{ "cells": [ { "cell_type": "code", "execution_count": 254, "metadata": {}, "outputs": [], "source": [ "## Projet Maman 2\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "donnees = pd.read_csv('inria_41016_session02_grade_report_2019-06-03-0808.csv')" ] }, { "cell_type": "code", "execution_count": 255, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Type Num Id Label\n", "0 Quiz 283 1 Module 1\n", "1 Quiz 268 2 Module 1\n", "2 Quiz 285 3 Module 1\n", "3 Quiz 259 4 Module 1\n", "4 Quiz 234 5 Module 1\n", "5 Quiz 190 6 Module 2\n", "6 Quiz 188 7 Module 2\n", "7 Quiz 181 8 Module 2\n", "8 Quiz 165 9 Module 2\n", "9 Quiz 149 10 Module 2\n", "10 Quiz 136 11 Module 2\n", "11 Quiz 129 12 Module 3\n", "12 Quiz 127 13 Module 3\n", "13 Quiz 93 14 Module 4\n", "14 Quiz 80 15 Module 4\n", "15 Quiz 74 16 Module 4\n", "16 QuizP 126 1 Jupiter\n", "17 QuizP 95 2 R\n", "18 QuizP 77 3 OrgMode\n", "19 QuizP 77 4 Jupiter\n", "20 QuizP 53 5 R\n", "21 QuizP 43 6 OrgMode\n", "22 QuizP 70 7 Jupiter\n", "23 QuizP 45 8 R\n", "24 QuizP 35 9 OrgMode\n", "25 QuizP 69 10 Jupiter\n", "26 QuizP 43 11 R\n", "27 QuizP 36 12 OrgMode\n", "28 Exercices 195 1 Module 1\n", "29 Exercices 117 2 Module 2\n", "30 Exercices 85 3 Module 3\n", "31 ExoEvalPair 11 4 ExoEval\n" ] } ], "source": [ "## Tableau\n", "\n", "Type_init= list(donnees.columns[3:19])+list(donnees.columns[20:32])+list(donnees.columns[34:37])+[\"ExoEvalPair\"]\n", "Type=[i.split()[0] for i in Type_init]\n", "Id=[int(i.split()[1]) for i in Type_init[:-1]]+[4]\n", "Num=[(sum(donnees.loc[:,type]>0)) for type in Type_init]\n", "Label=[\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 3\",\"Module 3\",\"Module 4\",\"Module 4\",\"Module 4\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Module 1\",\"Module 2\",\"Module 3\",\"ExoEvalPair\"]\n", "tableau=pd.DataFrame({'Type':Type,\"Id\":Id,\"Num\":Num,\"Label\":Label})\n", "col=[\"Type\",\"Num\",\"Id\",\"Label\"]\n", "tableau = tableau.loc[:, col]\n", "print(tableau)" ] }, { "cell_type": "code", "execution_count": 270, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABcwAAAIZCAYAAACbGXwFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzs3Xl8VNX5x/HPw44QUCCKghCr4ALEAAr6EwVRVCRaXCuilqIFLAWxrhVlK7hSl1YtxWrRliIKKgragrYxoFiFQhFQxCUolSIEoWEJhvD8/riTOJlsk2SSyfJ9v155Ze65957z3EngZJ577jnm7oiIiIiIiIiIiIiI1HX14h2AiIiIiIiIiIiIiEh1oIS5iIiIiIiIiIiIiAhKmIuIiIiIiIiIiIiIAEqYi4iIiIiIiIiIiIgASpiLiIiIiIiIiIiIiABKmIuIiIiIiIiIiIiIANAg3gGIiIiISPVlZo2Bk4HjgCOAZsB+YCewA1gHfOLuB+MWZA1mZhlAx9Dm2+7erxLaGAb8MazobHdPi3U7IiIiIiK1gRLmIiIiIlKAmTUCrgKGAv2ARqWcstfM3gNeAF5y922VG6GIiIiIiEjl0JQsIiIiIpLPzIYAnwHPAudRerIc4BCgPzAD+I+ZzTCz9pUXpYiIiIiISOXQCHMRERERwcyaAE8DVxdzyOfAZmA7kEMwPUtboDMFB2E0BEYCw4AmlRSuiIiIiIhIpVDCXERERKSOC03BsohglHi4L4CHgEXu/mUx57YiGIl+OXAJ3yfPG1dOtCIiIiIiIpXH3D3eMYiIiIhIHJnZb4GfhxU5cDfwkLvnlKGeE4F7gCEA7m6xjLM2qopFP0VEREREJHqaw1xERESkDjOzSymYLD8IDHX3e8uSLAdw94/c/WrgUmBHDMMUERERERGpEkqYi4iIiNRRZlYfmB5R/LC7z6lIve7+MpBSkTpERERERETiQXOYi4iIiNRdlwHHhG1vIphSpcLc/avynmtmzYE+QDvgcGAv8Ia7f1LCOT8ATiKY3qQFcIBglPsXwHvuvre88RTTXmvgDKA9kABsAVa5+4cxbqcL0A04muCatgDp7v51LNspJYYE4GygA3AI8DXwibu/X1UxxFLo9yvvZ5cIZANbgQ/c/dMK1NsC6EGwEO6hQCOC393tBL+HH7r7zopFLyIiIiKVTQlzERERkbprTMT2U+6eXdmNmtkw4I9hRWe7e5qZtQMeIFg89JDI04D8hLmZNSRYbPRK4FzgqBKazDGz14Bp7v6vCsZ4HDAVGEwRC5ua2XrgTnd/LZp2Smj/QmAScGox+/8G/MLd10dR1zCKuJYozmtF8PMYCjQtYv9G4BFghru7maUBfUO7N7l7UjH1JhEkkPNMdvdJpcUTOncY5biW0LlnENwQOpsgmV3UMRuAe4E/eZSLPZlZMsHPalBx9Ya4ma0DXgGmu/uuaOoXERERkaqlKVlERERE6iAzawacFlE8Kw6hAGBm5wL/JkjORibLi3IPsBC4jpKT5QANCeZVf9/MbqlAjOcAq4AfUUSyPOQk4FUze9LMyrXoqZndT3BtRSbLQ84H3jOzs8rTRhQxnAysB26giGR5SCfgSeBlMyspURxXZtbYzP4ELCN430qK9XjgWeAtM2sZRd2jgH8R3OQp7T0woCvBgrrHlHKsiIiIiMSJRpiLiIiI1E2nUfBvwc/d/T9xiqUTwVzqLULbmcAKgilVEoHuRZwTOfAjC1gLfAPsJki6H0eQwK4fOqY+MN3M9rj7jDLGeALwINA8LMYPgJ0ECfvTKJgwvRH4DhhXlkbM7G7gjtDmQYJk7KbQ6xMJEq55EoAXzexEd4/ZIqtm1hlYQvDeh/uM4D3+juC9zfu5/BB4PFbtx1JoOpnXCab4CbcLWEnw+9KE4Od7Qtj+s4F/mNkZ7r6vmLoHAL+LKM4F1gAZwB6C38NEoAvQqiLXIiIiIiJVQwlzERERkbopcnT5yrhEEXiYIBG9hSDBPN/dc/N2hkYvty7ivC+AZ4BXCeaHLjSFhpm1DdV5C9//7fuImb3u7l+WIcb7CBLUWcCtwB/dPSesnVbANGBU2Dk3mdkb7v63KNvoBuSNGP8DMMHdt0Rcz2nACwRzmkMwx/sdfJ9kr5DQqPg/UjBZ/hkwwt3/HnFsZ2AGQXL5pwQ3D6qbGRRMln9G8F697O4Hww80s+4EI+bz/m10J/jdvLGYuu+N2H4YuNfdM4s62MxOILi5MKIsFyAiIiIiVUtTsoiIiIjUTUdGbG+MSxSBvGT5Ge7+QniyHMDdv4tMHBMkQo9z96nuvqa4+abd/b/ufidwVVhxE2B0GWM8lGBxyEHuPjM8WR5qZ4e73whMjjjvCTOL9m/uVgTTdtzu7j8t4ppx9/eAgUB4+9eVoY3SXAf8X9j25wQ/l79HHhhahPU8ghHcELxH1YaZXQFcHVb0LtDd3edHJssB3H0V0A94K6x4pJmdVETdRwCnhBU97e63FJcsD9X/sbs/QPBERalzz4uIiIhIfChhLiIiIlI3RU4PEe8FCH/u7l+UfljA3TcXlfQs4fj5wEthRT8qS3Ah97v70lKOmUwwVUueY4ELytDG39z9oZIOcPd1wLyworYEc2/Hws8jtq93960lxHIA+DHVc3T5L8Ne7wQGu3tWSSe4+36CefT3hooMuKmIQztEbL8cbVDuftDdv4v2eBERERGpWkqYi4iIiNRNh0VsR50wN7M/mJlH8ZUWZZWfU4aEYwUsCHvdMTRKOFr7CKbcKFFopPvUiOKhZWjnwSiPez1i++QytFGk0BQr4aOml7l7Wmnnuft2Cs/lHVdmdjoF577/jbtvi+bc0A2CuWFFg6I4LXK+dxERERGpoZQwFxERERGAIqc0qSILi5tSpazMrJ6ZtTSz9maWFP5FsCBjuBMK11CsN0obnRx+LPC/sO3TozxvL5Ae5bEfR2zHImEbGecLZTh3bumHVKn+Edvzy3h++M+hnZl1jNj/KcFCrHnuNLOi5tkXERERkRpGi36KiIiI1E3fRmy3jEsUgdXlPdHMGhOMAL6MYERxZ6B+lKdHjrIvyQelHxJw9xwz+zdwZqjoGDM7zN0j3/NIn4amOIlG5BMBLaKNrwQ9IrajvmZgLcEo/KYxiCMWzgh7nQvsDd00iVbkDZwfAJvyd7p/a2Z/I5hPHoIpcT42sz8QTJfzr1jdBBIRERGRqqWEuYiIiEjdtCNiuywJ8zsoPO0IQHugtDm+ixLVVBmRzGwQ8DiQVJ7zKVuS+bMy1v0p3yfMAQ6n8E2KSGWZRz4nYrthGc4tTuQUNVFfs7vnmlkGcGIM4oiF9mGv61PxRW0j5/wHGEcwKj9vsdM2wJ2hrx1m9g6wDEgDVkYuZisiIiIi1ZMS5iIiIiJ1038jtjtHe6K7ZwKZkeVmVt5Ydpf1BDMbDvyBYFHG8irL9IT/K/2QAiKT34cWeVRBUS9iWkkiY6zoNcdTUQnuimgeWeDun4TmSn8W6FVE+xeFvgC2mtlfgF+7+39iHJuIiIiIxJDmMBcRERGpm96L2D6lyKOqITPrRLDIZHiyfB1wF3AOcBzB6PHG7m55X8DZFWi2rNNrVCSRX1NVp2uOxYj7cEVem7t/7O69gfOAPwFbijn/COBmYKOZ3RDj2EREREQkhjTCXERERKRuWg4c4Pu/B48xs3Y1ZPTrHUCjsO3pwO1RzBmdUIE2yzrHe+R0Lzsr0HZViYyxBWWbLicW86iXJtoBPzsIpsEB2OTuSZUTTsDdlwBLIP+GzhnAWcD5wFFhhzYFnjKzPe4+pzJjEhEREZHy0QhzERERkTrI3fdQeJT5T+IRSzkMCnv9CXBHlAsstq1Am8eW8fjjIra/qUDbVWVrxHbU12xm9Yl+LvnIhU3LMognmqltoOC1HB1aHLZKuPtGd5/l7sMJ5lLvD7wTcdj00HsmIiIiItWMEuYiIiIidddvI7Z/amZN4hJJlMzsEAomvpe4e7Rzf59WgaZPjfZAM2sInBxW9IW7l7bgZ3Xwr4jtqK8Z6EowejoakXOjR5sEBzgpyuPCbwbVo2LT8ZSbB/4BDAA+DNt1FNAzHjGJiIiISMmUMBcRERGpu+YDX4RtdwDujVMs0SrXwpShRPvgCrQ70MyindJlIAWnJ1legXarUmScV5bh3B+V4dgsIDts+4RoTjKzesC5UbbxZsT2sCjPqxTuvg94IaI4KQ6hiIiIiEgplDAXERERqaPcPRe4LaL4JjO7Jh7xRClynu3OUZ53K9CqAu02BX5R2kFmZsDdEcWzK9BulXH3T4AVYUV9zKxfaeeZWRvgxjK04xQcbX1GlDcjhgAdo2zmHwTT9eS50sz6RHluZYm8ufNdXKIQERERkRIpYS4iIiJSh7n7fODxsKJ6wHNmdreZNSrmtOIcFrvIiubue4HPw4pSQ4ssFsvMUoF7YtD8nVEkXSdScCqTz4G/xqDtqvJExPbTZnZEcQebWQNgFmWbVgWChHaeJhS+cRPZzkkUnkKoWKGbQVPCqwBeMrPuZQnSzI4r6qaBmZ1mZueVoZ56wFURxRvKEouIiIiIVA0lzEVERETkFgomMA34FbDBzH5mZh1KOtnMTjWzRym8sGFlmRf2ujGwuKhEtpm1NLNfAS8TLCy5vQJt7iRI7L5uZj8NzVMe3tZhZvYkQcI83OgyzLFeHTxHwalZfgAsM7NCc4CHblT8je8XYY0c/V+SWUD4Qq13m9ltoQR8eBsNzex6YBnBDZmo23D32cBfwooSgeVmdq+ZtSvuPDM73MyGmdlCgqT2BUUcdgLwNzNba2Z3mdmJoacLiqrvB8BLwOlhxf9y94+ivRYRERERqTplWZFeRERERGohd//OzC4E/kjBUbBJBCOOnzCzz4EvgUyC+aebEyy+eSIF5+vOkwU8X0khTweuB1qHxbnUzD4G1gK5QDugN5CX2N5OMC3LrHK2eRfwIJAAzATuM7P3CRK4RxEkQyNH5D/m7jVpdDnuftDMhhHc/GgTKj4O+LuZfUYwlUoOcCzQI+zUp0PH9Y2ynY/M7A/AT0NFRvD+3mZm7xH8/iQS/Azzfr8+BZ4EHi7DJd0AHAGcE9puDPwS+KWZfQJs5PubIYcRJMKPKkP9XYBpoa9dZvYhsA3YQ/BvpDOFFyr9DhhVhjZEREREpAopYS4iIiIiuHs2MMTMFgEPUDhp+IPQV2n2AX8GJrj7f2MbZcDdt5nZJcBCCibrT6DoBSS3EoyCjnbRzqJ8BFxGMFK4GUGyfmAJx88Abq5Ae3Hj7p+Y2QCCqWTCp2M5NvQVaSHwM2BxGZv6BXA8cFZYWSJwURHH5o307leWBtx9n5mdT/A7PQ6oH7a7M9HNgR/tqPaWQGlT9uwArnT3D6KsU0RERESqmKZkEREREZF87v5ngsT4T4A3CUYTlyYL+DvBqNkj3X1EZSXL87j7UuAUgmStF3PYDoIR8t3cfWUM2lwM9ATmU/z78hFwsbvfGFrcskZy99UEI6OfJrgJUpTPgJuAH7p7mRewdPfdwPkE0//sLuawTOAh4BR3zyhrG6F2ct39VoLreYbg96LEU4B/EyTZu7n7/UUcMx+4mmDKl6+jCGMLwXV0cve3oo1dRERERKqe1eC/40VERESkkplZUyCFYGTxEUBTYD/wLUHicQPwUTzn6Tazo4AzgfYET1D+l2D6mHfKk8gN1TmMYIqaPGe7e1rY/jbAGaE2E0JtrnL3f5enverMzBKA/kAH4BCCBPEnwPvhNwXMLI3vp2TZ5O5JZWijMcFI804EC4huAzKAdHffX+GLKNhWPYLf6RMJnhRoAewl+J3eCKxz92/LWGcHgqcbkgjib0RwE2ArwTQ262vYXPYiIiIidZYS5iIiIiIiEUpLmEthFUmYi4iIiIhUF5qSRUREREREREREREQEJcxFRERERERERERERAAlzEVEREREREREREREACXMRUREREREREREREQAJcxFRERERERERERERAAlzEVEREREREREREREACXMRUREREREREREREQAMHePdwwiIiIiIiIiIiIiInGnEeYiIiIiIiIiIiIiIihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuIiIiIiIiIiIiIgIoYS4iIiIiIiIiIiIiAihhLiIiIiIiIiIiIiICKGEuInFmZkPNbHG84xAREZHimdk6M+sX7zhERESkIPXRIrGnhLlIHWdmGWa2z8x2h309XlXtu/tsdz+vqtoTERGpq8xsmJl9aGZ7zey/ZvakmbWM5lx37+LuaZUcooiISJ1U2X20mfUzs4Ohz/tZZrbBzH4Sk+BFaiElzEUE4CJ3bx729fNYVWxmDWJVl4iIiJSPmd0CPADcBrQETgOSgMVm1jCOoYmIiNRpVdhHf+3uzYEWwB3AU2Z2UgzrF6k1lDAXkSKZ2e/MbF7Y9gNm9paZWWg71cxWm9lOM3vXzJLDjs0wszvMbA2wx8wamNnRZvaSmW0zs8y8UeyhO+nLws7tYmZLzGyHmW01s7tC5fXM7E4z+yx0/gtm1iq0r4mZ/TlUvtPMPjCzI6rorRIREanWzKwFMBkY4+5/dfccd88ArgSOAa42s1lmNjXsnH5mtjlsO8PMzg293hn2VNoeM3MzS6rKaxIREakN4tFHe+AV4FtACXORIihhLiLFuQVIDiW0zwSuB37s7m5mPYBngJFAa+D3wKtm1jjs/CHAIOBQwIGFwCaCO+XtgOcjGzSzBOBN4K/AUcBxwFuh3WOBwUDf0L5vgSdC+35McCf+6FA8o4B9FX4HREREaof/A5oAL4UXuvtu4A2gTFOjufuheU+lAY8BS4H/xChWERGRuqTK++jQYLRLCD6rf1iB2EVqLSXMRQTgldCd6Lyvn7r7XuAa4GHgzwR3vPPuYv8U+L27/9Pdc939WWA/waNjeX7j7l+5+z6gF0GS+zZ33+Pu2e6+jMJSgf+6+69Dx2S5+z9D+0YC4919s7vvByYBl4emfMkhSJQfF4pnpbv/L5ZvkIiISA3WBtju7geK2LcFSCxPpWb2I+Bq4DJ3z6lAfCIiInVVVfbRR5nZTmA7MBG41t03lKd+kdpOcwuLCMBgd38zstDd3zezz4HDgRfCdnUEfmxmY8LKGhEkxfN8Ffb6aGBTMX8EEHHcZ8Xs6wi8bGYHw8pygSOAP4XOfd7MDiVI8I/Xh3cREREg+GDcxswaFNEXHwlsK2uFZtYdeBw4z93LfL6IiIgAVdtHf+3u7csfqkjdoRHmIlIsMxsNNAa+Bm4P2/UVMC30uFfe1yHuPifsGI84vkMUC4B+BRxbwr6BEW02cff/hOZ5m+zuJxE80pYKXFeGSxUREanNlhM8CXZpeKGZNQMGAm8De4BDwna3La4yM0sEXgZ+7u6rYh6tiIhI3aE+WqQaUsJcRIpkZp2BqQTTslwL3G5mKaHdTwGjzKy3BZqZ2aDQHORFeZ/gcbL7Q8c2MbMzijhuIdDWzMaZWWMzSzCz3qF9M4BpZtYxFF+imf0w9PpsM+tmZvWB/xFM0ZJb8XdBRESk5nP3XQQLiv3WzC4ws4ahBcBeJBjZNhtYDVxoZq3MrC0wrqi6Qje/5wOz3X1uVcQvIiJSW6mPFqmelDAXEYDXwlbS3m1mLxNMa/KAu//b3TcCdwF/MrPG7r6CYB7zxwkW3/wUGFZc5e6eC1xEsIjnl8Bm4EdFHJcFDAgd+19gI3B2aPdjwKvAYjPLAt4D8pLpbYF5BMnyjwjuwv+5nO+FiIhIrePuDxL05dOBLOALgtFq57r7HoLpzf4NZACLgeI+aLcHzgTGRfzt0KGSL0FERKRWUh8tUv2Yu5d+lIiIiIiI1BpmNpxgRNsZ7v5lvOMRERGRgPpokfhTwlxEREREpA4ys2uBHHd/Pt6xiIiIyPfUR4vElxLmIiIiIiIiIiIiIiJoDnMREREREREREREREUAJcxERERERERERERERABrEO4CarE2bNp6UlBSTuvbs2UOzZs1iUpdUf/p51z36mUt5rFy5cru7J8Y7jtrg0EMP9eOOO67S6q+Kf+OV3YauoXq0oWuoHm3U9Pqrog1dQ0Hqs2OjsvvraMT77/Z4t68Yqkf7iqF6tK8Yqk8MsWo/6v7a3fVVzq+ePXt6rPzjH/+IWV1S/ennXffoZy7lAazwatDf1Yavzp07l/XtL5Oq+Dde2W3oGqpHG7qG6tFGTa+/KtrQNRSkPrtm9NfRiPff7fFuXzFUj/YVQ/VoXzFUnxhi1X60/bWmZBERERERERERERERQXOYi4iIiIiIiIiIiIgASpiLiIiIiIiIiIiIiABa9FNERERERKROyMnJYfPmzWRnZ1e4rpYtW/LRRx/FIKr4tVGe+ps0aUL79u1p2LBhJUUlIiJ1XWR/XRV9bmniHUNZ269of62EuYiIiIiISB2wefNmEhISSEpKwswqVFdWVhYJCQkxiiw+bZS1fncnMzOTzZs3c8wxx1RaXCIiUrdF9tdV0eeWJt4xlKX9WPTXmpJFRERERESkDsjOzqZ169YVTpbXVWZG69atYzJCX0REpDjqrysmFv21EuYiIiIiIiJ1hD58V4zePxERqQrqbyqmou+fEuYiIiIiIiIiIiIiIihhLiIiIiIiIlXEzLj22mvztw8cOEBiYiKpqallqicpKYnt27eXeMywYcOYN29e1HWmp6fTo0cPGjRoUKbzREREapvmzZuX67wZM2bw3HPPATBr1iy+/vrrWIZVZZQwFxERERERkcJmz4akJKhXL/g+e3aFq2zWrBlr165l3759ACxZsoR27dpVuN5Y6NChA7NmzeLqq6+OdygiIiLRq4T+urxGjRrFddddB5QvYX7gwIHKCKvMlDAXERGRuDGzJmb2vpn928zWmdnkUHkrM1tiZhtD3w8LO+eXZvapmW0ws/PjF72ISC02ezaMGAGbNoF78H3EiJh8CB84cCCLFi0CYM6cOQwZMiR/344dOxg8eDDJycn079+fNWvWAJCZmcl5551H9+7dGTlyJO4OQEZGBl27ds0/f/r06UyaNKlQmytXrqRv37707NmT888/ny1bthQ6JikpieTkZOrV08dkERGpISqxv05LSyvwBNjPf/5zZs2aBQR95h133EGvXr3o1asXn376KQCTJk1i+vTpzJs3jxUrVjB06FBSUlLYt29fsX1xv379uOuuu+jbty+PPfZYheOOhQbxDkBERETqtP1Af3ffbWYNgWVm9gZwKfCWu99vZncCdwJ3mNlJwFVAF+Ao4E0z6+zuufG6ABGRGmncOFi9uvj9770H+/cXLNu7F66/Hp56iqa5uVC/fsH9KSnw6KOlNn3VVVcxZcoUUlNTWbNmDcOHD2fp0qUATJw4ke7du/PKK6+wcOFCrrvuOlavXs3kyZPp06cPEyZMYNGiRcycOTPqS83JyWHMmDEsWLCAxMRE5s6dy/jx46vNh3IREZFijRtH05UrC/e5eUrpr4sUZX9dmhYtWvD+++/z3HPPMW7cOBYuXJi/7/LLL+fxxx9n+vTpnHLKKcX2xc888wwAO3fu5O23365wTLGihLmIiIjEjQdDBHeHNhuGvhz4IdAvVP4skAbcESp/3t33A1+Y2adAL2B51UUtIlIHRH74Lq28DJKTk8nIyGDOnDlceOGFBfYtW7aM+fPnA9C3b18yMzPZtWsX6enpvPTSSwAMGjSIww47rFC9xdmwYQNr165lwIABAOTm5nLkkUdW+DpERETirhL769LkPSE2ZMgQbr755hKPLa0v/tGPflR5gZaDEubxNns2jB9P3y+/hA4dYNo0GDo03lGJiIhUGTOrD6wEjgOecPd/mtkR7r4FwN23mNnhocPbAe+Fnb45VFZUvSOAEQCJiYmkpaXFPPbD33yTH/zhD/T95huyDz+cz2+4gW/OPTfm7QDs3r27Uq6hquqvijZ0DdWjDV1D/Osvro2WLVuSlZUVbPzqVyWe36xLF+p99VWh8oNHH82e114jNzeX+kWNdsurvwRZWVmcf/753HLLLbz++uvs2LGDAwcOkJWVRW5uLrt3785/7e7s3r2bgwcPsmfPnvz488qzs7PzzwXYtWtX/nZOTg779u1j9+7dnHDCCbz11lsF4sjNzf3+/QiTd15R+wCys7Mr/ecncaDP5iJSHT36KPuyskhISCh6f1JSMA1LpI4doYJ9VYMGDTh48GD+dnZ2doH9Zlbk66K4O126dGH58qLHOTVr1qwCkcaeEubxlDfP0N69GHw/zxCoYxYRkTojNJ1KipkdCrxsZl1LOLyov8S8mHpnAjMBjj/+eO/Xr19FQy1o9mx45JHgkUegydatnPTII5x04omV0o+npaUR82uowvqrog1dQ/VoQ9cQ//qLa+Ojjz4q/gN3pPvuy/+sku+QQ6h3330kJCSQVdKH91IkJCRw4403cvjhh3PaaaeRlpZGgwYNSEhIoF+/fixYsIB77rmH119/ncTERNq1a5dffvfdd/PGG2+wc+dOmjdvTrt27di+fTvfffcdzZs3Z8mSJVxwwQUkJCTQsGFDmjZtSo8ePdixYwdr167l9NNPJycnh08++YQOHToUeQ155xV3fU2aNKF79+7lunappvTZXERqqmnTiuyvmTatwlV37NiR9evXs3//fnbt2sVbb71Fnz598vfPnTuXO++8k7lz53L0y4izAAAgAElEQVT66acXOj/v7wWA448/nm3btrF8+fICfXGXLl0qHGdl0Gom8TR+fMFfaAi2x4+PTzwiIiJx5O47CaZeuQDYamZHAoS+fxM6bDNwdNhp7YGyLb0eK+rHRaQ2GzoUZs4MRqiZBd9nzoxZ8rB9+/bcdNNNhconTZrEihUrSE5OZuLEiTz77LNAMLd5eno6PXr0YPHixXTo0AEIktsTJkygd+/epKamcsIJJxSqs1GjRsybN4877riDk08+mZSUFN59991Cx33wwQe0b9+eF198kZEjR1bbD/FSCdSni0hNVQn99YEDB2jcuDFHH300V155JcnJydxwww2Fbhbv37+f3r1789hjj/HII48UqmfYsGGMGjWKlJQUcnNzo+qLqwuNMI+nL78sW7mIiEgtY2aJQI677zSzpsC5wAPAq8CPgftD3xeETnkV+IuZPUyw6Gcn4P0qDxzUj4tI7Td0aMxH1+7evbtQWb9+/fJHw7dq1YoFC4L/8sNHsbdu3ZrFixfnnxP+wXzs2LGMHTu2UL2zZs3Kf52SkkJ6enqB/ZFTrpx66qls3ry5bBcktYP6dBGpyWLcX69bt45jjz0WgAcffJAHH3ywyCfLRo8ezcSJEwuUTZo0Kf/1ZZddxmWXXZa/XVRfDFTLac40wjyeQqMioi4XERGpfY4E/mFma4APgCXuvpAgUT7AzDYCA0LbuPs64AVgPfBXYHRoSpeqp35cRESkdlCfLiICwIwZMxgyZAhTp06NdyhxpYR5PE2bFswrFK5hw5jMMyQiIlITuPsad+/u7snu3tXdp4TKM939HHfvFPq+I+ycae5+rLsf7+5vxC34ovrxRo3Uj4uIiNQ0RfXpMZoDWESkJhk1ahTr16/nvPPOK/G4jIwM2rRpU0VRVT0lzOMpbJ4hN4OmTYPysAn0RUREpJqK7McbNoTWreGqq+IdmYiIiJRFeJ8OwTzAjz6qBT9FROooJczjbehQyMjg7b//HTZsCEamFTH/noiIiFRD4f34X/4CW7bAnDnxjkpERETKKtSnr/z978G98CKgIiJSZyhhXp0cfTRMnAivvhp8iYiISM1x6aVw8skweTIcOBDvaERERKQcdnfuDKedBk8+CQcPxjscERGJAyXMq5tx46Br12CU+Z498Y5GREREolWvXpAs//RT+NOf4h2NiIiIlNfo0fDJJ/DWW/GORERE4kAJ8+qmYUP43e9g0yao4yvSioiI1DgXXww9e8KUKZCTE+9oRESqHTPj2muvzd8+cOAAiYmJpKamlqmepKQktm/fXuIxw4YNY968eVHX+fDDD3PSSSeRnJzMOeecw6ZNm8oUk9QiV1wBiYnwxBPxjkREJC7q169PSkoKXbt25aKLLmLnzp3xDqlK1dqEuZk9Y2bfmNnasLK5ZrY69JVhZqtD5Ulmti9s34z4RU6w6OewYTB9OqxfH9dQREREpAzMgmR5Rgb88Y/xjkZEpEJmz4akpOABmqSkYLuimjVrxtq1a9m3bx8AS5YsoV27dhWvOAa6d+/OihUrWLNmDZdffjm33357vEOSeGncGG64AV57Db78Mt7RiIiUqDL666ZNm7J69WrWrl1Lq1ateOqppypeaQ1SaxPmwCzggvACd/+Ru6e4ewowH3gpbPdnefvcfVQVxlm0Bx+EhITgUTD3eEcjIiIi0Ro4MJj7dOpU2L8/3tGIiJTL7NkwYkTw4Kt78H3EiNh8CB84cCCLFi0CYM6cOQwZMiR/344dOxg8eDDJycn079+fNWvWAJCZmcl5551H9+7dGTlyJB76jJSRkUHXrl3zz58+fTqTJk0q1ObKlSvp27cvPXv25Pzzz2fLli2Fjjn77LM55JBDADjttNPYvHlzxS9Waq5RobTAjPiOpxMRKUll9td5Tj/9dL7++uvYVVgDNIh3AJXF3dPNLKmofWZmwJVA/6qMqUwSE+H++2HkyOC3/Jpr4h2RiIiIRCNvlPl558Ef/hDc/BYRqWbGjYPVq4vf/957he/57d0L118PTz0FublNqV+/4P6UFHj00dLbvuqqq5gyZQqpqamsWbOG4cOHs3TpUgAmTpxI9+7deeWVV1i4cCHXXXcdq1evZvLkyfTp04cJEyawaNEiZs6cGfW15uTkMGbMGBYsWEBiYiJz585l/PjxPPbYY8We8/TTTzNw4MCo25BaqEMHuOiioC+fODEYdS4iUsXGjYOVKwv3uXlK66+LEm1/DZCbm8tbb71V4OZ2XVBrE+alOBPY6u4bw8qOMbNVwP+Au919aVEnmtkIYATAEUccQVpaWkwC2r17d+G6jjuO7iedRNOxY3m/ZUsOJCTEpC2JvyJ/3lKr6WcuUsecey6ceSbcey8MHw5Nm8Y7IhGRMinuAZlYPDiTnJxMRkYGc+bM4cILLyywb9myZcyfPx+Avn37kpmZya5du0hPT+ell4IHhAcNGsRhhx0WdXsbNmxg7dq1DBgwAAg+/B955JHFHv/nP/+ZFStW8Pbbb5f10qS2GT0aFiyAF1/UIDYRqZYqq7/et28fKSkpZGRk0LNnT/r3r75jjitDXU2YDwHmhG1vATq4e6aZ9QReMbMu7v6/yBPdfSYwE+CUU07xfv36xSSgtLQ0iqxr9mzo2ZM+b7wBTz4Zk7Yk/or9eUutpZ+5SB2TN8r87LPh978PhoaIiFQjpY0sS0oKHuuO1LEjpKVBVtY+EiowoOfiiy/m1ltvJS0tjczMzPxyL2I6yuAB4e+/h2vQoAEHDx7M387Ozi50jLvTpUsXli9fXqA8Kyur0LFvvvkm06ZN4+2336axRhTLOedA587B4p9KmItIHDz6aMl9bmn9dXnlzWG+a9cuUlNTmTlzZp1a26M2z2FeJDNrAFwKzM0rc/f97p4Zer0S+AzoHJ8II6SkwJgxwbxpH3wQ72hEREQkWv36Qf/+cN99sGdPvKMRESmTadMgNJ13vkMOCcpjYfjw4UyYMIFu3boVKD/rrLOYHZp4denSpbRp04YWLVoUKH/jjTf49ttvgeCp32+++YbMzEz279/PwoULC7V1/PHHs23btvyEeU5ODuvWrSt03KpVqxg5ciSvvvoqhx9+eGwuVGq2evXgZz8L5jz417/iHY2ISCGV3V+3bNmS3/zmN/z2t78lJycnNpXWAHUuYQ6cC3zs7vkruJhZopnVD73+AdAJ+DxO8RU2ZQq0bQs33gi5ufGORkRERKI1ZQp8842eEhORGmfoUJg5MxihZhZ8nzkzKI+F9u3bc9NNNxUqnzRpEitWrCA5OZmJEyfy7LPPAsHc5unp6fTo0YPFixfToUMHABo2bMiECRPo3bs3qampnHDCCYXqbNSoEfPmzeOOO+7g5JNPJiUlhXfffbfQcbfddhu7d+/miiuuICUlhYsvvjg2Fys1249/HGSfnngi3pGIiBRS2f01QPfu3enatSvPP/987Cqt5mrtlCxmNgfoB7Qxs83ARHd/GriKgtOxAJwFTDGzA0AuMMrdd1RlvCVq0QIeeQSuuioYaa7Fw0RERGqGM86A88+HBx6AUaNA65GISA0ydGhsP3BDsK5LpH79+uVPXdeqVSsWLFgABFOm5D2C3rp1axYvXpx/ziOPPJL/euzYsYwdO7ZQvbNmzcp/nZKSQnp6eoH9kVOyvPnmm2W7GKkbDj00mI7luefgoYegVat4RyQiUkBV9NcvvPBChaZiq2lq7Qhzdx/i7ke6e0N3bx9KluPuw9x9RsSx8929i7uf7O493P21+ERdgiuvhAED4K674L//jXc0IiIiEq0pUyAzE37723hHIiIiIuUxejRkZ8Mf/xjvSEREpArU2oR5rWMWPAKWnQ233BLvaERERCRavXpBaipMnw67dsU7GhERESmr5GTo0wd+9zsIW2RWRERqJyXMa5JOneDOO+Evf4G//z3e0YiIiEi0Jk+Gb78NlrkXERGRmmf0aPjsMwibGkhERGonJcxrmjvvhGOPDVbq3r8/3tGIiIhINHr0gEsugYcfDhLnIiIiUrNceikccYQW/xQRqQOUMK9pmjaFxx+HDRvg17+OdzQiIiISrUmT4H//U/8tIiJSEzVqBCNGwKJF8MUX8Y5GREQqkRLmNdEFF8Dll8OvfqWOWkREpKZITg4W8X7sMdi+Pd7RiIiIxISZNTGz983s32a2zswmh8pbmdkSM9sY+n5YvGOtsBEjoF49mDEj3pGIiEglUsK8pnr0UWjQAMaMAfd4RyMiIiLRmDQJ9uyBhx6KdyQiInFhZlx77bX52wcOHCAxMZHU1NQy1ZOUlMT2Um4+Dhs2jHnz5kVd54wZM+jWrRspKSn06dOH9evXlymmOmw/0N/dTwZSgAvM7DTgTuAtd+8EvBXartnat4cf/hCefhqys+MdjYhIpdm8eTM//OEP6dSpE8ceeyy333473333XdziGTVqVJn69IpSwrymatcuWEBs0SJYsCDe0YiIiEg0TjwRrr46mF5t69Z4RxOYPRuSkujbvz8kJQXbIiLA7A9nk/RoEvUm1yPp0SRmf1jx/x+aNWvG2rVr2bdvHwBLliyhXbt2Fa43Fq6++mo+/PBDVq9eze23384vfvGLeIdUI3hgd2izYejLgR8Cz4bKnwUGxyG82Bs9GjIzYe7ceEciIgLEvr92dy699FIGDx7Mxo0b+eSTT9izZw/jx48vcNyBAwcq1E511iDeAUgFjB0Lzz4bfD/3XGjePN4RiYiISGkmToTnn4cHHggWAY2n2bODx8v37sUANm0KtgGGDo1nZCISZ7M/nM2I10awN2cvAJt2bWLEa8H/D0O7Vez/h4EDB7Jo0SIuv/xy5syZw5AhQ1i6dCkAO3bsYPjw4Xz++ec0btyYp59+muTkZDIzMxkyZAjbtm2jV69eeOgp24yMDFJTU1m7di0A06dPZ/fu3UyaNKlAmytXruQXv/gFu3fvpk2bNsyaNYvmEZ+fWrRokf96z549mFmFrrMuMbP6wErgOOAJd/+nmR3h7lsA3H2LmR1ezLkjgBEAiYmJpKWlVVHURdu9e3fJMZhxaseO5N5/P//q2LHq268CiiH+7SuG6tF+vGJo2bIlWVlZ+du5ubkFtsO98NELjFkyhn0HghvRm3Zt4qev/pTsfdlceeKV5Wo/LS2Nhg0bcvnll+e3O3XqVFJSUjjyyCNZunQp2dnZ7N27l1dffZVbbrmFd955h44dO3Lw4EGuvfZaBg8eTNeuXbniiitIT0/nwIEDPPbYY0yaNInPP/+cm266ieuvvx5355577mHJkiWYGbfddhuXXXYZ7s6tt95Kenp6fr379u0jKyuLVatWcdddd7Fnzx5atWrFjBkzaNu2baHryM7OLvfPTgnzmqxBA3jySejTJ5jP/IEH4h2RiIiIlKZTJ7j2Wvjd7+DWW+Goo+IXy/jxsHdvwbK9e4NyJcxFarVxfx3H6v+uLnb/e5vfY3/u/gJle3P2cv2C63lq5VPk5uZSv379AvtT2qbw6AWPltr2VVddxZQpU0hNTWXNmjUMHz48P2E+ceJEunfvziuvvMLChQu57rrrWL16NZMnT6ZPnz5MmDCBRYsWMXPmzKivNScnhzFjxrBgwQISExOZO3cu48eP57HHHit07BNPPMHDDz/Md999x9///veo26jr3D0XSDGzQ4GXzaxrGc6dCcwEOP74471fv36VE2SU0tLSKDWGW2+FMWPo16wZnHpq1bdfyRRD/NtXDNWj/XjF8NFHH5GQkAAE/fXK/6ws1OfmKaq/3ndgH6MXj+ZP6/9U5Dml9ddffPEFvXr1yo8hT8eOHWnQoAEffPABa9asoVWrVsybN4+vv/6adevW8c0333DiiScyYsQIEhISMDOOPfZYpk+fzs0338zo0aN55513yM7OpkuXLowbN4758+ezfv16PvzwQ7Zv386pp57K+eefz/Lly/niiy9Yt24dW7du5aSTTmLkyJE0adKEO++8s0Cfft999/HMM88Uuo4mTZrQvXv3Et/r4mhKlprujDPg+uuDEWqhURUiIiJSzd1zDxw4APfdF984vvyybOUiUmdEfvgurbwskpOTycjIYM6cOVx44YUF9i1btix/jvO+ffuSmZnJrl27SE9P55prrgFg0KBBHHZY9OtHbtiwgbVr1zJgwABSUlKYOnUqmzdvLvLY0aNH89lnn/HAAw8wderUcl5h3eXuO4E04AJgq5kdCRD6/k0cQ4ut664LnvB+4ol4RyIidVxl9NfuXuRTVnnlAwYMoFWrVkDQb19xxRXUq1ePtm3bcvbZZxc45+KLLwagW7du9O7dm4SEBBITE2nSpAk7d+5k2bJlDBkyhPr163PEEUfQt29fPvjgA9LT0/PLjzrqKM466yygbH16RWiEeW1w//3w8svws5/B22+DHh0UERGp3n7wA/jJT2DmTLjtNujQoepj2LcPmjQJvkeKRzwiUqVKGwme9GgSm3ZtKlTesWVH0oalkZWVVWjkWVlcfPHF3HrrraSlpZGZmZlfnjfVSri8D+1FfXhv0KABBw8ezN/OLmIhRnenS5cuLF++vEB5cY+3QzAK/sYbbyz9QgQzSwRy3H2nmTUFzgUeAF4FfgzcH/peexbfatEieFrsmWdg+nRo0ybeEYlILfXoBY+W2OeW1l+XR5cuXZg/f36Bsv/973989dVX1K9fn2bNmuWXF9Vvh2vcuDEA9erVy3+dt33gwIESzy8uaV9Unx5rGmFeG7RpAw8+CEuXwnPPxTsaERERicbdd4M73Htv1bedmQkDBgTJ8oYNC+5r2hSmTav6mESkWpl2zjQOaXhIgbJDGh7CtHNi8//D8OHDmTBhAt26dStQftZZZzE7tPjw0qVLadOmDS1atChQ/sYbb/Dtt98CcMQRR/DNN9+QmZnJ/v37WbhwYaG2jj/+eLZt25b/4TonJ4d169YVOm7jxo35rxctWkSnTp1icq11wJHAP8xsDfABsMTdFxIkygeY2UZgQGi79hg9GvbvD5LmIiJxUhn99TnnnMPevXt5LpRjzM3NZfz48QwbNoxDDinYVp8+fZg/fz4HDx5k69atZZ4z/KyzzmLu3Lnk5uaybds20tPT6dWrF2eddRbPP/88ubm5bNmyJX/qtmj79IpSwry2+MlP4P/+L5hLbceOeEcjIiIipenQAX76U3j6afjii6pr94svgindVqyAF16AP/4ROnYkf2zHhRdq/nIRYWi3ocy8aCYdW3bEMDq27MjMi2ZWeMHPPO3bt+emm24qVD5p0iRWrFhBcnIyEydO5NlnnwWCuc3T09Pp0aMHixcvpkPoSZiGDRsyYcIEevfuTWpqKieccEKhOhs1asS8efO44447OPnkk0lJSeHdd98tdNzjjz9Oly5dSElJ4eGHH85vW0rm7mvcvbu7J7t7V3efEirPdPdz3L1T6Hvt+qDapQv07RusSZKbG+9oRKSOqoz+2sx4+eWXefHFF+nUqROdO3emcePG3FvEQJ/LLruM9u3b07VrV0aOHEnv3r1p2bJl1G1dcsklJCcnc/LJJ9O/f38efPBB2rZtyyWXXEKnTp3o1q0bN954I2eccQYQfZ9eUZqSpbaoVy/oqHv0gLvughkz4h2RiIiIlOauu4KE+dSpwffKtnIlDBoE330HS5bAmWcG5UOH8nZaGv1+/WtIS4M9eyDsUUsRqZuGdhsaswR5nt27dxcq69evX/6Caq1atWLBgmDmjvBH0Fu3bs3ixYvzz3nkkUfyX48dO5axY8cWqnfWrFn5r1NSUkhPTy+wP3JKlqIWARUp0ejRcOWV8MYbkJoa72hEpI6qjP766KOP5rXXXsvfzsrKonHjxgwbNoxhw4bll9erV4/p06fTvHlzMjMz6dWrV/7TYxkZGfnHRZ4Xvu+hhx7ioYceKtC+mfH4448XaD/vb4Ki+vRY0wjz2iQ5GW66KZgP9Z//jHc0IiIiUpp27WDUKHj2Wfj008pt6403gpFwTZrAO+98nywPd9ddwXQtTz1VubGIiIjUBoMHw1FHafFPEanTUlNTSUlJ4cwzz+See+6hbdu28Q6pwpQwr20mTQo67BtvhAMH4h2NiIiIlObOO6FRI5gypfLaePppuOgi6NwZli+HE08s+rjTTw+S6r/+dTAKXURERIrXsCGMGAF//Wvl3/gWEamm0tLSWL16NevXry8wirwmU8K8tklIgEcfhVWr4Mkn4x2NiIiIlKZt2+CR7tmz4eOPY1u3O0ycCDfcAOeeC2+/DUceWfI5v/wlbN4Mf/5zbGMRERGpjUaMgAYNgilSRURixN1LP0iKVdH3Twnz2uiyy+CCC+Duu+Hrr+MdjYiIiJTm9tuhaVOYPDl2debkwPXXByPXf/ITeO214MZ6ac47L1gT5f77tYiZiIhIaY48Ei69FJ55BvbujXc0IlILNGnShMzMTCXNy8ndyczMpEmTJuWuQ4t+1kZm8NvfQteucMstMGdOvCMSERGRkiQmwtixQZJ6/PigD6+IrCy44gr429+CEeYTJwZ/H0TDLBhlfsUV8NJLwXcREREp3ujR8MILwWfv66+PdzQiUsO1b9+ezZs3s23bNgCys7MrlPyNhXjHUNb2mzRpQvv27cvdnhLmtdVxxwULd02cCMOHw4AB8Y5IRERESnLrrfD448F6JPPmlb+eLVtg0CBYswb+8IfyfXC/5BI4/ni49164/PLok+0iIiJ10ZlnBje7n3gi+PytflNEKqBhw4Ycc8wx+dtpaWl07949jhHFP4aqbl9TstRmt98eJM5Hj4b9++MdjYiIiJSkVSu4+WaYPx9Wry5fHR99FCzc+cknwRQs5R3lVr8+3HFHEMff/la+OkREimBmXHvttfnbBw4cIDExkdTU1DLVk5SUxPbt20s8ZtiwYcwrxw3IefPmYWasWLGizOdKHWUWfO5etQreey/e0YiISAUpYV6bNWkSLPy5cSM8+GC8oxEREZHS3HwzHHooTJhQ9nOXLoUzzoDs7GBxz4EDKxbL0KFw9NHBKHMRqZO2zt7K8qTlpNVLY3nScrbO3lrhOps1a8batWvZt28fAEuWLKFdu3YVrjdWsrKy+M1vfkPv3r3jHYrUNNdcAy1aBKPMRUSkRlPCvLYbMAB+9COYNg0++yze0YiIiEhJDj00WH/ktdfggw+iP+/FF4M+//DDYfly6Nmz4rE0ahRME7N0KSxbVvH6RKRG2Tp7KxtGbGD/pv3gsH/TfjaM2BCTpPnAgQNZtGgRAHPmzGHIkCH5+3bs2MHgwYNJTk6mf//+rFmzBoDMzEzOO+88unfvzsiRI/MXQsvIyKBr2LoP06dPZ9KkSYXaXLlyJX379qVnz56cf/75bNmypcjY7rnnHm6//fa4zxUrNVDz5vDjHwd98jffxDsaERGpACXM64KHHw4+9P7856AVdkVERKq3m24KpmeJdpT5I48EN8dPOQXeeQfC5jussBtugDZt4L77YleniFQLG8dtZFW/VcV+fXz9xxzce7DAOQf3HuTj6z9mVb9VbLhwQ6FzNo7bGFXbV111Fc8//zzZ2dmsWbOmwGjuiRMn0r17d9asWcPEiRO57rrrAJg8eTJ9+vRh1apVXHzxxXz55ZdRX2tOTg5jxoxh3rx5rFy5kuHDhzN+/PhCx61atYqvvvqqzNPDiOT72c/gu++CNURERKTGUsK8LjjqKPjVr+Cvf4WXXop3NCIiIlKShIRgHZK//hXefbf44w4eDKZw+cUv4NJLYckSaN06trEccgiMGwevvw7//nds6xaRas33Fz3QprjyskhOTiYjI4M5c+Zw4YUXFti3bNmy/DnO+/btS2ZmJrt27SI9PZ1rrrkGgEGDBnHYYYdF3d6GDRtYu3YtAwYMICUlhalTp7J58+YCxxw8eJCbb76ZX//61xW8OqnTTjgBzjkHZvw/e/cdZVV19nH8u4cqqNgQESkaERELtqjRKGKMvcX4Rh2xgIIwiAULxYIFRRRRVFBQxEI0xhI0UWPBwZrYGxJbBCSiIBIBEaXs9489hqFJ8c6cO3e+n7XOYu6+5fyu41p37nP2fvYtsGBB1mkkSWuoZtYBVElKSmDUqDRr7be/TV/GJUlSfureHQYNSrPMn3562fvnzYMOHeCBB9Jn+6BBaaPOilBSAldfDQMGwL33Vsw5JFW6lte3/Mn7X27xcmrHspQ6zeuwY+mOzJ49m3V+xneKww8/nHPPPZfS0lJmzJjxv/G4nBWxIYQl/i2vZs2aLFq0eCb8vHnzlnlMjJE2bdrw8ssvLzE+e/bsJX5+7733aNeuHQBffPEFhx9+OI888gi77LLL6r05VW8lJelC9l//CkcemXUaSdIacIZ5dVGzJgwbBp9/DpdemnUaSZL0U+rXh1694Jln0gae5X39depX/sADqe3a9ddXXLEcUl/1bt3g/vvh448r7jyS8soW/begqN6SXxeL6hWxRf8tcvL6HTt25OKLL2a77bZbYnzvvfdm9OjRADz//PNstNFGrLvuukuMP/7448ycOROARo0aMW3aNGbMmMH333/PX//612XO1apVK6ZPn/6/gvn8+fMZP378Eo9p0KABX331FRMnTmTixInsvvvuFsu1Zg47LG2a7eafklRlWTCvTnbfHU47LX2xLts8R5Ik5amuXWGTTdIs8x9nXE6cCHvuCa+8An/6U2rJUhnOOgtq1YKBAyvnfJIy16i4Ea2Gt6JO8zoQ0szyVsNb0ai4UU5ef7PNNuPMM89cZrxfv3689tprbL/99lxyySXceeedQOpt/txzz7HTTjvx5JNP0qxZMwBq1arFxRdfzG677cahhx7K1ltvvcxr1q5dmwceeIALLriAHXbYgbZt2/LST7W8kn6OmjWhS5e0QuyDD7JOI0laA7ZkqW6uuir1Me/aFZ5/Hoq8ZiJJUl5aay3o0wd69IBNNmGfadPS53adOqlf+d57V16WTU41Zn0AACAASURBVDaBjh3TJmaXXAJNmlTeuSVlplFxo5wVyH80Z86cZcbatWv3v1YoG2ywAWPGjAFYou3LhhtuyJNPPvm/5wwePPh/P/fo0YMePXos87qjRo36389t27blueeeW+L+8i1ZllZaWrrS9yKt0KmnppXdQ4fCDTdknUaStJqsllY3G2wA11yTNhEr9wekJEnKQ+usAyHAtGkESBt9xgiffVb5Wc47L53/uusq/9ySJFUljRrBMcek79zffpt1GknSarJgXh2deCLstRecfz6U22BHkiTlmX79Frdj+dG8edC3b+Vn2XxzOO44uPVW/36QJGllSkpg1iwo670vSao6LJhXR0VFaQPQb75JG4pJkqT8NHny6o1XtF690ky5G2/M5vySfra49EU4rRb/+2mV7bEH7LBD2vzT/28kqUqxYF5dbbtt2ijstttSexZJkpR/yja1W+XxitamDRxxBAwZAj/R+1dSfqpbty4zZsyw6LuGYozMmDGDunXrZh1FVUEIaZb5O+/Aiy9mnUaStBrc9LM6u/hiuO++tAHo66+n3bwlSVL+6N8fOneGuXMXj9Wrl8az0rs3jBkDw4dDz57Z5ZC02jbbbDOmTJnC9OnTf/ZrzZs3r8ILxxV9jjV5/bp167LZZptVUCIVnOOPT3uA3HxzaosqSaoSrJBWZ2uvnXbs/t3v0tLqs8/OOpEkSSqvuDj927cvcfJkQrNmqVj+43gWdtsN2reHQYOge3eoUye7LJJWS61atdh8881z8lqlpaXsuOOOOXmtrM5RGe9B1Vz9+nDKKalg/sUXsMkmWSeSJK0CW7JUd0ceCQcfnGab/+c/WaeRJElLKy6GiRMZN3YsTJyYbbH8R717w9SpcOedWSeRJCm/desG8+fDiBFZJ5EkrSIL5tVdCGl2+YIFzjCXJEmrZr/9YNddYeDA9DeEJElavpYt4be/hVtv9TNTkqoIC+aCLbaAvn3hz3+Gv/896zSSpGokhNA0hPBsCGFCCGF8COHMsvF+IYT/hBDeKjsOLvec3iGEj0MIH4QQDsgufTUWQppl/skn6e8HSZK0YiUlaUX3mDFZJ5EkrQIL5krOOw9atUof5PPmZZ1GklR9LAB6xhhbA7sDJSGEbcruGxxjbFt2PAZQdt+xQBvgQGBoCKFGFsGrvSOOgNatYcAAiDHrNJIk5a9DDoHmzVMvc0lS3rNgrqROnfTh/ckn6YuvJEmVIMY4Ncb4RtnPs4EJQJOfeMoRwH0xxu9jjJ8CHwO/rPikWkZREfTqBe+8A489lnUaSZLyV40acPrp8Oyz8P77WaeRJK1EzawDVJQQwkjgUGBajHHbsrF+wGnA9LKH9Sk3Y6030AlYCPSIMVa/3iT77QfHHZcK5sXFqdeaJEmVJITQAtgR+CewJ9A9hHAi8BppFvpMUjH9H+WeNoUVFNhDCJ2BzgANGzaktLS0oqIzZ86cCn39yjjHmrx+2HRTdmvUiO8vuIA369VLrVpyfI7VUV1/D/l2Dt9D9q9fGefwPUirqVMnuOQSGDoUbrop6zSSpJ9QsAVzYBRwE3DXUuODY4zXlh9Yann3psDTIYStYowLKyNoXhk0CP72N+jeHZ54YqVffCVJyoUQwtrAg8BZMcZZIYRhwOVALPt3ENARWN4H03L7gcQYhwPDAVq1ahXbtWtXAcmT0tJSKvL1K+Mca/z6F11E3e7daVejBuy9d8WcYxVV699DHp3D95D961fGOXwP0mpq2BD+8Ae46y646ipYZ52sE0mSVqBgW7LEGJ8Dvl7Fh7u8+0eNG8MVV8CTT7qJlySpUoQQapGK5aNjjA8BxBi/jDEujDEuAkaw+HN5CtC03NM3Az6vzLxaSseOsPHGcOWVWSeRJCm/lZTA7Nlw991ZJ5Ek/YRCnmG+Ijlb3t2oUaOcLeHLq+WA22zDzi1bUrtbN16pX5+F9etnnajg5NXvW5XC37m0fCGEANwOTIgxXlduvHGMcWrZzaOA98p+fgT4YwjhOtKqsJbAK5UYWUtbay04+2zo3RveeAN22inrRJIk5adf/hJ23jntH9a1qyu6JSlPVbeCeU6Xd++yyy45W96dd8sB77kHdt+dXz/9NAwenHWagpN3v29VOH/n0grtCXQA3g0hvFU21gc4LoTQlvR5PBHoAhBjHB9CuB94H1gAlFTLFmr5pmvXtLz8qqtcoSZJ0oqEkGaZd+wI48aB3w8kKS8VbEuW5XF592r45S+hSxcYMgTeemvlj5ckaQ3EGF+IMYYY4/YxxrZlx2Mxxg4xxu3Kxg8vN9ucGGP/GOMvYoytYoyPZ5lfZRo0SPufPPggfPBB1mkkScpfxx4LG2yQZplLkvJStSqYhxAal7u59PLuY0MIdUIIm+Py7uTKK2HDDaFbN1i0KOs0kiQpn515JtSpAwMHZp1EkqT8tdZaaYb5ww/Df/6TdRpJ0nIUbME8hHAv8DLQKoQwJYTQCRgYQng3hPAOsC9wNqTl3cCPy7ufwOXdyfrrw7XXwssvw8iRWaeRJEn5bOON4dRT4a674LPPsk4jSVL+6to1TUobPjzrJJKk5SjYgnmM8bgYY+MYY60Y42Yxxttd3r0GOnSAffaBCy6Ar77KOo0kScpn556b/h00KNsckiTlsy22gIMOSgXzH37IOo0kaSkFWzBXjoQAQ4fCrFlw/vlZp5EkSfmseXMoLk4FgOnTs04jSVL+KimBL75IrVkkSXnFgrlWbpttoGdPuOMOeOGFrNNIkqR8dsEFMG9e2jhckiQt34EHppnmbv4pSXnHgrlWzUUXQbNmqdfa/PlZp5EkSfmqdWs46ii48ca0Qk2SJC2rqCh9v37+eXj33azTSJLKsWCuVVO/fpop9t57zhiTJEk/rXdv+OYbuOWWrJNIkpS/OnaEunWdZS5JecaCuVbdEUfAYYfBJZfAZ59lnUaSJOWrXXaB/feH666D777LOo0kSflpgw3guOPgnnvShWZJUl6wYK7VM2QILFoEZ52VdRJJkpTPeveGL7+EUaOyTiJJUv4qKYFvv4U778w6iSSpjAVzrZ4WLVI/84cegsceyzqNJEnKV+3awe67w8CBsGBB1mkkScpPO+8Mu+0GQ4dCjFmnkSRhwVxromdP2HprOOMMl1lLkqTlCyHNMp84Ee67L+s0kiTlr5IS+OADeOaZrJNIkrBgrjVRu3a6+v3vf8NVV2WdRpIk5atDD4Vtt4UBA1JLN0mStKxjjoGNNkrfsyVJmbNgrjWz775wwglw9dXw4YdZp5EkSfmoqAh69YLx42GTTdinffvU3m306KyTSZKUP+rWhU6dYMwY6kyblnUaSar2LJhrzV17Lay1FnTrZq81SZK0fIsWpfYs06cTYoRJk6BzZ4vmkiSVd/rpECObPvpo1kkkqdqzYK4116gRXHll6rP2pz9lnUaSJOWjiy5a9sL63LnQt282eSRJykctWsChh9L4b3+D77/POo0kVWsWzPXzdOkCu+wCZ58N33yTdRpJkpRvJk9evXFJkqqrkhJqz5wJDz6YdRJJqtYsmOvnqVEDhg2DL7+Eiy/OOo0kSco3zZqt3rgkSdXV/vszt0kTuPnmrJNIUrVmwVw/3y67pD7mN90Eb7yRdRpJkpRP+veHevWWHFtrrTQuSZIWKyri8yOOgJdegrfeyjqNJFVbFsyVG1dcAQ0bQteusHBh1mkkSVK+KC6G4cOheXP+18n8sMPSuCRJWsIXBx6YLiw7y1ySMmPBXLmx3nowaBC88grcdlvWaSRJUj4pLoaJExn37LOpWP7EEzB9etapJEnKOwvWWSd9bo4eDTNnZh1HkqolC+bKneOPh333hV69YNq0rNNIkqR8dPXV8O23cPnlWSeRJOVACKFpCOHZEMKEEML4EMKZZeP9Qgj/CSG8VXYcnHXWKqOkBL77DkaNyjqJJFVLFsyVOyHA0KHpS/D552edRpIk5aPWreHUU9Om4R99lHUaSdLPtwDoGWNsDewOlIQQtim7b3CMsW3Z8Vh2EauYtm3hV79K368XLco6jSRVOxbMlVtbbw3nnQd33gnPPZd1GkmSlI/69YM6ddKqNElSlRZjnBpjfKPs59nABKBJtqkKQEkJfPwxPPVU1kkkqdqpmXUAFaC+feGPf0wbgL75JtSunXUiSZKUTzbZJK1Gu+QSePFF2HPPrBNJknIghNAC2BH4J7An0D2EcCLwGmkW+jJNuUMInYHOAA0bNqS0tLSy4i7XnDlzMs3w4/nDRhuxx/rrM+uyy3ivTp1MMmQp6wxZn98M+XF+M+RPhso+vwVz5V69enDjjWlTr+uvtz2LJElaVs+ecMstaWXaiy+m1m6SpCorhLA28CBwVoxxVghhGHA5EMv+HQR0XPp5McbhwHCAVq1axXbt2lVa5uUpLS0lywxLnL9bNza68kratWgBLVpkkyEjWWfI+vxmyI/zmyF/MlT2+W3Joopx6KFw5JFw6aUwaVLWaSRJUr6pXz9t/Pnyy/Dgg1mnkST9DCGEWqRi+egY40MAMcYvY4wLY4yLgBHAL7PMWCV16ZIuKN9yS9ZJJKlasWCuinPDDenfs87KNockScpPJ58M226bepn/8EPWaSRJayCEEIDbgQkxxuvKjTcu97CjgPcqO1uV17QpHHEE3HYbzJuXdRpJqjYsmKviNGuWepP+5S/w179mnUaSJOWbGjVg4ED45BNnz0lS1bUn0AFoH0J4q+w4GBgYQng3hPAOsC9wdqYpq6qSEpgxA+6/P+skklRtWDBXxTrrLNhmGzjjDJg7N+s0kiQp3xx4IOy3H1x2Gfz3v1mnkSStphjjCzHGEGPcPsbYtux4LMbYIca4Xdn44THGqVlnrZLat4ett4abb846iSRVGxbMVbFq14Zhw2DiROjfP+s0kiQp34QA11wDX38NAwZknUaSpPwSAnTrBq+8Aq+9lnUaSaoWLJir4u29N5x0UvoyPGFC1mkkSVK+2XFHOOEEuP56mDw56zSSJOWXE09Mm2U7y1ySKoUFc1WOgQNh7bVT/7UYs04jSZLyzRVXpH8vvDDbHJIk5ZsGDaBDB7jvvtTPXJJUoSyYq3JsvDFcdRU8+yz88Y9Zp5EkSfmmWbO098k998Cbb2adRpKk/FJSAvPmwciRWSeRpIJnwVyV57TT4Je/hHPOcVMvSZK0rN69YYMN4LzzXJEmSVJ5226b2p0OGwYLF2adRpIKmgVzVZ6iIrjlFvjqK5dbS5KkZTVoABdfDM88A088kXUaSZLyS0kJfPqpn5GSVMEsmKty7bgjdO8OQ4e6w7ckSVrW6afDllumWeYLFmSdRpKk/HHUUdC4sZt/SlIFs2CuynfZZdCoEXTt6lIySZK0pNq1074n48fDqFFZp5EkKX/UqgWdO6cZ5p98knUaSSpYFsxV+Ro0gMGD0wzzW2/NOo0kSco3Rx8Ne+yR2rN8+23WaSRJyh+nnZbanQ4blnUSSSpYFsyVjT/8AfbbD/r0gS++yDqNJEnKJyHAtdfC1KkwaFDWaSRJyh9NmqTWLCNHwty5WaeRpIJkwVzZCCH1Mf/uu9SjVJIkqbxf/SrNNB840IvrkiSVV1ICM2fCn/6UdRJJKkgWzJWdrbaCCy6Ae+6BZ5/NOo0kSco3V10F338P/fplnUSSpPyxzz7Qpk3a/DPGrNNIUsGxYK5s9e4NW2wB3brBDz9knUaSJOWTli3TJuG33QYTJmSdRpKk/BBC+g79+uvwyitZp5GkgmPBXNlaay246Sb417/sUSpJkpZ18cVQv35alSZJkpIOHWCdddIsc0lSThVswTyEMDKEMC2E8F65sWtCCP8KIbwTQng4hLBe2XiLEMJ3IYS3yo5bskteDR10EPzud3D55TBxYtZpJElSPtloo7Qi7dFHYdy4rNNIkpQf1lkHTjwx9TGfPj3rNJJUUAq2YA6MAg5cauwpYNsY4/bAh0Dvcvd9EmNsW3acXkkZ9aPrr4eiIujRI+skkiQp35x5JjRtCueeC4sWZZ1GkqT88GNr09tvzzqJJBWUgi2YxxifA75eauzJGOOCspv/ADar9GBavqZN04Zejz4KY8ZknUaSJOWTtdaCK66A115LM+kkSSowo0dDixbQvv0+tGiRbq/UNtvAvvvCLbfAwoUVnFCSqo+aWQfIUEeg/DeuzUMIbwKzgAtjjM8v70khhM5AZ4BGjRpRWlqakzBz5szJ2WtVVaFtW3befHNqdunCK7Vrs2ittbKOVGH8fVc//s4l6Wc64QQYPBj69Emt3OrUyTqRJEk5MXo0dO4Mc+cCBCZNSrcBiotX8uSSEvj97+Fvf4PDD6/gpJJUPVTLgnkIoS+wAPjxmu1UoFmMcUYIYWfgLyGENjHGWUs/N8Y4HBgOsMsuu8R27drlJFNpaSm5eq0q7a674Ne/Zu9x42DAgKzTVBh/39WPv3NJ+pmKiuCaa2D//dOG4T17Zp1IkqSc6Nv3x2L5YnPnpvGVFsyPOAKaNEmbf1owl6ScKNiWLCsSQjgJOBQojjFGgBjj9zHGGWU/vw58AmyVXcpqbK+94JRTYNAgeP/9rNNIkqR88pvfpM3Cr7gCvv565Y+XJKkKmDx59caXULMmdOkCTz4JH36Y01ySVF1Vq4J5COFA4ALg8Bjj3HLjDUMINcp+3gJoCfw7m5Ri4EBYd920gUm6piFJkpQMHAizZqWiuSRJBaBZs9UbX8Zpp0GtWjBsWM4ySVJ1VrAF8xDCvcDLQKsQwpQQQifgJmAd4KkQwlshhFvKHr438E4I4W3gAeD0GKPTlrKy0UapHcu4cXD33VmnkSRJ+WTbbdNqtJtugn87v0GSVPX17w/16i05VlS0GteGN9kEjj4a7rgDvv025/kkqbop2IJ5jPG4GGPjGGOtGONmMcbbY4xbxhibxhjblh2nlz32wRhjmxjjDjHGnWKMj2adv9rr1An22APOPRdmzsw6jSSpgoQQmoYQng0hTAghjA8hnFk2vkEI4akQwkdl/65f7jm9QwgfhxA+CCEckF16Zeayy9JMuj59sk4iSdLPVlwMw4dD8+YQQmTDDWHRomX7mv+kkhL45hv44x8rLKckVRcFWzBXFVdUlJaTzZjhl2FJKmwLgJ4xxtbA7kBJCGEboBfwTIyxJfBM2W3K7jsWaAMcCAz9sa2aqpFNN02bfv7pT/DKK1mnkSTpZysuhokTYezYcUyfDu3aQa9eMH36Kr7AnnvC9tunzT9tbSpJP4sFc+WvHXaAHj3g1lv9MixJBSrGODXG+EbZz7OBCUAT4AjgzrKH3QkcWfbzEcB9ZRt2fwp8DPyyclMrL5x3Hmy8cVqNZmFAklRAQoChQ2H2bDj//NV4UkkJvP02vPRSheaTpEJXM+sA0k+69FK4/37o2jUVzWs4iVCSClUIoQWwI/BPoFGMcSqkonoIYeOyhzUB/lHuaVPKxpb3ep2BzgANGzaktLS0QnIDzJkzp0JfvzLOURXfw6bFxWw1eDDv9u/PjL32qpLvobJfvzLO4XvI/vUr4xy+B6litW6drgkPGAAdO8Kvf70KTyouThX2m29OM84lSWvEgrny27rrwuDB8Ic/pEvsZ5yRdSJJUgUIIawNPAicFWOcFUJY4UOXM7bc6cUxxuHAcIBWrVrFdu3a5SDpUkaPhr59iZMnE5o1S7t2FRfn/jxAaWkpFfIeKun1K+Qce+0Fjz/OdvfcAxdcQOmLL1a991DJr18Z5/A9ZP/6lXEO34NU8S66CO69F7p1gzfeSNt3/KT69eHkk9N358GDoVGjyogpSQXHlizKf8ccA7/9LVx4IUydmnUaSVKOhRBqkYrlo2OMD5UNfxlCaFx2f2NgWtn4FKBpuadvBnxeWVmXMHo0dO4MkyYRYoRJk9Lt0aMziVMt1awJV18NH3wAm2zCPu3bQ4sW/g4kSQWhXj0YMgTeey/9u0q6dYP582HEiArNJkmFzIK58l8IaUnZ99+nDb4kSQUjpKnktwMTYozXlbvrEeCksp9PAsaUGz82hFAnhLA50BLIZqOLvn1h7twlx+bOTeOqPLNnp83Cv/7aCxeSpIJz+OFw2GFwySXw2Wer8ISttoL99097gS1YUOH5JKkQWTBX1bDllmmL8HvvhWeeyTqNJCl39gQ6AO1DCG+VHQcDA4D9QwgfAfuX3SbGOB64H3gfeAIoiTEuzCT55MmrN66K0bcvLFq05JgXLiRJBWTIkPRRd/bZq/iEkhKYMgUeeaRCc0lSobJgrqqjVy/4xS/SErPvv886jSQpB2KML8QYQ4xx+xhj27LjsRjjjBjjfjHGlmX/fl3uOf1jjL+IMbaKMT6eWfhmzVZvXBXDCxeSpALXokXqZ/7gg/D4qvzlc+ih6e+Rm2+u6GiSVJAsmKvqqFs3feB/+CFcc03WaSRJ1V3//qm5aHlFRXDFFdnkqa68cCFJqgZ69oStt4bu3eG771by4Bo14PTTYexYmDChUvJJUiGxYK6q5YAD0iag/fvDv/+ddRpJUnVWXAzDh0Pz5sQQYIMN0nrpadNW/lzlzvIuXNSrl8YlSSoQtWvD0KHpa/CAAavwhFNPXfwkSdJqsWCuqmfwYKhZE844A2LMOo0kqTorLoaJExk3dix89RUceST07g3vvJN1supj6QsXzZun28XFWSeTJCmn9t03fbwNGAAffbSSBzdsCP/3f3DnnWmDbEnSKrNgrqqnSRO47DJ47DH4y1+yTiNJUhICjBiRZpoXF8O8eVknqj7KX7iYONFiuSSpYF17Lay1VtrXc6Xzx7p1S8Xye+6plGySVCgsmKtqOuMM2H576NED5szJOo0kSclGG8Edd8B770GfPlmnkSRJBWaTTVLXsaeegj//eSUP3n132HHHtBeYq7MlaZVZMFfVVLMmDBsGU6bApZdmnUaSpMUOPDDtyDV4MDz9dNZpJElSgTn9dNhpJzjrLJg16yceGEKaij5+PDz3XKXlk6SqzoK5qq5f/SptZDJ4cJrJJ0lSvrj6amjdGk46Cb7+Ous0kiSpgNSoAbfcAl98AZdcspIHH3ccrL9+mmUuSVolFsxVtQ0YAOutB127wqJFWaeRJCmpVy/1C50+Hbp0cRm0JEnKqV13TTPNhwyBt976iQfWqwennAIPPwyff15p+SSpKrNgrqptww1h4EB44QW4666s00iStNhOO8Hll8MDD8Ddd2edRpIkFZj+/dNX4m7dVjJ/rGtXWLAgbU4uSVopC+aq+k4+GfbcE847D2bMyDqNJEmLnXsu7L136mn+6adZp5EkSQVk/fXh2mvh5Zdh5MifeOCWW6Y9Vm69FebPr7R8klRVWTBX1VdUBEOHwsyZ0Lt31mkkSVqsRo20AioE6NABFi7MOpEkSSogHTqka/MXXABfffUTDywpgalT4S9/qbRsklRVWTBXYdh++7RF+IgR8I9/ZJ1GkqTFmjdPF3ZffDFtBipJkpQjIaQ/M2bNgl69fuKBBx0ELVq4+ackrQIL5iocl1wCTZqknU8WLMg6jSRJix1/PBx7bPqseu21rNNIkqQC0qYNnHMO3H57uj6/XDVqpF7m48bBe+9Vaj5JqmosmKtwrLMO3HADvP22V80lSfnlx+lfm2wCxcXw7bdZJ5IkSQXk4ouhadPF+3suV8eOUKdO+ptEkrRCFsxVWH73u7TU7KKL4PPPs04jSdJi66+f+pl/9FHaqFqSJClH6teHIUPg3XfhxhtX8KCNNkor3u6+O/VwkSQtlwVzFZYQ0l8H8+fD2WdnnUaSpCXtuy/07AnDhsHf/pZ1GkmSVECOOAIOOSTNNp8yZQUPKimBOXPSRXxJ0nJZMFfh+cUvoE8fuP9+ePLJrNNIkrSkK65Im1V37AjTpmWdRpIkFYgf548tWJB6mi/XrrumY+hQiLFS80lSVWHBXIXp/POhZct09XzevKzTSJK0WJ06MHo0fPMNnHqqX1YlSVLObL45XHgh/PnP8Pe/r+BBJSUwYQI8+2ylZpOkqsKCuQrTjxuZfPwxDByYdRpJkpa07bZw9dXw6KMwYkTWaSRJUgE591xo1Qq6d1/B/LE//AE23BBuvrnSs0lSVWDBXIXrN79JG5pceWUqnEuSlE/OOAP23z/tufHhh1mnkSRJBaJOnVQL//jjdH1+GXXrQqdOMGbMTzQ7l6Tqy4K5CtugQVC7drq07pJ3SVI+KSqCUaPSl9YTTkgbVkuSJOXAfvvBccfBVVetYP7Y6afDokVw662Vnk2S8p0FcxW2TTdNm6v9/e/w4INZp5EkaUmbbpq+qL76Klx+eTYZRo+GFi3Yp317aNEi3ZYkaRWFEJqGEJ4NIUwIIYwPIZxZNr5BCOGpEMJHZf+un3XW6mbQoDTbfLnzxzbfHA45JLWG++GHTPJJUr6yYK7C160btG0LZ50Fs2dnnUaSpCX9/vdw8snQvz+89FLlnnv0aOjcGSZNIsQIkyal2xbNJUmrbgHQM8bYGtgdKAkhbAP0Ap6JMbYEnim7rUrUuPFK5o+VlMCXXzq5TJKWYsFcha9mTbjlFvj8c+jXL+s0kiQt64YboHnz1JqlMi/u9u0Lc+cuOTZ3bhqXJGkVxBinxhjfKPt5NjABaAIcAdxZ9rA7gSOzSVi9de0KO+64gvljv/0tbLmlm39K0lIsmKt62G23NGPuhhvgnXeyTiNJ0pLWXRfuvjvN8O7Ro+LPFyO8/XY63/JMnlzxGSRJBSeE0ALYEfgn0CjGOBVSUR3YOLtk1VfNmjBs2ArmjxUVpYr6iy+mvwskSQDUzDqAVGmuvBIeeij9QfD88+mPA0mS8sWee0KfPmnt9CGHpFYtufavf8F998Gf/pR+XpFmzXJ/bklSQQshrA08CJwVY5wVQljV53UGOgM0bNiQ0tLSCsu4KubMmZNphoo6/6GHbsX11zdmm21e4xe/+PZ/4zVbtmSPOnX4sm9fPjz33ArNsDqyzpD131AmDAAAIABJREFU+c2QH+c3Q/5kqOzzWzBX9bHBBnDNNalP7B13QKdOWSeSJGlJF18MTzwBXbrAHntAkyY//zU//TQVyO+7L80eCwHatUtrs2OEnj2XbMtSp07qpy5J0ioKIdQiFctHxxgfKhv+MoTQOMY4NYTQGJi2vOfGGIcDwwFatWoV27VrVxmRV6i0tJQsM1TU+bffHlq1gpEjd112/tgJJ7Dpvfey6T33wHrrZf7fAAr392CGqnV+M+RPhso+v1NsVb2ceCL8+tdw/vnw1VdZp5EkaUm1aqUNN+fNg1NOgUWL1ux1/vMfuP562H132GIL6N0b6tVLrcmmTIGxY1NR/vTTYfhwaN6cGEJat73OOnCkbWYlSasmpKnktwMTYozXlbvrEeCksp9PAsZUdjYt9uP8sZdeglGjlrqzpCRdPF/mDkmqniyYq3oJITVwmzULerlJuyQpD221FVx3HTz1FNx446o/b/r09Bm3zz7QtCmcfTbMnw9XX51mmb/0UuqPvummSz6vuBgmTmTc2LHwzDPpgrKbZEuSVt2eQAegfQjhrbLjYGAAsH8I4SNg/7LbytBJJy2ePzZjRrk7dtwxrWwbOnTNL9ZLUgGxYK7qp00bOOccuP32tLmJJEn5pnNnOPRQuOACeO+9FT/uv/9NbcYOOAAaN4Zu3VLh/NJL4YMP4PXX07fiFi1W7bx77w2nnZYK9q+/npO3IkkqbDHGF2KMIca4fYyxbdnxWIxxRoxxvxhjy7J/v846a3UXQqqJ//e/afHZEkpK4KOP4OmnM8kmSfnEgrmqp4suSrPvunaFBQuyTiNJ0pJCSBd2GzSAgw+G5s3Zp337VPgeORL++Ec4/HDYeGPo2BE+/jgV1995B8aPT59zW221ZuceODC97mmn+RkpSVKB2XbbtAhtxAh4+eVyd/z+99CwIdx8c2bZJClfFGzBPIQwMoQwLYTwXrmxDUIIT4UQPir7d/1y9/UOIXwcQvgghHBANqlVadZeG4YMgXffTf9KkpRvNt4YOnSAzz6DyZMJMcKkSWnT6uJiePPN1GLl1VdTwbx/f9huu1Rs/znWWy+1gnnzTRg8ODfvRZIk5Y1LLoHNNltq/lidOnDqqfDXv1Lniy8yzSdJWSvYgjkwCjhwqbFewDMxxpbAM2W3CSFsAxwLtCl7ztAQQo3Ki6pMHHEEHHJI+mthypSs00iStKwHHlj+eKNGqXh+7bWwyy4/v0i+tKOPTjPYL7kE/v3v3L62JEnK1Nprp33A3357qQnlp58OwKaPPppNMEnKEwVbMI8xPgcs3SPtCODOsp/vBI4sN35fjPH7GOOnwMfALyslqLITQppBt3BhWpMmSVK+mTx5+ePTpkFRBf4ZF0L6Bl2zJnTpAjFW3LkkSVKlO+ooOOig1MXt88/LBps1g8MOo/Hf/gbz5mWaT5KyVLAF8xVoFGOcClD278Zl402Az8o9bkrZmArd5pvDhRemGXxPPJF1GkmSltSs2eqN59Jmm8GAAWnzr7vvrvjzSZKkShMC3HQTzJ8P55yTxka/O5oWu79M3bO+ocWgzRj97uhsQ0pSRmpmHSBPLG8d83KnUoUQOgOdARo1akRpaWlOAsyZMydnr6XVE3bZhV2bNiV06sSrI0eyqE6dCj+nv+/qx9+5pDXSvz907gxz5y4eq1cvjVeG00+H0aPTSqwDD0x91SVJUkHYYgvo0wcuvhhaHD6aGyd2Zu78uRBg0oIZdH60MwDF2xVnnFSSKld1K5h/GUJoHGOcGkJoDEwrG58CNC33uM2Az5d5NhBjHA4MB9hll11iu3btchKstLSUXL2W1sCoUbDffuz90ktw6aUVfjp/39WPv3NJa6S47Atq377EyZMJzZqlYnlxJX1xLSqCESOgbdtUNB/tTDNJkgrJ+eenhWSD3uzLgrXnLnHf3Plz6ftMXwvmkqqd6taS5RHgpLKfTwLGlBs/NoRQJ4SwOdASeCWDfMpK+/Zw/PFp6fmHH2adRpKkxYqLYeJExo0dCxMnVl6x/EfbbAO9e8Mf/wiPP16555YkSRWqTp20bcmC+svfN2XyNyvYT0WSCljBFsxDCPcCLwOtQghTQgidgAHA/iGEj4D9y24TYxwP3A+8DzwBlMQYF2aTXJkZNAjq1oWSEjc3kySpvD59YOutoWtXmDMn6zSSJCmH9t8f6s1f/v4ozdZxezdJ1U/BFsxjjMfFGBvHGGvFGDeLMd4eY5wRY9wvxtiy7N+vyz2+f4zxFzHGVjFGp09VR5tskpa5P/003H9/1mkkScofdeqk1iyTJqVGp5IkqaBcfUB/mF9vibHaC6D/D7/OKJEkZadgC+bSGunaFXbeOfVpnTUr6zSSJOWPvfZKm4DecAO8+mrWaSRJUg5137uY4nWHw3+bA4E6NepQk0D70S/BokVZx5OkSrVGBfMQQo0QwiEhhDNDCJeGEC5b6qj4XROlilCjBgwbBl984Qw6SZKWNmBAWpF12mkwf37WaSRJUg6NOqeYHZ6dSMOb5/LSiW+zqFZNurWZRHziiayjSVKlWu2CeQhhR+Bj0kaZg4GLgAuXc0hV0667phl0N94Ib76ZdRpJkvJHgwZw003w9ttw3XVZp5EkSTlUs2aaPzZ9el3uvbEVl7W7lL+0hj/dZ4lHUvWyJjPMbwU2BM4AdgQ2X86xRa4CSpno3x822ii1aHH5mSRJix11VDr69YOPP846jSRJyqE99oBDDvmcwYPht+ufz26xCd0bv8mX77+SdTRJqjRrUjDfDhgQYxwaY3w7xjhpeUeug0qVav314dpr4Z//hNtuyzqNJEn55aaboHZt6NIFYsw6jSRJyqHTTvs3660H3bvV4Paj72Z2beh+b4esY0lSpVmTgvlnwNxcB5HyzgknQLt20KsXTJ+edRpJkvLHppvC1VfD2LEwalTWaSRJUg41aLCAgQPhhRfg1df3pd9XbXig5of8+c3RWUeTpEqxJgXzG4BTQgh1cx1GyishwNChMHs2nH9+1mkkScovnTvDXntBz57w5ZdZp5EkSTl08snwq1/BeedBpwNuZOfPoeSvXZn+rZPJJBW+1S6YxxhvBu4G3g8hXBZCOC2E0HHpI/dRpQy0bg3nnptmzz3/fNZpJEnKH0VFMGIEfPstnHVW1mkkSVIOFRWlDUBnzoSLH2/HqHe24L8L5tDjiR5ZR5OkCrfaBfMQQlPgeKAFcCFpE9DbljpG5C6ilLGLLoLmzdMGoPPnZ51GkqT8sfXW0Lcv3Hcf/O1vWaeRJEk5tP32cOaZMHxE4Nu9rubi0sh9793HwxMezjqaJFWoNWnJMgLYFrgWOArYdzlH+1wFlDJXrx4MGQLjx8P112edRpKk/NKrF2yzTbqwPHt21mkkSVIO9euXti7p+uRR9HxzXXb8fgO6/q0rM+bOyDqaJFWYNSmY7wVcG2M8P8Y4JsY4bnlHroNKmTr88HT06weffZZ1GkmS8kft2qk1y5QpcOGFWaeRJEk5tM46ad7Ym+/U4LYdRnDHPbOZ8d0Mzvq77dgkFa41KZjPBD7PdRAp7w0ZAjGmNWmSpJwJIYwMIUwLIbxXbqxfCOE/IYS3yo6Dy93XO4TwcQjhgxDCAdmk1hJ+9as0w/zGG+Gf/8w6jSRJyqGjj4YDDoAL3zqajT/bkL5hH+555x4e/eDRrKNJUoVYk4L5HcCxIYQ1ea5UdTVvDhdfDA8/bJ9WScqtUcCByxkfHGNsW3Y8BhBC2AY4FmhT9pyhIYQalZZUK3bVVWnN9mmnueeHJEkFJAS46Sb4fn4Nem58D31GfsT2G29Pl792YeZ3M7OOJ0k5tyZF7xeBusDLIYROIYT9Qwjtlz5ynFPKD+ecA61bQ/fuMHdu1mkkqSDEGJ8Dvl7Fhx8B3Bdj/D7G+CnwMfDLCgunVbfuujB0KLz7LlxzTdZpJElSDm25JfTuDfdO24/nP92SOzY4hWnfTuOcJ8/JOpok5VzNNXjO4+V+3hWIS90fysac7aXCU7t2Kgbsuy9ceSVccUXWiSSpkHUPIZwIvAb0jDHOBJoA/yj3mCllY8sIIXQGOgM0bNiQ0tLSCgs6Z86cCn39yjhHTl5/3XXZZp992KhfP15t2pTvmjbN/Tl+gr+H/DiH7yH716+Mc/gepOrnggvg7rsj3SYO553bz6JXr170f74//7fN/3FQy4OyjidJObMmBfNTcp5CqkratYMOHWDgwPRvq1ZZJ5KkQjQMuJx0Ef5yYBDQkXRhfmlLX7xPgzEOB4YDtGrVKrZr165CggKUlpZSka9fGefI2evfey+0bs1ut98OY8dC0eIFjVXmPWR4Dt9Dfpyjqr9+ZZzD9yBVP3Xrws03Bw488Bdc+9T2XDTkOP7S8C+c9uhpjO82ngZ1G2QdUZJyYrVbssQY71yVoyLCSnnjmmugfn3o1i1tBCpJyqkY45cxxoUxxkXACBa3XZkClJ+2vBluRp5fGjdOn5PjxsHIkVmnkSRJOXTAAXDMYd9xBRfy+TUPc8cRdzB1zlTOffLcrKNJUs64cWfWRo+GFi3Yp317aNEi3Vb+a9QotWQZOzbNpJMk5VQIoXG5m0cB75X9/Ahp8/E6IYTNgZbAK5WdTyvRqRPsvTecdx588UXWaSRJUg4NHrYWNWvCGXftyi7rteG8X53HbW/expOfPJl1NEnKidVuyVLWS3SlYox3rX6camb0aOjcGebOTevLJ01KtwGKi7NMplXRuTPccUfaCPSQQ6CBy88kaU2EEO4F2gEbhRCmAJcA7UIIbUntViYCXQBijONDCPcD7wMLgJIY48IscusnFBXB8OGwww7Qowfcf3/WiSRJUo40aQKXdv6cnkMPYMz5T9Hvhn6M+WAMpz16Gu91fY916qyTdURJ+lnWZIb5qJ847ih3aGX69oW5c5ccmzs3jSv/1agBw4bB9Olw4YVZp5GkKivGeFyMsXGMsVaMcbMY4+0xxg4xxu1ijNvHGA+PMU4t9/j+McZfxBhbxRgf/6nXVoZatYKLLoI//xkefTTrNJIkKYd6XL8F29f9gB4jtmXhvDqMPHwkn33zGec/dX7W0STpZ1uTgvnmyzm2BA4AHgdeBdrkKmBBmzx59caVf3beOfUxHzoUXn896zSSJOWX886DbbeFk06CZs1sQSdJUoGoWSswtPsEPpvfmMtO/5w9mu7BOXucwy2v38LYT8dmHU+SfpY12fRz0nKOf8cYn4oxHgp8B3TOfdQC1KzZ6o0rP11xBTRsCF27wkK7AkiS9D+1a8Pvfw8zZ8JnnxFiXNyCzqK5JElV2p6X/IaOte7muj82Yvx4uHzfy2m5QUs6PdKJOT/MyTqeJK2xitj080Hg+Ap43cLTvz/Uq7fs+AEHVH4WrbkGDeC66+DVV2HEiKzTSJKUX+5YTqc+W9BJklT1rb02V5/0PuvGb+h26g/UrbkWI48YyaT/TqL3072zTidJa6wiCuYNgHUr4HULT3Fx2hCreXNiCNC0KbRpk8auvBJizDqhVtVxx0H79tC7N3z5ZdZpJEnKHwXSgm706NRNpn37fewqI0lSmY16nsTVXMBz/6jN3XfDXs32osduPbjp1ZsYN3Fc1vEkaY3krGAeQmgQQjgK6An8I1evW/CKi2HiRMaNHZu+OL7xBhx/fJp11b27LT6qihDg5pvh229Tv1ZJkpQUQAu60aNTF5lJkyDGYFcZSZJ+tPXWdGw/iT1qv8a550ZmzoT+7fuzxfpb0OmRTnz7w7dZJ5Sk1bbaBfMQwqIQwsKlD+BrUjuWGUD3XAetNmrXhrvvhp4900aS//d/MG9e1qm0KrbeGs4/P/3+xnklXZIkYPkt6NZaK41XEX37pi4y5dlVRpKkpKh7N4b90IkZM9JnY/3a9Rl5+Eg+mfkJfcf6YSmp6lmTGeaXLee4FDgLOBjYOsb4fs4SVkdFRXDttakv9kMPpZ7mM2dmnUqrok+ftF67a1f44Yes00iSlL3yLeh+HGvfPo1XEQXSVUaSpIpx2GHs0HQmPZo8xC23wCuvwD4t9qFk1xKG/HMIL05+MeuEkrRaVrtgHmPsF2O8dKnjshjjjTHGJ2KM9hDJlbPPhnvvhZdfhl//GqZMyTqRVqZePbjpJpgwAQYPzjqNJEn54ccWdM8+C6ecAk8+CR9+mHWqVbai7jE1a6aObM5rkCRVazVrQpcuXPrZKTRuOJ+uXVN32QG/GUDz9ZpzyphT+G7+d1mnlKRVtkoF8xBC+9U9Kjp4tXHssfDEE2kK0x57wPjxWSfSyhxyCBx1FFx2WWp2KkmSFrvySqhbN00MqCKW11Wmdm3YdNO05cymm0KHDvDcc+7ZLkmqpk49lXVrzWPwTvfwxhtwyy2wdu21uf3w2/no64+46NmLsk4oSatsVWeYPw08tZKj/GOezHnS6qx9+/QNbMEC2GsveOGFrBNpZa6/Pv3bo0e2OSRJyjebbAIXXwyPPZaOKqBcVxlCiDRvDiNHwsSJ8PrradL8I4/APvukLU2uuQa+/DLr1JIkVaJGjeCYYzjmxbPYv/0C+vSBL76A9pu3p8vOXRj8j8H8Y8o/sk4pSatkVQvmpwAdV3KcDrwJhLJDudS2bWrN0qgR/OY3qbe58lezZtCvX/r2/MgjWaeRJCm/9OgBW22VZplXkT0/yrrKMHbsOCZOXNyCfaed0j7tU6fCqFGw8cZpD/DNNoPf/z4tFFxow0JJUnVQUkKYPYub9nmAefPg3HPT8MD9B9JknSacMuYU5i2Yl21GSVoFq1QwjzHeuaIDuAeoDfQFdgJeAQ6suMjVWIsWaXZ527bpG9jQoVkn0k856yxo0yYVBb79Nus0kiTlj9q102qsDz+EIUOyTpMT9erBSSfB88/D++/DmWfCuHFw0EGwxRZw6aVuEipJKnB77AFt27LVA1fS64LI6NHw7LOwbp11ue3w2/jXV/+iX2m/rFNK0kqt9qafPwpJB+BfwC3A18ARMcbdY4xP5SqglrLRRvDMM6lPdkkJXHihzTLzVa1aMGxY6mPev3/WaSRJyi8HHZT+nrnssrRmu4C0bg3XXgv/+Q/cf39q03LppWnuw8EHp4WC8+dnnVKSpBwLIdUp3n2XXnu/xBZbQLduaTHZb3/xWzrt2IlrXrqGV//zatZJJeknrVHBPITwf8B44E7ge+APMcYdY4yP5jKcVqB+fXj4YejUKRViTz3Vb1356te/hpNPTt+aJ0zIOo0kSfll8GCYNw/69Mk6SYWoXRuOOQb+/nf45JM0z+Gdd+Doo1PLlgsugI8+So8dPToV1Nu334cWLdJtSZKqnOOPh/XWY63bbuSmm+Bf/4JBg9Jdg347iE3X2ZRTxpzC9wu+zzanJP2E1SqYhxCOCCG8BdwH1AQ6ANvFGB+oiHD6CTVrwogRadOskSPhyCNt+5GvBg6EtddOl9ZdDSBJ0mItW6YWZnfcAa+8knWaCrX55mky/cSJ8Ne/plXrgwalVu6tW0PHjmlRWoyBSZOgc2eL5pKkKqhevbQb9oMPclDbqRx9NFx+efr8a1C3AcMPHc746eO5/LnLs04qSSu0SgXzEMIBIYRXgIeA9YDTgNYxxtExWgHMTAhpfe8tt6Qdpdq3h+nTs06lpTVsCAMGQGmp33wlSVrahRemTc179IBFi7JOU+Fq1kydaP7yF/jsM7jqKvj442X3Pp07F/r2zSajJEk/S9eusGABjBjB4MFQVJQ+5gEOankQJ+1wEgNeGMAbU9/INqckrcCqzjB/HNgZeAMYAETgpBBCxxUdFRVYy9GlCzz4YFrju+ee8OmnWSfS0k49FXbbDXr2hJkzs04jSVL+WHfddGH5n/+Ee+7JOk2latwYevWChQuXf7+bhEqSqqSWLeGAA+DWW2m6yXz69YNHH4VHHkl3Dz5gMBvX35hTxpzCDwt/+MmXkqQsrE5LlkAqmt8M3LaSY0RuY2qljjwSnn4avvoqrfF9882sE6m8oqK0Aei0adCsGfu0b48NSiVJKnPiifDLX6am3rNnZ52m0jVrtvzxWrXg9dcrN4skSTlRUgKffw5jxnDmmbDttmmW+bffwvprrc+th97KO1++w5XPX5l1UklaxqoWzPctd7Rf6vbyjvY5T6qV23NPePHFtMPU3nvDU09lnUjlvf9+Woc9Zw4hRmxQKklSmaIiGDIEvvgibWhezfTvn1q+lle7NtSpA7vumv5csOueJKlKOfhgaN4cbr6ZWrXS/LFJk+CKK9Ldh7U6jOLtiun/fH/e/uLtbLNK0lJWqWAeYxy3ukdFB9cKtG4NL7+cdpY6+GCLsfmkb9/Ux608G5RKkpTsthucdBIMHpyaelcjxcUwfHiqK4QQad487en+2WeL90Tdaiu48cZl/5SQJCkv1aiRepmXlsL48ey1F5x8Mlx7bZpLBnDDgTew4VobcvKYk5m/cH6WaSVpCavTkqUghBBahRDeKnfMCiGcFULoF0L4T7nxg7POusaaNIHnnkszzk84AQYNyjqRYMWNSG1QKklSctVVaWr1OedknaTSFRfDxIkwduw4Jk5Mtxs0gOuug7ffhl12SUvZd9op1R4kScp7nTql5VJDhwIwcCCss07q1hIjbFhvQ4YdMoy3vniLq1+8OuOwkrRYtSuYxxg/iDG2jTG2JfVknws8XHb34B/vizE+ll3KHFhvPXjiCTjmGDj33PTFc9GirFNVbytqUFpUBA89lP5ikCSpOmvcGC66KO0M9sQTWafJG9tsA08+mfZ4nzUL9t0X/vCHNANdkqS8tdFG6QPrrrtg1iwaNkz7fJeWLl4Mf1Tro/hDmz9w2bjLeG/ae5nGlaQfVbuC+VL2Az6JMU7KOkiFqFsX7rsPzjgjLW8uLobvv886VfW1vAalderAppvC0UfDoYfCv/+dTTZJkvLFmWfCllumXiQ//JB1mrwRAvzudzBhAvTrB488Aq1apV6w8+ZlnU6SpBXo1g3mzIG77wbg1FNTF7aePeG//00PufGgG1mv7nqc/JeTWbDI3mOSslfdC+bHAveWu909hPBOCGFkCGH9rELlVFER3HBDuox7332pr/msWVmnqp7KNSiNIaRGpbffnork112X2ui0aZO++XphQ//P3n1HR1V9bRz/noRulCZdktAMTbogRQggCNLsrxiVHpo0EUGjiGIUFURpCtIVu1IUQUAMWFAUpCmgPyHBgmCXEBWB+/6xEwmQKCXJTTLPZ61ZkzkzmdmTSXLv3fecvUVEAlX+/Haif+dOmDLF72iynYIF4d57LXF+xRU2Ib96dVi8WIvVRMQfycfP+51z21KN5Z6Sp3J2GjaE+vVh6lTwPIKCrAHojz/C3XfbQ0qcU4KpV0xlw94NjP9gvL/xiogAefwOwC/OuXxAZ+DO5KEngbGAl3w9AeiZxvdFA9EApUqVIi6DikgmJiZm2HOlqVEjSt15JxGPPEJSvXpsefhhDhUvnnmvJ2krVw7mziUxMZGQkBAbe+89qFuXfLNnU3nqVErecw9JM2bwxdCh/Fqvnr/xSobJ9L9xEZHcpEMHaN8e7rvPTjiXKuV3RNlOeDi88gqsWmW1za+8Ei6/3OZJRET4HZ2IBJi5wBRg/gnjEz3PU/Yz0DlnRct79rRaLC1bUrcu3HqrNbPu3t36dFxX4zqu+ewa7o27l84Rnf2OWkQCXMAmzIH2wEbP8/YBpFwDOOeeBt5I65s8z5sBzABo0KCBFxkZmSHBxMXFkVHPla7ISGjRgpBrrqHJ8OHw1ls6ovJJup/3ddfB8uUUGjiQOsOHw403WtPW0qWzPEbJWFnyNy4ikls4Z7PMa9aEmBiYOdPviLKtyy6zpqBTp9rM85o1rZrNPffAeef5HZ2IBALP89Y658L9jkOysRtusN5qU6daIw7g/vvhpZegf3/48EMIDoapV0wlLj6Onot7Elsp1uegRSSQBXJJlq6kKsfinCuT6r6rgNzZbeLyy+2sblISNG1qWybJXtq1g23bYPRomzpWtartWBw54ndkIiIiWSciwuqZz54NGzb4HU22ljevJcm/+AJuvhnGj7cf3zPPqOe7iPgq95U8lTNTsKDNMF+0CL75BoDChe3c+CefWOVSgFIhpZjcfjIfffsRr3zzio8Bi0igC8gZ5s65QkAboG+q4Uecc3WwkizxJ9yXuzRoAB98YInZVq3stG7Hjn5HJakVLHhsGfrAgbZebe5cK/bWoIHf0YmIiGSNe+6xrO/gwVbCzDm/I8rWSpWy8wv9+lnP91tusV2HKVOgXj1YsMAm7O/Z04LQUOtHHhXld9QikkudUslTOL7saYkSJXwvY+h3KUW/Xz+zYihQty6Njh4l4a67iO9pvwqlSkG9erUZMeJcSpX6iGLF/qa0V5pmxZsxe/dsGr/ZmNBCoRkax6nKrZ9DTovB79dXDNknhqx+/YBMmHuelwQUP2HsZp/C8UflypY079ABunSB6dOtXbVkLxdeCCtWwIsvwrBh1jBlwABrDFqkiN/RiYiIZK7CheGhh6BXL3juOWV3T1HDhrBuHcybB6NG2bn2yEhbWPjHHwCOhASIjrbH68cqIhntVEueJj/2n7KnERERGVb29Ez5XUrR79fP1BgWLCB8xQrCZ86EfPkA27zXqgWLFjVlfnIV/JcvfpkLn7iQ6d9PZ233tQQHBWd8LP8hV38OOSgGv19fMWSfGLL69QO5JIuULAnvvANt2kCfPjB2LHie31HJiZyzmm87dthM8yeftDItzz2nz0tERHK/lG5gd9wBiYl+R5NjBAVBjx5WpmXoUNvls2T5MUlJNuNcRCSjBUzJUzk9AwfCvn3w2mv/DEVE2Cb+mWdgzRobKx1Smlsr38oHX3/A5PWTfQpWRAKZEuaBLiQEXn/d1uyOHm0dN1QrO3sqXBgmTYL16yE01KaDXXYZ7Nzpd2QiIiKZJyjItn/ffQcPPuh3NDlO4cLw2GPpV7MB8XZrAAAgAElEQVTZsydr4xGR3Mc59zywDohwzn3jnOuFlTzd6pzbArQEhvkapGQP7dpBxYrWoyuVu+6CChUsHXHokI21KdmGjhd25K637+J/P//Ph2BFJJApYS7WKWruXFuzO306XHPNyVOQJPuoX9/WWU+bZk3QatWyGq/6zEREJLdq3Ni6WU6YAF995Xc0OVLov5SA7d4dli+Hv//OsnBEJBfxPK+r53llPM/L63neBZ7nzfI872bP8y7yPK+W53mdPc/b63eckg0EBVlW/L33YMuWf4YLFoTJk2H7dmsECuCc46kOT5EvOB+9lvTiqKcu1iKSdZQwF+Oc1QidNAmWLLGZyz//7HdUkp7gYNvR2LkTrr/eaprXqAFvvul3ZCIiIplj3Dg7yT98uN+R5EixsVCo0PFj+fPDpZfCokXQvj2UKWMNQ+PitOBQREQySc+eUKCATQBLpUMHuOoquP9+SEiwsXLnlWPi5RNZm7CWaR9PS+PJREQyhxLmcrxBg6zB5CefQLNmWqeb3ZUqZcXeVq+2o94OHeDaa+Gbb/yOTEREJGOVLQt33w2LF8PKlX5Hk+NERcGMGRAWBs55hIXBrFlWL3bfPvuxtm1ruxUtW8IFF8CQIbaoTS1TREQkwxQrBl27wrPPwm+/HXfX44/b9dChx8a61+lOu8rtGLlqJLt+2ZWFgYpIIFPCXE523XXw1ltWK7RxY9i61e+I5L+0bAmbN1tt16VLrSnohAlaWy0iIrnLsGFQqZJlcrWNO21RURAfD6tXryE+3m6DnXPv3Nn6ie/fb3MnGje2Sn1Nmlhd2ZEj4dNPlTwXEZEMMHAgHDwI8+YdNxwaCvfeayuf1q0rDlhplhkdZxDsgum9pLdKs4hIllDCXNIWGQnvvmtfN2tma3Mle8uXD+68Ez7/3D6/22+3eucffOB3ZCIiIhkjf37rYLl9+0lLuSVjnHOOVXt77TWbeT5vnlV9e+wxqFfPzsmPHm27GyIiImekfn1o1Mi25SeciR02DKpXh0mTKpOUZGPlC5dnQtsJvBP/DjM2zPAhYBEJNEqYS/ouusjW4ZYrB5dfDi+/7HdEcioqVIDXX4eFC+GXX6BpU+jdG376ye/IREREzl6nTlY75N574Ycf/I4mVytcGG65xRavff+9lXS54IJjrVNq1bLFbSl9WBcsgPBwaNWqBeHhdltERCRNAwdaT6633z5uOG9eePJJ+P77gjz44LHx3vV6c1nFyxixcgQJvyZkcbAiEmiUMJd/FxpqHawbNID/+z9rXS3Zn3Nw5ZU2A2/ECJseFhEBs2fDUS1hExGRHMw5K3J68CDExPgdTcAoXhz69LG8xrffWp/4c8+1j6ByZahYEXr0sEZtnudISIDoaCXNRUQkHdddB+efD1OnnnRX8+bQtu33PPII7NhhY845ZnaaCUCf1/vgqUaYiGQiJczlvxUrBqtWQZcuMHgwjBqlApY5RUgIPPKIFR2tVg169bK9D9WlFxGRnKxaNWtUPnMmbNzodzQBp0wZ+/G//74lyB991JLoJ5aVT0rSOQ0REUlHgQK2EnrJEtiz56S7+/X7inPOsYnoKemHsCJhPNrmUVbuWsmsT2dlccAiEkiUMJdTU7AgvPIK9O0LDz8M3bur2VZOUrMmrFljM8x37IC6dW3meWKi35GJiIicmdGjbWba4ME6ke+j0FBrm5LebmEaORARERHTr59dT59+0l1Fi/7NQw/B6tXwwgvHxqPrR9MyvCW3vXUbX//2dRYFKiKBRglzOXXBwVZM7P77Yf58qyGqhGvOERRka6V37rTr8eOtm8rChUo0iIhIzlOkiBXQfv/944+kxRehoac3LiIiQlgYdOwITz8Nf/110t19+sDFF8Ntt8Fvv9lYkAtiZueZHPGOEP1GtEqziEimUMJcTo9zcM89tkFbtQoiI2HfPr+jktNRvLh9fu+/D0WLwtVX28mP3bv9jkxEROT09OgB9erZqqmDB/2OJqDFxkKhQsePBQfbuIiISLoGDrQm3q+8ctJdKXP29u+3NESKikUr8vBlD7P8f8uZt3leFgYrIoFCCXM5M717w6JF8Pnn0LQp/O9/fkckp6tJE9iwASZMsHIt1avbTL1Dh/yOTERE5NQEB1v3yW+/hbJladGqFYSHq9OkD6KiYMYMmyzonEfRonDkSJoTBkVERI657DKoUiXN5p8A9evDgAF2d+q2JQMuHkDzsOYMXT6Ub3//NouCFZFAoYS5nLmOHa2g2K+/WvL1k0/8jkhOV548tr5t+3bo0ME6c9WuDe+843dkIiIipyY+3hLnv/+O8zzrQhkdraS5D6Ki7ONYvXoNP/5oCxGHDrWPREREJE1BQZYRX7cOPv00zYeMHQslSkD//nYyFqw0y6zOszh05BB93+ir0iwikqGUMJezc8klVtqjUCE7KnrrLb8jkjNxwQW2BO7NN22GeatWcNNNKrcjIiLZX0zMsaPnFElJNi6+CQqCOXOsTUrPnnD0qN8RiYhIttW9u+UU0pllXqQIPPYYrF8PM2ceG69crDIPtn6QpV8u5dktz2ZNrCISEJQwl7MXEWFngytXtlnn8+f7HZGcqfbtYds2KxD38sv22U6bdnIiQkREJLvYs+f0xiXLhIfDxIm2IHHaNL+jERGRbKtIEVum9Nxz8MsvaT6ka1do2RLuvNNqmqcY1HAQTco3YcjyIew9sDeLAhaR3E4Jc8kYZcrA2rXQvDl06wYPP2xTiiTnKVgQ7r8ftmyBBg2sCUvjxlbvXEREJLsJDT29cclSvXrZ+fg77oAvv/Q7GhERybYGDoQ//rDlSWlwzk6+JibaNiVFcFAwszvP5o/Df9B/aX+VZhGRDKGEuWSc886zkh433ACjRsGQIZqZnJNFRMDKlXaW/+uvoWFDGDQIfvvN78hERESOiY21ZdypFSpk4+I752z5fIECNqdCu4YiIpKm2rWhaVPLiqdTx6tqVRgxAubNs/l6KSLOj2Bsy7Es3rmYF7a9kEUBi0hupoS5ZKz8+a3J1m23weTJljz/80+/o5Iz5Zytfdux41hr8qpV4fnntYJARESyh6gomDEDwsLwnIOwMLsdFeV3ZJKsbFmYMsUq+E2Y4Hc0IiKSbQ0YAF99BWXK0KJVK6vtdUIT75gY29QPGAB//31sfNglw2hUrhGDlg1iX6J6cUkusWABhIen+/cgmUcJc8l4QUF2NDR+vDWSbNcOfv3V76jkbBQubCdAPv7YGoTeeCO0aQNffOF3ZCIiIpYcj49nzerVEB+vZHk21LUrXHONtUnZts3vaEREJFtKyYDv34/zPEhIgOjo45KEhQrZoelnn8Hjjx/71uCgYGZ3mc2BQwe4ddmtWRy4SCZYsMB+/xMS0v17kMyjhLlknuHD7Q/5gw+stvm33/odkZyt+vXhww9tpvknn8BFF8Ho0VZrTkRERCQdzsGTT9o5+FtugUOH/I5IRESynXvvPXksKcmmlafSqRN07gxjxlj10BTVS1Tnvsj7eOXzV3j5s5czN1aRzBYTY7//qaXx9yCZQwlzyVw33mh1zXfvtsaR27f7HZGcreBgW/+2Ywdcdx2MHQs1a8Ly5X5HJiI5lHNutnNuv3NuW6qxYs65lc65L5Ovi6a6707n3P+cczudc5f7E7WInK4SJaxazqefqsS8iIikYc+eUx6fNMmqhA4devz47U1up0HZBgx8cyA/HPwhE4IUyQKed1p/D5LxlDCXzHfZZdaR49Aha+Lx/vt+RyQZoXRpePZZePttyJsX2re3BLpWEojI6ZsLtDthbBTwtud5VYC3k2/jnKsO3ADUSP6eac654KwLVUTOxpVXws03W8L8k0/8jkZERLKV0NC0x889F3766bihsDBb7PzaazZHL0WeoDzM6TKHX//8lcHLB2disCKZwPNg5Upo1iz9vnHp/Z1IhlLCXLJG3brW6en88y2BvmiR3xFJRmnVCjZvhgcegDfesKagjz0Ghw/7HZmI5BCe560Ffj5huAswL/nrecCVqcZf8DzvL8/zdgP/AxpmSaAikiGeeMLOu99yi3rDi4hIKrGxVqQ8teBg+P13qFAB7r4bfj62y3jbbVCtGtx66/FVQmuWrMnoFqN5YdsLLNy+MIuCFzkLnmeTEZs3h7ZtbRZ5jx4n/z0UKqRlelkkj98BSACpUMFml3fsaF2fpk2Dvn39jkoyQv78Vkera1cYNMjq18+bB089ZaV4REROXynP8/YCeJ631zlXMnm8HPBhqsd9kzx2EudcNBANUKJECeLi4jIt2MTExEx9/qx4Db2H7PEagfIeBg8uysiRtenefQ/9+u3KlNc4Gzn9+bPiNfQeRCTDpTTtjonB27MHFxpqycE6deC+++zryZNhyBAYNox8RYsybRq0bAkPPQT333/sqUY2Hclr21+j/9L+NA9rTvFCxf15TyL/JS7O6vevXQvlylnPuF69LM/SuvXJfw9qbp8llDCXrFWiBKxeDddfD/36WfmO++6zTlCS81WsaLPMFy60nZgmTaB3bxg3DoprB0VEMkRaG4w01yt6njcDmAEQERHhRUZGZlpQcXFxZObzZ8Vr6D1kj9cIlPcQGQm7dsGMGaHcemsozZpl/GucjZz+/FnxGnoPIpIpoqIgKoo1J/59vvQSbN1q+YOxY62I+dChRA4dyk03FeHhh+Gmm+DCC+3heYPzMqfLHBo83YAhy4fw7NXP+vJ2RNK1dq0lyuPioGxZOxnUuzcUKHDsMen9PUimU0kWyXrnnAOLF0PPnrah69NH5TtyE+fg6qutwevw4TBnjpVpmTMn/RpcIiIn2+ecKwOQfL0/efwboHyqx10AfJfFsYlIBnj0UQgPh27dIDHR72hERCTbu+gieOUV2LTJSoPedx9UqMD4MhMoWMBj4MDjDzlrl65NzKUxLNi6gNd3vu5f3CKpvfeezRxv0QJ27LBadV99ZbWFUifLxVdKmIs/8uSBmTOtBtmsWXDVVZCU5HdUkpFCQmD8ePj0U4iIsBMkzZvDtm1+RyYiOcMSoFvy192AxanGb3DO5XfOVQCqAOt9iE9EztK559r59N27YeRIv6MREZEco3Zt6/b56afQogWlHr2dB/8ewapV8NLc4/MKd116F7VK1aLvG3355Y9ffApYBCtR3KYNXHopfPYZTJxoy+0GD1aiPBtSwlz845zNMJ82DZYutTNsP/7od1SS0S66yJYazZpls87r1oU77oCDB/2OTESyCefc88A6IMI5941zrhcwDmjjnPsSaJN8G8/zPgNeAj4HlgMDPc874k/kInK2WrSAoUNtd3DlSr+jERGRHKVOHVi0CDZsoG/r/1GfTxjW63d+Hz0eDhwAIF9wPuZ0mcP+g/sZ9tYwnwOWgLRunTXybNYMtmyBCRMsUT50KBQs6Hd0kg4lzMV//fvDq6/a2eGmTSE+3u+IJKMFBdkM8x07bN31o49aO/NFi1SmRUTwPK+r53llPM/L63neBZ7nzfI87yfP81p7nlcl+frnVI+P9Tyvkud5EZ7nLfMzdhE5e7Gxxxaj/fab39GIiEiOU68ewa8v4ql5hfjeK8nosXmgQgXrpZWYSL0y9RjVbBTzNs9j2ZfadZQs8tFH0K6d9XbbtMnyILt2wW23QaFCfkcn/0EJc8kerroKVq2C/fuhcWP7ZyK5z/nnWyme996DIkXsc+/cWSdJREREAljBgjB/Pnz3nU22EhERORMNbqlO/wFBTA4awqaqN8Cdd1ri/JFHuKf+bdQoUYM+r/fhtz91dlYy0ccfwxVXwCWXwCefwMMPW6L89tutp5/kCEqYS/bRrJklUvPksVrXq1f7HZFklqZNYcMGq3H+zjtQvTo89BAcOuR3ZCIiIuKDhg0trzF3LixZ4nc0IiKSUz3wAJx/vqP/kSkcfX8d1K8PI0eSv0pV5hxozd7EvQxfMdzvMCU32rABOna0nZqPPrIcR3y8laQNCfE7OjlNSphL9lKjhtV3CguzpSsvvOB3RJJZ8uaF4cOtrnn79nDXXVaDLi7O78hERETEB6NHQ61aEB2ttjYiInJmiha1eVkffgizPrsEli+HDz6AunW5eNQkRmwowKxPZ7HiM52dlQyycaOtnG/QwH7XYmMtUT5qlBLlOZgS5pL9XHABvPuulWbp2tU6B0vuVb681bBfuhT+/BNatoRbbrHyPCIiIhIw8uWz0iw//wwDB/odjYiI5FQ33WRNpUeOhB9+wHILb70F773HmD8aUfUH6DPnKn6fOA7++MPvcCWn2rQJrrzSVjG8+y6MHWuJ8rvugnPP9Ts6OUtKmEv2VKSIbdCuucYaItx+Oxw96ndUkpmuuAK2bYOYGFtZEBEBTz0FR474HZmIiIhkkdq1YcwYeOklePFFv6MREZGcyDmYNg0OHLCk+T+aNqXAitXMafck34Qc5Y7Vd0KlSjBpkk3eEjkVW7bA1VdD3bq2Qv6++yxRfvfdcN55fkcnGUQJc8m+ChSwI6WBA2HCBLj5ZtW4zu0KFbKic1u22Manf3/rKL1xo9+RiYiISBa54w4r/zlgAOzd63c0IiKSE1WvbhVA58yxVmmpXdKxH8OaDGd6A1jdqCQMGWKJ8ylTlDiX9G3dCtdea2f3334b7r3XEuWjR0Phwn5HJxlMCXPJ3oKDYfJkePBBeO456NABfv/d76gks1WtahugZ5+FhAS4+GIYPBh+UzdzERGR3C5PHpg3D5KSrJ655/kdkYiI5ET33AOhoTYP6++/j79vbMuxXFj8QnpF/kbiyqWWMB80CCpXhmnTcJqsJ8kK7d4N119vjVZWrLBfrPh4WxJXpIjf4UkmUcJcsj/n4M477dTwO+9YMbLvv/c7KslszkFUFOzYYXs4U6ZAtWpWrkVHziIiIrla1arw0EPwxhswd67f0YiISE50zjlWbWXbNrtOrWDegszuPJuEXxMYdehNWLMGVq2C8HAYOJBGN99sJUKVOA9c27fDDTdwca9esGyZlY+Nj4f777fuspKrKWEuOUf37vD66/DFF1am44sv/I5IskKRIpYs/+gjKFvWGsG2bQtfful3ZCIiIpKJBg+2eRJDhtiCMxERkdPVuTN07GjVM7755vj7moY2ZXCjwUz9eCprEtZC69bWvHHFCv4qUcImblWpAjNmKHEeSHbsgBtvhBo14I032NO1qyXKH3gAihXzOzrJIgGZMHfOxTvntjrnNjnnPkkeK+acW+mc+zL5WqeLsqP27a2pQmIiNG1qSVQJDBdfbJ/3lCmwfj3UrGl7PaoxJyIikisFBdkCw6NHoWdP9X8XEZHT55zNLj96FIYNO/n+2FaxVCpaiZ5LenLw0EH7hjZt+HTyZFi+HMqUgb594cILYebMk2u7SO7xxRdw002WKF+yxJqqxMezu08fKF7c7+gkiwVkwjxZS8/z6nie1yD59ijgbc/zqgBvJ9+W7Ojii+GDD6z7cKtWsHSp3xFJVgkOtiawO3das43777fE+Vtv+R2ZiIiIZIIKFeCxx2D1anjySb+jERGRnKhCBbj7bnjlFcuBp3ZOvnOY1XkWu37ZRczqmGN3OAeXXw7r1sGbb0LJktCnD0REwOzZSpznJl9+CbfcYiVgFy60brG7d8O4cXD++X5HJz4J5IT5iboA85K/ngdc6WMs8l8qV7akedWq0KWLTT+SwFG6NCxYYDXmgoOhXTtrwvHtt35HJiIiIhmsTx/LWdxxhyqyiYjImRk+3HLdAwfCH38cf1+L8BYMvHggkz6axHt73jv+TudspftHH1ljjeLFoVcvy0XMnQuHD2fZe5AM9tVXVvq3WjU7mzJsmCXKH3kESpTwOzrxWaAmzD1ghXNug3MuOnmslOd5ewGSr0v6Fp2cmlKlrDxLq1a2TveBB9QMMtC0bg1btsDYsVbfvmpVePxx7bSIiIjkIs7BrFmQLx906ABhYdCqVQvCw+38uYiIyH/Jnx+mTYNdu+Dhh0++f9xl4wgrEkbPxT1J+jvp5Ac4Zxuh9eutXEeRItCjhyVb58/XMWhOsmuX5ZAiIuDFF61pyq5dMH68rSQQAfL4HYBPmnqe951zriSw0jm341S/MTnBHg1QqlQp4uLiMiSgxMTEDHuuQONGjCACKH3PPXz78cd8OXiwzTrOxvR5Z7BmzSgwaxZVJk2i+LBhJE6Zwhe33cbv1av7Hdk/9JmLiIicuXLl4IYb4KmnUkYcCQkQnTz1JSrKr8hERCSnaNXKejk+9JBtN6pUOXZfSL4QZnWeRev5rRn9zmg65uuY9pM4B506WSfRJUtgzBjo1s0m8I0eDV27Zvt8RMBKadw5b559RrfeCiNHWp16kRMEZMLc87zvkq/3O+cWAg2Bfc65Mp7n7XXOlQH2p/O9M4AZAA0aNPAiIyMzJKa4uDgy6rkCUuvWcOedlHvkEcrlyQPPPgsFC/odVbr0eWeSrl3htdcIGTKEerfeamu4H3ooW3Sy1mcuIiJydt588+SxpCSIiVHCXERETs2ECVZZ5dZbrZ65c8fua1WhFX3r92XihxOpULsCkUSm/0TOWXnYzp1h0SJLnN9887HE+f/9nxLn2UVCAsTGWinf4GDo3x9GjYKyZf2OTLKxgCvJ4pw7xzl3bsrXQFtgG7AE6Jb8sG7AYn8ilDMSFGTrqh5/3Jo0tG0Lv/zid1SS1ZyDa66B7dut/tisWbbMat48lesRERHJ4b7+Ou3xPXuyNg4REcm5Spe23OmKFVa2+kSPtHmEC867gEe+eIQ/D//530/oHFx1FXz6Kbz6qtUPi4qCiy6CF16AI0cy/k3IqdmzB/r1s6UE8+ZB375Wt3zSJCXL5T8FXMIcKAW855zbDKwHlnqetxwYB7Rxzn0JtEm+LTnNkCG2UVq/Hpo1S//ISnK3c8+1qQMbN9rGsXt3aNECPvvM78hERETkDIWGpj2eNy+sXp21sYiISM7Vvz/UrQtDh8Lvvx9/33n5z+PpTk+zJ2kPY+LGnPqTBgXB1VfDpk3w8st2u2tXqFULXnoJjh7N0Pcg/+Kbb2DAAKhcGWbPht694X//gylTrMabyCkIuIS553m7PM+rnXyp4XlebPL4T57ntfY8r0ry9c9+xypn6PrrbW3VN99A48awbZvfEYlfatWC996DmTMtWV6njtUoO3jQ78hERETkNMXGQqFCx4/lywchIVadr107y1OIiIj8m+Bg64mxd69VUjlR20pt6VC6A49+8Cgff/vx6T15UBBcey1s2WINJcHKs9SubVPalTjPPN9+a7V2KlWyHEDPnpYonzYNypf3OzrJYQIuYS4BomVLWLvWNkaXXmpfS2AKCoJevWDnTrjlFnjkEaheHRar6pKIiEhOEhUFM2ZAWBg45xEWZhPHvv0Wxo+3BYZ168JNN8Hu3X5HKyIi2VnDhlahY9Ik2Lz55Pv7VepH2XPL0n1xd/46/Nfpv0BQkE3m27IFnn8eDh+G666zDdVrrylxnpG++w4GD7ZE+fTp1oT1yy/trEh6y9NE/oMS5pJ71a4N69ZBqVJW0/zVV/2OSPx0/vlW0/zdd+G88+DKK61BS3y835GJiIjIKYqKsk336tVriI+32wUKwPDhsGuX9fB69VVrYTJ0KPz4o98Ri4hIdvXgg1CsmJVoOTF/HZInhBkdZ/D5D58zdu3YM3+R4GC44QZb+b5gAfz1l/XdqlfPmoWq19aZ27vXNvaVKtks8ptugi++OHZ2XeQsKGEuuVtYGLz/vm2MrrsOpk71OyLxW7NmVtv80Uet4Gn16jBuHBw65HdkIiIichaKFIGHHrLV1926weTJULGilXJRNTYRETlR0aJ2WLhuHcyZc/L97au0p3ud7ox7bxwb9248uxcLDoYbb7RSoc88A0lJ1iy0fn1YskSJ89Oxbx/cdptt5KdMsVrxX3xhZVgqVPA7OskllDCX3K94cVi1Cjp1snpWMTHaGAW6vHnh9tth+3YreHrnnbY0bs0avyMTERGRs1SuHDz9tE3ma90a7r7b+n5Nnw5//+13dCIikp3ccotVcb3jjrRXJT3W9jFKnlOS7ou6c+hIBkyyCg62mdCffw7z5lnX0S5d4OKL4Y03lKv4N/v323F8hQrwxBNWG37HDqvPVrGi39FJLqOEuQSGQoVsfW6fPrbuqmdPHTGJNf547TV4/XU7wx8ZaVPS9u/3OzIRERE5S9WqwcKFttiwUiXo1w9q1rRdQuUjREQEwDmr5vH771bW60RFCxZlesfpbN2/lQfffTDjXjhPHsvW79hh09t/+cUm+TVqBG++qQ1Vaj/8YGc0KlSAiROtqeqOHTB3rp0RF8kESphL4MiTx6YWjRlj/1i7dIHERL+jkuygY0dbGnfXXdaQpWpV+11RIxYREZEcr0kTa2GyZIntDl57LVxyiRaWiYiIqVkThg2zllcffHDy/Z0iOnFTrZuIfTeWTd9vytgXz5MHune3BPCsWZYc7tABLrmEYh99FNiJ8x9/pOKMGZYonzDBSth8/jnMnw9VqvgdneRySphLYHEO7r3XmkC89Ra0amUbJJFChazI6ebN1jC2Xz9o3Bg+/dTvyEREROQsOWcT97ZssZXb331nC8s6dLAxEREJbKNH2wLk/v3h8OGT73+i3RMUL1icHot78PeRTFitnjevrYT/4gurK7ZvH7VGjbKzvm+9FViJ859+sslsFSpQ/oUXoHNnm+D27LPW1VskCyhhLoGpTx9bo7t1q22Adu3yOyLJLqpVs2agzzwD8fHQoAEMGWJr9ERERCRHCw6GHj0sH/HIIzaTsE4dq8iWkAALFkB4OLRq1YLwcLstIv/OOTfbObffObct1Vgx59xK59yXyddF/YxR5L+EhFhZ7C1boGTJk7cDxQoW48kOT7Lp+008/P7DmRdI3rzQuzd88QU7b7vNzvC2awfNmsHKlbk7cf7zz9Z4pEIFFjyUQPjRXQR7Rwj/4DkWbESqRucAACAASURBVKjqd3QSYJQwl8DVuTO8/bb9U27cGDZs8DsiyS6cs0YsO3ZA374webKVaXnxxdy9gyIiIhIgChaEESNszsSIEbaJr1TJVsUnJIDnORISIDpaSXORUzAXaHfC2Cjgbc/zqgBvJ98WydaSkiAoyMqJp7UduKraVdxQ8wbuX3M/W/dtzdxg8uVjb6dOdob3ySdhzx5o2xaaN7c8Rm46Lv3lF5viX6ECxMayoNpYogs8Q0JSCTy0PRZ/5PE7ABFfNWlinaAuv9zW5b72GrRp43dUkl0ULWodYLp3t7V5N9xg67inTFHNNBERkVygaFF4+GG49VZbZHbw4PH3JyVBTAxERfkTn0hO4HneWudc+AnDXYDI5K/nAXHAyCwLSuQMxMSc3MYqKcnqmxcpYrc7BU9mWdDbXD2/BxOqfUiwy7y02pYtxTh4MD+U7weTe8GKFfDSi3DZY1BjhW2catXKtNc/FkMmPXliIixeDIsWwR9J0GQk3Hgjw+4LJ+nP4x+q7bFkNSXMRapWhXXroH17uOIK61B9001+RyXZScOGsH69Jc/vvhsuushaqI8aBQUK+B2diIiInKXy5e1gPC179mRtLCK5RCnP8/YCeJ631zlXMr0HOueigWiAEiVKEBcXlzURpiMxMdHXGPx+/UCOYc+eFoA7afyHH6Bjx5Rb50P1qfx2/fV0eXg8vJeZiydSJ8PzAh2SL8BnwF2Z+NJpxpDRQoCo5AvwQfIlHQkJHlWrHqB06T/TvBQocDT9bz4Lgfr3kN1iyOrXV8JcBKBsWVi7Fq68Em6+Gfbuhdtvt9IcImBFTwcNgmuvheHD4b77bE3Y1Km2NE5ERERytNBQK8eS1riIZB7P82YAMwAiIiK8yMhIX+OJi4vDzxj8fv1AjiG97UDp0rBkSeqR6xi18VrebXsvz9zXmYrnVs+UeDZs2ED9+vXTvvOvv6wv27y51iSzwcVWt6ROnayL4XQlJloNtAULIPEANG8B0X3gwuMbeXbuDN9/f/K3h4Q4wsLOIz7+PNatg0OHjr+/ZEnrQxIebtVdUr4OD4ewMCvHdiYC9e8hu8WQ1a+vhLlIisKFYflyuOUWuOMO+PZbeOwxK2ImkqJMGXjuOetgPnCglfO5/nqYONFOvIiIiEiOFBtruYbUM80LFbJxETlt+5xzZZJnl5cB9vsdkMh/SW87MH48XHzx8Y99vvpUqk99h4m7evJ+z/cJDgrO8HgOHjxw0usekx+a3QAPdIHp02HcOIh+Ei67zCZ3NWmSBTGcogMHrC/YhAnWQ65zZ7h3PNSrl+bDx49P+3N46qljJVmOHrWkenz8scvu3Xa9caOdS/j77+Oft3Tpf0+o589/lu9TchUlzEVSy58fnn/ekqJPPGEzzefP139OOdlll1kL9UcesT2rZctg7FhLoufRv1YREZGcJuUgPCYG9uzxCA11xMaqXqrIGVoCdAPGJV8v9jcckf92OtuBkueUZMoVU+j6alcmfjiR25vcnrXBpihYEIYOtQzzU09ZY46mTW0V9H33wSWX+BMX2IzyKVMsA/7TT1bXZswY+I8Z66fyOQQF2Xy1smXTPjdw9Kilc1KS6KmT6uvXwyuvwOHDx39P2bJpJ9T37SvIoUOQL98Z/hwkR1JWR+REQUE2W7hcOZtp/sMPdnqycGG/I5PsJn9+uOceuPFG6xY2dCjMnWs7Ko0a+R2diIiInKaoKLvExa3xfemzSE7hnHsea/B5vnPuG+BeLFH+knOuF7AHuM6/CEVO3elsB/6vxv/x4mcvcvfqu+l0YScizo/418dnqkKF4LbboG9fePJJm9jVuDG0a2eJ84YNsy6WgwetdOmjj8KPP1qvuDFjTp6m/y/OdnscFGQpnXLloFmzk+8/cgS++y7thPoHH1jlmCNHUh7diJtvtudKb4Z6+fKQN+9phynZmBLmImlxDkaMsJnmPXpA8+Y2g1glNyQtlSrBm2/Cq6/CkCG2YxIdDQ89ZOMxMbTYs8eK4mmqmoiIiIjkIp7ndU3nrtZZGohIFnPO8WSHJ6k+tTo9l/Rkbfe1mVKa5bScc471Y+vf/1jSulGjM0pan7aDB48l63/4wZL1Y8Zky8lkwcGW5C5f3tI9Jzp82Kr07t4Ny5fvoECBqv8k1NeutSqtR1P1GA0KggsuSD+hfsEFWoie0+jjEvk3N91knSOuucaSoG+9BVWr+h2VZEfOWUPQyy+He++FSZNsK/rXX3DokPVaT0iwRDooaS4iIiIiIpLDlQ4pzaT2k7h54c1M+mgSwxoP8zskc845tmJ+wAAri/LoozbL/BTLopyWpKRj5WD277dyMGPGWA4lh8qTx+qah4UBfE9k5PF5oL//hm++SXuG+urVlmz3vGOPT0nQp5dQL1fOHiPZhxLmIv+lbVtYswbat7daYG+8kaP/8UsmO/dcaxbbrZvtkJzYujspyYqxKWEuIiIiIiKS40VdFMWLn71IzOoYOkV0onKxyn6HdExICIwaZb22Jk+2euINGljjzTFjoG7dM3/uP/441nB03z7r8zVmjOVNcrm8eS3pXaFC2vcfOgRff512Qn3FCisHk1qePLYgPb2EeurZ7JI1lDAXORX16lkhq3btoHVreOEF28CIpKd27ZPbcqfYsydrYxERkbO2YEFK86kWqrAlIiIi/3DO8VSHp6gxrQY9F/ckrnscQS7I77COd+65cNdd1ntr0iSYMMHyHFdeaUnu2rVP/bn+/BNmzLBE+d690KoVvPwyXHpppoWf0+TLZ5VbK1VK+/4//0w/of7mm/D998c/Pk+e5scl0E9MqJcubWVhJOMoYS5yqipVgvfftyVMV11lS4769PE7KsnOQkOtDMuJ8uWz08pt2lgpFxERydYWLLCKWklJAE4VtkREROQ45c4rx+PtHqfH4h5MXT+VQY0G+R1S2s47D+6+GwYNgieesNXRixbB1VdbadFatdL/3j//hJkzrVfXd99BZCQ8/zy0aJFl4ecWBQpAlSp2Scsff9g8u5SE+tq133D0aCi7d8OSJVb5JrX8+a18THoJ9VKllHo4XUqYi5yOkiWtINX119uR8nffwejR+s8jaYuNTZ1hMXnzQsGCVuu8USPbWenQQb9DIiLZWEzM8f/KQRW2RERE5Hjdanfjpc9eYtTbo+hwYQcqFq3od0jpK1zYchmDB8Pjj8PEifDaa9aX6957YfNmiImhxZ49Vny7ZUtYtcqKc196KTz7rI1JpihYECIi7AJQteouIiND/7k/Kcnm5p04Qz0+HjZuhB9/PP75ChTgX2eolyiRfkoiUFdZKmEucrpCQmDxYptdPmaMbTCmTVPLYzlZylYkJgZvzx5cytbl2mth3jw7M9+pE9SpY4nzq67SOioRkWwovUpaqrAlIiIiKZxzTO84nRrTatBrSS/evuXt7Fea5URFilheY8gQS5o//ji88op1oDxyBAe2wzNvnk2HXrXKSrBowpevChWCatXskpbEREuop5R5SZ1QX78efv755OdLK6G+fbulLf74AwJtlaUyfCJnIm9emDPHWhk/+KA1uHj+efsvI5JaVBRERbEmLo7IyMhj49HR0KOHna598EFLoteoYadur79eLbJFRLKR9CpsOWf/wm+91VY4i4iISGArX7g8j13+GH1e78P0T6bT/+L+fod0aooWhfvvh6FDLVv6++8nP+avv6ynm2R7ISGWXqhRI+37f/89/YT6Bx/Ar7+m/9yBssoym5/qEsnGnLPZwlOmwOuvW0fon37yOyrJSfLmhe7d7bTtc8+B58GNN9pp4rlz028aKiIiWSo29uRz4gUKwEUX2QFDWBjcdx/88os/8YmIiEj20atuL9pUbMMdq+4g4dc0zrhnZ8WKwYEDad/39ddZG4tkmvPOs/3YTp2sKs9jj1lFno0bbX/2l19g06b0FxIEwipLJcxFztbAgdYReuNGaNYs7SloIv8mOBi6doWtW2352znn2OzzCy+07uN//eV3hCIiAS0qyv4dh4WBcx5hYdbzatMm+Phj63U1ZowtXb37bp0/FxERCWTOOZ7u9DQAvV/vjed5Pkd0mkJDT29ccp0iRaB27cD+VVDCXCQjXHMNrFgBe/dC48bWIEPkdAUF2e/Sxo22aqFkSejbFypXhsmTUwqHiYiID6KibJnq6tVriI8/tgy1QQNYtMiS523b2mz08HAYORL27/cxYBEREfFNWJEwHm3zKKt2rWLmxpl+h3N60lpaV6iQjUtACeRfBSXMRTJK8+bw3nuW9GzeHN55x++IJKdyDjp2hA8/hLfesszL4MFQsSJMmGAdPEREJFupXdsWnG3bZstbH33U/n0PH27n00VERCSwRNePpmV4S4avGM7Xv+WgciapltZ5ztkSuxkzcn/RajlJWqssA+VXQQlzkYxUsyasWwcXXADt2sFLL/kdkeRkztl0xXffhbg469hx++2WgXnwwbQbsYiIiK9q1LC2FJ9/bv2cn3jCemcNHgzffON3dCIiIpJVglwQszrP4qh3lOg3onNWaZbkpXVrVq/muKV1EnDSW2WZ2ylhLpLRype3BGfDhnDDDXakLHK2WrSAVausZXWjRse6zI0Zoy5zIiLZUNWqMH8+7NhhBxZPPgmVKkH//mp3IiIiEigqFK3AuMvGsfx/y5m7aa7f4YjIKVLCXCQzFCtmNc2vvBKGDoU77oCjR/2OSnKDxo1h6VL45BOIjIT77rPE+Z13wg8/+B2diIicoHJlmDULvvzS+jnPmmVjvXvDV1/5HZ2IiIhktgEXD6B5WHOGvTWMb3//1u9wROQUKGEuklkKFrRipgMGWCHTbt3g0CG/o5Lcon59WLjQGsy2bw8PP6xiuSIi2Vh4ODz1lCXJ+/WDZ5+FiAjbPdi5ExYssMe0atWC8HC7LbnPgq0LCH88nFZrWhH+eDgLtuqDFhHJ7VJKsxw6coi+b/TNWaVZRAKUEuYimSk4GKZMgQcesCPj+vUhNJQWrVqho2HJELVqwYsvWrHca645Viz31lvh6xzUWEZEJECULw+TJ8OuXVbX/OWXrXxLt25WqsXzHAkJEB2d8bsJSsr7a8HWBUS/Hk3Cbwl4eCT8lkD069EZnjRXUl5EJPupXKwyD7Z+kKVfLuXZLc/6HY6I/Ic8fgcgkus5Z/Wm4+Nh5kwbAv45GobA6ZogmSelWO6998K4cTB9urWv7t4dRo2CihX9jlBERFIpWxYeewxGjoQLLzy5j3NSku0mrFkD554LISHHX6c1FhJilzxp7OEvWGDPl5QE4LQb4oOYt2NI+jvpuLGkv5Pos6QPK79aybn5ziUkXwjn5j/3uK9D8oWkebtAngI45457vpSkfMrrpCTlAaIu0gctIuKnQQ0H8fLnLzNk+RAuq3gZZc4t43dIIpIOJcxFssrKlSePJSVZMlNHqpJRKlWCp5+Ge+6xMi2zZsHs2fY7dtddtv5fJAdxzsUDB4AjwGHP8xo454oBLwLhQDxwved56n4rOVKpUnDgQNr3JSXBkiWQmAgHD576cxYseHIyfcMG+PPPk58/Jka7IVllz2970hz/4/AfrN69msRDiRw4dIDDRw+f0vMFu+CTkuhb9m3hryN/Hfe4pL+TiHk7RglzERGfBQcFM7vzbOpMr0P/pf1Z+H8LTzrxKSLZgxLmIlllT9oHSXzzDTRsCO3a2aVRIyvlInI2QkNh6lTLhIwfb4Vzn3kG/u//bKxmTb8jFDkdLT3P+zHV7VHA257njXPOjUq+PdKf0ETOXmioLTw7UViYLVADOHLEEtwHDlgC/cCB478+8frEsROT5SkSEmxz0aIFVK8OQSrYmGlCC4eS8NvJH3RY4TDih8YD4Hkefx35y5Lnfx34J4n+X7dTxk5MlqdIL1kvIiJZK+L8CMa2HMuIlSN4YdsLdL2oq98hiUgalDAXySrpHQ0XLgx580JsLIwdC0WLQps21sjx8suhjJZpyVlIWfM/apRdT50KL7wAV10Fd98N9er5HaHImegCRCZ/PQ+IQwlzycFiY1OXSzGFCtl4iuDgY6VYzkR4eNq7IcHB1vYCoHhxaN7cLi1aWJsMncPPOLGtY48rlwJQKG8hYlsf+6CdcxTIU4ACeQpwfqHzT/s1wh8PTzMpH1o49MyCFhGRDDfskmG88vkrDFo2iFYVWlEqpJTfIYnICTSHRCSrxMba0W9qhQpZAvP99+GHH6x5Y5cusHYt9Ohhyc66deHOO62I6d9/+xO75HwlS1pt8/h4GD0aVq+2JrQdO8KHH/odnci/8YAVzrkNzrnkisuU8jxvL0DydUnfohPJAFFR1nYiLAyc8wgLs9sZWSolvd2QefPgq6+selenTrBpEwwbZudTixe3sUcfhfXr4fCpVQqRdERdFMWMTjMIKxyGwxFWOIwZnWZkaKmU2NaxFMp7/Ad9YlJeRET8FRwUzJwuc0g8lMjANwf6HY6IpEEzzEWySspRb0wM3p49uNBQO3pNGS9WDK6/3i6eB5s3w/LlsGyZldQYN86mlV12mc0+b9cOypf37/1IzlS8ONx3H9x2G0yZAhMnQuPG9nt1zz02rVAke2nqed53zrmSwErn3I5T/cbkBHs0QIkSJYiLi8ukECExMTFTnz8rXkPvwd/XKFcO5s615w8JCQEgI1+mXDkYNqwkM2dWZP/+/JQs+Re9e++iXLn97NkDFSrYpVs32L8/P5s3F2Hz5sJs3lyEN96wBGzBgoepWfN3atf+lVq1fqVq1QPkzev98xqrVqU8fwtKlvyT3r13cdll+zPuTaSSU3+XylGOuXXmHvucfyJDX6cc5RhWaRgzd89k/1/7KZm/JL0r9KbcT+Uy/P3k5L+3rHp+EZH0VCtRjTGRY7jz7Tt5+bOXua7GdX6HJCKpKGEukpWioiAqijVxcURGRqb/OOegTh27jBoFv/1mM4KXLbPLwoX2uOrVjyXPL70U8ufPkrchuUDhwlbLfMgQq28+frytv2/e3BLnrVvb76GIzzzP+y75er9zbiHQENjnnCvjed5e51wZIM2MnOd5M4AZABEREd6//t89S3H/9X89B7yG3kP2eI3MfP7ISHjggdSvUT35crLrrz/29d69tvht7do8rFlTjJkziwHWXLRxY9t8HDpk52BTysrs21eAiROrU61a9UxpKpqTP4fMfv5IInmAB3L0e8iq18iK9yAikp7bm9zOq9tfZeCbA4kMj6TEOSX8DklEkqkki0hOULiw1ZyeMcOah27bZgnOMmVg8mSreV6smK2bnjYNdu3yO2LJKUJC4PbbYfdueOIJW5ffpo1lQJYutdUOIj5xzp3jnDs35WugLbANWAJ0S35YN2CxPxGKBIYyZaxn9NSptguyfz+8+qrVXf/5ZxgzxhbNpa7BDnY7JsaXkEVERLK9PEF5mNNlDr/++SuDlg3yOxwRSSXgEubOufLOuXecc9udc58554Ykj49xzn3rnNuUfLnC71hF0uQc1KgBw4fDqlXw00/w+uvQvTt89hkMHAiVKkFEhM0eXrYM/vjD76gluytYEAYPtoT5U0/B999bffP69eG11+DoUb8jlMBUCnjPObcZWA8s9TxvOTAOaOOc+xJok3xbRLJIiRJw9dXw+OPw6ae2K5LeoqQ9e7I2NhERkZykZsmajG4xmhc/e5GF2xf6HY6IJAu4hDlwGBjueV414BJgoHMuZS3qRM/z6iRf3vQvRJHTEBJiic2pUy3ZuXOnzRSuWNFmpF9xhc0+b9fOxnfu1KxhSV/+/NC3L3z5pXWAO3AArrkGateGF16AI0f8jlACiOd5uzzPq518qeF5Xmzy+E+e57X2PK9K8vXPfscqEsiKFoXQ0LTvK1Mma2MRERHJaUY2HUnd0nXpv7Q/PyX95Hc4IkIAJsw9z9vred7G5K8PANuBcv5GJZJBnIMLL7SZwsuW2TrpZcssARofD0OHQtWqNgN9wACbmZ6Y6HfUkh3lzQs9esD27bBggc0w79rV6ubPmweHD/sdoYiIZCOxsVCo0Mnjv/wCb7yR9fGIiIjkFHmD8zKnyxx++uMnhiwf4nc4IkIAJsxTc86FA3WBj5KHbnXObXHOzXbOFfUtMJGMUrCgzSx//HHYscNmoE+bBjVrwvz50LmzzT5v3dpqom/bptnncrw8eeDGG2HrVnj5Zfud6t7dTsw8/bR1eRMRkYAXFWUL28LCwDmPsDBrAlq1qrVYGT1ai5RERETSU7t0bWIujWHB1gUs2bnE73BEAl4evwPwi3MuBHgVGOp53u/OuSeBsYCXfD0B6JnG90UD0QClSpUiLi4uQ+JJTEzMsOeS7M/Xz7taNahWDXfrrRTeupViH39M8Y8+4pwRI2DECP4sUYKfGzbk54YN+aVePY6EhPgTZy6TK/7Gzz8fJk6k+Lp1hD3zDOdFR/NnTAxfd+3K3g4dOJovn98RioiIj6Ki7BIXt4bIyEjAFrkNGABjx8LHH9uipWLF/I1TREQkO7rr0rtYuGMh/d7ox6Whl/odjkhAC8iEuXMuL5YsX+B53msAnuftS3X/00Cai0c9z5sBzABo0KCBl3IwcLbi4uLIqOeS7C/bfN5t2x77+uuv4a23KLBsGWVXraLs0qUQHAxNmkD79jZTvU6d9Lt6yb/KNp95RmjZEu68E1asoMDYsVSZNIkqL70EI0ZYZuScc/yOUEREsomCBa0lRqNGVjGuQQN49VWoW9fvyERERLKXfMH5mNNlDg1mNKD8xPIk/Z1E6KZQYlvHEnVRlN/hiQSUgCvJ4pxzwCxgu+d5j6UaT92S6CpgW1bHJuKr8uWhd287iv3xR1izBu64w2qc33UX1KsHZctaOY4XX7T66BK4nIPLL4d334V33rHa5sOHQ3g4PPQQ/P673xGKiEg24Rz06wdr11olryZNrDKciIiIHG/7j9sJDgrm4N8H8fBI+C2B6NejWbB1gd+hiQSUgEuYA02Bm4FWzrlNyZcrgEecc1udc1uAlsAwX6MU8VPevNC8OTz4IGzcCN99B3PnQosWsGQJ3HADlChhR7z33w/r11tTSAk8zkFkJLz9Nrz/Plx8sZ1gCQ+H++6zbm8iIiLAJZfYbsUll0C3bjBwoFphiIiIpBbzdgyHjx4+bizp7yQGLxvMVz9/haeeYyJZIuAS5p7nved5nvM8r5bneXWSL296nnez53kXJY939jxvr9+ximQbZcrYke0LL8APP8AHH8Ddd1v3rjFjbJ11qVJWuPTZZ2H/fr8jFj80aQJvvmlFaps3t9+NsDBLoP/4o9/RiYhINlCyJKxcCbffbn3IIyPh22/9jkpERCR72PPbnjTHf/7jZypPrkzo46HcvPBmZn86m12/7FICXSSTBFzCXETOUnAwNG5ss4c/+gj27bMOXu3a2RHwzTdb8rxBA7jnHpt1fPjwfz+v5B4NGsCiRbB5s/1ejBtnifPbb4fvv/c7OhER8VmePPDoo/Dyy7B1q1V9W7PG76hERET8F1o4NM3xsiFlmXbFNJqUb8KKr1bQa0kvKk2qRPgT4XRf1J25m+aS8GtCFkcrknspYS4iZ6dECbjxRnjmGUuGfvwxjB0L+fNbSZdmzewx118Pc+ZYeRcJDLVqwUsvwWefwdVXw8SJVqpl0CBrMisiIgHt2mutqlvRotC6NTz2GGiinIiIBLLY1rEUylvouLFCeQvxSNtH6H9xf1689kW+H/49nw34jCntp9CwXEOWfrmUHot7EP5EOBWeqEDPxT2Zv3k+X/+mYy6RM5XH7wBEJBcJCrLZxQ0aWMmWX36BVatg2TJYvtymkoElUtu3t9nHTZtazXTJvapVsxMq995rs82fegqmT4cePWDUKKhQwe8IRUTEJ9WqWdK8e3frHb1+PcycCSEhfkcmIiKS9aIuigKslvme3/YQWjiU2Nax/4wDOOeoXqI61UtUZ2DDgRz1jvL5D5/zzu53iEuIY/HOxczZNAeAikUr0jK8JZHhkbQMb0m588r58r5EchrNMBeRzFO0KFx3HcyebQVKN22yhGmxYjBhArRsCcWLw1VXwYwZsCftem2SS1SubFmQ//0Peve2RrJVqlji/Isv/I5ORER8ct558Oqrtovw8svWFFSbhexr34J9rAtfB61gXfg69i3Y53dIIiK5StRFUcQPjWd1i9XED40/LlmeliAXRM2SNRnUaBCvXv8qP4z4gc39NvP45Y9Tq1QtXtv+GjcvvJkLJl5AlclViH49mue2Psd3B7T6WyQ9mmEuIlnDOahd2y4jR8Lvv8Pq1Tb7fNkyq3kNUL26zTxv184aR+bP72/ckvHCwqzTW0wMjB9vs83nz4f/+z8bq1HD7whFRCSLOWe7Bw0awA032PX8+XDllX5HJqntW7CPndE7OZp0FIC/Ev5iZ/ROAEpFlfIzNBERSRbkgqhVqha1StViyCVDOHL0CFv3b/1nBvpLn73E0xufBuDC4hf+MwM9MjyS0iGlfY5eJHvQDHMR8cd559lR8PTpkJBgda4nTICyZWHKFGjb1maid+wIU6fCV1/5HbFktHLlrK757t3WEHTJEqhZE665Bj791O/oRETEB61bw4YNEBFhC9DuuguOHPE7KkmxK2bXP8nyFEeTjv5/e3ceXlV19n38e2cemKcwhpCKKMUJAUFQgljriNbhLSatttXSQWu1VakPthBtVCy2tupjS6uPtiVatdYJJyqkqFhU6jwgFkIEIogMAoGM6/1jnUzkZCJnSvh9rutcydnnnLXWZrGz177PvddizZVrqNxRGaVWiYhIS+Lj4jl64NFcNekqHp/5OJ9f+zmrZq1iwVcWcGjfQ3ng3Qe48O8XMui2QRx+1+H8cPEPeei9h9iyZ0u0my4SNcowF5HoM/OZ5aNHw09+Anv2wLJlft7zZ56BxYv9+w45pH7u85wcSEtrsVjpJDIyYP58uPZauP12+N3v4NFH/ZclP/85OXuvFwAAIABJREFUTJgQ7RaKiEgEZWbCiy/CFVfAzTfD669DYSH06xftlkl5SXnQ7VVbq3i538v0nNyTvmf2pe8ZfUk7PA0zi3ALRUSkNfFx8YwdNJaxg8by0+N/SlVNFW9++mZdBvpf3/4rd79+NwDD04ZzZtmZ5GTlMHX4VPqn949y60UiQxnmIhJ70tN9sPTOO31m+Ucf+SDqyJHwxz/CGWf47POvftUHWD/8EJyLdqulo/r2hRtv9Hcc3HgjrFgBxx3n7zZ48cVot05ERCIoJcUvb/KnP8Hy5X6KllWrYNEiyMqCk06aSlaWfy6Rk5wZfKq8xIxEMmdnUrWzirXXruW1L7/GyuyVrPnRGj5/9nOq9+k2ARGRWJUQl8C4weO4ZvI1LM5dzLbZ21h56UpumX4LGckZ3PfmfVzw8AUMWDCAI+4+giueuYJHP3iUz8s+j3bTRcJGGeYiEvtGjvSPH/0I9u71V8612edXXeUfWVk+8/y00/xiot27R7vVcqB69YLrr4cf/xh+/3s/z/mJJ8LUqT7j/KST/F0JIiLS5V1yiV/+5Lzz/Heo8fFQUQFgrF8Ps2b59+W1vB6ahEh2QXajOcwB4tLiOOS2Q8jIyyC7IJt9G/ax7eltfP7U55TeW8rGOzcSlxZH7+m96XtmX/qc3oeUoSlR3AsREWlJQlwCE4ZMYMKQCRxXdRyTT5jMqtJVdRno97xxD3e8egcAR2YcWTcH+onDT6RPap8ot14kNBQwF5HOJTXVZ5Z/9av1818/95wPnv/lLz7AmpgIU6bUT98yZowCrJ1R9+5wzTVw2WX+zoJbb4WTT4ZJk3xA/bTT1K8iIgeB2uzyYcNg377Gr5WV+fWiFTCPjNqFPdfOWUt5STnJmclkF2Q3WvAzZWgKg2cNZvCswVTvq2ZH0Q4+f+pzti3exudP+mzE9KPS66Zu6TGhBxav87mISKxKjE9k4tCJTBw6ketOuI6K6gpe3/R6XQB94aqF/HblbzGMowYe1SiA3iulV7SbL3JANCWLiHRuI0bA978Pjz8O27bBCy/AlVfC1q1+Tuwjj/RX2JdeCn//O+zYEe0WS3ulpfls87Vr4e67YdMmPy3P+PHw2GNQU9N6GSIi0qn16wflwafPpqQksm052GXkZTCpeBIshUnFkxoFy/cXnxJP31P7cuidh3Lc2uMY/954sudnk9AzgZJbSnjj+DdYMXAFH1z0AVv+tqVu4dDNizbzStYrcBK8kvUKmxdtjtTuiYhIK5Likzh+2PHMOXEOS765hO2zt/Pit18kPyefPql9uPv1uzn7wbPpM78Pxy48lqufv5qnPnqKnft2RrvpIm2mDHMR6TqSkvx0HSed5LORN2yozz5/+GG45x5/L/fxx/vM81NPhaOPhjh9d9gpJCf7L0cuucTfTXDTTfC1r8ERR/j0wvPP9/0rIiJdUmamX+Zif875G89mzvSnhV5KZotJZkb66HTSR6eTeW0mldsr2fbcNp95/vTnbP7LZoiH1JGp7PvvPlylX5+mfH05q2etBmgxOC8iItGRnJDMlMwpTMmcws/5Ofuq9vHqxldZtm4Zy4qXccerd3DbK7cRZ3GMHTS2LgN9SuYUeiT3iHbzRYJSlEhEuq6hQ31w9ZFHfMb58uUwezbs3u0DrMceC4MHw8UXw4MPwudatKRTSEyE73zHL/b6179CVZWPknz5y/DnP/vnIiLS5RQU+JuOGkpJgRkzYM0af2rIyICzz4YHHvCne4ldib0TyZiZweF/OZzJmydzzMvHkDk7s1GwvFZNWQ2rZ63m459+TMmCEjYv2sz2pdvZ88EeKndU4tq5+Lsy2EVEwiclIYUTh5/I3Jy5FH2riB2zd7D0oqVcf8L1pCakcvu/b+eMwjPoM78Px/3pOGYvmc2zHz/LrvJd0W66SB1lmIvIwSExEU44wT8KCuDTT+H55332+VNP+UCrGUyYUD/3+bhxyliOZQkJftLaCy/00+388pf+y4/8fLjuOrjoIn/XgYiIdAm185TPmQMlJY7MTKOgwG93Dl57zX///dBD8MQTftmTs87y36medpoPrktssnij5/E96Xl8T0puDj7HTk1ZDZt+v6nRgqO14lLjSBqURNKgJJIHJdf93uj54CQS+yaypXBLo4VLlcEuIhJeqYmpTBsxjWkjppFPPmWVZbzyySsUFRexrHgZv/n3b7h1xa3EWzzjh4wnZ3gO00ZMY/KwydFuuhzEFDAXkYPTwIE+oHrRRVBd7a+yn33WB9Dz82HePOjbF045xV9ln3KKT1uT2BMXBxdcAOed57/8uPFG+O53/c/Zs33KoaIkIiJdQl6efxQV/YucnJy67bXfeU+YAAsWwMsv++D5ww/7AHr37nDOOT54/pWv+O/RJTYlZyZTvr7phPXJw5OZuG4i1buqKd9UTkVpRd2jvLT++Z5397Dt+W1Uf1HdpAxLNFyNg/1eqimrYe2ctQqYi4hEQFpiGtOzpzM9ezoAeyr28MqGV+oWEV3wygJuefkWEuISGNVtFGdXn820EdM4ftjxpCWmtVK6SGgoYC4iEh8PEyf6x7x5fvqWJUt88Py55/x93QBjx9Znn0+c6DOcJXbExfn78s86y/fbjTfCZZf5zPNrroHvfa/pvfwiItLlxMXV31T229/CsmU+eP7oo34JjD59/HesM2fC1Km6mSzWZBdkN8oAB4hLiyO7IBszI6FHAgk9Ekg/LL3FcqrLqpsE0ytKKyi5JXgGe3lJM6vKiohIWKUnpXNy9smcnH0yALsrdrPikxUsW7eMJ95+gvkvz+eml24iMS6R44YeV5eBPmnoJFITU6PceumqNIe5iMj++vXz03z8+c9QWgqvv+6DrqmpcPPN/gq8Xz+f1XzvvbBxY7RbLA2Z+S81XnoJli6Fww6Dn/wEsrJg/nzYpbnxREQOFgkJPqP8nntg82Z48kn/3XdhIUyfDkOGwBVX+Iz0mhpYtMifLk46aSpZWf65RFZGXgajFo4ieXgymM8sH7VwVLuzv+PT4kn9Uiq9pvRiwAUDGHrFULJvzvblBpGcGXy7iIhEVrekbpzypVO4+eSbuWvsXWyfvZ1n8p7hqolXUVFdwU0v3cT0P0+n1/xeTL1vKvOK5lFUXMS+qn3Rbrp0IQqYi4i0JC7OLw46Z44PwG7d6u/tPu88WLHCLyo6dCgcdZSf/mPZMqioqP984Mp76kknoSvvCDODadN80Pyll/wdAj/7GQwfDjfcADt2RLuFIiISQUlJcOaZfr3oLVv8dC1TpsAf/+h/9u8P3/oWrF8Pzhnr18OsWTp1R0NGXgaTiifBUphUPCmkU6VkF2QTl9b4Mrg2g11ERGJP9+TunHrIqcz/ynxWXrqS7bO3szh3MVdMuIKyyjJuXH4j0+6fRq9bejHt/mnc8K8bWL5+OeVVunNIDpzmExARaY/evX1m+QUX+BXG3nmnfu7zX/8abr0VunXzaWt9+vh7wPfuxYC6K2+oX7lMImPyZN9Pr73m7xaYOxduuw0uvxyuusrfMSAiIgeNtDQ4/3z/+OILv0jorFlQVdX4fWVl/jtznba7jtrg+9o5aykvKSc5M5nsgmzNXy4i0kn0SO7B6SNP5/SRpwOwY98OXip5qW4O9HlF83A4UhJSOH7Y8UzLmkZOVg4ThkwgKT4pyq2XzkIBcxGRA2UGRx7pH9de66f6WLrUB8+feQZKgsyRWVbmA7RjxviM8549I97sg9r48fD44/DWWz5wfvPNfoLbH/wAfvpTvxisiIgcVHr0gG98w68DHkyw0/mBWvTOIua8MIeSnSVkvplJwfQC8o5QND7SMvIyyMjLoKioiEk5k6LdHBER6YBeKb0489AzOfPQMwHYvnc7L5a8WBdA/8WyX+BwpCakMjlzcl0Affzg8STGaxVwCU4BcxGRUOneHc4+2z+c86uIOdf0fZ99Bkcf7X/v3dsHzhs+Royo/71790i1/uBy1FH+Xvz334ebbvJ3B9x5p08vvOYaP82OiIgcVDIz/c1gwbaHwqJ3FjHryVmUVZYBsH7nemY96e88U9BcuiozKwZ2AdVAlXNuXHRbJCJdXe/U3swYNYMZo2YAsG3vNpavX14XQJ+zdA4AaYlpTMmcUhdAP3bQsY0C6PqS++CmgLmISDiYNX/lPXAg3HEHFBfDunX+5+rV8NxzPgO9oT59mgbRGz66dQvvfnR1o0f7yWznzoVbboH//V/4/e/h29/2851nZUW7hSIiEiEFBf5704an4rQ0vz0U5rwwpy5YXqussoyfLfkZF465kDjT8lLSZU1zzm2NdiNE5ODUJ7UP5xx2Duccdg4AW8u2NgqgX/fCdYBfbLQ2gL6vah/zX56vL7kPYgqYi4iES3NX3gsW+ElT9+ecX1S0Noje8PHee7B4Mezbb+Xvfv2az1AfPhzS08Oya13OyJFwzz3w85/D/Plw773++Te/Cddd518XEZEurXae8jlzoKTEkZlpFBSEbv7ykp3B53bZsGsDSTcmkdEtg0HdBjGo+yD/M/D74O6D637PSM9o9fZxZcSJiIg0r19aP849/FzOPfxcALbs2dIogD77n7ODfq6ssozZS2brS+6DhALmIiLh0uDK25WUYJmZtHjlbQb9+/vHhAlNX3cOtmypD6I3DKy/8w48+SSU77cSeP/+LWeop6aGYk+7jqwsuPtuHy1ZsAD+8Ae4/36YOdNvGz062i0UEZEwysvzj6Kif5GTkxPSsjN7ZrJ+Z9M7z3qn9OaH439I6a5SSneX8snOT3h146t8tuczHI2ndjOMfmn96oPq3QcxuNvguufvbHmHW1++lb1VewFlxElMcMDzZuaAPzjnFu7/BjObBcwC6N+/P0VFRZFt4X52794d1TZEu361ITbqVxsiW38/+nFB+gVcMPoCtlVs47xXzgv6vo27NpJyYwoZKRkMTBnofyYPZFDqIAYmD2RgykB6J/UOeUA92v0QC22IdP0KmIuIhFPgyvtfRUUdv/A2g4wM/zjuuKav19TA5s1Ns9PXrYM33oDHHoOKisafychofv704cMhJaVjbe6shg6F22/32eW33eananngATj3XLj++vo56EVERNqoYHpBoznMwc+fesfpdwQNZldWV7JlzxZKd5fWBdNLd5Wyadcm//vuUt7d8i6f7v6UalfdbL1llWXMeWGOAuYSLZOdc5vMbACwxMw+dM4tb/iGQBB9IcCoUaNcqL+saq+iUIzbO3H9akNs1K82RLf+4e8PD/old5/UPnx37HdZt2MdxTuKeW3Ha2zZs6XRe1ISUhjeczhZvbLqHiN6jaj7fUD6AMysXe2Jdj/EQhsiXb8C5iIiXUVcHAwa5B+TJjV9vaYGPv20aXZ6cTGsWgWPPgqVlY0/M3Bg8Oz0ESP8HO3JyeHdp2jLyIBbb4Vrr/UB9DvugL//Hc46y0/fMn58tFsoIiKdRG3Aum66lJ4tT5eSGJ/IkB5DGNJjSIvl1rgatpZtpXRXKcf84ZgmWenQ/HQwIuHmnNsU+LnFzP4BTACWt/wpEZHoau5L7t+d9rsm5+09FXtYv3M9xTuK6x61AfVVpavYWtZ4CYfUhNRGwfT9A+r90vq1O6AuoaeAuYjIwSIuDgYP9o/jj2/6enU1lJY2zU4vLoaVK+Hhh6GqqvFnBg8Onp2eleUD6klJYd2liOnXD375S7j6ah80v/12P23OV7/qM86nTIl2C0VEpBPIOyKPvCPyQpolFWdxDEgfwID0Ac1O+5LZMzMkdYm0h5mlA3HOuV2B308Bbohys0REWtWeL7nTk9IZ3X80o/sHn75zd8XuRsH0hgH1lRtXsm3vtsblJaY3Cajv+WwP3Td1J6tXFn1S+yigHgEKmIuIiBcf76ciGTo0eAC4uho2bQqeob5iBfztb/49tcx8QL25DPVhwyCx5YXLYk6vXj6z/Mor/VznCxbACSdATo7fXlpau1qc/8IglKvFiYiItKK5jLiC6QVRbJUcxDKAfwQCOwlAoXPu2eg2SUSkbUL1JXe3pG6MGTCGMQPGBH39i/IvWL9jfV0QvWFQ/eVPXmbHvh0AzHt/Xl15+2elN3zeK6WXAuohoIC5iIi0TXy8D3IPG+aDxPurqoKNG4NnqL/4IhQW+mlhasXFwZAhzWeoDx0auwH17t39NC2XXw4LF/ppW6ZP9/tUu4/r18Msv9CaguYiIhIJ7Z32RSScnHNrgaOi3Q4RkVjWI7kHR2QcwREZRwR9fce+HTzyz0fod0i/JhnqRcVF7KrY1aS8lgLqPVN6RmK3Oj0FzEVEJDQSEvxCocOHw9SpTV+vrPQB9f2z04uLoagIFi1qHFCvzXgPlp2eleWD7QlRPo2lpfls8+9/37dnW+Pb6Sgr8xnnCpiLiEiEhGPal4Y2L9rM2jlroQReyXyF7IJsMvIyQl6PiIiIQK+UXhzS7RByDstp8ppzjh37dgTNTv/v9v/yz7X/ZE/lnibltRRQ757cPUJ7FtsUMBcRkchITKwPegdTUQEbNjTNTi8uhhde8MF212Ahs9qM92DZ6bUB9fj4MO5QAykpsH178NdKtNCaiIh0DZsXbWb1rNXUlPkvuMvXl7N61moABc1FREQizMzondqb3qm9GTtobJPXnXNs27staEB99eeree6/zzWaxg2gT2qfoAH1z/Z8xriKcXRL6hap3YsqBcxFRCQ2JCVBdrZ/BFNR4YPP+2enFxfDc8/5+dUbSkjw84g3l6E+aFBoA+qZmX4almDbRUREuoC1c9bWBctr1ZTVsObKNaR9OY3UQ1JJ6Bb7l5jKkhcRkYOBmdE3rS990/oybvC4Jq8759hatjVoQP29z95j8ZrF7KvaV/f+77z+Hfql9Ws2Q314r+GkJaZFchfDJvZHMyIiIuAD6occ4h/BlJc3Dqg3zFB/5hm/IGdDiYn1AfVgGeqDBvk5yduqoMDPWV7W4Bv6tDS/XUREpAsoLykPur1qaxWrjlkFQNLgJNIOTSN1ZCqph6bW/56dSlxyO86rYaIseREREc/M6J/en/7p/ZkwZEKT151zbNmzhXU71vH0iqdJG5xWF1R/a/NbPLH6CcqrG48NBqQPaDagntkzk9TE1EjtXocoYC4iIl1DcjKMHOkfwezdGzxDfd06ePJJ2Ly58fuTkvx87MGy07OyICOjcUA9Lw9eftkvAlpd7bPXL75Y85eLiEiXkZyZTPn6pkHzpEFJHPK7Q9j70V72rtlL2UdlbP3HViq3Vta/KQ5SslJIHRkIoh+aStpI/zMlMwWLt7q3hioD3DmHq3BU7aqienc11buq+finHwfNkl87Z60C5iIiIg2YGRndMsjolsG+AfvImZLT6PUaV8Pm3ZsbLURa+1hVuopHP3iUyprKRp8Z2G1g0IB6Vq8shvccTnJCcqP3L3pnUf1i5m9GbjFzBcxFROTgkJoKo0b5RzBlZfUB9f0XJn38cdiypfH7k5N9QL02iL59Ozz2mA+Wg/95//0webKC5iIi0iVkF2Q3ys4GiEuL40u/+hIDzh/Q5P2V2yvZu6Y+iL73o72UrSnj0xWfUr2ruu59lmSkfslnpLsqx/Yl23EVft2S8vXlfHjJh+x8ZSfdju5G9a7quuB3w59Vu6qCvuaqXJN2BdNc9ryIiIgEF2dxDOo+iEHdBzFp2KQmr9e4Gkp3lQYNqK/cuJKH33+YqpqqRp8Z3H1wXQB9T8Uenvn4GSqqKwBYv3M9s56cBRD2oLkC5iIiIuCnTznsMP8IZs8eP0f5/tnpxcWwahVs3dr0M2VlMGeOAuYiItIl1GZgr52zlvKScpIzk1vM/k7snUjihER6TOjRaLtzjorNFT6Y/lEgmB4Iqpe9V9akHFfu2HRX47VK4lLiiO8eT3y3+LqfCb0TSMlMabRt/59rLltD5ZbKJnUkZyY32SYiIiIHLs7iGNJjCEN6DGFy5uQmr1fXVLNp16agAfUVn6ygeEdxk8+UVZYx54U5CpiLiIjEhPR0GD3aP4KJiwMXJIutpCS87RIREYmgjLwMMvIyKCoqYlJO02yytjAzkgcmkzwwmV4n9Gr0WlFcEQRLCjeYWDLRB7+7xROXcGDzobtyFzRLPrugmUXHRUREJCzi4+IZ1nMYw3oO44ThJzR5PS4/DhdkUFCyM/zX2NFfdUVERKQryMxs33YRERFporlM7+TMZFKGppDYK/GAg+XgA/6jFo4ieXgyGCQPT2bUwlGav1xERCTGZPYMfi3d3PZQUsBcREQkFAoK/LQuDaWl+e0iIiLSJtkF2cSlNb5MDXUGeEZeBpOKJ8FSmFQ8ScFyERGRGFQwvYC0xMbX2GmJaRRMD/81tgLmIiIioZCXBwsX+oVAzfzPhQs1f7mIiEg7KANcREREwC/sufCshQzvORzDGN5zOAvPWhj2+ctBc5g3YmanAr8F4oE/OeduiXKTRESkM8nLU4BcRESkg0IxT7qIiIh0fnlH5JF3RB5FRUXk5ORErF5lmAeYWTxwF3AaMBq40MyaWdlNRERERERERERERLoaBczrTQA+ds6tdc5VAA8CZ0e5TSIiIiIiIiIiIiISIZqSpd4Q4JMGzzcAx+3/JjObBcwCyMjwtwmGwu7du0NWlsQ+9ffBR30uIiIiIiIiIhL7FDCvZ0G2uSYbnFsILAQYN26cC9X8OZGei0eiS/198FGfi4SW1h0RERERERGRcNCULPU2AMMaPB8KbIpSW0RERKQZWndEREREREREwkUB83qvASPNbISZJQEzgSei3CYRERFpSuuOiIiIiIiISFgoYB7gnKsCLgeeAz4AHnLOvRfdVomIiEgQwdYdGRKltoiIiIiIiEgXojnMG3DOPQ08He12iIiISIvatO5Iw4W6+/fvH9aFdyOxsG+469A+xEYd2ofYqKOzlx+JOrQPIiIi0lUpYC4iIiKdTZvWHWm4UPeoUaNCtlB3MJFY2DfcdWgfYqMO7UNs1NHZy49EHdoHERER6ao0JYuIiIh0Nlp3RERERERERMJCGeYiIiLSqTjnqsysdt2ReOBerTsiIiIiIiIioaCAuYiIiHQ6WndEREREREREwsGca7JGlrSRmX0GrA9Rcf2ArSEqS2Kf+vvgoz6XAzHcOdc/2o3oCsxsF7A6jFVE4hgPdx3ah9ioQ/sQG3V09vIjUYf2oTGds0MgAufrtoj2uD3a9asNsVG/2hAb9asNsdOGUNXfpvO1Msw7IJQDIjN73Tk3LlTlSWxTfx981OciUbc6nMdgJI7xcNehfYiNOrQPsVFHZy8/EnVoHyRMwnq+boto/7+Idv1qQ2zUrzbERv1qQ+y0IdL1a9FPEREREREREREREREUMBcRERERERERERERARQwjyULo90AiSj198FHfS4SXeE+BiNxjGsfol9+JOrQPsRGHZ29/EjUoX2QcIiFPol2G6JdP6gNsVA/qA2xUD+oDbWi3YaI1q9FP0VEREREREREREREUIa5iIiIiIiIiIiIiAiggHnUmdm9ZrbFzN6Ndlsk/MxsmJktM7MPzOw9M/txtNsk4WNmKWb2qpm9Fejv/Gi3SeRgY2anmtlqM/vYzH4WhvLDeh6PxHkjUn+rzCzezN4ws6fCVH6xmb1jZm+a2ethKL+XmT1iZh8G+mNSiMsfFWh77eMLM7syxHVcFejjd83sATNLCXH5Pw6U/V6o2h7sGDOzPma2xMzWBH72DkMdFwT2o8bMxoWh/F8F/i+9bWb/MLNeYajjxkD5b5rZ82Y2OJTlN3jtajNzZtbvQMtvrg4zm2dmGxscF6eHsvzA9h8FzhPvmdmtHdkHOXDhPl+3sQ1RvTaPhWvFWLl+CfeYoQ31h3VM0cY2hHXc0UrdYR+TtLEdYR23tLENIR/btKHOsI99DqD+kI2LOtCGkI6dWqOAefTdB5wa7UZIxFQBP3XOHQ5MBC4zs9FRbpOETzlwknPuKOBo4FQzmxjlNokcNMwsHrgLOA0YDVwYhr+59xHe83gkzhuR+lv1Y+CDMJTb0DTn3NHOuXAM5H8LPOucOww4ihDvi3NudaDtRwPHAmXAP0JVvpkNAa4AxjnnxgDxwMwQlj8G+C4wAf/vc6aZjQxB0ffR9Bj7GfCCc24k8ELgeajreBc4F1jewbKbK38JMMY5dyTwEXBdGOr4lXPuyMD/qaeAX4S4fMxsGPAVoKQDZbdYB/Cb2mPDOfd0KMs3s2nA2cCRzrkvAws6UL4coAidr9viPqJ7bR4L14qxcv0SiTFDa8I5pmiLsI47WhLuMUlbhHvc0sY2hGts05r7CP/Yp731h3JcdKBtCPXYqUUKmEeZc245sC3a7ZDIcM6VOuf+E/h9F/6kNyS6rZJwcd7uwNPEwEMLR4hEzgTgY+fcWudcBfAgPjASMuE+j0fivBGJv1VmNhQ4A/hTKMuNFDPrAZwI3APgnKtwzu0IY5XTgf8659aHuNwEINXMEoA0YFMIyz4c+Ldzrsw5VwX8C/haRwtt5hg7G7g/8Pv9wDmhrsM594FzbnVHym2l/OcD/04A/waGhqGOLxo8TacDx3ULf+t+A1zbkbLbUEdINFP+D4BbnHPlgfdsCVf90qKwn6/bItrX5rFwrRgL1y+dfcwQClEYd7QkXGOStgjnuKUtwjK2aU0kxj7trT+U46IOtCGkY6fWKGAuEiVmlgUcA6yMbksknAK3E74JbAGWOOfU3yKRMwT4pMHzDXTiLynDed6IwN+q2/FBtZoQl9uQA543s1VmNivEZWcDnwH/F7hF/E9mlh7iOhqaCTwQygKdcxvx2bMlQCmw0zn3fAireBc40cz6mlkacDowLITlN5ThnCsFH2ACBoSpnkj5DvBMOAo2swIz+wTIo2MZ5sHKngFsdM69Fcpyg7g8cPv1vWG4Bf1Q4AQzW2lm/zKz8SEuX9qmS52vQyGa14oxcP0SiTFDa8I5pmiLSI87WhLyMUlbRGDc0hY21oPXAAANsUlEQVSRHNu0pquNfToqbGOnWgqYi0SBmXUD/g5cuV/2j3QxzrnqwK1sQ4EJgdu6RCQyLMi2TnmXR7jPG+H8W2VmZwJbnHOrQlVmMyY758bib+m/zMxODGHZCcBY4G7n3DHAHsJ0K6yZJQEzgIdDXG5vfHbSCGAwkG5m3whV+c65D4D5+NtlnwXewk8vIC0wszn4f6dF4SjfOTfHOTcsUP7loSo3EDiYQ4iD8EHcDXwJPzVEKXBbiMtPAHrjp7+4BnjIzIKdOyS8usz5OhSifa0YzeuXCI4ZWhPOMUVbRGzc0ZJwjUnaWHdYxy1tobFNbAr32KmWAuYiEWZmifgB0CLn3KPRbo9ERuAWuiK0ZoFIJG2gcRbIUCJ/K2eHRfK8Eaa/VZOBGWZWjL/N/iQz+2sIywfAObcp8HMLfp7NCSEsfgOwoUGW3SP4C9lwOA34j3Nuc4jLPRlY55z7zDlXCTwKHB/KCpxz9zjnxjrnTsTfRrsmlOU3sNnMBgEEfnbKaTTM7GLgTCDPORfu4GAhcF4Iy/sSPojxVuDYHgr8x8wGhrAOnHObA8G7GuCPhPa4Bn9sPxqYhuJVfEZrhxYvlQPSJc7XoRBL14pRun6JyJihNWEeU7RFJMcdLQnXmKQtwj5uaYsIjm1a0yXGPh0VybGTAuYiERTIWLkH+MA59+tot0fCy8z6167cbGap+JP+h9FtlchB5TVgpJmNCGTIzASeiHKb2iUS541w/61yzl3nnBvqnMvC98FS51xIM4TMLN3Mutf+DpyCv402JJxznwKfmNmowKbpwPuhKn8/FxKeW59LgIlmlhb4fzWdEC8gZmYDAj8z8QtDhesW7ieAiwO/Xww8HqZ6wsbMTgVmAzOcc2VhqqPhwmQzCO1x/Y5zboBzLitwbG8AxgaOlZCpDQ4EfI0QHtcBjwEnBeo6FEgCtoa4Dmldpz9fh0IsXCtG+/olEmOG1oR7TNEWER53tCRcY5K2CPu4pS0iOLZpTacf+3RUJMZODSWEuwJpmZk9AOQA/cxsAzDXOXdPdFslYTQZ+CbwTmBeOID/cc49HcU2SfgMAu43s3j8F5QPOeeeinKbRA4azrkqM7sceA6IB+51zr0XyjoicB6PxHmjK/ytygD+EZhJIQEodM49G+I6fgQsCgRz1gLfDnH5tdNcfAX4XqjLds6tNLNHgP/gb2N9A1gY4mr+bmZ9gUrgMufc9o4WGOwYA27BT51xCf6C+oIw1LENuAPoDyw2szedc18NYfnXAcnAksD/2387574f4n04PRBsqQHWAyEtP9TXLM3sQ46ZHY2fnqOYDhwbzZR/L3Cvmb0LVAAXRyDbX/YTifN1W8TAtXksXCt2hTFBR0ViTNEWYR93tCScY5K2iNC4pS1CPrZpTSTGPgdQf8jGRR1oQ0jHTq22QeMBERERERERERERERFNySIiIiIiIiIiIiIiAihgLiIiIiIiIiIiIiICKGAuIiIiIiIiIiIiIgIoYC4iIiIiIiIiIiIiAihgLiIiIiIiIiIiIiICKGAuIiIiIiIiIiIiIgIoYC4iIiIiIiIiIiIiAihgLiIiIiIiIiIiIiICKGAuIiIiIiIiIiIiIgJAQrQbENPMHPBXnPtm4HkCUAqsxLkz21FOMTAO57a28J77gKdw7pE2lnkicDtwJDCzzZ+TVpnhgL86xzcDz+v63Tna3O9mFAPjnKPZfjfjPuAp52hT/5nxE+BSoAr4DPiOc6xva5ukeZbvj3c31x/vll9/vLu5bT/eLd8f725u88e75fvj3c1t23Fr+fZ94DKgGtgNzHJz3fttbVOXVGjVwDsNtjxIrrvlAMopBnbh/20BlpPrrjiAcu4DniLXPUKhFQGDgH34/voOuW51C5+9IVDvP9tdr4iIiIiIiIiElALmLdsDjMEsFef2Al8BNka5TbVKgG8BV0e5HV3RHmCMGanOEWv9/gY+CF9mxg+AW4GvR7lNXYXv93xLdXNj7ngvdHPd7wEs32YAvwZOjW6Tom4vue7oEJU1jdwWvtA8MHnkutcptFnAr4AZzb4z1/0i6PZCiyfXVQd9TURERERERETCQgHz1j0DnAE8AlwIPACcAIBZH+BeIBsoA2bh3NuY9Q28rz/wKmCB92fhs8jHBJ5fDXTDuXmNajQ7Fh8Q6wZsBb6Fc6WN3uNcceC9NSHbU2mo2X43o0m/O8fbZgTtdzOy8FnkYwLPrwa6Oce8hhWa0aTfnaNRvzvHsgZP/w18I2R7LNBSv+c3Pd7dXPe25Qc/3i3fsvBZ5GMCz32/z218vFt+0+PdzW18vLu57osGT9MBF6od7lIKrSe+D2aQ61ZTaA8AS8l1f6TQLgT+B98/i8l1s1so53DgfnLdhMDzLOAJct2RFNovgLOAVGAF8D1yXUv9sRy4MlBO8M82zk4vxv8/OwW4E3iw/f8QIiIiIiIiInKgNId56x4EZmKWgp/+ZGWD1/KBN3DuSHwg5s+B7XOBl3DuGOAJILPNtZklAncA5+PcsfjASUFHd0La7UFgphnN9rtzBO1352h3v5tR1+/O0dZ+vwQf4JXQ8f2e3/zx7uYGP97d3PYf75Zff7y7uS0f75Zvl1m+/Rd/V0H7pwzpelIptDcbPL5OrtsJXA7cR6HNBHoHguWDgfnAScDRwHgK7ZwGZS1rUM5V5LoPgCQKLTvw+teBhwK/30muG0+uG4MPfLc2Xc9Z1E8d09bP7iPXTSHXKVguIiIiIiIiEmHKMG+NzxjPwmebPr3fq1OA8wLvW4pZX8x6AicC5wa2L8ZseztqHAWMAZZgBhAPjbOMJfwCGeNZtNLvzrHUjL5mNOp351hsxgH1u+/2lvvdjG8A44Cp7ahDWhHIGM+itX6f65ZavvW1/MbHu5vrFlv+gR3vlt/y8e7muruAuyzfcoHrgYvbUU9XFHxKlly3hEK7ALgLOCqwdTxQRK77DIBCW4Tvt8cCrwebkuUh4P8Bt+AD5l+ve2+hXQukAX2A94Ang7RvEYW2FygGftTOz/6t2b0WERERERERkbBSwLxtngAWADlA3wbbLch73X4/G6qicVZ/SpD3GPAezk1qfzMlxCLe787Rar+bcTIwB5jqHOWtvV/aLfL9Prddx/uDwN3teP/BpdDigMOBvfig9AaC911r/gY8TKE9Cjhy3RoKLQX4X2Acue4TCm0ewfsVaucwr29Xez675wDaKyIiIiIiIiIhoClZ2uZe4Aace2e/7cuBPADMcoCtOPfFfttPA3oH3r8ZGBDIRE8m+O34q4H+mE0KfD4Rsy+Hcmekze4FbnCOZvvdjBxgq3N8sd/2Jv0eyERvsd/NfMDcjEQzmvS7GccAfwBmOMeWDu6fBOf7fW7zx7vl++M9MLd4w+1N+91norfc7/n+eLd8S7T8pse75dvIBk/PANYc4L4dDK4CPsDfJXAvhZaIn1pnKoXWj0KLD7z2rxZLyXX/BaqBn1Of8V0b4N5KoXUDzm9HuzryWRERERERERGJEGWYt4VzG4DfBnllHvB/mL2NXwSwdoqEfOABzP6DD8qUBMqpxOwGfPBmHfBhkLoqMDsf+F1gepcE4Hb8rfv1zMYD/8AH587CLB/nFFgPIedosd/NCNrvZjTqd+eoNKPFfneOCjPOB34XmN4leL/Dr/CLQz4cmLqlxDlmdGA3ZT9ubsvHu+UHP94tv/Hx7ua6Sstv+Xh3c12F5fvjPTC9S3P9frnl28lAJbAdTccCtXOY13sW/2XHpcAEct0uCm05cD25bi6Fdh2wDJ9t/jS57vEGn11GoVUHfn+bXHdR4Pe/4Y+5EQDkuh0U2h/xc5IXA6+1ubUd+ayIiIiIiIiIRIw5F2wmARERERERERERERGRg4umZBERERERERERERERQQFzERERERERERERERFAAXMREREREREREREREUABcxERERERERERERERQAFzERERERERERERERFAAXMRERERkS7DzJyZzYt2O0REREREOisFzEVEREREYpiZ5QQC4ZdGuy0iIiIiIl2dAuYiIiIiIiIiIiIiIihgLiIiIiIiIiIiIiICKGAuIiIiItLpmFmGmRWa2c7A42EzGxTtdomIiIiIdHYJ0W6AiIiIiIi0nZklA/8EDgd+D3wAnAo8Hc12iYiIiIh0BcowFxERERHpXC4FxgA/cs5d7py7yzl3FrA6yu0SEREREen0FDAXEREREelczgJ2Affst/3XUWiLiIiIiEiXooC5iIiIiEjnkgUUO+cq9tuuDHMRERERkQ5SwFxEREREpHMxwAXZHmybiIiIiIi0gwLmIiIiIiKdyzpghJkl7bf9sGg0RkRERESkK1HAXERERESkc3kK6A5cst/2n0ShLSIiIiIiXUpCtBsgIiIiIiLt8ifgB8AdZvZl4H3gNGBYVFslIiIiItIFKGAuIiIiItKJOOf2mdl04HbgIvzc5UvwQfNN0WybiIiIiEhnZ85pbSAREREREREREREREc1hLiIiIiIiIiIiIiKCAuYiIiIiIiIiIiIiIoAC5iIiIiIiIiIiIiIigALmIiIiIiIiIiIiIiKAAuYiIiIiIiIiIiIiIoAC5iIiIiIiIiIiIiIigALmIiIiIiIiIiIiIiKAAuYiIiIiIiIiIiIiIoAC5iIiIiIiIiIiIiIigALmIiIiIiIiIiIiIiIA/H9aZ7il71nlfgAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "### Graphs deuxième version\n", "\n", "def Graphique(*donnee_toutes):\n", " fig1,(ax1,ax2,ax3)=plt.subplots(1,3,figsize=(25,7))\n", " for donnee in donnee_toutes:\n", " donnees = pd.read_csv(donnee)\n", " Type_init= list(donnees.columns[3:19])+list(donnees.columns[20:32])+list(donnees.columns[34:37])+[\"ExoEvalPair\"]\n", " Type=[i.split()[0] for i in Type_init]\n", " Id=[int(i.split()[1]) for i in Type_init[:-1]]+[4]\n", " Num=[(sum(donnees.loc[:,type]>0)) for type in Type_init]\n", " Label=[\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 3\",\"Module 3\",\"Module 4\",\"Module 4\",\"Module 4\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Module 1\",\"Module 2\",\"Module 3\",\"ExoEval\"]\n", " tableau=pd.DataFrame({'Type':Type,\"Id\":Id,\"Num\":Num,\"Label\":Label})\n", " col=[\"Type\",\"Num\",\"Id\",\"Label\"]\n", " tableau = tableau.loc[:, col]\n", " \n", " ax1.plot(Id[-4:],tableau.loc[(tableau.loc[:,\"Type\"]==\"Exercices\") | (tableau.loc[:,\"Type\"]==\"ExoEvalPair\"),\"Num\"],\"ro-\")\n", "\n", " ax2.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"Module 1\") & (tableau.loc[:,\"Type\"]==\"Quiz\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 1\"),\"Num\"]),\"ro-\")\n", " ax2.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"Module 2\") & (tableau.loc[:,\"Type\"]==\"Quiz\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 2\"),\"Num\"]),\"bo-\")\n", " ax2.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"Module 3\") & (tableau.loc[:,\"Type\"]==\"Quiz\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 3\"),\"Num\"]),\"go-\")\n", " ax2.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"Module 4\") & (tableau.loc[:,\"Type\"]==\"Quiz\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 4\"),\"Num\"]),\"mo-\")\n", " \n", " ax3.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"Jupiter\") & (tableau.loc[:,\"Type\"]==\"QuizP\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"Jupiter\"),\"Num\"]),\"ro-\")\n", " ax3.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"R\") & (tableau.loc[:,\"Type\"]==\"QuizP\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"R\"),\"Num\"]),\"bo-\")\n", " ax3.plot(tableau.loc[(tableau.loc[:,\"Label\"]==\"OrgMode\") & (tableau.loc[:,\"Type\"]==\"QuizP\"),\"Id\"],list(tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"OrgMode\"),\"Num\"]),\"go-\")\n", "\n", " ax3.legend([\"Jupiter\",\"R\",\"Orgmode\"])\n", " ax2.legend([\"Module 1\",\"Module 2\",\"Module 3\",\"Module 4\"])\n", " ax1.set_title(\"Exercices\")\n", " ax2.set_title(\"Quiz\")\n", " ax3.set_title(\"QuizP\")\n", " fig1.text(0.5, 0.02, 'Id', ha='center',size=\"xx-large\")\n", " fig1.text(0.09,0.5,\"Num\",ha='center',rotation='vertical',size=\"xx-large\")\n", " fig1.text(0.12,0.06,\"Module 1\",color=\"red\")\n", " fig1.text(0.19,0.06,\"Module 2\",color=\"blue\")\n", " fig1.text(0.26,0.06,\"Module 3\",color=\"green\")\n", " fig1.text(0.32,0.06,\"ExoEvalPair\",color=\"orange\")\n", " fig1.suptitle(\"Graphiques\",fontsize=40,y=1.05)\n", " ax1.xaxis.set_ticks(range(1,4))\n", " ax2.xaxis.set_ticks(range(17))\n", " ax3.xaxis.set_ticks(range(13))\n", " ax1.grid()\n", " ax2.grid()\n", " ax3.grid()\n", " plt.show()\n", " \n", "Graphique('inria_41016_self-paced_grade_report_2020-04-02-1234.csv','inria_41016_self-paced_grade_report_2020-03-27-0806.csv')" ] }, { "cell_type": "code", "execution_count": 250, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Nombre d'élèves qui on commencé les exercices : 326\n", "Nombre d'élèves qui on au dessus de la moyenne : 116\n", "Nombre d'élèves qui on fait ExoEvalPair : 11\n", "Moyenne ExoEvalPair : 0.83\n" ] } ], "source": [ "## Données supplémentaires\n", "\n", "exos=sum(donnees.loc[:,\"grade\"]>0)\n", "moyenne=sum(donnees.loc[:,\"grade\"]>0.5)\n", "Pair=sum(donnees.loc[:,\"ExoEvalPair\"]>0)\n", "moyenne_Pair=np.mean(donnees.loc[donnees.loc[:,\"ExoEvalPair\"]>0,\"ExoEvalPair\"])\n", "\n", "print(f\"Nombre d'élèves qui on commencé les exercices : {exos}\")\n", "print(f\"Nombre d'élèves qui on au dessus de la moyenne : {moyenne}\")\n", "print(f\"Nombre d'élèves qui on fait ExoEvalPair : {Pair}\")\n", "print(f\"Moyenne ExoEvalPair : {round(moyenne_Pair,2)}\")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 4 }