nJ7r+kydCy5CJNeHy5ctYts3y0hLJVJKbN28RjUUZuD2ylTSJWBzLdUkmEwQIUslprlA0msB3A0Ztm1ZjQiySJxFPEI16xIIoG0dVbGdMPBFnNBzRbg9JnxEM1V2ajSqXr1zEdkYEUqJqKrVqnf6NQ66efz8T22I0HDPoDzneqPPxj/4kI+kjbJNsdgFXHrBx/3Wkn+fK0wuoymwE+G68VQg1l88xHA6nxSmk5HOf+zyB9EkkEpjSoNftkk/FUVSFUqlIqVzk3r37DLodKnMlhBDYkwDdVLm91eBL1/4fbh58kWhkmdNnShwd3WN/4PHRT30E33bwAx/bthmPx/RqbbqiQ5jw8R2fZn3AQu40ly9dwXFcBt0+je0W45qN6ZoINHTD4MmnnuLmjZu8efNNotlLRCKzPMB3IoTAcezpPwcxNTfksjlSqRShH9AYjUjmMni+x9bmFgvLSxi6jjWxsMYWTz/1BKVFE8uy8fwB/VGdPl2MvEZuOcOAEJka0PTaDEc2RjfOqDOPIZPMz80jiDJ2epx6vMBx1EEG8zhtwa3nJpDpsHI1xiSYkM0V8HwPVSisLC+zcOoUqqrS7XTY2t5kYA0olQonisHJiyFIhQgGoe8jhUckk+b+7U3++P/7Q579+IfRFxQmCvQdGyViks0VGY7lg0WWQwwlTjgaE9iCEJXifB49EWJEMxzcb9Ia9ZF+GtuPkExk2bg/ZDlrMHcmh6aavHrtJu5oQm41i0gEqKZHbCFKZC5OKZana1UxapJBo8vh7jYD1SE0NdKRGIqSw11SuPHCNiJYQdNniyK9GwoKcSPGwcEevnAozBW4ffcOt169w/ufej9aKqTZaqDENNzAZqG8wI1XX2c8GdNp9NBEDOElGE0mdCYOetTlP/zJP8dMHRFLlpl0TQamhYjpFMsljvZbLBULrK6c4ej4kC9/+StU92s8/tFL5NezDII+81fnSFQMjIygvJQj9D06NYVOo4ocN5FmiJy4fOVLX+epT34Mx3awmmNsy/lBh/OHjjAMEahoms54ZJFKxciVM3hhQKqc5f6NfbLpJO1mg8PqASvn1tg+2GV1dZHFUgXLadEeVPH9ENuymNgjCAyODg5YzpRIeBl6LZP0whyFQgYRV4ipGhE1imkmGI9cjKhOoFvkT6l0hwMi6jL9KtjWkLvjPkHUYvlskfRigSc+WiEMJbYcI/FRdYGigeO51Br/mROhNVSCUcDdjdssnJsniJq077ZRew76BFrOmJihEkY0Mrk0ZkThS1/4PMVCkb3NI6JmBOEH+H6AJz2MuEDPeCTj69wf3SO3aNBv1bEtcAddTDPFpdwS2cwKk9Exr17bRY5b/Nypn6DeriENh/T5Ik7aJYwoFJZiHG9uEtoqw3GdTWsXLRMj2O/z5tev8df/0S/TvlNj++7BiYfPDzsKCs7YxQ5sLn3gAiIKvh/ijn062wNaokGiEsPVPdJRUEIFYZsotk+UFJ6l0qgO6Hdf4lf/w4jOcB8lu0XUnMfqWximjpqPM2lMKOh5xn2FrmozP7eAaQzRtDi5WJ61xFl61Q6KouIXJwwzDSbjLo425qixR2/Uww56jMd9xl2L7DBC694B1ff3yCSy1O7cx5nMbnS9E0WoKGj0OwNi0TiW3ebO1g3m1k+Rqcyh3ZY0dve40Wwwv7JAfr7MuBUg4pLqYJsgHJOJxvHDECWmIbsq9766RzJtYCV8RoqNYaUxvQhXly4xCoZs1XYprc+jqQqhdBkedVlcXaRHneipMQEKBSVPs2UQ9FV0L8645lI3hsTLOSx3wqRdRdUhnjQplLJY9FHMk1V0OvFNEDfwiZdyLJxdY+XCWQI5XePX8TzevHGT4bCNprvUm7uMrSah7XJl9Sqdgx53Xt6gcdDE9RyazSaObZNKpchmcmiaCkiikSiRqEDVfXqDGrbdRTd0VFVhfn6OxaUFCvl5Go0RQsQRYRxDV7GsFjdv3KR2PMC2BKPJGMu26feG1Kp1HNshnozT6XTIZnPftHnNeBcUhWSlwIWnn0BPJ2l3uxweHhBPxNg/3OP9Tz/N6vIKR4dHbG9tsbu7S6FQ4NbtW9y7d59ADijOT+iPb/GZP/1VOv0NyqV5PNclDAMymTQAiVgcVVUYj4dsb2/R7/dYWlrk0qWLBJ0hX/ntT3P8xh3mRJSCmWQytqhV69SqdYqFIoqisLGxgW27WJaN63usrp3CMHRisRilcol4PP4DDuYPH5FohIWFBVzPRSKpVCpYlk0ykSSfzXL+/HkGwwHj8ZizZ88yPz/PqZVVFKFgGgZzlUUS0TyakiDwdLrdMdVqjXg8TiKeYGFhASOrslm/x25rm7pVJZaI0u/1aLc7RKMxLl++jJQSx3KIRZKAj6q6lCslFBHFHkmGtRGj+oiMliUXzdPr93n++ee5ffs2k8mEfC5HuVQ6UQxO3AFG4jEKq4ssnDvNUPo0Wi06nS6n19ZASn78Jz5OOqtSb25x49aLvPnqdVo7Pb7x2ZfQrQiFWJHBaEC1ekw0FiOTyRKNT6tJB0GAqiqkMxrFcozLV9YIGbO/t4tjOyQScZ544nHqtT6//e//iNdfvUcuu4SqgWZO65l1mjbrpy5jGgbXrr2CJMQPPIbjEclUEt3UyWYzLCzMEzmhkfphJ5aI88SHn8XTFQ77bTq9Lp7n8aEPf5gzp8+yvLxMuVzG9318P+CNN97g13/917l+/TpB6LOyuoLnuaytneLSpcuYkQjD0ZBqrUa316XdbhExDaKxCK7r0Gq3qNXq9PsDotEoFy9epLK6hJqKY6sSW5eYqTij0ZBUMomqqmQzWcrFEu1WG9u2sR2bvb09+v0+/V6PaMREUdUTrxv7MBMGIWEYIqXEdhyKxRL5XI7FxQUGwyGvXb9ONBpDUzVMwyAIAqKxKJqukcvn0PUIETOPaWSwLYV6tUc8HiOZTOB7HhNrhJZWKZ8ucu3eNYayz+raKkg4ONjnjTdex/U8JtaEQIa4jkutvkene4SuGhTzq8SUPGIkqN2vc+vFO6iORiaTZnllmVa7xWvXX6PVbpFKp08UgxP/BI4l4qxdOU/Pr1EfHDB2IJ1LsZLN4yiSWEqn4BdBGiQyGjsv7PLc714jVylw/txF5soV2js1Pvih/4JG7ZhBq0m/qnC0W2M0dNH9IWfOrrK5uYNlNYlmBI1WjVZrAdOIM19Z5sLly8wP5snMp/EtgZnSaTZrZHILpK5U8JsuuVKeke9ghAbDdo/eToNEJErrsE1c6owaDTx7Virp3VB0jUQpRb/fYfdgk4RhMOwPKFZKXH36MoipQ2dufo5CqYjhmfzJb/8xq6fWWVs5jTsW6KLMpcce4/7GTTY33mA0gUAKPMdjNPYJfZNUIkateoim6HQHNSbjHsN+H1MzSayUCYoRsgtpWviM6h1iSpReb8j5Kxdp7/VZPLNKLsjR73UQUhKMPBTVIJ0t0htZYLmMTrhq2MNMEAbs7u4gXY9YJM7BwT5aLILUVL76uS9w98ZNfvan/wbNbhNfCfFCSSqZx3HHtDqHCAnuuEcQ+EzGHiomhXKeVDZOPKFzfFxF6i5OEDC0BgxGAzrdDtFonFOnznL/3iaf/U9/ihl3Wb+QZziZEMnoxJM686cKVPctwiDJZGAhA0l9p8Zo2CdRCYjGYpTTZap7R3hjj0I6f6IYnHgEGAgBKYXOaI9m6ybeoMFh75h+OiR7pgwRiKUWWVx6llx5lWw6jhFK5hZKuGbA7v4hWW2OpTMXQEisoyaNNzrEvTSmiGBGY3hanmihQsNpYJZdbLeNY41IxjIU0qtEi1FKZzLML5UQXog/UIlqOeq9Y7TyiKAwIndqnvnyIjk3TbpmkBkmuLzyJI8VLiO9OGrNZdIbnjQMDzVu6DLw2zhuB+m0GbV79LpdjnsHuKkJvu4RTyRIZjO4hOztbpGOGGSjaZp7fW584z6hq+MlBEq6x3w2RNRgOVtgcW6eubkrrMw/yULxPJqI49ou8ZjPG9efp12vMulNCPQQI2OSSedZzq2xkjtLOlrB9iT90MLLKgzN6Zcsp2S5EF8j4Sa5dPZJyjKPPZTI3gR1VvLxzyPgaH+fhFBR+9N1NVafuMxYlwQjh5iisrmzQdvqMokEyEiEqF6g3bLY3WuweW+frVubSFvi9m18O0CPGxiJADWi0e0LwoiKahgUUxWSYY7qUQ0zEiedmseaRNl/c5u0m8a0S4w7IXpFx7yg4JVqRJaPsCNH5OdX0PUYMdWEvqR7N+T2V3bJBjmePfsMftXjS3/4xROF4MQjQM+zqDeOsCwfayQYOn3a7TalUnG639UwDBWhDXBtj9ubm6QXEiiaQmuvw972Nh/7sQ9hTSxcz6VQKOAGkkQijlDGmKaBZXcxIyHpjEkkBl4Ycv2NFxFCIxkvEYYemq6RSCTI53IEwMHREbFYnkx6Dr/TxlXGbG3vcfXqVWKpJOq8jhv6XH/xFfqjHp7sY0Rmd4HfDd93OTzaYTwZYE8UfGuMbdsEfoCQgoFnIwNBIgxR/ICdjfusra+RSWewJwq1apXcYhzHmdBpjVFCE1v3GFpj2tUJit+hWtshEpOg2OhmgGeFNBod/uD3P83Fi+9DDwXJeAI5sjGMGBKfg4MDisUi8XicwJkQjcY4PDjGDQSpSpL0mWUG1Sb3vvwS6VSC3rqGEp1p/E4UoZDKZRj7Adm5EheevIAdMWi32zSbLVqtLou2zZNPPkW/P6DWOMSOTFgslKhubPDGGxusnFmj1+txeHREv99n/fQqZmS6joxpmiwvnqbX6xKEIa4jaLWPiZppVpbP8/jjj3P3xZc5Oj5iJEYkSlHMSARV1Wi1WoyaIyzbxVDblMoFqsdtVpbWkGrA0bFOqzkik41hW5A2UieLwUmDJ2VAq32M70ocS6ffH+N5Lt1uF03T8G2T4bDH0N7l4OCI/WaDtfetUKlUYKCQJIMQgnanA0xzksJwasoOwxChCrxwgB8OyOQMMlkDM+JzVLvPf/rj3+L2xitouqDT7XJwcMDh0SFbmwdMRgpL8+cRYRJdTVAsFjENkzdefwPF1IlVCrxx6yb13QP83oBY2cSIzb4c74auC8yogpQqldIZ+r0RjmNTq9dwXZeJCOgHUwdBZ++ISbtHoVBE1w38IMQwBbrh0GzVGfQcxhOF1GIFDI2IUJjUWqiqTbOzy8RpoWo26XSSWCzG2BoxmowpxNNsXr/JG19/mc3rNznY2iEai7G4uEgqmcJ1PQqFPOvr64yGQ0bWhDBmcNRusrSyTLlUQokaaMZM43fiOg6aafKBH/s4xatnccOQbqdLvd7g9Jk1Ll8+x+LCIivLK4RhSKN7zN7hHZ7/7Be4/YXXMYYa8wtzDEdDdF0nl8uTfFCUoFar0el0sSbgOipRM4djqwwGI+5v3se2bcrlMufPnefw4JBbt24zHo/J53M4joNA0G53MUxBvbHNaDSglF+mWbdJJeY4f+592JZCoz5kYf40ly4+faIYnLgD1AyVdDZKOplnsbLOsDfCGk8Y9Po4lo3jhoysLo7V4fZrd3E8D1dz2Ds4IKpEqeRLWP6Y4+MDOvUutuuxdnqNwPVRpYI9tnHtEa3WMbop0SIh2XyShVKJXDyBJgOS8Tj7uwe88fqbbG/tEIslqZQXyKRzjEZj/NAnV8lz+fFLJFIxjKhOzxuhxU0ee+wKZ9dPgy5mLoFviySVipGMpUlGcgRuyHAwQpEKrUaTkT1hZI8ZD0e89o1riEBiuzZ3N27j+x7rZ08RScHB/jZ3bm5hu1BcriAVwfFOFTMU1I8P6HaaTCY9RlaPRCrJXHGeiBIBLySqahSSaUyhEtF05ivzlIolHMem12+hqCHlSomFpXkuXLmI0CCZipFaKSPPz5H60GWivoJvz/IA30koQ05fPENmvkh2ZY5Wv8P+7g6T0RDXc7n0+GPMLS2AKiiVSiwuVajM5bj+8jWEBZfXLpKMpRGhykc+8hHW15c5OjzicL9Ko15nOBgy6FkUcgs4tqTXG6BrGv1eDwgwDZW1M2ucv3SeK1cvEYlEqR03mEwmdHs91s6skS9nSBcibO/exzB1EvEU21v7+K7g1Mo5NCWB76jUD7snisHJvcAyJJ3xsRoutBxkb4w6AdPVOLq9x2HrBp5+zGRfpfX1BhVDYzRxqTcHqAmHpcsxnEKH4/1btF7uEhhJ9KKJ3xoQHFookzjjekBMzzB0LQ4GR0glSrRTJLGVI91JoLsmF9YfY33pPJfPvI/zZ06jaEMOjq8xtm8SJBvo61ESp6LMn8kQqF0e+8AqellHWy9hnDmFVdeZDGc5Yu9GIEPCIOTutdd44Y/+FN0RpPUUCTXOoDag/uYNMo7F4LjB1v0j9FgMWw7B8BnabbRSDK/koisjIjKNGhEkTJdBq48WnIJAxT9WEb0YgaMxcl2a3R6TLY9Kq0KireD0RuRyBVYvnSd/fg1fNcCTtBr79Lpb6PoA1DFKKiAoSI7dQ/L5gEReJbVahkIGGaqEs5Jnfw6pSmTKp9PfB6/L0OkS2iOseo39o236houbUgkikM4liekGnXqHUFeInyoydAPuP3dIwl8kk8ogzDZaIGjtCirZIkvlefLZPOurV5grLeB6NXx3gjMZcO/uqzTqt/DjEGQF6bkouewimp+hmCnjKwF92SeyGIOswtpjRTb3v0Q60yOZMGg1WySjBVbmLxILsrTv/ue2woUhtmPz3JdfJCKmpfF1TSNimEzGE0aNEY8tl9l7dY9Oo8PqkgmAaUY4Ojpg9dxVBpogn89hFDw0XceybXqdLnPlZXLFMiNUzFxIw53QdTu0Wm2cvqSYmIMQRsMRUsLFCxfJZXPs7OzgyjGjSZtYXNLttllc9jAiJpZl0Wm1EdE4c3MVcoU8jWqHWCSOMrPCvTuSb67nOh6OKKUL39wOEAY+UdOkZ/dJJlN4vo+UIdlcFl1JM55MiAuJGTFZXV1lbs6cTpN0uqhqeurHTir4EYuI5nPQG2DbNs5AUorMYxomvucSSsnKyioiFaVeraIrkuGoTzJpUj1uEdHa5PI5BuMhXuBx5/YtRDSDbVn4oUJgqESi0R9cHH9I0XSd/qAPAobDadHYwWCANZlgWZOpnoDneXieh47g3sY9DNMkkUzg2A5HR20uFor0ul0sa4Smabg2gCAMAmzbYjgc4nkekYhBZzTAsiy++pWvsLOzTb60hmmahDIkkUixkM2xf7SB4zhkc1mEqiBUQa/TxXVtPN9F0+Jomsbm5haapqIq2oN1ot874qRJwEKIJrB3ojf/8LEipSz+oE/ih42Zxg83D5m+cAKNT9wBzpgxY8ZfdU48BzhjxowZf9WZdYAzZsx4ZJl1gDNmzHhkec8doBAiL4R4/cGjJoQ4etvr71u2qRDifxZC3BFC/Nv38J6/J4T4l9+vc3pYmWn88DPTeMp7ToORUraBxwGEEP8UGEkp/6+3txHTzGIhpfxeOjD/AfBhKWXtO2kshJjVuT8hM40ffmYaT/me/QQWQpwWQtwWQvwmcAtYEkL03rb/bwkhfu3B87IQ4veFENeEEC8LIZ75S479a8Ay8HkhxK8IIQpCiP8ohHhTCPENIcTlB+3+uRDi3wohvg78xjuO8dNCiK8LIVaEENtvBVYIkX376xnfnpnGDz+Pmsbf6znA88D/LaW8CBz9Be3+FfAvpJRPAf818FZAPyCE+NfvbCyl/HtAA/iIlPJfAf8MeElK+RjwT/mzQToP/DUp5S++tUEI8TeB/wX4lJRyD/g68OMPdv888DtSSv+9X+4jyUzjh59HRuPv9X/ELSnlte+g3Y8C58S3PLhZIURUSvkS8NJ38P4PAz8JIKX8nBDiN4QQTdcTigAAIABJREFUb5X8/UMp5du9bZ8A3g98Uko5erDt14BfAT4D/DLw33wHnzljykzjh59HRuPv9Qhw/LbnIfwZf8rbyy4L4P1SyscfPBaklNb34RwANoE0cOatDVLKrwJnhRA/AnhSyrvfo89+FJhp/PDzyGj8fUuDeTBx2hVCnBFCKMB/+bbdXwD+4VsvhBCPv8fDPw/8woP3/ihwJKV8Z8DeYgf4r4DfFEJceNv2fwf8JvD/vsfPnvGAmcYPPw+7xt/vPMB/AnwW+AZw+Lbt/xD40IPJz9vA34dvP3fwLvzvwAeFEG8C/wfT4e+3RUp5m+nw+PeEEKcebP5Npv9Rfus9XM+MP89M44efh1bjR9YLLIT4W8CPSSn/wqDP+KvLTOOHn+9W40cyLUAI8atMJ3B//C9rO+OvJjONH36+Fxo/siPAGTNmzJh5gWfMmPHI8p46QCFEIKZewZtCiN8RQsRO+sFCiI8JIT7zl7RZFULcfI/H/WMhRObB818RU9/hb570PB81Zho//Mw0/hbvdQRoPcj3uQy4wP/w9p1iyg90VCml/JSU8i3rzj8APiGl/IUf5Dn9FWOm8cPPTOMHfDcX+Txw+kHvviGm1R1uMvUOflII8YIQ4rUH/2ESAEKIHxdC3BVCvAb87Hv5MCHEmhDiuhDiaSHE3xVTD+KfCiHuCyH+xdva7Yqpx/BfA2vAnwgh/rEQIi6E+HUx9SxeF0L8zIP2z709f0kI8TUhxNXvIi4PEzONH34ebY2llN/xg2nFCJjePf5D4H8EVplmiz/zYF8BeA6IP3j9T5jm+0SAA6aZ3AL4beAzD9o8Bfzau3ze6gMxzgHXgasPtv9dYJtp/k+E6boGSw/27QKFd3n+fwK/+OB5BrgHxIFfAv7lg+1ngWvvJSYP22Om8cP/mGn8rcd7HQFGhRCvA9eAfeDfPNi+J6V88cHzZ4CLwNcftP0lYIWpuXlHSnlfTs/y3711UCnlNTk1Sr8bRaYi/YKU8o23bf+ilLIvp37B2w8+4y/ik8D/+uCcvsI04MvA7wA/JYTQgf+Wd1SfeASZafzwM9P4Ae81D9CSUv4Zu4uYGqHfbl8RwOellD//jnbv1SbzFn2mIn2YaYDe4u0rXQf85dcigJ+TUm78uR1CfB74GaYVLZ484Xk+LMw0fviZafyA78dE54tM7TGnH5xUXAhxFrgLrAoh1h+0+/lvd4B34DL1H/4dIcTf/i7O67PAPxIPlBZCPPG2fb/GtLTPK1LKky0x/2gx0/jh55HQ+HveAUopm0x/2/97MfX4vQCcfzDE/e+AP3owedp46z1CiKfEgyKL3+aYY+CngH8shPjpE57aPwN04E0hxK0Hr986/qvAgJlp/jtipvHDz6Oi8cwJAggh5pnOJ5yX39vy3zN+SJhp/PBzEo0feSeIEOLvMC3e+L/NvhgPJzONH35OqvFsBDhjxoxHlkd+BDhjxoxHl1kHOGPGjEeWWQc4Y8aMR5YTF0Q1IoaMpmKomoIQEt3QCAIfy7IxDR1NN9GN/5+9N4uR7EzP9J6zr3Fij4zIPbP2KpJFNsnuJnuVepFGI42tAQx4BnPh0Riwfekrw5hrA77wXBiGYcCwYY9hD2x45NY2krql3tndapJF1r5lZVbuGRl7xImzb75IqjVW0xCUDYwEqh4grzPP+5/z5/9/y/up5HlOkRdkeUKWx+RFQZ7nkINQyEBBnhfESQwCKJKMCORpRiEAAoiKjGFZSIKM77tYhk4SZuS5iCBB5icopkQsxEipiiIoBImPosnoqkGURuRihqapCAjEcYqARJ4XRLFPNEuIvFj4Kx757xy6pRZWxeTfjhOLgkiR5ZAXiKKApMgEUQiiSEEOhYAsga01EKQCL5xSFAJ5VgAChqkR+D5hGKKoCoomoOsWSVQgiiqQoWoSURSQJgVpmJKHKaIkIdsSogpFBv4sQpJEVFmmyCFKYtI8R5AEJEUgSzNUVSXNMvI0JwtzkjB5scb/FqohF6WahaKoxHEEOciSBIAsK4RJQCEWFHmGKAGIZKmAquoIgkgaZ4iCBORoukoQ+ERRgiQL6LqKYehn35qgIggCBQmSJKCICkmc4k5cirRAFiUkQTz7ESVkSUGWZSRJQhQEgsBjOp0CIIkSmqJiGAa6riNrKr1wQpKnDA4Hg6Iomn8dDc69ARpli9f+vVdoLtgstCvopsJpr8fdu3ep1+tsXLzB2sYl8ixjNBwTZmOCdIyASJZnDE/G6KlNGIXs7e1x+eoVcgWGByf4vREVw2Lz6iajcE55sUUqS3zxc3+Pve1bqGnIB9/b4uqN19HqMnf/7ztEpRkLX5RYjJcJ9so8POxSWbd49ZVVJsEYrayxsr5EPIvoHo9554cfMpt66FbC1reOzyvDJxqrYvKP//k/wPM8BEGg2x1iyhq5G1AEMdWqjWRpjEKPXJMZeUPatTWy4IgvXv/PCJMhP3r8DdJYJUtUREGi3lR59uwZiqIw92Zs3FhgqXMRdyKyunydMBzR7d/n2vULNOtXOH10wu0/ukV3r0e+HHPzVy9yejRjfiSjFRm5P6NVW2YYuIRCQShGLKxVsEyLwWDA7vM9aqUWt3/3r+XG9HeCaqvMr/ynb+P5PiXbJhsH2IZFq9Wid9qjl0xRKjKKkiCrCb4f4bo55dICmlJhNoxRMg1Vz1H1lP2DfRxnkcPjbcoVhYVOGbvcZGPlDfIM7j7+LsaSzZc//1WM1MLrB/zrf/GvkCYpNd2irOiU9Rq1Sot2u029Xqdk6vzh7/423/zWt6hUKpRth0vLm1y8cIG//2u/Tm5J/Ffv/0+Y7Tr/9T/9F3t/XQ3OfwJUJBotC6css9ApcefuI8IwoVwuE/g+g8EAw3QwDINyxUGOBPTColqp0j3t4mk53mxGnuW88cYb1Bp17m895MqVq0ztLqOTU/YPDnBadRRFQZAlhqMRQRBwdLTH3t4+v/z1r7B0tYP3oU8/HeE4Lt7+lNm4oLOwzMKVCoE25d6t++iiTk2q0z/p8s0//gFFppNnEptrl3gUHZxXhk80WZ6xvb2N7/tIkkSei9QXKpTsMuFoxmBwSkWuoygyaBpmYVKr1TjefY4oSsxclzRN0bQSMRJlp4rnnbJ5YZPhYITn+ew/H3K0P+f6tZsUokt/uIcX9JnMTBY7mzQ2K7zxpdf55r/6U6p6AzlRcN0ZitxiqdUmHKsM+0MG/oyF9RUqTpWjo20+/enPYBgGjXoDMdO4Izz4m5bzbx1FUSAIAoauk2UZmqbheR7dbhcBWF66QH8+pMhCNNnGK05Q9ZTJ9Jiyk2M7ZXI/RVIS/HDMyzcvsr8b0m63WVtvsrV9Fy/2IDeZz33aiw6xUyCbGafP9xidTGl3WpwMDgiCADnOUDGIopgkSUjTlDzPCaOIer0OQBzH5HnO4tISqqoyCV1EOULVk3NpcO4YoCBCXvhYJZkgnHB62uXw8BDLsmg0G3ieR5blOI5DEAQEfsxpd0oUgmXUWVnepFQq0Vposbi4yPHxMaIoEccRX//616k3GsznHo1mg8PDI4IwpCgKHMdhPBpRqThs7zzk6dY9sqwg8HKKuMWgKzOZTrl8o4LZ8Hm0/4jj7jHTU5f//X/4P3jnmz8idwvCYUTTbDI7nuG7/nll+EQjSRJRFP3sZfQ8n5OTLuPxBFXTWF9fp1KpoGkaAvDmm28ync4QBBFREJAkiTRNcV0XSZQQgFKphFAI7O0c8uqrr/G1r/wGtlXmzp1bvPvu9wmiMdWaSVb4zP0RP3z/ezw9fEK1XKVhtlheWEVRFURRRBRFFhYWWFxaZG1tjbnnYdkWv/zLX2FlZYV2u02rtQDAi3KvnyeKY3Z2dphMJliWRbPZxCmVcBwHSZLo98Y06sssL11kOAw+0jxCkGLi1GU8PQExQpJTKlWdwbDLgwcPWF9fZ3l5GUmSuHf/A+7ef4+V1SaKmnPy4D4nt2+z9eMf8fgH38MQRSzbJorjszX6aJnO3FogSRKyLMW2bUzTxHEc2u02tm0jiiLz+Yz+6JCJe3ouDc59AkzTlCSQGHUzdp70mU0jJFnGMGxUVUPRx7iTE5zNV5iPPdLIp151qJZtRuMxXuhRFBkIOdPpmKOjQzI1odkuSGs+G2/dQB/ZuLHLyfN9uk+PeW39TZYbV9mvDxCLKcNJgLAzwVxzUI5C5H6N8TjizV99DVo5D+/t8PS9ASv1C5RFlbk/ZnXpMvaqw6OHj8m8OVEuoyrqeWX4RJMnBUZepmw18IMAN/BRq3VipSAwIZEFgiigs7TEQnuB9to6prLJez/uMvVcUiKifE6axsiFjhcVuL0ejx49oVKpADmPb3/I6OiQ2WxGw7bY3LzCYNzlg1tbGNoi8eGQOLewXltgcDChdmJSKdmIgoClKZwe97l47TLXFm1+8ujHlFdFltcWOTk5YTwbIwoifjYmzc53QvgkI0sKaSCQGzKzUcBYGNDutDjsHbO0skSztsT6hatYlo6omtx9+D0EScR0TMLIJYgyymqVKCzodic8vPeUarXC8PSIB3feZepOKZvLNGp1xqMRn/3sZygyFX9e0GouEI991m+sE1kFB7dGTMIA04iQ9IJCTpEMSJKQ2I3QRBWEAkszsGUVZR6SRxFjMSGr6PjC+db33BtgnheU7DIiMsP+nEa9hWnrlMsV8rygWW1RdVYZ9Ea4kxnd3jFXblzn9PSE4XCEjIDjlHDKZZ48fkxnscM8neBUDabBmP5sRCplGIaBpZtEfsK9Ox9gWBaCJLF+aY1nD+7SOzng2o1rXLmxwrQX0FmqYdZkHu4+IMkibr76EoUf40g6n317gUkvYOvJFu50Snuxw+LSMpL04Xll+EST5wVCLiKLKmQh9VoNSREp103KVY29vWP8eYRhl1haXmJv7wB/rtFotrBsi4mfoOkqiqwjyQJzz2UwGLC6ukyapty5fRvfnbK8tIRjWZRMm93nh7z1+bcx9Tqa5mAKBgsb6wSKwe69HaY/PWbllQ7lRpnRyZCD40NSO+dieZOFVoN6uYqKhimbPD99zsMHj4iD+GfB/Rf8BXmWUyqVEQUJRdaoNAwyKWfiTymHZaq6TJxEzLoTVE2n01knzcckccLcG2BZJWRFodfrEccFX/zSF9nb3WLr6RN8z+eVm6/gxj7Lyyt48zlZKrK2fp3TwyOe3tvCUWQ2rm4yn8ecPj4kdCOiOEaSBBAKJFkgmAW40xkiAsVHf3Pg+4Suh+95ZKKANWvw4Tu3z6XBuTdAWZJQVZWigGvXrhILHoapUavVyPOChUUNWajwo+8/Yub2mYVDWpMxAgJJkiDKChubm9y6dYtbH3zAf/RbvwVGRrmWMB6N2dvdQ7Ezrm1co9Fo4hU+eeHx+OljqtUqktJhcanMqB9yePSUNFsgj2SWV5fI8Wm3y1QXTGytguApTA488rnIaHR09vsliTiOOTw8JI5fnA4+DkkUMU0TSZKwLAsvDzBMBaeiIMkR3nzCdBJRq1WZTCYUis547KEoCqZpUKlUqAcNRv2ALM9x53Oq1SqLi4sMh0O63S5xkmCYJrKiUK1WiUSBNJaRBIvtrWO2tp7z8hufxVpYYXD/BNEOMAyDyemEPIKVi8ssvtQhLzJu/eA2lzYvo1+r8MGtO7z77rsIgsDm2gb7f9Gz/4KPKIoCRVFYWlpCkiSazRLd3iHTyZR5bY7v+cRxTBAE+L6PY9eIUwW9piPLDpPejMD38bw5nU6HJIlZW1snCAK63S7dbhfRVBj0+6ytrdHv97ArTfqnHocHfZZrTXTVptPpsLS0RH9yjDefM597OOUy4/EEbzQhLwpMy6QA4jBkOp3ieXOCKKQ/6XN46wRxrJxLg1+gDlBAlmU0TUXTtLM4kCgwmUwol8v0+j1u37nDzs5zptMpo9GQvb094iRBVmSyNOXk+IRer0e1UmV5eZm11VUsy2R7+xl5UZx9QLUahqmjagqymqFoKa7XJ4zHNBYsrlxfpb1YpjfYIwhGuG6POJmgaAlBPmAu9cjNhPrqArMoJAxDSrbN+to6lmlRUCC9OB18LFmWMZlOKIqCer2O7Sh0lqoYlsDO7kPCKEDXdabTCcPBgCAMaTRbGKaBQI4oiqiKgqqqBH7AYmeRt95+i8APKNklPv+5z3Pl0hXu3LmPLEn4foAsWkzGEYpcYm/3FEmWOT09ZTQeYVsl/MBHVmQmkwlRELF2aZXECLl990OEUGT37j7/83/7v3C8dYIjlZFCmXAUEgbRX/3Af8dQPlqbNM1Y7CwShgFhFCFJEt2TLt3uKScnJ8znc6rVCoKg0VnYwLaaWEYDU3cQRZEbN25w/fp1/CBAkmTe+uxbfO2rX2NnZ4/VlVVMw2T/YB9FVSnZdVS5TK3SQZUdvvWtbzPoDzB0HVES8XyP/YN9nj17xs7ONgKwsbFBvdGg3qhjmGdlWWEYEQYBnj+nvFJi6XrnXBqc/wpc5BSAZdukacrVa6+CkPN8dxffCxmfejy99xgh07HkOrLToQhzKlqJl1+5ycOHt9jZuYOqZXQWWxi6RaXe5PA4oOI0SeIBTs0kTEOWOovs3/8pbjJkZX2JIAgxZJ39JxOOj7pceGmD5csLmGUVQSjIC5n+1oBqq0PqQlGogIFTbaJfLgiylOpii+Nul6I7QxRelId9HHmeE4cJWZIhSwp5WqArNuP+iAd3TmjUVyhXyhTAYDTntdUruOMp015A5BiYFY16toxtZjz0nlKvlxgc9+mPukiWyOW1Dd5c/BSR6FNdLLOz8xz/2S6XNjZpNBp0ajX8MKJ7cEhRCFQbMvHQonALpv6YX/raTeLMZ/u9Lbbu77C5eJU8EDCKgBsbLzMcDtndfU7ugyKd74TwSUaSZCq1OpW6RW3B4L3vPMEPA8pODYDAHyIVK7SqK5z2d0jiGZNJTrvdBkAuRLbuPWJ5bZmd3R1OesdE4pTXKi9Rq5V5++tvoJQLDp8fs3V3mxIWb31pjWqpQnF5jcCbMB5s49giy9fWmDzuMc19BuMBcRoT5wnXNi7y1pufZtTtMTrusrJYptas8upLr5CXTYZHEyzNwHfn59Lg3BsgwHQ6JYoirl+/Tp7luJ6L74XEUcqoP6VacjCadbxZQXthg7iY48986k6NqlOi3alg6BZxKJ1lDJMETXFQZZuSHbDcXkZKVEIxQtIFVNnAcxM67SUOdg8Y7UWEUcKCB74c8Pabr2FoNtsf7vDo1kNWlw1yKaJWNVleMmg3FU7HE0RZp7W2SKKJvPv+Y9I0/UVk+MQiSTK2ZSOKElEYEQYxu88P2dvbx1BrqKpOybGRZPksWxfHZKGPUCjEiYCfzwiCFG/uo+kKiipxsL1PlqUIkkgqR4iZzMblNcIgIJdS5tM5j+/dZW19DVOVaVxYo3t0yP2773Hx8iUWFxfoj4ZcunqB3Ex4ev8Rjl7iy7/0JWazFEetsVpfZ297j739PSRRYvPlTR7c2vqblvNvHXlRkBcFcRqyd/AM13WZez6bm5tYls1wcoLnzjCXbMLAQxRzFhc7TKcTRqMxrjuj1WqRFTmT6ZSllUUEKyIRYo4OjlAsiSD3qDbKpHHGtD/mT/7ojyjElM1LbRRbZedul29/Z5tXNt/GUHVmBRRCQZzF5ORYtsVyrULhBoRFn0sbF1m6skan1eaD/h4fPHvEwJsQBsG5NDj3BiiKIrIsk2UZg8GA2cGY57s7VCoVdF1nPnfRZJUkTZHks+txEiZ0T7v83u/9HqsbdTzPo1JpcbA35NGj+6xc6mDoBrJkUnNWqQktxt6IkTukvFaivz9nd3cHU6vTaq5jFSGmaXD5pYv89OFPCOYZmmCy0LjAQvOEnUcH5GnEtJ6RTeH44ID5cMTypU08z2PQH1CtVCjyFyUSH4csS7TbbXzfJ0kS6o06URpiGDrNZhO7rKEaBeWyyUJ7gWg65/j4hMnslOsbMB6N6PV66JrB5cuXeXL/Cf3jY371H/4Ku4MdJFHm4YOHjIYjlpeXqdcaBAOYuTO+//3vUy5XaDQNrAUdN5+yc/qMjfYlBAFKtk2RFVy8egFv4lEp1ymFAtEoZ3boEYQB1WqVPM8ZjUZEcfw3LeffOvLszDVqMplw64NHiKpOrVbDcRxM06SxcIWNtUs8efqE4WhIlHk0WyucnvbwfJ+yXaLaKvGHf/hHaJrOv/8Pf51JdEIYhDx58gTP97jy8mVKdplGo0q5UqE3GzKYdInSY5bXGnzms68zGMakE40wmSMKIoKQkyYpSZwgiiKdziK9vSM0XadcLlMpOQzcCY/7RwS2Qt2sE/n/jjfALMuI4rO4ynQ6ZepPaC20CPyAwXBAnMQIeYFTqpEJGkVecPHiJTRN5+nTLb797dvI+pTrV1tIssSz7SdUF0VkuU1RyNz66T3e+cb3efnN6wiVgsp6mdi1MOQmjdoqJ90uVy5eod4skyoJQRjw7Pk9LmwEyIXC5qUK+w+esVi6QlmTUeMCOU1oNhsUFOwfHrB/uE9NOaspe8HPUxQFoiiiyAq6oTMK+8iazKVLl/A9H6euYJYU6rUKeeHz4NET+oc+UTwlyzLSLCNNE9RSmTCMuH37DjfWLrO0vIRalzkaHDB35yiSTKfTQZEVuvKUarXGcDTi9PSUcmeJZsdBqyu43pzjgyNKSgVmOXpDJRJ8EiNkVozJJBU0lTRJkCUZQ9Op1+sEsY/0Yo1/DkEQMAwDw9KR5AuEScHS8iq2bZMmCZ2VBlmec/fuPQppREqAvb9/VpwcBtSdCifHJ5ycdPnqV75CZ7GDHuZsbW2RJgn1Wp1Go4GSqpRs56wtVoiwHQnNzGh1LMYnA6bTnOVyB89JcOUhCWdtjKVS6aw1TpbRDR0EAU3ToIAwSfBVAWOjw+D9+xTnTGSeewOURAlLNpl7c+bjOYUIumUhaDLuxEfFJvMT5rGLbSkIasws62ElOouLBiV9nWfPdnjv+/eYzyKWN5fZOdxlORJ5/0fvcrQ9oCZXEXOTesPkZLbLQnMJo+MwGPWRNLDsOtNhyOigx1ppk2ASMPYGRNMYqSHRvOow3jlmdpwxm5iUzArVSp37jx8yCTx0y0StlJC1F3WAH0deFMR5Si4VeJFPpVpFUs6y52vrm8zmp0iFijsOePT4Ic8fH1O3V8gKmSLJIYFrl29wfHzI9rOHOGWF5lKDarWGVtI42D8EQ6DsVImlGKNmUhQZj+4/YHGpQxKniGnC9r0Dhn2fKzcWaVyq4zhtUnIGgylT16PZqJP5Cqpm4jh1nEsttHqZWIzQLZ3o+OxZXvCXEECSZXw/oFRq42gxXjSikEKazSbueMLt93+KO5yQJCF+6lIyTllZWWFxs8P2syecHu/RaNksrtRoNuqYvsWe0sdeaJKKKUkuowgKjUaVu7ffpbFWZ31jndlszp99f5fTDw5Yf/0SaF2MXMDSOkzcHk61hNVwEGQQ4gIpgdSPENwINc05UkOktTrtfsSz0ZQ0Ot8J/9wbYJGdveAkYNoGqaQxnwYoikKlVCOe+GfNz0jYqspsPKZ73EdPBcxcIHZT8gEs1hYIpQDZzSkklclkhpzllFWd0M+hUDFki5JeYm94jGNGVKoVKtUymlLm3ffvE2cT1tdaCKZIFIrMwhgkKK1alFRwTzzEWIFYQ4hkKnKVyIvQc4mxPyCNX8QAPw5RFAmT8GctUrmXUalVuXhhneXlFfb3FSaTIaPpjNkwot1YRseiUtIRM4Hl9iprNzpMRn2Wl5oUuU97rU2WZ8i5gqNU0C2TSqOKWbIZDodYhkHoRnjunOXlZY4PHjM4jRCLKkEvpRCn3Pzi5xBynR+/8yEPfvqAlcpZM35roYXdFBjPPLqTIfaSxcrlDrGXvYjzfhxCgWGZWFYT151z6UYdQU7Z3z9kMDklHkV0d59TtlpIeo1cyTBkjS985vOIksR8MkSWfSQlp1Iz8IMZ0VxD18oIisbFy5doGG3c7hBZkTBsBW/ucbjXZ3nxMtHMY7muU67WmRRzCklDlw2kUETPJMxcQAhj3MGEul3hwtI6uRswn044bkV0oyk7791mbXmd/f39c0lw/g2wKECAer2OIAgEaYjnz7EtmzCKsE0Do+TgBwFhHOJQpRyXmZz0EMMUU8p5ZaWNgECAik9MksScTrq0O4tUtIhnj58jiAnPnx9it2zWX25iiiVmxy5f//Tf43t/eoucnPncZepqRPkcuZRjKiqDbp+m3aJ1bYmddBfRl4ndhF6/hyAKdJYWEQWBZDpFenE4+FhESSRJEjRNwzAMwsTHm88JgoDvfOfbBMEMRRGZzWYUFKiqQhbmlG2bPM+5c/cO+6NnOE4ZLxjQaDR4+uQp7YU2jlNGkWVKosNSeRkVlePhCWWnTBaOefzoCaZpUl1YR7JdFEVDdUr0hkcMBwPK9gIbm+vs3tvn5FEXp+IQTxPCXsLJTpdYiWgvVZifDDh+vI2qvMgC/xwFDAYDojBifWOdLM0Z9EbkqUYwj5gOpzRaZyUvSaRQbjn0Jof8zu/+Dl/4whcplyv44YB6vcHDh4+x7Qq2VcdSJGq5hXCccJrtEoUhoqbQuXKB9350l2XKpAsBaxtVokaG3nSQfejne1Q1EZUBVqJS9wrUaUKiplQXWlSMEqWSzVF0zIOHH/BkdkoxD0kFlStXrvCTd279tSU49wYoCAJ5UeC6LqZpkuU5um4QxzFQYJgGxGfNzKIkoigKuqKgCQVaUjDzXWrrq8iyTPfkhP3+NtoUKkqNlAhd1+gsOVgljV5vSLndYeO1VQbPB3yq8TqlrEyz2qKzOCROx0RxjBdN2Ll3yvrqBkqcsbzWInNl4jgmc0PqdoPJ9GxaXlEUBFFIbsggvYgPfRyiIGJZFq7r4jgO7mSOIAocHBwwHo+BGD9Imc/nJEmMXtIRJJ0ojlA1naXFRd57+BN8f4TlSFy9dpnbHzzl8PCQtVWonUWrAAAgAElEQVQRTTNwj+f8Pz/6HVZXV1lZWUGu6aiijqzIVMtlTv2E5StrRMkAMbcZH8fs7+1SKcWomsONSy/x07s/xc4dakoNJZJpWQ6SI9Lb2yeMPSRfQOBFqdNf5s/rX4MoZOa67D15Tn/Yp1atEcUxsRchC+D7PkJhkWUZjUYLSZL5gz/4N0SJi2lnfOazn+XWe++z83yLjYsp4WxM78EB3/3gIY3VMp/+0ttoJQtKBhcv3mRtaZFCCPCCHmufbnCy79M0V+mXdxAroEkqU39CnCVYuknn+jWyKCXy98A08JOcD+/f5cnxHhfUKmqtdmandw5+gVa4nCgMkT7KBgs+CAUIuUCtVCOaBYhZQZFCo9yk0ijheRMETUEvFFZX13Eu1tm6t8PBZIBdaRIFHlJZQtYk+oMeYe5RKhtsmGuM+yMq2gVKC2v85uv/IePtMW++9Cm8ucvz7Yd4foigqwyPh3jDZ5RKFlVjROgJFKpI60KbcXdInM2Jk4Q4zknzAioSSC8+jo8jz3PKjnPmoRhF6LJG5EdkUYZjOuR5zGg0gESkSET8aXjW3O6oFNkcTTVpdWx6h3MmhwO+/eD7KKpBb2GIVbI52N7h3gePSNOMzRWVilWjGx8iWQVr1Q2mboBh2GiSwqgf4pgqZafOZD5FN8tMxi5WpczKlUW8mcez7aeUNJu1Voey4/Dk1mPG0yGrpeWfNdm/4C8oioIkiknjhPFgiCKo1J0mRZITzEKKEIq8wLY1ilTAMAQ6Gw3mExchsdk/nDA8mfGN/+0boMgIqo5WVtl7dsD21i6Jn2OpBpVShST28JMQzTRJCjANAwSRo+0B9959xqeuljBaOvWNOtc/9yk+/O3b+LqGbNggqoiWipxEpNM+d55tUVZtVmodOk6LnYMe06H3Vz/wx3D+OkAB0iRB0jSmkwmqopN4Z64qfuShFjJxGFNxakwHLpauMTg5pVZpYNgVnGWHcbhFr3fI6GDAyzdf4zDYwxc8ojwikDzMZgXV0miKBttP7pEdXODX3vpnNPVF5pKHVvhcW7/E1u4DuvNjKrVFJMWiAALf59HjfeZ+xNe+9lXqzQYfvvtTrn3mFfJM496dbUbDGSRj8uJFfOjjKIoCb+4hSxJCoRLnIRQFkiCRhxkgYStViOYUeUAeiMhmQeTOKZI+w4MZpwfbpEPQxyZrzgbjdEwUZEx9F98dIasKMy/A9SNERSHVfSbzEXKeUm0uYRUZ9773Ib3uHEPzWL3ZoDfo0+ks4YUD+pMDKjcaVAMLZRuM3GI0cgnSlE5pnaqygKopZNmLYXA/RwGqIDMej1EFGUVXsVUDd+YiJDlFLJMmGbNwQrPZYtg/YurtUdMs5KmH2veQDkI2q036YoGg1zkdTHCjCL3qMB779EZzBFFByCV02cDVXHI5wakt8uDhQ55+5wGWrnEneZfmZp33ntznl99cZ/nKZxAjCwQdMonY7RMNTxiU4EHvFNUXqMkOcrlKfaKiKudb3/PXAQpn8SFVPcug5nlGlmckSUJe5NStKqZlIkoipmVCKKCEGnPXRaso7B3MeXDvPrNRQlBknMz6ZFqKIAiU7BK6ppP4EXEU485dXrl5E03u0KhsIhSw0G4SiSGXFi/wqexVDiY1FCnj+WMXBAFFVWi26tQaCyyt1OmdntJaa1C7vkYcidxYaXD3/fv03ztFeNEJ8rHIsoTruoRheFYOI0mYpkWapoRhCJydEiVZol6vU4QCqqqQ5ik5BQ4VgtsZi+1l7GYJVZWZB95H1lpzkiTl5s1XePDwEaIocHBwCLbB5YsvkecCs+mcuRdy0j1Flmxc38Ud60yiMb3SAMu28KOY1koLMZAJehFez6fkOGTZ2fuo6RpJEr3o9vkY8jwnyzIEQUDXdeI8IY1SZEVGNwzyHJAyDNNE01WiucngZM7B4JhoPKMhK7yq17FLdQotIoljplOXoshZXV2GsEBSM46Pj9npnfC5r36Z9VabLE44ONgHwUepqTQaS5z2T6iWVYrIQXZb3LxxjYffeYcH3QO0xTaH779LO0+5M5twmvt4Uk6S5swmE6SSQpSH59Lg3MGvJE1otppIkoQgQBTFRFFEmqZEYQRFQbPRZDqdMhwN6e320UKT2dTFk13uPLzH9rtdTvYmGLUqVqdKvVFnPB5jWhaiKBKEPt3TLsZHDfmeqxNGMkUBTsWhvlzFE12m+RilJlFu6qhayml/F1EOEeWQ8fSIe/d/wjs//mMyZuwdPaE33EO3Cj7z1qsoivKiF/j/hyRJEAQBURQpODPPzPMMOIsfZVlKGJ1liWVFJs9z8vysel+SJS5fuMjF9UtU2hU2Pr2KvWlgGDrD4ZA4SbAskyiK0DWder320RrDxYsv02zVEGQP29Z5+eUbXL58kUajTv9ggJnZPHr3MdsfPidxU0RJJC9y5u4cUZAQEYmCkCLPicPoZ8afL/j/kuc5giDQbrcJw7M++bN4bnLWM18qUXJKJGnCcDRCFSQaus2iU2et2qbSalH97EtU1hZRM0iHUxRFQRQl8uxsFEa9VqVUKhHHEYZp0lmqguShminNBZPf+Ef/gNJCE02uMd6L+cKV3+Bq6wuY8gqLG9e51T3gX/7pH7C3t8+xO+ZBMGCkQWm5jaJp9E5OiNSQxDhfr/f5r8DF2WwGSZQQCoFCzNBUDd/3z65MkshJr0up7BCnCWquowsKZadMQsJpf0hJbSJVNQRTY6HTRil7PH3yFHc6AwTmo4zOS4scHe9Trzc57k053DmidmkdJBEvmPPN7/8xR5M9dkfPsYoMC4GLl9cJw4ByzabVXuEPfu8PMFSTPEgQ5BnVmo0pJii6Qmd1kfSH57PS+aTz58amApBnBVEakyU5qqoQRzGyrKCXTKIoJM5iJEFEVzWWFjpMhhPWrm/Qut7k4qc2GQqnHH5wRBQn2BUTdzKjbhicnozIydB1lXZngeOH9382c6TilAnGMVduXGEyjrn34AdQRLTbFWRBJfIjgiDiXnwfdzTn8uYVLixd4s5PHuI4VZQwpHfaQ4g5c/B9wc+TF8RRjKaoBG6IqqpEYUS5VIYkh0ykSKDTWWSt3WZy0iW0ZdSWxerbLzFt6vR++IgizVFnKe4kpurUOOqekBQxoiJimAbtVovnT7dYeP0y85mHhErJFmitNZlMMrY+OOArn/kKX7r563iBgqpZrF15CbEh8iff+X1MuYxZtlHWO/zKxbcpSwa7957y7g9/TCinnBwfnevxfwE7LBkhFVBFDVEVCbIA1VBRRQVd16nW6zx5+pSaXENVVQRbJhchSjJmhxMkSWflxiqaoTGdTIkHEybhmKpTgaKgbJWpbXYY7U2QE4Nf/41/jPtU4+TpA169toQ7yPjv/7v/kdt7f0b7YpPLG2v4kynR2MOPMwRRQS/XMGoLWOYS3nGA39dYv7JImqZkasZ0dsL1L73KH/72t88rwyeaIs+REJAFkTgOz4ZYiRmkAkUu4M19REE8c3sJQxqWjRhDNtc4OnjO5fWXqazUCaSY3qzLo+1jqolDFZPA9XAVAc2S0BIRu6KTixFOKWZ36zZxKPH44RFGVaTa6bB0ZZUb49cgm1OtSOzu7aMbOvEwo5RWsFds1j+7RIiHEVW5efMV/MDn8b0nnH4wJCtexAB/jqIgj1LiKMWsaORhRhpDkZ6VNElJQTjz0QQdPTOQfI3MlVCcMnbHxlgUGZ1ucf/JU7KRz/rFJqdBSJD5iDZIdZBLCjkJrXKJaDLm+YNtfvhHj+ksbHLphoOs5Vx/5RpvdL7MVeN13EmGUgZBnPF06z7d2Rav/NISrhtybzUnqOSUrB3GHlTeWuTNjV/i1r/+E8qacS4JfqE6wCzLfhYHTJIERVFwHAflo5orTdOYz+esrq2ReiFRFBAQEhJSa1ZZ31hlMpkwzwT2e7skboBlWwiCyGB4wmarxs7jkN/6J/8ln3vtq/yb3u/x08ffo/Qw4Z3vPuKH7/0pnc0qlXKV1ZWLuMaI/dk248mEe3fv0lzc5MIVm5deusEBRxzuHqNXVBRZwew4dHcG5AIYxvnE+6RTcLbGWZYhSRJxmKJoCgXFzyzLwyhEEAQsy0QQz67LQRAQRRGHRwcoJYX3f3iLvdOnxF2ROXNKqYmoimiaRnOtxaF4iOd5pFnK2toqRS7yzjs/QlMcLt54DdOoohs6r79xHfIIRcqYTGdMZxN0x6ay4pBLGZlX8PDxQ9YvXcWdD4iikJduXqJS1PjO77+4Av9lzlrazmJns9kMQzfwg4AiL+gPBpi5girIVCoVZEVhMBgwmUwpWTZ2yebBB0843j9h1POQipRhOEUqWSAILHY6iIKAbduMx2Ns22Z5eZk//dZ3CSKX1Y0anYUWhafSrrZZblxhujMlkmyi2OcHP/6XzKK71Fds3FCgpup8+O57bHz2JiephqFXcV2XhXYbo1Ym6XXPpcEvVgj9kYhJkjAajbBtG9u2CYOAJMt46cZLdE+7yLJMoShIRUbDabC+uIKsyQiZQKteJ1J94qHPeOye+c6VShxPh+S5wD/9J/8FX3jrq9zfeshPdr9Jand5v/ttdtIer769QZLEaJpOubSIGBosNAvS5IhmbZ3JyEcQYHVlFS02efD+A97/3dtYlsXz0gF3H9yldr1Glr84HXwcZyNEY6bTs9hOpVzDdedIkvTRnJDkZ//4ynqFcDYjTUK8eYYsmjzb3sJaHrL3aJ9x16WqXaS8InPjxnXu795lOpkgGhKTyYRSyUE3dKIoonc6ZHl5mevXPkWttcRoNkRVPGbzHoPTU0qmdRabREKyRGbCmJa9wJ9849sIkki9U2Xu9SmXHQpRY+Fik1x4scZ/GUk8m/ny56a3XhCSZhlhGOJ5c2rNZWzVJE1T5q6LGJ196+5sRq8v8cM/+QnuUY6k1zHqMu1LqxyNeswncyzTxHVd5ELCtm0kSeTo6BghL/Hap5ZYXNXJCxk7q5NOMt7ZfoeXLn2awXiLD+//kKLWQ04mGEtVFps3+fH/9fuQZchBjlgS0XUdVVXxAp9rb7zGwHfPpcG5AyOiKBLHMZp+FgCv1+s0m02CIOD9999nPBljliySNOG02z3LwhVwfHRC5CcomoJRU+nPe0zCCc3lBdqLK2i6CuTIos6vfvE/5iuf+zoPH+7wx9/9X/GUY8wlgSN/G3tF4OrNTZaW26RZxmziMZt6pGlBpdzg4sVrvPvu+7zz4x8wcaeUK2WkXMZOHYzIIhvAYmmZKAxfuMH8FQiCQFGcGWhaHyWoirwgjmMkSaJSrRAEAZpuIMkKmqEjKiJJllAgEQYJq811qsqZU5BuGIiSjDufU6442LZNvVaje9TF8wIePXlCQU6ahbhTj9vvPeDPfvQj9vefMBn3eP78OaWSzeaFDSzHoLPRobO8iFJoaKgkSUC95mBZGkWRkBBScuy/aRn/1pHnOZ3OIoqiIooSYRjiex55liGJEkmaomgao/GI8XRCEIaIsohuarieizcL0XMHXbapL3RodDofOUHNyYscwzBwShZxHNM9OWX3+S79wQRVlyjymCzUcLsxf/adn1JySgz9IY9Ovkuo3cfnFEE1MawVnNpFSs46wUTn9LlHrdRAQcPWS4ReiGyofP4rXz6XBr+QIaqgQJJHaJpGmiZnfn6qyttvvcWw8OnFYxRTQpMKhDjBFE1qRpvTnYjJrI9ScZm7IXN/xkl/xMLqGoEwQEqq/LPf/Oe83vky3mDE//mN/4ZeuE1emiBkzlkpjeaxdOkqV167zpNnt9nd/j6T6RBDN7l6/TXyrZjyqcg83Ocotol2oX8ywCnb+NEcSZIpLdgsvbTA7k/+2uNE/05Q5AUiCiWzgud5hH6IIiuohoUqKWiahihJVGs1dvf2mHoxq+1VNPtsJq8jGax2Pkex8h6rL60weDRAsWvcfnCfSEopFBiFxyyt1pj1+5QKHVEqERUFvfkenUJHnAVMnvWQF0NWq01WXv0sI8/j2bMttp7tkCQ5l1ZvYjfLtC4vsPd8n8GTkEW1hKBpmLZN1OsjvugE+TmyPEdCwVBNKAR0UQUhpygKavUKlXKd/mTKwtrqWXVGqUWeTXHlY077LoWtc/XKEsNRgJmYTLYLkixCNxWCyKPk6NhGjDs8ZrF9gUEwJpaOicN1nOh1FpSX2el+wMX1C+RkJEqAUXd49iQmGHicbO1zofUG5vqcS2/dwNNl5m7Og9/pIggiy8sZz7afsntwh9/4D37zXBr8QoaoovgXL1UYhmfZI8fh6tWreP19VtfWCE2HB+99QJHF1J0GJduBLGE6G9JqlFhdXeDGjascdg/o9k9Riyq/9sX/BClY5cHhfXa7DzDKOXJakOQK3aMxtWqNRrVOpVxHVlUqlTJb23fIihhd05AViUrVYX19k2tXNjFr67z78D3SzKMQLLIiI09zvNmc4HROGJ2vhuiTTsHZNfjPS2EEBGaz2dnVY+7hVCtoukYQhlSrVUI5QtN0iqJA1zXyIkcSFZbWltEsDc1UmMxmzPMZWkOjWqvhujNkXSaLc9yxxyuvX+VzX/gcc6/PyuoSOx8eY9VMCiVBNcvUahcoJJ+FhoKQN7lz+32mkwny5kU2L26gKwZHD075zt73qFQqlEo2Tx7dwXXPd0X6JCMJZ/FaSZQQJYFyuYxtWSRpSqlUQpEVnu/t4vkeCwsLZFlGGIWM/RF+mtJebrN0qU20fYwqSjzdeYrUjlhYWCCK47PYsWDjzqZkDYm3P/MlGrstLq+9gqKqRMKUzoUKj/buoAglrlyuUBZKLC2u4SsT/O6Ug/09rr15nUarQXtpRu/5kJ1bT5EVhf7uCVN3zLODLQ7+XZshCIJwlt0VBNI0/Wj+g0qaZdy6dYv1168jCgInJyekSUoQZcyYUWQaWtlGiQ3Gw5h63SBMJkjiHCM1+Ue/9p+zYr/BztPnHFcecnfwYxQzpRyr7JyOCJMU25T/X/beM1iW7D7s+51O05Pz3Lk5vRx33yZwSRAgCIAwKIOyaIukSVGUS5JtyaJM+4NcpbLNklgum2aVVdQHy2XYQqEIq2iaBkESJJGBXWzO+/blm++dOzlPd09nf5i78ONiEfbuAgu8nd+rqddz+kyH//+e06fP+QckkSKRyNBqtfnq1x7DtFpkshOf5E6nQ7s9wB6H6FqBaDTBIz9xieerfdzhJH9Jq9kinU+j5zRSqdRxxfCewPcn8dmCICASiUwWv7zJ3N/e3h6ZTIbTZ07TqXYmtoOSwLZtVD1FNBrl7Nmz5OMS+kBjSc1y6+AGjuYQi2nY4XiSN9hRvrWIZpOnWEwgCZn5k2XmFucZOw0GponlCFRVQ5ZVspkc6ydO8Nxzz1MslibJslyN3jWTVr1DOBJ06DAajvDcqbfPtyFAURRs20YTGrVqlXQ6TTqd/pbd5LmzZ7Ftm2KxSHW3QSIeJa/nWZkpY419YvkohbCAMQxxrDFJRSGRSBAOh/S7XUYiQac1Jv/AIpn0HBfn82hSFBeLuncHoQzohRV0OUvN2sQKDQghmUxw3/2Xefr5JwlignJplaXlJQaVIarjk9CiyI5PPprg0sWLeL5/LBG8rQ7Q931se2KAqOs6nut9y7hyf3+fZHbSsVx54Ap2y+D2tTtk02XyhRyjpk27O+TwoIovHdJu9vjEw/8NH3rg53Da0Klf5c9e/Ryhb7P98i1ykSSpTJlhtcGNa1vEozluXL/FtetXufrqNWbnk+QLE7/V4XDAcDjA86CQXyCaS7F5ewtJcZmbm8MwDUajEaVSCTkzuY8p3xnLshBCoOgyiqxMEmAJQSqZnIwglEmMQNfzsEc2OS1HLBbDcyZJ0WutGkohzvb2Nu3+BsmZ+MRW9Ohfp9Mho+SQ0XjmmaexghGLSwVa7SFO4LG2tEouscrNGzvc2r6GOaoAgvmFBXxS7O/f4eWXX2amPENKzmA0TdJqBiVQsL0xS8tLVO503m0x/sgxWcmfBL2dBC2RiUQiVCoVwjBkeXmV9fV1XnzxRbq9LnokgueNsEyLk+VZnDAkkYEbu1tIWoKZlRK22wQBmqYxGhqM/By6lmJn+5BRX+ZE+hyeY1Pp71C3Kly4tMCp+xe5unWH1kYNz1RIiRQn19cZVVsoivwtI/ytzS02b2+QlzVUD4QfIOSAxROLR0FY3jpvowOUCEMFSUyyqo3DIT4280vlo2F1SOX2NZR0AvV0nqrZRy0mUEoKXaXKqfOL7F/16O7dwXOS/Hs/9Z9yfvYi1e0evf4Bv/N7/xQtqqL2HDJ+CisuYy9v4mKRzpbY2Njmy5//OrPFIg+cuUz1sEI8WGE2l6fT38AeBQih02rfJOXO4EkSS49cZPPlmwzGNpHZDLnVWUZynWC6CvymTBY/Qjxv4qKoKDKSJDCMEaPRCIWARx+6QmvUR0lFyCeL7N/eoWf0SSsZhKzRbtcxazbb1oDsxRIlSWNnb4dEIo7vuPQPAhoVk+LZFWbn5qn17pCLq7QPKsRiOmpqDi0ao1SeY+woXH/lefrtA2bKs0QTgnQ+xsqpFS4+cIFkKsnX/+IbNAdtZtJlwqEgEug0G9Wpjt8MIbAd68h7QyCFIfOzcxiDIdXDKpmFLNEgii8FOEOfhXyOTtskdAu89nQFkfCJFWwMc8B43MbxLHJzUQxrSDDQ6Wz4zCxFOL86RyY1x2LuA7SdNpbYoT1+hUI+TTSnEc8mmbN7vPDSiyhBhFRB4EojgnTA3P2zrD60wEJihWtP7mJ3XdBSWL6HhMTQGlHvdNAd/VgieFtzgJ7rEYYTNzjLscgXMhSKeRqNBrNzJa7euk5BS+O6NvuVfeazJTLFDC27zvbuHXZv7XLloYv87E//bQqZFV556Zvki0X+4E8+SdfqMD5wmFcSzM2U6WoQT56kFJWQZAc/MMnHLyK8ia9xVI1iWzaD3ohOe4TvaQh1zNbWLRKxLon4DMX5WTQ/4LDSpbLfpd3rEs+oiHA6Qf5mBEGAbdukUilM0/xWeRiGk/Dmvk+jXkPEImTzWaqNKsbYQLFdUqkMmqoy6PeIKDozcwW0FASOS9pIQgiOM2YoeuTWk8ycy6InJMqxMpW9A/qDIZm1AqlogZlMAbM7ZPvmberVCvHYJMSZaZo4rousSET0CMlUkssPXOaF2kuE4wAt1Bn1DKLR2NQV7k153b0xOOoEJQ4rFdLpNGdOn2FnuMfi6iL+MKS13aVRq5HLpYhF8jSMIYbRJlFSOHfuHJqmcXvjJpomo4yT2FaEiBvn3MUUC6VHSGjnMQ2PJ57/KlqmRrZok8uu4xgBkmSzfX0Ht+ciR2RMY4BpjXB8F8MwUUIFSRI89OiDtHY7uPsmkUgEyxrTbnTIl3IUSvljSeDYHaCqqiwtLbGzs0MQBGSzGUajEbdv32amNIOaSXLQaVFamMOotahs7DB3uUStWsVUDFZmlyk+OMcv/PyvsjC3zjefepyf+NmH+dLjn6Yd3GD5whJ7t/bxxy56WSOfjbF++afJFdMo2pDdymtsX99DktWJ/2k8AZpHebZMPldGSB4vXXuKVstGKaVJJSVGwyHVwxr1Wo+5uRU272wxX8jiO9NX4O9EEARH+Z8jyLKMaZqEYYimaQyHAyK+TlRXCcIQ0zCZmZnB7fmTRNqlHJFkjL3dEZ3re5RXcihCptlokctlkSSJXFqlNFMiFoHdrRuYbUjE0ojQ5eorG1y+nEceu2xdu8FX/+wLZEoxkuuzBEHAcDik3e5hWWNKpRLJZJJOqoOUgpmFIpqtM7w+oFAoIE39vb8NcZTb2z+y/bOOjKBfz7uxdHaRIAgYDAaTqa4gABzCWIRAAqFICCGIRDT6gwGxSBLJ1Hn43Ad56G98EPuXPEqLSe7cNHnq6S/Rs5/ADfuMOh36Q4NL5z6A1Xa58eIrfPMvnmNlZZHErIbjuhPddtqMew7L6TWS6TzVZg83aZNamNgV9qtdyieKFOdyk/ijx+D4OUFkmWg0SiabZXdnB1nXyeULbG9tceb0GRKlHPOnV7mzuYHm+qRiMeLJBCPJJ5FMkMkmuHTy/Zw/fT+O43PlyhW+8uIf8/LuFxEZE01NEclpROxJ8htDHrNT/0taRopsZpZWc0jgCWbLJarVKrPlORzRIZlKUtmxSWUEyysldg6rbG1tsbPdIHSgoESRZQnDMBj0BgQtEymcNo43w/f9b3kLTILeTiKHyLIMQpBKpUmmEjRGfa5fu040rnPp4iWqm3X2bxwAEIvFOHniJAfDm9y+cxtVqDSbLebmZ/HHCu0NB6M+oKLbdNptuoSUF3ScsUCWYuzf2eWprzyBqqpcPnmKneYWXuCzsDBPv9+n0+0AEeyxjSwrtLotFk8vMKgPqbaqxAsxTp0+xZNffurdFeaPKLI8mb+dDCLiuEfJhYbDISvRNfr9PgLB0sIiVqdDo3nA8tnTpFJx7lTb1OothsMRfuBz59o2+XCV7OU5ZlMryDGJaCbKn9753/jGM58mkdSIZvMMe0MUQr7+1WfZvnGHVDLCxfVztFtt1FmNhcV5xtYYwzBIagnM+hjf79EYNcgspckO4jz73HNIkmB9ZY1YIvrDD4jqeh62NcZq91BGNvlijGw6ymi5QHQti+s6rCdmaLoDUuOAn/6ZD7Nw5iJmt03PMyitn+Xh5Z/EHYMcldmsPM5LVz+LbUbodjwct0d5KU1wENLphHgFhVarhhABljHGsUPKi4sYY4doPoZekHAtGHY77Fzb4NxPrpBeypAJW7hdi9vPHXBh9aco57NUN1/FUX0K+RgDz0LSp47yb8br5i9BECKEhO+6yJKE53nIQpBdKqLEZBZEkma7RSACBjGf6qCPruUQssyAOvVOjZ3tGucv34cTtlhamiWZjNIbd5F8icrtGliC+dIibtll7DvkSkUURUYWPvNqkWg0iqJKLEbWUXwPs+PS2B+jyTJyDK7ffoxkPKpTPxsAACAASURBVEc8WSCby9FQWyhhhG69R92q4PrTtJhvRJZlzJFFEPioqkoQ9bHDMZGUxmAw4Oa162jJGLPnV0gWi7z21Q5JsYClhqRyCpfLFzm8dYv9rQMSiQR+O0CbhUbNIjgjY5shV7/2Db706X+LrgX0fAmfMVp0hkIxhmF0yJaT5FI5dD1CKIMxMAiNGO0DB9fWkBWXqxuvEG1EiWWjrC/ncAYKl5SLjOoGh7t1ypE5ksnjGbq/rbSYlcoBw06PqFBwlQibWxXmCzOck4osKcskTz5KbBlSUpTo0irMZvH225DQGZdiKK6AKDy38U0ee+HfkUpobFxrU692WTuTAWzssYQ/trn08H04yohIREOSBKoq47opvN4AKXQJZBdX9eiZbXQlQEWm3THJxLOkMhqx8Rzr5XO02lWEolCpVbjy0AMszcS589St44rhnkaSJMRRntZMJsOw16PX7aJpE3/qWrdOQk4wW55lY7tDPhOh1+uwvbXNldn3EYnpdJwK0YTCIw89Qjobw1N1VFWh0+mSSicQp+epUGFQGZFIJZFyWeZPrnH/5cuYlkWrs8GdjdewbQc9qpOIpxkM95kpzJKOLjGwd7i+9RpKrYdf8Jgp5pE1Fdu16Q8HlMuz1LYqCH86B/hGwnDykEul0vR6PcaBSaaQ4eTpk3TaHeKpONc2brF6/jRdq8WtnVt84ic/jqUaOLLJ9Vev4VT6PPzIwzTqDTKXEhj2mNsbG1g/4SMj8YUvfg7PsMjlMyglwczpkwgpoFhKYFgtOocDfFuQzWVI5zIY4x6ZZAZpJovtJdlvvMpO7TYL8iLRaAkpBkN3wG5lF8XQWJlb4bUnnmP9xIljyeBtRIOZ+IMOBgOSaoT9vQGXlk/zDz7wtzhZWEIO86BnQQjomDAEShC6UTYe36bwkTMoGZm99j7feOWzuKqH0ZPpdYeEwiIaT6LrMeSEjDUMqFarnH1wnTu3b1EoFJifn6PdDtFUi8HIIZkoMNQ6jLoDDMPkG59/jNR8hlgiQsOrEdXn2RvUuXXnOr7wOfvQ/Zx94D6G3ui4Irjned1MIpvNUiwWSScS9Hs9XNelkC+w3d4mM5Nhfm6e/b19xo0eG9vPEw9VEvEEQvYolhI4YxfbGTM0TSTdxnVdTMtChCEkAvSixnAIsZkIlt7CDuDmVodCPo9t25gjmC0v0e600eP6ZM4wFsN3YTY/h6947Oy/hOdUsa04vYGBsKSjhZoQq2ozHk2N3d9IGAZomkar1SIWixEEHmEQYo/tiY9/4OO5LvFA5vDWHgwHCNliY/NVimt55pbzzF48QywWpR9O5uI7O3WGXp3+sEsionB1+1WkrKCwliNWVlhajxHTddLpLBsbJmOrRSlfptVsks/liSVUCqUomioRjc9RXLJ57qVnODyUMEfgbjSQNBl7bKPJUSoHB1jNDlV/81gyeBsh8QXm2KJYLlKMp/j4w7/EB973syQiKegY0GlBwiaMRED2EdEEhBCMTIbVPTL+OjuDAV985g+xhI/PIgd7r9Bu9zh1poysjolFU8QySXzLxDItRqMhsiwTj8WoVCosLt5Hq9NHi+gEXsjA6+PLASvLy1x74Rp0VW68touadzhxaZniyiJKPIJpGaRSKTxNZtgZTFMmfhcmo0BBt9NFFpOpD8KQUqlEx29TLpeRJImZ2TKbz71M2LI5c/J95LM5/NgQR3EYGi1GoxGZbBoCCd93MU2T8dik122QyifJuiksyUCoFrXGBraTZWge4oxyzJYmUcCjkZBCrszYHWNZY27e2GHtXJaZcpmBmWPQc/nGNx5nbnGR86vnubl7h8AKCQoOgTw1g3kjkYjO6uoKL7zwItbYQk9GaLdbWKbFz330o+y1qvQ6Pfau3Wbr+ZeYTcQJMDCtNsurZ2l06nSsJl1X4EZcOu0akmIz6jXZ3d0iHddoWQ0WijqDsEutb2LvHJCIJMimF6nX+6SSaXRNI5fNkognCVUP2+lzZ+OAXEllZkliaaVAZXfMjWtbmJbPBz76MKEBt567zYX1C8SXyoTHzO19fF/gsc+qWOQXf/7nObV2ktn0GoRHc2nCZ3iwh5AhsboEhRzoMvQcGLQZOQ3GzRp/9OU/5Cs7f0V6NUtg+YxdSOZ0sqUkmh7B8lwMUSeynKBp7NF7vsWjjz5KJpfjxo0b7FS/zvJMmbMrS2w3thgbBik9h5LXyM7N0jwYkKEMoU2n0SWR2iedyZNIx/GDgLFrE2rxadLs74KsSli2hRpR6O8cIhk20XSSTrtNqEI8HadebfDcYy9SSidxNJn50kn0dIqhblFv9dGjKbL5WZSIoDHcRUFFDRWeeuIa5bkSc/NFAm1E9aDHQnmVeDZBPB4nDENimRyeJyaZyRQNkXDxHZ++fYBpNZFFkZHVoliaZWZGIaoWWMnfz3hkExExdvYOWLi8gBqNvNui/JFj8nBTiMkRRu0+8wvLOIFFNJNCKcbJ6CmKi1lefvUVNEfloQ99gPxamflxndHIoFqpIUsKxVIJ4ftIkoIXqIwZ8SePfYpY3Gfl5CxOxSDo6SyW8nQGe6RmovR6ffKFDLqmYww8ZJEgM5ehazZpGRXqrW1W599HTIkgohXOXFwjnbaIqwVSThbD8hGOysbWLpc//BAhIXzyr96yDI7dAca1OL/9D/9bcnOL4AGOSdBqIGQZdzSk02kRi0ZJyAqkEoQBiK6F3etjGkOUSpszdowXzDhue4DAwg/Bw0LWJJKpEt1+n+r4gJg0IJACErE8xtiB/gChqKgxmVpll6iTYiwNiaDjmwEv3X6Zmcw6JT/J9rVNIppG1BQ4/T5uJEngB+zt7TG/sEA0mUVWpqvAb4oASZGwnTGKlqVVqaEqKqZqMm7UWX7fEh4+u9v7VDaqnPn4WVregFRqFl+XUDMaC9lTBH5Ip90hFlGRowqyrTBoGWAJUokcniujKUmCSITBoM+pCyfo9/qEYUBhJs1gMMIjZGD0iWkqKGD0m8iqy+Nfe4rMvCCVTCOkkKgSBVPh9mvXGAxHzC8vcunyI7zyZ9Oo32/E8TzqtQaj9oBIKJFLp6gN68ytLeBE4JWnX2Y8NjAci1xxifTcPD1nTL48R722z+zMPJlMFsuyMI0xiXiWgSyxub+JHtslNwOam0ByomDpXFg+zzi1TqfbIZGIE41GsTwD01VQIwkC1UfEQsaegR6Vef6Jq6RLCey0gVrycH2LSEKicrPBxsYmUT3O+fsusnLyJIZ5vKmsY3eAhWKB3OoiGA7h0EQg4XeHtPd2icbjuLbD0PcpCgGui5BVkAStnX0iA5uimuFvXvoAdXObx5pPY4YjDup9YvEYiWQSXY8SdMbM5FfwfZ+e1SeXzdPtdpAkwdLSEt2RzxPPfJFnvrTF/H3LzF2cpXnYoN8bkFdcFtdWafarDEdDhnf6nFg5Q6lUYjQcoaoqzz7zNAvlHGLqJfCmBH6AaZqTBZDhkGguTTQWQy9kmFtbIVqW0TSFysEhqqawcWeX9fkLxONxbH2MiAleu7GLLMuTcFq2hCTFaTV7HFa6pNJFpBTIcUjEkxw6NWzHxTAM+v0+sVgMwzApl2exbQff84nHEnQb+wg/ZG5uln5zj3Cgcev2AaqqcuLkGeKLOnN2mXJQRI/GSKWSTAf5b0bIzZs3SSgK/thlY3MTSZcoForcvHGDL/w/X+ZnHnmUyLyONR4xdHskM3mCIEYsvoCQQzQ1cpQjPKBTb3JwsM9gMKRQWCKVFCTTOXqmQbV/wNXdkAfe/wDXb1xjeXmZaDRKPBanetDEc0LmF8sMHOj3BxQKRbb2aygNgTJSePaVF8gulFldipK9NEOsHMF1XAqLWSQB3U73WBJ4G54gAoIQXAfhufj7dZzDGu39KoEfYLs25XNnIJMG1wPHJ2i26GzscPHSBXQliX1QpZTO4lQd4qU0K3oOc9xGlgWdTpvdnRYXL16i1+kQi8hEozEGw8kiRzaXIZ+dRY/kGA1vk0gWMYwxjm1z5swZZrQlkukkxRN51AOF2q0GRm1Mb66H47rMzs+jR1S2XnkcZzydIH8zdD2C7wfs7u4R1XWy+SwP/sT7qI96KJkkht1hMLCIx2P4novvKVy57ycRnqDXq+KpA7zAYzga0ul0UKoKWloFUyL0o+SyObR8QKB4tOstlLREIIU8+cRTPPLww5RmStTqHba3dsnlc1x54AEO+1WssUVCkkimUxTTZQ63DsGNEUtnMDsBtdlDSusFhBDYloPtOEyjYX07qqJCCIP+gGIiRUyPsX7/GSKahud7RNwIsqXStJrIGQlik5XjublZbtx8HkUVhExSIviBj+2McT0XXY+STmVA9LFkAykFEVVjrJocHB5QnimjaRqddpviXIFMNkcyXsYwGoyMEaqqEIvHmFuYo36tht3uI+cVbMum1qsyl1OZP1ueeCcpAUEQoijqsWRw/DlA38dodoiEEkogGLW7BK7HaGQSBAEXPvQhkmdOggyBPcRrdmhe30DTFcpLS/gHWxjNXbbubGEpSc6eu4+tjWs0bw/Y327iuR52d0x7f0Rxbpmxs4tpuvT6bWzbotWcZ23tFHOzK2y+fJX6ay3iaxJKSkbRA2y5w6DbAtmn1+vgjR3GhslBdQ/hhxQzOQLLZH55lWfd460g3etoEQ0fB8sZEY2rLF1YJVLQKeWL7FUPaQ42iSoys3MlIg/orCxdIZUo0u3U2WlvYw/7RKUYGxtb7O8fsHZydbKy7Ag830WJJklFFXQlSm24SzFVpjtsE4kpjD2TgdnDdEwicZ1Ws4EuyZjeAKRJGtbNjTtE1GVmF3Ls7dym1+qTyiZxTQcv6uOGAbVWg9mMjJhmRv82bGeMr/lcfv8VcD1OPrhGGJXoDjtsbd7BdX1u3LxFaiFCPpXCsbpo8SyBI9jbbhOPR6lV94nF4mSzWUJbxXcgmpCJZCTi+QwDq4cT8SnNFdk82KBabfFzH/kY8XicSrXGbm2PVCTLueVVtusuruMTUyP0mkMiUoZibpm+3aLttvFGLq4xxojZCEVjaFr0+3XOn8mQSh9vjvf4HWAQsLezT0qOUIinaPT74Doo6SQnLl0ief7yJN70uE33YINRpcH2jevIQYDb2MULxniyzf4rt5GuzKGJPCIYUC4UqO/1KeZmmYkIEmGO02sP0DHb3LmzQ7YAg1Gdft8gKmmsra3xWqZM5eUK+lDivo+fQol49N09+iObsBfHGhl4gUMgufRGQ9zeCK/d5vGvfYOP/dqvIMlvyyX6nsVxHYTqoycU9KRK22thVg3i0RijUZNOZ59kbDKHe2blCifmzxGEIeOkha7E6O+3eezz36TX73Pp0iVmoiUavX0ajQZIkC1FKShx+j2T2cIS6VSJ5qhFOpcgUEIMxyBZyKIrMZ5+9TrPfvEx9IU0599/AqPVptMZENVKrJ6+QmtUx+yM2N24yfzqMgvZFfZadRQlwXMvPMZ4bH7vG36PMXbGFNYKnHj0DI7jUrMajNsW9niMrsGlRy9R263woQ9/kHpji8Ot2/imRypZ5szSwzzzzFMc7Nc5ffo0vqrQb9i4BiSLCnLGRUpH6e/0EQIcOY6ORn5mnmanh+35xNMZtFQEY/+QZ7/8JxgxBSUTwR757G7WibkuZ09doeO7mLUmWsPGzlgsXDqB4zh4EZmN2i5/vvmHrJ9YO5YMju0CIYRgNDKoVCr0+32s0KVtDolmU0SLOQg8MAw6u7scHlSo9zps1Q8ZOja2DNHzlynd99NcvHwfQhozHLVwxhqOHRCJCZSIjSRLJJIJTNNkcXGRWDxOs9HEtt2jiDMe6VyE+TOzLD96ivnTywSuRhhEcSwVTUlgmAZLy4tomka1WsU0jYkJhj0mm89hjy0keeoJ8mYIQFM10qk0mqqxu71D4Ad0Ol1M08J1BL2OTaM2QJYSRCIafjhC00Ly+RjzCyVsx2b9xBoLC/Pki3mEEKysrJBMJpmkGNa5dXMXx5bQtTQEOtn0LKOhx/5uk9DXSETz5HJztFojyukFxk2bbqfL/Kk5Zk+kyeQC5hYyFAs5DHPMYfWQ4XBAEPik0ymWlpaO7Sp1LyOEYHlpGd/1ielR7LHN3u4evV6fwWBIebnAQx98EE9TUFMlgliK9tjgueee5y/++LO89OTTJJJxFFWhP+hzWD3E9TwymSypVBpZyEgiTi69gCKlEMRIJVOYloGiKBQLBSSi3LpxwGc/+xVuXT8glCO0xkOyS2kiRY/iepzl84uU52Zwei671/fxPBchIBrVWV5eJplMcuP6zWPJ4G3FA0wmE/QHBv1ej8xsieLKAqXVVWRFJhwOMUcGu7u7DI0u21tbmMLnwY98kMTZ80AcqgOKuRmU8SaN5j6dtoPn+ySSEYRiYlgOO7s7xMtFItkIekTH9WIgubz88quUEkWyuRRBOoCkRjpTQFNUjKGNPZbRUDl/bpnWbodsJoM9tgmdEN9zqVarxGJRhCShKtMR4JsRHGX+i0Qi6LpOPqmSzWQZDIaM7TF6JEWnPiDwo8zOrKGqCkOjSs+v4SU6bO/eJh5LIMsyO7s7qHWZxTOzpNKTQLb7B/tYtoFphNSrA2ZLGqlEEduScByfdttEjXRZKp9jYe4U8eiLNLa65H0NLasSxH08aUC7d5N8Uae56xD4k/iFe3t79JwxpYUy2Vzu2HNE9zKqquK5Hu12B1VRcFwXazzJ6Fev10nnE8zOzBPGdSLSHOmMRkQDo2lz47mXOXfxLCdOnySbynLnzh3W19fpRRuTVAmSYL9aZdB3mS3lCLyQUmGFIIB+u4NjO6ytraFIMWZn1ujudDm5fpHOaETPtSjnY+Tn4hiRFqnFBKlamiBepjccsX9wwNi0SKZS6NEoJ06eJDxm2tO3kRhdkM8VyWhxZC8kU0yhxqMgSYSex7DboF6r0Wo36fUbWK7HT3/4wxRnF8D2wOwTjIY4OsQiGrv7t9l4tcqZ82ucWp9lf3eHwFbwVBdz0KdR28EPLGIJBVXRaey1+dM/+2Mu3X+eIABdjZDQ02QSSSRJUK3V8GybSEIjlU8i1hbpjUb0LQt/HFLZPSSVSNKpt6ezQ98B3/PZuLPJ3PwcCwuLWKqLYQ1IxHX8cYqxbnOrusullYvMZBcZjTs0RzsM3D0kV6K612RpfZ6oluJgd49Rrc/JS6sE/phsJkGjEWA5IcX8LLFInvnFVWLZOM8+9xiJZBTTcnBMH12JsbiwysLyOq++8gJ7bY9HP3YeLRbDGgwYtUxkO4LnOFimhabJmOMhXbOL37R5/itfY7oM/O0IIdje3+BC+iLDQY92t4U1sCbRYQYW1tgGRcIJXEJFQ1JV/MBjZ2ubTCLObLaA0bJwhi5zs/OcWFvlicbXqRwcICcF7VoXd6Qx6o2ZW5yn3e1+K+Ncs9mgVCowU14neiHBK09d5S8++yVK95eYPRknkF2CiMNe/Q6elaHbrtOq1kmksgS+x0Fzj/Q4g+TCiy98g4/83EeOJYPjZ4UTEul4jmgyh5rJIUkajH1wQuzBmN6oTqO9SX/Q4rBSpVheYCZTRhgSQW3IaGeLm+2rvOztYvpDYmmZhVyJjJwnisO45eM2Y6hOSG3rNr2DBn3zAC9skYsrrCTzJFIxLHtMbKQw+GaF9tUq1cM69cMmg/aQwkwZJZfClENGsk+nN+S+3FkifRXdi/GhRz/CUnIOptGw3hRJkul1TYYDC9+XUGM6nhiCN+L5r77E3mubRLwoj5z9WbyuT3PUYN+9hi1u07rTwapriKSNZQWoXpSsnkbyIlhGA2vUQZPSBJpCaNmkVI3WqE8sVmZmpkirs4nnGRidDioBmq4wu7rA0v1LnHjwNCE5okEByVbIpgu0G20yiTiFbIbNzVsYZpORfUCnv0FGjjN9yn07AR7p2SjRvISUcJjPlZmNlxlVh8T8GFYTImEaybOwrU2CfovR9oDWQY3V03Pgh3ReG3L9qdtkEjkCEaKnNQQS7d0uWT9HQU6iugJF0oimM7RaLRRZYIyG1GtVRqZNcnaBwsoaEU/F3m+R8CUWC/MMhjZqKHNw9RUKaR2hO/TNFo39A3pBlaaxz6jewTzs4gyOZ8lx/MkvAerRq5Gu6wiOfEddF9Mw6Ha7dDod6vU6g+GAXDxJTGhQKBBENa7vb/KF55+kNujhhwFhCKXVRYrLC7StEYedJplshlKxhGEYBGGIYwt6nTGeqzIeC4SlIY1lItEIPa/Dbn2Hw8NDfN/n/PlzLC+dwLE0Ai+GrhbpdU1anT1iiQjnzl3m6ku32XztJt5RCKApfx0hBIuLCwB02m3i8TjxWBxFUZCEwHVkTp64QLlcYmS2uPrak1iWReAleOaZ54lEQ4yRQa1WY3FxkXw+xcjscHgwwDJD4gmJKBI6MvXdA3q1Borio0Z8IlEIMNmvbPDMs4/R6VXxghHJZJSF+QU0TaPb7eAGAT3bZP3CWeKFLHo6hWEEOKMQ1VCQuj5hECBLU2P3N6JqKtFolPF4TDyewHVdJFliNDLodLoTA2fTnPxvWQRjm9svX0UIwdz6Klo6AQJkWcL3fZrNJp7nk81mJzEkdZ1YLEYymURRVdLpFEIS9Pt9PM+bxHFMxUnrgsWVIucfOcuZy2eRiDEcuIggiqzFSZdLWPjMn1pj7Ls09w+JBIJgNCa0HObn546d1uL4r8BBiAhDZEWBMCQYW4gwwA8Cms0mzUaTbrdLr9cjouuUU1kSsUmOEGPY47Gbr/D5a4+T/eASs/PztGsOvogTK+Wp90PWL50jvKnS7w9QdRU9GSHUQvrdIZX9Dr2OxkJpjniYxByblM+UiKTSnLtwP5n0JE9tp1ej068RjWvMxLOMegU6vT1y6WVqhzaNqkE+7iKmo4M3xfVczl84R61aA6Df7yOrI0rxLADpVJnTJ+6fRG1pbFNr3aI8l2PQUbBtl4AhIlTwfJ/RyODE6SV6tNjeaBMEHqfOpnBMn1b7AM+Wkccer7zyNJZXJZYQqGqElmnz2T/9v7hy5QqaqpLNJZFkmUK+gO95tAYdOoM+SU1GL6SZsVeIGyFOf0jM12jV9xmYFp43fci9EYGY5PLxXISQ+Mu//CvS8TRCSCiKMnlF3t4mX4iSzCg0divceekqqZk81WGXYc2kHJ0F2ScMQjqdNoYxwvcnOYH9wKPT6hBJJ4lYaXR9kgPacUx0XefmrZuU4yUW5hZRox5u3CaVLZBOpTBHDrF4kYNqheLyLLobpXKrxuzSIsKwkewQdzSmXx1juCbW2DqWDN7W8mcYhpPOLwgJEfhBSK/fo9tr0x/0aLfbWNaYdCZDPp1D+CFB5YCbt6+x1athRkP69oBcPsf6+mmkqEKte4hDQCSZQNIFzW6deqtGtXqIPQiQghjJRJ5sOk9SyzBsjXAcFzWhct99l8mm0mzvbNBttdnevEYgVUhkR6RKBssnY+hxFUmViOg6pZk5zpw5O7WR/Y6EtDsd0tk06UyGTqfNnVt3eObpZ0mk45y/cBnPD6g39nj+xccZO10M0yCVLPMzP/MhQuEQeCFLcwv4vk8ohYysIfMLJ4gnskR0CW9sYA4NdFmne9ig3azS6dSxrAHJVJSZQpZ0PIrnWCgy3LxxnWuvXedgv0Kn3afZ7BJPZ8nNlBC6yjgM6PdMUnqGjJrB7fmsrZ9CVae+wG8kDEMK+SKyrCKExGBgEoQAAaqmoMoKjWqVdqtJIpHi2ivXsQYjolGdRrdNzxiSzqZZWJ5nYHa5cf0mlb1DYvE484tzyKj4bgABRFSVdquJMRqh6SqarjLsjvirz/0pLz3zJLY9Il1IoqgRivl5VpZOoslxglDGlySkqE4QUZhbXSShRomHEayWQa/RJpPN4x8znsnbeAUWBG5A6IMzdrBtaHV61FsVLK/FYNSjXm8hKypLSyuYXsCoP2Bj+xpfu/04t5wtzn/oBDMzMOqP8IIZjO4Bg+6LKDbU9xvsS7cwM20e/vBlVk7O03y2gWokEIogHjExgi4HvSZyGOfRsx8hbaWpbW4wHFewe20ifZVxR9Bs9BFxhTCh0zdVwohCeh7U0pD4hZOgTlcI3wxN14nlU+w2D0mWMpSzefKJWYSSILsSp2fvs3nwFLcPvsZB8zpClkhnU0QTcPrcGqqSxOnIqH0JEYY0gzEdWyAyHsuXlvG0FJXeNkNNIz13hkQYI+LH0KU0w5aNPQjQWirJbhJ9mCAlzaL5cbqHXfZvNRm3I5yeeYD7lq+QUFOMPYdkTscddTHtMbYaIza/Tjq7hu9Nh/lvJAhCbCtEV9MoIkZE11E1ndLMPIoWI2IJlF6fhBzSbnhYYQwnIvCDgLwWJ6Wr7A+qZFd0TH2fUNVxWxKxTBEl6tC6ZRB0NdyeR3P3gN7hLrY5wNEGJAoqJ5IrZCKz2GOVqJ2g/WqdymtbbN+5xe7GBpWdbeaysyxmV4npCeKFOA2rSWWvw30z7yfjzSEpcS5d+SgL5fuPJYN3xP4jDMEe2xiGgWVZNBp1dnd38Tyf9YUF4vE4h80Gg6DPnZ07vHT7OtVxk5lxiUQ2RiQSYTQ0GQ4GZFQXEIRBSChCZFmQzqRYWVml/sIAl8kQ23McMimdKyceYHlpGVXReObxJwliJukTSV59/mXuP/MQqAo72zt4roI1GBMCB5UD8vkcuXyGUIipm9R3QFFk8oU8sqpQKBY5rA4IQ8hkMuzu7RHVTIQrcfv2BjPpLNliehJPzrH54he/iGU5xGJ5zI5J3+1ycekcK8k1tre2J3knEKyurWLoSbr1HnFF4CV8Urk0QZii1WyjNHU0RUUSCsOBQbk8Q54cp09c5sT6JVrdFqPBCMMwCMOQfD6Lu1pmc3ODhcVFZst5Nr/xPPZwagj9RiQhcXBQYTAYEAQB5XKZ82cv4HkTf+zaYQ1V99A0Fcsc8+9/4hf4ymc/x3g8RgiYmSnh21Ecz8bxbHK5dfZfZQAAB75JREFUHOlFjUQ8wXC4j2M7FPIzEIQcViooaZlxOCYwx6hCJfAVzJGFLKtkMjluXL9Jq9nDVQLKM2UymTTZbBbBJIWFqirMzs3SeLHCrRu3SCZSLC6v8NTXv4kkHW8sJ8JjmgcIIZrA7rF+/KPHchiGxXf7In7UmOr43uYe0y8cQ8fH7gCnTJky5cedqQ/YlClT3rNMO8ApU6a8Z5l2gFOmTHnP8pY7QCFEXgjx8tGnJoSo3PX9eJlJvr/z/ldCiBtCiE+/hd/8fSHEv/pBXdO9ylTH9z5THU94y2YwYRi2gfsAhBC/DYzCMPy9u+sIIQSTBZZ3Mtb8PwJ+KgzD2vdTWQgxDfFyTKY6vveZ6njCO/YKLIQ4IYS4LoT4DHANWBRC9O7a/8tCiE8ebc8IIf5fIcTzQohnhRDv+x7H/iSwBHxJCPGbQoiCEOJPhRCvCiGeFEJcOKr3O0KITwshngA+9YZjfEII8YQQYlkIsfW6YIUQ2bu/T/nOTHV87/Ne0/E7PQd4BvhfwjA8B1S+S73fB343DMMHgb8NvC7QR4QQ/+aNlcMw/PtAA3h/GIa/D/xL4JkwDC8Bv81fF9IZ4GfDMPy11wuEEP8h8F8DHw/DcBd4AvjY0e5fAf4oDMNpcuDvj6mO733eMzp+p5+Im2EYPv991PswcHoywgYgK4SIhmH4DPDM9/H7nwJ+HiAMwy8KIT4lhIgf7ftcGIZ3x8b5CPAw8NEwDF/PnfdJ4DeBPwf+HvB3vo9zTpkw1fG9z3tGx+/0CNC4azvgrzuZ6XdtC+DhMAzvO/rMh2F4vHAO3/0aADaANHDy9YIwDL8BnBJC/AzghmF4vHja702mOr73ec/o+AdmBnM0cdoVQpwUQkjAf3DX7i8D//j1L0KI+97i4R8HfvXotx8GKmEYvlFgr7MN/EfAZ4QQZ+8q/wPgM8C/fYvnnnLEVMf3Pve6jn/QdoD/DPgC8CRwcFf5PwZ+8mjy8zrwD+A7zx28Cf8d8BNCiFeBf8Fk+PsdCcPwOpPh8R8LIVaPij/D5Inyh2/hfqZ8O1Md3/vcszp+z/oCCyF+Gfi5MAy/q9Cn/Pgy1fG9z9vV8XvSLEAI8b8ymcD92PeqO+XHk6mO733eCR2/Z0eAU6ZMmTL1BZ4yZcp7lrfUAQohfDHxFXxNCPFHQojYcU8shPigEOLPv0edFSHEa2/xuH8hhMgcbf+mmPgdfua41/le4Iet1ynvLtN2/P/zVkeA1pG9zwXAAf6zu3eKCe/qqDIMw4+HYfi6684/Aj4ShuGvvpvX9GPAj7xep7yj/Mjr+4fVjt/OTT4OnDjq3W+JSXSH15j4Dn5UCPGUEOLFoydMAkAI8TEhxE0hxIvA33orJxNCrAkhXhJCPCSE+A0x8UH8KyHEHSHE795Vb0dMfAz/DbAG/KUQ4reEEHEhxP8pJj6LLwkhfuGo/mN32y8JIb4phLj8NuTy484PXK9Huvi8EOKVo1HILx2V7wghflcIcfVITyeOyleEEF89Mrf4ihBi6XuUf0oI8fti4l+6JSYuVIiJf+nfvOs6PvP638F7mPd2Ow7D8Pv+MIkYAZPV488B/zmwwsRa/H1H+wrAY0D86Ps/Y2LvowP7TCy5BfB/A39+VOdB4JNvcr6VI2WcBl4CLh+V/wawxcT+R2eS12DxaN8OUHiT7f8B+LWj7QxwG4gDfxf4V0flp4Dn34pM7oXPu6DXXwT+97u+p+/S1z8/2v71u47zZ8DfPdr+T4A/+R7lnwL+iMkD/hywcVT+gbvqpJkY1yrvtvzfA/r+kW3Hb1VwPvDy0edfA9rRzW3fVedvAK276l0H/g8moXceu6veJ14X3Hc53wpQB24C5+4q/403NKC/ZBJi57sJ7vkjJbx+XXvAWSDGxM1GBf5H4L94t/9A34UG8cPW66kj3fxPTBzjXy/fAdaOtlWgfbTdAtS7ylvfo/xTwK/eddzhXdvXgCKT177fe7dl/x7R949sO36rdoBWGIZ/zd1FTByh73ZfEcCXwjD8lTfUe6tuMq/TZ3KTP8VECa9j37Xt871tGgXwi2EY3vq2HUJ8CfgFJhEtHjjmdf4480PVaxiGt4UQV4CPA78jhPhKGIb/4vXdd1d9q8e+i7v/Pu72Zf008GvAL/M9PA/uYabt+IgfxETn00zcY16fv4kLIU4x6f1XhBDrR/V+5Tsd4A04TPwPf10I8R+/jev6AvBPxJGmhRB3Z1L+JJPQPs+FYdh9G+e4l3nH9CqEmAPMMAz/APifgSt37f6lu/5/6mj7SSYdFkx8Rx//HuXfjU8B/yV8y7VqypvznmjH73gHGIZhk8nQ9t+JiY/fU8CZcBLa5h8Cnz+aPG28/hshxIPiKMjidzimwWRI/ltCiE8c89L+JZPh8atCiGtH318//gvAgKnT/HfkHdbrReBZIcTLwH8P/M5d+7JHx/+nwG8dlf0T4O8dlf+do33frfy73UcduMFU19+V90o7nnqC8K0RydeZKPidDP895S0ghNgBHgzDsPUDPEcMuApcCcOw/4M6z5QfPsdpx+952y4hxK8zCd74z6ed372NmIRcugH862nnd29x3HY8HQFOmfL/tVsHMgAAAADC/K0D6YdosbU/QOBLAIEtAQS2BBDYEkBgK8YuKYWCIdQDAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc028c84d30>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1948,9 +1993,9 @@
      "output_type": "stream",
      "text": [
       "Confusion matrix:\n",
-      "[[138   6   7]\n",
-      " [ 40  95   2]\n",
-      " [ 33  11 198]]\n",
+      "[[133   7  11]\n",
+      " [ 48  88   1]\n",
+      " [ 40  12 190]]\n",
       "(0) forky\n",
       "(1) knifey\n",
       "(2) spoony\n"
@@ -2028,7 +2073,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/11_Adversarial_Examples.ipynb b/11_Adversarial_Examples.ipynb
index 8dc1bbb..2c63ec2 100644
--- a/11_Adversarial_Examples.ipynb
+++ b/11_Adversarial_Examples.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2 and it would take too much effort to update this tutorial to the new API.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -50,7 +59,6 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -107,7 +115,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -168,9 +175,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -204,9 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model = inception.Inception()"
@@ -689,7 +692,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -885,7 +887,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -975,7 +976,6 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1152,7 +1152,6 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1360,7 +1359,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1374,9 +1373,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/12_Adversarial_Noise_MNIST.ipynb b/12_Adversarial_Noise_MNIST.ipynb
index ab3473a..0688cfd 100644
--- a/12_Adversarial_Noise_MNIST.ipynb
+++ b/12_Adversarial_Noise_MNIST.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2 and it would take too much effort to update this tutorial to the new API.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -2774,7 +2783,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/13B_Visual_Analysis_MNIST.ipynb b/13B_Visual_Analysis_MNIST.ipynb
index c600282..6441ae1 100644
--- a/13B_Visual_Analysis_MNIST.ipynb
+++ b/13B_Visual_Analysis_MNIST.ipynb
@@ -47,6 +47,15 @@
     "![Flowchart](images/13b_visual_analysis_flowchart.png)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## TensorFlow 2\n",
+    "\n",
+    "This tutorial was developed using TensorFlow v.1 back in the year 2016. There have been significant API changes in TensorFlow v.2. This tutorial uses TF2 in \"v.1 compatibility mode\", which is still useful for learning how TensorFlow works, but you would have to implement it slightly differently in TF2 (see Tutorial 03C on the Keras API). It would be too big a job for me to keep updating these tutorials every time Google's engineers update the TensorFlow API, so this tutorial may eventually stop working."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -58,23 +67,35 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/compat/v2_compat.py:88: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "non-resource variables are not supported in the long term\n"
      ]
     }
    ],
    "source": [
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
-    "import tensorflow as tf\n",
-    "import numpy as np\n",
-    "from sklearn.metrics import confusion_matrix\n",
-    "import math"
+    "# Use TensorFlow v.2 with this old v.1 code.\n",
+    "# E.g. placeholder variables and sessions have changed in TF2.\n",
+    "import tensorflow.compat.v1 as tf\n",
+    "tf.disable_v2_behavior()"
    ]
   },
   {
@@ -86,16 +107,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.9.0'"
+       "'2.1.0'"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -120,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -137,7 +158,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -167,7 +188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -203,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -245,7 +266,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -288,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -307,14 +328,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f76ba043860>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -359,7 +380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -375,7 +396,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -391,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -407,7 +428,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -425,7 +446,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -441,9 +462,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-16-df6771052e21>:2: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use `tf.keras.layers.Conv2D` instead.\n",
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Please use `layer.__call__` method instead.\n"
+     ]
+    }
+   ],
    "source": [
     "net = tf.layers.conv2d(inputs=net, name='layer_conv1', padding='same',\n",
     "                       filters=16, kernel_size=5, activation=tf.nn.relu)"
@@ -458,9 +492,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-17-b75c98dafe2c>:1: max_pooling2d (from tensorflow.python.layers.pooling) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use keras.layers.MaxPooling2D instead.\n"
+     ]
+    }
+   ],
    "source": [
     "net = tf.layers.max_pooling2d(inputs=net, pool_size=2, strides=2)"
    ]
@@ -474,7 +518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -484,7 +528,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -500,11 +544,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-20-f3e227e0e1ce>:1: flatten (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use keras.layers.Flatten instead.\n"
+     ]
+    }
+   ],
    "source": [
-    "net = tf.contrib.layers.flatten(net)\n",
+    "net = tf.layers.flatten(net)\n",
     "\n",
     "# This should eventually be replaced by:\n",
     "# net = tf.layers.flatten(net)"
@@ -519,9 +573,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From <ipython-input-21-33fd5057adca>:2: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use keras.layers.Dense instead.\n"
+     ]
+    }
+   ],
    "source": [
     "net = tf.layers.dense(inputs=net, name='layer_fc1',\n",
     "                      units=128, activation=tf.nn.relu)"
@@ -536,7 +600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -553,7 +617,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -569,7 +633,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -585,7 +649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -612,7 +676,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -628,7 +692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -648,7 +712,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -668,7 +732,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -684,7 +748,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -709,7 +773,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -727,7 +791,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -752,7 +816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -768,7 +832,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -828,7 +892,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -869,7 +933,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -925,7 +989,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1010,14 +1074,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 10.3% (1032 / 10000)\n"
+      "Accuracy on Test-Set: 8.7% (871 / 10000)\n"
      ]
     }
    ],
@@ -1036,7 +1100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "scrolled": true
    },
@@ -1045,108 +1109,108 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Optimization Iteration:      1, Training Accuracy:  12.5%\n",
-      "Optimization Iteration:    101, Training Accuracy:  79.7%\n",
-      "Optimization Iteration:    201, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    301, Training Accuracy:  93.8%\n",
-      "Optimization Iteration:    401, Training Accuracy:  90.6%\n",
-      "Optimization Iteration:    501, Training Accuracy:  96.9%\n",
-      "Optimization Iteration:    601, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:      1, Training Accuracy:  10.9%\n",
+      "Optimization Iteration:    101, Training Accuracy:  82.8%\n",
+      "Optimization Iteration:    201, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    301, Training Accuracy:  90.6%\n",
+      "Optimization Iteration:    401, Training Accuracy:  89.1%\n",
+      "Optimization Iteration:    501, Training Accuracy:  93.8%\n",
+      "Optimization Iteration:    601, Training Accuracy:  87.5%\n",
       "Optimization Iteration:    701, Training Accuracy:  92.2%\n",
-      "Optimization Iteration:    801, Training Accuracy:  93.8%\n",
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-      "Optimization Iteration:   1401, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:    801, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:    901, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1001, Training Accuracy:  95.3%\n",
+      "Optimization Iteration:   1101, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   1501, Training Accuracy: 100.0%\n",
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+      "Optimization Iteration:   1701, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   2401, Training Accuracy:  95.3%\n",
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+      "Optimization Iteration:   2701, Training Accuracy:  92.2%\n",
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+      "Optimization Iteration:   5601, Training Accuracy:  96.9%\n",
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+      "Optimization Iteration:   7001, Training Accuracy:  96.9%\n",
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-      "Optimization Iteration:   9001, Training Accuracy:  98.4%\n",
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+      "Optimization Iteration:   9001, Training Accuracy: 100.0%\n",
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-      "Optimization Iteration:   9701, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9801, Training Accuracy:  98.4%\n",
-      "Optimization Iteration:   9901, Training Accuracy: 100.0%\n",
-      "CPU times: user 26.8 s, sys: 3.86 s, total: 30.6 s\n",
-      "Wall time: 25 s\n"
+      "Optimization Iteration:   9401, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9501, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9601, Training Accuracy:  98.4%\n",
+      "Optimization Iteration:   9701, Training Accuracy: 100.0%\n",
+      "Optimization Iteration:   9801, Training Accuracy:  96.9%\n",
+      "Optimization Iteration:   9901, Training Accuracy:  98.4%\n",
+      "CPU times: user 25.6 s, sys: 2.81 s, total: 28.4 s\n",
+      "Wall time: 24.7 s\n"
      ]
     }
    ],
@@ -1157,7 +1221,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {
     "scrolled": true
    },
@@ -1166,15 +1230,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy on Test-Set: 98.8% (9879 / 10000)\n",
+      "Accuracy on Test-Set: 98.8% (9881 / 10000)\n",
       "Example errors:\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f76b7c59320>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -1185,26 +1249,28 @@
      "output_type": "stream",
      "text": [
       "Confusion Matrix:\n",
-      "[[ 970    0    0    0    0    0    3    0    4    3]\n",
-      " [   0 1125    4    0    0    0    2    3    1    0]\n",
-      " [   0    1 1022    0    1    0    0    5    3    0]\n",
-      " [   0    0    1 1001    0    2    0    3    2    1]\n",
-      " [   0    0    1    0  958    0    1    2    2   18]\n",
-      " [   2    0    0    4    0  881    2    0    2    1]\n",
-      " [   4    2    0    1    1    4  946    0    0    0]\n",
-      " [   0    0    6    0    0    0    0 1019    1    2]\n",
-      " [   1    0    2    3    0    2    0    3  958    5]\n",
-      " [   0    2    0    0    2    2    0    4    0  999]]\n"
+      "[[ 977    0    1    0    0    0    0    1    1    0]\n",
+      " [   0 1125    4    0    0    1    1    3    1    0]\n",
+      " [   1    0 1029    0    0    0    0    2    0    0]\n",
+      " [   0    0    3 1000    0    4    0    0    2    1]\n",
+      " [   0    0    3    0  973    0    1    1    0    4]\n",
+      " [   2    1    0    3    0  883    3    0    0    0]\n",
+      " [   6    2    0    1    1    4  943    0    1    0]\n",
+      " [   1    0    8    1    0    0    0 1016    1    1]\n",
+      " [   5    0   11    2    1    4    1    2  945    3]\n",
+      " [   3    3    1    0    4    4    0    3    1  990]]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7690094240>"
+       "<Figure size 288x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1240,7 +1306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1256,7 +1322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1265,7 +1331,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
@@ -1274,7 +1340,7 @@
        "['layer_conv1/Conv2D', 'layer_conv2/Conv2D']"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 43,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1285,7 +1351,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -1294,7 +1360,7 @@
        "2"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 44,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1319,7 +1385,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1448,7 +1514,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1507,7 +1573,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
@@ -1529,9 +1595,9 @@
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f768803b7f0>"
+       "<Figure size 432x288 with 10 Axes>"
       ]
      },
      "metadata": {},
@@ -1560,7 +1626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -1582,9 +1648,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f75f62db208>"
+       "<Figure size 432x288 with 10 Axes>"
       ]
      },
      "metadata": {},
@@ -1606,7 +1672,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 49,
    "metadata": {
     "scrolled": true
    },
@@ -1616,54 +1682,54 @@
      "output_type": "stream",
      "text": [
       "Iteration: 0\n",
-      "Predicted class: 1, score:  65.21%\n",
-      "Gradient min: -0.754999, max:  0.602095, stepsize:      5.48\n",
-      "Loss: -0.24191949\n",
+      "Predicted class: 8, score:  89.26%\n",
+      "Gradient min: -0.846559, max:  0.558144, stepsize:      5.45\n",
+      "Loss: 0.3713841\n",
       "\n",
       "Iteration: 1\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.959483, max:  0.945845, stepsize:      3.74\n",
-      "Loss: 31.78731\n",
+      "Gradient min: -0.535254, max:  0.621156, stepsize:      5.34\n",
+      "Loss: 34.539898\n",
       "\n",
       "Iteration: 2\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.698926, max:  0.681807, stepsize:      4.26\n",
-      "Loss: 49.426582\n",
+      "Gradient min: -0.664117, max:  0.673569, stepsize:      5.53\n",
+      "Loss: 45.18827\n",
       "\n",
       "Iteration: 3\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.679672, max:  0.737549, stepsize:      4.47\n",
-      "Loss: 54.057976\n",
+      "Gradient min: -0.549961, max:  0.498956, stepsize:      5.67\n",
+      "Loss: 48.934826\n",
       "\n",
       "Iteration: 4\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.624817, max:  0.728835, stepsize:      4.41\n",
-      "Loss: 59.83038\n",
+      "Gradient min: -0.540532, max:  0.564252, stepsize:      5.45\n",
+      "Loss: 50.952587\n",
       "\n",
       "Iteration: 5\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.617483, max:  0.689194, stepsize:      4.47\n",
-      "Loss: 58.287357\n",
+      "Gradient min: -0.581356, max:  0.486933, stepsize:      5.69\n",
+      "Loss: 51.000446\n",
       "\n",
       "Iteration: 6\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.678464, max:  0.716904, stepsize:      4.35\n",
-      "Loss: 61.191967\n",
+      "Gradient min: -0.578246, max:  0.520858, stepsize:      5.55\n",
+      "Loss: 51.367252\n",
       "\n",
       "Iteration: 7\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.649330, max:  0.682045, stepsize:      4.37\n",
-      "Loss: 59.402054\n",
+      "Gradient min: -0.592440, max:  0.511202, stepsize:      5.60\n",
+      "Loss: 51.47485\n",
       "\n",
       "Iteration: 8\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.670582, max:  0.723849, stepsize:      4.29\n",
-      "Loss: 61.544674\n",
+      "Gradient min: -0.589151, max:  0.507705, stepsize:      5.53\n",
+      "Loss: 51.796883\n",
       "\n",
       "Iteration: 9\n",
       "Predicted class: 2, score: 100.00%\n",
-      "Gradient min: -0.639827, max:  0.774844, stepsize:      4.33\n",
-      "Loss: 60.820866\n",
+      "Gradient min: -0.614109, max:  0.527479, stepsize:      5.59\n",
+      "Loss: 51.947083\n",
       "\n"
      ]
     }
@@ -1684,16 +1750,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 50,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7638092ef0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -1713,7 +1779,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 51,
    "metadata": {
     "scrolled": false
    },
@@ -1737,9 +1803,9 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f75f6c32c18>"
+       "<Figure size 432x288 with 10 Axes>"
       ]
      },
      "metadata": {},
@@ -1779,7 +1845,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1853,7 +1919,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/13_Visual_Analysis.ipynb b/13_Visual_Analysis.ipynb
index 49286db..bcefc5a 100644
--- a/13_Visual_Analysis.ipynb
+++ b/13_Visual_Analysis.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2 and it would take too much effort to update this tutorial to the new API.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -46,7 +55,6 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -102,7 +110,6 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -163,9 +170,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -219,9 +224,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "conv_names = get_conv_layer_names()"
@@ -237,9 +240,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -266,9 +267,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -299,9 +298,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -339,9 +336,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def optimize_image(conv_id=None, feature=0,\n",
@@ -691,9 +686,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -860,9 +853,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -897,7 +888,6 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -932,9 +922,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -967,9 +955,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1002,9 +988,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1037,9 +1021,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1072,9 +1054,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1107,9 +1087,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1142,9 +1120,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1177,9 +1153,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1212,9 +1186,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1247,9 +1219,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1282,9 +1252,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1317,9 +1285,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1352,9 +1318,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1387,9 +1351,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1422,9 +1384,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1457,9 +1417,7 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1493,7 +1451,6 @@
    "cell_type": "code",
    "execution_count": 35,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1545,7 +1502,6 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -1591,9 +1547,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2110,9 +2064,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2209,7 +2161,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -2223,9 +2175,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/16_Reinforcement_Learning.ipynb b/16_Reinforcement_Learning.ipynb
index 849ccbb..fcffd32 100644
--- a/16_Reinforcement_Learning.ipynb
+++ b/16_Reinforcement_Learning.ipynb
@@ -261,6 +261,15 @@
     "You can also have two environments named `tf-gpu` and `tf-gpu-gym` for the GPU versions of TensorFlow."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## TensorFlow 2\n",
+    "\n",
+    "This tutorial was developed using TensorFlow v.1 back in the year 2016-2017. There have been significant API changes in TensorFlow v.2. This tutorial uses TF2 in \"v.1 compatibility mode\". It would be too big a job for me to keep updating these tutorials every time Google's engineers update the TensorFlow API, so this tutorial may eventually stop working."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -274,19 +283,38 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
-    "import tensorflow as tf\n",
     "import gym\n",
     "import numpy as np\n",
     "import math"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/compat/v2_compat.py:88: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "non-resource variables are not supported in the long term\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Use TensorFlow v.2 with this old v.1 code.\n",
+    "# E.g. placeholder variables and sessions have changed in TF2.\n",
+    "import tensorflow.compat.v1 as tf\n",
+    "tf.disable_v2_behavior()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -296,10 +324,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import reinforcement_learning as rl"
@@ -314,16 +340,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.1.0'"
+       "'2.1.0'"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -335,7 +361,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "scrolled": true
    },
@@ -343,10 +369,10 @@
     {
      "data": {
       "text/plain": [
-       "'0.8.1'"
+       "'0.17.1'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -367,7 +393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -384,10 +410,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [],
    "source": [
     "rl.checkpoint_base_dir = 'checkpoints_tutorial16/'"
@@ -402,10 +426,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 8,
+   "metadata": {},
    "outputs": [],
    "source": [
     "rl.update_paths(env_name=env_name)"
@@ -436,33 +458,28 @@
     "scrolled": true
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "[2017-05-15 15:48:47,348] Making new env: Breakout-v0\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "WARNING:tensorflow:From /home/magnus/development/TensorFlow-Tutorials/reinforcement_learning.py:1189: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use `tf.keras.layers.Conv2D` instead.\n",
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Please use `layer.__call__` method instead.\n",
+      "WARNING:tensorflow:From /home/magnus/development/TensorFlow-Tutorials/reinforcement_learning.py:1205: flatten (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use keras.layers.Flatten instead.\n",
+      "WARNING:tensorflow:From /home/magnus/development/TensorFlow-Tutorials/reinforcement_learning.py:1209: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Use keras.layers.Dense instead.\n",
+      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/training/rmsprop.py:119: calling Ones.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
+      "Instructions for updating:\n",
+      "Call initializer instance with the dtype argument instead of passing it to the constructor\n",
       "Trying to restore last checkpoint ...\n",
-      "INFO:tensorflow:Restoring parameters from checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "[2017-05-15 15:48:47,868] Restoring parameters from checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Restored checkpoint from: checkpoints_tutorial16/Breakout-v0/checkpoint-127639066\n"
+      "INFO:tensorflow:Restoring parameters from checkpoints_tutorial16/Breakout-v0/checkpoint-1175644\n",
+      "Restored checkpoint from: checkpoints_tutorial16/Breakout-v0/checkpoint-1175644\n"
      ]
     }
    ],
@@ -483,9 +500,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "model = agent.model"
@@ -501,9 +516,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "replay_memory = agent.replay_memory"
@@ -529,7 +542,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "87584:127639721\t Epsilon: 0.10\t Reward: 12.0\t Episode Mean: 12.0\n"
+      "2388:1176704\t Epsilon: 0.10\t Reward: 26.0\t Episode Mean: 26.0\n"
      ]
     }
    ],
@@ -614,12 +627,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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A5L8TESYl7VxAhySuOZDGpDAkUwqnXR7+QEX0cPkFXszNRq4Po2kOu5iPUdp4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\n3SjZ08d/0AAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8851b78940>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -653,12 +668,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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eDkUppRqVXyf3owWlAMS2DPVyJEop1bj8Orln5pUAmtyVUs2PXyf3rMrkHqnJ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\nF5F+xpjjXo3Kc1OB2caYZ0X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UsN/SIKCUqlAfrErm4U82MqRjE94cF0WdWlrN+DPdOkqpCjP9+x08/nkc53Vtxqs3DSAkOMjXSVInoEFAKVUhXl6ayH8XxHNxr5a8OKaf9gNURWgQUEqdsue+iWfKkkRGRbbm2ev6UjNIA0BVoUFAKXVKXl6ayJQliVwf1Zb/XN2HoBraEVxVokFAKfWbzfh+B/9dEM9V/drw5NV9qKEBoMop1zGbiIwUkXgRSRSRB8r4/RwRWSciRSJy7XG/FYtIjPvMr6iEK6V8a9bqZB77PI4RPVvw32s1AFRVJzwSEJEg4GXgQiAVWCMi840xcV6jJQPjgfvLmEWuMSayAtKqlPITn8bs4sF5Gzk3ohlTxvbTawBVWHlOBw0CEo0x2wFEZBYwCjgaBIwxSe63ktOQRqWUH1mweS/3ztnAoPDGvHbTAGrX1NtAq7LyhO82QIrX91Q3rLxCRCRaRFaKyJVljSAik9w40RkZGScxa6VUZfp2WwZ/+mA9vds0YPr4gYTW0gBQ1VXGMdwZxpgo4AbgBRHpdPwIxphpxpgoY0xUs2b6kgml/NGq7Zn88b1oOjWvxzsTBlGvtt5XUh2UJwjsArzf/9bWDSsXY8wu93c7sAzodxLpU0r5gZiUg9z8ju0O+r2bB9GgjvYFVF2UJwisAbqISAcRqQWMAcp1l4+INBKR2u7/psBZeF1LUEr5vy17shg3YzWN6gYz85YztTfQauaEQcAYUwTcBSwAtgBzjDGbReQxEbkCQEQGikgqcB3wuohsdpN3B6JFZAOwFHjyuLuKlFJ+7KeMw/x++ipCg4P44JYzadlAXwhT3YgxxtdpOEZUVJSJjo72dTKUCngp+3O4/vUfKSwuYfYfh9CpWT1fJ0n9ChFZ666/nhS9sqOU+pm9h/K48c1V5BQUM2vSmRoAqjF9wkMpdYx9h/O58c2V7D9SwLsTB9G9VZivk6ROIw0CSqmjDuUU8vvpq9l1MJfp46Lo266hr5OkTjMNAkopAA7nFzHurdX8lH6Y138fxeCOTXydJFUJ9JqAUorcgmJufnsNG3cd4pUb+3NuhD60GSj0SECpAJdfVMxt769lddJ+nru+LyN6tvR1klQl0iCgVAArKi7h7g9j+HZbBv+5qjejIk+mWzBVHWgQUCpAlZQY/jI3lq837+Wfl/VgzKD2vk6S8gENAkoFIGMMf/90E/PW7+IvI7oycVgHXydJ+YheGFYqwJSUGJ74cgsfrErmjuGduPO8zr5OkvIhDQJKBQhjDIu2pPPMgnji07IZPzScv4zo6utkKR/TIKBUAFiRuI+nF8QTk3KQDk3rMnVsPy7r0woRfS9woNMgoFQ1tj75AM98E88PiZm0bhDCU9f05pr+bfWdwOooDQJKVUPxe7N59pt4volLo0ndWvzzsh7cMLg9IcH6Okh1LA0CSlUjOzOP8MKiBD6J2UW9WjW578IIJgzroK+CVL9IS4ZS1UBRcQkvLU3kpSWJ1AwSJp3TkdvP7UTDOrV8nTTl5zQIKFXF7dh3hHtmx7Ah5SCjIlvz0CXdaRGmbwBT5aNBQKkqyhjDh6tTePzzOIKDhKlj+3F539a+TpaqYjQIKFUFZWTn88DHsSzems5ZnZvwzHV9adUg1NfJUlWQBgGlqpiFcWk88HEs2flF/POyHowfGk6NGnq/v/ptNAgoVUUcyS/i8c/jmLUmhR6twvhwTCQRLer7OlmqitMgoFQVsHbnAe6dE0Py/hxuO7cT914YQa2a+sCXOnUaBJTyY0fyi5iyOIE3lm+nVYNQZt16pr72UVUoDQJK+SFjDAs2p/HYZ5vZfSiP0VHtePiy7oSFBPs6aaqa0SCglJ9Jzszh0c82s2RrOt1a1mfK2H5EhTf2dbJUNaVBQCk/kV9UzBvfbWfqkkRq1hD+fml3xg0NJ1g7e1OnkQYBpfzAisR9/P3TTWzPOMIlvVvyj8t66H3/qlJoEFDKh9Kz83jiiy18GrOb9o3r8NaEgZzXtbmvk6UCiAYBpXwgr7CY937cyZTFCeQXlfDn87twx/BO2tWzqnQaBJSqRIXFJcxdm8qLixLYm5XHORHNePTyHnRsVs/XSVMBSoOAUpWgpMTwWexunl+4jaTMHPq1b8hzo/sytFNTXydNBTgNAkqdRsYYFm9J55lv4tm6N5tuLeszfVwUv+vWXN/vq/yCBgGlTpMff8rkvwu2si75IOFN6vDimEgu79NaO3tTfkWDgFIVbNOuQzz19VaWJ+yjZVgI/7m6N9cOaKv3+yu/pEFAqQpyKLeQZxbE8/6qnTSqU4u/X9qdm848Q+/4UX5Ng4BSp8gYwycxu3jiiy3sP1LAuCHh3HtRhPbzo6qEch2fishIEYkXkUQReaCM388RkXUiUiQi1x732zgRSXCfcRWVcKX8QWJ6Nje8sYrJszfQplEd5t81jEev6KkBQFUZJzwSEJEg4GXgQiAVWCMi840xcV6jJQPjgfuPm7Yx8AgQBRhgrZv2QMUkXynfyC0oZuoS28VzaHAQT1zVizED2xOkF31VFVOe00GDgERjzHYAEZkFjAKOBgFjTJL7reS4aUcAC40x+93vC4GRwIennHKlfGTxljQemb+Z1AO5XNO/LQ9e0o2m9Wr7OllK/SblCQJtgBSv76nA4HLOv6xp2xw/kohMAiYBtG/fvpyzVqpy7TqYy6PzN7MwLo0uzesxe5K+4EVVfX5xYdgYMw2YBhAVFWV8nByljrH/SAGvLkvknR93EiTCAxd34+ZhHfSWT1UtlCcI7ALaeX1v64aVxy5g+HHTLivntEr5VHZeIW8u38Gby7eTW1jM1f3bMvnCCNo01C6eVfVRniCwBugiIh2wlfoY4IZyzn8B8G8RaeS+XwQ8eNKpVKoS5RUW8+6PSby67CcO5BRySe+W3HthBJ2b1/d10pSqcCcMAsaYIhG5C1uhBwEzjDGbReQxINoYM19EBgLzgEbA5SLyL2NMT2PMfhF5HBtIAB7zXCRWyt8UFpcwe00KU5ckkJaVzzkRzfjLRV3p3baBr5Om1GkjxvjXKfioqCgTHR3t62SoAFJcYvhsw26eW7iN5P05DDijEX8Z0ZUz9aKvqkJEZK0xJupkp/OLC8NK+UrK/hz++N5a4vZk0b1VGDPGR3FeV+3hUwUODQIqYG1IOcjN76yhsNhoD58qYGkQUAFpYVwaf/5wPU3q1WLWpEF0bq5v9lKBSYOACjjv/pjEo/M306tNA6aPG0iz+vq0rwpcGgRUwCgpMTz59VamfbedC7o3Z8rYftSppbuACmy6B6iAkFdYzH1zNvDFxj38/swzePSKntrZm1JoEFAB4MCRAm59N5ronQd46JJu3Hp2R737RylHg4Cq1nZmHmHCW2tIPZjLSzf047I+rX2dJKX8igYBVW2tTz7ALe9EU2wMH9wymKjwxr5OklJ+R4OAqlYKikr4dlsG8zfsZsHmvbQMC+HtCQPp2ExvAVWqLBoEVJVXXGJYtSOT+TG7+WrTXg7lFtKoTjDXR7Xlngsi9IUvSv0KDQKqSjLGEJt6iPkbdvPZht2kZ+dTp1YQI3q25Iq+rRnWpan2969UOWgQUFVKdl4hbyzfwfyYXSRl5lArqAbDuzbjisjWnN+tBaG1gnydRKWqFA0CqsrYfTCXiW+vYVtaNkM6NeGO4Z0Z0aslDUKDfZ00paosDQKqSti8+xAT315DTn4x7908mLM6N/V1kpSqFjQIKL/37bYM7nh/LWGhwXx0+xC6tQzzdZKUqjY0CCi/NntNMg/N20REi/q8NX4gLRuE+DpJSlUrGgSUXzLG8NzCbUxdksg5Ec145cb+1KutxVWpiqZ7lfI7BUUlPPBxLP9bv4sxA9vx+JW99HZPpU4TDQLKrxzKLeS299by4/ZM7r8ogjvP66ydvSl1GmkQUH5j18FcJry1mh37jvD86L5c1a+tr5OkVLWnQUD5hfXJB/jje2vJLSzmnYmDGNpJbwFVqjJoEFA+VVhcwktLEnlpaSItw0J4/5bBRLSo7+tkKRUwNAgon9mx7wj3zI5hQ8pBrurXhn+N6klYiD79q1Rl0iCgKp0xhg9WJ/N/n2+hVs0a+rIXpXxIg4CqVBnZ+TzwcSyLt6YzrHNTnrmurz4AppQPaRBQlWZhXBoPfBxLdn4Rj1zeg3FDwqmhL3tXyqc0CKjT7kh+EY99Fsfs6BR6tApj1phIuujFX6X8ggYBdVrkFhSTkJ7Nlj1ZvLLsJ5L353D78E5MviCCWjX16V+l/IUGAXVKiopLSMrMIX5vNvFp2cTvzSJ+bzY79+dgjB2nXeNQZk8awqAO+qJ3pfyNBgF10vYfKeD1737i+4R9JKQfpqCoBIAaAuFN6tK9VRhX9mtDt5b16doyjPaN6xCk5/6V8ksaBFS5ZecV8ubyHby5fDu5hcUM7dSUcUPOoGvLMLq1rE/n5vUICdbXOypVlWgQUCeUV1jMuz8m8cqynziYU8jFvVpy30URdG6uF3eVquo0CKhfVFhcwuw1KUxdkkBaVj7nRDTj/osi6NO2oa+TppSqIBoE1M8Ulxg+27Cb5xZuI3l/DgPOaMSLY/pxZscmvk6aUqqClSsIiMhI4EUgCHjTGPPkcb/XBt4FBgCZwGhjTJKIhANbgHg36kpjzG0Vk3R1OiyLT+c/X24lPi2b7q3CeGv8QIZ3baZ9+itVTZ0wCIhIEPAycCGQCqwRkfnGmDiv0W4GDhhjOovIGOApYLT77SdjTGQFp1udBh+sSubhTzYS3qQuU8f249LerfSJXqWqufIcCQwCEo0x2wFEZBYwCvAOAqOAR93/c4GXRJuOVcr073fw+Odx/K5bc165sb/e5aNUgCjPo5ttgBSv76luWJnjGGOKgEOA5wRyBxFZLyLfisjZZS1ARCaJSLSIRGdkZJzUCqhT9/LSRB7/PI6Le7XktZsGaABQKoCc7uf39wDtjTH9gHuBD0Qk7PiRjDHTjDFRxpioZs2aneYkKQ9jDM8siOe/C+K5MrI1U8f20y4dlAow5dnjdwHtvL63dcPKHEdEagINgExjTL4xJhPAGLMW+AmIONVEq1NnjOGJL7bw0tJExgxsx7PXR1IzSAOAUoGmPHv9GqCLiHQQkVrAGGD+cePMB8a5/68FlhhjjIg0cxeWEZGOQBdge8UkXf1WJSWGv3+yiTe/38H4oeH8+6re2q2DUgHqhBeGjTFFInIXsAB7i+gMY8xmEXkMiDbGzAemA++JSCKwHxsoAM4BHhORQqAEuM0Ys/90rIgqn+ISw1/nxvLxulRuO7cTfxvZVW//VCqAifF09egnoqKiTHR0tK+TUS0VFpcweXYMn8fuYfIFEfz5/M4aAJSqJkRkrTEm6mSn0yeGA0R+UTF3zlzPoi1pPHhxN/54bidfJ0kp5Qc0CFRjGdn5xO/NZuveLBZs3suapAM8NqonfxgS7uukKaX8hAaBauBIfhHb0rJdhW//bkvLJvNIwdFxmtarxX+v7cN1Ue1+ZU5KqUCjQaCKMsbwacxupixOYPu+I0eHhwYHEdGyPud3b360n/+IFvVpVr+2D1OrlPJXGgSqoMT0bP7xyWZ+3J5J7zYNuO/CCLq2rE/XlvVp16iO9vejlCo3DQJVSG5BMVOXJPDG8u2EBgfxxFW9GDOwvd7jr5T6zTQIVBGLt6TxyPzNpB7I5Zr+bXnwkm40raeneJRSp0aDgJ/bdTCXR+dvZmFcGl2a12P2pDMZrC93UUpVEA0CfqqgqITp3+9gyuIEAB64uBs3D+tAsPbvo5SqQBoE/ExRcQlfb97Li4sSSEg/zEU9WvDPy3vQtlEdXydNKVUNaRDwEwdzCpi1JoV3VySx+1Ae4U3qMH1cFOd3b+HrpCmlqjENAj6WmH6Yt1fs4OO1u8gtLGZIxyb8a1Qvftetud71o5Q67TQI+IAxhu8S9jHj+x18uy2DWkE1GBXZmglndaBH65+9c0cppU4bDQKVKK+wmI/XpfLWD0kkph+mab3a3HthBDcMbq+3eyqlfEKDQCUoLC5hTnQKUxYnkJaVT8/WYTx3fV8u7dOK2jX1fb5KKd/RIHAaFZcYPtuwm+cWbiN5fw4DzmjE86MjGdKxifbjr5TyCxoETgNjDAvj0nj2m2syM+kAABywSURBVG3Ep2XTvVUYM8ZHcV7X5lr5K6X8igaBCrYicR9PL4gnJuUgHZrWZerYflzau5V26qaU8ksaBCrI+uQDPPNNPD8kZtKqQQhPXdOba/q3paY+4auU8mMaBE7BoZxCvtq0h09jdvPj9kya1K3FPy7rwY2D2xMSrBd8lVL+T4PAScotKGbRljQ+jdnNt9vSKSw2dGhal7+M6Mq4oeHUq61ZqpSqOrTGKofC4hKWJ2QwP2Y338SlkVNQTIuw2owbEs6oyDb0ahOmF3yVUlWSBoFfYIxhXfJBPl6Xylcb93Agp5AGocGMimzDFX1bM6hDY+3WQSlV5WkQOE5BUQlfbtzDWz/sYEPqIUKDg7ioZwuu6Nuas7s0o1ZNvdCrlKo+NAg4mYfz+XB1Mu/+uJP07Hw6NqvL41f24up+bair5/mVUtVUwNduW/dm8db3ScyL2UVBUQnnRDTj6WvDOadLM723XylV7QVkECgpMSyNT2fGDzv4ITGTkOAaXDugLROGhtOlRX1fJ08ppSpNwAWBTbsOce+cGLalHaZVgxD+NrIbYwe1o2GdWr5OmlJKVbqACQLFJYbXvv2J5xduo2m92rw4JpJLerfSd/YqpQJaQASB5MwcJs+JYe3OA1zWpxX/d2UvbfkrpRTVPAgYY/hobSr/mr+ZGjWEF0ZHMiqytT7YpZRSTrUNAvuPFPDg/2JZsDmNMzs25tnrI2nTMNTXyVJKKb9SLYPA0q3p/GVuLFm5hTx0STduGdZRb/dUSqkyVKsgkFtQzBNfxvH+ymS6tqjPezcPonsrfXG7Ukr9kmoTBFL25zBuxmq27zvCLcM6cP+Irtqds1JKnUC57o8UkZEiEi8iiSLyQBm/1xaR2e73VSIS7vXbg254vIiMqLikH6t5WG06NK3LB7cM5u+X9dAAoJRS5XDCIwERCQJeBi4EUoE1IjLfGBPnNdrNwAFjTGcRGQM8BYwWkR7AGKAn0BpYJCIRxpjiil6R2jWDmD5+YEXPVimlqrXyHAkMAhKNMduNMQXALGDUceOMAt5x/88Fzhd7H+YoYJYxJt8YswNIdPNTSinlB8oTBNoAKV7fU92wMscxxhQBh4Am5ZwWEZkkItEiEp2RkVH+1CullDolftFngjFmmjEmyhgT1axZM18nRymlAkZ5gsAuoJ3X97ZuWJnjiEhNoAGQWc5plVJK+Uh5gsAaoIuIdBCRWtgLvfOPG2c+MM79fy2wxBhj3PAx7u6hDkAXYHXFJF0ppdSpOuHdQcaYIhG5C1gABAEzjDGbReQxINoYMx+YDrwnIonAfmygwI03B4gDioA7T8edQUoppX4bsQ12/xEVFWWio6N9nQyllKpSRGStMSbqZKfziwvDSimlfMPvjgREJAPYeQqzaArsC6DxfLlsfx/Pl8v29/F8uWx/H8+Xyz6ZNB7vDGPMyd9eaYypVh/sdYqAGa8qpFHzxv/Gqwpp1LypnI+eDlJKqQCmQUAppQJYdQwC0wJsPF8u29/H8+Wy/X08Xy7b38fz5bJPJo0Vwu8uDCullKo81fFIQCmlVDlpEFBKqQDml6+XFJF2wLtAC8AA04wxL4pIY2A2EA4kAdcDWUAyUA/Y4X5rAGwFfgT+CJS431oBxe57CpDrFtkRqI9930GYG6cFcATbVUawG68GIG54CpAD9AJCgANAI2ATtrvsRm6afdjnHr4CrgK6unnmA7WBQmC3m1e4S1uWW1ZD9399INTNLwnbVXewS3eRG34Ie49xLZdnRUCGy4uaLo27XXpCgMZuvp7xawDb3LCaQDOXxiJKy8lhN21t99tOt8wGLj3iPmnAXmAzcD7QHFjp8raTW6a4ee/FdiyY75aR4vKnrZuncXlS7D413Lh1gDw3fX23vYqBg+6vZz2+d8MGAy3d9MYr/ze6NNUDNrhlFgB93Xg52G3bzA0PwnaC6FkmXuvyk5tPXez234YtY53cPNq58Ypc2msC27HbPcvNp5lXfidjt2snt9xo7Ds6ZgIXuWFg+/cKcfkUCkS4tNTCduke6vKgEbYMNPTaBsnYMtja5am49V6FLat1sds91K1DDZe/bd2yC10aG7h1DcFu/xZuGUVu+lxK94kabrrt2PLTyg3PB9Ziu5650Gtb/eTS18BrmcFuvjXd903ub1ev5dQC1rvlXErpfrzNpaulW76njBlsHRDstklN7Dav4T4Zbr3y3bhBbj4lXuPUcNMJtszXcd/3AO2x/ad58mubm39nN68sl9873Pa63a3Po5SWqXTgTWPMkyIShu2S5xNjzF14EZH5QEdjTC9OwF+PBIqA+4wxPYAzgTvdW8oeABYbY7oAi933u4FvgeXGmEjgBWAp0ANbcG9x49QE4o0xIcBoINuNfzl2ox/BVtI5wF3YSrsImGKMqQU8B3zi0ncvtpIoBK5wy1+NfflOb2zfSfuwFdRsYx/l/q/bIE9gO9Z7B0gA7sfuBDHu/z9gd8x8Y0wocA12xz3ohpdgC3YEcLWbXy6219bbgJeAJ7EFtgZ2R4l0aRxjjOkLXODS9in2JUBHgBRjTFeXjixsRVeC3XlaYgtfI7e8Nm6912Mr0lddWna5/Nvp0tIcW9BzgN5unb/CBueRlFaaa9y6/g5b4b0PnOPy+s/AOuBh4H/YnWoVsMVtpxxspTYfu0NkY3eYm40xtbGVVQ7QDXgQ+BgbGLJdem7BBp5CVx7GubR+BixzedME6I+tbD9z6f8Eu6O/h624s4B4bOW8GlvJ3+jmuR9bVjLdp7/bZvEuTVe6da/j5rMYW2FswVZG/wYuc3k1w63LIeA+bKW1wBjTB1uWPZXZaJdP2cCbbrkLseXiWmCJW/9k4HHsvvI0MMzle2dsI8MTBJ4BvnTTZ7u/B7GV2nq3zn9ywzKx5f95t34LsY2yw8aYULddpgGfY/exbLedU1x+jwT6u/3uH9gylOE+r7jtXAj0duXmNWxliVvuB9h3l+QBK7Bl9WKXx89jg3FNt9xMbJ1RDExx2/cHYI77vR2w3Cu/YoERbrkfu/QeAv4GLMLWC+e4bbDS7W+93DgF2PL/FDYwDcHu+weBEdjg0t3Ve4+75T0InO3y6XxsvTbW1YePA99xHBG52m2zcvHLIGCM2WOMWef+z8buDG049g1m72AL86XYQu4RAXxo7BXv1UB3bCEQbCsabCXgaX28hm0xZLrvnpaFYFt7S93wl4Gz3PA5xr485yugn/u9M7YCxRjzDaWtBc86ZXmlsRa2VVwH2yLIwm60MGAsthDvduOeja3Af8IWykRsYQbbmn/HzWOPMeZtbCX6Nbaw1nfLOOjG9xz5ZLr1bITdsYuB713L4gJsICoCSowx3wI3YHcKAXYaY9JdvlyFDQKvGGM+xe4sniMnAc5109bAVgIXYHfWj7DbLhdbgce6dF3o8i0H25oscfMKxm6zUS7dJW49P6H0aOhjbCXRBFtxzRWRBi4PmrvljMQGrCA3fDbwX5d/hS4NN2G32/sufWku/Y3cd+O2Tbpbx49dGmKxFehWbGeL3kfZjdx2ywaSjTFbsBVUJnCZMWYpcKfbDruxAXkXcAa2rMS4/O6CrSxqYVuW61x6DrnlPI89sinBBp4o4EW3HTZSWqZaYN/w94Mbdja2gorFBhrc9xA3XrxLbzG2ot7vxkkzxux0+RPptkcNN88Sl6c1sGUw3w3DvXUw1KW9nsuvIy7Perrp6rtlBLnpjmCDmueotQQwbl5nuOF5bpyR2AoyD1tGawJbjDHfYctoXew+dxC7z81wy3kHG5CnYytbsEc/R9y4GV7fcesb7JaTDSS5betpQHmOXGpiy/0qbLkZiH1D4wjsfl3ipv8cGxjAHkV0wtY7EdgG5hpT+nbH27Hb8Ru8iEg9bCP1/yivyn467WQ/2JZQsttYB72GC7agDgCGuwysgy2gjd3GWYdtzY3FBpIUbKtlFfA2tlJZ4aY5jN0JfsTu7CXYymUttmDeiy3IxdiKpo4bdyo2Gue5dMZiC1WqS186MMml+QlKWwRp2B3zfWxlsMItt8j93Yit/Oe4v//EHvJOp7SFk+zWyWArnxg37nRsYY1xvyVgC/BlbthhN21b7NFHCfZ0yfNAgktrErblBralFO3GS8UGiavdvDPdOEFuGcat23bP9nLL24OtTGZ5refXbvw47I5lsDtQHWzFatwnGXskYLA744/AXDfvg9ijmvOwp588p41iXd5ucHlxALtjeU5/7APucdsv2i0/1q3jZ26dj7i0J7nhOS6tYW67GEqPwg5gj4BaYBsHnm2y1o2z061zFjZY5LlPFra8LHfr4Sl3X2PLtMEeDV7ttbwYt7wEbHl6iNKWa7JL83BsI2iVy49VLj/udunNcXl9BqWnzJ53afGcMo1z2y0HW/Z6Y/ejeS6NmW5dn3PjpLjhm7z+z3NpzHXz2u/+X+62s+eUWR52vyjGBmfPtInYYFaArdj2UFrGst2n0OXjMjfeXuwRcR6ljbEUl1ZPpfu+yyuDLZcGGzgOYgOn56i7CBvUXsHuK8uwgTHG/bbIre94bONmM6Wnv27BBriDLr01sfXOXuyRkGf4D9j9fQ92u4tbVhL26Gwrth4Z6cr8H9y2a+uW+5JXvfg8NvCFA5uq/BPDLqp9DNxzXEsa7BFAiTFmrdewy4EfjDH7sRstBVuQE7DRdCe2Mu+CLTwPYVsVntb4VdiMfQMbSJa5v2uxLRPBbrhvsBsrhtKgsB7ogG0R7XHf07EVyp0ico4x5mGXjkfdcldjK99Q7OmM/7j5LcNWqn/FHRpjW+xQej43AZhsjGmH3QFTsS06gw16dbGFaC1wHXbne8SdnvgXdmdp5fLjCLYQTgAeK2NTdHRp+Jtb52nYAJqPPX+JsV2ET3d5nojdQeq6owtcXrfDHjGlumWeid2BZxpj6mJbPY2wp9N2YSvoOJe/D2F3xq4unzeLyO9dPu7EHtF5lrUT29pqiD0UzwM+xFaEy9x88rFHI8HuN+OWEY9tBX6LbX2vcXl5LrYS+R5bUQ5y6x6BvX5VE3va7HM3j/3A7yltqUdid/hQN588bBlagi0vXbAB5CVsi/RCbOPDYI9WrnHTFLl12g/ciq2oLsJW5m2xlWswtvz0d2nfit3evbGtz50ubZOxp7MisY2MxtgKRrBl9wZsZZmFvQ4xC1tB73Pp+KvbRn8CXnZl8U73exI2SLzl8vFVbAXZFFtRNcUGpHBs+boTWy6K3fqcRelR5D9cei5zebnTreMm7DZf5PJ1s5tHqFu/YErPx6e69Wzu8uwDt54l2P1wB7Z818PWDUdcvtXDNmhuolQJtsL/2uVvbTc8zRjTE7t9g4A4Y8wI7Om9OGxDpSn2VO8kbFDbAKxyp5HfxJbtfwM3Y8tRF+ARbDl5Q0QaYk8LJRljUr3ShIhEAp2MMfM4Gb5u6f/KEUAwNore6zUsHmjl/p+CrUCSsJE1Bxu9b3CZ9gm2Uk3FVkzF2Oicja0kF2NbrsWUXqzLwJ6//MIr4r7ilnGRW95mr/T8G7jDTffwcUcv8W7ZL2Er/fu9fvec/wt306ZjC3A7N82j2ILX3KXXc/FwK7Zw7qX0QmIrt6wsl2cJbj0jKD0FFoat/Dwt+5nYYFboPnnYnb0Eu4MlUXrB6wJsBbLcK/3TsefOS4BlXsOnYVuKnorDc+rEcwSxwI03CdvC2evyv50bPtat3zfu++tu2D9dHqRhdyLPee692IomCVvxlGBbyPuwO//Vbt22u+Xvcd9L3Ced0lMcnlMoh9y2OYAtUxnYxgbY8jDH/X4WtnwOcdsm3aVd3PolYwPHPrfM3ZSeNngBeyT3iMuHcDfPXK+8jMYGnFzsOeZ7XFoL3bYpwAbkFLfN010+pLt895R7T8s7y2ubZmFP9XhugvjG5fMo93++S2+YW79C7DWKApcvh9280ikNdG28jtBzsGVkGbYR5NmPPBeCw93/ycBWN9147L53wCu/xaU1E3jIDZuHDdBbgUNu2G2UHhmlu22WRekNBZ51+Q+l295TZxzC7kNJ2CPFJOy+/jmuJe3Sn48th8uw++eP2COZ57Dlajx2X/fUPQeA37vpd3ilqcDl35Uuz2d6Led1bPk6hN1/X8M2zIZgy9pibOMmBrv/JmHLVxb2OuDtbl2TKD0Tscy7Xq0yRwLuPN907Hm857x+8n6D2W7geWNMOLbl+B02ajfEVrJjjTEPGmPauhbKNmxhHYFtTa7DtjDex27QvcCN2As7qS4Nl2ILSg1sC3mD+x8RaY+tZD53y9zklc7R2MNOsJXRRbjzqCLSCnuo9xP2yGMTtjClYC9eiUtfiJtvTfdpgt15sl2a87CVzARKj3ZmY1uELxtjtmEvHH7njqJaUNo76y3YQv0ltkDOwVY47xljznB5moqtPP6HbWkViEgLEamLPXoZ7dLcXkQGiEgzbMDIcGmY7NL4D5eHi4DFrrVyh1teU2zFPtalawe2FbdTRPphj4K+w1ZOLbEt5OuxlcLZ2ILfHVtJ5mN3iMewLc9r3fAibEt9OHYnW4zdOfZgd+7vsTtZjjGmsVumYFu5q7FlplhEumN33AuwZWcPdscc5/IiFHvU1RDbMt6LDQrnum0/EFuxJ7t1Dnbb/01s8MwCskSkrytbXdywfcBQ7MXnZdhW9Drsjn4P7hSoMaa5225PuDRf4bZ3OvbIZSWu4sQGoBJKj4peBCZiy/8qt913YMtMHWxFOgFboSe7cVa67eg5WuniysalbrlDsOV4L7blaty8Mt16F7g8qy0ivd32b+vWy4hIhMu7TDfdQjfsPDdeC5cWz3Q1sQ2QXthA9qxL93Ig1e0D32Arz93YfeAH7FH/S9hGWHfgC+wR4XI4+rrc31N6OrAZtsK/wq3TMLcuTV1ejMCWHc91ENy2XII9pVmIvUnkE2z5GQmkiEgj7P5/CfC6238/wZbbNS4vu2P3OQHOctv7fuBdY8wDxphXjTGt3fBhwDZjzHBOxNct/l84ChjmMjgWG/ViXOY0we7ECdhKpbEbf7gbZxalt+p5pvunG2e525C52B1hPXYnGIk9TMx3BcFz/i3PbfRcbGE7gt2ZPRe8UrAtg/0ce5QRiy34xuuTgy2Am3AtHZfGVGyF4DkayceeBtmP3RliXFo3UXrXR5GbLseN7zl09VwbKPH65LvhBZSe3/QcWXhuvcvHVtyxlJ5zfNqN60l/odc8Cl3+bMPenXMJpefMvdOYgN3RVrvhyW65BZS2Zve6vM9y+ZdL6bUbzziedB/CnrI6gq1sC13+pLrfi73yI9flTza2vKzFVtpZlLaMh2HPz96GPfVSjA3ysdjTWYVumOfceZ5bdjE26B6ktKXpqSASXNqzvfIqG1uhxnltk8OU3tq8hdLrNp7y5Tn3vxlboXparIuxp2wuccv1LmOec/Gfue2ZiK3sPHlT6NKf5Ja10y0rntJrDMal7ztsBXXIa/0910YedfM54L5nYY/K17p1OYItV97pK8YGM882zsKeMtmNPTXpGdeTPwle+b0Vu68ud3lZ7OYf79Lkua6yhtJrS9mU3t78tUuX53uOy4sD2LKYT2lZy3PLjuXY8l9C6RGk9zp5jsjMcb95j5PttstUbDDMwAbQTW45sS4N+S7teZTWXdHYI404l9d73Lp7n3UYj9c1gePORpTrmoB2G6GUUgHML08HKaWUqhwaBJRSKoBpEFBKqQCmQUAppQKYBgGllApgGgSqIRF5WEQ2i0isiMSIyGA3/B4RqVOO6cs1XhnTRYjIlyKSICLrRGSOiLQ48ZQntYwrXedZZf3WTERWich6ETn7FJZxr4hsFZGNIrJBRJ4TkeATT1kxRCTJLTvGfab8xvlcISIPVHT6KpKIhIvIDb5ORyDTIFDNiMgQ7OP1/Y3tWfIC7L3rUPpw0YmUdzzv5YZgH7R51RjTxRjTH/uUaLOTmU85XElp517HOx/YaIzpZ4xZXp6ZiUjQcd9vwz7cd6axj/IPxD4XEVrG5KfTecaYSPf582+ZgTFmvjHmyeOHuweg/EU49il/5Su+fjBMPxX+oN3VwGdlDP8z9sGWjcBSN+xV7AMpm4F//cp4F2Gfql6H7TOlXhnzn4h9crGsNIVg+5DZiH3w5zw3fDzHdn71OTDc/X8Y+/TrBuzDNS2wT87uxz58FYPtJ8UzbST24asM91so9knkjdgHc57yGvcw9onSDcCw49KaAnT4lfz9WZ654UnYbgk8D/n0xz5w9RNwm9d4f8E+2BTrPf1xy0gCmpYxfBm2G+LV2If1znbDVwI9jxsvyjt/sQ/GvYZ92vc5l18rXTrmAY1OsIzx2CdYF7r03YXtd2q9m4/nwU1PL7ZrsQ94dfNa/hTs08rbgWu90n7I5dtkX+8/gfjxeQL0U8Eb1HadEeN24FeAc71+O6Zy8dpxg9zO3+f48bCPw38H1HXf/4Z7Cvu45T4H3P0LaboPmOH+74atrEP49SBggMvd/08Df3f/v+2pQMpYjnel19otx/OSliXAlV7zvr6M6cOAAyfI31/Ls9vd/89T2pV3M2zHYmCD6TTsY/813PqeU8YykrDBy/Pk6GQ3fBnwrPv/EmCR+38ypUG8Ffa9Gcfnx9tueUHue6ynbGC72njhBMsYj30K2bNOh3DBza3vPe7/xUAX9/9gYInX8j9y690D2zUyuB6Afb3fBPJHTwdVM8aYw9jutSdhW8WzRWT8L4x+vYisw7bmelL2aZYz3fAfRCQG21fOGSeZrGHY/o4wxmzFdlkQcYJpCrCVFthWZfhJLnMgtvOsDGPf/TCT0hfVFGN7p/1VIjLCnZNPEpGhbvCv5dl893cjtmfIbGNMBpDven+8yH3WY4+qumH7lSmL9+mg572G/8/99c6TOdi+ksD2rTT3F+b5kTGm2L1noaGx74oA2yfTOV7jlbUMsEeGnnU6hO2iwrO+4a7X36HAR66svE7pezvAvgGrxBgTR+lb2ZSP+dO5QVVBjO3WeRmwTEQ2Yivut73HEZEO2M6nBhpjDojI29jW+fEEWGiMGXvc9IOxOznYPpQ2Yzv8OhlFHHtdynv5hcY1FbGVdkWW1TyXR8cwxmSJyGER6WCM2WGMWQAsEJHPgVrlyDNPh2ElXv97vnteOfgfY8zr/Hae+R7NE2PMLhHJFJE+2M7sbvuFaY/8wvATLuO44XDsOnrWrwb2HRKRJ5gv2LxQfkCPBKoZEekqIt6ty0hKew/NpvSNTWG4V+O5O3gu9prGe7yVwFki0tnNv66IRBhjVnm1VOdj+2cfKiKXeqXlHBHphT03fKMbFoHtljgee9ojUkRquPdKDyrHKnqn7desBs4Vkabu4u9YbBfEJ/If4FXXcvf0aOup6H8tz8pjATDRtZgRkTYi0vwk5/FLZmN7r2xgjIn9tRGNMYeAA153UP2e8uXNrzK2p84dInId2LwTkb4nmKy821OdJnokUP3UA6a6SqwIex53kvttGvC1iOw2xpwnIuuxvTSmYLvV5RfGGw98KCKel2f8HXvN4ShjTK6IXAa8ICIvYHtmjMW+OOQVbMW60aVpvDEmX0R+oLSHzS3YUyQnMgv7co0/Y68N/FTWSMaYPe72yKXYVucXxr4C80Rexb4oZJWIeHr8/AFYb4w59Ct5dkLGmG9cl9Q/2tjCYezLStLLGH2piHiOVmKNMX84weznYruEfrycyRkHvOZuBd6O7Sq6ItyI3dZ/x3aXPQt7Af6XxGK76t4AvH3cqS9VCbQXUaWUCmB6OkgppQKYBgGllApgGgSUUiqAaRBQSqkApkFAKaUCmAYBpZQKYBoElFIqgP0/x4TLip78pc4AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8851b78710>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -710,9 +727,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "agent.training = False"
@@ -728,9 +743,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "agent.reset_episode_rewards()"
@@ -746,9 +759,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "agent.render = True"
@@ -770,65 +781,30 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "87586:127639767\tQ-min: 1.765\tQ-max: 1.783\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
-      "87586:127639820\tQ-min: 1.608\tQ-max: 1.619\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
-      "87586:127639882\tQ-min: 1.712\tQ-max: 1.734\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
-      "87586:127639931\tQ-min: 1.968\tQ-max: 1.998\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
-      "87586:127639963\tQ-min: 1.953\tQ-max: 1.988\tLives: 5\tReward: 5.0\tEpisode Mean: 0.0\n",
-      "87586:127639985\tQ-min: 0.013\tQ-max: 0.184\tLives: 4\tReward: 5.0\tEpisode Mean: 0.0\n",
-      "87586:127640039\tQ-min: 1.651\tQ-max: 1.664\tLives: 4\tReward: 6.0\tEpisode Mean: 0.0\n",
-      "87586:127640090\tQ-min: 1.902\tQ-max: 1.919\tLives: 4\tReward: 7.0\tEpisode Mean: 0.0\n",
-      "87586:127640130\tQ-min: 1.960\tQ-max: 1.968\tLives: 4\tReward: 8.0\tEpisode Mean: 0.0\n",
-      "87586:127640166\tQ-min: 1.915\tQ-max: 1.929\tLives: 4\tReward: 9.0\tEpisode Mean: 0.0\n",
-      "87586:127640197\tQ-min: 2.002\tQ-max: 2.022\tLives: 4\tReward: 10.0\tEpisode Mean: 0.0\n",
-      "87586:127640228\tQ-min: 1.952\tQ-max: 1.982\tLives: 4\tReward: 11.0\tEpisode Mean: 0.0\n",
-      "87586:127640260\tQ-min: 2.031\tQ-max: 2.050\tLives: 4\tReward: 12.0\tEpisode Mean: 0.0\n",
-      "87586:127640306\tQ-min: 1.682\tQ-max: 1.737\tLives: 4\tReward: 13.0\tEpisode Mean: 0.0\n",
-      "87586:127640371\tQ-min: 1.700\tQ-max: 1.726\tLives: 4\tReward: 14.0\tEpisode Mean: 0.0\n",
-      "87586:127640439\tQ-min: 1.555\tQ-max: 1.665\tLives: 4\tReward: 15.0\tEpisode Mean: 0.0\n",
-      "87586:127640510\tQ-min: 1.619\tQ-max: 1.699\tLives: 4\tReward: 16.0\tEpisode Mean: 0.0\n",
-      "87586:127640552\tQ-min: -0.068\tQ-max: 0.219\tLives: 3\tReward: 16.0\tEpisode Mean: 0.0\n",
-      "87586:127640595\tQ-min: 1.868\tQ-max: 1.893\tLives: 3\tReward: 17.0\tEpisode Mean: 0.0\n",
-      "87586:127640639\tQ-min: 1.975\tQ-max: 1.996\tLives: 3\tReward: 18.0\tEpisode Mean: 0.0\n",
-      "87586:127640681\tQ-min: 1.918\tQ-max: 1.947\tLives: 3\tReward: 19.0\tEpisode Mean: 0.0\n",
-      "87586:127640718\tQ-min: 2.025\tQ-max: 2.090\tLives: 3\tReward: 20.0\tEpisode Mean: 0.0\n",
-      "87586:127640751\tQ-min: 1.981\tQ-max: 2.006\tLives: 3\tReward: 21.0\tEpisode Mean: 0.0\n",
-      "87586:127640785\tQ-min: 2.041\tQ-max: 2.072\tLives: 3\tReward: 25.0\tEpisode Mean: 0.0\n",
-      "87586:127640818\tQ-min: 2.052\tQ-max: 2.329\tLives: 3\tReward: 29.0\tEpisode Mean: 0.0\n",
-      "87586:127640840\tQ-min: 2.298\tQ-max: 2.444\tLives: 3\tReward: 30.0\tEpisode Mean: 0.0\n",
-      "87586:127640860\tQ-min: 2.400\tQ-max: 2.477\tLives: 3\tReward: 34.0\tEpisode Mean: 0.0\n",
-      "87586:127640882\tQ-min: 2.344\tQ-max: 2.398\tLives: 3\tReward: 35.0\tEpisode Mean: 0.0\n",
-      "87586:127640906\tQ-min: 2.314\tQ-max: 2.418\tLives: 3\tReward: 39.0\tEpisode Mean: 0.0\n",
-      "87586:127640927\tQ-min: 2.211\tQ-max: 2.266\tLives: 3\tReward: 40.0\tEpisode Mean: 0.0\n",
-      "87586:127640947\tQ-min: 2.433\tQ-max: 2.514\tLives: 3\tReward: 41.0\tEpisode Mean: 0.0\n",
-      "87586:127640968\tQ-min: 2.259\tQ-max: 2.518\tLives: 3\tReward: 45.0\tEpisode Mean: 0.0\n",
-      "87586:127640990\tQ-min: 2.381\tQ-max: 2.445\tLives: 3\tReward: 49.0\tEpisode Mean: 0.0\n",
-      "87586:127641011\tQ-min: 2.299\tQ-max: 2.477\tLives: 3\tReward: 53.0\tEpisode Mean: 0.0\n",
-      "87586:127641032\tQ-min: 2.431\tQ-max: 2.521\tLives: 3\tReward: 54.0\tEpisode Mean: 0.0\n",
-      "87586:127641053\tQ-min: 2.292\tQ-max: 2.394\tLives: 3\tReward: 55.0\tEpisode Mean: 0.0\n",
-      "87586:127641074\tQ-min: 2.312\tQ-max: 2.515\tLives: 3\tReward: 56.0\tEpisode Mean: 0.0\n",
-      "87586:127641094\tQ-min: 2.310\tQ-max: 2.421\tLives: 3\tReward: 60.0\tEpisode Mean: 0.0\n",
-      "87586:127641117\tQ-min: 2.284\tQ-max: 2.431\tLives: 3\tReward: 64.0\tEpisode Mean: 0.0\n",
-      "87586:127641137\tQ-min: 2.328\tQ-max: 2.442\tLives: 3\tReward: 65.0\tEpisode Mean: 0.0\n",
-      "87586:127641156\tQ-min: 2.411\tQ-max: 2.459\tLives: 3\tReward: 66.0\tEpisode Mean: 0.0\n",
-      "87586:127641178\tQ-min: 1.457\tQ-max: 2.612\tLives: 3\tReward: 73.0\tEpisode Mean: 0.0\n",
-      "87586:127641192\tQ-min: -0.155\tQ-max: 0.483\tLives: 2\tReward: 73.0\tEpisode Mean: 0.0\n",
-      "87586:127641236\tQ-min: 2.176\tQ-max: 2.289\tLives: 2\tReward: 74.0\tEpisode Mean: 0.0\n",
-      "87586:127641282\tQ-min: 2.060\tQ-max: 2.132\tLives: 2\tReward: 78.0\tEpisode Mean: 0.0\n",
-      "87586:127641340\tQ-min: 1.806\tQ-max: 1.967\tLives: 2\tReward: 79.0\tEpisode Mean: 0.0\n",
-      "87586:127641389\tQ-min: 2.202\tQ-max: 2.385\tLives: 2\tReward: 80.0\tEpisode Mean: 0.0\n",
-      "87586:127641418\tQ-min: 2.359\tQ-max: 2.446\tLives: 2\tReward: 81.0\tEpisode Mean: 0.0\n",
-      "87586:127641454\tQ-min: 2.278\tQ-max: 2.435\tLives: 2\tReward: 85.0\tEpisode Mean: 0.0\n",
-      "87586:127641487\tQ-min: 2.157\tQ-max: 2.391\tLives: 2\tReward: 86.0\tEpisode Mean: 0.0\n",
-      "87586:127641546\tQ-min: 1.722\tQ-max: 2.306\tLives: 2\tReward: 90.0\tEpisode Mean: 0.0\n",
-      "87586:127641570\tQ-min: 2.165\tQ-max: 2.662\tLives: 2\tReward: 94.0\tEpisode Mean: 0.0\n",
-      "87586:127641591\tQ-min: 2.422\tQ-max: 2.789\tLives: 2\tReward: 98.0\tEpisode Mean: 0.0\n",
-      "87586:127641605\tQ-min: 0.044\tQ-max: 0.432\tLives: 1\tReward: 98.0\tEpisode Mean: 0.0\n",
-      "87586:127641664\tQ-min: 1.532\tQ-max: 2.163\tLives: 1\tReward: 102.0\tEpisode Mean: 0.0\n",
-      "87586:127641723\tQ-min: 2.338\tQ-max: 2.518\tLives: 1\tReward: 106.0\tEpisode Mean: 0.0\n",
-      "87586:127641783\tQ-min: 1.870\tQ-max: 2.321\tLives: 1\tReward: 110.0\tEpisode Mean: 0.0\n",
-      "87586:127641830\tQ-min: 2.606\tQ-max: 2.781\tLives: 1\tReward: 114.0\tEpisode Mean: 0.0\n",
-      "87586:127641852\tQ-min: -0.278\tQ-max: 0.069\tLives: 0\tReward: 114.0\tEpisode Mean: 114.0\n"
+      "2390:1176749\tQ-min: 1.247\tQ-max: 1.411\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
+      "2390:1176802\tQ-min: 1.227\tQ-max: 1.425\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
+      "2390:1176845\tQ-min: 0.109\tQ-max: 0.144\tLives: 4\tReward: 2.0\tEpisode Mean: 0.0\n",
+      "2390:1176899\tQ-min: 1.184\tQ-max: 1.423\tLives: 4\tReward: 3.0\tEpisode Mean: 0.0\n",
+      "2390:1176954\tQ-min: 1.336\tQ-max: 1.472\tLives: 4\tReward: 4.0\tEpisode Mean: 0.0\n",
+      "2390:1177004\tQ-min: 1.303\tQ-max: 1.382\tLives: 4\tReward: 5.0\tEpisode Mean: 0.0\n",
+      "2390:1177050\tQ-min: 1.247\tQ-max: 1.539\tLives: 4\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "2390:1177070\tQ-min: 0.140\tQ-max: 0.149\tLives: 3\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "2390:1177123\tQ-min: 1.260\tQ-max: 1.348\tLives: 3\tReward: 7.0\tEpisode Mean: 0.0\n",
+      "2390:1177171\tQ-min: 1.212\tQ-max: 1.473\tLives: 3\tReward: 8.0\tEpisode Mean: 0.0\n",
+      "2390:1177227\tQ-min: 1.333\tQ-max: 1.445\tLives: 3\tReward: 9.0\tEpisode Mean: 0.0\n",
+      "2390:1177273\tQ-min: 1.285\tQ-max: 1.542\tLives: 3\tReward: 10.0\tEpisode Mean: 0.0\n",
+      "2390:1177304\tQ-min: 1.227\tQ-max: 1.538\tLives: 3\tReward: 11.0\tEpisode Mean: 0.0\n",
+      "2390:1177339\tQ-min: 1.256\tQ-max: 1.539\tLives: 3\tReward: 12.0\tEpisode Mean: 0.0\n",
+      "2390:1177359\tQ-min: 0.078\tQ-max: 0.126\tLives: 2\tReward: 12.0\tEpisode Mean: 0.0\n",
+      "2390:1177417\tQ-min: 1.150\tQ-max: 1.406\tLives: 2\tReward: 13.0\tEpisode Mean: 0.0\n",
+      "2390:1177469\tQ-min: 1.298\tQ-max: 1.452\tLives: 2\tReward: 14.0\tEpisode Mean: 0.0\n",
+      "2390:1177530\tQ-min: 1.229\tQ-max: 1.372\tLives: 2\tReward: 15.0\tEpisode Mean: 0.0\n",
+      "2390:1177571\tQ-min: 0.060\tQ-max: 0.104\tLives: 1\tReward: 15.0\tEpisode Mean: 0.0\n",
+      "2390:1177617\tQ-min: 1.266\tQ-max: 1.462\tLives: 1\tReward: 16.0\tEpisode Mean: 0.0\n",
+      "2390:1177668\tQ-min: 1.182\tQ-max: 1.566\tLives: 1\tReward: 20.0\tEpisode Mean: 0.0\n",
+      "2390:1177727\tQ-min: 1.250\tQ-max: 1.491\tLives: 1\tReward: 21.0\tEpisode Mean: 0.0\n",
+      "2390:1177781\tQ-min: 1.172\tQ-max: 1.604\tLives: 1\tReward: 25.0\tEpisode Mean: 0.0\n",
+      "2390:1177796\tQ-min: 0.434\tQ-max: 0.717\tLives: 0\tReward: 25.0\tEpisode Mean: 25.0\n"
      ]
     }
    ],
@@ -857,9 +833,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "agent.reset_episode_rewards()"
@@ -875,9 +849,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "agent.render = False"
@@ -899,1724 +871,704 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "87588:127641897\tQ-min: 1.755\tQ-max: 1.774\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
-      "87588:127641950\tQ-min: 1.634\tQ-max: 1.650\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
-      "87588:127642002\tQ-min: 1.849\tQ-max: 1.872\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
-      "87588:127642037\tQ-min: 1.930\tQ-max: 1.966\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
-      "87588:127642067\tQ-min: 1.936\tQ-max: 1.970\tLives: 5\tReward: 5.0\tEpisode Mean: 0.0\n",
-      "87588:127642101\tQ-min: 1.950\tQ-max: 1.963\tLives: 5\tReward: 9.0\tEpisode Mean: 0.0\n",
-      "87588:127642136\tQ-min: 2.189\tQ-max: 2.341\tLives: 5\tReward: 13.0\tEpisode Mean: 0.0\n",
-      "87588:127642159\tQ-min: 1.926\tQ-max: 2.292\tLives: 5\tReward: 14.0\tEpisode Mean: 0.0\n",
-      "87588:127642178\tQ-min: 1.976\tQ-max: 2.286\tLives: 5\tReward: 15.0\tEpisode Mean: 0.0\n",
-      "87588:127642199\tQ-min: 2.169\tQ-max: 2.290\tLives: 5\tReward: 16.0\tEpisode Mean: 0.0\n",
-      "87588:127642218\tQ-min: 2.243\tQ-max: 2.338\tLives: 5\tReward: 17.0\tEpisode Mean: 0.0\n",
-      "87588:127642240\tQ-min: 2.127\tQ-max: 2.307\tLives: 5\tReward: 24.0\tEpisode Mean: 0.0\n",
-      "87588:127642261\tQ-min: 2.328\tQ-max: 2.408\tLives: 5\tReward: 25.0\tEpisode Mean: 0.0\n",
-      "87588:127642280\tQ-min: 2.272\tQ-max: 2.454\tLives: 5\tReward: 26.0\tEpisode Mean: 0.0\n",
-      "87588:127642302\tQ-min: 2.251\tQ-max: 2.401\tLives: 5\tReward: 27.0\tEpisode Mean: 0.0\n",
-      "87588:127642323\tQ-min: 2.339\tQ-max: 2.423\tLives: 5\tReward: 31.0\tEpisode Mean: 0.0\n",
-      "87588:127642343\tQ-min: 2.365\tQ-max: 2.458\tLives: 5\tReward: 32.0\tEpisode Mean: 0.0\n",
-      "87588:127642364\tQ-min: 2.278\tQ-max: 2.398\tLives: 5\tReward: 33.0\tEpisode Mean: 0.0\n",
-      "87588:127642382\tQ-min: 2.226\tQ-max: 2.399\tLives: 5\tReward: 34.0\tEpisode Mean: 0.0\n",
-      "87588:127642396\tQ-min: -0.085\tQ-max: 0.443\tLives: 4\tReward: 34.0\tEpisode Mean: 0.0\n",
-      "87588:127642437\tQ-min: 1.988\tQ-max: 2.028\tLives: 4\tReward: 35.0\tEpisode Mean: 0.0\n",
-      "87588:127642478\tQ-min: 1.929\tQ-max: 2.025\tLives: 4\tReward: 36.0\tEpisode Mean: 0.0\n",
-      "87588:127642522\tQ-min: 2.039\tQ-max: 2.062\tLives: 4\tReward: 37.0\tEpisode Mean: 0.0\n",
-      "87588:127642559\tQ-min: 2.125\tQ-max: 2.207\tLives: 4\tReward: 38.0\tEpisode Mean: 0.0\n",
-      "87588:127642595\tQ-min: 2.249\tQ-max: 2.385\tLives: 4\tReward: 42.0\tEpisode Mean: 0.0\n",
-      "87588:127642632\tQ-min: 2.044\tQ-max: 2.165\tLives: 4\tReward: 43.0\tEpisode Mean: 0.0\n",
-      "87588:127642666\tQ-min: 2.204\tQ-max: 2.507\tLives: 4\tReward: 47.0\tEpisode Mean: 0.0\n",
-      "87588:127642685\tQ-min: 2.409\tQ-max: 2.493\tLives: 4\tReward: 48.0\tEpisode Mean: 0.0\n",
-      "87588:127642703\tQ-min: 2.254\tQ-max: 2.433\tLives: 4\tReward: 49.0\tEpisode Mean: 0.0\n",
-      "87588:127642716\tQ-min: -0.187\tQ-max: 0.041\tLives: 3\tReward: 49.0\tEpisode Mean: 0.0\n",
-      "87588:127642759\tQ-min: 2.005\tQ-max: 2.038\tLives: 3\tReward: 50.0\tEpisode Mean: 0.0\n",
-      "87588:127642805\tQ-min: 2.048\tQ-max: 2.137\tLives: 3\tReward: 54.0\tEpisode Mean: 0.0\n",
-      "87588:127642854\tQ-min: 2.376\tQ-max: 2.597\tLives: 3\tReward: 58.0\tEpisode Mean: 0.0\n",
-      "87588:127642875\tQ-min: 2.335\tQ-max: 2.511\tLives: 3\tReward: 59.0\tEpisode Mean: 0.0\n",
-      "87588:127642897\tQ-min: 2.480\tQ-max: 2.536\tLives: 3\tReward: 63.0\tEpisode Mean: 0.0\n",
-      "87588:127642910\tQ-min: 0.048\tQ-max: 0.153\tLives: 2\tReward: 63.0\tEpisode Mean: 0.0\n",
-      "87588:127642960\tQ-min: 2.096\tQ-max: 2.239\tLives: 2\tReward: 64.0\tEpisode Mean: 0.0\n",
-      "87588:127643019\tQ-min: 1.741\tQ-max: 1.920\tLives: 2\tReward: 68.0\tEpisode Mean: 0.0\n",
-      "87588:127643087\tQ-min: 1.986\tQ-max: 2.044\tLives: 2\tReward: 69.0\tEpisode Mean: 0.0\n",
-      "87588:127643135\tQ-min: 2.272\tQ-max: 2.352\tLives: 2\tReward: 70.0\tEpisode Mean: 0.0\n",
-      "87588:127643168\tQ-min: 2.441\tQ-max: 2.554\tLives: 2\tReward: 74.0\tEpisode Mean: 0.0\n",
-      "87588:127643202\tQ-min: 2.076\tQ-max: 2.292\tLives: 2\tReward: 78.0\tEpisode Mean: 0.0\n",
-      "87588:127643225\tQ-min: -0.176\tQ-max: 0.268\tLives: 1\tReward: 78.0\tEpisode Mean: 0.0\n",
-      "87588:127643281\tQ-min: 1.966\tQ-max: 2.221\tLives: 1\tReward: 82.0\tEpisode Mean: 0.0\n",
-      "87588:127643349\tQ-min: 1.627\tQ-max: 2.724\tLives: 1\tReward: 86.0\tEpisode Mean: 0.0\n",
-      "87588:127643370\tQ-min: 2.374\tQ-max: 2.479\tLives: 1\tReward: 93.0\tEpisode Mean: 0.0\n",
-      "87588:127643390\tQ-min: 2.446\tQ-max: 2.602\tLives: 1\tReward: 94.0\tEpisode Mean: 0.0\n",
-      "87588:127643412\tQ-min: 1.203\tQ-max: 1.788\tLives: 1\tReward: 98.0\tEpisode Mean: 0.0\n",
-      "87588:127643435\tQ-min: 2.395\tQ-max: 2.539\tLives: 1\tReward: 102.0\tEpisode Mean: 0.0\n",
-      "87588:127643448\tQ-min: -0.182\tQ-max: 0.072\tLives: 0\tReward: 102.0\tEpisode Mean: 102.0\n",
-      "87589:127643490\tQ-min: 1.753\tQ-max: 1.763\tLives: 5\tReward: 1.0\tEpisode Mean: 102.0\n",
-      "87589:127643540\tQ-min: 1.656\tQ-max: 1.658\tLives: 5\tReward: 2.0\tEpisode Mean: 102.0\n",
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-      "87589:127644392\tQ-min: 0.043\tQ-max: 0.267\tLives: 4\tReward: 34.0\tEpisode Mean: 102.0\n",
-      "87589:127644446\tQ-min: 1.782\tQ-max: 1.803\tLives: 4\tReward: 35.0\tEpisode Mean: 102.0\n",
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-      "87589:127644540\tQ-min: 2.092\tQ-max: 2.265\tLives: 4\tReward: 37.0\tEpisode Mean: 102.0\n",
-      "87589:127644581\tQ-min: 2.203\tQ-max: 2.238\tLives: 4\tReward: 38.0\tEpisode Mean: 102.0\n",
-      "87589:127644611\tQ-min: 2.169\tQ-max: 2.270\tLives: 4\tReward: 39.0\tEpisode Mean: 102.0\n",
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-      "87589:127644973\tQ-min: 2.182\tQ-max: 2.255\tLives: 4\tReward: 52.0\tEpisode Mean: 102.0\n",
-      "87589:127645008\tQ-min: 2.057\tQ-max: 2.107\tLives: 4\tReward: 53.0\tEpisode Mean: 102.0\n",
-      "87589:127645029\tQ-min: -0.272\tQ-max: 0.309\tLives: 3\tReward: 53.0\tEpisode Mean: 102.0\n",
-      "87589:127645074\tQ-min: 1.963\tQ-max: 2.158\tLives: 3\tReward: 57.0\tEpisode Mean: 102.0\n",
-      "87589:127645121\tQ-min: 2.300\tQ-max: 2.361\tLives: 3\tReward: 58.0\tEpisode Mean: 102.0\n",
-      "87589:127645164\tQ-min: 2.119\tQ-max: 2.211\tLives: 3\tReward: 59.0\tEpisode Mean: 102.0\n",
-      "87589:127645204\tQ-min: 2.328\tQ-max: 2.377\tLives: 3\tReward: 63.0\tEpisode Mean: 102.0\n",
-      "87589:127645242\tQ-min: 1.591\tQ-max: 2.503\tLives: 3\tReward: 70.0\tEpisode Mean: 102.0\n",
-      "87589:127645265\tQ-min: 1.942\tQ-max: 2.711\tLives: 3\tReward: 74.0\tEpisode Mean: 102.0\n",
-      "87589:127645289\tQ-min: 1.739\tQ-max: 3.524\tLives: 3\tReward: 81.0\tEpisode Mean: 102.0\n",
-      "87589:127645319\tQ-min: 1.548\tQ-max: 5.599\tLives: 3\tReward: 88.0\tEpisode Mean: 102.0\n",
-      "87589:127645326\tQ-min: 3.214\tQ-max: 6.187\tLives: 3\tReward: 95.0\tEpisode Mean: 102.0\n",
-      "87589:127645332\tQ-min: 4.149\tQ-max: 7.073\tLives: 3\tReward: 102.0\tEpisode Mean: 102.0\n",
-      "87589:127645338\tQ-min: 2.279\tQ-max: 6.700\tLives: 3\tReward: 109.0\tEpisode Mean: 102.0\n",
-      "87589:127645344\tQ-min: 3.218\tQ-max: 6.832\tLives: 3\tReward: 116.0\tEpisode Mean: 102.0\n",
-      "87589:127645348\tQ-min: 3.802\tQ-max: 5.502\tLives: 3\tReward: 123.0\tEpisode Mean: 102.0\n",
-      "87589:127645354\tQ-min: 1.270\tQ-max: 6.387\tLives: 3\tReward: 130.0\tEpisode Mean: 102.0\n",
-      "87589:127645360\tQ-min: 2.805\tQ-max: 6.095\tLives: 3\tReward: 137.0\tEpisode Mean: 102.0\n",
-      "87589:127645397\tQ-min: 2.879\tQ-max: 6.591\tLives: 3\tReward: 144.0\tEpisode Mean: 102.0\n",
-      "87589:127645404\tQ-min: 3.505\tQ-max: 6.818\tLives: 3\tReward: 151.0\tEpisode Mean: 102.0\n",
-      "87589:127645410\tQ-min: 3.764\tQ-max: 6.270\tLives: 3\tReward: 158.0\tEpisode Mean: 102.0\n",
-      "87589:127645415\tQ-min: 3.677\tQ-max: 5.796\tLives: 3\tReward: 165.0\tEpisode Mean: 102.0\n",
-      "87589:127645421\tQ-min: 2.668\tQ-max: 5.257\tLives: 3\tReward: 172.0\tEpisode Mean: 102.0\n",
-      "87589:127645427\tQ-min: 3.923\tQ-max: 5.098\tLives: 3\tReward: 179.0\tEpisode Mean: 102.0\n",
-      "87589:127645432\tQ-min: 1.970\tQ-max: 5.844\tLives: 3\tReward: 186.0\tEpisode Mean: 102.0\n",
-      "87589:127645437\tQ-min: 2.983\tQ-max: 5.170\tLives: 3\tReward: 193.0\tEpisode Mean: 102.0\n",
-      "87589:127645442\tQ-min: 0.927\tQ-max: 5.070\tLives: 3\tReward: 200.0\tEpisode Mean: 102.0\n",
-      "87589:127645449\tQ-min: 2.823\tQ-max: 4.550\tLives: 3\tReward: 207.0\tEpisode Mean: 102.0\n",
-      "87589:127645457\tQ-min: 2.697\tQ-max: 4.629\tLives: 3\tReward: 214.0\tEpisode Mean: 102.0\n",
-      "87589:127645463\tQ-min: 2.279\tQ-max: 3.921\tLives: 3\tReward: 221.0\tEpisode Mean: 102.0\n",
-      "87589:127645469\tQ-min: 1.649\tQ-max: 4.535\tLives: 3\tReward: 228.0\tEpisode Mean: 102.0\n",
-      "87589:127645477\tQ-min: 1.761\tQ-max: 4.724\tLives: 3\tReward: 235.0\tEpisode Mean: 102.0\n",
-      "87589:127645485\tQ-min: 2.276\tQ-max: 4.794\tLives: 3\tReward: 242.0\tEpisode Mean: 102.0\n",
-      "87589:127645493\tQ-min: 1.740\tQ-max: 4.088\tLives: 3\tReward: 246.0\tEpisode Mean: 102.0\n",
-      "87589:127645500\tQ-min: 2.749\tQ-max: 4.242\tLives: 3\tReward: 253.0\tEpisode Mean: 102.0\n",
-      "87589:127645507\tQ-min: 1.777\tQ-max: 4.064\tLives: 3\tReward: 260.0\tEpisode Mean: 102.0\n",
-      "87589:127645516\tQ-min: 1.485\tQ-max: 3.484\tLives: 3\tReward: 267.0\tEpisode Mean: 102.0\n",
-      "87589:127645523\tQ-min: 2.242\tQ-max: 4.177\tLives: 3\tReward: 274.0\tEpisode Mean: 102.0\n",
-      "87589:127645531\tQ-min: 2.252\tQ-max: 3.996\tLives: 3\tReward: 281.0\tEpisode Mean: 102.0\n",
-      "87589:127645566\tQ-min: 1.331\tQ-max: 4.973\tLives: 3\tReward: 285.0\tEpisode Mean: 102.0\n",
-      "87589:127645575\tQ-min: 1.970\tQ-max: 3.440\tLives: 3\tReward: 289.0\tEpisode Mean: 102.0\n",
-      "87589:127645584\tQ-min: 1.505\tQ-max: 3.210\tLives: 3\tReward: 293.0\tEpisode Mean: 102.0\n",
-      "87589:127645592\tQ-min: 1.477\tQ-max: 3.720\tLives: 3\tReward: 300.0\tEpisode Mean: 102.0\n",
-      "87589:127645600\tQ-min: 2.563\tQ-max: 3.410\tLives: 3\tReward: 304.0\tEpisode Mean: 102.0\n",
-      "87589:127645608\tQ-min: 1.711\tQ-max: 3.448\tLives: 3\tReward: 311.0\tEpisode Mean: 102.0\n",
-      "87589:127645615\tQ-min: 2.012\tQ-max: 3.991\tLives: 3\tReward: 318.0\tEpisode Mean: 102.0\n",
-      "87589:127645624\tQ-min: 1.686\tQ-max: 3.728\tLives: 3\tReward: 325.0\tEpisode Mean: 102.0\n",
-      "87589:127645632\tQ-min: 1.994\tQ-max: 3.683\tLives: 3\tReward: 329.0\tEpisode Mean: 102.0\n",
-      "87589:127645638\tQ-min: 2.120\tQ-max: 4.264\tLives: 3\tReward: 336.0\tEpisode Mean: 102.0\n",
-      "87589:127645646\tQ-min: 2.023\tQ-max: 4.184\tLives: 3\tReward: 340.0\tEpisode Mean: 102.0\n",
-      "87589:127645655\tQ-min: 2.003\tQ-max: 2.833\tLives: 3\tReward: 344.0\tEpisode Mean: 102.0\n",
-      "87589:127645665\tQ-min: -0.107\tQ-max: 1.473\tLives: 3\tReward: 345.0\tEpisode Mean: 102.0\n",
-      "87589:127645674\tQ-min: 2.355\tQ-max: 4.078\tLives: 3\tReward: 349.0\tEpisode Mean: 102.0\n",
-      "87589:127645713\tQ-min: 1.669\tQ-max: 2.720\tLives: 3\tReward: 353.0\tEpisode Mean: 102.0\n",
-      "87589:127645721\tQ-min: 2.809\tQ-max: 4.243\tLives: 3\tReward: 357.0\tEpisode Mean: 102.0\n",
-      "87589:127645753\tQ-min: 1.922\tQ-max: 2.913\tLives: 3\tReward: 361.0\tEpisode Mean: 102.0\n",
-      "87589:127645772\tQ-min: 2.140\tQ-max: 2.795\tLives: 3\tReward: 362.0\tEpisode Mean: 102.0\n",
-      "87589:127645783\tQ-min: 0.064\tQ-max: 0.209\tLives: 2\tReward: 362.0\tEpisode Mean: 102.0\n",
-      "87589:127645841\tQ-min: 1.845\tQ-max: 2.442\tLives: 2\tReward: 366.0\tEpisode Mean: 102.0\n",
-      "87589:127645919\tQ-min: 0.936\tQ-max: 2.705\tLives: 2\tReward: 370.0\tEpisode Mean: 102.0\n",
-      "87589:127645949\tQ-min: 1.205\tQ-max: 3.975\tLives: 2\tReward: 374.0\tEpisode Mean: 102.0\n",
-      "87589:127645956\tQ-min: 3.382\tQ-max: 4.514\tLives: 2\tReward: 381.0\tEpisode Mean: 102.0\n",
-      "87589:127645979\tQ-min: 0.130\tQ-max: 0.357\tLives: 1\tReward: 381.0\tEpisode Mean: 102.0\n",
-      "87589:127646023\tQ-min: 2.012\tQ-max: 2.867\tLives: 1\tReward: 385.0\tEpisode Mean: 102.0\n",
-      "87589:127646070\tQ-min: 2.544\tQ-max: 2.705\tLives: 1\tReward: 386.0\tEpisode Mean: 102.0\n",
-      "87589:127646095\tQ-min: 0.001\tQ-max: 0.201\tLives: 0\tReward: 386.0\tEpisode Mean: 244.0\n",
-      "87590:127646139\tQ-min: 1.787\tQ-max: 1.799\tLives: 5\tReward: 1.0\tEpisode Mean: 244.0\n",
-      "87590:127646182\tQ-min: 1.817\tQ-max: 1.831\tLives: 5\tReward: 2.0\tEpisode Mean: 244.0\n",
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-      "87590:127646324\tQ-min: 1.892\tQ-max: 1.911\tLives: 5\tReward: 6.0\tEpisode Mean: 244.0\n",
-      "87590:127646358\tQ-min: 1.726\tQ-max: 1.840\tLives: 5\tReward: 7.0\tEpisode Mean: 244.0\n",
-      "87590:127646406\tQ-min: 1.681\tQ-max: 1.705\tLives: 5\tReward: 8.0\tEpisode Mean: 244.0\n",
-      "87590:127646469\tQ-min: 1.489\tQ-max: 1.679\tLives: 5\tReward: 9.0\tEpisode Mean: 244.0\n",
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-      "87590:127646601\tQ-min: 1.625\tQ-max: 1.658\tLives: 5\tReward: 11.0\tEpisode Mean: 244.0\n",
-      "87590:127646650\tQ-min: 1.949\tQ-max: 1.968\tLives: 5\tReward: 12.0\tEpisode Mean: 244.0\n",
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-      "87590:127646715\tQ-min: 1.990\tQ-max: 2.067\tLives: 5\tReward: 14.0\tEpisode Mean: 244.0\n",
-      "87590:127646738\tQ-min: -0.265\tQ-max: 0.133\tLives: 4\tReward: 14.0\tEpisode Mean: 244.0\n",
-      "87590:127646782\tQ-min: 1.799\tQ-max: 1.840\tLives: 4\tReward: 15.0\tEpisode Mean: 244.0\n",
-      "87590:127646825\tQ-min: 1.948\tQ-max: 1.967\tLives: 4\tReward: 16.0\tEpisode Mean: 244.0\n",
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-      "87590:127646985\tQ-min: -0.062\tQ-max: 0.107\tLives: 3\tReward: 20.0\tEpisode Mean: 244.0\n",
-      "87590:127647040\tQ-min: 1.724\tQ-max: 1.740\tLives: 3\tReward: 21.0\tEpisode Mean: 244.0\n",
-      "87590:127647095\tQ-min: 1.943\tQ-max: 1.955\tLives: 3\tReward: 22.0\tEpisode Mean: 244.0\n",
-      "87590:127647142\tQ-min: 2.024\tQ-max: 2.103\tLives: 3\tReward: 26.0\tEpisode Mean: 244.0\n",
-      "87590:127647182\tQ-min: 1.959\tQ-max: 2.022\tLives: 3\tReward: 27.0\tEpisode Mean: 244.0\n",
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-      "87590:127647290\tQ-min: 1.980\tQ-max: 2.191\tLives: 3\tReward: 36.0\tEpisode Mean: 244.0\n",
-      "87590:127647342\tQ-min: 1.706\tQ-max: 1.736\tLives: 3\tReward: 37.0\tEpisode Mean: 244.0\n",
-      "87590:127647409\tQ-min: 1.795\tQ-max: 1.842\tLives: 3\tReward: 38.0\tEpisode Mean: 244.0\n",
-      "87590:127647473\tQ-min: 1.780\tQ-max: 1.805\tLives: 3\tReward: 39.0\tEpisode Mean: 244.0\n",
-      "87590:127647542\tQ-min: 1.660\tQ-max: 1.909\tLives: 3\tReward: 40.0\tEpisode Mean: 244.0\n",
-      "87590:127647597\tQ-min: 2.079\tQ-max: 2.107\tLives: 3\tReward: 41.0\tEpisode Mean: 244.0\n",
-      "87590:127647629\tQ-min: 1.994\tQ-max: 2.072\tLives: 3\tReward: 42.0\tEpisode Mean: 244.0\n",
-      "87590:127647665\tQ-min: 2.155\tQ-max: 2.173\tLives: 3\tReward: 43.0\tEpisode Mean: 244.0\n",
-      "87590:127647699\tQ-min: 2.047\tQ-max: 2.189\tLives: 3\tReward: 47.0\tEpisode Mean: 244.0\n",
-      "87590:127647736\tQ-min: 2.219\tQ-max: 2.495\tLives: 3\tReward: 51.0\tEpisode Mean: 244.0\n",
-      "87590:127647756\tQ-min: 2.399\tQ-max: 2.565\tLives: 3\tReward: 55.0\tEpisode Mean: 244.0\n",
-      "87590:127647778\tQ-min: 2.284\tQ-max: 2.583\tLives: 3\tReward: 59.0\tEpisode Mean: 244.0\n",
-      "87590:127647800\tQ-min: 2.406\tQ-max: 2.620\tLives: 3\tReward: 63.0\tEpisode Mean: 244.0\n",
-      "87590:127647822\tQ-min: 2.359\tQ-max: 2.564\tLives: 3\tReward: 67.0\tEpisode Mean: 244.0\n",
-      "87590:127647833\tQ-min: -0.036\tQ-max: 0.223\tLives: 2\tReward: 67.0\tEpisode Mean: 244.0\n",
-      "87590:127647884\tQ-min: 1.975\tQ-max: 2.198\tLives: 2\tReward: 71.0\tEpisode Mean: 244.0\n",
-      "87590:127647929\tQ-min: 2.128\tQ-max: 2.484\tLives: 2\tReward: 75.0\tEpisode Mean: 244.0\n",
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-      "87590:127648445\tQ-min: 2.390\tQ-max: 3.135\tLives: 1\tReward: 119.0\tEpisode Mean: 244.0\n",
-      "87590:127648468\tQ-min: 2.370\tQ-max: 3.299\tLives: 1\tReward: 126.0\tEpisode Mean: 244.0\n",
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-      "87590:127648509\tQ-min: -0.140\tQ-max: 0.334\tLives: 0\tReward: 133.0\tEpisode Mean: 207.0\n",
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-      "87591:127648813\tQ-min: -0.174\tQ-max: 0.101\tLives: 4\tReward: 7.0\tEpisode Mean: 207.0\n",
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-      "87591:127649089\tQ-min: 1.940\tQ-max: 2.027\tLives: 4\tReward: 19.0\tEpisode Mean: 207.0\n",
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-      "87591:127649168\tQ-min: 1.749\tQ-max: 1.771\tLives: 4\tReward: 21.0\tEpisode Mean: 207.0\n",
-      "87591:127649232\tQ-min: 1.642\tQ-max: 1.716\tLives: 4\tReward: 22.0\tEpisode Mean: 207.0\n",
-      "87591:127649294\tQ-min: 1.752\tQ-max: 1.774\tLives: 4\tReward: 23.0\tEpisode Mean: 207.0\n",
-      "87591:127649359\tQ-min: 1.725\tQ-max: 1.774\tLives: 4\tReward: 24.0\tEpisode Mean: 207.0\n",
-      "87591:127649412\tQ-min: 1.957\tQ-max: 1.990\tLives: 4\tReward: 25.0\tEpisode Mean: 207.0\n",
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-      "87591:127649478\tQ-min: 2.056\tQ-max: 2.085\tLives: 4\tReward: 27.0\tEpisode Mean: 207.0\n",
-      "87591:127649509\tQ-min: 2.032\tQ-max: 2.131\tLives: 4\tReward: 31.0\tEpisode Mean: 207.0\n",
-      "87591:127649544\tQ-min: 2.193\tQ-max: 2.302\tLives: 4\tReward: 35.0\tEpisode Mean: 207.0\n",
-      "87591:127649565\tQ-min: 2.264\tQ-max: 2.424\tLives: 4\tReward: 36.0\tEpisode Mean: 207.0\n",
-      "87591:127649584\tQ-min: 2.031\tQ-max: 2.287\tLives: 4\tReward: 37.0\tEpisode Mean: 207.0\n",
-      "87591:127649596\tQ-min: -0.144\tQ-max: 0.076\tLives: 3\tReward: 37.0\tEpisode Mean: 207.0\n",
-      "87591:127649649\tQ-min: 1.760\tQ-max: 1.798\tLives: 3\tReward: 38.0\tEpisode Mean: 207.0\n",
-      "87591:127649719\tQ-min: 1.564\tQ-max: 1.715\tLives: 3\tReward: 42.0\tEpisode Mean: 207.0\n",
-      "87591:127649777\tQ-min: 2.073\tQ-max: 2.168\tLives: 3\tReward: 46.0\tEpisode Mean: 207.0\n",
-      "87591:127649821\tQ-min: 2.199\tQ-max: 2.354\tLives: 3\tReward: 50.0\tEpisode Mean: 207.0\n",
-      "87591:127649856\tQ-min: 2.322\tQ-max: 2.456\tLives: 3\tReward: 54.0\tEpisode Mean: 207.0\n",
-      "87591:127649869\tQ-min: 0.025\tQ-max: 0.418\tLives: 2\tReward: 54.0\tEpisode Mean: 207.0\n",
-      "87591:127649930\tQ-min: 1.381\tQ-max: 1.778\tLives: 2\tReward: 58.0\tEpisode Mean: 207.0\n",
-      "87591:127650007\tQ-min: 1.768\tQ-max: 2.462\tLives: 2\tReward: 62.0\tEpisode Mean: 207.0\n",
-      "87591:127650027\tQ-min: 2.428\tQ-max: 2.487\tLives: 2\tReward: 63.0\tEpisode Mean: 207.0\n",
-      "87591:127650047\tQ-min: 2.191\tQ-max: 2.541\tLives: 2\tReward: 64.0\tEpisode Mean: 207.0\n",
-      "87591:127650066\tQ-min: 2.439\tQ-max: 2.499\tLives: 2\tReward: 65.0\tEpisode Mean: 207.0\n",
-      "87591:127650086\tQ-min: 2.355\tQ-max: 2.534\tLives: 2\tReward: 66.0\tEpisode Mean: 207.0\n",
-      "87591:127650107\tQ-min: 2.535\tQ-max: 2.644\tLives: 2\tReward: 67.0\tEpisode Mean: 207.0\n",
-      "87591:127650128\tQ-min: 2.424\tQ-max: 2.611\tLives: 2\tReward: 71.0\tEpisode Mean: 207.0\n",
-      "87591:127650149\tQ-min: 2.291\tQ-max: 2.567\tLives: 2\tReward: 72.0\tEpisode Mean: 207.0\n",
-      "87591:127650173\tQ-min: 2.357\tQ-max: 2.671\tLives: 2\tReward: 76.0\tEpisode Mean: 207.0\n",
-      "87591:127650198\tQ-min: 1.918\tQ-max: 3.150\tLives: 2\tReward: 83.0\tEpisode Mean: 207.0\n",
-      "87591:127650223\tQ-min: 1.593\tQ-max: 3.739\tLives: 2\tReward: 90.0\tEpisode Mean: 207.0\n",
-      "87591:127650253\tQ-min: 2.184\tQ-max: 6.902\tLives: 2\tReward: 97.0\tEpisode Mean: 207.0\n",
-      "87591:127650258\tQ-min: 2.303\tQ-max: 6.611\tLives: 2\tReward: 104.0\tEpisode Mean: 207.0\n",
-      "87591:127650263\tQ-min: 3.708\tQ-max: 6.076\tLives: 2\tReward: 111.0\tEpisode Mean: 207.0\n",
-      "87591:127650267\tQ-min: 2.672\tQ-max: 6.862\tLives: 2\tReward: 118.0\tEpisode Mean: 207.0\n",
-      "87591:127650272\tQ-min: 1.783\tQ-max: 6.216\tLives: 2\tReward: 125.0\tEpisode Mean: 207.0\n",
-      "87591:127650277\tQ-min: 2.125\tQ-max: 5.576\tLives: 2\tReward: 132.0\tEpisode Mean: 207.0\n",
-      "87591:127650283\tQ-min: 3.175\tQ-max: 5.794\tLives: 2\tReward: 139.0\tEpisode Mean: 207.0\n",
-      "87591:127650288\tQ-min: 4.208\tQ-max: 6.206\tLives: 2\tReward: 146.0\tEpisode Mean: 207.0\n",
-      "87591:127650293\tQ-min: 3.793\tQ-max: 5.610\tLives: 2\tReward: 153.0\tEpisode Mean: 207.0\n",
-      "87591:127650298\tQ-min: 3.057\tQ-max: 5.366\tLives: 2\tReward: 160.0\tEpisode Mean: 207.0\n",
-      "87591:127650304\tQ-min: 3.419\tQ-max: 5.766\tLives: 2\tReward: 167.0\tEpisode Mean: 207.0\n",
-      "87591:127650308\tQ-min: 2.737\tQ-max: 6.274\tLives: 2\tReward: 174.0\tEpisode Mean: 207.0\n",
-      "87591:127650313\tQ-min: 4.419\tQ-max: 6.346\tLives: 2\tReward: 181.0\tEpisode Mean: 207.0\n",
-      "87591:127650319\tQ-min: 2.684\tQ-max: 5.516\tLives: 2\tReward: 188.0\tEpisode Mean: 207.0\n",
-      "87591:127650322\tQ-min: 3.003\tQ-max: 4.892\tLives: 2\tReward: 195.0\tEpisode Mean: 207.0\n",
-      "87591:127650328\tQ-min: 3.717\tQ-max: 5.497\tLives: 2\tReward: 202.0\tEpisode Mean: 207.0\n",
-      "87591:127650334\tQ-min: 3.530\tQ-max: 5.096\tLives: 2\tReward: 209.0\tEpisode Mean: 207.0\n",
-      "87591:127650341\tQ-min: 3.669\tQ-max: 5.190\tLives: 2\tReward: 216.0\tEpisode Mean: 207.0\n",
-      "87591:127650346\tQ-min: 2.570\tQ-max: 3.876\tLives: 2\tReward: 223.0\tEpisode Mean: 207.0\n",
-      "87591:127650353\tQ-min: 3.737\tQ-max: 5.336\tLives: 2\tReward: 230.0\tEpisode Mean: 207.0\n",
-      "87591:127650360\tQ-min: 2.802\tQ-max: 5.215\tLives: 2\tReward: 237.0\tEpisode Mean: 207.0\n",
-      "87591:127650366\tQ-min: 1.970\tQ-max: 5.470\tLives: 2\tReward: 244.0\tEpisode Mean: 207.0\n",
-      "87591:127650373\tQ-min: 2.147\tQ-max: 5.573\tLives: 2\tReward: 251.0\tEpisode Mean: 207.0\n",
-      "87591:127650379\tQ-min: 2.106\tQ-max: 4.824\tLives: 2\tReward: 258.0\tEpisode Mean: 207.0\n",
-      "87591:127650386\tQ-min: 2.746\tQ-max: 4.343\tLives: 2\tReward: 265.0\tEpisode Mean: 207.0\n",
-      "87591:127650425\tQ-min: 1.870\tQ-max: 5.265\tLives: 2\tReward: 272.0\tEpisode Mean: 207.0\n",
-      "87591:127650432\tQ-min: 3.059\tQ-max: 4.681\tLives: 2\tReward: 279.0\tEpisode Mean: 207.0\n",
-      "87591:127650438\tQ-min: 2.537\tQ-max: 4.428\tLives: 2\tReward: 286.0\tEpisode Mean: 207.0\n",
-      "87591:127650445\tQ-min: 1.591\tQ-max: 4.291\tLives: 2\tReward: 290.0\tEpisode Mean: 207.0\n",
-      "87591:127650454\tQ-min: 2.578\tQ-max: 3.873\tLives: 2\tReward: 294.0\tEpisode Mean: 207.0\n",
-      "87591:127650462\tQ-min: 3.137\tQ-max: 4.334\tLives: 2\tReward: 301.0\tEpisode Mean: 207.0\n",
-      "87591:127650469\tQ-min: 2.537\tQ-max: 3.330\tLives: 2\tReward: 305.0\tEpisode Mean: 207.0\n",
-      "87591:127650491\tQ-min: -0.535\tQ-max: 0.537\tLives: 1\tReward: 305.0\tEpisode Mean: 207.0\n",
-      "87591:127650552\tQ-min: 1.948\tQ-max: 2.805\tLives: 1\tReward: 309.0\tEpisode Mean: 207.0\n",
-      "87591:127650573\tQ-min: 2.012\tQ-max: 3.112\tLives: 1\tReward: 313.0\tEpisode Mean: 207.0\n",
-      "87591:127650586\tQ-min: -0.178\tQ-max: 0.125\tLives: 0\tReward: 313.0\tEpisode Mean: 233.5\n",
-      "87592:127650631\tQ-min: 1.738\tQ-max: 1.756\tLives: 5\tReward: 1.0\tEpisode Mean: 233.5\n",
-      "87592:127650681\tQ-min: 1.608\tQ-max: 1.681\tLives: 5\tReward: 2.0\tEpisode Mean: 233.5\n",
-      "87592:127650745\tQ-min: 1.693\tQ-max: 1.710\tLives: 5\tReward: 3.0\tEpisode Mean: 233.5\n",
-      "87592:127650791\tQ-min: 2.007\tQ-max: 2.043\tLives: 5\tReward: 4.0\tEpisode Mean: 233.5\n",
-      "87592:127650823\tQ-min: 1.982\tQ-max: 1.999\tLives: 5\tReward: 5.0\tEpisode Mean: 233.5\n",
-      "87592:127650855\tQ-min: 1.947\tQ-max: 1.978\tLives: 5\tReward: 6.0\tEpisode Mean: 233.5\n",
-      "87592:127650891\tQ-min: 1.860\tQ-max: 1.888\tLives: 5\tReward: 7.0\tEpisode Mean: 233.5\n",
-      "87592:127650936\tQ-min: 1.647\tQ-max: 1.686\tLives: 5\tReward: 8.0\tEpisode Mean: 233.5\n",
-      "87592:127650996\tQ-min: 1.627\tQ-max: 1.706\tLives: 5\tReward: 9.0\tEpisode Mean: 233.5\n",
-      "87592:127651058\tQ-min: 1.615\tQ-max: 1.658\tLives: 5\tReward: 10.0\tEpisode Mean: 233.5\n",
-      "87592:127651120\tQ-min: 1.606\tQ-max: 1.666\tLives: 5\tReward: 11.0\tEpisode Mean: 233.5\n",
-      "87592:127651171\tQ-min: 2.078\tQ-max: 2.122\tLives: 5\tReward: 15.0\tEpisode Mean: 233.5\n",
-      "87592:127651194\tQ-min: -0.342\tQ-max: 0.180\tLives: 4\tReward: 15.0\tEpisode Mean: 233.5\n",
-      "87592:127651249\tQ-min: 1.698\tQ-max: 1.723\tLives: 4\tReward: 16.0\tEpisode Mean: 233.5\n",
-      "87592:127651314\tQ-min: 1.764\tQ-max: 1.785\tLives: 4\tReward: 17.0\tEpisode Mean: 233.5\n",
-      "87592:127651374\tQ-min: 1.671\tQ-max: 1.684\tLives: 4\tReward: 18.0\tEpisode Mean: 233.5\n",
-      "87592:127651421\tQ-min: 1.929\tQ-max: 1.945\tLives: 4\tReward: 19.0\tEpisode Mean: 233.5\n",
-      "87592:127651453\tQ-min: 1.996\tQ-max: 2.010\tLives: 4\tReward: 20.0\tEpisode Mean: 233.5\n",
-      "87592:127651485\tQ-min: 1.951\tQ-max: 2.018\tLives: 4\tReward: 21.0\tEpisode Mean: 233.5\n",
-      "87592:127651521\tQ-min: 2.054\tQ-max: 2.101\tLives: 4\tReward: 25.0\tEpisode Mean: 233.5\n",
-      "87592:127651571\tQ-min: 1.697\tQ-max: 1.773\tLives: 4\tReward: 26.0\tEpisode Mean: 233.5\n",
-      "87592:127651639\tQ-min: 1.759\tQ-max: 1.799\tLives: 4\tReward: 30.0\tEpisode Mean: 233.5\n",
-      "87592:127651707\tQ-min: 1.742\tQ-max: 1.765\tLives: 4\tReward: 31.0\tEpisode Mean: 233.5\n",
-      "87592:127651752\tQ-min: 0.088\tQ-max: 0.286\tLives: 3\tReward: 31.0\tEpisode Mean: 233.5\n",
-      "87592:127651796\tQ-min: 1.841\tQ-max: 2.045\tLives: 3\tReward: 35.0\tEpisode Mean: 233.5\n",
-      "87592:127651844\tQ-min: 2.039\tQ-max: 2.095\tLives: 3\tReward: 39.0\tEpisode Mean: 233.5\n",
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-      "87592:127651973\tQ-min: 2.190\tQ-max: 2.513\tLives: 3\tReward: 48.0\tEpisode Mean: 233.5\n",
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-      "87592:127652042\tQ-min: 2.402\tQ-max: 2.633\tLives: 3\tReward: 57.0\tEpisode Mean: 233.5\n",
-      "87592:127652066\tQ-min: 2.368\tQ-max: 2.562\tLives: 3\tReward: 61.0\tEpisode Mean: 233.5\n",
-      "87592:127652088\tQ-min: 2.472\tQ-max: 2.575\tLives: 3\tReward: 62.0\tEpisode Mean: 233.5\n",
-      "87592:127652110\tQ-min: 2.395\tQ-max: 2.561\tLives: 3\tReward: 63.0\tEpisode Mean: 233.5\n",
-      "87592:127652132\tQ-min: 2.375\tQ-max: 2.585\tLives: 3\tReward: 67.0\tEpisode Mean: 233.5\n",
-      "87592:127652157\tQ-min: 2.473\tQ-max: 2.893\tLives: 3\tReward: 71.0\tEpisode Mean: 233.5\n",
-      "87592:127652176\tQ-min: 2.306\tQ-max: 2.499\tLives: 3\tReward: 72.0\tEpisode Mean: 233.5\n",
-      "87592:127652197\tQ-min: 2.349\tQ-max: 2.556\tLives: 3\tReward: 76.0\tEpisode Mean: 233.5\n",
-      "87592:127652210\tQ-min: -0.203\tQ-max: 0.078\tLives: 2\tReward: 76.0\tEpisode Mean: 233.5\n",
-      "87592:127652270\tQ-min: 2.092\tQ-max: 2.818\tLives: 2\tReward: 80.0\tEpisode Mean: 233.5\n",
-      "87592:127652291\tQ-min: 2.315\tQ-max: 2.478\tLives: 2\tReward: 81.0\tEpisode Mean: 233.5\n",
-      "87592:127652312\tQ-min: 2.388\tQ-max: 2.683\tLives: 2\tReward: 85.0\tEpisode Mean: 233.5\n",
-      "87592:127652333\tQ-min: 2.325\tQ-max: 2.544\tLives: 2\tReward: 86.0\tEpisode Mean: 233.5\n",
-      "87592:127652356\tQ-min: 2.417\tQ-max: 2.561\tLives: 2\tReward: 93.0\tEpisode Mean: 233.5\n",
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-      "87593:127653049\tQ-min: -0.249\tQ-max: 0.235\tLives: 4\tReward: 7.0\tEpisode Mean: 219.0\n",
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-      "87593:127653248\tQ-min: 1.998\tQ-max: 2.038\tLives: 4\tReward: 11.0\tEpisode Mean: 219.0\n",
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-      "87593:127653315\tQ-min: 1.936\tQ-max: 1.983\tLives: 4\tReward: 16.0\tEpisode Mean: 219.0\n",
-      "87593:127653350\tQ-min: 2.174\tQ-max: 2.322\tLives: 4\tReward: 20.0\tEpisode Mean: 219.0\n",
-      "87593:127653365\tQ-min: 0.036\tQ-max: 0.426\tLives: 3\tReward: 20.0\tEpisode Mean: 219.0\n",
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-      "87593:127653462\tQ-min: 1.701\tQ-max: 1.795\tLives: 3\tReward: 22.0\tEpisode Mean: 219.0\n",
-      "87593:127653529\tQ-min: 1.778\tQ-max: 1.801\tLives: 3\tReward: 23.0\tEpisode Mean: 219.0\n",
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-      "87593:127653611\tQ-min: 2.053\tQ-max: 2.078\tLives: 3\tReward: 25.0\tEpisode Mean: 219.0\n",
-      "87593:127653647\tQ-min: 1.991\tQ-max: 2.196\tLives: 3\tReward: 29.0\tEpisode Mean: 219.0\n",
-      "87593:127653682\tQ-min: 2.111\tQ-max: 2.268\tLives: 3\tReward: 30.0\tEpisode Mean: 219.0\n",
-      "87593:127653729\tQ-min: 1.767\tQ-max: 1.797\tLives: 3\tReward: 31.0\tEpisode Mean: 219.0\n",
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-      "87593:127653866\tQ-min: 1.755\tQ-max: 1.803\tLives: 3\tReward: 33.0\tEpisode Mean: 219.0\n",
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-      "87593:127653987\tQ-min: 2.132\tQ-max: 2.257\tLives: 3\tReward: 38.0\tEpisode Mean: 219.0\n",
-      "87593:127654008\tQ-min: 2.290\tQ-max: 2.414\tLives: 3\tReward: 39.0\tEpisode Mean: 219.0\n",
-      "87593:127654029\tQ-min: 2.187\tQ-max: 2.466\tLives: 3\tReward: 43.0\tEpisode Mean: 219.0\n",
-      "87593:127654049\tQ-min: 2.475\tQ-max: 2.549\tLives: 3\tReward: 47.0\tEpisode Mean: 219.0\n",
-      "87593:127654072\tQ-min: 2.380\tQ-max: 2.476\tLives: 3\tReward: 48.0\tEpisode Mean: 219.0\n",
-      "87593:127654092\tQ-min: 2.384\tQ-max: 2.493\tLives: 3\tReward: 52.0\tEpisode Mean: 219.0\n",
-      "87593:127654105\tQ-min: 0.072\tQ-max: 0.224\tLives: 2\tReward: 52.0\tEpisode Mean: 219.0\n",
-      "87593:127654162\tQ-min: 1.802\tQ-max: 1.834\tLives: 2\tReward: 53.0\tEpisode Mean: 219.0\n",
-      "87593:127654229\tQ-min: 1.875\tQ-max: 1.913\tLives: 2\tReward: 54.0\tEpisode Mean: 219.0\n",
-      "87593:127654301\tQ-min: 1.697\tQ-max: 1.889\tLives: 2\tReward: 58.0\tEpisode Mean: 219.0\n",
-      "87593:127654351\tQ-min: 2.277\tQ-max: 2.401\tLives: 2\tReward: 59.0\tEpisode Mean: 219.0\n",
-      "87593:127654375\tQ-min: 0.016\tQ-max: 0.213\tLives: 1\tReward: 59.0\tEpisode Mean: 219.0\n",
-      "87593:127654435\tQ-min: 1.763\tQ-max: 1.906\tLives: 1\tReward: 60.0\tEpisode Mean: 219.0\n",
-      "87593:127654499\tQ-min: 1.852\tQ-max: 1.911\tLives: 1\tReward: 61.0\tEpisode Mean: 219.0\n",
-      "87593:127654566\tQ-min: 1.833\tQ-max: 1.903\tLives: 1\tReward: 62.0\tEpisode Mean: 219.0\n",
-      "87593:127654618\tQ-min: 1.870\tQ-max: 2.419\tLives: 1\tReward: 66.0\tEpisode Mean: 219.0\n",
-      "87593:127654631\tQ-min: -0.017\tQ-max: 0.137\tLives: 0\tReward: 66.0\tEpisode Mean: 193.5\n",
-      "87594:127654685\tQ-min: 1.651\tQ-max: 1.682\tLives: 5\tReward: 1.0\tEpisode Mean: 193.5\n",
-      "87594:127654736\tQ-min: 1.850\tQ-max: 1.864\tLives: 5\tReward: 2.0\tEpisode Mean: 193.5\n",
-      "87594:127654780\tQ-min: 1.891\tQ-max: 1.934\tLives: 5\tReward: 3.0\tEpisode Mean: 193.5\n",
-      "87594:127654817\tQ-min: 1.999\tQ-max: 2.044\tLives: 5\tReward: 4.0\tEpisode Mean: 193.5\n",
-      "87594:127654850\tQ-min: 1.971\tQ-max: 1.982\tLives: 5\tReward: 5.0\tEpisode Mean: 193.5\n",
-      "87594:127654882\tQ-min: 1.880\tQ-max: 1.913\tLives: 5\tReward: 6.0\tEpisode Mean: 193.5\n",
-      "87594:127654916\tQ-min: 1.829\tQ-max: 1.878\tLives: 5\tReward: 10.0\tEpisode Mean: 193.5\n",
-      "87594:127654937\tQ-min: -0.237\tQ-max: 0.162\tLives: 4\tReward: 10.0\tEpisode Mean: 193.5\n",
-      "87594:127654990\tQ-min: 1.683\tQ-max: 1.710\tLives: 4\tReward: 11.0\tEpisode Mean: 193.5\n",
-      "87594:127655040\tQ-min: 1.909\tQ-max: 2.004\tLives: 4\tReward: 12.0\tEpisode Mean: 193.5\n",
-      "87594:127655083\tQ-min: 2.002\tQ-max: 2.042\tLives: 4\tReward: 16.0\tEpisode Mean: 193.5\n",
-      "87594:127655127\tQ-min: 1.953\tQ-max: 1.996\tLives: 4\tReward: 20.0\tEpisode Mean: 193.5\n",
-      "87594:127655164\tQ-min: 2.028\tQ-max: 2.074\tLives: 4\tReward: 21.0\tEpisode Mean: 193.5\n",
-      "87594:127655196\tQ-min: 2.035\tQ-max: 2.054\tLives: 4\tReward: 22.0\tEpisode Mean: 193.5\n",
-      "87594:127655229\tQ-min: 2.120\tQ-max: 2.405\tLives: 4\tReward: 26.0\tEpisode Mean: 193.5\n",
-      "87594:127655251\tQ-min: 2.246\tQ-max: 2.396\tLives: 4\tReward: 27.0\tEpisode Mean: 193.5\n",
-      "87594:127655268\tQ-min: 2.243\tQ-max: 2.392\tLives: 4\tReward: 28.0\tEpisode Mean: 193.5\n",
-      "87594:127655286\tQ-min: 2.245\tQ-max: 2.390\tLives: 4\tReward: 29.0\tEpisode Mean: 193.5\n",
-      "87594:127655308\tQ-min: 2.304\tQ-max: 2.416\tLives: 4\tReward: 30.0\tEpisode Mean: 193.5\n",
-      "87594:127655330\tQ-min: 2.293\tQ-max: 2.345\tLives: 4\tReward: 34.0\tEpisode Mean: 193.5\n",
-      "87594:127655343\tQ-min: -0.039\tQ-max: 0.290\tLives: 3\tReward: 34.0\tEpisode Mean: 193.5\n",
-      "87594:127655383\tQ-min: 2.074\tQ-max: 2.111\tLives: 3\tReward: 35.0\tEpisode Mean: 193.5\n",
-      "87594:127655434\tQ-min: 1.858\tQ-max: 1.963\tLives: 3\tReward: 36.0\tEpisode Mean: 193.5\n",
-      "87594:127655487\tQ-min: 2.120\tQ-max: 2.189\tLives: 3\tReward: 37.0\tEpisode Mean: 193.5\n",
-      "87594:127655527\tQ-min: 2.145\tQ-max: 2.264\tLives: 3\tReward: 41.0\tEpisode Mean: 193.5\n",
-      "87594:127655559\tQ-min: 2.238\tQ-max: 2.304\tLives: 3\tReward: 42.0\tEpisode Mean: 193.5\n",
-      "87594:127655580\tQ-min: -0.035\tQ-max: 0.260\tLives: 2\tReward: 42.0\tEpisode Mean: 193.5\n",
-      "87594:127655636\tQ-min: 1.821\tQ-max: 2.036\tLives: 2\tReward: 46.0\tEpisode Mean: 193.5\n",
-      "87594:127655705\tQ-min: 1.870\tQ-max: 1.949\tLives: 2\tReward: 47.0\tEpisode Mean: 193.5\n",
-      "87594:127655772\tQ-min: 1.753\tQ-max: 1.917\tLives: 2\tReward: 48.0\tEpisode Mean: 193.5\n",
-      "87594:127655821\tQ-min: 2.071\tQ-max: 2.226\tLives: 2\tReward: 49.0\tEpisode Mean: 193.5\n",
-      "87594:127655852\tQ-min: 2.208\tQ-max: 2.255\tLives: 2\tReward: 50.0\tEpisode Mean: 193.5\n",
-      "87594:127655885\tQ-min: 2.251\tQ-max: 2.297\tLives: 2\tReward: 51.0\tEpisode Mean: 193.5\n",
-      "87594:127655906\tQ-min: -0.061\tQ-max: 0.177\tLives: 1\tReward: 51.0\tEpisode Mean: 193.5\n",
-      "87594:127655952\tQ-min: 2.156\tQ-max: 2.214\tLives: 1\tReward: 52.0\tEpisode Mean: 193.5\n",
-      "87594:127655991\tQ-min: 2.186\tQ-max: 2.215\tLives: 1\tReward: 53.0\tEpisode Mean: 193.5\n",
-      "87594:127656034\tQ-min: 2.292\tQ-max: 2.545\tLives: 1\tReward: 57.0\tEpisode Mean: 193.5\n",
-      "87594:127656055\tQ-min: 2.133\tQ-max: 2.445\tLives: 1\tReward: 64.0\tEpisode Mean: 193.5\n",
-      "87594:127656076\tQ-min: 2.376\tQ-max: 2.508\tLives: 1\tReward: 65.0\tEpisode Mean: 193.5\n",
-      "87594:127656099\tQ-min: 2.311\tQ-max: 2.453\tLives: 1\tReward: 69.0\tEpisode Mean: 193.5\n",
-      "87594:127656122\tQ-min: 2.194\tQ-max: 2.632\tLives: 1\tReward: 73.0\tEpisode Mean: 193.5\n",
-      "87594:127656135\tQ-min: 0.041\tQ-max: 0.202\tLives: 0\tReward: 73.0\tEpisode Mean: 176.3\n",
-      "87595:127656179\tQ-min: 1.787\tQ-max: 1.804\tLives: 5\tReward: 1.0\tEpisode Mean: 176.3\n",
-      "87595:127656232\tQ-min: 1.614\tQ-max: 1.645\tLives: 5\tReward: 2.0\tEpisode Mean: 176.3\n",
-      "87595:127656293\tQ-min: 1.658\tQ-max: 1.683\tLives: 5\tReward: 3.0\tEpisode Mean: 176.3\n",
-      "87595:127656342\tQ-min: 2.007\tQ-max: 2.039\tLives: 5\tReward: 4.0\tEpisode Mean: 176.3\n",
-      "87595:127656371\tQ-min: 1.982\tQ-max: 2.006\tLives: 5\tReward: 5.0\tEpisode Mean: 176.3\n",
-      "87595:127656402\tQ-min: 1.909\tQ-max: 1.933\tLives: 5\tReward: 6.0\tEpisode Mean: 176.3\n",
-      "87595:127656436\tQ-min: 1.743\tQ-max: 1.803\tLives: 5\tReward: 7.0\tEpisode Mean: 176.3\n",
-      "87595:127656456\tQ-min: -0.313\tQ-max: 0.038\tLives: 4\tReward: 7.0\tEpisode Mean: 176.3\n",
-      "87595:127656499\tQ-min: 1.838\tQ-max: 1.848\tLives: 4\tReward: 8.0\tEpisode Mean: 176.3\n",
-      "87595:127656537\tQ-min: 1.963\tQ-max: 1.978\tLives: 4\tReward: 9.0\tEpisode Mean: 176.3\n",
-      "87595:127656590\tQ-min: 1.693\tQ-max: 1.720\tLives: 4\tReward: 10.0\tEpisode Mean: 176.3\n",
-      "87595:127656638\tQ-min: 1.960\tQ-max: 1.993\tLives: 4\tReward: 11.0\tEpisode Mean: 176.3\n",
-      "87595:127656657\tQ-min: -0.459\tQ-max: 0.010\tLives: 3\tReward: 11.0\tEpisode Mean: 176.3\n",
-      "87595:127656706\tQ-min: 1.820\tQ-max: 1.841\tLives: 3\tReward: 12.0\tEpisode Mean: 176.3\n",
-      "87595:127656748\tQ-min: 1.909\tQ-max: 1.929\tLives: 3\tReward: 13.0\tEpisode Mean: 176.3\n",
-      "87595:127656793\tQ-min: 1.927\tQ-max: 1.964\tLives: 3\tReward: 14.0\tEpisode Mean: 176.3\n",
-      "87595:127656833\tQ-min: 2.082\tQ-max: 2.122\tLives: 3\tReward: 18.0\tEpisode Mean: 176.3\n",
-      "87595:127656868\tQ-min: 1.989\tQ-max: 2.011\tLives: 3\tReward: 19.0\tEpisode Mean: 176.3\n",
-      "87595:127656900\tQ-min: 2.109\tQ-max: 2.127\tLives: 3\tReward: 23.0\tEpisode Mean: 176.3\n",
-      "87595:127656934\tQ-min: 2.041\tQ-max: 2.196\tLives: 3\tReward: 24.0\tEpisode Mean: 176.3\n",
-      "87595:127656983\tQ-min: 1.759\tQ-max: 1.890\tLives: 3\tReward: 25.0\tEpisode Mean: 176.3\n",
-      "87595:127657045\tQ-min: 1.616\tQ-max: 1.682\tLives: 3\tReward: 26.0\tEpisode Mean: 176.3\n",
-      "87595:127657107\tQ-min: 1.712\tQ-max: 1.735\tLives: 3\tReward: 27.0\tEpisode Mean: 176.3\n",
-      "87595:127657169\tQ-min: 1.645\tQ-max: 1.729\tLives: 3\tReward: 28.0\tEpisode Mean: 176.3\n",
-      "87595:127657218\tQ-min: 2.122\tQ-max: 2.151\tLives: 3\tReward: 29.0\tEpisode Mean: 176.3\n",
-      "87595:127657251\tQ-min: 2.031\tQ-max: 2.106\tLives: 3\tReward: 30.0\tEpisode Mean: 176.3\n",
-      "87595:127657285\tQ-min: 2.027\tQ-max: 2.106\tLives: 3\tReward: 34.0\tEpisode Mean: 176.3\n",
-      "87595:127657318\tQ-min: 2.200\tQ-max: 2.330\tLives: 3\tReward: 38.0\tEpisode Mean: 176.3\n",
-      "87595:127657356\tQ-min: 2.014\tQ-max: 2.550\tLives: 3\tReward: 42.0\tEpisode Mean: 176.3\n",
-      "87595:127657379\tQ-min: 2.378\tQ-max: 2.420\tLives: 3\tReward: 46.0\tEpisode Mean: 176.3\n",
-      "87595:127657402\tQ-min: 2.039\tQ-max: 2.519\tLives: 3\tReward: 50.0\tEpisode Mean: 176.3\n",
-      "87595:127657423\tQ-min: 2.143\tQ-max: 2.505\tLives: 3\tReward: 54.0\tEpisode Mean: 176.3\n",
-      "87595:127657436\tQ-min: 0.032\tQ-max: 0.222\tLives: 2\tReward: 54.0\tEpisode Mean: 176.3\n",
-      "87595:127657488\tQ-min: 1.849\tQ-max: 1.884\tLives: 2\tReward: 55.0\tEpisode Mean: 176.3\n",
-      "87595:127657542\tQ-min: 2.099\tQ-max: 2.417\tLives: 2\tReward: 62.0\tEpisode Mean: 176.3\n",
-      "87595:127657558\tQ-min: 0.040\tQ-max: 0.255\tLives: 1\tReward: 62.0\tEpisode Mean: 176.3\n",
-      "87595:127657615\tQ-min: 1.877\tQ-max: 1.897\tLives: 1\tReward: 63.0\tEpisode Mean: 176.3\n",
-      "87595:127657683\tQ-min: 1.949\tQ-max: 2.054\tLives: 1\tReward: 64.0\tEpisode Mean: 176.3\n",
-      "87595:127657735\tQ-min: 2.190\tQ-max: 2.218\tLives: 1\tReward: 65.0\tEpisode Mean: 176.3\n",
-      "87595:127657773\tQ-min: 2.213\tQ-max: 2.361\tLives: 1\tReward: 69.0\tEpisode Mean: 176.3\n",
-      "87595:127657812\tQ-min: 2.257\tQ-max: 2.287\tLives: 1\tReward: 70.0\tEpisode Mean: 176.3\n",
-      "87595:127657846\tQ-min: 2.189\tQ-max: 2.253\tLives: 1\tReward: 71.0\tEpisode Mean: 176.3\n",
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-      "87607:127681466\tQ-min: -0.662\tQ-max: 0.099\tLives: 2\tReward: 67.0\tEpisode Mean: 154.0\n",
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-      "87607:127681848\tQ-min: -0.115\tQ-max: 0.157\tLives: 0\tReward: 90.0\tEpisode Mean: 150.8\n",
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-      "87612:127690200\tQ-min: -0.037\tQ-max: 0.172\tLives: 0\tReward: 40.0\tEpisode Mean: 136.8\n",
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-      "87613:127690915\tQ-min: -0.427\tQ-max: 0.563\tLives: 3\tReward: 28.0\tEpisode Mean: 136.8\n",
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-      "87613:127691089\tQ-min: -0.006\tQ-max: 0.138\tLives: 2\tReward: 38.0\tEpisode Mean: 136.8\n",
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-      "87613:127691224\tQ-min: 1.812\tQ-max: 1.864\tLives: 2\tReward: 41.0\tEpisode Mean: 136.8\n",
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-      "87613:127691372\tQ-min: 2.097\tQ-max: 2.232\tLives: 2\tReward: 48.0\tEpisode Mean: 136.8\n",
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-      "87613:127691494\tQ-min: 1.720\tQ-max: 1.880\tLives: 2\tReward: 53.0\tEpisode Mean: 136.8\n",
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-      "87613:127691829\tQ-min: 1.921\tQ-max: 2.489\tLives: 2\tReward: 79.0\tEpisode Mean: 136.8\n",
-      "87613:127691841\tQ-min: 0.072\tQ-max: 0.313\tLives: 1\tReward: 79.0\tEpisode Mean: 136.8\n",
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-      "87613:127692055\tQ-min: 2.361\tQ-max: 2.563\tLives: 1\tReward: 93.0\tEpisode Mean: 136.8\n",
-      "87613:127692078\tQ-min: 2.379\tQ-max: 2.775\tLives: 1\tReward: 97.0\tEpisode Mean: 136.8\n",
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-      "87613:127692125\tQ-min: 2.469\tQ-max: 3.301\tLives: 1\tReward: 111.0\tEpisode Mean: 136.8\n",
-      "87613:127692151\tQ-min: 2.195\tQ-max: 3.053\tLives: 1\tReward: 115.0\tEpisode Mean: 136.8\n",
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-      "87613:127692196\tQ-min: 3.218\tQ-max: 3.777\tLives: 1\tReward: 129.0\tEpisode Mean: 136.8\n",
-      "87613:127692225\tQ-min: 2.640\tQ-max: 7.819\tLives: 1\tReward: 136.0\tEpisode Mean: 136.8\n",
-      "87613:127692231\tQ-min: 3.148\tQ-max: 6.144\tLives: 1\tReward: 143.0\tEpisode Mean: 136.8\n",
-      "87613:127692236\tQ-min: 3.346\tQ-max: 6.952\tLives: 1\tReward: 150.0\tEpisode Mean: 136.8\n",
-      "87613:127692241\tQ-min: 3.525\tQ-max: 6.480\tLives: 1\tReward: 157.0\tEpisode Mean: 136.8\n",
-      "87613:127692245\tQ-min: 2.161\tQ-max: 6.309\tLives: 1\tReward: 164.0\tEpisode Mean: 136.8\n",
-      "87613:127692249\tQ-min: 3.869\tQ-max: 6.309\tLives: 1\tReward: 171.0\tEpisode Mean: 136.8\n",
-      "87613:127692253\tQ-min: 3.571\tQ-max: 5.777\tLives: 1\tReward: 178.0\tEpisode Mean: 136.8\n",
-      "87613:127692258\tQ-min: 3.166\tQ-max: 5.918\tLives: 1\tReward: 185.0\tEpisode Mean: 136.8\n",
-      "87613:127692262\tQ-min: 2.885\tQ-max: 5.234\tLives: 1\tReward: 192.0\tEpisode Mean: 136.8\n",
-      "87613:127692270\tQ-min: 2.900\tQ-max: 3.831\tLives: 1\tReward: 193.0\tEpisode Mean: 136.8\n",
-      "87613:127692278\tQ-min: 2.557\tQ-max: 5.713\tLives: 1\tReward: 200.0\tEpisode Mean: 136.8\n",
-      "87613:127692284\tQ-min: 4.380\tQ-max: 4.935\tLives: 1\tReward: 207.0\tEpisode Mean: 136.8\n",
-      "87613:127692320\tQ-min: 2.739\tQ-max: 5.609\tLives: 1\tReward: 214.0\tEpisode Mean: 136.8\n",
-      "87613:127692327\tQ-min: 3.526\tQ-max: 5.042\tLives: 1\tReward: 218.0\tEpisode Mean: 136.8\n",
-      "87613:127692334\tQ-min: 4.065\tQ-max: 5.043\tLives: 1\tReward: 225.0\tEpisode Mean: 136.8\n",
-      "87613:127692339\tQ-min: 1.078\tQ-max: 4.988\tLives: 1\tReward: 232.0\tEpisode Mean: 136.8\n",
-      "87613:127692343\tQ-min: 4.129\tQ-max: 5.668\tLives: 1\tReward: 239.0\tEpisode Mean: 136.8\n",
-      "87613:127692348\tQ-min: 3.897\tQ-max: 6.170\tLives: 1\tReward: 246.0\tEpisode Mean: 136.8\n",
-      "87613:127692355\tQ-min: 3.166\tQ-max: 5.217\tLives: 1\tReward: 253.0\tEpisode Mean: 136.8\n",
-      "87613:127692395\tQ-min: 2.545\tQ-max: 3.698\tLives: 1\tReward: 260.0\tEpisode Mean: 136.8\n",
-      "87613:127692402\tQ-min: 3.140\tQ-max: 4.613\tLives: 1\tReward: 267.0\tEpisode Mean: 136.8\n",
-      "87613:127692408\tQ-min: 2.794\tQ-max: 4.494\tLives: 1\tReward: 274.0\tEpisode Mean: 136.8\n",
-      "87613:127692414\tQ-min: 2.961\tQ-max: 4.157\tLives: 1\tReward: 278.0\tEpisode Mean: 136.8\n",
-      "87613:127692420\tQ-min: 2.604\tQ-max: 4.554\tLives: 1\tReward: 285.0\tEpisode Mean: 136.8\n",
-      "87613:127692427\tQ-min: 2.394\tQ-max: 4.361\tLives: 1\tReward: 292.0\tEpisode Mean: 136.8\n",
-      "87613:127692465\tQ-min: 2.877\tQ-max: 4.571\tLives: 1\tReward: 299.0\tEpisode Mean: 136.8\n",
-      "87613:127692485\tQ-min: -1.033\tQ-max: 0.680\tLives: 0\tReward: 299.0\tEpisode Mean: 143.0\n",
-      "87614:127692527\tQ-min: 1.766\tQ-max: 1.789\tLives: 5\tReward: 1.0\tEpisode Mean: 143.0\n",
-      "87614:127692565\tQ-min: 1.803\tQ-max: 1.843\tLives: 5\tReward: 2.0\tEpisode Mean: 143.0\n",
-      "87614:127692591\tQ-min: -0.225\tQ-max: 0.154\tLives: 4\tReward: 2.0\tEpisode Mean: 143.0\n",
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-      "87614:127692757\tQ-min: 1.970\tQ-max: 2.008\tLives: 4\tReward: 6.0\tEpisode Mean: 143.0\n",
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-      "87614:127692854\tQ-min: 1.956\tQ-max: 2.014\tLives: 4\tReward: 9.0\tEpisode Mean: 143.0\n",
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-      "87614:127692963\tQ-min: 1.506\tQ-max: 1.674\tLives: 4\tReward: 14.0\tEpisode Mean: 143.0\n",
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-      "87614:127693095\tQ-min: 1.765\tQ-max: 1.803\tLives: 4\tReward: 16.0\tEpisode Mean: 143.0\n",
-      "87614:127693141\tQ-min: -0.065\tQ-max: 0.344\tLives: 3\tReward: 16.0\tEpisode Mean: 143.0\n",
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-      "87615:127696523\tQ-min: 0.266\tQ-max: 0.417\tLives: 0\tReward: 340.0\tEpisode Mean: 147.5\n",
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-      "87616:127697583\tQ-min: 1.657\tQ-max: 1.745\tLives: 3\tReward: 25.0\tEpisode Mean: 147.5\n",
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-      "87616:127697766\tQ-min: 2.042\tQ-max: 2.062\tLives: 3\tReward: 31.0\tEpisode Mean: 147.5\n",
-      "87616:127697800\tQ-min: 2.033\tQ-max: 2.101\tLives: 3\tReward: 32.0\tEpisode Mean: 147.5\n",
-      "87616:127697830\tQ-min: 2.066\tQ-max: 2.106\tLives: 3\tReward: 33.0\tEpisode Mean: 147.5\n",
-      "87616:127697863\tQ-min: 1.952\tQ-max: 2.108\tLives: 3\tReward: 34.0\tEpisode Mean: 147.5\n",
-      "87616:127697898\tQ-min: 2.262\tQ-max: 2.323\tLives: 3\tReward: 38.0\tEpisode Mean: 147.5\n",
-      "87616:127697912\tQ-min: 0.078\tQ-max: 0.422\tLives: 2\tReward: 38.0\tEpisode Mean: 147.5\n",
-      "87616:127697968\tQ-min: 1.802\tQ-max: 1.856\tLives: 2\tReward: 39.0\tEpisode Mean: 147.5\n",
-      "87616:127698031\tQ-min: 1.838\tQ-max: 1.876\tLives: 2\tReward: 40.0\tEpisode Mean: 147.5\n",
-      "87616:127698099\tQ-min: 1.856\tQ-max: 1.898\tLives: 2\tReward: 41.0\tEpisode Mean: 147.5\n",
-      "87616:127698150\tQ-min: 2.508\tQ-max: 2.578\tLives: 2\tReward: 45.0\tEpisode Mean: 147.5\n",
-      "87616:127698172\tQ-min: 2.409\tQ-max: 2.576\tLives: 2\tReward: 49.0\tEpisode Mean: 147.5\n",
-      "87616:127698193\tQ-min: 2.089\tQ-max: 2.658\tLives: 2\tReward: 56.0\tEpisode Mean: 147.5\n",
-      "87616:127698216\tQ-min: 2.436\tQ-max: 2.506\tLives: 2\tReward: 57.0\tEpisode Mean: 147.5\n",
-      "87616:127698236\tQ-min: 2.420\tQ-max: 2.482\tLives: 2\tReward: 58.0\tEpisode Mean: 147.5\n",
-      "87616:127698257\tQ-min: 2.457\tQ-max: 2.508\tLives: 2\tReward: 62.0\tEpisode Mean: 147.5\n",
-      "87616:127698278\tQ-min: 2.433\tQ-max: 2.551\tLives: 2\tReward: 66.0\tEpisode Mean: 147.5\n",
-      "87616:127698291\tQ-min: -0.079\tQ-max: 0.126\tLives: 1\tReward: 66.0\tEpisode Mean: 147.5\n",
-      "87616:127698343\tQ-min: 1.843\tQ-max: 1.872\tLives: 1\tReward: 67.0\tEpisode Mean: 147.5\n",
-      "87616:127698399\tQ-min: 2.090\tQ-max: 2.351\tLives: 1\tReward: 71.0\tEpisode Mean: 147.5\n",
-      "87616:127698456\tQ-min: 1.968\tQ-max: 2.183\tLives: 1\tReward: 75.0\tEpisode Mean: 147.5\n",
-      "87616:127698512\tQ-min: 2.150\tQ-max: 2.390\tLives: 1\tReward: 79.0\tEpisode Mean: 147.5\n",
-      "87616:127698549\tQ-min: 2.398\tQ-max: 2.454\tLives: 1\tReward: 80.0\tEpisode Mean: 147.5\n",
-      "87616:127698584\tQ-min: 2.203\tQ-max: 2.419\tLives: 1\tReward: 84.0\tEpisode Mean: 147.5\n",
-      "87616:127698620\tQ-min: 2.034\tQ-max: 2.903\tLives: 1\tReward: 88.0\tEpisode Mean: 147.5\n",
-      "87616:127698641\tQ-min: 2.441\tQ-max: 2.569\tLives: 1\tReward: 89.0\tEpisode Mean: 147.5\n",
-      "87616:127698661\tQ-min: 2.446\tQ-max: 2.627\tLives: 1\tReward: 93.0\tEpisode Mean: 147.5\n",
-      "87616:127698684\tQ-min: 2.499\tQ-max: 2.649\tLives: 1\tReward: 94.0\tEpisode Mean: 147.5\n",
-      "87616:127698707\tQ-min: 2.364\tQ-max: 2.641\tLives: 1\tReward: 98.0\tEpisode Mean: 147.5\n",
-      "87616:127698721\tQ-min: -0.372\tQ-max: 0.212\tLives: 0\tReward: 98.0\tEpisode Mean: 145.8\n",
-      "87617:127698766\tQ-min: 1.752\tQ-max: 1.767\tLives: 5\tReward: 1.0\tEpisode Mean: 145.8\n",
-      "87617:127698808\tQ-min: 1.814\tQ-max: 1.833\tLives: 5\tReward: 2.0\tEpisode Mean: 145.8\n",
-      "87617:127698846\tQ-min: 1.934\tQ-max: 2.003\tLives: 5\tReward: 3.0\tEpisode Mean: 145.8\n",
-      "87617:127698884\tQ-min: 1.993\tQ-max: 2.013\tLives: 5\tReward: 4.0\tEpisode Mean: 145.8\n",
-      "87617:127698913\tQ-min: 1.983\tQ-max: 2.006\tLives: 5\tReward: 5.0\tEpisode Mean: 145.8\n",
-      "87617:127698943\tQ-min: 1.895\tQ-max: 1.934\tLives: 5\tReward: 6.0\tEpisode Mean: 145.8\n",
-      "87617:127698975\tQ-min: 1.748\tQ-max: 1.790\tLives: 5\tReward: 7.0\tEpisode Mean: 145.8\n",
-      "87617:127699023\tQ-min: 1.579\tQ-max: 1.655\tLives: 5\tReward: 8.0\tEpisode Mean: 145.8\n",
-      "87617:127699090\tQ-min: 1.652\tQ-max: 1.752\tLives: 5\tReward: 9.0\tEpisode Mean: 145.8\n",
-      "87617:127699159\tQ-min: 1.698\tQ-max: 1.752\tLives: 5\tReward: 10.0\tEpisode Mean: 145.8\n",
-      "87617:127699202\tQ-min: -0.031\tQ-max: 0.225\tLives: 4\tReward: 10.0\tEpisode Mean: 145.8\n",
-      "87617:127699246\tQ-min: 1.889\tQ-max: 1.922\tLives: 4\tReward: 11.0\tEpisode Mean: 145.8\n",
-      "87617:127699296\tQ-min: 1.914\tQ-max: 1.953\tLives: 4\tReward: 15.0\tEpisode Mean: 145.8\n",
-      "87617:127699353\tQ-min: 1.757\tQ-max: 1.781\tLives: 4\tReward: 16.0\tEpisode Mean: 145.8\n",
-      "87617:127699403\tQ-min: 2.019\tQ-max: 2.053\tLives: 4\tReward: 17.0\tEpisode Mean: 145.8\n",
-      "87617:127699434\tQ-min: 2.157\tQ-max: 2.220\tLives: 4\tReward: 18.0\tEpisode Mean: 145.8\n",
-      "87617:127699468\tQ-min: 1.990\tQ-max: 2.004\tLives: 4\tReward: 19.0\tEpisode Mean: 145.8\n",
-      "87617:127699501\tQ-min: 1.990\tQ-max: 2.028\tLives: 4\tReward: 20.0\tEpisode Mean: 145.8\n",
-      "87617:127699549\tQ-min: 1.681\tQ-max: 1.707\tLives: 4\tReward: 21.0\tEpisode Mean: 145.8\n",
-      "87617:127699614\tQ-min: 1.751\tQ-max: 1.785\tLives: 4\tReward: 22.0\tEpisode Mean: 145.8\n",
-      "87617:127699674\tQ-min: 1.735\tQ-max: 1.746\tLives: 4\tReward: 23.0\tEpisode Mean: 145.8\n",
-      "87617:127699736\tQ-min: 1.770\tQ-max: 1.788\tLives: 4\tReward: 24.0\tEpisode Mean: 145.8\n",
-      "87617:127699784\tQ-min: 1.994\tQ-max: 2.046\tLives: 4\tReward: 25.0\tEpisode Mean: 145.8\n",
-      "87617:127699816\tQ-min: 2.013\tQ-max: 2.036\tLives: 4\tReward: 26.0\tEpisode Mean: 145.8\n",
-      "87617:127699837\tQ-min: -0.117\tQ-max: 0.201\tLives: 3\tReward: 26.0\tEpisode Mean: 145.8\n",
-      "87617:127699880\tQ-min: 1.936\tQ-max: 1.952\tLives: 3\tReward: 27.0\tEpisode Mean: 145.8\n",
-      "87617:127699937\tQ-min: 1.639\tQ-max: 1.781\tLives: 3\tReward: 28.0\tEpisode Mean: 145.8\n",
-      "87617:127699992\tQ-min: 2.026\tQ-max: 2.058\tLives: 3\tReward: 29.0\tEpisode Mean: 145.8\n",
-      "87617:127700030\tQ-min: 2.014\tQ-max: 2.034\tLives: 3\tReward: 30.0\tEpisode Mean: 145.8\n",
-      "87617:127700066\tQ-min: 2.029\tQ-max: 2.075\tLives: 3\tReward: 31.0\tEpisode Mean: 145.8\n",
-      "87617:127700098\tQ-min: 2.160\tQ-max: 2.572\tLives: 3\tReward: 35.0\tEpisode Mean: 145.8\n",
-      "87617:127700118\tQ-min: 2.057\tQ-max: 2.423\tLives: 3\tReward: 39.0\tEpisode Mean: 145.8\n",
-      "87617:127700139\tQ-min: 2.400\tQ-max: 2.545\tLives: 3\tReward: 43.0\tEpisode Mean: 145.8\n",
-      "87617:127700158\tQ-min: 2.066\tQ-max: 2.565\tLives: 3\tReward: 50.0\tEpisode Mean: 145.8\n",
-      "87617:127700180\tQ-min: 2.392\tQ-max: 2.474\tLives: 3\tReward: 51.0\tEpisode Mean: 145.8\n",
-      "87617:127700200\tQ-min: 2.233\tQ-max: 2.483\tLives: 3\tReward: 52.0\tEpisode Mean: 145.8\n",
-      "87617:127700221\tQ-min: 2.048\tQ-max: 2.191\tLives: 3\tReward: 56.0\tEpisode Mean: 145.8\n",
-      "87617:127700245\tQ-min: 2.330\tQ-max: 2.450\tLives: 3\tReward: 60.0\tEpisode Mean: 145.8\n",
-      "87617:127700271\tQ-min: 2.389\tQ-max: 2.500\tLives: 3\tReward: 61.0\tEpisode Mean: 145.8\n",
-      "87617:127700293\tQ-min: 2.307\tQ-max: 2.508\tLives: 3\tReward: 65.0\tEpisode Mean: 145.8\n",
-      "87617:127700306\tQ-min: -0.006\tQ-max: 0.113\tLives: 2\tReward: 65.0\tEpisode Mean: 145.8\n",
-      "87617:127700351\tQ-min: 1.970\tQ-max: 2.111\tLives: 2\tReward: 69.0\tEpisode Mean: 145.8\n",
-      "87617:127700399\tQ-min: 2.366\tQ-max: 2.450\tLives: 2\tReward: 73.0\tEpisode Mean: 145.8\n",
-      "87617:127700422\tQ-min: 2.140\tQ-max: 2.488\tLives: 2\tReward: 74.0\tEpisode Mean: 145.8\n",
-      "87617:127700442\tQ-min: 2.122\tQ-max: 2.493\tLives: 2\tReward: 78.0\tEpisode Mean: 145.8\n",
-      "87617:127700464\tQ-min: 2.243\tQ-max: 2.550\tLives: 2\tReward: 82.0\tEpisode Mean: 145.8\n",
-      "87617:127700488\tQ-min: 2.414\tQ-max: 2.670\tLives: 2\tReward: 86.0\tEpisode Mean: 145.8\n",
-      "87617:127700510\tQ-min: 2.252\tQ-max: 2.626\tLives: 2\tReward: 93.0\tEpisode Mean: 145.8\n",
-      "87617:127700533\tQ-min: 2.150\tQ-max: 2.691\tLives: 2\tReward: 100.0\tEpisode Mean: 145.8\n",
-      "87617:127700556\tQ-min: 1.972\tQ-max: 2.779\tLives: 2\tReward: 101.0\tEpisode Mean: 145.8\n",
-      "87617:127700567\tQ-min: -0.020\tQ-max: 0.190\tLives: 1\tReward: 101.0\tEpisode Mean: 145.8\n",
-      "87617:127700613\tQ-min: 2.301\tQ-max: 2.671\tLives: 1\tReward: 105.0\tEpisode Mean: 145.8\n",
-      "87617:127700659\tQ-min: 2.437\tQ-max: 2.946\tLives: 1\tReward: 106.0\tEpisode Mean: 145.8\n",
-      "87617:127700709\tQ-min: 0.855\tQ-max: 2.276\tLives: 1\tReward: 113.0\tEpisode Mean: 145.8\n",
-      "87617:127700735\tQ-min: 1.749\tQ-max: 3.022\tLives: 1\tReward: 120.0\tEpisode Mean: 145.8\n",
-      "87617:127700761\tQ-min: 2.380\tQ-max: 3.517\tLives: 1\tReward: 127.0\tEpisode Mean: 145.8\n",
-      "87617:127700778\tQ-min: -0.098\tQ-max: 0.169\tLives: 0\tReward: 127.0\tEpisode Mean: 145.2\n"
+      "2392:1177839\tQ-min: 1.184\tQ-max: 1.365\tLives: 5\tReward: 1.0\tEpisode Mean: 0.0\n",
+      "2392:1177890\tQ-min: 1.239\tQ-max: 1.387\tLives: 5\tReward: 2.0\tEpisode Mean: 0.0\n",
+      "2392:1177953\tQ-min: 1.205\tQ-max: 1.420\tLives: 5\tReward: 3.0\tEpisode Mean: 0.0\n",
+      "2392:1177999\tQ-min: 1.243\tQ-max: 1.541\tLives: 5\tReward: 4.0\tEpisode Mean: 0.0\n",
+      "2392:1178032\tQ-min: 1.236\tQ-max: 1.516\tLives: 5\tReward: 5.0\tEpisode Mean: 0.0\n",
+      "2392:1178055\tQ-min: 0.050\tQ-max: 0.106\tLives: 4\tReward: 5.0\tEpisode Mean: 0.0\n",
+      "2392:1178106\tQ-min: 1.229\tQ-max: 1.348\tLives: 4\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "2392:1178147\tQ-min: 0.103\tQ-max: 0.128\tLives: 3\tReward: 6.0\tEpisode Mean: 0.0\n",
+      "2392:1178205\tQ-min: 1.239\tQ-max: 1.342\tLives: 3\tReward: 7.0\tEpisode Mean: 0.0\n",
+      "2392:1178269\tQ-min: 1.254\tQ-max: 1.491\tLives: 3\tReward: 8.0\tEpisode Mean: 0.0\n",
+      "2392:1178308\tQ-min: 0.082\tQ-max: 0.123\tLives: 2\tReward: 8.0\tEpisode Mean: 0.0\n",
+      "2392:1178355\tQ-min: 1.247\tQ-max: 1.398\tLives: 2\tReward: 9.0\tEpisode Mean: 0.0\n",
+      "2392:1178382\tQ-min: 0.131\tQ-max: 0.157\tLives: 1\tReward: 9.0\tEpisode Mean: 0.0\n",
+      "2392:1178441\tQ-min: 1.198\tQ-max: 1.503\tLives: 1\tReward: 10.0\tEpisode Mean: 0.0\n",
+      "2392:1178506\tQ-min: 1.218\tQ-max: 1.342\tLives: 1\tReward: 11.0\tEpisode Mean: 0.0\n",
+      "2392:1178573\tQ-min: 1.211\tQ-max: 1.554\tLives: 1\tReward: 12.0\tEpisode Mean: 0.0\n",
+      "2392:1178628\tQ-min: 1.272\tQ-max: 1.546\tLives: 1\tReward: 13.0\tEpisode Mean: 0.0\n",
+      "2392:1178650\tQ-min: 0.079\tQ-max: 0.122\tLives: 0\tReward: 13.0\tEpisode Mean: 13.0\n",
+      "2393:1178697\tQ-min: 1.203\tQ-max: 1.427\tLives: 5\tReward: 1.0\tEpisode Mean: 13.0\n",
+      "2393:1178739\tQ-min: 1.233\tQ-max: 1.548\tLives: 5\tReward: 2.0\tEpisode Mean: 13.0\n",
+      "2393:1178793\tQ-min: 1.309\tQ-max: 1.414\tLives: 5\tReward: 3.0\tEpisode Mean: 13.0\n",
+      "2393:1178835\tQ-min: 0.102\tQ-max: 0.131\tLives: 4\tReward: 3.0\tEpisode Mean: 13.0\n",
+      "2393:1178878\tQ-min: 1.257\tQ-max: 1.521\tLives: 4\tReward: 4.0\tEpisode Mean: 13.0\n",
+      "2393:1178921\tQ-min: 1.275\tQ-max: 1.446\tLives: 4\tReward: 5.0\tEpisode Mean: 13.0\n",
+      "2393:1178966\tQ-min: 1.297\tQ-max: 1.528\tLives: 4\tReward: 6.0\tEpisode Mean: 13.0\n",
+      "2393:1178997\tQ-min: 0.083\tQ-max: 0.126\tLives: 3\tReward: 6.0\tEpisode Mean: 13.0\n",
+      "2393:1179043\tQ-min: 1.246\tQ-max: 1.419\tLives: 3\tReward: 7.0\tEpisode Mean: 13.0\n",
+      "2393:1179098\tQ-min: 1.231\tQ-max: 1.501\tLives: 3\tReward: 8.0\tEpisode Mean: 13.0\n",
+      "2393:1179151\tQ-min: 1.264\tQ-max: 1.522\tLives: 3\tReward: 9.0\tEpisode Mean: 13.0\n",
+      "2393:1179183\tQ-min: 0.069\tQ-max: 0.107\tLives: 2\tReward: 9.0\tEpisode Mean: 13.0\n",
+      "2393:1179239\tQ-min: 1.253\tQ-max: 1.325\tLives: 2\tReward: 10.0\tEpisode Mean: 13.0\n",
+      "2393:1179305\tQ-min: 1.280\tQ-max: 1.464\tLives: 2\tReward: 14.0\tEpisode Mean: 13.0\n",
+      "2393:1179350\tQ-min: 0.060\tQ-max: 0.100\tLives: 1\tReward: 14.0\tEpisode Mean: 13.0\n",
+      "2393:1179390\tQ-min: 1.216\tQ-max: 1.519\tLives: 1\tReward: 15.0\tEpisode Mean: 13.0\n",
+      "2393:1179432\tQ-min: 1.231\tQ-max: 1.558\tLives: 1\tReward: 16.0\tEpisode Mean: 13.0\n",
+      "2393:1179478\tQ-min: 1.285\tQ-max: 1.511\tLives: 1\tReward: 17.0\tEpisode Mean: 13.0\n",
+      "2393:1179517\tQ-min: 1.237\tQ-max: 1.543\tLives: 1\tReward: 18.0\tEpisode Mean: 13.0\n",
+      "2393:1179549\tQ-min: 1.248\tQ-max: 1.507\tLives: 1\tReward: 19.0\tEpisode Mean: 13.0\n",
+      "2393:1179584\tQ-min: 1.236\tQ-max: 1.507\tLives: 1\tReward: 20.0\tEpisode Mean: 13.0\n",
+      "2393:1179606\tQ-min: 0.049\tQ-max: 0.105\tLives: 0\tReward: 20.0\tEpisode Mean: 16.5\n",
+      "2394:1179648\tQ-min: 1.256\tQ-max: 1.476\tLives: 5\tReward: 1.0\tEpisode Mean: 16.5\n",
+      "2394:1179700\tQ-min: 1.234\tQ-max: 1.445\tLives: 5\tReward: 2.0\tEpisode Mean: 16.5\n",
+      "2394:1179738\tQ-min: 0.107\tQ-max: 0.141\tLives: 4\tReward: 2.0\tEpisode Mean: 16.5\n",
+      "2394:1179783\tQ-min: 1.214\tQ-max: 1.541\tLives: 4\tReward: 3.0\tEpisode Mean: 16.5\n",
+      "2394:1179836\tQ-min: 1.240\tQ-max: 1.416\tLives: 4\tReward: 4.0\tEpisode Mean: 16.5\n",
+      "2394:1179889\tQ-min: 1.260\tQ-max: 1.504\tLives: 4\tReward: 5.0\tEpisode Mean: 16.5\n",
+      "2394:1179925\tQ-min: 1.334\tQ-max: 1.603\tLives: 4\tReward: 6.0\tEpisode Mean: 16.5\n",
+      "2394:1179947\tQ-min: 0.073\tQ-max: 0.119\tLives: 3\tReward: 6.0\tEpisode Mean: 16.5\n",
+      "2394:1179992\tQ-min: 1.246\tQ-max: 1.600\tLives: 3\tReward: 7.0\tEpisode Mean: 16.5\n",
+      "2394:1180045\tQ-min: 1.220\tQ-max: 1.485\tLives: 3\tReward: 8.0\tEpisode Mean: 16.5\n",
+      "2394:1180108\tQ-min: 1.235\tQ-max: 1.397\tLives: 3\tReward: 9.0\tEpisode Mean: 16.5\n",
+      "2394:1180153\tQ-min: 1.245\tQ-max: 1.484\tLives: 3\tReward: 10.0\tEpisode Mean: 16.5\n",
+      "2394:1180184\tQ-min: 1.274\tQ-max: 1.610\tLives: 3\tReward: 11.0\tEpisode Mean: 16.5\n",
+      "2394:1180216\tQ-min: 1.277\tQ-max: 1.399\tLives: 3\tReward: 12.0\tEpisode Mean: 16.5\n",
+      "2394:1180248\tQ-min: 1.279\tQ-max: 1.556\tLives: 3\tReward: 13.0\tEpisode Mean: 16.5\n",
+      "2394:1180268\tQ-min: 0.142\tQ-max: 0.154\tLives: 2\tReward: 13.0\tEpisode Mean: 16.5\n",
+      "2394:1180301\tQ-min: 0.085\tQ-max: 0.113\tLives: 1\tReward: 13.0\tEpisode Mean: 16.5\n",
+      "2394:1180355\tQ-min: 1.252\tQ-max: 1.359\tLives: 1\tReward: 14.0\tEpisode Mean: 16.5\n",
+      "2394:1180420\tQ-min: 1.216\tQ-max: 1.448\tLives: 1\tReward: 15.0\tEpisode Mean: 16.5\n",
+      "2394:1180464\tQ-min: 0.038\tQ-max: 0.105\tLives: 0\tReward: 15.0\tEpisode Mean: 16.0\n",
+      "2395:1180508\tQ-min: 1.243\tQ-max: 1.442\tLives: 5\tReward: 1.0\tEpisode Mean: 16.0\n",
+      "2395:1180536\tQ-min: 0.075\tQ-max: 0.113\tLives: 4\tReward: 1.0\tEpisode Mean: 16.0\n",
+      "2395:1180594\tQ-min: 1.224\tQ-max: 1.365\tLives: 4\tReward: 2.0\tEpisode Mean: 16.0\n",
+      "2395:1180635\tQ-min: 0.088\tQ-max: 0.131\tLives: 3\tReward: 2.0\tEpisode Mean: 16.0\n",
+      "2395:1180678\tQ-min: 1.234\tQ-max: 1.464\tLives: 3\tReward: 3.0\tEpisode Mean: 16.0\n",
+      "2395:1180730\tQ-min: 1.274\tQ-max: 1.366\tLives: 3\tReward: 4.0\tEpisode Mean: 16.0\n",
+      "2395:1180792\tQ-min: 1.223\tQ-max: 1.372\tLives: 3\tReward: 5.0\tEpisode Mean: 16.0\n",
+      "2395:1180841\tQ-min: 1.232\tQ-max: 1.580\tLives: 3\tReward: 6.0\tEpisode Mean: 16.0\n",
+      "2395:1180876\tQ-min: 1.283\tQ-max: 1.449\tLives: 3\tReward: 7.0\tEpisode Mean: 16.0\n",
+      "2395:1180911\tQ-min: 1.224\tQ-max: 1.545\tLives: 3\tReward: 11.0\tEpisode Mean: 16.0\n",
+      "2395:1180934\tQ-min: 0.094\tQ-max: 0.122\tLives: 2\tReward: 11.0\tEpisode Mean: 16.0\n",
+      "2395:1180979\tQ-min: 1.259\tQ-max: 1.421\tLives: 2\tReward: 12.0\tEpisode Mean: 16.0\n",
+      "2395:1181005\tQ-min: 0.070\tQ-max: 0.112\tLives: 1\tReward: 12.0\tEpisode Mean: 16.0\n",
+      "2395:1181062\tQ-min: 1.235\tQ-max: 1.389\tLives: 1\tReward: 13.0\tEpisode Mean: 16.0\n",
+      "2395:1181114\tQ-min: 1.251\tQ-max: 1.598\tLives: 1\tReward: 14.0\tEpisode Mean: 16.0\n",
+      "2395:1181173\tQ-min: 1.195\tQ-max: 1.431\tLives: 1\tReward: 15.0\tEpisode Mean: 16.0\n",
+      "2395:1181215\tQ-min: 0.102\tQ-max: 0.136\tLives: 0\tReward: 15.0\tEpisode Mean: 15.8\n",
+      "2396:1181268\tQ-min: 1.211\tQ-max: 1.397\tLives: 5\tReward: 1.0\tEpisode Mean: 15.8\n",
+      "2396:1181331\tQ-min: 1.216\tQ-max: 1.481\tLives: 5\tReward: 2.0\tEpisode Mean: 15.8\n",
+      "2396:1181398\tQ-min: 1.215\tQ-max: 1.386\tLives: 5\tReward: 3.0\tEpisode Mean: 15.8\n",
+      "2396:1181446\tQ-min: 1.279\tQ-max: 1.453\tLives: 5\tReward: 4.0\tEpisode Mean: 15.8\n",
+      "2396:1181464\tQ-min: 0.236\tQ-max: 0.240\tLives: 4\tReward: 4.0\tEpisode Mean: 15.8\n",
+      "2396:1181521\tQ-min: 1.202\tQ-max: 1.430\tLives: 4\tReward: 5.0\tEpisode Mean: 15.8\n",
+      "2396:1181570\tQ-min: 1.263\tQ-max: 1.558\tLives: 4\tReward: 6.0\tEpisode Mean: 15.8\n",
+      "2396:1181620\tQ-min: 1.257\tQ-max: 1.536\tLives: 4\tReward: 7.0\tEpisode Mean: 15.8\n",
+      "2396:1181665\tQ-min: 1.262\tQ-max: 1.546\tLives: 4\tReward: 8.0\tEpisode Mean: 15.8\n",
+      "2396:1181697\tQ-min: 1.265\tQ-max: 1.603\tLives: 4\tReward: 9.0\tEpisode Mean: 15.8\n",
+      "2396:1181733\tQ-min: 1.242\tQ-max: 1.638\tLives: 4\tReward: 10.0\tEpisode Mean: 15.8\n",
+      "2396:1181763\tQ-min: 1.220\tQ-max: 1.614\tLives: 4\tReward: 11.0\tEpisode Mean: 15.8\n",
+      "2396:1181811\tQ-min: 1.219\tQ-max: 1.439\tLives: 4\tReward: 12.0\tEpisode Mean: 15.8\n",
+      "2396:1181852\tQ-min: 0.090\tQ-max: 0.128\tLives: 3\tReward: 12.0\tEpisode Mean: 15.8\n",
+      "2396:1181897\tQ-min: 1.292\tQ-max: 1.475\tLives: 3\tReward: 13.0\tEpisode Mean: 15.8\n",
+      "2396:1181948\tQ-min: 1.281\tQ-max: 1.448\tLives: 3\tReward: 14.0\tEpisode Mean: 15.8\n",
+      "2396:1181992\tQ-min: 0.110\tQ-max: 0.142\tLives: 2\tReward: 14.0\tEpisode Mean: 15.8\n",
+      "2396:1182050\tQ-min: 1.275\tQ-max: 1.405\tLives: 2\tReward: 15.0\tEpisode Mean: 15.8\n",
+      "2396:1182093\tQ-min: 0.132\tQ-max: 0.143\tLives: 1\tReward: 15.0\tEpisode Mean: 15.8\n",
+      "2396:1182154\tQ-min: 1.196\tQ-max: 1.422\tLives: 1\tReward: 16.0\tEpisode Mean: 15.8\n",
+      "2396:1182216\tQ-min: 1.259\tQ-max: 1.382\tLives: 1\tReward: 17.0\tEpisode Mean: 15.8\n",
+      "2396:1182260\tQ-min: 0.087\tQ-max: 0.123\tLives: 0\tReward: 17.0\tEpisode Mean: 16.0\n",
+      "2397:1182303\tQ-min: 1.241\tQ-max: 1.408\tLives: 5\tReward: 1.0\tEpisode Mean: 16.0\n",
+      "2397:1182343\tQ-min: 1.216\tQ-max: 1.535\tLives: 5\tReward: 2.0\tEpisode Mean: 16.0\n",
+      "2397:1182370\tQ-min: 0.083\tQ-max: 0.125\tLives: 4\tReward: 2.0\tEpisode Mean: 16.0\n",
+      "2397:1182423\tQ-min: 1.263\tQ-max: 1.339\tLives: 4\tReward: 3.0\tEpisode Mean: 16.0\n",
+      "2397:1182474\tQ-min: 1.246\tQ-max: 1.449\tLives: 4\tReward: 4.0\tEpisode Mean: 16.0\n",
+      "2397:1182501\tQ-min: 0.079\tQ-max: 0.118\tLives: 3\tReward: 4.0\tEpisode Mean: 16.0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2397:1182556\tQ-min: 1.242\tQ-max: 1.360\tLives: 3\tReward: 5.0\tEpisode Mean: 16.0\n",
+      "2397:1182598\tQ-min: 0.101\tQ-max: 0.133\tLives: 2\tReward: 5.0\tEpisode Mean: 16.0\n",
+      "2397:1182656\tQ-min: 1.242\tQ-max: 1.447\tLives: 2\tReward: 6.0\tEpisode Mean: 16.0\n",
+      "2397:1182711\tQ-min: 1.266\tQ-max: 1.499\tLives: 2\tReward: 7.0\tEpisode Mean: 16.0\n",
+      "2397:1182763\tQ-min: 1.257\tQ-max: 1.469\tLives: 2\tReward: 8.0\tEpisode Mean: 16.0\n",
+      "2397:1182803\tQ-min: 0.084\tQ-max: 0.123\tLives: 1\tReward: 8.0\tEpisode Mean: 16.0\n",
+      "2397:1182838\tQ-min: 0.112\tQ-max: 0.129\tLives: 0\tReward: 8.0\tEpisode Mean: 14.7\n",
+      "2398:1182879\tQ-min: 1.246\tQ-max: 1.351\tLives: 5\tReward: 1.0\tEpisode Mean: 14.7\n",
+      "2398:1182921\tQ-min: 1.223\tQ-max: 1.593\tLives: 5\tReward: 2.0\tEpisode Mean: 14.7\n",
+      "2398:1182950\tQ-min: 0.049\tQ-max: 0.102\tLives: 4\tReward: 2.0\tEpisode Mean: 14.7\n",
+      "2398:1183003\tQ-min: 1.221\tQ-max: 1.315\tLives: 4\tReward: 3.0\tEpisode Mean: 14.7\n",
+      "2398:1183053\tQ-min: 1.278\tQ-max: 1.396\tLives: 4\tReward: 4.0\tEpisode Mean: 14.7\n",
+      "2398:1183106\tQ-min: 1.283\tQ-max: 1.461\tLives: 4\tReward: 5.0\tEpisode Mean: 14.7\n",
+      "2398:1183151\tQ-min: 1.276\tQ-max: 1.649\tLives: 4\tReward: 6.0\tEpisode Mean: 14.7\n",
+      "2398:1183172\tQ-min: 0.064\tQ-max: 0.111\tLives: 3\tReward: 6.0\tEpisode Mean: 14.7\n",
+      "2398:1183216\tQ-min: 1.277\tQ-max: 1.555\tLives: 3\tReward: 7.0\tEpisode Mean: 14.7\n",
+      "2398:1183244\tQ-min: 0.100\tQ-max: 0.134\tLives: 2\tReward: 7.0\tEpisode Mean: 14.7\n",
+      "2398:1183288\tQ-min: 1.237\tQ-max: 1.577\tLives: 2\tReward: 8.0\tEpisode Mean: 14.7\n",
+      "2398:1183342\tQ-min: 1.251\tQ-max: 1.539\tLives: 2\tReward: 9.0\tEpisode Mean: 14.7\n",
+      "2398:1183408\tQ-min: 1.245\tQ-max: 1.439\tLives: 2\tReward: 10.0\tEpisode Mean: 14.7\n",
+      "2398:1183460\tQ-min: 1.216\tQ-max: 1.593\tLives: 2\tReward: 11.0\tEpisode Mean: 14.7\n",
+      "2398:1183492\tQ-min: 1.219\tQ-max: 1.558\tLives: 2\tReward: 12.0\tEpisode Mean: 14.7\n",
+      "2398:1183512\tQ-min: 0.131\tQ-max: 0.153\tLives: 1\tReward: 12.0\tEpisode Mean: 14.7\n",
+      "2398:1183558\tQ-min: 1.210\tQ-max: 1.508\tLives: 1\tReward: 13.0\tEpisode Mean: 14.7\n",
+      "2398:1183603\tQ-min: 1.261\tQ-max: 1.509\tLives: 1\tReward: 14.0\tEpisode Mean: 14.7\n",
+      "2398:1183645\tQ-min: 1.262\tQ-max: 1.532\tLives: 1\tReward: 15.0\tEpisode Mean: 14.7\n",
+      "2398:1183685\tQ-min: 1.190\tQ-max: 1.451\tLives: 1\tReward: 19.0\tEpisode Mean: 14.7\n",
+      "2398:1183709\tQ-min: 0.061\tQ-max: 0.101\tLives: 0\tReward: 19.0\tEpisode Mean: 15.3\n",
+      "2399:1183756\tQ-min: 1.252\tQ-max: 1.448\tLives: 5\tReward: 1.0\tEpisode Mean: 15.3\n",
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+      "2399:1183935\tQ-min: 1.218\tQ-max: 1.543\tLives: 4\tReward: 4.0\tEpisode Mean: 15.3\n",
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+      "2399:1184113\tQ-min: 1.240\tQ-max: 1.438\tLives: 4\tReward: 9.0\tEpisode Mean: 15.3\n",
+      "2399:1184154\tQ-min: 0.059\tQ-max: 0.106\tLives: 3\tReward: 9.0\tEpisode Mean: 15.3\n",
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+      "2399:1184443\tQ-min: 1.237\tQ-max: 1.543\tLives: 2\tReward: 14.0\tEpisode Mean: 15.3\n",
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+      "2399:1184508\tQ-min: 1.256\tQ-max: 1.506\tLives: 2\tReward: 16.0\tEpisode Mean: 15.3\n",
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+      "2399:1184761\tQ-min: 0.093\tQ-max: 0.130\tLives: 1\tReward: 20.0\tEpisode Mean: 15.3\n",
+      "2399:1184804\tQ-min: 1.293\tQ-max: 1.466\tLives: 1\tReward: 21.0\tEpisode Mean: 15.3\n",
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+      "2399:1184908\tQ-min: 0.064\tQ-max: 0.101\tLives: 0\tReward: 22.0\tEpisode Mean: 16.1\n",
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+      "2400:1185359\tQ-min: 0.051\tQ-max: 0.103\tLives: 2\tReward: 9.0\tEpisode Mean: 16.1\n",
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+      "2401:1186129\tQ-min: 1.297\tQ-max: 1.440\tLives: 4\tReward: 6.0\tEpisode Mean: 16.0\n",
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+      "2401:1186353\tQ-min: 1.269\tQ-max: 1.516\tLives: 3\tReward: 11.0\tEpisode Mean: 16.0\n",
+      "2401:1186389\tQ-min: 1.263\tQ-max: 1.532\tLives: 3\tReward: 12.0\tEpisode Mean: 16.0\n",
+      "2401:1186422\tQ-min: 1.207\tQ-max: 1.555\tLives: 3\tReward: 13.0\tEpisode Mean: 16.0\n",
+      "2401:1186459\tQ-min: 0.957\tQ-max: 1.438\tLives: 3\tReward: 17.0\tEpisode Mean: 16.0\n",
+      "2401:1186480\tQ-min: 0.075\tQ-max: 0.127\tLives: 2\tReward: 17.0\tEpisode Mean: 16.0\n",
+      "2401:1186526\tQ-min: 1.250\tQ-max: 1.473\tLives: 2\tReward: 18.0\tEpisode Mean: 16.0\n",
+      "2401:1186575\tQ-min: 1.282\tQ-max: 1.470\tLives: 2\tReward: 19.0\tEpisode Mean: 16.0\n",
+      "2401:1186639\tQ-min: 1.294\tQ-max: 1.447\tLives: 2\tReward: 20.0\tEpisode Mean: 16.0\n",
+      "2401:1186687\tQ-min: 1.198\tQ-max: 1.521\tLives: 2\tReward: 21.0\tEpisode Mean: 16.0\n",
+      "2401:1186708\tQ-min: 0.154\tQ-max: 0.162\tLives: 1\tReward: 21.0\tEpisode Mean: 16.0\n",
+      "2401:1186755\tQ-min: 1.063\tQ-max: 1.300\tLives: 1\tReward: 25.0\tEpisode Mean: 16.0\n",
+      "2401:1186775\tQ-min: 1.240\tQ-max: 1.547\tLives: 1\tReward: 26.0\tEpisode Mean: 16.0\n",
+      "2401:1186793\tQ-min: 1.224\tQ-max: 1.590\tLives: 1\tReward: 27.0\tEpisode Mean: 16.0\n",
+      "2401:1186813\tQ-min: 1.244\tQ-max: 1.535\tLives: 1\tReward: 31.0\tEpisode Mean: 16.0\n",
+      "2401:1186829\tQ-min: 0.159\tQ-max: 0.205\tLives: 0\tReward: 31.0\tEpisode Mean: 17.5\n",
+      "2402:1186872\tQ-min: 1.263\tQ-max: 1.443\tLives: 5\tReward: 1.0\tEpisode Mean: 17.5\n",
+      "2402:1186901\tQ-min: 0.128\tQ-max: 0.151\tLives: 4\tReward: 1.0\tEpisode Mean: 17.5\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2402:1186944\tQ-min: 1.235\tQ-max: 1.504\tLives: 4\tReward: 2.0\tEpisode Mean: 17.5\n",
+      "2402:1186996\tQ-min: 1.205\tQ-max: 1.336\tLives: 4\tReward: 3.0\tEpisode Mean: 17.5\n",
+      "2402:1187056\tQ-min: 1.194\tQ-max: 1.407\tLives: 4\tReward: 4.0\tEpisode Mean: 17.5\n",
+      "2402:1187102\tQ-min: 1.261\tQ-max: 1.519\tLives: 4\tReward: 5.0\tEpisode Mean: 17.5\n",
+      "2402:1187123\tQ-min: 0.070\tQ-max: 0.106\tLives: 3\tReward: 5.0\tEpisode Mean: 17.5\n",
+      "2402:1187167\tQ-min: 1.223\tQ-max: 1.614\tLives: 3\tReward: 6.0\tEpisode Mean: 17.5\n",
+      "2402:1187224\tQ-min: 1.242\tQ-max: 1.474\tLives: 3\tReward: 7.0\tEpisode Mean: 17.5\n",
+      "2402:1187289\tQ-min: 1.250\tQ-max: 1.433\tLives: 3\tReward: 8.0\tEpisode Mean: 17.5\n",
+      "2402:1187332\tQ-min: 0.094\tQ-max: 0.128\tLives: 2\tReward: 8.0\tEpisode Mean: 17.5\n",
+      "2402:1187375\tQ-min: 1.150\tQ-max: 1.484\tLives: 2\tReward: 12.0\tEpisode Mean: 17.5\n",
+      "2402:1187434\tQ-min: 1.273\tQ-max: 1.372\tLives: 2\tReward: 13.0\tEpisode Mean: 17.5\n",
+      "2402:1187499\tQ-min: 1.260\tQ-max: 1.461\tLives: 2\tReward: 14.0\tEpisode Mean: 17.5\n",
+      "2402:1187547\tQ-min: 1.192\tQ-max: 1.566\tLives: 2\tReward: 15.0\tEpisode Mean: 17.5\n",
+      "2402:1187579\tQ-min: 1.320\tQ-max: 1.556\tLives: 2\tReward: 16.0\tEpisode Mean: 17.5\n",
+      "2402:1187614\tQ-min: 1.214\tQ-max: 1.656\tLives: 2\tReward: 20.0\tEpisode Mean: 17.5\n",
+      "2402:1187647\tQ-min: 1.267\tQ-max: 1.472\tLives: 2\tReward: 24.0\tEpisode Mean: 17.5\n",
+      "2402:1187661\tQ-min: 0.524\tQ-max: 0.869\tLives: 1\tReward: 24.0\tEpisode Mean: 17.5\n",
+      "2402:1187711\tQ-min: 1.238\tQ-max: 1.335\tLives: 1\tReward: 25.0\tEpisode Mean: 17.5\n",
+      "2402:1187771\tQ-min: 1.249\tQ-max: 1.385\tLives: 1\tReward: 26.0\tEpisode Mean: 17.5\n",
+      "2402:1187823\tQ-min: 1.298\tQ-max: 1.476\tLives: 1\tReward: 27.0\tEpisode Mean: 17.5\n",
+      "2402:1187860\tQ-min: 1.298\tQ-max: 1.571\tLives: 1\tReward: 28.0\tEpisode Mean: 17.5\n",
+      "2402:1187881\tQ-min: 0.159\tQ-max: 0.183\tLives: 0\tReward: 28.0\tEpisode Mean: 18.5\n",
+      "2403:1187924\tQ-min: 1.251\tQ-max: 1.388\tLives: 5\tReward: 1.0\tEpisode Mean: 18.5\n",
+      "2403:1187964\tQ-min: 1.228\tQ-max: 1.512\tLives: 5\tReward: 2.0\tEpisode Mean: 18.5\n",
+      "2403:1188012\tQ-min: 1.254\tQ-max: 1.507\tLives: 5\tReward: 3.0\tEpisode Mean: 18.5\n",
+      "2403:1188059\tQ-min: 1.289\tQ-max: 1.539\tLives: 5\tReward: 4.0\tEpisode Mean: 18.5\n",
+      "2403:1188092\tQ-min: 1.267\tQ-max: 1.483\tLives: 5\tReward: 5.0\tEpisode Mean: 18.5\n",
+      "2403:1188120\tQ-min: 1.255\tQ-max: 1.484\tLives: 5\tReward: 6.0\tEpisode Mean: 18.5\n",
+      "2403:1188153\tQ-min: 1.261\tQ-max: 1.420\tLives: 5\tReward: 7.0\tEpisode Mean: 18.5\n",
+      "2403:1188204\tQ-min: 1.278\tQ-max: 1.377\tLives: 5\tReward: 8.0\tEpisode Mean: 18.5\n",
+      "2403:1188247\tQ-min: 0.098\tQ-max: 0.134\tLives: 4\tReward: 8.0\tEpisode Mean: 18.5\n",
+      "2403:1188300\tQ-min: 1.242\tQ-max: 1.317\tLives: 4\tReward: 9.0\tEpisode Mean: 18.5\n",
+      "2403:1188363\tQ-min: 1.229\tQ-max: 1.466\tLives: 4\tReward: 10.0\tEpisode Mean: 18.5\n",
+      "2403:1188417\tQ-min: 1.280\tQ-max: 1.528\tLives: 4\tReward: 11.0\tEpisode Mean: 18.5\n",
+      "2403:1188451\tQ-min: 1.322\tQ-max: 1.605\tLives: 4\tReward: 12.0\tEpisode Mean: 18.5\n",
+      "2403:1188483\tQ-min: 1.267\tQ-max: 1.472\tLives: 4\tReward: 13.0\tEpisode Mean: 18.5\n",
+      "2403:1188514\tQ-min: 1.246\tQ-max: 1.691\tLives: 4\tReward: 17.0\tEpisode Mean: 18.5\n",
+      "2403:1188538\tQ-min: 0.108\tQ-max: 0.133\tLives: 3\tReward: 17.0\tEpisode Mean: 18.5\n",
+      "2403:1188582\tQ-min: 1.244\tQ-max: 1.586\tLives: 3\tReward: 18.0\tEpisode Mean: 18.5\n",
+      "2403:1188636\tQ-min: 1.255\tQ-max: 1.427\tLives: 3\tReward: 19.0\tEpisode Mean: 18.5\n",
+      "2403:1188689\tQ-min: 1.264\tQ-max: 1.449\tLives: 3\tReward: 20.0\tEpisode Mean: 18.5\n",
+      "2403:1188726\tQ-min: 1.244\tQ-max: 1.492\tLives: 3\tReward: 21.0\tEpisode Mean: 18.5\n",
+      "2403:1188745\tQ-min: 0.189\tQ-max: 0.214\tLives: 2\tReward: 21.0\tEpisode Mean: 18.5\n",
+      "2403:1188793\tQ-min: 1.282\tQ-max: 1.605\tLives: 2\tReward: 22.0\tEpisode Mean: 18.5\n",
+      "2403:1188836\tQ-min: 1.263\tQ-max: 1.537\tLives: 2\tReward: 23.0\tEpisode Mean: 18.5\n",
+      "2403:1188889\tQ-min: 1.268\tQ-max: 1.533\tLives: 2\tReward: 24.0\tEpisode Mean: 18.5\n",
+      "2403:1188940\tQ-min: 1.244\tQ-max: 1.527\tLives: 2\tReward: 25.0\tEpisode Mean: 18.5\n",
+      "2403:1188976\tQ-min: 1.259\tQ-max: 1.581\tLives: 2\tReward: 29.0\tEpisode Mean: 18.5\n",
+      "2403:1189000\tQ-min: 0.055\tQ-max: 0.100\tLives: 1\tReward: 29.0\tEpisode Mean: 18.5\n",
+      "2403:1189056\tQ-min: 1.264\tQ-max: 1.346\tLives: 1\tReward: 30.0\tEpisode Mean: 18.5\n",
+      "2403:1189122\tQ-min: 1.162\tQ-max: 1.454\tLives: 1\tReward: 31.0\tEpisode Mean: 18.5\n",
+      "2403:1189180\tQ-min: 1.266\tQ-max: 1.524\tLives: 1\tReward: 32.0\tEpisode Mean: 18.5\n",
+      "2403:1189220\tQ-min: 1.201\tQ-max: 1.524\tLives: 1\tReward: 33.0\tEpisode Mean: 18.5\n",
+      "2403:1189241\tQ-min: 0.043\tQ-max: 0.098\tLives: 0\tReward: 33.0\tEpisode Mean: 19.7\n",
+      "2404:1189285\tQ-min: 1.241\tQ-max: 1.408\tLives: 5\tReward: 1.0\tEpisode Mean: 19.7\n",
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+      "2404:1189399\tQ-min: 1.247\tQ-max: 1.417\tLives: 5\tReward: 3.0\tEpisode Mean: 19.7\n",
+      "2404:1189445\tQ-min: 0.096\tQ-max: 0.131\tLives: 4\tReward: 3.0\tEpisode Mean: 19.7\n",
+      "2404:1189498\tQ-min: 1.243\tQ-max: 1.358\tLives: 4\tReward: 4.0\tEpisode Mean: 19.7\n",
+      "2404:1189562\tQ-min: 1.243\tQ-max: 1.428\tLives: 4\tReward: 5.0\tEpisode Mean: 19.7\n",
+      "2404:1189612\tQ-min: 1.309\tQ-max: 1.489\tLives: 4\tReward: 6.0\tEpisode Mean: 19.7\n",
+      "2404:1189652\tQ-min: 1.249\tQ-max: 1.435\tLives: 4\tReward: 7.0\tEpisode Mean: 19.7\n",
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+      "2404:1189794\tQ-min: 1.203\tQ-max: 1.450\tLives: 4\tReward: 11.0\tEpisode Mean: 19.7\n",
+      "2404:1189834\tQ-min: 0.096\tQ-max: 0.126\tLives: 3\tReward: 11.0\tEpisode Mean: 19.7\n",
+      "2404:1189891\tQ-min: 1.218\tQ-max: 1.304\tLives: 3\tReward: 12.0\tEpisode Mean: 19.7\n",
+      "2404:1189957\tQ-min: 1.205\tQ-max: 1.436\tLives: 3\tReward: 13.0\tEpisode Mean: 19.7\n",
+      "2404:1190008\tQ-min: 1.242\tQ-max: 1.529\tLives: 3\tReward: 14.0\tEpisode Mean: 19.7\n",
+      "2404:1190047\tQ-min: 1.296\tQ-max: 1.560\tLives: 3\tReward: 15.0\tEpisode Mean: 19.7\n",
+      "2404:1190082\tQ-min: 1.295\tQ-max: 1.465\tLives: 3\tReward: 16.0\tEpisode Mean: 19.7\n",
+      "2404:1190103\tQ-min: 0.097\tQ-max: 0.141\tLives: 2\tReward: 16.0\tEpisode Mean: 19.7\n",
+      "2404:1190149\tQ-min: 1.076\tQ-max: 1.388\tLives: 2\tReward: 17.0\tEpisode Mean: 19.7\n",
+      "2404:1190178\tQ-min: 0.086\tQ-max: 0.133\tLives: 1\tReward: 17.0\tEpisode Mean: 19.7\n",
+      "2404:1190224\tQ-min: 1.234\tQ-max: 1.558\tLives: 1\tReward: 18.0\tEpisode Mean: 19.7\n",
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+      "2404:1190338\tQ-min: 1.294\tQ-max: 1.477\tLives: 1\tReward: 20.0\tEpisode Mean: 19.7\n",
+      "2404:1190366\tQ-min: 0.037\tQ-max: 0.102\tLives: 0\tReward: 20.0\tEpisode Mean: 19.7\n",
+      "2405:1190413\tQ-min: 1.260\tQ-max: 1.473\tLives: 5\tReward: 1.0\tEpisode Mean: 19.7\n",
+      "2405:1190454\tQ-min: 1.264\tQ-max: 1.509\tLives: 5\tReward: 2.0\tEpisode Mean: 19.7\n",
+      "2405:1190506\tQ-min: 1.279\tQ-max: 1.414\tLives: 5\tReward: 3.0\tEpisode Mean: 19.7\n",
+      "2405:1190554\tQ-min: 1.290\tQ-max: 1.479\tLives: 5\tReward: 4.0\tEpisode Mean: 19.7\n",
+      "2405:1190574\tQ-min: 0.036\tQ-max: 0.103\tLives: 4\tReward: 4.0\tEpisode Mean: 19.7\n",
+      "2405:1190617\tQ-min: 1.251\tQ-max: 1.441\tLives: 4\tReward: 5.0\tEpisode Mean: 19.7\n",
+      "2405:1190661\tQ-min: 1.250\tQ-max: 1.502\tLives: 4\tReward: 6.0\tEpisode Mean: 19.7\n",
+      "2405:1190714\tQ-min: 1.227\tQ-max: 1.342\tLives: 4\tReward: 7.0\tEpisode Mean: 19.7\n",
+      "2405:1190760\tQ-min: 1.241\tQ-max: 1.505\tLives: 4\tReward: 8.0\tEpisode Mean: 19.7\n",
+      "2405:1190793\tQ-min: 1.274\tQ-max: 1.556\tLives: 4\tReward: 9.0\tEpisode Mean: 19.7\n",
+      "2405:1190815\tQ-min: 0.104\tQ-max: 0.140\tLives: 3\tReward: 9.0\tEpisode Mean: 19.7\n",
+      "2405:1190873\tQ-min: 1.258\tQ-max: 1.324\tLives: 3\tReward: 10.0\tEpisode Mean: 19.7\n",
+      "2405:1190938\tQ-min: 1.295\tQ-max: 1.392\tLives: 3\tReward: 11.0\tEpisode Mean: 19.7\n",
+      "2405:1191010\tQ-min: 1.018\tQ-max: 1.427\tLives: 3\tReward: 15.0\tEpisode Mean: 19.7\n",
+      "2405:1191053\tQ-min: 0.102\tQ-max: 0.122\tLives: 2\tReward: 15.0\tEpisode Mean: 19.7\n",
+      "2405:1191106\tQ-min: 1.216\tQ-max: 1.372\tLives: 2\tReward: 16.0\tEpisode Mean: 19.7\n",
+      "2405:1191177\tQ-min: 1.036\tQ-max: 1.113\tLives: 2\tReward: 17.0\tEpisode Mean: 19.7\n",
+      "2405:1191245\tQ-min: 1.231\tQ-max: 1.382\tLives: 2\tReward: 18.0\tEpisode Mean: 19.7\n",
+      "2405:1191295\tQ-min: 1.268\tQ-max: 1.527\tLives: 2\tReward: 19.0\tEpisode Mean: 19.7\n",
+      "2405:1191325\tQ-min: 1.234\tQ-max: 1.527\tLives: 2\tReward: 20.0\tEpisode Mean: 19.7\n",
+      "2405:1191357\tQ-min: 1.253\tQ-max: 1.586\tLives: 2\tReward: 21.0\tEpisode Mean: 19.7\n",
+      "2405:1191381\tQ-min: 0.038\tQ-max: 0.097\tLives: 1\tReward: 21.0\tEpisode Mean: 19.7\n",
+      "2405:1191429\tQ-min: 1.029\tQ-max: 1.394\tLives: 1\tReward: 25.0\tEpisode Mean: 19.7\n",
+      "2405:1191475\tQ-min: 1.266\tQ-max: 1.366\tLives: 1\tReward: 26.0\tEpisode Mean: 19.7\n",
+      "2405:1191503\tQ-min: 0.081\tQ-max: 0.112\tLives: 0\tReward: 26.0\tEpisode Mean: 20.1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2406:1191546\tQ-min: 1.255\tQ-max: 1.417\tLives: 5\tReward: 1.0\tEpisode Mean: 20.1\n",
+      "2406:1191594\tQ-min: 1.221\tQ-max: 1.351\tLives: 5\tReward: 2.0\tEpisode Mean: 20.1\n",
+      "2406:1191643\tQ-min: 1.213\tQ-max: 1.629\tLives: 5\tReward: 3.0\tEpisode Mean: 20.1\n",
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+      "2406:1191911\tQ-min: 0.034\tQ-max: 0.094\tLives: 3\tReward: 7.0\tEpisode Mean: 20.1\n",
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+      "2406:1192036\tQ-min: 1.232\tQ-max: 1.392\tLives: 3\tReward: 9.0\tEpisode Mean: 20.1\n",
+      "2406:1192088\tQ-min: 1.297\tQ-max: 1.460\tLives: 3\tReward: 10.0\tEpisode Mean: 20.1\n",
+      "2406:1192122\tQ-min: 1.253\tQ-max: 1.557\tLives: 3\tReward: 11.0\tEpisode Mean: 20.1\n",
+      "2406:1192156\tQ-min: 1.289\tQ-max: 1.533\tLives: 3\tReward: 15.0\tEpisode Mean: 20.1\n",
+      "2406:1192179\tQ-min: 0.109\tQ-max: 0.127\tLives: 2\tReward: 15.0\tEpisode Mean: 20.1\n",
+      "2406:1192234\tQ-min: 1.185\tQ-max: 1.409\tLives: 2\tReward: 16.0\tEpisode Mean: 20.1\n",
+      "2406:1192281\tQ-min: 0.065\tQ-max: 0.104\tLives: 1\tReward: 16.0\tEpisode Mean: 20.1\n",
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+      "2406:1192385\tQ-min: 0.073\tQ-max: 0.121\tLives: 0\tReward: 20.0\tEpisode Mean: 20.1\n",
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+      "2407:1192703\tQ-min: 1.314\tQ-max: 1.333\tLives: 4\tReward: 6.0\tEpisode Mean: 20.1\n",
+      "2407:1192746\tQ-min: 0.080\tQ-max: 0.110\tLives: 3\tReward: 6.0\tEpisode Mean: 20.1\n",
+      "2407:1192788\tQ-min: 1.222\tQ-max: 1.457\tLives: 3\tReward: 7.0\tEpisode Mean: 20.1\n",
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+      "2407:1192999\tQ-min: 0.097\tQ-max: 0.130\tLives: 1\tReward: 10.0\tEpisode Mean: 20.1\n",
+      "2407:1193044\tQ-min: 1.246\tQ-max: 1.518\tLives: 1\tReward: 11.0\tEpisode Mean: 20.1\n",
+      "2407:1193087\tQ-min: 1.291\tQ-max: 1.537\tLives: 1\tReward: 12.0\tEpisode Mean: 20.1\n",
+      "2407:1193138\tQ-min: 1.274\tQ-max: 1.322\tLives: 1\tReward: 13.0\tEpisode Mean: 20.1\n",
+      "2407:1193185\tQ-min: 1.229\tQ-max: 1.434\tLives: 1\tReward: 14.0\tEpisode Mean: 20.1\n",
+      "2407:1193218\tQ-min: 1.262\tQ-max: 1.493\tLives: 1\tReward: 15.0\tEpisode Mean: 20.1\n",
+      "2407:1193249\tQ-min: 1.274\tQ-max: 1.565\tLives: 1\tReward: 16.0\tEpisode Mean: 20.1\n",
+      "2407:1193281\tQ-min: 1.281\tQ-max: 1.457\tLives: 1\tReward: 17.0\tEpisode Mean: 20.1\n",
+      "2407:1193332\tQ-min: 1.266\tQ-max: 1.492\tLives: 1\tReward: 18.0\tEpisode Mean: 20.1\n",
+      "2407:1193376\tQ-min: 0.067\tQ-max: 0.116\tLives: 0\tReward: 18.0\tEpisode Mean: 20.0\n",
+      "2408:1193431\tQ-min: 1.240\tQ-max: 1.376\tLives: 5\tReward: 1.0\tEpisode Mean: 20.0\n",
+      "2408:1193480\tQ-min: 1.243\tQ-max: 1.465\tLives: 5\tReward: 2.0\tEpisode Mean: 20.0\n",
+      "2408:1193522\tQ-min: 1.224\tQ-max: 1.458\tLives: 5\tReward: 3.0\tEpisode Mean: 20.0\n",
+      "2408:1193558\tQ-min: 1.319\tQ-max: 1.640\tLives: 5\tReward: 4.0\tEpisode Mean: 20.0\n",
+      "2408:1193591\tQ-min: 1.229\tQ-max: 1.469\tLives: 5\tReward: 5.0\tEpisode Mean: 20.0\n",
+      "2408:1193622\tQ-min: 1.300\tQ-max: 1.513\tLives: 5\tReward: 6.0\tEpisode Mean: 20.0\n",
+      "2408:1193643\tQ-min: 0.079\tQ-max: 0.122\tLives: 4\tReward: 6.0\tEpisode Mean: 20.0\n",
+      "2408:1193698\tQ-min: 1.253\tQ-max: 1.480\tLives: 4\tReward: 7.0\tEpisode Mean: 20.0\n",
+      "2408:1193763\tQ-min: 1.184\tQ-max: 1.349\tLives: 4\tReward: 8.0\tEpisode Mean: 20.0\n",
+      "2408:1193825\tQ-min: 1.256\tQ-max: 1.328\tLives: 4\tReward: 9.0\tEpisode Mean: 20.0\n",
+      "2408:1193872\tQ-min: 1.325\tQ-max: 1.534\tLives: 4\tReward: 10.0\tEpisode Mean: 20.0\n",
+      "2408:1193904\tQ-min: 1.266\tQ-max: 1.451\tLives: 4\tReward: 11.0\tEpisode Mean: 20.0\n",
+      "2408:1193938\tQ-min: 1.245\tQ-max: 1.511\tLives: 4\tReward: 12.0\tEpisode Mean: 20.0\n",
+      "2408:1193971\tQ-min: 1.229\tQ-max: 1.489\tLives: 4\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2408:1194020\tQ-min: 1.239\tQ-max: 1.492\tLives: 4\tReward: 14.0\tEpisode Mean: 20.0\n",
+      "2408:1194061\tQ-min: 0.056\tQ-max: 0.099\tLives: 3\tReward: 14.0\tEpisode Mean: 20.0\n",
+      "2408:1194117\tQ-min: 1.193\tQ-max: 1.449\tLives: 3\tReward: 15.0\tEpisode Mean: 20.0\n",
+      "2408:1194186\tQ-min: 1.112\tQ-max: 1.377\tLives: 3\tReward: 19.0\tEpisode Mean: 20.0\n",
+      "2408:1194259\tQ-min: 1.033\tQ-max: 1.440\tLives: 3\tReward: 23.0\tEpisode Mean: 20.0\n",
+      "2408:1194273\tQ-min: 0.159\tQ-max: 0.206\tLives: 2\tReward: 23.0\tEpisode Mean: 20.0\n",
+      "2408:1194327\tQ-min: 1.249\tQ-max: 1.323\tLives: 2\tReward: 24.0\tEpisode Mean: 20.0\n",
+      "2408:1194382\tQ-min: 1.245\tQ-max: 1.443\tLives: 2\tReward: 25.0\tEpisode Mean: 20.0\n",
+      "2408:1194407\tQ-min: 0.101\tQ-max: 0.135\tLives: 1\tReward: 25.0\tEpisode Mean: 20.0\n",
+      "2408:1194461\tQ-min: 1.227\tQ-max: 1.444\tLives: 1\tReward: 26.0\tEpisode Mean: 20.0\n",
+      "2408:1194529\tQ-min: 1.219\tQ-max: 1.417\tLives: 1\tReward: 27.0\tEpisode Mean: 20.0\n",
+      "2408:1194574\tQ-min: 0.089\tQ-max: 0.116\tLives: 0\tReward: 27.0\tEpisode Mean: 20.4\n",
+      "2409:1194630\tQ-min: 1.216\tQ-max: 1.426\tLives: 5\tReward: 1.0\tEpisode Mean: 20.4\n",
+      "2409:1194673\tQ-min: 0.081\tQ-max: 0.123\tLives: 4\tReward: 1.0\tEpisode Mean: 20.4\n",
+      "2409:1194727\tQ-min: 1.214\tQ-max: 1.409\tLives: 4\tReward: 2.0\tEpisode Mean: 20.4\n",
+      "2409:1194767\tQ-min: 0.098\tQ-max: 0.134\tLives: 3\tReward: 2.0\tEpisode Mean: 20.4\n",
+      "2409:1194823\tQ-min: 1.266\tQ-max: 1.411\tLives: 3\tReward: 3.0\tEpisode Mean: 20.4\n",
+      "2409:1194878\tQ-min: 1.292\tQ-max: 1.494\tLives: 3\tReward: 4.0\tEpisode Mean: 20.4\n",
+      "2409:1194919\tQ-min: 1.288\tQ-max: 1.457\tLives: 3\tReward: 5.0\tEpisode Mean: 20.4\n",
+      "2409:1194955\tQ-min: 1.329\tQ-max: 1.503\tLives: 3\tReward: 6.0\tEpisode Mean: 20.4\n",
+      "2409:1194985\tQ-min: 1.274\tQ-max: 1.487\tLives: 3\tReward: 7.0\tEpisode Mean: 20.4\n",
+      "2409:1195018\tQ-min: 1.233\tQ-max: 1.435\tLives: 3\tReward: 8.0\tEpisode Mean: 20.4\n",
+      "2409:1195052\tQ-min: 1.246\tQ-max: 1.429\tLives: 3\tReward: 9.0\tEpisode Mean: 20.4\n",
+      "2409:1195106\tQ-min: 1.249\tQ-max: 1.370\tLives: 3\tReward: 10.0\tEpisode Mean: 20.4\n",
+      "2409:1195148\tQ-min: 0.086\tQ-max: 0.115\tLives: 2\tReward: 10.0\tEpisode Mean: 20.4\n",
+      "2409:1195193\tQ-min: 1.226\tQ-max: 1.472\tLives: 2\tReward: 11.0\tEpisode Mean: 20.4\n",
+      "2409:1195221\tQ-min: 0.087\tQ-max: 0.127\tLives: 1\tReward: 11.0\tEpisode Mean: 20.4\n",
+      "2409:1195264\tQ-min: 1.244\tQ-max: 1.347\tLives: 1\tReward: 12.0\tEpisode Mean: 20.4\n",
+      "2409:1195317\tQ-min: 1.241\tQ-max: 1.434\tLives: 1\tReward: 13.0\tEpisode Mean: 20.4\n",
+      "2409:1195360\tQ-min: 0.105\tQ-max: 0.136\tLives: 0\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2410:1195404\tQ-min: 1.236\tQ-max: 1.407\tLives: 5\tReward: 1.0\tEpisode Mean: 20.0\n",
+      "2410:1195457\tQ-min: 1.244\tQ-max: 1.450\tLives: 5\tReward: 2.0\tEpisode Mean: 20.0\n",
+      "2410:1195502\tQ-min: 0.103\tQ-max: 0.139\tLives: 4\tReward: 2.0\tEpisode Mean: 20.0\n",
+      "2410:1195557\tQ-min: 1.215\tQ-max: 1.412\tLives: 4\tReward: 3.0\tEpisode Mean: 20.0\n",
+      "2410:1195607\tQ-min: 1.234\tQ-max: 1.465\tLives: 4\tReward: 4.0\tEpisode Mean: 20.0\n",
+      "2410:1195651\tQ-min: 1.269\tQ-max: 1.479\tLives: 4\tReward: 5.0\tEpisode Mean: 20.0\n",
+      "2410:1195688\tQ-min: 1.267\tQ-max: 1.544\tLives: 4\tReward: 6.0\tEpisode Mean: 20.0\n",
+      "2410:1195710\tQ-min: 0.129\tQ-max: 0.154\tLives: 3\tReward: 6.0\tEpisode Mean: 20.0\n",
+      "2410:1195753\tQ-min: 1.237\tQ-max: 1.478\tLives: 3\tReward: 7.0\tEpisode Mean: 20.0\n",
+      "2410:1195803\tQ-min: 1.298\tQ-max: 1.509\tLives: 3\tReward: 8.0\tEpisode Mean: 20.0\n",
+      "2410:1195844\tQ-min: 0.102\tQ-max: 0.125\tLives: 2\tReward: 8.0\tEpisode Mean: 20.0\n",
+      "2410:1195891\tQ-min: 1.193\tQ-max: 1.486\tLives: 2\tReward: 9.0\tEpisode Mean: 20.0\n",
+      "2410:1195937\tQ-min: 1.239\tQ-max: 1.537\tLives: 2\tReward: 10.0\tEpisode Mean: 20.0\n",
+      "2410:1195979\tQ-min: 1.264\tQ-max: 1.491\tLives: 2\tReward: 11.0\tEpisode Mean: 20.0\n",
+      "2410:1196019\tQ-min: 1.295\tQ-max: 1.469\tLives: 2\tReward: 12.0\tEpisode Mean: 20.0\n",
+      "2410:1196049\tQ-min: 1.284\tQ-max: 1.577\tLives: 2\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2410:1196071\tQ-min: 0.071\tQ-max: 0.117\tLives: 1\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2410:1196125\tQ-min: 1.232\tQ-max: 1.368\tLives: 1\tReward: 14.0\tEpisode Mean: 20.0\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2410:1196191\tQ-min: 1.271\tQ-max: 1.507\tLives: 1\tReward: 15.0\tEpisode Mean: 20.0\n",
+      "2410:1196245\tQ-min: 1.307\tQ-max: 1.438\tLives: 1\tReward: 16.0\tEpisode Mean: 20.0\n",
+      "2410:1196273\tQ-min: 0.032\tQ-max: 0.089\tLives: 0\tReward: 16.0\tEpisode Mean: 19.8\n",
+      "2411:1196317\tQ-min: 1.245\tQ-max: 1.454\tLives: 5\tReward: 1.0\tEpisode Mean: 19.8\n",
+      "2411:1196369\tQ-min: 1.232\tQ-max: 1.374\tLives: 5\tReward: 2.0\tEpisode Mean: 19.8\n",
+      "2411:1196408\tQ-min: 0.145\tQ-max: 0.168\tLives: 4\tReward: 2.0\tEpisode Mean: 19.8\n",
+      "2411:1196464\tQ-min: 1.254\tQ-max: 1.314\tLives: 4\tReward: 3.0\tEpisode Mean: 19.8\n",
+      "2411:1196514\tQ-min: 1.190\tQ-max: 1.468\tLives: 4\tReward: 4.0\tEpisode Mean: 19.8\n",
+      "2411:1196556\tQ-min: 1.284\tQ-max: 1.550\tLives: 4\tReward: 5.0\tEpisode Mean: 19.8\n",
+      "2411:1196585\tQ-min: 0.108\tQ-max: 0.136\tLives: 3\tReward: 5.0\tEpisode Mean: 19.8\n",
+      "2411:1196639\tQ-min: 1.205\tQ-max: 1.403\tLives: 3\tReward: 6.0\tEpisode Mean: 19.8\n",
+      "2411:1196700\tQ-min: 1.224\tQ-max: 1.469\tLives: 3\tReward: 7.0\tEpisode Mean: 19.8\n",
+      "2411:1196764\tQ-min: 1.271\tQ-max: 1.385\tLives: 3\tReward: 8.0\tEpisode Mean: 19.8\n",
+      "2411:1196805\tQ-min: 0.100\tQ-max: 0.134\tLives: 2\tReward: 8.0\tEpisode Mean: 19.8\n",
+      "2411:1196852\tQ-min: 1.264\tQ-max: 1.447\tLives: 2\tReward: 9.0\tEpisode Mean: 19.8\n",
+      "2411:1196903\tQ-min: 1.253\tQ-max: 1.481\tLives: 2\tReward: 10.0\tEpisode Mean: 19.8\n",
+      "2411:1196955\tQ-min: 1.273\tQ-max: 1.441\tLives: 2\tReward: 11.0\tEpisode Mean: 19.8\n",
+      "2411:1196992\tQ-min: 1.248\tQ-max: 1.503\tLives: 2\tReward: 12.0\tEpisode Mean: 19.8\n",
+      "2411:1197028\tQ-min: 1.216\tQ-max: 1.527\tLives: 2\tReward: 13.0\tEpisode Mean: 19.8\n",
+      "2411:1197049\tQ-min: 0.023\tQ-max: 0.093\tLives: 1\tReward: 13.0\tEpisode Mean: 19.8\n",
+      "2411:1197095\tQ-min: 1.258\tQ-max: 1.547\tLives: 1\tReward: 14.0\tEpisode Mean: 19.8\n",
+      "2411:1197149\tQ-min: 1.229\tQ-max: 1.329\tLives: 1\tReward: 15.0\tEpisode Mean: 19.8\n",
+      "2411:1197217\tQ-min: 1.291\tQ-max: 1.439\tLives: 1\tReward: 16.0\tEpisode Mean: 19.8\n",
+      "2411:1197269\tQ-min: 1.278\tQ-max: 1.517\tLives: 1\tReward: 20.0\tEpisode Mean: 19.8\n",
+      "2411:1197302\tQ-min: 1.298\tQ-max: 1.503\tLives: 1\tReward: 21.0\tEpisode Mean: 19.8\n",
+      "2411:1197324\tQ-min: 0.053\tQ-max: 0.109\tLives: 0\tReward: 21.0\tEpisode Mean: 19.9\n",
+      "2412:1197366\tQ-min: 1.262\tQ-max: 1.385\tLives: 5\tReward: 1.0\tEpisode Mean: 19.9\n",
+      "2412:1197419\tQ-min: 1.206\tQ-max: 1.388\tLives: 5\tReward: 2.0\tEpisode Mean: 19.9\n",
+      "2412:1197471\tQ-min: 1.251\tQ-max: 1.485\tLives: 5\tReward: 3.0\tEpisode Mean: 19.9\n",
+      "2412:1197512\tQ-min: 1.267\tQ-max: 1.497\tLives: 5\tReward: 4.0\tEpisode Mean: 19.9\n",
+      "2412:1197544\tQ-min: 1.301\tQ-max: 1.463\tLives: 5\tReward: 5.0\tEpisode Mean: 19.9\n",
+      "2412:1197580\tQ-min: 1.247\tQ-max: 1.528\tLives: 5\tReward: 6.0\tEpisode Mean: 19.9\n",
+      "2412:1197613\tQ-min: 1.312\tQ-max: 1.677\tLives: 5\tReward: 7.0\tEpisode Mean: 19.9\n",
+      "2412:1197658\tQ-min: 1.264\tQ-max: 1.436\tLives: 5\tReward: 8.0\tEpisode Mean: 19.9\n",
+      "2412:1197726\tQ-min: 1.278\tQ-max: 1.484\tLives: 5\tReward: 9.0\tEpisode Mean: 19.9\n",
+      "2412:1197792\tQ-min: 1.245\tQ-max: 1.387\tLives: 5\tReward: 10.0\tEpisode Mean: 19.9\n",
+      "2412:1197860\tQ-min: 1.210\tQ-max: 1.525\tLives: 5\tReward: 11.0\tEpisode Mean: 19.9\n",
+      "2412:1197904\tQ-min: 1.272\tQ-max: 1.403\tLives: 5\tReward: 12.0\tEpisode Mean: 19.9\n",
+      "2412:1197924\tQ-min: 0.043\tQ-max: 0.098\tLives: 4\tReward: 12.0\tEpisode Mean: 19.9\n",
+      "2412:1197978\tQ-min: 1.193\tQ-max: 1.358\tLives: 4\tReward: 13.0\tEpisode Mean: 19.9\n",
+      "2412:1198044\tQ-min: 1.242\tQ-max: 1.429\tLives: 4\tReward: 14.0\tEpisode Mean: 19.9\n",
+      "2412:1198102\tQ-min: 1.279\tQ-max: 1.487\tLives: 4\tReward: 15.0\tEpisode Mean: 19.9\n",
+      "2412:1198135\tQ-min: 1.302\tQ-max: 1.495\tLives: 4\tReward: 16.0\tEpisode Mean: 19.9\n",
+      "2412:1198156\tQ-min: 0.057\tQ-max: 0.102\tLives: 3\tReward: 16.0\tEpisode Mean: 19.9\n",
+      "2412:1198199\tQ-min: 1.283\tQ-max: 1.472\tLives: 3\tReward: 17.0\tEpisode Mean: 19.9\n",
+      "2412:1198253\tQ-min: 1.226\tQ-max: 1.547\tLives: 3\tReward: 18.0\tEpisode Mean: 19.9\n",
+      "2412:1198317\tQ-min: 1.296\tQ-max: 1.547\tLives: 3\tReward: 19.0\tEpisode Mean: 19.9\n",
+      "2412:1198369\tQ-min: 1.259\tQ-max: 1.395\tLives: 3\tReward: 20.0\tEpisode Mean: 19.9\n",
+      "2412:1198389\tQ-min: 0.164\tQ-max: 0.192\tLives: 2\tReward: 20.0\tEpisode Mean: 19.9\n",
+      "2412:1198433\tQ-min: 1.258\tQ-max: 1.535\tLives: 2\tReward: 21.0\tEpisode Mean: 19.9\n",
+      "2412:1198479\tQ-min: 1.223\tQ-max: 1.540\tLives: 2\tReward: 25.0\tEpisode Mean: 19.9\n",
+      "2412:1198512\tQ-min: 0.082\tQ-max: 0.117\tLives: 1\tReward: 25.0\tEpisode Mean: 19.9\n",
+      "2412:1198560\tQ-min: 1.273\tQ-max: 1.512\tLives: 1\tReward: 26.0\tEpisode Mean: 19.9\n",
+      "2412:1198608\tQ-min: 1.235\tQ-max: 1.355\tLives: 1\tReward: 27.0\tEpisode Mean: 19.9\n",
+      "2412:1198674\tQ-min: 1.267\tQ-max: 1.486\tLives: 1\tReward: 28.0\tEpisode Mean: 19.9\n",
+      "2412:1198727\tQ-min: 0.515\tQ-max: 0.648\tLives: 1\tReward: 32.0\tEpisode Mean: 19.9\n",
+      "2412:1198763\tQ-min: 1.265\tQ-max: 1.527\tLives: 1\tReward: 36.0\tEpisode Mean: 19.9\n",
+      "2412:1198801\tQ-min: 1.131\tQ-max: 1.593\tLives: 1\tReward: 40.0\tEpisode Mean: 19.9\n",
+      "2412:1198817\tQ-min: 0.105\tQ-max: 0.142\tLives: 0\tReward: 40.0\tEpisode Mean: 20.8\n",
+      "2413:1198863\tQ-min: 1.258\tQ-max: 1.472\tLives: 5\tReward: 1.0\tEpisode Mean: 20.8\n",
+      "2413:1198914\tQ-min: 1.221\tQ-max: 1.476\tLives: 5\tReward: 2.0\tEpisode Mean: 20.8\n",
+      "2413:1198957\tQ-min: 0.108\tQ-max: 0.139\tLives: 4\tReward: 2.0\tEpisode Mean: 20.8\n",
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+      "2413:1199089\tQ-min: 0.021\tQ-max: 0.092\tLives: 3\tReward: 4.0\tEpisode Mean: 20.8\n",
+      "2413:1199131\tQ-min: 1.301\tQ-max: 1.497\tLives: 3\tReward: 5.0\tEpisode Mean: 20.8\n",
+      "2413:1199174\tQ-min: 1.251\tQ-max: 1.497\tLives: 3\tReward: 6.0\tEpisode Mean: 20.8\n",
+      "2413:1199227\tQ-min: 1.305\tQ-max: 1.513\tLives: 3\tReward: 7.0\tEpisode Mean: 20.8\n",
+      "2413:1199273\tQ-min: 1.203\tQ-max: 1.563\tLives: 3\tReward: 8.0\tEpisode Mean: 20.8\n",
+      "2413:1199306\tQ-min: 1.215\tQ-max: 1.508\tLives: 3\tReward: 9.0\tEpisode Mean: 20.8\n",
+      "2413:1199342\tQ-min: 1.305\tQ-max: 1.574\tLives: 3\tReward: 10.0\tEpisode Mean: 20.8\n",
+      "2413:1199363\tQ-min: 0.113\tQ-max: 0.143\tLives: 2\tReward: 10.0\tEpisode Mean: 20.8\n",
+      "2413:1199403\tQ-min: 1.262\tQ-max: 1.450\tLives: 2\tReward: 11.0\tEpisode Mean: 20.8\n",
+      "2413:1199446\tQ-min: 1.214\tQ-max: 1.509\tLives: 2\tReward: 12.0\tEpisode Mean: 20.8\n",
+      "2413:1199502\tQ-min: 1.320\tQ-max: 1.489\tLives: 2\tReward: 13.0\tEpisode Mean: 20.8\n",
+      "2413:1199552\tQ-min: 1.224\tQ-max: 1.480\tLives: 2\tReward: 17.0\tEpisode Mean: 20.8\n",
+      "2413:1199585\tQ-min: 1.245\tQ-max: 1.400\tLives: 2\tReward: 18.0\tEpisode Mean: 20.8\n",
+      "2413:1199606\tQ-min: 0.065\tQ-max: 0.106\tLives: 1\tReward: 18.0\tEpisode Mean: 20.8\n",
+      "2413:1199659\tQ-min: 1.203\tQ-max: 1.348\tLives: 1\tReward: 19.0\tEpisode Mean: 20.8\n",
+      "2413:1199723\tQ-min: 1.298\tQ-max: 1.356\tLives: 1\tReward: 20.0\tEpisode Mean: 20.8\n",
+      "2413:1199788\tQ-min: 1.246\tQ-max: 1.510\tLives: 1\tReward: 21.0\tEpisode Mean: 20.8\n",
+      "2413:1199839\tQ-min: 1.234\tQ-max: 1.533\tLives: 1\tReward: 22.0\tEpisode Mean: 20.8\n",
+      "2413:1199872\tQ-min: 1.224\tQ-max: 1.454\tLives: 1\tReward: 23.0\tEpisode Mean: 20.8\n",
+      "2413:1199901\tQ-min: 1.311\tQ-max: 1.505\tLives: 1\tReward: 24.0\tEpisode Mean: 20.8\n",
+      "2413:1199937\tQ-min: 1.275\tQ-max: 1.530\tLives: 1\tReward: 25.0\tEpisode Mean: 20.8\n",
+      "2413:1199982\tQ-min: 1.277\tQ-max: 1.504\tLives: 1\tReward: 26.0\tEpisode Mean: 20.8\n",
+      "2413:1200046\tQ-min: 1.304\tQ-max: 1.512\tLives: 1\tReward: 27.0\tEpisode Mean: 20.8\n",
+      "2413:1200091\tQ-min: 0.101\tQ-max: 0.130\tLives: 0\tReward: 27.0\tEpisode Mean: 21.1\n",
+      "2414:1200134\tQ-min: 1.229\tQ-max: 1.480\tLives: 5\tReward: 1.0\tEpisode Mean: 21.1\n",
+      "2414:1200161\tQ-min: 0.117\tQ-max: 0.145\tLives: 4\tReward: 1.0\tEpisode Mean: 21.1\n",
+      "2414:1200206\tQ-min: 1.249\tQ-max: 1.549\tLives: 4\tReward: 2.0\tEpisode Mean: 21.1\n",
+      "2414:1200233\tQ-min: 0.085\tQ-max: 0.131\tLives: 3\tReward: 2.0\tEpisode Mean: 21.1\n",
+      "2414:1200278\tQ-min: 1.198\tQ-max: 1.438\tLives: 3\tReward: 3.0\tEpisode Mean: 21.1\n",
+      "2414:1200308\tQ-min: 0.055\tQ-max: 0.104\tLives: 2\tReward: 3.0\tEpisode Mean: 21.1\n",
+      "2414:1200364\tQ-min: 1.229\tQ-max: 1.338\tLives: 2\tReward: 4.0\tEpisode Mean: 21.1\n",
+      "2414:1200427\tQ-min: 1.218\tQ-max: 1.375\tLives: 2\tReward: 5.0\tEpisode Mean: 21.1\n",
+      "2414:1200497\tQ-min: 1.253\tQ-max: 1.362\tLives: 2\tReward: 6.0\tEpisode Mean: 21.1\n",
+      "2414:1200542\tQ-min: 1.173\tQ-max: 1.653\tLives: 2\tReward: 7.0\tEpisode Mean: 21.1\n",
+      "2414:1200563\tQ-min: 0.019\tQ-max: 0.095\tLives: 1\tReward: 7.0\tEpisode Mean: 21.1\n",
+      "2414:1200608\tQ-min: 1.254\tQ-max: 1.446\tLives: 1\tReward: 8.0\tEpisode Mean: 21.1\n",
+      "2414:1200637\tQ-min: 0.049\tQ-max: 0.106\tLives: 0\tReward: 8.0\tEpisode Mean: 20.5\n",
+      "2415:1200679\tQ-min: 1.260\tQ-max: 1.373\tLives: 5\tReward: 1.0\tEpisode Mean: 20.5\n",
+      "2415:1200704\tQ-min: 0.125\tQ-max: 0.144\tLives: 4\tReward: 1.0\tEpisode Mean: 20.5\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2415:1200760\tQ-min: 1.242\tQ-max: 1.342\tLives: 4\tReward: 2.0\tEpisode Mean: 20.5\n",
+      "2415:1200812\tQ-min: 1.206\tQ-max: 1.542\tLives: 4\tReward: 3.0\tEpisode Mean: 20.5\n",
+      "2415:1200839\tQ-min: 0.098\tQ-max: 0.135\tLives: 3\tReward: 3.0\tEpisode Mean: 20.5\n",
+      "2415:1200892\tQ-min: 1.232\tQ-max: 1.352\tLives: 3\tReward: 4.0\tEpisode Mean: 20.5\n",
+      "2415:1200958\tQ-min: 1.225\tQ-max: 1.471\tLives: 3\tReward: 5.0\tEpisode Mean: 20.5\n",
+      "2415:1201015\tQ-min: 1.309\tQ-max: 1.508\tLives: 3\tReward: 6.0\tEpisode Mean: 20.5\n",
+      "2415:1201042\tQ-min: 0.072\tQ-max: 0.120\tLives: 2\tReward: 6.0\tEpisode Mean: 20.5\n",
+      "2415:1201086\tQ-min: 1.277\tQ-max: 1.517\tLives: 2\tReward: 7.0\tEpisode Mean: 20.5\n",
+      "2415:1201141\tQ-min: 1.229\tQ-max: 1.447\tLives: 2\tReward: 8.0\tEpisode Mean: 20.5\n",
+      "2415:1201194\tQ-min: 1.259\tQ-max: 1.575\tLives: 2\tReward: 12.0\tEpisode Mean: 20.5\n",
+      "2415:1201235\tQ-min: 1.259\tQ-max: 1.525\tLives: 2\tReward: 13.0\tEpisode Mean: 20.5\n",
+      "2415:1201258\tQ-min: 0.061\tQ-max: 0.113\tLives: 1\tReward: 13.0\tEpisode Mean: 20.5\n",
+      "2415:1201310\tQ-min: 1.261\tQ-max: 1.372\tLives: 1\tReward: 14.0\tEpisode Mean: 20.5\n",
+      "2415:1201369\tQ-min: 1.232\tQ-max: 1.472\tLives: 1\tReward: 15.0\tEpisode Mean: 20.5\n",
+      "2415:1201419\tQ-min: 1.263\tQ-max: 1.468\tLives: 1\tReward: 16.0\tEpisode Mean: 20.5\n",
+      "2415:1201463\tQ-min: 0.101\tQ-max: 0.122\tLives: 0\tReward: 16.0\tEpisode Mean: 20.3\n",
+      "2416:1201508\tQ-min: 1.226\tQ-max: 1.439\tLives: 5\tReward: 1.0\tEpisode Mean: 20.3\n",
+      "2416:1201565\tQ-min: 1.233\tQ-max: 1.393\tLives: 5\tReward: 2.0\tEpisode Mean: 20.3\n",
+      "2416:1201608\tQ-min: 0.116\tQ-max: 0.144\tLives: 4\tReward: 2.0\tEpisode Mean: 20.3\n",
+      "2416:1201664\tQ-min: 1.198\tQ-max: 1.448\tLives: 4\tReward: 3.0\tEpisode Mean: 20.3\n",
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+      "2416:1201803\tQ-min: 0.119\tQ-max: 0.135\tLives: 2\tReward: 4.0\tEpisode Mean: 20.3\n",
+      "2416:1201857\tQ-min: 1.236\tQ-max: 1.334\tLives: 2\tReward: 5.0\tEpisode Mean: 20.3\n",
+      "2416:1201899\tQ-min: 0.089\tQ-max: 0.126\tLives: 1\tReward: 5.0\tEpisode Mean: 20.3\n",
+      "2416:1201953\tQ-min: 1.228\tQ-max: 1.334\tLives: 1\tReward: 6.0\tEpisode Mean: 20.3\n",
+      "2416:1202016\tQ-min: 1.273\tQ-max: 1.509\tLives: 1\tReward: 7.0\tEpisode Mean: 20.3\n",
+      "2416:1202069\tQ-min: 1.240\tQ-max: 1.469\tLives: 1\tReward: 8.0\tEpisode Mean: 20.3\n",
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+      "2416:1202138\tQ-min: 1.194\tQ-max: 1.506\tLives: 1\tReward: 13.0\tEpisode Mean: 20.3\n",
+      "2416:1202161\tQ-min: 0.081\tQ-max: 0.119\tLives: 0\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2417:1202206\tQ-min: 1.214\tQ-max: 1.396\tLives: 5\tReward: 1.0\tEpisode Mean: 20.0\n",
+      "2417:1202233\tQ-min: 0.057\tQ-max: 0.112\tLives: 4\tReward: 1.0\tEpisode Mean: 20.0\n",
+      "2417:1202277\tQ-min: 1.269\tQ-max: 1.533\tLives: 4\tReward: 2.0\tEpisode Mean: 20.0\n",
+      "2417:1202306\tQ-min: 0.072\tQ-max: 0.115\tLives: 3\tReward: 2.0\tEpisode Mean: 20.0\n",
+      "2417:1202350\tQ-min: 1.227\tQ-max: 1.585\tLives: 3\tReward: 3.0\tEpisode Mean: 20.0\n",
+      "2417:1202406\tQ-min: 1.288\tQ-max: 1.457\tLives: 3\tReward: 4.0\tEpisode Mean: 20.0\n",
+      "2417:1202468\tQ-min: 1.253\tQ-max: 1.385\tLives: 3\tReward: 5.0\tEpisode Mean: 20.0\n",
+      "2417:1202517\tQ-min: 1.319\tQ-max: 1.524\tLives: 3\tReward: 6.0\tEpisode Mean: 20.0\n",
+      "2417:1202550\tQ-min: 1.255\tQ-max: 1.540\tLives: 3\tReward: 7.0\tEpisode Mean: 20.0\n",
+      "2417:1202581\tQ-min: 1.207\tQ-max: 1.530\tLives: 3\tReward: 8.0\tEpisode Mean: 20.0\n",
+      "2417:1202613\tQ-min: 1.282\tQ-max: 1.589\tLives: 3\tReward: 9.0\tEpisode Mean: 20.0\n",
+      "2417:1202660\tQ-min: 1.231\tQ-max: 1.373\tLives: 3\tReward: 10.0\tEpisode Mean: 20.0\n",
+      "2417:1202702\tQ-min: 0.106\tQ-max: 0.128\tLives: 2\tReward: 10.0\tEpisode Mean: 20.0\n",
+      "2417:1202749\tQ-min: 1.240\tQ-max: 1.517\tLives: 2\tReward: 11.0\tEpisode Mean: 20.0\n",
+      "2417:1202806\tQ-min: 1.243\tQ-max: 1.412\tLives: 2\tReward: 12.0\tEpisode Mean: 20.0\n",
+      "2417:1202873\tQ-min: 1.192\tQ-max: 1.475\tLives: 2\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2417:1202916\tQ-min: 0.107\tQ-max: 0.135\tLives: 1\tReward: 13.0\tEpisode Mean: 20.0\n",
+      "2417:1202973\tQ-min: 1.179\tQ-max: 1.458\tLives: 1\tReward: 14.0\tEpisode Mean: 20.0\n",
+      "2417:1203037\tQ-min: 1.230\tQ-max: 1.436\tLives: 1\tReward: 15.0\tEpisode Mean: 20.0\n",
+      "2417:1203108\tQ-min: 1.138\tQ-max: 1.512\tLives: 1\tReward: 16.0\tEpisode Mean: 20.0\n",
+      "2417:1203151\tQ-min: 0.098\tQ-max: 0.119\tLives: 0\tReward: 16.0\tEpisode Mean: 19.9\n",
+      "2418:1203192\tQ-min: 1.241\tQ-max: 1.486\tLives: 5\tReward: 1.0\tEpisode Mean: 19.9\n",
+      "2418:1203237\tQ-min: 1.238\tQ-max: 1.490\tLives: 5\tReward: 2.0\tEpisode Mean: 19.9\n",
+      "2418:1203280\tQ-min: 1.254\tQ-max: 1.523\tLives: 5\tReward: 3.0\tEpisode Mean: 19.9\n",
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+      "2418:1203454\tQ-min: 1.245\tQ-max: 1.396\tLives: 4\tReward: 6.0\tEpisode Mean: 19.9\n",
+      "2418:1203506\tQ-min: 1.200\tQ-max: 1.544\tLives: 4\tReward: 7.0\tEpisode Mean: 19.9\n",
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+      "2418:1203574\tQ-min: 1.254\tQ-max: 1.423\tLives: 4\tReward: 9.0\tEpisode Mean: 19.9\n",
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+      "2418:1203870\tQ-min: 1.232\tQ-max: 1.505\tLives: 3\tReward: 18.0\tEpisode Mean: 19.9\n",
+      "2418:1203905\tQ-min: 1.256\tQ-max: 1.547\tLives: 3\tReward: 22.0\tEpisode Mean: 19.9\n",
+      "2418:1203956\tQ-min: 1.249\tQ-max: 1.360\tLives: 3\tReward: 23.0\tEpisode Mean: 19.9\n",
+      "2418:1204020\tQ-min: 1.286\tQ-max: 1.434\tLives: 3\tReward: 24.0\tEpisode Mean: 19.9\n",
+      "2418:1204089\tQ-min: 1.012\tQ-max: 1.337\tLives: 3\tReward: 28.0\tEpisode Mean: 19.9\n",
+      "2418:1204158\tQ-min: 1.232\tQ-max: 1.487\tLives: 3\tReward: 29.0\tEpisode Mean: 19.9\n",
+      "2418:1204203\tQ-min: 0.071\tQ-max: 0.110\tLives: 2\tReward: 29.0\tEpisode Mean: 19.9\n",
+      "2418:1204245\tQ-min: 1.223\tQ-max: 1.565\tLives: 2\tReward: 30.0\tEpisode Mean: 19.9\n",
+      "2418:1204287\tQ-min: 1.197\tQ-max: 1.572\tLives: 2\tReward: 31.0\tEpisode Mean: 19.9\n",
+      "2418:1204344\tQ-min: 1.209\tQ-max: 1.404\tLives: 2\tReward: 32.0\tEpisode Mean: 19.9\n",
+      "2418:1204387\tQ-min: 0.107\tQ-max: 0.137\tLives: 1\tReward: 32.0\tEpisode Mean: 19.9\n",
+      "2418:1204441\tQ-min: 1.249\tQ-max: 1.339\tLives: 1\tReward: 33.0\tEpisode Mean: 19.9\n",
+      "2418:1204506\tQ-min: 1.267\tQ-max: 1.347\tLives: 1\tReward: 34.0\tEpisode Mean: 19.9\n",
+      "2418:1204576\tQ-min: 1.068\tQ-max: 1.384\tLives: 1\tReward: 38.0\tEpisode Mean: 19.9\n",
+      "2418:1204628\tQ-min: 1.240\tQ-max: 1.613\tLives: 1\tReward: 39.0\tEpisode Mean: 19.9\n",
+      "2418:1204661\tQ-min: 1.260\tQ-max: 1.551\tLives: 1\tReward: 40.0\tEpisode Mean: 19.9\n",
+      "2418:1204682\tQ-min: 0.011\tQ-max: 0.089\tLives: 0\tReward: 40.0\tEpisode Mean: 20.6\n",
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+      "2419:1204949\tQ-min: 1.239\tQ-max: 1.381\tLives: 4\tReward: 4.0\tEpisode Mean: 20.6\n",
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+      "2419:1205014\tQ-min: 1.278\tQ-max: 1.550\tLives: 4\tReward: 6.0\tEpisode Mean: 20.6\n",
+      "2419:1205047\tQ-min: 1.207\tQ-max: 1.475\tLives: 4\tReward: 7.0\tEpisode Mean: 20.6\n",
+      "2419:1205067\tQ-min: 0.093\tQ-max: 0.138\tLives: 3\tReward: 7.0\tEpisode Mean: 20.6\n",
+      "2419:1205108\tQ-min: 1.248\tQ-max: 1.406\tLives: 3\tReward: 8.0\tEpisode Mean: 20.6\n",
+      "2419:1205161\tQ-min: 1.235\tQ-max: 1.389\tLives: 3\tReward: 9.0\tEpisode Mean: 20.6\n",
+      "2419:1205202\tQ-min: 0.086\tQ-max: 0.129\tLives: 2\tReward: 9.0\tEpisode Mean: 20.6\n",
+      "2419:1205249\tQ-min: 0.806\tQ-max: 1.165\tLives: 2\tReward: 13.0\tEpisode Mean: 20.6\n",
+      "2419:1205298\tQ-min: 0.887\tQ-max: 1.359\tLives: 2\tReward: 17.0\tEpisode Mean: 20.6\n",
+      "2419:1205312\tQ-min: 0.120\tQ-max: 0.178\tLives: 1\tReward: 17.0\tEpisode Mean: 20.6\n",
+      "2419:1205345\tQ-min: 0.082\tQ-max: 0.122\tLives: 0\tReward: 17.0\tEpisode Mean: 20.5\n",
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+      "2420:1205418\tQ-min: 0.073\tQ-max: 0.118\tLives: 4\tReward: 1.0\tEpisode Mean: 20.5\n",
+      "2420:1205469\tQ-min: 1.249\tQ-max: 1.324\tLives: 4\tReward: 2.0\tEpisode Mean: 20.5\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2420:1205522\tQ-min: 1.275\tQ-max: 1.439\tLives: 4\tReward: 3.0\tEpisode Mean: 20.5\n",
+      "2420:1205575\tQ-min: 1.333\tQ-max: 1.425\tLives: 4\tReward: 4.0\tEpisode Mean: 20.5\n",
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+      "2420:1205954\tQ-min: 1.252\tQ-max: 1.531\tLives: 2\tReward: 11.0\tEpisode Mean: 20.5\n",
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+      "2420:1206098\tQ-min: 1.233\tQ-max: 1.522\tLives: 1\tReward: 20.0\tEpisode Mean: 20.5\n",
+      "2420:1206112\tQ-min: 0.140\tQ-max: 0.153\tLives: 0\tReward: 20.0\tEpisode Mean: 20.5\n",
+      "2421:1206156\tQ-min: 1.244\tQ-max: 1.475\tLives: 5\tReward: 1.0\tEpisode Mean: 20.5\n",
+      "2421:1206183\tQ-min: 0.072\tQ-max: 0.114\tLives: 4\tReward: 1.0\tEpisode Mean: 20.5\n",
+      "2421:1206238\tQ-min: 1.167\tQ-max: 1.451\tLives: 4\tReward: 2.0\tEpisode Mean: 20.5\n",
+      "2421:1206303\tQ-min: 1.246\tQ-max: 1.382\tLives: 4\tReward: 3.0\tEpisode Mean: 20.5\n",
+      "2421:1206357\tQ-min: 1.233\tQ-max: 1.420\tLives: 4\tReward: 4.0\tEpisode Mean: 20.5\n",
+      "2421:1206395\tQ-min: 1.247\tQ-max: 1.588\tLives: 4\tReward: 5.0\tEpisode Mean: 20.5\n",
+      "2421:1206425\tQ-min: 1.263\tQ-max: 1.477\tLives: 4\tReward: 6.0\tEpisode Mean: 20.5\n",
+      "2421:1206459\tQ-min: 1.332\tQ-max: 1.578\tLives: 4\tReward: 7.0\tEpisode Mean: 20.5\n",
+      "2421:1206492\tQ-min: 1.199\tQ-max: 1.486\tLives: 4\tReward: 11.0\tEpisode Mean: 20.5\n",
+      "2421:1206541\tQ-min: 1.196\tQ-max: 1.424\tLives: 4\tReward: 12.0\tEpisode Mean: 20.5\n",
+      "2421:1206583\tQ-min: 0.097\tQ-max: 0.121\tLives: 3\tReward: 12.0\tEpisode Mean: 20.5\n",
+      "2421:1206625\tQ-min: 1.214\tQ-max: 1.495\tLives: 3\tReward: 13.0\tEpisode Mean: 20.5\n",
+      "2421:1206670\tQ-min: 1.292\tQ-max: 1.393\tLives: 3\tReward: 14.0\tEpisode Mean: 20.5\n",
+      "2421:1206730\tQ-min: 1.136\tQ-max: 1.544\tLives: 3\tReward: 18.0\tEpisode Mean: 20.5\n",
+      "2421:1206783\tQ-min: 1.237\tQ-max: 1.514\tLives: 3\tReward: 19.0\tEpisode Mean: 20.5\n",
+      "2421:1206817\tQ-min: 1.265\tQ-max: 1.514\tLives: 3\tReward: 20.0\tEpisode Mean: 20.5\n",
+      "2421:1206853\tQ-min: 1.172\tQ-max: 1.514\tLives: 3\tReward: 24.0\tEpisode Mean: 20.5\n",
+      "2421:1206875\tQ-min: 0.094\tQ-max: 0.119\tLives: 2\tReward: 24.0\tEpisode Mean: 20.5\n",
+      "2421:1206925\tQ-min: 0.921\tQ-max: 1.427\tLives: 2\tReward: 28.0\tEpisode Mean: 20.5\n",
+      "2421:1206940\tQ-min: 0.208\tQ-max: 0.244\tLives: 1\tReward: 28.0\tEpisode Mean: 20.5\n",
+      "2421:1206992\tQ-min: 0.711\tQ-max: 1.110\tLives: 1\tReward: 32.0\tEpisode Mean: 20.5\n",
+      "2421:1207005\tQ-min: 0.121\tQ-max: 0.141\tLives: 0\tReward: 32.0\tEpisode Mean: 20.9\n"
      ]
     }
    ],
@@ -2641,10 +1593,10 @@
      "output_type": "stream",
      "text": [
       "Rewards for 30 episodes:\n",
-      "- Min:    40.0\n",
-      "- Mean:   145.166666667\n",
-      "- Max:    386.0\n",
-      "- Stdev:  105.131372842\n"
+      "- Min:    8.0\n",
+      "- Mean:   20.866666666666667\n",
+      "- Max:    40.0\n",
+      "- Stdev:  8.155706931686273\n"
      ]
     }
    ],
@@ -2671,12 +1623,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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cOseM1zJ+e/wDxnNbL98sH+NPyN/CeM7xM8DKguT9ly7P3d2L6Iw127+2y3sfcMkc8j6f\n8VTJ3cD+7nbpoo7xFnkXcoyBXwTu7HIdAP6qW/90xv+Z3A98EDihW39it3x/9/jTFyTvbd34HgDe\nw4+PYJn779ya7L/Gj49Omdn4esamJDVsoadTJElbs8QlqWGWuCQ1zBKXpIZZ4pLUMEtckhpmiUtS\nwyxxSWrY/wErup7CCPwjeQAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8851c83e10>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2698,9 +1652,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def print_q_values(idx):\n",
@@ -2741,9 +1693,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_state(idx, print_q=True):\n",
@@ -2788,7 +1738,7 @@
     {
      "data": {
       "text/plain": [
-       "656"
+       "1061"
       ]
      },
      "execution_count": 29,
@@ -2811,9 +1761,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "q_values = replay_memory.q_values[0:num_used, :]"
@@ -2829,9 +1777,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "q_values_min = q_values.min(axis=1)\n",
@@ -2860,7 +1806,7 @@
     {
      "data": {
       "text/plain": [
-       "41"
+       "42"
       ]
      },
      "execution_count": 32,
@@ -2891,12 +1837,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ylKAgdBFhsVZKUS6XWVxcZHFxkWw2W+ejhyvhlCLy3Y0IvSB0EeVyOYiy8X0f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\ngiAIXY4IvSAIQpcjQi8IgtDl/H+HLMff60gFRgAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c190a90>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2905,23 +1853,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.576 (Action Taken)\n",
-      "FIRE        1.573 \n",
-      "RIGHT       1.564 \n",
-      "LEFT        1.574 \n",
-      "RIGHTFIRE   1.571 \n",
-      "LEFTFIRE    1.571 \n",
+      "NOOP        1.188 \n",
+      "FIRE        1.169 \n",
+      "RIGHT       1.148 \n",
+      "LEFT        1.278 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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r+roiCakL7i5gW2vxPI/p6WkuXrzI7OwsmUwGY8y2Q3AF+dHXnVdP7uQnJyeZnp7u6GxXnZDjLlXBPfnDdMF9amqK8+fP02g09IOVbay1FAoFJicn8Twvbtlr7Lscd6kK7tDZ4jLGUCgUmJqaotVqKbjLNtZacrkcxWJxW90ROc5SF9x3o1aY7MS10FU/RDqlPri7se1RFKk1Jtvo3AeRnaU+uGcyGXzfjztRXUeaHG/JeuD7voZCinRJbXB3LTHf98nn8/j+VlFdZ5kcb8l64Hkevu+rbogkpDa4w915ZdwPV2kZ6eZGVanlLtIp1cEd7gZ4N8ZdJEkns4nsLPXBPUmH3CIiezMUx7Ia6ia7Ud0Q2dlQtNxdakaH37IT1QuR7VIf3JMX6tCPWHajuiHSKfXBPUmH3yIie6PgLkNNLXaRnQ1VcNcPWURkb1If3N1JTGq1y27UHyOyXeqDe/LkpeQPWCevHE/d37vqgcjOUh3ck2em6gcsu9G0vyLb9RzcjTEe8Cxww1r7HmPMJeBJYBb4KvDz1tpmD+/fMXdIFEWaR0Q66oG7lmq/g/th122Rw9SPKPkR4LnE/d8Cfsda+wiwBny4lzfvHufueV7HSU26Hc9bsh4k60mfHWrdFjlMPbXcjTHngX8HfBL4qNn6hf048HPtl3wG+G/A7x90He5wOwzDXooqI+wwUjJHUbdFDlOvaZnfBX4VmGzfnwXWrbVB+/514IFeVhCGoQK77EmfW++HXrdFDtOBg7sx5j3ALWvtV40xP3qA5R8HHgc4efLkjq+x1hIEAUEQ6OpLsqtMJkM2m41TNb3qZ90WGZReWu5vBX7KGPNuoABMAU8A08YYv93COQ/c2Glha+1l4DLAwsLCjsfULh3TbDYJw/Cw8qoyxNzFOozp65z/favbxhgN4ZGBOHBwt9Z+HPg4QLt181+stR80xvwJ8D62RhU8BjzVSwHdBZDDMNQoGdnGXTi9nzn3o6rbIofpMMa5/xrwpDHmvwP/Any61zfsc6tMRsgRnwfR97otclj6EtyttX8H/F37/1eAN/fjfeHuGOYgCBTcZRvXYj+sTvfDrNsihym1Z6i6Q+0gCKhWq7RarbiFpjMRxdUDay3ZbJZsNtvxuMhxl7rgnpwrxFpLo9GgXC5Tq9XiQ3D9eCUZ3AuFAoVCgbGxMTzPAzTnjEjqgnuSa7nX63UFd+mQDO7GGIIgUL0QSRia4SdqhYmI7N1QBHcFdhGR/UllWsYdaltraTablEolyuWy0jISS6ZlwjDk5MmTcb1Q/RBJWXBPBm5jDFEUUSqVuHXrFmtra2QyGTKZDFEUqcPsmHLfu6sHURRx8uRJZmZmttUJNQTkOEtVcIe7P15jDGEYUqlUWFpa4tatW/G87m5Ms4L78eOCted58TkQzWaT8+fPx2erJl8nclylLrh3azQabG5uUiqVAOIWmxxvyXpQLBZpNBqqFyIJqe9Q7Z7LXT9ggc564NJ0InJX6oO7u+qOk/xfjq9kPXB9MSJyV+rTMt2XUktOQaCc+/GT7JNRPRDZXeqDe/ISam76Xw15O952qgeqCyKddCwrIjKCFNxlJCg1I9JJwV1EZASlPucuIkfDjUzzPC8egnxYF0GRw6fgLiLAVnD3fR/f9w/9Cldy+BTcRQTYOhmsXq9ve1xz9Awn5dxF5J7UWT2c1HI/ADeBGdy9gLfIsDtz5gyPPPIICwsLRFHEiy++yHPPPUej0QC26r3q+vBQy32fPM9jYmKC2dlZZmZmGBsb2zbNrMgw8DyPXC4X35+fn+ejH/0oTz75JJ///Of50Ic+xNTUVPx8oVAYRDHlgBTc9yAZsH3f5+TJk8zPz3Pu3DkmJyc75jVRcJdh4eqys7m5yRve8Ib4/vnz5/H9uwf37mI5MhyUltmDZIeS53mMjY1x4sQJwjCkVCp1zDEvMiystbRarfh+JpNhdXU1vl8ulztm31Sn6nBRcN8nd+m/RqNBGIYEQaBKL0PFDXlsNptxMH/b297Gu971ro7XnTt3jmw227GcDA8F9z1IBu8gCNjc3IxP8lDrRoZNJpMhn8/HrfaHH36YX//1X+ed73zntuslKKAPLwX3PegO7hsbG1Sr1fiwVsFdhkkYhtTrdYrFIg8++CAf+MAHePvb3w5sBf4gCHjqqaf47Gc/y507d+LlarWa6vcQUXDfJ2stjUYjHh4mMiyMMeTzeer1OkEQMDMzwwc/+EHe97730Wq1yOfzAHz5y1/mE5/4BC+88AIAExMTVKtVgiAYZPFlnxTcRY6R5OiXarXKiRMnOHXqFCsrK/zDP/wDL7/8Mk8//XQc2EFTEAyrnoZCGmOmjTFfMMZ81xjznDHmR4wxM8aYvzHGvNj+e/L+7ySSLqNat5Ot74mJCVZWVlhfX8f3fb797W/zyU9+kr/8y7+Mn/c8j1qtpmsXD6Fex7k/AfyVtfb7gTcCzwEfA75krX0N8KX2/ZGTvPyfjKSRqttuOK/Ltf/AD/wAP/ZjP8b09DSVSoWJiQlOnDhBqVSKl3HBPfkeMjwOHNyNMSeAtwOfBrDWNq2168B7gc+0X/YZ4Kd7LWQa6dJuo2sU63byTFRjDG9+85v5mZ/5Gd7whjdQqVR44YUX2NjYYG5uLn7dnTt3Olr6qu/DpZec+yXgNvCHxpg3Al8FPgKctdYutl+zBJztrYgiR27k6nayBV6tVsnn88zNzTE+Ps7Xv/51/vEf/5Gvfe1r3L59G9/3CYKg4wQnGT69BHcf+CHgl6y1zxhjnqDrMNVaa40xO+7ujTGPA48DHadAi6RA3+p2WiRHd50+fZrFxUX+6Z/+iYmJCZ555hm++MUvximZbDZLJpNRnn3I9RLcrwPXrbXPtO9/ga0fwLIxZs5au2iMmQNu7bSwtfYycBlgYWFBx3uSJn2r27vtAI6Km8kxDEN83+eNb3wj8/PzLC0tcfnyZXzfp1ardeTaoyhSCmYEHDjnbq1dAq4ZY17bfugdwHeAPwceaz/2GPBUTyUUOWKjVLeT0wd4nsdDDz3Eww8/TLlc5qWXXuK73/0uV69eJZ/Pk81mMcYQhqGC+wjodZz7LwGfNcbkgFeA/8DWDuPzxpgPA1eB9/e4DpFBGJm6nUyxuFz6TsFbAX209BTcrbVfBx7d4al39PK+IoM2KnV7t+kxknOzFwoFms2mcuwjRvO5i4yw7rNLs9ksuVyu4xoEwLb7Mvw0/YDIiDLGMDMzgzGGlZUVwjDk2rVrHVP9AjSbzQGWUg6LgrvICPE8Lx7tYq1lbm6Oc+fO8eqrr/Lyyy/zla98henpaer1eryM0jGjScFdZIR0TxGQy+WYnZ1lfX0d2ArkyVZ78ipjMlqUaBMZYWEY0mg0tqVeXI5dgX10KbiLjAjXCnet95mZGU6ePBmfyOTk8/mOqX9lNOkbFhkBmUwmvvQjbAX2hx56iDNnztBqtTrmidFFN44HBXeREdA9S+nk5CSnT5+mUqlw9epVlpaW4ud08Y3jQcFdZAS4VIwL8MYYSqUSt2/f5vnnn48fM8ZodMwxoeAuMgKy2Szj4+NxeqbVanHlypWOC1wn8/Ey+hTcRYZQd0s9l8tx5syZeAz7zZs3uXXr7qSVbn4ZtdqPDwV3kSGVyWTi/Lnv+xQKBSYnJ/E8r2M6Ad/3lY45hhTcRYZUMli3Wi3K5TKe59FoNAjDMB4aGQSB0jHHkIK7yBDqPvmoWq2yvLzM2tpafOJS8uxTnax0/Ci4iwypTCYTt8jDMOy4mpKIgrvIEHKjY4rFIlEUUS6XqVQqgy6WpIiCu8iQSKZZMpkMU1NTTE9Px52qjUYjPvtUF7gWBXeRIRRFEcaYeFSMLrYh3RTcRYZE8uxT3/ep1WrAVqCv1Wod0wqo1S4K7iIpl0zHZLNZJiYm4ukFVldX47NSNSJGkhTcRVKuO2jn83mstWxsbGgSMNmVgrvIELHWxikXnZgk96JeGJGUy2az+L5PJpMhl8vt2ImqDlXpppa7SIoZY8jn82SzWaIowvf9+MpKyXSN8u3STcFdJMXccMdsNht3mtbr9Xj+GEfBXbopuIukXBRF8VzszWaTarXacdk8kZ0oUSeSMsmOUhfYM5lMPOQxeQ1UdarKbhTcRVLMXRrPpWSSZ6WC0jGyO6VlRFImOX+M7/uEYRhPCqZx7bJXPbXcjTH/2RjzbWPMt4wxf2yMKRhjLhljnjHGvGSM+ZwxJtevwooclUHXbWMMhUKBfD5PEARUKhUqlQr1el0BXvbkwMHdGPMA8J+AR621Pwh4wM8CvwX8jrX2EWAN+HA/CipyVNJQt7PZLNlsFs/zDmsVMuJ6zbn7QNEY4wNjwCLw48AX2s9/BvjpHtchMggDq9u+75PNZgEIgkB5dTmQAwd3a+0N4H8C32Or4m8AXwXWrbWuO/868ECvhRQ5SoOu225UTKPRUBpGDqyXtMxJ4L3AJWAeGAd+ch/LP26MedYY86yuICNp0s+6fcD1x0Me1XKXg+olLfNvgVettbettS3gi8Bbgen2oSzAeeDGTgtbay9bax+11j46Pj7eQzFE+q5vdfugBdD4delVL8H9e8BbjDFjZqsmvgP4DvC3wPvar3kMeKq3IoocuSOt292BPDnzo8hB9ZJzf4atzqWvAd9sv9dl4NeAjxpjXgJmgU/3oZwiR+ao67abO8adnNRqtWi1Wgrw0pOeTmKy1v4G8BtdD78CvLmX9xUZtKOs28aYeMijm25AnajSK00/ICIyghTcRQbM5dw1Kkb6ScFdZIDcbI8i/aaJw0QGxM3w6GZ8VAeq9JOCu8iAuOl8oyjadtk8kV7peFBkQLrnahfpJwV3EZERpLSMyIAkc+yuBS/SL2q5iwyIO1kpeY1UkX5RbRJJAU0UJv2m4C4iMoKUcxcZMM0lI4dBwV1kwNSRKodBaRmRlHHj3w/6vAgouIukjpuWIBnAuwO6WvtyPwruIkNGgV32Qjl3GQmjFPCO8rN0HyHsRbJ8vSy7l9eM0vd61BTc96iXHKcq6NFyc7UM83Z3Ze93bj15JmwmkyGfz+P7fsf2ut863dWiXPpoP9zsl275e723tZYgCDRb5gGlNrinrcNomAPFceDqSzI3Payn9CeDbL8v5JF8nyiKqNVqfXlfSZ/UBPfdRgCkLchLerlWZDK4J/8Ou2HcUfWDrlR1MKkJ7lEUdbS03OFZGr5Qd/iZzE/er1zJqVyjKNKh5SFzc6K7m/t+0lKH9mOnndJe6l33aBrXYEo+nslkCMOQKIoYGxtjbm6O6elprLU0m824nnfnvZPTEzcaDVqtFtlslnw+31HXd9uRusdbrRaNRiP+vSefd2UIwzAu58bGBtVqdT+bT9pSEdxdbs0YQxiG8ZceBMHAL2JgjKFQKDAxMcHY2BjZbPae+clkPjOKIhqNBuVymWq1SqvVOvLyHwdRFBEEAY1Gg2w2SxAEWGvxPC/VO9adjlbvN759L++XDLTZbJZcLkcURXieRy6Xi+vjpUuX+IVf+AV+4id+glarxcrKCp7nkc/nO7aZ+00Wi0WazSZXrlxhZWWF06dP8+CDD5LL5ajVavE2h7s7BNdIy+VyGGNYWVnh2rVrlMtlstlsvCPJZrO0Wi0WFxcplUqMjY2xvr7Ol7/8Zb71rW8BxO+ts3n3JjXBvdlsAndb8FEU0Wq1BhLcuzudJicnmZ+f5/Tp04yNjcWniyd/TO6H58rveR5hGLK+vs7i4iJLS0sdwX1Y88FpFEUR9XqdUqnUcVUjz/NSf/m6/QT3+3FHlu4zZzIZfN+PGySe51EsFqnX6wCcPHmSt7zlLTzyyCP7Ws+lS5e4fv0658+fZ3Z2dt/lfOGFF1hdXSWfz8c74Hw+T6vV4uWXX+bOnTtMTU1x69YtvvnNb8bLud+bgvvepCK4w925rd3f5F5/kFyL5dSpU5w/f56pqam4pQjEAcRx5c/lcgRBQLFYpFqtcufOnYGU/zhwR36NRiPeqbppdIFUB/d7pTK66/5Or0seQXa/PjlqKNlocq8LgoBSqRS/vtVq4fv+fXcwGxsbbG5usrGxse/g7pYtl8txGsg17prNJpVKhWq1iud51Gq1+HfW/Xnl/lIR3N2PEzqDexrSMnB3YkU5EdYAAAccSURBVKcwDGk2mx0t9+6crvsRNZvNeCeQhp3UcZM8qkqzXtIwuy2zU8pwp/w73E11AGSz2T2tw/f9+Ihgv7LZLL7v43kevu/Hwd33/Th1lMlk8DwPz/P6emRz3KQiuMPOIxzSMIeGtZZKpcLy8jJhGFIoFDoO9XfKubsO2CiK2NzcZG1tbVu+Pe1BZ9i4uuKCRbITcJTt1Ona/Xz3Ts69zuXX9yufz5PL5cjlcgde1vUFuO/LvZd73O0ERv37O0ypCO7GmPiLdC1i1zo4yBl0vepuiZfLZcIwZHV1teOEj90Ok5M/qGazSa1Wi/sUpD+S31EYhlSrVTY2Njr6aVxaJq052mS6JPnYQXQPRnBHi61WK66vrsHh6uLy8jJPP/006+vrBEHA2toamUwm7oB1XBldXvzGjRusra0xMzPDAw88gO/7NBqNjm2e/Dyuw9QYw9raGouLi1Sr1Y6Wu0un3b59m0qlQqFQoFQqcevWrW3lkL1JRXAPw5ByubwtuFcqlXjY1KC4oV/NZpPNzc0Dv4da6oen1Wpx584dfN8nn8/HwdwFgkajMcji3dNh1w03YstJtuKvXLnC7/3e7/GpT30qfm33a5KSo9iSHbbuc9xLcqfjhmLuFKjdjtn1DyTLnua+kzRKRXCv1Wr867/+a/yFusPrer3OzZs3O77gQQVJBeh0SX4XzWaT27dvUy6Xt3VwQ7qD+2HbqZPVCYKA9fX1oy7SvukkpoMxe9jj/gHwHuCWtfYH24/NAJ8DLgJXgPdba9fM1rfwBPBuoAp8yFr7tfsVwvd9Oz093b1ewjCk0WhQr9e115b7uteoE2vttiePom4bYxSR5FDtVLdhb8H97UAZ+KPED+B/AKvW2t80xnwMOGmt/TVjzLuBX2LrB/DDwBPW2h++X+GG4QfQS65PLY7B2yW4H7u63X0Oh5s4DPae09bEYemyW3DvGAu7242tVsy3EvefB+ba/88Bz7f//xTwgZ1ed5/3t7rpdpg31W3dRvW2W9076MU6zlprF9v/LwFn2/8/AFxLvO56+7H7cnNadN/UOy57kRw6233bp77XbZFB6LlD1VprD3LoaYx5HHjc3dehl/TiMFJf/arbIoNw0Jb7sjFmDqD91w1GvQEsJF53vv3YNtbay9baR621jx6wDCKHQXVbRsJBg/ufA4+1/38MeCrx+L83W94CbCQOcUWGgeq2jIY9dAj9MbAItNjKM34YmAW+BLwI/B9gpv1aA/wv4GXgm8Cje+ywHXinhG6jfVPd1m1Ub7vVvfsOhTwKaRsuJqNn1+Fih0x1Ww7bbnX7oGkZERFJMQV3EZERpOAuIjKCFNxFREZQKmaFBFaASvtv2pxC5dqPNJbrwQGuW3V7/1Suvdu1bqditAyAMebZNJ70oXLtT1rLNUhp3SYq1/6ktVy7UVpGRGQEKbiLiIygNAX3y4MuwC5Urv1Ja7kGKa3bROXan7SWa0epybmLiEj/pKnlLiIifZKK4G6M+UljzPPGmJfalzYbVDkWjDF/a4z5jjHm28aYj7QfnzHG/I0x5sX235MDKJtnjPkXY8zT7fuXjDHPtLfZ54wxuaMuU7sc08aYLxhjvmuMec4Y8yNp2F5poHq95/Klrm6PQr0eeHA3xnhszbb3LuD1wAeMMa8fUHEC4Festa8H3gL8YrssHwO+ZK19DVszBg7ih/oR4LnE/d8Cfsda+wiwxtaMhoPwBPBX1trvB97IVhnTsL0GSvV6X9JYt4e/Xu9l2tLDvAE/Avx14v7HgY8PulztsjwFvJNdrqt5hOU4z1Zl+nHgabamn10B/J224RGW6wTwKu2+m8TjA91eabipXu+5LKmr26NSrwfeciel16Y0xlwE3gQ8w+7X1Twqvwv8KuCuRTgLrFtrg/b9QW2zS8Bt4A/bh9X/2xgzzuC3VxqoXu9NGuv2SNTrNAT31DHGTAB/CvyytXYz+Zzd2m0f2RAjY8x7gFvW2q8e1Tr3wQd+CPh9a+2b2DrNvuNQ9ai3l+wuTfW6XZ601u2RqNdpCO57vjblUTDGZNn6AXzWWvvF9sO7XVfzKLwV+CljzBXgSbYOX58Apo0xbm6gQW2z68B1a+0z7ftfYOtHMcjtlRaq1/eX1ro9EvU6DcH9n4HXtHvIc8DPsnW9yiNnjDHAp4HnrLW/nXhqt+tqHjpr7cetteettRfZ2jb/11r7QeBvgfcNokyJsi0B14wxr20/9A7gOwxwe6WI6vV9pLVuj0y9HnTSv9058W7gBbauT/lfB1iOt7F1qPUN4Ovt27vZ5bqaAyjfjwJPt/9/CPgK8BLwJ0B+QGX6N8Cz7W32Z8DJtGyvQd9Ur/dVxlTV7VGo1zpDVURkBKUhLSMiIn2m4C4iMoIU3EVERpCCu4jICFJwFxEZQQruIiIjSMFdRGQEKbiLiIyg/w8TJ5sRm2V71wAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c199e48>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2930,23 +1878,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.630 (Action Taken)\n",
-      "FIRE        1.626 \n",
-      "RIGHT       1.610 \n",
-      "LEFT        1.617 \n",
-      "RIGHTFIRE   1.606 \n",
-      "LEFTFIRE    1.625 \n",
+      "NOOP        1.220 \n",
+      "FIRE        1.206 \n",
+      "RIGHT       1.163 \n",
+      "LEFT        1.310 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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l2dv3fwS+rZRKAB8A/57KzeNvlFKfBz4EfrvJYwhCO+gK296yZQvJZJJisUhf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\n2La8uvXViB3GYsCUxDGFjUb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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f89608fd710>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2955,23 +1903,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.641 (Action Taken)\n",
-      "FIRE        1.635 \n",
-      "RIGHT       1.632 \n",
-      "LEFT        1.627 \n",
-      "RIGHTFIRE   1.617 \n",
-      "LEFTFIRE    1.641 \n",
+      "NOOP        1.360 (Action Taken)\n",
+      "FIRE        1.271 \n",
+      "RIGHT       1.217 \n",
+      "LEFT        1.274 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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vDZoR+glgQmv9evX9d6lcHFeUUrcCVP9OrbC+IMSVrrFtI+pQybIxAm86ZbPZ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\nuhwRekEQhC5HhF4QBKHL+f8NrAmvL0LNtwAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c303c18>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2980,23 +1928,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.710 (Action Taken)\n",
-      "FIRE        1.703 \n",
-      "RIGHT       1.694 \n",
-      "LEFT        1.703 \n",
-      "RIGHTFIRE   1.693 \n",
-      "LEFTFIRE    1.705 \n",
+      "NOOP        1.301 \n",
+      "FIRE        1.335 (Action Taken)\n",
+      "RIGHT       1.243 \n",
+      "LEFT        1.305 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Ly1y4cIELFy6Ez6P96mUO2P7RTh39fuAK8FdKqcPA68AXgB1a60u1Zd4HdjRb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\nhBCiz0mgF0KIPhenQP9UtxO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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0d44a8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3005,23 +1953,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.743 \n",
-      "FIRE        1.736 \n",
-      "RIGHT       1.741 \n",
-      "LEFT        1.739 \n",
-      "RIGHTFIRE   1.725 \n",
-      "LEFTFIRE    1.747 (Action Taken)\n",
+      "NOOP        1.307 \n",
+      "FIRE        1.337 \n",
+      "RIGHT       1.255 \n",
+      "LEFT        1.435 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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pLMuqy0QpMfPdQ7Mdpr4K/IvW+iZgP/A68AXgGa31PuCZ2rwgdBpdaduxWCzo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\nVUN9y21bENpN01E3Wmu9Fj+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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0e07f0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3030,23 +1978,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.768 (Action Taken)\n",
-      "FIRE        1.749 \n",
-      "RIGHT       1.753 \n",
-      "LEFT        1.757 \n",
-      "RIGHTFIRE   1.747 \n",
-      "LEFTFIRE    1.764 \n",
+      "NOOP        1.362 \n",
+      "FIRE        1.359 \n",
+      "RIGHT       1.260 \n",
+      "LEFT        1.496 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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TbTzOZDLJwMAAiUSCmZkZpqenwx6xZh/hypihJqJ2YIavFtaGZDKJ4zjk83kA\nbrnlFt797nczPDzMl770JR5//HGuvfZafuu3fouhoSEee+wxvvvd7wLzLwkZAqH1xE7o68UuCIKw\nmm4GsWqnGZqiqWnd3d0cOnSILVu2cPToUS5duhRuJx1Llk/9VILtOANZO1EqlWp6u547d45vf/vb\nHD58mMcffxyYt/Nf+ZVf4cYbb+T73/9+KPTJZJJKpSJC32JiJ/SdRlTou7q6OHToELt27WJsbIyT\nJ08Cl3O9paorxAlTS4qKPMALL7zAyZMnGRsbC9eZobfFWYknsRf6TopnW5ZFNpulp6enpt2hU66v\nVcj9WxuMaKdSKTKZDEEQkMvlGB4eZnh4mJ6enjB2b/LpTRw/egwR/9YTe6Fvd6IhhWKxyBtvvMHU\n1NQCb0geBiEumB7axnb37dvHoUOHOH/+PM8991xYQ00mkzU9knt7e0kkEgucGHkRtx4R+jUmGo7J\n5/O89NJLpNNpRkcvz0InQi/ECdu2sW07FPE9e/bwoQ99iOPHj3P48GFg3stPJBKh6Luuy6uvvorr\nujW27fu+tJ/EABH6Nabeoz99+jSWZdU0TsmDIMSN+kmAjPgbgiAIXwQwP1Txl7/8Zbq7u3nzzTfD\n9aVSSew7BojQryNaaxkHRIg1ppNTtAF2ZGSEw4cPMzIyEoq267phb2Qz/pRJLoDLYw5JgkE8EKEX\nBAG4PNx2vTifPn2a0dHRcKRQw5Xm6xUvPl6I0K8z0Y4+EpcX4oKZbN33fWzbpr+/H8uymJiYYG5u\nrmZWKbOtwXRiM8OI178QhNYT366lHYyIvBAnor3PYX4Yg7vvvptbb7110TTgxbx1M0Jr/UiXQjwQ\noV9nROSFOGHCNYZUKsXNN9/MLbfcwvbt28MXgG3bdHV1XfFYvu8vyKMX4oGEbgRhgxKNyfu+T1dX\nFwcOHOC6664Lh9I2IRgZr6a9EaEXhA2K1romzGLbNlu2bKFYLHL06FHeeOONmrkfJGOsfRGhF4QN\nSn2WjZk05MKFCxw7dozJyUmgdmJ7oT0RoReEDUR02Oxodk25XGb79u10d3czOTnJzMxMuI9t2/i+\nL7H3NkaEXhA2EFGhdxyH/v5+tm7diuu6ZDKZMJyTTqfD8edF5NsfEXpB2EBEc+BNumQ6nSaVSpHP\n5xkfH2dqaqomdi9hm/ZHhF4QNhDRHHiTSRMEAZZlMTs7y/DwcNgAW98xSmhfGsqjV0r1KaW+pZR6\nQyn1ulIust+DAAARh0lEQVTqZ5VSW5RSzyilTlf/bm5WYQVhvehU244Kt+d5YY9W0zEqmkIpQwx3\nDo12mPoK8E9a6wPAQeB14PPAs1rrfcCz1WVBaDc60rYdxwnFO5lMEgQB+Xye2dlZgiAglUqF20rn\nvs5h1aEbpVQvcC/wGwBa6wpQUUp9DLivutljwGHgc40UUhDWk06y7WjjK0BPTw+bNm1CKYXrukxP\nTzMzM4NSikqlUhObl7BN59BIjH4PMA78jVLqIHAMeAQY1Fqfr25zARhcbGel1MPAwwC7du1qoBiC\n0HSaZtutJir0lmWRyWQYGBggmUwyOTnJyMhIzbjyQmfSSOjGAW4H/kprfRswR11VVs9b2KJ1P631\no1rrO7TWd/T39zdQDEFoOk2z7TUv6TIwoRrz10wTKKGZjUMjQn8OOKe1fqm6/C3mH44xpdS1ANW/\nFxsroiCsOx1j21ExN/nw0XWOc7lSb9u2NL52KKsWeq31BeBtpdT+6qoPAj8BngQerK57EPhOQyUU\nhHWmk2x7MY/dsiwSiQSWZYmwbxAazaP/z8A3lFJJ4KfAf2T+5fF3SqmHgLeAX23wHILQCjrCth3H\nwbZtgiAIhzLI5XIUi0UKhUJNOqWMI9+5NCT0WuvjwGJxyA82clxBaDXtatv1WTbpdJq+vj4cx6FS\nqZDP53nrrbfC7WTo4Y2B9IwVhA6jfjybdDpNNpsln88zPT1dM/SwsDGQGaYEoYMxDa+e54Vzuwob\nDxF6QeggFkuZjA5lEJ02UBpjNw4i9IKwAVhM0CWHfuMgMXpB6CAcxyGRSITLWmtmZ2cpFApUKhUq\nlUrNd8LGQIReEDoIx3Ho6ekhlUrhui65XI7x8XG01liWJeK+QRGhF4QOQimFbdth7nw0Zi+DlG1c\nJEYvCB1EdBwbybIRDCL0gtBBaK3DLBuTVRMd1EyEf2MiQi8IHYTpLBUEwYLQjcTnNy4SoxeEDsC2\n7XCgsnw+z9zcHFrrmiwbELHfqIjQC0IHkEgk6OrqwnVdZmdnW10cIWZI6EYQOgCTbRPt+SoIBrEK\nQWhTog2rQRBQqVTwPK9mvTS+CiChG0FoS5RSJJPJ0IMPgoBCobBgTHmJyQsgQi8IbYmZJSqVSqG1\nplgsyiTfwpJI6EYQ2oT6MIzJi5fwjHA1xKMXhDYhGoYJgiCcHUprje/7C2aXEgSDCL0gtCEmR96I\nvekcJQiLIUIvCG1CNExjer8KwnIQoReENkApheM4OM78I+t5nkzsLSwbEXpBaAO01uEwB2bZ933x\n6oVlIUIvCG1C/XywEpMXlosIvSDEHDPkcBAElMtlQBpfhZUhQi8IMcbE5i3LwvO8BT1fBWE5SIcp\nQYgx0YlExIMXVosIvSC0ASLyQiOI0AtCjLFtu2YqQEFYDSL0ghBTbNsOhb4+40YQVkJDQq+U+q9K\nqR8rpU4qpf5WKZVWSu1RSr2klBpWSn1TKZVsVmEFYb2Ig22b2HwQBHieJznzwqpZtdArpXYA/wW4\nQ2t9M2ADnwa+DPyp1vp64BLwUDMKKgjrRZxsW0ReaAaNhm4cIKOUcoAscB74APCt6vePAR9v8ByC\n0ArW3bZNvrz5iMgLzWLVQq+1HgX+DzDC/EMwAxwDprXWXnWzc8COxfZXSj2slDqqlDo6MTGx2mII\nQtNppm2v5LxG6CUuLzSbRkI3m4GPAXuA7UAX8PPL3V9r/ajW+g6t9R39/f2rLYYgNJ1m2vYKzilz\nvQprRiM9Yz8EvKm1HgdQSv0D8D6gTynlVD2fncBo48UUhHVlXW3bePKwcDwbQWgGjcToR4C7lFJZ\nNe9+fBD4CfA88MnqNg8C32msiIKw7rTMts04877vi+ALTaORGP1LzDdMvQK8Vj3Wo8DngM8opYaB\nrcDXm1BOQVg3Wm3bIvBCs2loUDOt9e8Bv1e3+qfAnY0cVxBaTStsO9oDVsReaCYyeqUgxACJzQtr\niQi9ILQQ48VLrrywlshYN4LQIupTKgVhrRChF4QWEBV5CdkIa40IvSC0GPHqhbVGhF4QWoA0vgrr\niTTGCkKLEKEX1gsRekFoISL2wnogoRtBiAESpxfWEhF6QRCEDkeEXhBigIRwhLVEhF4QYoR0ohLW\nAhF6QYghIvZCMxGhF4QYYUI4WmsRe6FpxEropdoqrJbF7KZdbUni9UKziVUe/WK9BTvR6FcrQJ14\nL5pF1HbM/2a2pnakHV9SlmUtq9zR38cQnU5xpfsKVyc2Qh8EAbZt16zrxB+z0VpLJ96TtaBTxKCd\nJiFJJBIkk0ng8rDL9bYenSrR8zyCIEApRTKZJJFIhNe7VOiqft/FzlF/vna5f2tJbITeeAPRH60T\nQzlieGtD1FaUUti2jW3bbWs/7WQjRpzL5TLlcnnF+zeyr9lfuDKxiNGbh9R8TBWuE4VeWBuMuAM4\njoNlWW0v9u3CckIuQmuJhUevtcb3fWC+amaqZNH/OwGlFI7jhOKzXE/EbOt5Hp7nrXEp25MgCMJ7\n43kevu/juq7UoNYQ27bxfR/f97Ftmx07djAwMABAuVxeNGbv+z6VSoV8Ps/MzAyFQoFEIsHAwAD9\n/f04jhP+fvWhXADXdcnlckxPT1MqlbAsC8uylgz3mFCP0ZeNSmyE3nVdPM+jUqng+z7ZbJZyudz2\nwhYV9FQqxY4dOxgcHMSyrPDaLMta8EKLrjPGf/78ed555x1c111w7I2M1ppSqcTMzAy2bTM7O4vn\neaRSqfBBbxea1X6zmtrwcrc3IpzNZsnlcgB0dXXxm7/5mzzwwANYlsWFCxcASKfTNSJcLpcZGRnh\nyJEjHD58mNdff52BgQEeeOABPvnJT9Lf38/ExASu65JKpcLrUkrh+z4TExMcOXKE5557jjNnzpBM\nJslms6ETFH05mJDQzMwM+Xy+5jo32nMTC6H3fZ+5uTksy6JSqeA4DqlUikKhEHpl7Ypt26GgZ7NZ\nbr/9du68887w+rTWOI6z6DUawzUP1Pe+973wIag/9kYjer9832dmZobz589TKBSYmZnB932SySRB\nEIT3K+40Eqo0Ymjuy0qPtZqXQrTxNJFIcOutt3LDDTcAcP311y+577lz58jn85w4cQLLsujq6uKm\nm27iPe95DwB79+5dct9SqUS5XObkyZOMjo6STqfp7e0NawrRMJJ5tgqFwoqurROJhdAbj14pRaVS\nIQgCKpVK6OVHH+p2E/2o4aXTafbv3899991HNptldnY2fEjqr8vcC8dx2LRpExMTE7zzzjv84Ac/\nWPTYG43o/QqCgGKxyPT0NEEQMDs7WyP07eTRR2mk01T9vksdK/qCWOm56p/Lubm5cNnzvJp2k+j6\n2dnZGifO9/0FYux5Ho6zUJ6mp6eZm5urCcuZUI/v+wtqxr7vt51mrAWxEfpSqVQjboVCgWKx2PYe\nfRStNZVKhWKxiFKKUqkUClG9gUbvRSKRoFQqLfDeO+W+rIb67Czbtkkmk+EnCILwBboRG2Prr3k9\n7kFU1BcTabPetFNFM+3qXwhL7Z9IJBZk6EX/Rp0fk7opxEToTSOlUoogCEJxM9kT7UzUmywWi7z2\n2mvYtk0qlaJYLKK1XrTRyex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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0bd2b0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3055,23 +2003,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.751 \n",
-      "FIRE        0.753 \n",
-      "RIGHT       0.762 \n",
-      "LEFT        0.757 \n",
-      "RIGHTFIRE   0.768 (Action Taken)\n",
-      "LEFTFIRE    0.755 \n",
+      "NOOP        0.391 \n",
+      "FIRE        0.377 \n",
+      "RIGHT       0.366 (Action Taken)\n",
+      "LEFT        0.430 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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KYQ/YbGu8/1YRM9klRnzNcTpp/OZY1Wo1eNporV1j6pbcqt2daEu9Xm9K1TTHMRk27fCX\nf/mXnWim0CFWkikmdJZICH0sFmPPnj3dbobQo4Q7+ISNwzg5YefAOESmQJ95Og6HFOv1unjzHSYS\nQg9EoQTtDSGWWxEerdnOtq316FsLfrXO0tOOZ9+6bbvt7qRX39rJul7HEjaOcAjTLC+1jvmt5Tde\nHyIh9GZyjVbWcnGvZJvWddYyX6UJc4RFeqWdRkttaz43y63C3k5JYLOP1u8MqystcLN2t9Mus6/l\nvnP4WGshCk7EVuZm4x5Mn5SwvkRC6GH5Yf1rieOtZJvWdcLLN+vsXK5TcKmOzKX2tdS+l1teybqr\nYaltl+snWG272423LnfT69T+BWErEwmhtyxrQ/PohRuJSmhkPdohFRGFrU4khH41YQ9BWC1RuIEJ\nQjeJhNDD8qV3xRsTVoo4C4KwNJER+psh8VnhVojXLgjLE1mhN6NVzUCadkaDCr2LsQtTJkGGzAvC\njURO6MOTV8P1+usGEXwBls4KMqORW21IELY6kRN6aK79Ei4UJgjLYQqwAWuqcCkIvUykhD782G3e\nm/lVTaExYWuzlCdvHAIzlD7s2YtXLwgREvpwyVulFIlEgmKxyJkzZ3jhhReYmZkhmUxi23Yw0k6E\nf+thOl3NdIflcpkdO3bw0EMPce+99wZ2Ey5NIQhbncgIPSwKt6lNbkaZ/uIXv+CrX/0qExMTQb1y\nM+WdCP3WI+wIlMtlSqUShw8fZmhoiHvvvbcpPm8qiwrCVidSQg83psnlcjmmpqYAmibgELY2YTuY\nmpqiUCg0/d/cEEToBSGCQt9KIpFgaGiIcrkcTFggHv3WxfzuyWSSUqmE7/sMDQ3hum7TeiLygnCd\nyAl9q3jbth3UEzcTcJhHchH6rUc4b95xHKrVKrFYTDKzBOEmRE7oW72wer0eTC9XrValrKkANJe3\nrVarUopYEG7CmlMSlFL7lVLPKaV+qZQ6q5T6fOPzbUqpHyulzjX+jrTbyE6WwxV6g/W0iY20bUHY\nCNrJPfOAf6G1vgt4P/BPlFJ3AV8AntVaHwGebSx3DBF6AdbdDrpi24KwXqxZ6LXWV7XWrzTe54A3\ngb3Ax4GvN1b7OvCJdhoowi5sNBtl24KwUXRkNIlS6iBwD/AisFNrfbXxrylg5zLbPK6UOqWUOjU7\nO3ur/XeimUKPsp720a5tr1vDBGEVtC30Sql+4PvAP9VaZ8P/04s9q0vmuGmtn9Ba36e1vm9sbKzd\nZghCx+mEbW9AMwXhlrQl9EqpGIsXwje11k82Pp5WSu1u/H83MNNeEwVh4xHbFnqJdrJuFPBV4E2t\n9X8M/esp4DON958BfrD25gnCxiO2LfQa7eTRfwD434DXlVJnGp/9KfDvgO8opT4LvAt8sr0mCsKG\nI7Yt9BRrFnqt9c+B5XrBPrTW/QpCtxHbFnoNqeEqCILQ44jQC4Ig9DiRF3ozF2h4WRDCdiCzSAnC\nzYm80IPUuhFuRGxCEFZO5KpX3qxMsW3bTbNPyTRxWw8zd7CxA9/3pUyxINyCyAn9UmWKTTnaer1O\nvV4PHtWlNO3WRGvdZAe1Wk1sQRBuQuRd4mq12jRNnNSiF6DZDgqFQjBngUEmphGE60TOo2/Ftm3i\n8TgAlmUFU8jd6kJeaiq55T4LE/7/Svex1OcrXa+1HTfbh1leybpLbbOW9oWPdbPp+ZZq03KE97Pc\n/pd77/s+lmWRSqUoFov4vk88Hse27RuOLR33grBI5IS+VXjHxsa48847mZiYYHh4GNd1qVQq4rFt\nUczvbuwgnU5z6NAhRkdHpYNWEJYhUkIf7mA1nW4HDx7kgx/8IDMzMyQSCRzHwfM8EfotivndjR2U\ny2V27tzJgQMHgOuplqbDXhCECAm9eSRXSmFZFp7nAbB3715+8zd/k1wuh+M4wQUsQr81Mb+7Ugrf\n9/E8j4GBAfbu3QsQ2I2xDcmxF4QICX0r5gLt7+9n9+7djIyMYFmWpFQKAb7v4/s+iUSCvr6+4DOT\ndikIwiKRFXrjkdXrdSqVCqVSCdu2xYsXAkyapVIqSK80nr4gCNeJrNAbjNBXKhXx6IUmjEfvOE5T\nHr149ILQTOSF3nEckskkQODRSyebYLx4rXXQSS8IwtJE9uowGTiu6zI0NEQqlQo6a6UzdusS7ow1\nBe9isRiu60qmjSAsQ2SEPhySMamVcH3AlKltIh69ADQJvamBBDdWO5VQnyBESOiXw6RbGg9fhF6A\n5tGyxi4EQViayAu98dCMlyZCL0CzRy9euyDcnMgLvcHE5c17QTA2EbYNQRBuJPJCb0I34dRKeUwX\n4LodSOhGEG7OphB6M9FEONtC2NqEq3KalyAISxNpofd9vylcE06tBPHstyLhm7yEbARhZURa6E2o\npjVlziAX+daltT692IIgLM+mSVcw3rt48QKIPQjCaoisR288NDNgygyikhi9ADSF8SzLahowFUZq\n3ghChIR+uXxoU4NeEG6G2IggLE9khB6axd68dxxHipkJy2Lsol6vBwPrwjYkCELEhH4pbNsmFot1\nuxnCJkCEXRCWpu3nXaWUrZR6VSn1dGP5kFLqRaXUuFLq20qpeJv7b7eJwhZgPexkvW1bEDaKTgQ2\nPw+8GVr+c+AvtNZ3AAvAZ9vZeWsuvVmW19Z+LWUX68C62rYgbBRthW6UUvuA/xX4t8A/V4tu1QeB\nTzdW+Trw/wB/tdJ9mgvWxFk9z8PzvE33WH6zYflGoDbbd4oq4Y7YTs0utR62LQjdot0Y/X8C/hUw\n0FgeBdJaa6+xPAnsXWpDpdTjwOMA+/fvv6EDzXSyVSoVyuVyMFXcZpomzgj6UkhIqj3CdmDbNolE\nAtd1m85rm5k4HbHtXsSUJIHrNm7Oe+vTlhAN1iz0SqmPADNa69NKqUdWu73W+gngCYCTJ08uaRW+\n71OtVsnlclSr1U2VfXOrcIIU4mqPcLZNPB4PZiPr0L47ZttKqegb6yox2XCts72ZidlrtdqmuEa3\nEu149B8APqaUehRIAIPAl4FhpZTT8Hz2AZfbaWDYQ6jX65vGozfZQmFPp9XrCU9oLawOYwdh+zCz\nTXWADbHtzUb45nor290sDtlWYc1Cr7X+IvBFgIbX8y+11v9IKfVd4PeAbwGfAX7QTgMtywrSKzfD\nDFNa66DNZrBXa7+DeVLxPK/pBiCsnNY5Yzs5YGqjbHuzsdprL+rX6lZiPfLo/wT4llLq/wVeBb66\nlp0Y8avX69RqNarValCTfjN49KVSadlOZNu2g0dfYW0YOzDndzmb6LCtdMS2Nxut53rXrl3s2bOH\neDxOuVzG8zwSiQSO45DP57l06RKZTAZojt0L3aMjQq+1/inw08b788ADq91HawkEYyDlcpnZ2VnK\n5XIwQXjUjMbEJpVSOI5DtVplamqKqakpisUisVgM27YD4R8YGGDv3r2MjY2hlKJerwdPAlH7blHF\nnPN6vU4qlcJ1Xfr7+7Esq6MhsU7Y9mbHcZwmp+X+++/nk5/8JGNjY0xPT5PL5RgbG2NkZIS33nqL\nb3zjG7zyyisAxGIxfN/H87ybHUJYZyIzMrb10dss53I5Ll++TDabDQQzah69EWvLskgkEuRyOV57\n7TXOnDlDPp+nr6+PeDxOsVikUqmwc+dO7rvvPo4ePYrjOFQqFbTW2LYtQr9CjKDXajWGhoYYGBhg\n+/bty9qRsHZaEwf27NnDAw88wJ49e5iYmCCdTrNv3z527txJIpHgb//2b5u2FZvuPpERekO4Bx+g\nUqmQzWZZWFggHo9j23bgsUUl9KGUwvM8bNsmlUqxsLDAuXPneOmll6hWqySTSZLJJJlMhnq9ztjY\nGNu3b2fXrl3EYjGKxSJaaxzHkYviFhj7sCwLz/Oo1WoopahUKoCECjaCcrnMwsICruuSTqdJp9P0\n9fXhOA6ZTIZarRasK79DNIic0LdeqCYcYjo3TZGz5apddgPTZsdxcF0Xx3Go1+tUq1VgMV5fq9WC\nG1SpVEJrTSwWIx6PB+loIvS3xvzuYS8z3N/RmtcttE/rE3Q2m+Xy5csopUin0ywsLACLdj0zM0O5\nXA7WNemXQneJnNCHCWewxGIxXNcNRD5K2SrGwzQplfF4nFQqRSKRCIzexDkB+vv7SSaTxOPxYH1A\nQjcrIOzRm1TKm5WyjlqYbzPSep25rsvAwEBg48lkkoGBAQYHBwPPPrxtVK7TrUzkhD58ISulKBaL\nXLt2jWvXrkVa6E3oxoRoSqUSsViMcrkcCJFJN7MsK/CKYrEYpVIJEKFfCWH7qNfrVCoVPM8LzmF4\n+snwsrB2WmP027dv54477qC/v5/5+XkGBwc5cOAAO3bsYGpqqmngWlSu0a1OpITeCGF4iPXMzAxn\nzpzh0qVL9Pf34zhOEAOMkhGF6+eXy2UuXboUePOm09CITz6fZ3x8PMgkiuL3iSrmHMZiMWq1GoVC\ngQMHDnDw4EGApqH5ksfdGVrDL5lMhqtXr7Jjx47gJnvt2jW01mSzWYnRR5BICT3caBjT09O88sor\nnD9/nuHh4SAcEiWPPozxNHO5XGDwWusm4y8UCpw/f57p6ekgTVBYGeZ3N3awsLDA3Nwc73//+29Y\nT+gM1Wq1yUZ/9KMfUSgUePTRR9m1axdnz57lySefZGBggGq1yszMTLCuSR0Wukukhd54CJcvX6ZY\nLFIsFpvi3psV3/eDbAVhbYTt4PLly+Ryuab/i7h0DiPyqVSKcrnM9PQ03//+97nzzjs5fPgwFy5c\n4Bvf+AZAkCxhkPz5aBA5oV+K8EUb9oyFrUtYQETUN4ZKpRKI/r333svdd9/N2NhY0/k3ZcVbkTBa\nd4l8T5XjOCQSiWBZphUUgKbMDjP8PkwUw3qbldbxKw8++CB/9Ed/xLFjxxgfH2dycjJYd3R0lIGB\ngWC5tXNc6A6R8+hbL9Bwx6zp/Q9nr0SVW+UPm1zwlawrXMeUmgjbgSlfLawPJhxjMpsOHz7Mbbfd\nxtmzZ/nKV77Cc889x44dO/jjP/5jDh8+zLe//W2eeeYZAIaHhykUCsGANqE7RE7oWwUvXCfDFFbq\nhRmawkWihNXROrnFZpyBbDNhKq0arl27xgsvvMAbb7zBc889Byw+aT/22GMcP36cn/3sZ8G6ZtS3\n0F0iJ/SCIEQD88TUGnN/7bXXuHDhAoVCIfjMPJXW6/WmJINyuRzpJ++tQuSFvldH1oXDUOLdt0cv\n2kcUCI9ZcF0X3/cpFotcuXKFK1euMDAwEJQw9jyP+fl5lFLcdddduK6L67rs2bOHK1eukM1mAemU\n7RaRF/peIWzglmUxNDTE4OAgSikKhQLpdLpp4JRcDEK3aJ2/ee/evRw9epS5uTleffXVoFM23Ddi\nwmmWZfG5z32O+++/n6GhIcbHx/nSl77E2bNngcXyCeG6T8LGIM9UG0T48dVxHPbu3cvJkye5//77\nOXToUFNmkcwnK3QTU7PJsGfPHk6ePMnhw4cDuzTTZBrBrlQqvPDCC0xPT7Nr1y4+8pGP8NBDD/HI\nI48wNDQU7Esm3OkOIvQbRKvQ7969m7vuuovjx4+zd+9eqQ8iRIpWGzST/oQ9+PDAxWw2y5e+9CU+\n97nP8fzzzwefz83NScZNBBChFwQhwHjpYRE39abOnz8fhHNMjRulFCMjIwCk02n++q//mnfeeSfY\nVsI00UBi9BtEuLPV8zyuXr3K2bNncRyHS5cuNXk9Ep8XukE4OSDM5OQks7Ozy4p2eH1TrtjQ19fX\nVBJB6A4i9BtEq9Cb+ixKKfL5fJMHFc4RF4SNwCQAmIGIQ0NDKKXIZrOUy+Um+wwnC7SGcIaHh3nt\ntdc4evQoqVSKZ599tind0vM8se0uIEK/QYSN2/d9MplMkHJmMhaWWlcQ1hsz+tzkyw8PD3P8+HEq\nlQqvv/568Hn4ZhAm/DQ6MzPDV77yFb71rW9h2zbZbJa5ubmmdcW+Nx4R+i4hefNCVAh3vMZiMQ4d\nOsThw4eZnp4Okggsy8J13aAMwnJUKhWmp6eZnp5u+jw8YZCw8YjQC8IWpXXAXiKR4LbbbmPPnj3B\nnAomJh8uRbIWpEO2u4jQd4nW9DXxdISNpjUMY1kWg4ODVKtV3n77bS5evBhMcA8rKxGulCIejwfp\nwrVaramp+tO+AAASLUlEQVS8sdAdROi7hAi7EAVMCQNYDNtYlsXc3By/+tWvgj6kcIniW6G1plqt\nNt0gxNa7jwi9IGxRbNsOsmtqtRqjo6PB5PbhgmVmesyVIsIePUToBWELEfbgbdtmcHCQoaEhPM/D\ndd0gAywejwcdrxJ22fyI0AvCFiLcN6SUwrIsYrEYsViMUqlEOp0ml8s1ibt0pG5+ROgFYQsRDqvU\n6/WmDtZCocCVK1eC+HrY+xc2N23VulFKDSulvqeUeksp9aZS6jeUUtuUUj9WSp1r/B3pVGMFYaPo\nVdtu9dQty8JxHFzXxbKstlIohejSblGzLwM/1FofA04AbwJfAJ7VWh8Bnm0sC8JmoydtO1xDPhaL\nBQXMSqUS9XqdeDwerCudqr3DmkM3Sqkh4GHgHwNoratAVSn1ceCRxmpfB34K/Ek7jRSEjaSXbTuV\nSpFKpbAsi1qtRj6fp1AooJTC87ymeLwIfe/QToz+EHAN+C9KqRPAaeDzwE6t9dXGOlPAzqU2Vko9\nDjwOsH///jaaIQgdp2O23W3CBciUUriuy/DwMLFYjGw2y9TUVFPOu9CbtBO6cYCTwF9pre8BCrQ8\nyupFC1vSLdBaP6G1vk9rfd/Y2FgbzRCEjtMx2173lt6C8JzL4aJkSxUnE3qXdoR+EpjUWr/YWP4e\nixfHtFJqN0Dj70x7TRSEDadnbDss6KaoWLi4WLhWvExh2busWei11lPAJaXU0cZHHwJ+CTwFfKbx\n2WeAH7TVQkHYYHrJtlu9dqUUjuNgWZYI+xai3Tz6/wv4plIqDpwH/g8Wbx7fUUp9FngX+GSbxxCE\nbtATtm3mevV9PygVXCgUsG2bcrnclE4pOfO9S1tCr7U+AywVh/xQO/sVhG7TK7Ydj8fp6+vDcRxq\ntRrlcrmpVrzkzW8NZGSsIPQQ4SwbWPToXdcNJg3J5/OSZbMFaXfAlCAIEcZ0vtbrdXzfl5j8FkWE\nXhB6iKVSJk2KpSliZpDO2K2DCL0g9DhhMQ/fCCSPfusgMXpB6CFs28Zxrl/WWusgy8bzvKbOVxH6\nrYMIvSD0ELZtk0wmicfjeJ5HsVgkk8mgtZYwzRZGhF4QegilFLZtY9v2DaUOxIPfukiMXhB6CJNl\nY17ixQsgQi8IPYfJrgkXNDOfi/BvTSR0Iwg9RrhwmWTZCCBCLwg9gZkS0LIsSqUS5XIZrbWUOBAA\nEXpB6AkcxyGRSASZNoIQRmL0gtADmLh8eOSrIBjEKgRhkxLuWPV9P5jzVTpchVYkdCMImxAzgYgR\nda015XK5afYoQTCI0AvCJsQMjIrFYmitqVar1Gq1bjdLiCgi9IKwSZG8eGGliNALwiZEa029Xg/e\nm1GwErYRlkKEXhA2IVprarVakCffOjhKEMKI0AvCJsGEaZRSS458FYTlEKEXhE1AuColQL1el1Gv\nwooRoReETYDWOihzYKjX6+LRCytChF4QNhFSW15YCyL0ghBxTBql7/tBrrwMjBJWgwi9IEQc27ZR\nSlGv1/F9v9vNETYhUutGECKO8ejFgxfWigi9IEQck0Ypo2CFtSJCLwgRxkwJKAjtIEIvCBElPPcr\nSKaNsHbaEnql1D9TSp1VSr2hlPqvSqmEUuqQUupFpdS4UurbSql4pxorCBtFFGzbiLzv+5IzL7TF\nmoVeKbUX+L+B+7TWxwEb+APgz4G/0FrfASwAn+1EQwVho4iKbZtiZZJtI7RLu6EbB0gqpRwgBVwF\nPgh8r/H/rwOfaPMYgtANumLbJsPGZNlIvrzQCdYs9Frry8B/AC6yeBFkgNNAWmttinBMAnuX2l4p\n9bhS6pRS6tTs7OxamyEIHaeTtr2a44bnfTVCLyIvdIJ2QjcjwMeBQ8AeoA/4nZVur7V+Qmt9n9b6\nvrGxsbU2QxA6TidtexXHbKpOKZOKCJ2knZGx/wtwQWt9DUAp9STwAWBYKeU0PJ99wOX2mykIG8qG\n23Y4s0a8eKHTtBOjvwi8XymVUotW+iHgl8BzwO811vkM8IP2migIG05XbVti80KnaSdG/yKLHVOv\nAK839vUE8CfAP1dKjQOjwFc70E5B2DC6advi0QvrQVtFzbTW/wb4Ny0fnwceaGe/gtBtumXbUtNG\nWA+keqUgRAARd2E9EaEXhAggQi+sJ1LrRhC6iKRQChuBCL0gdAkReWGjEKEXBEHocUToBaFLSFxe\n2ChE6AWhi4jYCxuBCL0gCEKPI0IvCBFAOmaF9USEXhAEoccRoReECCCxemE9EaEXhAghdeiF9UCE\nXhAiiIi90ElE6AUhQpgQjoRyhE4SKaGXx1ZhrSxlN5vVlkTkhU4TqeqVS026sNWMfi3itNXO0VKE\nbce8NzM1CRuDmdR8OVqfVsJ2ayZGv9W25r3Y/OqIjND7vo9t202fbbUfMzwp9Gq+u1l/q52vmyHn\nY+OJxWLE43GA4AYbngvXTI9o3tfrdXzfRykVbBu25dZ5dM32ZtuV/r5iBxESeuMNhD2CrRbKEXFa\nO2FbUUph2za2bW8p++kWRpwrlQqVSmXV22utqVarVKvVdWidABGJ0Yc92fAj3FYTemHtGHEHcBwH\ny7JE7DeIm4VchGgQCY9ea029XgcWH/nMY1/4fa9jRMk82azEszcC5vs+nucFj7ZbEXMOADzPo16v\nU6vV5ClpHbEsKwij2LbN3r172b59O0Dg2TvOosR4nke5XMbzvOB9Pp+nXC7jOA7bt29nx44dxGIx\narVasE+lFL7vU6lUqNVqTdtWq9XAMWwN9xiMhmwVHVmOyAi9+RGr1Sr1ep1UKkWlUgku3l7Gtm2G\nh4fZvn07w8PDxOPxQLjh+gVl/hocx0FrTSaTYXZ2lvn5+S35+Ku1plwuk8lksG2bbDaL53m4rhsI\n0VZjtU8xq1nf2GIqlSKfzwPQ19fHH/7hH/KpT30K27a5cuUKWmsGBwdRSjE3N8elS5e4du0a8/Pz\nnD9/ntOnTzM+Ps7Q0BC///u/z6c//Wl27NjBzMwM5XKZvr4+4vE4+XyeS5cuMT09TSaT4Z133uHV\nV1/l0qVLxGIxEolE8Du3fo9qtUqhUKBUKq3qfPQakRD6er1OoVDAsiyq1SqO4+C6LsViMfDKeo2w\naMfjcXbv3s19993HsWPHGBgYoFQqUa1WgxCEubi01nieh+M4JJNJarUa58+f59SpU8E20NwJ1ouE\nv1e9XieTyXD16lWKxSKZTIZ6vU48Hsf3fWq1WhdbujraDTOFvdrV7GstNwbjrcNiR+z73vc+fu3X\nfg2A22+//YZt3nnnHSYnJ4ObwPj4OACu63LnnXfy67/+6wAcOnTohm2np6eZmJjg2rVrKKWYmJhg\nZmYG13VJJpPBdRH+HlprLMuiXC7f0PZevS6WIxJCbzx6pRTVahXf96lWq4GX35patdlpvajMo+vx\n48f5wAc+wLZt24LHWtu2cRwnyE4wnV6u6zI4OEipVGJoaIirV69y4cIFMplM0zF64XwtRfh7+b5P\nqVQinU7j+z7ZbLZJ6DerR79UKGKt2y23L/P5Wo7Vel0WCoVg2ThoJgsnn8+TzWbJ5XIUi0UqlUpT\nuLZYLDbtu1wuk0gkgn1nMhlyuRyFQiEIAZkMHPOq1+tN/QUSsrlOZIS+XC4HQu84DsVikVKp1LMe\nfRhjsLVajVKpRKlUolwuUyqVlhT6Wq2G7/vEYjFKpVJw0fT6eQrTmp1l2zbxeDx4mfOzVrHsNdbj\nHLTuM5webc59eNlxHBzHCfqiwvtpTa2OxWJN/zfbhfuxzP9abcEgncTXiYTQmx/SdLw4jhMYRi/+\nWK2C7Hke09PTnD59mnQ6TV9fX9D5tNQgFBO6SSQS1Go1Ll68yMWLF5seUbea6MdiMZLJJKlUKrgR\nGsHfrDa0VnFez5DNzfYTFufWfbuui+u6xOPxJcW+Vehbl+PxOLFYrEkXwmJvWdaS14rc5BeJhNCb\nzshwjH54eBitNalU6oa7fy8QFuJqtcqVK1colUq8+eabOI7TNJhkqUwCE7uv1+sUi0XS6XRTh1Ov\nC31rjD6dTjM5ORk84oc9+s3UQd2J363dfazkKaj1vFYqFZ577jn6+vqwLIvp6WkA+vv7UUqRTqeZ\nmppifn6edDrNpUuXmJubA6BUKvHSSy/xne98h9HRUebn56lUKiSTSWKxGMVikampKWZnZ8nlckHH\nrHniN0/9S3XGmv938vxsRiIh9OZCVUpRq9WwbRutdSBevRajb8X3fXK5HPl8flUjY8PrbbXUynDs\ntVKpcO7cORKJBIlEIrAZY0e5XK6LLe0eq7WH1Vxnpl/EUCgU+PrXv853v/vd4P+mM9QsG+fFpMIa\nAc5mszz55JP88Ic/DJyX8LZGxM3n4ey8sCO0XJu30nWxHJEQ+rm5Ob75zW8CBB0qyWSSYrHIqVOn\nmjpqNmvH2q2QfO/VERb6crnMW2+9xfT0dJDNFA7ZZLPZbjWzpzH2asQ5l8ut6abq+z6FQqGpM3e1\nbRBujorCiYrFYnp0dBS4/thovNVisUihUJDec+Gm3GwUdcO77ErMTynV/QtM6GlWYtu3FHql1NeA\njwAzWuvjjc+2Ad8GDgITwCe11gtq8Ur7MvAoUAT+sdb6lVs2Qi6GphIQhlulxIWX5Yng5ix1MYht\ndxbT2QqdLWpm9idFzZZmRU5MWCSWegEPAyeBN0Kf/XvgC433XwD+vPH+UeC/Awp4P/Dirfbf2E7L\nS17r+RLbllevvlZkhys01oM0XwxvA7sb73cDbzfe/3/Ap5Za72YvpZSOx+NNL9d1dTwe17Ztd/1E\nyiv6L6WUtm17yRcsfzGwzrbd7fMir95/rUTD19oZu1NrfbXxfgrY2Xi/F7gUWm+y8dlVWlBKPQ48\nbpY3UwqcED201p3qqO+4bQtCt2k760ZrrdcSh9RaPwE8AVsrjilsHsS2hV5hrUMGp5VSuwEaf2ca\nn18G9ofW29f4TBA2C2LbQs+xVqF/CvhM4/1ngB+EPv/f1SLvBzKhx2BB2AyIbQu9xwo6k/4ri3HI\nGotxyc8Co8CzwDngfwDbGusq4D8D7wCvA/dJZoK8ovAS25ZXr75WYoeRGDAlcUxhvdEyYEroUVZi\n25uzrJ8gCIKwYkToBUEQehwRekEQhB4nEtUrgVmg0PgbNcaQdq2GKLbrQBePLba9eqRdK2dFth2J\nzlgApdQprfV93W5HK9Ku1RHVdnWTqJ4TadfqiGq7VoKEbgRBEHocEXpBEIQeJ0pC/0S3G7AM0q7V\nEdV2dZOonhNp1+qIartuSWRi9IIgCML6ECWPXhAEQVgHIiH0SqnfUUq9rZQaV0p9oYvt2K+Uek4p\n9Uul1Fml1Ocbn29TSv1YKXWu8XekC22zlVKvKqWebiwfUkq92Dhn31ZKxTe6TY12DCulvqeUeksp\n9aZS6jeicL6igNj1itsXOdvuNbvuutArpWwWi0X9LnAX8Cml1F1dao4H/Aut9V0sThf3Txpt+QLw\nrNb6CIsFr7px0X4eeDO0/OfAX2it7wAWWCzI1Q2+DPxQa30MOMFiG6NwvrqK2PWqiKJt95Zdr6Ty\n2Xq+gN8AfhRa/iLwxW63q9GWHwAfZpnp5TawHftYNKwPAk+zWElxFnCWOocb2K4h4AKNvp7Q5109\nX1F4iV2vuC2Rs+1etOuue/QsP0VbV1FKHQTuAV5k+enlNor/BPwrwG8sjwJprbXXWO7WOTsEXAP+\nS+PR+/9XSvXR/fMVBcSuV0YUbbvn7DoKQh85lFL9wPeBf6q1zob/pxdv5xuWqqSU+ggwo7U+vVHH\nXAUOcBL4K631PSwO9W96nN3o8yUsT5TsutGeqNp2z9l1FIQ+UlO0KaViLF4M39RaP9n4eLnp5TaC\nDwAfU0pNAN9i8RH3y8CwUsrUKurWOZsEJrXWLzaWv8fiBdLN8xUVxK5vTVRtu+fsOgpC/zJwpNHT\nHgf+gMVp2zYcpZQCvgq8qbX+j6F/LTe93Lqjtf6i1nqf1vogi+fmJ1rrfwQ8B/xeN9oUatsUcEkp\ndbTx0YeAX9LF8xUhxK5vQVRtuyftutudBI2OjUeBX7E4Tdu/7mI7HmTxcewXwJnG61GWmV6uC+17\nBHi68f4w8BIwDnwXcLvUpvcBpxrn7G+Akaicr26/xK5X1cZI2Xav2bWMjBUEQehxohC6EQRBENYR\nEXpBEIQeR4ReEAShxxGhFwRB6HFE6AVBEHocEXpBEIQeR4ReEAShxxGhFwRB6HH+J2W2xoyuJmxD\nAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f88457e69b0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3080,12 +2028,10 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.796 \n",
-      "FIRE        0.806 (Action Taken)\n",
-      "RIGHT       0.794 \n",
-      "LEFT        0.790 \n",
-      "RIGHTFIRE   0.797 \n",
-      "LEFTFIRE    0.791 \n",
+      "NOOP        0.394 \n",
+      "FIRE        0.386 \n",
+      "RIGHT       0.369 \n",
+      "LEFT        0.436 (Action Taken)\n",
       "\n"
      ]
     }
@@ -3112,7 +2058,7 @@
     {
      "data": {
       "text/plain": [
-       "161"
+       "517"
       ]
      },
      "execution_count": 34,
@@ -3134,12 +2080,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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UHNbVaMeo0U5sez3CI5bDI2NbHWYJlyYGIjkDmdAbNIZuFhcXuXDhAsePH+fS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\nC4Ig9Dgi9IIgCD2OCL0gCEKP8/8B8s+udmS2ndkAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c1334a8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3148,23 +2096,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        2.008 \n",
-      "FIRE        2.006 (Action Taken)\n",
-      "RIGHT       1.995 \n",
-      "LEFT        2.014 \n",
-      "RIGHTFIRE   1.996 \n",
-      "LEFTFIRE    2.006 \n",
+      "NOOP        1.289 \n",
+      "FIRE        1.206 \n",
+      "RIGHT       1.333 \n",
+      "LEFT        1.653 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Y/1pS48L7KqVqHpywUOVPJpM4jtPwuep7YwqtwzgE5n/NZrO8+uqrt93P2LKIfGuIhNAP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\nl42nncvluHz5MtPT08GxVyv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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c2c9c88>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3173,23 +2121,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.982 (Action Taken)\n",
-      "FIRE        0.977 \n",
-      "RIGHT       0.975 \n",
-      "LEFT        0.977 \n",
-      "RIGHTFIRE   0.968 \n",
-      "LEFTFIRE    0.980 \n",
+      "NOOP        1.073 \n",
+      "FIRE        1.088 \n",
+      "RIGHT       1.106 \n",
+      "LEFT        1.239 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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nMkqg3qM3opZIJEin02QyGYBAgJcj/H06nSaZTBKLxQLhA5YN3YQzWmKxGMlk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\neDx4iAh3D7Zt1024vWPHDo4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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0d1748>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3198,23 +2146,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.048 \n",
-      "FIRE        1.047 \n",
-      "RIGHT       1.052 (Action Taken)\n",
-      "LEFT        1.032 \n",
-      "RIGHTFIRE   1.043 \n",
-      "LEFTFIRE    1.043 \n",
+      "NOOP        0.563 \n",
+      "FIRE        0.589 \n",
+      "RIGHT       0.629 (Action Taken)\n",
+      "LEFT        0.553 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SKWKxWODNxmKxoJbT29sbHNuEe9Y6drPXxIit4zhBuXp7e5mbmwMIYvEAPT09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\nOnSIoaGhunZArXUQMjbORG9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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c14f908>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3223,23 +2171,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.053 (Action Taken)\n",
-      "FIRE        1.058 \n",
-      "RIGHT       1.056 \n",
-      "LEFT        1.051 \n",
-      "RIGHTFIRE   1.058 \n",
-      "LEFTFIRE    1.055 \n",
+      "NOOP        0.506 \n",
+      "FIRE        0.514 \n",
+      "RIGHT       0.564 (Action Taken)\n",
+      "LEFT        0.548 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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PhR4gmUzau7g5vvGYATtA2fx9TLuNR5rP55mamiIWi9mewWpCbwwrmUwyNzdH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\n",
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tjAOD1Lm/HfhZ4BtKqa+13/uvwG8Af6yU+jBwA/jgYCYKwqEjvi0cefoWd631/wV2SnS+u992BWHUiG8L44DM2RYEQRhDRNwFQRDGEBF3QRCEMeRIiLssFCbshtxiTxC2cyTEXdaWEXZD/EMQtnOklvw1d2iSKE0wfqC1lhuoC0IPEi/udpfbrN8t4i7YfiD+IAjbSXxaJgxDfN/veC0Ith/4vi9+IQhdJD5ydxwHz/OArbSM3CBbgPs3yNZa43me3GZPELpItLinUiny+TwnTpyIhN2+u73kWY8f5v9u/CAIAk6cOEE+n5f76wqCReLE3Qi21hrHcSgUCly6dIn5+XlSqRRKqW1dcBH58ac7r25f5KempigUCh2D7eITwnEnUeJun5hG3Kenpzl//jyNRkNOWGEbWmuy2SxTU1M4jhNF9lL7Lhx3EiXu0BlxKaXIZrNMT0/TarVE3IVtaK1Jp9PkcrltviMIx5nEiftOSBQm9MJE6OIfgtBJ4sXd1LaHYSjRmLANmfsgCL1JvLinUilc140GUc1AmnC8sf3AdV0phRSELhIr7iYSc12XTCaD626ZagbLhOON7QeO4+C6rviGIFgkVtzh/roy5sSVtIzQjamqkshdEDpJtLjDfYE3Ne6CYCOT2QShN4kXdxvpcguCIOyPIyHu9tKu/dDrd3KhGA+kDFIQenMkxN2kZuLsfktXfnyQ/6UgbCfx4m7fqOOgJ/FeE1yGcdEQRsNx+x/ahQbAtjV1giCQ1VOPOYkXd5t+ut/7EW/p1gtHDa11x30Oen0uHG/GWtxTqVRUZWPXQJvnZj1wORGOLsctYof7/rsfv5Xa/+PLkRL3ftIy++maHkeBEI4uBxFrEfbjS+LF3eQW9+uk9pKv9XqdUqlEvV6P2jIRj+u65PN5Jicn8Txv4IqcYZDUKp+djtGobDsO4yZmrocJVmZnZ/mO7/gOTp06RavVolqt4jgOExMT+L7Pa6+9xquvvtoxi1dy8MeLxIu7PXnJPoFtIe5ew9s48traGjdu3GBlZQUgWqMmCAJyuRwXLlwgn8+TTqejxaeSMNNxvyJ52IKWBLu6L8BJuyAPi+5bTM7NzfHOd76T7/zO76RSqbCyskI2m+XEiRPUajX+6q/+im9961si7seYRIu7PTN1rxPY3KHJROUmmrl16xbXr18nDMNIxJvNJjMzM+RyOS5evBi9HwRBIm7Vtlc+dVSR6n7ssv8eFsdh2d/u/7mJ0guFAo7jUKvVyGQyzMzM4Hke2Wx22++F48XA4q6UcoAXgdta6/crpR4CngPmgZeAn9VaNwdov2PtkDAMt0XX5j0TvZsI3fd9NjY2WF1dBTpXEmw2m5TLZWArovd9P9qWkHxsPzAX5rjFfdi+fRC6L17NZpONjQ0WFxepVCqsra1FC+xVKpXIt+3fC8eLOHIQzwCXrdcfB35La/1twDrw4UEa765zdxynoz69W/y7a9dtp+713PQO7B7CqB9mmeN0Ok06ncbzPDzPi56bY9C9v4dll22L/dxe4G3YD9sPbD+JmaH69kHp9t9Go0GlUqFardJoNPB9n2azSa1Wo9ls7vhb4XgwUOSulDoP/DvgY8Avqq0z7Engp9tf+Qzw34Hf6XcbJmLZT77Q/q6J0O1I3PO8aHKHWQPcRH3mbxIwNyfpdUIeJFUVN/aNU3phXyQP264hRO1D9+0+bIqeu67LzMwMp06dolKpRGlHUyAwNTW142+F48GgaZnfBn4ZMJ40D2xorc3sigXg3CAb2O9MO2Xl3E1Kxvf96A5OvU7+MAxptVo0Go1I4EeRlumuvy+Xy2xubkZVPuYipLXG8zymp6eZnp7G87xIaId18tqDzLVajY2NjajLb9vlOA6Tk5MUCgUymcxIqo9i3tbQffsgdF/Mlbp/f+FUKsXq6ipa6+j4nzhxouP7SSgUEA6XvsVdKfV+YFlr/ZJS6l19/P5p4GnYKuvqhZmFZ0R6L+wyR9/3qdfr+L4fiad9oQiCgGazSb1ej77XK59/WNhVPnfv3uXatWusra0BdIwh5PN5Ll68yIMPPsjExESUax6GiJrjaY7JvXv3uHbtGnfv3sX3/egGKr7vk06nOXfuHJcuXWJ6ehroPT4yDFKp1LZ01SDE6dtxYYIWQ6PR4ObNm2SzWWq1Gqurq8zPz+N5HpOTk2QyGdseidyPIYNE7m8Hfkwp9T4gC0wDnwQKSim3HeGcB273+rHW+lngWYALFy707FObFEuz2SQIgm0OakTbiJsRbiPutrDDfSe3xd4IvJ2uGZSd8vy2HfZz+3ZxzWaT1dVVrl69yp07d4D76STf9ykUCqTTaR544IHoYhBXCWe3rUZQzDyDjY0Nbty4wbVr12i1WlGE3mw2yWazhGHI3Nwc2Ww2+t/1StPEKTTmominq2IgNt9WSsWSL+pO062vr/PCCy/wla98hTAMOXnyJO94xzsi3280Gt02xWGGcIToW8m01h8FPgrQjm7+i9b6Z5RSfwL8BFtVBU8BXxzEQCMwRii66R7wM2mY/ealzUljHnHdn3U/A33mhDPbNPnser3O5ubmtooH85tqtRpduOIeJ+hlt3nu+36UMgKoVqvRd2q1GuVyOfo/2eki+4Iad358t7RbvxyWb/dhV/S8XC5z5cqV6HWpVOI973kPZ8+e7ehVGSRyP34Mo879V4DnlFL/A/hn4NODNrhTVLZTRYfjOPuOZntVycTBbu3ZAtctomYfbNttsey2176gxYHZbvc2TYRs22WLqrmPqf0dx3GiMYxh1aEf8uBy7L4dF47jkE6nyeVyBEFAOp3u+FzE/fgRi7hrrf8O+Lv286vA98bRLtyvYTZ16L0+M9Fr9wzVSqWy58p5pm0zoBqHAJl2TZvGbpM+UkpF1Tr2oCQQReT2wK7papsUCRDZbaeeBrXdttvuyZi0jKnKMPaY933fx3GcKLLf2NjYlpYx5Ytx5cVtm4GhVToN07cPin0xnZycZH5+Htd1CYKAQqHA5cuX+cIXvoDruly5cqXDL3Y7D4TxJLEzVI0j+75PtVql1Wpt6+I3m02KxSLVarVD4I1g3r17l1qtFrXZnQs3s1iz2WwkxAfJXRtbbJuUUrRaLcrlMuVymVar1fFdgGw2y9TUFBMTE9HJCVsi3mg0ouqdXnabCp9qtRrl4nv1UvYj9L3sLpVKlMvlSAy6B1SNwBtbDEEQUCwWWVhYoFQqRRcsI+SmPC+fz0dr+ex0DPeD+b6pIPI8b9s+jROml2b8YmJigje96U08+uijNBoNLl++zPPPP8+XvvQlcrkc9Xq94//TXfcujD+JE3dbEMxEjXK5TL1e3xbxVSoVFhcXWV5exvf9DoELw5BarUalUulo245mGo0GpVIpuhh0l0IeRCTMd1OpFPV6neXlZRYXF6nX61GEbgRzZmaGM2fOdEReQLRsQqVSiS4KQEfdvu/71Go1isViFB0PMqBq9yZqtRpLS0ssLy9HdtuYUkhji30B8n2ftbU1giAgk8lEF0rz3Xw+z+nTpzlx4kT0OfSfLrDFPZvNks1mmZiY6EgDjVMqwvR8zDE3g+sXL16kXC5z+fLlaAC+F47jkMlkosKDZrMZ2/iSkEwSJ+42JnKv1+vUarWOKE8pRblcZnl5mYWFBZrNZnRim1RI94Sb7sjdtG3WlrHF/aDRn9mm4zhUq1Xu3bvH7du3KZfLUTrCiHulUiGXy5HL5Uin01HKJZ1O02w2abVaHXZ3i5SphjAXhkHE3ba7UqmwurrKrVu3qNVqHUs6mGOymyBUKpXo/2TsNr+ZmprC8zzy+XwsFyVb3JVS2yqjxpHu/TOzUU3v1KTLoHPMxPzWBEDDWKpBSB6JFvfdMOLdarWiyT4HiUR6Obd9MRhkoM6UB9br9Y5afYOpq7e3mwTMomqmS39Qu3ar3uneZ+Fg2IviTU1NceHCBVzXjS7CuVyOfD7P5uYmmUyGVCrVkZI0/1sbu4csjB+JF/fdBNYepItjQK27ImeQlIGpHjHpFTuSMoOp5rvdlTEH3dagJ6e9n67rdqSKBm3X2Gb2uVd1kIjL7tiD7rlcjscee4xLly4xNTUVjUUB0cWz0WhEYxC7Icd9vEmkuNsDbCYvXqlUtgmDqYYxXU0jHnbt804ObLdtvmcW6zIpFHtgcy+hNzabiKnRaES/MTl3u56+Xq9HYwnmpDTd6lqttuuAqrHbrvDp90Jk212pVGg2mx127/d4Gmw7zD7bK3EWi8VoUlr39w+CbU8QBMzOzsZWNZQkTKBgj3Pk83mmp6cJgoCrV6+yubnJ9evXox5srzbe/OY387a3vY3Z2VmuXbvGP/7jP3Lz5k2AqHQ4KT1IIR4SJe7d1RthGFKpVFheXmZ9fX1bVGsE0gjFTvn1Xu/Zba+trZFKpaK1UUx3d3NzM5qoY7a9k5Dadvu+T7FYjKJ2e6IUbEVWa2tr0YWpe5+NAPayOwgCSqUSS0tLUXQWh7jDlviWSqXoYrPX8dypPYNd4tlqtdjY2ADouLPWQe22L0YmdTQ7O8vc3Ny24zAuvQJ7H8yAvQk8bty4wTe/+c2ocMDss+d50ThEKpXi/e9/P7/+678OwOuvv84zzzwTibupXuqe1SocbRIl7tBZvWEL2fLycjRBxixFEATBtpKv/RKGIaVSiUajEdWVFwoFWq0WnudRrVZZXV2lVCoBRPXlO00YsoXFRNd2jtk+QY24l0qlbRc0U6K5m7gXi8WOapa4xL2X3YNg223EvVqtDmS3adNEs6by4/z589vmFIwDZsxGKcX09DQPPPAASqloyQfT4zLYvViDUopHHnkkev3II49w4sSJ6LXdMxDGh8SJezeNRoNisRiJbHcVQL+YSMXuygZBEIm7KfsbRjQThmHH1P2DYFI6O3XBk0rcdtt+kMvlaDQaYydQ9j5mMhnOnz/P2bNnyWQy0fwP2Kp5N897zUHQWnPt2rXo9Y0bN6Ib2ABSPTOmJF7cuysw4jyBux3a1JebmnSZ+JFcbD+Ia2Zx0rDF3XEccrkcMzMzAKytrbGyssLy8nLUk7VTf81mM3oehiF/+Zd/yfr6OnNzc7z++ut84xvfiLZjz6kQxofEi7sZUDIM80a/ZtEuIfnYftC9Fs+4YF/AWq0WxWKRe/fukUqlWFhY4OrVqx3VWPYFrjsl+NJLL/HSSy/13E5SblIjxMuREHd7Ukx3aWScZYC92hokl32Qbcf120EZdgQ8qN32mIw9qW0c6V4+4M6dO9GM6s3NzY6Ie6f/225pzHEbnxA6Sby4dy8ZEHcXfK+2hun4g7R9VE/IOOzu9oP9lGgeReyJdGEYRusVGWxx3mn/7Ul55h635sYv43jMhPskXtwF4bhgV045jsPU1BTT09O4rku5XObevXsdKZSDRN5G3M14kgyijj8i7sJYMA6pGVvcwzBkcnKSs2fP4roua2tr1Gq1vqvGupfAEMaf8RuFEoQxwIwluK6L53k7Lt0gCDshkbsgJAQ7TZLNZmk2mywvL+O6bjThziAVLsJeiLgLwoixc+epVIpCoUAul6NarXLjxo3oO1KPLhwEEXdBSAB2rj2TyZDL5SiXy7Lei9A3knMXhBHTXbXSz1r6gtCNRO6CMGLMgKnv+3ieFy1SZ8+6NYt7SfmisF9E3AVhxKTT6ej2g0opPM+LJhsZRNSFgyLiLggjJpVKRdG7uR2efftISM6tGIWjg4i7IIwY++bs5h4G1WpVonVhIGRAVRAOme7JR+YmI2aikr3ui0xWEvpFxF0QRoy97ICpdTdI9C70i6RlBOGQsRcHM4On5XKZarUa3Tqw1/cF4SCIuAvCiEin0+RyuejG5AZJwwhxIGkZQRgR9hrrNhKpC3EwkLgrpQpKqc8rpf5NKXVZKfX9Sqk5pdTfKqVea/+djctYQTgsDsO3d7pphkTuQhwMGrl/EvhrrfUbgDcDl4GPAM9rrR8Fnm+/FoSjxtB924i75NiFYdC3uCulZoAfBD4NoLVuaq03gA8An2l/7TPAjw9qpCAcJqP2bYnchTgYJHJ/CFgBfk8p9c9KqU8ppfLAKa31Yvs7S8CpQY0UhEPm0HxbKYXjOKTTaTzPI51Od5RCCkK/DOJFLvDdwO9orViF2AoAAA3GSURBVN8KVOjqpuqt/mXPPqZS6mml1ItKqRcrlcoAZghC7MTm27ttxC57dF2XdDrdc4BVEPphEHFfABa01l9tv/48WyfEXaXUGYD23+VeP9ZaP6u1fkJr/UQ+nx/ADEGIndh8e7eN+L5PvV6PbsJxkBteC8Je9C3uWusl4JZS6rH2W+8GXgH+HHiq/d5TwBcHslAQDpnD8m2t9bYbV5uVIQVhUAadxPTzwB8qpdLAVeA/sHXB+GOl1IeBG8AHB9yGIIyCQ/Pt7ojdcRyUUgRBIKtBCn0zkLhrrb8G9Op6vnuQdgVh1Bymb2uto8XDzABr93rugnBQZPkBQRgxQRCgtcZxHFzXjaplJPcuDIKIuyAkADtKt1eJtJ8LwkEQcReEhGDukWoGVR3Hid6XFI1wUGS2hCAkCHtdd0AmNAl9I54jCAlGUjJCv4i4C0KCkdvsCf0i4i4ICSeVSkl6RjgwMqAqCAnFrDtjbp4NyMCqsG8kHBCEhGKWJ+gl8oKwFxK5C0LCMdG65N6FgyBhgCAcAUwNvCDsFxF3QThCSPWMsF9E3AXhiCECL+wHEXdBOCLIMgTCQZABVUE4QkjeXdgvIu6CcMQQgRf2g6RlBEEQxhARd0EQhDFExF0QjjhSOSP0QsRdEARhDBFxF4QjjgywCr0QcRcEQRhDRNwFQRDGEBF3QRCEMUTEXRDGDKmeEUDEXRAEYSwRcReEMUOqZwQQcRcEQRhLRNwFQRDGkIHEXSn1n5VS31RK/atS6o+UUlml1ENKqa8qpa4opT6nlErHZawgHBbi28JRp29xV0qdA/4T8ITW+k2AA/wk8HHgt7TW3wasAx+Ow1BBOCzGzbeleuZ4MmhaxgVySikXmAAWgSeBz7c//wzw4wNuQxBGwdj4tgywHk/6Fnet9W3gfwI32XL8TeAlYENr7be/tgCcG9RIQThMxLeFcWCQtMws8AHgIeAskAfee4DfP62UelEp9WKlUunXDEGInTh9e0gmCsKeDJKWeQ9wTWu9orVuAX8GvB0otLuyAOeB271+rLV+Vmv9hNb6iXw+P4AZghA7sfn24ZgrCNsZRNxvAm9TSk2orRGbdwOvAC8AP9H+zlPAFwczURAOHfFt4cgzSM79q2wNLr0MfKPd1rPArwC/qJS6AswDn47BTkE4NMS3hXHA3fsrO6O1/jXg17revgp87yDtCsKoEd8WjjoyQ1UQBGEMEXEXBEEYQ0TcBUEQxhARd0EQhDFExF0QBGEMEXEXBEEYQ0TcBUEQxhARd0EQhDFExF0QBGEMEXEXBEEYQ0TcBUEQxhARd0EQhDFExF0QBGEMEXEXBEEYQ0TcBUEQxhARd0EQhDFkoJt1CEJS0FqP2oQDo5QilRosvtJaE4YhAKlUiq27AvbfhjA+HDtx78f5DUdRQI4jWuvokWRc1yWdTpNKpSJ79/JPs0/motBsNmk0GqRSKbLZLK7rEobhnm2Zz5VSBEFAvV4XgR8zEivug4jwbiT9hBf6w/iLESzzPIn/b2NXq9Wi1WrF0mYYhlSr1VjsEsaDxOTc7ZOy+31B2A8mmjW+ZD+SRL/pk2GTVLuE/khM5B6GYUfkYLqWcUYSqVQqeuy3XWOT1pogCCSySShhGBIEQfQw/6ckpWeMcAZBAMD8/Dxnzpwhm83SarUIggDHcXb9fRiGhGFINpsF4O7du9y+fZtsNsvFixeZmZmh0Wjg+z6O42yLxu02XNfFdV1KpRILCwtUKhVg6zyRFM3RJxHirrXG9/0o/2dOAt/3YxNUpRQTExPMzMxEJ4Zp145WTC7S/kxrTa1WY3Nzc+CurxA/YRji+z6NRgPP8/B9H601juNEQpYE0uk0YRhGqZh3vetdPPPMM1y6dImlpSWq1SoTExORANsopXAch2q1SqvV4sEHHySbzfLss8/yiU98gocffpiPfexjvOMd7+DGjRusr68zOTmJ4zjRxQTAcRxarRaNRoPZ2VlmZ2f5h3/4Bz7+8Y/zta99LbLTXGyEo0tixL3ZbAL3I3hzEgwi7ka0jWAXCgUuXbrE7Oxsx7Z6/c5EfCbKX11d5dq1a5G4S34yOYRhSL1ep1QqRRG8EfckVYJ0R+UXL17kne98JwAXLlzoq823vOUtuK5LoVDgySefZHJykrm5uQO18UM/9EN86lOfil67rhv1gISjSyLEHYhOQPPXCHxcAppKpZicnOTMmTOcOnUqOul3KkUzdpjIx3EclpaWekb1wmgxPb9GoxH9v8yFGUiMuHeniJrNJq1WC8/zAGg0GmQymV3bMBeyiYkJAMrlcrT/xWKRycnJ6H3zvBf1ej3qwW5ubuL7foedwtEnEeJunBM6xT3OtIy9HdNt303c7XI6Oxrs/o6QTMxAatL+R3ZPMZVKRcIOdDzfie7fuK4bvW+e76et7jZkIHX8SIS4Q2cpm/k7aKWDfWKHYUixWOT27dtRtLPbAJZdT6y1Zm1tjUqlkjixELYwvtJdM55k0er2vf1OaOq+IJj9tKP+vXoA9rYzmUzHcUryMRP2TyLEXSkVRQ9mQNWM5MdVnhWGYdT9TKfTwP1c/E7YnzcaDcrlcsdnwuiwj38QBFSrVTY3NzvGaYxYJiV3HARBR4rolVde4bOf/Sznzp1jZWWFer1OLpfrOaAKW4Jcr9dptVqcO3eOdDrNCy+8QKvV4u7du3z2s5/le77ne7hz5w6bm5tMTExEg8qGVCqF7/s0m01mZmaYnp7m5ZdfZnFxMfpOq9VKTCpL6J9EiHsQBJTL5W3iXqlUaDQasTlatVqlXq/39dskldQJnbRaLe7du4frumQymUjM7QtzEjBFA4avfOUrvPzyy9EApt3b6OVr9kC/ScGYc+T69ev86q/+Kul0OrqI9Gqru1gglUrRbDYplUrRd5JyvITBSIS412o1/uVf/iWKWEz3ul6vc+fOnQ5nG1RgJSIZD7oHJldWViiXy1GFjE3SxMpE07VajVqtFkubvu9z7969WOySIGY8UHv9I5VSvwu8H1jWWr+p/d4c8DngEnAd+KDWel1thUqfBN4HVIF/r7V+eS8jXNfVhUKhe7sEQUCj0ZB1L4R9sVOKrR2pbvvwMHxbKSVKKQyVXr4N+xP3HwTKwO9bJ8AngDWt9W8opT4CzGqtf0Up9T7g59k6Ab4P+KTW+vv2Mu4wTwBZOOx4soO4j9S3Pc878MJh7X2JxqIajYYsHHbM2UncO0r+dnqwFcX8q/X6VeBM+/kZ4NX28/8N/FSv7+3RvpaHPIb5EN+Wx7g+dvK9fhcOO6W1NsPrS8Cp9vNzwC3rewvt9/bEXvfFfkhZlrAfei0W1mcpZOy+LQijYOABVa217ietopR6GnjavJYuoTAIw0iZxeXbgjAK+o3c7yqlzgC0/y63378N2ItknG+/tw2t9bNa6ye01k/0aYMgDAPxbWEs6Ffc/xx4qv38KeCL1vsfUlu8Ddi0uriCcBQQ3xbGg30MCP0RsAi02MozfhiYB54HXgO+DMy1v6uA/wW8DnwDeGKfA7YjH5SQx3g/xLflMa6PnXxvz1LIw0BqgYVhs2O52JAR3xaGzU6+nZjb7AmCIAjxIeIuCIIwhoi4C4IgjCEi7oIgCGNIIlaFBFaBSvtv0ngAsesgJNGuB0e4bfHtgyN27Z8dfTsR1TIASqkXkzjpQ+w6GEm1a5Qk9ZiIXQcjqXbthKRlBEEQxhARd0EQhDEkSeL+7KgN2AGx62Ak1a5RktRjInYdjKTa1ZPE5NwFQRCE+EhS5C4IgiDERCLEXSn1XqXUq0qpK+1bm43KjgtKqReUUq8opb6plHqm/f6cUupvlVKvtf/OjsA2Ryn1z0qpv2i/fkgp9dX2MfucUip92Da17SgopT6vlPo3pdRlpdT3J+F4JQHx633blzjfHge/Hrm4K6Uctlbb+1HgceCnlFKPj8gcH/glrfXjwNuAn2vb8hHgea31o2ytGDiKE/UZ4LL1+uPAb2mtvw1YZ2tFw1HwSeCvtdZvAN7Mlo1JOF4jRfz6QCTRt4++X+9n2dJhPoDvB/7Gev1R4KOjtqttyxeBH2GH+2oeoh3n2XKmJ4G/YGv52VXA7XUMD9GuGeAa7bEb6/2RHq8kPMSv921L4nx7XPx65JE7Cb03pVLqEvBW4KvsfF/Nw+K3gV8GzL0I54ENrbXffj2qY/YQsAL8Xrtb/SmlVJ7RH68kIH69P5Lo22Ph10kQ98ShlJoE/hT4Ba110f5Mb122D63ESCn1fmBZa/3SYW3zALjAdwO/o7V+K1vT7Du6qod9vISdSZJft+1Jqm+PhV8nQdz3fW/Kw0Ap5bF1Avyh1vrP2m/vdF/Nw+DtwI8ppa4Dz7HVff0kUFBKmbWBRnXMFoAFrfVX268/z9ZJMcrjlRTEr/cmqb49Fn6dBHH/J+DR9gh5GvhJtu5XeegopRTwaeCy1vo3rY92uq/m0NFaf1RrfV5rfYmtY/N/tNY/A7wA/MQobLJsWwJuKaUea7/1buAVRni8EoT49R4k1bfHxq9HnfRvD068D/gWW/en/G8jtOMdbHW1vg58rf14HzvcV3ME9r0L+Iv284eB/wdcAf4EyIzIprcAL7aP2ReA2aQcr1E/xK8PZGOifHsc/FpmqAqCIIwhSUjLCIIgCDEj4i4IgjCGiLgLgiCMISLugiAIY4iIuyAIwhgi4i4IgjCGiLgLgiCMISLugiAIY8j/B+M+1QYAMcuCAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c256908>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3248,12 +2196,10 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.050 (Action Taken)\n",
-      "FIRE        1.028 \n",
-      "RIGHT       1.035 \n",
-      "LEFT        1.041 \n",
-      "RIGHTFIRE   1.022 \n",
-      "LEFTFIRE    1.043 \n",
+      "NOOP        0.503 \n",
+      "FIRE        0.513 \n",
+      "RIGHT       0.559 (Action Taken)\n",
+      "LEFT        0.520 \n",
       "\n"
      ]
     }
@@ -3280,7 +2226,7 @@
     {
      "data": {
       "text/plain": [
-       "217"
+       "115"
       ]
      },
      "execution_count": 36,
@@ -3302,12 +2248,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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D3HXXXfzKr/wKrutSLpfRWuM4Tsvy+L6Pbdvkcjny+TwvvPACV65c\niY4XP7bQPvH/IAgClpeXmZubo1Qqsby8TBAEpFKpyPtLIsYmzG85fPgwn/3sZxkfH+fChQt4nsfI\nyAgAnufheR779u3j6NGj2zrf0aNH+fDDD3Ech/vuu4/jx49v6zj5fJ7XX3+dUqnEyMgIqVSKarUK\nXLtWYL73PI9yuYzv+5sKXWmtsW0bx3FQSlEoFK5qmHZdl1wuRyqViq7rZrx7y7IIgiByMuMPAhMO\n9H3/qgfEThL9RAi98eiVUnieRxiGeJ4XefnxC9rNixs3uGw2y/Hjx/nCF75AJpOhUCigtcZ13ZbV\nO/OA2rNnD5cvX2Z2dpaXXnop+j7pceKdRvw/CMOQcrlMPp8nDEMKhUKD0CfVo2+2o2q1ysrKCrZt\ns7Kygud5kSdbqVTwfZ9MJkOpVCKXy23qHL7vR2GeWq1GsVikUqmwsrISbWPCO+sRhmHDvbG6uhqF\nToxAbtaJMccx4TXjebeqKZvtm9eHYdiQShvPTDKeuQkHmwfBRlk6QRA0lCV+vPjnnSTszSRG6CuV\nSoNglkolyuVyTz365jJ5nkepVEJrHXn0xiDixMttYqHNDyihszRnZ9m2TSqVil5hGEYP5Z3ykLUs\nK2oXMvFw07BsapLGxjaLEXlY83hNDDu+fiORN+VqtWwcmHjoZj3vvFU83Xw2YtxqX7M+Hoa51v9p\nPPS4t99qn+ZaxrWy/naaFx8nEUJvDM80tBhjNkbeK+KeX6lU4u2338ayrIbQzXo3hTGsbDbLysoK\nZ86cibwc6WDSXZRSuK5LNpsll8tF3qYR/J2S1eI4TsPDCiCVSjV4talUaktC34zruriuGx1/O6TT\n6eh+tSwrip3D+qGbuKg3v8cfHOuxmUy8VoK92TaDaz0UdoqzsB6JEHrbthkbG2uI0Y+NjaG1JpfL\nNdyo3bzgcTFeXV3lzTff5KOPPoo8hI3ObzxH490sLCw0xIZF6DtLc4w+n88zMzPD8vIyKysrDR69\n53l9LOn6BEHQ8Dvee+89nnjiCYaGhsjn89RqtagxtlarEQQBIyMjHDhwgNHRUYIgiGLHzXZpvE/P\n80in04yNjTE3N8cLL7wQNaJevnwZWIu5m4dlc6MlrMXTbdtmz549lMtlXnrpJT766CPm5+dZXV2N\nEhDi+7QiXrsyna6Mg7QRJmxiaiPVajUKa8WdqGq1GoWmmhuVr9XByoSh1muMrVarPQshd4NECL25\nUY1B27aN1pp8Ph950oZuXuD4sT3P48KFC8zNzW2pyhbPEogbzU4zjKQTv7bVapUzZ86QyWTIZDIN\ntS+tdUM8Okk0NxK/+OKLvP7665EH3xx2imeeGAHarF2Zht9KpUIQBLz88suk02lg805IPJOnUqls\nOaUyznZj3vGU1HhaNqzpiAkBb+XYm9leYvQdYGFhge9///tAYwikVCpx4sQJSqVStG0vG9bEC08u\n8f+mUqnw3nvvcenSpUgk4yGbQqHQr2JuClNmI6C9oFwu9+Q8vWSni3E3UUm4MK7r6snJSeDqcTVK\npRLFYlFEV9iQjWK3de+vL0FWpVT/bzBhoNmMbV9T6JVS/xn4MnBZa/2Z+roJ4K+AI8A54Pe01ktq\n7U77DvAIUAL+Z631G9csREJvhngmQHMLfTOtUrGS8BAV1mh1MyTNtk0SQjz81xy6ac4dvxZxx6l5\nULPN9q6N/Zao17cMapYcNuXExEWp1Qt4ALgTeDu27v8BvlH//A3gW/XPjwD/H6CAe4FXrnX8+n5a\nXvLq5ktsW16D+tqUHW7SWI/QeDO8Dxyofz4AvF///J+Ar7babqOXUkqnUqmGVzqd1qlUStu23fcL\nKa/kv5RS2rbtli9Y/2agy7bd7+sir8F/bUbDt9sYu19rPVf/fBHYX/98EDgf226mvm6OJpRSjwGP\nmeWkpsAJOwPdlIHRBh23bUHoN21n3Wit9XZi7Frrx4HHIbkxemF3I7YtDArb7TJ4SSl1AKD+frm+\nfhY4HNvuUH2dIOwUxLaFgWO7Qv8k8LX6568BT8TW/4Fa415gOVYNFoSdgNi2MHhsojHpB6zFIWus\nxSW/DkwCzwJngL8DJurbKuA/AB8Ap4C7JTNBXkl4iW3La1Bfm7HDRHSYkjim0G20dJgSBpTN2PbO\nGNZPEARB2DYi9IIgCAOOCL0gCMKAk4jRK4F5oFh/TxpTSLm2QhLLdWMfzy22vXWkXJtnU7adiMZY\nAKXUCa313f0uRzNSrq2R1HL1k6ReEynX1khquTaDhG4EQRAGHBF6QRCEASdJQv94vwuwDlKurZHU\ncvWTpF4TKdfWSGq5rkliYvSCIAhCd0iSRy8IgiB0gUQIvVLqS0qp95VSZ5VS3+hjOQ4rpZ5XSr2r\nlHpHKfXH9fUTSqmfKqXO1N/H+1A2Wyn1plLqqfryTUqpV+rX7K+UUqlel6lejjGl1I+UUu8ppU4r\npe5LwvVKAmLXmy5f4mx70Oy670KvlLJZGyzqN4DbgK8qpW7rU3F84F9orW9jbbq4f1ovyzeAZ7XW\nt7A24FU/bto/Bk7Hlr8F/KnW+lPAEmsDcvWD7wD/XWt9HLidtTIm4Xr1FbHrLZFE2x4su97MyGfd\nfAH3Ac/Elr8JfLPf5aqX5QngYdaZXq6H5TjEmmE9BDzF2kiK84DT6hr2sFyjwEfU23pi6/t6vZLw\nErvedFkSZ9uDaNd99+hZf4q2vqKUOgLcAbzC+tPL9Yp/D/xLIKwvTwJ5rbVfX+7XNbsJuAL8l3rV\n+y+UUkP0/3olAbHrzZFE2x44u06C0CcOpdQw8GPgn2mtC/Hv9NrjvGepSkqpLwOXtdav9+qcW8AB\n7gT+XGt9B2td/Ruqs72+XsL6JMmu6+VJqm0PnF0nQegTNUWbUspl7Wb4vtb6b+qr15terhf8GvCP\nlFLngB+yVsX9DjCmlDJjFfXrms0AM1rrV+rLP2LtBunn9UoKYtfXJqm2PXB2nQShfw24pd7SngJ+\nn7Vp23qOUkoB3wVOa62/Hftqvenluo7W+pta60Na6yOsXZvntNb/BHge+J1+lClWtovAeaXUsfqq\nLwLv0sfrlSDErq9BUm17IO26340E9YaNR4CfszZN2//Zx3Lcz1p17C3gZP31COtML9eH8n0eeKr+\n+SjwKnAW+Gsg3acy/TJwon7N/l9gPCnXq98vsestlTFRtj1odi09YwVBEAacJIRuBEEQhC4iQi8I\ngjDgiNALgiAMOCL0giAIA44IvSAIwoAjQi8IgjDgiNALgiAMOCL0giAIA87/D3v3Rsp254W5AAAA\nAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c278908>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3316,23 +2264,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.531 \n",
-      "FIRE        0.466 \n",
-      "RIGHT       0.695 (Action Taken)\n",
-      "LEFT        0.507 \n",
-      "RIGHTFIRE   0.407 \n",
-      "LEFTFIRE    0.543 \n",
+      "NOOP        0.627 (Action Taken)\n",
+      "FIRE        0.617 \n",
+      "RIGHT       0.605 \n",
+      "LEFT        0.585 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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KUYVrOI1Gg6tXrwZevRm/aLNCbM7V1GhKpRJ33HEHhw8fBmiaaarXfS6E/sM4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\nOSL0giAIfc7/D4oTSAUqWcXyAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c1e1860>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3341,23 +2289,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.462 \n",
-      "FIRE        0.746 (Action Taken)\n",
-      "RIGHT       0.673 \n",
-      "LEFT        0.544 \n",
-      "RIGHTFIRE   0.561 \n",
-      "LEFTFIRE    0.626 \n",
+      "NOOP        0.585 \n",
+      "FIRE        0.589 (Action Taken)\n",
+      "RIGHT       0.566 \n",
+      "LEFT        0.564 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Dhw8DNM001e8+F8LgYYQeVjsVUSZSQg+rb9rMzAyvv/4658+fZ3R0lGQySaVS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\nz/MoFouBJ2D+YaVSKfDKdjp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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c07aa90>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3366,23 +2314,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.258 \n",
-      "FIRE        0.317 \n",
-      "RIGHT       0.035 \n",
-      "LEFT        0.463 (Action Taken)\n",
-      "RIGHTFIRE   0.183 \n",
-      "LEFTFIRE    0.227 \n",
+      "NOOP        0.378 \n",
+      "FIRE        0.380 (Action Taken)\n",
+      "RIGHT       0.375 \n",
+      "LEFT        0.360 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SQg83nrRr165x6tQpzp8/z+joKMlkknK53FOPPoyJ1ReLRVZXV4PlN3tsC39f\nKBQ4f/48165dCzJ6Nnts0x8QTmMMC2qhUOC9995jdnZ2S/tuB3NOCoVCg9CHvXvXdbly5QrZbLat\nsRDm/27sYHl5mcXFRR566KEb1hOEbhLup4o6kRZ6M6x+ZmYmKHdrLvBBxvd9stlsEN/vJJ7nsby8\nzPLycsf3vVVahW7MU1C7hO1gZmbmhs5wEXqh25in/EGwtcgJfSvCJ9KEIoRbm/BTzCBcaMLg0+y5\nm3pNgyD2ke+pMp2QBplWUIA1uzAkk8mGzyDplULnCWfZhEd+R13kIYIeffMFGu6YNb3c4WH4/aLd\nu3g7sb2bHbtfccNetMt0AIftoDl/XxC6wXo1bcw4jigLf+SEvvkk+b4fPKY3n8go563ejG4+7kX1\nUbJT7WoekRjFGciEnUe45IF5b0qGm0SJarUayWsvckIvCIIQRcJCbwg/XUY5AyfyQh/lkydEA7EP\noVc0P5Wa9OZw4cMoEnmhFwRBiAKt4vPhUtxRFXkQoRcEQdgU680VMQiI0AuCINyEm5W/NjWnejVf\n81aJfB69IAhC1DE1nDo0OX3HEaEXBEHoAFFNawYJ3QiCIGyKjUTcjOWIYtgGROgFQRBuys08dZNi\nGVWPXkI3giAIHcCUZQlPbRkVROgFQRA6RCKRaFlkr9+I0AuCIHQApRSxWGzDOYz7RbRuO4IgCBHi\nZvnzzZjqqlGL1YvQC4IgtGCrcXatNZVKJRg4FSVE6AVBEFqwnXmpwzOfRQkRekEQhHWIWghmu0Sr\nx0AQBEHoOG0JvVJqVCn1PaXU20qpt5RSH1VKjSulfqSUOlf/O9apxgpCrxDbFraLUopkMkkqlYpM\n7Zt2PfpvAv9Xa303cAJ4C/g68LzW+hjwfP2zIAwaYtvCpgnH8o3Qp9Pphnz6fg6i2rbQK6VGgEeA\nbwForata6yzwReA79dW+A3yp3UYKQi8R2xbaxbbtSOXTt9OKo8B14L8ppU4rpf6rUmoI2Ku1nq2v\nMwfsbbWxUupJpdRJpdTJhYWFNpohCB2nY7bdo/YKfaa507ZSqVAqlajVan1qUSPtCH0MuA/4fa31\nvUCBpkdZvfbrW3Zba62f0lo/oLV+YHJyso1mCELH6Zhtd72lQuTwfZ9isUg+n29It+xnBk87Qn8F\nuKK1frn++XusXRzXlFL7Aep/59troiD0HLFtoS3MCFnbtiMRvtl2C7TWc8BlpdRd9UWfAt4EngGe\nqC97AviszOgSAAAUk0lEQVR+Wy0UhB4jti20g1KKVCrF6OgoY2NjDA0N9V3s2x0w9feBp5VSceA8\n8HdYu3n8D6XU14D3ga+0eQxB6Adi28KmCde3CQu9ZVnk83kqlQrVavWGdXtFW0KvtT4DtIpDfqqd\n/QpCvxHbFtrF930sy0Ip1ff69FICQRAEoU3CHrrWmnK5HIh7qVSiUqn0q2mACL0gCEJHMUJfqVTQ\nWuP7/g3f9xoRekEQhA5jxN2yrKAUguu6VKvVG4S/F4jQC4IgdIhwR6tlWYyNjTEyMoJSinw+z/Ly\nciD0veyU7X+CpyAIwg4kFosxNDTErl27SKVSfZ1HVjx6QRCELuD7PrVaLQjX9CNkYxChFwRB6BDh\nUIzruiwvL6O1JpPJEIvF+pZmKaEbQRCEDmNGwpbLZfL5PLZtMzQ01LeyxeLRC4IgdJiwiPu+j+M4\nWJbVUApBhF4QBGGACYdwlFJBueJwnL6X+fQi9IIgCB0mLOi1Wo35+XmUUnie13KdbiNCLwiC0EVq\ntRrLy8t9bYN0xgqCIOxwxKMXBEHoAaYzVmvdEMLpBSL0giAIXSJc5iCdTjM5OYnneczNzQUdtJZl\ndT1eL0IvCILQBcxUgmbe2GQyyZEjR3Bdl2w2K0IvCIKw07Asi3g8jmVZPa97I0IvCILQBZpr0ZdK\nJS5fvky1WiWXyzWs121E6AVBELpEWOgLhQLvvfdeELJptU63EKEXBEHoAVprlFKMjIzgOA6VSoXV\n1dWGScW75d2L0AuCIHQBMym48djT6TR33HEHhw8fxvd93n//fc6dO9fQKduttEsRekEQhC4RzqhJ\np9McPXqUD33oQ+Tzea5fv95Q2KybRc5kZKwgCEIP8H2fSqVCsVikXC4HaZeGbnbKikcvCILQBZpH\nwObzed5++208z2NsbIxkMtmwvnj0giAIA4jWOsibr1arXLx4kcuXLzM0NMTevXtxHCdYN1yrvtOI\nRy8IgtBFjNCbUI3ruoyOjhKLxUin0xQKhe63oetHEARBuIVpHjhl2zblcpnV1VWq1WpP2iAevSAI\nQhfxfb+hozWXy3H69GkWFhZYWVlpWK9biNALgiB0Ea11g9DPzs4yOzt7w3rNWTidpK3QjVLqHyml\nziqlfq6U+u9KqaRS6qhS6mWl1LRS6o+UUvFONVYQeoXYttBpbNtuKGa2e/duPvOZz/Doo4+ya9eu\nhvU6zbaFXil1EPgHwANa63sAG/h14LeB39FafwhYBr7WiYYKQq8Q2xa6gSlbbDh+/Di/8iu/wj33\n3NMQq4/HO+8/tNsZGwNSSqkYkAZmgU8C36t//x3gS20eQxD6gdi20FVSqRRDQ0N4nke5XA6WR8qj\n11rPAP8BuMTaRbACvAZktdYm2HQFONhqe6XUk0qpk0qpkwsLC9tthiB0nE7adi/aKwwmuVyO5eVl\n4vE4u3fvDpZ3IxOnndDNGPBF4ChwABgCPrPZ7bXWT2mtH9BaPzA5ObndZghCx+mkbXepicKAEu6U\nrVarJBIJPvGJT/Abv/EbnDhxAqVUIPSdnJyknT39VeCC1vo6gFLqj4GPA6NKqVjd8zkEzLTfTEHo\nKWLbQscx1SwN8Xic22+/nc9//vN87GMfo1qtcvbs2SD7Jh6PdywTp50Y/SXgIaVUWq21/lPAm8CP\ngV+rr/ME8P32migIPUdsW+g4zbVsYrFYkG1z4MABRkdHN1y/Hbbt0WutX1ZKfQ84BbjAaeAp4Fng\nu0qpf1Nf9q1ONFQQeoXYttANfN9vqGeTy+U4deoUtVqN8+fP89Of/rRh0FTzTFTt0FYQSGv9r4B/\n1bT4PPBgO/sVhH4jti10Gs/zGoT80qVLfPvb30ZrzdzcHNlstuH7TnbKyshYQRCEHmBGyJr0yaWl\nJZaWlgA4ePAgk5OTzM/Pd2VqQSlqJgiC0EMcx2kYFPWrv/qr/MEf/AG/+Zu/2ZBpk0qlOnZMEXpB\nEIQeYtt2w6CoL3zhC3zuc5/jK1/5ShDDV0qRSCQ6dkwRemEg6ea0a4LQS1ZXV4G1ztluVbCUGL0w\nUCilGmbsCS8XhEGgVqs12OsPf/hD0uk0b775JqlUilqthtaaYrHYsWOK0AsDhenQEo9eGFSas2n+\n7M/+jNdeew3P86hUKsHy8Pt2EaEXBg7f9xuKQIGEcoTBw7KswHNv5b1bltWxUI7E6IWBw7btGzIS\nJHQjDBrNM08100nnRTx6IdIYr0drjVKKO++8k8OHD5PNZjl9+jSe5zWsJwiDgsmw8X2feDzOQw89\nxLFjx3jnnXd48cUXA5uPxWJtj5IVj16INLZtBxeEbdvcd999fPnLX+ahhx7CcZxgvfDQcpBQjhB9\nUqlUkE9frVb57Gc/y+/+7u/yxBNPBOvYtt2RNEvx6IVIE674p5Riz5493HnnnSwtLTWIe7PQC0LU\nsW27wSG54447SCaT3HPPPcEy49G3i1wdQqQJZ9horZmfn2d6epq5ubmGjqpu5R8LQrdorn1z4cIF\nXNflrbfeCpZprYPwZDuIRy9EGs/zAqH3fZ/Tp0+zuLjIyspKQ9yyWeilc1aIOpVKpcGj/5M/+RPO\nnz/Pu+++GyxrnmZwu4jQC5Gm2Wt/5513mJ6eJpFINHg6vu+LuAsDhZlUxBQve+mll3jppZeC783y\nTpQrjpTQN8/AIgjNaK1xXfeGx9lWna+drP4nCN3C5Ms326plWR0J20DEhL7ViMdBvlC3e9Ma5N/c\nCyzLIpFIUCqVGpaHY/nmNWixe2Mz4VK1BpNu1w6t9rvZNt1sWavjtGrzZo59sxzznYQRc5Nh5vs+\nnud1TOQhQkLv+35DRTcYbMFr9+lkkH97NzHndTNCM2jn0NTx2ehJJJyBtBnCQhu+8VmWFVxvNztP\npl3rfW4+llIK3/dxXRetdfCbDM2fW21brVaDkEXzzW+nYmo4dVrkIUJCb/75YQMY5FDOIArNIGCy\nEJonTW5OwzSlYAfJfjqVYbEZjBAPArfKdVSr1To6fWCYSKRXhr20sLcwyEIvdJdW4QDjocZiscBj\nHQSxj3r7hMEnEh592JPxfT94vAy/HzRisRixWGxLHYLmgvc8LyhVKmyOsIdqOmvNOYz6eTTtSyQS\nJJPJIHwBrWP24dHC6007F/5snCfP8yiVSmitSafTQb0gz/Na3mzM9o7jNIxCdhyHRCJxwzFNmMa2\nbcrlMtlsFtd1SSaTOI4TTKMXj8eJxWIN23qeh23bOI5DtVplbm6O69evo7UOriNzTtarYNoJx7DV\nPsPHHFQiI/S1Wg3XdalWq3ieRzqdplKpDMzjZdjoLcti3759HDhwgHg8vuFvCFeoM8a/sLDA5cuX\ng4p2kj2yMVpryuUyKysr2LZNLpfDdV0SiUTQsRVFmqsT7t+/n6NHj+I4DuVyGd/3g1GRxulJJBJk\nMhmSyWSwzAhcK6H3PI9YLEYqlSKfz3Pu3DlqtRrHjx/n7rvvBtYmvjA3kHBM39jt5OQkk5OTwfK9\ne/dy+PBh4vF4QyndarVKOp0mnU5z6dIl/uIv/oLFxUWmpqaYnJykUqmQyWSYmppi165d1Gq1oP3l\ncplEIsHevXu5evUqf/iHf8jTTz9NtVplZGQEy7Iol8vBDatcLuO6boOwx2IxHMe5oT7SerTqv1hP\n6I3jMKhEQug9z6NQKGBZFtVqlVgsRiKRoFgsDoxnG06RisViHDt2jMcee4zx8XFKpRKu694wlNl4\nQOaCSqfTeJ7HqVOnyOVygdDbtj0wN7xe0ewNrqysMDs7S7FYZGVlBc/ziMfj+L4f2Qu0WYQymQz7\n9u0jkUhQKBTwfR/HcVBK4bouvu+TSqUYHx8nnU4HN7GNhN51XRzHYXh4mMXFRRYXFymXy0xNTfGR\nj3wErTUrKysopXAcB9/3g6eFSqWCUooDBw5w6NChQECnpqYYGxvb8LfdfffdJJNJZmdnOXjwIKOj\no1SrVSYnJ7nttts23PbIkSP85Cc/CUJxiUQC27YDr984hM3n0XRmblbowxihX2/g3SBo0EZEQuiN\nR6+UolqtNvS6m5778LpRJGxclmVx5MgRPv7xj3Po0CFyuRy1Wq3h8Rc+EHojRMPDw7iuS6VSaRg4\nIXVcbiRsB77vUyqVyGaz+L5PLpdrEPqoevTNGLuHtY45M0TeeLEmM61SqTSk4W0UsjD7icViwROy\n67qUy2UKhQIAxWKxpdCbthQKBfL5fGDjKysrNxX6arXKrl27KJfLeJ7H0tISnueRTCZbOj3N14cJ\nMZnzYm5cG0080/z9VrQivE1Y3EXoO4h59DZCH4vFKBaLlEqlgfHom3Fdl1KpRKlUolwuByGpVoMi\njNA7jhN4K4PaN9ErmrOzTOzXvIw33Inc815hYummAzn83oidZVlBhlpzymPzvsxvD+8nnPBgPGbz\nXfgzfJAJZzq1zfE2U2TLhCGNM2Pi7LZtt9y+2Qlq/m3bycXf7P99vdDooNjNZoiE0JsKbcagTazN\nPIYNAuH4nud5nD9/nhdeeIHR0dHAq2keJ9C8bSqVwvM8zp49G0wYbPYnrI/xRlOpFOl0Ooj9GsEf\nFBsKi2qz6Ib/mk7L8NNKc7zffDbXkRFYI5omWcDsMxz2MOfL7Dvc+QpsqmyuUor5+XlmZ2eZmppi\nZGSESqVyg6CvR/hm0JyVdzMB3mjQmaH5u62OTxg0IiH0tm0zOjraEKMfHR0NsgM28lyiQrPQnzt3\njqWlpaAmy0aepdnOtu0g9JDL5Rr2LTTSHKPPZrNcuXKFlZUV8vl8g0ffPEdnVGj2IrPZLBcuXAjC\nLCZLBT6wL8dxGBoaIh6PN4Qn1ovRm3BPMplkdXWV+fl5qtUqb775ZjCy2Pw1nbHmejPh1NHRUcbG\nxgL7nZycZN++fUGGjMHzPBKJBKlUipmZGU6ePMny8jKHDx9mbGws6Kw9dOgQmUymZWfs5OQk8/Pz\nnDp1KrjRFItFLMsKQlbhAUXNITwTqtpqFGCjTB6z70EmEkJvLlSlFLVaLTC4bDbbEKuD6MbKmg1u\nYWGBpaWlLadXGmMLG1ZUf3M/CZ+fSqXCuXPnSCaTJJPJwGaMHeXz+T62dH2axWN2dpbr168DtBRt\n834raYStRqsCzM3NBf1Azamc4W2hcRRt+HMr2zbHMn1N5gk9nNHTKu3YfGc6XQuFQhDSNE7Pejpg\n3reqgbQVdvJ1FgmhX1xc5OmnnwbWRN+yLFKpFMVikZMnTzZMnDsoYYxejnK8FQmLZLlc5u233+ba\ntWtByCIcsgk/HUWRcCpkr2zGdMgOAlvxpneyWLeDisKJcRxHT0xMAI0eiNZrM6SbVDNBWI+NvNx6\n2KMvMT+lVP8vMGFHsxnbvqnQK6W+DXwOmNda31NfNg78ETAFXAS+orVeVmtX2jeBx4Ei8Le11qdu\n2ogdeDE0P2JvJ6dX6BytLoao2Xa43tN61+VWOw1bDQqCxrl4N6EBmypqFv6+naJmWmsqlcotV9Rs\nu2zKiWmVe9rUMfEIcB/w89Cyfw98vf7+68Bv198/DvwfQAEPAS/fbP/17bS85NXNl9i2vHbqa1N2\nuEljnaLxYngH2F9/vx94p/7+vwBfbbXeRi+llI7H4w2vRCKh4/G4tm277ydSXtF/KaW0bdstX7D+\nxUCXbbvf50VeO/+1GQ3fbmfsXq31bP39HLC3/v4gcDm03pX6slmaUEo9CTxpPkc1BU4YDHTnOr87\nbtuC0G/azrrRWuvtxNi11k8BT8HOjNELg4/YtrBT2O6QwWtKqf0A9b/z9eUzwOHQeofqywRhUBDb\nFnYc2xX6Z4An6u+fAL4fWv631BoPASuhx2BBGATEtoWdxyY6k/47a3HIGmtxya8BE8DzwDng/wHj\n9XUV8J+B94A3gAckM0FeUXiJbctrp742Y4eRGDAlcUyh22gZMCXsUDZj24NR1k8QBEHYNiL0giAI\nOxwRekEQhB1OJKpXAgtAof43akwi7doKUWzXkT4eW2x760i7Ns+mbDsSnbEASqmTWusH+t2OZqRd\nWyOq7eonUT0n0q6tEdV2bQYJ3QiCIOxwROgFQRB2OFES+qf63YB1kHZtjai2q59E9ZxIu7ZGVNt1\nUyIToxcEQRC6Q5Q8ekEQBKELRELolVKfUUq9o5SaVkp9vY/tOKyU+rFS6k2l1Fml1G/Vl48rpX6k\nlDpX/zvWh7bZSqnTSqkf1D8fVUq9XD9nf6SUive6TfV2jCqlvqeUelsp9ZZS6qNROF9RQOx60+2L\nnG3vNLvuu9ArpWzWikV9FjgOfFUpdbxPzXGBf6K1Ps7adHF/t96WrwPPa62PsVbwqh8X7W8Bb4U+\n/zbwO1rrDwHLrBXk6gffBP6v1vpu4ARrbYzC+eorYtdbIoq2vbPsejOVz7r5Aj4KPBf6/A3gG/1u\nV70t3wc+zTrTy/WwHYdYM6xPAj9grZLiAhBrdQ572K4R4AL1vp7Q8r6eryi8xK433ZbI2fZOtOu+\ne/SsP0VbX1FKTQH3Ai+z/vRyveI/Af8M8OufJ4Cs1tqtf+7XOTsKXAf+W/3R+78qpYbo//mKAmLX\nmyOKtr3j7DoKQh85lFIZ4H8B/1BrnQt/p9du5z1LVVJKfQ6Y11q/1qtjboEYcB/w+1rre1kb6t/w\nONvr8yWsT5Tsut6eqNr2jrPrKAh9pKZoU0o5rF0MT2ut/7i+eL3p5XrBx4EvKKUuAt9l7RH3m8Co\nUsrUKurXObsCXNFav1z//D3WLpB+nq+oIHZ9c6Jq2zvOrqMg9K8Cx+o97XHg11mbtq3nKKUU8C3g\nLa31fwx9td70cl1Ha/0NrfUhrfUUa+fmBa313wB+DPxaP9oUatsccFkpdVd90aeAN+nj+YoQYtc3\nIaq2vSPtut+dBPWOjceBd1mbpu1f9rEdD7P2OPY6cKb+epx1ppfrQ/seA35Qf3878AowDfxPINGn\nNv0ScLJ+zv43MBaV89Xvl9j1ltoYKdveaXYtI2MFQRB2OFEI3QiCIAhdRIReEARhhyNCLwiCsMMR\noRcEQdjhiNALgiDscEToBUEQdjgi9IIgCDscEXpBEIQdzv8H8cb51Kq+mZ0AAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c072550>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3391,23 +2339,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.169 \n",
-      "FIRE        0.261 \n",
-      "RIGHT       -0.042 \n",
-      "LEFT        0.104 \n",
-      "RIGHTFIRE   -0.020 \n",
-      "LEFTFIRE    0.306 (Action Taken)\n",
+      "NOOP        0.225 \n",
+      "FIRE        0.232 \n",
+      "RIGHT       0.232 \n",
+      "LEFT        0.236 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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kZIREIkGlUumrRx/GVNVKpRKFQiFYvl6IIPx7sVjko48+YmZmJsjo2eixTXtA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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c313cf8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3416,23 +2364,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.193 \n",
-      "FIRE        0.247 (Action Taken)\n",
-      "RIGHT       -0.042 \n",
-      "LEFT        0.119 \n",
-      "RIGHTFIRE   -0.032 \n",
-      "LEFTFIRE    0.120 \n",
+      "NOOP        0.197 \n",
+      "FIRE        0.203 \n",
+      "RIGHT       0.217 (Action Taken)\n",
+      "LEFT        0.208 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c178c88>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3441,23 +2389,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.160 (Action Taken)\n",
-      "FIRE        0.154 \n",
-      "RIGHT       -0.122 \n",
-      "LEFT        0.141 \n",
-      "RIGHTFIRE   -0.039 \n",
-      "LEFTFIRE    0.132 \n",
+      "NOOP        0.184 (Action Taken)\n",
+      "FIRE        0.171 \n",
+      "RIGHT       0.188 \n",
+      "LEFT        0.183 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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stvbdCuaaFIvFBqGPevee53HlyhVyuVxLfSHMfTd2sLS0xMLCAo899thN6wlC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\nRugdxwljdFvx6JtvvonPGsO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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c06e7f0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3466,23 +2414,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        -0.076 \n",
-      "FIRE        0.045 \n",
-      "RIGHT       -0.298 \n",
-      "LEFT        0.085 \n",
-      "RIGHTFIRE   0.018 \n",
-      "LEFTFIRE    0.106 (Action Taken)\n",
+      "NOOP        0.187 \n",
+      "FIRE        0.177 \n",
+      "RIGHT       0.194 (Action Taken)\n",
+      "LEFT        0.191 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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6sHfvui7Xrl0jl8t11BfC/O/GDhYWFpibm+OjH/3oTesJQi/ZcXn03SRcYaZb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\nfu6VHrS2DV66dInvfe97HDh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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c1ca9e8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3491,23 +2439,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        -0.075 \n",
-      "FIRE        0.067 \n",
-      "RIGHT       -0.214 \n",
-      "LEFT        0.122 \n",
-      "RIGHTFIRE   0.073 \n",
-      "LEFTFIRE    0.148 (Action Taken)\n",
+      "NOOP        0.149 (Action Taken)\n",
+      "FIRE        0.113 \n",
+      "RIGHT       0.141 \n",
+      "LEFT        0.126 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0c7ac8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3516,23 +2464,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        -0.428 \n",
-      "FIRE        -0.168 \n",
-      "RIGHT       -0.416 \n",
-      "LEFT        -0.043 (Action Taken)\n",
-      "RIGHTFIRE   -0.103 \n",
-      "LEFTFIRE    -0.119 \n",
+      "NOOP        0.140 (Action Taken)\n",
+      "FIRE        0.108 \n",
+      "RIGHT       0.132 \n",
+      "LEFT        0.111 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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N9vzY22W90I15C+qWsB3Mz8/f1Bge9QdP2P3sJo9+VwQwwzfShCKEvU34LWY3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\nc6tneKfP+FaP3y9MZWvCar0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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c30c358>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3541,12 +2489,10 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        -0.179 \n",
-      "FIRE        -0.293 \n",
-      "RIGHT       -0.518 \n",
-      "LEFT        -0.155 \n",
-      "RIGHTFIRE   0.095 (Action Taken)\n",
-      "LEFTFIRE    -0.152 \n",
+      "NOOP        0.137 (Action Taken)\n",
+      "FIRE        0.109 \n",
+      "RIGHT       0.130 \n",
+      "LEFT        0.105 \n",
       "\n"
      ]
     }
@@ -3575,7 +2521,7 @@
     {
      "data": {
       "text/plain": [
-       "503"
+       "699"
       ]
      },
      "execution_count": 38,
@@ -3595,12 +2541,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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PNE07YNYwFYTVaDQadv76jcxwKQg7mUgJffix2/yfy+WaJhoTdjftPHnjEJiZRsOevXj1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\nF7/4BbDk4MRisaZy2tE6ZUL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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c29ca20>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3609,23 +2557,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.666 \n",
-      "FIRE        0.905 \n",
-      "RIGHT       0.768 \n",
-      "LEFT        0.408 \n",
-      "RIGHTFIRE   1.149 (Action Taken)\n",
-      "LEFTFIRE    0.213 \n",
+      "NOOP        0.428 \n",
+      "FIRE        0.428 \n",
+      "RIGHT       0.906 (Action Taken)\n",
+      "LEFT        0.358 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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t7VgOX8NKpcL8/Dye5zWlV25E6MPz5pj+BKWUbUhb+xUEQYig0LfeqK0dn2bw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\nE088QbFY5Nq1a1t2TCG6RMK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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c2c2198>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3634,23 +2582,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.784 \n",
-      "FIRE        0.383 \n",
-      "RIGHT       0.674 \n",
-      "LEFT        0.731 \n",
-      "RIGHTFIRE   0.611 \n",
-      "LEFTFIRE    1.086 (Action Taken)\n",
+      "NOOP        0.391 \n",
+      "FIRE        0.426 \n",
+      "RIGHT       0.849 (Action Taken)\n",
+      "LEFT        0.311 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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3N3nyRng7O5aj17BarbKwsEAQBG3plVsR+ui8OaY/QSllG9LOfgVBEGIo9J03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\nJ4iKeK1W47XXXuPKlStMT0/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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0f2ac8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3659,23 +2607,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.094 \n",
-      "FIRE        1.070 \n",
-      "RIGHT       0.808 \n",
-      "LEFT        1.409 (Action Taken)\n",
-      "RIGHTFIRE   1.315 \n",
-      "LEFTFIRE    0.993 \n",
+      "NOOP        0.413 \n",
+      "FIRE        0.486 \n",
+      "RIGHT       0.852 (Action Taken)\n",
+      "LEFT        0.306 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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jvK0dy+FrWC6XmZubw/f9pvTKjQh9eN4c05+glLINaWu/giAIERT61hu1tePT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\niNALgiD0OCL0giAIPY4IvSAIQo/z/wMphXH5TzEoOQAAAABJRU5ErkJggg==\n",
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IwsICrusmnr3kvgsPO5kSd+j0uJRSFItFFhcXCYJAxF04gNaafD5PqVQ6UHcE4WEmc+LeD/HChF4YD13qhyB0knlxN7ntcRyLNyYcQMY+CEJvMi/ujuPgeV7SiWo60oSHG7seeJ4nqZCC0EVmxd14Yp7nUSgU8Lw9U01nmfBwY9cD13XxPE/qhiBYZFbc4cG8MubGlbCM0I3JqhLPXRA6ybS4wwOBNznugmAjg9kEoTeZF3cbaXILgiAMxokQd3tq12HotZ88KIan3/9hGmUqaZCC0JsTIe4mNJNm81ua8ukzrTKV/6UgHCTz4m4v1HHcm/ioAS7jeGjMMlkuT/kfCkInmRd3m2Ga34OIjTTrB0fKUxBOBjMt7o7jJFk2dg60eW/mAxcxGowslqd47ILQmxMl7sOEZQZZ2EMEYjCkPAXh5JB5cTeDmAb1Bu0pX1utFrVajVarlRzLeJae51Eul5mfnyeXyw2dkTPOzJEsZPnYZdJut6lWq7RaLeI4TgYOmfemPPP5/IF9x4n0mwjCQTIv7vbgJfsGtoWjew5vswTb/fv3eeWVV7h79y5AMkdNFEWUSiVWVlYol8vk8/lk8qlBRzoOKrLDiM44jz3o+e3yNGVSrVZZW1tjY2ODKIqSKSHCMCSfz3Px4kWuXr1KoVBIJvRKW3i7HxgyiEkQepNpcbdHph51A5sVmoxXHgQBjUaDW7ducfPmTeI4TkTc932WlpYolUpcvnw5+T6KooGXajsqtjyKqI3z2MPYYRbBaLfb3L59m5deeokgCBIRb7fbzM3N4XkeKysrQ5VnGnZK34kgPGBkcVdKucDzwJrW+p1KqavAp4AzwNeBn9Na+yMcv2PuEDscYDDfGW/TeOhhGFKpVNja2gI6ZxL0fZ/d3V1gz6MPwzA518OOKU/7YRlFEVEUUalUuHPnDtBZnvV6nVqt1jHXiz11xLhsNO9NZ26ajLtuC8I4SeOu+yXgBevzbwG/o7X+PmAbeP8oB+/Oc3ddtyOfulv8u3Ot7Ru+13sjPrYYDfIyUxHn83ny+Ty5XI5cLpe8N3Z22zTtYw/yMsc/SqDtqZftsrX36/X/StPGXiG7FBlr3RaEcTKS566UugT8W+C/A7+i9u6wtwE/u7/JJ4H/Bnxs2HOY5vYgWRr2tkZ4bE88l8slHqiZA9x4febvoJgFRHp5i7YgDiM6Rx170FDVqJi4uY3rukmfhumIDsMwib/b5X+c8hzVzjF47WOv24IwTkYNy3wE+DVgYf/zGaCitQ73P68CF0c5gRHjo7Bj7iYkE4Zh0qnX6+aP45ggCGi324kg9QvLdOd01+t1KpUKzWYz+d5s53keCwsLLC8vD5SJ033s3d1ddnZ2kiwfO0SSy+VYXFxkcXGRXC6XiG/aQm9sscs0CAKiKDrUWw7DEN/3E5E32487Hj6GB93Y67YgjJOhxV0p9U7gjtb660qptw6x/7PAswCnTp3quY3xCo1IH4Wd5hiGIa1WizAME2GxHxRRFOH7Pq1WK9muVzy/+/jGa71z5w7Xr1/n/v37iehGUUQYhpTLZVZWVgCYn59PPPFBj725ucmNGze4f/8+QEcfQrlc5vLlyzz++OPMzc0lseZxePFG1M0Dz5STXYZ22fq+T6PRoNFoTLRD1YSxzLz/o5Jm3RaEaTGK5/5m4F1KqXcARWAR+CiwrJTy9j2cS8Bar5211s8BzwGsrKz0dOuM9+f7fofHaP9u/iqlEtEx4m4LOzwIl3QLUqvV6gjX9MJe0s33fe7du8eNGzdYW9u7PFvcFxcX8TyP06dPJ9/3axWYFod97K2tLa5fv87t27cPHHt5eZl8Ps8jjzySPAyGSeE8bH4YOxUyjuNknEEQBId64HZLyIh7r9DUMALcbbf9fzTxd7svYkRSq9tKKUnhEabC0OKutf4Q8CGAfe/mP2ut36uU+mPgJ9nLKngf8PlRDDQCY4Sim+6OSBOGGTQubcIO5tWrhWALsNm+1WpRqVSo1WoHtg+CgHq9nohud+ikW6jsY8dxTKvVYmdnJ8nm6S6PRqORPLiGiWsfVi69Qi7d3/UKs/Tq4LU/29c8bIimXwdq2q2WSdVtQRgn48hz/3XgU0qpDwP/CHxi1AP265zslUXhOE6Slz2IN9srS6bf+e1BOUcJpMnAMfaYc0GnwHWLlL2vbaO9QHi/B9ogHGW7vZ39oDTledh+9jXDg87X7msehn52D2JXiqRetwVhXKQi7lrrvwX+dv/9deANaRwXHuQwmzz0Xr8Z77V7hGq9XicMw16HTbY3xzahk34ZKvZvYRgmw+1LpRJaa/L5fHKshYUFlFLs7u52dIba6ZomW8f+3RzbXIPBhJlMiARIzmWHno4ST7uzubuTt9f77rBMvV7vG5oxg5l2d3epVCpJ2XanRQ4TOrE7Z227jR25XI75+fm+IbVRGGfdFgTDYffEsE5RZkeomps3DEMajQZBEBxo4vu+T7VapdFodAi8EczNzc0km8X8Zr83o1iLxWLfuLgtJEZ0zYNmeXk5eXiY1oIRwyAIWF1dJZ/PH4j7FwoFFhYWklGddl9Bu91Osnd62W3i2o1GI4nF92qldAug6ZNoNBo959vpV/72se/evUu9Xu84hx1aqlar3Lp1i1qtljywTKXN5XIsLCxQLpeTDCL7PL0eLLbdu7u7VKtVgiAAOjOI5ufnuXDhAsViMXkQjauTWRDSpru/qPt+MOHa45I5ce++MOMNtlqtAzdrvV5nfX2dO3fuJN60IY5jms1mXzEyx67VaolQHJbR0i1GURSxtLSUTJJlE0URzWaT733ve4lddofv0tIS58+f58yZMwfE3cTrjYiZ45l/bhiGNJtNqtVqYsdhIShjt+M4hGHI1tYW6+vrVKtVoPOhZNMdCgI6zttdnnEcU6lU+N73vkehUOgY5QpQLpd57LHHOHv2bPK7Kc+j7PZ9n7t377KxsXFgVLHWmkceeYRiscjZs2c7WlkmnCQIWcYOO9v6Z7eehyFz4m5jPPdWq0Wz2ey4eBP2uHPnDqurq/i+n3jdJlbc/cTr9tzNsc1cKEelK9o4jsPi4iILCwvJ8YxdrVaLV199lc3NTer1ehJ3N15+vV6nVCpRKpXI5/NJyCWfz+P7PkEQdNjdLYBhGNJut5MHw6DiHgQBlUqF27dvs729nXw/qAB2V7Tu8tzd3aXRaPSsnAsLC+RyOcrl8kAPJfM/dF2XdrvN9vY2a2tr7OzsJKmPJpwWBAGXL1/umVElCCeBw0Kkw5JpcT8MI95BECQhhuM84Ub16FzX7fDazT/EPGCUUklKoIlzG0y+uGHYJ/MgdHfcmgeDnaue5rn6Ha/7mo+LeRD3K89JjYYVhHFhZ+2lQebF/aisFHs4/CTpFjJ7JKwdhzfYIQrTmQoPmmT2dsehX8zc/NYrw8i267D9R8U+trnmXtlBvdIqe9ltd5ja/3N7biFBOOmk1frMpLjbnWomLl6v1w8Ig8mGcRynIzPDFtp+wmUfGx7krw9asN3HNu9d16XZbCatCXiQImg/mVutVtKXYB4GJtTQbDYP7VA1dtsZPkfFrl3X7WjlmDK07eqO+R11zb2w9zXHtmfirFaryaC07u372e37Pr7/YPJF84Ay157i4CVBmAr9HJqZCct0Z0nEcUy9XufOnTtsb28f8M6MQBqh6BcP7vVdHMdJzL5SqSS/DysStt1BEFCtVhPRtgdKwd6KRvfv308eTN3XbASwl91RFFGr1djY2CCXyx1pd/exd3Z2aLfbyW92Gmb331HKwb5uIIn3Ax0raw1idxiG7OzsJGVix+zNeQThJNPtKKbRos6UuENnx6QtZHfu3Ema36bjLIqiJA57XOI4plar4ft+x+CiYcS910Op3W53xIXtf5QR91qtdmBfk6J5mLibpe4Gsbv72L7vJ+Lefey0sY9txL3RaAxld7vd7lsmacYpBWHSGGelu0N11BZp5sS9G7Nupwmf2LHrUTCCYQvdpIjjmEajMdS+JqRjh1dOAuO0e5ARt4KQVQ5zTkYZfZ15ce/VcSkIgjDrdIdzj0vmUwy6sztkGTxBEB4GuvvEjkvmPXe7yW3e282UUWOt42rOD2LXUfHmYfY9imnHpk+q3YIwKUx23ajrAmde3O1myahPsn7HnxZpZaWcJE6q3YIwKewJ9uxpSI5L5sMygiAIDxNm/En31N/HJfOeuyAIwsOEnULdbxT3IIjnLgiCkCG6F6Mftp9KxF0QBCEj2AOZRp1ITMIygiAIGcBMZW2vLzHTqZCCIAgPA67rksvlkknxutd1OC4SlhEEQcgYacyXJJ67IAhCBjBZMvZU2TM9iEkQBOFhwMwIC+ksoiPiLgiCMEXs+bO61yoYBRF3QRCEKeK6LoVCIVnwvt1ujzTtgEE6VAVBEKaIWR84n88n2TJpTGgo4i4IgjBl4jgmDMNUJ0aUsIwgCMIUieMY3/cJwzDJkpEOVUEQhBNOFEXJanP2+sKjIuIuCIKQEdJcRnSkmLtSalkp9Rml1HeVUi8opX5UKXVaKfXXSqmX9/+eSstYQZgUUreFk86oHaofBf5Sa/1a4IeAF4APAl/WWj8FfHn/syCcNKRuC2PFcRyKxSLz8/OUy2VyuVy6xx92R6XUEvAW4BMAWmtfa10B3g18cn+zTwI/PqqRgjBJpG4Lk8DzPObm5lhYWGBubi474g5cBe4Cv6+U+kel1MeVUmXgnNZ6fX+bDeDcqEYKwoSRui1MBMdxkjVTu5fUGzXXfRRx94AfBj6mtX49UKermar3unx7dvsqpZ5VSj2vlHq+Xq+PYIYgpE5qdXvslgonFq01vu/TarVot9vJykv276MwirivAqta66/uf/4MezfEplLqPMD+3zu9dtZaP6e1fkZr/Uy5XB7BDEFIndTq9kSsFU4kURTRbDap1WrU63V830/1+EOLu9Z6A7illHrN/ldvB74D/Bnwvv3v3gd8fiQLBWHCSN0WJoFZkKPdbuP7fmoThhlGzXP/ReAPlVJ54Drw8+w9MD6tlHo/8ArwnhHPIQjTQOq2cKIZSdy11v8E9Gp6vn2U4wrCtJG6LYwLpRSO4yQdqKOuldoPGaEqCIIwQVzXpVwuUywWieOYRqNBs9lMXdxlVkhBEIQxY2fBuK5LqVRiYWGBcrlMPp/vu+0oiLgLgiBMELP4tQnFpO2xGyQsIwiCMGZsAdda02w2k9kg2+32gd/TQMRdEARhgoRhyO7ubjJn+7i8dxF3QRCECTLOUIyNxNwFQRBmEPHcBUEQJoCZ4jefzyfzyrTb7VQX6LARcRcEQRgT9lqonuextLTE4uIiURRRqVQ65pNJY91UGxF3QRCECeA4DoVCgXK5TBRFNBqN1HLaeyHiLgiCMAFMKKbRaBCGIUEQjLVjVcRdEARhTNjiHccxtVqNVquV5Lfb8XaZW0YQBOEEEgQBQRBM7HySCikIgjCDiOcuCIIwZswaqd3zyowTEXdBEISUsdMac7kcp06dYmFhgSiKqNVq7OzsEIbhgW3TRMRdEAQhZWzBdhyHhYUFzp07B8DGxgbVarXntmkiMXdBEIQxYwu94zhjzW83iOcuCIIwARqNBkEQUK1WiaIo+V7mcxcEQTghdK+8NDc3B8Dm5iZbW1vJNrJYhyAIwgnCFvdSqcTp06eJoohWq5V873keYRiOTdwl5i4IgpAy3YKtlEIpheM4fbdJG/HcBUEQxkilUuH69eu4rpukPwJjz3UXcRcEQUgZe86YKIq4detWMoip1zbjQMRdEAQhJexOUtd1WVxcpFQqEYYh9XqdRqMxMVtE3AVBEFLCcZwkzTGXy/H4449z9epVHMfhxo0bvPjii9TrdWAvi8ZOiUwbEXdBEISUsLNkHMfh1KlTXLlyhXw+T6PR4Pr16x3bjmt0Koi4C4IgjAWtNc1mk0qlguM41Gq1sXrq3Yi4C4IgpIQt3kopNjY2aLVaxHHMvXv3OvLcoyjKbraMUuo/Af8B0MC3gJ8HzgOfAs4AXwd+Tmvt9z2IIGQQqdvCMNhi3Wg0uHnz5kDbjoOhBzEppS4CHwCe0Vr/IOACPw38FvA7WuvvA7aB96dhqCBMCqnbwrBMYkKwQRl1hKoHlJRSHjAHrM0YJVYAABBmSURBVANvAz6z//sngR8f8RyCMA2kbgvHxp790XVdPM+b2CyQ3QwdltFaryml/ifwKtAEvsheU7WitTbDsFaBiyNbKQgTROq2cFzstMZcLseTTz7J448/juM43L59mxs3biRzuDuOM/YBTDBaWOYU8G7gKnABKAM/doz9n1VKPa+Uet7kfQpCFkizbo/JRCFj2HPGeJ7HysoKb3rTm3jrW9/K008/TbFYTH43S+6N3aYR9v1XwA2t9V2tdQB8FngzsLzflAW4BKz12llr/ZzW+hmt9TPlcnkEMwQhdVKr25MxV8gi+XyexcVFFhcX8bwHQZJJhWhGEfdXgTcppebUnrVvB74D/A3wk/vbvA/4/GgmCsLEkbotjITWmkqlwrVr17h+/TrNZjP5bdwpkIahxV1r/VX2Opf+gb1UMQd4Dvh14FeUUtfYSxn7RAp2CsLEkLotHBc7zOI4DmfPnsXzPL7xjW/wla98he3t7WSbSYn7SHnuWuvfAH6j6+vrwBtGOa4gTBup28JxsMV9YWGB7//+7+f06dPcvXs38dqLxSK+73dM+ztWmyZyFkEQhBnG9sRzuRzFYpFCodARa580Mv2AIAhCiqytrfH8889z/vx52u128n0QBBNJgTSIuAuCIIyI7z+YhSKOY774xS+yvLzMzs5O8v0410vthYi7IAjCkJgBSXEcMz8/zxNPPIHjOHz3u9/l1q1bwF5eu9Z6ol47SMxdEARhaPL5fPK+VCrxEz/xE3zgAx/gDW94Q8c2rutO3DYRd0EQhCGxR57evXuX06dP8yM/8iM88cQTyfdmUY5JI+IuCIIwJN2hlmazyfb29kTXSu2HxNyFiWG8l0l2KgnCODAThZnJwK5cucK73vUu3vjGN1Kv17l//36y7bTqu4i7MDFE1IVZoVAoJN55Lpfjve99Lx/+8IcBePHFFw/kt0tYRhAE4QRgd5Aqpbh48cHsz695zWtYXFxMPp+4+dwF4TgopcjlcjiOQxiGExuCLQjjwI61m0nCDOvr6x0x9ziOp9JqFXEXxoZSKqnU+XyeRx99lFKpRKVSYWtra+J5v4IwDpRSeJ5HpVLhxo0bfOxjH+NrX/ta8rs9wGmSiLgLY8MW90KhwIULFzh16hSvvvoq29vbxHEsnazCicQOyziOw2tf+1qWlpb49Kc/ze/+7u8CUC6X0VpPLXNGxF2YCK7rUiqVWFhYIJ/PZ2ohYUE4LiaOrrVGKcWlS5dQSiVL7cFeR+s0W6fSoSqMDdsbD8OQWq3G/fv3aTabEpIRTjT2nOxxHPPSSy+xs7PT4bT4vk8QBNMyUTx3YTK0223W1ta4d+8etVot8XAkHCOcRFqtVvI+DEM+/vGP86UvfYlvf/vbyfftdnuq9VvEXRgbdsX2fZ+7d+/iOM5YVqKZ1YeE7QmaEMBhmHI4rC9j3CExE66wbRnknMexq/u6jrNvGtkrxiM39flLX/rSAXvsEM00EHGfYUa5icchllEUTaTCG2HJuuAb0bM7nrt/H+XYpgzsEJjrusmqQd0PAkO3KPezr995jbAFQZCkwHqed0Dw7XM5jtOxmtFhmGuy9z3sAWIeikop4jim3W6nlorb75zHKbNxkVlxlw630Zl25erFuCq9qS/2TZ6FG+wwpvEAmtQD1qC1xvf9qaUDHkYa9cOUpT2GI4qiTPQpZaZDtd+TV0R+dhj3/9J4frbHOa0Z+bLGoF7xw8I46kXW6lpmPHeT82z3QJ+EpnVWUUrhuu5QzWqz+EDa3sc4/5dxHCdeqR3Tz3Id8jyPfD6P4ziJnXZ6nR2qOOoaeoU5tNa0221arVZyf5XLZUqlEvBglKV9TvsYrusmYZzDzm/2j+MYz/NwXTeZPMtxHB599FEWFxeTkcnmuuxrzuVyFAqFjnBSr/4GpRRhGHa0BgqFAoVC4cAxzbGiKMJ1XXK5HK1Wi/X1de7du9fzmoclCIKpZsb0IhPirrUmDMMkVmcK3DRxsnpzZplCocDS0hLlcrlD3LtvZIP9ne/77OzsUKvVTkTZx3FMGIa0221yuVyynJnrumN5SA1Lt5AsLS1x/vx5isUiQRB0iLvjOBSLxWS+cFuIDyOKIhzHoVAoEAQBq6urXLt2DdgLHTz99NM8+eSTOI6TDK4x8XD7vgOYn5/n1KlT5PP5JNTQrwUQxzG+77O4uMjS0hLf+ta3+PM//3Py+Tw/9VM/xVve8hZ2d3e5d+9esoB0FEW02208z+P8+fNcvHiRfD6P7/vEcZw4J+Z/6HkenudRq9W4desWm5ubKKV47LHHuHTpEvPz8x0PEPP/bzQazM3N8dhjj3Hjxg0+8pGP8Kd/+qfJtTuO07HW6ayQGXE3T2HjYcRxTBAEIu7HwBbxcrnMysoK586dS5YCO8yLt73FarXKzZs3aTQayY2e5fh1HMe0Wi1qtVriwRtxn8byZv3oLsNisciZM2eYm5tLvGvzv3Ich8XFRUqlUkfmxWHirpQiCAIcx2Fubo52u51MSQt73vyZM2d44okncF03eXjn8/mO+mE80OXl5WTKCONo2YN3DK7rEoYhzWaT06dPc/bsWWq1WuKN/8AP/ABve9vb2N7eZm1tjWKxSLlcJggCms0muVyOJ554guXl5YHLcnV1lZs3b+I4DlevXuX8+fMD7beyssLnPve5jjKZ1ZBVJsQdHngmtocyrQl3Tir2TVcsFjl79iyXL19O5p6G/rFXIyiO47C1tcXW1lZy02YpjtgL0/Jrt9vJtRrvFw4uqJAVjANjXrbn7rouvu8nU8faLdrDMALs+37PrJAoimi1Wrium+Rqm/vMHN+Ie7PZpNlsJuXbz0Ew6YDNZpNisUi9XqfVaiUP1kajQaVSYWdnh93d3cRpC4Ig8dx3dnYGFvcgCKhWq+zu7qKUYmdnh0cffbTvUnbtdptCoQDstUrtHPVZJhPibioPdIq7hGWOh11O5sYyIQojDv2Ezhb3WRhgdNy+hmlhPGHbYzciaqf4mf/bYV6m2c7sa8Ia3duY/7Np2ZhYtdnWfG/i7eazvX93eqX5a17moWT6fkxIxX4PeyEgs8+g2MdyHIdcLnfo/vbc6kdtO0tkQtyhM5XN/M1a7/NJotlssr6+nsQfj4rZ2p1QtVqNSqWS7DPI4JlpY2zv1amWVYxtdmjA/muEFegQy8Ny4s0+Zv/u63ccJxFGI9qe5/UMuXieRy6XI5fLHejg7T6mUqpje2O3+b5YLFIoFMjn88nLOBImBn+ccjPHMO8Po3vudRH3CWIqgN2hap7O05ro/iRi3/T1ep3V1VW2trb6dqJ272s3y+v1ekc+dNY8YNueKIpoNBrs7Ox09NMYIZr2SEFDdxk2Gg3u3LlDPp9PWlj2/6pYLCbCdVRoyb5WI3hhGHYs9xZFEWtra4n4N5tN4IGnbv7/JkwzNzfH4uJiR4dqrwemaTH4vs/8/Dzz8/O89NJL+L6P1pq///u/JwxD6vU6lUqFXC6XxPl938d1Xc6ePcu5c+fI5/MEQZC0YuzwrNGD3d1dNjc3k7pt9i2Xy0lr34i46Y8xYcpbt27xwgsvdJRJ1up2WmRC3KMoSuJntrjX63Xa7XZmY6ZZxvd9tre3h34wZjmFsJsgCLh37x6e51EoFA50PmYlE6K7PO24sfndFne7FXvc/4WdBmgIgoAXXniBl19+ucOeXplTcPTIz17XZzz8IAhotVo0m00++9nP8oUvfCEJFfZKcbTDSP2u1X742AOFTCuke9/utErTh7S7u5tsM8uLxmRC3JvNJt/4xjcOxAxbrRa3b9/uuDlPiuBkgZMk0MfFvi4zb83u7m5HfNiQFXHvZpJpmiY0N418bFtMs4LRmKy06saBGmBwxO8B7wTuaK1/cP+708AfAVeAm8B7tNbbau/R+lHgHUAD+Pda6384ygjP83R3T7nx4u1BGIJwGIf1J2itD/w4ibqtlJrNp6uQGXrVbRhM3N8C7AJ/YN0A/wO4r7X+TaXUB4FTWutfV0q9A/hF9m6ANwIf1Vq/8Sjj5AYYD6P0Vcyax99H3Kdat+2kgcM6SYfBDkn0mzhs0OMcFRayfzfbHzZxWK+wjPGkB6H7uo47cdi051lPm37inhTUYS/2vJhvW59fBM7vvz8PvLj//n8DP9NruyOOr+Ulr3G+pG7La1Zf/eresEOzzmmt1/ffbwDn9t9fBG5Z263uf3ckJs2q+yWZMsIg2F5w9+uYpF63BWEajNyhqrXWw4RVlFLPAs+azxJTF0ZhHGGktOq2IEyDYT33TaXUeYD9v3f2v18DVqztLu1/dwCt9XNa62e01s8MaYMgjAOp28JMMKy4/xnwvv337wM+b33/79QebwJ2rCauIJwEpG4Ls8EAHUL/B1gHAvbijO8HzgBfBl4GvgSc3t9WAf8L+B7wLeCZATtsp94pIa/ZfkndltesvvrVvSNTISeBpEIK46ZvutiYkbotjJt+dXs2JzIWBEF4yBFxFwRBmEFE3AVBEGYQEXdBEIQZJBOzQgJbQH3/b9Z4BLHrOGTRrseneG6p28dH7BqcvnU7E9kyAEqp57M46EPsOh5ZtWuaZLVMxK7jkVW7+iFhGUEQhBlExF0QBGEGyZK4PzdtA/ogdh2PrNo1TbJaJmLX8ciqXT3JTMxdEARBSI8see6CIAhCSmRC3JVSP6aUelEpdW1/abNp2bGilPobpdR3lFL/rJT6pf3vTyul/lop9fL+31NTsM1VSv2jUuoL+5+vKqW+ul9mf6SUyk/apn07lpVSn1FKfVcp9YJS6kezUF5ZQOr1wPZlrm7PQr2eurgrpVz2Ztv7N8DTwM8opZ6ekjkh8Kta66eBNwG/sG/LB4Eva62fYm/GwGncqL8EvGB9/i3gd7TW3wdsszej4TT4KPCXWuvXAj/Eno1ZKK+pIvX6WGSxbp/8ej3ItKXjfAE/CvyV9flDwIembde+LZ8H/jV91tWcoB2X2KtMbwO+wN70s1uA16sMJ2jXEnCD/b4b6/upllcWXlKvB7Ylc3V7Vur11D13Mro2pVLqCvB64Kv0X1dzUnwE+DXArEV4BqhorcP9z9Mqs6vAXeD395vVH1dKlZl+eWUBqdeDkcW6PRP1OgvinjmUUvPAnwC/rLWu2r/pvcf2xFKMlFLvBO5orb8+qXMeAw/4YeBjWuvXszfMvqOpOunyEvqTpXq9b09W6/ZM1OssiPvAa1NOAqVUjr0b4A+11p/d/7rfupqT4M3Au5RSN4FPsdd8/SiwrJQycwNNq8xWgVWt9Vf3P3+GvZtimuWVFaReH01W6/ZM1OssiPvXgKf2e8jzwE+zt17lxFFKKeATwAta69+2fuq3rubY0Vp/SGt9SWt9hb2y+b9a6/cCfwP85DRssmzbAG4ppV6z/9Xbge8wxfLKEFKvjyCrdXtm6vW0g/77nRPvAF5ib33K/zpFO/4le02tbwL/tP96B33W1ZyCfW8FvrD//gng/wHXgD8GClOy6V8Az++X2eeAU1kpr2m/pF4fy8ZM1e1ZqNcyQlUQBGEGyUJYRhAEQUgZEXdBEIQZRMRdEARhBhFxFwRBmEFE3AVBEGYQEXdBEIQZRMRdEARhBhFxFwRBmEH+P1iqwp8+HNuAAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c333e80>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3684,23 +2632,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.382 \n",
-      "FIRE        1.363 \n",
-      "RIGHT       1.342 \n",
-      "LEFT        1.431 (Action Taken)\n",
-      "RIGHTFIRE   1.374 \n",
-      "LEFTFIRE    1.368 \n",
+      "NOOP        0.409 \n",
+      "FIRE        0.434 \n",
+      "RIGHT       0.737 (Action Taken)\n",
+      "LEFT        0.332 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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NnrwR3uaO5fA1LJfLLCws4HleQ3rlZoQ+PG+O6U9QStmGtLlfQRCECAp9843a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\n29hJh6DTNhgZoa/X63ieR61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vue/Cg06qxB26PS6lFPl8nsXFRXzfF3EXDqC1JpvNUigUDrQdQXiQSZ24D0K8MKEfxkOX9iEI3aRe3E1uexRF4o0JB5C5D4LQn9SLu+M4eJ4XD6KagTThwcZuB57nSSqkIPSQWnE3npjneeRyOTxv31QzWCY82NjtwHVdPM+TtiEIFqkVd7i/roy5cCUsI/RisqrEcxeEblIt7nBf4E2OuyDYyGQ2QehP6sXdRrrcgiAIw3EixN1e2nUU+n1ObhSjM+h3mEWdShqkIPTnRIi7Cc0k2f2WrnzyzKpO5bcUhIOkXtztjTqOexEfNcFlEjeN00ya61N+Q0HoJvXibjNK93sYsZFu/fBIfQrCyeBUi7vjOHGWjZ0DbZ6b9cBFjIYjjfUpHrsg9OdEifsoYZlhNvYQgRgOqU9BODmkXtzNJKZhvUF7yddms0mlUqHZbMZlGc/S8zyKxSLz8/NkMpmRM3ImmTmShiwfu05arRblcplms0kURfHEIfPc1Gc2mz3w2Uki4yaCcJDUi7s9ecm+gG3h6F3D22zBdu/ePd566y3u3LkDEK9RE4YhhUKB9fV1isUi2Ww2Xnxq2JmOw4rsKKIzybKHPb9dn6ZOyuUyN2/eZGtrizAM4yUhgiAgm81y8eJFHnnkEXK5XLygV9LC23vDkElMgtCfVIu7PTP1qAvY7NBkvHLf96nX69y4cYM333yTKIpiEW+32ywtLVEoFLh8+XL8ehiGQ2/VdlRseRxRm2TZo9hhNsFotVrcunWLb3zjG/i+H4t4q9Vibm4Oz/NYX18fqT6TsFPGTgThPmOLu1LKBV4CbmqtP6KUegT4HLAKfBn4Ka11e4zyu9YOscMBBvOa8TaNhx4EAaVSiZ2dHaB7JcF2u021WgX2PfogCOJzPeiY+rRvlmEYEoYhpVKJ7e1toLs+a7UalUqla60Xe+mISdlonpvB3CSZdNsWhEmSxFX388Ar1v+/Dvym1vptwC7w9DiF9+a5u67blU/dK/69udb2Bd/vuREfW4yGeZiliLPZLNlslkwmQyaTiZ8bO3ttmnXZwzxM+UcJtL30sl239uf6/V5J2tgvZJcgE23bgjBJxvLclVKXgH8B/GfgF9X+FfZ9wE90Dvks8B+B3x71HKa7PUyWhn2sER7bE89kMrEHatYAN16f+TssZgORft6iLYijiM5RZQ8bqhoXEze3cV03HtMwA9FBEMTxd7v+j1Of49o5Aa994m1bECbJuGGZ3wJ+GVjo/L8KlLTWQef/DeDiOCcwYnwUdszdhGSCIIgH9fpd/FEU4fs+rVYrFqRBYZnenO5arUapVKLRaMSvm+M8z2NhYYHl5eWhMnF6y65Wq+zt7cVZPnaIJJPJsLi4yOLiIplMJhbfpIXe2GLXqe/7hGF4qLccBAHtdjsWeXP8pOPhE7jRTbxtC8IkGVnclVIfAba11l9WSn1ghM8/AzwDsLKy0vcY4xUakT4KO80xCAKazSZBEMTCYt8owjCk3W7TbDbj4/rF83vLN17r9vY2165d4969e7HohmFIEAQUi0XW19cBmJ+fjz3xYcu+ffs2b7zxBvfu3QPoGkMoFotcvnyZK1euMDc3F8eaJ+HFG1E3NzxTT3Yd2nXbbrep1+vU6/WpDqiaMJZZ939ckmzbgjArxvHc3wf8oFLqw0AeWAQ+DSwrpbyOh3MJuNnvw1rrZ4FnAdbX1/u6dcb7a7fbXR6j/b75q5SKRceIuy3scD9c0itIzWazK1zTD3tLt3a7zd27d3njjTe4eXP/69nivri4iOd5nDlzJn59UK/A9Djssnd2drh27Rq3bt06UPby8jLZbJazZ8/GN4NRUjgPWx/GToWMoiieZ+D7/qEeuN0TMuLeLzQ1igD32m3/jib+bo9FjElibVspJSk8wkwYWdy11p8EPgnQ8W7+ndb6J5VSfwz8KPtZBU8BXxjHQCMwRih66R2INGGYYePSJuxgHv16CLYAm+ObzSalUolKpXLgeN/3qdVqsej2hk56hcouO4oims0me3t7cTZPb33U6/X4xjVKXPuweukXcul9rV+Ypd8Ar/2//Z1HDdEMGkBNutcyrbYtCJNkEnnuvwJ8Tin1n4C/Bz4zboGDBif7ZVE4jhPnZQ/jzfbLkhl0fntSzlECaTJwjD3mXNAtcL0iZX/WttHeIHzQDW0YjrLdPs6+UZr6POxz9neG+4Ovvd95FAbZPYxdCZJ42xaESZGIuGut/wb4m87za8B3JlEu3M9hNnno/d4z3mvvDNVarUYQBP2KjY83ZZvQyaAMFfu9IAji6faFQgGtNdlsNi5rYWEBpRTVarVrMNRO1zTZOvb7pmzzHQwmzGRCJEB8Ljv0dJR42oPNvYO8/Z73hmVqtdrA0IyZzFStVimVSnHd9qZFjhI6sQdnbbuNHZlMhvn5+YEhtXGYZNsWBIN9TfSOoY3qFKV2hqq5eIMgoF6v4/v+gS5+u92mXC5Tr9e7BN4I5u3bt+NsFvOe/dzMYs3n8wPj4raQGNE1N5rl5eX45mF6C0YMfd9nY2ODbDZ7IO6fy+VYWFiIZ3XaYwWtVivO3ulnt4lr1+v1OBbfr5fSK4BmTKJer/ddb2dQ/dtl37lzh1qt1nUOO7RULpe5ceMGlUolvmGZRprJZFhYWKBYLMYZRPZ5+t1YbLur1Srlchnf94HuDKL5+XkuXLhAPp+Pb0STGmQWhKQxveNBDHI6jyJ14t57oRtvsNlsHrhYa7Uam5ubbG9vx960IYoiGo3GQDEyZVcqlVgoDsto6RWjMAxZWlqKF8myCcOQRqPB66+/HttlD/guLS2xtrbG6urqAXE38XojYqY8E5YJgoBGo0G5XI7tOCwEZex2HIcgCNjZ2WFzc5NyuQx035RsekNBQNd5e+sziiJKpRKvv/46uVyua5YrQLFY5OGHH+bcuXPx+6Y+j7K73W5z584dtra2Dswq1lpz9uxZ8vk8586d6+plmXCSIKSdXsfVvDZO+02duNsYz73ZbNJoNLq8PBP22N7eZmNjg3a7HXvdJlZsBNsur1/ZZi2Uo9IVbRzHYXFxkYWFhbg8Y1ez2eT69evcvn2bWq0Wx92Nl1+r1SgUChQKBbLZbBxyyWaztNttfN/vsrtXAIMgoNVqxTeGYcXd931KpRK3bt1id3c3fn3YBtR7E+itz2q1Sr1ePzDwGkURCwsLZDIZisXiUDcl8xu6rkur1WJ3d5ebN2+yt7cXpz6acJrv+1y+fLlvRpUgnAR6ryW75zwqqRb3wzDi7ft+HGIYJhfeMK5H57pul9dufhBzg1FKxSmBJs5tMPnihuPYfVx6B27NjcHOVU/yXIPK6/3Ox8XciAfV57RmwwrCJLF7xeM6KqkX96OyUuzp8NOkV8jsmbB2HN5ghyjMYCocjLcdd5Gtw7pu/erOvgEd9flxscs237lfdlC/tMp+dtsDpvZvbq8tJAjCPqkUd7tbYuLitVrtgDCYbBjHcboyM2yhHSRcdtlwf9Bi2Ltlb9nmueu6NBqNuDcB91MEzWe03s+TN2MJ5mZgQg2NRuPQAVVjt53hc1Ts2nXdrl6OqUPbrt7BzaO+cz/sz5qy7ZU4y+VyPCmt9/hBdrfbbdrt+4svmhuU+e4JTl4ShJkwTHrycUmVuPdmSURRRK1WY3t7m93d3QPemRFIIxSD4sH9XouiKI7Zl0ql+P1RK9i22/d9yuVyLNr2RCnY39Ho3r178Y2p9zsbAexndxiGVCoVtra2yGQyR9rdW/be3h6tVit+zx6J7/07Tj3Y3xuI4/1A185aw9gdBAF7e3txndgxe3MeQTjJ9Iu5j0uqxB26ByZtIdve3o6732bgLAzDOA57XKIoolKp0G63uyYXjVKp/W5KrVarKy5s/3hG3CuVyoHPmhTNw8TdbHU3jN29Zbfb7Vjce8tOGrtsI+71en0ku1ut1sA6GXfgSRBmiXGyetOBx52clzpx78Xs22nCJ3bsehyMYNhCNy2iKKJer4/0WRPSscMrJ4FJ2j2JLq0gTJNBYd5B41LDkHpx7zdwKQiCcNo5zrIi/Uh9ikFvdodsgycIwoPCOCHH1Hvudpe73+JR48ZaJ9WdH8auo+LNo3z2KGYdmz6pdgvCtLCz/k71JCb7ztWb3ZFU+bMiqayUk8RJtVsQpoW9p/M4E/9SH5YRBEF40OgXpTguqffcBUEQHiTspBGT+j0K4rkLgiCkCLN20lErpx6FiLsgCEJK6BXyUz2gKgiC8CBglga3l8oeJ4FExF0QBCEFmH0KzCx8OzQzUnkJ2iYIgiCkBPHcBUEQUkDvMtjjLrUi4i4IgpAC7I1+kkDEXRAEYYbYE5Z69ykeBxF3QRCEGeI4DplMJt5dzN6pbKxyE7BNEARBGBGz8q3nefGe0Ekg4i4IgjBDTCjG3hM5CSQsIwiCMEPMQKrZF9hs0jGuyIu4C4IgzBAzExXo2kd1XETcBUEQUkKS+x2MFXNXSi0rpT6vlHpVKfWKUuq7lVJnlFLPKaW+2fm7kpSxgjAtpG0LJ51xB1Q/DXxRa/0O4NuBV4BPAM9rrR8Dnu/8LwgnDWnbwkRxHIdsNkuhUCCfz+N5yQZSRhZ3pdQS8H7gMwBa67bWugR8FPhs57DPAj80rpGCME2kbQvTwHEccrkchUKBXC6XWApkXP4Yn30EuAP8nlLq75VSv6OUKgLntdabnWO2gPPjGikIU0batjAVlFLxnqmOk2xm+jilecATwG9rrd8D1Ojppur90YG+IwRKqWeUUi8ppV6q1WpjmCEIiZNY2564pcKJRWtNGIa022183ycMw7H2TO1lHHHfADa01l/q/P959i+I20qpNYDO3+1+H9ZaP6u1flJr/WSxWBzDDEFInMTa9lSsFU4kWmtarRaNRoNms5nIkgM2I4u71noLuKGUenvnpQ8CLwN/DjzVee0p4AtjWSgIU0batjANzIYcvu93TWJKinGHZ38O+AOlVBa4Bvw0+zeMP1JKPQ28BXxszHMIwiyQti2caMYSd631PwD9up4fHKdcQZg10raFSWIPoNozVJNEZqgKgiBMEdd1KRQKZDIZtNY0m01arVaiIRkQcRcEQZgq9uSlMAzjjJmkxV2W/BUEQZgyWuuuxyQQz10QBGGKaK1pt9txrN33/YkIvIi7IAjCFAnDkEajASCeuyAIwmlhkoJuIzF3QRCEU4h47oIgCFNAKUU2m42X9g2CYCJZMgYRd0EQhAlh74Xqui7FYpFisUgURVSr1a7B1CT2TbWRsIwgCMIUUEqRyWTI5XITWb+9F/HcBUEQpkQQBLRaLaIoSnwVyF5E3AVBECaEHWbRWlOv1+Mcd9/3u9aUkeUHBEEQTiBBEBAEwdTOJzF3QRCEU4h47oIgCBPGcZx4Cz2t9USW+O1FxF0QBCFhelMgFxcXKRQKaK2p1WrUajUZUBUEQTjJOI5DoVBgZWUlfq1er8fPk85vj8+beImCIAhCF1prlFK4rnsgv92Ea5JGPHdBEIQp0Gw2CYKAarU60RRIg4i7IAhCwvTG3HO5HAC7u7vs7e11HSPiLgiCcEKwQy3ZbJalpaV4Oz2D4zgTHVSVmLsgCELCDPLGJxVf74d47oIgCBOkWq2yubmJ4zhdsfZJ57qLuAuCICRMr4hvb28f8NonvRuTiLsgCMIEcByHYrFILpeL901ttVpTO7+IuyAIQkLYoRfP8zh//jwXLlwA4NatW2xsbNBsNg8cOwlE3AVBEBLCDr04jsP8/Dznz5/H8zxarRZbW1t9j50EIu6CIAgTQGtNu92mWq0C0Gg0prJgmEHEXRAEISF6xfvevXvxJth7e3tdee6pzpZRSv1b4OOABv4J+GlgDfgcsAp8GfgprXV7YCGCkEKkbQujYGfA9IZhDjt2Eow8iUkpdRH4N8CTWutvBVzgx4BfB35Ta/02YBd4OglDBWFaSNsWTgPjzlD1gIJSygPmgE3g+4DPd97/LPBDY55DEGaBtG1hZJRSOI6D67pdG3VMk5HDMlrrm0qpTwHXgQbwP9nvqpa01majwA3g4thWCsIUkbYtHJfeFMgLFy7w0EMP4TgOd+/eZWtri1qtBkxu/fYDNo36QaXUCvBR4BHgAlAEfuAYn39GKfWSUnAVmvgAABARSURBVOol86UFIQ0k2bYnZKKQMhznvpS6rstDDz3Eu971Lt797ndz+fJlMplM17HT8OTHCct8CHhDa31Ha+0Dfwq8D1judGUBLgE3+31Ya/2s1vpJrfWTxWJxDDMEIXESa9vTMVdIE2YZX8/zKBaLzM/P43n3gyTTCtGMI+7XgfcqpebUvrUfBF4G/hr40c4xTwFfGM9EQZg60raFkTHiXavVuHnzJpubm/GsVJh8CqRhZHHXWn+J/cGlr7CfKuYAzwK/AvyiUuo19lPGPpOAnYIwNaRtC8fF9saVUqysrKCU4vXXX+erX/0q1Wo1PiaKoqnE3MfKc9da/yrwqz0vXwO+c5xyBWHWSNsWjoMt7nNzc1y8eJGFhQVKpVI8cSmbzRIEwUQ36LCRzToEQRASxPM8stksmUzmwGbYU7VjZmcWBEE4hdy5c4evf/3rrK6udi03EIbhVMIxBhF3QRCEMQmCIH6utebFF19kYWEhXjQMRNwFQRBODGZCUhRFFAoF1tbWcByH69evs729DdzPgZ/mipAgMXdBEISRsScn5XI53v/+9/PDP/zDvOMd74hf9zyva5LTtBBxFwRBGJFsNhs/L5VKLCws8C3f8i3x7kswvUlLvYi4C4IgjEhvDL3ValGtVrsmLc0KibkLgiAcE7NQmFkXa21tje/5nu/hXe96F/V6nXK5HB87zUFUGxF3QRCEY5LNZmPv3HVdPvShD/Hxj3+cK1eu8MILL3StJQOzCc1IWEYQBOGY2GIdRRHFYpErV65w5coVrl69ir0Y4olbz10QBOFBxQ61OI5Dq9Xi7t27LC4usr29TaPR6Dp2FqEZEXdhKtiey6xikIKQFHZ7Xlxc5PHHH2dhYYHnn3+ez3zmM3zta1+L32+32xKWEU4vxnsRYRdOA3Z+e71e5+1vfzuPPvooX/nKV/jiF79IpVKhWCwyNzcXT3KaNiLugiAIxySbzcbeeKvVIgxDHMfB9/34GLN/6qyQsIwwcVzXJZPJoJQiiiJ835+JJyMISdFsNuNe6OrqKplMhna73eXRB0Ew056qiLuQOL0bABeLRVZWVshkMjQaDXZ3d6nX6wOPF4S04nkeYRjGC4I98cQTPP3003zv934vOzs77OzsxMdOa932QYi4C4nTK9Zzc3OcO3eO+fn5WNiNuCc10CQ3h+ExdW7qrPc3GPT6cbHLOeoGftxzHef4fucd9vO98fJ8Pk+j0YiF+0d+5Ef4mZ/5mfjYUqk0ko2TQMRdiBmnMR524TqOQzabjTcwmHQc8iQN3k6qLoyY9taD4zjxOY+qH9MejiOERsijKIqXwbUXzrIF3z6/UurIurA/e5zccbOtnbHvsM+acxhbfN+n1WodeN2wvLwcP19cXCSXy3W9P0uBT624z/qu9yCSlBj2W2+jVCrRarWoVCpdGxgkhS1E9vO0C/y0xx6iKJr6Oe1BxpNOu93ualMvvfQSr732Gm9729v48pe/zO7ubvxeFEUi7tB9Ufa+LpwsegW1VquxubmJ53m02+2uRZWSFF/jVfV6nNKGTsaNLs24rksYhl1ePMBzzz3Hm2++yerqKnfv3uXVV1+N37M38JgFqRF3c5czFWd3pYTJ4zgOruseSwTsjQoO29G92WzSarXi/yfxm0ZRRBiG8cOcI81tyM4i6mfjKNPW7dCI1hrf92NvUylFPp+P0/iMB2+O7Y3F223Cfr1fSMXUs0n/azabVCoVlFIsLy9TLBbj38i2z5zX87xD68I+3nEc8vl8vH7LIA/ZrgOTruh5HrlcLs5q6f0epi3ncjmUUuzs7HDz5s0DvQ9T9sbGBhsbGwfes+t3VqRC3LXWBEGAUir+8YF4p/C0XpynBcdxWFxcZHFxkUwmc+hAm33xmd+rXq937fLej0n+hia+22q1yGQycQqa67ozCUMMol8W0dmzZ7tsNsc4jjNQhA7D5Ftns1mCIODOnTvcvHkT2L+ZXLlyhbW1NVzXjXtQnud1/abG45ybm6NYLJLNZuN6HCSiJsW1WCxSLBZ5/fXX+bu/+zsymQwf+MAH+LZv+zYajQZ7e3tkMhmy2SxhGBIEAY7jsLq6GteF7/txHdhx8iAI8H2f5eVl1tfXOXPmDGEY4vs+Silc10VrHdeBqdfbt29z48YNarUai4uLXL58mXPnzuE4TtxmzU2pXq8TRRHnz58nk8nwZ3/2Z3zqU59ia2sLuD+getTvkQbNSo24m0o2Dcg0FhH3yWALTSaT4ezZs1y5ciX2sOyLq/dzRixd18X3fTY3N2m1WvFv2M/76vX+kiSKothTNN6hEfdZzQ4chF032WyWhYUFcrlcl3dtbC8UCvFmEMNmsBhhM2Xae3g6jsPS0hIXL16MhQzui7vtVAHMz8+zsrJCLpcjDMP42uz9fR3HiUMWCwsLrKys0Gg0Ym/86tWrPPHEE1QqFXZ2dshms+Tz+fgzruty4cIFLl26RC6Xo9VqEUVR/PuZQeB2u0273ebcuXM8+uijQ9d5s9nk1VdfpVQqcfbsWR5//HFc1x3qs9/xHd9BPp+P//c8r+v7m56Aufm02+2Zp0AaUiHucH9gye4qHtbVF5LDdd34ol9aWoov7kHZC+Y3MjF03/e5detW/H4/cZ/k72h6fkYojLjPau/KYbFDSb3xWfOdjAgN+x2iKIrDKb2TxYxX226349mU5rXeMmB/INxM1jHi3q9NmGu11WqRy+VoNBpx2VrreAOLWq1Go9EgCIL4u7daLTzPo1arUalUYifBFnfjlRtxz+VyVKtV5ufnh6qTUqlEpVKhWq2Sy+UolUqsrq4OrL8wDOMeU7Va7Wq7ve3YOKF2SCctpELcTUOGbnGXsMz0MN1bu84Hibsdx07rbzRMbvWssQd8zeYP5q+xv9dTPyxdsDdkZsfLe8uwyzciattkeg+mDHPeQeJu3jMP+7zmZmNCH+avHaN3XRfP8/A8LxZYc2Mz57ePsbe3O4pMJoPneV2fH0Sv7YcdC/t6NYnsryRIhbhD/wyHQRk0QrIEQUCpVOL69evs7Ox0DXT1wx5wC4KA7e3tiQ+YHoVpK0Y07IHFNNMrmnbGj52Tbjjq+xix7ieydo63ETtzQ+k3oGoEOZPJxJ67sdH2UE1vyRZg+3uYMszDhGtMOeZ/MxcC6Ool9ObA28cNQy6Xiz9jQkJH1aHBDPL2ey/tpELcTWOzB1TNHXZWC92fdmwBDoKAnZ0dGo1GPKB6mLibzxtPsdFoHFi/etLY5zCDunt7e13jNEYQ0hIDhW67W60Wu7u7scjadaqUolqtxp7jsDF34/WbwUR7u7cwDNnZ2emKYdsDz71hrFwux9zcXByTPypbJggC8vk8c3Nz3LhxIx4kfvnllwnDMB4XMde2+YzjOCwvL7OyshJP7++96RhHIgxDFhYWWFtbY2lpKQ5p2Td2uw7Md97a2qJerzM/P8+LL77ImTNnukJTdpZPGIbx4O5zzz3XNW5hjj8JpELczVoNveJeq9XiwRVhcpi9IO31Xo7DrNMNfd/n7t278eCWEXMjhHavYpb0y/9vNBqHpv+NmgppsG9sYRhy/fr1OHvmqN/suL1nu7dkYvsAL7zwAn/7t3/bNbht9xIG9VIGncMO7Rz2PexUXXPDNz0JE/I5LKUTiG9IhrS0pWFIhbg3Gg3+8R//MR6UMD92s9nk1q1bM+/yPwjMWqCPi21ru93mzp07VKvVrvixIa0XZL/BzElhe9fTnlzT27M7iXieN/NVHo+LGuLu/bvAR4BtrfW3dl47A/whcBV4E/iY1npX7d+OPw18GKgD/0pr/ZWjjPA8T9trNHTOEY+mN5tN8d6FIzlsjEBrfeDNabRtpdTJUQPhRNKvbcNw4v5+oAr8vnUB/Bfgntb615RSnwBWtNa/opT6MPBz7F8A3wV8Wmv9XUcZJxdAOhhnbCPtHs0AcZ952077wmHHaRN2WMZeOMxeLO6wuP2wYRl7YHgYjrNwmDnHoIXD0sggce9qAIMe7Hsx/8/6/+vAWuf5GvD1zvP/Bvx4v+OOKF/LQx6TfEjblsdpfQxqe6O6Dee11pud51vA+c7zi8AN67iNzmtHYufIDsqXFYRB2IN/vY9jknjbFoRZMPaAqtZajxJWUUo9Azxj/peYujAOk+g2J9W2BWEWjOq531ZKrQF0/m53Xr8JrFvHXeq8dgCt9bNa6ye11k+OaIMgTAJp28KpYFRx/3Pgqc7zp4AvWK//S7XPe4E9q4srCCcBadvC6WCIAaH/DmwCPvtxxqeBVeB54JvA/wLOdI5VwH8FXgf+CXhyyAHbmQ9KyON0P6Rty+O0Pga1vSNTIaeBpEIKk2ZgutiEkbYtTJpBbXuyOxULgiAIM0HEXRAE4RQi4i4IgnAKEXEXBEE4haRiVUhgB6h1/qaNs4hdxyGNdl2Z4bmlbR8fsWt4BrbtVGTLACilXkrjpA+x63ik1a5ZktY6EbuOR1rtGoSEZQRBEE4hIu6CIAinkDSJ+7OzNmAAYtfxSKtdsyStdSJ2HY+02tWX1MTcBUEQhORIk+cuCIIgJEQqxF0p9QNKqa8rpV7rbG02KzvWlVJ/rZR6WSn1NaXUz3deP6OUek4p9c3O35UZ2OYqpf5eKfUXnf8fUUp9qVNnf6iUyk7bpo4dy0qpzyulXlVKvaKU+u401FcakHY9tH2pa9unoV3PXNyVUi77q+39c+CdwI8rpd45I3MC4Je01u8E3gv8bMeWTwDPa60fY3/FwFlcqD8PvGL9/+vAb2qt3wbssr+i4Sz4NPBFrfU7gG9n38Y01NdMkXZ9LNLYtk9+ux5m2dJJPoDvBv7K+v+TwCdnbVfHli8A38+AfTWnaMcl9hvT9wF/wf7yszuA168Op2jXEvAGnbEb6/WZ1lcaHtKuh7YldW37tLTrmXvupHRvSqXUVeA9wJcYvK/mtPgt4JcBsxfhKlDSWged/2dVZ48Ad4Df63Srf0cpVWT29ZUGpF0PRxrb9qlo12kQ99ShlJoH/gT4Ba112X5P79+2p5ZipJT6CLCttf7ytM55DDzgCeC3tdbvYX+afVdXddr1JQwmTe26Y09a2/apaNdpEPeh96acBkqpDPsXwB9orf+08/KgfTWnwfuAH1RKvQl8jv3u66eBZaWUWRtoVnW2AWxorb/U+f/z7F8Us6yvtCDt+mjS2rZPRbtOg7i/CDzWGSHPAj/G/n6VU0cppYDPAK9orX/DemvQvpoTR2v9Sa31Ja31Vfbr5n9rrX8S+GvgR2dhk2XbFnBDKfX2zksfBF5mhvWVIqRdH0Fa2/apadezDvp3Bic+DHyD/f0p/8MM7fge9rtaXwX+ofP4MAP21ZyBfR8A/qLz/J8B/xd4DfhjIDcjm94NvNSps/8BrKSlvmb9kHZ9LBtT1bZPQ7uWGaqCIAinkDSEZQRBEISEEXEXBEE4hYi4C4IgnEJE3AVBEE4hIu6CIAinEBF3QRCEU4iIuyAIwilExF0QBOEU8v8BOsnKygouN14AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c190fd0>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3709,12 +2657,10 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        1.345 (Action Taken)\n",
-      "FIRE        1.331 \n",
-      "RIGHT       1.317 \n",
-      "LEFT        1.345 \n",
-      "RIGHTFIRE   1.284 \n",
-      "LEFTFIRE    1.295 \n",
+      "NOOP        0.443 \n",
+      "FIRE        0.692 (Action Taken)\n",
+      "RIGHT       0.585 \n",
+      "LEFT        0.308 \n",
       "\n"
      ]
     }
@@ -3743,7 +2689,7 @@
     {
      "data": {
       "text/plain": [
-       "630"
+       "134"
       ]
      },
      "execution_count": 40,
@@ -3763,12 +2709,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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yfd+37e/7PgsLC1y5coWlpSVKpVJLttB27MW01fDwMIODg4yPj69rR4Kwn4mN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\nBHieRyqVolwuW69M2F84jtP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NHIRhyKlTpygUCnJ9XSESUpfcTcLWWmPbNvPz81y8eJHFxUUsy0IptWsXXJL8+Ouuqye/5GdmZpifn+8YbJeYEJMuVck9+cE0yX12dpbz58/jeZ58YMUuWmtyuRwzMzPYth337GXuu5h0qUru0NnjUkqRy+WYnZ3F931J7mIXrTWZTIZ8Pr8rdoSYZKlL7vuRXpjYi+mhS3wI0Sn1yd3MbY+iSHpjYhc59kGIvaU+uVuWheM48SCqGUgTky0ZB47jyFRIIbqkNrmbnpjjOGSzWRyn1VQzWCYmWzIObNvGcRyJDSESUpvc4e55ZcwHV8oyopuZVSU9dyE6pTq5w90Eb+a4C5EkB7MJsbfUJ/ck2eUWQoiDGYl9WZnqJvYjsSHE3kai525KM7L7LfYicSHEbqlP7skLdciHWOxHYkOITqlP7kmy+y2EEAcjyV2MNOmxC7G3kUru8kEWQoiDSX1yNwcxSa9d7EfGY4TYLfXJPXnwUvIDLAevTKbu/7vEgRB7S3VyTx6ZKh9gsR857a8Qu/Wc3JVSNvACcEtr/QGl1APAp4FF4EXgl7TWzR5ev+PcIVEUyXlEREccmGup9ju5Dzq2hRikfmTJXwVeSdz/PeAPtNbvAIrAR3p58e557rZtdxzUJLfJvCXjIBknfTbQ2BZikHrquSulzgP/BvjvwK+r1ifsx4FfaD/lU8B/Bf7wqOswu9thGPbSVDHGBlGSOY7YFmKQei3LfAL4TWCmfX8RKGmtg/b9m8C5XlYQhqEkdnEgfe69Dzy2hRikIyd3pdQHgA2t9YtKqR89wvJPAU8BLCws7PkcrTVBEBAEgVx9SezLsixc141LNb3qZ2wLMSy99NzfA/y0Uur9QA6YBZ4B5pVSTruHcx64tdfCWuvLwGWAlZWVPfepTTmm2WwShuGg6qp9lywR7FUuGHCdeGjMe73Xe+7+vR/rNEm9j+f871tsK6VkCo8YiiMnd631x4GPA7R7N/9Ja/2LSqnPAk/QmlXwJPCFXhpoLoAchuFIzZK5XwIf16l7yUHOvfT7fZsLp/fzNY8rtoUYpEHMc/8t4NNKqf8GfAP4ZK8v2Ode2bFIzuzoNq7zsg/ynvvtmI+D6HtsCzEofUnuWuuvAV9r/34V+KF+vC7cncMcBMHIJHdTTgrDMO5ZmsdNInIcZ+S+sO7F7GEFQRAn8u5SjG3bfauLJ9cLDGzQfZCxLcQgpfYIVbOrHQQBtVoN3/fjxJiWHq9pS7JNSil836dSqVCpVPB9v+O5ALlcjpmZGaamprBtu2PZ7tdLm/3ecxiGVKtVyuUynud1PBfAdV1mZmYoFAq4rtvzezbP11rjui6u6+5apxCTLHXJPdnj01rjeR6VSoV6vR73dNP44TVtsiyLRqPBxsYGa2trNBoNLMvCsiyCoDWLbm5ujrNnz7K4uIjjOPFMoFHrxSffc7PZZHNzk9XVVSqVCkD83qIoolAocPr0aZaWlshmsz2/52Ryz+Vy5HK5+MvStG3UtqcQ/ZS65J5keu6NRiP1yd2UX2zbplarsbm5ya1bt6hUKnE5wiT3arVKLpcjn8/juu7IJ3fbtmk2m2xtbbG2tkaxWIxLT6Y0NTMzE/feTdlKa33kQfJkcldKxeUgIURLqpN70iglPq01zWaTRqPRMVffaDQacY04WZYYNd3J1HwRmy+rZB280Wh0bAMhxGCNxNzCUUt8pgfvOHe/O5M9VDOYmnx+8uco2GtmjNlDMfZ6z92DrKP0noUYJansuScH2JrNJuVymUqlkuqyjGmzZVnU63U8z4sTl6m5J6dANhqNuGQzDmUZ3/fjgVS4O30ViN9fs9lkZ2cnPijNPO8okmWZMAxZWFi450FUQkyaVCX37hkYURRRLpfZ2NigWCzGSTKKotSVMpLtDoKAnZ2deKaMaa95jud5bG1tEQRBnPTNsqOk+39VKpVoNpvx35Kn4fV9n1KpBNBxZa3Dvufkl6gZrF1YWODEiRN7Tr+URC8mVaqSO3TOBTfT69bX19nY2IjP695rr28QkokliiI8z+uoMSeTjEnu5XJ51xfaKOmezthsNuPknvw73E3utVot7tEf5Qs6ubdgjoFoNpucP39+1zEFQkyy1CX3bp7nsbOzQ7lcBoh7bKMsiiJqtdqwm3GsTCmq0Wj05fWScZDP5/E8b+TjQoh+Sv2Aave53OUDLKAzDkzZSwhxV+qTu5l5YiR/F5Ore1bOKJ1UTojjkPqyTPel1JKnIEhzjfogPck0t/8ojuM9J8dkRiEOhBiW1Cf35CwTc3KqcZnyNurtP4p+vOe94mASt6UQ9yL7skIIMYYkuYuxIKUZITpJchdCiDEkyV0IIcaQJHchhBhDktyFEGIMSXIXQogxJMldCCHGkCR3IYQYQ5LchRBiDElyF0KIMSTJXQghxpAkdyGEGEOS3IUQYgxJchdCiDEkyV0IIcZQT8ldKTWvlHpWKfUdpdQrSqkfVkqdUEr9vVLq9fbPhX41VojjIrEtRl2vPfdngL/VWj8MfD/wCvA08GWt9UPAl9v3hRg1EttipB05uSul5oAfAT4JoLVuaq1LwAeBT7Wf9ingZ3ptpBDHSWJbjINeeu4PAHeAP1FKfUMp9UdKqQKwpLVeaz9nHVjqtZFCHDOJbTHyeknuDvADwB9qrS8BVbp2U3XrqsV7XrlYKfWUUuoFpdQL1Wq1h2YI0Xd9i+2Bt1SIffSS3G8CN7XWz7fvP0vrA3FbKXUWoP1zY6+FtdaXtdaPaq0fLRQKPTRDiL7rW2wfS2uF2MORk7vWeh24oZR6Z/uh9wIvA38NPNl+7EngCz21UIhjlqbYVkrJxb/FkTg9Lv8rwJ8rpTLAVeDf0frC+Cul1EeAa8CHelyHEMMgsS1GWk/JXWv9TWCvXc/39vK6QgybxLYYdb323IUQxyBZmmmN5Qpxb3L6ASFSTGsdJ3Opv4vDkOQuxAhIJnkhDkKSuxAjRBK8OCipuQsxIroTu2W1+mZRFA2jOSLlpOcuxAgy9Xepw4v9SHIXYgSZGrxSCtu24168EIaUZYQYUaYcY1nWruQuA7BCkrsQI8wkccuysG07LtGEYUgYhkNunRgmSe5CjDCtdUcPXurvwpBCnRAjLpngzX0hJLkLMQZMjz050Oo4zq6evPTsJ4ckdyHGSBRFRFGEZVk4joPjdFZepVc/OaTmLsQY0FoThmGcvE393SR33/eH2TwxBJLchRgD3VMfwzBEKYXruriuC9xN8MkSjhhfktyFGENRFBEEQVyeyWQycS9ea00QBARBMORWikGS5C7EmIqiKO6tmwRvWZYk9gkhyV2IMZaswycPcpKSzPiT2TJCjDkzg8b8rrXuSPRiPElyF2ICmHPPmJ58LpejUCh0TJWUZD9epCwjxATQWuP7fjzImsvldtXfpVQzXiS5CzEBfN/H932iKMK27fhAJzG+JLkLMQGS554JwxDP82g2mx2zaSzLwvf9jgtyS29+dElyF2ICNRqNOOE7jsPs7CwA5XJZjmYdE7JfJsQESvbkbdsml8uRz+exbTt+3JyATE4lPJqk5y7EBEqWXMx5afYrw0hpZjRJchdiwoVhSLVaRWtNs9nEsizy+TxRFFGv14fdPHFEktyFmEDJ3ngURdRqtbhUMzU1xeLiIr7v02w248v1yQDraJHkLsSE6z6jpJkHPzU11dGbbzabVKtVuTbriOhpQFUp9R+VUi8ppb6tlPpLpVROKfWAUup5pdQVpdRnlFKZfjVWiOMyabGdHDD1fZ9arQbA4uIiFy5c4Ny5cxQKhY6BWJknn25H/u8opc4B/wF4VGv9vYAN/Bzwe8AfaK3fARSBj/SjoUIcl0mPbc/z2NraYnt7G2iVaVzX3dXDF+nW61evA+SVUg4wBawBPw482/77p4Cf6XEdQgzDRMW2mfZo6uq1Wo1yuUwQBIRhGJ+iQHrro+PI/ymt9S3gfwLXaQX+NvAiUNJam5NF3wTO9dpIIY7TJMd2sjxjLtMXhiHNZpPp6WkuXLjA3Nwc0BqINUe2ivTppSyzAHwQeABYBgrATx1i+aeUUi8opV6oVqtHbYYQfdfP2B5QEwcmWXaxbZswDCmVSlQqFaanp3nggQc4c+ZM/By56Ed69TJb5ieA72qt7wAopT4PvAeYV0o57R7OeeDWXgtrrS8DlwFWVlakkCfSpG+xrZQamdjurqd7nsft27fjwdWZmZn4SNbu5VzXRSlFFEUdFwgRw9PL/tR14HGl1JRq7cu9F3gZ+CrwRPs5TwJf6K2JQhw7iW2gXq9TLBbxPA/P8ygWi2xsbFAqleLn5HI5bNuO58QHQSCJPSV6qbk/T2tw6Z+Af2m/1mXgt4BfV0pdARaBT/ahnUIcG4ntvZVKJd544w2uXbsGwMWLF3n3u9/N/Pz8kFsm9tLTQUxa698Bfqfr4avAD/XyukIMm8R2S/Kaq41GIy7RACwvL/P2t78d13Wp1+uEYcjU1FT8vOTsG+nNHz85QlUIcSTNZhPXdXnooYc4c+YMmUyGcrnMSy+9xPXr1wFwXTeeTimOl8xhEkLsK9nrNqf/NVZXV7l69SoAjzzyCJcuXeL8+fPxUaxaazzPk8Q+JNJzF0IciDktsJkiubq6Sr1ex7Iszpw5E5duGo3GsJsqkOQuhDgErTWWZcW98WKxGCf4MAzJZDI8+OCDzM7OYlkWURSxubkZn8pAHB9J7kKInuTzeSzLIggCpqenefzxx1lcXCSbzfLaa6/xpS99SZL7EEhyF0IcSrKGnslkKBaLfPvb3yYIAjKZDA8//DDvfve7mZubo1QqsbOzEz//1KlTeJ5HpVLpOMOk6D9J7kKIQ0km5SAIeOONN3j11Vep1+ssLS0xNzdHo9HAcZz4Ck+G7/sEQSCJ/RjIbBkhxJFFUUS5XI4vx7e5uUkmkyGKIjY2NshkMvzYj/0Y73jHO4DWgVDJufJicCS5CyF6ksncvWbJzMwM09PTVCoVXn/9dQqFAh/+8If56Ec/ytLSUvy85NknxWBIWWYEyLUrRZolp0cCfOc73+HKlSu8+eab/OAP/iA/+7M/y6VLl9Ba89JLLzE/P8+tW7f46le/yp07d5iamkIphZwdtr8kuY8ASewizTzPi3/f2dnhueeei0svzWaTf/iHf+B973sfTz31FDMzMwD82Z/9GV/72tcAqNVq8eOif6QsI4TomzAMO2rqr732GpcvX+Yv/uIv8H0/flxrzcbGRny/XC4fazsngSR3IUTfua5LoVAA4MUXX+Tzn/883/3ud+O/e57HqVOn4vvSc+8/KcukmG3bZDIZbNtGa02z2ezo/QiRVrlcjlwuF9fRPc/rODXwY489xm//9m/H95977jmeffbZuASZyWRoNpvH2+gxI8k9ZZKDp5lMhoWFBaampvB9n2Kx2JHcZaBVpFWtVuu4BN/8/HzHUaqLi4t87GMfi2fNBEHA5z73ufhC3a7rSnLvkST3FOmeHmaS+8LCAvV6Hc/zOo72EyKtwjDsOIHYrVu3+MQnPkE+n6fZbHLp0iV++Zd/mWw2C7QGXpNnk5SDnHonyT3FTA8mm80SBAG2bXf8PXkCp0knezDpk/yfXL16lStXrsT3b968yRNPPMHy8jLQuqSf67r4vo9t2zjO3dSUPM3wfpIXFelHe4+T2Vvpvt9reyS5p1gQBFQqFWzbptFodEw5M8FwlINBxj0RmnOQj/v7TIvuRHSQxOQ4DouLi/H9ubk58vk8vu+TzWbJZrM0m0201rs6NYZZh2VZWJYV9/i7k+VB9BozyStOJc9/f5B1DqpdqU3uk3gEW/c/sNlssrW1RbVaJQiCjilmWmvptSckv+ySv0uCH7zubbzXNnddN75Sk/GNb3yDxx9/nLfeeovXXnstLjnWajUajYaUZnqUmuSe/FB2Pz6pfN9nZ2cnTlIS7Pdmdt+792omOYbSwgyOmv/RN7/5TZ5++mnOnz/P9vY2//iP/9jxfIn13qUmuUdR1NHTMrtXk9zz0lp3zDgwbNvGsqxD9UyTXxBm246TKIoIwzC+mfc36TE0SN2X3bvX88Iw7Cgrrq+vs76+Ht8vFAp83/d9H5ZlsbOzQxiGuK4L7L0noJSKY9mUcaIootFoxN1qBoUAAAndSURBVONTB/18mNdqNpvx1aYOu9dnnp+8Xux+4wDmcROzyTJO93ODIKDZbO6ZB+4nFcndbBQTBMnpUck3L1qJfXZ2ltnZWRzH2be+1z0oY7ZttVple3t7rKaZRVFEEAR4nhdfkNnUak0CEP2XyWTI5XJxcoTOOEzWvs2XrIlJy7I6pkY+8cQTfPSjHwVaBz2Vy2UWFhawLCue/ptc1rKsuHRz9uxZLly4QKPR4OrVq2xvb5PNZnFdN84fe30+TIzYtk2tVmN9fZ1KpRKfK6f7PewliiIsy8K2bXzf7zh/vRkUTuav5BhCvV6nUqnEg8jJur35vJZKJW7dukWxWOzYvgfJialJ7ibZmB58FEX4vi/JHeLBIq11PBB18eJFpqam4l64eU5S8kNngm91dRXP8+LtPQ51adNjK5fLHb0hc/CXJPfBMAfZmTg7yECmed7c3Bzz8/Ncu3aNubk5Hn30UR577DGgVZ8vlUqcOnUK27Z3xapJhLVajTAMefDBBzl9+jQAy8vLbGxsUCgU7pvcoyjCdV0cx2F7e5vr16+zubmJZVlkMpl7xk4yEVuWheM4eJ7HxsYGW1tbwO7kbn6a9u/s7FAqlWg2m/HeeDK5m976nTt39lz3/aQiucPdGluyBzCO5YNeOY7D/Pw8586dY3Z2Ng6A/XaPzfY0wddoNFhdXY3/Pg7J3ez5eZ4Xn53QfOhA6reDZHquBy1/meeFYRjHbrPZ7DgjZLlcplwuk8vlOnruZnnTUzbJfXt7m9OnT9NoNNjZ2Ymv8pTJZOK9uKRkidJ8QVUqFarVKrVarWOdh03uyQuEm7JSd8nZ9Nx9349vyfUke+57tf+gUpHck7XlZHKXskxL9wfHbK/k9rlfcodWME1KDfoodVNxeIcdrDbPTx7kVK/XO+LUlEocx9m1R2p67iahKqXiHrLjOPHNfAEke8LJNpgvGNd14/WZW3LZ/ZiLf5vf91o2+ZlMxmJy4D85kSS5p2le/yBjGvtJRXKHvWc47DeDZpIFQcDm5ibXrl0jn8/vWetMSgZUEARsbGx0DGyNS/IzsdK9ayvxM3h7TUO9l2RvF+6Wd4xMJhPfzMSB5LImiZoOjjnK1XEcMplMfOBfNpuN42Gv5B5FEY7j4LpufHMcB9u2cV03fs5Bau6mBGSWN+8ruX2M5JdR9xdVMm7N2MJRYzgVyd18+yYHVJPfwJP+AU0mYN/32dzcjK9RuVfPZK/lTeCYOcR7vfYoSbbbnGZ2e3u7Y5zG9HrkeIDBMKWw5NjO/SQH+E3pQ2vN17/+dT772c8SRREvv/wytVqN2dnZeA8+OZBocoKZ3XL69GmWl5fxPI+bN2+ys7NDNpvFcZwDDaiawdnNzU0qlco9e/3dugdUy+VyfN3Y7kHZ7p57o9GIz8Fjknl3eWZ7ezu+hGFy+x1EKpJ7GIbxKHUyuVerVTzPk5ppQhRFcX3wKMaxLGO+8BzHIZvN7pqKltxTEf3Ty1lK6/V6x7TnL37xi3zlK18BiGvQ9ytJJGvYJhmHYXjf3vZ+r5WcWXXUDuVhXsN8Fu/1eTQTBLqXO4hUJPd6vc4///M/xz0A8y1mBv/GsYzQi3FM0IeVfP/NZpM7d+7Ep2ro3jaS3AfnqHHYPbe7Wq3KZfb6TN3vn6OU+mPgA8CG1vp724+dAD4DXATeBD6ktS6q1lfVM8D7gRrwYa31P92vEY7j6OS5ntvriA98kEORxUHca9xBa73rj8cR20qpyf4WFgO3V2zDwZL7jwAV4E8TH4D/AWxprX9XKfU0sKC1/i2l1PuBX6H1AXgMeEZr/dj9GicfgMPrZRxiEnv9+yR3ie0+OMqspO5lzAAqsG+dvFuyht3vE4cd9QjVwyxzkOcfpHSzX3LvWHi/G61ezLcT918FzrZ/Pwu82v79fwM/v9fz7vP6Wm5yG+RNYltu43rbL/aOOolySWu91v59HVhq/34OuJF43s32Y/dlvn27b5M+U0YcTHLqbPftkPoe20IMQ88DqlprfZRdT6XUU8BT5r7U1EUvBlFq6ldsCzEMR+2531ZKnQVo/9xoP34LWEk873z7sV201pe11o9qrR89YhuEGASJbTEWjprc/xp4sv37k8AXEo//W9XyOLCd2MUVYhRIbIvxcIABob8E1gCfVp3xI8Ai8GXgdeBLwIn2cxXwv4A3gH8BHj3ggO3QByXkNt43iW25jettv9i771TI4zAJ08XEcO07XWzAJLbFoO0X20c/5ZgQQojUkuQuhBBjSJK7EEKMIUnuQggxhlJxVkjgLaDa/pk2J5F2HUYa2/W2Ia5bYvvwpF0Ht29sp2K2DIBS6oU0HvQh7TqctLZrmNK6TaRdh5PWdu1HyjJCCDGGJLkLIcQYSlNyvzzsBuxD2nU4aW3XMKV1m0i7Diet7dpTamruQggh+idNPXchhBB9korkrpT6KaXUq0qpK+1Lmw2rHStKqa8qpV5WSr2klPrV9uMnlFJ/r5R6vf1zYQhts5VS31BKfbF9/wGl1PPtbfYZpVTmuNvUbse8UupZpdR3lFKvKKV+OA3bKw0krg/cvtTF9jjE9dCTu1LKpnW2vfcB7wJ+Xin1riE1JwB+Q2v9LuBx4GPttjwNfFlr/RCtMwYO44P6q8Arifu/B/yB1vodQJHWGQ2H4Rngb7XWDwPfT6uNadheQyVxfShpjO3Rj+uDnLZ0kDfgh4G/S9z/OPDxYber3ZYvAD/JPtfVPMZ2nKcVTD8OfJHW6WffApy9tuExtmsO+C7tsZvE40PdXmm4SVwfuC2pi+1xieuh99xJ6bUplVIXgUvA8+x/Xc3j8gngNwFzLcJFoKS1Dtr3h7XNHgDuAH/S3q3+I6VUgeFvrzSQuD6YNMb2WMR1GpJ76iilpoHPAb+mtd5J/k23vraPbYqRUuoDwIbW+sXjWuchOMAPAH+otb5E6zD7jl3V495eYn9piut2e9Ia22MR12lI7ge+NuVxUEq5tD4Af661/nz74f2uq3kc3gP8tFLqTeDTtHZfnwHmlVLm3EDD2mY3gZta6+fb95+l9aEY5vZKC4nr+0trbI9FXKchuX8deKg9Qp4Bfo7W9SqPnVJKAZ8EXtFa/37iT/tdV3PgtNYf11qf11pfpLVtvqK1/kXgq8ATw2hTom3rwA2l1DvbD70XeJkhbq8Ukbi+j7TG9tjE9bCL/u3BifcDr9G6PuV/GWI7/jWtXa1vAd9s397PPtfVHEL7fhT4Yvv3twP/D7gCfBbIDqlN/wp4ob3N/g+wkJbtNeybxPWh2piq2B6HuJYjVIUQYgyloSwjhBCizyS5CyHEGJLkLoQQY0iSuxBCjCFJ7kIIMYYkuQshxBiS5C6EEGNIkrsQQoyh/w8/RbpDN87oVAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0b99e8>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3777,23 +2725,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.791 \n",
-      "FIRE        0.791 \n",
-      "RIGHT       0.790 \n",
-      "LEFT        0.791 (Action Taken)\n",
-      "RIGHTFIRE   0.789 \n",
-      "LEFTFIRE    0.791 \n",
+      "NOOP        0.600 (Action Taken)\n",
+      "FIRE        0.595 \n",
+      "RIGHT       0.596 \n",
+      "LEFT        0.599 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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TJwFsrNiEFKL53qbDsl6vUyqVbJz9vvvuw/M8SqWSzZxpxaQSaq3JZrPU63Wu\nXLnC6dOnmZ6exnVd63VHvePWl2REKZVK5PN5EomEFd6lpSUbCz948KCtv3layeVyVixPnTpFrVYj\nm83azJ16vc709DT33HMPExMTJJNJFhcXbfpntVptEvmVzrNardr8/aWlJRvvd12X6elp3nnnHX72\ns58By3F3kydvhLe1YzladrlcZn5+niAImtIrNyL00XlzTB+Lqbc5zkrtLQg7mdgJfeuFagQ5mUw2\ndXyaTsFo+qAJG6xGdFsTWjAdjEagVhN6E/Yxg5oAyuUycDvksZFzNB3J0fi98T6TySSpVMrWxfd9\nEokEg4ODdnCUOZdSqdQU545m4UQ7PU29TfgrWhcTmoo+LZn4ujlns1/0yWRpaWnd52zOz/zvzECv\njQq9eWqKDlgzfRLQbDeCICwTO6GPEs2sMdkaWmu7nkqlrBcPt4VytQ4413VtCMZxHJsZExXbu3n0\nZpSqyV4xoQrT6bgarcJjbl6JRMLu57quFdxovN48KZjQjWkT83v02NHsFnMTiwp9VBRXa2/Ttial\n02S1mHNeqT3XgznndoQ+ekMyHelrTWUtE50JQgyFvnVKW5PFcuPGDTvy0XEckskkN27csNkuxjs3\nYYqVOmNNvNtkqVQqFa5fv04YhlQqFVtGK9FRoOl0mnq9bkMi5nezn+nQbRXA6OcgCJifn2dqasrG\n1+G20JsOY7OP8eJTqRQLCwssLS3ZbJlWkXMch4WFBaampmyHtcnO8X3fhk6i9Yp25hYKBaanpymV\nSjajqVAo4Lout27dauroNO1psnDWEn3TZtPT0xQKhTtG9K6XqH2Yvg+Tw2/OP9reEqMXhJgJfTSE\nYIRzdnaW06dPc/XqVQYGBqwX6bquHXVphMsI/GpeXDQN0/d9pqenOX36NLlczmaIrCYMRhBNlsjk\n5CSLi4v2t2h8fiWiv5XLZS5cuGBH+5owTPTmFA1BROfmL5fLTE9P2xBKa2qpyfgplUo268bcGMMw\nZHJy0g5iMvtHP09OTnLq1Ck7rUEYhvYGe+PGjaaMG3PstcTdUKvVuHr1qvXq79beq2GOZZ5oisUi\n999/PwcPHgRu5+4bO5JYvSDETOjhzk6069ev89Zbb3HhwgWGh4dJJpO2s9Wk6UX3XevCjgqP6bgs\nFovWq1yPKJhYfalUaopR3y1EEP29Uqlw8eJFrl+/vuKNKdqRbM7L3PzMORuBNn0NhmKxyEcffcT0\n9LR9Eom1W8AJAAARQklEQVT2MZRKpSahj3roYRjaDKfWMJdSikql0tTeGzlncxPJ5/NtTTxm2iKd\nTlOpVJifn+fmzZt84hOfuGM7QRCWibXQm+kATKpiqVSyF3gnMGVuNSZ0Y/LnO0kYhhsqO9reJrwS\nFfNO0emyo3YwNTV1R2e4CL0g3GZbBDBb49uCsFoapyAIdxJ7ofc8zw6rN+uCELUDM5FcFEmvFITb\nxE41Wy/QaMesiRWv1Gm52WNtVhA2M2x/q469Vtnd3PdutHPOBpPVFM3/bx0bIAhCM7ET+lYhMbNM\nms8bydtez7F69djfzWO3U3Zc69VaTtQO1noDmSAI2yB0IwiCILRH7IW+E4/7Qn8j9iEIaxN7oRcE\nQRDaQ4ReEAShzxGhFwRB6HNE6AVBEPocEXpBEIQ+R4ReEAShzxGhFwRB6HNE6AVBEPocEXpBEIQ+\nR4ReEAShzxGhFwRB6HNE6AVBEPocEXpBEIQ+R4ReEAShzxGhFwRB6HPaEnql1LBS6ttKqQ+UUmeV\nUseUUqNKqR8opc41/o50qrKCsFWIbQv9RLse/VeA72mtPwY8CpwFvgT8UGt9CPhhY10Qthti20Lf\nsGmhV0oNAZ8Cvgagtfa11nng14CvNzb7OvDr7VZSELYSse2tQymF67o4jkSRu0k7rfsAcAP470qp\nt5VS/1UplQPu0VpPN7aZAe5ZaWel1PNKqZNKqZNzc3NtVEMQOk7HbHuL6rtt0VoThqG83L3LtCP0\nHnAU+COt9c8DRVoeZbXWGtAr7ay1fkFr/bjW+vHx8fE2qiEIHadjtt31mvYZ8v7f7tCO0E8Ck1rr\nNxvr32b54riulNoL0Pg7214VBWHLEdvuEkqppjBNIpEgl8uRSqWAZQ9f6DybFnqt9QxwVSl1uPHV\ns8D7wEvAFxrffQF4sa0aCsIWI7bdPZRSeJ5n13fv3s0jjzzCgQMHmrZzXXerq9bXeHffZE3+L+Cb\nSqkkcAH4XZZvHn+ilPoicBn4e20eQxB6gdh2BzGevFIK3/ft9xMTEzz00ENcvnyZjz76yHr0juMQ\nhmGvqtt3tCX0WuvTwEpxyGfbKVcQeo3YdmcxQi+hmd7QrkcvCIKwJo7jUK/XqdfruK7Lnj17KBaL\nFAoFpqenSSaT5PP5ppuAZOF0FhF6QRC6hsmTN8I9MTHBsWPHKBQKvP7661y/fp2FhYWmuD0gYZsO\nI0IvCEJXSCQSKKWsaI+NjXHs2DGOHj3K+fPnrbhXKhVJq+wyIvSCIHQck11TLpcB2LdvH8899xyP\nPvoohUKBmZkZarWa3V46X7uLCL0gCB0hkUjYfPggCKzIw7LQHzt2jGw2y+uvv87x48epVCo2E0c8\n+u4iQi8IQkcIgsB2qJrYvPHSgyBgYWGBq1ev8pOf/IT5+XkAUqkUlUpFsnG6jAi9IAgdQWtNEAR2\n/amnnsJ1XU6cOMG5c+f48z//c8IwZHJy0m4ThqGI/BYgQi8IQkdIpVJUq1UADh48yO/+7u+Sy+VY\nWlri1KlTvPrqqwwODjaFaaKDp4TuIUK/RXieZzMQJEdY6Ac8z7Me/O7du3nuued48MEHmZ+f5/Dh\nw/zKr/wKk5OTZDIZu8/S0hKJRAKttVwHW4gI/RYRfaQVhH4gnU6ztLQELHvmzz77LL/zO78DLKdM\nXrt2jTfeeIOZmRm7TzKZJAgCEfktRoS+yyilJAYp9CWJRMJ+zufzFItFu14sFvnGN77Bt7/9bS5d\nuoRSikQiQb1elzTKHiBC32W01jiOQy6Xw/M8KpVKU9qZIGxXTDweltMnozNOTk5O8t3vfpczZ84A\nkMvl8H2/KXde2DpE6LtENLUsm83yS7/0S+zZs4czZ85w+vRpu43EKoXthonNl0olXNfl2Wef5bd+\n67f4zGc+Y7eZmJho2sd1XcmV7yEi9F3C87wmoT927BhHjhwhCAIr9GY2PxF6YTuRyWQoFArAcqbN\n888/z2c/+1kArl+/zsjICDMzM+zatcvuU6vVxM57iAh9l4h6L47jMDg4yMjISFMGgng4wnYkOgGZ\n4zg89NBDAPz1X/81v//7v4/jOIyPj3PlyhW7XbValb6qHiJC3yWiHU7VapWzZ89SqVS4evWq/b5e\nr4vxC9uOaJw9DEPeeOMN6vU6X/nKV3j11VdX3Ee8+d4iQt8lokJfLBZ57bXXeOutt5idnV1xG0HY\nLkSTCXzf56tf/Srf+MY3eO+993pYK2EtROi7RNSD8X2fjz766I5txJsXtiPGQTGdsj/96U/tbwMD\nAziOQ6VSoVariY3HBBF6QRA2xUoibkZ+i8DHCxH6LcKkl5lXqgnCdsd49ul02nrxMkYknojQbxFa\na7sIQj8RBIFkkMUcEfotQrx4oV+ReZzij9PrCgiCIAjdRYReEAShzxGhFwRB6HNE6AVBEPocEXpB\nEIQ+R4ReEAShzxGhFwRB6HPaEnql1D9RSr2nlDqjlPqfSqm0UuoBpdSbSqnzSqk/VkolO1VZQdgq\nxLaFfmLTQq+Uuhf4v4HHtdaPAC7w28AfAH+otf4bwDzwxU5UVBC2CrFtod9oN3TjARmllAdkgWng\nGeDbjd+/Dvx6m8cQhF4gti30DZsWeq31FPDvgCssXwQLwCkgr7U2Y6IngXtX2l8p9bxS6qRS6uTc\n3NxmqyEIHaeTtr0V9RWEu9FO6GYE+DXgAWAfkAN+eb37a61f0Fo/rrV+fHx8fLPVEISO00nb7lIV\nBWFDtBO6+ZvARa31Da11Dfgz4ElguPG4C7AfmGqzjoKw1YhtC31FO0J/BfiEUiqrlucofRZ4H3gV\n+I3GNl8AXmyvioKw5YhtC31FOzH6N1numHoLeLdR1gvAvwT+qVLqPDAGfK0D9RSELUNsW+g32pqP\nXmv9r4B/1fL1BeAX2ylXEHqN2LbQT8jIWEEQhD5HhF4QBKHPEaEXBEHoc0ToBUEQ+hwRekEQhD5H\nhF4QBKHPEaEXBEHoc0ToBUEQ+hwRekEQhD5HhF4QBKHPEaEXBEFYg+V57bY3IvSCIAhroLXudRXa\nRoReEAShzxGhFwRB2ATbKaQTK6FXSm2rxhN6R/Rxul6vr7iN2JIgLBMrodda3xEP64f4mNB5HOe2\n6bqui1LK2oqxI631qjcBQWiX7aRNsRH6lS7I7dSQQndRSuE4jv1rFsB+H7WXlZwGQdiptPWGqU5i\nLtbo47aEcgRDVLi11gRBYJ0D3/ep1+tW+JVSuK5rPX1B2EpanY44EAuP3gi6WaIXrFyowkpEnwAr\nlQphGOJ5y36L53k4jiNiL/SEqMjHRcNi4dFrrQnDEFi+gM1FHP0s7Gxc17VCrpQik8lQLpepVCrk\ncjlc1yUIAgCCICAMQ2q1moRwhJ4TBw8/NkJfq9UIggDf9wnDkGw2S7VatRevsLMwXpC5QMbHx9m/\nfz+ZTIZ6vY7nefi+z9LSEgcOHGBoaIjFxUW01hQKBbtN1IkQhK2kNQy9kti32nm3iIXQh2FIsVjE\ncRx838fzPFKpFKVSyXplws7CcZwmb/zgwYM888wz7Nu3z4ZqlFKEYUgul2N8fJxr166RSCSszZgy\narVaj89G2AybDXmsJaibZS0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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8965455518>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3802,23 +2750,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.781 \n",
-      "FIRE        0.799 (Action Taken)\n",
-      "RIGHT       0.791 \n",
-      "LEFT        0.809 \n",
-      "RIGHTFIRE   0.764 \n",
-      "LEFTFIRE    0.796 \n",
+      "NOOP        0.572 \n",
+      "FIRE        0.566 \n",
+      "RIGHT       0.545 \n",
+      "LEFT        0.704 (Action Taken)\n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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bzVKv17l8+TKnTp1ienoa13Wt1x31jltfkhGlVCqRz+dJJBJWeJeXl20sfGJi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\nHBF6QRCEPkeEXhAEoc/5/+ZhsAJWyUBuAAAAAElFTkSuQmCC\n",
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bJSbEWZeo5B7/YprkPj09zaVLl2g0GvKFFftorclms0xNTWHbdtSzl7Hv4qxLVHKHzh6XUopsNsv09DSe50lyF/torUmn0+RyuX2xI8RZlrjkfhjphYmDmB66xIcQnRKf3M3Y9jAMpTcm9pFzH4Q4WOKTu2VZOI4THUQ1B9LE2RaPA8dxZCikEF0Sm9xNT8xxHDKZDI7Taqo5WCbOtngc2LaN4zgSG0LEJDa5w93rypgvrpRlRDczqkp67kJ0SnRyh7sJ3oxxFyJOTmYT4mCJT+5xsssthBBHMxL7sjLUTRxGYkOIg41Ez92UZmT3WxxE4kKI/RKf3OM36pAvsTiMxIYQnRKf3ONk91sIIY5GkrsYadJjF+JgI5Xc5YsshBBHk/jkbk5ikl67OIwcjxFiv8Qn9/jJS/EvsJy8cjZ1/98lDoQ4WKKTe/zMVPkCi8PIZX+F2K/n5K6UsoGXgXe01h9USj0IvADMA68AP6u1bvbw/h3XDgnDUK4jIjriwNxLtd/JfdCxLcQg9SNL/iLwWuz1bwK/rbX+DqAIfKSXN+8e527bdsdJTfI4m494HMTjpM8GGttCDFJPPXel1CXg3wD/A/hl1fqGvQ/46fYknwD+G/C7J12G2d0OgqCXpooxNoiSzGnEthCD1GtZ5neAXwWm2q/ngZLW2m+/vg1c7GUBQRBIYhdH0ufe+8BjW4hBOnFyV0p9ENjUWr+ilPqhE8z/HPAcwOzs7IHTaK3xfR/f9+XuS+JQlmWRSqWiUk2v+hnbQgxLLz33p4EfU0p9AMgC08DzQEEp5bR7OJeAdw6aWWt9FbgKsLKycuA+tSnHNJtNgiAYVF217+IlgoPKBQOuEw+N+az3+szdz/uxTJPU+3jN/77FtlJKhvCIoThxctdafwz4GEC7d/OftdY/o5T6FPATtEYVPAt8tpcGmhsgB0EwUqNk7pfAx3XoXvwg50H6/bnNjdP7+Z6nFdtCDNIgxrn/GvCCUuq/A/8AfLzXN+xzr+xUxEd2dBvXcdlH+cz9dsrnQfQ9toUYlL4kd631l4Evt59fB763H+8Ld8cw+74/MsndlJOCIIh6lub3JhE5jjNyG6x7MXtYvu9Hiby7FGPbdt/q4vHlAgM76D7I2BZikBJ7hqrZ1fZ9n1qthud5UWJMSo/XtCXeJqUUnudRqVSoVCp4ntcxLUA2m2VqaoqJiQls2+6Yt/v9kuawzxwEAdVqlXK5TKPR6JgWIJVKMTU1RT6fJ5VK9fyZzfRaa1KpFKlUat8yhTjLEpfc4z0+rTWNRoNKpUK9Xo96ukn88po2WZaF67psbm6ytraG67pYloVlWfh+axTdzMwM58+fZ35+HsdxopFAo9aLj3/mZrPJ9vY2q6urVCoVgOizhWFIPp/n3LlzLC0tkclkev7M8eSezWbJZrPRxtK0bdTWpxD9lLjkHmd67q7rJj65m/KLbdvUajW2t7d55513qFQqUTnCJPdqtUo2myWXy5FKpUY+udu2TbPZZGdnh7W1NYrFYlR6MqWpqampqPduylZa6xMfJI8nd6VUVA4SQrQkOrnHjVLi01rTbDZxXbdjrL7hum5UI46XJUZNdzI1G2KzsYrXwV3X7VgHQojBGomxhaOW+EwP3nHubjvjPVRzMDU+ffznKDhoZIzZQzEO+szdB1lH6TMLMUoS2XOPH2BrNpuUy2UqlUqiyzKmzZZlUa/XaTQaUeIyNff4EEjXdaOSzTiUZTzPiw6kwt3hq0D0+ZrNJnt7e9FJaWa6k4iXZYIgYHZ29p4nUQlx1iQquXePwAjDkHK5zObmJsViMUqSYRgmrpQRb7fv++zt7UUjZUx7zTSNRoOdnR1834+Svpl3lHT/r0qlEs1mM/pb/DK8nudRKpUAOu6sddzPHN+ImoO1s7OzzM3NHTj8UhK9OKsSldyhcyy4GV63vr7O5uZmdF33Xnt9gxBPLGEY0mg0OmrM8SRjknu5XN63QRsl3cMZm81mlNzjf4e7yb1Wq0U9+pNsoON7C+YciGazyaVLl/adUyDEWZa45N6t0Wiwt7dHuVwGiHpsoywMQ2q12rCbcapMKcp13b68XzwOcrkcjUZj5ONCiH5K/AHV7mu5yxdYQGccmLKXEOKuxCd3M/LEiD8XZ1f3qJxRuqicEKch8WWZ7lupxS9BkOQa9VF6kklu/0mcxmeOH5MZhTgQYlgSn9zjo0zMxanGZcjbqLf/JPrxmQ+Kg7O4LoW4F9mXFUKIMSTJXYwFKc0I0UmSuxBCjCFJ7kIIMYYkuQshxBiS5C6EEGNIkrsQQowhSe5CCDGGJLkLIcQYkuQuhBBjSJK7EEKMIUnuQggxhiS5CyHEGJLkLoQQY0iSuxBCjCFJ7kIIMYZ6Su5KqYJS6tNKqW8ppV5TSr1XKTWnlPq8UuqN9s/ZfjVWiNMisS1GXa899+eBz2mtHwXeA7wGfBT4gtb6YeAL7ddCjBqJbTHSTpzclVIzwA8CHwfQWje11iXgQ8An2pN9AvjxXhspxGmS2BbjoJee+4PAFvCHSql/UEr9vlIqDyxprdfa06wDS702UohTJrEtRl4vyd0Bvhv4Xa31E0CVrt1U3bpr8YF3LlZKPaeUelkp9XK1Wu2hGUL0Xd9ie+AtFeIQvST328BtrfVL7defpvWF2FBKnQdo/9w8aGat9VWt9ZNa6yfz+XwPzRCi7/oW26fSWiEOcOLkrrVeB24ppR5p/+oZ4JvAXwLPtn/3LPDZnlooxClLUmwrpeTm3+JEnB7n/wXgj5VSaeA68O9pbTD+TCn1EeAG8OEelyHEMEhsi5HWU3LXWv8jcNCu5zO9vK8Qw5ak2G6V94U4HjlDVQghxpAkdyESrLvXLvV3cVSS3IUQYgxJchdihEj9XRyVJHchhBhDktyFGFEyBl7ciyR3IUaUKdFIkhcH6fUkJiHEkB2U2KU2LyS5CzHCunvvJtGHYSgJ/oyTsowQI05rLYlc7CPJXYgxIMlddJPkLsQYiNfdtdYopbAs+XqfZfLfF2KMmBKNSe6S4M8uOaAqxBgwZZn4T6UUtm2jlCIIgmE2TwyBbNaFGBPxursZLWMSvG3bQ2yZGAbpuQsxpsIw7EjupkSjtSYMQ8IwHHILxSBJchdiTJkkHq+/K6UksZ8RUpYRYoyFYYjv+1HN3YyqkaGT40+SuxBjLn6Sk3kuo2jGn/yHhTgDunvsjuOQTqclyY8xqbkLcUaYWrtSCsdxpP4+5iS5C3EGBEFAEARRScYkdzG+JLkLcQZ0j4H3fb/j5CYzkkZOdhofktyFOIN8348SvmVZZLNZAFzXjco0SikZVTPC5GiKEGdQPGmbGnwqleo4wCp3ehpt0nMXQtzzmvDSex9NktyFOOPCMKTZbKK1jmrxqVQKrTWe5w27eeKEJLkLccZpraPkDpBKpcjn8wRB0FGbF6NFkrsQ4tAavOnNW5ZFEAQ0Gg1J9iOipwOqSqn/pJT6hlLq60qpP1VKZZVSDyqlXlJKXVNKfVIple5XY4U4LWc5toMgiMox+Xyeubk5ZmZmSKfT+zYCIrlOnNyVUheB/wg8qbX+LsAGfhL4TeC3tdbfARSBj/SjoUKclrMe277vU61WcV0XaJVpbNuWHvuI6XUopAPklFIOMAGsAe8DPt3++yeAH+9xGUIMw5mMbdMb9zwP13UJgoAwDPddVVIk34mTu9b6HeB/ATdpBf4u8ApQ0lr77cluAxd7baQQp0liu8Xc6ENrTRAEZDIZZmdnyeVyANGlDCThJ1MvZZlZ4EPAg8AFIA/86DHmf04p9bJS6uVqtXrSZgjRd/2M7QE1cWDipRfLsgjDkHq9TqPRIJPJMDc3x9TUVDSNXHQsuXoZLfN+4C2t9RaAUurPgaeBglLKafdwLgHvHDSz1voqcBVgZWVFinkiSfoW20qpkY1t3/epVCo0m00AstlsNIqmm7lHq7n7kxi+XmruN4GnlFITqrVf9gzwTeBLwE+0p3kW+GxvTRTi1Els06q712o1fN/H933q9TrVapV6vR5NY64uaa46KYk9OXqpub9E6+DS14B/br/XVeDXgF9WSl0D5oGP96GdQpwaie2D1Wo17ty5w87ODgBzc3OcP38+qsGLZOnpJCat9a8Dv9716+vA9/byvkIMm8T2fr7vd1yOYHp6mvn5eWzbxvM8wjAknU7jeR6e58n9WodMzlAVQpxIGIbYts3CwgKTk5M4joPrumxsbFAsFtFa4zhOdJMQcbrkkr9CiCOLD3sslUpsb28DsLS0xMWLFykUCh2JXK5NMzzScxdCHEn85h5hGLK3txeVX8zwyO7SjRgeSe5CiGOJ997r9XqUzONlmmw2G93JKX4pA3F6JLkLIXpirj0ThiGZTIYHHniAfD6PbdtsbW3x7W9/W5L7EEhyF0IcS3wsu23b1Ot11tbWCIIAx3FYXFxkeXmZbDaL67odiT2fz+P7fsf148VgSHIXQhxLPCmHYcidO3fY3NzE8zympqbIZrN4nodlWft67GEYEoahJPZTIKNlhBAnprWm0WhEdfdqtYrjtPqM5XKZVCrFww8/zMLCAtBZoxeDJcldCNETc10ZgEwmQyaTwXVdtra2SKfTfM/3fA9PP/10xwXHxOBJWUYI0ROlVDQyBmBjY4OtrS12dna4dOkS7373u7l48SJaa9bX18nlcuzu7vLmm29SqVRIp1s3tGo0GsP8GGNHkrsQoie+70fPG40G169fj64kGQQBb7/9No899hjf//3fz/T0NEop/vZv/5Zr165FZZ1MJjOs5o8tKcsIIfomDMMosQNsbW3xla98ha997WsEQcDKygoLCwsEQUClUommk157/0nPXQjRd7ZtY9s2zWaTW7duoZTi4YcfptlsUqvVCMOQycnJKMGbYZOifyS5CyH6znEcHMfpKM/k83nS6TSpVIpHHnmExcVFUqkUYRjy6quv8vLLL1OtVsnn8wRBQK1WG/KnGG2S3IUQfWcuAWzkcjlc1+XWrVtUq1Xm5ub4gR/4AR5//HE2Nzf5vd/7Pb70pS8BrSGUUoPvnST3ERUfnSBE0piTlYy9vT1efPFFvvzlLxOGIe9+97t59NFHKRQKlEol9vb2OuaXGnzvJLmPKEnsnWR9JNv29jabm5vRa8dxqFQq0a37ZmZmWF5eZnd3l9nZWTzP486dO2itsW27ozOjtd73/zbDMY/ioPnjfzPvd9T3SupNSSS5j5CDeuvdY4zvJWnBNyjmy3tWPu8oymazzM7Okk6nmZyc5JlnnuGHf/iHWV5eplQq8cILL/CpT30K3/eZmpqKLmVgEqm5ryvcre/Hk2w8OZvXSinCMCQIgmje7sTcj5jpZ9z1EseJTe5H3XKeJfHraZtAlSTWYuIl3oOT0lVyWJZFKpWKRsRYlsVbb71FtVqlUqlw5coV3vve90bTf+5zn4sScKlUuud7B0EgZZwDJCa5H7ZbJUl+v6mpKXK5HLVabV+t8iyzrNZpG/HkHv8phqf7jkxvvvkmV69eZWdnh4mJCX7u534uSu7f+ta3eO2114bV1LGRmOQehmFHT0t6pXfF10s+n2d5eZmpqSmKxSK+7+O6brRbGj+IFZ933K/GZ3a3zeNe9VnRP/crC5oNaxiGHWeyrq2tcevWrej117/+dSqVCpOTk7z11ltcvHiR7/zO78TzPCYmJqKbcFuWhed5lEolyuVydBeoQqFAOp2O4jzeLlOWsW0b3/fZ3d2lXC531PODIOg4CHzcOnr39yz+Hocx09+Lief7TXeQRCR3rTW+70crOV5Xk5vrttaPZVnk83mWlpa4fPky09PTTE1NRbu6Jki7N5LmeaVSYXd3dyx3X03iaDQapFKpqJdobiBxki+GuD9T6wb2xVtcPMmaaTOZTMcZqrlcLrrGzBNPPBFdRdLkhCAIyOVyZLNZbty4wRe/+EW++tWvYlkWTz31FO973/u4ePEi9XqdWq1GKpXCcRzCMIwubzA9Pc329nY0r+d5FAoFbNumUqlEd4yyLAvLsjo2DIcxf7csKxqbb8b2H7bhM+/neR6NRmPfxij+3vV6nVKpRL1eP/7/59hzDIDWOloh5oOGYYjneWc6ucf/2Y7jMD8/z0MPPcSlS5dIp9Pk87RSdOEAAAjKSURBVHlmZmaiHg3cDTaT0EyPZ2NjIwqm7vcedWEY4rou5XI56sGb5H6U3pE4GdMbjsfbYXFlEpr530xMTJDL5dja2iKTyZDP56Npl5eXWV5ePnS573rXu9jc3OTmzZtYlsV73vMe3v/+9x+53Xt7e6yurtJsNjl37hypVIpisRglUfO5jpvcfd+nUqlEJ1+Z72R82vi6aDab1Ov1jg7tQdPHN4Jm/qN8dxOR3OHu3V3iQTLOZYTjsm2bQqHAuXPnmJ6eBloJf3p6+sB1ZNaj4zjRRnJ1dTX6+zgld7Pn12g0sG07SiDmyyXJfXC6e5pHmQ7ultHg7siXZrNJOp2ObrKdy+Wi6YMgiC4tXCqVoh6y4zhUq1X29vai70V8WrOseOenUqnQbDZpNpu4rhsdkDW/M8n6qJ8/XvLxPG/fSJxu5r3jZcT47+Px2ksOTERyN19O6EzuUpa5y/QiPM+jWq1GNzxIpVKHbvXNejuL6/E4Q0TF6YmXaOKXJpiYmGBychLoLPcY8WSdSqWi0olJrKlU6sBpobMHbaY388efd7+n2eu7V6I3fzfxZp7H2xE/jmjaEG+PaaNZN/3qlCQiucPBIxyOc2LCuAuCgFKpxM2bN5mYmIi29t2BbMSHTfq+z9bWVseFmcYt6cW/XPHdaYmfwTooUR11vnjsHmfeTCYT3ZTbJPbjXK7AzGtZFo7jRO9jSkwmycP+0spBnyO+MYjP293BiCfy7p/xeeKloPjG4rgSkdyVUtFoD1N/MlvvXj7cqIsnYN/32d7exnXd6MDT/UaCmCAxB2biF2Ia9eQeb785kLW7u9txnCa++yv6zxwXO84ekolZ13U7Rs+88sor/Mmf/AmLi4tsb29Ho2RM58T3/eig6+rqKl/5yld4++23sSyLF198kUajwfLycnRDbpO0TRtTqRSTk5OUSiVeeuklXn/9dTzPY3NzE8uyqNVq0R5xvCxz1N6zKQe6rhvtVR+2Rx0fMGKuwXPQSVdmPXXflvCo6zoRyd1c27k7uVer1eho8lmntaZarVKr1U50uvM4Dwn0PI/t7W0cxyGTyUTJ3KyncRwhlATxevFxVavVjtef//zn+bu/+7uOYyYH9XxNudbUyJVSfOMb3+Azn/lMx0FQM3085i3LikbPNJvNjg5Ar2c1HzQi6ChDIe+3vJE/Q7Ver/NP//RPHUP5zOnGq6urHV/OcU1QRzHOCfq44uuh2WyytbVFpVKJvuBxktyTJ142DMOQWq124kv8NhoNyuVyP5s3FtT9koVS6g+ADwKbWuvvav9uDvgkcAV4G/iw1rqoWpuq54EPADXg32mtv3a/RjiOowuFQvdyo6PYrutK713c12E9pfZGcd8fTyO2lVKyNRYDdVBsw9GS+w8CFeCPYl+A/wnsaK1/Qyn1UWBWa/1rSqkPAL9A6wvwfcDzWuvvu1/j5AtwdL0cfzjLvf5DkrvEdkKYg6LdZ5V2M3v3pg5vDmaa43P3inHz3vGLjnWXOPvxHenn9+yIpZt79mru+aDVi/l67PXrwPn28/PA6+3n/wf4qYOmu8/7a3nIY5APiW15jOvjsNg76Q2yl7TWa+3n68BS+/lF4FZsutvt391X91jT+JhTIe4nPnS2+3FMfY9tIYah5wOqWmt9kl1PpdRzwHPmtdTURS8GUXLqV2wLMQwn7blvKKXOA7R/mlusvAOsxKa71P7dPlrrq1rrJ7XWT56wDUIMgsS2GAsnTe5/CTzbfv4s8NnY7/+tankK2I3t4goxCiS2xXg4wgGhPwXWAI9WnfEjwDzwBeAN4P8Cc+1pFfC/gTeBfwaePOIB26EflJDHeD8ktuUxro/DYu++QyFPgwwXE4N26HCxAZPYFoN2WGyftCwjhBAiwSS5CyHEGJLkLoQQY0iSuxBCjKFEXBUSuANU2z+TZgFp13EksV0PDHHZEtvHJ+06ukNjOxGjZQCUUi8n8aQPadfxJLVdw5TUdSLtOp6ktuswUpYRQogxJMldCCHGUJKS+9VhN+AQ0q7jSWq7himp60TadTxJbdeBElNzF0II0T9J6rkLIYTok0Qkd6XUjyqlXldKXWvf2mxY7VhRSn1JKfVNpdQ3lFK/2P79nFLq80qpN9o/Z4fQNlsp9Q9Kqb9qv35QKfVSe519UimVPu02tdtRUEp9Win1LaXUa0qp9yZhfSWBxPWR25e42B6HuB56cldK2bSutvevgceBn1JKPT6k5vjAr2itHweeAn6+3ZaPAl/QWj9M64qBw/ii/iLwWuz1bwK/rbX+DqBI64qGw/A88Dmt9aPAe2i1MQnra6gkro8libE9+nF9lMuWDvIBvBf4m9jrjwEfG3a72m35LPAjHHJfzVNsxyVawfQ+4K9oXX72DuActA5PsV0zwFu0j93Efj/U9ZWEh8T1kduSuNgel7gees+dhN6bUil1BXgCeInD76t5Wn4H+FXA3ItwHihprf3262GtsweBLeAP27vVv6+UyjP89ZUEEtdHk8TYHou4TkJyTxyl1CTwGeCXtNZ78b/p1mb71IYYKaU+CGxqrV85rWUegwN8N/C7WusnaJ1m37GretrrSxwuSXHdbk9SY3ss4joJyf3I96Y8DUqpFK0vwB9rrf+8/evD7qt5Gp4Gfkwp9TbwAq3d1+eBglLKXBtoWOvsNnBba/1S+/WnaX0phrm+kkLi+v6SGttjEddJSO5/DzzcPkKeBn6S1v0qT51SSgEfB17TWv9W7E+H3Vdz4LTWH9NaX9JaX6G1br6otf4Z4EvATwyjTbG2rQO3lFKPtH/1DPBNhri+EkTi+j6SGttjE9fDLvq3D058APg2rftT/tchtuNf0drVehX4x/bjAxxyX80htO+HgL9qP/8XwFeBa8CngMyQ2vQvgZfb6+wvgNmkrK9hPySuj9XGRMX2OMS1nKEqhBBjKAllGSGEEH0myV0IIcaQJHchhBhDktyFEGIMSXIXQogxJMldCCHGkCR3IYQYQ5LchRBiDP1/CrGtBBSMb50AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0cfe48>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3827,23 +2775,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.785 \n",
-      "FIRE        0.801 \n",
-      "RIGHT       0.793 \n",
-      "LEFT        0.808 (Action Taken)\n",
-      "RIGHTFIRE   0.766 \n",
-      "LEFTFIRE    0.802 \n",
+      "NOOP        0.654 \n",
+      "FIRE        0.674 \n",
+      "RIGHT       0.663 (Action Taken)\n",
+      "LEFT        0.615 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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0ZGPhBw8etPU3rZW+vj4rlidOnKBWq5HNZm3mTr1eZ2ZmhnvuuYeJiQmSySSL\ni4s2/bNarTaJ/ErnWa1Wbf7+0tKSjfe7rsvMzAynTp3igw8+AJbj7iZP3ghva8dytOxyuczCwgJB\nEDSlV25E6KPj5pg+FlNvc5yVrrcg7GZiJ/StN6oR5GQy2dTxaToFo+mDJmywGtFtTWjBdDAagVpN\n6E3Yx7zUBFAul4HbIY+NnKPpSI7G7433mUwmSaVSti6+75NIJBgYGLAvR5lzKZVKTXHuaBZOtNPT\n1NuEv6J1MaGpaGvJxNfNOZv9oi2TpaWldZ+zOT/zvzMvem1U6E2rKfrCmumTgGa7EQRhmdgJfZRo\nZo3J1tBa2+VUKmW9eLgtlKt1wLmua0MwjuPYzJio2N7NozdvqZrsFROqMJ2Oq9EqPObhlUgk7H6u\n61rBjcbrTUvBhG7MNTG/R48dzW4xD7Go0EdFcbXrba6tSek0WS3mnFe6nuvBnHM7Qh99IJmO9LWG\nspaBzgQhhkLfOqStyWKZm5uzbz46jkMymWRubs5muxjv3IQpVuqMNfFuk6VSqVS4ceMGYRhSqVRs\nGa1E3wJNp9PU63UbEjG/m/1Mh26rAEa/B0HAwsIC09PTNr4Ot4XedBibfYwXn0qlyOfzLC0t2WyZ\nVpFzHId8Ps/09LTtsDbZOb7v29BJtF7RztxCocDMzAylUslmNBUKBVzX5datW00dneZ6miyctUTf\nXLOZmRkKhcIdb/Sul6h9mL4Pk8Nvzj96vSVGLwgxE/poCMEI5+zsLCdPnuTq1av09/dbL9J1XfvW\npREuI/CreXHRNEzf95mZmeHkyZP09fXZDJHVhMEIoskSmZqaYnFx0f4Wjc+vRPS3crnMhQsX7Nu+\nJgwTfThFQxDRsfnL5TIzMzM2hNKaWmoyfkqlks26MQ/GMAyZmpqyLzGZ/aPfp6amOHHihB3WIAxD\n+4Cdm5tryrgxx15L3A21Wo2rV69ar/5u13s1zLFMi6ZYLHLgwAEOHjwI3M7dN3YksXpBiJnQw52d\naDdu3OBnP/sZFy5cYHh4mGQyaTtbTZpedN+1buyo8JiOy2KxaL3K9YiCidWXSqWmGPXdQgTR3yuV\nChcvXuTGjRsrPpiiHcnmvMzDz5yzEWjT12AoFot8+OGHzMzM2JZItI+hVCo1CX3UQw/D0GY4tYa5\nlFJUKpWm672RczYPkVwu19bAY+ZapNNpKpUKCwsL3Lx5k09+8pN3bCcIwjKxFnozHIBJVSyVSvYG\n7wSmzO2v+qbIAAARTUlEQVTGhG5M/nwnCcNwQ2VHr7cJr0TFvFN0uuyoHUxPT9/RGS5CLwi32REB\nzNb4tiCslsYpCMKdxF7oPc+zr9WbZUGI2oEZSC6KpFcKwm1ip5qtN2i0Y9bEilfqtNzssTYrCJt5\nbX+7jr1W2Vu5791o55wNJqspmv/f+m6AIAjNxE7oW4XEjDJpvm8kb3s9x+pWs38rj91O2XGtV2s5\nUTtYawYyQRB2QOhGEARBaI/YC30nmvtCbyP2IQhrE3uhFwRBENpDhF4QBKHHEaEXBEHocUToBUEQ\nehwRekEQhB5HhF4QBKHHEaEXBEHocUToBUEQehwRekEQhB5HhF4QBKHHEaEXBEHocUToBUEQehwR\nekEQhB5HhF4QBKHHEaEXBEHocdoSeqXUsFLq+0qps0qpM0qpx5VSo0qpV5VS5xp/RzpVWUHYLsS2\nhV6iXY/+BeBHWuuPAh8HzgBfB36itT4M/KSxLAg7DbFtoWfYtNArpYaATwPfAtBa+1rrHPDrwLcb\nm30b+I12KykI24nY9vahlMJxHJklbItpx6M/BMwB/14p9bZS6ptKqT7gHq31TGOb68A9K+2slHpe\nKXVcKXV8fn6+jWoIQsfpmG1vU313LK0TvQtbQztC7wFHgT/RWv8yUKSlKauX/3sr/ge11i9qrR/T\nWj82Pj7eRjUEoeN0zLa3vKaCsA7aEfopYEpr/WZj+fss3xw3lFJ7ARp/Z9uroiBsO2LbW0g0TOM4\nDslkEs/zulij3mfTQq+1vg5cVUo91Fj1GeA08DLw1ca6rwIvtVVDQdhmxLa3DhOTNwwMDLB3715G\nRkbu2E7oHO0+Rv974DtKqSRwAfhvWX54/Eel1NeAy8A/avMYgtANxLY7jFIKpRRhGNp1/f39TExM\nsLCwwNzcXNO2ErfvHG0Jvdb6JLBSHPIz7ZQrCN1GbLuzGJFfDRH1rUUCY4IgbCnGO9dao5RiYGAA\n3/epVqvk83lc16VcLjftI8LfWUToBUHYUhzHseGa/v5+Dh06RKVS4eLFiywtLVGpVHBdt2kfEfrO\nImPdCIKwJbiui+u61Ot1ALLZLIcOHWLfvn0MDg7aTtkgCKhWq92sas8jHr0gCFuC4zjUajUABgcH\nefjhh5mcnKRSqVAoFJo6ZR3HsQ8EofOI0AuC0BEcx8HzPJtZY0QeYGhoiIMHD5JMJvnwww+5cuUK\nQRDctZNW6Awi9IIgdAStNUEQ2OVoimS9XqdSqZDL5bh8+bLtfPU8r+mBIGwNIvSCIHQEk1ljeOCB\nB1BKceXKFebm5njvvfeo1+vkcjm7jYRrtgcRekEQOoLnedajHxkZ4ROf+ATJZJJqtcrU1BTnz58n\nlUo17RON0wtbhwi9IAhtYzpbR0ZGKJfL7NmzhyNHjrCwsEAymbTb+b5vO14lhXL7EKEXBGFTpFIp\nmxZZq9X4yEc+wjPPPIPjONy6dYt8Ps+lS5dYXFy0+7iuSxiGIvLbjAi9IAiboq+vD8dxKJfLlMtl\nSqUSQ0NDZDIZrl27xrFjxzh16hS3bt0CsDn1IvLbjwi9IAibIp/P2xj7yMgIqVSKYrGI67rk83nO\nnDnDzMzyPC3JZJIgCKTztUuI0AuCsCGSySS+71uR/4Vf+AU+//nPMzk5ieM4OI7D4ODgHePOS758\n9xCh3wKMQUsTVeg1HMdpGpdmcnKS3/md3+Gzn/0sp0+f5tSpU2QyGQqFAplMxm4ncfnuIkLfYVzX\ntVkFkjom9BL9/f0opSgUCgA8/fTT/O7v/i5f/OIXmZ2d5e///u956aWX7LYmNg/L49mI0HcPEfoO\nE4ahCLzQkwRBQKVSscu//du/zXPPPQfAH/3RH/Hd736Xa9eurbiviHx3EaEXBGFNzFAG0REmlVI8\n8MADALzxxhu88MIL3Lhxo1tVFO6CCH2btE55Nj4+ztDQEMVikbm5Oevdy9Rowk6jta/pwIED9PX1\n8d5776G15tVXX8V1Xb75zW9akR8aGsJxHBYWFrpWb+FOROjbxIypHYYhjuPwS7/0Sxw9epQPPviA\nv/iLv6BUKqGUwnXdpgGfBCHupFIp6vU6vu8D8LnPfY4vfelLvPLKK7zwwgv8/u//Pj/84Q9tCiVA\npVKxE4BLKmV8kIlH2iSaNqaU4vDhwzzzzDM88sgjJBIJu13rDDqCEHcSiUSTDT/++OP86q/+Kl/+\n8peB5Zj98ePHuXnzJqlUCtd1qVarVCoVEfmYIULfYer1OrVaTTpkhZ4gGm40LdLW2aDMUMMi7vFF\nQjdtEn2lW2vN2bNnSSQSfPjhh7bJCzJKn7Dz8H2/Sehfe+01BgcHef311+26gYEBQIYbjjsi9G0S\nFfB6vc7Pf/5zPvzwQ8rlsvV8tNYi9MKOI+qoAPzwhz/kjTfeoFgs2nXlclmSDHYAIvQdJpfLNU2s\nYJCbQdhpGJt1XRetNfl8nnw+b39XSkmCwQ5BhF4QhDVZrTUqzsvOQYS+w8gQCEKvkkwm7SiU0Tdk\nhfgjQt9hZAgEoVfxfV8m8t6hiNALgrBuJFyzM5E8ekEQhB6nLaFXSv2PSqn3lFLvKqW+q5RKK6UO\nKaXeVEqdV0r9qVIqefeSBCFeiG0LvcSmhV4ptQ/4H4DHtNaPAC7wZeAPgD/UWn8EWAC+1omKCsJ2\nIbYt9Brthm48IKOU8oAsMAM8C3y/8fu3gd9o8xiC0A3EtoWeYdNCr7WeBv5P4ArLN0EeOAHktNbm\nLYopYN9K+yulnldKHVdKHZ+fn99sNQSh43TStrejvoJwN9oJ3YwAvw4cAu4D+oBfW+/+WusXtdaP\naa0fGx8f32w1BKHjdNK2t6iKgrAh2gnd/CpwUWs9p7WuAX8GPAkMN5q7AJPAdJt1FITtRmxb6Cna\nEforwCeVUlm1PCD7Z4DTwF8Bv9XY5qvAS+1VURC2HbFtoadoJ0b/JssdUz8D3mmU9SLwr4B/rpQ6\nD4wB3+pAPQVh2xDbFnqNtt6M1Vr/a+Bft6y+AHyinXIFoduIbQu9hLwZKwiC0OOI0AuCIPQ4IvSC\nIAg9jgi9IAhCjyNCLwiC0OOI0AuCIPQ4IvSCIAg9jgi9IAhCjyNCLwiC0OOI0AuCIPQ4IvSCIAg9\njgi9IAhCjyNCLwiC0OOI0AuCIPQ4sRJ6pRTL8zwIwtpore33er2+4jZiS4KwTKyEXmvddAObdYLQ\niuPcNl3XdVFKWVsxdqS1XvUhIAi7idgI/Uo3pIi8YFBK4TiO/Ws+gF0ftZeVnAZB2K20NcNUJzE3\na7S5LaEcwRAVbq01QRBY58D3fer1uhV+pRSu61pPXxC2k1anIw7EwqM3gm4+0RtWblRhJaItwEql\nQhiGeN6y3+J5Ho7jiNgLQoNYePRaa8IwBJZvYHMTR78LuxvXda2QK6XIZDKUy2UqlQp9fX24rksQ\nBAAEQUAYhtRqNQnhCNtOq73FwcOPjdDXajWCIMD3fcIwJJvNUq1W7c0r7C6MF25ukPHxcSYnJ8lk\nMtTrdTzPw/d9lpaW2L9/P0NDQywuLqK1plAo2G2iToQgbDdxaU3GQujDMKRYLOI4Dr7v43keqVSK\nUqlkvTJhd+E4TpM3fvDgQZ5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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c27b748>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3852,23 +2800,23 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.812 \n",
-      "FIRE        0.824 \n",
-      "RIGHT       0.810 \n",
-      "LEFT        0.829 (Action Taken)\n",
-      "RIGHTFIRE   0.807 \n",
-      "LEFTFIRE    0.818 \n",
+      "NOOP        0.655 (Action Taken)\n",
+      "FIRE        0.646 \n",
+      "RIGHT       0.719 \n",
+      "LEFT        0.648 \n",
       "\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Zs4exsTGSySQLCws2/dP3/SaRX+o6fd+3+fvFYtHG+13XJZ/P8/rrr/OLX/wC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\nAQBBEBCGIfV6XUI4QlfRWls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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c0b8588>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -3877,12 +2825,10 @@
      "text": [
       "Action:     Q-Value:\n",
       "====================\n",
-      "NOOP        0.861 (Action Taken)\n",
-      "FIRE        0.854 \n",
-      "RIGHT       0.851 \n",
-      "LEFT        0.846 \n",
-      "RIGHTFIRE   0.853 \n",
-      "LEFTFIRE    0.845 \n",
+      "NOOP        0.686 (Action Taken)\n",
+      "FIRE        0.660 \n",
+      "RIGHT       0.675 \n",
+      "LEFT        0.675 \n",
       "\n"
      ]
     }
@@ -3906,9 +2852,7 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_layer_output(model, layer_name, state_index, inverse_cmap=False):\n",
@@ -3987,12 +2931,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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UHNbVaMeo0U5sez3CI5bDI2NbHWYJlyYGIjkDmdAbNIZuFhcXuXDhAsePH+fS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\nC4Ig9Dgi9IIgCD2OCL0gCEKP8/8B8s+udmS2ndkAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c17c470>"
+       "<Figure size 432x288 with 2 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -4028,9 +2974,9 @@
     },
     {
      "data": {
-      "image/png": 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QumuvvTZJcuuttxauhOVqJ93oViKyatUzeUQP0pCWSUYAgKI6SkZWr17drTqG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\nytC74IILkhw/t+mhhx5KMtq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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c148c50>"
+       "<Figure size 720x720 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -4066,9 +3012,9 @@
     },
     {
      "data": {
-      "image/png": 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sv0Xt3btXRMamvypQ1+0f1le+8hWN3/3ud0/6fElNUcVdh2oZN6rsxLX/hje8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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884c14d9b0>"
+       "<Figure size 720x720 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -4110,9 +3056,9 @@
     },
     {
      "data": {
-      "image/png": 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B4pQPpYqw+SJV6jMf+MAHAM+P8ZFHHhm0bUlTTokxqimpEqTE+FTfyNdLC9bX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heN7Av+PTTwVhqXXHKJ+5qtRqIoS/2BfJFPV1xxRRLNESnBUtIfffTRAHz84x/vcUxfiramHcsZ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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f884575b320>"
+       "<Figure size 720x720 with 64 Axes>"
       ]
      },
      "metadata": {},
@@ -4232,15 +3178,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Min:  -0.68262, Max:   0.14787\n",
-      "Mean: -0.05167, Stdev: 0.11923\n"
+      "Min:  -0.24494, Max:   0.13658\n",
+      "Mean: -0.01729, Stdev: 0.06023\n"
      ]
     },
     {
      "data": {
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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8802991e80>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -4269,15 +3215,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Min:  -0.95588, Max:   0.09746\n",
-      "Mean: -0.03578, Stdev: 0.15025\n"
+      "Min:  -0.56904, Max:   0.06957\n",
+      "Mean: -0.05132, Stdev: 0.12694\n"
      ]
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUoAAADuCAYAAABf005JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACX1JREFUeJzt3UFvVNcZgOHvjo1xLQtN7UGlYOOrKMqy6oIgIUXJLqso\n+yz7S/I/8iOyKRJVFqiLSKjISKGLVqpQZROEaBlIRFwzgfHcLrKqUvTNnMONh+R51vP5HA6X1zOS\nfWi6rgsAXm1w2hsAWHZCCZAQSoCEUAIkhBIgIZQACaEESAglQEIoARKri7x4NBp1e3ttT1vJNbOT\n4tmD+/dj/ORJ8xq381qNtra6dmen/AusrFSt3w3K5w8PD2I8Hi/v2W5vd+3ubvkXmM3qNjCoez9y\n5+7dcdd15+s20Z+trVG3s9MWz6+tVp5vU/7oHRwezvXsLhTKvb02bt3aL95UrbXJs+LZKx988Bp3\n8vq1Ozuxf/16+RcYDqvWf7F+rnj22rUrVWv3rd3djf0vvij/ApNJ3QY2N6vGm+3tw7oN9Gtnp43r\n18u7cHl0XLeB1YUy9j+uXLs21+t89AZICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigB\nEkIJkBBKgMRC124005exNn5Yvtr6evlsRMyGW+XDldeQ9W22uhbHo8vF85VHG2tH5Tcz1Vx/95Op\nuGGm9mamh0flNzO9CdbWImpuCIxpxd9NRMR0Wj7bdXO9zDtKgIRQAiSEEiAhlAAJoQRICCVAQigB\nEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEgtdBDdbORPHw4vFiz16VDwaERH39stnn5Vft/iT\nmM0iJpPTW391vfzOxG6w3Hd9xmwWcXRUPl952edw+PO+jzJevozBo4p7amvuk4yIGI3q5ufgHSVA\nQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlACJpuu6+V/cNI8j\n4rC/7fRqr+u686e9iVdxtv15w882wvn2aa6zXSiUAL9EPnoDJIQSICGUAAmhBEgIJUBCKAESQgmQ\nEEqAxOoiLx79+tdde+lSxWoLLfdjg/KuH9y/H+PxuKnbQH/W10fd5mZbPH/2bN36Dx8eVEwfRddN\nlvZsR6NR17btaW+j2J07d8bL/Js5w+Gou3ChLZ7fXJ1Urf9isF48++DBQTx9mndhoXK1ly7F/uef\nF28qhsPy2YiIzc3i0SvvvVe3ds82N9v4+OP94vnaDnz66R8qpv9Yt3jP2raN/du3T239WeUHt5WV\nZql/PfDChTY++6z82X3/wj+q1r+//k7x7EcfXZnrdT56AySEEiAhlAAJoQRICCVAQigBEkIJkBBK\ngIRQAiSEEiAhlAAJoQRICCVAYrF7z86erbum5uiofDYiYjotn13y/7+86+r+eLdu1e5gXDFbsfGf\nwMlJxLOj8vcE51aPq9YfTOquEVt2m786ifd//6ziK1yoW7/i8Zv35kbvKAESQgmQEEqAhFACJIQS\nICGUAAmhBEgIJUBCKAESQgmQEEqAhFACJIQSICGUAAmhBEgsdB/lrGvieLpWvNj6cKt4NqLyOsrB\nStXafXv+POKrr8rna6/6jPhtxeyZ2sV7tbIScW5zVjx/PNmoWv9Pf66b/7n7y9/PVc2/+2757Oqc\nBfSOEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgETTdd38\nL26axxFx2N92erXXdd35097Eqzjb/rzhZxvhfPs019kuFEqAXyIfvQESQgmQEEqAhFACJIQSICGU\nAAmhBEjM+d9//2B7e9Tt7rbliy202v8xnRaPHnz9dYyfPGkqd9Cb0WjUXb7cFs8PYla1/vPvy79n\nPnx4EN98M17qs93ba09t/abyZO7cuTNe5h84r312T07q1j9zpnz24OAgxuP82V0oXbu7bdy8uV+8\nqeGweDQiIgbjfxfPXvnww7rFe3b5chtffll+thtxXLX+X+9tFM9+8smVqrX7trfXxq1b5Wdbq/YN\nwspKs9S/9VL77H73Xd365yu+hVy9Ot+z66M3QEIoARJCCZAQSoCEUAIkhBIgIZQACaEESAglQEIo\nARJCCZAQSoCEUAIkhBIgsdAFUKurEVvD8nsP//W4rsu/WdobD+sNXn4fG4/+WTz/t8lbVes/f14+\nO6u7CnPpPXhQN/9W+/M+oMEgYn29fH7j24dV6x9PLhbPzvvsekcJkBBKgIRQAiSEEiAhlAAJoQRI\nCCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAYqH7KGeziONJeVtPTopHfzCdlM8u+aWJk+5s\n1Z2SNfcBRkS8/Xb57MZG3dp9a06msXb0tHj+raO6CymPJ7+rml92k0nEvXvl8+9MxlXrj6fl91FO\np/O9zjtKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEk3X\ndfO/uGkeR8Rhf9vp1V7XdedPexOv4mz784afbYTz7dNcZ7tQKAF+iXz0BkgIJUBCKAESQgmQEEqA\nhFACJIQSILG6yItHW1tdu7tbvNjJ4EzxbETEykr57MHBQYzH46ZqAz3a2hp1u7tt8fyZlVnV+l1T\n/j3z8HC5z3Z7u+5sVxf6V/Jj02nd/N27d8bL/APno9Goa9u2eL72R7mbiidv3i4s9Ai0u7uxf+NG\n8aaebV4sno2I2Nwsn7169UrV2n3b3W3jxo394vmLw+Oq9V+sbhTPXru2/Gd782b52Q6Hdet/+23d\n/PZ2s9S/9dK2bdy+XX6+td9Iar6RzdsFH70BEkIJkBBKgIRQAiSEEiAhlAAJoQRICCVAQigBEkIJ\nkBBKgIRQAiSEEiCx0L0bs5UzcTysuAGo8paQwaTihpxZ3TVkfWuaiPX18vmnk/Lbf2qdnJza0nNZ\nWam7eWowfVG1/ta08vqgJXdyEnF0VD5f89xHREwm5bPzZsE7SoCEUAIkhBIgIZQACaEESAglQEIo\nARJCCZAQSoCEUAIkhBIgIZQACaEESAglQEIoARIL3Uc5GERsrJff6/jsqLLLNZfeLfl9lKvf/ye2\n7t0unn+4c7Vq/YvT+8Wzq7O6+xqX3rTyItXaCxeXXO19n6epaeZ7nXeUAAmhBEgIJUBCKAESQgmQ\nEEqAhFACJIQSICGUAAmhBEgIJUBCKAESQgmQEEqAhFACJJqu6+Z/cdM8jojD/rbTq72u686f9iZe\nxdn25w0/2wjn26e5znahUAL8EvnoDZAQSoCEUAIkhBIgIZQACaEESAglQEIoARJCCZD4Lwga+Wql\nUchDAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8801f0cac8>"
+       "<Figure size 432x288 with 16 Axes>"
       ]
      },
      "metadata": {},
@@ -4308,15 +3254,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Min:  -0.30984, Max:   0.24492\n",
-      "Mean: -0.02332, Stdev: 0.09427\n"
+      "Min:  -0.24590, Max:   0.14826\n",
+      "Mean: -0.00605, Stdev: 0.06365\n"
      ]
     },
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f88029365f8>"
+       "<Figure size 432x288 with 36 Axes>"
       ]
      },
      "metadata": {},
@@ -4349,15 +3295,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Min:  -0.33228, Max:   0.24060\n",
-      "Mean: -0.02068, Stdev: 0.09566\n"
+      "Min:  -0.25325, Max:   0.17733\n",
+      "Mean: -0.03257, Stdev: 0.07194\n"
      ]
     },
     {
      "data": {
-      "image/png": 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+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f8802915a90>"
+       "<Figure size 432x288 with 64 Axes>"
       ]
      },
      "metadata": {},
@@ -4456,7 +3402,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/17_Estimator_API.ipynb b/17_Estimator_API.ipynb
index 47117c2..4d90650 100644
--- a/17_Estimator_API.ipynb
+++ b/17_Estimator_API.ipynb
@@ -11,6 +11,15 @@
     "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2 and it would take too much effort to update this tutorial to the new API.**"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1215,7 +1224,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/18_TFRecords_Dataset_API.ipynb b/18_TFRecords_Dataset_API.ipynb
index c3c6b91..99a8d54 100644
--- a/18_TFRecords_Dataset_API.ipynb
+++ b/18_TFRecords_Dataset_API.ipynb
@@ -2,10 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# TensorFlow Tutorial #18\n",
     "# TFRecords & Dataset API\n",
@@ -16,10 +13,16 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
+   "source": [
+    "## WARNING!\n",
+    "\n",
+    "**This tutorial does not work with TensorFlow v.2 and it would take too much effort to update this tutorial to the new API.**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Introduction\n",
     "\n",
@@ -32,10 +35,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Imports"
    ]
@@ -43,11 +43,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
@@ -70,10 +66,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This was developed using Python 3.6 (Anaconda) and TensorFlow version:"
    ]
@@ -81,11 +74,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -104,10 +93,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Load Data"
    ]
@@ -116,9 +102,7 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -127,10 +111,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The data dimensions have already been defined in the `knifey` module, so we just need to import the ones we need."
    ]
@@ -139,9 +120,7 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -150,10 +129,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Set the directory for storing the data-set on your computer."
    ]
@@ -162,9 +138,7 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -173,10 +147,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Knifey-Spoony data-set is about 22 MB and will be downloaded automatically if it is not located in the given path."
    ]
@@ -184,11 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -204,10 +171,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Now load the data-set. This scans the sub-directories for all `*.jpg` images and puts the filenames into two lists for the training-set and test-set. This does not actually load the images."
    ]
@@ -215,11 +179,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -236,10 +196,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the class-names."
    ]
@@ -247,11 +204,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -271,20 +224,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training and Test-Sets"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This function returns the file-paths for the images, the class-numbers as integers, and the class-numbers as One-Hot encoded arrays called labels.\n",
     "\n",
@@ -295,9 +242,7 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -306,10 +251,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Print the first image-path to see if it looks OK."
    ]
@@ -317,11 +259,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -340,10 +278,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Get the test-set."
    ]
@@ -352,9 +287,7 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -363,10 +296,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Print the first image-path to see if it looks OK."
    ]
@@ -374,11 +304,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -397,10 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Knifey-Spoony data-set has now been loaded and consists of 4700 images and associated labels (i.e. classifications of the images). The data-set is split into 2 mutually exclusive sub-sets, the training-set and the test-set."
    ]
@@ -408,11 +331,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -432,20 +351,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for plotting images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Function used to plot 9 images in a 3x3 grid, and writing the true and predicted classes below each image."
    ]
@@ -454,9 +367,7 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -514,20 +425,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Helper-function for loading images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This dataset does not load the actual images, instead it has a list of the images in the training-set and another list for the images in the test-set. This helper-function loads some image-files."
    ]
@@ -536,9 +441,7 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -552,10 +455,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Plot a few images to see if data is correct"
    ]
@@ -564,9 +464,6 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -594,20 +491,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Create TFRecords"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "TFRecords is the binary file-format used internally in TensorFlow which allows for high-performance reading and processing of datasets.\n",
     "\n",
@@ -616,10 +507,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "File-path for the TFRecords file holding the training-set."
    ]
@@ -628,9 +516,6 @@
    "cell_type": "code",
    "execution_count": 17,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -652,10 +537,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "File-path for the TFRecords file holding the test-set."
    ]
@@ -663,11 +545,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -687,10 +565,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Helper-function for printing the conversion progress."
    ]
@@ -699,9 +574,7 @@
    "cell_type": "code",
    "execution_count": 19,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -720,10 +593,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Helper-function for wrapping an integer so it can be saved to the TFRecords file."
    ]
@@ -732,9 +602,7 @@
    "cell_type": "code",
    "execution_count": 20,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -744,10 +612,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Helper-function for wrapping raw bytes so they can be saved to the TFRecords file."
    ]
@@ -756,9 +621,7 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -768,10 +631,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is the function for reading images from disk and writing them along with the class-labels to a TFRecords file. This loads and decodes the images to numpy-arrays and then stores the raw bytes in the TFRecords file. If the original image-files are compressed e.g. as jpeg-files, then the TFRecords file may be many times larger than the original image-files.\n",
     "\n",
@@ -782,9 +642,7 @@
    "cell_type": "code",
    "execution_count": 22,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -836,10 +694,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Note the 4 function calls required to write the data-dict to the TFRecords file. In the original code-example from the Google Developers, these 4 function calls were actually nested. The design-philosophy for TensorFlow generally seems to be: If one function call is good, then 4 function calls are 4 times as good, and if they are nested then it is exponential goodness!\n",
     "\n",
@@ -851,11 +706,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -874,10 +725,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Convert the test-set to a TFRecords-file:"
    ]
@@ -886,9 +734,6 @@
    "cell_type": "code",
    "execution_count": 24,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -909,20 +754,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Input Functions for the Estimator"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The TFRecords files contain the data in a serialized binary format which needs to be converted back to images and labels of the correct data-type. We use a helper-function for this parsing:"
    ]
@@ -931,9 +770,7 @@
    "cell_type": "code",
    "execution_count": 25,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -971,10 +808,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "Helper-function for creating an input-function that reads from TFRecords files for use with the Estimator API."
    ]
@@ -983,9 +817,7 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1039,10 +871,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is the input-function for the training-set for use with the Estimator API:"
    ]
@@ -1051,9 +880,7 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1063,10 +890,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "This is the input-function for the test-set for use with the Estimator API:"
    ]
@@ -1075,9 +899,7 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1087,20 +909,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Input Function for Predicting on New Images"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "An input-function is also needed for predicting the class of new data. As an example we just use a few images from the test-set.\n",
     "\n",
@@ -1111,9 +927,7 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1131,9 +945,7 @@
    "cell_type": "code",
    "execution_count": 30,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1145,10 +957,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The class-numbers are actually not used in the input-function as it is not needed for prediction. However, the true class-number is needed when we plot the images further below."
    ]
@@ -1157,9 +966,7 @@
    "cell_type": "code",
    "execution_count": 31,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1168,10 +975,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Pre-Made / Canned Estimator\n",
     "\n",
@@ -1181,11 +985,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "feature_image = tf.feature_column.numeric_column(\"image\",\n",
@@ -1194,10 +994,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "You can have several input features which would then be combined in a list:"
    ]
@@ -1206,9 +1003,7 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1217,10 +1012,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "In this example we want to use a 3-layer DNN with 512, 256 and 128 units respectively."
    ]
@@ -1229,9 +1021,7 @@
    "cell_type": "code",
    "execution_count": 34,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1240,10 +1030,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The `DNNClassifier` then constructs the neural network for us. We can also specify the activation function and various other parameters (see the docs). Here we just specify the number of classes and the directory where the checkpoints will be saved."
    ]
@@ -1251,11 +1038,7 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1276,10 +1059,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -1290,9 +1070,6 @@
    "cell_type": "code",
    "execution_count": 36,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1326,10 +1103,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -1340,9 +1114,6 @@
    "cell_type": "code",
    "execution_count": 37,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1364,11 +1135,7 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1391,11 +1158,7 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1411,10 +1174,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions\n",
     "\n",
@@ -1428,11 +1188,7 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "predictions = model.predict(input_fn=predict_input_fn)"
@@ -1441,11 +1197,7 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1463,9 +1215,6 @@
    "cell_type": "code",
    "execution_count": 42,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1488,11 +1237,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1513,20 +1258,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions for the Entire Test-Set"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "It appears that the model maybe classifies all images as 'spoony'. So let us see the predictions for the entire test-set. We can do this simply by using its input-function:"
    ]
@@ -1535,9 +1274,7 @@
    "cell_type": "code",
    "execution_count": 44,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -1548,9 +1285,6 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1570,11 +1304,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cls_pred = np.array(cls, dtype='int').squeeze()"
@@ -1582,10 +1312,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The test-set contains 530 images in total and they have all been predicted as class 2 (spoony). So this model does not work at all for classifying the Knifey-Spoony dataset."
    ]
@@ -1593,11 +1320,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1616,20 +1339,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "# New Estimator"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "If you cannot use one of the built-in Estimators, then you can create an arbitrary TensorFlow model yourself. To do this, you first need to create a function which defines the following:\n",
     "\n",
@@ -1647,11 +1364,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def model_fn(features, labels, mode, params):\n",
@@ -1753,10 +1466,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Create an Instance of the Estimator\n",
     "\n",
@@ -1766,11 +1476,7 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "params = {\"learning_rate\": 1e-4}"
@@ -1778,10 +1484,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "We can then create an instance of the new Estimator.\n",
     "\n",
@@ -1794,9 +1497,6 @@
    "cell_type": "code",
    "execution_count": 50,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1817,10 +1517,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Training\n",
     "\n",
@@ -1831,9 +1528,6 @@
    "cell_type": "code",
    "execution_count": 51,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": false
    },
    "outputs": [
@@ -1867,10 +1561,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Evaluation\n",
     "\n",
@@ -1881,9 +1572,6 @@
    "cell_type": "code",
    "execution_count": 52,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -1905,11 +1593,7 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1929,11 +1613,7 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -1949,10 +1629,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions\n",
     "\n",
@@ -1963,9 +1640,6 @@
    "cell_type": "code",
    "execution_count": 55,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [],
@@ -1976,11 +1650,7 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -2008,11 +1678,7 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2033,10 +1699,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "### Predictions for the Entire Test-Set\n",
     "\n",
@@ -2047,9 +1710,7 @@
    "cell_type": "code",
    "execution_count": 58,
    "metadata": {
-    "collapsed": true,
-    "deletable": true,
-    "editable": true
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -2060,9 +1721,6 @@
    "cell_type": "code",
    "execution_count": 59,
    "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true,
     "scrolled": true
    },
    "outputs": [
@@ -2115,10 +1773,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "The Convolutional Neural Network predicts different classes for the images, although most have just been classified as 0 (forky), so the accuracy is horrible."
    ]
@@ -2126,11 +1781,7 @@
   {
    "cell_type": "code",
    "execution_count": 60,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2150,11 +1801,7 @@
   {
    "cell_type": "code",
    "execution_count": 61,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2174,11 +1821,7 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "metadata": {
-    "collapsed": false,
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2197,10 +1840,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Conclusion\n",
     "\n",
@@ -2209,10 +1849,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## Exercises\n",
     "\n",
@@ -2232,10 +1869,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "deletable": true,
-    "editable": true
-   },
+   "metadata": {},
    "source": [
     "## License (MIT)\n",
     "\n",
@@ -2266,9 +1900,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/19_Hyper-Parameters.ipynb b/19_Hyper-Parameters.ipynb
index abcbcd5..d20ff3a 100644
--- a/19_Hyper-Parameters.ipynb
+++ b/19_Hyper-Parameters.ipynb
@@ -8,7 +8,7 @@
     "# Hyper-Parameter Optimization\n",
     "\n",
     "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
-    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
+    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsl1877BS8m3yt8t_wq2IWji)"
    ]
   },
   {
@@ -53,19 +53,8 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-test/lib/python3.6/importlib/_bootstrap.py:205: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
-      "  return f(*args, **kwds)\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -84,20 +73,17 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# from tf.keras.models import Sequential  # This does not work!\n",
-    "from tensorflow.python.keras import backend as K\n",
-    "from tensorflow.python.keras.models import Sequential\n",
-    "from tensorflow.python.keras.layers import InputLayer, Input\n",
-    "from tensorflow.python.keras.layers import Reshape, MaxPooling2D\n",
-    "from tensorflow.python.keras.layers import Conv2D, Dense, Flatten\n",
-    "from tensorflow.python.keras.callbacks import TensorBoard\n",
-    "from tensorflow.python.keras.optimizers import Adam\n",
-    "from tensorflow.python.keras.models import load_model"
+    "from tensorflow.keras import backend as K\n",
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import InputLayer, Input\n",
+    "from tensorflow.keras.layers import Reshape, MaxPooling2D\n",
+    "from tensorflow.keras.layers import Conv2D, Dense, Flatten\n",
+    "from tensorflow.keras.callbacks import TensorBoard\n",
+    "from tensorflow.keras.optimizers import Adam\n",
+    "from tensorflow.keras.models import load_model"
    ]
   },
   {
@@ -123,10 +109,19 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/sklearn/externals/joblib/__init__.py:15: FutureWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n",
+      "  warnings.warn(msg, category=FutureWarning)\n",
+      "/home/magnus/anaconda3/envs/tf2/lib/python3.6/site-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.metrics.scorer module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.metrics. Anything that cannot be imported from sklearn.metrics is now part of the private API.\n",
+      "  warnings.warn(message, FutureWarning)\n"
+     ]
+    }
+   ],
    "source": [
     "import skopt\n",
     "from skopt import gp_minimize, forest_minimize\n",
@@ -148,14 +143,13 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.4.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 4,
@@ -170,14 +164,12 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'2.0.8-tf'"
+       "'2.2.4-tf'"
       ]
      },
      "execution_count": 5,
@@ -193,7 +185,6 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -235,9 +226,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dim_learning_rate = Real(low=1e-6, high=1e-2, prior='log-uniform',\n",
@@ -254,9 +243,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dim_num_dense_layers = Integer(low=1, high=5, name='num_dense_layers')"
@@ -272,9 +259,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dim_num_dense_nodes = Integer(low=5, high=512, name='num_dense_nodes')"
@@ -290,9 +275,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dim_activation = Categorical(categories=['relu', 'sigmoid'],\n",
@@ -309,9 +292,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dimensions = [dim_learning_rate,\n",
@@ -332,9 +313,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "default_parameters = [1e-5, 1, 16, 'relu']"
@@ -352,9 +331,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def log_dir_name(learning_rate, num_dense_layers,\n",
@@ -383,45 +360,30 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given path."
+    "The MNIST data-set is about 12 MB and will be downloaded automatically if it is not located in the given dir."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting data/MNIST/train-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/train-labels-idx1-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-images-idx3-ubyte.gz\n",
-      "Extracting data/MNIST/t10k-labels-idx1-ubyte.gz\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "from tensorflow.examples.tutorials.mnist import input_data\n",
-    "data = input_data.read_data_sets('data/MNIST/', one_hot=True)"
+    "from mnist import MNIST\n",
+    "data = MNIST(data_dir=\"data/MNIST/\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The MNIST data-set has now been loaded and consists of 70,000 images and associated labels (i.e. classifications of the images). The data-set is split into 3 mutually exclusive sub-sets."
+    "The MNIST data-set has now been loaded and consists of 70.000 images and class-numbers for the images. The data-set is split into 3 mutually exclusive sub-sets. We will only use the training and test-sets in this tutorial."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -429,34 +391,49 @@
      "text": [
       "Size of:\n",
       "- Training-set:\t\t55000\n",
-      "- Test-set:\t\t10000\n",
-      "- Validation-set:\t5000\n"
+      "- Validation-set:\t5000\n",
+      "- Test-set:\t\t10000\n"
      ]
     }
    ],
    "source": [
     "print(\"Size of:\")\n",
-    "print(\"- Training-set:\\t\\t{}\".format(len(data.train.labels)))\n",
-    "print(\"- Test-set:\\t\\t{}\".format(len(data.test.labels)))\n",
-    "print(\"- Validation-set:\\t{}\".format(len(data.validation.labels)))"
+    "print(\"- Training-set:\\t\\t{}\".format(data.num_train))\n",
+    "print(\"- Validation-set:\\t{}\".format(data.num_val))\n",
+    "print(\"- Test-set:\\t\\t{}\".format(data.num_test))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The class-labels are One-Hot encoded, which means that each label is a vector with 10 elements, all of which are zero except for one element. The index of this one element is the class-number, that is, the digit shown in the associated image. We also need the class-numbers as integers for the test-set, so we calculate it now."
+    "Copy some of the data-dimensions for convenience."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "data.test.cls = np.argmax(data.test.labels, axis=1)"
+    "# The number of pixels in each dimension of an image.\n",
+    "img_size = data.img_size\n",
+    "\n",
+    "# The images are stored in one-dimensional arrays of this length.\n",
+    "img_size_flat = data.img_size_flat\n",
+    "\n",
+    "# Tuple with height and width of images used to reshape arrays.\n",
+    "img_shape = data.img_shape\n",
+    "\n",
+    "# Tuple with height, width and depth used to reshape arrays.\n",
+    "# This is used for reshaping in Keras.\n",
+    "img_shape_full = data.img_shape_full\n",
+    "\n",
+    "# Number of classes, one class for each of 10 digits.\n",
+    "num_classes = data.num_classes\n",
+    "\n",
+    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
+    "num_channels = data.num_channels"
    ]
   },
   {
@@ -469,55 +446,10 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "validation_data = (data.validation.images, data.validation.labels)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Data Dimensions"
-   ]
-  },
-  {
-   "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "The data dimensions are used in several places in the source-code below. They are defined once so we can use these variables instead of numbers throughout the source-code below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {
-    "collapsed": true
-   },
    "outputs": [],
    "source": [
-    "# We know that MNIST images are 28 pixels in each dimension.\n",
-    "img_size = 28\n",
-    "\n",
-    "# Images are stored in one-dimensional arrays of this length.\n",
-    "img_size_flat = img_size * img_size\n",
-    "\n",
-    "# Tuple with height and width of images used to reshape arrays.\n",
-    "# This is used for plotting the images.\n",
-    "img_shape = (img_size, img_size)\n",
-    "\n",
-    "# Tuple with height, width and depth used to reshape arrays.\n",
-    "# This is used for reshaping in Keras.\n",
-    "img_shape_full = (img_size, img_size, 1)\n",
-    "\n",
-    "# Number of colour channels for the images: 1 channel for gray-scale.\n",
-    "num_channels = 1\n",
-    "\n",
-    "# Number of classes, one class for each of 10 digits.\n",
-    "num_classes = 10"
+    "validation_data = (data.x_val, data.y_val)"
    ]
   },
   {
@@ -536,10 +468,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 18,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_images(images, cls_true, cls_pred=None):\n",
@@ -580,16 +510,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 19,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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mmFrFKfF6+eWXgaBLVJgfTrvvvvvGGlNllBmKiBBjZvjUU09l9Xy+m0VRURFQ+XAe31VH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\nszKJ3CabWSczKzK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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc289fca7f0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -598,10 +526,10 @@
    ],
    "source": [
     "# Get the first images from the test-set.\n",
-    "images = data.test.images[0:9]\n",
+    "images = data.x_test[0:9]\n",
     "\n",
     "# Get the true classes for those images.\n",
-    "cls_true = data.test.cls[0:9]\n",
+    "cls_true = data.y_test_cls[0:9]\n",
     "\n",
     "# Plot the images and labels using our helper-function above.\n",
     "plot_images(images=images, cls_true=cls_true)"
@@ -618,10 +546,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 20,
+   "metadata": {},
    "outputs": [],
    "source": [
     "def plot_example_errors(cls_pred):\n",
@@ -629,17 +555,17 @@
     "    # all images in the test-set.\n",
     "\n",
     "    # Boolean array whether the predicted class is incorrect.\n",
-    "    incorrect = (cls_pred != data.test.cls)\n",
+    "    incorrect = (cls_pred != data.y_test_cls)\n",
     "\n",
     "    # Get the images from the test-set that have been\n",
     "    # incorrectly classified.\n",
-    "    images = data.test.images[incorrect]\n",
+    "    images = data.x_test[incorrect]\n",
     "    \n",
     "    # Get the predicted classes for those images.\n",
     "    cls_pred = cls_pred[incorrect]\n",
     "\n",
     "    # Get the true classes for those images.\n",
-    "    cls_true = data.test.cls[incorrect]\n",
+    "    cls_true = data.y_test_cls[incorrect]\n",
     "    \n",
     "    # Plot the first 9 images.\n",
     "    plot_images(images=images[0:9],\n",
@@ -662,9 +588,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {
-    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
@@ -748,13 +673,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 22,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "path_best_model = '19_best_model.keras'"
+    "path_best_model = '19_best_model.h5'"
    ]
   },
   {
@@ -766,10 +689,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 23,
+   "metadata": {},
    "outputs": [],
    "source": [
     "best_accuracy = 0.0"
@@ -786,10 +707,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 24,
+   "metadata": {},
    "outputs": [],
    "source": [
     "@use_named_args(dimensions=dimensions)\n",
@@ -829,14 +748,13 @@
     "    callback_log = TensorBoard(\n",
     "        log_dir=log_dir,\n",
     "        histogram_freq=0,\n",
-    "        batch_size=32,\n",
     "        write_graph=True,\n",
     "        write_grads=False,\n",
     "        write_images=False)\n",
     "   \n",
     "    # Use Keras to train the model.\n",
-    "    history = model.fit(x=data.train.images,\n",
-    "                        y=data.train.labels,\n",
+    "    history = model.fit(x=data.x_train,\n",
+    "                        y=data.y_train,\n",
     "                        epochs=3,\n",
     "                        batch_size=128,\n",
     "                        validation_data=validation_data,\n",
@@ -844,7 +762,7 @@
     "\n",
     "    # Get the classification accuracy on the validation-set\n",
     "    # after the last training-epoch.\n",
-    "    accuracy = history.history['val_acc'][-1]\n",
+    "    accuracy = history.history['val_accuracy'][-1]\n",
     "\n",
     "    # Print the classification accuracy.\n",
     "    print()\n",
@@ -890,9 +808,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {
-    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -907,23 +824,23 @@
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.2525 - acc: 0.1995 - val_loss: 2.1754 - val_acc: 0.3578\n",
+      "55000/55000 [==============================] - 4s 64us/sample - loss: 2.2207 - accuracy: 0.2039 - val_loss: 2.0769 - val_accuracy: 0.3326\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.0279 - acc: 0.4612 - val_loss: 1.8432 - val_acc: 0.5558\n",
+      "55000/55000 [==============================] - 2s 39us/sample - loss: 1.8787 - accuracy: 0.4489 - val_loss: 1.5766 - val_accuracy: 0.6934\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 4s - loss: 1.6227 - acc: 0.5998 - val_loss: 1.3877 - val_acc: 0.6654\n",
+      "55000/55000 [==============================] - 2s 39us/sample - loss: 1.3661 - accuracy: 0.7220 - val_loss: 1.0646 - val_accuracy: 0.8080\n",
       "\n",
-      "Accuracy: 66.54%\n",
+      "Accuracy: 80.80%\n",
       "\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "-0.66539999999999999"
+       "-0.808"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -947,10 +864,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 26,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -963,603 +878,618 @@
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.2287 - acc: 0.1868 - val_loss: 2.1264 - val_acc: 0.3182\n",
+      "55000/55000 [==============================] - 3s 47us/sample - loss: 2.2126 - accuracy: 0.3096 - val_loss: 2.0888 - val_accuracy: 0.4494\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 1.9607 - acc: 0.4438 - val_loss: 1.7713 - val_acc: 0.5082\n",
+      "55000/55000 [==============================] - 2s 38us/sample - loss: 1.9393 - accuracy: 0.4852 - val_loss: 1.7300 - val_accuracy: 0.5342\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 5s - loss: 1.5763 - acc: 0.5579 - val_loss: 1.3832 - val_acc: 0.6166\n",
+      "55000/55000 [==============================] - 2s 38us/sample - loss: 1.5558 - accuracy: 0.5634 - val_loss: 1.2548 - val_accuracy: 0.7250\n",
       "\n",
-      "Accuracy: 61.66%\n",
+      "Accuracy: 72.50%\n",
       "\n",
-      "learning rate: 6.1e-04\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 474\n",
-      "activation: sigmoid\n",
+      "learning rate: 7.0e-04\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 365\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.3354 - acc: 0.5258 - val_loss: 0.3002 - val_acc: 0.9112\n",
+      "55000/55000 [==============================] - 3s 46us/sample - loss: 0.2217 - accuracy: 0.9350 - val_loss: 0.0633 - val_accuracy: 0.9828\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.2336 - acc: 0.9269 - val_loss: 0.1626 - val_acc: 0.9538\n",
+      "55000/55000 [==============================] - 2s 39us/sample - loss: 0.0576 - accuracy: 0.9822 - val_loss: 0.0507 - val_accuracy: 0.9870\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.1403 - acc: 0.9563 - val_loss: 0.1113 - val_acc: 0.9692\n",
+      "55000/55000 [==============================] - 2s 39us/sample - loss: 0.0397 - accuracy: 0.9878 - val_loss: 0.0396 - val_accuracy: 0.9892\n",
       "\n",
-      "Accuracy: 96.92%\n",
+      "Accuracy: 98.92%\n",
       "\n",
-      "learning rate: 6.1e-06\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 333\n",
+      "learning rate: 6.8e-03\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 466\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.1702 - acc: 0.5067 - val_loss: 1.9186 - val_acc: 0.6892\n",
+      "55000/55000 [==============================] - 3s 53us/sample - loss: 2.3098 - accuracy: 0.1117 - val_loss: 2.3022 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.4878 - acc: 0.7480 - val_loss: 1.0546 - val_acc: 0.7940\n",
+      "55000/55000 [==============================] - 2s 44us/sample - loss: 2.3015 - accuracy: 0.1123 - val_loss: 2.3016 - val_accuracy: 0.1060\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.8226 - acc: 0.8264 - val_loss: 0.6324 - val_acc: 0.8514\n",
+      "55000/55000 [==============================] - 3s 47us/sample - loss: 2.3017 - accuracy: 0.1123 - val_loss: 2.3019 - val_accuracy: 0.1060\n",
       "\n",
-      "Accuracy: 85.14%\n",
+      "Accuracy: 10.60%\n",
       "\n",
-      "learning rate: 1.7e-04\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 252\n",
+      "learning rate: 9.8e-04\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 122\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3075 - acc: 0.1058 - val_loss: 2.2968 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 54us/sample - loss: 2.3093 - accuracy: 0.1038 - val_loss: 2.3061 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 1.5272 - acc: 0.4944 - val_loss: 0.8210 - val_acc: 0.7386\n",
+      "55000/55000 [==============================] - 2s 42us/sample - loss: 2.3057 - accuracy: 0.1078 - val_loss: 2.3039 - val_accuracy: 0.1060\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.6595 - acc: 0.7967 - val_loss: 0.4940 - val_acc: 0.8544\n",
+      "55000/55000 [==============================] - 2s 41us/sample - loss: 2.3053 - accuracy: 0.1073 - val_loss: 2.3054 - val_accuracy: 0.0978\n",
       "\n",
-      "Accuracy: 85.44%\n",
+      "Accuracy: 9.78%\n",
       "\n",
-      "learning rate: 7.3e-03\n",
+      "learning rate: 3.7e-04\n",
       "num_dense_layers: 3\n",
-      "num_dense_nodes: 166\n",
-      "activation: relu\n",
+      "num_dense_nodes: 72\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1821 - acc: 0.9431 - val_loss: 0.0705 - val_acc: 0.9808\n",
+      "55000/55000 [==============================] - 3s 48us/sample - loss: 2.3049 - accuracy: 0.1066 - val_loss: 2.3042 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.0605 - acc: 0.9829 - val_loss: 0.0678 - val_acc: 0.9848\n",
+      "55000/55000 [==============================] - 2s 40us/sample - loss: 2.3008 - accuracy: 0.1220 - val_loss: 2.2349 - val_accuracy: 0.2808\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0549 - acc: 0.9855 - val_loss: 0.0736 - val_acc: 0.9846\n",
+      "55000/55000 [==============================] - 3s 55us/sample - loss: 1.1898 - accuracy: 0.7546 - val_loss: 0.5112 - val_accuracy: 0.9176\n",
       "\n",
-      "Accuracy: 98.46%\n",
+      "Accuracy: 91.76%\n",
       "\n",
-      "learning rate: 6.1e-05\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 209\n",
+      "learning rate: 6.7e-04\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 230\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.3187 - acc: 0.1073 - val_loss: 2.3030 - val_acc: 0.0924\n",
+      "55000/55000 [==============================] - 3s 57us/sample - loss: 1.9215 - accuracy: 0.2895 - val_loss: 0.5522 - val_accuracy: 0.8572\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.3016 - acc: 0.1121 - val_loss: 2.2993 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 5s 90us/sample - loss: 0.3142 - accuracy: 0.9098 - val_loss: 0.1402 - val_accuracy: 0.9612\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 5s - loss: 2.2858 - acc: 0.1573 - val_loss: 2.2243 - val_acc: 0.2898\n",
+      "55000/55000 [==============================] - 3s 54us/sample - loss: 0.1451 - accuracy: 0.9567 - val_loss: 0.0997 - val_accuracy: 0.9708\n",
       "\n",
-      "Accuracy: 28.98%\n",
+      "Accuracy: 97.08%\n",
       "\n",
-      "learning rate: 1.8e-04\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 453\n",
+      "learning rate: 9.7e-03\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 132\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.3601 - acc: 0.8920 - val_loss: 0.1234 - val_acc: 0.9640\n",
+      "55000/55000 [==============================] - 3s 53us/sample - loss: 0.2108 - accuracy: 0.9304 - val_loss: 0.0595 - val_accuracy: 0.9840\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.0850 - acc: 0.9741 - val_loss: 0.0576 - val_acc: 0.9830\n",
+      "55000/55000 [==============================] - 2s 45us/sample - loss: 0.0719 - accuracy: 0.9801 - val_loss: 0.0487 - val_accuracy: 0.9874\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0566 - acc: 0.9824 - val_loss: 0.0535 - val_acc: 0.9856\n",
+      "55000/55000 [==============================] - 3s 50us/sample - loss: 0.0673 - accuracy: 0.9824 - val_loss: 0.0474 - val_accuracy: 0.9870\n",
       "\n",
-      "Accuracy: 98.56%\n",
+      "Accuracy: 98.70%\n",
       "\n",
-      "learning rate: 5.5e-06\n",
+      "learning rate: 1.6e-04\n",
       "num_dense_layers: 4\n",
-      "num_dense_nodes: 186\n",
+      "num_dense_nodes: 112\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3129 - acc: 0.1039 - val_loss: 2.3025 - val_acc: 0.1100\n",
+      "55000/55000 [==============================] - 8s 149us/sample - loss: 2.3076 - accuracy: 0.1080 - val_loss: 2.3030 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 2.3016 - acc: 0.1106 - val_loss: 2.3010 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 6s 118us/sample - loss: 2.2995 - accuracy: 0.1135 - val_loss: 2.2653 - val_accuracy: 0.1128\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 2.3013 - acc: 0.1123 - val_loss: 2.3011 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 6s 115us/sample - loss: 1.7192 - accuracy: 0.4761 - val_loss: 1.1804 - val_accuracy: 0.6904\n",
       "\n",
-      "Accuracy: 11.26%\n",
+      "Accuracy: 69.04%\n",
       "\n",
-      "learning rate: 3.1e-05\n",
-      "num_dense_layers: 3\n",
-      "num_dense_nodes: 427\n",
-      "activation: sigmoid\n",
+      "learning rate: 7.7e-05\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 154\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3132 - acc: 0.1070 - val_loss: 2.3007 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 56us/sample - loss: 0.8023 - accuracy: 0.7727 - val_loss: 0.2123 - val_accuracy: 0.9404\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 2.3029 - acc: 0.1080 - val_loss: 2.3020 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 0.2085 - accuracy: 0.9384 - val_loss: 0.1236 - val_accuracy: 0.9644\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 2.3021 - acc: 0.1093 - val_loss: 2.3016 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 7s 125us/sample - loss: 0.1413 - accuracy: 0.9564 - val_loss: 0.0950 - val_accuracy: 0.9746\n",
       "\n",
-      "Accuracy: 11.26%\n",
+      "Accuracy: 97.46%\n",
       "\n",
-      "learning rate: 1.4e-04\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 29\n",
-      "activation: relu\n",
+      "learning rate: 2.9e-03\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 156\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.8474 - acc: 0.7524 - val_loss: 0.2954 - val_acc: 0.9190\n",
+      "55000/55000 [==============================] - 4s 75us/sample - loss: 2.3168 - accuracy: 0.1028 - val_loss: 2.3084 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.2392 - acc: 0.9315 - val_loss: 0.1741 - val_acc: 0.9512\n",
+      "55000/55000 [==============================] - 3s 51us/sample - loss: 2.3055 - accuracy: 0.1059 - val_loss: 2.3023 - val_accuracy: 0.1060\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.1643 - acc: 0.9517 - val_loss: 0.1346 - val_acc: 0.9612\n",
+      "55000/55000 [==============================] - 6s 101us/sample - loss: 2.3016 - accuracy: 0.1119 - val_loss: 2.3027 - val_accuracy: 0.1060\n",
       "\n",
-      "Accuracy: 96.12%\n",
+      "Accuracy: 10.60%\n",
       "\n",
-      "learning rate: 3.7e-04\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 338\n",
-      "activation: sigmoid\n",
+      "learning rate: 1.1e-05\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 496\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.1610 - acc: 0.1844 - val_loss: 1.0813 - val_acc: 0.6678\n",
+      "55000/55000 [==============================] - 10s 185us/sample - loss: 1.8064 - accuracy: 0.6548 - val_loss: 1.0878 - val_accuracy: 0.8440\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.5982 - acc: 0.8131 - val_loss: 0.3252 - val_acc: 0.9100\n",
+      "55000/55000 [==============================] - 7s 124us/sample - loss: 0.7844 - accuracy: 0.8393 - val_loss: 0.4786 - val_accuracy: 0.9046\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.2712 - acc: 0.9201 - val_loss: 0.1858 - val_acc: 0.9468\n",
+      "55000/55000 [==============================] - 7s 128us/sample - loss: 0.4776 - accuracy: 0.8791 - val_loss: 0.3288 - val_accuracy: 0.9226\n",
       "\n",
-      "Accuracy: 94.68%\n",
+      "Accuracy: 92.26%\n",
       "\n",
-      "learning rate: 1.7e-06\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 512\n",
+      "learning rate: 3.4e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 451\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.2568 - acc: 0.3895 - val_loss: 2.1984 - val_acc: 0.6048\n",
+      "55000/55000 [==============================] - 3s 62us/sample - loss: 0.1423 - accuracy: 0.9556 - val_loss: 0.0378 - val_accuracy: 0.9904\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 2.0854 - acc: 0.6719 - val_loss: 1.9276 - val_acc: 0.7052\n",
+      "55000/55000 [==============================] - 3s 52us/sample - loss: 0.0438 - accuracy: 0.9869 - val_loss: 0.0379 - val_accuracy: 0.9896\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 1.7106 - acc: 0.7158 - val_loss: 1.4589 - val_acc: 0.7290\n",
+      "55000/55000 [==============================] - 6s 106us/sample - loss: 0.0342 - accuracy: 0.9892 - val_loss: 0.0370 - val_accuracy: 0.9890\n",
       "\n",
-      "Accuracy: 72.90%\n",
+      "Accuracy: 98.90%\n",
       "\n",
-      "learning rate: 1.4e-03\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 62\n",
+      "learning rate: 1.2e-05\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 182\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.2396 - acc: 0.9249 - val_loss: 0.0643 - val_acc: 0.9822\n",
+      "55000/55000 [==============================] - 3s 59us/sample - loss: 1.9464 - accuracy: 0.4581 - val_loss: 1.0907 - val_accuracy: 0.8004\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.0587 - acc: 0.9819 - val_loss: 0.0536 - val_acc: 0.9838\n",
+      "55000/55000 [==============================] - 3s 48us/sample - loss: 0.6953 - accuracy: 0.8265 - val_loss: 0.3989 - val_accuracy: 0.8992\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.0427 - acc: 0.9867 - val_loss: 0.0480 - val_acc: 0.9842\n",
+      "55000/55000 [==============================] - 4s 78us/sample - loss: 0.4034 - accuracy: 0.8862 - val_loss: 0.2750 - val_accuracy: 0.9256\n",
       "\n",
-      "Accuracy: 98.42%\n",
+      "Accuracy: 92.56%\n",
       "\n",
-      "learning rate: 2.7e-03\n",
+      "learning rate: 2.8e-04\n",
       "num_dense_layers: 2\n",
-      "num_dense_nodes: 364\n",
+      "num_dense_nodes: 512\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.3014 - acc: 0.5223 - val_loss: 0.2531 - val_acc: 0.9232\n",
+      "55000/55000 [==============================] - 3s 56us/sample - loss: 1.8869 - accuracy: 0.3200 - val_loss: 0.5330 - val_accuracy: 0.8646\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1956 - acc: 0.9386 - val_loss: 0.1221 - val_acc: 0.9650\n",
-      "Epoch 3/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.1138 - acc: 0.9646 - val_loss: 0.0846 - val_acc: 0.9758\n",
+      "55000/55000 [==============================] - 3s 52us/sample - loss: 0.3947 - accuracy: 0.8847 - val_loss: 0.2235 - val_accuracy: 0.9346\n",
+      "Epoch 3/3\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "55000/55000 [==============================] - 4s 78us/sample - loss: 0.2316 - accuracy: 0.9292 - val_loss: 0.1444 - val_accuracy: 0.9592\n",
       "\n",
-      "Accuracy: 97.58%\n",
+      "Accuracy: 95.92%\n",
       "\n",
-      "learning rate: 5.6e-04\n",
-      "num_dense_layers: 5\n",
-      "num_dense_nodes: 13\n",
-      "activation: relu\n",
+      "learning rate: 3.4e-03\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 5\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.9357 - acc: 0.6775 - val_loss: 0.3024 - val_acc: 0.9184\n",
+      "55000/55000 [==============================] - 4s 64us/sample - loss: 2.3031 - accuracy: 0.1100 - val_loss: 2.3020 - val_accuracy: 0.1060\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.2416 - acc: 0.9338 - val_loss: 0.1749 - val_acc: 0.9520\n",
+      "55000/55000 [==============================] - 3s 46us/sample - loss: 2.3020 - accuracy: 0.1118 - val_loss: 2.3021 - val_accuracy: 0.1060\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.1685 - acc: 0.9525 - val_loss: 0.1541 - val_acc: 0.9570\n",
+      "55000/55000 [==============================] - 4s 70us/sample - loss: 2.3019 - accuracy: 0.1128 - val_loss: 2.3018 - val_accuracy: 0.1060\n",
       "\n",
-      "Accuracy: 95.70%\n",
+      "Accuracy: 10.60%\n",
       "\n",
       "learning rate: 1.0e-02\n",
-      "num_dense_layers: 5\n",
-      "num_dense_nodes: 352\n",
-      "activation: sigmoid\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 104\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3316 - acc: 0.1049 - val_loss: 2.3019 - val_acc: 0.1070\n",
+      "55000/55000 [==============================] - 3s 52us/sample - loss: 0.1708 - accuracy: 0.9451 - val_loss: 0.0552 - val_accuracy: 0.9836\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3024 - acc: 0.1090 - val_loss: 2.3017 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 46us/sample - loss: 0.0630 - accuracy: 0.9813 - val_loss: 0.0551 - val_accuracy: 0.9836\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 2.3020 - acc: 0.1104 - val_loss: 2.3014 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 46us/sample - loss: 0.0514 - accuracy: 0.9851 - val_loss: 0.0415 - val_accuracy: 0.9904\n",
       "\n",
-      "Accuracy: 11.26%\n",
+      "Accuracy: 99.04%\n",
       "\n",
-      "learning rate: 1.5e-03\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 5\n",
+      "learning rate: 5.5e-04\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 277\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 1.7072 - acc: 0.4784 - val_loss: 1.2153 - val_acc: 0.6980\n",
+      "55000/55000 [==============================] - 4s 78us/sample - loss: 2.0127 - accuracy: 0.2534 - val_loss: 0.6090 - val_accuracy: 0.8268\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.9949 - acc: 0.7914 - val_loss: 0.7749 - val_acc: 0.8564\n",
+      "55000/55000 [==============================] - 3s 50us/sample - loss: 0.3406 - accuracy: 0.9004 - val_loss: 0.1451 - val_accuracy: 0.9582\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.6663 - acc: 0.8663 - val_loss: 0.5469 - val_acc: 0.9014\n",
+      "55000/55000 [==============================] - 4s 80us/sample - loss: 0.1563 - accuracy: 0.9533 - val_loss: 0.0969 - val_accuracy: 0.9700\n",
       "\n",
-      "Accuracy: 90.14%\n",
+      "Accuracy: 97.00%\n",
       "\n",
-      "learning rate: 1.0e-03\n",
-      "num_dense_layers: 3\n",
-      "num_dense_nodes: 496\n",
+      "learning rate: 2.8e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 441\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1843 - acc: 0.9426 - val_loss: 0.0483 - val_acc: 0.9852\n",
+      "55000/55000 [==============================] - 3s 58us/sample - loss: 0.1397 - accuracy: 0.9561 - val_loss: 0.0428 - val_accuracy: 0.9864\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.0506 - acc: 0.9840 - val_loss: 0.0471 - val_acc: 0.9856\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 0.0471 - accuracy: 0.9853 - val_loss: 0.0401 - val_accuracy: 0.9892\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0347 - acc: 0.9889 - val_loss: 0.0451 - val_acc: 0.9856\n",
+      "55000/55000 [==============================] - 7s 120us/sample - loss: 0.0316 - accuracy: 0.9905 - val_loss: 0.0482 - val_accuracy: 0.9882\n",
       "\n",
-      "Accuracy: 98.56%\n",
+      "Accuracy: 98.82%\n",
       "\n",
-      "learning rate: 3.7e-03\n",
-      "num_dense_layers: 5\n",
-      "num_dense_nodes: 512\n",
+      "learning rate: 5.0e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 309\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.2060 - acc: 0.9377 - val_loss: 0.0739 - val_acc: 0.9832\n",
+      "55000/55000 [==============================] - 3s 56us/sample - loss: 0.2504 - accuracy: 0.9302 - val_loss: 0.0794 - val_accuracy: 0.9784\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.0781 - acc: 0.9814 - val_loss: 0.0765 - val_acc: 0.9842\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 0.0642 - accuracy: 0.9801 - val_loss: 0.0631 - val_accuracy: 0.9814\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.0908 - acc: 0.9818 - val_loss: 0.1368 - val_acc: 0.9766\n",
+      "55000/55000 [==============================] - 5s 83us/sample - loss: 0.0439 - accuracy: 0.9861 - val_loss: 0.0465 - val_accuracy: 0.9878\n",
       "\n",
-      "Accuracy: 97.66%\n",
+      "Accuracy: 98.78%\n",
       "\n",
-      "learning rate: 1.0e-02\n",
-      "num_dense_layers: 5\n",
+      "learning rate: 1.1e-04\n",
+      "num_dense_layers: 1\n",
       "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3199 - acc: 0.1105 - val_loss: 2.3015 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 4s 64us/sample - loss: 0.5362 - accuracy: 0.8733 - val_loss: 0.1483 - val_accuracy: 0.9572\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 2.3020 - acc: 0.1104 - val_loss: 2.3011 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 50us/sample - loss: 0.1423 - accuracy: 0.9581 - val_loss: 0.0895 - val_accuracy: 0.9730\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 2.3018 - acc: 0.1110 - val_loss: 2.3013 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 4s 81us/sample - loss: 0.0942 - accuracy: 0.9724 - val_loss: 0.0687 - val_accuracy: 0.9806\n",
       "\n",
-      "Accuracy: 11.26%\n",
+      "Accuracy: 98.06%\n",
       "\n",
-      "learning rate: 1.9e-04\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 418\n",
+      "learning rate: 5.5e-05\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.3595 - acc: 0.8999 - val_loss: 0.0888 - val_acc: 0.9732\n",
+      "55000/55000 [==============================] - 3s 58us/sample - loss: 0.7263 - accuracy: 0.8272 - val_loss: 0.1854 - val_accuracy: 0.9470\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.0868 - acc: 0.9738 - val_loss: 0.0686 - val_acc: 0.9782\n",
+      "55000/55000 [==============================] - 3s 51us/sample - loss: 0.1967 - accuracy: 0.9415 - val_loss: 0.1209 - val_accuracy: 0.9666\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.0584 - acc: 0.9821 - val_loss: 0.0478 - val_acc: 0.9850\n",
+      "55000/55000 [==============================] - 6s 115us/sample - loss: 0.1333 - accuracy: 0.9604 - val_loss: 0.0909 - val_accuracy: 0.9748\n",
       "\n",
-      "Accuracy: 98.50%\n",
+      "Accuracy: 97.48%\n",
       "\n",
-      "learning rate: 2.4e-03\n",
+      "learning rate: 3.5e-05\n",
       "num_dense_layers: 4\n",
-      "num_dense_nodes: 144\n",
+      "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1906 - acc: 0.9390 - val_loss: 0.0576 - val_acc: 0.9834\n",
+      "55000/55000 [==============================] - 4s 70us/sample - loss: 0.7778 - accuracy: 0.8057 - val_loss: 0.1853 - val_accuracy: 0.9496\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.0550 - acc: 0.9840 - val_loss: 0.0402 - val_acc: 0.9890\n",
+      "55000/55000 [==============================] - 3s 54us/sample - loss: 0.1914 - accuracy: 0.9435 - val_loss: 0.1170 - val_accuracy: 0.9678\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0380 - acc: 0.9885 - val_loss: 0.0459 - val_acc: 0.9880\n",
+      "55000/55000 [==============================] - 6s 107us/sample - loss: 0.1281 - accuracy: 0.9622 - val_loss: 0.0848 - val_accuracy: 0.9778\n",
       "\n",
-      "Accuracy: 98.80%\n",
+      "Accuracy: 97.78%\n",
       "\n",
-      "learning rate: 6.8e-03\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 105\n",
+      "learning rate: 3.6e-05\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 446\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.1552 - acc: 0.9507 - val_loss: 0.0498 - val_acc: 0.9860\n",
+      "55000/55000 [==============================] - 3s 63us/sample - loss: 0.7959 - accuracy: 0.8041 - val_loss: 0.1977 - val_accuracy: 0.9454\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.0485 - acc: 0.9853 - val_loss: 0.0534 - val_acc: 0.9836\n",
+      "55000/55000 [==============================] - 3s 53us/sample - loss: 0.1957 - accuracy: 0.9419 - val_loss: 0.1231 - val_accuracy: 0.9658\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.0417 - acc: 0.9875 - val_loss: 0.0496 - val_acc: 0.9852\n",
+      "55000/55000 [==============================] - 6s 110us/sample - loss: 0.1334 - accuracy: 0.9598 - val_loss: 0.0973 - val_accuracy: 0.9734\n",
       "\n",
-      "Accuracy: 98.52%\n",
+      "Accuracy: 97.34%\n",
       "\n",
-      "learning rate: 2.5e-04\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 435\n",
+      "learning rate: 6.6e-05\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 143\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.3258 - acc: 0.9131 - val_loss: 0.1024 - val_acc: 0.9676\n",
+      "55000/55000 [==============================] - 4s 67us/sample - loss: 0.8583 - accuracy: 0.7593 - val_loss: 0.2149 - val_accuracy: 0.9410\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0856 - acc: 0.9742 - val_loss: 0.0603 - val_acc: 0.9812\n",
+      "55000/55000 [==============================] - 3s 50us/sample - loss: 0.2304 - accuracy: 0.9302 - val_loss: 0.1499 - val_accuracy: 0.9538\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0601 - acc: 0.9819 - val_loss: 0.0477 - val_acc: 0.9868\n",
+      "55000/55000 [==============================] - 5s 86us/sample - loss: 0.1615 - accuracy: 0.9511 - val_loss: 0.1022 - val_accuracy: 0.9700\n",
       "\n",
-      "Accuracy: 98.68%\n",
+      "Accuracy: 97.00%\n",
       "\n",
-      "learning rate: 2.5e-06\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 409\n",
-      "activation: relu\n",
+      "learning rate: 2.2e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 195\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.2504 - acc: 0.3689 - val_loss: 2.1796 - val_acc: 0.5498\n",
+      "55000/55000 [==============================] - 3s 53us/sample - loss: 2.2477 - accuracy: 0.1821 - val_loss: 1.6547 - val_accuracy: 0.6054\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.0835 - acc: 0.6384 - val_loss: 1.9688 - val_acc: 0.6812\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 0.8448 - accuracy: 0.7859 - val_loss: 0.4386 - val_accuracy: 0.8970\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 1.8409 - acc: 0.7098 - val_loss: 1.6977 - val_acc: 0.7404\n",
+      "55000/55000 [==============================] - 3s 61us/sample - loss: 0.4028 - accuracy: 0.8893 - val_loss: 0.2623 - val_accuracy: 0.9310\n",
       "\n",
-      "Accuracy: 74.04%\n",
+      "Accuracy: 93.10%\n",
       "\n",
-      "learning rate: 4.4e-03\n",
-      "num_dense_layers: 3\n",
-      "num_dense_nodes: 311\n",
-      "activation: relu\n",
+      "learning rate: 4.2e-05\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 512\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1504 - acc: 0.9523 - val_loss: 0.0746 - val_acc: 0.9800\n",
+      "55000/55000 [==============================] - 3s 61us/sample - loss: 2.3073 - accuracy: 0.1076 - val_loss: 2.2982 - val_accuracy: 0.1126\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0559 - acc: 0.9842 - val_loss: 0.0751 - val_acc: 0.9812\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 2.2914 - accuracy: 0.1344 - val_loss: 2.2685 - val_accuracy: 0.1802\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0431 - acc: 0.9884 - val_loss: 0.0500 - val_acc: 0.9870\n",
+      "55000/55000 [==============================] - 4s 79us/sample - loss: 2.1696 - accuracy: 0.3317 - val_loss: 1.9508 - val_accuracy: 0.5936\n",
       "\n",
-      "Accuracy: 98.70%\n",
+      "Accuracy: 59.36%\n",
       "\n",
-      "learning rate: 2.1e-03\n",
-      "num_dense_layers: 5\n",
-      "num_dense_nodes: 436\n",
+      "learning rate: 5.1e-06\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1884 - acc: 0.9418 - val_loss: 0.0664 - val_acc: 0.9840\n",
+      "55000/55000 [==============================] - 3s 59us/sample - loss: 2.0897 - accuracy: 0.5289 - val_loss: 1.6486 - val_accuracy: 0.7448\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0598 - acc: 0.9837 - val_loss: 0.0454 - val_acc: 0.9880\n",
+      "55000/55000 [==============================] - 3s 57us/sample - loss: 1.1361 - accuracy: 0.7831 - val_loss: 0.6805 - val_accuracy: 0.8716\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.0435 - acc: 0.9887 - val_loss: 0.0553 - val_acc: 0.9864\n",
+      "55000/55000 [==============================] - 6s 118us/sample - loss: 0.5963 - accuracy: 0.8549 - val_loss: 0.4089 - val_accuracy: 0.9120\n",
       "\n",
-      "Accuracy: 98.64%\n",
+      "Accuracy: 91.20%\n",
       "\n",
-      "learning rate: 1.9e-04\n",
-      "num_dense_layers: 3\n",
-      "num_dense_nodes: 441\n",
-      "activation: relu\n",
+      "learning rate: 1.4e-06\n",
+      "num_dense_layers: 4\n",
+      "num_dense_nodes: 512\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.3664 - acc: 0.8989 - val_loss: 0.1076 - val_acc: 0.9698\n",
-      "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0872 - acc: 0.9736 - val_loss: 0.0626 - val_acc: 0.9816\n",
+      "55000/55000 [==============================] - 4s 70us/sample - loss: 2.3907 - accuracy: 0.0994 - val_loss: 2.3302 - val_accuracy: 0.0986\n",
+      "Epoch 2/3\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "55000/55000 [==============================] - 3s 52us/sample - loss: 2.3122 - accuracy: 0.0994 - val_loss: 2.3043 - val_accuracy: 0.0986\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.0583 - acc: 0.9824 - val_loss: 0.0504 - val_acc: 0.9856\n",
+      "55000/55000 [==============================] - 7s 121us/sample - loss: 2.3020 - accuracy: 0.1115 - val_loss: 2.3020 - val_accuracy: 0.1060\n",
       "\n",
-      "Accuracy: 98.56%\n",
+      "Accuracy: 10.60%\n",
       "\n",
-      "learning rate: 1.7e-03\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 512\n",
+      "learning rate: 4.8e-04\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 225\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.2528 - acc: 0.5598 - val_loss: 0.2764 - val_acc: 0.9186\n",
+      "55000/55000 [==============================] - 3s 59us/sample - loss: 1.5780 - accuracy: 0.4531 - val_loss: 0.3782 - val_accuracy: 0.9030\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.2010 - acc: 0.9369 - val_loss: 0.1251 - val_acc: 0.9592\n",
+      "55000/55000 [==============================] - 3s 52us/sample - loss: 0.2985 - accuracy: 0.9146 - val_loss: 0.1567 - val_accuracy: 0.9564\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.1203 - acc: 0.9629 - val_loss: 0.0916 - val_acc: 0.9734\n",
+      "55000/55000 [==============================] - 7s 118us/sample - loss: 0.1712 - accuracy: 0.9491 - val_loss: 0.1077 - val_accuracy: 0.9704\n",
       "\n",
-      "Accuracy: 97.34%\n",
+      "Accuracy: 97.04%\n",
       "\n",
-      "learning rate: 1.5e-03\n",
-      "num_dense_layers: 5\n",
-      "num_dense_nodes: 285\n",
-      "activation: sigmoid\n",
+      "learning rate: 5.5e-03\n",
+      "num_dense_layers: 1\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.1378 - acc: 0.1588 - val_loss: 1.2723 - val_acc: 0.4116\n",
+      "55000/55000 [==============================] - 4s 69us/sample - loss: 0.1434 - accuracy: 0.9557 - val_loss: 0.0516 - val_accuracy: 0.9834\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.5670 - acc: 0.7991 - val_loss: 0.2616 - val_acc: 0.9266\n",
+      "55000/55000 [==============================] - 3s 49us/sample - loss: 0.0457 - accuracy: 0.9858 - val_loss: 0.0441 - val_accuracy: 0.9874\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.1877 - acc: 0.9460 - val_loss: 0.1365 - val_acc: 0.9618\n",
+      "55000/55000 [==============================] - 6s 110us/sample - loss: 0.0330 - accuracy: 0.9894 - val_loss: 0.0582 - val_accuracy: 0.9854\n",
       "\n",
-      "Accuracy: 96.18%\n",
+      "Accuracy: 98.54%\n",
       "\n",
-      "learning rate: 3.3e-04\n",
-      "num_dense_layers: 5\n",
+      "learning rate: 2.4e-03\n",
+      "num_dense_layers: 3\n",
       "num_dense_nodes: 5\n",
-      "activation: sigmoid\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3570 - acc: 0.0907 - val_loss: 2.3175 - val_acc: 0.0868\n",
+      "55000/55000 [==============================] - 3s 63us/sample - loss: 1.1980 - accuracy: 0.5365 - val_loss: 0.3991 - val_accuracy: 0.8454\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.3074 - acc: 0.0952 - val_loss: 2.3029 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 3s 50us/sample - loss: 0.3059 - accuracy: 0.9074 - val_loss: 0.1823 - val_accuracy: 0.9488\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 2.3019 - acc: 0.1123 - val_loss: 2.3013 - val_acc: 0.1126\n",
+      "55000/55000 [==============================] - 4s 77us/sample - loss: 0.1815 - accuracy: 0.9497 - val_loss: 0.1492 - val_accuracy: 0.9606\n",
       "\n",
-      "Accuracy: 11.26%\n",
+      "Accuracy: 96.06%\n",
       "\n",
-      "learning rate: 2.3e-04\n",
-      "num_dense_layers: 4\n",
+      "learning rate: 6.6e-04\n",
+      "num_dense_layers: 1\n",
       "num_dense_nodes: 512\n",
-      "activation: sigmoid\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 2.1591 - acc: 0.1861 - val_loss: 1.0381 - val_acc: 0.6422\n",
+      "55000/55000 [==============================] - 3s 61us/sample - loss: 0.2145 - accuracy: 0.9392 - val_loss: 0.0638 - val_accuracy: 0.9830\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.6686 - acc: 0.7868 - val_loss: 0.4403 - val_acc: 0.8662\n",
+      "55000/55000 [==============================] - 3s 51us/sample - loss: 0.0591 - accuracy: 0.9817 - val_loss: 0.0539 - val_accuracy: 0.9856\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.3814 - acc: 0.8831 - val_loss: 0.2920 - val_acc: 0.9090\n",
+      "55000/55000 [==============================] - 3s 62us/sample - loss: 0.0395 - accuracy: 0.9879 - val_loss: 0.0454 - val_accuracy: 0.9890\n",
       "\n",
-      "Accuracy: 90.90%\n",
+      "Accuracy: 98.90%\n",
       "\n",
-      "learning rate: 2.6e-03\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 126\n",
-      "activation: sigmoid\n",
+      "learning rate: 1.0e-06\n",
+      "num_dense_layers: 5\n",
+      "num_dense_nodes: 512\n",
+      "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 1.1633 - acc: 0.5922 - val_loss: 0.1928 - val_acc: 0.9422\n",
+      "55000/55000 [==============================] - 3s 64us/sample - loss: 2.2933 - accuracy: 0.2440 - val_loss: 2.2784 - val_accuracy: 0.4338\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.1490 - acc: 0.9550 - val_loss: 0.0859 - val_acc: 0.9778\n",
+      "55000/55000 [==============================] - 4s 68us/sample - loss: 2.2577 - accuracy: 0.5072 - val_loss: 2.2230 - val_accuracy: 0.5994\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 5s - loss: 0.0885 - acc: 0.9729 - val_loss: 0.0735 - val_acc: 0.9786\n",
+      "55000/55000 [==============================] - 8s 154us/sample - loss: 2.1768 - accuracy: 0.6255 - val_loss: 2.0998 - val_accuracy: 0.7048\n",
       "\n",
-      "Accuracy: 97.86%\n",
+      "Accuracy: 70.48%\n",
       "\n",
-      "learning rate: 5.7e-04\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 246\n",
+      "learning rate: 2.9e-03\n",
+      "num_dense_layers: 2\n",
+      "num_dense_nodes: 299\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.2579 - acc: 0.9261 - val_loss: 0.0748 - val_acc: 0.9782\n",
+      "55000/55000 [==============================] - 4s 69us/sample - loss: 0.1429 - accuracy: 0.9546 - val_loss: 0.0407 - val_accuracy: 0.9882\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.0691 - acc: 0.9787 - val_loss: 0.0502 - val_acc: 0.9858\n",
+      "55000/55000 [==============================] - 3s 59us/sample - loss: 0.0452 - accuracy: 0.9855 - val_loss: 0.0391 - val_accuracy: 0.9882\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.0465 - acc: 0.9854 - val_loss: 0.0423 - val_acc: 0.9880\n",
+      "55000/55000 [==============================] - 7s 132us/sample - loss: 0.0310 - accuracy: 0.9903 - val_loss: 0.0370 - val_accuracy: 0.9894\n",
       "\n",
-      "Accuracy: 98.80%\n",
+      "Accuracy: 98.94%\n",
       "\n",
-      "learning rate: 2.4e-04\n",
-      "num_dense_layers: 1\n",
-      "num_dense_nodes: 164\n",
+      "learning rate: 1.8e-04\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.4321 - acc: 0.8849 - val_loss: 0.1429 - val_acc: 0.9608\n",
+      "55000/55000 [==============================] - 3s 62us/sample - loss: 0.3695 - accuracy: 0.8938 - val_loss: 0.0923 - val_accuracy: 0.9740\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.1163 - acc: 0.9654 - val_loss: 0.0821 - val_acc: 0.9766\n",
+      "55000/55000 [==============================] - 3s 54us/sample - loss: 0.0903 - accuracy: 0.9729 - val_loss: 0.0664 - val_accuracy: 0.9808\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0794 - acc: 0.9762 - val_loss: 0.0679 - val_acc: 0.9796\n",
+      "55000/55000 [==============================] - 7s 126us/sample - loss: 0.0613 - accuracy: 0.9809 - val_loss: 0.0611 - val_accuracy: 0.9830\n",
       "\n",
-      "Accuracy: 97.96%\n",
+      "Accuracy: 98.30%\n",
       "\n",
       "learning rate: 1.0e-06\n",
       "num_dense_layers: 2\n",
-      "num_dense_nodes: 5\n",
+      "num_dense_nodes: 512\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.3000 - acc: 0.1046 - val_loss: 2.2987 - val_acc: 0.1122\n",
+      "55000/55000 [==============================] - 9s 168us/sample - loss: 2.2758 - accuracy: 0.2655 - val_loss: 2.2455 - val_accuracy: 0.4236\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 2.2981 - acc: 0.1124 - val_loss: 2.2965 - val_acc: 0.1224\n",
+      "55000/55000 [==============================] - 8s 138us/sample - loss: 2.2145 - accuracy: 0.5053 - val_loss: 2.1717 - val_accuracy: 0.6046\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 4s - loss: 2.2959 - acc: 0.1221 - val_loss: 2.2941 - val_acc: 0.1290\n",
+      "55000/55000 [==============================] - 7s 128us/sample - loss: 2.1320 - accuracy: 0.6202 - val_loss: 2.0713 - val_accuracy: 0.6850\n",
       "\n",
-      "Accuracy: 12.90%\n",
+      "Accuracy: 68.50%\n",
       "\n",
-      "learning rate: 1.3e-05\n",
-      "num_dense_layers: 2\n",
-      "num_dense_nodes: 512\n",
+      "learning rate: 1.0e-02\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 5\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.6243 - acc: 0.6472 - val_loss: 0.7587 - val_acc: 0.8260\n",
+      "55000/55000 [==============================] - 3s 60us/sample - loss: 1.5650 - accuracy: 0.3523 - val_loss: 1.2933 - val_accuracy: 0.4494\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.5184 - acc: 0.8724 - val_loss: 0.3656 - val_acc: 0.9038\n",
+      "55000/55000 [==============================] - 3s 48us/sample - loss: 0.9217 - accuracy: 0.6472 - val_loss: 0.6613 - val_accuracy: 0.7856\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 7s - loss: 0.3292 - acc: 0.9091 - val_loss: 0.2724 - val_acc: 0.9268\n",
+      "55000/55000 [==============================] - 5s 85us/sample - loss: 0.6513 - accuracy: 0.7897 - val_loss: 0.4982 - val_accuracy: 0.8736\n",
       "\n",
-      "Accuracy: 92.68%\n",
+      "Accuracy: 87.36%\n",
       "\n",
-      "learning rate: 7.6e-05\n",
+      "learning rate: 1.4e-03\n",
       "num_dense_layers: 1\n",
-      "num_dense_nodes: 241\n",
-      "activation: relu\n",
+      "num_dense_nodes: 512\n",
+      "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.7636 - acc: 0.8233 - val_loss: 0.2393 - val_acc: 0.9368\n",
+      "55000/55000 [==============================] - 3s 62us/sample - loss: 1.3383 - accuracy: 0.5226 - val_loss: 0.2304 - val_accuracy: 0.9322\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 2s - loss: 0.1961 - acc: 0.9448 - val_loss: 0.1449 - val_acc: 0.9612\n",
+      "55000/55000 [==============================] - 3s 53us/sample - loss: 0.2098 - accuracy: 0.9346 - val_loss: 0.1193 - val_accuracy: 0.9642\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.1309 - acc: 0.9617 - val_loss: 0.1068 - val_acc: 0.9688\n",
+      "55000/55000 [==============================] - 7s 123us/sample - loss: 0.1266 - accuracy: 0.9606 - val_loss: 0.0846 - val_accuracy: 0.9750\n",
       "\n",
-      "Accuracy: 96.88%\n",
+      "Accuracy: 97.50%\n",
       "\n",
-      "learning rate: 2.0e-03\n",
-      "num_dense_layers: 4\n",
-      "num_dense_nodes: 512\n",
+      "learning rate: 4.6e-04\n",
+      "num_dense_layers: 3\n",
+      "num_dense_nodes: 105\n",
       "activation: relu\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1668 - acc: 0.9474 - val_loss: 0.0605 - val_acc: 0.9832\n",
+      "55000/55000 [==============================] - 9s 168us/sample - loss: 0.3599 - accuracy: 0.8924 - val_loss: 0.0980 - val_accuracy: 0.9706\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 4s - loss: 0.0548 - acc: 0.9845 - val_loss: 0.0419 - val_acc: 0.9902\n",
+      "55000/55000 [==============================] - 7s 124us/sample - loss: 0.0884 - accuracy: 0.9728 - val_loss: 0.0749 - val_accuracy: 0.9788\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 8s - loss: 0.0408 - acc: 0.9890 - val_loss: 0.0596 - val_acc: 0.9844\n",
+      "55000/55000 [==============================] - 7s 124us/sample - loss: 0.0643 - accuracy: 0.9799 - val_loss: 0.0548 - val_accuracy: 0.9860\n",
       "\n",
-      "Accuracy: 98.44%\n",
+      "Accuracy: 98.60%\n",
       "\n",
-      "learning rate: 2.2e-03\n",
+      "learning rate: 1.0e-03\n",
       "num_dense_layers: 2\n",
-      "num_dense_nodes: 326\n",
+      "num_dense_nodes: 512\n",
       "activation: sigmoid\n",
       "\n",
       "Train on 55000 samples, validate on 5000 samples\n",
       "Epoch 1/3\n",
-      "55000/55000 [==============================] - 3s - loss: 1.1358 - acc: 0.5865 - val_loss: 0.2104 - val_acc: 0.9356\n",
+      "55000/55000 [==============================] - 3s 62us/sample - loss: 1.1924 - accuracy: 0.5680 - val_loss: 0.1600 - val_accuracy: 0.9518\n",
       "Epoch 2/3\n",
-      "55000/55000 [==============================] - 3s - loss: 0.1576 - acc: 0.9505 - val_loss: 0.0999 - val_acc: 0.9712\n",
+      "55000/55000 [==============================] - 3s 54us/sample - loss: 0.1456 - accuracy: 0.9542 - val_loss: 0.0808 - val_accuracy: 0.9764\n",
       "Epoch 3/3\n",
-      "55000/55000 [==============================] - 6s - loss: 0.1011 - acc: 0.9679 - val_loss: 0.0856 - val_acc: 0.9726\n",
+      "55000/55000 [==============================] - 6s 117us/sample - loss: 0.0892 - accuracy: 0.9727 - val_loss: 0.0612 - val_accuracy: 0.9806\n",
       "\n",
-      "Accuracy: 97.26%\n",
-      "\n"
+      "Accuracy: 98.06%\n",
+      "\n",
+      "CPU times: user 12min 22s, sys: 2min 47s, total: 15min 9s\n",
+      "Wall time: 9min 35s\n"
      ]
     }
    ],
    "source": [
+    "%%time\n",
     "search_result = gp_minimize(func=fitness,\n",
     "                            dimensions=dimensions,\n",
     "                            acq_func='EI', # Expected Improvement.\n",
@@ -1580,30 +1510,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2830202e8>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8da0d14a8>"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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2zZs3r2BMnZ2dtLS0lPV73PyfT/LQk2s4a+aBHDZlfFnXlqOS2AaLY6uMY6uM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\nAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc285dc5cf8>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1622,19 +1553,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 28,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[0.0023584457378584664, 4, 144, 'relu']"
+       "[0.01, 2, 104, 'relu']"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1654,10 +1584,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 29,
+   "metadata": {},
    "outputs": [],
    "source": [
     "space = search_result.space"
@@ -1672,21 +1600,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 30,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'activation': 'relu',\n",
-       " 'learning_rate': 0.0023584457378584664,\n",
-       " 'num_dense_layers': 4,\n",
-       " 'num_dense_nodes': 144}"
+       "{'learning_rate': 0.01,\n",
+       " 'num_dense_layers': 2,\n",
+       " 'num_dense_nodes': 104,\n",
+       " 'activation': 'relu'}"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1704,19 +1630,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 31,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "-0.98799999999999999"
+       "-0.9904"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1736,58 +1661,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 32,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[(-0.98799999999999999, [0.00057102338020535671, 1, 246, 'relu']),\n",
-       " (-0.98799999999999999, [0.0023584457378584664, 4, 144, 'relu']),\n",
-       " (-0.98699999999999999, [0.0043924439217142824, 3, 311, 'relu']),\n",
-       " (-0.98680000000000001, [0.00025070302453255417, 2, 435, 'relu']),\n",
-       " (-0.98640000000000005, [0.0020904801989242469, 5, 436, 'relu']),\n",
-       " (-0.98560000000000003, [0.00017567744133971055, 4, 453, 'relu']),\n",
-       " (-0.98560000000000003, [0.00018871091218374878, 3, 441, 'relu']),\n",
-       " (-0.98560000000000003, [0.0010013922052631494, 3, 496, 'relu']),\n",
-       " (-0.98519999999999996, [0.006752254693985822, 2, 105, 'relu']),\n",
-       " (-0.98499999999999999, [0.0001905308801138268, 4, 418, 'relu']),\n",
-       " (-0.98460000000000003, [0.0073224617473678331, 3, 166, 'relu']),\n",
-       " (-0.98440000000000005, [0.0020143982003767271, 4, 512, 'relu']),\n",
-       " (-0.98419999999999996, [0.0014193250864683331, 2, 62, 'relu']),\n",
-       " (-0.97960000000000003, [0.00023735076383216567, 1, 164, 'relu']),\n",
-       " (-0.97860000000000003, [0.0026064900033469073, 1, 126, 'sigmoid']),\n",
-       " (-0.97660000000000002, [0.0037123587226393501, 5, 512, 'relu']),\n",
-       " (-0.9758, [0.0027230837381696737, 2, 364, 'sigmoid']),\n",
-       " (-0.97340000000000004, [0.0016597651372777609, 1, 512, 'sigmoid']),\n",
-       " (-0.97260000000000002, [0.0022460993827137423, 2, 326, 'sigmoid']),\n",
-       " (-0.96919999999999995, [0.00060563429543890952, 2, 474, 'sigmoid']),\n",
-       " (-0.96879999999999999, [7.5808558985641429e-05, 1, 241, 'relu']),\n",
-       " (-0.96179999999999999, [0.0014963322170155162, 5, 285, 'sigmoid']),\n",
-       " (-0.96120000000000005, [0.00013559943302194881, 2, 29, 'relu']),\n",
-       " (-0.95699999999999996, [0.00056441093780360571, 5, 13, 'relu']),\n",
-       " (-0.94679999999999997, [0.00036704404112128516, 4, 338, 'sigmoid']),\n",
-       " (-0.92679999999999996, [1.3066947342663859e-05, 2, 512, 'relu']),\n",
-       " (-0.90900000000000003, [0.00023277413216549582, 4, 512, 'sigmoid']),\n",
-       " (-0.90139999999999998, [0.001544493082361837, 1, 5, 'sigmoid']),\n",
-       " (-0.85440000000000005, [0.00016937303683800523, 4, 252, 'sigmoid']),\n",
-       " (-0.85140000000000005, [6.1458838378363633e-06, 2, 333, 'relu']),\n",
-       " (-0.74039999999999995, [2.4847514577863683e-06, 1, 409, 'relu']),\n",
-       " (-0.72899999999999998, [1.7068698743151031e-06, 4, 512, 'relu']),\n",
-       " (-0.61660000000000004, [1e-05, 1, 16, 'relu']),\n",
-       " (-0.2898, [6.1011365846453456e-05, 2, 209, 'sigmoid']),\n",
-       " (-0.129, [9.9999999999999995e-07, 2, 5, 'relu']),\n",
-       " (-0.11260000000000001, [5.4599879082087208e-06, 4, 186, 'sigmoid']),\n",
-       " (-0.11260000000000001, [3.1218037895598157e-05, 3, 427, 'sigmoid']),\n",
-       " (-0.11260000000000001, [0.00033099542158994725, 5, 5, 'sigmoid']),\n",
-       " (-0.11260000000000001, [0.01, 5, 352, 'sigmoid']),\n",
-       " (-0.11260000000000001, [0.01, 5, 512, 'relu'])]"
+       "[(-0.9904, [0.01, 2, 104, 'relu']),\n",
+       " (-0.9894, [0.0029398096826104927, 2, 299, 'relu']),\n",
+       " (-0.9892, [0.000695826471438557, 1, 365, 'relu']),\n",
+       " (-0.989, [0.000658408209046353, 1, 512, 'relu']),\n",
+       " (-0.989, [0.0034329866293724173, 2, 451, 'relu']),\n",
+       " (-0.9882, [0.0027527776962813647, 2, 441, 'relu']),\n",
+       " (-0.9878, [0.0004989932212151087, 2, 309, 'relu']),\n",
+       " (-0.987, [0.009700568764470742, 3, 132, 'relu']),\n",
+       " (-0.986, [0.00045720538478821585, 3, 105, 'relu']),\n",
+       " (-0.9854, [0.005470139269128146, 1, 512, 'relu']),\n",
+       " (-0.983, [0.0001756750312956145, 3, 512, 'relu']),\n",
+       " (-0.9806, [0.00010996497783044355, 1, 512, 'relu']),\n",
+       " (-0.9806, [0.0010101832379944083, 2, 512, 'sigmoid']),\n",
+       " (-0.9778, [3.542177009701199e-05, 4, 512, 'relu']),\n",
+       " (-0.975, [0.0014121597194479596, 1, 512, 'sigmoid']),\n",
+       " (-0.9748, [5.4968307266680435e-05, 2, 512, 'relu']),\n",
+       " (-0.9746, [7.662555005436298e-05, 5, 154, 'relu']),\n",
+       " (-0.9734, [3.623853563736315e-05, 5, 446, 'relu']),\n",
+       " (-0.9708, [0.0006699631867581338, 3, 230, 'sigmoid']),\n",
+       " (-0.9704, [0.0004806874905820532, 2, 225, 'sigmoid']),\n",
+       " (-0.97, [6.592244748528267e-05, 4, 143, 'relu']),\n",
+       " (-0.97, [0.0005519055319736135, 3, 277, 'sigmoid']),\n",
+       " (-0.9606, [0.0024078003512664754, 3, 5, 'relu']),\n",
+       " (-0.9592, [0.0002839701110319199, 2, 512, 'sigmoid']),\n",
+       " (-0.931, [0.00021682795230749897, 2, 195, 'sigmoid']),\n",
+       " (-0.9256, [1.152958307942762e-05, 5, 182, 'relu']),\n",
+       " (-0.9226, [1.068205878028229e-05, 1, 496, 'relu']),\n",
+       " (-0.9176, [0.00037183580449927443, 3, 72, 'sigmoid']),\n",
+       " (-0.912, [5.101545871674443e-06, 3, 512, 'relu']),\n",
+       " (-0.8736, [0.01, 3, 5, 'relu']),\n",
+       " (-0.725, [1e-05, 1, 16, 'relu']),\n",
+       " (-0.7048, [1e-06, 5, 512, 'relu']),\n",
+       " (-0.6904, [0.0001581796478320478, 4, 112, 'sigmoid']),\n",
+       " (-0.685, [1e-06, 2, 512, 'relu']),\n",
+       " (-0.5936, [4.158851683068185e-05, 1, 512, 'sigmoid']),\n",
+       " (-0.106, [1.42502793530235e-06, 4, 512, 'sigmoid']),\n",
+       " (-0.106, [0.0028996992551655475, 4, 156, 'sigmoid']),\n",
+       " (-0.106, [0.0034427213718442543, 3, 5, 'sigmoid']),\n",
+       " (-0.106, [0.006781678732829231, 4, 466, 'relu']),\n",
+       " (-0.0978, [0.0009844064941977042, 5, 122, 'sigmoid'])]"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1807,20 +1731,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 33,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc2704bb860>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1842,20 +1767,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 34,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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JiMbc65uBSkmT+6l7dUTMjYi5lVSPaJxmZvuToiYGSYdIUu71ybl4dhYzJjOz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\nicHMzPL8fy6cRQja3MY6AAAAAElFTkSuQmCC\n",
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iUhojJg93L3itqXxmdr27f3r0IcVPSUREZHQi3YZ2BGeVcF1locN8RUQOTSmTR03SuSIiItGN++TRT0lERKR4pUweY+KwByUREZGRRU4eZjbUDRC+O8pYqooSiIjI0KLcDOpMM2sjvB+Hmc01s+/1z3f3n5Q+vMpSK0REpLAoLY//B/w5sB3A3R8H3hFHUNVGCUREZLBI3Vbu/lJeUaaEsVQ1JRDJ15WpH7mSyBgVJXm8ZGZnAm5mdWb2BcbZLWPVjVUZ+pIWqT5RksdlwOXA0cBW4NRwetxRAhGR8S7KVXU7gY9EWbmZ1QMPApPCbd3h7l/OqzMJuAU4jWA85a/c/YUo26mEvZlJuryJiIxbUY62+g8zOzzssnrAzF41s4+OsFgvsMjd5xK0VN5tZm/Lq3MJsNPdTyAYlP9mlDdQSXG3QNqXbeN3X3+c9mXbYt2OVK/lS7r5xjU7Wb6kO/Ztrbl/Dz/4ylbW3L+n4Py2pR3c9W9tBT+PL67YzKr/eIStD7140LxXH36Wp69byo7Vz5Q85jjt2ryeFx/5NTu3rC96mc5X22h/+n/ofLUtxsii68hu5bH0gwAnlGqdUbqtznX3PcD5BPcvPwG4argFPLA3nKwLH/mXd38f0H/xxTuAd5pZzZxwGFcCaV+2jTuvbqX1tue58+pWJZBxaOWSffzjp3dw+83Bc5wJZOWSffznlZv531t38J9XbmbtAzsHzX986XYWX7WO1T/ffNDn8cUVm1n2Lw+y8ZdPs+qapYMSyCsrn2fDv93L1rsep/3rv6mZBLJr83qeW/FTXn3qYTat/GlRCaSzo40NG25j69ZH2LDhNl7dXh1Dwh3ZrTyRXcV2tgFMLdV6oySP/i6u84BfuvvuYhYys6SZrQM6gCXuviavytHASwDunia42dQRBdZzqZm1mllr967q6i6KI4E8t7qDVE9wMFuqJ8NzqztKvg2pbo+u3E9Pd/Bbq6fbWf1QfPc1eXTlfnp7gm319jhPrhz879328E5SPVng4M/j1jUvkwk/q5meNNvWbDkw79VHN5PtTQOQ7U2za+0Lsb2HUtr9cjvZTHDn7Wwmxe5t7SMus7OznWw2XCabYvvOTbHGWKzt/gpOtuTrjZI87jGzpwjGJh4wsyOBET/N7p5x91OBY4AzzOzkQwnU3W9y93nuPq9hWvUNWJf6SKzj5s+krj4JQF19kuPmzyzZumWw3ZmhLppQWacvaKS+IWiE1zcY898e31Fnpy9oZFK4rUn1xikLBv9AbTlrOnX1wddF/ufx6Le+lmT4WU3WT2DWW485MO/I019HYlLwuzMxaQLTTpsd23sopamvbSaRrAMgkaxj6qzmEZeZ3tRMIhEuk6jjiOkl6yEalSPsNVgMlzE09yFvEnhwZbMZwG53z4SXKTnc3V+JsPw1wH53/8+cst8DX3H31WY2AXgFONKHCeyolhl+8eJzi4673Eo1kN6+bBvPre7guPkzaT57VknWWavivpvg1OT+Q1qu2LimJIbvcpqWKLz9xx7YxeqHepj/9noWntOQs750gW0M/QXRlc3mTQ8cK7MnG/zoWblkHw8/1MepC6bQsuiooF7OYdKrl+ylfVUnx75tFs1nzzrwY6krXc+LKzazdc3LNJ3+eo5+++vZmxr4IfXiis3sWPsiU958HDPmz6E7FXzB9qYGYkilg+ST7gues6ngvXh64D1ZX/DaUgO92v13EkyEZYm+gffYv4sGlaUGz8stSw6q5+zavJ7dL7cz/ahmph9zMslez5k/sD9zy3dsXc+OHc8wY8YcZk47caB+z+BT4hJ9AwFYX97fsqdv8HRf3nRv3jSQ7T748+W9A99DHdmtbMk+y3a27Xb3aQdVPgRRk8eZwGxyjtJy91uGqX8kkHL3XWbWANwHfDPnfuiY2eXAKe5+mZldBHzA3T80XBzVnjxAN5oqtfGaPA5PFP4cRU0eMDiBFEoeALuyjeH8IFHlJo/+Flp/WW7y6LcvPTGYl5M89qeDZNETPtdK8uiX7J9fRPJI9GVz6gwkjEonj35L0revdfd5B804BEUfqmtmtwLHA+sYOLPcCQ6zHcos4GYzSxJ0kf3C3e8xs68Cre5+N/Aj4FYz2wTsAC6K/jaqjw7lFZGxrOjkAcwDWobrTsrn7k8Aby5Qfk3O6x7gLyPEUTOUQGS8Oqyud1DrQ8aeKKMo64HXxBWIiIjUjigtjyagzcz+QHDyHwDufkHJoxpD1Pooja5MfezjHiJSvCjJ4ytxBTHWKYGIjG/Z+uRBg+a1Lsq1rVaY2euBOe5+f3iobjK+0MYWJRARGUuiXNvqkwSXD/lBWHQ0cFccQY1VuhqviIwVUQbMLwfOAvYAuPszgE57jkgJRETGgijJo9fdD5ydEp4NXvwZhnKAEoiI1LooyWOFmf0T0GBm5wC/BH4TT1giIlLNoiSPfwReBZ4E/h64F/iXOIIaD9T6EJFaFuVoqyzw3+FDSkBHYEm1m5Ls0T3kpaARk4eZPckwYxvu/qaSRjTOKIGISC0qpuVxfvh8efh8a/j8UTRgLiIyLo2YPNz9RQAzO8fdcy9yeLWZPUYwFiKjoNaHiNSaKAPmZmZn5UycGXF5GYYG0EemvncRYNLESkcARLu21SXAj82s//6Uu4BPlD4kERGpdlGOtloLzO1PHu6+O3e+mf2tu99c4vjGFXVfiUitiNzt5O678xNH6MoSxDPuqftKZIBNyI5cqcb5xCgdQNWjlGMWNnIVEREZC0qZPA46bNfMjjWzZWbWZmYbzOyg1omZLTSz3Wa2Lnxck19nvFHrQ0SqXSnbS4VaHmng8+7+mJlNAdaa2RJ3b8ur95C7n19g+XFL4x8iUs1K2fJ4OL/A3be5+2Ph6y5gI8F9QEREpIYV3fIws2nA3wCzc5dz98+Ez1eMsPxs4M3AmgKz55vZ48DLwBfcfUOxcY1lan2ISLWK0m11L/AIwVV1Ix0CYWaHAb8CPuvue/JmPwa83t33mtl7Ce5OOKfAOi4FLgWYMqsxyuZFRKTEoiSPenf/XNQNmFkdQeL4mbv/On9+bjJx93vN7Htm1uTunXn1bgJuAjiqZca4uaaWWh/lsTvTyNTk/kqHIVIzoox53GpmnzSzWWY2o/8x3AJmZsCPgI3u/u0h6rwmrIeZnRHGtD1CXGOejr4SkWoTpeXRB3wL+GcGDst14LhhljkL+GvgSTNbF5b9E/A6AHe/EbgQ+JSZpYFu4CJ3HzctCxGRWhQleXweOCG/O2k47r6SEU4edPcbgBsixDEuqfsq0JWpZ0qyp9JhiIx7UbqtNgHqFBaRcSkzSRfRyBWl5bEPWGdmy4ADP4H7D9WV+Kn1ISLVIkryuCt8iIjIOBflkuy63HoVUOtDRKpBlDPMn6fAxQ/dfbijrUREZAyK0m01L+d1PfCXwLDneUg81PoQkUor+mgrd9+e89jq7t8BzosxNhERqVJRuq3ekjOZIGiJ1OYtsMYAtT5EDpadCIm+SkcxPkT58v8vBsY80sALBF1XIiIyzkQ5SfA9BNepeoDg3h1bgYviCEqKo2teiUilRD3PYxfBJdR1fQgRkXEsSvI4xt3fHVskckg09iEilRCl22qVmZ0SWyQiNagrU1/pEEQKsknxdmtHSR4LgLVm9rSZPWFmT5rZE3EFJjIUfWFXlykT1Is9HkXptnpPbFHIqKjrSqYkovwOFBm9KNe2ejHOQEREpHbo58oYocN2ZSxJ1GUrHYKMQMlDREQiizV5mNmxZrbMzNrMbIOZXVmgjpnZdWa2KRyIf0uhdcnI1PoQkSG5c2QJL2Yb97Wp0sDn3f0xM5tCcLTWEndvy6nzHmBO+Hgr8P3wWURESmQOO9kBbyjV+mJNHu6+DdgWvu4ys43A0UBu8ngfcIu7O/CImU0zs1nhsgV1vbKfZ5dv5fiFR8cZvoxhbUs7aF/VSfOZTbQsmlnpcA7Z/ff1sPLBXs5Z2MC7zy18CPPv7uth+Yoe3vr2ibxriDpRtC/bxto7XiDjCU754PGx/h/uf6yN7ic3UX9SM5NbTo5tO8Xa8fIGdv2pnQmJiWTSvUw7cg4zZ7QcmN/5ahs7djzDjBlzaDqyhUQqU8FoA9O8B8NZkFnPmhKu14Lv7PiZ2WzgQeBkd9+TU34P8O/uvjKcfgC42t1bh1mXT6hP8p5vzFcCKWA8HLY7JXno5xa0Le1g8VXrSPVkqatPcPG3TqVl0UymJvfHFsuURPew86clCm/78EThv+WURJr77+vhyit20dMNDQ3wg+/NOCiB/O6+Hv7+H3bQ3Q31DfDdG6bxrnPr6coO/G7ckx3o7tyVbQSgK9twoKz/vJrdmUbalnbw08+tI5MKBrQTdQnO+48zmbngeAD2pSceWG5vKljv/nQdAD3hc3cqeO5NDcSQSicBSPclB5Zf8xSd378N70thE+to+sRHaJx7EpayA3UsHbxO5JT1X1U3kR48HdQbPC+3LDmo3sD3YjKcv3PLejat/CnZTGqgXrKON869mKaZLXR2tLFx3WKy2RSJRB0nnXQRM6edOFC3ZyCRJPpyAgAsd7on77LAfQUuE9w7uCzbXfjzdVzPK3w/cx9ZgmtKvQNodbeClSMqy4C5mR0G/Ar4bG7iiLiOS82s1cxaAdI9GTY/8kopw5Rxon1VJ6me4Msv1ZOlfVVnhSM6NCsf7KUn/M7o7oblKw5OYstX9ND/vdLTHSwzGu2rOg8kDoBsKhvb/2H3+mfwvuCL2vtSdG9sD17XlecHb77d29oHJQ6AbCbFzs4grp2d7WSzwfxsNsWOHc+UPcZ8z9p0/jXxdvZhJe9mij15mFkdQeL4mbv/ukCVrcCxOdPHhGWDuPtN7j7P3ecBTKhP8rq3vSaOkGueBs6H13xmE3X1wUe/rj5B85lNFY7o0Cx4xyTqwwZCQwMs/LODu6QW/lk9DWGd+oZgmdFoPrOJZN3A10aiLhHb/2HDyXOwiUErxSbW0fDG5li2U6yps5pJJOsGlSWSdUxvCuKa3tRMIhHMTyTqmDFjTtljLGRN4rX8gqMxCtxHfBRi7bYyMwNuBna4+2eHqHMecAXwXoKB8uvc/Yzh1ts4o97fdc3p6rIaxljvuhpNtxUUHvOotW4rOPQxj0PttgJYe//Og8Y8utJBnVJ2W2VTiSHHPPq7rsrZbQWw+/n1w4557Ni6fsgxj0p0W3lv8Pm5Nf0bjmQ/zdC7yb0k1/eJO3ksAB4CngT627r/BLwOwN1vDBPMDcC7gf3Ax4cb7wA4qmWGX7z43NjiHguUPA7NoSSQSiaPgemROxG6stmc14eePPqnc1u4cSUPAE8Hz9Y38B4rlTySvR7Ozx5UFmxr8MmN1ZA8Ep7la5kHuTl5Ctdn7l/b33szWnEfbbUSGHZwJjzK6vI44xiPdL0rkWgyEwcnkLEiawm+NGFhyderM8ylJunKujJm1U8cuU4VUPIQEalmE6szmSh5jGE66qp65I4hiIwFSh4iUhGT6tIjV5KqpeQxxqn1ITL2JRrK37JV8hARkciUPEREJDIlj3FAXVciUmpKHiIiEWXr9NWpPSAiIpEpeYwT6roSkVJS8hARkciUPEREJDIlj3FEXVciUipKHlKzdGVdkcpR8hARkciUPMYZdV2JSCkoeYiISGSxJg8z+7GZdZjZ+iHmLzSz3Wa2LnxcE2c8IiJxyk4cP7/HY72HOfAT4AbglmHqPOTu58cch4iIlFCsadLdHwR2xLkNiU7jHiIyWtXQxppvZo+b2W/N7KRKByMiIiOLu9tqJI8Br3f3vWb2XuAuYE6himZ2KXApwJRZjeWLUERkGJlJRrLXKx1G2VW05eHue9x9b/j6XqDOzJqGqHuTu89z93kN09TtMlrquhKR0aho8jCz15iZha/PCOPZXsmYRERkZLF2W5nZz4GFQJOZbQG+DNQBuPuNwIXAp8wsDXQDF7n7+Gv/iYjUmFiTh7t/eIT5NxAcyisVsDczicOSvZUOQyRW2YmQ6Kt0FGNPNRxtJSJD2JPV2JRUJyUPERGJTMlDREQiU/IY52r9kN1S39Njd0bnEIkUQ8lDREQiU/IQEZHIlDyk5ruuRKT8lDxEZNzJVvqqfmOAkoeIiESm5CEiIpEpebbQIfoAAAikSURBVAigcQ8RiUbJQ0REIlPyEBmlUp+oKFILlDxERCQyJQ85QOMeIlIsJQ8REYlMyUNERCJT8hARkciUPGSQWhz30NFOIuUXa/Iwsx+bWYeZrR9ivpnZdWa2ycyeMLO3xBmPiIiURtyXB/sJcANwyxDz3wPMCR9vBb4fPkuZPLt8K5sfeYWJh9XRtzfF6972Gua+s6nSYR2ytqUdtK/qpPnMJloWzaxoLGsf2MmTK3dzyoKpnPbO6RWNpVJeWfk82/6whQmNk+jdm2LaabNpmNcS2/b2ta2n+6mnaTz+RA6fc3Js24lTR9czdO7eRFPD65k5+YRKhzOkWJOHuz9oZrOHqfI+4BZ3d+ARM5tmZrPcfVuccUng2eVb+e2XVpPuyRwo2/A/z9PwzXk0nz2rgpEdmralHSy+ah2pniytd27h4m+dWrEEsvaBndzw2Wfp68my4o5OrvjO8Sw8Z3x1r72y8nn+eO3vyfSmD5R1/P5JZn9xAlPf1lzy7e1rW8+fFt+Kp1LseewPJD741xx2Ym0lkI6uZ1i39S6ynmbL3vWcynlVm0As+N6OcQNB8rjH3Q/6K5rZPcC/u/vKcPoB4Gp3by1Q91Lg0nDyZKBgV1gJTQV2x7xsMfWGqhOlPL+sf/pYoNC3awfw0ghxRVWO/XlCWLdf/vsYbj3F7s9i9m8T0MDgfVvqfXqo+zPKciPVHWl/Hs7In6+R9m8T0FlMsBz8eS52n5fjs1lM3UL7rAPYM8RyUf7X+53o7lOKjHd47h7rA5gNrB9i3j3AgpzpB4B5RayztQxx3xT3ssXUG6pOlPL8sgLT42J/Dje/2P1Z5P6t2v0ZZblS78/x/Nkczf6s1v/1Sh9ttZXg10K/Y8KyavCbMixbTL2h6kQpzy8bzXs7VNWwP4ebX+z+LGb/lsOhbjPKcqXen+P5s1lM3Zr6X690t9V5wBXAewkGyq9z9zOKWGeru88rcajjlvZnaWl/lo72ZWmVcn/GOmBuZj8HFgJNZrYF+DJQB+DuNwL3EiSOTcB+4ONFrvqmkgc7vml/lpb2Z+loX5ZWyfZn7C0PEREZeyo95iEiIjVIyUNERCJT8hARkcjGXPIws4SZfc3Mrjezv610PLXOzBaa2UNmdqOZLax0PLXOzCabWauZnV/pWGqdmb0x/FzeYWafqnQ8tc7M/sLM/tvMbjezc0eqX1XJY6gLKZrZu83s6fACiv84wmreR3C+SArYElestaBE+9OBvUA943h/lmhfAlwN/CKeKGtHKfanu29098uADwFnxRlvtSvR/rzL3T8JXAb81YjbrKajrczsHQRfVLf0nxdiZkmgHTiH4MvrUeDDQBL4Rt4qPhE+drr7D8zsDne/sFzxV5sS7c9Od8+a2VHAt939I+WKv5qUaF/OBY4gSMSd7n5PeaKvPqXYn+7eYWYXAJ8CbnX3xeWKv9qUan+Gy/0X8DN3f2y4bcZ9Vd1IvPCFFM8ANrn7cwBmdhvwPnf/BnBQ0z88n6QvnMzkzx9PSrE/c+wEau9mHyVSos/mQmAy0AJ0m9m97p6NM+5qVarPprvfDdxtZv8LjNvkUaLPpwH/Dvx2pMQBVZY8hnA0gy9utoXhL9v+a+B6M3s78GCcgdWoSPvTzD4A/DkwjeDy+jIg0r50938GMLOPEbboYo2u9kT9bC4EPkDwo+beWCOrTVG/Oz8NvAuYamYnhCdyD6kWkkck7r4fuKTScYwV7v5rgoQsJeLuP6l0DGOBuy8Hllc4jDHD3a8Driu2flUNmA+hmi+eWIu0P0tH+7K0tD9LK9b9WQvJ41Fgjpm9wcwmAhcBd1c4plqm/Vk62pelpf1ZWrHuz6pKHuGFFFcDJ5rZFjO7xN3TBFfe/T2wEfiFu2+oZJy1QvuzdLQvS0v7s7QqsT+r6lBdERGpDVXV8hARkdqg5CEiIpEpeYiISGRKHiIiEpmSh4iIRKbkISIikSl5iIhIZEoeMqaY2d4ybOMyM/ubuLczxLY/ZmavrcS2RXLpJEEZU8xsr7sfVoL1JN29Ipf0H27bZrYc+IK7t5Y3KpHB1PKQMcvMrjKzR83sCTO7Nqf8LjNba2YbzOzSnPK9ZvZfZvY4MD+c/pqZPW5mj4Q3xMLMvmJmXwhfLzezb5rZH8ysPbwVAGbWaGa/MLM2M7vTzNaY2bxhYs3f9jVh7OvN7CYLXAjMA35mZuvMrMHMTjOzFeH7+b2ZzYpnb4oMpuQhY5IF92CeQ3BDnFOB08K7rUFw17TTCL6IP2NmR4Tlk4E17j7X3VeG04+4+1yCe8N8cojNTXD3M4DPAl8Oy/6B4I6WLcC/AqeNEHL+tm9w99PDu8I1AOe7+x1AK/ARdz8VSAPXAxeG7+fHwNeK20MiozPm7uchEjo3fPwxnD6MIJk8SJAw3h+WHxuWbye48+SvctbRB/TfKnYtwe08C/l1Tp3Z4esFwHcB3H29mT0xQrz52z7bzL4INAIzgA3Ab/KWORE4GVgS3ASOJLBthO2IlISSh4xVBnzD3X8wqDC4+9y7gPnuvj8cQ6gPZ/fkjTWkfGBQMMPQ/y+9RdQZyYFtm1k98D1gnru/ZGZfyYlx0NsBNrj7/EPcpsghU7eVjFW/Bz5hZocBmNnRZjYTmErQnbTfzP4P8LaYtv8w8KFw2y3AKRGW7U8UnWH8F+bM6wKmhK+fBo40s/nhdurM7KRRRS1SJLU8ZExy9/vM7I3A6rBLZy/wUeB3wGVmtpHgy/eRmEL4HnCzmbUBTxF0O+0uZkF332Vm/w2sB14huKlPv58AN5pZNzCfILFcZ2ZTCf6fvxNuSyRWOlRXJAZmlgTq3L3HzI4H7gdOdPe+CocmUhJqeYjEoxFYZmZ1BGMT/6DEIWOJWh4iZWRma4BJecV/7e5PViIekUOl5CEiIpHpaCsREYlMyUNERCJT8hARkciUPEREJDIlDxERiez/A0c1qzlH/2FGAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc270556320>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1877,10 +1803,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "dim_names = ['learning_rate', 'num_dense_nodes', 'num_dense_layers']"
@@ -1901,20 +1825,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 36,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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UN95Jqlof4n33uHYYsacB1ao6vv0TqnqRiHwLOBaYJyITVHVrGPcwKcjaNEyq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\n+VF3Tz0MvEDg5TarH56Z/Y3c2wLHcRynE0RtNMrN7BsRX9N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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc27c3010b8>"
+       "<Figure size 432x432 with 9 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1931,20 +1856,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 37,
    "metadata": {
-    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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PycCReJLU+6pa5JRPcd5bASOBd6vtN9F5/xZ4RUTeASb7icHspyxJmOaktNq0C0jGc3ZR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\nbTAYDPUxaxLeLATusO+2EZE+ItIdaxdLvq0ghgFnhaj9FcC19tpED/z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gBHhJRCYBk5z9xgKDnJMJgHYikqyqRfW8jsmqWgqUisgOIANv0vlIVfc7dX4InIg3KX2kqgec8onOz2RgFPBetXrjnJ8/AK+KyLvAh/XEYA4RlhRMa1Ja7bkbSMB79lDZDBrfwPaeassemve3L8DtqvpljUKR0XXEFq3eO/RHAqcCFwO3AWOceI9V1ZIm1utz7GbE7gIKVHV47RWqepOIHAOcDeSKyAhV3dWMOkwbYNcUTGu3Hm+TCXg/eAOiqgVAgYic4BRdWW31l8DNIhIDICIDRSSpvmM5385T1XuX/q+BYc6qr4Dbq23n80HdBN8BF4hIohPDhU7ZdKc8QURSgHOd17UXWCcilzh1iogMc573U9VZqvogkE/NQSnNIcbOFExr9wTwrjOc+uQgHfM64GURUbwf4JX+g7dZaJ5zITkfuKCB46QAn4hIPN6zjLud8juAZ0VkEd7/wenATf4EqKrzRORVYHZlbKo6H0BE/gcsBHbgHWSy0pXA8yLyB7zXJd5xtntcRAY4MU51yswhyoa5MMYYU8Waj4wxxlSx5iNzyBKRZ4Ha9wg8raqvhCGW64A7axX/oKq31rW9MaHS6puP2qUmaZdeHgDyy5Op0CgAYiSKvsld691v04FdFFX4dv5Ii00hPb4dALv27Gd34X7cbiU+LpqMtHYkxMfUe8wlO7ejokRFe3zWqYKnzBtblEsYlNaZlTt3UuZ2kx4TQ355OQBd2hUQ7fLdv6AwmeKS2BplnVOTSUv1XufML91Cmae4al00SkZ03Z1bStVd9TzK1YHo6F71vqYKrWDTAZ/J7wDomdidaPF+r8jNzd2pqun1HshPaWlpmpmZGazDmQAE+701ka3VnylkZHTi2YlJ7KlI5PlNo6vKL+t1Cjf2P6fe/SbnzeORxe/XKBOEN4+/nf4pXfhkykL+9sIUulVbn5wYx3vP3UC75No9H73umDqJiT8tI7nzflxRNZNt2b4YSncnAnDVEcP40+ixPDp9Oi/Oncuvu3fnyTzvB++5Ryzi+H6Lax7YE88//nUepWUHk0KUS3jvj78gs4v3xtxZu77io7yaUxrc0XEVXWolhgOeCnZUSx5dOr1BYsLYen5LXo8sfYxVRWtqlA1I7sfDgx+oWhaRDQ0exE+ZmZnMnWszfEaCYL+3JrK1iWsKJZrC1F0nAeBCGN15GNf2OaPBfc7ufhRXZZ5IrMubF1Oi4/nt4Avon9IFgEnf+I6BVnSglJyZq+o95iPHn8qJ3TMp3pOAp6LqBiGiy+Ip3ZOAAGP79OP+Ud5Y7zruOMYNHAjOzURdkpO5OOsP9Ew+g8q3JiGqMyd2e4KfHX8MMdHeM43UpHgeuvr0qoQAcHTHsYzqdBZRzjf3xKgUChJ+D9FVoxxQ4erObvUeVySBDu3uazQhANzS/3r6JvWuWu6b1Jtb+/+q0f2MMa1Pq28+Gpg1QFetXI1bPawr2kb72CTS4lKbvH9h2QG2lRTQOymd+KiDTUPX3Psaa9bn+2x/9/WnctFZRzZ4zE37CtlfVoor2kNKTDwZCams3LWT1Lg4uqW089n+62++ofuQIQzs1Ikol/dDu7gin1L3HlJj+yHiTQZ7iorZvmcffbp0JC6m7pO8/RV7KSjfSee4HsS4vGcWWrEGiEWie+HxFFFesY6Y6N64XL6xNGRr8TYAuiZ08VknIrmqmu3XARuQnZ2tdqYQGYL93prI1qzmIxHpAPRU1UVBjsf/WJxv1FHion9Kt0a29pUam0hqbKJP+ZjjsnySQnS0i5NG9m/0mD1TfJPS4Wn1N8lGu1wcnl5zfUJ0OgnRNcs6JCfQITmhwbqTotuRFF3zw16iD8bsciUTFzukwWPUp65kYIxpW5qcFEQkBzjP2ScX2CEiP6jq3Q3u2Epdcd7RrN+8i69/WIHHo7RLjufe8WNJ75QS7tDCyuPxMP/bFezM28OQ4wfSrU/wrj86N6CNB+jVq/6L3yZ0Mh8I1v1/prXy50whVVX3isivgNdV9SHnjsw2KSYmiofuPJubrzqJ/F1F9M9MJy621V+XD8i+Pfv57UVP8dPiTQCICFfffy6X3zMuKMdX1QnABPA2HwXloMYYv/hzoTlaRLoCl3JwtMc2r3OnFAYP7HrIJwSAN5+YXJUQwDvs+uuPTmTjqq1hjMoYE0z+fNL9H94BwX5Q1Tki0hdYHZqwTDity9vFlBkr8CiMPXYg/Xt6m4jm5Syrc/vcb+ouN8a0Pk1OCqr6HvBeteW1wEWhCKo121m8n/+tWcSmfQVkd+7BeX0GERsVFe6wmmzqrFU8+Oxk3B5v683rE2fzh/FnMO7EQXRIb8emVdt89umQ4V8vJmNM5Gpy85EzTPDUyknMRWSoM9qicWwuKmTcp6/y+LzpvLN6Eff+8BnXTX0Pt8f3DuVIU1JewRuz53PfJ1+wr6Pidr4ueFT551vfUlZewYU3neqzX5feaYw6qzkjPxtjIpE/1xReBH4LlAM43VEvC0VQrdW/l8xiR3HNybN+2LqBqZt/ClNETeP2ePjVmx/y5y9yKIp3U9pR2Ncb3M5tGwX7isnbUcixZw7j9y+PJ2tEHzp1SWXMJcfw2Md3E9vA0B/GmNbFn2sKiao6u9pUfuCd9co4luzybVqpLD+914AWjqbppq1ex5yNNcc30iihpKOStB3i46Lp3CEZgBPOPYoTzj0qHGEaY1qAP2cKO0WkH6AAzjy11u2kmqwOdffZH9ghrYUj8c+q7TvrLHc7M/hecdYIkhLj6tzGGNO2+HOmcCvePuSHiUgesA64KiRRtVI3Dj6GLzasorDs4CB0w9K6ckavgWGMqnGHd6k7mXVLTuH+W0/ktOMOa+GIjDHh4k/vo7XAWGc+WJeq7gtdWK1T39SOTDr3Wt5YMY8N+wo4unMPrhg4jBhXZPc+OnlAH0b16cWP6zZWlXVITOClX15C747twxiZMaalNZoURKTOYSwqry2o6j+CHFOr1jM5ld9lnxLuMPziEuGFKy5g4qLlzN2YR/fUdlw6YggZKcnhDs0Y08KacqZQOdhPFnA0MNFZPpeDk4abVi42KoqLjzyCi488ItyhGGPCqNGkoKqPAIjIdOCoymYjEXkYaNLoWeId+3kukKeq54hIH+AdoBPewfWuVtUyEYkDXgdGALuAn6vqen9flDHGmObxp/dRBlBWbbnMKWuKO4Hl1ZYfA55U1f7AHuB6p/x6YI9T/qSznTHGmBbiT1J4HZgtIg+LyCPALODVxnYSkR7A2cB/nGUBxgCVc2G+BlzgPD/fWcZZf6rUujHCGGNM6PjT++gvIvI5cCLeexWuU9X5Tdj1KeA+Dl6b6AQUqGrljW+bge7O8+7AJqe+ChEpdLav0ZG++rj76enp5OTkNPVlRKSioqJW/xqMMW2Dv+NBuwEP3qTQ6IA+InIOsENVc0VktP/h1a36uPtZWVk6enTQDh0WOTk5tPbXYIxpG/wZEO9O4E0gDegM/FdEbm9kt+OB80RkPd4Ly2OAp4H2IlKZkHoAlWMs5AE9nfqigVS8F5yNMca0AH+uKVwPHKOqD6nqg8CxwA0N7aCqv1XVHqqaiXfwvG9U9UpgGnCxs9k1wCfO84nOMs76b1TVZuDyg7vCzcLpy1ny40o8rWB0VmNMZPGn+UjwNh9VcjtlzXE/8I6I/BmYD7zklL8EvCEia4Dd2Cisflk9fx0P//xpdubtBqDHgC488t6v6TGga5gjM8a0Fv4khVeAWSLykbN8AQc/zBulqjlAjvN8LTCyjm1KgEv8iMk4VJVHr3u+KiEAbF69jX/c/B/+8fUfwxiZMaY18af30T9E5Fu81wmg6b2PTAvYsDyPzat9h+5eOmM1Bfl7aZ9us6MZYxrnb++jBXiHy44GEJFeqrqx4V1MS0hMia+zPDomyibBMcY0mT+9j24HtgNTgEl4h7iYFKK4jJ8690zj6NOH+pSfculxJKYkhCEiY0xr5E/vozuBLFUdrKpDVXWIqvp+CpmweeCVmxl7xfHExMUQnxTHueNP5fanrw13WMaYVsSf5qNNQGGoAjGBS26fxG9evJF7J4zHRgcxxjSHP0lhLZAjIpOB0spCm08h8lhCMMY0lz9JYaPziHUexhhj2hh/uqQ+0tB6EXlGVRsb9sIYY0wE87dLakOOb3wTE2xbCvfy33kLWb97D8O6d+WK4UNJiY8Ld1jNUn302169eoU5GmMOTcFMCqaFbSoo5KLX3mZPcTEAU1b/xKRlK3nv6suIj2l9b2310W+zs7NtzCtjwqD1fXKYKq/MnleVECqt2JHPpOUruXjoYL+Pl1+ygoW7/8fe8jy6JAxleMcrSIzuGKxwjTGtQDCTgnV5aWGrd9Y9qviaesobkl+ykk823o5by6qWNxbN4KLMl4hx1X23tDGm7fHn5jUARCSxnlVPBxiL8dPgLp39Km/Iot3/q0oIlQrLN7N237RmxWaMaZ38GeZilIgsA1Y4y8NE5LnK9ar6avDDMw355cij6NYupUZZdo/unJk1wO9j7S3f6le5MaZt8udM4UngDJyZ0FR1IXBSKIIyTdM5OZlPrruKO084juEZXcju3JWxvftSWl7R+M61dEmoe8SSrvWUG2PaJr+uKajqplp3y7rr29a0EIXJc5azYVcBAAvXbuWT+ct4+8bLSIpr+j2Gwztezsb9P1JQdnDQ2/4pp9E9cUTQQzbGRC6/xj4SkVGAikgM3gHylocmLNNU/5u9qCohVFqzYxcf5i7h6lFHNfk4CdHtuaj3f1i771v2lW+hS8JQuic1fX9jTNvgT1K4Ce/F5O5AHvAVcGsogjJNt2LbjjrLl2/N9/tY0a44BqaeHmhIxphWzJ9hLnYCV4YwFtMMWRnpfLlktU/5wC5pYYjGGNPa+dP76G8i0k5EYkRkqojki8hVoQzONO7nI4fSo0PNqTb7pHXgohFHhCkiY0xr5k/z0emqep+IXAisB34GTAf+G4rATNN0SErg3Zuv4J3Zi1i9fSeHd+3MpUcPabXjHxljwsufpFC57dnAe6paaOP2R4b2iQncNPqYcIdhjGkD/EkKk0RkBVAM3Cwi6UBJaMIyxhgTDv5caH5ARP4GFKqqW0T2A+eHLjTjr9079/HRGz+yemkevfp15mdXj6JLDxvQzhjTdP4OiHcYkCki1fd7PYjxGD+oKl9tn0HOjjm4KzxseLeAws8qAGHB7LV8+8Ui/vn2zWR06xDuUI0xrUSTk4KIvAH0AxZw8E5mxZJC2Ly+/lPe3zzlYMHZ4IqJw/OJd1TTwj0HmPj2LG6458wwRWiMaW38OVPIBgapqk1+EgEOVJTw6ZZvfcpdo0vxfBEHpd5OAJvX72zhyIwxrZk/A+ItAbqEKhDjn4LyfZR6ynzKJRZo56laPnxojxaMyhjT2vmTFNKAZSLypYhMrHw0tIOI9BSRaSKyTESWisidTnlHEZkiIqudnx2cchGRf4rIGhFZJCI2+E49MuI7kRbb3qdc9wjs9L6tmf0zOOfn1lXVGNN0/jQfPdyM41cA96jqPBFJAXJFZApwLTBVVR8VkQeAB4D7gbOAAc7jGOB55+chq8zjZmdJEenxycS4oqrKo8TFjf0v4bHlr1Ch3qGyoyWKcfGnoFfH0rtfZ04+cwjxCU0fKdUYY/zpkvqtiPQGBqjq184MbFGN7LMV2Oo83yciy/EOqHc+MNrZ7DUgB29SOB943bluMVNE2otIV+c4h5x31s7jqWXT2F16gLS4JO4+YgwXZw6vWn9sp6G8kP1Hvt85H1BOSDuKzvEdwca0M8Y0kz+9j24AxgMd8fZC6g78Gzi1iftnAkcCs4CMah/024AM53l3YFO13TY7ZYdcUpiTv4EH50+uWt5Zup/f535Kv5Q0jux08DpB5/iO/KxHk94CY4xplD/NR7cCI/F+qKOqq0WkSZMBi0gy8AFwl6rurT48hqqqiPjVo0lExuNNUKSnp5OTk+PP7n4pKaugYF8xHlVSEuNISQz+mEJFRUU+r2HLgULuiOrvs+3yWfMoTFwT9BiMMQb8SwqlqlpW+YHu3MDW6Ie5MyHPB8CbqvqhU7y9sllIRLoClZMC5AE9q+3ewymrQVUnABMAsrKydPTo0X68jKablruah2BG11oAACAASURBVJ+fhNtz8GVedeYI7rz05KDWk5OTQ+3X8Nu5E/lgg++H/8+7HMUVR432KTfGmGDwp/fRtyLyOyBBRE4D3gM+bWgH8WaQl4DlqvqPaqsmAtc4z68BPqlW/gunF9KxeIfUCFvT0bMffF8jIQC8PWU++XuKQl73OT3rHvr6nJ6DQ163MebQ5U9SeADIBxYDNwKfAX9oZJ/jgauBMSKywHmMAx4FThOR1cBYZxnnmGuBNcCLwC1+xBdU5RVuNmzb41PudntYt3V3yOs/PqMv9w8ZS1K0t/dQSkwcvxt6OsekZ4a8bmPMocuf3kcevB/UL/qxz/dAfeNr+1wddXodRcQUnzHRUfTp2tEnAURHuejbrWUGmbt+4HFc1ncEefsL6JHUnsRo615qjAmtRpOCiCymgWsHqjo0qBFFkNsuOZH7nv0Ut/vgHcJXnZlNWvvkgI67dFkeW7YWMHhQd7p19b0Brbqk6FgGpjbpen7AFi/P46PP5lNQeIBjR/TlgnHDiY3xd8xEY0xr1pT/+HOcn5Xf4N9wfl5FEy40t2YnDe/H63+8kk+/X8KBkjJOGTGAE4b1bfbxSkrK+cNDH5A7fwMAInDlZcfRr0+wIm6+mblr+e2fPqy6hjJ3wQZyF27gsQcvCnNkxpiW1GhSUNUNACJymqoeWW3V/SIyD++1hjZrYK907rnilKAc680PZ/L9tvVEdYDYPYIq/PftGdx/d/hH83j17R99LqrPmLuW5au3cviAri0SQ/Wuxr169WqROo0xNflzoVlE5PhqC6P83P+Q9tnG5TxW8T07zvCw9XwP209344nxfgjv318a5uhg0xbfi+oAmzaH/qJ6JVWdoKrZqpqdnp7eYvUaYw7y50P9euA5EVkvIuuB54BfhiSqNmZXyX7u/nEiFdEHv4mXdIOCI73LUdHhz62DsnzPBkTg8Kxuje67Na/uhGKMaX386X2UCwwTkVRnubD6ehG5RlVfC3J8bcL0rWsp87h9yg/0VvqsTKBdSkIYoqpp/NUnsnTFFoqqnbVccl42PRuYtW1vYTH/7w8fMG/W2pYI0RjTAvzuWlI7GVRzJ97B7UwtSfV0JU2KjuXJxy9nw/qlIau7YFcRK+atJ6NHR/ocXv+3/gF9M/jvc9fz5bSl7Ck8wHHZfTlySMPt+s8+8bklBGPamGD2N6zvfoRD3snd+tE1sR1bD+ytUX7XqJPpk5nOhvWhqffjl3J46f9NpKLMe5Yy8tRB/O7564irZzjtjh2SuPxnI5t0bI9H+f6b5UGL1RgTGYKZFNp099RAxEVF88aYy3lk7ld8v20dHeMTuS5rJNcMzPbZtqSknBk/rKK4uIxjjxtAx07Nuydi4+ptTHjkY6rPnjp76jI+eGEaV9x1RrNfS3WuKBeUexNOdHD/llicV0jmA5NrlK1/9OxgVuFz/FDUYUxrY2cKLaRvu068NuZy3B4PUa66LyyvW7uD++5+iz279wMQExPFfb87l1NOrX+8I1U36tmDuDoicvC4s75eWiMhVJo5ZXFQkoLLJYw9ayiTP8oFILPmQIbGmFYqmN1efgjisdqs+hICwDNPfVmVEADKy9089ffPKS72nYsZoHT/O+zdPpK9249k745RlBUfnB01KSW+zn2SU4N3UfvGX5/OsDMHkpS5n1TvPBvGmFauyUnBmQXtDhH5hzOP8j9F5J+V61X1ttCEeGioqHCzaMFGn/L9RaWsWLbFp7y8dAbFhb9BPd5Rx9Wdx4E9t1NRvgSAk849knYdknz2O/vqEwIP1uOBoiI2btrMj/s3MWbLosCPaYyJCP6cKXwGZOIdJTW32sMEQVSUi/btE+tc1ynN97pC2YF369jSQ/mBDwBITk3kr+/cyvATBhIV7aJbZhp3PX45x581LPBgVeGJJ+h/WH9++Md93P7DF4Ef0xgTEfy5phCvqneHLJJDnIhw8c+P4T8vTKtRfsxx/enVO62OPSrqPI5qedXzvoO689e3QzDobFQUPPwwz5TGcemzf6PrvoLg12GMCQt/ksIbzjzNk4CqO5xUteXGQWjjLrtyFIlJcUz+dD4lB8o44aTDuOraupt7YhPOpbz44zrKz6lj69DIOHccb/34I/dMn9RidZrmsZ5Wpqn8SQplwOPA7znY/VSB5g8banycd8EIzrtgRKPbxcSfTlzyrykteg4oBUkiPuVuouOODX2QjotGHsGmvNUUR8ewu6I8v8UqNsaEjD9J4R6gv6ruDFUwpmlmTVvOR698x+585ZhT/szF1/ehXYdBiCulReOI2b6NvomxrJj0BevOPNX3KrkxptXxJymsAQ6EKhDTND9OWcqfb3uj6h6ETT/tYN4P23nmo6Nb/kaRigqYNYvDEsI/dpMxJjj8SQr7gQUiMo2a1xTuCHpUpl4fvPStz01pa5dvIfe7VRx98mEtG0zv3i1bnzEm5PxJCh87DxNG+Vvr7umTv7W+cQqNMabp/Bk620ZAjQBDj+nH1I/n1SgTEYYd2y9MEUWeunrahLqOpvbksV5AJtI1OSmIyDrqGPROVa33UQu65tdnsDR3Pds2HewJfOVtp9I9s657GYwxxj/+NB9VH9IzHrgEG++mxaV3bc8Ln9/DjClL2Z2/l6NOGEjv/hnhDssY00b403y0q1bRUyKSCzwY3JBMY2Jjozn57CAMV2GMMbX403x0VLVFF94zh6COoW+MMSa8/PlQ/zsHrylUAOvxNiEZY4xpI/xJCmcBF+EdKbVyv8uA/wtyTBGjqGA/Py1cT7d+XUjv0Snc4Zg6BLunUTCP1xKxBdJzqSV6aZnWx9/7FAqAeUBJaMKJHB8+PZmXf/cWpcVluKJcnPXLMdzx/A24GpgkxxhjWjt/kkIPVT0zZJFEkFW5P/H8r1+tWva4PUx+8WsGHt2fcb86NXyBhdC+8r3sdxeREdcVEWHbnn1UuN30SGvf6L5uz/5GtzHGtA7+JIUfRWSIqi4OWTQR4rsPZtVTPqPNJYVyTxn/3fAyc3bPwIOHjjFp5M/PYva8YgAG98rgsWvG0bOe5LCt8F9s2/tsS4ZsjAkhf9pCTgByRWSliCwSkcUi0ibnYYxPjKuzPK6e8tZs8taPmbX7Bzx4ANhdvhMdMBNXtBuApRu3c+8rdbc9FxyYwpbCv+FRO1Mwpq3wJymcBQwATgfOBc5xfrY5p151IrHxMT7l4341NgzRhNbs3T/6lEXHuWnffW/V8orNO1i33XcupT0HbCgsY9oaqT3iZmsjIvuAleGOI0BpQGufpyJLVQOa0EFExgPjK49HZL6vkfxehSq23qqaHoLjmgjUFpLCXFXNbnzLyGWvofWI5NcZybGZ1sP6VxpjjKliScEYY0yVtpAUJoQ7gCCw19B6RPLrjOTYTCvR6q8pGGOMCZ62cKZgjDEmSCwpGGOMqWJJwRhzyBGRTBFZEsb6rxWRf4Wr/oZYUjDGmDZGRJo9AZolBWNM2Djf2JeLyIsislREvhKRBBHJEZFsZ5s0EVnvPL9WRD4WkSkisl5EbhORu0VkvojMFJF6540XkREislBEFgK3ViuPEpHHRWSOM67bjU75aCeO90VkhYi8KSLirHtURJY52z/hlKWLyAfOceaIyPFN/B2cKyKznNfwtYhkiIhLRFaLSLqzjUtE1jh11FmPiDwsIm+IyA/AGyIyWERmi8gCJ84BTYnHkoIxJtwGAM+q6mC8c7Zc1Mj2RwA/A44G/gIcUNUjgRnALxrY7xXgdlWtPcH59UChqh7tHPMGEenjrDsSuAsYBPQFjheRTsCFwGBVHQr82dn2aeBJ5zgXAf9p5HVU+h441nkN7wD3qaoH+C9wpbPNWGChquY3Us8gYKyqXg7cBDytqsPxTp+8uSnB2BzLxphwW6eqC5znuXhnd2zINFXdB+wTkULgU6d8MTC0rh1EpD3QXlWnO0Vv4B3kE7yDfA4VkYud5VS8iaoMmK2qm51jLHBim4l3orGXRGQSMMnZbywwyDmZAGgnIsmqWtTI6+kB/E9EugKxwDqn/GXgE+Ap4Jd4k1q99TjPJ6pqsfN8BvB7EekBfKiqqxuJA7AzBWNM+JVWe+7G+2W1goOfT/ENbO+ptuyheV90Be8ZxHDn0UdVv6ovNlWtAEYC7+MdLfoLZ70L7zf+yuN0b0JCAHgG+JeqDgFuxHm9qroJ2C4iY5z6Pm9CPVXj2KvqW8B5QDHwmXOcRllSMMZEovXACOf5xQ1s1ySqWgAUiMgJTtGV1VZ/CdwsIjEAIjJQRJLqO5bzrTxVVT8Dfg1UNkd9BdxebbvhTQwvFchznl9Ta91/8DYjvaeqbn/qEZG+wFpV/SfeM446z6Jqi7ik4Fw8WuxcHJkb7niMMWHxBN4P6vl4hwQPhuuAZ51mIKlW/h9gGTDP6ab6Ag2fcaQAk5xJxr4H7nbK7wCynYu6y/C26TfFw8B7IpKL79DnE4FkDjYd+VPPpcAS5/UeAbzelGAibpgLp5dBtqpG6pj1xhjTIpweWE+q6oktVaddaDbGmAgkIg8AN1OzqSv09UbgmcI6YA+gwAuqaiM/GmOaTESeBWrfI/C0qr5S1/YhjuU64M5axT+o6q11bR8JIjEpdFfVPBHpDEzB2ytgeq1tqqZtjIuPG9G9ZxcAoiWWmk2FgSkpq6izPDYmCpf41lPqduNRj095jCuKaJeLsnI3Hk8d66NdREVFBR5wNe4KDxXlvvGLy0VsXPBPEFetWrUz0Ckbq7+vCQkJI3r27BmU2Dwepby0vK4a0Tqvqkmdf0ZRLiHKJbhcEXcpDgCPx+MTm1uVMncdfwcixEfV/Xfg0Qo8uKuW167eEPB7WyktLU0zMzODcSgToNzc3Drf14hLCtWJyMNAkao+Ud82/QZm6o0fH05GfH+u6ftMUOv/9VMf8f2idTXKOqQkMOmJG4iN8f2H+veSWTyam+NTPvncaxncMYP/vTeLf7/ou/6Be0ZwxhljgxU2ABtXb+OmUx+l9vt79T3juOKuM4JaF4CI5AZzKsjs7GydOzc4/QzKSsq5euRD7N2zv0b5sacdQWFaCvMXbKhRntg5gR2xvh+kf7lxHLHF2xg9enRQ4gq2nJwcn9gKS0s49v3nKK6omRQv6T+Ex48fV+dxthav5I11d1Ut3z/4i6C9t8F8X01g6vufjaivPCKSJCIplc/x3lTS6KBV7WI6M67b3Y1t5rf7rjqVPl0P3jXfLimOP40fV2dCALju8BGc3vPgneQxLhf3H3UygztmAHDh+SM48fiBVeujo13c8MuTiQvBN/deA7pww4MXEB178Azk6DGDuOjGU4JeV6SLjY/hvmd+QXJqYlVZ74FduPlPF3HPnWfQo3uHqvLU1AT+330XcvlpR1WdDYrAhScP4bSRWS0ee6BS4+L5+/HjSIqOrSob1qkrD4wYXe8+XROyODH9F7gI7tmraR0i6kzB6Vf7kbMYDbylqn9paJ+BWQN0xYoVuCQ0f8CqyoLVeRwoKWPEYT2Jj41pdJ+Ve/LZsK+AI9O7kZ7g29153bp88rYWMOiwrnTsmFznN7xgKdi5jxXz1pPRsyN9Du8ekjogss8UKpUUl7FoxmoSk+IZPLIvlXeEejzKosWbKCurYPiwXsTGepP0lp2FrN6UT99uneiZ4U0coXyvAtVQbPvKSpm9fRMd4hM4Kr1pfwdF5bvZWrKSge1G2ZlCG1Tf/2zIeh+JSD9gs6qWishovDdOvO7cRFInVV3LwRtBmlYPrpAlBPC2vR45sIdf+2R1SCerQ/1NsH36pNOnT1CaaBvVPi2FY08f0iJ1Rbr4hFhGjhnsU+5yCcOH9fIp75aWSre01JYILeRSYuM4tWd/v/ZJjunIgJjjQhSRiVShbD76AHCLSH+8c8f2BN4KYX3GmAgkIuNFZK6IzM3Pzw93OKYRoUwKHmeMkAuBZ1T1N0DXENZnjIlAqjpBVbNVNTs9vWXOkE3zhTIplIvI5XjH8qgcRbDxBnljjDFhE8qkcB1wHPAXVV3njE/+RgjrM8YYE6CQXGgWkSjg96padXu2qq4DHgtFfcYYY4IjJGcKzhCvvUUkttGNjTHGRIxQDoi3FvhBRCZSc+KHf4SwTmOMMQEIZVL4yXm48I4/bowxJsKFLCmo6iMAIpKoqgdCVY8xxpjgCVnvIxE5zpkVaIWzPExEngtVfcYYYwIXyi6pTwFnALsAVHUhcFII6zPGGBOgkI6SqqqbahW569zQGGNMRAjlheZNIjIKUBGJwTv70PIQ1meMMSZAoTxTuAm4FegO5AHDnWVjjDERKpRnClr9jmZjjDGRL5RnCjNF5D0ROUukjgmNGyAiUSIyX0QmNb61McaYYAnlmcJAYCzwS+AZEXkXeFVVVzVh38rrD+2aUlHegZ38a/XHzN69kvYxSVzc8yQu7z2m2YE3V7nHzd/nfM/bKxZRXF7O6ZkDeGjUGNITk1i/bzePzJ3C99vW0ik+iV9mjWT8oGNr7F9R4eaV/3zLZ5/Op6SknBNOyuKW20+jQ8fkkMeuqrz5/ize/zSXwr3FHDOiL3fcMIZuXdrX2O7Tl3J4/19fsXPLHoYcP5Ab/3wpfQaFbka3QO3dW8xzz0xh+rTlxMRGccZZw/jVjadQQgV/mvc1kzcsAw903BKL6/syBvTO4MZrTmLkkX3CHXrIrF2ymQl/fI/FP64irXsHLr3jTM6+tmbHwI/WzeW51RMpj9pfz1FMWxXKm9cUmAJMEZFTgP8Ct4jIQuABVZ1R134i0gM4G/gL0KSJl+9d8ALbSnYDsLtsHxN+mkysK4aLep4YhFfSdI/P/o4Ji+ZULU9au4LNRYW8e+7lXP3N2+TtLwRgR3ERjy74hvioaH6RdXA2vJcm5PDeOzOrlqdNXca2bYU88/y1IY/9fx/PZcIb31Ut/zjnJzZs2sUbz19PdJT3hHLquzN57oF3qrZZ+N1KfnfxU7w8+08hj6+5/vTQh8zPXQ9AWVkFH743m/LyChYcWci3W9dWbbelawWJRwmr5+zgt3/6iJeevobMnp3CFHXo7N9bzG8vfoq9u4oA2LFpN//6zVskpSYw+sKjAVhZsJWnfnoHV7Ti1ym+aRNCefNaJxG5U0TmAvcCtwNpwD00PAPbU8B9gKcp9XhUqxJCdZ/m1ZlzQsajytvLF/qUL9ixlddX5lYlhOreXDPv4P4eZfKn8322Wb40jzWrtwU32Dp88sUCn7K8bQXMXbC+avmzV6f7bFOQv4/vJ/nGHQnyNu+uSgjVTfpuYY2EUOlApuKJUsor3Hz29eIWiLDlfT9xXlVCqG7yKwff23+vmILLFTlzt5uWJd4v9CE4sMgqvPMnvKKqm2utu19VfYbRFpFzgHGqeoszr/O9qnpOHduNB8YDpKenj/jzS75j7EW7ouib1LITvS3ZuZ26fpudE5PIL/H9R4xxuchq35mioiKSk5NZvWobdb0dPXt1JCEhtAPO/rQunwq3bx7u1iWVlOR4ADau3EppSbnPNp27d+CCS84LeHL36u9rRkbGiHfeeaeRPRpWWlrOhvW7fMo1Gso71L1PTIGAB9qnJpCR7tt6WfleRaKmxFaQv4/8LXt8yuMSYuk1sAsAG4p2UqolVetuPO/qgN/bStnZ2Tp37txgHMoESETqfF9DeU0hS+vJOHUlBMfxwHkiMg6IB9qJyH9V9apa+0/AO+8zWVlZ+kHKYso8FTUOdH73UYzOGh3gS/DPf7/4kK83/lSjLC0hkUlnjWP0p89R5ql5794vBo7gxuzR5OTkMHr0aKZ+8S4zflxdY5sOHZN4671LiImJCmnsc5Z8yadfLapRFhcbzYevnl+VFF778RM+fPLzGtu4XMLLc4LTfFT9fc3OztbRo0cHdDyPR7n6smfZvq3mWdrwo3qTO2YfG4pqfjjG5gudp3r/Jf720EUcO6KvzzEr36tI1JTYtqzdwQ23PYTHU/Nf86r7zqnad/LGBTyxxubDOlSFsvdRmog8LiKficg3lY+GdlDV36pqD1XNBC4DvqmdEOpy/+GXkRgVV7U8tH1fftV3XKDx++3/ThjLYR3TqpY7xifwz1PPpUtSCo8few5J0Qe/7Y/s3JO7h55cY//bf30mffp2rlpOTU3k9w9eEPKEAHDjNScx5PCDF4wTE2L5/d3jqhICwM/vOovsMYOrluMSYrj9iSvJ6JVGJHK5hN8/eAEdOyZVlfXs1Ym7f3M2T406n4yEg9+qo/dBh9lRRLmEyy88us6E0BZ069uZWx67nLiEgzPjjjx9CBffdnrV8tm9hjMkYUidZ63mEKCqIXkAXwHX4+1FdDLwMvCYH/uPBiY1tt3AgQNVVXV/ebHO2rlcV+3dpOHk8Xg0d1ueTt+0TovLy2us21dWojl5a3TJrq01yqdNm1Zj/6VLNuvcOWu1tLTm/i1hxZptOnPuWt1/oLTebdYt26yzpyzWvXuKqsqAuRrEv58RI0YE7TWVlVVo7ty1unjRRvV4PAfL3RX6w9Z1Omv7Bt28dY/+OOcn3Z6/t8FjVX+vIo0/se3dU6SzpyzW9cvz6t1mTeE2fWHZ1KC+t8F8X01g6ntfQ9l81ElVXxKRO1X1W+BbEZnT6F4OVc0Bcpq6fWJ0PCM7HeZ/lEEmIhyV0a3OdckxcZzcrV+j+w8aHL4unln9MhrdJvPw7mQeHrndUGuLiYniqBG+XUxjXFGM6pJZtdy9VvfbtiylfRJHjz2iwW36tcugX7sMbmyhmExkCGVSqLwiuVVEzga2AB1DWJ8xxpD5wGSfsvWPnh2GSFqnUCaFP4tIKt4uqM/gvRHt1yGszxhjTIBCefNa5RAVhcApoarHGGNM8AQ9KYjIM1Bnd30AVPWOYNdpjDEmOEJxpmB3phhjTCsV9KSgqq81ZTsReUZVbw92/cYYY5ovlBeaG3N8GOs2xrSQ6sOX9OrVK8zRBEftHk5tqXdTSOdoNsYYVZ2gqtmqmp2enh7ucEwjLCkYY4ypEs6kYEO1G2NMhAl5UhCRxHpWPR3quo0xxvgnlJPsjBKRZcAKZ3mYiDxXuV5VXw1V3cYYY5onlGcKTwJnALsAVHUhcFKDexhjjAmrkDYfqeqmWkXuOjc0xhgTEUJ5n8ImERkFqIjEAHfinVvBGGNMhArlmcJNwK1AdyAPGO4s10tE4kVktogsFJGlIvJICOOrUuGJzBMY1Ybjcle4ne28U5FWzrFcWe4vjx6co9njUZ8pG+ujIZiiy99jqiruOuaY9q6r8Cmrb9vmcLs9jcbrz+8zkpS5S8MdgmlhoRwldSdwpZ+7lQJjVLXIObv4XkQ+V9WZwY8QJufN48U1U9lSvIfD23XnzsPGcVRH38lYWpKqsqLgFVYXvEWpp4DOCSM5Ku0+UmIzq7Z5d0IOH73yHQOPWM4vbl1Gp8672FiQwZPfjWLxmj4kzd9L/4R2XHPbWE46Y0ij9X2+7RO+2fEV+yuKGJg8iIJlA/nixzzcbuW04QN44KJTSE2K99m3osLNRx8/Rvtebwf710Bx+WI+XHYcg9Ke4bDO9c8Z765w8/pTX/HZO7M4UFTCyFMO55YHzye9a3vKS7+nZO9fcJcvwRWVSXzKPezaczLPPvE5c2f8RFJyHOddcjRX3zAal8v/HtL52wp49v9NYvZ3q0hMjGXcpSO55tZTiYo+OH3q3uIS/jo5h8+XrMIlwrnDDuP+caNJjI1p4MjhN2PH5yzZ/TTtY/LDHYppYaHsffQ3EWknIjEiMlVE8kWkwfmWnVniipzFGOcRkq9XM3eu5pHF77Ol2Dt5+/K9edyV+yrbiwtCUV2TrSl8hyW7n6XUswdQdhTP4tstt+DWMgAmvTmDV574nE6d13Png9/TqfMuAHq1385j4ybSucsu8kemsG53AY/e/y5L529osL6pO75g4pYPKKrYh6KsLFrKxo6TKS0vp9zt5rPcFdz/+md17vvu2/+mz4gX6NSlMKi/g0qZyXlsLLy2wW3e/NfXvDshh6K9xXg8ysypy3jwhleoKF/H/l3X4i5fAoDHvZ4DBXfw8jOPMvuHNXg8yr69Jbz50ne8/cp3fsemqvzx1jeYmbMCj9tD0b4S3n1pOm88X3Ma8gfe/4JPFiynrMJNSXkF781dwkMff+13fS1p8/61rC18yBLCISqUzUenq+pe4BxgPdAf+E1jO4lIlIgsAHYAU1R1ViiC+3jTbJ+yEnc5n21ZEIrqmmzt3g99yord29m2/3sAPnvH++sYc/ZPuKJq5svYKDfjDlsKLmF/rzg8HuXzDxoetPa7/Gk+ZXHJZbTvfvCDfsaKDeTtqvnBr6qUuD7xiSHY0uL28s2a1+tdX/n7qG79qm1sWfsy3hPP6pShQ33f98kfzfM7ruULN7F+9Xaf8s/fPzjj7Pa9RXy7ap3PNl8uWcXe4hK/62wp07e/TqwrNE2qi/MKyXxgco2HiSwSivZgABFZoqpHiMh/gPdV9QsRWaiqw5q4f3vgI+B2VV1Sa13VAFvp6ekj3n33Xb/j23RgF/srfP8xO8WlkB7Xzu/jBaKoqIjk5GQACsvW4NFyn22SYroR60pl/aptlJe5yehWRFJKmc92BcUJbCtqh6vUQ3Sxh+R28XTtUf8sqHnFm3DX0eZeUhRHRenB1sV+XToSF1OztXHXnpUkJHljOPuMO3JVtf52niao/r527tx+xCtv/B8A5Z4MUuM717nPT8u21NlW37u/h6go37O+A/tj2bat5vvrcrnoN7Dxuanh4Ht1YH8peRt21fUa6H94VwDKKtys3uG7DUBWlzSiXcH9Tlb97ygQu0o342Jf1fLPzrwl4Pe2UlzXAdr1mqdqlAV7MLmWmI6zLQyIJyJ1vq+h7H00SURWAMXAzSKSDjT565GqFojINOBMYEmtdROACQBZWVk6evRov4P7YOMsnln2iU/5K8fczOD2Pf0+XiBycnKofA3zd85hTeE7Nda7JJaTe39G3IYMMAAAHelJREFUXFQHXpwxiQ9f+Y5jT9nAnQ/94HOsuz79GbM3ZZI+cy8JO8q5768XM3r08Hrrfnvja3yXX7PJw10hzJs2hIoy759Hr/T2TLzqEkRqtru/+OLnjBgRvOsJ1d/X/9/emcdHUWWL/3t6yUbYE0DCLgFFZJGMCOiIC+owOuoI6u/pPBdccGMYdcZtnFGfjvNGHfd9Ax0cRVye+nCXgOyymQDCAyTse8i+dbrP74+qJJ10Z0+lO3C/n09/uurWXU71ra5T99xb5wwZFqM9jnuMYr+XYT1X0T62Y9gyyz75N+mf/VgtLbFjPDO/m0BZ/uUh+V996Sy+/mJAtbRzLxjB+BvGN0jGir4qLfFx5YR/kJ9bXO346eedyHU3VdX17DMz2bI/u1qe4b2P4Zb/OLNB7TWG4OuoOaw59D2bcqY3XyBDm8Qx85Gq3g2MBdJU1QcUAhfWVUZEku0RAiISD0zAfiO6pbmo9y84P+UkxHbBFOPycOug81pdIdRkaJeb6BY/unLf60pkdLf/ItbdGYArbpvASaemsnReH774YBB+vyW/z+9ixorRLN/Wlw6biml3sJzzLz2ZMybWPTC7KGUyg9sPqdyPlXjyMqsUQo9O7fnHVRNDFALAxRfex/qlaQT8zrixKvJ7ySu7vVaFAHDjfRcweHhVn3Xo3I57n7qChPbjiGt/JxBjH3ERk3AFp597D+07xFfmP2F4b66/7exGyxYb5+Wexy6jY+cqLy6Dh/Zi6l3VnxgfmzyRlE5VI5N+SZ3522/PaXR7rcmIrqdRLhdRHjD+Mo9GHDMfgeXqAuhH0IhEVWs1EIvIMGAm4MZSWLNV9aG62hg8eLBu3LixyTLuKspmR9EhBnc4hs4xzR96N4VwT3i5pZso8WfTNW4YHld8SJltm/aSvT+fwcM8eL3bOVTcmy0H3SR7Y8nfnU/v/sl0O6ZTg2XYVbyDPF8uxyam4pUYMrL2UO4PMLx/Tzzuum8OG35axfFDRrWYiQFg0NC+unJlRp0KIZjN63ZRkFfMkFH9iImpGgAH/Afx+9bh9hyLy9MLgNISH+szdtChUwLHDurRKLlq9lVZWTnrV2+jXft4Uof0DFvGHwiwevtu3C4Xw3sd06SVTk2RrbnsL97D+pxFnNFzsjEf1dOGMR81rMG3gWOBNVS9yaxArUpBVTOAkU7JFI6UhC6kJNRuc48UHWNTqet22De1B31TK25o/ekRBz0627v9GnejA0iJ701KfNUT9/D+4W9w4Tju+JMa3V59dIhLbrBCABh4QkrYdJc7CZf79GppsXFeRp48IGz+xhIT42HE6GPrzON2uUjr16tF2mtNusUfQ7f4SZEWw9DKODmnkAYMUSeHIgaDwWBoUZw0Gq4FGv/IajAYDIaI4eRIIQlYLyLLCVowrqq/cbBNg8FgMDQDJ5XCAw7WbTAYDAYHcNL30XwR6Qukquo3dgQ2d33lDAaDwRA5nPR9dD0wB3jZTkoBPnaqPYPBYDA0Hycnmm8BxgF5AKq6CQjvq8BgMBgMUYGTcwqlqlpW8SasiHhwyOOpwWAwHEm0xgt4teHkSGG+iNwLxIvIBOB94FMH2zMYDAZDM3FSKdwNHAAygRuBucCfHWzPYDAYDM3EydVHAeBV+2MwGAyGNkCLKwURyaSOuQNVHdbSbRoMBoOhZXBipHC+/X2L/f22/X0lZqLZYDAYopoWVwqqug1ARCaoarDH07tEZBXWXIPBYDhKCI6o5+6QHGFpjk4aE/bUyYlmEZFxQTtjHW7PEEE8zi5vbh4HD0ZagqMaVX1FVdNUNc2d0HB36IbI4ORNegrwgohkiUgW8AJwbV0FRKS3iMwTkfUisk5Efu+gfK1Kmd9PoIlexEv8VsxmVaXUFxpP2a9+inw1g9RXoepDtWGB2Et8Pnz+Esr9Acr9gQbL2A8iG7KuFlQV/623Nbue8kAAXyD0N/QFyvFrw3+nKrkC+ANlBFQp8zesb5pDxfVX5isPG9O6NnIK9zsolSEacXL10UpguIh0tPdzg4+LyFWqOrNGsXLgDlVdJSLtgZUi8rWqrq+tnYCWsO7AvQzuei8eV2Qip9XF9twc7p//Ld9vzyIxJpYrhw7njlPG4W5A0PYvd/3EE2u/I6sgmyR3Ip6NHgqyyjm+TzfumHQ6g/t35d4Vr7GldBOK4ipI4o4hVzC+/0AANJCN5j0IJV8DHjT+QqT9PYgrIaStNTv3MOPH5+jVcwXtE0o4sL8TK78YxrCUMdxx1Zl0aBcXVsa5qzfwwb8+pCNEXaSi2Usy+N/3PmHme+8ybWAaV117GaMGNC7YTVF5GY/8+BWfbM8koAHujj2Bw6VFBCjjxc2z+SF7LbHuGCZ0H8PV/S/E66r7L6WqrDr0FpmH51AayGP3oWS+Wn0ixyedyF/POZO+nRseLa8h7Dicy4Nzv2PhlizcCO7sAN1LYrl0wkiu++2YsGFWAb7NfIQTO80iyRv6EGI4snHcnKOquTUVgk3IKEBV96jqKns7H/gJy2dSXS2wu+Aj1h+8vwWkbVn8gQBXffIhC7ZnoUB+WSkvrlrOsz8srbds5uHdTF/2AVkFVtD3g/4C9g7IwZ/o56ft+7nt+Y+5+4cX+dn3f4hLcbmADgd5KOM1duXmAaA506HkcyxdWwLF76H5odFNs4uK+a/vnuH4gQtpn1ACQHK3HM68fBELflzDgy99Ub1AIAAFBazO3MgDMz9mxLLvm/ErtTC2bPOXZ/DYu3NJW7EIgNT0b/jDi+9xYNdeKCiw8jWAv6yey/tZqykNlOPTALm+Ym5f/hEPrXuZZdmZBFCK/aV8sjudmVmf1Ftf5uE5rDj0BqUBq496dj3AJeMWs3jbz0yZ/RH+BsrVEAKqXP/OR3y/xbr+ylFKuwj7Y0t5/aOlvPP5yrDl1u2cx2lJM41COEqJpI2/zkC1ItIPKzTnsoZUtr/wa3z+nOZL1YIs3bWDrNzDIenvrs+st+ycrWvw1zQ3uaC8p/VHLaWErb6tIeUSOhcye+1qtHw7lIVRPsWfooGiaklz125kUJ/NIVljYvz0H7qLxWt+5sDhgqoDqvD44wwbMYTlT9/DbYu+CCkbMWzZTh0zkh+eqZLttkVfsODxO+napxc88YSVrx4KfKXM3bEuJH1l9kZ+LtwZkv7V3iXUF2hwQ+5nIWnt40sY0GMv2w7nsHT7jnrlaijLs3ay9VDo9Vdqm/X/57vw1+HBw//E40wYaUMbIJKTg7X+e0QkEfgAmK6qeWGOV65mSE5OomTTXQAs3LYCiaL5zvyyUm7vHmqucIuL9PT0yv2CgoJq+wCDinxMcw8MKSspgqurC1yKN6972HYTyWX+9+vBPy28YJ4lBHsxjyss4kQ9j5is0CfD8T3iOfnMWNasXIbXE+T5fPx4Dgw6jk779uIN+OHOO8O31QiC+7V79+4hv0mDGT+evQMH0/XAPks2G5/LTWHPFDp1T4bv6x/d+DXAza7qsZy7E8tUjiMmN3QeQID58+fXWaen9HS6MjYk/ZLEdhT3iyF74wbSs0KVfUOoeR0VlJYxLTXcQFtx9wePxx32Ny4s+Q0L9gXPUTV/TsbQdojkHTTss4iIeLEUwixV/TBcHlV9BXgFIHVQH41LfY6OscM5uect4bJHjCKfjzEzXiavtPok8OTjT+Dm8eMr99PT0xkftA/wze6NPLhkdkidcRlxeA55EIHjLs8hT7KrHS8piOHJkX/ihO7d0IP/BH9W9QpiTsHV5dZqSVmHDnPP1/czfmT1J0dV+OilM0hOGMDUa84KkWXu6g1kvPxH7lgQ+vTbFIL7NS0tTWv+Jo1h1sLVZLz6TjXZHj/9An7z7zcYdExSg+t5c/5bLD+4rXJ/mnsgn8UfpluH3Rz2VX9eGdt1BFOG1C3zkv3ryDhcvV99fhevfHEuHunAwt9eTEKMt8HyBVPzOir2+Tj9yVfJLal+/cXkKu32waXnjAy57gAWbtzC2I7PNEkGQ9snkuajRTUTxJr1eh34SVX/2dCK2nmP5YTkR1tSthYhwevluXPPp2t8fGXa6J69uHfc6fWWPbvnYK4fNBavWF3kUiFmawyeQx7iYjz86dIzeHTUTcQGqibXfcVeLuj8a4b26I6IIJ2eAnfQSMUzGOnwt5C2+nXtzMWDrmPj9r6VVpUyn5slnw+jvbsPD908MayMvxoxmMv2/Uyxx0u25ecqarhszHAm7dlCscfLe8PHUuLxclX29kYpBIC/jbqAQUFr62Ncbp48+RLuPn4KXWKqllcOat+XqQMn11tfWtI19G43unK/uMzL3BVpxHs68fSFE5usEMIR7/Xy1KRf07Vd1cICT5ESfwBOObEvN04eF7bcqYOnkL5vGOXmVdOjEsdGCiLSCfhPoF9wO6o6zf6+NUyxccDvgEwRWWOn3auqc2trxyWxjEn5tNZVFJHmtD79WHz1jazeu4dOcXEM7trwm9IfTzyLq1NHsyXvIAM7JFFWGGDXwVyO651M+wRrNdD7v/wbS/b9xJ68fM7qPYxOQQpIvEMg6WvwZYB4Ee/QWtu69KQRTCx9lVW71tEhoQBXQS/OuCCeIQN64HKF/21l9256xbg5tGAhW8eO3t7gE2sFPHv30DfOw/70BfTvnkJ5zn6Sr70Gdu+Gnj0bXE+fxM58NmEqmYd3Ux4IkJu5meM79QDgjZMfZENeFgnuWPonNmxVk9eVwMRe/yCnbDtF5dnkFSQzdrwyvGcPYj0t/3ccO6Av6dOvI2PnHuI8XsryyujSsR39eta9WOzM4XPYcXADG/e8D/ylxeUyRC9Omo/mAkuxvKQ2aEmFqi6kngnoUFxRqxAqiHG7GZ3SuKWQFSTHJZIcZ48G4qBn1w7VjosIY3sMgR7hy4u4IWZk+IM1SIyN5ZcDTmq4cOXlsGxZtZFQ1GDL1i0+3o7s1BuWLYMDTRvQnNjZUiTpVE3Iu8XNCR2PbVJ9nWL60CmmDz1DVwe3ODFuN2l97euvnrV8wfROOo7eSfdjlMLRhZNKIU5Vb3ewfkOk6ds30hLUTjjZ4uOhT5/Wl8VgaEM4OafwtohcLyLHiEiXio+D7RkMBoOhmTg5UigDHgPuo2r5qQIDai1hMBgMhojipFK4AxioqsYbmcFgMLQRnDQfbQaK6s1lMBgMhqjByZFCIbBGROYBlW/PVCxJNRgMBkP04aRS+Nj+GAwGg6GN4KTr7JpusQ0Gg8EQ5Tj5RvNWwji9U1Wz+shgMBiiFCfNR2lB23HAZKIwEIvBYDAYqnBs9ZGqHgr67FLVp4BfO9WewWAwGJqPk+ajYCc6LqyRQ/QEOzAYDAZDCE7epJ+gak6hHMjCMiEZDAaDIUpxUin8CriE6q6zLwdCgwQbDAaDISpw+j2FHGAVUOJgOwaDwWBoIZxUCr1U9bzGFhKRN4Dzgf2qWntUmFYiP7cQ8bpJtIPaNIbi8jI8Ljdel7vevEU+Hwne5kfdCmiAwuJ8Yt0JxMSG1qeqqBYi0q7RcSh8AR8KxLhaLjpYXfj9fsqKy4hPjMJ4DRHAV1ZOwB8gNj7GsTZUlaLiMhLiYxARNuVscKwtQ3TipFJYLCInqmpm/VmrMQN4Dnir5UVqOCu//pGHH/6A/R3iIdbLMR3ieeie3zIk9Zh6y+4szOahjE9YdnArcW4vl/QZxR+GnBOiHAKqPLl4MfEHDjDl2Wf5RUoKD511FoOSGhcysoJvsz7im92z0UQfxZtcdM8YyfQ7p5PQ3rqpFhbP5VDuw5SXb8Xj7k2XjveQmHBxvfUWlhfxZtYslmevBODkLqO4pt9/0M7TrklyNoTsPYeZ3P068rMLOG50Krc9N4VBo5oW0KatU1JYyvN3vMW82Uvxl/s5ZeJIpj19NZ27d6y/cCOYt2QjL876nl17cxh3dQaThi4myVPYom0Yoh8nHeKdCqwUkY0ikiEimSKSUV8hVV0AZNeXz0n2bN3HXbe8xv7kDmA/be/JK2baX98jv7BuS1hAA9y07G2WHvwZRSn2l/GvrUt4YeN3IXlfXbGCF5YtIxCwAtP9sGsXV3/wAaXl5Y2WOTNnCV/nzUITfQDEpwY4PHElT979EgClZWvZd+gGysu3AlDu38H+7FsoKV1Rb90vbXmDJYeW41c/fvWz5NByXtryZqNlbAwHdx8mP7sAgA3LNnHPeY9QlF/saJvRyrPTZ/DV29/jK/UR8AdY/OlKHv7dcy3axoYte/nrk5+xa28O3U/aw5Th3xqFcJTipFL4FZAKnANcgGUSusDB9lqM72YtpDQl9D274rJy0pduqrPsqkPb2FZ4KCT9w+0rQ9JmZ4YOovYVFjI/K6vhwtos3PV5SJo7Hjb6VlCYV0x+0WzAXyOHkl/07zrrzfXlsTonVJevzskg15fXaDmbSt6hfBZ9vLzV2osWSopKSX9/aUj62kUb2blpT4u1Mzd9Hf6AtVjwnPNW45UGRdA1HIGIaogniogjIv2Az2qbUxCRG4Ab7N2hwNrWkcwxkoC2HndisKq2b04FNfp1MLCx2VK1PNHcV07J1ldVk5taOAL9Gs191FBa4xzC9mubVAo18q5Q1bT68kUz5hzaDtF8ntEsW2tyJPwOkTwHJ81HBoPBYGhjRJ1SEJF/A0uAwSKyU0SmRFomg8FgOFqIOl9Eqvr/GlnkFUcEaV3MObQdovk8o1m21uRI+B0idg5ROadgMBgMhsgQdeYjg8FgMEQOoxQMBhsR6S0i80RkvYisE5Hf2+ldRORrEdlkf3e200VEnhGRzfYLmifV3UKLyOgWkdUi8pm9319EltkyvCciMXZ6rL2/2T7ez2nZIkltfdcWqdnHrY1RCgZDFeXAHao6BDgFuEVEhgB3A9+qairwrb0PVS9opmKtw3+xFWT8PfBT0P5/A0+q6kDgMFCxMGMKcNhOf9LOdyRTW9+1RWr2catyRCsFEXGJyCMi8qyIXBVpeZqKiLQTkRUicn6kZWkKInKRiLxqP7meE2l5akNV96jqKns7H+uPmQJcCMy0s80ELrK3LwTeUoulQCcRqd85VhMRkV5Y0Qtfs/cFOBOYU4tsFTLPAc6SxnpAbEPU0Xdtipp9HAmiVimIyBsisl9E1tZIP8/2p7RZRO6urbzNhUAvwAfsdErW2mihcwC4C5jtjJR10xLnoKofq+r1wFTgMiflbSlsc8tIYBnQXVUrfErsBbrb2ynAjqBiO3H2RvQU8CegwgdFVyBHVSucZQW3XymbfTzXzn/EU6Pv2ho1+7jVibolqUHMoIa3VBFxA88DE7D+AD+IyCeAG3i0RvlrsV6pX6yqL4vIHKyhf2syg+afw3BgPdB4390twwyaeQ6qut/e/rNdLqoRkUTgA2C6quYFP2CrqopIqy/Zs0eJ+1V1pYiMb+322wo1+y7S8jSGaOnjqFUKqrogzOTYycBmVf0ZQETeBS5U1UexHO5VQ0R2AmX2bk1vcI7TQucwHmgHDAGKRWSuqrbaU0QLnYMAfwc+rxjiRysi4sW6qcxS1Q/t5H0icoyq7rHNQxVKbhfQO6h4LzvNCcYBvxGRiVgPCB2Ap7FMVh57NBDcfoVsO0XEA3QEQj01HkHU0ndtiZA+FpF/qeqVrSlE1JqPaqGxw/UPgXNF5FlggZOCNYJGnYOq3qeq04F3gFdbUyHUQWP74TbgbGCSiEx1UrDmYCuv14GfVPWfQYc+ASrmpK4C/ico/T/tVUinALlBZqYWRVXvUdVeqtoPK6ztd6p6BTAPmFSLbBUyT7LzH7EvJdXRd22GWvq4VRUCRPFIoSVQ1SKqVmO0aVR1RqRlaCqq+gzwTKTlaADjgN8BmSKyxk67F2uUM1sslyvbgEvtY3OBicBmoAi4pnXFBaz5pndF5GFgNdaNEfv7bRHZjBWf5PIIyNaahO07VZ0bQZnaJG1NKbTmcN0pzDlEKaq6EKhthc5ZYfIrcIujQoVBVdOBdHv7ZyxzXs08JcDkVhUsgtTTd22O4D5ubdqa+egHINV+YScG6+nnkwjL1FjMORgMhqglapWChPGWak+m3Qp8ibUOebaqrouknHVhzsFgMLQ1jEM8g8FgMFQStSMFg8FgMLQ+RikYDAaDoRKjFAwGg8FQiVEKBkMdiEi/mn6f2hIi8oCI3BlpOQxtB6MUDAaDwVCJUQqGNoH9xP6T7YJ7nYh8JSLxIpIuIml2niQRybK3rxaRj8UKipMlIreKyO1iBS9ZKiJd6mhrlIj8KCI/EvRymljBTx4TkR/ECqpzo50+3pZjjohsEJFZttsFROTvYgV+yRCRx+20ZBH5wK7nBxEZV4csD9ieatNF5GcRmRZ07HYRWWt/pgel3yci/yciC7GcQlakHysiX4jIShH5XkSOs9Mn23X8KCLR4g7GEClU1XzMJ+o/QD+sQCoj7P3ZwJVYb32m2WlJQJa9fTWW+4n2QDKW6+ip9rEnsbxo1tZWBvBLe/sxYK29fQPwZ3s7FlgB9AfG2/X3wnrQWgKciuWqeiNVS7872d/vAKfa232w/PXUJssDwGK7vSQsp3ZeYBSQieUsMRFYh+UuuiI9Actp3mbgTruub4FUe3s0lm8d7PwpwTKaz9H7aWtuLhxBRApUNdHhNqYCRar6Vr2ZW77tq4GvVHV3a7fdwmxV1Qq/NiuxFEVdzFMr4Eq+iOQCn9rpmcCwcAVEpBPWjbHiifltrAhrAOcAw0SkwgFdR6yoa2XAclXdadexxpZtKVACvC5WaMWK8IpnA0OkyiV3BxFJVNWCWs7jf1W1FCgVkf1Y8RxOBT5S1UK7zQ+B07CU0kdq+f1CLJfmFS6lxwLvB7Uba38vAmaIyGwsJ5KGoxijFFoQEXGralgX3ar6UqTaxnpqXgu0daVQGrTtB+KxRg8VZtCaMSeC8weC9gM07doX4DZV/bJaouXevKZsHlUtF5GTsfwmTcJ6C/xMW95T1PJP1BBC6m6C7C6sgDwjah5Q1akiMhor4tdKERmlqke0m21D7Zg5hRqIyB+DbMYPBqV/bNti14nIDUHpBSLyhG1/HmPvP2LbZ5eKSHc7X+UqENs+/N8isty2/Z5mpyeIyGzbBv2RWAHX0+qQtWbbf7FlXysir4jFJCANmCUia2w7/CgRmW+fz5fiYAjJViALy2QCVS6km4yq5gA5InKqnXRF0OEvgZvE8tuPiAwSkXa11WU/nXdUy1PnH7ACJgF8heVOvCJfyI26AXwPXGRfM+2Ai+20BXZ6vIi0By6wzysP2Coik+02RUSG29vHquoyVf0LcIDqzg4NRxlGKQQhVvzgVCyvkyOAUSLyS/vwtao6CusGO01EKkIbtgOWqepwtTw1tgOWqupwrD/o9bU051HVk4HpwF/ttJuxgq0PAe6n6mZXGzXbfk5Vf6GqQ7Geos9X1TlYtu8r7KfEcuBZYJJ9Pm8AjzTsF4pKHse6Ua/Gsrm3BNcAz9tmoGDPm69hRcFbJdYy1Zep+6m9PfCZiGQAC4Hb7fRpQJr94LEeK0xpo1ArWNEMYDlW2MnXVHW1nf4e8CPwOZbzwgquAKbYDxHrsMLVAjwmIpn2OS22yxqOUozvI6rmFOzVIZOAHPtQIvCoqr4uIg9gPY2BZS8+V1WXikg5EFthuhGRUiBOVVVELgMmqOp1dvkCVX1cRNKB+1R1kT2SWKSqA0XkY+BpVZ1n17UKuEFVV9Qid822L8GK75oAdAGeVdW/2+3dqaorRGQo1h//Z7saN7BHVc9p7u9oMBjaPmZOoTqCpQRerpZo2YzPBsaoapF9k62wX5fUsOX7tErT1mX/LW1AnvooCVIIccALWCtxdthKKFxcZwHWqeqYJrZpMBiOYIz5qDpfAtfatmBEJEVEumGtMjlsK4TjgFMcan8RdlQvERkCnNiIshUK4KAtf7B9PR/LlAHWEslkERljt+MVkROaJXUbRUSet+dZgj+RiJ6GiFwTRpbnIyGL4ejGjBSCUNWvROR4YIm9bK8Aay38F8BUEfkJ66a61CERXgBm2nbmDVh239yGFFTVHBF5FWuV0V6q25JnAC+JSDEwBkthPCMiHbGugafsto4qVLXVo6bVhqq+CbwZaTkMBjOnEEWIiBvwqmqJiBwLfAMMVtWyCItmMBiOEsxIIbpIAObZSx4FuNkoBIPB0JqYkUIbQESWUfX2aQW/U9XMSMhjMBiOXIxSMBgMBkMlZvWRwWAwGCoxSsFgMBgMlRilYDAYDIZKjFIwGAwGQyVGKRgMBoOhkv8PVtuNa3SwEYUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc28784fa58>"
+       "<Figure size 432x432 with 9 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -1963,10 +1889,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 38,
+   "metadata": {},
    "outputs": [],
    "source": [
     "model = load_model(path_best_model)"
@@ -1981,22 +1905,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 39,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " 8960/10000 [=========================>....] - ETA: 0s"
+      "10000/10000 [==============================] - 1s 64us/sample - loss: 0.0490 - accuracy: 0.9882\n"
      ]
     }
    ],
    "source": [
-    "result = model.evaluate(x=data.test.images,\n",
-    "                        y=data.test.labels)"
+    "result = model.evaluate(x=data.x_test,\n",
+    "                        y=data.y_test)"
    ]
   },
   {
@@ -2008,17 +1930,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss 0.0363312054525\n",
-      "acc 0.9888\n"
+      "loss 0.048988553384863916\n",
+      "accuracy 0.9882\n"
      ]
     }
    ],
@@ -2036,16 +1956,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 41,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "acc: 98.88%\n"
+      "accuracy: 98.82%\n"
      ]
     }
    ],
@@ -2064,13 +1982,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "images = data.test.images[0:9]"
+    "images = data.x_test[0:9]"
    ]
   },
   {
@@ -2082,13 +1998,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 43,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cls_true = data.test.cls[0:9]"
+    "cls_true = data.y_test_cls[0:9]"
    ]
   },
   {
@@ -2100,10 +2014,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 44,
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_pred = model.predict(x=images)"
@@ -2118,10 +2030,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 45,
+   "metadata": {},
    "outputs": [],
    "source": [
     "cls_pred = np.argmax(y_pred,axis=1)"
@@ -2129,16 +2039,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 46,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc287ae2fd0>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -2164,13 +2072,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 47,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "y_pred = model.predict(x=data.test.images)"
+    "y_pred = model.predict(x=data.x_test)"
    ]
   },
   {
@@ -2182,13 +2088,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 48,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "cls_pred = np.argmax(y_pred,axis=1)"
+    "cls_pred = np.argmax(y_pred, axis=1)"
    ]
   },
   {
@@ -2200,16 +2104,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {
-    "collapsed": false
-   },
+   "execution_count": 49,
+   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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BOP300wEoO/2kX2co8f169eoBcMUVVwDQsWNHAPbdd18AtthiiyxGHI0yTRGRCJRpSkEY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\niETw/wHzcqwbcSXHTgAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fc285c98128>"
+       "<Figure size 432x288 with 9 Axes>"
       ]
      },
      "metadata": {},
@@ -2283,7 +2185,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/20_Natural_Language_Processing.ipynb b/20_Natural_Language_Processing.ipynb
index 076fb73..a24a12b 100644
--- a/20_Natural_Language_Processing.ipynb
+++ b/20_Natural_Language_Processing.ipynb
@@ -124,16 +124,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -155,12 +146,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from tf.keras.models import Sequential  # This does not work!\n",
-    "from tensorflow.python.keras.models import Sequential\n",
-    "from tensorflow.python.keras.layers import Dense, GRU, Embedding\n",
-    "from tensorflow.python.keras.optimizers import Adam\n",
-    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
-    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import Dense, GRU, Embedding\n",
+    "from tensorflow.keras.optimizers import Adam\n",
+    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.keras.preprocessing.sequence import pad_sequences"
    ]
   },
   {
@@ -180,7 +170,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -202,7 +192,7 @@
     {
      "data": {
       "text/plain": [
-       "'2.1.2-tf'"
+       "'2.2.4-tf'"
       ]
      },
      "execution_count": 4,
@@ -288,7 +278,11 @@
    "outputs": [],
    "source": [
     "x_train_text, y_train = imdb.load_data(train=True)\n",
-    "x_test_text, y_test = imdb.load_data(train=False)"
+    "x_test_text, y_test = imdb.load_data(train=False)\n",
+    "\n",
+    "# Convert to numpy arrays.\n",
+    "y_train = np.array(y_train)\n",
+    "y_test = np.array(y_test)"
    ]
   },
   {
@@ -341,7 +335,7 @@
     {
      "data": {
       "text/plain": [
-       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+       "'Return To the Lost World was filmed back-to-back with the 1992 version of The Lost World.<br /><br />In this sequel, the same five people, lead by Challenger return to the plateau where a group has started drilling for oil which is threatening to destroy the land. Gomez has something to do with this. They manage to defeat the drillers and the plateau is saved, much to the delight of the natives.<br /><br />Like in The Lost World, what few dinosaurs we see are made of rubber and these include a T-Rex and Ankylosaurus.<br /><br />John Ryhs-Davies and David Warner reprise their roles as Challenger and Summerlee and three of the other actors are also back.<br /><br />Despite reading several bad reviews of this and those cheap looking rubber dinosaurs, I enjoyed Return to the Lost World.<br /><br />Rating: 3 stars out of 5.'"
       ]
      },
      "execution_count": 11,
@@ -429,8 +423,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 10.6 s, sys: 16 ms, total: 10.6 s\n",
-      "Wall time: 10.6 s\n"
+      "CPU times: user 8.21 s, sys: 33.2 ms, total: 8.25 s\n",
+      "Wall time: 8.25 s\n"
      ]
     }
    ],
@@ -604,8 +598,8 @@
        " 'say': 131,\n",
        " 'these': 132,\n",
        " 'here': 133,\n",
-       " 'why': 134,\n",
-       " 'scenes': 135,\n",
+       " 'scenes': 134,\n",
+       " 'why': 135,\n",
        " 'while': 136,\n",
        " 'something': 137,\n",
        " 'such': 138,\n",
@@ -720,8 +714,8 @@
        " 'sure': 247,\n",
        " 'rather': 248,\n",
        " 'hard': 249,\n",
-       " 'girl': 250,\n",
-       " 'anyone': 251,\n",
+       " 'anyone': 250,\n",
+       " 'girl': 251,\n",
        " 'each': 252,\n",
        " 'played': 253,\n",
        " 'day': 254,\n",
@@ -771,8 +765,8 @@
        " 'instead': 298,\n",
        " 'high': 299,\n",
        " 'during': 300,\n",
-       " 'year': 301,\n",
-       " 'said': 302,\n",
+       " 'said': 301,\n",
+       " 'year': 302,\n",
        " 'half': 303,\n",
        " 'everyone': 304,\n",
        " 'later': 305,\n",
@@ -804,8 +798,8 @@
        " 'nice': 331,\n",
        " 'budget': 332,\n",
        " 'poor': 333,\n",
-       " 'completely': 334,\n",
-       " 'short': 335,\n",
+       " 'short': 334,\n",
+       " 'completely': 335,\n",
        " 'second': 336,\n",
        " \"you're\": 337,\n",
        " '3': 338,\n",
@@ -855,8 +849,8 @@
        " 'remember': 382,\n",
        " 'mean': 383,\n",
        " 'came': 384,\n",
-       " 'understand': 385,\n",
-       " 'getting': 386,\n",
+       " 'getting': 385,\n",
+       " 'understand': 386,\n",
        " 'perhaps': 387,\n",
        " 'moments': 388,\n",
        " 'name': 389,\n",
@@ -887,11 +881,11 @@
        " 'went': 414,\n",
        " 'finally': 415,\n",
        " 'mother': 416,\n",
-       " 'case': 417,\n",
-       " 'title': 418,\n",
+       " 'title': 417,\n",
+       " 'case': 418,\n",
        " 'absolutely': 419,\n",
-       " 'live': 420,\n",
-       " 'boy': 421,\n",
+       " 'boy': 420,\n",
+       " 'live': 421,\n",
        " 'yes': 422,\n",
        " 'laugh': 423,\n",
        " 'certainly': 424,\n",
@@ -974,15 +968,15 @@
        " \"they're\": 501,\n",
        " 'act': 502,\n",
        " 'art': 503,\n",
-       " 'matter': 504,\n",
-       " 'kill': 505,\n",
+       " 'kill': 504,\n",
+       " 'matter': 505,\n",
        " 'etc': 506,\n",
        " 'tries': 507,\n",
        " \"won't\": 508,\n",
        " 'past': 509,\n",
        " 'town': 510,\n",
-       " 'turns': 511,\n",
-       " 'enjoyed': 512,\n",
+       " 'enjoyed': 511,\n",
+       " 'turns': 512,\n",
        " 'brilliant': 513,\n",
        " 'gave': 514,\n",
        " 'behind': 515,\n",
@@ -1041,11 +1035,11 @@
        " 'extremely': 568,\n",
        " 'score': 569,\n",
        " 'violence': 570,\n",
-       " 'involved': 571,\n",
-       " 'police': 572,\n",
+       " 'police': 571,\n",
+       " 'involved': 572,\n",
        " 'strong': 573,\n",
-       " 'chance': 574,\n",
-       " 'lack': 575,\n",
+       " 'lack': 574,\n",
+       " 'chance': 575,\n",
        " 'cannot': 576,\n",
        " 'hit': 577,\n",
        " 'roles': 578,\n",
@@ -1061,16 +1055,16 @@
        " 'looked': 588,\n",
        " \"wouldn't\": 589,\n",
        " 'crap': 590,\n",
-       " 'simple': 591,\n",
-       " 'please': 592,\n",
-       " 'murder': 593,\n",
-       " 'cool': 594,\n",
+       " 'please': 591,\n",
+       " 'simple': 592,\n",
+       " 'cool': 593,\n",
+       " 'murder': 594,\n",
        " 'obvious': 595,\n",
        " 'happened': 596,\n",
        " 'complete': 597,\n",
        " 'cut': 598,\n",
-       " 'serious': 599,\n",
-       " 'age': 600,\n",
+       " 'age': 599,\n",
+       " 'serious': 600,\n",
        " 'gore': 601,\n",
        " 'attempt': 602,\n",
        " 'hell': 603,\n",
@@ -1091,18 +1085,18 @@
        " 'across': 618,\n",
        " 'none': 619,\n",
        " 'hero': 620,\n",
-       " 'possible': 621,\n",
+       " 'exactly': 621,\n",
        " 'today': 622,\n",
-       " 'exactly': 623,\n",
+       " 'possible': 623,\n",
        " 'alone': 624,\n",
        " 'sad': 625,\n",
        " 'brother': 626,\n",
        " 'number': 627,\n",
-       " 'saying': 628,\n",
-       " 'career': 629,\n",
+       " 'career': 628,\n",
+       " 'saying': 629,\n",
        " \"film's\": 630,\n",
-       " 'usually': 631,\n",
-       " 'hours': 632,\n",
+       " 'hours': 631,\n",
+       " 'usually': 632,\n",
        " 'cinematography': 633,\n",
        " 'talent': 634,\n",
        " 'view': 635,\n",
@@ -1125,8 +1119,8 @@
        " 'level': 652,\n",
        " 'ends': 653,\n",
        " 'started': 654,\n",
-       " 'call': 655,\n",
-       " 'female': 656,\n",
+       " 'female': 655,\n",
+       " 'call': 656,\n",
        " \"i'll\": 657,\n",
        " 'husband': 658,\n",
        " 'four': 659,\n",
@@ -1138,8 +1132,8 @@
        " 'change': 665,\n",
        " 'mostly': 666,\n",
        " 'usual': 667,\n",
-       " 'silly': 668,\n",
-       " 'scary': 669,\n",
+       " 'scary': 668,\n",
+       " 'silly': 669,\n",
        " 'rating': 670,\n",
        " 'beyond': 671,\n",
        " 'somewhat': 672,\n",
@@ -1156,11 +1150,11 @@
        " 'apparently': 683,\n",
        " 'non': 684,\n",
        " 'strange': 685,\n",
-       " 'upon': 686,\n",
-       " 'attention': 687,\n",
+       " 'attention': 686,\n",
+       " 'upon': 687,\n",
        " 'finds': 688,\n",
-       " 'basically': 689,\n",
-       " 'single': 690,\n",
+       " 'single': 689,\n",
+       " 'basically': 690,\n",
        " 'cheap': 691,\n",
        " 'modern': 692,\n",
        " 'due': 693,\n",
@@ -1189,12 +1183,12 @@
        " 'earth': 716,\n",
        " 'tells': 717,\n",
        " 'predictable': 718,\n",
-       " 'songs': 719,\n",
-       " 'team': 720,\n",
+       " 'team': 719,\n",
+       " 'songs': 720,\n",
        " 'comic': 721,\n",
        " 'straight': 722,\n",
-       " 'whether': 723,\n",
-       " '8': 724,\n",
+       " '8': 723,\n",
+       " 'whether': 724,\n",
        " 'die': 725,\n",
        " 'add': 726,\n",
        " 'dialog': 727,\n",
@@ -1224,12 +1218,12 @@
        " 'sequel': 751,\n",
        " 'clear': 752,\n",
        " 'falls': 753,\n",
-       " 'needs': 754,\n",
-       " \"haven't\": 755,\n",
+       " \"haven't\": 754,\n",
+       " 'needs': 755,\n",
        " 'dull': 756,\n",
        " 'suspense': 757,\n",
-       " 'eye': 758,\n",
-       " 'bunch': 759,\n",
+       " 'bunch': 758,\n",
+       " 'eye': 759,\n",
        " 'surprised': 760,\n",
        " 'showing': 761,\n",
        " 'sorry': 762,\n",
@@ -1240,8 +1234,8 @@
        " 'ways': 767,\n",
        " 'theme': 768,\n",
        " 'theater': 769,\n",
-       " 'named': 770,\n",
-       " 'among': 771,\n",
+       " 'among': 770,\n",
+       " 'named': 771,\n",
        " \"what's\": 772,\n",
        " 'storyline': 773,\n",
        " 'monster': 774,\n",
@@ -1256,31 +1250,31 @@
        " 'using': 783,\n",
        " '9': 784,\n",
        " 'feature': 785,\n",
-       " 'comments': 786,\n",
-       " 'buy': 787,\n",
+       " 'buy': 786,\n",
+       " 'comments': 787,\n",
        " \"'\": 788,\n",
-       " 'typical': 789,\n",
-       " 't': 790,\n",
+       " 't': 789,\n",
+       " 'typical': 790,\n",
        " 'sister': 791,\n",
        " 'editing': 792,\n",
        " 'tale': 793,\n",
        " 'avoid': 794,\n",
-       " 'deal': 795,\n",
-       " 'mystery': 796,\n",
-       " 'dr': 797,\n",
+       " 'dr': 795,\n",
+       " 'deal': 796,\n",
+       " 'mystery': 797,\n",
        " 'doubt': 798,\n",
        " 'fantastic': 799,\n",
-       " 'kept': 800,\n",
-       " 'nearly': 801,\n",
+       " 'nearly': 800,\n",
+       " 'kept': 801,\n",
        " 'subject': 802,\n",
-       " 'okay': 803,\n",
-       " 'feels': 804,\n",
+       " 'feels': 803,\n",
+       " 'okay': 804,\n",
        " 'viewing': 805,\n",
        " 'elements': 806,\n",
-       " 'oscar': 807,\n",
-       " 'check': 808,\n",
-       " 'points': 809,\n",
-       " 'realistic': 810,\n",
+       " 'check': 807,\n",
+       " 'oscar': 808,\n",
+       " 'realistic': 809,\n",
+       " 'points': 810,\n",
        " 'greatest': 811,\n",
        " 'means': 812,\n",
        " 'herself': 813,\n",
@@ -1289,8 +1283,8 @@
        " 'imagine': 816,\n",
        " 'rent': 817,\n",
        " 'viewers': 818,\n",
-       " 'crime': 819,\n",
-       " 'richard': 820,\n",
+       " 'richard': 819,\n",
+       " 'crime': 820,\n",
        " 'form': 821,\n",
        " 'peter': 822,\n",
        " 'actual': 823,\n",
@@ -1301,8 +1295,8 @@
        " 'believable': 828,\n",
        " 'period': 829,\n",
        " 'red': 830,\n",
-       " 'brought': 831,\n",
-       " 'move': 832,\n",
+       " 'move': 831,\n",
+       " 'brought': 832,\n",
        " 'material': 833,\n",
        " 'forget': 834,\n",
        " 'somehow': 835,\n",
@@ -1321,11 +1315,11 @@
        " 'average': 848,\n",
        " 'open': 849,\n",
        " 'sequences': 850,\n",
-       " 'killing': 851,\n",
-       " 'atmosphere': 852,\n",
+       " 'atmosphere': 851,\n",
+       " 'killing': 852,\n",
        " 'eventually': 853,\n",
-       " 'tom': 854,\n",
-       " 'learn': 855,\n",
+       " 'learn': 854,\n",
+       " 'tom': 855,\n",
        " 'premise': 856,\n",
        " '20': 857,\n",
        " 'wait': 858,\n",
@@ -1335,17 +1329,17 @@
        " 'expected': 862,\n",
        " 'whatever': 863,\n",
        " 'indeed': 864,\n",
-       " 'particular': 865,\n",
-       " 'note': 866,\n",
-       " 'poorly': 867,\n",
+       " 'note': 865,\n",
+       " 'poorly': 866,\n",
+       " 'particular': 867,\n",
        " 'lame': 868,\n",
        " 'dance': 869,\n",
        " 'imdb': 870,\n",
        " 'situation': 871,\n",
        " 'shame': 872,\n",
        " 'third': 873,\n",
-       " 'york': 874,\n",
-       " 'box': 875,\n",
+       " 'box': 874,\n",
+       " 'york': 875,\n",
        " 'truth': 876,\n",
        " 'decided': 877,\n",
        " 'free': 878,\n",
@@ -1357,9 +1351,9 @@
        " 'acted': 884,\n",
        " 'leaves': 885,\n",
        " 'unless': 886,\n",
-       " 'emotional': 887,\n",
+       " 'romance': 887,\n",
        " 'possibly': 888,\n",
-       " 'romance': 889,\n",
+       " 'emotional': 889,\n",
        " 'sexual': 890,\n",
        " 'gay': 891,\n",
        " 'boys': 892,\n",
@@ -1369,14 +1363,14 @@
        " 'forced': 896,\n",
        " 'credits': 897,\n",
        " 'memorable': 898,\n",
-       " 'doctor': 899,\n",
+       " 'reading': 899,\n",
        " 'became': 900,\n",
-       " 'reading': 901,\n",
+       " 'doctor': 901,\n",
        " 'otherwise': 902,\n",
-       " 'begin': 903,\n",
+       " 'de': 903,\n",
        " 'air': 904,\n",
-       " 'crew': 905,\n",
-       " 'de': 906,\n",
+       " 'begin': 905,\n",
+       " 'crew': 906,\n",
        " 'question': 907,\n",
        " 'meet': 908,\n",
        " 'society': 909,\n",
@@ -1388,8 +1382,8 @@
        " 'hands': 915,\n",
        " 'superb': 916,\n",
        " 'screenplay': 917,\n",
-       " 'beauty': 918,\n",
-       " 'interested': 919,\n",
+       " 'interested': 918,\n",
+       " 'beauty': 919,\n",
        " 'street': 920,\n",
        " 'features': 921,\n",
        " 'perfectly': 922,\n",
@@ -1399,24 +1393,24 @@
        " 'stage': 926,\n",
        " 'nature': 927,\n",
        " 'effect': 928,\n",
-       " 'comment': 929,\n",
-       " 'forward': 930,\n",
+       " 'forward': 929,\n",
+       " 'comment': 930,\n",
        " 'nor': 931,\n",
-       " 'badly': 932,\n",
-       " 'sounds': 933,\n",
+       " 'e': 932,\n",
+       " 'badly': 933,\n",
        " 'previous': 934,\n",
-       " 'e': 935,\n",
+       " 'sounds': 935,\n",
        " 'japanese': 936,\n",
        " 'weird': 937,\n",
        " 'island': 938,\n",
-       " 'inside': 939,\n",
-       " 'personal': 940,\n",
+       " 'personal': 939,\n",
+       " 'inside': 940,\n",
        " 'quickly': 941,\n",
        " 'total': 942,\n",
        " 'keeps': 943,\n",
        " 'towards': 944,\n",
-       " 'result': 945,\n",
-       " 'america': 946,\n",
+       " 'america': 945,\n",
+       " 'result': 946,\n",
        " 'battle': 947,\n",
        " 'crazy': 948,\n",
        " 'worked': 949,\n",
@@ -1429,16 +1423,16 @@
        " 'writers': 956,\n",
        " 'fire': 957,\n",
        " 'copy': 958,\n",
-       " 'unique': 959,\n",
-       " 'dumb': 960,\n",
+       " 'dumb': 959,\n",
+       " 'unique': 960,\n",
        " 'realize': 961,\n",
        " 'powerful': 962,\n",
-       " 'mark': 963,\n",
-       " 'lee': 964,\n",
+       " 'lee': 963,\n",
+       " 'mark': 964,\n",
        " 'business': 965,\n",
        " 'rate': 966,\n",
-       " 'dramatic': 967,\n",
-       " 'older': 968,\n",
+       " 'older': 967,\n",
+       " 'dramatic': 968,\n",
        " 'pay': 969,\n",
        " 'following': 970,\n",
        " 'directors': 971,\n",
@@ -1453,24 +1447,24 @@
        " 'appear': 980,\n",
        " 'brings': 981,\n",
        " 'front': 982,\n",
-       " 'ask': 983,\n",
-       " 'dream': 984,\n",
+       " 'dream': 983,\n",
+       " 'ask': 984,\n",
        " 'water': 985,\n",
-       " 'admit': 986,\n",
-       " 'bill': 987,\n",
+       " 'bill': 986,\n",
+       " 'admit': 987,\n",
        " 'rich': 988,\n",
        " 'apart': 989,\n",
        " 'joe': 990,\n",
        " 'political': 991,\n",
        " 'fairly': 992,\n",
-       " 'reasons': 993,\n",
-       " 'leading': 994,\n",
-       " 'portrayed': 995,\n",
-       " 'spent': 996,\n",
+       " 'leading': 993,\n",
+       " 'reasons': 994,\n",
+       " 'spent': 995,\n",
+       " 'portrayed': 996,\n",
        " 'telling': 997,\n",
        " 'cover': 998,\n",
        " 'outside': 999,\n",
-       " 'wasted': 1000,\n",
+       " 'present': 1000,\n",
        " ...}"
       ]
      },
@@ -1514,7 +1508,7 @@
     {
      "data": {
       "text/plain": [
-       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+       "'Return To the Lost World was filmed back-to-back with the 1992 version of The Lost World.<br /><br />In this sequel, the same five people, lead by Challenger return to the plateau where a group has started drilling for oil which is threatening to destroy the land. Gomez has something to do with this. They manage to defeat the drillers and the plateau is saved, much to the delight of the natives.<br /><br />Like in The Lost World, what few dinosaurs we see are made of rubber and these include a T-Rex and Ankylosaurus.<br /><br />John Ryhs-Davies and David Warner reprise their roles as Challenger and Summerlee and three of the other actors are also back.<br /><br />Despite reading several bad reviews of this and those cheap looking rubber dinosaurs, I enjoyed Return to the Lost World.<br /><br />Rating: 3 stars out of 5.'"
       ]
      },
      "execution_count": 19,
@@ -1541,17 +1535,19 @@
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      "execution_count": 20,
@@ -1702,7 +1698,7 @@
     {
      "data": {
       "text/plain": [
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+       "0.94528"
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@@ -1823,17 +1819,19 @@
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-       "         36,  146])"
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      "execution_count": 32,
@@ -1896,20 +1894,20 @@
        "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
        "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
        "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
-       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
-       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
-       "          0,    0,    0,    0,    0,    0,    0,    0,    0,    0,    0,\n",
-       "          0,    0,    0,    3,  591,  929,    7,    7,   48,   67,   10,\n",
-       "        131,   11,    6,    3,  393,   19,   12,   10,   67,  103,  121,\n",
-       "          2,  121,    9,    6,  406,   27,    4,    1,  342,  713, 1317,\n",
-       "         90,   16,    3,   78,  174,  694, 4910,    2, 2556, 3599,    3,\n",
-       "        399,  227,   31, 4033, 2628,  441,   20,   24,  288,    7,    7,\n",
-       "          9,    6,  144,    5,  114,  871,  221,  922,   43,   22,   25,\n",
-       "       3639, 1897,   27,  217,    1, 9206,   20, 1306,    4,  258,    5,\n",
-       "        197,   48,    6,   20,    9,  631,  411,   11,   19,  405,   18,\n",
-       "          8,  614,    9, 1003,  405,   43,   22,   62,  103,   11,   19,\n",
-       "         27,   67,  380,   12,    9,   80,   26,   14,  152,    2, 1451,\n",
-       "          3, 2997,  153,   36,  146], dtype=int32)"
+       "          0,    0,    0,    0,    0,    0,    0, 1037,    5,    1,  432,\n",
+       "        181,   13,  748,  141,    5,  141,   16,    1, 7418,  318,    4,\n",
+       "          1,  432,  181,    7,    7,    8,   11,  751,    1,  167,  707,\n",
+       "         83,  469,   31, 1037,    5,    1,  117,    3,  547,   45,  654,\n",
+       "         15, 3336,   60,    6, 3746,    5, 2222,    1, 1379,   45,  137,\n",
+       "          5,   77,   16,   11,   33, 1894,    5, 4399,    1,    2,    1,\n",
+       "          6, 2011,   72,    5,    1, 3029,    4,    1, 5836,    7,    7,\n",
+       "         37,    8,    1,  432,  181,   48,  171, 3847,   73,   63,   23,\n",
+       "         90,    4, 4118,    2,  132, 1469,    3,  789, 4019,    2,    7,\n",
+       "          7,  315, 4180,    2,  611, 2991,   65,  578,   14,    2,    2,\n",
+       "        277,    4,    1,   79,  150,   23,   81,  141,    7,    7,  467,\n",
+       "        899,  439,   74,  838,    4,   11,    2,  143,  691,  256, 4118,\n",
+       "       3847,   10,  511, 1037,    5,    1,  432,  181,    7,    7,  670,\n",
+       "        338,  405,   41,    4,  447], dtype=int32)"
       ]
      },
      "execution_count": 33,
@@ -1980,7 +1978,7 @@
     {
      "data": {
       "text/plain": [
-       "'A simple comment...<br /><br />What can I say... this is a wonderful film that I can watch over and over. It is definitely one of the top ten comedies made. With a great cast, Jack Lemmon and Walter Matthau wording a perfect script by Neil Simon, based on his play.<br /><br />It is real to life situation done perfectly. If you have digital cable, one gets the menu on bottom of screen to give what is on. It usually gives this film ***% stars but in reality it deserves **** stars. If you really watch this film, one can tell that it will be as funny and fresh a hundred years from now.'"
+       "'Return To the Lost World was filmed back-to-back with the 1992 version of The Lost World.<br /><br />In this sequel, the same five people, lead by Challenger return to the plateau where a group has started drilling for oil which is threatening to destroy the land. Gomez has something to do with this. They manage to defeat the drillers and the plateau is saved, much to the delight of the natives.<br /><br />Like in The Lost World, what few dinosaurs we see are made of rubber and these include a T-Rex and Ankylosaurus.<br /><br />John Ryhs-Davies and David Warner reprise their roles as Challenger and Summerlee and three of the other actors are also back.<br /><br />Despite reading several bad reviews of this and those cheap looking rubber dinosaurs, I enjoyed Return to the Lost World.<br /><br />Rating: 3 stars out of 5.'"
       ]
      },
      "execution_count": 36,
@@ -2007,7 +2005,7 @@
     {
      "data": {
       "text/plain": [
-       "'a simple comment br br what can i say this is a wonderful film that i can watch over and over it is definitely one of the top ten comedies made with a great cast jack lemmon and walter matthau a perfect script by neil simon based on his play br br it is real to life situation done perfectly if you have digital cable one gets the menu on bottom of screen to give what is on it usually gives this film stars but in reality it deserves stars if you really watch this film one can tell that it will be as funny and fresh a hundred years from now'"
+       "'return to the lost world was filmed back to back with the 1992 version of the lost world br br in this sequel the same five people lead by return to the where a group has started for oil which is threatening to destroy the land has something to do with this they manage to defeat the and the is saved much to the delight of the natives br br like in the lost world what few dinosaurs we see are made of rubber and these include a t rex and br br john davies and david warner their roles as and and three of the other actors are also back br br despite reading several bad reviews of this and those cheap looking rubber dinosaurs i enjoyed return to the lost world br br rating 3 stars out of 5'"
       ]
      },
      "execution_count": 37,
@@ -2087,17 +2085,7 @@
    "cell_type": "code",
    "execution_count": 41,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model.add(GRU(units=16, return_sequences=True))"
    ]
@@ -2177,17 +2165,7 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model.compile(loss='binary_crossentropy',\n",
     "              optimizer=optimizer,\n",
@@ -2203,21 +2181,22 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
       "layer_embedding (Embedding)  (None, 544, 8)            80000     \n",
       "_________________________________________________________________\n",
-      "gru_1 (GRU)                  (None, None, 16)          1200      \n",
+      "gru (GRU)                    (None, 544, 16)           1248      \n",
       "_________________________________________________________________\n",
-      "gru_2 (GRU)                  (None, None, 8)           600       \n",
+      "gru_1 (GRU)                  (None, 544, 8)            624       \n",
       "_________________________________________________________________\n",
-      "gru_3 (GRU)                  (None, 4)                 156       \n",
+      "gru_2 (GRU)                  (None, 4)                 168       \n",
       "_________________________________________________________________\n",
-      "dense_1 (Dense)              (None, 1)                 5         \n",
+      "dense (Dense)                (None, 1)                 5         \n",
       "=================================================================\n",
-      "Total params: 81,961\n",
-      "Trainable params: 81,961\n",
+      "Total params: 82,045\n",
+      "Trainable params: 82,045\n",
       "Non-trainable params: 0\n",
       "_________________________________________________________________\n"
      ]
@@ -2249,22 +2228,19 @@
      "text": [
       "Train on 23750 samples, validate on 1250 samples\n",
       "Epoch 1/3\n",
-      "23750/23750 [==============================]23750/23750 [==============================] - 464s 20ms/step - loss: 0.6517 - acc: 0.6002 - val_loss: 0.6218 - val_acc: 0.6752\n",
-      "\n",
+      "23750/23750 [==============================] - 16s 690us/sample - loss: 0.4935 - accuracy: 0.7452 - val_loss: 0.3798 - val_accuracy: 0.8328\n",
       "Epoch 2/3\n",
-      "23750/23750 [==============================]23750/23750 [==============================] - 447s 19ms/step - loss: 0.4292 - acc: 0.8102 - val_loss: 0.6701 - val_acc: 0.6512\n",
-      "\n",
+      "23750/23750 [==============================] - 12s 510us/sample - loss: 0.2919 - accuracy: 0.8887 - val_loss: 0.3111 - val_accuracy: 0.8736\n",
       "Epoch 3/3\n",
-      "23750/23750 [==============================]23750/23750 [==============================] - 445s 19ms/step - loss: 0.3092 - acc: 0.8765 - val_loss: 0.3182 - val_acc: 0.8752\n",
-      "\n",
-      "CPU times: user 35min 19s, sys: 2min 41s, total: 38min\n",
-      "Wall time: 22min 37s\n"
+      "23750/23750 [==============================] - 12s 511us/sample - loss: 0.2210 - accuracy: 0.9211 - val_loss: 0.3090 - val_accuracy: 0.8760\n",
+      "CPU times: user 48.9 s, sys: 1.58 s, total: 50.5 s\n",
+      "Wall time: 40.7 s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras._impl.keras.callbacks.History at 0x7ff79f0d6cf8>"
+       "<tensorflow.python.keras.callbacks.History at 0x7efdb7c5fef0>"
       ]
      },
      "execution_count": 48,
@@ -2296,10 +2272,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "25000/25000 [==============================]25000/25000 [==============================] - 175s 7ms/step\n",
-      "\n",
-      "CPU times: user 2min 59s, sys: 340 ms, total: 2min 59s\n",
-      "Wall time: 2min 55s\n"
+      "25000/25000 [==============================] - 12s 493us/sample - loss: 0.3331 - accuracy: 0.8674\n",
+      "CPU times: user 14 s, sys: 404 ms, total: 14.4 s\n",
+      "Wall time: 12.4 s\n"
      ]
     }
    ],
@@ -2311,13 +2286,15 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy: 86.71%\n"
+      "Accuracy: 86.74%\n"
      ]
     }
    ],
@@ -2343,8 +2320,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 7.01 s, sys: 0 ns, total: 7.01 s\n",
-      "Wall time: 6.88 s\n"
+      "CPU times: user 1.08 s, sys: 23.5 ms, total: 1.1 s\n",
+      "Wall time: 1.03 s\n"
      ]
     }
    ],
@@ -2418,7 +2395,7 @@
     {
      "data": {
       "text/plain": [
-       "121"
+       "132"
       ]
      },
      "execution_count": 55,
@@ -2445,7 +2422,7 @@
     {
      "data": {
       "text/plain": [
-       "13"
+       "18"
       ]
      },
      "execution_count": 56,
@@ -2473,7 +2450,7 @@
     {
      "data": {
       "text/plain": [
-       "'I would like to start by saying I can only hope that the makers of this movie and it\\'s sister film The Intruder (directed by the great unheralded stylist auteur that is Jopi Burnama) know in their hearts just how much pleasure they have brought to me and my friends in the sleepy north eastern town of Jarrow.<br /><br />From the opening pre credit sequence which manages to drag ever so slightly despite containing a man crashing through a window on a motorbike, the pitiless destruction of a silence lab, the introduction of one of the most simultaneously annoying and anaemic bad guys in movie history and costume design that Jean Paul Gautier would find ott and garish. Make no mistake; this is a truly unique experience. Early highlight - an explosion (get used to it, plenty more where that came from!) followed by a close up of our chubby heroine and the most hilarious line reading of the word \"dad\" in living memory. And then... the theme song...<br /><br />Yeah, this deserves its own paragraph. Sung by AJ, written by people who really should wish to remain anonymous, it makes the songs written for the Rocky films sound like Schubert. This is crap 80\\'s hero motivation narcissism at an all time high, with choice lyrics such as \"its only me and you, its come down to the wire\" and much talk of having to \"cross the line\" (it\\'ll make sense in time - our hero cares little for the boundaries of bona fida police work) abounding. Not to mention the Indonesian Supremes cooing the film\\'s title seductively. At this point anyone wishing to switch off officially has no pulse.<br /><br />Our hero is Semitic cop Peter Goldson (essayed brilliantly by Intruder star Peter O\\'Brien), the \"stabilizer\" of the title. The man\\'s bull in a china shop approach to crime fighting and particularly his less than inconspicuous undercover work truly leaves much to be desired, but he is without question an entertaining guide through the mean streets of downtown Jakarta, with local sleaze ball connection Captain Johnny in tow, as well as Peter\\'s own waste of space partner in fashion crime Sylvia Nash, who does little. So many highlights, so little time - the \"slide please\" arrogance of Peter\\'s not all too convincingly argued case against chief baddie Greg Rainmaker (Intruder fans will know hirsute slimy bastard Craig Gavin as the monstrous John White - helluva name eh? No! Oh well...), the x marks the spot location map stupidity, our hero taking horrible advantage of heroine Tina Probost during a moment of weakness on her behalf, the latter turning up at a sting operation dressed like a member of a particularly flamboyant dancing troop. And believe me that barely covers it.<br /><br />There wasn\\'t even time to go into the plot revolving around the hunt for a drug detection system and a kidnapped professor with an alarming but commendable amount of national pride. Or our hero turning up at a funeral dressed as if an extra on Boogie Nights. Or the absolutely hysterical craic between Captain Johnny and Goldson - two guys have never made more heavy weather of buddy buddy shtick than these clowns. The trowel was possibly too subtle me thinks.<br /><br />Ah it tails off people, and you never thought scenes of wanton destruction and general mayhem could be so unbelievably boring, but the character interaction is stupendous, the dialogue truly priceless and the incompetence on show somehow endearing. Oh and the shoes people - watch out for the shoes!'"
+       "\"This HAS to be my guilty pleasure. I am a HUGE fan of 80's movies that were designed to entertain and they didn't care if they offended anyone. This move has no meat, not substance, no deep thought provoking scenes. Just plain old college kids having fun and if a few breasts have to be shown, then so be it! This movie is for when you just want to relax and NOT think. Viva la nudity!\""
       ]
      },
      "execution_count": 57,
@@ -2501,7 +2478,7 @@
     {
      "data": {
       "text/plain": [
-       "0.08332923"
+       "0.27373913"
       ]
      },
      "execution_count": 58,
@@ -2619,14 +2596,14 @@
     {
      "data": {
       "text/plain": [
-       "array([[0.868934  ],\n",
-       "       [0.72526425],\n",
-       "       [0.33099633],\n",
-       "       [0.49190348],\n",
-       "       [0.3054021 ],\n",
-       "       [0.14959489],\n",
-       "       [0.5235635 ],\n",
-       "       [0.21565402]], dtype=float32)"
+       "array([[0.95301837],\n",
+       "       [0.92733926],\n",
+       "       [0.79257476],\n",
+       "       [0.9019553 ],\n",
+       "       [0.5875022 ],\n",
+       "       [0.55110747],\n",
+       "       [0.89896274],\n",
+       "       [0.33616564]], dtype=float32)"
       ]
      },
      "execution_count": 63,
@@ -2785,8 +2762,8 @@
     {
      "data": {
       "text/plain": [
-       "array([0.86528164, 0.6867993 , 0.4362397 , 0.66128314, 0.11546915,\n",
-       "       0.94507647, 0.32628497, 0.535881  ], dtype=float32)"
+       "array([ 0.01839033,  0.05229224,  0.0848575 ,  0.03222338, -0.03947427,\n",
+       "       -0.03776564, -0.01149088, -0.07443853], dtype=float32)"
       ]
      },
      "execution_count": 69,
@@ -2806,8 +2783,8 @@
     {
      "data": {
       "text/plain": [
-       "array([ 1.0691622 ,  1.124244  , -0.04477464, -0.05861434,  0.16965319,\n",
-       "        1.2626944 ,  0.76136374, -0.00998422], dtype=float32)"
+       "array([-0.14307617,  0.08333486,  0.15650608,  0.08930028, -0.08659173,\n",
+       "       -0.12289459, -0.14367667, -0.10402057], dtype=float32)"
       ]
      },
      "execution_count": 70,
@@ -2844,8 +2821,8 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.31903917,  0.53934103,  1.3727672 ,  1.4083829 ,  0.8475107 ,\n",
-       "       -0.22946651,  0.0251075 ,  0.77032244], dtype=float32)"
+       "array([ 0.05553182, -0.09014519, -0.06248455, -0.11525143,  0.14601274,\n",
+       "        0.07451952,  0.10784499,  0.10799433], dtype=float32)"
       ]
      },
      "execution_count": 72,
@@ -2865,8 +2842,8 @@
     {
      "data": {
       "text/plain": [
-       "array([ 0.47915924,  0.12226178,  0.90192014,  0.742338  ,  0.58730644,\n",
-       "        0.32736972, -0.17633988,  1.3744307 ], dtype=float32)"
+       "array([ 0.15100664, -0.13359004, -0.15154287, -0.12776676,  0.10830297,\n",
+       "        0.15224072,  0.13508266,  0.14284784], dtype=float32)"
       ]
      },
      "execution_count": 73,
@@ -2969,26 +2946,26 @@
      "text": [
       "Distance from 'great':\n",
       "0.000 - great\n",
-      "0.016 - touching\n",
-      "0.017 - arguments\n",
-      "0.025 - nevertheless\n",
-      "0.031 - elmer\n",
-      "0.032 - 8\n",
-      "0.036 - ritter\n",
-      "0.037 - juliet\n",
-      "0.041 - randy\n",
-      "0.045 - afterward\n",
+      "0.012 - spring\n",
+      "0.013 - 1980\n",
+      "0.013 - permanent\n",
+      "0.013 - robinson\n",
+      "0.015 - anime\n",
+      "0.015 - pleasantly\n",
+      "0.016 - inter\n",
+      "0.016 - profit\n",
+      "0.017 - ramones\n",
       "...\n",
-      "1.057 - rubbish\n",
-      "1.060 - dull\n",
-      "1.064 - disappointing\n",
-      "1.069 - unlikeable\n",
-      "1.078 - uninspired\n",
-      "1.083 - lacks\n",
-      "1.188 - worst\n",
-      "1.225 - waste\n",
-      "1.247 - awful\n",
-      "1.282 - terrible\n"
+      "1.988 - mst3k\n",
+      "1.988 - consist\n",
+      "1.988 - save\n",
+      "1.989 - unless\n",
+      "1.990 - ripoff\n",
+      "1.991 - insipid\n",
+      "1.994 - avoid\n",
+      "1.995 - drivel\n",
+      "1.995 - expand\n",
+      "1.995 - profile\n"
      ]
     }
    ],
@@ -3016,26 +2993,26 @@
      "text": [
       "Distance from 'worst':\n",
       "0.000 - worst\n",
-      "0.047 - embarrassingly\n",
-      "0.053 - terrible\n",
-      "0.094 - retarded\n",
-      "0.095 - poor\n",
-      "0.095 - stereotyping\n",
-      "0.096 - uninspired\n",
-      "0.099 - awful\n",
-      "0.100 - severed\n",
-      "0.108 - lacks\n",
+      "0.004 - horrible\n",
+      "0.004 - dull\n",
+      "0.005 - below\n",
+      "0.005 - boredom\n",
+      "0.006 - conceived\n",
+      "0.008 - salvage\n",
+      "0.009 - slapped\n",
+      "0.009 - fails\n",
+      "0.010 - virus\n",
       "...\n",
-      "1.167 - restraint\n",
-      "1.168 - available\n",
-      "1.176 - foremost\n",
-      "1.188 - great\n",
-      "1.193 - mesmerizing\n",
-      "1.222 - highly\n",
-      "1.229 - exploration\n",
-      "1.239 - delightful\n",
-      "1.268 - wonderfully\n",
-      "1.323 - 7\n"
+      "1.989 - cried\n",
+      "1.989 - compelling\n",
+      "1.990 - carell\n",
+      "1.990 - stadium\n",
+      "1.991 - deanna\n",
+      "1.992 - eddie\n",
+      "1.992 - resolved\n",
+      "1.992 - sirk\n",
+      "1.994 - sidney\n",
+      "1.997 - concentrates\n"
      ]
     }
    ],
@@ -3107,7 +3084,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/21_Machine_Translation.ipynb b/21_Machine_Translation.ipynb
index f0653c2..94146fe 100644
--- a/21_Machine_Translation.ipynb
+++ b/21_Machine_Translation.ipynb
@@ -59,16 +59,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -92,12 +83,12 @@
    "outputs": [],
    "source": [
     "# from tf.keras.models import Model  # This does not work!\n",
-    "from tensorflow.python.keras.models import Model\n",
-    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
-    "from tensorflow.python.keras.optimizers import RMSprop\n",
-    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\n",
-    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
-    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+    "from tensorflow.keras.models import Model\n",
+    "from tensorflow.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.keras.optimizers import RMSprop\n",
+    "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\n",
+    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.keras.preprocessing.sequence import pad_sequences"
    ]
   },
   {
@@ -117,7 +108,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -139,7 +130,7 @@
     {
      "data": {
       "text/plain": [
-       "'2.1.2-tf'"
+       "'2.2.4-tf'"
       ]
      },
      "execution_count": 4,
@@ -566,8 +557,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 2min 17s, sys: 608 ms, total: 2min 17s\n",
-      "Wall time: 2min 17s\n"
+      "CPU times: user 2min 18s, sys: 940 ms, total: 2min 19s\n",
+      "Wall time: 2min 19s\n"
      ]
     }
    ],
@@ -595,8 +586,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 1min 42s, sys: 492 ms, total: 1min 42s\n",
-      "Wall time: 1min 42s\n"
+      "CPU times: user 1min 49s, sys: 752 ms, total: 1min 50s\n",
+      "Wall time: 1min 50s\n"
      ]
     }
    ],
@@ -1209,17 +1200,7 @@
    "cell_type": "code",
    "execution_count": 46,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "encoder_output = connect_encoder()"
    ]
@@ -1308,9 +1289,7 @@
    "source": [
     "The GRU layers output a tensor with shape `[batch_size, sequence_length, state_size]`, where each \"word\" is encoded as a vector of length `state_size`. We need to convert this into sequences of integer-tokens that can be interpreted as words from our vocabulary.\n",
     "\n",
-    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token.\n",
-    "\n",
-    "Note that the activation-function is set to `linear` instead of `softmax` as we would normally use for one-hot encoded outputs, because there is apparently a bug in Keras so we need to make our own loss-function, as described in detail further below."
+    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token."
    ]
   },
   {
@@ -1320,7 +1299,7 @@
    "outputs": [],
    "source": [
     "decoder_dense = Dense(num_words,\n",
-    "                      activation='linear',\n",
+    "                      activation='softmax',\n",
     "                      name='decoder_output')"
    ]
   },
@@ -1428,134 +1407,25 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Loss Function\n",
+    "### Compile the Model\n",
     "\n",
     "The output of the decoder is a sequence of one-hot encoded arrays. In order to train the decoder we need to supply the one-hot encoded arrays that we desire to see on the decoder's output, and then use a loss-function like cross-entropy to train the decoder to produce this desired output.\n",
     "\n",
     "However, our data-set contains integer-tokens instead of one-hot encoded arrays. Each one-hot encoded array has 10000 elements so it would be extremely wasteful to convert the entire data-set to one-hot encoded arrays.\n",
     "\n",
-    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays. Unfortunately, there seems to be a bug in Keras when using this with Recurrent Neural Networks, so the following does not work:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# model_train.compile(optimizer=optimizer,\n",
-    "#                     loss='sparse_categorical_crossentropy')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The decoder outputs a 3-rank tensor with shape `[batch_size, sequence_length, num_words]` which contains batches of sequences of one-hot encoded arrays of length `num_words`. We will compare this to a 2-rank tensor with shape `[batch_size, sequence_length]` containing sequences of integer-tokens.\n",
-    "\n",
-    "This comparison is done with a sparse-cross-entropy function directly from TensorFlow. There are several things to note here.\n",
-    "\n",
-    "Firstly, the loss-function calculates the softmax internally to improve numerical stability - this is why we used a linear activation function in the last dense-layer of the decoder-network above.\n",
-    "\n",
-    "Secondly, the loss-function from TensorFlow will output a 2-rank tensor of shape `[batch_size, sequence_length]` given these inputs. But this must ultimately be reduced to a single scalar-value whose gradient can be derived by TensorFlow so it can be optimized using gradient descent. Keras supports some weighting of loss-values across the batch but the semantics are unclear so to be sure that we calculate the loss-function across the entire batch and across the entire sequences, we manually calculate the loss average."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def sparse_cross_entropy(y_true, y_pred):\n",
-    "    \"\"\"\n",
-    "    Calculate the cross-entropy loss between y_true and y_pred.\n",
-    "    \n",
-    "    y_true is a 2-rank tensor with the desired output.\n",
-    "    The shape is [batch_size, sequence_length] and it\n",
-    "    contains sequences of integer-tokens.\n",
-    "\n",
-    "    y_pred is the decoder's output which is a 3-rank tensor\n",
-    "    with shape [batch_size, sequence_length, num_words]\n",
-    "    so that for each sequence in the batch there is a one-hot\n",
-    "    encoded array of length num_words.\n",
-    "    \"\"\"\n",
-    "\n",
-    "    # Calculate the loss. This outputs a\n",
-    "    # 2-rank tensor of shape [batch_size, sequence_length]\n",
-    "    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y_true,\n",
-    "                                                          logits=y_pred)\n",
-    "\n",
-    "    # Keras may reduce this across the first axis (the batch)\n",
-    "    # but the semantics are unclear, so to be sure we use\n",
-    "    # the loss across the entire 2-rank tensor, we reduce it\n",
-    "    # to a single scalar with the mean function.\n",
-    "    loss_mean = tf.reduce_mean(loss)\n",
-    "\n",
-    "    return loss_mean"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Compile the Training Model\n",
+    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays.\n",
     "\n",
     "We have used the Adam optimizer in many of the previous tutorials, but it seems to diverge in some of these experiments with Recurrent Neural Networks. RMSprop seems to work much better for these."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "optimizer = RMSprop(lr=1e-3)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There seems to be another bug in Keras so it cannot automatically deduce the correct shape of the decoder's output data. We therefore need to manually create a placeholder variable for the decoder's output. The shape is set to `(None, None)` which means the batch can have an arbitrary number of sequences, which can have an arbitrary number of integer-tokens."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
-    "decoder_target = tf.placeholder(dtype='int32', shape=(None, None))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can now compile the model using our custom loss-function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
-   "source": [
-    "model_train.compile(optimizer=optimizer,\n",
-    "                    loss=sparse_cross_entropy,\n",
-    "                    target_tensors=[decoder_target])"
+    "model_train.compile(optimizer=RMSprop(lr=1e-3),\n",
+    "                    loss='sparse_categorical_crossentropy')"
    ]
   },
   {
@@ -1571,7 +1441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1592,7 +1462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1609,7 +1479,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1620,7 +1490,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1640,7 +1510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1662,7 +1532,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1675,7 +1545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1694,7 +1564,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -1703,7 +1573,7 @@
        "0.0050792360828931325"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 64,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1719,7 +1589,7 @@
    "source": [
     "Now we can train the model. One epoch of training took about 1 hour on a GTX 1070 GPU. You probably need to run 10 epochs or more during training. After 10 epochs the loss was about 1.10 on the training-set and about 1.15 on the validation-set.\n",
     "\n",
-    "Note the batch-size of 512 which was chosen because it kept the GPU running at nearly 100% while being within the memory limits of 8GB for this GPU."
+    "The batch-size was chosen to keep the GPU running at nearly 100% while being within the memory limits of 8GB for this GPU."
    ]
   },
   {
@@ -1732,7 +1602,7 @@
    "source": [
     "model_train.fit(x=x_data,\n",
     "                y=y_data,\n",
-    "                batch_size=512,\n",
+    "                batch_size=384,\n",
     "                epochs=10,\n",
     "                validation_split=validation_split,\n",
     "                callbacks=callbacks)"
@@ -1749,7 +1619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1864,7 +1734,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -1875,7 +1745,7 @@
       "De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.\n",
       "\n",
       "Translated text:\n",
-      " you have expressed a wish for a debate on this matter during the part session eeee\n",
+      " you have expressed a desire to speak on this subject during the debate eeee\n",
       "\n",
       "True output text:\n",
       "ssss You have requested a debate on this subject in the course of the next few days, during this part-session. eeee\n",
@@ -1898,7 +1768,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
@@ -1909,7 +1779,7 @@
       "I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.\n",
       "\n",
       "Translated text:\n",
-      " in the meantime i also asked for a minute's silence on the memory of victims of the atrocities that have been committed in the member states eeee\n",
+      " in the meantime i have a part of the house who have also asked for a member of the victims of the terrible victims of the tragedy of which we were affected eeee\n",
       "\n",
       "True output text:\n",
       "ssss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeee\n",
@@ -1932,7 +1802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 68,
    "metadata": {
     "scrolled": true
    },
@@ -1945,7 +1815,7 @@
       "De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.\n",
       "\n",
       "Translated text:\n",
-      " you have expressed a wish for a vote on this question during the vote on thursday and in the end i would also like to ask you to pay tribute to the memory of a tragedy in the case of the victims of the various member states eeee\n",
+      " you have a part of this debate in which i have had a request to speak during the debate in the portuguese presidency as a member of the victims of the tragedy of which we have been victims of this morning eeee\n",
       "\n",
       "True output text:\n",
       "ssss You have requested a debate on this subject in the course of the next few days, during this part-session. eeeessss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeee\n",
@@ -1968,7 +1838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
@@ -1979,7 +1849,7 @@
       "I mellemtiden ønsker jeg - som også en del kolleger har anmodet om - at vi iagttager et minuts stilhed til minde om ofrene for bl.a. stormene i de medlemslande, der blev ramt.De har udtrykt ønske om en debat om dette emne i løbet af mødeperioden.\n",
       "\n",
       "Translated text:\n",
-      " in the meantime i would also like to ask you to remember that we have received a silence on the victims of the floods in the member states of the european union which have been particularly sensitive to this debate in the house eeee\n",
+      " in the meantime i have also asked a member of the members who have asked for a debate on the victims of this type of attack and that you have expressed a part of this debate as part of the spanish presidency eeee\n",
       "\n",
       "True output text:\n",
       "ssss In the meantime, I should like to observe a minute' s silence, as a number of Members have requested, on behalf of all the victims concerned, particularly those of the terrible storms, in the various countries of the European Union. eeeessss You have requested a debate on this subject in the course of the next few days, during this part-session. eeee\n",
@@ -2002,7 +1872,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
@@ -2013,7 +1883,7 @@
       "der var engang et land der hed Danmark\n",
       "\n",
       "Translated text:\n",
-      " there was a country that denmark was once again eeee\n",
+      " there were a member of the european commission eeee\n",
       "\n",
       "True output text:\n",
       "Once there was a country named Denmark\n",
@@ -2035,7 +1905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -2046,7 +1916,7 @@
       "Idag kan man læse i avisen at Danmark er blevet fornuftigt\n",
       "\n",
       "Translated text:\n",
-      " can you read in the newspapers that denmark has been sensible eeee\n",
+      " read you read that the netherlands has been sensible eeee\n",
       "\n",
       "True output text:\n",
       "Today you can read in the newspaper that Denmark has become sensible.\n",
@@ -2068,7 +1938,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
@@ -2079,7 +1949,7 @@
       "Hvem spæner ud af en butik og tygger de stærkeste bolcher?\n",
       "\n",
       "Translated text:\n",
-      " who is by a and by the powerful eeee\n",
+      " who is a of the and the eeee\n",
       "\n",
       "True output text:\n",
       "Who runs out of a shop and chews the strongest bon-bons?\n",
@@ -2162,7 +2032,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/22_Image_Captioning.ipynb b/22_Image_Captioning.ipynb
index a134116..d5782f5 100644
--- a/22_Image_Captioning.ipynb
+++ b/22_Image_Captioning.ipynb
@@ -55,16 +55,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -89,15 +80,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from tf.keras.models import Model  # This does not work!\n",
-    "from tensorflow.python.keras import backend as K\n",
-    "from tensorflow.python.keras.models import Model\n",
-    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
-    "from tensorflow.python.keras.applications import VGG16\n",
-    "from tensorflow.python.keras.optimizers import RMSprop\n",
-    "from tensorflow.python.keras.callbacks import ModelCheckpoint, TensorBoard\n",
-    "from tensorflow.python.keras.preprocessing.text import Tokenizer\n",
-    "from tensorflow.python.keras.preprocessing.sequence import pad_sequences"
+    "from tensorflow.keras import backend as K\n",
+    "from tensorflow.keras.models import Model\n",
+    "from tensorflow.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.keras.applications import VGG16\n",
+    "from tensorflow.keras.optimizers import RMSprop\n",
+    "from tensorflow.keras.callbacks import ModelCheckpoint, TensorBoard\n",
+    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
+    "from tensorflow.keras.preprocessing.sequence import pad_sequences"
    ]
   },
   {
@@ -117,7 +107,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -139,7 +129,7 @@
     {
      "data": {
       "text/plain": [
-       "'2.1.2-tf'"
+       "'2.2.4-tf'"
       ]
      },
      "execution_count": 4,
@@ -407,12 +397,14 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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xjYkTD5YJkpl0gk2kHIOQioxOIuzkPSIS8Jb6F+LlF6Z5G2P+FPjTv8fxCavWBqkyxpww8TDMZvBEuZqEQyLr0rOMVGBwHQtbCoLAS9542mGzx2Wm9bSTJoCOTOdZAUamzDjT40EYiKIQaSUvzfMdvvRqieNDj3Ec4PkWi0vQG3iM47Q1nQyI0+4o8bmZoCxzPK0NlqWSiYccRnkYLAQBJk6kgXzeIgw1GohjjdZpxKI1xoDnBwRh8rx+JBiHcGG1ztUFyWAE+4HD5uGQyEiOvRAnclnICdbWFd1NQ7tjiGWMZRLJKhhJjF+iUDUQ5/n40SZ9L+DJzpjd4xBEwoYEEiENWhi82LDdHrGwdI0rq0WOu49A2gShjx+YdJI26FAQDuHaq8sIMeLg3gk6Mox9hSECBbaIWahXKbiaUlnw1VcVD54Znu1KAiUxJsAyMWGoQMJivciD3VM68xYmtsB2WCrabLfHqLyF8SRKhOTyEssOCEawdzSg8GzEW2+9xvFqm7sfPuRbX3kFRJLPWF9ZZGtzk5fWbjIIfbZOtykNXaoli3b7lM3tfa7e+BqtXI2w8h62c4A2Vyjm58lZBXK2i9HgeT7t0Yh7DzfxvJBHz+7zcLdN5AxxiRFK4PkQG4M36nPU63DtyjwnP3rA00NNrSko5x0GwwPqrRZJhtNKgEyEANiWTblcYuPSFf7p7/weJwfHvP31b3Lh2mXmF+cpl8sIaWGMQUlDGAXUG3VeevkOn3z4HuBy/dotrl+7xPLyApV6hb29kFqlgq0cIiSN4hzXX7rDq195m+ULq1RqVaQUjIdDup1TDneeMx71iYh5trXFD//6uxitCf0hOvTQBkwcYTBIYRBGpL6kiQNNHCqEdEBYWLaNVBKETGQNTKJT68RDkQKdShVaT3NhetafRTIxEMeTHKucifa11mghQSf3IyfST5JonWDDBJhJtWwzkV4SVm0mGnqmc8+qnlPiCFOhJv1skgkoCRrEFNR/jv2DJSxftKTD05/TiEenYJR0XiZpmPQ7iWVJjJGTxGZmQiQzneNIhLAJx+ELyUrzeWmCF5g4BlsZotighTX5fnpwUi1gtEXkwWk45rN7Mc15qLoO3dDneC8JWY1OgMik2rrWJg1nzYT1J0k0MdELW80CYRDjawsdS5R0iAKT9oMmDEOQEikVUgqCQJ9pU6fhaBga4kjw8HEHr1Pk5Zs1VhcsNvf72MSY2GLoG4YyplSqEAV9kCEgCGXEgx3N+vNjHj87xLIa6Hyf5rzL+LnN1u6IUSgnbMEWGscBLxAEWvPTeyMODz8CXiKkgOWGkGqJiETK6vs+3b5L5yRg+WKBpVaFrU4XP0wnS5M4bXvoIWqG9VaLl64s8/KFEZtPA/7kx7sM0+SR0Um+4qVLa2xcq/D6apV/Un+V/+s//g3L6y5P25tsrOd5eH/Iy6vzfO32KlbOo90asrnTYZsH3L70NSqLBazDj3i812a9WWP/qM3y6jLVWh0z9riQK7DjD7j3OKKas2l3bbrDI3KbJ8zfqBG6TfaOA9YWbtAZjglNiB/E7B2ecHDc4bB9zP7+DsrJ8ezgkPlba6y5G2x/9gGWowmHBktIpBHUyk3Wag5rzQI//GiLp89HrCwGHB+cUKyPQAvCcESuUkXlbYyOsC2XfD5PrdHkS1//Nbyxx9zKAvOLS5RKJZSyyIReIWJcN0+92eTNr3ydwAv46U8+5tqN6yyuzVOrN3FzFiUnx1Jrkbfe+AoXNy5x4coNlteWqdQrVGsVcoUc2hjCMMb3feKXbtHrdtk73kdJi7/5/vdAx8j0PQmhmF9YolIv0zlt0z44Tu5HCmxlUXAL5N08ruNiWWkBghFkNEukyX0NhDrVkGd8OpFDxAyuaGTKfjMJUsgpaUp8Z1q5lMbhZ/xekeJ0Kq8gE5I3PTRNWIqMZk4niMwkU6Y/0WpIK9lSNi/SB/jbKlt+qcB7VqqYaNWp/DHJIqc6tslmuhmb6ObG4EchQkSJ3KFUkkrUZqbtz93BjFRjKJZcXKXxA8NgbMCcrXDJQNdSIeWihRIKx7YZjTT9ETQaebrukHEskSLRtDOmnQ28s/edRB5ap5pcEHJ5vcLmZhfXNXgBBBJ0bAg9jdYS27LScC/LqqfAmOl1KQswGKJY8Px4jHwUk7NsIp0nFj5WJLBDzcKyg12SjHyDMQolbYTxaZ8GhJ6hNW9TLth8tNXn7r2Yzx706AyTUa5kwpzKBcNc02VnTzMMAzqepu4pNp9sUWpWyOVsbBUT65kMvJGAYtAdEMYNLs6tcvR0hGGEEEmfhyImGAuGBz0uv/wq5YLDUaFPrWTYPQh458kRpBNX0bF48OyA/+G/f5t4aLj/+AH/6ndv8Bc/3OXq4iqvX7nE/7L3Adc3Nrhz9QpXNlYIRprToc/GpRZW1OOg/4j8nUV++oNt1herBEHE7n6XZklSqhQ46BR4Y/1NBuoZlfkyVrzMTz/cYn55nuP2CcIbs3T5TXwdcdxps7p6kcOjQ0aBT7d3jIk8Xrp9i08ePaW+VuX67bfZefwhURAz9jSOsIhMTHvc5/27n/G1t15le8/GsUsctA8oVxc43P8EY7pY8YBxGHD91d/FOHMpIEkcJ0e9WadQLBGGMZVqiXy+hFRWMgJN5ggC23IoFcrMr67ztd/4TS5eeYV8Pk+5WcEp1iCOyVWa3HjlDRYvrOIWi5QqVcrlAvm8S87NI5WVSB9pBBiEHsVSCZV3Odk9xLZzxFGUSoIWzcYCL916idUrF7Adi7/8k/+Xo6MjfM+m2ajTahSplguUCg62FEghEQhiUkInEskkNiapjEKAUWmuKmHMKq36MFnykGluCEhJ1NQHbTmDusYk2reYkjqDSSJwkUwmVlpZMsucdSpdZ7KngLO+nt4bejI1TDw281UpE9Ytz+L+5+yXBryVksRxAkIyTQTYtkUURSlYMtGJSHUvHRkQKnXyqfQhhAQDQWiShKcCM5MZNz9zVktm31zOIQx9bGXRqDsE3og4Ai8MJ8dls7eUFvUqXL9UIOiG9LoxeycRpaLF/Ycjhl5Sf6JSnW1aUiWTwUE2YWssqYikTiucHLrjkJNOhBQw36yztX2c6HmpxKYz9g0oqVBKJVGIjid3CaTDN9HeIh1z0rUwZoQhxrKgUZLUy4IokDz4rI8XaywRExmQwibA0Pc8yp7DwO8zHMdsP+0zGiqIo8lzFRzNzcsVanlB93REPxTYQjAYBTzbi6n5Lo2qpOhanI7ShE0ahoZI8o7h9Vde5Y//9IccePFU70+KjChVXJbnFzk8GnFiHbLSXKWhAr7x+hKf7pzQiTWgsKSg4AwZjUJ80+fOnVW8WDIad/k3v/e7/Pi9TYLI4+7mp4zjTS61a4iwxsmpoPhBlfVWmeXmMouL1/m1X4v48IMnNEt5nmw+pf76GjqqYKQmb0HLWWYUQs6tc+fWVTSLPDr6MZeWlhn2NTBADzrsPdvm/uNHxCYkNIZCocLRqUekYawsBt4QX4eM/RBvLBjHGkcpyjrH6xuXeLLd4fvvfYjKxRhTIWdXUfEuo+4p/cGIxY2XkW4OISOMsdEqQgibXKGMnTMILXBcOwn3Z0rkEnBRWMpFFECqKrbt0JhfRxpDuVrAsmxiLAolsCybylwF20kqRSzbTiZ5IRPJQWikNFiYtD4dPN+n0ZhnrtXi+f4QE4NSJRZWLnP5yhVWr2yQq5QpFso8f/KEJ0+OcWyXcrlIsZgnny+gpEhr+iUSpnkuS6WJQIPRSSJQi1QSyaJ4MUvxzoqsIgVuyVQOzXxSJIUi6fFTb9JIlBGpVyUgm0XqRoA0aUWLnmJFjJmUD2oESggsmeIQOpVZJHGK+kZOgf0X2S8FeGcVH1kkodP63SiKZsB2ynhtW3HpUo3T4yGnnYDYJAnMaSUJYEwKdPHZROaMNJIcNv2stSYIAqJI0+8G5FTMymKRXm+AF84ydpFhC3GsGI0Na6sF8gUPa5DM6ENfEeto4jBTrSsdJCJJ4AljKLiKlVaOQkHxYHOIZ0JGEWzt9pBC0316RKzT+tT0nrM+k1Kkk1n6DAmvx7ItDBCG4aSkK9KG094QZVlIKSg4ikpZMZfLc3g6Rlk2gY7QRiAUCOEjTZ72ScDtmy2Oj/uMBzFBAEEcpc4vyAnDxQWbt+/U2Xna4cJygZN7QyJisPKsLFpU8jmOuz3maw6dYIDWcqKVR17IxfU1NIJCxaY7DEnWsKR1PUIy8EM+29zhrVfXGQ9dDo7GXFmuce2i4vr6Dj991CeyffqxxSgwjD2PRj3P0sIGm9tP+bf/9e9QsOf58Pm30XlBbBQbG2u89eZF6pUKH3/yDv2dHWJZ4I++9z1ydpV8scizree8du0Kr924hT/WzF2waIUNhLdNHHs0Ivj46CmIV6hVY1Ya8yw0FrCF4KQdcPXmVfr9IdVOJUmwCsHhaY/9k1NyrYDFpQs0l6+zsfEK777zP+OFPkEkkI7h+NRH2wGu2OXaimHxwiK7J1dRzohaNSbC59K1f0m5uYYJFZZrEcZDIl/i2nmMACU9lGOR1S5MwPuMA0qkcsjnBLZyiEsCIQ2OayOTwn2kcpMJwBiUkum7l6TQl/gvCVnQIpn4bdslnyvQaNW5cvUGz55vJt+7dVbWrnDx0mXWNi5QrjdZnl9k9cJFbr8W8vjhDrm8g5NzUbY1qeYAEi06lcmyiv+M5Rpmi+uST3qSHEyJ0+SRRaq3J5JFMilkCnTK1lMmbCZQnUb2kJQoJlAwkVNkBuCYJKDMzk0PzPAjNpqsgDM5agKEE5KaRBRn5eAX7ZcCvJNyvKRgc7ZkMKsOeTFjrBScHA+RwlAq5Rh5MZDp2uZnADSTqqHEZitTzsooUZRID5HQ7LdhOBxg523EOEaIKWPXJklsjD3Ds+djykVBY6mCPG1jMGzthmmUINLFDMnQlnL6EkU6cEysCUzE+oKk3VE8P4qwhCKOQ7QUxCJbxDNTVXNmQKShlgAlLaI4Thn4tB43e1iDTMJFYbAciWUUv/eb1/n2f37EZ7s9/Mhgi1SaMiUs5VNrufT6PsTgjyV+4GBEouE7Ima+7rCyaJPL57l+pcbdR5tEMhndYy+gUKyAFfLK2xfRP27z7MhjrCVSJdr6URDx6aMx9fV9Ij0GbKQIJwknIQV+pDnp+Tw77eCPAowf8Na1lyk78JVX2uwcfsj+MFk0FfuCzcf7DBfnWZgrsdpaZdlt8Vc//pRc3ufODcHyQoU3XrmNaykOj0N2jsvcv3fMa1dcvvJyk44RFMs5WgvX2NvsMAwMcRQRhRbzF27S2QnJl+p0jzdZcdv86N4WzrVbBAGYUKItTaFcpFydw4/aFCsjAn+MpXLs7e0RmZj19YusLV3BtjqEfkylYBMFPjLWxGhikWMcSWwn5tr1Gp0+1MpV5lcWsCyHnHDoH32P4z1oNS9TKV/g5PQR3mhApbFMsbTAyBuzsPESqlCZ+FoWmQogW1iCUInebCtcW2BUEsEKoVAKdOoo0kx9ZoKpk/qB6YpXjUIIi1wuR6VW5dqt27z37g/J5eq0Fm8xN79ErTlHszVPtdGgVCxRrtYY9Dzm51YwJsJx7El1SJwlEmUi+QgS0MyqbDK/Th4yAeIkFhPolJgpmdyfNpm0MpVJISFUk4cSTPTvSaPZ32Ya0SbPnMo4E6yZgrBJ+yXpb5NiR8bup5PNrDSj08Vj6IhfZL8U4A0wVT2SRJZS1vSBZhOJxuAHyQlxlJS9GRPzov49y05na1InVxGz7UIGhFnNqtFgREB/LNHjJBzM7mF6vk5WVhrFvccR9nYX18Rg2Yx9nYhWOklESkm6oCJLcKRsAEFgDH1P8OxRQBxLtFRgAqRKygEzyWeWLhlIRkGadHEdhWNpwiApa4z19BmzRKYUJGWFQK2c47U7Oa4vlVjdKPLNYIVnfzxCEqW6nEIoj4JjEcVQrEV4oxG9wQg/TPq7KBTrCw43L+eplWz63VOOOx6D8RihZbIYxRh2D2N+/esWx6Mhc0s53qTJ+x+eMIiSWt163qJS9nn6fJ/2SYDRAiE1wiiEEug4SuQvBNu7HbQ5pqAb5POS2LW5sDTHt95a48/ffUp7JOkNxpx0N5HFE+5+MKEUq6wAACAASURBVOarV7/M886A3ZNnrK9XuXxrjkquzIOHD7hytcYP3nlMNw5orbssX2myuLzK9t5T3r97TKPUwrc7fPf9D1lZ+A0GI6gXK9Su/QbFep5G7wYfffcv+cm99/jJ4wP+u996mXK1iG3ZjMMQIR1220GyrF3Z/PSTh5wO2+x3Ne896fM//psLjLpPsfMhhVxAO4qwlCKKbKQVMex76LzGskqE0YjVxS2ODiykvo6yO/iDAyw5YCSf4/UC2id7VIp1jvdWaDtNbNVi4eLts34hZznfFLxi0tUtaUSltcCSyW+sNNekMulRZjmLFAjJGFLKwIVAWgrHdqlUa2zcuMadO69y79M95lpzbFxYo9Wap1qr4+TySZIyl6OQD6jVWgg0hXyerHBbpKhpdHaFVB/JSExCS1AZRKaVaAlLTrdSSPWQTObI0mY6jRZmlNcEA5iulMxkzqzXkqZMqsObJFo1YiLBkKrhOuX/L5JHk6g8k0jFmETqScobk36M418R8BaTxMELxf/Z72ekDx3H+EZjtESTlBZKqSba+JRNT8H5RQDPu5I4johiSayzao+Ze8BgTFpXLhIWO12dmbSskAgjkZZh5EeUyREqODzwpyuvhCKrIc1CKamTlyrT+9IG7MBw/bIiJ4t8926HQ99OsNlojMhKFvXZyQODIFkY5NqGoqPwpSFnKw67iR6dhWc6GaUp8zd4vkbGirmKQ66cQ5RLFFyBkiZZYYmmWbH55u0q9QXFtdVlHo17hDwgjgxLRYuvvjnH2qUCXntEt+1BQZJ3FdJWaBViRZJYag6ORlhijstrEkeN6QwF84s2g2cBWIaya6g2PI66Pt7YAiIEEitlSVIYwijG05LQ6/DGnUUc6VKqzpEvl1jcP+ZVYTiOOzx9NGS1XKBk2Xz1+mssOuvs7nZ4sLNNvhLyZGufSFWoFnM0GxFBKKnUczgyz531iywtLxKFhkKphuLbGHNIpEK6gwPe/ewRv92sYZHHNnlCUceEx1TLS3ztQoNqZYFqroayCggliTyfe5tP2Xy6TaOaY+/4mEe7z1jZWKH+0kV6723j1m7z7PARZRPhFhQlx8GPI7qeoNWoUM+Xqa7V2T3YplF3GPR7jIeGuQWfQnGOUfcAZTyOju+jlM9oaBgNJXa5RvswoN5ssuYLisUk6We0wRAjEm1jhjqnviLlpHZZQJr7kOlhYsI8ESIp8UvPzdh88nPK1LEQjk21XGZ5ZZlv/vpvY8J3uHxxiYXFBvVGk3y+nMg2roWlbCzbJcMs27aT+m2dyE0Jf5kuYU/uLamJFkIke/hkUUD6lzQmTWKKyf0n2nOWzE/8w6TJzwnxNmYyP0wcjozcpTgzWZQjJmCujUFmi8fS8GSSLJ0QxnRx0CR6Thh+bCARVDQCjY7/geq8/772IsDOyiWzwJ1YhrLJQpRpGJOFeiKVOD7PxiF5Oa7rEIUQT3ZtOiutTIpb0uPPZowFaAujNFKBQuNaeXrjIYHvJBsvCYVCo4hSndtKl/IaYpmWS2XaOYJxGBNT4uqlCtcur/GH377PTt/DCxVGKiBMJosXQj1MUuvt+4JS3qZRUqyV4QefWAyiAFJdUAg5YekY8IIIbzCiWJ3j+LjCSfsud27l+HTXY+DF2AYqymG+JikX8tiBTVFVeGl9kbduxdy8uszalUWcQLO93eNjfY/FpTI7T9uoOMTSBiMtIGY4ipF2ActW3Ly5yPbeAxZbXeKRYjQyrC8WCHyHvd1n5MpVrl7I8+5HfTwlsXXqXsrh+HTM3pHD3U8Omas1GVzsUKs1KLl5WrUqF5clb760Tt2ts+Z2WTQFHmwf8r33P2QUjTkZhqxemKO92+bes095bXWei6tFqvU8997dYr7QpBv59HZ7dDodqsUqX/3SLdaPd/ju9z/i/Qcf0Cw2+FahgMkNefLBx1xYXGTzYMTuUcjRyWOM1uScPJYrGXgxR6dtCq4mCEYEEdTqNa7dvsX82pfYvP9/o0wLhA3GZ26uzt7WNvWiy9D3adTq7B94jB1FHDt0+wN2j4asrL9Fu/uIfl9TzAe097sUiwbXKWCMpOuNaBaT/XPCaIQQEdrEaBmjhEIYCyPjSd4mA+YMsKcMMyubE5N9P2R6qDRn1hOSLU2fYF1KXBzHoUiepeYc4qU7FAsNwiCm1WpQrlaTCJtkBbKyks3AtC1S4jODDzP+n7HmDGSThTtmAqQirdPONO6p4JFEB8YIhJHotDLFpABKpnOnzi/P4ME0yYvJ6sDPxvtm9rPRE3ln0p86jbYNqaadPNnk+ulnUpIY/4xy5ln7pQHvWYkkC/Mzm2XMZzdjSmbVSZJhktScnvfi5lWZlDIYjLFtibIswsB/genPdvnnP2sMWsXk0dRKLrmaSzjWDAObgCgJ0XSMEYJIKGJho0SEwiCFQmiRJiOmJYdhLDjthRwPByzPS/7L32nyw/fbbJ9E7BxGKZPhcxOaSXV4P9IM+2MCbbOYt4lFUndoZFrPOtNHUiaVAGFs8+lWl62DHzE/73KtUmL5bo8H2xa+NlTKMVcuX8WyDI5ZoD2+x8qlmGalQKkJ7aNtSu48+502uYLDwVGf3jhPoRxjOn1iYhQaL4Kdow5Xyk2Gox43rzZw9Cm313MIxyHvCPa3PRabBaq1kHeeRIjIxlURsUjq/LUxtBo1VE4hyhatDZde/5BRL8dCs4xQFjeXlhmZfb51YY5YXeM7Hz9iu3fI2B6CLXj6eMhJe8Qbd2oszlX46NERCw8l124s8E++coHnz3vs3j+lIgfo2MHkbQZDTckKaNaKHDPkrz95h/pCi69/8w7zoy42AbFluPtoi3/+rTcYHI8IvRFeJDg4HWLbNhsXl3i+d4yTK7OwUKKYe8an7z3i+voyxbLNratvcPDse3iDIRJBp6fRONx7vEm1kUd0BI5UNGsRebdKpxNRKrYp2wVOBnsUyyVqlQJF26FQiBBOgdH4CQVVRblFek9/SnCySGXlOgO/R6FcQswuK2dGg/18GVYKbGIy9tP/ksgwc7b0ZymmIGQEIBWOnaNaArFsU2nMYaKYUrFIvpBPgFDKhCEDSJnq0glITrXgRPdWWQ7JzAQOMoFgmW4QlexBMoMT6V/ZxlXJVkeJT2fSSLJhpZlKp5IJrmSSyexeLmf65owlYIwQZ5KeUUwa4RuMSGrKk5zO5BIz/08WDYXxr0DC8kWb1i2/sLkNPwO8JskHOTl3mjT4fHUJJMnGWIMtRLIjXcZAXgDI2Wsmk+50MFgabNchl1fculImCiSfftZm34+I05ImI1UiP9gxc0WHXuAxJiaKDEGQVH9k9+ZrxXCkUXmXnUGXX/vSa6ytDrj7YJs/+tNjerF3VpObNSHQRnJ1ocb+sI9j2dxZdnj3yWkywzNd2QUpQxCSz7bH9LyQcXDMG2+tEntd1pZLhKGHH8LlK3UC1cXEFs8P77O+qgh1k1Zjlb/54C5YHq9v5LlzfZmnxy73Hz/n0dMTRtqka8eSLQyUE7O9f8R8o0CxEtEozbP0xqv4wyEjO0bGMVJ1KeSXePezPv14gMlpolChjMHoGNcBJQbk3CKX1he5uHaNzn6ADmGu1aA9OOTa8hq1/Ar7PYutzimm1ufmYhUrP8/i8iK12gf4BxYtO8IuSbo1BxHYdEY1Cmj2D99j6+AUN3a5fLnO3tEBW9tPuHRxHmXtMw4DVG7EX737PS5dvkC1VEa6BU7ah7zx9lU2nx2yNjfPcDxC2xbdbo/5hRauXaTdfcbmzjHz65qlBZdgLDmJ++x/9h7tk4+5c6NJo/yYouuwNxwRUaSUy3N5pcbQjqnnR1TUAvd3hixsPKfsRig5Zr6xgAwjhFa0B2NsJSlakLddoqhDHL/L3tZH2M4izrMNYkosbrxN69ItskUunx9OnydKGWAnTN0QZ0m51B9E6lcCUnDNVjgKLOEgHENJ2eSKBnSMm8un5a3TTeIStptovonUN8WBSdJdJqV6WVQMCaBnWxdnKVMpkq0oJvq2SPXndF8RoUBqyFY1IlIZY/q40wUzM35DKlXKibZ+tp8mqztNVgqcbPsb62R7D1KGb2au8SL+J7tdJuLJL7JfCvA2ZLXd2fJWMZ2KRDIYpgx6WlI4yVkYMDN68GT2xExqxrXOOngK9J4fTwZKhuBZOy++DDGZRiVSCOo1WKlZKCR373a5suZQzBuUTHY8kyi0EFQsya+/ucrGxhI/vnuPJwdDTvoayxLE4XRmFSrgsCcxgUukOjx49BOWWjdZXlBc3pDcf2Yx9uMEiDOnmXRTIh+FUchCrUIpb/PmrUUeHPQ59eOJ9mbSvkxCUEMQWrTmCvhRwI/+5pBCMcAYaNZzXF6pU6jFbB8d0yyVqZaKFJtzPH64S6/3gBvry/S8NnnrEn/247+G/Ii5Sp21RcXms1OklsRKkZMx1ZpFrZjndHhE1yuQU22ODgbML+TpHg0oV1yMbbF7PGDU73LnYg0n7rC1G2OUwZKwulDhxvUiV67P06heRFllAnmIIcC28riuy/OjArlimXvHH5FfqlEZz3F9/SLv/PAjtp+fcuv6bT4ZbPO83eN0v8dvfXmD9z494od//H1ev3EVJWp0fZ/Yj8ifjFhs5Qm8ER/fe0S5lKNZ0wx9j6PeFu99+BHfevNlCnnFmzfXuHntOn/x7T+n19knitc46vUwJsJ1BJ3ukP3DAwbemKvVMvcfdhgeF3j91Vsc7+0TFnscngQsLS3y6N6Y61WXfKlEXveoNdd4ZTkmZ69yOHiOddillm/iyJjOuEMQKzYqawzHuzw9GFMsSBpVCCKPnKNRwmXkgRFHWCcfY+XK9Ep1WhsvoUWU+IKWnxv3cFaunBAakUF1AjrZsrBsS9o49T2ZOSKJlmukjVJgpzFglqOSGXCnJbSZLq1nQH2yh0+GF2m7WiTVJNmEkoGwSBOvIt2AKtOXE4VVpsckWn5Wn40hWY+RTTqZlGqy5Ga2V3zaHzM3NHtfevIn2e0yIdIzerpIk5UTuekFLDRxOhkKXlyd+aL9UoC3EALLsgBDEMRJwT1Mk8kTtIaJ/J8lDlPGnM3MPyvZmbU1/T7Vm9I38OKATcD9LGtPAD7R4Quu5MpaARPGXFhocfjZPoOBZhxYWJYhHMdIKWiVDHMFwcePDzgdnXDSNkhpI7WXZKfFDMvXilEY0OsNqLdyOLZC5k64c2OVWsXiB++f8ud/3WUYKRA+GBuIJ4zFGMFpz/D164usLTmMRh2WayV6u12MTJwsq8gFkuld+SwuzDEeBawtNXj/01OiKODCtTquHFNwHFx7hB/A2KtRGcNCM8f+YZuDky75Yp5nR59w6WoFN1cDz+XRkxMco8i5IUGkubiS5+UrNheWXFTFZevhAc2WoOcPGOy0UcJhrtli99kR+yc+zZpLre7ilBY47rTp+RGOA1KMWFyuMe7uc38QEQnDheIcRyc9qrqBFDGhEWztdnjaCRg//Qzp+DzZ3mNz54TR2OHhkzJ1O+anj09569oyhUKB197IkUfy5oUN9psxD57vEpdDqk1DqV5mFA2xc3B82Ge+nsOLXdonETv7DxiPruIWJK2NS3x6/zm9coODJ1u87diMT7tcWFnBsRVbT/cxTp5YHnNyOqQ3CujsFPj4sw6h7/HKGw6ed8qjzwZIDDlLMNdUBB4YQpx8iXGkKdavcOtOwOnpHqdDH+EqVDzGNA0PnvbYOT5ldb6B60Q4ro0fhBgzJjaGaq1I92SI55cQ3YCNQCNshUEj1dky3ckKYrKEJCljmPXBqX9NwfbMbh1YIt0ESrzovSlhS8E2azdzcyGShSwTBUYyM3LNtAUjsi0E05Y1kvQ5JvuLTzXtTCrKZBDS3yZkeLpEfXpL6VYWKbk7mxOb2WJDpNG8Mek+Q4k/muzqafsZS/+cKjuDUdNadZFuY/Dz7ZcCvDGGMExSzCINaZKvpxQ76zg9m1Ke6YGfp4vPHpetwvx5mpUxSQSQ1EbPAPeMdq6UwLIMA99AIJirVbm97LFYDGkXYu7GMWPboMo2zYrg8kIJS+Q5aXusr0S8+vIKf/Dv7zPsR5P2Ex3MULByDIM+q/kCo77mwuuvs/Vohwtrt9g7+oyluSGbu8nOgrPaPoCQ0PHH/D8/uM833ppno2XRC/rJG9Yg0iXE2fMIASqSeKMxfhBzeNznwrJLvz3GCXM8b5/ypfUq6yvz9Lo+sRhw2B4zHkXEjHBVARXbGF0k7wIyQlg1lL2FUoKlOZtGIHjzVhPkgEahhDaKuVqNueY83dOAfKnI42fHLA57FIqC4HDMeGThFEPmGgW++maL7/5kB8fN4RYUjfoyVdsnFiUe3vuE1qVbVGprGKNxLYVSMT/69GM+eP6IK80FNj8bICyP5SWXbqdPHHpcuXmZf/XPKyxX5jkc7fL6zW/RLO1TiHN8/OBD2m2NXTDsbXcZHoVcvdii1+7S94uE2gAROdchDDscHp1QKhfwBn0uFRbRtwXboceTnV1iIwl9H88L6A+6dHr71IsejrBxhEGHMf1hn8HQ5+DIZWNBEXkORH1sK48QGtsWVCtjhqOISDgE3pC8UyC/WOTh5gEysLlx/TW2n+9RLi2yf/cAIdqUShuExOw8P2Fxvs7CXBF/3MaxFaVqBc0ezx+/Q2v5JoXaHCYlJZ8rEJgJ22cwdoYBnPWwjEglnEhMc1fCkCjOmf78+QYm8osQ6epIkdZdJIcnk4PJFOXkNgxIpj6dYbw44xvTxKrO1jmmD2NMAjTJP+QgJr/LrgvJyu9pv6TSbArSWeRhdMbWRQrcs8+VJlRfeN6MgU+3ns7uNtXChUBYvwrgDZOdtIScgu+0NO9FsJ6JV9Jf/axEQvZdAsiCKIoRQqb/wIKc2XT9TFO8OClANlkmQyfUmqMTn4qI+cmDJ7x5bZV3729hVyW/+XsXuPfxEc+Phqws5/jqy8scnXa4cavKYDTm+eMnyfJaM40GIJFZysUxtdYKrabLwvJFBuMqFE4YRAPcgmRuzuXxXh+EldSdm2l0YExap+vGDIaCsBIgFJOEjJDijDMCNOsWq0sWyqpw77NjVmol3KUCroqQJUF31MeIEs3GItv7Y7Tqc+32RUx4m2AcYOk+7V7AOPRQQtIddhkFIKyQnBBUahZeFOITc9DW9IZHGKFZMAfk7JjV5TVC+gRaYLuKSxdddg8Cuh3N0tICN27mGAYBj5526A8Cvvvdj1lfqKPVNsb3qV26kPwLR5FHFAVIC476XUyUoxsbivUcgWf4Z197m62jD/nReyHf/5tH/NbXF9H1Y9rHHR589gllucDTMGRt9TrGPCTwDIFroXKC1ZU5eiGcfLrP2AspFivMNx2WWxWwPQwD8tUquYOQi+sXyfcec9wJaDWbCCEJYkE/GHH7pSaXl+7w/Q9/jI5tQk8z16xgK0PRVRwdRBz1xygkYRgxHEiqVYe55hzGdAm1g5E9bEdAJHnpxmU+/ehjPnnwEYYmsfKRWlIpl+j3O4SRZuBH7B+eUsxZIAU5u0g4bEP4EacHglptCVGZQ4tp4vz/Y+7NfiTJsjO/37XV3Xzfw2Nfc6usyqy9qrtJTpPNZQBSHEHSSAIE6UHA/AuaZz3Nm14lQhCgBwnQaKDRCMT0SE0Oe61udnZlVe5bRGTsi++r7WZXD+4eEVnVxcYMhwAvkHB3W65ds0g799zvfOc7v/7l5OIdEDCl0QkkV4+f+NzTuicXMswzg6vMVsxX+xUCZHy5bbrCnTGs4ymkcWGYp4Z4ZsDFRRhnctyEa/2maYinY7qEVK7kfUgmHrKYwaYXA7kwqhf9yxk+La7AI5dZmXLqNUdXntPsniZZlvIrNz+7pHjDEVPkjBIpJpr1f0P7uypA/O/c3tDYllOtgguP+aoxneFFs7+SRNd0NE17M5vw6nnTWU5VFDRNRdNmEpOTpaCmgK7M/twa0XQMAtAFmLOJQUyi4EJR0LWIUj5H1w14uH9Cz4559sLlZ784JPRcSsakAs3nj4+4ubXIR7feIwwtXp55pJIhujbBtuIpPl5KxhRLSYIgJJfJcXTc4/XJDkYyDZHF2uImq4tpSmkTpDb9Tw1C6CAnUqihJ/jORpl/+OkGY1ehVrCYz+moYiL+VMwYVLPKxOjHCnEETt+mmJLc2shQyBlksyblsko9XcNUTfYPhxw1xuimRsI0GLQtjITCyG/ieA7JtEfgDAn7Nof7L/GcgGItj6ZKEppKZzjEMhRcxaPpjhkHPo+fHxOrCp43pJ5fxXMjuu0mlWKVP/n9O3z4XpmYPq9ev6ZYiqmUTFYWDJLJFM93Thj3Je+uVSgYEhWNseMQ+jZnjS5nZw5xoGEakm7HpdUM+fH9Y8raHdZWTKx0zIvjAfcftNAp0HIsdvZP+emjz3CcQz7+pMT1G1ly2YjN60Vc6dI47XBrw+C//E8+oV6w0PU8vXFI0siQyVXZ3dnnvNsm6HQppOYpZNJUKgWEIrA9ySgKyZUrmLkyoUjSbPVJ6gkiYWAlTG6sr7Oz49IZB3SdkEHkM/JiZFLn+GRALlOg1e7Qasd4ToipOaixz/x8nWGg87rRo+c1qc0rVNI6i5UsRCr5rEU6o2B7Lm6Y46wd0utLXLuLGkcMO6f47mCKW0+iZEIIRCwmBjpW3vRqZjAHXEIAFy+mvNgXTY1aGMcTrFeIywIH4grLZebBTLdMPNkpBi3kNL9hdrnpMVf+xXJGu5tUVAqkIEQhQCGQgkBKwvhSWySKIYoFsVQntQFQp96ynIw1lhf/Jslxkxjc7DpBJAmiSfWlWQUnKaZStVJMizTMGCyXKT5vzAOzZygun+EsvX9SkAI0IVCFMqU9fHP7++F5C4GqXVHti2ZR5q9CIALEpFhBPIVAFDFJtplNXVcj2JOinjMVskkkW9MEAnVi5GWIqgoSpoEfhkxkRX0UqSClhqFE3L1bRcgeT594jAKNYhpSpoKha5w4Q1IJncFQong6KpJBWzL0FAI95lotief4/PzRHt/7dpV8QmdzI0MYjRnZksZYYCgRmxWTzU0VL3bRCImx8OMxTx8+QpLHGY/41qd38HyFTEah5bgQG6ixj6+5qMKYvCwixpVjDs/2UTSNdFqQGguMkcRKwvV5wXK1zs8fnXFux9zeSFGvqiwvvEUqdYSIIgrZJL1eSJi1UdOLNI9bNPrn5FOCSAievPgB60vXSFtFusMBSTOiaunsnA5p+hHtsYM6CshZKoUkyERMdxgiEi6jgQl6wNJSnZHTxx5qFGsLuMc2pWqdw5Mu19Zv8J071+gOx5wf/4ieH7B5XWXJKlPK1Hj0UHDQ67LXFtxZjVDtMbFm4TtjIqlydDQgnUnSb+t4oUJ75LF/esD1Gwn+9A9/h3ZjyA9/8oiFuQJP9vax9AF3Fwt8un6dZ9svkY7DUi2D44X0By2WVsqUSynSyQxpa4H5lVNevjxlfX6TdMbCLJk8397nsDHC0FRurZSpV6qkUxamkeTVyXNOGvt0fn7EXGWbMOqztVXh6X0XohSnzTG/fPSEQIa4gc9o5JMyVKwMBIqNlnQY9hJEccBRo4+iLWIInXazgVR00uaYtdvz2P6AvCVI52KS2QjLMun3QbfmaPdddvYPUXWTjYWAQpzAV16hJhaoKu+gxYKYSXIUIp7S5GaSCnLiHEwhhQln4AoWPmsX3uNs+wRHn8ELU4HWiVH6Cn4+Of/y50XN62nQa5ZOfuExM9l+JaXmjTjY5eRwiR8DF4W4LxPyounQ5XTEU1bLzEPnMvYlp+fPIOvJ2K5AJFOPeWZuL1CDSyP39QmPiV2KBROe+6SbycQ5YRd8zVRebX8/jLeUFxzKGad0ssyXl3XmePPGFVQUdfqHmPZxse8rutZSxsRSkEwapJPaRHM4nJYeilVkKNDViDCelP4iFphpSSknOD7uYBo6mWySftsmn7C4dauI7XXR4wJf7rRRNAVdhVwxRBcmkSrIhVlenPT5ZKNKpxfyv/yLz/jgpskffXeRt66P+KsfnvKTRw5z6QT/6Pdu07dPiLWI5eU8O4fnNDohqi7ZPzim2/Notu4xHI7xwghNaIQEBEJFRVDMmCwWVRrNMaW8RSYF3nBAKZfg1dEYJMxVLBbXNFQF8nmN9TmdSs7i5u1N/vqvd7h5fRHbPWG+ssaguU3CgNe7TzCp0RrbaNKgVClipVyOz18hZURWK9OOJZsL81gJjaDfYHMhjaGYeJ6kUilxcHKCT8xo0EVTU5y1YjL5gJWtEjLS8QIXFY9G0yOVTTLstmie7LOyfIP1hTmOTxtUrRSqprH96pR+PEKJNWRkMhz6FEsBqiYYSAUhIv7zP77BB+9f569+usPp3japTAqpKZTyFX7wiwMO9g/54NoimuJjCB1dBzNdotUbIMMh792wkGZM34fO8ZD9Z89J5i2kkuZHP3lMdS5NyjojaxikMmlkrNAbeZz2h3iux8Z8DtNMISON/YNTzrtt+qMOp92QtDHPxtYqrYZHLAcgfTQzoNOOCNyIKPARyqS4bqakcPeDdVRV0LbHjJ2IarZOOBrSDzVUdaJuqKkqsWfhDjtUygnGY5+uK9EiHUWMeL1/wmmjg8QkW4lwfI1cBJFzjjMe4QXgjbrYgUfSTGJ7DrWFeZAqMSGCgAtRK6Yw3/Rd+2o+xlXgcVIRL2YmkXdhUNUJRiy+Fpea2utZcG8KvUygivjCeAOXEq/yimmeefTy6igu6X4z+GTiSc/u4+qVpxDKpaTf5PhLE/XG/V0m80z7mk1cFzDmJRR1SbecBj9n50yvrV6ZcOLpvUyCrL8muHCl/a2MtxBiDxgyec6hlPIDIUQR+D+AVWAP+MdSyu5v6uuNZJopJKBrBoLJ8muWcTmZzeLpokS9MNxXk3uuUpxmwTkhVMIgRIQSA/CkgqoomGqIiCNGgYIqVCoZKFoSV4bEvokmIo4bPnGsoqiC037Ax2bIuqH0egAAIABJREFUe29VWUyscdS+z+tGnw1DYz2TJ79epGV36bQ0vvf+Fp+8v8qXe7v8+K8fk0rV6DVcLC3io/dqyGjItbUC5VKSzevr3H884PjUw480jEQHZwDXF7KoizH5TBotbXFwLLh3/4C9M4mHRsmCbFLhves5km+XsWXAWWtEpxVw5oCuJlDVAN93iGWa33p3CV9E/OgXpzSciEK9jRsM8KJ9tm7O0zxrEyoa7YZCQmbJlPK8u5xFV2PMVIFuN8R2YxwvopBL40cd0pUiXfsMU+iEImIulyQjsmyfnKKZBgQxvhPgOBG2hO3TISe9MSvVKsgub229RaaURUY69+49pZJKsXf6kEZnTN+OMBH80Se3OMg7LHTP+dXLXfJLVYaRIB+5KHGEbmZQo4BP3vuAZi/g54/22byWo9FxGfcc/of/7ceETsBHd/IYlsPifAUtq3De7HHcG1AqKmRygjkrx/zKW9zf2aWFTbPtk7Bjmr1nDIchheJ11leWqFkriFjhaPsI35dopsl40EUIjbNODzOZoN0fcnj2Gl2Bufk5UqZB82zAsxfnpPQqg7GHIVWk4+N7ATExlq5g6ZKllTkC12bkKQzHMbfe2oIwIqma+GHAefsEIU3uvLvOw8f3cH0T2YxRQot6Lckw7nF4opLKWCwZGmHo43oCP0ozRKeWmmPYa9D44ofo6TQOOn0zjRdINCEZ2DYL8ysYljblW196gV/NeH6DlTLdPilDeEGIm2C4TPnOUw9Vnb73MybGRQLQ9H2OpvtnCTtvRL6uiMRNSSXTgOWMpjgLIIKcpq1fMpDFZZLO9PfMu75MzOECvpmtAq7CHxesEcTFPV6M5ddRSaY7L8EUOcXyr54963uKq38tzPlm+w/heX9XStm68vufAn8ppfxnQoh/Ov393/1NHcyyHi8fwGVAb3KTUx74NIPq+nqB/mBEs+PhTYuzvFGZZlpFZsYVnTwulZwVc3s9R0xAoxlx2vZYXkmztWDy8kWPnXaIVUgyV5MksBiMHK4vFfm3n/do9mJEpOHqAd7IJEeVMS6qECjonMWCT5fmeLzdpVA2efdulnE8YPcgImOV+P3fukZBKZPLmXjKgJPWDp9+VKCQKzJfSXJ4+hojkWfghDx/1qA+b7CxmubdzVV0kaOQyfH69BWbywZJVcV6fsrjZw4biynqCymSGbixZHFuOzx71eW4CbvdMQQx9RL89m8vk0/ZfPbkMQm9yPqcRTodIaJdbq1XWVtYJRlDX0B+vsCjox9jD2OKukY5VFFzWfaOGoy8IVIz6HaGZE2b1VqFoOtRsAzWFsv88tEZiThAXwwQZop2s4eMPaycyTgQpFIJhBrx0c23iRWPB1/uQ9TivYLF6VEbyxQ0BzbjUZswnOiNv3+rQKNr8+NHv8ANAyLp8vzFIbXrm6waKXrdDlq2Qr1a4fGjZ7hqwEcfLpAJXJIpF6EbhJFPHEO1mAOhc3zucnjaQ1Mc5pZDVFKsb67RcuCLe89IqiqaVHn77QXanTO0TImbNwp8fm8fRYv5L37n9/DGA3Z3XzJ2XDQFajmT8XhAIq3j2j4Dd8DIHVKvlcCQuPYIbzBmONbZGw355E6Vo4MIVfFxAgdVhaQu0FQNRUkwV19h7/UDMqkk427I+aBHrVJGU8EOVLQ4YKG4wivjJXFKI61GdBojAr+EpcRkkiOa4zYiToIiuLZVJpV5h/mtjxCqx/joJeHJl8hCgqG2xeqdNTy/h0JM2oJu94RqYoWZdO83tq+ksssLoz17p6cByJl4kzrT9bjU2kGKaSV1STSDNYRyBTqd0BonxvZqYsvMys6Mv7jgnkdy5vBdWBpmsUPEDI65Gk8TU+G22f1MDpxNUbOP2QpEcnHp2W1eTioTHIerD2Zy/PSZzBxRcXno1aNnT+1van8XsMmfAv9g+v1/BX7IbzTes9l7JsA02RaE4aWEqpwUNVBVqNYkn96dY9hX+P7PDumNoiusi6l+QBShqBPYRJkGAK5vJFlbiMmmNMRahr+812QwdBnZIbfupOCJR3MUkVzQKRQC1tc0Vms6eibHaKyz/bpJr5Ug9AN++WqPlJXBHXtsLaokVPCdmLEdsf1oRC0t6KNQyj9EJc2rgy61LKxpC/Qdn+FIMpBHhMGQQspCMTQ6Y5vWmYLQNZ4fuRimSrnQ5sZchVhPoBllPP+I73znOqV0ihvpQ4JEzMcfFpnP51CDDKliF8dxaLUaGD3IZlS++2mJcsZma22dH3V20ZWIb7+fZqmapD6fQSh5Ds488pkA21PZ3d9DCSxuXMvhuRH7p22SYw8jqSPikGF3zPJclpP9PpVCkqHjo+hJ5qrz1KtdSkmLTMpgruJy/foCr3ZPMWLBWNXQEhadfo/zsxYvj7o4bg87GFGslsiKNDc2cnz+8BnX16u8Pmtzd22La0ubJHJlHu095uhszHAMScsljPpEMqaQz+EIiWGlaNlDlhYyjAenGJkMtypFNjZuIDIp/vKHv2R3/wx3GJBIVCjNbbBYNRkNuwgjSbVQ4/7hA+4/eMbqfAWpwoPtU0q1PF5zTCa9hRe8Iq+XqZdqFOZKJPt9QvZREZTyObJpkzgWCGHhBzYHpyNknOD27QXG3SYrtRq724eMBiMictQqAcNziakbaEIACqGIODlosLRQJGMUWFpd4NnLPSIvQLgFHjx7gjBV6rUqP/zlI/bOuviuQcVIUk7nOG6dUMzopBKSo7ZHZXGBclognBGKecbL+z+mlr9NbX4ZVUQcHZ6gFWIMvUi+UObk5IClpQ1iJhIPTAv9Tt/WN6izkyYvaIKzd/ArbzgSjUnSTECEwkR/BIIwQlGUyWp6FtyMp0p9s2LhQkziYMpX+pUTL3WmZXRhQeWM0je99mw8V2CIeFa4GYGc1tCcJQ1dHfelAZ4a3atoC9Ng5MUhl8fNIPs3oRkx6/VizDNvfrbnknfOhVf+Te1va7wl8P+JyZP7n6SUfwbUpJSn0/1nQO3XnSiE+CfAP4GJPremCyL/TcqSjBUieUnbieUEKzvfs5nPCuaXTN7ZyvDzL7sE8VV6YYyhK4RxdFHR2UpK3n9/g815aJ0coZqS5brOLx477JsmuuXz7fct/s2PBpw2VColk9AfMLAd6ss1eoNzMpaBoadZXiqBFNz74hQ9GXL7WoEb5Tn2Dxqs5LPcuJ5ltTrPo/MvaQ4TrCuCrVIFT/PoxQckkxU212rk01X6rQ5u2EZRPW5upDFuFdjZPufFzhAZxby/dYeO7XKwv8f8Yh0oYiQV7tyZw0r1kJqJtPuU5guk0ikOTj3K+RIfv59ic36MIUw8fYjA4vikwepCBstMcNZs0LfBsBNEYcy9z15QKWhsbN1kPAY/lrx40sfMFtg7DzFaYyoFg80bGW7dqtNtNPH6gqHd56zZJlcpc3rWp28HmLLLTaPC6s0CGc2g2T5jtarjihzPX/apZ/J8+4N3uLEy5v/96U8YuDZPXzzmg7e2KJc2WF+ZI9RDEqMEHTcgUc0ydAbEiopmgm3bbKXrqFoWIQPKpXWOWk16fQ87jhmGCd678y2cbh+ZtLj/+AUDT0eTKglNJW0W6A12CeIWc5W7PHu9j5Uu0Bv0iOMOd99d5eB1A8cTeE5MNB6zuq7zev85yWya5fIq5WoJX4HdvQOcUOJ6LrVkAoHK2A4xEpLOqE8yZaEYLrvHuyRFTMaG2rJKaX4ezYP3ri/w5/tP8cNgUpA3jkjrBtfX82Q8F6EYdI9OSWsWdUuj1+2Qy1ucd/qMXA+n3wYs8gWdTsshbaSollMIwyTjuBSqVZpnLSimKCYg6jUI5T6FvIPrrGJV3getjaV7HLx6yI07n1BfWCCUElUxmUAM0+xFZjDG117mC0/y69tnxsrFHboYWgphRKiGShgLhKoTTOuaTqrCS1CViZa1mCqHSkCJJyyYK+MQykTVUwhBJP0rsMavN3pXJx0hxIUtv/C05Tef+5vaVeDo69TmK2O4+JzSHa8qHsqrXvsMefjm9rc13t+RUh4LIarAD4QQz6/ulFJK8SZh8uq+PwP+DMA0VCnjywoZsynrAvWZ8T8VgaIqjKVBoZShdxKyfzwRL7oa/DBNnWRSBRkyGAVEsYIGnJ2fcm1ji/LiEgcHh6yu5Nk+ijk+9thcSyAU+O3vlPjpZwM6vYjNhRSKZjEe9Vldu0Vi2aDZfk6hUOC0bTO/WMB1bJZyOhVNIXezTMyI9bcTFEqSd8vL7BwdkqgqbK7VuffE4bjjkc3tUatXSRgVCEusr27xxYsnKIbkV/fPqS/m2Zg3+YPfWaJYucXu/b/g4OgM1/WRcYJrt1c5HewQqi7FpEkmt8kvnjUppEc43gDNsIh8j3zeI58X7HfGBHYKy4Ruv42Sy1HKW4RqTKt5iqXDJx9WiGVIbVHl0V6Pw2aAKSW6b7O+nMG1Ha5dK6EqWXSxiGufc/tWkVKpwsvdM5rDY9xAJ5FJoFggpcrYN1Fdh6pZRMQKi/UaS4UiB7sj/LHk6avXzC8YLCVU7qy/zfL8Fs1Bh2o5x8iPsbYsVrNVdJHm9PiMcnGe/iDk4xtFuk4XU08QhoLeeEQmVeDw9Bd8+tZ1np02uf/qEH9koyojNFXDdR2yuRIrGwkWCgp38u/zYrfD9v4uw0FEQh3Tc1uU65v81U/vIaWgXMqhel3++Fsf8qvdL1mYS/JkN+T6+tsoSQNdxJwfn4JQ0FQF2xnT7nWp1lcxDcFx85CsBQuLSQJ3QDaZRpguoeJzejLid79ncnzYwfV9YmI0DQxUNCXJyEsTC4PQG+IO4e33PmDv6Akjp4+uTrSuA99j2IsRuomqBigJSTcIkI6K9GwMTSOfWUWGXRzfZBB2ubFe4LWdJtQLZJI19rZ/zGjgE5tpRPQMnlvU5xYp1tIgYdBvkE5mUQxt4jwpVw3dpM2W/b82SW76oQgF12nwen+PVGqetZtvgwpxGGKPRpjJBNKLUAwDKSLwIgxTodU4JV+qTwOgl+wOyQTi0EVAvzsgkcqgaBNe9IXJucDE38Tjv5nTLi+CpvLqeVODKme49xRSuUqYuXgks+DjV2EULoRjL79fYMOXY5kxbZQLL/6b29/KeEspj6efDSHEvwQ+As6FEHUp5akQog40flM/igBNUSbes7yciTQlJp1SsT1BOPW6haLgumMePdYZDAZ0xzFRPBGJvwh0RJPyaYapklEkg4HADwLGtseTF69YWU6xdXMJYeu8PPJ53egSudDzJVrgsLokGZyoiFIey4xQYxW785qNzSX8jiRruCy8XebwwEDENhiSXjygmKuztDmkVCwgEKyvLTFXzWAKneOuSigC+u0Gtq/wbOeU9z+8jnSh2/FpN7t4sU+tpjJfUTkfxPik2T7Yp9VrkjEGmHoeT/o8ffEae9zmxubbtNs9/GjM3GKFoROyd9Bkfj7PykYdwjZqQrC6sczwdIimZtjbb5BIBGwtlhFCgzBLrIwxjQDMKppZZnP5Ds3mEwwrppRNcG11hSCM2T/ax4+PSWo6VsLivGnT650jFRMhFEp5j0w2hecanIxGbD/f4fdvv8M789fohscIByrzCwyGe3SGO6gJB1UzyJsRrw9O0fQcxXyeUehgmRqN7oDnrXP+7U93uL97wngo+Wgzz3vXlvm/ftki9lMkEmmSGYNhd8zCUp5ybR7v+WNubKyzfdjmrD2ikC6wvlikUjWJozwLpTXaY51fPP+MYibDrXqOeibJ/ihi5+AF5x2bXDqJUAKu3azRV4e4QUBnZJMgYHN9FUFMgCAWBp43wHFGLGXTVIpZKsUczX6fj95e4VfPdxic23x46zqKZhNoWdbiLp/MWfjS4Lx9jutNCmx7ro+p62TrJkHS4WAQI6I+dugy+OUPUZIqFiZ5NUkq5TISMNACOr0m7V5EOT9HojyPFG0yUUTDHaEKBdu1qWRLLJeu0bX7VFM36YSC5sE+vrdHrngXJZHHShdYWK4jQo84kqhaBNJn7/Ur1q7dRCgQywiBdhGmAybOlbj6cxbQZMqYiAnRyFfqEMRoWoYgGOIPPdrNE3Q9QSpZ5vEXPyGRKFNemeN854zVzQ32nv2S1bVPKayUL8oahk6AYWVACQj9EU8f3Oftu9/ByE6kLSaww+S6F3RCOcHXA9cmiCRJy+KbvOxLCH9y7lUJ2iuEkjfudWKn5eX1LkDwmQd9NY43M+DTFctVeOabnfavtX9v4y2ESAGKlHI4/f4HwH8P/D/AfwP8s+nnv/qNfSmChBETRrPlkySOBcvzJrdvFPjsXoe2G6FMK0yYegrbFgxdFceNJrldV55oGEhQJzNsPqXhORLbjTg79kmqMd2Oj2r00DUNT0I+pfPl8xH/9X91m93tbYplneNBwOsTh4HQ2NpMkKJAr9GnWq6jKRGGjFhbW6Nj+5zsnLH4VpGm16aSS/Pg0R4D16ZSq5LNpMiYHuOhS6lSYCGX4LDVRWpZvny4x1K5yO7en5PJWYDA6UmUqMrdD5fQlTQvXj6BKECIBMPBCZ1ehB2N+fCd27gDwcnpEFUdk0jUefayge27jPwDNubLrC+v0x0d0+j7ZPQKb92pIRIqZ91dur0Ra6U7jCOXJzuveP/6Gs1Asn18RgKNWkngRIJifolnL4+ozpuo8YhSIosftZBGAn8wRhM9AsXE9zRqOYvBKCanS9brCXZ2Bxy2DmmgkZLQlsf0xl0IQtKhYKNg0QySEI4Y+2eYepk40hkMx0SBy717h6ytrHBwcEhnOCarZfj4zl3UGFrnLoY+oFgs4kYRzrhPJpunXM3yH/3hd9nda7C5eo1K6ZCjZpOT8y47B8qkIrpM8aK1TzVtYOoBbihZNAvEgcFKNSL0fGxb8vaNZYqJDJ6rcWP1bZ7sPCel1sgkEsReyHg0mGhQGzqWSFLJ51icX6YzDjB0ncHQ49vf/oDGyXNaRzaJvMogtNlcnCfhKXzx4oxGZ0gQxyhSohkGlqXw4d1Vxq5HMRcRBAqtMxcSGsk4gxy5KEIlynkYaopc1iIMHULFYBwIwiDFcsrFEEkGcYCZgq1FSSVbpN3pUKpvYgPNxh5VyyRd+Ah0ye7OA65tfouw3aV3fkTX6qNaBt3RGdlUDhFpoEgUJZrqUl8u6+UU9lDegCUmok+zSusydHC9iKOTIwrFTZJViHyV2vICmlYgCPq0Ww9YKn1K+/AVTneXRz/7jOG4zatRkvcX/wAUA+mf8Oznf42RrZLMFqjVUgRuB00HVejEMpyOKwY5mWSEmBaYIKB98ppYprDWV7gICX4FLpmt+2e5nuLS3Z7aPi7u8aLNvHwpr/y4DGy+6UNPsX05USh84+rTsmpcTHzf3P42nncN+JfTmUcD/ncp5b8RQtwD/rkQ4r8F9oF//Ju7khimiXDdCU0GQUKJ+JPf26JSUmg1A375tA+KQhhJekOXwdjBCxXC6Nel3ao4dkS5lmS+AjL0OGlOkkXeyikIReX03MPUHLJZjWROMh6qPHvRIpvW+dadd/iZso0b2vRcwZcP+9zdFGzl1/jRkwfcvHsLf+AR+i0ODg/QswHH/RM6LUE1q9IfeFTmMzijPgktxpU6oa/gReCLGCOZoWLYbFTrtE7HzFWzeHFIr+OTTyssVMs4scKXj15QLOrMza8x6jVZLlT5+U9e0e72eLXbYdh7yUhCvVzi8cOnOLZGZ+Rjh1m6/QadcchWLYU96hEXmjx7bXM8PCWrL3J83mK9GmJZAfWVAr969ZrB2EdPKSzViqxWM3TsEQmzS6HgoysqQqqEboSGj6IK9GRIJB1yaRNDqAxtScpQ0GRAtf5bbK6GRIFD1w84G3v0hGAoI6TsUIx04oTG9nGPUkEgFJ8Xz/e5diNDPZfkZ/c8tISJiLr8x3/0u/zk8TO2t9vEmHT7L7BkTNIwkYqG7g3RRUDGsvC8kOHY5bS/z95RH+mPWd/cwLI8xiOXdj/C7vapqPDpb2/Sdly2jySPz1qcH5wyd2uej99b5vDxKXZ7iFGxMFMG5+cdVtfrpGWZlKoSDAe8evgYV4KuJUgqIYQBL14fkcoVyaV0PNfny0e7LM9nsbKC2IlYMExK5gI7Z00yiQTngxGODNFCnXQaNm6U6I17fHB3mUQseH3SpVxW0Q0d4Ub0FAdIMwoNko5PvpLACRPUshV2G/vk9Dbn4zGtdoxlWSQjUJPznJwdU66uMRy3UbUctcoCnnvM0OtSSSygBR2C0x/TGT/EHrnkFtcYqQGDsYU+d4unDz/n+u13JhXb9ZlE6wwamfq5V/Wur7BIpIyJvRGvH3zBoO+wdb2K33cRqoqipZFKhK7DWx/9IQ9/+pf4Tg8/ylCplBCJCNOKUOMIKcecHT2m03uJGTdoNZK8etKjvngboRgE7ohRu403trGdiMXNdTRDJRIS23Uwhc2rJw+4897vT2qwxspVkzw1mFNv+Upw8dfBF1/VTrqkCH7NTE8VSS+3TD5miobi4jiudiEvx/BN7d/beEspd4E7v2Z7G/i9f5e+YgmjsceEGjQhDH1yt8RSUWIkdbY2cnzxwiYmwNBVVhZMVCXk8FRi2xJFVYmi6AJrEyLCdXUi6fPhh4sQndEbhuyfKGi/jNjYSmJaPhtzNQyZ5vjoBZWMRtryEa4gL3JkVA3HD9Fik0iq7L484/QopOlERE+fgK5hqiZpM8nd27dZW17n5d5zjg6GtFoDbMfh9lsl8rkE4zF0ul1UQyNXtLB0iZaoUcyvEGsnHJw9o1LJky9IKqZC82iffGWRSiaN73WxlCp6cg7XtsjV04zaBgMCcrUNdh89w3f6dAcxhAGEGoPumGo1hab6qFqZ0pzOy509NjYNGlIwDIdUSik0ZYzv2uiaYICNUcpgRhPNi0G/jTIYU8lWWZ1f4/BwhzGSTDLiaDiioMNiTmcQCgZ9l5EdMF+vsncwYuA6PPs//2diV1IoJ1Eil1CDfDFNHNioWkgHF+FlWK3rXH/7LV482SadMxiP9wjCEiSbVBMq9XyJuVJEyXIZ1xdIGUWWbrxD0kySzWbwnT5GEJFImQzcPocHJwy6PTrnLpbpkq0l6I8OSJtLvHVti5OdQwadDrX5IqHU6Yw8uudDTmMHPVZYV1KkzRIrNy0GjiRbCHj4YIdYuizd/JS59CpxFNDqtfAclyCI0AUTiQVNJZk0KeYSuE6PhB5hRh6vdjusF+YoqyaFwiK9gYsSRrw+b+AEEXEMmohYXs5Rmk+xf97Djm6wslxm+6yJO4aiWSNdztDsP+FoPCD0NTZKOUa9LgupOp9+9CeUX/4CEcU8eLmPUBUUmSFr6XQij540SYg+UdREGSfI1b/D7W//MZ2zDs2jnyPjc/xRByu3wsmoSUls4vT7mIkUneErNq5/CGqAqunIOEZBeYPKJuUlXVdRJkFGgSAKfQQBJ8fnLNYzHJ0cc7DzlOPdh8yvvkWyuEjSiBHSRLdW2bz9Pv/6X/yPxOMURG+zsHWHa+98gqOA6vexj7f5eHmeUrXCo+cPkLpJ6I54ef8zkrmAvQcPIWqjG0V07Xv4QUC+VCAMI3rjI1zPJV0sIuOQCdPkKo59FbcHvmpQv24Fv/L56w75inGeXOUy6UdcbnvjerNNf0P7e5FhKWNJHICiKkgRYpkqN99RKRTKBGqMbgywkgZDN8TUYXMtQVINMWKfTjdGxiqgTGrqiZnobkQUmhhama2NgCcvT4g0j71TQbMf8/4HKSLPoDq3hJV6RTGvc3raJa0m+b///B6uaXP3wxpOZ4CZKfD21g3+9V/eZ9gfY71Vp5JOga4RxxGhZ/P68JhXzx1evTihmDV5fdLj9HDE4koaq6DjjHz2jlvM1XNkDFhb2eTYPmJgt/DGDtXF65zH+6QSWWLd4OXBHp1xkzCSFMolVFw63WOGMWSyKs444PP7j9CigHo9g9eQCFVh5Hn4UUx6qFBO1Qn1MaZZwTQS/PDJY27cXOWL7SHjwRnC8xl3fGTGYWUuz3Hbo5RMk2REmAQ7adEf9Dk6O2DsOBgygjDGd4e8PNEYFPMkCgkU3WW+VqLZ65IvKDhnEmEZdMd9hp0YK6tiKRbjUchKoUTbPWSxVARN5+PrdznqhVSKOlbSpFaZ4+CwSbmu0Wx0GakRWqrO+3ff5sW/OqAXCWqpIndvvYs9OoU4xosjhoHKWbOJSEQkcynWlg0evGzxR9/7A1r9fXYO2hw+fIzlS4qpLC/OXvN2cp39/XMqhRo/eXBIXk1y2Biipi0WF6scPX5KKX+dWr5LqynY395FVkzk9dskqkXY3sfzIvwoJAglo0jBCCX5dIpTu4ehCTZKOUIrjSIFWbOMp6bodlt0R01e7zZwPTAUwdx8ivc/3mQYxgQnXU5bPRYrVW5e38B3XxH3I7Lzi+StQ2yG5IwU/ZFNOpNhJbvED77/QzaXs/SiBulkkmIhTas1ou0nidQSpfkFIkVnYeFb7L3ewQlDtr98RG+8w6DxgES6TGd4xF4njVZe56TbodHfp7y4yPrmXeoLN0GNJqyOKVwgrhgmAcQyRFV0xqMhvh+jCQVFkZyfHeKO2jzo9Tg9fMCw+RQlUWVesUlZNqPz5zy992MGQ4VstUAkTFKFiKHn8urJl/gnD1hduYNwmnxnLY/EoNXdw2yfcNpqc+DcY27+LUZaxPHOEdlsluJimVcPv0+zccLi3AKO65G2Cly78QGRCppUpxi+/JoBhwsCzfTH123WLNNUzmghV1gsM6AkngIvk5jkV5N5ZiuT2SUuoqsX33+D7f77YbxVBWIlJo4F1YzO+jWTUBqc9XVOmqeMvQELtYAXeyqKFLT7NktVnd//B/OcdU45adpMMrriiwekSGi3fL7/F0+5806NhKmi2RORGtvx6PUSHNkNCok0lpqk3fIxpI6vR5y0+6xsZfBHCdzQJWWaJIoL/Gd/WsS3j/nn33+Afh2ub75F+3iboK3yg0cveXqtG9B/AAAgAElEQVRwzM1NCzXKslCPONmzOWt60LNZW86ztlbm0bNDapkkO/sHoERsLBUIhwnOWzuszi/x4Mlz1u/WKSdSJJ0cg9YhvfMBpbrBabPPq6MO2bzBabNHIqMghgoHp31CKVicL5JMB+yct8gWkzzf2eNO4hrFap7cex/z+f2fcHp2RsL0yaUV/uj6Lf7iya9ILa7TCyzKxUMyCR1V89BkGidqkTdVqlYaT+pkchWOj8ek0km+6Nn045jOmcONrXWyusuN6yXGdgrCPRZXc5yfpfBci/aoyUGjS8FI4hUdNtZr2AMQ0RjXMTlrHKEaCsORxzC0WZ8rs3MwYDDsc219hSCQuE6HhBbz4Ok2n975Hs5on0gmGds+2WIJ7/wMxw+Zy83hij7r9QUOG3uEg5i8o7FqrnBqDygVAmyhkaPM7mmHRsvhwDnBdVSsYpr7O8dIExaX51mcy1JM92mqPrY3ImNVyCQ0gkBSrNWxg8/puz6qquK7Ll6YxXZc0tkMet/ETGQYNXos1Rdo9xx8U0XxbOI45PC4gS99DCHJJXQSOQs7jkCMyWWK7B8d02nvUUnXKCkFur0OD+/9gq3VIg3ZQYsUSqUcG4UiYThgNDjm0YsjNm5vslRo4cUuiuojgggZ9ZF6jtagR1ZRyKVz9DtPGIZDhJzwu+v5VVphQLYyR6NrE4UNPEdDUap4tiCKHFpnffL5LEY6QRzFqNNEOKnECGFeGB3LUmkcPeH+Z59RKFbIZYsUCll6pw/x3R5SXcAwYkbNMWqij6qm6HZ30ESC0fETdDfDGIX49DF//O1PKCld+iefsfP6lO3HGbrdLs3+MYVMEmGY6JVldl7/NaqaxB706fcFsTcilzdJqS4n+z8jn9ZRtTVODpaItBfML6+TtLRJoRdmWoZvJiLNUuhnqMfXJHNnGP/UQCtCmWSDEqEQE3kxiqqgaleqWMlZHYJvLIsFCIT4m4sPw98T4y1RWKslWclAfkmwtlWkcTbkXH/Cq8OAclmwup7l1X4b00zihwr12jwDt8dmNYHt+DSGPkKRk2ruAoRQCaSgO/R58qxJJCI0zcCPHOLI4OW+jVNVuKWP2FjI8uy0R1aRZIs5PM3mYH/Mi90+G2sZ5usajYNdkjnBsN0h8gRtO6ReX+Hlkyb2eY+X2+d0YrAsnYyl86t7Dn3hMW/kyZViDpoDKlkVS0/gSqgkPJrdLs2+JCJAS8OZe4xnTirflFIWod3Dd3wCc8xpa0Ck27xzpwhxgpRl8ezZAWMR4AuBlUxw3OyjqAaFbJLADdHSgub+EV5/SH2rTiGTxtA1kj5Uq2m8KMnc/AoHowEHp6fMV3PEWpaDozZCH9MZ2DjOGasLyxiaRfNowM6rLgtLi2ysJThuDNEsaPZPGKsxSyt3OT7fI1Q9LDXD7c1lHj7/kpyaZOFaim6vyWjQY23lOqOwT6FYodHrIBWJgooXjhm3jpirLIIy4PZqnsBp8GK3ycJyDaG32N0b8+T5DW6ul/D8PsNgjK6miByffMaiMd6mvrBEoz1CjRb4/MkuViqgogW8PH/MzblblGt1vnz+I1KpDLoK5WWLfthDzwZ8MD+HlUuxs7+D4/QxhM7m6m1c/x62d0DfX0WJQ8IgYP+sxaDXolKdxw4DuiOXhfocnXYLzwkxlBQ9YdNo9AiJcL009bkqL1694uCsS+xHLJdzRLpBFBUZDmJKlQyKfkolnyajJlAZMzx3yecUakmLSE8QhpJEwsAVMXOJNNJI8iffXeIvHvyIw4NdtmppBoMRpkzQ7g/IpMckhU4yVydp6fSHI5bX3qH9+gWuCMDW8dwOamEDNZHCkE1GTgdDL3C8/1dYhd/h0f1DhEgi43nmEmvoqkYUh6AIFGmAEqGGKtsvn5IvVuh7Ln/wj/5T4tjD73XodxtUSzUiV2JaGmLcgcHnnD9fwY6GLGz8DloYslIc8vmXz1Atne+98wmdwzY/ePyYw1YLW0g8z+HWShVyY1q+Sz53HTsCpVBnuaKS2W9DnKaQcUlGY1TdY6iWKCz9FsnKIl3XRag6ujWp8zpbO8TfhDBfQTa+Kjk9q7hzURJNRghFJ0ZFBCMOX7xkZfMtpK4TE6LIGKFcCufN+vkqdfFSCuXvNknnP0jLpBT++Hsl8qrGcceh1xlipnR6Q4VOf0SjFeH7OqgqPiH9fsgPf7yPrkniMZRy0B5BLDVUYhShESuSWPgkzBzDgYcfSuI4RBEKpglGAOvZEkvFPPuuTRT2OOhF6IMxUkpsN6QxVogOhtx5G8aOhhRJQrvDh+9e4/s/e0Y6tUerFXB8doCiu2zMp3i23WN90URLJrD7Pq4YUjXK5ISk1XbZXK3Qscd44wRnjRGtYYd8MmBtbZWkkWQ8GmJoEWEAyYTGO+/e4PjsFENLMXYEo9YI11G4f37OXNnid2+WedXs8uK0j6GlGY5tFqopSlnJJx++hd3w2DvaJzrSUfQki6ubGGgMzlrc23/F0WCEkxCUSglSeR896bFQmiMaepyHKSyzzPHBCUZSo9V3qJTy2GObbDnBZrJKf9BnbW2FZtPj4GxEpbpAfWGJ4+1DVqp5FqpVWslzVKHwycffot0+nrAlIp9YaBj5NHK8Rz2TJxiPyS9m2Hu9h+tKcrUVOsMhTtBHPRKszYd0z9v86vNfsb74bfJzFQ5fvkSzFISRYPtZB5cu2wdDUCIazTZOF959Z47C2hzffe8tIjvJj7/8JQNfI1vIc21znSgasFYO6AzG/NZKjZHXZ//kgMValVhN89kXX2Cmstx65zbSzuL7LrqfoDP0KGSShH6b0cjhae+Ajfoynu+TMBUUIjqeBxmJlUySTOUIXIezRpvuwGG+mEHVBPObi3QGI1pNhWJRp15dQvc88qpFt99neWmdcHBOIZsiWzA57oBmqNwo11mrz/P59jZPD/ZIZVU0z+bZ0YhARMT+RMXR9SARnqIbeSItRa5Sx/ePSST79Brn9NwIvfi75NJZGuMAaTfwAoE7PKFSK6MqKU5eP6NYnidp5NjdeUK9vkoilSJwfc4Pj+h1Wv8/c2/6a0linvf9aq86dersy73n7t2395np2YeUuEuiacFUbCgRAgQIAv0lAySGESQI7BgBDAEJkCiwEiFWYkdwJMoSSQ05nBnOTPdMd08vt+9+zz37Uqf2PR+alJhNdoIY4PuxUEB9KTx48L7PQp555MWS04PP0fQ694YHdFsWpveYBiKXkxHB6jnOyKNIMoK5RlgcMA8W9DovY8/OWbv7Nt/98hs0tRI/vveYP/jeT9l79ct853d/F9sb8dPv/QFqtcNsGVC3NhBkk2Z9i/1bL1OWFgzTkFTvEA2eUAgJq3lIs2jhCgJaRaWqd9i7tvMzaZ8KRYYo/Mxa/7P5G7PNf+EdKJAECYqCLM95sYfJKTKP6cUBk/Mj1te2cGcDmq11MiQELf8/BHr9PArk54am/zfzSwHeJV3Dqq7xybOnGJmEa0dU2wqqBJWSilXLWS1lRlMHQ9PRJAk7jCllGbkoo8sSlq7gRwX7V3SkPCIuZEYzBUFNMY2MpSNR5AmyrGJYGesdhd31Eq/efANLH3I2HPPJeE6rlLPVqPM0yiicCNfJee+DM66sCWSCgyFb9Cc2s6nCX/zwPb6y28GWSlwWGRcHIfMwpVJfcGenzs1dlSeDJReTS37lrR1EpUpuZwhpmYPFGFkX2K9V2eru4k4XNLZrrHUkVn6BXKuxWF2ytfcyslTFX9icOnMaVYvH5ylhmBKkEanZY01WaXQsPjscERdQqSmUdBVFMejtdsnlnEpLpVbdIQgDdEWn1ttmYk6ZDUSePz/m7pUGVanL2cUKXctQsxyxpJOrSxJy5EIiS3Ik0eDZ6ZRtISdwc/IixHNFfM+lXrc4vzil09hi/+ZNDg7uc94PCYOAuzeuMDg/Q5ATsiznrS/fwfck5rMJ/X6B3Z/Q3tAooTEVFYxWwNaewfjDIbNlQuTN0NUy9Y2UsX3J8PwQ09TJ4hjX9hCMiCgaolgZBAW+F/D6eodnZZ9bazcYzRyGgcJX3vwyfPEUwyzx4OEx+zdStus9/s6v3uT7n/8Ie5Kycf0ah0fHPHowZGOnhJfD6UVIb7uG8TNJn7NYkgsK1ZKOHSR0um0G4wUUIVksUqs26LQ6/ODeE/Y3dtCVMqZe5vDwEQvHRZEldFVEr9SYLn0Wi4xOs2A+dTgeeNzdX6e1LnF+GaPuWtzu1lCsOs0336J88wqL/ohbr75GMJ1ROs949XqbzyYrfFEjVALITULNRYohEHJET8WMZ4wW/xuK0KEsjVCFGbJfoKslsuWY+lodlifk1QplUcApbiDgcvLwx0znD1nOOswXl+xfe5UiSRgNhpglgXsf/y/4yxE5FWqVOovpQ0pGlZIg8vjJikpJIBLKiGmf167qPDhOmS9TamJGZp+hBCLNjsdvffMdDEGgP13y4ycf8+NHD6h2K+iiw+efPyJyDoiTFrWtb1NoPyRxA3Szw5tvfg2tWsefPyNLY3xnhev5dOycakfHL27y0pe+g27KzGdTckFFSB1mE5uKWSPNUkoVi0IS/ipL5Rfvh/9XMP9rN2Sex7jLFdVm84WRKM9YXB5y8OhjSnod3xswPjvh4ccfc+uNr7G23WRl25TK1i+E5v2fWfbP5YL/Fk06/39NlIRYVZGSInMyDJCkBMezabdFdrs6r7/5MotZxFfeKvHBp0fMFiNeul1FzgqCUCR0czLB53Sa8vorXfbXK3xwf0Kj4vH23QbVcsFHpRnvfVSQ5BmKLGCp8Pi8z3/+T/+YliVQqUq8dEukZSh86eY+2pNjOgOPbUvg/S9clOiUim7hiiuGjk+QeexaBl//1q/x/v0PeHbpMJ2IXLuh8+r1CtHCptvtsvBdssxiOfQZzBIoEha2x+ZeBVOUufvyHexlQKXU4t7BJYamUjYUjo4fst7Z4Lw/YTq8JI8XKCWD46EDioK3iBgUcNocE4Q561sat642eP/DOaPLFfW9LoEvkmtLuusKcaYR+gWhL+EkZ1xprhMnEW4oE9o5o4HEg0ePiUjQNJWGoZMrAa90GnwxLTjo2yAXyPOIOMjoWT1Olpe0KxYHT45ZrVaohsm1/W2cuc/BwZCy3mU0esTMLXCjc25eb1NRC6b2nOMfrVDUnI2mSRqHpFWDdm0dexGReTpECqtZgSmYhF5IQsF2U+TXr1/lvb84xfZXNFsm1ZZF4L/QH9erJU4mfbJMZW+zTGe9Ttlp4AQeR5fnjNwZw8mUrY0miBaHBxe4ixSpFfG9j7//osUmnHH8fIwsCDQ2y8zdS6pmCVFIOD+7x1q1R47I0YPnlAwZ301wkoK6JlCvyNy8to4qZSRhQL3a4eZWh/7Q45vv3CUJIjzPo0gTOiUFBJlSpYqTpiB7XMxyKmaZN/bXGU2nfBJarNd7mBnYcZmrt+8ipjKbW6+w1QyI04Lq7Wv07IBnz4+YuQFICi21YLRIaXXbLJcuhgCuExELF5imjpofU1UKpjHEQkFeBKTJCWJ0E7mQOF74xFITOZtTZEOW/nPKzV1MVUPJSwRewHs/+CNWtkuj3sWy6giImGWTPBhRViPCxUO2uz0GwpxwmWGU6iSFgFl5G134PlbhsvJiRFHhtWtX2V1rc+/+Qw4PTwgym4U/x2gaWDULDZtk9D5pFCAq0D/6U5J4SatyhSwvGPfPCJ58RLg8pZLrJPGcOBQY+imm9iZKq8mD937I/p1X2NjfJ84TRKng8Sd/ipzodHqb7N39MoIkAuILV6QAf9Xr81fAmlP8rN4tJ0cQU7zxgIuTS8q1OoKSkyULfHvO2sYdWuubDC8ec9E/5sqtd2iu13DnF9hjD2NXR9Q1/vre+SJH/EUi4os+nn9dGYP07rvv/lsF5n+T+a/+8T949/rVKuu7XZZTl96GSknP+fJbHa5v7lAV1jgZDTkcLAidFTIhmlJD1wMUWaJRi2nWTCQFsljkdGTz6PkSwhzLTLm8DAkiWCyg3TDZ3syomSKqKRKkOWUzebEndgNmdoZVs6hVS7SaGd+4WSIhYXdrj3rFxLAkmlUFP14xs1NO+30qaoW9LYU33qwSuC63r7exfdDMEnvbPaQoZVNvo0gFS99B1mX2Nurcbq0xWGYsY4fVsmAyX7LWlri58Tar1ZKgiDi6vCAXVVRdI0pXLFchh8dLDFFByBNu3WlQb4g8eTjADyUkWWYxTvEdkaOLMVGWsLu9R7W6ha4KrIKYzx8MUESdDx48ZjxeoQoe61sCvb0CoyKQpDmJkNKqWKxmDqsgx9BV7PmCs2lMXVUZjMaMlwmqUuAkHnfuNLkYnpNnGaZe4eTkmIyU6WKOlEsIhcP2xjZSZrD0R0TxErnQkYWAellCKoGolFl6AZejGSQis8GEQtGpVpoUuYdpGlzd26VslPCWLrVKQUKNPPYRC5UwizmajtDVjFev7rEY5iSpxCpN8cWITqdJtSGyu3WV54en2K6PZbqIRYhiaqyvt5DSBDmR2Oy10BSD2A2RQxlL17E9h/PLgFf2r/PR/adcvbLOJw8eoyom9nzAGzdvossislQQp2P8BbRqBq3GGrvr6ywXC04uzpmsYqIwQdVUdne3UaUMXRGgkJCKHMtUcIqEwI/pNXpsrXXJiQl8H7NRI7joE4YSzvAUS9dJ5YRP73/ELHKJcyjyEFE0WTlLZFkiTwLKuoCqiFR1i40qtNolvjiZUjLWkHKJhtlgtnxCngaEiUSW+OTBQ+zQRhYEDKVEtHpGMD/m4PA9ZuPnRMszUtej29lHESXUUpluY4307ANGgwvyLKGkFwhSCS+Z4y9dxEBGM01EQyJyHa73riCmAj/80Qfce3yAviZR76psdZuoqkZJb9AtKwi5DeSIRURF8sjCCA2HxB2TZ0vE+Iw0OCX3fGzbQRIV5sYG+sYeTx9/hBLOWdkRgihh2z7VusZqNaQIbLIww0tkGp32z3oEZCR+oQtHeCGDFIoCURLJKRBFEPC5ePIALZeorW9SZAnnTz5jeDZgZYfAilm/T7t3ixuvfQVZchkcPWI+WLG5ewXEn1eCF3/NwvkFwl3AP/kv/7PBu++++3v/d7j5S8G8gzDj/sMjOt0S13d1tjYNJgNwJgmLcM61tYyamdGfTtnbNlktBMaLBVmkslr4vPZam/07db5UCCCV+P0//IxW1eDahk5Zlzk6exHCVKsKbKxFfOebt9HzHFmXmKxSbl1pUxQGD/JPWSssng6GXN+p8quvX2V2MWJrt8Ei9rAyhYpS52R1zv5mi/nCwQ3HjGc+t243qDRKWDWValVDkiSWKwc1lfny3Ve49/iCueeSZjEbW9tcTHM+PziiWTPYataIEpu33niJIMj5yZPHzGYRaslGkVQOnx1xdaMFuUKvK3N1c4uffnBOtWTy4NGU9Z6F75awFxFWRUYWM04vZgiySC6mXN93uHxwxtWdPc76fZ4PZhyPjxFkkZa1jpKEtNsN9GqV8eSY2WiGrKnM3AmpkyIXMlJJJSkMbCekKeaMfZFcCLm8CNHqJdJY47W7b2GqJU4PPyNLc5K4oNGpoSg666qB5Lr4SkESZHSaHQaXY8pynRv7PT47PsGVQhAyettrzMcO1ZqGJ8jsrDXwDvqYasGPPvycbmON89GKK1sNBCHGKBnEQUHL6vDSjsGN/Ts09BZpPOLDR0/xKKjVLfRIJ4lk+scDug2J1UJgu9cmL2SQBQylQJY86maF9+6NOHNcPC+kWqpS0nM2dxq44Yjjvo2kKax3t9lab1PWylSumDTMEtPFnDguk6Q+ipLTaXXZ3NlHTGPm0zGO4+H7HrKsYrWbOGmAnsgYBURZjqjKCJpIIzWplizu3rqB4IGil9D0CvPjQz5770fois6db/0Gtu9y8XjMKzffpn/vjxmvImxRoCTF6HlCFkt06lW0PCbwQpptGVEVuHfsUyokZBIkq0yKSqW5yfGzzylbCqQimtimqefMfR93ekCWe1TUBBIHQSojkJBEOYfPfGqNPSyhzTwMCTwDI5FYeUsKqcUkmJAmBbomsAoekS2qhILH3voOUVjw8SefMHNdXn17m5PxlMVFmetrInEioYkpFDme69Osl0mFiLW6xkRKeWOrip9pDO0hTiKRCzWyZIyfu6DUqVU2CRfPsHSNrddf4eTxPe79+IS9/S/Rj1sYiUESn3Fx+Rk9yWBUrqGZAqBQbTcoxBdSPkkU+XnUX5bniIKEkBUUhYHjDShcjfZ0zmr1E57f+x6G2iDyJR4fBQhanUb7NhePP0XQC6b9E+yJyLg/otbbQNZ+0W5f8PMu0H+T+aVg3v/wv/iP3/3d/+AlWrUKpTIsFhK7ezU6TY12Q2d3p87+1k1evfka9UYLUJnMl2SFQKtd5tmBzWCcopsNWnWL7bVN+heXXLlZ4+hwQZi86KTr1gT+1teu48xs5vaS2/uv0lrbAHmDJ4dHiILK2F2wtG3e3G/SrJY5GCXoVs6VjVfJiRDVhJtX9lHjMV99tUlvrUSrZRAJ4Ccrtje61KwNWtUGi0VCHmtcXvqoqkERTFCUGiOvj7uMSBKBTEzony44OZ3Q7Rh88MEBWiWjZuW8c/s11mp7fP70lJHvUm+kXN3dI16ZbNdk9nd7PDteYlkC612JIk6oV3Rm85TOtsRXv7ZNvamxmtv0L2360wX90yOEPEMRY7bXOxweDzBrDS7ncxZOiISIJoOi5Nh2wsLJyVKRy1VMEIjIJNQUjUkQI6sFRqHiuS4oEGQWtj3Dj+ZMFimVdgVyAVOTEESZqZchKgkv7b7C80cnbG1baKqA5yesQhdThivNCpW6Sa3ZxaqqSFmGqlaRZBUhzTClOXEQsfRkDNWkU5NJEp0oDTC1EqVqhShXKXKNNI1Zb+rUGhndegcvXrIIQlb2iLVOE9PKiROR45HL3HZZq+tohsHxcMXj8zFKuYxSQKupk6cZa1aZ9brKk5M5r710k+VqwfnZOXKlze5aBSGL0XQRTcyI4wRNNbl15zad9R7Ocoa9shmMxkRRgiiIVGpV0jwhUUXc1CHNRcqGwm6vhyYqlKwKPaPMwcETdt5+i2Vgs3brO9R7BrJWIBk1SGKeP/iUxeWMu2+8zNnpEZ26yY2r+7z1jd/ga7/xdzl+8CFSlpD4IpJZ4mQwIxYyDE1j7Pj4eUyShOS5iialVDSN5dKhY1mcO+cUeYEkCyQ59AyZNVNGkGIKcjTVQC0iVtNn7DbqzC/H2PYFgeewFCWyPCROPNbUDDdIqFUNuuUGr9y6wWV/xp/8q79kYq+4crOHJGSESURSJHieS5SDrmfEscPEB10rCMICI9cZrhYomo4IzFcunr1AUiJqYoppasz8FavFhF5dwpRzyGRk5tSNhNXwEZPTT/HmX5B4l8yHLr4/Jwht/PFTBqfnbF29DZKImOfkcUIeRwRegqobQIAzP+Xg4z+n//hjyDMyCtzVGN+T0A2Jfv8+K9ul1SgzGx9g2wMun3/I5eEj8jBEN0vopRpGpQzk/FxoLgoS/LzGWBD4J//ol5x5G6rJ06eXFEKCF8t4iwDLtGjVNTwvxs1tJBmIMqbeCk3XuLLT47MHz/HtnEbd4Gzsce/gAa2GzFffuM23Xy6j1RvEuy7CZcGmLNCsl7j/2SmNpk57o8lnj5+gV1rM5g56OWI697HKZTbXTApRZbjySDIfOV/j+OKIIhnRsNa4vDjHauhEioGop8ixRLRagiQzGMao6z5LJ2SjY7FyNezEod5Ycv3Or/Anf/YF/hQywcUyG7RqKuV1g+FFzA/fP2fhp3S3EgTB4r/7w/vcfaPJl97YJ1cDxpdjiiTmyqYAqwZys8u18Rmv3G7gRyE1SyTyM9rtnKvX2iyGIaenDooaYTZVqrJIVlLY27B4+fqvcnh8wVuvSzx+PkVVVUaTOWVN4+qOTKXaptEsuBwtGA986qqGm0YYqYBigeJmRHlBIAmUFAVFErgcPKWkd1Bli72rVRw7wjKqDC8vuPnSFQQdNLWG56T4pHQLCzsX+fDBOVeur3F0NqZrrTMPVozGU1YrDz8qQBljWTq//trLhCuNewcXrPwY264Rtyr4WUQhCPh+wDKbY5QtwsJm6QaIQglBKKHKArGfQRzRbXbJsxLzeZODozPaXYEokjGra+SLFUZZplLXmK2W1EwT1RRRxAqCGDNe5hi6RH88IolUdne7fPbslO3GJl3LZG7bhKKEKipc3dvGarfIghVZkrFYepiVCnF2iVWp4KY+NalKHvsslyGbu02iFM5nIXd3u3TUKtbaDumFw3/9P/yEb371Lc7+1X/L/q/9Fs3rX+Hp7/19et/+Li994+tE8yli2eLXvvXb3Pra36XeWkNI5/z0X/xT5DSlUSgY1Zgo9hAUmTxOEHQFq6IQpQJZUUKVROzYw/ET/LzgxBlQUjWyXEYUBDaaHUokWGWDeLnEy10cZ8hGwyTK4fnJPZR0SZI4WE0F200wVBMzEbEMmb4T4DoKmi7zB3/0lzw8PEDMMr791dtQxASAoRkoYkEhFXQ1nSANEASBFBgsM7YMldPlggSR8+kSOZFpVQsSKcCdRSRSwWoRMlEEFD3nvB8gKwqNfMVkvkKUFTrVKgUpcSYhiDmdtRaKVUNPJ8SFTnP3FSJnzMpeEHhT/OWE2XSGLHW49cbXKdUUxMLn/OH/zHiYI2zCtK9hNDrc+dJ3GD5/H7PU4PbdXycrzjh6+ozR5JiaFBElVV7/+jeIk4Qie2HlKYoX2d1JlBPGIYalAjLy31SAwS8JeNueS8XsMejbfP5shlEr8eDgiO01g4Z1jc8//gJNlNneqqArOc9Hl8SRQqtb5nIYcT5doGkKophxOs64+NN7bNdNRPmIWjlGiER2b5fYXrOQVY1e9xqn05if/vQRhXLI26+/jOv0GNsPMJyI3fY+XlxnHk0wKlUGoxPcEC0RwOsAACAASURBVMQ4wV31kSUJL8oIAVXP0csGG2aT9XaV1crH9xUePx2gKAK7uy8BMZfTgO1th699qcEf//mMSAxQ1YhWq0FJNfECh8u5gOcl9IdL9A2TmTfmYpgjJjFmRSMOE2J/xbhQaDdVJCnkq+9cR1IsJmfPubaxybOTU/7WN6/jRjmqGSNIEYpY48nxkFBP2WqX8dyMz57NGY2HFJlMyTRpNWtcfnaIomZYlTXsecx44HB1v0qS2WiixWAKURSSCwaqluG7Mf0iZKdZYj5PQMlZrvpY1Rflu4PRjGbTod6U6VYbGLLHFwefEas9kHX+8uEF1pbJzbtXOT66BMnk/mDGyfkYJUpxwpQruy1Ox1MUrc3x0ZjhZMXWToevfv0On384JUpU1ls1xCxnMFliqlus/Ed06jcRiwJBl3HjHFUSMXWB3d1t4qTgX3zvPueXAYIo0al22O6W+fiTA17bvcLl2Tnbe22WX8wR9DKdmkmpleOGPpKgUGlU+OJZn7pewk0W9Ecz3L0e19fKqJJInAg0N6v0XnsLzXMIPI/T0wv6wzFmuU6tViOTQdZknGhF8TOzS55AGET0h2d891d/k07dZ/Docw4uDvj+X9zni88/5Xd++3fYkxsoATRv32L68BHVjXWs5k1q16+zXe+RuWOii0MmqyEPHnzMPHSZFxpVRWCzK5G5AnkC9iLAECR0RWQWujh+gV42MLFYKwQcf4UT5dzZWiNJfEYDl1xXsZ0liySmWa1RiDlZkoMio7JkHIagKqw1q6glD9tJiJOEsR+jCSqB4/E//eDPibKAalVhf3+XkBkIFn4cEecpqiJTkRVUIaYk6YyjCE2VWKxs5Mgij3JoCqySiHoh0SoreFlCEiaMZw4FGkmcIAoapXqJ1cpltRRo1A2CUCRNEzS9TBwtKSjwixBZmuIHIiVtg3S6RNndJEmGhCuXMBiRxjmbmzH9wz9Hlcqk6XNyrUeplZA4S3J5wiIOUOQS5xdHrByDMEpZOVMsucn6ns/owqG3sYsY2jjTOXZlAkpBrdNGEnwe3vsznHmZ17/ydfSyz+Xx4d+Im78U4C2KIq1Wi8ksRfIDhn6EkEq4w5BYecp0FnD1ioo8WtJt6Hzp7RvIRYXT/oD3kjPytIRAyuV4yaZVYeX4POl7KGJOuQw9yyAXoNlukUY5P/7gIVNP4Lu/fovBasUnjy64GB2S+S4VVeLxwRA/7hMLLlf2N+j1NhCyhDhMmA5D0jxlb32XQkwR5AUVU8LStjHlDLOpcnyxIlcWmM0Ok9kZSeSxchMOHi/Y3KhSbRhEmUAUQJa1eHw05Ph5H1lUMIwCSZU5H8xBEqg2qshJjK7LWOugCCYLPyCcuxiZSNUokSsilVoPUdZY+CcMHk2ZuSGW1UCXpBfrOknFDwr68wDfTtjfkEjTDF1LGfYdFhMbq1wm8BMuByG9XpWoiBj2l4SRzipeIUYFUi5wcbFE0HPSPEdDpJJLrFYZ0yCgpApoeobve9zYWycOXCQt4enJx6y1r1A16rQ3a+iOypPPv2B6DDP7hJu3dvjJR88gtNhsmQznIZlT0KvWGI6WeLFP35sgGSJf/dKvI0gKw26BrtVI4xhT1THNMuQCy5HCqLzktD/g1Vu3MeXKi3jgakIctbC9YyoVEWlQsN6QMVsaY8/lxo2rPD86Ra/qpGmEEOWkcxuxISLXLMyqiC5VqOkaga7ixh67nTqL2YKd5hobrQ6KZvDRo/tsvf7vone3KPofE8cRgizQXe8yX7noRolQjciKDL0kkaRQqZmIkoaqFBA5/OiHP+Xf+92/h7Fr0bp0KWmfIag5hp4SfvD7FFaP2utfRz15iilFXBy8R3vtKlnNZ/7oHkIa8pNP/gxDURCyEmGao1csFoHPdOwT5ymIKnVDxksddNUkiRKKBHRJJJJCNMmiYsbMI4e6JKNbGUXm4ScCzYbJullCN0Qen/WR0MlyATWNyQWTzJOxg4BVmpEGEYg6V3Za/PijhwyXLje2S/zt71zj4ZMxyBprJYvBMqLXapOnAZcrnwUilQS8OEJXFUyxRLMpE44SwrxEKkYoRc79kyWCnGMkMpmgMxBE1ERAkjNs38MqlTFkGVmU8PyCRnuP1vom88t7XJ6dk2l17lxt88lHP6K3blCrL5gPhmToDKfPWU0d1td3WIUq9TWTy8/vMZ8f02jfZrL4IXkcozoiuDpzd4azeMZ8aSIkPkIik0khudZm65Wr9A8fce+jB5SkOheXPr/ym38Ps6KytGfoqsrJ+DEPPiko1zQ0pL8RN38pdt7vvvvuu//+d99geFnw9HyG46YIRcTbb++jVBvsbOxgal1eulJif+cGjuuz1txjNHbYuv4mUa6Sh1P0UonZ0iXPJbw8QU1FgljB0gV+7RublFSNRlvm6tUrlMwNqpZKq3GFkgjeYs7BmYOg6AhZRLNdIGk6Z2d9ZqOEp0cLXC9GkiCNY8LI4fj4gv39q5T0MmHy4qfORR0KE1VXOTty0BQBZzJhp9diFS1A72F7EYv5GFlQuDwb0qrDd759B0MTSbOUVtfi+MmUJMnwApurV5pEvo9lWExmY3KhhB/k6KWcXFJ4eHiCpMacTQuGI4exvUISdIJgzs3ddSYXS6aLmEIoePNOD12AzlqTKzfqWEaF+cxlPklxVglBlJCEOY4b0b9wqMkWg/EMLxUplXXCOEDKBG7uVJFTgbqusrXVZDZeIqsyZiVjo6Pz8tVtNrpdEFOclU/NbFIipiZKXK5Czi4HaKZGnr+49A8HU5rNMsgyjh3QMnWWrke1VkIRykwnNpqqYWoJvVaLi/4xpqUhpwaZmFMuNykEkch1kGQJlAQnFTibDDk8mxJ4BeOxz70nD9jd2OWd166jiB69XoOvvnaTekXkxx8esfIiBF3AW6b85te+jFLYnNo+j46HtMwKndoVtFKZ/mCCUsjs72+yciOKTOWtr70CpTJlAaq7r1B4UwTXwVkELFYhimbiuj5L1yNRIsRcQJYSDEkjIcOPYixF4UpvgzA0qYkJZSXh2fEFYS7Rba/zzW98hbWKiOjM0TfeIY6XBKcjrGt3Sd0Zp6dPefDhI5LU5fPn9wnjmDABy6rg+0tOJx75MiMWcmSzROwnJIWMkAmUNROVkGbZpNOoI0sCXuRTNUTqhYKAxoZoIMgRnpiRxCJxXnDsBAgJRMjsWlVyAap6iTxz2JR17EXMO3dvI2Y2nx29iCL47rduslrY5LrCyPYR8hhNVCEXyLOEvBCpGTJOGvPyzVtIeQKFSq9bIYsTqhUdpJQgSAiKgrmX0VDK2EKMfb5ESTU6mw0iCkqyhkjI6XBFnMrUS2WC4JIoDvC9GC+xIPXIA596s03g9lmML5iO+ziTZ6T2BDGeQaFzOXzA6PjHjJ2IerVDEKu0Nt+hXBUYDc4RhSWem6MpAlI25vRyxGJVYJX2abVqCLLOyl6hiyprvT1Kpkn/9EOG/RMWiwlrG1cwSyKNSpMgcvnDP/zDX+6dd5YV/ODTI5x5hbmfESc55WqZVVzhp59eUG2pOJcJqqDz/OIhzVYdiWeYFYt//oOHNMpVMqXETjdgo9Hm+z9dIOcCSQGIKaEs8Uf/6zm/9e1tkBoMZxM0pcc/+5fP6PTO0WSR/SsdOhsJzY5FU+vx9GjOyrUxKTEbOQzHCdVrBqppoRgmhq5w+6rM8UUfEYOqVbCY+9y6dYfB8Jhao0qnaWCVBDpmj7W2wrPLFmdnx+i5wFuv3OH54RARhzhMefz4KZJaQRQSGhULvexz44pOEmV88nmfdlujXKnS27rBX/7oPvU1mXLNQpFTpMKm12oxmi4plwQEuUScw63NLdIoZqutUW1XkHUF34vZ6rSI1Aw/LFOydEazI6azGN2QaHRV3CBhZnv06jXmTozvKdRaCkniEuYyQZLy+GxFXVa5mPmMoj4qAo2KAEqOpTVQszqPjx4hSjk3r9/k5OKSLA3Z622xmvpUdzZI/CULU+KwPyHOBWoCmFoMGZye2Fy72WY0csiLjE5XpdEuoasBTy6eIOYyQpGxYXUpq+D7HkEYE5NSpGDPfI4Pz9i4UuPkbMHZ0QpVzVE0hcl0BkVKo9nms8+eEoYxllGlokg0N02UEux0O5CEbO/fJDwfIchT8qLE8+MJX/+GQJJESIDreMRuSB8XSa4jtrusHh/SDGZoVY1iEOLFGU4S8vDhI5ZOjB9FbK6ZnM5nNCwNx8momgpN2UAwytSNEs9Xhzx+WqNizjh8dEi7t8lGvcnmjX2Kp8fgeyCDWG/gjv4CCNE3bvD9P/sTNFVjdmGjmy/S/8pSxNyNUWWRtWadSPMJghzZD1AUg0xIiXIBIVuiGgb1loxIwNIv0GRwVhFBlOHFPq6gomkGE3vBEA8hK8gKATdP6Ugafqiy39OZ2BFVUyaY5Vzb3UHJBezAJo5yOp0ylgLLIGfhSShCTKPRYjKYImVVSnlKVRa5mHt4ssKjg3OEIsULY9JTj6qiMbIXICkocglDELDdGasiJioS9LbO4mJJ1TVZFSlinNMoW/RaErbnkwQTPGdJpWQhKjl1dYJrx6i6wnL6BUkaIwgW1ZpE5vhossZibBN4M1JhjlHSEZQSnn1CvFzxeDhBUwIUAubDBNNsUzUCJrMTRoOAeq3GgwdTKuIbuEmEl1apdQ1Wy/vMPjygtXWLl7/6txn1P+XJvWfoWgMQ0Ev634ibvxTM+z/9B//Ju46b4XguieeRiwXdnR0+vX/JZDRiY2eTay+/zo/fv+Dg6ISLmcP7H5yxsWvQUTWEtM9qNefGzTZRotJZ04jikLkjIEkCSSLiRjFLOyRD45/982cIes77H5/w9GhOIUbc3DfY6DUJFgWZEzOdjVjZEZ1mi+nYJU1Ffvu7v8qPfjLiaDbGcVyqdYv+MML2AixTR1UVFosISTfIUgFDq5BlIQt7ySJNWF9bx8yhZBaYtS5GNUcU6/i+S1ZITOZjQMZbBbRqJodnAYkf8vatPU7PFqxmGYOzOVc26rQsBU0t8+zpBE1TybOY82FImKkookDFLCHIKuVakyANOJmuuHNlm3euvUYQpczmHufLSzICdFPGXsRQ5KgKhEGKqsuEaURn0yQrdAInZq1j4roRKSJxnlKq6viA42ToYoaExMROWHguM3uCbujY85AgSHGDFZ31LrY3JXNdilKFmmnQbGpc2dxGVUQUKeWdl+5wY+82V6+3+ODTS8YrjygRsR2BIA0IYpVGs4KqVxg5c0pShVpJRpZysswljlVSATIhxShFJLGMXheZzR3293pERUS1JZMXIfWqRntNwHY8/Chlbc3EMg3SLOLq3jbPjj/G9T22NprUaw2SQMHzBlSqBpPJgiSSUESBMF8R+hk7hkhj/xr17XXSxRwlS3CmSx49P2Y0GrBYzHhyOmS9t46geNTqBjtmldjzuXZth25To15eo71epSxLPH72nAeHA7pr6zw/veTb3/ga29d6iLt3yC2LTF4nGQxIFR8lz3n6xRdIxRl5MmbmxIxmE6KkxNIPWUUunutT1kv4jotZNqhbGpoRUhQmZVNHSjIKRHQRGqKMaa54dukSJCmuHBOlOZlWEBQCbp5QqRrkGSRJSK0hkyQinbU1smjF+TQgTAxKZpWdrQ0OTz/ngwdDCnSuXq2xdbXC8XCOH+SIsYRUwMoFEZF206Rdt+gvF9RLXbIUyoqKlwYIGkRpztSOCWKBmJTR1EHFolXVyckxKjpWuYJhCqSFQLlURlcEGpUSoqGxsD00WcH3A2wnpd3ooZsqiiIjyTJxWmBZFoYuQ5HTbJbRNJkwWuFHCZ7vsZz7hIlDEvtk2QBTCiniAokKuuAiIVOqlGnXa1TKEp7rYBgQB5dkbkBhtRkMB8wXCZs7W8wvLhByjSIaw/wJWlHDWr/Df//7v/f/yLx/KcD7H//Dv//uf/hbO9TKPsMxzMMMNckgEsBIeeOdm3TW3+KTz54ymUwZj0IWQYZgXmU8nZCKAUs7wHdmvP7yBvPpjLWmjpTkrJyYOIUizahXRPr9KZfzmMeHM9IkQ8pzkjDkchhxerlk78oao2MbvaIxHCT4vkwURyxchWalwLRECtHHXqa4To4gZ8wWLqWSRLNZ5dnzA04v53S7NQ6ffUGvu4Fe0UkkBXc1oF1aZzKfY1oxiljl4KTPdJUQpzGikGKVcsqSzE6rw5PnQ2qmgiEYGF2JL718k0quEJPzfDLj6DRlaC9QFRFdU0iFDFmAO/sb3LpxA02VmE6mXF5OWUx9FFL8IGSewhdnh3Q7Ooaucn7sM57FvHS3TLVmMp3G+GGOE6RYNRXd0NFkgbKhM52G5IL2InsdgbTIsQyZb35ll3deX2OvV8bxXLobNXobNXRLJfRtNltVaqaBKMgg6kjLF8etre4OeSZQr4mQZ3hJTrWp4zkJueBTMS3kLKVdq7NazClihbPnU9pdjbntoFChVW6QJi5ZKpCmEW4Q4yYOWzvXeP/9h/SHDp2uxnwa4s5d9nbWWdpjSoZEo75OHmb01hsIucLFyZh6Xaak1hnPVtRrVWI/YnAesd7t0apVmc1CkEIcW6BRrdBraywiie/8yl2U7U2SpCC4OKPwPZ4+f86gf4JjT6mYBlalTm+9TkvKeHV3B6vdYrPT41vvvIZVtzh5fkHLkFDrBktbZKvXYDgNyaQCIZNojc+o7ryC0rrJ8vgD7A++R+dX/h2c0/sslwPscUBMyGjgoFsKK89H1CXKkoIgyaSiRJRnmLpOtawSxCFx0iDNYiaRjZ/FqL7AyIcvxh55WJCJORWlROQHuBkoukijblHEAeVaD1E2QdDIqJCIMoqq0p+7KKLF9as9+hcnPDw6ZbzSuPVqBy8IOR/5ZGjkYoSQGxSCQCbIZJJKkItIahVR0vGTnKqhsooXCFJOlqu4QYwsQ0vTcZY+iaiA5JPKL8rMW+0akiBjlU1UWSHPJEoqIBREUcTSc1ElkUVk42cStUqDIgtYuTaTxRzTbOL5c5I4IksTNENmuXIJogAvcPAdaNY1BCHH91ZsdDfRZYlKGUoVicuFj1kx0CWJNFqhihn1SovpPKDWuYYTW+zcuYuaOFRKKrnbxxk9w/cvEeIROgL+6hx7fMQf/8VP/r+vTQRB+G+AvwOMi6J46WfPGsD/COwCJ8DvFEWxEF6ktfwj4DcBH/iPiqL49F/3DU1R2FyvIwgCu1sXVFYSgWcTZhJCmvLkwRDTusd6o03iHBLGHuQyn330E/bqCkHlRQdmpWwiFwEvX9viT75/iNVQqHgphqkShxGqpLCxpbB0A84uQjJJAFVkvkjZrMr0zzz+ZfycZlmhIkpYXZOjwzENS+fGbYnNfQVFr6IfBGTdkPnUx9KaRGnKYhmTJmfEQYa3Srj/+RdstlQ8b0h3Y4dKrrBSFA76R5QrGufnHq01hSRZULV0VMmk02pR0X12arcYjlf0egqJn2OWVS7OBpwoZzQrdeYXNqNLH8/1iRW4N3HY3OrSVqFVVkhjl6PTU0zVpNdpIxUeZq5xfmnz6GCCWZKRxJxkGVKoEr/xjX2S4oCiUBFlCbWskPghzZKJs0jIhCGaqDKaJnh+SpSnmBUFERHDUChSiIsysdTh9isaezeuoRtdWmWFwfiMfCdnOjjFLBU4SY6kZyg1mXhi8+ToOf3pjFv7PRqGwdnwDEQVoTBQFIFO28SVc4JkgR8k9OoaR5MFw2FAt9vk8PiIN6+9ROAGFKKEpio0LJnzozPuH32Kn0Hs5lTLJsNghVsUHJy6vHzrKrm34gf3n7GzpvP4/iGZbLC7U8ZbLPDqx0gSVKttzk6e0u1uM5/Oubpbxv/fmXvTUNvy9Lzv91/zuOfpzOeee+69VffW2DX0UFJrtCRHAmFi5AQSggmYQPw9/hCIYlvgTyYfAgEHgiOIkziJgixatmR1S+7uqu6qrq6uqq6647lnnva8195rHvPhlEE4UUuJCOgPi7XXu/9rr/3pYe/nfd7nSWsY8ohu12Fzp0UeTwlmUxJKpMkcY3MDaWOAN7oiWs1Z79WQFZkozNjompRyQVZYTK58OlvrdFoOkpDZ39wkfiGl1rLIS/iXZ494+fUXODg9oN7sYVoxzw7P6U8eM/mD/5PrJMAKMorJFWqtw21N5fzxIVcUlG2TNI3puTaJLJgvZki6QUlFmGR4ZYpe5ERZg1jSKOSIPBD0BnUif0G9yihjQaPWwOndQs6GLKKUVeYz0G56Sw21RMkFd3p9TqanqMaIJLK4DDJyqeDeXpfJ1VMuR2MmU8Hrd2sUaOSsaMgKjZbMwlNIibBMm0UUkxQFZWIy9iNkOYFqQZLrqKqOVIGUR4RFSpiqUC1Za9rMcwlZVOiVTL/psFit8IKc65nAdTT8pMIwXaIwxlVl9rb6hCuPO06d43nA1fiIlmMgqYKFvyAIJXodBcuyKIscP4o4H3nsbffRTZ2ViFjvrBFlHjXLYLlaEqYZtmHRclTalowkYBJEFLlEw1BIk5iRd40+LrDlOpPH30fRHXrrbbLZIbk7YPvuKwRRiD87QlG2+NLXfwn+y3/8Z+LmX4Tz/qfAfwv89p+q/T3gm1VV/SMhxN/74vq/AP46cOeL48vAf/fF+SeuiZfw4+MJDbvkN/7mS5ydhRyfDPnBw5zV1YrDg0dU5ScYiomqCfb3+5xdTHAsE0gQpcrWlk2jaxLEEU7NYHdTZekVfLpICVNBw6mYrGKWxyVFWVIVBYWkUJU5QrnRkMqazNOHCXv7CkrPR1dU7t5xubNt8/LLL/KN3z/il36uy+2dTVQtpkgVvve9A67mKZ5ZIkklSZiyPmhzd8+l7eo8fHSIpHYoU5uT6wP669tcjsYYhsR0POXrX9pjdKny7qc/phIOr7z6FURaoNoVFBCVBReTGS9srSGpCUHq8+LtNRyz5Ogo5PRyhaGq2JbN2y+9yWJ5giKZzOZjnh88Zq1v8OD2Dh9lVxw99PnK/TX+zQeXDHoNlvOSQb/O4dkljrlkOpZorQ+QdBUTGct0SaIpuqJSFiWGqqHKEWmRYWgGmqpTkWE5CiWC7//oc9JilzxOqbVWXJyoSFZFS7OZhRGKgF63wWRekKRL2rUOR+OAUtIReYOzyTnDScTz4Se8/tIet3drzGY5Zr/D+Tim1W+iWTov7q8jpxl5LBPGCXFSglQSxSmKYlBVBm27ze+9+yl208W2bKbTAqFIKJpElWcsxis0I6bd0Ll/f4vN9RTJdhBiyVQVnB9M8AuNtK+xvrbB6WGF7cjEYUwapdy6+ypnT4fE+Yyt9R5JcY7iOEjkFMuALM7RDYuN9U1mk3OapkLNqXM69vCuzxgvVvTqPT46/hRDKGwMXO7vbpBUPmv1NT49XuJ5EeNhRJUmnH3+KfpXXmQhLTm/GvNP/6d/RqE2ebDX5/Abf8zP/ce/Rv7wXe7e2yF4ckwhHHxJhtJEKZZ0azayazFfRRi6hef5yKXNJI+58+pfw18dUGot0jxi0NBwVjn3DYlAlTk9ekKlpORViFUozJY+Xl6Qxwrr5gTdWhFfJMQp7HRsFEVho1XDlRMeX874+PGcl+5uoMsFYZjgmiZ+HrBVNohkiZamklUSuloRRRKaFJPmMm/c2kXVJMZX8PhqDpqNruo09IppUVBGFddTn6wUKIaG7pb4nk/HtdnYhsPhDKScHdMBOUOVK5KyJPbm3KrV8IIZpp7TMVz8sKAUJf1aHaFoSCXkWU6QREhCpt3usvR9Ij/GNE2myxFzz6eQdY5PL2k4NWpOE92UKZYuWrPJ5bMzqCx29t9mfXuTqz/45zw59djd1Bifj6jX+pDOKBOZTtNl5U1YTs6QCoeqtYGidX4ibv654F1V1beFELv/TvnXgZ/94vX/CPzJF+D968BvVzdOLt8XQjT+bZL8T3pGmhX8zr865Rd/3uEFaYu97R5C1qjw+G4UgZRBaRGmMXmp8uxw8kU0UUJU5Nxu6ZwNEyS5wFuCOQvJswJdlel1DU7nEdVc8NYrDeKk5GoYo9dkyFMsU73JzHRy6pbJzraJ7VTUTImmUydKI2y74Opiglvzcdw6y7Tk7Drh4iLm+UWC2bCQ05havY6flSxmM6KuTCTqqHqdk9MzJMWm1thEk3Xy8GZsfXerQ7eu0TJdbHWf8+UFT4ef0zP6bAz22d7xOJtf8upr21h5QCk3uRif4cWCq+GCmtVkd12wiATedMrJxRkXw2O6vTbeIqXe2wdV0Gg4fP3Nl3jtxXtML0co9pjrWUjdqZgvPTbvbLJYBpwPPdT5iipOyQuJ0XyIo+vEYclgzeVsuCIpSmxdJfIjEi3HMlXSvOTi4mZyUFNtPv7sMVv9JsvFjI2NNpKlICoV3XSIPIPx7AoFjd39DQa7Eu9+9BEfPn7Gi/0+9ZrE9ekVz5+do4s7XF1P+eWfe4HQG1Hb0PGjim23xXBVcHy6xFuuCJMEQ9EQZU5aZoR5imPbNPQ6i3GE24LldIUiBJassLNtY+jwwt5b5Hslk/kzpn5OOc/Z6LscHo7RCpe4TEizFFmyKUVMrlxhGH0ebJnU7Yxbb/TJYnAt+OrbO5wfD9lbWyccnlIs5hi2hWu7zKc3wcJBJvH44SHeYoakKRTxlIXv0es3uBglmErGL/zy2wRxxO/87rexTJPR+TMsPaa0C4ZP32eZOEyCKY8vfJpmxuruS5iqwmKW4b7w8+z01jh48t8TFxKlrTKdL6i5BjkmszgiL0EVgkxWUAyBmmWcn31EnnnEmUbfHfBs/pBb631KT8HP/RtnTkkmjEvqLZVJluOYDYJ5wNIvODheMZANzosVjmWy0R7gBUt+fHDF9z8dsnarTWWmXI2WtJptdjsdrmZjwkgmJ8WstcnCkIahkyQplaIgMp+r4SlFEiFKi71WnYeTBTESVZYjiRKUilIIDFtn7q9wdIXVKsAym+hRwWudAYf+hHbd7iW6zgAAIABJREFUJohjtKxknAg6dv1mXiGT6VldpLwgExUYMrpqM5onCCHhaCm2oRNHGUW6ICNHMeoUhYyiFKSZxHi2ouE26Dk6plIwmqyQpR12N76CqX2MPw5g5TM8PWE2i+i39qlrJbEeUxUT/JlCf9BkOnmIP3FxbAW1WOEHJ8xG3l8OvP+M1f9TgHzNTRgxwAZw9qf2nX9R+4ngXVUQJDmPHgb8R3+9zfnpgq+9/DL/4vf+FXklkSYFhq5gaDKIkrwoUCQFRa7ISpmjk4x7tyWqwmCWj/ny7XUmIubx5z6GVuBqglUo8/7nHu2axI0MpUTWFTAViqJkEmaUZUEKFKnJWZhwbztD0zMGna9SSikvvpjz6MkRZ6MRyzCiZzXZ7zs8uljRaljEKURZiaYrHA7njAO4HCrMZ5dsDEK62YA4XPHOO28SxTHrLZtgkaEaKXt39xk/nDHotqiyipPZh9zfrfj1n/kyjjNAUbucXJwgqQqfPz+hd/cFPn//CZqaM5kXXF9p+N6nWLWCLEtZrJaMRhLzecQbr96i19/EWy147zsHKHrF0ovpDiwqo+T87JowhDQtsVSFWIYoyQhWClUqUKWUIBJkpUSSF2iqRFlWaIpBUcnM5gGT0TXNmst7PzxElmSCOGJjc4MyXZGpLkatIq3g6vqY08sJK78iyGJe3NpHygSaVrDRaxKdBVi2TBgVLJYhFSnDs2uaNqzd2mI2z9hf2+PsdMz/9q+/S9PVycuEihLbLChylQCJtBDkeUUpwAsktjsqclwS5QkHp0NWqxLPs7lzu0WYyDw/O4fIYL9/m073mvW+jpCbOGrGYlIhsoitbpe9jX3qpkzslyhqTpQuaFsNTGVJmPrkcYhahATzKYoQyLJMnoVMvIgnFwvOvID7d7Z48vnnqFqLosoosoiq1CmzHNep8ejxOUlWcv/uixxPh2zV2jRfq1FTfN7/3imv1HeQRUJWgSZivvbLX+e9f/Y/0NQdHrx9h/XNdQ6fDimdilWZE8yXyDJkqoYoJFargAKbsBRUIiULT8nzAFXSqElTdF3jehYRRRFh4aMIFfICUTlYGshxQZX42IZKUYAfynQ7Fq6SMJ6OcVSLh48O+eDTh7R6LW5ttoiKGLffoygEkmYiYeH0u1xcLPFXGmHloxdAFqNbNfKk4mq6pJnqoOaARL9mE4QxXqpQ0ypKQ0a3TIoiJ0ahknMwFc4mIwyRQ1Vh2xZH5yO6nQ6KFNDXXcaRR6XlXC5WmLlCSy4o04xCVQmChPFkRb1mI+Q6UVywWqV0O3UmqyWSktHt1clyj76kMl/MabQHFKT4WUacVTTdCaODP0FWFWrGimgxwhQmt/sZq+gQSWpj51MmgUy75uIHK8bBFMNqMBwZtMyCNH2Cd/nwJ4LwX1oqWFVVJYT4f2kjDkKIvwP8HbhpMsiSzPVlyQcfX/PtHxzyzmsjfvWX7vLbv/MuqqzQ7amcndzorA1VJoxySl1GFiWKUuHHKpv2GhfPPZR7JmUVY9V1XHKCtEASElFSsFhJmGaJmlSEKShJgq0KmpqOaxfs7ei0GxuMfImddZfpwuAPv/cBuzsNOjWZqFiQZBEg8d3PL5hNUiRNoBYVi/EC26hIk4LNtU1sp8mT54/o9R0MTaLZrGg1Wzx+/pAs9LFfeJ1n5+fY6hJTGDiagioZTKOUeVwiNXt88PmSB/c2UPIAWVrjOx98wocfXyCMMdt9QZIIhARX4zlCkVkvarhZRhRZxHmILATvfveAWBxg6AZp7LOpN4msivEsx0tmNC0FRTPo1k1aLZOsyFnFAULEpKmBbBgcn89pNzSWVGRIKLIEZY4QCkUlIes6Y78kuwz45V+4T9No8cOH73N/0GJ2mbO7vU+hBtTbBenhBFnknJ5eM50UREnBg1tdwmzEz73+Jnz6OYKAmmKitxokVU6tsUaZlVRyzOnFGacXZ/zGr73G5laP64Mz3I1dhDxGAjRVwTJU/rO//YsMp3M++uQhJyOPPM2glHCrCqcm8fDgmPH8gn7LwdJtVqnPJLrArBlYTouZF7PW3kAXK2QRYsoGp0dX1EyLZDWlvz7A0i0Wq5jXXn4Zy7ExVcjSBE1IJFHEKvRRbYezR+cYqsbP/dQLnHz6GT1dhTJh0HHI04ysKlh5GpdHE548n2G6Tc6nz/nxj04ZDFqMRzbrW2021ttodo3XfvptXNXmja+8QZlr1G0Z1cgZP7rkzuv3OT8eoksKXVtGSBmDbptHTy8x7SZqTUZRFXRFwtVyEj9mKRTyVFBmKdNlSKrFFFFORgpKSSnAEgqzsGJNM/AqiZiEZSwwJZOztKTdaLOudhiP5/zws0OcToM7dxpoSkRegCyllJLg4PwCXTGYLy5pKRKataKWyFyucly7TUMriCsFypxJnnB/w2SRzKkKlV7bRFJKgvgmxYeywJQkVCGIqNBVjaoSLPOENCiocglLU4mzEimFJA3wi5QiKTFUHT/JqLV04rRgFWSEXoJlOnTqFnGaMhpN6bc6rJYhy2XM5rqF703xgxSkkv5gB9OtMx4ekfkJilmRjkrKusdoGZOnEt22hVJB0zIos5DJYkIU5ZSVTd2tE8zHGJrCwDH46GrCWmcXXR9y+Nn//hMx9P8reA//LR0ihFgDRl/UL4CtP7Vv84va/21VVfVPgH8CoGtSZSoVmg7f+NYP0RSDDx8d4Vpj1tsq8yhHSgWqXGHZbbJkQVlUlLmCrMHtbYtCKzkZX3Gnt44qFG6tvUDTGWG4JhfXcx4f3CSsJGnO6w+6XJwuORwVVHJJuyV4675CnheYbsmXXl8jyTWmZ3MqV+dq7JOmHtcTHVPR2G/XGE8yLtSABy+2MbUaz30fLy+pZEHgB8ilwXa/x9/4lSZRXLCcHhEuR6hSiqRbhEHCux9/QhDP0RSLN3Y1RGlwfH5Jvb5BMJ9z6iUEaUG92+fZo3PmwZRVHHD3roO/SHBll/EXjV1Ddhh5PuP5hLptMBqnVDIopcDzC27dMllfKzg7kpgsF0i2iqkV1BsWd7Y3efj0hGbDYDaZUXcMWvfqfPxwRhAbhMmKhqvQbNsIAd6qICsFZRCjIciLBE0V2KbGfJbw6OmQi4uPaMkRgWFxEGUsokNMp0kwG+GHKYYhk5UyJ6dnrPddNrbXkcuESgr40v11Pn/6iBdfXGcRXBD4JRN/wk5rl6ZcJwpylmVGIUriVUQqjSnEDnWrgedltF2LyyjH0kqCYMhimbD0U6pCQYicbFoiJIWtbYPAm9LcrrNYFmxvbLC3PmCV5Gimjjc5oSyWxIspr7+4jyapXF7OMBSJ2/ubfPT0lF6tRnezTyVSZDIuH/0AuXIIF0t0t42uOwRxSbvVZhlENFyNt379AcOjIX/8yRUrb0UaFwgq4rAi+OZ3+PxgiappRHGGJnLyKOBiesX1+THrm2tET2VkPSXWVb75h+9z70GXJ0+esN1dQ22k1Mtddm8PODkaYndqnMdDPnl+TZFX7HYEU09DVBayFGHpTbLVnLYhuIoC/MhGMw2CMCJJSzQTWq5OzZCYXy8psUlLgZeFuHWN1SyibQmqHO617zNfeHznRw+xVZ07+wNMI6bbqjMb+bStJmfBjAwDKQ3wC439fp9KjkkkGTOZEEUZr93e4rMfHRCqBapj8jwIsDKFdsdFlnOGpyMsu4kppxhqSZkptPUb/j5KUhRZQ9VdNFmno9cJsxSqJmYtYzo5JRMFeSpRlBBkgm5HcHI5Bs1AEyWOrRKkMZNFykZ7DalMibIY3RDU7YrhfIWqWmgV5JJK6Hl0bINVHKNKBqWU4UUZV7OIjV6bMI3IZymNuk5d6GiKykmyxBYFx1dLNjsyuaQzX0xoWAWUAZdX1zTayf8v4P0vgP8E+EdfnH/3T9X/rhDif+GmUen9eXw33NDXdqtJHAiOj0e0GpAhGE0XaIpKGCTEVYomKXizOSUVslyRFSm99gAhZ3zttVf4k+9+yi++MWDQadJoDgh9lyo3WW8HNOtP2dtqYZoKa70Bw92Qs//jQ0gqNBwGa9tsbbd5+PSYR4+OeeneXa6ExTx4yq0NC8uRqavraBSQwnPvjJ21JuvNOpGXU7Mq+t1dDk4v2Nrt4cULVqFD195Fa4YU3Vc5PvuYZqdGvXWP4+s2s8UBPfkWw4trwuWcuqNQR6ZRz0ijJu1OH28Z8e57H3J5GdHu1DDMgnt7A7zrnDJT6K21+eTwgpOzBbKuEIcZNUWj0agI/BIhyyAKkjRjPi0Y+hlCSLTKgpdf3yQWKdfznFmQ8Ktfe4Hx1RzbUXAsjUbd5DvvnTPzNC7HCZ12xu21Jo/SGcmqpJAEgoKarSFTsNZzeDSb894Hj7lzu02lFHxyMQZF5d6aysx7hmOoNFyDVZggU7K91aFZd5jMQnQlo9mI8BfXVK7PKrxA0+rkRoicpNTMLvPJmEHXQVV3mVyM2GqYvPLKXbxxhhfc5JRmZYplm8RhiLeSiYOcjqswXeQMuhb37rbZv7PO5cWU2lqPaRCDkFmMA06eeXzpldtEZYzUHRAtlrxw7y67O+scffAhnrdCkSvCOObOvT7BzGM6OufKS7j7wj3CZcR8ekTsF2zumthUXF2OcG2H/prOy2/fRfVG6IZFY6hy8PQptYZDGAeMI59yaOE4Bqomk6cJm9t1fM/HMjVCP2U8GVMyQULByk/5xZ96mZ//5b/BneySQphQQDWacev1txif/S6reYJXZSyDEr2QORnnKFpBtIxAlcgWAVWaoWk29XaXMPRxFBWjlKibGqVRUsk6ZZTRa3XxigQryukZFvNKwrAEb9x7kbpW53I84U8++DF+kPHOfo9VEGL1HMZeiCbZxOTc2V7j0dkCRVYZLiOCwGKVxpSaRM8yOY9TvvX4KTVFR9IMKkVhvogYFSa7toxaCe5t7hGFIU1LR4iEk6nPLCiQhEKhJlDJmJVBs2VSSgXSPMBbhjQMm3vrfebFnCw2ufJSVFlhEkoobg1NVOysd1FIkeQbOqiqYuKyICsEkmwxXxbEqUJWQavncn52RcOpY+oqSZWSJSl7t9aYeTP6lUMW37gcSmVC7GdURYGl6djGTeiKH8dUiU5S5NSaKqZpcT28ICtzgp9Mef+FpIL/MzfNyY4Q4hz4r74A7X8uhPhPgRPgN77Y/vvcyAQPuJEK/u0/7/O/eAr99QGmvM8nH3yT67GPn0kYhowoE0pVpopTCgl6fYfxdQiiRFVkXNNBEiW/84c/JPJCfvj4kO3+m1hNHbfb5HsffMjLr77Ajx8q5NmM0VwiyVTatZK/+7de4Ho25+g64vhKQdVK5EJDllKyMuF4fEW33aWYFkRRjmpFSC2VOC940K3x3tWEovTwlBxD8QkD0FQNU80wZZVmY0BaRMiGRB5Bo7dHWkIQC0zVRM4dclL27t9GmstceCdUyETFhN5aCyELdpobGPUWv/8HHzNaeDRbKk8ezwn9lCwtCauMdr9OmiRsbtUJZy6nx3P27jSwtYzlMqJdM1n6OUle4QoBsgEi4933T8gE6DJIKPzxt54xmqywTA1LqWiv2eztaLhzQRgpiLQk0FN0UVGYBbpskCQJ3bUOvu8R5zHtpoJYykwnHkvJIMPjrVdcaq0a05mPosvImUWzKdgY9Hj8dEQU5UynCzS5Qrmv4acZReRwNl1Cdc3+3osY7gYn548JfYV6rc3o8oJGvYmt9fFmKePphF6tgahSikpFUTV8L6Shx9y9b1GqBm8bNl957RXW19f57NEn1M0YQ2vS61acXY7wpgty3SBWNqgbGo7sUuQ1FnnGj3/4GX3XQp751AyN3p07nD4/QXc6zBPBvRebfPT+t+kNNtne3MJfpkzGV0idHlQVnVYL2fDRqwpvGeN7AWWywLI10iRj5afEsYYoZ9hOndl4hWNpUBYYpoScVWzc7VApGkvPZ7JQ2HYV9ta6oDdxFZ2QCkVTUUydxv4D3NofUC4EXdXFqJUEucwqKVADH0mXGc992o06690G4WpJHqXkgKFWaLqEhIoXLImKAiVXwVQp5ApUmVCNCb2KV3fvYSoDvv2DD/jej09wmwpffXMLP8yZVxL6MkNOISfHcppMhz6Rf+MhJKmC8TwgVSANY2aaRCWXNBSbFTFSmmFrBkJIyHJMmDTY6K9zNjxhsZoTZAZv7nUYtE2uJ0uOJhWa06bMCgZtCz/MmEc+t9faPDw+JQ0tVqsxV1mOYggsQyU1K/zpJZVfoXU2OTyZ0mnoNOsWioBKUgmjFd5qBUIjiMCyTWbemCAMSRJBaVT4RYah2oiqZBlGBH5BFBZEUXJj62BWpFFBve4yni0pc5XJPKZmuiAVDDp3yNJrJGlJmgrajR221np/OfCuquo//DPe+oX/h70V8J//ReD637mRT977BCE9ZntvneXUYOGNqSFRZhmmIShyQVaWzIsFuiaT5Tdf/eTZEaatIJclmz2Lr7+xS6mu+IN/86/Zf6HL1776Er6fERQJjtNiw47I0iH7mwbdtdcYzqb0rmb44YQnnw9v/oqnPuMgYT7JCGYGmsjRLZ3LyRmdwEAVGnfubPDra+tMjh9R9Q1G44JdWyGZrzCUNovLJde9R3i+C2pGreby9PmY2SLEtp/xyr372FaLSmR88Nk5r+zf4vi5z+v3B5xdL5lXK/a31ggzCbmM6DfgyZlPWamYQqYMS96+u8WT+YTr4Zy4EDz+fEQYy6hWjjcPaHZN8lLh3vo63/nhM5ZLic2GzvUkxtIq0kKm2yvptx0eH3ogwzIuuBpFDOoyyyRis2myvVHQ7jlUkcbZcIGUp7z16jpTP2U6h6xICRJBXbYwGwm6BHdu1djv3eO9j3/A3mCbJI1Y21BpNl9iNHsf1AZykpFmIZWsoqgm3UEf9Dq1GqRixHw6pyoEP/QeIasailJnOj/F0GK6zSZvvfIOjw+e8enTT9jZvA10ECIiiSQqRcK2bWqpw+0XBuiGRBLoaIbG3J9Rajljr6IpQuYXJTuDe+QNn+PhEPX0gC/ff4luf8DV6SmryZKu4TJTSh586TVmF9dcLWUuj66w6gbPzz1OrBb3H7xKPF3QqHfpuhm9jsTZ5ZROo8k09NjWXZZJwdOTCb2Bye3NHvNgQZxo1BwXzRA8OVnQsRPyKCWuqdiWzmKVcqvX4Z2v3KK/f4fR5TP+1298SrpyoJQp8PGTAt01UUuZ+itvU0ZzGv0t5otTWuhYuiAkIK4KLtISzdBYbzpsNDVEFZFrBQ1dZbRMmXrgpwWd1gC1VGjroBQZVZSSqznjNKUoDX7+wQNcTeePv/8dPv78kLU9m1fuNQkWGV6e4roq0TQjVCR0IyedLOk2DfbaDY6Hl9h2iySWkUwdsUwIopKmbbPXXKPIhkziAqnQUM0MScqZrSZUpFRVhmu4NN06B0chpZrhRxKaLrHVbKBKMf4qYbUKybKUp+kFQtVIs4xolRHJOjsNG10qCEmw0ya7azqPz6eEccgyrkAXKEAShCBAs3TiVCLKCvS8YGNjQFFALQ/RtRSQsDQJ21YJ0wzLdfHOTjB0E9tUEFlJp1lj5k/xoog0rMgkFdMUWJZOmC8YT+a4js3erRY1Y5cgG/0k1PyrMWH5D//h3//Nmq3TMBWqMibOJLIiwpZUXt1uMJtlhEmFrqjIssCxFFZRwSq5UT5UQlBmFbouc3SRcGu3T7/dZLma0OpvEUQ5zz+5Yja9QjIEvTWTbm+dxULm6bNzRJogFyX1ukatbbMMQyxTo2YqbAx0BgOH9UELy5TwU3h0NOLp+ZzFdMm1VHJwuKIQBRubdfJIQUgaTbeFUiUcHq84PjunP1jj+bMZYTjBUS2SOGUZJxwcXXN8OGR/p8/FyYq0SNnb6TO7GpMEKWm6QpMVXLekVVcxDIcwLbEdhTv7bZ6cL8mERLdRY7GIKZHptppcnHn46c2Y+2K6II7BEBpeHpDmKq6ssXfHxKmrHI8yXFOhWVdJkwIpU3jrloMk5+QUvPb6Pq++9GWW0ZxwEaFSYckSl9czwgSKSBBEGVfjEk1kiCpDFQUfPz0lq3IkreTDj68phY1udEgLwWw+Ja8Sbu32qGk5k2nE4ek1qT/l3m6L68mcBy894POnY9Y2tzF0g/liim0ZNK0auaZRaWCaOuPxFVkRYutd6pZEUerEeUWzXgdRsrN7By0TSNKKi+EJcRhgyR3Wu2tcHp0gWwVrbZsSCZUaX3/9NVzd4ersGkUx2Oxo1Nwaa7cf4C/njM8uUJF4cjIkR2fhg6LE9Go6YZDy5PgI1ewgIUijgNUyJg4DdnY3icsV4WLE1nab4emUi2ufKy9lvWcSrlJ6/R6fH47RFYkszUjzjGbTRdISmp0O09WcQmQslh75Cn7mp3+WwZ0NZj96F8tuots27ivvcPRHv4ftmjw/PqWSYV4GNISFJQtmVU6lSGjATtcmDAvaqomeKPiUSDLEcYQiT5HjCrWUKcqMwk8QCmSZyjuvvoyelXzrox/x9GjOi6+sc3+nQ9NSkSgJFIVe3cLzMyqpQpVKlAziRKKioGVrFELFzyOqNMPRXDpmSbdtczlbYmsGaRDi6DKmKWEYFjIFpqziRwFIJat4wWS+wHYVwjxl4NQx1IymLiHKCkXOmEcZwjCRhESll8imAYaga8noGHjpknkQMwtDwiil33SxTY0wXuJaTRp1E1WOocwYT0JCP8UxLKAEKWd7s4Nc5WRZSb3eJssLpouQhZciSQq2BnXbxNKMmynooqRea5MSEQQVSSwoJZO2vc5y5TNob5KlAVEyx19m/PGHz/5qj8f/N//4t37za2/UGHshQgKtiBCVwoubMqosMVpFlAjS/CaxQjNUciCMCspS0DAlDE0ijkt2Gy0enp2jWSntjoIiB7z3/gXD0yEv7VrItkmIzeOHY1qmQRHM6HXafPI8orveoNdr0O+tMVtWPH20ZD4L0TWFxWTBYhaySiRKSWEyDLichIxHKdfzlPmyZO7FFLnMbLhgOvZJU5WD5z6DdY0qX+J7MBz6+HGM3VQ4O5oShwHbWx0W4wDHkgmSAD9O6fbWmI2X+FFFJmpcXHhcjhZIao3lImQ4j5Cp0CqBYqlcXHvkWUVR3DTqivzGMKjh6vh+dOM04AiUUqFuV9QaFf/+v/cGtmQiqQlyeUNLmbbKixsOr2402b67xrKc81Pv/BoPnzym09awtYK6qxB6En3XYmtrncuxh25pJGnATlvmalrRGGgYtgaF4OLC46039zDUis8en1IJQRT5XFz4CElDU2tcDhdUhcAxddyaTqvdwnW7HFxcM5oMSfwZm5stLNVGsTXe//QAKXH4wcNHtHoOpm0hoaNLFbpuIyTQFZksVji5/ohmrUGcywznl8h6jWWyRIgJruugSBZIG/TqNXpbPda31pidPef6eoKsSjw/PKTpuFwdn3E6vOLp8YTu9gaPHx6xmHkoSskqWlCKgjRNGM5WPD26YnId0e64PD88Yn2nQbsJ3nRK07UwJYdvvvuI63nAchFRZhLrG3Uats5kNMewBJksIaPgWipmU0GvaeTqHNkyCQrYb73K/oMt4mmGZJbIYYDTuU3qOkx+/GPcRp3rywOQGmRFzDAMUCSBL0kgQa1VY76MuA4yFnMPvxQs/Yw7jTWMMqDTaBHH4PQlLldLGg2HORItu8lmr8O3PviQDx/N+PmvfYmGU2AVEnmZEGYRIheEWYFTV2hoCixLdFWikiXiHEhhmMTsdJqskgWakOi3m1hShq4kTL05vbqL42hcLpc0dYNaoySNIyy1ZByFlIXANBXkvCJNBX3FQq5yIpGxpmoIIdCcnKUfUEgSmnAopQLKhCio6FJxMF4iJBVLK5FyjV/Y7xMFIbYqM10MuZokqFqddsMkDnx67QY1W6Zu6diGwXS+IM4zbEfHD1akWYmqKKhSha6WtFouCz9mvAjIBNQsjaKKWawSogDiNGAyW5FGU7JCEEYLZguPIMwRZHz349O/2q6CcVKQ+DK6brO5JRFNczRRMFuprKIY5Yvkj6yUCcPiRnCvyBiaBKKk7TjYms48CjiYD7l/y6LfMSiKCkXZodO65I3/YJNb2z2+/f0F3/zg28y8GKUm+MqDbbJUsFqd8PGnIRubfQ4PRsRVyWTm03BLNkoFQxd03RbyvEBOc4ZxRZKVPLhrgWExDxJm8xQvGlPLHdQG+JmPruXIaQ/kHFUDRZRsrlssFz56JdHtmKh2ynieYcs2m9tdPvt0RpRc0q5JjOcBP3p2RbjKMYDg7Iy0AkNV+Oy5h6Ak1SUGLZXLNCKrJObLkkoyiPOE0XiFLXRe2K4TxytGZU6nrfHVVzf52k/9Ku9+5/f5qXdeIAhiwqrk4eERmhzjVxZ54tFoKnzzW98gKcFfmVTZjP29V9i+LeNUEgcPPb76yj3+5fee0mjJfPnll8m0Y7KswNEqMikhzypEWXF9vMTzY+aLFQoFQpjM/JDji4AiV5DTFLmUOD484+VX9wlmYxq2QhqX7G02WXorVM2gmi0ZOE3+6L3vEOQZktLkpXsvk6QxUdFA02U0UWBqCq5pEsQ9Do/HnIzP2N92qLt1fvDwE3Z37iAZFrISkWYxsrnGTn+H1fkFiS8IlzG6nXB7bQ2RFTx8PiRY5vh+yPn5jGUgIVcZhRbSMBwur1J+9s098vKc8bSi17NZrQJG8xCOlmyvWWhyxp98cMb2hsvV9AKplBl0dFazBFmG2XiM6Wo0NAlFkojT4CZB3XXxYoijgFZuIVUZkRTz+Jt/hGLU+NKvfBmlt4Xx9l8jOfgYR/UZTw36a1scPL/GbdVw6yq+UvDs0wPqTp0gGGJLKr1uh9U8IDJhmefMM/j4eIHjrahZLQxfwrVcDF2j9EMe7GxyeHTIyekl/UGN49kp97Y3eHh9TVOR0RstFDOj4dapqwnjkcewKKjLdXTbJYtGLBYrEiFxFSwhFgij4vNhKx0VAAAgAElEQVTjCwb1GqWUMs0kzBC86RKhygxsl0DKSEVJR7aZiIowKzBtiSossGSLcLkkMQT5LKXMIyRdJ7FBES51Q6GuC7wVGEKh27GZxylVWXCnYaMpGquayWTu05Qq6utdHn+w4GoWUqKwvb7NV15xSPKCoITrcUhdUlh6Ibrr0FQMzLrNcpVgmzq2qXFxPeLp2RXBKmN7bY00yTiY+wRRzulwzuZGk5ZhEcUygzWH07M5w1WF6QpKUaEW2k/Ezb8Sv7z/wd//r39Tr+fUaoLJJEeUElUB4yjAtCrKvCLOSyRFRpFLqlyQ5YKqgpqj48UxF0sPwgqjIehYOnt37vDJxwuses7O5g7Hlw9RnDZJBboOeZwz9wIs0+XhkynPjmcsg5gsq+ivmYSrEm+ZognBl166BXJEFOecXwfIagM/TtHVCtWAd966x0+/8RrLGVzP58RyhVPX2Nvt8uJ2j6cHI55fevjRHMdoYBiCKE5ZTGNu7XWI8op2T+f1B3dxtIBuR6fbrVNlCRvrfRotg/EooxIVJYK8lDAkiaRISYuKNFf52Zd6bK/VCKOSxTxHyCllKRHGAl0ofPm1Or/6K6+i6QVVUrDVEcT+hLgKOb04YhL61B2HB3uvQH6EkqbE3Hhj7+0YUPnEeULL2sYbz7kcLjh4eo7pVnzydEKpZFiGRpLlaE2JQb1Jr+USjGOkSmI0m6HbCkmWE0QJZalQiRQhStI0ZbHMyYuYjV6DfreOkFW2dzcoypK6Y7C70+byOiBKYbe/xc+889McnZ1iOwUPbm+i6TUk3cFfRNQsG0XKSJOYmiORFwbLYoKmZCjagG9/+0P29rb48PMjHh1dU3ds7uzsUulLmprG5OIaKS+JEbQtg+U8Z7QKuBoOsRtQhCmqqZMmc+7fH9Btm2RRzpuv38ZtapRlzvHzc778xpucnp1wNDynXWuxsVGxSny++/1zPn5yRbHMmC5CVnFFv6HTbTZQTYWPn44QVYHpSqzttmj3bQ4vx5yN5rhujSpVWN8ckM6mN/MKQcDm9gMGP/uLCN1FMnSCk0fkfkqzbTC8XlLIcOaveD66IkpUKhksw6BuO8hxTpYGFFmMZugsAh9/UVBvWUSkeElClGfkuUyv7uKaOp89e4RsOqxvO9QbGgoRQsSEcoVbV1hECaqA0XzF6XhFIVQa9RpL3yMuczTTRFUEZZnjhymyYpJZMkLRWSwyUiExD2KKsoKqYhaESPlN8G+ykJnEKzTLIg1jNnsdVlFErkAqy5BCpkisREahVphqSc2xSYUGpcyX9nqs6zl+HKDJOnXRo71p8Hx6zjwsMP2K6+mKp7OC/f0NdjcssjRBFCXH5+ecDBfMvYB2zaLVcKiKgiTMyDMoi4KyyImTmLojM2jqCEklFRVLP0SXddL0hjFwbRu1gnrNoWNpSIS0WzbeMkUSBlvrbf7oe3/FaZPf+q1/8JsIjeWswNCg2VVxOzZZWpFWOfxfzL3XkiVpdqX3uXY/7ker0BkRqTOrMkt2daFFYdDd6CEBgpwBCTOa0SjeBIPhe/CWNF7AjGMzHGAAtEB3dZcWqVXIE3G0ci1/50Xiln1dD7G/bXvZWnshUUoSminTrJp0mgWmIVExNJQSkrzAkiVqVkHsC4yqzsefnPHydEroxhw9f8HeocPLZy5xFrJc+0znS4bTgOOLJc8uZxiGSqdjc37pYekZ/ZaKlJXsbBrsdhts9e6wmMPz0yFLL0EoMf/tn9zh0cs1yWqG60n83W+fI5eCekVjucyYLEIOOhW29uq0t2poqARFiGHViIKENI6QyoIsi2k3LMqkhW4UGFqHMFxhKxYpCgc710gzncFkhOdm6FpJtWKwv+1wbX8LR8u50utRr+u8+/YOVw6arOYBcZAhq4L3393izTtXOL+I2dqqcmunRhiWLNOU8cRDpHB4ZYfRYsnFdISGgpQUeFFJKeVQOiiS4NreBnVH5Xzq0mzWMTSJS3fAjdsbNKsqbhwwW8lcHK0YnE7IkKk2HHRNcHwSkhUpSVawudklz2OSGCqaTb/aZLhwabVMDKdCVIZsdPfx/ZjZaE7mrxByyWIUst9v0+jWUBSFVsWkVS+5eeM256MLBuMljumgpIJuvUKcxuSFgqFbhH6Cv0o5nQ5474M7HF3MaXX2aDktOmafb558xX5/F9+P+ObzJ8zWS9qWyWjtsrfd4cGTIxRNQipkLr0V88uYP3rvDrcOdijzGEkUtGsNLGeLIC04OzujVevzyTcPcOwmpq5z8/YB/+E/f8Xd2/t89tkFURyyyEpWQckbt3dYzRfce+sQfzrkzq0NGh2dW3f3CfOYvJDRKjq1mk2ZF1R1lel6TSXVqVU0+ldvIM1PmP7iHzG1Gva9d5HPH1AqBpfjIasoo8hjYk3FTxMsXSaTSkoFRDbHbNdxrDaaWqFXq2I7Gvsbm2Sxj1ZRsTULQ3F47+oVhsMBL04uKWo2mqmx3ahjRwGKXmWdJvhhgutlLNceWSYTxYKmZVOzZSxygkwiKyQMOadn2BhVC1Fm5AWkWYqkamDJZEWObhsEeUpYFKzzjNkqBkwiKcJNU2RNIS0lvEKwjlJ0zcQ0DFRdpYLG3naFGxtVlLLKehqw3dexVY/pPMT0TfrbbcI0IMoTiiLBc13cVcnlKkdxVPa3K0RRjB/npKVEt7OJJAtajQ7NqooXpCDJaLJOEpWYFZsoy1AVDV3RkTAYTpfYloNalmxt1IkiD13XWUwiqrZFvSpjGRa6rmFqYJklqqYgcplff3n83Yb3v/+bf/fXlvE6td5r1ric50xnAUkkKEoJVSlRZYUyFxQlVIyCu7fqkJRs9DWubBuEUY4kv5YlgjDFiwsWIYwmLm4Cj448JvMZZZ7z+JsFUZIgCgkkDT0XJFlGq9EkSxLiTMI2DSxD5fqtPSTF5PdfPECTJdarFFnOaDkatzc6tAqDrwZLvj2eM1vHWLqMrCiss5zALZguV5g1hW8ejrE08ToNeeSR+gIhSa9LG3pVksjnxfEZYVYgI2GYGYps8MW3L1Ex8JKIs5MZSSFQVJkP3tng1s0Oe9s73L7WoxAF63CJO/OZzGd89KM3ONyto5kCRVf5u398yfH5AMs0cDSDy+WcanuT9dqnkAKSLMIxY77++hkVrc5wsKZTdxBlSSRSZmsfVXWQqfLkaMLZRUitsc/zly655GKpFtd3WsyXa3S7jirnaEqO70aUqoZZ0VBUiSQSzJYRSZZiaTIQMx65LDLB9kaDvZ0mZZpgGwHPnpyw03a4sneNVRLQb+k0+j3qxgbPn57zdHDGwZU9SiyarSquN2Q8vEBTKyiSjFSmyHoVUzcI44xKJcVPY/b2rqKbBu5ywv7OHmt3Qr1a563bPR48eolVbXM0XVDTqhzsNhnPC5IiY7BO0HWHqlYiUoXdmw5aaaCrJUrF4ctvnxJmGQUZk8Gcfq/L84unLNwIp6lycGOLy9mQrMxQdZfD61VaLYsbh226LYXtg02ctkG336Hd2SLMM54Nhky9GE2RiEKBYcJ/9bP/muPjR3gp1M0N/vx//EtyRWX66gn+6TnqfIRV7eO88wHx8ASjojJ+MaZWs5grCdN1gqYadOtVaiLg/Te3+PTJnCDJMSSD/+GPf87777/PJ199g6TVkWVQDYGjV+gYFs+OX3G5jFArBpokKJICK1VZZwLdlCgCGX+xRlcMqpZDXOY4UoKm5NQ1mxCBpqh0Gk3yrMQ2HfIsR5MV/CAnFyGykNA1jazISNICSVJQVBlJMdBLGbNiIiwNWVbwgoyiLLA0E8uuoFPiKAplmjEOU1w/xw1ALUvkpM5er8VgsmbtKUhqRm4EzJcR+80msRAsRY7W1FENhTjOeTWYMV4ktNoNRFkwdyMkZBwLjgdjVMOhlBLyMmcwHuPHBp3uDqVIqFgGggxZKv/lMVaBJAniOKfRMNnbbaNpAi/wcT2ferVGo+EgREaRZ/z6y8F3H971hkapSLjrCCFyijyjlCRKWdBq6nRsjY2GTZSmaIrOZsemXVPodMFLJFodi2ShkBQQJYIsF2SySk7J3m6DVh1MTeL8xKPbbBHGgkKGxE9RdJUwLhmNffa3WkhWiayqbPR3uJzOWEc+aebzwXt3eP5kRhzn/PCdPcYTwcPFCYthjhARYS6jmAaGoWFIOapZYlkak2lCUMToqsz2jk2larNcuKx8wTotubhckCd1cnLORyEbGxofvPN91usFpxc+T56dgyLRblSJo4yNhsKPvneL6zvvMb084fr+HaoNk9FqxcNHl6iqCVpMRpMoTVgNV/zg+1vcurvPfDSm3W4zWix5eXyBIkls9bvs729TliVCirm6t4+/CjgdjXF6Fgs3pN/r8OzVhKSQmC1W+LHBV4+OsMwCNxB02jUONuu8cf8Kk8kc3/coCgu5SBm5MVquYJsZtYqKG0sEbspOs06rYrNeJzg1g426wpVNhzLPaVcbXL26RX9vm2bTohAxSa5iKjU++/JTosKl1bZxWm3OLs6Jk4Dt3hWa/RbHZyO6rStYUk7VkIgyDV0rSWPBs6NLWr0a4bykWpP5P//fX9Oo1nj3zg3+4XenHG43WQYzLk8nHBw6hFHJLz97wOkoQiojuo3Xi3a+yKhXNI6PJ8wzhcfPXjEYu3S6TchLpDxC1XVKGUazNZvbVaQioV53MA2D/kaPWzcOKaQUyVQxrCqForOzs0GQ5rw4e8ps7eGmKfVahappU1Ekru5tMJssCSMfz41p9W5z//59Xn3xJZZpMTo/RnEs5NkQxWxj7h9iFCGj4xOyLCYRINSCzmYdzw9w7AbPL6bIaPyrd97g+2+9h+N0yZOQjx98ysLNaNZsJKlgq96lTENenp8iqRXarQZqKdAtnSyOSKoWblKQZC5FCpGQMdCxFJ0ggJrukOoZhAnLLGbpxyyDiLUXoVRMolgg5JwoK5HJMDSdledTKhphkrLR62KZrwMyqqGjaQpqqqDLCputOo4qQylT5lA3bdBkFqEgFRKKFqLJKZ4IkS2LdSHjuwGrOGW2yDFli/2e9bpYXDPpduvUHBlZlBiaAqnC/qbDq9Nz3CxnuVDRJIW93Q5JvEYqS3S9oOqoeL7PZLomSTPKIsa2dExVRVEFo2lEr9dH13K6jRpF4RGGGZpuIkTJdBXjxSlZGpGXJR9/Pfxuw/tv/ubf/XW1ooCkIAkohYwiayiSTpYUKKqCVAru3tlCkQyy0ufqfovr+31u39mgXnFYuSFuGCAXMoqkIhsySZ5Sr+k06mDZBmGucD4RLGOXmimTRQpRCUXxWmdXZJW5uyYNcnJfZTS7pLsjEyxcdvo1Wt0eL86XBLGHpso8P1+CLhELQb9qEkSvrXW2UVIzdCxbxlIrSFmBbemsg4jxNGPlZzRaJpPJa1tkmsvM3JAkyCiKkla7zmIcsLnX54tHLt4iYj5JKIWgoUn8r//m+9w43KeUNUrdwI1dlouMjz874fRiReILojCiZUlcnHkYGhiWzbNXx7SbNXJJUG3WWa8jHFOh35LoODUado2ylJDVHD9boTsxkqKwmkf48xJVcpjMV4xGEZeDFUpe8pOfbFEGEUUmE6Q6EhqbrQpJljIfeSxmgiBNieISSeT097oEcUawzsnCjDyXUCQZXU3Y26lz5aBFs9Om07aJopST4RjXj9jq7dHdOOTo9DG2Doqk8eJkyIOnM1TTpBAyp4MJz16OGV6OsTWTXqNGXU9JZBPbqCBKE0WUfPPgOX/31QO2ax0efDvm8Pp1nj14SrtaQWRQFBb3rvWIM4mK2eHxywEPn8x5980DPvlqSG1jn5OLGYHQ2Wh0mLpzkkKm362RJxlRlLDVqrJaF+i6hB/5XLt2FX99SbvVA6XJy9OnJGnG6YULuUKcwtl8TJTlHJ285M6dA3Z2KmRxgmM65EnObreDpSucDIYIzaTX6HF6dIkYXhBcnGP1+yyHJ8i5hmnIZNMJpmZSu/8W66MvcOcJizRlmKu0mlUkIXO3u8H3brzB3d0+u87rqyfOCp6dvGCdhSQiJvIDmnqFXq3NdDVlNHPpb3WJE4+GXUPNCyxTw197rNcF7+xv0UkV9IaOKee0mnViRSLwNc7HGRXNIDdyMqEg6zqKUhLEOZJcEAY5RtWkWWmSxwlSqaDICjKArlLJwctiqrZFHGbUKzUURbAKQtZFipxCzTCpq2B0YR6tkEqHjm6z6ejIVVgsA+IwIpNUapZGqigoqUfNkBi7IetcJo4zsqwkyWNSVNwwxVQFUSwjSyXz8RJJkrFNG0MXdBp1FHQ0uSRJM9Yrn82NPo6tkScJYZKzcANKIeP5MUkYYqoatmWQZBKSqhIFBePpklany06nghAFv/z84rsN7//93//NX1umAoUMZAhFopRBVwq26hqUMmu3ACVgschBBX8R4Hkhay8BCn7+kx9Sq9Q4PpuwiHwiIYgyCSFKECqzeY4oQqpCJgsSFlGJoUhIokCrqPTbVayKyjLM0IWOJBI2t1qMLxLuXzvEnVo8fjHgdBqDgKpicTFdcmO/jmFWGC8jTF3Q61psb3RoVmziSGG6DPmr/+ZDBheXaLZBliSYmkQUl4gc1mGOVCrIpsDExHFUepuvh/XV2ZrLiwXfu1vlve/t0NmEn//wOm/feItXl2d88vAZv/lyyMXY5fPPTzk6XhHGKZFfYlk2w3HKbqvKnWs2kjAYzWY0TY3nRwsuFyu8qOTslc/b967QdhrkhY8f+gTL1wNm6G2iMELEJZKa06tqqLrKZOayu1Hn1kGbP3rjx6ioHJ0t6W1JDIYuz4+n5IkNsUzL1siFICxBVlXOxwt0BWRea5VhmaOqYNkmblQwn7n4XkyUxJi6Ra/a5+GLFzx5OuDs1RglL5ktAyTbISlCrh7e5JuvnvLg4ZC1GxLHCX3bodepYhgW/YaDIkvM1jlGRTB3FTYaLQJvxbOnQ/K85KN37/Pw4iXXexX8KKBiJVy/ts1vfn8Emc/55ZTzs4xxGPHw5ZKHL4cMRiu8hc/SXfPRh1fxwpjVMub8ZEyzWef79/YYTaekmUqtVSdRY2z7tTz38be/RdNlVBTybI2kCQoCdNWiLDKGi4B+t027bmOUAtePyCQDXVY5GY9YhSkrP0bkMZG3Qg9SKhUVlAq6lpJEGU7NolRUyukAvX0duWnx8usHlJRkTZ00LUjigO/duYNNxtVOSZIlyKxYzAb87slLhss1WRSRpoI7u7tEccY/f/mCeCXxr9+6h2HqTL01cRFh2yr1ioIuSsoowRFNbr95l92NbSbjguG5yzJ43frkmjFGUZJm0uvuUstELgqq1R5GFjCfRDiyRJlkRH6MIRkUfoRh6ohCZru/gwIYikGjrnM8PSUMSyI3RjMrXNmrghXihwVemlORZCxZZpF5PJ/E2IZgGSXolk0hoFWvsLPbZBoGXLgZociRJYlOrYKlggQkSYRjd/GTkq1Omyv9Os2GzeFOF3fpMp6DKAVhAGkqU7EN4jgijAIkRSIVJRW9glORKUuoV9tYVYtCUqEsKIsUVZGp1iwUYdBpVGjWGvw/v3z63bYKQkmWSehWSppZKHnJ9nZJxTAZTSN+cr9PGMUs44S8SPDWKY2WjrvO+PrpAEVTePByTV7ouIXAqOjkcYmuCopUMJ8FlEqJWdGRKJBKid2ujaoKLoeCPABP8qlYGk3LhFSi1FXCLCFOBV4S83xwgZdDnmWs/JIwWhIvBFV7Azec0WsaLFY5zXqFiiEjZRqSmvE//8W7HJ1ecjlLKFVBsMq4/84eL4/HKLKGURXohcDUFUxNsLXbYLkKSVYpvXadv/rJHnZNgUqPm+YO270OkW4Qaza1aoWaNGU5jjgauoRZioSGlwnSwRpLFaR5wMb+Jp2WzP9246cMLs/IizWpKvC8lOvvtvn950dM9mf8qz96i6PxlPPxEKNscjabsrHR5HCvy3y5xnE03BXUKjYbHRunDp9/9StKTeP2vTqJXzA6W3N24bOO5wgEbx10YV2gGTLjZYCuaCilTLOpMThfI0qd2gYkWQlqgRAmRZay9jRUxSNMMu5fvUOZ6ZxPzvDjNZKUMzgboBgyDx8+YnujRRTNSIIECpXDm1WGoxHuwqNh3kYiwFBbVDWZqx2VZWTxzq23SHZTKGe0TIsrikbd6TA6f8W719/B0uqUpWA0Tpgtc4yW4Hq/ykfXG2hVFT/UePzkJfPZjMFJyMVggutqSKqEVW8SxjAPQoI8ZTCNuXarhrBqPDk6xqrUaHdlRudTilxGFgGCJl5Q0Ntvs4HMs+cjll0LKYupVasspzGLco2fg2GaGOTIikyjY/Dg2YpOo4bsh7SvHuA/eYWaZ2haglAsstWS7be+j/23f4vrglglyIbJX7zzPnVZQlDgxypxFhNnBeNYpzB07DxEc2oYik6ZBzx4OOBi7PLBm9u0tnVawuHGniCIVaaegakrHPRruO6EyTzixeffkMcR5+uArtPh+kaPb04vMHSNetVmNh2R5hJ6p4oqFVgio1E3mEewil57piVTJ6IATYE0xWjZXJ6dYlQsWloVJfPoyzrDNKKQZaJsxXqk0zahjFMcoVEpC+QyZB5GVFUFpxQsC9DyEiGrqBKEYUwBrKKIwFfY26xxsRCs5jG1egVdrVMxVRxDYrOxxZ0rO9x98zZ1Q+EXn/4T//mTp1xOAyoVBcUoyQsJgUKBjlVxMGSJ2AuRVZmrVxqMx1PmKxkvjKjqOq1Gm0XgUm9Y5KnPcGbgOOEfpOZ3At6SJKFoMiLWaTqCIC2wahWGFz5RCuezGT/83h2+/HrAO7ccng09Xgwz0jJAk02yICd4MgdF4NRNdE3BdmzOL1ZIKGRFSZoKRGHiihxfkpkO1iiKTh4XtKsampBwbAlZaNS70JV0ns8Colzj428u+fEPtmg3LP7xn8/Z35TJMo1Xq5ivHpxgkLO9YRCFFpeXQ8ydDfqdBjeuXKVINE4nczIhk8YCu1bj7PSC2MspS5mmoaJKBhASZYKLoY+iZkilTLEY8v33ely7ep1YcljOF0xXLl0kqnLJI8/j6CJltQpJYoGiaKSFoFBlgrzAsmxeznzc311yY7tBz7nCwhVUKyW7B32iaEmW1jA2t1gsj/FTk2+eDnnjxg5aLLBbTSzHwNJDmqWMamrIwYIbN3MMYmr1TVq7TZzGNv/xH39FHHkoTY3/6cP3efbNKf/wcMKz8yVBAAKBo0vojkQsClYrhX6nSpDGKFrBzkabyWhGf3Ob7U0Tz/fQtZi6aXA6PMayGvR7NaJSZ7nOWa5eYIoqF5drNu46XN2zcf2AWquK4djsNFUuLzzOxwu6nTqeu4Rcol41WboBex2V0MjZ6W2ymF/w07dvcbGK+ZO7NzCkBBG4vH9zi1qlhh/4NKI1zZbJdk9jo9Xm86cTRKESpzB3FyxnLr6noBsmqtlgHMW8HHjYlkTNMqhWHUbLGV2nQbXRo1o3mI6eMZqu+OlPP+Bv//Ybzidr7pUSTkNjc6vHdDKiqulYuoKpFYRpSpnllIqCJMPS9ek2KhRy/i/uhpyNndtkuoWzvYFugvvNE2rv/5jls19w8+4t5r/4mh9dO2Dn1g564ZFEAaIoWBU2qmkyWfscDYeocoRQDXZbMgf1OudTwWy1xtILsrzk48dPiOM5rptj201OhgF122I0j3nr2gbTaMrWzj7hvMQSAbopo8oSYZ5gFSrn8xWKZqDnOWWpUOoaddskjUMazQphsCYqY2rNKkopcJQaqiSRhgGaqZBR4MUh1W6P/R2ZRTBEb9Zw9BI3j7Fim2ESoUsyRpmga4J6Red4ClfaKsUopdSg3ykwlYyXs4iKY1MqkKQKSRlycjxDkw0WbowXwEbjgP/+Zx9y88oVUjciGM+QahaqbuJFS5B19rZ2SUXEbOlyMfRQVQnLUInTiDSH/d4G6/mSODNJU5mtbhNdUQmCEN2ooEsWaVYgrJDjc/8PcvM7AW/HVtjtK7xxtc29W03+j//7FeNBThqrmGpOlpQ8f3bCq0nE00nKzpbDdlelWZNAtjkZ+SilhmHLzJcelmZSpAGWoZCJEiEEWQmjsY9IJfp9lUITLNyCw02b6zttHh8PCGKJ6zfaIEnMJx4Xq4K4DNlqVjh6MuD2n3/Iu7cE55NLbnZ2eP58RrOiEqUxQlWoOBL7u3ucvZqQ+RryjouvBlyO1pDlqBqIMqEsS2p1k8CLsUoFy7KwDYvT5YJCpOjl6zZ4VZH59MElXmDS6zTxIp9nL0f4oeDu1UPy0uTaVhfXMRmuA8beDFKJJIAChWkQ0aubjEchNUXjdDUirKjMLgqCZ6+4/vZ13OWQwfiEVr3GfDFib8ukW29y/e23+fLBPxOmBUJx2NyuoOk7CPmUxeyC8cQnyRKatQqNWoWqVXLv1g0cYXJ0kvLJoxkbjQzL1jmbBWixxs1tk+NlzI8/3GVnp83wYkmSlwxOh+zv1GhXVIbDOZv9m1y9uoWjhyhpgJcorMI1oetwejLBMkwqRoPVKuH+29v86Y/eZDp1+fjLJzi2ys5Bn8Vyyv7NGpenF2xsHZK7U5aRxHDt4rs5V9sFabCiXa2TRCmBrLC9YWDU65xeDJFXK3S7yTRLmAULbmzvUXd0FDV9XQgiSaSSQNIlHj2fIdKczX6PVq/J3Td2WQ2O2OhYjGZr6s0GdaWCocbo3SoVy2a2OmNrq0Wc5ZydzbhxvcliuSL0AsJCwipLzFym7jhEgUtDF/iSAUWBZOqs52tkoaBIMu2qQNEUGm0HRTGwD29Tu3GNvH5I5cYE4RgUzx7RafepWRJF4FHTM9aLCD/OKOSUIF4iW1tMVil1WyOWde7vqNzb2eDjx6/fvJ5MI7Z2+hSGgpfrWOoGnV7Gq0nExnab1cqj3tJpb/SpJAqTyQW2gIoqs1r7FNGSK/0qHhnzmUezZiEpKis3IS0zdmotXC8iiTJsU2N4HP8AACAASURBVEdTFbI0xTIsqrrBYjml1AyQwZIhk1OenA/pVGM8FeRwhSRsEpExXS9QnAaKnIEbkUc2cy3DTQIeXOjstLvs9WUWuYfrZcwWCXKUEacK83FCGSsoWp133jxgq9PixpVrbPWaVGSD5XSOF/uMpzPmvsujl2eomsFymhHFLvP1lNVKolpRyYTMZB6w0axgaRmqlLOIBBezADVPKcsmVdtke6uL771OSUuKTBimtFuNP8jN7wS8647FR+9t89Of3OPo6Tl/9ZdXsXSL+aLg73/9nMEiZL4SrIsMCTg98VAsCSo2V/caHF2ExGlIvVPDCm2SIOJgv4qsCDzfYTZfsLNhs1p4bG7YWGrMRSojEMxXKePFCZKuUJVgtXC5dXuXZq3Ci1fnFLlCEMNkrPLLfzrCadu8PI347e+/pq5J7LRlJkJjc2uT4GxI1bHY3tzkeLQmmJ0RrVPcoEBBocgEeZwh6yqpLMgk6DdtyjxGZDlXum2COKQsErb7NQwyarrGgydPGAxTZMVk7q7xFhnuPONXX51iWYKNps2tzT7DmYeuFNzc0+h1LeI4IQsNKo7E9UOHy1GEJ3loho1hyaTrmCuNA9r6nCyNWSwmbNcsWi2HSTAlzDO+eviK7717jSCD2fAxizBjtaiSlRKPXp1yOhrwx+/8KX/+Jz9ASBrT0YDNK23KT0t03SAIM2qWjKJoBElBo67QrtvYZg9JznFXC/r9LWaDES1HBclnPp9AGVEyZ3vLYnd3g/nDV7w8mrJYxvzZR/toxgaWozMdT/HXK9IkRNNS2k6DeKWy3dnhbHzO2F/x6TcPuX11Bz/wqDgOQeny4Cihb5es/BlJWWO5Ssj1NXM/Jox9/FXEjbsNvvjiBe+/uYOUmtRrHWqOR7+eImUZUaTi+StkSWDIKqejFU8vFtx984Bf//oZd641ORmFbOgNJl6MlAqkmY++22Z35z5ng8dEucZs4WJpMn/245tcrkKiXFAmGYpk4vqgWwaaKlBSgarqhFGGocmErkJZylgNjbJUae9fJSXk9Ldf03z0CNOo0n33h0iSTeYtUI0a/cM+g5MZk9MhK1UnjSXqpsCPJSQlZ+2t0Uqd6ztV3jjs8/zM5z/99gHjZcTWfp3tKzaaKuHGS869Al03kJXXHaK5JrNrVZAjCdu0SVKfPAy5ut3mi4djanYVSwmZZSX9ThdVyxECNCEwMei2WvixiyoKdEtGFiqFSMDUsewqPS1kFaYUAlRZwomgTEIugxKnZtNrq4wmATWtiqsKbE1BsUxyoTNVK7jJis12j5auohUlGTl39/vML+Zcnqm0el3uX++gv2dzfXuPbrdL3TERqc9yNiVePcbPNV7NVnzy4CVnZ2uMikUYpdR7Mt1+hbjIqdQqxHlKHASEaYU4Edza67DyJnz69SlhltPt9+l3FSIJnGYFd7VALgWyBnopU2YZSTz/g9z8TsBbQuIH79xjNQtA1/ny0wsmsyWyJqNoIBcabirIS4EiKWxtKmx02jx+vuZBMCCIMryoJH7hcbBpc3h7j/PBnCCTmK9XhBHE6RK1lNHtiFvXD/C+nUAW86O39vny2Tn1hsr777eYjSQGp2PqzSp373V4/PCS6TolsCXOHk7Z6s0JIwlNL/nZT3fxlhKarKA7HVRzyePPJvS32ohY4+VojlOxKYqSuExotzT2Nru0HZPLZYBQJFo1ILIpk4IsDzBsnfUyompJdHstknzN9+9eZT7NyfycX39ZEAifr5+eISgRacHTUcJ/970Ws6XHs8slnZpBu61zfWeHyTSmpmukWcJvHr2k2bH48Qcf8vtf/Z6Vm3D/nkaSmrSbG1wMzzm8sUta6IymF8ilzu6Wg1MqJInMap4wWq+I1oLNRg25odPfbjJbvKRS2aDTu0pR6aD4OTe7Oq8uI1ZZjlGzqFclKvUq8WLNw8cT4vyCXOhIKDBd8fMfXmU2c4mjnJOBjyJ77Gy1WK8lGg2ZK/st2p06v/j4kr//bMLNw4z3776JyCc8fHnBIoiRVAk3XnA8fIBq3SSOCrZ3asyGZzw9yTjcvcJosma9XqFoJvWKwslYoZBsLofHVMyIxXJCJmss1jmxvubVmU8hdK7tN4izFFttkqceihTjhymaalEWMlGWk5chP/7RfZIs5NuXZ2z2N4ijhHUYsR7OKcqUuZfybw93eHExII8LGorE1C+ItJTpKEKzDCBDlBqZKSH8BCktkDWJKMu5nPr0N/pESUGpxpxfptzd3cNPU/TeHlEyxfWWFKGLWSpIQUDnL/8XZEvHXXlc2T/g9NUl80VCpBekpUqRBRyPBc2uy1a7jeOY3NzrcXq55j/+0z8znefcfOMK+9t1VrFPmqZUqw2kIibxApxGDeIU25ZJpZypv+Rqvcds8YqtnTq6qqIpOUkJilRBjgLC1IdCoGsyzZaJKCW+PnpBWSR0Ox1EkrJehjjdOuvViqps0KrXCMolVqAQ+jF6oVBJIFIL4qwkyhXqUp3hcopu1rFMjeUq4GwdoFkZkiFjVytIxJjjFK3bxvNkknKDO280+Oj7P6SiSET+GjmPSRbnLJYaq8gjzlym8wsen0y5dAWGriOUFNfPQNHRlQ4VPaHTqLL0Utx1RM0xuFiu8QKFJ6fHeGFKJmk4TZO88BjMSiRJQ1Og4zhoSoobBKSJRFmUlGX+B7n5nYA3kqBgTq1b5+mR4OlRSJxlKFpJWSjICNBAJSdLQS5ge9Piy2+m+JGMgkAtZWqOjCPDYcdCkzb4h09fICnQaeukuUSZSDx+GnM2eUVFVzk4NFH1Gf/2p1fI4pi00Ni+ImOoG1hmlQ/evYsp/wOyVfDkgY+S5RxuHPI0e8nd+z3GqxC7AcMXHiJ7jqEYuP6K4fMhaVoQFArBKkUH2naFK5sqhwc1+p0trkRzcmFyORmzsdVicDahYtnkYc7hziGtjo4kKUhhia5rHO7WaMv7DJffsg6ecDn00WSFrIS2UZDlGT/+3tvkT3/Pyg8YPwlIipKGbrK7tcfjywtSITMeunz2+TNOLiLumm0ePZjz4vSUWwcbHOzXGKeCyckDFss1NaeBXCj4iymDtcu3r05Q0fnpDw+4cXCFQIyIwip5JPGb3z9n6b2i01T49tmCvi3R3tCpyyZeIpHEGVklQ1UV3HWAaVkoqSDKInI149ePLqiZGklW4uNygz63d6/zqy+ecnpyzN5eD8cq+dmdLS6DkBeXHuPJxxxsVFh4MwyryVZ/F88V2I5Gtdrg64efUm3UaPYdXj49w3MFe9sOuZhTSg4pmxi2zWI6Jyrgq0czVm6OZanU6y2iXDBb5qxCn5cXPu/duYVaxrT7KlEGuiJBIYhSAZJKLgvyYsVvfzdAlBmDSYau6/hLF7WaE2QBJ+cu/+kXD2k5MkUGw7VLFEhoNYvJeEFFhs26xk6/y0W2hlJFkaq464BSg0ajThz5WKaOJlv4XkppVLj+xoeEgUfsLvG8lEwBCwnFnLEhlyjVJuVsiCx0nGaD4WBCbbvH1F1REqC1eq8DYquEzfY206nH45Mvmc5LtrZqFGHA6DKkWqshSRqhL3F7/yZluub56JyEHBWdIEtIkwX7WZ9ep8HlbIZIbOJcocxSyliiWeZcBikGKrqskqCBUlJ3HPyoJJUhjmMUVUUTJpZYoyopw3FAkOWomolqGhRIvIousB0bpchYzwWt0gZTQ1dhuVoihExhqZhySRKH+JGGJJV4aUG8svjBvff56IdXEe6aIFwiJQvKzOV0knE8DRlOl8x9n0KKCMOEVMDKzaibgt3tLlnhM10krNdrqn0NW5dILQ1Flmm3ami6zMwDw7GYLAIQAnSTogDDrGBoMlKhcDkJ2OxpFLkgzAW1apXruwfAw/9fbH4n4L12Q2aTiG8+8fjkm+fEaYhR0YiCDLnIEJJAVjSqmkFUCmYLhd/8doCkypiKzNVdB88vWA4TjJZKksHSnXH9Wh1FCGy1wqNXS1oNAwOD6SpANkve/Nk+cRiTMGVzZ5dffnFGqaYolDQakGQxpgNhUHBwXYdZQRIlpLnBz994A0tKqDRanPQHLAc5I69Abi6p5CpqnBKtQ6RCoBsaSRqzs79Hp9fH0HXM5h4PfvN7Prx3g9O5x9j3qSsSmxUdx8pQrCoXZ2t0w+DyfIEmNJ7NXT7/9iGjRUKcKVRNjY2+w5+9tc/xYsWWnKHlKp2OxfadNsXK43v715iHGSN3xp/+SY/PPx1RbyTcvW3w7hv7fPngjGq1jpQL4nXM8+kpw8mKzmaX8dDFqpnUt/s8GhwRxFVuHDgsPZ1Pvjjizfs7PH3xisg3KND57NsjDEOm33LoX6nQlUuOTxK8PMO2SrxVTFKW+HHBllHHDSbEhaCilFQ2LQajOY6WUWoVRG5wdDpnNJoThimjccjBtQ32r9fYwuT6vR0mF2tOzk85HhRE4Qr7j3d4484tjo6/4PhswA8++Dkr7xzb7tOwx/z+d085G2hAyTI8ZnsrQZU1/HVAEPgMpgkiV9hsg9HJMLUIXXgQpXiFwek847NHz7m3X2e0zjF0lbIUrOMCNS8RqoYuK2iygqEXPH4xZf9KFcvR8bIMPxXkms6zx1Mq1RKzbqHlOboCoQ81R6NuGGi6AqbOjVaDwWBCLgSabpBJBYnv45g6WimIQlAUAzddM3RdNrstaoaBG0SEeoktQHM14vNLMjQUVWY+WtCt1/GWPv5sjWSWYDRY+zG2XtJo9GjVUi7HC5698ukf1EmzkjhMabQ3iYMQ1VKQSZlOFjTqgrnvY9oVUi+iZVVIopgXwxESIUVW4AuVGAVHKTG0GFM2MNwMREmpSvhxjGGoxEmBZlRYLNc0VANTk0kWU3abFZJszX6lyjhTmUQBg3VMx6nSa7QoKyZlkZIEKZkNLSzMNCUoEsBAygSyDk2zTiXRuXllj70Pr3G400dEGcF0gqmkFKx5cjrmq2dHeH5ILGWYtkyapzTrHeIgQeQlWRoRqgqZMGjUKtSaDdZeTCkrBJny+ioqFcpCJl4nyKXCdLJkd7NKv11F5AVpIbicLpGlCmmcEaUOw+Eay1LZ3uxwdjnixZn4g9z8TsDbMFX81ZAvfjdjngiKUkFKc0SuYug5lDrLZYpWMRBSRlbKrIYlQpLpd3LanQZh7HLnfp3Ajfn27IxXJyHNhsn9m00co8mLkzWZyNBNia5s8UdvbPLqszn9uw0k6YDPn5zSaVmouo2MxcX8hCh/xWBaYv1LNH97r898vuKP7uk8fnXMz37wfYaLNc8uQv7Lb5/hGBYZGYaWYxgqOxsd5pdzkliQayX/5e9HHF5ZsrvbI0oVtg4OOY1rJGHCH7+9S64pLAYXOEZOq9rhTAxI/Ai7ucPa9THqJvVaDc9fcO2wTjRL+ejeNkeTgIdnl9zdfYuP7h1wNLtExAXVVoNPnl2yjDxuHTS5fdhjMQ1Q5JA/+egdnp1eoFQ9uk0bpbBws4xWw2YWJXjZkg/f3+Tzb2c8fDHhnXffxE8fMD13if2EH/7oBorUxDYMhgMfOVW5dbXOv/mLdzg5nvHLb4+42q/z/NWIatXBqci8eb+D02nzq98+JgkX7GzVuFyE3L7eZ3d7kzevbdKoF3z+YEAQKPxf/+FLDq626G01OT49RzVfD8TxzGdno0YQLrCtLu/dN/nk85e8fDrgxdMz9vcaIAdgWBw03+Ly8gHp8pSffPQ2p5MB33xxzMILmD4+xVIUKoaEpZbst15bQUWZEa5M2nWTRk+lu91gZ89E02ccXK+znBZMPRdNc4jCgjKD7Y4NesEH793i1799TK/e5GLhURYyciLQUotKolBDJxAhtmTTtEpMVaPfq+NlKU+eeIi6QaZK+EWGk8ZstJssVzmaUmUZxeRpyDAUlHnI4U6T1dJH8kvml+dIO7tU+/8fc28Wq0ma3nn9Yt+//Tvf2Zc8uVdmVVZXV3dXuzd3t2m3txl7hMAzgouxGMQibriCGwwjS8AAwwUSYljEIjEjMzaWPRi7p9ttt3uqu/ZcKrNyOXny7Od8+xf7HsFFFsIC1IaxRvJ7ExFPPPHGRUj/CD3xPv9fD8FWSMMYpahI4wTv7BTRaZALNUIN3U6PF0fHRFGJYqh4dYWoVNiWQ7ffIQoyLoYXCLKCY+sYhsrpNCZBoJBEakVErSsW7gWYy1SCSpVWKLnAxJ8gaQah77LTtQmSgqnvoeoipirRsU2ePFlQVqD2TIIsxkyVT5ttQNJkQKOp2/julL5tsGpYJLpKowANDU2TSaMEpc4BCaICS1Io6gI3WKDLApai0+k0CRYFty9f5fLly+yubdBqt3CogRqyGYWS8OJizt7RMfsn55x5HtgSt3fbHF7MkUyFKkyZJhFhXmNrDo0NnShOqSsJWbaY+QGZH3GxSJj7GVWRISExnofkgs5sGiMoImkq8nx/iq3LaJaOjASChqbVeGFAf7kFckpZvDTBmy6Sn6ib/18waP8d8AvAqK7rW5/Gfh34V4Dxp2n/bl3Xv//puX8H+DWgBP6tuq7/8M+7R13VSHrJdl/j9NBH+pSCopo54zmYkoghiaTUFKXIimUQLyIqEWa+yDsfDikKgSIT8BYZSSUw9WWCpEJTIqbTCTMvoyXpiEVGp20y81yePZnzg8dj3nilwbe+uo3aWOPukxE/eu8JLUemG9cEwxJXKlDkmjP/kPVui6X+Zf7R//4OiyRG0C3u3jtG10SyPEdSKuK0QlZEZq6L0dfoORruJEGm5OjM4/4jF9uUsEyVrTWbLI345jdvkS8qVKmNYjvsHe7RdHJWetd5/GTKYLmF07L4+W/c5Mdvf8DNqzavXb3Mu3enPDs7omHo7A2PuHXrMsrCQdNEsjJm/3jGs/MFZdrl4GzK5laLjdU+YlHSbIts6k1G45iL0RFNyyEl4I2bO0wWCZN5jCEpHI9dNGPMtSs97s7P8b2Mt989oE5PmbkLrm1t8dHec1aXdP7X3/uI4TyiUkq8zER3GvgLH0VVyQuDR4/HpHFJVWbsbK+ytWni+wL7ew9BEvj6lz/Pt7884Afff865m5Icz1nv51zfvY6cyPiLinAmIK83ubxzkx+/8zEN3aDbazEJQmy54MrmK/hBxIuD59zzJyx3DG6sXOJ0NmJrvc/GepPnL2Y8fHhCnuRksUAqVEiyxOpqH9HMWFtap9kXWdm1WN5ssrbaRhGXePLsLtdurZJnEnffWaDIIppWY9omN66s0Gh0ODoL6TY1jicBSVoQ6TGel3Ftc53FwSHYMmeLiNuffYOL4QFxKrM6cDg5mVN6GaUqUagqiSVTzT1M0yJLM1QxRrUrpqcRuys9yjDFUHTyPOfZ3hN2TZ04vEJ30GG0f0apQilWFONTjCsdqiLFUAV0u8HmRpfk2RhJgNJyEJOarbaBZRpU5RQ/yRmstsgylbyQEYyK09MZays9KAqiJIEk4WQ8JHETKlNHQ0W0JRRdpMoK2ss3mbsf09AdFnJMVJXUqUa3YSHpMokGjmwRz3PqXKHOavwsxNIM5m7CYpGjtlWOPZdwHrNWWgiWRX/QZvOzV9gZbNC1HfwgwlR0JFlgHroskgilEFFtm9XBGgNHJnB9sjJFDEb4NUzcES+Oznl4fEqapRhqDmnOUlZwVpXsnw8JSwE1kMiyglpOqeuK1WWbJPeRFZU8EfCimGCRsrO2jG7OsAyVZ0cBsVcwPCuxxZJ222Jts0tT14jjCEXRcPMmhjmmzEUadg+z4TK8CFledgijijLPSaP5X0y8gf8e+C+A//H/Fv+7dV3/J382IAjCTeBfBF4BVoHvCoJwta7r8ieKNzV6W+atzzksr9n88MEYRyv5m7/4BX7nD8/48PlzWrZEvyWyu7XKUktDfnOH3/29dzCsjLmnk5Czfxiytm7wra9/hh/8k33OLybsH82pkekua4ilzGDQYGvHZnaWESshr28ZzMKUw6OM733wXVK3otdtU0xjpqlAFr+0BlVqATeviP0p58Mcq2cynC6Yuh5zP0aVZExNQaxjNnd6JHWK55WEccU0D+i3FdJYQhFFFAMs1aCoCr795hcJowWjUcCTR8946/Yuk+EUL3HpdQwuxiMEMcV1QxZeiq26/Oov/RSGbHF6fkxnqeQXf+4aaR5ydhpy4p4TlS6vL73Gf/Vbf8qbr66R5Blz32VzfY1a1njwyYweNZVdgaKyvirRaViMjlL6koJAQFbYPP1oxrm74Eu3tnjy7JxX7lxh+5LMx0+eE1+AUMJqz2T/eMpqU6eSFGxH4K3P3CARShpdA1Mc8Xg/w3NLHj05II5rWoaDaAjsnXoICLiLc8qophBqpPo9Pn/tJq9euc4ffbhHfu4jCxKBd8CtS0vkc4lZAH/yo8e8euUSVW0Q1gKXd9f4uZ2rXEyOkYQaTYWsnHE23CNb9Cia6ySWQEsQGA19NEVhbaeJ3dBxpx6bqwNMuSQKdTZ32rQ0hWajjec9hWGMqdkkgYsgyBSZQ68hICsz4qRCArwwYmV5hWAWYGkKli1DnbLwVHodjbgMOThZ8OqVNb7/4BmWojB6ccT6cgPL1DncH9Jqt7EVAc8VOfVDBEXl0uoKqqGyIQiYCEQofGgeUOQC4/EUSRERjYo4SZjNJ5RlzebuLoujUxqKhiAIaGt9jG4HTRARzCZ1XNFb3+LpoxFJAG7g0zAclpttBAEqs02ru8rpwQl+HBHk4OclZSZQnE1o2jI9S8VebhFJOnkRk5QiSZKgI1LVMqpRMh09p9XrICBTqSWj+YK4qFAdFb1lEHseUlkjGwrn/oS2bFJSoAgCYpqzsbqEluUstZZxeh2uLK9hdRroqoAsKARxTBJ5REmAJFkQBAiFTEtRaDd0FE1D10IqBKbBGScXCSeTIRfjOXmWMg6nhEqOqWuoqYA6T+mhI5YipaCRlyltUaBuWEzjCtUSCbKULJPo9ns8urfPPFG40V9lND9HFRVOhhFSUbI/9XE0nbgUaIgGSZSgVjXHZwuiKictzmjIEv1ek4vREYUqc3jqI0gvuzBvXVsjC0t+54+f/dOLd13XPxAEYfvPy/t0/BXgH9R1nQIvBEHYAz4H/OgnXaSpEk3bRltR2SlcLnU2eOfsnN/6/mPOfI9Kkrl2Xedf++uvIgYWv/WHJ3w8vE/lZMxCUJQaU85JM5UgzHn77Ue4bk5ZZOiKiCBVLEYlgvgSUfR4f8TGSoMvf7PNl+9c5e57JzSA13d2iOKC83nI8STns90GV66vcDIcElYBq5bO7kYTTe1zMD1hd13j4AjCoMCf5RRSzspylyzPOBsX6JpImRRUIkySGlMRGbopqwOdO7sNGn2HP37wQ15bXqXd0tjZ7DKbT1jddFhVV/jwoxeYSs5kvOBoVnBtt2b7tTahFDLxZpTInJxPGfR1ZElBrhM2rRU6XZFVJeYrn9sksxW+dfk6UiUwWcw5OJ0wPHL56rWrDIcez45OKGUB3TJ48/YS3/rmN3j+eMi7H/+A+0dzzErjk8MFoV/z4ftPMeU2RWVhGArpIuZ0krG9dYX94R47Szq711e4stzhowdnvH9wjJBLLLwYRRYYTWGrqyILBUmeMxunaGhc2xjw1bdWePx0ShwXiIbD8GzG8qpDu60ymweAw8cvAt5Ydfh475halbgYTpmOPKRTieWlBnFWIgtw+Og5O1dbzPwZIi1Gbs4weEqumnRbCaaoMDx9hmJD7Ct0bAlbmVOmKoqcYzebaILFeBLw1a/tYOoaSbTAS31aLQvTqTmtYhBrigJ0TaTbsymqkqwqcXQdS5fQJZEkKQj9EFMTsAyV6zstvLKLqUtYioqChDuLWVvp0t/apExLxhdjtIWE2jfYuXkVy2xg1AoVAR+8+wF2Q8DzIhRLo8oqOqrJ9qs9vIkPZUK3WmPl8jUur6zgbCzTfOU2tWaz8bO/SBm6TJ/cZ7O3y8MPPmQaFgR5SbO3hK2JLPV0LhYVflQAIk4DiqAgTSq8VKA0VeZeSB7H2C2DZs8kK3KazQbNDoiVzGJWs7LpUKYFtpLStmUuLe3QarcpypKF95It2bikY6gKtaggSwaqDEVZ0XaaNE0DXTfJs5cGdaJcEecVoikTuPOXNek0QRJFFlHI0fAcSaoRBQPPj3F0ncLo4mUhB588JUgXyIaIrsnoqAw6DTSp4jz3KGrQTYfQq5npBmIlkC4iWj2dTsvAKlWev3hBrRmE8YIkLRl7PqVSAyVe4WHZMqKm8/TeCZapo1dNVpYkjs9Dxp5LnsHcNEhSkduXuszjnINZxaVmGxmXpITBUsU0vEBSBySpgCT9ZLH9i9S8/01BEP5l4H3g367reg6sAT/+Mzknn8b+H0MQhL8F/C2AblvneKrRFha8/pllvLBmY8Pgw0djJFHglcsyn/+MxWi2II4L5ukYSY3odxQMVcEwJIZTgbOLjCiq8IOQrM6REBAViSiuiLIcVVGpq4rltsHNm220WuHJ4Tlf/6kNBEHlUtLkD95+xNP7J2wsidy82eHh81O+9voVkkTlvb17bAz67Dpr3O7bnKVzXH9CxxJZbjY4OIl5/HxMy1HI6pzNbYe+IXFx4rG0rjMdZhS5iqOoLA8c1ja2efP2F7j/4H2W1D5zbYHTLdk/c3nlushXv3iF7/yTfXq715glJ3x0f4amqrQbHnUUcntrncvbK8hqRpgv+OJn10kWcB5P2O6t8cbSddIqYraIiQto2Tpffv1NHjx6wbv3DvDclLKW8aYxN253yHONe/c/5qO7z3nj9i3ajXMOng25OI2Z5wkDRyFXfbwgZLYQyauaOPWYhx+x1h+QZSp7Z5BmCx48G/HgZMzrl5vYpsHqoMEnzyekkkpaZFi6QJWk9Fc1Xrm9xvGFx8lkTJHXPP/wQ4YvRmiGQttp8cpOk6uXLiHLIhvOCk9OU+6fnEBR0W44NBslqz0QqjlHFwkbq20sp0WYCJyGU9I0pmk3ZR2IlwAAIABJREFUcRA5Ohmx1GyzsbmOREoY19y5vstiFCKaJUZXxp3IdDdNprNTVpa3OTo8Ymf7EhcX95mPFgxWSmZBTCWCBAiiwqDXppZyHr4452RyQb9y0HWNJKgQxJKebbPRX4Vc5PNvbPL48TmuD+u3+wimQcNoYugClejx+huf4WA6QrMtxrNzjk9OSfOaXrPF0cRDEmVKQFJKDBGWnBa2JjOKRjQZEF3MuHrnDZoNG9OQWTx8gv/iAuf6VTp3fgXnjZ8nPHnE1saHnN59giWrLDsaZeQisUCoRMbhhEavi9WUmT46ptmVGXsL/EVFV5coJY0qFwgvTtl0bFa6HS5vbGJIFivLbQaSh5In1KpNlOcgGZxOIuJUpt3WkMQCQ7fRVBFJEsgKhaIWERSVPKtJsoT9Fy+YBAVOs0MSnDEPAlwvJooCjicugZ+iGQqoAMXLMnaSEaY1QgGqKlDUNSudJXZ3+0RFSNcyiRcxaRoT5zmVoFOmJX6Yg6qwKFMETabbV1FLidlsztpSkxu7Kzw58zg/m2MYGh3HQdUyqjJhUdfIfs7Hd0+pchkvSlC0Gkttc2u3zdFFxErfIghjGpbCojIpFdDVMYdnZ1zdWMaqPS7fuc77H++ThBmZrrPUM/+ZiPd/CfxtoP50+58Cf/P/zwR1Xf894O8BLPe02vdO2L7yCq5k4fQrLq8P6No2l7wQ2Yy5vHWd00lKHsW0TYv+ksOLE5fL1zrkacjOlQYfvL9gvMhJipiqEKCuIFdoyhWGohFEL+0ZkyLn4NDn4tzji7e2eShNuX7lGv/D//JDVL3g9nWLN28MOD0J0IQmhZ6w2lnnF5ZuE0Yu9VZGY+GgOxLLP3eJrByxs7bJ737nlP/pt9+jLkt+7a+9xW9992MqKWMWC1xXGkjtAlmK+KVvvEqv3yWtE8K84nQccO/xe/zst16hKAv+6E/eJ4x0+h0JWXK4+/4+s1mBG2T84z85xpTPWOk2OD6c0d6wmE181tZlVMml3VxhUHaZuRNqUgTR5vDwBa3WJl6YcveTp2iawMZmj4PzC0gVqjTn8JMhag2j8xndlRUePz9C01oUkUgUB2QZBGKEYejYloTd6PPJk1PqWiaJaw7OxqizmiA9YKenM+itIR8eo8kdVE1A4qUH+nyRUuUZymoDSZWoc40f/XCfKPNBzdE0EQlo9yz6fZPXb2/RkGu2lltUtU5dy7z1xW2OvzNFqqHbUliyl/j+j/a5stqh1zZoNSWqLGa120FSHd57e486DYgaFYOehqqUHI1KfvEbXycM5tRHe1zMpsSKiTAvKcIZX7h2h4X4BMqcNPf44O5HDH0XTTdJk4jjo5AieykQUZLzfM8lLSRenO9T5jkCBooiIMkyRV4TxQWDhoof+6w1dBQrx25oTIZnFJJA1DJYXVpnvbVBjoTdaFAKMpbRw00Dzg4OmZ2OqUpI4hhHVFjrO7T1JnUmMvEKwigjdwqiwKeqc872XrCYvGBxdI4M9PbvU0cV1rUVDv/hb7J0eRP53kN6gomSlzxfaExLDVPxEcqaMz+iJ6hE009RXw2HnabFF673WO02sPWMjm3QsmxktYM6uMH87GMy75RZEdFpBARuyChwiOKcpIyZewq22aXRFJnPA3w3RBRF4kpFUSxqMWZvb0KzKWPqNY/2hnhhRlYEpCk0Ww6qXiPpMroqopgimiohIyELCjIlcQFikRDmBaWhkxYVJwsXRSiJ4pCqqklzEVmRUBQdQy052x/jdLuICtxc6TMfHRFWNWUoMDEF5n7CV660SXdMnp8l1GJBEIVIiokUJSRA07A492NevdynqRmoRs7o3MeLEkYTlW5DI80L6lpA0S2S5ALFFLn/7JSfurPBvafPeHEaIZUhUdLE83+yPP9TiXdd18P/c18QhP8a+EefHp4CG38mdf3T2E8cuqYycHS6VkaeV2RZysNFgdAwaecbpPIJdz+5YOKfcGWth+hU/PijCzRN5Or2Gmsrm4RRQhG/TVHrHJ6cMxyDH/m8urXEl+5c4nsf3kdWNNqmwtOziDIs+eWvvIKo1bSaNqaY8zf+yh0e3H/OB/cveHYy5va1l2/XlaUluk4XSesyn53x6NEhndYKuTina3TwJynvTY959cYqr2yvczg65XvvPCWrE7yhiGnJvPtkiFbIdLsSv/2dR2xv2Ny4cYUffvA9VLPGTRPOxgvqWsSNRX7w/jFpUvL5L66i6RCGMVkhIKsibiYwO16w3baxlmx2traQRRFdE1ikMZJs8PD+Ic2eyebGDW7s3kYSLO75J0R+zeVXtsizCEVIePPOJb7//Se8/3jKvUcTLE0gfTRCUjUa1ohpGrMz6DKce3ipyNQNWB44iOQ0LIXxIiFMBCSpotdtsenAzHd5uNjD0VXm0zlyXnFxEpEiY5saTsfEC2KiBBauiyYXiGJJt6+y0m8xnXpoDly7usJqt8fN3Zs8ePQe79y7S1XaDDYHfOvrr/L73/mYaZxhmFNu3zGwDRFFlJjOCrY2ezw6uGDhe1x/bY1nz54T+wo1JRsr0NA03v/oHr/w6g3uUXPp6mV0dB6cPEcxM46nQ2R1hfnE43PXPs9Hh/ep6oxZWCG1r7Cycoo/HIEkYooiuZASZwG2pqDaEiU5qibhjxN0oybLoNPqcL6Y8WBvil9V9HUZ05C5e3yOaV1HNRQenO0zHweUdUKnZ3NwfMbZ85if/tznsOSC44sLOus9GppGEQXE8ZzKVGnZfbzhCaZiYJgyeTTh+ON7VLkHaUkiSaR5Rr6YUMQt8iQgG8Ol7RVGiUUpd7h+9QpR6HIyTMhRUcqSNIxZ7nW4sbXOncs73Lx6mTy+YLEYs/AqDoYRS72aWsyJLn6EwjmjyQUxPeYfn1CXAiN/RlkUiELJIgJZn5HGMa6bkeQ5VVUR5gKCLCDLJa5fsbrco9+TOPDmbK8uI5YOp7M5nc0uoRsShxGSDoZhIkklQl3ixjllWiLAyw7UAuRMQBEFgizDUBXyBFRVpZQK4izhUq+DaugUUkWcpNiCQeq5SJLDOJrghiplUHK972CRMY8qCiWHWmR1dZ0wdunqOsO5x0Zfefmsq4KZGyK4NTMX0jonrgsaXYfHT2ZoeoSQCoSxxKDjYMslD15MqfISUaoZDJrkSYIf/DP48hYEYaWu6/NPD3+Z/2sl+e8C/7MgCP8ZL39YXgHe/fPmy4qcR09jQi/g5uu75JMFjtnlePKYyeEYxarx8yG3r1xis7fC8bOHbPYsnCUFWc6ZT+cE/ghTkJGcnK/+6jcYjQXuPznmvT/9hLc+s0pHW6Gx7nPnao+vsEQe1tx9uo+tFawtbyOJfS6tqZiGjuPYzOJ9Wk4DzdbRDR0vGiMnClHq0lhaZjw75dmLhMHyPiI2P/zgHpa+x/EkJogr9p7PubyjY+oKw9OYuMwQFTgZ5zBLmMwiHjyeceF6yJKCVOV86XM1Z4cp4/OCIM2RFHjnxxMGHZ3VFYfT8QLN1IiiBM1S2dgesNbVGPQcFmHEcFqAnNPSuzhtnZ31SxyPjilqAcc2We41WDcsNjtbRO4hNy/dwLFNBktrpPfGKHqFrAjMJiKpkOF5Mss9lbSooNRIch9V7DAKSjoNjXbHQDFVqjRDKCvqwOebr1/nH36Sks4TFEOmyCVkI6PbMxj6JVWdY5g6haQQ1VBQYmoin3ltDVuHTsNgyREQBYPlhkkSe/zR29/l3icXPD8dYhkS5+4Fq8ttbt20abc1uk0VyoqLiwm2qjMauRwfQLBYsNzt8uW33mR1TePsIub54TkfPjhHrUWu7S4xKmW2r79JWeV4kzmOvcr59DmPjz+m29DJEoVHey84GSf0e00Q4P6zd0k9DUOvccOauspRVRHPW5BnOYpuESQpqihSZAV5lTOZ5wRpimZarLQ0jj+KGQ6aeN4Fa2u71LJAHGccnh/iByJXVweI9TL//M/9DGJYkZYFh+fPEYUJ7niCvX0VudVEzD3SaEaceHQdmbatsHJphzwLSPIMkMnTnFqBqhTJpxNk9bMIikAS+qxeu8LD791H6w5oNldJU5/xNMDPMmSx4vXVHb7yV3+aZkcnuzhhuhjjLmLmsxGicE4pwJ/er9k/rQijGUVRU8kStuoSJBAXJbYkYHccZq5Lo9FiEkQUdUltQpCAIBj0Ww5LywbBIqCTJwShx8g16C93ySsZBTBNg0ePz4ijlwDuNauJIsjMpgtajTZdPScUUtqNBs8OTqlEgTgMcTSdipIqBUGoqcoUXVNJBZEiLVi4AYPuGv7MQ0xSDkcLEgEWkUjiFkgdkVBziOMJMipimRDkJZLg0yoUTB1evzRgIaoELxa8OFywMVimYYesmyo3r11ltePw46dPQQJFKZm5hzgWLMY1vY7B+dCj321QhBnTykUSIeQv2GEpCMLfB74G9ARBOAH+PeBrgiDc4WXZ5AD4VwHqun4oCMJvAo+AAvg3/ryVJgDUMioKo/MZx5MLtldbrDopdVnTaTg0BiZRYpH6Ir9z/x49p0ujmdNfapOmJsg5jXZBs7mEHxs8fHbK4aGHPxfQNZPvv7PHL3/ts/hzF6EsccPxS0Bv7fNgf86jkykbDYcrlzZoLhm8/rnbLII+7370EQgSr15WuLK9y8lxxPPjIVmqEKUKk2hMsOdhWQ55IvDo2CUqwdZEFEWiSlSub3WowguSoMZNK0IEFKFk4iXkKZSSRMeusRWL+XHN/qMZa8s2By8W2JrKzE/xFyldE1RkgqBEkzU0Rebukz2azRUkqyQWcwzLos4imuYGyZLDKFgQlhGxH9LrrLHwItw856H3mEwp2Ts+oRI7/NGPjpBUE0WtWO45xLGPWEukWYaqGPT6TWo1JZ/leH7Owq/wFjFiLYCoYJs6Sx2dKs95ngZkRc16r0Uu5KRxjGiqpIWKqaUUUYWcKZhCjdYBqc545faA2TzEDTWWBz2uXl4mjTy6vR7DUcrpOMJLFxR5jmIYVGnOx89OWTOhIGCUSjQUh4baQJNtUBLOzlyuXb/ErTvX+b3/7Q9YRDGq2oRKxDAaDDoKZp3z2//4d3jt6nXkqmZnpcf5o/sYHQfHsAlcn7RImYUBCCJW4xqm6BKRMCSjDBL8sEZWgSxHUgQKEfoti5lbE1UlYVETJRV+WnAynYAUc3PQ5ZXBgPdPT/mZr3wbS8343T/+Ljcvf4PUfZdoYmMtmUgZvPe9PyaJZhSFCJJMVWd4UYn39AmmXGBqFVFcU4k+TbWN5hisX7/J3e/9LnGeIQg1tShQCwVRGjE/O6BbStjLfbiYonQGVFnIw/cfUFYq955/TBT5LK2a/OJbb7DWEKmCR8x9lSgpEIXneNE6d1/scTEOSHKVJAfJUjFba7QNAU2SSNIYw9FptDWKMmQ+Dek124iKiF9KqKKGodSgJVS1iOu6VFWCXBnoTQtVbbw0m5NUksxlFkEQ5+SphirkLPc0XhxdICkqMz/BMiqubXdxHJkqCWloOplYUSsKRVwg1CWFJCGrFXmRURc1iqaw8FxSVeXw8T5CVLOx3CasVEohQaag0zMpSeg3BzQ3ZSazBcMDF8ORyeMU2VJp2y2O53NypUYSZbY3VE5ejFE3+1xaNzmfzQkvUvxRTVXICGLFxuaA4dmMWpJYeBGKmHN4MqGla5RliaBoFMVfULzruv7V/5fwf/sT8n8D+I0/b94/O6o64wtfWCULTcIM8thjEbnIlkFvbcDbP3yIpUVs9TrcfX/CR0f75Ei0W2dkacntmxa//PPXCdyU1ZUlfE/AX7xgMYNvfeY6+8MDNCPgxfmM0fGI3UsbJEnIq6/02NiVON1TmC0yPtk74a2VGwxnZwhSiixY3Lm9w+XVXcJFRRiPuRjHmAJYbRVbN5lf+ByfzAjzFNuQMYqS3pLMPCxJq4T1ts3QMXgR5eQq9G2J2ayg0bFQzYpxmGEpGoOeiZhX7I1niFWFpcNnb+zw/XeeEKMQ+wmZIFIaEkVeEVc1m8sK6Ca+bxLnI8RC4q3PfZnzg32KvKRhi6jmEkpfoShKtlSDcRSgGQlVraJIHZ4cBiySgCiTkVWJNJZAEEmiijCuuL8XsDITaJoSAgI7HY3DRQAxlFVKpmdcWlshLwOW2n3uH/mMxxHSEqxvLzGdzZnOExZxSEOTkJSao/GcUhZZXjFwTJlrmxs8zo54fjrn/YcfU9dbXN1dQxIa/PjuuxzsHXBtbZnczrl9a4AXq2T7Z9i2RNdUWbt8iWePLrh3dIBuCOQ19PUGZ6dTnNYeeVqShgqFP0G2TQYbLW5dvkIWDUnOFR7sHSMJJYpZ8i/80k8zmUVM5yGdQY97nzxhabCJral4s8f4acru5iVERgSTAlMraTct6qqkJme549BudRiNpmiailALnExi3KDkfBLwmdtrHJ7MmBYxkpRRlgFnFx4rVpNk4vL62g3MnS4n8wll7JHEC1aW11hMxgynLrpuoIgSsiiRlQn+LCUOCnyhwklTbm4ZSMTkc5+8lpDLhLQEoaiIpYzADwkPX7D6V/91hDQidCdcefiEd//gbb73+yMexxHf+PwNdjY3+G9+8ztYmsI33nyNjpOiGnO+/+MD7h0+YRHXqBJcXW/Q70s07SZuktI1LWaZR5ZLtGydcbBgGvgQ19hGzma7yyiKcBcBgSCh2TJWQ2WeQZEmuFFG1zDoGAJnk5DhxTnrawZxKlEVNZZWIQolbghr603Gw4ggElCljDCLkNycMgVBhiTKaIoKtWIhqAlmq8XwbISpaEiVRFczEGwVIYtZaVtEesmx59PRVXTNZipFrFsN7GaXPE2Q6oJHx8f0uj0ksaQQJMxK5GQ+ZlbWNLUWeRZhyyZudsHRac7U1bAMgzCcsQhzbu4ss7ba5fHzM3r9S5xOR+QFtDo9RotTZpQYqsjcT6hz/Sfq5l8Kks7f+Tv/wa//1FuXuf/wY2TFhzonjkVkKaXKJ2z3DB4/nhAkFZFQM/RK6qImjSsapoyEgKOkiJSc7h/w+VdWWd1Yp8xKbu92CAIJvZVw+coKdZGiazVxXtHuaDRMB1GoeX48Qm7UPP54xMZawa2NTcLpgAcHT/AWI0ZuzOH5Ptk8Z5plVERkrsAo9GhYBrWokhUxmiTwL/31z5PHAuOJz7PjIfMoZfNyg6ZR8Nk7m8RxRV5EiLJKmuSs9Gwiz+PCjTicR+SICLJIe7nEamsMTxNkAXrLCqoJdSlQ1yk9RyFKF6y0HVAqVjZ2Gc887OY6n+zvUYo5stDn6ZFHHJ0giDpzP+XwaMKzM5+L2Zw4zQiCiJKKEpkoi/HiDC+AtAallPCzhJWGSRwVxIjURU5KSVt86UWiYUJckhUZaRyhaMpLHJwls7XRxl34RHFOs6lwPM6IypqyFmnbFgIV5ydTmo6NLKWs2wYtC3RR5u0PXvDs5JRSqtlqWARqTLvXottQefLkiJOTFMle4htf+BqqVpJmIV/7wpeYLiY8fzEjqVMW2YLFWUHqheSGwaWVPv48Y2NjCVlx2Ns74WLi0l1pYuqQxyUdR8IxTd79aA/DUbgYHlFlESuDJSazgCSNuXP1JsPDIe48p91pkOc5WZmjawqWaX5K0akZeQVxWhFkFXVRcXAyI4wqVMnEUkw2232ajsZAMZlNIxZpgRemVLJKq9XCXZyRRzKlIBMHEd1Gj7LM8IKQs7HH05MFB6OYvaHLytIuv/DtryOZEkePH5JGFWkWI9Q1tlAjG6BJCs3OFjUZ4+/9Du4nj9na2cSdHFEGAVttk3k4ZnK6j0DJPIRPDo+5++SItx+GzCoNydYZdCyaikImllSiTBBFQIUtaYRZQFEJpEWBYWsUWUwtyaxf2kKqKuIsJY9T4iwnTV52UE+nAVWd0+28dPJTahlFKzENmXbbJkpigiBFUUWyNKJSFCohpSpB1SXWlm0kMSOMcjRTZTxdEMU1hqYilDKG/BIooZkGyBmDThdJUEnzDFVWSbOUWq7xvZiW08XWoSgEHM0izV52oDasitecBqImUwslSRASz1PcoqLb6fL+g1MmiwpJLkmSirpUmcxj5kGBqcErV5ZJZAkElY7ZBrWk1duiyHxUBAYd2F7psrEiYJoSoQ9H5/O/3Bi0//zv/savf+tNmyub68xDmZOzKY22xdHxkKWuQ0iHp8MhXhjT6Zl0lJKJV3NlXeNvfHuJX/vVn4HaJC+e0+8NyIUUWbW4c32FIK1Z3qxoNCxGFwvK2IVIYzKKOTqaIGka/V6Xy9dfJYpbpNGCpY7F4fEML1D5kz+9zzRImXkTbgwamFILN12w1jMQSpkorbAcEdcLyPOKQd+hZeo8Pz4lTmoWQYFlqRRZwpuvrYFQU1Yx3a7D4UmKJOaEccb2apP9M58qf7mCQapyVEVgMU3ISgFMhX5X5OZOi0oEWRO5utLlla0lbFNBsXX2nk85OhkRlh6+G/PkyZzBik5VFxQJxKXI9rWr1EIAdUWj2WU4cXG9ksCHLMoJUoFev0OSJiRpjVRCs6XRMEX6qsIoK0jTCkuCpb7BkqPQHLQ5PBlSpBVxHCFIMkVRE4UpjqXjNE1kGdoNnTwSeP3VJbJFztaaxnDh4oYCRV6xs75ElAQMpwGa0yQVcnRDQ9ckOrKDUIuYhoSQpHz2jctcutZgOjvhxckRx+MR/Z4JWcLB6YiZL1AUKVuDJfbPPHRdYstssmE1KYuIpUGf9x98yN7pBEOBK+sDzoYzXhxPOBpnnJ4F1JKA2LSxFBVTNeh3ljFMi3gWsrO+wtnFBUfHPg3bJC8KkiJlY3MV3TA5H02YT0O8qKYWa3IEsixlEmSMw5yT8zknQ5eTszmWWDBJx7iLBbJc45gWaRKQhAsksSTPSjY6A0b+DC+IqYua9x4f8+jMJ8oK+l0TUVJpdjb49l/7Gcz+Et74hMXJOYokoFOgGBJt06HRHLD0pS8wu/fHuGcXpN6YmV+xtbvM2YtjKHLMjsT2joTn1kR5BnXJkV9RKtDttBi0DNoNgzyJCKsaqgpFd6CuWF3aQhQhzioqpSIMQ1q6iljXzGYuWZSh2gaR54KsIdXiS5JNGKPJKgImWRbTaw9oN2Gl3yMJQ9wwYx4XNG2dviFTi1CINXGc0GurGGZBkZUUWYRYK0iCSJYLSJKIIChQZzRaNhkuvpfTbTeJ05A0CwgXCWmWUgBCmCGXGrYjoVYOlzZaaHKBGxVIsUTmJkyTgKiWSKuSsViDrDKKE87GKUolYpg6eZIxDzKSSqRv69x5dRfdlJAEFYeamT9hrdWkyM85vzjk7DTBafSQpZyG0aapNWm2bN57cPSXW7z/4//w3//121ckFNXAnc1IhJB2+xJPnl1w8/qAwHdxbLi0BSt9jS++eo0vXV3la595hXajwx/96AOCdME8kjgdz1GLnObA4nR4jutP2e61OT8NeHb0nJVen2Sc0mmrTBclR6ML7KbBwr2g0Y5pOg0Mvcd3336EpsW8caXP4dhDqBLeuHGdQNX5+qvXODqIkVs6cTLl+WmB69f4cYVqSzzbu2CxqIiLClGruTUwWV5SMB0dUbVod2z8Rc3U8xAzGUGEblfmeJKw3W/S6hm4UcTFtCJwa7K8QBAFyGJKWaa9ZNMxKz73+iZn5xfUosrFwufk+IwSgbPhnNM9n9EiY7zw6Tkmiq0SBRFdU0ZPQ167vs350KVSTbwkRxYzmppAUoikSYQiiuRJgWUrqKXAdJ5xnmboqsjWdhNRqMkEhRKN07MxDUHjPAwRNYO5H1AiUlYqk5lHmtfEYY2maSytalzddgiDhGbLAUHACxMUseALr++CriDJFlPPQylFdnd3kJWQQEjJghChknj11i3isqaoItaXl0iTEKNK2T+bEfgRB4cBqCKX15p09Q7HQ5++YfL5Gzv8/oeP2J8lTMM5F+OALMtptVooVk6Sxly/+hpNSyXLfRBF2naXso5pOk2qUiGray7mIaKu4noZL57OGfR7FGVBLYMoVgSRS1bk5ElBJQhkRUlWSMiCRFwW1IBQCuQVTL2Qp8cz+qbFrctXqauKfnuJmTskSWNGsxixlilFm2eHEx4fDrn3YkiaFdy8tIqiVUTkzOOCjr3MN996lcRPsDsa4yefYMgKtqpg6Q0u/+wvs/0rv4K6uk2VTJnuvQBZwp+6OL0B88U5rlvx5q0+/9xPyURVzcODmka7AyKokkmvZ1ELNXlSMgwSUj8jL0VWlrrEecB8FtCwNLw4QTBkvNmM3bUBnh9QCwrhNIQSug2HpCroNRv02xaWKSLWNeNpTKdv4YU5klyRxTVnZy5RkqLr0ktKe1FSyDKGreK6GYooU9YCiiTTUnR6TYXpLEOQYD5foOomyBFplVFXAhIiRVmRlRkNB9aWenSWFEbzmCWphy7kiJqD7dTkyZTADxmlCZJUEckReVqg6CK6XuMlAsejkHBRECYC1za6xFmMrRt4YUKal4SJiCLnLLdkLFlinhTYFGDktBoilSBgNXTCcIEfiyhayXLTwAsWvPdw+JdcvP+jv/3r3/7GgH5nhSubt4iSCWlS0muCZlQ4Lfv/YO5NnmxJz/O+X345D2c+dU7NdW/doW8Pt9HoAUBjJBCkCJIhQLQpBi3aDnvhlfZeeAVFMBxBOSTb2ji8cNgR2li2ZQdDoihaEAdQQA8Aerzdt/vWHWquOnXmPDlnfl96Udia6/4TMiLzjTef93l+D9QmpV4yWN/hahzSbzo8nT7lo5MxT08W104M1+TW7T6LicfhySmthsGtrS0ePBqjZMYLewPq2KC/PmRZFXhdyWZnm4cHE5ygpmF32N3ewQ+2eevdJzRbFY/OFjTaBluDBk0K5uch0jU4naw4HS8ZDCp80+B8nBOlOlFUkOQapSqwTYFpGVzFJZ2hyb3b+zz+9IKPPjohznJAoZRBmVeUdUU4kUhZUlOTVBWFAqFr18D9QNEKbOKoRNQZa76Or8PNmxtvtOodAAAgAElEQVSchTF6XXFxlVGLElHWWBYMhyayBGEVdLs2VaU4PQt5er6iLgx+8t4xJ5cJw05AmETYlo6sJK5r03QM1hsBUtYsVgWuo2MYGqquEZrEdR2q8joU1dAVpZLMEkm3aWFpLrqhgZKkhWS+LKiUoFA1N3bXeP7uDm7L44OPjwhXKV1TxzZNRqvldZ2bgMCweWHvJX7x4AOErmg1upSYrLKYNFtQoSgr0GswTQ9pWDQ7fTTboNX36fsmN7d3OJvO6fcEb375PqejFQ+enJLImvHVgobvoQuBkjndZvt6g/RhPDpjc22Xy8tL9DpksNbj4NkRiyjh2eEJs+WCnu/htXWePpnTdlsYpmI0i7i9u42mcixLUOsVTd8hjApqCYNOkzjNUQgMU0NDQS1IspLjcYRt1xi6zubuXR4/OyTOM84uQuJc8JP3Dnh4NEMIjdu7W7x6b4tKGGi6TqPpYJkK34QNXSN/9JiN175MFY6RYYzfaXLnN/8enVffYPn4IfMHj2jd3Wf64D1EVSPqktlkhbIhW0bXtERH56ePEua5zqDfZnerRSpzZvOUeFESpzn9QZMqL3A9i7TMyTToOi5FpSjISDJFu+HiGjW+FrDMc+bLFdEqJwKUEOwON9gMGjR1wXq3xzxMafd9hJBYmk6ZlihNY3d3jUV0XYs4NF2auiQsMizTxnYUpmZSazqBcw2ymq5mpKqm1WzhOpIMCBomdWnSCgySJEIpeH6rQRhflxVPzyR73Qb9rgeBTpjNeWHYQYmcqIzJswLHtZkvIs6iiioF3TA5vkixDBPPNDibZNy80SfwPJarAk3U1JXGl57fpuUboNekJRiNFr6RczFd0AoCiqzAcgSbfR/H1Di5mJFkko8Opl/sAmLHNjkbLThffo4hrxiu91kzfOoqoBlodAc7+J7Gp5/9DJkXaBIqarJyQa9vc7UwOLuM+cr2Jrams8qO6LR87mzdpe3dY7H4Sx4cfs4Pfu0u8/mCG1sDTmagPB/T1dkYtpiMx0TJmOPzFVtDRV4sef+Tmj/8vVdxnSa2rjE5e8T953tsdHyuFimDdQ1pBuxv+YwvdGyxIi0Nmq7OOKxBE5Qqw/IDfEzu7L3AwUFGc7LCcyTrd9e5uir46S8jzJXF+sBibd3lfJxiGBaeXqPXBhkxqrLorBu0W33MJOKlG7eomzWTqxXVWULvVoff/+F9PvjgE3ZvtBF2gyKJQPdI5YSzs0uiyGM8WjC6UvzikwWtlk2WppyeVpRKI7cFCEEhFZqu0WkHXEUhugNZXeJZGk3Pp+UY7O+2yJXGT352wtCzSbWSRqAT5wlNp0m7FVCjcTKeIzOJpqAudZ4+vKQn4Xg8p0gkUVYhhYS0YFmW2MaSTqfN3fUOnzz7GY2mieWYLKMCKW16rS6hXDA7TOlt+NSVSVHoeA0fhE4dm5yfHfPGy3dZH+7ywvM3eXz0hEWd8M7pM3JTUpVgajrZKsd2dXQBo8sFWl2jGwlr/S2aa0Mu3ntAUricXD5msNGj22kQRSG60BknK/aaWwRNwWIZoxsVVZbT8jwMFVIWGb1GEzSdVVzy5CJDKRC1oKoVlbzWfmUFta5RSHj8rODmt3f4yc//itky4vB0yjwsGS/mOKbg1maTvc0mqywikR2i+IpZouEJQaOpIcsln312wP2ez+XffMit3/gBc+vfYt17HevGXR78b/8T0fFntJwB3Rf/azZeepGLd99DOA6qzNhq72O+5HB6dEj6iYdvdrl/zyOJYmaLhHieoBseShYgNa5m1y6crtegrhWyyjF8g2m4wLRsknhCnrpIBF5V0TANim6baRhxb3+dskgpkiWFaCMNlyhPCRwHx9TB1CAHDA2rYfLxp6dUmkYpM3LPYDNoEJcL0qxGCJ3FbIXnN6h0xflsTq/TQiUZigLDsFGFpE4VQa1odbtkYY6mWzwdx3SFy521Nnu6i+lpLMoVp5NLNpoGz05HtFsNLM3lVsfiaLkgVzauoxGUOcuw5s5mQIpFz7cYLxLSPGcyTVmkMUmiMQxcqlWB3bcpqbHMBNsySWJA9AjDKcNekzhOqEpJZQtOrlLWOq2/dW5+ITbvf/ZP/+hHv/d3byG1gHBZcjEOKdMUw24wmyd4Isdt2AyCAZ5m8+Qk5mKxYveOyd19h5OjGNtVrHUNOp7PrZu3afg1ySrj4OQjNjY8zEQRl1NevLXDIimZhgkX05jzixmdbkGneYPTywkKQa4u2Rj6zOY5JxchSsyJSo20TFnOK+pacjid0G4JHL9Bt9nDtiJ+/ztb/OEPXmJ/q8MqT1jMIyg9/pv/4td5/c7L/PnfvMU7Hz7EcnWyGpK0ZDqdUVQ1ujLQFDQCA4eSb765xqDbZH4Vk+U1nY6NbUuePF6xv79Oo9fi2fEBVgtutgd8erKgMHRyFTLsXbeXFLVOVTlMLhZsrA1YJhqHhzNkrpGmAqkkrl1TSMXawMa2HWStY5oWSlM0WjpCl6DpZIWi1XAZdiy++bXneOneC6wmGYeHVzSVxFkzEUCUKlA2nZZLEksW8xDPg1de3qXKVqxOI5JZSKokmVIYjo3vCNpNC0MIaiHoBA5b+7v0mh3G4Zzz8ZSL8xXLRUZdwws393h8co6GyfkixbQ0LKNi2N+iTMeUQidKFG98+R5ZUvH0eMTJ6RWLZYxpCoQuMAR02h5JnKDrAlnVqFpRq5rpIqGqS6I4YVXoXC0zJuMpNzf7vHR7n921LqenI6aTnEWSEE8rGs2AKMn54W//JpaoqFVGWSa4rk1RlRxPM5JCIoVASoVUCmGYCCHQNQFlTaNl0G10+OzgmLNxyHhe4jo69/bbfPnlTbyGJK5KTMvjbDni5mCfi9UcR9TodU2r7ZMvVuwEHapsgWussfHd38AZ9Dn5k39B+OSz6zab2qE92MF96T7jn/8HKt3ELCuiZMbdL7/I4dEx83mBVwh836JuNem3PDxdY3u9gx8IojhhEqYYpokGmLaGQOFaHkdnY1pei4YviJcZWB6D7RaT5ZJuJ6DbdPDtBqZmoQEKSVhmaJZJlpZ0Whbr/R6yqIiKhEUcYSoDv2uhZwWe5fIsCklSkIVCKxQ9P0CrClCSWaHIi4qGHyCEpMwVSjPw2y41itOrBTLWsWydXNPYCfpEZwsCu4HR91jGEZbt0tYNkkwSz2M84UJUMFM6eaWx3jFoihqRa1jrPlqpM5qHdAddDo/H9Boem2sNLi9iep0mN/YGmHpyXfbR8GmYBVfzhP2ddVQdUyqNVV5zNIo5OU1p+Bpb3YB3Hlx8sWWTP/7jf/SjH35/G1N3ubW/hV7rmNWCREoODk9Z82s+enjE5rBBlem0h23iekWpSeqqT7Pjs76xgWFqxFGF46Ss9/ukClKV0mgkOA2TVtPh86Mxs2LOK298ie9943epcXh6eIxl6GxvblPVJZ98cs7T4xWmpyEo2dr02Gz4VBqcz2eUscJv2ZjGBm1Tw3V0LKvmxTs3mRQlyvDJs5Ra1fzgmzs0Wxv8H//ur1hlgmcXc9Y3fRwMLs5XuF5Av+dioiFrSJIMUwSMxkuWieLr31kjCyuGQ0jjmm7DZnvLYRGGRHFFlJgcTSPiecn77x/y9GTJ5mabeF5y+nTO+x8e89mzSx4fLjFyQYqkxiAtKgxTo9O0CaMS2wBDlAhMlFKYpoHn2gz6XWRR0O34xGkGmslkHvHZ0zPeff8JGJKgafMf/eAV2kFw3bGZleQq4mqZgDCuIfVxSZSWaKaG4VvM0pBmYLGx0cSwoKwr0Bz8lktRpfTbDstkzjxOWEYxpmEg85hBN2CeSqSW01sbMFzb4Hb/JmtBi6PRY5ygR51KGkbNPFnxzgcf8OR4xGKekOclmioJGi5+w8ANQNMrAs9BVjVFce0HNm0HKQs8R2AailvbfTqBz0ZvA9dt8otPP+Arz3+NZT5ne3ebw0dXFEVBWV+HR7YH2+T5gkqWmGaArQsenS5RtUmtJAL9Wn7SBSiJUjWqLjmbxVyMrqjMki+92GO3rzMY+mR6QZnENDWbOK2QGmh1zfFozgub60zmIcNumzBJkEnNTruBIzSKVUTnxVdIzw94/PZbGAjKokZYOvUqovv6d0kvHpDOU1zX5fZXv0P3q98mIOH4+Ihwcc2gqYscKWr2bw3RrZJEKzEci6oU2IaO1GpWqby2L5YphmPg+A5JEtEILDANZtEKE0FRVjiOS7wKUSjQYRFH1AJMS6OSsDnsUheSMJmT5iVFVjFsGliWjoeFEVj4hiJeZTiOTRwXlFKj3emRZilhWbDWsImRNLouCANsE4Rgkae4GGx2HG7tNlhrBFiWwTI2aDgtlnUKSpCUJWGYgilIqho7znkaZSyLHJXnWBo0coHZ95lEOWfjFdFSwzBqVhHcWG+x3hboQhEWNYPtdc4uxnRbDnWR8fji+s/MC3SyouLkZMJ8kXF5lTLstdkYNqiFxs8/Pv9iD+//8b//b3/09Ve6/PzBGc2gQZZGJCuXwK3oNxv0B2s8OY5x/RzDtJB6iesaIDwOnlyxOexzejbHsioWiwlJXPHkNOHDJ6c8/GTCzm4LzICji5j2QMPzG9TknJytKGTNBx895v2HVxyfjpBlBdJmEPjcGDQ4vcwp0pSnp2M80+fVV7dAs3h4PEGudObLSzRbY3frLuM04fDwFL2y6Ptt7u21efXll3j3ozP+7dufMZ5GtDyXSlMs5jlZBUpVpKViOPC4uMgIPIMsLbhKC5aLCkMoHn++ZPvGkNVCZ2Ory4NH50SZ5Oh4xvgqIS1zek2ds0mJaZvYbsZ8mhDNDT47nWBrOpeLAlUpAsdkuUjQzRohoNuxePX+Boswo6w0irSgQiHLGlXXnJ+MSbOaeVIhNMHdW30MTTBZzGi5LtvdLnf2t/n4wed8/av7oHL2bw3R6hzLNKnKa000XKWkhaDWFYZjopsaQnfoNDxee+U2SS55ejbGd+G1l3eJ4hUHx2OSLMPQa1qBYNBtYpoW33j1TV6//yU+efAui2nIYrVgNB/R7Qe0GgZ3bj0PRonpahhCYWg623tD0iQm8CSqFgzWbVQu6fQDomVKu6HTCDxyKanqkjJPGQy63L2zwXDYoyxytreHTGcr7t14Dt/1sQPBMkk4Ppyi1RbDQQfPgiwvSYoCQU2a5bRaTaIoYrEEzbwuAhDGtW+527DwTPCbGrdvtrl5p4nrKXpWgCoVnuuSxjmq1KiVQuk6oNMOXBZ5ga6btB0Dx2ti6im6MNhp9LB1gWU4NG9vsHz7r8lmIakEYdiIWlEXGZ7bp//mV1g8+oTd7/4OuTB5+Kf/kvloxd27N8jiBek8Q69qTMNgKaBha8yjGlXBIo6pJBR5To3E8g1qJdFNG03XCIIATB2trqgSiWEY2JbFapUhdBPP0lhlKxrdNgYVeilwaeE3DCYn5+hSA0NQ1xLPt4njiDyXlKXCMz2yIkPXjesQkjC4vTlgulpiOZJCFyDBMHWKOidKKrK0wLEMWrbDXtDCthNm8QpD10kLid0N+PzsmGUeYWkGrm/iWzrLKGFepEwMHcc2cEXFjVYDERUUpUYZWHS2XmE5D3n53hZ6LWk0QRcBeS3RNINB24Y8wfVtRvMZhm4wDyOeHp+jaT576y5hmlGmoITGIlIo3eWTz06/2MP7f/inf/Sjf/iffJnFtOLjZ485PBlxOl8xiSsmy4zp/ISX9jZ5eHDFPIoYND00UuLl9Wbw7Chip23SbrTZ2NpgNJtyep6zmIV0mzV7O2ucnKXYnoOuQ7d7l/lyiaYc/s3/+xaGr7G31WSjrbO112CySvjy823ubd3GsnRqKQHJfLXi5DKmtm3qGJ48O6LKFY6eMZnPeeedp3i2Yr2/iaxy3v78IQ8uHjManfLyiwM2ezuMJleMpxVFWSO0mjStabomq7Ak00zipMA1DYSlkaYls2WFaQvGlwloimePp0ipU6mEMNFI84qNnsPXX99kvEqxHUG6KJgvUjzDZjybE1YahmmRpZLaBt20cTSDQlWMFpLzixgpBZfznLjQ6IoWR5MFRVpxNStZpBplVePoFp2WzcZmh1IVGL7N4dmYWTim2W6R1BU/e/+I84sV1DVCSPq9Bpaj0ez4TMYxgoq1XkAWKWSSUyxXZJbN2cWCX/v6HXSheHx8hZQGpoQbuzfodDpcjk5J0oTTy4hHT0bMpgtkmRJ0NK6mM2oDTLeNLlyW6RV5Jbkaz6hVhufCWm/I9k6DTq9JvMoYNBvYQrLe7/HK/VfoDT0QGu2mh8qWrK8NMUyf+SJkbdhjb7BOUzPZWGuzWkX4rkEUL3n29JhoITBqg/VhF0sIbAGNVhPqConE0AyCQCNJS6KkJJMCWUl808ESBt/61j6dpqLT9Oi7ggqBY7kMbZfAlTQaGmFakFYarmNiNVwsIdFrSSJyxvOQq3HCYL2FLBQ3ghYt16DRXqO2JJPPPqMqa/JSkhcZ1BWFqqkvT2hs3mH969/j2Vt/QXzwLpUSlJWkTgSv//o3aTYFeZhxfnKBn2l4lolJjbIMtBJWSUrbd/B8B83QKTJJlEm6ls+iylCVhFJhuybNpssyjMkLRc93eflumyzV0XSTKlnhBwGj5QJhKMJwSrvfIqxywjinqCArSkqlkVQFUZaiag0TDV1TOI4AraRhSgYdj0WRY5omRa3jaCWWcW1JtC2bqpTURUxUlczDgrgsULXkfDUhyq+/s/1Bj03fALlkDYdnRYRjNdlstNgM2qxUxbSoMHWJ42tcTsf0Ow22Bk1qVeH4GlJClucUWUoWZeiYZJWkVjrNZsDFfMlkAqZp4to182iFqsAwNRYzhY7BweH/v2zyhThYGprGOx9NeXgyJslLxpcS3Sk4u0hoBT5J12DTX3J6mbC976DpNt1em46n8AyLRn3FXM+YTp+wY22zvbVBXkxAt1jGggcHEa22iVQgdI8f//u3oS65s18TznKaRknmW1wuKkIZIbKSQmWURkbXN0A5rNk1thswn0mmp+fc2nue4+kVyrIxvCa9bg9Ns9jZ7LBzc5tV5vLbuy/x4UePqfJHNG2Tv/npZ2iuoNBAUyV6ZlLoBUVU8/pXN0njgL/66UPSRsXmus/+jSGfPrpEM8A2FZWs0U1BWcWseT6TWQ7A1aTg02chPc/j0ydX6FpNJC2UTHCbDqLScF2dRagRp4JASHbaHqsEIq0mVw5n4xVZaeJoNYf5jNtBk1GUIoRNKSUqk1SUtJtDxqOYju+TFBWWofPaq3d47f5z1FXFxZMlG+ubvPfwQ4JewNb6Jk8OR4yvZrimiYVAAwoq3MAnLSWPHh0xmkgWq89wDIs0LwnFmDfudulbMzA8bnz168ha49HRMcmqJowvubk95EuvfpXRaMbZ5SmPDy/oD+DF51/h8Nmn9PvrWJbDcjbm4vSUnb0hszxkfWMd8pyd7Q5JWWD5FkK1MGlQEzEYOFycL3jy6JLBWgeVwOnZOYO2y/HBCGk6ZM9WNJptJmFKpdVURU1cFizmCf27+6hK4FgBy1WM32qSlYrf+vYLPDp6QBbpLOIE02niuAaj84jbd7dZRlOE0MiTFVltEBU6lm8wURIn8NCzgrCQ1NMYgaKgxnM8Srem0i3KSmexLGDDJJM19tY2i4tTzkchjm1RVBVZllABnl2gvAarzz+gtfUbxKePaFp9bD3F6dg0t/bQWm302mFrZ4ON9T7LcMLl2YyO6+M3AtJGyYblsdawOBpF1NJGr3VUXeJ7BrmuI6QkXeY4BkipUBJULcEQXF6Y+K5LWSra3QFXyxSroZOXJYZpczxfUlUFtVaSKa7BTZrCtTVErSFlTcsxaDYbJFWKUaW0LIvS0AkaDRbLEEvp3L21xng+59lZSacrEJXEwyJVGbVWowtFXkf0bAup2XSFTTgq6ez3GbQsvIZF2fC5WlUk2YpFkaKZBhuDNreCmlzA46tLdNchjTOklJjCIi1Sdne6OGZIONeprRUnF7C/HdAwDIZNHb1UvHBrDSUjtjc6TK2YeFXx4j0HWf3tHZZfjM37n/zxj0RpMJ7NqGuYLDMGfZ9Ow2S5yqmpETo8d/8Wq9mK117c4uhsQRyHZIXH+89O0MV1a83pueJiHLG702Sjv0avM0ToAtvX8IMmn35yzNW45Ogk47NnE4qi4IV7e7SCHqvljIcfz7lzd5O+22EWR1QiYzBwSdOMOMtIleTiKkIkEMuCaBYSRhKt0eZ8dMmdO7eZzB3Kas7F6Clv/fIzDp4lLEcVpixQJazKEluHNhaTsqTXDIjCClEmuHqNYQsMw+H2foPpaEVZWdz/8j7TyxmWblJUkjI30YSgoRts9QVOy2b/xhChley1WzhOCpogFzBoWszjDN8S+KbGesOnF/hYviLoBaxCyWyRoguNsiwIHI9FlJLUNQiF5xiYmkBWAtN3+PjTI2zPoxYlWVmj9IrD41NWqwU3d7Zo+DpKFxRCZzwNQTNJk5JVVBEXJbZlcvvWGkLXOBkllLWAGgSCulJ07JrnbraoZERvrY2wugSdLqU00ITBsNdmOp2xzBRxJqmkwnZ8FquCd3/+GZejY9Z6G6RxzFu/eMBsumJvt40fXFP8lGly8PQpN7e7aErn2ck5B08v0TSbG9trGCrFNzWMquTNr32ZH//lBzx35zmcoOLtDx7x9OKC0SxisqgopGS912F2XjIY9pjOruiv+VyOxty5fYOr8Tl5UVNSYwqb3/v+tymznKPLGVfTiJ1+g4bnELRdhICzqwWGJWhbJtJUrGpJLWEeppiOg28L8rwkqxwuTubYwkTUkCclSsY0/YAX1noEumD7a19n9OR9nj48pTb067SlrGi6Nq7v0ml36X7j1zE6NuGnH2EZOqYObWeN4Te/S/bWj4minNVqiZ7U3Lv/Om/8wR/iplcUl2f0fB/Lsei0GyxXOe1GB1WWOC0DN7CxdMFoMiVMKuJ5QhpnaJrO+maXqlB4ts88jq//ACdTdMujLGY0PIckCylqDdcySdOCoqqpZY1rWTiGSdPx0WpJx/NQQCEUa5ZNvsy5t9tF2CnLpMK3bDoNk/1Nm/hXEfy1ZsB2XycXEk2Y9P02Td1GCcVVVHJvZ4MiXLGoNKZxxKJKGY1HnK1ypFZTa7CKMizLoeXA+ShmXpfYls18GqKJ6+cWhovKbXxf4QcOaSbRRMk0zFlEKUrY3NndoC4Lmv0mQSvAdU1u7e7g2jqdVou/fPvJF1s2+cd//I9+9M2vrfOVV9pomke4DClLxZ0bbXQdylJjZ7OBqSweHIxZrBJ2d3d5/70lb336OffuCu7d2yVa1Xz48QVJXnB6uqIixm3AW+9e8PTZko8+veDoLGMxTbCl4vVhn6ah8dF5yOMnVyRRRVJpTMcxyULyZDmnSkOE02G9O0RpGZ8/XXJ+mZBWMc1GgK7BdJ4TpzGi9vnF5yOqakxRLHjh7usEesrJ48V16MTSeTYvMDWQlSJDkGYSXWkcX62oZcFw0OJ8lIOs+O6vdXju1g3KKubhwwWaLvFsm9UiR6tqhF4TeC63b0K3Z6FLhW4azOZL9vsWr33pJo6vaAYmeaEzCCz+wW+/Qp6mHFzMiZSFVlR8/7tvcHQ5oywKSkNhKo2l0rBtgevo1FVNXVfkNYxHK8pf+c/LtKJUgoZfMp2kXC2XuIZGJZY0uhbzyYqTs5RkVaLQCaMIgYFu1KwNWsxmIXGi0KmxdQ1V5mSlotZrPM9h7/YetelyNs44O0k5+PRzOo6FqnJmyxi75fJnf/Eh7/zyEQ8+fMZnB+eYTkArgGgVsooT+v11ksJgMovo+B0sQ9G0DL735S/x5MkZbjvg3u0X8fw2b/3ifRZ5xcbOFr1+k0W6Iql0BsMdgmaPBw8/ZzpfIKWi1fDYXR/Qbg+opcv5yQzXETQ9B11boiG5+dLXCMMxUtYIXRLHkovpkqcnV5zPlrTtgDtbbb712h5rbZOBX/LG87fRFYwmVzR6XeIwwtQFrq6x2Q74zmsvY6qCnWGb//wf/CZ5MiNMagwpMCwPrTZ57cXnufvN79F5+TniwyecfP6UURjiCx3b1HBsl903vsfGD/4zlGaQHR8yfOk18uMHiEKj//J3qBZnlMcPKbKQZDLGkrD7/f8UTU6onj7juW98DVWV9CuNVVUx9B0ykVPUBeOrjFavw9HpGUKzKDOFlAZ+w6ZSGo2gSWBpDJsu57MJcZxSagZ+w6UucyzToVAlnmnSsHSiKANhI8S1FCGjHBMD2xM0HQtVp3Q7HmWYEaUl80WBspusBQEChdAEmaqYLnMMr4Ejr51Rx2GBK12CroGsC2YRoCSFtNne22ISXSJqGIczcksgEbQMSKSNnle0DIsiLdGERoYilgqFju03mMwKoKTVbNFqmVzNMy7HIaZpMw9TdMOg4zcQmkaz06LRalHkCfEqoyoTigy6XY8//8nBF1s2sWwHy9P4/NHk2kzvNtnZN3A9HTcxGU/mPHlasN6sWO8alFcFh+885IXbTV58fZu9/gDX88m3HN4zJyyWOVlZMglTXhE+riF49+Hq2llg1BSlYCVB1zS8wuf8corbUES5hl7XFKuaY3fCV26vky91phdjUDUfvD9hGuesrdnsrXvoskYPLIrIYDAI2F7b5e33P0FoDlWu8+4HP+X+9nOE6QmOpdFCw9Y0fENDr20WRU7Hd/nOGzt8/GjKaLqgmsy49dwa/VbAwZMFgasRLipQJaWUuD2HajLHMWzW13Q2thQdz2HoCKrM4MnlDGkKbt+/zXB4k6UquDwNoSzY2tmg668TuIfcf8nm1vY6Hzy84v/6s7e5u2azsH2eTa8HcJGmaFjXGFFZAxoVJZ7lUpQlZ6chupQMdhyGg1uU8VNy5VDIlNuD27zz6SNqDTZ7GmksSMsUz7Cwm6CkxmefnBL4HlWtYQiBawl0S2eRK7a2WgzXexyeL9jc6fLs+IhsLiHKsZiPx3sAACAASURBVNKKref6fOvbb3J8fM5ay6ax02N6OYFMsjlsk8dLZBkxnyYo/ZIqhW6rxf/56H2++dUbfOP+fR4dXpDVgqG7zuHhCNM12dnuUYQ5f/WzA+7fHjBobvLek3M8e0GRF2SlosxrTLPF7s4+NzZ6tDtd/vWf/DWGoRMETWq5wnNN6qLkg3d+hiVyfN0ilQJZKXbW15menzH81aHytTd2aQYBUarYu/Uc84sFg6ZL2vMoCo2t9hq7gxaBd00GTOclDb3Dq1+7QRmVrLvbHOQHnF6uuIpmGErjD394l+HNfcqixBtu0O4JmOoYusD22tz69d/C2drk0b/65+SHT+lt38D/jT+k/72/j0gz7LtvUoXnBHdfoitD9kvIz6/ovfEqi598iq0VrD4/47n9OxR3StrHh3xw8RhXd9GXOa5jM70a4ZkO4XKOrduYDjimyTRMWUYpzX6Lg6MZnjBIrYR0aZISsmmajKMlQl6joltth5tbbZZRxixMr4+h1MR5jB20WFUlAEaisBoB7cDARGcSrXCFxiKtcEwLU2p4ukG7KFnaFRdnCfMoY/Pmc4TllPw8JdI1Ou0eulbz4cHHCKFIs5KNRotVVWHoNYO2yeXJjJZucjGfkUcGg02fWvcp05BalWSZglLQH/q4ZkaVQllECARxLBHSYHfQ4+aezyKaMU9SsnpBtJiRpjrrwy7dbhul4r91bn4hhreqK8JoATY4lmDTaGKiWK0KZClpmC67ayZ7LY92K+DF5/Y5n1fcubnNwXjEVtfj8jTj85+fUxeKOJasqpLFhWRyccb959dxyylK6eRSEOUlQ8/gZBLT3tdpxyVS1gS+z5fu7vDSzi6fHH/E6CzjdBTy1ec2eOutI8I4QVk1ZWZSKYOvfnWDNG2wMbyiMl267Zq/853nidKIy1FCq64x95rc2mhiaymm5TNKL3j55i4fPLmk0EqEZqLpYCIJPB1RaxTxgttfGvDehyegrVjf8OmvGxyfTFmuZmiGQbNb8+vf2qPbl6CaLGaX7O1vk5iCQuU4Zo9/97N3CZcRy1HOeJJjaiP2egd4rS6HR4ekxTm1qGlvGEwXBctlQcPzcM0SWbrkNVzHoWoM08KrayxxDdV//tYOR0dTljPFo8djtoc9vvPVr/Pxw3d568FDHn6+wrEVtmWxe3uN6XiBY6W/+vBqzk5TpCxZs21s16bVajIeTdlbd9kZ9rixe4O3fvlLwuWc+aIkCgv2dpos0pJH7x5xshLcvTHgt77/Dd7++S+5dXuDs8szup5E9w0WUci9O9soJXj89ARdz9kKDLqiyZ/9+Ocs0xlrw4Cg3eHzxwck8RKJ4OhsTlIGTC6n7Gy0OXi6IM5SWsGI/RvbrDIHE52PHhyga5LzyZg333ydPzl/F02zQOgUUtENLDIlUbJmulpQ6Q5JWRHFCf/x736Xf/6//zkba7tMp4qfvv0Rsja5dXPBoyfP0DQHWUOlQCdnlSYoda0XG0KwNexR5eucjR4QrTQMTRLHEdqvYuIffnrA7lCSjpbc+d43GWz9Dav4BNdr8PIPf4ciTnnrf/1n6ElOJ/BJpxZXf/q/0P/d/wrRqZn/+f+MUi6VYRNNTkhXOaLZpa7+ku6Xvw2LOcIf4G3dw+m3CDY/xf+gy599/h6+a5GGIVGs8Boe61t9irLAdhxmowRdCKL5hEeLOXEI94d9LMtAc1x0XSMIHGI9RRQ5hSopRE2ZSjxhgmtR2x6pllALg0kYUrkmrm1gS5NCCDzHpUgzTGGwiEo21tbIqwWPJ5INW+PJ6RLR8LE0A1MzOV6cYSYlN/sGk6WiriSOUbMedDCoqO2crCrJUWy7NnEa8uJWG1WVPHgWkxsaHz2d8+bXX2TLHHI1nRCnGq5bI3ON2rKpNcVaJ0DXJLbv02lWtAOLcD7DFAK9rFllIWWmkZU582WGkgVl8bfTtL8Qssl/94//6EfP3bBZhCXLZcxyKbk8XFKjMDD5zrfv8bXXXuL0ZMrShA8fP0a4BbNlxMnxObIosY0bRNUIdy3g2UnBdBZRlDVZoTi/WqCZBm2h2Gi7VEqxCCuEX+IELlld4us2/+Xf2+ONl2/w4LPHvPP5GeNFSeCaTMIl3b5Go2VRyprNTZPL85Rhz2Nj/TaryQG2W2D5NU2/TbfZ4cVbd5GJy2h+iq5nzMYl7z2dM3B9nl7FnMUFaSEwDZ2T4ylXK8lwzcO3NDBLNL0gLyHMNOK8osjBtX3G45RW2+SF2022ew6W1WQZTyCWzNIR6ULj2bMRtTBJZzG3Nxvc3epjWiZ39lq88/5jGusttLxivbdJr62z16/5/ve+RbKKQaW88uoGrYZBkpV0uz5KSaS6frEN3aCuFVQlel3TbIDtGdzcabPRHlJIwaMnx1yMEuaRYDxLmC0TTKHY3rQxdAvbhu0dwa29JtudLje6LV58bhtZV7hNl3ceHHE+DpksZuhSp8or1gfr1yRJTTFdShZhyCIMee/DJ+RVxZ1bQxpeji4Vww2X2VJiGiW9tsHmWpv97T5r/YCT6Zw3XnyFdz8+Js4rLL0iySpUlWPZDnFesVpkNAyfxXTO5SQjL2rWh0MmVyPCVYpp69xe75AsVxwcjdnducnTZxfIErrtFkka0u9YTMOCpKhAaAhx7TDZ3LrD2dkll1chpcwZTeeklaRUgjiKkZqFlNe6alkVGLqOgUDJjJoSXTPoNBvMV+f4QZeHTz7lcDRnskpRlSQrc6aTOWtVjJyN8dfWWdvbIDse8dIPfwB5yrv/6v9BRjkKA903cR0fW9Nxn/sSy49+TPTwI5ZXZ1w9fo/Z8TNWoyekZweU50u23vwdzJsvojW66LpLjY97+zX8nssGNR88fkytC5rdDlVVoGsFGjWUNZ6nk+WSKJastQJmqyVXdYJjG0hVsopDLqMEVE3XNjCFYhqmVIVJNs/JkpIwV1S1gWW7NFsmaZojLANdr5kvU2qpYegGpZB0mzrLXFFUBUhIqoxFaeC7DjItqZw27bUNrPKKUubosqCsSpSQnJ/NMA2LjWaDea2TznI6PYP1hsPRrCAcp1SmSatr43geaVYShyuEcMiUT1JKzs7GdLsN8ioGzcbUFZ5nIuqU2SJhlVpUtc2NnRvMwjHn85w8q5jPY8JwTrPV5Ke/OPpiyyZFqVB4XFyek6UCtxHRXAuYLlI8T/EXbz3lbHzGqy/uICkYzwVFJWm2AiKnICubnMzform+zi9+8hQoaAYWeqqTFRlS6jQN2O8ovvbGDkUAZyOTh0dP0X241xuys27w+ptv8ORRytdeeZ3PDkI2hzW1pbHzwh3CMOHjgzOEsJhcKeJU8ouPJ+TlJ9zaHmI5PZb1Eq1K2b+5h2MOCbwuj4/Oef/RmFQa9PoNjmcxpiFoN128NEXVElVrdNyaWRLTMK+3qyeHc9ANNKEDvzqS5CV1XfN3vvU8QVCx1fHYHdwlXD7h1F+RVwXvf3DBRq9Hupxy/9UNeoMO1azkG3s+ntFhe0OnLAtSv4spBes7OwQtnbOzEbZtoumCZwdjTNvG8Qxc38AKS5oND0O3SFNFXhgoYdJeq3j+1gBNU6y1Awp1iS0SmljsDGouFgVlZRItUrq+w3Qp0ERFVei0Ax0Tl3mcMthq8q2v3Of523u8++kvOL7QCVcTNtc6LKIVnmdxe6+HG3j84tOP2NyyOTuOOAxzrJaOIXWOHj+i1zW5ebvLZBnSX/PY3Vzn/o098igl1Q3OpiOSixH/8sd/jZlEnERgmZdEUUiz6bBMl1zOSrKoRFUpRqlwDBOFJF7OuN33OVCCYb9BjaLME2bjhH/947/EEj5JlFOuSaSSSKlo+oJ5WFPWoLICSzdJFgtGV+dYukKWBUlWEZcluoJZLSjU9ZEOIXAshSoBS5GUkKcpss7QRI1nK45Ppjx+MuXZeE5g2MzlNebgs8tzfvnI5PW9Lmc/+ymv/P4f8I1/uM/09Ih//y/+b+o8R1aKpi6Q2IhaB8vD9Jskzx5xFS6YhwlaXlAVObWmEfgO/sY26XTE4Z/+E1bjmKbl0Fh/ifW//wfMf/Y37Oze4e9+r+Lf/Pl/YLyMqTSNdsPBtkyUVPx/zL1XrDRpet/3eytXV3XuPjl+OX8zs5M2iLs7u9QGUiIpijRMQxIlA7yxL2wYsAX7hqJ0oSvb8pVBQrBF2hBJMYjimvSS3NnZ4eQ8X07nnO/EzrFy9sUZA2vLWgneGz433XjernoL6Op/F573ff6/ktCxtJD9oUOaF3z5mQvc2nmEqpeRspTFapmqbTIYzRm6AXqRUwpkerMpfhxS0my8NKZRsQjigJKm02pWWFgqEc6mTL2YUMoYT0bUSiWqizWmPQ9NrWAmCYVRQ9VCskyFloqlKTTtEeVqjaphcXLSoe+EZLlMs25SCJmxExKLjFhI9AY+H7sxNVQqpkYSAzrYhgKZymwWoAoJWSkTzoZM/QLDUplOEtypjCwyiFycyMSbzVhp6xSFRGcuEWQK20tNMjIGfYdmy4TC/ZG6+R9C0lkHfhNY5JSc8+tFUfwzIUQD+B1gi1Oazi8WRTERQgjgnwHfBnzgl4ui+OhHzZEXBbVWk+zJCXkO04nCeOpx4WwZRRa0qjqGpnL20gXu3+7hhn3qVUBpkhQzQhEg6RaPdvdZ34aN7S3eeespSzeWeO0HewRFRpEU7AYK1nBO0QfNVBmOXMJE4cb1Mu16nU/v9Hj1rY+5sLnFlWcXCKYzkKrcf3BMZ+ziuzENQyVLUs6et4kcyHOfVC0jFAc1ttjpnuDEO5RLIyp2iw8//gQhXBY3a4RPuygKpCJBFoJKRWfqZCRZiqmKUyuHwjg1C0olchFTqZaZTRw2z9bpd2aY2wbHY4/00YjFy2t8uPsDCr3OsT9AVmrYVZ3rlze4cfM6JWuV77/9Hm5yyIMHR6wvNNGlhC997iJRYmDmNTLdIFdzKqUuy22Ho6GOXMo4PpxRb1foDHw0VUcRBZqi4iUhzz27xqcf7bK03Ka5sMBwPAQ9RLcNNqvL9EYOUm+KpqrMXYmkFKFkKVVZY3G1wfHJHLPUptWqs7IOK606r733fXSlTeQUXF7XiZMSsqVxkkYkhcR+d8BoGkAa8+JLlyjSh/S6OQ3D5PLFJrILzrCLumFCOGehnGDJKbHQiOWEQs4JApVUmPjJhDzMECWd7smMNItw3BjHj5EVk1q9xHE/xNIFVxdLHI5Dzp9d5GKzyon3GGc6Zml5HbWcoJYdciXFNMEJQqZORMs2SPKCJC0ol2oUUk63N0TWVZLMZ2FlDem4Q5pmBImDN3Fx3JgwyRDitG1eKAqVkkzgTRGyBEWCyMDQVEpaxkeHA6apYDqOmSYyiRqyVhJ4Gvg5HI3HnG/U6HYO6Nz/hObWCq/93r9iNpmBEGiKQp4ryEIhI0dfWqbQfWbDMfPRHDcI0QVEUkRVtWlqC6z95M/g3Pl9EidBkiRSWaa0uEiauMy6+yS9ERcvX6X6d/8Ov/Hb/yuqlqIpCr7jsL29TDJyaS2XMW2FyTikn89obNbJ4hRJUpAKKNyQyE9IZAmkAokESS0oWRXcaYhpm9QrFqECofDQDYt4GiALDc0+pVhluYJDTs/xkMQpMSeREpw0wp276IZMmgoqWhlTUhn7GYQxQaZQ0TUiWaaQI7SSz/FckGoRpmUzi1KccUazUWFbU3lnPib3dHTNJ/ACEDaKqFK2QlolG1NSUTINU9bAyGm1yhycTJHJ2VppYWoZBQGT0W1ErFFuFDihz9z3mBzGjMezH0+8OcWZ/VdFUXwkhCgDHwoh/hz4ZeB7RVH8UyHEPwT+IfDfAN/ilF15HniJU9L8Sz9yhgIyRtQbNUbJCE0TxGmV2SxDlgLObjQYDCN+9w//DEk0GE/n9OQSk6UPkGRIA5m5l1BvFMShxfff3EEtK9y7vU+5pFBXZMr26ZfYWlMwpTVef/sjbLtMHHqsri/w0b0B7vSI4czl7t07fP6FBqvtKiM3QHMKXrzcRMbg0uUKRx2HWk3HlMpkSUaRS3heSt2sEEcBH378CETK5tpF3Lkg9nOqiwG6peH15pRVA0kqcKOYQlKQTYXMNAgjH5LstKnFVPDDnMCNMeUyn3zYp1JWcOcxk8kOC4rJ7727y5kFmb3pCUmmIeKY9WUVE4OP3nuHw4MBH+z1KFQJPTdQlYQbV1bpDyKevfksjqez1z3EFCk3zt1g0Y756NPfR66mvPjSedaXl/iXf/AeyKeNG5VaTkvSeXz3GJB4/LTP+59MWV+WOH/uOT69PaHaVDiZpuweztlaKXNmo0yzVaZtV7n76THDqUtv5LC+VSYKu5zbvkatWsHxRwxGU56cdDi/toxVj7nXC8gTlUpFp12VeObCNgv1Fcp1lUmvw+aazrDj4c1dvvjMM4z6Ng1jmdr5OuV2nb2TPp/u3kXKNca9OZmU8WingzdXaNRViqxA1iTmc5BlmVSoeF7CahkutDWGQUJCRujFDHsDnl1bYW2hClLG/ZMB1WYJRdLQdBOjpDKfxOzuDWjeaBFnPn6QYxkSa8vLDAZjQOGkd0KUyizXGsxnM/ww5GA443Cagjj1KCkkFZEl1AydMM2RyZFkuHFunaVmlUQUjGddCiXlzIIORYoryWy1yrSWTDJZol6u0N2b0LQWmOwdk2QOUb9HEglyGTRJpzAUKoaEpOhUXvxrFFGMtKCTHfgoQqJIQ1Qpo2XXWP7G36JgiHR8gl4yMAwF1dBQ6zWieZ+kN2Boh6iPb7O2dYWf+9Yv8Id/9L/RiWdc3FwhnM45t7VEnKbEBWyUTQI5Zb87J4sUcilFUzUIE0SUkCsKoVpgWzpZlKHLKoYGG2tL+JmLEwQ0SwajwYTllk2QBohUo6TAwlKLgeMhCR1VFDjjKYuLJRLPoaoZlKyMYy+HLOH+0xFlWSO0NKLcp0hLNLKQSSgRRDMypUVNBdvIKS8u84G3R1vX6OYBdlkjlHOmEzC1NlHqcdzZRTk2OL/V4PKFOoEzRVYlDEUligvWlqukRYTIEzIKSpZOW9EQkkVBTEmXmbU8Hu25xKH244n3Z6DhzmfvHSHEfWAV+BlO2ZYA/wJ47TPx/hngN4uiKIB3hBC1/xew+N+KWsXmzOp59vfuI0kKpmzizF3a52oUscWtu3tYZZvDwxhVC9lY0bhwsc7B/oDEkzh3tgG6oL3YQJYaRInC/s6QL/z1y/SGEf3ZMaaZ0e9M+eijLmZpiiLnhL5H2RYoRYSWx9y4usC776RMmVHkDuuNyxT4zCc+L1zeoD9NqNkq2kqZ1994SJQdcv36efSiwocfP2F5qeDO2w/YOF/lxjMVHt4/5rkvNnj8wGfQ89Bkk5WmiarZ6EDUG6JLOc26SZCnVMsCOYUMiTjMkRUFMg9dkliumpy70eDh/Q7HBwmPkoRXnl8iEAVHBzPsBjizKdtnVzne97h0Zp1Xvl5n9Psz3tmNseQUzfQ57IwJTShbHe4fHnN2o0URwmvvfQ8lKPiPvnmZRycuS8slLpw7z+tLd3iwPyTLMrLCYn3FZn29wl++eUSQCFQzZ6HZ5Mluj1ff2sUyJZKwwA8BNcCq6wReyKwwWN82KIRM29ZYtRY4f6ZFJicU6ZT1lQa2lbN7dIQpyfz8F7+A+v5bvDnzmLk5NbuEXrIZhWP0bJm1xRpLSxvslB/RXlnDDXOEYTDxRzw6PGQe7nDp3BmevXyeP3n1HRQlJA0Tbpxv8ejOGFFATdH4/As3efXNTxi4HrKsIUk5ZzfW0CKXDU/h/miEWTWRJBsncpk7Ps2mhZLHpAm0mk0i3ydPYhp1HTmXGLk5C3UVVcrx4zmHnRRJVdHNKmniEsUZR4M+RZ4gZRmbzQZOMKHIYqJcZXOtTEVPqaglJvGcsm6xubTAYD7hsL9PqaxxZbuG2TC4tlXjZNajYlQIhMD3fIJAwZIt5ppDnPj4UYAdahTkRJmCpp56i5dVHVSLlW/8LUaP3md+6y6rX/s5oiin9+HH5GQ0lRq1rStUn7nO4I/+Z+L81DdbUlUMWcFQDSazCakIELHJfOYTPXyPSwvr/OyXvswfvPsDxpFHHgs47qMIHTeFMJ+xULWpqRp+WadIEgqlIBA5uVRQLVsMBiNkYZJmgtSPEZZKUYRoWkYTjaapEHpw2J8jZwq1umAcRkwnIbIQjPsTyBXiIOb8SgujnLDjzziYRkiZSpblIDKqtoKXBGSRxDAZ05mk1FrLlGsmIoRWu8rB4YTj8IB6Q8VJXaxMoiUrHAeCiZdRKuWkjoec5iSpy3FXwrarLLZrTGY+k2mIpoGSRbTqNcI0ZfdkwGrRwpk7WGZCuWSyvFzlmas6Vy+e2id8eKf7/1+8fziEEFvAs8C7wOIPCXKX07IKnwn74Q8ddvRZ7t8p3o7n83j3KeQenpORJz6qCmGaoctlFlcq7O0GNFqC/r6PqslsXqjRWFhBjRU6hy65NKVWsXjn9m1Kdbh0Y5lPPjkgFz43bm5xvNflaz95lidPIubOlC+99Hle/Yt3uXzBZrVlcH37MrXyApfPnqVzvEsaeXQHA3Ix4ua1Jt97+4CQGWe2nqHZrnJ8GDKOPZz4CcvtBt3BnA9vH/PS1VVW6hXm8zF2o2B9dZFnLz/PB+894O1P7rC0aPH5G9e4e3eEMwnQbYM0T9HzjM2VRRarS3Q6PdzIRdETtrZX6HeHnN9usble5kKzzP3bPXZ6A3wxZeTEtFcMpkHCuYUqL2xf5v7OAZfyJl5o0TaafON6zKX1FnlJI5MiKnmVnXsP2NgoYZoah5N9MinBqhm8c6fHPJ6SyOAFc1oNFXssk6UyeRFzfDKivbTFxUttxt2MzmDC2MnpDKeYisbZjSU+/mQfZJhNI+ZxTNXWsKoGJ50OS4uLGA0Yjfap+xrrrSV2959ilUt0uxOu37jAq3/+MUttk86s4Is3N/jwzi5zR+X7r90iS2OWVm6zvrbCzPMpl6sQROzvP+GLX3we2yxzf3fO3tMdVtZWODoYcOXCNcJwwPsf3OWZi1tc2mqzc+zR645x3SkLtRKeG5AGOaquYJUr6LbFUWefuZ9w7coaIorYP5oDAj8RtGyLQspBlVBMk6VGg+l0TJ6WCMMMIYEqBH6a4E5nCKGy93SHRqNCnAuKvCDPUvSSzmrFYGcwZxpKTJ2En7uwRJaPSCOZhl5n3bQ5DKfESUJryUBWTUpZQpT7dB0JVVeRhMyCnXPgZURISLqNqmn05yErsQSqhiJkVF2CHHRdUFJN6meuolUV9v7wu0z9jNl3vsvVn/9louMD8pmLVVlh8cvfZHL3dSLHQy0gkyQKCsgEqVai8AegGBT+lFk0pyrVUUYnXDEXsX7+7/Jbf/BbiNQgVmSOYxdTmGR2hbSQEALCJKZimMRZjhsFWIbJxPOo1Mt0uzNyRadW0U6tHbQcgUpeZHRHU2JUvCimqgmqtszDvoNINERxul5hGipZHtO0Ij7dD6hrBlGU44YZmqZycbVBrcg56MWM0gAtVqFkMY1mpNMKFh4P9iMMzWI8j1kwTKapS5RprFkWae7TrFdwgoDzW2s4gcPUCyES5LFgMvcZTj183yWTmkSzmCSeUiqVqJcECjOWV2xkSaFqG8yDOU+fOhiGRcsqfqQe/weLtxDCBn4f+C+KopiflrZPoyiKQgjxo2f6t8/3K8CvAGgqvPHODpJQWFotMR+FLDYUiiDmoHfMhW2bC1smx0cOdsXALhm8/dYh/X7Cl55bI1MyTjoQS3NyOeLJkynVZsSFmyt0D2d4jk/JyrA0i3o1ZzAp+OjBHbJcZnVVx9BLCEVmNJsTxmMWWxpRWIaFCrlUpdOds3MyIEsLvvvGXX7+a69w7kKLR52YNBccdWcUpJy7vESQxFzc3iCT6wQiYD6ZMB/L9Ocu3/rKeXb3Jf6nf/kaaSaoKCqFH2BaOkqe8vRhj4NKj7WFBb718k3uPbxL7CTEiUK372HLFabuBE9zWVovc2Fhg7idsrlQZTCOyeWCkhXw0nMKD/fv8nhe5ts/83VGoxOyQifLddy8g20KQlPh0aRLfNJnpb3MhZWbPLm7R6EkXL26hZqojEb7fPv5a7x4OeT77+2wP+qgazU++HCfkiohVIschbv3e9QaOiVNRsozLp2psbZaJYkC2u0KdTNGS2c07QXevXXAQtNkOEiYe0c8tobsPekSpip3do65drZBQ6/wOz+4T80w2LnXp7Vc43gw4NvffIaCmI31M+zt7dEdTAh9l5944VmevfE5jo72efUv3+bjB/sYRoX33r3L2t/4GifHRyw067Rba0znCj/1jed4Npf43htvcnb1CkIJOZll+P0ZtlHwYO8JN65eY/YZ4uvpziFKXpC3m4ymHlWpzFqrRBzFzJw+fgh+5NGsGZilgtkgw4tkiqwgy6HIclRN5vq1i0xnM/zJHEVoFFn+2dNwTNPWeDxyyBWZ7tDF1nOqloWfjJmicjwOCbMM34NmNWajaiLVdA6PUs6vlXk6nhFQIKcSWhRzNNojLnK8cciVwCXO6iAEpq5CITA0k3qzztLnXuT4ne+QpgmzyRC/N2bnL9Y5/0v/Jf3f+h+onXsGuV7De/1DlBxiIZAkGZEXSJJAVyQwVTRNJlVM5Cwh9hNq1UXKP/kL3FzZYjBz+d5rf0xvnCBsjahImfVSjIbBeJbipOLUpGrmk2YZi9UKg+mcoVdg1DTIZVaWajhegqbJDMYesioRIpORYRgGslli7mdkeYqtlXDdECEKVFXQaCyyN5yT+DJV20ASMRVdwSxBnkQM5jEJKqZlEIicMJPIZwm92ZClVpXO2MEWEZWKghelJBj4KvhCsFit4xUQeTG3H+8wm6Xkqcxz15aI8jF3911a1RKqkTMcD6mYJoXICWIPTasTyTJyEpIkISKPOOqOOR5FbC+r6JXmjy/eQgj1M+H+34ui+IPP0r3/uxwihFgGT3/mdAAAIABJREFU+p/lj4H1Hzp87bPc/yOKovh14NcBLFMu4gSyHBgHJHGGNJXRNQVNz7n/1OPshsHNmxWG3RzfDxh2T72Rp/Oc2cRBrylUWwZr8gYPbr/N070xT5+ELKwUZLnB+TNnKJUrrG7UOOkHuE5Iu6njOAqvv/6EV766SRzJJKGKm7jYVpvdwx5+JLh9a5fIjclSiTsPAq6fe0qnkxEGEqqksLReYdJzmI3HVJYX+eM3PmZlycCdRSy2UtJ4SJi5GPI1VFmmadiUTBlL0zBlhZE3Qi6ZeBOwi4L9/T6baxoXz23TG8wZDCbUjSZGBte2znJZsZl0RlxaKTMSIY4bM0vHNFpVer6LrnioLZmDzjGvffoetpZTM1rUFxZo6otIwmGztYy/t0Nu5Gw3NilXWry/9y6Xb7YwJY27R4/JcpX+yGd7pU5dEXRlg2HXJU4LGisGcg4v36yyvdVg6oYc7I2olz3+2ss36XQOeOHaZepVCceZ0enrPHnyBEWq0R2PmA9S7u2OWV2tsdrSyWcJjXKJleYZ7t55RNdzGRQBaZaiVGzyLGHmebhORJDcY+dJn+kspV4tMZzHzJNjEILBDPyYU2JNmvKd775NvWKys3vI2so1jrtP6PQHRL7DQmuNW4/us752nrX92/hdFzUDOdfY2+8gsgyzUCmiHKtqM5r6GGaVzn4XnApntxdJkxIjf0ittoBh6GwtLPHOuEMQm6giQpZyZE2lWq0yGPRIkwKpKLAsE78IEUVOuWSz8WyLu8fvEaRQoBG4DlkyJ1Ry/DzACyIqZZ3MB2Hl9IIcQ05QdJVAjijrOjc2Gtx+MqDjZxSRR6FXCPOUTNIwa3VSQBMyiiJRK5VorJ0hkUKSJw+Zz+aEoUca5Qw/fY3NZ19m8+//15gLN3De+W0MEiJJIkagF5ALAZJGMh9RWlhisdU8ZbqmIFVXqfzEN/He+w5SmPCVF19hNh7x8PYtAlni3s5TLm+tM/FDkkLF0AWHvT5kCqgKh1MHRE5JkzDVNmtrVYaTHk6YkTs687hASk8hC7WSRhTneF6CECqaJGOqEqJUIkhcMmFQSIKPj+YsFBW65ZjZLOB8u03dyonHPnM/ZZJmhIpMnIITO2y2W5wMp+z35xiKRLUsoWkwCxL0zCBLAxaaTeZqgZEU5IaNXKRwVqFtmywLmbhkUDFtKpbCQX+C6+VIkkQhUua+T1qEKKpEYQgqlTJ7vQGuE1Epqbx364h+f/7jifdnu0f+OXC/KIr//oeG/g3w94B/+tnrH/1Q/j8XQvw2pwuVsx9V7waQZKhZCmGSMhjlLDVKqKUSR8cpy+uCz203qFXbhMUIYyFl2tFOfTkMic5oxMpime0zK5RMBbskcfPGBjNngqooTB2fmRdgX63SPwkYTFyWl21OEkGpXHDnTp808/nBWylxHKNIMk+PPL719UVOTkLuP3hKGGS0mxa9WYocpbx764CR7zCf51y5WuFgr4/IVcYHCno8ws9y7tztsL5Uol06Q5qPePbqFuNRijt9wn/87WvouUSQRsSJypu3ZHa7x5DLZCgslzW0zEUkJqPuBFnVOBj2CHOVvajD8uYm9zr7PO6aaKWY7bUGQRbiRTIry8sMpwpKXnB2tcpgPsU2BNtbKxxNJ4ROxmh8wsXthGKeYDcreGHA4eA+W2tlPr23h6YL1pfbFEmV3/juO3zp+jqfPjqmKKtkUQZFxtKizkvXz2BZOpVKiSz3kf7aNd569w5/9uYO9XpK82Sf0tCGHA4GI3SrxfH4gJWGhWhrBGlC4mYUTYW6raOuxzx6ep+8JNiqLxBnGb3BnJ39KVcuN3jz/V2cuc9P/9TzRLFMb+Dw4NGIySjjuRc3IQ7YPzkiipTTjkRVZu9wjlhPGY5T3v3oNbaWLd545z6tdovf/9d/Saul8Pipw/2HfVpqCr7KyeGcSqOgbBhEXkyt0SLwp1hWCc+dsdCoEkcRo8mMNM+RU4EpDDwnppOcEKUeY0enZpz6rsRxTqOl4vkhumZh6ALXdbGsEkUcUygpTj6mVVN5Okp42jlhsSJhaAqWWUPXM5aJCeOcWBQ4AeRyguYItts6kuQxy0u8/7jHUq1Mq8jIpRaIFH29hLG4gWmUUc0SRVygSQUlRcfYOsvk7pskjs/U9UijBCQJwZTha7/LmX/w3xF2bxMd3gFJIHKBBKiSQJMkFCmjaK9RvvgsdusMmcioJzHa4hbH/+Z/ZPrwQ4x6G/sv/pivv/AMXueQP7t7l5phUi7B1MmQVUGaxkhCJssiMlknlGT0kk6YKciVnKP+MaqhUzcFqpKAJrC0MhN/jjsPQAgsQyXKExp2lSiMkCWZdrVKWsiEmUdWGMjNGu2FHNWPSHQJdx6QeeDJErEi4foxC9Uaa6qKbstICRy4grahU7dg4kbYskFUuDSsEoNZRGOxxmQ6pmYaXFlax6rojGcden5GZ+aQ5zHGTCHOwFQzNF2nbFcpgFzkmJpGnsd0+xMqto2hKMwDn7PrFSau/+OJN/BF4O8At4UQn3yW+28/E+3fFUL8p8A+8Iufjf0Jp9sEn3C6VfDv//smEELm7NYl3v7wIcgpw0nOL/30Nf71793GsnWcIOX+wz6d4YDPv7hClHgM+hmLyxnbFxeZj3zyMOZoMqZseBRWyFZrBVXLSTKJzvEQfzpkMAi5fH2D27cmPDnsUDMLVKXg0rkt7j4c0F7VOXO2RWeq0R0F3Lm1D0VOERf0hh6pquCGKQ/2PBQlZ2Nb5rAzQDN0VhdLnFkTLLeWGY6mvNo7YDKSOBlFmDWbDz4dIeU+r3z1BpnX5IN7D/DCAVeWzvD159v88Q98enOf68/WWTVVLrQaxHrClZtN7u243Nk9JJV0ntlYpb97zM3zC+S5ye5+jwdPJlx9Zou569LruGS5h5tJuKM5DVMh0RJ2ek/oDgeQyfT7I6rlMo+edlD7U+K4i63ZHHY7yCh0xx537j/gzLqNmsDd/ROWztdo1kvcCgY0qiY3LjUJk0Mi16I30ygZZepNg2Z9m7fef48ks7iVJVTshLZZZrO9Qd/3cYMaB0cjvvXycwSXEsZhwe17D2nVLMIkYWXFJlMEk36ByAuWFw3m04LZZIysaEwGBf/8f/kAXUqJ8tMuxA/udBhMJ3zzK89y7fomb7x7AHICmUBVZDwvpGwZHBY5F1dXuXO7R6IMSQvojhOywTFCpIzzU2OmPJfAi5BsFatu8hNfuMr3v/cWds3En81xfAdFhpPOlOWtGu2FKo7j8NJLL/Do8SdYlVOWaUVNkYRJVsDS6hZ7u8ckWYoQIISCJCQkRcGUJbww4rkzTabTPrKqo5gSqqWRxQ6XNlpcWazz4aMeE18QazJpIROkKYPxGG2q0EsDjDwmJyAsBHVZ4mQ+p1xS+YNX/wyt9JNcfuEl7rz5OkWmolst6pdv4Pzxd3GjmCwpMFSZqqrRsC00ZCRdw+k+wkQiSBOkVKAYCnkBenmZ0he+TWGbjL7/G4gwJp1PkOY5ta/8NLpRoEkSsRszt6cYn3zMz968wsGTR9ztJfQmLnIhUA2Z2Mso6xUq9YS8EDiBT0lRWLESQs+kXTaoVDV8T6Hd1ri9c4Ic+KgIwgLkHCz51LUwjDMUWaVklYi9AFXK6DlTWtUaDZFiSSpKTebprM/9kxA1NZiTM49ge71MWxMsCp3MLljILGIlIAoKilBGxDrr1RLZsoHjxgSZRJ6n1GoCXSRMk2NCZ5Vla5EDBmzKOhNPwzR0huGURJEpWQW7T/uYlompgazkBIFCu26xfzxASCamrXEwTWlUpR9PvIuieAMQ/47hr/1/fL4A/rN/33l/OKI45dajHcbzBF0XeGHED167A1pAty9xuBsznYJkyTx47KLrDmfO29TsKp0DhzQK6Nddbj3uc6Nq0AsjDvIRnp8QeCorSwp5JLh9Z8g4jjk6yojzmG89t8TjicCNxiy1TRQShJ9RknW+++qHRFlKraZTaIIwCsnSGNM2ydKUzY06hh6zs5egElM2U9baFmE04vz2Jh/d3edkEHIm8CE2CBSHm5fb7Dw+YDzepX8yRxgGzbrMy59r8eajI6orMl//6jUmJ3NKepnB4IjVTYuJGxOIZSLH4+QgpDvyWGjZ7Dzt0z9xMKsah3vHFEaNu3ceUl8UtKQ6h705AxXOmYscPzqiyHKWFmyu37yOYZu8/OVrJInCu+/f5pNHHUaTBE0VKCUDuyRz4cwmknzE+fNLmHqOXTZQpBQ1V7lxbQHPazJ2TP6P776B6+dcu7qOMz41JxoPZKqayb0HXc5tKux07rGy2WalWSMKA/rxgJpVobvbwVRUZCFoVOuMpjNUJcPULaajiEvXljEvT6lYdYpUxXefcjTIMQyVxE9plTWSIKVIFN75ZIdWq02aQJyrlMsS1bLA8WQqispWRePG2ioTH965+4hyVUdSJEqqzHjskuWnN7ooCooCoqjAtFVO9h6w1qpwNJyiaxaSnBEVBVmQ4EwdKg0Zo6RRtiwunb3ISWnCzmMPJJ0szbn57PM83T/GtioEcYgsSRSSACGTSzlRliEkjcWmzJXzGSMvQS/LIEOlLOhOHT63tsD2Wox0LGGXPTpOjFvAiStYqNoYUkiaS4SpoBzJFMWMJIWh5yBFAX/yndf4lb/3s2B/QOEKqpsbpJUy9We+yXzmURUJVmbTWrxA6/kvo2+eJfUmGLU2eQ5FBkJkSGGB1dqk8rW/TTh6SPT9P0VLBGGUEmgxpbgEjo9eWUW175GlAi2XsJcuYH/+a/zKxg3+xW/+BmPPxSNEeBmaEGzXFJI8RkQVGnULQwK7IvBNhd7Q4dBxKcsGoQ9SWlCXdCIR4/ohsmGSKaddmmESYuZQUmUqlkalmpNOaqRRhpwFODsBSjtDkXUKTaLvhhx3cjbPVpHkAknKoX76pPzkeMpjR8Kb+5Q32yRGAkVBMc8p6yUmoyknuURSeJAFXFmqsjc9oalWWClXmEgeblygKApN0+Kpm+G4BomIEZmELqokQkKyc+Jkjuv7zN2UGxcWeWE7Yn/wo8smfyXa4//JP/m1XyWTUHKJpi2oWQZmKUKlIIsyvvCldYpUwg98RHFKUA+DGFlWCNOI+TyhP5kTRxJ1Q8ZPI4aDnO1zbbIs58GjmN5sThLB470xh8cOzWrO5nmTlfUaL73wErfvuRwcjIijDKOiM5w6ZLFKLjJSIEpTikxCFKBLgiI1GQ1c5FwjSxI8D2p1gSIEJCkvvHgW5TOSyuXtJgv1gqtXbqIbm4w6XV5+fpMLzQqWVuft+4f0xg6rTZ2DTsCnd57y7ju7VNZsGotrZHhcv3kFmZBLl6pc2L7BZDQmkyAMUyq6ioRMpuTc/WTExWWNv/mNz/PqD+5x6+kciYTJPKAzyOgOXWS9RKfXo2HXkESVYOrQnYSc9H0URSEIYzRJolmvUK5LnDuziZAyLDNjcdlmbWmV2cSjXrnBa299zL1HDsORT1pEpOnpgp1pwdaZBguNZRK5QNJiqmWFn/76V8iZc/vhAENVCP2AqmVQtRQEBeWSSb1SZjCYsLTe5uKFJdYWV5ALl2euXub8mTXaNYnrl0uc21znuWvnee7KItWSzv0nR0xmM5otwdmNNpZhcPniWTrTAf/Jt7/IF56/xHde/YBPH+8jKTpFniPIkRQQKORpjiLB0nKLOPIxNQXSjKKAum0ym7rImolIQoQmEycZmizIhKBRLbG81KbVqGCqgp3dHopmoUg5RyeHjCdTVElBILB0EyFBXvAZNzNBljUgp1ox6IwmtNsSMzdBtxSGk5TE9dFkwdE84siNQJZQ8hxVl059M0hYlmTW9FM7A10v0YsDarrGxmKJo4Me3iTg7KULTDp9bvzU32TywXfpffgB5toNbv7iP2D1679A5cwFou4e0Yd/CkGJ8rWXyI0U2RmSiRxD36Dyyt9g9NF3CG+9Q5FKhEXGHIFcyChoGJsXCZ0OYWefqrmG+YVvEtdM5m99B23s8PK3fpHR3GN3bxdknbNLiyiFS55qZEJGM2VqElCyuNc5wnULSlIZJc1JUKjEOSNy0sBHUTW8JGKWxDjzAF0/NU6TRUG1oTDzBGM3JkljolmCqsv0w4ShGxPGKY1mm5yEc9sNJrOQ9qLJrYMx95+MeTiCqtCYBTFeAhumTjDx0csyByOP2AtwcwmlomEImQVVI9JVhv6YKI4ZOi5BFDNPUkQBYR7x9GDAcBIyGMSsL+uURUGzrHMymJBEpzi8PNfpz2cMxzlPns7+alvC/uNf+0e/WmlIvHC9jUmE7yfEmWB1VeD7Bf2BS7WsUCpL+H6CrhXcuLZImqQMxgmSmjEapyjknLt+nqkHnhsxmaSsn21w+45DEGXkRUoY5ORCwtJU4sTjwuYC455EQY+d4ylBLBFnIb6TELopigpxlJKmp9daZAWRFyObGZqlkyUZGSqqnLPcLCMrBb2pIEgmXD6zSCZFNEqgihpxIvHnr76Prie89OwFAkfh5OiQpycuAqjVDOaeYP/xCE+AVwQ88/wrvP7aO9RqFq1WQc2uEQVTFKnFn/7lI86utlg/U2VzvUKjWSb35nzhYpuzVy9y++FTvDTlsFNw4fwijpfTGaTsHnSZjH1sW2E2C9jvDvB8HzeMkSWJOM4oMgnTUhlPHDQ5ZGOlTRj4qLpJEtR4/PgAGYnHewfEeYRtKJiailRkLNo6FVsQZxEvfW6DIg+oVm3qtk1vNEVg8dpf7OKkCa4X0KrXkCSYzh0WWjUMSUWSNILYJ49S6jUV381o1lqsNVY5t9Zkqd1mqb6MWrisri4QxC5KHvPtb73Cmc1FDLng44+OGE0i/vpXb6LHCe/fvccbd7oIWUKRBDIpC80qSArTmUeeCdIkRTcUoshFUySKXGI4jVFUaFds0AWhN6dWK5NmOetLizhzl4qlU+QpR519LFVDyVWKwkAmI04iZElFFQpCgKGZ5JzeU5qqIguJlJyiyFEVBblIeO7qMoPRnAwV2xBkyMR5wTALsTSbzY0GYRYQ5TJmkrFsW1RNg3DkoAmVe84E1ZCJspxFTdAfz/nw1j7Xzpxn5dw6dlNl8umb3Lr3mKMHdwgefkL0yZt0b71BOumhoWF//hXy0VP0lZsoF59D9kPsz32Zo7f/FRzskcgqGoJELpDzGCUBY2kb9fxNpKUt7LMvod+4TvDR9/HvfgShgnXlCv7ggI3MoSwihv6YPEqJC5UsFZTMhOPJjDBJOR7NIQdDrRCqMVGRkuagIRh051SbNXJVxo8TFEmhpJvICISmUOQ5vYFDJDTixEPXKjhezBxBu2GTCwlb01iqSiy2NCaTGZ4fE2YZx72YetXG1HOiMKJql3GCgJqkUko97nkeuWKBCamUU9Zy8kImUwvmnk9SqLhRTJorlApBnkuoZROJGHcWE6fg+RrD4YT+bM7QndMbuCiRTL1UZ1y0cPoOvhtx0HP+iov3P/61X11tt9jfH1OyDFIZUhmWVkoMhxFxLCHkgsOnMeNpTNlWWKgZjHsBYZSdljuQUWQwDI35JGY8iGg1VujtOwSpR+TLGJrMxmoJN8i5dMGgUSlhaDY3L5bQMpXCaLO/c4TIU4ajAq0EekknCFPS9HS7V5YnFMh4gWDqe4hMYbGscWF7gY21OvO5wl5/SpaOKUg4t7xCwzZQLUHq9fn6V7/Ka3/5mJ7Tp6SqHI8drLLNxW2b7Ws3cWZHrDQqDP0EZxTz9NETjg/nJHmEItt8fOeIcXi6iNk5HtMbBDxzqQ3Y7B0c8Ut/+2WqNRvTanL78R6tpUVuPezizefEcQyiYDpNME2NuZtxMpjz8d0BoZuh6wq6rCBLCmGagsgoUFlatFldqJNFMYGvEgQpmWSxt79P6Cf0ui5lXWKhprGx2UalxDOXV9FNmYe7XSazOXbZIPQjjgYJr79+j0kYcTTwSdOcXn+GImQqLYth32G1uUa9ZtKoVlloNcmAZrtCEhfsPn5Id9ghw6JiG5xbPc/7n+6Syym2nLO+rGGbZfzIYWtzEZmcs0tVJFNCUTQoTn+oQha0W2WKIqUQOZpukqYpuq4RuD6yYuIFMetLNkUhgUhZWW7hB3NioFav0l6oo6khq+t18jSjbFt85UuvEAUu/c4xaVaiXraJkpgsKyhpBkWRYpol4iQiyzIUqSD6jC4jnVo4oavyafOYJLHaaHBuWcJ1E0IpQFYNhAwKPouWQFZkut0pql5ifNJnc2uNB+MJsa6jliRmfQ+DHD/T6PZTtttVzl6+gOlMOHh6wNHxmOWaTcUSpImMrKmUhYL1zDcQTEnf/T+JH32MWt6k9BM/w+SD30ba2SPQVCRhEEsCPS+wyiuUXvxJMl2m//rvEN76GDmcY51/Frd3B9VqYj//MnK5RrB3m/LqOc4+/3nWWov09x9SIKPKgrKsEQiV+Tyl3VylMOH46AQjTEkoiBTBzPMpqRZxHpHJGbKmICsKGRmWqVKrVjCzjFSSSGIwVRNT8tk9nNOom6RxwqKtcmaxQruuEDkhWSZYaBtMRwn1soYQIZKiU2tAQcF4GiF08DMYJiYLizamZbC5tkjizVGVEmrJRFF8JvOYKISSZmDKKnEKuUgoqzLlpkG1arG6ZLG8IHN2s0KR+kyDjMNOzMHYIQrHqGpBa8Xg/qPxX3Xx/ke/utYymYYxbhiztmiShxGTcXAK+BQp41lMSdOQpdN/Wm8W4TgZspEjyzpZKKFocHA8ZT4NcTyoKRKLNZszCzbPX6hQBD7rF+qc267w89/+MqZR5oOPdpjPJwS5zJ0HT8iEhl3SmEwDVF1jNIrIUpBlQZ4LrJKKqggUCtJYJnHg28+vo5spiWQTzQsePumyttTi8oVVCkJW1rdpNEpUEkF/5xijktOdTzg86PLh4xFR8H8x9x6xtmX3md9vrbXjyeGem+/L+VWuIllUMYuUrVY3REGN7rY9EAxPDBjw3DNSkg0YMHpg2DAaFmy3bMltWZIlyjRFKrIYikWyql6lF+9L976bTz47773W8uDSQ3pce7L3fC98+K/v/4UF5y4tY5OU5Y0Bwg3oesvs7J6QpglJqYkXlkd7exwNc86dCTjan9NqCdJCYsgYDuc0WjUW85yP7kxYP7PKD354B79ZJ5pHhF6TsO7w+TdeZWfnGb5reLYXM57l5GmFFIqyUiTTDF1UFFbj1xT9fh3PLZmMpvz0vRPuPtpj0O6RLwoOp3M+enRMw/dYW24xjzIUgl/98gv0u3U63Q63H0zY3Y94+fI6yd6YsOby0qc2GY9SDk8qyqoE61ElmmlS4piSaH5Ap7/CbL4gqPnM5zPq9Q5VJYltSuj02d/dodFSbD8bs3N4RL0jcPw6lU3YefyQaJpzca3P8eiQ2/fHZLlkqVnDqbcInYKXr57h6eGMRW7ANZS2otus0fABqYmyAkdJtlY6fOHlPsNRydHUsNFtchzDPKt48coaQR3macFklpGkC6pqwt54h26ny/BYEPgSXeVIIdlaWaXVCAk8jyhKcT2HMPDJ8wRTSZQrwVq01VSyQhqLQLPS9qlEjWyRUa85XN5okyQRCId2r0VUFUzynGajSSwWDHNDq15jPq2QriFLCzpLdaQ2pPMCP/Qw0wP29w9xHI/1lR5ULk6oqAch9aXLtF68TvnWn5BUsMhS0qNdmps3yfZ/TpUkSKNwpUS6FY0zN2H9IosP/pbxw1voOKWSOfk0xqn3qNotsv19pvc/QJ+M6b72GzgrfY6+/y3caMHlCy8gBUyPRhRORSlyTqxGSEWZlWhAhA6FUpRJSt2v0VCSVsOj8AN6bp0snuMHLS5tdLgwCBknFXGaE7oBpTWY0nJ0XHJ50OezN+rsHM1JS0OjUnzmWh8RSibzlM1unShNKABd5biiReBrplFJbhU704qaI+jWHJr1Bp2apuc6TJICiSItChwCGiKlKiWlLsgx9AIXVRiENhRScm69T72mmMcZeaXQVRcRKqSQXL8QENRgNE54shN9ssH7d3/vm9/QVmBUha0Ek3nB8mqDZkcxiwxxLJhNFYMlh0uX20zHBl1AUllOJjmdpgvG4CqPc5tthk8SsIqEBZHJ2B/POIkzsjJnb5rxKy/2MKQcHB5yOJrx3vsTJvGCaKGo0CwWGUiJROC7IDFUgLUGT1QEgOeA5zi4wjA/GfPoGHTm8uaHj1hkJU93Jqz0a+wOI3ae7lM5C+48WvDOnUPevj/kxqUuhRLsH2oms5gfvjfkeHHMsufyvb+5y62HuwSeRaPR1hIlFUleIbGcPdPi0cMJn39twOuf7fN4P6E0gidPT3i0P+H+dkqv4fHtv71LlFV4vs/weAKiosgLptMEYS2LqGI2dRCOwQ984l+Yaowu8V0HIw3nNhUvX79EUki2t5+yGGu0qEhLzdNnY9b7Pdptl0sXl7l0tk9vrYdf6/LzW4+48+AZG2tLTGYZH9064MLFDTZX6vRXzhFHEQcnEV4gUFWJVIbDSUa71WBtq4H+hS06SnNkCbWwyfv3t7GlJComnDvbpBa4HE7GZImitD5/9fe3uHz5Aqgatx/uMxzN6Q8C4iLn8bMx248OkSIH1+HDh3sMpzOwJUvtFjUMNdeiyxy8FktLIXWZM40KXr2yyv2H+zzYn/GZl85xOBmzebbBhYvrjOcTJrOIKEtYLDQ7u3OavTW6dUWS5lgjmccRtXobhcBRlkG/z+HJEGMFjnK5efUcx8MJSIXCIAC/ofCMpTAWvxQsbEXdCVi9sMFifISuFKrwiZMSx/pIJej0+qft7UoRxRFVJVlZ6uCHkroP613B3Xs5L716k5qeky9iNleXqTuCwkKrGRDKgMGXv87wJ3/BdJwRlxGuqGOtxu8s4dZdqt1HSKVwWj6N1UtEiyGTj79PPI0ItI/jCHy/T+8z/4R5ucPkH77LfHKMjueYaMri4T3q4YDW61/EKyPqfpOldpuyzAw3AAAgAElEQVQzGxskecLeYs6N9ibH02NOogTHCdBooiSn5vm0lctZQvIq5yCdYT2JcSVUgkHdQRQxuihJcnAcS+hJdFFRr/lYX1CqgEkUYzSMZik744TjSUGRGs50XcapJvDboCw1L6S0BUlU4nd84knOp1++jLALNleWuLLeYTaLOYliHKciSTNkWCOPFyz7XUQA9bpPniVMoorMc1htuZxEx7z/aMTTZxHTyDKPDUlSEacJgQePH6ZgffYOfznn/YmIhBWcckcKhSOhyiSbS3VeefEC//Mfvk3oaXJP8fRZSVwkLOYlrVqJUHVabY8Hj2PCpsL3BCrIyEWFEoZMh1zZ8tl5mHE0BgfJ65/b4MGhw1Iesbq6grs3oXIc2q0++ydj5gtBzbNUlaHRcaiHdRDmlA8rKxqeJLSCUlikEOiaZJR6pJMpT47mbC23Gc1yKukw2iv4+aMT1noaEazx8TuHDGoNorTgx++OOT+oE1cZQgqEZ/jg3oLx8DFloinykolwsZmhHfiEfsXy2Q6bZ32KTJHGDpWuWB1c59MvHvPzWw9ZPdNkdzsmSmL+5Fu3UF6dxazCmIKN1SWmScpkkjGLLO2WC1JjRYVSgjLP8V1F2BC89OJ5GgFkiWBpYGg2A867AftnlxgepghR8oXPP88Ll4958PQZulKEfoPhouCdH9zD9bbJU4vyfToDn053k3vb77O9G1MJyfPLBseWyNKQpxpRCKwAUzpsPx5i6HLuXMRKZ8Dtew84t7bMPM04OJnz8Mmcr3yux8ZSg++9vUOSpGBC0rhgNNaMdhfcvH6NW/oed+4OKfUqg6Uao+MpR4uSICppdtosr6xQaosuC+JRwq9+4RWOx7scjSeIKOXmxbM4qklWOLz90S6rF3roZsZoEnF2uc/RcMh3/+Ed2r6iVQ9YPnOed959h16vhrQZpW4StmpM9wqUcpnOF7x08zmuXz3Lz3/2IZUBpKXbafNoZ488L/CEixASgWTneExDKvy6yyiW+O0cWcEHH2/jSh9joadTEl2w1FsmTUqeHR7R8jRV6TNPKpT3C012w8dZZCy3GxT6BCl9vEaLZjMFLHFaUm8FuMKl89pvcPz4LeKTA6oMciWRqiJ0XLJogbeyRX3rZYJLL1L2W0z/7L9nHi8oM4kjJHJ1k6XXvohRLq6j6OuLuM8dcvzBO5Q2pKoKPFlQuhZ9+yccf/A2VeEwzzS6KrmiDEG3x+3FIcZm2MxQaUm36ZALaBeCoKxwHMNgaQkXnzzN8WXAvixYFC7HC816WCdrxpxkGWdXNyiTKUejEl/WOTickC4stZqg7jqM5iX+oEYrbKADn6yICWsuvXqLNJasuTXKZYGuDIMrXQ5Gu7TqPkvdJuWiZPtggQpr5EXEbKa42AHbcRgWEQ3HI85ytFTkvsPFwTKoko5xeOOy4fb+hHduDSkqn7ISXFhrcm6tzuVzDrrUvH3rl+PmJwa8FQXCeOSmQnmSh/sTnhy8z7ASuEahlEIbzdH+HNeRVFZiTEJNhjQDlyozuCpn9rDgxqrLUSbxlkKeHCc4dQ8nzhDKocwU33/rMUrB1uYTJieaC2fO8GD7iDzLwRcIW+I6Lo7UTE5mSEcQeNBUDi6nKoEiqThaaNyGSy/UCFfhFCWr7Rqfv7bO//2zR1gJaJgnluGew+NxwTCeURaSh4cJjm+RSpAU4IuChieZLlKKzOA7ln7vtEfSTlK21up86Z99ige7T3iwHREXFd9/J+PbP/oeKx3J7m7KhQttblxZY7zY4dlsjltJasJDUpIlMVRQVhV+4FPoisGgix9E6NLiCkmjIVnp+vQ6Dco04lrLZRhHLKJDnjt3BV9c5Hv/uE1cVuzvHzEeHfPiSy/wl//PW7x9+11Wl2vU2zVORhHNWo394wl/92bF3sGEN57r8GuvLPP9W3t49j2+dGGZhztjDo4Nxjh0uiE7j0c4NY/JKKUsj+m90sALPCbRlESntNo1otmMt3++QygdfNXg0TChqlKOxhMCx0NUwDyhmTWJkoo3f77P5mrAc1dXCIIZkzgmz0qyrGSl2yEazxmnCX/z9k+4fGYFtINXlMyeTHC7Hi+/vIV6weUHb97mzKDL0cmEN25eZTIZ0QvrLHUcjqcT1gYVF1a2eOnFm9zdfpeVi+skesrGxgr7B4/BCs6vD3i2s837d+5hAJ1nNJp17j95jOecFgmXBnzPQ2sH2WgSJ0MSpRikgkHYpWHmSGWIjeQkKk6rxZIRQSPALx0OZinSnurVrQwYzmLyPOOllXU0mlYL9vZOMN4IVZSEXoAf1ui4AbXrX0EHEflP3yNKK2yhUC5oXyKp8MuK4Mw1kmTK9P4DGp/9NKK3Sf/6edxWF7fdR4U1pj/6U6KHt7HG4q4+z+obX6N989coZmN0FkHQoDFYZbK7wF0+h5ws6DckwcYFnE6fs/Uer3Rc/vL/+B9Jo202a03cRYy/sUZ0OCT0PJSGg+Mhi+UWNRR+zaGYRFjtUBlBEqxyYZBzcP8euztjcHLSUhMLjeMDlcFt+HSbIdFizHxWEMiK7TghrDVpNkI2uh7L3QWjo2WuNCb8dHvOPIPA92m5IU/2JqSjIQ3hMDWa1XaLmiowOuVgqLm8tYQpY7CGCIkWhp3pCSEVu/sF/V6Tc0stlr8S8Pc/OKQ0Tfp9F181qLualY114MNfipufCNrk937/m9/otXy0NVQGHFcQzzVJmoOVGGsJXYtwoTIuxloKLUhiSZEWoARVpVkdBFxba7K21CGuAq5c7tMRll4nQMiQ2axgOD2hSDWLhWGRVjhSYXXFIsnQ1hC4Asf1ydMKz3PIswoNJLlAFxVaWGa5RRjJvIIsg4ajSS3kxnJ0HHE4nxHlKY+PI5o1wyTTSKMxKGZ5SaFPt+YagzUwizVZBb6yBI6i48LNrVWSNCPVBtcBW+QsLff59t9us30vottW7O7NGI8rZosUqRS7BwllVSBlwHRWUFYGXzkIx0UYkMJQaUvgeygBjRr02zXSeY5yDDdv9Gh0PA4nGbXQ8NLVC5SeoN1s4fkBK/0+YT1k9yDn7vYzhqOEx08OmE0LFosSz1X0Wm0OD8ZU2hKlBdNpwde+tsHXvrhOZ01x6VIXUcFaI+P2wwVntjrs7U9Ic8siN/QaksCHeVRidMHhwQRtQEk4Go7pdRo06g5xnDM6GnPl4hUuri7xpTde5qWLHfaOh/z03gH3Do5wcsMIyeuvXOD1V88QNgMW0wThK46OZ8wX0alSIVD0W02KOGGRVHTrLTxHMS8z0rLkxrkLnJyM2NuL6DbqBJ5kre0zTEpW11qgPTAZ589tsLE+oN1r8LP3P+LZ7gRRNMiLkpeuX6ZRd/jxe/eYRillVdLrdQmDEF1pjNZYKzDWoBxFpVNiU+IIg5AGX0CpLZM4o3IFaZ7TbHcoipKbF9aRWYZy4Okop0pK+v0Bx6MRntdgMV8grWKaJ+i84tzlm4TJEaFyUI5Hq1XDBn36r73OwQ//L9K4IE5y/FDQqDeoK0WwfIna67/G/G//Lcnte7Q//+9TCY1J59ijHfLdp7Qvvsr83j8Qf/QWWa6opIU44vjOu4y2H+DGFbXLl5g8fciTH3yHeuHQPv8cK1/+Os3zG4w/eotk+y7TJ/fIHj3ixpkrrG+ssbe9zd1FTL1WcZxXRNGC+4uEWSDJdMU0SehJH+W3sE7J+PiIIpsjnBorrRrD+RhbuTQaIMuKRRljjUOz5lCVBUa7uEoxCH2qQrPU65IkCY2a5eHeEKPBFBU0GrRswUpPEMVTRlmOFQYtJa4nsRbatQAZNLmwFGIXCbMopdutM09z6q0G/UBRVIrxImH/eMbq2hKXt1YZdF18R6CNZW25i++X7A1HvP3e8Seb8/693/3mNxoNiZIWR4LnO7iO5uKlJfJMU1SGbicgikvAglRoMro9H2E1utCn47CQtBunwVWOLdjZmfPkZMHJLGP/JGKelpRGUVYC31coeerQG89SjIXKWExlwWqElFRaU2iH8VwTRaCBQsNkbqgKSVpqlCMxpcWoU2OHY06LZpd6LcZRReVIWo7LPCrwXclxpNFCoLBoa1haXmI6TilyQz30CCQMOjVm85h5YZhEkJcOJ1PB/YcH3Ly0yvmLDo2uQklJVhSkmSI3mmhmSEaasorJtSSvLJXWKCVBguMHpHnxC2pKk8YVNc+n0wx5+eUVOk7Axc2r/OxnD0jTmHqrhbU+Tx/tEYQZrVofz5O8+NIN3vrpI548XjCLCg5PEp67eZawbtDCMj5eIKxhuXvK9z2/2aWsKqyqI2WN82sdVLtHZ7lFuyt4/pUN4sUMaXwcBdN5ia2gSjMwkmmUUZWawWCJ1aUumxtdlPRwvDbvfLjP0fQpg3ZIoVv89K2PeXAYUUlBWVa4jkELzd0HE168epaza206suLsis/hSYoWhspCmmUs9/vMooy4zMgdwSLLcArNhY0L3L//FD90aDWaPDjY5dqZC0zyE27ceI5FNsFTdV5//Q22H3/M9s4xxcQyEJZR4uBLhy+98Qrf+bu/53hUABpjNdeuXuGD92+RFRXWghSn9JHvSIw1TNI59U4bz1hqoUOkDUnxi3OZaeqhR7RYsJjFLBLLIsoZpZpeu0dRVnTaLYooJ8lyxlGME/gUpuL1y9cww2dQGHq9OqFVrP7qb5N+9B3y6ZRplCOVx2YrJKiHuF6P7pe/zujtP0dHBb3f+Jcstt9k/vffoho9RCxyHNGg9toXyfMjykf3qKRlVAb4W2fpXXmF7rWbBDducO87/wOL23cok5hyMqI62KM1WCe4+DLCCLyGQsoKGY+Jdu7SMoILF59nNy2wi5zCGNa7bbQXEjR86oFHLA0d36fVrVHmczphlxzDdLEgriQhmrioWFtq0QoL4kWAEwgKrWg6kq5fY1os0HlJu6EI3IK98YypUZgqpO7C0SRHuCGrjTadWoOWF6BcTRBKpunpVC+EIEoLljshgbZY5XEwLSmlAk+hXMXKksvhuMBzJFc2V9g9HlJkDmuDBkuDBtcv94iTEY92R7x/e8r+UfIJB+/f/+Y3Wg2JkgLXcSgrEGg2NuocH6TkhSb0HYo8RwlwpMYTHmVW4giLlGBxGc4lB6MFWVmAqnF3d8S8gjQtMUbieII8tYAhqAmkhOVBnbXlNsfDGCF8jNaEoYv0TivHtLFkhUILSVla8sqgrUOpNVZIXMcgpERJebpsci3Pb6xwbbPH52+uozPJKM6QwmE0iRFSIoVBWkNZKSaTmE4tpMoLPCUwSCaFZZpDZgxFWZLm4NQV7bYDJufchS7dQZvZPEHiMZ5lpKXCaBDSA6nRxemC1VEKZQylsRSlwVWSwKkwqSGtKrQuiOKKrAAbWFbagq2m4rPXP8WyW+fJs326QUhVSnKteTxM2Fhd4sH9Xe4/mqKtxhhJb7nGxx/PmU3m9FsOFNBwFf/hv/oCKEvpZLz54yfM0gMCGSBDyWyccOvOIeks559/7bN86tolbt1+zP5JjivtqQGmqlDKpSor9g9mLOYZz93Y5NKl8zRbNQaNBa6RHJ08QIUujpNy4+oygRAczFJyPFwUi3nGz95/SL0ZsnV2hclYkumcet3D4oKALEmQOJw7u8poNqTdrHO21+HhwVNGs4qyUMz0BCFg0Oqw1q+zvLrBar/Le7fexyifx3sHVBq6iaFrHfJaHdf1aIU13rv7EOVJQv+Usz46OsZoe9qgg0AKEAKkPB0EvFASNuoUs5h2wyetNPOkJMtTTCVwlaUqNUF7iVmZU6u5xKWkqDKcANxKc3VrHeVqRtMELVwudAe8evM6ycPbuIFioz+gfvFlpFuQPH2XLBbERqKEwK81qckGzS/9JmKwjF8Lab/+T4kOHrB4++/IqhzPDvDPXyf81OfRR49oX/k88uwGRAWDixfRo32G924R339Ao3aG1c/+CsmdH1FVgrqjcNsb9D79qyx+9n8ipie0V27QfOFz9K9+hvaLr4Kb0Sg9Pvc7/ynHH7/D1PG5ceEi3bZPlGVIX9Ly64QoWpmgMhGTUcRqGJLGMUdpSr/RJdMpqtIEJiRQHjrwCG3AC1vLSGkpbM40B2sleZKRWkGapehZgS1jIgTNoE6UxxzMUzaaNaSNUcoHVVJVLoaSfhAwzzKS4wUP4pxxmhEXmsqk1P06Js8YznOySuN6FQ+258wSS5adcDCKURJOxjPmkcPO3ozxtPhkg/fv/943v9FquGhtMRZKXUDlE8cxWhu08YjijFotJC8N/cbpYrPZCqgKQ5xKjNLAaT9iM3RJCo3fCdBFgWMFVWXxfRDaod92CF0LyqXb92i1fCajCGtBqNM2+yKXuI6HsQXWWCqjkco7vdYqiVQGKQVSScKGh5AGpEBpybQqOJ7HnFld4tWrG/zmFz7D4ZMTtkc5gbIopcm1Is0UVnkURYrvu1itiLOSRV4S5xZTabrNgI1Nj3/29Ws8fTQkK3OePK3Y200pUkueas6tt5lMM6yAQpZYrfCQOI5AYHERaOmcBvZYS6tmcITLeGGoJCRJRRQXXDy3RaPn0FjrcebCTd57eptXXrmBlHX+4E/fotltsbGyzB/92Vs8OY5YLDKUtEirGM8iFrOS5Z5Hx/e4dqnDzZf7BB40Ap+XNpbxyoL2epuTowUf331Kp7WKbzUKQztsc3d7j5PpmHFScf5MB0eBMeBIgdGQGYWQcP36GfZ2jtjcOMudxztcOL9BhESUFUeTGDiVPkonIylKPL/G3mhKrC1Pn05OC6l9S56VBJ7g5GSO6/sYU+Jg6bZqKEeD0Cwvd3j+6ksMZ3MOT4YI4bOy3mSxmPHS5Uu8c+8OrfaAj99/yOHJMZKCXDsICbOkItUCP+ywttrm8f5TrLUII9BaY6wFISi1xfM8qqpAWItyHRwBBSnGaJI4p7/UYpEVjBcJVkmSIscITafbI4sjmo5E6Rjjh/TbddIyo5jNCGseaTbBGoe4MLzYXuX6p55n+uA9tgbrLF3+DL1/8ttYt8Du7JDkMdmiolVvYFxJ+/mvopb6RN/9N4iZxrl4ncnf/AFllCFVk8GrX4K1FbIf/zmLZx+T37tD88ob1F58gcX3/x3pNEKICmU1TE5YfuHXqYoD7MkBRi6x/sZXKYKS2Q/+nGwyYr57m/LuO6SP34e9Y1Y/9x8RfP7XcdyEweO3OJzE7Ewr+jUHnZcYRzKeDvEKwWCpzqiaMz+pmGlDK/QpPIly6tQaLsksI4oq0jRhYjQSlyqaIo0k05ZpljNLNZ1Wh0bNwUqX1ToM5yW5c5r7kuYxZQUqc3DDJkmVMZqkBK0683lCzQtxbIEtDWMsSQFKevgeTMcZx/PTM6lLFylL7u9MyTKXy2cD6nWfR0+HVIWGQrKyFHDn4SfcYflf/v43v+G5YK0CQFiBEZa8PF1m1kKfWkPQrftsLLv0Ok2mkWE4zIgygdaGCoEnBSoULNKKuCyYzFJCRyGtwFiLxLK05GPKkobvYkvDaFhisKeJakJgOQXnNNN4joMVp9kECAlYAimwhlN7snPqjCuK01TEUJ1O6kbD3rzkp3eHfHD/KV6Q8Ttf/zKTk4idgzmVMhSZQqIJQkHYcvGVIssrjFQYbZEVXL2wxcHxhKzSBJ7g/OYmXuhy58GELMuJZhDlGedXGuS6oiot9YZHFGuso3EkLDdblLYijSoUIKSiXhPkGZSVpag0vVoARYXXsHRampdvPM8iGlNUksJWXD1/jXc/3Od7P7nLZJGSpJKPbh+gUUgknmdQRmCRJDGUVUmmSz5+MKJWV1w4u8I7H425/3jB8TQidGucv7TFk90jHj+Zkpc5Nb/DrQcHLIoZn/70Ra5f7lNrdxlNFxSFZjqvMEIihGU0nHGyWOD6gh//8GPevbtHq9nm0sUzPH4849n+jEWSYYyD67lcf26NM1vLPHsyRpeCRVqyf7QgjjXzKKMqDYUVeJ6DpwuSLKfVbiKkx6PhMTv7e5zZ2GJrtYGnUi6un8P6gvl8wXA4Yn+0IMDBKkEnaKNcwbOTGVEOWpUUWvHgwSNWlpaIktOBRHBq/hBIsOB4LkIZJArPDVCiYpQljGcRUilCF6aziEZYRyofYUrOt7r06i5OIJiMc0wumKYFjihINGwtNYnjnLPLW8x0Sjfo8cJgwIXPfoXmbEj/V34Td61L9c73kW4X59rzzJ5+QJ4L/HqAJzt03/gi03/4n9CzBUYFGM8wu/0uWgf0r76K2Fwh+fFfoA3Ms5LSSuxwm1Ct0PnCb9PqNmk3AupOA68W4m+eRbRd5L3HdK68SudTn+fo2/+aZFGR6QqMAOXi+G0ar30ZURdUt9/CKRSi32Zw/JSf7zzG+h1smTJcpPT6bYQ1qChjLCRxXGCaITZwWG82sSxQomLg1YnIkdISo8mqnMB4pHHCHEmz1oLSEoSCgecTm5TrW31KJ+Niq01Oyv3DCTpRLLdCllc7zOIU47tMJ3OEFjw+mNBaGfDkZMIisTx7UtBt1XG8gCzNyfKE8dQyGseMpzlJbogS2DtKePQk4salNV6+sUmjFqL8Bj97/9knG7x/93e/+Y0gUCAEQliEANdV/H/9DkFouXkppNtx2FpuM1uUPH02xQtctK5YWg5oOi5KSl5/uc+zw5g4EWTFKWj3+h5owdZ6hysXmygJ9XYLowv8huJknGAMSNfg+86p+kUJ0qwEpUgKyHJDKBxankS5BuuCspJu26EhFI7vUW+5BMqQZ5KkVJRUFNbw4YMhP3n3I547s8Jv/colVlf67B8cUQsctJSYMscahfTAcxRntzqkecY8Lqiqkovn6pzbVFw8d4Ptx3tUOsP3Q86cb3N2a407D47IFiWlNadAICS+L/EdlyJPqDmnnLi2itD1EaVhHplfxFRamq7iaGEoSs1Sr8WN6y/xl996k+//+DHf+u59/u6tn/JoJ6bfrJPECY93TihVAFS4QuA4BiToCkDjuZJGPcCg2N8f02r2+Ot/vM2Hjya8+vwZrp1d4pWXrrHZbyBkwP2dQ977eJdZKmi0u6wv9/DqCT/44TPiTGMFxKmmrCSN0GU+TdnZjzgcjTkally5cp4kiej2fNbWQrafjhnNJUYYlNaU6ZSNpSZn+jW2tppoKzkcZVglUEqRZhqpFK7jUWWCskqptEdR5djEISscJrOM7Z2n/MqN59k/GTKOIqaLOS9dusbBaEgPRacR0GmEHEwmPDmccfZMk/EsIo40EsBo3F80qVtrkBaUFThSARKUAASOc3prymzBPDv9T8vNGnU3RDgK35T0gxZnVtrUa5KTWQpOEyl8Br0VFnlEQzU5HM+Jpil3D2bYUrAa1ni+X2Pt5X+Pzitfo4h3id7+a6p8TLz3EBEOsEHIbGcHaRWbX/1N0uFHxPcfUBbgrF+hmD5CHyxonbtG/flXOPrH/40qsYy0Ji1bNJcaRCf7ONMJjTPPIS6+gH/+VfxLL9G8fAPVXkUuncV1NMFLn+XgzX9D8uyIAgcPFys9mivXWPr1f0E62mbxD3+CPbhH/uAOqr9O7cwq6f4zbg8nXL18AV0kBL5kkWRY4TA/nnOcCppth/ONOrWqYLVeY2FS3BSqwGF5dYnRdIrjSOK8onIcSkcQF5qt5TYuOcdpSb/bY//4kJVeh4FXI5ea9YbPJIvRgUsxXyCVPN0hpQVUgtmi4PCopNWpUW/4nF1v8eLNLlQpa2uKykhGo4ROJ6SqOOXdayGvXVvi7FaP9ZUWaRwRZzOeHhxxd/uXm3Q+EVJBANdzKKsKYy1CCIQQONKlKDQvXGjw4laDsW2QRSlpBn4guXi5zuFuiS5TLl/uIIXFVpYss2hAug5pmTOcFLSbHtM0J3lsCAPFRluy3l1mODVMTg7ISrClodENycqYsrAgfYpSYyrwlYcQBscVKFdw7UKDh/fm6EQx6Dvsjxd4YYPN5WVOxiNclSFRFIWkkpYnE8sf/eg2z296/Of/ydfJFgnv3N1jtlhw6UaXpim4/vISR7s5o6HmSFripEBIgRJ1jocei2yH0WRB6DV48mxBQkVNRlTG4Ckw2qKNRNoKVQqEB83QIc4MrlLMqwq/FJjCMLUCUwmkNFSVINcOxxPLKCn57/7gT7j17hG5NkjH42QiMKbAGMnWsuJkanGLklbNnkq08gqtT+0lypFEuWH/KMUPNUmu+d//9F1KY8mN5KO7x5go4+JGl52dIw5Phpyc5BzPLVk5QfspH9yd0xk08eqKx7spvg9WC6SswHH53K88xwd3dnn8ZEKeOhzu7+PWXEbjBc+dafE7//Il/uqvt3n6OEVJQ7MVIOOIwcDj9c98Fl0k/P1PH/KTW08pUo0rLO26woqKSkIjqJNmOZurfdaWG3x0+5Aba0t87gtf460f/oSTbIZvJUJoPGlZavhsNdukVYE0klbY4LmzFRttn1sflDx3uU86m9IIQ8oyoZKnbl2LPc3JPv3Cml+8LWBdlhptdvZnaOWQ5iCEITcVjUZI05M4wtAIeygnYdPrc2++w+OjMWtrHVphSC1cZ7jzhLgs2VjrcLPVod05B3rO+K//LSQzslTQbjqkUcLRz36AvHqBweVPMXjt09Q3L3L0x39MGuUU2qe3eR63u8XgpV/DtJrs/dUfEk8i4srFuG02X7vCya0f4skWLh4mUKTf/W9pVAVCaypb4OQu8szL+G/8B5in78DREOH4hNLiiya1zQvU3vin7L/9l8T330UpF4Wg4Wa4OyMGv/Uf86vNAcd/9L+SziKUznGUZTzPqeoFWaqZ5D7nvIDjyZxaJTneWzBv+cTWMtWG+fGYTEtaoU9W5hgfZvMZnU4Hn4rjKEfi4xtFZ2mJ8aLAdzUrNYcqEFh3hXmhwQpc6VELQ4q6IBc5Ipf0Vhs0fItQBiELnu4eYWXA6Khk51lEVXmcjBKa9YCe1+CrX7hEWR5RSsF3f3SHc5t9hs8WNLq/LPczSvYAACAASURBVMz19PlEgLcQ4IgKrcRp5CKSPNOEbkVRCHRc0HIkozjHtQLHlbhKUeaaZlDS7oT0B03cUnK8yDm7UWc0ywgDRZk6lAaOJinK81ksMooSzm2mrHRqPH00Q9V80iqj0hIzjqjVFFKeNqa7jsZzQViDlpBaFzJJvx9yEOZkouJ4otno1QlrAsdUSFFhrYMUFt81ZKUlRyBdw08fWf6z//rf0ZUga03AMny0IKtLdr+3x9pSSKenKLQkR9AIFSavSKchw/ERZ9a7zGczeh3LwVGBIgMh8K3gbKPO9ixGBA71WoAuM3JtsZVDWZY0UBTKkKUltlTUlMJTEqtLHGPwHMH23SOKtMILBLXAYaXvcLBTEjY9rpxb4tnhEFNJrHUoKCE3CKvQVmOVRMsKIRSVEKd9h9rBCoE1Bl95fPBwxOH+hFefP8ef/M2HPBtllIlD+gvJ1sF+ydA1lE8SWl5ArQVFZpFS4XgGx/XYf7ZLlc7oNDRDa1ir9alcwe07R8zjjNFRznA/QipNhmD9/ArSZLx7P+K9J9/n61+4RqgUbgUXLqzgiIywWWOWLk6vq/gMxzGNoEnbd/nqjWu4DY/x8JAiLNHTirkjCYXg8eERZ7e2ePDoHlu1LuPhDN/P+O0Xr/PjB8ds1kJu333AtcsXKY0kLzVSSLQ1GCEwRuMpB21Os02UUpSlRklJXbn40sFaiGYzWv2QUGrOOC5+vWJ/eoTIEqwpaYgMQ0zpGHb3D9DLDc6vbVC/MCB/NMJJFGeWO/Re/SzHd36EOx4RiwDhFOTGYaE0MpuQPz6hdf0MT773F1z6yj/HNlY4SR/SH2xhazmzDx7g1Fv0PvU6Zrx/usCnzrU3XuPJrZ+TRRoTWmwjpNIV6d4zcikQQRNXOQhSgqcf4a1foDjzPOv/6r9Az2N0YdGuQ+PseXa+/d+Q3XtAJRVlUVCXDsZ1cRstsmgP8WSfL37hK3zw3g+ZFlBkHv2+oUwMe6Xiiy9f5MHJQ0gLWr5Prx5Q2IpUOBTa4DkurnJx3JB20wGb0m3WmMwLHmaAGzBoOKTREBohsa2IpjHrXoPK0cx0xsFJzsW1JeJkgVt6CMeldFJqHRddpYR+FwOEATjK8PP3n1EaRVUJZknObKGZpSUKwaycMzuc8GxUEDoN4iTm3NUau09H/7+4+YkB7+fOD1jMEnJH8Hh/gSx8PnetxvjQsl6roa2lyE95t14N2Giwsz/nxsUmayttnLDFKD6h4blsDmoYa6jVXOZakCclaW4QhcUUBmEsKq1xZzghzyVVWtHwDEJ5FGVFHltCBJVx8DldKlnrEEiLtZK6I3j2eEYUF2TWYK3kfNNnbcnneFadljM0BPvTDKX0aVN8ZQlCF11kJLHEuAZTzQh8gZCGaWqRRjHSKVYoXvtUhzffHFFohw+eDDm/VLJ1XjBOC+bzkk4noEgrxtMU6/kYoXmWFaSlxBOWkypCCcvcKJIk/UUoU0XTcUG6eDXFhXZAkqcU1hKGkrAOrq6YFiWe5+P5oJTlxpUaEpf37+6SlxYjBdqWlJEkcStqStANa5zkCVWpkEoQVwWO64K1hH5FjqIoMiQQ5ZZ//b/8CKs10oCnKoyGSmgwp5LMdhASKLh4fsD9x1OypEJKBbbkytWLLC1lRNGYkwPNZ69f5Pv3brPSbXKwFzMeFZztdflw9xArBH/xd3cZDHzSuabhK779/Q8ZDNr8i197lcpLePjsGc8OTuh3Wix3HT7cPkEZh5uX1ni6u0uzV+fuk2066YDPffor/OGffYuTYUy/U8eZxvR7OefWVwminI9mM46qgsHigCU/4KtXN3kyz0g8nxvXr7O9/Q7zRYUSzimAVwYlBdqROJymHQJ4niLLCuqhj5aG/STh3NYAYUqQikIarBQEfoOGUzKNxzi4tEJDve5zLmxDlhFqw0anzacG52h02vjLSzx58+co45PrOaELnrBU2kGZCjzFd/74j9hwmyyfew/CJYy9j22GzG69xcHdpwThgPoLL5HKkjixrF47R5TFlHuPOC4layogrywNMSPNMvxanaY0OFLhyhC7vI7ttUj+8r9CLBJwWyRZRpZpvM//Fiuv/wb7z/6AdJFSGgfHWpxc4fZXKHRMsnOHfrNDWUpqhFRFTlqWSOWy2tMcPHvC7vGM9bU+lYJjoXEcSZlpAkdyNJ2z1lziaDhkeWkJp6pQogQLaVmxUj/1RfiizsFkwjiuOOPXcR3J/b0Re5MFgWyQ64yWp8iGMXQC2rUOJ64h9Gp0Qp/SWIbRAsfxyApJWlqK0jKcVgir6NUlz11tovQM4Xk0GpLGssPxGEIleP2FK3znzZ/8Utz8RIC37ymWVMGZy33efTzHVz7y/2XuzWJly877vt9aa4+1az7zuefc+d6+3X2b3ewmm2yyRZqSRUMyYllQgkxwAMeR7CBBECBPcfIQwPBDAMdJngxIURJHiuRYFhVroKSQ4NAi2ewmu/uy79C37zycsapOjXvee62Vh7o2BCNijMgBvJ/qVJ1V+6Hq/M9a3/f9f/+w4oO9BU4dEC0KLukuL58LyBIPr215/+GQT29u8dzz60yynHuHBV7LQWaw3W+wmOXcfFxg3RpRC4SVS+ekp7AaJouMLzzX5/phwvG0prYSdIV0XaQ1rIQecZxT5A7G0fjWwYqUtabPJ890yRc16xeaHC4qhoOEe48XzHNNMq6IAkNeLGe5PWFoNxWLwqCkxQ1cirQiV5LI1DS9kEmaoTyQ1pJrQbMZUJcJu6ci9gYxtVbMdc2NuxmLuGa1qbhyqUun3eTOfUU2zlBKUpaGMARJhWY5B15pTRC65MWy5u0VNcZCWhoemoLTkUNqFaubFqksi5nk3DmPshYMjktGlWbma44GC2pjcYSi1gaJoNYGH+h7HmVRLEs81i7FqIay0hSFJQgVSIE2BsdZMmNGsxzhwfpKiChyQKEdl9qAqTVElrKqOT6agTRI19BoBjQjnydHx6z0V6kXlr/5s59jMJkSWcn+3QnHRUZDSx6WOVLIZWNZLYE/0pW0PJ+eL1mPFI9PPuLzr75JrgtOFim9fkTo92gFNadPrdNpt/C8kEcnR+QmIwo8bn34IdNhTFXX7O5CrjPev/2Qn3n1eW49uEuj5dMaSw6HC86f79NpNfDlMcOg5nB/Dw8XXZcop2ZjpcfR/phS1wjloY0h8gPyoiBNCxwHep2IwXiIF3rERcU4X+CWOXpacqnTpkhnNByfaV1QCYsnXZQvMI5mPI25shnS87qsNgSt3ZeY7t0mOxkjw/4yEUc6FIWmqKBOClZfOMPOpcsc37xHcv8DDicz4hjOrvYYfvRDhouYRuxiZ7D56l8gnb5D99J5nnzj/+CkTJklAa0wZ/D0kHY8R7geQiqUgNAx2MZZ7Is/SXrrm6TDIXUFOWNyo2gby/i9b7D5b/4S6twpmtdvUFiBozwcJ6ASAmUFFHNK1/DZM2t8d36No9TF8XxaUhC0GpwUhk7kUqYl0UaPWRyTpiV+4JEJjTaWxWhOGDjE8wxHGBzPpRc6ZKRY2cVVKUJ41HWIclIG8xPU2CdLJY1mk4YRiDonGiucQDKZFfgtwc7aKq3Iw0jNtZuPmOQunqtIUo2xDkFTsW4KXrm0ziee65BnKcdziR8arqy0uff4aAnjsl1m89GP1c1/mQzLXeB/AzYAC/yytfZ/FEL8N8AvAsNnv/q3rbVffbbmvwT+BstN1H9mrf3jH3sPLP3tBieTpUW172miKGQ8K+hFmg8fLFjr+nyiY9lgC1kIvnBmG6etlijTKGCtOUOnDsataYQSN+xQmyPWui7joaY0GkcumcGhrPjkuZALGx0eTRNmCxDSshop0srSjBrIPKcdKJquYJRrek7N6d0e5zc9PnVqDZFD3lBcv3WEWlnlpCy4/3RIo+vTBmZphdHQajYJPEiLgjSusQIC31IZzfOnVziapuSlxTcKoSS5rZjOJMeDivG8QElQ1tCKaoYjizUeNYYf3Zuys9Hi/NmI96YVl/tN5tmUUgmyQlBWEqzG9xystihPkVZghFqaiWxNoFzSylCKivV+xIN7KfHC4jdcSmOZLBR1WeKoCmvAdQVCaxy5dIKhJDWaUVGAElS1xVFq2bNwXEqtQTrkRU2aWnTl4FiBtpZuV/HGly4yPkm5f3NCXCUYKwicisgLcLTBFZIrl3pE67vc+egxZVagjeD2rUM+eTXib/z7/xEf/OD7/OEPb7PIJK6j2Oy2qGPNZG7pdh1EoElmFWWeg41wQp+Nbotz/ZCnucNgOufC7hWG04Lbj0cU6QhlPFa7NQ8fD9h7cLjMR11pYLXPD68/IMkN66ca1HXN4sTwND7h/NoI4zY5mMRYV9Lb6XDcTlARrFQ+/prmh/dzZicZ7YZiZaVDJQQrvQ6TaYyqDcJRWGuRAowV6ErTa7dY6AVJUSA9SbNyqVo+WakZLmJqT5AXmoPFAlQbH4kQcH84Iwo9kqLFZzZ3Ofvpn6Xz2nPsf/D15Z+9KalrQ+1GWOmiyMAa8Bqsdn0+Gsc4xYLFbMSkXqWz2uH2ZMp8UbL1iVXi4Uf0Ln6G57bPcv3X/1fGBycca2h6HqED6/0mIQFuM3xmoHMxfgvxwhtYR2Aevk0pXIQPYS0RNkcrkIsTig/fZuXKFxk+OiRwNmm9/CbNS1cp8wnlZMDKX/2PGb37NbzBAWd659hfHNFSBqcULJTgeDKnFbpsrbTAZLiOh1IRMtCczMbUiSGtBaudJidxSrcT0Qh9QDIZZCgvoX8q4L2bBwQ0UYAfNHl6PGalt0VhS/zABb/ALyzxikvxOGaW1LSkz+PpmI/3pjg0OHu6h5IVjZ0VdnciTk5OsHYFKr08eTmCRiCYJfDB42MCx+fUps90IrhwtvXnE2+gBv4La+37QogW8J4Q4mvPXvvvrbV/718Q+xeAfwd4EdgGvi6EuGyt1X/WDZSE3Gh6mz4XtnpMky4nk5R9R/HyC31mewXXn55w+fJZnowWbLRdmu1N7i32+M6tOXceTfmFv9yn5XrkpWU6N3x4d8bWuuKVyz3eSWekSYmVlsjVXN7t0fJd7hzNONyvaIWKMyshvpS89zRmkmaEosa6ktPnOozuzvjpV7Z5sR/RDpsUFSzMECcJWOl5OC1JkHrEecgwVwwmGZUUJLVFJgVeJdHCUmuD63rYsuT0SsSq73CQWXpuiONbjiYVaeIh7AI0OMLHiJyiFpzMNJWxuK5A1oK68nj8OGFn3WM7clmUCYWUJPnylGG1xggXgcFzHWqjqTHEmUF5Pr1A0A8EB7Ol7frexwlFqcit5fgoo7AGrMT3HerKIJQBIamNRltBXpmlWcpVFICpLI70KesSaQQaC9bgCAetJdYKpPIodEElFF3X4dzWGrY45vT5NtUjQ5ZZ2mEItWGzq1jvtTi90eTO0z3K2YzN9S6j2RzPhtx79JT/+Sv/iGbo8HQ4pheEpJQ4aUDUkJzfXKfha753Zx9TByhXoqRhEs9pBSu0VpocvvOQ924+4XOvvYCsBNm8YpYJOoHHjVuPaDcVnhAcTIdsrq3z+OET5klBw/eZD2KOGk1sltNvSmbJgosXdnk4OGR1p02vrZHHipv7R/Rdj9nMJQokwVqIMDCfFjwejpDSw5UCKZfNy1JrPM8hq2qEXCIZ8rwmkgFVZWBRMglqVA1FIyQeJQxMQaxdsjhme63HPD4hciOaZpOffP2nOPP5L5BPBtz41f+WzVf+Eqd/4nWefPf7VKWmdBSladBq+MxmCRKLT85gnjEtSvLKEDgho+E+5aKkt3UKJ6r5+Hd+jUb/DFtvforR/n20G7Lieay0mnRa0GoYzPgGZZbTclqUpiL0u+jtM3Dz9/BME0dZQltQ+R7KGhxCTBjhuk38S18kOPVJhI7RRw9J3/9t0scfk4wNZnWbjS/9HHk8xH38MaOPv829w5QyKahCwVqjT7vjICy0WhHToxOMdIjHJXle4FY+GZaD8QLjeDil4WQ6wvcdhsOYs92IB49n1DrAdSQvr28yq6Y8fJoyPhkyLDLObO/glpZho+JglHEYx5xub3C5EWK3V3n+xTO0fIekqkEKPFcxHg7odyOEcpcTRS4oKXm4v8dsrnBdBVawttpmNJmT5eWfT7yfJb8fPnu8EEJ8BJz6MUt+DvhH1toCeCiEuAe8Drz9Zy3ICou0lvkgobsJZ7c7BIWL1ze8fW2fL7y4jmg3MAtLNbH4yufB0RFPkpjTfUExd6jnHo+HKQfDkqNxTVWV9MOQ0xseD9sho2lGaSAt4faThKOoZp4rTm1FNCPYWfOYzwyaJWdEYKisy95xznOrAZd7AY7SEFakE8ux1jTqimazyft3jtChyyix7J0sENpilINCU2uXIheUmSFoKgTQ8XwanuKt2wMyK9mOPAa5JvSWkx+eq9jZbPD0cIZjYE9LdFWjhIupNalV5FWFtIZ7TyY0IodQS+LEsMgEgaep6+U/i6ICYTUCQ9sVaOshqFhveewvCuZI2oECbXAdQSA0CIkwlspaAiXQ0hJYiZEV0ipMqfEci3KX9VlX1PRWQubziloqtDb4UmEAYwx5vkwaMegl7lTBPNX8n3/wAc+9cIb5NOPM2R7TvSFxpnF8l1mSc2Fzi9t35hw8HNHsuARRyXPtPp978VVuPnzK3dEhw1lJ5CnaXQc5j/AdyYuXdlkNLApLaGryqaRSFdF6j9Av6XVdrn00YvfCae588z1aYZtzV0+xut7mD75xk3k2x1ECsyjpNZsI1eBw9JRGs4t7JAl9B51XlMZSOYrLayukecU4KXD8EF0IxnlJlc2ZKMWd+YQ0r/j0Z79MMRC0WhGP9vZxHBchluUtIwXUGuGrpcHI1hgBZVnTb7Q4HB2yWQfknqEvA47yBccaXASVWeIhmm2Xoizp+gKRu/zMX/vrXPzMBW790W9z/M7bSCugcZvTr16lyr5FK1B4Tkkcz1m4PseLBHE4JFpbZ1qWnBQhEyNZj1zSZEGFZme1xYdvv0Pg+Kw2oJ8mKD+g63fZuPQi2597ncXdWxQqwC0zAuUjPYsnPazXxkwPqW5/QK4LHOVgjUfLEzjBFvQ2UFc/B6Ig+8avEWxcpmgl2O9/ndwatOPi9yxZPmXw7W+y9uYbtDfPcdUz3Hr4W0xSy05vFbFtyauCw+GCpAwYzjL6Gx3q2GJNzfHUErQcTGrpNn2GwzHzhWWl4XH27AaHeQy1S1kWJA4MTyYIayiVQ4om8Bsk6RQn8thsNGkUKRc2O2xLh1PWpwoUY18QpyMGc4+VdsXj44rtfoS1Cs+31FVKUVTsjXLiwmGj73M0icnyijhtsdYN8P0//877n19CiLPAJ4F3WKbK/6dCiP8A+CHL3fmEpbD/6Sr7Hv8PYi+E+CXglwB8T5CelLz5iR3GRxUbGz4vfH6Hj56Mie0T3I7PfDbn0egQnTfwEslJVrGxBu0Vj3jocO39EZ7j83C/olIFYWT4zEab8lBTpwVbUcTeSYl2NGllqOaSVsfw0kWP+48W3NuvsY5DqgUgqYVAU3I8hc+/2mOSF6zu9MgTS75ISSiYi4pFLvl4r+DueApCYhF4SLQs8P2AvKqwVuN6ktBCYgpQLQ5OCrR0Odt1iecaR4BQDu0QXlxr89rzLaZnehxMKqKDhEWSME4svQgCYLXV4GQeU1hYTDQTBcZYallS1wHUhkBCL3B4/eoWf/zBI5rNED8vcRVME01ZK1xlKK0B64DQzyBfoI3CcwW6zrDuMqNP+A5xXOF5CimWDbPluJRAlBrXAmi0kBTa4nkSZaA2EukIEAahBQZBnNWsiiYfvPeYyA9YEZJLlzb4eD/hwSQm6ijeebBP6ClmVU037HJyWOKt1Hz/+jsE7XN4WPqbTeosATPnU584y5nTF3nw4JgzV68yT2JOBjOmfkUynfGLX97hwvpldNBAXLvBtRv72MLh/VuP+MKbr5HkOVc2VjkapTyZZjgtj3mRIYcZZzZaZIsJX3zjEkcHhzw+aZDriquXTlEbySevnOXb332Xz3/6KtfuX+cwiyikZp5qXE9xer3HYrrHamuH8XjAIs5BSLQxKARKGjzXxxhDLUA58hkPBkLX5fTWBt12k6xYMF8kCKEo0xTX9YiiAFEUYGpCFbIedJHROiv+nB/8w19m7+PblEWC44S4T+7i/uSbbHzms/jTmHL8GPIZotFHUzF/csTFN7/IWvC73BwLfuKlN0mlZXWjx+OWz1vvfJ88q1htubTKGk8qQr/H+dfepHHlNMMPr7Fx8VWiF18j+/gbdMIeNLt4Z68iLr6GGV3HkOM4TTzlYm1JsHIB8Ym/gGy7JB/8HvnTp+RasFIJ/M99kbLxFiwsDeuSOxWecDFFDnnF4L1vI2vLtrtG75SgDsAta+bW48LZdY6mOc1ewOwkYTqvWF2LmJ4kqFpQGYexyYiiFg4TmisRs2SGK/ylo9t12FhZZf7ogBWvidfqEFQZKytrJIuUKq05cnKaqz1aecrR4QmxStnK+xQCzChnEqcMRwnDiUdVKwIpCUNJli7I8pL9UU2a13TDFkUBcQK+cji1ETBapP9qxFsI0QR+G/jPrbVzIcQ/AP4Oyzr43wH+O+A//Jd9P2vtLwO/DNAMHdsKWvzOtx7yxmt9bn405KVXNLEpOXO5Q3/Vp3Xcokgq/HWPxMuZxDVlUtBp+1xZ3+aTazXv783QYY40gp9+foszTR9j2ly8IPnBh8d02oIkk9RC0wkDAkoCz+Hy1jp3j2dkmcb3LXmmqaSkZR2agWFwVPHcVp+DYkRgl9TCju3w/nBAy5ec3g0ZpZpM1wgryMsK3xEoqwlDD12XCGUwtYPSglplnNttsygMZV5h3JpIK0oreHFLcPV0RJ5Y2sZjpGtOdRW3ZxbpVNQammsNjo5LstrguYKqrpFKYpEEDRcKw8p6SJlVvLDqEgWGs5tNnh4nRMLSjzz2xhW1kCilqYTAU3YZimuWDUdpwcNSipDn10I2wybvPjnGWLFEfUqxrM9ikRakdDGmxPV8FnGGdFyqqqLhBmBqDIZGI6RKc5TUGAuLk5hGU7Gz3eDR3RGXXjtPnqUUSYXTcsjyjLVTp9je6eDaGlUpHh2foBqKg4/epxMY3njxJf7K5z/BdHpEv3UGg2R1xeHm7Xf5wY09houKTrtJ1G8zrAr68hBMwNUXL2EbR7z54gX2JwMeXvuIz3/6Kruf2+Qf/MZXGE3ndJ1wmS2pDbN5TOh5PNx7TOR7vHZmldEiZXYSk+ucaz9K2Dq1iqME270NHk9yFgV4gUcYhjRcl5PjE1I3xLEVjXCZ+pOXJcpxwBqajZAsL9DWIAVgDVUFvvRJkpgjPWVWlDgioukqWq0AneZs99d4dDxgkKfUZYESkk4vIH56lxs//AEFDkWREwYunUVKXSt6579Af/cCVT1k8p2vkD29x0YQ4jU9Wudf5qf+1i/yf/3Gb1P5Z+msrSKzmlTDSVyiK0GzUVNri7AB537ip3C6Htd+63/BqQTpo8ecm6c0X/8Mcu0F6O8ikkPs6B7u5st4P71JtneDYPAI4W5iX/kc1cEN9DvfoRhPmBcOGJdMDvGlIVWGSlfU1oLfpdfcxJ49i7+yyqnP/QyjBx/Rmx0irSDJFzwczFjdXOFkOma+MMzjHCoXUxtm0xStwfccDvYqrrzwIp994w32b3+NRTpBqhbKMSSLBY4W3LrxhGqRcnrNYVBZQikps5xOr0HL8UmKBQeDEStSMPMD1s5vYYTEzo84TYBdrfn6jQFHhzWbqyWHWcHRk4xmp4sfapqeQ5kXPNobUmlDo6HQWI4HCYNx/OcXbyGE+0y4/3dr7Veeie/xn3r9V4Dff/bjPrD7p5bvPHvuz7yUtPzJvQHzuOb0LOfc5gr3HudkwTJd4snRjI31Bou7Qxqlh6SJ6464cnWX6rhkVkx5MK/44WTBVtPFGMvujmB/qPnD6x8zjmuUYyirpe1eScsiqzBWsPcwJtNiCWr3NDw73ltjuLTbRmnNo1nM+kLwytoK3URBXfPx8YzYFKw3AvS0oLYVpTH41hI1BFiJri2ZrfEdiUSxuubz2mqLampwAsVxXnB+o4HxNdceJiAF06Qmx9APAupas7W9SpBOOIkLvJnl3LktnuyNSPKaVujQjAKelBmRL9k91eTOwylGOpxMF6z1XILuCswgncXU1uIGHg1P4aqKolqOJzq+h+dU1M9Ew3UEWI1VgqbrcjzJGU1rssJgNFRWUGBwPYEnQXkOs7ggTi2iqpHCQVkQLHeP0tEII8iTHFcKAnd5epDWMJlbrjQV4yzjq9+7hdXgO3A8K2hLyce39mn0fc6c6tJyNOfO9FgkJazk+ELRCQ2n+gEma3CSHLO91mcRL7h66Qy91VP8zh/9kP2DBaVZum13/r3P8Wtf+RpvvPQqv/XVa7x5dZUvvvlpPBsxPX4K/TNoEbKx2mV3q0thUmojqIRCmIIoEAwnMcdeBkrSjUK2gh61gK1exMngkIa3yvHgOrbyCDYVRZ6xSGOKzKMm4exKj/HjhzjSwVculiUGIo4XGKlwhEBIi+tIhF1O9SRZjpaC2lOcTBIC1yVaidC1IJ3O2MBBlA5TbclkybbnY4TheBFTVw61gEJnVJtdxrff4tE3v8bayiZbn/oSu7/wX1OND+ndfBvv9Mt89Ot/j+LGXUYDjReucvsH36GPoNlug9qnHwa0g5DaWhp9n4N3f8Dw6x/jBhGzvGLTCwhdME4D8/jb6Gu/R+gK0BJ99+tItU545grmhS9jyzHlN38VM5xSWQ1OgKLG1AllOUFME8K1K6RH38HYNu21VcQL59h/9wNW9nu0P/06zsMP+MT2aX713bcI3C79XpvZYsLhKAEjSKZgyFjtNMnriqJM8Zs+YbtiPrnLH/3+Ez51ZQXVjBjOZ6SpwfV8ng7mTBJw3YDQFYQel/mV9gAAIABJREFUlEnB3tOMqBWwvtrGVZK6EsyVoa49zKLi3nTCxfWQ/fmI9++ntJwm21cVw8MMrxXQiGA2L4gHFTurPlubHTxP4SvJ8cmEH157yKmNNu22+vOJtxBCAL8KfGSt/ft/6vmtZ/VwgJ8Hbjx7/LvAbwgh/j7LhuUl4N0fd49Oy+PNlzd4cjzl0ZOch3sjLl5u0ZUuO/0u83iBCGr6z7UoZ5Yqr2l5LTQZqadYFA770xldVfGl107jG+g1Ij6wEzILZ7aaPBks6LQduoHPw0FJYQxJBTcnJToXrDXgudUelCnGL1C+S9e11MLhk681ubzZoZ+GULhUdcWaZzlauPzmN59gjAQkZ0PBQityIalLjdCCIHRZcRVhoMh1yXqoWG038doe91sJNk5oS8F6y1nuXoOSVdpstzs8TqdIWeJlFVfOrnBvb8poFDOLS+SyRsE0yXAdi9Yl6bxgJZAcpxZTQpLADx4ds+61wLooUzHOKlYCuNBzOIgF06qgQU23EzGYZ/SFYmEsrqMQ1jBNc6TWWFtiAQeFFHaJmEXiUNBqthnN5xg/xLUW+cwpCAKtodYC6UtqvUTwFrklcAWlWTLQ3353j7VeE5FlZHrZ/3CloCwLJILJSONazWdfPsfN23usbPc5uLUg7MAHd59y/emQ7c0We09nrPXX6AQNMgx/+NZ15rmmNgYjDPvDkl//3WvcuGH4+OPvUxeG+08P6dy8TdBcwRqXb/7GP2Gnt8q663GYjmlvBHTCBiavEW7ELM9JdMZuu81gOCZ5titO54Z4kbHT73Nqrclur8fBYIyuXcrK0mj1KOo5aZrTPN9lo9fh0WSCsZLIcalquxzFdASOcjC6XJ5praSuK9qtDoKUojC4ATQcwWyeslY6BCInckOIGvQ6Ae5qxs2bN/jMixcJPJ+DJCPVgj4+jY1tRsMjprXBzmPCm9+jWwzwz1xl7bN/hSQfMblzk8m84nCR0Dh7ig+/MuBLV1aI3BaNMGAyrViNPC6/+gkW+494+qP3cN0GRTFnNJJc3glRl58jfvefkNy9T6lgI/KwxlBbg2fH+IMDVJqjVzqoZEYCGOGAsLjUKMcnUMDhU7wrb9AZDVFhG+fKyzz5/V+hTGB01Cds9Qn6W4zv30UmmpkoCIJlWPh4XLHWa6H8CmV8bKWZjBN6axGudTm90mS+qIlCTW5DbG1ReOgsoaolSgZIN2e1H1HWS5dyIwzwWW5GTiYzZlmJwaV0BKf6HeJ4waUtH1ElNGXE/tGI7Z0+WxsNLmy18RoOdx8fkuQ+p7faNHw4HM8ZHMTMdIXAY76oCKOc/YH584k3y9r2XwOuCyH+WSjP3wb+XSHEKyy/Yo+Avwlgrb0phPjHwC2Wkyr/yY+bNAEoC83pnuH1y2cZjOZ86+aMW3eP+YtvnmIzcjm7usOj8ZDaOqysW8Zzg9eSzAqH3Mk5mE2JVgM2rUvHsUSqzfGDGZsNj1P9gF4ID44tLpaVwOJ0XC6eavLW/RN0DqaoGdSCrpyTlpZ2E6QjePFsl299eMK5XgtXF0xmDvPihFM7q2zR4QePnhJEPm5hef25VXY2Av7oe0+4c5RhlEMnUlxZCygKTcP3WY9c9k3OtYcLPv3CFkejBVpIhBCUeclKy6HRbeDVFW2l2O32mcgUmXuMHyW02z6Zrmlqh3Sg8do+WZoAoK3PaFrgKwhcS6ktWWHICsVAz+gogUVQlRVPFy47kSAMNKPakiLJTmZI6TAXmlC6GCWozLMpCKvQ1ZILbm2NeMZB11T4jZBZrNFWYnWJqyQag2HpDPSUQHoC5SrKeYXjLUsE6pmzU0qPRVJjqwXdSJGXmrKWGGPohD5lUYO0DKYlH9weIrVhcDCm13UodcXeSc7FMytsrKzQbq0xn1XgNvnGNz7AVQ6ba5KPRykiFExnKdeuTVHKIy8qpBBMcp+bt4+oykeMphW6DrnuDGhFIX/pUxfZ7EoeHg5Q1jK1FkdZNtdbxHlN1/U5txnxeDzChB5Hi5RQOgzjgs9fPc+Htx3mteZEx6RVRi0FQdjg+HhEu9MnWKQUVbHsiTiSWhuEARQYo1ESrC6XdXADjhLMpwntfhspM5K44nK4TSOSTHXNximX4byi05SEKufGg8es75xHmDuMa3CBlTMb5If7WBQ1LIFm8Qhx7/ukRzMaX/p5Vne3mOdHZHrB7//WP+bRgwHlxQ71eMrKxgYH+/eINtYZjfeRzirtrV2Ko6eMRhmHiwZ12MKIgvLxPSqWZEilBYWpyLOC2glxuwIRCERzDfwIp4jRWiKtxpEOjaCL2t5Bn9qB1inCL/w8qrXN/Mn3UDj4qsZ1S+zJMc3XXqB1821+cvcs/3TvMWG3S1Wk+L5C62VgxslRgdaCMzsreFGHl69sMTk8xpQVsauYLQ7oRhGGmrLWVEVNu+OyyFxmswXeehPlRYQe6DqntpqsAqsVvZWIfDpn/2jIpe0GJycp3sJFzyrO727w6qfPIu0JSQ5lXnA8Kjk80czikrJM0donzQrKSjKbp0TNgOGo5sJOBzj6/y7e1trvsDzV/YvXV3/Mmr8L/N3/t/f+Z5eUArRhMsjY2mzweTT37kek44ICQe4bGkJR5poq0qzstkkWKWVSkeqaS1e3KYscJ82wTZd7iymtQBLnml7P4/HxHF3CYS1pVBl/+dI6b49ieo7HWjfi4SjFaWgGhcaoks5Kl5bj8O2bBwwSwR9cG/NXn9+iVDGr/Yht26TsKtabMX99q4esBN89HJCLFJTDpYsud5+k5LmkvxJhhMtXP7jHbreBYzRJ5vLRW/eRWPpdn14laHcCrJKUNmd9Y5ck03gdgdKaJKnxhaAbwEqjRXZSICKX2Xzptju11mA8TWhELtk8JXA96lJitUVIjfQEgTQYK1hULk5peKItvgLXCiqtaTguRggqai70A85sr/PW+/cJpSIpl6G2kSugttRSUhuLEs6S6mgr/FCytrrGeH+A6zjkZonMRVjC0CHLShwhUdagXIVAE4Y+aWYAB2mhrJalrerZaOFCaJTQNFwXR/nsH0xpRg6Xzve5d/cQz5e88clXOHhyyPHRhOGi5t0fPcLakMGkRAnL9paP7yjiogbpIZH4PlSVBKkZnJR4+Fx9/hyL23fYbTaxZcWsjHmwt8csjrgQtGhutNhLphyWOXY0w8YVrYsrKJmx1W0ghKHUFiU1qc6Y5TCJczY6HpvtdYppxuHxmPZqg75scv/wgFmcEIU+ylHoWuOoJerYWoNSDoGncJ0KUWjSuKbTauIucg72J1QF7JztEcuccexRmjnTWjLIavQPFEkquHb/R/z8Z38SpzxGjVOsDdjcWOXOrQlRFKGUR2kEi7ImFBrX93AbHc792/8V4Y++wSsf/Q988M51kjLl3tGchpD4W5ts726S2pq3vvUWl668ymdefYNrJ8dkccwbr7/G9tkNTDGhzjKkE+IKhe10scUCshyhDU7Yx/gRptPH6fdo6hxdSaRcOoCV30ZdeIn61PPI7/4K5ZOHEG3j7l7i7L/1t3j47h/TfJoQ7pzG2XyZxs5bnJ7P8cZgjUuaCjbXA9a6EbdvnRB6HouqWjYaT3I64dJRejy3dFouzahHlkrSdEySVgSuohIWYzW+8um3QtJshpQeeZLh+iF+6OCFkCYxumb5+YQh128N2Vo/Tfuy4RNRwPFsjx99tOD1F8/R6zX44qsR79wccO9gynRa4Tk5nc6SV7NzuYNAcHZzg+efc/mdr939M3XzXwuHZV1ZZomlmCQwF/R3muyuGnQ8J204FFVGuqhoeQH7exPOnffoq5Cq1ECF6hoWBylR1EKXy27tzHcZxkd4jTZNV9L0AJuTCnhvXhL6Hg+TmLuzE8glOhf4psJxHKbzhNRVzFNDGLgcDTM+2hjzE+e2CcoWlVOz0uvxyc2AvufjBi3+5GDMwX6OqzW+4+FKCRi+cf2A5073eONcn0lSsshqzrQDbh5lbEQOh9OUQSzZ8jWGmpfPbDMtKuJZTPYoweu6tEOf4FSHh3HG9VtHRJ6Ho3LitKawCkcnCEdAxvLYpw2VERhtafqatcBDyxrPCDYinwfDgsqVzKslEAxTYaREYAmky+F8QZJrOoFHEAgGyiCVxRGWbGGpS5CuoKZGSPnPp0hGwwnGAhaEtVgsNYKyAiuWM+PGaCQG15WEUcCiSKnrispIbLGc+ZeqxhgotURKhS0c4iLHKMFJYmgdZ3TWu8SzlP/pt96mrGs+/8Zz3Lz+GO1oZFXSbBpms4rF3EWqZXiHkYZGEBCFBqE9Kp2itUdeZjw9HhKFEaNZTC0kpzd69JoOcZbxZJ6y5tUUWcoLvQ3kxS6PDo8oJBzOzDL1yEha3QYpDuNkxpPjEUGzzXE+pWcljq/wAh8pNKHnLt2mKKRUGCOQUiEFKGmw0gUjUEKhbYm1FQKB0TVlWWCtg6MscV4wChTSrcmFs4RETQNqNaXTXCWZpNx8dMCX3vgyw6/+LlltKIqSoBEQTxcUWpBUNUlpaCiFOnWa4uADkm/+Jp71WOn2mWZz8iLjR08m7KyEdMdz1tZafHTrOuODOfHiBs+/cJHV88/z9Mn79Fo91q6+TCULVi5+Atf30Z6D1FPs4YTm2jqiv4l87lXorGNVA3npdcS5AjGfo9I5lAV10IfdS8i9tzEnTzB5STK9w/jO++TBGc6/9BLeT19A7pyiTI6QuWHlpZdJ37vFZHSIlIIKyfBggNU+lSmYxjmuCnFUxfhkjLESI1dJ6dJwDVEUk2tBq2yirCHyPV5/dZ13P3jAk0NBIMEqB+EHNNsh2uTULHsWjaZPks15dLhga73Nwo0JbYs6K7lxb0Aah2AK7j5aopZP7bR49aUtjo6G3LgzZm/o0t112d3ocvF0k04rYHCy+LG6+a+FeGtrMT6otsudh1OKJKOHotOOODheYCNBU/nUpualS1uQSDZWuhzNZjydlISmxO03WNcRC6eg4YeM0wndjYiiCBiMS86t+9ydVfzEpR7vP4x5NEkx1kUauXR2iRrpKZQV7GyHlLVABg59T3J4YtBlCXOLdipKQj4cPuLJvOQ37x1xsJgSI5c8bmOophUroSJquKSl5d7jE/7iKxtkVvFoXDCYTsARHCSGtRUHLPh9lyhs8oPrh9wXAy5s9fC9AD+16DplL57x7pM5Xl3htB18KZESpLZkhcW1krisUbXGbwhOr4XsD1Laro8rCgxLhG1ta6SBtLI4UtJrBzSbPWbjCbXVaLEcHTzJEnxAZILQQmYU07xGKQdjaoyWeL7E9QUCSZ4LsqpGKYsVlhqJrwS+IyjyGuUIaltjrCLPalxXYKlALG3DRWVwPJb1dAGestQ1zFKL7xgcC0Yso+6SSiPSmFootLB4ns877z4grzVSWhQlbePj4nF4FKOEwNQVyvewdUnDa9Dr+xyfGFwCpKlZzDSB64HMSGtNoxHRbCmiqSYIJGlScDhdEOuKtqdY3eoTBRG3bg+IjxboyEGHlkGdoTPB4WjKZ158nu/dnNJ1Sx7tJ/SjANsoya3m/Kltbt57QrfZIE8zagu1tnhugDUGYw1lVRP6PmHoU5QTtHZpt5oIlRESkNeQu5Ku4xOXGelUE6cZ3a0QXVdEoeTmnWtc2F2nvX2B44+fcPD0IblRlLrGd6HKFbM4wReK3skQYRLK+ZDxImV2MuT24wVNR4GNeX4rpMhSjGsYHU05XhgW1QH/9Le/yr/xC1/m8suS/s5Z9LkLiMfXcXZ3EbJCjEaowQBVVcwWMUFW4ucpTqOFevlnMWc+h5mPYNuDoIO2BmXBuB5i9oeYWlKUFeMM2t0+x/v7HB2f48yLgvEf/EOsaBG88llG3/oKHeNQdyJqUopMMUpi1tZ9pPVYaUus9hHky++kdVnfbdPcaHH/3g0yafGdgFqPkU5AkRV8PDokNx71zHBpp4eRmsjzaLouidY4KAppaQYNZBjz4HHKzoaPrSwLNWZuFFv9Lm88v4qxKZWBwTihGC5wcDmzs7U8nfqS117us9p2yHXG96895dHjf0Wjgv9/XsKRjBcar06JpaYuoGrAQmYEskE6nNBf8QgbKVtrO2R1xmJUkVmN1/ARpSYKIoQrSeKKp+MJ958mzFNLqmfsJSWNTkCvUXLnuOL+cYGUEmULaulglcZ1FZe7PkoaLp/pMjjOqbOcKND0g4BT/T4DV9KoUqaDOXfjOTcepTwdx+TWxRMlVimscnB0xaQwDNMEYxVSKT54PGcea57RwlntSUQNoSvo+BGdhqHZkKRlxJODGUWdUtQnrHuKRNbIKKClBKtrDTp+SCOvyTAczQuMtiglcZTFcV2yuiY9SVBG0owkXuUinIpRppnkDgVgjUApgW9qGrpERC7T3AA1lA7KX5IUA99hNWjw5GhGW7lotQwOSJISiUNdLQ1AVoN6FlShpAULrrOsXQPLzki9jEcPpEQYyWxcIUqJLzXC0YStkNnU0m5IQgfGtaG2gtVuh9nwmKgREsc140nMatsnyTLyAhrB0iJeaoVUS+RvVdWEgSIuxDJNx3vG5xYh+6OC3Ap86WHTHOmFzOcxte8s0boODIsURhUbtkHU7nB3/ylauIy9ElVGvHfngMZqyKoX8canPsPe0VOOZlNE0yGzFfOjGdWL0A5BBRF5OqCuCk5H28zmB5x/7hUeHQwoa43yXPIkA6HIshwDtJtNpK0Jg4BFEuP7LtoI+s0WeWmI5xlaWfaKisNyvHQ+WUm44lJpS1UYgtBjEcd89ztf4/TODjGGg/sDVpoCLwixdYnWNUmSErstur5PXeUUtSWrSjwftIDcCMKiZlE5rK1vImWCVIJCa/LU8PGDhzR+70/44s99md6ZHuLgMfViQHrtbf5v6t7k57IjvdN7IuLM59z5m78vZ2aSLE5F1khNJbXUcrdt2TDQ3hkGDNj/gBdeGtVyCwYMd3vtlXc2WkC3DcmQZdgtqdSlLtXEYpHFSmYyyZy/8c73zBEnwotLeKdeV9/t3R0cvHhPxO/3PJEM0coSRhHB8RHJ02ecz05JVzmT668gsXSPv0dw/ycUxuF/5W1cXuGUj3jtO3Qn3yJY5WRJj/LsgkY7Pn7wKYvKR88/RpVzIjlkuHPEya/9Ab8/O+OPf3FKXTtM3XDzzj5O1BTrFts6yjqnP4xwvmA08ZiuPmG6HjCIoak0EBEQ0ksinp3N6EzMqBczTC0y1EyncPiVjGx8zPL0ky0KYOeARtdcXBgmWUZbG842a657Q6bzmsGkzydfnOGkoK0dsRfw+s2EpCfIqzVHez2O9mJ82fDjD59TtY7ZWjMv/h1AwiJgUVqGoUT3YzabFrOouXU9ZHq14OZRRGoVKWNm5zm+NvhZzGrWUqG5Ph5TvtjwNFojg5CsDXjvRsaHj664Whn20mibpxUJ9882uMBu6Xd4BEqBdQwzn7Xu+Pt3MgZGbWNPOuerB0f8fH6BaDWXTcVuYHEarmYt63XLtczjUdOShD6bjd5eMim7TXd4AXVjiTzFdK0ZxDF3xj5RYhgnAb98WGxN4IHHoC2I+yM+f3FJFklee3WIrQRZP0M3Hpd1i24XZKnHu6/s0l0WgKBsOxrjKNqWvvTopEYFgndePeTFiw3aNhzcnPDibAWqxvMDQq9BWIv2JZ7v2D8Ys8grpqcX+EqBcJi2w0pBZS0hHXvjPutNjXYanKWfeNRlTeAnaF0Th4qu6ZC+h6Qj8HyaxuBQyC/Rp77voQW0WoPZgqr8Lxngxgk2taAxjq4TCF9huhoFLFYzksRDKUsSC2ptOJtaTLc9e7fdNnNsrNhejAnwfJBNg7PbTK+QHVKC7jSuC7m6yrk+iXHWcTlbg7BI6aibDt/zaLUhGSTknmRuSs50R+MgKWOeTKdkgx7FQnNWnHKaL3n3rbu4p4Kn6xnzRUlkYn744UN+7b17/OzHn1Jby6qsCYuScTJB65CTgz2ePH9CmmZI5SGExOFwzuHs9svIdRYlJYN+nzKv8cOAS7dEKAjDiPmmYRBEbNY1WaAQymxxBkJgBURRzLrWPPz0OXEcEScZu6+/hs7PaVZXtKsVuq04nc6Jzp/SH3sIAUjF4U6fQKzohGM06SN6fWTos54uGe+OuVids9GCTdttiz7ljPUvz5l4Pt7+HgWWsgPP+Sh/H/fGm8TC4+jJFwg1QB3dxMV95Pf/DW2xIhY97OVLgqbBrmqE7lBf/Y8wb66Qjz7AfvaQ+y9y4oMxP3n2S/y9r+IvHTtBTvjZfcb/8D/gG7/zH/KnH/zP5GiiKKQ1G5JMkGUepjHE/ZQOS0vLg6c5w3GfttQoJenoeHF6irAe66bmsqgJpEesJK/cucXHH3+M6wIunkcEcsMw7QEt5xfn+PEWaaASKFpYLBzzYsnVRY5Qc7wwpakL7p0MuXbcZ9hPuf/Fc4wJiEPBrDhlemm5vpdx63pMcJHz/Pm/A0hYabc4UBfGLJY5xVWFNUCv5q2DHS5Pc8rxmjQ8ZNNYkrjj4uJqW12dbhh4AaWSLBvNQHcsXEdmBUfHfUySc+uox26sWa9D+k3DWiuerw07qc84EPxyJXj9hsexy9jfifnKaEgVC25nklUJd2/3yf2Yjz49599/95iTZMDtQcfgbswvPp/SVx5NpQl8hxIdnvIx2pJ322FmMOwPPL5+L2Qy8khFnywMyDcVz5aCzXzO7/3uNZz2uTFJyQLB0LSc59D0LV3c8fTBkm9/85ByXtA8XPNksaELJMZaStOhnMJTjigMqI1hIBwb5dGNIh6e5jw/a0gihRIVsZPEmaC0lvHukNPLS5YzTWUETnrcOQlZrAxnq4a2g6qtyUKFFppeGDC0FhP4yPGEJ2eXxKmPJzpC5bZNSrc1xQhPYa0jDCWeAk9aysZRdhJpLYm/Naa3dUcQ+nSmJgoERbstDCmp6EcOFXl4WDpr6JyHYbvhe0qibUfVOmCbLAhCn6bZtvA8IYiV2eJVTQtiK1ygs6SeD9aACqgt+FKjbUurPAIcj84WOA1pIkhExGXZcu34mPX8kjSJqdqGclVxNB7S6Ja/+eghttNEIuLW3h5nZzOW6w2hH5MQs2wgy0bUaKzneH52yt2be1xdzWl0g/I8jN6CyzpnCYOAcZYgRIcSgsYJkkmKMRVvvXKTjx89prECD4OnHDK026++KCGMmi2ALQmYrVbYWNEu1hzHY4IhPP3kE5Bim8Y5fheHIfIFg6yHKc5ZlBXOCo4nPXZ7ilwrDq8d0JqOD3/8M3wFw4Md9vsz9EJTGcWmLXny0QeE149o52d4x/sEnqIqG9JRivMEnr9De+9tvGyAtAndm99ALL9A6jVt0aL9knixwaYhuA5xekZ3+xQ1uAXRI1SSsnd4yPHtHi/+xZ/w//7tB7z37u/x7r/3mwykh+jvMDh+m9fuvsHi408JewmDsUfk+SzKGVEkqE1DkW8xDV4SoHXH/tGA1XRJqwWDnSFdqckbTRgGhM6A6/jBTz5Ca0kUaD58+IJKt1w/cBQN9PsD5vOctJ8yPy8Y7cWsyhKTe+hOMRkEzJc5B4MIYzRns0vuP9NMLwyek1w7jLhaa1QMD5+1VG1LVTuskP/WufkroUH7H/+H/+6733pnj6I1XMxrfM8nChW9QURDTtlZhgPBIM2olobRqI8LAp68KKikYZj5aOdB5+FaRy07ikozGMcc7PbYGVqOej2O44TrKuHvvX1I0LUcjH0iD5xyfOetPfyqZaR8jo4GBF7KatMwXxZEnSULFG8fDxlNYqb1DOxWEqx1TaQErREMM5/fefOAcpHzW7fGTKuWzjlOdj1+67UBd/cH7EYxmSfZywb0IgVhyK3diHdPRqTSMTrx2BsP2VyWtIFg4Ets6rh9OMaoBt8optOOUGpyrXg0XXMyGCECQYchMB6Xa8tsUbOoWwbDAS9Pc1ocvtoKlqXvYSxUGura8fZXdimKjqrSRGnMpKcwDggV0ln6UUTsB8yqCt8ThL7AGXCeopECzzqM3bZLdSfxPJ9QdvgCkJYgYAup8uS2BKQECkGsJJXp8KWkFzqkhECy5apog5QS6SuiUNK0ZruVWotUEmG3FqBACqwCTwgkIJSlcwJtLAjLIAuQusMBAZAqQeBL/FAyGQ/otAbh0d9NKZoCRYD0A4RQDPoxVVOxXBbc3g2ocsFwmPHx/SVKbZutXddRN5rBeMjpixnZcAyexvdqpIwo1yXDQUgnO4a9FG01vnREMuL1u3eZzme8uLwg9SI6DEYbAqHQOETnaJpq+wx8n9DzEUrRWUfoS6ZFThgnWK0RXkBv6FEVZnvnYDWbTYluBL00ZZpXlG2HqGe49QXF7CXPHj/ixdPPefzoAS+en2IKy/B4wpNHX1CXLQLL6WyFH/dYzOfM5hsupgsqHbK/kxDGCp0X7A8SyroljRNujVMiqwkOr9PMn1NVjsFgB+/aK7ijtxCTa4iDtxDHN7HRIWL5kO7iKbbK0UZTLlZI3eHFIYQKl/rInTt00hLahtGNW3B2xsEbX+fP//wH/OCH9ylnG65/9R3ia3340b/i9quv8/LslHO9QbqOTb7hclGiW2i0wgpHGiUkscQpwaaoKJc5gZTgS9brJU0jCKQiDT2Gg4yybMhCiScVvUGP2WIJKuByVvHsfMnVSrPZ1AyyCFMWbBqf/XHATs9npxfx2q0+b74xIks8JsMAbR2m9blzZ8iNGwmz5YrTK8uqbAjw6SceVzPLclP+ajss/9k//aPvvn07pasd63WH0obWtHR0jEYJ79zZxRQeI9sjlpKzqzXebkCrG64WFYNkQtY5bJKyrGuiyJIlCYNhTBR4CDpC6XEYxPjOZ6FXXNsZcTzMONyN6QeOTeHI1y27hymFDrlYzrl/NiOMNcfXD7miYG83pNtA1IvZC0YMx4paaV4b77DclHzt3R1evTbk+m7CsB/zyu0B62bNP/yNY946nDCwEaaQWAZOAAAgAElEQVTsCIOItswpG81kJ+DOzgi9EZTN9uths6l43tYo5fNats+qq+hUQJ0HXFyseXyxIetHrOqGjYamrOkPQuZ5yd44Y3cU8uSiwI9TXk5X1Now7gcMYkUQBuRlAyKgaQXroiX0fYYDhTXQti2jNCJJMk4vl7RaUreW1mhaoLEKowVSdvhdx2LTYjoPY7cDvdWOttXEUYRzgiDaWnRwPlVjcF/aRBrtkEpiOvdltd9hnNw2OA04tv+1uiONY5pSI9y2fSiVxBcCPxCkPmhjEBbiSKCUh3MtWSI52ZvQdtvNCSlphE8YKOJQbm021mO1qlEeBGHG5XmJ8n26DnYnCXEqqSsJieJqbrn/YsN0lrNaaxSaQc8njD3iJERJePR4RWk1VV4RqYjNssFZh8EQdAIjJV2liWLJ+eWS3fEeWeg4vVhhWo0fgnAKP/Ao2gYnwPMkTkIShRzv7+JMzWKVo8KQ88srTg6O6KSGtOP4eIwpYDrL6fcnmMbgSUXTtOSVRhqNrxvKvCQvay4WOZeLnEVRsyxKtBL4UvH8akGtfOq2ZNO0nC+3Eo2m0TgJtXbcPNpjMOozTBKSUDLqJwSB4vbJHlhBlGYE/Yxok+MfvQLv/BayXmE//zHKWPRgD7X4GDF5HfZ3iDZTfBwqSXCm2wYELEjjcLsTGB7i7x9y8Zd/RtsEvPIP/hGf/OAveX465+nVirNHTzgejegFNd1n9/nW177NrJV8+MEvWDQeSf8Wa11T5hsOhn2y0OGHIXWrqVY1PRFQVTVRL8J0IQaNcR5F1aC+VIzuH6YgLFXd0raO5bJmNtOUpWUUZdzcG9BLHB98tmB/NOat2yNevT7m7p0JB3sRwtbEYYAfe0yvKo52Mg5GHr3YBwfK92nzjv3dhCyW9HqSR0/Xv9rD+w//8B9/t+c7Oi04n61IBiHRMCGJFHd2M+pmxVCNcdLgPJ8/++AFH11d0FpL0wqEXrO7rwiSmH7ax4+3USqkwrYlsnYQebxczOmUIvA9jocxrjZMXMayqbgsNafLhkgK0q7js+WCtWt443AXz+/YD1JsbEjlmHa5QlQG3Vmu7UUoF/Pw2YKjyQAVSnaCiF7P43CnT+ZJej2fXJTkXrflT9DR8zO8FPzUY9Nq1lrz/PkFTgvMxpCmCbEnSAwEfsLFquLqYsnL6Zq263i5yak6ixUSjSVNAhZrjfAF/SjkIoe2rVmWjjAQHI5Crp2M6LA0nUYoyclOjyRS5BtNP4BCC6p2SyJ8fjqjayVpGFEVNV6gOBoOaXVBGPmsK80w8PCFoHUWawyVcTgh0E6QN1tesa8EUkiqxlG3UFcGpULKdnvO6NORRh510+JJgem2aRUlHVEASEkHKNMhhMRoS2ch8Dvkl7Jq63waB8qHXtrD9yGNFXVeMOr18FyL7zqEt0UnSCGRQuCUxEoP3VVMr9YomdLUDeMkZna2wfNjxn2FpuXqQmOQLJeGooUglox3M5qmhNriOsH5WYnwIO2HbPKSMPTYORwgjCETisbrEL6gyEsqo1A25NbxHk+fndOYljjysB3004Su1TgEoeeTJjGms4yGA3aGfSSO5WZN2otpbEPVChAeVdVxcbWiagVtaQk8Sds0BF5IlkRkgWK/n3J1MaW2gqp1bFpLqQW67ahdSb2csdjMePB8QScVnZWcTyuiQFJVFVkvpchLFLCzNyQOfG7dvMnhtWOOjg8ZJwrPWYJ4h+yd91BeCq//Nm72C9yHf4Y7e46yHmo8QP7wz6HOkbuv0qURTivCG7cQgxjyNRKHGp/A0Q4sriDyKU5PCbwJg7u3ya5+xk8fPmXc71OEkqZUHNw9Jrn7NSbf+nu8+Y1vkZy/4PnSMdhJmZ5fMvAyJsOYdVmxylsme4cYo2nbGueFpKnP+cUGPxKYRuNLReSHqE4iLNvmtGs52E2JfUsyEKwKgQorFrlhetXieSE3rwfMFiV11/L4fMbLi5K69kl6HpeLBVfTlkHPYekoS0uYBKSJz92bA5JYcXwwYGcn4QcfnP1qC4i7zjKvW0ZBgFIetbaUpt4SALuEmD4Gze5wlyDrOLrR5xf5jNWiJUojwiRBNR4iqWhrzaaQ1FWJCAJGUcft3j6zYsF00RLtdpSNInU5d1+9yeWDElt6pJnHvWGGqUpa0fHV60dUdUk4TmnbElMbqrxjbq/oAkdfOWpgcDzhi4sLlLQ8/uKcNN0jnPhknkdSw93d6zydPua9myc8rtdcxjUv58utab4NWFclpWtpKk12bcA611xcaM7mmpOdGJGUVGuDiDK+/bWb/MW/+RQrFfNlzbDv0098ni9ydnoeB4MRj682NLYjCTW6tfSikNjvkCienS0p6pYwDDC6I0kDrG7QnuPFrKFutxd/Z+WXuWKryWzA9f2YQoDGUbZbbZ0UPvGwh5guiWOPda54YfSWjqc8TOcAS1sbwnC7dQt/G8tr64Yw8DGmww9DQIDwUUJSOU3gKyIJgzDgMm8pW0doHa2xKKnQxjIeRVSbBotDWoPnCyQKhMALUkpTIyXU2tCpAKEbYtXhJYpWKza1JbBmu3lVfJn0yMFKhJOsaoOb1thakDtN5G2HfCcFnXDcvHeClA3GNDg66q7hzmt9usYglSHu9zna7dPIkmyQYoqGa8MJn52fgxdimprZ7JIguUuWejRsRSG+v33ucRCwNoaybVF5R206XvzwA1LfY39/RN120DmKTUnVOJLM48XTJVJJGtMgrCCOAtZlxWi4gzUFIulj45DeZMh0usL3tvcCKIcXSnDw4PSMtw8nzGwJwR6Lyzm+EozHfeqyIIsUVSDwfZ/heMD9Dz7CGcUrb9xhudjwlYM77B0dom7dAhEh33kf1p9hPvxr5GpBJ3z8KMFECs9v6Z58jor7iDvfQR7/NkY4HBX+6wvYLNGjEB78mPyDh8Tf/AZRtoMY9bHr59x+5S2+/u0Vy1Kz2bQsNxXp0TWePHrAs5cz3v6N3+E//c//S75RC/7Xf/m/YzdTitWK2WyBtQGHuynL2YLlxgAJTVux68cMxz553iKA0myT3E5YxknK3mhEEG7LfJtKMFt0DPsGrX0QjvEgIPItv3y8ADyaZ0uWa4+bxwnf/GrCZlVwOJiQvSJIU8l0saZzil6scKbB2ZyDnTFOt7gvERh/1+9XYvP+Z//0v//uN947Zr2uKLVjudEIC1+5O2RvJ6YvFUN/iNe1OE+xpEKXhuW6o+k0h5nHqmi5/2hNmAgWs5ZlURP0M0SnyXAMkhhhPNq2Y0NJGIecnV9xfr5C4GFMjWhblvOGV97IGNoQD4/5cs3LpibUgmEXY63P2WZN1xOEneOXL2Y8eDnHto5BlrGc5+z2I5LJgMv5HD+y7AYZnVA4FXG5WtPrR4xHKWfnOU0jwLZEKqDEoWpLogLKusapgP29hK+9cYMoyHh5tWCxKen3I8bDkGu7fQ76A0zTcuv2PvduH9BqR10ZIukIPQ9tNZnvMxmPWKw1J9d2OOp5XDu6hrYwm5VoXbGpDVhAQucEFoMXKu5eH+MFMF2UGFsixLZlOewH+ElGuSkRxtKJgNxohFJbcw8WoSSN6ciigFbrrXNRbf18vSTE2o7GWCoDxmx5KVJuWSi2k2xKzaoBGQRIq5AO6s4gnWXcSxG1Bk/hxJbIJzuomhaBwXYCq0LKxuC8CCe38HuNQMstNCzftCAC2moL2IqSkHVtcabDSccy34pileloypp5CVmoUJ7g1rUeT88u6KUZo4MhnhLgaoSTpEFIsV4TJiGhFCjdYJylXDXc2Jtwtpnh+45ROmI0HKJEx+n5ijAQhGFI4HsEvmJZWwLh6KcxAEXVMt4d8+TlcxZFQxSF+EIgImg7gS1b8tyi3PZs/vp+n3JTY6VidxJR1AZTOrJRH5qazjbEaYSnBHEvpZektGXLvaMjfu033icdJDx+9AhtJMJZdg/3kHIbJtg/PKA/SFmsFjS15vhonyqHu195lZ1f/y1mH/4l7YNPSTyFHByiH/6QsigAD394DRPB8m/+T+bnM9J0hDq5RicqRHmOEj5dMkAO9rGBh/v0h3zxi1/iiz7+wQSlFLJ1DO69x+F7v8WnP/8eq7MV54/nvHL9mHe++Rp/8sf/nOnT50Q7RxzKDV//9m+QjGM+v/8hm8IyHHjsjxNOz5bkecH5NP8yOaWZ7KVM55p+0sdax1du7nGy3+PevQNaM6duNX4Ugx/R1IresOP8rGbz5aKxKlvm8w7bSS6XmkAqXrs1YK/vEScB54sNWSzJdQUyJJEwHARkRtFaR6sbqgaGUvHXP7v81T42+aN/8o+/K1xDpSXWdVtzetPhh1DkJf1eyI1hRiYHuDjkLz85o0FTlw1ZEtBTHcM7I1ZaMJ9tmK1qhmnIclMQBh57kUcdBnz04Cn1oiEbh1zlBc8ebJhVliiCJAkodcvNOwn3rr3O42dXVGhmTYcTjjDz0HVDYHysLzkSY/Ainl5OaaQkS2Ok9NClIUVRrLYas7Z0zFYlF13DIt/gK58ISexFPFnOebbeEKiIyPoYYxlNJkzbEmdq4tSnrFuWq5L1quD05ZLRKGUw9DneSUiThFm54uT6AYEMObu4JIlCykZjnUeoJGXrmIyG6KZilCYIW3Jtb0hZV6zKgstFhRIKqzsmfR+lOgI/RFpJHDr6aYoKBNZsI3mtlRir2FSG82WO7jpC30d0HT3fI4wDStPih5KucbTGo3EWJRQJHpM0wZPbTXUbqu7wJASeR9VtaY5BkJJvakDS2Y449AiVwAlDgMB2llq3NF+WjZzy0dqgpEDYDpRFeh6dsaRJROw5PKHRnaXWHp306SUpfifRRcmgLxn1MmbTnA5LFAqCJAAp8azkxsmQg92Y6bom7yw39jPKKkcqSWcgz3MEAj/wyasKV0N/b4zyBK5u2R0mdFKzWjYE1uP63g5l21JXhkk85uRows9/8YCoNySUDl8q0jikqDXjQY9bR0ekkcSYGucgCn2U52OMIQp8VsucZV1ztHPIKEs5nS1xCHrjiNWioDENsnMc7R/y928dcLw74tWvfh3dGurNhlESc/v4hIPbt/j93/593n3/DdIwpqzWPHn8hLK1rBc52kiGvZQ0jsiGMc7BwcExaS9ms7jCC/f55ne+iX75S+7/4C8ROmY8TOnufQ1/3CeopgjdQaPhxhvkv/xritmSRjv6Rzfh/EOav/rn8NkvUNNHCNVCNoYoJAsiRBZRlJpnzy7JBgf4t99muD9CFS/54HsfEQawOq94/+t38ETBv/p/vsfjzx/Qeik7N27zzru/y3vvvY+1hsg33D99yWjS4+bJgJPRCK229wxJGLJaGPxQ8sr1CXV7BcayKlasixrpJfRGHl4As8slRWGYrxWlMZRFTSB8RsOEsqrIAo849nBex2K94ecPp/SiBCM7UgTGVgRWYVc166ImiyM6oVFS0lt2/NWD2a/2sYkQgryR1HXNOPNR0uCEx+nLmu4w5rho+ESfsn/Up9YRV+slzvMY9CV74wHzywb7bM3d0SFPSk3hKvZHI9qy4YvHF7x2EjM/X+CJGBcoLtc1iYadGwOsg2SQIJTCqxoeXzR8/PN/TRQ5BkcxjVQcqIBi3dDPhmymDca3XJQLTtuCzhfcOhhRFIbZWU4rDS/oCKmxXsfF5RI8WK0lcaLo7YQMogA8zduvXOMH91/y+eWGN6/vE2Op8wV+rIiDkDQNuVhoLqcrRmO49+Yx+aYiLzUrAno9jyyJaRvLqlyxyS2RV3LtYMh8kTNdgjEtF4uSNIJpnrM3DnB+Ri9d8+q1G9A85uX5hjiMcA6U77Fet1v5LobNumXQhwiLFwQUTUvbbrnfDsnaOSyaxEkSKXCNxjd221b0tsmK1Fp6ic+wF1HVNefdltYYOItQDk9uQUwI6DqB6xxSCKQSeNLDNB07g4R81dAoi1AKIT3q2qAdSNvhS4cXgmctzoIxDQqBtT7Nl4O9kzHWss2Fa8veTkIv83nyckHbGayUIODa3QOK9RW3ooTDXkb/2oBn53MO+yGT8YjhqIeWa7rSsajWdJ3k6qoiihR0PoGwFPkCmcaYuiOfFZjUsjQNy/NLfn38ComKeJpfsSxKXusfs7uTsti07B31wWhwjuNxn9Z0yK7jzvUDrl3b58NfPCZLe6yfPMN2DuEpXlyUOG251HN+/2uvU1QlRVMRWYUvfW7cHvHg4SnvvL7LW6+PGEkfszvi1976Ay7mG5yR7N084aO/+r/p9WMGOzd5sXzAaLxD0B8RdxXGwsV0QeBJjq+NsK7m5fMp145vkA0SWgzL+RVGWGLl0UqPzWqO831YPUbtv4V4f4I/O6OrC+jvMXn3fdKPHxHdeh03mFCf/ZRuMaUWDeF6RlRL1Pg2sr9L9vZbLJ+esT6dEcUpyeEuXmDQUvDtN+7yxdsTPucIfzimin0aKailQE165OEhf/qnf0xq4R/8o/+M/+q//m9YvviIn33/F3zvh3+LLK/Yfz1mfxYy7I0p9Zw09khChdHwzmtHnL1c8fnLYmt6kor+ZACN4/b1AZeLJaenG3qhx51XDskSx8OnV3R+zP4wYLWq2GwU48jn7rUeptuwE/RpO0GqA7y849iG2EHCQisq19C1LZvn+t86N381Nu8/+sPvpvFWXnDtKCZJApLakjoYHIS8cW9Ep30++3yGw3F5VeE5+Mr1PfxByHxT4GUBvaHhaNKnt5dgu4oAxeWs4PGqYVO3JEpisYRKcHM0ZjKJ2RQNulEkwuILn0cP1lhPYJzH5cbgxYKgVbxc5lzphkVbs9tPaWhwnkA5y+GgTzKI8CvDzb0hti/JdctxlrLXy8BskZ9du0WgWtHRSwY8f3rBy5kGJNeHGbZuOQ6HPDmdsakcbWnpnGMyGSKlx2pdYa3DSklrWoSQrFYlqA7bdfTSiCcv5ijfY2cn42pWoCtL27bcONhhpy95484ucSgIVYcSjpNr+4wGPZAdURqyLjqqSnKwP0b4ERdXa77+1deYr9svUyMC3RiGvZC2M7SdpUOyaTs8oBcF+J0jdJZJAMdZSOx5oBTnZc3Kwd5Acetwj3JdYboOZIRyAuVZnBII575sdyqE6TCeR+B3RCjaziKFQgiLkApPOgQCJSVxoJDeFnIVKh/rDMIIlB9hpELKbRpFWgdNzaZc0uBobcS6qIljyc3bI1JVMw62+OBAwJMvLsBPGA4VcZtz/3JJv+ej2ALFYi+g1ZY0CulHAfuHPY57EdpZpsuW+aygRrEoatJeymK94v1X30R7msViyTuvv8ViesrFvGDcHxBHijSOOdgZUNQdt0922d8bcXU5YzpdszsZ8ezsbGtmFx2X65aLvOMoifj85Qt2+j2ks5yvFngE3Ls+oupa6spxvRfQlgv0co7fFIyzMfvvf43n3/8L1tMzZoWiNx5wcLTP1fSCv/3ZJ7jO4HkedVXjIcn6AaZtkZ2hWC9J0ozOdVSrkns3ruEC0Os1TbFiZxwTXL3EbXK6669BeoA9fAcvDBBC4m82BK+/Tbd/g2Cwh0dL2BnywhDffguuH1N+9D3KZ1OWlUEbxdG9V4h3h5DPEFEERnPzzde5/9kjfBXSd4aoXROMDT/99ByRnaAi+MGP/prTX/yUH/zV3zAZ7vPmt9/gO7/7H/PGN7+DNZaHn0yZLmum+YYvnhRMBn06KkK/Y3ZlmOz7SKfQrUDrBq+LeO3eLqNexLXDId9695hru4o4NqSpx+VFg65bsixmk7e8cX2AUSX9LCK2PnbVUtQN0liaeYVtW2bFhrI2SCFxa8uPzv/utMmvxOatjSXwFDduphzuZ7S1It8sGMQRBZqPT0t6wsckIVdFye0bezz49AXzusKjYnc3xg88pFVESrDnCeapIkxCTnYjwjpizzN87e4x4U7GMl/w2dMl85WjwDE/mzEdKlzoE40FvfGIZlmg/I7JICPSgh1/QOt1FEVJvSmRk5h1URK08PhiyUEacmt/zK39IZ9fXnHebKvOm7xj0RjqLGA9X5JFA/zKbW3gSYA30Lx1MmbH9HniHE+XK7x+SOgsV9Ma52niWNEfjMirDcJBHA558vicS7nh5o0Rxngc7sbM5kt2d4YsVzWrVUM/zWgLj740qABODvdZNzWnz84YDYfQ5VTVKdev7/Pq3T2my5pFbtmcznn2ck7VtNR1xfd/+pDVqmZnGEBnaK2jbg2Rv62ke2JbEKqdY1UXTNKQ1PMwQvDFWiNpcb4iiGAch5RVzf2nz7GtQOJRGoOHZT+JWHYNthYEcYhzNcMsYlZXZEGf1tQkTqCdo3YCPEuoJNJuz+nzxhCGHr6w+AISESE6R7Fu8XshncuRncALE5QNCJKEykCn1+ztZRyfjIkzWJ4WVJXitFxwtN/DKcFsscYLFBkRIS2LK8Mg8zFNg1MhoYJBKFGiI/QkmZDY0HHl15Q6ZNLrkZeGa7t7lOWCH332Kd+4e5ufrp/z9MUFe/vHxKdr5puK8UGfXjZkPEg5mzak4x6zdU2ja9IwZGeY4X+ZsXeAlB2dhZUp0Y3jsrhgmPjsjcY8+uKKp5dzTKd5Pj/jydM+49f3UMZBNCY4uYltHLaeb+XdRUE+XyNMwfnLx+imodYNTa453htQFzm2qVktcg4ODui6mipfEoYhXuhztbakI8Xm4oK6tiyfPGHRlgxv+KS372G+978hxie462/SXX8XufeVrYDYrDDpAPWb/wUqP2d3eoZO+6j1lOn9j5jPLWVvQjw4pDfaQ2Y9XC3ozAZ/7x7Dw1d47/2H/OD7D/nBX8347V+/ybLNefTgEpl+SGE2oHr86OwzPv7RnH/9wcd88+0D9pMJx6++ze177/Df/k//CXpd8PnDFzz+7BM+f/yA5eYLrqY5cT+lqUp2dlLaesMwHOAFgvufv2QnDIlTwfn0AmOhrQxxIPnOO0PytiFJQ1TUY5J6DNuYTkp015Gbjl6UoaRgpld4SpD6IVZIijZnYet/69z8lRje0jmkk+SV4exizcnRiORWxDBQ1DLAtx5RYJk5n661DDLN/s09pHSIjcb2BcozCOMoLOActvNZbZbcfmXEW8Mj/E3NTpRQ1ZpxGKGUJT83VFaT7sSsq4J+T3FyI8ZuGry0JegPWRQV8xpiCf1hyqWDx1cFal2Qew67tOwfeMgooBAVF5VmN8i4thfxky8umDVzni9LIpuQpH2kJ9GtptqUYBOefnHJSTRiWl3iaNArQ7CXsGBNUTbkbUeadngqJ40jlANdl3Q6Z7wzYL0u8TzBR5/NyduOYZZAJ7A24Gqec1XWRKEgyjt8b8JipdnfP+GXnzxldzclixPaOkQF8PLlitWi5uRkwnyV0zQt0ouYrgy+cEDHq8eHmEenVL4jS306KaGzSGvZGwyYFxWj4z1WF+es2y3LO5UCP/awnUbpbSVeSgXSQ2hNFG8ZKUbXdFWHYyswHgx6BE6gbUvZ1gxiBbVEKENdd0iZoW1LJB1COCQ+gaeIQktrFFZr0kCwb0IKI8m9kKH0OJtusE7SKw0FFiV99Kbl40+eYpTCN5JQOnqZh5f0ubo6wwUCtKOMAg4OB1jdcno5p7WSNDEkkWS5WTAepBT5hmWrcZ5PmCaUxYrFYoPyfdIkZdNuqAv48SdP+OL5BTuD59w5GXPrYMLzaUFtLKt8ThQ6rK0wusV1gv54hzy3xKH/JUfGbi95neSkl/HunX0efP6ceS1oWsnZYk7cj5ku14xHfTblio+eveDXfvvbnHzjHaLjV3A12PKMwb2v0Zt+n589/JjJ/oj+0qM/OmA4TFiuoEIzna84ONjDSUnaC3hx9pIb14+RwkN6HlEqeXr+jHtvfJuDd7/O4w+fMXz/13j8F3+Cv1wSCEmXxRQffp/e6Rw1OkD1r+GcBw//JWpZweu/gxlfx2U7ONegH39Iudpwrn2WFxu+ee0t6G8z835vgFquMKlGyIa3vvIGf/K//B/k7OP13uPBp+eMB2NOJgnxzjE/v/8Jp1+sqMqGycRnWpxRNgt+/n/9BP2nKfOZ42S/x80br/Lut97iW+//ASbY5Zf3f8blsx/ys48+IpCS3X5MMoy4mp3yfObwTjxiYYldQxAmCClQsUemHbWKkEJibEPTQrm2DLMtXyiJfRAdpjFE+wOm0zVRFFOcz0l7If5eBiz+zrn5K3Fs8of/5A+/ezgQ7A4j8hpGPQ8/HYHycbYhSTy0sahEMOglFJsOZx1rq1GR42h3yE6WcLu/j+cElWvIW4vVljh0BEWBamC9rsF6dNOOJgi4iloy6aEzS9eFDFK4fjJkX2Tc2t2nWhQsyoZKQIOikaCCiGdXJbOpxfYkJ7f6XDsYI7Umv3KsNy1eoNCt5iBNOLgX4wTkdcu6rIiTmKuzGs/fSiVeXhbcuDEiiARahpz4KZ+cLrlzeJ2nz+c0eESx5bVbQ45HA5Qfsqo27ByMKFcFV8XWNn96WqBLQyAFOwc7XK4KVnmNEh6Wbenk+GiCE4qHnz9HEPz/LcSmEvRGAZNxii4LeqmgqQwOH+csvjQc76fsDmLaJsfzLeNeRC9RHO6OkJ3hcNRD6I5hGrEuSk7nJWGc4QMKwd3b11BAVxkMBiM6rJUYuyUJDsOIRChqp4g8QagEd092GCaCQZwgPMd+GnFVbmgJ6LoO6Qt84RNIS5xuo1rK95HCspg2HO5MKLRhoUsioRjgo7UlLzUKD2MdvcAD0zEvGjoR4Ps+OIMUiiLvWCwLjm5M6EcSz2h8z6OoCwoDMgwIfUXgBQwHIYNBTFu3lCvNBoXfi6k2a7IwYrmpKSrHpB/z8OFLQi8GHH4g6ITioNdjnAVcLTfoziNNPHwVMdkZoJCEvsXKAJzBU/D4/BIhPay1xFnKOM34vV9/m8cvXpKkAXt7IXjguu07p6QHTtN5He5swZ1bN2mWL1h/71+wefI5u+9+k51r1/nZ3/6ER6fPmJ0/ZwQu2mQAACAASURBVHf3mE++eMz5VUGWRuRFS162GAe+F5CmGUEAcbxFIIeB4PL8JfOrJa/evcOLq5KTr73JxYcfUG8cB2+9jS8M7YuHeHtvIF77Nvbq51jpYPmM5qMf4xbnIHLE2WcoA2DR1nJ2ugTX4/XffJe4W+PJAHf+nOb5I4LRHsgMZUqKly9Yae//Y+7NfqXZzvO+31o1V1dXd+/evedvf/P5zkge0hwkipJN0pIcO4OdAXIUGEHgAbkIECD/QHKRm1zlJkYCB04gO0gYW0icRBajRPAgaiAlncND8vCcbzjft+ehd89dc9VatXKxT4AgsCglRAK/QKGrVq9aC+jhQeF93+d5eOfd+zx7+SEbOyN2Dt/ihy8/4fLymN3ugI0eJKuS7XjI1jBC+C3PTyd8cjKnFwpuVmNOTj/m6cc/ROcLHt57ws/+2X+V1x49wr1eYuqWwe7tw+MiWdFkFmfXS3p2zEDaWKWm0RY7nT4HhxtUaYkwNkWucF2HfL1mfV1ghR5pktEWhoskBSWZNYo2acnWDZWU/Ogs+X+fNhFC+MBvAd6n83/VGPMfCiHuA98EhsB7wF8xxtRCCA/4O8CfAmbALxljjn/sHsawUg7lRc7OIGSdNIg6JfY1g9AitDxGux0mSY1Vaa50Qy5yBsLjnfubNKLFtgTJcgVGE3VCmrYmCIJbckwgKeqKSktm4xnnVwlKOrSy4OFmH7uQzK5W3L2zid1Iop7DUAZUfpeLdY4eBKQ3Jc20QkQOnpHM2hyn7nJ0NiMULW/4EfG+oIhqesZmfbxk6UeMj9eEkcdQg121TMZL+kHAItFk2ZLdzYDp7IoVFn6tWQc+87Lkdz86wXFdXF0zXysuLpck3ZpMafA7ZJVhmVtczVKuL2vefm0L1zXkmeLoZMmryzU7g5C2aFikFY435OhijlKaOwcjXBnw9NUVz89S4qilUimj7QFP3thkMq64cWp0XnK46fBor0uS5FSqwLcMP/PWA5bpgtYR+HFM5FhUOZi2IA5dslmOkAFNnfP4MEYZi34ET15/wtOnJ3zyaoIrHASC2hR4xqKqNcYyOEKCEDy4O6ITalx7wLudCJMvqdyWqyTleqm4N+xRtRVl1TLoeHiRQ1a25GVJk0o2Y583Hx3wm9/+kDhySY0irRUdzyPwfcpKoVpF4PloAa0ySMBpDa7l0TQaI1uULShUTadV9OMIJ3DohhHPTy95dHcflaeczlIc12M8XYBxqWtFx7eZT+Y0tWB00KOqFR3hk6xTBBarMmP/7iGXszMW6QQ3fBunXbPZ9/no5TXbvQdIS0CjGd19TNddkyaKLJ3yydEZddNiOTbYkixdsD88oNIF2hgWq5zBaIfiJuVgf4dlVmICi9cePKDMShaJi5Y2i+9/l9n5K3xnQHR9ioh6/Pxf/EV+5e/896xMQ1L8FpfXGXHcx6Gi07ntgDk5n+FYFrubAzaG2yjR4kmBsCS9ED54/7s8jCwWi5TJx0d07j4hmWoaCc7hZwk/W+P09mhFhfz491BVD/GVX0CdH3Hzve9gfvh9pOwx+urPYnZ2sNweeQOj+9t0ixz8mLoucVYJwWufQ3X3EaIm2HuTX/irf53pf/XfcXx0jtIWWbHif/3WrzFZOfzyv/XXmJ38A8pMoIRhI7TIkzXTiymhkvyln3mXtz8XczIZczZfYAd9Pvj4D/jBD474xs99lZ/6hS/z6PG/y82PPuY7v/8DLpMVQvS4nBcc9kP2kWRVSj90UFXGeG24eb4A6VDRoC2DNhmtK1imNbLQ1GWLdB0G3RDZ6NuOLlfjOj5a1z8Wm/8kaZMK+LoxJv3UiPi3hRDfAv4D4D81xnxTCPFfAH8V+M8/fV0YYx4JIf4y8J8Av/TjNjAI2qqidW2Or1OmK8m9ex0ONiIiHWC5Ls8u5uStQRW3biVf2ttkZxgz6EacJxPG84TYCmh1S2SHFFVBEAoWxlCtNV7j0R9EBH2Pu29vcnGVc3q8IEsNl5OETiAJew46M1yv5gR3HPxhSJsKbiZrmrTBERbVoqTjhBjbx2lq7mxvolaamd2ii5KqNXidjCRU3GQ3BLbP+ckaPwxQZUNbS+ywYBhvcby4ohd3ELKCRLA/iLhqBb3IJZ0rbFuzLFuK2uZHRwnDXYuuW7HtOJydLble1YwGEZ4l2R+NuJwmKKultTI2ui6H2z1eXU1xdEg6z3hVVLRa8Pj+PnZgqBtFVrSs0xRH9Png6Sd85q0Nnjx8ixdn38dywHUlkStptaJvB6yl4nw14X4YUgnDYrHi/GzGuhAEvsX1LKGsFZ7r0dQW93a3yIzD93/0guqDExaZAdHSDyWtkAzCDpZoqLSNG0iKpCLyXQaxxbuHHZJW0S1SPG2zzG28RrDfD3i0OeBkscARDZ994yHz8RUf3yzohS47B9t8Mr7k5OyIRjRU0qGtDMu8pXDyW2lOFIEtGacJfifCkTWGlqJuaLml55etZqPTJ52njEZdXN+gLMXKrHnw2ogiXyEjH68KWJcZk6zFEQ1R5NDd6LI4yXCcDtP1Aku6xJFL0LHZ3u8zH6cs05rZskTrhkWWMwwFTdkQ+lA1CtdxoK4odMNeHNHxFY44IF2nmEtwpI0joT/okVQ5L45OGSc5xrIYLxcY91blzjE2WZ7RKB+tJHtvv0PTKtpwi9XqBd52DN0eH/6DX6WzM+JrX/wM759ccHN9RVVoYldibLDsFs8R9OMIpRWNrjg9v6ZpWmzXYWMQE8cxjePx0aszhgcHPP3eexze3cff20KPT2mljfvOF2mjDWR5Q5kvMNdnWOXPEv/MX6et/0uq64Lo9bfwD/ZJpnMuF2OuJwlv/9QIe+Ai+hvIqEsz2EVIFykBDTpbEA9G3D0YcX55jR/FJJMOn3895ubyjJPv/31Cu6ATuszTjMnU5eH+Nm/c3WW1WpNaiucvX9GIAJ0KFuqEurHo9wI+ev4jjo8u6fckrao4Ob+5/X3373J/a8FqNudyWaOtGjXVdIchmXXLSr2z1ce1aygbfDoskgzZ17i2YGdvhB84rNI1tYJkLahcw/VNxrDf+cnA2xhjgP/Tg9759DDA14Ff/nT8V4D/6FPw/lc+PQf4VeA/E0KIT9f5I0OKW2nEh/f6hF6A51eosqKyPS4ux0zXKaoR9IOA0BFsb0S0RYkfbSAan7QoSOQau3FQZY2vDMbvUM9SKiEQnmRZT/H8kLxUuEEXVS6ZZgVlo7n7YIenLxYMrACVFJzOzriuSqQXMb1a8MZOF9d3wWpJlxprINjb9Lkz6GLnJfP5mv5ml8m65OknYx5tDJicacx2TjIr8FOJlgX92EG6FhuDLsk8I7Thzs6IY6tkqRX5MsVyXA4eeJyfZ+Qz2BnAN776COHYOI5hcTRjMc3pRl0GvQ69vuBonPDidMJ8UTEI4UufPWSVC9ISpCq5mSuSUlOqlqvJU/r9gMB26HfDWwEjaqLIJfD6fPD9j5ktUxSGadLy/aMpfSmJA1iXDYHvYkUOXtuy2QpCKfGGETQtNg339zdJ8pRCFyTpgoWK8EUAXkNQN0jLZ7WqubvvMUm5ZWCWNaUWZLplqwOj2GLTGWEVE1pX8aM8ZSfq8tUnB0zzmk/OLrkuoRP5pKsCYXzu7m0zma04H8/oR136ocsgqsgyQ9o0t3KprU1ZGhxbUGiF7Tgkq+y2JU/YIFws26IVCoNkOc94/WGXeNNltarpDQZMFzOqusazHZaLNWVu8DsWdQHxwGe1TEjXNet1Q7eXYbTF3oZN0LmVApiuF0DDj05PeLQ/4vxqymQ+4+5oj8PtLbr9mLPLMfs7G9x78wHPvvcBD772eSwB/V4fR94aYISej2sbLq9XhNGAXhSR1yW0Dlne4Ho2py+WFE1NPOwxnymGkcs6OeJ7//SMva0ej//sN+h1tmiFom0T1teGR3fv8eVvfJ3//dd+nV//3e8hhflUxdFByQZUhSUEjiOpmxYjbSrjcHaTMX11Q20a1quKv3T3HufjS2SzZtxI2uQMro7ZvP8Oe7/4F9HXH5LMZxSzit2Pfg/ni/8y3T//79OrVyjfRdZrOsLQPlujyoRivkZd2FhXRzjRPuw+wQwiahQOAv3yI5If/DbheIJqukStRXfQkKUXfO3Lr3M6GWO0RdnU2MblZrXknSc7ZPUKE/hsdQL63Yg0L0mSBXHcZ7mqQBYcX70kXfp4botpW5paU6kK8Akii2mSc9VI+hsOSQKv2S5204CWLJIU12pppaDxFMpuuXN3wFYnIihKVmnFIOixSqY0rsG4Dt2HO1jNj7X+/ZMVLIUQFrepkUfA3wReAktjjPp0yjmw/+n5PnAGYIxRQogVt6mV6R+5gQEvAD80xFGHOssRgYUoHeaiprIMrucTuzY9G2wbxvM58ajPs5spRbvAthqswGN6DZenN9yNh3wyP+PgThe/7+K0BTuig9cGvEoX1KQ0SlGWNWWteHV8iT/0uFwXLFYtaIhawVom2K7NWarYDy1+9kGfRSK4zBP8vkaEFss0YyfsM5msuJrnXC0VVxc3uAK0sAmDkPPxko0efO4zh+RtRWlqrMDw6G7MVj9mmSs+vp5yf3uXhSm4MxqxGl8z2FjyuS/u0NQl60KQJCVXs4JoZ4PQs1nM5xxs7rOxWTEKtxnPMrSpKJuEm+sS33a5t9NhksJiNUdKsIRDvgATlAhL4HkObdvy1pN7OLbLMk1JilvGY6sbtHEoHYkVuDitoFE1J8sZHh7CD/C7MS+mCXpt6PcMRZPgCMHBvW0yKYkdTXtH4K0s6lqR1ArhKia5zSCS/PKf3uJv/sYZOrPZieDB7pAPno/Rls9jJyKtUtw7Q44XObvC5V7kUfhzUtfleprzwpzRGMH9vT7DQZejy5JOW7OYa8bL+ral0PMpyxJbgue6qKZGSEFrBE1jaI3ACIPtKIKORVMpAs+h1/XpdD2Oj2bYTowVZZxe5NCmBJbEdhxq1d4SeJISVRuSrObeXg/XEkwmNXEoeOeNIVdXV3SDgP1BD99JmJ/meAikDcu8ZJkqFukcy/I42OyTFTn9Xpe6zDk9HRN3XcbjG/KqJfACQtfFkgo/8PBDj7gXYtkWtndbpKxSw/69AQPH5XK2JOhsYGHRteHm+oJi/BL72XN+7pf/CtfPj9n58l+gF4R0wx6X0wsCz8NgyGpFqzRNragbhW5BCkjTHD/08CIXXVfMpxneMMJ2XDIfvvP73+HB629yk86Yr1ueyWv89JTJdU338DGdgWJ5fk7P2UK7Fvb8h1SmosgtnGbN5dU5rqX44R8+Z7JsQRi4dx+dXSKevYDOBvR3cE0AKKx3/kUG+2/xp97/J8x+8BHFQjHwJY8e7LNWGRaaqzyF2ufR/ojXDzVeMScPLZJVirBdbNfCCM2D+wc8O7omSWtAoSooq5KqcNC6Jc9T4o0OeZowHqeUlsPNquQyqfnC3T6TRYLtuQRbMaUqwLYIhcTR0FoOjdaUkwUGSI2ALGM/CCjtlMJV+LZDKdUfCZl/YvD+1P39XSFEH/gfgdf/JPf9uBBC/A3gbwBYFlRKMF9qvOsFLuAHIZfrlP4wwJYWTiTpWDAIfEbdHtKqqMuGqLVpywi7TJGWIuoK7HtbPD2+ZvPhJq5nE6YObiMp25bOHdCqhUKyt+/iP/TwHRvhRbz3bIwUEl/leK6H34P7G0PUOsPudRBOxjRVGBPwxb27VLGizGucXo+1ltRuF5ErNrcdqqRlb+CQGxs3b4gfDYiDiMXNku2tHsYK+KRsWNiaPEnp73Z5y7cxLfiWT13O2NoNKbVCtAbtaHquS1HZDDsRq3VC2DT4sUullqxKQyMtBnsBdeHgex3u3VmypyzeffSQv/vrv4dvQJlbB5SkaRhuROR1Q5o3zNYpp2erW7syfdsT3WqDEi1J3lJaGk1OWdXs9HymdcFBDKiau3HEOCu5nufUOmSyrBh2AxZXa5aVoDKKQezxxqHLX/jZB/zXf+9Dtg92uFlrzqdzvvmdCXZtUWuDN/DY3okJQphMChK1Ymdzh1md8p2n13xxa8Cm9BjuDRmM5zR9B6/rYleas/M588KiKA17gw6OLXlnZ4NaVVwkCbUQjDb6jCcLXMelVA2t0iBu/UZ1q5GtTZpoWiXwA4OuGqqiYnu7w9XNivk0unXpsTwc3VJka5zQJ0kUru1QK4Pn+pRKMZ2l6NZFi5LnJwv6sYcfuKzXc3pty2vbAa5jiAOf9XJKpe+yzGu2NmK2+yHHNzOqmznbwx5et0tDzWy+ZJXW2JbEGI20bZZZyjipuL48oWwF9WJJrW61ShotsG3YHg4YdHyiTkTRerj9PYYdQZNmTF+ckGZzTv7JP6Qb7jG4/5j+3t5tOlNYLLMKqVua5vazMhh8S+C7HtJIhDKgNaFnE8UW83VOPwqpTcn7z47YiwOKIufpacEb99/h4M4edauIOzHDrT0sEeH1NhGjx8iz77L4zf+BdF6Ss8Hw7T1eHZ9Siw1W02P+t//2ir3D+7zzpZ9C7j8AU6PrS8zxSzh4C7mxR/CVP89hlnF18YoSw7RYUeCgQoPXhDzZHLIfC1b1mmXZkGctcdRjvkqI4+CWIHg1RdctO8M+uzsDtG755Nk103GFwaWsFH0hEfKWrNYLbg1fet2AaGRTFR611Chd4pWKVlkYUdM4kOcNuQKVaJzNLrtdF8eCPE/xtYMd2MyLkiAMfiyG/j9qFTTGLIUQ/xj4aaAvhLA/ffo+AC4+nXYB3AHOhRA20OO2cPl/X+tvAX8LwPNsI2iIIpu60jQCenWJM5CEsUeR1XhWQzfw0LJm0sypEklgK6LeHVQ1ZRgPuMlmWJbAjgTDNzYY+B5lWnE6XlI5iu1On5uXa+ROhFUV7N3pM4oDotrmpJywu2eRTjWjcMBO5OE7La0yLCyPcrVm9/4AbVnsdCRrvaQtHG7Wc2wTMM4TPCLaWcmu7RB0HaKNmBuV8oXDQ47rhMtxgm4aOmrF47cOeI8Tlpm6pTCXOY93tsiblv1RgLCGbAwEcdcjazRZI6mSkrZtEb7iXq/H0dmMw507lEWCIzV5ZnCFpClTwkATdhx8Izi6mrMuFY3TohuNLx0OD3q0rSGvNXUtbjmhusXVDZZrsGyPtq2xpMC1HbRqqNsG2wEtNE7X58ObjMi2ETuarKgY9h18VxJ2euzux6R5SZvM+Hc+/wW+9d4Pmawdiveu6G0HHE9WLNKKjrA5flWxM5C8/bl9mjLj6YtzlLGIAsH1TcJlWTC50TglPB5ucbG8pCM7PNzbpq8b7NBjcrHgZlowKUoix8FWDtLYvLgZUypFi48vagY9h8Va0CIQGmzLoqnVrdqgZYNuiTwP2bVoQ8ASVI0mDB2GW12WmWJ7e0CzWBL5NtLyqLShY9l0Q4+b+YLN7QHLtMEIl27HwvZtRr2Igy2XxfmSQRwx2h/wcn7NbJpyd9jBaMlsOcX1PMaLOUpVNGXJsiyJOz6Xl2Miv6UxBtexkaKlbCpqbDpRwNXJAt/1iayAzl6HulI0mcLzJWVVI20XXdt0u30cp8VyY4ZvP2Z/sEGtGrx2QGCFnL/6hGK9Jh6O8D0PzxJoAQ2gWnC8W6ckaMmLEqVb7LwmiCI83yYMLC6vW9azNcoXZE1KYMGd/V2evXzF0+NTLi/OeXie8vV/7SuosE87bRDdHtrWiOUVblXQcTwe/5k/w8fjj1gnGVvbO+RZSp2s2Lx/H2e0h65uMDeniOdPqWYpUTBgdvQt9CylrBI2NgdIV5PVBfPlir4b8faoy2aoWNoWaxMwtwTFumSxnNKLI3StUHXF1saQu/sd2raiaQpUVdLrSI6LFY2yiaMQpSAIXSxp040d3ny0gXArSq2I3JikmJLOKxaLnD07xNsMcIUiWGmaRt/60wYF8zpBhi5OC1WuqC3J0JFkVfWTgbcQYgQ0nwJ3APw8t0XIfwz869x2nPzbwP/06S3/86fXv/fp+//oj8t3WxLeeBizOXBBSE4vV0Sex962JGhdFnXFqBdSY2gsjWOBHTvYjc3TmyuavMFZNtSqxN/0CByXfn/I/GZB3mr294YEUmP7Adutxaqy8DoWm77HUEjOrhP8LZ/Hmy46FHRaybqoyIGNfshM3XAv3ECnimTHYjPwqNYlHSWw/C75zZpBJ6bMFDLyoGix+i5HiwWuEVz3Feu6vfVZbGr6g5h1MeftxzGjqMcfji8RdYerVUuxyglcSRgNmM7HjEZd5q8u0K1HpxMiLIft4ZA8mXG4I9DrGd3BAN/xyKsFs+mK7WGHQadPnszRBEwbKEvBfj/GEg1f/tIjTj455/llgiUkUtRoAbaRtNIj8gWh3bJoWiQOrVZYloTa4HdctDA0uiWIHPa2u4xXOZHnY6mGuk7o7g8Rdstgc5N1kvEb3/6Am7pGtR5tXaMcGEYtOzsdAgTjWcMyaTg+uiTsB6ySmo7VklQeHdXBah2UXvLu/SF3ujaduEeyarlazrF6MW3VcDNLiaMQ31bM65Lpekm0EWNJgW/5TKucRw93SddrwEE1EqnBlxqDxvI8qqrGcm0cr2W00+ejkzG1DLCEotPxcaRDnRdou2U46EBesq4UZSsRuqXruHibXRxbYwKDGEDc8Xi8NeLze3foCKi3h+Tpmouza2ZNRtT12YsCnh8tmHk5FgqpalrhsDvocfzhC7a2+5zeFPzCN97l5SdnlLpBmVv9800/xL3R3I036XRtPvP5Q5wITp9eUNDlw9NzqkpjOjnrMuWNh/dxbMPHH37A8vQ59+7eYXe0xdGH7/PZb/wib45+hsn5BVKC140BQdNqpLhlvjqujY2gLiqELcGyyGtNW5TYCLzcIKXDOl8xW8CqrFncBIgWlrOMzbhHleQ0TUk2rem//i4yayDyIblEzWr6b32VyotRHY+OAdcLcGRAr7vF6F7ExoMRui2oP36GuDnGjnYJ/tzP0YYenaP38N7+HI+ya777/h9iQpuOkqSTOdv3hyyqnEy1eP1NTq6Oqar2tsZmuxRliW49om4XjMC2DVnWYLRLNk9wBTi2oS4NruWQlw1Rx8aY2/92Wre4okXVLWEscYyHXFeEWwPqrKBNC8qVYrUs0d2Ycs9GWQ150uLkGj9QaAMy6jBwJeZy9ZOBN7AL/MqneW8J/D1jzK8JIT4CvimE+I+B7wF/+9P5fxv4u0KIT4A58Jf/uA1sSzAY+ERhi2O39B4PCRwLTxgiV7P1YIRyClTR4Lld5o1imWegNfNlQ5UL6rKks+EQrFsONyxWywQvCCiSjPliBb7F/HpBZ7SJ3XVwnYj5ZEHhWyQdGOBz6PjUIcSNovf4Hn/46ohWNTx8uIsqS/p0KWeKD6tzDnYjPKVp6paeCGhcieV5bHVsFkcr5nlJU2i6G33ee/oSt2wpU0EY+axWOWey5P52zKbr8+6bd3n+yTXLFayzlFfHNY9f77Fa5rRaMOrF5E3OepkyvpmjdYVVw/6gQ2p5vHd0xcAP2d50+dLnv4xuF1zcXGFHAQ4B9eWUJ9t9rKDGcTx++KOXbGyGdAcepmgpa0PkR9RZTkrN55484dG9XX7jd37IdJ6QpxWBL+lFEW+9+YAinSKM4eFuh27P5w9/cEHQNYwG93j2/BNqpbgZXxP3G6K65Uq1rLSgWmekpmVzexdPSi6XU+rAY5GXFLXEyjXzvOCnv/g6nir54dmU54slnwmHPDjcYsuVzOZLlrLiWCoevX2HH768oVhobG2IA0ljW+QzqFSLyXOE3bLKFQPfolmviEYxcZuzWNdEnsQxNutSU+kaYQS2EehGcX22RtYOG4cOw00PNwRBy3AYMU9LKssgm5a4GxDbHhSKIICmaMlyRbcfEYY2nmUTBC3L8YzcltAqsrzEdTw6bcMoDji9vgLHJclmbMYdagPrqsQqLay2ZT6xyfOSl0djhGXxzoN9mqLk4+NXzJcL3jh4jUEsWc0rdvp9Pjn5Pot1w3denbBuDIMoZLMTYlSGaMByPZIkxVqvMMmCzue/yv79d8ivlmy8/SZvP7jLs/d/B1sopBRIIfBsC5oWdEvLrX9mUVUYIXAcCwS0QnIzTQmCEF0ZkryhbuGmyjifLhiNdjjYu8/BRszu/ibJ8grH26X/+AnGC0D26XzjlzCyxW81Tr7k46fvUcuGWtSsqoYeDuvJmPNXx+w8eJP45/8a4GHsAn3+IY63Cw/eRDydUpc5Dzb2uDg6YVE2vJpdsDPcBjdEZQ0b8YBGGCzHplglaCVvtXSaBiNulSebymAbiygK0DT0YpvZvCGpajq2oKwktuPi+A5lXbERhUhZUzUlPpJ+p8uLZMWMhu1wQJatMX2X08spu36XMBfYFsSWxDEueaiZ3kypkAjj/GTgbYz5AfC5f8b4K+BL/4zxEvg3/rh1/69hObfWTt3ukMhv6fgOnmgIOgOyfI5NTWtApS3Gq9HS0DaG3XsHCHfJfJ6j1xpvELK4TNnySrxeh7wFk2pEbZO0ijf2N0mEB+S4E5dyWdDb7nHY9VilGSgJfsS3L55x10/xLUikJFtnvL4x4oPFlE3HxlceRoNwHNR6TR0ExFFAscjxmgq761FdJWQdm2SdYdeSeHfA+mxFVmZ4GyFqJbgTS14lcxJqvJ5gw3V4/bWHrJOCs+sJ86ygQeE7NsYWDAc+y7nF2XhFs0ixHnRJZoKrmzUyahn2A65vTlAqRUoLaXyEsDGOQQY1vnQZDLpMSTi/UJxNCpRtI9oW2azRSEIBjiP4re9+j9ViSV232H5I07ZczNZ0X53w5O4G49kEy4uRVofPvfkOqp1wdLYi7Do4ns/ewYjZZAmWhXRa/FaSaUGqNK8PelzcTEhqxeFmh9CHMm2xCMjLlJOjK/69f/PP8fK/+RamNcxXBb7R5KpkLBw47JBVmnGyRGtNlpZE3YBWarRSjFwHYUlU1dJog+O2dC2PnuNyOU5AQ1MZZxeLxAAAIABJREFUtONQVSXasnGAtq1RxlA0PlVREW9IBhsuWa5BOGAMy0WO59uopkZ2QqLAY7lIkQq0tqiNYGN7xHy+xpYGJSss3eKaFsfzEEApIbYlgYhQ84Zl1pCVmt3NIWWhcNBsD/rYGGxpY7WaPK1A1/zcl97A6WwRhiHvfPYBRxeXvHpxwXsfHBOJiLc//4TimcvJ9ZS6NjhCkCwTNoYejiU4PT6n7nfo9keUqzV+0KFpWl7/wltMLp9R5qfMz8bcvHqF9kLiIKCocnzHxTaCstE0qsVYEtfxMdKABUYbjFS4TojUmixrUAiaRiOkJDMtPTT9jU3uPz4gjjUXH7xP+uoVtvQIe6eUR0e4b/80cu8R0rJodULresSdgNn8iucvInzbkJ5nbLkR7tYBWuQIy0avU9zZEvXuT9EKF0s3/EvvvsFHl8+5bgwbcQ+jJK3SjOfXdP0I3RosW1LXFRLBKs2whYMnJbWukbaH47jYdUttwc0iYziMePrymqa1ODzY4tXLM6LebQrStzq0RQk0JGWF09roWmNZNjprqGNDaRsi6TPsGnb8Phc3FzjKx/JLNocuizTHbW3SdU2w9RO2Cv7/EY4tONgdYVPjSEGWmlvSTXpDpXOCu7tMXk4I1h5lXSF2DXHH5dXLY+J+h/4wxPUVxrREg5jrPEerCpUrtO1g9WxMY/h4ljD0CnB6XE7HfOGuZGS7oF2cvo+uNItqjtj0OLtO6NhQBjaB65LUGfdD9/bLFDZZWmOQPIwGBP0+dZWz6fWxWHHSrHHjDr4pmKcFVW6ws5IgctjvD3m43+f6ekKWa1Y1TLMSueXjBQ2qkqyrmhfHC8bTnIOtLvfvuBxu9VjngngUs8obisCisBR7W7u8i6RcLAmjPp7vks9tFmmGa1fM15rHD+/z8vkps1XB+OUlvY2I7T2bg70dnp1OGAzu8PTlBUIaXNvi+8/OeLLf43C7z6uLGWGvT7IsiToxk/kEYc3YGXQoMoXSU3xnh9lqRX8z4N5r25RNRpkVvPXkkKZOeKAMJ0crWstQJD4XkyUn1wmrvCFbzzC2xI8FZV3RCsl0nnH68Ud86fEO4yKn0i1pssb3O3S3XPAMlTQUjUVRKGaLDNfz0KphA4kThsyokVWLjcV9z2aiNZd5TqUMvW6IyVIKbLRlcIGNjkN/s888qcjymvtvDPCchqJoaJoGpWv2trfIswxd1QxHXa5mGaHlY7sCrUD6HqJS2FmF3TRIXxJvDZCuj+cF+IMuyTJBOAHGq5knGUEn5GvvvM7zT67R2iC1AM2t/K0fUFUlwgi+8pXPcrA7pEiuSYxEOj0ub875+//oQ373d16RlyX/wpff4f3vvk9g24ShDcv21ole2ozHK8IQRLOgFwQY6TA4eMybb95Ba8lysWR1fom4WqFkTRz3aLyATuQTaAOVwnVshLBRlkFjbtMmtNRNicDDcg1FXhJYFo4TUucJ0nIQbUud5dRByPHLEw6HEXujDeyyJu7GuAbM5gj54hnlB9+lO9inaRaoP/gubgE3TUE/jPEth9B1uXewy3DvAPHGIyyjaJoxdpvDW18D28PmCqU0P7h4xofHS7q9LQK/wZUhnidIawvHiijrFa7tUKUJnTAi7nrosgLLRdclTmgTej5aN1ydZBQ4HOxvEkQzlssVmE0ODkZcXs9AONimg7EctFWRJjmhE6DaBlUr/Faidc6GH5DVLWFkobRh//4e88kcYTssFPjCQndcmhqC6sebMfxzAd7GQFpkNLZClyAag+u6zMYFm0PB4myK1ThcTWeMl4qebzHa7mJbLjQSWWp001AVGu24mNamrTVxt8e6SDGuIF21NKuMa6C1lzza6jD0dzhdJNCWjGyLbmdI3VTEXodY2Ti2ZJw0jN2cbtflUPdxlCRqWj4xUyq/Yb1osZbXNEKiVIMbeFS14eR8xpc+t0vZGMq0IfID4oOAlhbpOXRGMcLqEBQlge/TGEGVN+ShxfFJwiDscNHWtEiyGrKqRLkB56sSkzV8+ckTfv/7HzKzz7n7aIh1JySvDIvzIywnpigU3a6PJQxNk7K94zBdrylqwbbn0nMFB9suT+4+5p++d85m5KGE4Z2HHQ63RlwtapbpEt22bPcM9zZ8fvBiirBszk4XWE2F41h0QgfXHaPalp5T4gqbqijZjgM8r6LUQ3SzZHe7y8X5jGVSIHJFVTdIDQibumy4OwqJ7IaLsSYvG779g1P+9GcfUS5Lhhs2s6RlmpfEtmI9N+ztdLm6XLJOC7qbEd3Ao0pTYuEwrzVZrgktiWcUluPj2IJEGwSGi2WBkQ57cY/VKqGsNf3tkI2hx/l4iWpv5WUtCzzLZzFtePhgg804ROQuwhpwnVSsbmp6nsUqbXAsl6TMkaZmXip6Wy4uDk1Zg6UQUmLbAgDXdShMztk6Y9t3mK9XKNFgRE2/O8BqSoSqEbWNFBLbbjh5/hE7+1/FCft885v/C4N+h2ena/7hDy54ezTgG19/gqcUQls4vsdsnmCwEPJWd2YUx9i+hRc6+B2bV+dHXI3nfO61fd559y1m0zFvfOFrBBsxTZ6g0oJlmdDq38eTAuMArcEPfSzfpVbQ0FAmKaIWGLcljDqsxgu6kUtZ12hVI4XD/lYEdcLFBDYHm5RNh8W85vDLX8dzbdy33gBLYb78Rfj2H2Amz8m++5vYjcA92GeagD9SXI/HnPcitns7WIePcfwdjBVgq2NENkZHW1hIdLEi+eQPuF4JDg8PKcoU23Nw/ZZqnvL2zg55vmJj0GNVrbFcnygOadeK+eQ2d5/WObO1ohd7JFnK8dWUrZ0haZEx7IUstGI6S9je9pHC4FnQ6orLuaTflzhuRMGtPvh8nqAqh62mJXdLskpjWkG2LnF7LiKUjFcJvdqmMwqxHcl6lbPIf3KG5f/3YcAWFpFjsx2FNFXB7sGQ48tzZlcJo1GH2WTMdrSNbhOOjhLmaU3eSN64G90q0vW7lD3J9SSlqHKyRFEFBf3hgOWiARnSdWqeLh1e79V8Md4mm5RUlU1k5ZiNTU7blKt8yeu9DS5kRpKWZNpwfVOgUkPVa1CpzavFmNxpceYeW92QTeMgdE1ZaVpbsrvf4cWrBWdXK959ewfHCdHVmuFWj9PLGcdX19iWhdUxuL6gp3ySsiXue7y6zvjKZ99gsVoxTUqKRLEKarKeS1WmdJsuox2JKpckucXLZEbTs3h4dxM7cJmtW3Z7LlIq4kGE1VngSI9JPqZFow2cXSWYHYtDEdO0PoebPoc7Fp60qIyisgR3dne5/mBCv9fFtR16/YjNUU3TaDbv7eMIwzptkaZkd9Th4kowyxs8adFWLrOswnYNq/UCLFjOb01pR9isK8WwtVmKhqKpebjXpcwV87zm/t0NkrzlR1cJv/SNiG7QId5wmJYLkkRxNtXYvsNlk+DbBstyqbSh0AWbOxHrm5xMGTzHYdDz0NOM66ogK1ts38d2Db5jU5eKpszY6LtoofH9lrIoGA08sqKizBuEZ/A6mif3BoyiDtlszvZwl/F8zOXZEqkEN+cLnDhkYyOkG0ikauh6LuvVAtdzWZfVrVmybQG3UhBNmZG3Bft7O6BLkszQH4xYzHNmywm+kWxuDEBIfFti+za//d4zPlx+m7ce7fPw9dduzYf3Y4Yv5qyMQ5ot8O1NtvY2ef7qhtJIjFDYUqI1lEXBIAioVcKLm4asKmjLmj/4vd/FaRIsN8STHr1WI4qEtDbUrcKxJJ5rYXkSRYNjC2xX4Po2jZGYpqapwFgwnS+RCCzbxrMbHDvgwW6IqmtuSkk8EBxNzjmenvPkrZ+ie7iFGcQYP6ZVOeZyibX/Ok2wQXj3s0hpMez0+Po7u3zvZEKRZ3zG7TO6f4CIA7RrYdoCTl5A2mJtCZTlgX+HzN5CqWcYqbmeTgAf6bm8vreJdgoui4SDIEa1NTezCi0ErrRpWkGSGSplI31BbRSq7vDOG12CsGG+LPEci7jrUpaajTii3KgpKkM/MpQV5ElLp+tR6oayMujWwtaGrajD0qrwQ5t1VWO0YboosEObYaeLqTRV7lC1CZHj0e1tAad/JGz+cwHeQt72ji6TjLquyMuWWVMhPUl+YvHByYyDRwPef37G3oMeq5UmdnrYpmSxLjBGM7R9riY1VZKipOTu4218z8ZUgourNSdXOXc6Lvl8ztbWDot5wXW2YpkU/Nxn7zGpC2aLJaF2eTGbsaxrlGcz8G36qc/pVckn50v2+31k6GKlhukqIwwt7nV8tr0d8mXD95sJumoZbXdoPYvZMgWRsTWKWSwnaKURsoNuW56fj7mzs8XmYEDRrrBsl+2Bg6pzHt15i4tlyXCgmC8VtuwQRylvf3mPD19O+eD5JQLoxiF39raoa01RzHn86DFZMkEazXSZkCclUVxgOxFx0LDzZhfbrihXLec3S/4P6t6sV7fsvM575pyrX+vrm903p6lTfUOWSEoUQ0A2bSWGjDRw4FwlQJAgvyVB8guC3KUHoosEiCNRUWwpllwUyWIVq+rU6c/Z/f76ZvXNnLnYug1vYgf0/AkLC2Ou9Y7xPqPbFbzzyXd4/fwxjqtxKpcqafgXL35NFEiirkEIxbcvr/ng4ZgmT3B9D2F1+OLbS3Roc3Y5oRUNmdxes9issJWNEwRM53PyrMH3JWEUslnNmM3WCG2RFBohFErDYmNYxilhKDnxBbgWFwvNtNB0u/7dRmRg0S8MduAS+BWjnT6iqlktE5KkIY5rmgyKssEJPLTR4Cqw7pp/pOtR1iWPjrvMlwkrYxiftKnLlLK4i1DWTcOjkyGe45BVGWHo0uQVVA3ZNiHwNWeXFxD5fOfdMfEyZx6ntCKH6WTKxnGJAmi5iuPuAN8FjENWSKS4iyUqIRFNjWcHCM8j3+SkG0NZLxGNJFARroRKGxxH0Rm0aHV8Qsfm/PU5Pc/isO9R1hWRb/Hj99v88WcTPnzrHioQ3CzWPH7xikqDEgJhGixpkeUNepXS6dtMljEWFsaAVC7rq0uCqE/7g/dIXj9G24rW+B7ZMsOSEiU1ti1xUTjCwkhQnkOh7sw+K9SEjs3l8oJR1MZSATeF5r37Ifl2zcXNluFpDyUqSlI++8UzPn3vPlFLIyyJsl20FWB98PugS/T6FvPO7yK6HaLZK8qkJG1SfBRPLl7wu6uPaU8u0PIlyg1oBsfIoxNwhjiNoNYWraMP8YO/Ik0bBr1jirSgE7XYpjUvX1xzsNPh8YsXFLVENJKu1QEnp9N32axKwrBNt+dTmS0mKBh1umipaBqfulwTBh6OG9CL+oi9imevYmQDgTI0ymc4lCTZHSCtE7ZwRxbRWJGuDLlo6HouIRZlJyBJcyzXEBuF3zQc9sZMVxu21eY36uZvhXi7UvBhu8eqsTEtSbTISFPFuliTug2LWLF8PcMRim9erkgqmG1SygKgpMoSfKtFaSqSXLI3CBhZNaEfkGwy3hq12CwLNrnmqB/y5XTDcpNRY5jrhr+5mrPJcmRVc2/vgF9dXuF3JbtWRMeXqMMO8+c1t5nCThPsDbgtj6LSNNphdVNhWmuMlsi6Ia9qdrsGJ3BIUokSgs9+dsXevoMSNpPlmuPDIf1Ol3RbcllesXd4zK+/fMNuP+TZbMpH772NUymms4zZqsB2Y0aR5mJ7RWP7NALKpqTTdvCV4PHTBd1BxJOnE3SzZX93hBAG7QyJ4yVlWiFdQVlofOkSdQsmS4tXV1ecpJrVfIHvtNjfb+E4bU6P7hZ2lLTohg7H+wfMFzFKGDCG2WIGaN5c3PLwrUOubm7xbEGeZQgPknRJ0xiywqAcaEU2m9hCYKFtD6kbtnGO1DAnJbQd4k3D1aahNwj59KMTlsmSf/cPH/HTX79m841htNtmHWfcOxmT1YbVMqfMBQYLx/dANDiWg2ffgcg26wbbhpGlmKU1niXZrlOqSlA3kjTNiXyXuhJY0qbXtRn2DWEYUAmLyWxKXUkUNi/Pr+l3PWwRcXW2orvbxniKYbfDapqjS0XLczjoeXTQjB0HrSryGqTWeJ6LZSk8z2W9NqzTgqvNHAtD6Pvs7PQQjWQzawhsF8txUY5Nd9jDcgRh5DKWzl1LTh3iaEPSaDrtgHcOI6bTHLee8tVnExzXAdMgjAAhMNTUWqIkDMd9Xr8+57jfZ1IU7Lz1AZ/84D2q9QRLeTjdfUY7h+Bonjx7DEYgpYXrKBzLwrUcaBpcP2TTZORFgusG9NoBTrdPx3UoCw8n6KCLkvN5ivItknWBZ1kYS+N013zx5FvUZsDpj/roF4+xj96iCbqYRlK9+Yb500v2fvIPiVo+s03GZm14eM+ijCc8fX7BzkkfSYMZHyPcXRplgAxhKup6he3k3Exn1IXN28cP6HcNWbwmzTWdtk0uQVgSq5J0uh6z5RWO20IJB0NOp2sjZIFndQnGmmK7Zh1viYsAx3XpdSOK2sJoxen9MS+vEryogzFbtnnDbJmxWiWEoc9opFluC65mgjDwSaqK0PIJ8hqJxh23qU1GL3KIgogkywhGAWH1/zHn/f/H8SxJmEjO84K+aHj/+IB5oTGeZu5q8nrOeinvKGpS8+69PSaLLaKskXVFt99hXmXkWqKlpqUsyoVmnq7R25x1IUjSu/lb5kDPt3i6EpSy4GTP4dt1zmaeIQrDLL+kdi3Sy4xaNSwXDpWSFHlJGFkM2hYPeztc5ls+fb+PKQQX52vmtSLPSkwP9kY+nm5hqTaPz66QKiQuJJdLQbktEUZxzpRB10XZDnnSML++xLZtvn4+4Xi/w1fPvuX9e4/4b//ZTxkELZ6/uKU88Ol3Qo72uxRZyu3kCq8wpEnMW8dHfPn6AiMVybLA8muqoma9XjMc98iqhuUypW4qBu8eMJ1kzFYz7p+c0utavHN8n+Xa5atvnuF6M/p9j92dMUHQ4uWrV8SVYjwesd5smSQ1b25Sbq8W3D/sIquCVjsiTddYjctyU1NX5u6ZBT79ToQdaNrGYp3bLBYJUTvE60asVyXrTYlWEt00vHi5ZCcpOX4w5mox5eH4PnGm2e23WKU57bbLcp4SpxVlo8kqSKuKUjXYtqTX8XAdm3hWoJAIS2BbDWmhWBYl5wuNlBJjSaRl0wktOoHEth0ORyH9ns16kyAtMEIy2WQoUTE62WG7TZEmY2fYQjSaqN/i8vqG1aKkEQovUlQ0VKJhm22ohSapBX2/QxgEYAlKx4HCoB1BK4wodYmwbG7nU7p+RKM1VWnw3RFGG6LAoykLPNeiLwTrvMLUBdgOeZahbItP3+vxTz+fsVlXbHMILUOpoTY1lrDQuiJw7vL7eZ2AdJjOEiqheP7tN/zou+9i2R7ZOmZ4uocIHCbPn3Lv/n2sX/4ckZdYloPTuATRXb7dDzxMLalaFrkR7O+OeT1dsU7vDLqdbotX10uCrkOIhZEGY8CVDdPpNb/6qsWj/iHUGZuvPie8vcA+fQ/6O9g7x/D4imJyhd1/xL233uWLs58xWVWoKuXF+Wu+l7yP89YRruuD0BjjIvSWZvMlbDeY25cMopDUyXkzec0isjjZ6fPm5QWL2sLKChyp6YYO221KUjT4jsXRYEh/qFkkK87OFnz3408ZDUIO3n2Pye01j59NMYcRw17Ial0hbINveyhKchpcKQmloClLjkYRtmWzWhcUUiBtH9tyGAQeluUivQxVgOtZOKJF3ZQIlYMwtEIHW/xL3LD8V3WKoiZtVhzu9Xh+PiVbnKFDSbcXkV4v6AsQrs06LsgQZGXMW/cDyqSk02tjrJAkXeH6giYa8NXliiw29O2GH4/3+PVyQSMlRVFiKwhbHlZQc3Ebs7vfp2t7yFZJIh0qSsZdmyqpOBrs8CZZcLONWaQw6Et2Wi0e9EOsGo47bZ68vuL+aZez6yWZsHHihm4QIpqabVEz3zTUxQbX8nj9esnOyGUnclF2QBj1WG5j6qqmKBy+fPyampBGr7GUy48/jjhs73G5vmbYtlHizvk2Qv5tya7CGIub2zXbeMXNOqGoNQKL2a/OCXwHoeF6do7C5bsfHDGZL/jm+RtmC03kC3yrpO1G/PqbV0hRc3I6wODx6uUVv/j1NVHoAoraNPTbW4rK4vHzaxzPohPYOK6NNobteo3j+iRxjdESLQ3jgz5uWLE7dDifL3BdycP7XYoDwWKTcz1PcGRDuyWxhKSuFb2RTa/vUyY5803FyA9pZgUJFUYrVquMwhYYc9donlcape9ceikMHhqnLomkQiqbOE1JtSST0BhJp62IPItGG3a6Ia6q6HQD0nSL63Yoy4Yw9FlvY2xsfE/jhDaL5ZbxOKLMDctlTKfjMplMqHOBBiypifMCx3NJGsHFJMFpu/i+zdh17zjhlgAyoiCiG/modohQFsZIJAYpNJWfsVmndxeMaaibGm1qXMdHScPNaoXvHGNZhqzIqQGjawJPk2dQAwrAGCypwIAtoBO4uLZAFJK9bu+O2+4L5osrfvmXf84f/Sf/MZat2D5/RXn5c7IiJdw7RLoWsizQtaHTH/Jv/hs/xA0sZtsVf/PzX9JIRb7M6HYDBjjM3sR0Wh2uF9fYvoOTa7Kspq4NVSVofIdtUbC6fM03N484ne/S+e4PqS+fk339JcGnPwDtsPfRhxgazPySH//4d/jpn/w1k2nKaC/g9fU5F2cT3hkHmPmS5uQ+Fh20EajOp9CSzL49Z7GJ2ZYVWd7w8nrJZFHRbfno9ZJlaYEpSdsthBZEnkBaEi9QWFpyu0hotyOyLGYd18yXt5wcnhC1CqSlsaloB4r19YYdv0XgVVxcTtkbRNi6QlkGYQlmyzkit7HdEFyD7zsIWaCshtjccYVsNAO/TVLkGEsgHAic4C6+/BvOb4V4GyVYeNCxNSf3eijHJqlrFpuM5bpiU0BcC1INWkG8yXn3h108Z8RsVXB7u6QrGmzHRbRdOo7Nm+dLtBS8oeLVNsNoQ6fl0fYVjqtx2y5uZ4e2baHyEruxEY1hvdFQb3h70GdTxQyjDrezHOMoWl0b2xJM8w22hMUiZr8boiub/rhNVDgk9ZZlHhMpm7JaczAecHl5izGGB6djxoOG3V5ImkjyJCPPasq8Il7PiVNDqROSrcAPE86ml5wORyzrFaNxyGjUIo5XLDYzBjtjOqMEXeaE7R4ffvw2r19dkpYJ8/mGRaYpdEWcSR6OXCqt+PrpSz75ZAhvPAq75P23BhyfhNzcznl4vIvrj7ieTLmZXjHecfDbPi8v1myTgnZgc5XF2MpmHLl0Oz7zJGUVFwSBj3JcVssM23J59PYpm8U5B4Ek1Zp0usKpBK2tpt9v86JacpsVZKuGpLoDDu30XNKk5NGDAUmScvFmycJyma4yVFFguTalbIgcmzQtKGtwhcDDIB2bsmrItKEIQGhNXRfYrqHVD1knFZajaeKa+/d2sPUW3w8Y7YTESYzX8lAu1FKxTjOCUKJch1Ab5FDTGJfSsjGFoMrXIBqk5WI0rJdLlBD0Wy7KdRCuz/M3t2Sbmr7fMDwaYfkutuuQVSkAg/0hD0Yj9nd7RLsdvNDHCiKWmy1//mf/lDyzcX0Xbeq7mjWjUcLG9UFgKKsGIcCzbAo0hRGc7LY5f7XCeDamuisrMQoEAul4LPMMzxiGUcSDoz1eX72iaCDo7DBunWAmCya3X3Pyw38b8+F7rH72FxhPkheaqpQ4Vs3haMToYIBIFgx/9EOCkwN++j/9D9hlQ7cfcBbXhF6AF0qWVzVKCZJNgUZh2RbSFpRlge0qknzLr77+ince7fNhfw/n+C3cQmC2JVJJmuEQPbmg/OzX7Cxe8pNPurwoHDZZzqrZcnUx4e3vPqIRFpZwaYRGJGeUfhv79gl69YQXlwnahnSTcrI/IEszjsd7SNZUuuKD+wcY3SClYjTyefz6Nb94Oeej+4/47keP+ObZMxynJEtyLOHw5Ns3xAn4YYgyDb5lU+U528mCyLPI85hVYiN0irRqslVMGw/HCOzIELUEtchwpEWRZsSFpiXA9yzSfEamJPnWoxV12Y06fNLf4z/nF/+vuvlbId5I0LbAJJq8yNjkc7YFzKuaOTXLAooq4e0Pdri52HJy4LO6Ktiur5GRQ0vBw/19TK0ppCHv1Oy1A2ZFjI2DmFl0jEdZlBRaYOUFvgxo+RVawkVWkGYloesgMkGeGC6GCXbo0pWazrDNZrWl2/PJEVymOd2Ww1Fh4dBiJROytKQucu61Wzxfr3AtRa/lYSuBOOqT5RlhS9DEOUvh0iCIE8OzF3PGoza6gU7rztxKipw4bvj25Rv+8d/5CeVfZVzMXrO306auHLK85OzsjGyz5Z2HYx7eG1KUE3pjST0vOTk94vbzV2Sl4f37Pf7u94dkscX1as5ux+PdH+4xWS4JbYvFJKPTdfidt97ji5cThLLw3Yhex6UXVRSFz4Wu+PDeCD8QnO7vg25Ia81ff/EGQcOg12a9mbN77x43szlfffuM77/T4X4v5Mk0Z7VJcFsBx7sj0iJh33NpeoqbeUbgSBzL4mDXY28g2C6XpJlGKYebbcKzyxkH4w6TmzWVKalzEFKB1kjR4EnYVBmFcnBtj/mmoBc5+N0WtivZJCkY6Ld80DCdbugGDrPZEr/bxfYCsrTANJLGAktaLOZLhPSYLdYc7I+oy5qj+zZnZyu63TFis2ByvSTZ3H3ntiMfx2pwXJvFbE2VVdhIdC25mmwY7o1QSqEaiRCCn311xs/bVxwctxFfFWwnMWErxA89bp5PGI0OUI59t+1ZFhRVQ1HU9Pt92tGSbZJiqRLLcsmKhLSscX2H0HOJkwJHOiAFBoGQgkZrhNQErRA3lEi7wG9pdGpoQsEHf/h9eu++i3xSsP3yF/R+8ocM/t4/Ip58jYr+DJ3mRJ0Be4enhCdHVC9T3Kri4Q/+gCrT/JM//t/Yphuur0qGdpu0UAhpgTaEvkOSa7ZxhrJ8lBLcewt/AAAgAElEQVR0ghbz6YY38wu++vaK4/GA3rCLdm1kmhAnKX5rSKErbrclA2vMd37/J/z5f/fH+FGLpor54uUzPk1/RPftd2iEiwSI9rAN6NFHHH5Y0HH/hNF+h6vrFW3fp9vtEoU+w3aXTugSOSGeA+sk4epmQcvpcrZZcRPHzLOam0nOfHbDyfEBjrrb7ahqG08bpOswWyb0PYe6yinTEtcSiEYiLYuiFghCLAleGEBo4VQF27wgKwoOeiGFSqEBWYBVeRSlxmoNOO0e8tHxCEf9azDz1sbgaLiYbFiqinwV43g+N9OMOq8wteBk2GI88FncLMnSgitjs11kfDRQ7Pf7tLoecVNyebPF9wR9RyM8l2Vc89aDPo+/nbFclKihJvIDZtMtLdchlinzWU2WaMpOTS8UnIy7WIGi5fu8ej7n1STn8Min27LpxGChSJcZ//d2zSfjfR4vJ4xGI9wkIc8qvHZApBVJkiMlRF4HihxVGZTlczlNWExT9gYe7717xMXFgrPbDWEQkqQJGMN0seLspuHf+0lKFrs8fhGTZK95eDDAMgF7u4JhX9EbuFyvlqSxYTZLcEOHpqrQosa1Ff2Oz1//+g3dsIdsBFfVGn8DSZ7StCM2yZJ3jz/hzVXMfD0jL9Ycn4yI05LGCA522jw42SPyLUx9N8tdrJd4rs/RXpfr6ymzeYY2mm5LYskGae3Q69ts0g21avD6Peq6YukbhAstFXC/K1ADi5vbLednCYtNdse2ySsQCosaYQzPr7Y8uLfPX75ZENoWgavxHUUpK5QTIqVNuomRAihT3JaHrBrQmkYFNLlAao1G47vgKIfpNCNquVxfTXlwf8xmm1JWFVJCvE7wuwGW4xAqQbpcoYVLKC2ODoe8Oltxfh5jIaCS2EKzmm1hFJEtlzSZ4eB4xHK+ZlNoQuHgOgFGNihp0+iaLNvy+CbH25GsNgnf/OqWdq9Lu2eIqi6HQYgxCqNr/LBFk6bIwGL34TukouTmKsa1BPc/+ZSzF58zWy1YrO6ASHUDjalAg7IEwtz9idjKpqgMRVHTVA1FJjFVThFPefLP/hTn5hWeEgTvfQJuiEkusFyfoCmY+5JUN7iDFqoVYn3yfcyrL+Dzc+rrJyhbMJ+tGbeGlEnBTq9D1k1ZrGPiJsZxHOpSsclyIt8inm9wlEWRxjx+9pyP3h6TpQl74wHnT79muy3YOXqA1/UIRyd4geSTBwe89/mvOL+c0siSF9NLLp69on3vFOmAVh66KSGPUcGA4fiQk6MxbtCmF7QZ9TtkZYMpBB0rQrmKcbdPmiYkTYIr23QjByMDlLCI3A4PD1sslzOW6xJHSGwp8TxFGa8wjc9imrB3FGKUYr4pQIVoIfFCmyZ2OGn3GboOrmXhOoblYsZ2uyWwXDq54jwrMZXDwlQ4no/b6nC6c0o0HLBuLNpB9Bt187dCvIU2+IlNVuVsy4K8kcgyQ2ubXscQepLZJiZaOXzv4wFK2+y2Gl6qgOODMYulZr28Yj7XlHWNZTxK3YLlhpHQ4DuMegFUNXFccRbHVKUhOvFZT7fYlYUTWBRVQ6pc9ls22zXEqyXxuqJqNLNFwd68IRUCq8o59dvc2hkzS7KapgycnEVjeLKe06pCjK+xXUmW1kzmF9iiQcmAkpqDoU8nKKlzwavzOUpJLN8n1w1ZDZaw7qrLhM2fffZz/t7v/z6Pz56jrIbusMVqWlCaAmNp7NAmiDpMri8QBLx5Oefj77aJwhY3kzV1rdmuJMeHLTqtIZPbZ6SpojIWRSX53gc/4vLmmlxCUwsOd/eo8imnuz2WG5hMNb7jsViuqZuGLIMkL+l0PS5vVgx6XT5894j5zTWLmyucoCZqGercgO6wXJUUJES+IN5usZGsRcZwPMbNcmxlEbmKthNSbUs6gUfgaPKkREuX55dzfvDJEXVx10DfClzGjaDoBazrkqQskBZoIOx4KGWRbBN8z6NJK5rKYAubNCkp6pqi3qKzivZgxPnNmvF4yCbdsj/aIdls2QkC4jylMjBPDZvJipbnceh4RG2XwHaglCjLMB47xMuMdhCyyXJaqoNqN2BBNPCwG4E2BSAoyhKJAmMYtG2iTUIWl8yvMspKEPk18bzAb7XJ8oKyqBHUNE1Dpes7uFRjWG8SOm2bXm9Imaek5V2BsmvlfPrRQ/6vv3mBQaOUQBuNEgqDwQBImGxipK0plYLIoylCZLiP7A1pvfcx2Irq5VeoNy8Rb73Fqe+xNppaVFjlFv35v0DuPsAcfoyZv0J1B5jyKXYd4LBGejbrZMO2SFCeYi8akyY5SVKiNSw3FbploRTkqWY2v+Xp01ec7vaJLMl2k+L5bbKspPYgS7e49oAozvm3vv82/8uf5MR1iqUzvvnyax6+ex/n9D4oHylt6jdPUK7BERXfe/8B/+eXTznu9ciyCrSiaQzbPKfTHZImOde3C0ohcB2b/fEY5SyJohausrH6Fic7PS5vN2AF7I86NCTEa4vNtsR1FcqDrKjpjnusz7fUjUNDjW0pgrBFlTcE0sJtKvaiLsJ1+Ozla5pMk00rSuUT9Dsc9YYcHu5ihxFVo9mUhnL7L4Hn/a/8CEEsM6IDm8vXgswYusrBaWrCls/AcXDdhkHfI85TRjshW1nw3oNdLpOCF6/nOC6EvsPRbod8axB1hRt62EIhqoxGN6zXgrKWFHlNECrOrlNcz/Doux2mlwmz25xmUhAHoKyaJtastiUoiU3FepZwsymReY39rmIwaHF+eY3reXx7c40bdTgaHlM1JYmJcbTD7dWGKi2pbZdpvEY3Na6XoyJBN7DxhcbSFr4sKCqJb9/NgLPMIJTgF99c8+//YZemqLmeGIy5wRUwHrexbcXN9ZKdnkcU+kwXt4StFn/52Wuq0rC357E7iijzLbe3a548u+FH33mXgTOmyLcYq+DzZ4/5/Mklrcji3mGf6+sZ3ajL+fkcN1C8//4Bi0XGq9drhITzs5yg45CWW0KvQ8uPacotrU5IMPZI1xWuY7FOc6rKYCuHBotBe4Auc56fv8GNPLTeYIxNVgqCoMPNdMWo18ZRgryskEpyejRk9mrCfhQgcMhKuJ4VTI2h9gWBtDCNQTeCumlYbWp6TkPgeKRVQ9XUuEpihMETFsq1aYxkVSfoKidyJJ9/c8bHH59QTVcoSzN2BfuDEV9PV2zWBY4dYUmbm+mUdrnC8yXf+3REkVXoumJndMibZ5dURUXlb8lz6A76lKUgye7Mzju+ikuRFggBoefhu5LPvzynSiWRZ9NvBZSbGiUrsjSn7jTYFli2Ir5eIwnoDsYoY3OzWPL4csMPvvcd5ss1USDBtPneux/x13/zHCk02mgsy0IIgRECz5eUecHhwQ61AAKN01jUjcO9H/8evYePoN2lvn5J88XPsN//GGvnCN0TWLVNTcPm5gYefIzZzJAP30G3Pyb+8mvW2xX3Tncp4y3fPpuQViXShaIssY1AehbbqqTSAtvxkUgkUNaSOFnz6mJC1Anx1yn9B29TFpo0rWCzJZ1ccH255PujT3irO8AVW6zIJ7Rcns4u2czm9A93EVaANjGVBBnsIXYOeP/HFevNisouyOqSdKPxZMjh4QhbaixVI1RD2454dP+UVmAz6vV5czWhFYX0Oh79TodKPyevJL5nyAofx9csX0/pRza73TbTdYlSMd2uz2pe4imBBayKFNdAz3cQQpClBUVe0eCysQLaxzsQRNwbDHhwtI/wYLuNIS9ojEWV/2bZ/K0Qb2MMF3mFKRtCR2KUxV444LTjc54smRVzRODy7dcz9o/buNuE416HN4sJPWnzdjDgZpkyGFloI9ikJcW0wD5w0bXh87+Z8ORii+17FFXNqBMABX5k4SloS8WsENSloBdZ/OmbG959K0ILhfQtvNqQxZIzE6OEg+1avL4q2PEcbhYpWVxRu4LsdsH22YRB6PPgUYfrZMlqXTJwXc4XKZUWtJXPy0lKP3fw2injtk1/Z0z2SlMbuLypKQpDN7KIs4bJtOFmfc37j055fHZBkcHDt9v0Ih838CnqGl3l7IwcOtEplzc5l7MFrg3jrkNTrokih8s3Mf/Zf/Tv8OzZJb+8fMwvn77k3bf3MQUUuU1Taa6tLY/unxJnMZPZ3Ty6qc+IWiHf/50PeH12geNumU0FeZFztAvjwZAki9nGDVmVsNs/RhQFlrRx24K9QZd5mdJkCbWuODzdI0kyhFCUZc6w1eVyucK2FUJVTKYFbjhEk3A1XbAuDNJ2EUZTNiVa3ZHW7FywFDUCSWVqUIJt1tAOAwoMdd2gaoPjCypXIhBQ1bS7Af1uG4MmjyFwHEQeEzQauTuENKfMNRc3G6rS0PclyXbD3ukuaZZhoRjv+NxmGVeXK3rdhv2TkMh2uF1k9HY7XN/eoFWH12dr9G4AhxIQKCnBaDxbce+wz/T5BHSNEYpvX0yoG0V/IMHcNQ65jqIqS4wWdHeOGTx8gPMvWnSKhG1aE683NFhUZczBXo8mf03Xa0gzi1o0IEBZkiKvqHPD7u6Am/MVu/sdOrgUTYZWKZu//inTJ/+c8Qe/hx7vYf/gj9Chh7l5yaqwmCcJgRjhuDamtYfu9ZFWhFm+oIo37I2OsJVDtm2QxmPvoEtRbCiymkbXpGlNpDy6bYt5mpNUElVqLOGyiTe8uZ7x/oePSMsCGYOlJU1dg2oQdU6eSkwhCe+9xR995y3+18dveDV9Tcuz+eLXv+YDz2P3ky5C7eOdNNTPnmCFktHJe7RHLjeTLaZyCEMbu5H0+106oUddJVi+S57DoOMS+T6+I6n2dmi1AizdUDWGtCixpcd2HXM5jRHC4YOP7jG/vOX81SuSqkYmFfdDn9vKsCgLhp7LWCsao2gaQem5nFcLtHR4a/c+xnPpRV3efnBKt+PTlCXbUhNFLVRRYbsST/5m3fytEO+iamg0KOXhOSWhVDzcPeDZ8wmXrya89UmX20XByXGfvCl4/jJjaiW0d23e2duhfW9Ip14wm8dkWclqlvPN4yl64tFrSV7P8jvucKyp0ZyeBtSiw+1qhRcp3lxuuN2U1LJhXkniSnN227DOUnzXQogaS99FwpQFlZQ8nWxJAiirhr39Ho2reXWe8HCnTZEJnr2aMxwHHB4N2Ky3nBx1efNqwW2+xfE9bjY5i8zQ8lzm9TlFWhGnDk0teedBj4/v9TDaYZkUnJ095QfvP6DVF8TbFZHrUtQ1Xdcl3cbMZgsQgs6wRW2X+I6P7zZErYCrleHDe8f8wcfH/B9/+TP+9794TBg6xGnG9eQ13U7IbJbg+Yq0qXj7/paqWjPuBlxNVoSBh+35uE5DVtUcjI8I3Zivnr+i7Qq2aY0R3C1HpJKtfUMw7pHEBlfVlJbGkx7aqxAFVFWFKz2ksYkAW0iEhizO72j/liFezyjTCnLFD066WKqkLSRN1EaQ07Icaq0RwsIWgtskZzhokaYJRQlVU9KPbNqBwyatMXWNa9t4kUunbRN5kqwsUa0IITXC85hsUqybKYUrkdQUDdzb6fBRZPPVWqN0gWM5HBwOeP7sNatZRp3bxLMSz3KZxCley2O9jplOKmo3w5I2oeUBgrqpURikkGRFhrY03a5HLkqqxlBUEsuxuL5d8Wi0j+tbd+9eDbISdMJdHDwsqen4Ia/KS75++hrfaXBth6ISTG8bBu02ebkBLe9MS6NpNAShzf7IIuqOcCNNsq2wbZd0o7B238dSa+rLS8zuDvXiGXL4feonZ1RlSscLyJOKnaN3IOqhhic0198gXvycfLqgFhmzrSaPa3734/f47OvPyUVNnZaErYBu5KIOSs5mKZHroIShLgRKGkoMcbnm5as3BP4p9WZCNt3Q3Tth1N3DOtJUL94wuZgzPnibd/7hf8Bnr/8L1mHE7dUbLq8eMnp5Rvv4GL9/gnF3sN2XYA+QKuf09G0Wi4R4U9H2fdqWoGkssFoc7e3Ram+IkxohDaAptCRNY4RoCF2PIt6ymq45Pmqx2CbMpkvef+ceL1+9wZMeCQUqiNh1BeUiRQqJqxyEqGkaQ65zrhc5+4MeKogIrJDQcgn3Rtw/3MN1HWxlQ20h4wKjLTqdEKUz1mX1G3Xzt0K8lSVpDVusNhuCSLFj2ojaQdgRlu9S5yXvnwyJt2v2WgMumgSaijgVPJ7dYs1WyLDBdX2SxHC53aK7kvkSqqphZ9iCvOQ8TvCaiMtJwv6uw97IR9U1izTDVobGs0DC2Auo5zXSEzSVYLsV6BrU1sGyKg4OfN57q8tkCaWoKXRKFmsODxTjdki35aDKAOFbYBxO94c8Pr9ABgFaFOR5hWfZeJai11YIY/gHf/cT/uJnL7DXDTvdiGWa8sFJh3CjMMbjneNdnl/9kkFfUNcC17eRTYlj1fQHHVabmudPJ3S6PQ6HFoFvU24Nf/DRR2zKnP/qv/8nzJMtwvdJ8wwHm7JuuFnEBJ7iYGjz7oMRvu1jjTrkeYIXK15cpuSvX/H3f+8jfKvDdLXlm2fnRG0XBMTrjDiL6Xc8uv0Ax7a5vrnBtiyEaFPGM1qtANvSVKK+Ky+2Wyy3KZPVhizO6UcO/eEJT88ntJTAEtBtOXgDw1dXSxbaZjhW4Evmi4aiFBgJtsioGwuamsVqRbcT0O84mNJCFRoPi7TO8AKf4ahPSY2yBdlsSeD6ZLJBhR7xcovBsN/psNI5qraIOi3iOGc6bNO2BMpRHI5HFOWGk3EbrwmY6i1vv7OPpQuE4xOXOdvJklxZrNYZ94YtVnmJEoKqLHFtB6M1vgy4Pbskzu++ri3lUG5T6gYwNsY0d38iUqCUQghJb++A/v0PGfS6rLKE4WCXbV7Rb2navYg//bOv+cc/+iF745DpMqOs76BICAMIDndbXGxiAtfnzfMVndCn73iUqUTtv0//+6c0SYL19Oek335J0Bpinb6LcFqEymWv18Xr+KjxA4wo0a0+emeEE/isVi/p946IBh1u17e03JAiT5BSc3Z2S+j5ZIVmOjeEIaA0QkocRyEtQZwsePL8W7otl5Yl6IQdgqiF53n0RvuYLCOP54g8I9h5xA//wX/I2f/4X5MUMb/84jFvPzxk+fwV/qd9pOWiu0NUOMIxPg9+9z/lybP/knh9BlVFKUM8bDxhWP1t2bfv2/i+zTbdMLmYoLXCVjVG5Fzfrun0uzRVwfQ6ptV1eXl2htYOo/02stCY3CBsyYIGWyj2opBhy6bKK2rhUgPaCnCrmk63h6kzdFOz2mYUs5iqqDnd69Fr+TR1Rdd16Fguajr9jbr5WyHejYaz8wn9YZ/tKuHeOEDQEOczhiPYGXeRVcqDXR9XK2zfZZOBL++YD3lWUJQ+t/OYuio4fXuXy39+jmgKZgvB+w8DFpcVnnHYP4AP3h/S5BWbZcXkMsXkFqIscF2JlBJVlriBRehJWjasPJfposB3odV2qDRsG83vfDDi/NpnsljhKZuDfkA/2qMsJsR1RV9bWI5iXWbs7PQ42HP47OfnbOucjz/cp9cJqcoVeWXx9MkZbdGw+/YunUgTahebHMfVrPIEr6MY98YssgVxWnE9TVl1akyVEQUencAmOBzSCyOGD0853N3hahLz089+xbOrCVrYuMJC1yXakihj6Ls2wvbwfTg5HpM1a6ZrRbxtmC5WrJMGN2xRGYskT1lu52RZjO9CiE1eWWR1TKt7QG1iLmdbOl0bx9i4lY3jKObbjFVS4Ucepi7ptxVpsmE2mQKSXi/EVhWhr6Dq8/jNDe/vtlFRTVUrfjg6oO1V2I3FMi/vUhiNpGgqhCtpB4KOcphuKxZVyoO+j9PxqEyD51j0QxDKxwkMVVWxuSloRQNebqbs7fWZTWZYnntnLgFxVpEWFUGpCPpdXl9O2B2FBGGXdLvlzeWKfFnQCyyOhhHxagNOQ2hbxIs1Q7eD6QqssmS5ysBycC0HKRWWbSOFRPztJdYLPJCa9abBC3yS5M6bsR0LrWukuMuSO4FHnC8oq4pyPUcpeO/9R/zVz36GQHN5OcEPPMoi5+Rwj2+eTlFSUApzlzqRinYvpMgV1Dme7ZA1GbdbgaoDXCVphEt98y32w+9jT6aAS03NKhNs8g3h4Jjo0SeYekNTVSgN6ujHmNZTirzg8asXFJbCdSS1rTF5wzbZEGd3BqHtGaJQUeuaqtC4UpJlBZYlCNyI6WLDdluwe3pAq9dnMpsgZc2ge8h4/4DHT54x/cUXdHevePvj32Hnz37KZPIE7cT8+vFr2n6PnaM2Tv+YrVH4jcJYCivc53f//j/iL/7n/4ZSV6wKjZ7dEvg7IKAsC4KgTVGXKNtmNNpFU7BcLpguJdOLa2wluCokCEXb0dRWQFEYyjTFrRqsUtHpdFl6GktAFLhEHY/dR0Ma6y4WbBnDnulh2RaWMyTJGooiYbLKeXO2ZXq75mAnYDhuUZUFMQ2O/68Bz7upGgLPZ71Y03fbvL7e0LITOpHhrXcf0FQ5dVIR1B5FmjEIuzTOiq4jyAqNa+DqZsayqVhe/T/MvWesZUt+3ferXbXzyefm0Ln75ThvAmeomeEMJ8lMIkXK/ECbNkHBETAMG7K/iAMDNiDB/mALtgDCBCUZoilLtOmRxRmGCZzESS+Hfu91vw63b74nn533rip/uE2AEERSwNiGCzg42HV2VQEnrLNr7fVfq2J7CSKvabsuQcui8xyvK3l04HL5SsiTa0Ne/P59skmJ1opcGoQDa32PaVHieS5h26eD5oWrG4yV5bV3z9i/k5FrixaQpyl6QxEpzQevrWDckM1hiHZgOgpxCLj34AQRJGyvrSJYIqzD9mYb78IavXaMKyuE6xN1XO7cKbk3adDjYz75I7t0ex5v3T8GL8QXBs8X9P0BoR/wzJU1qtISKHNuOSpq4naI63a4dXcP6yl+94+/xau3ZiRVTeg6PHJ1l7uHJyynGRoHa2tkYLmw2WK9CxuritkyJJSWoO2yP3JIC01ZLRGO5c79A27vjXn8cpeLwz6PXr6A6Kzy1q03ee/uPfK04gPve5JBb4Vbt98AqYnKkiev7/L2yRxtDVlWMVsWBGFEq92lsYb5eM7VTkjfhc5Oh65TsGg0L99Z0u0HLPIpnw3aDHshp3OLdhr6gcc0KSmtpCwNTWkxViIcy0wLhqHg6sYKTlIwKUCLAFMn9HyPeFUhlEKVHnljWe2vMtEVSVHjtyM81wMrmc7mRKFABorIUdy9d0iRlSwWgk7oU6U1bqjI8oqw4zOfLam1ZXo2xWiNqAsSJ2DFGJQQaN2cp9criR8GxO2IWZ5xNk5Ilg4Izepal8AKwtDH81xcz0UpRVJmPLj1Pf7Fb+c8fmmXH7z5Di/+4AdEcYuizJAEeF6BkQLPiYl8h0UtQChqU9MYyzQv6PkKE0dMTws86XBpu01axIhuBzM9wrv0IayZoH7sb+AELZyz1xh6KUczh3YY4k5fB3URpaHpXUUcfR+huqxv7TLJT/FVSNzxWVZzrPQoK4VZCqZJQdhIui2X+dJSW0BoWm0f34UsyylKw8loyqWL24yTKU2Z0unukM9TjJBceeoxRAb+1gV0NubfeP5pXnvpDfyhZX9+xvFZxuNKYpqUfHZA5EfYwXUcStZ2LnL5+i6np1Ome6dsbw6orTz/HKuSo5MzonYbX0FTQqcfcXpWs9rp0r6xy607EyIFF7ZaPNg/oKwsrW5AUVTUjiLwA8yyYrW3TlnntPotusMOqytdHByUE+K3YpbLBePplGV2Xm0atn18p2JnJ+avvP9JitmUew9OMOac73acHzJJRwgRAF8H/Ifn/zNr7a8JIf4B8DHgT4PWftla+4oQQgD/PfBXgexh/0t/0RpRqLhyYQ3TFDiFg0lqhBvRqIbFPGG2mLLZijnIMnRVUZ0dkg8scTDgvf0xBIqs0DTSQZkA7zDnydUh9+uElVBwaaVFe9Unz1wsBWeZ4SjT5DWkTUMl4ep2TGc1Jjw7V7uoeU27J2ivCHzhcrLV4e5Rji0lw1XBI9dbrIeS929dwFBxd1yxmBv2pnsM4wApNd1BhCPaHB9OWZYZnXbE5csboCviEOraReuAxXLO9Rvb3N+/w4ULAcZYyspy6cIFXN/DVBNiNaTXaTNeZhyODjiczTnan1JWhtXNDcbTk/Mt8YMZp9OUxkKjLW4jQDW88dY+eVUSRpKBG2NlyaULq5ydTHn6xmMIGgbDDoGvyCtNcLgkChXHkymxgtMzcB2floy51vPZHnZ5Y3zM2jAg8LZJspqz8SkHx3ugJcPNNR67sMsXvv4nNK7PoN3m7v2COHKIopLrl1dBSlwVMOiG5KrAJhoVu1SLikB5KFehlSDJFceTHOkprBEs8oociakNphEYYakrQ2MseS2oliX76QPW11ZohTHZIiFud7h9eEqr38KUcySG8emY3WevMb57QG0gTRcMAwerKhZuQOM6pAvLNE0IjWZpXERd4PZ8AqUQaEJXUmcalEBWFq3hvXFKIySSik6/BRI85SMxGH0earCcJKR5SYBH7YHjWDypyVNBFAZIKbFNxXJZ0VSa/b0H5MuSJ370Or1WSDV/l/FZl/WuQHU10p7r2V1XsdJr0R84vHM4Qdjz4Ip23CJqw979KU1lWelFzG1FvxPjOxp3cB0jA+z+G9juFiweYJ2Y7fUNEmt4/v0fQXS3qeslrtNHOh6mf4Hl3j8myTK0gNVOxCKZ0u6ExDJEKot2K7I7FUIrzhYpoRcjqgrrgFCgraasa7zA59337jCM2ly4sg4Gbt2+y4XdTZTRlMsZne4aQVMiXYgCl41hj9OFoMwzpvM52pGQTlBCYyd3od9DU1Ke3GStFTGdLCjLhCKPMXlJLxoSBgHT8QKbOdw7nZFVEk9KNnshG2HB/vGITtOw1o94ZNPjYnuHo3HFJM0IWj3iVoyUAqkkeVETmIjAj/CsR5kZ6rqibmrM8QwrBW4YoXRNtxOidZcpp7kAACAASURBVM5a1yXNBG/fvMXW9ioba32CwAMEjpA/HHgDJfAJa20ihHCBbwohvvjwtf/cWvvP/qXzPwdcf/j4IPD3Hz7/uc1oQ73Mmc5GNAY+sHGNzIk4cRqMLejHbWYp7L85Z2NdMehETMZz7p+OuHsvp3ItvhcipMEmJd6mj+w4uMcheVLw5mJOeyK4vDEg7nh897W755akuiHu+Xz0yR6XW0OO04SejDiYTQgjjZAtvvzKIc9srJAdLogDQSU001zQjDT9OCDCcmqAJiWrDVHc4t7RktWeJC0KvNBBdBXX4i1cxyI8SdNI9h4c0WkPGZ2N6XRCRsf7PP/0Lot0gu/7nJyeMhy0cIqGGzvXOXiwz/FywWt3bzMcbFDkMJmce2a//Mpt5lmO40isCElyfU4vWM3Weh/flnzus8/z7l7Jd99+k9Vhw5XNDeazMbGj+Odff4lLmwNOTlPyPMPzPOrG4WyS0G65BL5iltYkieH2wTG2GbByIWE+W2JNRp6lpEmG77hsDrqMpiWPba7w4ht3uHmw5OlnhsxnYwa9GOOAcQRBZ8DdvTu4gcs7o4Q4clFG0ltrUypB0UhWNnpkSYJ0GtZWYwJpKQJLoAJO50tm8wQ3aHG2WGJxePzygN6q4varYx69sMb+4ZjhsIP0HGbzBZEf0OQax0r67RZKpcxmC9KqZHcwpFwuOZk1RF7I2orHu/fH5A3kqcf2Wg9VTAg6IY7VWEeCI7HGErguVV0hHJdFkdDqdpgvl3SjEFPXCMBoDVLg+R7KFaRVw6wC4QgINVevrdEJQg7fW55rs60BC8YaqtpiHcvaWo+NnS2qomR7f5/ZUUa71SU3NVK4OAKsqdlY7VM2FfdPHXQJxkgm05xaGo5PFjz11CXS5ZSL29tUaZfe1gbWqXFwMJuP4eiSphzj5RO06lE0OVcfuYZZv4x7+iJ0d3HcNrZ9gc2rj/Ktt34P2RFM0jnzoqBOEjwnxEoHh4peR5ItGkSlKCrDx57qMT5LeDBrqEyDsAZdN4yqDCsF7dBnNB5xmOUcns64srPJ1YvrJJMJnekYk0vqWjDobHC6N+HyI0NiN+Puq6/jCEiTBR4OnfmcMFJY4bPINL4r2F7rECjN+PCIfHKEbixlZSiRKCPZikN2tvtEscPkZMSFwYCgnuMYQVpYtPJobXRRlcWXEgeDsRqMZXulTxgG1BriKDw3SMtqgjCk241wA8He0TFVnjI7S7EGagtnZzPCMCJPD3BtTRwFVFWD5wU/HHg/TH5PHh66Dx9/UT7PTwP/6OG47wghekKITWvt0Z+7BoIHB2dEUQsvlrx7dERnZYejdEbP8ejUXdoq5C09I58I3K7D999YUtegQ49AaxrbYMyCrZUYf6eDDRUbbclrL2W0PYe9gwx3GKP3M3AihsOMobuFGJT0wojp4YS8qpEdh0e2YoTnI6oAp7R89dYJwrpMigZlDLJRLPOKWdjGNCMoAxrHwe84HN+fsbnW4+69M3Z2h7i4FMkZ88YwmUyQYYeNjXVW1reZzhZ0VwccHpwQRz6+l+JYqMsK5fq8/NYhK32fH312m3phEFpw5couLU9yYjJacQhG04kFL3zwUbJJzWs3b1M6gqIBoxVSVDie5Evffpl/86NP8dHnPsetg2O++upLDFTIr/78Z/jil1/lq2+9gzUWYyyuq8GUOI6i327TG8Q82D9jo+3x+OYmh4slk+OEo6MRO1trFOWCdtzCKh/Hjbmw2uG1N/b5ne/epjaC73z7Lu9/co211T6v3rzH5vaAd+68TdztsRglOLaiJ6DT8ri3mKL8GNfPWcym6OocxFqhR5ItGLRdtNHsDNu0fEk6LwiUz6zWiChkfJrR77TJF0uENayuBtS2IGzFTA/HTKc57W4XVEm3E/HgcMza5jr1Ysx0tKS9vcpiUdPMc7qOz8W1IT/x6U9jy5x//E/+KZ2uRDmGwA/QusFqTVVpIj/gdJmyKDVlWREogaMbpHUR1uC7LhKN1g1gqXCYNw2WGh/Fg4Mpj1xx8b0A5Uos58DuKw/D+RWqEAY3dMnSJUWqqXKN7yjyEoqsBGuwWqOkoBECLc7VHJU1vHv7Pv5RjOc43Ht7jAoLVi9WjI7u8863vsaTH/9RjDnGUQNMsIFNTxFVBm5A1RT4boUdvXJuTaB8hD5GyAHDx3+E3u9/C9VXFHmFwEMKRUODJxSDVov5qGRWn0sEu17F+6/3eNsxPBjPCaIYT1myNEcIwDH4ocfp2YiisXRbA16/dZ+T2YiVfp/q4IwkT5kuFgzjDh95fJXdzQ43LvbIj/cZT2f4nk8uJPt37jFfzAjKMZEfUDuSnjZU8xndRlDWCtcNidoRcRTh+j6u61ABi4Wg9ndIqwx3sEFpBCfN+Y7IVbA+CHCEobGaoqzxlUscRjTG0gjDsqzA87CuJqlrykVDv3bwrEs3CqkcgdGaqqnpX1rB83yM0VhrMU2D1TWO8/9ADNrD5PgXgWvA/2it/a4Q4t8H/mshxN8Gvgz8F9baEtgGHvyZ4fsP+47+pTn/JvA3AVqRpPYVR/Mlu16f8bKg1/XIJjWuI4mdgiXw1O5FaGqy4woqFzeq6bdDBqom7kUoP6JINcfTOdP7Fr8bcPWxPndvTikan5MHS5SRGN2go4iWlzM5LDhKR6zIDnuLGdd2YtpbXTZwsU1D4imubnU5nBfUp+dgOOgrhhcUaytd/MZwd39OpUtM26WqGl6/dUhTaC44Hlon9FdCxlOJ6/eo6or55JhOGLDSjUhzje+1uHd/ytauBiRx7BOomg++8DjT0QmXNq9xaE/YOzhipmfYJiOKQ154fotWKDk9a3jn7hHztCLyHVZ6HRbLktX1IVEYoVhy7yjn7/7u9/nwo+/xi5/7OKEN+fZbr/NHP3iJDzy9zRv3HlBRU5QNWV6wuztk/3TBZJHgtyNsaVBeQ6NCnr28hecJ1noDbr37AD+WWCHA+BzcOeLHPvgEv/X7byIci9KGwPVI0op2nLOxvkGdp4hGcfPBfa7sDlkZdGhby1TA6VlGU+Q0RUkcxkSdAOUKwlARGQHCoo3GZhltT6Fihass7UARqJplYohbYDKJCiXzJMWRgsatcCyUpSU5S1gdSjytqSpLtn/GjQs9JqOMauEwXRZoHDy3YWdrkw9c26U19Ll7lPDKi1/HOg0YcKVEaAOOIpQuVVHSAK7yUFT40oUGlOMgsEghaJoaKQRl3VDWNaHvstl32RzGDIIWSTNBOQ5KnlchgsDzJE2pyRcFkbRcvLxK9tUcjODGpV3eeZAzDQOEgKbW6FLjRz7KkQgERkNZSrJySS9qcelKi8mywq991gaXWdl+hOJ0D3f3KWRzfmUmWj2apE1vrY1+7YBKebQjH+O1EcU+OmhRH36HYTdGBhZhY64Mt4l2IqbphNfv3SEKW9R6zqXNXZziGFtrLg0jvvbShKSRRGFIVlRY32drdYVQCvb27tBqKQ7PJgShj5SCsoQ7D/bx3IjhsEXoKaSrKKqSdnAue3zxtTHS86irhnYYkTUNQnlYR7BUXcZZhS4q4jjEC2OidkDfj/BbbbwwxA9cyrpkkSwp8pROO0QYQdVYQELeUNYFPT9id3XAPFsyms5ZJCVanHudx0EB0iEvKoqs5ODglMPDY/bPMhY1/NUPP8H7Htvl7OwUhIPWGk84SK9isZyjXJfQDwiUSzwYUpm/WOj9rwXe1loNPCuE6AH/hxDiSeC/BI4BD/h14G8B/9W/znwP5/z1h+PYWYvsaqfH7eUpx2cjntneJQg8dtY3yWYT2oGHG3YpkiVp0OIrd16jve0hcOhFiirPCJRlZdUlc2C110dXOYvMsJxOsa5gZyei7eRc3V5nlqfMjivKyuHwQcHadouZV9Fu9elJ6ImQWZbSDUOKE8Otccp8ltAVLhevtLi0HbG11uZgOsfMGtzGZaFrivGIwPP58FMX0HXBO3unWGvRZcWlywPKtCQKII7aJI1mMZ8xaLd45NoaK70WQjmcjk+ZLabooqGYZHzwycvYyuFweshgrUM9L0mWJUK7CFPQ1C6j8RyfkLbrYzsetil58pEVcMDzAlZXhgx6h7x9B771+oyb9/5PfvbTz/MrP/9Z/vnXb/Hd117n0x+4wpe+9wZGW7zI5/hsganBiQSj2ficLujDaLng6etDVlXEF2/+gDvjgk5gaJTPRq/hx56+zNd+sEdpzsGr05Ks9zxW2hFxECBIGYaPcPveEXW2IJvmHC/HjBwfv9ehzjS6FLRbLXTdkC0rUOdBAkHUYnw2J/I9rC/wI8XqVp9AKVqtgLCjuHX/9NwYyldUi4SmbOis9FguFwgE7UGH9w7mpE3JamHpx4pi0lDmNXsnDY04odsPafUc8rTi5lvv8jtOzdWtIb/yb/01/qfljP39t7DGYB4GFVSlRjuCsrLkmcZXhlBBLmpi38cR5/p26ToI57y+sBW6XOtFhBJ2djoEQqKamrI2WAxCGLAORZWT1JoHo4QnbmhsWZDMRnRWhzyxGtPvu3iHHsKpsCgcx5xrlh0XT4KQAcqA70nmWcE8yXnv/hGxKxkdZvzYjzzGxuNPoI9fQib3qTqbuMUDzDvfRl9/lsgPGU1OSI6OaK09glMuMUdvY3efQ6VLRH1A0MBWZ421bpdLF3forbR5/M1XycqSd+8c4W/F7K4M8BwPV+fkeYHjxkznOcYK2pGiHbtkZcV8mfJg75DVYY+izFkmC5pG0zQNRhcsE02pHITVONKhlAHV1GAB1/UR4pxS0RY8FzxXEYYxcSRQUuK54EiJH/VRvo/7MCSjygtsoymWCVmWo4w4/w7VGoshrwuM1qSl4N39I7RtaHRNZWp0rQm6AVZJmqqiKFNq09Dp+4StdWRvzBf+6BYv3mzz2KUVXKfGWB/HEeRlSeAIXNdFWKirmqaq6cUOayvDHx68/wzgzoQQXwU+a639bx92l0KI3wT+s4fHB8Dunxm287Dvz23aGNoi4bGdFpUriHRMMpvituE4T8GW9J2KOOjx6tvvYUxJv6VYXe2y1u/hOD1GowXSBLRXNMuqwG972NECKV38sKHMK2TgYZWkbhRhX3D7MCE1DfePl3zog+ssjuAbJ1OuL0r2T0oGT7aZFhWh1zAn5NI1y42rLdaDCNsYltpjmiSsqIaWI4kKuD8peVufsRr7WGvpdiIc4ZJVBj/qU1cps3mB8hVpYkjmCzpdTVnA4fEpV69u0VQ+nW5BNs3YvXCDaZ7y/XdeYj4vCeMIqcBxK45Pa4oaOt01uu55tNbts32uPfY42XxE4EHWVLxz65hL21doWFKZitM85u//79/nuYu3+dlPvg/f+wR7e4dIt4222bmPtHXwIyhyiVs0/PiPX+TOnUNqk3IwfsBTH/oYpo7otSzLQuMbwyO7fU4mC+bFKb4SDIceGy2PtU7IjccucXJyhqsFn/v4o3TWP8U/+K3fY3/vXfywBUHDZJRijINBMl3m+L5PqDVhHNDttTg5O2F1pYcbOeRpwUq7CxLqvCBdLFimhk7oYryAYadPuZxjpGA8OkVacX7jUBr8SJDXLvsnDb6qCGPYn2tS6+M0KSExolBUaUbTzvntr36H53b67Kx3+Xd/4XP85m8ZWm1wENy8+Q6eX5PXGfP0XEFRVc05t19rHOOAtRhtEO65q2BlNa2+x3Cliy0XhFKz0mqznCSEQYAjwGiLQeCgyJOELCk4HC+ZJCWF9nj3zgG9zipNtYG1BtcVCEDQIAGpAgJvwLXtTT7015/D+g2/+b/8E5ZZhQ4DRmnKpcxyNt5HUOKs78LkJqoYoZVPenifyTuvog9znlnf5vCl7+GaKZN7d1HSkr30Nr1ui9nhPkGnR1Es0d2IrMqoz3J8t8Pp6THd1pDeoEPb9aiTFNMEdMMOjueyub5CpcHzHExTMJASdTLC2IasKCiKBq0bFos5UeCjlEO6OEN7Hq4rcVyPZVoRegFRGNPp9lCOwOpzS1w/DPF9D9/3AKgNVLWh0QKakgaBFeB7EVGgqB3Fzu4q4/HoYUVvQmMajBZoXYNwmC8XCCyhryjLFMdKLIr5ckbZBA//VAyeAwiLEg3CpLgK9s8mvH33iBsbHRojSPIctIt2zoMgHMfgKolUkjpbMD35i+vj/3XUJqtA/RC4Q+BTwN/5Ux77obrkZ4A3Hg75AvAfCSF+m/MblfO/iO+Gc8773ijF1iGXt3zarRBTG3SScXF9nUUyI9c50vpcu9TnsmpRORWuY5mPzwhaEYHQ9GVDiaUKXOJ2TMv3OTqZsrneo2400mlY3VSs91e4f/v03BdDQVZCkjW8cn+EzhWsOCwaxeHbSyJfsrPdY/1CxJ33jjg+zIgHmvagza5ruHFhnbxwOU0Tbi8nHKQVwyDAW+lS64TZbE7c6pEmSyL3IS+oIrymRMkO9/b2CScLHr9xjc2NbXqtNdI0YTwtMbXk6rWr/PFX3uPe0ZxrF3Ypkoq6DJnXELoB1ij27x/wy7/wExyPDHlgODw5oNMZkpuK4/tHLJOKL+29xmRR4XkuTZNjcXlxb8Fr/+gP+PEnL/LcY5f40Uc3+OrrJ8zyKcIqjJE4ouK5p7eIvJxruwOsWBIEXe6cvMff+Jkf5Te+8IfEnkZYjxtbA/7XL71CpWB9tYenKmLPIQwkB3v3iXyfqBUyOjrm7OgOv/JLP8Mf/uF3efmN7xB3IwadLmL/hGReEcZdsqqibhqkMDhlyfWNDbIiJw58FsIjbypE1RAoF9cLmGcpgSsRrsFRGZ2Bz2yRE3keTVGhgoCm0DjWQWDY2YxZ7fZ57dYxTZnjuzXKCzkdZ8xyjXJBNprnLl9BiZp/+sU/5pd/cciv/NJPsf/gLsNhl/XhgB+8/AoHozG5Fecl4JMKvxWisxLXEdRNg+/HGFtjzLniZH1jQNwLkMLl5punrFxaY74oUUKd0x/GnJtEFQVxHLA6jBgtFpwscvZPpzi+wlUOrqfwPR8lfEwjcJ0IJS1SdHj0So8r167y/Avb9DfX2V4dcPPN+yyXc4zVXNlZJfYMt7/5+1SmYnq4R7J/gO8LEBGj2QJHwuUrm+wdHTCaz6mrCuNLTF5RlDkHpyOkFcynKfNJzv7+mChwKcsS6Z6DZ+gpRBwiogBrz+s6LBYcEHWNNhohBd12RJmHHBwf4kqJdC1GNES9kMZAUVc40qXRNa6SONLDdz2UF4KMSBtBK/ARNLieoEZTlRl5U4C1lJUGJ8QLI6xuCKTGNhW2dBBCY40mS1PAUlQ52jRUTUNZNFSlRggJQtDUJem8wOocRzlkFXT6q/R6faLA4Wx0hDGGOJYYz6PTcpHKktUlx2cTHtvq0g4DhsMQ6UiEPJemNtqSFQm1run6Abg/PG2yCfzDh7y3A/xv1tr/SwjxlYfALoBXgH/v4fm/x7lM8DbnUsF/5y9bwGLIrMQqw72jktUrGcqN6Lkhd46OaK8pXOXjGLgYuAR+m73FBFtb3J6HG1i2NjY5vpOhg5za8cnrBCd0uP74KsrTKKPwdY/x3QVImI5rxvOCKhVUEt67l51fZeqas5nBiJqgCPBd0KJhOp0zmVm0zri4EkMKRZER9SRC1Swo6fcHtMdLHhxOOD2dEQQR165u8PIr99lYCdi81mf/YMbLb51hHYOUZ3Rih51ejCDBkxFNM2O6yMhryUY3OI9ZOxyx0ovRxYLHrjzJ7331DY4nx/z0Jz9CL1zhB9//Pl//2kvnqezDNdY3Ik5PxtQyY+PCGuuizfL7b2Dbiqw4Lyt3zLlLndQhX3j5kK+9ccALV/r82q9+li988WX2kjPePZgSRxAGLlkGnW5MVhky4fCDm0f86k88yQfuPMJ7ew9Y6/R569aUeWWpswwbN2wHIe24QycOUdIQuR6NsXzjxZcZxD6rG6/zi3/943iu5I33XsVp54Suxe9ELIscIQTt4YDaWhJd4UqPVd/lvfGUuwdjnnn8KsvlgiAOMY1GN4ayrEmTAt1VOLZkvsyIg5CqqDBpQSfwkcAyt9jIcvPOIRklbRmijKDtS564scNbtx+wMhzwwacucPdon+NxyWxq+IMvfoPPfE6iTM2ffP1PeOZ9TxF4Lr/9ha8QtgMoawaBRHkGV3q4vsB1FY50MLVFuQocwWSxoJI1nWGMbEVM5lOsE+DgIB2FkAJHCnAFpYFWEDA5m/KlL3+XfuwxHPRpORFJkqOkz/XLV+i12lSO4uLli1x+9Cq7l1dwfEVZGtKDE3b7Lv33XaS2DVVSUdUF6Irvf+VLFPOUSdIQhS5XdjeobUJdV2yvDphMU0I/YN6k2KJC4VMUOUXTUFclw+EqvusSxzGOY1gZdum0Q4pCUDY5ge8SeG2kq2i0Pt9V6JrlfEI2OsKx0FhBtpxTlxW+62JMQ+hBZTTzIidtBLVRRG50XhvRahMEDmVTMV3OSdIRrnLpdlooAaHvghA4DniuiwAsDjIQVGmNcj3qskSEAcpUhIF37gluDVpX1E1B2WTkWYbj+DjSIQ4laZYQhBLleHjKpdY19TzlYP8WgarxVwfky4RlViGUYjEdMR5PQBiyqmD/bMJhMkAuZrRDH8/zyIuCZZaRJAmtKMAPfJa6ICmXPxx4W2tfA577V/R/4s853wL/4V82759tdWXICs39vTG7G13emxzx6MbTHOwdsNXvUYgcmnNHsjKbMzk9w7ElUd9nrmvKacPdk5LC8RglDUYUID3Cts/RvSlX17v4bUVqM/LGkGeCo9MEUwhq0YB2OD7LUY7BxcfoiqbxsEJjraLJSvYOU3SjuHqhw2C1jbvM6Q+GHKQpWdNQu/D6W/eYzR3qVOP1YtqtFpOzGe975jKeFBhp2Lmww73jilmyACN45JENYlcRRgFpGjJqJhyMUjbX23Q7HpEYkuYT1vs+yVHC8vCAuNViuS85GB1Q9TwuPvokXZVzOYoIuz1i5bAuXSb6jO/cGqFZsNKPWAm6fOfFBzheha8UjnPu9exjWFbw4t0Z1e//C37yhadZVhf5e1/4Glo3vHtrjOtUXLvSZW2lzWR+zGyh+KNvvcpHn32a0eSYX/ipz/Abv/O7hF6FtIplUrOQiqZbI2yA67i4CnwVUDWWvK74xre/y3yW8HOf+RDrL67yJ299m+2VgDTNaAfQoEiShGZR47s+eycTZq2ArXaE0zc8OJlBmTOf58hGkCQpQS/A9xRNVaF1jXAkzUPzLdsUpNmCorAsiprTswK/LcmOYC8v8KXmaGo4ee09Kms5SM64/eAEFUY0Rc3VtRWuPfMCX/mjb/CJz3wKA/zgey/y3AtP83N/7dP8D//w97BKsBKD8M/9O7QVYB2UI9GOgzEgXJej+ymrV4fcP1xysb9GLBX9KMDfaiHdNtgMR0KpLW7t8dEXfoSD0xOgYbC6wUXp46oQE/S48cQ2EkmkJMrz8FSbuOXQVDURmm5bUimfMhaUWcpyWXBcLPCspqZ5SCFIXNXQ68Q0TU0DhL7i8PgU6XmY0pKnKWErRkqJacAxltWVFXq9Ft12QLvVJlksWUynD7Xfljj0cUzD4t4dsqygNBZcn5W1AZ7Q+EbTbnfIpU/Z6HMnRKVojKGuChAudWlYJguUaBFHXVYGbaoi4WwyZpnn5HmDaSRhEJBlUxzHQSlF4Hp4nocjBUIIlPLxipxaNwgh6XV6mKZA2TbSqchNQVovqcjIqylJmmHtuXMlQpGVKclyQZMWhFLQ7oVoIakrQ20qHhwfYq2hqBp0XVEul9RVcb7jlJa5MZwuZuwfHmCKjCDqEEcBaVmiXJ/ZdMrBMQwGMaYp8d0fUir4/0UzjmD//oKPXNuldgyVyQmUZqu3wmg+ZrZIWegzvJ0uR/MRsqnY6A6pXJekMITGQSiXw9mC8bzGcwtkOOB0dsCNjSGhA2ZZY32FXAlQucbGM0yqoXHodBTPPtHHLgr2RhojJMPQ5cmdDi1XM5USXwhkCO97coXJg4y+9tk7njKepcysZkTNyUxQFA6N1uys9xkvE5aLjHcfLIkiRVlWXNpa4dlndnCVRFc5GE27FSGtodOXzNMVZqczpuNjPvrzn0D7ktWOJly4XOqvc2+es9WyyEcvspjlhGqCxOHG45cQbkSezNne3OGlVxYov2RzY5s3377D7u4qk5OUDz+7xv7plNNZiSMlxta01HkxjETx/Zspt/a+xS9/6kn+g899jP/5D7/G5nZM6HZJi4ayMbx9r6DjxqwPe6zHHn/rP/2Pufn2HYosQbmK2bJESXke2WgsVhv+tOjAlZLA8xGtmNl0zPdef508mfOhj3+S1vpP8qU/+BLl8hgCiH0Xx/GwdUao2gwHFlfnFKphuKFYFwF3j0p8JXFdBym7TGcpBDWqMUgZ4zuKDzz9OEIovvbHf0zTWDxb0pZQLzW0HNCWqjFUwqKxqNJSa4dO4OLIgrjnENBm2Pa4dnWNMHqOL3/5y3z6k5/kpe/e5E+++RIf+sj7+W/+k3+bv/sbv0MmEq7urDE9nCArQSPAuj6OkPT7IXFvk5/76BW80BK6PtqVRGFAHEfE7Q7j8RmO7aClQjeSR5+NefL55zmZ5rzy4mvkSUMr7OH5Lo6wYAt8LyIMXWqtafd9okAxuLTJ+PiQs1v3yPOMfjcEBGejMWeTBVWtkZ6HcH1Wt0KMtQz7PZqqoKMUBktVR/h+gEUQ5R5FmVGWOcqTuEJR5glVbhER6Noh6vg4sSJyXHxPgRWIJiMa9BBRjU0LRpMZUauDlgITd7k3Taj1EhdIk/nDdWswlul8jlWKKGgRhn0cqSjqgqapmC9KkqxksSgpshotwHUlURAQxyFhLHHL80Qfx3FwXQelHLSBpjkP7l5d6VEWGXHbB5EwHo+YTec0Rc0iqagb6HS6xK2YwAuZjE6pjUb4DsvbZ4wnBZXWdFoBkjlVpWmHPliJIwOUa6iWC9qx4mxckSSaPC2pS823X3sHED7/5wAAIABJREFUzxUYHKSF61fXKIuMO68dUdWS2SL5C3FTfv7zn/9/H53/kvb5v/1rn3d8l65vuLgyYKu/TkvGTBYppcwRyiWMQlqtIW+/e8juZkTuOpycjdDW0hIuorFUymM8q5CRotOLCLEoL0J7mjwpMY7HeDEnlueOdqEL1y/1ubQT0q5TVroDbt4647Pv3+Rnn79MK4J1d4jDAtGW+K7P0O9wcPOQZd1Q1w7HWY7WELVbnM1riqoh7nhMR0vGs5ysMBgLk1lCUWo8DJQZ3dil03bwfUPguzhS4yhBVZdEUU1LCT7w7HV0IinffJHrVze48fzH+eJXXmJvkeIrhzTLGXYCLm6v8fY77zBaVnzle2+xqDKOj06wjYdWKa4b8Ppb9wk6Hi888yjJuABbcWO3zcZKTJrWaByWVYWvDLNakadTfulzH2Y0Llg0BRtdyeGZ5tU3TzmeF3i6YRh6fPCTH8UtFozHS15/8wGjxZLKOASBR1WmtMOYTuyjXHCEoBW3MAhmy4y0KtncXUEn8PatV3n8xiUevfYU3/rOA2TH55GNgFw7DMMerVjy9v4BRnlYZVnkBisa1oKAUmkSUxFGAUEYMh5l6Nrl/e97jkG7Q8fTfOj9z3DrzgMaKVkWFanROMLjdJwRupLtfkzbC0jyAhl4VJXAV4KnHr3EanfAdqfLB29cILQLLlxaY3ww5vRozCd+8mPsj2q+9a3vcXmnw6c+8gKqcuh7gkvr21zdvcTG6ibCi7BBGxG18VvBw/fDID2PtueirAZds5zPSbMM5UjyJCMvMkTdMD2esphmFFmF7ztIBdZoyiLDUx5C1xTZHCkFYewgKOms9umt91gcn4GxRCoAY1FhQF43eKGPDHykq6irFNexoCsCz6M256oV4YA2FhyJ4zg0TYO14CiXIHCQNDRVRVI1jKZLqrJmcjKiqZbMlyOmsxnLLGG6nNMYaIyl1e6QVTVnk2MWyzllkjM6PMH1QjqtLq1WC0dJGmHRjiUtKvK84t7eMbfuH5DlCVWZU2tNmqSUZU2tLXXTUJYVVVNTVBU4lqIsyYucuqmp64o0y5kvM6oaahGwvTZkMIxwKcnTHCVc6qykyDJOThImkxQrXYracGfvAYus4GyW8uBwydHRlEWmGc1zTG1ZTnNmSYWrXMaLOaeTOcdnCybTBUVVMc00pZaIumY0nlGZ899EWRoC18cVhqSoSZYlvifpdiRvHOZHn//853/9X4Wb/78A77/33/2dz1/orHLreIE0CTc2txFuwL3TMZ5nMFIxWZ7gyxXyZkQ3jDmZLgjbLUwNp2dLjs/mLPKCrLQIbZDasrs7xBGSuqkh9MnygjptGM0T1vsRTzy6ylrLYb3n41URKx3BE7vbDCKHfJKymGcMhiGRo6BtwHXJsxJtXN7Zn3PnaM4kb6jyikIb5nmNF/vQaMrCkhY1FkFVVEgbooEr13rs7uxy89Yh25d7NJUg8H0Wy4bxfE4URygTst4d0PM6HL/8Is98+BmufeynGO5s8djlqxyP56yubxOEgk4QEArB8emCtf6A5599jsmJoduKWF8dsn+wz+XLWxyflrx5a8TdB0fED30ZVoYdlK/YO5xRC4E1NY5VNKbGKp+imvErP/0ZvvbNOxROyiO7K7x3b4rbwLPXhzw4PuXdmzfpRS6rOxf58jffZJ7muEqQFSUaQZk3dFsBnmeQjiLLc+pGM5ku6XSH2Cbn4tYGX/nuTdL5ARstwcc/+XHyWc17t++SNg7DOKDdCrh1PCGWijzPEPI8A1RHAU7QpqkM1oVFmuO7IburQ5555AItWdJ1cnqRx+rGJqdHp+yfzTkrNXneMOyd64abxqXUNVs7Pd7/zDW2+l2euniJv/LEdT71wlN89iPPcuPaFo4bkC5zvLbLfDanE7T58E99mqTw+ca3v8n2is/Hf+Q5Lu7sMBhusLG7Rac7YHNri0GnReRobJmjHEmWN7jSIQwDwjiiqmusFTgqxqWiFzZ0PMH6oE8Y+Pi+S1Fm1HVFWdSUlSbJM0ajCdeu79Dvef83dW/ya+l93vl9fsM7nvHec8e6t0YWWaRIiiIpWfMQ2ZbcVmzBA2wncQMBHAftAJ1FgAABsgkSL7IIkl5kkV2CdNyJLcXu9iDFsSarLVOyREmkOBarijXXnc583vE3ZXG4jI0s0ojyAucPOMB7vud5vs93QNAgZMmNd25xdO8+EZ579485OnqEbcccn51y73hMbQ0uBKqqpm5qvPEE0yLDekuyHhpTYZ1FiPWEb51FRzGN8TjnSeKA0p5FUdO6gBRQLqe01RwTGoqiwBhPa2rackpVLrDBsWprXn3jDrZtKBtDIxKSrEuaDDEOhNYkaUZrGmbLGXVTUxYNy5VhVjnqpsHWDc5ZvLNIJTBh3VAfhKAyjlXVsFiUGOOxxiAEGO9prMcTESc99ra22O5IJrMjpuNTTo9OOLr/iCzJaBpH1VgMgUlR8ePr91nNKxItiZRnYxAz6K1LFhrjaO36mHpytuTO8YLj8YKjkzmPTmqa2hCcIYiE0hgm85Jl7WitxWEpnGFRtxxPK07mFYvGcjKrmRSOo6X9KQfv//a//i8+9/xV7h4vkXHE7iBGA72sS5J2WTQVdCWjqI/OVlgveHiyJO2mnNyZsTKG/sEO87om1TGmsnjjyPqSCI0ya/2sijxPb20h0xQnDT5YlFIUxhCngn7Hc9jtoHzGcT2jOW6Je4JxHUijjFA7ZpWlXcHtu0uWSrA1zNnZ6DG3jrIM1GWD8Qon1wcSEzyRVGhl8SjOJiVnk2MynXL8YEZrWnZ2hlSlpbCW114/odPxfP7DH2f81iu88OlPkg862Luvk117jrtvv8GdB7foDzaoFiXNakpoYx48PGXQF/zKr3yaz/3sz3HvnXdZNCsOtzfoxznfe/MWy5WlrFrGsxVV47l3OufotCTSCb41bHQyjLdYK2mN4879Jfvbjs+/+ALf/tENxsuGO2dj8jzizmmJU5Kqkch6ymOXLnD+0lO8/MO3ELJEq4TWrRUF/SRaF772eiiV09QVSabY3t3lbDZnO415/d0jbr97zNGD+2sX3vufZmv/GvcfztkeJkQq4cfX72Jcy/lRTjU3LIwjJBqtW3pdxaNHBZd39ol9QUc44tCy15H00oi2abl45SLnD84jRUSiYjIhuLo74n3n9/i5D3+Az77wLE8enOOp8+d58tIFrl7e4fxOAhgW0wmT6ZIyKH5y8wGvv3kP71uyRJPLwGNXDxhGPb76l99iWpyy0cu4crjH3sU9Ljz9GKMrB3RjTVNMiBPNYDSg289wZl251jgHBCIMq2XNfFmQasmgmyGiGKFiFrVh0RhqE9ZHWWMwvqZql5yePmQ6P+HW7Xe4/sbbnJydkkQxkZBMizneOLTQFO177exNg7OOWEdMT08JwZMlEq0FKo5pjSXgCWE94ZtmhmtKZtMlAbC2pm4KFvMFxpQYU5Anjlgb0q7Ge0fbro+iTbOeZAUti2XNclVx7+EJG9u7RGlKVTuybJP+cIud7U16/ZQ0jeikKXEkmIzHlFVgvGixQoEISDzOBdr3JHzGeBrjqW1Yf1pH4wW1MTSNpSgNs2XNeFkyW1YIofnYh68x2O7yv//pS9x7cEwsBFor5kVNaSzLumHeCE6mNd5ZskiSd3KOxktWC8N8VrOq1lV1IQQaY4hivd4IWoikoJcGvFprzMHRTxT72zFNG3NmHJUNxGhaC9PGY5yidApLYN4ElrX7e8H7p4Lzbq3hwobi00/t891Hd/nrtx7wy586JExKAgvOJT1q6UhTRTEH7yybmzk0liA1som5d/uIwlq2BgmNaTm330P4mCb2SBKkK0mc5M7JFJ33WRnHXi+nWbVkQ02uFKqMGFc1D8ZnnDWGOEp5dDamBbbnmt6gS+4EzgfyBFycsvvYgGq24NzmkOl8jCBBBJi2LVoIUAphJcb7dY6xDVw7OGRrW691qHFKUddsbm+xum2YzVbUcca9V65z9dLj1GfHTMdnhH5CrwVXw/65J7h/9xVeeN9zbI0Sut0e26/vs6hX/Oi7L/HxjwmuPtFj8sMpW6njcP8Q2QZQDpzCWE8tKjQxS9MSxTWRUpTzCq0jIh3QWJwI/NlfvcJ/+jvn+b1f+QW+e+MHLGvHydEcFQzzxnG42ac32uZLf/wnfPGLX+C3vviLfOlPvkmjThimio1ujtSS0e4eURSwxoL0TMYzrr/zkHwrodk7YH805J3WMo0jvv3qT5gsal54/wf4zc99gsXqFCElwzgjiTPuPYLGJeyeS8h7MUf3xjQh8MT+ExykCWXp2Bz0ScWaooqSLlkkObt3C1TMJ5474NmrW+sfHZLNrX3KuqW2lqzRKKnxYU1rVHWNdQ6hu7x79xGT6QLnFU898TgHe10iwC6WzJZTtjdbfvWLH+WrX/shN9/5G5598jo7+4c8/uRVRlcep1kseXj0EK0jGuew1rEs6rUcMorw1rDRiel2BUmvjwuGaVVjljUyXkcRN+WKcrlCiXWVn1lWzJZnvP32CWVpKAy0leH9j+8S3B1k1KVyhr1ej7ataJsagSBSAWtaTNOyOewggEQFhLc0q9n6PpFonPcgFKVpMXXFbLKCWCKlp6zmaz115FnMSoIZvscpG0JQFFWN84GAIEs1zgtUHpF4eP79VzFB0NiWNFOMtoaMNgfkUUBKRV1bVk2FayyRSkA4oCaTnuADpRVY3xKCQ1QOHyS191TW4dy6nctYEA0kkSRSDTaA8wopPW17nz/4o79ECMNitqSuNbO5Z3Orw7KoEFIzXlQcTwoQ0I0kc+eZFKfUraUbJfRVwNsW66F1giA0tvXw3mHaakmkFDIIjhYlmUgZdRJ2Es3lp1O+9QOLSiJ0vGKjl6OmARlDFmt28xQtBV/6u5O/Fzd/KsBbS80ylDxxNeHatefoxZuIAIsMpm2gq1pSJwllwxO9C8ybgqP6iOACm+d63L21pG0ERSkpVwX9WLCqI8qzMb1hlzSBZ4a7HBUFZ6XhtR/dZ38XNnwgSvrr1ukQaF1NLBMi3WV28wFR3+NKQRpBM4wRZUOzMszmBUsC1jteeeURaVBcuZKA88yMIQmC4CIkDhk8/a5GOKhthKPCRILSwv0bYzaGkqAlKmpAR1zYHPDcdsqzH77ApSsf4a2vfw3nBPtXP8zq6DpaVDz79GV8OeHtO29z61bJY+f2oUywyxXfePM6b719h6yb88SVx3BWcX9+zO/+xq/wtz94mU9/6tOU0wUP7j3k8uEG1sl1DkWc8Iff+Fveffhwfe13gRAM8XCPP/raD/mnv/Z5bt8/pF3dobQt1gdGpWYYQesi/vbtEy58/xV+/vMfhfbj/PFXvoGOWy5euEDAURaew70RVlvalSfVDu3BVYpXXr/F5fPnqLUkSyKK2YTv/fB17t65y9OPXeW5D36QLE75Dz7/SbQORHIdcbpwEUFAvfsYpyczHrt8kScvn6d48IizyRlu8YiD3S4xDq09q6ZmvqwpW0FrBauqZefiZWaNo23tGrRdSwgtUaxw3vHquyfcO5riWkumFJfOH7C9s8WoL4mVYNDdoKgmPHg0BhHRtoYXPvAML//kTf7say/x8598lk43sCoX+Bq0UgQpOH10Rlk3CKHo5hmrZYGOFQaF8Q1EUDct88ZR1w2VMTRtSy4EwnmSVFHVC5bLBbZx2AqaJuG0WqsUbKtYTeaMJ2NUHLEE8ljiQ8AYj1AaYx1NWxFYOxK1CGsrvnN4a9ecsVnn7DTG09QzQOBrR9sYbKjxQa7pH5lQVZ4kifAYvK+xocEBAk1pA6YM66A2BbZZYAk0JrBYVCRxh82+ZlmuGE/GVG3Ncr6gWJU4D2VVkUWaRAtmVcPSCqRwhCAQIrxnLFtvCt4DYs3HSxGhBQx6Cd57liuL1opeCj5qmD1a0e8nVL7kwcRwVq5wXmAaT+0EQmsi5dcgbC2xAmSEs4HSAirHBUsvS0kiicTTeEGQknOjDod7HWxTcaUYYkPCpVGXjbxDp78iEZqv//iYZZswH9cIrxABRPCskhxp2n8YN/+NI/P/k0cHXJozL+b0hwNm5RGZSohJ2c0HKC0JZBSzlkGmaU3FKOpSbynsZMVgK0OfWky1rjM6HA44O5mzd2lIaBWn84LXjo6I+go87F/o8MReF7lqKaoFmYZObx3tmMSKyXxFoWJmk4rKSa4c5PQ6CZO7U6pYkY86uIVFuphOV9LMoGpbhr2Yqgq4AjJhMASiOGV/FHFplDNrAq/fNty4M2F7o8tWPiCNA7cfTrh/+xGPj3KeOezzoU99nNW9M5bn7/D4F/8xQXnu/eRljD9j7+o1/vybP+Qv//a7IODcpmJ3r0vS3eD5xzf4hZ//PF/79nd4694Dzu8VRMmQ127O+LlfeIaf+eBj/OGf/TmrcsnORoc3j8fceHdC62qM9ZzNW4JYlxb44PFW8uO3Tngr9owGX+MLL36ar373OtPiiGVd0niPEZ5ivmRiDCel4Kt/8RLPP/8E+1ufoHaBuJMhvaefJyTp+qU/vzWgrBtqE+GRSF8Cng/0E4bdnNl4jFcJ3//x99lZnVD7gjRO2drKmU2m3F8Y4k7G+e1t7t55gGkqklhQFqdMZ5LHnrzE+c1nuP83f03hCxZVgy1aikYSsg4uiwheMhhtsWwabNuQxBLvappiiowSqsrR+oiXXrlLv9Pnym6fQabodxOyVDDs5gRXUZZLppMJi/KMKInpdPoIKdBRSyUUL/3kbSZtw7PXniKJMvK0RxRLsiyiKgssltqs44OTOKGua4zzQIsUlqIsmExX1I3BtJZltLZ9+3L9hyNVRDfPmXVKTssSraGTaaqmYu4F+WzK9kafRrh1rotx1JXHonChpaoqEp3gvEUrhfUGx9pubkyLkBJCQTAGpQNVZalqA3hMMKxKS/CSUT/mYCMlUZpFVbGoLbOyonGB8VlBL+8SScHDk2O6G13yzFPVLY2RLOYl79494+3rfc7vbTBfLTmezmkLh/Kgs4TWWqJIURtH68K6JUhKvPcoGVAqEFqPVgqn1rpxESRS+LVBp4FRL0MiMM4jZbS2xXvNo2OHjFIQDhUJkihmZmuSSICAYAUhkhSNRBtBv99j0El5fL/H1mafhycnnNveJI/AestZVRO0pJ8ItrZ3WCxnhBaWK0OWKuJhYGUT9HDFs08NeePmGcsWGuOJfIQ1NfPGMOz+w/D80wHeDs7uTjl/bkCmHasmMJ5P2O6cY7lsSLSlM9xCSceD+Zxu1EIhedie4FYCFTyb/YTdnQFRR2GLAtXpop0m4Dg+8jQjw2EQ5Dpiv59wJY3xnS51xzCSOXcePmBDdZmvKpJthXokMY3CJ5JKwmy8QFaSWV3RSQPL+XpabxYlLz6/z2MX+twSc05utCgfGHQzyuA5XbRMz2o+9+I53rpZEExLMbE8fXmbza5k0QSqecnHDze4tL3Bhz/5PKaasDqb0xYNqxt/Rv/KiNXtM46SU+Rhn2+89Lds7Y64fJhhvOKNtx9x4bEMc9sy2tll/7BLJHdIVY8H906ZjRf8+Ve+ycFgyA+/f483pkuELglGo9AYYYmlxAWJ8xIlII0jwJB2c5ra8Cd//S4vPPUY//lv/zL/9L/755SiRQiYrwTzrmBZKG4en3K+C++86bh85Sp101AsZ0itWLVz4u0hwZT0MoGpV3T7A4SAetnidIwWOSFyTGzBndt3SYddFs2SO0c3EdphCcjRPpo5TnlunT6klg2n8zOiOOel773OvVsdJo89wXCri6in3HzwkDQf4EjpbeyRpjleBNrxnGI1o24bokSjRESUJHR7HVSkQWmmE8OFzSHPPnmezY5gMl+h44g47iJUlyh4VsWYebHAC4/wgtlshk4yHh1PQAlOJy35vTGHuws6uaM2LVGhWa2mGFfRGodUClHUtFWEC4Gyajk6Pqbf7axdk0qwsTOiqmqMa5jPTyjqeh37S8DjqEyLxZNFmk4eUXiBx7O4dZ/Fdocsz8iSmNPJguAVjXGgPFppBBLhLctFiVWaIB0urPnwdQmyx1UWr1pKqxBOsL2RYrxgVVvKlWE2r7CN4FMfeIKA563bU8Zlie7lyH6X4/GSi9tDUJ6z2ZI9mZLnimpWsawD1jnK8pT7D6cQJwRnqMuAFAq3WuKDIJGGyoANgVivqR+kIMsUnX7EyXFFnqg1/+08bRshdCCKJVquy8k3ejm9fk530MW1DZfO7XB6tGS5CnhpGI06tO9lmwTl1uFYQlOWNQfbXQ5HPbYHOXvbm8RJBJF8r/XJ4uKEJIlRiwaRRmuhRVPQHXSoqortjR7TsuL6acF4XhKnkqce3yYfaO48mFOVgdYasjTDtJI8E/8gbP5UgHdrHd2+AFEQdA4YDg8uszqdk6YRd6YTdjoZvY0O04c1t6qWt67PaISliAK7qSRTMdPFjNxrDrdHyFnA1yt6gx26uiY0LatW0QmghceqBN911HXFvTPDsg6M/Yxl46CV6G7Mpd2U+djQGompFWnXszEY8ub1OSpRNHULPsXVLdnKc2W/j3OBWzdnzMoSB8RpRKsUp8uCom1J4wTTWF5/9yFxa4nQXMklLzy5zRd+7z/i9LsPufPmd+ludHFTx+mNWwyfusKifIMbj8acvvOXPPtMzmJqeff+ktpb3ro75tLJlI899wTf+vZ3uHrpAp/6wifYfurD/ODvXmNSw8mjtxntdfndX/0s//2ffgXnR7Q28GgxQxoPWYIINVIqnJPU1pArxbCTcvNkhQuW3/8fv8Hv/17Of/xrn+G/+l/+jCoErJU4GdBeo3zJU088xcVz20RRimk9aSIQCuI0o6prNIHJYoEJAmUa4jjBSY9LJK/cuMXSzhHaoXsR739in1RYHsyPQCviqEMsSpbNjNo1FKbibDxhuVjx6k+OEcHRuoynr/VZHLc0IaW/vYPWXYTOidIYhCEEQ2+YoFtJEhTeW6ytiJ0n+JbgNc5LdkcJv/TZa8RKslouiCLJ5cNzHOwc0N0Z4u2CO9dfIyrnLJcGb8AHxQ9eeYNZZRBCE2cxKpU8PL3PRneIVhJr35PgsY4yLgpBowqkhKpp35O7NRS1piksF8+fZzYbM52NERKW8wWt93TyLkVZM1uWazpACroJyKbE6oi02+fh/SUnZ3OSTkaiPVplCOlYTJdIneGVRSUe3zqqlae0Gh0pllVLLCVZqlkuW4wQ9PqaplF0ZCCJNMuqprWeJE0xCGo0rTcUziC0o0QyUJ7hKCHIiOmyJEoVW8MYFSR53qE/ShDxnLt3A1Mv0S6gyoo8idcmvGmJ9hHCOVopQHiUACUlwfv3OGbPZieHYNjZ7mIaR91KgvAMugmdjiZOFZGOGWQxo2EXHUOncwCqJXv2IqCZNyV1qOinKYtpxaOzFajAxjCjKkviKGez36GbRcwXBbNmRTfNiLc0y0lBYRo2ki5RR9JgKIyhKpdcyHbZ2O7RGkuuc0ZRjIwFSgp0Ar0BPNXbJJICFyRKSB7cHjPsD/jaDyZ/L27+VIB3HEmGO100nmHUxcUNOlUsPWhWnN89RMeaYrHWiv7onQlL47C2ZmOzR7fbJ5KWjY0B26McX1ps3lK0EUJ5TouCctFycSlZdgxPbuxR2gWq0ETCMzldsrfTwyQBWdYkqeK50QaRM2w9scF33rnHKN3Anp1wZ9qsk8ZaQWTh8oUuVy+OGMQ59WTGZq45G2QsxwUbSUTjPJVxvPzWKcuVwFYt/Txhj4yNnmUnHXF4mLCXx9z4yh/w/n//v2T3mStEO5obf/US/YNzqHiHl955l2R3A6FqfAhIGRjPJrx+r+RwsM1nP/IRdi/t8odf/jLfffXHCD3nFz/8IfZ2+1zdTzi+7Xn31g1+43Nb/NYnPsjbiwe8c2/Fqi2YmwZhPZf3tjk+W2CD59L+Bs9cO4dUMU9cPOCvvvVjHpy2/Df/81/w+7/zm/zmp36Gv3j1FbrDmI0s49d+7gU+8ESPw60Nzl88ZDZesnEw5M3r19FaQ6Qx3q+lcGlKXdd4DItVzfGy4pUfvQVpwvYoRsqSi1f7mHqJkJrTsqCNNSkSV1mapqQVDa20VN7hO4E2Vmxv9HC55gc375HYPskg5tx+QiokmQJ8CYCxDVLGLMsFrajwoQXnqQuIdU5lPVGsWC4VmgitPM7CRr/Lub0hw51N0scfx7k5F8oZ129f52h8TKQl9x/OaWUfrxRRvA7ykJHg4fiU0/Gcfp6TpRlKCuJY07QlLoC1JUmSUJXQti1F3bCoLAd7+xTFgratSBK9lsk5T2McRTEm0glV6ZitDK0MNE7SSRKgwS0W0BdUU8V4UrE9igjNikiCTLrMq3Wc6ezUkGlJJGOWdcUwU+SdGEGgqCuIFGmuiDNFNlBs9jTG1mwf9GjqghAcRavZPzditLPHN3/0NrcnNVs7MUQeoQJb25vcK2aUleX8oIsPLePlGVHZJSXnhacyTo7mXBp2GG7k3J6v1i7Rg5SHdyvapqVuWno9TZRG1E3z3h+hRicStCPKFflIUZeWxXGFdwpCTiRjdCyRqcXGHiMladyhpSJomC4mZGmH1lWoTsTCVGSbHfb7jlU5Q6hAN4sIwbNigfUakwfSrkYnAYlkM+5RFQ3boz6GnMlyQZakJOkOtmlwal1VuDoek3RgK5VECtJE0AhF20rwnp20S7/X4bnDXVzt+B945+/FzZ8K8BbAhkjpZB3aRqCsJvYZUU/ifUA0LcIHEqHJYsGTV3aYGsPZ6ZJnr3TobqbkUUrTOLyTRKlkq9NDqDOW5ZjPfPQC4+OCe6czolby0qsPSHqOj7z4GEcnSxbtiuqkpbPTo99N6A0HbC4cu+d2uX0y4XAoWc4m7I9GTN6ekISSYZby73zug/S7G9yY38Y2DlFo0hDwsWR/t8cz2wNMYzhqDQOVMg0LummGlJZzlrMmAAAgAElEQVQLo4TnP/Q0Tz35C7z+zT/B2oCM+py88jecfOfrjC5scvVz/yGnN/+Ov/nO93n19kNe2N3gdDxmOjOcPzfkE89/mI8+HnPx3IB/9Xff55UvfRUtBWUbM/mffsz85J/h84QDYp59aov+4IA/felltMt4690zTk/m0KxNRN4H3rhzRBLFHG53OLffo2lOObd7no1BzOF2xqNpwet3Sv7PH77KL37mZ5jVj/DG8b6rXWS2T6yWVHXL9evvsKiX5HFE3PPoTNCEislqBhZM1dBKQZKtZVe3Hy45vHRItwNar5jPlyBjKtkwXq5QSrCoZqi4y872iDfuTChdg23rdd57r8vlp/rrogxpGDtNJwt04zkLIxBRH5xdg2XdYoLFm5ppOeFo+RChPXmUksqURLaUxmBWAkxErjsMuxnbW5uMNoYYN8XpjPLeMfPjU8rpgtG5LrdnAYJkMYcnX9xmVSxRKiIYwcHuLjcf3uXhdEK6XDHo5qgQiLQk6SgW84I4TYkcbAxHXBpt89LLP2JVlsRpTOwEZblCRYrpbEVdtbTeU64ahDDMG4sX60zBZetZVO3a2XpScHh5yNm0QmeexkV89ENXefede8yaivPnO0zmDV5r+h1FWwgaulSVw2Po92OiLMN5td6gfGB7L0dJy9Ygp9/JiKIuaSfl/sMzPCU3H91hUs8ZbOWE3PPYTp8oJBytJuzs99FBIuPAfOLoJH12dmNC4+gnfa493mNRLsG0vH93iEoky8KQZ5LlIl5zzxiSToSKuyitSGJNnCaU7Yp+PyJJPL3ekDxvaRuHjiVJV9LrKLaGOUoZNocpwRp8MKysYWt7k243ozJwupgQpOe0nBKpmMGwT/AtWnskioAi7cSUdU0aRygEcZzSMZYwzImlRBrYHnWREhBu3YokPKtmjO6t9ei9aC2HXq1WpInCtg4rPLfPjoiL9ffw1T+Mmz8V4E2QOK05WZ7Sk3s0hWMRP0JbSeskTXBIHVHULR5L1nX0ugmXtlN6XUltIiZnE3ZHm9QYhPZI2XJ5b5dJvUJoR9ZPUCc9HswLmkLx9F6Pd+/NaAlsHe5SnKzwJzVmlDFZnJDpDd649YCHYUmvUhArllFgUZZ85vkP8psf+QBaL9l+30d58qihvnudYuuYKHE8dfOYKIZNDVVT8+54RlNVXDrc4Pln3s/quEG7E5598WfZe9+LTG+8y2z8Ov29XeZv32RmBMPeJjd/8E2+97W/4Cjd4uJTV8izhNHGDp2kZjvu8uHHDzB2xZsPjvjY4xf5/AtPolPBonBob3j8ymXeevMOzcBxOOqzsSG5f3vI9954SNxKPnP5Kt968w6Dfsz9ZU2uBU9fOeBDz1xC+JLxYoLWEd/7yQPiJEJLjdSer3z7TX7m+Sv8wr/1IebFnCyL6PQkte+xNcwwfsn923dYtoHQtGS+Q+0MlWnQIkJFEdP5itnxmLqB8+d3GW0LhF4yKwv6G5skShJEjuxrlJTgNf18xKOj43V2hdfs9s8xKaZM5wW9nkILSZ4MmC9LmrgidpraVggREEZga48xltliTqxj5k1LE1nwChsqitqyFfeo6owLB0+xtZERJwZcS0RLG6a8ffeMsx9+F600ZVFz9/iYk0lJ0o3Io4YPvHiV7cMNEOtMcWkjumnE3G5SeciSDrU3ZLEiyiNaWvp7Gzjj2NzokeegOoYnr12g9YLT0ynzRcPmoM+ymOEjiOOE2CsmsxqhJadFg1QxURAkkcRKz2gjZTppsHXF9na+LqLOUiIFTz5xwGu3Tzk+WnHp8j77uzWdNOfB3RmdgSfNNA2KJIvReh2/G4Ris58jlaeTdOn2NP1hByFgsVixOcq4++4jBoPAMy/uMVm19JKYJHgOtjpkpwapc5JEIRNJuCKQeISHumrQaUwaC3RmcUjySGFbSU9pdOzZ3M6oVhZnUoQOEDmkUKRJoNfRjBhSVEsgQhKTKagbT916hAg44ziarBDKMWsNPgTyLEMlGhUaUqGxGHp5jmssWRKDsChvifMc5xxZktDYtTdEqvUmKeNkvQlrgXWeom3Ae5wIaASRFjhXIVWEYx2/sCxrKuGJlUcIiY48vZ7EWEsaxdTO4KQg6P8fcN7OeyaTijTVPJqccbY6ZShyEtOh34mQMmUyPqMgojZjsk5M1Fp8BL1ki6Y542B3RKoi7t85Je0mDLqajjD4VnO7nVN5xZ3bE4Z9SXeQ8eihQcUNj13u4eaWxfGKNIOmF2Paimp7RHHWclQ7ulsp8weOv3twj9/4d3+N3/qtX0WvAp6KeHubi4cT3p4+opy/zrWPfYTPPf1R2ruvs/HkNcbvHLH58AGTasJmJ+PKtQOyj12jbFoqM+b6v/pnXPyVXyf51326Fy5x8safIEzN5vs+yav/4s/5zo0ZP350j81Rwvj0lGcuX+KDH3iCd96+wVt3b2GsYzjscft0wsm9tzEyMCk9wTS8eeM1toY5D6cJUuXsnI4Znsv4wqVrZHnMhVjzy5+9ShxpTpdzKpvhXIPQgmWVYxclx7fn3Lh+Rmezx7PX+kznMw72t7kzPuLy4TmEbzApZCNLXTUc13NWzZSTZrFec3XKYjFFZSlx1sE6mFcVy7ZkuDNAR4pzOwMaW2BFQuoCWkkWixXbG1tIW9JUBtF4Vn6JSyLwgu3NLey8YXNzC7dYoAl0uglVXXGws0mUpFjr1txqklK1FdYa4jhic7CJEArRtdRTi7PQOEGmI0To8G9/5lNcOn+eo0c3+dFbL2Op2UxTWm+ZtjVGBYq25LSYEm93uHQwoK5aDna26OcxtVuyuZMihEfLmM1OF6JNdvZ6KCK6ccx0NUEKj486BBzKJ7R1zWrVcufRKRd3L4BpGXQzdCu5cuUSs/kxm7ampQWvUAmIOKE7z1mVnlwrbNMSlGC0pTl3OFpPz3FNUVs6WUqcaIaDiI/u9xnPFsRSEekILyKyziadPIPQMi8KitoQJyliI2FVrifWSAWE0Aw3c2KxVmZ0dnO8b9jq7SGVpR8y9qwizxNsU9KJE0Y723gXsM7jvUXHERpNLDUORxMadKKI1S7LYoFUEXVpaJqWsLL4piGREtOuD7RRGpMnOcNeh34n5/j4BJWmeCuoq5rGtOuDrvOURYPPNHGsSVVCtWjXngtf05M5RI6qrCjaAu8FCoV3Dh1FKKUpG4PSgsZaHAL7npY8jTXSg3UO6yxIScDhgydSGu8Es7LCS818VmPaliRa955a7+h2UryzeLN+d61RhKDpaSjKgnyY/IO4KdYhgP/fPgejbvjPfv1T+FDRtIrx6ozOZp9RtkUxeQgyYmt/xDt3zxiMFmgjeXhccuwNaRrYyKB4ZNnc1Ay3N7j/aMlhR9Pr9rl5vGAaOfa7Pa7/6C6NirjxqKJsLb2u4NnntlAWjt6dM6s8sq/Y3U5Ji5aNcx1Wq5Y90eHmacHHn9zjt//Jb2NuNUTDY4af/ce4GwsevvQl5O5Fvv7lr9NXD/jUr/8joos/z+zkPt1uAA5495vfYHRtk2QwJO3nnLw+5c53/5jSOPqZ4Mpnf4Z87zM8+tbX6T/1JJPyHl/+4+9w494t7s4Mm72Uf/Lv/RrUDX/01a9SKugozeWDTRrv+e6PbpIoSevBElEtWkLwjHoxs0XJtHRc2s5YVg1SScrScfXSNlnTUAfIssCHPniNfqoYxpp+1mHz3CFRvklcLSFuOZrNkTJisjjBxAKvFdY1tLZGx5LpssAZS6+f0XpPU1l6cYaSARc8G4NNFkVB2bR0sgwlAk5aoihGSoVpDSIoojhiMZsjASsdsVcM0x7TqiDrdXGuJRv0CI2jrJcY53H1WpuddRLKoibSKXv5JqJpCHhUqpmVS2zbIEVGv7vFWXGGiBU4Q+MilLTce3PGfn+Dqxd3OVkeUVETZ5pulJLEObOmJk0ilsWCNhjKtqLf62A9yLDurUyzDklQWFOu5ZKJInhDg8OHQCJinA+sZktUktDJc1LdoSyWlHWF95JRf5vx9BQtNNZ6IhWxvTXiZPoIpxz93gBjHIt6RTUrGAz6WBraxhJnfc7GU9IkInjLcCMiCIGxilSndON1u4+LHGW97uFUOqJsl0glcM4x6HZZFhU6jvHOsZwv6aYpaZziXEBqT9RGRCohHia0zYrgNSIKuOBIVI4AbGNQDtI4wXpPkGItR3SeOE4YdHs0piLJNFVd0ZgGoQTBS6yRrIoVxliqqmG1rGlaTxCeIBxpkqJYO0AdDusFymuCDTjnmc9LytoREAThybOULIrp5glSexrXkCYRWapIsgjEGlSNW6tftI6RAdACBfj3MtajSBPrdZiYsw6BpGoavPMoCQRIoxg8FHVBYdYBV5EM5KkmzTVNa/FO4R0oJaibCiXFOklQeHS0Vhn9zn/y8sshhA/+3+HmT8XkLYHQlGT9Lrce3CPLJfOTY849tsnYQ6QCsY6IsOimZaezS3e3Q7k8Yzyp6ISEOAHV71CXBU9v7XB3seB4/ogqy3j1jRk/qSY8OmoQeUWqNY/vd8gyydn9mvGyYLVwiEii5oLTozkiCC63FmUVQUd84TO/xEc7lubmOyynQ9xbb9Pf+BocPs9qmlDPvs3V517k5g+OePcnr3F540Ve/9/+AOKKS089xqVPfIDx7YIb3/6XdIeBa//od7n/coa0FcZF1PPAxt6UK1/8HP/Hv/hf+fGPvkf//D7v37zK07Xl488/x/dee5lvvfYmd+7VXL3Y44UP7jPIO5xNKva2tzg4pzg7q3nsfZv8+Hv3WdYOH6C3lbHTSVDGkI1iLl3ZZ3xWcLATYUtJ2aaMNjNCH6pE8HAyZX/QZ24McTPDN1OqeoELBV2REYY1lgQvLRt5n6JKyNOcbrfBYwlY2sYQ92K0ktTVijjJyBOBt5LtwTYgKesK48E5hwiSncGIEDxCKWIgiRSrpsbW7XoyiRxZHpPIjMZZvAzUCLp5StzJmRcLlFQkSUQcRUwnp/QGPVwICOfQcUakM4wLFKagdZZESJx3ZFmMc5LRXoTUllfvvU7eX3cbahWBkjTGoNUaZGxwqEiR6wwR1r/YXt7B1g3Weuq2IfiaQKA2Cb04wbmGom1ohUWh6HU3iNOYKEpRQZPnFofh8sY5IpUilcGr90AjeFZ2isokBIF1hiyL8TJBtg5vHNYEvFDYYNjbGZHGIElQsaH1oL0gzyRm1RALhYpiJAJroNvtkIWIqi6RCLq9mLwb0zYtcZLTyTW+tWihUCrCewOsV31ahdYJrWkRIaKTdpAEnPWYpqWbdylXS4wUhDRCxQLj183xwUHdFmgLWum18sh6vAk0jaMNBmM9eEmWpGjpEQSCt1jjiOIYJ/2aBokiXOVROqJwFSoTREgQita21KYm+PUBVViDFWtFSgiCNngQ62OxihXWQWMMSgoUEh0EsYrwHsqqwcXrvHAlBNiWSIh1K7uDoARVWTHsdREyQYcIjKGTKsaLEttKfLCgIvIkw9qGXrdDCJ5EJQjpsd4g5f8LHZb/xh8hUFGCs4rTVUs5X7CdeVxZczDaZVnVFIsWK1pWMmIoGqwzbEQZshfoJRKRBoq2pitjLCtcbPnhqxXDc54reykvvzZm5RVD4dGRZyIEXdNw76jFKYUgQhqDtJY0iaga+Mn1lq2tPr/0yz/LJx83nPvwr6JFzPgrf4E1Fbf+6q/Z/uAxFz70Av/6S29x4cUT3vfspzDTCau2oa5aTFXx7uvvYJWiN/wAxscU8xW+eUhv8zx6eoLYThjsPs2r//KfIw4P+Oq3Xmbn4pDxrOTqwR7PvP8pvvyNv+Tm/TGbWcbFF87x2ONDrK1xyhLFBdce7zDYzTi8IokTzUc/dpmyahhuDfEOju4fcfXaDqYxbA5SYrXLvCiQ+T5pnFEvFmR9jceyuTMAlqyqM4a6S5xl+NbTRJqibrC+QCeBZVUhrUNFCVUxReqYVVUQbEukYxpnaJxDxuCVo/F2nX/sDDrStGG94gfhUTEYGirToIzChQaFQgtB3Mmo/XqyblyD1hmmafHB0+v28WEd7m+9pzANmYjJ05RZ33JUzdBCkUbp2nnnBFmeICRkIqH1nqA1q3aFVhndrQSJQImI7qBDN02JdUJoWwb9AYuqpMBg0bTGoJMYfABnmc2mJDpm0VZEaYc4SgnGEwdNN+4gjKauoR9lSBkhpUNGkhAsnkAcx+gm4/7ZmCzpYGTA2zXNEGUa45r1kS6J8KaCIEiiiGi3u87XnoKONOlGBx3HtKsVxWyF6gq6gw1kYwm+XTe0aEVVt8RJRCQdq2pON++QROvpdFWUCGDY3cDYhiTJsMKQRilpktGUNSFeT7jWOZp6ncUdgqKtPL1OQm1KskGP4+WMvJdjvaPxDar1/xdzbxZrXZred/3eYc17PuM3D1XVXe0eqt2N3TZt485gd2wn2CDAJhBAishtJMSg3HEBElwBEhIQKRcMEpZihRAEkrGJHQI4Njbutru7uqurq775fGfY817TO3KxPllCgraRc+F9c/Y6Z+0l7aO1n/2+z/P//39IPJ0xWNeS50No26HeIYSgyFKUFgjv8K5DKIlKBAGHllClCdZGFBm99UipiT4QwvDl3lmH0JAJRZamWOPJQ0rdO5wY7ts0l3gRCQF66wltR5omJErQ7TuSNCOIQPQR6yKJHGKHJYpJOSZRkkQIqjRF6QDRo3LJ7tDSA6rI8IDMCnarFbMiw9keoTJCzFEyASEp8hS8IMkU++0WEe2Q/6404Y/oivyxi/cbks7vAC9jjH9RCPEI+CXgiIEs/1dijEYIkQH/FfBFYAn8Qozxyfe7tpTgbY/IEiqdUOZzjiew2zWMqshkPOHq+oqoAobIB/sl0WVs/Y7FdMKqtfS7nkKWbKuWf/C11yxOEmbHJUkWubmKuAi3z3Jcb7hZGppXW05PU5yOBOMxITLSEhNT6r1HePihz/8A/9a/9nPcwXD8+JRkdg/hnnN6+xE366f41vPiH/4Ob//CJ7h19ogPf/u3+NF/4V+h6xsKkaCLlK7THGxg+fKCe1/4MtNvzWlqC8Lz+Cd/GhFrksWC3/0f/h7fvr5EGcmP/cR7rOtnfOrtR2Sy4g9e/h6f+PwxX/ryYxrbk+WCcaI4mByH52g+QwqN84HFfEzbOzga0ZgarSRCwGxxzGyUI+KY4CTQUuaB1u1o4orpZE7f9IgyAQS9tUMhBvLEcOgNaSa5vZhztTa0vSMTBdpKNt2Btu9RMsG3PakUpOOKXd3isANUoO/Ji5w0S+mjQ1iF94JRkVG3O5wNLJs9UmlkVIPETkkaZ0lUSvAO7yx98OyTFqXkQKfp1uAjWZ4jE4m3HS5T7PsdobOYxkCa4pQHQCmJEA5rzfC/kREnHOqNptl0gr7tOD6ZkekElWiid6RK4a0BZ1AasiSBzuOCQ6sEGQVBSvKiRKUF+77DOId1kaPpBOs9udTcWixo6waRKhye4IdoAhs8Smn0tGS9usEJhdBQyhxlNJ31FOWUaB0KwXqj+ejVNcd3RlQzTSIyxkdTumBxBET0zGcLZpVn57sBzJCmhGjxiWJajih9pO4OuOiZlmNM15DkCXk2UGL2hz2Jk0ihwIIUww5GWod1hhg8kkG2qtOMTGl89FRJjg9D0JbxPTrRQ7IfA9sxUQkhKFItkFIiRYrWCW1n0UrSNC2J1hTZEDkRVUTnirZT9MZR5Jok19g3g0UlIo0bqDbEgFKCRTXHGzOkDgqFC4KrzRpjAyEMoF8boCMipUApRSIEUmgSqWibBqEUynmSLMGLQK4LVBRMYsIsKREq0HuDUAIXIzIZoNjBR9q+xzuHDZFMJjgXQWqUBpUo8jQn2I5Ka1QiWTVbylGO7x0uBkAi+cc3sPzrwPvA5M3xfwj8RzHGXxJC/OfAXwX+szc/1zHGt4UQv/jmvF/4fheu+56NbTgOBbdnMxxbykrx4MEjthfXjLVAnC8oD4EdNcvYcTYtSJsUHy3t1YZH5yfsVyuypOTdR7e43Gx4+Dijrg3MJKvL4cOwWXbMxhWzsUNrzWrnSKIgRWIdPL59wo8/OOGf+rNfpNq85tS95uiHv0w6uQftlme/9qvc+amfZHL/Iddf/995+eFvUb//NU4+9zk2V88wh46Pf/Mf8ehLGlXk4BtsZ3GNpV6+5O4X3uWwn1Nfb7h8/X/QKsXxrdusiw3lZ+5xe3SLi9UrPvvwHEfPVX3D+AyIgnEJpcvo+55gHVjL65fXnEwXzKY5qfJoA/udpfOGmEQ62xCjfYOWEiQKml1DMdIUaooOhpvLa/xYUepjtnXL6a0TNmZNKjzSK1wq6YxB+ZSdaGg2B0gU0zLn1mhGt74mCk1vPTpJmYwnBDtkQMcYydMSKR0+eoz1NHXLuKjIVYZreup6T5andE1HnqdU5RTjAnXTIYWi8Yb97kClE8DTtA1pmdM2Lc53HC+OWa2usWFwp212N0gNy5uGJCSMqzFKJQgR6YzBhwQbLWmW0vYtMhlgwaZvGecTqlFFDIOt2gcPQlJ7Qy8jrbcYE+ijIc9SgrPYzuCCZ1ZVYHp6ZymqYihwNuLrmjpCTCV121GqnN7UiESQqIy6ObDI58S2o0wbjDREP2zDZQx89vYn+Pqz79AJT3CB9brh6YcN8+MjqnGONx1KC4yzuOgggLaRWAjSrCCtQWcCnQpEqKj3e7aHDRFQUkBQxNZRpgmtb6nbjkxqRiNN9D1aSjpv3uSeGBACIT2IQb2T6pxEC8oyxXiLCD1KBKLsgUipFZiAjYBISEkw0TEZVbR1g20MKoVFOSFGN2T9KIFpe87mc0zT40NEJZrMetrugFIJMk9JhCVV4F2C7z0aMSQiqkASAkJK2qanN5YiARE8Nko6E/A2IpQkSMAHttbSKce4TEi9xJtAJOJ8T5ZofOnI0xKBR2vJpKrYdnsu6hVVVWJDIM9yZqLE5IFdM8yAskySpAn7riMJERU12kGejigCOARSSIw1BB/orSPRCZ7wJy/eQoi7wM8C/z7wb7yBDv9Z4C+/OeW/BP7dN8X75948B/hl4D8VQoj4fSajxgYuWoOWO8pxCUlB71qWhxVOdtiomY4K6gNcXm9I8oyYGIq25KNmyflizFVbY/Mc3xvuVRmvLyNtF9m9Sni13RFJePGqJZtUpDPJVGf0u4hICqLseO/hY37mq3+BT5yPsdtrjDU8+Mm/xGwyxWxfEEPB1Te+xuydH2H94fsc/+hXOZKK/avnVMePOPr0V/Chxbk9n/tLP0/fe3ya0I01ZdAc37tDbQ1P90+ZVAXfu/o9VrHjWFUsr57Sij2nkwWjTPDgeE4Ike2qJnhHlgpC0DRNg+sjJDlCFvT7hruTB0x0juwUQXbcbGukHFFQocjZ79ZkaSTx4BtIM8FML7i53JLnKY/u3GER74HWxChJE8HNx9csTo6pkjFlIXm+eUGFJn1DQa+SDCEV677h9c0NrRK4zjEZjTkcapTSFGlFkY9oliuCD2y2K2SWkOpsIG67QJLB1nSYziFsSnsQ+M6jiPgAXdtiOoOIkjzL6OqOGHp0JtG9Ie8DWxN5vno1zETyBGMNto+DKcNDmefIKKl3NXmusKZHiGHAFYGLy+th5SUFk8kUI3t0GjG9I0sLTGchiMERaS0RCN6SJJq+6XDBo8UgHfPWI50hkdC2DdF7EpkP/VSr0E4yz0d0xtP0DUmhaPoOmQj2/Z7UGoxYo4JE+Ij1PU52fPeD75CNNR4LqSLkCZ/+3DFIy0g7qvGMQ9fiWsPRdEzbtBRSUKlI2+0pVELfN0RjSWXFcTGh9TVBeIROcF4QrEEEaJqWAOSpIiooKcmUJlUDf7OzDeu6ZZxNCHhioklVjtaK1zdX+ESSRJhVBTpGvLfkRYYjImJAZxntrkaoiI6KeVWQpxXRuwGoLBP67kAIhl6DaTqKquLi+pp67zk5PiJLC6Qb2hlRJQTfkWqFDymZFAQs2+WWO/Mjbi6XpFkKfsCfAcQQ8SYSm4jBghJI3rTetCA3MCkL9qYnpBrtA5lOSKxkTM40Lcm84rBr2XbNcO9FUF6QxBQRIzIE5nmJ9T1pzBFWgIs4F9ESUqUYZ2OUgLrrkEaQJxpDhw2B4CNKqj958Qb+Y+DfBsZvjo+ATYzRvTl+Adx58/wO8BwgxuiEENs359/8f11cCMlRXrGzHRWek5Mpu7UkTxQvDxtUlTHeSa6anpsbw92jCe+/7MjOdngXuJCWj5533D5NuXxu4c6BfCbYXQaePtvw/lVLTCQgSTCkIWXf9DQ+8mPvfZa/8vNf5d3TY4q3j3nx67/PaJKxePs+AsHzX/1lyk++y9XXv8b5T/ws+w+fkmdzrv/b/4LFV36Kt//CP0vy+G3c629z+t4n+O3/5u9QXX6D84efR51XTFTPfD6nz0c8u/oubbdi1wakSThRFeuLFfPJEVN9yiyOWN8cUFZxqGtk67G9QUwyVpuWUTphXE5BFyRkNIeXbJsrfJVy79EnePq0w0fFfJZRFil1Z5hWM6JnQH15i9c5XQdpek6WCW5uLLNZxWrfkaQDc3E+O0ERkSLDtjXNrsbXLdPJFJ1lmI2jMy1yXCI7jdYJobfoLCP3gbGeI4bOEKM+p5ApR9mcvEopk5S67nGdJsmOOa0WjNSCspgSy2HY1vQdh90NTROQQpD6iLDDEFCVAoGgrwPtsqN1nsVsTtvUJCpD9pKKjPZQMy1Gg4bbW5xxRK9IUslhe0BJhU8is9GcTVNjdoYk9iyXax7cvotvPeJNkL9WGqUEIvhBQbDfoYqMRApib0F7GuexqaZUEtlZCpWxGJ2y3dXU0XHYNmQq5+amIUsSumBpdg1957h/OieNAUHK1QZ0AtQNAkeL4dluydmDe2SjDBctWS4pK3CdYl5W7NsNUmmKIiERkSgl/eFArCSZVhg3rEgT4xGxJ6tSROsx0hASqOuepBS0bY8z0DuPDFhclcwAACAASURBVBofHXkmyZIC7Twff/iKXjqKMqHrW/JM4iO8WN5Q247ReEqlR4y1JlrJOB14mMvdFqEEPnikaZmUFc52tIcNaUwJKuCUJARPaC15oklTiAjq3rE1W7xKmFYVvukpp5pCRXa94fpgiNKhEsGkGHHYHjCNwfeRF8+uIEaih+Ai0UhEjOQipW1rQh8x7s28QUsmUlIoifKR9WaDi5rQRcpRSbd3bJwh+AP9aKDXkyWkeUmuAxmR3nQs+xUqy5AyUumUJNUEn5BIAdZgrcEJT5qW2E7TO4FQipwcabrB2JVA3Vlc+BMGUwkh/iJwFWP8XSHEV/6o8/+4DyHEXwP+GkCRDatGGSpu6iX+Sc/RaMTr51s+Xl6jqzkCz0Tm/ODd+wg54te//jWqLmO721PNK1Zry3rnWa9qivmCWSq4PHR842oY7Hgb0THg6oxl53l4dsS//JUv8Qs//QVmJ8e8/sZ3aT7+de79xL/Ik7/7Kzz59m9y+u67LL74Y+yfvqZ6+8d5/b/9Mvf+zM8iz38IXT7i+a/8bR789E8hju6w/LW/QzwNkCo+vlyzSv+Ag2s5n1acphNeX68wrmN7CEx0xpic5WqPVBXGK1Qi+MbNBe/8wCdpthvwPaiIiyNKMefx/Qnb7R6R5ORFifWOxe0zJt2MIlPsDx2z01OkFHRNzaEbKN1SpfTW0xtLmmXsOs/9h/d58uFzCBKrob2xJEkGIXJYbQcZVllSZinPnl1R72pUFOxUQy07ClMxTY+osoLJ6ZjL5Z5aeEZpwlweaNbXFOmI2/M7XDaedVNjHEgvuXP/lNNSc+gcQSYE55iNZlhrcc5BzFgUM6RLKWgZFRnjPGe1XYM/cKhrPvzoinsnc0I7ZZSNWF9cD4FTckqWjSjyBK1brjfXdLFmMU8pkoHUvd3vyGVJajNm6YzLzTVFNkPLSNz3zI7PkH2F7AKH1Z7xNCPTCiUEbXMgUzl227HfGVIlWYwmSA2dbzFND0Iy0yXz0Qmn01NWF9/ker9BhJREShLmTIqSQgZ29Z4qVzQ3LTa05LOStJignaccVUgXaY3j1lsTIGG77MmqEtt2vLraUoyHHaqxkqbZkQgFuaTIM/JpxnpjB903UJYaIRU2dqz2LbtdQ5AenQXm5YzVckVrBI0LLBYVqdQINMSEV1cb5jpHu4TRoiIrUnwNo7TgxbNrpEoZVfmQB281RycnyBAwbcf0aMGuObDersjHBanSmK7Be8G2dsgG9ustderREkZpwmxSIVLFwUZcE/F1SxA9J6MJZ2e3aF1NZwLrfcvrV0vKaYHWElFasIrY+2GO1TiyMsNbMAfo2ggCmuZA03iMi3jkkKbYG/a+odeaVTxQVRWzacWoyIk+sDm0XLxcsZi13Lk1YT4Zk0dBDA5RKEJQWCNY1y2Hmx2TJMGP0iEpsq8pdT7s7OoNu76jWW7J6Gm7HUImjGYzhBPIqBHCkjpJMMn3raF/nJX3l4F/WgjxM0DO0PP+T4CZEEK/WX3fBV6+Of8lcA94IYTQwJRhcPn/eMQY/ybwNwFGhYrffn7Fpx+9zcffWxGOKubHFWVSct/d53hywuriJa3pOdQdv/HNb/PRxmAvW6RyiJcesISoyLIRH3+8J3rP9iDwVrCYFLz9bkFbB/pdyy/++Bk/95f/OunFRyid8fHf/59xzrPZvmDx+n0e/OzP8/RX/yfq7z5n9hlLWY3x+9/FXzfUX/8t5mdfJH8QuP/wrxKVxe+e0riOiw++C+cLRkxw65rjbEJBws3llicfPaM8vYU/jIjZGFmUKJkikxwbFTFKpqfnHJqOfV2DzuiCJqkK+qhRXuFFQjEuWK+2+CBAWFKliS6gkhQvBLvdgWA9EoHUkmgdEYnSCdYOmurl8preNghZ4hBo1JBhIQQhSLJEEKMnyzLm5ZRxmvHy+iWtihRW8e7jT6BiydXyhm5nmeZTZuOcsqj43jf+gKcfv+Tuo7egWyGl5mxxn+nRHKkEfdMhshRPzaFuwMWhRxkGSVyaamxvyHXO5GiOcx3GRoSqyNMEe4DPv/MFdtsto5MKLTPOT04xxtK2QyZ3jBotKs6mJev6kt3ra26flYhOsNAnXF6sGZUjXF5wd/FJ2mApKri5WXH9qubeO7eYHVeY7ob94QJnO3ZNS56lbPsdgox265ieLaj3LaEbVBCJH/T1TeFZXV/xXX9FWuaUyQKi5uzoNnkxZrfZUipFVubgei7We1zbUfWKxckx01GCipG26dgtl/Q+ADXHJ8e43tN1nnat8bVicVqQ+UASc4IA2yl8azk7m7G+XiNiRqI0pSx5dfmcoC3bZkeaFnSdZzRKUK3i27+/Y3I2YXoyo79ISQqBl7DvLZt9oJ8EcgpePrsYQqrkmE0W2R/g/HTBwV9TZSkazauX1zTWE0PAPLug957FUYEOGtsaXG+ZnSxwQjM5njPJE272O4LQYCKmt1RlgWws7549xG73XB9uaK3j2fISS0DEksPecjwZIWJk+fJALVvuP15gg6BpHdFLhFUkusS2AdeZIRJC6AEaYSSBSDJOKUYlWarf7LQURVEwOTlmv9uRpTnO9WRZhoiC5eUOc4gUeUdepeTjHKkEN8sVtdJcLiEdlzQmchN2LOZzljcNbQZNqOmMx7uMm65hOi1RAVwHoY1kOqXrHSFIXPf9C/MfWbxjjH8D+BsAb1be/2aM8V8SQvxt4J9jUJz8q8B//+Ylf+/N8W+++fvf/379bgAXBL//4Y533zJ/qIb47strFseOu7fvcXF5RWstF9sN33m+53tbi9CQKkt0ESEGeVzwHhkbDpuUug/cvZPx5//MGf2m48XlliJPmKeCf+bPf5Xm679H9YV3ODzZsNlHbL3n/K1Pkh7dJZkknH3mHsXJZ6je+QrN9/4uyycvOf/Cp8nv/xDWbXn9679CemeGqWZsr19QTzo2jWf1+inedfzg/c/z7W8+4eN6z9VyxcndB8S+4CSdEJSn9Q4TI+qNcaFrmkGyV9f03dCLbI0lSVOCizRtSwiB66slwUfquqfIC/b9lqZe8/Y7j9nu93jjCSECglTmCCkRDLnEioS2sYTgSZOcQECSsD+0pGmKs5760DGblfRdhzFrzu8s2CzXFM2c2Fsend3DR2h2a8pqgkjlQDHpLc6vefiJT1FMz9A5LKblsG0NgiJP2Gw3lOUIEyLL1QFrA4vZaBi2GUsIIGRC23Tkb9Bli6Mpq+sNzjqmRcbtt+9yffAczRRK5sRoSdIEnWakqaduapp2T54XaCXJZUVnako5RQpNmo45+4GH9M4yGuUYa/F9QpoIjk+OUfsZmUpw9sB2eY0QDJGtXcJ6Y9CZJliBPXQkp5LtrkUmg0InUxnKS/JkStCa6WTBZrtF95bb92+TqWGFHEWgbXpGRYpzLbdv3yJPMtKyQCkJ1pOXOUnpkPmMw77F2ZbtZs94VOC84eT0hGA8J/mcPEupe4PKMqw1gCdYxWysqMqSNBmUIrduPeBmdcMsz5jmI+SiYnPosUbx5R/7Ct/73nNEJxmlAh1hNFqQasODO1PyLEW6jtW3tshoOXjHoa0ZlQnbzY58kqCUwjSWruvprKRQBUkP07EmA8zB4dpIuzVcvnyOTgXdKOCaSKE1PnTIKDgtF9jOcHucEN2avNLoTnDYWGxjqLKEm9VLRmVBkWiubm5QZGS5wnvP5csD/SEMzlVVsTk0OAfBDmYnHyQiSsoyZTSpSAs93P/OkUkoskFxY0xL3zZcX1yRlQlCOMbjCd4Ytk1HHyLtcs3s5IjpbMxuLzgEEG6EjyP2jYWo8UVKnki8t3QHT98M/NSsKAlNxX53zS41jMsxN/WB5e4wcDTr+k9WvL/P498BfkkI8e8Bvwf8rTe//1vAfy2E+BBYAb/4x7mYC4GnL15wOj/it777hHcfj7k1V+zrBqQAJci0ZlxG3j4u6G1g03ta1VGkA4W5TDPKVFNbwWju+OTDCZOs5TvXNfudZF13/Af/+k9T3f48I/WKQs3wo9d8+qt/ju2TV4xOKnaHC7onv8+h6ZHXe+4Vksnn7kK64aXdUf3Bf4f7lqIrBM+/8z5ZWXBzaLB9Q6VnmJuE2eyc50/XXC93yDTn3jufI0tzms5ibM+oyDjsO4TKcE7i7IDjEgKOjhbsdjWdHQLxRYhkeUoUkbZpkXKYxKfFIHPzCKrpMfu9I/aS4CM6TQgx4IKn2zeEEJgfjxmNCvrrLVpr+r6lyEqCB60Sog+MRxnBGso8w1hBkSt2u56v/V8fc+/eglvnRxQxwTnB2nhCuydJBHlREEOg7SNts0ZXEhE1262jGr/5EFyv0GnGk+cX6CxFCFAiYowBG4gxUuQFSSpBJBS5JgbBdrsmyxPuTo/R3iJ0ht+tUCIhzxRd74ko2r4jSxLG1RFpnlJ3e4SIpC7l4f2H3D6fY/pIXhbUfYcSCTEO6pVpWZAoQeIdh3pPcBbj9+y2e9JUk2aCRCvu3jplvbui62oe3D1nd7NneVnjfECLjMVJSlam1M2BWMzpTM/5+fHAqAyDi9GjiW/0xdYG8nJCliXE+EZdgqLrewI9QkauLl5SjQtG4wKlxiSJoDKO6B1ZkdH0Q1xrH6BeHxgVihh6MjEiTUuCizx7dYF+s/MSItIfep6vDihdgch468Fj5sdTfuRoRtd7lO64ePGK15fXfOZzn0OlARED11cti9Ft9tsN2TjFG8Pd0zl943m9WlKkCtMbytEMlUKZjLnafUx5HLDWUteRaApMn7NctSwmFctDQ+9gVGimZU70jve//gTjJcWkJArH0WSElJ40VzS1Z3mzI0sUiQ0gcrzLMVGSJRWvXndcXTlm5QghAqb37Le7AXPXxDfu0JQYNWVRMJ6MiXKIpc7TCmKgKAvKLGG/vmaUZ1SnGSYMyLjYC4pkBFjyvEQIjSZjdblhv6qJScmn3n7EfD5luV5S5hVlKkizwPX1JfuDQ5JQ5mN0KiiVZ3w648XVFXss3kvqnaFYVNy/cwv+caUKxhh/A/iNN88/An74/+WcDvjn//9cd5Rp3jo65fJix498+hZf9A/48OUNn34UqGvPvlkiYyQl8k9+8iHtPvAPPnjKZWcYlQmFBqEV0mlGU4VZGt5+fITzB9LZObVvePxgzPm04If/iS+iM0ujW26uX7B7+h2OfU9395zvfvQt+nBFj6OQKctNz/Zb/4gNnntB8nqzJSiIUhCiQBUpbdtQHKCtBcV0xuj8mJgo6n3H2YO7WCfo+kjb1mgZuHd+yrOLG4RQSO8QAoL3mN4jpGJXtzSdx/uheHfOUm+7QbZm3WAFDgGdKKLr0VqTF8kAixWgEknftyiVkirNp94+Zbk6sO88B9/gY6TrDEVaElAILWmbPYlOWW5byjShaVvOz6e0Tcer50sePDrn+KiiyAta22P3Aa1K0kqxvFkT8Wgl2awtUkmEEAQkVZmSeYH14Iwh8Ya+H9iNbetIE0XXDdIz8FRlQVMfECgONuCco2kbJlVF8AHjDLduLZiMDU3T4rxHKo0xlrKoaNqW2ajgB3/wM3zz/W9yc7NmNp2RSk9vHGmWkyYJnTEQPMYa/IAcpO0NzvTYbsd3/uA7nB/PaWpDCBqCZlSVGO9oOkWWnbFeN4zHJ6RFQIuUcjrh9PYprh9eb9yGH3jvXRpjUXoI9Wo7Q4ySiOToaMZhu6XpB5NIWYyYTXO6/Q70QLwR3nB8doZzjs16B2FYkYcYydKcJC1wNuBjT1qUlNlgFY9B4YLHO0OuJPPZHCkTjGn54IMPkEIyGpcIESjKhHyUk2cJiQSE5eOnr3n5/JL7jx6wb3e8+viCq8sb6rrh3lGJTiSXLy+ZlCUXz7bs9g216Xh4p6Jta7Zdw753ZFmP0p7eKLZ7x/LGoNCcHs0IVaDrGrROKFVKrhS73Z48zUiSFBLN9aoleEGmC8p00F5LGVGpo8xTXi9bnMiI+ozpouT4dIxtNSeTBgmsV1esVmuavSOSk6cJ1XSMSiR5ng00nkSh05Q8RnQc6sh+f6BtJPWuH5iedYf1krQYU8aSLElYTDOWmzUhaFSvODq+R6ILmrbFdC3La0ddtyhRkCcaayEGSS4V9aFFq0izdcTZiEO95+ZyT6Y7kirl/q1z6t0Sd/Dft27+qXBY1p3h9izBdiPef/acH/r0O9goWa9aillJW2sWuULiUUCbOibnCbMeRhUcz3MenOZsW8HRueTmw5pJLsknZ5wkU37mRycUY8lcOTq556OPnyD0knoTCJVjOhG8eP4B63DDpCwwXQshMr815sXhkl1jiLmkkRBjgo+Sic4prKbvBIfOc7a4w2rTkqYRZRwOyWprIWYEHONRTlVmLNdbEJIYIr115HlKZIA2OBfI8or9bkXf9yRpQtd1dF1Lnud44mD20AnRewIBIQEkOhF4hqB/lWQIJGmisFbz/OWK0XxKLjUSRwyRtMwGhFndDHrn1pAWKToL5GmJ0gHbWB4/fEBWWbq2Z1cbXl9fMpockecRrMK4jtTlmN7g/MAylFIjAkPA1PZAlINxodk6+t6RpnIILXKGLB9S2dI0p+t7ms4hZSQSEQKSrCBIzaHtMcby4UcvANBaYq3FOE9VVSgFi/kYb3u+88G32W6GLwFne7zvaPaB8WjKZleTFgV5lpFogelajDPkVcbV9SWvPvyI05MZ02KMGweikGRFTl5N8SLl5PYpdVtz7/EjVlcbvnXzEe9+7hHz0xlloejayNHtu2RZwWQ2wnuJ1xllEshkxMUMYS1NX+OJOOOQWtAtrxjlx3ih6INFSgaiS5YRY+T0/Jjgh89Klec4ZwcnoRpYms5ZbO+IAqo8w3U9RI/zkfGo4vXlkvVqi5SCLBdUVc5+3/D69QWBiDNnmN6y3e0JwOJkiveWVy9e0rYdpu9JJOxbQ9seSHWFDwlR5BRlQpJkHHYtiHSY34wrpkc5q23L9552SJdyujhBp0ML5/hsRttITAOT8ZzO9WTlmN22Zl93ZEXO6dGcPM2oioKiKqjm0O1vuLna8+TVlvnxXY7OzolScDSfIoWgUT1d4um7A9Y0WCtJigXGR0aTnMXRFOd6pBQIneNj/EP6ezkqaOoW7yPr1RofHIVO2dcBFwTH05zpyTHzcU6Ra2wMdH3H6a0Jp2dHtO2a3fMlpjXcunsXEQNysKnhjOHqxSvcocYZxa7bUxSaTb3HC0muFXkxZMG020smRcp+vfu+dfNPRfEOSIIwTI9Lnl1I3n9yyWc+fYvrmw7jN1QjRd93jM+PeXV5xdmdGT9y7xbvvSVIM8PtoymP7xxxtW0h3cDje4jcoscjnD+QZwVtXVPHyP/4f/4K0kGuJVXt2C8ki36DFJYURdcfKEJBLTt8t0ehSXRkiaDfWpKgKdKcUTnBNbDa7fGyot32CJWyO+wgKDyCLK9oGodxjrS3tI2haTuEVKSJxjqLsIJD3ZKnGUIJbm5WSKXQiSZG8E6gVIIxBmMt1kVEfKNfVgJnPb/9W+/z3ntvIaR6sx0fHIOt9jQ2JS9zsizBOs9oVHByMmO3q+l7g5YCYwxFrrl8fUmjJQ8elfzGr/0Ok8mIH/nRI7ZbAwj6tqfKh2Q811m26xUuWrzPCTFFSMiKnL63ED2Jhr4HwVBo29YhpUIIyLKUut4T42BKmE0nw/v1IKUgxoizlmI8pu16+rYn0RopBFVV4IPDR/0GCKsRb1xyWo3Zbg8oFZDS4p1AkDMaFSAVaSKJwOGwZ1Ll9Lsdj96+x9PXW16+3DKeH+FRWJEyXZwxmU3oTEc1rmj6niwtIVV0rmN+NuW9L73Hdm+IIRCCwgfJ954+Y7e1fPa9T5KXimo8IV+MKYqU5XqLs47mMKiglFZ4G8h0wevrDUpnqDSl6xoSYF93SJ2SBAjRM1vMqJuO1jhi9FTjMcZ6+m6PEAoXh5wPnCXTkqg1m0MHMuPqZjMYixrBbruhLGA2G7Ne3XB9eY1Umq5tkQKSLGc07vFRIKXieH6MloFD15MHSXPoMVFwPjuGGAhEAgGlFLvtnqbe0rWSw36EFhknpxNOTyteXz6jbj197yhSye2z29St5d7Dx2z3NdV4zv2iouk7Up1w8fwFRVmis5woBU1boYrb+P0eXZySlTPKLOHZk4+RmWQ2n0PQ7G8OXK4Mk/GMs/MxWaZZ1y1CBNIkBaFAKWQMxDDg6W5WLWVeAoK8KAcCfdcThaCocpSKdH1Hm2uQ4LygzKa4TnD1ckUicrJ8PPgDjCEvMp4/eULT1KSJxNQ1/aFF65y8yOmjw7ph5d/bHh8ss2mBxNPbiCpn37du/qko3lIKAi06zfjyD59w3XYkU8OjRU5RzNAxpe4P9MLwqffeRqWS/X7PKMswwTLKc2QVqFRgubOE6RpFirCW5WrL8ayjcwoRAlWmaGQPIuPsnVtMOkO323DV7ki94OX2wHQsMa5Hu5wYZizkGLMPpK3m/Pge3gtevlpTHxxOJ4gYEaojERprA63xiAhKd/S9JwbQk4rW9ozGIzbbFWlSMh5X9MYCoBJN3TQYHxiPJ8MgzQ0r42o0tBMePnzMk2cv8W+4hWk6FPm33npA27YD1TpAmiYgIxIIrqNKYTHKCDrj8uUFUlqEkETrSWWK0I6qTDn+xCP+1//lH3J2PuJofs6P/rnP8vLpkuAsRZ6jsoIsB0hYrW+QYUg/22wP9HZIWavrDmstt86OSTNJvzpgbD9ofEVKmiaUVc5hXzMaTYcilebsDy2SyGg0GlpJUaDyBGLAO0uWDW2gNJd03YEgJCLJSHDMi3LI+3COTbOjrDLaxiCExoWAVBqd5ygtcHZItOu6jjSRyFHFNz68IM1SHrxzm6PFMU2zp8wznOtxyhE09M7Rdp5oaqyzJFLTxkAxHnF2e8TZ6Yz6sIcYOTq6w+O3xpTjHGMCWmgurtZkaYLve7777e/y6OFjEBFve8ajgrozZLkmU5HtZkvX1GQy4ERCqgoOnRuACDISvIMYMcbhtwcgkqcpSmticGRlyXa1xlhLFjJ2+6H98MUvfYmLFxeY3jGfj1neXNHUDtPD6fl9XLAEdzk4LQ1s1w3vfOodPnryhGZbc3I8YzY/Z3P9msm4ICkKqvGE9fqGssqG3ZKU3Lt7h76/RdCOauTo64a+q1mu9nz08YrdITCZHkEV2dY1LsAHHz5nv+14/PgRbWcpRhN8iNy6fx8toTd2GL7nY+a3piRlxfRoxL2HJ5zMJ8wmCc+eL3FW8+Jiw6g45eHtgvnJmBA9ddOTJoKyLNjv6z/M6CZGRkVJ7yzr3W6gzmtNoTXWWHarNZNpSV7lJAk409O0CVonHN86x/vAq2evmIxyqqok6JxqsmBxPMX4buDBkpAKTTZOkXGNkoGyULStRWeSo/MxyxU0DQSZDtjFXpOWo+9bN/9UFO8q03z+8w+ZnEpGi4o7XcZ4lCN8YJYNcrZFMubQ7NDCYqJCFXCwG6zVbJqWrJdsD4amieis57P3PsGm9pjRnrenc57tGq52a0hyml6Sp5Gbw4HbsuDD7RKTDIlmpu2oVUm7j8zKMWeje8zyAis9VrWslmtUXrKtBTKtBpqL6tARmq7H+GFApxVEr1EKZvOSruuRUrLf7UhUSp7npKni6maHEIoQImVeDEV8X2Osx3tLkkrqwx7rPBeXr5ExkEg92H3zgsN+RVUWKDXCxcj20BG6QJVJjFWsNo7l1W4IlxId+31DWeWMq4yiiLy6qNG5YDoteP+Dl9x68BAlJ/zgDx3x8uNrrO2ZL6a0TUvv3RBE5IZdBkhCMCghqfIMrTUhBKRQtG3Hvg40ZogX7ft+iANl6HnHGOlsj4ugY8RYS1UUTCcFJ+dzrq53bFdbhJA4E0jLSMBhbCRGjTUe1xw4meZoHTCmwfuIlgrvDCEE2rYnzVKUhqgik5NjPv7gw0F9g6BpDaYfVvd106JkymZ3INFg7FAsnI8EK/ACQoBDM8Tfpoliu9szm0/YLJcQLT54goi89clzri8PJCphciypdy2LowpjehQ59+7fRcqAdR6lNfuDIQaLV7CzjiTL8M7j/CABPT6ZcdjX7Pc9fb9HIPDOo6RACogBuq5lPBnhOzsMqX1Aa0GV5agIeZ4TgiEbpcxOF0ghmSenXL26xIfA5eWS+2/dpTeGdttRTQpciCATzm7fwi8cMUZ2qzU6KUkSTTkq6GPP4nRO3/bs1mu8D+zSnqPTBXgASzUeobOM1XpDUZ3zqc8+pGtrZtMK7zsOrSV4x/yk4lOfvs/2cOD15Y7eeJxzJMEglEIXw5ehJDIajzCd4eOPXrA/WXB1dYUJUOkJP/5j7zErJfNpzgdPnvLNb7/g0DiUygHBeDzH+v+7vXOLlSU77/rvW5eq6nvvvc8+5+wzM57xyBMnDmDHILBFhCAokRMhnoJEhEQeLOUlD0FCimJFQuIxL0lAQhGI2wsCRLgo8gMhOHl2cGLHM7Yz8cSeM+e+b929u+teay0eVk04GezBGRnv06P6Sa2uWlUP69+79ldV3/rWf3laH7jKd8xHE1oXK7t2dYUSRSIaAVRiIEmo2kDTNkwnQt05rnbRumEys/z5j34fXevQRtEEYTadoFRHZjJu37nNvW8+YnxwxPGdmzx+8IDt+RkhtHjfokSzfrLCjmcUraHYpdw8nnM4mrKYTd41bj4TwXu2sLz4fSlXdcmm2FBtdyTqkFk2YdfW1KGDytG2jla3FD6n6Rp8qJlMZtTblizMefm5l3j1jdf40Ac+zM3ZMVe7t1htNjwZz1k1ObPphKJz3Lp1QLtteP38nLN0wrZtubOcce/hKUmmee7ghOl8SeIWNBWs85wyb1C06GREUUYXRAh452idp3IdH/rwK9y7d0FTR1e9rquYTBJmswxByPOKUTbCe0fTOdbbLdYoJuMxdVPHqpLeWKctG3xfa23QdGLY1g6N4FvHeJxR1C11K9gsc8CXSwAAEDtJREFUoXNC29QsZhNC59DSkKbCjRsLphNNU7WIh+lkjMNz78kTlrMlnWqx2vLaHz5mOsv4cz/4MllqubzY0LaOJBmx2xXUdYXrAsc3b/P48Sld12KVImCBWJs9maUUec1yuaRtaqo61sbWTYPWOvo5B0iShLqqo89ICATvsUqhiKuyXK7OMWZEVTe4zqONwVodgz4GjwcleAe72nP1eIWIIKKISRGP0jbOYmsaus5T1yvW6zVd6+PiAx66NppfgWBtGhcLaBsym+LaDms0TduQ2DibUiRglMJ3wrapECxnp6t4w31ygQ9CvquiL/PYYjPN2fkK5YXVpcL1/tE+BPKiwlqN0oKI4DpFvqsQk7GrthwdHVJvrxCE1WXUt1hMKcsdVVVhtKbtYpWOF3BByKsmLmDcdaSpISjDo8tLBIVtolFU8FAVHTZNqKqAthOmc7h5coMkG/PiSzMSFSjqgqZ15GVOVTekSRbHUbxgrMFoDzawXp9TXF0xSReYJGV9tWaRzXCdxygFIWC0Ztu0JNmUD75yxGRmScaezgk6XaK6gmzSMk4Tvvilr6K0JhtNaboa73s/c2NoimgPm6Ymen+UnscPz9luovVuNjaI1Nx5bs7hNOXLr36ZJ+dbbDphvlCsVxtu3z5hsykIbYtRgel4RGIt0gn5Lsc7jw+Ow6M5uQSOjm8gKEIIGC0o4xGJSaLEKoLrOLvY0DmFtYLSBi9xgemLswue3H3Mk4c7gp5zcNtydPICs/mCcar4xje+TlMrVquSEZr5wYzjm8fcOjmI9ebvPkfn2QjeWoEdWfJ8xcHhjMnkkOAUIU3Z1S2Vr1AuOm9Ci9gAXmF0BhKoqh3GWlYPvslinvHg7D53797l4OCA5eKIy7IhGEOe5/jUUJVbgrFk6QgUHC3nrNc7rCR84PCEk+yE1E84f7yjdY6LizXWJrjg2a03uGBRKprcGK1oW0+aJrx59x673GESgzaexKakJuH+vQuOjhYcLBfsdjnKKLRRVJVjlFqsFYyZ0HTx6S0EIYSot25aqqLu87mBF194jny3JR2N2F7tODg45OxyzcPHp7z4wgnet3jnmc6nbNZbVmen+OD4yA8+z5t3TzFZghZYZjPOzzdUoWOkNV3bkdo5l+cb6qZmOp2DeIJ0NE1N3XSIGM7PLvtJFFN2uy2JFbR2LOZT2i465NVNTVu3CBpjDE3TICFgraVuGuqmQiTm8oNrydKELE2oqwrnDc4L1a6i7aJBj1KC8x1V3WCM6lcQ90xHCZNJNKgCQWsYjyasN1tc6xhPxnTO0dQ1IoIxOqaLQsAmCV3boJVQVRVI9EWZjRPSxFKULUmSxjx88NRFQdN0aJPi2gqdWNaXW6aTjKYuUEbTlB1G634Q2XN6eklbBxbTFGsNwbfkeRFr0m3A+Q5UrIR1IowmU652NRpQwbFcTMFHZ8Ku87imiAOOaQYhPgDEt58AovBBQKJ/9Xbb0LZxlsdiOadoKqqiJrEJU2UxAiax3Do5JrWazW5H0cTJMZ0V8spRlhVl3aKUpW0qnHNYG6t7JE1pK8d6VbG52CI3xyynC26eTPDesdnsCN71Yy0tQUC0xgfFZhOd/lznQBVkI02awO6qYDadsdtt0SbgfUJdtlhjOV8XzMdTjFIkxtA0Vfx7T1LarkEbixZDU5c8eviIbxRbTs/XOCzrzYr5bMR4MuHJ2SXbbUUIDqUgaI1Rjm3ZVy9JzPE7H8uQRGuqqiaEwHI0Q5to1eq6lmJ3xWw5o2wc27wkMQo8ON/R1Ft26y11mTOZJUxmGaIDNlFYu2C1uqJRS+4+esSNgyPuvHTC7GAOOMp6R9soXPFdMKb6/40ooWxaZtM5dV7QeE82mvLw0T1QFq1atEnZrNcc31ygmposmVOUJak1LBdzyECJZhwMTQcruaINDaOZoS5L8suSxASCr3C7EXqUkNbCZDGh6GoSM+ZglnDTPIcuMtZlw8Vui040STIhqBbfJXGpIx9faVOt6NqGqizJsimrixzMmPFUkxoLXcPxzTnHt2Z0nWN3VfTBJ2CsYpRljEYJeVnEWXtliTIK7yUa7rceoWO5nDNO4wDlbrdjc7UlbTuO5hO61jObjnjh+ZM4E6xtSZIRRR1H1F/84E0e3H/E6ema+WTEWw/PyTLNrRtLbp8c8OpX3uLv/Phf5M23Ljg939E5cF1AtI+ldM5ycXGFtSMSC+nEcHR0xMHRDV577Y8oXcnBcsRmvcWjGU+neBdTJwHYXm2xqaVpO8bGAoGyyEnTEdoHjLIoEfIi+o2UZQ14mjagjcZaDcT6XEHjXcd8PqZtKpLEUFUlVR3HDZJEsc232MTQto483yKo3mda6NoQ64VHGpGAtYY0TVltdgQJKBGM1ezyLYhQVCVd50ApOt9PpVaaJM3Y5QWz+TJaGask2rkmsf++C2gtGFEsb4xomxZtA5myXF3tSBKJLnXe4WtHYky8mVmNSQzWa/I8ByVMx6NYr54E2ia6SQqQZQnWWryPA7uz+QKlNE1V0hsixvSKd2yvNmTjEWk2BmBXVgRl0caSjcd0bU1Rd0zGhqIsqBtDUdQYozHGx7Sei+WpznVorWLaynUcHNzgYHlINs5oOkdXVTFH3QaMsaSjKcG3KN2gg8e5BmU0Bh+tB0YZ69UVTVkzGWW0XcdkPme12pGkE+7cOUArqB+e4QmxSquqKasSpTRJkoGJcxoULW1T8/DJKaenl5RlYL4cM19M4wQ+bQiikASCi541te9YXW1pfIe1hqpsmMwXXG13iJK4vJlE/6Wq7shsLMttu4arruVyu8NJQtM61CRhNpuiqBklijcfPkI5mC3GTOcpm9W2n8uxZDafopMEpROeP7kNOrDNG6wV0tTSuZq2bd81bj4TwbvpHBfFmtOznA/cPuLJ5WMOZgFrErRReK8RDcfHC+q6whrwTcHN20s2m4LHF2tuHWcs05ustg3BtszSDO9bVhc5Yz3i1uEBHY6mLLgxPqJrG56/fQvvWi5JSFTGWJ7jyf01Nq0pSk+iNV2nyCbCxVUHraNtA0mimYwS1pst4FgsRgSlWR4cxKW4UkPrwOiE3VXOVR5XATcqkJclXiDxjpM7c6q8RsuU9bYiqJha0EZQQTAIAYNzjjTVvHV/x40j4Wgx5exyjZ8b6qJgcXjIfD7GO09iUvLSk2XC5MYSLYEbx0vOzrcEBYkVqirwZFMQmoJXXj7m9KKirj2IoqobqsrTPTlnOhnRtL6/4EZs1g0HywmvvHSL0WzeTzqIiYrxfILvoOvaOJ1dHHgfg3MIjMYpneviStraUpQ1o1F8CyirlrbxZPMMpYSyaCB0jLOMNFUURYNzgWycsd3mXFxumE1T0IGrVYPqyyI750mURilBqZii8b3lJj4wncSJJb6N9ehoTV00CIHpNOktZuOElNSaGKTaFi2Cc9EHOt/lJKkFr1ivr8hGls45CNDUDa3zcfBQG6wO/MAPPM/9+2ecXxa0ZUWSpGgNymgSnVIXJSpRXBUOVeU47xmPE6wGhUFpT5pYbCKsLpqY3vEtwQlt19F1DpERp6dbFvMxSZbiO8irHU5UfHoMmjJv4g1Gx6CfjVIOD6dcXK7Z7hqcV9RVg2sCo6khzRLOz66iV7eOg76K6IeutUWJwXkQbUFaVuuKQIvRCVXdIBiMJdY66+ic532s/QePGEPZdJRFQeMDQae0RMc/X7cYE7DiuHVzxp0XTjg9O49vu6LQVpHKBNe6/gbWYsSwqz1N6bjcXJCNMpzPeXDvPgpB0gkH80PyfEumoXQeMbC7WJPnDTa14Dyuc5yerkhH8Y1PiBMAA4qyaVClYjkdU5cl603OaDbBtVuMMWx3FV3TMJ9antx7ENO5oxGz5RHOBe7fvcvR4RHJKCOEWDZ75wO3UaJpuxbnW0ITZ2KWdYdNkneNm8/EGpYisgVev+5+fJe4wbs4KO4h7yc9g5Znk0HLt+fFEMLxtzrwTDx5A69/u0U29w0R+cL7RQu8v/QMWp5NBi3vjXdf4XJgYGBg4JlkCN4DAwMDe8izErz/xXV34LvI+0kLvL/0DFqeTQYt74FnYsByYGBgYODPxrPy5D0wMDAw8Gfg2oO3iHxKRF4XkTdE5Beuuz//L0TkX4vIqYi89lTboYj8loh8vf8+6NtFRP5pr+3LIvLx6+v5/42IvCAivyMiXxWRr4jIz/Xte6dHRDIR+V0R+YNeyz/u2z8oIp/v+/wfRSTp29N+/43++EvX2f9vhYhoEfmiiHy2399LLSLypoi8KiJfEpEv9G17d40BiMhSRH5dRP5QRL4mIp+8Li3XGrxFRAP/DPhx4CPAT4nIR66zT98B/xb41DvafgH4XAjhFeBz/T5EXa/0n58Bfu171MfvlA74hyGEjwCfAH62//33UU8N/EgI4aPAx4BPicgngF8CfiWE8CFgBXy6P//TwKpv/5X+vGeNnwO+9tT+Pmv5GyGEjz1VRreP1xjE9Xv/ewjh+4GPEv8+16MlhHBtH+CTwG8+tf8Z4DPX2afvsN8vAa89tf86cNJvnxDr1gH+OfBT3+q8Z/FDXIf0R/ddDzAGfh/4K8QJE+ad1xvwm8An+23TnyfX3fenNDxPDAQ/AnwWkD3W8iZw4x1te3eNERdT/+Y7f9vr0nLdaZPngHtP7d/v2/aNWyGER/32Y+BWv703+vpX7R8CPs+e6unTDF8CToHfAv4YWIcQuv6Up/v7J1r64xvg6Hvb43flV4GfB952Jzpif7UE4H+IyO+JyM/0bft4jX0QOAP+TZ/O+pciMuGatFx38H7fEeItdq9KeERkCvxn4B+EEP7U2kv7pCeE4EIIHyM+tf5l4PuvuUvvCRH5W8BpCOH3rrsv3yV+OITwcWIa4WdF5K89fXCPrjEDfBz4tRDCDwE5/ydFAnxvtVx38H4AvPDU/vN9277xREROAPrv0779mdcnIpYYuP9dCOG/9M17qwcghLAGfoeYWliKyNs2EE/390+09McXwMX3uKvfjr8K/G0ReRP4D8TUyT9hP7UQQnjQf58C/5V4Y93Ha+w+cD+E8Pl+/9eJwfxatFx38P5fwCv9KHoC/F3gN665T++F3wB+ut/+aWLu+O32v9+POn8C2Dz1enXtiIgA/wr4Wgjhl586tHd6RORYRJb99oiYu/8aMYj/ZH/aO7W8rfEngd/un5qunRDCZ0IIz4cQXiL+T/x2COHvsYdaRGQiIrO3t4EfA15jD6+xEMJj4J6IfLhv+pvAV7kuLc/AIMBPAH9EzE/+4nX35zvo778HHgEt8U78aWJ+8XPA14H/CRz25wqxmuaPgVeBv3Td/X+Hlh8mvuJ9GfhS//mJfdQD/AXgi72W14B/1Le/DPwu8Abwn4C0b8/6/Tf64y9ft4Zvo+uvA5/dVy19n/+g/3zl7f/xfbzG+v59DPhCf539N+DgurQMMywHBgYG9pDrTpsMDAwMDLwHhuA9MDAwsIcMwXtgYGBgDxmC98DAwMAeMgTvgYGBgT1kCN4DAwMDe8gQvAcGBgb2kCF4DwwMDOwh/xshOglY1loKiAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcaee67ed30>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -462,10 +454,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Model: \"vgg16\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "input_1 (InputLayer)         (None, 224, 224, 3)       0         \n",
+      "input_1 (InputLayer)         [(None, 224, 224, 3)]     0         \n",
       "_________________________________________________________________\n",
       "block1_conv1 (Conv2D)        (None, 224, 224, 64)      1792      \n",
       "_________________________________________________________________\n",
@@ -809,8 +802,8 @@
       "- Data loaded from cache-file: data/coco/transfer_values_train.pkl\n",
       "dtype: float16\n",
       "shape: (118287, 4096)\n",
-      "CPU times: user 116 ms, sys: 256 ms, total: 372 ms\n",
-      "Wall time: 365 ms\n"
+      "CPU times: user 187 ms, sys: 621 ms, total: 807 ms\n",
+      "Wall time: 806 ms\n"
      ]
     }
    ],
@@ -841,8 +834,8 @@
       "- Data loaded from cache-file: data/coco/transfer_values_val.pkl\n",
       "dtype: float16\n",
       "shape: (5000, 4096)\n",
-      "CPU times: user 8 ms, sys: 8 ms, total: 16 ms\n",
-      "Wall time: 16.7 ms\n"
+      "CPU times: user 7.16 ms, sys: 32.7 ms, total: 39.8 ms\n",
+      "Wall time: 37.8 ms\n"
      ]
     }
    ],
@@ -1091,8 +1084,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 8.75 s, sys: 32 ms, total: 8.78 s\n",
-      "Wall time: 8.7 s\n"
+      "CPU times: user 8.43 s, sys: 20.6 ms, total: 8.45 s\n",
+      "Wall time: 8.45 s\n"
      ]
     }
    ],
@@ -1174,8 +1167,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 6.72 s, sys: 68 ms, total: 6.78 s\n",
-      "Wall time: 6.72 s\n"
+      "CPU times: user 7.8 s, sys: 27 ms, total: 7.83 s\n",
+      "Wall time: 7.83 s\n"
      ]
     }
    ],
@@ -1391,7 +1384,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "batch_size = 512"
+    "batch_size = 384"
    ]
   },
   {
@@ -1443,7 +1436,7 @@
     {
      "data": {
       "text/plain": [
-       "array([0.    , 0.    , 1.451 , ..., 0.    , 0.    , 0.6562], dtype=float16)"
+       "array([0.   , 0.   , 1.483, ..., 0.   , 0.   , 0.813], dtype=float16)"
       ]
      },
      "execution_count": 45,
@@ -1472,9 +1465,9 @@
     {
      "data": {
       "text/plain": [
-       "array([  2,   1, 126,  34,   5,   1,  29,  25,   1, 247, 116,   3,   0,\n",
-       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
-       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0], dtype=int32)"
+       "array([   2,    1,   21,   80,   13,   34,  315,    1,   69,   20,   12,\n",
+       "          1, 1083,    3,    0,    0,    0,    0,    0,    0,    0],\n",
+       "      dtype=int32)"
       ]
      },
      "execution_count": 46,
@@ -1501,9 +1494,9 @@
     {
      "data": {
       "text/plain": [
-       "array([  1, 126,  34,   5,   1,  29,  25,   1, 247, 116,   3,   0,   0,\n",
-       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n",
-       "         0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0], dtype=int32)"
+       "array([   1,   21,   80,   13,   34,  315,    1,   69,   20,   12,    1,\n",
+       "       1083,    3,    0,    0,    0,    0,    0,    0,    0,    0],\n",
+       "      dtype=int32)"
       ]
      },
      "execution_count": 47,
@@ -1568,7 +1561,7 @@
     {
      "data": {
       "text/plain": [
-       "577"
+       "1541"
       ]
      },
      "execution_count": 50,
@@ -1717,9 +1710,7 @@
    "source": [
     "The GRU layers output a tensor with shape `[batch_size, sequence_length, state_size]`, where each \"word\" is encoded as a vector of length `state_size`. We need to convert this into sequences of integer-tokens that can be interpreted as words from our vocabulary.\n",
     "\n",
-    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token.\n",
-    "\n",
-    "Note that the activation-function is set to `linear` instead of `softmax` as we would normally use for one-hot encoded outputs, because there is apparently a bug in Keras so we need to make our own loss-function, as described in detail further below."
+    "One way of doing this is to convert the GRU output to a one-hot encoded array. It works but it is extremely wasteful, because for a vocabulary of e.g. 10000 words we need a vector with 10000 elements, so we can select the index of the highest element to be the integer-token."
    ]
   },
   {
@@ -1729,7 +1720,7 @@
    "outputs": [],
    "source": [
     "decoder_dense = Dense(num_words,\n",
-    "                      activation='linear',\n",
+    "                      activation='softmax',\n",
     "                      name='decoder_output')"
    ]
   },
@@ -1798,134 +1789,25 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Loss Function\n",
+    "### Compile the Model\n",
     "\n",
     "The output of the decoder is a sequence of one-hot encoded arrays. In order to train the decoder we need to supply the one-hot encoded arrays that we desire to see on the decoder's output, and then use a loss-function like cross-entropy to train the decoder to produce this desired output.\n",
     "\n",
     "However, our data-set contains integer-tokens instead of one-hot encoded arrays. Each one-hot encoded array has 10000 elements so it would be extremely wasteful to convert the entire data-set to one-hot encoded arrays. We could do this conversion from integers to one-hot arrays in the `batch_generator()` above.\n",
     "\n",
-    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays. Unfortunately, there seems to be a bug in Keras when using this with Recurrent Neural Networks, so the following does not work:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# decoder_model.compile(optimizer=optimizer,\n",
-    "#                       loss='sparse_categorical_crossentropy')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The decoder outputs a 3-rank tensor with shape `[batch_size, sequence_length, num_words]` which contains batches of sequences of one-hot encoded arrays of length `num_words`. We will compare this to a 2-rank tensor with shape `[batch_size, sequence_length]` containing sequences of integer-tokens.\n",
-    "\n",
-    "This comparison is done with a sparse-cross-entropy function directly from TensorFlow. There are several things to note here.\n",
-    "\n",
-    "Firstly, the loss-function calculates the softmax internally to improve numerical accuracy - this is why we used a linear activation function in the last dense-layer of the decoder-network above.\n",
-    "\n",
-    "Secondly, the loss-function from TensorFlow will output a 2-rank tensor of shape `[batch_size, sequence_length]` given these inputs. But this must ultimately be reduced to a single scalar-value whose gradient can be derived by TensorFlow so it can be optimized using gradient descent. Keras supports some weighting of loss-values across the batch but the semantics are unclear so to be sure that we calculate the loss-function across the entire batch and across the entire sequences, we manually calculate the loss average."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def sparse_cross_entropy(y_true, y_pred):\n",
-    "    \"\"\"\n",
-    "    Calculate the cross-entropy loss between y_true and y_pred.\n",
-    "    \n",
-    "    y_true is a 2-rank tensor with the desired output.\n",
-    "    The shape is [batch_size, sequence_length] and it\n",
-    "    contains sequences of integer-tokens.\n",
-    "\n",
-    "    y_pred is the decoder's output which is a 3-rank tensor\n",
-    "    with shape [batch_size, sequence_length, num_words]\n",
-    "    so that for each sequence in the batch there is a one-hot\n",
-    "    encoded array of length num_words.\n",
-    "    \"\"\"\n",
-    "\n",
-    "    # Calculate the loss. This outputs a\n",
-    "    # 2-rank tensor of shape [batch_size, sequence_length]\n",
-    "    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y_true,\n",
-    "                                                          logits=y_pred)\n",
-    "\n",
-    "    # Keras may reduce this across the first axis (the batch)\n",
-    "    # but the semantics are unclear, so to be sure we use\n",
-    "    # the loss across the entire 2-rank tensor, we reduce it\n",
-    "    # to a single scalar with the mean function.\n",
-    "    loss_mean = tf.reduce_mean(loss)\n",
-    "\n",
-    "    return loss_mean"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Compile the Training Model\n",
+    "A better way is to use a so-called sparse cross-entropy loss-function, which does the conversion internally from integers to one-hot encoded arrays.\n",
     "\n",
     "We have used the Adam optimizer in many of the previous tutorials, but it seems to diverge in some of these experiments with Recurrent Neural Networks. RMSprop seems to work much better for these."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "optimizer = RMSprop(lr=1e-3)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There seems to be another bug in Keras so it cannot automatically deduce the correct shape of the decoder's output data. We therefore need to manually create a placeholder variable for the decoder's output. The shape is set to `(None, None)` which means the batch can have an arbitrary number of sequences, which can have an arbitrary number of integer-tokens."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
-    "decoder_target = tf.placeholder(dtype='int32', shape=(None, None))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We can now compile the model using our custom loss-function."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
-   "source": [
-    "decoder_model.compile(optimizer=optimizer,\n",
-    "                      loss=sparse_cross_entropy,\n",
-    "                      target_tensors=[decoder_target])"
+    "decoder_model.compile(optimizer=RMSprop(lr=1e-3),\n",
+    "                      loss='sparse_categorical_crossentropy')"
    ]
   },
   {
@@ -1941,7 +1823,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1960,7 +1842,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1971,7 +1853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1989,7 +1871,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2020,10 +1902,10 @@
    "outputs": [],
    "source": [
     "%%time\n",
-    "decoder_model.fit_generator(generator=generator,\n",
-    "                            steps_per_epoch=steps_per_epoch,\n",
-    "                            epochs=20,\n",
-    "                            callbacks=callbacks)"
+    "decoder_model.fit(x=generator,\n",
+    "                  steps_per_epoch=steps_per_epoch,\n",
+    "                  epochs=20,\n",
+    "                  callbacks=callbacks)"
    ]
   },
   {
@@ -2037,7 +1919,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2144,19 +2026,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 67,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcacd243b70>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2164,7 +2048,7 @@
      "output_type": "stream",
      "text": [
       "Predicted caption:\n",
-      " a small bird perched on top of a tree branch eeee\n",
+      " a bird is sitting on a tree branch eeee\n",
       "\n"
      ]
     }
@@ -2182,19 +2066,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 68,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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1gfj7zX2oVXn4aNNDQY16O0rYN3Wjbe5SLa7uynrezNK0nGvCGEjR/LExmTAYUjLMQmZwchkKgkXUwf1DAAmRoAGJ7hIU1zJ5IufKxfk55+cX7HY7clGqBtKQTJqHmXWXJBgzLwXGZGh0SPvCzvZrQHWfExCjEYoa+CcYjtLClw0kbFyAhpxb6K/2RWf3mEOc0qi59qCPaaw9AbIAc40cNi9daf5DE5qLyEMTCg3M27N+1DRs451oEzKXBFMTNGGpOOLCtUyX8A/X+ZefybS2aVIJimhEqJSspDQQwuTCQLv5b9Ef6RtzxqOUYWjW0RxOLwWGgS4wYkxYFEH3x74puxCo7rrM4233tkhCZbPZ8OjRI44PRnIuPseO1wR1d8vnJ2jHWogLDOgp2jMhFFSVzcbCMW1CSylsQpwXQlucgvvOCgHn7WdiShys1oxDYoxi8WCnIA9hIIbUTbLqAz1PYAMzgcaAE5wdiS1ahZIzuRQz13Km1ErJ9t1A4HB9yJhGdrsdQyhEzdQKGgMBSDEYw3EIDCmQBhNaEmbBtyQtSVBHrq3vMYG4r7zn6/v+irrQ8ECwWB8lzxuxj2/QrkXE3Z8gEGXBqvMNH4JRg0utVNekpUUqnJ5cFxu9UXS7EBLTYuhMHGqae1cKEQsDLnGFQPPKnDcQw+KZw76gAliwSrup7kK9ulup/qypaftgJv44jqSUePToEWcPLyhqFkSlID5OqsWYqdLWpFlKw7BCJDq+JFQtIJUYxxkLw6zhqjB4v5fuaUyJXAv4M5Y6W8YDgayVUJRH5+dkrWx3E8PBISrBXK+UbC2WgmYjs7Ww/pQndtP0nvjZk9ozIRSaGbVEYME2SNuE6nxvMAk6+9UQo2m6Wm0TlgxBFGpEY5zR6jAnl+DasyzQfgSLF4fm25vQ0VrZTbuFKSuzhhRDnROJEFrs2rj3U0mYY2v9bkJhSMmpp0a2QffHYt6US40SXOtIt3JsY7mAq+rhx8fN9MvAll16ad6aaRsaS3BhHnetphn1UINWqLLwyZcuCo18JY9pxI7GLftSDZMxwFUs30U8f4TQn7tZWyKW09DCkj0q4QIE6HbE7PrEro1jip1ePq7W9u849jW4PjhgeHjOVHbkIgQCheqAsYC2uTAMyB2czotQ5zDMUQSnWxeoIeCkjMdaE6St38swfLOapu2Wi/Nz9MoVU2Y5900/7Wx+NhcbpmmayU+YNdPD1k/Rngmh0NZIrZcQ72o+JiHSfGVECWlguZNCDMQglO2OXSmUMDHtjEQyjoODmHST0UBB6UkpbWEZ7XlpZtLN5UGkuwJtAUUHQJs/jC9sC40q45DczG9MvMTgC1Kk8S6kE7Das/ffA74Il6E35rCb/2b9BvGMPbOO50jEY9cVAam+8RZzIHOk5zGhUBNVKmhFtaAqe8Dm0j0p6sxEB26XmMjSpQCcINWS0cz3b1aBqtPT/b32e6mX8j50vuC+8OtvdisBiRAjGqIJrjQQUvKHjwzjSIhGmQwOQhpeEDpXo7mooAzRhH3AgNKgglQhT4WUjOzW5rkBmUu3qCkVFoK7uxSXohWlFLabDffvn7HLnuhWJksFyJVaXEmGASGSS6bk4oKYp27PhFBAlbKbXJrZDMdoGYsxRsYx+u9zyEZkH8WtzuEvuWBsVkO0p4stsWdVAjglOAvTNLGbdoYreF5FdBAvuvuRYkKCMEg11qJvEkt0Sq5pQ9+AfaKHxFhHTItYuDCJhzqjadjlRl22PTRaTDiYQHBtxEyyaZ9rYUjcN7fndUthgY3Y583/F20Cxv6nT+jODNr2T/YIwWWr7tJDmHaPc0THhGe1K+3507qwAkCahRRSx5mCSQ5EhDGkDkib7rC+TKVtAO+bznksjdCoWi1kGZTi27y6ZFGhC/3gP8UtSIkBKftAYMuViKEJu3k+bFP7e6poNSFqVlFAZJEAqDO/Zi/0rCboowRKzZafwkzxD0GomhCthGSCrxRjp7aM2VqrWThPXmpPbM+EUGhTk5JlfA1pIA2JlOzBYzRyiSVCGS0V8El3X1Zb+FGpeES5ZIIESvZcipKZpp2BgZPTli8RflJqaamLdGgXAkEmM0HdDBUJpNSiASbQYoyoVgomKEKIzoyDIURCnAkuyhy3f0yTY4vYlGMDA82kXm6/Bs4twUT77sKshj0UvwFYWmvHJ4J4SHNhIbTriBgb0Si+T9jUy43SQFXnRSw5H9aR6v1qHArbOCEEg/NcyEoMREJnJtoY2OsY95dtM9Wjj6WFrxUpbaTmNGOzSFIX8PaMsw9fnYwUxLAHrRlRRULFomBKCBAjXSGIRLcuLNrRnqf1u6oR5EIOls4cZoshiMVNl1ZU+27JhTJV+4yq8SucH6OqhJSIeAQKpZTc6ddt7qpWci2//4DGGCJXrhzR8hlapp6l8TYt13w1Q/bNnModdMy5spvMHSiqlGqCgGILZMozkNlsZQkym4qu0bRUD6F5UpT7zJY05Kj6IiIiAcbVyDgkRCAEJ02FZJmeoqAmWGzZM2vYsM9UlL0N2RaWdoFjLE1jOiqO9jueUFsNgY7eq0cUZI+xaSMJrbZDwyeCupmvi/wPkVkAVJrx3DEIREjJ+muoujCkAcTDhL6BlyAxTq5rVpCxV10AR2OzWkRBULcIaRiK3zNInJ/DHgwJFtWptRorUhUN/rwt3IdbAiEiIaJgdRGKzXfRymazmxPKbDJ62BUKIoYTRA/9Sa0E1O6N14DIhVJiH/cgUINZMLkUos5uWqWaBoM9jkwn8KVIdR5LE35ahVqULKUXhaGPiAtud5UHiazXa1vnT9meCaEQgnCwGrsZHFvqq5pNawsHtAYotpimPLHLhd02W32AaeLe2Rl5aj6uWRnrITAOQ2cmthBRm/PHgLxB9qT2rLWXfnPDJgzZLjWjRGhREVWopafX1uCWRhSCL+A2Se3zzWwVMLNRFMvInE3NGbGWnjKNzvn5S4r0sr97QGYDZ4NlEcZgnI1AJGGm8NJkb5/vRWWa3+/jsiy6om5VmWWV9rkgzWLRJlyMj9Gy9ypONKLlBATiEIy54OOiwVwok1eLa4+DDXkD+Kql1ve5pWE+TXu6ILZpgu3Ebps5P7/g/MEF01TZTW3+2hqx8HFJgZQqJYMWJaZkUYBazXoMYk9RlJoVoaIBalbikEghGgs0CMTgUYlKqGZZJiejpZCIQcnTZDjayqwbnTJCJkUlRCUNyV1XQddiLmEblwa2yL51+c3aMyEU2gKeyTvFX5spvpuMEbjbTeQ8ceHSvGVQNrQ1hUgcA1rNhIsxEAN71N6lUJh9cno69mUT7jK7rrVu7iuzUMGFhcDszXZQ3DaxCFGNltvdnjD79ks3wrxS6b4/tdF/503f2JIth38pFBrOEJhTgq3ykTDEYFWhHLsJbmKnGAxcc20fnGLbCF9Ls1iXfRazulJKZqYvTOjLWEX3n8W87tKo2c4fUMFs7CjdUqhaew2Mou5EtYpc7Vkb8HkJsE4SbYxdYM1hT4WGBxXMXWB2mURMcFXnxLTQdQN3a60mxEpBfTxaNKeiTo7S7v4NPtZtPS77uMfC3YvmWPQA8YIqKYFE748ijhuIW1rSxr4JUkxYP1Y35Bu0Z0MoALtc3E8LvaxazjbBljmoTJMBKCJz0Yo5NCloncAXoaql/6a0v5CX4BzuS89akV61pkcEmkWh7nMuMzEvYQENmfZv7N2vf2JhwjeTFmTPhWj9bdRudIENiMWxm1BYFmQJbl3Nt9wHvmIIhMGSu4bBEmrAwntpMJN6Lndm1kHsgGHsYyYNxPPnrw3cq4WatcfmlxYR/t0hhJ6TYMJKEU9NDk4uMzA2Imh3sUSt2EhD8dsoLseBuo+r9PGKgjSBGWfui2p1IpR0ULStrRYOtHlekr0WnBmlC16VZos4rtd/HJCMkTSMDEn23c9LVmkXuAtLL08ZotHo61S4uLhwct6MZYSgnpEa3T1qoWShhVGftv3/Fgoi8grwPwEvYnP006r6X4nIfwj828A7/tG/olZb4T1bKZX79x+6KWspzVOeZvKQ3RHQeaBDiz6U/n5M++BRjNEXvn1nls7QYswhNHPehUvc38zaNLr7fQ3UU3UPexnCXCzG5Xu1WvivaY7SBYsHMnPp5oSIEFrYKlhiy3KxNEyiPU8MAYZ9ULD1PfqCsRoD5qunITlQKhwfHTOOA4Kwm3ZstjtiGr1nzDUngxN/mkCr2gvS9HAv9FqUDWgUs+ltTkVIYm5CbdcXIdfcsyFb2rUGs6hCcvqzmLALtJ22qHWps1VACB1P6IIKKE34mrllwsznNYpHBxZxTcOd7AvzBp1zR1qlq26hyBwyJEBiwRlx13Fw9qosLNLlXC1Dlcw9IddmrQjb7ZbNZsNhPer05taHEMzyq1qoSShuuVkhmtRosk/VvhVLIQP/rqr+uoicAJ8QkV/0v/0XqvqfPu2FSi48uH92SWKaNN+vwtPMfmON1UUI0zY4nY0I2Ebwe8wba6nh5zhx+1n6y3DJlOtafq7tsAS7gO6rImHv+8UJWN3UE+cXtO8u/N/i7kJyMKwh8k2TDTIshN+iBJlTfmVppYiFAaPX7gshMKwGrl474Wh1YOZ0rWyniXRxwW632HAyE59KLd2F0VqtjkQtC80KNecuFGz8g5uupokdpuyYAljSW51yxzFKGqjF/Oc0BJbkL1yQi+hMzV70EZ1j/RF6v4pnMzZatsoSkO3GmDMUB8ZxpNaJnDcdtCs9HLlwn3x9RjwStkT+xfCmqKHfO3jiVSsRuFxXl60EmiByElOtym67NXLSNpPHSlvdfb3mggZhUi/u4sWIVMp3JyFKVb8GfM1/PxORz2Kl3X/PLabIycmxD9Rc6qrUydyGXDwk5pTa4pvNrQbDEJQUovP/fQOp9Jj+ni/sn0EasNdAzdk9mLW+Oojlr6SJIZ9IrQQM+4giPZunhQqbH2qIvlj+RM19IQQH51q0wIps2HurceibrCHTMVrF3jky0UxDJcXVXErON07TxqiSSMRBuHL1iNOjNVKq+8GBdLAiRuH2gzMDxUJwS80EztCqWcdArZGJCSmzX73kKzSXouMN7hqE5prMSplpNxFrZZerYRlaGKoBcsNkGk7UOARdYEv0kHET6tGFfd7Tvi3fIvV5n0FlxGjH4pvSyrpZaThjpi4sEBOzCzZsWxeFEgKi1QR1tOuKWx8iFtUC3BKdAdKlkmn36W5jcwvV1ryECKWw3WzJ00Sedux2W6KAuGsdF4K4XcuqRCckzvP3NO3bgimIyIeAHwT+IfDjwF8WkX8T+DXMmrj7jb6/Wo18+COvdFS4eF5BQ9QbkGhVdNXKV7e6hMXANlWrsmSgTuPN165FKsWR2eAl4h2Vl6aljbF2GTPor+u8CGFGulMvFe/cg/b5YJWYlwBlL5Xm2m1IiTgYuzHG5BGKSHQgqlV5bsVRWiWlFrtveIm5RUqtHiZrrghe3NNDbqKCBi8iAxS10l8iloMQUmJMiV2ZQ3LBkfIkc/h0uZgbDbzk3HwC0/hT7htfYiDGwTkc+9ma2/Nzt45MKMQUyWGyatJOXmogpPEBgvvQS0E5E7uWUYmufWMLo0YDFh2wTV7PQsUiRMgSj1mOo4HV8zrMeyUCZ5RoxhhakZ8YjIdgBYjrHgHPxnfGvKZp6s8lggPIuqeo8pTZbDbENBCr1YGoRS13pFskYY82PcThG22/x9q3LBRE5Bj4GeDfUdUHIvLfAH8VG6W/CvxnwF94wvf6uQ/Xr1/l1Q9/wCVk0661x2Vb4VZjaRk/odT2fiXnyZHYRYUdP+8Aj9Mvay+A9BToFgOsWBl38TTbx1D8XD01tRWAtUnP1RDgwVQuDdtWrAxZWwT2e3QcwLIdV+ux1+MziR7678lTqxur08es/wQHURsxyPgclilq9zfgD+BQognSqlSZiMNAGkbTXuJRhGpVesxaCR08A0sEkzCP45Le3Mg3GpwM1cbG/XoFIxENrj11/m7Omc35BbqsBO0uDmIl8OY5qEY6SoHkgLSNk1e2bHBAAAAgAElEQVTEiokYBkLQLiSauyjairI61SGYhRgwi6Y0sFKXYO+MQU1qFbagZT0ui/WoR0H2BZGbCdDyOMQERahKYc5LsGvuK47QrbTZ1ejgpq/hfQC7LUndu47lDmUkyx729c3atyQURGTABML/rKo/6x17a/H3/w74O0/6ri7OffjoRz+kL7xwY2FSzUklZi14cYvc3stewqzuWQ1VrcTWXHnJ/t4EiYV3yh5i3eL9PdzkrsiS+lxrpUxGoa7aYtf+HABipeVtwdiQxijUOhkN1sNQw2hFVYYhOWMz9fBUSLYRAiApWeiQGYRq/q8ZQLZ4S7Xfu18cQEIidrB08H4GcqlQKpuLDfce3COUE1bjyFQKwc9R2G13FJRhNaJA3lmF7RSMSNbAzRBmE7dMuZuqLUlHmcusmcbcB0mbQMjTxHa7JVerzamO+iuNy2DgY1sT0cdsHIL/OzKurPLQkJS0Mr5FlJkm31yIPc5ENQFPNawn50yZJspukRzHvAnNnc0dwOyYUhcMC4BS2MMQltWhQ5xdBN8De9jCMru0W2rNrWguWCN4hWCZwEHIUkyYh9gtBRGLLkkbv8cx8Pds30r0QYD/Hvisqv7ni/dvOd4A8K8Cv/XNrhVC4ODw6Al/aceaAY74G7hYnKDSqg1ZrD57cpMutdGUHaxslscsDFoVnZwbRXQ+z6E2oePVf0suPR116T9H7PSdYTRU3w4WsQIYu92uC4SWnjsOA+N67Oc/pBTnWLYI9NJpEcHM7Wma9kxWxAqDVKmWMagRURiDWR2Wzah9keJAGWPkQx/4CIdHB9TDFVcOjwFhKhMPz8+Z7t3n5P45Dx88JG93xHFkCInddmvEmb5YQxcKBlQ2oatUtYhHbhvc94y49dDg1bbxqyqlWoHXZkloK8HuocAeRZgqgYLKgCUtCjVY2beKslHt492FbXC6eSNqLcDY0kry12oREJbA3wxgilgui+adVdbS4tWkY8dNlq4GzHU9Qoy0oi+GMdXOidmLNshsmZRczCoNwQS/zBbkkvVowkJISqfl7/0tivNQAk+yLN6rfSuWwo8D/wbwKRH5pL/3V4CfFJF/EpNNXwb+0je7kCpMU+5Ss+fFOxo/17szszbEylKit+Kll0HC5eadtW2zQiy7TIuFQEvxUFNZ+o1eTRlLZpmmiWm369hH9bBQbMAm6gVDPYQW55i0WQiDCxADgIYUTSg4pRcRJM2l0ryUFFIDmrGst2KgawhWjyHnuOeDNi0VPRqBCIyJ97/6Kh/44Cu878UXsBw6yzxtAcKK1ZA8u9hw7/59XvvdL/HGl7/CxcUFQ4zkPLm3tbCk1CIpWibTuKV0E7wlNoWmpYMXnPHnTMFCrqv1yFpWBJ3Tt1WEKkr1OhBFbayrb9BWEDWKXa9Ok1XrjhaGbvMXUyKKRaXIZtLPLE3xeZqtFGrtOAiL2JJ9xjCTFAM1Jq8Erv10qfa5vr7UBba7MNWtIauJIYu13liac3RAQqtfAa0OJI6JpJh6OHf+eTIXxzplP08Kl79X+1aiD/8PiyFctKc762HRSik8evSo+4Hd9PIHjguhEIJQsw+KT6rgPqanWDfNAl4DkDlageuqQnG/Wy3RRKsLpwk7UGWBQwAqwXzPBQiKL6iwmAz1km2lWA2GqmohOWCQ2PP5WxowzFmMtXomZox+hsWcgFS1stlu2e12jo2qk5BSD0VO2y3DMBBDIA0D42hpwS+9/8N87/d9L1dPjoiAlkyL9beBCiKMItw4XHHj8BbXT68i45rPfOKTDLnaeLVUbM80bMG/2tyEarURgohnItrchcHO04xer2EprMfB0pYvL2hBetizuyqeBRmlsfeaFpxBtq5ta0UcPFWTQ1TUAFF7YAJLDV7sO9XZpl3BQBWLNBhUEAmhElOAWgmhMW9nV2DOdTErahiaSzN0IBnwVG4LPVIX5Dh3+UQqQ7TyAVNVMpMJmjhYURm3FFqOUCtrt1RGxvUKPDEF9j3aM8FonHYTb77xVmeypZSsOs4CnGuorAmIRUkrZtDFqt0swk7ezAd07RAcfHJOPWoEodZKeTx/AEDSYBv30vkOmr1GXidTzT/TNNHKgC772uLrFgDxE6ZcvgY/uzGX3OnLpRZkCj1LUL1oRnVXJiYL0ZVqh9Ks12tGzAY4GFfcuPUCw5iMCKV1n8iyXCu+6XNRxtWKD3zwA3zp81/gzc9/yawON//nDWybpGWSLjf2MA5zUZMhGfsuzElLDVeAfa3HYpwE6VT2mb3ZQrxmHbHw0ZfhuD1gbvmINnlQIVdTDK2C1tJNM1dN+jkc3THQWYForV0ANNozSMehOtNSo7FlL7kLZkV58V+d+7+M8IQQMK/Yi8/6dxpDVaKllEdfy23cluOKPiG1/Ru0Z0IobLdbvvjFLzEMo4XivLhqSH4I65DseDXPnoxJuoAwLQMgHIyrXudgeZ5BdDqoxEDQ0LMHG+MsMmuo5k+awFjEkt1sQ/fNsGapSAh9k6NmmE8lMy8n9qIasF+gxP48b45Rm+lqIdc0jqwODpgmO0S3+DmR7cQis1qs7JmGRCGwmQoyFWO3hSb8GmD5ZM0hHqbc5onVao3EwIPzh4wyWOlwR/2HRqcVSzFOfrr2skr0clHa+QrVKy3P6c7tuS+TngQ/O1HEypTVaq5HCXOUwzeIBs87WRDGlqByp2PDzHQUMY4CM3iIiCc1BWq1iFbJhfk4OyttV7J6wVwxu7PhN26DVp0xlz7fi1PLG/HKZaBbjhZ2bmFPW7teIVqMUJtCInloN3guCjhw6spmvt9inWl9z/l+UnsmhMI0Zd5+6/aiCOdsEbRNnYbkprElPSUvxNpDdCIcrFaM65HVuA/kpWQ+fHTef4iJQebQ1xRmAlCBRbGX/TiyyZ4F0kxzSx4f8qD0swyRfaGz/GnXaqSf5QZZIvWr1apvJKWBrNqPy6u1MLnLMw5m1Uy7HYhwdvaA+sJNNFkgbnauLjVp9TEnCIFtnnj73Xd5eP6I4/UxUsWKkfqmaqGxEANpHGaauQCd6GOmt23OAPK49l5qsY7Ge/ShjcdyzCQErytQaYxXAYrMjEZdrIvkOEKvruBWTozJuCk+3VKVIQ09SrK0UBp4bYJiPjRHULTnd5gFsrReu8Xp/UpeOLhbWmEJbs7zb99dVCPzaMgwDhZ1GQZL4BJ/VqULAkseE4tMiTgv5/eZUAhBWI9pXkRlolbTFJMXnVxqfdW6Zx4283y9XrFajRwcrDk8PGS1HlgNKwYXEqkVbxkGkpf3CjH66cRtEpfZcIsc90USC8xaPTZxz7552BYli342DaquQfaSrhahpPasbeuWUlivVrZQa0VCodY5lt3M6urkq07Yctfj7PZ9bp/eJb14k8M4GJfiicCToDEAge12x1de+wqP7t3nxpWrhME2S3PrJBjiH2U/3NeK4oYYqDn3E7W7QPWTu23eQz8qrX9/ISBymasHWbiz9NO0lhut5RlUWWZmLkJ5e+DiHDq0XkViMG0r0BXT5ZBjWxctWc9M/gohMnRr1bAe6WmtbXpnwHLPZQrGlVA1UV0XJ3/V6vk/KtTqvJpg+Q3JQ9bjaKHjULPzP7RHnVqmawNUv1vRh29bW40jH3zl5R4CbGc8NlKJgX/qMeDYTzYudV4oDSGetjum3Y48Taw2A+txxTCaYBhGQ//TMOyRifCzDi2SN/u80hB0Y7zsLarLdQdnKW+TEBeLsVOVFxpOVZEqDdbYcx32w2Kx11IUkW4p1DmrqJdgkzhr06W1kUvgtdde5+7ZPV699RJXDo48bdidKJlLmm114uzRls9+/ot8+Suv8/KLL3GggV0Pm2KuiguiJFbXMMVIldklauHkhos0IV5y7tmfbZMsk6qAvhHb8z6RRdksArBMQKBxBEKIlDY2PU4/20ci0l3BVi9CYkJTMTfVN16tkHMjGrVrmaC1bF2v/cC88ZpbszTGmpe/r1RaGNE+ESTuuRwtbF5DNBdHWmy3ges6g+fOHW/AKYhXiwoNW/89tWdCKAzjwEsvv29vATQi0bIEe0E9nqwdBLJCHdkTVqxu/zAkwydS7Me8ixh7LXtoqx2ievlwj3ppAPv7Knvv9YKiYdaUSx86LbCRjmvYVlyE19oCtX60kFvPyxDxYKEp9gbyaQOuwNZJo1oH7eHK9fqQw8NDRAK7Wtg8fMj27Qf85p27sEqEaNWikofw7Ej6ifJoy7TZUqfCy8fXkOPrFtXS/bqQfU5K6TTs5aIGs/I2m80+fbcU1MG8qmpgX5kLxOALWVUJaS7ZLk6YWobXWtRmPkPS6Q7SMgPN2my4zhIMbeAgqh2LaLUI7FTwrVVzjsFS/7zce0wB2bmgEXdl1FmeJSAp9RT0HjmLERkiBBiShYGtfyZ0RAIleA0RncPrMUTQwIQT8/JEnSao2Y/J8+iU+nF1WDVz8LoOuYVN+e4xGr9dLYTAycmJCwMjIyFCUOnxcIVepSY6oKcKSjvHkTkZqkcq5vBPCGEujQ7Umvv997SQ/9vPZ3RzGJbVmtq/c7bjXmTBrYXR+Qj9mLZhTobJfv0YAlEbRmIAk2mp6j5nW+6m6SzDr3bLZs9lwVyw4/UBR6enjOPgFkC1HIsY4eICnYSwK4QL88mHIMRaCTmzGxIHV1ZoNm1vqd5Kck122Zpx/dXfW2q6hoW0I9bDQnA0BWAZic5xWPBMlsKlafru28eGVVxSgqFNjjo6ZIw+PF9EXbsGmQ9l6RaEzrTiHgWRVjjGaOJm7SxLprVIhWl8ozG3DUqnYM+uzkyGah0PwRXFpTM8+5w7wSq6q7XdbNjtdmx2FwxxbQLJIyh2luoiX8dtlHEBSj5NeyaEAn2zzWGuJassOTLrzAJiXZbXArSahl8ANa1SUJT5BOllqLbW/dDjbE3YwksSll1zroC/WgqRNuFNoGkG8QwIzWgdKI7YC3Oiivr5hnhIzyoaY2HYZDn4JiAiMVl8O6TgJdSco8EcNq1V2ewKaOXoaMXBgYdntbKWge0QeLgJTA8yYxyQgwNiCByOA2XaUXJmYE2YtpQ89RBrC3kayGhWl9ba3Y0WW1+6VG3Tp2Tg8MHBwWKuZ4C1J7Wpxeq1ejSgzBbH5fCwWScLM7tzJ+x7bcKWCqC5f00AtHoWTeEEN/2zcxWKP1+jQDeuSLMw9nIVaPxMWVgsMvMcaELNXZsYOtOxWa9qFzJswRPAQsAKDvc1B2XKnJ8/4uHDNSEExnVBmOdpchKZ0fPVFYew8QzVp23PhFCoWtlstnsoM8xSW/z3Zjoq7uNjcy0hNJ3g35v9+JYRB/uI8DKLrAmFJQ99Txq091w72WtoGklklhOdmOPXTGmRyacwOKI+9ErVCfaoualvpnFMDOPIar0yoHQc5mzKBTegA501O4029irRWhXdZUpaMY6RdwLkzY7dbuL23bs8uHeXe3fvsDl/xMnxES/eusV6NZLigHgYWHWOjjSt3kKRTXvbGMyp3DHy+JgyJ/y032ut7hLPY9uqMS9dhVZNGrxQyzLk525FO27Q1lCZr1dmIdCJZ36fNkaIQM5MpdhpTbMy32tL4K6tuOXzN+EQQiCXQirZSEselZEg8zGBMl8nRCM6SVlk6rqSDBLQWtBiNRXOz84QVVa7Lah4FEopmj0XqHbrGbGCK7/vgMZSKvcfPnJzDmA+AajRZFu6cBMKlhSiPRGkJZ+EEDwmboMT9gSC7N1zCRY+6STm1pp5OV9nFgpV8x4m0cw++8yMWViBj9BxBrBKxjFFq0rkYdOWJzEMiWFlh9msxrW9ToMxBJf4xaKXokJYjf46YaVGBA7s2U+p/N8//3/ymU99ivO37vHVr75BDPCRj3yIF25e5/Y7b3Hvra9yenqNe/cf8u69e5yc3uClD7yfF156saPeqMXOd1MmYrH9ZhrDLHiX47gMv84afHan9g7EaaAv8/VgoSxUutW2vEdBLSLQKkNhDMiqsxAqJbvwcDxDLYkOhYsY0ACTWzAdJwrRT6UKtCzMXtVKvKJWszh9DKRRzBfr1+jxau7vwn0wIRMQLeCKMRBQsTyJ7JW5tFZ2Fzsu0hmaM5tHK7ID81Uruzx5peeGs1l2aBxmpufTtGdCKEw5887b7+6RV3o2nvvDq3HsdOUQ7JCVKOL0UXcZhraxF0QY6MkwTbAAqJZ+0At47nqsC61/SQiEBWYAfa0OXmm6fba5P63cVzMZYwxoGg10anUSPOtt9CSo9rPySElaWQLVelxZjb9o9pA4SNoPJI0jTRhdbLacn1/w4OyCKRfOLza8/s7b3H7za7z1xhv83Z//BUSUl25e5cVbN8l5R1xFTm9c4WC34iuvvc4bX/4KpVTuPDjnnXd/E2Lk6os3uXbtGh/60Ad55dVXOTw8sHFGLOszDcYydEp31TmhTBbI/F4ouVkWbSF0sIZuWrfrsbAEgwY77fsSyFMx8I/mUlKQCmVxEne3MGjVsLSHI1ebFffevcP5ows2Ti5KKaGaKU2pLFzUIHYCWMcaJBCETjtfFmht+MuMKcxurqKUvI/PEAQh7BXwqUCZduwuFAqkODG5UOsVqvEIlwu6qoXiVvjTtmdDKEyZN75+t+vYdjq0SuX6jat870c/zLVrVzk/33D//n1uv32bzcUFqqYLU/QqRWk+WqyFAK0mgZ36a7yEBfqc5hDa8sCS7gfiKK7776FZJNJotkKWumCotciB9kUIs+0ganHp2BeSnf4TQnTUeM58izGS4tjvY5WkPAGpNmFwDAR+9ZN/n//3H36C43jE2+++yZtvvMWv/+pvobUwDsqV9Sl3771LrYUbN045OTniwYNHrIYDXr71MudnD7j91a9zcLCmbM2lOXt4jyTCKgzcfveM83s7vnDxJb70whf5Y3/iR7hx6zonp9eRNHBysiKxRuohRSdWY6EWYcq5E6iCFzQJTSv2hQ+pnbzlI9W5BaixwJpl4YKlhmXFKWYBTfSNUFENRBmQJKSF68EibKtNA6i7NRXW6wMOVgc85LyfzpSVBU1ZDf+JECQSuttQe2pznjJDiAzJniEKBAJJEkJEq9eb9ATxlkdjXtSCp6IFciYFo9/PrgSgSik7y5+vZiVGDQbSoySdBWUWKHk/7PuN2jMhFFRh57Hq2v155cqVI37gD/4hXrh5g1oy69MV62HF17/+Nu+88y6omVTGEoPBz44wKe3HurkJP46thsGcbNUKnMBMUnqS77W0YGZ+/UTnJchsFrfPJufmW18sszMNjiirRR1qreSQGRgdTymUIjNQVy1ctcsTafAKxxVgQMOKX/gHf59f+Plf4Au//hvkBw+ZpsIrH34/d+/e49qVE15+6UXeffervHDtKq984Iah8O7r3xpf4otf+BK379zh+rVr3HtwDlS+/Pqb3L93RogrJAw8erRBgV0+58H9HbfffYCkkQ9/9FV2+Xd45f23+NgfeJXr1xNTPkOAi0dbYGS73XJ+fk6tlcHPgViCuq4Waac1tZyQGCycN442P5fdO6mN5HOp+KmfPtW0uTSwUUCqkYRaREnZb21uV+Oqa/jqEYUYAwOJMs0uiyzuYQLMDnDBM3ZzS96Koeem7Fkq7mos3aqGz8xkN/p66e6sCwYRUDEXqGQr71+VDnA20LydRRqesK7fqz0TQsGAKTOBo9DLun/vxz/O0eERZw8ecHR4SN5mjtaHvO+lF/nd332NKNb9OpmJutme92u2xCL8dB2jSTcwL/Qciza5ze3YS7aSuRhqiAMxWCltW0AGGrXNL5cWYnFmm4gSi2MfuRInO2R2Dm0Jm+2WlAZyHokxME0T6/WaUreIHBOiHVWe/Wi0IQ789Z/9Wf79/+A/5u7b7/KBq1f48K0XuHL1Gm+/+Tbn5xtiSkzbE05PjhiGyNVr11CB880WVcxSWB3x5S+9zhc+/6YL40qRwsOzHSUPFA2kMREibKZzym5k2mQ+9+nXefON2zx89IjjdeJP/5k/zj/7Z/5pBCWjSBjIkx3Tl/PElDO73c4iR4SemQiuoXv1qLAneFuiVTtKsOExSYwUNp/l4RbeYu4Wq8s5Di0noHa3wY5jm1GLHl3CQ6zBiuIGjagfL7gEq41CRC/oAjNgrTqXW+sKp1VRCkapZ3G9TmHvRBkPkV7CxEzBGQiteCKVVPJUjZ7eAXIr2IPMNPCnbc+GUAjCMIx9YzX/6+TKKVrVcxkGzqcLSlVOr1wjpoEhefFRtVOlGolnBrkMzKuqdnZkydTBz3uUQpraCUxzpV8WVNPmF9rElrn0V/CkrBD87E7pyUKhlfpyQNDASOPdV+fM56yI5C5ECMbDHzY7YhRW6xWHU+WojEwqHBwcml8MHKxXfPlrX+TTn/g1fvxj38cH/8Qr/NbnPsnhyYpAYByOeevBfa5cGfjkb3yKF27e4MGDM1arFUFgt9ty5coVdrsdF+c7Lh5eAAK1dCr4eHLI7TuPyDtLC7595w4nVwbGlGAobC8uuHfvXQ4Pj3n7bMPP/MwvI+MhP/nn/zXOt+c8eviIIRjJRtcrVmUwv7kUpNjhLxUsBJizWYm6hGjbunCXQ0I/7DelxHoYLd8iJseLLNZ/+TDb5rvPUQa77jKcaUC110jc7pi2G0s608a30HnDLsFnVYoW7GAWs0JQeqVo2HdDGx61FFpLe6Wt19kq0Dl65GHG5hKPa6PyxygGik5WmnC33fZQ8Wx5aB/zp23PhFAIEjg8OJiBJoz1t91uuXJ6yvmDMx492kCMDIdr7r3+OuMwsh5XlGky7UwhOJ8B5sFNXuevVT5u2ZUV8wmhUTxMa8QGGDk2ESU5gOSfEgMIk+MT6vGoXnark42aOxFpXHiryWBVgRsnSgBJEd1tiTt7lnixYXj4iNUwMK5WrA8PGNcjV49PuPPuPd584w1Oj4948cYVNpv77LZbtmXHq6+8wue+8Hneuf2QTOT+/S0PHt728w3vcnKwZjVU8nYHZMY0cnoUuHJ0xLWrR1w7vcL5xSPuPbjg+tWBN996QFa4IVcIceLkaM16fUStE7dvZw4OD3lw/pA7t8/4G//bz/Hg3m1+7J/6EV563y3W6wSrNVSjMguCDqaxqvMAci1MOSMaFinrRl4rVa2YazVBWkumhIlJhCnGuSRZK/XO41q5VTiu0OslWHk+A+bUTXE7qGWg5sLm4oLq/ruIAXWGJwWgLBSO4SNhUbhXpK07xzu6EHHSllgeg0U2IKbZpeg5D8WtlBbdapXMvaBPSomD40NOjo8Y1yvAMjdNKGw6KaylfNdaqW61PW37dhRu/TJwhmV3ZlX9ERG5Dvx14ENY9aV/Xb9BRWcRq2k4vw7UoLz11tt8zwc/yMHRoW2qGHi4veArr73BmAZWQ2KnhfWYvJaAYwS+2wQBbZZAq5Hnefhe7aZVPGoocQMTl1VxzYqonnE5ux/RD/ew783WhWmpSK+V6F5scWJKpPml9tnsEj2ru07TBXLh2PNgz5ZS5HA18LnP/Daf+8Rv8Nbt2xRVzs/OmR5uCQhflq/w6GLHo01md/seeYIhBE5Pj6gP77PNmRdvnnC4GgiSuX7tKjevn3LrhWtcPT0EMkeHx2hIfPX2XX7p7/4ar331ITkbJrDd3OX46Jj3v/oSp6fHvPHmHV79wE3ekjPCBJ//rc9y6+YJQy0cnl7tBKxl6BfVzuJL1XkZxK7VkEaOqpTGO3AJ2hKfetNGasqoYoJkibIvohi5JTPtsrk1pVLEsgljjKzWK1KMbHdbqidppaRk5zDUrJ1x2gQ+Mm9w1bZ+OnuhYxveVccTGi9hv1Zjt2wW3IwWaeouhLsPKVi+yeH6wFzVWslToayHRWZnI4QZW7KU776l8KdU9fbi9U8Bv6yqf01Efspf/3vv9WVVOxJuRuwLEoQ779zmV37lH/Dx7/84q/UB9x884POf/zzb8w0pRXLJhBiZqj1KDBYKbGBVaOZn8A0aFptX0mzKiRFx7MyFllTTwkpW3UgkOrswdnPWiHIzNmCgk7tAbt625wOrJrAMSYn/TbzGgwFUmVpXtOIcJCGUQkL4mf/lZ/nNT/w6B2mwxZMzQRJK4p379/nsa3dZDwfkHNney6QkpFWmnJ9xvBq4du2QD7644mMffpVbt25y6/2vcHLjBkfHJ8QkDCkxrE/I5/f5vvt3yJsdf/sXf52HZw+4+sIpMZ7wta+/ya2XX+YPfvwjHK8DEkeOhsi79+7x8OyCr7z2Fh///j+MaODi0YZhHA1FBxRhiHY6t6hVNFp5ObrQNruY318dUYfZr7bzGBY1E2ynMbVcisZ0VWZBIkLQSs3ZajJgFZkkTx2UyyKQJ+owIMWOCohi0Y4hRi52k6P/xjMJskMwk36mI7RTmuz0rX1+RQvNujAckh+og5+qFfEgK1CpmPCMQchhotTJrikVpVipPQUc5wiqxGrp7gEW50YOfsXfC6LwnXMffgL4k/77/wj8X3wDoVBK4ezhmXEJWKD8MfC1r7/NW2+/SwhW57DUypACeXKSSEdjZU7TFaEEr+FnAW0DXrRpdfMzZ+m8JNaopVXHZPdMRhpqVsOMMdgPIfTXoQmdIFRaDHpeHjg63lFx/91J+671WlKY7Y9cC6vVyC/+7/8Hv/WPPslHXvkQdRLefOM1xmGgivDgwRlvv3uf882as3rGwTgwpsJ6rRwdwNWjkRvXjnjx5gl//Mf/CT7+/R/n9MZNTq5cJa1WSIyoHxiTd5V4cszx6RX+5J8+4PWvnXH24BPceecBN27c4GMf+QHu3Tnj2umal95/jfv3MnkqDMPAZnPOl7/0u3zqN3+Tj//AD6CqXGw2bKYdq3F0ws/M5wgheARIujCNoQmASEpjF7Yd5Q/Sj6xrHIPYqiXlRi1WsyJ82JVqB6KMllNSs1W1Qrx8ns70Ys2FXCqpZKZSe23NVvy3zVOjVrfjB32C+2di7GJuTvUOYEVz3J1yy6hRxTsBSofQsy8AACAASURBVKyKdfZCOq3VUpmm7MVjjQDVaBlTtQK4e8xbsT614/6etn07hIICvyB2pM5/q1a6/UWdKzp/HTtvcq/J4tyHg4MDNuebvdCfAFVaroAxEzdlS0qRnSxTaX0CxEg0eyivzIejxBiQsAg9ssheDIvqxF70ongR1PZ+jLOJa+ZwQDUSkk2CiBFHRMTj28IQFui4CDgDcxm+FLEipZfJNYhAriCBspvI2x0/9kN/hHVI/M7nPk+KkYtd5mJbOHuYuXn9A7xz+wFDhJPjgTFkjg7hytGamzeOuHXjlD/w0Zf54R/7QY6uXmM8OLUN2bAQtcSkgzGSWTNNykf/0Av8y//Kfe7cfpNPfeEet9/+Grm8j49+7FUOjw+4c/ur5Bx5+OgBH/rQqzx4cI/VeuD+3bvcvXPXzHTFQpvnlhQ1JDevxXx+07zLMzEaMzUyjq3IzhxhCAKlQZK+8dt6Wa4JX2OA12uUAE5tt7RktYiCW24pRnIpbHeFsVY2045ARl0Z5JytlHow6jrM+RqXVrb/bQYol8Sh5kYMaejzLUGcR9CwBMNScp4rh7dQqgHXhalM7LKxKqtWtrsdpWiPkPR1hmLJpt/dkOQfV9U3ReR9wC+KyG8v/6iqKu0Mrv33+7kPp6dXddrtAyEigqRImSam3cQ4jpRSGQY/RNMlNYsN1gqiigsEiULsLsPsFjxWqm1hBcTY3ITQM+Ssnn7ysOZEiq0snB3YOlsKs2BqoGfL54gxGMkktBoJc380zoy7ZUxaBrMhHlxsePGF93G3Cm9+5Q1yPefeozO2u8DZwwlK4OH9t7h6Khyu15weD7zv6k2unh4iWrl164SPf/RVPvrh93P19DqaDmAyMC8EQeJAHAbEY/Pj+gSyMtXKH/4jP8RPnN3l4Jd/hdffvM2jR/DZ3/4ceXqVH/ujfwzVwt/6m3+H1770RX7wh3+It9/5OucPH/Lw3h3Op8xmAvXTrVfD2M3sNubr9QpR7eHilMw1izGSa7UaGAwEhSRKqHOp+SYIeuHYht7ozHURWWQg+tpqeQihla3HNX6dQ5rBDwXqJMk+LxVLmW6Y1ZJrQJ/HDmy2CIAD1dbvBdZAq/BkkTCrEUmPfiwjCRala0lpxc7pqHYOymazI0+65/raATmtbsN3keasqm/6v2+LyN8AfhR4S/z8BxG5Bbz9Da9Ra0+vbS2IwI5ugttgZQ8Xzemu1tz0HNKcB+EnF8UWGaBhCjOIuAxfpZiIg53jmJIdzZ48+SgNkSBWJ3IYYw+PhRgYW8JTCj2ZKUabvGmaZg0YIzE60ap6BmS1ZChqclPWohTBAaZcdsSYuHvnXS42FxSFr739Fl/92jucbwJ37+0IAqcH8MJLpxwfw7WTK5wcHXB6fMTV0xOuHB3wPd9zixdu3uDqzZuoBigFZAIVwjA6Wr4mpJE6CLsK66MTap4Ih2u+74d/hIfn53z6t7/IG1+7yyvhFp/+9G/z5lff5M/+2T/Fxz72MT796c/yuc9+luvXrzKmREQhVx7cewRpBao85IKYbG5a0dIhDQwpepkxy+2whLBolbNWa1ar0t21lGzztLES18iN62/Loi5IcJZ5yuK1OOZQq/ZEO/EU8VKrRT2wqtFV53Dk5XRubcldCyAQVavpsBDw7TulFmJl3uSyCMF7VMqsA+ZnhDkL1ZVJVEWnQlYL6067zPnFOdvNbhESX54AHveslW/WvtUToo6AoHbA7BHwzwP/EfC3gH8L+Gv+79/8Ztda+kKqlg2fVMieBrrb7WZ0utQespndJWUYh7lsmvuooZn0uFkVl5GGmRUXnaKqgR5lMEuhCY9ZQLTjykRgTFZq2yyHVnI9koJwcHBgmi6NDEMkRO0WiYjsYRTtlO3eL19sU534+te/zs0bN5AKt+/f5+6Z8vC8sN0Frh5Fvvcj13j1/ccwDUQqx8eGIbz04nVeeuEGx6drVocrNAW22y1D3JFFrabi4AIpJRhGhjHRz0dMkakGTl64xQ/+0I9w/eaL/Oo/+iR37j3iX/yX/hn+3t/7FX7pl36RH/3RH+ePnvwYn/nMZ9hud5yenkLO3Lx+gwfnhfNtwajcDnmJWsqxKpMUs7i2kwnWtpBj5OBw5OBgx2q1JkZ6XU5lLpgSLG5ozD6PQkjzpZvFPLmSWaL6GAW44UxtDRY/89HmYUGlZi6KYxGqRhya76OYYJFWDr590+srgKIxeMGU7IrCrJUQYLvNvehKCC0yYd9s1m2tlcGjXylEqEoNhhtonSgukJj8ceX/o+7dYiVLr/u+33fbe1fVufT9Nt09d5KiyLFEURQkiqJoSYYNKE6UOEISJQ7iIEgCJE8JgsgPefGbkSCPfhACOEjiBH6IX2RLcZDItGVbEm/iDMnhDDmcnuFM37vPtar2/q55WN/eVT1i5JZFGKMCDrr7dHedc6r2Xt9a//W/bNm9P+XjT9spXAb+Xv2CFvg7pZTfVkp9Cfi7Sqn/GHgH+NU/7kmcs1y5dEbcf7J484toRUJYNm66deZGS0pPHtvDMQ0qoGKaeAUAXpVNYVBqSmUeY9ZH+zQq2ajVlqikOOiaWSCIscY5C4xBLLVqVzR9/NUqQ9M0mMawmHU0TijWwkTrpBDUNClbw2Cs0TjXTO2qrh4QRhtCjAyrnitnz/L617/J8iRyeDgQmJPyko8/f53PfPwmQ1hiimHWdjRNw+6sY+Ys1ihyFmKWH3qsNsQIuijKzBCSxs1nYF0deEXaKzHrQBjQwN7157jZdhin+ee/+3v44Yhf+Pxn+fY3v83h43vcfPYGIT7Lnffuc3y04uKFfRSJ/f0Z8XCFVk5SqkqU922LYFRSDXyJRYqVLkSTCSnSD5G2CzjrsHYkfG22ENNgqgA2FN/R6RtEPrFNGtoAvZAQEZypcubRVFUOpiTfVxUa5SJgn1GKRPXnLElOcBBHJGMwI5kJLV1YVpSiUcpQMnifJmBadAsgFowGEV8K0UpwL1ULamJk54YITWtQaJwWxindDGfsJPbKW8xNJhzs6R5/qqJQSvke8Od+wOcfAb/wtM+ztzvnFz73KcYU6dFEYwRqxMdPPlKK+CSId4iRnCQSrZTCEEfkPpNSdWIq09Z4cxHK4SIn5NhZlko+GdvXxtG1DVmBHwZSAD9EueGVxfeBYZDuxXsvKHHatJqq5jOikNRjSrXllpHG2dFA1tIaQ9t2tUhUXMIobLXy6k/XPLr9mD/4/dd5651DjNsjhDv8+7/yS/yHf+Uv8JXf/UfMvcY2Qq9VRFCRYVhzfKRYBIlla7oZRjdY51A5YJNF50z2A0MWenJTPQGLEcDWtXO0aVieHNPN5ly+co3Pff5zHDw+5Fvfep0bNy5y/sI5UIkf/ehzfOwjz/Po0SHffeNNnn3xRS6eOcd6tSZjGUpCK1fR/g2/X+m8dZIVSgVtdVLkIbIa4jSHK63AiVDJatkQjQld0yytJBLOTFZ5sJ2iJP9u01LLKFk5JLqfurec5VBKuUiyeRb+iVJJVpKM0nw1Pc9kw1dxqcY5nLUyqihZvcu2pUb8TduK0VTHTmDkeE1tPCgUMUaOj4/w3su1aC0xRUKMkA1KGSgZgxj3KFWzQP8Vdgo/lIe1hnMX9qZItBxF+pm2ioIUhvr7HEix4EN1+60iIh+jtE9UeyqUeNnBREdWFWRKT4A9UhRGFLybzWg6h7biXxhiIOVq4VXfuPGk8j6wXq3wg5fv0XtikKKV69xb6t6oFI33nmW/InpZi6m6Mhql4sZKR2K0wtqGrDKz1mBT5v7BPZTKhDhw/cIFPveTP8qwPgTkBsg50bjaKhZZX/kQmeVCComs5WsmnSAFiA4VBrLSaJMxJhFNI7tzZ0FrMckFuq4j9C3tbMZ8MWe1PGV3Z87x4Zo33/ge88Wc/b0znL9wka7peO7Z53jn7e/x4scaFl3DnfsHGDsX96wtso68B/mJ8Wkkr6W4ofaO45lSmpIKaAFFdUH4DJkRERTsSG0AN7X1+00Wo5nAYVl/ymnctq14SqqeQj+BltLFfxAvr+BmqZLlEW8Y6apQ19RCMBrFSeOBl+tWRPIdpFhsXoMNYDliDlDwPqBQpAI+JIoSqnMMiUaNAr+RFyGEr2jsn4ip8KEoCtoY9vb3SDEK2BMTJSVilos4Rolxi6kWixRqoRiTpcckpaqEU8i7gRQCQSuYOoMNR0BPaHWp+2ZTEfFiIFTTC+2q4lIbvPfkVGfkJFTXMOxUTXuW/MNS0FX5J9wLWXEOPrFerjg9OWF1uqRf9fjgSSGB3poftWRR+uBRBlbrARWk4GnTEGPg+RvXuHJ2l9OjQ3zwWMQf0OgGa6uHYCrEoOh9IueeGApusUYHGX+K96AHUlE0rmCVJg5LdGowRdaVZBm5cs7MZnPWyxP2z+xz8PA+u/MZF86dZ1itOT1esl4NWNuQUmQxn/PMtSv0qxMunb/Ge+8/YgjrCVUfxzbZzowu2PIejSIo6SI2xWOkNrvqg+GmWHo13eTb4T+y4hy3UNJ95VJqZ5EpWEwZNz9bUndVO4yatSmHhoyv41qQKnYrmSf8D8d157hw27AT5cY2ZnNdjo+JNr3lxwniuVhKIsY8FbMYMykNqCFS6IX1WUYSnMLarVWkVjWZOv3Z82hUSmFbaYVyKZBqyElOlaI5dguj/38QPn9d5YwrnRyofv9GzEy0mtqmMbykaJmXTc1CTLWiT+NF22CsZufsPuevXOL8hXM08462tpQxSCE6Pjrh9p27rI9OSVFkspPJZk320dIoSMEKkSEODH2LX88Y+oF+3ctaqcRq8T2ePXKRogo+eFrXcPTwiJgsPgaMSjx75Qonh48YfM9ssSD7FSqNCLjMo2BJueB9ou89dr1i58wC17UURNMxOgjFEFE6yPeuEB/MUgk4xVKKXJhnz5xjdXLAlStXOD0+4uhojTJFrOOc496993HW8uj+A5594ToHx0dce0Ys4B89OhIwlw1fQ2sFeYPgw4YViimT89a2gtIqI2QkreQkNjJOjN2EMeMaWToAtWXnL5+rJjdbGyPrzNRdjZ4EqqooJyUV4w08Hjbj1mE8aDadxIh9lCf+vPkYV9WbcXNTQHKWGLtcyXijC5RWBorCh0RMnlXv6YcBUJIvWQp2tPnTGmfq5sHYiRj4NI8PRVFAiaa+qIwuhaTEMccYRansL60dWkdKEjQ1pSTzcGKKT4tuDNrQE9A0BpGOjzIy5tQm1NW6lpIyzjnWtnDj5jU++cmPc6Zb0IhSYfzfjOzDfDESnr3Jq7du8d57d9C5YHxCUUgqo/OWtVsFfEIMhLnIiMcE61DZdUbrrSBcNQUppRBpWsft1jHEJVplzsxaLlzcox/WxOiZLzpWeGxNQk6xGoHoTFEZH3qZfY0jFWi0RRVDVtWuLSWKLWTjwA9opfEpC66hFCoHnJJxTqvCmTNnmc3mdLMFuf8DHj++x8HhKV23iwYe3r9PiYX37z0ixcDpo0dcu3yO1997j7meAaWCjTULIqtpm1C2VKqGcczYrNfUKJu226OB3MDGSRGzRuTpkmItG6LRk3OUzIu1nBF+hpWQFWcMOQ/E6InRk0nkHCunod7YjEQqI4X0CVXtuDEokAXM1YWJlZhLQmGxCDVZZSRzRCnICaMdSS5oVEFwgZwhRUnh1lByIifIqRD6SL9O1exXxtv1WsRc1lrpuBS0biMUfJrHh6MolFLHgk2WwGhxLrkONVikMFmWZyQRISvh0GdBr6TqalUxhK3VldZSEJQoIUfWXCkZpW11VNZcPLvDj3/iFfa6Dg2kHMWxHRHqKCUsQ5AX/hMvvEwKkccPDuiaToDHGHDKsM3TF5bbOAoFAVRrl6NKZdypTVFAyfeeYqLrWvqVpzGKmbWcO7Pg6sULUBJh8LI6VWJBP660io80nRPhT4qVOKQnubDVDmOFYiwcDQfaYHVDKgqLEb+KnEhkuUlSIsdE1oq2abh+4zq+X7KOkde+/i2G0yW2bZnt7XLv0UO6YWB33hHiwLlz57mwmLEexp19JAXhF2Slpw5n3MDA5ibcbuclBm5TNGEcH+TO1XXMMFbTmJpKPQGOW5oWY5i7FqzCNJauxg12jfAJlNpgGdYYcoFoJEMyjaQiraur/GarMW20pnPkSZ/K0bVLANEi7b2VfIdxXEmxEKsobDu2QBShCmPka3edbKxSzZs0RdVCL6I7VTucMZXqaR8fiqJQSsHXYE0RBaXqP6jqiFCmHXBKUXaz9UMSe6rHXaU/y3leZbOqoJG0ZVXqegcqI60WEgUYRTGK5569zrnZHjmsJIxEG1IRS62xxd2EssDMaK5fucTpySk5yNbBzSw2lT9SncVvMmNj5eCXcV6IT5BLRj2GNZaUCs459vf22J3P6E+WnNvvOLM3Iw0HDOseaxtK3U/nakibi4jCKKOhR01bClLkTNti2xnKiu2baRyhQBRaT7UfK/gUCIOH4lGMcmTZuHRdy6UbV7l65z6P7z3k9ddep9nZxS1m7O/t8uidd9h/7ibd3HDlxkV+6qd+jCHJjZNqAMwwDAD0657las0wCIM1pfFwKLWQ1ri2lDcah60bDuRWGE9rARVlTRyrX+Hm5tJYU8VZRgRMs1nL7u6cS+f3cK5uibTY7Uvid8JYRYpqIgapUXhQv3qZMgTGCILqMznhCjBZ0bFlO1eLXimFkja28eNTGyPenDpLmIxpFDEWurZBGyuOS6VMh+DoF6+E3UVME6r2VI8PRVHIpbAeBnI1TNmO/8611RT9fZ3n6l63ElSnjmEIdY+dxSEJpVD1ZByJLloLF10lI3p4Z1BWZv75fJdnrz5DKV6SgXKetgejd970GN/sFLhy7hLfn9/l+PAUoyqhyuhKpJELoICoIQWOxoxjAgplopweAFRCjqqoetE0bcPOzhyjC7vzhkVnSLGHKEi0HwasrhuXnDFmM5crU3fZ2siqNwo4lsiQEyUIct6ptq6vxHo8J4/SNTRWKWJfMxrqvlxrTT942vmCazee4dZ3vsuZs3sse8/yqOfm5Stcf+FlPv1jr3D2+iXuxci569dZdLOJBZhSZLVc4Vc9q9WKk5MVp6dLVssVfe/rISAR8d7LRwwJHzYU4BRlOxRDJGYZCb2PDEG2VT4EwhAYhjhtEErJaFt1MMZSKDSN5vKls+wtGqyZb3UWBm0CJkt3kW0hhsQYmpsFgUTlUvOE6wFStqTSaqN/KSVNHaSwa2XtrLewA0WFMeoKVuXNWDIOsDFEvE/EVMioicmotCh6xw5mTLX6kzw+HEUhZ/q684fKLEuZUcGWMlNxkBMv1LXPJvgzVeBxG0EuRaLHJoCnbARR0hZaTE7oYvA6c/XMPgvnyDlNuY/yJhtKRaHHFedYmVEai2E+X3BwcIguWlKJpw1HLSaKOn6Mn2dymR7TmkdEWiE3Z8wBpSXifWd/h6Yz+GXEaFgtlzQqyBhVIrm6U1dGDFpblIGusVBzG1IInJ4cA4pmNbBz7ixN27I+WfPo/Xuc9Gs6a1jsLNCtw3Uttu0gK2ZdI87Vdec/dnetaXnm+k2effF57j24z6z3EAsX9+e88pOvEI5P+Cd/93f59C//Mt3FPZSq/H2kc3JaEZxl1jl2d2YM/R7r1ZrVei1tbxl5AlFyQ1NhCHGa23MpohyMkZITIcLJsuf0NHB4suTo6JR1X+h9IAZB9KmdUIyD6D1KpnXQdm3Njhxt+eRmk/FBeAvKJ8lg2LpWP/j7UrZ5NkzXozFqwlHGSILp2tRKDg1j5ECp6+qCRqmtFWaBXJSs5IdAPwRhUVozhf3aqsUZ+xX9Z5GnkHNmtVrL961UBebqGqjugfPEEtsaO4v82GPKTlFP2nYXIIcwsRs1G91D4yw0hZzFyz/qzM7ursytGkIOgtgmpCPYbhLqN1EUqASRxO6ZPeI77wgYVwpF2yfe8MkdaLOIluJkxZlJ1bl6bDGLEkp0RDNEz9kL53jp5Rf5w0evAULHzUpAWessmiJ2acgpYq3GGk0768gh4wcPGY6PTlivexbNEavjE3xMvPv2e3z31i0eHR5y8/Ilnrlxjf2ze1x+5joXr16lmc/oc6SpydfaVjam1lAUiczlZ67x3As3ef+td3jmxhVe+dQnSY3i8PYxb33pa1y/epOP/Nv/Jqd9wpnNRWpVy9oOoNcoO+C6RLuYs/By+o/gf665oSUVKKFmX8qaOgTZSBUyMcLxqefoeEBZR0xwMhSSCvTFiy1fjmhdKFHeTbl6DN6LjwNb3d247lQEYLSHH7u8EScYMQU1XZyb4qAEh0KcvlzN95ioWrXTyGpjKWeNoVjp6MKWY5JsOdVE7pPNUiCEiN46EIw2NFbXVeoGCH3ax4eiKKRcWHk/UTEnZRlCK5bHZi6SG0jsKOTPo85BQQXTJqMK1LTaKYqpRSso+hQxWdFaQywZ1VoCGQ1YnISO6CxrznFZXV9bYUWWyR/QuRreoQXRV1lO7kpvQZWMU7ay4iohNxdKEtXdqOSTn6VeRFnX0BXPom149uYNvvLP/lDIVDFTrKjl0LKCTEpsxVujcU40Auv1gMEQvPA6vI94E1jmRzz89tt88833uPX+fVZxzf7+ghQgFcWFw2PS4Olazfn2CrpzUGQ80wV0FMNSbzI2KVrbsr/YQz93mZ2dXbr9i4T+gJ/+t36VS+ef4ft//7cZ/vIv0MzPUXLapCT5hCuK3DUYY8kx0phI6fLkK6iyyIVLEg5AKiICWg8D3kdsFAyqRM0weLqoGXyhaRvaeUd7EkimZ1AGrxwFj6ps2BIjMRWSdWKVp8qU8aEUoMUcp74j0vrX9d4YPydjWuUL5AqKKwhJgnJ0bemV0uhShVV1nM2lYEpBixUzKSZUKpg6MusilmaqbsuKKjgNqQQinj4PrH2QkWFaeY7bN7lvjNXopzde+nAUhRGZn/40Mt7GXr0+am2uQFVi9EHYpqsKCWRE/SUNuC7bK9VURILDUMCIjXiuPId+OVBCwrixGAlanHMUBmR9k2Tu05IQnDPaGlYnS3Ssb1jtGVXa5BRKXlGsBizyEM/A+ITlFoxdUEGnQlYKnwecLly+dpF25tBGhE0zJ9LtnIo4R1lHQbqq7BP4AVQQLn7OlJQZql38aV949dtvcvvuAy6dP8/Ozjl2Fh3Xrp3h2Zs32Nvb4/7Dh3zpD77Miy+/zMuf+DhmPsc0DVkpghJukx4ibTdjtpihreHMmXOcm+1gUs/zn3oF7xPnf+bHyG+9w/Gb32fv01dI3lNfGRKGYip/P49CN4UmV8o2YkufsxTolFExkWqITtaBpDxFabIKNf8xCcuvKGIxeCzYjqwHYkkY41DWkoYARpNzYEiJddwA2FrXcr4NZpZNsTB1gzHJo5NG243hjqgqJXw2aTk0ZH3pnmBZyoWiNs9fRjm9EaxCbZiNo/dE1rDY38Xt7mEWa06Xa1Is5By2uumxwy7Ipf5nrFOgAmqMzkhqnLm2ySBQ8Vuo2MBYEEZpqX4irWnUstdtxTTvyYezCm3NxAbTaA7vP+LxtVPO7e/jtJK+tVRO5LRHr89fyUrZNhyGJbfv3iX6gDZl+n5i2hBbJPBz01mMe215Tr3pQCpAJQVpBJwyJ2Hg3IUznLtwlpPViiF4Ct3UARWtKTlOku71uoeSsMYQioCvVBC3RMXydE3bOT7y8nVa13Jm/wyNm5PsnPuncO7GeS61M86vVqwPHvH47h3OXrjIfH8f07YCvBawqbBerpjvzNjZ36c/OmR//wy3vvUqw+qE51/5DM5Y9n/6xwmHa8K6F9OTJK126D0pD/gh4oOAijkExAFrVPdtUYNTrj6LCZ8yMUMumpgyfUwMuTAkxZAMPmmGpPHGEU2DshndCG9BK9BOOAD9MGA7g2raybDnBxGRxPB1xLpK5deY6QIdb/Yxv3S61ytGJgp59cR7P17V478rW193G6sYTYMyUJxhb2cPO59xtkDvA6EP9MOaUeKd8wawj0n9idyXPhRFoSBg0cb0tEiSU2V6bQA7AReV4o90FtvW1kAFbmrVpdQXq9TnHFssqfQlFmyjuX/vLq/fOcsL1nBmsaAVUp2kOBUhLQVSlWVroi48Wh7w7u3b3HvwEJszQ/IkJV3C+JgusrIl/JF1RB2FxvmvFpo8zqMeYxpCDLQWduZzds/scPvWIXXRSghJqMVFo7Nm2fe0zmG0ReVEGgaSMjKmlIJ2lhgDhCU7jcF2LVk53rh1m+/fOeAb766BU/7iL36Gz7zyHOtH73Pz6iXC2rM6OaVpZzRNK1bmUb5/ZyBEaBtHmS1w8x2+/qUv88X/8x/ya7+25PxPvMLec8/z8N33efett4Q2bsWmfeg9IQyEUCZjVQF6Yda2UPkJZfQ6SJk+RkIUlyTvg/waI8MQyKmwXEWO1pmTdWI5FIYgY4c1lmbhaJsqOoqFkjy2McwXLTs7cyE5qfG9yFNtKGMMnRKdiqR4KUjS0htq8H2hSvtrBoQZs0O2qv4f96j/bNu7ASoZScuh1M7n7J7dw84WnGkcGQgx1S44bT5ykp8xPLm6/Rc9PhxFoYgeXk8Mtjzd0NNOV21at1LiE1V0IjyVzf56JH4I4UlvVeEClS6aUrXCShETHf3pije/8Qbr4xWXL11if3+PxWwmarRK8/UxsV6tOF0uOT4+5uGDRzw+OMAvV8yVpaQsgSh1T5xLriw4JaSYacdQ4+6VmsgwkxVb/RmEfBLwfqBXhdZ1XLp4kXe+8x7LlcecX2B0RtuGk+MVDx+vODo6wmpodeHKxXOc2Z1PIhoFlBAY/MDJaoXWDf2q8Obb3+Hi1RvcfOlFbp28w/p4zec/+3lefv4ijf1zLJdH7F66Qtu1FOtAW6w25CrOKkNi3joWXUfOios3bvDg4JhyuOLWV38fc2mP5z5+lbet4Tuvf5+269BOyFMxZNY+EHwixEwOEaXBWUvrBqizeC6iG985pwAAIABJREFUhk25sPaefogs+4HVamA1hMoQFcwj+sR6FTg8WXN8uiLFhDOaxlhaZ+haR86Z4BNWW0KwdIuGM7OO0QCmqqVlRqrjbanOTKKxEMAhpfE9FQxrBAtVHVmnzsDoSRYtjw3VeRLmbY0qTwrGNiBmKaXqczqaeUc3n+FcQ4ijwrhS/2MlAtaxMf1Z4ylQEPKRqZk7StYpSj8JJG4+nnwBN1FcUtG3P6eKZUsSJfv/ChTFmGnqBaJTpjUWfbLm7pu3uP32u6iugcZhGieUX60oIaFCgpDxwyC001ywRbL9SpZ1ZGsFZIw+UEqhbVqcayg5E0Ig+UCfMtroaS4VlWg1bdVAKfh1pGsbTlYnzNoZL7/wIv/0n3yNw6Nj1M2LKJU5PDjhrbfe5bW3HnB6csTOvOX82R1WPnFub87evGE+m8t2ImVWKXPqM4ePTjhdDpRsuXH9Gi+8/ALnL+yR/Zqbl3e4euUqexfO0ZdI11UQmELacrRO2cv7FyLz2YI+w/61q/z0z36B3/6N/4078TEXbt1ife0V0jJy99GKpssoZ7GmIcTMydqzWq1ZLQdC8Git6bqWzllQwjYVm3ZhFIaYWQ+e1bLnZNWzWg/i7K0qZS2JgG7drwk+YrSiaSyNsTgrRaFQyA04o/Cxxzjo3LgxquEzWHKOW2W8Xq51Vi950+yPlnBigzYK6NSEa5WsKUVvxs9pCaWmjdvmWueJsXhUVo4kJ600zloaJ5mrrTVYClFrslbkrCl2JMgVIhnVPP2t/i9dFJRSH0WyHcbHC8B/B5wB/hPgQf38Xy+l/IM/7rkK4HOaAlR1VZjpUt2QK6gl2x7h9Zdc0FnmzaQMueISKfjpBRRn8VTbQdlylFJQqdBahy6avC5EW7sRRgFKIK0V6aAXLEBpMhljNa0T+zCjwFBIRUAwnxJDKVjEJ7GxmkihUYrGWnYWuzijyWhOl6ec5BMeHT9CK00UsoVU9BjJRTImSpDiNqwHlFIcDits1/LRj3+Md7//Fp/6xEv0feLbb7zLw4dHnFnMeP7yDq0rdPMdjNI8uvuIR0Vx9tI5nrl8lqtn99k5f57bD45IMbG3t8/J6pS777+LGVZc35lz4+WX0OGIfvUA2zvcbIHVDtt1WzkHwtF3RTFk6A3sXrzE/EKhP1nzmc/9HL/3D/8f7DDjytXnGPKKu/cf8813Tuk6Xz0ZDSlHhiFxeHjCyemKfvAoJZsDSyNrXzkiJl/OlOooWU/EnMSJmnoj5RQJg5C75lrXrhOcTlijMEThHzSGmOQ9a8coQaVQWd7romqMQBECstaqch1EsDaSq5QC6ypTlooHISe6c0aUnGYkpEmHqItsPpS1MtbpTTDM6O0wdsC23uAlZ+FVBNmYtMaKEzcKrS2mmrlPQPtoH0Di+Y9df+p7+1+6KJRS3gB+DEApZYD3gb8H/EfA/1hK+e+f+slUVYDVmWwLekHVtXGpirOSC8rpiZAjb0MFAEsm5kwMcZqrjLbT1xhzBHPO9NpXbwRR0rnx9JucdxShJhUVBL111pJdIbVOdvQKIcwk2X+XnNiZz8kx03sJM5kv5lw4e571akWInpwVVll2Fns8fnzM44Nj+dlrclGK8v+03cR+ZWVQQMwZHzI3X/o4bxw95Pv3D3ElEXzPjeuXObc3ozEa08wZiuG9926zXAWOV4fcPT2ibQw/+9mf5qOf/kmuvPBl/s7/9Lc5t7/g/LkdTk5PeXxwjFKwWvVcaVpm3UzQjhwBN3kSOmNIQyL6WDkcehKY6VIYhsAqB372F3+aF196hfWsgbDm1e/d4bvv3mHe2XrSNTijicPAyfGK9boXglIWV22FnTQq6I3qVTMS0ORmtcrIQTLiSll0MlDla2qkuYPKUFLFkLWQvJrG0LWy20eN5q9SBJyzNKllXTsYMwqjxrGg0g9LSlMXqhVbeZl6AptHy79cmbIKhcmZrPW0adBab40ppupl4obwVMSZbFivsKtW/r1rZYNWv4fxMa4oLYrr+xef+nb8YY0PvwC8VUp5509CkhgfCnA/QNpp0EyGFWVstYCiawu3MbW02hByJIbIuvcMNQlI4cglVRKKhRIJMZCTVFNnpRWzVmSyXWNr3LdiyJFQZdxN09BYQ+ssbWNFlmo0qkDICYoi+ERnFesKmNnW0SVF8BE/RBGpGBiGgI/Qe8PhaaotZiHFKgArgBHFZS6yJw9JaNw+RHTMLK5+hLfvPeJTLz3Di8/fxPvIfG4Bx1de/R73TjN37t/n4oVdLuzMwFoe3jtgNt+hOMtnf/EL3H3/Xf7Z7/y/9ENAqZZub0HbOrqmpTVONgUcs3PWkGIN2zEOTansQgHeRrzHIBySEBPdfM4XfunnKedf5MHt97HG8M3v3mN16km+YPBYPeCspgwrghfVqwJc0WJhVp9vDIWpggx0lth4YRWPtG3xKFQ5U3JE5YRTub6GVYJdjKgXlQiqSsWqrNa0VuNqETATJsDk3DSi/9tbCQGPYz2QEiODrlTr91GP8kS8a6W/o8a1Yak6H7Y2GZsiMhaFcQsDMmr49RrdNKRSULqXVCuowCxTAG/OmcXejL22e+r78YdVFP4d4H/f+vN/oZT6q8CXgf+q/DGRcTAtGvlgOTGqVK59fZF0VR4qVQ1VxNDEKjHeiGEgh8IwJFYrj0/i25hSzQM0EjbrQyB7pk6hrfZnisys1RhlKSh8igwpEclY52ibhnnX0DWGzkqKNVmMLzKa6CNFebrWEYNHp0TTzehT5nTdo7EYa1muMx7Hkbe8f+jFEzJDComUhaySAVuE155RhCh2czEmTMmQWs7ZfbJ2nNnf5dHBEcde8fVXv8ni/LP84atfAQpnLl7huStn6QdPZzUPb9/l/HPP0l2e82/86l/h81/4HF/8nX/M6998k/XpwOmJ53tvfZcYVtx84Sa7585hSah0FjMXRemqFPLgxbHZynaGOmZpo4gp0jjDowdLsjrihRde5Gtf+Sa33nnAXFtMQm7mNBCBkj1GqUpTjtOVIAeCBW2E9JWlcyCJ+U3ReqwTUArWZJRVkBUKg8IwmrGO1v+j+avcY9KGWqNxjaVp1GQcq0a9C0DVz3yQ1Tp5K4yAoBKHpZQ3kYAy+lbSU12nKy2kJqEsj3T5rSef1pYbDwljDKPvAjHg1z1oIaWFWlgculr+yf9vrGMdAvMzOyT3r9BkRSnVAH8Z+PX6qb8F/I36uv0N4H8A/toP+H9TGMyZM/tSXYHtSpyTqhfbaMYhjEKVPOTMaM1pikKFAD5CTKQ+sVrJqioMkZAzMRci4FP1dvSiybc1gEQcawragKtv4JAy6xQJJdG5llnbsJh1dK1l5ixNBaaCl325956DdeD82X3wkZjXhOxIpWW9jPjkMcoSUJwMA99+74B3Hw4oGSspUeZVdPUYRNfkZaF4xywBpRZNTA0m9jw8OOG5C3PmPvLVV99AAz/+yY+QjeHtt27x8tVzmARn9vbJw4qjh4+Ix0u4qrE7e1xY7PDv/Wc/wvde/zav/cGXePj+eyxPDlkdHbJ8OMeRMGGAkCl+QFUJtiLjXEMKmWwqxtOI/NpUjoY7dx0fIv3qhN979Q2OlisW3Qw1WbDLjOzqzJ1MQVu5icb0ZttYrHEoI/4HktilK5ovN9vIATK6cgOqaIuciTkJWFlX25o6hlBASyK4VbCzaOnaBFpUopvONH/gBq3ZEAUBxLUQ3QqanIVpnMuWW1g0OCPFoCDpz7b6Q1ADacYiMI6Lo4Cv3ieTF8SIM+ScCcMgRKtlLweHkvvA1OwTrRXJOkLJrE7WnK6Hp76nfxidwl8CvlpKuVe/8XvjXyilfgP4zR/0n8pWGMz169dKqfbcmxAMpsSb0Yyz/j+K95V4Ko4zEQUxseoHfCgM64HToyXLtcf7SFEQi2bIhT5E+pBY+aqWrDPhpMkvMqMqoE+JPiZ8yezYhsV8zv7OnN1Zy6xztE4oszHJDRsGz73HRxwtPQvboXXh4Oge9+6fcu3yZULJ5BJZDpHvvHuXb3znHZLtKNmLmUYuYjRr6okzqiqnaLLqXh0TYMi+52AO185YlIb9tmO3VRzfe4sfuTbnsrmEYyAGSF4RvES46SJbjz5ElLEsh55Lz17jM+YnuPu9Cxw9ekBYntBZg02JloxJER0jKFXFXoWgCipLS51UoSSD0oZMZra3i2aHc3Hg7u33+Udf/jrtbsfMSmETKMLQNS0NHUWLPZrSolxUiKTZuUYMUeq2omkczZi9YcV2bcyQENlCIadISYmUg3hTKsPoc1gqIU38EAo5Cwg5bwyN9VMS+bjWHpWJ4+k7qU8ndyhp0VMluIHgUeJAvtkeKL3RSkzPXz1JTcUyJu7NyFXYypwYQcexOOWYSGkg5kF8JEQaK6vw+vuMyMOP7h/w+NHRU9/QP4yi8O+yNTqoGgJT//grwDf+RU9QCsQ47oMFvJP2UrwV0NLplSiIdyiZ3gfQFq2shJaoQr+OhAzLpef48JiTVSRRajyapiQIfWS17umTGFmEXLNRqIVBieOPrpp06UcMqzZOYI4fPJ1rxC2pCLuuNjHkmHh475C2bbBWcXy6wrZzzp27x5X9OdFY3n7/HrcfPEIri1HiYKALst5DLN6p0tlSzTWKEuYigE6g6VFkDrxiiNDkJXtnZyzmFxj6gZOju5xdzEmpEFpNCJ4zewseHhzjlytS8jgMau3JJnGSejrboFUh+Z55NxMKuG4IpoUixiopZ8rgMVaxDr3cqNoJxbduB1CKfnlKObrDKjq++HtvEJTl2iVHy3hqj223xtjNPt9UGjCIk5IZU6MqJb1pGzrX1GKwobdbY0gji7WqJ8dczlSxp5y2PCygAqcWhcLpRGMsxebJrLZkKfboCmgaTdCBgjguGSU6DIPoQQwgS4YyOR61RrqLXDIhBZpKQkqVHm+KgjFno7Y8CXnejLyem0hDPYmpYimkoqQTygVXR82SC0knWXWnjLGJFHtee+2Np76hfxhhML8E/Kdbn/6bSqkfQ176Wx/4ux/4SCnz+OCk8gpqVcyJkuIkZUUBSf6eCKt1D1qCNJL3NM7gi2JIhQcHpzw4WJIRMNCoLCuslLAlMlfglJCMPIVAkc4jZXljS6lWXqoi3pmYNGnds/KB3Dp6I55+ktJTORIgIJiSE0v+v8Efr3jv/Tu8ZjTGOTKGxjS0RtZSVK9BUy9WI2gYwuSknhyFjYwjoXXBKU0KieNTz/nFHmfPKLp2Tpy1DLMZ1lj6fiD5wJkzu7ImDYGjh0csjgpqN2NUZjYY/DKxPDymc5rWOvrTExp3hrbrsG2DbZwUpyLGNylFwT5MwdjqPF0SZJnbB5+5/+gxjx+f8sZ7b/PCR57DKzsh8ahRESo/2TiDa7UJLnHKVuv2MRawBvFURyVdr4vJ1LREStpsqXJVV47FYPx1c1oDVd9glYCfqgRyDnKdle0Ytidn/JHybrT4MUiU4Jhe7ipFe+TLiDWbqhuU0bXJWLvJs9wy2ZnYjGWTkFbvt4qRyNgTc5YsDTV22AqTE0rJHKN1xjpLKonvffd7T31f/2lzH5bA+Q987j/4kz5PiIn37hww2lJLUYiQYRg8Iea6r642Vl4Q5ZPlAaVk5q3EkikroasPDk9Z95FmNpdIcQq6ZFQR+mzbKJbrQhiprGRMJTPYcZWVkjj35Fx3z7YKogqoQq5RZDIab35FlRoOIrvu6CNWW/a6jljEO8EYiy4JpyLdTNKktFFikFFGQVf98zhvbqOwSU4jqxqcHjhcrdiZ77C7O8cYh+/HdlNM62atYW9nNtlzLU9PIfak+TmWwxFzHenOL7h9P3PrG99kZh0pDBwdHsCsQw0tzXxXQDnnwEVyzFiNvBY5UlK9UaImFgH6bjz7PPOLPXu3H7J/5SaxCHgMG6ae3Hujk7FsG8ab1ig73YDAVr7Dxg9RsWnlQwzT8+UsRKecJKp+mzE6EtxS3SwBWA05KsIyyGs+vdib70upNHlgVLJGtW5TdZNRUU9FxURGQHK8OcZrZWuEkCd/AmQfNw8gMJqpn1N1jBY3e1ldhnogKSXKYJNyPWSkwzQpSYccnl4m+aFgNIaYufNoXVczUtFTkgrvBy+pUUXV+G0FSTIfTo6PURR2F7KfzwmGmPAxYI1jrqCxCmcUVoGqTsK5KErSrFWQ9V9WYvGuDabmCKos7amtwNd8dAm2sg4dA2h0iaiKOJcspBVltPgIZoUtIn2OXjFrFmgyjc5YC21n2F04FlbTtk0F2TJWVfBKb5Dk8SEXvbTFVhd06mnymqxg1jQopYjIOg4inSksFnOcA78OJODe/TtcfPNVdptP0SrDzi54BS+/9FEefONrvP3mm5zb3WOhDcO6RztHUYcErWlnM2HsKUfOAp6GpadLiW6hUMYKJ8BYtNMs9ht+5OMfI7g5qiia6pMJcsPUfmFC6uVnrKzUrWQvStUPqGl03zwJ46Yi1XDWLVHQZNazyYIcZ/ecRH4v30cm9g0H/Zpq4FAtjra+iNp0j9vU5PpXW++RkNCY/m78puXPdjRSUUjGRgUdYcs2QFXNRNmIwca1ZMnCR8gjL6fqbBQKX3EPUVPKq6tjmUaTp3l8KIpCTIVHJ2Eyb01Jch9KDISQSUURCvSxEIrYb+UYMcpgcubo5FAclIxBNxZnFK5TqNTjTIvTchII7VROiHkHI9MxVo8DVURERUX8lSq01tA4DTpLnoJx5CxFKcRCKo6SQ+Wx1e87JYJRlCHJNaUNyrQMacAUhbMt8/mMnYVj3mrO73QsFh1t5yr/QQF15bZ1sW0YfWN2ApToaVTCZo+JK2lLVRXipIJqLI5MDh6lBBC79/gxu6+9znXbcnqU+Z0/+ArP3rjAX/rsZ/iJz/4c9+484OHjh5wuV2StmS/mIhnPkorkGosuiHMwyPsWAykENJqiLVFZCBlrGq5cuMz9kxVt200XP9QT0Yr/IKpMLXOZXk3qFqCamtb2WantRClVsxrlpLaGrZu/qmIrAW2bFg8Vp6oAXy6JoSjatsFP2xHYzhvd1iWMY0SZRHx6S/koGNAH14rjB3qTX6q0EmB1S0TF9L3Kc47hy+PXkG5VDHiyEmu/kguqpqKNkYhUXAWtKCo99f34oSgKISbuP1rW7kCi4UrOkGuScLHgHMU2KNfROJFDlxAxKdIAqV+z2N2jm7e0TrFwip3WsdhthCNeY8VGGzFrPI21zBrhpKva7inklJNrN9EYTdvVIFZkBRWLZugDp+uepRcUPgApC+pMkaqdkhi55lJdo0tm5hp0TixSotFzdpoZrdXMm5adeTch60opQZHL5oIeTUbEl6/uI8LAfN4QVyfk4xUml2rkkcToRSsM4tmnnaMfPAfH8Hqf2PuR+3z91bf5m3/rf+WFvR3iX32Dn/zlX+GnPv8Fbn/3O9z9/rscHRzRzuZcXuzJ146pAn0txQ9YLKUyQUdQTCmIOeCqu/KO63iUl8ScUMVMhDTrhAwls3ciFxG1idQ8CxGpEn2yyBFl9TmxCnVdARZxLyo1lau6XcqJvzFRrR1/7TyYKMFaK3KCqA2Na4jes30L/SBC3gc/M/2TyiWokNCEoYjdevWQyEk2XFrXf7jxAqG+11NxiGkDwtbAY2UdjTKYFpq08TFVWcvmpSCMyiyO4dqUP5Lq/sc9PhRFIcbEg8NTVMmU6BmN7aTyGxqn6KymWzjarsMpJShvCag8QGpQzNhbzGgbKQKN0SJ+6eRNt3akLydCgNCJGCfGRCqVJq0UOdWrEIVWmaYxOKexylKsSK1DUKzbhpUCFQPBak5KIqY1uRg5YXwmmRlt0uRi8EbjskJnS1SOqJ1Imo3DNg7TWFxnmM1bmq4jlU21nxDo6jBEqvkXWqFajWkMptnn+PQxHB/i4oCPnqZthMCTCs4pBt9z7+4Rfsjg15yknp//ws/xX//azzOcrDGzC4TVEtN1XPnRH+Xiyy/x+P33sUA0iqFfs2Mb7MKStKLZ2YfViRjFKE2NnQCVaLKhHwrtTNFaRNqsGnTsq9WcobOKFKBpLKiIc5ph0JtucBjbdjkktBF2o03j6Z0xVvIVa2UhTOy/TUdQ1EaROOIX47iRk6IUQ46yxmRikY404TxZ8pcCIURKXWHLunzjnTBZ+lfvCgmfzYIZacPoCqZTlu6gyrmdli4oplRZnKMfqaxCrTNUqEDGDStOTnPnaBkPC4ioaVQajWBLki6qa2ZPfT9+KIqCVjBvmNq8VCpAZoQPsDNv2V3Mme/MaWctrpJIDAVdApIBnJg1srs2RsnNbG1NCqo+e4qaSekJxUxZEgUhC41J16UgXHStpMA4jc4Kr8AH2S7EZGjaRJ4ZBhI+R/HVI9QwikRxDRFFsgZlDQ5oOoedOXTbUGxHUJagDLgWbVu0Fg+/mW1lj14ELIshENM4O4/5hRZtG4wzaByz+S4Hjx6SY8BUA5m2aTGNAgQHsVpz6/a7aN2x+vbb3L//kL/45/88L3/0ZdpZy+BXZJUZ+hUhDpy9epYUPd3+Lkpr1nENK828m9MpxUkI9bUCpcUVW5VC1prlesnezoKQC8PQc+9gIEcRd+3szNB6yWLRsRM72tYRY0EVjV97YoSj9cm0ijOqoGo0XFvRfWmltfhDABQ2lGA15nQwHeMj4BdjBRuL2J+XavU2VMfoMXdk5AaUKn+fRplxG1I3DOOBMq5jR7NXkIIkLEoLWk3pVGyPFhNbsSIso5Mz42q1kqm0qputsQUR30dlLCDmhalSrCllsmQrqIlK/TSPD0VRaKzhxvmF2J6FOP0AnbXMO8fOrGMx65jPHU1naaxDW8EJDB26rhyNFt9A44S26hqHVeObIO1UqK7AIxibx3yI6s5Ebe9yTMJZcBIVr1KhT5F+ncmpiO22aoiuIUUvayxl0HhyEBk4TUfU0kuatqFrNK3TuMZQnKHHorOmjYYmKNqoMbGgg8zNJYrDdfBZzESGQIyJwXsJeGlb2q5BxRoVNtsjYIk+M1ca62SNV5KsxebzBft7npdeepFb7z/kZLkkhzVvffdNbr50g8PTJTO7L1yAztLmwMnhY06PV1ywc85ePM86e4Y8YHNDaxxOG0kEjwlqq1pSJmrZ4/v+lJ3dfVQpvPX2OwxBTt/z588yX3TspYA9q1mf+ul0W532LFeB248eUHKmsTUOTovh7n7tCLVR9YYSzUSsALXWT874okLfOCKD4AgxeWKslvw54ddr+r6vruBIh1aviXG0kVtMTdqCUrkE0zhR5GN0ZpLs27FbeDLkFuoIyARlbh4VD8m1QAETqY+KGShjBdCd+A0JVzYFZvx8TBufjqd5fCiKgnOaZy7MSUkKwjjrmVbRuYZZ2zDvWubzlqZraJzDGHG+sVqJQk4VVLIoKy2WdVZu6LpPlvkq48YdcKrGmwoolSBUqGYVYysJKAHucoxkXwhB0P8hFPqYiFFRkkIhQiGSgTgGejYUY9BWMWtb2qZgdCFRWMVIXPcsqwBqXdbEUvDJsYgZawdMEYnsuh84OV2xWntCSPTDQCmJ/d0ddndndF1bv8eEnu+SfI9HSC3D4IXwUmXFO7tzusUMMxfG5V5rODx4wDvvvMWl52+yUitOTg5YzDoWs5ajhwPf+sarmNc6PvqJl7ny3FV2z++TreI0BFx9XaECkUVi8Ia8hgK+MczZ46PP3eD/+sdf4tvvnmKtZX//iP1zuzz3whV2uwXz2T6pDBwc3YMER0cr7ty6w3q9QhuNcw1d27FYzEkX5sxmMzmRnZluslR5CGM03LSxsIpUsmyBQiRncSjyfpCQ4lQoVW7t12v5WVTt9kYi09bWYvx7wT4+sGEoG8u/MTsi1d87u+XwvTXibGMIuj5Pqj4dSmuJkRv/TwU8jdZoa8XFedxsTMCoHES6rkht9ep42seHoygYxeWznVTyWjON1qhG0daiMOs62tmMputwutSiIB3AqFURmq38eXS/cVaArDFZaINAM6HdSo84AthYIEdxii5Uvf7YSUgyz+Aj61BYh0AIkLJmzKhgpCIjeRHJaVzTsNfOmJsBawqmRoWvUmbVR47XmTNrTymZmBqWDpzWWJPxPnFyuuLx0SlHJyu8D/RDxFq47BM+BRbzFlOTr2btDsUdMcQlo5FnZxSNcwx9wDjLerli0TmaRnN2f4/V4RFNdlzZvcCgIiW3PH54wKAH7h95fuuLXyKfeF56/dv8zM/+OJ/+mU8zO38ZrMIHoZHbxmG0IQTh8xe/ZggFzp5ltV7y/JWLfOTSPv/H//xbzBZ7Ep3eOhYLx/6F89y8+SKf/vRHuXFzTggDZ7oZ513hwcmaMIBnTTAr0tAzb2WEslaTksPaxJheXUqpcXcbQ5LxhM2pEIKEyIYQyF7UtIP3pBAowVPyILRqY+Qg2Roltk9gWVdbyXkcAcJc15v13xWF0L/V1sZi6wQfC81UKBCItCgFZRwfRurzRlFZlKLoBCpuwNiSoa4xldJgVDV6GbkTfxQs/f97fCiKgtGas3szSSKqxu1KK7pWuoLGNbimxTUNxjlaXabg2DHyG6CYMukZxlnP6Lry0gVMbf2Voug8bshHvonMr6WAVdi65kEZGWtyIYTE2gd671n3spZEObQRK/mSi6j0jBXg2ymwBu0U1ilabSpnIuET+KJJBYaQaYNiHTO9T+hcSFpRShRnoj5y0gdO+4D3kpDUFU3IEKunozGFUKRzGjIUH0ml0LYdMWfZ1BjDelhJ/FmfKdnQNgv2r57jn//uV/nN3/wiDx6csFyusN2MZn+fO4+PeffOmpvXZpwGzze//g125x0/8hMtSVtKEuBNJVODWSQrc3nyGLo9Se8qmbg+5V//pc/xv/ztf8Cbt25h2WeF5xDP+2/d5Vu//x1+/4tf5Nd//a/xsRdv8ujuAed3HSbPiEXjE6xDpjEZXYTT76yVuR6x90/1/dTIKamVEvl8GP4uAAAgAElEQVQy1YC3EoDGLUYKksW5Wi4JQ48qiVm3OcnrrQ48uYFQiglXMNZQqvUZavQDGWnVaQKux6Jiarcw+op+kD0wcjds1ZCkkiYikhi3FmIMkn+hxeXrjxQsrdGujs/V4fvPXKdgjGJvb462mlSqr5wGaxuapqVpHFpLS6i1JpvaJuktw9O6v9dFqiyUGknuxPY7xylBanxxtdJVuipveKyEFVUFNGjQSvgSvmSGmFmHRJ8LJUd2tKKxirMIoNVnx8mgWI3dw0yUlGcbx5mZYbcRObRFFKAxK7IxpBRobWZmFa0zWJ1xuuCTWNIZVbBkWg3GggNmXd2wGFvNQRVtLHirSDu7pNMVOS5ZB8/czEgx07VW1qYFrFM8uHvEa199hyFmbt874OHxCc9fucHP/9zP8clPvIxyAecUX331K9x7fBcVPMfHS772tddY7O9z9cY16cyKgaQkGSt7er/k/uMTnrt5Xhh12rDqe27euMB/+1/+a/znf/03yMXSpkKgQVFwjeXg/h3+79/6Mp/+bz7Jsr1L23ac35Hbpk+JAbGCazuNtQXrBD+SlbLGlGrJpkGrMjkY5S3bdN1KhL0iYbJY8UVvKAMiXJC3HSuQMaCJWYxflJJrVSlbPUFB02BVosS6ejGbzkQVw//H3ptGW5ZcdX6/HRHn3HvfezlVVdZcUqk0QoGYQSAaaIY2tMDgRRu7Vxt3AwY3bS8vf2kbbBZu88GL1WD36mUaaDO0GFoWtEUDapBADJonkNAsVZVKpVJVZc2Z+TLfu8M5EbH9YUecc97LLOllqYRSLaLWq3zv3nPvPfeciB17+O//32VvhK7kQu+vpcyseMVwBhMcxLDRCfaeCk3TjIlIceScCo19pk+ZJGp5q5xKW7jDzwJKS84NXtznXqJRxPQS8dZU4yn149BY/qDoGVIsfdXxq2MwCjkX+rSKqxe63m5tnhxTCVvFy6HzGAEqQza52m5XpeITThJbM6GdCU3IzGct3nm6nDm3B+cvLom5wW8L87lwonUcX8Bi4fFF8cBAWqbr4NiiCY6T2zN2Fg2ehMey3pqURpRFcMiiNfCSKrM2sLPVMpsZg5H3pipFH2nncy5KQbitNrTeiGNiSuyvI0274IEHzvGxux9gvezYWsw5ffwUX/vlX81Lv/QOto9vEfw+0gRuueNZ3PHCZ/HwQ/fx9je+mdX+HrfeciOKFVnIjtliZniBmPHScM/d9xFz4uSpE9aQ1Fkj0O75i3zX93w3b3jXh/i1V/wJ8/Y0ue/xkum7Hu+P8cY3vInbn3Ud3/F3vo6d9nFWfSaElpCDUdY1tfJQyE9w1B56Q5mW7lkq36eFfgWEYjBl8cxzS6oAo2yGt48R0X6YU5RF6iqGZZILqAlDLyb8om6cYwakso1Jh01n7IK0zcoPYYhSmaIqKpbhM0IYZeTHqkpvvR2JwhxdDE7qSxNUoA0Lu2axL/iIS1KZTzmuEqMAUnT2DCBEScw0pVfAl+Ns15hmb6c95gNSTUZXMReehlzYnitpi0ty4FgoIi4CXkYu/6q240PAB2vnnTfQtJ6mCWzNlK1ZAznT9coxJ+yosuwT8+3M9pZwfOFZNA7fGurOdE/E6vrO00hL8LCzFdiaWS+EYNTpbeiRHHE6Yzs2iJjGZAiBrUXLrLXr472HAH3q8e2C2fHjrJ/Yo02ms9i2LZuu59yFffaX5/jAex5kq93m2utu4MZrj7O1mBHymnf/1Tu55vRJrr/xFDfcdgOPPXo/oW05vmj48hffyWq15PQtN3Hs9LXMt7fx0tLHFTFH+tTz4Cce5d6PfZyXvOQrBtSpawI5JZzz9Gmfn/ynP8hH7/oEb3nXhwmcspxPjqh4Ugr88q+8ktRnvvmrbiNgXl6KmXnTsE5WZRKwDH22SoG4PCSTh4WoIytUBStJMQxhMcPNGuZNYBm8dX0u9+n7cUedeqEVel3bp+uCThpLOOGMBs5VlWk5kIuYJip90bMYEI5lVOM1LF9naEUpeYFiZgqNgFV7Bho2lNytjYLQe9pguTpxDhV3oOHqU42rwig471lsL8hCUTpuBqHNGiYMyDBf6bHGxIHVZjPZdTYpwJ4LvlxMq06kPpGn16a8hV1z6wB0uFGUVjH+PBG2NJPTNsF74slIE4TFvKGZFX5HTaxXHRf3N5w6FcjRMZu37OzssL29bTj2Iu1FYXCuQJrgrC3XCERCAeZYviDFnuObjq7rho66itgLbYsL3pKgKOSOE/4YOMfpm25k9/6TPHH33fR0nHQNMXas9y/gBV7yktu5cH5NjpEL8REu7im7F1cQtrhmdYGvOr3glPY0ccU1J4/jd04QVh2ZSFgsaObbxOzp4kW6Tc9yf8073/EO9vdWvOQrv5oT8xndZs28aUwmLnliWlnFqNnh91/1f3LmwV1e/PU/DDQgESfW2di2J/jVX/sdXvPa0/zwD3wvz7rlFN3+OWal9BecGBuUWk0/5YT2Sr/cY7laASMRqnMeP5szn83Y2pozn89oZ4YbUFXaRghBIPdo3oC0aG/6jZozsU+FSLcZ8BDDIq9waEucUCsAIAUvY8urTz2uH3MV1SAMCU01b8OSjDUpUXIZZUMcjYfiGPshDL1Yvmu7IJT3zuLpcuEW9daId9RxdRgF59je3iJipCm+MaGQ0DZDLViL9XXOIaEkeSrJanG7NquNlRO14OCDkX4ItQTVmXpxIbdwfvQ8pNTIJWVTbwZz1WMhtijA4tBYHNo0wnwWaFt7TnI2RqDGs5UWaBa25w3b2zvMFluYgIxJvkkYiTwqAWnwHl80DihAqoiVxVLqSUVZOeUMyWTopJSjuhhJOeFzxmuwOHU24/bnvoD14+fY232Svf0VO1tzbrnxWlSV9XrN4vRx+pTZ3btAQjgx2ybEDddfs8Ozbr2Ja6+9lnY2J2wdZ+vaa3neyWNcOPskiCVZl3v77O8/Tu4d73vPh3jowTN81Vd+GTltgBmx61mvVviZXcfFbMvKt1uwt7fhWBtRHMEblXrORsXWdUucm/Hwo0v+5S/8Bn/vu7+BL/ni28ndvs2HVFuLjYPRISSNeMllcRvLds0bgYfGWq6DdwP3QWhbkjNCl67boHnbBGvLzluHbSs69J7EaLyJMSZSVCsZDn3tgKO0bluCL0VH9LG0V4+Jyxquqqr1SjBJaDqMPCrFSyoHDttgfOORxpHFvOy2hNkhBJpZiwRLUG61LU3bHnk9XjVGYTZb0HpvHXnBdut5a/HjNLsqIngJAzJsWNAxsWkbYoqUgm0BmBSXO0a6ris3KRVLPCYkwdBw1U10iLmDKRkKMlgnZQhWgmuCGH13sI5GSYq6luw2zNQUo49vzdhaLGgX26Y1URZ9xQ1U61/l0S7nalaVY61y7CmhalltY+YRfB/pYk9OltJqg2PRNDRhwbO+/Mt435/9Mau+x22gwcIW5xu6tCG0nptuuNbyF1HZv2jIuN0ndrnhxhs5fvo6shPSasU6RTYq5Nhz7slHuHhxl8d3L/DQ/Y/w8Xs/zp1f8ELms0DwxhqV1XQvQmiRIGTpyBJwK2XrWODnfuPPEeeKcIld9TpUN3iv7O5u+J0/fBvPv/PFbC+EvjuHuJ2hjboJDknG1Nz5xGLe0G0imo070gdvyVqjdbbw0Hvm8wWLxYKUMvN5T/COi03D/mpt+h2pyA04M7QpFlYmAehNuzEqLpsSk4LxTFbPATPc9p8Y/4Eq84m3UO9xExq8miEDBvxDyolUcmzVMCQ1ihfXtEivgKFlXZG7E+cJs9bCcUxASIPB6Y86jmQURORXge8EHlPVLyqPXYPpPtyOkal8n6qeEzN1/xL4u8AS+Eeq+u5P9v7OORZbC6vnNi0SAtKMRmHgrnOV4MLTNlaRCGEErjSbMFJolTgvhPYSoxBjLP0VliUejYLFk9aMw6DDUDvlyI6mMcsdQoWsWlqr0mC5prVJN2s5vr0wiGvbIuLNCyrxvxuSZTJQcY8uoR4oIVVsfS46Ayn1heU303URv+5wvSdGEz4JAo0PzBdzdm67BX3JS3j3O97BLMFyb5fF9jZN64j7BhZrZsasJDPPsZ3T9N2aveUe5558kutuuA6vDev1EtWE9BvOnz/LuYu7PPzo49zzkQd57JEz3Hj9aba2dhACIjOaEEDN9vabDqeBdrZA15n5Ncqb3vIR/sW/+r3he11m1mEaCDMunN/jFa94Ff/Ff/7tXHvNzXS6JksaFqEToZ1vk3sl67LQ5CVSjhjvZlNCMsW7wHxhBgFGV342m9Mv0uCR5oo5kNrXYH0zKWXry8i5cHGM4KYhR+0qC3lphBrY9GQANE09BYMxHyx91s2BMi8kRuveVSWLGZCYlUSyLKeWpLUzoFaKVjZtFKRPA3L3KOOonsLLgZ8Dfn3y2I8Bf6qqPy0iP1b+/p8xzsbnl5+vwYhcv+aTvblIccsFfGt4/tB42ho+lAs3NQpN05SuMfMYqojGlFfPsOajUQghDEZBYz9UGg56CsWC57ITd7aAjaNJ8NmUf4N3+ACqE5FRH5gBbWsJwOPbCxCxBhZnXZb1nGsCdShFiZRk6MjHN32uJstiSuRsmon2nXrUOeiEblN4DZ31WVgLtvDcF38Jm5j40Dv/giCw7juOtVvs7GyjGdrg6PvewEAaWWwt2Fvu89F7P2Y7VdtybGebxXzGE2fP84mHH+XRC3t8/BNn6M5f5NZbbuWmG69BnIUAUopw4oW+26AZtrfmdN2G49ue++5/mH/6E7/I7l6mgJAvnROGSyersWu/7713c/bsLi972bdy55fcxqlrrkVTT0qd6SB0S3wjEBQpxlzVyGXxvsTdMmwW4r3NhZzY9H3BnNTd+zLnU55LaUzumVR88Swn+JhqaKrBr30aNQqotO11bgOFWHo0FMOoQCjV0iJuWYWkmeyNus2kAwMiAXVu4NBElU2Mhu7kYAjyycaRjIKqvlFEbj/08HcD31R+/zXg9ZhR+G7g19W+2dtF5KQc5G28ZIgTmjYYc0xTOgZDU5h8wwGjICJ4FwiXMwpukjHG4ApNMztgFAYXPIYRUFIWpz2XC/oxGVosmHKUbxvL4qpBUb0HH2S0/s6o1rz3LGYzQnC087YAViyxJeKHkMe4B8OB7r2pqOh0co5gGi3n15JjKiIh3kpghQwINazDPARmbUPfdfQifOVLX8rO1hbvf8dbrHwogvcNs8YSpYrhNFKGPq5IMdIneP/772Ln+A5JV8wXJ7nn3oc489hZdlcr2ibwjS/5YnLq2Kz3OL7VmNSf9MS+J+9l2sWcEDyx62lbuLDe5yf/91/iox9/AtcI9HOU9aVzjoJMLNfCuRkPPvA4v/TLr+T5z7uVL/uKL+bOO1/As599PVvbwmzRcXHvIlkyKskgwNk6VKtGKeJLTrAoMpdEpOAGnEuVbxt2akYo8ljlKl7BMC/LfXVjt6RFKwYwqkhFXzu6dUQyVtyM2I0+uC5quDz0MBiaUZzDNULrWlrnB/kB75viUdtG1/ed3Vdn3CBHHZ9OTuGGyUJ/BLih/H4L8MDkuAfLY09pFMCst8MWnAGQCjmGL0ixqVtViEwLSmXCZzjurAcM46Gsr6qCD5OwpJaIKuMvZDeGIQpDR6VQ6LEo4iDOzk89Fs44bw1ZTWO7FGq0as4RXFPoxKzEORB1lHOOA21YoWRzeex2E7smVgxxJJXBO2q8WMv2fEHsuvLdR4NHiiw3G1780pfywP338fAnPs4a2GpntNsLEpBw7K1WzJotnPeE2YwuOc49cQ597Dy7qxWPnr2HJ85tOHv2cZ7z7Gt42bd+C9tbjgfuP0/sM87NUTXEYN9H2tKQ1G16WhHC9jY/+/+8ite+8f14dwLoys9TjUjwNU8E3gdSTNz1kfu56yP3sNja4Y47buVZd9zGc597OzfefD2njl1PE5TN6iKx60nFQ5ABLeCH0l9wpj7dtrbI1+vugGFGylyYhHWHexcOhgEUqQDrYm28pyl8ETa3D1K3O+cGz1BLCTWlEYMzLVdWYJNDkGTvZYxYvlC6g3NTTVW1XqJcpBDypWJLTzWekUSjqqpciSkCZKL7cP3119niGICl5ja62the3lrLqkw547SScJrijmI3rzbnGPOxkJ2RvVY13pyLslEWVN0E22DYgcFFzPkAn97QkirGsGxSaca2OgCmnAx9GCA0TVMMlCuMwCPpZ7kGZYc4cC2plHSFztDAVmXiVSRd/S6oFsitxbyUcq1SWHdSZoYjOc/55R7f8T3fzT3v/wCv//PXc/7xJ9lfrvAIx47vEOZzNvs97bwhJeXCxfM8cXaX1arnkXORJ3bX7K8jdzznFr7+a1/I8a3I7sWeJ544R+vnLPcj6aRYX0OreN+w6XrmCysF/oc/+FN++Tf/lMafIrKBGBA2GEbzMnPEOcMvaMS7hpg3iHhEZji3YLVc88EP3MMHP3AvPmxz7MQOz779NF/wwtt4/vNu5trTJ9lqGpp2TtN6QuOJsaeLnrZv2FosiKUTVQq6NU8Wvpvck8s1Q9kxk4VbwUoFEOFLiXmaQ6o07YMxySNrVE75wHd3Yi0AeSB3NUGkqFZx0WJ8YoxF64Jy362Kk0ruIycI4a/HKDxawwIRuQl4rDz+EHDb5Lhby2MHhk50H57//DuUYgmzmqqTFyGo3URrBMESfE0gd9bDT7aF4wpwZd0byIVqeRHaZL3w1iUXJwueYaFJCU3qjlDzDjnV0lM0dWmgYOhoxJiVjNLbKMk1K1EhOWiCGS1RB2JIv+zKLpDdoH/YpzhEsDHGYUeKsbcdxo3xOVr4ILSHaDV0CyccMYEvykTaRTQEM67Z5PXmjYMMW6dPc8OLXkz3zo/y1je+jxtOnWBnZ8bpUz2LpiWlRH/+Ant7e5xfdlxcCRdWkc06s2jhlusXPOfmLdhsuHAhce7JDY88fI75vOXY8S1OnZixvYBeBd8fx0um2e74wL2f4Gd/4TWk5MgSzaNA0acwCMDAPQi+LJgqitKTsxQD0YAKKXacf/IRzj/5BO9910cIwfGcO27meS+4g+tvuYabbz7Nc55zC9efPk7XbdjESLpwEQqS8fEnz7JcdQWrUCntnDF1i7En1x4YqQnKaU/DUNa2DSl5ocuR1rUGxGuaAtM/VAKn5CsquqoMKe3fXpUkVnZ2pTRq5O9CzlWyriipqeXUUowDWS3F0x04J44wPh2j8PvAPwR+uvz7e5PH/3sReSWWYNz9ZPmEOmoiRcWSKMRI5wRJYjjvPpnqMzNUhKSJPiVCH82YpEzX98TeOhABi+GrME6u8Xgsid6xgaSq+sa+J0bLKcSYBsKNlBO510GcVr0iKeHF2JRUgGRIBi9Cj9AEIfe9VT6dH7PZOJRASsrGlT794gn0XU+sdFqaCTKGNuJkKEv2KZJL/kNz4RHIGSNlyngRU6jSBJrwTUfIxzm2cy0v/zev5g/+4HXcd/9ZWo6zu/SIrNhpV5yYe7L0JbQ1TymlzFwc156esZi3LGZW8nvk4YtcvNhz9uyTdJ0Jkzz6yDluu+km9vcivc+49klO+Tn7Tyz42f/7t3no3D7Oza+ot/9TzhmtAAHrSTBew0DOiXvuvot77n4/sMXxEye57vpTfMt/8lK+6Zu/lhAT+3sXSDmx3pjKkpYNownGnZgzjMlt2+GDMwJh7xx4R58mrdJSGrHUqlE159VM8ke1WjYNEablyeG75YwWgJ5QuoZLPsG7YnjUdFGqJB5OIAniHQ5fJBONWOdKxlFLkv8vllS8TkQeBP43zBj8toj8EHA/8H3l8D/EypEfxUqSP/Cp3n9IstW+hpyJqoXmy0g8uq7D+2Dqzg6Ct+Yo5x3ijGhjtb+h6/piFCyK9E2hys7G4Ueyxakkw4i3LaG0v8YYSYV9ZbPZsNlsSuckxD7S9RZC9N6RC7tzSlKSfIYuT04gZ7xTZkEsKSWmeqTJdjfFsA4qVsuOpdLQ970hF8sEm4kcwL7nbOWwPlrrb51YWuKnrND3G5KAxh5Jkfl8hqQZ5853vP6Nb+Tnfv43AEPbRXV0OVuSJPXccuok9Ev6bNnsJjhahMYDoSc4R0o9Fy+a8la4EOjWF1A1hOam69m9sId30MwcqUls3Al+6df/jHe+/z7C/HrienmUKXfFo2b9c9bh/ju3Y96EOi7sdlzYfYiP3fObvOtd7+W/+ZHv55YbT/LYo4/YfVxvCgW+jiXiUhL03pVGKE9MGZMYKlXGSdLQOVfYoZXGeYILhJpY9iPvwwBQYgxFpiHF9HGD08jgXSBCCIWevmxSTrR4TaX/RRzBgboMGkva65mvPvz9p3jqWy5zrAL/3ZHPYHyd7X5q7lxWHYBH6/WGvu9Nu7CL9MkWtBSDIIX7brW3pOt7Uj8mhbRIwVkjU73YFp+17Yw0N6LVSruVS4vtZr2mW5tmpRa3fbMxz6ENHm0bmhDQrIX/sSSoJJB8D3R4etvpXUDFo8kbjwNSukHNEUw5glIWezdUWubOD5OhToAYI5s+0fedJTYbX6i/TL9CnLC3t88stATX8sCZs3z4g2d469vezl333ov3J8sV78i5w4UF5Miy71n1kS+6+YTxRGS1OngJ0bzOSH0ipoTzQp8j3aYjZVc8lsjWesmZxx5lNhNOxkAXruMX/r838Yo/eCttOEFcnwWOrn589FHp6TKuKExZ7kWKNsUSlx3N7BibbsW73/YefuqBR/jhH/l+vvRLv4jHHj9TeBc2BOep7UO1IjDwJMZEKmGPicuMBmFYtDaZqd2WdRwuPx/+mR5z4JuJ5dKGjSElYh/Z9D3rZOFMdg43q2jLOOTDskllkbIMsotHGVcForFmXWNK9DERUyxuUSzZ68464KLSsSbmRGhanAsmQY7Qx0y/XNIXks0aqG9KgtA5pfF+EJR1IaAJpBBzmNqxZaGdmC5k7jq70CkRU2bTrem7nhQCjhlIwPcVfGT5gqQBjY6cOlzuadsZuEBWoU/OGm6K9bfvbPX0VFiga8nUOaETcz+rupFm8yrW655NiswWc7ZYkLPSlJ4QxeNki3vve4R3vvM9fOB9H+TxJy4C4P0p88Q0IWJyaURFpUHVcf+ZfY6HnhPHZgQiOfYk9WwSBC1wcnVkday7zGq1ousNbp5zQQY2W/QS+MijPX/2u3/A6//iHsQt6NXKpzwzkcPhCUStC+Vs+QbnjME6pdKw5B2bzS7Ot8AWjzz4JD/z0z/Pd7zs2/imv/0StucNq/0nmLUzW9O5yrQJVRlaK+mqGxPSh3f6Mp1N71PLfHKjBmWtCtXX1HHYixgqY94X5a1J2bqP9Os1KZZu3xDImw3E3sKOPOpESKmm6dFtwtVhFLKqxdM5max7+WLr9ZKmbbAcjBK7zlqhhUK3a/DYlClxtmlHMLAgmSsvGEJRnCOgBhRRRWMi971lekvbtQ2DOFfrKiXbH2Okjz2kRBsghEwSocnGLJxLjBuzQI6sSEaG4QMxK8t1pO9iQTYGNBf6ObEypJQuYCVDhqglmVT4I2Pqydmw9zlFYt+R5y3tbEHjG3bPXeRDH/ogb3/ne/jwB+9ltbTMvnPBavSasJSWfabzQk4bczvxrJLy/gf3eNGtc67b9lDVvVWIqQdxbGImroSuz+wve9bR0/iMEGlbZZ1a3v2B+/mjd32cc+f38G4bESVmSCwo6ipPYxRAzvD79O/JUWKhpGoqqEKHMkfVMvKa7TnnFqzXwr//d/+eD7zvr/i+7/surr9+m3WOBf9hyWPvkgkE5TjE9AOY6BDIqCIgXSkfqwheLGFY8x/eT43H6DUcDhPLlxnem4qZSNlayKORzTq8iRMLtN50KFJKRjgj9ToxMJodZVwVRgFV8wbKjhiLAk4QIEbjz4sR8IWP0ZsCD3FwqQ285HAyFjZBabyVHsUVFGKN3cDKmn1vvfCl4cXnsjOkhNSSpGYk9kgfoU/02rGRnoXfssmTPNmZqKiq4rIiktis1vTrJRICqp71OpEyqFjt2pOMaVpc2enNVU1iCMNMJvbetBXKpFI1/sg2CMe2GuazwONPnOdtb3oX73zHXZx56AEgAXOcmwGuxNh5uCoQagULMJYosEm87Gfc/dCT9Ddsc93OghTXxC6z7KGLmVWfWW4y66hE9UTA5UgjjtX5yMf++L3s7i0NGyDbQ4nYJmfkoFP9qdwGNQh5ndiuHK9zCwEpi7/kAnTYDmXcFAC0GiJfHvdojjifceEY99z1ML/6K7/LD/7If8aJmeJcj3fbrDZWYlZZGrLSt7i+HxrqMlYBq+XGUhjHSuEWkmbGHb4iX+u/Fcg2LoOD+ARVI8Et9fZR3yL2RQLRyHW8M+NjLGNKI2KSiApSGKef8ZzCZ3oo0PfdAN5RqdnWmvltQAptRrnZY4JHCd4ywZVvAUbwUtbKtmQXzQdfPI+CiyjlycrKq7UqESy0yNGShqb4U4g1ldI5VxNcheWHck6qOPzwfjW56QuIQV1t7KII4Aq+kSGR5EQhB6JC40Fzb+Sbpdd/+9iMnB2PPLLH29/2Zt73vg/z+GOPYwnEBeCG0uuVTIaqjrXXZT56Zo8ntuc4lw0G3BmDUVKIJYTIiHlc2Uq+q35dwum6O366sYJgTSi1Ndzg4uJLfX8wduNufNShKKJtyV0tePjM4/zSL/wWP/kTP8jeRTMYTSN0UfEEtIFN2hhtfF3MWkR3JslBO2cZKlV1158K0x7lngzHSPEcKqoSHRSggvM0bUvwRlDsxYhlHJY3M6Z4bwxR7nPNKKi11sbOMureOVzjcN56wWv2tYKTtFhNVwhXJRSK60ngNLhiGDLSlbqzL/aiApMqPRYpgyhayoAOQCA6tSJimQjBKzg15CK2gN3g9guiCXImRUEK4tCJR51YKans+IL93ThKmUoQryUyMlCUJYk6Nt0a1NH6LbIG7r3vE7z5jX/BXXc/wP7+GmgI4WSJp82bEAlOsaIAACAASURBVDFYdR5dgk99HwpxR/A7rFPk4QtFrswJaGn3BqxcMVxoopqku7nsUkqCTzdMmA4ZFoIt/BYhgNZu1nzg2MuFE089nEGapcf7BnTBY4/uc+bhXW666TqWq3OExpFVyNqSUjeAiwY1chjISwYkrf1R8gnjz3CWcukcPfCNDxgYDhoFuwo0oaHXwhXhzAum0tnXaoSTCSeDu6LN4aowCkIJFQqqsbr3odR3oaDbCrLL9PsyTARIVXVQlgKGXSp4I8AUkQJPtjGUkdRyBhHr1hNf2L1KXOgo4YOaMrWWWNOJhQuSKb30tohdMk0/JRtrTmYgzjBGHsWRDPBU5rVqYQqq6tXJWrHJhs9owoKm3ebDH7qfN73xbbz3A/cSI8AC73eAnpQqOMWVBWrItivdQYWenGzHc2KCNCl35hlpoTgreQER06xMOSPBo1kg9pYY4+gIuqc8l6ovScCFGUIoHkLk089Y2iYgLpOSgVm8b3j5y3+b//r7/z633HqKvf2zhNCQkqDYMc6PbcpuaD6yUSqYkzGWDWtF6anG1KgM83ny3IG/nZXbnVbwdn1CCtq1iAhlM/RKNlm/I46rwig4hNZ5nLedW10RdZkIaFAktbwqmYoGGyXJ7aLrJQvA6rcMTSeCTWKVcWdRivXHOqpER/JNo9p2oHEAkZCLx2HUTMbYW4g/chRclsK7b7ZCcy5U4A5yMoVrsV01qjeuvcZKYVmTUZhla4E+sXOKR59c8ke/96e87a3vZLVa491Jo6WvCbVibGwh1h30aG7qwWGGIJdYHc220NUDE8ETdMyBFW0CIeDIRkdG5Rz8dIZh96ABtw3iTchX12X11e88Ju2u6JtK7VoUI3YVQbXnzJl9/vW/fiX/5J/8A2579mmeeOIxhq7PMt8GRGPptqyVAu8riKriJUaDMG3qm57DNH8wfbxcApOZEznA2jz0S+hIPSdQDEJGspKSWv4KV+b655qnIELrvbndQHbm8hhozPz92imG9yNtNkDJI4gDNF3WyiLFlapIMrVM/+DeFYipafiV0KL2UOQa59fdwZJf3lE6FLPpEdYwRGvFooBgMORZuWNlQpsrmMDg1pTMtDNF6r5PpKx0seM97/gQr/vzv+D+Bx5HZIFzbamSZFT7km2Heisrms/e/fJtyZ/kTpQ6vGWzLSr1uFK5mGb/q4nwpbU5ZyHFciM+5QI9yjkVD01akNaqBqk0ULkWPt18hQqKB3UIvlQGBOQY587v8esvfxX/7Y9+LydOneDcuQuD4a3YhCoSg4ydjFWdGhgW7PTnioy01B1Fh88Y5vJwjF0nMxQgqYgaF1LXpJS8ruNSMvmnHleHUUBpvUcUEplUeglsz8uFttu+VM6ZxpekHbYGVY0s05XOx+lOhiuoQqeo5KL+W4grMEtqypW1X2JM0JkbBlkd4huamZA1Qi4lq+zI9YylLFQRNJRdOgQUo/BOOSHZPACotRElaSaosNnss72zw/s+fB+vf/O7iRLY39vw0bs/ivECHCelHh10JGtdvl7FytRU/74yaCvDWRkasOYQ7J0Lm9W0FKgjzX7txqtvocP5yKEfxvd/ys+nPO/A7SC+BenQfg0YwtUM9uHd78o8BTPiNdy0cChG8CETguOBMxd5+W/+MT/6o9+J+Ibge3zj6DYbs5midCmSYk/AOCy8yjCPnPgD1ZApSes0AVz/rb03w6aV62YlQ36iXhkA52VMvEfQ4K06k41joUuJaOkvW0l/Ta3Tz+hwzmrA1oloyTudZGoHa8sht2uauKmAjak19RN3jRLXl8SlajbF6WqUxZicNdeFV9iXXa2IeBpxOBprmJHatZ3QUm6z7raGpjFoM7U0lixh6mobNBg1eMo4DYSww2te8xb+8E/fwP6yw0IBRWRukOTYW4JSKo3PX/eY3otJInfIsE8XdP23/j4+51wY/r6k1j/9XuIQF8wIp5GZyI5/5r+/VX6wBR8a2rDNR+/6EG98ww38rZe+hNVy35z0cpjlvWzBVoi8egsnpJSZ67URGYlVQgjDdz5cnRgf14HkJ+dRtqCycUmpgCnWzIez+ZpLi0CKcZCkTypGiHwF/SZXhVEwKIDttFnVMqkWtI+JxHKslMWoKkPWVWs4EKUk8yguv6DeGVGK1s8q/kBFpFGXn5bSpbVQFxcEyYLH2riTRlxwNM4SlE4VoUOzlcTEgfctIcxo2xbnKrOOkrMQUyljequ9G+V8pm1a/uqv7uPVr30rXZzRNMdISXHOlKIrcs77hmQ++l/vDWK8dofHUzEVXXqOdh3GcOeTDSnlaCXHVDyDNDz3mRhjbB5JMSLqEDnORz58P1/9VV96WQgyFIpAZZinUnIOWccN6kDD1MRjGL7tZJ5X8FPtZxnbsUcukLqxWcm7IB8zVC+XPJLFuKKOdSV+1FVhFKzw4PCYAKuIRwplmVFJUWK5coHc6HLhKxFGsmapMuMGlqZmZFhCTdY95YRP2dqWdeKJUHZ+JrtgYtDzy9mXzjeHL7mujIfUIyS8d4R2TjvbMjJOV4hcSlk0qTc1oGAdbZpMFizjeONb3sm639CEE6S0QdUTo7mpzllpMefCtPQMdRk+vXE4ufdU000u+9zlz/1gqCFiCV+TY6uhy/R9n+lRvRDAW4tyZg0aiNHT5374aGvCqwt93LUrj2flR3D4gZGpzsnDhmWafJxqlky/Y8oFAu88uJG9wU+S7zX/Y/iYXH63sNvWk5Rg/GjjqjAKCKa042wXpoCRmrZlVqipY8yj1axJruCRCYdj7+Jo8UvlIszbkq8pBiFGYrLGKx+jwRNk7IqTEq/bexYVHs04D1lbfHAEZ7RsHsgaiP0a5wwT37Rz5ostvA8E19piLnPavCBDVVImwmw248Mfvo+PfOR+RLaJumZQRRRHSUdS4+zPlj2wHW+saowJ3adapHVy1xOeLLxL3rc+Py2vUZKb1ROZ5jQ+U0PJubUQwSu598y3rjNC3iQEH2hCpndpQDDmnPE6YeKuqIpp5WxyzkMpMx9MRAID4auU71nDB6vuWNzixLzhgcavXhln5XAVJWqGHMlisnVBwF/BvLkqjEK9UB7BtQHX2GIPjbnhAN6PXsDgDYQwaDdYKHDQKlvJyG6KABqU5D0hG1dj7wSfKbRqliTyWOiQtYKkKjuOlUBDU0ukWgqAVl4UKZa59DWEdl6IYg3fAAzELq6I4+ac2dra5u67PsHFi2fx4QZy7qwMhZSSXN1dBdVPv/b/dIct3oPJsTrZp171Jy8NXs6I6JjQqe+prmAUag9AzSn4iTG64m/A6HFMz2M0NPbelUJPwB2jjy1Raw+DDC3QFX1aF+v4KVKo58fciYHTbPOqocM00XgY7WgJ99pM5QbMTPVIcqlsafm9FiqE2khlhLQKRumH+xxMNIoQ2tbyAs7jWpOLC36Ob5qC5hp33PoFayOJc84oqeRS8oraaKI60qY7tWSf1Bit1pxFStVwvIBGqZ6IzlD4TQjmXkoyOKkqtFYy886k7hrv8c3MJoCMxszERw0r3xRRma7refNffABkhuSIMAM6q2JksFtdb9NnL2yokHJzWBTNDrS60rVV3X5Ahph2HJff5Yddsoq2qE3grBNEpF7aH3AlQ6RkjRRGHIcD2nqA5YQQ8B7ymtx5YMXWsWO4oOSueKkecBnnA4GG7CxZbG9jhsI5RxOK/J+YWpTN05HbA8Y56sTmltlHLcSyY3I1lJDxgA62FLwNOhFFMlLZlK10ihRKwVDCjyOOq8IoiAjNfEYQh3pBmgYXAt43hKaxnVrEstAwzC3bdcOQ7PE6SRhVqfAJH0EdOeeBIt7yCKWaURbi1CPJhedfNFpTVSjS5wKC6QcKmSwR5yyH4Yo6dmWPru81zbzbJBHu/8RD3PfRTyBU0ND6gHG7mobqiPZUEdSNhc+6m9XQ7ujg6lJ+HG7qM2/4VMezqcanhovlCDNsWJNcCL5QwSX2ds8RBLQpyFrpiwGxUzYqeWPccs6VStZBSYLprbxUz8MMySWhRN3QyOTewpWc0tA+P53Pin2mZCxBmkv4kZU+RyQ36DOpOi2XF4L5GeC7MCree4EfUNXzInI78GHgrvLyt6vqPz7CZxBCS/YCzpkYjBu1FaNmXIlfa8MUjE0mU22IoY984u5Ny5TVM5gmdqbHWfI2D8caUs0PVtsVmvdUYzxsx9TSLJTVlKQuB1lVHWnqUzJ9whQT62VNtCVqYjrlT1bP/2wMQwAqZigRAedJDlBrNa/3R67YoH2mcwX1XpdQUmqnSiE7nZyvlQBzKY8n+vUSlyuicHxH1ZIERHFqn5ByAnEGc9eDXZB1LsUqQ3gojJjmUqd9D6ZTnkrSO9UDLvmGgpiuZjQSlpwzhACVZ/IKzPRREC4vB7790GOvA75IVV8M3A38+OS5e1X1S8vPpzQINgRpjPFWfLCSZAHGVHm1Wkc+SBZhaZbqvh54x8tcuEs+tXyOD37AtB++YUOZiGC962rAKmvDNQCJGQPQLMb1xzTunWSSkxGt2u5hrt4111zDjTefQkqSNKvxIiKfvfzB5YeO9yErEjzt9oKwPcdvzZF5izbecjNXuL5FaoUoMZLAPB3w1VN+ApfDd1w6bxSKFL0BAYWHHnqYez76IN4bibB5AGYgaydqKkKzA2bGl/xFXe9q3ZQDafChuWpIRS7NWZRTQpW+7033AQaej8G7KN5Dn5OFL8HTzmY0sxnBt7TFKz7q+JRXXlXfCJw99Ngfqw5B39sxxuanPwSjVXOhsBiZCpROjcABN8sWXlbBaNkP5gKmrtgUe37ARRsMz/hvjQcPGIPBKE3cvZq0krIAxM7HssQO8tjiXbPrqvW1OiQO+77jutPX8G3f/nXktEsIM0TbEgN/NsuOlxnC6AU4AbHiFzFDLLDfVJKDV+Qp1Jtcp+JnImwqBly1GOPqfh82FOYVanbkLGgpc585cx6jza+Ao9HN71MiTnocKjIZOND/YKTBaZh/h8Ffh+eoJRxtI8zW2WSzrsz/kVbAwpOsSnaCn8+YbW8z395iNjNVcl+IaI86nglz/IPAayZ/P0dE/kpE3iAif+upXiQiPyIifykif3l+90IRXRnbZC8Zl5SqZbwYOjaJPNVFvpx1vuSxQ48feL4IiNSJZRbaaN/rYRbbGbR0apSGyVgO3Gw2eG8s1bGPfMfLvpmbb7udGPcQZxJf8mlzETyzo/JgVvCXxp64XBL31+TVGja9te3qQS2Eo733wYX5mTEM9TMUy3hMsRH1fC00tEqUIO0WsxM3sHP82kLqIyUEqEK/xRhO5lrKGUOeMs6XshFkvbSsOsyRyXvUayJehjOumxaqlrvynhAaQmjKpuZxVWk6BHzT0jQtoQlQSuBHHZ9WolFE/lcMOP5vy0MPA89S1SdF5CuA3xWRO1X1wuHX6kT34UUveG7hV5WyyAp7TVKSs1KMThZ6jQUtc+ugUJk/1eK/FJJbbs2kQ60aFjLD4p2+LmHkFTULLyhaEJEkRWoba8Gsj+UhLTV3678QdQTviXGDD4HlfuKPf/9N7J47X864cgU8k+7zpz9qv0FGSgK/6ErJiJarRvVTvNMQGmiZ4DlPVaLqc8+kUTzMuyCXebw8koE2Qt+gcUHaWXDDTdcWBSzrNfElKZ1rrqtcA8V6ZaxNLplxSULMglM1dfHyU6n7zfuCXBiUxI0weFHbHFQogjHmkTqRguQFirSe8w6NJvtXsRGqmbb1FZF35PG0Z56I/CMsAfkPtMwEVd2o6pPl93dhScgXHOX9hs4ztcs7Xbw15jpw7CEvYLorl88/gqcwdrsdTnVd7nUHw5ExGQmTz5m8dnhNcak9jhwjThzdJuP8Nq945e/wiz//r9jf7xFpDdfgG65QcOuzNqbf9ygVk8rIZAZhRPJdLUNEBp5PHMxbYT4LZtQpye3ghupSJTkZw8Tq3lfm5qnbr0PycYp0rCHCJR4uBzkWyqHDextRUMlnlO7NSjeYsyUbQwi0oRkaCI8ynpanICLfDvxPwDeq6nLy+GngrKomEbkDU57+2FHeM6uWGyHloo47OMplJp3Vnac96odjsssZhuliFRXqgoYhUzB+wmVeUz+7/r94idMXHXh9uS528/qIE1M7ni+2+dh9Z/it33o1sDAeg6yl9bkanast2XjpuNQQXJpgvfT4adPaU4SLn6WR6SA7ggskcSzmnq2Z7d5OxrzRkHPyfmT2kurW+4OVLzfhBp0kE1PS4XpMW61hWoE42PdDxTMMIDul7xLe22P7y/VYzhQhxZLYTkc3vkcpSV5OCObHgRnwunLytfT4DcBPiUiP+Wb/WFXPXvaNDw3jth+WWXG7SxzPwYU2TqxLqwyHDcL0NYd3/SG0KGGs6qFjD7+GiedywFB8Ck9hSBRp6WRT2lnLW97yDnbPLfF+e9gx7d++ND9dXbvoMzN0APGMYdLV4xWJCuoC0JL7yKJ1JgGYxvtYz9e5sUkpFLe+dvYeSFQXw3A5wRcoJvEpLsGQw6nnV+yC9WCUjkoVYix6ozhSVmJX8TFC8umKPLJPaRT08kIwv/IUx74KeNWRP72+DpsgSr2YB2N9LrOoD7xa5IBxqHF8XZD1xuVJCcpo3ktyM+eSy9CS+edA4mdqQFy5K7kmmmroopaZfyrvZGokWq9sNis+8J4Pgmast6Wn0stB+Kz1OHz646l3/XpvDzb/5E/6mr/u4cQhfo5rjyO03PKsm5nPHcv9kltKps7V9z0xJjZdh89KlrYYCYPfH9vZZrFYMJvNCG1L8JZLqhiZzIS1OY8CwlO0I3AgpDAYvYUefezZdD2bLrLeWBm17zoTTiq6kT4EthZzdra3h3aBo4yrA9GopRMQy976os6MAxFTUrJSV2kJnRqAnKk5WscIMMlFWVqCH6ecysBColrUj/zYbIIIkgyMUl0zUQqsebT61bXIGO1Vxix2pW44nEm2mqsh5CRtE/yGi3u7nD+/wQyAUkMFHXaiq2f3fKbG5by1q8kgiIC2CwInyCeuZev4jdxy/QLRrpSmKblJb7k7VdNzzNHYu3H42iehGXFafkYtCIcJ99ShWlmXD3oQw3UqlQYt+BZvcQKKCQstl2vTQsmK9onNqmPdRVKOzBYtKSa6LjKbfY4ZBWASJujBx/RSmS3qY0wARhy8sNS/s9UILxcOUBb9ADsAVNQw5FK6MsW4GrxOZeQzFaM/AJ2YJCFzEZxByu+1IpHJdDTtnLxcc+HiLrXM9Tfjsz9UldR1iKxJ654T10Ruu/k62pmyXC0HOLwrHB4VbuzEej1SMr4N7x3O+6EbtiI8q2zhQBpcy4SHULhwMLRw4gogqiheOfu8PkY2m40ZBYVuuWa56UcNFU3ENtB1a9brzzGjoGCWTmz3dROX2w/x/piASTkP8vFPFVZczkjUmA/G3IM7dBMG61AMlCulnyDGBR0K513UiKj1ZDi0UqUWCXOgiJU4Z/lT4xk1w/LII/u88pWv5qEHzwDNBIP/N+OzO4TghCBC7BMntjI337hDt36C6tHUSsMBtKKOgCbBJOtCY0zkB7RA1fQZahViagCmMPzD89kV4B6AaKbPySDWMRP7RIr2uX3WQqTrkdL9W2H4V8D0f3UYBbTi6SuhaYk7sxRXXtGK566x+QRYWKGg5GyU7GU4xjINqsWtz4zN1DYOEANP7sdQVsIWvhE9WVNzIWYaSsCFb4esEdXWGlS0AJmGE25R5/iZf/6LvPUt70Bkp9S+e/5mXB0ja6anh4v7XHPMcWwbHn0kFmXzg9UBI+YtbfZknGuHjkXEWpultO87TL/U8AkHCVcOUrGNGpVGkmJeR45G/oIzFrBhC1MLXS08KSAmSrXEmfaHqiBXUMm6KoyCqtJvNuQgBahRMrdhvBE1qw+gKQ8WewgdigT5tLxYO48H6S41qqqKgKjU2YiJaFjob7JvNVmZC5ZBnaDOD4Ylx2SkLaW1WnMkKkgnNL7H4cky0rE5MZny/eUu9937ACInCY0pUP3N+OyMA7F7fUxt0TI/wTUnZmheGnnsBDBXtTQqnZ4lrWuznuK8GzRLKt9Hnb+VSas28U27JuvfRqxSGKLtiRKi6JAcT0XbNKVM35sAkCUeO2KfBj6QUJoL+/7o4jxXh1HIRQ8SIzuRWseWkaxyihvPmq17THUoaI1c+COGwKkO5Bhgxa80+cxcrL0C6oucnPGvDTqSVcVX1ZU3tZtjNFkmRhr7iKky2fvF2ON8wKeJdVbIEjl93SluvuUmHn7kI9azoWOS8fN3TEpz5InTZsbUCGkoeScrY45OXS6YlqefsJw6iBmHDy1b11zDbbedxoh1WrpuOYn7bYe2DSEShkpBKmA4E2WpXq1zBv32pY36MK6m/DFsRJRvKCJD9c2QjrbBmA7JtEpngsrixFr9exMubrzH+0COSrqCLsmrwihkhU3Xo9ERZmJ4Bedst51UC6Zt0ZTrV1rHyWIXsgqamvSbEAwjPWR5FRluVsoZdTLs4gA5m/XNWYcmFhEhx57gQznfTMyRvuvJfSL2falqWCWkzwmJHSYdWd1Eoe+BWeD5z72Jd73rfaAngH0ubcz5/BkWgwcy0YhwC5uQPenRtCanFXAcL63Bh0VxRfatyHMSSXCFzFSKsWN7TIRHceCO4xY3gJ7n2DFYbwINK6IIPpT5mBPBB5xrSCnhUGISQmO7f+xto+i7zohWaHGeApazHFXfJwQlOJtTqhnt+8LYNEmgOxmUpCvjkiSGBLZ5K4XjIZvkYts09CUf5p0jqyfp55inkHNmverws2BEq3l8fFp9qONwpvbyo2DsL3NcLtWAqhlRqxA5GUil63r6PpJSJEULXXJK1tpdpMxijMTYIynTdz2geCdkn0gxkgpbjmbLSagooemIMXPnnS8E/oSUIbhZIfT4fB0J5ztEG1IWRFpy2mBLveOOG6/l677uK/izN72DM4/v4sMMVePYNKYnT04eJ8EMxpUMNbYi0xlpUByzk9eiNPjUMQ8B55WeZDtu4cOg5prUyHJysgVnG4l5DzFZ01RMCR+yKRpqtML5MH/dxGswXMHhSpsUb3mK3I0pgla+hkATWhTocjQ/wnl8aFGEmDPeBa6kn/2qMQqbzYZ5E6BkS6fIxsNZWovdRhag6ranQzXwwwZlahuycID2naSkGOm6ns16bbXePlruQLUkmjYDn74lIDOSk2EixKjJcsqkPpJ8KLkG80ScF5I2LPczkosUucRRaejzdCiOPgleHJo3aN7nuhM7vOTFd/Kdf/tLuf2Gkzz/Bc/nq77gOfyP/8f/hXNbpOhBO8Q7Ui4CMU/rMpqrr+LMy/BzpF2w2V1z4kTDqWNbdKnDNQ15Y7RnyRmDSkpWAXAYn4aVGA3UNlD4xUjOpev1MLiOCpyzatcUmjydswfC5lL+HMqZJWTK2chbuj6yWm9ArR7mQ2NKUVOxniOMq8IoWHxmcE0nRftO3JCQOWwUUmkUEe9pCo12VsgTIolLsA2YURi48xnh0NUj2Ww2LFeRzWrDerMmbiIxFhodX/Djak0o5FQSk6YW1TRGH+edH7ova15EnHE+/Ma/fS13vf8uzjx6FifBypWaINVSyuffcOJRZqR0gVtP7/A93/q1fNkLb+OLX/RsVheeRPOGj3z0Xl7xe69GdYc+zvG5I4RtQ4EW3IiTp6NfOZYXVcE1Lf3+Pqw3zK8/yfaiYb2OJYc0JrEZ5lUpmztH8IHgPCKOnDIx9gdIVWoo4GpJs0LjSxxcF/rhisThUmVF3lam55RMSLaPmdVmw6brzQNSg+xm5cCcPMq4aoyCkcYIIt5q/M4dSMhML5yik3pxxTOOzwMWK3pLSLnSZKVu2tcADOUkpU+RdbdhvYmsNhtWeytW+0tSTDQ+kChUWhWtWNy5+VxommaAsKpjUPRxTkil1Xa57viTN7+LJx86g5djZBw5rmlce6VO7380Q0TM5c9n+cJnXccPfc+38Xde+mXc85H38dBdd5HcnI8/+iS/9uo/4/33P8hN1z2P1gv7q32evHARZIGThpxXxe27kuk8LjaHmnOaMml/F5zj+htP4hpF1o7cjYvQwsZYQkNLWDchGECp4A/MtfcDqXD9CQfYjy7dBCo70rQqcrmwuZ53jJEUEzlZc6C1ZRe9SzUBY3GO0PgrYl66SoyChQ+bdU877yALglqM5SZuFOWEK6hQMkkjWcQuTk7kbAhEVzJQUthprMQ7IdTMhRYgMyQVN31kuVyzXK65eGGf/QsX0ZyZtS1ZhPVqReosqRi8ZzZv6RPMZjPECU024ZrBU8ChmoYSkvMe5+aAGIbBt6R8dUF9P6NjUlyv98Xnff7Tb/1ivuGLvpBm/3He/id/xLJLdFHYu7ikb+d878texo/deSdbbsWxkDjrtvln//wX+PBdj0IWmtAQi5z8kU9lAB+lGkSQ+w7vAwnh9ufeQO3TcBKgNLL1XaTrOvquo++7YSPKZfeu87NWBkbg0hgmTBv2plD4oeqiEy/2EDbCOymkw2VeRas2pJwR16Aa6WKPqrJwWzTNjNDI554Ufc7KZtOzWq9wS4cEwXWGCWjnM8RD15kbF3wYmHMFy8wiEGOk6zYgivcOmgzOk9UXCLJh1GOOpcxYjE1MxCLN1i179lb77O2tObe7YrXXkzXRhJ6UE8v9Ff2mw6nSBsfW1pz5omVnJ7G13RiQORVLHpScHN5D2zRcvHiOi48tAU/KHSLWOvv5NAQFByE3RFmSU+Yn/uHf5UV3nOTJTzzCputZNoHFiR2ec+vNPOfOL0D3NyzmC/ZTz+p85Jib8eI7buXvfft38FN3/QqeaFLy2lyRx1XxI1YOttZlcRuSNMxPneR5L9pG1h4vHctS1bINRHBqoWROnbFvJSNOAUcqDXpGyadDD4/FrjLkBERKdaskDHPdOJyzkvjgAR8ES3knJEmId2QJbJKyiYom6JY9wut+iwAAIABJREFUWR2qHt+GoiplRmRWlNaOMq4KowC2qPtNz3q5Rrxd2NRH+vUGF6QkdswtM+1GGTrGEOj7yHrd40VpWs/WPDFrWkiR7I0xJ8Y0ZIgVY1SOOZOiEWOuVmuWyxWr5ZrVcp/VagU5EYMjZdi/uGSzWiMK89bOA6fMZnb+mrVI02c0OpLvaWaBTOBdf/kh1us9C48wohFgAMJ8/gwh07Jwe/xX3/PNfOELbmL1+FluevazmZ8+yfap46zO7iJdT7+3S1puWJ0/j3OO7tweZy7sslzv8sH3vgfIqG+Nn1Mc6JV5C9MQwoZHsnDNiR1uuP402mdyFkOnYuC4vu/pYixGwlx4L4GUwCeD3081L6Y5K+CA1ojIyBx+OHc27STVwvWImJq1Ce8akeum61l3PTlmun6DiqNtAy54nIO2CcxnnjZ8jlUfVJVuEwlhg4G27QJ2eyua1uMbA3EkdUYrrq5cHIcPjpgzXdex2SQaB/OZp18FtmYN7ZYJy2gWYjJrr1npksWHKVspct31XNi7yHJ/Rbfp0ZTRnCAnUp9J2bFebti7uI/GSL9YGAbBJeYzIUWz/Dkm+r7DyQyZrdlE4cLuPr//H16PAW0aLMkEBzDV/9EPK/85Nf3ML3jWrXzNc67hpufein/R84nrNU6Ufm/J3kMPs//Ik1z4+INsHz+Otg3atvjZjON33M6/+Xev5Xde/wZ8uB7yBskd3rfE9HSJxCbVrgyLVpgHT+4j4hu0WwNY7J6s8akbeBoN76BqWAdJbqgY1ETmwM5UPm0qyjtNLkIJL8rvNRE5egt2Hfuk9CnTlQqIUoBLOYEXgvc4D94pwQvBK/P50Zf609V9+GfADwOPl8P+F1X9w/LcjwM/hIEH/wdV/aNPeRYFHbZercmxQ7E6rwea4PABIkKSgLpAdq3tsAV41PWR5WrFar2mbRt25g0788DOomG+XgxGoSh8k1RJg+dgn73a9Ozvrdkse1N7EiWII5FIfWTTJfb2L3Jh92JZ+JG2bTBnJBeMgwGZkkZSH1ivldDOec1r38wDDz6KuDkjrbhjinn/fBiC9aMokZtPn8ArzI9fx/75x9l/+AlYb8iaefLcWbrckfoZguKSMMuBnflJnvXs5/HSr/9GXvG6N9GJgxxovKe7ko6fej4HYM5C1R+/6fRJgstsSj7BOyt31y5HSmdrQvF+WmqceAY5FxamQNO0uFJunOpIDuX0Q4ahnhsFkDeWJCn9NQWGJ57QBma48uE9GcEHR+MdszYwaxyzENhazI58XY5iPl4O/Bzw64ce/xeq+rOHvsgXAv8lcCdwM/AnIvICnUr0XGZkVTbrjn6T6bySck/XrfEojQdxSsxClBZtttAmFAbbgCIsVxt2L1xkuYq0s4atecOJ7ZZT23O25xHf+EG8Uws1eewLalGhi5F+E1kuO2LXDxUM658vXkqM5N48h9q0krNBTp04K1vFZIYmRjrpadsTfPz+B/mj170BCAWBVr+1lkl0dZGMfOaGoir8/+y9Waxt2XWe981uNXuf7t661ZDFIlmkSIqWKMpmoMaJBCeRAQV5MOIgDgIEQYAAjoHkKXnNUww9Ok8JAiQwED04thULSmIFQSzBRkQ5sgRRlCizb6u9dftzzu7WWrMZeRhz7b1vVUm87IuSJ1B1T7N2c9Zea8wx/vGP/88m0LiJrsk8vFzz4OsvEbYb1nfvs5sG6FuefvG9PPf0sxjr2I4jve148I3XuVrfZnfjJuP6EistJSnbdMSBab7l8uEYwNMRI/3v/S88h7fCzuj14qzDmUzedxJmbY1qKnNEf9anmG/2epyzB2s3EZVwkz2x9shG4E18nL0IcC1zitKzrCi42vcti77DOyUzOVM1Qgw0radvnW6qFpRO+2TrSZSXfssY8/4nfL6/BvwDERmBrxtjvgL8FPA7f9qDDEDJxKLI7rjbsttt8EQap6jslA3RdtBMNMteI6/zYCzb7cB6veV6lREz0bWede/ZLCfOFjtCCFhnoBq7as1Wo70oHpFiZhijcsZR+q13TvkSVVv/ZNEjWf0fu76laRt80KwlZzXksDkhaMawGwL/zz/5JKvVNd7fJOfxbca9/6x2H+pEwQHmVzqzGE67yLtvnbLdbHnji58j20B72vPix3+CGCMPv/YqMT2ERhjGieQ7rLO8ev8hv/H3/iG//jufZ5Osou1lSzD6OZZvY4bkMWJb/UgWC0eOOsuC1ZvMOqfTiVXoZB6LTikfPY+ptG0Vdz02tNGAoDZzylycN54jAyKRt1wJUrsWhzcJRRLeWRZdYLnoMHYgp4LkQMoJQeh8UEZmnbcYhicPmN8JpvBfGmP+E+D3gf9aRB4Bz6PmMPN6tf7sLcsY8zeBvwlwtjzRXdd5EMMUr9kOAz5tmJyqHSXTEL0HEym7gPUF7zNtt8RiCcazGTYUccSpIQ2J3Xpic9LQtgHvDW2jTjneBkzTEtNh149xoiTlkzetw1Jxh5IR0RaiCm4GXIDQNvjO4dqg05wGitTJyZLJk+XzL3+JT3/mK1h7SinjUWagay4j/sytGRCTqPZ61uMQ1Z+QiZ/98Q/wvqefZhJ474c+TDk5wTeWpgnYDG3b89r9+2w31zxcZ77y8n0+98pt/vi1h6wmmM1hpQyAJX5bFZjR2RqJGDNbu2ckF7plwrkeZyJZHuKkYTJ5HxCstTRNg3OOWElIzjltF1pLGyy+UZ5MmYsmqbMIchBdmYMLBqxRIFF1PAuixpCYYxvD+s7btsE6Ydl1DMuJKe6I04i36oXqjMOKQaqd4ZjVs+JJ17cbFP5H4G/X9/m3gb+DmsI88ZIj34dnn7olq2Gszs0wxsI0Vgpw5R0kow44tv6hzgaaJtA2nnECTMZZS07COEWdDIsGZ3Jtbc4EIzWqMMnuTT1mjrpIoXMqu+WdgVZrzHHMuhMVncbTOfWqymANotpc+/kJKZkpjfzhp7/INI54f0rOm+/gdP+QLREgYyRjzYRIr92eMvL+W+d84mMfJXTCj370L3Dxrhus7t1j9fo1Epbshonr9Yg/PefdH/4o/+B/+hV++w8+zyQL4ATjLJTtdwmLOXhQlCIqfRbq7ot6Q5p5/L3eU2aPKxwIdDNGcLB80+zSWos7BhFRm/rDxn88HVoz1zovM+uJzp22+VjvPc77yubU5/DOqy8ppUq9KSkv5ogtDmcE8y0ko9/WVSoid/Z/qDH/M/Dr9dvXgBeODn1P/dmfunIRVptRh0ecMO0mtmOmr1HWZIhSSJKxpuCYcN7Vt58V/UVALDllcp7IVim0OQqTS0CmsQbnG5wVco6YkjGlQE6QkhJUjMGIxxpBJJNLJKWJrOMRe0coQ90NjQYyFbkAkzPjsCNh+eIXX8KYhU6xWcufjqz8WVu2UvMdzhiSGJz1/Bs/8SK3Tnu213fYXF/y2rRhe+cOvmm52l0SXKCRgtlt+NgH38MLz7+L6VOfw4cO8kjOI8KTS4v9yauOIRt1HhfRqdx3P3/BzZsnpGlSeTXnVD5dzF7G3RiLM+ouOmML8407lxVwNBp9RFQ69oHUf/W9zCClBoZqfFsquHhE11egUu3mvXP0iwUYS7+MlCykqCB4SpoBibXEkvev+yTr2/V9eJeI3K7f/nvAv6xf/5/A/2qM+e9QoPFDwO99s+dLubDeJb1RDeSpELNRtyYAA5PoyDK20JBp2kwTI6OFaUzEpCc2pUyMIy4ooaXkiRzV3i03hjwWUvE6dCUFJxog0jCQc6R4S/CK/OqkW8JY3Slc0JQQdFdo2kBwjuAcvpY5WbSBZF3LMCSsDZSSv6VI/UO/jFFdAtfrABkAE8/fOuNjH3mB3W7FsJ34yh99npvn5+QUeeqFnsWzZ3S+pR2F8XLHb/3T3+dLX3oZaBCJGJMwju9acD0oM2jnwRjPe993k9OTVjUxrGAIGJNwWLIUjHVVmJV99hBCeGxWwdqqtMTMbJ1Pi5mRFmAODNrOnL/fzzsIVTrwUG4eC7c653De42yqJYghMU9PGqyHlCaKZFV7+hZcor5d34e/Yoz5yfr3fQP4z+sf9VljzK8An0Oz9P/im3UeQLsPq93IlCKNBZMy01RI6L1rgaEUYk5gE9Y7rd2TgBVihBhV+76kiKSowycCrbcEq5HS4rHFQlKGo6LOgqSRMu102tF1iCSdQJOMUQVWVbrJEZxoEGi0FAnGqg6AaKsoC/iu5YtfegPnOgoJjCDy/cQOHrv0+P4CmaYCZhMijYKLOXLejPziT3+EzglX24kxgSmFr33tVW4+fZMPnl1Q7MR2THzltQ3/7JN/yD//0td4tDG4cEaJI2ICmBa9tL7z92mMtqkN6nZeRPjAB5/DGWW5emcRPMXGfXfBiiC13FR3cH22x6jJVfdDZ0ArV8EcBH0eP34erKrvam6TmuqIYRTrOHZDn4NHjJHNZsNmNygjUwSqObO31VPSQ9t0b2l5/mnru+r7UI//JeCXnvgdoCnUZjcxTSMpWEyOpCnRe0sSgxHDmDKTzcg4YU2h8eAt2CwMY2Kc9INom0BjhUUDvfd0rcUaARKWhHcN3mnRoWlbwZHxViXkS47EKdI0gWXfsegdXTdSrjeMk+ISTQgslh1t43BqPsk0TQgWnCelzO/93heVvZinynL1ZFEhlsdv2sfOBI/dwObox8df7B9+/By6M1XheTBVnQeHvMVL8fi1Hg8gZv+bN9Fs918dP4c5PHxvt6xovXeOXNS6/cYy8B/82/8mP/G+cyRFFv0J3vXcv3Ob0xtnTCRe//pX6fuez7z0gF/9rc/yxVffADqsbyBtCRQQRxLzXfLjlsf+NehG84EX36WCO0aDm/MG8R5i3h+dRchJO1UG8xhjUaTqjR6VDMdlxP60HXc93uaGnbsV1oHEo7ZnfZCb25yV7m9q9jJvdNZC13c0bVvp0T90U5LCOCXAsYuFNEy0PuAkY4vfewQDUCJWPLkIQ44YEYY0kYtaZwXrCG3LorG0tmCLUVakc/RdR98HrDXEZInDQI6RMo2kOJARJAplsFgKrm0wtmBbS3juJjdvnBKnRIwTFCGEgvcFkZZpzEhc0/QnfPlrr/P5r7yCYs8C1qP1q/aYATCWXKLeyHvr+WM/ABWyreOfUBNSIzoINk95Hm5pnfYzFCKa8VAKrmRK5dqXkvW9yPy4Ol3HfPPXm1obsphaDpl6kxzeXal8i4N0nrNe5/aZQJT2DZEPPnuLv/av/xQfeNcp07TmC6/epVs8zUu3r/kXn/o0f/mnfozL+3f4+IsvcHc18ZufeZW7j64JtiGJo6QIGKZ9u/E7qR3mWYf5vSuoXERlVgoT77oVKNHggzot5ZLJhqodWsjzdlI1EI3YCj4ezo4z6tOwt6cvBeM17VcTmENZIFLxqGIwRv0rnXFY40iUvU+Jq1eHiBBLJmY9tg2esuh0ijNNVUzFYr3HtYGmb+ia9odvShJAsk59WSN4K3hvsQF847DWECYFe3zjaZzTVCkVxERkmvTiieCcEDwEB/2yo288bec5Pe1Zniz2LUEXJ4w4SpqIcSSOEwIkybTekbLBFMfJyZLuZIlpWtqmp2RhtV6zXa9IccCmSeXeS6GIZ5w8n/zdz+PsBK7TKbc0Mu/C8yXtTEvXLasoR8IYy3xdqZuaxxWpYJ2BSrCRAoL6C2AOpqYYzX4kWaw9RVICE0lMWOlqliJ4ycrsJKPdE5RDILYGgTlEpP1mao0ji0NMddkWlbq3hqo6FCjFYfyCtl/QLRY4Y1httpizd/Prf/CA87M12/GaL3z5s7iwJBdLjp5f+38/BwT+6MtfYhcHduIx9pRUdm/KcL4b63hHrroY4jDoxoMU2iaw202kVKXSjU4qeudI7gAqUksBkVy7UkqGmwPBNE37EesiooHBaHQRAWNUtEVJS4+/Q5kJUVDJSEb9I+rrWlEXa2ehbwPW66Ny1BkMkap0WSdRjdP/nnS9Y4KCM2CN0kata1j0Lacnnr5pwVraYWSIBeMD3hjNIjL64cQJiRFToO8aumAIvtC1nqeeucXp6ZKTsyVd1zAOO3bDDoZEigbndIos+EwqhRinPVvROqFdNpyen9Aslyz7U1JM9IuG3bJhs75mdXWJ844UE856fv8PPscrr7yOYYlU6fYbywVdZ1kNA9Y1WNtyefmIPKwAnYUAgXxUXmRXK2e9eXWfcMxU3Lyn9crR7xdgEoVrMBYXLigsCMtA1zXEcWR79UBFZY0Ke5YcmUbl+DdtSwZSHEBULl9lxwQrEYwHowSkJNqBDxc3aBZndIszjG8p1iIps3ntDaK0fO31h5TNJbQ9pB2mBPI4YEzBWo81Lcm1PJweKSGNguQrtVbP3zoZ6UmXqeVVEcE4h6SJdrHASKLkCMbh1cADZ1T121mnabtzhKrUHKeouhm54NyB9yKl7IPqjDOAwXgNDKaqPrvHqO7mSLb2wGKcP2WMTknGKOQ0UeKE5EgZdyQpxGT3fB/rggrK1gnNHz6RlaKDMq0XfNB69Py855lnb3K6XOKdY7Mbubpes1rviDEhWQVNnPM6I4FKrzcuEJzQdYGT8xMubt3iqVs3aduGpgnENGKvHuF8ZhozLhTaDqYo5N2IdXXE1BmatlWSSm0zqT9DoW0DRnpynpimhmG3I663WBdh84gX3/00xhmeOT3jYx96kb/685/g+educm+1VXu50PKHn/ksL796m8ViSeMtu93AMOwoUmhCS993YC25KNNytb7m4cNHbNZbcllSTKngqaa1MUYeXl5xb92zjQFMQJoT2tNbdCdLvfimiZP+ll7YJLwpbFePmKYrQnfGyY2nWF89oGTBkPfOR5ITnshUAAL0S5rlKV1/Qrc4Z3294sGdFZIeYU2GNGKna2Zjo8ZlcrzCmEIxATFKJc8pUQCXB5wJxJQUYLOt3pjfq7Wv6avKlxhc2yIlUeJOpyJdIMsBU6FqbVLrdpytmcKhnTgL/arIarUCqHiDAtsFqRLye8VyHkd13gxGWnNoX2Jt1RUtFcwVSonkNDHFyBgtxRq8QOMdxjc4p8Hrhy4ogOBtoQmWxkPbe27ePOXZp5/i9OQEY+AsJZanC16/fVeHknIiJZW2lhyRklkuA32rGgb9YsHJ2RmuCRgXwDZgAy4Y+sWpaho0A5kdUy4HZWfbIlYxi5TVhSdXGjQFrFU9/+Qc1nrEWtKQOGt73vvUOT//kz+GW57TnTVsXnqFi5Ml7/vgc4xp5NmLJdY6sggff//P0PU9uQp3cNQDnwkyxar3hQHilNhsNmy3WyRFVZWqcm4pJbqu5bMvTfxXv/T32TzsaNoO22ZsyOwePSRXDYDGOSaZyLtL8nANssW4wDjuuHf7dSgjOkMwZygCeIy7QdMtcf05JrRAVpuyu49Uhj9NNFbwppDyQPZaLMWSKRV8jKI7tIjXzpHxzDYlhQZoMFKQbDCmR2T6HlxrFU8R0TrNOkQKwTUMw4qS415XE6OZhBR5jI5snVMRX2cPHQfR1uIswQYzrjiLvM4K4SozqNob6mWqeI22GzTIlL3SU6kKzTMNWtDWeFMalCCjmUsbE9tJSXY0DaFpK9EpVBOaH7qgYGgaT9dA8MLJsuPixinLrsM7wxQj3nvOz8/YjgPjMOpEZRFKmRjHgRgji9NW0WJT9uavUy5sdpFUXIX9Msk4ivGUYhlSZhcTyRhsaLTes4acCrvNwK7fEEKDOEcynuAVdEsxkdJEjJFl23GrbbjoPAt23Dg9xTjh5Vdfwj37PFfrd1PCglJGiij3nTwxXq3AVJuyOm47z9UbDK5xevNUMNxg8a4l9EucD5ATUx5ZnhhSavl7v/IPufvwEW7xLuJ4RYtnd3mNSMT6BoNhVzLkCdhiZMIwwZ6L0SAkxRPIdSdrsH6B6Z+j1EGestmQd2uIW3AqWosXomQiCjCalHWiTBStN1VR2NpBQbTZu8PESlNOdQfPauyzF+/9VtafxHJ86/PojqzcBOM7xiljCEiO5OzVFCgog7ZQ9TLk0IK084189NLHbcVZos+5Ywk1qjqYBv4iBXtEaDpuiGgwOjAl987pCFnmTESviRACPjT4RogFsndYHwg+4K3bO6I/6XpHBAXVXERlo4zgg+LoQiYXSxKgCFmKMsyCJW0KJUNMiZiL6tAZqzsilpgt27HgdqCiMzUdDY7NrrAbCrsMyQTENoS2Q4zFxC2LvqvXc2EYRsJ2SyqW1hvEB4YiSE6Mwwpi4tQZfN6SsiHLGVd3r3lwueFdH/koH/zxjyIFpt2ASY5Uqj9FFoL1+BBAko7g7tm02hPPQ1YOBBBjJIvQdS24hpgEjyflHacm8t//8v/Hr//zz2P9AtleATCkyrOwVcewOl/gMiaP2n3AAw7lZ2UFr+eOAx3G3UDcKS6OlGEi5R0iE0YSOMEWV4NI0YBS266CPWoZGdWmAAUYa92cpBr11qsAqMHgu79MHWozSL2BM8b2iLVIgeALz5z2pCER/KKiPHq+xFqEzCzrbkX9ToO1ROP2BCjnVA8xNA5nK6GtTueWgmZ3YpBUwARwBjFpj9Xo5O7BsVwMVcT4cdEVktXsOKsHhreu4giWPIxIsXgTaENL2wSM/9ZG9N8RQUEHUkasbTEWYpzYbddct56uW2CcR4DtGFmvB8YMQy7s1jsAXGhw3mB9wIWOYizJ9awmw7RKREZOlx1dKZTtxDgNrDeJ7WRIBPBaFhgMtu0xwdeUV0jiWW8zflyxc4AxRANpHLB5YNE4bpyc8MxywcX5CSG0PLj/kM3qmpNFx/Wd+yxOT2itZ5dHxmnEVDbajBlYo4q7UmXhnFU+uylRZebGiWGc8N5h2p5xs6VPE5uuZRknfvt3vs7/8o//b73I866i29r2mgPu3MY0kh5jHOiapzZz/c/qrikOIUJZEUvai86AToKShfwYkWhua/6g6Jt/0use+BjziLSxYFpPThNPn8N//O/+BAu/Jhdt89H4vYjJPAwXx7Fauqlno1q7OWwVNnHuQHc+4A1vOh9S1bmKyv9LMcqUPDqPM/nJGYtxB7bj/LssBTOrR6dCygLGUcjEnDFe1ZdCsFgPTdv+8AUF7y2+yYxprTfHBNvdhqbv1JnHNcRcWG8GNuPIbkzoaVSvvNAplTgZx1YcmQaJDSIWl4SHw8jF6Fi0BWQCiay3iTgZBI84q36BourLBf2Ag3NEMtMQ8TIiZSKVpIBPHLh50vDj738f7zq/IG62TCmzWl+yWm0Q4PXbt3EnPYuLc2LKilnUoRnvfU0Fi6bLOe97CCUmxhiR7cR6tQIRur4jBFd360QJETMWHrx8h//hV/4pq8HgQyGnNF/2zDe7AWYhB92xpXIfHifwaHocQZUsUOHSEcyIKbFmMmrdNr/Xx+3IDqj5O2vNRKG5Heh0940FmhZvCx96xmKDCqvMsutzCBGZhYO1RtDOQtnrKYByxax1OOtV6JWZB6KBcs9jMOzLBS0fqjRf1U6YP6/Z08Q6d6TkdCAnYcCIWhvElBAiU0w1wxaGcaCQaSWQk/zwYQp93/GBD71XbbZ8Q9u2dN2Cpl/gfaDgWF+tuby65Hq1pYgGktBY2mBY9J6UoD+7wIYFkzRsomM3iPIP8o771zsWnSWQ6AJYpj35RIyliCVnQ84WbxqCbVXFpkRyhFCJRhhNtRtvuNk1LItw/5VXMSI82mxJMbPbbPHLjve98ALPvefd2ODZxW1VdLKYXMhlUp2/SipKk1JpLYZxN7BZr5nWW4ZhIDhP3/eaTmLoQsvDZuDCnfFPfvuP+dTLj7CuQdIEzKKfR+IcopZiUr2Q9OI7ZjbKgShFweDR27/UFmEGyXvY8U0J/9FPftDrbZiBHL9Paqqu7cgQehLC9aOJL750j4//ay+Q8doUFuURFCkUyXtPU1OVk3LOiFHbujkrgINSc865Koy/mWuhDk76lQZR7VIYHcBCJyGtOfhRPq6/gZbSOeljkm4EIkrFLxX7EBFSHBmdxYf+h4/R2HUNH/vJjxFjUp16F7DG6lRiUtUlYxxXV2sMWxrvMV6wEmiC5XQZQFrOb5zim1OG7LjaweVmZD0kxjiySxMkQx8EX4TGac/XWMuUMiXDGDOFQPANKTnlv4vFlYA1LWDwZsRIZBkcTYk8uP8GjWl4dHnF3ctHbNYbnr5xk5Mb55yfnNA2LTFGnPMkV8hpIg2jchJqawuj3Y+SMnmKbK5XbNZrhmGHKUJynt2wUy9BZ1Q/0gY2suL/+szLxJLobWEQW0uDuXNQFYUkKQlq3m04huTmLEHLBsTXWno6VAMcdAL1u1mpSDsTx8/zg11vDQr1VgVkfw500MhjvcC0Zhcdd6cGaXpccdq+NaqchFStwxAoOe7LA33yWbGZ/Ri1golHrcmKEVg7C7AcyoG9zFoln+0HpkT2WVkuh+Nns1kphTTGKjwspBhJMTFMic0wkI2j6TqaJuC9Z0oG/8NGXmq7ng//6I+qs07OGFGudkyJcZwYx4mbN044O2l45RXP5dWKHAvLpqOxlmVn6ZqGs2XBhEjCcHPpiBctIg0pN+y2A+M4YI2SVcdprCKXHm8MQ0zYZFTKfYykrN6BrRf6pnDuJsYy0fjMeSu88NwtpusHPLrzkNJOTGPgxs0LXnj/cwRuUKYNX/jcF3j5Gy9xcn5K1za4uOPh5QrjgnY6KoFlsVhiDAzjwHa1YRgiOWViKkw5YW0h1X60FIcrHk52/PKv/RF/9NI11mXGMk8nKKp+WPLY/bq/zw+d8aNjj3e1N9/k9m1+Y97muHfWMlSZMmsxJRNwFNcTLi6ID14i5zU/8v6P8gt/5cNcP9zgl2DDLK1WsAaoZKWJiThFYopkUQHXJIZgXKUpm/0UrbFgg9cbvGiCgpGDzsKMG6E+o8WwtygE7djMcmzwuK9qjhGbJ9JuRxomYoqstxObXeLeoyuu11uw1WWqZHzo6Rc3nvicvSNEdz1bAAAgAElEQVSCgjFq9y0eXO00iAiNc4iY2nrUEdWuWxDWGwIOXEPrDIs20LaeLghiqsy7DSQDWRJDHhnTBtKIDlEXvGTyVEjWgDil+VpP8J4shlh0VmERLF3jWPqOPrQ0bHn2zGOnHQ2F++PAJ//lfV5YnPFX/9ItTTfNjuvVitY7SkpcPXjAvZSYklXjGMlYdjobYWE3RgwwTdpqzbGw2WzYycTZyRnDMJKS0IaekjPLpeP1tfCNOyvdtcViaYDvRV//h3spDQscExnLZDqWJ08xrFfkYoETfvoTH8S7jn4hiNeySaTsx6DV73Ou6ecRZuUbGKMlG+ZAcTbW4r3yWZT85vYZhrYXD3Luc1wtaAajiZnsfzdnHjJzFpxqOZRcSHFiHLdMMVFSwhmhCwZ7cQJoKz9GHZ3+VjyM3xFBQUTNLKgRtIjW2c56vJ/ddjX6Og/egPWO1gf6LrDsPX3X0HcdoH4MQiGlwjANeB9JzYQpqdaIpTpDF1xo6JoG6xqMacBAkQB4rHU0wdEES984QlwTRlhaTfVfu3PF//E7X+RLrz3iZ//GL6IQ3oJ4/YD7dx/xwvPPsN1sK4nEYSVissJIU86Mw4ixlrTZEOOI947LR1f6czzNSUPOGe8s47BlPU6E4GkW5/zxp1/lcoiKThuhpHf2jv2DXMaAlARmiT1/FgkNcp0Az0m35CMfOSWOI955sDPgpxwAnVcosB9kM/sZBl1z+XUoCax9XHtxJjy5GkycdwcAmApSoiSkUrELOS71arCZhYQs+vyq5aEguQ+BYhwXNy6ISbj38IrRWvxJx1h8JYc92XpnBIVSmIZBVW6pmYEIYk3VT8xq1RXVDqsJHmcty0Vg2bUsek/fdjSh1RMtmkrnmAihoes8besZY2YqSdO/pPVgaAJt2+F9g3GhAjJOU3xn8ShPvWla7Hpi2A7EseH2wy2/9s8+w2du7/j3f+4v8hc+eMJmEiQGNvdXxJTZ7UY22y02NATf0NiB7abgmoZYDLsx4XzDbrMDo4NR69WK5eIEazxxW7C9I8eJnDI2tCSE2w/WfP6rb0AFDm22FFPZbP9qvWmJpuelwbWnnF2csXlwT7s8EvjoB5/h1mli2g6ENmBYaIlZMYAspWonKJkreDUTDqHR9N+YisFU2XWLXjd+HnYyh45C9Xo09oANGGa6tJbMbn+8lg8xaavyMUm4ymJ0zmOMx2LouqBgMyB1TuZqvUWsx7sF4/hdnJL8E3wf/iHwkXrIBXApIj9ZVZ8/D3yx/u5fiMjf+mavEWPk4d038E0L1WnaBU/C7WmfOiNuaULA37jAO8tJ39M0gc47+l6BQCM6OzEPqYQSETEskpByZpgmhnFLyR4RCE0gtB1t0xEabUtaY9Rxy1qMVd28ru1Ybe6wWV1yJR3/6Df/gM/e3vD0xdP8zIdfYDdNZLFMD29zmTJSYDcmHlytGcbEaj1A6Hj2uVuI7JimAWsMcYogQts0xGmHsYaz0zN22x3jOPHqq6/Tth23H17z1dfu0SxPmZLwyv212pAVEGkodjoiAv2rNS9jBMoEzdM0J09jp0fE9R2sPwW34C99/BZPLQPr1Y6Stxha1d+QQsraNlT+UOUjBEfTaOY3zxWUkhBxtaRQivQsy2ad0tRLmTsI8ygstT2KYmhSlaIx+zKkMM9NVDyB6mAuql6dCsQkqlJOANOw6Dqs8xjbYnzHLmZWyfCtTJJ8W74PIvIfHk66+TvA1dHxXxWRn/wW3gNxmrj92mv0yyVN09D2C9q+w/luj2NZowGh73pM3xOc52TR0YaAd1q7CRmKtpK8dyAQqk9Gm1VeLQxb3C4gxVOKliFN09B1HW3X463HIFhTMJWshDEEa1iTyMXwG5/8FF947RLMCTdPE31jGXKHGS5huMdL11tOpoabtwzX6w2v3F7xxqMVL10KwX+Fpy4azpctjYNF2+r4qxHOThYsFj2vP1zxxu07rLdrYirEErh3OfDS3SsmHintlhNw+jcIOmT0gyUOfT/X2/2NR/Cn2TdNmMlYoX2aftmzfuPLmDKQpaVpz3nfeztOmsDkYcyTlgpUkd55GElKBQcduUqm642rjNFjY5d5bmVuT9p6/ei7Nge84E1wrTWzj0Q9Lh+Jtz5GPFLBWAHGKbEZJrCeUAI+B9rOseh7msUC23bIasPV9bgHMJ9kfUe+D0b/+r8B/FtP/Ipvs+I0ce/2bS5u3uTk/OxwMjuDMV4/FCzBdyyWhlQSjbeEtqNf9PimRdDWkamp2jyrHmpfuWCIKSsdNHTkrHx2Y1Suu+t7ur6rEd5rdlIFL73zxHHN9vKKL33jEZ96KYK7gPwQ37yH/iyQpw0PLq+J0fCNL9/nve96D5BxQfjCawOvjoUpTjA53thugBWYlq6LELc4k7g4WdL3Cx6tNjxcrXCuBazalWGApX4mc8swz/oMW8h/HoLBn7bmLKmAsRipkunWgznn5tlzPHrwu0yjqMZiGrl45pTzk4G0XUGdRg0kQsgUp/wLJ4ZYMqkIRuq4NahGIyApEartfKnGPsGrCbJySgs5F1rbVBEcg0lFreScmSOCOpjt+0JaOlM0oByXIWnGHJJht8tsJsF4OPFeBV9cwPUNTfAspLAZIyZP2PzkIPR3iin8HHBHRL589LMXjTGfBq6B/0ZEPvnNnqTkzOWDh7UFo73yIo7WGHyogIszh3rN+sqCDDRtQ9N2Wktllf9CUFXmSkENTaOmnLnokMgwMgwJ7zPOWZqmpe97mrbFVKSYUpT0U+d/L1+/w6N7E5/8468yCuin2fJjH3gXTtQYN8aWP/jiXf7oGys+/uNLcoScG7Y5MqWMtU1V53X7fvS42yHGYaSwfbRCHl0DAetOdFRbSh3vFf5k0ZE/bwHh7Xa9A2tQSsLgsLYh58TJzQumfIdpc40xPcVERBqeuZFZ9CcMcVuZrCPjOCFhwLTNPs4a67Fx0kGkUiAfMoOjaRVmNecQwp7kVAr4CizqpsRRRgFSfSbn4SqpNYWZ40XVWjzOGErKjOPIdjtw/+GKJJYbF5ZbF76qhms3xGOU55JHxnHzxGf3Ow0K/xHw94++vw28V0QeGGM+AfzvxpgfE5HrNz/w2Azm4nTJ+977LN3ihG7R0ywCoXV45wje7U+S0nAVQPTOauoG+wg9Temxk9c0hiYEDQ6Vr+5F8ElUrUYsLqh8m2sCbrajq6Iae4YahavLR/zO736e25dCCQ12Kiy6JR978XmVdIsTq23k01+/y1oabtzo2V1veemNFQ93O3CLuruoKSk1aJVSMDiokmzWaItRg9tsH14ev+//3AOK8wl4PBiKpL2SsvqFJnxzhutPWD34EsYExV2kxZL52R93LIMwbDZMU0tKTtWKxkRoFMMqdTLSWshZmZ/O6nCT9552niswh/ey10moFnNmFjkxyjYvtorCWYNxahVgj4ae5ueaadV7Mde64pSYpsIQhevNyGbICC3Lk55SCikmTBbSVIjjxLhZs1uvnvjsfttBwRjjgb8OfOLwocgIjPXrTxljvgp8GHWRemwdm8F85IMvyM/87Ccw1pGoHpHOUqSZjyWmTAz1JkpKD7bWYMnkOFCyYRh0QConbQ6KqDaelAQkxBhSVLfpKSoBRTCEUCpqW6pZR5XqQsdmpcCHfvTHeerDX2L6wtchBYpJ3Fh03GwtznqM3XL70SW312tc29F5uDNMfO7rd0lO8Q1VSzoecJlVfzOqm1gn4Zi59zNzrnLszZ/7aFCXedO/89Jgaq3Tm8l2LM+eUQ3OYYd1LdgFJUV+6mPv5t/5uefZXF2Sc2AYPJvdgnAakGIJRlW5JCtgPVOZLWroogK+nimEfWdiXkVEb0yOAgRoyVC/PsYbZkn3tyzRjsWMQ+ynNI0l5cxmt2O92bLaRkJoeGY8ZZoi3sAkwmY7srpes72+Ztptn/jsfieZwi8AXxCRV+cfGGOeBh6KSDbGfAD1ffjaN30TTcMz734eqJ6MonUY4vfDIKVkYrDVjdoRcySVrC2jGMlTYnO1RgRiihQRTlIi1xMrsHeY3g4jm20lnSyXOo6MUlV9/RCUK6GlTZomUmr5xf/sr5PaE/7R//abFCO856memyeWe6vEepf58it3mLLw7LLj6Ytzvv7qJQ+ngoiOQB9EO+e+9lwOZHzVcyxVBs0ZnUXUg9n3xnUI6UmDw59V4PHQZTFQd9aZ+BPV7ck0uMUNinds7n9VmYMI+I6FPeEXfv5FmCIxn3G5Fe7e37BJPWctXJx0iFEXMGshx4pV1V3b29nrQzNQ1VpQvEDNiOcx8cfdpVVJyap4b9XfNAjiClL0eOrrzLRmMwu9zJmCBaoyiLXCctnR9UtunJ/TdR2IEMeRaYpcrrZcr9YM25GSnlwW/9vyfRCRv4u6S//9Nx3+88B/a4xR3TL4WyLy8Ju9hrOe09Mb+mECuZq4So5q3CTqmzAhVZ8ukaqWXhZVR0pTYthtSDExplhZkpZYRK3oRXvBMRfW2x27MSsRqKuAlNMUz2IQUycAi/aoYyqsrkZeL3f42Z/+OP/4V/8p2zLy4nMX5DwxxsQr96556fYKOIUx03nHGw8fMeD1+YrUqcM3TxXqx5BL0iElo5JbqeTHWMQiM3B1/Li3/bz2k3nOeR3R3Q/rHIHf+qyPPdeb09R35pr3WqcovRJTanZX5zcw2GaBCQ3bYQV5hTUNYhzFwFM3znnh2cDVpeH+yvBw7Xn9UlhNkRdvWC58i3F1NNo4ihdyPjg0+eBU2MTrMcczDCnN7kxmjwk456rgK1WGvf4pImhFXHU5j4anTP27qKQozYCqO1TNhK01tMGpmlNKpCmyXa1J08jV6pr7l2seXl6x3Yxvuu7+9PXt+j4gIv/p2/zsV4FffeJXP1oWrdNE9CSJgxFVL84xV9qp6txhIoaIxAFJapW13anNl3oNJHzTUcSQpwkTo7oDG88uCvcfXrMZMzcvLjg9Bak6/daoVfzMTy9SyBg2qbCZMvFy4vYrV2yd7tgffuYmD68zl2+8wR9/9Q3ujgbDwNnJOZTEGw9WpKxMOmHc35xvfz7hcBHUM/Km+/Ob364HIQ6RvO+i+H1QFEpRs1HnGmYNwXfuOp6tUCaopbpN2xZsUDZn3CBlxGIoJoNbEsIZLg4Mw0PENEixNMkw2shTt86wuXD3qnC1Eu5eWe6sW6aS8b6vugjsHZuFfCR4osDhcXieg4VB6cdFdOef6czzJ944j63PezxYNYuzzu1QhZyqGY2oL+TBql6qc5XBmUBKkGJmFbeku8JuM5LjxG63ZsyRJhSeOmsZ05N/zu8IRiOg6kr7iAtJDBIzEjM5RqQU9YmMykhMMRJjZBwT41AYdwNpijjnOO0bcA0UcI0jxsQwjMQ0crUZuHfvEbbtKOV0r8WnzMmIa92+D51iUmWnKbKetqx3O67WO6y1PH9xk6dvXTBurnjl7oYvv3anYiCGmyc9xhteef0hUH3OzLHK0Hd/zReY9xbvG87Pz3njjdf2CPxMnBHhqMVV0+59dlB3rHfoMkYAB67HuqAlYRpBVD5OTMC4E7C9ujiVDSXttLAwnmwmyB1PP7NgiIXrybAVyyCWaMAENS0OwWOdYgmPcQ6sBVs7RxxIRcfOTTNWsJ9qLMpMzKaQRQheb7k5GB8/dpZc0zFtnZOI8bDDzxkgziBO30sswnbULtXlMPKG3OO0bzjtA6ddoLs4ARGG8fvXkvyurFIyu+0KREGanBNx0imwGFV9KOWiE2oxI0Yts3a7HcMQGYbENGnNZK3FuwbXdOAcxai60ThG1puBq9WO3XbE44hxIqVq/4WqL6WSdDR1SgzjyG6I7LYTU5qwOG499yw3zxe8+NwCZzKb1cjLDyYeTQYXTsnxEWeVX3E1FKw5oUhEJALt9+wcipSaGRiGYaSUa1WyMhbn/B4My1lB1BjffJGoaOw7v3wQcqk7LVll9KUCy1isaTEESpoQ2aLOYHodGBMhTzz7/AndaU+PI68zYUyEcaRIrqxEDY0zJjBjP9Zq20Bv5HkqVY528SqgYpVzYMoBC3izbduB7GT23x87TdWjDsdxCBzOaoszG0Oxnl0cGIaRLELvBUuhtYWz3nHzpFP37PLknMZ3RFCIMXL/9hv7izLGiXEcGYahjqpmphTZbQdyLvjQE9PENE1M40SKKjhxsliAU5PZYpIa1NqsmEPKbLc7xjHWdLowjpHVek3woPLbWRHnWhtOw0ic1Equ8Zbnbl5gwpK/+LEf4Wz9kNVmy72HK75yZ81UHM7pxfPcrQseXU/sxIIVVM/AfY9bibOPoWIX4zgeGY282RHZME2PXyRvZc69M9bjOMdMHBAsSdNtowCxwVHmY3OksEVkYu9rZeahJuHsRkd/8TSnJiMMLIeRs2KQNO25INYaBZpnyvF8w+5BaLWM16DLgdZcd/sZB6CUoyzDUHJWKT4OWcIcGGYhF1s5DhroZ0GWgyqTMVaDe1HVLinKd9mNA+60J/lE1y05P1lytuzBalnzpOsdERS224FPffqL+AruzA470zgyjFGzhJiYpngQXykJa8HXD6RvO6y3WO9QSzYh5YjYUq25U+3vZopYYolaUkyx6vXX4+JMcy1ISXjvWJiGNhlOG8fUOH7uZ36M27/3KVabHa/cf8jddVbOerrG4njhmad5cO8KsZ5SBkA7Kd/rNWMJYBV7AUoxpKS4r2r/AcyGpm/dvd4aGH7wHYyDjFrVKipjdcqSmi3o/W6MYEpGZETYVsKXWvZhIjlbmm7JctkTpSPZQb0RWqEdBVzGWlVCEjMDe6aChTVA7OeSDhmAMRbvAyE4Ffwtqo8wC61Izir5pw8Ajks4eUuGMJch+nUNHkbxJkSJUhZIw8RuvWJYrbAx0Xuhb2C56Lhx45zTM/X7GCN8C82Hd0ZQ2GwHPvWZL6gZZu0xl6L6deOgKX4qSl/1PpDzhLPQtY6mdSw6Q9OAD0EZYtWoI+fMOE7sdgPr9U6nFtcDWQy+bzEI3quAxqz2Sx2VNfXDUHq1xwZPkMjZxYLp+ad4w3teu7/hc6/cZyodjfdI2mFd4M7ljtWDRzADo3hEHN+ZD+I3WzMHX01rrA0VXEzMN/ZB7efAxHvr42dp9YPI6ZyevyWI8P3mUVXRkTIcXtfoNKOI0YysKMHImIIQMFLnEE0mE7lx44x+sWA3GIYIE55cJnZJu1hKhhNK3iO++sp1l5ZSVbJyoexl+cF5JTNVWewakIByhC2I7MlxcBBonTPTg6LTzGo0+7dg6uSvMeo12fqgVOqSWTQOsZYhbmmsY9EpXX+zG0iTsNqMXK2+f4zG78oqRVitI+y0jpuGRBsC1hZyjkw7lSNvugacIU+Jrm3wrqXxQW3QGg9NV1V2PYiQs8pdj2MmFfBNy2KprcebN27yzDNPc+vmBYtFR2g83quLdClCykkz/yKQMyZYigu4DO954QV++cEln/38y1xue5CRKVmM6UkZ/u5vfIYuOBU+xleIunyP7yBTW7oKxh26CsemtXrc26+Dz4LiHwUI4BxGPCrMPqsUo+Ce4XsKnh4yGl3aVjsOrLYavFqsCQgjhQQSQJZgEmJHkoDNDbCCMjAOO+7Tsd4mpmSI48T1rrBLnt2QkGKxoqpIxeR9lgLqnWmkqm9XkxgtGwCTscYhBfU2FTnILtRAgjsCFo1BdBRTD0lZx7Ht3J6swc4oX2ZmSHoLxqu9n0sTLk+M04jF8eDeJRjh9LQnDhPB90wxst58f8hL37UlImy3I6vdFVNSp53GB1qnEdSKKA5AVlS4ZJqgO54AIbScLM84P79R5x20H72YlsRYWC6XFCAXYZr05Da+4eRUU8m+bwjB1r1x3nnY143WaI3nveN6vebd736BZ9/zHj75e5/Ch6cpeb5oKj/AGB2NtmG/O8+y3++c9eadX3fC1kQuzjpOu4br1YoH2xWFtqoCVQMVlDKupcr3fx2XObOaEYByhvTz07+ofmfUe9P6Jffu3eVrL9/nve/pWO0iYzSs1hMPrncMU2Qc/b4FuO8mWKsEor2qssrohSYon4RZLs3uy4HZQm5+j3vq8tH1MK8yM1vNQVLPze3QalC7xxMwVSHMceOsZ3tjwTYI211mPWmJcfXoktc6TzANcdywmiKb3fDE5/cdERQU+CpstiMpg3UNRUByJk+ZpnEE57HG0fhAaE85Xbac9A3BG4J3NKGha3tscJgQcM6Sq9BJ0wRmBZ2UsjIXvafrGtoGvM1YDizGFBOSVQ1KRGtNEcM0TbjGMKbIMy+8APiqlHNMu60Xg3FaBoq6KFSs/Ad3it+y5vesbpQGofHwrtOWp3rLWZcJN2+yKc9ydz1yuc6sdwPDFGcoDvmB6zeUep3MaXg1uzGlljb2qFSyWKfsw9uvrfnIR5dsZWKaIldD5v5qIGXIKRJjImflc5hK+mIfhFSGzVp1ZorVWfrARzoAtko9qY+bf18EsXJUGijFuVSCSill7yc5iw0dVJcEyUWFV0qmC3DSGhpxLJoOt0lIMay3A/fuPsK7jtV6ZL0bmMqTX3vviKBgajtsZt2VkomTyqCD4JsenKVpPV3bEBrPsm85P20JHk76lkXjCN7i2wZCVVByQgiBFCekpOo5qYq63ju6zuGDGs3YmtZNSUhRT/xUCtY4Zbd5RwiecdgyjAM/8qEX6c+eYnc9aoTf57mzZTg1yzCVtnocPH7wS5tmrmIoBkuhMZaOiDdC41uQTI4FJ6JCovWRUIOlEQ758fdviRzzKaqf6Fuu+UodlCqogSHHCQi88o1H9AuPXe/IJZJKYhgjMZdq9DsQY0PTtIiUPdVeOOoY1Gt2zijmtzO/F2Ps22IuB1xH8YFjlex9e7KWHVKDQM6KNxRjqpGQo2sDwRnysGV9daVi/MliUsH7VgemmEgF2hBorefRE57fd0RQEFF/BlNKnT3INUW1LE46Fsuevmvpg8dbi/cG74S2gWXfsOgsjS0EJzSNwzQBZzymGBKJ3Fi1q8+CKQbvwNpCCBnjdFAqlkgcE1NK7HYjSRyu6TG+xTYB3zRQMqdnJ+Q08LEf+1Geeeqcl1evYMyCsk+la4Con7UgYGcr8u+dtfq3umYoUZcABW89U7Zc7QybbLjebXmwGhiLIavMLFV5poKxMxj5A/objlJyXRaYagYTtAzEYEyDoVAkYUzL1b0tgYFb55bdFq5bvaaGcSTn5aHck1mMtX5+lbMwE4zmr2ch18P70n+PFZhnrUZjDyCjyu/PACSHdmbdSErOkHWA7/BYs/ef7Lyv2IYKDccxIsXi0LmMIuAaS8oeawNPut4ZQQFhNwykpPboBmiD48atW9x86ganpz1t2+BB2Y050beGxgneqklLyQOGhHOO4APOBgwWKyiSbAVJEZMj1grOW4zLGANZDGWaGIeB1WrNmCAsb9B0jfoIquQdJ4sTbJkoOXO27PnLP/sJXvr6y8zgl8Hsd9O5PTiniPvuxjtgmaP/76OXsSQRHg5Kq93GFREDdoGqC82ZzuyKVN52J/x+rJnPchgoO+6mHDIIHeQNNb3XoGw95JSwUrh52vPw4UjfOFovTK7QNKrCDHrjlzpjkJLyAkq9SUvJ+5aj974yGf//9t4txrL0uu/7re+y97lU9WWmOcPhRSRl0ZKJILAIRzEggYBjxLGYB4oCnMgPsWzYCBzYQAwkQJjoxY9OABtwEsOBHRmQEyNKAMu2gliwFTtCrBhSbDIUL6JIUSZpcoYzw+nuqq5z2Xt/l5WH9e1T1SOOWEOO2dXGWUChqk9VV31nX9Ze31r/izsk2qtYhVorHusZ2CjStYTStD9af3gmVc3bCBMZvmIGM48nY6DWbOAqAuoWdl+giGumxHMHQsyiMMSnLCkATMns2BEhBMftO2tu315w+2TBetWzXPWUWkij0oljGStBBso+U+oC9VDTZNDoHvACDqIlWyrmgVjZkdKeoie4KqScGAdDSpaspO0jiutYh2cJzprFsfMQAlLzAfxTdc+P/vs/zM/93C8yjQPeLZhZcEo+kLvMWl4eI6T89ifcdzfsGpzrXbuxijoupqvraVVNzVdufG3jSZhp5U8ifhuYyV5tH11LViOoR2UJ7hynStGOqoFJ9qTcc+fOgnWALvTc7oWleqKzrZSBkjy12CTGqc1jatEGjlNSSQdtD6fuwJlATMvBqO4m2zYng6sf5jIF4hTJejCUMWQviATUF7z6Szi0OFQ9BRiSsh2E3eh4tBPG2pkQjHdUDAaNePqu5/T05NrH90l3ig7R94H1qme17Lm1WnLn9prT5YJFy9zeBxb9gpPTUxaLwGoRzCw1D2jeMGzvU6ctZbpApxFpxqBwpfMLVBVq0y4ww9SKc8Z1D044Pb3LyfoWXVPrdU2n36NozTixsdQ47PjAD3w/P/bRD6O6aYw5T6kJPZiFyqHEvNptvqnowX99QpkrGkERNT6LjQsdIoGsE6GrLFZC7DKLheP01oJ+2RO7eLgJnfgGFXr8nM1KS/bn5JBkbWLQmoQzNuGKpkItV3oKh+3DjMC4nKjMWxJ7Tl5yL0T10Azd7Ebun+95+f6OzVDYDhO7VJmKiboOKbGfBopm8E8ZohFgfXpC7DwBZdF7TtdLThaR4JTghD5Gm9fWzDJ6XBnJaUMZNngi3p2Qdhd0cQHdGun71li3bi7eUdXj1Jh1Pq7sD2tCKATnKAF0PxLVmf5BTogLZBJSC12MpGEw96qUOH/0gD/9p/8IF4++wd//P34B5+7hfWwM2NeP/K4W29/sSXeMtypmE9zZddtpo1O7gMrKSHMnC0pJhAD9IhA9pDZ2nsfLh/L/AG1+vD8Qgj/wELRekpxEhFq0VYczI5J2/dbHjLhm6LRvyMgDJNqKDAQ5wKdnW/tSMlMyV7BRIvvqicslMYS2XckMyfRGnAPVCfcmgHM3IymI0PcrYh9wmnDeTKf6aMMAACAASURBVE2dzOMmiCGgmqg5EUMhjXsgUYqhFFEYdzu6fkfsN/i+Q3NAmzGqNS57XFAcPeLWhk7TkZwLWiClyjTuqE7xuaCaUWcIN1c9mgulJBb9gtCbbp6ELR/7qf+E97zvPfz0X/9ZprHg/MqqGL1EEh4ujMOkBeYL71g0vFXRSuz2L6WAKk46qiaKKuIDy1XHs8+sGQcD/PQh0PfRHgTV+gWK4p3Dobg6TxmszzpvIZ24JvE+9xnMEkCcMI4wjhOl9R9qLWYuLJeyazJfGwi+9SXgEvNyFYMBl6jKGCLiAkU8Lna4RU8V6L1AF0gJyBNdCCwXPbdPVpyuV9c+itcRWXk3Ju/+fDvef01V/7KIPAP8r8B7gS8D/4GqPmwKz38Z+DCwA/64qn7id/4jDvVdo6U6nLPx0JQSlIqMHf1+h5QBpwl1CUclBEf2jpQKQ7ZGWC2Fcdij/oLS6G7Rx0aacUAPTknZCC+lOqrOwJyK971h+4qS8khmoorgvGHb+76jipGuQr8kTyMiI3/iT/2H/J4PvJ///r/7H/nC577IrLxsDsPzk8dwDIYYnBGE8/fnY3GlBXjMFt9mKCZxFxBv8L9aNjbuThPveuG9LPrCODRzWMncub1EV91jfQDUW1F/wCg0Q5eGiTiocx0EUKwR6ZzVKtOYzQlaC0ULXgNOLxWZD+5Rs+Dsla3GPP704s29esYriJCnTKlK0QpOuXVrSaoJR6FfLNGlVdhaq0H0q6LlLVReAjLwn6nqJ0TkFPi4iPwi8MeBf6Sqf0FEPgZ8DPgvgB/FZNjeD/zbwF9tn3+HEFIRdFIWnRijEFOZQTMljey3iqt7lp3N1b33KJ7QLQi9R/zC/BByJu+2jEWpDWMQQmwdYoOjihPUFWtcpgzZbNdSKgdV3ZQnxlJJVVEXTGDT+9Zzd7iup6L07hZZRx4+fJUP/lu/h7/yP/xFfumXfplf+N9/mU/92qfJqRGiWhK4c/cuzz/3HNM0stvuefjwoSW/Q+OPVvq2kccxvs2Y9/Gms4Az45ZSCt/zrrchmkl5ous8J6uO0HeIKmuficHjBJu6NAMIuxbhSov2MJo0tGvTQyhKqYqP7tDEdWKKXuYuLuRaDNIcwiWwDrgc8MrhLTh1FC22jibhllKiqlUfzsN63TGmihPHatWDOnRKbDc7hmmL0w55E/qe11Fe+jqm0oyqXojI54B3Ah/BZNoAfgb4JSwpfAT4m2rp9VdE5I6IvNB+zxuEkVPKMFGK4PpCWASkViDhk1A1E0IlRkcXFkZIiT0x9jjpycUxpoofE5KFPBSqMx38EAKhizgX8K1pWb022nWiFqUk41l4b9l6GhKpwlQg9Cv6RWfNKhdxPtotGz2lGtegdx1pSnQdfPTH/x3+6E98mF/8B/8Pr7z8gM3FjhAj69PI97zrHfzA938v3/jGq7z6tVf43Ge/wJe/9FVevv+Is7MNJSX2w8Q+wdnZ9RV4jwHzBMJurYAhHh8hLHBuAToCgbe/c023XNH3JnzztruO/W5gyiO3+o7oAl7aTd34Dc5HaDofpRSbQOR54nHZS4hdIOV0GJtKFQIRr960YNrDRav1Ehzmig0N6CYwj7hVQYu21ljrPWD+JrUWwy9EIxD2PiJtSlELSAhkgTElhjywm8ZrH8U31VMQkfcCPwj8KvD8lRv9ZWx7AZYwvnrlv32tvfaGSaEq7MbKOE3krLgCS+/oxNP3ztSYSzGLN8RKIa04F0ANnBJ8bPBoQdPEVAqlVlznKT6SUgc+mhmMjyiF/TDiXSCXzH6YWg1g9uOqTd3GR1ONbt6CDrMb985B0XaClKbySs7K+YMzHuSJD33oh8jJ9CG896hUNo/O+fpLX2EaR8RVXnjHPUItdF3HygMlE8KClx884uzsEcdm5HcYVfBBGxlJgA0nbaq17iOhCqU3EpVPSogeHzvEe5PwqyakCpduTaXMH4WcMiGaGYwlD9Ni8M1QVjHehcGUoU4TPpgXpXNi3pGtmTlvJ+aYKROH7ctMt8ZZ0xS4eLShVKXrI7VM5ltRhXGcGMeB3W6HE9M1vW5cOymIyAmmv/jnVPXR60ZsKm+mPrHfd/B9iN2S7ZDZ7RIpFmKBlRPWMbDqPG7WUKwLak4ksflxSVDU44Pgu4iKJ5VKzYmcR0qZcFmRbonIErSnakeumZxK0/QXcEJYRBvBV+NGmCdgQF1ohrbWIMolUfKlmYuIqQfPe89abP8nVL76L790CdtO9jdznkijaUW89sp9fuuLX+L+y68xJGW/v4BpYrEsXJw/5LdPMI7x5kPROhhwSKEw8eDBQ/LUACxa6YJDu2DXEY5cC5KsPT2f16twZNB2LbQHT71UrKrFJh6m4DT3CuoBw+LE4XXeHM7ajsYOfv3YegY2HSYSl3/eHoY4pskqy6X2JjrcvFNTLsxMzFKyNR+vGddKCiISsYTwt1T159rLr8zbAhF5AXi1vf4i8O4r//1d7bXHQq/4PixXdzRNmXHKUCt7B/susduN9CHgYjYAkSppUvJojUHTH3QMZSLSIfsdNWc0j/g6UsuEixyakoqQS6aoo2DOUBWrOPrYkVLGlYD3jWcnjpRNWXrhO/I0MrR9Zoyzku/8fg7vy5SgUpOlz+lAsR3GqTVCE8PFyMP752zOtwxJGXJhGBKaKwOJB5vrl3vH+J1CQEe8W5l0Gx1f+PzXeLT5QYZRqdXhY4evYuV3hZxHcikm+gOtMajtYdGe1rXpL2gl50TO0YhSXpqmgzSMyxXdRS9EteQ0c22MAPW4kOv8+qyrOScFG33aa8MwMg5TG30a/iF2ERVpKkuFvo/E4A3B6QTuX++IXWf6IMBPA59T1b905Vs/D/wk8Bfa57935fU/KyI/izUYz3/nfgI4gRjsSTyME3sH272yDJlAQVaFzi8puZqNfALvzWI+l8J+2rJPlZwc0zTiqZz0QpBEzYIW0/ETzca/V/Bxgfcm4e28x7tIEEeq4NrseBbfdKUYGEqEmjN5GnHS2d5wNiRtfo+lFKZpok6V7XbLNE7s9wkvkaITw34kOsc3XnmVi0ePmMbBqNl5Mm3FXJkG2E/HKuGtCUHriMqaUh24ni/9y/u8+PUNJrJjUu2p2BPWt57EjAlQOKAMZ/XredQMYmV58MyGs9azmrcP1ig2UWAz/PHOAaaLgJhBUBW9tKAXqzaMW0F70pu+ZtVKLdYQn6aJlEsTJbLrSguHEab3Duf7ds2Wy6fWNeI6lcIPA/8R8GkR+WR77b/CksH/JiJ/EvgKZjQL8PexceQXsZHkn/hWf0AEc3rKE3kceDQVltJzd+lIabJua3HkpOSaqNmRPaiM7BPsJ+iqkHxkmkYClRwi0lRwDFlWoDk0OfGoD1SBGKOBQ/D4GPH1AEmzC8IrLgR8DFb6BXO09t43jQdFizJmwzukKbHf7dlebHl4dsZuN3FxsbfxGIlxGKAUtGQenZ8hUsnDgKjiHeScuNhPTUz2mBTeilCtaMmIRJTM2Tbxxa+es173rJeV9TJSxgmo5gwVDpt56zN5hyvaSG8NqYjpNMxcl1oN/uy9ENp2c7aMM3RjQbXBj9tYUhytuWh6DdIqgZmRaexLadwNacClwphGdvuR7XZLqZW+73FecM4fJA0Nim/JSyLwJkDp15k+/DJvfHX+wW/y8wr8mWuvoIV3trebto7NOLLqhc2u0HvPro5EV8Gf4kJEnSChZ1TPfirkAlGFqgEnkaqZqQSm7OmiJ6o3CXlACbiwpPqOGBeEvjPCiA+mMrQfqBW8OHKtSHCEvse50C4QSwZdKw1rrRSsj7Hf7Mgp8+hsw+Z8w4svvcYwZl5+5T7DOBFQtCTWy54uOkqaLBkEhZQIsRJWHQ/2OxA5SHAd49uNBnd2Cwo7ArcRnUjAZ7828uxd4bm7lXc48KWZvMYmslMNSavioBZcNYi8D7GZxJj/Q2jmr2BP59lA2M/wZObtRqEWQZ0Zwxgt2poLKpjitippyg0yH6haDjDnS3RlNnUp51Dn6RaeIAEnQhJP7ExeMBdt23HHchXp++s/YG4EotE7IXYCAeJJJFZwC8fkC+elEpe3kOUJRTpCtwDtEB9x3ZI7K8M0xOCptRBCD2VWaKoUHxlqoIwRVyIuRGLo6ENHDKZ1R9NoFByEaM1LILRSD2/Gs1TTdAzek0ulTIncyv7dZsNms2UaE4/OLnjlpW/w5Zfu8/IrZ/yLr7zEbj8SxbFeRt7+7C3u3V1x9ySyWi9YdgtOJnh29RwvvrLjYvsAWB4TwnccBhZDE+DJuke6FaTAgh2nyyVRKtMwmg6Bq0gp+GXES9cs4QyHkFJiGqeDopI9yS+xCrPmAtBQlG2qUAo1Z1wwvUivDbosrhGgrPKoyejRnTfnq1n966p24yzMkpKZzaxOT/DLFX3XE6ON2sEzpsx+P7FWS1zP3Vlx586af/yPr3fUbkRSAOhi5PTkhNXScdIpzz+74N4prBfCM6eRO6crpMlWlSy42BP7pR1s8XinpGEwSGkpeIfp3zlvN3kNZver1uktOVOcJ7ti100Dp9dsePGCQaxptvGxeTZogalkSi42iSiJzcWGs7OHPDo7Z78zkdiLzYV5SmSrgJJ3SJMyq8Wsv2rtoFr52ImiXWA3JAp2weibUMs5xhvFTPPuwGW0FPou8L63n/LMMwtEJ1ytjNNA1oxfgHaC+ZjaOLFkAxtpKQZbzpmazaToKt/BEsSsmm19BRGzQXS+XhFo4bHPr4/Xy8pfbVbWbL9ntV5y723PgPOslquWFDy1Cg/ON8jZFhVhsei5d++EZ992+9pH7IYkBSEEE0vxEri9djz/7Jp3v/0Wd2+vWC89nZ9l3R0pZXy3wMeeooI2VBmq5DwhzoZJvhn3SROoMKizjQtTqqDNv9E5VNyhqYNgDSdnUul5ykSXDyYgOU3knCmlMAw7Li4uODt7yMXZOSkZViF0Hcsus+o9z925zabbM+ZKFwTnjeeu4qhq9nSxPQXOLrZAhGOV8NaEGAbRqQOZUDLLzvG9LyyJCxiHyjRm9jmBK9hldGkCk2s53OilCa7YVl3IVwRQZoWmENzh349Jtzcm5GXyMIk/cdbz8hIOOIjZsBYs2eQm+VZrNbh0gNu3b9Gf3saHjn4R6aKDYLyH0PWEvieVSt9F7j3/LM/eO732IbsRScF5Rxc7uuyIoeP0JHDn9i3uPXuPtz//DKulh2pekZYUJsRFqnhSUqYpmemsjMxUaWlw5plpxlzmVaHqgKRAjeY9KS5A090rOVNqbt6W1r9IRRlpc2eBPKVLp2GnhBg4PTmhjx3eG5x6u5nI6SU25xdMXijBU7Qgas3EYRoZRk8QMyxVYCrKxW4AQoPIHhuN33kISMCk7ito4dbS8/yzS6ZcqWPhYtiQc6KLHqcef8jHeriZwZqCrvUghUtg0VUqvBNrMGq9VG26HClWilZDKbpZfrBtIZhBUleuWwERY+SWUsx8Bui6nrgI3IpLXNcRvW2fiyjDUBinQhYhF6XznpPTFScnbyEh6rsRrjVtVBz7KTNls36TYMpHfd8TXN8yrxB8YkqJWipBbM9fFJLvTCNBHM7I6xh8tLlIZ08NRjDpnI2CqlQk6AHFiBY0ZxOzkIwieCfkJNQ64YOnX3YsZQl4kMT6ZH2YM3vvmcaJi/MdF9sLLrZbHj58ZEjKMdkItYLUgeg9WisL78i9sp0q0zQTpW6WfNvTGqIGVxYSENE6suhGuugb/sDMcnwwI94+NBm3JpaqYG0lBzjr8LuZCyFm06cqUCB4jxfB1YJ3CzyhXbOWWHIueAr4K7qOB60EDgkkXCFXtcaF9SZqRZxjsVgR+h6/WuJi30haNtaOvrKfKoNCGQuhsXU83bWP2Y1ICoowFMeDR+ekcc8q3mE3NcemqRgfQtSe5gBOUCfUbOSTTCWrIkEQbKzonKNznUGTxQBKWq2pWF0hSCB0wdSfxYNrzcTQZslqGbuK7UiXywUhOOvuxo4YOpzzVDFXoZn6KgjjOND3F7z09W+wWFxAiAwXG6aipFQZk5WCsduTS2JylVO34mKbDoOjI0HyrQlFjfmoM0HJyvNFv2ScBhaLwK3TNY8ebag5URf9wZuBNiZ01s1iHvPNdvClXMIEqxpOoThHKsqUErHLdGpbwVoqXgX1VzUZZg2FS8co+7NzHwFKutpbMOHW2nvCuqdb9s0r1dzMEMyZSs10Rn1lnGA3wHZ4yvQUiipnFxcM457oMLprQxUWhZxry6h2UlVMakpdbVRXoVLx0fTwKwFB6WKk8WXxLiCyIPZLsysXseZMU3OumCmsSCWHiZqtfM8UVIT12kQsQgi4pnlnYprN1HZ2E9ZqySRXlidr1DsebQce7QbGMVHVePilJmJnF0bsKzk77j84JxlrxhLOTXaJf5pCQGdtSak8PD/j1VcecHI74KfMctGx31kFOTMhq1Y0W5d/1rwwGHs1x/OcSFM60J1VGlS5VoPRZ9e0FGojMllvC7mELTtpICYe34ZcNhovlZtmN2vnHeINcEeraKZhYj+MiHjqCI/OtpzvR/t7U+H8fGtN82vGjUgK3gnrHrpn19w+XXHv9oKTpSCSKWli2As+OZyrjQcnDWkGwZlkWimFznnMoVvIeaLvbKxUyoioIM6ya1F7Ivf9wvbzCrUZnOSSAEVdw46rZeeu6+z3tYQQu4h30qYWHJBormn7GWYepslMbIdhbKg0yDWTSmI1KuuFoyrsx8LD84G5W67HhPAWhRrISB2iFZXCw0cP+Sf/9BP8gT/wg+x2E8NkUyqckkom5mYA28q1yymQHCDFtdrDKqVkE7Fi40sFxFV6jeS5AV4U6WwMqfWSWFW14q44cwGHpDCPOM0BqwkBYzTs3nvIyj5NDBk2u8R2N+KdJ+8rr7xywStn51TxRGDdnbFaLq59xG5EUojB87vf8xxpSpwsIrdPO+6uhc5XnCbbzycQh20bGra8lIILdlBrzoRlTwhC30WmERaLRRsJYbPj0NOtF6TqQE2VJnRGYy3VqpNKIO89aRytmVjVvAiphmVvHz7aqFJyy+pcjqOmYWTaJzaPLpimieADqvvWPXYovs2xC9O0g5M1KQtTApHuErh0zAxvQTRtTY3WqfEVzR0f/7Uv8G/8m+9nPxTTsxDT8TCDYmzr4BxSzHtB1bYOpWZKqY3ZeOkCBZirtJpHRm0kKsGUu7S5SEu75Wao9GxQe1UKfoY1iwgOT6lXRVlsepHGxGvbzKvnA2cXRoryvqKT4+XXtnzl1Yds9iNB4PbSDJivGzciKYTg+L73PMd+syNK5e6tFet1jwuePho6zPjnglQ1007arF+tvC85M45KzQ4vSpnZjFpJZcQHg4KGLgKegKPvO7z3pGyVg6lgzdZfzRgUQ5zNYhpUM+eYJmsASTHNvFr10CUe9iO7zY79dsciRt7xjudZLhaUOuHigq5f0kfPSaz4OhBc4WJbGOtcvlaDwx7jLQlpFvQVhWJtt5defMCLL73Gar0mlcpyuaLvAoteCL5VFTTdgpKpRSilknNtakr2RJ+NiP2s29iajVZ9aruoIOWMOEdAyNkcyqRAcQ7vD3TIy1Ekpq2gTg/jTeccWm3atsmFr736kM9/5VW+9uoF2yERg6N3C5IK39gMPNps8cCjC8HL9bU5bkRScCKsl5GV9HTe0y97fN9x0oUDlHgqiTSk1rU1u/mcKzgQbz2F0ioImRS0kMtEGgeGcWJ1q6OWRKwFxVE1o9WT1ViQuZ00oSdnTPK9FIoYCWWqVuZ3jSsRfMA5T0qj/f/Grd/vRtI0sd3uiQLP3FrRved58rvusVh0dIve9prFrNrKNJK25zwcLprNuSU/U186jiS/8xCU2I4noB6RiYvNxNdf2fLDH/o+Htx/jdsnz7FceLwMUDJ1SuSUKI2CnMuEiEewKZlglPiiTRVcA16h997g0moIuFoKlUpKaqrgzplbtdjWU8vsPCUHJ2vbhkrjMNj2wYeAF48WZRhHJvV0MbI+WbPaJIasvPTaBSmd03UdkhN3YmTZGdJ32E/XPmI3IilYWk04sZtcmdCqDIMJQ9RajRWW7OaNsW/7/zbW8SZR5RceYiC1m8oHQX1Pt1qwWK7xnXHOU84UILUGZi42EQCTe98NA2kY26y5kGvGR6VOmSmagpM0fYUyJob9nmlKTCmz3e4Zh5HtxZZFXLJ4dsWdWwlxjn7RA8JrD19jt90QQ6DzHQt/B17amvqueOt/XHlqHOOtDRGT+vvsp36Lf/cP/Qh3ftcp0S0RB6RIGvYGZuJSRxG5IrDTzo3OGgjNXxInlEa3WITQektWZXqkjRW9KX+pUlO6rAyqIuIa/HnmTZj/qDiPq8WSDy15qLLuAu9+7hlOl2vONjveduchDx6c2cQieaQWYgDxHcEpr13z+NyIpKCqpP2EpokaHCUndL8jNK9D10owE7UoMA2E0De1LAOgjGnPMpzgmsy1Dx7n48EyHLFZruaKU0XxTFM6VCHTWKhVwE0Mw9C46gYr1QqEER8U8RWRiZoL4zgybLYMu10zlEns9gPjlPAC733Xu1mtFlQtuGAjz8VqwcnJgvOzByZ+sR/YYUo5Bq7uUMphz3mMtz5qLQR/wm984Tf59Kd/g4/++B9kt9vTxxWbRw8gZ/Zi0y+n4HAE5w7N31prM5a9bAoWrYfphbZrkNZTcFhVcGgYaqWUmUTlD1gEcfZ5bj0KBr8PTqitYgbolz0OR1RP6CtRlFBHmHqe6e6Sp8L5/TMuHg1M+y3bZBiJ68aNSQrjbo+mhCw6EJNIm1w6jGLAZs5aFQkmZlmav4L3Qi+dZVpvcFGT52606Ta20QJ0FR8jaKFMmVIm+3m1Ie9+HBnHzDAp+6GQJuOsu6Coq2TN5JzZ73bsNxuG7YZxu2XYWXUxTiMFWHY99555jkW/wDXD29BFFosVzzwD0Tu2uwv22Dgy5Xp4jzLvRd9koXCsLq4fRQsQ+ZV/+v/x0R//w9y921GyMuyaSK9rDlEK0qwMSy7klMjJxIDAqs2UsgkAC/jWe8qpQ7THi/UbxJm+glzRR5jH2ErDJXA5mjx4QNTakkqbcIljsVyw7hZk51kOE04rNe0ZLoSdJrwWVkEoAdI2MW0G0puYb9+IpGDD4BGo1AJpKlSBNE6HJg5yaYrhgzuYcIhAiI5Ooo0Ko3kH9jHi2+hBAVcLooWSrAysaSDlkVqSqdWop2ZBipBTZkiF831iuzWGXew6CsJQTCFqv90x7Ab2+z2bh+dcvPaAYXuB88JyveTWes1rD84JIbI+XeCKY+l7dtuxeQAKJcM4Fl597TX2455LBKMY3ubbOJRP2pLu6Qgx7UUcn/3M53h4f8P7v/8dbDYbXDQM4IG3oArF0IUllyv7/nLJVWgcCFA0GI1Zy+y1qZcNSH9p/zbHrKZUGq55Fvaxe0KA0qqRxn9wnkohRqELAQ2e02qj1JQywSVqyvSxAnv2e2URlN4Hzq55dG5EUnBOWS6FmgyOqmo473oAXBiXwSNWCTgxyGkwJmNOuenQ1ZZhzSO5FnOajr2pPncxoBKIMdDMe6jtJjJREyUQ0VQYx8KQhfNR7WAHM5qdqiHWSgkk6al+ol+dwh0lBkcpkynuqFFYt8NkJrUo9882TGkk18w0bqklc+fObZ59/jkuNp9hLjftYnrzcawUrh/aCHPDOPJ3/+4v8Md+8scQNSakoY+l5QMbPc4nZH6alwMM2V49eIfOf6D9//n7MhMmMGEf+2VWFapWUm4jUC6xCrbxaB4TDUVZnbIfRwimOB1iR7/sOS1rfHCsFo7dZgMPJxZ7z/pWoNLRL1d87SvXOzY3JCkIISRyGfHesOcyZTQ4vMdkrMWZdFaM+AiSEwFhnKcD+xElMY57QhS2rhBcpaiwPj3lRAxpFkJHDEsr54I3IY2qqGa8U6NDTxPbi8xm9DzcVHYZw8b35kLsJeBCD0wsZUnvFe0L9V5HyRkdMl56Upk4u/8a03jK+vYt1ndWfM8z72S1XJBqwneeF975PJ//jS+z+5//gW1RcmksT+NFXDdm3kV6TKHz2Jd44zDYPGXF3/nb/5CT5YK768jt26uDFJv1nkw9WYuB0QqKeg8SDl4QorbVC94TY2g8mnYjF6UWG0bQqNXmgChNiIWDypdeMYmRK1VDnrcoU0KdqX/lUoiNUu0DLJZWGQffuEKxI3YLTk9PmXLGu8gnPn69I3MjkoLFJWXUuYp4WHjwwaFiJb4TRcho6dq+29tWwoNUk3dHWpnHRKqJKU2IVrxzLJaN+FQMolzqpR5eKYlclFSF6kz27WK353wzUujAFUIJqDg639F3gvcdvXMsvJpArLf9H1NBguMHPvA+7p6scU7YjSYkO20esn1tT1UYxpEvfPITfPzTv4nWkdivrQqppUG638TRayxQuLqFeMtP0r9GYUQmJ45xmvj1X/88v/cD38fDh48OEOTo7cHhROi8VQelOESugNh8PSg3u7mZ2DQaDwIstRhwyTlijIdegmvb38vKwOKAZjxUsZmUEmOaEOfwurD1xUjoF8RSWCwKdd20G09PuHPnFndv32aYzEpA5Pq3utyEclNEvgFs4dpTk5sY93i61w9P/3t42tcP/2rfw3tU9W3f6oduRFIAEJF/rqq/70mv49uNp3398PS/h6d9/XAz3sMRS3uMYxzjsTgmhWMc4xiPxU1KCn/tSS/gO4ynff3w9L+Hp339cAPew43pKRzjGMe4GXGTKoVjHOMYNyCeeFIQkT8sIp8XkS+KyMee9HquGyLyZRH5tIh8UkT+eXvtGRH5RRH5zfb57pNe59UQkb8hIq+KyGeuvPZN1ywW/207L58SkQ8+uZUf1vrN1v/nReTFdh4+KSIfvvK9/7Kt//Mi8u89mVVfhoi8W0T+LxH5dRH5rIj8p+31m3UOrmrDfbc/MLD/bwHfEUM0sgAAArNJREFUC3TArwEfeJJrehNr/zJw73Wv/TfAx9rXHwP+6ye9ztet70PAB4HPfKs1Y36gv4BBIn8/8Ks3dP1/HvjPv8nPfqBdTz3wvnad+Se8/heAD7avT4EvtHXeqHPwpCuFHwK+qKr/QlUn4GeBjzzhNX0n8RHgZ9rXPwP82BNcy28LVf2/gQeve/mN1vwR4G+qxa8Ad0Tkhe/OSr95vMH63yg+Avysqo6q+iXM8PiH/pUt7hqhql9X1U+0ry+AzwHv5IadgyedFN4JfPXKv7/WXnsaQoF/KCIfF5H/uL32vKp+vX39MvD8k1nam4o3WvPTdG7+bCuv/8aVLduNXr+IvBf4QeBXuWHn4Eknhac5fkRVPwj8KPBnRORDV7+pVv89VaOdp3HNwF8Ffhfwe4GvA3/xyS7nW4eInAB/G/hzqvro6vduwjl40knhReDdV/79rvbajQ9VfbF9fhX4O1hp+spc3rXPrz65FV473mjNT8W5UdVXVLWoSV//dS63CDdy/SISsYTwt1T159rLN+ocPOmk8M+A94vI+0SkA34C+PknvKZvGSKyFpHT+WvgDwGfwdb+k+3HfhL4e09mhW8q3mjNPw/8sdYB//3A+ZUS98bE6/bYH8XOA9j6f0JEehF5H/B+4P/9bq/vaojRHn8a+Jyq/qUr37pZ5+BJdmOvdFi/gHWHf+pJr+eaa/5erLP9a8Bn53UDzwL/CPhN4P8EnnnSa33duv8XrMRO2P70T77RmrGO919p5+XTwO+7oev/n9r6PoXdRC9c+fmfauv/PPCjN2D9P4JtDT4FfLJ9fPimnYMjovEYxzjGY/Gktw/HOMYxblgck8IxjnGMx+KYFI5xjGM8FsekcIxjHOOxOCaFYxzjGI/FMSkc4xjHeCyOSeEYxzjGY3FMCsc4xjEei/8fG/PLfFZHQ1kAAAAASUVORK5CYII=\n",
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klHt6PJfn3BOorXF+cdU1ZcRskwR5Yx3jWvyG6pjI5ISRZIsv50TJxYgVWZg2xUCUnJlKJqdsAKQcknHi+JQA2VVMy4txFyIdVpfKPC/sd3sWzx2LJHIqTKV5fGsxZkmJyZHiUoxLMOVMKocKyXRPQvv1bCGknLr2D8uac+qhUQBWES7Zs9GzJuujp8HEsgaWhhuLrn9uZa1DGaJDIfmn/H1Clg88ughf4nyB0ah/SfsZVmNP3Id7ERJCOTIi9hzJvSFLE3SwzXzArkzk2oMFUcjOlcit0naJUhspz4hUkOoEJPcKkphC8bEe3tY4v4WD1bGCdXrQQVwGc7H/dHyn9Wd1/wlp8S/LHlxeXlr2rG6Q1LmDSFOaRvhhIUgY0yYr8PsZx3OhBFDY70cKI9zXvYzFk2IS3L039wrweLMUo7lO08QmJbJ/PoshyMknzxRM7dda59VFAKegpmzWQ13hGHOwdhZZ7blt+3vKhXScmMpMSTMlLewz1FrMRfa0WymWKiqTp4xyGotb6JkFVUWSuZfJOQ45u8e6WkAxfuF2j9jbBFvVFsF1T6CJoskzH2GNxMbruveRUiIRoFos9EbThjSLp1u4uQIll4PQCUkuLE4mCoFpjaraXdfk6L2IIdvdHY977N7bSjEFYHiQmhscCwVnDiZI4l5hcZ6GeYWbzYZaK08eP6E13CD5ecTGqDV1ctLAU1QbIgWRRGQamlbCc+hCrl6XoFByrOc0wrpkKWVJEdY59yI8XwxX2e/37PY79stCQ6jhNYqxQ1tT6rKw1GpkNv/37On2zzqeDyXgk3rdKmsguZ+Kj2OB2gTlkqBV2mJ86cVTcW2ptGKxfK21swcBVM0LqCu+PQLiQkmEtK2BsxYHZ0Y8zegTmYTs9NB1ilBEqW0IXnJG2lQKJY86gwPhjZAIbFHoGriz+9f+mW5P/bvDte5WeyVMByMuakLhrqMBeelgkcc9x0I2w9IwHTrOt8YIUKha0WuurqxuVUJBiJDWLnAWioizAgVI/bl7XUZ4Etcsmw2HELbBPJIAGvF6Dqdvl8I0bdhsNkwb42tYrUVjt98xPT0n593wOsLwaHiDqSvmJCtlBdAcH6q2ZsQBytQq2jLqnJN1TBPGKsbShtmB0hh3EVqt7K6u2O/2FmrOC0s1DMpwJ2GeZ+qyOADdHDw2cPqzjudECRhRp9VxpxFTClE44wxAXyT+NYsjRQj/vO5ndKnUXL2IJ7Pfz6vF46BiFaNULrMNvEKjmeDFpPoiQGASOpaQRIxHHzkpZGVpw0XPIEq5BgJNxQCdsXBWKLKGcrFDnDshKRbbGJOhOBwoFRCV4a5zyNi7fhy4nKxc+euuah8HxyFUUCwbEUDkOnwSEapYLlyBcq1oy4Cz1T2F5Q8FvfJMwME1MQsuXQnYWMRzBADa1gZkjVeoosm8DCWhKZnnIgnJGckZarPwsUxW+yGp08YjIwPVwxTpKdKpJEq2wiZR8RSlWL1JhAuqBK/CxshCg+7lrEKJPl/J8/xJSM08MW2NZV64utpRzi/IKVNbdW5JcBY8bAJnNloa9LP9gOdECagqbVn64giLaa6bxc7iYA9txGExyKqNVsWIKs4RaNpIKiyLdoKNIeTuJs3mHczzPPLGKKVM/R56NiEJU8IzDmncX8qeChp5WJcTkOSklggzIIspJXNbB1psY+AWTA+tnLnCoRQjrqwHgi0uCet6iuuAH3q4DOx6agtEQLKRfZQVv2L9nVWVnx6c59lAl6Hj2bn45YCAJCsBSK7VkuMT+NiZsh2CH+EAIuTslYz91mxul1WaNkI4wFOFQgtliykSFcsmOqiPg0quDC2Fq61aYjBSbyk8UBB8jXhVqfS7Cv5DzFcYuYjPx+eMyrxKecsACWlmBFL3MnSEfuop5r7y7L+tLl6FacSkKFp6liGI47lQAiKw2WaSmOBPZaJM2eYkSV9kTY1TrzUNwdXQeGqFFl5VaLnZ2YZaoTZzkVqtLHXpqHp4AeIAzrJffHEmWmosUhGBJSVEZoLskbx+oZTk5I3hFlrcbKHEcLONq+/r+MBSdWELOenLewB1IR+srSCHQNq6yMnG1ZXDKkMQh8XN9NBCMXJLbaDpED8QEaSZpxTEoCQJTYNYo62ZW+uKMqrbci691NrMpN/5KuYNcA73ssJ1796ODKVhIczhspVaoVayx+adKNaVQOrPkXIiJSvVtTFpY11had7aakfxw80XGiLxo32+TcxTpwOPuodhpBoWHuTUqO459pRgsmzFwXj4eq9q0t6VpeNZIdg+yzGTaKsjdF7JVsrSn/dZx3OhBFJKnBwfETnvoMeuMzuqSqtCpVJVDANQi50M/Kjs55n9brYYaTEgK2kjJxcrWTV20NC6Q3OntH79ECAzXEFtMSRBFnt9zonNtjGV4vfaYSlfBKviFxfjSHEiIbithzbCCqgL70dW0+rVfcGVsHvzjIWfq6PrXcvAgQXvGIh7IymRVClqgCFqZcC6UsCiMlxjERJK0tzvUxk8C8uOJFes2RbwqvovYpq15QyEv/dpCJ5BfN5xmKhtoH/XxiYnV1StkdYekc97kNEkOXOzNZZq76damedqvRYurcw6gDYTqbjHNQaQLRuJ9FJmlVFFGOFtjM/SGlmd1NQqopbBCuUtGq68jYVqs+IoYFEQL4aKngatVusX4cbQ5GgoVKuZKYhCyZOzBp99PBdKQERciGKgu1eGiYWlwVrEVxjgtngF3H6/ZzfPXO12Ts6pLIsJ1pTFGmRMUy+IiXTN+vodxIp7yMN6QFjRdvAdd57d82Bgl2GZfXKqGKbRAAkL6xYQj+G7AuiWR7GKxRVPwoUHV37r+Ne8oQFy9vjYxyxi/j6qEqHGCnhc1ed3fCBFlxwH5vKwzKraOQviPrKI56WvczFk5eG4UlMP3eL5uw07EHp3g8DCBB/LtYJOOXUl3YWwezIxyoehjBkVi4XmVtnt9lw8vWR3YeunVltfow4kmaeamoGCroQlUn/qFtspuqoGxmlTbwIi49lWP+oKOqlnINJQiCoN1WXMVU6BVpOSmpzkRFYHLfPw3NZjniRbSPQZx3OhBEKw7ebVGV5rJluj1taBvP1ce838fj973tRSIa1WhAFITVnI3rwjPUMJBCjX0d6wdM/Iq65j3zHQ7ZqFEFAnNBHK41pOmeGqh15Zg3D2RUj+IxoYdX8LiIYnq5ZYB9152gh1MLdzHYsbgcQtb86WSnUuQ2QNovZAEisLnboSgOHCIoLk3D2AKN0WVyjDC6HjM4s0pA2l1bSRmyumVFzheKp2HTLFz+Hs9PG//pMloUP/jDKorhRrL2rqgJ7P3eD1j/mzMbDqUU2p409rgpR1q9LuFyax3gMGKpcR9/cV8em1FvWYUcSYU/b05mhCYw1WxPtepO6ZjLVir7fnXQko1hIpYw8/KujcwrVGWxr7efE8qDVoWBfrGICSmDJ40RhRPBPpuMHg8lXkXocBWW7xHODp4Ny1ifo0ldXFsysTUwIBTF0PKfrE+6LzUxzgdv3zEak6iaT6vVYXcOM4tFVWJdxWe/Y4oiWapOQEquyVZtlJVjZOVkadUVcYKXsfhgC+egzvQh2gYL9vVhZOV5Y8hM6+2zwUyiIg6jE4RFu2VAopFwPQUvA7Gtq8OAdjFgZrM7pL0WQltK6gQgGGUgjcoUfUdkR9hYRw6jBKgzQWwcGY04aaInN3XTwsWE0HIvQw1wDvQSleK6u14elZF0f4o4UbCosT1IwhmPtYi6rjKnkoZw/jyueBCYjIm8B/AdyzW+Mvqep/KCL/FvCvAR/6R/+sWm+BzzxaU56eX/YFV53sYFqZbkXXSOcQmtH+yVCWEF7nEKTDwpmw/IG0G9XWimfM5ZJrguuXiZaFqisty2DN6QoL6FIyvhNIYHfVfUbDLQ4Tsg5J+jUY8bTIoN6G8orS2hFTYs8WApg8Rg9BdyUQxSc5ZZo2lqV6itTvZTVu5DTahbUAZb2voT9naglJ1RFz76mQbIGqJPdWAwl3D6F3I+oqrHcMWvcFSCr0TgkOdgxvLEKKIeRxzoYL9Go0O6au9NZyobw6MNdnT1ZrcPAh1mBrcBOj8C3THZhO8462cqkccjEOw83xTIDThJW6WJ9F6xK0Z5737OeZQpQve7VitkXQ1vhF8mYrz/Bs4/h+PIEF+DdU9RdE5Az4eRH5G/7ev6+q/+5v9kR1qTz65MkglTCEL4o2ulqN+NGrvtyomFV3JL5XG0rq5bgj7sffC6spjp6u8tQRs61i7vXR//yUhxVNN8cb4VKu/w6CTAf34iHiXu3OjASFl1OvFk4JwSSUUhpcghX5KFxx8fRmZD3ylDk+2XLj5ITNNCHAflm4vLpiXoZAhQIxh9ksbyiAVttB/K2AqDHlWmtoKWatVTH+g3pdO71RZm2NpZp3hxr9u2Wb15ILZTJevKaIJ5zEFf0k/H/D6h027IiQrIpn/5JVDq1mA/CiJRdsWaWG6zLQ9hbpuWvrQZtCdqq7d//xGIzIwORsljh34O7Q6l8PMQO47V6wh8P7/czV5RX73cwyN5I06DUBzTy0JizO6kzFi9J0AT4HT0BV3wfe938/EZFfwVqN/wMfIsI0RcmuEjLTdEHU8r84+BG8/QHxjIDTUGiPodNhjLZ2u9QXKz12iiDzsG7fni3492HM3eJL6ABP0KjVfTO8thinHrZoFpKKp67WxSJ2D9HRBhfoaSrddcyeNgs3P5h+9myRm5+6ohuuubnS0fwjJWF7vOHmzVOOpykQil6V9uj8gmWx1GYH18Tcb8AKVcRALPVha90dX1FdVYdH427+0q1/fM+6SKnTWpuAlIWlFuvEsxR6sc4q1BBZMQlFOgXX5oCuxLMNTjcErH6bm98QHR2gIgWYs1gjlK7LD73CdbhmxcUe9yfp89q/GfeYR7r7uvVfr08YxULRYNTcisay6jw87/c2ru5hJs+AWchWSSkxTYYfkOWAtHb9+C3BBETkLeAfBf4O8PuAPy0i/zLwf2HewsNf7/ub7cQXv/S6u8bWVaeqxf0W/8yeEgkOf3Clnc9eTUKzhPDH4K/c9T5lXkdKFL2ulclw6eCaFW8hXKu4Fmd1jS94vJuMhLIq3w3PQzW4AgHO5c5R6PFitgrDTZlGzr2TZ4a3kvMgNdmCyteUg3dibpZWNOxC2WwnNlG56IQctDFtJqZ9odW5j4sJsdNau2WnC0ikJeuyAEJzoLQuS1eykg3Q6vG2H7VaE8wILZqALIklW5FXSdbMhQifJPnf19KReV2gdFisFEAoIiTyoScYJC/PktBT0gMHCmWfU2ahdjpwa96ZKJWDZ4rDehKMnhGKrYXsWacD3MJvqta6UqID7A3MqzULv/beOdo6OFk/iyypr6Pog6GqlKIUKY4uPvv4vpWAiNwA/jvgX1fVxyLyF4E/5yP554B/D/gTz/he33fgpZdu8dbbXzpoCLLuojvPC3UxhRDvR3qwerdcra2DPev4DcRrEEYuHhH3CUO1m4Kojv4icnAOVUWXUYvvFzGQSkIh+GrR4QdY+25Z/aQew2fvRjxtJlssufSipWhVnn3R51z8tg5DmyAqhfVXZMWodhK7K55e7CSNMk2UYinTWOitmjBkv8fmjTmAXncx5mcFcIaHIWl0NlqPm0CqDS3RjUh7M5R5mdnvZ9abfQR4acJdDuYzOQGpZPpCN9c9GZAohZRaL8qKkUBDOawwIb/3SKU27XzJ7kmlnMgtow0LkwglsY4Dw+k/WN3+a1wTXyfJe1Cs5KBnCsLoBCV5LEcZ+Ig6SLoyUBEyyyoMDYWCgNSR8n7W8X0pARGZMAXwX6rqfw+gqvdX7/8nwM8867u62nfg7be/rK+99mqPgywkiAXXqMv4t/1ejDO9tJVmHmSZVlctu2p0hzVWWHyuo8hNzeuokVKTcX1HZVtTqhjbsPfXxz7anMOAeJdiCWujzHNyATdLOG28FdRUrKe/d4TJvZw4+eIrzl9feR06wMM+hqufMGwWPoBI6ViJKize/Whe9lzuryhJONlu/VkSTazFW1UlT9apf1mqYROrMGlkUkwZVW/Ouu5TCGYB2you90l3tLt2kGu/3zMvi3dgCkEMWMXTX65Ykxf/bLWGH/IAACAASURBVKbkRUDWvt3GsbHdxN3Sqby9bDcNrKgbCFXv57hYp+b9AKNxgDLnbGtyrh37QEYoN9YMXdhjc5rutaXhkVxv3b72WqI5zHqsDZT1DIArwQ5yezYDab3CcRgFL3BbgZqfdXw/2QEB/lPgV1T1L6xef93xAoB/Hvjl3+hcOWVOb5ytXnEknegH5/G4Ri7cd9YJmvAqVbgmyzQPLVrV4V4dAFqtp9lCkVhWQj0FaSFJU+s/t8xecNTLfRtZEtNm451kc4+7Y8zNJbMFO03W1GSz3bDpbaFyd+9jkeSSSal0HDu6L7dVyXPSbGQSMdppQpiCThsLKxmxproTtDk+5ubxbY5PjignRxyfnFCydXm+3F1RHz/h+PE5l08uWHYzaSoUKSzzjBnxcOdTH8Pk+ECtC9RBXY7GnbH0hjIY6LpRdJvve+Btv3zRNhpVcevnwGNNaMsknaA2kioVcT6FsldTuC08qaDmoh1Pkc5GHGtHa7UCIlcMNsbulTTPHhWFxdKzVW3cAzRdx/MdZRJnS7oyUAnjMhqvXlcG4RGYIvVUr002tbVOwsornEg8tZ04bB0XxC4rvJJ+X886vh9P4PcB/xLwd0Xkl/y1Pwv8cRH5Pdi6+ybwp36jEynGrQ5XO+c8UmOKP2hoXpC0rlyT1c417UD41i7WpxWEuaFasboD7xXQ6tyJSbVGGylrTTfPM/O87wpGfbORHIVE4CW3JhibrTVMtTx87opg2vhvt2xkGQ0lSu5EJ7ylmbQEC4akuyKwCrJErtUWuAhtMkBvFLVYyvT47IwvvfEF7r12j9PTE6t8E1M0dlhd/1wr51dXPHr0mPe+8y7vf+c99ld7soizEWORN4/jm8X5Tl+tbbjUI3zxYqBcLFRpJkBZoLiSz8Uq8MxwWkjUxApuwhMKZSwSSHuyDTyatXJfVI1rkjPLsoxQITCSsI5plG8HBtUWU0CiGq/66ltxBXz9RNq5inmWaYVB2FoeaURCiAM8rY1cPh3WrbtYgaWtwYxcpL7V5aLkcvD9wHWSpIPX/kGO7yc78LfgmerlN7fXwOqotXJxccFAuVeltimRo1AleONtpNKsAm6cq2eBe8bAXeZulcQhQi8aaQo1mkxiu/Y4INlqI3La6q5vW2b77UKA8xZiskfzz9HCu2HPUsTAv1igvTRYxoI0bCAPsKy1EDuudjtvV2aLI5fsCLAtgnm/Z4qtzaZCmSZObp3xxbd+gC+/+QVuHB/1smsrGxiBp0riKGdubCdePbvJKy+9TN4e8au/9Muk/UJjGWGJP7eNZ+5otikyB7vciqec+l6MSUyphyI+2m5ZjpeeWVnHz4J0r82ad9YesmUR5zxkD8FSz8eHSx1hiUixzsfuXSxah4LC+f61MfszEFCIV6uq2tg3rDeAOHU4l+TdkEeV6hr8DehJ1UKj7IVPwdCMeR97OQY/wcI+SYmsjSbVMKsEjWoM1ZRhxeBsYpmYYGlGwVAfS01dHp51PBeMwXk/89337ncBKKV4d5/Dzr/2b3eTVq6YHe5+dRJGoKw4CpR6IQsCiWjTM9JfgFu8QcFtYaGj2MMXl/qijy3EIj5cM9jWSgAYdQk9dekKqdburiUXaKt0tOYoJIF5b/G9mUavmjTWZC4mYE0bpUwcbbdUVbYpsz054dad22w2k7fkDp4yB787PcbDr+OTE77wpS/yrXe+ybt//x2z4t1SjtSmyOixEErbKiadjlwyOVKdUaPvLm/1uba02op+zBDSZTlkhjavlDOaN93Cw0DaU4p2c2swLITaBD32euiU9P2exanoo3W8rrJPcZ7BT4mW47HTVQei1+ugNcMpVvczvADM66mRYhzb0PWwz18Tr0+xkmdZpY2zpzlHiLEOSXo68nnvLLTb7fna177BNG2625xLJhehlGls7On75OWgvNoo9phoclpmtI8KTZlz7siyaFq5cB6Dc5i7FcldjXdAxZXAdZUaDMIeu6rLlbvHw5fwzzPyw2uQEg7dxI0O3GFZKmWzYXN0xDzvDVxzjyXyyaiitdEk0SQzK+hc2StOJTUFIKjX1V/TAvFsCqVk9rVydHRMKpnH508pmj3X7aBc92RiD79iOzTnsWHpuiuRNIXUUD6932Ivzw52YLjrYlZUarZnbY1a00jbhlJ3g3DdNe/C5KBq72TcvcIRHqqfL4C3UM51cZBZo6ekFypVC0WT0kuv1XdYajowkwFCrgQziF3uLpRJyFL6NaO9mKRk/TTFvBirzpy6sey9Cf0ZkqQejsgKXNRrGYnrx3OhBOZ55v73Plxt8DEsfuzZt0bSyyZTyrSy+rYQp1LYbCa2201HjaepdEWSp9hZtwzWnSSWJB5G6OiV50IY+fmwUFyLudYCHocnByJv8KnvXG+jJjLqy9dxYnxmWRa22y1nZ2ee5ag969E0wE4rpwaYAql3Ms7V1RV686aFK4ySZjlQTeP+arP2YPu68NHDhzy5OOdkOia1xDQ5b3/1XLlkpu1mcOIF8K27RRT1DU1E8zMDyLUiPLTeruC9mWqkIINv0NQLfrwhTZMVY7B7XeJFUWkYc4/Vk2QHn0ElobX2alOUAQy3dhjmLcMjMUUShCYNLX/wbHGvQEfvhxLAQfCxFmKtRNq0YxSSKFMxcNnxJXGcJRR4H081ZmprVvq+ZrFeP54LJZCSsJ2c8NIq2ipLHYUYodGizwArKwOYBndrtNlMHB9vOTk54ehow3a7ZTNt2Gy3pgw8Vi45W2FRzr1u3q7F2NCTse14j7GIS7oASCC/IzTR/u8h1Ov3O7d9PS+aD5Wag6Ng93O03Zob3RqSKq2lvuFluMkNW6ySpDdDTSJ88uATbp/eIN+8ySQJYXAq/GkGNuD9Ffb7mXfffY8nDx/y0o2bpGIpxwjTSAbeZQ8BekgUU5ITbVlsK7muQBMajUn8888qsorXYgvwSD3WpfYQaC1YgX43GRTi3uMwlL0rgTXm4DdKxijMEYaka0C0J6s8e2TpzdqMh6GSmKZB0LLQ5pA12P0OV+iF4r0ZVmtCtZN97NnjGgOGMU8ld6O28Y1Hk9bR+Slqa7q3IT2F/FnHc6EEtpsNX37zjaF5vSqu+oKIFmAR61d/4PW2X+b17tjvMvNux7yf2R1tONpu2Wy25hlEWm6avGrMWWfFq83E0mDrmKyDkdeYaAFAyWrh2b+lx3c9Ro6w5FrMB/TrxrkOw5IR38b73RNo9m0gGhVAGt5FZ541uHxywde+8U1eunOLWzducPP4hG0JHkHg4Pbdvc48vdjz1Xe+yTvf+jZ3X36Fo9uvsu+5cQxkc8VTJFuzzpy9vVs8m/Mr6txDg+akrXXWZr2PYxwjpz0ISus8t67+Vv9PjGPU4zdD/4gY3d0SH9eo+HOcBsN8ajEeR8kefhbnPaxCp2D+LfMCKFOJefC580Yt6yOi9EMj4teO9DCHIUR/Zr/XJrE9WxRgDXffGwf4pV3oNZTjWCafdTwXSmDaTLz2xt1rpB+FJgctwSuG5Bs2ph2BX/pCUp+8ic3GGkaWzdQtQlNvFKHRvIFPpWjatQELa7BmhUX4QUziSgkIIzw5ZLVlr/YTJx2F+weBqLeV4EdZta7uIRqSqGYHlXzx22m7O1pK4ejohKOjIxqw2+24evqUh9++zwfpe9RJkGliKhOT74C7VOtYs1zsmC93tP3C3aMz5I2b7uEeWuxujVvrOMB1gd3vjd4a7LUkAlEh2pRFG0szjkCUj7vmNRDSLXKk2wLUGwq0i1//d2tYfjzZXuyxQWoX+OuKVuOSkVq1jj+bqbCfZ/MKFgCL94MoZQKqHpo4Z6UmpGQkBUnJKc05I1OGZC3HhWb3J87G9H4H2iyW76GRJJYGi7dMa3WhzTPUhdSshLnVxdvnNcvgrOASWXIfztGN6dPHc6EEUkqcnZ258NuCAwOUWoBrAeCo7foTIdB6X/tI06RrAtg73IQrKEJrn97nIIQOxiLvFkdHrDqikDSsOGHJU79OCZAzMhxT7qy1aIqZxDhuJU/kXHvYY/RRIfZaCKfSNu1s3fKtQxD17MjR8SknZ2eUkq2v/2YilcLl+Tkyz2gFqUpiRttMEti4q0pJHN24AZUOdFXVzhqM1GzvXBSu/moc4/c8z2y3274jtAnpsP7BHAyORqT1rntLYcl7j4kclnCsIQGrCREPsql07ejMvQ6auZcgacx3X1/Cqg+C9KrCumhH+HtqTiOTYKXoRgvG+RLiIHVehS6Ha2jgG+vY355GMMUfaVLDmdS6aO12XO2vrFuyz0VV2+My6msiUyEImxWI+KzjuVACMZvhbqp6GyWxmHzyB6g+SCmqdR2EUdQr2jy+ionKtm31Ov3UPeg2WnEdxKie/inSq85XtzkAw/i7/0DPndv210qrCW1GXGk5kzSTJxNUbQsewzizz7rQpiyeFYkNUW2TjOTUYnLqJamxqAOw2s2VnBKnp1uOjibPhioVW7C788o879lIIW23pKmwKQVapS4zRbekZU9dfF9IMQzCsiriY+nEptWcrUMXG1sT6Ihbuyu/Uqprr6E6iBm04Vj4B+O7Ugx19X6EF6gepPJ0pSDHrkSre9BhOBKGocRmHVG+G3Tz8DIDaByly/QOzTA6+gijp2HMERp04uA3+EYjvvxbC6G1HgxVR3eiWOqtNnZXV5yfnzNtJlptnfDVWmOuc09pGsZha/4qj813nnU8F0qgqXJ1tTtAxIHhaqN90FFDgbsb12OqEfpEHB4obz9WHtE6pr++iGPS1t859AqAPvmHVYcHaLA4uy2P1FkxgidTnroLKjlb6FJGJsN48YVps2F7ZJhG2Vh6KBREL9V195m2OC3VuiOpgvp220fbDdM2cf70nOXSGrI+evAJjx4+5NEnH3Px9CnHRxtevXuX09MTSp6QXEhTAe+jL9lc/sWZkiVnF5A1MBZuMJ8eU/99PR8e0X3oijbqtsf3olzZR/wgBecA2uhAHRkJP19gTLGDlAtXt5gKTRpNYGm+ozTXgNt4uojfWIcVMQVDGaSUWGql1Nq7NuHrNZXwFoPaZqXGQVyrVeNiveMV1epg5v3M5flTchKWeY9IJtrsV116hW3sVI0IdRUCPet4LpRArZVHT89JXWiNDAIBnqTOrw+wJHvu24Q9E515RcRTc16RJaN093BW26oEd12aKgcCb3eDxajhSXTDZtzDg0wFq/d8wUesKWkIu1kVKyXWlFy4rbiopze3tnvxdnPENBXb0DSviDlxMZd42yCkYGBYBjJsbJGeqFKvGu986+/z//ziL3L/m+/x4HvfY7e75I3X7/HG6/d41CqP7r/P2c1bPD2/4sEnn3Byeot7X3iDV19/rYOqglna/byQsRShLUbLZa+f/8ClZ1jnUBDrcTYQy99HUAkb6+FQnONaD8d4vaJ0NmMzlh9qeftYZ7XVke7T6AzsNSPa2O12NNR7WAwwurf+Tr7XZcksEUKutnlLamGi5CHosX6D05EDlSRSorY2m1bLYjTLOmQjITDaiyvLfubq/Bxpjf2llRPH9nhzXWgVtDrGU6vJyjSYlM86ngslMM+VD+4/OCCL5DzAr2m7YTNtjOir2GLH0lO5u1jJuwMNklAISvC9A2gCi3dLHjF6q42WWzeqIen988kWY1rjAAnvdT/wrAAH1UMVa7rpaadSSMUtbBp7HsaiClLUdmM8h3JkOeGjzdY2Ml1jG543N4FPXoWnXFw+5snTC548vWS/n3n45Anv37/Ph+99l2/86q/x7Xe+wX5/yc0bx7x0+yY3zrZsTzac3johZ+H9997n/XffY54XPnl6yYcPHtMQbt29w+3bt/nyl7/El9/6MienJzbWiFdHTkT3IotTR+YmwNKY2469+MAlH2cNQNCVrdoE+CqRkSWx+jjCWEeK1gBE9+K0mRJoVukpjBr9zjFYeQ5tWSi50Grj6mrHxfklIpWci5OEhnsdoeNUit2/WOem0c16pKwPKgP9d/cCVnyQbv39mfuuR9WUVPLn1Low76yPRZ0XCxuCTakKXkvTWjTiacy7Pcvz7gnMy8J79x92I2s98IwZeO/1u7z1lbc5PT3h4vyShw8/4cGHH7Hb7UCtWeWmWBeVqMKLRhnrFuOl+CYYvmNQEqF54wVVtY7EaeAAw0MY8XdKo2lHt/7SBm3WvZNhot0y+EviazRh9x0bgKaUHdV15eVKI6epe0SSYnQEVasyW9qWi4tLfu4X/zZ/7+/+KhvNfPjgPt94513e+fvfIknjaFPImri4PGeaEsfHR9w6PQGFq4s99159FZ0bH3/vQ05Pj9ldWPrx/OICGkxkHjx8yvknO752+U2+8crX+amf/r28+sYdTm++RN5suHXzmEmPoR3RWNiUSq02r/M8d8WI4BuNjhoBxHZmWm+3PlKjELsOxesGgMamJ9Ef0BR09tJZ2zshkWWCvPJKWDVGiRlyZb3MM7o0dscnHG/PeZInhJmMWPeg7k2q4TfZlVEHIo3TL0lY5oUiiSmLGytjtBYpCHmVgjqsDwnIaY2tJBolw7KMgq3AwlpdLB3SrMlq0mTCj3sbOGiIdrr7s47nQgmo2oIBLzndz4jA3bt3+JEf+TFu37oJ2tje2qINvvvd9/noo4+9kCg6xXqXHnffSjEX22rLTUlMG2/26K2fw7UF6XHb9bAhBB448DCMbBhCv+IIyKG7blV9Si5WQVY8zm3OnU8pUXTyPPrCsrCqhMswJfbLTPH2a9IACk8uF/7qz/51/vf/7Wd591d+Db28IuXCS3du8eTxOfdeeZkbp8cs8wW3btzom3Ha1lvWw+/Bhw/46te/wenpKZupAI3vffghH3/8CLRAmri82qMK+2XmyeOFjx48hrzhyz/wRfbLwhffuMeP/thXePVu8SyAcjUvtJa5uroytqKqdbtdCTOfAnLzamyNpTlNo2JubAmXSC12/V2RelAT/u6mjfDQogS3kvE/jeuHx2dzO5XSS7xTyjTvTTjlTM0KLANIZq2wsqV43Xgs0VfBx73vEO1WW64JvMmBBz89hg9A9DA87fToZPH/UmtsxcnYyMZTq64lf50M4fOhBAxI2gBCFpuwlIWvvP02282Wy4sLjrZHaFXOTm9wdus27733gQ0GVt3HvCDM45zhEYgLYim2Jfgqb2+LbF25aIj4uggpl6g/mMjJkFtbtF7Jl1Ztx6K1WV+Hxh5LFdKipgyW6l7J2AdBdlfkMjHPG3JJ7OeZ46MjatuDnJLKxOy7LJVk21H/5f/2f+Av/IW/yNXjp9y9ccwX7t5hsz3mwf2HXF3tOD1dON4kNl5leHRybHHjsoAmzs93LAt88vCcb33je75olSaNi4uZ/S6xtETZTCCNuV5R5w3z1cLXfuVd3nv3Qy4vrzg9Lnzy+3+SP/DP/JMcHx8xo0grTret1Dqz1MZ+b2OS1lkNt8rSlcAgV3WilYh3ExpNWIqMmpCDLcnlkEka7jvCECTvYYD6nPnvaEITaWq7WXPbJCe0rnouMgTW0tJplYJbCTBhBPLw8Pr9Rt1EZAcsw2Nb0R82TF2Tp6K2ZrudrImMLOSUWObGvs2Oq9i9xw5UawXyrOO5UAIpCZvNdmh1VXLJnJyeWrcUt/S1LkgqHB+dUDYbikxWB45au7gVChppoIgjW1VmbbZfW4F5aSxLO1ACptrbgUUKrnfOred9o5oxq5NT3DNImjoF2dJSEV74/oRNaYt12BWpHivbx1LeM017chI2Rxt2u4WTecPV0jg+PmFflZJMqL/97jf59ld/jd/3Iz/OK7de4qvf+BWOTrckCq1mnj7Zs99XPrj/IUfbLft5tvhVbUPW7XZLTondbubqYoc0ZZMS281EznA6wYOHlzy9rFATnzx9wsmNzNGmUESpy577333IyckZH53v+Jmf+T+R6Zh/7l/4w5SkzLs9JS3QFtCjXgJ80MmpKeoVm3VpzL6AAyswYzaELBRBKZlt2bj3VzxsMlbdqD3x+XOcobMUG9eyEto3XWmqtu331RXzftd3c+r1Gdf2+TPhtBDAGuB60Diypx56rNY568rGsPT0841M1qAAa7R3r0EgEjbbieOTE6aNNYSpi22jtt/tOytTkJH9qJaG/azjuVACIonjo6MVCGRDdHW14/jkhP3lJfu5IlOhzpWnT8/ZThvby61WUu9DP3rIqbvdwdILPnf0pGscpgkj9s6pDG0tQkll7KojvhB7Xzvp112HE70bbmAHjiVqcta+qX6i1SkpoctMnq3WPV1d8bicsymTgaJHWzbbDbdOTzl/es633/kqCTg5znzy5AGXl1fMrXJ2c+L9+w948vSKo+OJy4tLcnJCEI0bJ1umAm2eyQk2U+Hls4mzk2Neun2DWzdPqXXh6cWOB4+veOfdjzi/UkROSXnh5LhwcnJMzvDgAaS85XKGxw8v+Ot/9W9y8fQhP/lTv5fX7r3O9mhiO21M6FPtuAodlGuD6dnBLKN/93qBDuQ1dPGmJYvQ8szo3U/PSJjXsA4r3ADAqoPU6BZlzU1sA9yUE8t+5vLyknm/A9yAiFvsADR1WOc14DlWLd3LWL/emnlZQYgyD2GkxONZRp9bVwR1FC/Z9xLb4y2nZ6ccnxwbE7Yq81yZ9ztnY3rlo4OKYXg+6/itaDT6TeAJRtFaVPUfE5GXgb8MvIV1F/qj+ut2HA6evqP/IiDKB/c/4N4rr3DjximSEru6cP/DD3n44CEbd6ltvxHx7+cR5kmklqLcVXr2wEAer3hztLaHA+6ih0WJ3gaIrhqCjF1315uHhvcQTS7GBpF4zLpuswXhOnb2HU762M/s9wsXzOSyo7aH5Jy5fPqYX/3lv8d3fu1rfPzJI2qr7C72LJcz+uSCjx6d8/Ri5un5zPnVjKhwvM1spgxtT0pwdrrh9tkxp8cTt27e4JVXXubundvcvnVKKXB0dAKS+OjhI/7m3/p5fvmr95n3C0fbDdouaW3Pl958kzsv3+Y7737Iq3fv8FF+itbKN7/6dV5/9TYnm4mjG2cuRMP6OabfGZ8ltU6VxtvJG/DpZB2lE4hQPt0mSyNmtlLf6u3C1hyPoDPPtfZ+AcuysLRm5bmMyjwBdlfmBdh2YdZotCmkZdW2i0RsR19bZJTGtmtdAXSDpP2zRS2bE8sgPF8LAdxT0chEia3VFvZRevOQUia2m633QGxsSmXZ5NFqT/Fdir0E+v8HT+D3q+pHq7//DPC/quqfF5E/43//m5/1ZVVlt9938CQG8sGHD/iFX/y/+eKbXySXwqNHj7n/vfvUxbYPr832HWwtrAAkL2NLkqxNdgpLLZ2xZa7iaMiIGPGllNKVSvT5j9y9SGQscu/1to5h0zoMSGL88Wugj+WTW7/mSCJY0ksZDDWzkAlNpkAef/yQn/krf5XvfuvbbKSw3+2s4YhkdvvGR5884cmFkmVi2QNUtptE0j1HKXPz1im3b225+/IxP/jW63zpzS9w7/XXuHXnFU5unJEnS1nmckTbX7A/f4Jo4tEnf5snj9/3isxTHj1+yDw33nrzHkcbpbbMURYefPKIJ4/P+c63v8dX3v4hprmxr4vF0813cnbXO1xhSLZZrkTsXhBHzMzSDs8OcL7HqobekfHZqcetDTCsKw7HhLQ1q5DM4rtJqXfhbrB4gVoSpDUKiSJWIVpSZtHa562U4gS2ZPteOinKPM3UN7JZg8vq4UTsG5iSe0QLJAcNJViy/ZvJwb1m/AExQ9kw7CaBe5Ne/9AWe81xFDuTpyfXivMZx+cVDvwR4J/yf//nwM/y6yiBWhtPnz7t22n1Gv4kXFx+yAcfPGC9W2434AQYN1KD1xHmaIShviFJVhPeCAd63jpFBxcl9nJLHldG81DbsDP3kCJ7D7/4d9/sVAS86ahE9gDoW4EDa6uhDCyk16+rIOrWo2T+zs/+Hzz84EN+4Itv8fTROfeffhfJiXlpPH56wcVl5epSyLLneJvZFuXkRLl5mrlz+4TXX73FF15/ibfe+gJv//AP8urrr3Pj7DaboyNSyR00a4vStomjG2f8xE+f8b2Pznn0yUO+9/EF1FPuvvpF9rvGvl5x66Vjnjy2zTpu3Djl6uqCD+5/j69/7Wu8/UM/bFtnebFUKWVVwEOfq+ze1BhjF3onUkWruRhbSbJSAF43n80CLsug6nZ3EAs9Uk5MtfjuSb7bsAYt19ZVrZUdBryWupCWSs7CNE2+5+OCSJQc+xxeW8vr1HIos1ETYV5OrZUk3hyl2nOty9dRL5xz176f2/clrK2aJxM4gir7CHV00Iy79/AbCOtvhRJQ4H8R2yDuP1ZrJX5PR8fh72H7FR4cstp34PjomN3l7iC2EwF1AoaqtZDWZk0prSa9n6db4oNF1RfWWEApMXbXlQHydbff+xXUKZPSYp5AtX6DOWfKVJlac4tprmLK2d27uL6llhKWS+6KKUKWzmMYiqolVkpgVTZbzSvaXVwxpczv/NHfQb3c8fEHH1K1cXFZOb9c2F0px5tTkl5xtC3cPNlwepw4OyncPNvyxr3bvP2le7z9g2/yxpfe5OadV9mc3KBM285sSymjKNOUIJ8wL8rdmy/zT/+hf4JPPrnP3/mlb/Lxx0+4OJ84PX0JmNhuM3IT7t+/z81bL3Hnzm0kNR5/8gkPP37Afqks3gRSIpWbxpx1kFVGWbf1eLBswbRpYxNPTWSse07zhQ90zzGlhNge3XQGf7gQzf42IzNAtyi5i8/t9zO1YtedCynNJGmdbyJujSPdKp7JGmt6cAlin4f1hiJgn9ekfTv1njb0DsPNe0QEuzHub3RhMiVX28J+mZ0EVdn51mQRAg2DqJ/yTK4fvxVK4KdV9T0RuQv8DRH51fWbqqoSO0gevt73Hbh585bud/PB+z2l4hpzXVkXRT6h7YciSCshD0FbpfE8Tl/3LFxXHBqHINz+2LgzlIVz+jfW8bV3PCqD9Xf4xpuRJAAAIABJREFU+XKgZIIBmbOgOSOafLs0tcKcZKBTXtW6a2pkER5fXXHjxg3q5Z6vv/tdnl485tH5FReXym5X2UgilUteu5M4Ozni9tkpd26dcXbjiFtnR3z5S3f5ypff4LXX73H60m3y5ghpoPu93UsupE2BlNEsyLRh2k5oq7z1Yz/KH/jDf5B8/Lf4+je+y8cPdzx5+phvf+uSH/nRH+TNN+/w3nvv8eDD+7z1la+wn3fMuyuuzp/w9GrhfNcgWS1D8RAqRagVdRBiBVObqfSQq5TCNM/Wnn1j2YDSEqmNDUkENW/ALWSrwQHQlZEYMXl/LRRESgy0H2Medld64A/aBqBpuIW6txJCOc4b99a7V6+VuuKWemAGiqH/8TnbYAe/38Py7Q5sp2Rh0H72kvqFq6sd+111gpUp9QhZaxmb1j7r+L6VgKq+578/EJG/AvwEcF98/wEReR344Dc4SS839XP1Zg/WyVUOmk/0TUp1OH2xfXYnnUSMLtIBJYl4P+dPIckl246xpKDwBs/ftweT0pVAdrDQWprFrjhj8ZaSVo0pSrdmOdMXeSiGkosxzaLKa8U5aK2SUuajDz8wwSmF7330Ie9/+JjzS+HpeeVkk3jt1WPu3jnmaJM5Oz7i5o1jXr59xp2Xb3P3lVvcvXeH2y+/zObkFCXR5gVJ1fAP2aBZQBIybWEyKuw0HaGtwnbDl3/0d/BTl1e8dOcdvvr1b7OfhQ8/eMjP//wv8Lt+1w/z1ltf5jvfeY8P7t/n9u2bHG+3ZIUpF/ZXT6n4du/gjM3xE4Ve02TYS/aW66VktkcTR0dHHB0tnVqdveV2jFVy8HCJjkO+ng7gV3E72JWAYzQMl17VSqYb0Trd605Y1ZK4Mlkj/9frRiKteE1G7PytUhyz6h6CpydV6WXV9NEansKaRZnxpIV3ya57Sw9eXV725+tZqpXR+6zj+92B6BRIahuSngJ/CPi3gf8J+FeAP++//8df7zwpJU6ONz5QHu+5xlTwOE4HetpMS0ZutbuEPU03mGQW7g1CT3wmrhsFHGNnF+nIf8pW+isen3aBd08hiTCtLH3OqW9BXbwd+Cb2GHArV0q2zkZp1AuEFxFmpW+SIYld2/Pwwce88tJtHn7wgIePznn4qHI5Z1pVXrtzg3/kh1/lxqlZye2UOT094s5LN7j36k1evnOTo2Nz+5dW0Xkm14Uk0EpB8kROBS0Tkgo5W9mydbVN1No4unGTt3/sd3J66yWOTo75+te/xd1XfoDvvPtdvv3Nb/KDP/Qj/PiP/zDvvPMN6tLIqZAFzk5OeHI5c3G5IL6HgrZ1eaxtALqItRLb75c+JzknNleZo6M926OjvkdDSpapiRqOhMXettnJ0rNLUT4cQjHqDugYgC/ijksS660zCnUUBzEsfvT5R8wb8do11AoVQFO/lire+svasWm2/RE6PqIhtLG+QzEFAGpKIYDntcyUlElNIDc2KVNLHntw4BvCeGOez00JYLH+X/GbK8B/par/s4j8HPDfiMi/CnwL+KO/3km224m33rxn/duioquNRpK1jU1IqzOrOsOrDc17EPWY9vBtp70pgwjahOp+3NgSSnqVosWn2RtRQC4FFXpPQvuq0ZJjJ1g7tWvp5ELuSmC7sS41ZbI2XFOZusWbJvMoNtEvLnnX3FQciRaurmZ2VzuOjgrf/sZ3+eTjHZdXyl4rd25u+Omf+HFeuy1cXD5hW7ZMpbDdTBxvJopvalKXxXYR2u0MUU7Ziq8QlmoofLjB2lj3vkBUyblw/NId7grsdxfU/Z5Hj8758R9+mwcf3SbJwt27rzBNX+E73/4ujx494s6dM7ZHx9w4PWJpV6DFwbgR5/ZruPJrQYxJHk+3hXmp7PazhVdRoCRugSONFj9pWMHYjwDMcq4t9rrLTuwXGeGYrMMABqchBFQ9E2WKxdZZvw9tthFNb0Xn6UTTqCQytTZEqrdaH2pKZGywasZNEDFsSRxkBN/stQ7MQbA+D5sy9XAD1i3V7cY/typCVX0H+N3PeP0B8Ad+s+fZbibefusLpgRWfQPX7cOW2brQLMtiOV//bKv0CipTGoNv3cMGVhpWLGXSm5CIo7aRzxchTeaS5smUQa0VqmUxci4IwrKvvSptWepotKEQNNKcrXbcUG6jIJe1x+A02KNSLOdbbMecXAo5mxKYl8rTpxfsHu/4znc+4ONPrmiyRXjM7/kdP8I//lO/m+++8yvosmW7mTB31brMzPOe3dWOlEZ3ZjAFRsLYlqpordTZeAWkjDRvOCpCyhPTBpZ5pkwTpzfOeOsrb/HhBw9477vvc/v2DWNPJrh392VSEj5+8AkPP/6Yu9sTTrYT5xc7ahuNYmAoAdPB2pW0vei/FNTZhIssQ9iLhxHi6VrHGGLvQTxOl8QAZA9CkHVOPxQEQCLJAPIMzcdz7epEnlAgZm3XnPwDbMrvKWoHAsOyNTTChZFNsB4MKWmvAVgXFsX9qSrzvOfy8pK62XSewNIqfQMTdS6Guxl9N+vPOJ4LxuA0Fe7de6lv+NC8pXNQIpdl8Yo0J3pUsxCL7zNYXRFYh5qgeTrpYmRd6IhxgqayUgKmCERAcma73TJtzWJXtTZZdRFPdZmCiP0J53lmt9vZphXLwjLbpiG1LiwVmOkhXlA5a10cVXbPQ8R6BRQT0GkaGQsSlrtelAeffMy+VsjKnZvH/PRP/hi3ziberbO1kBIDTpMoS13YXe2ZysRm2tregmkipWbtuaqnp7yrkO6uSEvFtnNS75VnFWs5GV99lzKnZzfZ73bsrq54/33l408ekxJcXFxydnaTl2/dpqTCxfk5Dx98wK07dymiXO2vQDMRrR8CXtoF1V9wy2rNY1pgRGHdFWjJcv649faUakfGRZzpOZib6zLz0dZ+bG3+/1H3JsGWZVl61re7c869r/PeI9yjzayMrMysrIaEaiRUqEpCJiRAJhWNGNAbxoQZIxgw0QwDwxgxwIwpZhiGRGMgoZIMFaXGpMyqysrKyjYyIjI6b5+/7jbn7GYxWHufez0qo0BSysy5Zm7v+Wvuffecvdde61//+v9GFY4x4twIMx6w3wXY30xN76CRvXYAXn0blVmqZVU7kObR32Ixpsyn/+6a7Nb0Pqipf6OOOgtqzGKd6hrEmHDSeAFlVjYybYzevOBBwDnH9RsnqNuwUFIVn6xUT80AcnWj0SDQvjbr7zeUeK9+28Nh9fK34s/s9eaZY7qmVt4xDAM2WEo9UcQKVLGOknNNOW01AclM4ziDOiXlWQocdmloE0YdtxPr1YrNesO0nUhJB2xGO2Jq6uddozpbsEJwYFLiaqPCK1kib967zedee4n11bm6EKFDMcF1OKd/eEqFGIVpShgzanrpdCM6p2IYjCPFOHyB4IVsN0jpsCVo+7A0tNkyDAvGruPo+IiLZ6ccHyzZXCUeP3oE1rC6Grlz9y4IHB0estqsKGnkcNHx9PQZYgLN2/GTqPcnP29068YfaFp/DUjUIFnJVDbX77fTt8zprxWZZdQxZdc1N4KObu9azCL7hp97AGQrBWQPGTANnH5eGn838NOCRs1yRNeYc039uP18AwB3giymopgieS8Q6HVJKYNMxFSwdtrZ45WixrQtq5GCq4daC4af9nghgoBxluFgsdOWa67Alf+cWvrfgkOKu7KhqRGrDLzOZhlTdft2s+gtCLQ019QLq90YqcIUBtsFQufpD5csj484PD4kDB2hCoHEmMgps15vOD87J24mckpay9ZWUqtxtW6s9NKciTGx3W7ZrDZs1xu2mw3jqL+PMTMApcxJU4HSRPCO9fmKnB1ZHM5mXr93G5NG1us1LnhMmuba1FaiUimGmArrzaR95KwdgY4CXYfxTt97TmQq2BUnBe6MIKWCpjhECqGWA94I166dcHb8lKvLiVOntmnTtNVORu22HF07IE1bDg5vkVNitd3uMn6zA2trVV2/wV4QaLoBbbO6HSBmDcE17scOy2kEo92/Fhg0APq9rzvnZhDX1rIvzQSdloPvsRClnf3Vdarm6g2H0KVU2Y5tI7c1vlcGzSSxivzvMIoGDtaBpbqeWsfAOY8UmHImj4kpZaaoCsPGatbkfFsDhmDrGLNz/2RbhD+OhwEV06xuwxoMHK6xq3LGhoKtJqElBfwebqAsu50arQJDNQWyrR6qqX+94K1DrIyzgBSdeZ+C4fadm3zms29y/fiYZT/Mrr/GoNRUEcZxy7Pzc979+AEXZxeq3jsbmFLBoIYQSw1mkWlaMh1PTNPINE6VoKKouGjbe+5qgNbiXR94+NETpjwhUjjsPXduXWe9umSKI4uDgWmT8ZVcVnI1yTTqJjRNo56e3tBNPWHo66ZzYCymCGISGQdJF1Aqev0cKm3tqhnm0HX07gT3mqbU4+qbPHniuFolNUjJkYvLK4xxFNc6P9dYDIGPnpyqfXrNnHeboQaCmgrv23RpzN5Ti6pdE+ftPNhlrcxSba27E5yv9G6jU6iVsei8V9PW2gJ23s/yWxapo8+x+iU0V2qp8yZQ5YgBi05fq0CsBq69NS1VMUmg6TAKorJhpoa8VmrUCURTGYWSC6Zo+1MPxVwPhyqhnnUKdrOZWG3GmtmF2h7NGINyWSovpquTsJ/2eCGCAFAvSJszL1VUsgko1vhrzGzIqMWyrWd5TfXsrjWzG+ypuu+7FfWc+pBIwdpQQTDLwdGCL3/pS9y9dYPOOlUCqmIVUgTj9DlKHzheLuiGBT949z3G1QZPG98sOJrl1s78orkdxxR3TjZZs4g29ioNBap/bk6Zvu/IsWDIDN5y82TJ3VvXdcHGCW8dWZUqK/qMXg8nxJxQNmOHSBsk0dkJ50LtatjZ284aVb4xYnFY1cHPmVImDbgp4a3h+OQay2FBGkdW2w1vf/9dyhTVqcg7rtYbuvWGw+UCSuT6tQP8x1LpsTshTKm9+edaEuxRq9krD+rf6qyZAT9ojFCDqcCgDtg4gmvEpB0Y2DIAxUrUP9H3KunmvcNZQUqqvfm2uavojHNYuzNxQ1oTu/7V89/J3DVonoC6xLUT0zALJfbYquZc10pzXZrJSXvZZQNRjTJovatiJxUA14ADYoQsuYLfzGPIn/Z4IYKAiMxDICLVIKSmQG3ctEhziM1zW3D3dZnlmRuUKjVNK6J1oa2QsbZ3dC5Bef4a4o13YC2vvXqPV269hJU4O77suma7G24xdD5w5+SEq1s3eBAfYcrc3a30mD/4Pn3JhNQpeCg15TN5nribbzgKyOVc6LqOZ0/OOVz0TKuRG9eW3Lh2QE6XTJsR63xdAFJPJltlzexcIolQffRUQFONWXpc6JQN2QX18jN6YvkahFJOpCkiZYKKnLRW37Bc8OpPvM7T02dcPD3j/fc+pDs4wAWPD5arR4+5/tp9FoeB12/fojhHrJn2bHbS7nnKynqbUnUG3jlDtxHglJOekki9VA0wq9fXNNOP3WbfUW73WaWW4CzBeYy3dL1nuRz03xDoguImuvk1qFinMxK5BRyjLcnnPf524GHLCPfVhubAZndiN2ZvBH0epW4BoK21WtZawGPA62v3JYBxsyNX3fM8h4iZMjMQP+3xQgSBIsJmHGfxiYYFgFqRSZNUbuows+GIbvICpOq9B/VCS1V8EcGW3bjvzCgslowoS9Bruj4slrzxyit4q09qiqq+itkBM1BTfPT7g3PcvnGT09Mzxs1Esy0zc5+qMtJo/VrNTKQUAvXMs1lLjvrsO2KLAbGELnB0dEDnLYeD52jhMSRyjBpM0oQ1shcE2KHkVkVZEFSYMmYk6yx9MSiKXKnLVOccbR9qBmFqXZnHavSiyxSxlikmDk5OuPfqfT74wbs87j3juMVkwys3bvDytZt86Us/yeHLt7mwjlc++ybBd5UNqc7KMSamcWLcbLi6WnN1tWa9WrMdJ1Kqmz9FpikSp1QzqT0rs5RJWXGaVEk6MaoK0zjWztIUibHs7VGZna31/RmODhfcvn2Nm9ePOD5a4oPbtfycweYqse41YLHXh8+i5p8tIDRPjLmXb9qBw4y3wK5jYZydy8Z2dtTEYDc+vYc1Wq1L5wMRYeasuGrZbmllZalqyy94EJAibMdpbms0JJ06U16Kkh9KfcO5uge1/m0uO6PKshd1BZ6b+TeymxxstmCu6HBKtMKt47tcWywpkmjjp3r6VX9ho6PKsvca1lgWYaDrezbrDbYUUhayMcwecbW+nTnk7IBLa23FQ6xmK+jPO2PIkjBGpcYPTw4JvaXvDN7BdrPGl0gbJjG26FSjVEkzSzUx0Rpcs4DEdr3m8vyCLIYhF/rFgszE1ek562nEG8OwGHCDeje6rodi6ILDGzubeogIU4x0NvDKq6/x4evv8fjJY+IYsWJ45c4NvvTFL2I3W55+6zvc+8pXSEcnlSrtaPz6mCJxOzJux6pJOLFZb1ivN+pBWQN+rO3XnApj7cBQVC+xtY6VswFX6y1Xq8jlasPFxYoxJjbrSEqaweiAvq4frA7ZbE5Gur7jYDlwuBQIlv1JR+c9pRhsLLV0rROLe2XsrtO00xJs+p77pUID7mbNiUoSU3xK1amoYF+bH5gnJ2tHIVeG5XaMSviquFXrnjhn51LF2B/tBt0eL0QQKKWwXm9qLWvqQEU96WkiE2YmXDRZaan680VE9dcN89DGjDHE3QluaYKiSgHuuk75+cYTbeHo+BhX7aqTpDqoAXOeJbWtVvdyu1k2WPrFQHwcMZXFJXvU5eeIKrVglFZreh0sagw4vQS6ML3xZCyxRK7fvMHrb7zKt599D4PW+sYUsimVwiwEu1NP9l7FMvqur0IaeqquVxtSzmyu1iwuLhHnefr4Ge++/wGPn55y4/iQl++9xMn1Y27dfYmbd+/SLRbQBULXaZpcSTCC3gPfdbz86is8fvKQpx8+4t6du7z1xc/huo5H777Lh9/4NjfvvsLNr9wn5qroZBpgmpl8xPktNvR0i8ji8IDDcVLOhUgV0ax+hVnpwaURyEohxsp1EA0CF1cT5xcj7uk5KcPlKESJbHMkp4xI1u5Hrh0hB32fGceaKe0aA/O9sabo78xg4Q703X8I+4GhUIrBVHUiV7kfzu/aj5rZlj1ylpszt1IBwd3RoWtwbofnwjRploRtVmOqptX5dn92cnmf9nghgkAuhfU40uy4d66znt0l2IEb87DNPigDVcRS7948a021pzJaJYkIzulCHHPCFkPvLUkKbggkpOLmvm7mesPb3ajgZEUgNJIXgw+2pnrVh4Adp1z/PsGJmze6tOcsDTQq9ekNxmhQs0Vfa0oTi77jjddf45u/9S21m0oFcSo/bqzD4BCnjEOLjlyXSiIpSYgpIymTpkwcExtzyfqHH/LuB6e8/cMHPL04I/SOu9evsVptuXPtiPFqRXDCzZdfgt4hkgDNqGzWRR2tYIthORxw89oNelu4cf06J7fuYkzmlT/zZ7neH7P6wdvc/Ke/TBiWgGZoiFCyQWwhS4cxlpwS2SfKUN2CEExRH4MmtZUlkabMZlIMIdbWsSTDOEaybInJMKxH+uWC7jKR3MgWR8RBiVC0LCpZCTfLpASwYgrF1pZxBaHVBKVNPNimbjKr9RhjdIy5phdSS9SYwXmLMU3QVo1mpR5a1ug6daIehiIFkwu2gGuAYM1+G14kRiXMiyQSkW0e2UwT0jgCMHMm9A1ohmjlBQ8CmtKWeUvv2FPPb3KowLmxKqbYTle7U5t5Xs2nZhR112mapvnZNE2QVbiztRnHTaSkrFLfey8skhVmkeZi2+q0ujhyIW5GXFFAsBRpQO4uEBgQVCGm3Q895fLeDEO7Hmhtn6EYw1S2BAZevn+Xrld/hWmaGJaaSZSisw3GBYQ6azFmpmmLMZOODTeNvaLEmlgK77z3IT94932s9dy7dczh4cBLd094/bU7XL92nYurS373d77O6xeXfOYLn8cdHOBCQAykChzaKdF3PYuDBaHruHnjJjcOjxk6x5033yCVgXt/5Cuc//1vsHl0xvDaibZ0TU2BDYj1WK/BpIgCt04yZie4txu3zQWXPUiiLxbJkVImEEexqQKgVcwUSzGeZAPiB7IdSSjAh83qiGwMFGGTC2MS8izdLe1Yn1N92r2vGZ13bmdcW0Q7rqZNvu48Ip1Vc1T1GdwpKe+G3GoZWOqasTutgef5BHbGbPrlwPEwYIYFbrUhRRWRnRMTW9uNYogijVz5Ix8vRBCo/b8ZWNG+8CeCwLxJKspv7XxhoAWA2aNbA0VRDj2fMB+1VjnZ1tlZx85Yw9njU87uXXH95IRg2h+299hPqWptFq3ldHPJ6ekzRdHbAMje391uJDBz283cqjSae5j5aWcvPmNQvropXMaRG7evc+3mNVabLWOcEFShWQyItSAFbzUNnKaIqRZpUsBUld9UJbnW20Quhbt3r9GFjpOjY4bhALc44CJ23Ll2gxuHh6T1mtXpE549POH6rdssT06wXTe/P5+FcbNlebjg4OiItDIcDAve//Y3KSly5zNfYHHrJvL5z1DGRBwnCm1xU4G9adZVjFEBT6TUPreeaDPVNhfSlEm5EIuQRa9fLoVtzoylMGUYs2MqVj/aQHYdxhccls7VtLnTmYkiGdv1iO+gEpM+edv1IC51mKgeWDV9b+tyTrs/sWxah6N4aP4Gc4fB7LNa5Q/83v7aaQFDnGV5eMDJcsk1Y9hOkWkbGcet/n1FOwIz2a6YuUPxox4vRBAQFNG1jSFmUHEL25hXZq/9of9v/XSpbcJWi0G7WChhw+oimee85yxDwcEiglQ578cPH/DtB9d50ztODg7oAScawyv1g0SZV8VYMo/Pn/DeBx/w7PwcmwqJCk7ut4XaJyK7OFLrAWN00myuJefOR6FIxNlAzJHewdHBkqNrhzz+8IG+J3QE1/uOLBaThTROhKrWo4NBSacmc5mJU1kKJW4YbCEsB3AdHz0548OH7/HtD9ZMacUv/9Gf5ud/5k3yxSPu3b7BtL7P+vKKrl+w6DpNjZNea28hZ0Pfd7hygDjPP/iN3+R3/sbf48/+hV/j5Cc/x/LVV3n06Cmn772HDV7Zb1DnLyZiTMSY5xkMa2DognI85vunJ+s21unCmJnGqB9jYpwiOQmrTeZ8U7jcZFaTMCbtDHQhMPQ9XdDsSVImpRGMcHy8YLHQKcz9g6XtHU3hFVRsehXOGaTqmqrzYy318k4FyDRMwe5F+baKf0Sdvk9B3v/YGJAChL7n8OSI/vAI13cUo3RiqaVvbpT7klUuLslzB9MnHy9GEBAhlazL2iiQYmQvsrI/YCK1Nt0BMPs68jM6u6dYW8TO39ecztKcdtuUoLOGzeWK7/zed1hfrLl75w4nx0ccLDTNdaK232OKbLYbrlZXnJ2f8+TxU87OziibkQ5L06lvbT4pjQpcI/2uC4SrwSjvvY8mnCIiNR1WduHWCMH13L51i4/eecB6E3HXlxQrYD3n52uePlupbbWFw95z+8YJQxfU5wCDLQUpEFNkvdmQC6RseP/BR4TFEbdefpnFxUM2T6742S//HF/60hssQmazveTw9l36xYLiPBiPt45iCilNSMosfeBgWLB1HSe3bvL4yRkHl5n3v/41upvXOLj7Bo+3W9796DGh77FBiUolS93AiRgLOSYEZW/2wVWSj62y4dom3kwT2zGx2o6s1yPrMRKjthCNMaQxs15Hnl2suVxtKCkRnKP3gT44us5XkLFgxIMpXDscOOo7gt8btqkQgN4PxSPszEEwIKoNWHNP3eBi5t9RLkClPDudEnyuQ7TfcpbnZw725ynaYwa4naMfepYHC8U8up6Ud1O3DUTVdruWUPlFbxEikJMgrkpGmQrx2eeHTfanrPYj5b5zTENu9xV7zUwS1g1pKo86JSH0OoppU6HrPOZizcfffYeP3vkhZugwXcB1Qfnp1ijaM2Uk6uCQFB0j9kVFHErFJWwFZtrQk3Ee1wUwqiCTJsUfjG1utZVF16jPFhBh2qjc9+X6kqFf8BNvfoa///e+wfnFJeb+TUQyp0/O+d7b7/Odd58wblccHy64c/OYq+3E9aMFR4uBoe8VdS7CVIRNzDw+W3FxsWGzTXzu1Vu89cW3ePn+HdZXr/PW6ze5//I9rt2+yUhmGDyY2qr1VRfQO2KZFMlOmeViiYTErdde46d+5iv89l/9dR5ePeT2Bx/iFy+xvpz46MmK0Ec1ZrWekoXNFLlab1mvRvWYRMfLhy5gbZU9EyEVqSBnYTNOrNdbLldb1puRmJO29ACyZhTr7ZY4KcOx7z2d83RBZcwUlTcYk8kSOeg9Q9Dgpim7w1FwRT6xGXfrrwV42BF8LLpJdw7XmppLsYjYHdLf4ox5PkNoDMmZMOZ2ztmllDourcpV7b30wdPZTHKWnC0lO8TvmIeJguk+fav/IwcBY8znUW+B9vgM8J8B14D/AHhcv/6fisj//oc9lwBTUSBIqav1gkgzB6lMYQPaQFX41YqaeRRc5QcYTYGbVJm2GvTrMJONYhZ6H9TAcSskZ2qqrid4zpG8TuTTTdXFtxS0FdeHoApDRs1Glcyk9agBXWi+wxi1yg5dR296lsOCoevBWNbbDZeXl5xenermFyAr+p2rRbb3Dol641WEFc7HNd1ywU+89RN88OEH/PTn32S1inz3ex9w+uyKWycHHL98xNBb+mFJ3EYenF/xbBi4c/cG924ec3S44MiecDVlHj48Y+gXYD1np0/48DvCraND7n/+DRZmy7R5wmbsCctDvAv4YdCTr4KlJqtc1iQwWsvxnbscGQPF8HO/+Et8/7e/zsAR167f4mp7xQ8/PuP337ukr2PatgK8MSUuLzdcXFyx3owUySq4YnuoIKzMHR8h54oXzW3DpJvIKjZQUiSOW0xOLIwi49ZCsGrj5k2eqcapdjk657A+6CwBCqQZ48iSscWxTkh8AAAgAElEQVSoI5kxpLapRaf3mpKwD47dStPMVZWjLN4bFfs0unS90ecjZ6jiIg0MLChu0Q6xBnY3+jBowM25IEb1IcGoKhS1Pd2AxaIGN5bMmz/5yqfuv3/kICAi3wF+VjepccCHwF8G/l3gvxKR/+If5vlMHeU1cyujbsz2qdmd/qb1UUupQWD+o6pPuy4OTdXMcy3FxiPYmmlm0/kqHeZGN89eixhiyRo4UK528J4ShNyHCsAJpSRi0padt4Zu8KRJa9AC+OA5PrmGM4YUR00pxXKwOOT8fMWzZ88qcNd64UUZaI6ZO16MkpBTzoyx8Opnv8APfveMD56cYaYJKYk3XnuJa4cDnffgBy43kYcPHnB5cUV8dsomTyw7z7379/nyL/wiX7xY85f/h/+J0weP8N0J682G8/MrrDFc34y87APDsNCAXBIQdMbBVr76qHhDS1tsw8MExjFiloE/+qf+GK++/nm2neP08oJvvvMx3//hAxad+gp2vsNaQ0mRzdWG1WqtrMAaaNRMpvL+VTueZtltqw6Aau7Vg6MqE5mmJUFjzmlppfr8IE3Gr2oKOO/pu6p03LZxxW+8Uz7JNkaaAvU+qGcrYChZ3aOqUn5dbVTMp1GZVZ6uVKGLuUQzZmb4WWvnbLJlAQ0gbKxAyZlpu2XcbHHeQ69l5+w8PGcZFbPB8srJ7U/dez+ucuBPAG+LyHt/GCnh0x7GGMLeqGOrlJrI4w7Mq3W2tDRLL5CrVN0shZJUfnk7KiVVU7AqFW09kEkpan9aIPimC6iBZej0hJJiGEsiVgXbruvovKOvkmHBWXyVpEp1jDhhCEaYRN03rbNgPDlqTVaibu4YE2MUtqPlYlW0z120JMpZSCJIbRgoEUqIGcao6LlJheHOZ3n/yTk/9dod3nxdZwIWC89qnfnG773Nx+db1psVt28MnCx61pvI+bMrwOOGgc+9/gZ//OwZv/6//i88+PgBpXiWJ7foh65OCgbSdkQuLjm87smpynu5oNN2Ncju4zUqR6K8j+s3b/D6r/4ycXmHiydPWZ+f8s77z1hdTkSfcUx4u9XaOk/kUbEFJ4KTvcPA2d3nlcFjRbCitt2aHOo1khyVeFMSVjLOKOtU6iluxGkGaVrdXok1ztE5S7CC96aOFle2njXzBrSmhYg9dFdSzTjz3OWS0tqGFSbYX+y1e9M6RFKDgH5rpyfQgsDsYtzYS3VPxHFku1op32AzaoCu2ZChcQU0iCyPBo774VP3348rCPxF4L/f+/9/ZIz5t4CvAv+x/KEWZPp4btBRgX+cqX39mhLOpzSaxil41ubKjRpcpkIcC5t1ZDupIUWqIIlxSuSZUqRMGol93djWGQyFRW9xxiMYppwYcyYZUSfYrmM5dAydY6iCopJNBawU6EsS8VbJHMZaDrEMy4zkRBoz1nnGKIzZcD55PrqIbKLaaJVYdAaiZREiNdMxxCSMSTMcKwVbBrwX8B3HR4c8u7jk4fnI2+8+YG0P+PaHP+ToYMFryxvcuzngcsZmw+XpGRdPntLfvMlX/sgv8pOf/wm+9g++yu987Xd59uSc9eqK9959l5w2vB5f5+TWTTwZk6/jlgVjPWsRyjjhjYAzs3SVauE1lWTD0/MrOneTm7fv8n9/9R1On1yywGETOqknk26IkjFoAEgpsVPpERCdaaAYTKnuP5XrgKhMmqmdF+/rZik79qWCw1LHjneu1KYZwViL7xxdZwmhgn62iYzUScUG9H6Cy7HfPWjtu6Zu1YA/LWWb3uHuOqnoicxmIfvPvc9/mUeo94HCnEjbLdsrr+vbqNiNlzpCXwNX5wPblFic3CeHf4KjxMaYDviXgf+kfum/Af5SvU5/CfgvgX/vR/zebD5y7drJTOKZ0VHYzeSbKg7ZNANzxpRSUyiLzRlSgRghZsqU2W4Sq81EHBNT1s2VRJhKta2a9Ib7yrLzvhk1QKg3bMyFTU5EKSxCz2LoOFgMDL1nEXQuHSDGQkw63XYyJg6HnhITRTLLZSFJhzeGcYqAJWNZReF7H53xg0dbEkryUEacAiC5iI7yWm0FasZhKEXTu5w7Qt7y7HzFvWtLzlcbPvjghxwtF/zUW1+gHzrW55e8dHzAwntsB4nC+mrF5uxCT92jA07uvcKf+lfe4Gd+/hf4va9+jY/f+QGXZ08Zry5ZPX1CbwsuTRALMo3Y0Gn6T8GEjpLKjuveBe2zGyH7QDi5i+SJJ08u+b3vv8dmu2UIgXZENusu55QTIFKwTu8plW/hgse7gK10W+89we/0+0w1mAF27kUlo4MFVXvP+LnVbHE1aJXajrP0wXKwdHS9CpSI2Znb7DId+/ymVIQZY33tR1lK0XVapMwiOCnpSHNtDJGl4KvPBGUHZO+mHf8gEN5Ukva5LilG5GrFdjPpQWEaLd7PQSx7ZcCuLzdcbcZP3cM/jkzgXwB+S0Qe1j/0YfuGMea/Bf63H/VLsmc+8sor92ROofakxFPWaG33oqCUQolRzSSN1opTAcmqtLKdCuM6sr5YcXG1ZTvGipBapgLbmNjEzHrKc6RGygwUIehNArY5s02ZKMJh6DhYLrl2uORw0bMYAp13FImkDDHrVNyT8xXXj44IbZrrfOTx0zV3btykHwIZpbu++/FTfu97P2SVDVJSnZIqSu90VYtQmjpSO0UqgSjV0di05ezAcvvI4p3h+mLAdcD6IV9+5Yj1kWCL2pQXCyYI6zRRkhpuRgERyzpGDu/c4Ge+8mVevn7Ms0cPGK8u6IPFl0JPUZnyqoBUjDLiohFMsRivpCubHXgdMlocH2NlgM2Kf/Ct7/HNd95jOAwMdiciYp0qEIWGKVQxUeuUZmudJVQxVh883nd0XaDrqj9BVc1p3hIqyCKUnBQgLpEcM6XJnUtt0bUhsDodGpxh6ITeJ7x3e7yN1nrW03se+DFmPm2pE6G5EaDMrlzdNw8xrZ7f72plHes2leePtAwC2jTtjkLPc0FCciGWiSSTjlA7h1iL8YJRxVIKen3PHz3j6ZOzT93AP44g8G+wVwqYajpS//vngd/7f3sCEWiAvrZTMhRR8kvJc7onVdV3yjoqivWqxlISVlRtZUqFq23i4vyKs4stUxa1jHJKEIljYrvZMiYhlso6y2Ca2YRRNR2rYZpiHGBZ9zq0UnJm3E70IVTudyLlyiArguRzPraPGfoe62C92ZLEcnh0wp1rR4S+4+PTcz589JSUFM8AVLxDIggq7KGoUgXD7EyoFFHeviWBEc6iMCWhNyPXbh4xdD3b7QaJieNlT8pCLII1Qt8HVtvI1eUVcdwyLA+wk2DIrGVUn0ULJU4MnaoXi+2IrseIoe867YZsR5w3bOIW7zo6F7DGVVaacuw3l2eUixXnZ5Hf+dYHhEXHy8tAqAF2Zk2is/G2Um6d8TM3QJWaFa9xzmoA6DuG0M2tMqACvI5sKqJeKpZSZelzA5FzFatpCKYo+OiMdg6CS1ir7tG0iVVRsRcDeGuIVlD0p+CqeIer+JUz+s/WblYfPJ0zGKsDcDFHVfkxdWIwVHm32XhGD7pUCpk95yKoXZmde7aOz2u3QiQRaukoRa3gm7ip85mctnzjG9/51P334zAf+eeB/3Dvy/+5MeZn9Srz7ie+9yMfOReenl4oAFLTHaU86ujorOWiM8WUKTNGHfUpWVuLzlkyMGU4W215dLpiO6kRpaKw+vu+JBYGvClEhEn0Y65lhqOyBG2r5Urt7UPOWzZTpPSBTaXpxqJAmK5/5fHpvECdH7CODDx6fMr3EawPYB3eBnoXsEVRZWvblCQ4jQTMhJJaChbaOlF2ZTCWNBWu1omT4Zjr1zYE37NY9OpLJyDbCWdg6DusZKQk1hcrtmcj3bFyMcJkCBthfb7CSqZzjs3FOcEdKb+gciVaCptLoUxJ/XEL+FpLK0Vbe+ybbeLJ01Pe//iUp5sLPvvWm6Q9pBzTeuIgtbnWNBCa/qBjZ6WlwqJuVnu2FcnHtMlQS5KkWgm0WX5q4K7EsfqxkbakInQGwZG0e1AdiJFSNSn2CD+fqNEFsJXD4KpOhfM7CzpQ1H7Wnqy+CRrfNeORiug3Vaz9TMEaq67He1+DBhZX/CE3tqzOCbiSdc1ai7UFHzxZMu+8/c6n7r9/XN+BFXDzE1/7N/9hn2dKmfc/PqNUq3EppaZCwjhO9aQ1qBmDwURhSonNdouzlt5rzWesYcrC2dWGy/WI9R19JZB4NZjCWeg7wyqr4pBe2DIrAfm6EW3RwKJDQ7V0kKKae5Oi9/OQSR17Vkfj2ge2tT7MGRHL0nmK8ZjmeYgQTGLoHKEy0IwL+hx1rJg9ffyZTgqQtboNBoIduRxHDpYLDg8X9UzStDHGhHfQ9x1D35HGESOwHUfi+orsYBTo7Eg46VifO955511kvYYcdUhrMWAWyhUQ1IyFECipoA0VlVC3uWYsSQ1WuzBw//U3icsTbm8zi2u3Z+ZkS3mh6frvOgyGNgUvWBpjUN/87C/QSjdqIKlYQExpfj49+aWKkmSajv8+sayRaawBI4k0QZ5GJMl8+jdmf3O1aqKlNWffMTzZo4S3+yRtg+6+2ByC6l6ZOwP7j7kzAEg2s5S6Xr8mQ2eQQrVfU45LwWBzmdWhjTWKl2WI06dLjL0QjMGYCh8/3dQ+Z5n5zyVlpilWxNzMqHlJpYpQbOi8075zXVBTEWJNnQ5cIDjmf7a2C4sYyBZjInlEzTaMbjrXToqi6WbwelMO/E6ltlQtPxHBSsI0RLg2p40zWtsLsx5+Sobgerx0dKYQOsswWA4PPIfBMwwdLhicEbypp0jri++j0lLHakvBW8HmLb2Mqthcx4cThWAymMzQW4aFBykk0S7E+cUZT979Lt3xku7kBriIWOH+Sy9zdvsO3/rtrzFYx8EhbNcbXNeBDSTn6RcLvQ4mVFHOibSaGEqhrwi8Ea2Vrbdcv3mDz372MyTX4bA8b5Br9pBxs7eJ2uRelX4zBqTy78384+1H22+AZHLeCwJ15r7V9rsA0ILAHtE8Rca1Y3MFUbb1+YqOObYXMU2msnZEjJl7+Pv/mmDK/C7nzoI+j3eupZqzcAnleQp8E5lp/Jj2dWOqfD1ULUEta0Wqbd/czlSwEMBmbR1+2uOFCAIpFZ5eTLvBh5xVYTWp3XLGEgXGDEkyKUcdKRXPehs5iyttm1mH7VTfbtl5HGrK0flC53anR8rCckFNSZU/jzHVF06DgV7SQu8dXecwtmILNpCLqJhDSpQcKCWRqTMNOZMyM+03i1CMBRfIJhFywebAgVtwtAgc9J4bBz1HhwuGhbIRfTXFEGufW+ttAc8ByAB5ojMZn7fYtMGgKLk14K26HNuSyVK9BoCL1Yr3334P3/VIOORvf/WbeC/8qV/6OT77uc/z+MEjHr//HtvTM4q1LJZLbBFMKRQKXRcUg9kokNdk4EuKCqpZIRtHSMLgOm6eXOd8M+FDmGUhNHNrxJs9WvecndXev9RTuFmliZ56O979TpsP4xXTKAURJeWI32169q7hLnhoGzFNE6RC6ROUXDdW29jNkYj695hZLFTm3v4uiGmQ+oNtvvZPGvZU23nWOiU4ld37Al1DUpo4q8wdClcNS4oTxDic1JIj17IAqRLkiotYZyi88JlA5uHTK63ZcqxGihrZSxGM8ZjQYUJH5wd6LUwhRVx24A1Ioet7hkXPMHgWwXLQOQ4OgpJ7qkS1ADFGOh/pg+EgKmjTbjJSMM7XRZOVINQ7bPDowLgjFsNmG7nYbBm3hckYJsqs+GKQ2v5pp1kldEqhrw46y1JwxrMMA31wLLqOw6W2H11Q5RnjKnBUU1xtIRZirlW0gMkdw+BIqwvK5QZywZZMkVzprwVbTTbEWaaYOb9csVlNuBtLsnj+2v/1G1w9foY8fZ9/7l/6s3z+p3+Wmzdu8vijDxm3G64uLhlOrlc9w4zpeozrMTFqmWXU+rp1dzRNToh4vLUsXOCsbIm50MQdrHXKuqx1spJ6cu2xa91LUT8JYxSMA02BnWW3OetQjtSxcWXj2ZYyVfxPUff99vP80RqM2Pk9BBdI1hHNTkf4D2bsz6f+7aA3tUQAWn9BsaG66a3ZjUU3+fR9MtJzD2OU+IQGtJYFqFR6oLMOXwzdwsw6nBT7nKaAZkNZVaen+Kn774UIAjkXzq/W+qbTRBNmc9YRvGcIjsUQGA4G+r4jGKNyTyViyoSRBc5A13mGTqWkO+/0X6/U4AYeqUefIS56YpXcynW9YAwltwUD1ghd5wjB4nAUZ0lZmKLBhMBKQFJiLI5ViWRb5tn9NuPvRZlqybiqN+/INpBdT7ae4gI2BDU96T39sqdfDEjbuPX4aeVR48o3ZR9jHC5YjD1idXlKWV/g0qggZRe0rkZPCJszm9WW02dXpO3E0/MzfuYrP82v/cmvsL244t69+9qmDI7rr7/O0b2XuHryWAVXO0+KEyF2Ne10dMsj8uocMcrDzRmUZJ+xxbFNhX4weFPYTJFxEkwlEnWdJ4iSf4L3+JohS7Ha/cmJOFa7ttrGNTVF9k0s1hRcMaTcWktNdm3XTgZqivy8zgPUMiHZytZMerDInty3/rY6Y1VRz0Y8a+Qhle9rhKl94EZfw1odU28dj4ZI2nqpvHGzBkSiBixFS2tkoc4d1E6IswooWk/vPd6YWW8x0VqTVWm7ThAWhKHbf+/PP16IIOCs4WThtASLjhJ1SGjhPItFz9Fy4PBgoaOTQ4e3FmelDkwkJa4Y5e6Hahse6siot24OAJg2vx6JYijzYdF02xSA1FNIAZYuOIK3mGKYpOhCNjAag+sKuU9MkkjF1v533i1c58hGe7YEvdld5wiDxw0dxQ9MeEY82XWI66C2yELoFewR9WaU0uYeUOu1rKmj96qdb4HQH3AenxCyDiBZY3WYCZ1LEBx9yKRp4tnlmqspcr76O/zCP/Vz/PKf+FWOrh2TRZHlHLekEllePySNI8NyIPQdYxlhY1kOB3TGsKqlm9qFqzJQo/GmmDlYDHgrrK7WPLgckZzpusByqS3UrvccL5Ysu45crd3GbWIcE+frS2KKWGtmgRHnHIsQ6ty/wWZHznrKaat5Z1y6AxztnMrPJUdpfpda+qdpYhy3TONYBU7LDqDeCx77bD5fWX/zsaG1gnY2GtpfT2/v/MwUnLMAY+bP20mvOJK+VlMn2ucHNEyiMuWURes1w/Dt50Vlzmc8UpjVu3/U44UIAp23vHrroLYE1YzDGEMfHMu+43AxcLAYWCw7uqHTXqtrNa9gmw4g7Nx/O4fvAsEqwgyaMqWcqoa9zAkbdeO3DDJXsonBqDmFM5AKm5QwUphiG+xRsCy7iHiLETurGOlK8Ij34AyuC3Sdow+qR1icZSMGk8BN4LYF36Hj006JLgZV252mxHY7sd2qack4jZSSWSwWLBYdRToMQukWJBMoecQ47VK0zeCcByMsF4V79+7i+guuNhtKjDz4+ANOz14n9RDCId5afDfQdR3np0949PFTjteJO/dfwg6WbBKRjIiOFMccSZKhMv5KziSt4ilpy3LokJz4wTvvs94WFouOk2vH+M6wWAZevaPBwxodstpuRlZXEx89esJmu8U7DXbeefo+cP1oUXkY2pJrdzFVG7udtLyWDM5IBXNTFSpVxeqUVIFYilCiyp7HcV1nS6pYbdmVY7M9GcymIUXsjN7PNUL9+XaSlzqD0ALAvvCntKyjBhpjjA457ZV/+98ToSo+WzV6cc1tmrnuF2kuTlULscrKfdrjhQkC928tKTnNUc9Zi+stQ+hYDB3LYWCx7Omq8INz1RiiZUpilDNuFZ13QX3pfOvpFtXeC7WnL1lmefLWoxahDvNoIKrtZIwYsotEKWDVHGUbhW1MpARSDAanPeasvXTltnvEdtjgGLrAsjd0TsAWxpLJ48Q6C9ssrJKSeqbccTglHUElEZOw3mw5v1yxWquw5jhNGCPcODni+HjBMPR1wwlmcUhOI5NkTMwYlAVX0Drbd4Ej5zCdJ5XCweCxOXH65BEnd28gPjOmLRbofcc4jnztt3+HsoW3fvIzfOYLb/Dy6/cRq4xKlxV0NLZu+jrBOeWINY60XLDsl7xy64TLhw/55vcfMwwDy8MDusFxdLzk/JUL7t66zcm1I5zdUuLIuI2snj7j9PSZtvG8pws9BwdLuHPEcrlUi7HglTdgbR0VL0otDpqZGQdSwcIpRuLUTG4jcZpU7yFlcpxI45acJiWOVR7IfkehHRS7CcJW+e899jY0Nfss6Hrwbt8SXYPAPuoPzGI0TcS0tSKfe4kiah7dgrx+tb5kDTANcDQG55/vVnzy8UIEAe8td64ttJdb0yvn9DTvg/a4+2GgHwZC1xGszP3iuWXUKHU1KDR6Z4u+pQg27VKr0qI1c8DWPmwSdDKscrRTJsf6scAUM+MUWU+FMSVyabSgWgJYYG7VaLpiO8+i71kGoXcZb3TIZhIYY2E1Tmxi1rlzUxhH6KzF2kyMhYurNafnV5xfrpmmyDhl+qCy5lKDknOaSndhIBlLjqOKtDhlPNoW0KxuVG8NIQSOj45wBbaXE09++JgJ7Xys11ts6Pjo8Rl/6+9/m5ATDx8/4vL8CZ013HrtDbBqQCJIldG2OjGZEnFcYfxCKcYSef3WMa8cDfyfv/8tYuU52DprPywWXLtxh8989lV+4Rc/x/2XrhM6y43ekryOT+dYDV3JbNeBzgcIytWjtJn76vzjdC20Md65LViYZbrjNJHGie1Wy4Aco2JMJs9W5Y0HIHUScb8daGspRk7zhpXapZjJPSgJbTcEuVuPLajsa//NTkVVct7IH2wzljq2bEwCiWBVBLciqHOmgbN4L1WSTPUlP3X//eNt3x/Pw1nD9ZOFsr6oNY01Or7bdXShw4eOEEKtr5jJEMBzCHpjpLU2zc5ium7SxlizKsCwg3N0BNRaARNm5qIYS86RWApjzGymxKbq4ZkiDM5jrQqTJGuJ1tfAYNXAonN0wTF0lmUHg7V4kynFMBVDNraaYuws1XScuFBiIiZ93bGKcKakXQjlFba/XmvfbGBylmg8TAXjhdAJJpd53DrGRBbV0I9j4vTJCm8D3/r2t3n45O+SJjg5PubW7Vt0RwOX25GDxQn9oFyCH3z/HRZDx892A8Phoc49iI5BYxIxRrajiqac3BwUH0iJ42XHr/zSl/m7v/lVvvaNd0E6VMVZODdnPP7gGe9+93t0MvKZP/8nCUPiatnB8SGpCGMWtllBS+8MofoJ+lCDnG2iI0qXUk/Cmj6XOrtfWYclFdVdFJ0ziONIiiPOqMbHc1QGdlhCXVI0+zBTDDZ4JGWadPzuhBdlL+a2yqQeUDu9AqQ0FQ19HZg3MiIIBVN2VOH9QJAmnZ/JrZStf1+zIXedJ/Qd3geM+f9BJmCt5eBgUQdRZE4vndcg4IPOsjdRBvWk3wEqOowh7T5UWfB6s+qwSpYqxS1lzhhsuyHoz2eR+SRvaZgR0b43OiQ05Uym0FnhpDecuAoCGcMqWi42kc2k+jAEhx8cR53j+tJyvDB0VvBikKLj0MUqaBWc4aj3LHtPZwreFmJUZWRvhM4Ky+DI1pBDYTEEJUlVa201Aykk75BhQbq8wMREiFFRaadA6JQKMRviVHjy4JzHD86ZYmEzJnCBz712n5/6wlu89sZL+MFyfP2Qjx5+jgePPuDB++8zrdc8ffqMp48e8XKvO8a5DkutySXz5OkTtmPi5XuD8iZSIvjAl37ydX7tz/0yHz5+xsOHaxyeJNpGsxbiOPJbX/0mX3zrs/zUF+6xGAKyGADDWISNFLJ39J3D+WrDXWXc1HKuIhG2omuK1un+s5VebEKldWsLVXJBYmSi0rdNcxdowJpmellkXjPGuKrlZzAELQuq0Ke+m/abpvpT7niQubYHd31K05ajfmwoozVQ9k72+cdt9WDQMfmYVYRGLNiSZ3mzIB3OqomON1aHcj7l8UIEAWMNvvOzIII1lTrp6+nfIuEMqNR0qwWA0hhhOxWW9lNN8UVKmQMBezXYPpK8D8DUT2Z02bo2u17ovMzA0NBZHbQR2EyJMx+52GQyBtd5+oXhaGE56i2LweBc8yZQHQK1qg54Zzk56DgcAt5mLAVnMjYKORgOh0BXraWSFPrgOVh29L3H+1CDo2rPm34g+kCaJlKMWosCMQmXq5FtLDx+cMmjj84psXB0sOClGyfcvHGTN++fcDQk0uYp/eKQfjjirbfe5NV7J3zHGdarK+69dp+Dw4O5BWmcQenDkfPzS955531effUefReUAFNl04Zh4Fd/5Rf4/rvv8z/+ld/k4mpCxNUOYAI8H3/0hL/yP/81cvoVPvvSkuWgo7o2CyKOOCsKmV1yV0O5ZgIJ8l5tPC+EOtHnIBiPZaB3TuXGLKw3Rl2MStplASK7zTqX+Rq01e7LUSSrTkVdYzuC096aqp2JVoqqf8CeTgC77GB+yVY61NO/ZQEKgCoIK0WQatgL1dsx52rNfoAJTrtcxr74vgPGoMagFc3UsU23a3/ZRh+twF9FfVtdVWoAmE96av1lmONyqRrs841grxWrtQMpqzuwIs4VkDE7LzofPF2no6PWO/resxwcvffq87e1DFgWzpDE4HtYLA1HS8/B4PHOYK220kQq1dg6vNGZ88VgWVRegzWQg1X/AFHNuyaXliXjvGOx6FXm21e9PptxpcMuD5GTEzaPV0wx4ruAYNlsJ84vr3h8es6jB5fYMnByfMjxsmO58IzjGd9975SDpx137hzxZngFQmRYLrFSODxYMAyel+69zMnN63T9QCmGOK0pkri8vOJbv/9tJAs3r18nxUjwXu9ByYhEXrp7wl/8C3+Sy8sr/urf/DoX56lumAJG0fZvf/s9Sv6b/IU//c/wuTdfZppWFFcIOm2Nt62M0/pYBDDKWsx1E5QUSU5782orXr36nMV7i6lv83EAACAASURBVPUddF5BZqvzFttRxWdlL3WWqh7d1lRbK60clVQzBKMYDbMM3q7tvPMlzM8dPq3lqa9TB+Vaa68eevPrNvaoAVf0MCg5kWKsMxPKsZFcatlT51ecjttrxvSjHy9IEFDfPIxRNxrndVTU7/VUMfPgSNu4gg765HraSKqLonVundXsot6UVglA43Kxi7JQ07C9Hm6N6MV7Qkgs+o60HHTopxKY+kGlxkpKbMKEcYXQW4o4fPAsFoGjw56h7yq5x8z1ayla9nhr8M7QhaCUXKtCGTkHfJdqwOnqRtrVjl3f63Wr78WVgut63NDTB0verJiuLvCx0IVCTBMpbqFEbt5c4s0ChyGxZhVFRT5tx0EOHN1aKKhVEn3w4HvcckHaipKbfKCIJaWtAnabDT/43js8efyUL37hC3TWzwKgoj05Sso4G3jrc2/y7//bf45SOv6Pv/41rjYTqrmnWZq1ge9//31+/Td6lkc3uH1jiUlbvKgugjUoN0SU7aezFFDGLeM47vXpq7dfpzoEfd8RbMBX4Q116fGk6AnBkZJFxFW1n3a4lLnlZsouLZjBRv0vjepcb848dQjaIsylKL13L9t8rlVorZKyKt0c2YGBbWnO05f1fJpfv5Ysxnmcq10LY8lS8YbaKfi0xwsRBKy1LJcLMjpJ50JXe8C+6vQxXxR1GX7+AhbRAKBKLqlGblNbR2p+WUpRRLilT0U0SqIsLGMMLmVVg63lB5W3rZ9n5HCohiWZLliGQVtRzqjWQQgW1zsOk2q8eu9YLAYOlgf4TiW2rbGYanNWpOnY62v6intQRSkyhpITi+VAimqm2WTUFZEPYDWDyVLVlkQFJvqDJWGaePj224xTxhotW64dH3Cw6JVYEw0xCtspk6VgpcOKcLAM3H/lZW7eusnyYMnh8U2GGzc4vHbC+elTuuVSmZNXK8btGXEsvPvO+/zg7Xe4f+8ey0U/s+xijDryK3XsNhiMN3zuzVf4+Z9+k7/9d36Xq23LBvIcpUUs3/jWR4j92/yxX/oCr75yHUO102rUbCm03kwpGZMn8rgBUQynoKzTPCxVI6IPCv6hUnAEzSZjp8SyUlQleipS1YlolcYM3u0Gk5rBh0BScdP6NnWj7kGLubZNi9Pt9skAUOT5DgJ17bWhovZnzCdAxbmcc3TGq5CMQZmJtYwIfZPKtyy6QAjhU/ffCxMEFoslxVqdtw86j911oc6p7+qs5uk+z5TXsiBntadOWV1nQbn3rqaEOWfiFGcve6WUmgogqgpQSpXwUus0qoJrSkmHsKwq3YiBLhi60ARKBUkJnMd1CcHgraUPnsXQMywPcKGjKSFpirbTjVNduz1MuqWRtWPRZuFT0o1Faa5LhlJgm5T4IsVhW/DpAov7r7G+WnH6wXsYA0PnWAw9nQ/ElLCuEHrDQo7qqQdxs+FoCARjGBZLjm/cwg0D1jmGwyMVQS2JZ89OuVpdcXrxjNNH57z93R9w88Y1blw7xpIoYsgpwzTRGVsn2nSa0Yjl0eOnfPO773J+talBb4fCq7mMZZwmvv6N77DarPjX/9U/zcmhwZc1bYupH2Bti5hCsYXOG1LcExc1YEpSifjGOrSOvu8JPhC7XLUrdR0qWUxVn9WXoH491zVl7E4VOhUdOqrlw5xwS/tQyJLJ4rXr8wn5sIZnzd6De4GjtfUaBXieIKQOqzqPEYcVzXats4QKInYh4ILOZIQQ8J3Hh5113Ccf/5+CgDHmvwP+ReCRiPxU/doN1HfgDVQ85F8TkWdGw9t/DfwZYA38OyLyW3/Y81trGRYLxFpsCOD9TLBxex0AjZ4WZxUVt3W0F5QumlPc4QI1tXdOabg5Z6Zpqj+XVb2oLrpWlzVeuCCYerVzSrjYEFpLCAmsIXhbVWkrsJMy+DBTdvsu0IdA3wVC12O9GmnYKjhhG3209pybt+IO5Nyxv6j41s5hJtXPC1PMuDGyjY5SnZQ6axlCICwGKD9B3K64fHZKXk9IioQKJLZSatEvNAiJQZYdRgpXVytWVytuv/wSxhim1VpxlZS4XF1wevaMx0+e8N67D3n48cd0PnB8dFKvt15zEdF5Bxu1fi46O7C6WvPX/9bX+eu/8fustkXbqfLJxlxBlaHh7Xc+5jf/7tf54//sT3NyckypxPsKFalGpBsoMRKcYKn6ASJqGlNViIxRM49+UDMWZRXmOZ2PMf8/zL1prC3Zdd/3W3tX1Tnn3vum7tczhyYpUrKogbZiSZajyXIMwUbiOEiC5EsSx4hjwEa+BEjs5EOCOAYMxEm+GEmAIIAtxPKQyA5lWzYlURIpkWxSFLs5SuyJTfbr7jf0G+67956hau+98mHtXVXnvHPuvU3SwKvG63tOnRp27dp77TX813+xWK5gBAISJ7iUyWUg+54McJRiNmGyeVBUdwqARwc13uDo61R5/fvNwYzxvnVzI8Occ45BAjTXwogZ/KHiLR3eV6j3ZgokaJwnJTktOHBuTeDvAH8b+IXRvr8KfFxV/6aI/NX8/b/GOAc/mP/9GEY8+mOnXdw5s29VMI9z1eBrm0huQwjYv6qPGvis0pv62ZhpkCcyIvgql7tKibquiXll19D1qtYgBAKq0psLqonY2oRFWszZY1z5lXfGUCxmg6U6ZRJOMQEwsQo6lfdIZRNDMoS51KgvUQ/IvocYewhpKW+llJWDDHYxSHGKxsy7ajvEr5DWEbqA9yYE6lzG67FnngYSL33pS5y8/TaiSgwts2rae++brM24SoxTQRzz5ZzXX79G3dRUkymTyYSmrjg8OuKNGze5ef+Ib117i8Mbd5lNpzz15KP42q4jVD3yLXSdXXMCKQbaVeJTn/0K//CXfpvrN48RqSzXYm3LPhxVC8d1ynPPvcDR0RE/8cf+MO/9wFX2Dy6bY1Bjjj5EfFXTuRaPpVtLFvDO5wmCOdhK/xucNkeMxJinh+hTaZN971GnubhNoS5zI6eh/d1wIGZNTwor8kgDYHSHYu5uRqr6HsmCoAiBwq0RXS6a4y3DFWcl2wrKsCuEPA/08bCdSwio6idF5NmN3X8W+Jn8+e8Cv4UJgT8L/ILaUzwnIpdlnXfwgU3EUTcVCcHXZsvUVUXd1D13el+a2ZkmUGUhUGXG3xQrS5LJAqCwtvhq0ASqqjKTIQQ01JSMqzIZQwg9EUUKsccUJDHKMc08evZi7V8ZWAC1KnVVMclkmE1GnlhZsjqvPJmcpDAMjbLbxskiazj10eCwgRtIIdF1AedWFl/2QpvV3UnlmWbIdEoVT7/v/UyaCS9+8QXu3bqBSEKzJtLgqCtPDIGoBlSKElgdreiiMl+07B3s43xkOrvAa9+6wbUbb3P3ZE4MgQ9/z7uNeEUilUsYZjpDh9uWqs55DdHqPbz40jX+3j/8OH/w8htEDZAM7NMTDdgT5//nUK/CyXHL889/nWtv3OJDH3oX3/8DH+LZ9z7D449fYjqDEFoiAXVZMDjBa02uF27RJGOO7CHU2keOSnRpKAZbHG9rTkAdyEoKZVjKITgbl6OQcjbtJUeDTNtj9G7HTysZnjJoCJtRBMltTjliJV57U9dXleFpfA1SWK2cvVOScXH+KwoRPjGa2NeBJ/LnZ4DXR8ddy/t2CgGE3knnnctkjUMnINZJfagw29TOe0NuASatR8kY2Unjsg0OrEtXkV71HlZkS7aAnDkWDTykJTYj5qT0Ymg0X5yWGfzhMT9B0zRMGmPJFch54x7vqh42WjSBIgSKECrfnXPgLH+hgJGg0GV5G/CqpORpokcx2K7G0Gfc9WWzxfH0+9/P/uVLvPLVr/DGN17hZDFn4isOpg24CnWwWCwMTJOpvFedcvvaTcR7TlYL7h1Hrt865u3bb/P44wf87L/+r/H41X1uXr9FGwLe1Tkkr3SdmQDUELqIrxNv3L7DL/6TT/CZ33txRLzCEBbL73EQAgnvzPuPKKFLvHHtJrdv3eHLX/wDrjxyhfe97xmeetcTPP3ME1y+cpG9yWW8T3TLhTnjMn+D9CLF9ZqHcxWVd9S1ZjSmOTI1DZpAEQYlO29t0Oa/QzLQAFdHNaewZ+czpQDtMK7Hq34fHhxpAWXyF5+AnecyGM40Gs1jqq4NNGZCCby3cGeMkeRKR2/fviuOQVVVEdl9ly2bjOoOPPbYVRv8FBBPLu6YSSGKt1WTTcqoKSO6iudU+sHXmwN54oozLv9xvFb7WKFVmcnaIKqDqrZmkwFRS4pwZpMptFDO0mZ7lpwSxswJI8ZHV8gjPF6G4hAF1MRoYPSrT0p9XLgUqFhXIzWr3pZv7ovdWgZXjs07tUhFco4rTz/JH7l8kaefeoovfeEL3HjjTeaL1jSH6QR8RbdKVJj6fHh8wu2791kuO24edty6t+Ro3vHE4xf4oQ9/gGcen3GyaLlz5x61n7BaKikWQWpMOCFGJnXN0f1j/vnHPs2//I0vs1xl9EaqETXux8GtNloNnaCYo9eJJ2oH6litEl235Pada7z+rTdpJhP29i5z6ZGLvPtdj/D+9z3Ju55+hIuX92mqmrqe0Ews0hRCoIuBJlkiWoqJkm0Ys7pvQ25Q6ft+H4X3NhOBLDqoa+2vqoqmqvtU9uKgHhcTsUXL/CJ9uq8UM5NBSOaFzUuub4DY5BZIKRgDVzZxi2M8hJISbabOru07EQI3ipovIk8BN/P+N4B3j457V963tumo7sAHP/j+HPrOsOEQ8CJU6s3rbdEg0wgy178RgJJtKSOFCDEXakxD/LSqUvb6WtGRkMNsJZ9CVZGcgFLAHcVvMPbIpxQzJ67LrL+SczaGwZIyJV3KqmIRU4ZT8CBKEmPkRXKRjpw0BcZ1UPLXYwhZnczoci9GHBGDsep2MVc8TqRo9/ZqjEMGYYWUVyTvoNJERcXs0atUzR4vvnHIS59/iTA/5tLBlEcuXWBvMkGjElJgsVhw72TF4UniaNExnye8U556tOZ9z1zkoKlYLCJ3by+5/tZdZrMJly4ecPnSlL2ZM494OKCqE50seO6Fb/BL/+xz3Lu/ouT30z/5dl019nZszgvIgkI1EqP1+WoFq2XL/cOb3Lz5Ft98ZcLvPtewvz/hve97ivc8+y4ee/IKTzz5KO965glm+xPDNbiW0FpodT5fcu/+EW1ImdLLUINehOQM1psK/0Qa5acUHTTjCBBDgboKoheCRssizVGluq57VR3MLCjzPPXLjW3OCQ7X57D0dr6Aivb9oBlbYXJXSFiuRpcrXCMGp+/a3fbAdyIEfhn4j4G/mf9+dLT/r4jIP8Acgoen+QP6TQf7LKpVtWmdIFH6we4rw0RbhZ5IFyOVr+y8WFJE0zonm8/JRMWejpmCiiEjrKoqUkp95KCULuu6bogHd7nWuybUg6SUKxdl9lcxF74kCM4Rq0iKLlNEmSfehIUDPNFD5yIpE6uKCCGHMFUN+1CJUtJBi3fdVrKur0ybohJiMtx+MMIRRCF2VpKaQD1xNO4SMTqef/5lPv7xT/G53/0qt28eUalQ+SX7kyUXpxUiVs8gpaE/FeGRSyWlu0ZS4taNIxbzyJ07d1gsWroucevWPZ5+/DHmJ4HkO/zkkGk15ZU3Dvn7/+QTXLt1hIjPAqAM//K5Hwg8KBRk9FfXjhs0dMsfWcaWtk0cHZ1w69ZbfPGF56nrA648coV3P/sUP/UzP8oP/ND3wmpFWFpJ87Zt6bpxoY+clYgzhOcIoOZyzUqfM/W6OKjwxUlcdGJxrvf9FP9PqXNoQ17XPq/NBSMN6DWN3mx0zrS7vAKaAzQLluJayTaEcSgo3gnrXoj17bwhwr+POQGvisg14L/DJv8/EpG/AHwT+Pfz4b+ChQdfxkKEf/6s6/cquDP6L02JsCrwTUfXWXZaVdXUdTSSDlfhfJftXotJh65k2oUsNO2lFViqaQAFdZcx1k1DFQMKhC7XOVClXa1Yta1NUNV8bTs3eEfK/Pd1jfHUSa4+473h/p2lgrocHhJXYQ4G4xzUcjw5w0vEGI/a1tR/ESZiKuWQmWbaTBdKsdXBoYjayhm7loAJAY9RrsUlvH7tGp/69Bf59Gde4MbNO4ROUSqWSSBFlilw4WBK44zGuqprpt5RY8lNrg5U3qMpcnx8QgiR+vCY5eLQ8iBSx3yx4v7xnKpy1I0jNML1O4n/56Of5Usvvom6GRrGXHfbJv8pHqzto2e4mhS8gc2EEGpidKzmkfv3b/HG6zf5+tde5qf/5B/jT/+ZP8HetGI5n1v4LQQ0BTTT3jtxJBnSc70XVDPDVEh9a8vYLQ68hCEDa3FUzjgWSxSrZxXa8AuUz+O/g3DA2jAKP3rJuRTJMAolqcnKt6VMa4eVUyMa8vWUHjxvdOA/3PHTz205VoG/fJ7rbpxHyh7qLoSM9rLmrVYW36/rhta3mWTCqgqJGCLQctg7m0jdAAYqdaK1oMtEENEMpGiYTDMeP2ZQTlbxV8sl7bK1lVwtfLhamY01qTypMWbglMj557ZiRqlIsUNTS6yL869CnYdkMVtVIYIVWEGJOR23C4Gua/tIyNT53mlZ/BkhBFZdpOtaCzfWPkNkze8dNdEuWxpfseoiL796ky9/6WWe/+KXefPGbULw+bVHVAM4A5EsQ2AZI+97/ACIdLl2Y0qWSemZkEIixIBzwip0LLsVMRp+QTRyND/h+q1bTCfCxYsNN48Tv/Srz/Evf+draPRomgMFuTZe8Xd93vZ9rA1s7rOQohGMJKAk4KyQ6MFPuXnjPr/y0V/j+hs3+XP/zp/m8ccf4fjojmmKYYWmiM+Ygh6m6wRfmXNNQ/FD2So7TgrqHYTk1OWR32AzHPyAT4EhVD1+quHR8n2TRa66EFgGo+P3IrjGNIKQi61o1lqNxXgkRLZsDwVikBwXD7m8WIhm33tnA6ZtjWYrdUY5klCqqsZYfC0FOHaB2NkKGWImqFTo1EI6IuatrXMBUldVpEb7kHAXMs2jGtKsW7WktgXVvl2r1cp8BVWFMAHx+K4HlBrGAE+IntgtaeuKSdPgqxrFE5KjC+aPMNPHJpUJn0xkmePQzgkrsRDoEJoyIbBcdbQxMplNmemUxmcKNAG0Yrns+Oorr/GFL3yJl198jXuHc1ISYJKfsUBiq+wgrVBmXH+75XKjPHppQu0ixECnjjZi6c9ofkbHsk0sFgu6YKhNNLK3HxA/YZ4cL3zjkN/63Gf57JdfJyaPVUyR0fzdnNjbPm/7ftowckAgxrwyYmaNiIJTuu4EcRXzk8hzn3qeG2/d5t/4+Z/h+//Qs+b/aVeWnOSqPGbA+8oK0iiQBbZz9NDh8co9OAkNJGX2PD1ScYgiKJtawGbKcEqDk7doev04CJGwXBI6Q6dK5Um0SKbF0xJqFkulV6WHJW/bHgohkNQokUMye9xKkEW6aCZA9sjQZlVfvDM++exgCil7RlNxDMbeVtRotM1rHAPmvbPKwc6ZRtHbgxZtMHx630BSilkN75AYqSuofGXOt1zWPCpEdYToSNERg0djpKottXjZJtpVB3icNwhtisFCm6VwCZYcowmCCkZ1ZtGSEE0Ydl20wh+VQ6cN9WSGw/H2zbt85Stf5/O/9xVefeV1lovOJkZ2XKKFzzbllS6hqcvzzLOM8PXrcz5Aw+MXPC62lmOhjhA7EMcqJMIi0XaJk3nHKngLhUlgNlOOV45Xnn+VT375GncP5wgTm4yaeb5OtU63bdt8BPCgtlC2Eg4rBKEOZWJaD/QMxCFUvPTiNW7d/Pv8sZ/4I/zxP/6HaZqaQMokJCDq8c6qTqUUkJAzWWUAsA1N0CHKU8J9IjksmLUI3RAWDAKg4F1gG45g8BmU9GEN9s9KtQtEqEVyTUbTNMeRp03H43h7KIQAqrSr1vL9R6SIHiB0aCw5AVlNU/pwSHHcgXVojfa2NmqVh1I+r8q150tozqnZgqRgXlVVXMpItWjJRKZRJCR0SBegC7S0NC6w56eIdxCN6MTBKCUUQqfMV4uMWKtoO6Xr1MqRiWTfgQmmyg0c9JEMXCIROo/HU6rcpmQFTppKuDCzegrXrt3gud95gS984UVu3XwrA15qROz1juPetmX2Xeu1/icF5l3Nq9cPiXHKYxempLQitJF5Z4Qkiy4xXyWWQQnqCCguBWpxnLy94sWPf4X7xwvzVmfNY9iK12r8HR6c5L3FDX1832xc2+y6kmnDe3VudJ3B+Qj0NF2jMGQKiIfDe4lP/NYLdAF+5k98hOmkoVvOcZUnBBPUyAoFnDNCEvMtqRF7jkBsQ9stShRjzPwCtoIXdb+Hizv3gFAov9szZNITzdGmlNX8aAVSvKjxabpcDNVZinHtnJlymusfFtNmx/ZQCAFV6Lo2O/RsEnvnRsUpTfU302hQqZJm/DilI0de5PL+GZIwvPOZKwBjBiZP2lSExjCYnFfj4wuKdybVzUQUxq/bwniGFzL6d8vyM+lfJq6ARERdn9RiDh4rKe5F8PVAHOGcrUIhQVVbwg7JIhYisHfQEKPj9dfv8dnnPsFXv/p1br99G6XCyaR3hJa89vXtNPXaHuakS7x6Y86do4j3SttZzYCUS8EFdRYyKyGsZGxQi25pkY3+PuuefB7Yf1ZUoOwvRUQ9SJWLlWhe1bcJkkGAbH/ubLWrjYX5ScenfvsLOBw/+7M/Ql0rMbZUVSIGq4nofV54MlbEe49WVTY3ilpf+tCwLGME6HjCr/sCtr+PsX/BYOwDxkXJzFuuwmf69UoG/gwripsZusSTskmya3s4hADmfQ+dre7eOVxt4b2iJnmfiRmyNOwFQC7KYAkawzWHTqQXAs673FF5EKkNr6hqhSdE0RyWKyxjwVmnFi9v5a1wRJVLWjvRvhQ1qkipfpsyj4HkeG9fXCOrZppDjA7qkojk7SVqEtMwRImppe2WoI7G7RHV8/Irr/Gp3/48L738BicnK6DC+4uk1JFS0YosarKJQT99S7ldM1Yxcf2oy9eCrJfl6evLi6PUaTBIQsnM9IPfgdyRa9su597mZztugGw1CBWUysEPQI11y/ddpoRlaIpLeFezmCu//ckv4kT4qZ/6IZpG0NhRKSStjAUqWVtcDtkCa9WE18FD63Dj/s4bvoBdU7O/jmRU4chcrXxFVWXUSi5lRg5jOjUDKDlLIIIhVX7X9lAIAcEqidlTDEg645rPK7dzffxfXWZjHXVoSmkjSSJlFW7A5me+oHy8DvdWq/6SMiLR5aaQO9TSX61ysTqXJ74JA0kM942K5MwOlcydh/RacM8mq9GEVzL/hAkp80MoikbydSJdF6n8lLrZ5/e/9k0++YnP8OWvvUoIADOc2wM6MxMo9meZ/Jvq93jb5ZHvcsaZIDSmDWk78iyZvW2vS/Lvan6aBMQuCwDP7kk4bkN5C9uiAuWvt7JnVOZ008DZvoXT7p37RuyvCbGG5XLJ7/zO56gq4Sd+4oepasW5SOUqWjogLxB+UOfTaHKVuS6jto+RqmPHX7/1MmN9PPcpxPmwpNrfQItGqpI5NIeLqeb6lzmykys6br933h4KIeAQGudxVUZGOfoc+z60kuGcnqx2Z4CNOOk7zMsgdQ0noBSAuvT/rZM4lI41DoGcBacF0w1o2W8ossq5PokIMEhyMPs0JSCIrZNuJOnVSEeSuj50qWJU0UE9KYLWVnZdsdqBkuzlXNy/zI3bcz720Y/zmU9/juVyhZNLGBNPHK005gRbR2/vsrU3vw8rr6PJa6/RcmgSRpnyo/OG7jNUY2UOTRn6f/0e47/b2rdtwkagAtkDqVANqC5HZtumENl2r00Bk/0M+bEVi/+7LBCOjzt+/dc+i5Oan/zpH8T7BV3b9aOnpI73iT3ej3JQhgSiTWqxcRJc3+sbIcK+J/qxpf3YHucZ9GXSNC9Q+Dyus+MzGXAq10+hLEe7todCCIjAxFuGXiSjar3LEEvrED9SuwwVZ/Zz7wtwtnIO+HvoV0SRzMQwqGpW5DI7X7IzUSSrfIXRRU01N7BGdtxh3vKSpJPU8PJZN+7va1PHmGb7idrjz60tCTW/E4Yf906oqwlta4w1bVjxwme/yq//5u/yrWtvIzJFZJIhtAkl9Gp/1l/y40WKUBi2023k8j3hsMk37BfzjzOedCVfw6tDyDnrEQbv/Kbdv2uVH7dHN45JQIVIky2VDmhB6lF/7zYjtt+79FGfGWb7iu4sDYuV8olPfI6LFxo+8kc+QN0kFq2Nk5SxASUJSaXg/EvkoFx/lH+iA6Iw/9iPxfXxOm7m+rGWD0KRHmuHmmAAyeS1JNMmY1I0k9XsNjweEiEAUGe1P+a1kIzRt3CW6yWoTylXlRlXf8krva/6FNzB75KTNFy5llip5lTULTEGn+wsGkJLPcOTRRd8TT0Rw5VrNI9/cqhVSuhXYHVD4REpWY9Fw0iCKzkLZKePKl6Vtl0wnU350u9/g09++nlWyTE/aXnlpVewqjoXiLFwIJQBXjD4oyv23zcl/2mqcfkrDGq2Z+jdOPp9mKxDmauQbfTxfXZNwsTuyTreHMge4icgAcISM9o8OZFk417j59n8bdt91tubsgpq2ZeJw/stH/v48+xf3ufd775q9G+VtxBvxp100YhsvEJV1XjNiWxS/CIjDWsDJ7D2pKNcgtIiyfkvCmv+gPKoLueSKFitnMqTMs16wqjxQ7L8GtebPtu3h0YIWPzeYMOIeeYZqUtlZS4q9iAZC5hi9PtYUrqsBUCvmgOZpyARVcx+V1sYvHg0mXfdPP8+q/fW6U68OQpFjKNeAImQM+HEVQYwqYxKrLw082NJ7yzEvho7rFZ4t8+v//pn+Re/8UnuHy0YJuEU5zwhg5kYnoTtk2fX/m2TbdcE3L2Cls9rabBbq9tsNzsK4eVgxggPTtx8vqvs2qMMvgfNis3Jvuv7ac9pHwWzsQVP5RvevnGL3/3s81y5+JPUEzc6LqvyCORVOISAemdI1lz5qJgCNLUabwAAIABJREFUIvSJaeOVf0wtNh7npuVrBpENKcxrTka1RcRSCjMsPvdVDIGUAXOqua7BKdRCD4cQ6Bc3U49xJulUBnVf+9VH+iouJXMrpZxmnEYqVzm3pCiXvss2VkkbFcp0sw62OLCYRFDDDTgcPilRgxU7dcZE7DQhtObNz+Wyq2pCXU+o6jpX6YUSiQgxJ7z4Uo7CkpKqquKLX3yNf/nxz3F8UlFVj2TEWuptS7D89+L9323fb+vc86yMu847ff/ZAmB8npko2yMWG5M6Z1mW2PhgomxqEZufT2vDuP0b5+TKH0quskxCqXnrzUPu3rvPE09c6vP7x33p3JDfLz19kCXvbHIGDNiAdYH3QMRAQWVkSmT0ohhUMScQSRaMWUtIAKkPJ2oWnFas97T3/JAIAcE0AY+VHBcxSi5fVT1LqtliWWkvsdYcGumdMCMsd9/hmTKqhFmKRPYx0cXAGHeglFSDoiImUqTnnU9qJBSVd7nITUbCpQ4nVo+vnsxomqnx+BUHUe/QsVXGeQdesrSPdFH53Oe/yMlygXMzUlqh6rOKatmQqpZXX9Bq2+3ezdVx8/M2G3yXcNi12o6udu7w43CdTTTc5u+22cQytGfhDd5s+2a7dgm2zX27hYP5jxJOQOlAPTF5QkqG/5DCEjVyHOf7ljyBUoDE5xLza9GpEXkNsO4sHGuxo5U/pGgFTsh+qVyQxBeHY26CZqPWURCyESFHsigJ8Nu3h0IIIFZDMjlH7QRyclA9mdBkIWAprcVbmp0xldndNlkNbWhmQxYC3mqyFUbiHncdAyElfAgGD8idbwUis/c+h1iMjzQZGAilqpzV9VMLH8bkiXGFc0rlK5rJjGYyy0LAZyGQ6aog+wuGEmp1XfPii9/kpZdeJ6UJSmtGHiXcV+Lhguo4wWTbgD9LMzjt+y47fVihymA+C+hi26aDcHPVLtclC+IHV6wBC5BG5+yKVLwTzai0Y4sGoZWBoJw9Q91cxNdTCkuxVXuKmeXKTCHRDVVd6MllzN5/cNXf6jQUoSQfrRHIFKcjOarhHNENfjLTijMJD1ahSlMg4XHJ4wT8KRHVh0IIlFXbixV4dLXHVRVVPTGKbzWwkI4kJGL8gSVEGHN+felUk9iZYiv7EVSV6CM+enyMlveftPf8W+a/mQIpl3kqYZeE2XNVlSGiMSOzVJDOcAPeZ39A3eDriU32lHC9KQJmFxvIQ1VpmgmvvPImh4d3QfZAu9FAKG9uc8Xd9n3Xir/rmNN+P2OSC6xlpKzdenPSb95j/QQ7fHOVLwJk/Py7JvkuDeA8ggrGUGJbhXOOgwBMSTojqOt/9xk0ZqaBTcz+jmIOA+cd9SgXwDgE/HqEgEEgrKEJoQ+zItKnIJdVxGVto8cpaMq+CTOabcGJmXUbo6gTY8DatT0UQgARqskE50CdtyIRVYX3U3xdZYaUOCACcyeVxItCtiAxra1WbvTCSp5BOU9yx5cCIIW/UBNrwqbkJgRn0diqqozaSXLxx5QQGkCNX6AybsGqbuyljqCj41W1mDlt2/F7X/o6bXBIiihVHtbjwV1e07bJwBnft63A28yG07Yh6mC2afGbWBjXoKwgWWW2vttc2dex9Q+2zyJC0iMTx76PbdRY51Hxx/fW0b+yL4dXi5Mv47+FkE2RlqrxVLXrJ6Z4QVwyh7FUIMVnMbRFxNioqwx8q6pcUi87RQv/QC8Esh+AbJL2VY/satnNMLw3W0ukxwsMvIY5uzHjBJTCshVBHvIKRCJCPZlYeM07pKpNE6hMGKSUDJnVc7DZH+ctG09Vs6CTnUJgbIuOSSDMD7BbCKSY6EJnFW9dpqVW8x2IuV2xSWKFKV1ttQVKDnlpi60CQ5ioSPi3b9/l2jevk4LPzs+WHtdgreBBW33XdpqA2LbSbx63S1sY7RvP4R5aaW5OVHpUpO4UNrtXbOubUQz1gfbvusaurZwzOBUHXEV2NucV1hQSEwTOK+Itc3S1OEZDoPJTqKvhPZYrRytLnsp4EsxXlAaKfB2ZC+MS4ZsIwfG4M6YgMZBcHq/FrxVHAKTylEIeijmjsJifnUZDpX4npclle+GR/wn4N4EWeAX486p6T0SeBX4f+Ho+/TlV/UvnuAdVXZOcgPNItvULpXhIEZcncQ/+oSRl2AtNaeCtG3fwZqZWUcnGDsQyYW0/6x2sOqhjgCs8d6Z/IepQtcISkv/q6OWObWnNoY/CZ1hVRb3L6qfGHt+g54bF7prcZ02a85oHY/vdvqeYbMX03gqBKEgsCT2DY2v3vTe3PCm3aqzndeztuu6w+henXP9O1iIbijE/JTSmHHlKrJYnrOZLVA9G7bPoVExWFtypZl6LZIIw2X3XCo7mSR5CfIBgpL9qblfPOI2AK1ToudLRRicVjQHFzNfsGwNsHnlLIOoX0C3bbizhsP0d4Oc39v0a8AOq+kPAi8BfG/32iqp+JP87UwBYawWpbFUX7y1/IINtSgXi9YQg8uecBJSKuqqjS+4eLL22kFmBfeV7+vJt2V4igrPYBdIj8/Lkz2FAk/a5Mt7aexraUfjty2SKMXHp0iXe/z1PU1VGulGeZ0AA7lq9N/dv2uIy+ndep9npE2yAQdsAq2YT/KTBNVbhl1Kie81s2W2LDlt51hIK7LPhN/5uu95Z38u54xW5HLd5bLm/hZQFuH94xGvfvJ5ZpWKO9efWJiODCVrKwuXWutKSIY24nLvmQCRrmyPttRcQG68iZbM0Zcf4+IBSFCWkBN5RNTWT6ZR6MqHylmW4yVo03s4UAqr6SeDOxr5f1cLSAM9hjMLf2easeoo5STNxQ5lPQjZGiyDIsNVUVu51Fb50/PACBvWpP66/5vrfTeHRCwI2ppFq377SHuOElww2Ggmr0Web/EZ6EmNgf3+Pn/25H+fChcqKV9BklXWcJz+cu76dd8U9zWdw2vVGE1lyH6tmcIqpwtoax4KGRC8N1+5x2r22CazT2jQWXpv32eXnMAEwPE/K4daxoB2u7wQES5VWBBXPyUmuTchQACZlHoMwUs8HBqB8tbKCF56MkRAYJ75tG58F6KtYiFrzvr4XxKIV5mfISMXK4ScN9WxGszezsvV1laNou8fHeTSBs7b/FPgXo+/vE5HnReQTIvKTu04Skb8oIp8Xkc/fO7zfv4thpddh8lhP9FJcck8XSbtt4m+GYID171sWjM3jH/itPyYj2DI9+HgRlty+B9qkJZ8r25EYEKhtA08++QSXrjxKSi30dNxnraBnqfO7zjlt/7YJ1FucfR+gCiGQFgvScoWuWqTrkJQZnN7RxO+H8Eb7trVp2+dtx53Vd5u4g6E9qhhQRwSVBj+7zMGVRy1cm8djP3E1C77ReCuM1MV5rVoOSZmR2oGsm6cFFqx5fBgGJvsEes1leMQS/rZanLVpzb5CqjqbaZWV8qtqA61VtdX43LF9R45BEflvMUD338u73gLeo6q3ReRHgP9PRD6sqvc3z9VR3YHv+9AHMuq62IXG10dJ5knjyZn6TnG5ZwrrzubE3yUAykDuuQjKhM37e/Ust9UqBJMdPgkpseuSppVKKjA722C+DDMHKueIMeDrCa+99iYf/X9/hVs33rZnJo5i56UVmyvgaZPsnWgEu/aPr1Okc/bJFHOn1ODjfAr/zhbJaaHQbdvYzHhAPzvlnC3P9AAhSRYE5f1qBX7ChUsHmdXaruG968eO8U6Ylmq5IGAu3mSaYpJMxpKh5rk2Yjm/NNlyW+xSfZlyHUBx5m4YIPNQNFFBc4jbWIgGDIqFoOs+jL5r+7aFgIj8J5jD8Oc030FVV8Aqf/49EXkF+BDw+bOul4pTKU+A3uEBJoHLWMyrpAgUAtF8vzP/9VuvDSTz8A+w8GEYjVb+ze8i68JlfH/YMRSLxmAVS0A983nio7/8q/zqxz7OcgmCYSIsphzYrlJvEw7bJsSo897R/l3b9mN157fTfA7rAnj7eWcJvl3X33bs5r5d2oP5JTTH3sVZCfrZxGcIuGQ/lTmkvTem50RR74sPaexTYjRxB7vfnH8pj3fWIgAD9H04z84FS22nWDYU6LlTyYtlGkWWstkgrqfs27Z9W0JARH4e+K+An1bV+Wj/Y8AdVY0i8n6sMvGr57mmOTwSOiJlLGp0CeWsTzxhs/LZubSA0T7pGXTLRB/Zc3bQuvbAoOpv3nft89Z2ZL0Qi0xMpzO++vVX+MxnXqBdeYQBTJL6lOgHep7tK9pp23lX/22/fTsmx65t6MF+Fdyqku/6vGvl32zrWcJh1zOtawdGYOJoKsdsYpRvGouGWCJPtrITjXDGZTXej0hHCh5l7HAun1NJWZf1RQTy5H9gAAyYgT68mJQUlCSmjXZdRMlFa4CuDeD9WmhycztPiHBb4ZG/hrE9/lqWVCUU+FPA/yAiXe7Nv6Sqd7ZeeLTZAqm9HVX2bk4o4IEJ+MC1tkzQrRqBLev0MXnRB85BH5zwZSANCsIwydf9BhsCKJUM/Cy5neOlr7/M4d17iFRr17PGDam8D95/175tK9yu7TxmxVkT7qyJddp9Sh/tmrib22nPvfn5NM3hrL7KwB3xaFImjaep7RlTb5qOUnvFcIMGIx+u0Ree3cktSO9wXhv1m2Mn33PtOcQEkZkgNowLWrZQocdoeJOkoM3p0/xMIaDbC4/8XzuO/SXgl8665pYzYewU2QKgKN/PfcWsfm8XIENsdXwfM0FGauqG4OhDZJY1sP3aI61h7WUyGnZi/PVv37pNDF3WAswcskcf8wTs6q9vx77/dq953vNOm6iDOjy8h/EUOO3e36npsu0e269XkIPiG5ApewcHTKZ19tOYACjhPqsbYRgWdd5UdQHxjknTUNcGdnNZIBRh0I+1EvHKiUBnabBCyUeQjAeIdJ1R8VtNiq4vn5dizBW7Fe9mRt2/Y3soEIOoDQ5j2slY/t6YYq1GHFl9Gs4dETHk/8qxKcUh7ZhBxS/CoZzosHTjbBKaGNBiouSBQak1l7kGcpisD+TpMNk3hcdwd0WTp25gtZpz/3BOjJ7B+1E0jM31YaOzThUAm7+fJSy2rcbbzIFdfonxcWdP1rMF+a4Ju+0e2+53mrq/+duDfaXO4f0UmV5C9h/hytUrzCa54nS+REoFvVdW3WAmADmHxGUW6crKl7lMdZ/ZHx+oBrRTE4CMmcl8ggymhEar0bFcLlmujAU5dYH5csWq7UiaqJsqt1GZNM3OHn8ohID0/y/ht4KoKhqC9g4W8w8AI5upDGEnA8Vjv8rn/2ueqWPVKmlGZa29k6wBjF6N4eOzXdfb6gpJiSONwAZG6qsfCWOCSMVEhsP7imUbuH90kgMMu1Xms9Xcbce/k5Xznajxu64/FgqntWHbBN6ltu9qwy7hsO33zeM2r/mgaWD4E4dKxXRvn8cfv8z+XoNIzBiCnNJLRgzmvP2oMRN/5gkvpUT94NEvT1tG6ZAWzpq5MHYiFh9CGU/WWhvPXYgslyuWq9Ym+6pjsWytbF+KTKYNIQTadkVdP+RCQMHCgWKxdLdhkw+re1YnC9PMWKLKsFoPu0aeVLKmMFJHBUtZKb8BFnYRpfxnfkqj0RSxGgGKhXxwubY9xZjJL1kKfKh8Z02JWSwiX3jhD/jWN68Rw9iZe9aAPmtib5uM72Q7r2p/1vnnXaHPWt3Po9GctZ32TGNBZIJaNCFEUohMfOTJqzOmTUXbBsjhOoMUj1btbIsXsJD3Dl8bU7ZkIpKUEviB22JbJaIxgKh3DObxXzg27V6xN0m61orworBqrUJWiBnAFBMpJFpVTiEWejiEAKoW48wgjSSD+i9IrroSN/AC2r8IyddANSew5JVYhv39fbQ46GCsg5TvY7ro8h76TC+s2osdatO8JJMKZC6CzHGYZ70ruoiC4lHx/MZvfIZ/+k9/nWvXbqDqGSrknKUNvNMV/p1qEudV77e159sRIO9E0JzVls3jNs2Os7SG8Tqb0NWK/SryyCXjNDTqSl07vDcPMrWXSJUnt+uZiAscXRDwzrz2sl6ObFxxqM8glKJxmAAoFHpmhooN8VQ4L2yeJLVlLYMI870cqIP0kGcRqiqha0le+ilU8PqaO8C8pAMgSIA1mG8qNQhHvycZSoArRs2VCm5PRs4erHaAmIrvssVR/ALkegTiCmos9bRXRSobflsJIVCFSJKE+EwSMVL327DghRe+yquvXCeGsVWzOXi3Td7zCIDNyXja983jGR23rQ2b19gltDbP3da+swTeeY7ftn0nWhBkUn+QioO9hmlj3JFsrNo2Dgpr1LCcjNF89i8LgB5HQJ9YVCY9DFpFQSJ6502jlAKJG5oIJniMIi8RgqJqNSqsXqfxCYi4HHVzRL8pFIftoRECXRdMkknmmHGOSoTo4pqE3Oy0Ip3HnQjDMHB9z5Xk1nx8yqCdEmbxRgoqxidmbK8mOQbHpKrh5nNGV4yBGGImATVKEt91RF/bS9x8TpTZtGJ/f88AQURUO9YH+Vmr3Vmq9mkmxLaB8E4m12nnbN5ft/xWPp/lUyhbZpFy0lOtbRdip7XrvFvR8MwfUO9f4Orjj7A3qzPCL/SLTsFwGFVdGBzJBUaOYByJBfGX6ee3rPxrUaWRz6o8yVgzoKAKEYbEmgJjNvM1hGjJTjEaSU9uq+U+bN8eCiFgGPoODQ7fDGEyp+6BfIDxplj6dNkkL+al00SMosJlR1+JIxRNIaWcMor0PIKk0HMVxmxbAWgMVL7K7Y100cqmWfm0AGr+Ae8cXeyQIJkbrkBMjRO+9hPe9dRjTCfCcumxbOyB3Wb3KnbaCnueVXWbmvxOVsyzjt02sc+nwguFySflAixZWFsxSFKaAzMc9cD1V95j9r9EVbaTj+xq63DvQjiPVCATpL6Mqz0HByCuwmnqvf6pEqtG5RwinhgT4iCmSKW2upeFIXQdVeHH8CUlyP7ZpFRjt0YzxDhSVUYqU+DCPUFuGliHDdU8LH4pBdNG1CIPlfd0yeDnThwJT9LvMmLwu72llFguWlzjcZXPUb/1ib/m0JPCBLN9bStb35li0rPXArS4/RgJFvNLpKh0XZvLfwdiyMelmKnKTFqHEAihQ0MkdB0CVJUjxsrOi76/rmR4qLhASpH3vucpZnt73Ll3hJOadcbeXav+eSfgprA4TZ0+SwCc5Rs47frnOdeOc64zjUxtFU5G7AgaeeLyPj/4Az/MH7z0Td68eZgh1bHP5UAcmgp7c2Ez2nW/cXvyWMgRG8UDFX5yATe9gCBMvOC9CfOeri4WgZV9RN4ZvXc2C0rI0MZHIAQjj0kRIiVLVnqbv685UFq4JUqgqn1y9XhBdBTinIqkSrcK5qdyHl81FAe2k9MnykMjBFarFZNqD4qqU5T3ogrBmjeVPLH7jhp12PivjM4biDvz/4VBzY9KDIGu61gtVyzbQOwCKcSMDXdrUleT1SckRVI0LSABKURiCEQ/UIKJWsETEFarROWa7PSJa89ajt8+8U+bTKdN0PHf8b1O+7t53c3ftrXxNKfb6VtUo3VXjWhacTBr+L73vYef/qPfx/e993G+70Pfw6eef5H/8f/4uyzbmhSdmVHe99rWEIt5p5uYAJAaqWe46YGZdaocTBu8g4Qg0VJ3o7MV1XxBprlYQSxbbEref4ymDaRUD/fRdRNgCHfDNh6L8YTfNH+LdlmuG0OkC5HVqkUzR2ZVOStHRiSl3VLgoRACqsYmPMl1/4yZx/WUzePQidnwCs6cL3XmbYtOiX47h9sgBIYCpaJDp5SOXq1WLJaB1WLJcrUirMzJgqoRZsQEOWORZOmikiLeO+MMrP3o5dA7kOyFCs899/v83ue+xGvffIu3b90zViQtgqBsu1bU86j8m+efJTQ2J/c78Q98O5P+QUFiCM2apB2X92t+/Ie/nx/7wQ/wke97loOJ4oks5vd57vkv0LaOECe4FPG+phRhteIxabTY7RJYm+0Ueoef8/hmBuqIywXVfs3+rKJysAo5p7+MGRktUpBV8IrKeQRD84XQ9ahCVXrMwFAivMDMTRAMzMSDNrBJz77uDytl7y3814XEYtWybLuBIk9Mz/GFbHTH9tAIgRSLHeQfkIyl88v3JGTGofwSRz6APnFDxgkbWUvIoB9zwOR755fRxcCyNSGwWK5YnMxZniyIIVJ5b3w3IUNE1SIVvnJMGqGpjVxURDLGwLYyvkSEEBNf+PKL/Nanv0C7yHXitKM6hQAyn/1t/mZPd7bw2CV0TrvXLn/Dtvtsu0YWAH2y2JzHL0/4M3/8I/y5n/txXDgmHN3m6KTh+p37fPSTv8vvfPnrXNx/kklVs1jd5+7REpgirkbTMl+z2tKWMwSh5lAwoF0ktSdojBxcfIy9g8ZCcgGD6ebYfAwhR6xMI6x9ZYuKDtRgIq5nCSpj0hf6cXmwXcO4HTTabbkG+QOKZm3DNFFLwhUrtqOlaKntM+TiQx8iNHNgtexoph0kgxCPKcVT5khz5WESqERiiQr0UjezsMhQtaXP/Xb0BJCChf9iMoBSjIlVF5jPl8znS44OT5gfHaFJaeqaJMJysSB1AVKiriqaaUUXHLPpFFd7mpImnF+oE98jBgvOPCaXVTPFuWoEFHonquy2le4sreA8+8tvpzkhN/e/UzMlq7NZCxLt+PAHHuNP/tEP8+ylCTde/ApdF1h2ynzeshTPj/zgR/i3/u1/l4tTOKgi92TK3/rffoGv/cF1UFuFQ2zPaPM24VBA32bWxdUCEas58OjVAw4uzkyTK4DfpIQu0LYdXdvShRaBzFpt46lMqJJOXISCAc9k8GfpsAANTVqf8A+YApjGUHmP95W1PCZCZ3T7uBrVQBusZuXUzXI1LMG7h1wIpKSsVh2L5QI3d0gl+C7Xop804JRuZbZY5XzPDpyycyVpoguBmEN1zktemSuSlsrAEFIgpJBj/NbhMURCNKnazjuOFyccHy+5e7hgcdyhGqmqlpgi85MFYdXigab27O1NmO01iCiz/YlRUiXJbNZCLqROVXmO5yuO7iwILSQNFI7C012b53HynWdFP49jb3M76/jTzJQd50kuI6dK1CVXL17ip374B/nJjzzDjMDi8JhDgXpvxuPveZz3fOh7qPFM6wmtKIujBQcIP/reZ3j1T/0pfv/Fv4uk7AyjOoWadVtflKNLEDkgkkAa/OwCT733Ahf3GlwKRLpMIWZ5A6JG4JFCi6ZIig7JPp9k9l9f3t6qZDEsDmV1zyXmopoQidm/VJx4kkPXxcgRkZyRmDVf51DxtBFWQYkBukUgqUPV42qfKfuM3n7yr4pZ6Lu5hRDoVh3L+RLxZvPHrqNuasRLtq8kVxMa6MRFzAnStoEQjPWnqhzTScW0aYyyubJzQozmKInRPKcxGUdcULquY7FYMp8vWMyXLOYnLBYLSBFfOUJUju+f0C5XOGA2MQIQ8cqss3ztUkRSo5ICRJfZg53ntdeuc/PGrSyozrPajrd3MuFOExTbtvOq9ZvC5p2bB/bUHi/KD37gaf69n/8ZPvDMI7T3blE5xxPvfQ97j14irVp0scLFFSkqx8fHOBHC4Qk37t9nubrPS7//NYzmfWrpsjgs3Lqr3Zv7x1/LceZg3JtOeOzqFWbTCWEVsvwqgJxA24UsFCxK5PDEKPiYBo6A3twYsVcLo9XeemPTf1W2vro2pmH0iEGx0KTiCElZdR3LtiN0kbZbkYC6tiibc9DUFdOJp6l2j4GHQgioKu0qUFUrkNRXS2mP59SNx1Wl0EJGEGpJzfTgoAshI6UUjzKpHbOJJ0xqJrOaqqlBHSHbTpqUNiZCLkOWYmLZdtw/PmJ+sqBddaQQ0RQhRUKXCAGW8xUnR8eQEmFvD8HhfWJ/ryaGjCvoAp3zCB3RB1QSd+8t+J1PvcCbb17vMRA99Hm9Jzh98p4dbvvubNvMim333lxhy7HbNQslIhq5dHDAR559ig9drXn06h7+fR/OBWUDqW05vHWbozducvhqxf7Fi8ikQZsGN5lw8J538Yv/9Df5x7/5W4h7BNUWUot3DTGNyUrOMlHGfVWopcxRWXthVvtcGXugmE8RNBpAqA2hJ4zVTIeX1LSCFAfQUFnBSyIRZORqubNbd9iNU437MHZpa/YlhARdVLqYKw2huSZnRMVRe4/z4J1SeaHyMJ3unurfbt2B/x74z4Bb+bD/RlV/Jf/214C/gHE3/xeq+rGz7oFafHW5WJLCioR1sAfqyuEqCAhRatRVqKvt5eR03uWqZbFY0IWA9569ac2FacViVjObTambBnJNgKQQVYkJc6oku/di1XFyvGQ1L2grxWNx1tgFVqvA0fF9jg6PLXswJppJxbR1xFCSNQJdK8SktK35JHzl+cpXv8mXvvwi86UVlhy4AzYptrZNqLMm/ubx38l22v1OEwDn8xEUhXl/5rlyMGV//wIXHn2CRVwxv32LcHhECoG7d+5w3M6Z6AxSooowSZ79yUXe/e7386M/3vJ/f+yTnAQHsaJyjm4r1mKXqbRtX1lhhQv7Uy7s1aAGvfXO5YIzuRQ9mXUYzaHf/OTZLxBzwZBSN6OqG/NvZTM2ZKDQuiN7aGvBEuRv5j8oviVyeTHM4++rimYyyQC4YD6vylF7x6SpmNSOSeXZm022vhM4nybwd4C/DfzCxv7/VVX/1lq3inw/8B8AHwaeBn5dRD6kegpcCeu41XJFt1JWLhFTR9et8Ci1NzUqqCO4CVrPrGCpM5snhMTR8ZyT+ZyuS4j3zCYNF/ZrruxPuTDrjGzRG8hDsehC6AabrA2BbhWYz1tC2/UvwDnMSamGIUidaQZFcBgGyPX14UKIFoHoWpzrqPyU+8fHfOa553njzZuGZuyfunAHjFek84QDx3/Xep/TBcZ5hEm5zrZ7jn/bbDNsb9P6/TWXLZtUgRhbXv/WDZZB2ZsIizv3ODq+T6wce1ev8N4/9L1MJlOWXUdDzeG1W9x5tKS9AAAgAElEQVR/4waLS1dojw9x2pCCDasoFayZA7vatK2PZPgnAio8cvkily7sgRsqC3k3FAEt4TxD443V+XKpEf1YphuzXACz860O5VBbYbNAzhgnMO73ghuQZM7Q6aRhbzalCKVKNCNclWZSMZt46srhHdAFdm3nYRb6pIg8e9ZxefuzwD9QIxz9hoi8DPwo8JnTThJAY6RNAdWW1WLOcnFCJYHa2cRtk6PzM9zkgHpvivMVeBMCJydzjk9WrFZKF5WqbjmaVpzst1zaXzJtanzlwLscLbC4vWatoOsioYssM+a6doZAq71HxfUlxg/29iAZPns6m1A3Ruts/gZjeiEUyHFAJfClr7zCSy+9ag4lIyboX1ruYU6f+Ft7iwcn665tfP2znIWnmSO7BEC57g4hk0O4tsJ5Kpd45ELFXuO5e+sWYX7IZL/GT6c89sH3Mtmbcf/Nm4Sb95CJZxlaWme1Hq8f3uM3/tE/5p8/9wccLhWVGnRBlRF1ulawZZd2tMVXsfFoTePwOZmsTGyXcSnifL/Ce+8tWkRZuUfEH9UQlep7KxnYzHtPqQ3Y8w+OsCylHQVctPl+ExHnzC+1vzchYRECYk2IAUWZVjXTqurLoC2XqwffTd6+E5/AXxGR/whjEv4vVfUu8AxWjKRs1/K+BzYR+YvAXwS4sL9vzMG+AhXa7j7z5ZIqzg17LUKQKV1d46QjisdXibpu8M7j8ZCURbtk2SrVqiasIqt5x/ykZm9WU9cux/M9lauRZmKOwlRomlpSMBBR3XiE7DdIEc0lxnzmeVdx1JOaauqt9HmVSaY1QrRkjRCUm4d3+NLXXuL2XXsBZgs+qIYO27ZJuEsQbPu+bVJvHneWvbxt5dx2r23mQN4nhgBEAwkBVxkNt0YeuzTjhz/wbh595Ap7B3s888RV9i5fxM0mNE0FXaBppty+dYf5m/e5c9Ty6rU7fO31t/jytdvcXZb71qArwBEeaM+2vnjwWSX7KazJBh3WlKiaSD3xeDchcITLNQoRW9WdczRNjfeeNof5jHlYqJ1jUjuqxo5N2eEIILmobWlZESZ2/8IvletTSKKvr1FChFmTqOsa52Fvmtjfn7BqF3Rti3eGf3E4Yx/OJfJWMZ7aHd+uEPjfgb+O9fxfB/5nrAjJuTcd1R144tGrerRcmR3lYNVF2pXhsUsabxBFvT0Y6qh8TdPUNuBctr/FISS6ENEYSR1WSFQTaVbnEIsVSpDgLG4/gnhqSoYXd1jIZ2Jkn6tVJKqBBC0ykZGBlqGRAX/WVsXAJKsu8ca1t3nrzVujkndned9Ps11Pm8DncYRtu97mubv8Eue9X96nCkSEkPdMSJqY1fC973mCZ9/9NE889QjPfvCD7F+Ysbh/h/u37xCCkCIc3V+Qmj0e+/5n+dWP/iYf+8yXOVw6YC/TPC02ZNN5TZ0tLc7RJs3NF+eZThvqyufKP6P+yBZDYb0qcf/i/S+TWsT3eQF+I/ZfMCrlu+m5tqdEAfooU9YExpGDUombkPq2eG/Fe4NGam9kAkmVLna45PHCSPQ8uH1bQkBVb4we7P8E/ln++gbw7tGh78r7Tt1CUo5OVoQY8V5pFx3zVWQmedIDHcnUIIkk6agbQ4cZOKgQNbpcRTgQSFA7ZsHTtRYDrp3gK5PWKXZIikhKEAMagmHXRUArrLZAJKaOEFoTAuTocoY324tWfE4VNfrnQBta7h91fOMbb3Hv3tL46qUkt2zbzhrAZ4XgzlrZT5vw29R8thy3ufKfMfHE5eFt91BxPH5lnx96/5NMPZzcP+TtG9e5e8ezOryLtp0BXnJBz0oT73/iUd7zzJOot4QYUktKK5T6jDacxzdS/hYQjUdUuHix4fHHL1JXLodzSyl7i/G7jE1x4qhwvW+gz1r1nmqjCOl4NS85i31ril9IB5t/oKobdedICCiGOHXOMZ3OuKjCdDY1PovOwpghdDaGnRA04b7bQkBEnlLVt/LXPwd8JX/+ZeAXReR/wRyDHwQ+d9b1YkwcLwIxdohAbBNdFIsaKKhAh3lGnYuoizQhUHXm7W+7RBcKjjrRti2VS0hVoSl7752QOkirRFALGaIJr0oMHXG5JMQOrRx1JSAQYiDGgDhbBVxlKp6iVJWnaWrq/NIL/ZO5qjxvXb/Jt751gxizN1DPMzB39vgZx5w2Gca/b6r349V+l69gm6mxzUm5fk7C4dw0m0CJvUb4wDOP8uRjF1nM5xzfXbK4e8JsOkFjZP/KAftXD2iahqYT2ntLfu9zX+MrX3mVthXDBBAQe22ntGm8//R+zZ4KTITbxL10ZcbVxw7wDkKMCB6RhMcRNOZVPqf45kvXve2dV22Xacj7Glm5VbLelgEJmCnq+qS3LDh7X8twvvdWV9B7+uIn3nsqrREM0+CcWEQttCjJNNdTahF+u3UHfkZEPpJb+Brwn+eH+qqI/CPga5jW/ZfPigyAqUFHixVt6GgcECJdmwhifAECLDURUsD7SFUns7s7JSh0LbStOfhiiBDNBPBJabxj4lMmWPA4NXsgm1goisaW1C3RGMBPUQ1WAoqEc2bLJQ3EFHAVeFdRNR4nUCE4VdBIVKs3d3Sy4pVX3uDevXn29MSMDtxms2+bnNu+w/YJvHmtbb+fb1KsH7u5neabGLdXAMuwVK0RcdQS+MDjB/zIh57GaWTeRTTA8dGcO28fUk9qLl59hL16wqINvHb9hM/87ot8+msv89a9lsgEjR2JCqShVA4e7neWabOrzaWQrM82f8WjV6/wyOU9JK+e4j2kbogAoH0V4BjTyALS3qNvpepAyzVEeoKPEiIaZ8eaRptblfMCpHzWIZN2bEqoKiFG5os5RycLY9Zec8A6pKrwlTBpJg8IoPH2Xa07kI//G8DfOOu6G+dwsmjpupZQCQQD67jKEbMXfxUTnUbcckXllKa2kExIwrKNpgko1JXHUzNxiVnjmda2soskHJHKK3VFXqHN9vIa8BJRSaTY0bUdk6Zmfzphb7rHdLpC/ZwQA2lS09Q1s70JTe3wJFKItO0Kr5Z2+vrrN3ntmzeJyRw+oBaD1pLzvvb0rAuC0csa3vj6KbJlH4ZwH8qebnrKdwmZTQEz7B9zMGx5axttlbxEm63qnSeljqZyfPBdj/HzP/aHeNcjE9qQmEwvcG95n3ZxwnQ2AS/cunmddnGfb70952Off5kXXrnGohXj/0/LDAq28TD04C5/x7bftvg4ZPQcCk1T8eQTj3Dx0ixPxExB5w1+W47uQ8bRcB9j3ovCDjRmutKU0BwZUhzI4Acww37cvqE/c37Vul+gNwsKjNj8D0guBpvNBScwnU1pJhPTFjZASePtIUEMwqo1PP2iS8RVx7Sq8SScVljQwzz3TiOiEGJiFbqMnDKedXHQOKGqa2aVMK2gEgNO1LWwvzdjOrNOCVHplktS1xHbFaFbElG0VZI3B6ObNLbyz2omB1e5+uhlui7QtS2kRNMozluu9mrZ0QTlcB74+svXuH33OM/VSP82pdQ00GwzWy1E7eNCbtQnCpLyGC0qq+SFZPAvDNO5ZNQrUQRxNaSYCU1KReGUw1Y+n7Rmnea/QxmuQrsq/ZSgP2Z9HS7JUuavMSh3pK6U73/PU/z0D38vj+w1vP72Xa7fW7CKU1589RrzxTHPPHWVFJZc3Z9QVQ0vvHabV6/fI0Vb0TRaRKXrKzJtFhFdG0mjz6dpRaXV4wmYuHy54t3P7DFrKrPdfSk9WwhwlUTMIjVlTokC7hnencPSzody5Zr72rL7nJecip6HRcYniKQ8x62QSYwxa6TFaAFRJWQtQMVyWGZ7E2KqSaG1xDp1uKrCT2rqacNsMnn4swhBIVkNNS+K84Z/riaWp+8EYhuJ4qibyuL4lkRtLMXtCqIi0dDfObWf6cziqLNpzcGFGQcHM7ubJrpuBeqJoSXGjtCaqAkpMqk9IQpOK/b3Z0wPDvCTKZNmSugSR8dHLE6OCe0CQkfQgCToWs+r1+7w2rfeQlzAYsHGJiwEigPISk576qoxrEIK9qJdzhdPgBdcMiYjsBVAcT3rkvPST+6ymEUVSBVCZaaNZEYj8VayOuWwU9YWVDCHpSpoAb/4NWcrKE48UV0OW9kg85IfAxCpwU/wfspkNqNpJmgIdCFyO1zmlz9/k8nUcffwJjffvoG4xspmpcSL148BYeYrRCPLBEnqXCdyU2va5ofYZhZsbuPjxyq4ZAFtfp6LF/a5cvkiToz+S5zL/a54J1SFLdgZ2lOlkIvYmCo+qeKXimHgx5RCI45pts6Bl8KXQf8cvX6Vm5kKK9Uov8BpXhBJTGqPUqGaiMERoz2XpdubQxPvDCy3Y3sohICq+Wi9U7wXfF2zvzfj0sWGWTNFBU6WLcsuglgCiksRl0BCQEOHdlaNtWk8s7piUsN04rn86GWuXLnEwYV9ZrMJoWuZL06QRSJ0bU8I0tTGzBK17YkgfAWTvYaDi/tM9veZTfbo2sAkQ5KPj4T5yTFoQkPi6P4R33jlWyzmK2o/QQSa2vHoxcs8cmlGmyJBwbkJ9w4PWSyOsuOpspBQKuq0M0QkQGaFKXgGo7Y3PwMMq7QBliojZiX8/8y9W6xsa3bf9ftuc1bVuuy19z77nD7dvnQ7ttsXsB3bIUEmeXAsUMBSpAiCCAoY8WIBD0g8ECGeeMoLSHlCQooQSCgJIohYURSSoNhJWoSY9t3u2G53t9Pnum/rVlXz8l0GD+ObVbXWrlpr7z42OlPae601a95rfuMb4z/G+P/Btlj/ENssaBcN1sCwXhOHDmuMPmsLlMTQjxjraGZzTS2lXjvaqPGoFKxEBA8mgHUUY8BawulDXDMnNHOM1ZZrGUe6i+dE4JvdM2TsEO8wea0Tee7VK6peidhAJ6MaSuegdNo/Uip39o3lNvh3H8Zxe/BPe91kI3J1wOc0QIlafmtqCnoafMbirLbl+goGbr+bgnPbupNdZuyNITBqPKbSY+umIqHJ36pWdfLpdjMLNRQw1kBCKc3SiKSRMnbEnIjJKp2Y81jXKC4wtS9/2sMBJqvmwQftfHr48Ih33nnM8WKBMYZVN3B5teTqekWMCSmq2W4FnAhWdKYNztJ4oW09RydHnDw84+GTJywWc5q2oZSIuQ4YVxiGhPWJ0BTckIlJsL5Rd8+CDwHvw6akU7MXQtsGKDNibBmGNcOqx8XMwhS++90znjw8InjHzDreffSAP/Yj38/3ftfnSAhjKhjree+Dj/jgo6cY6wjOMY4j4zBQRAg+0M4asJYiwhgTy9WSi/MLVqs1Jc8QW6oWgpBF9eje+/iSr/z+ii4GjG+x82Oaowe4ptEiGDviF1nRYxJWRmK/xIzXWDcjzB8w9isdjFP4WTRVailkE8AusLMj/HxOE+aEsGC9WrK+uIKcsSYhqcfkDmNUd8GaTMm1pMd4MBM1PBgKJve16VpnZGN8NYiwH+DbE9+/+lJx0Duog3AyBNY6jFOAWNKA5BFjQjWuG2+eCbU3CnpsvIQpn59z2dSdTFwB23SfUEzB2m024KYhqwHXBDQWPfGNOzBmc05DLWs32jlbciJFyMaoh9GA8co7YGul7KHl02EE0B6BNlgaD/OjhkePT3jr8RmL+QKRwuJkQTtvyJK5vlrqTSepzCojxhTaxjGfOUIwNG3DbLHAhQYxjoJXdNlCMztiTD2EFamCjllExSGMB+vJpZYTj1H7CXxCnBKBWDvx0GtJphfLW8dzvv3JGf/6T/wo7ekJ3sL6xQtkGPnst32G+Um7RZCN4QvvfhchfBHBVLdx+o63OWf1ubV5JadM1/cM/aCZD2eZhE2RwpAsf+sf/i5f/etfoitHOK817qlfMl6XWvU4SbUVSlyRhysoawVYRbg6j1ASWomXNr4GpsGEx/hWy7aN80iJjMtr1t3z6u5GvBEsmVwGilMMIhUd2hit+zIYpNT4fqqlVxZHRNQU6Bj3TN7O9I7cHjS336F979V2eza/q/ctGmpNA6voQJKSNJSyoSL1ZgPCbshB3SQuUglOZSruMbWzsAJ5N8699eaUbr6K6lidpS0GqRhQmURFqiGcSov1slUVywdHoWGGZg1CaAlNIRVBQsA3bRVEDRj3CVOE/38tIXjaBoIXFvOW4+MFsxCwRoil4L1ncbTg6GRB13UMlVhxHDWrIEbzptZrsJqBlHXmXQ8ZMVrCaqwwFEMsjpQtQxGGLBTncTZU2jAFZoZ+pFuv8aGhGEe2Du+D9huMIzH2UAonbcOD1jN3wsKMNGXg+vyaq2fPWRwdE8ViS0MRZRs2zkDOxNXkFms7s8hWnspgME6JItU1qTqG1tO0DcZ6TMmMuSdQ+M3ffcbf/ge/xPW6w3hPjhmJVE0ENjNBEqkDvQMZMUQdj8VgTKOU3qT6z2HMDOOPsO1DxBhSjEi3ogxrdevtxImv2RtE9zVZwU9kiuz1d2PSBnDUexKljZ8IVswu/+PuPHgb6LuNB7zuIhWEM2C8AqhYrCnMGo83Na5HcBtvyNT2YOWVpBpTxy5TUAUbK4+g974yAOnsvk0hlqp1CMUW7KZ8yGy4AaXsMG1P4cjESixbA1FqStA7j/MB38CYCsk5bGhoQiBUdq4pq7Bv+VQYAaVeyrhKhGCsop8xx1rxROUAqP3bxjBmbfpJSePIYJV1yBiPGEeWQBcNdi2YUBBU3MR4Szck1l1mnSARENvi2zlgMblnNtd4XkxhGDNu3RMSNN5grGeQQo4DsV/TAKetY946XAiMUbj84DkXF1fMFjOefOd3cvLWIyQLeSwkybW8uAJDzio4V4tN1AVU657Hgq3qRuMYEQPzxYIsBTuOiLXIGHn/w+f8j//bP+Y3vvYxxjRIXqL49UR35jZ4wzTQkAjaDAvU4ped/Lu+Mh7sArELiB0lR0oZQEaQDFawZUojlrp/qd+ovTk51/bpV0lvpwE0bWduXMHuW7LZ/tbM/nrLnh4NGzDW8PDY87m3FvzgFx/z5GyGKRYf3Maln05TiuJOth7NW4s3VVbMKP248w4fXCXJrd2ATLiXwVT+ClsxH21IViwg14zCpjagtsqbiaJsSkOWrSOjBsJXFiEY04AphmA9bWhoGo8LYXsfe5ZPhRFw1uD8iOApGMZxYL1ectUG2qJAR5LMct2z6kb6JPQpMw4D1jl8CPrAfUBcQ3ENo2nJ0dEtC2sZOU2ORTQYMikNLNeR9WCIeMTPsFZLUS1zSvBgBGcMUQzLdcF3K6zVGSIDEnsWwfD2o1PePjriOHiapmEYRpbrTqnKx8T1y3Nmsxmz2RwQ7fIqlf6sVh8aqa+2KBfBJL9hYmIcenJMZBGC95CFuFwzI9KHQHx+wc/9vV/hS7/6WxjTIqVD41bqzGX1BUHUH59ms1vu83ZmnlpOA+AQIpRrUkm1eWLapugLfQPBPzQzm1uf315/e9m3/r7BftfnN42GUGNkZ/Be+MEvHPOTP/6E+YmjDWlTmZegit9yoxAI2FYGVnTfOVtDtG334CscgptFqoRdzTJUxuldDMFOxhtuHGMKPTAW641+QzuhSCoCrgrpmiktfJO16PbyqTACTes5e7RQKi/nCTNVbFGcOyPZsO56Lq6WLPueNFVqOUNoFakVLLaZU8KM7GZEGlLvKVHw647jVeFo7nFoYVCMkRQFEa8zqg0VbDSk4pWswVtEEtKPeOlBRuW5txBk5MHRCd/x6Iy5ccRh4GJ9Sb/u6fsBI6I8BTkjVu8lI5vYzlJdO6r1zzUCLzDGRIwjeT2wXq2wwGw+V57DC30JUzMi64Zf/7Wv8nNf+i3GbLEm7WTwq8MsRmsFNjPJDtIFt34KOptbpNYJUEaUiHO3H71s5uPdmoX9QNy3MmvvW26nBt/keJNRnH7X1K0RnY1NKZwuICwCEYvfgPR18EjZhgPApEVZMfzNpRjjqvyc3aQKN6XA0yCsuI8eZxr0RZnn6/HthCeYmw1K24Kk6Rq0hyAlJdyNqZLtGhiGgVwSTfKMY/70FwvN5jO+7we/lxgjznma0BJCgw0NBkvM0A0jwzAwDiPOGdpWH/h85mhCQGygXZzQzk/IZsYqOq77QjdkUhq5XvXMZ5aZK8yD4G1m0hUuQC6GlCAXj7ctwTbkpKCfJKGQtHjJgJXMUbAsjBCvrxmGxKpbc7FckWOmnbXMF3OOT495/OQt2vms0kABGEpKlFG7JIsFI4WcatdkLnSrjtXymmHdkcZIcJ5u3Sl8ZhX9zV7w0fF//uLv8t7FGmdUCkvqANV3s7LkbjCFraN9c36qL/ctl1mm2oZSYKf6ewK8DlcTftJlX0bg0IB/PaMgFZwEBWatUT6AHBPPLyIvR8u7szOczDbxt87GFjHbfU3tzy+lbI85je860DVToCXsm2KhnW223YO6bDoGS9nqF0qt5pA9/4q+LzkrP2aK+vuYEsMYKdbgYsJ7y+gdLszwn3Yj0LYNX/yB79PUH4KzOgulLKQxMWYtu12ve3JV+GlcQIIwawOztsH7GbOjGe18QTYt89HR+MxsSHSDarq7HLFkMBX4cUZpyA2UYkmlkLKhZEcSGEVoDAScstlKxFvBucxR8LiSuLg4J42Rq1XHehyYhZajEDTNPUbGdcewmOO8h1KI48C47pGUtJjDOYzTlzTHRL/qWF1dM/Q9YxyRlIkmIv1aXygrSDZ4Gj56fsGXvvohIoVAJNXuuklaazso7mrfuO0JTJV5sa5+FYC7GbPbW/vfXvYBevctr+va3/57H45gXjV6xmG8A3pKHsjulOTaOghvluhaC1KlviC9mv+XOnA34iFm4wVsKgZhC/ZOHoFMM3oFfndcdqkK2SLb+sjd6kPJhVI1MHMp5DjS9yPrPrIaBoaYwXnm8xmz2QwbRm0/PrB8KoyA9563njyp9N+5FpFAiol+GInVnRmHDskDq9UKyQ6TPbPGMW8sbWuZt0abi6z2B8y8Y1wYxgjjOJJixpHBZNURROMuawy5RK3SzZE4GEpxIELrCzNf1NXOGeMLIRiOF3Mkday7jjEPFCwnp8ecHJ0QbEvs1lxcXIK1POh7FosFpoysrpeMQwQ0xWSdJbQt1hnGYWR1fc163W2o0GNSjyWLdlmKGExxGJv5R7/5+3x80dVU4fQ0NXV5Y76/NTZv/nnfID0EyE3rDnkD+wfk/cvrbvf6+07zrqIBFrx6maW7Inj4zDsnPHywIEXBhg2FxdbM1eYdahZnQub1Z20MquDmliKMbZXe5hFtQV8t5FPlajFbBQSRWqs5QTjVWkweAFScomRIYy17Hxm7gb6LXF+vuF51ZBHatiUEjw8t7ezo4FP7VBgBYy1tO6MEFQOZuqFySFjr6M1AKYXjo5areUOKHZK0PnrmnTYKNZY2FJyLFGPxttAYQ5ZC9JFV6elSj0iuZbFRqcFRQcsSLbZYGut1n1LBQbQupPEW3zbMLDw+tswcDN3Ii6s1T5c97xyf8vbDBS54clQ03yCsrq9JceTcW80QJEWD7aQ/bw1hPsNaBUS71ZpxyAx9z1ASPgRKnoyjQzK0wfFsTPzy119qbt0kEg1319XD3am12+DdfQPx9oDb/fs+j+B1j/mm25lbn2/jcGsyIhbsDN8ckctAzsLjh6d8zxfe5uzkmHHU9nN9QoIW4kzVglN4AJiJUGQqGJp0KiuBqDU1SxB2VIjUMEw5f2fMJk6fegomoRpTAYxXw4CJ6LTKrqWR2HWKH40Rsq4zaNfs2Hd0q4zzLU37Kc8OKPqqOX4LOjhLIRhDCVq0Y23UHv7gCM5irafxgUXrWcwCs3ZGCG0txNBGj5wNY4oMZSDbjmwGcjUCBm39teIIvmUWDKAFIlms9sMbwyw42sayCNCUnrZkHs4seex59uKa//sr73HVw5/5sScE21ByYX29ZL0eOZq3mlfPRanRs9SuL4dIIid1uWXVqdApwvJ6SRyUR15aw6k/0Vr0YcAQcNbQnLZ87evnPLvWOgPZzP775Df2AWrs/P46nsCbuPCHtt9nNKb9bg3avdtwx3Z3X5egFaVij2B+hvGBfL3CmJYnjx/x7Z87xRqVlMNpT4XUVK2xVmseJvyvlv7andh++rdB9m3t9d/hIjS1k895d7OZZ4M16GQoZRfanbIBspEmV54Cw6TDjGSsEULQ0NKHBzzIsFz1DOMIxpEJYD/l4iMiQhpG7d3GbIohbP0yJuLOTaegdwSn3IFHs8Bi3tA2Ld6F6ppV9pWcGSMM3uFMw7yxjCUprVjSh+qbQNvM8L7B2AZrjSLjVsuFg7U4B23w2HVGLiMSHR8+X/KPfvlr/O7TNX/8+z/PZ945IhpL6hLryyWp0levV52KQvqAMyqTZpwji6EftclovIqUEtUIXF1pqSdBM3lzNorJWCjGcrnu+a2vfsSYk9ZViLLeyp2A2idF6fcZkUMD+9D63c8OeSR3AX2va2h2r03j6yIe2xzTnpyQVktMgXk75zvefcCDo0yOnRaJIRiTFQxkIqMtG1Vfa2s9gPOVQVjPu+UBlA3D8C6DsLVKD64k2VNfwG43qHoGMqUxdtKRm8xOLR6auAV8vQaPxXsLTkudixjasOR61WNcYDQzYvqD1x34G8AX6yZnwIWI/EhlJf4K8Nv1s38qIj973zlyilydv8SFoKCNVTIHi92QN+Qq2NA0Df70hMZ7juYtszYwrz3+xtg6J2rjhJTCmBPzUlgcF8aUGWJkiD051ZLfEGjalqaZ4UOj1h+LdVODh6by2hDohhdcrK85Hwz/8Mtf5de+/pLPPHmbP/rdnyO0MA4j3fWa9RBpZ4GS4fJ6zaofGEdN3SyOFvjGEXOq8aUCgs47chpIKfL44QNSTMQx8vL5Bc45nl8u+fhiiZ/NGRN848NLfeEqoSRmUjc+5M7fNROz5/fb617HQzhkXA6d467z7TvXfZ7AvmvUFJzxDwjzU4J09N0lWM/ZgyO++IVTTtqi1Z8pYLHeZEAAACAASURBVMwc/ITDaAp3o29pTWWU8vjgN3X5pXbATtWCEw+gc26jnSllShXqdRm2ZCEbFMc5zQpMmprl1ZDAUEVva0lzEW0es75Vtz8EjPVY2+LCWqthi2eUQ8/sW9QdEJF/d/PYjflvgcud7X9PRH7kNY67WcZh5KMP3mc2n+NDQzObEdoW55r68ARrlC14MZ9j5nNmIbCYz2iqzppztWcf7bz31atoTCEL5AwxZ4ahZ92vKdlRioqDNE1LO5vRtjPcpgJMMI5a668Pqv8gsVx1/LPf+Ca//NWnRAk8edBwdjRnjIbcXbFcXfB8HXnba/fjehh5/6Nznp4veXqdwXuOjxxHM0dwhsZpiOOtUem0tuV6SLx4/pLVeqWkqabh4/M13/j4guICqcDFWmmrpRiEgJi+3v5ds+UhkO8ul/+uEOE2DnCXEfokyyFDdGjZXovqC1r87DFN2zJcfoikDsIZD86O+I7PLjhuLNc5VRWkFiNS66q2cbqtMfw0w0/nmYqyDNQKQTYztZlKfnevftdZ2qzbchdOH+aphHjnn+4gm6c8pkI3JLKAJ+AE2rZlsZgR5gtsO+di1bFcRfJhSOCT6Q4Y9XX+PPCT9x3nriXGyMfvv8/p2RlHJycq/yWCtIDo4HbG0TRzykIfwaypKZB2puk3M1EyqVWdCCCnTrwsSkTi+gbbtOSk4YIxltA0zOdzZvOZulhOe+qRUi27I3XXdNdLvvHBNV/+3UvW0dM0mfm8oZ1Zxr5ntVzz7GLFR89HHpw+BC8ImY/OO37rgzUv+5FUwDvlO7DW07YtnoQl8+B4zmK+YNV/yPOLS2RSTcqGIRX6aBHyRKsKYmryT5Wcb307HMYBNt/unnWvs+y+1rdn511D8EmQ/mk5ZFQOeQzqMm9cbeOw7gFH84d0q98jdh2GjDOFBw9mnCwiJhckJw2vpMX5jLjayyFojYfIJhov0+MX0QK3KkM+hWPeuQ2tmHJUFBrntk+oyKYGQfvQDEhlrZ4Kgm7d2WR4yk7p8DhkVkMmY5kbSxAD1uPnLU3wZGvpU8FcJUyOB5/wJ8UE/iTwsYj87s66Lxhjfhm4Av5rEfnH9x0kp8TLZ89V/08M4Cg4WowOcMA4jcV8EwDBN57QtrSLuQqAVELL6ctRa+y2bZTWUYoQQoMPA8OQakeXoWla5vM57azFeK9fUCmIqJEwFs4/Ouf50xW/+NvvcTFozf0sOD739hlWEqkbeX6R+Y2vX5Nx/PBMQ4tSLMtYOO8TfVbXLRahjyBkbNchKHv+x1c91l6SiiGLw0imZot2wD94daDtm5F3t7sdJ7PzORweqHdlAPZtd5fR+VYMwn0eyu2lXoMUJp4GEWiPHiByzbh8iVQm6eCFR2eO4A1jVNXpmEdMbnBuxNlIcYrrTOWGCs5p/wBQUXw96zSLO+cIIWxAviLgKgaQc64l/tUA1MYeY83GiE9UlLc9CmCnd6CQoipmnV92DFk4OXY8PGmm/mIslsY5ldLLkTiuDz7lT2oE/j3gr+38/SHwHSLywhjzY8D/YYz5QRG5ur3jrvjIg+MFb791yvxowaL1hGDxzlRWVYt1W4BQENWncxNhQv2OMJQsO6qwgveqZbiZ3dE4KhdIxYLLeG9p2hmhbRQTqGInCspMvydevnjOr/zqN/gXz3uy87gMZyen/JF3H1PiyDiMfPBizW9/uOTz3/YW89aT+sTLy57n1z1DAYzfzFCiz6BadktG6dKVHsqBgYlufT/qv3mSb/D3mw7Cu461Lz7fNU53Het1sxD7Qo3b59j9u7xSbecbZYVaX31TayzqYD07Knzx2y3BZsauJ45FlbqMVpMStDxcQ2lNESpf5MShqEh/mJpzNvUBOwPXbMODqW26CBRbleunNmKz885N29f7fkWSTCClwjhm+jFzteq5XI0M0dHOZooxpazFarGQxsjQrehW1we+l09gBIwxHvhzwI9N60Tlx4b6+5eNMb8HfC+qUnRjkR3xke/5wufkx//YD2N9QIzD+AacQ0ydTUWIIZGCo+QMuWjzhzNQEmms7MMp3hBwCE1Qy2iUnUczBsoCk1ImFeX/a4TK3FJxAL1AtIYewPK57/gC/vGv0qWvgvUYW3i4CDyaN1iTGWLig4srXg4d391o6826T7z39Ipn1z0Zu5lBts8ANrHrzgAwZss+Sz3/hHJv3/99g+quWP2Vb+DANq87Y78uOLfvmPu2eR1vZJ8BuLmveoHawWhsy/z4MSVFYq8pQWhZtJYf/8F3+ZHvPSb1PeNo6deWLre4Zk7JDiuGUKnDs0y6Fvo9Oacuf+O1aSyldKNBR9BCtxuUYDv4gIattcjITq3I+x6JYZdHYMoQWAw5F7phZLnquLzqEByPHx0TY2TsLBFYdyPL6xXrqyvG9erA8/1knsBPAf9cRN7bXrN5ArwUkWyM+S5Ud+Br9x0otC3f/vnPA6q5nqWQi4D4DUlDzp4YXKVWNqSS6naJHDNjnxiGUeWacyaXTDubaffdGMFUReJc6PqB5XpEpLBYLGjbRi/EooCiiKKuRZHaNEb8/CE/+Rf+La4k8PM//2VCA5992HLUGi6WhRdXHR+8uECM4ex4ziy0vEw950NmHRNGtMnpxsuyIdAvWNsoBlD9FceeYl8xB6sB6jew83NfLH0IGNwX2+9b3tSlf5Pt7ws9dq9vn8cwrYtqa02Dmz9AnKO/+Kbubi3GLXjn8TE//kOfoTWOi/GI8+vEy6vEaALNwnA687Qm1B4Co+IXO0w/rrJBee9ukn1Q3f4qlLpJ8e0sFqOyZsqwgkEQu+UQmNKDUznxLu243qqpk4EAmabxnJ4ccXp8RNM0iAhxGIgxcbnsuLq+pl/15PgJMIF9ugMi8ldR9eG/dmvzPwX8N8aYiL6rPysiL+87h3OB0wePN7nYnGv/fE6kXFs4s2U0oloDKZElUbI2TqQxE8dI33dqCGLU9E5JmqMPDTDx8BVWXc+617Scb1p129wuw4vOvVmU12CMmeV1pPeRP/Gv/DBf+oUv0/jCZx8fUUrkat3zL55e8/RlxEhDwNA2gW6MXPSRhGYqppdkD+xDkbz1DAzkPSSb26H9eq61tWbnRZzcytvbTcd709n/TfCB19nvkCdzCGvY8g9OrdfbngmLCXMILd24QtIV1qiGpAuetx+f8vZZy+Wl5fm14dkFPLscSTZzZmEhAVyorrpBipCT2ZQPe+8IwavoiNv2+kt9X1LaDripLXmjUrR7JyK1s7uyKU19BJvnJBuMa7eduOQKWhtDExyCpUGQlOlXa7oUuVpe8/xiyYvzC9arnpw/mSrxPt0BRORn9qz7m8DfvO+Ytxe1rhav5DPqhHvDUIEXSdodp80dBWMiRkYkRkosjENi3Q0Mw0hKkZQjWGWqH2PEJK01EBxDEl5eXHPdJx6cnHJ0jFb0iWzZc9E0kKREElinwrJPdBcdT19eMTjDWbB87sEp55c9H3/4Mb/zwTmXMXM8U62DXAYuVkuu1z2lhPoqbzv5bt49NwbnNky49XwPPr3p0+0WxsiGuGJSpnXOqWeTItZ6jLEbUtXXj9Nvewz3gY23PZJ9g/rQPd3+u9bKmYDYRqvgjCBxjbIkqSnAzQjhBBd7+uEc8CAWn8FbOHtwRE6FF1eZF5fw8QU8XwVms8BD5lgfNvl+jeeTVhHWsmHnJ7LQHdfeqvGZegs07betLDTGEKzD7fytj2cnBbiZ7TUrBUpkamSXf1C03Lx2Qkox5JhZxZ7y4pyhj0iOdOslXRpxNnF2FBjyp55ynE0eU6Z0nhgkZiRmcoxaNZgyOSblAhgj4zAwDJm+i4z9SIpKkDlrWqwLWNQC5yIMw8gYC9frkafPLxDnOV4sKlJrKk4QN1VgIltdt3GMLMe1xl/LjuA97z4+5ez0iMuLc37/wwvef35BEUcbHIt5YLnu+eYHL7laDuhj3h2kr+si3zVgXh1cxqg8WtvOcM5xeXmBta7OAjfVbLY8+fsAt30zOAfWHbrGu8KL+/CEQ6GAAA7cDOsqIWwe0cApAx7cDGPnUAopr5DUqadgjGpYWnhw1tKNwvVoWBdDJ5CtxTQzfKsFN85PM/z0bPWfs25DCDb1+e+GBMDm/dnY1iJkUyjOEaZUXykbI7PLOTAZ5anf4FXTL2BVEwGr3a7rUZvbLoeBp09fcDTzHM8Cx62nPX0EAv0wHnjmnxIjUEqmW1+DVHWXnIjDSOw7HfApkVImjvqzkBmGka7r6ftI3ydyqoQMTimffGiVacg6Yh4Zxshy2XF53bFedZh2popH1UtQC+vIkki5kMZEPwx0faRbq0Sas55Hb7/FW2dHfNuTM4xkLq4G3r9ILLPHuIbghHlwrIfMi+uBMTvUtxnYurGvsxyaOW8P1O1LYq2nFFive61mq6XPsENeIYqg5xzZP6C/leVb3e9bOL4RSpmacgpSIsp1IAoqmxaDCnGUsgYSBocYgyERfOHxOye0JzNaDI1kQj/iSsQ51RewztwoWVc9xTrY3ZSz32oFTjRiwAbsKwimyI0BrndSGQVvewTcxBC0cYntdnqH1RDVlmUD2Tj6VFivR3IRWi9I8TSmcDqf8+hkTimZK/nDqxP4A1lijDz/8COUakmIcaQfBoa+J46RMels3PeDtnnawBjHStM9klPBGiUXaUxDycq2Yqo7lapGoRqNUZuMpDAMkeVqpZJmVoCyyemmlBj7gTgoXXbrLcePzjg7NvxL3/d5zvKKq+sVH7245r3zXlOOVljMWprQ8PSi5+U6VnHuQ919+2a8fdsdmiFvblM22QchxriZobZpplo7Yd1WS+/g8q2AgLvXa/ase93j3uMpGMGQ2SiTmkofPoWPJZJZIxIxu3wHosj+ycNjFmcPODGJMfccjxaxllkQnNUBv52Jt738k8u+m4FS7GXbKDQJk266CqvewKYVuWTsprOwGgbzKnVZqfe26UIUYWorNrXmZQoVJAtj37PuezhqmbtE2845PT7iwdFcC+bu+K4/FUZgve758i//Nr5SI6uCy8DQDwyjKtnEmIgx1ThWK/GsBe8MbdMwa5z25/upShByVFmszf5jYhwzuRhiSfT9wDjEytCSGceINRM4mSlF2VkWJjDLLceNY03hT/zo93L+m7/F+fWK915ccdEVjCQkR45nj5j7hvc++JDrLlJkIt/c7VA/tLzu5/sBvamEVd3XUu9DNlmIbdGJipjcfc67PI/XcfHvAwDvOsf+7Tc03jIgeVpfC6qmjj5JiFQ2ZQTB1XAgUSTQzhe08zmJluLAhobQCm0utD7jfX1Gpqr5lqn9V+nQi0YWN65JwcJACEqUK0XRn40GQc6I260dMDdCgV0ass1db74rtt5cBQrV5BnKGOmXK/rlFYwjM1uYB1jMWx4+fMDp6ZHycCTI+fC79akwAqt1z5d/7Z/TtNoKjEzSTUr7PXGoGVstbUl4b5i1jtnMY61nPneEJmCcB6ezQi46sLt+YLlcs173rFY9MQtu1mIQvLdKy2zsFpwVqUyu+uU33mOLI5jM0emc7jOPePablo+ervn60wuSBJy1FEkMqfD1Dy/46nsvWfZDHZhV/2+DC9yFmt8VDx8aaDeNgrr8rnoG2xlgqmnJ+ZAHsj3GdpmSkofDkFdxhX3A4V2ZiLu8Ibn1mUAZdvac6MvBbOSmlT0KUUDWIhSTsa7w4MEJIbR0g6FPqnEYs4K/Qq3ZRyhZNhPC7nVIKVpGXCbeQQ0HnNemIaqMfYUoYeo/KBOD8J4KwFpNCHXw72ALE5YzBRMAzlga53HGYiQz85Zm1tDHjsZaFrMW7z2rbiBFYbkaubz+w6kT+ANbShGulhHWQi6FOGTa4DGmkJMCgMYYfBv0OZTCYtYSnAVxuODBO4pX0QVjPVC5/IphHAspa6pwvoAZhodnD3n77Se89eihNlw0Hu8dDk0tpqxVV5K1tdQEizhPYxwP336bL3/4nN/+6kdc9wGRSBILNHzlm+f8zodXWAopT1JXsH+222cQ7psdD8+a23Bgp8LsBm/gFoB+ddkdnMomrJTjSsppJ5LN6QpkN8S5bQD2hQFvCoa+ukwaiTe3rT0iJiAyICSQACzAJISRDJjswHVI7ll3A2N0rLtM32e6PnLRGQYHDxaRGAUjDstEO67n0paEjClKF49MbcOuVutW4pcCJUVF/qfbLkVd8ppS3NxpLlsDURTTwoCdalVArcFuK7M1WAeljNg04vJIigNWDOcvrsAIJydzno8J72bElLhe/uGVDf+BLCLCetVz3fWMSV+kxnsaq330FvDBU0Tr+I2RjSaftY5Zu+D0RJuPfNNozG8tRzkxjonj42MtQqqqQmAIvuH45Ijj4znzeUMI6nLpUNB8+lZRVlNpzlnWfc+Dt55w9uQtrn79Kzj7YKeoRypYNVUjOsyNAbnd7mbcvM9FPmQM9s2w089DXsTep77z+/b8jUk8OG44nbesViterC7JNKiKcm1bxlbPaZdpmFvHm87xptjC7v7334ep7wCAYsNm6x3s7KXdgIGPPn7GNz98yePHlmWf6daRF8uBF5c9J6GwPpqplsUGlJOqOaiM0FOdh3Wqfu2quIu69FuGoUmSDNiEAcCed0Fp200tAlLFhonlGDW29V1UD0J1Kr13nB61vHW2oDGR9TqzHHTb64sr3v/I09iWOCy5HiOrrj/4tD8VRgB0tl6tR3IB6xqtsTaZEgtt6zHWq/pOE2jnLadHLYvW07aBEAJtO2PWzgltg2kCzjukCH0/0jRDHcwVMDTgvGc2a1T1yCo7y0TLn8aEZAVcAIzTxqYYI2HmyMCjz7wL4iqYs31BpXLAqyKx2cRwEyq8nQO2934f4Hf3+n373zX77ttWryo44e2jhicLx4N5pnl0xlqe8Gw5cr7MLLuefoy1x34X49hn1G6f/02MwSHDeHvRct6UpwEyAYXaQKS0X9UTMsruMwwj5+cjn/3OI5Z5pMuZ83Xk5XLELBwxF1LNSLmpwWfn9KaGiCr9FfA1fb15EjuFPVNouXsHUrRCcGuodoxDBR13DVfe4RTQCrZSpfcyjYejFszCMfctbp0QMVyvep4/u8C7GcvVyLLrGV9VfdksnxIjwCZvPTXsxEEVgo0xBOOx3tG2nrZtmLWe40XLySLo77PAzFsVI208tm0UgRUIPjCfBdWZyxEpZkP/NJs5fPBq9SuSPiapzSSJKCrLbZyy03rviOOAC4XPf9d30h6dMqymVNuO+70zNrZOdtljAHZf8vtm7bsG0F2Ywe45Zc/vpl51oTGWGQlvhOBakEwaC6ZIbaeFm4P9dvx/6Fyw/9ruuq77rn33vqeBV//ebLpzbaLdquMAz58umc0s5iqRSySmRDdEep/oe+j6gXGMlahmJzsAOym9SjM2KUcZc+PSJoKbV3zAqThowwsgO/toFoCpVLgIJeetJiGWUslu2jaoLsY4sL66JOVCSRYTBe8bxigMUVvX2xBoreec/cunwgiIQBxGTCm1dj9XTjbP4njO4mjOYtYw8x5nLcEbghfmM8vR3DMPEEwm2EITLK7xOBc2tFu5WEockaRxl0qgCz5krEuIMcQSGYfEmBJdN5DxuGau6r5NwDcBWwpHrcNY4fu/94/w+OExH66fAu1NN+/Gr2oJRKYMwe5yKP7dF1vv+/y+z25vY278tj26DiRnIBbLVWdYZVgOHS+ve4ZitMsRw7bOodwVvd9xfa9ey+t5MbcNwKHjJXWoxevANPV3lFuyZGF9sWbuI49OLKtrQ9sYrMmkMZGi3VFEngzAFsFXT082YiRTsZBzN3P+N1D/mg2wVSoc2KbsalHRJvMx3WERDT+S9sFQqxWtsVgpWKBxDm8diCXmQhwSpViceLyFIgbXWFL2VWFr//KpMAKI0PU9OWe8VQs5bxoevvWQR4/POD6e0zZBwZKo2gGzVttAHSMUR8k9InMlXfQe7xuscWSJioYbQawyslpTtPTTZZSu25DHkaEfuL5eMiRojh/RzBrEWp3cneFofoQpIwbDk8dzfuSHfoAP3vsYrVbbnRFvvrBqHw6LP7y6zz5X/9D6137I7B9s21k1CVwMIH2hSysiBsy8bnMbCDyEcxxa/ybXeBe2sc+T4pXPVYTFIwSEnTSt0QHcWMPZUcuLZsUsWFovNN4QgvYFTH0Xsg3nq3Jx0d6VkslZOSmmXL41k7T6dsbXeoKJ4GSrTbDxXnb7BYRNdqBIqaIkEzApm8+N8whKuVfEUUxLztXXtJacUMYpo2Gp8147ag8snw4jAMqvX3OoTXA8ODviwYMZD45mLBYt7SzoTUdorWXmEqasyX3FDlqHpDllYvcNgAdfan+5UVEzoSelNVnm2GJJOTH0kRgzOQm5u0ZsoxTjVunGQ+PAO4ykyjoER8eOn/hTP8rP/8Iv0q07DM3mXoSJHEVf3m1p6L5Z7L64+a6Z8VuPv+XWYC4Y1mnXza4zvtzuZZyMwdRmfQgPuH39h9z/fdved6+3t5+OCfrFA6i2JbRgrnUCoaFgiUSElqOZVncuGs+juWXReJo2oAC9DljVjSrYOmNLqTUkCDEn5Ye0BitTn4ACzLkkpO5bSq51AROoqrN6yQUtfBLNatrdJjNUyNlutQrU06icGGIYorDsYdUbLteGPnttnLNQUCIdjNLnnZwe73neunw6jICB2SxgvcV5/TLOHiw4mbe0jVZjBR9obANNIEhHQ6b0A4VEGiJxbcizOWWYIW0LIWzifOrDw1S6LjF4g1rhUvO81mFs4fj4jBFH44MWi9Qvz1RX0NRafOM9P/wv/wA/+ZP/Kn//7/0DSlbFJJGE0gRPXW6yyc+L7A6CnZvfrNsX87Ln89v73l53n7E58CXcea7X2W/fMW7jBt8q9nHX9dy830oyzmTkjFggY4xDCVssYhO+sbQzoWmE+cJz3AYW85ambXB+qtTTpiVgJ+SrdLTW1Fs0THDe1AI8VfRNvRrTHUw9A5u/t8Up2yPX0uBCUWWjajgm8dOcEilG1v3IxbLn6XnHWIQkkI1iBmIg5YgQcUHf7UPLp8MIAEcnx4RG8/Tz1nE0n7FoPM5oVWATAlDAGloDMvTk8ZpSRhwzcvCMqzlNaCnNAtp5zckWTC3oKNZhfQA7x/l5naG19twZQ3ZQuh4vOuhLihjrSURMyTTeE4cBay3jODBfeP7Cv//TDMM1X/onXyb3vhbpvPrAD+fn4fVBtEOD5K79X3efu7CE+85/17HfJGQ5dJ2v+/nuusLktZhaqGWtNhi1TWAxCyAjIVidaKxiRd7VGX0HcCyirnapHAAbARGnephSW4JvlP1mlb67afhlm3qe1k6FaXWmn8KKIgVbag1EJbzd8AyWQsyFoRgGAr148F7VuRFKTgwxkkquWEXC2cMv4KfDCBhLaBY0rcNKwjrNyRo0fjOofLmUjC3K/5byCCTGsa+Uzw3WHdHOOtJsReqVUESYCEgNmAZjBWcbsHOlYioDKWckQ4yFOHYUW/ApU0qkWEXGrXOUqEU0bdvialz27rc94Gf/k/+Adz7zWf7u3/0FLs5XCA5qPPdqDz+3ACR4vVl6J3C8sf7254fChNvexSEDsM8LuX2+Q/u9zsB/E6Nw6Jy319/GA+r/kqsDGCgSEYHgPCenM06OW66vMt5a2sYznzXMvNUaFMmb2v0NjbixWKvMU64yWduaHdD2bAXljFUFomGAoR/JR0mPVzJSFYs2xmK67kpUCux4DTqju52GM3UYBGct1jiKsRivxKKpCM4bgnekZBhLpHWeedtyuphzNJ8dfMKvQyry7Sjd+Dv1Ov4HEfkrxphHwN8APg98A/jzInJeGYj/CvBvAmvgZ0Tkl+45CWKDqv44izGRlAtjTJgiuL7BW7ClJ9gEIWqaz1uyc2QMqai7XYowDgOyWsI4Itbgrcc6hwKzXrkGkn4ZqRikKP14KQbrmqqCVIhxIDFSjMH6hrbRFGXBgIAzKjn26PED/uLP/Dk+/13fxt/52/+Ar3/tA9arSIxxxxBIfaksyp2q16q1/bcfyH0x88EHeevnPjDx0Lluu+1vct7d49+37SGD87pexl0hx+76rSQYNEhZY4wQLHzmyRneZzCCszCfO548PsZLwQdqufCUFqzpOqjJhik2nxqJhJzLJlWYYt6ECXFMFdwrG3EYKUo8AmyrDU3tLNy5h2nmt0iVy5NNPUKOmVTLl7HC0XHLmCKGQjtrgQZvtAnOGwMpk+MnayVOwH8hIr9kjDkBvmyM+fvAzwD/l4j8ZWPMXwL+EvBfAn8GpRX7HuCPA/99/XnHYhgTpFKYt1J7rqdUTSGPHQMRb0aaWXXXrKO4lmbuwQasX1Cs1Qfc94zZIE4HvJtcpVrkYa1BnH4ZcYyQhJKKyp3VevE49gxZiEXANbii2IQYi0qmBYx1OGnJecQHw0/9G/8aP/QjP8j/+89+jV//td/hg/c+5OLiknEcQbQk9PT0lM+++xlAuL5a8uzpM66urhlG1RtUmqlcqdCmF/r24DyMiu/fZt/f9+1/e19z6+ehffYN5n2DdZ8xuG+f258f2sewycZIRKy+I8ZA01jeeftU3X0jzOcNj88WnB7PoERmVpi1TZ1tVX1IGUXq4SuiP+Xxpz6CDU8DU/pvoq3XEmMrOtCzVEWjlDWL5bYEJZPXOqEaBqUiy0hlKK0gbk76jhQlQ53NPC7r9rNZg8GSx0gcRrphjRRfAc79y+swC32IsggjItfGmK8AnwP+LEo7BvA/AT+PGoE/C/zPolPfPzXGnBlj3q3H2X8ODF2ElEZyBjcTTOsgg6Fgk7LuudYQvM7s2WkeX1GEgDENBU+MBZFIGQsJTac473EhYF3Q352nOKkdhJmSC3HUlmHnNMUTcyYJJLH41uK8pnmsCVjnlSHGqatv8Trb58S7nznj3/53foqf/uk/yUcfvuDZ0wuuLleUIjRzS13AYAAAIABJREFUVb15953HDH3H849f8I2v/j6///Vv8v7HL3n58oo0jsRYuO4THz873zwh6suxXaYBcmiw7AMR9xmGb2UWvi/EOHQth67vLu/jkPG4DwNRlkaRDswci0qLhyA8euuIdt4y7wsU7cjr+wERw8wbZiHgbe0+LDWctA5ThJRHcs7a1Jam9N+WHyA0npjStvhNDFZUTUuSwMRYNMX5sMEfpqyBhjITyFghTtG2YSUsBWrTkXZTaMqbUjkOS9baFyn040gfO/pP6AlsH7Uxnwf+KPD/AO/sDOyP0HAB1EB8c2e39+q6g0agFFj1ShSSYsFlw9waWuuYOwt5xBiLJ2CKoeSxNl7YDZGE821lm7GVSXgg5aR6BT7gmhZ8g3HaaVikMIwRaxXI68cIAiYWnFXDhFUZKe/Ue5hQXC3zFki5xpBT+igTx4H1com1hnfeecS7n3lCStvCkr7vuL48p+86xmFNaAwPjmZ0pwvK0CGNEMKcD15c8vGzzZO//U3sWX9oAHJr/aHY/XUBxNvr7vNA3mR5nTDoTcIO/WGpNf+mAD3eqvLTzDvEF3KrzWqlOGUY9to4VaDO5gL1p0zIf5aNMfDebmsFrCFUbgFntW4gl8yGiDQlJXzxTlOLm7oA2aD/U3i4+Uan0mNr6zr1RjGWbt2xXA+ExoPAMIxIMQxjJMaRYegxaMfjoeW1jYAx5hjlD/zPReTqVnWUGGPe6Nvf1R0IzZyuT6w6VeNtxXDkDEfBMvfax40xmNKSR0NJphZuqEiJCSpSmjEMKSE5IWkk50FTI22LNUcYMrkkSnKkWt9TKhNMmDWUJFCU3001DRwFi7Pq5uWUtGzYGorfAWw2RqBsS0xL4bosN4IVJWspsmoMDgzdwMtnL/nmN77Js4+f0w2Zrlsh40hqhcvLKw67z9xad9tN3/vEb/3c99nt5XVd+7uO9bpexrTvoXPedY67ziVQdBJBII4jz56eMw6fpSTVEGiCr1tW9oFSiClvpcMnvQvDxnUvUki1pDfnbepv0hxUvYyqQ7gBibX018qGDnUbQrAFBfWcN6nNNuXJ6hxo9iErBtF1A0UK3qmuRSmTupbe210ko/CaRsAYE1AD8L+IyP9eV388ufnGmHeBp3X9+8C37+z+bXXdza9mR3dgsTiTUjQmJyfW1rAOhlXIapnbQusCJWf6yYWzAWNbxpLIqSdhiGnQcs484iXhiGAL1mRCqNa9FJIYivGEpkUsWOsIzhOtZgmcFpYhoHoGMeF9IceRoQekEIJXlZnJAFT3LedMHqvqcc7EFIkxgRhyzsqEHBOrqyXnLy5YXa+IURhTpu9HckyUNHK5vk0HdQjs27fNH+SyL3a/Kx6/vRzCAN7E62DP+kP7voqXiAxYc0Qpln4QvvaNZ7y8GMlRwFTqMatqYEZAStSBW4+1KfQyMNF+IbJJA4JmB1SAVD1GLXvfMg2llPEOlKGwkr+y7Q7cJRGZJpKNHNHO7UzGYRwjwzAyNbqmmKuOpoYxxkDbNjRNoNSmuUPL62QHDPBXga+IyH+389HPAf8h8Jfrz7+1s/4/M8b8dRQQvLwLD9BzgLfKLZjHgZUIS5c5bgprGwkIs2ZOHJNWYhWH9zOst/QxESWSSyYES4ojkiPzYJj5otWCOWsfuKTqHhrwAeO2mQNnA856UhHsTkeXlYrSGjYNHjIBQfUrklIqi4wQa/nx0A0Mw8AwRNbrgZwAUcYkcqFbrbi6vGAceq0Rz5mUEnGIrFJmiHe16d6eje8aIG8y4HY/Y8/n5p7PDh33PrzirvVvErLsBxulJKTO82MyvPfhFd/8aEUTHG2jFYK5ovoWQAS/wyNorMFkJWspVaZc1YxMBQFtzRLkyu1oFVisnkTOGZMSk3CJBpvb8mLDtqh8IjDdKGDBBngE1UUco/Jf9sNIqSlDjU4F7/R6g1EsTLGqfSzX2+V1PIGfAP4i8OvGmF+p6/4rdPD/r8aY/xj4fVSYFODvoOnBr6Ipwv/ovhMYwJmMkczQJ66GyMIXhrkw+sJgI0MD1rU1TtP0moyJbhTEBG0GskZTbrmQrGU0Gsu7UuW+pNaCWwUJrVWswHmHMwHvLC4mNRhUI+ANrgk4H1SZtopOhCo7PWnT5RgZh5G+G1her/Tfas26G7m8XNF1oxJLpBGLFqYM3RopGSkjSMY7QZwwrPpKEHLfYLlrgNxnIO5z6Xdn/dcZwLe33ReqvKmn8qb77PNYJiHPiEHFOV4sI7/z/oqzk5aHJ4WjxmCy0tU5Q+0y3Xl6ptJ5SSUSpYJ6lk1D0G6vQPCNxvvWMDFWlZKRYinWYkWzClokpGcpqL6BFA19hSn+v338TMqRmJU1CyO0baOeRdVEmErbU9K29mZmcXfw275OduCf3PFN/Ok92wvwn9533N3FGLBWsFZz9V2KXK0T1/NawZ5GnAfjA6GdYUwA25IlIKZgjAcTwDisrflbLGMGjyWJJ4kWXhjTYMMcQkPTqAahC0F5+J3F0JOTahAUDC7YykNfOfz9jvKMVIOTInEY6Nc9XdezvFxycX7F+dWSq+uOp88uuLi8RnLGGeFk0XK8aPBW8AbaxpJJLBaBEUc+H/Sh7DXe983Eh/7e++Rf47P7XPj7jvemx7nLaLyJB7FzRGOAiDUtAOsh8/7zFVEE74XGBrwYzclbAdF+k4maXaqhl1KTeGYyAjoR5JR26kF0HzcZh4oRTHiR1hrcHNgiVIC6/l6zBOol3HwJtIIx66TmHKFtaFqtLCzGVYYsT8wFhogUlDhn8SnXHTCV5hkLrrVYFzAeshUGKSzcDPwR2BnGL7A04FqCa7DBYOvNa7nnVMmlxxZryXjG7HDJqeqQaAumtUZTQbYiu1QAxmm5sqK7FqzfxHbObsUjVatgpO97uq6jW3es1z3L62suzi84v1rx8nzFe+8/48X5JeRCGxyPz44gLzg9CviZhiHWZBpzxIs4MMYE0sAmBQjf2qDcXb6Vmfj2vm8SQhy6ztcxJLexh/uMxl3nE5SMNFDIYFso8P+1dzYxsmTZXf+de29EZGZ9vM/unp6x5Zkxw8JCg2ms0SAsswPszcDOK7xAYgOSvWAxyBtvQYIFEkICYckghCUElr1BfAkJIRmDDeOZMTPjHrdb3dNMT3fPe68+MjMy7sdhcW5k5quuelXVj5msp64j1at6EZGRJzPinjif/3/rDJRDtJBjAtQQp13BBQGayi9QatmtTg+O5CLr6oNuLebNNksbjP0ENbGtlnOwe1Rsm+jaAxjZr9afpOgGhWIrqB+NRWgaZvt7eB+MDt0b8E4B+lU0b1cc9+/MOLgzvfAbvBFGAKBtPNPphKaZMPN7vHSv4cGBsj+BB4cNdw9m5q77gGrANR2+nRj4qFjMXkquuILZrLqZWDKemD0lCZlC8QVJhexL5Y0TkIrlnkq1whsrLq5y04siKuQ4wkdFhrhifjLn+PiI05NTFvOeJ4+POTo+YT5fMV8szUAse0skpUDfNvRdYK91SGcXqvPQTBrezUtrUFqvhevG8xfJRzUAZ89x3arAVWL6q57rKsd+OCdgE1ygREQnzLqWTz6Yce/OhM4XG8hJiewKjVccHlpXw84NqGhJmZwSOVlvSU7pQ3Mim3ieNQFpyXmdJJQxx3gGsci2VbWr4dhAirEONYyCzMqQB4f7NNMZbSVMCSGg6jhZ9HC8pAXatuHh/T3uPzi88Nu+EUZAEJqmZX/mEDx3ZsInX5rx6oMpdw5aDmaBSWtgIyCUIvh2ggutuWe1kaKkSIwrK4lobeQQMKivLTgsLRVmLCNESAV1DkFsVkFsUNbmsQuaLF53IiRshtxuHOM/PD4+4snjx5yenLLqbTQZIDihcY69SUfem7GKaU2pDmNuwzLTHpuPOJn3FPVb9/Z5T8OrLuiLnuBXXYxnF/LZDPxF5/yolYKrGphn6XredhAVcBEhczhr+PTLU9qJIw+JobeaOt7AOkpp0NKYt1fyuqFs9P60cg6MkOLAujIEY6Z/482MlaPNx7QFbexX45SpPHWebZCaDQmK6SNOme3PeCW0FPF0E5u2FR/IWXj05JTQnJKK0nUNL33iHg8e3nQj4MwITDpP8A137wQe3Dvkk6/e5+GDQ2YTh6gNYghiSMDevoAYzSJrznWGICFaUW98JXzcirFyLhCjYbflUlsvvTUGOWfWXbPVcb21Caei1vpZmz/SYBh0qoWYBtPHOaaTKdOJEBNM5wPN8ZxhlVh2DTptrQlJAazGPCQjOw3BV7ppOJ4bzfTT3MNXdcG3t28v3rOG4KrexXn/vyyZePbpf55cZNAu+hxXCQsu2CcCdaALCl4K9/YCrz7oiClzEiPLtLT7IBgwrJSxfbeiCI1MQtsxumwWp+UCKspQbRgaWYZHBOhxfmTM/o/5Bkv9jGHEpiw5vgaoxscMkarig+dgf8bssEFCR9N4IyZ1wmqwMWr1npiULnju3Dvkzt2DC7+5G2EErMvKevGzKogtqG66x2xvn8O9BidjIw4GBFkMI160kAzgm5ILzjWW3KEguHXCxuDDDUsgayIUNTZYsnURBgszSrYF7hB8UNRJJZIoiKgNOHmhcQYi0nYN3aTj7t07mE8D/TJyfDSnnTxmFVccH53gFx4vjpgN524uK9rgcUDXeEpT6CMs+3rja+ZpwpLLFun2Qvkorv9Vcw0XvefZfWflsnzCeV7FWSN2dv8VdFXBDGoC9TiJ7E2U2SQwX1rpOOcBEWhCSxeMNJT14meNLuSdQGWutu4evxn+KtR5AzH4L7FW4TUQrVQyErHRY4Mao5ag62dRS45bzqluqgaojEQmQNt0TJoON5ng2gk+GKuUlkQ7WHl5BaQhE4AmeLrwHFOEPxwRojqOF0tyXLE/OWRIQq5TdohlYQ1rvaICD3EN/mhLHsRby6dKQagccWpTYc4H0Ab1wUaFxRPaUAEXPDhr/nGNEVZQyzdFKhdu0xCCEJpgKLO+scyx5JrYtKd5KYXFfEE3PUZRjo4XhO4JWU+JWRliYVAzaCEIpWQm3ibBjpepwmZvy0Uu+dljOHMMZ4676gL9KGHCZee87LyXeSAXneu6noGCRkQKXdOwGlYG2NkG4hCtn0AN0nuTGLLe/SKb7j5GdKFii3JcrPZMt3s25VInRG17yQUlU1xZV5rG7/CpjkBq6EAhp01icQ117hzSNjSzCe1sivimTrXWdRIE8QYpVgrkWFgN0MdzS03ADTECRZXj+YL5ckEQQ7XNQp3SUtIIeyVY0kSMakxdda9EyRVwpGkbghprTgiVF55c+eE7fDNBXbFZhKYSl4hQaj+2SCENvsKNC1kKKsJ0OqMJlXOuaQiVvpqKXOy9EVXklCsFuDJf9DSTCUNWTvuB+XJFTMVCmlLwwZJDrlPa2PH4aEEsCWjW9eUPL/6L4vCz7vjFF/3Dr7+u53BZfuGi977o2MvOd139zuQZBFQtFsslcnxywmLRE4IBiky7hhKThYLOo62vbvv4JGZ8UFeeS0skxhjRYt5hkVr7L4VYEiFGUk5r7grz6cwjGEFJ3LqXYDNqPjYG5TziC26HBwZ3LsHuWwtXzTNerQbLMQ0wP10yX/SoCjpkjk96RI4v/LZuhBEQERqfeXjYcrA35aV7E6YdiGT7gL0jhcpCi01UKpZLCC7YtpJxIjTeyoOqGe8dwXtKScbx7jqablrxBqFtW0JTX19JHXJJVmlI48VziPdMJiNldSC0TR1NNj9xPQpabEhk7NRCjBNxsVwyXyyJKVMJZ4gl0/aFaefIrbAaCo+fLCuYRfVBn1pMV3nqXfXJe51j4HrZ+e1tV/EGrrLgr+L9POMcolAfDClH3nn3Xb75rTf58T/xSYYhU1Qqf6USS6apxCE2vWf/jLF6URsVzllJ0cqGY8k4pVzvy0KnTQUaKZAV11gtf/NUH5OFG13HRZ/rTMJ4KyA1P1BzDo230eS4SgxZmC8j80WPiCP3hffeO+W9J0dkcQSFk6MTHs1ueImwCY7PfuoBMSYOpi13D1ru7wmNy1AG4grygAEvjl4aNsQhzllGX5XGW4KkaTxacu3uc5Ris93OdTSzCRlz+yZdR9OGWge2drGigeQcaRgs+Vesi0yE9UiyDw2hDVbuyWWdOLJaciQOkVUfWc6X9MvlJrObE1mr16FGdxZjj8qEIUG/KiAVKPNDeISXLdirZNkve91Fcp1zbR//UXITz3r/88KWZ1cFzKBmhIBUr/HJ0ZKvfeMN7j28y7JPxJQM0MZhuJQ16Uct6WldkGPn39grUNSMhZXmjHKsqBrY51OGw/Apt3UdeRJGTME1HsGWURh7CSiQMRj+cZIwx8TRKvLBycCTk8h8ucJJQQfh3fdPeev9R8z7gSBwOAlMuxueE2iC53Offpl+vqRzyt3DGft7HaENdMHhqFaxurmGr2AjmuKtWlBSJNaL7SsyjApoLpb4cR4JjqZrcNLgEboKKJlSMiQqJwieXCHBFLsGKrXts2aDc8kQrSxJHucGytpFXJwsWc6XLOcLNGfuHh7Sv2zlRJwntBPaJrDfKp1EWl9Y9oVVrQGL6Jpm+2qu9/O4z9dN5j3Lfb9qGLL92rM6XOZ1nPWOrnBsDdztl2O1yrz11vu8/8ERPjQgjq6bGt5g2HiTAKqbuRC7xiPUd+0HKPrUrECouSFVwyUctYspIc4REFISQghIwXgC3EbbNQJVNQBmfApryje1cKRXePf7c17/zge8/b1jjucD3kMrHaukvHe04Oh0gUfZCw4vF0Pe3wgj4JxwZ3/CQYDOOyazCc2kZdZap17JhRgH0lATMdXNzkWrd6BkzUgppKysYjGEIMmkmFkNK5rJHiUkQsmG264FtFAyxJisb8AJQktKxllo2dxi+IPqKYqFBIO3sU0R4jAQY7SS3yqy6lf0y56ToxPSamCvbfiRT9znwd29yhzTglhs6ShoGkjLE9783pyMlaDGMqLJebH+9m+2jnuWXMc7eNY5LzI4F+UXruq2Xyc/cdXk5Xhs2CrDCTkPPHo853RZ+LFP3yUOhf3ZHZom4yThFTQlcozWGFSsMcxAQ62LVKhegRr3JBrwCl01AqhAHTEuWohRcc4wBko20A/7qRhCwprXQCsCts0QANlalAV7MMQ+sipGye6DoWqnUvju9+cMw2NCaNA0sOcck8ajmhn6/0+gIj8wUcWRcF5xQUEMFHJYWSNGzpmhuuelFHxoAVfLiUboWHKE4BAawCa0EIe4gGs97WSPppvgxNUuQSxJ54zLbhVH3DdY9Ctiv1pDfSXN+EYpQ2IY5wycxYaxH1j1PcMQ6VcDi0XPcrGkX/Sowp2DQ/Zme5SiNG2D956T+Qknp8c4Ak4d2njc+z1ppLribMf4eYv9o7ro29svOsfzGIyrGqeLwpfLEoVX1evZHsLJ8ZzvfucRr/3ZP0XTeIJr8UEhR1K/YrWYk1NcZ+4Ra/UdgUC0hglj7sc5D7WcLAKhThNaxJjxSKUU84ZspYpWMtPRexWEII4yvoeAkebYlOI4N5yThZ5dcHzi/h26puPxyZJ7B4959PiIHDMlOqQUmgDiWhY3HW1YVYnLAY0DGhw5RVguCYbBZJdNtYI45Gopm1ouLKQ8WCKwa2hGjnhvBiA0TR3QCDjxlqRBAUeMZlSGHBlWmVIEnM0CrPqhtorWUKRR+lBwvnYtpmRP/dM5/XLJqo+shhXLpaEXN85z9/CQu3cObXzUGchEM2lZLA548nhCjGZsluIYhoT1BrSMIJkbeZ5Y/zoJvcv2bRuUq4YmF+l80cJ+ntDmKu9pSdflsvCNb77On/8LP8nnP/8nyclaw4fVkhUQ+yWCrME/glgFAKTei4mRnixn8whKLkQSWnMEI1qYgGEWyBj/W2JR6lTqiEU44hRsGCvqH07MwKi9d9M2zMTh1eM7pfVCS8KlKfc7Ia4yJ4+PODk+JZ5G5kmJ6WJgkRtjBFaLJRojMmlR8eScWdXGiXF8cw2zJIqOk1Rg/IXIBkhU7MePcXVR4pAsQ9wqvnIY5CGR82DNGypoEfrVitUq0Q/Kss/EIdt5o6KukDSSYmK5mLM8PWV5espqPme1XDH0PUNKOOfYm85wrmVvtk/TGPZBaAKT6Yyus7Hl+fyYpYOSnRGXMCaTzhqAyxb0eU/S6z7lr5KAlEuOe9a2j+JdPOt1Zz/z9vudfc+nn4IG+Kl88MEx3379bb7whT+Nd0IcMmgmrTzOG/I1pc6MSK0KpEgaWa5USakQYyLGhDjB18x+ii2iHV4sHrfhHusPMNQfWScUwe7zTU6g9g6s9R1DB1BxNF3LtJtSfGA2JIJAST2rU+F0lQmSKEHIAY7nA6vTnngOF8YoN8IIWJ//CrAYXQdPRkmruE66UK2m9954BCvDjHNWkgPb3zStlQaDJ7hakgGkZKRkcrRpQU0DMfWUHO0LVo8mgSykmOhj5mgZmc8jgie0LRmhT0o/RJanC/rFksV8zsmjR5w+ekwcepo2sLc3I2YlNC1dN0Gd0HYNuMCqt3ZjRSjZKNm///gxi37Bmkb7Q7H/+oviek/VD33Rz9j/vG72VV531oBcFqqc/Q7Ofs7zqgXn6XpOeKFwcnzKG99+kzgo+/enQE/KYV0u1LEWXWP1kmplINeBoloFSHksFYIGm2bVPBK2qlWp6r27Zh9a15Ur+7DbJAZHpmKHrvdbcjIZ1wAZF8C3AdpAUks8xiHiJJJbRxcKsKRfqvEsOs+TC67MjTACTpTpFEosCNGANiqDrIkN2QSpuG1u072lWhhWxXjdnbVxNo1Di4Ni4KG+aQjdlLbxNUQIBuThrLnYwCDNBQ8ESsz0q8wywlFvrlQIjuJgyELMSs6BKB0aJnSzA0iF1dJ6/gVHKY4hFZargXY50MdMPl4Q00DMkTgsSWngYH+Puw8fsFiOYJTjLfs0f/2zZfP0YJ1YfHrf+D1eXz7qE/y8c5w1as+K/bf3X2a4LvMUzntNQUvijT9+i9/+7d/jz33x81BsDsVmBOy4DdRXPatyZqLP3mt7vmDTB8B6/zi/MnoAG00s7xQLVp7cahpinEHQcT0UMoU8DNCsrF+g6WinLft5D/HCtHMsTk+QxwOL3rN3GMja0E1nvPPW+d/ijTAC4iCESC4DvlIoy5AhGCKKNIadFprGuvwcSE4gEEup4J0REIa+J7RC8EpwluzrpjP2D++QdUoIHd5PDAOu9omrFhgy6hSXE3kYmJ8kTnvHo9PCMoMPBd9lbNA0IE2LMLAnU5pQ0D3IZUYZEpLAhRYXYH56gubE3uEhe3dmvHL/Ifv7eygFaYSXX3nIW2+9S/zN/4Z4NbIBsWhUn1rNz36Kj/FlWsd+1ynVbct1ynZXNRDXPeZ5jc54jktCH9fy9lvf5zf+9b/n8bvvcTBtmUzsHkOwEjCg6mr3oJX91DlUwnqRS+UlCL4yGos9WEZymZItEqV2AjaNtbN72VgWBXSLlAQ2fIapcmIMQ1yjG/ku0VRT5T10k4DDxu27riU0LU07YX9/nyElvGv43xdQAN0MI1CfYCkl1CsiARdg4sEFh0oESQgF0YCWYM+VsT4rI+gHlk0thVgiqQykNJBitJBij8ouFOrQBlv4gJGUlViEIpZsPFkkjuYDhRZcxucA4uh8S9tACB2dM1pr1xmqkRT7mexPeenle7x075Bp1zKkZGPOcc6Tdx+Rc2E1DPzR177K1775BsvFMaFpSQWKjlTa5+UDznehN6OsbO1/liF4Vkb+PLf7otc/T5XhskTjs/Q8LydwFcM1ioDaA+C9Dz7grbf/L6/cv2M4gSHgxBGcIwS7VxpvXmfKwmaWpYanvrYBj8k/v5kFyDlXyHFrbGsaqxAJW7zOZ9qDcx5ZjCuuYcmkFBlipKjStgGH0DSBdjqlUaWbZMqeVdHiwT537x5y784d+mEFkg1966Jv4umnzW5ERN4H5sAHu9blOeQhL7b+8OJ/hhddf/jBfoYfU9WXzm68EUYAQER+V1V/atd6fFR50fWHF/8zvOj6w24+w8W9hLdyK7fysZBbI3Art/Ixl5tkBP7JrhV4TnnR9YcX/zO86PrDDj7DjckJ3Mqt3Mpu5CZ5ArdyK7eyA9m5ERCRvywi3xKRb4vIl3etz1VFRN4Uka+JyFdE5Hfrtvsi8h9F5PX6+96u9dwWEflVEXlPRL6+te1cncXkH9br8lUReW13mq91PU//XxGRd+p1+IqI/NzWvr9T9f+WiPyl3Wi9ERH5URH5LyLyf0TkD0TkF+v23V6DbfaUH/YPBrf/R8BnsfG53wd+Ypc6XUP3N4GHZ7b9PeDL9e8vA39313qe0e9ngNeAr1+mM8Yn+e+wjpsvAr9zQ/X/FeBvn3PsT9T7qQM+U+8zv2P9XwVeq38fAH9Y9dzpNdi1J/AF4Nuq+oaqDsCvA1/asU7PI18Cfq3+/WvAX9mhLh8SVf2vwKMzmy/S+UvAP1eT/w7crRT0O5ML9L9IvgT8uqquVPWPMYLcL/zAlLuCqOp3VfV/1b9PgG8An2LH12DXRuBTwNtb//9O3fYiiAL/QUR+T0T+Rt32im5o2N8FXtmNateSi3R+ka7N36ru8q9uhWA3Wn8R+TTwZ4DfYcfXYNdG4EWWn1bV14CfBf6miPzM9k41f+6FKr28iDoD/xj4ceAnge8Cf3+36lwuIrIP/Bvgl1T1KSzwXVyDXRuBd4Af3fr/j9RtN15U9Z36+z3gNzBX83uju1Z/v7c7Da8sF+n8QlwbVf2eqmY1JM5/ysblv5H6i0iDGYB/qar/tm7e6TXYtRH4n8DnROQzItICPw/81o51ulREZE9EDsa/gb8IfB3T/RfqYb8A/OZuNLyWXKTzbwF/rWaovwgcbbmsN0bOxMh/FbsOYPr/vIh0IvIZ4HPA//hh67ctYuOy/wz4hqr+g61du70Gu8yWbmVA/xDL3v7yrvW5os6fxTJdR9eiAAAAoUlEQVTPvw/8wag38AD4z8DrwH8C7u9a1zN6/yvMZY5YfPnXL9IZy0j/o3pdvgb81A3V/19U/b5aF82rW8f/ctX/W8DP3gD9fxpz9b8KfKX+/Nyur8Ftx+Ct3MrHXHYdDtzKrdzKjuXWCNzKrXzM5dYI3MqtfMzl1gjcyq18zOXWCNzKrXzM5dYI3MqtfMzl1gjcyq18zOXWCNzKrXzM5f8BjUED5c3U3o4AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcace1c8438>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2202,7 +2088,7 @@
      "output_type": "stream",
      "text": [
       "Predicted caption:\n",
-      " a man in a suit and a bow tie eeee\n",
+      " a man in a suit and tie is standing outside eeee\n",
       "\n"
      ]
     }
@@ -2220,7 +2106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2263,19 +2149,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 70,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcacd278470>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2283,7 +2171,7 @@
      "output_type": "stream",
      "text": [
       "Predicted caption:\n",
-      " a giraffe standing in a field next to trees eeee\n",
+      " a giraffe standing in a field next to a tree eeee\n",
       "\n",
       "True captions:\n",
       "A giraffe eating food from the top of the tree.\n",
@@ -2307,17 +2195,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcace0e6cf8>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2325,7 +2215,7 @@
      "output_type": "stream",
      "text": [
       "Predicted caption:\n",
-      " a bird is standing in the grass near trees eeee\n",
+      " a giraffe standing next to a tree in a forest eeee\n",
       "\n",
       "True captions:\n",
       "A couple of giraffe snuggling each other in a forest.\n",
@@ -2349,17 +2239,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fcace068748>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
@@ -2367,7 +2259,7 @@
      "output_type": "stream",
      "text": [
       "Predicted caption:\n",
-      " a brown bear is sitting in a grassy field eeee\n",
+      " a dog is standing on a grassy field eeee\n",
       "\n",
       "True captions:\n",
       "A big burly grizzly bear is show with grass in the background.\n",
@@ -2453,7 +2345,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/23_Time-Series-Prediction.ipynb b/23_Time-Series-Prediction.ipynb
index 69a35b5..f8c5759 100644
--- a/23_Time-Series-Prediction.ipynb
+++ b/23_Time-Series-Prediction.ipynb
@@ -32,7 +32,7 @@
     "\n",
     "We will use weather-data from the period 1980-2018 for five cities in [Denmark](https://en.wikipedia.org/wiki/Denmark):\n",
     "\n",
-    "* **[Aalborg](https://en.wikipedia.org/wiki/Aalborg)** The weather-data is actually from an airforce base which is also home to [The Hunter Corps (Jægerkorps)](https://en.wikipedia.org/wiki/Jaeger_Corps_(Denmark).\n",
+    "* **[Aalborg](https://en.wikipedia.org/wiki/Aalborg)** The weather-data is actually from an airforce base which is also home to [The Hunter Corps (Jægerkorps)](https://en.wikipedia.org/wiki/Jaeger_Corps_(Denmark)).\n",
     "* **[Aarhus](https://en.wikipedia.org/wiki/Aarhus)** is the city where [the inventor of C++](https://en.wikipedia.org/wiki/Bjarne_Stroustrup) studied and the [Google V8 JavaScript Engine](https://en.wikipedia.org/wiki/Chrome_V8) was developed.\n",
     "* **[Esbjerg](https://en.wikipedia.org/wiki/Esbjerg)** has a large fishing-port.\n",
     "* **[Odense](https://en.wikipedia.org/wiki/Odense)** is the birth-city of the fairytale author [H. C. Andersen](https://en.wikipedia.org/wiki/Hans_Christian_Andersen).\n",
@@ -86,16 +86,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
-      "  from ._conv import register_converters as _register_converters\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -119,11 +110,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from tf.keras.models import Sequential  # This does not work!\n",
-    "from tensorflow.python.keras.models import Sequential\n",
-    "from tensorflow.python.keras.layers import Input, Dense, GRU, Embedding\n",
-    "from tensorflow.python.keras.optimizers import RMSprop\n",
-    "from tensorflow.python.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard, ReduceLROnPlateau"
+    "from tensorflow.keras.models import Sequential\n",
+    "from tensorflow.keras.layers import Input, Dense, GRU, Embedding\n",
+    "from tensorflow.keras.optimizers import RMSprop\n",
+    "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard, ReduceLROnPlateau\n",
+    "from tensorflow.keras.backend import square, mean"
    ]
   },
   {
@@ -143,7 +134,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0'"
+       "'2.1.0'"
       ]
      },
      "execution_count": 3,
@@ -165,7 +156,7 @@
     {
      "data": {
       "text/plain": [
-       "'2.1.2-tf'"
+       "'2.2.4-tf'"
       ]
      },
      "execution_count": 4,
@@ -185,7 +176,7 @@
     {
      "data": {
       "text/plain": [
-       "'0.22.0'"
+       "'1.0.3'"
       ]
      },
      "execution_count": 5,
@@ -285,8 +276,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 16 ms, sys: 16 ms, total: 32 ms\n",
-      "Wall time: 30.1 ms\n"
+      "CPU times: user 13.9 ms, sys: 55.4 ms, total: 69.3 ms\n",
+      "Wall time: 157 ms\n"
      ]
     }
    ],
@@ -574,27 +565,19 @@
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a507cee10>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6ab00579b0>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Esbjerg']['Pressure'].plot()"
+    "df['Esbjerg']['Pressure'].plot();"
    ]
   },
   {
@@ -606,27 +589,19 @@
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a4c19cc18>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a507d9e80>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Roskilde']['Pressure'].plot()"
+    "df['Roskilde']['Pressure'].plot();"
    ]
   },
   {
@@ -859,27 +834,19 @@
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46be8a58>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a507d9358>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Odense']['Temp']['2006-05':'2006-07'].plot()"
+    "df['Odense']['Temp']['2006-05':'2006-07'].plot();"
    ]
   },
   {
@@ -898,27 +865,19 @@
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46b8dc88>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a48d91f98>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Aarhus']['Temp']['2006-05':'2006-07'].plot()"
+    "df['Aarhus']['Temp']['2006-05':'2006-07'].plot();"
    ]
   },
   {
@@ -928,27 +887,19 @@
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f6a46b8d7f0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a48d3a828>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Roskilde']['Temp']['2006-05':'2006-07'].plot()"
+    "df['Roskilde']['Temp']['2006-05':'2006-07'].plot();"
    ]
   },
   {
@@ -2116,7 +2067,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f6a48b09be0>]"
+       "[<matplotlib.lines.Line2D at 0x7fcb3fc12898>]"
       ]
      },
      "execution_count": 53,
@@ -2125,12 +2076,14 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a48b722b0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2156,7 +2109,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f6a48a1ce48>]"
+       "[<matplotlib.lines.Line2D at 0x7fcb3fb54cf8>]"
       ]
      },
      "execution_count": 54,
@@ -2165,12 +2118,14 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a48bf3d30>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2231,17 +2186,7 @@
    "cell_type": "code",
    "execution_count": 57,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1456: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model.add(GRU(units=512,\n",
     "              return_sequences=True,\n",
@@ -2340,18 +2285,10 @@
     "    # These sliced tensors both have this shape:\n",
     "    # [batch_size, sequence_length - warmup_steps, num_y_signals]\n",
     "\n",
-    "    # Calculate the MSE loss for each value in these tensors.\n",
-    "    # This outputs a 3-rank tensor of the same shape.\n",
-    "    loss = tf.losses.mean_squared_error(labels=y_true_slice,\n",
-    "                                        predictions=y_pred_slice)\n",
-    "\n",
-    "    # Keras may reduce this across the first axis (the batch)\n",
-    "    # but the semantics are unclear, so to be sure we use\n",
-    "    # the loss across the entire tensor, we reduce it to a\n",
-    "    # single scalar with the mean function.\n",
-    "    loss_mean = tf.reduce_mean(loss)\n",
-    "\n",
-    "    return loss_mean"
+    "    # Calculat the Mean Squared Error and use it as loss.\n",
+    "    mse = mean(square(y_true_slice - y_pred_slice))\n",
+    "    \n",
+    "    return mse"
    ]
   },
   {
@@ -2383,17 +2320,7 @@
    "cell_type": "code",
    "execution_count": 63,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/magnus/anaconda3/envs/tf-gpu/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "keep_dims is deprecated, use keepdims instead\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model.compile(loss=loss_mse_warmup, optimizer=optimizer)"
    ]
@@ -2414,15 +2341,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "gru_1 (GRU)                  (None, None, 512)         818688    \n",
+      "gru (GRU)                    (None, None, 512)         820224    \n",
       "_________________________________________________________________\n",
-      "dense_1 (Dense)              (None, None, 3)           1539      \n",
+      "dense (Dense)                (None, None, 3)           1539      \n",
       "=================================================================\n",
-      "Total params: 820,227\n",
-      "Trainable params: 820,227\n",
+      "Total params: 821,763\n",
+      "Trainable params: 821,763\n",
       "Non-trainable params: 0\n",
       "_________________________________________________________________\n"
      ]
@@ -2541,16 +2469,117 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 70,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:sample_weight modes were coerced from\n",
+      "  ...\n",
+      "    to  \n",
+      "  ['...']\n",
+      "Train for 100 steps, validate on 1 samples\n",
+      "Epoch 1/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0086\n",
+      "Epoch 00001: val_loss improved from inf to 0.00398, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 68s 684ms/step - loss: 0.0085 - val_loss: 0.0040\n",
+      "Epoch 2/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0048\n",
+      "Epoch 00002: val_loss did not improve from 0.00398\n",
+      "\n",
+      "Epoch 00002: ReduceLROnPlateau reducing learning rate to 0.00010000000474974513.\n",
+      "100/100 [==============================] - 71s 713ms/step - loss: 0.0048 - val_loss: 0.0043\n",
+      "Epoch 3/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0031\n",
+      "Epoch 00003: val_loss improved from 0.00398 to 0.00258, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 71s 712ms/step - loss: 0.0031 - val_loss: 0.0026\n",
+      "Epoch 4/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0029\n",
+      "Epoch 00004: val_loss improved from 0.00258 to 0.00250, saving model to 23_checkpoint.keras\n",
+      "\n",
+      "Epoch 00004: ReduceLROnPlateau reducing learning rate to 0.0001.\n",
+      "100/100 [==============================] - 67s 670ms/step - loss: 0.0029 - val_loss: 0.0025\n",
+      "Epoch 5/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0028\n",
+      "Epoch 00005: val_loss improved from 0.00250 to 0.00248, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 71s 713ms/step - loss: 0.0028 - val_loss: 0.0025\n",
+      "Epoch 6/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0028\n",
+      "Epoch 00006: val_loss improved from 0.00248 to 0.00243, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 68s 678ms/step - loss: 0.0028 - val_loss: 0.0024\n",
+      "Epoch 7/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0027\n",
+      "Epoch 00007: val_loss did not improve from 0.00243\n",
+      "100/100 [==============================] - 65s 651ms/step - loss: 0.0027 - val_loss: 0.0024\n",
+      "Epoch 8/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0027\n",
+      "Epoch 00008: val_loss did not improve from 0.00243\n",
+      "100/100 [==============================] - 65s 650ms/step - loss: 0.0027 - val_loss: 0.0024\n",
+      "Epoch 9/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0027\n",
+      "Epoch 00009: val_loss improved from 0.00243 to 0.00239, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 65s 652ms/step - loss: 0.0027 - val_loss: 0.0024\n",
+      "Epoch 10/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00010: val_loss improved from 0.00239 to 0.00239, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 65s 650ms/step - loss: 0.0026 - val_loss: 0.0024\n",
+      "Epoch 11/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00011: val_loss improved from 0.00239 to 0.00231, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 65s 652ms/step - loss: 0.0026 - val_loss: 0.0023\n",
+      "Epoch 12/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00012: val_loss improved from 0.00231 to 0.00229, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 65s 651ms/step - loss: 0.0026 - val_loss: 0.0023\n",
+      "Epoch 13/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00013: val_loss improved from 0.00229 to 0.00228, saving model to 23_checkpoint.keras\n",
+      "100/100 [==============================] - 65s 652ms/step - loss: 0.0026 - val_loss: 0.0023\n",
+      "Epoch 14/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00014: val_loss did not improve from 0.00228\n",
+      "100/100 [==============================] - 65s 653ms/step - loss: 0.0026 - val_loss: 0.0023\n",
+      "Epoch 15/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0026\n",
+      "Epoch 00015: val_loss did not improve from 0.00228\n",
+      "100/100 [==============================] - 65s 653ms/step - loss: 0.0026 - val_loss: 0.0023\n",
+      "Epoch 16/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0025\n",
+      "Epoch 00016: val_loss did not improve from 0.00228\n",
+      "100/100 [==============================] - 66s 657ms/step - loss: 0.0025 - val_loss: 0.0023\n",
+      "Epoch 17/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0025\n",
+      "Epoch 00017: val_loss did not improve from 0.00228\n",
+      "100/100 [==============================] - 67s 665ms/step - loss: 0.0025 - val_loss: 0.0023\n",
+      "Epoch 18/20\n",
+      " 99/100 [============================>.] - ETA: 0s - loss: 0.0025\n",
+      "Epoch 00018: val_loss did not improve from 0.00228\n",
+      "100/100 [==============================] - 69s 685ms/step - loss: 0.0025 - val_loss: 0.0023\n",
+      "Epoch 00018: early stopping\n",
+      "CPU times: user 15min 17s, sys: 4min 8s, total: 19min 26s\n",
+      "Wall time: 20min 4s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<tensorflow.python.keras.callbacks.History at 0x7fcb3e686940>"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%%time\n",
-    "model.fit_generator(generator=generator,\n",
-    "                    epochs=20,\n",
-    "                    steps_per_epoch=100,\n",
-    "                    validation_data=validation_data,\n",
-    "                    callbacks=callbacks)"
+    "model.fit(x=generator,\n",
+    "          epochs=20,\n",
+    "          steps_per_epoch=100,\n",
+    "          validation_data=validation_data,\n",
+    "          callbacks=callbacks)"
    ]
   },
   {
@@ -2564,7 +2593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2586,15 +2615,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1/1 [==============================]1/1 [==============================] - 4s 4s/step\n",
-      "\n"
+      "\r",
+      "1/1 [==============================] - 1s 729ms/sample - loss: 0.0023\n"
      ]
     }
    ],
@@ -2605,14 +2634,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "loss (test-set): 0.0021468019112944603\n"
+      "loss (test-set): 0.002279780339449644\n"
      ]
     }
    ],
@@ -2622,7 +2651,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2643,7 +2672,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2726,39 +2755,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 76,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a180459e8>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f6a48abdbe0>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69fc02f710>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2786,37 +2821,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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f9HhtQpzNJOjzobaRDe2GsztKPXWDURq5CCFEP9mSWUZTq637E4UQp6yuuW37Sk/KMFttdoqqG7tt4gIq0wdQVN1ITlk9j3x8gFm/W8MFf1rnOfCrL4OMNTD+agiOgWWvQ2g8HPyo509IiLOYBH2+5Mr0tS/vVFk/XTOiG52ZPmnkIoQQZ0pmaR03/nM77+zoefZBCNF7GSV1rs9Le9Bps6iqCbsOCT3K9Kmg750d+Vz23Ebe3ZnPyNgQdB1yyhs63+HwJ+r92IRl6mujCWJGQWV2z56MEGc5Cfp8yNOePlcAqBnagj6bBH1CCHGm7MqpcHys7OeVCHFuO1Zc6/o8v8JDINZBvmNcQ0IPMn2RQX74mQysP1bK+CFhrP+/C3hm2SQAimuaOt8hZzOExEHsuLZjEclQIUGf+GYw9fcCzmmO8k7cRjY49vdpxrag0CZzZoQQ4kxJz61SH/Pcg76K+hbe2pbL5wdO0mKzY9Dg9vkpXDs9sT+WKcRZ78CJatfn+ZUNTE+K7PL8XEeGbmgPMn2apnHbvGQCzEbuvSAVk9FAs1W93yqu9hD05e+AxFmgaW3HIpOhqQoaKyEgogfPSIizlwR9PuQ502d13dZW3il7+oQQwpe+8/ctHDhRzdzh0aw9UoJBg6LqJi75y3qsNp3BYRbyKxvIr2hkVnIk0cH+5FbU8+AH+wjxN7FkQhwAT31+hOUbMvnhwuGcPzKm2zex3WlqtXHRM+spqlazyW6aNYwnrhx/2s/3XHbJX9Zz1ZQE7rkgtb+XIrqxNbOcWcmRbM+u4P+9t5dRsaGMHRLq9fzssjosZgNDwrrP9AE8uHi029f+JiMRgWaKazsEfTWFUJ0Hs+9xPx6RrD5WZEO8BH3i3Cblnb6kdW7k4tzTh6F9eadk+oQQoq9lldbR0GKluqGVtNxKmq121h4pAeCdO2YzKTGcY8V1ZJXVsyWznPyKRh7/9jjeu2sOL9w0lRV3nceUxHAeeG8P/9mVzxcHT/Lq5mzsOjy3NoNrXtpKVmldN6voWkZJHSeqGlk6cQgXjYnljW257M6TslNv8sobOFZcx9Orj/T3UkQ3SmqbOF5Sx4WjB7kuZKzcV9jlfbJK60mKCsJg0Lyf1FgFXTTAiw21cLK6w/uqrHXq47A57scjU9THsmNdrkuIc4EEfT7k7N6JW6bP2cjF1C7ok0yfEEL0JavNzhV/28wN/9xOer57EPX985KYlRLFP26eBkCoxcRFowcBcNWUeNd5AX5G/vW9GSRGBPDz9/dx5xtpWO06t81Ldp1z0lMZWS9kl6kug/ctTOUv103GbNT438Hi03rMc9nGjFIAzMYuggLR7+qbrazaVwTAvBHRfHf2MOakRLHmcEmX98suqyclJsj7CZU58PSwLufrxYZaKOmY6Tv6OQQPhsGT3I/HjIKgGDj2vy7XJcS5QMo7fcjzcHZH+2LN4JrTZ5DunUII0acKKhupa7ayN7+KH7+7B4DJieHsya9iTFwIAIPDLJyXGkVydBCPfGss1Y2thFjMbo8TEeTHyh/N58jJGgDCA/0I8jfyr02q+UNJ7elVamSX1aNpkBQVhMVsJDEikLyKLuaMfcNtz1JNeMxGA7quo2kS/A00K/cV8v/e20OrTWdMXChj41Q55/yR0fxh9VGqG1oJCzR3ul+rzU5eRQNLJgz2/uCrfqo+bv0bXPy4+/48h8GhFg4X1bQdsLVC5tdqVIOhQ67DYITRS2H/+9DaBGZLr5+vEGcLyfT5koeRDbQf2eCa0ydBnxBC9CVnq/hrpydQ3dhKRKCZ80fGADB6cNueorfvmM1vr5qAv8nIoBDPb/gC/IxMGRrBlKERJEcHMSjEwt5HLwGg1EvQV17XzMMf7WdbVnmX68wqrWNIWAAWs/p7MSwqkJyy7rscflM5M6MNLTYqG6RKZiD6IK2AVpvOhPgwfnrxSFdgnhKtMnjODp0dFVQ2YrXrJEcHe37g0mOQ8RWEJqj3UiWHPZ4WG+pPWV0zVptjO03BLmipheGLPD/u8IuhpQ6K9vb8SQpxFpKgz4faMn121zHn/j5dM4KmYTf4SdAnhBB9LNOx1+6Xl43lkcvHcvv8FK6YFMd3piYwJs57I4meCrWYsJgNncvIgO1Z5Vz23Ebe3p7Hbz49hK57H0qd1aGcbVhUELnl9V3e55sst7yewaEqOO/JCABxmkqPwq5XoYevR13X2VdQzTXTEvj0R/NYNDbWdVtChOrI6e3nll2m/p9NjvZS3nngA9AMcON76qL63nc8njYo1IJdh7I6x3urrHWABsnzPT9uvCrzpjC9y+cmxNlOgj5fco1ssLYdc2b9HCUGutFPGrkIIUQfyyytIzrYn7BAM7fOS+a+hcMZPiiEZ66dhJ/p9P/0aZrGoBBLp/LOg4XV3PDPbQT6mbjz/BQOF9WwJVNl+97dkceYX6/mh2+ns+5oCc1WG0eKat2C0KSoQOpbbD0aZH2m3PNmGt/91/b+XgbVDa3UNFmZOzwagMNFNVy/fCu/XXWon1d2jmqphxdmwsofQ/b6Ht2lsLqJ8voWJiaEdbot0RH0FVQ2erxvVqnK4qZ629NXsBMGjYXB42HUEtjzFtSVdjrNeVHANasvez0MmeJ9JENonJrfV7i7q6cmxFlPgj5f0gzoaB329LXL9OEI+mRkgxBC9KmMkjrvbx77yKAQf0pq3IOzlfuKMGgaH95zHj+5eCTRwX68vDGLvPIGfvPpIeLCLWzKKOP7r+7klx8doMVmZ+rQtjejyTGqtG1ffjUDQbPVxucHTrLxeBl2e/9mH/McGaJFYwYxenAID324n21ZFby9PY/6Zms39xa9lvFV2+drnuhRtm/dUdWoZVJCeNtBuw10nbBAMyEWE3kVDezJr+r0esoqqyci0Ex4oF/nB9Z1OJEG8VPV1/N/Ai0N8J/vdjo11hH0naxpguZaFSymXND1wodMUXP8JMMuzmES9PmaZnAbzu7c0+fc76cbJNMnhBB9Sdd1MkvrGT7Iy96gPhIT4s/xkjr+tvY4r23OZnNGGX9fl8nM5EgigvywmI3cMieJr4+WcucbuzAZNN66fRY7Hl7E5MRw3k8rAGDqsLY3yHNSohgU4s/rW3N6tAZd13lvZx6vbc6m1Wbv/g690NRq4+fv73N9nV1+ZhvMtNrsfJBWQE1TKza77hrTMCwqiF8tHes6r77Fxmf7i3r0mIeLanjh6wzScit47YsdbNu+mfd25vHvrTnY+jmoHXCK9qn3Kkv+CCd2ddvhsqnVxvNrMpicGO6e6XvnBnh5ETTVkBARyBvbcrnyhc28szPP7f7ZpfXeSzsrstQQdWcpZvw0uOAhyNsKVflup8aG+QNQUtMEuVtUtVXKgq6f64iLoTIbTu7r+jwhzmIS9PmYbjC57+lr18gFJNMnhBB9rayuherGVlJjfBv0TRkaTlldM3/64hiPfXqImx0lkFe2G/tw06yh+JsMHDlZy6+/NZa4sAD8TAbuv2g4mgaTEsPdGsj4mQzcNGsYG4+Xedwv2NHWzHIe/GA/j316iBG//JxffLj/9J9YYyVkb+Bn/9nNx3va5qodLKzp4k59790defx0xV6+9fwm0vMq2ZRRBqg9X/NGRHPz7KHMSIogJSaIFbsKevSYf/zfUf74v6Pc9tKXXLjpRsZ+dg2PfbCTRz4+yOoDJ335dM4+J/erkQbTfwDBsbD/P12e/tqWHE7WNPHQktFtXVVzNsPx/6mg8avHmJ0S6Sqvfm+ne7CWXVbvvYnLCcd+u/jpbcfGfEt9PLLK7dSoIH+MBo3immYV9BnMkDi76+c69kp13v4VXZ8nxFlMgj5f04ygtys7sbeNbAAV9BnOgkYuXxw8yb1vpbFqXxFNrbbu7yCEEP3E2cTF15m+O89P5fhvl3DsySWMjA1G1+HtO2Zx7fRE1zlRwf787JJR3DJnGMumJbiOXzg6luNPLuG/957X6XEXjlZdRrdkqL2AL67L4P53drP2SHFbR0KgpqmVZ748RkS79vfv7HDPnvRaaxO8cTW8/i2ePHYFK4e8ytGHZ2A2ahw6A0FfYVUjNyzfxpUvbOaP/zsKQG55g2u+21c/OZ8AP3XR9MkrJ7Di7vO4dnoiO3IqyHL83LuSV9GAhp2/mF4gwVBOqNbAX8dlMDQykH9syOz3EtYB5eQ+GDwRjGZIWagaotg9Z5OrG1p58esMFo6KYXZKVNsNu98ASzhMugF2v8GjCyI5+sRifn35WPYVVLtGodQ3WzlZ0+R9Rt+JNDAHQszotmNRqWq4es5Gt1ONBo2YYH9V3lmeoc5rN4oh6aFV/O6zDp0/AyNh6GzIdn8sIc4lEvT5mK4ZXB07oV0nT2fQd5aUd76yOZvP9p/kvrfTmfnbr/jlR/tJz6uUDnNCiAHHGfSl+jjoo6UB86uX4rd8Lk/PM3DXghTmtH/D63DH+Sk8/u3xnWbKmYwGj3Pmxg0JIzzQzIbjpby6OZs/rD7KF4dOcutru5j9+7X8dtUh/nfwJJc/t4k9+VX8culY3rhtJqAyhfaak3Dok1Pbn3T4EyhMpz7xAsK1esZXfIn/4Y8YEh5AYZXnBhx9aePxUrZmlRNgNjJ1WAS/v3oCAJ/uLUTTIDEysNN9rp4Sj9GgsSKt62yfrusUVDbwXGoaC417qbzgtxA7nkuqP+CBC1PZV1Dd47Lac15TDdQWURqQwssbsyB1ITSUQ7HnTPI/NmRS22zl54vbBWV2myoJHXkpLPg52Fog/XU0TeOqKfGYjZorQ+scxeG1vPPELoibDMYO46Xjp7VlAduJDbOoRi7lGRA13HW82jHmY/mGrM7fI3GWym62yJxMcW6SoM/XDEa38k50m2tcA4D9LCjvbGq1kZ5XxQ/mJvHmbbO4cPQgPkgv4OoXt3QqzxBCiP6WUVJHgNlIXKiPBy2vfxoKdkDJIabsfoRfXDqqT4aFGw0al4yNZeXeIh5feYhLx8Wy55FLWP7daUwbFs5rW3K46400rDY7/7lrNtdMS2D+iBh+e9V4Wqw2Wt+9RTW4+PSB3n/z419AUAw7zvsHi5r/QKslCjK/JjbUwsnq7stNvTqRBicPdHvaseI6LGYDb90+i9d+MJPrpicS4m/iRFUjcaEW/E3GTvcZFGph4agY3tyWy9eORiKelNY1E9haxaUnl0PqRUQtuEc1BCk7ytWN77NwVAxPrz7iCkB67Ojn8LcZ8Na1504jkFpV6vqHrbU8ueowDbGOvXRFas9bfkWD66JvXbOVN7blctn4OPdxKIc/gcYKGLlYZeRSL4T0f4PdTmSQHxePjeWj3Sdosdpd/+YeM302q/q+ziYu7Q2ZCrWFrvU6xYb4U1pdr/YCRqW6judWdPGzTZypOqxLF09xjpKgz8d0zeg2nF3Tbeha2z/72TCyYXdeFS1WO3NTo5k3Ippnr5/Czl8uIjk6iM9lD4QQYoDJLK0ndVAQBsPpB2Be6Toc+FC9ob3yJTXja+MzffbwP7pwBJoG04ZG8Nfrp2AxG7lk3GD+8d3pbH94EX+/aSqfPTCfacMiXfdJjgpituEw/oXb1f6k9Nchb1vPv6ndDhlrIPUiCqqbydATaB15OeRsJD7UpMrlTkXRXtXI46W5cHhll6ceK65l+KBg18/OYNCYPFQ1uokLD/B6v0cuH0d8eAA/eHUnj31ykP/syuf9tAIq69u2T+RXNHKX6VPM9kZY/JS6+Dr2ShhzBdqa3/Cn2c34GQ38bMXenjd1qcyF974LZcfU3rXjX/TsfgNdnfrbnm9VDVkKiQGTBUqPkFFSx/w/fM0/HNmyFbvyqW2ycvv85Lb7N1bBJ/errpijl6pj478DNSegTJXtLpueSEV9C898cdS1nzIpykPQV54BtmYYPKHzbc5AsGCX2+HBYRYMNSdUdrFdpi+vw4zAQ4U1lDrHriTMUFVY2Ru6//cR4iw0YIM+TdNyNE3br2naHk3TdnV/j4FJ10xuIxvQ7a7OneAs7xzYmb5tWeUYNJiR3PbmIsRiZt7waHbmVPR5xzghhDgdmSV1vm3i0lQN790M1Xkw+nKYdD1MWAbrfgelx3r3WNZmWP1wp71EiZGBrPnpAt68fRYWs3t2KzLIjyUT4jq1tk+rYrkAACAASURBVE+KDuIyw3asRgv89KiaS7brlZ6vpTxDZWaS5nGishE/owHLqIugpY6phgxO1jSdWkn/V4+B0R9MAbDpL12eery4jpGDQtyO/WBuEgCNLd73kw+NCuS/983lpllDeW1LDj9/fx8/W7GXJ1e17d0qqGxgkSGdhsQFEDNSHTQY4cq/g18IUYff4LErxpGWW8lvPj3Ys+e65y21V//+3RA2FFb+BCpzur/fAFdbqqp4inU1TuRETStEj4DSo+wrqALgz18c43BRDa9szmbasAimtBs9wv4V0FwDl/8FTKqbpquZSv4OAM4fEePYS5nFqv1FjIoN6fRaB6DkoPo4aGzn24ZMAb8QOLba7XBsqIXoFkclkpegz2bXuX75Vn7v3N8XGAkJM1XmVohz0IAN+hwW6ro+Wdf16d2fOkBpBrfh7Jrd5urcCc7unQM707ctq5xxQ8IICzC7HZ+dEkVDi439JwbGPCkhhGhosXKiqpHhvgz6VnwfjqyE2PEqi6FpcOnvVaOJ1Q+6j+npzvqnYdsL8PrlUOw+ZDwhItDzm2AvBof4cYkxjYyQWRAUBcMvVrPWvDTf6KRoj/oYP1WVU4ZbMKQsAM3AhKZ0Wqx2Kht6eZGyqVplTmbdCRf/Ru3NKvLcFr+6sZWTNU0Mj3X/2S0cNYgfLxrBE1eO6/JbWcxGfnvVBHb+chGbHlzIDTMT+WTvCdW6H8jMzibVUITf8A7t+/2DYfKNcOBDrk62ccf8ZP69NZcX12V2/dzsNtj9ltrvFpkC178FLXXwn1vAOvAbtHWlqCAHgBJdZVkLqxohehSUHuXoyVr8jAaCLSZu/Oc28isauaN9lg9g77sqMzdkStuxqFQIiHQFfUaDxuofz2fTgwvZ9OBC/nvfXM+LKTmsLpbHjOp8m8lfDWo/shLaXUCPDbWQrDkqkdoHfeVtQd/OnApqmqzszK1oe7xRi1UDm6rTbIgkxAA00IO+s55uMHbO9Bk6BH0DONPX1Gpjd14Vc1I7NyeYnaIyf1szy8/0soQQwqOsUrVnx2dNXBqrIPNrOP//4J7NKjsAEBwDFz8OmWtVx8KeOPYFbPyzKhE1WWDHP05raYaiPQzWKthsnqMOjLhENd/o6R6lwt1gCqAxbDjbs8pV4BwQDvHTGFatxlEUVfeymUvGV+rC58glKhtqMMO+9zyfWlIL0CnTp2kaP1400q2UtSsxIf4kRARy94JUrHbd1Zyl+qgq2zMnewgu5j6gLtJu+CO/WDKGb08ewh//d5RP9xZ2Ptcpax3UFMAUx4DwuIlwxfOqnDX99R6t1Wcyv4aCtFO+e3VJHnW6hXpUSW1hVaPqnFmdR3bhSUbEBvPEt8dT2dDK0MhALh47uO3OjVWq3HnUZe4PqmmqhLJgh+tQoJ+JhIhAEiICXV1ZXary4a1lsPVFFbg5M4YdTbpOjRnZsdx1KDbUn2StCKs5GIJiXMdz2s2adM52zK9obCvxHHcVoEF6D/8fFuIsMpCDPh34QtO0NE3T7uzvxZwyzdg2kB3QdKv7nj6DH9oAHtmQnldJi83uCvDaiwr2Z1RsCNuyJOgTQvS9kpompjz+BXOfWsvVL25m/KP/4+aXtzP84c944esMj/fZkqlmuU1ODPd4+2kr2AXokDSv823Tb4XQeDWbrCc2P6syRMteg/HXwL7/qDfMp+rIp9gwsLJpghqt4xxInbOxLftYmaM6FHpyIg0Gj+fdtEJKapu5a4GjAUby+YRXHiCIRpY+t6l3XTxzNqvyu8SZKkAecYkq/fOQDT1WrLqujowN6XTbqRgWFcSlYwfz5rY8Fv5pHePrttJiClFdIDsKi1fz6Pa8jaEyiz9eM4mpQ8P51X8PqC6Qnux+U5XQOvesgZodlzhLlbHarJ7v52vHv4I3roSXL+zV3e5+I41Rv/qcO/+9i+ITOVSbojj65GI0DZ5fm8HtX6r3KtWZaYweHMrSiXH8+vKx/OGaiRjb75/N3aLe9yTN7/xNEmeo/Y8NFZ1v62jnP9UeSf9gmH2P9/NSL1JZ7a9/DzUqkIsNtZCiFVEblORqnAdqv69zlMu/t+a6bnL+3iAiSb1G01/vXcZeiLPAQA765um6PhVYAtynadr57W/UNO1OTdN2aZq2q7S0tH9W2AO6ZujQvbPDnj6jH4YBXN65LdOxny/J8xXW2SmR7MqppMUq+/qEEH0rs7SeyoZWTlQ1kp5XRV2zlU0ZZVjtOhuOef69/9XhEsbEhTKki6YfpyV/m/odHu9h14GmqblmRXu7f5y6EvXmeMIyMAfAzNuhtQHeuQEqsk9tbce/JD9kCrtLNUb/ejW2wBiIGqGyj89PhWcnwHNTYfkFcPhT9/tWn1Bld8MXsTmjjJSYIGY693EnzUPTbTwxtQ6jQeOhD/f3fG/fiV0QP6WtwmXitVBXrLJkHRwrriXAbCQhou9+drfPT6a6sZWCsmqW+qWjjb4MTH6eT573E0CHve/iZzLwp2WTaLbaeNjT822oUCWFE651z0Bpmsoa1pxQjV3OtMI98M51bV/3cI+p1WZnzZFimq12vjhUzCCtktCYBPxNRoY6xmRMmKmCyHtGVnHPBeqCwG3zkt3n8oH62ZosKqvXUeIs9fFEN1lIm1WViI5aCj87pgJybzQNLvuDatqy9klANXJJ1k5SYm6bjVnd2EppbTNXT43noSWjufeCVJZ/dzqpMUE8vzajrXnP5BvUazR3S9drFOIsM2CDPl3XTzg+lgAfATM73L5c1/Xpuq5Pj4mJ8fQQA4NmcO/e2XFP3wBv5LItq4IJ8WGEWMweb5+TGkVjq821sVsIIfpKdaN7FcSLN03l7Ttm8Z2pCR7b6lc1tJCWW8miMYN8t6jCPTBojMo+eBI3CcqPdz/r6+hngK4yQ6D2PiXNh7wt8NJ8176nHmusguKDlEe3vdEurGqEYXMge73K8NWehLFXqGzkf74H+Tvb7n/gA0BHn7CM9LwqprZvypE4Gwxmro7M4dFvjWXDsdKejetpbYTig+4B8sjF4B/mscTzeHGdW+fOvjBtWATTh0VwbWQWgfY6zBOu8n5ySKzah5a3FYCUmGB+fulo1hwp4f2OMwAPfayCjCk3d36cEZdCSBykvda7xR7872l3jrTtfx+7rlFxy9fqwOGPe3S/nPJ6Wm1tge0wSwMhUUMAeO0HM/nqJwt44Io5EDaUC4ILXNmyTnQdjqxS4xnMHkamDJmq3hflb+96QYXpKvAaf3WP1k9kCkz7Hux5E969idDWcuINZaTXt12wds7vHDkohLsXpPLzxaO5eGwsdy9IJaOkjmPFqryYEZeo/blvfqf74FSIs8iADPo0TQvSNC3E+TlwCdD9gJ+BSOs8p4925Z32ATyyobHFxu78SmZ72M/nNDNZ3SYlnkKIvlbVoWnIlKHhnJcaTUpMECW1zdQ1u5fPrT9Wis2uc+FoHwZ9pUdU0OdN3ERV0eGthNLp8KcQkQyx7ZqT3PIx/HAXBEXD29f2LvA7ocpOo8a2FcVkldXD9NsgNAGGzYNflahS0rsdnULbZ6KOfwGx48nRB1NR3+Ie9PkFqv1cJ/dz86xhzEmJ4slVhymodG9/30nRPrWfL35a2zGzBcZdqZ5/c53b6ceKaxkR6yWYaKlXIzF6mX3RNI1XfjCDR1KPqzLT1G5KHhNnqzf6joux3z8vialDw3n2q+Pu2b6sr1Xw7GmMgNGk9vkd/1LtS+uJ7A2w4nvw+rc6jR/ojcaDq9liHcncV0vQk+bBnrd7NDvwcJEKeCYlqBENofYaCFR/35Ojg9qCvIRp6nXp7TELd6t9js6LGR35B6tseO7WrheUsUa9V+ru59XerLvVxyMr4Y2rMaDzSVWy63WaUaJebx33+05MUKXgrqDPL0jtz7U1d86IC3EWG5BBHxALbNI0bS+wA1il6/rqbu4zIOma1mFPnx29YyMX3dapdtzQUtvvQ17T8ypptemdSzfaiQzyY/TgELZK0CeE6GPVjeqN94hBwYQFmBnsGLaeEq1meeV0yPatOVxCdLAfkxJ8tJ+vuRaq81UA5I2zpK2rgK2hArLWqzfG7Ye5G4yqLf53PwRLuOoSau3hRcGsdaAZSJq4gO0PX6QOldbBkMnw/w7A91e2fS9LmApcnQ1eWhpU5iXlAg4V1gAw0fHm3yV2HBQfxGDQ+MM1E9F1nQc/2Nd1maczS5LQoRR20vWqlPXgR65D1Q2tlNQ2e97Pp+uw4gew5nF4dUmvs6Chfkb8Mz5XnRm9NQNxGjZHrc2R7TMYNG6cNYwTVY3sLXB0qrbb1YiN5AXuP7/2pjqau7RrLuJVayONH9xHgzlCNbrpzZiN9upKCK45zgb7RBpbbdSNuU4NJ+9BtmpPfhVGg8blE4dgwI7F2hb0uUmap0pXK7I8P1DGGkBT2U5vkuZBwU5o9bJXUtdVJnzI1LZGST0RlapGlYy+3DXmYad9FJ/vV108jxTVYjEbSOxQPpwUHYjRoHG8uN1FiJl3qOzhqZZaCzEADcigT9f1LF3XJzn+G6fr+m/7e02nrEMjF5Xpax/0qTcx7bN9poZihr9/IYlf3t6vG4m3ZpZjNGhe9/M5zUmNYldOJc1W2fQshOg7VY2tmI0a9y5M5e4FqWiON9gpjnEMznItgFabnXVHS1g4apDvhrI790d1FfQFD1IZvI7la7bWtgt5W55XGbDJN3p+jMgUuPzP6s31zpe7X1dVPux8RQWR/sEMCvEnxN/UVgKraZ2Dk7jJKujTdVVSamuBlAvILlP/pikxHYZkx46D2iJoqCAxMpCHl45hc0Y5b23vorX9iV0qyxgy2P340Dlq5tq2F13/JsecnTs9Zfrytqms5IIHVXbti191/2/SXvF+NX9wxCXdnzviUtWcZXtbJ9WLx8ZiNmqs2lfo/ngpC7w8CBA+VO3X3PFPtX+zK/vfJ6Auj3sa7sY25go1c+5U/vaXqqHnh/VhAGSFOnbFZKxRFyy8WHO4mNe25HDxmFiWTozjmnHBaOhqvEJHSY5Mcs7GzreBuvgQN1GNDPFm2Hkqi1aY7vn2nE1qbIK3/z+6EjJYdVAdvgjm/4zR8ZGscnTp3FdQxbghYZiM7m99/U1GkqIC2zJ9ThHJUClBnzh3DMig71yiGrm029On29329NlNKugzWNu6oflXHgcgoGwfftVerqadAduyypkQH0awv6nL82anRNFstbM3X+b1CSH6TlVDK2EBZq6akuBqHAGq3MzfZGB/QdvvnLTcSmqarFzky/18zoxJV+WdoIKa3C3w+YNqX9C2l+CPw1XJ5oEPVNA3/jtdP07KQhWkfPVY18046svhX5eooO6iRwFV0pgcE+Rx36PLkMlqnENljuoa6h8GSfPIKq0nLsxCoF+H3/vOMtRitdPixplDmTc8mt99dpjtWeUcPVlLRX2HTtQn0lQ5YEeaBnN+CCWHIHMN0FZaN2KQh0zfthdUIDb3xyoDk78dqgs6n+eNc5+cp26SHfkFwtRbVKapsRKAsAAz54+IYdW+IpXZzFqvzk3uIugDmPdjsDY69m92IXMNpVok623jKYpd6Bizsaf7tXZUpoK+DHu8+tgQrILkdb+D5Qs93iU9r5L73k5n3JBQnrl2EkPCA/jDEkfzE0+ZvugREByrMp0dtdS7MsZdcpb7eiuB3vxXNWbhVII+UNnBmz+Ai37NZRPi2JNfRV55AwcKqztnsB1GDQ5hT36V6nrr0Bo6FL0yx/v3sdvgo7sh/d+ntk4hzjAJ+nxNM7hn+uxWtz19ukmVGbQP+sy1bVdO/Wq7uIrqQw0tVvYWeJ7P19Hs5Cg0Teb1CSH6Vk2jCvo68jMZmBAfRlqeelNeWtvM7z8/gr/JwLwRPmrsZWuFrX9TDVciU7o+d9xVKhO0/SU1p271g2pI+fEv4P1bVaZw6TNdP4amwRV/U38z9q/wft5Xj0J9iSrfjGoLjFOig1wzCz1yBix734VDn6iGGeYAssrqSY4O6nx+vKMBh2MchaZpPH3NRAyaxnXLt3HpsxtY/OwG7M4OiJU56j9nt8aOJlyjgoeNfwG7nSNFtQT5GYnv2HW1Mkc1Bpn2AxWQjXKMRzjSTSDV3tHVqotpaFzPzh+1VP3dbtdhdOnEOAqrm9idX6Ua40SP6v7xBo2FkCFqZp43dht65jrWW8cDGvuNjizyqTQQKTtOsyGAOv9BGDTILa9vyy6XH+90emZpHbe9tpPYUAuvfH8GQc4LvA2Ov+WeSis1TQXPORs7b0HJ3Qr21u6D4eBYVWLsyEy6KTkMGV/CrLtUV9vTtHSC+hk98+VRmlrtXku/b5o1jJLaZv70P7WmzRllPLOrFa2p2vt4ifTXYe878MmPoDzztNcqhK9J0OdjeodGLh339NlNqhWy1i7o86vNw25Qb3T8anLP0ErdpeWq/XyXhOSqfReHP/W6xzAs0MzYuFBp5iKE8Oh4cS07snswl6uDqsYWwgM9t9efNiyCgydqKKpu5JqXtnD0ZA1/vX5yt5UJp+zo51CVq4aye9vH5TTiYph8s5q9d96P1LF7t8EdX8MFv4BbP1dDz7sTEquyhkdWeb7d2qwyh1NuVsFoO8nRwRRWN7plLtxEj4CwRFj/lApw5tzHrpwK9uRXeQ76AiJUhsaRmQOIDw9g1f3zePGmqdwxP5mS2maOOkvknEHZqCWev7/JHxb8HHI3wZa/sjOngilDI9xLc2sK4Y2rwWBSGT6AmJEwaJzqjNmTfe8Faep7TL2l+3NdT2yaCkp2veKam7hobCx+RgNfpx1SWa7UC8kuq+/6756mQepC1fSl9qTHU/TMtWhNlXxtU7MDH/26itaAGI6mr3fLZPdI6VGKzYlEBavh9DnlDXDJE+o2k3snzZKaJr73yg6MBo1/3zqT6OB2ex1dQZ+Xi77J81VnzbIOgWTW12D0U6/ZrmiaCpo9BX0HPlAXF6Z1MaKhF4ZFBTEhPoyP9xSiaXD+SM8XheYOj+bm2UP51+Zs3tiaw11vpJFlc5zrrcRz+z9UJhXc9qcKMVBJ0OdrHUY2dNzT56m801yTR3PEKFoDBrll/Xr1bW0thGZ+QnDemu5P9mBrZjm3mz5nypfXqmYC792srmh5MTslirS8Su9vMIQQ31g3vbyda/+xlRJvQ669cJZ3erJobCytdjtzfr+W3PIG/njNJBaP72Em51Sk/1tlbUYu7v5cTYMrX4Br/gUXPwH/lwWDRqts2QUPgX8vho+PXqqaUnhqnJG/QzUd8dA0IzkmCF2H7LJ6nlx5iHvf6pA50jRVPhcYBVc8B9EjeOhDVW7nms/XUeqFKgPlKHsE9ab6sglxfO+8JAC2O4OgQx+rTFdXWdHpt8HIxdg3PUveyVJmtf++LQ3w8Q9V4PfdjyB0SNtt5/1I/Ztk9ODvW9orqmtnV3PeOjKa1My+nM3w5a8BCLWYOX9kDKEHXlf70abfyvdf3cH1y7d1Lmttb+adqgxwxfc93ty06UVK9HC+sE9nUmI4JXUtbKhLwFSUxt1vpnHTy9tcpa/peZW8vDHLc/Mcux2K9pJjSiIswMywqEByyutVRnXhL8HaBFa1zqZWG99/dScV9S288v0ZDIvqEOQ7M1vemqg4y2Rz2o2XsNtVJjtxlsrIdidmlArGT3TY13d0teqgGhTd/WP00J+WTSI+PIBfLx1LZJCXGY3AL5aMUed9fJBQi4lhw8cD0FLqIYtXfEh18p33/9RFiJxNfbZeIXxFgj5f6zCcXdNt6J7KO23tM335tIYk0ho6FL+aUwj6dJ3YrY8xePsTDNn0EJbSfb1+iF2ZJ/mR+RNIPh9uX6vKkT59ADY96/H8OSlRtFjt7M6TeX1CCHcNLepi0Ktbcnp1v+rGVsK9BH0zkiJ5Ztkk19cLRvWyrLO5Vo0A2Pb37s+1NqtSv/FXtw0Z7ylN67qpRXdGO8sZV0FTDRxrN2Yh4yt1ETFpXqe7OTucLvnrRl7fmsPqAyep7jACg4UPw8+zYNL1WG12csrquW1eMt+eHO95LakXOcoe13e6KSEikPjwAHbkVKgMUP42mHidhwdpR9Ng/s8wNFXxtHk5y0qea8v+rPieyipe+mTn5zf+O2oPYnfZFWszHPoUxlzeu0Ab1H68qbfA3vegvgyARUlmrrN+SlPqpRAzErsj+Jr6xJesP1bq+XGGTIZFj6luoHkdmvuUZRCQu5a3rBfxym3n8d97z2NGUgQb7BNJNRSRUrOdzRnl3PnvXTy35jjLXtrKk6sOu0YPuCk5BI0VpBvGExpgJilK7enUdb0tgHJk8L46XMyhohqeWTbJNa7ATXeZvsgUleFy7utrbYI9b0HZMc9zCz2JVQEVry5pm2lZkaWa5IzqwYWVXhg1OIRNDy7k1nnJXZ4X5G/i2esmMyMpgtdvncl5M9Tew6Lsw51P3veu+n9v7LfV6zN/uyuoFmKgkqDPx3TNqK6AuQ7YO2T6VNCnWR1XwHUdY1M51sAYWkIS8avrfdAXnL+G0LwvqRhzC62Bg4lf92P8KzyUUXhR32xlVtFbhOnVcN4DaiP+LZ84mgo86nEvxYzkSAyazOsTQnTmb1J/ajI9vVntYN3REuY9vZapT3xJQWUjYYGegz6Ayya0ZfZCLd7P60TXVQOGNY/D6oe6zxidPKD2KiXO7Pn36CsRSRA7Aba+AH+boZrBlBxRQWv66+r3siW0092S2pVottp07Dpsyijz+m0KKhux2nVGDe4iOIqfpoKtzLUeb56VHMmO7Ar0fe+pv3OTbuj++SXOoMSSwreM2xh89N/w7o1qf9TxL2DBQzDj9s73MfmpwODoKtc8PY9yNkJztdpjeSpm3qmyegc+BF3n/KxnCKaRvEk/BSAurG3P2b589wuej31ykL986WjAM/lG9e+W9qr6urlOZTLX/Aa7ZuJt20UkRASiaRqXjhvMO7YLKTEO5hemd9CwU1DZyJ+/PMZ5jj322z2VSju6aW63jSHUkemrbbKqWZdBjgsi9SowXbWviJgQfy4ZN7jz44AK+kwWNaDcE9e+vk2qO+nTSfDJD1Vmd/w13fyjOky9RZVKW5va9qzueVtVR/X0MXpB664k22F6UiQr7j6PEbEhzBiZSKkeRnVhh0ZK1hbY/ZbK+gcPUkFfa0PbCBQhBigJ+nytY/dOu81z985WNTzUYK3HYG/F5h9Ba9AQjM3VaK3dDMBt/+1sLUTvfp7m8OGUTbqX/EX/QDf5E7vjtz1uAX0kfQM/Nf2HssRL2wajhsTCNa+oNx+rftqp/XNYgJlxQ8I6z+trrFTDZp+dqObdVOX36xgKIcSZ1Wy1Ue4ofyvuprzz072F3PHvXQT5mVg6IY7vzRnGDTOHej3fYjby0s3T+M9d3ewh6uhEmhrgfMEvVGv9Lc91fb6ztfyQqb37Pn3lW8+qrEudY19YxpdqlENjpXrj7EGwv4nHvz3O7di6o95HBzg7faZ42s/nZDRByvkq6PNQYjgrJZKyuhYaMzeroeUhsV4fqqi60VWm+LXmmG04cgmUZ8DzUwGtbdadJ+OuUs+/feazo9ytKvgcNtf7OV2JHasCme0vwbqnGJL7Mc9av0OeKQlQF0gXjRlEZJAfRe1e2+V1zbyxLZfPD6hRAfgFwejLVBfPulJ4fhr8bggc/oRtSXdTSjhxYeq9wLUzEnng0vHUzv4/xhpyucSwi5dunsaz103m37fOZFCIv+egL2MNRCRzrDmCMEemD1Alnu2CvvpmK2uPlHDZ+MEYvY02aahQr7euAqXhF0FDGXz2M0icod4f3LFWvUZ6wi9QlZ1Gj1L7+PJ3qD1yqRdCmJdM8xkW7G+i3C8erbJDb4WdL6vnPuM29bXz9eVtjIUQA4QEfT6md5rTZ3crD9IdjVyc5Z3GJnW10OofgTVI7WEw1xf2+PuFHVuBX30hpVN+DAYj1uAhlE7+EZaKwwQV9qzmXN/zDi26icBlfwdDu5eIyV+9+agtgrWdRyfOSY1iT557y2O++o1ql12VC89NhmfHq+517bOfQohzVkmNmkGqaVBU7T3oe3t7Hve/u5spiRGsuGcOT1w5nt98e7znYd3tLB4/2PseNG8OfqQaTsy6G0ZdpsruuhqCXrgbAqMhLKF336evJEyHuzbCXRsgeqTaL7fFMYvM00gEh1vmJLnet/uZDKw/Vup1mHqWI+jz2MSlvdQL1YD6jk08gJnJURixYT65u8usaHFNE3OfWsvf1mZQ29TKo1VLWDnyt3Ddm23dORc92vW/9/CLVYlhV3MM87aqmXH+Hmb/9dS070NFJqx/iqZhC3nediUlteq1UtdsJdjfRGyoheJ2r+2V+4qw2XVyyhuwObuZjv226uD6t2kqeB+1BG56n1Wh1xMZ5IfFrN4XhFrM3LdwOIPn3UymPY5Hgj9h0egYrpwSj6ZpzEqJYkd2ufvPsbkOstejj1pCtaPjrTPTm1ve0C7oK2PNkRKarXaWTmy3R7KjxgrPM/raG/vtts+//aIque1tt01NUxnb3C3w4Z1gCYfLPW8h6S96RBJRrSeodO7btLXC+qdVqbPzonhQlOzrE2cFCfp8TdOA9nv6rG57+jqWdxqb1QZ5u384rcGOoK/uRM++l91GxNF3aYidTkNcW5vs2mGX0BowiPBj73f/GLpOSulXpFtmERjqoZ4/YbraEL9jeacWxbNTImmx2UnPdWzyz9+hylnm/BCufEl19IpIhkP/VVfZhRDnPGegNzkxnNK6ZlptnS/4/H1dJg9/tJ8LRsbw+q0ze1eq2Vt2uwr6Ui9SHTST5qtZal21yD+R7hhZ4KOh7z1hMEDcJJh0PRTsVNmYCx7u9m5mx4W7pRPiKKlt5nBR5yHdVpudT/YWMijEv8tGF0DbG10PJZ5JUYHMDi7GbGv0PqoB9Zqw6/DXNcd5Y1suTbofETOvV1mi69+C/3dQNcjoitEEHgLImAAAIABJREFU029VHSM9zbSzNkPBLhh6XteP052Zd6pg+7sfYbzxHdAMrox1XZOVYIuJuDCL2wWNj3arv9ktVjuFVY79+iMuhdn3qmDqsj/BDe/AiIspqm5icKil07cNCrAQeukviW/JcstEz0qOpLimWQVzTtnrwdZCU8olWO06YQFmEiMDMBk01QTGuadv17/4fG8+g0L8mT4swvtzbij33sTFyeSvZuFd/iyEJ3Z9bldGXKLGklRmq26up/NYPhAWP5LBVLL1mON92Ik0aKqCad9z/33QF/v6etKNVojTIEGfr3UY2aD29HUO+pzdO41NKmCyWtoFffVFPfpWgSe3Y244SdWIDvXwBhM1KUsJLN6BoaXzH/z2Ggr2E2mvoCrxIu8nLXhIXSXf8Ee3wzOSIjEatLYSz3VPQUicKqGafAPcuhp+lKbahG/7u/yCE+Ib4GRNW9Cn62qmnlN1Qyu//u8Bnl59hCsmDWH5LdMJ8Otlo5TeKtgJNSfa9nklzVW/z3a/6fn85jo19Lq/Sjs7mvNDiJ8Oc+/vMsvn5Czhu36GejPtqeHIPzdmsze/il9dPrb7vU8RSRCZ6ja6wUnTNJaFq/1Pehdt+6sa2t4Y/2H1UUwGjSlDw50P0vOM6sw71F65Lc93vq1wj9qPN3R2zx7LG01TwXbqhZj9A4gK8nNl+mqbrQQ5M32O13l2WT178qtYNGYQAGuPlPDMF0d5L60AFv8eHtjTNn4CKKxqZEh456APIOa8m1VGbc3jUK2CDmeHU9cIlOJDjj2pGvsZAahsrb/JyNghoaq5mn8oGP0hfzvm459x2YQ499EYHTWUe2/i0t7wRb3riurJ0PPgokfU63ritaf3WD4QO3Q0Bk3n8EHHIPmsdYDW1sHU6XT39X3+ILw0D6r6Zzaz+GaQoM/H9A4jG9SevnY17wYTusHUFvQ1q/JOm38ENv8I7EYL5rqelXeGZf4Xq384dfHnd7qtIW42mm4nsHhXl49RmK6atERNuNj7SSGxMPN22PcelLZtcA6xmBkfH6aaudSXqV+Ok25wL60xGGHuA5C3BTb9uUfPSwhx9mlosfLAu7v5yXt7MBs1pg5VmYWTNU00tth4aX0m8/+wlje353Lr3GSevW4yZuMZ+JN08EP1Btg5Py4gQg2C3vM2fPUYbPwzVBe0nV+0V12six8gQZ/JH27/Ci5+vEen37VAjUyYlBjOmLjQTvv6jhXX8pcvj7Fk/GC+NbGHIy+GX6RK2TyUxJ5n3cE+ezLvH7e3DWrvoLpRNV/52aWjAJiYEEag3ynMV7SEwfir1AzFlg573/O2qI/dzYzrpUEhFkpqmmix2mmx2gnxV5m+8voWfvh2Oi9vzMJk0PjxopEAPPrJQZ5fm8EvPtxPel6l22Nll9VztLiWcUPCPH8zTVM/Z92umvYAwwcFExnkx7bscvWc/z4Hdv0LwoeyIbseo0FjjqPhy9ShEezJr8Jq19F/rLp4T9MPsrS7n3NPg76+YDDA/J/Cpb9Vr+0Bxhil/v85fnSfCuwzv1YzMTtmQp37+l65pPdlnvk71L7R4gPqd5AQPuKjKbbCpcPIBjWnz/2Njd0U6BrO7gr6LBGgabQGD+nRnj5TQzHBBRuoHHU9GDuXRjVGTcBuCiD82H9g9jVeW4jr2RvI1gczfsw4j7e7zP0x7HxF1bZf8y/X4VnJkby2OYfW/f/FrNtUnX9HM25X+/zW/0EFhaFd7C0QQgx4jS02Hl95kP/uLnS1sbfrOq029fn3z0ti+CB18ed3qw6TlleJrsOFowfxf5eOYkxc5+6TPmGzqqYRIy9173i54CE1KmDTX9TXhelqf1lrkyOLpHUaft6velFm+sBFI7j3guH4mQxcMCqG5Ruy+NV/97N4XBy7cit4d0c+wRYTT1w5vscdDkm9UJX4522DlAVtxxsqiKnay1dB1/Pw+/v4aPcJDhfV0NBi48rJ8Tx9zUSgLei7ZloCBg3Xa+OUjLtaDWrP+NJ9n1nuVogaAcG9HOXRjdhQf9YcKeHFdRmAavbh79iPt3Kfqsq5cvIQxg0J5f4LhxNsMXHRmFi++/J2frZiL5/dPx+L2ciWjDJufHk7RoPGTbO9NysiIkkF2Xvehgt+gaZpzExSXVI59LHrtC3VkazcV8ikhDBXefTUYRG8tiWHOU+tZdrQCG6yjefCwEzih3ZR2mm3qYH03ZV3flNEqjEP8ZTw9//t4bGCnWqch0NVQwvXvLSVZ5ZNYtLIxXBster26mGMilfZjnmHIy5Rr1shfEQyff+fvfMOb6s8+/B9NL33nvFKnL1DJmRAEgh7l1WgZY9SWsrXQcsoUNpCoewNLaNswkhIgITsvZfj2I5XvKe8ZK3z/fFKluQp2XLiJOe+Ll+Kjs559R5b0TnP+zzP7zfIdLZskGQbciefJ5vGzyXTV49NrUdWi3IPc2BC35k+WSZm65PIKg2Nw0Vp59H6dowWl2BTraV27C34V+8WRutWS7fjxDbuozBgXN8lVoFRcMat4gbKJds3JTUck9WGcdfHQpUrtpvgUZJg4WNi9XL575QyTwWFk5gjlU1c+MJ6/rethCXj4rlx1jBunDWMm2en8fK1k3js4jH8ZuFwMmOCSAj1Y3tRPRnRQXxy+wzeunGq9wGfpb130ZXeyF8lZOs7Wwnog+DaT+D/SkQv2aFvoPKA+K7MXQ6L/yak2U9CJElCZ7fMuGVOOuePi+eT7aVc9+YWnvvxCOnRgbx+w2SigrzIsgybAypt176+ki1IyFx9xbX8fEYqG/NrabfYSI0MEJkpOw12v8BQfy23npnB/OyeVT77JHWWECpx9eyztAslxbSuVS8D5d4FooRy2T4R4AX5aTlvTDx/uWAUL14ziTvnZvDA4mwkSeL+hSO49cwMMqKD+Pvl4ymobuEZu43D1kJRnvn0FeOJCe6+vLODMZcL8ZxSUalzRnoEpfVtVGz7vGMXk8VGYW2rm8fiOSNjuWNuBs1GC98fqsQvYxZJpqOozC09v1dbAyAfv0zfUCcwGrSBnBPXyrHd34uF+/S5HS/vKmkgr6pZ2KFc85FYECnZ0uNw3VJ/FIJiRZ9xU5l7pYGCgg9RMn2DTafyTpHpcw+oZI2/W0+fVR/WsZJrDkrAv3qXCIy6WYVVmZqI3Pc6QWUbqJp0P+agJNYXNvPoqnICtCrOSgvinMwQRsf6UT/yeqz6cOI2PyLEVMa69/41V+QSIhuwJPTdJwLA9LvEKvj2t0QQp9YyOTWcBGoIqtwqevl6WjkOHwbz/wTf/xm+f0jsq+tDNU5BQWFIkVfVzBWvbkKjkvjPzdOYk9V7VuXm2Wk8sewQ/756IqMS+pHdO7gUPr9N9OBd+pr3Js57PhRCGplnd/+6XwjMuAd2vAsv2wVAznkMpt/u/VyHIBGBOp67eiIGo5mNebWMTQolMcxLxUUQQXLyGaKv75xHnNuLNoJKiyp5CndFS3y0vYSrp6YgI/PxtpKO3RpazQTpNb4p51VrYOSF4m/b3iRM2Is2iP6qrIUDH78TE1PCOW9sHMv2CfuMIL2a0AAtN80SGaGeSidnZ0Vx7RkpvL6ugEsmJlJS10ZciB8XT/TAniD7PPGZ3/cJ+IczO1MEyU0lB6gnmZGqEioSFhBRo+OKKc5+SH+dmgcXZ3PZpETMVpmRNa1Q+KoIKmKyu3+vvozZTzckCSLSmORXRZ2mlDZVIP4uIkU5dmGkPIcHacpMWP24sBPxt2dUrWZxD6fpQSSp7qgQuUu2W5eUbjtxSsEKpzRKpm+QkTuVd0qyzc2nD8Cm9ndR72zAqneWXpgDE1CbW1CZDJ0GlvGv3EHyD7cSfvhDmhNm0TDiKhraLDy3sYr0cB2zUgNZXdDE/ctKuenTIt7bVUtu1DmiCX/Lq13mmrdjNQDRI+d0ea1bgqLFRXXLy/D+FQBEBum5L3gVNiQh3tIbM+4Rctgbn4d3lnSffVRQUBiSVDUZ+flbW9GoJD6/Y1afAR/AzbPS+Om38/oX8NUcgS/vFAtGgZGw8o/eVQkYDcInbezlPd98gRh7yT+dz11EN04VQvy0LB4T17+Az0HmfKjYJzJsNaLUkcL1ovdR609MsB8//mYuD547gqggPS0mK20msQDa0GYi1N+HCq0TrxVB3pq/i+cHlwpz8TQPr2Ve4mprEaT3/DweWDSCYL2Gf6w4TEl9K8kRHv7+/ULFQsXWV+GFyWSZcth8dj5ZqmOEjr+A5vvyufDmP/Ddr+Z02xuZGRMsMuqOQKKxpMs+HXQEfUp5ZwcZ89EVreE8aRP/Nc2l2eq8h8upEPdmR6rsInlZZwMy7PnIefwHVwlvRqvZuU2WRfk4iKAvIg2iR9qfFwziySiczihB32DT2afPZuna06f1dxNysfqFdbxmCerq1edfuYPU5deS/OPtaFqrKZ37HGVn/QskFS9vqabFZOXBs+J44Mw4PvpZOr+dE0t0kIb/7Krjhk+L+Z95DpRupaVerFTKssz7W4rI37oMA0Fkj53q+fnN+yNoA4Vsdk0eGBu50LqSFczAFtKH9LJKJeSeL3pJKF4t+63zS1BBQWHIYrbauPv9XdS1mHjnpmmkRAZ4dJxKJXm8bxe+vENkO677TBiS1+Z5Z4ZcsgUsRsg+v+99x1wG130O13/pvffY6cKoi8XjJzcK77n81aIXcsR5Hbskhvmj16iJtpeO1jSLstzGVjNhAT4M+hInw8TrhbXBT0+JG+6xVwxa9UhalLMHMcjP84KpsAAdt8/NYFVOFbtLGkgO9+L/wsgLnP9+82zi1j8EQELmeILCogjQa4npxvrBjVD7Nbm3oK/Nrgral0/f6YTdhN0mqXnTci6l9U7RIEemL7+qRQgXJUyEpGmiiumDq4WKbP6P0FgMW193jrn5ZXg8FgzloqQzPE0Y1vuHdyi1Kij4GqW8c5ARmT4X9U7Z5ubTB0LIRdMmVtfUxnrMwc5gyenVV0Z7xEi0hiISf/oVFv9oKs74E02pi5A14ot+V1krqwuauW5CBGkR4iLrr1WxMCuEhVkhVDSZ+SHfwLqCEVwN/N8zr7E3ZA4Wq8yxhlZ2Bu5HnzEfvb4PnyZX4sbAvTvhmVGw6XkITcLP1sqL7UvIqm4mqw9jZSQJJlwj+mc2vyhu5G5Y6mZg70blAfju93DFO8pKpILCCeIfKw6ztbCO566ewJjEHpQHfYmpRZQ8zf0DhCaKgOOHh8UK+oy7oOoQzL6/dwuD0u1iwc1TFc7MXmxrFCAyQ2Qmqg+J5/+1B4Gd2gYAooLFNaWmuZ3kiAAa7AbiPmXJM0Lu/qcnxPMzBq8k1z3T591t1E0z03h3YyGVhnaSwr1YUBhzufBm1AXCN04hEaKyPB8jOA5UGmjwJNOnlHd2ED4MblnNgdYwKt88xN7SRv76zSEunZRIfnUzkYE6altMVDYZiQ/1Fz3A/7lI9AOX73GOc+grmHGn+Pfml8XjdrsQXlSmeAxJEpYyCgqDgJLpG2w6Zfok2Sq+dF2w6UI6yjc1nco7TUHJyEjoGkW6379qFyprO8fmPosh46KOgM9slXl+UxXxwVquGte9MldcsJbrJkTywm9uBuB59dP8InQHU4eF8/xZEhHWWvQjeuh16Y3gOJh+h1BQW/VXWtMWcUAexrbC+j4PBUTgt/gJWPSkWLkv78ZoV5aFj83LM4URbcFq7+epoKAwYL7bX85rawu4YUaqm2jEoFJjF4uKsZc/6QJgwV9ESd/af0DON7CqDwuD0m0QM0r0fCn4hhuWwu0bhJn6vD/Bkqe77UWK6sj0CX++xjYfZ/pAlOw6Ar1hc8SC5CAxLimUVHvGOtobARxEn53DziE5wotMn0YHM+8WvniXviEqZLIWQkwfStuuqNRCLbs3oRAl6OuexEkkxIvvuw+2FLM+r4b7P96DxSYzPV38rupb7OWbSZPhzo0w7TaRxQPRd1qyBVrsv1/HwvbafwhRpIz54nlIglAA/ezkKStvbldac04WlKBvsJEkJNwtGzpn+qy6ENQmA5K1HZWlVdg1OHbXBmAKTcOv9gAAuqZibCqdWzYQ4NP99ZQ2mrlrejR6Te9/VknrJ76AgBvMn/Ls1RO5wPA/YeA66sL+nef8h4Ts+Yy78b/6LaKC9Gy3q5N5zLgrAQnyVnV9Lfc74WPj4NjO/s1TQUGh3xRUN/PbT/YyPjmMPy4ZefzeuCpHPEa7iE9MvBYeyIdf/ghjr4SCNVBf2P3xVovI9CVNGfSpnlYEx4rgKjQJznpA2PF0Q5RLeWeryUJZQ5t3aqGeknWOyIjN/5Pvx3ZBq1ax6jdz2fnQOYT2I3i9ckoy/7xiPOeN9dAXsTPjrhCf/2s/AW0fJZ2dCU3uu6dP4y8WVhTciAjUEaBTs7ukwW37tDRRdeSwIgEgLAUWPCQWmoITREm6LMPKP4nKhYYi574Z85yiL6H2hbR9H4O5bTBPxydUGYxMfHSlsBBRGPIoQd8g09myAdnWRb3Tqg9FbW5GbS/xtOrD3F43Ro4WQZ8so2sqxhyc5NYXWNls5oPddcxKDWRasoc9DFf+B877pyjNefcCUXYw/Q7nF4+3aP1g3u9h0eNI+iCmDgtnW5GXXwKBURA/XvgtdWbLK6LE4k/Vol7+2I7+zVNBQaFfmK027nx/J1q1xEvXTkKv6cPWxVtKd8Caf3QvzlKdI1bD7Z5ZHQRGiUDunEeEP6nDZ68zx3ZAe6Ob1LrC8SMiUJR3rjhQwZ+XHqDVZOWC8YPgz6rWCt/YlOm+H7vzW6mkjvPqz7GXT04i0MvSUJ8QmtRHpq9eaZ3oAUmSOkpyp6c7f0cTksU9m1vQB6Kq4I6NogUmfpzw99vzgbC6km1CE2H+n2DRE85jNC4lv7X5g3YuvqK6uR2zVaakrrXvnX3A3tIGXlubT1lD/wPi1YeryKkw8N3+Ch/O7ORACfoGG0nlXt5ps3ZV79QJJTtdk1h96y7o07Q3oG0qQmsoxhTsbuT68uZqkOCOM7wwoZUkmHCt6I05ulasRM2815sz65XJqeGU1LVRafBSmCV7CZRsBYOLN2Fbg1CFG3WRKHFJmiKao63mnsdRUFDwKYfKDeRUNPGH80YOTPWxJz66Dlb/FfJ+cN9ec0QYU8eNETf13RGSABOvE/sZDV1fz/teLLalz/P9vBX6xE+rZnhsED8drubTHaVMSgljSmo/FxgVBkZosri+9qSW3VqrBH29MNn+uT17ZCwXjE9gfFJoR/Bv6Bz0gbjXcohBTbpBPH51jxDAm3G3yAC69mWGupTM1x4ZjFPwKRarWKRrNVv72NPJff/bxaqcSq/e51C5gdlPreLa17fwxLIcHvn6gFfHOzBZbNz09jYWP7uO29/bwab82r4POoVQgr5BprOQS7eZPkfQZxDpfove/WLYkjgHq6SmfNXLaJtLMYc4g74tJS1sLG7h2vERxAR5WWaiC4Ar34W7t8MvVgjvJR8xdZi4aGz3tK/PwaiLARkOfOncdnSNUD11qMIlTgZLmxB1UVBQOC6U1ImV1X7ZLfRGe5MQZ3L0vvz0pPM1cxt8dL3wN72kq82MG2OvAKupq2E4iEAyaSr4h3V9TeG4sPxXZ3Lw0UUcfHQRn94+E6knD1eFwSU0Sfx/aiqDlpqur7fWKv18vfDEJWM59Ohifjknned/NpGld8/uKPHtkunrTES605Zh+KLuS2in3QY3fCX+XXMSBH32SjajybOgz2A08+XuMm5+Z7vb9m/3lnPVq5v4bn95t8f9+8cjlNa30WTvH1x5sLJf2cXOiYiXfsrzeoyTGSXoG2y6CLlYkFWdevr04iZK2ySCPqtfGFabs8RpbXUAyyzTmNm6CqwW/tswFoPRSrvFxoubqkgO1XLZmAGsmkZlifpzHzIqIQR/rZpt3vb1RQ8XJZ673nOWeVUfFo/x48Wjoy/n2PauxysoKAwKJXaZcq/EJ/rC0i7Kyze/JKoiJt8kSjFL7eXbG18QJeiXvAbRI3ofK2makJk/vMx9e3O1sITJ6odIlYLPUKskAnQaAnQaVCol4DthhNn1AFY+BP/IcFeXBGHZoAR9PSJJEv4694X7IJ0GleRB0Adw8YtChOrsh7t/Xa2B9LNERtZx7zOEMTsyfR4GfeUNXau/apvbefCzvWw5Wsc7Gwu7vG6zyewsdiYQ/nBeNrJMl95KT6iwB33hAVrOHB5NbmWT12OczChB3yDTfaavk2WDTkie6wyFAOyu9+Pi9/K575sS3t9dxxM/VfBWyJ3kjfoVL8Y+ynNHE7nx00Ie/rGcimYLd8+IQaseWhdRrVrFxJQwtnvb1wfixq/qgLNvrzYfQhKdJRJhqRAQJYQZFBQUjgvFda2EBWgJ8fOh6uKGf4uA7Mr/wB8rYOFj4BcmPDtzV8C6fwp/Mk8CNrVGrJ7nrnAvXXNk/jKVoE9BocOr76C9mmZlJ9Gb1lrFo89LVCqJEH+tZ0Ff4mSYcz+Ep/a+X/x4oTg8xDFbRVKjzcPyzmMNzuxcrd2384XVebSaLMzJimJPSSMWq83tmCNVzVQa2jueOwSQKhq993V2HPO/W6Zzk/YHFrQso93ieWnqyY4S9A02nXv6ZCuy5N687Sjv9Ks7jEXtzx/XNhMVoKHFZOPdnbVEBWr4/cJMbBOuY9HZi3nl4hRGxvix41gr89KDmJgwNFW2pgyL4GCZwXs53zGXgVovmp0B6gpEWYQDSRLyxns+hDcXCW8mBQWFQaWkrpUUX2b5QCjUDZtj79fVC+GDC58XgeAHV0JwPCzpQZylO0acC8YG2PaGs1Ig73sIjIa48b6du4LCyYirpUZEOhRvdi6SWC2ih17J9HlNqKdBn6ekzhIKn0PcqN3R09dm8uw+75hLpu+PX+znQFkj720u4sopyVw+OYk2s5WcCvfsm6Ni7LM7ZvDfX0wjMcyfQJ2assY29h9rpL7F5PF8HUFfypF3mZf/FE9o36S6aOhnVH2FEvQNNpIaCVncgMgyUjeZPkd5p9rUyFFrNAE6NX8/N5HXLknh5YtSeHZJEmH+zkBxWLiexxcm8vJFKdw/O/a4no43TB0Wjk2GXcVe9vX5hYig7uBSoXxal+8e9AFM/rl4LNkMm170zYQVFBR6pLiuleRwHwZ9VYeE/97ITjYxoy6E29eJks7b1kCQFwJVGQvEgtF3D0LBT2CzQt6PYrtKudwpKKALhNAUSDsTzvyd6IOttfc1tdUDshL09QPfB30zxWPRRt+NOQh4m+kra2hDq5Z4cHE2Pxyq5ILn16OSJO47e3iHSM7OTveMO4rqiQ7WMyklnDlZ0UiSRHyYPyV1rVz16iZufnebW0tUb5Q3GonSmfHb/C9aQ4fTLmuQtr/hxRmf3ChXwUGmw5NPtnZk/Lqod2qdZsGlcjRPLEwgOlCLJElkROrdAj5XMiL1fXrynUgmpoSjkuB/W0sob/RSXnfMpWA4Bge/EOUmnYO+1Flw9iOiKXr3h2D2Ps2voKDgGbmVTRTVtjIxxUdCKI3H4L3LQRckyjc7EzcWxl8FfqHejasPgnvsZd8HvhBZjLY64d+moKAguGe7EAuJtRu7V9lF0ZrtiopBMSdmXicxPg/6YseANmDIaxdY7MFWm9nWx56CsoY24kL9uGNuBh/dNoO0qEDuXZBFXKgfiWH+xATr2VnkDPpsNpkNeTVMS4twE3+KD/VjVU4VLSYru4obeGNdgUfvX2kwcovfKqTWWpoWPs1uORO/8q1enPHJzdCNGE4VVCLAk2Sbs7dP5R70GW0S5ZLI2CUnD2NY+CCY1p4AgvQarpqawrf7ypn5t1U8+Olezw8eeaHoK/j0ZpEZzegktS5JwvNm0V+F/1Z3in0KCgo+4bMdpWhUEpdMTOx7576oyYP3LxdlmDd+CyH9NKjuibAUGH0p5HwDm14QgeOIc337HgoKJzMavbiGRo8QYnOVB8X2jqBv6FYQDVVC/bVUGowdma8Bo9aIvr4h7knckenzsLzzYJmBYZHCT3pyajg//mYud83LBIRIzqSUcHYWOwVa9pc1UtXUzvwRLgsRTRUkBatxJPemDYvg6e9zOeKBKEtbbQnXWD6HjAVEZM9mly2LsMZD3icOijbB938R5dAnEUrQN8jI2FcmZFu3mb66VgsPrSxjo2U4AGHhp1ZZxZOXjmXNA3OZnRnFV3vK+j7AgdZPiDqEJsNZDzqVOzuTdpYwlD/4ZfevK5xwNhfUMvbhFdz236G9YqnQM/uONTImMZTIoAEsSNlssOkleGshNFUI8ZaECb6bpCtTfykqBA4vg0k/FyVtCgoK7mj0Qr3bYX/UXCUeg5Wgz1sWjY6jvNHIyIe+Y/2Rbqww+kPiZKjYN6Q9iR3qnb2Vd7ZbrCz611qG/d+3HKlq5uyRPX++JqeGU1zXynf7y9lRVM+FL2wAYF62Peg7/B08O5ZfF91BBAbiQvx48dpJBOrU/Op/u2npRUNClmWur30OHRZY/CRatYojupGoZYvoI/eG7W/B9rdB4+fdcScYJegbbBwBnmxDku0fRnvJ566yVu5YWkxOtRG/kYsBMAf71jphKJAaGcj09EjazFbaPJT1BYTZ8q/3w9z/63kftVYYuucsU0o8hyg7iuppMlr44VDViZ6KQj8pa2gjKXyAhuxFG2DF74VYxE3LIXOBbybXHcNmwaxfwfhrYP6f+t5fQeF0JXZ01/LOQKW801suGJ/Ac1dPwGKT+f5ghW8GTZwEFiNs/DeUDE0lT4fSZm+WDVsK6jjskoU7d0xcj/teNjmJsYmh3P7eTm5/T2Q5/3bpWCICdUIb47sHwWoipiWXN1JW8MSlY4gO1vP0lePJqTBwx/s7e8y2Vtc1MJO95Cdd1mEBlO8/Fhsq76rFjAY49DWMvUwkKE4ilKBvkHH09EmyTYgKALJKQ35tO39ceYxgvZp/X5hM1pSFFC75iKbUhSdyuoPQoovbAAAgAElEQVRGZKAOgLpWz1WWPGbUJWBqUko8hygOtSyrTT6tpJFPFWRZpqzRSGLYAIO+3O9ArYP7D0JMtm8m1xvnPAqXvCyyGQoKCt0TM0ooYBsNIujTBYneWAWvuWhCIjPSI9nhrXhdTzhsZn58FN4cmpYzZkdPXy9B36qcKvy0Kjb9fj5f3jWLmJCeA6WIQB2f3jGDm2elUd3Uzm8XDufqafZkSOV+qC+EC56DM25nUvVS5mv2ATA/O5YnLhnL2txqHvhkD42tXbOj1QfXoJfMyOnOdiE5IJIj+lGQu9zzky7eBJY2GH2J58cMEZSgb7BxEXJx9PRZZDX/XFdJsF7N0+clkWbv4TOFpos6+1OQCEfQ1zwIQV/6WaAPgSMrfT+2woBxmKEC1A7G319hUKltMWGy2EgYcNC3QtgzKDeUCgpDh9gx4rHqkAj6FBGXATE5NZxD5U20etjj1it+oZC1yPm8tR++x4OM2dK3eueWo3VMHRZBfKg/E5L7FgPTa9T8+YJRrHlgLnfOzXS+kLMMkGDEEljwZyHk99WvwNQKNXlcPS2F+88Zzpe7y5j6+A/c9f5O8qqcGUbVkRW0y1qixjiDvhA/DRu0M0QZ7Q8PdzuftbnV7HARl6HK3gMbN67PcxlqKEHfYCM5hVwcmb5t5Uby69r51cwYQv3UvR19yhAZJIK+2pb2PvbsB2otJE8Tqy8KQw5XA9Wa5kH4+ysMKmUNQnl3QEGfqQVqj0DKdB/NSkFBwSfE2YO+8j2ipy+o59I7hb6ZPCwcq012DxIGwmWvw5JnxL+LNvhmTB9isTmEXLoP+mRZpqSulYxo7xf7UiMDUalcEiFF68XnNSha9GkveAgMpfBEPLwwGcp2ce+CLL65ZzbXnJHCuiPVXPD8Bj7dUQpWC0ll37FWmkhMZETHkCH+Wj5iEYy9Ajb8Gwzu2hM2m8z9H+/mka8PODdWHYKQRPD3kZr1caTPoE+SJD9Jku6XJOlzSZI+kyTp15IknVxFrCcQWdU107e5xMiZw4KYmXr6rHhHBIpsZp0XJppekTIDqnOG5ErY6U55o5ERscKWRAn6Tj6cQd8Avvar7ea30cehrFNBQcFzQhLFT/EmaCyFYCXoGwhnpEWgVUusz/ORmItfKEy8HvzCYNd7vhnTh/Ql5NLYZqa53TLwnnCrGUq3Q8pM57asRaJ6xF/4+7HqrwCMSQzl4QtH8/39ZzE+OZTffrKH7z56gWBLHfsjF7lZP4T4aalrl2DeH4S12o533d42p6KJmmYT+4810uwQiak6CDEjB3Y+JwhPMn3/AUYDzwMvAKOA/w7mpAAkSVosSdJhSZLyJEnqRcljiOPW0yc+MLKk5vYzvDAcPgWICLCXd7aYfFP20JnUWeLx6Frfj63Qb0wWG7Ut7YxJFH5rNU1KeefJhiNTG9dLH0afKEGfgsLQRJLEoumRlVB/FGJHnegZndQE6DRMSgn3nYIngEYHM+8RfdFDLPCzWHvv6SupE4uGSeEBA3uj8j1gboXUGc5tKhXc+A08WAjnPAZ5P8Cu9+Hr+8DUQmyIH+//cjqLswKZnvsPdtkyMWcudhs2xF+Doc0svKBHnAebX4IW599ugz14t8mwvbAOLCaozj2lg74xsiz/Qpbl1fafWxBB4KAhSZIaeBE4FxFk/kySpJPym0h2Ue/cVWoAYPqwUKICuzdcP1UJ8degUUn8+8cjTHjkezb6ahXMQdJU4euX861vx1UYEFVNRmQZxiSGAFCtZPpOOlrsF/MgvwF8Z1UfEiIuEek+mpWCgoLPSJ0Bpmbx7/hBslE5jZiTFcWBMgO1vrzeTb9TZLW+uhfafFQ66gMc5Z0Wm9ytamZJfSsAyREDzPQd+V4kUYad2f3r026B4HhYeifseBs2vgCAWiVxR/h2wmjmUfP1jEt2t0UL8dPSbrFhNFth/kPQboB9n3S8vi6vhuQIfzQqia1H66BsJ1jbIfmMgZ3PCcKToG+nJEkdjRiSJJ0BDLbh1jQgT5blAlmWTcD/gIsG+T0HB3umr91s4ZM9ItCZnBxyImd0QpAkCYtNxmC0YLLaeGjpfkwWH5mYgjAyHXGeEIsYwp42pxsNdgWthDB/AnVqpbzzJKSl3YJGJaFTD6AFvCYPIjLE/1MFBYWhxUiX26uTUJxiqDErMwqADfm1vhtUFyA8i2UrFG/x3bgDxOQS6HVn21BSJ4K+AWf6cpdD0jQI7MHLWusPi55wPt/8orgXlGXGHPuIfXI6jRHjmZPlXmUX4q8FoMloEVnusBQoXA+A0Wxl69FaFmTHMjYplC1H6zpey/Mbx7sbC0WweBLhyVV8MrBRkqRCSZIKgU3AVEmS9kmStHeQ5pUIlLg8L7Vv60CSpFslSdouSdL26urqQZrGwHFk+r45WEdjmyhtU5+mNz5nDo8mOy6YZ64cT351C+9uLPTtG6TPhfZG0dunMCRoMopS3mA/DWnRgaw/UoPVLvGscHLQarLir1O79UF4TUMxhKf6blIKCgq+IyhaZJFAMWb3AeOSwoQqpC9LPAGSpoBKC8UbfTvuAHCUdwLdBkCVhnYCdWpC7cFVvzCUifLO4Yt632/0JXDrGrjiXTA2QtFGOLoWdW0uaefex8r7zyJQ737/HWKvYDEY7cmC1NniOJuNnUX1GM02ZmdGcUZaJHtL67HmroSYUby0tZ6nvsuh3ZfJi+OAJ9HH4r53Of7Isvwa8BrAlClThvBdpLhRWpHbwFnJflDlUvJ5mvHOjVORJJH1+2ZvOc/+kMuFExKIHUivkCsJE8Vj2S6IG+ubMRUGRJP9izTET8sdZ2Vy1wc7+f5gJYt7MWdVGFq0miwE6ga4UNVQrCh3KigMZa77XBiBKwwYtUpiZkYU6/NqkGV5YAtmrmj9IXGyCEqGCJY+Mn0t7ZaBtQaAqOACGHFu7/tJEiRMgMhMUOtF/2P5HgiMJmjyldBNtYoj02doswd96WfBng+gZAvr88LRqCSmZ0SiVkkcWPcF6tItNJz1GF99X8Z101MHFsyeAPrM9MmyXAQYgFAg0vEjy3KR/bXB4BiQ7PI8yb7tpMNhzh6ggUtGCgVDWXV6Bn0qldTx5feXC0Zhtsk8seyQ794gIh10wVC223djKgwIR6YvSK9hXrYoqyisbTmRU1LwklaTlQDdAL6zjI0iAx+W4rtJKSgo+BaNDvxOv9aTwWJ2VhTHGtp4cXUeV766ib8t91EFUuoMsbBtGhrXUbNL5U53Yi4tvlg0zF0hrh+eCoHpg2DcFbDvY6grgMvfFgFzN4T42YM++70KIy8AfShse53aQ2uYnuRHkF7D5CR/HtW8Q4NfIr89OgmtWsUv56QN7LxOAJ5YNjwG7AX+DTxt//nnIM9rG5AlSVKaJEk64Grgq0F+z0HhQLUo6bx0VDAhOvtG6fQs73QlNTKQ289MZ+nuMjYX+KjuXaUSqzzlStA3VHBIHAf7aQjQafDXqqlpUvr6TiYc5Z39psFeqR+W3Pt+CgoKCqcIc7JEX98/V+ZyqMzA6+sKOuxvBkTqLKEEXzrY0hqeYXYpb+zOtqHVZCVArxZ2WrZ+lELKsrATSZ8rMnmesuBhSJwCF70IaXN63C3YnoV0VCWhC4TJN8D+z3iq8Xc8bHkOZJmQ3C9IU1XwtPY2fsht5Jdz0gbep3gC8KSn70ogQ5blubIsz7P/zB/MScmybAHuBlYAh4CPZVk+0PtRQ4/SRhPLcoUi1pmpAUgOy4bTNNPXmTvmZpIY5s9flh7oVvWpX8SPh4r9ipjLEMHxReoo74gM0lE7WF6NCoPCgMs7G4rFo5LpU1BQOE1IjQzk1esns/SuWSy/bw6yLPtGxyB5mhAIPLJy4GP5AEtfmb52CwnqRnhmFDweCy/NgE9uhHoPCwVr88HYIBTavSEoGm75EcZf1etujh6/1naXuc/5Tcc/M+t+gm1vwK73qfZL5b/VGQCMjD85s+KeBH37geNuOy/L8jJZlofLspwhy/Ljx/v9B0pVk5HfrziGzV7eqZZkJNmePj5Ne/o6469T89D5ozhc2cSb64/6ZtCEiUJOt2yXb8ZTGBBN7RZ0GhV6jfjMRwbpFQXPk4y2gWb6Gu2ZvlAl6FNQUDh9WDQ6jvHJYSSFB3Du2Hg+2FrsNPjuL36hMOZy2Pq6c0HtBOK6YN9Tpm9J+zKwtIHVBMFxwn7hyztEFq8vSreJx8QpvpqyG4H2a5vb38U/nFemLGOc6S0sGefAst9CyWbK06/EodOREnHyZfnAs6DvSWCXJEkrJEn6yvEz2BM72VmdU0Wj0co1E0SKH9kKNvEfQlYp5Z0OFo2O5eyRsfxteQ5/WbqfdssA5W8dYi5vngMHl3b8zhVODE1GS4c6FkB0kI7a5gFk+hqKYfmDYFYEB44XLSYrgfqBlHcWg8YfAqN8NykFBQWFk4hb5qTTZLTw8baSvnfui7P/IrJ93/9l4GMNEItVRqMSgVCrqWtAa2pvZX7ztzD8XHi4Ea7/As55BIo2QOG6vt/g8DIR6EaP8PXUAQiwV7F0nvu6CjXJcTFornoXZv0Kzn4Yzay7O15PPoWDvneBp4C/4ezpe3owJ3UqcNXUFN6+fBiJYUKZUpJtSLI96FMyfR1IksRL107i5llpvLupiMte3khhzQAalMPThGoTwMc3wCtzwOyDOvqTjdp8OLwctrwG9YUnbBpNRgtBLhLJkYF6alsGkOn79GbY8grkr/LB7BQ8oc1kxV87wPLOsGTv+jEUFBQUTiEmJIcxdVg4b204OnDbotAkEYgc+By2v+WbCfYTs9XWoYDZnWXD7LY1BFsbYPrtzo3jrxELgYe+7n3win1w6CuYdisMUluUTqNCp1bR7FLeabXJ7C5uYFJKuOjxO+dRmP1rMmKDO/Y52VQ7HXhyJW+VZfnfgz6TU5DIAA002j+oss2ZdVJ6+tzQaVT8+YJRzMiI5Lef7OH859fz5KVjuWB8gveDqVRw3144ug4+/yVUHYB1z8D8P/p+4j7g6z1lvLa2AJUEBZ2CXb1GzTmjYnnsotFovDHG3vsxfH6L8/mqx+Cm5RA3xkez9pxmo5lgP+eXY6Q902ezyahUXgYBLTXOUo/8VZB9ng9neupQaTDy87e28voNU0g2FYgV1dGXQFBMv8ZrMVkGpt7ZUAyhioiLgoLC6c2NM9O464OdrM+r4azh0X0f0BtnPgBlO2HZ7yB5ujAWPwGYbTLBfhrqWkxdLBtkWWaedT11+kQi0s5yvqALgIz5YmH63L93vyBos8E390NAJEy/c1DPIVCvdsv0Ha5oosVkZXJquNt+jjaVkxlP7iTXSZL0pCRJMyRJmuT4GfSZnSI4LBsk2apk+vrgnFGxfHvvbLJig7jnw10s3d1Pl47gOCHX+3AjZC2C3R/0TzXqOPDAp3vYd6yRPaWNzM6M4vLJSR0/09LC+XBrMQ9+tg+bpyuDxZvh6/sgajhc8wncvkEofW17Y3BPpAeajJYOdSwQPX0Wm+w0QvUGh1dPcIKS6euF/ccayaloonjvGnh9Hiz/nSh3bm/u13gd6mv9pbFEEXFRUFA47Tl7VAzhAVo+3u6DEk+1Bi5+RdhsrPyTsCY4AVU9Fqut4xrv2tPX2GZm1O8/Z6p8gIKIM7sGdiPOFdeGin3ObY3HxHmAuMaXboWzH4aAiEE9hwCdxq2nb2dxPYDI9HXiw1um879bT17PWU8yffYmKVzPUgYGVcHzlEFyZvo61DsVy4YeSQoP4OPbZnD5K5v467eHmJ8d45Yp8poxl8GRFVCyGVJn+m6iPmJYZCA5FU1oVBJPXT6uwzPGwXM/HOFfP+QS4q/hz+eP6tvkddkDQrXq599AcKzYlr0EDn4pVtQ0ut6P9zFNRgupkc7a96gg8f41ze2EBXg5l9zlEJIIk2+C1X+F9ibQB/d93GlGTXM7U6Qcpq37J4QkwLw/iaz33o9g6i+8GstitWGy2Ajob3mnqQVaaxW7BgUFhdMevUbNxRMTeX9zMfUtJsIDB3g9DrRnwVY9Bv+eCEiw5Gmvv+cHgsUqE6jTIElgdMn05VU1c4bqEHrJzLGYM+kiwzJ8kZjv4eUQPw6MBnhlNrTVwaWvw+73ISgOxl096OcQpNe4qXfuLK4nKkhHckRXb78ZGZGDPp/BxBNz9nnd/CgBn6c4btJlmxBzAaW8sw+0ahWPXTSamuZ2nv3hyMAGyz5PlAe8fS58cbu7qmfuCtEI3VY/sPcYAA2tIuM1LzumS8AHcO+CTG6elcbbGwp5YVVe74PVF0HFXpjyC2fABzD+anGO+z7x5dQ9ornd4ha0x4aIHtdKQz/6+oo3C68eRxlL9eGBT/AUpKGxkWd1L9GsjYQbl8HYy4WVyY53vB6r1b5y228hlwZFuVNBQUHBwRWTkzFZbXzZ30qmzky7BUZfCmc/AnFjRc/7ccRss6HTqAjQqt3KOwuqmxkjFWKTJZojx3c9MChG2E8c+FyoeG59VQR8INpTCn6Cmfccl4XqAL2aFpfyzp1F9UxMCe97kf0kxBNz9lhJkt6UJGm5/fkoSZKO3zLCSY6jlFNyzfQp6p19Mi4pjKunpvDOxkJyK5v6P5A+GJY8A/oQsaL07kVQsAaW/x98cCVseBY+PTEfZ6PZSoXByD3zM3n52u4rpiVJ4k9LRnL+uHie+/EI5Y29iNLkfCses5e4b89YALFjxLkexzJXWZapbzW5NTw7gr6KRi/VN02t0FINEekQM1Jsqzroq6meUsSUfEeSVMOnCb+B0ESx8JR9viij8XKBw7H62W/Lhppc8RiV2b/jFRQUFE4hRiWEMDYxlI+2lSB7YlnQF36hcMXbMPs+mHCt+M6tzR/4uB5ittrQqCT8dWq38s786hZGqYoolGPRBfTgaTf5RqjOEfcu298RfX4/+whUWmFCP+3W43IOQXpneWdtczuFta1d+vlOFTzp6XsHYZLuUNXIBe4brAmdcth7+nDp6VN8+jzjd4tGEOyn4c9L9w/sy3H0xfD7Erh9nfiC/M+FsOVlmHabKH3L/9Fzo1AfUlrfCkB6dGCvQi0qlcSDi7OxyTLvbuxlnjnfQswoiMxw3y5JMPvX4mJweJkvpu4Rze0WWk1W4kL1HdviHEGfwcugz+H1FpYCYcOE8lfVIR/N9NQis+ZHjsmRbLG5CPekzgRkKN7i1ViO5vZ+C7k4srFRw/t3vIKCgsIpxpVTksipaOJAmcG3A484Vzwex6oei1VGo1aJoK9TeecoqYhDckqHAXoXxlwOERnw0bVgKIVJN8CIxfBQNdy07Li1owTo1B0LnLuKG4Du+/lOBXq805SkjsazKFmWPwZsALIsWwDF/MxDnEIuzvJORcjFM8IDdTywaASbC+r4em/5wAcMS4E7N8KFL8BV78O5T8HI88VrnvjF+Jj8aqHWmRoZ2Oe+yREBLB4Txwdbimjpzty1pQaKN4qMTneMulgoKO7670Cm7BWV9sDOkd0DkTEK8dN0vOYxDS5Bn0olsn2uDeAKAqOB7JbtLLdOo6bFxQ8xcbJYPS3e6NVwLfYLocPLyGuqc8TfTNf3Z1xBQUHhdGDxmHgANubX+Hbg8FQYvhi2vCr6qY8DZqsNrVrCX+vM9MmyzNFjFQxTVXLIltpzpYhGBzd+A2OvFAHgCLsi93Euqwx0yfTtKK5Ho5IYlxR6XOdwvOgt07fV/tgiSVIkQrwFSZKmA42DPbFTBjchF4c5uxL0ecrVU1MYkxjC498edFNX6jf6YJh0vQj2JAmisyEwWlg8HGd2FTegUUmMiu+h9KETv5yTjsFo4ZPulL92vCP6Rkdf3P3Bag1kzIOiTcfNsN7Rt+ca9AHEhfr1I+izZzgdKpAJE6F8z9BRZZVlKN0hHk8kuSvQYmaZ9Qxqml36JrX+oheyYr9Xw9W3isAxor+CA9WHxf8xBQUFBQUAooP1pEQEsLOogeLaVt/c2ziYdZ/ojdv1ns+GrDQYqW3uvg/fYpPRqlX423v6LFYbn2wvRWoSPYvFcgzt3fj3dRCSAJe9Dpe/CRp9z/sNIoE6TUdVy86iekYnhOCnPTXv03sL+hyh9v3AV0CGJEkbgP8A9wz2xE4VXC0bsPf0oah3eoxaJfHoRWOoNLTz/I8DFHXpDkmCYbPh6NrjfsO+s7ie0YmhHn+5TEoJZ1JKGG9tKHQ3d7W0w+aXIfMciB3d8wCps6G9ESoPDHDmnuHo2+sc9MWG+FHhrZBLQ7HIVAXFieeJk6DdALV9iNsMAsW1rby94Sj51S4WCFtegTfmQ8Hq4z4fNw5+SRXh7JIzKa1vY29pg/O1mFFel8Q6gr7wgH4o6NpsUHtEKe1UUFBQ6MSklDC+O1DB2c+s4fKXN/ou8EudAclnwMYXwDqwMY1mK2+sK+CcZ9Zw3r/XUdbQVVPAbLGhUYnyzlaThd98sofffbaXWEn0j1fKESSFB3Q5bigRqNfQ0m7FbLWxt7SRiadoaSf0HvRFS5J0PzAX+AL4O7AceB04e/CndorQ0dNnc/r0KZk+r5iUEs754+L5yBfeNt0xbA40lTn9YY4DBdXN7ClpYFJKmFfH3TInneK6Vr4/WOHceHgZtNbA9Dt6P3jYbPF4dI2Xs+0flU2OoM999S4uxK/bi0evNBRDaJIo7QRIsAvflO0c6DQ9YuvROl7+KZ/S+lZ+++keHvn6II9/6xJA7bSXzdYdPS7z6Zb2ZuS8H/jWMo20KGFl8eBnLiWw0dnic+6FmEt9iyPo60emz3AMLEaIVERcFBQUFFyZOyIGEFm/nIomvt1b5rvBZ94LjcVwaOmAhvnhUCV//fYQJquNZqOFR77uumBstskd5Z3bi+pZuruM4bFB3DpB2B28ePsSxiQO7VLJQJ0ak9XGvmONtJmtTDpFRVyg96BPDQQBwUAgwtNPDQTYtyl4gkO90+YS9CmZPq8ZkxhKQ6vZt2UQDtLOFI9H1/p+7G7YXljHpS9vJFCv4Zpp3knZLxwdR3KEP6+vcwkudn8o/OvS5/Z+cGgiRI+EIyu9nnN/qGw0Euyn6dIPNjYplOqmdopqveg5aCh2N/iOHgFq/XHp62szWbn3w1089V0Os59azdajQlb6ULm9Cb+9CartAeBxXDjowpGVSBYj31mnce+CLC6ZmOgeXMfYrS6qcjwesr7VjCThpsDqMY4sbGdhIQUFBYXTnIsnJrLv4YX89MBc/LQqcioGoFLemRHnCoGUjS8MqIIpv0pco7f98WxuOyuDFQcqOVRu4FhDG3e+v4Pr3thCQ6sJjVoiQKdBluGGGamsuO9MzooTdlRRCcN8cUaDikNoZm1uNcApq9wJvZuzl8uy/Ohxm8kpiuyi3tlR3qlk+rwmIUysGh2rb2NEnI/XHCIzRdlg4TqYclP/xrCaQaXp0oBssdooqGnhYJmBQ+UGDpYb2FJQR2K4P+/cNNVdxKXgJ1j/LzjvnxCV1Wl8C1jbUesCuXlWGo98fZCdxfVMivcTmbvJN3r2uRq+EDa9JIxQ/TzrJewvlYb2LqWdALMzowBYe6SG6z0QsQGEemfWQudzlVoEfsfBtuGdjYVUGIw8d/UEimtbyaloIj06kOdX5dHYaia0Yqfop4TjKpXdhYNLMekj2WYcwYORAWTGBPHFrmO0miwi8Ha1ukid4dGQw0o+Z5I+sld12R6ps/8uIpSgT0FBQaEzDg/b4bHBHKls7mNvL1CpYcad8O1vhL+th9/3nTla00ximD/Bflp+Ni2FZ77P5Ytdx1iVU0V5QxvZ8SGMTwpjwchYWtutxIX68YfzRgp/u6YK8AsT/eRDnIQwcZ/y9Z4yYkP0JIR2vW85VfCkp09hILgKuchWZCRnyaeCxyTag77uygLbTNaOJtx+IUmQNkeIufRnVcxigieT4fuHurx02SubWPivtdz30W7e3lBIfauJK6Yk8dkdM7uqdq5/VgR+718uxnRl+QPwRCJsfoUrpyQT4qfhzXVHoXiTKKHLWODZXLMWgc0s3sejc2vv90phhcHYYdHgSlpUIIlh/qyzr6o5+GxHKfP/+RNmaydxFnMbNFdCWKr79tjRUDm4QV9Dq4mXf8pjfnYMF01I5J4FWbx47aSOlcCcCgOUbhM7D5sDucsHljHe9R68uQhyvLTWMLXCkZUURM/HhoqUiICOC1lZg100JzQJdMFCUbM7jq6Dr+6Bg0uhpRYM5VxS/CTv8uf+nUttgbDWCI7v3/EKCgoKpwFZMcEcHogfcXeM/5m41xxAn3lBTQvp0eI+JTpYT3ZcMK+tLaC4tpU3fj6Vz+6Yyad3zGTeiBiWjIvnofNHoVbZQ4em8pPmu99xL5Zf3cKkU9SU3UFv0YeHd5EKvSHbPzwSNqGaqGT5+oUj6CvtJui758Nd3PbfHQN7g2FzoKXKaSbtDcd2gKUNNj4vMmh2moxm9pQ0cPnkJL67bw4HHl3EN/fM4fFLxnZVQzQaoGiD6LuqL4TdLspbxkbY/QEgw3cPErjyt9w0OZLl+8tp3v2FKHMcNos2k9VZctgTyWcIr8IjK/o+r+pceHYcvD4fDN5bZlQZjMSEdFXjkiSJM4dHsSm/FotLgPdjTiUFNS3kdr74NZaKx7BOpbAxo6C5QgQog8TLP+XT1G7hd4tHuG0faVdczalogtLtQqzE0TP55V39e7Ocb2HpXVCyGdY97d2xB74Acytb/ecQoFMTGagjPlT8n3EI6iBJEJPds5jLuqdh53/g4xvgtbnwxW0ABNEqgkpvqcuHiHRnH6aCgoKCQhdGxAVR3dROQ6up7509RRcoFvr6WX0iyzJHq1tIi3IuTs/LjkGS4F9XTWBGRmTvAxjKIORkCfqcQjOncmkn9BL0ybJcdzwncsrilumzKB59/SQmWI9WLXXJ9MmyzI6iOjbm19JkNPf/DQbS1+cqjJL/Y8c/HcHLeWPjyI4LQdtbiVzJVrCa4Ny/Q8xo2POR8ze68f0AACAASURBVLVDX4ts3oy7xfMdb3OLZhlRqhY0+z/CMvoy0AXy6tp8Lnxhfe8XDrVGZAWP/NB7Bq++SJjYN1cIsZQvbvMq42ezyVQ1tXeb6QOYnRlNU7uFPS7qkntKhBPM3tJOjjAddg3J7tsTJorHovUez8sbyhraeHtjIZdMTCQ7zr0UNiZYT3iAlsPl9cL7LvkMmHkPpM8TvzNvVdNkGX58TPRcLvgzHNvuudKmzQpr/wFx41hjGklKRACSJBFvL1Epa3Tt6xsp1Fu7+1s6yjHjJwgRANfPdZF3/n6AuNmITPf+OAUFBYXTiLSoIAAKa/uxuNYbkZnO73UvqTAYaWq3kO4S9N13dhbf//pMlozzIJhrLBVaAycBATpNh+DcqazcCb1n+hR8gYtlg2SzKiIu/USlkkgI8+dotbv4R1VTO/WtZqw2mc0FA1inCB8mzMv7Y9JevElk6FRaKNvdsflQuQj6RsR50DtXc1g8xo6GkRdAyRZorhLb8ldDUCzM+4PISOqCCdr2HOsCH0Rts/BkwwKsNpmtR+swW2V2lTgDqf9uKmRbYaffS/pcEZj0lNW02eCL20V2546NsOQZEQAc9rzksLbFhMUmd9vTBzArMxJJgrW5wpy2trmdY/aA3s1mAISIC3TN9KXMgIAoOPClx/Pyhmd/yAUZ7j+nq+WAJElkx4VgKtktMrHpc8XK6rgrRfBe76WK59G1Qgxm9n0w6UbQBcFPT3p2bNFG8X6zfkV+jXNlNs4e9JU3uHgixowSHk6Oz5aDpkrxe174ONyyGq77HH75Izdq/yFe99Yaw2oRc1KUOxUUFBR6JSVCZJqK63wc9EVkiDL7frRo7CwS1+EJLkGQXqMmM8YDTQVTi6icikjz+n1PFKmRgejUKsYkDq7WwYlGCfoGmY7Mns0qxFxUStDXX2ZlRrEmt5oWFwVP13LG9UequzvMMyRJBFRH13lv+G0oE6IiMSOh3Bn05VQYCPbTeNYUXH0Y/CMgMEoYxyOLcj9ZFgFB2pkiqLjxG/j1fphwDfqQaNaPeZQ3c/15+KsD7LEHe7uKhCR/XlUzDy09wB8+34fs+qWfNkc8vnth9z1xG58T2avFT4ogdNLPITxN9Bx6iMN8vaegLyxAx7ikMNbniaDPkd0L8dN0ZPw6aCgW/2869weoNSJAzl3Rv/LDXjhS2cSnO0q5fkZqjx5D2fHBJNRtEU/SzhKP0fYyUC/98Di4FLQBMOoiCIyEabc6e+v6Yv+noA3AmL6QorpWsmLFRVmvUZMU7u9e8hs7RjxW7HUfo2SzeEyeJsoxMxdQEjCKdS2JmFQBouTYGxqLhXCVIuKioKCg0CvJEaIUv8TXQV9khvDmbanx+tCdxfXoNSpGxfcjCKq3V+eED/P+2BPEheMTuHZ6CnrNqV2NpwR9g4xsD/Ikm0Vk+pSevn5zycRE2sxWJjy6skNa1yFzPCE5jHV53n+xuZE6Q2RBvM3SNFdBYAwkTIDyPR2rajnlTYyMC/GsKbgm1xkwxI4RoiU530DZLrFi5ggqAPzD4MLn4e6tzLvibn45O43/bi6ixSQsQV5ZU8CER1dywfOi7PFIVTPjH1nJze9sE8FfeJrIJDVXwNuLnV/QIMpMf3wMRl0ME64R29Qa0RReus2tZ7E3nEFf154+B3Myo9hd0kBjm5k9pQ1IElw6KYnDlU0YzVbnjg0ldo++bv7vjL4EzC2Q971H83LQbrFy7nPrmPDoSq54ZaO72T3w9xWHCdRpuGtez5mqkXEhDJcLKCaWCc/sYs7fV7GjVXgvUX3Y88nYbCLAzzzbqXSWPheAdz7rJYspy7DjXdGHN+ZS8hpkZBmGxwZ17DI9PZLNR2uxOc4vfpx4dMlIA1CwRnwmHCWzwEs/5aFVq5AiUp0ltp5Sa7euUOwaFBQUFHolQKchKkhPsa/LO+Ps3/f7Pvb60F3F9YxLCkVnNgjdAm9wLBKGDfP6fU8U101P5S8XjD7R0xh0lKBvkOkI+mQLkmxx9vgpeM2U1HAeWDSChDB/7vpgJ1abzOGKJuJD/Th/XDwF1S3em3674rjhLdvl+TGWdjA2iPLL+AnC+LqhGFmWyaloIjveQ3uJ6sNCDARE1nHkBeJG/MOfCaGWkef3eOgfzhvJQ+eP4raz0nnt+sn8bFoyF41P4MopSfzrqvHcuyCLM9IjWZVTxaaCWjH+TcvhqvfE/Fc/LgZqa4BPfyH8/C54zt1+InkaIIteMw+oNLQDzhLD7piTFYXVJrMpv5a9pY1kRgcxIyMSq03mQJlLcNlQLEpvuyN1FgRGw8GvPJqXg9L6Ng6VG0gOD2BbYT0rDjjN7nMqDHx/sJJbz0zvKrjjwqLRcUwPrKQldAQXjU9ALUn8/L2DtAUmOX37PKGuQATgmWd3bLLZL9ZVh7f03Ku692P4+l5R5rr4KY5UiQWQ4bHOz9yM9EgaWs28vq6Aj7eXCBGfiAy3jDQgyndTZ4La6ceXX93CuKQwtJHp3mf6HOWgSqZPQUFBoU8Sw/35aHtJVyGzgZA6U1gdrX5SlFx6QXFdK5kxQfD5LULMbdf7nh/suF6cRJm+0wUl6BtsHOWcNgvIVkXIZQBIksRd8zK5d34WTUYLBdXNHCo3kB0XzCy799v6gWT7orNFgOVN0OfojQqyZ/oAyndTWt9Gc7uliwBIt7TViwyja//TjLtFENhcAaMvBv+em4tVKolfzE7j9+eOZOHoOB65aEzHzyUTk7j/nOE8/7OJRAbqeMNh6h4/TgSW0++AvR/Bmr/De5dBUxlc9pbIJrqSOBmQoHiLR7+WCoMRSYKooJ4zfRNTwgnUqVl3pJq9pQ2MSwpjXFIoAPtc+/oairvaNThQa0Tpa/Fmj+bloNKuaPng4mxSIwP41/e5tFtEdnF1jsgiXzWth0DTTqjORlR7CSPHn8EjF43hw1unExWkY7853isD9I7PW+Kkjk05DWoKbbGMVh1l3ZEePtNbX4WoEfDzb0AfRH5VC2qVxDAXK5CJKeLv+OTyHH73qb2k05GRdlB3VARp6XPdhm9ptxDipxEX7vpC7/pCSreJhZCgGM+PUVBQUDhNGWVfIP7X9/1QEO8JSYJZ94GpSVSTeIjJYqOm2cRc4yo4slJs3PyS5+9bf1RUjgREeDlhhcFGCfoGGYdwiyjvtCjlnT5gTKIIDHaVNJBf3Ux2fAjZccFEBelZ39MNsieotRA3pmvpW2+0uAR9MaNFkF+2m8P2slOPMn2O8krXpueQeLhtDdy2TgipDBA/rZrrZ6SyKqeKvCqXlcS5vxfZstWPC/+2K96B5KndDBAiyk9dg4VeqDIYiQzU96pYqtOomJ4eyTd7y6lpNjE+OZS4ED+ig/VOBU+zUQS+nUVcXEmcDIZSIUbiIeX2oC8hzI+HLxjNkapmPt4urCHW51WTHRdMTHAfvZg1R0Sfrt30PD7Un2lpEeRYEqD2iOcKnuW7QeMnFh3sbD1ay245g6mqXLbkd/OZrskTJTeTb+ywRChraCMuxA+dxvk7TwoPcEvY2myyXZ2zxNkveNBeQjryAre3aG63EKjXQHgqmFuhxcOeWVkWgkjDZrtnixUUFBQUuuX3540kPtSvozXCZ6TMgNAU2PM/jw+pNBiJpp5FuX8RCpxTfwlVB6HdQwP58r1CD0D5/h9yKEHfYOOi3onNqpR3+oCM6ED0GhVf7ynDbJXJjgtGkiRmZ0ayIa/G2b/UH2JH92xe3R2umT6tn5DcL98tTLtxL7XrkY76907ZLLVWZOT0QV0O6Q/XTU9Fp1Hx5vpC50aNXmSKbt8A9x/scuPvRmSmxyqOFQYjcaE9Z/kczMmKorFNlC+OSwpDkiTGJ4U6rRwaS8RjZ7sGVxLsGbKynR7NzTE/EOWnc0dEo1EJOxCj2cq2wvqOzHGvONRPo5wefnEhfuxuj/dOwbNkq+jjdCmtrG5uZ6M8jhipAam6G7Gd/FXiccS5HZvKGts6bBoc6DQqEux+fQB1rSa3jDSyDPs+E4Fzp8C62WghSK9xlujUe9jXV50DzZVCGElBQUFBoU9C/LTMSI/saI3wlg15Nby/pZvvaJVKqEoXrIamiq6vd0OlwUimqkw8ufglyFoEss2zKiirRSwOJ0zqe1+F444S9A02koSs0ohMn2zt6PFT6D8atYrs+JCOUk6HUfbUtAhqW0zuvmTeEjUCWmug1UP7B0fQF2gvY0sYD+V7OFRuICUiQNw090VH/XsPJYw+IipIz2WTEvlsZykvrs6j3PF7UqlEhtMvtI8BskQgY+3bD7HS0E5sX5kyYM7waAA0KonsOBEgj0sKo6CmRfSyOYLMyKyeB4kfB0heZWgrGo2E+msJ0GmQJIkQfy2GNjPbCuswWWzMzvIg6DPYL4qhSR2b4kL92W3LQEaCdR5kaKtzoXQrZJ/ntrnJaGG3VgRnKfWbuh6Xv0oEYy7Z4YpGY7c9lA5lOLAL7Dia+9+7FDa9CJX7YOJ1XY5rarcQ5Oca9BX2fT4gzlvj5xaQKigoKCj0Tpw909efhetX1uTzxLeHuj92/NUiaNv3qUdjlTcayZDs17fILHt7B54JutQcBkubmyiYwtBBCfqOA7KkAUfQp2T6fMKYhBBkGXRqVYcvWWa0yIjlV3vXsOyGQ0zFU/VF10wfiNK51lrqygo6gpg+aSgSdg19BV0+4N4FWUxIDuMfKw4z82+ruP7NLXy565i7WmZPRGaJ3lQPMj6VBiOxHlhVpEcFkhjmT3Z8MH5a8X9jbFIosozwF3T8HaJ6Cfp0gSJgrvFcMbPCYHQzjg/209BktLD+SA06tYoz0jzoRTCUgTbQ7e8WF6onX06kaswtsOcDMJT3PsaOt4W/48Qb3IduM2P0j6PCL53RrZ3Ec6xmUT6ZMb9jkyzLlDcaSQjzpzPJLpYTVYZ20a8ZO1ZsWPlH0S869kq3Y0wWGyaLjWC9xpkB9CToazwG+z4RlhPBcX3vr6CgoKAAiKDPYpOpaek+2yfLMhvyavj1R7uZ9bdVvLY2vyPIy6loosVkpbS+m0XvqCyRedvrWYlnpcFIulSOrA2EkARhIxSSBBX7+j74mL3iJlHJ9A1FlKDvOODI9GFTfPp8xegEcaOdERPU0TeWESOCvrwqD+vOuyPaHvT9f3v3Hd/2XecP/PXRsCRbkuW9Eiexs0czmqbpTmnpul4Xo+UKtGwKB8f40YNbjKPHDaCUY/aOctBjtNCyehTogC46Mpqk2bNxHO8tWdb+/P74fL9a/mo4iSVbfj0fjzwca/nrWJH8/r5XpsXl6cb71C/9Fq2UsUllZypH9mJ5vvttho5Ne5ZP11TpwMMfuADPfGoLPvKGJTg+MI6PPbQTH38ojyyZHngNHs56s2AkiqHxUF6ZPiEEvvLWtfjCjavjl13QVoOmSjvue+oI5MAhNRAkfbDMpGNbprJmeTo55E8JSlXQF8ZzhwewYYEH5WV5/D8d61RviEl9C41uFXQdrd2iLuh4MfPex5Af2PkjYOUNgLMu9aEDEbjsFnTVXIh1cj8C40nTTDu3AiFfStA3NB5CMBKbVN4JJBb/AolVGrjzMeBDLwHn3wW8+w+TSoj1XZgVNotaI+FszC/oe+1nACSw8V25b0tERHH6icgXMgyk+9qTh3H7f7+MJ/f3ot5tw7/89gDe+8NtONLnQ79XBYr7ezKsVTrnVhW0Ge3mTXNqZAKLzd1q5Y7+/ta4Gujdm/ub6NoB2Nyc3DxDMegrAGmyxFc2MNN3dqxuUQHViqRsWk1FGTzlVhztP4Ogr3K+Kk3LN+jz9aqgRNe4GlKYsUocTzk2AMC27wPf/wvgxJ8Tl8Wi6syYFiwWyoKaCnzijUvx7Kcux1+d34qn9velLL03VLdc/dsc+l3Wm+lvPvn09AFql9yG1sR0UrvVjI9fuRS7To5gpGMvhhwLc2ci65aqUtBY7ozln48O4ECPF5cmlXC6bFa8PujHvu4xXLKkLsu9k4x1qaAviV5e+cNjWsD/83cBf/yi8f33PgoERoGN7550lTcQhttuxfi8S2ETEYztfzpx5ZGnVG9wUs+cPpjGKOi7aX0LPrRFvQHH+0UcHjWA5tp/TZzoSOLTngvx8uSqhfnt6jvwmCoFqm7LfVsiIorT3z8+/tAufPqR3SknsHvHAvjus0dx7epGbP37K/HoXRfi8zeswvOHB3DlV5+J3+5Ad4aVD6vfpN43dj+U8zheONSHc8wdENqQMgCq73zgkBqulk3Xq6pv3MTwYibiT6UQ9J6+WMR4wTRN2dIGF+pcNlzQXhO/TAiB9jrnmWX6TGZVxph30NefGvRZHRh1tmG1OJ6a6YvFgCf+CTjxPPDLDwFhrQSjZzcQHFOTDovAZBK4bnUTQtEYXjw6mP3Gdrc6W7jrp2rNRAZ60Ffnyi/oM3LLhhYsq7PDMngQj3W78dDWk9nvULsMiAbzykb9ZlcXXHYL3r45kV11Oyw4PqDKgvMa4gKooC+pnw8AqsqtaKq043eHks62PveVxN/7DyYC063fU4H0gosmP/REBG6HBea2izEmHcD+x9QVsZjKpi28KCX7qWfwGtxGPX3luPua5aipKEOvN7/JcN6ACvpcdj3oW5D73zYaUWeS52/O62sQEVHCgho1pK7eZcNPt57EZx7dHb/ua08eRjQm8ZlrV8BuNUMIgTsuXIj733kuLCaBijIz5lU58PiebuO+Pmed2gX72s8yV58AONTrhWVgHzyx4dQ1Po2r1bTqbMNcIkGgZw/7+WYwBn0FoPf0cU/f2WO3mvHK312Bt2xMneq4uM6JY3lm+l7rHMXCT//f5Mxg7ZIp9PT1quXgSU6ULcEa0+torUrqrxo8ooK7c25Vw1D0QECfwrjgwvy+3jQ4b1EVysvM+NOhvtw3XvNmIBLI2tA9ok3j9JRnXmyei8Vswhc3+OASE3ghthr+UK5MnzZBM49gfWwignqXLd5DCAAuu5qcabOYsKYlj97KaERNQkvL9Akh8PQnt+DzN6zCRyMfRa/QnhujncDhJ4FvbgJ+eZd6fnXtUCsXDMZaewNhuOxWNFZX4unYelSefEJ9zY4/q4zb+nek3D6fQLvebUdfnuPAx0N6pk+bKFq1UH0PkVDmOw0eVs+NpnPy+hpERJRQ6bBi7+evxit/fyXuvHAhtp8YxvB4CEf6fHh420ncfv4CtNaUp9xny7J6vPa5q7HtH96IT129DAd6vLjmvmdxzdeenfwF1t4KjJ1SPeEZ7DgxjEtNWrCZ1EKAtsvV7IGnv5g5aOzdA8TCnNw5gzHoK4D49M4Yp3eeTcLgl+X2+goM+EIY8Wf55VTz8DaVPfrjgbRgp26ZWggezmMKqK8vNdMHYGd0IWrFKMw+bYhH0JtYJ3DRx4BzbgOevxc4+DjwwtfVcvG04KGQbBYzLmyvxZ8O9kPmWsDdoPXe9ezJeJNRvwr6Kh3WjLfJx8bQVkSEBc/HVuf+eU5hAI+aSpl6bHpGq6XKAbMpj91C3i511tPdMukqR5kZd1y4ELfe+Tf4oPxbAEDPU98CHvuYusHuh4AnP6f+vvImw4cfC0TgtlvRVOnA49FNsIVGgBMvAK8/D0AAy1KnfQ74VNBX68wc9DW4bXmPA/dpmT6nPam8EzKxQsNIt/aLQiODPiKi02HRZhTcvL4FMQlc9bVn8aZv/xl2iwl//YbFhvdxlJnhKDPj+nOa4Sm34lCvDwd6vIhE04KzZdepfrssJZ593iCWmE5BuppTh3E5PMCVn1XVSpkWtXOIy4zHoK8AVE9fVP2SyEzftGqPT/DMne3T+8QmLRCvXQJA5t5JF/IDIW/KEA4pJZ4e00r+Xv4O0PES8G+LgF98QE16rFsGXPMloLwG+MltqtTvuq9k+AKFs2VZHTqHJ3JPPi2vVoFOb+agTw/QPGcS9EkJsf/XsLRdhsrKKvT7cgQrDo8KvvPI9PkCYbjtqSdf3FoQaNQTZ2jwqPpYk7lZ/aLFtfiPu25Dv6hG4+5vIuQfA+74jbry4G+BeZsAd9Ok+0VjEr6gKu90lJmxy7YRIZMd2P9rVVpTu3TS4JUBXwgumyUle5muwZX/4l9vvKdPe7x81jb07gHMZYkAnIiITsualkp8+PJ2XLKkFlesqMc3bt+Q9aQeAJhNAhcmtbwM+NJOllodwOIrgOOZM329YwHUmf0QFTWTr9xwB7DgYmD7/xjfuWsnUF6rZiPQjMSgrxCSM30M+qbVYm2C59G+3Gsb9JLBwfG0F0Z92XaurNG4vq4hkenr9wXxjH8BDjXfBPz568ADV6tyB5MFuO4/VM9geTXwnj8AWz4DvOf3hoM0Cm3LMhW4/ulgHiWeDauzZ/omVMBwRpm+UztUGePqN6HWZZv85mWkdml+mT596XgSPdPnceRZkjqkB33GZ151ixtc8DSrqaf/7r8eXz/WBHn+XapM5up/MbyPL95Pp/79qjwe7LJvAvY8ojJ9zZOH/gz4gqjN0UPZ4LZhwBecfPY3yzHEyzs9Wv9jtqBv8Iia2GZmNQMR0ZkwmQQ+dfVyfPWt6/DVt67D5cvq87rflqWJ23Ub7SxuXg+MdmTca9vnDaLG7FfvUemEABZdorWrGJxY79qhHt+gCotmhhkX9AkhPieEOCWE2Kn9uS73vWa2+J6+WJjlndNsXlU5yiwmHMkj03dqRL0g9qcPt6hpByCAgeyrCeDrVx+Tgj41OUtg8A1fAd78fWDzh4APvgD84wCw/vbEfasWAls+DTSsyv1NFcC8qnIsqXfiTwf7c9+4MfsUr5GJEJw2S7xMJS4wBty3Djj2jOH9Umz7HmBxAMv/ArVOGwa8eZQl1i1Tx5WjRNUXnBz06dlelz3P/5+DRwFrOeCanKlLZ33jZxGbvxm+Vbfjq08cwidH34rgxw8A888zvP1YQJXH6tnI5ko7HjTfoobnhHyGk14HfEHUOrMHrPVuO2LS4CSHAX2Sa7y809WksnjDxzPfafBI1swnERFNrzedOw/33KzaMAwrO/T3j/svA/b+YtLVfWMBVAmf2t9qpGktADm52icSVCdd2dM9o824oE9zr5Rynfbnt8U+mDMlTWa1siEagjSf/kRDys1sEmirrcDRPCZ4nhzyA9AWViezOvJb9u3rVR+TBrkc0HbkLG9yA6tvUaWcjatnxZmvy5fX45XjQ/BqQUdGDdoUr/4DhleP+sPGWb7+gypoOPJE9scf61Y9B+feCTg8qHWWYV/3WLwHM6OmdWpYTobj0vkCERXMDB4FHr4D8Ce+Z3e+2cnBo2otQT4/14UXwfSe3+NLb7sQn3zjUjy6sxtvf2A7hjIEX6PaIBw909dYacdz4y3AVfcAF34UWHvbpPsM+EI5S3/0yZ75lHgO+0OwmATK9XJRk0lNte3L8G8bjQBDxxO7HImIqODMJoFrVqlePH2VT4qmtYm/b//BpKv7vEG4pTdz0Kf3bHfvSr28/6D6vWCGnMgmYzM16Cst8fLOEKT59CcaUn7a65w5M337usbiGY8+oyxS7dLcmT6D8s4D3V40uG2oqph9P+erVzUiFI3hiX292W/YuEZ9zNDXNzoRhqfcIHjSs0RZSkPV9bvVtNtVNwNA/N/y04/sjmdnDelrL15/PuNNYjEJXyiiAqpf/TWw75fAK/djvbYncMvSPHf0DRycclZLCIGPXLEE//m29djVOYqbvvmC4XqRYa0nskr7N2z2ODDsDyNw3l3AVf+syoPTD8cXzBn01Wvln/kMcxn0hVDjLIMpeahN8zqge6dxJnW0Q5Ux5yh3JSKi6VWtvWd+/jf7sK8rbVm7wwNc92VgydXA8WeA4cT+1VhMot8bQHnUa/g+A0ANnXNUAX1pS971z/VhbzQjzdSg76+FELuFEA8IITKcbpg9VHlnVGX6TLMvGJht2uudODnkz7rQ+76nDqHSYcU1qxrRZ7S7TA/6si379mlBX0Vir9uBHi+WN7oz3GFm29DqQYvHgU88vAvfeeZo5hvqi7d/9WHDUs2RiQyZviEt6MsyBEY9QIf6qA0PiURVkBGTwNX3Povr7nvOuFehaqFqIN/9EPDAtcDA5EE846EIpAQaMKTWHwDA9h/govYa7PrsVbgwnx1944Oqt+00dxH95dpm/PT9m+EPRXDlV5/BW7/7Im751gvxTGaPdnZWX9SrD5cxPGsLIBSJYcQfRk2O8k4902f4fE8zOB5ETUVaENm0DhjvB740D/jBX6b+3+jXBugw6CMiKqrkyeZffcJguNmm9wHX36sGC774jfjFQ/4QHDE/TIhmzvQJoeYepJ8U790DmG2qr5tmrKIEfUKIJ4UQewz+3Ajg2wDaAawD0A3AcLShEOL9QohtQoht/f159CEVUXxlQ5SZvkJor6tATAKvD2Ye5rK3awyXL6uLr3iIpi8zrdOWfesBiBFfr5rCaVYBTjgaw5E+H5Y3uc7Gt1FwQgjcc/NqrG/14F8fP4AdHRkWsJvMau0EALz6v5OuzpnpG+9PBMxGhl8HLHbAqRrSP3BpG/7+uhX4tzetwY3rmnGkz4evPWGQhRUCWHIV0LlVBXSv3D/pJj6tV21eQHsjXP1mtX7B253/4Bl9R2HLxvxub2BDaxV++eGL8LZNrdhxYhg7OkZw989348TgeDzzrAdpevDXnSHLqQfAzR6H4fW6WmcZhMgv0zegZfpS6ANkQj7g+LPAF6qB/do00p7dAARLe4iIZoBv374B86sd+PPRAeMT4JUtwKqbtGXt6npfIIJKoVWfGA1y0RntMu7eBdSv4CCvGa4oQZ+U8kop5WqDP7+SUvZKKaNSyhiA/wKwKcNj3C+l3Cil3FhXl2dJVpGolQ0s7yyUXBM8YzGJ3rEAGisdqHfZEY3Jyf1V+tj5bCsAfH1ARWJS1vGBcYSiMayYpZk+QC16ve9WlcHK2hd5y3dVwHT8mUnlfiP+MCqNpmDqwRwA9LyWX2dmhAAAIABJREFU+bFHOlTGTjtbWe+2432XtuHW81pxz81rcMO6Zjy+p9v4vsnDcl772aRhM/pUyqbxA4AwJfrjevdmPp50p7ap+55mpk83r6ocX7plDR6560J87VYVUO05NYbesQAqHdb4+oXmShXMZcr0dWi9qa3V5YbX6yxmE2qdtrwWtBuWi7acC1z5eeCjOxNngQ9oLdddO1WWzzY7T3gQEZWSa9c04Z+uXwV/KIq96SWeumXXqQFhx58Fjj+HQDgCD/SgL0uRXd0ywD8A+IfU57EYcOpV9R5BM9qMK+8UQiSPw7sZQI5asFnAZIGIhmCKhVneWQBttU4IAcN+KUCVMISjEo1uW7zPaVLJWz7Lvn198WwUAOzv1oe4zO5ffKu1DE+mQSNxbVtUtjNpcIqUEqMToclZs2hE1fwveaP6PFuJ58gJNUgng4U15RgLRIzPXjZvAC78iFqHMTEE7PpxytVjWtBXPbZP/YznaRM0swWh6Tq3AvUrJ+3KO11r53twxQr1POoY8qNnNIAGdyLgimf6jEpakX/QB+gL2vMo7/SFUJPel2oyAxd/DKheBHx4KzD/fKBX+3fr3mm4SoKIiIpDbw0YyLTntv1ydQLzwZuAH1wP25HH1eROIHvQl77WavCw2lnMoG/Gm3FBH4B/F0K8JoTYDeByAB8v9gGdKSksEBH1C1uMmb5p5ygzo8XjyLigPdEz5UC9Ww/60l4Uy6vVktH9v0mczUo33pcyxOWJfb1w2S1oqz07wUCxVJSZYbOYco/21wOmpCleE+EowlE5ubyzawcQGAVW3QK4mrNn1oZPAJ7WjFfXaBkow+MTArjqi8Blf6vegJ79sloVodHLO90j+1SPmsOjsor5ZvpiMaBze+J7P0tcdiuqK8rQMTSOXm8wXtoJAHarGdUVZejKkukrM5tS7pOJWtCevbzTH4pgIhyN/zsbctYBCy8BevepLN/YKRVwExHRjKBXa2QM+hxVwKV3xz9teuVfsEBog9zKDZaz6/QqlxPa0LSTr6iPDPpmvBkX9Ekp3yGlXCOlPEdKeYOUMkMd1+whTRaYIupsPMs7C6O9zpkx05c8KKPepX5R7jf6RdjhATpfAX52h/EXScr0dQ778fieHvzVplaUWWbcf6spEUKgpqIMg7kWotcsVuWaSVmyEb9aN+BJz/QdeVKdUWy/XK2wyDTB0z8EBEYSw2IMxN/Isu3uEwK49t8Bbzfwx3viF/sCEdRhBGX+3sTo6obV+Qd9A4eA4OhZD/oAlanrGPKjdzSAxrQArqnSHn/epuscmsC8KgfMptzrI+rd9pyDXPSfe67BMGjdrEZ0P/o+wGQF1rw559cnIqLC0F/DB7xZ3ssv/4wq2X/T92D3nsAXrd+Hv2p59qFczjp10vTIU+rzg78F3C2JCimasWb3b6ezhDRZYAoz6CukxfVOHBvwIZY+oAVAj1be1lRpR12m8k5AZYsAVe+eHhT4h4CwH3CpfTjff+F1CAB3XrTwbH0LRVXjtGFwPMfAD7NFlTm+8l/x/W160DepvLNzmxry4ahSzd4Dh4wno+oTwWoy73vTl5BnPHupm7cRWP8OYOv3gKFjwKE/oPLIL/FP1h+q6/VyxIZVWZfNp34f2hnN+YatxmektbocB3u86PcF42U5uqZKB04NZy7vnJdHaSegyjsHfCGEo7GMt9HLP3Mte4+vyBg4pHZSJpU6ExFRcVnNJnjKrbnfK6sXAcuvR8imhrf0XvBZtZs1m8VXAh0vAvetVUHfihty34eKjj+hQjBZYIqpMy3s6SuM9jonAuGY4V637tEJmE0CtU4b7FYz3HaL8a6+c94K3H0csJYDL34z7UF2qo+N52AsEMZDW0/iL85pQlNl9gmKs0V1RVnunj5ABXDRIPDwOwEkFotXppd39h9UASKgArpYWPXupRvUgr4sS75zlqwk2/JplY389kXAj9+Ci3d/Gn9pfkldp+8bbNSWzQ9k6d/UdW4F7J5pWU3QVpeYJLtxYerktOWNLhzp98Efiky6X/foBFo8uUs7AaBFm/D5j7/cg/4MmdIXjw4CAFa3VGZ/MKsjUYZ7ySfz+vpERFQ4NRVl+b1XWu14ZsvDODfwbUQXXpL79voQNH1A27l3nslhUoEw6CsAKRIjbKU5+wJlOjviEzwN+vpeOzWG9rqKeDlcvduOvkx9TuXVwLrbgd0PA6Odicu7XlUfm9bioVdOwheM4L0XZy5JnG1qnKq885XjQ3jwpRN4/LUMVdaXfkoFQQMHgd/ejfKDj6IcAXiSp3cGxoCxTjXxC0gETIMGuwAHDqtSQU/mQS56dnYgV/kpoBbJ3vQtAAKobMUP2u/FA7gBWPu2xKRJfZlsrqXxAHByqyrtFLlLKafq+nOa43/ftCg16NuwwINoTGJ352jK5cFIFAO+UN4nG25Y14w7L1yIn2/vxJb/+CO++ccjkwbiPHWgD2vne+Klz1nd/nPgLf+T+NkSEdGMUeu05Rf0ARixNmIQlbBZzHk88BKg9QKgog74u26gfvkZHikVAhdqFIA0Jf4DSXOeu8DojLTXVQBQEzy3LEuUnUWiMWx/fQi3bJgXv2xZgwtP7O/FH/b24KpVjZMf7KKPAjt+CDz0DjWMxNerdpU5GxEpc+P7L2zH+YuqsWZejszILFJTUYbB8SA+8OA2DGslm4995OLJ2Z/qRcCN3wAeejvwynexFsB3rGtQWX5d4jb62os67U1Bz+INHE5M89QNHlGPmWXXj91qhtNmyfuNDCtvAJZdC8gYtj68F/ucbXj3zVuSvoc2taR2KMtCekD97PsPqFLGabC43om18z1w2szxdQ269fPVJLUdHcPY3JZosNdPVjRW5pfps1nM+NwNq/DOCxbgXx8/gP/4/UH870sncO+t67C5rQaxmMSuzhF88LI8F+zWLWPAR0Q0Q9W6bNiXaWVDmkBElf3brHnmg97xC9WmwbLOWYM/qUJIzvSZmOkrhBqnDVXlVhztT93Vt7drDOOhaEom5Ys3rcaKJjfu+tEOPLK9M/2hVAnbJZ9QEyiHjqqADwJY/3b8dk8PukYDeN8lpZPlA9S/XyAcw7A/jHdesABCAE/tz7BQXV9SbrJi1/y342LTHnhk0puMPtZZD/rKawB7pQrw0g0czqsZvNZZll+mT2e2AhYbBn0hVButInA1AmM5Zkad2g5Aql7BafLoXRfiwXefP+nyqooytNVWYMeJ4ZTLu7Ty5fQewFza6py4/50b8dP3b0ZMSnz9KVVWG4hEIaXBIB4iIpp16pw29HuDkHLyfIN0Qa3qI/2kY0ZWx1lbXUSFwaCvAKQpEfRxZUPhtNc5J5V3Hur1AgDWJGWsqirK8OP3no/NbdX45M924YHnj09+sMv+FnjLD4D3PAG89yngs8OQb/gH/Pdzx9BWW4E3LC+tIRbNnkS54PpWD9bN9+DpgxmCPncTcN2XgQ+9hJ2VV8AkJMo7/pS4fvh1NblT7/8SQpV46v17umhEDVzJo1+u0mGN9w9OxdB4yHgqpasJ8HZlv/PJrQBEIsidBmaTgCnDFM4NC6qwo2Mk5c07MZTo9HpJN7fV4LyF1fHgcSI0xTd9IiKasRbUlMMXjGTs4U4W1DN9s3wCOWXGn2wBJAd9nN5ZOIvrnTiatrahO2ldQ7IKmwUP3HkerlnViC88tg9ffeJQ6pkxIYBVN6mpjfM2AkJg6+vD2N05indfvCjjL+qzVfKi7wa3HWvneXAswwoMAMCm9wG1i3HI1I4ROCH0/T0AMNKhxjknlzbXLJnc0zdyQg14yTLEReeyW+ENTD3oGxwPorrCINvubsqd6evcqgbX2N1T/rpnw4bWKgyNh3Bi0B+/rGvE+Pk8FS0eB7pGA4jFJCa0M70OBn1ERLPe0gbVu36oN8v7tyYQjkIIoMzM0KBU8SdbAAz6iqO9zonB8RCGk6ZQdo9OoKaizDCTYbOY8Y2/Wo+3nDsPX3/qMP50qD/r4//Xc8dQVW7Fm5L6A0vFgqSgr6nSgQa3Hd5gBOPBydMjk41MRHHEvFgt7I5f2DF52XrNYrXQO5RUfpvHugady26BN5D9WNLFYhJD4yHjVQSuZmAsS6YvFlNB3zSWduayYYEHgOrr0/WMTsBlt8BpO/327GaPA6FIDAPjwfhQF3sZgz4iotluSYMqvzzc581522AkBpvFBDENg8poZmDQVwjJQR9XNhRMe70a5pJc4tk9GkBTlvH2FrMJ/3zTapgE8GrHSMbbjfrDeHJ/L27b1ApHCf6C7ElaudDotqPBrbJj+g63TEYmQjhhWwL07QciWjmJUdBXazDBU+/xyyvTZ5lypm9kIoyYxOSePkBl+kJeIJjhjXHoqFoaP+/s7+fL15J6F1w2C7Yn9fV1jwbQfIZrQvQ1Dl0jAUyEVHkPM31ERLNfndMGT7k170wfS/tLG4O+Akhd2cCgr1AW16myhpSgbySARnf2X5LtVjPa6pxZJ17t7RqFlMAFSZMUS0nymT5HmRmNbhUo92ZabaEZnQijp2KFKtPs3QNEQqpXzijTB6QOcxnpAGxutSYjB5fdCt8UM3363kHDoM+lrUvIVOJ5UlvKPu+8KX3Ns8lsEljX6sGOpJMR3aOBMyrtBBL9m10jEwhEWN5JRFQqhBBor3Pi+EDuoC8YjrGfr8Txp1sAqSsbGPQVSkuVA2UWE378cgcefOkE9naNomt0As15LLJe0eTG/u5sQZ+6blVzcfq7CmFpQ2IqV3086MuR6fOHMVB5jvrk+HPA6ElAxiYHfdXaSoDkoG/slNqrlweX3YLxUBTRWO6JZLphvwr6qsqNMn160HfK+M6dWwFbZV6TRafT+tYqHOwZg08rs+0eDUx5cmc6PdN3angiPsjFUca3BiKiUtDotqMvj0EugQgzfaWOe/oKIGV6J1c2FIzZJPCeixfhZ9s68Y+/TCzezmfS4YomF36zqwujE2FUGoyv39s1ika3HTXO0v15/vqvL0ZMG2ajZ5NyBX2jE2FI9zygYQ1w+A+AZ766omFV6g3LygH3vLSgr0sNfMmDy65+Jr5ABJXl+a0X0Hs7DYM+PSgdPWl8557dQNM5Rd9HdO6CKsQksOvkCM5bWI0BX/C0J3fq3A4LKsrMODUygdYa1cuZ13JeIiKa8erdNjxzKI+gLxxlpq/EMegrhJRBLtx/VUh/e81y3H31MnQOT2BHxzAO9nhx47rc2aSVTSqDt797LGUZtm5v11hJZ/mA1LH9TpsKDLKVd0aiMXgDEdUPuPQq4PmvqUXrFjvQsHryHWoXJ4a3ACrLlh4cZuCyq/9TY4Fw3kHfiLZk3mN0e3ezWisx0jH5ulhU9Siee2deX2c6rZuvDXM5MRyfsHqmmT4hBFqqHKq8U5/eWYJ9qkREc1G9yw6fNoitIsvQr2AkxkxfiWNIXwCpPX2lmxmaqYQQmF9djhvXteDua5an7KDLJDnoSzcRiuJov6/kg750DW571kzfmNZj53FYgSVXATIKvPq/QNPa1HUNuprFapCLlKr3z9eXd6bPrQV9U5ngOeTP0tNntqqvbRT0DR0Hwv68A9LpVOmwYkm9Ezs6huPrR7INJspXs8eBrtGk8k6+8RMRlQR9EFuuEs9AOAo7qzxKGoO+Akgu74Tgf6jZoM5lQ62zzHCYy4GeMcQksLK50uCepStX0KcvS68st6YOPFl0qfEdapYAwVFgvB/w9QCQQOXUyjunMsFz2B9CmdmE8kxZLE+rcdDX+5r6OAOCPkCVeO7oGIkvVD/TTB+ggr5TwxPc00dEVGLqXeo9oi9He0YwEoPNyrCglPGnWwDSlJTl4P6TWUEIoYa59EwO+vbMgSEuRhrcNvRkedMY0TJpHkcZYDID538QaN4AXPwJ4zvUL1cfu3Ymgq0pDHIBppbpGxkPo6rCmnkHkacVGDHo6TvyJFDmAupX5v21ptOG1iqMToTxwpEBAEDjGfb0AWqYy7A/HO97ZHknEVFpiK9cypnpi7Gfu8Qx6CsAf6Pa7RXjjr5ZZUWTG4d6fQhHYymX7+saRaXDinlVZ/7L9mzSUGlH31gQUhpPzBxJzvQBwLX/BrzvaTW0xcj8zYDFARx5Ajj5srqsaV1exxLP9AXzz/QN+UPGQ1x0VQtVX2Hyrr5oGNj/GLD8OsAyM0qz9SXtf9jXe8aL2XX6BM+jA+MAwGZ+IqISkXemLxxlpq/E8adbADFbJQ6/5Rm8fv3DxT4UmoKVTW6EIjEc6x9PuXxv1xhWNrkzZ4xKVIPLjlA0hmG/caA1pgd9jjwz21a7Kv089DvgyNMqk1ZRm9exxAe5TEwh0+cPGQ9x0bVuBiCBE39OXHbgMbWUffWb8v46062t1olKhxWjE+GzUtoJJHb1He3zwW41zbnnNhFRqXI7LLBZTDl7+sZDEZSztL+kMegrEGktR8SZX78SzQwrDIa5hKMxHOjxYnXL3CrtBHKvbYhPxzRYcZHRxnep0s4TzwMLL8n7btXlZXBYzegY8ud9n2F/2HiIi27++YDZBhx7JnHZi98CqtuAxW/M++tMN5NJYH2ryvadjdJOAPHdlUf7feznIyIqIUII1LttWTN9gXAUvWNBzKvKUJlDJYFBH1EGbXUVKLOYsC8p6Dva70MoEsOqOTbEBUjqC8jwxqEPcnFPJehbdi1w5efUOoTL7s77biaTQHt9BQ73+fK+z/B4CJ5s5Z1WBzB/E9Dxovrc1w90vgKsu73o+/nSbWitAgA0n6VMX6PbDpMAwlHJoI+IqMTUu+xZVy7pJ1AX1jLoK2Xc00eUgdVswtIGZ0qmb++puTnEBUj0BWQK+ryBMBxWM6zmKQZIF3/8tI5nSb0LLx8bzOu2UkqMTIRRlWunX8MqYMeDQCwGnHhBXbbostM6vumkB32NZynos5hNaHTb0TUagJ1DXIiISkqD24aDPd6M17+u9XMvrKko1CFREcys09dEM8zKJjf2dY3Fh5fs7RqD3WpCW52zyEdWePXxTJ/x2UJvIBLvtSuExfVOdI0G4Avm7usbC0QQjcnsg1wAoG45EB4HRk8Cx58FrBVAc37DZQppwwIPVre4cf6imrP2mHpfHzN9RESlpd6lBrFlcmJQy/Qx6CtpDPqIsljR5MbgeAj9WgP03q5RLG90w2yae4MubBYzqivKMq5t8AYjcBYw6GurVW9O+hnKbPRVBDmDvvoV6uOh3wE7f6Smdhotli+y8jILHvvIJbig/ewHfXYGfUREJaXebYM3GIE/ZHyS9ECPF55ya2L6NpUkBn1EWejDXPZ1jyEWk9jXNTYnSzt1DW57xmZwlekr3BuG3p83lseC9mFth2BVRY7jq9N2Bz5+N2CyAG/8whkd42yytEFlr9e0zL1+VSKiUpZY2zA527fz5Ah+8Wonrl3dWOjDogJjTx9RFslB36LaCniDkTk5xEWXbUG7NxCGu4CZvqksaNcni+bM9Dk8wDm3Abt/CrzhH/JeFl8K3ntJG25Y24LWGjbyExGVEn0QW583iIW1iRLOQDiKTz68Ew1uOz5z3YpiHR4VCIM+oiwqHVa0eBzY3+2N17rP6Uyfy469XWOG1/kCETS6z85gkXzoQZ8vj6BvKN/yTgC4+TvAhR9RQ13mELvVzICPiKgEZRrEdu8Th3C0fxw/fPcmuAtYqUPFwaCPKIeVzW7s6xpFa7UDZpPAskZXsQ+paBoq7RjwBRGJxmBJm9JZ6EEueimpdyrlnfkEfUIAjavP6NiIiIhmiuRMny4Wk3jwpRO4cV0zLl1aV6xDowJiTx9RDiua3Dg+MI7tJ4axuM45pwddNLhtkBLo903uC/AGwnDaCnem0GnTMn15TO8c8YdhNomCBqVEREQzQaXDijKLKaUnv2csAH8oivMWVhfxyKiQGPQR5bCyyYWYBF4+PjSnSzsBoKZCnS0cHk/NrkVjEuOhaEGDqjKLCTaLKa+eviF/CB6HFaY5OHWViIjmNiEE6l22lEzfcW3ydVst1zTMFQz6iHJY2aQGt0gJrJrjkw3jfXRp2TX980Jn0lx2C8byGuQSgoejqImIaI6qd9lSevqO6UHfHNw7PFcx6CPKYV6VI15KONczfYmSytRMX/GCPmte5Z3D42FUV+TRz0dERFSC6l321Exf/zgcVnO8349KH4M+ohxMJoEVTWp4y8q5HvRlWJOgD1Mp5J4+9fUseQ9y8eQzxIWIiKgENbhTM33HB3xYVFsBIdj2MFcw6CPKwxUrGnDx4to5P9LYlWF4ih4E6pnAQnHaLHmtbBj2h1DF8k4iIpqj5lWVwxuIoM+rAr9jA+NYVMd+vrmEQR9RHj54WTv+973nF/swii5Tpk8PvIrR05drkIuUEsP+MKpY3klERHPUxoVVAICtx4cRisRwcsjPIS5zTFGCPiHEW4QQe4UQMSHExrTrPiOEOCKEOCiEuLoYx0dExhxWM0xi8kL0sSKVdzptuXv6JsJRhCKx/Hb0ERERlaDVLZUoLzPjleOD6BjyIyaBNmb65pRiZfr2ALgFwLPJFwohVgK4DcAqANcA+JYQYu4uRSOaYYQQqqQyQ3lncaZ3Zu/pGxrXF7OzvJOIiOYmq9mEcxdU4eXjQ/F1DYtqOblzLilK0Cel3C+lPGhw1Y0AfiqlDEopjwM4AmBTYY+OiLJx2a2TyzuLuLLBF4xASpnxNiN+FRQy00dERHPZpoXVONDjxY6OYQDAohpm+uaSmdbT1wLgZNLnndplkwgh3i+E2CaE2Nbf31+QgyMibXhK2soGbyAMs0nAYS1sYt5lt0BKYDwUzXibYb+W6WNPHxERzWHnt9UAAB7Z3omaijJUsgJmTpm2oE8I8aQQYo/BnxvPxuNLKe+XUm6UUm6sq6s7Gw9JRHlw2ieXd/oCEThtloKPftZ7CLOtbWB5JxEREXDOvEqUWUzo8waxiENc5pxpq8WSUl55Gnc7BWB+0ufztMuIaIZw2iwY0bJnOm8gUvDSTv1YAG2wTKXxbVjeSUREBNitZqyf78HLx4cY9M1BM62889cAbhNC2IQQiwAsAfBKkY+JiJI47RZ4g+nTOyMF39EHJHoIx7KsbdDLOysdzPQREdHcdv6iagBAWx2HuMw1xVrZcLMQohPABQD+TwjxewCQUu4F8DCAfQB+B+DDUsrMzTpEVHAug4XovmC4KIvr9aAv29qG4fEQ3HYLLOaZdo6LiIiosC5orwUALKln0DfXFP7UPAAp5S8A/CLDdfcAuKewR0RE+cq0sqHRbS/4seTT0zfsD6OaQ1yIiIiwua0aP3nf5njGj+YOnvomoilx2i3wh6KIxhJrEryBCJzF7unLYNgfgof9fERERBBC4IL2GphMhR28RsXHoI+IpiQeaCVl+3zB4gxy0b9m+t7AZMP+ECd3EhER0ZzGoI+IpiS9j05KCW8gDKet8IFVRZkFQmDSYJlkw+Nh7ugjIiKiOY1BHxFNiR7c6SWVwUgM4agsSqbPZBJwllnQOexPKTdNNuIPcV0DERERzWkM+ohoSpzxTJ8anqKXVrqLEPQBQCASxaM7TuE7zxyddF0wEsV4KMryTiIiIprTGPQR0ZToPX16sKdPzizGIBcACEdVhm/7ieFJ18UXs7O8k4iIiOYwBn1ENCXpPX36R1cRevoA4MZ1zQAAj0E2T1/MzvJOIiIimsuKc2qeiGat9DUJesavWJm++25bjyN9vnhWL9nQuAr6jAJCIiIiormCmT4impL0NQl6eWcxBrnoqsrL4lm9ZHogyOXsRERENJcx6COiKako04K+YGqmz20vXjbNU241zPSxvJOIiIiIQR8RTZHJJOC0WSaXd9pmXqZvmOWdRERERAz6iGjqnDZLfGWDPsilWD19AFBVbsXoRHjSrr5hfxgVZWbYLOYiHRkRERFR8THoI6Ipc9ot8WDPGwjDbjXBai7ey4mnvAxSAmMTqSWew/4QPCztJCIiojmOQR8RTZnTZkka5BKBq4j9fABQVaG+fnqJ5/B4KH4dERER0VzFoI+IpsyVnOkLRoo6uRNAPJs3KejzhznEhYiIiOY8Bn1ENGXpg1xcRRziAiSmcw6Pp5Z3jvhDDPqIiIhozmPQR0RTpga5qKBvwBtEZZEDq+oMmb6h8RB39BEREdGcx6CPiKbMaVeZvolQFId6vVjT4i7q8Xi0vr3kXX2BcBRjgQjqXLZiHRYRERHRjMCgj4imzGWzwBeKYOfJEURiEhtaq4p+PBaTSMn09Y0FAQD1DPqIiIhojmPQR0RT5rRbICXw/JF+AMD6Igd9Qgh4yq0YTsr09XkDAIAGt71Yh0VEREQ0IzDoI6Ipc9pUOeWzhwbQVlsxI/rmPOVlGEnK9PXqmT43M31EREQ0tzHoI6Ipc2orGl47NVr0LJ+uqtyaWt6pZfrqXcz0ERER0dzGoI+Ipix5RcO5C2ZG0KcyfYnyzt6xIKxmgapyLmcnIiKiuY1BHxFNmTNpGfuGBZ4iHkmCUaav3mWHEKKIR0VERERUfAz6iGjKnFqmz2mzYEm9q8hHo1SVl2HYH4aUEoCa3sl+PiIiIiIGfUR0GvSgb32rB2bTzMikNVXaEYrE0O9TA1xUpo9BHxERERGDPiKasspyK4RA0ffzJWuvdwIAjvT5AKiePq5rICIiIgIsuW9CRJTKbbfif961CRtaZ0Y/HwAs1oK+o/3j2NBahdGJMDN9RERERGDQR0Sn6bKldcU+hBSNbjsqysw42udDv1ff0cdMHxERERHLO4moJAgh0F7vxNF+X9KOPmb6iIiIiBj0EVHJaK9z4mifD71jKtPHnj4iIiIiBn1EVEIW1zvRNRrA8YFxAMz0EREREQEM+oiohLTXVQAAXjo2CKtZoKq8rMhHRERERFR8RQn6hBBvEULsFULEhBAbky5fKISYEELs1P58pxjHR0Szkz7Bc+vrQ6hz2mCaITsEiYiIiIqpWNM79wC4BcB3Da47KqUthaQBAAAHB0lEQVRcV+DjIaIS0FpdAbNJIBCOoY79fEREREQAipTpk1Lul1IeLMbXJqLSVWYxYUFNOQCggf18RERERABmZk/fIiHEq0KIZ4QQlxT7YIhodmmvUyWe9W4GfURERETANAZ9QognhRB7DP7cmOVu3QBapZTrAXwCwI+FEO4Mj/9+IcQ2IcS2/v7+6fgWiGgW0vv6Glws7yQiIiICprGnT0p55WncJwggqP19uxDiKIClALYZ3PZ+APcDwMaNG+WZHS0RlQpm+oiIiIhSzajyTiFEnRDCrP29DcASAMeKe1RENJucM68SQgCL613FPhQiIiKiGaEo0zuFEDcD+E8AdQD+TwixU0p5NYBLAXxBCBEGEAPwQSnlUDGOkYhmp6UNLrzyd1eijoNciIiIiAAUKeiTUv4CwC8MLn8EwCOFPyIiKiUM+IiIiIgSZlR5JxEREREREZ1dDPqIiIiIiIhKGIM+IiIiIiKiEsagj4iIiIiIqIQx6CMiIiIiIiphDPqIiIiIiIhKGIM+IiIiIiKiEsagj4iIiIiIqIQx6CMiIiIiIiphDPqIiIiIiIhKmJBSFvsYzpgQoh/AiWIfh4FaAAPFPggqaXyO0XTi84umE59fNN34HKPpNBOfXwuklHVGV5RE0DdTCSG2SSk3Fvs4qHTxOUbTic8vmk58ftF043OMptNse36xvJOIiIiIiKiEMegjIiIiIiIqYQz6ptf9xT4AKnl8jtF04vOLphOfXzTd+Byj6TSrnl/s6SMiIiIiIiphzPQRERERERGVMAZ900QIcY0Q4qAQ4ogQ4tPFPh6afYQQ84UQfxRC7BNC7BVC/I12ebUQ4gkhxGHtY5V2uRBCfF17zu0WQmwo7ndAs4EQwiyEeFUI8Zj2+SIhxMva8+ghIUSZdrlN+/yIdv3CYh43zQ5CCI8Q4udCiANCiP1CiAv4GkZnixDi49r74x4hxE+EEHa+htGZEEI8IIToE0LsSbpsyq9ZQog7tNsfFkLcUYzvJR2DvmkghDAD+CaAawGsBPA2IcTK4h4VzUIRAJ+UUq4EsBnAh7Xn0acBPCWlXALgKe1zQD3flmh/3g/g24U/ZJqF/gbA/qTP/w3AvVLKxQCGAbxHu/w9AIa1y+/VbkeUy30AfielXA5gLdRzja9hdMaEEC0APgpgo5RyNQAzgNvA1zA6M/8D4Jq0y6b0miWEqAbwWQDnA9gE4LN6oFhMDPqmxyYAR6SUx6SUIQA/BXBjkY+JZhkpZbeUcof2dy/UL0stUM+lH2g3+wGAm7S/3wjgh1J5CYBHCNFU4MOmWUQIMQ/AXwD4b+1zAeANAH6u3ST9+aU/734O4Art9kSGhBCVAC4F8D0AkFKGpJQj4GsYnT0WAA4hhAVAOYBu8DWMzoCU8lkAQ2kXT/U162oAT0gph6SUwwCewORAsuAY9E2PFgAnkz7v1C4jOi1aGcp6AC8DaJBSdmtX9QBo0P7O5x1N1dcA3A0gpn1eA2BEShnRPk9+DsWfX9r1o9rtiTJZBKAfwPe1EuL/FkJUgK9hdBZIKU8B+DKADqhgbxTAdvA1jM6+qb5mzcjXMgZ9RDOcEMIJ4BEAH5NSjiVfJ9X4XY7gpSkTQlwPoE9Kub3Yx0IlywJgA4BvSynXAxhHoiwKAF/D6PRp5XI3Qp1caAZQgRmQTaHSNptfsxj0TY9TAOYnfT5Pu4xoSoQQVqiA70dSyke1i3v1kiftY592OZ93NBUXAbhBCPE6VAn6G6D6rzxaqRSQ+hyKP7+06ysBDBbygGnW6QTQKaV8Wfv851BBIF/D6Gy4EsBxKWW/lDIM4FGo1zW+htHZNtXXrBn5Wsagb3psBbBEmyBVBtVY/OsiHxPNMlqvwfcA7JdSfjXpql8D0CdB3QHgV0mXv1ObJrUZwGhSOQJRCinlZ6SU86SUC6Feo56WUt4O4I8A3qzdLP35pT/v3qzdflae7aTCkFL2ADgphFimXXQFgH3gaxidHR0ANgshyrX3S/35xdcwOtum+pr1ewBXCSGqtIz0VdplRcXl7NNECHEdVL+MGcADUsp7inxINMsIIS4G8ByA15Doufo7qL6+hwG0AjgB4K1SyiHtTe8bUOUtfgDvklJuK/iB06wjhNgC4P9JKa8XQrRBZf6qAbwK4O1SyqAQwg7gQaje0iEAt0kpjxXrmGl2EEKsgxoUVAbgGIB3QZ1w5msYnTEhxOcB3Ao17fpVAO+F6p3iaxidFiHETwBsAVALoBdqCucvMcXXLCHEu6F+ZwOAe6SU3y/k92GEQR8REREREVEJY3knERERERFRCWPQR0REREREVMIY9BEREREREZUwBn1EREREREQljEEfERERERFRCWPQR0REREREVMIY9BEREREREZUwBn1EREREREQl7P8D0+rYNNS9q/0AAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69f54a59b0>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69e014c7b8>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69e00a7c88>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -2833,32 +2874,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f69f54d37f0>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 77,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69dbd9c588>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "df['Odense']['Temp'][200000:200000+1000].plot()"
+    "df['Odense']['Temp'][200000:200000+1000].plot();"
    ]
   },
   {
@@ -2872,33 +2905,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f69db165860>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 78,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69db106860>"
-      ]
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "df_org = weather.load_original_data()\n",
-    "df_org.xs('Odense')['Temp']['2002-12-23':'2003-02-04'].plot()"
+    "df_org.xs('Odense')['Temp']['2002-12-23':'2003-02-04'].plot();"
    ]
   },
   {
@@ -2918,39 +2943,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 80,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69fc054198>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69db1866d8>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": 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\n",
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UCgOwLhOL72ANI22ilAoG4oGGTneHW9tK0FpP0lp30Vp3CQkJqfyWVwabrVgmUArDCCGEEEIIIVzL1UHgr4C9wucYYBaAUqqZUkpZ1zsBNYBkYD4wVCkVYBWEGWptuziVmBNoFYaRIFAIIYQQQgjhIh5VdWCl1PfAACBYKRWHqfI5AZimlBoLHAZutnYfCdyllMoDsoBbrOGiKUqpV4H11n6vaK2LF5u5aJRcLF4KwwghhBBCCCFcq8qCQK316DLuGlTKvm8Cb5ZxnMnA5EpsWvUpsVi8ZAKFEEIIIYQQrlVthWEuR6pYdVDtJplAIYQQQgghhGtJEOhKJTKB9uqgkgkUQgghhBBCuIYEga6iNQpdNBNof/u1LuNBQgghhBBCCFG5JAh0FZs15LOUTKAMBxVCCCGEEEK4igSBrmLLBxwLxJvrUhhGCCGEEEII4VoSBLqKPdtX6mLxkgkUQgghhBBCuIYEga5iDQd1nhOImxSGEUIIIYQQQriWBIGuokvOCSwMCCUIFEIIIYQQQriIBIGuYrMCvVKGgyoZDnpu0hNh1iOQmVLdLRFCCCGEEOKiI0Ggq1iBXuEC8Ugm8LxNvRk2fwMxi6u7JUIIUTkK8mDHz7Bhsiwb5AondsHphOpuhRBCVBuP6m7AZUOWiKgcyTFwbLO5nnWqetsihBCVIT8XPh8IJ7ab2xF9Ibh59bbpUrZzJkwfA02ugLtmVndrhBCiWkgm0FV0ycIwWklhmHO27nNH8Jx+onrbUhXycyEtrrpbIYS4ADabZuneRNIy80g8k82zv2xn/4kzZT9g968mAOz3T3N73zzXNPRytXeOuYzf5Nh26jDMuF86F4UQlw3JBLpKqZlAGQ56zvbPhxbDIH4jnDle3a2pXJkp8GkvE9zeNh0a9YAaNau7VUKIMuQX2Ph+3RFWxSTTKNCX46ez2RGfRkxSBgC+Xu74eLqTnJHLqgMn+XB0R9qF1yl5oA2TIbAJDHgW9syBffOh16MufjWXkaxUc5mTBhnJ4BsIn3SH/CxofSO0HFa97RNCCBeQTKCrnDUTKMNBKyQrFVIOQoNOUDPUFIipauu/hMlXQcqhqn+uo+vgTILpFPhuJMx7uuqfUwhxXmw2zUPfbeKFWTvZFpfG58sPsnz/SYJr1qBfixAeG9Scq9uG0SUigJevjeZ0dj63TlpD4pnsogdKT4LDq6DtzWbZoBZXmtv2QEVUvmyn9/bEdji2yQSAcGmOMBFCiFJIEOgqkgm8cAlbzWX9juBfD9KrOBOYlw3zn4Mjq+BXF/TKn9hhLkdMNJf7F1b9c16sbAWu6QQQogwzt8SzcNcJnru6FSufHsimF4aw9tlB/NhyGV97vM7jLU/xNu/zP9/PuLtXBD8/1IvcfBv/nbe36IF2zQQ0RA03t1sMM52GMYvM7aVvwqJXISfdpa+vwpL2wob/q+5WnJusVGjU01xP3AO7Zjnuu9RGmAghRBkkCHSV0haLlzmB5yZhi7kM62gygWequMd27++md7hhD4hdUfXPd2IH1GkMHW+Hwf82QW5GctU+58XIZjPDZt9u7lh6RQgXKrBp3vtjH20b1GZsn0gA6vh64enuBqs+goNLYfJQ2DkDtk+HQ38SGezHA/2b8NPGOBbusr5LEnfDwhehQReo19ZsC+8CPoFmSGjcRlj6H1j+Nix8oXpebHnWTYLZf4eEbdXdktLl58KcfxYN7rJOQVBTQEFmMsQsgch+4BtkRmMIIcRlQIJAVylcLL7kcNDCLKE4u2NboHYj8AsymcCMxKp97w4sAu86cM27gDZBYVU6sRNC25jrDTqby/iNVfucF6MdP0HSHnM9J6162yJcLy0eZj8Ou36ttiYs2HmcoylZPHxFU9zclOOO1KOQewba3Wrm+I38EnyDYfO3ADw2qAXRYbV4+udtJJ/JglkPg6cv3DoVlHUcN3doPhT2L4DFr5rvoI53mmxb0r5qeLXlSD1iLtd8Wr3tKMvBpSZQnfuUua21GQ7qGwQ+AZCVAqmHIbgl+IdJJlAIcdmQINBVCjOBJYeDXk6ZwOy8AnYnnOZwcgYZOfn8sesEE5ceYNHuE3yx/CA74s9yUn9sM9Rvb67XamCG0Z4+VjUN1dr0DjcZAHWjTc/8sS1V81z25zt1GIKamNv1O5pMcfwGc9tmM3MGL/f1w07uhz/fdNyWTOnlRWuY+ZAppPLzWCjIr9Kn+2pVLE9M20JuftHv6C9XHKJhoA9DousVfcCRNeay5zgYvxna3mQKPFnL2nh5uPHeLR04nZ3HN9OmmU6ewS+Bf2jR47QcZrJVB5eYiqGDXgR3T1jxLiz5D/x4J0wb43i+6pR61Fzu+An2/wGLXin5PbX1R3i5dvXMc7RZnxF7cJeXBQW5Jrj2DYRTsZCdBnUams5FyQQKIS4TUh3UVXRpcwLtPciXRxCYmZvPiI9Xsj/RzG2p5e3B6eyiJ3E1PNyYel8POjcOKPrgrFNw6hB0utPcDogwl6mHzY93ZUs9DGeOmSFCSkFoa5OpqyrZqVCQAzWtk8oaNSGklSMTuPI9c3I1/B3o+reqa8df3fR7IPkAdH8I1n5qhnLRrLpbJaqC1ub/1y/Yse34Njj0J9RtDYk7Ie0oBEZWydOfyc7jrfl7Sc/JZ96O4zQK9KVpSE26Nwlkw+FTvHRtNO7OWcA9c2DVB+AXYtpnV78j7JltAiCfOrSs588jVzQnZOkk8r198WgzsuSTtxhm/s4L8qDb/eDhBR1ug41TzP3BLcxSMkfWwGNbwNOnSt6DcmltMoHNrzSVm7+zXkuv8eDjVAV1wXPmMvVI0e2ukJFkLrOtDkZ7URifgKKde3UamSCwKr/nhRDiL0Qyga5in7vkPCcQa47gZZAJ3H/iDEPfW8aBpHReGdGaMT0bU7OGB1+O6cLaZwfx7djuLPpHfwL9vHj5153YbMV6ku0/1GEdzGVAY3N5KrZqGpy421za5+mEtobEXVU3B81e5MTfKbMQ3tkEgQV5sHaS2Tb/Odj09dmPdWKXGcp6qclKNZX8BjwD7W8x2zJPVm+bRKXIK7CVyLax/B14q2nRubj75gMK+ltD+zZ/U6nrui3bl8TDUzeRk1/AMzO2k56Tz40dG5CZW8DJ9Fzm7TzOi7N2Eh1Wi5s7hsLH3cwwzfhN8MNoOL4d2t0C7k79q/U7mkt7YSvgof5NuMpzM4ttHUkr8CrZEE8f0+Fz3YcmAAS46i248g2zfMwj6+G2aWbe8Japlfb6z1lmCuRlQNMrIKy9Y3vxCpv2QCzzpOtHM2RY3632LKT90sfKBNq/Q+o0MsNB00+Y71whhLjESSbQVXQpw0Gt25f6EhG5+TbGfbeJ7DwbX93TjX4tQgB4+brWKCsbGlrLG4DHh7TgqZ+2seZgMr2aOWUAjqw2WdTwLuZ27Ybm9qnDVdNo+5yz4BbmMrQ15GWabGRQ08p/PvtJU826jm0NupiAb/dv5mRv6Ouw7n+w+hPodFfZx/rUqnr3UqpTtvkScMxa2LlhdzOfB6xMoLhYxadm8dwv29l0+BSBfl58M7Y7DQN9zZ3rPjeXx7eB/xBzfd88s0RMox7m9vJ3zHDEkZ9fcFtSM3N5YtpWTqbn4K4Us7cl8M8rWzJuQFNu7daItg1qE5ucwcGkDAa0DMEveQec3GuKooRanUVNBkD3B4se2B4EHtsMTfpDzGK8sk/jpVNZmNuGxXN2M2Fku/Ib6OFlhpnaRfY189h2/gJdx17w66+o09l5/Lb1GLn5Njp5xtIezPdx/Y6OQDf9BIS0NNfzshwP/uYGaH0DjJrisvaSnuRoU16Wo9PAu47jewTMfPOACNMpm3bUzOkUQohLmGQCXcVewMSt2Fuu3C75TOC3aw6zPzGdN0e2LQwAgcIA0Nl17evjX8ODnzfFF73j8CqTlfOubW67e5of8GX/hUPLK7/RiXvAv75j6FKwdUKTfKDynwsc2Y6aTpnAelaRGHvmr9W10H40nNwHuZnlHzPtaOW2sbrFbQSUCQJ8rQ6CDMkEXsz+M2c3S/cmYdOQnJHL0zO2sf/EGVYdSELbh+8dt6pOpieajFuLYaY6sF1G5SwV8urs3aRm5gLw69ZjdIsIZNyApiil6BYZiI+XO63CajG8XRh+NTwc7QKTob7uI7hrVsnh6b6Bpurvsc0mSPrmBpg+BoDGXa/mh/VH2RCbcn6Njh4Bh1c6Ap0qduJ0Njd/tprnftnBv3/bxa+zpgPwxgYbtpbXOnZ0zt4mxxQ9yM5fHAVu9i1wjLqoJFprtHO2sfDzoU2HQbZTJtDHmnbg6WeGHQdYQ4tTDlZqm4QQ4q9IgkBXKWWxeACUO+oSLnOflpnHh4v307d5MAOj6pa7v7enO9d2qM9v244Rn2r1IOdlQ9x6aNyn6M616pvLb28082MqU9IeR082OHqFy1s0PmkvrP/CVKTDDHOz2YqdlJQiId5kNP+3KZ3sPKvDICQKUKY4hF+IGa5Ur53pNKjIvJUdM6q8cIZLxa03/yfetcHLFzx8JBN4Edt/4gy/b0vg0YHN2PziEJ4Y0oKVB5IZ8t4ynvnyV5R98e7j200HwNvNAW0WUy/SgXTh2e6lexP5eVMcD/ZvyshO4TSo48Nbo9qV2lFVKGEbePnDA8vghkmmgmdZ6nc0QaB96GaXe6HLWMZe3Ze6/jV4c96ecr8jShV1tfk+iFl87o+tIJtNk1dgI6/Axh1frOVoSiZz+x3hQMPXecHzOw75ted/O935LbOVKYYDRddwzSglQN0+3QyjnToKJvaAvfPOu30n03PYeDiFxDPZPPbDZnq+sZg7v1zneD/TkxzTMFKPOEaP+IeZAB0grJ35TFX0e14IIS4BMhzUVbQNjSpaGAZreOglPBz0f8tiSMvK45mrWp39hMrJw1c046eNcby/cB9vjWoPh1dAfrYZauXspv8zgcEvD8DeudDtvspreNpRxzAuML3EXv5n7yFeOwnm/rPw5v9CnmdCXDThAT5k5BTQKsyft25qT/06RYs4fLH8IPkrN3OPuydvLDnG3jQ33hzZDk8vP6tk+TEI72ZOUsKsYWNfDobHtjoK5Ng5n0j+8ZLJmHQYfZ5vQtXIL7Cx+mAyAb5mrlNCWjbZeQVE169F05CapT9Ia/N/HXW1Y5tfcMkgMGYx/PEy3P071PCvmhcgKsWXKw5Rw8ONe3pH4unuxp09GnMmO59tcan0yt4LCZDh2xC/uI2w6kPzoKBmpiME4B974aexpgMoPwc8apxXO9Jz8nnulx00DfHj0UHN8HBzw02VPlKhiIQtJlsf1r7ofLjS1O9oFoVf+xm0HQXXvAeAD/DooOa8MHMHS/cmcUUFOsqKqNfeZLMO/emYJ1uJdh5LY9x3m4g/lUWjQF8Onszg87u60Grr15C0E+q1o/HQ12nzO7w6exc9H+1DXQ+fossslNZRE7PYzOeu29oEsbMfN9+5TQee03D7+NQsRn26imNp2UW2Hz+dzc+b4rmpc7jJBDboDHHrTMGvI6sdRWDswWFIlLn0r2c6lyQIFEJcBiQT6CqR/dh/2zqy6nYqul25X7JLRGTk5PPtmsNc1aYe0fVrVfhxDer4cGvXhszacozEM9lmyJCHt5kD4yyoqSnC4BdiholVloI8c+LiXKRFKVOF8FTpJwdJa36Auf9kg3dPBuW+xXpbC+5Lep0Pm2wgK7eA7LwCNh1OZfiHy+k9YTFP/LiFpDM5vPzrTt6Yu4f2dbLxrBPG+IHNmbEpnus/WUlWboEpZQ7Q/QFzWbuhIxi2ys4XUbxIhlMxiuqy78QZXvltF+8t3Mfgd/+k2XNzufPLdVzz0QpGfrSYb7/9kvHfb+TqD5bz574yhrWdOmTW82rQxbHNN7BklmHdF+Y1r3jPFK0Qf0kxSen8tDGOW7o2JNDPdAZ4uLsxflBzvhjTlbsj08jHg3fTh0DaERNAdX+Q+NsWk5xh/U341zPBV/J+eK3ueWe935y7h2NpWfz3pvbU8HDH3U2VHwDmZZliVQ27VexJOt4JLa+GZkPg6reL3HVLl4Y0CvTlv/P3liyIVR43N1PB+ODSSi+48s2awwz/cAXp2fl0jQjk4MkMRnYKZ3CruubvseXV8OBy3Jr05QuziyoAACAASURBVN2bO5Cek8+tX6ylwK+uWbpn2zQTnBcfst12lFn6JvMk9PsH9H3CdHTNeRK+HHJObXxjzm5SMnO5rr0ZFTJuQFMOvH4VnRsH8NRPW9l65BScTjCfEzdPkwk8sgYa9TIHsE8vaDrQXNq/5+M3Qm6GWfIicc+FvI1CCPGXJZnAamYKxVyaQeDXqw9zOjufsX0qOMFea/MjrDX39GrM16sP88fKtdy29QfzI11aGXSloH4nR9GQymCv1Fmz2NpdgZGlDsOct+gP+i97lI26BS94PslV/RtSs9UI9PLHuHb/uwwdHonqeAeHTmbw7sK9xJ3K4tetx5ix2cx7vLVrQ7qmZeGmw3h8SAsiQ/x4/MetPP7jFt4f8Rne8WtNQQn76x01Bd6MKH2NRPsaV6OmwJ9vlRm0usqhkxmMnLiKjNx8bBrah9ema0QAzer6066BP9f+OZyamXEcHfQx92+KYPz3m5nzWF8aFMuW2ofX0rC7Y1tYe3OiefqYGRqcnQYH/jD3LX/HzN+8uZxKqqJavDl3D96e7owf1NxsOLTcfLYjzJBvtxPbyQ+OYnZCD15wmwxATpf7GfbRGs5k5/P+LR1Iy8pjTO1wx0FTD59TFinxTDajJ60hJimDe3pHlFyW5mziNoAtDxr3rtj+fkEw+vtS7/LycOOJIS34+49bmL09oTCgqbDGvWHXLDgdD87vxwU4kHiGV3/bRf8WIbx3SwcCfD1JzsgluGYNUyE55ZAjcAJahPoz5Z5u3P7FWuICatF45wzYOQOdcZId+w/SRrk5Ojv7PG6Gg4IJip0Lx2Qmm+rGodHltnHzkVPM3pbA+IHNeGJoS/59XWtq+3ji5qb4v3u60uW1P1iybiPtc8+Y49UON98jGYmOwkKd7oLg5oWfO8AEqYv+Df+x/h+UO9w0GVpffwHvqBBC/PVUWSZQKTVZKZWolNrhtC1QKbVQKbXfugywtt+ulNqmlNqulFqllGrv9JhhSqm9SqkDSqmnq6q91cYKei41W4+mMnHJAQZF1a3YydWcp+A/DWDKNfBGOJFTOvHv2rMZtP4B8x4Ne6PsxzboZObiVdbC8YWVOosFgQGRZj6JNYfzTHYeoz5bReySKXgoTcNxM5j7j8E8eWVLWjUKxf3WbyGyPzXm/B2vjZ/TUh3lf4E/8HvPvcx8uDcPDWjKF3d1YcLIdnicjoPaDVFKcUPHcF68Jpp5O4/T7pt82i3ryhM/bnHMFfSuA56+kFaseA44gkD/MHNCXFWFbIpJTs/huNOQrIycfJ79ZTtXvreMLmoXO1p9zdYrDzBzXE+mP9iLN25sy+hGadTMNHM5G55cxae3daTApnl06iaTBXW25XuzbmLdVo5tfZ80Wdv1X5rbS980mdOu1rDgo+ur8iWL83DoZAbP/bKdBbtO8NCApiaoOL4DvroGpgx3LMFyfDte4e156OpuvG27nfvzHmfkD8c4Y60r+vcft/DSrztJy3P6CUvaS+zJjAq1Q2vNUz9t43ByJuMHNuOpK6NK7rRvAXzSA3bOLHlf7HJAFe2UuADXta9PVD1/3l2wl7yCc+wUtGfH4zZUSlsA3pizhxoebrx7c3sC/bxQSpn/KzDfMflZJapn9mgSxO3dG/Fuan9sbp4AqPnPUOfATFJ1TQoirI6s0NYwbg3c8TN41wL/Yt+z++eX2778Ahv//m0XwTVrcH9/E/gH+HnhZq3bWMvbk77Ngjm+1/oOqNfODAFNsJYaamRVUHZzLxoAgslMXvsBuHtBv6fM4+zrMwohxCWkKoeDTgGGFdv2NLBIa90cWGTdBjgE9NdatwVeBSYBKKXcgU+Aq4BoYLRSqvwuwovJJVYd9MTpbO77egPXT1xJLR9PXr6udfkPykk3633lZZiTK6+aENKSMTlTUflZZN86veTcN2ftbjY/2POfq5wXYQ8Ci5+c1Glkev+t+1//fTfrY08xtE4cKqwtdesVqwro7gG3fmeGb859yizdsP5z+P1J2oT68K9hUQyODjWVY0/HF6kqeG+fSH5+qBd39WjMkOh6zNgcz/Mzrf4UpaBWA/OY4k5bQWDNUNPDfSq2Ste8SsvM45/Tt9LjjUX0mrCIB77ZwLT1Rxn9+Rp+XH+UmzuH8YX3h/genEftP19ELfmP48EH/zSXjXrB1qlEzLuTCSPbsvloKg99t9Gx38kDZj5Ph9FFC4IENDZzrQ6vgkWvwppPoPPdMPxtGPi8GWJmrzApKo3WmoS0rPJ3dPLL5jh6T1jMFW8vZfqGOEZ3a8jYPlYlxj9ecuz4SoBZdD0jEeq14+7ekTz8/EfYWgxnR/xp+jYP5oF+juBjju4FrW8EIGvBK9zxzjSW7Cm/WugfuxNZujeJp6+K4omhLfHxKlawqyDP/M0m7TZLQDh31NlssPUHEzxU0sLnbm6Kf17ZktjkTKZvOMciV/XamO+/+MoJAnceS2PRnkQeHNCUoJqlzLO0z4suZQmFf17Zki11BjNIf8qf9e4GoKFbEkk2fyZHvAXPWd+tdVtBs8GOB/59Bzyx28wRjFly1vblF9h46dedbDmaygvXtKJmjdIHNF3XoT71svahcYO60Y41X6Fo0a/SdL4bnomDgc9B8yFwdK2sHSiEKBR7MoMRH6/gl82VXJTQxaosCNRaLwOKT8oZAXxlXf8KuN7ad5XW2j6ZaQ1gH9PSDTigtT6otc4FfrCOccnQuKG4+DOBZ7Lz+Hp1LKM+W82K/Sd59Ipm/PZoH8eaX2ezd65Zg+/2n81QoXvnwd2z2Xj9EvrkfMDCtHKGOAU2Mb23O2dUziLpZWUCa1tBWtpRjqdl89PGOO7p2ZAmufvxaNiFUtXwNz3ed8yA6z625gNpx/BGMEUUbPmO41s6Nw7g+Wuieefm9owfaIrlFH7h1KpfehB4cp85Iazd0BTRsOWbeTBVICEti1H/W8XMLfHc1q0RD/RvyrpDKTz18zb2nTjDpDs781rnLNyzU0wRn/a3wYp3HUUjDv1plt4YaAXvMYu5pmEe/xoWxdK9SWw5apVy3zrVdJa0K6XwRaMeptDD8rfN0K6r3zLbC9dm21Ilr/1yNn/nCXq+sZiVB0ouz6G1Ji2z6MnylqOpPDFtK7V9PPnHkBasePoK3rixHd6e7ibbduAP6PWo4wEzrXX2rJN2Hy93/ndnF+b9vS9f39uNB/s35fHBLWhQx4f5B7Nh1P+Z/VJ284rHFObvPM7ZrI9N4ZGpm2gZ6s/dNZbCyf0ldzq61gylbjLAzLN1HlYdu9wMPe18dznv1LkZaI2a+GDRvpKZ8LPxqGHeq0r4rOfkF/DW/L34erlzR/fGpe+UYi35UEoQ6O/tyTf3dscvsB5PHB/MQk8zZDTYM4cPl8aSlu9e4jGA6QCrVd+830fWlBlwpWTkMvS9ZXy39ggP9G/CiA4Nynwt17arT1efBI6qehR4+EAPa43F2g0rtn6qvdBQ497m96m0OdhCiMtOTn4Bj3y/ia1xaTz+41ZumLiSTUdOlf/AvyBXF4YJ1VpbqQqOA6Gl7DMWmGtdbwA4L3YWZ227dCh1UWcCs/MKeGPubnq9sZgXZ+3kVGYu797cnieGtiws+FCuI6ugRi0zx2Twy2buHdChXUeCavvz86YK9LT0/rsJemaOu/A1s+xrXPmZSn2ZuflmKGYdRxA4de1hCrTmvmgb5KabeYllUQqaDYJOd5pAxScAtjrND7Kv51enUZmHGD+oOd0iA3lh5k6SzuRYmcBShr8m7jaBlbuHo7BNeuWso+YsMzefO79cx7HUbL66pxv/HtGGfw2LYuPzQ1j4eD+WPDmAQa1CYe8cU5Ch2SDo+w/zWd/2I+Tnmgxek/4mozLeOoHdNYs7ejSmpXcKb81cS1ZOPmz/yXw2nAv12DXqAWhoOgiGv2fWjwRTDVC5WcP2iinIh33zISu10t+Xy8H+E2cA+H17Qon7nv1lB51fW8jBpHTAFAV6YeYOgvy8mPZgTx4d1Jy6/t5m57xsmH63CWD6PQWPbjJ///bsrVPmxt1NEVWvFkopAvy8eGxwc3o0CWLnsdMAnKrfD4AwlcLiPYllFlg5k53H+O83E1bbmx9ui8BjzuPwcRdYVrRYS2FA1Wu8uYxzykwfXApuHtDyqgq9XxWllOLpq6I4cTqHL1ec4zp1IVGlB7NncTQlk9s+X8N9X29g0DtLGfjOUnr8ZxFL9ybx1JUtqe3r6dj5dIL5mwWTCXT3KnP+YaMgX2Y/2peNL1/LkPvfBCCw4CRnsvP5cX05HVJh7aAgx4xgKE5rPly0n8MpmXx2RyeeuapVyX2cuLkp2vqmsD8/lD92n4DaDcw6jneWMrz3bOzzPmNXnNvjhDgXWptRUeIv7/0/9rMj/jSf3NaJV0a05nhaNn/7agMnTmeX/+C/mGqrDqrNIj5FfqmVUldggsB/nevxlFL3K6U2KKU2JCW5ZuHcSnERDwe12TT3TlnPpGUHGRBVl18f6c32l6/kqrZh53ag+I0mc+NW9OPo7qYY1TmcP/clMWHuHkZ8vIKrPljOx4tLOdnx9DbZpvTjsPH/LuBVYY7hE8ih1Dyen7mdTq8upNvrfzA71rTPduooP2+Kp0+zYOrnWwFq3VLmFJXGo4ZZ8H33b45gNdUKAotlAos8zN2NCTe2JTuvgPf/2GdOwM4kQPbpojsm7na0xS/EXJa2TtcF+njxAWKS0vnsjs70ahZcuN3NTdE81J+w2lZhl33zIKK3qcIX3MzMX9o50wxdy8uESGueUGCkWVA7YQs1a3gwn0d4KelxXv32d5N1aVF8ZLml+ZUwbILJBrk7DQvzCYCGZaw/tmYiTL0ZPutjhuKKc5KTb76v7AGY3frYFL5fd4R8m+btBXt5d+E+hr63jN0Jp3nt+rYlh+2dOmSGgPd6zMwNC2oKPR42nSGBTcy2s2gV5k/SmRymbzhKz0NjmZw/jFZuR2iRsYGd8aUPA564NIaEtGxT7CTdab7s4lchw2kpg2OboVa4+Xx6+prvKLvDqyCsA3j5lf9mnaOuEYEMbhXK58sPkZl7DtVOg5qZ763i3wdlyM23MWbyOlbFJLP2YDKRwTWJDqvFFVF1+e5v3bm7d6Rj55nj4N0o+G8T+P0f5vUHRJj5dOUJtgr/tBlJjyaBfLXq8NkroAZZ+5/cV3T7mk+xvR7GzRtG84/o0wxrU4HfGK3xzzpGimc9pq61gs8mA8z30LmoGWKC7HMNArV2zHEVVe/McZj5sFmn979NYNNFUBQsZgm8XBuS9sE3N8CERlKN9i8uLSuPr1bFMqJDfYa3C+OunhF8M7Y76dn5TFzimhoMlcnVQeAJpVQYgHVZmKJQSrUDvgBGaK3tv8bxgPOZcbi1rQSt9SStdRetdZeQkJAqaXxV0CjURVoYZtbWeFbFJPPqiDZ8NLoj7cLPY35MXpapuNmgc6l3j+3bhDo+nnz2ZwxubgqtNR8uOmCWjigurJ0p1LBr1rm3w0lG0hGOFgQw8J2lTFsfx7Xt6tOynj+PzDhAlntNFqzeQHxqllmDyj4/JiDy7Ad11uYmM7fwsHVSYe/1rlN2EAjQJKQmd/RozA/rj7LHv4fpPNg5w7FD9mk4HeconlJFQWC6tfTH1W3C6NM8uOwd9/9hTuZaOq3t13SgKc6wY4bpAHEuyhDU1Lyf1sl4C7d43A6a+UG2yCtKfw4PL+jxkKPUu7OWw+DE9qIZ0/xcM3QUTAY2cXdFXrJwctzq7dx6NJV5OxxDLz9fdpAAX0/u7hXBnO3H+XDRfvo2D2b2+D4Ma1NKFjfZGlboXNHTwwtG/wgjvyi3HfZlZ95duA8fH1+Cok2Hwrdeb5A/p2Q/4o/rj/Dp0hhu7NSAjo0CTBVKMJV0ARKchvslbIH6HUzHQkhLSLJOzPKyTSXixr3Kbd/5emhAE9Ky8hyBS0XYg60KFoL6enUsB09mMPnuLmx7+Uq+GNOFj2/rxLs3d6C3U6cOaXGw5TuIHgGtrjEn1nHrIbCCVViVMnPrbvgfo7s1Ij41izWHSlk3sPB1WAGacxC4ZSrMe5pYFU6ISuNvWRXs5Ms6hco9Q3DDFizfn8SBxHS01vyyOY4f1h0pMWzZLr/AVrI4T+PeZ58XeDqhaCcCmGIyr9czBatE1dv2I2z51nRUZCa7JgjMSYef7zPB5/lY97m5/KQrHFxi1oy+wPMXUTVy8gv4desxHv1+M5m5BdzvNDe9Wd2aXNu+PtM3xpX5vfJX5eog8FdgjHV9DDALQCnVCJgB3Km1du4CXA80V0pFKqW8gFutY1w6LtIlIrLzCnhr3l7aNqjNbd3KHsZYrvhNZt5aeOlz6mr7eDLtgZ78Pr4Pv4zrzad3dCbPZuPb1YdLP16bkXBiB8yteCHZzNx8cvJNRig1M5eEI/uJya3DwwOaseLpK3hrVHu+/Vt3rm1fn0N5QdTMTuD54a24tl19E7T4BJ5bgYjQ1qbsuH25iaQ9JvtRgczC+EHNqePjydUzssio0wLmPWuCLTA/gmAWlgfwDTKXxdfpqqjkGFO50cmpjFzu+nItZ3Lyua9fyTlBhRK2mmyblz9EDXdsb9LfBK/rPzdDOJ3ft8AmkHzQFOOwPByyjVhbKNdOPcaYyeuYtSW+4tUT7WuBOVdNTDtqhhv2fdLcrqRiGpeTE6ezaRVWi3bhtRn//WaW7E1k1pZ4Fuw6wV09I7ijh+P7YOLtnYiqV0ZGzx6wFF/WITS6zE4hZ9Fh5rgJaaY9I266G3qNZ6NXF6KOzyxywp6Skcvrv++mZ5Mg3rjRGmaauMsM+bYvdWAfApqdZtpWv4O5HdzCMdQyabepQFuB9p2vTo0C6NcihLcX7OVAYgWHhwVVPAjceSyN/87fy8CoulzRspzF6fcvMJdXPAc3fAY9rZPdGv4Va5d9X3dPhkbXw7+GB9+uKeO7G0xnjqcf/PGy+bs9nQCzH+dEUHeGnXmehOa34HVsXcW+06zOtdat2+Hl4ca1H63g2zWHefzHrTw9YzuD3l3KqgMni2Rcl+xNpMcbi7jp01WFvwmAGYmQm16yUmxupsk8fdQJvhxsOgnAZABXfmCGtv75pmO0h6g69rWCG3SB7g+Zz08VTIUoYvt02D7NBJ955zEUsCDHcX3QS+a3e9/csvcX1WLtwWR6T1jC+O83s/LASV4ZFEJrn1PmN8b63RjbJ5J24bVJycyt5taem6pcIuJ7YDXQUikVp5QaC0wAhiil9gODrdsALwJBwESl1Bal1AYArXU+8AgwH9gNTNNal1yo7WKm3C7KJSJ+XH+UY2nZPHt1q8Ky3Gd1eLUZ8lDcoT/Ne3CW9baah/rTur7J9EQG+zEoKpRv1x5xLJngrMu9plrg+s/ND3QZ1hxMptcbi+j4ygLavDSf3hOWEHcqk6d+2kaoLZE20W148sqWhfOXani489HojrRoEUXvkCz+1reJed2nDpVaIOGsPL1Nz31hELjXDDeqgEA/L/54oj8NAnx5pOAfZjz1xv8zn6EV75vAx55dc/c0wyKLZwIL8mDeM2Y5jtJ+JG0FsPg1c2LzWW8OzX6L2JMZJvv52Sp2HDvNp7d3okPDMgLfgjxY8ALUqAkPLi86dyi8a+FcSzrdWezFNYWcNDPczBKWupHDTW7B38eTQyczeOyHLTz+YwULYNRra+ZuOa8hmWqdgDYZYN6bSiyrfynTTt9Rx9OyaRTow9f3dqNp3ZqMnbKex37YQtsGtXloQFOa1fXngf5NmHRnZ/y9Pcs+aEoM+AaXnsWtgDq+XrQIrQmYderw8oWhr7Kv/gh8dDZZhzcwY1Mc3609zOhJa8jKK+Dl61pTw8MaxphorUfnXdt89uwnkQnbzGWYVVwouLnJsOdmODLHoRWoenyelFK8Paodnm5uvDGngpnqwEjTsVROZjsnv4BHv99MgK8nb93UDlVegZT9C80w7eAW5na0tVaePfN4Dny83Lm7t8kSb4s7y3zcCOu34JsbrGVD8nlFPUDDkDq0HTjadCLtK38ZCfvfdt2GLZj3WD+Ughdm7STA13Qs1vBw57Yv1tLmpfk8MW0LGw+n8Nj3mzmZnsvWuDQ+XRrjOFazweY7es3Eos/x22Mm85SXaToE11sZ7JhF5rdh8L/N7c3fVPBdEuclM8VMPWg7Cu5bBF3uMecVC54/92Md2wyzn4Dj28vf17nT5XyWY7J/1wQ1Mx0sLa8yz19Zy12JC6a15j9zzZI5347tzvaXBnPXyiHwQXvTwTOpP+xbQHT9Wvxwf08igyt/mkBVqsrqoKO11mFaa0+tdbjW+kutdbLWepDWurnWerDWOsXa929a6wCtdQfrXxen48zRWrfQWjfVWr9eVe2tNhdpYZjftyUQVc+fnk2Dyt/55AH4v2FmyMPh1UXvO/inmQ94Dpm0+/pGkpKRW2qP8oHkbCae6gq2fNatXFjifq01r83exR1frGUES3guaCk3dAznZHoOfd5cwupdh/BXWQQ3KH3eiEdgY1SqU6GalIPnHgSCOYk8vsMEXCf3lV+y3EmAnxcvDI9mSZI/W2v2QcetN8HN6TiONLiK52ftICXD6o3yCykZBG6bZk5mYpebbJ1zD2ZmCnrqzbDsLWbZ+rC6IJr66ydw6wezGfb+MhJP5/D1vd3OPidn4YsmuB/878IiP4U8asD4zXDXr9DquqL32d/HPbOLbO5/8+P8cH9Plj45gLF9Ivl9ewKHKrIenKe3KQ0f7xQEnrI+MwERZs7goT8vyk4YV1qyJ5GOry7kv/P2sOVoKvsT06lXy5s6vl58ensnBkbV5Y0b2zL9wZ6m4ifwzFWtGNq6lCGgzu910t5zWty9NM3qmiAwPMCncFt+uMkAb5w7hSembeW5X3aQlpXHl2O60rKelcGyFZi5N3WtYK7ZYDiw0MzTtVeBtGcCnbNsJ3aCe43z+5s/B3X9vRl3RTMW7UlkVUwFsl72CqFxZ18bc/HuRA4mZfDqiDalL//gzFYAh1eaDhN7sFi/Azy40hTiOg/392uCt6fb2ZfBuP4zuHuOGRmREkNKl7/ze5w3IzuHo8I6mO805+rKpUmOgbn/NNcDIogI9uONG9vSqVEdXrw2mm6RgSx4vB9vj2rPXT0j+GVzPCM/XU0NT3eW/fMKhkSH8tWqWNKyrGyym5sZZXJss6OgVNxGkwVqebWpbN2gs2M0xrpJprp0j3EmeJQqxRfGVgBz/wW/PFhynmV+Lnw5BPKzHb8pIS2h/1Pm/2P7TxV/Hq1h2hjY8KXJ5JbHOfA7ubfizwOmAzYj0cxpf2SD+Ru2T53YV8pcduFyeQU2npy+ja1HU3mgfxP6NA/GN8bp/2aZVY18/jMX7XlEtRWGEcbFuETEidPZrD+cwpWlneSVZtNXjuurPnJcP7nfzLNoNuScnr97kyD6tQjho8UHSM9xDOXJyMnn/q838l28KTq7cvFsNh0uukrJwZMZfLHiED6e7vwr5yNuSvqEd0a2ZsKNbWldvxYv97NOEsuofEftcJOtyk6D/BwzZ6Z4oFMRYR0g7YjJehXkVDgTaDe0dT3G9onkp8T6qPQTsONnAMYv9+DbNUe46oNl/Lr1mBUEFjuJ3PGTCYJu+c6c1Hx/q3k9W3+ASf3RMUt5Nm8si6JexXbVf6mh8nkscB3RYbWY9mBPejQ5S+CfnWbmwrQfbXpjS1OjphkWWjwLEWJlGxK2Ora5eYBvoLnqpniwf1M83dz4v5WHqJBGPc1nrLAIzxFzzFr1Ta9r6pGK9fheRvIKbLy7cB/vLtzHfV9v4IGv1+JPFhOXxnD9JysBCKtjgq6IYD++GNOV0d0aFQaAhXbMMEUP7MVKFr4IH3c1GfrUo3B0HTQpY65nBY3qbObRdm4cULgtNCyc3wp60CfpB16sv54V/7qCFSMy6TfvSsc8xFOxZsFz+/zZrn8zwzzX/c8MEa7dEPysuXH2LFjSPpM9DGlZsaIoF+ie3hE0qOPDm3P3FMnElqlhd1PApqDsgjI/bYwjtFYNU7m3PCd2mL/n4oup12tj5m6eB39vT/q3CGHBruNlF4jxCzLZwHGr4e7feS/3Brzc3cz/tVImKD249OwnXYnWfM/rPyssMDSiQwNmjOvNDR3Nd7tfDQ9u6hzOy9e15vv7evDs1VHMfLg3jYJ8eaBfE1Kz8rji7aWO0u+NegLafJ+ACfS8/OHGSdB8sAkSj28zlWb3LzCjUjy8TKGuJCn2cd4ykmHSAFj7mamq/VnvIqNF2DDZBGO3fAvRTh2LfZ80Q0MXPO+obFue5BjHaJF9C8p/XPIBU5xMuZlOrXNhrwUQ2NTxWxjS0mTendfKPJ1wfkNNxQVJycjlmRnb+XlTHH/rE8mtXa1pDnHriu7Ycrj5HDh3Nl9EJAisbhdhJvDZGdvxdHfj+o4VXK1j7xxoPtSsBbZvrikGA7DyffDwNidg5+iJIS1Iy8pj2noz12J1TDLXf7KS2OQM3r5rAPmh7XjcfRpRk6M4csjx5fznXhMMzBnvdGJzbDO3dmvE7+P7MrKpdWJR1nINhWsFxpkAQtvOLytg7/FbYK2RF9bhnA/x/PBWBEQPwqYVLHqFLO1Fg5admXx3F+rV9mH895uJyfQpmglMTzLZ1zYjTaGH6z4yGcF3ouCXB9A1avOgx6vsaTCS92/tSO9efaFeW0YHHeDHB3rSKuzsFRvZOdMMjep23zm/HgIiHUMDm19pLqOLLgsa4l+DER3qM31DHKkVGXvf7T4TrK/91Lz2zd+YANDN3fwfKHezWHl+TumPz8u+8CVH/gLyC2zsPJbGj+uP8MXygyzZk8hdk9fxwkynOZ856WibjSenb+XDRfv5cNF+thxN5Q//V1huu4t5g0/y9qj2vDmyLbd0aWiGwS18qewnXfSKuUyLM8O1Vn4Ayfth1YemwwENHUZf0Ou6Iqou214eagq9WBoH+fFY3iOsLGjNXacnIBy+gAAAIABJREFUEa6P4/H7Y2b46RxrLqg9SAiNNpchLaD1DaZnd9css0C4XXBzk/07vtUMt6zCoaDOvD3dGXdFU7bGpbH64FmKqdg17Gb+9o5vK/XubXGpLNqTyC1dGuJekSH8R6xgp5KL4FzdNowTp3OYtqGceXI+ASQEdGbahqOM6FCfEH8rcxnZz2RQzjb8zj6cznlB+rPo0SSI+/s1pYHVudElIpBfxvWmZg0PHv5uk5mH3KCzWe5m41fmhG/7dOh4u2N+ZPvRJmu8+FUz1LzHQ2Z7SJT5rcitwOgFUdLyd0yHxI1fmMAuMxm+vt6MMLIVmFEtjXpBq2uLPs7dAwY8Y6poOxdQO5sD1vz6oa+Zzt5jZZzYr3gPPh9kPoOhrU3gVsElWvYcP206dQqXhnIqCKeU6WjOsjoetDaVeX8eW7H2i0qxcNcJhr73Jz9viuOBfk14/ppovDyscCk5xizDBeac5fqJZskcqyP+YiNBYHVTbqiLKAjcnXCaRXsS+fvg5hUb+5yTbv5oGnQxa+lpm/myzMuGnbOg7UhTgvscdWhYh64RAUxceoC9x88w7ruN7E9M58VrounZNAiPTncA4KtyWDJrCifTzUn+wl0niAz2o6GXU8GF3U61huwLq5e1XINzEGivDHo+QWBwMzNUMWGrOWGoG33Oh1BK8fDNVzOr9u0ALPXswzu3dmFgVCjTHujBNe3CWJ7gRl5qvKPXfNdMU4GszU3mdqe7TG95ncbQ/UFmdZ/KgjONeWhAM8dcz7rR5ge3Io6sMfO8zrZuYtkvyPSsA3S8w2Qqr/u4xG739WtCdn4BE53n7JQluLnpHV73Bfx8rwmIa1lZ3pohMOwNiFls5j6VZtpd8HFn0xt7kbDZNF+uOMT0DUc5cTqbfSfOMParDQz/cAX/+nk7r/2+m3umrGfZviS+WXOYZs/O4a0pP5L3dhTHP7mK+VsO8eTQFqx7dhBrH2hCoxwzlzfq+G/c1DmcW7o2IsDX08x/Wvl+2Q3JsTKAuelmCDKYzPSuX03FyYi+JiN9gWoVm3fYKNAXG2586nMfHvkZ8FFnc+IYPcL8X58+ZlUGVUUz8ENecVzveIfjurunGWoZs8ScUJ7H3+r5urFjOME1a3D35PUs2Hn87DtH9gOUo5iLk+y8Ap7+eTtBfl5nL+jkLCXG/D3Wqtylea9pV59eTYN4dfYuktPL6HyxfLT4AFqbgliF7O//2YLAtDhzYuZ3lurF5ejQsA4vXxdNQlo2v29LMHNO+/zddGp+foUZvtfnCccDfAPh3vlw9dsw+gdHh1ZIFKBLLnshypcWb75n2t8G7UbBoBfggWXmb3Lhi2appdTDZXc6NhtkftuKF/Qpy46fzf+XvVhUWXPz/vyvo6hYeBezhm0FqnAfSDzDsPeX8/mMubDFWiu4+N+Xp6+jw8D+HVpsioSoOjvi07j/mw2E1vJmzvi+PHN1sfVIkw+YTsPHd8JDK81UpiYDLtqCPhUOApVSPkqpik9cEhWiubgygT9tjMPTXTlS4+VJ3AVocxJlH3qVtMdMnM89Y4q4nKfXb2hLek4+V76/jLSsPH4f38exvlW7WyCsPQDhyau5ceIqvlh+kNUHk7mla0NzggOmguaaiY5evOQY8KoJNcuommcfJpp65MKCQDCLp4O15tb59cd4e7pz3WMfsWPMHvo8Oa1wSF4ND3fev6UDBYHN8MxP551flrH1aCqH//yaWLdGTNzt5Rhi1m4UPLyGnCH/4e2FB2gVVotBUU6vP8ipMEZ54taZ4i/lFZwoS1srOG3Q2WQqvXxL7NIi1J+RncKZsjK29KVCiuvzhOnVPbTM/MAPd1oYvOMdgHIU6bHLzYSvroX9882QuNmPXxRj/hftPkHHVxfy6uxd/POn/2fvvMOjqrY+/O6Z9A4hCQlJCIHQe+9dFBQQ7AV7ufbutZdrvZbPK4q9o4KKIiqKAkqV3nsCISSB0NJ7MjPn+2PNMJM+gYTmfp8nT2ZOzpk5Mzllr73W+v020+/FhYx5YwmLE49wXqfmjGgXxm/3DGH2bQP4e+g2Jnksx2IzGJH8Gp7l+URmruSJ5qu5fXgbwoN8MCUvlBduf4FImBfZy6uzXcpxa/KmcywvzpZBTFgH6HMzHN4m27sGWg2Ir5eZ87tEMmHMaCmRNGwyqBv+mKyw4xc5TsPaVVTkDYmV3pwJb1edxIjqLtkIOKlBoK+Xmdm3D6Rd80Ae+G5T7dnvgHApWdxeVUD7vcV72J6Rx38v6krg/mWS+f/t37Uf01l75dp0vOdyDZhNiv9M7ExxubWi+EolLFYbv27JYFyX5sQ0dbkOOK63tWYC90vG/wT3fXjbcNpGBPC/BYmUWWww8gm4aYH0RF77CwRWKqv1D5WAJLa/c5njeKl8jdEcY+fBPMa+uZSRry9iadIRliQe4bfPXoI3OmJYy1gceR1TPl5F7+fn88KSLGyD74ddc+G7ayGic9UsoAOlJKu/d0nN1R4OMvfIdaH7lU7xspoCO68AqSK5dLpUlPiFuqVYm5olYnW3bLlCepC9Aqv6oXr6SrVUeTGk2Xt8lc7XNDZWm8GLv+7ggreW0cTPixm39K9a+WS1yHUxtI2MBR33j4QxMh7MdGNi+jTDrSNLKTUe2AjMsz/vrpQ6u6waThXKfEYEgYZhMH/7Iaav2Me4LpE09atF9c8VR79V885S+27ykJKqJPsFsNXQ496nthGB/HTnYO4elcCs2wYeUxAFZHbm1iXQ52aGe+0gKzuT5+fu4LPA97j5yMvOAcTFn4hFhcMI2CH0UtPgISACPHxlvay94B3ktGKoL50vgjEvwHg3GtBrwWw20blVZBUlRg+ziSvPl3KotWtXcdu0ObQs3MwP5QN4Zd4uvnTxITMMyR6lZxfzeGXFV3c9yIqyZJ2YPsf/YUY9JcIxwbVnH24f3ppym43PlqfU/ZpR3WHiOyIEM+XHiuV8Xv4y0D1caYC2e4EMHFqPkoFf4m8VM8anIcVlVp78cSs2w+CVi7sy/ca+3Ds6gX+f157Pb+jLe1N68en1fekQGUSP5PeJWv0Cb3hMY9uDXellSmKm/9Xs9W7P5ea/MCkkQNj4lZy3g++T82T7jzI4OeDiqVfT4NZmF9XITpEenvbjKg6OK5X6NiTTrurJpb1jYNL78nPJ5xL0hXcSwZDdC6pXJG6WIKq1lc//aJdjOuLkBYEAMU39eGlyF/JLLPy8qQ7VwE6T5Fh2ESJJyyri/cXJnN8lktFtm8iERn6G9FjVprKZnQJNWjbMh6hEm/AAJveM5ouV+8jILa52ndV7s8gpKq8qQuXXVGx5ahtw5e53ZvxPAJNJ8cjY9qRkFjHNYQQd3RvOeRai3bQJaRov94kztGfoRJm+IoUL3lrKmwuSqu1tnbE6lfOnLiMjt5j07GKmfLyahz/5jX57pwHwaPmNXDv7MImH8ukQGcSHS/dy194BlIfEQ3AsXPgu5Zj5/O+U6gXD2oyG8kK5x2+fA3PurP64d4gNdZggx5gyVa+eXZIr5cijniIz9lxRdPBvJtUGdbA/u4hm5DoXlOVXXcnTT/Z35pXw1UWyzFxLD66lDL6+HN4fBt9dV/OknKZGbDaDu2du4IMlyQxvF8YHU3pVqTABJOtsK5cg0BVH+8B2NzPOpxEebq73DNAXWARgGMZGpdRxqGFoqqAUnKbCMBvTcnh89hb6FC1hQOlyOtt20jv4RV61fAb/mS/y/3X1xxzaBt7BUkaplAwoD2yQmdrY/lLWcQK0jQjk/nNq8azqcjHmNR+ycGwe+2JG0vfzK2Er0LSl05rCw8cZ4GTtgeZda349k0kGgQe3SEB7IjPlSsHAO49vWzfxjZQB683ty7CW7oL9cO89j7Dpp6M8+eNWPlqajEkpcorKyC4qZ3i7sKoG8I4g8GjSsewq85+CNZ/IwH7kE5JFcSjjOUppjgeT2a3ManxYAOO7RvHOoj1kF5Vx85B44sMCat6gx1XyUx0RnapK6yf9LuVcV34jx8mmb0TwocOEBs+MNAT5JeU8NWcbB3JL+OaW/vSzi/cMSaim1PpoEix9TT5fSS7+Cx8FDC6/8kY41A9+uktEW4qz5Vyd+I4o+IIEECnLpOTXQcYmaDmg4nu4ChnsWy4lyLEDJJgK6wDDHpIZ78amaauKwk1TZov1SVlB/XrdOk2G2bfK48BalHEbic4tgmnfPJCvVqVyed9YPM01zN92vVR6XFd/SPqwV5m1Lp1fNmfgYQ9m2Pq9ZGEv+0rWm3GZlDLlHZBJnAvfhbZjRIExZ588biTuGZXAnI37mfbXbp6/sEuVv3+zNo0Abw+Gta3mGA5t7azmcFBWJKWwrYaKeEvXSxtkP0e0C2dyjxa8uTCJ/TnF3Di4Vd290a6YTHLdrGBVkypB9glMgp4J7D6cz5NzttEixJc3FiTSq2WTCveXUouV1/9I5LkmvzE5Kpt8r3CW2LowMelxzJYimPIj1/r1YmJROb1aNsHLw8RHS5N56beddOVpRnSIImGrD0uTVrA+NYcQP0/uG92Wawa0dNqfxA+XMcjP94oYG0p6wye9L+dyZDeZND64GXxCnPd0v2YS7FXG3vuVolow6sWF9IptwvPB3iQUZaJstpqrer69lot3/UlLz4oTK5kFpYQGeJN0KJ9lu48yxeyLR3mxlK47MNei5LvgGWcpYsZGsclw9ebV1MkPG/Yzd3MGD53bjjtGtJEJ0PLiqveonXPld0y/isubxEHLwbD+Cxh033FXdp0K3A0Cyw3DyK3kKXR6Ri5nGMZp2hNYUm7ljq/W09R6lMctb+BplIOC6QlLMG+yS+Qe2lZ3EHg0UeqnHcdOp0mw2G4P2f3KxvsADmL6QZM4IlLnEjH0Bufy/AzJ6pk9JTDN3CP+djmpso+1EdFZegwMm7N88XQlsDl4BzGyaZb0MET1xNQsnmlXxfLZ8r0kHpLeSD8vM12jQ5jQParqaziCMkf5656/ROQjpp+UnpXmyw11xTtidusIGBqZVy/pShM/T2asSWPWunT+79LujO9Wzf7XRXhH6fOxlIma39Hd8rkSznFOUgy4XQKgw9tPmjCIO/y+7SDhgd48P3cH6/Zlc/fINscCwBrZ+r0IKtz2N3x0jvTVNIkTcaJmbWHeY+I9aTJLoNj1MruQzvlSgrX1ewiMkjKowzuktLv/vyq+h+NYAQkoQSYTvPzgjpUN+h3Ui8AIuPEPGTi1GeX+dh5e0gOSf/CUTQLcNTKBO75ez0u/7uSp8TVkI31DoPtV2NZ+ytzN5YSVHSU+YCzPX9iXmGX/hp2/yvHe/nyZuPl0nFhl+DeT8/ivFyTwKzgokvsN0LNZEzFN/bi4VzTfrkknITyQS3pH4+1hptRi5XBeKXM3Z3DtwDh8vapRYm3aWgStHNis4inoGmg5VF1PEKUUz13YmY1pOcxal87qvVksfGBYzYF4dbToBSumyeSI2Uv2NScVJk5rtLLoGinOlnO49ajjU7auB58sT8Hbw8T3tw3kgreWcfXHq7isdwyxoX6UW238tuUgYYWJXGn5ApLAB7gIJIt75R/QvDOVOrK4aUg8Y7tE8uaCRL5dmw7bjhAZ7MNj49qzcMdhnv5pG1v25/LAmLZEBvvKQL7LRaIi2vUyuOB/8v07JnUCmkuJb8YmiOzqPL8DwquWeGbukfsA8NpaC1abweqULGaai3jK00pJQRbPLcxg3b5svD1MRIX44mE2cd3AlvTa/iO+wFDzFj7yv4mmeTtZZevArs/X0rdVUz5etherzSA4OJtJZdlUuMqU5sIPt0Db86CzvYWmrFCymtt+gL63SAn7j/+SKoC6gkBruYxfPOqwiTnbMIwK1+/8knK+WLGPD5Yk0y06mNuHtxZLkT+ekCzwHasqeqJu/FrGONX5pPa+Hr6/SQLxFsehiXCKcDcI3KaUuhIwK6USgLuBv+vYRuMWp6dZ/Pzth9ifU8zM7ivxTDTgro3w/jDMm75yrlRwqO4XOppUcbA15AEZIKatkj6jxkYpUZpc/0XFnoC8AxIEgswqH94hF3ibpWqqvzLNuzhtL2oxuT8tUEr2ce3H8vzcFwEI8PbgzpFuGj57+sqN0uGxt/4LEbO59mcxS136Orw/VLK7k95rhA9RPd4eZp6d2Jk7RyZwx1fruXvmBo4WlHL9oHoObEJi5IaYnyHlb/OflKBn5JPOdVrYrUuPJp02QWDykQJunb7u2PMXJnXmqn5ulO8l/i4lbcHRIobyw00w6mmZvfQOkImNTTOkVD3hHFHZA5j4NvxskqAx/wB0elYmCFZ/IANLX6dCJ3sXOx/nZ0i2PdjNPuLGJqITXPVd/bcLjq7ZOuYkcH7XSNakxPHJ8r10jw1hQg0THosjptDX9jm3qm+w+fhyVfky+MMfirPEjmfUk3JdiOwKD+2WgaBSsOp9+O1hCdpL7WVqoW5eI46Te0e3JfFQAU//tI13Fu3Gz8uD1KwizErh52XmpiE1nMuhbWDzTMn+efnJ8XZgvWR2lAnGT4XWJ2Y/4oq/twczbunPjNWp/G9BEo/P3sKLk7rg4W4gGNNPRJT2r5XBpUOA7LdHJBgLOknZ5eIcmHWDZJn8msnEhqdP47xVmZWfNh7ggq5RNA/24bmJnfh2bRo/btxPqUUmvts3D+STln9AdjDcuwkyk2Xfek6RCcwaaBHiy38v6srFvWJoGxFAiJ+US948JJ435icy9c/dzFqXztc39WNgm2ZyLY/pL1kykwmu+VEmcktyYdHL8O0UqXoYeNexfT9Y4gf79hJkz9QB0gICLPEaym+Hgph2ZU/Gdm7Oj18kQgpMenUOO8qbM7xdGDlF5azem4XFZvDzpgOkuHzNbcY/zIq9WSQEeDN73i42puUwvF0Y4zpHkjNvNsqoxuZl8zeUpKzCxxEELnrJHgDeCmOek/P476kVS/Vr4svJMvnzkHuKpmcFZUViNRLRiR39XmZZSiEz16Sy50ghbcIDeOuKnqjCozDnDvkuDau0hDgCvvISOLLD2VtemQ7j4Z6NjTpx1hi4GwTeBTwOlAJfA78DzzfWTv2jUAo4+ZnAcquBUrAytZDcEivBzUuICJKrlGEYzFyTSlSQN9EZv0tNfdNWcqM6kitKXdtm1x4EHk2y19QfrBhUeXjBRR828qerROsR4v+1b7lz2aHtzoxVaBvJBO22K0TGDqj6Gq64lpFVLoM7HRnznAySgmNkJvR4aNJSysNK86Ukote1cqHse4sMHrP3SoAZd/KD4rBAb764sS/3zNzAsz9v53B+KQ+f2w7lbsYm0D6Yzs+QgUfyIslSu86SOx5XLkE7RczffoibvxB1ugfHtCWzsKyiWJOlTIKzzpNFIMNBwWEZLI98Qp53vUTOD1cVxZ7XSCYQpOHdgV9T6DBRgkCzt8xKh7aRDMen48RE3FEGs3uBBBA2ixwboQlnVInM6cpj4zqwdX8u/561mfhm/nRuEVzh77sO5nP33EP0a/IWb00ZgLe3L3xyngQdF31ctXLBNQDodoVI3899QDw0lanRZ7Qjgnz4/raBfLp8L8/+vB0o5bqBcaRnF3HDoFaSyamOUHt1QvZeCeq3zJK+u7s3OoPaRtjXe0YlYLMZTP1zN1mF5bx1RY/qM5WViRskkyrJi2DfChkoXv0DTOsrVRVjX27w/a1CSS5M6yf35GbtxNx8zu1yDve+sarIzQkyb1sGBaUWLuol/d1ju0QytkskVpuB1e4R6XVoA3z4l1yPfJtIn6WbvZZKKfq2alpl2f1j2tE7rinXfbqat//aTdvmgeQUebLbPJShFhszV+9jTUoWvVoOoX98KHmdvOiz7UVMQdGUdbyMksIybvh8DVOyvJhs3sGsN66jePRLGECb9M0MBJ4uupgPrxElboBJg7tCCoxr7ckjA/tWKGEuKrPw3Zo0yuZ74IWFt8Oe4c72EQy3b3vdwDhsBscsCHKyE2pMsZTlHiblYB7tw/xg7adyPx/3inOFqB5SEl0p41WBkjwJbqDq5N3ZzNpP5Jg/uoukzQd5v3wKCoMbB/fgifM7yHhh4euSLPjXMvh0LKSvhT52e458ez92TROBHt5nXAAIbgSBSikzMNcwjBFIIKhpQE5FOejcnblMW3kYP08TeaXy3h+tXcS8e4cS09SP79als3x3Jm8OtqLWpjtnPqJ6iLLnkAckoKquaRrEsPhDl76wBirLOW7iBsuAxlHPDXIjdNz0YvvDsv+TEoDQNnWXyER0ghv+kIDgFGYG3KZZAjywSxTNjncgHtJS7B/2/CXm9g5Rj8DmYuqculJmWU8RPp5m3rmqF0/O2cq7i/ZQVGrh2Ymd3dvYMQufnwGppeK11rpSqaB3oGSOM+1ljtvnwMp3pYeqkUuqKpOWVcQ9M2W2d2zn5tVndDd+KR6Uq94ToR1HWavDPsDhwwhVZfSjekCPKfJ5K08ahNstFdqMElW7Fj1lkuGPJyTT0XGifI97/pRZ9b1LIJvqy2c09cbLw8Q7V/Vk0jt/c8Nna/j1niE0s2cpViVncuVHq/D3MvPY1ePxDrUr192xWsQM6urB9AkS1ct5/5ZSs4hOTg+8RmZK/5akZhVxbqfm9K+rnBmkHBSklzu8o2S3257baFktB44gIyzQm6d+2sbVH6/ik2v7EFyXUJpPsJSELnlVno96WipQOk2GDV/CyMcb/7tePlXuexe8AT2ugbd7O73NNn8Ld62TCogGoMxiY+rC3bQJD6B/q4r/T7NJOX0qt8ySCaW+tzbI+zoY2jaMR8d24IVfd9D7+QVV/h7s68lvWx2WKzEopmHkKzzfTSM88AhHCkoZFOsDB+Bi66/EzZGS3bvN2xjoCXeMH3IsAARQ9mvoXf2aQqUeVj8vD67tEQzzLfzW4m66DqtY/ls5mxwSHFLj5wpSRfzrh3V8NSEIVVYgE3GuRHYXMa9dv4qwzG0rRMMgN13GP92vgnmPONdPXwcJ7nlpnukYW74l0asjW4ubcpF5GePNK1AYlLX8DKU6SnC85kPJ6DVLkP51V2N4h11I0HG0nJzG1DkiNAzDCtiUUsF1ras5DpQ6qeWgyVmlTP37MME+ZrpF+vHs6EimTYjBahi89NsODMPgwyXJdI0OZkLxbFHwdNSXj/2vKG42ayMDxCM7qzfSXj614vPIWoRWTgbegaIKWNkLziHw0OYcCXKg7n5AB7H9Tk5PY0PhE3RimZgmLcUmYudcabJ3bYwOiRURhlMsmGI2KV64sDNX94/li5X7SKlOKa46HMdBXob0hUD1Gd6mLmIUaz6G1BUVb6gniQ+XJmOxGix9eATTrqyUqTEM+Pstp4l7bhok20szLWVicB0YJSXNNaGUlH6OetJZCuqgWVtpgO/nMmiL7C6/Fz4LH4+RTFKTOBj6kFOlUgsVNBjhQT58dG1vcorLue+bjVhtBoWlFp79eTvNg3xY+MBw4lw9XM0e7ovwOFRQs/ZUFT9oRDzMJp4e38m9ABAkgAIp4T+8A4qOigDISWLKgDimXdmTTWk5vPjrjro3ABj6IKAgoovz/Ol9gyhE1uRT2pDs+k2+o943yDFx00K4dan0JWbvdfbuniAWq41bpq9l79HCqkrTrhiGWMfED69qk9AA3DSkFV/f3I9nxnfkhUmdef0SETVrHuTDuidGM+/eIZzfJZL3ru7Fx9f15Rn78ZdfUs70G/oSca5YONlMniy8LIANd7bm9l6+2PyacXG/SuJlDqGs6iwlDEOEaICxA7oztDqhI1fqOFfT0vayZ619Mq+yuFWU/VrsuP47/AV/fVhKvd/oJEFin5sAJfewswyrzeDl33aybl+2c2FpARzcyryidpSMfhkmvY+y35O8kuwaFzt+kmz5wLvleXRvmWRy2CIdCwIb1jf1VONuOWgBsEUpNR84NrIyDOPuRtmrfxQmTmY56IdrjhLgZeL9SS0J8nbO+t05og2v/ZHIU3O2kXS4gNfHNUf9ORsG3S1iAyCzmQ51yIBwucC81gaeya34JhmbRGHz4GaZeQo5DXqBons7S9wcOHoCTSYx981OqTqzphGaxEnf3OaZ0OXSE1Z1bSyUUtw9MoFv1qQxdWES/3dZ97o38m0is9H5B+SG7eErKnGVCY0XYQ2bFY7skmU5aQ37Aeogp6iM79amM6F7VEXvNAfrP5esXJtzRMb+4zGwY47M9i54RsrRRj11/AG7hzdcP7fiMtdy76Kj8jP5I5l8ccym1uTjpTkuOkQG8dQFHXnix610eGoercMCSDyUz7tX9SQs8ATEHlztL1yzxacbjsz80USR1IeTrrQ5rksk6/Zl8+nyvVzWN4aesXWU1bU9V3qGfJs6/cVi+sr1J2m+U/CjMSjOFlGrTi79TP6h8tMkTsROtnzbIO0NUxcmsWjXEZ67sDMjXP1mK5O5W8qUB99/wu9ZHUopBrZuxsDWzkqHyGAf4pr542E20b55ENOuqjiJdu3AOEotNrvf7kA45zlM85+k9ZwJskJEl+r7NwPCRS08t5r7QcpSUdMG6a2vC0+X67p3kNMw3k6CbyGmnT9JiX3lvsmIzlL15FA7t5RKa86uuaLBkLZavFrPf020GdZ8KC0dDVwKfDLJKiwj6VA+nVoEE+DtwfztB3lv8R6+XrWPFyd3wcOk6FS6iRjDSqJnB24d2BE8u0C3y+G76+WeaBiQslzsvqLt/f+OCbH966Q3Pm+/PD/LMoHuBoE/2H80DY1SYDs5mcDVaYWs21/ErX2bVQgAAW4b3oY1KdlMX7mPFiG+jA1IAgz3M2MOSnJlVnHkk3DJZ6dPjXR0n6pBoOsFNKLjSff/OqOIG+J83K9hS3camvAgH/41rDVv/bmbYe3CmNi9jpk7peTGnpch5VABYdUHSW1GS+nWirelrAok4DmJzFidRnG5lRsH11CCuvYTyfJd9Z1dFGmMZABsVtg6SwYCQx4IChqIAAAgAElEQVRo2J2qPBBpEue8blz5jdgx/NNU6E4CV/WLxdfTzEu/7WBHRh6vX9KNMZ3cGGTWhmsWIn7Yib1WY9NqqFQmHNklA+JTMNl496gE5m09yH3fbOTPB4Y7yxxrovL90GSW0vPdC2rv4zpR0tYARkWfTgc+QTIgXvuJBP7tzhPl75CWIhRVE/vXweJXpKS1m5SNp2YW8e7iPUzu0YIp/esQqUpbJb/rY9Vyggxs06zWvyul7AGgncoD/kNbqp8cMXvK/7Y6L11XhdFaxG6O4RoEPpgoJf0LnpH/R84+bm22ifjD23nTdjPGgkTuHe3SbuPlB2HtJeAHUTN2ZAPHvSoTJw7j+fNelp7ULd8eE8Q509hzpIArPljJ4XwR/fMwKayGQVSwD+U2gzu/lraJO82zud9DMWnCpIr/39YjRVxn/3pI/Vv0IBznYFQP+a7S10gQmLtfEiG1nRNnIG4FgYZhfN7YO/JPxVAmTCehJzCvxMobyw8RHezJ+A5VK3vNJsUH1/Tiu9UpnNuiHL9Ns+WAr8kzz7V3wNUbx2EOH9ndWbJzOuCY3QHJSgRGSa+gxj2atBQ10LTVFb/L05R7RiWwMjmTR77fwpLEo0zu2YJBtQ0AAqOkl83s6cwQV6bdOJkpdMzqJpwr9giNOXizczC3hDcXJjF7QzpDEppV71N2JFGy8Oe97NyfNqPkJrf+CxFy6nhhw+9c5c8++D5nGalfU/nRNDhKKS7qFU3vuCZsSs+tUS203lzyufQEnu6Be//bpLz5wHoY+vAp2YVgX08eHdeeO7/ewN97jlbvy1kX0b1lgqbwiGSUGoPUFZKpalGD6MrYV+Xa/vujktl/f6hU8UyYWv365SXw1SVikJ44DwLCOBI+iBs+X8N55nW8WPYZpNxd+z02bZVUXDSyAu0J4RoEth4pvc4hMdWvG5og9kKVcRXQc8dj1MslCPT0BX/7MRUSCzn76Hf4O/LNIbybNxAW7+GGwa0qGptHdncGgdl7JePXvGvVgDasnQSuqSvPmCBwceIRHp61CYXi0j4xzNuagcVmMPWKHlh2L6ZvyrssjLufzr0HEuzryd97jtIxMoiIn6dhMdoxumclfYqOE+DXh6R6JjulYm+qd6D0G6evked5B866UlBwMwhUSu2lGl9AwzDqdnXW1EH9LCKCk2ZhKi8iu+M19XqXOTtyyCyy8s7EKLxqkLX2NimuTn4Y/lggIiLxw2tuFB/7qmRO0ldDSY5zoJe8SGZPTpJXnNuEJkgvW2mu7PvJkuQ+m2g19IwxN/Ywm3jrip5c+dFKvl+fzsKdh/jtniHYDJEXr0JQpMwGevrWbFbv4Q2Xz5Aba3QfEaNI+l2O/0ZUWLPaDG7/ah3rU3MY1CaU1y/tVv2KyX/J73Zjncta2bM5vz4IJs/GM/++YiZYy2SgEulGCa6mwWgZ6k/LUP+6V3SXTo0wUdAYtOgFwx+Fle80mDH88TC6QwRBPh58tzb9+ILAcLsT3uHtjRgErpRWDq8ajhNPHykTn3klzLxCVH03zZSKnoBqPtPOXyQAvPJbmPsAtj+f5171In5ZO3jTayqmPWXg4VFHELhGrqOns2qwa9B26RcSBNbUKxvaWq7BG76U/nFHaW3+QQnAH06uGODVhGcN67gEcYHD7mJW61Fc8NYyPl2Wwj2jXQLpqO6w6Wt57FBEr8nWIKb/SZvIPFF+3ZLB3TM2EBvqR0wTP6YuTMLfy8x7U3oxJMZb7FZKcrh2zwMwfgt4+dEmPEBsUfI3i1dkZXyCRTHZ3rNZRQgtujdsnS2Jjsykuu3DzkDcLQd1nfr3AS4B9PRuQ1AfiwjDIGLNfwEoadaF4nD3Aq1yq8HPO3LpF+NPm9Ba1NPSVklZCkgJV9+ba143MELKAtNXi0qoX1O5kGybLRd+fzcb/E8WJpNIT+/509njqDmraR7sw893DmZx4hHu+Ho9A176E4CoYB9uHhpf0U8wMFJu1l5+tQtixPaTH5CsIEBhZqMGgfO3H2R9ag6vXdKNi3tVo0Zrs8pkzd4lEoS5lpyFxIgo0uFtUuri00j6Xq6Bp0Zzshj+iGQBT2Eg4eNp5qJe0UxfsY/Hz+9wzGrJbcLtbQiHdzSOuI2lVLKlfW6qfb2EMXIdO5oo5f8pSyVD2f+2qusmzpP+tjbnYOt3G6Y/HiOsbA5f+HyEySdQvGl3L5CMYXWKrcU5IizXuZqB+emEaxDoHehUxa6OZglgKRGfuei+cJNd7KfgkHxX7l57KweBDn9jDx8Y9m9AwcC76ezhxdjOzXl/yR5imvryxYp93HdOW4Y5JuE8/UTpOm4IDLqn+veK7S99/keTIMyeJds1T0oeT6NKqVKLlafmbKN/pOLdG/oS6O/HgZxiAnw8JAu6fY5Mxo54Av56Hj47XyZX9i6FXLsnZ0339fNelr7L2IFVx63RfWDdZ3Boq4hQnYW97W5dOQ3DyHT52W8Yxv8ALffWANTHIsKzIP3Y48B9f7i1TUZ+Of9dfJCcEivj29dxEUr6XWasznsZelztzCLUhGPWsvCwBIBfXyo18cfrRdfYtD1PBsjuKuVpznj8vT0Y1yWSGTf357bhrXlwTFvCg3x49uft/HfeTueKgZFgKZbZ7ZrKQau8uP2GUZTZ8Dtux2ozeHdxMtFNfJnUo5pSlCWvwYstYOFzcsOLqyZTe8Eb8rvX9Y22nxrNKeM0yCRdP7AVVsPgq1Wp9d/YP0wmlDI2i4Jvfi3+u8dD+loJTqrrB3TF7Ck9w8oE498UERSHhURlclKhWQJHCst5MlHaPv7n9Q5m3xDxC+19gwQgMy6XSarK7F8LGBDT58Q+W2Pj6SOTDDe4Md5KGCPfX0x/yRo5yD9YP+GVyuMTx/0orD2MeAxGPCp+y4hvqFkp7v92ExvTcnjyx62UhnUU8aGx/4UnDksbR03WKa3tVl6OyX/DgBmXSRB1GvHTxgOMKP6dLzMvJ/BvSYREhfg6y2B3L5BKr8H3yvd/YL2ooIa1kx74PjdJO0d1eAdIlrf/v6r+zSEOs2mGmMeHn326Ee6Wg7pKKJmQzKC7WURNrShRXXQD30PrALB6+uOZ797N5rWlh9hysBiAXi3qKEVIWiDZgupm/qrD3x4EFhyWuumkP2DIg9JLcDrS9xb50fzj6B8fekx+/rbhbXh89hbeXbSH4W3D6BcfWrE8uLryp+pwyII3gjhMmcXG23/tZsbqVI7kl/LGZd2qik5snAF/Pie2DUtfkwmc6kR7YvvBo+lS4q3RaBqc2FA/Brdpxg/r07l3VELNtgjVoZSo+W7+RoKH9DVOf7f8gyIsEtHp+Mv1HJO7dU3qAox+RqyPQltL+dyCZ+DwTqc/qIOcNPaH9ufSacs5WmBwS2hfWuaulsxsUKQIoDiyMqkrIW5Qxe3T1kiwWVOP4unESDftsYOi4PKvYMU70ltZmCkThQWHoEk9vGQdJbsOAZf258PV30P8yCqrxjT14/0pvVi3L5v2kUHc/MVaXl6QytP3b5fMYV3HTJOWcv/YPR8G3O5UwITq/+8ng8WviJrtyCfByw/DMPh42V7e9/5NiuY2fyvHqeOzGYaMXeOHyUTG9b+JL2pZ4Yn3o4cmSBC+8h15HnYKvo9Gxt0ptNddfl4CegGnrgj/bMJkdjsI9Mrbi83sTWGLIXjlVQ0CfY5uw6NQVAuNpa9TtPgNth8qxM/TxNOjImtXLjMMuQFF1tBvVB3HMoFHRJreK0BmYk7X2nKlTt9905w0zCbF0+M7ERnsw02fr2XhjkMiDOMg0E2BDYfJemHDBoEFpRZu+GwNUxcm0SYsgMfHdWBSj0ploEeTxI+v5WAZME7+UH5q8uT0DtTHvkbTiEzu2YL07GJWJB9HZcD5r8lg0yFCMe/f4sH70Wh4b5AIVxwvib+LAqc7Xnz+zZxqnT2miHXOqvcqrmMpw8jP4Ic9Cj8vM9/cOoCW9/wOjx+EPjfKOkrJZLKHD2z/seL2NqsEvNF95Lp0ttHM3p93NFF+1zcT6GHP2pkl2yeTBKNrzHgPbNOMu0YlcE7HCK4bGMeny1OYn5Tn/vU+brCYxhdmVvSKfKdfg3lHuo3NCn+9IEHXbyL29Neuw6QfPESsLd0u4HbAKXwDUkadf0AUPEG+Jw/vhhEkM5mg88XO581OYxGj48TdctARLj/nGIZxs2EYuxp75/4JGChUVc2davEozsTi24yywJZ4Fh1EWUpcXsgg9o/riJ8znuSDWbRLm0n3/V9zoXklb0+IYVDLOrIAxdlSMlIf9SOfEJlhzEkTGfp2Y8/Oi7rmrMPXy8z0G/sSFeLLEz9upcTX5SZdV9mUg9oMgutJudXGY7O38OKvOxj52iJWJGfy2iXdmHFLf24eWo1Qzd9vyU3+og9FibPrpY3rM6bRaGplbOdIQv29+GhpMkY9xN4AuW/2vkEeB8fAvr/hl3tFsTiqh9jSHNhQ/506vEN679odR3mffzPocZWIZhxJdC7PS0dhkKHCmH5jP7rHhMhguXIZo3cAxI+QCiGQXrM/XxB15ey90P/2+u/TmYBDPORookwQFmfVLxPoHQjN2sGk9+petxKPjmtPu4hAXpm30/1jMKSlCOa9Gg+zKrUMZCXXex9OCEdwFxgFG6ZTvvZzXvx1J2NCMmScPOop6XVc+JyzzHi3vfey9ajG2afe10NYB7hq1umvmHwcuBUEKqXuUUoFKeEjpdR6pVQjycz9w1AmtzOBHiWZWH1CKQ8UPyTXHkFzafaxx4mrfz32+O7OZUQHe9X94nkH5Hd9VDNNJmk6XjlN+qK00brmDKJNeCD/mdiJjNwSXlzqPH/cnkH09JGG/+q8oeqBYRi8MHcHX69K5YMlyYQHefPNLf2rF4FxsHeJKLWeZca1Gs2Zio+nmesHxfHXriNMXXgc14TB98EV38CF74g6585foN+/YMpsQImhfGVsNsniABarjRmrU7ln5gamfLSSzX/Pg3WfgzIf/wTR8McwzN6w8h0Mw6Cg1ELiLhmod+/ShebBdYjgtBwg0vt5B2DO7bDkFQloE849K0U2ABHnCoyS6ihHZrc+tkomM9y5uv4ezYC3h5lrBrYk6XABW/fn1b0BVLW86HWdUyE7p5a2o7Q1sOi/MPMqmNa/+uOzvjgyj1Nmy9hy7oMkH87jjnb2z9L2XCk5TvwNvrpYKtj2LpEyzeBGsm9olgB3rHRmGs8y3O3ru8EwjDeVUucCocAUYDrgnjqJpmaU+xYR5pJMyoLiKAsWE1bvnD2Uhcisk1fu3mPrXZI/HYvJAw/DQqAqptSdFz8WBNbzRDr3RSlZ8Qk6a08SzdlLv/hQbh0az/tLkrk2vB+tBk52u0YeEGP2jM0ntA9frUrls79TmNK/JYPahDK0bRh+XrVcmnNSZSZd97dqNKcVtw9vw46D+byzaDdTBrSkqb8bE7AOzB5i1G6xW62EtIShD4piZ3hH8fqrzLLX4c/n4aaFfLA7hO9+X8TDvj8RZ91Hh/QUWafT5HpbTxzKK+GlX3eQXVTOdeUdaLdhHnenX8rafdlcZl7Efz3h/CFuVEw4FBnnPy0TxeNeE9XG6L4120+d6ZjM0kc45w57xYa5fm02J8gFXaP4z8/b+WrVPl6OrqE9wJXgWOfjpvEw4nERBnqtLeTsq34bhxBgcZZ8PsMKS149oTGgYRiog5vleA9rx4GoMUSlLOWmnoG0Nh+Wyhu/pjDwbkDB/CdhyywJRnUVzHHj7njHUVw8DvjCMIxtLss0J4CUg7qZCSyWTGBpcGtsZm98MrcSsutbfI5sIjB1wbH1IlUWZX6RWHyaYirLd29H8u1BoDtmpq5EdITH9sMDOxtPfl6jaUT+fV57rh8Ux6jD9zBpbWe+XpXK3qOF7m0c2VXKrVKWyw3Jaqn3+8/bepCE8AD+M7ET53WOrD0ABFH7A6cPlUajOS0wmRT3jU6g1GLjxs/XkF1YVv8X8fCCezbDdb84rWdi+8lgt7LS5k6p+snPSOT9v5L4LPBdxtoW00GlAPCNOo/sc96o19tbbQZ3z9jAjxsPsH5fNhs9uhFlyyArPYnrBsYxpslBrJ6B+Ie7YRMd2V36Crd8K8FG7xukB82jHsHxmYhDiXLfcgnga/JnbASCfT2Z3DOaHzbsJ7PAjRSAaybwzrXOCYOQlpBdQxCYlSwB4NhXRHRs4F1SrmxxK+VQhd2HCxj08p+k7N5BoX8sn/6dwnOLpTrn9l7+kk12WB8pBQPukJLZn++RUlZ3Wzg0VXA3CFynlPoDCQJ/V0oF4ra5naZW3MwEKmsZ5rI8LL7NwORBaZN2NNk1k/B1rxI7/yZCkmYBUI7MrimfEGxegZjLC9zbj7wDgBJVr3p/Bj0foDlzMZkUT13QkVcu7kpucTmPzd7C+LeWkeJOINi8q8yCfjYOvr8R/p5a/XplhZC1t8ri4jIrq1OyGNY2DOXueXRkF6DOSqUyjeZMp014IC9P7sKG1Bx+3Li/7g2qo/K1IHYAlOVXFMSAY2qOK1evYoR1GS3LdsOkD2DAnaRMmsOjJdfwyp+pbveHGYbBa3/sYtXeLF6/pBtrnhjN7TeI2MvcCVaemdCJUUHpmKN7uGfN4enjVBvvcfXZm/2rjF9TZ894m6qqno3N9YPiKLPY+HHjgbpX9nfJErv+f5q0lEzgwS3wTLBMQjhw9KfGDnB661rLIGNTvfd1adIRrv5oFQdySzCyU/jrkC/P/rydFrHSRxliyawYBDr2s8fVUG6/RzvEjDT1xt0g8EbgEaCPYRhFgCegTacaAuWeRYS5JAsAi4/I3Jf7S8auIHoYxc26UtBiKPOi7iLHkBknq3cwVs8ATG4HgftlBsjseRwfQqM5s1FKcWnvGBY+MJyvb+6H2aS46qNV7D5cx/lT2VA3bVXVdX65H16Kgak9Kt5IgZ83HaDMYmN4u3qUax3dJTdo7Xep0ZyWXN43lrhQP5YknrhoFOAsq0xd6VyWlyH2A4D54EYeDv5Tyvm6XALnvkBct+HcNCSeGavTuGX6Oh79YQuz1qWz62A+5daKY47MglKWJB7h6Z+28e6iPVzRN4aLekXj42nGO7IjBDTHN22ZZHoObhWxGncZ+QRc/GnNhuVnK9Zy+d3+gpP+1m0jAukaHcysdel1TwA4gnlH1tlB03jITYdNM+X5zl+cfzuwQTK84R3keUx/QMGev+q1n1abwRM/bsXb08Tn1/Ui1pxJQrtOvHd1Lx69zB4856bJfrgGgQDdLhcvy/FTpXxac1y4GwQOAHYZhpGjlLoaeALIrW0DpdQnSqnDSqmtLsuaKqXmK6WS7L+b2Je3V0qtUEqVKqUerPQ65ymldimldiulHqnfxzsTcE8YxqNYZKetvhIEZnW6jux2V3Bg0EukjfmYA8Ne54lDQygxiwy01TsYm2cgpjI3g8DM5PopWGk0ZyFmk2Jg62Z8dVM/Si1WLnnvb1Izi2rewL+ZmNSC+C0dqSSaXJgJaz+RhnbfEOmb2PMX7F2C9Y+n2D7vA7rHhDCojd14/uAW+Oul6g2WHRxJlFIYjUZz2jK0bRjL92Qye0N63SvXRUistGq4BoFHdhx7ONK8kajC7dIv5ZKhe3Rsey7pFc387YeYsTqVB7/bxLn/W8JNn6+lzGLDZjPYlJbDBW8t45pPVvPFin3cOLgVL1zYxfk+SkH8cEheJH2JtnLp6XMXs6f0bNVkWH62cvEn0GECtKiHKEwDckXfWHZk5LFwx+G6V75vG9y1vuKyuCEyNt31mzw3u5Twpq2SPkdH0iAgTLJxW2e5rXGxNiWLns/NZ19mEQ+d245hkVbMhoV27TpxXufmmAMjACXtD4a1ahAYEA63LYNe17r1fprqcTcIfBcoUkp1Ax4A9gBf1LHNZ0BluchHgIWGYSQAC+3PAbKAu4HXXFdWSpmBacBYoCNwhVKqo5v7fEZgKPcsIsylOQBYvUMAKAtpw5Fe9x87CbOLLRwttIhtA2DzCsbmVY9M4NFECGt7HJ9Aozn76NwimO/+NRCrzeCuGesps9QyUXPdLzDoXlFzy9kH5S7WLXsWAgYMeVD6JpJ+h+kXwufjMf/9Jo9a3uXBvr5SCpq9D6ZPgsUvV5x1dcVmFTVSfa5qNKc1tw5rTYfIIB76bjM7D7qp1FgTSkHsAIy9S0g7ms/fu4/y0Q8yOJ9hGSHrXPuLyNlX2Ezxn4mdeXRsexY/NJwR7cIY1T6cxYlHePSHLdz21TomTltORm4J/3dpN+bdO4Qnzu9Q1ey+wwUi7PLFRMkAtR5xYp/nn0DCaLhsuntls43Axb2iiW/mz5sLk+peOTi6qip2TD/wCoSsPfK80B5MlhbA/vVVq2C6XCzjyMq+kNWQcrSQ6z5dQ4C3B/eOTuC8Ts2dIjRNRPgQsyf4hzkFkSoHgZoGwd2j02JITnki8LZhGNOAWg3hDMNYggR3rkwEPrc//hy40L7uYcMw1gDlldbvC+w2DCPZMIwyYKb9Nc4e3LSIMJWLwIvVs/qvPTlLGnJNvpKVcJSDutMTaCrNgaKjOrug0bjQqpk/r1zclU3puTzx4xYs1hrO08iucM6zENZOzmVXy4jkReDbVMqnBt8vpVFDHoRLPufZqPcwlGJgyttQnCNqa9YyCIqGlTV4RGWngLVUn6sazWlOixBfPr2uD0G+njzy/Rastnp6B1ZiV+hIVOFhHv6/d7nyo1WElaZQ7BFM+5s+hH/vg1ZDqt3O18vMrcNa0zLUn0+v78vH1/Xh1mHxfL8+nYU7DjOmYwTPXdiZyT2jad88qPre5PYXQILdFazN6JMqdKI5PjzNJqYMaMmW/bnsOuimQKArHl7Q1sUJLnc/lBXBJ+dJZq7y8db9Ksl6zn2gYjYwebH4JdoptVi5a8YGzCbFN7f2597RbfEwm+T1QXwyHQS6Bodx9f8MmjpxNwjMV0o9ilhDzFVKmZC+wPoSYRhGhv3xQSCitpWBFkCay/N0+7KzBzeFYRwZPZtX9abvyVmiQuYdIHXdVu8QyQS6oQ7qlZsiD8L0wFKjceW8zpHcNbIN365NZ8Tri/hhfS2lXY7A7KhLSWj6WojpK7PBSsHQh2DUk6wLGManyUFsjL4a07bv4cOREjxe9qUYv6evlhtuZY7aTZv1uarRnPY09ffiyQs6sDEth9+2ZtS9QQ38tfMwkxcEUoQPT8Vs4pah8ZzfPA/fqI70iAuTUvN68OjYDvz5wDCWPzKSD67pzZT+LWvfQCm5Nl0xE8a9ctyfQ3NymdAtCk+zYuqfSe6bx7sy4A7n47z9sHcxHNoiSvAxlRQ5Pbyh62WSMc4/KMsO75Ts8S/3AXAwt4Q7vtrAlv25vHJxV6Kb+Dm3L7T3z7ramYS2lt8mT+2J20i4GwReBpQifoEHgWjg1RN5Y3tm8cSmxlxQSt2ilFqrlFp75EgDNWOfBBwWEYVltfQAwbHePptn9UHgjiMlhPl7YPKTm4H0BAZgspY6G5RrwCvfPtPSLKGee6/RnP08MKYdH17TmyZ+Xjzw3Sa2HZB2aMMw+HVLBmlZ9mAttI1M6jj6AkvyJGhr0avC6+WVlPPQd5toHuRDl8ufhW5XgqcfXPaVGMDHDhCz6P3rqu6M47Wb6XJQjeZMYGK3FkQEefOTO0qN1XA4v4T7vt1IXPNQPHpcQYej83lscDAehzaLT+lxEh8WQERQPfr0PLyh3VgpHdScEYQGeHPPqATmbs7g27WSTzEMg4zcYkottY85Abl3TXxHssC5+8XM3eQB9+8UVdDKONoUjiZCThr8fDdgwI6fOLhzBef+bwl/7TrMsxM6cW6nSkr0hUfktX1cJjQiOslvv6b/HGXZk4xbZvGGYRxUSn0POKKEo8Ds43i/Q0qpSMMwMpRSkUBdHav7AZfcMNH2ZdXt4wfABwC9e/dusOCyoXGUhJjtNfflNkVhqYXJXybTP1ZKLK7vFUpcE+8K25nL8zFMHhjmissBDheUsyylgIkdgrF6OctBbfbSUXN5AVZzkyrbHXtte78hAXUlZjWafybndIygb6umDHv1L/715TpuHNSKlclZzNt2kFB/L7771wDiwwLEW8kRqB3YABgQ1fPY65RZbFz14SpSs4qYfmM//AOCYNK7Fd8spo/8Tl1ZteTmaCIENK/3zL9Gozk1mEyKcV0i+WplKnkl5QT51K+I6o35SRSUWJh6RQ+8jDDY8Cn8+hCUF0GrYY2015qzhduGt2FFciaPzd7K16tSyS0uJyWziFbN/Pnx9kEE+9VxPPa4SrJ7SX/IT/Ou1QeA4JycPJoIK98RobMxz2Nd/hZF396KYfsvv987hDbh1bQ1FR6RHkDXcuSIzvK7vLj+H1zjFm5lApVSNwOzgPfti1oAdXd/VuUnwCHlcy0wp4711wAJSqlWSikv4HL7a5yRGIbBE/MPcPnMvUzfkMmXGzOZv0fkmge29GfzwWJWpBYyd2dV4VVTWaH0A1aq10/OKuXqb1MAOCchCJu3XR3UKxirvXS0LnEYc1m+KD95/MPUuzSaehDs68l/JnYmLauYZ37ezpKkI9wyNB6bYXDn1xtEdj2sndwAbTZY9LI01kc71eF+3ZLBlv25vH5pNwa0Dq3+jXybyAx/8qKqfzuyU4vCaDRnGOO7RVFmtTFv68F6leUdyCnm27VpXNUvltZhARDeHsI7iXCUMlUV59BoKmE2Kd65shc3DW5FkK8n8WEB3DykFWlZRVzw9lL3+gUdnrSHtkp7Q00ERso9b/scSJwHg++DgXfxtd9VxNv2MX18UPUBIEjfoH+zisscmUAdBDYabmUCgTsQkZZVAIZhJCmlajW2UkrNAIYDzZRS6cDTwMvAt0qpG4F9wKX2dZsDa4EgwKaUuhfoaBhGnlLqTuB3wAx8YhjGtvp9xNOD7QfyuHNOKslZZcQ38WL6BtHM+aCJF0EWeHqU1Ds/Nf8Aq3YZYcQAAB1HSURBVNIKub2/UaFB21RecKwUtKjcxu+JeRzIK+NokQWAh4ZE0LaZD4V+g8hJuISy4FZ4FEtZrLk4k/JAZ0LVMy+V8HWvcajvY1j8m0vfoE+wNn3XaOpgQrcoAn08iA7xJTbUD28PMz1iQrjtq/XMXJPGlGZtYc+fkPwnpP4N49+skLX7cuU+4sP8Gd+1jv6GhDGw7H9QnO30bzIMsYfodnkjfkKNRtPQ9IgJISLIm4dnbWbu5gzevbonfl5Vh19pWUXsz5EB754jBbz+RyKGYXDz0HjnSu3Ph8PboOOFuiJA4xbBfp48Oq5DhWVDEsK495uNPPnjVr64sS8+nrWUW4a7bFtbEKiUTGCmLAVlht438NWqfbyfHssUb+hm3QYMqn5bRyawwo7HQKfJYgyvaRTcDQJLDcMocwQlSikP6ujnMwzjihr+NKqadR19htW9zq/Ar27u52mLxWbD06QYkxDIvYMiOJBXTkp2KX0yAzHvdX6VfWP8WZlWSGpOGS1dSkLNZfnYvAIoLLPyrx9TOVRgOfa3K7s15ZwEyQBa/CI43OdhAMqC4gDwzkumJLz7sfXj5l6KMqz4ZG6lwDUI1Gg0dTKikrH7eZ2b07dVU/43P5GLLh6K399T4cuLJLve+eJj65VZbGxOz+W6QXFVJdgr0/Y8WPo6JC2ArpfIsvwMKMvXojAazRmGUop/n9eez/5OYXHiEf7vj0SeuMDpdlVmsfHI95v5ceN+XEVEQ/29uGtkQkUBjUF3i29g18tO4ifQnG0MbRvGQ+e249EftjDx7eX8fNdgvDxqKA4MjpYMX1m+WEfURvcrZQLUJ5hF6TYen72Vke06YWS3QO1bDv1uqX67wiNOIRgHSsEln9b/w2ncxl1hmMVKqccAX6XUOcB3wM+Nt1tnH12jQ3hrQiwPDmmOh0kRG+LF0FaBUtKBU3q+X4xc7FelFVbY3lRegNUzgG+3ZHOowMJz50QRGeiJr4dicqfqZwMt/s2xefjilZN8bJkqL0QZVvtriqCFuTy/YjOuRqNxG6UUj4/rQGZhGe+kxkL/2+UPMf3A2ynklHgonzKrjS4t3JhwadEbglrADzfBp+dLeY0WhdFozlgm94zmpzsHc2nvaL5YsY/UTLn/GobBi7/u4IcN+7l+UCuuGxjHhG5RPDexE4sfHsF951Q6370DoecUkfDXaE6AK/rG8r/LurPrUD5frtxX84pKSSlyYFTdwkCdL4LovnDhO7z0607ahAfwztW9UHGDYd/ymtXwC49WzQRqGh13M4H/Bm4CtgC3Ipm5jxprp/5JGEqhXE6KMH9P4pt6sTKtkEu7inmnYRgU5OdQHBjH91tzGBEfQL8Yf5r4mikssxHkU0MaX5koC2qFd+6eY4scJaLAMfsIU1kBhGhRGI3meOkWE8LE7lF8uDSZy+9/gui4IRVLaIAt+6XXt2u0G0GgyQQdJ0pz/b5lkLERWo+Uv+lMoEZzxnL/Oe34eVMGj83eQkSQDz9vOkCZ1cYNg1rxpEt2UKM5GUzsHsWsden855ftrN2Xha+nBx0iA7m0T0xFEaPRz4hRfF14+cFN89l7tJBdhxbx5AUdpdS05UDY/A0cTara115WCOWFVXsCNY1OnUGgUsoMbDMMoz3wYePv0j+Maszie0b5MWd7LlabgdmkSMstJ6ikgJWFCsOA63vJidK2Wd1CLqUh8fgfWHHsuUeRMwg02w3ozWV54KOzCxrNifDQue1YsP0Q93+7mRm3jD2mAOxgbUo2wb6exDatQVmtMsMeFtuJ6D7w8Tmw4yfwa6ZVfDWaM5jmwT48fF47np+7Ay+ziYndo+gT15RLemvrBc3JRynFY+M6MP7tZSxJPEqgjwffr0/nfwuSuLxPDLcMjSc8yKfeIkSz1oklxZiO9vtVS/v2+5ZB03jxD+w4AfrdCsV2hXrfmlXsNY1DnUGgYRhWpdQupVSsYRipJ2On/lmYqNxeGdfEm3KbwZ6sUtbtLyKn2Ep/isjDjws7hdA80H2J6XL/FniUZKKsZRhmr0qZQJnVMZUX6J5AjeYEiW7ixzMTOvHQrM3M3rCfi3s5B3UWq40/dx5iZPvwCoJPteLbBPrcKI/vXCuWExGdtICTRnOGc/2gVlzQNQpvT1O9LSM0moamY1QQSx4eQViAN14eJrbuz+XDpcl8+ncKf+06zLx7h+Jpdrd7DNamZPHe4mTGd4sixjHpGdpa2o4OboGNX0ow6B8qQaBD/dPTvxE+naY23C0HbQJsU0qtBo41qxmGMaFR9uqfhFJVMoFxTaTWf/qGTFalFWHGyhs+JcQ3D6VXt/rNlFj8pMa66bZPCEj7k6II8SCzeDeRDKBhSFmoVhnTaE6Yi3tF8+WqVF77fRfnd4nE10tKtVfvzSK7qJxzOx1nFi8kRn40Gs1ZQVhgVc9fjeZU0SLE99jjzi2CefPyHozrEsmt09dx3zcbeXFyF7cmLPZlFnLXjA20CPHlxUmdnX9QSvoJM/fATrvWY4HdKtyuT4GnL5qTi7tB4JONuhf/YAxlQlUKAmNDvFDAqrQivD0UN3fxhR3QOTacHK9aZHyrweIrQWDo1o8BMJfmYvX0x+IXjqksH2UtxWQr15lAjaYBcIjEXPr+Cu6asYHx3SIptxosSTxCgLcHw9rW6qyj0Wg0Gs1pwZiOEdw2vDUfLEnGZhhMu7JnrZUs2w7kcu0nq7HaDD66tjeBlYPGoCgxnAdoEucSBDoygToIPNnUGgQqpXyAfwFtEFGYjw3DsNS2jaa+KCqXg/p4mIgM8uRAXjnxTbyZnGCCHWDzCqj+JWrBEQQ68CjJojSoFTavQEzlBcfEYXQQqNE0DH1bNeX+c9ry3uI9LNhx6NjyS3tHH8sMajQajUZzOuOwNgny8eS/83YyfeU+rhkQV2GdpEP5bM/II7uwjKl/7sbbw8Q3t/ajdVg149Uguz+udzAknAubZsjzY5lAN/vlNQ1GXZnAz4FyYCkwFugI3NPYO/WPoppMIMDI+EC+3JiFl4fCbO/dc5jF14fKQSBAeUALDLMnXnmpmMtEsVAHgRpNw3H3qASuHRDH9ow8TArmbDrAzUPi695Qo9FoNJrTiFuHxrNqbyZP/7SNYF9PJnZvAUBmQSlXfbSKw/mlAAT5ePDxtb2rDwBBLCYAmraCgHAozZMsoM4EnjLqCgI7GobRBUAp9TGwuvF36Z+FoezNtoZRQfDhgvbBfLkxi/PbBWMql2yC1Suw3q9v83YGd+X+UXgWHqAoojfeucmYyvPxLNgvfwxpefwfQqPRVCHYz5MBrUMB6Bcfeor3RqPRaDSa+mMyKd67uhdXfriS//y8nRHtw3lrYRLfr99PQamFZyd0ol98U9qEBeBRm4CMIxPoEyRBIEhJqM4EnjLqCgLLHQ8Mw7C4rWqnqQf279SwgXKWijX18+D369uglMKUfvyZQNfA0lQqWb+i5n3wKD6MuSwfr/w0+xvqLIVGo9FoNBqNpiI+nmaeHt+JC99ZTtdnpK+vU1QQT4/vRN9WTd17EUemzzsI/O1BYOERZxDopYPAk01dQWA3pVSe/bECfO3PFWAYhhHUqHv3T8CRCazUFwgca8A12/v2jisIBAqiBmPz9Cc/7jyCd/9AWUgbbJ6BmCzFeOUmY/UKxuzn5kms0Wg0Go1Go/lH0S0mhHtGJTB1YRJT+rfkmQmd3Lc8AojpK7/7/csZ8OUfdCkH1UHgyabWINAwDK1i0MgY9hNIGbZqwkDBVC6ZQOtxCMMAHBj+xrHHhS3EsLO0SQIAwck/UxzaGV2JrdFoNBqNRqOpiXtHt+XmIfH4e7trLuBCSCw8Y9ehKMkVgZglr0L7C2SZ7gk86bjv/qhpHI71BLqIwxgGzTa8SWDyXMBp6n68mcDqKIwciNVTegzLA7X/mEaj0Wg0Go2mdo4rAKyMTzCc/zpkbIRdMtbFw+fEX1dTL3QQeMqpGgQG7/6Bpju+JHyDZPBM5fnYzD5gaoATz4HZk8zON1IU1oPc1hMb7nU1Go1Go9FoNJra6DhRgsEDG6QUVOuOnHR0EHiKcaiDKpxBoE/mNgAsPtKnZy4vxHYcyqB1kdPhKtLP+YDiiF4N/toajUaj0Wg0Gk21eHhB2/Pkse4HPCXoIPBU45j5MJwdgSaLNMl6FGfK87ICrA1YCqrRaDQajUaj0ZxSHMr0DVnppnEbHQSeaqrpCVSWEgDMZXkoS4mUg+ogUKPRaDQajUZztuDwDizNq309TaOgg8BTjotZvGOJteTYY4+So5jL8rEdpzKoRqPRaDQajUZz2hFoDwIdXoGak4oOAk8xxywicM0EFh/rFTQXHcVckn2sP1Cj0Wg0Go1GoznjcWQCNacEHQSeaqopBzVZSigPiAbAo/gw5tJsrD5NTsXeaTQajUaj0Wg0DY8OAk8pOgg81VQjDKMsxZQFxgLgnZuCyVqKVWcCNRqNRqPRaDRnCz7Bp3oP/tFoOZ5TjEFViwiTtQSLXxhWT398MrcCYPHWQaBGo9FoNBqN5ixBKUA5rSI0JxUdBJ5qVDXCMJYSDLMv5f5RxzwDdTmoRqPRaDQajeas4ulsbRR/itDloKeaY+Wg9kygYaCsJdg8fLAEtMBcJrK5Vp/QU7SDGo1Go9FoNBpNI6ADwFOGDgJPMZXLQZWtDGXYsHn4UO7vbJjVmUCNRqPRaDQajUbTEDRaEKiU+kQpdVgptdVlWVOl1HylVJL9dxP7cqWUmqqU2q2U2qyU6umyzbX29ZOUUtc21v6eMioJwziM4g0PX8oDnEGgxVsHgRqNRqPRaDQajebEacxM4GdA5U7PR4CFhmEkAAvtzwHG/n97dx9jeVXfcfz9mbsuiE88uBILWG2gVUoLygbpg9ZIg0pJaaxVTBsJWkhakgLpkzZNiW1ISmNqMW1piKDQVKwFWmljQGKt1qRQl2oURGWLVZbysC0PbURgd+bbP37nzt6d3Y0dmd/93Zn7fiWb+7vnnp2c2T05s589T8Bx7df5wBXQhUbgEuDVwCnAJePguGGsuCJiYfd3AFgaHcyTh78CgCcPezmMnjVI8yRJkiRtLL0dDFNVn03y0hXFZwGva8/XAP8E/HYrv7aqCrgtyaFJXtzq3lpVjwAkuZUuWF7XV7unry0HbSFwcibwyS0/yj1v+xw1Omiw1kmSJEnaWKa9J/DIqnqgPT8IHNmejwLum6i3o5UdqHzDqIUVM4GLXQhc2nRwV2wAlCRJkrSGBjsYps361Xet+P+U5Pwk25Js27lz51p92SkY/xV0fxTj5aDVQqAkSZIkraVph8CH2jJP2uvDrfx+4JiJeke3sgOV76OqrqyqrVW1dcuWLWve8N6suCJivBx0aWQIlCRJkrT2ph0CbwLGJ3yeA3x8ovwd7ZTQU4HH27LRW4DTkxzWDoQ5vZVtGJXxnsA2E7jYDobZ9OzB2iRJkiRp4+rtYJgk19Ed7PLCJDvoTvn8Q+BjSd4FfBN4a6v+CeAMYDvwBHAuQFU9kuQPgM+3er8/PiRm4xhfkjmeCXwKcC+gJEmSpH70eTro2w/w0Wn7qVvABQf4OlcDV69h02bLiisisrSrezvaPFSLJEmSJG1ggx0Mo061PYHj5aBZ2t2VL3gvoCRJkqS1Zwgc3AFmAhd6m6SVJEmSNMcMgUPL3ldE7AmBzgRKkiRJWnuGwIHtWQ7azQTSQiCGQEmSJEk9MAQObZ+DYcZ7Al0OKkmSJGntGQIHN74iYs9y0MpoYpmoJEmSJK0dk8bQ9nNFhPsBJUmSJPXFEDiwaiFwvCcwi7tcCipJkiSpN4bAwbXloBN7Ap0JlCRJktQXQ+DQMupeamJPoCFQkiRJUk8MgQMbXxEBk3sCXQ4qSZIkqR+GwKHt52AYRs4ESpIkSeqHIXBo45nA5eWg7gmUJEmS1B9D4MCq/RWkLQfFEChJkiSpR4bAoe0zE+ieQEmSJEn9MQQObXlP4GL31tNBJUmSJPXIEDiwfS6LNwRKkiRJ6pEhcGhpSz+9LF6SJEnSFBgCB1YL7bL4pd3t1T2BkiRJkvpjCBxaWgh0T6AkSZKkKTAEDqxWHAzD4i4wBEqSJEnqiSFwYNX2BGZpPBO4mxoZAiVJkiT1wxA4tLYncK8rIuKeQEmSJEn9MAQOrPa7J9AQKEmSJKkfhsChjWcClyZCoMtBJUmSJPXEEDiwfWcCvSdQkiRJUn8GCYFJLkxyZ5K7klzUyk5M8i9Jvpzk75M8f6L+e5JsT/K1JG8Yos29aaeDZmkRaonUoiFQkiRJUm+mHgKTnACcB5wCnAicmeRY4IPAu6vqR4C/BX6z1T8eOBv4YeCNwJ8nbfpsI8hCd01ELS5fGO+eQEmSJEl9GWIm8BXA7VX1RFXtBj4DvBn4QeCzrc6twM+357OAj1bVU1X1DWA7XYDcMCqjbjno0q6uwJlASZIkST0ZIgTeCbwmyRFJDgHOAI4B7qILfAC/0MoAjgLum/j9O1rZxpFRmwnsQqDLQSVJkiT1ZeohsKruBi4DPgncDHwRWATeCfxqkjuA5wFPr+brJjk/ybYk23bu3LnGre5XZUSWJpeDGgIlSZIk9WOQg2Gq6qqqOrmqXgs8Cny9qr5aVadX1cnAdcC/t+r3s2dWEODoVrbya15ZVVurauuWLVv6/hbW1sLKmUD3BEqSJEnqx1Cng76ovb6Ebj/gRybKFoDfBf6iVb8JODvJQUleBhwH/Ov0W92f8Z7ALLocVJIkSVK/hppyuiHJEcAu4IKqeqxdG3FB+/xG4EMAVXVXko8BXwF2t/qLg7S6LwsjWJqYCfSyeEmSJEk9GSQEVtVr9lN2OXD5AepfClzad7uGsjwT6J5ASZIkST0bZDmoVlg+GMY9gZIkSZL6ZQicAbXiiggMgZIkSZJ6YgicAbWw92XxLgeVJEmS1BdD4CzwsnhJkiRJU2IInAG14GXxkiRJkqbDEDgL9pkJdE+gJEmSpH4YAmdAjU8H9bJ4SZIkST0zBM6ChTYTWC4HlSRJktQvQ+AM2HNZvDOBkiRJkvplCJwByyFw0ZlASZIkSf0yBM6CjGBpzz2BjDwYRpIkSVI/DIEzYHxZvMtBJUmSJPXNEDgLVl4REWcCJUmSJPXDEDgDJi+Lr4y600IlSZIkqQeGwFkwMRPoRfGSJEmS+mQInAHLl8UbAiVJkiT1zBA4CybuCfRQGEmSJEl9MgTOgFoYLwfdDYZASZIkST0yBM6APZfFOxMoSZIkqV+GwFmwsOeyePcESpIkSeqTIXAGlHsCJUmSJE2JIXAWpJsJzNJuQ6AkSZKkXhkCZ0AtjGcCDYGSJEmS+mUInAWTl8WP3BMoSZIkqT+GwBngnkBJkiRJ0zJICExyYZI7k9yV5KJWdlKS25J8Mcm2JKe08iT5QJLtSb6U5FVDtLlXGZFaIotPGwIlSZIk9WrqITDJCcB5wCnAicCZSY4F/gh4b1WdBPxeew/wJuC49ut84Ippt7lvtTACIItPeVm8JEmSpF4NMRP4CuD2qnqiqnYDnwHeDBTw/FbnBcB/tuezgGurcxtwaJIXT7vRfap0IXBh8SnvCZQkSZLUqyESx53ApUmOAL4DnAFsAy4CbknyPrpw+uOt/lHAfRO/f0cre2BqLe7b8kzgky4HlSRJktSrqc8EVtXdwGXAJ4GbgS8Ci8CvABdX1THAxcBVq/m6Sc5vewm37dy5c41b3a/lmcBd36ZGmwdujSRJkqSNbJCDYarqqqo6uapeCzwKfB04B7ixVfkbuj2DAPcDx0z89qNb2cqveWVVba2qrVu2bOmv8X2YWA66+KznDNwYSZIkSRvZUKeDvqi9voRuP+BH6PYA/lSr8nrgnvZ8E/COdkroqcDjVbVxloKy52AYgNpkCJQkSZLUn6FOIbmh7QncBVxQVY8lOQ+4PMkm4Em6k0ABPkG3b3A78ARw7hAN7lONDlp+diZQkiRJUp8GCYFV9Zr9lH0OOHk/5QVcMI12DWVx8/OXn5cMgZIkSZJ6NMhyUO1taa8QeMiALZEkSZK00RkCZ8Di5uctPzsTKEmSJKlPhsAZsPdM4HMHbIkkSZKkjc4QOAP22hO4yeWgkiRJkvpjCJwBk6eDuhxUkiRJUp8MgbMgWX40BEqSJEnqkyFwxhgCJUmSJPXJEDhrFga5ulGSJEnSnDAESpIkSdIcMQTOiKcOPXboJkiSJEmaA649nBHfesOHydKuoZshSZIkaYMzBM6IGh2011URkiRJktQHl4NKkiRJ0hwxBEqSJEnSHDEESpIkSdIcMQRKkiRJ0hwxBEqSJEnSHDEESpIkSdIcMQRKkiRJ0hwxBEqSJEnSHDEESpIkSdIcMQRKkiRJ0hxJVQ3dhjWXZCfwzaHbsR8vBP5r6EZoQ7OPqU/2L/XJ/qW+2cfUp1nsX99fVVv298GGDIGzKsm2qto6dDu0cdnH1Cf7l/pk/1Lf7GPq03rrXy4HlSRJkqQ5YgiUJEmSpDliCJyuK4dugDY8+5j6ZP9Sn+xf6pt9TH1aV/3LPYGSJEmSNEecCZQkSZKkOWIInJIkb0zytSTbk7x76PZo/UlyTJJPJ/lKkruSXNjKD09ya5J72uthrTxJPtD63JeSvGrY70DrQZJRki8k+Yf2/mVJbm/96K+TbG7lB7X329vnLx2y3Vofkhya5PokX01yd5IfcwzTWklycfv5eGeS65Ic7BimZyLJ1UkeTnLnRNmqx6wk57T69yQ5Z4jvZSVD4BQkGQF/BrwJOB54e5Ljh22V1qHdwK9X1fHAqcAFrR+9G/hUVR0HfKq9h66/Hdd+nQ9cMf0max26ELh74v1lwPur6ljgUeBdrfxdwKOt/P2tnvTdXA7cXFUvB06k62uOYXrGkhwF/BqwtapOAEbA2TiG6Zn5MPDGFWWrGrOSHA5cArwaOAW4ZBwch2QInI5TgO1VdW9VPQ18FDhr4DZpnamqB6rq39rz/9L94+kour50Tat2DfBz7fks4Nrq3AYcmuTFU2621pEkRwM/A3ywvQ/weuD6VmVl/xr3u+uB01p9ab+SvAB4LXAVQFU9XVWP4RimtbMJeHaSTcAhwAM4hukZqKrPAo+sKF7tmPUG4NaqeqSqHgVuZd9gOXWGwOk4Crhv4v2OViZ9T9qylVcCtwNHVtUD7aMHgSPbs/1Oq/UnwG8BS+39EcBjVbW7vZ/sQ8v9q33+eKsvHcjLgJ3Ah9qS4w8meQ6OYVoDVXU/8D7gW3Th73HgDhzDtPZWO2bN5FhmCJTWmSTPBW4ALqqq/5n8rLrjfj3yV6uW5Ezg4aq6Y+i2aMPaBLwKuKKqXgl8mz3LqADHMH3v2vK6s+j+s+H7gOcwA7Mt2tjW85hlCJyO+4FjJt4f3cqkVUnyLLoA+FdVdWMrfmi8RKq9PtzK7XdajZ8AfjbJf9AtWX893f6tQ9vSKti7Dy33r/b5C4D/nmaDte7sAHZU1e3t/fV0odAxTGvhp4FvVNXOqtoF3Eg3rjmGaa2tdsyaybHMEDgdnweOaydUbabbqHzTwG3SOtP2KlwF3F1Vfzzx0U3A+KSpc4CPT5S/o51WdSrw+MTyBWkvVfWeqjq6ql5KN0b9Y1X9IvBp4C2t2sr+Ne53b2n11+X/hmo6qupB4L4kP9SKTgO+gmOY1sa3gFOTHNJ+Xo77l2OY1tpqx6xbgNOTHNZmrE9vZYPysvgpSXIG3X6bEXB1VV06cJO0ziT5SeCfgS+zZ8/W79DtC/wY8BLgm8Bbq+qR9kPwT+mWwzwBnFtV26becK07SV4H/EZVnZnkB+hmBg8HvgD8UlU9leRg4C/p9qY+ApxdVfcO1WatD0lOojt4aDNwL3Au3X9IO4bpGUvyXuBtdKdpfwH4Zbq9V45h+p4kuQ54HfBC4CG6Uz7/jlWOWUneSfdvNoBLq+pD0/w+9scQKEmSJElzxOWgkiRJkjRHDIGSJEmSNEcMgZIkSZI0RwyBkiRJkjRHDIGSJEmSNEcMgZIkSZI0RwyBkiRJkjRHDIGSJEmSNEf+D1hpvoMn+tE9AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f69db1e2f98>"
+       "<Figure size 1080x360 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -3028,7 +3059,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.10"
   }
  },
  "nbformat": 4,
diff --git a/README.md b/README.md
index 475ab44..d09884e 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,10 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 * The source-code is well-documented.
 * There is a [YouTube video](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ) for each tutorial.
 
-## Tutorials
+## Tutorials for TensorFlow 2
+
+The following tutorials have been updated and work with **TensorFlow 2**
+(some of them run in "v.1 compatibility mode").
 
 1. Simple Linear Model
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
@@ -21,7 +24,49 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/02_Convolutional_Neural_Network.ipynb))
 
-3. ~~Pretty Tensor~~
+3-C. Keras API
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
+
+10. Fine-Tuning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
+
+13-B. Visual Analysis for MNIST
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
+
+16. Reinforcement Learning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
+
+19. Hyper-Parameter Optimization
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb))
+
+20. Natural Language Processing
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb))
+
+21. Machine Translation
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
+
+22. Image Captioning
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
+
+23. Time-Series Prediction
+([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
+([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
+
+## Tutorials for TensorFlow 1
+
+The following tutorials only work with the older **TensorFlow 1** API, so you
+would need to install an older version of TensorFlow to run these. It would take
+too much time and effort to convert these tutorials to TensorFlow 2.
+
+3. Pretty Tensor
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03_PrettyTensor.ipynb))
 
@@ -29,10 +74,6 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03B_Layers_API.ipynb))
 
-3-C. Keras API
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/03C_Keras_API.ipynb))
-
 4. Save & Restore
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/04_Save_Restore.ipynb))
@@ -57,10 +98,6 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/09_Video_Data.ipynb))
 
-10. Fine-Tuning
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/10_Fine-Tuning.ipynb))
-
 11. Adversarial Examples
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/11_Adversarial_Examples.ipynb))
@@ -73,10 +110,6 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/13_Visual_Analysis.ipynb))
 
-13-B. Visual Analysis for MNIST
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/13B_Visual_Analysis_MNIST.ipynb))
-
 14. DeepDream
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/14_DeepDream.ipynb))
@@ -85,10 +118,6 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/15_Style_Transfer.ipynb))
 
-16. Reinforcement Learning
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/16_Reinforcement_Learning.ipynb))
-
 17. Estimator API
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/17_Estimator_API.ipynb))
@@ -97,38 +126,10 @@ Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb)) 
 ([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/18_TFRecords_Dataset_API.ipynb))
 
-19. Hyper-Parameter Optimization
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb)) 
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/19_Hyper-Parameters.ipynb))
-
-20. Natural Language Processing
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb)) 
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/20_Natural_Language_Processing.ipynb))
-
-21. Machine Translation
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/21_Machine_Translation.ipynb))
-
-22. Image Captioning
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/22_Image_Captioning.ipynb))
-
-23. Time-Series Prediction
-([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
-([Google Colab](https://colab.research.google.com/github/Hvass-Labs/TensorFlow-Tutorials/blob/master/23_Time-Series-Prediction.ipynb))
-
 ## Videos
 
 These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
 
-## Obsolete Tutorials
-
-Some of these tutorials use an API called PrettyTensor for creating
-Neural Networks in TensorFlow, but the PrettyTensor API is now obsolete.
-Some of the Notebooks are therefore also obsolete and they are clearly
-marked at the top of each Notebook. It is recommended that you
-instead use the Keras API for creating Neural Networks in TensorFlow.
-
 ## Translations
 
 These tutorials have been translated to the following languages:
@@ -203,8 +204,6 @@ Now you can switch to the new environment by running the following (on Linux):
 
 The tutorials require several Python packages to be installed. The packages are listed in
 [requirements.txt](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/requirements.txt)
-First you need to edit this file and select whether you want to install the CPU or GPU
-version of TensorFlow.
 
 To install the required Python packages and dependencies you first have to activate the
 conda-environment as described above, and then you run the following command
@@ -212,8 +211,9 @@ in a terminal:
 
     pip install -r requirements.txt
 
-Note that the GPU-version of TensorFlow also requires the installation of various
-NVIDIA drivers, which is not described here.
+Starting with TensorFlow 2.1 it includes both the CPU and GPU versions and will
+automatically switch if you have a GPU. But this requires the installation of various
+NVIDIA drivers, which is a bit complicated and is not described here.
 
 ### Python Version 3.5 or Later
 
diff --git a/reinforcement_learning.py b/reinforcement_learning.py
index de81a9b..d5f0e09 100644
--- a/reinforcement_learning.py
+++ b/reinforcement_learning.py
@@ -155,8 +155,12 @@
 #
 ########################################################################
 
+# Use TensorFlow v.2 with this old v.1 code.
+# E.g. placeholder variables and sessions have changed in TF2.
+import tensorflow.compat.v1 as tf
+tf.disable_v2_behavior()
+
 import numpy as np
-import tensorflow as tf
 import gym
 import PIL.Image
 import sys
@@ -1198,9 +1202,7 @@ def __init__(self, num_actions, replay_memory):
 
         # Flatten output of the last convolutional layer so it can
         # be input to a fully-connected (aka. dense) layer.
-        # TODO: For some bizarre reason, this function is not yet in tf.layers
-        # TODO: net = tf.layers.flatten(net)
-        net = tf.contrib.layers.flatten(net)
+        net = tf.layers.flatten(net)
 
         # First fully-connected (aka. dense) layer.
         net = tf.layers.dense(inputs=net, name='layer_fc1', units=1024,
diff --git a/requirements.txt b/requirements.txt
index 9c32b92..d303a8b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -24,11 +24,9 @@ Pillow
 scikit-learn
 
 ################################################################
-# TensorFlow can be installed either as CPU or GPU versions.
-# You select which one to install by (un)commenting these lines.
+# TensorFlow v.2.1 and above include both CPU and GPU versions.
 
-tensorflow		# CPU Version of TensorFlow.
-# tensorflow-gpu	# GPU version of TensorFlow.
+tensorflow
 
 ################################################################
 # Some tutorials use other individual Python packages.

From d5f33973570fe6ef9c78c8a38c7449a932c81010 Mon Sep 17 00:00:00 2001
From: Magnus <magnus@hvass-labs.org>
Date: Sun, 12 Apr 2020 14:17:48 +0100
Subject: [PATCH 61/61] weather.py tiny fix for new Pandas version

---
 weather.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/weather.py b/weather.py
index 524766d..e706034 100644
--- a/weather.py
+++ b/weather.py
@@ -165,8 +165,8 @@ def _resample(df):
     finally down-sampling to 60-minute intervals.
     """
 
-    # Remove all empty rows and columns.
-    df_res = df.dropna(axis=[0, 1], how='all')
+    # Remove all empty rows.
+    df_res = df.dropna(how='all')
 
     # Upsample so the time-series has data for every minute.
     df_res = df_res.resample('1T')