Visualising keras weights and output using matplotlib

visualising keras.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# visualising keras using matplotlib\n",
    "\n",
    "Sometimes you want to debug keras by visualising weight and output histograms. Tensorboard is the best solution but it may not always be available. Want to know what you are looking for? A good resource [is the cs231n notes](https://cs231n.github.io/neural-networks-3/#baby)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import keras\n",
    "from keras import applications # needs keras>1.0.8\n",
    "\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "plt.style.use('seaborn-notebook')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input data\n",
    "\n",
    "To calculate outputs we need some input data. Let's grab a 224x224 png image from the internet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AtaP00qZ7ED0oqozBn411vpaJXgcqhiFDdMl5Bs20N4Oh23XptTufBLL1i/8e\nJO+bqRp48OAdnj59ik7mJrOAHW9jYLDv486n9Tih6g7SPF4MOTR8pJvw+bxCpV1dmzlYTu+YRIcO\n6I5v054/rPacs47yZO3k/jaJtAIGHz+/n70LWyihPEGut8rvClDaVhlaBuERoz2ayPN5qgz3Sh9r\n26E9emgZxQ20ghuX18KmAHMkZQ5GCzPGows9J1sy96JmAsobIUXyZrSm89trwpKFBtmy6WQdq9mw\npe1ozRw1SF53NpJQEUKElAyGaypYwSdGEkCUEDSvCsTAheQsvxn2q5ktkgndgMiGuEhsNomD5Vvs\nLY/4reNvshwWaBohjigbs2wvWYTbqG4gXCCSM1pLsuSchVC1LP0GRSWhtsGpadCAEiXZyklHbTsY\ng51dpJGFDYv1c0mei/Wh82EBlYkk2TgY3Bag1YWcnxuK1iEqBNXcb1rPFR8YmexpVk2X5u3gCpRV\nkZIysxXfDlBhMvdc63XwEHBtpDm7gUmLprL3IeY07iJE2xauknLEM447MpgQG7dtntAyGrEgtrxH\nqC97rx4Ir0y9ha8W220ZuMmqiFdqU2jjyrdtCHm9w7jJC3+CucyuVh2uYJcuKZuhaoNK3I7QHgsh\n5sGWnLNfhBLAlCVBbFJ0989uYakdadh5A9vFjZvCOCY0BY6O7pA0cXZ+ikSDgzKABtIkxLBkGATV\nTWYYZBRRJJGH9RpcLs23amqTmHUnKi3H5jN2GzH4NeV2dn2LDLZQiH3uIfGuCs0lpPdVmzG6wnJ/\n375nX9e2bKdda9+bO12KEvLU6VySoZ1b23P7+tIwy8JZG6BZK5H7ILQ623Zdt8plEZpWXm0+hZnf\nt/kFt0JHc8ElD7pQLlUfblZCP6A+YJnic32sThIisCl1lTRaEE5GECq6c8IXK6/W79nKPrP+tsSr\nAANDXPLO2+/x8eMPEcasMhX1JqAaCWHBlDYknRqi3e7DreLGwgbzi0l0qTHKRnpNAhuH3U792jOG\nLJikWfwkDcHSvOfPDa/CJ3yFcbsm65wxUKRlyza29P7O/XlFv7hNYccvXS2uUB/aTV/qIii6WIYf\nC+EXYvd7icmZHqleVtfPkqHstWEKblOonFvLaLcStyAGcgKRXb7k9vNOA5GpIUXPE7EVjL6lOeUY\nKRQ1IsaBDM9qYM90CWOrSCHRLvns3et5vUImlgVIJIYlh4e3ePTtx8TB1jOYyoQEFsM+Ma7YTC9Q\nRoKknsimuXitAAAgAElEQVSCGxvB13K0q+O01F9ziKAZ99zNWnQAd9E1C4/EQ3cz/qcGBlVk0CKE\nmmWpsTXgfHCOAiiqIZr8EdZnmUnVnbo8x2Rua5DLBMwcfdTIQHdjd1ETfqy8m9pVgtUoz3A0UPIa\nuMeBmsTV+6WGx7duVaVJT94Rd6c+SMMEaJgu9di87Dre2uyuQxKvDVNo3z1bUFa9U2/Fdal66WIn\nk2g7i2y9bFrVz41AzH73qmsvojLpVIgrp2a9wkB1JXNuJKShhSkJdw7v8OLkGSmdI4MTUyRpzsa0\nXO6RUmKazgmx7RBvX5441e89y2tJzrZUVTe/tFUz2v4rlNkclnq8MJ/2um30Ur0+nVaD97uRn51w\nSZo9X0hVGFG94W5J2RhEyzNnc6N5TieQmmb7b3k5fW1bR7g0n8srdsd7zevmuMEZYH+stvOm6on3\nyXXlldoUYswSd74qjYZb+5xvtPBy/daad7ab3A8S7GIMgCH5llHkz772wQfZDUiBbFASqdu4X+bW\nuqz4fpNZggho4P79t3hx8gxlg8ccqjGnxbAgSGSztv0eQlYfsmZVONnWU0rdGrmYP9sqB8kuulxq\nzgXx/zOB3i8WsnOb1O5Fve2It+nrhkH0SKHVTGYIojNM9hWqbmW6YyJbFd8qu4ipxIJccv4uqb7r\nFcRzJl769E7tuZSwZdY2+ud8tnL9+a82eKkgAy2MAXxaXz4ofk1bKkO58dNxbu9wuyIX0wsR2rTc\n9UpxHFfUmSDhMzOFfCdjCgh7ywMODm7z5MljQgPtc5KQyGq1x2Zc530hSWiarL61RfMO2J4zviim\nmfbN9uWpOc9pT2bX9+8NmUr/atPM+eTfTaz992r3m52n3me74TEdwdJ9v7r087BFCjufM2uLE2m7\nH4iIEG+0OfE1DGH2bJE6IJcxhl136gXj1eWVqg/Fcm/oIEOsPJGSN0Ck7u+IQWNSIcasKzX5/JAi\nWbZeWcFDyyuQTLQFg8FziJXHwCSViG3iAUEsEasNQVBzObbQWWzXRot5CK0dQ4UpKosEIktOw5q3\n9pccrm6xnjYsZMNIgriAsCTGFcthn+OzJ4zhjIgAA2nK6kBmVNZHKtT9nxRHrr4op4hkhcSEhgF3\nzarlhpQUCGpWdc+RKFmb99HIyEDKSsiyT2RhDEaomOstgSd9LHmMFaak6ASeuVlUyh6wAWw1Y763\nb4DbMoYWKDkqT8WNmjeLrSHME8pEEttI1vGS5kVoQafClJK2blZ/kkcrlhlCTvmL9VdeahZkoETG\n0u8o6sVrWDY0ltDwYkc/oXYoM0Z0FUPZWg3ZiAy5Wna+NnEKXZEqWW6AdvoLrz1lJx+dnSI79OQq\nEfK7TXy3z0nepQnmMnRXtfzAhIQBknI7TPzC197i/OUTdFyThmhEIkgS9pZ7sFFkSiyiVlvELEjH\n2ZKjH6Agg+KjvtLS71XUYkYo6Mx/U5fKvf2mIBZjCC3MrfXzSEUpde2rsXt8SrukP6f35rRMWcuK\nRHXykxrJ99nUvPYRPVLo93hoQ8i3iXinUtLUsW+alN/blG7dnJoZKEvZGZl58/a+FupD8T7QyNnP\npS/dpOglr4oKnFOHHZCwewXZasNnqbKgjDohKD915xa//xsPOPnwUU6sJiuQBaKBSCCGwGZzQURZ\nNnaMnfedw8kCO31SmUXBsyVJu8ty3x/t91ZPKcQp8+9932RU9dn65cp23VhONGM7k4xt0p4bP5vt\nsXaG0DOG7byMN5vLDXEL3bO6s2Yqy65zbtLZV53xaoOX5p+LTndFg29wT9cWPIqxfeEW6R2MISjF\nD+HJtH0R1C6DpcxmaJEOs3rv4tJFyIuyYuQnDxac/vCbnB5/SCShYYHGBYHIIkYSE2dpg0Yp8RTz\nkfVQgiuLYLkiaphvZ2GQmnvJGlJf/rUB1I6avPfL6X5ukGbr9R+jSH3eZ+S89u62ggZWX2FQvLwa\ncyEwI/zZfKgoYY5qKrNtPJMG72fRt7tooaCyHfW5pH79xZf34edWHx4+fPh3gef29bvAfwr8N2TF\n69cePXr0Z667R9sgW5WccxaUivvy4+0GzPMpVEOjQFLLF1BfVQdrO6n5XlSCqq2WCW+4NdtAApqy\neyqlVIN+OlXBkM+OOjathxRgSOxtXvJ+OOSTDz7gxZiQ1YAwEUVYotweBk6nDaNMaIDBiLnd79Lv\nX/evvIQpNXA1p7OfcmIWO73aIKpNwneiFg83FoyVeOdAzeDsS5PVJF4T51D6xu6vmC3IMb1/7Jme\nCE2b8hJs9YPeLGlOLu10IZNKe9uFULlvLPvTjhJCIE2eAm+b0Py5HXKYCZGuAf7R2+i/m55WZ2TD\nyxoiL231vxsKzs47p1Wtuqx8LqTw8OHDFcCjR4/+BXv9KeDPAf/xo0eP/gAQHj58+K9ed595U3pu\n+9k4+M2flQm731LLmIPSv0q9LpcMdWB6CXlZad2vooGBwBHnfGW14Nnphk/YZy3CKo3srzd8abXH\n/WFA1muLgapZfYskbvurnTxzCSGX9KqrEWATRptu0YILqtrkOyxDT+xzVYyd+i2N7aVdGdmqj1tV\nnH1piaJr7/bDqus69R4qf7Z/Lld0vHs3Q9j18hBnZghhLgy2EETz0OIBa5BYi9LKBXqZsLm8uFs6\naV4TdFn5vEjh54FbDx8+/OtkR/t/Avzio0eP/pb9/teAPwz8lc9y0zy3bIOQG0ZffTFlJu1nvzik\nE3ZPhnqmD+DldfZ2JU3EuGDaXPD1tw5Zjht+8OlLzvbeJgZlOb3kKAW+cXiHJycvWE6J5SJ7YqKa\nfBfo7QFWE9k1Gf1HJVu5BU/g3GodRf1qLYC94C5EqQVGebNlflIhwh1CszxR68edfddgiaaNu8/t\n2ukaA7bwqXgZ6vzq1qdcouYV2XytYBDbRo5uA5g27iF3WZ0jtfWXtKUIml2/mzG4wtnL+6Mp12Ul\n+bw2hZfAf/bo0aN/CfjTwH83q9EL4M5Nb7bTEFMMAe15Ge7l8Jps7e9fNgnFQ3Qt156JfiG7DqW4\nuyQnA00JcWiJNkleG3enCqKBoJbEVcWzHAIQVYgaCBpNwOZVlJ5AWdKM0YnkFODjOT/75dv8aDzn\nR8Mt9iWwSANo5Csx8fb0nNPzF2zCwthOImoEyWpCSo4cLJ6imdiOIDoUU/7bwdwBJMkcIm+rO+W+\nEE/hmnMwEvM+ic73Kh9oCMP/2Y/52XXi5zCA5juhUSMqgkBBkuQckuoOzEq8FdG5i1LJyWx9pWNW\n31KTnRpclagJZwtm1JTDpckuahVfcSozYKkFIeWEOzYn3BXpzKPRfVpVtXSSz8k6MNWeANWm0LiD\nfQXwhDJJYhJ3t07Wzsle7YY/GfWp+Xc1KEkmpi6lf18+L1L4TeBbAI8ePfrmw4cPnwC/2Px+CDy7\n7ib/7//zdwC4ODn/nNV4fcov/fVv/dj3uFbf+sdQ/upf+N6rrsIXUv7Hv/R/vuoqfCHlL/z5/+W3\n5b7/7n/4Ry/97fMyhT8J/BzwZx4+fPhl4Aj43x8+fPgHHj169DeBPwJcOyq/9/f/Ps6OX7K6vddF\nA7quCSaJQgPHBCTm7MPDMBBm74soLAchxsgwDN17CIGhWd5aXUqSN1VxCdDtJJxrJOK6aSLpyJQ2\n+XMa+T/+13/AP/9HHjKl0ZKJT7gm7m4qYCsbTwjwT90X/tjPvMVf+3u/yW9eHHGxt2Qk8fXxJT93\ndMj3zj/hO8s9zsMtgm4Y4xkIpCFZ+u+JEBJhgLzjMQX/tZGiXQYo7+SUN5GRLEr4G//5x/zL//7X\nCEQiCwaWRJZEhpKEvuZsByQRgiIDyJBzTbAAIsQlhCiEIbcz96GnNBc0BVICHWEac/BSGgNphDSC\nboC15ONTICVHClktCHh+AZe4+RmK8t//13+DP/Gn/hCqExMjk26Y2JDSxJTWTDoxpYmUEiltSGlk\nHEfGNLGZamTtNFVpGoIQYiDEvIx+iAuGGFkOS2IcGIaB1WLJIg4MYcEQF/gmPUHD9SYyBQjNnBz4\ni3/+r/Lv/dk/VtGG2zdCsD6wulVcUs1xbrfxeZutCYYDxysViM/LFP4S8F89fPjw/7Iq/FvAE+Av\nPnz4cAH8OvCXr7vJrmr92OZF1zq2Xl+QbcLhMkWbrj818P0yW0hKdYGX6JqffPstnp2e8fE45OAn\nVZay4b7Ay9MLnoQFZzKQdGJQZWBgDJPVQWmWNVrldujFTV3KOihpdP6touUlDQ8pQdASS/u1ydpM\n+9q63xWlNV30NrnqSm41o11GhitvXsOXy75QTijtM/z2Upe5V+/XJS6/bpfyUIRAzc/42cpclS5s\nfKuOtT/mNiH/fdYDNCKXqzrwczGFR48ejcC/seOnP/hZ7lPq3bWgEtW2ddWb37v8/HzvKE1YZqYs\n3VKCIdbZ2hriqvW8FifcWg9/dn7LArfRG/2eO/t598QYYmQZhPfurXj+7JjH60BcDEybkbvLkffu\nHPDk2TnHcckmQQwjiBCJTExmR8vUUXIfhNx/1ajXMoPW0OXt8YsaFtcI5FRsMp7uvi5dVqiLn6QO\nYc4abf1aEItQtpVo6pMDLcUfRnFBlONN/4kda20j2lZ4RhbahDYXxpDKM5qZ09tEpB/TiuqkBmRt\nIcl6neBIsL6uNPx219c6dO5MmZGxNh4h65ZkJ5Vj1hcOGlTbbJC6U3h4eT0St/YHa6Mb6zZQiNNj\nd3w5awf5wfWPnAfNDIpOCNmoVa+r990mX2c8ZZGMnSRgi6a1JMjMhFHNeFfBM1VlSomD1cDtA+F7\nPzzlIuyzipGFKu8OgUHWHEdlLXssp4TEkSSBqBAb0xqCuZccKbQE3jO/mqfC+8MYYhcLUiVJ+TOp\nGkIzFj6xWhVrR1uvB2jaC6/WN2lrIXyyt/yhtk93PkSdCQAe5l1eHgvT0IaorfOQuijMl0rXxKzz\nZCo1JiGrp9FQQqSyrm3GUerYocpLzs2wpJtN85mVVPO6G0cPBhgLA2hmY0ULly/5f63CnHcFalTr\nbYWBLcN1nXkcR6bJ92voubOqMo5jcY9NUyp6o92lzKt2y/tthFLrhMy5e8OcOi2vr6u/T9PEg7uH\nDMvE07MzRlZcSB7ce2HgxekznstECnvs6YJFCIwx3zea5yMv4/Z3778m16K99xPZ25Or7lmWt9Qd\nj+OnqgZF6jTIIHPIjqrr/W+C8Z3g7TppL28e0UrBG6kOjghmwW19INfMrSjQZUpq+i6GbEuIIXb9\nGex7NIaQbyt42FxT662yC5XsRCD28v4vZiGdryxma5xKd7ZAdlcnN+XVJlnZccy7I1DTdmVo3uiu\n9NKvJ+Spk1lFhoogMgCDTZiIyFAYTpAA01iIS1Fb0Occu0mwoVgkY80GlJFD3uPRF0cVrqxikHoD\n7IEOLOSc99864KNPz/ngkzOWw5cZpw1HcsxqteCD8xXHi32iKAwCRAZD+7neOZdC3jQ25sRMkqF7\nAQzMBl/anvVXjiX1RKga8q5QKeU2ueVSnRNYW9QQm5gIzy4vcf8eHhBV4h5doDePrlI6BxY5sqvp\nGqoevK2eafO/DArJmYDVERcizZh1TMsJJ1RuJy5pvX6CpZtzJOCvvLo0NKtMCaHRsto61rmTe6yq\nB6Vr0TzPxLh1Oa+tc98PKpK3xRVjqNamoO06WXO2SzY16rwrZ+XVMgUn8O5oFUEeY1/0VNehU05x\nJiJF/y9S0MVayFuvjZMypZEQAtN0jug5q70laRLWk7LaWyEoQRcFDac0McSIR+gpCU2ZAeXVwb4i\nskI+908Hzd7yLCls70CTcirZKzFoYCmJg8XI4+cXvEx7IJFFuuDe3sTLUXimK6awIgSLF5ggBtCY\nn5bhejKGFwhW12IjkRb9+IrHNqbeoCu2apFKTOJjU4ioJg/tqbraI7SgJ79rN5S5ni2AMKIrE7m1\nmnVzwqGEjX8FOeVG7TxK5bP/NffcYfdRGz0kQQhIETbWX6oVhUlsEJenYTOEYCpGSaLq6NI4os8D\n74zSNT5nrd/yz3VetWi0Nr/pc2OcqdiSDCEZVxNxu0qeR57D+yq97hUvna4Nty6cGWNk5+ekOXW5\nQy1VGEffQSkwpcCCwN5qxe3D2xwcHLBcLDnY32O1CqzXF0RzL43jhvX6gtMXpzn0RJQYlGkzsVy4\nZTlvOutzSruZ20BGRzMqRlzePhocDmjiYH/Jrb3I409OeRlWbHTDIS+5dzvy6fE55+E2SESCcXyd\nyv1UAyKpSLUcbBVQqdvPd3PJpV/bnaXD/b2Ohf/lgK+5TOmoki0q21FUXXLn57hdp7+R2y4okv0q\nkOvS19dQ9Lss07jhtBH7aXY1FuBkjDVURuD38PeSpTkE8zjEvHOYfXeYX97nPdc115lOf0y68aoc\ntTKC/nY1JNrr2TzIgrqKPcXQWyp3ek2ZQmc6wOanfSihts3kztcIMQZSUi4u1iwWC0KA/f197t+/\nz52797h9+4jbt2+zt7fHarVXVI29vX1Wwx7rzQWLxYLlYpkXBYkwpQ1DnHhx/Jxnn37CyYtjpvGc\n9XrDEAOiG5aLBQBjVzEt9SqRbOJQ1QfNJIB40hLl6GDJQhKPj085D3dIbLizXIPA8aSch6HC3hCI\nYYHtFpB3oPY0X4YIKiT09fc1jbvHYqgmM0DVerlq1hN5nkA1X2XDQbrxuAFDwK7X9kh+eiF+hTYv\n565o1q40aLrA7hZ+UCVlxQz+dEcW9lvREarhWQozoJxTXY02ztEZBJ0dour/LelpZRLaErz3rzOE\nbdtOqXfbHT4U0tbRzvZNbcqPfR+0fXFZeW28D7XBfsws+A2nUFWmcUI0sFytuH37kLfffosH9x+w\nt7/P3t6KcUycnV/wySefcH5+zrjZME55q7VYAk8G3LW0v7/P7VuHHB4dsn9rj8Pbd3jnna+wWg38\n6EcfcPrimNOTE44//YiNGShDzFDSoWWpOk3dJa9iFBs9FdAg5K3u4dbeguMXL3i+hlECg1xwsJp4\ndr7mIh6hYZXtI0q2LJslPDsgI3XLtfzuwj4vaJoqipj5281aUhlYMyFzaQisXd6LJ2qp7VWDw257\nqS7KnqgKQEKbVaU098l1SM4g2vlQpF+DKrV5Bk1gWTPlM/E3pKAW8NysnszVDybZ8xNSK8LdGF1o\n3VBA4/EqXqyQVQjPCJYaRhCkeqOq2uAbJbdxELVPWu+Deh18ZBpbS9njwzvcfgseoO7tFa2L3a7h\nCq9H5iU3EqbUba4SRfJ+D5pI04SIcPv2Le49eIsHb7/NrVu3SClxfHzChx9+xHq9Zr0+B0kshgWL\nxZJhiAyLRY5qDBMxnuXItLBAVVlfnPLJ2cd8/LEw6cBqb487d+5w5+iIg4MDvvS1b3Cwv8/J8ac8\nffKYx48/Yn1+gqaxwEpvQ4x5H8gQsJ2I8hxMzUQXlBjgwZ3bnE+nPL8AUI7iyCLC0zPhIqyMqMtW\nttRkqqYKFNBohsJC5BSGkD9WFcava2FrjXeox7akulAkcDdsvrDDVKsWNOdVoPX5zhAy3G8huqsT\n9Z1m7rqxsJQtxNFKwz5ZTCsb1X5Xb8slkjk03+cBbynkOeleh4wUotkV8r0mTLVt8JUbP3PXij+6\nqBliHD3XJTQp4Vv6NbTZMIStsWqNq2WcW8bRIL4rymvBFHauiFTN+rQqaZy4c++In/iJr7G/v8d6\nnDg+PuYHP/gBp6enpJQYhiGrC0shRiEOymLIBCqaEJ0YwpDncFLQVFx5e8s9lssVcTUQFwsg8fzk\nKSfnxzw7eca9u/e5f/8t3v/GT/Pe++/zwfe/x4tnn/D800/wpB3Fi+FpwCWS0mRjpwW2JpTFInL7\nYI+zszPONgMxjtyKCQmRFykwhgVBU5WwRXRKURdylmDNKcbIVg9146YLeltqnevXM4ViwJK5hMpS\nuNjKerndneft9vv6RK/Q3IijzF9t1Kq6OKq4ma2NWtrcS7XKzlpU0xzSeqyF2m33FaNfd+H2N539\n0iLZoib4FaXdV1yrHnuTl8y3D+xd27OLm8fszBjVLG3Xru0ZoYpW5tAzhsvLa2FoLDzUMyKnlPc5\nGEfu3L3Du+++w9GdI87OTvnOd7/L8ckxk02m1WrJcrXMtoXoiVrEEpvmlW/REmtqgqRC0IG43OfW\nrUMOD+9x+9YRw3JAhjMgu7VSysbFEAObi1M++vics8ND9vdXvPPee7z35Xc5PXnOxx/9CIBp0hzr\nL5k4s3ssVWgqklOrqXB7f0mQwLOTNecTLGXD7ZWwGZWNHDAmWMkImu0K4vsfunRDQJK9V5dWjfTJ\nBtNMXraNfKgSV1Szi01torldIf+IBvNsJE/9PhlqsXO9LgaLVaI904ayITotzC0/oyKCXFUtu97X\n45UNaSEoEbEkp0I1NgEtgXTEEszq7t+1ucyVKPtJmlSADTjquCXZ4xrNu9DGNljTzAPjva5FrW9l\ns1hdijG4nJu5VzLflZZVq01fNIits5SIt4j27Ly/R3CWkFHITTbSfS12nRYJaMqbf2b3jrC3XPD+\nV7/K/ft3+eijj/jOd77Ns2ef5sGMgcVyUQYmpcks8uZTD9E6wTpCA+OFMiwjq1t7HN29x5e//GXy\nst3AxXn2PqzXx4ybNdM4QkoMQ06FpqKEZeTk+WP2VnvcPrzN0Z07HN17i9XtIwDu3X/A8adPICWi\nbdISRCAuyNmnFdHIUgOH+0sSiU9fnCGLgf29wO1bCz5+esYki8zLXT9004GSDVo4OUSbXGrLnzOj\n8GOC65M1YzAkZGqYSDJ7Q8ICkMhxCil7MjTkzW8y3wjEYtwk94kE28zXtj5vebxLpWLsG3BrWXbv\n5ve8IxRgEcjJUEPuA+zaSladkdRJQWkgss0ps7toYXZGOFrPMZ5Kc0r90qpZYDYZ9zwE4xCSs4lY\nujl3Egep0aOlK8zGVJPJOuEa0Yracn2FkIrqkkJFCOU84zTVlt1iBylzwDdcLu3V3C95mfzlKsTr\ngRRM6iTN0unB/fv8xDe+zosXL/jNR7/JycmLnJRkyMa9suejc2uqLx4UmUYk5q3apwSTCrcObvOl\nL32Vt9/9CiEI5xcnfPrsI87PT7hYv8yOxZQnQrSQ1jTChaXrkpj1vJeLgeefPuXj1ZLDw0OOjjJT\nePjwd/L4o0M++OH3uVjnpeDDEEkqTJKQkHd2lmmCYeRs/ZL1ZkSI7K8WTETOR4WoiFbXkQuHsodV\nQa7SEEEqki2nrE/WN05ACuZurRKqXt8JRO/TYGIu+ZRLJRahUEsJ7mqzNvZFrd7VjesMgaI21JcR\nuM12P9ZK8DpzKntwd6c2p6khgy4+QNwwS5G4vfrk5/g3KbBdPGeFuSCrPiY5zX3pT2tz+7k8S70L\nSo+1dgtvh1BVHJXUNV2b3zKVd62un4V+rHYiq93ltYho9MShIQbee+89jo6O+Pjjj/nB978PonlV\nYcgDKiKEWLMZD8PQLQ0WW8CjKbBZC8NiydvvvMfXf+IbHN25z/NnJzx9+jFPn35ECCOLQYlhzMlS\nbPWfCJbpMMPuIAFRS98xJcbpgs3FBafPj3m+/wSATz55zN27RxzefsinT5/w9MljzjdrNA5IGHOy\nI10QJSHDBesJzseJZYjsDZHjszUbWZH3UYwlMKXQUhlrqfTsahfBbAvR9kkIhSFk9SWQtzRPDVOh\nSvMQskgCOhuBgifuioWg8kyrerD0BLCDM7htASfyVlWYMwa7k5pULahhhsELw5TWkFhlpi/kyjaE\npn60Kx/txlJ/Kz3bNKTz3ojUlZGNCqFGoMn6LtSqFs6uJXo0WhyLe0AqpnBvbJC2HQ0hK3l+4wl2\n/WD7GUv34vJWrB88qOxqx+SrdUk2WYmXqxVvv/UWB3v7fPe73+X8PEvbMiB2Xg1nzq9pSribqpV+\nY4KDg1t84+s/xVe+8j7rzQX/8Df+PsfPnxPc1hAjUQKRHNU46Wjoq87AgCCaA6ME0CkhQYghggib\n9QUAH3zwIad3Djk6vM07777L3bt3ePb0CZ98egxsjHwDMShxMRmsG9hbRPaGwItzGGVJJogJwsI+\n5z0km83pstQKoXZCJZEiPSlHGsOdH8m6A0XPbhfHSCBJjqVwMhObhGocU2zHbSSaRuDP0/ZOjTZR\nIwS9DaoZ3YmxX697WcjozKPFIA3DmYxBOTT3hKRlqnt6rVTh+k46MI6TNQAP625+oyIzISDRUQIW\nNOb7c+YTnTEp1ZORHyGZ4ctQ20pePTpHOTnISK2dY+lDkcwo07QroVp/l+yO9PZkqJllgJJEdlxf\ny2thU4jDwFfe/wrrizXf/s63SVMqVnxpoZL915RyNJlIWfewXC7td2HUwJ2j+/z87/5F3nrwFt/8\n1m/w+PEHrNcnLKMSF6u8gEUhTUM2ujUTrjVCZeBtA63NBHEC8fMSPHv+gucvXnDn8BZvP3jAl7/2\ndW4fPePp8Q94dnwMLIlxzcG+cHE+orrk9sGCKEpiQVoMxHG06MQIujHpWjqsvAfTHXPcdTZoqiQI\nQnJbgxkj2yAlXxuBEVw2ss2gL5jUMxdxN3/y+bJ1jas8Fdok1NKlOSNX0NCpDiRFk5pDKL8n38Wu\nSU7SSvc2JqG0zavp8yVoMai2dgK87j6jxLtj7lXw36QKL6SsmGwNhapadHfx+dLFY2gx6opMhTFA\nv5zZxVC+kyV6McOjOKrDdr+q7pryjO6leb3KfMm699PuNa25vFKm4Cu8vvrVr3J6csKPPvxRtu6G\nvPIvTdkgsguSAngiCw9ISilxfqG8/9Vv8Lt+9ucJRH71V/8BHz/+LZaLidUi5I1UVE0dVnKgj/Pu\nCs1bmZvcgwCdTukTBGAx7EEEDcrJ+cjFR4+5d+eCo9WCL799jxiV85MDxnTC+uKUsDlgtTxgGSfS\ntIbFAeiSmF6iCJPYgiS3F8zb3mXciCATSM62oCWiUUBCDn4yiZjSmL0iZOaQJyodMagf9wlW9NqK\nSAI0yAMAACAASURBVFqxreWIFrsAmJS2RUqB8rVTF0pPN7aD+tvOx5V61+fntviWcqVWDuVFSJMY\nE0/9zQr6mTEEGhXC+q+Q4ezcclyz4XDSrH7mHAe5TsGEyqSatxysosaSvhijkgnRWFrhEbet2bOM\nn9anz60qOcLFj7fI8TVnCj7yx8+f8/jx4zIwqr7qsbU1e7EOcikSMpefUobZX/vaN/jZ3/W7efHs\nGd/9znc4e3nM/l7MUiMJGjzkV2ugkZqaYpNILb5XDCK6MSpLDVsya2snygazMSJDtkrnbePh+GRN\n2ozcOph4cHSLcRh4cQKrKUISVoNCmLiYLkjhFkEjMWYoO2pobWEWui5mV2oMex4Prj4J8h6QbgDM\nk95lu7mprB87OFS6N1/nk6aGmyuTZFUiFCPmhNhOE3W0KvvIQ1wJyqVlUQ9S9q5MFt2V7QheNWkY\ng6FERwHWeDVYXHXu1ICCJua/QDyLk5Cm/zqm0LDgDlxYy4penkge8mwVyipmKCwnIc0CMFNvfE7V\nJlSm0PSeL3cDV5OcyPPFk7lqpEULncExuzZDGUcpjS3rS7pYjb68UqawGPJagiefPCGGWCBijJES\nfYZDwzpKBp6pBhNlAr76tW/wi7/4+/joww/4h7/+y6BrFkNAWTBNCyAwDDZgYLEMOcADNfWrdHIR\nrsUaL5KXSocY6spMZwphKAtmsu1gwf6t28hSOVk/5l7Y8P7ROZuF8LWvP+Tp8Qnf+uEPeakbznVJ\nYMjZoBcrQloz6MgoA5I020DcAl6YFc4V8masFncgPhmTFlemE6QLt5A8lqL+7j+6AbHqy5U+ivZv\naonqVFGEX09lAr6mIkd8eAwJWJBqtitMMBn9lnhEq5fbk2pyGOz5mZRoF4V1xEFxUQp0bl08oCv1\n4saxYJBKWsXZYvMsiZZ9HZwBaQmTNtTZ9GdhVeU++RUFQxDZBTuJFnQGVWUA2JhNoTAFcYLPCM65\nS+dAteek0PdNEBoG9JoyhRKo65to0CbLzIPqkngOFxWjDBWQyHvvvs/v/cV/mieffMJv/MY/YL1e\ns79nKxtzcgBEYNLEEGytQHPPArA6qWn/hJJMoyTdMJtGRQoDIVqCWfeOSGJiydl6D9m84B1e8tZw\nxvDyB0zrDQ8OXiLP14zDXdZRWMWAbm6zGc8hbgjJI3tSnpCSMvzUQEyx6rdBjWFhhGIp4C3i0Zlo\nposhA1v1dPaNFZxKHG1vl65pOIvr87nUfAyZKAyZJEFDhsZZhchoLRU7gtkSNFWPBI4W6oIsyjSu\nW5io55NwKY+pDg3jCJb3wOuTbRjOGVuubwyobG9XcFKDHmm4hVpYufdfE7Y9m9vtVIrmLp5EivqX\ntNnAT02lrokqutR7rkR42vrSXoXOWKw5aW4yb11BVlJia19fpuBdGGOF82KMIEuCim+lvcwWd6gE\nhMiDe+/yc7/nF/jow4/4//7+3wW9YLGMxuFNBxMPQZ5yzEOoWZXtprCzo2yimK1DYo51DzFPOHeP\nxiFHVPrer6rKxcVLxvOJxeo++7ePeP7ym9xZPuXlk3/ErcPbDMuELFesl3ucBxjCBZE9NnKLC70g\ncWHW/WiDGoiDWkbhRY6gjOQAmig5QEpSXkxl2ZDy3g0jWYqNZas4h7xS5PNkra2qQyGwCrYpLNkX\n2LhEbNyn9RqqpNfqBSmvZLswGBIoS8CNWMtCJ39vpnIB28Y0ClYvrjytWa2LmG4UnBbDN8jLfysL\nR4Xcl6WODcMoCsA2kfUKr6MXj6nQEj+RpDKFBKTGOAxuP6j5OvJlmSm4R6qNdKzj1qSga8dRdte3\nLa82TkErUujzCOaS3atpdqyOVpqUu3fv8tM//bOcvjjll3/573GxPmW1AoikSRiGQIwDMZqm5pCU\nyuHrunQz/qilJTcJ0q2bL/YEl9TOFJaGFJSkExjDCCMMccndd3+SxcmKzToS05p37y45WyqTDJwO\ngZOzFXFKrMIpRwcHPDuZmOIe6wRh2EfigjgIwyqwv7+ENLHerCGkzIgCZYFSCmP2RIjFbTDZawOS\nX1mKBIJOZf1E7oRQoK5qJW5f3RmdQblkRvMYpap+aCPBXXXBiF98KWQ7xuI0Z5zCpPqEb+SSGmKy\ne7kOXfaB1M4gJy0B+po1+0uoP6bORVeUPGrTWaHU87xfzGiDh7LvIrCWKUT7eUqUnI6tcTTZnKuk\nWhnzyFS8GR7A5vWatBeW5WrL3jTlDMY5O5j3myoaHGvsLq+UKQwLJ6g2yo0SjNSW1h1VBfeCn3n4\ns4gEfuVX/h4vXz5juZfXHYyTEiyq0VNladOJhTG4ZblIAJ9UNTFnDAMSBsvTl9+DJep09SHGSIgC\nQYkMxGGBSGQ1JNJ4xsWzJ9y/+zYL3TC9OOH0xY8YlhvC6jnv7D1gs77Hedpn0n+EjD/k7uoWT1+u\nODx4wHL/Lip7jGlEFlP2tOgadEQkkgOeHFiZAcr80yqp2CJypONI0TLcfpBquI1PuiL2NSEWeJPD\nZpOZFp2xVndiGatQw3mFnKUqB09pjn9o+YJJNQcaSigqiBYLfarS1ewJnvDZk4ioakZNdt/k4+lI\nomT7tTrRPr9MCnzBWXOyzYd6suFPU3lKwrlunrY053aeEAJjghQ8oazfL5WVlJlR1EqpZgsDYt4b\nsp3AbQwtcqq38IDrek9MDZrU1hW9tkxhMKYQLXw5UtSIzBhSJ8mzBMlppSQEfufv/Gnu3r3Pr/7a\n3+f4+CmLBYQwAjnApk1IWhO+yq6q5InofSh5wGL0yLVYlsqG6IihHgOKSuHLaqNtEjLqxEqf854+\nIX58xv7bRxy89zNcvNjw9Phb6LjmTvyAeGvg+2f3OB3uc/zkGUe3XnJrf0RD5OzsAhkOmRTSZs3p\nyZohDsQhwFQXCYXkaCFvSVMt8FN+pTUZLWR9vFsc0/nyG6lTWIT9qRbGUOD2vCu7mIKCvDNcTppD\npz1WAdsFGo9yzFZ8pSK6AnetPTn01wKlHLW4nm/NSFKyThbTUyWcGjfQSXlxCS+1wh1MoHimqgLT\nqJ2XTi1DcAglEKy9hyq78YbZFLxW6tXw2BLXVev4gCMij2jUgjvUes0Zw2Xl1XofFvnxw8KYghN9\nyn5lJS+U8sFJCkEGJpR33/0KP/VTP8U3H32LJ08+ZlgIcZEMQVTDZVv8GZeVuoS7SaIRY7czkKfh\ncpUiFPWh7kKVVBjiHnfu3CMMI4dnG/Y/+HVWuuZUDzm9t8/R0ddYP3vMQXjG8uIT7h6ecrH/DX7r\nyfvcPvxZJPyIZXyKMnF2csxmc0IKK2IEZcNmE1AJBIkwmeEqJoLtLejSM0NdUx9kDYy48bJO5vkE\ncf25OdSExrbT1zMcJaXaujriguo+S9nzoTVAKWkqe4DWEAf7bNZ1J6qWIdT0bo4kaJYJVx29tULk\nsTWyCrYQrCNF2fqowo4pY0ZBm5fqOrxWpND+nwr0H21RFNau/ABt6lv4kJYn5TbYRUKONnVVt7dq\nOFPIvp5AsIV1yYy2GT+81kwhLHOnxWUoiMA3CJEYytbhuT2CTEIIkVurQ37HN36Kp08+5ocffJu4\nSNl2YNvHBQkm5WP5ng2YUoIAzWBg3D9/d5dRiDWPfwgDMQyEsMj3HIZqU7AXQBgiMQ7ZJTkJmzFx\n/PwFb8un/K53V6zky5xunvNRnPjmp4/ZW9/n/t77DHpGkpcM+pKvhucs997m6fJLnIQFJyfPCeMz\nDveWvNwoJ+sNQfdAJ2ShaNqQUgBdEIkkNkgcMywtEzWBjKDZ2Oibx6pFLLpOXAhezMJvjCIFyatX\nsfsVYp9w/4NW2s9nFOu6wOSJbEFUGVXziliMESQHum6IrFSoTM2CJm3ZTCH51IQ258S6GR+MbLIx\nuaFocb1TPSJxtoxY6GxWKnSMMdjS/tQYPb0dJdaBEu9ZMYc0kYs6Eiw4Kf/mXhctfdeS66QtsVdu\nESQzmyFkw+xkBnQRtXUPoag21n1Wd5sBOmt7U14pU1itcpzC3t6y2BHyase8WjLv2ygGO0EWA5qE\nn/iJrxGC8L3vfYflcoHvabhY5v0Fe8ZgCTc9MadHIYoPehMw4/EIMSJDNAYQCYMhg8bAOGcK0c6V\nEAiDcH5+wUDgk/NTfv3Dp/zhn/8ZfvRrf5u1Ttw5uENKt1jrPoujB6QRZDpH5DF3D4XNRjh7eYc0\n3kUWC9b6nL3FKYlzLjYbpmnFSoZMAGmEcJobwABpgDhlCSomvl2vNlGsmIHM1bMyvWkmu03FWZSf\nF50d9mugqmGIqRKmP3h1igDAvQ/ZIJZjmEpy/1ovw86eTkytLdqhF6+H6+szSL9DMM6zLuHtdS+F\nqwxNmxOUurfKh6snnnrNQ8n83ZFBuU61cRG2/d7Xyc+t/dFU1SJHvA+LemTqiDNiHxBVUx14jZHC\n3t4KgNVqWSaKM4cpjY1NAdBAmgJ37z7g3Xff4Xvf+x6Q2D/YY5o2hKCWO9FgvxkJpRwT2+WnSb7p\nk8K/NzsARSf6diMVf7VIwdSHHKdQrwcl6Ybhzn2+/fFvMf6dX+Z3vHuX/YtjNiMMy8h4cY/l/oKD\n1YLTJ99B0hlL+YjDvSVT+EmmzVs820QIE8gzbu1NLAc4ORfSmBjiAUwL+30yBrfMerk44Vw3CpUh\ndN8LBPCFU6ahS49wi/SWDEqyfl+9OtkunC8qDoNibMxRqDX+HwoaESdsLcp0CbumZQjtf4fOUHIS\nuhvFGVQd8mJfaFteUIq0x/pe6ojYGYSpDkl7xpC0X/uheM6Iao1w5FE7sj5rSlMxrsuMYURxW0xF\nXq4eOVOYsS4zMr7GSGFh2ZEXi0XHEFSVqDliLhsdBWEgrBZ86Utf4tNnTzg5PWaxGkhpyhJdahCP\nxyAI2K4+toNPyAE+Ja8ilTl4zn63H2QpSZH+BLFdo0PHLGIxlg4W6SgMQ2T/YJ+XZ2dMYWB1/6t8\n53u/go7H/I6vP0CPj1mff8ByuMs0PWDSU+JynzCdsxj20cVzbt95zHJ4j5MfCuN0SAobVvGEYThH\n4kRa7zGNAcYDlst7bPSUFBMapgp/ocyu1uDaLTUvx5Od5+8myVIrjaMZGp18tEMS4rqyEbOH9iqN\nOc6ZggUvZbtCqz4Eajr7lA2ndm+1VY9V1amIw6d92QzG82CIMwxDAIaUsh5JkazWoJ49WoPUUSRS\nCLQYBqS0rGEQaqn+MkOY7DtCQ6w0CEILowjBPTu5TDr5yV2xlRWVIZgBVMVWd2jKSXB0QlMqjDrb\ncKbXmCksh/qu2RXpnTNphsN5Auftyu/ff4AKfPr807zFeaQGEQXpt5K3aeXLowsRNyihJjU120Zo\niD7WmASJHjmY1Q4x9SF26sOiMI3FIjIsIkeLyPHpiAz7HH7p63z7+7/Cy4tjfvIrd7m9XHNy9gMu\nXr6NjofsH7zPtP4B6/MzYpzQ9EO+cn+Pi1P4/uPIGO8xLiJ78ZR3DxPT+pyLMyGNkYszYTi4zUV6\nyRQvwDY5zYSfULGNQBpPTr9tXlNKzEKLGBSPlHQC9MjhwhS0qhv5EZYrskRA2ml2Bw9aqu6xQGU+\n5DpIKsF9HpmYGkOjn9vCav+cNC9Myq5SaWm3SPbaZj8us3vRMwqzMWQjKM151Q6Qu8tiMgytYmqH\nw6rQ3VMLE82S3NWAymjKc4ohPDMawoaU/n/m3jxYsuu+7/ucc+7tvfvt82bDzAAYzAAgCe6SSIq0\nlIhaTKcsJSqrnEhxJZEVV1RK4oplV5yqpLK4KnHFVqIsTkmxK07sVKkiRy4piqyNIilSXMQdIIEB\nMMBg9uW9eUu/Xu9Z8sdZ7uk3bwBGJXtwgJ5+3X2Xc8/yW76/rU4am8ZaeO9R76hW+27gvL+JeYhv\nRWyPlCjEcOf4XpsiHcapwEUMzlkaDcXa+jL3t/exTnsHHmrqmlcFTiqCI1MlapXiKBUinqfCZldK\nUUTgMhUAOfRSKkkKRVFQFCVKFRSFQikoyxbtpuP+zjZyZY2ueJo7t19F3jngiRN92u0pSm3h1BJj\ns0yrJZDcQjDBzib0B22eO3GCjmtz+UAyEk2aBlqTA3qtAtUa4lzF9m6P/XEPtMO0LLOmNxdaFxeZ\nBRnBMbdAHGpnrry5GocNfvkR7xOLR9WxEWnXx00ZubAllUBztRgeJQQbOV36z2Zc2KZ7Rq+96LRU\npyVzC2rSgoi/sHkz4uXCRnb1E7nsVUsOD8FT8ueP0kF9+URSo5dFrbOQmUez6yV8xF/VJUJJ8MhI\nHQt/hpgGETx/U1RK3TEjamBW4AfCEyuT9tTD2tuIKCyKtcb6yszG+AfvtDtYa5jNRzSaRZ2vMIQ5\nJoIQsYTI/bMCHpKILUSiUetgiybICCwu/h2tGyqCj8UhoLFoUJQlZXB5VoWgVTpEucyd+zvIpU2a\nFvYPbnPtvubkUoNeZ4pt73EwazGcLLOxUoK4wmS8j53c4kS3jzve4dYNyXDWx03mrHbarDZnqOZd\n2u2Kvmxw7Y7l9v0K0XW4gcG1JEVDMddVWPcBwMtWz6IPSBLA/XgEvT5jQA9tubrgP1OrCTicjS7U\nUed3h/4jAJ/U4j1BBEaEjVZHPdZnZdIMhzYaWV9E/dy5mlEfLx44L357JD8VmapwxDF5HIQLamxO\nTV3++QG1YMFYfOTmjcKbIwKKMeQsfw5DIgnx2V30ATILEsjh9mhNkqXI3r0ZK3Yca1PgD07QanWZ\nTCY0GgUxbl8FS4ILCUhlXjGYSBy8FKGSdOBNk7X0nB2f+yAo6Td9WS5IBjJaJpT3cpTK4yKibPja\nEmVBUQarhRBoKegvDZjOHKO9LUSnw1QPuMuc2b7jhN3j7KkZyx3BrUmDg0mLlWOSonUDhgfM59fo\ntQXrg3X2rzfZ1Bc4pgVO3eK5597J/Tfu8OprIybz4+zd36UpRrROlri1KTM1gUKCKZBCIcQMoQRT\nN8MvKZOJ7BFb8J+kAhsSqwoBzvpqBp4DB+6sovnSf2/DZkmuu+G6MYdBAsWCGGvD98nylG118EVw\n4tq11mVSHSSfvSR9BLtD8E+xErQwSazO96AIxMU7V7jEuWMqtcjRI1FIIf0yPJuNMo1L0Y0Lrh7h\nxDi6xgUyK0LdCLHozi9z6uMWTa+5C3S8tK8dKvFuXvGpoit7eH5i7fNAGGzAE6wPhuPtShQajXLh\nfdECYcLGVUhRBAuFDfka6xDrmHkpcfo4DPnnJD1EzifI0jyGxSaRIkgCRQQNVXJIkpFISBVAxdpZ\nCaBQBUVZpnySSfUI1aTW1zaYT4ao5hIOTTUbsTvZw21Bv9lj87ijtzJjZ+LY2hKcO3UOuIEcDmmq\nKWdWS3bvGTb6Xe5evs4T7XOc3fggN7/xJa6+fo0rwzkVsCSEx1tKhTaGYrmJNhIhDMh5kHN9n+Pi\n9sLSYXGgHq/o95BznKS/BkR/UQWoReoFB6HsrebkLhGK7JDwWwZZhC/i/BE3S9TxD/U+ZkeO0k4t\nfecSRk5U6vPivRefccH2kckqCcY8PHwL5y70LZ3lW8ytnCwQmRQTMbb6XBDWeqtaAnEPK3UEwksg\nQDaBjBHkPVoE8u1tpD4sEgXrDDiBQCFkQVmWaKMpbUFRRK4v0VovhDHHCZB4Z5NYnEtENDh4POaD\nEomCEDWeUIONZHUD5QJu8SCmUBMKIUQiDEI4Gs0W65sn2Nu9R9Gq0Cj0bM7BfMTeQYncGtI9Llhq\nS+7emDLsLLGxNMBNpigl6MwmPHHyBG5fszXd4rnOgNneZba2r7N7sM8Ll28zs0M+9szTrHd6CKVw\numC6P0E0K4zUWCEy70FxaDPl+mrUGQJ46yKXZ1EMdvV7rjrEz2kTZRpKDAZKnDa84zL93M+Ktz8E\n8T86JS2oCoHDukSUDmEeb8IN0zHZuQ8QltAvArAns6svhlKn9Az5mQDBjahu3mRZP0MezJz3+Tvq\neyRWRxCe/JhkdYgxRUc9bNYebexDkBDKzE+hJgw+q4+3jwusM15Hl42EJAspkKoMEZAR6RVpGqQQ\nteSQdOS61Nui9UEgRZQEMutDADFra4NMDk2q9IFPQC1RHAIrPUgJUlqWVta8JaMokc02o+mMmbmO\nEY47t4d0teLUk6s8dmKVajZmbzqhJRWuGtNtwunuKjcrwbbosN84h+idZVZ9i7t3b7O1f5ehMLxw\n5z5nzjUYtJaRjQHXxgdoN0c2Wmgj8W7Oiwsomgah3mx1shWI9RYjozUE0Z4Q7JSU5gWemwhCLmEI\namIUScKi403tumSECCnpooQQzhGeP+bgoe+0O5JD11tUJKnh8Baqgcr62ORNG9ZITrSSJJTdnvQW\nqVVwhRYkK0Q6JyMqadSihPAWBKF+rmDifEASSVHjibhES4+zDmEFuMMjULdHKykEP4VGWdbcJb2C\nl1uw5VirKUN2pnxBKDi0yUXQn2vXWhlqMgrBQrLefDBFJAphM+eh0kLVpkmpipBTYVFSyPuQSwsy\neDj67yUrK2tIpRgOm7SYMpo20HZCVR0wulmgiiXOP95nXh4w0oKi22W6O6ZRzGi2Bc1eh6Vzz/LS\neI3n5JN0+scx80/TUDOMU1y9f483rkz54Q+8h6bYRXRb3NnpcH97QrnmMylIocBprHFHbgac8Lkj\n4iYKBXqwgSsRFqRzkNS3elyjZ6qJKY9cDEkXwRSaLWqRZQNa6EsgBykyMur+dVh2TDxEFLvJsh2F\nrSbCz5FIxHURLSrxkWsqkfHucJ4sfCSqDcFnlmBdCff1x7pD+EU0b9aYQPIVYHFjH2aIh1ueUiA/\nj6j2CZHTofCeKSguIwpED9O3KVGI6djKojxyYGIhUmej+GoCd1q8Tm5B8NhATRQgiHBJKjiaCnv3\n6CwaUuauzTI5JyXLRZarMfYhr0KcXsq7WwtRUiiHlAUrS0vMpxOMkvRW11ByG4fE6AZbO4JGa8rZ\nM2uIqsVMb+EaBdPZNidWxyhXsXyszcZjS+zNK5565gmOb5b0d6dM5o72dJcOPZ48OeBUd8rlm7uU\nVYNqe8h0f4TsNz0kZfwijxmpYssDgPJkKxGwTSHSkQu6kHsCMnXEiwdHWyVcEssTuChIjlJ52nmf\n1ZpAp1y9gch0/CilpH2RKUQP2WTOgci+T7JNps8nM60If4uoThyKfXD5det+5d95IlBLR3W0I2l8\nDvf1cK+PVA+kl+TyUgmHJiLegazH6Tkf1h4pUVBKLbwvDE4UX0PlJ5tES++UsgiM1SZIifKckIjZ\nuKRG+P8dOVfIrxHVhwfjG2QmPSy6TScV5DAxCC8/DZJCedHdWku33WHz2DGuj/cZyRZjMaPRbVO4\nDnNtub41o1F2eGyzw1xUSOWwbo4ZX+eps89y7Y+vs9q9QDUec2xjhb/87/0onf/7i6iixVObcGrt\nGI9vnuPqfsWp3oR+s6LbaXH5ruH23hTX9diHDubejKcSl2udQiViDNKnK0sutf6flN0sclh3+GUz\n9SRSm7AdnE8z56Ow4/n5enbZPNep23LfivyyNaJYezbWZ0epMa6TeIpYkBRyghD7I6zPAhbTmyW3\n5PgoYSzeTL+PmzLFQpA9p1i853fS4nMLITKPy/igpBiTdIuFPjl4CHOER22SLNTCe06lI0MSChwG\nYUPNJhfDqcPvInLnmJeGZNpMOAK1XuhPim/iEF0IGWqUp74i4goxICqqE3iTpAzJVyB4rCmJk3Ih\nDSDWi2uF8BcWQmGcpN1d4txTT7PVNZhJk4Ot1ymkjxg1Gt64s0O3XObE5mkK0aVye2h9wLGO48PP\nnKFTVkxvvchBH77nz/1LvOP7PoBEc/DKC3ztU9+E/jr3tvfRpmKtNUSsTGiKPtza5sZwH9d1NJVg\nbgUzBEHgwaKQAStI+r0XwPLaKsGV1i8uawXI6GyWeSrGPIxWpt1TWw5c4vSJQ2dp1wBsAo+iWlhb\nABA22Oi9a2/ifGHsbdyguESw/OYLfg9Sps0Ylt6iKuPi8Zlenm+kDBNIYd0h+jJmpY6EIGY+inUw\nooqRJAX8s9sgieQtPiPZ7ZSI1/dDI4UIY+WPEgicciFIth5TEdy6nV1c9ofbI06yUiy8x2atzR5a\neEKQJVxRCy660epQSwe5fnEU1X4YRffWuuDOnN7DJAYX6phrgcwJCghZnP2iNUEMNtYhlXfC0sb6\nzNIhJ58S0Gh1OHbqCYbb3qo83d+i22x6cVyP0IVENno0i5Ky0eXgwCBLyfnzZ9jfK1jvbjAa7VJp\nRXdjFX2ww85kxuaFc9iDCS1dUvUfozNwzG5v8eRGj165z7evv8SV/dsMmxZTKGTlfIbhOA74hV0T\nTT8Z3ipk/aISnh0pS0o04/BEwbjc/BUXoq31eimTx96iuujS5k1rAe/DH6WWmI7NQSC+LmEE9ST6\nPrvMndcnq/XfRwtILoVEYpOkHWqRJUk9Ml83GSEKBC3RpqgqiPy6JKYns3WX7hmPyhh+fE/9jd9l\niV0faIFwinB/m1+bwAhjau2HtEerPgTrQ3yPTWbip9eXaqIQXaHrFh006g0aM1oe3vRJYshE1bxZ\nbK0WSDJC4AdXSQ8WEpxHnBBJofYWBkHM24d1HggTBQ7Qwod/F0ogi5DNSUlkY8Dy5hMoVYBoMx/e\np1UalgY9hvNtbmzDyY0VlnpLiFKjpWS57y0JS+0esimg0UU7y9y1WTnzDIPjM24//zLHBsd4ZWKp\nmgMK1WW12Wd0+2U+svoUp+c9fn/3VeZKUOAozOFRqsfQObGwuOMCT6IrIs1JtKvbbA5rx/+om9dL\n1QZ9IdfX87nzHo1RVK/F7gUgLetvTROiipLr07leL7LnW9Thj8IlXPZ3eppDCyhiHbXUIo7cuy77\nPRvRo1sAWuORyQqTgImgCiQJjPSem/ijUpgTp4e1R6s+SLnwfqQfvmf9iShI57I08P4A73eQEYV8\nYR2elUOTuuBZhgvh0z5WIoVaZ2zUi52yRsIDyBOj26ypiRd4+mStAGdotRpJZLXWhJTiCic6d5rJ\nQQAAIABJREFUtJYfo1Ad7uyPaMkZLTljpifcvrmHm1d0n3iSbqeHnhvMdId+r4Odz+h2W6hCIhpN\nVAcO3H2GOweodo+l5RWa23vcuztjoJoczGb0Wis0qoJ3tJrszCd8fu8687ZEh/oCmYJOyiHogsu5\ndWhridW5ZUxNJjNTo4vn1XMhguRgbIhrkDVYHD0C430OE/Joq5CAsXkgj6zzLr5ZC6poyrOAVwuj\nhOHVygekdj8CARfSWvu5tfXdc4sAkML2c7UjX3sPWA8OYR5v2ha13owI5H0lEQRSngx/rJAuJcpZ\nkKoe0r4jonDx4sXvBv7rS5cuff/FixefBP43/Hy9cOnSpZ8Nx/xl4GeACvhbly5d+s23um4qpKJq\nTCHqW2m4awmP6N7sP0by7gFChFgYcC/1Zps5/ZEdE4lQEltFYpQ+IpKkL4LEWEsRLmSsTXVF4vWi\nT3ktyfjrKqVAeXE2braIjTjpMK4A2ljRBSN44sQmveY2u3uSqWzjphOqyYhes6DRUFTTO1Bouo11\njO0y3RU0lpapRmMmuyPMUCLWTnJz6hjfnzAajZAbKzSbbQabpzi+3OHylz/Hv3z6PWwdTPim2cE1\n/RxYa5P1Jk6JC0Ngs89pPMMXuYNOPeLRTAfY4PwcCEeY0qAaxjEWiYvFxSsJ0oc4fIeavUeLUg7i\nxXt7q0bM7RRv4RY2qYvfP/AM1MdkWcDifMdr1KH42bNnao5gkYDEa8YxiGGT1hwR5xAz08QnFOAL\n1cogOfjfa2Iapa3sFebIxb5G4vGQ9pZE4eLFiz8P/BRwEL76u8DfvHTp0h9evHjx7128ePHPA18A\nfg54H9ABPnvx4sXfuXTpUvVm1150HkrL4gjyKUjVc11G8ZzPVecnJdPv3dFcJ7+XNWaBMFhnM/NX\nFM98YvOEdxE80jKrQx2/792yrTVJkok6rZBeWjDGWzF8WK1DOJNVSyqxFSz3Oqy0BXp4j54c02q3\n0M5SmV2MFfQ6S2DmGHMHYTXzcQ9jQTVLmlLRKguWTp3krm1ydvNxrl37PVR1gJ5UHIgBTpXs3rhH\ns73Ese4yP/G9n2D4ld/mtdEt32dLKOBiE04Tgd8kCcS5cnFjHxbl81c6yAOV2fERH7DZRk7NRYBO\nHP4lYxQ1cFkLx4eU8kMtic+BAeXrJDKSw1LAwrnp1m8mgKcnJ6lGh38/ykJx1D2z7xbx1AfXd/rd\nZdJCZHiRcLxJdGRs34mk8CrwY8D/ET6//9KlS38Y/v4t4Afxc/3ZS5cuaWD/4sWLrwDPAV95swsf\nVh/ytijiBC4rjtjszgcyxTTuYZ35vx8CxgghMKLWg52LAS2Re/i//bqJurGv1KONoaGKlF8hIdMB\n6zDGLGAeQgqfQNlZXyymsijh4/0L60BaHCXOSrSuOL62Qq844Mb2dVpLM2CGKNqoRoeJdvRVg063\n4cutTfdpdwfQ7TKpKoR1lI0WQyyzfbinJzx28T3MLlWUsstwv8Xq+iZ3b9+hqQVDUfD4+gl+/B0f\n5Z88/8n0HCLktKwrN/mxsCGoxoUgKRPFBynCJk4UNb1EtDoQxjcQlzoSMMMe4pTmcxw36QNTWROC\nKFvmHHlBzD90FgTi7lytnsh6/cQ6JG+18b/jdogwLBCdiBGEvw/f8qF9cEEGyc3fcdySBJzn0Ajj\n5Wq84WHtLYnCpUuXfu3ixYtns6/y6RkCA6AP7GXfHwBLb3XttJGjFHDkQVDHggVxLdVxAMQiUUir\nLr9+HPl0kt/sPurakeqT2TCgQiSzYkw64hAgLM46lPWTYK3x2Y9C77U1aFOlbgvnMBbsXCMoUdo7\nYEkBykqfTtF5JN5WFbIs0K5Be+U0olhlOnyD9nqbomFQk2vYkaRqFsj1J3FumdH+LfrNLjBAiBJT\n9NifaaaqxfZwyu6tN+isLLF66lmEdQzvbHMwazGVJzioHIN5k9nVbR5fOsW//aEf8/3WDimb4CqE\n0GgsWjS8tSUV5gkLCxAumBuFHyMhCCi9SFmAEA4jfOSe98HP8HDp0kKNMnzUy42I832I20ZxstZh\nwr+1rc3iwnliIWjKq6BRCnIJpvZl2z2oHBhrLQWFNZGrryIyKMLyCVsp3iMHERNoLkKkqQMh6tqp\n3kMypqL1kY45PlZLtHFhxWGo3b+9uuSCihrSrWWEAedjYiVBpeLh7U8CNObyRx/YBfbxxOHw92/a\nfv7f+usA/N2//gt/gm68vdp//FP//p/q9Y6/9z95098lsLxef+6F9/OBfL/zT3jf3/87N/+EZ769\n2tf/h9cedRf+VNo3/vtr/1yu++7/6MxDf/uTEIWvXrx48WOXLl36DPAjwCeBPwb+1sWLFxtAG3ga\neOGtLvS3/8Hf5hf+xi/wV/+bv/oQcSaG5dbFP7w5KRLLujpTpPyLKSoyp6ZMb3QQQMFoS/eR7zqa\nyhZUibqIbMQKWq0WZdFCySZl2eK//Jm/yX/1D/8O8/mc+Xzmr43zqdlUHT3ZbDbqPI9SIFsWURgE\nBQKJs5pyMqU9meCmd5nLK/SbO1xYn9KZXKXEwuAUrY3H6EpBr+izt7UPg00Gm89hxivofdA0+Oa3\nrnDvfkWjd4L1zXMMpxW7u0NuD2E+nbPRbzHfv81Gv+D0yT5Vtc93/djP8kd/8J/xP/7WL3OLCVKt\nIXUToTVGVsyMRmsbXJ1r1c87kNVh5Lnp2Fif6ccag3UOHdSrTDDI5j6CsIGDx6AzFet45GukVjlz\n9dMBX//FK7z7584llcVaCyZE3sYksMKbhUUAVVVI4R89/YwxSRWMUoFxFc6ZGPiQJAUpJbJseFVH\nyQSBxXVmta9GHccq3hvwlq14fWP89YOE8cJ/d4vnfu50XSZTSh9GEjKOy7IIkbi1tBCjIauqAmMT\nQIpzKU3hWylFfxKi8NeAX7548WIJvAj86qVLl9zFixd/Efgsft/9zUuXLs3f6kIPOA9lolIUu6Rc\nDC5NKHL8d8HsU5MF/4UNEZRehciMCyQHFKjFKecW+uCyzxaLMdqb5jA0G45mw9d4AKiqeXp5lN2F\nhLOgCoW2FXZmaDQKCnwBl0JIlLEgZmhTIZVCW0FRDBhrw8gIbtyXDEdDjpcnOd6ds+6aqMkBlRXM\nyi5FbxndbuPkEpXuUpkp23fucnJjg2bTMDYtHJal5WW29sa0Oop2p0Or2aaUJaI0XLu3y/HjXux4\nz+Mf5qd/vMHf+7V/wO68QqoSjUMHhyWf3MNmY+5H3NjMacbVfgrpuPASQoaEqTbp2ofxBK8+xFTv\nD9ftH4YZ1f2q7yxEnWXZJcuKTUwj9iMHuhfum+dZyI6JoIC11nu95r4J6WKiFuMXRgOPuyRMoY5E\nrcettmDU+sODz+p/qterFDJlbXbW52r0lqVMlX5I+46IwqVLl94APhz+fgX4viOO+fvA3/9Orvew\nlk+Cr/8QS4gFOSEOeAJuIuGoOUXKH+FqoFCGghlEBpcTkoX/yCYvJiLx0oEVBmN1kBZ8YJOURZo/\nbSq0mWNsVZ9jha+oTYk1hqoyCNHEOu9v6kwT719c4WSFFjOoLBNbohoFctxkrJf5xu05dwdrVGpK\nOdylyZBm7zFkp0ej3UU0ltGmRDWXqOZNessdhgdT+oMmq71VrtzaYmNtheX1HjtXttAzx9Ttc+7U\nKXrtkp37Biu99qfaT/LRd19gOm7yj3/jl7hX7TErW2jjKEwtPS2CVYIUk0C9scN2hFCUllD924Vk\nvD79+WGiIB4A2/xY+rmsg99IfXnIagrXiWnc6l8SbpAf7Uw4PprH8+tGwhJASOFwxqZ15MOXbfBw\nhUWq4HNEPWwjuhhJmvpWM6j0FplU/MLlv9exICwkZD0awA03eVO68LaoOh3bItd3IWw6cCUZCUEu\nJ8RjIW3vxKXCDyHsNmXQdZ4v1Ak+CJmFjRf1Yj7BCE6FxKfGaYzVPumlscjKi56JKOgKrTXG6HAN\n79hkjMToOdGCMZ2YEDUJpjAYIZFCIwvrCY+pcGbCWrPFkjXsTC3TecHV4YzVfoPmzpBuIVg73kc2\nBU6VYFvMJgdIenQGq9iqokMbi6Sz1GVmLOPxkBLDarfFzft3GR8ccNPNeer8k2ysn2QymgAwFcuo\noeVj7/oE1cEev/LpX+WanSbpyVjtVZ1swbkQ0YizKT4hiWXJ5TwAj6FMXF18+jAFOPxZPPC9yNl5\ntnYWOXsEFf25npm4bNOEPuFF+zSXgXk8wNXDPVNvQrWxutl0n8h/Engq8jOPeFwXB8OlW+W3T5ax\nh0jW1tYHxz2wSBAWKOLR/cjaIyUKsR0mDvmE1H8eLTrF4+Kbjfqscx5RxqAcOKmQ0nOc6L8RuVry\n6c9EvGRqDN9bYTCuxiEwM6hUGmSt51irE1ZBykps/UZ3tXOTkIJCSbSbUimLcgKhBU4JnNNM5xUd\nJdnorzAYH7A7HHIwsmx1S06dPMf92X02xkOEmWDdFKsFjVJS9gcIO0ApTbsNw4MRO3cOcFohtWKl\n0aYqNdNOA1HB7tZ1brcUJ0+cw2nvaj6eWJZ6koIe733qB/j9z/wx90eXUc2KKnjFGRMTtWTRihGf\nyeJBIFPThPOiMpKYCEHwcJ+At2o5YVjwd4nWgXRcEh1DN+rgqJzQuMCBw6wvcNwkKVBHJIpgIVmM\n46+PS1aGADB4qfctNuQCQVjc6LVLX0RKSHhHXTd1kSgsjJXLmO5bdOPRSgpETkNGGv33MRV1FJ1E\norVxYA4NkouCgUhgC8iUpMXbbkUwqYdae5AKYxhn0LYK+lgdxSYCdxHWL4RYoEbHnPphQmZ6gjEW\nb/jx3FPii3FU2i86v5kIOIlECn9v7YSn9lIiFVSzOben+6yd3WBtcIytu1uMneDbN3Y5d/Zd9Nlj\nb7RPc25xZoIS+4yVZdAaIEyPQihss0CMNaPRLv3OGrLSdBpdtkdbMNliqdtGrq4wt1AZnYr93r76\nMvLMBtVc0OYUT7Se5fmvvkzzyS66McI4g8FLU8r5IDBfY8HPkwpLKtrOScBWbU+XIpp4H1wR8V0E\nFDIoC9kxNRYU7xPfo0NS+KI+Pp6S54uM93ORFQeZ0QXJJxL2LPV6zfGDe7tzdVCWyLIpB+AwnikE\nwaclf4a6D4tSyeFj/GqqsbT4a4i4THk2RTpWpCwwOWHIJOy3NVFIDN4tdNSrAIEo4CdCutoK4MXA\nqFsqfESfPxLApaCpYLsNTjXSCr/xAETwDyCUXQ2L3WMXKmXdJVRts1bgDBgzR+s5qCI4iviHGM+G\nKYlsxDAkEmOLTJwLUgfgjERan6YtSitKKbACYyz78zG3d7c5tb5Cv9Xk7njOjrC8eGvKeO44dWyD\nTtFEWF8VShaS3a17rG+s0lpeYTyXTJ2kP1jjtRdeZH2wysHtu9jJAaUy3DsY0+9usrp+HFs2mM69\n+mCs5t7OLrrqYW4POdc5y+wKDKsZy0/3sMUEGgJnKpw2OKeIpcicEymrkHeVBiVjtS2RuJWUMoyV\nA2RA3Q8DkwaBIqnoQR1xESgLjCIGZEVJPe6r3IkHSF6qi0JJZCjBbdgZ6rgBu1hbIgo8YZ1KCM6B\nIfqTAhY8MG1a1z63o0wqWHJBSOpC3a8HpObge5Hqb6QfbPARcWBcChlIGyuAayKXEPDj9yapFIBH\nTRQe0B/9t4fbohqUn+XdnONZ+carnUz8BNtAEEQIy/a6hIsMwnMIG8/1V0aqsM5CUIn2JjZtKnDa\nYwaBcM2rSbifQDoVVAdFpedhUYggIUQzkXdiIvbPGITxyViM9aDm9Xs3Obm5xqkTp7m1u42sNFs7\n+7SM47VbLZ57osugpznYm7K0vMLurmFn+xqd2T7zWRsxURTFMu3OMuWgz3g8olFucPz4MtX2lJlo\nM6oksig5dfIkAKcffw+NFty+N2Xegt3dERxotr+1g1IbLF9YZs/uUGGCC3gR0p7HuI8A/IZgsgUc\nKHndBWkpLVibfq/nXAY0389tFJGP2NPp/bCGGVWMGnM6ui0EKUU9PYKiwtUXjlLBkeeH46Lon0TX\nGlN4QJ2PUonNOX3sxyH8oNZtapk5bn5BxgSzc46QFBYH7uj2tsAUFlu9gHLRsNY9Y8BR9GT0yC9Q\nU/hAHPx3MUzGpvOclEiCR5vwORJiphqjvbQgra9HEZmUc76ytVISaUC7inllKaz3YDRmhpdcZAAa\nBVBQCYkKXNPYQPnDfQspQwShSbUuTED4jTPsjEbc2r7HudVN1vtr3NkaMxpNKY+d4O5+g90JLC0X\n9PsryKLHymYHPZ0wfuMa2vXpd06hSjj/zAVmhaDT6uD0Mjt7hnl3jmytcOv2FlOa2LIPgJ2VTKcj\nBu0+u90RT7/nXXz8B3+I3/3DT7P10j2Wj63SGrSZ2ylFQ1GZoO4Fi4J/fosgouKkOcx15dyVWMTk\nNtS4QMx/WefDlBwtZi+2I/EJ8ZDvF04M6yfklvSMIJKSxMa9NBCDo1zuch9iaIypuVh43tpXJgaE\nRXXFeY4ffK1FvGbedVHjNnEwnQ2YjAxm9pC5SlAniD1qXKSsK66/WXvbEYVajFwc8Nx3IcAs/ntZ\nEKPkpIwWx/i7zybhI/FMSm7hmXtwMgk4RMIsgi7ocyLYOv8dgTjYwEGcxVlD5TxOMK9GSZVRssA7\nxTikDdmcRW2rds4EsEoFjlkvMhXCtI0zTOycN25c4/xzJ9hc3eTy9k0aQtJutLBGsrszoT2f0G8u\nI/WQZs/HRLTWTjGdw0QfMNvdAdHBqBWKwTJ7lWFUwamzj4Nsce36XZyV7OyNAdi/dptf+Yf/C//6\nz/4VVo8vsb52kfdNP0Jn8xhXrrzCqDNh5YkBX770OeazGaIIIrKUGQpe8+XaFyCNYshFUZstj1qk\nqvAVuVIKvOChYzMpsL5XuvTCOiLjqLU5jgUuHI9yQYRPfTp89QUA2nGYLiUEINvUtaifH1UTtnit\niFlGSWXh7oeITwRERVJtSGpZDrcI4RMIP0AMAzF5s/a2IAq1qJ9N1kJi/TDYqWRYNCT6WALvlx5F\n0OBhFqsoB+en6G/vx84l3dafEzIXu5rixqrI0kbsQmKMCNKaVwiMM+C8pDCZHvj0bEiUKpGyDH1R\nnvO5GDrtpYWYTUehPAEK4FVlPbiqrQYc98cH7E3GnHnsLJeuv4y1U/qFpW1HTPemvHZ7i17ngLX1\nNnKvot0c0CiWmJopSjoOhlt0+8cZjg5oNDRTLTFWUo0OeOPqKzAbIcoSPfbWh661vPzZz/GPjeav\n/Bd/g96JNRqbK1xovY/T559iR+9g21MKq/ijFz6Jbc9wKhLgB8XwHPuDmIimPk4gcbLecHGhqyxx\nbkySiwARnKSstUdsoMW96lzkxofFaEcK37YWQ+2sJvG1QmLq9JTeZEEtESE9nag3KbWunshKePjD\ncYmxX/m6f2tJJmIjXpJy1oYwaBF+y/ooalD3qELCDzWPhva28lPIW7IuBT2uFrtyChvdQkOaJFwo\nKiuQTtaJPEJwSIypqwEoDwB5Q9lilKVzFmcMNuYujIzGKTxohDdBBkzB2Dk+PLUE4wmJcyXO+UWn\nddZvvBqi4ioWtYqS6mkab9qcmjlXbt7gQ+94F2dPnuTWtZc51pFsdhSFLhnNu8iyCdL6RVoV7OsR\nxin63WV6XRCuZHdvh9WlA5RcorSWyy9+k9nU0Cs62PE+87B4pICzq+t87ZOf4cs/+Gd498fezWQO\nYysxrR590WM82uaZ4+9jOhnx5aufZ+YmmZdgGPN6lg/PbMAJg/SXAciHo0vdQrk+mRZGEuiz4482\na7u0AR/Y1JAIQ43M1xKpIGIB8ZlqJhVBTOFCn0W20TJJ40F15/D6zVSFuOAfIimkZ0+qhJcWvMU1\n8xkJj5pHTT7gD8Sbt7eRpBB1r1qHq23R2eTGgcVPai4VIoKeZYOp0EapIniaBTVBOhDO19QLcgAW\nEQaaJOab6IaOCJs/YBt2Me0YQGWmWFd68V8IsBJtK6QJZeHjAg7iihSEXHsm6Zx+fUnvTl05hCiY\n2xmv3nyddz71FE889jizu2+w3nOsFGOsKCi7yxSdro89cAXjSUU1EGjj6FhBp9HHOsmx1S7tRosD\nbbl/f5vJwQ6FbOI0WB1KmwN3bl2nVAVlu+Slbz7PuSfPYGeKsTaMxzOaUiFsh8nuhMc33kHlLF+9\n+iUO1AiJCkWmRZCwXcoWls0kQYYN+rBKz69i/oaYNZl4Xhj3uCiixJVEkKjy1WbAZBLMuLFI59eu\n8gtmUruodoSb1KoBMgTUZrk7MoKS1A8LKVW9qNdm7CkuIwzx98P0g+xz/K7uCCLgEWm8k3RymAT5\nE2tfh38+sQ9/is0eeq85aUR9Y6muOMlO1GVIfe4jhTXC15cMeFVuE3bh+oJQTzLNkkUkh5KYC8AG\nNcSbpnwxTk+ski+/oPZrwKU4gMpWQbTTOBsyBWsPcqigQsRstBIV8js6km08mCKlUOhK0O+eZH39\nOFfvfZO7927y6q3rfM/jFzEnT7DUcVQ7t1hZOsOeUdg5GOmglFTOYacVZjJDLmu2d+9R9FZoLZ/B\nluuI+Q672zdpNVuMDg7ATWnIVsp+devKK1y+c537xZTf/H9/nZP9VY4/9y729ZBWaVBCMJlNOJhU\nrK1t8qHHNzBjyxdufQrX8pYd6QqkET4TtzTgokAe7P+B1bkAxsoQUgyETaRA2MAJg+kxzqUIBDlL\nMeYC04ggLoATNqkYnhHkQVMBlANivs3YQx0ybQkiMavVPuHKoH7WgUWpjojPHpOk0pS9Ou56V1/X\nubhNY3/q0OgHIIDE+IQfC88NPZMTJqgxMqm+keilXFPpmrW5NKUFeEh7W6kPOeDmItvOJtxmfwtE\nKkJSF2EBl8p1spC11otU/q9kzSCjm86XrTc2ZJO23gphhc+07ATBFm/S4k5oMzGCUgOVLx0nvesz\nwlHENPREjz6wsSSea4AwwQxpqSxoo9jYeIpea5WmvIXTWzz//Ld5z4nHePyxJ6C6gQuBSWVDQdkM\nxeAEU20Q7TaNpQFVe4Xl02tMR1PuXrnJvTuv0Nro0iolVhiksFTzKaLZYDzy6TBeu36Fy3dvcUNM\nmVeaX/0nv8q7btzgXT/4fdjWKtVsxvhgyHg848TmBno+4gNPfi+FtHzq5qeYtSpK00W5hnfMkhVN\nirQ4AxNFhYXqEXSZuOoCdmRtsKt7m3wmI/o5TXREJEZQW51c4KiBESQJXKZzPTTgIzy9p6Op1XKo\nNyok/4g6kK4OZEpSKgTnuXodS5nHJS6qMzXWEp8pXrtuCzibraWgOFYyJcEJYxJwjHovhc45Qk5L\nUTvbPqQ9UqJgw4717sM+l2FE/k0Q7aUguSFb57DSIoVFSBUqSYtUNFYIhzG5qlETHs9NZEqlltyd\nMhFUSS91OFt7UxJy+ZuA7hpMkoejXT7/2wqLlBFItGhdYYVIaeylCyKyACEKBBqE9viE8fEewhZI\n0WA6s4yHczY3T3L90ktcvnGdD59/DLOzjSr7iKIEK6iMBlWCbNDpd6iKJrtTw4Gb0yw6LHVX2b97\nhatff4FT738HatBjPpl6hzDnsGZKzIVrW5J5U6K1QDUavPjyi+yPh3z4z36cWaNJu9mmms4ZDQ/Q\nc4k1LTrtFT723r8ArZIvXfk0Y6cxTY1QfoPMhQ4WB8/5/B6QOGS2D0RiBrWTV6YTu6geRCp/GC7z\nfiAmdzsWkSjUTYm6ELFzDuFklrdQBkkxcHkZpJSYR3KBMMRuRLUkbkASwJdbDhbxsHApRMpQ/bCW\nWx1q3CAQEeeSJBE3f04EYiGldK34IT7iQ9qjJQqBqmtTYYyhcL5KswnejAJfzBQXiAI2uAO7kHk5\nE9/EoqSRiELSqmrxNL7n45LMQQkZjnEOgBOYoLdZTCBmQRyskSKiudFZg5MaXxzEp4J32l+rLEqE\nkFRWY+djXFki0AinKSjBFWBhsnePotnEVPuonmJeOl688Qbve+opWs1j6OkdZrbACIVxBVI0cbJJ\noVqgFaUUzK3xVpfplP5Gj81zK3T7JSMzZzYbg2tQlg1UKRhPvUmyu7ZCd3VAeW9CgQ/i1PMZg26f\nA9WikDDrzXnsdMHB3h6FbCBln1cuvcYHHvuzLLkBX732aXbZY+oKcN65yWcDcigiwOitCsZYENbH\npAgZpPCIDYSFb10Ik1ycu8Puz9m01/NKwKocaXOqjChEou8C945IXfJfSVzcZWBqhlMkjGJxQeUA\nXw4CLqxBajL0sJZfYwG4dI6UMexNzs0JVS1NvLn94RF7NEbRu8JYg7CemxtjgsGx1jwjUVikrLn9\n1vooxyTex0FcNJc90IeckCRvyKA6BAnG4jmQ53TGJ9sIakoNOPn+WGuxMlzH3wDnQBvnQbXg6ViE\np6u0oV026JY9mqKJnUCn1aU5PWBn+w0GwrK/tctgZZVXb93i9njCU4MTTGe3GM/mNBpNZNEF2UG7\nEqfBzR3tRouiKLFCsL29x9bOfTYvnGFvbijKJoUqUKrJeDrH2RLZ8kuh7HTZWF5icv8u0/EEZxWD\n1TUajR4FJVbPGfRXaTc6zMeaRtGkKRv8s9/4bd79/g/wwz/8r7HWbXBt++s8v3WDnbKBKzXOWa+J\nx40k0lZDa421UIaCwzlREGl+IEftcpEdt6ifx2tkR2b39YiADO7XwQ/IE6NcehcBm0IEK0dQFw4r\n/Q9ZU/nfi2uEjOh4KVcJcej5HrzG4e+iarSIQ4j0W/rBRlXIJf+EiDU8rD2YMfVfYIsT6EOXHZXW\nzKo582qONgZtNJWu0NUcY6oU/Vhz6SjKWazRPrtPEtuybLbOpDsu3v8QjmFt7eocCIy2FdpWVKZC\nm4oq5EuI5iSZz3RqEfSyiXhYZ9F6zmQ2Q1vN3FYY4QvmCtOgW6xxbvUCZ3qPcaq5ytLM0dobszwt\neKx3mo2lk8wdvHb9Oqrdo2ydYjJrYGkhZBshOsiiw9wpRq6gaDTpNZp0aPC//6//iP/ryIfcAAAg\nAElEQVT5l/4RorfKyrFjqLKg0WoymY4pypKy3aK/vAJAuzvgqZMnOSlg01ne99w7+Us/8+9Sdgbg\nSpaXN9jcPEm3M2BpsM7G+gncfMbwzlU+99nP0Ogc56lz389zm9/HRfs4vesVpVE+8b/2zE0mrEhj\nEWhrqYxO68A4XyPCHvHKnZBqIS0SmyPWetiAEXcqQlVxJf27zB2rgp4fk/LW140ZvP40WqgpIkJ9\nkdAvFVy6H9YOSwxJsF34nL3b+MrGzIUgqrcgbI9UUjDOJ2eyEce3Li0G4ZTHRZJeRqL0TshEZUXQ\n5fyiMRgXk6rFRB6G6CDzoNAU9bxayogRlr54iQcALY4q+sJH9QJXU+Os5ZzQc7NgvnJghcXZCW5e\nIWWDstGj3RnQUQNKsYysOky29ljfWKM96PL0qcd49dpVuieP88r+bdyq4fUrrzN717todY4xHO5R\nmZJms48RTYRooBSIRoM5CjWp2Ll1ny9//kts7+/ymc98hU/86A9jrGJ0sE2z2aZsdCmaLaqQXKTZ\n7vKxj36M3v4uzW6Pd/zAD/PE+7+LoZMMBisoYZASVlc3qGaWUpXofh9d7TO9O+LGlaucv/As9+8d\ncKG/y81vXOaynbN0ep2xPsBajVLgJL7+oazNxC5YC1wEehO99WbmpNM7P65HSQpkmydiRx74jWnX\nZNqIDuf7YeuYjHQP6nmLgHd9+UxsP0Jleavm4zr8JWJFsogNHK79UEtNh1SILDfLUV6PeRxPxDIS\nFpKe4ej2SInCzI4A0ExwUmC0N/U5QDiNEsqrFSJiyN7JyILHFYSvUmSsxWKoXIXG5wK0wviCr87n\nsLWUgKNw0XU5ilIucHPtCUpUIaxNqoK2/hqpNqH0plGL52r+Qi7EYojkb20BJbxJzucQmCPEnFJ0\n6ZerDMpVBmqJleUTNESbiga78zkrlabZ66CXO7SL0wwrw0Zvg8c3TnDv9ut88Zsv8aGnn6HRPsN8\nPqZs93CqhRUKJRRtZ6kcGOO4eulbmINtGlg+/9uf5oPvfx9Fv4Mrm35dyBJrJEQgtNNk5fwFvvsn\n/xJlr0938yxj2UYWLWQhcVWFrgx6VnHi1Cnm2qH1hFK1mI4mvPatS7z/vR+k3VxlWq5xfvVpLn/t\nedoMOPH0OW6Nvk1VDbHNElTPz62z3r/DVuBAxsK0+LqUAgHWuzoLK1JK+UMOEB5viqZHp/FVpEAI\nRaz96U2vNXPwNX9sMHUDoojyNgviiLM+eCVEz4mAF6WAvAWdv27+MjW+JSIhTPEeizlARQjVThYL\n7yG1IBGkh7akorGxD9b6pDEuZbKBOrtTxEvefF8+UvWhqmZAABqDd6DPfuTR+ErP0LbCOO1zHKKJ\ngJVDppL0ntKG8GdnU509a0OizQAQRv8HP/kBNHQV1lYB3PSLI8JYCdEFUvRlvE64Vj7hFut9D6R/\nlxKEm2DNPno8oTRdeuo0J1fezbnND3Jy7RnOnHiSx04+jhAlZatNZ2XA0M0YC8PrN29wMJ0iZMHx\n46dYGqxwbPMkb9y8yX5V0RosI8o201nIfCS8V4cqJQ2l6Lfa6NnMl2BXihcvv8qv/8qvo0zJ0rET\ndB87hVxbQQ16rKyuAbDcXaJY2WDw7HMUZ88zKbsgm0ihcNaiY+BTodDOUZQNtDZIK+k1Gzz/1S9i\n9JT+ygrNlQ2OnTzP6dYxrv/xZVbnPT7+3o+zXm5QzEtKJG0HbSkolefc2vkRzgzLHmMyMaSZ5LWa\nam/garUxra4cDKylgxgU5AQp+MmSEZfM5JgLAZHjCmqJ9TBOlRyhFu4VpdpFbEPEJK7h+xh2H0Qf\n6idxC59i37K7LqgR8ZDMqJak7fplFyq3H26PVn0ISUdi2Kc3O3p9HeswITWa58AgZYkDjAHj/O8m\nJD8y1gSx3yBLbxfXRuOsQCmLc9qfa4X3tQ+goQ1hytbp6AmxgD6LWEzWRE4iIFQY9hFpNafwpNv6\nPI2Vpdls0S27FLZLo3OcQq2ztrLJY6dPYqopzggKWox2ZqyoPs1JhZlLzNY2PSPYf+MKzf4KnfVj\nPHbsce6M7qJkk6WVdd64fZcPPvuMdyaaTqisoxQWJQuQglIpGkJx+tQpuu02k9kcLQSf+b1PsdYa\n8MGPfpTu6WNMpGL37hZyeh/4CN/63BcpO302Tp3hxNnHaXQHjMZTyjaosvT+GEpRNJoY602tpSpo\nq4JKz5gf3KdQmvZyn87maTo7Yy48ucedr32Br/3uV3jPu/4NPvGhP8/vffmTbM8PmJcTRKGwIeBJ\nau8w5mx0JIo+ICpwRg/+xQSkEQeKLtKHueDhTZowBBfNn4tmu6PEapf9m6TMCOBlGzSpLBnSLzPC\n5T9Hn5rapTovmiylDMDror/Fw3CAeB8bYiFiVfT42cRUABnReDOCAI/cozG22HEb4gmC/4LVQXXw\nApWx4IxBlQ4jNBqBcRVYEQqxaLSzKBksGsYn4/SDo5OXpAqBJF490FhMMoNGq4ETIJREigJlBQ7t\nJbkQY+8lioyCK+/BZ0N8fKEK5jPDqbMf4Mz6s7zx+j1OHn+S5eVlZtV9tu/fQIg2ZzafodttovYn\nTLdvYbe3Gd+7zmsvv8jui1dpdZbZvHAR3V9DNCqkgpX+Btv7Bwxnhm6zR4liVunwDFAJQ6kFppqz\nefokJ09usv3qVWgIJtWUf/pr/xff/KPPs7S+Rn9jjXt37jLZ2uPP/Qd/kV/6xf8WKxqsr57k3JMX\n+Ys//e+w/uTj2MJSlpJm2Q1is2I+1zhn6HRbtJTC6jnDe7epRkOWBqtUJ84yPtAcmxnki99i6+Zt\nvvi7X+UnfvrHee+Zfa7vXuPV2RuM9RiMRSG8s1hhU3anKPZaa/CCmCQWsfWQk1vYxgkQjNxcCKSK\nIcNER8NDFos6AZsIjnHe6iUyguD8taLeniP4kUGLByWHyLYjs8kLaCWHO3fIsnC4BSbl3KIFIz5m\nLji4qG4F4FVKiTX//0CPtwlRiENvsc4vNAsYp/3EWB08AgskBUiNFlOENVTWpwCLwUQ+1bYP4/VJ\nVEM2JBHUCukdPqyLTkoRoPRmURPz7kuBEgWxwq9P3uoQGJL/Tb4clfDJZQU4K5CigZ4JmvIUp088\nixKvYuw+3/r2i5SNAUsrp1juDVjp9RnfH/LG9SsM2op7rSl3m0O6xZyb9j6tvRHV1gD70ktsvOMJ\nuq2e72ujy+tXbvDOJ55AV2OsET5zlLFUhUAa77YmOy0uPH2Bb798xWejlo5dHF/beo3B7df4gXd9\nAHbu8tLt1wA4qHaYSMWt29s8f+PbqJUGf+0//c8xhWA02qXV6YMQVFUVag4IZtMJ8/mUbqPJdF5x\n9+ptHn/vGZAjWmvHaOuKcnmZ5nSPa5dvoQ8Knjr5HMv9Dc6oJ7ly/XX2htvsznbYd45ZWVGVAmaW\nhpIoJFVVBWJgsE4gLD6cOu3X2kwJhACq2gwZX5ZYJelhGKGrN1mQ5p2L5rzgKhzdMoUIcQ4E8+DR\nmy86KpGkg3inBxO2HN1EjZ9EEyvRRya470cgHm++X/CbeCsQ4VB7WxAFPzkh5iD5yBtvsrJeXSgK\nhZQOKx3GztDzKYVrUCifhdc6izHeYlCEx/K1HTXOQaEaSGmxVuLw3pApe3NQVbTVOOOBGlXUJeg9\ntmW8mGpE1s9M20tSqUBS4kxBpzWgaLZY3Rjw+vVd7ty5xdLqCZZXztLtrTG+f4/rr19GzzRaVYwa\nBnluiTtzTRPD7NkB49szlpYcK31FubkOhWB2sAtGc/vmXZ574gLOqlRZ2VpHVUkUDluAFoYPf/TD\nfP4zn+eNvRFaFlQKykaBbki+64e+H+csl375f/IPoCRaVTSKBm5U8cblS1hdYQwoNK6aIso2OIc1\nloZs0G2XlC2FOJjRVW2q4YxBq0+vN+bO1hbLx05y4uQpRrevMLq/i9ANVlZOUzT7rLiKpeoE0+4W\nWzs3eGP/Da6NbzNUs+AXEutzGhBgjDflYY/wPhG1MB+LDntxPabIq/GfBXf6wyw/fkrqAGlDRynC\nA3j1GTLf7JkaIYKK6cHMzDrgvNoQ65E+DKhc2CQLrbaIkKSOug9RShEhhiQe6vJOP6S9LYhCKiUe\nkdoU6xCyLIcZcMa7EWMsej7CzgTSQLPsY7XHFXKqKKWgqizazIIa4aszCeMTbtoQnuysRTtf08EZ\nEzzeqMGhUFAVwoKyDitc3bfwvQGkc16asYrTJ86h9QFf//ZXUEWf4xsrrKwc5/bObb7xtc+yrFqc\nXToDztIqBc7MUMZyYnmFyeg+uq1obfRxgxK10ePGdJdOv0/Z6cBwitPwyqVXefKJM9y8fYuikJSq\nwXyuKZQDYZgLw8mzZ/johz/E5HNf4ObuiK5WNOaOzsYS4olTnNk8zide/jgA89mMjnK0RxUrjWU+\ncPYCZmqYFw4zn9JqtNjfu0+z3QMEFIrx6ABdzSmdoCUaTPcnDPeGTMYjVgYD+kvrPHv+PK996Q9Q\nukSJkv5gEzProrVgQx7DqjucKjY53z/N169+g5vzO9xS99mthhRlgfGFH5DOeQnPghPe979eR9nf\ngSg4KXw0aiz37mp0Paw673EaQcxDa9PHL8iU7MWfZIPja0ZMxGGH6hxU9CF5CbwUtZQgLMmX4Kjc\nB/XFUo+yD4su++meLLrx1xqT47CKc1R7xLEP3voQC7hYKaHwVZecEbiQDdk5vKUBhzUaZgopWmg7\n5tbuLTqdIc2yS9FoI6zEWg3OokKeP200c2FRwiKdz4EoEJiQjt2H6QZMQRiv10qBTFs+FHch6p+k\ncmjpCOHNaC1jkVRIA+8/8U5euX6Z1w7m/IVP/DQvfOnzXLv6Bb5+9YtYLTi7+QGWO106Sx1ef/0V\nrBLMVZ8Pv+NHuP/lr/CZyy/g3vEU++fafOreF1mXp3hn8R6Oq3VE2cU1NNev3+Hx0ycR2rB9MGV1\nbRkhKmbOoKxAOYFrNPn+H/tXOHb+cV56/nn2bmyxdWeL933sY/TXNxiqJn/mJ34KgI88/SR6rmk0\nOnzXRz/Od//IjzG0c5zsMdUTzP0tnNFUVjNYW6fdLRgMurRlg26paeAY7m+xY4eMqhFLRrG+tMaJ\npy5Qlh26Y9B3hhx772PY4RB9/z6y1cKtdxDFMY73LnDz5RFu2uaJZ87zrdsvcG3/FjQlFm9lktZb\njZzzbuHSqeC6W1uDhCxCLk5PPGwIsvLm6pDFKRIKE8FDFyyaGZPCA9JK+NBugU+X4YInVnR59yB0\nlF2CKiH8vT2e6Gp1hOhcJzD4ZL0pZ0xSA2rrSfSNiRzfCy51YiCfIkAEDMyXpEs4hRAh10Zmv1hw\n3XywvS0kBRsRUuEdhJDgjBf9tfEJUlUYaAugQTUkzVabg9E+u3s7DPqCVlMhjaCQQbwLC8E4izNz\nEAqN9cGMeXMkc6Sv1hsTsgYHl+CTIKX0ExgkBCdA65Bx2vp4DOM8Ir7RWaKoLHvbu3Q2TtHoKa4e\nXOHzX/0dKjfkufMfpN9fhqaiM+gihQ+dbrYbKFGwfWuHbrkC7Sb7s/tc27vGHX0XqxqUJz5I3xU0\nOssUqsX9vSkrK5vcfvkyf/jC53jy6Qt0B30aeGcdpRTtY+t87w99nO/62IfZu3OfuzfucvLpZzDt\nNlY1KAYtAH7yP/x5rBZ0+2ucOn8R3exzf6ZRQtDv9Ni9c4P11RVG2lC22hghmdkZB3qPhpWstDsI\na+h0upStCYVQYCqanTYHds4qBV/7Z7/Dcx/+ECvrK+hQSm/n3jaigMl4yKc/9UX2q7t839rH+Mnv\n/zf5rS/9U75581tUjQoj21ihaLoSZVUqzZclUvbzkUEJRD8EEbilqzGFdHAGXMYW1Y7E8ePh4RTP\n2WM2LYfIPYrS7o3XrFGoPIbB+vDbzLhQE4O6e8G5Ktw8+REkdSjf4rVSFXGGlIsinhY8HR/WHqmf\nQjTnWfIKTDaZFi0apPNeegqcjH4Chvm8wmFpt1tIKdnb32UyPcDir2NsRaVr/wdjKm92DNmYZ/Mp\nlZ5jrE5+Er72g0abOVVwaTaYYMsOSqwMyHMEdaIpyTqfClYVKBo8sXaam1evYhAUJXzm87/BF771\nu+yM79Bv99m+P0a02ozmY27fvEGnbFAqSWUqdse7rD55lic/8lE6J08ytkOa7TkzfZdvX/4y17fe\nwElJo9mhaHR45ZUrdBodSi34g//nt/nil77EvKqY6Yqp0UydY2QMUykx/QEr55/g2Y9+hMb6GkYW\nWKGowlz0z7+TjXd/D70Lz7Ff9Dmw0GgWtBqCVrNBs9VCNduoZo+ZlWgnGA4PwFmOb25SSJCVxs0r\nymYD0SqwrkJZS2U1xs0ZX3+DvZdeoiUd3V6f/mAFIRSN3oCxdtzc2mK4P+brn3yRE/IM/+r3/igX\nVx+n71rYsUXPQBjpozwFhKw5C2BbTRBIXJsI7AkbXv57qRxSBU6cvvdp01URi7hm/gYB68gxCRt8\nZEwwbMeXCyow1DhC8qC1EVjXAUOrPQ+lDAVoF7AJkcyg3yl0mJ+fPILtm6sqj1hSCETBRZNg5sDk\nDEI6T/dUkCIAi3dbBjDaUZSKopQM9/coiwJBdBryZkrvcWi9Z6LxXode4vCTJa3PvuzBTY223l/B\naEshCmTI169D/ESqXOy8x2DMviytT1A6FxJsiZha9odbrK0vYcyY3/zd/5Pd+W1WV/r02yso0WY8\nmiKpKBslJ9bX2Z4NuX73CsJWnL9wDj3coDA30Qcvo4SlJR1CH/Dqy19h46k2sr0KwxEvfPFLbLQK\nTiwv03YGN53RLspgYXFBMJJYpXBKMjW+IK5stFEoQFEEr7pKNjG2QGqJEpZOS1EKy3wyotUbsHHs\nGHvjGeX/x96bR8mWXWV+vzPcIYaMiJxfvqFeVb2qlzWohEpSUZqARgIB3cIMom1jtw0Gm8FueoFZ\nbrt7uRd2u7Hdy9hgeuFuMzVulmmgEeCFGSxAAiQaCQlJJZWqlDW8od6Qc0bGeKcz+I9zIzKqKCRs\n7FX8wa2VlfkiI27GcM8+e3/7+77dbJOXBq0jLl+4l3/z6/9dbn36M+zvvoSZ5iTeoqnwykMi2Fzq\nkXiB0I44hZYWRIUh0jHeCjpLK9hpSdrrsbpxnv7xdY73TiiHgov3vY4ve+wbuHZ8g+d3n+NofJcq\nn+Kadbkpau6C12emPPX+OVs8Z8rGsIiD2/RssYYrKwSCuvKf81FCVhGMWGbnOVv21NQnMWMMzsPE\nWaPTu7OOxisl1O5lz/KsS/HKY15SzFqT/w9W2Z/CEb7Ag1/TTMEx220tzoUBraUpgzjGnaH7QSjj\nMLYGA2sew4zFFkURYX6CobQZhcsxwmL8GTHJ+grrCywVThicqLBUVL6g8iWVKzHeUHlD6QylKSlt\nReUMlStrtqQ9Y78ha1ew8BpMHVCwoGWTza2LeFfRmU7JD26Syz6yAXGjSxR1WdZtJnf3MNMpG2ur\nPPLIw/SWe5RVTl6M6R8fIZyiHa2w2rkX4doUVmAix362y439HfrDPY6PdlG25A9+5/20W5o3P/E6\nNrpdWjomQhAJiXDBFs2VlkjFpGkDqSKwEDmJqhzShPdUOU/kLaLKSHyFKnOq4SmRcBhnqLxHxgkW\nibeW2HvausE73vaVvO3L383m5XupvCXWgvWVNkkqqXzJxXMX2VxapzQVu9M+U1MgM0c7baAJDtVx\n0qS3eY4oTRHeU/kSIyJa7Stsrb2Fh8+/k3dc/UoeX3mES9EKaQGpJ5j0eoP0HuVebqKy2HgUAoQS\ndYI608e4Oes1jAuos4TZQ+tOw4wU9HJA8Cwp9wv/8Yrrdpb9Lkr6IQCM1p5hWaF8/rPXy8varjPQ\ncKFEWGx2zu//pzoSLOAWr368xs5L4YnZmkRknAngn1uIpDU2IOo32DuHVOGD8x6MCQSnJI2IYoVQ\nULoSoTXGh5TVeQPC1go8EELV4qTauGVGkXU23N9ZHLKuvQIXfkZmca94zCxrKVwFDhLXpNnqoDsd\nEJbBS9c4UkdEDUtrounKJUTcAumJFCSdBqqRsNc/wjjDarPJ6NZtbp68xNU3fCm2sUmx8himckzz\n5yl8iVdTPnf4Iuu9dVrCURlDZUtEu8nb//pX8tGPfRKPIYoUXkqqosI5T1nkOAedXo+0kWIqUD7Q\nlcUsXcXjTRZmMzlL5SQ6SkmbbbKqojSGpNXDek071vRiz/t+7Vf4sR/9Eb7k7U/yyF97G43lNXIU\nUdJAVJLcO5pbG6ycv8T+M3dorSyjlpdJGh1KIB+NKHODRyEiTZZNiIQAFTMYF7RXL9DNFLqxznpr\ng0YfzrHK7vAmL965RbquGMsCNHNpvRBi7p8Z/r2wSHwQQQXKwdlCDvLimXCuHkrsfA3qza5ZNwf+\nFgPOGci4sOy9mIeIcGvNfl0IHDPhHsywC3i1yCDOXsR8juVZLrRQGswzosU5GQtlFeIvd1CYAyU1\nvRkRUv/K+nlgmCGoEsHMTw9m4KTHOItWGvA4VyKkpyxM+EC8DJmCM6DPmIqBURvMSp1z8ypwRl7y\nuNqKnLPMYE5iOqOl+noHBqjq59r0ilZriWFVkFUZewcvkp2XpLnl0kHK+nKLuy3NSbOks7QErZhB\nNeV0eExeTFiJU/p3DjCDEt2IWFreItdtdBwzvZGR5XdwtuTIjrib9blImzsHx1y5/zI3TvqsXDrP\nw5VlUk0RXqOStBZ6BftyU1WUeYGME6JYIFxo26GDl4HSEd5WYQiv8DgpSTo9jsdjms0IKWOMs7TS\nFt1E8PHf/31+7md/msPxPj/3W+/ju77tO/mmd74XubSMjBvERUSiLLYRUzQSQJLoBNVsMxGK6XTC\nUqtJOemjkwQdR7SX2uQHhnbaQlgFkWBprUujvYQ76sC6Y3WwRLdscrR3ymkxoXe5Q9+P8dF8+Yb0\nXkiYlQyi5i/UfUlrF0DAWXYgZoFezNemrAVY1s0y1Vdp9M9TCzlfwKIW0Z25QS02sBf+m+34s9bp\nbMW/7Pyz5T87EwuZAq/IFF750AVnZxYtB179eE3LBytCSzKk9gaEQ0iHF2egYLA4CcaqWipiHdWK\nyALjS4yrKExGUeVUNhCexuMTsnyIIcNQ4ERoa+IVeM1MICOEJvQMAoBpffi7Xvha2uuC54FwOOlx\nEpwUGB+EO14KZpZyVCBpYlXCymqPvH/I6GifftOg4oTVvqKZOawakps9smJInCS0lKKaDnDTIYPh\nEbF0iOkpUybkEkodk67dx9q5N3O+8wZWWveRNDo4m/Hi+CajdsZDj17loe3X4VQXH6/SXllhXJTk\nFvLKB6t0JVFSoLSmrCqE9ygfTGV1pIj1jH0lETrB6QaVjLBSY6ocYwyIBKkUGkNjOuFPfvk3+OF/\n+F9z/aXn0VLhjOQ0d3TPn8PJiripKBJNoTXaO7Z6HbQHYQSJF2hfEUcSqpysf0hDCGKrWV3eQEpN\nYgrsaIgoHA0ds7G6QtJsYVQXka4zGSjcXgzXIu6PHmbFb+DyHIDSW6zweBl8NsGjkGghkLVhrqjV\nscKbunMQgryq5dzMgcSgtalsWOChhR7s5Fz9Nc8SZh6i8/KlbhHWCz3EDlE32YLqd6axOWNfsrAy\nJTMXcoTECzlbEWGHcxL8jLY/Cxuivob9vAM3C4zz4/MMhHltVZIuBAWPpzQFlSkD0OcNXsxk1LVj\nrfAoCToOWvSwD9i6exDETmVZAgLnDHkxxZgy6NZlQJJDS9cF11BRp4FCIKQKi3v2nkqYGcUC89vP\njFvCjVII1GwegRe4yhHHCWkz5eh4j9NsQLLSIWl2iESLeGWZQVQyqYZIV9JLW3SiBuvdZVpxgkYz\nORoz3TvFVIaCgsJMyfMprlLcd/Exmo3z3HPv69lcu0C/f8zp9ITWkqI6PqC88RLy8JSV3irGEURQ\nNnhYCSkRSlKZMmQ6NT4Tx3G4UOvdTDmHJkLLGCUTvPNUVUUjbZKVFQmOwaef5v0/9eP8D//4H/L0\ntWcwzlAUOY+/4Une/Tfey+m0DKWZMcRpTKwaaON5y5veyNQUtFaWSdpt+uMRItJcv3mdPJ8wHvap\nqpyVlWWsrZhOx1R5jhYxGoUpDUJIjFAYrXjpzi7D/VOG14/Jbk542wNvYdWvAGBKg3QebSFCIYNB\nN3MJ8ezLz4DHWoq/sHi9n7Fi7VxwZ91iYAgXS3ALO+MSBBbhWWA425lnvYOFpxDS0cCpmbMSF9mN\n4k9/zXd58ar38TU4Oit7F7EOam3PX9ryoTJhupIXZ+2dqigpq5xINmsWGUgdaMfOB6GMq/kEztq5\nm7IQ1Ooyi1KKsixI4gazi8DXGYB1BiGTkFWa0N1wnnm7SYgzNuP8uxJIF/T6oWRYsPSqUXupFTY3\n9FpNnM25dXyHxoVlfFwRLy2z9tBFVlWL3A7Ihnt0E8lGd4nN3gpHo0NM6WipNns3nie7OyW3lhd3\nn+Xhey6y2mhwcvsUW3oa0Rqrqz266Xleuv4st27fISbBTWI+8YEP8PDb385Xf/e3011ZYTQOvosz\nNqd3dc/aOYyxWGOIk/B+zVpgkQyBriotItZInQSvCylo4jl9+ml+7cf+CZ/65CfZsxlOO5CCx1//\nxXz/f/mDrFx8kKkriZGYLMNklmLiaEWWq48+RKYcnYtbpBubiCqhxNNaXoG0pLCWfDjg0sXzeGcp\nnafRboeukUgQXtBqdbnnnvsY2iw4dOUFkRBc+/gOf/Ob/ybLrU54HU6gKo+MfOgMqdl8CaiX/BzM\nnoF2cxrzy2KGp7LmZYv15Qv2rAT21Ira2W9FXXogoSbbvpLOPMO1tNa83N2p7moJgVtI94MCsv59\nfZqzMnvh3zUDdPFpLvIjPh+i+ZfC4t0z28kNOpIUhaewOc1Gi7nbkQoRtrIllTGhHWgM1pj5HEPn\nDcYYoigmz0cYE3rAcRwFmbYMfeTSOZKkgbQi7KQChFYIXD0foHbyVTML8pByelLwEZIAACAASURB\nVFdz3Gse/aJ0WscJPi+IpGAyHeFTiWw0mZ72iV3EMNakrZjRxDP1BUJ69u/eZCNeonIFjVaK94Kj\n27tMT8dM2jnXDj9N9mnHe7/222jT4nPP3qW7tAamwdbqJVp0uZ08TZENMIlk7EoK6ZiWFUu9ZbIi\niJbwoOMYZwxKKYwxJA0BStYTjs7sxkRUS5ij0KO3SuKkIFEKe/0G7/uRH+EzT3+UE5cjpSbyAtlo\n8B9/7/dy4f4H2R8bZJKgpABvSSPN0GYIZWisrRB3erTWNjAiQcYNHLC0cp78dAAmdDSuPPgwcZRi\niwoVRRRZSYVGSUWeVXS6y0QXzlOo4BCtkTB15EeWiyvbAPRczLDKKCNNRUlDayI1Y/YtaB9mpCCY\n4wDBpp06MMxEdjqYBXOWTXjqbAI/35UDJlGXADWoGXadhQW58PNigHDWBhOYBbBRyHp2mZiBhMGU\nJly0s6y1XiNOzN2sZsD4wpnqp/MKgPRVjtc0KJTVjOZsa+RXoiKNB4b9MaaqSJJo7vqrI01lfG2F\nHiKsrTMFTwgSVWVQWiGlDNlCkgSgUYZyA+Epqjx4LigdTJHqydDgwqh6fO3UQ02MCYFB6bqW0xJb\n1WST+gOOo4h2r0GSxAwnI3prq5z099GyRWUlx3ZKPzviMDum8AUyiiiN5alnPs3mlYt4U9JsNdGp\nYuwq8kRiOOH5G3/ML/1qzhseeger5zrE04jR2NDSm9CW3P9Ih4M7O9zdPeT13/QNbN1/P8/fusWF\nCxepjGU6HZDGKVrHOK/m4G6wBAvTqBAKpevyIY2CYYuVEAmkd0RCsqUi3v/BD/DJT/0xEyZkWpBb\ng/aatc4q9z30KNMyTJ9QUgQqtCnxKkF3GpRuSntziyfe+W7OXX6QooTKQ+lBkxK3FNJKtJQs9TZw\nKqGyGcZUVHmOJQ1loA2y+bjT5bQsmXpL5AztuElRKmTZBGB7bZvnjm9yXIxRiQpUX6pQ5i3smov7\npXf1ri4EMxNf5+rZHiHdCt/9/G0MG4YXWLHQppyXDLP7nP2NOQ9hwRIemAPqsx1/vqClOOsMzQhz\nXkIt0Z9Z3jvvmc/PcEHvMSdvzZ7DLLOYP9dXP17ToJDnGTDTEXi0Coq2RjPF5obJcEisVhA6DFZR\nMkLLhIKKGb1UCFHbWIV3wFqLVJIoiijygna7TVFmRJGuOw1QFiVFNaCR9qDOBryzteClfjPn5p11\neSMkQioipagKh4wC99zYGTVI0Ol2kVpxtN/nyv0Psre/RyNZptFaYexOGPSPKfwAoWOy0pKcW+Ol\n567RcltMpzmimvLQm17H7Rc/S/RggyzyCG947uanOTo55c1veCdvfN2Xcu2ZO2grQCTEyTrddU8u\ne6itc5w4T7G7R3upR295mb27d7HWMp5MUSoiqgFba209lThcMKoug7SUVPVr1tKjSsu5zhK3Pvox\nfvVf/Sz7dlRbp+lg+eY9X/muryZpLZONDJFwSJNT2JwkiijzDKcivI5RzRbf8t3fx1LSYoqnItDC\npYBGq0EiFKf9MVGzhUoSykFJnk8oJlNKb4mjBlVRgbCYsiKvJELFOF/Q6LTZunwvJ/WFf9/qG1Fu\nmf3RLU7HJ6H9qBxe+7ku4NVEUGKuf6+Fb/bMAGWeHdTzFGZGL0Gaf3aO+e3MOgTyDJAGWAAEZ9et\nMQZZW+LNCFOznxe/L55ihnGFFxFKhjOfxjoDX3hls/LlLFN59eM1BRrzorZjM7VzsjXkRY4UguVO\nh2baoCoKbOkoM0uZOxQxODFvDc3ppwvn9d4TxwmzmYQQCFJCSrxQlKVlNJpQllVQ37GI0vIyLMfX\nBq5OWFSi6fS6IZAoBTpMRQaIdcRgPMJrjU5SysLRaa6w1tuk0+mSFyOcnKB0gRCW8bRkVApW73mQ\nSjUoXcTpJKO1uc5bv+6r6D1wGXSKw9PoNihUwVOf+wzTyYQrly6z0WuysrZM4lNaroMRTV446COS\nBs3WEuM859zWFr1ul8FgwHA4JstKPAIdRYHfUW8dznlMFfAdigpblpgyJ5Vwrtnk07/9u/yTf/yP\nuHb7OYzwTLzA2YjUxbznPd/Ie//Db6NyGuEdCYamdLQSDVIxGGdoa0ilJptaLj3wKNHyOmPhySKL\np8CLiqQh0Q2BiDzd1Q5PvvUtKCWJlCDVGpsV+KKizDKy0Zgqt6SqgfIyDLTBETdb9DY3Aeg2HuTh\n1mO8ST/CQ9kW7RONUA0KqV9WOvzpYwYGBp0L3s+Be1eDp7PM4czReyad9nMOg1wEGOdB4tXr+LmU\n2toa1DwLRA4/N2VhFizmEcjPKdPWLtoZnrVNX0lznmNnn2flv6ZB4azd4zAOsBIzNqQ+oZd0uGd9\ni6VGHOrf2FFUGTgbar4aQxD1QFcHoMHNVI461MXGVzjhKG1VG2aKeacAa3C2rD0Xajm1CC7DTgQU\n94yR5kE6dEMgE4uMXKibZ60o4QBDq5Fgjac/yGgubRB1GhyNbpGbEypRYGVwEepnJ4wo6GxsYX0D\nm3RwUYP94ZD0/BZKJbiqpHQTCqYsrXZxSvKhj3+Y5+8+h24lnF9b52JvjauX7uMtX/TFJDphMC1o\nNtpMT8fkowntNGU0OGWSTSiFpZSQe4fzYK3D2QpjCyo/A30FGsGKSkn6I57+7f+Lf/5DP8izzzxF\npYL5rfIG6Uve+298E9/1n/8D5NoWuanIjaMiTNMqrKVynnanE3gJDlqtFpkQiG4bJxWx96SxpNGI\nERKqwpBECuMlT7zzqygaDabDnE57GdFbIdcpxC3yLGP3hWeY9u8iXIkD2p3l4LXgwm5bqR7N+Aqr\n1SaNFyuKPz5F3lEIqzEyAHzShy/qhQcLEx49CC9DG5vQUlz0dpiTmGY6ijnl+eWby2xBz/0XxcKO\nI14+8q1OYcKcidnksYVzLtoFzs8/u9272uA1tFnE7HwEl6zw2VJ7iJ6Vva92vKblQ5IEwoz1UBQV\n7U6TvJggK0GntcQgO6YbpRgFqt3g+HREntVtwAqMKWl2OoyGGVKFWtYJg1AROpboWJFXGVprjHEI\nJVEIlJB4GxiMeIeTIDSgZqq48BXEV7M0L6IqDPv7u0Q6CpRn6+e77TifkoiI036fbneZqlLE7SWO\npnc57N/CyKwOCArvHYUbcaf/EhvLF8iLkpaO0HFCb2kLIsfG5CKZmLI/vE2Z5UxHQxo65Xj8EsfP\n3iH3irc8/hY21tZopzHPPvtZ2rpFZST7WUEqPIfjMZc2z3Hx/DG37+wy9gKf5UQ6Zn11lSKbEtUD\nY3QSAxA3ImRhEcenvP99v8zv/tr72D94CaeCT6WyoJTmPe99L//B938/LG8wCcbZeBG8FidFgcMx\nzUZsrm1hyjCzIxEEE1kk0jqiKCLSEiU8eVkxOB2jvaKygtUL9yGjlIObd8gmBYWIQUeYsqRwBdPx\nMfm0DxicEOSlpX80wGW1jZvxGB8TL23gipTdz/TBwMo71ii7Ho/ESrBCYKwgdppIxThmYGRwW1ZK\n1d0xizdmQbtwVmp4fE1VDrhY3WWck4bmi3gOCs5Dz/w+vsbHFv0kwxE4FYvtRylrK4GF886DS11K\nMP95ppIU4Twz8PMvK9AYpSEoFEWGqcJI9qVWh2JaMfZjhnt97r20xe3jPVRDs5SkDMZjUDp0ErwJ\ngidR03SFrHnsIXLO3teZkaVSiihOGA9GZ3bsM0BIyLlzeCCChOxASBV6yD7BG8vpoM/axkot4qrC\nPAigKiqyLINij4evXmKaWQoz4rB/i9yMkDEIocMcTDzOZxyd3mJYXmU8mtDonSdttLhyz2Um+YS8\nrEjSNmvtC9w6vo0ynjgpmI5PODw54bQqWN5a4ur519FsdtG6S6+9zMnwkLu5o9dI2RtNuHzxEl4q\n9vd2WVk2VId94jjGT6b01tdQUpKomLQKryM9POFjH/4In/yDD/PJj/wRo8kxharInUEiSFXMW//a\nu/mGb/tO7PIyZVmhZUzlQEcxSgW8IstzIiUx1uJVilQW5SxRXjE4OSVdWaGI6jQbsMZQFhVCK5RO\naTaXWElbTA+PGR4dUSz1sFbiTYZcihibjKIqibzDITjYP+Bwf4/Ne+8HoOM8PomJV9dJzl3Gi89g\nblfoa5a1L1rjbr5PmQhKAQJNbCKcEbgkoPZhjuRsXqmjMnU2sbDDBgaID85d9XVYD+8OxinzuaUw\ny0LmeAYsgL4vnz358rLm7OdFnwUpCKMM60YE4bKd282FNTCjOotaWl6zLJ16Gcj5yuO1pTmLENXH\n43EwfrCCle4qB7d3mez1ubJ1nrZNSDM4GQ2J1zsI4ZnmE2QkqKqC0WiAVmkw56x7xMZbfFVSOQve\nIpQKhqaVpdNrgzxGR3GI9qrmpxtHyLJqkKkOtrZyqCQmVS0m+ZgyD8BiZcPUqFn3ozKGqrRU2jPN\nctqdDjd3n6M/uBOckEUCMsFTAgVClEztEc+89CfENNhcXmaps0FVWLSPWIpXUS5mvb1FTJeJm1DZ\nnFYa0Rc5t/c+xO/9kWS8PeXqhTfTWz3PF232uH33Oa69cBdVGq4/d5Pp/iFXLl/g3OVLKKU5fuo5\nPvWJT/Kur38P7dUexpSsttowCZyGD/7YP+N3/+gPubF3Byeh1JZchtRYVJIvf/dX8W3f9/fx61uM\ncksax4Fubmd27xVRFCNkgyRq4ImohEYpQVNWvO+n/zllXvL1f/u7GWNJnKCqSrK8IE7TAOJKTZK2\nuHLhPLu3XsS5HCU949MhcaTodFcYTsdUrkKJQCRqNlusr64yHY8ASFUTLxJS3eD8xYdR6ndgWpC9\nlPH42x5nWnom2S7IAqXA+gAGClt7HtYbrZpnN6H74OoORDCA9QuZw0Krk3rhWzsfLDxrA87LgRlI\nuPBYWKwu6vLhrEJlRlH2nAWCxdbGvMVfny+Ey5rqzRm+8YrY9qeOP1dQ2N7efhL473d2dr58e3v7\nDcD/CTxX//qf7uzs/Kvt7e3/CPgOwoCwH9zZ2fn1L3Te2RtmjEGhKPIc1Vgin0xIhCKJYrJRRuwS\nbD6mHE1RqSLVCd1em5O+ZTyeIhJFopLAdptbuYP3lrI0KBVjnaeqDFXlSNMmJdMw8FSIGsyZDfio\n3XlseDOtDbbpUkZY6ykrG4BRF8Cm2dRprRUVkmajyzTLsbJkOD3AkqGI8MQEOmr4eKWESXbCzWKH\ni+v3cTzYYzVaoijTMPjEeGQFiWqzsXSZkRkzrcZEiaKdrPH8rY+ze/0pnnUJ3XbCyWSFTm+Dzvo2\nD7BCNjhkJDwf+cMPcH7lq3nsgavs3dnluYN9JtMR5y+eQ2qQkeD4+AA9DcHud37tfdw1GZkKmZUr\nK3Rl0VrxhiffzN/4lr9FtLXB1EgSFyz3S1fhnMDaikgF8pdSUSAS+4AZdaTnhY/+Mb/60z/B5Qev\n8tcn/z5R2qMqSrwJabPxAmcFjVaTSEc88fa38Jnf+9eU2jPNJqRCk1hBeTLEZFOksBR5howT8qok\nbTTnn4eNOrhRhbKaezev0G2m9CcjRodj4rLHvd2HkCPNqDqirCZMyLBakbgmSsl5wh4y8LrNOhtG\nK+qUUs52/QXLwJo4FOzgZoB4fcGHaAEz3IFXBpWFVul8sS92SWay6fDMZvb1oSPizgLGLIjVeJjE\nIUSdwhCu8c8XFb5gUNje3v7PgH8PGNc3vQn4H3d2dn544T6bwPcAbwSawIe3t7ffv7OzU32+c0sZ\n6tgoihAOqjInm4xwpkK3Yg5PT4gKT1ZUeBUxmRboOKllzhVLyy2KqmSS5zTbbaTW+LIA75BaobSE\nMnQeAKxzVJWpL54FfVxt+aajcEFLHKYqcV4Ei3elETrwKqJYMxlPieMIHcXk4yEASZKimjEra5tU\nlefg6C7Tsl9rOtJ5b1oStPkCcNKTVaeMsxMG4yMG6Qr3blwgjRqIqOL2zQNcKWg1lpmMLKvLPcbj\nMeeWt6CQqNgxyY/YeeH36HSusFo8Slk2yMpjzvWadM6tkZuKk70DXv/Ekzz1wQ9z4/YNHnnT64mW\nUsbllKPTEzoqZjVuA3DTnFLqQFjylaEVxWytnOfRJ57gPd/+rbTuvZ+TLEN5aDVS8rJgPJ6gRUyk\nWwH0FR5UhJcRzkJDWtLxkN/4qZ+kGuyTVVsYZ5AlxEqjoohSOkaDEUqlxGkT56Y88OZ30GxsUiRt\ndNRkBcVv/8ovcv3GM5zs7ZAqyEUYMZeVFYenA5rLYajN0JTIokCVCfesbrK+uc7w+gEUAj1UXLn6\nCFG6xDjbZ5wfcFQe0rcTpK1ZkFJh6y5C+Lme9KVCpnBmm+5r0LumOdeLU9U8kKoKNgBKzNCnGfpY\n//wyqvLibfP2V7h11pqs/yZQ05nr3V/Khd8As8ll9ZR23IzH4MPrcH+BoAC8AHwD8LP1v98EXN3e\n3v56QrbwfcAXAx/e2dkxwHB7e/t54PXAn3y+E7s6B+r1VjB5QVEWnJwcsbG5yumgz/HYkBhNXlrK\nRmgnWuOwtgoWbN0m7aUWo9EpRVGQSh2SJu+JVEI7beL8BK0jhFBUlaU0lmbawBqDdxapoPJlrZwM\nqHKz1aQoM5wNnV7nLShP5QqEBGMtsYuxlqDiC58Q7XaHpaUeh0dHHJ8esrQeM8k8SimoqdyIgAwr\nGRNJQWUyDo932WxtUrmMu/svcW59C2QJqqJyJZBSliUNmVBVBkFEM9liZW0F4w2TaUGVVUwGd2g2\nlxkWY/b2B6h8yH3bD9DeWGFMRaZga/t+Hv+yt/DsjRc4Ou2jheLR+68i2yFAr22usnt4TGIFadrk\nyS/7Et76lV/BpUdfT2/rMuOsAAs+dRRUTAdDRFEiUoGMwi7pFQghA8lGCBQ5z3zogzz3kQ8RyYr7\nH3mQJE2ZnhakqwlJGlEVJVJpBApjQciY9QfeyMbmYxRLXVpxzIsf/BB/+Bu/TJ7dYTA54Op993Dr\npSljEz4nlTQZZnm9OApILf0sIykh6XVQVtIiplsoNjoXOaggjtfppX1WiyOOprvsT+6SFwYRhe6V\nlGFnlfWuLP2MBRp2ZMeZYneRxuzx83mOMGssnAGMC8jjFzjOMoizYbgL7IP6eb3cSWmWeYTRBPPn\nU5dEzp7FjFc7vmBQ2NnZ+ZXt7e3LCzd9FPiJnZ2dT25vb/894AeATwGDhfuMge4XOvds7l+zmZL7\nMGS2LDJavVUG01OyvGDqSrxSVB5kpMLshbovXOYOhCaKJcaWZJOybhGJAEwuLVGVFilimmmTo+M+\npqxIOl3KqsD5IkTRUgbtgstDBhBrSlOiVYwQntLkJD7BUZGXU9qt1VBHl2E4C4Ssp9lcwQpPf7KH\nkwW95U2EGmJM3a7y4WKSWhLrGB1JclswODzm+HSP8twDnIz7CK3QSoJOaChBWZ1QTQ4pmuB9QX94\ngPMe42JM2aIZxbiiYPfkRXq9JTbXLyGdo3865sEr91MYxzMvvMCFB+8lWU+wSvD0J5/lnnsuka4t\nMfIF4+MTAL75O7+dZ555hmsvXuOJt7yNx7/0y1h54ArjSnDYH6FRtJstMlOxf/wSynpiHZN4i/IF\nRC2cijGeILFWEvYP+a1f+gVG4xPotnnne74WEceoypFVOUhB5RxCRVijsNYTI0jVMl5brj9/ncOb\nL/Cxn/8X5Cc3mZhDEgVPPvkkVms+/fwNhPeU1lDGDQCSVou4rennfY6zITpugHVoN6WVT1mXCau6\nR6kcSWudfLKBsku04iWmZsj+aA8TfGjqEkKjgl83phYVWWZBgLrvOFM0yjoIhCIkuPjVOky/IE5i\n1kKAPytInJUTzANPoCoIhAruXx7OnKYXMI3wwLOyZqYFOxP1vfohPq/XfH3UQeFf7uzsvG17e7u7\ns7MzqG9/GPhR4H8GvmZnZ+c/qW//ZeAf7ezsfOLznffa3gv+/nMPfMG//1fHXx1/dfx/ezz6dy7z\n2R+9+apsqv833Yff2t7e/p6dnZ2PA+8ilAgfA35we3s7BhrAQ8DTX+hEf+uHvpZ//UPP8vB3bKCl\nIJKKVqPF6GSEKRxF6WgmzVALCdBpRNJK2T++QbOd4hBMsinWWlZ6XZQQTCcZZWno9Dp0el2KosKW\njjRuYm2w9262lyjKCU4WYeyciJBCEQnPYNhnOBwQ6YjKWJK4yVK7x+bGJjdvXqcsMzqdNo20SVUY\nJpOMp//pbd7z334dy8sbXLvxGaw4pLuScufOPlo1EKh5ehdFEa1Wi7IsGY/HKCnJBwVL0Qpvuvo2\ntEk5t7zG8GRI5CNcdszu7nUqpWlvnWf1whZHR3c5Odrj4qVH0WodvEZLaKdNUp0SCY0xY6yZorwi\nVi2e+sRneOLNb+LCWo9f/z9+gdPdO7z1rV/CQCq2H9rm13/sf+V/++CH+N3f/AUKU7CUNkh8jLES\npxNa3VXiOGWQDdm59hzTyZRm3KQVtYhlQivt0k4aqGYH0emileK8FvzBL/7v/NyP/zB39u9w/v77\n+S/+p3/G+iNPMPYRKEnUULjKU0ws04kHJ2hKw+f+5EP8+A98D2/7osf4hff/Ou0o5lyc0Hc5B2XO\n6tol/u4/+AFORn3+u//mvyKOFN/5n/49Nl73BN/6jV/GT/zqp2knCeWgj+nv8exHP8Bv/uLPsLKU\n8p6v+yZWHniEqtkhXV4iaTSYFAWtpS7l+AhvTjHmlGd2n+Wzh8/S5wDfNJzWrMPIWERpUHWHypiz\ncYOzz1hqNQf+Zm4Ls2lkM/ITs/reqzkTMujtJFprnv7RA173vefCQGU3AxbPWIl4i3EueHvUyn85\no+lTO0b5WfYSpquFksf+xYDGVzm+C/ix7e3tEtgDvmNnZ2e8vb39o8CH69f/93d2dsovdCJXs+iM\nKcmN4eKFexBIZMtibY4zJbIZEWzQPEIJyipHR3pO8Eh0Qm4LrHG0u0ukaZOj42PyIiPKQt2PFxRl\nRdpsYWxA0vMijJUzPvgxJLqJEJBPcyKliaMoOBWVhqO9AxRhCpNWGu88cRxhjKXZDAKcVjtl/+hF\nRtld0iVDd3md23f26/HoNigTkyRoMooitDJFMMhotZpQhFZrUypymyEbMDkdcnp8yNQYVDPicLKP\nzBXHkyMG+ZROkXH/fcvkmcVXDqsjGt1lGkmL4fiAbFyio4TlzXt4dGkd2eqgWk0uX73Kzdufhoah\nE/XoNrqcv3IPAJ/c+Rwb6+tEcbNmxkm88BhTMJwOeOr5p7ix9xLeeZqiTcu16C2tsb7qSdqhBSaV\nod1ucOsjn+DD//JfcPdol0uPPsq/811/h3sff5KhjYhFmOyFFWFugfPgw7xO5Qs+8UcfZHJ0g90X\nHW0dXKBPy4wsSnjdFz3Jldc/SfP8fbTcJucvbTE6PCAbnRLXgFukI6C2ZIs0Dz/+Bj779MM0mjHt\n7QdxzQ7oJpNRhRYpSdQkkjFLnfNIs8zJ4ICLPYVQbYb5dcb5HQ7MgEFlKPDkhDnmivD5ztgIDo+x\nBl0TmebdCs4o0OFY/O4WSI6vcEWSsrZfCxHI1WVJWNMBLBezx4UzLJynDkc178b4YBk4m8D+Zx1/\nrqCws7NzE3hb/fNTwDte5T4/BfzUn+d8s2M2dbqRJByNM6ZZRpw06a6sgjuhMBmlz0jiGCkcOpEY\nU5E0UuI0Cu0ZF+YM5kVJB4iSiO5Kh0H/NDg8xylapZhaW2GMIY4itFaUhaOyJWXl8FYg6zHraRoT\nxzFGWpxSiERz7dqLrK2tEMVBxWmsQ0pF0goA3XH/FvvHt6jsCJ8rDg+HpEkPW9mw9j1oHWOtx5gK\na10NflZ4K4i8Ii8miEhy+2hAluW0oi5FJBHLXfLIMHAjsqNrHJ8eBpHT7ac4qUbhPFlFEjVop106\nnSUGo33u7N1kOJ5w/5XXs7Z2iclBzpdefZz1By/QeW6VkZhydWuD04MDkpXQfcjNlMIGL0bhHGmi\nsZQcHe9ye+8uL92+QeFzbGk5HZxiTizn1i4SRQmrzZRyOCYyI6YvDfnNn/xfuHP9eZKti3zr3/0B\nXve2d3FqVOgM1RulqTy2CsSoONH4sgRXcf3Gc4yt52iQkTY7nEyGCC+4eOVhvvHf+hZW73+MMopo\npU2+9Cu+hl//xZ9ndW2j9tAAGcUYa6mcA6mRaYsvftdX42SFXl+j8g2SZIlqMGAwPKXd6zIdj1he\nXqbZWcepiMonRFWMmSh8FjHN77IzusPd1HOYCMa+CvZ+GLyTKB0FFM/VxKH5JOwzYdLMDTrcDtQ8\niBkvZtHmPdxHzFmPiwQn5zyyFmWomojn66ARjoWgIELnzVmHt8zBxz/reG39FOoXHumIVpowGgyx\nfsj6xhbNNGYkPdNiiIibtFtNvCsR2hPVzETlFRWW6TSnLHPGkylJUxMliqghmQzHIQikkCYtjKuo\nqgAOKiVAOKqqpCgsggglIG4lbJ5bZTIc4qwLlFypWWo3GY+HbGyu1sNrA1U2SUKmsHdwA609lQNX\nKnZfOqHZ7IQxdbXv34ztJ0Q9xYqgrZhOc1oKHDkWxfHpEaeDERvr99FdWQ5W9bZPWVaUxZRKTcn9\nKYohzx/cDe+ltdjCYwqPigVClgFEJeIzL+2jd1PwgvHpC3zVW97O5oP3sXtywjsea/GBD/4mthUu\nkpaWCFdSFlMaSQupLaXJ2D/eYzQYcN/Fi0yrguEgY+oKTienjCcjjvpHtJqSlU6bhq34jV/9FT76\n8Y+ghefRt7yD7SfeznFhiWNLo6baOkd4fz313uWDGQqKixcu85RskNuIZppwPBrj0xaPPvkOLmy/\ngalLGU5zpE54x7u/gU5ng3u3H6dMWkDgSUihUEmT0hRkueLSQ2/A+BwfNUA10M0unSRhdLjHdDKm\nkTYYnJ6QyDVaIsH6JZr5FDfoMb5xBz3IOVcIRlFJ84FlTuKCkR1hnaO0HuttEMgJ8NYzE9bNxXbA\nbM7YfFTifDEs/nA2F1LNpj3V5YB1ZxwZIUNXRBEUuw5XjzMMnIo5J6ou0stE1wAAIABJREFUP3zd\nOv0zfSbr47WlOSdhKpF3nu5SOzgFOTjYvct95y6S6JiqKOup0KHemrngVFWYl7DUblBVJf1BWb9R\ngLSkjQhTasqioChCew0gSZJ5tNVK1yMGPUmaIIQjTmJ6q0s4mzOdTFFaMxlP6C23mE4FVVkQp03m\nfngivIWNpEmSKIrckI0McRwzHByzvLKCUhHGBzPZNGkwmUxQUs9RaF0HqPG4j2s7psUApywVFi8j\njA2OgmU5xZFjijwIWpRHiIo4VQjnsNrjEkFRz19M4gamVESRROoKKS3Xdv+EG7sbXL7vKgcv3KV/\n6yWOX9ghvrAWXof2xN7iiowCzzg7oZ+fYpxnpddheWWdk5MRyyuSagny9ZJsnBFFkqk0dBPBdDDk\nEx/9GENn8KnivY89xLB/QCmbFN4hWy2ipIMhAl8iCCa6xtcGJyjuufcKaayoshERKUndiy90jO+s\nIiaGpSim9I5ma413fu03UxiPTENQiOMYrEXHKaZs4qIc0hRpGiAilGyCbhPHTTrOI00FzpMVhmow\nxR2NcHdPUMMhupC0G2tc/9xnKW3MeqJJOj0eeLDHnh5wbXCHYzMI5aWc+TGc9RgEs+zgrJNwljrU\n/1toPiyWD7M5JTNtBNQkJkJFoaUkqnkNzstAu/dgfKBUiXlHohZVzUyH/7IGBVMGTKEsS3rdDiA5\nGQxx1nLcH9DprlANLHhFWRh6y8uUZeh8WusoTImOItqdNlk5IYojojgijsPI8vVza5weDxmNC8pq\nSiKg1VoOTjpa4SuPVIo0ETQbUWhpVTnHJwN0nJK2WthKoHRFWU1ZW+8xmUwBh5SesnDkdV98ubfC\neDxASk1RBHKTUpLKVDgP7VabmRGMc5ZI6zBNqDA4aUmcITs6wo4ziqhkZAt6okTEkE8zsmqMKQvK\nakxlDcgYHTUoywIVRwQTWksUaUxZksgG0sZEREQ0kM4iPFTkfO7Fp/mKJ9/D+rIlG+Wsra0wIEBA\nnaRB5ASxB1dkHB7fJfNTWq1l1lY38d4TCY2WmjRSNOMGyfo5fKQplUGLiE999MPsHu6RScHy+gq9\njS63bzyLlA26nS5Z1WGalFSiTUPbWoylUBKiSKMLycVLl4kjjc8z1pc2mFQFk+YSFx+8ytTnNVAW\n7OcdCqPbuGKKGAa6tpKavDLIKCJtJJiqgVApQiY04hSnY7yM8RKS9jpRWWCyKbaaMj2ZYO8ekd3a\no5qOQOQIpSijLqene2grKfenNM9vsLZ1GaIV1qpD9vp3GJdjZKpqhqMOLEg5W+2LDIP6WCgtFqPF\n4oyGsyOEmZm8CQIzX4bTBA0JzF2jfF2TBLymVnKKRXv6Vz9e06Aw7PeBsAsKFaFTgRiOkFqw1z9i\nM96iu7zGeDrEGcHodIqzAuMNUkuwFdX0FOE8STMhSWNs5TBS4Lyg2+4wGk5qQ06HkjI4LklHnGgG\nI4szjuVum26nwfHpkP5gQjYp2No4R7e7wWm/T6PdIM9yxtkprXYbKSMiDXmWUxbhzXWiQEQOR4lx\nJQ6LllGYAB1LkIKlVovB6SlJHFGWZbDxcp6SirbQtMc5bmyp1iWqFVEw4ji7Q2ZyCjtCKI81PljT\nSRDS4H2FqdR8MnJZFQg8SRST5watFTryYYCpE8Qq4u7pPvujY+7dvER+Z0x84R6k2AVgealHVEma\nzSaFLVlpt6isoLAV+/u30GmL1fVNqrHDFB7jIG1pLIqLvU3Gt+7wgff/FqWsMMpz5erDHNgJ3ZGn\nIxuM8mOwm4goQ9CGVgNPE5BEOib2DlzFaX+IsRonEpZaPZZp8Ohb385jj31xGOGuBRmeRGokiswa\nbn/m0+z8/gf4mnf9UEiVpYRYUQ1zYiHQIiFuxOQnewz6fS499Agjq5BpF8hJbZDUWzPGKw0ajo72\nGZ0e4n1JMc7o50O6yy2WN9YYJwrVXOO8Pc8D0WVOOhf5zO1PcZTtIbRHRm1yB9ZYtHRIpeYBwtf7\n/YxzAwR3cDvDEMIaCUVmeASyxh9qDxDpw2IXvrZeC9y40OmSco5R1DrOsNKER0j7F2Y0/v92TCbB\neakqLVVlUSpi5pvf6XaY5mOStIsQtWhKBEclmQTHo7I0YcetKpSSJEmEc55pZZiMJySqDT5BRxAn\nHaZZQdrKg022M3gPRV7ROreEFIp8mtFIUowxjEZj1tca6CgCpWikaxwc7CNlSaOhcd4iNeTFBIAs\nn6AjzWzqkDUVKlZIEToZe7t7dDpLbK5vMBmPA+CY5ygD2nikt1SjgihdIjYSrQST8pBpNkYJTbMd\nMR2W6NQTxymmtPOhqmVZEMUx1hrG4zHL7WV0lCAKTxzHpGnMNJtgfIVQgnE24oWbOzz8xqvIMsYd\nNxEucM2EyEmW2ty4c40Xb93k6kNXSOMYlxc02pokjWnFHr8cUxpJbh3NRsQ97VXM0ZSf/Jmf5Lkb\nn6OlBUvdLvc+eC8H128wkgm9VofltR5eQyeqaESGkoJEWIQKHYkqKymnOUZqSiS63QheD86w2Vsn\nFm0MEWkagS3QSJQALSqe+vgH+aP3/zzwQyzFknzqKEpPYRSJSEmF4p5Wg1/86V/is5/b4d/+7r9N\n+8FHgrhIa0QUo+OY3FqWl5oMbMG1689xfLSLdSW9jTYrGz3K6ZArG5vkK6uMkhjQ6KrBvZvbCCXZ\nPb7OwekugzJDRZKqHlYMITAL9fIEIASB2SCXmVKyZkLas89Z1p0MIQXCuroFWTtRI0NW4kPJ4F3t\nmVDTGF+uwPSvkrKcHa+txXtVW5lJxXA4YTrNaDZbNJvteoEbTvqHSClpNFKiSDMcDZGCMCQ2z0jT\nBB0pPJbJdESeZ5giKBYP9o8oCoNHUllDXuYMxycgglNNVVU46yiyipPj0+D41OsSR5qyyMiykIoi\nBFIlNJpLGGPp9/vkZRaYlLVNfZZN0VrS6TSJE1m7TxukFDTTJqayRDKiLCqsFcQqJYlSlFAkKiZK\nEqamRMYSX5a4MiMvT8nNCC8taTPBekuz3Qr0WxUGjUgl5h6XWTZFaUXaauORNFotkjRFCI/3FdZV\nlFQI5bl5+zoFOWuXt2hvnce1egBc39/FCMiHI649v8Nxdsru9AinLc1GRCosdtQnlZZEB4n2WhLh\nT/q872d+mqc+/scoLamk4Mu/+iu454EH6LV72MpxeHjMNMuZVlOMzElaHm/G2HyErgpEnjE9HTCd\n5vzfzL3Hs2XZld732+64655NW5WZ5QsFFNAOIJoC25BSKJqaSBxJEw00lf4rTiSFFEFGKMhQU2Q0\nu9Fo2EbDlUGhqtJnPn/dsdtpsM97megGe1o4ERlZ8TKz8uZ996yz9lrf9/v2r7/C61/9I37vX/wP\n2MkONZ6YBVpq2ixZuWNMK10tBDJ6mu0SKdJnSo9KQu8jUmQUIfL85z/i6Q/+Mx/95b/n/Fc/5Tv/\n7/+Dtt1YwDNkUbJpepqm5c69Ozx4+ClPnz+ksw0OS7Uo+f0/+iY7d27TRajKkkxEDANGK3Q0HGR7\n/PFX/5h/8vbXqWKOGh9kV/xEeMn3IF/oHa+ODmNfcPmbQ3qqX3YVL35bQqdcGSrjiyOEHDuDF5EE\nL9uyQ2K4/LZ2CpfhrErpcXjoqKqKuq6xzqJUpO8T+Xh//4C26Tg7u0AqSaYMQ9cxnVYQPet1m96w\naFFKU1UZbdfjfCArSnrX4OlxQaBMWgFqLZlP5ywvVgxDz87+PK3hsoymben7Dmtd+qaSkZmSfoj4\n0FPXWyaTCZfgzMtvQpZl5HlGnhu6bria9BqtqKoJw2BRQjEESxQKsgyFwGQTJjcMezducbp5BsJT\nNy2ZKthdTFCqJHhJllW0bX01mHqxokpT5d3dvdSaKsN0MkUKQVNvrpK1bQzIYOg2W+bTBZgcNZuS\nx9QpPHcZs6Mt9qxnr5zz+PwZTdZxvdxF6IydfIL0Ctc1iEEhh4HP7n/Ef/6Pf8F/+uu/5tU791gO\nK2a3D3jjD7+OEBl75Yz9eZqfIAL1YAmuRuqOnWyC9wObTUNnT2i7SF7MmU1LXr3zFoPb8PTsHK8i\nXbsmNxEne1yIBKHwUYJMoJjF3i1mO68AEETqIIS36ODR3Zrv/dt/zZOFwrk10DN0K6QMKAEgGXqP\n85DnJTdv3WB5+ozgaqKKeB+w3jK7e5s37xwSNbhZRm48oq1B9ljfc/v6PsSed159nU+f3afZHiOz\niHd2lEu/GCwktqNIWPiYQm/DSx4KSJ1C2r3LXxM4keQdY/JX+jmQjg7OJ/9JmmFeHldeLg68KFC/\n4fpCi8JkkrYPcmTOZZmh6xryPKOvW5wf0tNt8Gy3iZugtGY2ndEOLY3Yst02OOtRSieSTybpuwYh\nFXkusXWPVgVgsbYFVdD2DZNySpFlZNOC+58+oKxyqjynbuqU7+Aug2xHs4vSCK3wfSQv042ZFhCp\n2XI2WbPrukl21nEtZPuOoe/Ic8MwdMSQILFaKSwBU5T4oKgJ7F3fxU9y6pXFdwNuiJhM0dWBWaUY\nuogdAt6lVZR1A84NyeIcHEKk91AIickzsizHO0vXdfTdQCS5QX07cH1xSCErnINyPqU5S13RBZKP\nnx4hnxxTzip+9vw+3XTg1KyIKuM6u1SmYCpzMpnx+Gcf8m//9f/FL4+eYYuS2bV9mnPLP/1v/wW9\nkQzLDcEGZmbB3u41ilnG1m+I0dN1W7pMcrHaclHXrLctmZmwHxLq+eij73L08CNcv6GYzHjyi19R\n1Yk4LXNFEyPSjdb2rODOa1/iV4ukrHdIJD4lbuWS7njF8ZNP4SIiMoEImsNb11BGoZTG9RbfWbKs\nJDctv/jhDzh6/AAlPCEG+ujI5wvaYkLcv0HvLTLzGBpyOxBVjxM9SjhE6JiVU7589xWOf3HCxkfi\nZeDQr5mZZIL98OLo8OL48KIohFG8dIWAG1OofLw8PgAxEJC4OGZiX80T0nX5Z6/oTPG/fH74QovC\n7m5qWWNMwMrptMJ7S1FmbJpIjP6qZWrbBqMvp6ip5cqykouLJZOywuiUaFSWWUqbGlzCwYeIGxxV\nlZPnKf/h/PwcfWBw3lEpgQ+BSVVRFAVt29B0LV3XMlukYBHnLEIK8jxnu01P5cth0OVbm2UZ89kO\nR89PsEOgyOUoTupp2jVFUbLdbkj4TpV2y1olBWeWsa1rwtRwPjR0wRJcUmnu7O0SrOfo+RHRJ3Co\nIKKUpO/TNznh5tJRpe87iqpk8MOYnuVf2ksLVPS4xvONb/4BatBokzOpCoZ+CcCz5WOcKrl9Zw83\n8dSrUzZNS1CB9ukHKJ+0GFkx5Y2de9z/xc/46PkjBiKHu9eoY8fX//SbHB7Ocf2WxWJCXPcMfctF\nI1mUU67PZ7BcsXPaUB+UPDh5wqpreHpyTC5yrhe7lE6xPPqEdvMMKyPn5w1f3lughaesNLXt0TEl\nWuE0rh3omg19Px75gqMw4HKJp0Ts3eR3/vS/Yzj6hIsPfo4IgUcPnyKlJoyrbq012hTsznf54Nt/\nTrdZkstA7XqigvmdO9jJDlZNUCKg5UCmFbkI+LYD17I9f86iFPjtOdfyni8fzvjJ+Tnb8WiQWAdy\n1DCMAqNxLXn59L7s/CARqaJMEXXpUDBGGoxCu+QKZlzlRqyPyVw2Pqxe5jS8OEqI395OQenL85NH\nSUHbNQgp6PqGLNP0Q8BohRi14EKCtZHttiWvcgQ1XWupivQvzPKMtm1RJkfIgmGoCUEwDJadxZyJ\nEHTe07Ydq9UK5z113YzOM0HwnjzPado2dQs+4J1DSI0QEa0VJjN0XUtdtxweztAqKRqLvKJtO6xz\nZHmGEJIsy5FS0LYNeZYDAWMKlNTpWKIkbdfirSNYTzMMDN6RlznOJvaglJEsz3n85D7lTF6lYkWZ\n1l5KSSQCNwREUCiZ0TUtyjiy3BCcRcqAHlWPhc75k298i//qa39EpXc4bWtOl8fcupF0CiGuaXOB\nm+9htaeIc+rTNW3o6FyKg2uDp1kfc//sOdcOS3Z/7wbtacsb79zj7nvv8Ob7b5NFj5YaHxw704o6\nE/gqp6oE8eyYH/zv/4bX5jd5/3/9XzBGsq0bzrYX2OWWZ7Xj9YNb7N28xrJfsdwuGaRA7We4ckNQ\nA8plTMUkuU59w3K55oOffg8tUlHo2xUwoBDoyZSsmPNn//P/xukH30W6/4Pv/fDHvH7vLabzXeo+\nJq+C91RFhek8uTFXKZHWDuTVguLadUJWIWKedCGdxeZQ5RVVmDH0NVmuKEzDrDAEa7k9VdzfSmo3\nLhNF4DKJSgjFldwV8ett/VWnkKTMwafB4RiTnI4ZLw8PQyREiYMr6TOQhFQh/lqnkH78lnYKfgyD\n6euO+WxB1/aoXBNCIvEYqcgKg8k0fWdJ/EXHelNzUFbovER2LdP5hHp7gQ8NPlikySmLFIAyuGO6\nocdhQQR8N+CFoM0SsOVitcVkBT4q+gh9TDRnqRTRR0QQCJ9i3JVWCa4RNX0niEFTTmcAnC/XFKWh\nnE7QWlLXG7Is5+DgBsvzM5DJL1EUJf3gcM5jXU0fGvwwUKkKK2DZ1uhSEowmGzTW98x39lIupqgI\nThCjTjRinZ4oQz0w1ztYBPvzW5ycPMeGgU23xIcGLT1TVXK4d5ev3P0dvvWV/5pD8yanfsuPH/0t\nj04+52uvvwvA0ydPWE633PuD1/GrNV/au8dHTc02XGBygaMHHwkbT+dqjgpL/NqcPXEbebCPuF5w\nPqyoRE6pJRpFKwKZUBgcBz7woz//d3zvL/+CRzfv8d7Jv+TO7pyj7TnXdw4IsaRjyVo0LF6/hTp9\ngqkbovOcnTyjXh8je4UMOdPiABEzpDQUtmZz+ggjkm5E2jVCaMqgmJo0aFZ6ys33/5D36w2f3j/n\n97/+h4jCUEmIsQOS/LrreiblHJPPaYclfRTkJkdMFwhhkq4iV9jOEn3LYDuKKCiNYFLC+uQpdw7e\n4J13fpfTv/hLbjdTzk9r6sxgcUgBRkiUMCNTxCNICWVjJtxLKoJ0DA0hvsC9j+sBGUbRV0ikMcZI\nA6Ve5FKGELDBpYdcZFTjcrXd+E3Xb0VClJTiahDmrcPkOm0GJOjMUJUF9bYh+ICWaXXovSfPMmbT\nCdPplPXqPE1ex6GlcykgZrFYUDdbNvWWqqyIIdD0PUU1TQrEvufa4TXatkVISVPXCARlWSSU1Tg1\n7rseZRRN09L3A1k2+hbGit51DQeHNzC9pOk66rolz0qyTBMYA3DdwLCxhNHJlkJtPUWeo6UBIWia\nlnlZ4qzDmAqtDVKmdKq+75EZuOCYzDOGTiEsCAyv3X2L1XaT5hmjJt4NPcE7cme4vXuXf/Un/xMH\n5S0yO8cFz5Pj+3xy/xccrZ7z+u1X0/ekbamqgtPzY+Zmn1eu32FlNzw8s4DFuw7vPDGmNO6LeoVC\nM9vf49PTz3h0/pB37r7Fjdl1Fn6HShc4ETisZmSVoT065gd//QMuosOdHvHhpx+RvXUPmecc3poi\npj1ubx9P6jSiUMQoUJlhsjPj/vFjogZFxk5ZU6kJmayQIrKu12BTUShkl/QkecEk93TOolAUpmL3\n4BqzqkTVK9TyhKmZoIwiao3tHa63zGcLXrlzl7/74BmDCMidKdlihpAaYwq8gsl0DnWDDj0DKTXM\nuhXC9+wUks3RZ1RxzWuLnNNNw+PeIvMChEcLOTIWXoK5jp6GlxWNL44ULy0tLmcC49Dw7y8SUhfy\nD30U4ZKjMK4t/0vXF1oULmuVKSR1uwYlkUHi/Mj9I5mHrNVMqxkXpxuih67tiSGQZRqvDRcXS0yW\noUyGUYq2SxH1Xdczn885ONjnydPH9J1lWs0Yek/00Lc9ZVFQVQXW90gBdhhQSqC1QohUlEKIaKN4\nGZI5mUzo+55ujD4XMjAMfSpmzlHonCqfjetAh1KGtushRpTJ0SblXw5E8tzgOs9qs0apNPgKLqJ0\nknNbZ9PrIP2bdC6JOoywWo3WJfPZHkFELppTkClcRwWJ8gq/Fbz33u9yZ/9L5HFOFwaenj+mDmec\nb5+y7S/4/OhzAN5962029SkXZ8fs3noFbXYRlGSyoA+eTOVY514MrWRkPp1h6ViHFTE4OI9Y5emz\nwMIs0M4jMsvt4pDPf/wLTo4u2AKlUZx1W9zzJ/QhEnFI57EukOcF9157g9uvvMrzR085uHGDN957\nm+frE45Wp1TllKk6YVfvcji7zsH+PmYx5eP7CR3arU/YOdzHZIJy6pEiogPkWU42mXLjlet85z/8\nO74We37nj/85ajKjs4Hz51v04ChVxu58hg6OItfc/dLbRJMxxJRirYQgUwGT5+S+Iy8KvMuxy5pF\nBRdHn/Ls+DkTozkUgtcWGevnNUsPXunkkYgBEV4MBV82PL2c9MTofUj/MYbKXM0Kfv2eehFXlwRN\nUkh8ckGlI4UAJcQ//IMvXV8w4j2dx7u+x3pLnhUIkZ7Ks50F6/WapukRQVCYMjkOQ3qD+q7DqJKu\n62kutuwf7ND1jumsQEpP29b0fYdzFZvNFqMz3OBw0VNkBbnMGPoBQcRHR1FleO9xztJ3liLPMaXG\nZJoQQBmN957JpCLPC6SUnJ6eM50mebAykvV6deVhV1JjezsyHg1S5lRlQVUuuFitCD758Ikpes1H\nz3Y7UBQF3nnwkehg26wp8inT+YTZouLs/BQpIn1v6QYHZPRNy9Pnzxj8hvVwTtvXOO+QZkIeNbms\neOvO+5i4w2LnkNY95umzh/z8yQ853T5C5Tk/HXk4r7/2Bh//7Izm+Iy479kuWw4Wt9n0p3TrFUE6\n4mgUG5wgzxaYvGK5OicYi1OWh+uHOCJ25rGlQzY95/6I+OQZP//O97EhYICd67tMD+esNeRe4Jyj\nH/p0VIsRM5+wd7BPingUbNoNajLholmzHTpOuzOO7DNWuytU8SXe+NK7fPcH3wHg29/5Nv/9//iv\nWHVLzs/WmJhhQsFc7ZDtL3iwfM6jD3/G4vYe/+zP/pSnzREX6w1utWXWDOjB4jZr9oQiTqa88fY7\n9FmeOpcAykc0AzulwQyBed5R5YLjrkb3S9bLI2SuMIWitJY3by44ayP1xhN1jpdJZxC95zLlKXh/\nNcS+vOLl6pl0H8uXVtHhyl9xabgap/IiJYsL1IsW42oTIX/de/Ebri+0KLR98j4krJXg1o0bPDs6\nxrtI8AoZDS4kjfvp6TkupMocg2NoO1xuuLhYk+eaEAXOelarDdPpnL63KDXQ9y12JDArqdMxQJgE\nTx3x4herU6azGc12i1GS4AJVVSYuYpUsxcvlkrZt2dnZpe+3TKdTrD2hHb0Pg7VIY9Aq2VhtN1D7\nTVoRItNGophQlTscnyxxMiBFwGiJtT2DDbRdR5YXRB/xNhAUaRAlIC9yyqogrzNCDNi+w/aW6DxK\nGurunIvNKRSprVc6eeiFTGiyO2++w+HsVZ4dP+T+8pf86PPv8OPPvsugOjICT54fA7DYW3Ct2uPz\nX33OZucxBwcHDGLGYnKDwW95evo5joh3IIWmyGc0TUfTb1DTJCJTSrLuLngcDCJEDtUcFPzyu3/L\n46PHuBhZGMWX/uBdXAZGCaYarIJ8ZhgUZEKDjriYFH2nx8d89smn3J28nYq6yZFCkmnDyfKU7PFD\nVJ4hVMoSefjsKQ9Pn/Gjj35M21tmxYLD6Q3evvc25JLPVies+y3f+f7f8M7PfsiT0HB0/JxXzJzX\nww5iaAk4ShmZ7+4z27+Oz0tinmOUIpOeSgYWmWNeKUR9RmlPOcgtdbtNzkiVYXVgsC2zyS73ru3x\naHXE4CRh3BgJIcbA5HgVmPxrYTCXHobxSBhHDMfVxuJFD5HqgRxZkkKMLu5wVRBiHNWKQr4UPfcP\nry/W+7BNMuf9gwNOj45GACVINOfHK6bTir7rCRGGMYZMmUBmDMH7KwdlUU3ROtGeY9RsN1tmsylK\npVVh03QQHUYZmjad711r2dZbVA4hOPJCpf+/lFRVyWRSshzWmFGEdHZ2RlEUCCGo6xqtNdb6K41F\nCDFJtYVKlmspaOoaZSCvcpwfsNawWl2MPoVIva0pC5O6Be/php6Jc0BOmZXIKCnynCwzxOBoupqu\na5FSEx34wWOHmtuHt4mqpx5WFFVBWeRpHiJhcD35POfp8jlDPeWXD77Pn//N/83T5gGdTh/es7Mj\nJrOxa3M9r+7d42nzGY9+/rfcuHMdyj0qc5Ob+5reep6efY6UEZUrouiouyWmkGTG4L1E6BSf7kXL\ncfMMVOB6UVAPK05dR09kXmjmt2Y0skeolGjirMXpSBdq2s4RtUsS5xjxg+X48TNe+/Jb3D64TpFV\nMAgqPWW97hhIuROlSdqX1958nUfPH3L/6DOaoaOUFReTU7ztuHvrDne/8i4/vH+f3cNbmJ05fhj4\n+Bef8EBY1vFVFhvJx2cPMSoiyxJblOg8Q5UlucnIVc9BlXFQKSYEbCuZmpK9a7dYyZbBW4xQbAab\nBEYh8MrOgtcWWx70AytrIaRwYzcKi8K4Ov41ncI/6PJjAtPwYhj5948cCJFgwSHgox8NUYwgmHEN\nKn5Li0LXXJKXEpVoudrQd4kW5AdHGCLCp1+fL6YsLzb4mNZrIQS22y3T2QQ/BmpW1WRUIdqxCsuX\nzmYRozOKzGOHlP40DAOZ1uR5hXWWxWIHYuTk9CilQGuNkIK6qZlMJkwmE7bbLVJKmqaGeEn4gTwr\ncMPA0FuKLEcSUUbQDy1edGQjdSlESzXJEMpjB0VmsjQZxjMMSVPQdS2FyXB9IIQU6W79QLetsdYy\nnU6QZPS2RZcZkZ6LzSoZsoRP+2pnmZYVLjpUrvnVo8851YGff/p9Pn7+M8LEk0007bLFO8uNW9cA\n+OzJA/5w8R43F9d5evGI42f3Wby+Q5Uf4vvI3dvv0/Qdy+YIpSN1fY6LDYUqwEc0ChHS1JtJQOSC\nAciN4e4ff4P53iEnHz4iywLZTs7Kbmm3PUNv2bY9RV7inaerG9bc3Yr8AAAgAElEQVTtlk2zgnHF\nNskLDud7iIlBC0MAfEhDSCkkh/sH3LlxG4Dv/81f8TbvorMUdlsqgwwDR0cPUc7zxpvv8LPqbzg4\nuMmDh094HI8578+xWUN/vqE8C3zmTrlZwWv3XiE/vEa+s0CbEglUOrI3g5lZEuotuzv7LKo5GsXB\nrKBu17TPnuHqNV0nUK5mms356p1X2BkCv3h2xKqx+HBZBC71RL+pKFxOG8d7WY426MsCMsqekQKU\nQsp0bLjsOC5nFXJMUeOFQPo3Xl9oUSjGF9bXG5SOFKUkkIZkl4MXYxQiRBCenUXFZt0ggqRrLTpX\n3LxxndVmifeO3GT0LqCzjL7zXKyWzOcT/BDot55CJvmHVNAOLTEK5tMFCkWzHKAZkHJCUwuqaXJU\nbruGVbPi2t51ht4z9AElFVWhaQuJHQeNRWlorKfvIsGlOLnZ7oRm22DbRJkyeUCYZPv11qGKClNO\n8ENHDA2ZBiku/fAaGwVFmdEPI/zLJ3qTkgIVFbmYsLu3YHAtXrboHHIj6S0M3nIgFSIXRKlRehcp\nex4ef4QTPcM2IrxBxwxZCFqfjF1Pjj/n9Euvs/jd9xiO9nBVxbP2EYeHr1OFfaKe88Zt+PzJD1m3\nj/F9h4rpw+bxiTIsUxp3Oww03ZIuz5lPFhwc3OAb776LW52xXp2xc+2QiTKcnFlqF/Eq4oeG4DxC\nDQgXcEONlxC8ZLMdQOY0XU/0FkV2hfQTIZBJwd5+EsT99C//CjHtuPv77yQuppwzLa5RqQmFFNy7\nfY3FtOKn3/42P/7xd8jfPyR/c8a0mHM8OWFQK/pvLTjeFvjffZPpfIrMJbnRSB+Yac2MFtuc0TbP\n2N0rqPsVp0ePqApDZnbJVcdbuzkfH59zujlmPgkcTN/g3s777MtjPn3+gFY6Pj8/5tyvUg4qFuEV\nUYyskVGPIK6UcpezA7jMjxAxHRmUVGihUtcVQjqCSIXSBttbtDEjtEX89nofLhOiirKiGxqENuwf\n7HGx3GKdpes78iIpCiUyrSS1vCIfzaqS3vZIKZPBKSboZd/35IWk7y3OWpRIAS5aakyWqrJ1jhAD\neZHjY4vR6Y29/+Ahewf77O3vITVcrM6ZTicImcQlRVUSgiLLJdN5dRVFb20KH03xcQGdiXHuI0FC\n36d069WqTQlEwWOyIiVbj2uoIs/puo6ymuLcgA+Kxc6Us/NTFrsLvB8IAbquZlZNUVLinGMYBrQy\neJlaRe9St4LIaJoth9OMRVYhNks2mxN8GKgmc86OzpgUJWVlcGnRzcav+eT4M96+9yXKgxmnwzkf\nPPgR39xb8P6bX+fp02Py+T283fJ3v3xKNilohyGBRBmxX8FhTE70jr5rWa43bJZnXCxPeHZwjUVV\nkE8K+sEzNwU7k332FgbnI0M74HqHs46syHCt4yff/QAjAt1qiQoDVaWonaMetihtEFrQbXsGG3F6\n7D5jJNjIXjFLGyY9JQZFwLPxHqVh/5U9nv/dLwmnHRO95p3bv4efChavXOPBcYuXE9ThhI+Gz+ke\nf5v5bM7tg5vsFzMOphOqqef86ZZpPmV1eg7Lz5GrTxHTCr97k2s3b7C7UJina/7qxx/SdR3BnbJT\nLvnWu3c4MEvUzpyfPJryowcfctx1ILK0avQvlIuX68Okqn8pVGa8XigjBTFAHO3ZIVwmmAmkVDjr\nyas8UcN+W3UKbT862vISnOX09IKimFCWE4ZO4IKjysqkBwgBHwJ+DH6tqgKt0jBtGDrQGb1rMTol\nOoUQyLIEST3YnRNZYq1jZzcxFgCUgq7fYrIIQiGlIATPzZs3KCrDul7Rdy3zxYy2sbTDgNEZ0/kU\nhGMmJSKm4Ifgky5CSVCjB8P71Okk4YlAG8V0PsW7geXFEl3qxFOwA1JKZvNZKmJKMdiBwQ0sV6dY\n16HNDpvtirIsRkkzzGYVTd/S9z3TRYWLKpmlPMi8YNVYbBOZyYpXywkPHv+Sod+ACJRlzmQ6oatb\ndvd3COkUhK4MT1fPef2VL1HkM85+9TEX9VN++uFf8bU7X2VnOkctFa/uvMvx/mNO7Kc4uRwVNfFq\nF56m6AEfLNbWrAh8cm456o6pdMZETyhkhXGSIi8oioosK8hVBjagEJQicnj3Otde2eXk4Rkydrjm\nAj2ZYErY2Jr1tmFoLXbTk6NRCdGID5GT+08pO9ifVRiTsRkGLBEvDc448psV9c9bch9ZPzxl89ET\nFtNb9AKEF0z3dlkvVyzXH/Dxh78kC4rD2Q6vXbvBV+/e46t3X2G9XTFRjtPTUw5Fy81cEBmopnPM\nznWkCXztq19FZjf52Qc/Z7vtsO0JWSW5ZrYsqjmLt+8x9Gu+92lHHQIuesLIL3U+oIVAXbIaX7p/\nkh7h16EsqcMegSve433yW2id5nDeB6S49GH85usLLQpZmYZbF8s13g9Y62lqizEFs9mU1fIC5wLO\ngxaRW6/c5OL8gvOTLdduLBh8izEJVyUVDL3DDj2LvV2U0uR5ztA3CCGYTAr84Mnzgq1oKYqCQmRE\nAsMwkGcFdVMzW0xpu4ajkyXKJHejc44Y0tqoH1oWuwV93xJG+TAwzgUCk2lJkRcpfDY4tNG0TUtR\nFcSYlJFaSqILdE1DsVtircMFz6yaE2yiPzk3MNiezRYm0ymbzQrvLUIUqRDajjwvsNahtCGGS9ep\nRoRA9J6md8Q+km8tHJ2wPnqAdR1FmeGDoygN7XaLMTnDGPZrMsPqbM3xxTHvvf4eSmoMgccnn/Ef\nfvjv+b3X/5i93Wvss8vglvzwkxO6uMWN4NCU2Jx8HzGAd5FcFakjU5GVqGl8zXF9AoOArMAtPUoq\njDLgAqXOKExOJQsOsgW/96e/w9/91d+yDWtav6GIUGYlU+3Jcsmmt2jtkc5x43ryq+TA+f2nHH/8\nOXevH9KJZL120fLo2TMGu0TfMuRv7nL2yRnaRT78+D7vvlExmRxiRJW6r3gOxtH5FXVvOV1/xqeP\n4O8+mvHWrTsssgkyRDb2jL1szT+5M+G9xZSpCKyPnyPzKYdTw5uv3iU6z0efPeZifULfrvH9GnHk\nuH7rTb751pucXGz48OgEJwQhpI7nSrTE5aBw1DVcfu3v0Z+vho6kopDQ7xKlJFobvAsI9Y8ol/iC\ni0I1yQFo2xbvPM6lm7Bv15TV9AUrQAqKKqeaFIQ45/y0JssUfkhPp8VihrUDaeAasLbD+UhZlBgt\n8c6S54bG9pyfXWBMBlKitUKawGAtLgR8GEa9wZLetkyyHK0kuVboIkOiWa7WECLOdUQh8COSIsRI\nZjKMGjFsPiUhSyLOujQ0to6jZ+fMp1NiABmSqs0YQ8iSFkIA9bIlBIvRisVihjaazbZO3EFAazMO\nUxNRWhuF946uG9K8YgzsHQbYyyv88Qm/+s53OLKfEaJF6RxlBNIK9g522TZbpqM5TQSJdVt++dlH\nvH7rTW4d3uHh819y5i743sd/zc78Bt/60l2mYsZ6+YwvX/8dus9r6iyRjYehQwiJUho7pKdSqSdo\nVeJkAOlwsceLARs9wmX4GBLo1ELwgcpnaKspzC7bvubO9UO+8S+/yfLsnHwvRxWC0DTEzYbKZOhc\nMwiBloob13cBMKWgrS0P7t/n7T94j2GW8enxU2SmOVndJ2iHuZZz7Ztv08wes3l2QYfjlrfkUiF1\nwc50h2azxLEluIBVEYenI/C0vuDZxxu0LNmZ7TOpFB9bx6O65c/eCvxTv6U/O+Lma29z8bhj3SmM\nCORasg4dF22PiIHN8hgbPfdee5/ff/NNjpYbnrbbK/ft5Soxjga8OBbfK3XjeL3cKaSQ2+SXSE7M\n0Y05HmV/qxmNMaYWSQlBlhcsm5pSJ4R627ZoI8myjGoy49at62S54vj4iLISBJ9i5tquJss002lJ\nPT7NjTH0g0dIyWw2JzqLUoLFYspgB0IY0DoHJYlBQDQMvWPbrCiKnKKqwAa0VoBHKUHfDBhpiNbS\n1JvxSVvQNsmAc3h4SLPeslqumJQTdnZ3WK7X7MxnmKyn7XqUCgSXti5GaapiQhj30tPZDBkUQ9OO\n58lIURYYrbEuWZ6Tnj2JY4NPjjnrPSavAIEf7dNVNcXXHb4fmE8myONzuvYIc5AEY8IYtNFY7ZhU\nU07PzpmQnrCb7Yreb7n/bMPDZ1/h5sEN7tx8k+NP/4Y+LvnBz/4Th/PrvHvjd3njjff58pffYPgL\nzw+ffxedafwI1lVKE1Qg0xGlElrUSIFSaQhGJvEuYKzD+8DgPX4MSOmdY0DgMokTPZlObfutw7vU\nrmXuFJnMKIsKlWnMtETYgSF6li5J5+/8szd49tljuJbzoD3DTOYMytNs18yv7TCEnudnp2yKyOL9\nm+R3Sly9ptEdj8+fIPOMs9Ux1vZjuKxGxvTUFWPmZZSSoA3bOCD6CqF2+fDoCW77EPPlBW9OJev2\nObu7exS6wtWSnSqjaRsu6gYbIsG3dOc1k2s3uLs/4ZW9OcdPt0Rhxntk1CnIUXH09wrCy53CrxWE\nl9qJS6OVIOHgvXcvdBC/4fpiXZKJbkGeGTKT4wc7EnEFTqSKprWi7weapkWbip2dBXhB23UE5XHe\nEoJlMZ8TypC+id4So2Cz6RIMVCVyclmWhBjYrGuqiUJIRbTJr+7iC6BLYXX6e7sepWBrNwifE/yA\nkoKurolyYD6bMqjLtWpaJ9phYFAaqRRNU6dgmaygrnvs4DEqiZn6diBGcNbRNA1lKchUjlRpBuFH\n1d/FcokQKvH9RLqRnPMoJIMdEFLibApLMdpQFBnTapeT9SMyCcp3TGTOtZ0Z7TygfYYXkq5LBi+E\nZ7A9XZ80I8vmnHZYgzB8/PAD9nb3uH37NT64/2O8vWC9ecL/91f/hvyPF3zzq39EX19wePg64vkP\nU9eiTZql6IzLEByvLMooMiORSuGcIARFQIAVeJc6NScgjLjyzBgmSmGUxEtHLz1mWqKzLHEUM4GY\nlGxtx8lyyXm34nSzZNluAAh3K24cvkZ18xoXxtJeHFGanGHr2ax7rGuTtDqXdHFNm50iRMtpM+B7\nTdSSPDNIH5BGJFSbVORBENw4/BNJeFVoUip5cDgz5WcXPeffX/Mn71xn99GSrw7PeO3em+gMXr1x\nwKQ0/OrhA56fr9jahrzIubg4gvyQ29d2+fDk6GrwGyNpm/PSEeGK5jx+6df8DSG81CWMHpsxkAip\nrjIm/hGZwhe9fRgZ/ZlhcB3TRY4dEq1ob2/K6dmKfqiJIfLs2XOePvNcu36INAVD16PQiBggwHbT\nElzA+4jBI4SnzBXe9miREWNB8Dm50jDRoD3ObwkhooQGL8mEIlcSwoAWis1Fw3w+H3FvAut6skzQ\nDw3z+QQjMnIxTu2XazKTIZQgiIHT86cICetNzd7OPlrluN5R5RWZyli3S+p1gyk1Q9sRXaDanRJU\nRog6bSVEwA2WYCO7uwuK0rDtO6IOWBfph46yShF0w9AzWUySMnN5jlSGQkhkLDn43W9y+51vUp/+\ngnj+c5zz9M5RTTKGEMiKjKHZAqQV4yDQRrOyxzy6eMDtvde4d/gVPnnyA7bhnKftL/neJ9/m3mtf\nZnu2ZLON6DhBeIeQCi0NQppRcStROkNqjcenoubjleN18BIfEnw0Ke8SKVsgsL5G4tn0EmEK4vaM\n580F2ZilcbY8Z9s1DMHhZcQ5z7ZLReGsPqHMZixFz2ZzAlKzaZP2pBk6ohZEL8iEwEvNIKHzfZIa\n2/SahZ6BTEIgiULIDLTBCz+mlgdiVCBS7JsmEqSiFQWfbBuOPjilVJ63Ng/4VpPx1vVbXJ/NmE2m\nvCoqDvY8D54+5nh5wrOnF2Q7JTuLQ+b5U1ybhuFSQJSpYKookVEjhBtXES/0jHH0RAiZou0YNTqX\nXIUQ09evZE+/rYaowabhVtum1lprRVGVbDZbqlnJzHZsll06g0fBatMSOCF4yXQyoSgzLi5OUcbg\nhsDFxYqqKijyKZv1ivliTt+lJ/nu3pzT5+cUZkJWZEjt8AGci2iRj3tvz850B2kibdMRnICYaH91\nX6OkRBmDb2E63aHvB/oh6RSUSgTk1VqhjMJ5izEZXWMZ+pY817TbLbNqh+mkZBhq7NChTIVSCpMp\nBttjTEFTO7JKYPKC4CIhDsynk5Hpn2CsTd/gx7OhGxx917N/bR8hJM/PztnfuUm3qhHFjDe/+S3m\nN9/g6M9/RNN1dNqCkITo6doOISN2dBdG59BojDJMZgVn6xOuzV7h9Tvv8Pj4Q5bdEdo0/OrRjzhZ\nf8bQWM7Xp8wnC5b182Tb1ZoYIASPVhJjcqQE6wa8HxiGYczb8ISYVsNSaXKhUthJjNh+wA89nezR\nqqezA2erUyZVhRSC1XpDRCC1pJhOmFQTpBDoUdFojLoqAMKn0BglSvYOrtFsWpxN6P1MGCpTMegK\nKxtEACkkMgpkTMc1yZhH4QEuMyIDnhHlJlIUiyAi4ghUzTStgCbC9nnLw4uf8pW7p3zjvXd5ZW+P\n2cEhN29OuXnzVX74k5/w7PScZ0+e01QWKQxZNlLJwqhK9mOHICO9gqAjxehpeAFjHQlOQqTXLMRI\nAbtcTcYricM/dn2xLkl3uRaRSKGRIsWqFcWMrh0oy5Kutggh0cYQo0Crgsl8ysnxKYdmlzyrmEwn\nHBwc4t1DsiynzBc0MjB0Bu8ibbvirbf3efRgk2CvlQGdrNdX0eBR4l0qElWW412PyYoksfUOH3pi\nNFjrMfkEIQ06j1QmDUuFBB880+k0zUqEIDiJUQHbb6kmE7QJlBODUB6PxTswZsFOMSevCvomIKSi\nax0q03gXmc93cKZnu+nobE+QKWTU24hUGhklbd/S95YYPJv1KuHZ7YBVkfO24aTv6J4/4Xuf/IzW\nNQQZUSaj6xv6oUs23vEo511MpjMdkDrlfZ5cHPHarbu8+urrnHx8n+AbBvmc//jd/5Nr09ucXDxG\nVgIpSI68IPDeERiQBqQiocWFoO1auq4jL5JPxBo3dhOJLOSGy/mJQohIkJ4+bIl2INclw6ahaz1G\nV8wWOyitKcuKspxgMoMau8+inEBUIAXOJedqWSis7ei7hq6t01E1S9L6YUgGIqXHOZPQxJBuquAF\niAA+KQGTP+sybalPhK/xVnLWXoXIJqS7pMXwqLGcfvSED56e8/4br/I7d1/l3mTK7nyfO++9yb2N\n5Rc//YRfHZ1Q2o6zkI5zMpcIqVFBIn36jF1Zn+OLOQNXAbfiJYjLy7OGMB4bxpDaf+S+/GIhK86N\nPyf342I+oSymLFcrysJgbYsx46TdB4Y+UlZTrl+7weNHTzk6OuPatUPKYpo+zKP8WYhAUVQELzHa\n4JxjebHEeQ/eY0LECMW22RKsYD7JccEz9I6T43Nu3ryGs+AGz8ZtmO0UWDukHMmYZKIeSTkpiX1y\nSeZZxnazHW8ASVGUxGgod3La7QYpFHqMMus6ix0c3gIuZVYIEbE+5ShKk1rWGNNgyEbBarmmmFTJ\nbx4kmckxWif1nwCtBXWzJS8Me4s5ZxdrslzR2pqffvQL5pM9emURRiBEwBiJC5E8zxi6gWw0Eskg\nkGik1KxWS2KlebD8hP2dfe6+8h6fP/qIZf+UfDfwyaMfsZ1fEJwgNB1aKgbn6G3yqwSRXv8wNEmo\nJn59Ny6lIq8U3npAJOPaCBnJsgxlJEEMBOcJoqdzDjcotJqQVwXSSKIIdK7DRINCYYr0kVZG03UO\nNXQgk+R3GBo2mzO6ZknTbjAqI2YK51usa0nhTiplJowcDQEjuSgSQ3IxRjzeW3wYko/GJTZG8B4X\n05DY+xT6q4IEozDZBKTiSd2z+ugBnz18wleuH/L+nVe5tbNgf7/g61+7w6vLjtunF/zk808A0H1D\nKGZ4YwjKw9BTuIhAE/RlQWCEtcBl0YLRDEV48fqvzBL/eLvwxYqXmlQNnfUILeh7x2ye03YDM0ra\nZkhDK6VTxoNJTMPl8gKloGlalssV0+mM4+NTzs+XzBcZIRr6oUZguMzQOTvdJAeagMmsYnd/l6OT\nYy7qNfu7Jg1mYnpKOhcwyrBut0RhUSatzIxUBBEY7IDzA9s68RcBjMlp2xXVpERKRdf1KCkQ+YSD\n67eo1xtC3BC8RAqDUQWhG1BC0tYNVlqaNrA3nV/hwLXRiZkAZCZDo2jaNrXmeIxKGokiKxiGgbZp\n2dtdUBnDZrXEaEEYLNv1iv3FAbs7E+pYsWo2aJ0jYip8IgakTB2PkoZc5TjnObs4xegCW2/49NHn\nvPPml7l98A4XvzqlnyTp9ao55dbePVabDiUlRmg62+OCRxeaQMKZOa/GyDKfjks6w2iDyg1Dn7wP\nQYDU8sr3L7UY7b9h/AwLpFZkxhCVpbFLhmHAaJ1oyqG8WtvmVUYUPs0nRILZ9H2PjwOEDhF7ssyg\ntadpWqIYUkgKOSKOadGXugvS09Z6jw+OGFPK1yV2PUaPCxHnX8TMS5lIzUpKTBRkCHwURDOhxfJo\n07NaPaK92PDVwwkX+xXT+ZTd2zP+5JUb/JPrqUj/N4fX+HBj+awbsCags4jxERUiIsiEeAuj6Yn0\nQErq2zQJveyEU4F4WdPwW+p9uHxwOOtARJRWLFcXNG1DUdzm7PSMGBR5VeJ8Q1UZnLM8OT9CiBTf\nba1NSU2DpShyTKZp2prB1ihpCKOAxpgMrSXgmc5ShJsxhumsorcN1WRCs9VoDdFbiqIcjw2O7aZm\nNp0ig0QJjxCWttlQTkx62pNWVc5FvAuoXLFeryjygPeB2WJGVIK8LBiGHhFhUuS4xjK0PXIKTVMT\nRZ5YlAJMllFNSkRI8e5Fnid6U9sRvMMUGjv0GJ0lRaSSxJACdqwckHJkQfQZi2qP29df4fhiwWld\nsm5atMoRQaIyEMHixtmLigo7OLbdlmKnxGNTEvbxfW7dfo17r77Hoyef0YVTdAl2qCnLnPVWpb8z\nGkSMVxmdIVj6oUcgGIYBIQRlWZJlBUolPYOJYF1AKY/WapygJ4Wo1iYh8YRO+DIpMEbR2y2dbbF9\nT55lmMyDnODFeJzToHJBdJZI2moNQ09wJZkpKPMJWiliCPRDj1JJdAUklNH/T92bxdq2pudZz9+P\nMeacq9l7n7NPV1W2q8rbDsSOiRRIFEIQohOdkBBXiBtEbiJEriKRCO4sJIQQgiAhRUEIJJrQ3CEa\nIZBCgIsYjBMr9q4ql6tcdc7Z7WpmM5q/5eIbc53jUA1prGMPaan22WvV2nPOMf7u+973eVtdW+YS\n5pNzIqYETcC5WjUp5tGoua4EpUKjyrOsBchqlMFrg2l6NSVVYoOkHYcKz2/21OXAhyfHexcdW+/Z\n2o6nF9Ii/tP//D/L//RrL/gvf+mX+fbpFclEkvekIgItdWavnFVOSujWWL1ODJ8Zon6bk/JHXF9w\n7sNnbRetNBeXWz799CW1JU6nmavLJ4x2T84L3numeeZwvKeWJJyA4NBak7LEo4XgGY8zSleUrrhQ\nRR5tG9vthmnSa3aC55MXnzJspMW5v9tjtWYzOHJJwlcMjaHfEvOJkhdKUmSVKSXiTKWWyDwmplNc\n34MoxuZ5QRuH9xbvHbEsvL17xf7+jt2wQZVCSwVvGsEZ9vf3XA4bjLU0DLnKGXu7HbBW0VLlNB55\ndHFNynXVv0s7t+REq40YE1pLW/TFi9cEv0V5CMqBCvTDI4ZwRSsWmqPrLmjNYrRld3nFfJy5jRLh\n10rluD+yvd6hrOY43rMLVxxPB7753ef8wa/+PM++9nfz/O1fwV00ltcTr199ilaBItRQVAEMpJwo\nVcA1OWVKKRLqu7bYZPFSQii0lmWZMaLFk/eowaBpKtCFC6iazILViuM0EuMkse9VU0skLoq2KjPH\n6cA0JnKKaJ3RqpJixYRAcDu8G6itSAxfMxgdqMy0ltHaPeQvtlZoTVNLorVIa1VsyeccpbVWUluW\nIwTlobJ/ntSa7cgVGmktrEaK0VRjuK2ab94tpJhgTmycFGRfP73iDwF//cWvc7F7yh/9+s/y4ZtL\nvvHy27w4jKhu4JxkfW5Dnge8XhmNUodcCdJaZPe1VkrTv3tbktp8fsujORz2oCIhKF6/+pjL3RXO\nOrbDBfM0kebCuD/RDZamlYhH1kLgPE0EL7QjZeDq0QZUpipRNBYaNli8cRxO96S8EKMi2A5qZZ4n\n6f4aSLkwHm5F+DRZWsxMcaHbCO9RmUYXNPO4fE4g0nA2cDgu9EMALA0JmL07vKXURK5eiEot04WO\nsIXp7sAyZpR2aOU4HU4oC9pZUs4YYE6JKS0o5fDDBhcClEJZFqqWCalm6IaOzXaD8T1zPKCVQ/se\nrAffUdC4botviuk04pzjZn4hqd+XksqdimbJlQsvxbQ4J1oIeJ/4+JPnfO39n+SDD7/Ki+Nvcppe\ns7TEzfyWd3dPUfeZLlXmBqMpkDNLzuhWIBcsGpVAlwZVYttzW1tvWs7sKUsovXWyipdSaHisc5J/\nQCOpiVIWWskPEevzuOCrRq+P9Lw/MU8ztRW814ihvNDUQmsJazuc68gp0tkjqh6ZYqFWg7JVughK\nHLu5BnJLNJpIuPU5u1O8Mko1VFkRdfUz23MIAW0tGE1V0NYuhrce5wwlJWJ2nPB8PJ/oQuBRUeRl\n4ULWGv7nX/lLRC7x9poPes9P//6f45Ox8n9+49vc5RP4SiFiCBg86gxt1XLwOZOclFZQoVGpZNSP\nCIf7QmPjzoASreF0nNnv97RWMKZxOh6ZphO3t3cYY9ntLtEYqLCcIqqBMaLOKjkzHkeMEqGSaorg\n/BqcoqnVMk2JJ+88obTCMs90XZD+s5JCp3eOeJ48nKGRRfZstXzQDoZNT+gG4tLQBJYxC3AVkfcu\ny0JOFa0cCstxP8o2soLWjlwL+/HEfpooSqO9xXqLM4FtuOSyv2I6TdK5WF1+yyKsCd/1uK6TjEis\nVMQxLIsoAkMXCD6w2+0wa4JWjZnj6cjN/S1LjhynkVIhpQ9dx/AAACAASURBVMLhcM/ptOfly++z\nzAeWKP19GwL9RUCZijGigmsNasmcTm/43otv47vA0+svUyYxbp3mW0yasfcLmxPsfIfpHAaFyhVK\nwymNVRpvLd46ckyy1a5FCnh5ReMVifRDyeuMUfIsKpmqErhKMZl6hpk3EXqVUmUbv7a587xQ4wJF\nQoSlY2eE3RlHrHV0YWDTX/L46ikXm/d4fPkldptrqOfjQaWURCoZSd3SKCM2cbXKhhuC0mtNAnpo\njVJFmm+dXQdnpZJW8I3B20BwPcYFitUkZzgqx6cneLmvHI+a8SS76KEZ8nLPfvqEN/vv473hn/yj\n/zD/xC/8gzyyO4hSK9DGYo3HW4+xGmMN1toHqvNnYTOclQ0/fFz+Tgz2/7/XWWopg7syjTM5N2Ks\na08YlmXh7v6OnDPdMJBLQzsjZ0zj6LoAquE7g3UW7wMpFuYpQtMsY4KiyEumpsbhfmSeI48ePWYY\nBioV4xRnPHZrlRAC5wAarbV4JZB2UAidYNarpu92OCP9ZO8doOi6wHa74eLygpgkmv1ic0nvexnM\nVc7PsTSMc4Ja6wOt1dXPIBNUKw3TAmnMaGWpBeKSaKUCBeMaJsDSJqopmKApKjHFE2/eCCZummbG\nceT+eMtxumeJE4f9LWotlh4O9zhvQFXGScRL1on7slHRutD1GqUX8XqQ+PjlNzlMt3zwwVd5dPkV\nvDZ4tVD3e+onb1l+6w1MlVQhLwWX5HVb6/DOoY2mtCq7IGUIYUOtUmQ+I8a0VeJ7QRDmpRamUXQd\nUGDVa5xX5LPUV68oMoBcZTCXImYzUGhlMMpSq6JUwcaFruedJ1/hSx/+Aj/z1b+fn/76H2Dor9cW\nuUHjoDla8yiUdCh0k7iG8+6jlYfnua3/65xbX0ujNkkHV6pirHzPWic1LwpzWxiV4k2sfOcu8zZ6\nXt3Le3vMjnf1BWWB0Rh+/ZOPsXj+oZ//w/yjv/DHedq9i6OXhAoDShdUTYIb/Bvlz5+TQZ8Lkz9w\nXP4dGNt/y9d2K/zD1hTeO6YpUdd7/ujRBcsy0fWBGCfe3LwS0IXVeN/hQ0c/9AzbHqUr/eBXgIom\n+E7SfasmL5lWFMs48/LTl5TcyHGVgtYqwbDOStBGq2sLNK6zrEwSu+0WpRSH+yPzFEmxcDrMXF48\n4p13PgDg/fffp+8DxsD9/R3397cC9xi29GHLxeYKjWWzvcC6QKNhnCWvYh2tNfMyompmt+mxGDo9\noLKFrBjHmdPxSF4DWYzXKK/wncH3GhugqshSJkpeOB1P1NIInWPJB+4Or2mmSeAOjS44Li+3YkH3\nhn41p3WDQVkpEOay0AXN1VWHc5phG7g5fI+PX32H0F/w5Q9+hm3YstlYrC4Mx4XyzRuGfUWPlXlc\nqLXhjOH60TXGC8V4XmYZYBhKaszHmThljHZrEpeTibqJRHccTxzHA9N8oiSZGIUupFbzlcEYoW+f\nd5/GGTDIsaE1cQsqgzUBVGWOR6Z4R8wjyliuLz9g6N/jYvMhH33wjN32XZTySIbj2sXQqw2+yn9r\nLWtuXVewtqoyrbVSI1pFQ20NADbGYD5XT2lNFpq5LsxKs9eBV9kzusfcRtFbnBbNZXjMpb5gmSv3\nMTNrxfE48fve+zp/5O/6IwR2oKQzBplWM7XI0Us6PvX/OzH8CEPUFzwpyDm26zzvvPOEzaZnWSKt\nabbbLfO8SPp0ky6AWJsvQEkl+5wVMaeZYbMh5cThdMT6QOg6QbNbjzWObb8lzoWapSBTingI2ioA\nyUWqxpJCldbKuDxo3lu884ynkTQv6NaYp1l0CauM9Lu/9R1Op9MKcj0z/BM3N7fs7wUGEoJ0F2ot\n5FKISY4nJUuIraQTy1mwpMQyzdTa8F0vhWVrKKVwGk/kmljiSL8JbLaDcBypzMuEtYppmjmeRpY0\ng468ufuU03RAKUWMC10QoM1m25PPLRSg6y3OWWptzNPC27e3gq0LnstH1+yuB77z8W/w9vaOy+0T\nrvrHeBuITqry2+r4yd172AlKglSqBPG21eSvBdufcybOidPhxLIkUhaasfMO4xwNVnVjAV1RWir6\ndT0myOKs1/btOWW5PbwX33usk8mCNSatVWFjKlOI+Z7D6SV3h4+533/KlG7JLbHMjb57wtMnP8VX\nvvQMazxKS2fEuw6jHa1BjJFz6pI8RzLIzvcReMACngt9551EzufBKvyJ2hoLlagto/aczIZDkwXz\nuxHuo+XJ5imP9CXzMfK//7Vf5rdON1Dgqx/9NF/58OtQLawJUrkIavD8759jA397OtQPrzR+wVH0\nUk3ZH/bM08Qw9LTW2Gw6xnEmZ+EVxjRjnOZuf4/rOja7LZVCaZmqKsfTiHEWYx3H40QqEW0N1luM\nk2CXrg90wZ2VniuEJaCtY5wWMRkZ0bBvtgNaayE+aU3OBaudsB1SRhtFq5lpPHLz9jUAh8ORXCJm\njZbrOjkSzMvC/nhgXmYqlXkexeFZEofDHusdsSRSiiyzOPzmaSLnzDSeQDW00+QmkJnUBPA6nibm\nKVFipQuDSHOVEYPVtACGGEW8gskcTrcsccJ7T82VnAq3N3fUAvvDkeMoBb9KRRlNSo1xrNzfzhzv\nD4TQY6zl8tFjYln47ve+RUmR966+gmodiyvwwQXuq+9gnzxmf5hpFZwXqfbrV2/IOTEtE7UJw2J/\nvyfOC1ppjNbEVFbytvgjiio4bxiGnq737HYyUEp+CFKSmkIR41Vds0cBXJD7r+15G62Bc8ejksrC\nOB84nN7y8u23+dZv/hK/9f3/h2m+YZqOdGHHT3/t53n3na+gsGijcLYj+I10J5rwK2pZs0G1nOG9\n97Lo5CyvqdZ1R2NosIJO8sPuQSlNq9IJKi2DhlNt3FR5I6+r57v7meOseHfzhEe25zu/+W1OJF7e\nvgZjee/plxm6K3JqUjOqirx+JufX8NCObDyoG3/Y9cWCWxd5EPvecxoP6KgppWGtJi4L3hmJT8+Z\nq77jON2DErbCOCvm5US/GfDe8OLFS+mxl8aUFk7LiNLggsNYRamNza4XR15KHPZ7umGQVSpJ5bvr\nRAzknOC3l0UeuhgXcpKeczvv+xCqUMlrTJliXemB1nDOYowi5kS/G8itMo8naJW4ZGqXWZaZYdhS\nW10jxBOKKiKZbChtIWw73tzd4IKnSQGZXCo5VVpWeNehqqIpI0KfAtQi2+RWpNhlGkua8MGB6aTb\nYyTRurVG3w8oLe9dHKYi7c0JdsNArVas2kaRl0q/3fLJy+9yPez4yjs/wWm85b58TPqJC7qPLvjN\nvhIHj5oTuiqm00yqCRMMV1eXHI8jMSacVigrn5tRhnmZJczXKowXEpYJWtK4oqy4Vgv2X2M4c4ha\na6SUVrzfWmfQal3y2sOiWIt8WWuhWVKWWoniBO2Gu/33+eijr2DUhpSv0G3Dk+uvcL8/omzE2c1D\nunfMI7Vmzqizc4VfKYkNKKWI09W51TpuHgajsWqt2SAismqwSpHTTAgDVTf2Rd7HnCypNFQb+drT\nd/nKzvGNmz1/9a/+3/TFMSwz05LY9lvG+TW5KHKzqJZXiX75XKFxxQPyWb3hB11f6E5hfxBF4+V2\ny7YPDKGjZJhmkRT3Qy/BGxguh0tss9y8uWOeToROHoB5FgKRZCU0agKnrMBeqRijubu/Y54nqfT3\nFpRif3di3J/QFSya6RihgTVyFhyGgYvL3bqqJUoubIYtu81u3QJW0oqTA6GRKSXEG+ccPgS0k5vh\ntMcgHYmh38hsndfX2RpGSaHV+4B3AW881NWDkBtxEmNRSZEWMzqDqQanDBfDlrpk6lywzTG4C3a7\nC5zxBN9hrKW2RGl5NY4ldAWnHKY5xuOCs5bgZH2IsZDnBkUTrKbvHU47OrchTZk4F0qJTNMbXnzy\nG2xD4KsffA1TPZ/Gt9xcwd4Z7NATgqHmRG2F3eWOx0+uCZ3FaOiCAGhlF2YxonaSgq0Sa6820MjE\nFJnniWk8rhV+0WvYlS1x/mq1EONKLKpl5RQ1IWKnSKkLSlWsNxhrZHItkWk+ketMUwtKLxifmdId\nL29ekFFYd4lzj2mIW9auhUJW5yF1rX3mRk6FkkRheFY0no+hCoU1Rt6vEtJU0AGvOnQzMlE4iHoh\nankfS/FE5bgrsNjA0w9/giebR4xvb3hb9nx8+zFv335KH8Iq1ivUGqlViqy1/vajgwBeLUb7Hzou\nv9BJoa1JmXFeULWx7QeG3jOeIkuK9ENHTZU8VzrbUWNhPs4C9VyruxqNNU7OtXOiRkVnAg7LeDgS\nl0WCW3IBhcBaQ4/VnhILH777LsFYWqrMUwJkVRqGnqurS3JKxJg4HU9YY2UCypqSVjDmOi/Ulskl\nrZVdkWD7zqIapClRsyaE7SqUMZSsxdIdC6pJloRW9mG1t9VQU2M6TgSrSVOkJen929bQyuCs5XTc\nczruuX37FpUFYDqfMrVqpjnJ1jpliZ+LC0YplnFC1xXFvm5nu14mBVU9RglmfbPzGCc7GGcCx9sT\naV443t/SBcN0umN//5pH28eEcsU4Hnh7fMN4fyAdj/Qbt5KzzNpiXDid9mjdGPrAsBmoWSTiRluM\nUjhrV5mzULe10eJILJklRiS5WwjfVitUKRhgGAZC6Mnpswh3WpF2YMsoXdC6UupMLhOFBWMbxooZ\nzBihHmtj8Z2mMPHy9nvcH+/AOJQaZHJaZnEtGul0KMBog0HwcxSFaqAREpTV5wmhrf/t0M1iVcDr\nAYNZDzYa6zoSmWPcE5scJUfTMWI5oPnGzYGPY+OdL38dF3a8XWbulwPH6ZZxvH+Qc2s9P5iyahXO\nh9EGrWRHo5WWHe8Pub7QSWHTC2XzcDgyzZG7+zu0knPX6TiRYn4ovhln5EaYz4I4nfUCYjHmof3T\nWuM0TsQUAcUyC+257zu8l50IaD766COuri6Ylolu43CdJiYZRMMgNYW7u3uUUjhnCcEyzkcO+/u1\nSCRn25g+c3qWXEkpE1NmnifpEpjGskxSG9BK+vqnzDwnjLHMS3rYyhlj1jTqhPeOwcmOIXi/ht4M\nrNQYiVKzitwKzYIbLIfpjuO8Z1pGrFWgCs5ZYoqUnAQKEhypZZQDXCOWhW5wDNtuvRcntpcbtDds\nLra44DnMe2qLHPd75lG8F8ZaqoHvvPw+bw5Hnr73dbrwGO86YjyiKSslSqTMpUBODapB4VDKYo1j\ns9lw/egxj548WUnFUsHXKIz2WC1KyZLbOrlV+kFavsY6umHL5eVjri6eYHXPsnzWpsxZqNC1VNSK\nQxcdRMKuABJnLX3XMwyDYPEosouoUj8quaDbWvhdRlKa5AgB+BDoNxuc94iv4Lwr0GhtsU66KecD\n/Ll4DTy0BJ2xWGVoWcKT05LIc6SkFdzqNNl7ou94EyvffH1P2j7i4svPwF0yxkZRcJz2pLTI62gO\njVpPTlomKW0kvUzUIA9W+R90/ciawrNnzyzwHwE/AXjgF4G/DvzHyPH2V58/f/4n15/9l4E/ASTg\nF58/f/7f/ajfDbBMUmh03otyrGSa0hijcNYQ50htlW4TaAaaqVgPMS4YF0hrYapVCYaFhjGSRbnM\n0t149eqeflgYNlLE7LqetuYWvvveU169/gRl+dz0KOfTdmosc6IUkRT7VVJdWsE6mGc5n6YoN9dq\n82BXTVEGoNEG7+y6lUtYK2f4R9dbTvsouRZeKtWb7Q6tNEua17ar4/LyCnO44T4eCKHDhcBxPXIt\neUF5wZtrq7BW43tHaom8IC+uVGpOHO5uGZ5u0NpwnA4op8GKLdn3BhcMaa3a39zeE7otTz94DxeS\nhO6WTCNDKeSlMVwO8to3HXfzgfzJx/zUT/1+nn397+XT19/lmF+z2XTc7+9k96MMXdjQWqI1SdCK\nKaNU48k777Lb7Xjz+rXI1bXGd5YUE8YE4lKZR2kDq1XludUGOzgwGmssXb8lLYUUG97KQlNykbqD\nqg8Yu7OGIcWIdVa0DlVCUrSWI1zMiTkllpTYhA3Be+KcSHGmlBltCjHJ8aULHc4Klr+sEXDKaNmF\nabXuciCXgtYWKXRKPEGtRVbu1SdSUsYYSf7SGPqVp2AHYTs0NAXHm2VGffKC3eUj/OYJ8/EN1cxg\nG6ZIsblhxFG56icAOXat5q7aClJ8+sHXj9sp/AvAm+fPn/8x4B8D/hzw7wB/5vnz5/8AoJ89e/bP\nPHv27CnwrwB/eP25f/PZs2fux/xu8spTGNbZ1jjLmUSrmyRDlVZxnePu/galG7uLjQS+GkdMwlqY\n5lUFWGQ1tk4zz4vAPFZyzm63W2dsuVE3NzeM05Gr6wu0BesE5DrPokwUh5liPEVqYXXD1RWm0q9m\nrMbhfvW9r6uiRlNikeg4JVBVYxvTdKIUOZZ89NGHAqhdCrvtBaU1nPfELAUqkH9Lgn4+qxynJJF3\nklkh5OozNbofOoZNIPTmgQERl8rxMBJjxhqxdr9885JYJk7zAeeVTCQ5cTye1ruiuLl5w+MnVxjj\n0dZz+eiS03TAWoP3XlqrIYA3DI+2JFvJyvDRhz+Dxsnjax05Q7cd8F0nAyI3KIqSK/MSiSUxLSNz\nmhmnEzlXFJrNsMEoi6qGmiGn+pDMrLSiUMkt0w0dvu9E+bh6K/QakqCVJoTAxXbH9dU1jx494mp3\nSd91pByJy/KQm5FTIi2ZlDKH48LpFKX9aBylJOblwDTfUetCq/Lzkj5maEqcm0VkTAJc0Wqti8g9\ny1nuaa08/FmSmxrjNJLTsu4WhW0ZfPfg9lQs1DYypz1TOpDawuv7V7x484JYM6kmYp4xBjbbDX0/\nEPyAtQ5r7frl1jqCXQ13MmH9sOvHdR/+IvBfrX82QAb+nufPn/9v69/998A/guwa/vLz588zsH/2\n7Nk3gZ8D/q8f9cs7L4KZ2hrKaGpMWKtppZFixoaVTacb2imGi47gPbdv7iipsh127A97ipIk6dnM\ndJ3DWUcpE9M0Y6zmeDxyebVbb0ShVkleuru/w3lNygXfS43BOTE1dd2wagpAYXDWcTjs8Va6Ct4r\nUpHwFxDCshSWpDc+ztPKVijSJydzGo+0nBhtYBgGkVBrjW5mVd3JLF6VZlxGdCvEIjsKamOJi0Sz\nKY1zGqjM80KvPMfDiZQjtTSsMRwP83r0CWyGC6wJHPcn4WLqwrJEUrJ4YxnH6aHF1wUPOnF784Zh\nu+FwOBI6qWkordeJSbG7EqpV1gU7KH7r0+/y5Q9+kuvLd8n5hvtTZre7xnoJ/s054p2nlcr9aY/r\nAv0QqEQOh1usFQx5qzCPkc4PxCRmr7r6CYwzWK+xTgxUKRdqbUxz5HB/lN3BuhuY5wWFJrhO4uet\nR2tDb/VqqTZ4H8gxUUplmWdaVcwUNk4T/IacKzEe2Z/esCwHrIlkrWlNEXxPXs1etZWHXSBKXtt5\nYii1UHMRY9S60Flr8S6IeG6esaoJSLgpQjcwDJuHjklZTvJM1EpTnlwiymROx5mxRpZ4pJQRbdfn\nwjqUV0ynslYrVsPhuhsShWV5WHz+pieF58+fjwDPnj3brZPDnwX+7c/9yAG4AHbA/ef+/ghc/qjf\nDTCPcq6Zxol+14sFWCkwCtWaCI2cwnpH043tbmCeJvq+w9pAq5FapaLqfaDrMvOUWZZIvzESP7eC\nMd68eYvWDWcVcy4YK7LYKc4cx4m+21HTJAN6HLm7uyP4ni545nnmYrchJTBUgneEYDFNUqgA0hKh\nCuFGIUk9NBFmpQglJ5R2LPNCc4phuERq4w1jPcuyUHMRfUNpTPNMy5lmQVtpZ+WYMWgePbpkUSeU\nEt1/K43ptAipqDS60LOMUbz/pRFchzMBjWO73ZDbQquKOC9Y61mm+uDhCB60tdzfvuXRo0e8mW+4\nvbvj3av3qUpxcX3J5cUlhcoSZz55+SnvPHmKSo1PXgy88+R9jDug3jjy/Q378ZUIsKzHKIjLgvOG\n0DmctyhbRVRV5MhotIFm6PyGedwTpxmtWY+V0CgYp9FWsZxGapU2hdIF5xu5yDM1nkY0hkVHnJlw\n1guYxjuMNXRdRy2Ni4sLSqkc9we0DXThGopHNceyHBnnPVWNND3Js1YtalUrLstMqXktVErtBK3I\n5Rw1EFfhEMSYKStMVSuz7v401lvSMqHxdN1A120IXSdZpQDnAmGT5PRpvKeYgjWOqQkjRBkrRjsF\nBeE5iJTasoos166DW4OV4G+Lp/Ds2bMvAf8t8OeeP3/+Xzx79uzf+ty3d8AdsIeVEf7b//5HXv/H\nn/8VAD79b3540eP3yvXNP3//43/o98D1nf/k9ON/6PfA9fF/Fr/ol/B35Pqlf/c3fkd+73v/3OaH\nfu/HFRqfAv8j8CefP3/+v65//cvPnj37Y8+fP/9LwD8O/C/AXwF+8dmzZx7ogZ8BfvXHvbB/+s/+\nfTz/T/c8+aekMd33PcuyYL2n1MR2tyFn8SE4L5XoEDru7+/Z7jZM05GYJs6EmRgLuopW3flVuqwd\nm01P05lhCBzuJ/b7cY1N2xI6RyoR5wLHm4nbu3uurnuWRSaqUipGO/wqaKIpjHEPW7JxmnnxFye+\n9i89gVKZTqMUNbVinCeGTUChSTFzffWO/H/GhZu3d9Ra2O0uqLlw2O8xWuHXFOtxf6LkQr+x9IMn\n5cyyFLp+y+7ygqLFm59rouscy+EAtaKaJmZFro15WXjnyVPee/IHuLi64vb4qyzLLfvDCaphv5/4\n0pc+BBrzcuSv/Qcv+H1/4gl9P7DZDrTWGMeJVy9fsRmuefbs59jtdvz6N35dukJWcb/fs0wLFs+H\n73/Ek8uPeP/pM968fsmv/Nr/wO3p2xAcqigGv6VGqe5DY8kLTVcuLq7Z3x/pQk/oOqZJsjRc2KCN\n5f72DTEdRDPhNvTDE2ynOB1vWMaJkgoXmy3H04mYM5/85wtf/he7lTYEoLDaSe6kaeyuBiie0yGR\nIzx5cr2algopZ/JaSExLJC4TFxcbconkVClIVIAyWihYNOEXNEXnw0M+6rIs3N3diU7FuQepsbXS\ndfEh0HUdziuWNJGixaotu90V9/vXlHbi1/7DT/hDf/orWDVg6dHNsT8eKCSOp1tKWWBlNohXx6yd\nuYJuwq5QyuKsw/ueWuB4PHF3vOdvZ6fwrwFXwL/+7NmzfwORi/2rwL+/FhJ/Dfivnz9/3p49e/bv\nAX95/df+zPPnz3/sVD2vst5h6FYlo8H7HRhNSmKp3mxkRhv6rQyKsGH2C9TG4f6IMRWUYlkStSiG\nrsP6jqYyORaolbhUMIVoMiL/bXRBMU0T43Rge7kBKssyryYXcM7LebFC19lVeCIfcoxZzm5I0i8g\nNRBj2Gy2cqZcxTFGCXaslYWcIq0pckrQCiWfv0R9Ns+R6qqg4q1G1fX7Vc4i2kpLK6XEKe7X6naj\n8wHjOsp8ztyMKGW4vBjoh0uevvtlQrdlya/YH9+sUXaRmBO5ZpzXLCcpmPo+oJ2mG3pOxxGUYXtx\nRecHPn3xCVp/gHOWzaZnijNxnsQ2nkfevDUEf8HlfGR3uWXoL9hPDnTBu8Bu23H39kBtmlzWzhEF\nqyxuzcoIwaNMY5xOpHrC647t1nE8aWqNzLEybMXFmFN9MLhNJhHCQFMymW82W0rJDxOMcVbMSEYk\nx7f391i1wTq5n00lUpqlBoS0p8d5hbiogWEYOE0LeVnQRpOrwFZyyaSY8No+iIM+T1EGyCVTS8Gs\ngJnaIMXCbisJZDk3Um30mwFa4+bmLf2wYgWURiupv9Wi2Wx65gx60dSmHhyiZ9zag508y9FR6YY1\n9uF7xhi88w/dpr/pSeH58+d/CvhTP+Bbf/wH/OxfAP7Cj/p9f+N1Po97HzDGkksRbT4NawfUOT23\niDx0mmasmaDCKvOh7zph7BVQTTh5GMGXnwMxQhhIWRyOCrdq58V774NhWRa0Vnz40ft87/sfM00L\nm02/Brxk4QlUKEUmiFqlOKW1VNKBtfItvofd7pJpmbGmgyYMylYlbMZoRxc8qQ+keKKVQiviu5im\nSAgCZnFOsGZoqROIfrqCbpyOB5Y6Y70jp4zVnquLK5Y20nIh03Cuo+sHrDFrXLswCru+Y4kz0+0d\nlUbME7m1B+DNkmfa6idR2nJxtQFjONweUcyEYNGmEdNMShOtZdFE6MxhfMtpuef++Ian77zPT/3U\nz3KaX3OMn3L1eEvNmUJcdSMb2qjJ8yhvS0lVvCJiqVQiRhlSErbBbrNhnA+U2igl0umOFAut6nUC\nL/TDQBikJemcw3vBqJVSxbmoLVVVplEm534z4EwgLjMoMTmFrqKMxSlFKFbusxNbsveWJS5M8yQF\nzdZWH0tFW+kWnA1QMZ7XxPbAbazVrLqNwMXFFdvtJXGZaCXijMZay2F/T8mZ1RZESgltgzxrpYgP\nJiapXa0dC2vtg/7hXJStayvZKUMuBZUkq7VU8bao+ruV0biuskZbsSxnSUtqSqrwXeepNbIsiVKU\nrKRFUdOCohMprNJCNS5CDsYYqcI3KfAoWEVOMumYVR+vlGHYdMQkIqngG8e4X40q4qIspT6IYHSz\nn3NWthUBhwBBAOqaxKMULnhO04hCCX9ydfCdTiesEcGVuEEbrVZylnaYUgrvvTxQetXSa0WTVBUx\nYrVCKgvWCVI9JcGRWdejes0yjTg6rBWPQ8ojN7ffQe0t++PHuD4LzAYIQXM8HthddKy3gpgjS0w0\n5eg6wcdNy0IskQ/efR/nFC9fv0VpIT2N04G+8yidqTSO4w334RXvvPOI99/7Esf9z/L8N29p+Szi\nkYmtH3rJvmxKoK21oJW89+PpxJJmQusAy+7ymk3vef3mBcdxYpkiQ99ETpwLeuVappLZDtLROgvA\nQt+RVlCLMnpN+RZNAGuxcJ4nNptAjAvWK4K3aO0JXWC/P4iisinZZejzPTcPVukzx+Hc+Thbls/S\nYmMUruspRUxVm80llxfXq6pQWpvC7zgQ04hzhnWM35MEagAAIABJREFUk1PBa4G91Aa1Zoxd8zHK\nKhBTZ/o3tM9pE6Q9qteuUSKl8mD9/lHXFzopbDc7QHq3DRl8x+OIC44lJkRGUZnnjNbzA+TCdYH7\nwx7n3YrIOnvoLW3dbhltaE4TJ5HInmWdKS9sNp7Hjx9xHE/c30+898Ejum7gzYvXxJgIwQv7H421\nKzwjn/vOMkuXUlbYp7yXaZxxXWXY9MS0kNJMiotoLtZJhtIE/hGlz+2NlVVmVTRaq4k5o1eFZllV\ncg1h6hkjcurQO7pgyAVms4pmEBNWWkTbEJeMsZqqZpZ8Q5ozVR148+bIPGec9RgtXMShOPo1Afyc\nshV8h9WG0/FAWmYBlurKdjfw6atEWiL9xlObKDidbtiwZVzuOc43vHr7Ce9df8BH7/00d28+5ni6\nwwbhWGqtmcZJ8PQGEWwZJ1vxJTGeRnyw4mdpje1wjQGsHtCqkFPlsD9KelYp1JrXXcFCzCuObZ4f\nQCoyiCrWSQ5DKhljNLlE4pKY5xFjBc2u1GcRbf0wkHJmjhMueHQzq+lJZMsyicuCBDwMzrMW4DPr\ndOXy8pqcYDNcEULPPM/UmgneomqRroxzGN0Izok5BuTfRDFNJ5S2KGfobaBUOXZqLano52PEAyuh\nwZPHj9nvj6s3o2L0Km9unwGOftD1xYbBrBPW8TgSOo9eb6B86IbTceaddx+h1LRuv8TA8sGXv8Rv\nfGtPbjLQUq1kGrpVmZWdQFNraaR54njcQ4uyjTaaqyvBqM/TQqtg7cB+P9H3gRiFflTWoNIztqqt\nuYhCZRKTTYwyAAHGKeNaxXcntIVUZmqLQlBaz3QheDk/NoGzKq2ZJmmDBu/IRfrHylrUmkZ1dta1\nNeGntCLtUCNW467rMNZwGk94pygqkuuERpOzhlpY0kytsCyFkiqd62hVi7RWCS7OKFmaggv0Fzue\nXD/h5cuXnE57luVEcJ5Xrz8llwUfLDGJpb3vHa0JfwJdKS1SmPnk5ffIk+bL736Jn/2JP8j3XnyL\nl/ffx2CpqbKcDlIINuA72ZWM4yR8iqYYwiDu0Qz7eymiLkskxSTakkWtE720ZGtTAkFZlXqXV1cc\njwdAFIvdGhgzzVI7KSWhGtSaVl9EwwdHjhlFQWtFj6IbOqa7kTxP9K6nUQVNv7IdRBUpxqOzVVnk\n6nltCTa556lwsXuMNT0lN97evMU5jb/eiWGtTGw2Dms1OSu8X0NtQkerct9zSgTTMedIadLOTkna\n8n3f03W9JHRpcec+ffcp8yQL07kVaoNDW80c/xZlzr/T1/4gCLB5StRaMVZ4dtZ6iaYvhdNp5PJq\nyzSP5JTJZeFwuMd6R22JZRUPabtCNJtIjq015FYJwbPMI33vBLhpDdZpbm/eiow5Nk6HUQRLXh6G\nhwFYKqU2nK0PJNxaC9ZpclEr+EPei+wI4HQ60Wqi1ijSZ3MuPIm12TlFinIMoeWHWd56h1pn8Vwq\n1kLoOqmCl0TOkVoSxss2sWRhJxolpOGzarFVwYNZt6owgZIKuWrSonFmwBovgp1lYeg35BhZ5nV1\n7Af6rmc8jeSUmKYT2qzWZO159fIlrpPJqiTB6o9jxDqH84GiHPvjLV5lvvXmGzzZvctmeIfOv8Xw\nll2vud/f0GolOI9yjYp8eC4ELsLAdntJ3/Ucx1uB49a4EqwhxZkueNElBAm0pVa6IYBRD6HF/WaL\ncU6OBNbJjksrmgJrFDFlphjFF8HqylTiEm0tE3rPskSUUWy3O47jgaqQ7fgqV9ZaY42AbwS6AtDk\nNSlEC1GbSJybTHatVm7vbihFPrMpTixxJpVEpaKtoes7QjjLtQXkstlsyePMEhPzsgg7oyq571Yx\nDLIYCk9T0Q9bjqeRvtvI5NtEoSsnuLwKmX7w9YUaos7hl05bBu/pgn9Aa1tV0apQifhBs7kMuA76\njaHkieA0fd+vq7CsdKo18pJYpsjxMNGqYrMbqKqtiU4XVOB4OLIcT9Qp0iKUJWFUFSGREWHN7mJY\nt3Maa4WSW4Gm5Mt6SScSvqMkNJkGbarUpZHmVVNvnOjWG4L2UhrjDWhoqoKpKPM5LXw15LkS54q2\njm6zwXUB7SR0VnYxkLNBtTVFOEdUy+QURQKuAyhoTYpeqZzQZsY6izE9SnuU1nS9EJ1KbrS8OlZT\nJMWFZTpitGwzd1dXYBzGeGpV9KFHo0hLwiiHUZ6cV6dfa9QlYo1ijLd85/U3uS+J7ZN3ubh4jKpr\nmK8PbLY7OrtBV0taMjlXbvcH+u0Tpmh58/JIiYVcTnJ8VBGrQNeGImNDxfcNNzR8vwqf1hKP1h7v\nBqzpqUWvkuXVOdkq3kleptYiAxbnI8S8POw2UqrUrBnCjt5uxNUr1k1KFcKRNk5QaCVTc1yPKxof\nAtY5jLUC29WGcTqypAPTfIvRGWvEFzHFRCyN4ziDsRLGu4ainKbMnBI2BEqz1BywbWDrL9DFSOdG\nGzQCVkm5YmxH6K+YF8D0oIM4Pa1BOSNxg+aHuxC+0Enh+voRAF1whC6sORAavUbHKyVFndPxRM1F\n2kxZXJCVhvWO60fXDJuNUHVFk7xy+tZ2jDNYJ3mCXRfIReAmwsYH54WDEIKj7weGocc5KXx2XVhJ\nPmuFV8sKQWvic1BqrT3IsyLSd2ldWmNwXop90n5LkoNQpNijjcF5cV9q/VlLyRj58zJPNCrW2TXI\nRlY7KXZK7Jxcn0WCnSvf1n4mH5ei5oLWCOQWaVk671aCVFlZiJ/dl1KK0JiOR/q+lzar1uIW7Tyy\nGlpyLgTXY43H2oFlKRgtzseuszx6vOXm7lPe3L5AGcXu8hGlWKwb1m7SiaoK3eDFcEXi/u4NN28/\n4dXL7zPPJ2ot0i2JC6kWdHAob7m6vhaUXE4sS2SaFu73eyleAvu7e46HIzQ4HU/ERXgZJcuqGXxg\nGHr6LhBCoO8Dj588xofV2UhdgTNSO+p7MSiJESrQanuoGZzpRkLz8gTvH44O1lr6PpBS5HQ6cjod\n0EY+S0WjpkRcElSIMWG1EJiXadXJVFmsjqejOF1bo+s6ur5j2HQPHFHRV4jxyqzPSq2rknE9zojv\nYk3R/hGQlS/0+HDW+3drkvDF9pKuTzz98H1ev/yYw+GAdiLHXSbYbi8Z+guWZSbmSGc1777/lP1B\nqunzOGON+BqstczzTM6RrhNE1rScgIoLFrUWDnPNoDLeb8TRaCpayzbMGEPX9VKYQaOVtIMy4IOT\nrfvai7ZWmP5qnRic8zjryXFNOK5N2qbKQJPsSWsUpUihqpT1OKCdRMVHMXSVNWHFWoMxVjj+aDlO\nVA2qsdl8FmwiE+JKNVaKVKT7kXOh6ztA5LJat9Uf0FDaCk0ZWMZIdzHQ9wN3d/d88OgDlmkNQbHQ\nYubm5kgIHRLN2dAqENxALokuiGek1Eg3OD7+/gsoFaW/TN/vePreT/L67fe5P75E28rmcoP3np5V\nuGYNXReI04nm5ZiSi8IqRbcZ8MMW7wPDxYaqEqfTiGhPBPwagnA/9/d3zPPM5eWl4PvnuJrWDEbb\nz8hDqq4EZsPV5TXH03EtUqb1mADDcIXzYqeex4azUrM67IWWHZeIWfUJZ2mx8CWlbW2txbpMjBPz\nLKI8tcqgtdaY1WzXcqasYbh5bWk+HDOmE605oKxZGAVtBUMf+kF2JsZjtYe6Bv3SHsjk5+AlpdZC\n4+/WSWF/kqyBRmNeInWpNA0pJh6/8w6FgrWW0/EoO4Q6cn39GDoDax/3OJ6Y5xljDSEEcllE6bee\nxVJa2GyGhwHmvcMZR5qSuBBTxQdPygvOSaqwDDwZhJvNerZs7cFem3PFWmE6nPvD1gpJpxWpRRi/\n/uzq56+lrrmeFaU0fWelYLlq+mXFl9/jgyUXiVubl/mBVnw2tZyRX8ZIxbnve6ZpotS8nmFXF97D\nhCWFTq0Nl1c7pmlimqa1DiLbyXldmVppLIvE5g2bDcH3HN8eUE12bTJRdtKRqeJc9L4TEtUKc0E1\nxnEEFNYVajvy+u0nvP/eT9INlwxxZH96SykzcSlYq6m5CFxniQz9jg8+eB9q4/WrVygHw3ZDvxkI\nw0BripIXQhjouwuWecGsbIbzWbkUoWXd3d7x/vvvY60lpbwa1jY0CrnE9YiFoPD3B7wPkjlZJHVs\nmk/My4z3js4H4rTQaiP4wFEdSUuUz3GdhB+ArEhNYZkXSkmE4IiLuHdz9rS1te29pw9BnvFaWE4n\nrPdsB5ncztxQ8VoZcomUmFBaaFqX15dcXl5DEyZnSZkSM5j2gIgDtcJkzxh8hQA1fvD1hR4f3v/g\nXQCWNJJrIqaFaZx4/uvf4s2bG7wLBBcYwvCAsDrcH6E0tuuW9u72Lfv9HafjCWf9WlFeZ2mjWaJA\nTBor7379cP3Qg1Z0fYe1hpTiOlhmpnFat+syy4veIEE71y4UVEVastiB4cEqe16Baq0cDkdKyQ+z\ncl0Tj2JMxBgfMGPLsjz0jmutK79BJo1lmYlxeRDgeB9WgYpMTiGI2y7GKIlED264deu57lxqqZKY\nVIV0VApY57FWqEdnKnVwAYVifzgSQk+KiZzE6ZmTqPK2260o47yTQdBkIJzfk3RUZOW8uNxyed3h\nOjjO9/iN5/L6iqtHjwHDeFooqZGSJClb4wSfF6UGsrvcCedgEfrVzZu37O/uqBn67oInj9/Duh7n\nPK2JRR2AVhmGgDWG25tbaEpQekXjfc8wbMRpqtraTSoc7o9Mk2DpxSovjMNPPvmE02kUR2X+rMug\nV36Gsxa32pRLEcKXc46L3QUhBFKJlJZQSnDv8zQ+SLBTTCitxYKtJZBXoC+rN0GJWKu2vNaeIo0E\nVC6urri4vMK7DmE9CaoOiuDtaMzzxDzPWCvUsGHYst1sxA37Q64vdKdwmkWCOi4zRim6zmObYVpE\nwKKV4tHlJc448KIbiLlwPBwwsyLViO8NeYnMY6a3/br1Lyg0y//b3rmE2LJedfz3veqxd3efR25u\nxGhQBMuRCUZ8ERJU4mtinDswqEEREcEIJqijqCBx4HMQDQYRxAhRUEwcODDJIEjMwKBUInEiF03u\nueec7t67qr6ng/XV7tP33hPjBdMd3Asa+r2rdlWtb31r/R/e15U9klMRB6iSCV4QaX7xbPqOlBN9\n1xFjYVn8YSy5ct6dc2QvLMgUq8Nv0eJOvObVUohBHiDrLCUrlrDQGOlQa7Q0p4Ls82MVGQlexpPW\ncuB5NE0rcFY/V0RlphQRK1nHy9bq+ncrInNVKxaAkHShU7XVEz+AmNKV9JhqKEaUf5Z5ke4psk2S\n8rpwdnaXtnWkGAjeo43BWMWy7OtrClpOfDs6CoIZMMYdjq1r20rXLuzmh2xCX+nPDXfP7h2YrFrD\n9qTn7M4znF88JJXI490jnHGcnp4y+4lZlHRxjWW6mNG65dlnn+XenSy4kDgdYOqrB0Tft8yz5/kv\nPOC1r/0a7t69x8OHD0F57t7bkEsg+FQnXhBSIfqCEvFOUWfGCBow5oOITgzhcN27Kt2f1pFyKTRt\nJ8pLSpNzVXVW8pFywmqN1o5lCdVsSIBGpYB1jnmulVvJuCpiC3U7Ygxt1+KaripaZUpare5yRTsa\nbN1u5kRdVAT30rWOsuoIvkzcaFJoNvLy9+6fkXwQp6hcMDESgkCeQ4iU+mbnHLGupe8b9vMOP4nu\nQd+0OOWwStSgMzAHSQhaKXY7sQkTHwh7TeximmcWD6enJ7V8l4fk4vyCruulIWgtXd8fkI6yT3RV\nfEVWZe8DuqgqeFRERdqYg1WYMVrsw4l1dh0PTcyDIlCVgxO+fUPbuIpSE6izcxq0RhsDWZJWCKH2\nMBzTNFUwi0idx5QEHZpl3yxy4ppUlFDPV+HRa2AW0YRoGplO5BRoXVuTGJWHXw7aFEqJSbM0L2Xl\n3Wy2lKIIPuKXQFhmllgIUZNVRqOY55ltf0opE9pUKTw8RTWYthAWz+ITSWXp4itxl8olkUOkFEPX\nW5HEWyL37t9nPz1mP50DHGDNxliUksT64MEDXve6r0fQiFxVNI2R72lNCRGlzGHfnrOMnZd5Icdq\naxcTpkr8KRCuSuU7+BjJtZrYXe7EZVzB6jm5HtdBawG5NhlIpbCEwH6e2e2q5H5OInZT1aNSkSrG\nOitNRW3YzVOlAqSrD1wdT6+CL1TUpfzPL8KHutmkECbJttsT0UnYXexFkTbKNKDRlsePz7l37w67\naS++iZd7ntF3aBrH/eZ+FSYN9N1GAEFJvIfmeZEOrxaG4rbfEPyMUbKHXWLFo6dCTDDphWzAZI3N\nBhMLZVnITpPrSNI0hi4Ld6KxhhSi+BQCJSiygaIEaKKLJhdxvY51BKZyJocCVsmkJFNvWpkfO2fl\nRiwBsqKzBo0lxYyPCaM02mq8teSaDEoR6zLQtXQ1lGLqjbHqWYrisLMOq0S3IufMq151n4cPH5By\nolTFopg9cc7gLI92j1AIsWfJHlfzhms7gZxnEFhAEfEPpclVi1EpzbSPoBIhXDAt++rGDfMcyUHR\ntS3KOAqia6iYKSWxaXta23Me9yxzJC6yHTw56cg5sttNnG42UDLLcskc95xfQtu16FnK4rsnz4ir\n1H5P8J7t5g6qGB6+IN3/fnvGgxf+A2ML280dGrdhniJ52YMGVXTV4khoB9N+wU+Jpu0pudBspWpq\nWvGCsBh2F5eEJO958JE9e6ZJuCSKTAoZWwV3U07E7ClayahQUU2PAjEspCDgOactKlcYtbL4KBVb\nKcKjICsMqipTabKqo3MfBP5fpM/hnKuVSqnN9Vsq3Pr5554HZHwUfKDrOmlUFVmJY4zsdyJU0bQN\nxmicNWIN17acnp3RtT0JxewDGVh8BUKtdtxFOvcpCUEqLBmNPvjprYIoyxIJPjJNAhCJsUqFVzty\nIVa19FX6vVbbhwadtVb8B2sZv249UpJRaS5ZILJG9vgoqkOwqXtYXWm14lkoHgcGpw2tdfSNNKeo\ncFXn2iqksc5Cq+8EtX8ipUHtLwiKyRhLIRP8UlcghbH6MP4F6VrnEut7FqTUtwqU9DGcs4eKRl5W\nHfgbCoH2Xl5esNvt2e93gsar05WmbcTHI8zM816crkKmbTa0neAAdpcz0xQwquH09IymbXCuIfjA\nNO9pu5aT01P6vieXxDTtCMHz+S/8F4/PH9E4Gcc27UpGC0KT327oupaLi0eEOKMUnJzcJUdDKRrr\nLP1GRFjkzVj1GxXWiOJzLnF9d/FhIZOZZpkoNI0AjtbtpNJU2/mAXxZCjKQ6ItRGiZERCeuUqIVV\nDw5jlIxCBdKFqDF7ULmO10UKPgTPfhIhWaWutg0reS+EhF+kyl7/R0wLqQTBYZhbOn3oKhzQFCnL\nN2enBJ+Z6nyaUjjZdiLiaQ13zs6Y9pPc3FmRsqxam5VD7hwpF1Sdx8pDKc0xKallNS1Zsm6qltyl\nRCEelSz7Rq6IJKmIom9RScaI3QatDPMsF27t8Ov6+03bcXl5KTcUgFoRcLni4sVQJqvaGqoNyvIi\nYo010lg1iK240Raf9iLwiUI7J6VgieItoDVZC6Q2V59MpcR4RKu6LTOanEMdw2Uud4+vJh8VsKNU\nkZVNS2IQineQPag2hybbIbEpsbkjy/umEdl4TUapgl8Wcobt5kTQkzEKPDdOXFy+gNbPoLVj027o\nuobd9Ij9vGfa7WhaQ9v0dcTXM82PK97ilN1uJy5IVRQ3RM/F+WNKL+dxeXkhilxtUxGCjv1+RmkR\nCL64yNy/dx+jmqrZOHN6dsocWkJYhJFYl8wVQ+JaK7oLFIxpcNaQk4WihIq+CB08l0jTye82rcbH\nUsl1ut5n0ttZjWKsU3SbBr3IZCCEhRhlvJaLJ2VFTJqmGshkBOOhlSEojdUWZRRxCYSUBcBUNK4T\n4xchdErDMqWq5FUrw5eLG00KfSMvryuG1S+S1cUpCXTFCaQsja47d+7hF4GmLmkhl0wqRWy360z7\n1c8+y+OHL7AsC20rMs3rapxzoWQBHBltyfLUAlKayxZBUSIY5wSiXKTU91H26yfbLdHHuhKDbZ7I\nuEWYms45weXnAkWRUgFViR4VCqtq2S3gEtmfr9bhq0CqKUqamUqLJ4I2zHEWd+HqoWiMkW1HrQZX\ngVmxJFOsPorG6MrfEBfknBLn54+qtqCU5yB+BsUoSQQUwjJTUiYnoWTrKnbqnOAp0ELDXSsGTJUa\n0wVnjfQ5TKFtN7RNR0p7lIKud5Aj5+ePaFzP/Vc9Q9ttRD/ROGKAab7EGC0SdbQ03amIrHovGgrT\nRNEFH2eslWQqorvC9mwai21PCCEw+0kgy5ueabng0aMXMLphs9nKxImJ7emGvu/Y7y5Zai8oZ9G5\nEKEf6WFoFNrIKt64nk13BrGwnxdCCLS9xdhVaFfMj4NPlFgoKoG2NM5iW40qhoJAlVMUTs3asIS1\n1yPy9t4EYiwoAyEmjJLk3zhH23RipZgyKSSM6dC6QVu5pqgkFUb0MpJ/pRqN/9fh2nV0VsUptHRE\nNpsNcUlSloYg++yUOH/8GGssYfEUCtNujzKGZiNOSGhF4+Qh8X4hZ5H39t7XBqM07HIdTa7gpKZp\nSClK91YbdGPQxogTkLakItuJWLv5MReUMdVuXM7FhyjszEVJw7PiGuYoI0hX5OJKSEaRKkGw8gIh\nFvKUs2KDrkCWBSX71HW0SinkLIxR+ZdXAhorAm81EV2rEKGAewoGyHU8mg+VlHTAETSpEgLW5fk5\nJWWcMTStEK/WUZpzjuBrmVvBXULckRtcFUkKs67I1BgPvhrb7QYqy2/aJy4uH2Gt5Y7eyoPWdHRt\nIziNaaHvO9k6ti2LkumAMYbTk1OmsMdnkeE3RmFVNbXR4jyttRXUY5jZbDYsfjpoHex2l7XcLkwX\nO07PtrSdJIZ5v5PFquosKKUx1tG05mrrpRXezzQ2oLOpAK+1MpTGeIwL3aan7RoZYQfh12gn93uK\nCYo5oHetbQ5jc4DGdaS81IlObT6rLJXjfi9/3ygSqeqPZHEdM6K4pA3iRq2kGgzBg6H6orx83GhS\n2NwVWUfxdPQVmAMYYbtd7iZSK2+2AEn2wgpUslpd7ma6Xsg97aYj5kR396x2nR1+8VhrrpKANoCs\nisYaUpQL13aO4IUxuCyJpm1xTQu60LSWxRe0FlTgfj9j1GokmiBIxo0xCdFmWarGg8E4TUgQcpLE\nVx+oAoeeBzmjNHWkJTe7quo8wpUQnmbKqV54SPXRFmh3QaeIrVj2lAraZHKWXklKSgRPS8aHhC1X\nEvJSUl4J34KwU1OdKqiiCN6jjHS5n33Nszz//PMHMFWMkZDEhNfUbZEARQyUjFbQWk3WiULEL4K3\n2G4brFYs80wMCznPTPM5Zicyem3nsMZx9849LvQFFHGAWsK5NO6yRSXLyfaEpDxZC1bj8PpAv+kO\nU56mazDasNlueO655wgh0jadKE75HW3TYOwJ+8sFlEyKXOPIKdO19X1RGpStfBaFdQrnNCXBMk84\nIwjVgojw5OwqdiPSbiLbzZZgpGeC4sDZCSGizBP3kJaE0FaJd2Na2ZY2PdvNXRq3Ba3QOvH4wQMu\n9o8Rs50kC5kpKKuxVvokBbHPk34SlZ4u/JanxY02GlfxF9M0KCOuvKXKIK+NuhAiztqD/LdW0m1N\nS0BlkZ1qnaOxjmWaK6ouVk9I8ZYw2uKsULPXjByj7K2FthoqXVuYZikntK3OvSkdSnqlNPMsIiRa\nm/qmSzStPch8S/YvFfJcm0tPcN1lYlBX/Hq+qb7OapaaUiZWl+lYMpFMKjJiXAFSpfYO1o9S6bTA\ngQ8hIb+vDvtIVclolUZZR6mwOinL73RtT9f2NK6Vpu9+f3gdYQVe6QhQR6ciBxerpkRAKhjZK6cs\n++quE4s3ay3dRmMbsYd3jQFVDgasxghKteQKSa9cg3leWA155ZjFnTymeOjxtG1D0ziapkErzWYr\nPYu2aap9GhgL1kn1de+egKnmeapIw/aAIm2ato4ppSEsIDVqlbh6NwaUrvB3a64s6JXCLzMhLXUL\nWftQRaP0FZ9Fxue2ojULpib5GBVGt6SkZOKgnVCgbUfjNmglPQ2lRYPDOVfP3QKS3NdzSRVtG5ZA\nXG4pTmHxsnLGWFF/q/ddEKWcvnUss8dtDNvO0pfCVz3zanKIPOcnXGOZSQQWVISuaVC54OdFbOaV\nrTeJcBy0UaisKXWGb6yRhS0KPDhWBKMPMzaK/p7ySt5UrTEFlhDxKeFsLw3Lih7se1dtxpAOdZLt\nhC4Jo8S/jyxJIBehAcsDKSt+Vgj0NkQ0BtNolgp6EQ2+UHUY5MbMrA2wIueENFcF16CE51/kBUrR\nNQlRtxIckhNKVcivPGCy4iZSVhVI1ddrE3l0flFpxoZpnmXchVQURmiZ0tSOieSL6AtWXQhDS4pe\nHnqjmSeP1qciHGL3BJUIRYRPynyBSq04RGtDzpr5fM+yg06divCNElix6zt6lQjTQmsbzs7uAmDt\nlhgWtMrEkFBJkkrbGqa94FfEvYvanJUKUStR1VImY5wwIkX+XujRsuzW2YDRFOUxagZl0Ep6SqZp\n2E+XaJXoGk0mk3yUhY6A0Y2cNxpUxZpkoW5rBcoqcgUXJeVlquM9eZcIeUcqggmZ/YQveww9JStU\nMcLBaBTaQcwBW6XtfZgP4j+rC/bT4maTwiw3ovceP82okg8Go9Zo2iqUoos40dy7f497JyecnpwS\ni+fh/hKlIj5FUn04ZUVJbHpRgF6WpZbZgk/QFX6b68gn1VXWGCOTAqMgyN4s11Fb4zqcsSJsUUIt\nS1Ol4kqxZas3g9YWi0JnaKzDRFm91BNsxjUOKjmA0ooQI94vtKalUIg5SdWiVe165wOUutRkIv+n\n5pe1Uniiz1Bf6YnPOSSLJ2MVi1kNSdf3ZFUizqXqBRYOq1upr1F7rkCR3oIcjDSLixbgERZyBJN4\n/OgxF5cTp9tnmOeI6SVpzSGSkmeeZxwCYze8YRuUAAAEDElEQVTKUbzCLxGVLa0zdI05zOtd73BW\nESZP327Ybk/qfWBRyJa0bzcoZclZCFcri9bUKuDiYsflfk/f9/RtR97vUCqitJyRvOcFc9XEISPJ\neXu6gQDRX10bjUYhdnDaiIKWIE1lamOqAPDV9ZPphgJyDELTX5WXTCEVT8wLKipMVPg0QYiEORFT\nppSu8lBk8VklCcraDV9fvzphO+vQ7umPviqlPPWHxzjGMf7/xY32FI5xjGPcvjgmhWMc4xjX4pgU\njnGMY1yLY1I4xjGOcS2OSeEYxzjGtTgmhWMc4xjX4kZwCsMwKOD3gdcDM/AT4zh+7iaO5ZXEMAyf\nBFbv+X8Hfg34Y4Sp8OlxHH/mhg7tS4phGL4d+I1xHL97GIZv4GWOfRiGnwTeAQTgPeM4/s1NHe/T\n4kXn8Qbgr4HP1B//wTiOH7zN5zEMgwXeD3wd0ADvAf6FG74eN1UpvA1ox3H8LsTZ+rdu6Dj+1zEM\nQwswjuP31I8fR47/XeM4vgXQwzD88I0e5BeJYRjeCbwPaOu3XnLswzC8BvhZ4DuBHwB+vbqM35p4\nmfN4I/DeJ67LB78CzuNHgefHcXwzcny/yy24HjeFaHwT8GGAcRw/MQzDt97QcbySeD2wHYbhIwjQ\n8t3At4zj+NH6878F3gr81Q0d3/8U/wb8CPAn9es3vujYvw9ZpT42jmMEzodh+CzwzcAnv9wH+0Xi\nJecBfOMwDG9DqoWfB76N230efw58sH5uECubF99LX/brcVOVwhlX5TdAHIbhK6W/sQd+cxzH7wd+\nGvhTriveXQB3buLAvpQYx/FDHHyUgJce+xlwyvXrc8ktO6eXOY9PAO+sK+zngF/lpffZrTqPcRz3\n4zjuhmE4RZLDu7kF1+OmHsRz5EQPxzGO49NF425XfAZJBIzj+FngAfCaJ35+Cjy6geN6pfHk+74e\n+zlyM774+7c5/nIcx0+tnwNvQB6kW30ewzB8LfD3wAfGcfwzbsH1uKmk8HHghwCGYfgO4J9v6Dhe\nSbwdeC/AMAxfjVysvxuG4S315z8IfPQpf3sb45+GYXhz/Xw99n8E3jQMQzMMwx3gm4BP39QBfonx\n4Se2od+LlNa3+jxqr+AjwC+O4/iB+u1P3fT1uKmewoeAtw7D8PH69dtv6DheSfwR8P5hGP4Bocz9\nGFIt/GFt/vwr8Bc3d3j/6/gF4H1PHvs4jmUYht8GPoaUs+8ax/HpUj23I34K+L1hGDzwn8A7xnG8\nvOXn8UvAXeCXh2H4FeR++jngd27yehxZksc4xjGuxVdKc+8YxzjGlymOSeEYxzjGtTgmhWMc4xjX\n4pgUjnGMY1yLY1I4xjGOcS2OSeEYxzjGtTgmhWMc4xjX4pgUjnGMY1yL/wZERxpkZMFEwQAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e64c6358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape (1, 3, 224, 224)\n"
     ]
    },
    {
     "data": {
      "image/png": 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b3P4Y8Fi9i+olM4spcoUSR/Y1/2PkgUE/7z3t46XRJP/rhSlWVtOE3cWWbux9YXwJgNOH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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e18e5828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get a 224x224 image as input\n",
    "X_test = plt.imread('https://www.allpondsolutions.co.uk/SiteFiles/Handlers/Shared/ImageSizer.ashx?image=~%2FAllPondSolutions%2Fmedia%2FSiteImages%2FCategory%2520Images%2FTiger-Shrimp.jpg%3Fext%3D.jpg&width=224')\n",
    "plt.imshow(X_test)\n",
    "plt.show()\n",
    "\n",
    "# remove alpha channel and add sample dimension\n",
    "X_test=X_test[:,:,:3].reshape((1,224,224,3))\n",
    "X_test=np.transpose(X_test,(0,3,1,2))\n",
    "\n",
    "# show dist\n",
    "sns.distplot(X_test.flatten())\n",
    "\n",
    "print('shape',X_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model\n",
    "\n",
    "Lets use the VGG16 [1] model to give an example of how the weights and outputs should look\n",
    "\n",
    "[1] Simonyan, K., & Zisserman, A. (2014). Very Deep Convolutional Networks for Large-Scale Image Recognition. ImageNet Challenge, 1–10. http://doi.org/10.1016/j.infsof.2008.09.005*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "____________________________________________________________________________________________________\n",
      "Layer (type)                     Output Shape          Param #     Connected to                     \n",
      "====================================================================================================\n",
      "input_9 (InputLayer)             (None, 3, 224, 224)   0                                            \n",
      "____________________________________________________________________________________________________\n",
      "block1_conv1 (Convolution2D)     (None, 64, 224, 224)  1792        input_9[0][0]                    \n",
      "____________________________________________________________________________________________________\n",
      "block1_conv2 (Convolution2D)     (None, 64, 224, 224)  36928       block1_conv1[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block1_pool (MaxPooling2D)       (None, 64, 112, 112)  0           block1_conv2[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block2_conv1 (Convolution2D)     (None, 128, 112, 112) 73856       block1_pool[0][0]                \n",
      "____________________________________________________________________________________________________\n",
      "block2_conv2 (Convolution2D)     (None, 128, 112, 112) 147584      block2_conv1[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block2_pool (MaxPooling2D)       (None, 128, 56, 56)   0           block2_conv2[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block3_conv1 (Convolution2D)     (None, 256, 56, 56)   295168      block2_pool[0][0]                \n",
      "____________________________________________________________________________________________________\n",
      "block3_conv2 (Convolution2D)     (None, 256, 56, 56)   590080      block3_conv1[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block3_conv3 (Convolution2D)     (None, 256, 56, 56)   590080      block3_conv2[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block3_pool (MaxPooling2D)       (None, 256, 28, 28)   0           block3_conv3[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block4_conv1 (Convolution2D)     (None, 512, 28, 28)   1180160     block3_pool[0][0]                \n",
      "____________________________________________________________________________________________________\n",
      "block4_conv2 (Convolution2D)     (None, 512, 28, 28)   2359808     block4_conv1[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block4_conv3 (Convolution2D)     (None, 512, 28, 28)   2359808     block4_conv2[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block4_pool (MaxPooling2D)       (None, 512, 14, 14)   0           block4_conv3[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block5_conv1 (Convolution2D)     (None, 512, 14, 14)   2359808     block4_pool[0][0]                \n",
      "____________________________________________________________________________________________________\n",
      "block5_conv2 (Convolution2D)     (None, 512, 14, 14)   2359808     block5_conv1[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block5_conv3 (Convolution2D)     (None, 512, 14, 14)   2359808     block5_conv2[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "block5_pool (MaxPooling2D)       (None, 512, 7, 7)     0           block5_conv3[0][0]               \n",
      "____________________________________________________________________________________________________\n",
      "flatten (Flatten)                (None, 25088)         0           block5_pool[0][0]                \n",
      "____________________________________________________________________________________________________\n",
      "fc1 (Dense)                      (None, 4096)          102764544   flatten[0][0]                    \n",
      "____________________________________________________________________________________________________\n",
      "fc2 (Dense)                      (None, 4096)          16781312    fc1[0][0]                        \n",
      "____________________________________________________________________________________________________\n",
      "predictions (Dense)              (None, 1000)          4097000     fc2[0][0]                        \n",
      "====================================================================================================\n",
      "Total params: 138357544\n",
      "____________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model=keras.applications.VGG16()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Histograms of weights and biases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eed56f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ee865828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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mZqhlItOnkj2BQ4AOM7sL2AP4AnCYu/fG+1cBxxP2Cta4+w4gbWYb4mOPAb6cV3fpFLZf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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8fc6208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8f9beb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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aGFYys48Bn2brxZvrgD+y9fIaBcLlNrKPeRtwGvBB4Iu1UBOED6yZnQv8EzCm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\nAgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ee9a0438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eeb083c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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kICIiCUoOIiKSoKuVZFwNd09BLpeFwiRUSETKouQg4yqXy7L50edoak4NiO9r\ne4nmVAvNs3U5qchUVHFyMLPHgIPx7fPA54DbgF5gp7tfEctdBiwHDgFr3H2DmTUCdwDzgCxwibvv\nrbQuMrU1NacS9xR05NsnqTYiUo6K5hzMbBaAu58Z//1f4HpglbsvA+rN7D1mNh9YCSwGzgOuM7OZ\nwOXAU+6+FLgdWD0G2yIiImOk0p7DAiBlZpuAY4C/AE52963x8/uBdxB6Edvc/TCQNbNdcdklwOeL\nyio5iIhMIZVerdQBfNHdzyX0Ar4JFD+tLAe0AGn6h54A2oHWQfG+siIiMkVU2nN4FngOwN13mdle\n4OSiz9PAAcJ8Qsug+P4YTw8qW1Imo8nLPtOlLRoaepmd2kdqduOAeGe+gfr6maRHHYdUqjERr2Rd\n9fQwd26a1tbp0bZDmS77xURQW4xOpcnhUuCtwBVm9mpCAnjAzJa5+xbgfOBBYDuwxswagCbgBGAn\n8DBwAbAj/tya/IqkPXtyFVa3umQy6WnTFtlsjvZ8N710DYjn8z3U1x9hVtPo4uGzrmHiR7eujnw3\nbW05enqm5+0/02m/GG9qi36VJslKk8PNwC1m9j3C1eofBvYC34gTzs8Ad7t7wczWAtsIw06r3L3H\nzNYB681sK9ANXFxhPUREZBxUlBziBPMfDvHRGUOUvZmQTIpjncD7KvluEREZf7oJTiTSX4gT6afk\nIBLpL8SJ9FNyECmivxAnEkzPyzJERGRcKTmIiEiChpVkTOjR3CLVRclBxoQezS1SXZQcZMzo0dwi\n1UNzDiIikqCeg0gJujlOapGSg0gJujlOapGSg0gZdHOc1BrNOYiISIJ6DnJUdD+DSG1QcpCjovsZ\n+mmiWqqZkoMcNd3PEGiiWqqZkoPIKGiiWqqVkoMkjDRcormF0kZqP9CQk0wPSg6SMNy8AtTm3MLR\nGm64qe8zDTnJdKDkUMNGuvKoqSk5rwC1ObdQieGGmzSJLdPFpCUHM6sDvgosALqAj7j7TyerPtVs\npCTwgx+/TFNKVx5NlOF6FR35dhb/5nzS6ZbEMkoaMhkms+fwXmCWu59mZguB62NMKlRxEtCVRxNq\nqF5FR76dLY//TElDpozJTA5LgI0A7v6omb1tEusyaUYaZigUwszv4APAzJlHOHgwl4grCUxvo00a\nDQ29HDwY9qXB+8Zw+9Jw8T5KQLVrMpNDC3Cw6P1hM6t3996xWPnzz/+UF198IRF/1atexdy5mbH4\nijGRy2USw5kRAAAEGklEQVR56LHnaWxsSny2f18b9fXH0HrsrwyI93Tl6Ow6nIjv39dGKtWSSA4A\nXZ0ddORzg2J56utnlB2vZJlxj3d00NV1ZFrUdTTrGmo9G7//zIB9INU8i1/84n+G3GeG25eGiwN0\ndXXy9lOOH7LXMtU1NPSSzSbbf7qajAsYJjM5ZIHi06RSiaEukyl/DDyTWUCYzpj6TjrpLZNdBZGq\n09qqK8JGYzIfvPd94AIAM1sEPD2JdRERkSKT2XO4FzjHzL4f3186iXUREZEidX0TUiIiIn309xxE\nRCRByUFERBKUHEREJGHKPlvJzBqBO4B5hMteL3H3vYPKfBJ4P+E5od9x97+a8IpOgHLaIpbLANuA\nE929Z2JrOb5KPW7FzN4NrAYOAbe6+zcmpaIToJxHz5hZM/AA8Efu/uzE13JilLFffAD4BGG/eNrd\nPzopFR1nZbTD7wFXAb3Ane6+ttQ6p3LP4XLgKXdfCtxO+MV/hZkdD3zA3Re5+2LgXDP7rUmo50QY\nsS0AzOwdwCZg/gTXbaK88rgV4DOEx60AYGYz4vuzgTOA5TFRVqth2wLAzE4BtgC/Pgl1m2gj7ReN\nwLXAMnc/HTjWzN41OdUcdyO1Qz3wOeBM4DTgo2Y2p9QKp3JyeOXxGsD9hF/8Yj8Dzit6P5OQMatR\nqbYAOAKcBeybqEpNsAGPWwGKH7fyZmCXu2fd/RCh97R04qs4YUZqC4AGwsHiJxNcr8kwUlt0A6e5\ne3d8P4MaOEYMbod4c/Gb3b0dmEs47pccWZgSw0pm9kfAJ+n/MzJ1wC/pf7xGjvC4jVe4+xHigdDM\nvgg87u7PTUiFx1ElbQHg7v8el6/WB+GM9LiVwZ/lgGq+PXbER8+4+yNQ1ftCsWHbwt0LwB4AM1sJ\npNz9u5NRyQlQap/oNbMLgb8D7gPypVY4JZKDu98C3FIcM7N/of/xGmngwODlzGxWXO4gUBVjiZW2\nRZFqvXFlpMetZBmYMEu10XR3tI+eqWYjtkVMkF8A3gT87gTXbSKV3Cfc/V7gXjNbD/whsH6kFU7l\nYaVXHq8Rf24dosy/Aj9y94/Gs4RqVU5b9KnWs8WRHrfyDPBGMzvWzBoIQ0qPTHwVJ4wePdOvVFv8\nP8JY/HuLhpeq0bDtYGZpM9sSfzcg9BpKnkxM2TukzayJkNmOI4wdXuzuL8crlHYRej13Aj8gHBAL\nwGfieFtVKdUW7n5fUdmfAidU8dVKb42hS4FTCEMF3zCzdwJXE/aFm939a5NT0/FXqi2Kyj0IrKiR\nq5USbQE8Bmyn/2SqAHzF3b890fUcb2X8fnwE+AhhruEpYGWpE+opmxxERGTyTOVhJRERmSRKDiIi\nkqDkICIiCUoOIiKSoOQgIiIJSg4iIpKg5CAiIglKDiIikvD/AVIh6FrpqgPCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ee946390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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H4CbgRHe/NTz8gJkd4O63A4cCt9SzodWr8w0V2k6Dg1nVD+RyeYYLo4yzoQlVbVEojNHZ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\nEpn/D9dn2f6KSh08AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eefe8588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RkbKp6enpqXQNu6unWg7/slZnPr+JFU//Dw2NOw9Nc031vPjiWiYffjDNzS0VrG5wWdyf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\nBYaIiERRYIiISBQFhoiIRPn/pvkDOYwTqL0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ef0876d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5efe92eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3aqiB6u9k+LqOdg5+9wQKhdY+X6cwERleeQyMVmBt5vEmM2t09y3bM2hnZyeP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\nQ0REkigwREQkyf8HtKJZndngHcoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eefe8e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ef087198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ef0ed860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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DhoE17r64YelERKRqFXvsZjYDuBQYCE8tBZa4+3wgY2YLG5hPRESqlGYo5gLgEuB5oA3Y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\nkJzFMQQ8Bpw2FR2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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5efe942b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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I3JRUjdnHHT5hLm8+EbbdcBxfY6tUyrt945mJMVlsZmZ7nROGmZkV4oRhZmaFOGGYmVkh\nThhmZlaIE4aZmRXihGFmZoU4YZiZWSFOGGZmVogThpmZFeKEYWZmhThhmJlZIU4YZmZWiBOGmZkV\n4oRhZmaFOGGYmVkhde+4J6kE3AoI6CW7W14zcC/wdKq2KCLulnQxcAmwFVgQEUskTQHuBA4lu8f3\nhRGxXtLJwE2p7vKIuDa93lXAOan88v678ZmZ2dgqcovWtwJ9ETFb0lzg48C3gRsi4jP9lSQdBswH\nTgCmAe2SlgGXAY9HxLWSzgWuBD4ALALeERFrJC2RNJNsxDMnImZJOgL4GnDSqEVrZmYjVndKKiK+\nRTZqADgaeAE4EXiLpBWSbpU0nWzH3h4R2yKiCjwDzARmA/en598HnCapDDRHxJpUvhQ4PdVdll73\nOWCSpEP2OEozM9tjhdYwIqJX0m3AZ4GvAg8DH4qIucDPgKuBVmBj7mmdQBtQzpXXcmXVXN3aEHXz\nbZiZ2RgrMiUFQERcJOkjwA+BUyJibXrom8BCYAVZ0uhXJhuNVNPv/WUvkiWIoer25Orm6w+rUinX\nq9LQGj2+5uZeprdsoGX6lIGyzV3NlEqTASin8hI9zJhRpq2tsePNa/RtV4/j278UWfR+F/BbEXEd\nsIVs4fvrkt6XFqRPAx4DHgEWSGoGpgLHAquBh4CzgUfTz5URUZPULekYYA1wBnANsB24XtINwBFA\nU0RsqNfHdetquxV0I6lUyg0fX7Vao7Orm162DJR1dfVQKm1nRgVqnVn5pq5uOjpq9PRMjJP3JsK2\nG47ja2wjSYZFRhj3ALdLWpHqvw/4BfB5ST3Ar4BLIqJT0kKgHWgCroiIHkmLgMWSVgLdwAWp3UuB\nu8imxZb1nw2V6q1Kbczb7YjMzGyvaOrr6xvrPuypvol+FNDo8VWrG2l/Yi3TWnYc0XQ8v5ZSaRJH\nHX1kboRRY/Zxh9PaOjGWrSbCthuO42tslUq5aXefMzHG/mZmttc5YZiZWSFOGGZmVogThpmZFeKE\nYWZmhThhmJlZIU4YZmZWiBOGmZkV4oRhZmaFOGGYmVkhThhmZlaIE4aZmRXihGFmZoU4YZiZWSFO\nGGZmVogThpmZFeKEYWZmhRS5p3cJuBUQ2f28LyW71ert6e/VETEv1b0YuATYCiyIiCWSpgB3AocC\nVeDCiFgv6WTgplR3eURcm9q4CjgnlV/ef+tWMzMbW0VGGG8F+iJiNnAl8HHgRrJ7ds8FSpLeJukw\nYD5wCnAmcJ2kycBlwOMRMQe4I7UBsAg4LyJOBWZJminpeGBORMwCzgduHrVIzcxsj9RNGBHxLbJR\nA8BRwAvACRGxMpXdB5wOnAS0R8S2iKgCzwAzgdnA/bm6p0kqA80RsSaVL01tzAaWpdd9Dpgk6ZA9\nitDMzEZFoTWMiOiVdBuwELgLyN88vAa0AmVgY668E2gbVF7LlVUHtTG4br4NMzMbY3XXMPpFxEWS\nPgI8AkzNPVQGXiRLAK2Dyl9I5eVBdWu7qNuTq5uvP6xKpVyvSkNr9Piam3uZ3rKBlulTBso2dzVT\nKk0GoJzKS/QwY0aZtrbGjjev0bddPY5v/1Jk0ftdwG9FxHXAFmA78KikuRGxAjgLeIAskSyQ1EyW\nUI4FVgMPAWcDj6afKyOiJqlb0jHAGuAM4JrU9vWSbgCOAJoiYkO9Pq5bV9utoBtJpVJu+Piq1Rqd\nXd30smWgrKurh1JpOzMqUOvMyjd1ddPRUaOnZ2KcvDcRtt1wHF9jG0kyLDLCuAe4XdKKVP99wFPA\nF9Oi9pPAPRHRJ2kh0E42ZXVFRPRIWgQslrSS7OyqC1K7l5JNb5WAZf1nQ6V6q1Ib83Y7IjMz2yua\n+vr6xroPe6pvoh8FNHp81epG2p9Yy7SWHUc0Hc+vpVSaxFFHH5kbYdSYfdzhtLZOjGWribDthuP4\nGlulUm6qX2tnE2Psb2Zme50ThpmZFeKEYWZmhThhmJlZIU4YZmZWiBOGmZkV4oRhZmaFOGGYmVkh\nThhmZlaIE4aZmRXihGFmZoU4YZiZWSFOGGZmVogThpmZFeKEYWZmhThhmJlZIU4YZmZWyLC3aJV0\nAPBl4GigGVgAPAfcCzydqi2KiLslXQxcAmwFFkTEEklTgDuBQ4EqcGFErJd0MnBTqrs8Iq5Nr3cV\ncE4qv7z/tq1mZjb26o0w3gl0RMQc4Czgc8AJwA0R8cb0725JhwHzgVOAM4Hr0v2+LwMeT8+/A7gy\ntbsIOC8iTgVmSZop6XhgTkTMAs4Hbh7dUM3MbE/USxj/zI6dfInsyP9E4C2SVki6VdJ04CSgPSK2\nRUQVeAaYCcwG7k/Pvw84TVIZaI6INal8KXB6qrsMICKeAyZJOmQUYjQzs1EwbMKIiE0R0ZV28ncD\nHwN+CHwoIuYCPwOuBlqBjbmndgJtQDlXXsuVVXN1a0PUzbdhZmbjwLBrGACSjgC+DnwuIv5RUltE\n9O/YvwksBFaQJY1+ZeAFssRQzpW9SJYghqrbk6ubr19XpVKuX6mBNXp8zc29TG/ZQMv0KQNlm7ua\nKZUmA1BO5SV6mDGjTFtbY8eb1+jbrh7Ht3+pt+h9GNmU0byIeDAV3y9pfkQ8CpwGPAY8AiyQ1AxM\nBY4FVgMPAWcDj6afKyOiJqlb0jHAGuAM4BpgO3C9pBuAI4CmiNhQJIh162rFI24wlUq54eOrVmt0\ndnXTy5aBsq6uHkql7cyoQK0zK9/U1U1HR42enolx8t5E2HbDcXyNbSTJsN4I46PAQcCV6QymPuAD\nwE2SeoBfAZdERKekhUA70ARcERE9khYBiyWtBLqBC1K7lwJ3kU2JLes/GyrVW5XamLfb0ZiZ2V7T\n1NfXN9Z92FN9E/0ooNHjq1Y30v7EWqa17Dii6Xh+LaXSJI46+sjcCKPG7OMOp7V1YixdTYRtNxzH\n19gqlXLT7j5nYoz9zcxsr3PCMDOzQpwwzMysECcMMzMrxAnDzMwKccIwM7NCnDDMzKwQJwwzMyvE\nCcPMzApxwjAzs0KcMMzMrBAnDDMzK8QJw8zMCnHCMDOzQpwwzMysECcMMzMrxAnDzMwKqXdP7wOA\nLwNHA83AAuA/gNuBXmB1RMxLdS8GLgG2AgsiYomkKcCdwKFAFbgwItZLOhm4KdVdHhHXpjauAs5J\n5Zf337rVzMzGXr0RxjuBjoiYA5wJfA64keye3XOBkqS3SToMmA+ckupdJ2kycBnweHr+HcCVqd1F\nwHkRcSowS9JMSccDcyJiFnA+cPOoRmpmZnukXsL4Z3bs5CcB24ATImJlKrsPOB04CWiPiG0RUQWe\nAWYCs4H7c3VPk1QGmiNiTSpfmtqYDSwDiIjngEmSDtmz8MzMbLQMmzAiYlNEdKWd/N3A3wL5G4fX\ngFagDGzMlXcCbYPKa7my6qA2BtfNt2FmZuPAsGsYAJKOAL4OfC4i/lHSJ3MPl4EXyRJA66DyF1J5\neVDd2i7q9uTq5uvXVamU61dqYI0eX3NzL9NbNtAyfcpA2eauZkqlyQCUU3mJHmbMKNPW1tjx5jX6\ntqvH8e1f6i16H0Y2ZTQvIh5MxT+WNCcivgecBTwAPAIskNQMTAWOBVYDDwFnA4+mnysjoiapW9Ix\nwBrgDOAaYDtwvaQbgCOApojYUCSIdetqxSNuMJVKueHjq1ZrdHZ108uWgbKurh5Kpe3MqECtMyvf\n1NVNR0eNnp6JcfLeRNh2w3F8jW0kybDeCOOjwEHAlekMpj7g/cDfp0XtJ4F7IqJP0kKgnWzK6oqI\n6JG0CFgsaSXQDVyQ2r0UuItsSmxZ/9lQqd6q1Ma83Y7GzMz2mqa+vr6x7sOe6pvoRwGNHl+1upH2\nJ9YyrWXHEU3H82splSZx1NFH5kYYNWYfdzitrRNj6WoibLvhOL7GVqmUm+rX2tnEGPubmdle54Rh\nZmaFOGGYmVkhThhmZlaIE4aZmRXihGFmZoU4YZiZWSFOGGZmVogThpmZFeKEYWZmhThhmJlZIU4Y\nZmZWiBOGmZkV4oRhZmaFOGGYmVkhThhmZlZI3Xt6A0iaBXwiIt4g6TXAvcDT6eFFEXG3pIuBS4Ct\nwIKIWCJpCnAncCjZ/b0vjIj1kk4Gbkp1l0fEtel1rgLOSeWX99+Jz8zMxl7dhCHpw8C7gM5UdCJw\nQ0R8JlfnMGA+cAIwDWiXtAy4DHg8Iq6VdC5wJfABYBHwjohYI2mJpJlko505ETFL0hHA14CTRitQ\nG//6+vqo1aovKS+XW2lq2u2bg5nZKCsywngWeAdwR/r7ROCVkt5ONsq4nGzH3h4R24CqpGeAmcBs\n4Pr0vPuAj0kqA80RsSaVLwVOJ7vn9zKAiHhO0iRJh0TE+j2M0RrE5k1drPjRBg46+JCdyk6f9YoJ\nc9tWs0ZWdw0jIr4BbMsVPQx8OCLmAj8DrgZagY25Op1AG1DOlddyZfnDyNoQdfNt2H5kytRpTGsp\nD/ybOq1lrLtkZkmhNYxBvhkR/Tv2bwILgRVkSaNfGXiBLDGUc2UvkiWIoer25Orm69dVqZTrV2pg\njR5fc3Mv01s20DJ9ykDZ5q5mSqXJAJRTeX9ZOVevRA8zZpRpa2vM96DRt109jm//MpKEcb+k+RHx\nKHAa8BjwCLBAUjMwFTgWWA08BJwNPJp+royImqRuSccAa4AzgGuA7cD1km4AjgCaImJDkQ6tW1cb\nQRiNoVIpN3x81WqNzq5uetkyUNbV1UOptJ0ZFah1btmp7MCpO+pt6uqmo6NGT0/jndA3EbbdcBxf\nYxtJMhxJwrgUuFlSD/Ar4JKI6JS0EGgHmoArIqJH0iJgsaSVZGsUF+TauItsSmxZ/9lQqd6q1Ma8\nEfTNzMz2kqa+vr6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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8bc7e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RkXqkSez3Abvc/QHgTjObBB5TtjwH7K1VychIrr4IO0QntK+nZ4aB7BjZgd6KZTJMMzyc\nY2jo0PbMtq+ROtpZJ3x+jYi5fTG3rV5pEvuNwLuAT5vZo4As8AMzW+3u24B1wNZalezZU2go0HY2\nMpLriPbl8wXGi1PMMFmxTHF8kt27f08ud7A9w8M5RkeT54VCnvHx6nVMFKcYHS0wPd0ZF111yudX\nr5jbF3PboP6DVs3E7u7fMbMTzezHQBfwDuDfgU1m1g3sAq6sa+3SdvZPFNm2Y4wjlh/54GsD2THG\ni1MAjI3eS392kP4B9ZJE2lWqyx3d/ex5Xl7T3FCkXfT29dOfPZi4swO9D/bQJ4rjhyssEUmpM74r\ni4hIakrsIiKRUWIXEYmMEruISGSU2EVEIqPELiISGSV2EZHIKLGLiERGiV1EJDJK7CIikVFiFxGJ\njBK7iEhklNhFRCKjxC4iEhkldhGRyCixi4hERoldRCQyqX5BycxuBfaFp7uBTwCbgRlgp7uvb0l0\nIiKyYDV77Ga2DMDdTwr//juwEdjg7quBjJmd2uI4RUQkpTQ99mcBWTO7FlgCfAhY4e7bw/ItwFrg\n6taEKCIiC5FmjH0COM/dTwHeAXwF6CpbXgCGWhCbiIjUIU2P/U7gbgB3v8vM7gNWlC3PAXtrVTIy\nkqtVpKN1Qvt6emYYyI6RHeitWGZ/sYdMppvcnDKzzystL5dhmuHhHEND7b9NZnXC59eImNsXc9vq\nlSaxnwE8E1hvZo8CBoHvmdlqd98GrAO21qpkz55CQ4G2s5GRXEe0L58vMF6cYobJimWKxWkymQMs\n6ztYJjfQS2F8suLyP6tjfJLdu39PLld9m+Ryg3R1dVUtsxg65fOrV8zti7ltUP9BK01i/yJwqZnd\nAJSANwH3AZvMrBvYBVxZ19olSvsnimzbMcYRy4+sWmbtyqMZHNQonkiz1Uzs7v4A8DfzLFrT9Ggk\nGr19/fRn9RVZ5HDQDUoiIpFRYhcRiYwSu4hIZJTYRUQio8QuIhIZJXYRkcgosYuIREaJXUQkMkrs\nIiKRUWIXEYmMEruISGSU2EVEIqPELiISGSV2EZHIKLGLiERGiV1EJDJK7CIikUnz03iY2cOAnwIn\nAweAzcAMsNPd17csOhERWbCaPXYzWwpcBEyElzYCG9x9NZAxs1NbGJ+IiCxQmqGY84ELgXuALmCF\nu28Py7aQ9OJFRKRNVB2KMbM3AX909+vMbEN4ufxgUAD0M/OyYKVSiUIhX7VMLjdIV1fXIkUkEo9a\nY+xnADNmthZ4FvAlYKRseQ7Ym2ZFIyNx/2J9J7Svp2eGgewY2YHeimX2F3vIZLrJzSkz+7zS8jR1\nHFrmPn7i97J8+QPzLp+YKPLyNU9jaGiwWpOaphM+v0bE3L6Y21avqok9jKMDYGZbgbcD55nZKne/\nAVgHbE2zoj17Co3E2dZGRnId0b58vsB4cYoZJiuWKRanyWQOsKzvYJncQC+F8cmKy9PUMX+ZJczQ\nM+/ymdIUo6MFpqdbf+FWp3x+9Yq5fTG3Deo/aKW6KmaO9wOXmFk3sAu4sq41i4hIS6RO7O5+UtnT\nNc0PRUREmkE3KImIREaJXUQkMkrsIiKRUWIXEYmMEruISGTqudxR2lStuzkLhTyUFjGgBqS5MxV0\nd6rIfJTYI1Io5Lnulrvp68/Ou3xs9F76s4P0D7T/nXr7J4ps2zHGEcuPrFpm7cqjGRzUrBYi5ZTY\nI9PXn6U/O3/iniiOL3I0jent66/YFhGpTGPsIiKRUWIXEYmMEruISGSU2EVEIqPELiISGSV2EZHI\nKLGLiERGiV1EJDI1b1AyswxwCWDADMnP400Bm8Pzne6+voUxiojIAqTpsb8MKLn784FzgE8AG4EN\n4TdRM2Z2agtjFBGRBaiZ2N39auBt4enjgD8BK9x9e3htC3Bya8ITEZGFSjVXjLvPmNllwCuB1wBr\nyxYXAM3C1GJpZjvspNkbRaR1FvJj1meY2QeAnwB9ZYtywN5a7x8ZiXsyp1a3b9++fVx78+/orzBz\nI8DonnvJDgyRG+idd/n+Yg+ZTHfF5dXKzD5vpI6FlElTR4ZphodzDA01vu21f3aumNtWrzQnT98A\nPMbd/wmYBA4APzWz1e6+DVgHbK1Vz549hUZjbVsjI7mWty+fLzBTWsoMPRXLzJSWUixOsqxvct7l\nxeI0mcyBissrlckN9FIYn2yojoWWSVPHRHGK0dEC09ONXdy1GJ/f4RRz+2JuG9R/0ErTY78S2Gxm\n20L5dwF3AJvMrBvYFcqIiEgbqJnY3X0/cNo8i9Y0PRoREWmYblASEYmMEruISGSU2EVEIqPELiIS\nGSV2EZHIKLGLiERGiV1EJDJK7CIikVFiFxGJjBK7iEhkUs/uKNJu0kxlnMsN0tXVtUgRibQHJXbp\nWPsnimzbMcYRy4+suHztyqMZHNTPBchDixK7dLTevn76s5qPW6ScxthFRCKjxC4iEhkldhGRyCix\ni4hEpurJUzNbClwKPB7oAT4O/ArYDMwAO919fWtDFBGRhajVY389MOruq4AXAxcAG4EN7r4ayJjZ\nqS2OUUREFqBWYv/fwDnh8RLgAWCFu28Pr20BTm5RbCIiUoeqQzHuPgFgZjng68CHgPPLihQA3f0h\nItJGat6gZGZ/AXwDuMDd/9XMzi1bnAP2plnRyEjcN5G0un09PTMMZMfIDvRWLLO/2EMm002uQpla\ny6uVmX3eSB2LFeusDNMMD+cYGqr92Wj/7Fwxt61etU6ePhy4Fljv7teHl28zs1XufgOwDtiaZkV7\n9hQaCrSdjYzkWt6+fL7AeHGKGSYrlikWp8lkDrCsb/4ytZZXKpMb6KUwPtlQHYsVa7mJ4hSjowWm\np6uPOC7G53c4xdy+mNsG9R+0avXYPwgcAZxjZh8GSsC7gc+bWTewC7iyrjWLiEhL1Bpjfw/wnnkW\nrWlJNCIi0jDdoCQiEhkldhGRyCixi4hERvOxt4lavwZUKOSTU9ciIjUosbeJQiHPdbfcTV9/dt7l\nY6P30p8dpH9A1+yKSHVK7G2krz9b8deAJorjixyNiHQqjbGLiERGiV1EJDJK7CIikVFiFxGJjBK7\niEhklNhFRCKjxC4iEhkldhGRyCixi4hERneeSrRqzb8za3h4YBGiEVk8SuwSrf0TRbbtGOOI5UdW\nLXP6cA59eZWYpErsZrYS+KS7v8DMjgI2AzPATndf38L4RBrS29dfcf4dkVjVTOxm9j+ANwCzs1Bt\nBDa4+3Yzu9DMTnX3q1sZpEirlEol9u3bx/33V+6x53KDdHV1Va0jzZBPrXpEmiVNj/1u4JXAFeH5\nse6+PTzeAqwFlNilI+2fKHLtzb+mZ9n84+z7J4qsXXk0g4NDFeuoNeVy2npEmqVmYnf3q8zscWUv\nlXc5CoD2VOlofX1ZlvU1NlxTbcplkcVWz8nTmbLHOWBvmjeNjMS90zfavp6eGQayY2QHeuddvr/Y\nQybTTa7C8jRlGqlj9nkz4mh1rAutA6hYJsM0w8M5hoYqf761Pru09bRSzH9/MbetXvUk9h1mtsrd\nbwDWAVvTvGnPnkIdq+oMIyO5htuXzxcYL04xw+S8y4vFaTKZAyzrm395mjL11pEb6KUwPtm0OFoZ\naz115HLdD7bvz5aPT7J79+/J5Sp/voVCnvHxyp8dwERxitHRAtPTi3/1TTP2z3YVc9ug/oNWPYn9\n/cAlZtYN7AKurGvNIh0gzSWT+tlCaTepEru7/wdwQnh8F7CmhTGJtJVal0zqZwul3eiuDBGRyCix\ni4hERoldRCQySuwiIpFRYhcRiYwSu4hIZJTYRUQio/nYF0Ga2f8KhTyUFikgEYmaEvsiSDP7n+5e\nFJFmUWJfJLVm/9PdiyLSLBpjFxGJjBK7iEhkNBQjsgjSnEBv9KfzKq2jp2eGfP7g1Lb6ib74KbGL\nLIJa0/8246fzKp2kH8iOMV6catp6pP0psYssklrT/zbDfCfpswO9VX8EROKjxC7SBtIM1YCGUSQd\nJXaRNpDml5o0jCJp1ZXYzawL+ALwLGASeIu7/6aZgXWSUqlEPr+v4nLdVSpp1BqqqdWrj20/q9Xe\nUqlEd/cB8vnq94A8FL/l1NtjfwWwzN1PMLOVwMbwWlu55z//wK9+cy9dmcof6nBuGc96hjW0nny+\n+p2luqtUmqFWrz62/azWHdtjo/cykMvSs2ygYh0P1W859Sb25wPfBXD3W8zsuOaF1DyTU1Nk+paT\nyVS+XH/qQHN+4bzanaW6q1SapVqvPsb9rNbfVV9flmV9cRzImqnexD4IlI89PGBmGXefaUJMTbNk\nyRIm83+Eal/DlkxVHUZJo7t7hv0TxYrLJ/cXyWSWMlGsfBCpVeZw1pFhmolwuVwz4mhlrPXUsXQp\nHJiZfx+Job3ln9/+iWKqk7TtoFDI1/y7qvbZAVXfH7OuUmnhg3Jm9ingZne/Mjz/rbs/ttnBiYjI\nwtU7pcBNwEsAzOx5wC+aFpGIiDSk3qGYq4C1ZnZTeH5Gk+IREZEG1TUUIyIi7UuzO4qIREaJXUQk\nMkrsIiKRaclcMWbWC3wZeBiQB97o7vfNKfNe4DSSm6CvcfePtSKWVkjTvlBuBLgROMbdpxc3yoWp\nNU2Emb0MOAe4H7jM3TcdlkDrlGYaDDPrB74HvNnd71z8KOuX4vM7HXg3yef3C3c/87AEWqcU7XsV\n8AFgBviqu3/usARap7TTtJjZxcB97r6hWn2t6rG/A/i5u68CriBJCOXBPQE43d2f5+7HA6eY2TNa\nFEsrVG0fgJm9CLgWePgix1avB6eJAD5IMk0EAGa2NDw/GVgDvC0ctDpJxfYBmNmxwDbgiYchtmao\n9vn1Av8IrHb3E4EjzOylhyfMulVrXwb4BHAScAJwppktPyxR1q/q/glgZn8LpMqTrUrsD045AGwh\nSQjlfgu8uOx5N3TUhNG12gdwAHghMLZYQTXokGkigPJpIp4K3OXueXe/n+RbyKrFD7Eh1doH0EPy\nx3XHIsfVLNXaNwWc4O5T4flSOuvvDaq0L9zx/lR3HweGSfJaW39DnkfV/dPMjgf+Erg4TWUND8WY\n2ZuB93JwXrku4A8cnHKgQDIFwYPc/QAh4ZnZecAOd7+70VhaoZ72Abj7D8L7O2VauWrTRMxdVgA6\nbValqtNguPvN0FGf11wV2+fuJWAPgJmdBWTd/fuHI8gG1Pr8ZszslcA/A98GOm0ugYrtM7NHAB8h\n6XiclqayhhO7u18KXFr+mpn9H2B2Zp4csHfu+8xsWXjfPqBtx/vqbV+ZTrlRIM/BNgGUz/2T59CD\nV602t6Nq7YtB1faFA9a5wJOA/7rIsTVDzc/P3a8CrjKzy4G/AS5fxPgaVa19rwGOBK4BHgn0mdkd\n7v6lSpW1aijmwSkHwv/b5ynzLeB2dz8z9Cg6SZr2zeqUHmC1aSJ2AUeb2RFm1kMyDHPz4ofYkNin\nwajVvn8hGcN9RdmQTCep2D4zy5nZtrBvQtJb77SDdsX2ufvn3f0v3f0k4JMkJ4crJnVo3S8oXQhc\nbmbbScb3XhcCfi9wV1jviUC3mb2EpFf7wTC21Amqts/dv11WtlMOWn82TUS4kiLr7pvM7H0kV4x0\nAZvc/T8PV6B1qtq+snKd8nnNVbF9wK0k035sN7PrSdr4WXe/+vCEWpda++cVwA1mNg38nOSqtU6S\ndv9MRVMKiIhERjcoiYhERoldRCQySuwiIpFRYhcRiYwSu4hIZJTYRUQio8QuIhIZJXYRkcj8fwQ8\nofaupOnHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8d6bac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3QGpTuVymVCr2KSuVilAe2+cAyOebyeVyo/dEIjIkBYmMiVKpyPKHn2FKY1NP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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8a1acc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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J8quBo4A1ZnYw0APcamYr3X0DcCpwR7VKtm/P9ss780F/f2Feta9YLDFYHkk9h3qhu4PS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8a1d898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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wwMzqgUnAwcAq4DHgVOCJ+HWZuxfMrMvM9gdWAycBlwHbgCvN7GpgP6DG3deZ2aPxubfH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\nAgWJjDkNkxp3uF+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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5fc225278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0p+yfu3/L3f/Y3Y8Avkby4fCUoQ7N+2m8i4CrzGwdyfjeh0PBZwKPhvt9G7DQ\nzN5NclT7hTC21A6q9s/db6xo2y47rZdMExHOpMi5+2Vm9jmSM0YywGXu/v/mqtAGVe1fRbt2eb4m\nmrJ/wL0k036sM7M7SPr4DXe/fm5KbUit7fMa4E4zGwMeJDlrrZ2k3T5T0ZQCIiKR0ReUREQio2AX\nEYmMgl1EJDIKdhGRyCjYRUQio2AXEYmMgl1EJDIKdhGRyPx/4R37jsq5cloAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8a864a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pBZgFHAOsAx4CzgEeTd+7I6IiqVfSUcBG4EzgGmAPcJ2k64EjgaaI2FrPTmza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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5fc225fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5efda1c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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U00c7A8yaVaK7e2K2vZ/z5nKeraPehPmhZMNKCyTdn8KPR8Q8Sd8DzgDuA1YD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\nh5mZFfb/AX2SGek+WZo9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ee9181d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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zu9x9QytzmdkrgfcARxMNEzVVg7+/bcBAWP4cYG0z99M41abUGP9YkSYe241k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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ef0588d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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v6yuQyezioInbyba1kO/dXrJtAgM0D9lnoNjPhg15CoXanLBXD/1ZTiPECIqz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\nIqn9f1cb+odxuC0qAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eea02e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ee9d5390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8faed68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2TAL4Ha9NvZAhmIrhVe4+YmbfBn5O8GZ0SbszAfMJ3kH3BUaAB83sYXd/tl2Z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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eeb6f780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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t2SKfXnm1taWrNneYfP6ZTJbuXB8D7BqK5XL9pFJ7mVm/a1jbQvHJxtLpGWS7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\nkcSoqIiISGJUVEREJDH/H82ew4XIX7CvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5efddb550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VSiW5Z90munviE22jw1uhrbPmP2wiIpMp8KXmunvik9aab2OMkZGdDaxIJJo0hi8iEhEK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\nfBGRiFDgi4hExP8HEtTx/bjFBIUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eeb177f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OLAZmA2cCN5jZZOBK4Dl3nwvcAywNZawELnT3U4FZZjbDzN4OzHX3WcBFwG0V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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eeb839b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RWG5mq0If5wEPApeb2VzgceDqOvsWEZEGqCvw3X0TcMIENy2eUjUiItIw2vFKRCQSCnwR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\niEgkFPgiIpFQ4IuIROL/A8+u/acFsyWYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eeab2940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_layers(model):\n",
    "    nbins=10\n",
    "    for layer in model.layers:\n",
    "        if type(layer)==keras.models.Sequential:\n",
    "                plot_layers(layer)\n",
    "        else:\n",
    "            if hasattr(layer,'weights') and layer.weights:                \n",
    "                for i,w in enumerate(layer.weights):\n",
    "                    data=w.get_value().flatten()\n",
    "                    plt.title('model=\"{}\" layer=\"{}\" '.format(model.name,w.name))\n",
    "                    sns.distplot(data,kde=False)\n",
    "                    plt.show()\n",
    "                \n",
    "plot_layers(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ouput at each step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EWdYONidvJc8XBP1kppvzfDPZOSYnM+RynZsUtpJ277W2WIlUKmj5Z2S1UFssaiQY1hIE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ed1ca2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eb7394e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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JamfvkLYDA73s3Fkd0l6pVOns6mOAoc/p7upj164q/f0Tu1axvb087GvnqYg1QTHrUk3Z\nqKbsiljXWMNrPEtnrwPuDhPY24CH3b1mZncAm0lOV612934zWwesN7MOoA+4NIxxFfAQySmtjYOr\nnkK/Z8MYq8ZRm4iIHAGZw8Ld3516eNYw2+8F7q1r6wE+PEzf50hWTtW3rwHWZK1JRESmhu4NJSIi\nUQoLERGJUliIiEiUwkJERKIUFiIiEqWwEBGRKIWFiIhEKSxERCRKYSEiIlEKCxERiVJYiIhIlMJC\nRESiFBYiIhKlsBARkSiFhYiIRCksREQkSmEhIiJRCgsREYlSWIiISJTCQkREohQWIiISpbAQEZEo\nhYWIiEQpLEREJGpmrIOZNQB3AwYMAFcBfcB94fFWd18V+l4BXAkcANa6+6Nm1gQ8CMwDKsBl7r7b\nzM4Abg99N7n7mjDGjcAFof1ad98yebsrIiLjkeXI4n1Azd2XADcAnwNuA1a7+3KgwcwuNLP5wDXA\nYuA84GYzmwVcDbzo7suAB8IYAOuAi919KbDIzBaY2anAMndfBFwC3DVpeyoiIuMWDQt3/3uSowWA\nNwJ7gYXu3hHaHgNWAKcDm939oLtXgO3AAmAJ8Hiq7zlmVgYa3X1HaN8QxlgCbAyv+zIww8yOH+tO\n1Wo1uro6qVT2D/lTrVagNtYRRUSObdHTUADuPmBmXwU+CPwuyRv7oCrQCpSB/an2TqCtrr2aaqvU\njfFmoAfYPcwY6baonu5O/F9209fw70O27dn1S+a0tDJnbnksQ4qIHNMyhQWAu3/MzP4nsAVoTm0q\nA/tI3vxb69r3hvZyXd/qCH37U33T/UdVntt02OMG+mn7lTLz57cP6Vuin4aGWUOeM/i8E04o09Y2\n8SBpby9eGBWxJihmXaopG9WUXVHryirLBPd/Ad7g7jcDvcAh4HkzW+7uTwHnA0+QhMhaM2skCZOT\nga3AM8BK4Pnwd4e7V82sz8xOAnYA5wI3hbFvMbNbgROBkrvvidVY7ew97HF3Vx+9PQeHtAN0dfXT\n0HCI2c1Dt3V39bFrV5X+/oktEmtvL7NzZ3VCY0y2ItYExaxLNWWjmrIrYl1jDa8sRxYPA/eZ2VOh\n/38HfgLcEyawtwEPu3vNzO4ANgMlkgnwfjNbB6w3sw6SVVSXhnGvAh4imTfZOLjqKfR7Noyxakx7\nIyIiR0Q0LNy9B7homE1nDdP3XuDeYZ7/4WH6Pkeycqq+fQ2wJlaXiIhMHV2UJyIiUZknuI8FtVot\nWVo7jHK5lVKpNMUViYgUg8Iipae7i6de2MNxrzt+SPuKRW+ltbUtp8pERPKlsKjT1DyHOS1H9xI3\nEZHJpjkLERGJUliIiEiUwkJERKIUFiIiEqWwEBGRKK2GymC06y9A12CIyPSnsMhgpOsvBrfpGgwR\nme4UFhnp+gsROZZpzkJERKIUFiIiEqXTUBM03OR3Y+MAlUpVE98iMm0oLCZouMnvuS172Llzjya+\nRWTaUFhMgvrJ75a5TXR29eVYkYjI5NKchYiIRCksREQkSmEhIiJRCgsREYlSWIiISJTCQkREohQW\nIiISNep1FmY2E/gK8CagEVgL/Bi4DxgAtrr7qtD3CuBK4ACw1t0fNbMm4EFgHlABLnP33WZ2BnB7\n6LvJ3deEMW4ELgjt17r7lkndWxERGZfYkcVHgF3uvgw4D7gTuA1Y7e7LgQYzu9DM5gPXAItDv5vN\nbBZwNfBieP4DwA1h3HXAxe6+FFhkZgvM7FRgmbsvAi4B7prUPRURkXGLhcXXee0NfgZwEFjo7h2h\n7TFgBXA6sNndD7p7BdgOLACWAI+n+p5jZmWg0d13hPYNYYwlwEYAd38ZmGFmQz9AQkREptyoYeHu\n3e7eFd7gvwF8BkjfGa8KtAJlYH+qvRNoq2uvptoqdWPU902PISIiOYveG8rMTgT+DrjT3f/azD6f\n2lwG9pG8+bfWte8N7eW6vtUR+van+qb7R5XnNh32uIF+mppnDmkH6OlqpKFh1pi2jec5c1tmc8IJ\nZdraivOBSe3txaklrYh1qaZsVFN2Ra0rq9gE93yS00Sr3P3J0PwDM1vm7t8FzgeeALYAa82sEWgG\nTga2As8AK4Hnw98d7l41sz4zOwnYAZwL3AQcAm4xs1uBE4GSu+/JshPVzt7DHnd39dHbc3BIO0BX\nVz8NDYeY3Zx921ifUw43Ety1q0p/fzEWnLW3l9m5s5p3GUMUsS7VlI1qyq6IdY01vGJHFtcDxwE3\nhJVKNeCPgC+FCextwMPuXjOzO4DNJKepVrt7v5mtA9abWQfQB1waxr0KeIjkNNjGwVVPod+zYYxV\nY9oTERE5YkYNC3f/BPCJYTadNUzfe4F769p6gA8P0/c5kpVT9e1rgDWjViwiIlOuGOdIRESk0BQW\nIiISpbAQEZEohYWIiEQpLEREJEphISIiUQoLERGJUliIiEiUwkJERKIUFiIiEqWwEBGRKIWFiIhE\nRT/PQsanVqtRrVZG3F4ut1IqlUbcLiJSJAqLI6Snu4unXtjDca8b+smwPd1drFj0Vlpb9UGAInJ0\nUFgcQU3Nc5jTcnR/OpaICGjOQkREMlBYiIhIlMJCRESiNGeRg9FWSmmVlIgUkcIiByOtlNIqKREp\nKoVFTrRSSkSOJpqzEBGRKIWFiIhEKSxERCQq05yFmS0C/tzdzzaztwD3AQPAVndfFfpcAVwJHADW\nuvujZtYEPAjMAyrAZe6+28zOAG4PfTe5+5owxo3ABaH9WnffMnm7KiIi4xU9sjCzTwF3A7ND023A\nandfDjSY2YVmNh+4BlgMnAfcbGazgKuBF919GfAAcEMYYx1wsbsvBRaZ2QIzOxVY5u6LgEuAuyZt\nL0VEZEKynIZ6Cfhg6vFp7t4Rvn4MWAGcDmx294PuXgG2AwuAJcDjqb7nmFkZaHT3HaF9QxhjCbAR\nwN1fBmaY2dC78ImIyJSLhoW7PwIcTDWlrxirAq1AGdifau8E2uraq6m2St0Y9X3TY4iISM7Gc53F\nQOrrMrCP5M2/ta59b2gv1/WtjtC3P9U33T+qPLfpsMcN9NPUPHNIO0BPVyMNDbPGtG08z2lpGftz\nSrU+Zs0aoLFxYMhzarVa0meYq7tbW7Nd9d3eXszrOopYl2rKRjVlV9S6shpPWLxgZsvc/bvA+cAT\nwBZgrZk1As3AycBW4BlgJfB8+LvD3atm1mdmJwE7gHOBm4BDwC1mditwIlBy9z1ZCqp29h72uLur\nj96eg0PaAbq6+mloOMTs5uzbxvqc8tymcb3Orp17eOT//fuwn4GxZ9cvaWiYOe6rvtvby+zcWR21\nTx6KWJdqykY1ZVfEusYaXuMJi+uAu8ME9jbgYXevmdkdwGaS01Sr3b3fzNYB682sA+gDLg1jXAU8\nRHIabOPgqqfQ79kwxqpx1HbUG+nK7u6uThoaZuiqbxHJRaawcPefA2eGr7cDZw3T517g3rq2HuDD\nw/R9jmTlVH37GmBNlppERGTq6KI8ERGJUliIiEiU7jp7lBvtszFAn48hIpNDYXGUG+mzMQa36fMx\nRGQyKCymAX02hogcaZqzEBGRKIWFiIhEKSxERCRKYSEiIlGa4J7G0stqGxsHqFReuzfNeJbUjrZM\nV0t0RaY3hcU0ll5WO7dlD51dfa+2j2dJbbVaYdP3X6J5TsuQ19ESXZHpTWExzQ0uq22Z28QAQ++A\nO1bNc1q0TFfkGKQ5CxERidKRhUyYbjkiMv0pLGTCRrvlSHdXJ4t/cz7lcuuQbcO1iUgxKSyOQaMd\nCYz28a3VagVqw4852oc2PfXCv434CX/z5ikwRI4GCotj0GhHAiN9fOvgtjktrcyZO7YJ7uGCZDCw\n9u/ff9iS3kE6dSVSLAqLY9R4Pr61u6tz0l5/MLD+ZefBV5f0prcNtxRXcyMi+VFYSG6amufQMrd1\nyJLekUKhWq3wvX9+heaWliHbdK2HyJGlsJDCGek02aunwXSdh8iUU1hIIQ13mmwyT4ONplarUans\nH3G7TnfJsUhhIdPCZN63qlIZ/rYmoNNdcuxSWMi0MNKpq9He3EcKmFmzBmhuzve2JvW1TcaNIEUm\nQmEh08ZoS3SHM9KEeW/3PijNHnaJ8EjjjXZ9Coz9zb3+po2TcSNIkYkoXFiYWQn438ACoBf4fXf/\n13yrkqNV7JqS4SbMS/TT03NoTOONdn3KaFexjxQy1WrlsKOb9I0gdat4yUPhwgL4ADDb3c80s0XA\nbaFNZFxGu6ZkssaLXZ8y3FXsMHLIjHYB5EiBNZ5QmuwjIpm+ihgWS4DHAdz9+2b2zpzrEZmwsV4E\nGQuykQJrPKE01iOiwYCpn0cZpICZnooYFq1Aet3iQTNrcPeB4Tr3VnfR13/4DYu6uzrp66nS3TX0\nB7m3p4uGhplj2jbW5zTQPyWvM5bnNNBPdzjnPZ7XOVJ1d3VWXq3rSL7OmJ7T3U1v76Ej/jpjGS/L\n92+wfbL09nTx+NPbaDvuVw5r37tnFw0NM3j96/8DXd1137veHs4+7aTcbhI5UoDlLY+6JntOq4hh\nUQHSvzKNGBQAF79/aUF/hXl73gWIHJPa2oo58V/UurIq4ocfPQ2sBDCzM4Af5VuOiIgU8cjiEWCF\nmT0dHn8sz2JERARKg5NVIiIiIyniaSgRESkYhYWIiEQpLEREJKqIE9yZFPG2IGY2E/gK8CagEVjr\n7t/Ks6ZBZjYPeB54j7v/tAD1fBp4P8nP4J3ufn/O9ZSAewADDgFX5PnvFO5e8OfufraZvQW4DxgA\ntrr7qoLU9Q7gDuAg0Ad81N135llTqu1S4A/d/cyprqe+JjNrB+4GjgNKJP9OP8+5JiP5ea8BP3X3\n3489/2g+snj1tiDA9SS3BcnbR4Bd7r4MOB+4M+d6gFdD7MtAd961AJjZcmBx+N6dDbw555IAfhto\ncfclwJ8Cn8urEDP7FMmby+zQdBuw2t2XAw1mdmFB6rodWOXu7yZZxfjpAtSEmZ0K/NeprmWUmj4P\nPOjuZwGfBf5jAWq6Cfiz8F7VZGYXxMY4msPisNuCAEW4LcjXgRvC1w3AgRxrSfsisA74Rd6FBOcC\nW83sm8A/hD956wXawhFGG9CfYy0vAR9MPT7N3TvC148B75n6koChdV3k7oPXQc0Eeqa+pMNrMrPj\ngT8D/iiHWgbV/zu9C3iDmW0CLgWeKEBNPcDx4ee9TIb3qqM5LIa9LUhexQC4e7e7d5lZGfgG8Jk8\n6wEws8uBV9x9E8khcBGcAJwGfAi4Gngo33IA2Aw0Az8B/pLk9Eou3P0RklM7g9LftypJmE25+rrc\n/ZcAZnYmsAr4izxrCv//7wE+CXSR08/7MN+/NwF73H0F8DI5HIENU9OXSH7G/xmYB3wnNsbRHBZj\nui3IVDGzE0l+c1jv7n+Tdz0kFzWuMLMngXcA94f5izztBja4+8EwL9BrZifkXNMfA0+7u5HMg91v\nZo051zQo/XNdBvblVUg9M7uIZO5wpbvvzrmchcBbSY6ivwacYmZFOD29Gxicu/wWyS9KeXsQWOLu\nvwE8QIbT+EdzWBTutiBmNh/YAPyxu6/Pux4Ad1/u7meHyb8fkkyuvZJzWZuB8wDM7PXAHJL/UHma\ny2tHqvtITqvMyK+cw7xgZsvC1+cDHaN1nipm9hGSI4qz8piwrVNy9+fd/bfCHMrFwI/d/ZM51wXJ\n92tl+HoZyW/zeZtDcpQKyenp42JPOGpXQ1HM24JcT/KPfoOZ3Uiy0uB8d+8b/WlTphCX67v7o2a2\n1MyeIzlV8AfunndtXwC+amYdJP8vrnf3PM7BD+c64G4zmwVsAx7OuZ7BUz7/C/g58IiZ1YCn3P1P\nciop75+f0VwH3GNmV5P8QnJpzvUAXAH8rZn1kMzPXRF7gm73ISIiUUfzaSgREZkiCgsREYlSWIiI\nSJTCQkREohQWIiISpbAQEZEohYWIiEQpLEREJOr/A2M4aqqt5n+5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e6564828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e1da6e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OLO4Bbo+Ix6r+nwL+BritWsBeB9yTmc2IuBlYTesy1bLM3BkRK4A7ImIVrbuoLqrGXULr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e6500748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ed0f4ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eddf2908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eb9af978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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fQnt/ofLKy7+msfGYPsOmv21HOrJx2JiNL2MxOKYCr9b83CWpMSIO99X5UOVl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\nuTg4zMwsFweHmZnl8v8BCSrxTCLUTnYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e4863630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IHw8SEb8aS+/+yBEzM8tS5qUqMzNrAweHmZllcXCYmVkWB4eZmWVxcJiZWRYH\nh5mZZXFwmJlZFgeHmZll+f+XmFENwrWtkwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eb739630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3nca2mZnZKCi6x/EW4NyImA/8KfBJYDWwIiIWAeMkXStpBnArMA+4GrhH0jnALcCzEbEQ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\nF4eZmSVxcZiZWRIXh5mZJXFxmJlZkv8HV8pUsKDZZ7wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eb915470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e8a1c978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e1c15908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eebbeb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ZwDXAEeAJYCVwOH3ti4iypGFJ84HjwDJg3XiNlAfPjV6A80OcOFFuYDHaq6enVIg+x+L+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\nWFNlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5eb206ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Dah3jB+nsLNUYfeE0+vlrcU/FuKfimrEv91R/RULhvcBrgaUR8WKyF/MnImKWpCeB+cBW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\n6Zj90Yh4UYN7Avg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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ebab1160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5ec401be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Cj7V2OE23FTgX+AHwl2RTEG1P0uNkUyknVP/dLJEFYNuqrU/SzwAi4h3AcuDP\nx9u/HU6uDX0dRjuKiF8DtgBrJf11q8fTRDeRfUDx68BbgS+l9YVOsRfYJOl4mms/HBGvbvWgmuhj\nwNOSgmxN70sR0d3iMZ0O1eeTArC/VQM5XSLiA2Rrs0sk7R2vbzuEQkd/HUZEzAQ2AR+TtLbV42km\nSYskXSbpMuA7ZAtcL7R6XE20FbgWICJeA5xHFhSdYhovX6XvJ5t6mNy64Zw2z0XEwvR4MdA/Xud2\nExEfJLtCeKekH0/U/4x/9xGd/3UYdwCvAlZExCeACrBY0pHWDqvpOu6j85LWR8SCiPgW2RTEhyV1\nUp2fBb4YEf1k54o7JI07H92mbgceiIhXALuAdS0eT9Okqfb/CPwYeDwiKsCTkj411j7+mgszM8u1\nw/SRmZn9kjgUzMws51AwM7OcQ8HMzHIOBTMzyzkUzMws51AwM7OcQ8HMzHL/Hy7LLfeexGyxAAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e498be48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5efddef60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e188cda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e485b240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe5e192f400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# y_preds=[]\n",
    "for i in range(1,len(model.layers)):\n",
    "    model_tmp = keras.models.Sequential(model.layers[:i])\n",
    "#     model.compile(loss='mse',optimizer='sgd')\n",
    "    y_pred = model_tmp.predict(X_test[:1])\n",
    "#     y_preds.append(y_pred)    \n",
    "    plt.title(model_tmp.layers[-1].name)\n",
    "    sns.distplot(y_pred.flatten(),kde=False)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (with sys packages)",
   "language": "python",
   "name": "py3syspck"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.2"
  },
  "toc": {
   "toc_cell": false,
   "toc_number_sections": true,
   "toc_threshold": 6,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}