{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# kNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- KNN算法实现\n",
    "- EX1:约会数据\n",
    "- EX2:手写数字识别"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MLiA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Load Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据读取可以用Pandas，更简洁一点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Miles</th>\n",
       "      <th>VideoGame</th>\n",
       "      <th>Icecream</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40920</td>\n",
       "      <td>8.326976</td>\n",
       "      <td>0.953952</td>\n",
       "      <td>largeDoses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14488</td>\n",
       "      <td>7.153469</td>\n",
       "      <td>1.673904</td>\n",
       "      <td>smallDoses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26052</td>\n",
       "      <td>1.441871</td>\n",
       "      <td>0.805124</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75136</td>\n",
       "      <td>13.147394</td>\n",
       "      <td>0.428964</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38344</td>\n",
       "      <td>1.669788</td>\n",
       "      <td>0.134296</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Miles  VideoGame  Icecream        Type\n",
       "0  40920   8.326976  0.953952  largeDoses\n",
       "1  14488   7.153469  1.673904  smallDoses\n",
       "2  26052   1.441871  0.805124   didntLike\n",
       "3  75136  13.147394  0.428964   didntLike\n",
       "4  38344   1.669788  0.134296   didntLike"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data_df = pd.read_table(\"./Data/CH2/datingTestSet.txt\",names=[\"Miles\",\"VideoGame\",\"Icecream\",\"Type\"])\n",
    "raw_data_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pairplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PUV1arZPfUPqdKgbB4tLF5NhzqBhWwaufv8qUK6ZQMayCS7MvxRP2pBgP9111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cyc2Weyzz5rr/IuL7JkOoAzH2qJHpl1IyRe/H7RBYRaul1+mNsu5kRCLeD+aYDHKeamLDSKbvOB\nnYuF1w4IbUQ6jBLPS6glPH8p6cD54yLMqHaMr6YAXV5Tn5OuYuD5XHCPE7ZiB+Y8nIlTuXnwO4tE\nR4tAEUrwPYoCWUTNewFtBgH2c4prg/V4E3q9FczvDYVBh+1Sf+/8Y8CCtqFxHvpEhKb3rwmGgOEq\nAnK2Ak3uAsBDx2neSxGWFtf2/wlDUV7s1W0+8N1bYC16o9DDkKDzQePIFUYsANz3MvDJeLC1g+Ht\nszJ4HY25qz6M6waFPuPU68Vm78vJQM/FUTZ3CaLAw6iUiSHihwqp9o0lqNpXCVX7qlLpVkDUeeq2\nAV4n4CgQi3rRacCUBIADq/pFVvr1XCLORn6T6LUE+HQCUO9GoFVf4aVzForwrscJwA8YEsR7MQbo\nzICzADi5G6jXFjBVEzfnrbPE+9ydrTQYpbwsKUk/IJTL/jtL3ERdNjH288fhMiRh9EfHkFvkwaKB\nrUVSeTh+vzBUDRZwtw1FPiOGKnL+MlHTaoDd41NUlgIi52/RwNawGkLhOrWWbtIx4swArPTBlmk9\nDWhTws8Bv1vMlcSrRN5ackOg6AzAvUBiHWF06fTA3lVA64GANVVUqDbtFjLMik4BWoM4nscu5pI0\nH4vPAv9cK+brOplh2HupyH8FwL0u0clDykd9eAWYzys8e4qNzxvAFy+I99WaRFGUWiUtIKppAWGo\n3Z2tvoGSVRSj80zh+btpqDCg8n4Tv7cZBFhSxTUuVSiHF3ZJx3hkDXDheCCEHDj/nz8Q1dBeF5is\nwjk4Dr0ZsOWBp6bD5yzGG9+exrC7GkOT91voOMZE4P0nQnnAm8ZEvDd/5F2A+8EMVrFOSJXV6lT6\nPCUiIeNPDTL+4oLLaChW+mIV3fhTylYEF/VqdYAptSMlGCaeBba+Ctz4qDASJSPP6xKVe3LPSa8l\nIhfQVRDpUdm/BrhxCGBOAuRSD817Afe8KF5nsIK7bWA73hD5fRIN24P3fQecaaFx5EeMnVtSUOjV\nw2rUQscQNPTgtoublT1PMR7eeylchprBBHzJa1dSt458mzto3IXLjwDq3T/igNidp3L8vtBGInyD\ncsdzwsiTb04kQ01nEHPAYBVese8XifSBzjMBYzWR86o3K+dq76WAzwPsXQk0fTDkUTvwLvDLh+Ja\nMSYBzvPCW553SHi/bxoqCkTCDSzJKweoyqRgYqBecbIsV7XFQ8L7qLeIufzRM8oiDEkaJfdXIPcI\n0PgOYQC67eI1gNDz1JvF9Wqurrzm5MdY1jVyzD3eAjdVA1P9rAcpjGLeaymgNSiMYXR/Q7z3rn8D\nmf2EoS2//vqsAPPYROGZ/HO3pEYzACt9nhKRUKCeIOIJ7lMv4IiWR5V3SISBTYGb5c7FQMFJ4W0J\nS0zHukeF9yP88Q+GA+2eEDdvKcwLhMJR7z8BTG8ILOsqQnw3DonIHWLfvQUGrj527sPjb++BzeUB\nt+cCq/qKm92qviEDNUxU1sSdItFeloBfUreOrFV7g/1HJfkROfI+sMQlxO8DbLnAd2+K3wd+ILxJ\nUm5f0wcjCxvWDhaaXfZzwOpHhNH1bn8go58IXb47QDz2wXDA5wUeWR0qCPE4hFHy9cvAwpuFUfZu\nf6BR+9B8YxCbmSm1hFerVR9wY4J6eDM1XRiu54+rX19FpwFXodDQk86r6LQY1+RkcQ5Fp1VedwZY\n2A5Y9z+RIVR7rjCSp9QG1gwsOUeyx1vKa637QnC9RT0Xt+mDwvALL85ynA+7Jp8QovGtB4pr+9Pn\nhIfz+Vygx1tgTBNSHJD9z+CxX+QkISoDMv4IIp6IVmBhSopMHu82X4SCGrQDnEXiZtm0i/he45ro\nx4kmH/Nuf+GRe/htcbPr/KpKVeVgQKsTHhN5hebW6cqxN+8lbpYDRYF+aqIebkexyA+UH88Q5aZs\nsER8NBa9NqJgZHqvlliw5YjCuItmJFJRyGXAbQP2LBf5bav6hQyujpPEHIhWtRuQFoowSlw25WPv\nDwU4F8dd2E5489SOl5Ie+tmQIMbTtFtwc8Mk/To5DdqJ3Lfv3gTMNSILInouClwXA0LndXe2yMcz\nBTTvNFqgx5sRBhp0JnH+DdoJj5+ESrUwvl8UWdjVbb54XG8RBqB0rX2RDbZmALhL5XyifdZSTmDz\nXsAzP4pwMuciB7D3UqHJWOMakbeo1YlzK+M1ScQucRXjIIgqT7QCDinn58G5Io8q/5hIfi8+KzTL\nzEmhm+CJHaGEeimhXMqncgX6m8rDttLxE2qJv0th24lno1cSa43A+iHKTiPyxPowXbVZ3RdDV616\n5PGiCdO67RHJ5kJ7zYBFA1vDYtAFhZ437j+Fdmk1gxptkpEYnvMXXhRCXAKMCcLjFK7r98FwMVej\niAazaJscyVCRP2awho4hn9ey40niyMGfN40RxtKP60LV6d0XAvtWK8PF+1eHroWbHxcC6lKeG2PA\nyr6RIusPvyM8eU/tBRKvBor+Euda4xqRr+j3CU/8A6+K1zGNyIvUaNSrhbdOBzo8C/RdKd4771Ao\np/bYVrHR+vx5cQ33XAwUnQLjvsiCGKlCOPyzOX9crAH3TwOgCaWVSKLvikKTpcK7WsZrkohdyPNH\nEPGERqfuSdg2Wxh6Wr1Y5BNri7yjQRuFNEXRWeUNYOss4T244zmxwG8aI7wXq/8pwj2y/qZBD2KH\nUcqwbTRpGEeBSI6/O1vkPzVsD3vXRXj7hzy4uy9W1VUzbBgSMmzl/PyhyEuSn29Au0z149EwWA06\n5NvcyN74EzYd/CsgGRMy7iQjcfGgNiX2/SUuAa7i6B6n5IaARh/pUeu+MHqo8/zxyMcunBB5ag3b\nhyrW1a4P+VyWewOlEKrjPHjrQaK4Qgo1N+sOTDonDEKDJZjeEMzPi6aL6SgQ5+e2i0KWBW3FZsjv\nE3N/Si3hMXQVA9vnBwpi/OL50c7bYA15OKVNVeJVQFI94RlMvBoABwwJYN8vBnxuYXRKXsH9q1U+\nmzcAo1Vcky5baHN3bJtoIRmeprF2MOC4EOmJLOGaJGITKvhQgwo+4oIqWfDh94mduVQxK1X7Gizi\nJmhKEs/x2JWFFT3eEuEuo1XccIyJIgfQVEM90b3vO+L5548DW6aIm014b1A1CYpu88XNKO83ICVd\nVOe6gYkfH8bG/afx4oPXY2CbWmB6S8hbGejZyp/PBYrPik4Nss4g35wCrk/RIyW5RrBnqx+sRKmW\nKiLlUuknVOp66nGK4iK1OfbQMrFZMSYIo8NgFfNm22yxwYnoW/2GKAKRe7PkUkQdJwmNP48TABeb\nHoNVGHbGQPW69B4/fyQMuk2jQwVNNz8ucgzVij42jQ52/YDjnKhGvnmo2CyFP//hd0LdRaQ2c8YE\nUYG8c0lEMRT6LBePt3syUI2bG1md/9MGIVK9ZmDo/dQqi6VzadVHyMmk36+8PvusEKFbg1Xk737+\nvDhWryUi1AuErvEovYClIjJ+8+Ng0udK1b5xB4V9CSKecNuE4GzTLoEH/OKmYrAIw8/jEoafXJZC\nyo3qtzryhjpoY5TQbYJ4rrlGqL2WlPQuHffHdUDK9SIH0FRN3HR9HhHG0pqAXUvAmtyDxOSGmNI5\nDW2vqYG+zSyiClF+swLEe7htYCd2ipuhuTrguAB29Bs0SrkZbWd+F6zItYCVKtVC7dpiBJ0BKD4t\nDCK5pEnb/wX8HmDXUlmYtRi4cDJQRFEscgX7rAhJC33xgjimlNrgtoH7vGDFgfSD4rMhDb1m3SMN\nqD3LQxqYvZYA1hQx10xJwliKVvSRcl0on/XBucLIOfebuEZ6LVVKyvRaIrQ2pXSK8DZzUvs5uedO\nqwduHxWScQqOq5r4HEzVgMx/BrykAU3OEzuEt06tHWPnGeJ7jzfERnDQRnFsMGDHQuVnkHK9+P3O\niaFzLi2EXvAHsHU62O2jAg+SbReP0KpYxSn65ZXSnyQjnj2FVwQGq7ihfDA8lJOzYagyJ6dGlA4H\n4BH9UJF/LHqO1KYxIs+ox1tAtatFl4Wei4D1j4Xer/UgYfD9d1ZoXGE3XLZ1Oqo1aIf+D78jegCr\n5X4ZLOLmVqel8G7IbpZ1kmoCCFXk2t0+ZK3aG5RqkTqExKFUy5WP1y2KGxR9dpeKx3YsVJkzS8Um\n5ewvwkjyFAttwE1jQs8xWANeKgZmShR5eJIn+cvJIj0hfJ6ve1QYRV+/LH7fszxSYubhd0rOF5Ry\nDpd3C+UrWmuG5GDyDgnDbet08fwOo9RzHaVcQ8lzLt8MdV8ozqHmdZHjk2RqJFF3xqIXtyReJSRa\n3g/zkub9qqzu7/uOyCcsOiU2bEBI6D2a6LvOKDyacuHqkqVeiBiE/lMEEU+4baEbSrScnGitr9SS\n6L+eKhbu8DwgKS/KmCAqFj0OkbtkrAb0/reQfei7UoSR1/5PqIo4XDqmaZeQrEQ0z0pyQ3BrqshR\nCj/GB8PhdxYDkHXykEm1dG1VB5+O6IC3H70J4CLcS8QQPrdKj9rBALiyEET+t+KzYgPz4FwRXpVL\njfR9B9izTIQjdywU3uniXGGQSblw0XpUSzl+zXsJOaLwcX3/lnpVrSRmLhmCUr7i7/8VnsxNo4Ws\ny8J2yn69JY1Do1N67uTSR11eE7qc0viadhMGY7W6APzCSJtSK7RxkyON8Y4JKtXSTwqDVPoMOs8U\nYey834DPXwA+GQv4nIAlRRjUPReJLkJh1cRYOxi46TGRDkJSL3ELGX8EEU/IDahoNxdTUmRid483\nhbZY+M2i6LTI15ESwx+cK0J1QKCCzyZuQv6ADAr3CwPQlituvDqzsoo4fCzyG25J/Vg99qjGodaU\nqCjakKRauraqg1H3piN7409In7gZQ5bvxjmbmwzAWCKawW+wliw9sjZgBLbqI+bcvExRaGE7J7x3\nfq/YWKx7VBghUvHSk98JIySaUSR520zV1KtqrSnCyJl4VqQz7F8T6icsk07irmLgHw+IDiSS9NGT\n3wnRZsmAlBuC8nG4beL4Na4RBphcI1CSVZIkl6TxSgVZ7w4ANEy8vlqdyI1bt/kinzFav+KUdNkx\nRws9zU2jQ231XmsOrOwj2ufZcoWH9vWWIeNWXh0tha6D/1Mq+IgnyPgjiHhCXhEbrdrWWSi8BH1X\nCm9Jv1XArx+LFlrhN4teS4QHZV6mWODnZYob750ThQHJmAghSZWGqx8ReUlrB4ubV8EfoRtrtBsu\nIDwO3y9Sb2RvqSEKQNSqfRu0Azw2RUWuJNUy8p7rMHbdAezIOQevnwfDv5KYMxEDRPufuoqj/03u\nXfP7RQcZIFLqRdpw/LhO5Pm1HigMmY+eidz89FoijKIOo4W3Mep8/U0YOZOTxXy9+XFxDT04Nyid\nxHstAfvuTZFH63GIquD3hwp5o6ZdhPE28AOg+jUijB2+CTNYxfNtuaHKYkn7sMNYMTZ5b+Nw7+ja\nweAeu+jE4+ehjVuf5SIc3KK3KP5S/dwLgQdfV/Wwo8PoUOWupLMY7XNSq7p2k+cvniDjjyDiCY0u\ndGNTk7XotUTctCRD7cIJYaxd/0CkWn+/VcocJQnpxqszA4e/Et4JxoDHtwmNPmNiSCtQaxJj+Pkj\ndcPu54/E7ynp4n2+nBzyrHSeKTwnxkRRwfzdmxHH4L2Wguutik4eklRLg5oW6tQR62gNkQZQt/ni\nf63Vqf9NEibPPSQKl7SGkCCyqzAkEM4YMGyX+D2tQyhMevA9EZ4MhopXivaDLXqLjh0ndoSkjqLN\n14btgcxHxM9FZ8V10nMR0Hcl2J7lwvsopV0k1BJCyB9mCU/a6kfEpmj7fFH81G1+yJP4y0fCM3nH\nhMiw8wfDRTh166zQ+KJ51A1WYZx9NkEUjCzvBsy6FgAHfK6Q/EvE2rA4ukRNarpYEywpoRQRtc+p\nR0D0OvzYenNFzSriEkDZ0QQRT+hNwKHNoYpYj13k4Flqit040yqTuj8YLhLonUXAwA2B3r7VRYWw\n1gicP6Ge5O4qEh6V9PtFqElerVh0KqQV2GuJKABpP1LccKTqSY9dhJlvkbWGG7ZLhOgWBjwJDduL\nG7Q1JZSflPerMA5T0gNCuhr4/H5oVBLJbS4vDk3phCNni7FgyxFs3H8qmBdIhR8xgs4QCKXKiiK+\nnBd9/oIAACAASURBVCxCqbePEvNSmstStes9L4kCowsnhGG1VlZla0wUYsThci/V6igNmh/Xifd4\nPlcYY4M2iuKEx7eJ10ghS2muOQuE0djuidC4fG5h0BWdFt6w794UxRHSZkkyzB7fFvKkSYLpSfWF\nIff9IuENnJwckI2ZATgvRA/LGquFBNeLTot2i6qCyjbxfEmGRSoCseUJb6IkM9NvNYT2X0DaJe/X\n6FW8bhv8eiuY2wYGf/TPadMoUSUsXet5h0QBTbsnSeQ5jiDPH0HEEx4nkN5JVMS+lCo6DHjsQkB2\nXqYovpCSugERsvXYgINrRU/fNQOBKanCoLOfE0ajmvdw3yrhTQkPD+1fIyoOB20UoWFbrrhJLWwH\nTK4JzGgkvBCAOLarUFQzvpQaIfyMXktEwYk8L+zHdeJYU2oBxgSwVX2hc5wT4b8Afj/HOZsbjy3f\ng/SJm5G98SeMujcdI+++ljp1xBoep6iKlRdF/LguJAb+x05RLb6sqwjXehwiJPpSqph7HSeJOZzc\nUMw9V5F6IUM0ceT8Y+I5bptS3Lxhe2EcbhojvHSbRgG/fCh+XtZVGJqfjBUGoVTQ0LSLMgwq/SwZ\ngRH5eYF+xCnXAfdPF7I1qdcDhsQSwuGFode/P1Rs1vqsiOyV7bKFXv/jOuD1VmLzJ+/dm/cr4MgP\nXX/vDxXjy9ka6c3rvhAcAHMXg0laoFKKiPQ52XLF5/TjukC/8KTQ/3TrdMr5izPI+COIeMLvjawQ\n/GB4yOCTF1kAoao/tWrcDU8AzvOAxiDCPVKI7MRO4LPnIkNOkm7Z6kdCxhwQeXPqtVTItjBEhrak\nasZu84VHqOh06MYsf59hu8TPnWeA7VmmqCS0e0JSL1Ku39h1B/A/tzWiTh2xBvcJr5Na32lTYiBc\nOzh69foHw8Uczj8mwrBGWaGGvD80Y8DDYfOw91KxuQCEt637QlFE8tWUUEi4x1uhNojy7h8Ga2RB\nQ0q60niU0i4k/Uu1/LwNTwhDqll3YM0Acd28218UUIWFZXmvpcJTKH/9+seEIdr3HRE67rdKeE4/\nnwgenr8b7k0M78gjfZ5pHcQxpM+g8wzg101gjvNg0rX9/lAh09PjjUA+4QpxvUqfiTyfV/qdcv7i\nCoqNEEQ8EVWINmDwScnYGp34WbohRMsdqt5A3GB6LhJhtlMHgMa3iwXfWSBCR027hEI+8g4Dkkek\n2/xQWMhjF7k/9nMid0jtPfUW4IN+4ubTa4kIVUt6YkHtwrCuBbJ8IrnUi8SuY/mwGnXQMDL8YgqD\nVeTu/fxhaI7kHRJevBsfDVW1AtHnaHJD4UH8MEsYiCr9oYNac4+8K+aKq1jkChadFsf5/AURLpY0\nK/OPATsXi64ZPd5S9stt2F6ESAFl32tngXhMMpykccEf0LmLMt9N1YBl/ZXXzZoBYqP14Fzw5Ib4\n82we6lprquffGhJC2oI+Z2iMhgRlr+ELYSkcJVXgF58Vnrp1j4rjPbkjUjB6wxPif/Z6LbEeyNcV\nSTRb+p3au8Ud5PkjiHgiaoXkbyGvm7l6SLZF6pEarWov/5i4iXqdYvFu2kUkqfs8YmG/fZQo6nh/\nqPJGLXFih8g1kuBceABKqxTsvVT0H7amisd1ZjHeLq+peyvctuAhJKkXOVKuHxFjeJzCWyefR5vG\nCA+yKUkphxJtvrhtwoNYdFqELHstUe0PjbWDRZ6pVHThKgh5A3/+ADj+vcgZXNZVpEhsHgN8/KwQ\nL980Rsz7p/aKlAZjIvDQCmEwSuLHjgvi95TrheHEufiuswhDzBWlH7GUnycnoKHJDVZ8+uNfokdG\nuAdcer2zQGyKElKF4fbUXvA+K8B0RrHZWtZVpHTsX6P0sEoeyfDjeexC0PrEzpAnryRDUcoB1ulD\nnsKfNogCmudzRV4hCTzHHfTfIoh4wmBRqeJbKvKK+q4Ui3TxGfFcS00g77AQbVarxu02XxRg7AsU\nhKz9X3HjXNVPhMm+ezMU3r3v5eg3J1dRKE9p9SMh76RapaBk9FlqCo+FRiuKWD4dL7waakLUkth0\nAEnqpV1aTeg0TKEBSMQQfj/gLgrl8EnzqN9qYagU/CE8guFh1PD5orcK73Dv/wOu7yw8TtEKJmpc\nozQGmSYghXIGaHBj5Pz6cZ3w5D2yRoxNXrHbqL3YBH2YJeb2h1miT/Etw8SmRROYbxqN2LwA6uNn\nmqhyN9yagvsa6lB38/+CGSxRwuPVxAZtxxvCWK5xDZhGA/i8ofzHrTOBNoOEoSqlcCTWEh79iPFo\nxfV0zU2lG4rnj4v1Zv9qoRbgLBAG4bX3ApYaAEdACJ5MiXgj7sO+jLH7AbwOQAtgCee8fP3KCCKe\n8LrE4v3gXHGjO39c3FzcdmGshbeE6rNCeE1a9BbVuH1XBprby8JcT34XyrsC1NthrR0swmO9loT1\nTJXlKUmvlToPhFcKuoqAj0eKkFO/1SGDzm0PFY08uSNKJaI9+HxJ6mXxoDbBdm8WvZZy/WINjz1k\nnAChedRvlagC97mAjL5i8yFVA3scylCm3howrkyiF/Da/xHHadWn5FZsQChk+koDMa82jRFzMfx1\nRafFWMLH6jgf2SN7w5NifJqwjYZGIwqhtMbI8YOrXDdLAIMVGq9LPG/gB8Kw2r8mMjx+0xDxGam1\nwku8KjQGrzvU97dBOyHJ8stHoeOdPy6KTaTCDEuquA4NFuGh7b1UUUXNey8F83Pgs4niM5KkYqTe\nwL2XXpJpQlQOcW38Mca0ABYAuAfASQC7GGMbOec/V+7ICOIywf2hG6BEw/bihiN1PCjpBibdBOWv\nj9ZpQV44cmKHuNFsfTXQ1i1BhKAN1sg8JallnOR50ZpEQr7HIQR7E+sIw8DvFzdNvSX0fLV+oir5\nRBoNC8q5kKxLjGKIoicnGUbvDhC5ex1GiTl4/rj4P89pJvu/W8XrJJkX6XgarXrf2S+yQ+8lpUMA\nobDm1lnCEy43knotUU9pqHFN9PFLc1eOZKQGi5NYaKzW1MjrBkx4Rj/MCkmzhG/eei8VYXN5Kzwg\n1Arv4RViTegwSpyT/O/vPy4MP0laSaMTHkH5eKUNmMEixi4Zg247mN4srtmei8SYv3tTbAal468d\nrNzEEXFFvK+aNwI4wjnPAQDG2GoA3QCQ8UdcmUQLixqs6nk74TcwKRQr9yBIeYQleVGk37dOF/lb\ntlyx+Heeqe5J8XORfO8ujtRke39oSDtNyhUK90IEvSd2YRBQWCn+kORXwudV/rFQ2NbvDXmINTqR\nqyoP24Z7iKXjJdYR80jyahX8AeiMwqscLEpYKvoAA6F8wh/XAfVuFILLUl/bPcuFJl/4WKVQaPj4\nC/8SAtXheW5+P2DPVc734BzXivAtEPoul60BQobVw2+L50ieQ489+gbNWE3IJ4XrHEp/l2/gwjzo\nEciNQbXvqsUoVOQRr8S78VcXwB+y308CuKmiB9HQubKi35KoqkQz1JyFIfHlkm5gP64TCesPrxA3\njrxDgNGq7g2RV/N1my/CxJKxKM81Cjcmuy8E9MaAl3JwZNhM8kbIb+7hXggJ8irEL3KPrrxy+8vJ\nomCjTGFbi/rx8n4LpQpI3PFcSHjYbRObhzaDgGNblR7ltNuF3Ir8vYHI0KwxUf26+HRCZOoCUEKY\nO4p3TG0jJ22ulnUVr5M84+6i6J/XpjHCq6j2d3mF7t+pyI1myJdkTBIxTbwbf2pJPhFd3RljjwF4\nDAAaNGhwucdEEBdFmeappJkmN7a6zRcL8PcfqdzAVAy7jH6ie8HybuKxYbuECLQ8V8nrBG4YIG5E\n+cdCWmiBXCWFKDMgPICp6YGuHFoRQmIo2RtBnoO4pMzradCju0oYHfI8U6aJNAzVwrZy40LuIdab\nhWdvnez1rfoAO5cIg680j7Ka0dXhWeU18NEzYgMTzMH7LaR1p9FFzt2oYe4oc1wqoIrWvUN6nUYj\nchfDz1cypKWCqPDPs/dSkeP3fO7f96CrGfIk7xLXxLvxdxKATGcC9QCcCn8S53wRgEUA0KZNmwjj\nkCBigTLNU49DPSm83RPiS28J3ezyjwGfjBevU2vPJOUgeZxA60FAcS7wYT/lzeiO50Rzeynvx2AV\nYwj3JgY9IYmh15YWTibPQVxSrvVUowHAxEYjPDXAkCjLMbOJcK88bKtmXMg9xFaZYSfNzXZPKo0c\nNY9ytHnptgkjiwXGXHRaPEfa4Ejt2YLPD5u75fWOyfUt5Qaw84KK4SvLGwwv2GrYXjxXbuiGG3t/\n9xoLN6QpHSPuiff/3C4A1zLGGjHGDAD6AthYyWMiiMuH3iI8G5K0yqYxwnDTW4ThpQnIOHAIr1/x\n2VB7psI/hbZZ8VlxDOlGZ7AIj0ZirVBLJ0kaQv48U7WANIsl8nlqN2q153VfKEJw0V5DXHlEmy86\nk5irLFDMYUwSxkVZteMkw04+N8siOxJtPAbZay9m7pb1upDQmcR5Pzg3pMupMwJ7V0U3fA0JgD1P\nXM8/f6B8D/nncTnkVy738YkKhXEe344wxlhnAHMgpF7+zTl/uaTnt2nThu/evbvkg2YnlWsMVSnn\nL/Ef4yp7CEEODjp4uQ5d6ZohJc5Tv1/kF5W2A1c8LxCO1Zuiv8bvF+FeqSWXXGqjosZAlIfYnqdy\nyjpfKoqyjOdi5m55z1P+fLlnvaTXxdpnWTqVPk+JSOI97AvO+SYAmyp7HARRYahV5ZX6PFk4tqRq\nP0WxRaL68y7nGIgrk7LOl4qiLOO5mLlb3vOUP1+qAi7tdbH2WRJxSUxvFwiCIAiCIIhLCxl/BEEQ\nBEEQVYi4D/teDqpSDl95KfqlfN3zYilHkCAIgiAIMv6IOKbFshblev5lLBAhCIIgiLiBwr4EQRAE\nQRBViLiXeikvjLFcAMdLeVoKgLwKGE4sU5U/gzzO+f2VOQCap0Gu9HP8O+cXL/MUiJ3/Y6yMA6g6\nY6n0eUpEUuWMv7LAGNvNOW9T2eOoTOgziH2qwv/oSj/HK/38JGLlPGNlHACNhahcKOxLEARBEARR\nhSDjjyAIgiAIogpBxp86iyp7ADEAfQaxT1X4H13p53iln59ErJxnrIwDoLEQlQjl/BEEQRAEQVQh\nyPNHEARBEARRhSDjjyAIgiAIogpBxh9BEARBEEQVgow/giAIgiCIKgQZfwRBEARBEFUIMv4IgiAI\ngiCqEGT8EQRBEARBVCHI+CMIgiAIgqhCkPFHEARBEARRhSDjjyAIgiAIogpBxh9BEARBEEQVgow/\ngiAIgiCIKgQZfwRBEARBEFUIMv4IgiAIgiCqEFXO+Lv//vs5APqir5K+Kh2ap/RVhq9Kh+YpfZXh\ni4hBqpzxl5eXV9lDIIhSoXlKxAM0TwkiPqlyxh9BEARBEERVhow/giAIgiCIKgQZfwRBEARBEFUI\nMv4IgiAIgiCqEGT8EQRBEARBVCF0lT0Agrjc+LkfDq8DZp05+F3Dqt6+p8WyFuV6/sFBBy/TSAgi\ndqH1gqgK0Iwmrmj83I98Zz6e+uoptF7RGk999RTynfnwc39lD40giBiD1guiqkDGH3FF4/A6MGbr\nGOw6vQte7sWu07swZusYOLyOyh4aQRAxBq0XRFWBjD/iisasM2Pvmb2Kx/ae2QuzzlxJIyIIIlah\n9YKoKpDxR1zROLwOZNbOVDyWWTuTdvIEQURA6wVRVYgL448xVp8xtoUx9gtj7CfG2NOBx5MZY58z\nxg4Hvteo7LESsYVZZ8aMDjPQ9qq20DEd2l7VFjM6zKCdPEEQEdB6QVQV4qXa1wvgWc75D4yxRAB7\nGGOfA/gXgC85568wxsYBGAdgbCWOk4gxNEyDZFMy5t0174qr3itv9S5BECVzJa8XBCEnLmY05/wv\nzvkPgZ+LAPwCoC6AbgCWBZ62DED3yhkhEctomAZWvVXxnSAIQg1aL4iqQLx4/oIwxhoCyATwPYDa\nnPO/AGEgMsZqVeLQCIIoB+XxXJLmIEEQxKUjrrY0jLEEAOsAjOCcF5bjdY8xxnYzxnbn5uZevgES\nxN+A5ikRD9A8JYj4J26MP8aYHsLwe4dzvj7w8BnG2NWBv18N4KzaaznnizjnbTjnbVJTUytmwARR\nTmieEvEAzVOCiH/iwvhjjDEASwH8wjmfLfvTRgCDAj8PAvBBRY+NIAiCIAginoiXnL9bAQwAcJAx\nti/w2AQArwBYwxgbDOAEgIcqaXwEQRAEQRBxQVwYf5zzbwCwKH/uWJFjIQiCIAiCiGfiIuxLEARB\nEARBXBrI+CMIgiAIgqhCkPFHEARBEARRhSDjj4hJ/NwPm8em+E4QBEFcGmiNrdqQ8UfEHH7uR74z\nH0999RRar2iNp756CvnOfFqcCIIgLgG0xhJk/BExh8PrwJitY7Dr9C54uRe7Tu/CmK1j4PA6Knto\nBEEQcQ+tsURcSL0QVQuT1oQJN05Ao6RGyCnIweKDi/H5sc9h1pkre2gEQcQIfu6Hw+uAWWcOftcw\n8meUBbPOjL1n9ioe23tmL62xVQgy/oiYws/9OO88j6k7p2Lvmb3IrJ2JybdMRlpSGhxeB6x6a2UP\nkSCISkYKW47ZOia4TszoMAPJpmQyAMuAw+tAZu1M7Dq9K/hYZu1MWmOrEHSVEDGFw+vAmG3KcMSk\n7ZPwyD8eoV0pQRAAKGz5dzHrzJjRYQbaXtUWOqZD26vaYkaHGbTGViHI80fEFNHCEQn6BNrREwQB\noPxhSwoRK9EwDZJNyZh31zz6TKoo9J8mYgopHCFHCkcQBEEA5VsnqLJVHQ3TwKq3Kr4TVQf6bxMx\nhYZpMOXWKYpwxJRbp9DCRBBEkPKELSlETBCRUNiXiCmMWiPm/jAX428cj7SkNOQU5GDuD3Mxtf3U\nyh4aQRAxQnnCllTZShCRkPFHxBQOrwNnHWfRc2PP4GNtr2pLVWgEQSiQwpUASlwbqLKVICKhWBoR\nU1AVGkEQlxJaUwgiEvL8ETGFhmlQw1gD8++aDw4eDOkQBEFcDNFCxABg89iCj2mYBkatkfKLiSoB\nzXKi0lBrLO7nfhR7inHBdSGiOs/hdVT5Cj2CIMqPvKLVrDPD5XNFVACfd55Hkbvosq4xamseQVQG\nZPwRlUI0+QWXz4UCVwEmfjsxojov156LIncRLZ4EQVwU0rqTa8+NqACe+O1EFLgKLlukIV4kZ8hA\nrRqQ8UdUCtHkF/zcj7oJdVWr8+om1oXNY4v5xZMgiNhEWneirjEJdS9bLmA8SM7Ei4FK/H3I+CMq\nBbPOjFrmWljfdT32DdiH9V3Xo5a5Fsw6M/4s/lNVwLXIXaTqEZQWT9qxEkTsEUvXpST7klOQo7rG\n/Fn8Z1Rj7O+eRyxIzpR2DvFgoBKXBir4ICoFl8+FrBuyMPHbicHG7FNunQKXz4UkYxKm3Dol4m8J\n+oSoiyc1eq98WixrUdlDIGKMWLsuJdmXxQcXq64xVr1V1Ri7FOdR2ZIzZTmHWDBQiYqB7opEpeDn\n/ggv3sRvJ8LP/Ug0JKKGqQbm3TUPewbswdTbpuLrE1/D5rFh94DdWN91PTo16gQgtHjSjpUgYo/L\neV1ejCfOrDPjtTtew/CM4ahtrY05d8zB7v67Me+ueahhqoFEQ6KqMXcpzqOyJWfKcg7UXrPqEBee\nP8bYvwF0AXCWc9488Fg2gCEAcgNPm8A531Q5I7yy8Ps57B4fLAYt7G4fLHotNBp2Sd+jpB2mhmlg\n0Bhg89rAOQfnHPc2uhfPfP1McMc6+ZbJSEtKQ+/regcXT9qxEkRscbk8SX/HE+fxe5C9I7tcr7sU\n51GeriQXi3ztdnp84MyleK/SzkEyUMM/V1pHrzzixfP3HwD3qzz+Guc8I/AVl4af389R7PLCzwPf\n/bzSx3PO5saQZbtx3XObMWTZbpyzuS/5uEraYdo8NhS7izFiywgcLTgKj98TsWOdtH0S+v+jf3DR\nph0rQcQel+u6vFhP3N95XXnOI9q6Lpeckb5Ho7yeTfnaPfLdvTjvUhZuFHuKSz0HuYG6Z8AezLtr\nHqXOXKHExX+Uc74VQH5lj+NS4/dzFDk9yCtygXMgr8iFIqfnkhhaF2tU2j0+ZK3aix055+D1c+zI\nOYesVXth9/j+9pjkqIVApt42FYWuQph0JjDG0LF+Ryw6uAj1Euup7lgteosiV4VU/Akitrhc1+XF\neOL83H/RHrxo58G4MWKNvRQbaMmzueLnFci5kAOTzoRiTzF8/ujrsHztfvKuBnh++ziFkbvyl5WY\n0T7yHExas+JeAc7KbKAS8UtchH1LYDhjbCCA3QCe5ZyfV3sSY+wxAI8BQIMGDSpweCXj9PpQ5PJi\n/PqD2HUsH20bJmPmQy2h12lgMZT9XxMepjXrNMi3e5C1am/wuHP7ZaKm1VBq+NZi0GLXMaWdvetY\nPiwG7UWdY0lY9dZgCCTfmQ9wYMw3oXDD9PbTsT9vP04VnwomSndq1AlDWgxBWvU02D32oAFYESGV\ny02szlOCkFOeeXq5rsvw4olOjTpheMZwAKGuHeHv4fA6cM5xLmrRhXx84eNUOw+vR4/B/9kdscbK\njTAAwQ304kFtkGAMret+7o/6fg6vA2t/W4suaV0wafukUAi2/Qwkm4UnLiI9R7Z2N05JjjBy39r/\nFoa0GKI4B5PWjHzbxd0riPimwu+MjLFrGGN3B342M8YSL/JQbwBoDCADwF8AXo32RM75Is55G855\nm9TU1It8u0uP3w+Mfu+Awss2+r0D8JdDQUB1l2l3Y9X3xy/Ke2d3+9C2YbLisbYNk2F3XzrPn7Sr\nHfblMNy26jY8+tmj4Jxj7eG1SDGnYM2Da7D4nsVweB0YccMIzN07F1NunYJhGcOQlZmFaTunoc2K\nNsjakqXQoCpPSCUWidV5ShByyjtPL8d1KffEPdDoAYy4YQSyd2SXqE1n1pmxcN9CTL5lsor3y1Sq\nvp18/NxvxONv/6C6xpZlA12anp5ZZ8bdDe7GpO2TFN67tYfXwu6xBzoh2fDvb3KC636x0xtcu3/P\ny1cN8Tp9TsX/wuHxV0ikh4g9KtTzxxgbArFjTIYw3OoBeBNAx/Iei3N+RnbcxQA+ukTDvCSUpWjC\nYoyySBjVvWyKY7p80GiEARm+y3x61T5kd22G2V8cVh63DN47i16Luf0yI3aCFv2l8/zJ824AYNfp\nXRi7bSxevvVl+LhPudPtMANpSWkwaAx45PpHMOLrEYrXjdk6BvPumlchUglE5VFeGZmDgw5eppEQ\nlYGal0zyxAHAU189Veq64PA6cNZxFnP3zsX4G8cjLSkNfxb/KYwglTWppLWlJANP2kBLazIQ2kBL\nnr/S3s/hdaBR9UYK712nRp3QJa0LsrZkBdfHF2+ehiNna2Pj/tP4z7dH8Xq/DDy9ah8WfnUCLz3w\nCp7fPq7Ewo2KjPQQsUVFu0aGAbgVQCEAcM4PA6h1MQdijF0t+7UHgB//9uguEWXN+bC7onjZXL7g\ncYK5GE4vipye0DGX70a+zQ1zlIu3Sa2EiOPaypADqNEw1LQasHhQG/z2cicsHtQGNa0GgPFLItRa\nUt5NNWO1iJ3umK1j0O/6flh7eC0SDNF1/oj44+DRE2X+Iqou0bxkAIK6fGVZFyRvYZ4jD30+7IMh\nnw+Blpkwfu0vsOgtJWiIivXX7g6tmyVFSKQNdLu0mtBpGNql1YzYQJc2ZrPODJvHpvDeDWkxJGJ9\nfOG78Rje8RoAwNyvjgTX7tkPZ6KGsfTCjZLOI9aKEYlLS0Ubfy7OuVv6hTGmA1DqjGKMrQKwA0A6\nY+wkY2wwgBmMsYOMsQMA7gTwzOUadHkpa9GExaDF3H4ZYYtEBiwGbcCAdCmMvSKXF/c1q42Ps9rj\n7UdvgtcnLkq1i7fY5VUc9/W+Gfi/b46WKQFZo2FIMOqgYeI7GL9kLX8cXgdOFp1UDUlEWxATDYkY\n0HQAVfQSRBWkpApdEf4svYoViKxkfaHtLEz/6A9s2PcXCl021WMUueyKzbZUkFeSgRdtAy2P/JS2\nlmmYBladVVGgkVY9TXV9bJwi1v+2DZPhcAfWZA5YDDpFiBecRRhz0c7DrNNUiOoDUXlUtPH3X8bY\nBABmxtg9AN4D8GFpL+Kc9+OcX80513PO63HOl3LOB3DOW3DOW3LOu3LO/7rsoy8jZXWli0XCGLZI\nGKHRMNjdPmSt2qcwINfvOYlOLa5G9safkD5xM8avPwhwjlkPtVJcvNN7tcT7P5zEtJ4t8NvLnbBo\nYGus3nkCs784fFF5HZdSqNWkNUGv0UdUzk1vPx12rz3qgijt8KmilyDii8vZFs3hdWDlLysj8/ja\nq68LQUMIDB1nfYeN+08DABIMVrx48zTFMV68eRqsBgu8fo7URD183IlEsw52rw1gvEQDL3wDHZ7y\nU5a1TKvRItkcMlYdHnWD8fe8fLRLq4mZD7XExA0HVQ21aNEoAKrn4fCWnAsYSy37iIujoqt9xwEY\nDOAggKEANgFYUsFjuOyUJedDQlokACDBqAu62tXyAe9rfjVGrN4XPG5qohHn7R40qGnBG/1vQKJJ\nhyNnbZj12SFs3H8Kuo9/wW8vd4LVqMPcr44ojlWevI5LJdTq9Xvh8DpQ21obTq8Tc+6cgwR9Aoo9\nxVj5y0ocKzgW0XJJviBeCRW9l5LyhkNbNKIKYqJiKYsYc0lVr0DJbdHMOjPe2v8Wcgpygnl8RwuO\nooapRonrQvga/ftZGz79qQDjMmegcUoyfs/Lx/u783FfMwu6troKozvXwwvfjYo4B/naXZZzkQhf\ny+wee9QqYynn0KK3RAowt5+B6qYamNazBWZ8ItZ9ABHVxaVVIIefR0kOjFhr2UdcHBX6n+Kc+znn\niznnD3HOewd+vuL8yGXJ+VBDvjs7fKY4IpzbpFZC8ILs2qoORt2bjvHrD+K65zbjibd/wJlCF3b8\nnodhdzbB71M744uRt8Pp8anmdWTd1aRMOYDApRFq9fl9OO88j6e3PI0J2ybggusCRmwZgZwLpg6W\nbwAAIABJREFUORixZQQW7FuAj49+jDk/zEF2u2zsGbAH2e2yI6oD472ilyCqEqVFDUqqepU2wiat\nWVWfTjKWMmtnYvPRzei5sScyVmRg6s6pcPqcJY7LrNfgrUHN8fvUTvhs5E3IyS1E37YN8MKGI0if\n+Ak+OZCPQbc0QpNaCZjc4zq88N34UiMfpVXwhqNhmqDMVdaWLLR5u02Jr9EwDWoYa2DOnXOwe8Bu\nTLhxAtYeXosLrvOY80XI8AMiN/flKezw+7miclhCyke3e+zUSvMKoELvnIyxLoyxvYyxfMZYIWOs\niDFWWJFjqAjKkvOhhnx3tmDLEUzv1VJhQNpk+X3D7myCseuUMjHPrtmPnjfUU4SFbS4vzDqNIrdw\n5N3Xou+NDfDY8j1lyue4FOFWh9eBsdvGYtfpXRjcYnCwr2+jJGVF2+ajm9FtQzdwztFtQzcYtcYy\nvwdBELFFaVGDkoxDaSOcPvETrNyRjzl3zA0WL1i01QHOwLgRL93yimJteumWV8B49HXDz/0478rH\niK+z0Obt1nhl7xi0bWxEslWHxf9qjt9evh//al8Hy7YfRfrEzUg0WMsU+Yh2LkKaRX2TXd6UGqfP\niRFbRiBjeQZ6bOyBBfsWYMzWMXjm3oaK54XLc5VHwsvu8eE/3x6NuP+83jcDEzcchFkXvTiGiB8q\nOuw7B0BPAAevRI+fnPBwblmQ786kXVx212a4tnYCipxefHskF9N7tcTYdQcUXkCJXcfyYTXqwlz7\n+7B4YBsYtBpM69kC9ZMtKHJ68ERAoyr0vL1YPLANEkyRY70U4VZ5NV1aUihxOacgRzWkIz0u5fsR\nBBF/lBSyLa1S99FVO4Nr1OzPD2PH7/mY1rMF7p7935AYcYIBM9efxLi7QuHamR+fwKt9UoJizw6v\nA4wbYdILGRbGXBEyK2sPr0Xva3tjzLZQKFOSUZE086Kdg0T0c7Hguuc2qwoolzelJtrz69eojt+n\ndsaRs8X49Me/0O+maxSRpvJIeFkMWsz96giO5NqQ3bUZmtRKwJGzxUi2GrBh3yk8eVf9Mn0eRGxT\n0cbfHwB+vNINv7Jo/Km9xub2KvJQNu4/hdwiFxYNbI3HV+zBjpxz6NqqDrK7NoMjSl5hkdMTXAQW\nbDmCTQf/gsWoxT8X7w7lt0ztHFVf0O/nqmOV555czAVu99iDC4bc4Ft8cDEm3zJZoe03+ZbJ+Cjn\nI0y5dQq8fm8wBFKWXBqCIGIHKWoQnh8m9/xFMyTU1qj6yRZ0bnE1ht3ZBMlWA2wuL84UunHv7O+D\nzxt5z7U478xXGHIv3fIKvthdjNuvq40GNSMNqLsb3I0x25QG4Qvfjce4jjMw/8vjeLHzNLzw3fgS\nNfOincvvefmKogl5Ll5pxnE40Z7/x/kL6DjrO7RtmIzX+2Ug2aJXrOPyaFRp9yWnx4cvR92MetWr\n4/e8fDzz7m/ILfIgu2szACjz5xGNPXv21NLpdEsANEectJiNY/wAfvR6vY+2bt36rPwPFW38jQGw\niTH2XwAu6UHO+ewKHsdlQ8rbK0+7HOk1q74/HvTs1a5mxIi7r0ODmhbYXT7UribCGBv3n8LG/afw\nYtemQUFP6X1e75uB5duPYe5XR9C2YTKm92qJJqlW2F0+xUJ65GyxquF44pwdKYnGMnsqy/R5BBKg\nLXoL5tw5Byt/WYmlB5cGCzs+P/Y50pLSMOeOOUgwJKDIXYQEfQK6pHXBnB/mIM+RhwUdF8DmsVGC\nMUHEGaVFDcw6kc8X7nErdmhU16jTBQ6MujcdY9cdwK5j+ci6qwle75uBp1eH1sF/3VYHI77OUhhy\nz28fh9dun4vHlx/Ei92bRBhQ4YLKQEhGZeP+79GkViLm3jkXFr0l6uZTzdB98eZpmLnpePA54Xl2\npRnH4ag9/6VbXsH0j44GDcynV+3DooGtYWUswgAsLRrl537YfRfw4q7Q8ac+OB06JGLyh78AADbu\nP40mtRLx+p1zYS3h84iGTqdbctVVV/0jNTX1vEajuaIdQZWN3+9nubm5TU+fPr0EQFf53yra+HsZ\nQDEAEwBDBb93hVBSVZVFr1X1CMpfcyTXhlkPtYRBp8Gq70/gvuZXo0mtBLzYrTm6Z9TB1dUtaFIr\nAcUuL7YfyQ265e1uL/7vm6PBrh47cs5h7LoDeGtAa2g0UCykC7Ycwdx+GciSGY7Te7XE7M8PYfbD\nGZfss1CtCms/AzVMNeDyuTD1tqlINafiL9tfKPYUw2oQO93x34zH5qOb0alRJ0y4cQL83F8u9X0i\nPmjoXFnm5yZi3GUcCXE5KSlqoGEa1DAlK6psZ246Dg3TRKxRMx9qCT9HMNcZQHC9WzSwNaxGXaDH\nrUbVkEswWLAj5xzmf6mP8FxJgspqXrt2aTXR84Z68Hp14NrokY9wQ7fIZceyb08F5WQAIKtjE9g9\nNoURWZ6UGjVj+rl1hxTvIQxMHc7Z3EGnQ1mjUWqdRyZ8OxZz75yL3CIXdBqGtg2T0a9tAxTbOaxJ\nDNxvBDgDyt4KuDkZfhWDRqPhqampBadPn24e/reKNv6SOef3VvB7VijyvL2urepg2J1N0KRWAhxu\n0aHj8bd/UHj1ip1KWZeN+09h2J1N8Omek+ieWU+xw+17YwPFDnd6r5aY9dkhAMCcvhmqci5SDt+i\nga3BOYeGaWAxauF0+zC7TyvUqmbCkbPFmPXZIeQWuWB3+VTz/i4G1RZG24TRZtKaoGM6DPl8SHAB\nfu321+DwOTDttmnIysxCoj4RBe6CSyY1QxBE7OHw+PHChiNITTRi2J1N8NrDN+CPfDsSjbpQmNLl\ng8/vR4JJHxEOnvvVEQzveG1QU68kQw5A0FB6qfNrqG7RiYpbezFmtp+N0dtGBtej6e1noIYpGW/0\nvwEJRh1OnndAr9XAHPCoqRtUou/vPxfvRGqiEaPuTceO3/PFGt6xCfq1S1a0Z5MiGHLjWNLOi2YM\nyo1p7jfiTGGwbwIAsdE/crYY2Rt/CjodwqNRr/fLQE2LAVptpPdSba216C1YPLANLEYtzhW74PZy\njHpvf5mjW2FoyPCrOAKfdcRuoqJjZl8wxq5o40+qqpKkWKTK2yHL9wQ7dIy8R0i0jHx3H/KKRfT7\ni5G3o2urOgCEpMt9za/G2HUHkJpoxMdZ7TG847Wwu31ITTQG3ftj1x3A6PvSMeredJw4Z1et5jpT\n4MR1z23G/31zFE6PH0OWC5HPwct2Q6thWPDVYTwwdxtyi1yY+VBLaC7hjCjJaGOMKQRMF3RcAA/3\nYMI3E9Dm7Tb4KOcjuP1uZO/IRs6FHOrsQRBXCOFtw8w6Dd7sfwPG3C/Wy2fX7AMAGPRa0f+Ji021\nVqMJ5jrLkbfEBNTVCaa3n4FPDiqNRmhcQVmWMd+MgMvnxvRbXw+uR36/HhoGFDiLMeq9fRi//iDs\nbi+cXl+JLTwlB8DG/acw67NDyO7aDIemdML/tq+DsdtKruwtr1yMmqzY9F4tsWDLkVCvYZWOU0+v\n2gdboIWb/P9RkqzXxA0H8c/F38Og1WLUe/tL7WBFxDYV7fkbBmAMY8wFwAPhKOac82oVPI7LhnQx\n2lxeRXhiR845jH7vAN7ofwOeePsHpCYaMfKeUO6KFNbQMOCPfDua1EpA7WqRz5neqyUA4SHcdSwf\ndWuY8c/F3yM10YhZD7UK241lwKzXYeID/0C7xil4WiYQvSPnHJ5evQ9v9L8Bw+66Vnj/PlUP+5a3\ngEUudPpB9w8wf998bD66GYBYSM45zsGoMyJBn6B4jdxL2LFBx6A0zKKDiyKKQqizB0HEH1LbSnk4\nd26/DFgNOox+74Dquvhm/xvg9vmRtWofalczYuZDLTH6vdDfX+3TChoG+DkPrk/hoVEtjOh3o1hv\n7m+RjCapyThZdBIp5pSgITZx+ziMy5yBlz86jIldG2D8t7LcvU7TMHPTyaB6Qnh6j+gA4gCYHg6v\nA9+OuxMvf/xrMEe7XVpNvDPkxlIjGKrRkhJSXKRCjkUDW8Ni0OHUBQc0DHjt4QyMvOc6OD0+mPUa\nRdWuVAgohckdgXPZdSwf+7LviBDan3LrFNicPoy8Jx2zPjuEBJOuzJqBsczp06e1d9xxRzoA5OXl\n6TUaDU9OTvYCwL59+34xmUxXtHeyQo0/znliRb5fZSBdjDUTDKoXSDWzCFt8nNVe1ThcPLANNAyw\nubwYcfd1Ec8Zu+4Asrs2w8b9p4I73l3HRDXZ2PvTMbtPK9ROMuHEOTte/vgXnCl0YU7fDKQkGFXH\nk2jSo/GETQCAdmk1I7qQlLeARS3Pb8qtU6CBBmcdZzGj/Qy4/W6M3TJWYcjVMNZQLIxyORjJcJxw\n4wSkVU+jal+CiCPkm0eb2xtsWwko5aiirYvn7R6MX38w+JifA9N6tkCDmhb8ed4BvYZh8LLdwfSY\nf93aCAkmXTAXTTKa9FoNHmmXrCgumXzLZABijZEKPJ65V4Mx20apVv52nrMTFqMwckLpPVdhXJf6\nmLB9pKIIY9KD/4CGAWcKXZjeqyX+LCgotbL3YlJcNBoGq0GHIqcHjAGj3lMazsUuL7I3/qRwIDRJ\nteLI2WJcWzsBQ5aHlCBMOhMcHjOy22WjbkJd/Fn8J/TMjJc+PBys+I1WMKjWwSqWueqqq3y//vrr\nzwAwcuTIOgkJCb7JkyefqexxVRQVfvdkjNVgjN3IGOsgfVX0GP4u4WGLcOFOqTevWniiKKCcHk2n\nz2zQwg/AatCiQU2L6nOurZ2A36d2xlsDWkMXKOYAgKuSzCh0evHPxd/jjllfY8O+U9iRcw4jVu9D\nkdOjOp4/8u0ldiFRCxlkrdoLu9tXZtHSid9OxPPtnsfkWybDoDUEBZ7DQx/ycIMkByOx+ehmTN05\nNbhQkuFHELGP389R5PQgr8gFzgGrMYrXyKiNui7WT1augxv3n8Lds/8LAEg06bBq5wnsyDmHzi2u\nRvfMehi6Ql283ulzBOVcpLVn0vZJGNJiCABhiJ28cAH1a1SPWvkb7HIhW9+Hd7wGE7ePUxz3+e3j\nYHPbMaV7C7w1oDU27D2JVz85GiFIHR7BKG83JelexMGh0blxdZIJL3Zvgs4tagcN56fDesSPXXcA\ng25phE9//CuoJPHpiA74fWpnFDu92J1jR01zTQAMTqcFL23Mwcb9p7HrWD6a1ErApz/+hddlTQPE\nvSOj1A5W8cKwYcPqTps2LVX6/Yknnqj7yiuvpG7YsCHxpptuuu7uu+9u3Lhx42YDBgxo4PeLcPya\nNWuqZWRkXN+0adN/PPDAA2mFhYUxf4Oq6A4fjwLYCuBTAC8GvmdX5Bj+LiXleshRb/GWAaOWYeZD\nLfFHvnqO3qkLDoADTMMUHT26tqqDT0d0wKEpnVDo8ODZNfswdMUe5Ns9eKP/DRh597UodnojFk9J\nFzDRpIu4YGc91Ap6LcOhKZ2waGBrVW9etLZAZoNW9dxL27lao6jlS30rpYXxyxNfYnr76X+rqwhB\nEJWL2+sDGEP9ZAuOnC1GbpErSs6eF3P7Zaqui/LHwtfB5duPoXtmvWBx3YZ9J/Fi9yY4NOV+vDGw\nGZKtetjcXvj8/qhrU1pSWnB9SU2oBltAk1SOZBi+3jcDZr1Gsb43TklWPW696tWDXsJH26dh9sOZ\nqGEM5TnPu2teUK7K7+ewu73wenSYemvkuse4McLZIN2L/v1NDk4V5eLpLaGOJaM710PXVldFGM6A\nFPHRod9N10CnAUbdF8pNf+LtH9D6mpoodmjRf8lO3Dv7+2CBjOQsGHRLQxgDTQMOTemEaT1bwKCN\neVunzDz55JN577zzTgoAeL1efPjhh8mDBw/OB4ADBw5YFyxY8MehQ4d+Onz4sOmdd96p/ueff+pm\nzpx59bZt2377+eeff2nevLl96tSptSr3LEqnov9jTwNoC+A45/xOAJkAcit4DOVG7umzub1Y9f3x\nCE+Yza30gqm3eDPCoNdi1qeHoNcyRcs1yRgzGzQYsnw3Rr67Dy6vDzMfaomRd1+rKB554u0fMPKe\ndKQmGvHsmv1gjOF/bmuEZduPKnoyKotOPsHq70/gzQGt8dvLnTDvkUyY9AxJZgNYoErf6fHB51Mm\nFkfzYB45W6ya6Btt52rz2DBp+6QSizekPJ09A/ZgQNMBit/lCyVBELGP389R6PLi8RV7kD5xM7I3\n/gSvj2PeI8p1TxSaifWyVqIxYl1MMGnxer8M1XWwe2Y9bNh7EqPvS0fjWlb0aJOEV/aOQZu3W2Pk\nf5/GOWc+vjl8Fn+ed+JsUaHq2uP0OYPri8Wgg0VnUe0lXDPBhD3Hz8Hh8cPu8SHZqseiga3h9Kmv\neScvXMDhM8UYumIPit3eQOGKLqI3uWTEnS10Ydn249D6E/FC21nY3X8PXmg7CzqeiCVbcyKcDVJU\n5v4WyRG9h1/4bjyGd7wmqpPB7ha5gH4OjH5P2Sb06dX7YDFo8Wb/GyKcF7USjdBqGB5/+wfcMetr\nNJ6wCXfM+hqPv/3DFVPw0axZM1dCQoJv586d5vfeey8pIyPDlpqa6gOAVq1a2dLT0906nQ69e/fO\n37ZtW8JXX32VcOTIEVPbtm2vv/7665uuXbu25vHjx2O+L2lFB+idnHMnYwyMMSPn/FfGWHoFj6Fc\nqOW8Te/VEkdybcEWbGq6SoC6qGaxy4szhS7cOn0L/vOvNlgyqA04ByxGLYqdXvzn26NITTQGvHV6\nnLrgwP/e1ghDlu9Rzf17YO42JBh1YExIHlQz6zGnbwZGrN6n6P/btVUd3Nf8aiQYdSh0eGA1iPL/\n4St3KxKnLQYtEo26oASA2OFGagJKEjNlFS3VaXRYdM8iOL1OvHbHayhwFQRzSpIMSTBpTYpcvqD0\ngSZSH0xeUEL5f5ePFstaVPYQiDjG7vYFQ46AWLdGvbcfM3q3xNJBbeCXrXtGrQYaDYPJoMWE9w8q\nChSmfPQLXu3TCv+6tRGGrlBfB+tUN8HutaNOtRSMv3E8Fh9cjM1HN2PctjF47fa52H74PNqn11AV\nYV669U/0u/EamK1iF6zVaGDRVcfcu+bBojPjZNFJzNo1S+Qsd5gBjQb476EzaFzbiCapyXB4GKbd\nNh3jvxmryPkzcAte/fSXYHWtvLOH4nPy+LBq53EM7lAXwzs2wR/nL+DVT48GPW7t0moiu2szzP7i\nsFI3NhCVieZ5bJySjGKnF2/2z8QFpw31qlfHyQsXYDVYMHHDQZwpdGFuvwzc37y24vN+4+sjsBh0\nOFPoxJJBbWA2aBU55O8MuemKKPgoiUGDBuUtXry45okTJ4xDhw4NOqgYU0bGGGPgnOP2228v3LBh\nw9EKH+jfoKKNv5OMseoANgD4nDF2HsCpCh5DuVATbZYXXQCRukpqF7g86XnRwNaw6LVwePwocHjw\n7Jr9Qe2/4R1F+PbbI7lIS01Ek1oJsLm8uL95bdzXrDa6Z9ZFNbMehQ4PEgy64HtXt+jxxcjbUT/Z\nglMXHJj1UEtcXd2MXcfygx5AeQXdWwNaB3d80nk9u2Y/pvVsAa2GBdXhNRoGq1EXTLA+cc6OWZ8d\nUpy7PNFXTYTU6/di2U/L0CWtCz7K+QjdGndD9o7skIL8bVMx7ZtpwcVV7uELN/RMWhPOu85Ttw+C\niHHk+qUSu47l4+okE/LtbmV3on4ZqGk1wO724UyhCwu2HMHY+9NRt7oZsx/OgM3ljZqC0riWFfnO\nfIxVKeT4/NjnsBrMaN3Yiawtw1HLXAvZ7bJRL7Ee/iwowMxNOQA0sLm8qJlgQLHLC4teC5Nei0KX\nH49+9aiiQGPM1jF45ZY5aNPYqHi/1+54LdgBxO6xQwMDxq37KcxBIIyjcPUEk56hR5skPPXVUyGj\ntPM0AFDm2o3oEDTQzHpNMCoTvfewHQkmC8678hUdO6bc8gr83C9kw3wcA9o1xIlzdjy7Zh/OFArJ\nr9MFDox67wAWD7wBf5wvRP3k6njyrvqY/+XxoKxYvBd8lMSgQYPOT58+vY7P50O3bt0Kpcf37dtn\nPXz4sKFRo0bu9evXJz/55JNnb7/99uKxY8fW//nnnw1NmzZ1FxYWao4fP65v0aKFq6T3qGwq9G7J\nOe/BOb/AOc8G8DyApQC6V+QYyku0BadJrYSoukrhhOcJPrZ8D/684ESRUxh+krzB+PUHcd1zmzF0\nxR60viYZn/74F9Init87tbga3TPr4om3f8B1z4mQR77djTf734Adv+fB6+MYv/4g0iduxpi1B8AB\n2F1icZB7ACXXfrTE6/rJFliNOkUun0mnhdWow/wvD0PDWFDpPVqRiBzOOVb9ugodG3TEpO2T0LFB\nRzz37XNIMadgzYNrsPiexXD73Mi6IStC98rn96HYUwyTzoScCzlY8fMK2Ly2iIKScK0sgiAqH2n9\nkdO2YTIcHl9EEcLTq/bh1AUn/u+bo3ij/w2Y9OA/wIGgLuljy/cg3+ZG1l1NIo7n9NoV+nkp5hT4\nuR+vtH8Fm3tthtPrxLjA3z8++jEeeP8BPPrZowCAGxrUwEs9rkX9ZDOO5J7Dv7/JwTmbC063D9WM\n6vnJVpM2Qq/vma+fQb4zH61XtEbWlizYfYUQbVVD47QHdPWKnB6csxWCc45ztkI4vI6oYVvptcVO\nb0ADcS+SLD6RqqNxYcmg1rA5Gaa3j9Q1NOssosglvABv+ziM7pSGUfemY+Sa/bjuuc1CdzaQSjT6\nvQPwc6B2NQOcvBAv7hqlyCX8729nIkLzpd0H4g2LxcJvuummoh49euRrtaHzyszMLM7KyqqXnp7e\nLC0tzfnII49cqF+/vnfhwoXH+/Tp0zg9Pb1p27Ztr//pp59MlTj8MlEpZjpjrC4AyUWqrl4ZI0i7\nq8hdjheHpnQKdseQtJzUdj/RvIeS+1xN3uDp1fsUrv6nV+3DtJ4tIp6zeGAbdM+si0STHtldm2HB\nliPYuP8URr93APMeycTrfTNQU0XmJVq5/h/5dlS36JG1ai+W/isQmjFoYdZr8WiHNBh1GmUrpTDN\nPzWpl8m3TMZV1quCydW1zLUwPHN4hG5fp0ad8Pmxz2HWmeHnfhS7i1HgLoBFZ0GqJRWPtXwMAKjb\nB0HEARoNIjT5Xu+bAatRh9rVDPhs5E3Blm4LvzqBujXMmP3FYTzUpj5cXr9C3kVa797s3xo7cvKD\nx5vTNwMWvSG4JnRq1AlZmVkRa0stszL/fu+ZvaiblISBtyThZNFJTNs5JRh58Hm4yH9mTmTWzkSK\nOQVDWgxBWlIa/iz+EyatSXUNqptQV7EhfeG+Wdh08ExQHsus08Dp9aLYdwEv7hoXHN+Se5dEDdu2\nS6uJ1/tlwGrUYtZDLaHV2zDhW6WkTKOUJOz4PQ8v3vQq6iYlweF1oNihgcvrh1mvXuRSNykJ/1y8\nM2oqUZ3qZjxzb0OM2RopefNC21mwyruvlEH7NdaZPXu2IgLp8/mwd+9e64YNGxRtsywWi3/z5s05\n4a/v0aNHYY8ePQrDH49lKsT4Y4yNB6DnnE8OPLQDwAWI/r7LAEyriHFcDFJVV7jOnUWvRb7NHdRP\nKmn3E817KO2M1Sp0h93ZBNfWFq5+SZSzfrJFcYza1YxweLwR+XgAsOngX0i2GkTLNrc3wtD79Me/\nIhqiSzl/G/b+idrVjLC5vGFirJkwajUReQ9y1ERKJ22fhNl3zEZm7UycsZ/B+JvG45mvn4kQMp18\ny2TkOfJg99ih1Whh89qw6egmdEnrElzMP+j+QalaWcSVx8GjJyp7CEQ5Mem0qG7W4c2BzZFotKDI\nZYcWGjg9Xox+oB6e3x7aIL70wCtwBgoGalUzgYPjxe5N0DjlRvyel4/5Xx7HpoNnkGDSYUbvlqhb\nw4zcIifcfgccXl9wTRjSYggmbZ8UsbZkt8vGx0c/Do4ts3YmThadRLcN3YIb1Ll75wqjre0saPQW\nHD/twrw75wOMw6wz41TxKWw6ugm9ru2Foa2GYsG+BYrj5RSEbIK9Z/aifo3qODTlfjg8fph1GuTb\nPbCYvHg+IAsjje9k0UnVNc3pc+CtAa3xn2+PYu5XR/DlqJvx/LdjFa99fvs4vND2/9k787io6v3/\nP8/sCwgC7kbggrvihmFRLpmZhhZlYmrdW2aLmpmCmhapuZC5DGqL1f2WpNbVMq1rVi5ligsqZrmh\niIgb+zILs57fH4cZGGdou+X13h+vx4MHcubMOR/G4T3vz/v9fr1eS+jasiFOJzy65qCXeLYLR53x\nsq6OlrsIEB7qX/LmlobBIAqeZO9/pdXrxsGDB7UPPPBAm/vvv7+0Y8eOtl9/xn8nbtT/2sNAXK2f\ni0VR7C4Ighz4jps4+avN2r1+l1PXcQBcLrCbQaUDq4nnB7ThjWoTcpCqbOUWm5fsi5uYcf18nluU\ns7LKTny35p45kil3R/kIprp3b4WVViqrHEzZ4F8V/6Fet9BAo/D4NZqtDgA2Hs4nZesJMmYM8CPG\nepS3x/ZkwtrDdQo+1yWn0EDVgNS4VByigwBVgN9zmgc0JzUulfST6YztOJbZe2czM2amVzBfmbXS\nR4G+XgLmfx8RVet+1/m5f80y6vF7IIhUiRU+87kaND4J0Jx9M1jezwBAkbEKmcLEoqNJXjNwbRoH\n1sxWj+uBRmXDaqtELW/O4rjFJO9J9hKHd+PotaO0DGxJ76a9vYTnlx9Z7qX3NzNmJiO3jqRlcDCr\ndp3lsdubUG4r83G72JS9idEdRnPw6kGf67nRvUl3LpaWoVNKYzQWu4vJ64/6dflYnbXaL0lOEFVe\nBJeWwf6TsZbBwVhsLi+xZrd49vJR3Xj1toW8sn+mV7WwzCjU2flxO66YbGa/iaPZbkan1GGySf7D\nMrsFlDr+VG/Q/yBiYmIsly5dOn798REjRlSOGDGi8j+xpr8CNyxlF0XRVOvHFdXHnIIg3PSf2v5Y\nu790HJcLzIWw8QnIy0AWHsvEhPeAtqzYedaT0G06nM/Yas0kN6O29nwe1CR0b4/ticm7EFhzAAAg\nAElEQVTqYPmoaKYPbsdnR/LrFIFu0ziAFYnRVNmdpD/Zh7MFRr49cc1D2jBWSaKgLhEQQHSJnuB0\nKLeEqXe3pUmQxu+19WqFT0JYm+TilnrxFzC0Si2Tdk5iZsxMv+fkV+ajUWhYlbWKp7o+5WkT1w54\n285vQ4bMi1BSz/atRz1uPtRlVVZXm1Ov1BHbKhS9xsnkXUk+7ca0AWm4nCrSn4zB6qyiwmryEMcm\ndJvA8v7LqXJW1Rl/FsQupXFgAywOC/My5nmcg9z3bxXUiu5NulNpM3JvlxDKbeWkZKR4rWP23tnM\niplFgDLAc72CygrkgkiRpQiFoPCwiF//13kKK+2euHsot4RCU6XP+gosBYhONTO6p9KmUQgmuxmd\nQofF5qJJgxrFkLqIHUabiQCV3m+8DgvQ8MLHJ5gxMFVi/9rMfHa4gEEdA3xUHAyJ0cgFAbVSjloh\no8qhJvXOVDae2cjd4XcTGRyJyW4i43IGSd8nSUlqbAohRzcg6/kY6Br9zySA/z/gRiV/AYIgKEVR\ntAOIovh/AIIgqIFf9fUVBOF9YBhQIIpi5+pjIcDHQATSRn+kKIqlf8Xifw3Xs7f0WBA2PgG5e6QT\ncvcgbHqCZx5Zx7MDJDZvgEbOIzHhOJwulDIZIXoVb4/tWadvYoBG4VVxW5EYTaXF7nf3ZrJK0glP\npx/xqh4u/Uby7hUEUAiyas3CPBL73EqITumpYlZY7OQVm5k8oA2DOzfzMMy2/3RFEqG+bm21SS4y\nQeZTmVsct5j0k+mM7zKeo9eOsub4Gr/+kYYjBhbELWBI5BAuGy97Win+gqUb9a3eetTj5kRdXYC6\nNogWh5l/PN4LlVLm93kauZYx/zjI4oSuhDYQPU5BAKuyVnHw6kHSBqT5jT8ahQaz4ODRNQd5dUQb\nrxjivv8l4yXm9p1LgEpPYFgA0NDvOiKDI7E4LFRUOTh1uZDo8IYEahSkDUhDI9dyrqiEHT+VM3Hg\nrbQOC6HKaaGwsorJA9ogc6l5485lVNq9pa70Kh1Ol5MKi51n0n/yGsWZPrgdTYO0lJisLI5L9WE1\nrz/9EYntEvlhRl8aBTTwtMkLK+1YbHYWPtQerULLpfJymgU2YED7pkz75480aaD2ssn78scrDGjf\nhPT9FxjRvSXJm37k3s6NSYhOIHlPstc9B0UMYtv5bSRlpJDWIwn9xicgcQOoA6jHfwduVJq+EXhb\nEATP0JogCHrgrerHfg3/B9x73bEZwA5RFNsCO6p/vuHw5/iBSg95Gd4n5mUgUwfwwsdZlFvsfP3z\nVdQKaSh3/IeZtJv9FRPWHvbYv9VG74gQ8orNPuw4u0tkzbieZL08iJyF95H18iDeGtsDlyiy71yR\nj6XPlLujyL5mlJhzZhuCAIkx4WTmFtckr1aJsPLdmQJGxYR7BFVTtvzMqJhwAjQKn7WZbTXinmq5\nmt15u1nabymHxx5mRf8VbMrexKqsVeSU5zCh2wQmd59MU31TlvVbxqExh0iJTUElUxERFIHRZiS5\ndzIni0+SemcqO/J2MLfvXC8m2/zb52O2m+sZvvWox02MugTfBQQvN5/eTXszt+9c0k+mY3SUUWQ0\n+n3e1cpKXh3RhhYNNb/oJKSUKT3i8HP7zmVT9iYsjioPw3jljgvM92OzppAp+CLnCy6VlWNxVGG0\nG8kcm8mn8Z8yJHKIZx0mm4l5GfNYdDSJTuFyPszIpd3srygshzHvHmRfdjlDuzfwiE1P2jkJUWbk\nibhIMi8U4xBtpGSk0Cu9FykZKVicFmb/8BKzMqZicpbTKFDpidsvfnIMu1Ok3extTF6fheAKYHm/\nFWSOzWRmzEwMRw3klOdgcpiYlTHVw8pNHnYLa8b1wOgoZ9LOSfRc25NXDrxImbWUzVn5ZOQUsznr\nMv2W7ObRNQcw25zEtg4jedOPDO7czNN9im3TgOQ9yXVa4h29dhRtaFvp807lPZNej5sbN6ryNwd4\nDcgTBOECkqHELUhSL3N+7cmiKH4vCELEdYeHA/2q//0BsBtI/lNWWxsuF9hNoNIj2kyIghwUGsx2\nFzql3C+Tt6iklEbhsTWVP4DwWIpLSz1t3dSHulJ2nWF5Rk4xH+w97xFprl2Of+3Lk17LOpRbQrBW\nSYnJ5kXaWDEqmsMXSohtHeZzfniojikbpAA4/Z8/snRkN2QygR63hvDUh4e97jeie0uevk5Q1c0u\njm0V6kN+ccPqtNIvvB9Td0+lsbYxC+IW8PaxtwE4eOUgCW19d5Ers1ZSZCliWb9lrDu1jvsi76NP\nsz6o5WrGdBiDVqFlRf8V6JV68ivzUcvVKGSK+jm/34nfS5roEhn+F62kHv8/QCPX+lSqFsel8u73\n+eQUGlk2YgUBah05ZTkYjhrYdn4bB68e5NU+b/jMqS2+4w3sLiuLjs74VeLXPRvvwSE6PMcVgoLx\nXcZ7CCSXK8rRy3Wetu31Is46eSCV9jIv0ea5fefSKqgVCW0T2Hpuq4c8krwniRndU1n6jch3p6+x\n9rEumAUnU3ZN8WoXz9qbzKqBq+gbFcgLu6977IdZLO23lEBVIEabkWWPRDNxYKmH5HJLiA6HS6RR\noBKTzUyIPpiea3t6fsdP4z/1qoLWzFCuYNZ1BJGkPUm82ucNln5TM3/uHhUShJp/u7tPdQlItwpq\nVfOaF2ejD48Fm7m+8vdfhBuS/Imi6ARmCILwKuAWajoriuK/U7ppIorilerrXxEE4c/30rtudk8I\nj0UYsRpRFci5IheRYYEEyq2sezIGZ1UlMk0AlwuLOVVkJyzhPYRN0vMIj0V86D3UskBaBytIie9E\ni4ZS4nJ9i9ew8yzP9m9DSnwn2jYJoLLKgdPp4lqFt16kRy9rQ5ZPgvbmmB400Cp9zi+ssHqJjjYJ\n0mC2OnzcQyavz6pbxV0t/0WKv0t0MXvvbMK0YUzsPtGLyRbTLMaziwR8Bq0DVAG8fextxncZj4hI\nmbXMZwi6kU7y21bL1fVzfvWox00Mi93F+owSZnSX5s0qbSY+3HvFk3i8MTKaXrWSGKiRIflwXy7L\n7jIQqNZxsbSMKju8cqCGJOKX+BWXis0h+iSFE7pNoLSq1ItAMq/vIhZ/eRGAiQNv5bU7FlBpMxGo\n0lPltDDzB984taL/Crae3cqiQ4u81tumUQiv3t+ehztosJoL0AeH+02YXKKLgDq8zQNVgfRa28uT\naO688gXT73vAQ3KJ79aU6fe15JX905gVM8vrd6yL5FLXvVoEBXkRB3tHhFBld2J3ujg9fwiVVXYm\nD2jD0m+z65wzPF9+XqqYxqagPboBHnpPIn38l0Cn03U3m81Hf/3MPw6DwRD6yiuvtGzatKndbDbL\nbrnlFusrr7xyedCgQaZff/Zfjxv96ekA+gOvAGsFQZgkCILyV57zb0MQhKcEQcgUBCGzsPB3WAnb\nzVLil7sHXA7p++ZnESyldG2iRucoQVifiDC/EYpPHkVWfpGWRfu5ozkIhz+A+16H2QUw6iMEXRh6\ntYISsyQPE/XSNo9Sem30jgghv9TCUMMeVu7IRhRFVAoZrz/c1UtUM210dJ1CzQ20SoxWh49/psPl\nLTqaV2xGV8c16hJodbeFZYJEdrle28ndjnFLLqzMWulp29YVpNyD1m7f30vGS17D4rW1s1yiC5d4\nU0tD/mH84ffpTYLj5/N+11c9/jvxW9+nOpUcw46z3LP0AK1nbSNQFYBhR41s2uWKcr/t3YLKCu7p\n1IxAtZ6pHx9DEDU0bxDkQ/wyHDF42rvL+y1Hr9ITpNGxvN9ynot+ztPSHd1hNEnXiTLP2TeDiQNv\nZcuxq9yz9ADtZn9FoCqAiyUWNHL/LWWdUscdLe/wWa+l7ALjeoSh2/IU2qBwzped9/t7aRXaOh/L\nKcvxaqsODB/IK/tn8tgdzVm16ywTB97qEYJ+5/g7XqMwl4yX/F7TbDf5PX6xtIypg6I8nw1vjulB\nucXOM+lHPJ7Jo2LCmXp3W1bvzGPedS3yxXGLiQiKZPldywkJaAF9nvmfJnu4XC6czj/mW3z//feX\nnjx58sSFCxd+Sk5OvpqYmNjmyJEjN4UA9I3+33oT6Amsrv7qUX3sj+CaIAjNAKq/F9R1oiiK74ii\n2EsUxV6NGjX67XdQ6fzO7hESgSC6UHz6pHdi+PlEiLwDYdOTsPs1WH0bzA2BDY+C3YLF4fJStl/6\nzRmfpM6QGI1SLnB6/hAGd27G5qOX0KkVLNl+mpT4TpyeP4QlD3fFahepqCZ81Iab8OF0iXw0vg9Z\nL9/Dkoe7smT7aZoGab1cSZZ/e6bOJK/cYmNxgu/afsm/0SW6MNvNHB57mOYBzXnt9tcAMBw1MDNm\npoeJVxu1B6135O1g/u3zCVQFolf637Vq5Bom7ZxESVXJ/1wS+Iffp/Woxw3Eb32fmq3e88uXyyxe\nP7vJYb2b9mZo5FC+fOBL3r3nXfRqBQq5HRB54Z5b2XnqKpU230SmwFJApa2SEksJRruR53Y8R8+1\nPZmyewoJbRM4NCaTZXcZCFD6l5Zq0yiEH17oTXy3ppKLhtXB0m/OeKpdtdG9SXfOl533SMZ4ZgVv\nS0G7Yx6COgDyMrAUZ/Nt3rc+c8qpcYuwlOf7fWxu37msOb7Ga23ujXKgSkdhpdWr/brt/DYMRw3M\nipnF4bGHCdOGseD2xT4JmvbsLlJvS7luHam0DA7i1kAXZ+bfy1tje6KQCbz4yTHvmfINWfztjkiW\nPtKdhuoQDP0NZI45zIzuqcz7PI82s75iwocnMFpdoAr4SxM/l0sMMVodXVyi2NNodXRxucSQX3/W\nb0N5ebksNjY2qmPHjh2ioqI6pqenBwOcPn1a1apVq05jxowJ79SpU8dz586pli1bFhYREdE5Jiam\n3ahRo24dN25cOMDly5cVgwcPbt25c+cOnTt37vD111/7ZSHef//9lWPGjClctWpVI4B9+/Zpu3Xr\n1j4qKqrjoEGDWhcWFsoB5s+f37h169adoqKiOg4bNqwVQEVFhezhhx+O6Ny5c4cOHTp41pmZmanp\n0qVLh/bt23eMiorqePz4cbW/e/vDjVZn7C2KYrdaP+8UBOHYH7zWFuAxYFH198//3cX5wGYCP7N7\nFJ6GsCj/iaE22P9xlQ4dgleVbcuxy8gEvLT2yi12ptXy3AXo164x1yqsDF7+PQDbp9xJypafGdyp\niY9Q84pREl3/qXRphm/ygDY81jeSpSOjMVodnJp3L+cKTSz5+jSFlVZkArw5pgdlZju3hOi4WGJG\nr5Iz78uTtGmk/0U3j9q43tljQrcJjG4/mkVxi7hsvMx3F7/jnoh7/OpZaeTSAPfYjmORCTKcLqeH\n7Xt9uyGnPMdTBUwbkFbP9q1HPW5SyASBtNHRmGxmWgYHY7KbSRsdzaR1UrxqGhjISz8sZP7t81HJ\nVV5xYf7t85m1ZwEFlgLm9V3E50cKmdd3EXP2zfCKHXanHbPT7CPJkrwnmeX9DChlmrrZxUVnaLlt\nGkseWYdVLkOvlDP3gdZk5Zo8uoG1Z/6+yPmCEaoRkoevQoulOBvtNynIftoEd07HdVcyKHWM7zIe\nk8PEu/e8K5HSRBHNkXSE/IM8NCiFjTlfMCtmFpHBkZjtZj46+ZGX7ExtlQOjzcyacT2pcnr/DtvO\nb6PIUiRJXsl12GUKXum9hJbBwZgdZvQKLbKNfyOk43DS7kpCG9pWWq8mGNn8xhAeiyX+HQKDm4Ig\n+O3+6Ks7PBqFnCqHhhKTjVc2n/WYGqxIjEav+mudPVwuMaTYZL118vosWfVnnMqQGH1rqF6NTCaU\n/PoVfhk6nc715Zdfng0JCXFduXJF0adPn/ajR48uA8jNzdWsWbMmNz09PS83N1e5ZMmSZkeOHDkR\nHBzs6tu3b1SnTp0sABMmTLhl6tSp1wYPHmzMzs5WDR48uG1OTs7P/u7Xs2dP85o1axoBPP7445HL\nli3LGzp0qHHKlCnNk5OTm7///vsXDQZD0wsXLhzXarViUVGRHGDWrFnN+vfvX/HPf/4zt6ioSN6r\nV68O8fHxFWlpaY2effbZa88880xJVVWV4HA4/N3WL2508ucUBKG1KIrnAARBaAX8aj1VEIT1SOSO\nMEEQ8pHaxouATwRBeALIQxKS/nMhyOGBt+Czpz2zewxfCTvmwp3T/CeGljL/x21mzGh8pFmkWT4R\nY5UDmSCw6XA+ixO6eok8B+uUrEiM9hihuwdy3ddxz/iZrA4cLpEnPsj0CEaP6N6Sp9MPe0kHBKjl\nLHtESgYP5hYT1aQBMz897jlnycPdGNK5Cbe3aeST+F0va6NTykEQMdvNnjbtkMghDGs1jCm7p3jJ\nLWzK3kRuea7HWN3sMDM/Yz4uXL6WTHGpvHb7a7y09yWvAGw4KgnB1lu61aMeNzfUShkV9kpePVST\nRM3vu4glD3elaZAWo81EgaUAk93kQ1hwC7w/uOVB5uybQdqANIwWGWn9V6BV6LBUXEIm16DSNATR\nv+VjgEqHTJDhcAks778cvVLP+bLzfJv3LQ9F3If2mxSc7YdRLlpJ3pXsFasKSuVez/ki5wuGtRrG\n8sPLWRC3ANkH8ehrxXhXYTYlvf/GxuxNXo5E3Zt0J/X219DmH0T20yZCgLED56ANvhVL0Rl0hWd4\nqO1DXoLR7kTz1dsW8n8/XGZU73AulVX5kGdS70yV5p4FkUCNEqWigeR/vP4nlgxvRYvwWGQ/bUL/\n0yYA9BFxuB54E9Mze9GGtsVlNyIiYrKZmTywjRcJxD3io1XKMNmc6NUKSk02lo7sRpMgDSarA51S\njlz+1zYPzXZni8nrs2TXzaTL1jzWq0WAWvFvJ38ul0uYMmVKy/379wfIZDIKCgpU+fn5CoBmzZrZ\nBg4caALYs2ePvk+fPpVNmjRxAjzwwAOlZ86c0QDs3bu3QXZ2tufDyGg0yktLS/2+MKIoAlBcXCyv\nrKyUDx061Agwfvz44ocffrgVQLt27SwPPPBAZHx8fNmjjz5aBrB79+4G27dvDzYYDE0BrFarcPbs\nWVVsbKxpyZIlzfLz81WjRo0q7dKli9Xfff3hRid/04FdgiDkIDF+bwX+9mtPEkUxsY6HBv6Ja/OF\nUgNbU6SELzhcqvjtmAvVf0wMXym1emsnhud/QEx4V2r9uo9XD8PqEHys4pY83A27S2TtvlwSY8J5\nsGdLjueXeSV0WoUcm8vF22OlKlxlVY2+X8rWE6RsPUFsq1BS4jvRpnEATRqo2T7lTloEa31U31/8\n5BgLH+xCu9nb6B0RwltjevJ0ujfhY9o/j/k4eaxIjCZEq6LUYvda/1tjemAXKmioqdHE8mexlLwn\n2RPMvzz/Jb2b9mZF/xVEBEUwMHygryXTniQWxy2WdtlKHfmV+R5GINRbutWjHjc7LA6zD9t09r4Z\nEgFk1i5GRDcjdXiqV+xwozaj1K3xZxJs6JR6hHmN0LscuO5djLHHaMqqyupk/moVWsqqSkm6LmnS\nyTWID76DxWEhedfzPrFqRX8DCpmcS5WXiAyKZGD4QAxHDRRZirhUXk7jEWtQbx7vifHm1v3YeHod\no9qPYuruqd6xbO9LpA2cg/7E58iMBegFOXz6FPrKqxIRUAhkRT8DepUOk92MVqFlQLOHeP1fF9hy\n7CoZ50pIie9E5rkKr3hYm6EcognBJeJxZVq8U8mi+HfQbXnKs0bXQ+9RIjpJOpLqk2gmxj4EtMWw\n46xH8UGrlFFstnmKDu7Pq8JKK40C1RirHOhV/KUJoE4lV/klHqrkqj/j+m+//XZIcXGx4vjx4yfV\narXYokWLLhaLRQZSVdB9njtp8wdRFMnMzDwZEBBQ90nVOHLkiC4qKuoXia67du3K3rZtW+DmzZuD\nU1NTm2dnZ/8kiiIbN248261bN6/krkePHlVxcXGmzz77LGjIkCFRq1evzo2Pj/9NLiQ3dOZPFMUd\nQFtgcvVXO1EUd93INfwu2MxQeRVWdJMqev+aXpP4/bQJjn0Co9bBnELEUesQ9Y0ROw6jStBQMiId\n1+xCnI+sx1U9DFvbEu7Ma0NIie8EiDybfoTBnZsxeUMW3564Ro9bQ3gm/QhRL23jqQ8Pc7m8ine/\nz0EURS6XWQhQK1iRGO01j7c4oSurdp2lyGhl2uB2pGz5GW0dnsJu6YCMnOI6RaXdTh61dQUtjhpZ\nG/fxsiojSd8necgaUDf7zB3M3T/rlDoS2ibQOri13/NDtaEIgoAoiugUOo+CvluXq77yV4963LzQ\nKXV+/65bh0kjW60aBUhOFnb/eoBur1y3AHSYXo1gM0sbakD2VTK63AOEakN9dANT41LRyCUHoOvJ\nHknfJ1FUVcIV01V0dcwW65U6Zm48iVzQMP6b8YzcOpIiSxHz+y5CJshQNGiCafR6XLMLcD6yDq1K\nz7BWwwhUBfrXHwy+Vfo8GLUOlzYU8cF3KLz/A6Z+cYmn1h7FYlUwZcMxdAo97Wdv556lB9hy7Cog\nxeO2jQPo1LwhxUYbT379JEM/G8qX57/0/D4Wh8XLQ37LsavM2H6FS0PeR6z+fLKILpL2zfbR7BsY\nPpDkPUn8Pa45Z14bwppxvQjVq31m1N2FAYvNSdRL25iw9jDFZhsu16/mPH8YZpvT5pd4aHP+KZ67\n5eXl8rCwMLtarRa3bt0aePnyZb9JZVxcnOnAgQOBhYWFcrvdzueff97Q/dgdd9xRsXjxYo/ayL59\n+/x+MH355ZcB6enpjZ599tmi0NBQZ4MGDZxfffVVAMB7770XGhsba3Q6nZw7d051//33V65evTq/\nsrJSXl5eLu/fv3/FG2+80cRVTdrcu3evFuDEiROqDh06WGfPnl1wzz33lGVlZf3mD8UbmvxVizxP\nByaJongMCBcEYdiNXMPvglInVe0i4uD4PyHhXenfMoX0vec4UOklmzS7BWHdSIR5jdBuHEMAFqZ8\nfJQxa3/GbHNSWWXHJVa3TJVSyzRly880DdJ6tXJjW4d5tPju69LMIwszrm8EH+zLxekSOVdoYsOB\nPJY/Es2Z14aw8MEuLP1GmuHTKuVMr54ZPFtg9EvmOFtg9Pz8W86BmoQwJb4T5xbcx/YpdxLfrbnH\nb3LN8TWeAHy+vA5GWy3jczfDLXlPMqY6WGlGu5FJOyfRK70XG7M3srz/cg6PPUzagDRCNCH1Ui/1\nqMdNjLpEns8VlTB1UFsSY0OYuHMi8/fP9xA/agu5v3f8PXo37c28vouQoZFmy2rFZFeXkZQ168ik\nnZNYcmgJKbEpHB57mIW3L2NdRgklJnudYtAtAlrw8r6X64w9FVYjLlEEl9rDKJaqc2rm7H9BEm/e\n9Twl1lLWHinC7DDz8r6XvTbBta93trCEVrO2gSqQSyaB0WsO0vv1/XyWdcVDsHiufxtPV6c23GSU\n5E0/1unvq1VoMdu8yXtbjl1l2uc5XCi2UOnSoA1oUuem3L0ZB6SeHHglk25cXzx4fn0WZvsfY8L+\nFuiU8kuGxGjXdcRDl04pv/RnXP/JJ58sOXbsmL5z584d0tPTQyIjI6v8nRcZGWl/4YUXrvTu3bvD\n7bff3i4qKsoSFBTkBHjnnXcuHjlyRB8VFdWxdevWnVauXOlhQW3durVh+/btO0ZERHReuHBhs3Xr\n1p3t0aNHFcA//vGP88nJyS2joqI6/vjjj9pFixZddjgcwujRoyOjoqI6du7cueOECROuhYWFOd2P\ntW/fvmPbtm07zZ49uwXA2rVrQ6Kiojq1b9++Y3Z2tmbChAnF/tbvD8IvlTP/bAiC8DFwGBgnimLn\nal/fDFEUo2/UGnr16iVmZmb+9ie4XJLki0oHDhs4bZKQpdVYrWguQ7QZETaM9p7zi4hDTFzP5TIL\nzRqF8ei7B72EkUN0SkrMdkxWBzM/PU5KfCdStvxM+pN9aDd7G7OHdmBIl2ZeYs+LE7rSoqEGAYGp\nn2QxdVA7Nh/N91iwmawOAtQKomZvw+ESie/WnGn3tPOaH3z94a6kfnXao/E09e62jIoJ9yaNJEaz\n4UAeS7+tmQGZOqgtf4trjk6h41xRCV8dL2FEdEtUShuzMqQ2x+6Ru1HKlOiVekr9tFpEUeSNzDco\nsBR45ve+yf2GQ2MOUVpV6jVgnRqXysbsjazKWuVZQ++mvX08ff8ib9+/boL5N+I3vU9Tgv7SNfxe\nkeffK98SUbXud53/e5C7aOhfdu2bCDf1+9Rsc1BqLWHOvhk01jbm2ehnaRnYspoEITBp10RPe3RI\n5BAmRk+UHjdeQ1AHoVFKZA21CDZRhUblnj+WIbObMckEJu2c5NXufS76OcZ0GINOqaPEbESnUjBx\n50Svc3o37c3MmJm8d/w9UvqmUGmr9Io9i+MW01DTkJKqMmbUjmFxi9lY7VZU+1puT96ea3syKGKQ\nz/zyvL6LWPzFRbYcu8re5P40C9YS9ZIUo91QyCSFB6m7U+UVs91xv93sr/jXlBgWHU2q83c22sz8\n3w+XPe3bxQld2XnqKv07BHNLw2DyK/NZmbXSMz7jfi0WHlzIgtilVFQ5aB0m+QurZBr+9o+a+fHp\ng9vRPFiDxWFGp9RxqbycN746z9JHuiMTfvGt6PXgsWPHcrt161b06+8uCS6XGGK2O1voVHKV2ea0\n6ZTyS38G2eP3ory8XBYUFOSy2+0MHjy4zeOPP140bty4shu9jj+CY8eOhXXr1i2i9rEbPfPXWhTF\nRwRBSAQQRdEiCL/8rrmhqJ3o2czSLlMmk5I9lwscFjCXSo+LThBkYDcjCAKM+xyKTsP3S6SWcF4G\nglJHi22JiA+9x8qR7Xl12zm2HLvK5PVHWfNYL0L1KvRqOYbEaNYfyMMwSiJhTB7QhgeqiRq1Z/GS\nN/3I22N7AjDl7iiPBY87SYttFco743p65gHdCV5t/0a1XEZhpRWFTKB3RAij+oQTpFZ4fIWNVQ7O\nFVYyontLMnJKJMbwwDYkxobw/K7JnoD26m0L+SwznyfuiPSYf9ucNqZ/P73GaA83v8wAACAASURB\nVL1ae+tS5SUQYVP2Jqb1noZGrkGj0DC+y3gGhQ+itKqUTdmbPAw4k92ETqHzOIO44ZZ6qc0qdieW\n9ZXAetTj5oJGISfAEcwbcQacQpXP32xjbY0u/7bz2/gm9xsOj8lE+/XLWOKXgyhC2UVkJ7Yg7zaW\nFz+7wtUKG4bEaPRqDVqFtwewm2g2uVacWnDHAlLjUr02onP7zuW7i98xucdknt3xLHffcjfL+i0j\nUBWIyW7mh9PltG5S5pVkSXPIycyKmeWV/LklYyqtZro36e5JqmbGzKRVcCvMdjN6hY4598iRCwIy\nQfDou17vyW6xOXG4XGw+mu+Z3z5bYGTz0Xz+dkckvSNCWLnjAq/eV+N+MqHbBBLaJnj9zqlxqTzb\n/16ulVehUjoZ1qMBSd9P82JSy5B5NuFf5HzBwjsWI0P0EsJOjUtlzbgevP9DLgk9b2HTkYs80CvI\ny3llwbDFVNmd6FR/XSohkwklbnJHgPpGpyw1mD59evPvv/++gdVqFe66666KMWPG/FckfnXhRlf+\n9iGRNPaKothDEITWwHpRFGNu1Brq3Kle5+bhIWq4xSttZjAXQdYG6DZSInoENoWBL8PmZ33ZwMYC\nuC8VVsdKLeL7DdjkWorEIJoEaTHbHOhUcix2Fxq5DIvDiQC8/8N5HusbSYBGQbvZvrvDM68NYeWO\nbCYObOuzexwR3ZwFD3TBZHMweb23/MuGg3kYdp5l8oA2PH57JAFqBdkFRnIKK+l5a4hX5U/aLV4j\ntnUYbRsHYHKYeH7XZJ/ds7TjDQUktu9kP+e4SR61d5gpsSkM3zz8Fyt8K/qv4Plag9ju44b+Br/3\n+ZNlX/7jG5L6yt+/h/rK343Br71PXS4Rs8Pk9282JTaFoZ8N9Tq26vbFmEQbSfvm1CQht6UQkrWB\nkm5PUWJz0KaRVJmSCd6Vv0/jP2XhwYU+95nbdy4AzQOak1+Zz+qs1Twb/ayXPIz73Fd6L+Gu1AzO\nLRhCr/SePjZxmWMzif4w2us5af2WczjXTPtbFD6VwpBD/0D23WKPy5Ooa8TUT44xdZB3R8ZdABjX\nNwK70+UVv19/uCvBWiUWu5PJ67No0kDFC/dEcEvD4DrjrqF/GmaHhSqH2e/vmTYgDdHlQKvUU1V+\nEUHfmIm7Jvk9z+VU8dSHh3l1RBufqmPvpr1J65+GXvWLsfffqvzV49+Hv8rfjS6VvAJ8BdwiCMJH\nwA4g6QavwT/8uXlsfEI67obTAbHPSIlf7h6ImyolftcLPfefLSWB3y+RnpeXAQ1vRbV5PM10Tq4W\nFvJ/P5znUmkV7+/JocRs4x8/nEerUmDYeZYAjaLOWTyT1UFOkYnCCqvX4/HdmjNtcDue+CCT1748\nycIHu3DmtSGkje7OpTIzj98eyen5Q3gyrhUmqwN3yti1ZbDHIs49x5G86UdiW4exatdZ8kst6BR1\nD26bbU5kgqzO4e7ajD33bEnLwJZkjslk/u3zcYgOnur6lJd5ujRwrSc1LtVHAFYQBK+Kgfv8evJH\nPepx80EmE+qMDT6CyXGLcal1JO2b403Q2J+CJXoUqB0sOppEz7U9eX7XZMw2m5e4catg/0SzZvpm\nDPl0CLP2zCJUG8qCuAW0DGzpf03BwQB1Cj2bbEZfkef9b9E3XMeGaiu7zDGHMfRfISV+u17zfDYI\nG5/AZTVyrcLKkq9rRPsXPtgFvUrB3+6QNuV6lYI3x/TgzGtDeHNMD749cY3xHx5Gr1awZlwvlj7S\nHdGlZurHx3xe2yGRQ5gVMwudUkuVw0yLwBb+ZwTlGgIWhiOfG4p+RTQahabOWcIAoYqmDVR1+vxq\nldq/lPRRj78GN5rt+w3wIPA4sB7oJYri7hu5hjpRl5uHSif98doq4fhGUOlrzgtrV6cDiJckTHis\n1BL2tIL/zhM9Avi8el7v+Q1ZDO7czJPwnS0wsv2nKz4OG8tHRfOPH84ze1gHFHJJQHX3tH6cW3Af\nc4d34tPD+WTkFLM56zL9luzm0TUHUCtkRIYFMGHtYV74OAuTzcHUT47RbvY2Urb8jEoho0kDb1Fw\nNwHluf5tSN70Y92B0G6WdP6oe7i7NmPPLVyaX5nPSz+8BMCsH2bRc21PFh5cSFLvJLYnbGdCtwnS\nLJ9Sy+qBq5nWexopGSn0XNuTSTsnMbnHZE+i6L62xfHv2ETXox71+KtQV2ww2oysum0uh8dksrzf\nMjZmb0Ij19BY25hP4z8la2wWn8Z/SmNtY7QNWvrYPSb/8CJOp4pXei/h8NjDWPy4gHRv0p0rpiuA\n5AiCsQDZvEZYyi74PTe/TOrkrdxxgVdvW+id6PWdhz7rY9Ji5kjEsz4phHyTguy7xcjUASz9Jttj\nZadT6KWKX23kZSBXB/D6w10prLQy1LCHMe8eIESnQC1a0KvkVJSX4XA6PWoPz6QfYUD7JjRpoEaj\nlIMAj645QL8lu9mcddnrtR0SOYTJ3Sez4OACeq7tSUpGCqY6XhNLcbbXMUtxtv/zis4grE9k0b3N\n6rTju1ha9peSPurx1+CGJH+CIPRwfyFp+10BLiOxfXvciDX8KmxmuDMZns2Al0uk73cmQ0kuOKxg\nNcFd06CqXDoOUkJXLTvgQXgsYlWl1PZ1s4LdVUB3Epi7B92Wp3iwSzCtG+lJie9E2yYB6FRyVo/p\nwfafrjCie0vP7Mfp+UN4a0xPth2/wtJvszFWOflo/wWsdpGZnx73+DGO6N6S+G7Nie/WnO1T7iT9\nyT4ISB68h3JLeK5/G48OlLvKN3l9FlPujvL6FdwJqJuB7DcQxqWiV+o86u4aucZTqfPH2Ktt37Yy\nayVPdHnCI+xaW4LB4XKQ0DaBz7M/Z9LOSdhcNp+gP3vvbCZGT6yXfalHPf4LoBUFUuO87cfm9p3L\nulPrcNmMWIqzmbL7BVZlreKa+RqTe0xm4cGF9ErvxcKDC5ncYzJWp9Vv1alpYCADl+wHEWSC3C9r\nWC7IPcmbdsc8cDnQ7phHat953jHtzlSCNXpiW4Xyr+PX+CyznBX9DVKi1/c1Qlwu5DFPoneJyDY9\niX55FwBMkzJBgK+n9iG+W1MArhQW+f1scFqN7Dh5jX883ovsV+JYNz6GQKEK+f43kc1vRMiWcaht\nJTQKVHp1YqbcHSWRXVRymjZQ8cMLvclZMASVKGNxddx9qstTHr1Ud6xcd2odi6977VPjFqM9scX7\n/+jEFp/4nXpbCtrvUiF3D+rN42moUrGs33KyxmXxWfxnPBf9HIvjUln2de4v2n7W4+bEjZqefKP6\nuwboBRxDmgPoChwA7qjjeTcOSq0k3VJbnDnhXbjyI6j1sHWy93GAPUthxGqvmT/biDWsP1LE/fEf\n0LBhQ4SSXNg5X0oG3fOAAHkZNG8URoHRRsqWnz3zHUsf6cbf41qhVcqk2TyNguxrRlbtkgzRt0+5\nk/BQHeP6RvDhvlwPE+u5/m1o0VDLvOGdsTmcTL6OvTt5QBtPMlcbh3JLCA/VEdsq1Ov8UL0KY5Xk\nzenWm5oxMJXWYSEetpdMkOESXR7GrYjI3L5zaR7QnCJLETqFjgVxCzwEjrEdxzIvYx7bzm9j4R0L\nPTv8VkGtyCnP4b3j79EioAXjvxkvzQceWlinx2/LwJbSbv+vYfvWox71+LOg0NBQoZYIXUGR5JTn\neJj+T3UZD9Q4dLhEl4/g++y9szH0W+5XyPlckRSz8koshIdqMeyfJ5EtqmOK4YiBBXELJJWALVMk\nKzaQ3DYEOWnxaWjkWvLLytDJG6BRyD12m1U2J06XiADol3WWOkCdE6Q5b2MBri4jKbknxWs+8dX7\nFgLw6fEyJia8h7BJmiF33ZWMuc/T6NQBPNBThtJRifDJWO9Z8aJT8NMm1JvHkzTkfS+dv/BQHYhg\nsztZdG8z1Jv/jiuwGeX3pLApZyuzYmb5bXu/fextnuzypOc1uWS8hF6pR9bzMVyApWO8ZP1mNxGs\n1LGivwG9Uoel6EyNdR3gCmxGlWAhabc3IeSnPAfXKmyYbc7/KBmjHr8fN+R/SxTF/gCCIGwAnhJF\n8Xj1z52BaTdiDb8Ku0VK/NxyLbl7pJ9HfQQbHvU9/kg6aBpAZXVSF3QLotXI+iNFvLL1FIfzmjJ/\nqJLAgEbw4DtSEli7FXxnMtiMNAoI4PXhrUjdqWTLsatM/fgY74zrKf0xaRRUWOxs/0lqW1wv27I4\noSsNtEoGtG/iI+fSKFDtpcX09tieXCzxzzIrMdm8HEXsDhcg4HA5Pd7B/zp+jcJKOytGRROqr0n8\nKm2VlFvLaRHQAovDQpAqCKPNSKg2lGuma5RZyzyD1kHqIKn1Ap4d/uy9s71YaNfM17xmBc+Xna9T\nvV+v1Nc7fNSjHjcxXC6RYpMdncbBgoMLfMgCFocZBBndm3QnTBtG84Dmfjd7OqWe1L7zvBOt2xby\nWWZJNftXgcVhocBSwINbHvS6x8XSMuR2B/rKK17XlVVeQWV30nrONg+ZTiYIBGgUOJ0ujDYHz6/P\n8lilkbunJn7fb8DSoAlJtQgnh64e4pX9M1kwdClahR5RI+fykPdp2iiUkqoSkr+rsbtM7TuPkIDG\nyGrPit+XKl37zuk0DwvlWEocAaoA8svKPIxatWhB2Dwecvdgee4AG3O2MjB8IJFBkVTYKvzGyvPl\n5z2viUJQcHjsYVxyNSW9/+4txxWXik4RhLGinAZfTvN85rk6J2AetoSk3S/4uDClDUijZ6vOaBX/\nf2++dTpdd7PZfPT06dOqYcOGtc3Ozv75iy++CExMTGzdsmVLm8VikYWFhdlffPHFq4mJieX/6fXC\njSd8tHcnfgCiKP4E3DCNv19EXTN/6kD/xzUN4IN4WNpOcgCZG4Lw8aM80DmEB6Kb8fqQ5jT4dDTC\n4giE75YgqnQ1reB+LyH2HIewYTSy+Y1oue3vLBrcjPhuTT1iyk99eNgz8zEqJpyZQ9p7pF1qtwNG\ndG/hc3z6P3/kuf5tPMs9lFtCgEZB40A1huucQVaMiuaLY5eJnvsN23+6gihCkE7F2QIjNofIhoN5\nntZzSnwnNhzMw+KQVMatTismu4mUjBR6pffidMlphOoBb5PNRFN9U1yii1l7ZpGSkUKAMoC5fefS\nu2lvXKLLp+07e+9sXKLLa1bw27xvfdsW9W3eetTjvwJmu+QKZDHZfdust6WgVWjRHPmItP4Gknon\nkV+Z73/2rDyPEIXOI7hs6G+geWAj/n5HK0L1anQqBVqF1tfpo7qV+9nxMszx73iJ9NtGrEGuCQCk\nTbDV7gCrEVF0IdhNfHwgr9oq7aL3c40FoNbXKSDdOLABT6cfJrvAxLTPczhXJGmYeo247JuD5a5a\nXMe8DAiLgoEv4zq5lRLjJV74bgq90nvy6qFpmJ1luESXZCoQ2AzTcwfQhkWR2D6RHXk76JXeiw2n\nNvjEyvm3z2fN8TXer2XZBSyVl3ydT/YkIQo2jC411hFrPELaJYPnoVHqmRUzyzOHOSRyiEd66/ld\nkym1lkjrq4cXevXqZTx58uSJ3NzcnwwGQ960adPCP//888D/9Lrgxuv8nRQE4V0gHRCBMcDJG7wG\n/3DbBtUWag6PlWzd/B23mfwmhYENglj6YHuEdSOl53ROgG4jEQIaI45aJxFGbCZvUejqGcCkIe9T\nWGknr9jspe/3/IYsPhrfx2/LtoFW6fd4m8YBnp/dLGGAhjoVb47pQaBGydkCIxsO5jG4czPiuzWn\nx60hXn6+H43vg2HnWS+xZ4VMYOLAtgBeCdyQyCFEN45m3cl1PsbmbkHnS8ZL/Ov8v5gZM7POHX7z\ngObMv30+hiMGejftTXzreL7O/dq3bVHf5q1HPW56uF0i5m47R+qwCKn9KtdgKc5G+00KDHqV0o5D\nMVeVkJKRQpg2jLl953rFj9Q7U9HKdcgUGvQy6e8+QCXFtwB1TRyQCTJCNCE+QvBVdhf3R7dAE6zF\nPnIdCk0ARaWlINNRUmAitlUoaaOi0dhKYOMTCHkZCOGxTBixhuzCpp72a/KQ92neOEyymFPqPGSL\n6yttF0vLyMgpZtWusx6BZr8s2dC2NQfCY6GqEj6fiGXoEpJqybO456HT+qehFqHsulbz3L5zySnP\n8chlGfqvQKfUY3FYcDgdHltMd8VR8/NWhD5P1cnu1eqr+CjTQv8h79MwRM/GE2tJaJvAgoMLvO7p\nbq171vfnym3VwOUKwW5qgUqvwmayodRfQib7wyLPFRUVsvj4+FZXrlxRuVwuISkp6XJKSkrLBx54\noOSHH34IdDgcwltvvXVhxowZLS5cuKCeNGnStaSkpMLy8nLZvffe26a8vFzucDiEl19++fLv0frr\n27evZfr06ZdXrlzZePjw4ZVnzpxRPfbYYxHFxcWK0NBQx4cffpjbtm1b2/vvv99w4cKFzWUymRgY\nGOjMzMw87XA4eO6551ru3bs30GazCePHjy+YPn160YULF5QJCQmtjEaj3Ol0CmlpaRfuvfde46+v\n5sZX/v4G/Aw8D0wBTlQf+8+jtpVbbaLGj59I368/bjX5JYgIJbkIolNKDDsnwN2vSiX9eY0QNoxG\nqLgkiUb7SRybNwrDkBjN8m/PeD10KLcEs9XpV/rFPZd3/fGLJWZPdW/Jw91wuUSe+vAw7ed8xTPp\nR7hUamHVrrPkFJloEaxl+ahoLDanV7vYLUZ6/bXNNonZVXvnO77LeJL3JDMwfKDP0PHL+15mfJfx\nrM5azUNRD7Hw4EIqbZV+d/hmu5mGmoaeOR3DEQOLDi3iwS0PEr02muGbh6OWe7OT61GPetyccFuO\nbTl2laQvclHbHcg+HI5+VR9kP23CIook7ZtDiwBJkmTb+W0YjhqYGTOTzDGZNQmFUoPJafnV6pJM\nkHk2h+7vGqWcu5d+R6tZ22g7dw+Rs7ax4JsLhGlEohrCuvExhKpsCJkfeMl2qTaPJ2VwBFBjlWay\nuaT4LZPVWWncfaqM7VPuZNkj0chlYLSZ66xmuj9TxIT3ELVBkJeBNrRtnZIqZQ6njxSOO76CNOOn\nU+qR2czolXoC1YGeamnagDRCvk6hqv19dVZY8yvzsZiuMbKjltSdF9HItdwdfrdP5fLlfS+T2D7R\nU1X8y+S2XK4QzIW3sj5RxbxGsD5RhbnwVlyukF9/sn98+umnDZo2bWo/ffr0iezs7J8ffPDBCoBb\nbrnFlpWVdapPnz7Gv//97xFbt249d+DAgVOLFi1qDqDT6Vxffvnl2RMnTpz87rvvzsyaNaul22v3\ntyImJsZ87tw5DcDTTz8dPnr06OIzZ86ceOSRR4qfeeaZWwAWLVrU7Ouvvz5z+vTpE1999dVZgOXL\nl4cFBQU5f/rpp5PHjh07+cEHHzQ6deqU6v333w8ZOHBg+alTp06cPHny5z59+ph/6f61cUMrf6Io\nVgHLqr9uLshkkqBz4gapBWw1wv63YPdrkH9QmscIawdVFXBwDdw2wT9B5MTnEDNeSgw7DoPNz3jP\nC25+FuGRtXVWE/VqLdcqrF5L6x0RgsnmYHFCV29h0FHRWJxmPhofw8XSMpZ9ncu1ChtvjOyGKIqc\nnj+EswVGFHKBp9OP+LiFLHm4KyIw/sNMrzlCgC3HLrP82zMYEqO9BEcNid098i5Wp5XPR3xOi4AW\nVDmraKxt7NHyqw33DF+BpQCdQseK/ivQKXQ+O/y5feeiVWiRy2qYYxFBEV6kkB15OzzzfvX4a/F7\nRZvrUY/roVPKMSR2Z/3BCyT0aoJVqUD22BYsxmtov34ZbQMp6btmvuaJJTnlOaw5voZWQa14qO1D\nPjaRv+Tm43JV+6er5B4rOGwmzsy/l8uFRaTuvAhA6rAIBHORr0B/NenC1TkBy11JBDdsyNdT+/DV\n8RJGxYR7Yh/4rzTKUTOwg47p/6yJ02mjo31cRtzVTOYUItpMVDrViJVGFJMy0QoCn4/43MuGzb0x\nDtEF/KKeavcm3bHYjGiVeix2k1dCpneJuMLaog1qyeo9s0i9M9XLdWVu37msPLqSBXEL4PslzLnn\nCc4VldC6UaTfewaqAr3W95fEZbupBRufkHl9hm58Qkbi+haoA/9Q9a9Hjx6Wl1566ZZnnnmmxfDh\nw8vdlbKRI0eWAXTp0sVsMplkDRs2dDVs2NClVqtdRUVF8sDAQNeUKVNa7t+/P0Amk1FQUKDKz89X\nhIeHO375jjWobapx9OhR/bZt284BPPPMMyWvvvpqS5BaxY8++mhEQkJC6aOPPloK8O233zY4deqU\nbsuWLQ0BKisr5SdOnNDcdtttpgkTJkTY7XbZQw89VNq3b9/frHl2Q5I/QRA+EUVxpCAIxwEfNUhR\nFLveiHX8KmpbuQmClNzlfi8ldMYCSHgP9GGS0LO5uEbsGWqIIPcbJHmY2yaAqlaFr3MC3DlNSiDt\nZsRH1iJ8PNbLTUSm0qNBwJDYncnrj3qCxxsjuyEDNh/N9xAzCiursAsVzN47oyagDE9FdAQgEwQm\nrjvq1b5t0kDF11P70DoshHNFJazemUeQVsX4DzN9ksKU+E5sOXaZaxVWtEoFS0d2o3EDdTXLV4nF\nYUaDxjPvdz1hw18r5JLxEq/d/hoCApW2SkqrSj0tYHdi90XOFx6PSovDglquJqFtgo/vpkauubHv\ni3rUox5/CDKZQEOdnMdub4LJYWLSzhqCV+p9qeidViZ0mwDgE0saqIKYvGuSb/vzuvZibcUBo73G\n2/b5AW2Y2CfIw7htGR7Lovh3cMi1KK2lkoJD7fhdTbpwASWDUkjaX7Oe1LhUgtVKj7RVXXCJ8Nnh\nfF4f3ormjWK4XFjE+v15PHpbOIb+Bk9sq61QYELL3nPX6NVaxQsZ8+q0YUs/mc7oDqPrJHW4Jbg0\nSh0l1lI2ntnI3eF3ExkcidFuRK/UUXXb0xRX5lNgKcDmtJESm+JJuA1HDRRZisivzEfXfRShAcGE\nIGCyG/3e02gzMjRyKAWWgr9uDlulV/nX39Wr/uglu3btaj1y5MiJTZs2Bb300kstvv322woAjUYj\nAshkMlQqlSdPkclk2O124e233w4pLi5WHD9+/KRarRZbtGjRxWKx/K7u6aFDh3Rt2rSp+qVz1q1b\nl7dz5079li1bgqKjoztlZWX9LIqi8MYbb+QlJCRUXH/+999/f3rTpk1Bjz/+eOTkyZOvTZw4sdjf\nda/Hjar8VQqCcDtwP36Sv5sOjiqwlEpWbve9Lg3iWitBoQEEyXMyOLxugWfRJc0QCgI8dwiyv4Z2\n90rBxVMlfA9x9CcISo2Xj7AMCNWrWPNYL3QqOXnFZhZtOwXAooQuiIIVUVSg0zj56OSnPoFxRvdU\nGmoDWPhgF24J0XG2wEix0cr0oS2Zs69mlzdv6CK0Klmd84JuUemNhy9yJK+E5GG3MGdfTaK5vP9y\nj/6e+/6z985mwR0L/M7s2Jw2RERcSHOCYdowHwP0xXGLybicQdL3SZ57uNsN7nsk70mWgr+svvJX\nj3rc7HCJLsxOM+W2ci+bMXe8MvQ3MLbjWC+bNncsSRuQVudcmjvGupRaSqylXhWsV29byNmCJjzQ\nJRhh0999ZqvFx7aA2ECSYKmu8GlD20pziKFtsNyVRNL+69ZazWxVyL2TTn8+4+P7hKLZ9Jgn4Xwi\n/h00OhUIamSC4FMd0ypl9I0K5IXdU/y+BpeNlzEcNXiqbKlxi0mqtSFOjVtMw+sqkBvPbPSZvU6N\nSyVEG8LqA1KM3nJuC8NaDWP8N+N95rOLLEWk9TegVwWgV+j9+iOvO7WOObGzwViIFjkykT/fcNBm\nshEeq/LTJbOh/mO8idzcXGXjxo0dzz77bElgYKDrgw8+CP0tzysvL5eHhYXZ1Wq1uHXr1sDLly//\nrgT0wIED2tdff7356tWrcwG6d+9uevfddxs+99xzJW+//XZIr169jAA///yzesCAAaYBAwaYtm/f\nHpyTk6MaNGhQ+Ztvvtlo2LBhlWq1Wvzxxx/VERER9qtXryoiIyNtL774YpHJZJIdOXJEB9xUyd+P\nwBKgGfAxkp9v1g269++H6Kyxbdv9mnQsIg5GfwKmQtj0BIyso3VbVQlVpd6J3iPp8PEYryAkbHoC\ncdQ6XKKAGQ1awGIzSjtDpwWZIM21WR3umQIXRkfZdd6RqQxrNYym+qYY7UYCVYFUOapQy5WUWoyA\nFkFmBQHm7J3hFVjm7JuBob+hToPxlPhOvPblSbYcu8zXU/swZ593oleX/l5jXWNEUfTa5c7LmMeX\n578ka2wWgiBw9NpRj2emu/JX5axi7Ym1DAwf6Jkrqese9UzfetTjvwMeSSZFHX/LSi2I1Pl37lfm\nqewC+rReEB6LJXGdzyb0lf0zmXffMoJ1ClzjPpeSuu9SJc26vAyJrFdVgeuuZEqiR/lU+ELCoupc\nj9HqQKeUI5MJWJ1WzHYzawat8bSqk75PIq3va5iGLqlJKI+n44p5miqZzq8WnsVhJkBVd6xbc3yN\nJ/F7+9jbjO8ynrSYOWiDwrGU56EVFMioTipdLrQKaU7ver3EpD1JGPoto8BSgOGogfFdxtNU3xRD\nfwNapZacshxPkqkQFGiVOnC5kMvkNNQ09K/T2PUpZCuipc/HxA1S5+zPhFJ/iYfeu5WNT8hqdclc\nKPWX/uglDx8+rJ05c2ZLmUyGQqEQV69efSExMbH1rz3vySefLBkyZEibzp07d+jUqZM5MjLyFyt4\nAJmZmQEdOnToaLFYZKGhofbXX389b/jw4ZUAb775Zt5jjz0WsWLFiqZuwgfACy+80DI3N1ctiqJw\nxx13VNx2222WPn36WHJzc9VdunTpIIqiEBISYv/Xv/51bvv27YEGg6GpQqEQdTqd86OPPjr/W1+H\nG6XztwJYIQjCrcAo4B+CIGiQLN42iKJ45hcvcKNR28LNjbwMKSncVO3/qwmUZkRqJ3nDV4Jc6dsO\nrksuRh1AsdFGZm4RfaMCCVDpySnL4du8b7m/1YO8/mk+1ypsLE7oiiC3xFpL7wAAIABJREFUMmPP\ni54/5jBtGDaXjS9yvvDa4U3oNoGEtgksOprstRv154erU+p8WsyGxO7IZJCy5WdPUujP07Eu/b2c\nshxaBf8/9t48Pqr6bP9/z5n1zEzIQgirCChulQKyCGhYpNqiCGp4rFCoX6uIVaHgEgSRpoABprbE\nsCiKT38VK8oTUBClBReWKrJDtYqgAZE1hISQmTmz5ZzfH585Z2YyM1ZpXWLner14hZk5c86Zk8l9\n7s9939d1dcIsmblrnRAX1bX9Kusqaelqabxv7cG1rD24ll6telE2sMwIbP/qGJmZvwwyaBqQLTLH\nvMcMCadU8UL/f+PXTvnq+V2f2fz2/SkJ+njy3x4zSBlyigVigVyA3RZm/NuTYu+7toQ8QPJWUR/U\nyHJko/QZl1K7rnzAH1Oez6enavjtq59SPrI7eS5r0tiLPjMnu1ty13uPxo7dt4RcuxNTQxBVk5La\nvk6rk8ozlSmPeaT+CBO6TwBg7cG1sfjnzAeTCaczH5PVJUaWVBX8p1DCfjrmpJ7Tk60uPH1ES/vW\n1241Oixj141NnWQ78wETAcmURqdRwQVweAuazfkfL/whSTViFn/Zf4ztW1RUdLaoqOij+OeOHj1q\nSNBNmDDhNHHVs/jX9uzZsy/VPv1+/26Aiy++OHTgwIF/AgwdOrS+vr4+bZHr4osvDr3//vtJuc+6\ndes+S7X9ggULjgIJSe/48eNPjx8//itV+hrj2/b2/VzTtLmapnUHRgE3832RegHxxxP0ipVhCmue\nhKSwej/sXS6IINOqxM+9y8HqSE70qven3l/Qi00L0usCO5M2TKTn0p6UbitlaKehvFa5kt/ddCEt\nsqxMXvEP2mZnJ/wxj+0ylmnvTkti1w5uPzhZU2pTMfd2uzfh8N1bdicQCeC0R/jL2N7s/d0Anvt/\nPWnusuGwiCFtXQ/wyJkzScywNw+/mdLOLdueDUBEjfD7/r/nrcNv8fhVj9OrVS+e++A5XBaX8Vh/\n3+NXPY7T6kzQ90t3jIzGXwYZNB0EIwFki4zL6kqyXpvRbwbPfvAsz37wrKH/GR9LHFZwW7NjFmtR\ntqruOgGpPWnv7XZvkiVk8fslKIMfwz/sGaa9fgCsTmRravKEbHMnaRLOLZxLp/xcfnfThSzb9jlK\nxJ90jOnvTefebvdypP5I4rG3lOCL+Bn/9njDn7wmENPFUyIKbx5+M+kazOg3gwV7FjD9venc3eVu\nY6bPaXVismdhMkmY7Fki8QMI+6HiTuS3ZuILeVOyeQNnj5G3voT5VxSzc/QOygeVs/XY1qRjewrn\nIL9dimp14pNMyBaZsoFl3NftvoTfkeSvFTtv3xct6PsPf3uikKQa7FkfYJJ2Ys/64N9J/DKI4Vtl\n+5pMJivwM0T1bzCwEfjdt3kOaRFdNVFxJ2S1SrJtY/gCOHM41urd9ISw+Ymv/I34k2ADN24Hf/Sa\nIItEB49p3xet6DnQGrA0nGHSlpkJq8/p701nau+pZNlczPlpayr2BfCH/QkrQ51V25hdm45t2y6r\nHb1a9YrN1139B84GfUx9N7FC6LAKJl383GEg3JDEDBtx0Qhy7DmUDSrDZXVx3Hscu9nOw5seThhY\nHnbBMFo4W1B+TTlOixN/2M+qz1YlED1WfbaK6ztez9zCuaw4sMLQpBpx0Qhy7blJul0Zjb8MMmga\nUNF4eNPD5Mv5TLxiovG3XB+qZ9m+ZUY7E6Ckbwntstrx2ZnPKNtVRrVSzW97PUGuw4VJ84kKUyOX\nDuFJG5uBG9d1HO2y2qVO6nLOZ+JLu1m99wSTr6kmx+ZLWW0L1H1Bnj0n7ly9LNv3Iov3LjZmCp1W\nZ9o4O3Xz1KTnXVZXWuKKbHYwonMRFQdWMP+a+TjMDqO1qrdgO+V0Yv6gJ5EtTqS4GfEERI0KJDWC\n68cjkxnG/WZGW8TgWngldCjEeftqijcVc22Ha42YfLDuILmOPMjvLGYaGxHu7upyF8e8x3BZXNic\nLny/2YPZ0gybLdONaUr4tti+1wIjgRuAbYBu8/YNLRXOAdFVk5G0aapg7uaeL14DUfn7+V9g62LY\nNBfyLxHzfPYsiChC+2/rM8nt4K63wuGtxrZayAeSBdOLt+L45asJsxTPfvAs6w+tp2NOR5TqA8gf\nrWZIrzt44eMXEogUR71HjUpZfABr/BhiMgHzBpTjtjk5UV+PzSLhtjVjSu8pxkxJfECSJJMxn+K0\nWXBoiQPFDrOD2jhGWWt365RD21N6T6H70u68MuwVOmR3oD5Uz4iLRiQNSbusLmySjTGXjeHuH9+d\nkOjp5I5MqzeDDJoWdC3QiBYxEr1Xhr3Cm4ffZGinoWw7sY3dJ3dTrVQjW2Qe2fwIIDob+iywNejD\ntPyXKRfl0hW3k/fBSuZfUYyj+YXUBs4YGnap2ra6YPPKD85w79WtKRtYhsvm4uCZg7x5+E1GXDQC\nh9kJUUFpb8ibRMT47ftTKB9UnjbO6mMu8c8fPJM4ihU/uyyFFfK2/4kxlw0Tn319ihZsyItr2SjD\nJ1jpcw+yzZ24INaNCtwFmFt0Ji8Sic0Gnj6A/LfHkLxVgsTorUIres4oKugjOCDaufN7PwYp2uI6\n4S7HnsOLcQlx6VVzaRZRcdoyC/Omgm+r8jcVeBF4SNO072fJtrG924crwCSJP5RgfWIVsGgJ9H9A\nVPnsbtHWzW4Xmwes3henC1gHbzwk9jfwUeg9FpOcDSEf6qU3UhuoSamc7gt5cW/0oAwoNtq4lXWV\nYnWW04lgJIinv4eK/RUJSeFbh99ibuHcBHmUWVfNokFtwGV18+DyPTw4pC2TNkxJOCbA+kPr07ZU\nddFUEEmYL+wz2h4L9yxkz5g9X6o/9ebhNxl16ShWfbaKEZ1HGBIDR71HsZqs2M32TKLXxNEh8OJ3\nfQoZfM+QygXjzcNvMqLzCCoOVIiFb05HfGEfW49tBUhSATB8cD/4v9iiPK+DiMtmO9LHryF/sRXv\njfMo3lyc0iVkbqGHZVtqsEgmenXI45f9OlCrnaV4YyKBLteegzkcEKzVoBenLXWFT7bIyZW1PiXI\nkXCSB7GncA4VB1Ym7CNhdtnmRNo4F9c7j6NeXoQnhcyM/P7TcGgz6uVFgqSyYWLC4jnP7ESyysKo\nIOiDVfcj/XIVrlkFoEYwoqlkgRYXw8hlmKxOnCZTUlfH0CC02NN+9rvW3ZWQFE59VySF375pWAbn\nClO86GBThMlkOgTUAw1ARNO0nl+2fc+ePbUdO3YkvxD0wrLbEtu1kz6CSDBRDwoEs+l6DyzqG3t8\n+2qY2UIMIuuQLGIecEae0Plr1Cb2jfwL4+NWViBWXWWDynDtehHzXyejTq+hxws9DXYsxMy5AaMK\np0QUnFbRVrVIFqr8VQmCqdVKNWUDy/EHI7x68CUGtx+cIJw8uP1gZm+b/ZUtelRNpcfSHsZ5rRy2\nktnbZid9lqm9p1K6rVR4bNpz8Ef8THxnYtJ235g10LnhPz63/HWR9nsaj5Lsb+dkviK+T8nfoTk3\nfNen8G3ge/89TSWHUnrVXPJtWQTVoKhenT6A47MN1F56PX4TCZIwEI0PVxSLViWIuPrYqZhomP8U\nvrAfR057ei4VsXJIxyEJ1UOHWUYJq4b4s0kKJnQqjOMMLDMqbCJGv8j4DanjlWx2CCFlq0tU1j5a\njdTjDlTJghI8IypuIS+Oyo3Utu2WzCqWo2LVje496uVFKIMfQ845PyrU7ESKJnG++7Yyfpcn+Xx6\nP4bL6oQoEYSZLWD8zgTyYdJ+ow4o8TqJSkRB1kxISi0+NcT4bTNTfvarl12d8p6UZiQn4Xu6d+/e\nQ127dq1O+6XJ4D+OvXv35nft2rVD/HM/lDR9kKZp/96XSbd3q4jN5dGstdD0S8XUzb9YBKGoQDNB\nb2rpl+pPxP/7P5TEAk43cOy2upHWPQodCvGHUs+lGBIK0YRJ97pEc2CVJIa/Ojzpj9Ntc+Kyaim9\nd1u5Wn0tMkXjFf2zHzzLrKtmMe3daYkraUdsZk8ySbijnzk+OB+sO4jDLESjMzN9GWTww4FkknCa\nc/htrydol5PDZ9U1lL72OWU/744LK8wqwBVdMOcd2UZe0ZKv5oMb8sdkRZwtkE0kMGbjlQTmXzMf\nsyQZPsBuuwVVk9KSPeJlWhyfbUiu8BV6kM0OJMmMy2SB2s9xNe8Mlw6Fv05Gyr8EV597wGTCJVmg\n7RXk7XmR+VdE9QTDXmTJFotzje49krcKi6UZkbqTuF4dK7pP0XtLWuu37Pbw/HAht6JfI8lstMnV\nrNbUNPIEjndLEYmsH9nqFD+duchBX4oqpgcTpowKww8Ambusjnh7t2lVcFu0ihHypmbqhnxi9Tl8\nAdizRZJYtCTRA7hoCXy0RjzOvzgpiUzFVOvesjtK2Ic67RRHhvwvFTtP8bs+s78y49VpM/NZdU3K\n/VaeqcQb9qb03g1EAkYgUDUVX9iX8LMxGvtaVivVuKyuRB9JOQ+zZDY8NkEkjeO6jmNC9wnM3jab\nni8IhnNNoIalHy1NYMFlkEEGTR8Oq5mydYc4fqqazvl5/HH4hZgiAaj9PCG2Sh+uQDnz+b/0wWXE\ncyJhioMS9qdkzHoKU8dKffHa+DjesJfxuzz0eKEn43d5qO3Yj9z4uNanhLyD7yGFvKIFrTXAhlLR\n3VnUV4z3bJorElOTBFYZ3ixBunQoruadkao/wbXmQSRLnD959N6jjVxmxH1fGGyvjo2SC39v+Mun\nvWecPhB1vnDGksmsNvDWDLjegzKsLMkTuHhTMUpEQVUbqAnUMP6dCYKN/M4EaiJ++OdK8lQ14bPn\nOnIIq+Ek5nZTVmF44IEH2kyfPr3lxIkT27z66qtJytFr1qzJGjRo0IVfto/q6mrznDlzWuiPP/nk\nE1vnzp1/1Hi7+GO0bdu2y/Hjx7+zAtwPofKnAetMJpMGLNY07ZnGG5hMpruBuwHat2+ffk9S9I/V\ndyrm2dt/skji4j18b1okCB7vPw3dbhMB4OVfQL8JImm0u0E5A0d2CH/f/g/Gksi4ymBjplr3lt3x\nXPU4Dsz8Ysk2Q2dv1+FW/PanT3Bebk5Kxmt82d4f9vPZySBzCj0JgtC6cnvp1aUpCSZOq9NI/FKp\n1ufacwk0BBJYt7n2XEPM2R/2J/jyplsByhaZMZeN4bRyOkEcdfLmyUzpPSWlfdN/C77y9zSDDL5D\nfN3vaSjcwJyftcb+6q/g8BYs7fvCTU+Bs3kSgUO25yTPoBXOBZz4phyOxR9TtHIRVWmQd/6ZEd1v\no6JyTcIcocsSXXiqqiDu2ZwQ8iFL1hTH8fDixy8ms3J7P2aISrtuegrOvxJe+kXi/UBTReIHiZXJ\nkB/qT8RGhEAksCE/qi1m9aY0KJgkM0ve+ZQ/rj9AZemQWLHgwxWo7XqjjPwLsi2LskFlbD22lY7Z\nHcXnDHlx7F4WlQ+rB1uWKGSEvMax5ek1aef3lLCf4kZOSsbnnne5MS/o6lCI8ovl1AXraONuwx8H\n/pEsWxZH648mLPCbKsrKyo6d63tPnz5tfu655woeeeSRU9/UMf7T+CEkf1dpmnbMZDIVAOtNJtM+\nTdM2xW8QTQifATGj8qV7C/lEoqcnabrDx63PgyM7RuDwRrX9Xr0XRi4TTLQWF8FLoxLlYfYuh25u\nUR286Sl49dex13uPxWG2Mm/gPLJsWdSH6rFKVgJo/GVsb+qDPlw2J0fP1JHjcIMWswbSDcxlq0Rt\noCapLWGVZJZctwQlonA2eJZ5u+YBUBuoTUkw0Uv2SkRJUsyv2F+RZLA+b+A8wmo4KUn8MtN1HUpE\nSSmOqsvUNNUV5L+Lr/U9zSCD7whf93tq1xRMehULxM9Xfx0VxXeI+GlzQciHZDKTt2VBrEV6+gCO\nQ1uo7dCP4rcTY1yeIxcprEDFnUiHNpN3ah9jBhQjZ3dECfuxm5yYTBKBUAR76DSmaFtVsGXHkefI\no3zgPGSrGyXsxWF1sXjv4oRzN1qqUVFpde8ylCvHIUedQxyfbSCgNSAXLRE2cR+tRupxe6wy2ail\nqzN1HVZZxO24+DnrqlncflVLAI6fqqZttFigXl5EzaXXU7whJlqty2Itfm1xjBRz+c1I7y+GvveC\n3Y1qc6GMfBHZ6sIfqmdc13Es3LPQ+Gx6q1ZOI1sj55wvEtXo/Ur9+VJ8EX9S7F60ZxGlhaXn/H36\nV1A1NU+JKG1li2xTIkpItshHJdO/p/U3efLkVi+//HJ+mzZtQs2bNw93797dX1RU1GHo0KF1d9xx\nR21FRUWzhx9++Ly8vLxIly5d/Pr7HnjggTZffPGF7fPPP7cfO3bMds8995ycNm1a1YMPPtjuiy++\nsF9yySWXDRgw4OwDDzxQleq48cfQn/N6vaYhQ4ZceNNNN9U++OCD1YsWLcp76qmnWobDYdMVV1zh\ne/755z+3WP7zqVrTTtUBTdOORX9WAa8Avf+tHdrd4st+eRHcuwWm18BlN4KjGcwqEAmgbhPU4hL4\n5Srxvp/8LjbTd9lwkRhmnwd9xsG+N0Rl0ISY33jsFIxcRtBi52zoLJM2TKLH0h4s27cMX9hniIFO\n2vgbTviOs/aL5YRNZ8Ek4qyqapz2hfjfv1dSH/JSvFkka7pWU66cC6YIUzdPZfzb49Gik9ETuk9I\nEoCe/t50Rl06yki4dGmGePyk/U+MY+jvqwvWJQupRtsIX4b45LKxOOpx33EjIGWQQQY/AKiqmPb/\n5SoRTy8vEs8f3gLZ56GufwyfJKGC8VOq3o+80RP12u2McuGgpPhTvLkYf0RUz3w3PIF6eRHShytw\nLbwSaVYBLouToL+e41WnRPIZlfFSLxtOTbfbGB+NuRM2TKLWdwLZ6uZQ3aH0LVUEYaKm+22M3zjJ\naAvX/LiIpYf/JtqluzzU9PoVqjM/psEXN06kTquiptevGL9hIgfrDibFwWnvTqMuVMevCtvQukW+\n0ILtUJjgNaxvO3nz5AQrzIrK1/BbHaj9H8QnmWhQG6gJ1jJ+w0R6vNCTCRsfoKhzUYJIs6fQg6yZ\n0rfaQ/WoNz+Fb8ph1NtX4zdbqdhfkTJ2f1MxW9XUvJpAzfnj3x5viwpk22oCNeermpp3rvvcvHmz\n85VXXsn74IMPPlqzZs2ne/fuTWgz+f1+0/33399h9erVn27fvv2Tqqoqa/zrn376qWPjxo37t2/f\n/vETTzzRJhgMmv7whz8cOe+884L79u37aPHixUe+6rmcPXtWuu666zr//Oc/r3nwwQerd+3a5aio\nqMjbsWPHvn379n0kSZL29NNPfyXv4a+LJl35M5lMLkDSNK0++v/rgBnnvENVFaXy/pOFNl+8Vl/R\nEvG8TuBo3zdaBXxYlNZvXx1LGhuLPw9fAEd3iBmMV4bDLUvAZEJ1uJn27jSjyhbvzgExwefG7VB/\nuIFl2z7n5p7ZZNldBoGisUSC3uqd9u40SvqW0MbdJuUKz2VxJbSNx3UdR2VdZQJbrrE9XFt326/k\nu9uYSeYwO9KKo9YGapk3cN5/beUvg/8cuvy5y9fa/oPbP/jXG2Xw9RAvnB8XC9V2vVEu/imyyYT3\nxj/w4kdLDb04T7+Z5F7/B2pVheK/T2X3yd3sGLMjjVWZkx5LeyTat324Ikq0209Wi4tp9sow1F++\nij9K4vCH6qn45KXEFud7j1E+qNyYGUyQmSmci/zGZACRhMUxkfUkbErvKSzcs9BISucPelJ0aIJe\nUdGUzGB3o4R9RhLbMTvZfq1ALqC53DzW2nblYxr5EnIauRldRmtIxyEM7TSUCXGVQU+hh4oDFUnn\nWj7oSe7uMlYk1tv/F6n/Q8hvl+L5SSN5mf4eHJ9vo6blxRS/PT7hnlJZV2loAuqx+5uCElHaFm8q\nlhq1pKX518xv67K6zqn6984777ivv/76M1lZWSrAdddddyb+9T179jjatWsX7NKlSxDgF7/4xekl\nS5YY83zXXXfdGVmWNVmWI3l5eeEjR46ccx41bNiwCydOnHji17/+dQ3AX//616wPP/zQ2bVr10sB\nAoGAVFBQEPnyvZwbmnTyB7QEXjGZTCA+y4uapv31nPakB6odf4Yr74aXRye2KVbcJUSa33hIlMKH\nL4Ctz4pKns5kv287WKzwyq8T37vqfqFN5T0l9uFoBjWHkN0tvpI7xwU5FxgtXFUTcgU/65LHb98v\nFiLKLbsztsvYJCNvPXG89bVbaZfVLqXm1riu46gN1Ca1jU0mU4Jbh6e/hwlXTKBsVxld87vij/jZ\nOWYnZ0Nnef2z15mzfU4S40vVVOpD9dQF62jrbstp5TTZtuyU7Ydj3mNMf28686+Z3+RnRzLIIAOS\nhfMPbUb9x3Jqet2R4Mgx8pKRjP3xWCrPVFJR+RqjLxlJ8aapMeH6NL63lWcqE+zb5l9bgtziEpQ+\n45BtWSjBehyXDBXt1V2eL01gnFZnsvZgyIdLbRDCyJLFYNo2VirokN0BEEnY3V3uRra68FXvFy3g\nK34JrhYgmRO6Ko3F+Id0HMKEKyYwPi7R0sXv1RRxO94KM1XsL95czNTeUxMW8QfrDop58Rl5Md2/\ny0cg1R8Xlm8Doq32usPIDQ0oBRcbFUd9v/o9Rb923zTLV7bItjRFBtu/s99oznBOr9vtdmPUwWw2\nE4lEzllyqVevXt6//vWv2ePGjauRJAlN00z/8z//c3rhwoVH//W7/z006buspmmVmqZ1jf77kaZp\nj5/zzsI+Eag2PA72ZmKGT2/73rtFPHY0g5sXi5buWzOgTTeIhESiOLOF0AM028S28Ti8RTiFmEwJ\n2yqN/Bf1gBAP3dw73hMyEG7ggvw8dp/cbfhidsrpRIFcwMphK9kzZg8rh62kQC6gU3YnxnUdhz8c\nAGDJdUtYP2I9N3S8gV6tejHqklFJLZWKAxVYJAvPXvssy29cTr6cT/GmYiJqhEd7P8p1Ha7jN+/8\nhh5Le/DAhge4rsN1/HHAH5MYX8GGoGF+3vOFnpRsKcEX8THmsjFJHpblu8v/q+f9MsjgB4fGwvmA\nctkwg1xwbYdrGdppKJM2TKLn0p7M3jaboZ2GJklgpfL+1X2Bdew+uRtHVltqet1htHTHb5yEr/tI\nijc/ktSqHNtlrPFeER995Ml5jL5kJB2yO6CEvLhtbgIWK+qol+GxUygRf0qlgtpALY/0eoSJV0yk\ndFspUzdP5bTdCf0fwoeGGhGxN55h/OwHz1J6danxme7vdr/RBYofoznlP8XMLTOT2LVzC+fy1uG3\nDOu3VAlSh+wOKc61BlVvvYNgKo94DslbhbzpDyLxyzkfxSThaJa6u9Mpp9O3xvJVIkooZUs6ooTO\ndZ/XXHON9/XXX8/xer2m2tpaaf369Tnxr3fr1i1w5MgR2z//+U87wEsvvfQvW8zZ2dkNPp/va+dT\nv//974/l5eVFxowZ0x7gZz/72dk1a9bkHj161AJw8uRJ8/79+/+tRDcdmnrl7z8HmysWqEJe0bqN\nd/W4aRGEFZjTXsz0DZ4OOe2h5hC4C4yBYCruFFW+D/4vtm9dGmZF4ipYfv/pBLZvOneOsl1lXNvh\nWsZ2GUuuIxclrBCISIYtD8D0PtOZcMWEBJ29WVfN4mzoLCMvHsnZ0JlEDb4ogxdIYP9uO76NAecN\nYFJcC0EnZLRxt0GJKOTZ8xJs4SZvnsyCaxYYs4W6Xp+qqQltbX2uZf418ykfVI5slak8E/Ow7NWq\nV0YrKoMMfijQ7cbiFQ7idOrSdSvKBz1pVLqGdBzCxCsm0szejCXXLSHYEKRBbcBpdRoJ3NqDa6MS\nWd4E1mq+nI85uojVVQXWHlybkMCM6zqOos5FTHjnN8lkirhWdN5rE5HzOzOq7z0JIvV6O3XewHlM\n2jCJfDmf+7vfn9g67u8hT3XgMDsML/SDZw5iN9sNpyOTyZQy0WrrbsvrB19HRTW8j5Xq/TgObWHM\npaO5+8d34w/Vp9XdS64IPsL8n5TAAGGHp4R9OG1ZKKNeIqI1sGzfMn7CTwy2tKe/hwc2PpC437Do\n+ighryEU/U1BtshHPf095xdvKpbirqcqW+RzroxdffXV/ptvvrnm8ssv/1Hbtm2DvXv39sa/7nQ6\ntfnz538+dOjQC/Py8iJXXnml9+OPP/7SDLdVq1YNPXr08Hbu3PlH11xzTd0DDzxQdfDgQXvLli1/\nrG8ze/bsL1K997nnnvvi1ltv7XDPPfe0e/rpp49Mmzbt6ODBgy9SVRWr1aqVl5cfvuiii8452U2H\nJu/w8XWR3uGjHpaNFIFqypHY/3V0KBSstC1PQbeRiazdEc+JxDD7PGH1ln+RENyMf93VIqUDiDqt\nCsVXhexuiTfsxWlxcqjuEB2zOxJoCDBzy0y65Hdh6AVDcdvcCR6UVslqJGlri9Yy9e9TEwJAr1a9\nKB9UTk2gJqVqvqfQg4aWkGzqQazxtqVXl2IxWRLaw3rFTkLioV4PpZSHefTvj3JnlzsNN5HnPnjO\nYIalkpT5KmzhbwHfe+cEIOPw8SXIuvSRr7V9E535+35/T+Nm/tSs1ijXTEXOOZ8qfxWqptLK1SrB\nJQhiThE1gRpDZSCkhpj27jQK5IKkBe6MfjNYU7mGER2uJy+rreGG9GUz0NVKNU9G5/L8oXompIh3\nU3pP4ZbVtxiPdYcR9be1ac+5x9IeLL9xeUqno/mDylEaAgnxbsl1S5i6eSp3drmTNu42KR1H4s/D\nYrKwc/QOpOeHo/58KYrFFpVq8RGJhJi0+eGEhf+XXd9n/vFMktj/7/v/nmBDMEmov+JARSwRLpxD\n3sH3kdr8WChZRJnF/wL/lsPHN8H2/W/DD9nh49+HyRyj5MdXAXUc3iKe7zNOaDzpiaG7QFjANSaH\n3LIEsgpEZVDV0jqASPUncNmzQAM3FvxhP6XbStl+Yjsrh62kQ3YHhnYaSl2wDrfVjc1sE7Mp+ysY\n2mmosRoEUq4cnVZnSgavGJiWEwLO9hPbcdtSu44UOAuS/Bz1+Q+CNCz6AAAgAElEQVS72Z4kD1O8\nqZjyQeUpq5GBSACHxUGeI89w/0ilX5hBBhk0YUgS2LJQb1lCjdWSJGty0ncydcXKe5K8ddMZPfQJ\naoJ1xsJ15bCVSZ0EvVIo7/oLysU/NfanJ36Nty3pW4JkkvjLx39h9MW34bRlfSmZQn+sO4wo1ftT\nnrM/7Kd7y+5p57Zlq5OlH7+QcD6nldNGfCyQC5IckvSuT8K1aQggj1pOTYM/gYjhKfSwaPAiGrQG\nZIvMMe8xTvhOpDzX+lA9g9sPTro++ohO49nBeQPncfeP70Y5ewR5+/+H9ONbReJ32Y2itf8NQzJJ\nNTq5I9MV+s8hc6fVYXGI5O7GctGiTeXq4asGe1ZiYtj/IdEePrQ51vpdcRfoCu7O5mB3CbX3mxYl\nOoDctAhQxcpJkpAsdpwNDXj6zaRXq14898FzjLl0DL5I4txcSA0x/ILhtHa15oZXbuBI/RGO1B9J\nOS9YH6rnqPdoytdSJYUHzxxMTfuPKGnnP9pltUubeDaeY5n27jTOhs5SExALN10c9IcgEppBBhk0\ngsWB4nCllDVp0BqSZvnmFs7F8c9VSB8sx2l1J6gKpEusnFYXvu6jkHPOp2xgGX8c8Me0ygbtstoh\nmSQO1R3CaW+W1jFDJ1Poj71hL+rlRYYwf2N3i1BDiFlXzUoba4/UH2FE5xGsvWWtMZOtoRnx8fWD\nr1O2q4ySviXCTePqubgsLqqV6jhplrnChs2kJV3PigMVeENeQyZs+nvTAfAUepJmJV1WV8prmU7B\nwW11c9e6u0Qb/9Q+Mcc44CF8ue1Ro7PkGTQ9ZO62OiQJLLJIALc8JQSZ4xO1Ec8BcRU8HSls2zi8\nRZBDZrYQ+n4hH1gdhtUO06pipJGsNmKfAGEFafkY8v72GPOvKKb06sfBRMoEqpm9Gcd9x/lb0d9o\nLjenjbtNyj/0NZ+tIduWnTQwPOuqWRzzHksKVG8efpO5jYLb3MK5SCaJcV3HJRBKxnUdhxJWUu7n\nyxLGFnKLr6QJmEEGGTR9yFZXyjjQ2tWa8t3lTO09lZ1jdjKl9xRWHFhB4IKBgLC/jE+m0hHi6kP1\nTNwwkR5LezBxw0S6F3Snyl+V1uJy2rvTmHDFBAJhf9S7Nzne6WQKPVa+uG8ZyuDHkHrcTp41K2Z5\nNqgclyaxfP9ybJJow84bOI/Xb36dPWP28PrNr+Mp9LD5yGZCaojp702n5wuC3JIv5ydcl7UH1zL8\n1eGgabh8p8jaupj5VxSzc/QO5l9RTN72PyGFla+sxTrt3WkEGgJGQqm3yI95j6W8lukS18q6SkGo\naX4hNdeWMH7bzBgBscF/Lnacqqqq3/nIwn8Lotc66ZeUSf7iIZnB1VxIvTRrLazaooLM2NzgzBfJ\nYdRnEcmS5E8JRHWmPkmsBAbqYzY/ug9k/QnUsILPbBY+upIJNau1IVbKyrHpW7YWmSyrsCEc//Z4\nDtUdouJABeXXlBveupJJYm/1Xlw2F81szYyAVdK3hLJdZZTvLk9aeRd1LmLdoXVM6T2FHWN2MG/g\nPINkUtS5yGCOzd42m6LORVgkC2sq16T01JRM0pcGkwyzN4MMfuAI+1G8J9PGgbUH11K6rZTPznzG\nLatvYfHexUaLVf5sQ8LC9bkPnkv2lC30sGzfsiQBaE3TUjKEn/ngGSMxUiNBan90I7ur9jBv4Dx2\njNnB1N5T2VO1h5GXjGTHmB2U9C0BEOeVcz4485GsjljHwuLEZnFQ1LmIigMVRNQIYTWc1KkZ1H5Q\n0iI+XbdGCdULA4FuIxM9jKsPQNQSrvH7OuYk6wbuPrmbNu42AJz0nWT6e9MZ0XkE2bZs3jr8VtL1\ncVldSQt/nVUtzsubJDZ9jov4D0+dOpWdSQC/eaiqajp16lQ28GHj1zIzf40R8gs5FncB/Gx2sl2b\n2SHmHa73iKqfUpPs/Tt8gajq6dArgcMXJMwGNty2jIAU+/7Xh+qJDJlDltYgTM4HFFMfXcE2ntvw\nhX3UhWLzMB2zO3Ko7hBKWGHC2xMShpxrA7WsOLCCwe0Hc0HOBQx/dXjCEPDU3lPplNOJyjOV5Dpy\nmbN9DhAbDlYiCiE1lEAoiYmGlifrY0U9NU0mU5J/pj50/U3rQ2WQQQbfA9icyGEfnn4zKX7vsYR5\ntvJd5dzX7T5GXjISt83NymEreevwWyh1h3F1+R+kS64na+tibN1GGbPBJ30nKRtYhtvmpj5UjyuN\nJVuBq4Apm6cwpfcULsi5IEFVQN/GKecyYd1dTOk9JSXJTddI3Tlmp+hypIlXAS1ixNdm9mZJc9S6\nwkHj5GzRnkUpfYzlrc/Q4MjB1+222OdsfiHeoX/AFQkiW+Sk9/mismGN7xPHvMcY/upwURAYWIYU\nVvjzgQoGtx9MK1crg/hypP4Ic7fPBWBK7yl0yumEN+Rl9tbZVCvVeK56PO18pGyRBblH+mq1pEgk\ncteJEyeWnDhx4nIyBahvGirwYSQSuavxC5nkrzF0e7d7NscESi8vErN92ecJVnDPO6DiDqHnN3g6\n7HlJiD3nXyRauJUbYybfEDXc9kaTRrGdGlbwag34gvUJQ76lV5diH76AhmtLkJu146zvJKVXlzI1\nqnavs2KdFidOd0z5vbKuknu73ZvSIWT+NfMNb96pvacmBIm1B9dSrVQzpfcUZm+bzZTeU4zT1hM0\nySRR4CxISxp54eMXGHXpKNxWN0pEwW11G/N78aSOI/VHWLB7gQgm37A+VAYZZPA9QDiA5GpB3spx\nzO8vRIT9gVpMVpnHr36c2kBtgqzU3MK5OCxOuOUZ1PoqlK63IWe1Rjl9AMWRzaPvPUq+nM+jVz7K\npA2TDJH7VIvjaqWaW1+7lVU3rTJIdPHb6GMp6WYJO2V3Mub1ijoX4cCc4vP5kaMJ6MI9C9kzZk/a\nBKnxeVYpVTgtTsoHluG0CQcQectTcGoftdfPoXjDxGRW80UjcKKRa8+lfFA5TqtT+Bif/DhBNkxP\nsF0WF9tHb8cf9uN8/2kofJDFexcb4s8X5FzASd9JLJKFaqWa3Sd3i/hc6CHXkcu0PtOwNISxmW0o\nDYHUBJ0zn+NytvgqrF8AevToUQUM+0obZ/CNIZN1N4auTaXP8ul2bW8UC2/fl0dDJACjlsPQeYLs\nseFxWNRHtHNf/gV06p88L6ipgh3V4mKo/RxFqaEuVGe0AnRf3hbOFoS1BpYeeoMeS3vw6LuPYjFZ\nmNFvBjtGizaEyyrs2E4ppxJEQ9MRLxxmBxUHKigbVEbH7I4pS/u6xmD8rMu8gfMAsJvtBpstHvq8\nzdguYzkTOJOSsauTOQCay80pLSxl/jXzvy+SLhlkkME3Ca0Bag4h1R8Xvrsz8jCF/Ix/ezyVdZVJ\nc2qTN08m4KtCXTmOGlMD47eWGD66EbMFT38P1Uq1oUqQSgDaU+jBefITygf8kZ1jdpLvyMNz9exG\n28zFbDKz6qZVmEwmVt20iiEdhxin3b1ld456jxrjK3lyHooWSZ5vszkTSCPp5hK9YW8yUSTqpOS0\nuaOx04m0ca6wkUshTD24/WCKNxVTrVTT84WeTHhnAjWBGuwWB/6WF+OyuSnpW8KO0TuY0nsKZbvK\nmLRxEofqDvHCxy/g7TMOTCY2/nwjs6+ejd1sZ+rmqTz67qPYJBsz+s1g55idlA0qo+JAhXGMei2C\narEjBb14+iW33eX9674V1m8G/1lkdP7ioaoisWsIiscvjxHt3TeKkzX/fr4UHNkptfuYViVm/vJF\noofdJVi/dUeEMHTIh2pzoWkaPV/oybUdrk3SpJpbOJd1h9YxZ/scerXqxdTeUyndVoqnvwerZGXZ\nvmWMvnQ0Z0NnjcphOq0/XSuqV6tePDnoSUINIXxhH22z2uINeXFb3Rz3HWfjFxvp3bo3nXI6EYwE\n8Uf8VOyv4CftfyLaAGEvL378oqH5lCSGGrUj+gFU9L7zWZSMzt+/h4zO37eDf/k91VRYeTdcM80Y\neVEfO0WPpT3YMXoHPaO6fDp0LTvl9AHG7/IkxbKF1yxAbQiD2WK0Vw27tZxOKMF6ZJubWl8Vxe/F\nOirzCn+PxWpHtjhRQl4cn22g9ryeCdvoregqpQpPfw8mTMm6d/095JmdSBa70HZFQ33/KWq63Ubx\n+yVptQjLd5fTKbsToy8dLap1vioiVjmh6ukp9JC3/X+h8EFDrzD+uujXa8foHXRb2g2A+7rdZ3R1\nnr322YTrqdvNdczuSE2gJkHPdUa/GXx8+mN6t+6N2+bmaP1RnBYnVrM1ZQtc13+dN3AeFhD2eaF6\n5E83IrW6XIxJpa/8feff0wySkSm96NAFSd9bIFq0W58VM3rp2Lz2bKHhl4rsUfs5PF0ohJ7NFpBs\nQiZm1f0iWVw2EiVOgiVe6T6iRciX81EiCiMvHcnaW9YKm7acTpQPKsdtdTNpwyQW7lmIbJUp31Vu\nkDOy7dlpB3ZBVAFdVhcPb3qYG165gW7Pd+Pql65m7PqxKBGFOdvncMvqW+i5tCcamqElWLqtVDDp\n3pnIiM4j2DFaEEH2VO1hcPvBxkqzYn/FuTC/Msgggx8o1HAA3zWPomafh++2F1CnnTQIC+mqZMrp\nAwlOICASmam9p2K3OEAy4zDbDXWD9YfWM3vbbGqVWuRoFa2icnVC5WzS5odBVZGCXlzLRhFocRHF\n7yWrKDzW9zHKBz1Jxf4KagI1KS3XFC0i4vmy22DNJKSut5F7dA/lg56ktLCUHFsz5l9TbsRFfdZw\n8d7FOC0y0u9yQdOMJCueqKL0uQfFl5qpfNx3PEmGJp7lG389dZHr0m2lHKw7aIwD6cdaU7mGbgXd\nDGu9ki0lYAK3NbXOa5YtS1zHDZPAJCEBLn8t0r7VkNchkZiSQZNAZuZPR9gPO/4Mve+C5b8Ulb7q\nfXD9EynFmQmehU/Xx4Sh4908bC6Ydkq8/60Zoj28fEwja7fFZPcZx6yrZtHS1dL4g0ulTK8Loq76\nbBVjLhtjzNB5Q146ZHfgltW38LeivwGw+rPVCcbkr332WpIJ978SNR3XdRwAYy4bkzS8XLy5mPnX\nzMdldXFp80uTFPQdZsc38uvJIIOvg/qP53zXp/BfD1VThRjxtpmx6la/mbgdecy6aharP1vNjH4z\nEq3Q+s3Efvwj/Nlt2TFmB5VnYpaTjS3Tch25sVjYqCsxo98Mg00MUCAXgGRGtcgoNzyBo/mFqWfz\nzA7Y/AdG9PoVuXJu6m1sbrC64HoPauUmghYZX8d+FMdZxHkK57D0oxdYuGeh8V49sXV1KMThKkiw\n1Xz2g2dZf2g9ss1N0CSlFHy2StYk4ed4lq/eAp/+3nTu7nK3UVDomJ3MBP5J+58kzYcLYf6YtV78\neZ8NnY19fotTFDEM29NApu3bBJGp/OmwytD1VtHK1St9H66ANx4SbN74Gb7hC2DrM3DhtdAQglue\njUnCWJ2w6wWYkWvIuaRyDJE2zsVmtmGVrCjhGHW/cRVQX5HazXZGXzoaJaIYQp4TN0ykqHMR93W7\nj2x7NtPenUZlXaXw2NXgTPAM13W4LqEKmG5276j3KBaThfu63UdR5yLGvz0eh9mRdng53jcyfi4l\no92XQQYZACgRJUmMuPi9x2jQIrisLq7veD2tXK2YN3CeIU+VJTfnTLtuTHjnN/RcKiSlbrzgxqRY\nU7ypmECDEBgONgSZ+M5EFu5ZmBCLdO/fIR2HMOGKCUbcHL/LQ22gxljk6tCTM2njXPIcuQQjQVbd\ntMrQNX2k1yOsumkVAL7TB2io/pSaHxdxSk3xOTc/wqhLRibPxzW/EHXUy9QGaindVmrIZk3oPsFg\nFNutzlhHR68e7iqnudwcm2RLEH72hX1GPF97cC3lu8sp6VtCp5wYiSVVhTWdNIwzhdzL3MK5vP7Z\n6wnXyJAxe/VeMdeZQZNDpvKnI+QTbdnrPYmVvg9XwC3PxNi81Z+Iat5Hq2DAQ7DtWbjkBvjzsFj1\n7+an4egOkfgNXwBnDqesHtr9dfgsFl74+AXmFs5l8ubJaZlnOY4cjtQfSbLfmbx5Mk8OehLZIlMg\nF6Q0Fd8xegfesNcgiiy5bglH6o+waM8iqpQq5g2ch9lkZueYnfjDfia8MyGhjdB4FajvK52rRwYZ\nZJBBeltJFyh1WBoakDBhMVmo8lfRQm4h5owPrEiIcS5b6ljjMDsYu34snv4eUdlr9HqnnE5YTBbu\n73Z/ki1c8eZHKBs4j20ntsVVHWchqSoN0da0Hsse/fujdMjuQFHnooS5OU/hHCoOrGBsl7EUyAWs\nHLYywcPcbcti/sAyoxUtmx1I/mp8YVENbazK8OSgJ5GVepTgF1QpVYanL4i5O3+onlxHDuUD/ojT\nloVSdxhHOIin3yxjdrFaqcZpceKP+I3YHV8R1M/dm0Yaxh/2k2fNMpjEvrCP94+9zxM7nhAJbN8S\n5HUlsQut255m0OSQSf506BIvm54Q7h6v/jqWzAW98MbDyaSPwFnoNgqWjUxo6fLKPaIK2BABRxbU\nH4ebF8Mr42L7vGkRktVOnkVmzGVjsJvtlA0qI5CGTn+k/kha+x2n1ckx7zHu7XZvkl9j8aZinhz0\nJIfqDtFcbp6UGLqtbrxhL5M2icHjHWN2pGwjxA8lv/jxiwxuPzg17T+j3ZdBBhmAMduXFCOCZ3Et\nH4PLXYAyrJy6ONJaqpatbjnZeD+VdZVGjCvpW8LrB19PeN0b8rJj9A5MJlNq2zJbFvMHPYlsdaF4\nTxIx2/hz5f8xtNPQpHEWySQlt0k3P8LU3lM56T+Z0sM8GAngsrpBVzwIeqHiTuRfrkp5Pi6rC3b9\nBfnINjzXllD8fklCYupUVaTnb8J9eAvqgMnQ5x5MNjdyqJ6FV83G7swX85JvFEOLS/AUeijeXMz6\nQ+vplN3J0PRTIgpmk9koOMSTDGVNw/ziCNzR+5Tr50vp17af0HsN+5G3LEJqLGMW8n9lmZcMvj/I\ntH116BIvABab8PidViV+oiXbvRUtgb0vpWzpGquh5WNgVkt45deC+DHif2PtYTkX7FlIZ4/hioQI\nNgR58eMXqQvW4emfaNPm6e9h0Z5FaQekfSEfDrPjSz12O+Z0TNk6CavhhJZF5ZnKlG0EvS3jsglN\nq1QSC7OumpWRb8kggwwAUflrbDnp6VMiZuaiGqmqyZREqohv2UJqy8nGRLZ2We2SYubsrbPptrQb\nn535LK39pMuWhaQB9iwmbX6Ywe0HpxxnybZnp4ytHXM6ompqSgtOFS1R+NjmhMNb8Ifq0/r/KhcM\nRPpwBXnrS4S125idwtpt1wtI4SBc/3vUaSep6fUrxkct7cZvmIRPDcLKscIZClAuG0auI5fyQU+y\nc8xObu8wlGAkwF3r7uLqZVdz71v3YsJE6dWlRmzPs2Zh1gsZelu3cjNoKpqmoQH0fwjfb/agdrk1\nJmOW6fY0SWQqfzqsTvFFDvpi4s46OhQKXb/b/iJs3qr3w87nxYxgyJeaEBLyCfr7PZtjki/uAtA0\nUBvEzOCmuUYVUHa0M4RCh3QcIlTWszsRaAhQF6yjSqlKXYnr7xEJ3OZiygaWpV4hn6lMmAHRoa82\n48kmLqvLWDHqbQTJJPHMP54xJF+6t+xurMobq8GXFpZ+c7+jDDLIoMlAMknkOXJF69PqElWpI3uQ\nOmXDwKmw6n7k21enJqBFW7bdW3Zn2AXDDMvJC3Iu4Ej9kQS3Dj2R01uV/rAPs2SmSqkC0nQw4kXm\nJQnZ6vxSwedUIs16dbG1u3V654t4RAsMss2d0vlowe4Fws8dkD5cgdziEpQr70Zu3hmlzzjk3cuQ\n/joZ5b6tFMfJ4Gw/sZ3iLSXMH1CMDNQ0rhoWepCdORS/PSGJvDe191RaOFsAYLbYjEKGenkRys9K\nkV0F1PurUCJB457QvWV3PNfrkjeOr+zskcH3C5nfmg5JAmcLQVtPVcnTGuClX0R9efsIYedV94NJ\nEoyn+KrgTYuEXmC8OPRrEyDsE63fl0eLxPGy4cbQbLxf49qDa7ll9S2MXT+W497jlO0qY27hXKqV\nahbsXmBU4kqvLsVhdvDwpofZfmI7/6j6R9oVst46iYc+49G9ZXeDZTzt3WmsO7SOsoFlhtflmso1\nDO00lDcPv8kx7zGj4qdLLJz0nSTcEKZDdocM4SODDDIwIElmXFY3UljBlX8R0gUDYetiI84qdWn8\nbcNKrNtgcfHWF29x62u38sw/nkG2yAmkB09/DxE1woR3JtBjaQ8mvPMbQpEQpVeXGnFqTeUaygaW\niX32fow8zKLiB6Cq/1J+pspflRRbPf09bDu+jfo0lTwl7E+8GNECQ6DuCzRNSxBkLt8t9AWVusMg\nWVAHPUpNrzsYv/EBIXK9YRI1P74F9Wdzk2RwIJpsNu8sBKIb++9uLka2ONNWLn1hH7JmEqzd9n1R\nLy+i5toSxr87lR5LezD171MJqSHy5fxEyRuTlkn8mjAyIs+NEfQK/abGlb/bV6cXdPbXCNu33PNF\nhU/OFdIxr4xL3s/1HsECjv+/ZEGZeoTaQG3C3Iguorxwz0Ie6fUIQy8Yitvm5uCZg7x5+E1GXjIS\ns8mMbJWpPFOJy+rin9X/pE+bPjitTirPCAmBtQfXJoiBJsgl2HOpDdbiD/sTyCRDOg7h/m730y6r\nHZVnKnnz8JsMu2AY5bvK6ZDdgVGXjMJlcxnH6JTdiV9c+gtjpqSx00cTw3cuSpoRef52cWjODd/1\nKZwLmsb3NB6aKuLo+J2w6n5UdwE1Q0opjrevvOpx8swOJHs2SBKq2iCsz6LVQ8ep/QQuGGgQKSST\nxH1v3ZckTDx/UDmnAzW0dbflqPco2RYXWWE/UlYbEaezWolWbNCLGvRSY2qgovK1pJk/T38Pmqax\n7tA6IYKf3Ymj3qO0sLjxEaHiwMrk9xTOIdeRh1mKNddUTTVioy/sI9QQ4uFNDycLSFsd+MJ+xr8z\nIfkzDZwHSh3jt5YkvzZgHrI9ix5LeyQJRP995N8TZLv095QNKsMWDuH4v/8nOl9mG77AGcbHEVL0\nbXWzAH2fO8fs/Kox/jv/nmaQjEzy1xi62HO8dt/wBWBvBsoZkeBVfyKIIfmXCF1AR7bQ/bM3E6+d\n+hQuG5qcLHb5H6H5Z3VFHUA6w4zm0KEQdcRz1EsSdRHFCFZ5jjwCDQGjPTCu6zgjwTqtnCaiRnj0\n3UcTyvs5jhzqgnWompo0zJvryCUQCQiF+bgETRdmThU0do7ZCWAEWbvZjhJRmLllpjFgnUqb0NPf\n05Qt3L7zYJVJ/r5dZJK/c8NX+p6qqlgMRxMt3n9aaKAOni4SwJufQlEjyNntRWt4owfJWwUjXxJE\ngnQL8pEvgdWJakoTu6JOIXL+RSJ5bIggvTwmUZPV2QLQUJUagtF9OcwOlLDP8Nt1WGRqg2cS2rSe\nPiXkvTkTbn4KJezDbnXhj/hxWV3G4nxE5xHkyXlGjK0J1CTuI+qIpMdUWTMhWRyo0d9qus+E9xQ1\nFnOCj6+nv4e8N6agDH4sZWK4sM8MfJKU4Ggyt3AuLosTh8UhrtNHq5H6/BrV5kp57HhnkV6tehl6\nr18B3/n3NINkZGb+UsHmFqQMm0sweis3QfveonVrBI4/iVbw8l8mBpOP1kDP20UlMH4WUPcIXjYy\ntn3REhj4KHQbifTXKWS1uARL33sxmUw0l5sjW2ScVqchZKq3VO9adxdTek9h9rbZKWc4SreVMm/A\nPOYNnEeWLQt/2I9skTFLZtw2wcqK/6OVTJKhF5VK1sVtdRvbq5pKg9ZgzNNAojahcS6bir9OcMgg\ngwx+iEi1mC5aImam354FN5YjNWuLK7pQNqKFZIkJB0eJEgk4vEVos/pPoYT9KWOXcvoArqr9kNUa\nlz0L6g+JuWudzFBxJ4xajhoJUqOGKH4nXsZlLk6lAZckwfM3kXfzU8zv/VgsQV1fIhLUkB+XpuIL\n+5jYyBZt24ltRgyM1zyEuBg5sAzphf/BFXcPUexuTiun03+m/IvIC/kEU9kivIVlVUMa4kEGPP1m\nUvzeYwmfxb79T9irDzD/useR3S1RIgqRhjD3vzM+tl3fEvKihYFUx9a1YJNmJjNokmjyyZ/JZPoZ\n8CRgBpZomnbu0v6pAtXNi+GCAWLeL17OJVgvksH45yruhJ//RVQBd/xZVAyjfpYMmiYEMeO3X3GX\n8Ah+42HwVsENfwBT4iJJMklG4qf/LJAL0g4md8zuKGx4Nk6ipG8JYTVMrj2XQEMABw5Dv6px5U8y\nSUlDyJ5CDy6LK6F6p0QUXvz4xYQB6nRkkkxwyKCpoMufu3yt7ZuoF/C3j7A/kUCnx72Ry8Rjkzmt\nDirBerBliX2keF2NBIT8SHZ7ygbO48V9y2I+44UeZEcOOHJF7I7v4oDQb43OcivBM0m6e8WbJzO/\nTwmurLZwaDPSx6/j+tFN8Pxw5KzWKIMfQ845Pyp/8jRy4YNfGgO/VPOw0T1Evn01i/YsSklSsfvO\niBk9m0vMkG9fguuLrfCzuSCZkF4eTZ67gPk/KUHObic6NhqiwJDVBlf1J7BzKfT7NZM2PpBMGhlU\njmx1Jt8L+ntwmh2imlp3GNnsbKpdnQyiaNLJn8lkMgMLgWuBI8B2k8m0WtO0j85ph5EAqFpi1c/u\nBkyJIs+bnhDt31SrUUeWGGi+bChknwe3Pg+OZoIYknL7bLj5adRISFghvT0+5Uxe/B/irKtmGT6P\nqbSvICZ/EGwIYjKZjHkTp9VJfaiebce30b1l94T9F8gFlPQtoV1Wu7Rze7JFZvHexVTWVRqM5HSC\nocGGIKqmJiSvmYCRQQb/RUhbtXPC88NRb1uG4sxDvn01SrAeee9LSB+/JqqDNjeEvGIfRc/BijvF\nnN7Aqai551MTrE20jiucy9gudxFoCCK/txCp9zhYcSequwDl1+8KQkTdYeRrfye06tr3BZvLYPrG\nY/fJ3cjN2kHIhzr9tEjybG6Co17CFzeKoyeazoagYUenz+VIXT4AACAASURBVFmLGBhAVRvAJKWv\n5DW6NkpEoUqponx3uRFjj3qPYjVZqXVmMznBRm4ued1+gaRXSQ9vgcuGo5hg/Lq7Es4xL+xHyr8Y\n+rRDTiPSL0dlW/IcebGOU/Asss2NVL0fNj2B66NVQrIsWC/ukyGfGGXKkD+aFJr6b6s38KmmaZWa\npoWAl4Dh57QnVYWGIKgh0Zqd2UKwcv214DslqnOzCgR7d/B08J+O6QLqaN9XMKa63hpj+S7/JdQd\nMZhUSdufPQ6+0ygmLdkiaFNxSosk3e6tsc5evPZV95bd8YV93PfWfUzdPJX6UL3Bhpu0YRLdCrqx\n++TuhP2/fvB1bnjlBu5adxdAykRNbwnojORuS7uxbN+yJD2veQPn4Qv7YpZKb4+nJlBjzBdmkEEG\n/wXQpbDiEa3qqf1+Q40aiOnVbZxETZdbUEctF23hWQXw0ijwVcPhrXDzU/DTx+G1CSj1R1NYqk0m\n4DuFq/ZzpHceB7sbNau1YK7u8gjW7LaZ1Nhk1EGPClWGM4dR6g6nZuuG6lHff4qaQI1xjqeic3uN\n2bTVSrVhRzeh+wTu63Yf8wp/jy/kY/w7v2HmlpnMumpWst3bR6uTro2saXj6zaRaqebW125l7Pqx\nSCaJ+nC9ITQd/5kV/ylxv6o5BO37pmX8KiaE69RLo1Cq96fVGqwJ1ADgMstI3lO4XhqNNKtl7N7X\nf7JI/PT75LKRomOmZmJ7U0JTT/7aAl/EPT4Sfe7rI+wXiZ7emtXnQoL1ok0R/9yq+8VqNJXEixoR\nrzfeviGc7BF80yJAhRV3pm0LONOsSpvLzWntak35oHJ2jtlJ2cAy1lSuYf2h9YbgciASYPuJ7dzZ\n5c4kEdLJmyfTu3XvtPtP17KVLXKSCPWIi0YYJuu6PINFsqRNZjPIIIP/EpjMab3RlQ59KE6VzKhh\nIaWlx88Vd0GLC0UsjraQ5WapBe1ld0vRmQGo3o9yzdTkRGhTMcqV4+DNEnhrhmhz9pvZKDGbi/z+\nYpTLhlG8+RHj/elcltq62yaIQo+++DYsIZ/x+V4/+Dplu8pigvkD5pF38D2kH9+aZB4gBbzk/e0x\n5l8zP0EKprUrjZ5gdntxrd6ZJTRj00nBWF2GAoW80YOnT0lS8WDBngWxOB32i2pr43vZlXdDSEl8\nvuJOsX0GTQZNuu1LahZREn3ZZDLdDdwN0L59+9R7sjlTt3LTtXetTnhropBryb845vl7yzOpt7e7\nwe6KE4qObn/zYqPUn85r8cts1Nw2N6qmUrq1lDu73MnYLmOprKukfFc5j0cFQ9PNB+pkkK9j0yaE\nW/MSSCh6O9clie1dVheqpmbmAL8mvtL3NIMMvmN8re+p1SEck1J4o8sDHkodI+xZifs4vEXEWP3/\nfIl1XETBpduPffRa+mPY3GLuD1EBybv2d4kxzWxH2jg3aZYvnd+5Pm6j799pywJbVsJ71x5cy/pD\n69k5ZicumxtW3CG0Xo17yH5w5QMm0ZYeUMzYODHnsV3Gfnnr+MMVYJJQbpyX/tpEr5/04QrygPnD\n5+MwO8Q9IyqcbTFZYnE65b0sS/xr/Lwt4/TRlNDUK39HgPPiHrcDjjXeSNO0ZzRN66lpWs8WLVqk\n3lPIL7SfGrcoUj3Xvq+Qfak/IXT6ZuSJn/UnxPOptq/9XEgWrJmUuH31J9FSPylt3VJV2hozrfQZ\nEb0Ne8vqW6hSqjjqPQqQ3hYu7PtK+28MKepVGf+zMeJFq+OPman8pcdX+p5mkMF3jK/1PQ35ofaw\nGJvR41503k6JKgzEQ3j/1ifuo31fESejsRJA9tckV+v6zURW6mNVtG63oUTnkZOOUXc49sSHK5Be\n+bVoF/8uF9fZk0i1goSinD6Q8P5nP3g2qX0766pZxriNsf/TB5LeG/t8Z2P3lQ9XxO4hbzwsrlXt\n5+IzbvTgKZxjHOutw28lC033m4m80RM7QP0JZMypbfWU+oR7k/ThCvBWMXb9WG5ZfUuSY0qC5Wn8\n76L2c+McE54PZSp/TQlNWufPZDJZgP3AYOAosB0YpWnaP9O9J60ulapCsE60Fl69N1HSpSEIr9wT\ne+6mRfDJWrh4SOK2wxfAsX8IWZgVdyVub8sSpI+X45hnNz0Fe5ZBj9vBlY9qMiWweuPZuKmeN049\nlYZUoQeTycTDmx6mQC5IMh7Xdf8skuVf7v9ckE7Xqolo/33nulTfB52/pqzb93WRdekjX2v77wnb\n9/v/PU0bV59DtTipUQOJenWFc4XAc2NJrJ3Pw+n9Yubs1XshqxXqT2ejhL1CfqXuMLI9BykSBHcL\nkZzYs1D/uZKay4YmSZ/kYUFaPiYxRr81QyzIb10qZLzCftS9L1HT/TaKt8Ts0uYNmIdFkoTodNhH\nJBJi0uY4seZ+M8lbVwL5nanpdUfy5zu4Ben8K4XN58q7E8/BniV6V9FzU4v+hHLhwEYC1wOQbVko\nIS9yJIT0f/8vSbtQRRUkFd1W76PVSL3GxswHoturI/5EjRZO0P8z4rRGsvqFfi9TI1BxR7JmYmrS\nx3f+Pc0gGU06+QMwmUzXA2UIqZf/1TTt8S/b/kuDlaoKxq/WIFhMQa/4GQkIZXr9Ocki2hnhgPgj\n0IVIbS7xxyVZoSEkng/5RNJncSTvR2dK2Vwgmf+t69A4gXOYHYTUkMG2DTYEaVAbot6XMd2/bxLf\nRFL5LeE7D1aZ5O/bRSb5Ozd8ZZHnVHE15EO1RWWnoomUbJGRIqHYtiG/0PMLK6KtGI7bT1gRCZQe\nZyWLiMd6XDWZwepADQdQUJGtTnEMk1W0vNRw3LaSOE7IJ+K3TkzTGlCtTpRINJGKE2NGkkBtEJIz\nJqJxzo+sSUhWB4T8qFZH8ucL+aP3lWDc54yer8UBaOKx8bmsjc41GretDnEN9HtKY9at2hDbT9AL\nZhuYrYn7NplRLfbEzxcfp1VVSMrEXyeLPXruaY6bjO/8e5pBMpr6zB+apr0BvPEf2ZkkJc4tOJqJ\nnzZX8nP8/+ydeXhU5dn/P2f2LZCEJCxShIBLFYVIgoAGRNwCFlGsigXt+1OkFQmLGhYBw1KWkSIG\ntFVK31ooUQoKqOCGbBWQxQTRuiEgAgJJJgmZfTnn98fJTHIyk4hdXpA8n+vKNZmZM2fOOc8z89xz\nL9+bxNtGcyGMFu39xvZTf3//BtEQLNQJOFt1daHb+mHcqNDzf5tExyQQCJoZjX2vWlqgA+wm9Tsy\neoup3rJkdmhv6++n/vdpwxy0evd1JltMTiX2HuoBxL+24X5Ae4wNv8d0enQme93+jfW+W82OxOcX\nW1fqnUvD9224niQ6Vmj6Guj0ideZBvtu+vx0dfvVrGX1xyj+mgnOf34SbhiBQCAQCAQCwX8GYfwJ\nBAKBQCAQNCN+8mFfgUAg+Hep+fzHdYUU7eAEAsFPGeH5EwgEAoFAIGhGCM+fQCAQ/JcRnkKBQHA+\n8ZOXevmxSJJUBnz7A5ulAeX/B4dzPtOcr0G5oii3ncsDEPM0xoV+jv/O+f1U5imcP+N4vhwHNJ9j\nOefzVBBPszP+zgZJkvYqipJ9ro/jXCKuwflPcxijC/0cL/Tzi3K+nOf5chwgjkVwbhE5fwKBQCAQ\nCATNCGH8CQQCgUAgEDQjhPGXmJfO9QGcB4hrcP7THMboQj/HC/38opwv53m+HAeIYxGcQ0TOn0Ag\nEAgEAkEzQnj+BAKBQCAQCJoRwvgTCAQCgUAgaEYI408gEAgEAoGgGSGMP4FAIBAIBIJmhDD+BAKB\nQCAQCJoRwvgTCAQCgUAgaEYI408gEAgEAoGgGSGMP4FAIBAIBIJmhDD+BAKBQCAQCJoRwvgTCAQC\ngUAgaEYI408gEAgEAoGgGSGMP4FAIBAIBIJmhDD+BAKBQCAQCJoRwvgTCAQCgUAgaEYI408gEAgE\nAoGgGdHsjL/bbrtNAcSf+Gvq75wj5qn4O4u/c46Yp+LvLP4E5yHNzvgrLy8/14cgEPwgYp4KfgqI\neSoQ/DRpdsafQCAQCAQCQXNGGH8CgUAgEAgEzQhh/AkEAoFAIBA0I4TxJxAIBAKBQNCMEMbfv4Ms\nQ8ANSu2tLJ/dc//xw1BwB8LISu2t/N8rsPq/fC/B+Y8sK/iDYZRADYoiowRq/vNzvYnPkpiPAoFA\n8OMRxt+Pof4iFPSCtwyK74NZ6eqtt0zdRpabfi7ohUBN7WJWgyzLCRew6MIWkWXcQTeyIuMJeZAV\n7eJX4Qky8uW9XPrURka+vJcKT1CzCNZ/XcPX/7jT/+H3avL1P3Ac/6njvOCRI+A/o84f/xn1/o96\n/Y/7YdJwXCJypO5+2IMueAapeBjSrHSk4mEo3jLk+tvU3v5LhloTn6XG5mMk0sjnScwvgUAgAITx\nd/Y0XIRqTsLqh+DIdpDD6u3qhyDkVf8SPueBQDV4y6F4WO1iNgzJU8b/bj8Ut4BVeIL8+R+HOFFT\nRv7mfHos78GYD8bg8rtiC5c/HMETCLPi4Wt5Kz+X9CQz+cUleEOqQSArMi6/izEfjNG83huMX3x/\naHH0hiLkF5ew81AFYVkhPcmIN+QBSdFsH5EjMWPVHXQTkSONHkf0NT/0vKAWOQKeMnjlfnX+vHK/\nev9sDcB681h+bRQebxmyRJPGOECFr4Ip26ew/J/LNeM0dnM+ZxQfsiMjNteVfS/j8lfGjWWNP8TI\nl/cy4dUSKjxn1HkT9KhzsRGDUA778YS8yA+sw/PbD9X3qf2cNZyPOw9VUPzRt1R4ExiEsphfAoFA\nEEUYf2dLyKM16FIuhqM7tdsc3QkmG4rJ1shzdvBWwtpHNYahtOYhHsttG2e85ReXcNtVqTy9azJ7\nTu4hrITZc3IPBdsK8IV9yLKCJxBm8msHuGzqRgrXf8YTt1zGbV1bgwKyouAJeSnYVhD3+jL3GY3X\n7myML5tJz54jLgAGd2vDkwPbM2PPE5rtw3IYl98VM1bzN+fjDrrxhrykWFKYfd1s3rjzDZbevBRv\nyEsgEgDAF/YlPE5f2PffG9OfIkEPrHlY+8NizcPq44lo6OWLBCHgQX5gLa683zFm96y68fO5kOUI\nBNzIckQzHwp3FvJY1mPcnnk7E7dP1I7Tjmn4+hUgdx2KZ/RH0PcJvGEvadY0bu54M5N7TibFkoKk\nD3Drlek8nndR3bzZPIbKgIsJr5bUGmqB2JyMyDKuiFc9xhXZjPnYievmQuSktmCyaeZjlFu7tmVs\ncanGIMwvLsEXTvw5EPNLIBA0R4Txl4i4sFhYNdzqG3TlX0KH3nX3uw6F0XtUOfOAW/scqPeDnkaN\nRsVojxlvrVuYsZn0FA6+ki7pqZScKtFsXnKqBKvBijcUofijoxQOvpIvZ+dROPhKPjtRRV7Xtoz8\nq+r5sBlsCV/fPjk5ZmTKsoK3ESOx/uLoDUbI6ZgKwGMDLk5olPrDfo1xkGZNwxP2kL85n6e2PwXA\n9B3TyV6RTeHOQjxBNYxoNVgbPU9BPcyOxD8szI74bROFTP1VcGA1vpoTFGyfpB2/7QX4In5wn05o\nLE3fMZ12jnZx45RhzUCXcjGuQU7GfOyMGYsF2QWMu2Ycc3fPJXt5NuO2jOX2rJa8deR1zX6n7ZjE\nozd2qDXUSvEGI0QiMt5EBtuuQnw3ToGgVzMfo3TJcMQZhHuOuLAZE38OxPwSCATNEWH8NSTRgump\ngDPfQ9+J8OhOmO4CcxLc+UfomAtX/RJuKoQ38tW8p11/hKF/Up/TGdTbO5aApIfKbxMahifKytl5\nqIKJaz7hqUE/p8ITpHD9Zxwsc5HVOkuzeVbrLNxBL1ajjiFZ7Slc/1nM83fNxam8svtozPPxTXni\n139T7lIXRZOeCk8QayNGotVgjXlibEY9RcOy6J3Zis5piY1Sm9FGhjWD1wa/RumIUqZcO4XPyj9j\ncs/JzMmdQ1hWDcL6Bsfh6sMcqzmW8DiFZ6YBjf2wCLiBBqH7sBd538vxXsJu92Bt0T7xeOst8EY+\nVqM94fO+sE8zTnmd8si/Jp8yb5nGUEuzpmHUG2ltb83knpO5uePNsfG+qcNNcfvtnKYacXuOuLCa\ndFR4g1gNVqb0nELpiFJeG/waeZ3y1GNMvhiMNs18NOgkeme2whMIxxmEOR1TqQl4xfwSCASCWoTx\n15BE+XprHgKDCXo8ABsKYHYGvP5bMLeEe1fAXS9BJAzRvKctv4N9f4X7VsK0MrhrKegtYLSAvRXc\n/b8awzA4ZCnOD74D1MWvlcMcC10t2fQtM3rNJadNDgbJQE6bHJx9nfgCerzBCBPXfKIJcY17pZRb\nu7aNnU6i18/oNZclm74lp2MqnkCY/OKSRo1Ed9CNP6zmk+l0Eq3sJpY+mI0/4ovbflS3UfjDfp7I\neUL19qzI5pUvXqF7Rnfm7p4b8wjlZ+WT1ykPUBf+Ti07saR0CbOvmx13nsIz0wCTDe5ZDmNK1B8h\nE76E+/4GZgdy0KsN3W/Ox5V1H3LXoXWvP7oTkjvgc59KbAwFa8CRga/q24TPe0Ne5ufOZ3T30bw+\n+HXm5c4jLIc1HsG8TnmMu2Yc47eMJ3t5NnN3z42NecmpEjold4rbb01t2DqnYyreYIRXdh+l0u9i\nzu45ZK+o28eobqPwhLxEFDUHNdVu5KUHevDV7/JY+kA2Ogme+eXVGoPwmV9ezev7Tif8HIn5JRAI\nmiOGc30A5x2N5esZLGqRxpHt6mOODPDX5u8d3al6BQctVA298i9h+0IwOWDrAtVoXPOwul2H3ihD\nl8H9q8BooeZMNVM3HGL9/pNA7eIXiMRCV9HHJw1w0iU9le8qq3irpIobLteR5mjJHx64ghZmB2cC\nbhwmO4fKK8lMs8cOff3+k3TJSGLRDUU4TDa+q6zi9xuPUFYT4rlh3WN5U0s2fYvzDicF2wsoOVVC\nVussZvaZycovVjLiihFEp4pOJ+EwG5AVHc6+Tgq2qduP6jaKoZcMpdxXTuHOQvac3APAgA4DYmFg\nIBY+nNxzMhsPbySrdRaHqg+x8fBGdOhYfONirAYrvrAvtjB7Qh7NYzqpGf9mCQeBekUKRgvsehG2\nzcc3Zi8Fu2dprnXBzkIW9yvACvj6FWBtdQm+kAeLzoCzzywKdkyLjbezdyHWj16CAdOxlB9kUf9F\n2I12Dlcd5v2j73P3pXdjN9ox6ozcfcndmrkyP3c+o7qN4vnS58nPymfqh1MTjnm5rxx30ENOm5zY\na2f0mkuSyc43cwbiDoSxmw3cdlUqE7cXxO3juf7P4fGHsSdBhecMz757hFNnghQNy8Ju1vPQX/aR\nnmRWUyYyHPiCEaauPcDa0hN8fLQNkwY46ZyWij8i5pJAIGi+COOvIUGvGkaLGnldh0L/qdqcv65D\nYeACWPWAul3XodDtHnh1eMzAY8gLEPapj0cT9CFW4HEs78+0SbNQFTZTVhPCoJPI6ZjK/KFXo5NU\nI3DnoQpANeDKakIsvKcbv3/nME8ObM9bR1Zxu/F2pu+YrjHWPvj+TVIdd3NwTh7fnPbwzqffM6xn\nB6a//jmyAqP7d+H392Rx8LSbVnYTvpBMTsdU1u8/ybP3dmdKzyl0atmJQ9WHKCop4r0j7/HI1Y/E\nXSadpCPVkhoz1rwhL/mb81l681JNuDCzZWbC8GFmy0xy2uQws89MikqKADjtOx3bt91ojxWhRA3M\nrNZZOPs6SbWkNu9FO+iBN/Lr5todS6D8C6wtOyQO5aZdiuuWQgp2FmquY8qnb7G430KspiR8FV9j\nfbcQ3adrkIHKnP+hYPO4uu1znaSYk9GH/HgUmYIGhtnE7RN59oZn2X1yd8K8wJJTJWQmZzIv18mO\nr2qYlKUaYd+Uu3h9r4vB3RzctHArOR1T+eOIHo2mFdiNdsZufrjOcMybyzMbjpFfXMKyB7NjRt/B\n027Gv1rK6P5dOHUmwOBu7Rjdvwud0xyUuwPYTCYwSLgDYWxGPTqd9F8dMoFAIDifaMYraCMYbXD3\nsrhcPs4ch9F7YHoF3DoHLC3rjMG+T8C6x7Sh4rWPgq8Kkjsk9CRelJ6GJxBhbckxTcHGP09UYpK9\nrBzZkz1P9uLO7m1joSuDTuLJvEye3jWZAR0GMH3H9LiE/AEdBlCwvQBvyMs7n37Pfdd2IMls4NSZ\nAOv3n+DWRdvoPGUDhes/wxeSNXlTLq8Xk96kOdRoqC+RFEfUSNNJulhC/aHqQ5pwYcP70X36I34W\n9V/Em4fe5L0j7yUMw4kK4AQokbhqcdY9Bn2fwB/2sW7IOk2OnDp+HgpqvbGa4pxLb8ZqcqiGX6tL\nYhW7visGU9Cwond7Af6QF4rvw6q3JDTMHCYHhb0L4/ICoTakHPKRZknhli5JvPOJi8umvs3Taw9y\nd4+fsfC9r2KpCy9/eBhPKHGO3rGaY5rjenrXZB4bcDGtW5jxBMOa/NcnbrmMQ2U1/GH4NRTcdhmF\n6z/j8VWlhCIyj/x137+kVSkQCAQXAsLz1xCdDmzpMOwVQFFDvY4MNWcvHIKQT/XkDXTWeQjTLksc\nKk5qA64jWk8iQIfeRAJuXt5xkiFZ7Zm45hP2HHEx9sYujL62JbpX74ejO0nv0JuFdy/j+1AS897+\nkrKaAH8b2TPmOWvMuzKl5xQcJhsjb/gZ4UgYk9HES7/uyj++rGZM8X5yOqZSNCwr5vFoZTex7NfZ\neCNVFH5Y5x2afd1s7AY7f95+gqJNB2Ova2U3xXlKogv+0gNLmdlnZswjuenoJubnzmfi9okar1PU\nyBtxxQgeufqRhCHd+hXAeZ3yGHnVSDKTM/GFfETkCP6Iv/mF7hpWnQMc3YmcdineQBWFO7XjZ9KZ\nYsU8k3ImMajzIFqYWlATrMFstOPyV1HwsbNubG4uJLWxYhCjHY5sxxesIat1VszzB7UGfdhPq1qv\n7OzrZjP1w6maY9EHPejmXQwdejN66DJG33gb3mCEqWs/Zf3+E7F9FX1wkEdv7IwzV5uG4OzrZMGe\nBXHH1TktlXE3WcmvzZMd3K0Njw24mHYpZlKSWmA3Gqj2u0lPMvLbG7rw5N8/iXnVo1IwSx/MxmHW\nfh3KihyblyLlQCAQXEiIb7JE6HSqdEZ0ob15hhrCfSNf9Qwe3QnbFqjhto65UP1d4grM6u9gy5w6\nT2K08nfIC+j1Boo+OMiCd7+Mef5+06cNujXaYhNp9UPIQTfr959gzxFXzMhqzKPmDrqZs3sOU7ZP\nodJfydgt+TEx3uzOZr6YdSvLHszGatSDBO5AGABFCsR52aZ+OBVfUGHhe183KeoMqqHm7Ouk3FfO\nkpIlFPYuZN+IfQzpMoT3jrwXu/9c/+dIMaegk3Qaz2H0tj7Rc83rlEd+Vn5MMiR/cz7fe76PCQ43\nK6HeoCfhXPMF3QnHL6yE8YV9OPs6uaXjLUzYMoEey3swfst4Kv2VlJwuYc/JPXV6fC0uwhvyMKrb\nKM1bZLXOwlfxNQBWkwNn70Jt8UTvQqx6C3aDDbPejN1gp7B3IXuH76WwdyF2nRnz25Nj81q35iEq\nKitRgFNnApr3yumYij+oYDMk83TOAvYO38ekLCeBoDGWGlD/uI5VVdGhlY09R1wx/ckPvl/NSc/3\njK3Vm5yx5wmeHNiezhn2xFIwJr3mMSE6LhAILmSE8dcU0fw/S3JdqC2q7/fpGtg0U/UA2jPUHL8G\nBh7mFmonkEhQ3W7qafV200wwWmpz7epCsXpLYg23dulpgLooSooJZ66TTUc3MbPPTM0CPD93PsVf\nFLPn5B4euuqhWNJ9dGFPtabgi/gIRSIxHcCRL++l3BNoVGcv3dECgMJfXM60OzrEiTpHF8P6OYBz\ncufQytqKYCRIMBLk3svvJRAJMGn7JMZuHos/4j+ryx81KB/r/ljjIe7mFgY22uN/TAxdhtXcIuH4\nZdgysB78gF7tesWJM0/cPpGebXvGqnPrjOux3H3J3YzuPrrOuMudh/Wf6wHQlX9FaskrLL6mgH3D\n97K430JSHe3Q1Vbs6iQdDlMSfr8NkGhlbUXSxknoPl0DoIpBD1pAq9QUdPogSx+4RlOdW1RbiGQx\n6hmwYBedp2zkloUfMX/DwYQVu61sDvy1mn9R/clEaRFP75qsFpskkILxBrUdUkTKgUAguJARYd+m\nMNpQhi5DMtpg4DOQdqnqzbt7mSoH88914D4ND66vMwTTLlMNxE0zVQmYe5bD7qWq/AvUFZAAK0Zc\nyQsffs9zH6ghVSWq4dYgRPx9WTm9M1vxx+HXEI5AsiWV+y77FUkmG8/1L8JutFETrMFhdPDi/heB\nukKLqNesfmHI/Nz53HplOjsPVbDzUAVji0t56dddE4byjlVVMbhbG+7MTmf8lnHaStJtBSy+cTF2\no1pdHPXgAbGCjTvW3kFYCcf2aZAMZy2voZN0pJhTSLUkTv6PnmOzkuuon5Zgsqk/UIy2mJe04fj5\nqo9hXzUC+9OVifP0jA6mXjuVcQ3HdnsBRf2LeOSqkfjOHMeqSOh6PAiHt8H2hegGTMde+gp0uwf7\nusfU0HO/ifh6/UbNIwx7efuAi4XvfcQ/xudgr/keUA0/182FFOyqV3yS62TZr7OxGPX4a0XHkVBl\niG7swsL3VY9jtHI9Oue/q6xi9rpotW93iu7rTqrD1GRaRJLJzjO/vJon/66mWtRPgaiPEB0XCAQX\nMuet8SdJ0p+B24HTiqJ0TfD8DcA64HDtQ68pijLzP3oQOh2KPQ085UgbnqxXyfsHuOtPkJShhuGC\nHtXD90K9cFzHXPVxnR56joQj29QcwAHTYe2jSEd3ou/Qm8eiuU8hGcmoQ7l7GdLqhzSyMG1srfjT\ng6l4gmHGFpfGFq35Q6/msxNn6N3ZiCcSoDpQHTMAomHhkVeNjHlAoK4yc9ENi/j4aBXr959UhXUN\ntoQ5VkbFweO3dsJhSiz629Ri2KhBEvahk3TIitxkPpWsyFQGKvHWJv833E/0HH1hX8zobA7IEvh0\nkirfopOwSnVeUk1ldK9CrO8VAuANnIm7hqO6jaLSHZsj4AAAIABJREFUX0mqtXHBbt2Z77G2uAhf\n0I3VnIRv2EqsRjs6dxly70fxecuwPrCOQM33eHQ6CraM08yfB3NyWf9pOfcMWYp57Uh8/Qoo2FUY\nZ2guvnExKLZa3cm6Of7cfd0BNQ8wp2Mqd13THiMmjlb4+FlqCo/fYkEnQardjDsQjhWKROdGXF5i\nxEeq3czSB7KxmVWtzETVvk3N3eY01wQCwYXJ+Rz2/Qtw2w9ss11RlO61f/9Zwy9K0IvUIA+Ptb9F\nMVrV9m8hLwQ8icO+/io1bzDkgTv/ALc/m7CvL0EPNpMeb0hGsaYRuXcl8tQyjuf9mSUfVVPhCaEo\nSlzP0olrPiEzPYkkixGr1IJ0WzrOvk5y2uSw7MAyZl83m8zkxB4Qu8nOk3mZgBr2OlXtx26ys/jG\nxewbsY/FNy4m1ZJKksXIz1KSOVx1+Ed3SIgaJPXDdLOvm03JyRJCkRAWg4VDVYcazd2Lht6WlC6J\nC3HP7DOTTUc3NTuh3sZy0YBY2H3fiH0s7jmN1PcKY6FW66FtzM+dr7mG9//8frWlW2PVuWEfcunf\ncLmPM2brePX9tozD5T1NxNoSl+yP9d0tk2QKdmjTDFIsKejNCr/KSsFrSOHMncuxpl3aZLvC/AZz\nfOwrpTzQp2OsGn7T56eoqdfPumD1JyjA46tK+c3yfQRDBmb3mZcwLSI6V2wmAw6LAZ0kxYo83IGw\npqI90dxtbnNNIBBcuJy3nj9FUbZJktTxXB+HZE5cXYklSfXsrX5IrQYe+Hv4RZHau7fyWzCYYe/L\ncMXtaleQgU5Iapd4XyY7lz61UfV0DOvOKx+djIW6AHYccrHi4Z7MGNKFzmk9+aZcFWXecOAUXTIc\nfOfyEgjLdLE5mLj2nzgHLyLV5iAQCeANJfZgHK46TGZypppjdV93IroaRm+Kr8jV6SQ8IS/vH31f\nU8UbDddZ9JZGr11DLcBjNcfYfHQzt3S8hXFbxpFhzeDR7o/yyNWPcNp7mkAkoFlco6G3aNh4cs/J\nZLbMxB/xY9FbGHHFiGZXgVk/Fw0ahN9lBbvJBkEPdkuympKgMyD3m4i/8w2kGu0U9X8Om9GOJ+TB\nXtvCrTpQzZzr5zDlH1NiYzvn+jnoQgFV9mVnA0/dh09R1L9IcxwXOS6KSzOIjq8tqT2mkBeJpJhn\nLpFHzWayJSzGSLIY6TxlAwBbnrghZiCCWq375N8/oXDwldy6aBtjVpay7NfZsbSIov5F2GrD4gm9\ny7JChSdIfnGJJgzcym7SzF1R7SsQCC4kfurfZL0lSdovSdJGSZKu/G+8gRQt+qhP34lIAbfq1Rv4\njPrYJ6+CrTaRPBJQDb9u96hVwUd31uUCNtLXN+bpKFbbsw3u1o53xvXlmzkDWfDLq6n0u5hXUkD2\nih7MKyngyYHtyR/QBbc/zKL3v6Jzhp2aoJtn783CoJdY8sFBfj71A55a8yXOXGec1+z9o+/jC/v4\nw/BriOBnyocTEya3R71xj1z9CBaDhaL+RewdsZcpPaew+uvVVAYqm6yArJ8HeMfaO+jZticTt08k\nzZrGY1mPUbizkB7LezDlH1M0FcSyIuMNedk7Yi+vDX4NgLvW38XI90YCoNfpE1YIX+g0zEXL65TH\nlJ5TsBqseLxlyK+NUuWJIkG4fxXy1NPUXDuKikAVAC5/JTWBM/zt87/xTdU3ZLXOYvPRzVj1Vk11\nrlVvxXRgNdZWlzQaEq7/eMM0g4bjO2ZzPt5IFVbJEOdRm9VnHpJibrQv73cub6wYpEMrG61bmGOf\njXfG9aV1CzNdMhyAaiyaDXq6F27jsqnvYGuimhyo9TaWaLyN+cUleEORH6xGT4Smt3KDiniBQCA4\nXzhvPX9nwcfAxYqiuCVJGgisBS5JtKEkSY8AjwB06NDhx72L0QZDl6n9faNt3Ho8AK/cr+2wsGkm\n/HwQoKiFIVfcrj726Ro1DFz+pWoIDnmhriVch954B7+E853vYm+354iLLhl2Zt15CQ6TjW/KK2hh\nMcR1VHh612QW3VDEa3uPkZlup8rvisvXG5p9PfM3HERSLCy6YRF2k9qq681DbzK482BQJJIsBlpI\niStFLXpLXIeN2dfNZt3BdfRs25ORV43kuPs4dqMdq8HapC5aNLQYTcRf9YtVcbmIUQ+W1WCNe9+Z\nfWaS2TKTuy+9+4INvZ3NPPWFPDHPWaJiHudNhaS+Vwj7XsbX+1EsQFAOavT/nH2dDP/5cNYdXMfM\nPjORFZnxW8drvHE5bXJY3HMaVHyd0FPXMA9z6YGlzLl+Dum29KbHt+c0Uj+Yw+Ibp2FNvphqnxeD\nASxGHb6wjyX3d+exlXU5f7+/pxstrUa+nJ3HwdNuKtwBnrj1Mk3BxjO/vJqT1Wr6QU7HVA6edsf+\n9wYjcfp99Ym2N6xPIumXs6G5dKT5t75PBQLBecFP9htJUZQziqK4a//fABglSUprZNuXFEXJVhQl\nOz09/ce9kU4H9jTVwzf1NPR8uK5dm6bDwpNqWHfDk2pF8IYCtRq4Y65aHbx9IbhPE9DbcQ1+GXlq\nGZH7iln2sTvWvxcgf0AXKv0uxm/Nj3n5MpISG2d2o413PjvFr69vFzMO63vuHBaYNjiTN0pPEYrI\nHK85TqeWnRjYaSB2gx2zwYxep2sy5yuRdtztnW9XZUFWZFO4sxBPyIM/7G9SFy2aQ1XmK9MYgQ3P\nKWo4Nnzf6TumM/znwy+4hbQ+ZzNPrQZbTGPvkaseiZMzKdhViO+mQlxZ9zFmcz6Hqw/HSbwUbCvA\n5XfR72f92PrdVtonNSLqnHwx1n+uj9f0q00JqO/By2yZiVVvxVNrnDY6vi07oDuwCvtz3WHbAnS6\nCJV+F4qiUOGrQKcPUDSsO1/9Lo+lD/SghcWA1aTnO5eXP2w5SDiixESao566J//+CbJCrBPOH7Yc\nrJWMia/ibYi3ViKmPomkX86G5iIP8299nwoEgvOCn+wqKklSG0mSpNr/e6KeS8V/5c1CPtWoe20k\nWJMT5+2lXwaBM2rV75dvwz1/hWllcO9yFHML5Dtf4ljen3nyzSNc49zF46tK0Unw2IAusTZuE26+\nhP/JjTfkjtUca8Q48/K3kdfiMNkSLrQOk4OQ4mPg1enosZJqaYUkSbQ0pWI3JeELyk0mtzcM7dXf\nb8MFLhCJF4muv/BF8/9amFow+7rZHHcfb7R9V2MyGzajrUnDrzmE3HQhL6nflbK438JGi3msLduz\n+vAGNUeykW0uSrqI6Tumc23ba5uYXz501/6GVMdFLO5fpCkE0uv0mgKT4T8fzvit43EH3U2Ob1Qo\nGiDQ/X48YQ+FOwtjPyR8EQ82s8yKnYep8oUYWduGbfJrB5gy6Oe0bmlJ6Km7KMXKSw/0INVuYuG9\n3Vn6YHbCTjQNqd/eMBpa/uPwa5B0gR89j4Q8jEAg+Klw3hp/kiQVAzuByyRJOiZJ0kOSJP1GkqTf\n1G5yN/CpJEn7gSLgPkVR/jsNOo02Va/vpsK6dm316dAbAm4wWuHe5XD5QFj1AMxKh1dHoPjP8PwH\nB7n+2T2s33+Swd3aMO+2tkjFw5BmpZP+xoP8/o5O3N87FZsxfgF5ofSFhFWzETnC8p2H+a6yKm6h\nHdVtFDXBGlrbW2Mz6zDoJP687TjHXH5e/vAEh8rV0JY75EFRGlSK3riYFHMK7pA74QJ+uOqw5jFV\nPy3pBxc+naRT8wY/LsKgi8/9mtlnJi+UvtCkJ7Ixmk1HBqMNXYee2F8Zjq/8q4TXKRAJMOzyYWQm\nZ1JT24qt4TbuoJsMawaZyZlYDVZmXzdba/znzse6fhy8cj86b7kmlB/NBdUpYPO70b08GFut4dPa\n1rrR8XVe9zusW52x45BtKTEh8vqeZSSFEVfZeX3fMW3lb3EpZ3yhhJ46tz+MzajHYqiVbzHp8UY1\nA+shy4qmshegld3E0gez+ep3eSz7dTYh6cy/NI/+lXkrEAgE54Lz1vhTFGWYoihtFUUxKorSXlGU\nZYqi/FFRlD/WPr9EUZQrFUXppihKL0VRdvzXDkanA71BzdXbPLuurVtU1uWOJbDrj+CrAkkfJ+ei\nW/MQv72uTcy7MO2WjpjXjtRsE4gE8Ya9SEisG7KOvE55sbc/7TuNRW+JJeRP7jmZRR8vYvzW8Qy5\nJoPNn1cxq8+82EI7uvtohl4ylAlbJsTaobnD1TyU24m1pce4M7tlrHhk3JZ8KmulQuont/sjflZ+\nvjJeLiPXyftH39dcnqzWWZwJnjmrhc8X9nHad5pb19yKc4+TyT0ns3fEXhbesJCikiJO+06jk3Q/\nWmajuYTcCHljaQfWrU6cvbQh2Wf7PYsn6GH8lvFkL8+m+IviOImX+bnz2f39bh7t/ii+sI9bVt/C\noo8XqWMxXC3mSbGkoDuwCo5sR973Mi5/ZbxBFPbHZJB8tbmBh6oPJRzfohueJdWUhK62ApmOuU16\nyqQ1D3HXVcma5/YcceEwG5g/9GqNp27+0Kv5y4eH8YVkavwhymsCKAqU1wSo8YdiBmC0snfky3Xd\nbSo8QQAcZlX6JVGbw7OdR0IeRiAQ/FSQ/lvOsvOV7OxsZe/evT/uRbIMEqonTw6rXTr6PqFW8Ia8\n8MbYusKOB9fXbRdFZ0CZVkbY50ZvcSBJINXbRu46FNcgZ1xhRdHHqjE0s89M2jrakr08O65bxt7h\n+zh42sMftnzN7LsuxWq0UhOsYcKWCfEJ/Dcu5nilj3klBQmfqy9eKysyPZb34OaONzPyqpFktszk\ncPVhOrXsRGWgMu5YNx/dTL+f9YsVH4zqNor7f34/DqNDU/yRKCm+/rlGE+SBRotHEhWWAPRY3iPu\n+uwbse9fyRFsOlb4f0Cj81SRNfNL7joUX78CrGmX4gt5QZIY88EYzfgu7LeQa9tdi92oFvy8f/R9\nbs+8nbb2tpzynop536LktMlh8TUF2J+/FgDP6I8Y87Ez8ZyZ2wHkcKxzx+ojG7g983Z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N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\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UqKhHUJO/+HjxUp9AHYD6HtR91IfP6Jd+jb/06wujrlxnXTkPUM9FxSWEOvOnQoUKFSpU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\nUgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ada4471470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "sns.pairplot(raw_data_df,hue=\"Type\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 4 columns):\n",
      "Miles        1000 non-null int64\n",
      "VideoGame    1000 non-null float64\n",
      "Icecream     1000 non-null float64\n",
      "Type         1000 non-null object\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 31.3+ KB\n"
     ]
    }
   ],
   "source": [
    "raw_data_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Miles</th>\n",
       "      <th>VideoGame</th>\n",
       "      <th>Icecream</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>33635.421000</td>\n",
       "      <td>6.559961</td>\n",
       "      <td>0.832073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>21957.006833</td>\n",
       "      <td>4.243618</td>\n",
       "      <td>0.497239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13796.000000</td>\n",
       "      <td>2.933963</td>\n",
       "      <td>0.408995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>31669.000000</td>\n",
       "      <td>6.595204</td>\n",
       "      <td>0.809420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>47716.250000</td>\n",
       "      <td>10.056500</td>\n",
       "      <td>1.272847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>91273.000000</td>\n",
       "      <td>20.919349</td>\n",
       "      <td>1.695517</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Miles    VideoGame     Icecream\n",
       "count   1000.000000  1000.000000  1000.000000\n",
       "mean   33635.421000     6.559961     0.832073\n",
       "std    21957.006833     4.243618     0.497239\n",
       "min        0.000000     0.000000     0.001156\n",
       "25%    13796.000000     2.933963     0.408995\n",
       "50%    31669.000000     6.595204     0.809420\n",
       "75%    47716.250000    10.056500     1.272847\n",
       "max    91273.000000    20.919349     1.695517"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Miles</th>\n",
       "      <th>VideoGame</th>\n",
       "      <th>Icecream</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.448325</td>\n",
       "      <td>0.398051</td>\n",
       "      <td>0.562334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.158733</td>\n",
       "      <td>0.341955</td>\n",
       "      <td>0.987244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.285429</td>\n",
       "      <td>0.068925</td>\n",
       "      <td>0.474496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.823201</td>\n",
       "      <td>0.628480</td>\n",
       "      <td>0.252489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.420102</td>\n",
       "      <td>0.079820</td>\n",
       "      <td>0.078578</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Miles  VideoGame  Icecream\n",
       "0  0.448325   0.398051  0.562334\n",
       "1  0.158733   0.341955  0.987244\n",
       "2  0.285429   0.068925  0.474496\n",
       "3  0.823201   0.628480  0.252489\n",
       "4  0.420102   0.079820  0.078578"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_data_df = raw_data_df[[\"Miles\",\"VideoGame\",\"Icecream\"]].apply(lambda x: (x - np.min(x)) / (np.max(x) - np.min(x)))\n",
    "# feature_data_df[\"Type\"] = raw_data_df[\"Type\"]\n",
    "feature_data_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Classfier\n",
    "1. calculate the distance between inX and the current point\n",
    "1. sort the distances in increasing order\n",
    "1. take k items with lowest distances to inX\n",
    "1. find the majority class among these items\n",
    "1. return the majority class as our prediction for the class of inX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'smallDoses'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# k-Nearest Neighbors algorithm\n",
    "def classfier(inX,features,labels,k):\n",
    "    features = features.apply(lambda x:x-inX,axis = 1)\n",
    "    features[\"distance\"] = (features**2).apply(lambda x:x.sum(),axis = 1) # Euclidian distance\n",
    "    features[\"labels\"] = labels\n",
    "    features.sort_values(\"distance\",inplace=True)\n",
    "    features = features.head(k)[[\"labels\"]].apply(pd.value_counts)\n",
    "    return features.index.values[0]\n",
    "\n",
    "classfier([0.1,0.1,0.1],feature_data_df[[\"Miles\",\"VideoGame\",\"Icecream\"]],raw_data_df[\"Type\"],100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EX1: Dating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def datingClassTest(raw_data_df):\n",
    "    hoRatio = 0.1\n",
    "    sep_index = -1*int(raw_data_df.shape[0] * hoRatio)\n",
    "    print(sep_index)\n",
    "    test_data_df = raw_data_df[sep_index:]\n",
    "    print(test_data_df.shape)\n",
    "    train_df = raw_data_df[:sep_index]\n",
    "    print(train_df.shape)\n",
    "    features = [\"Miles\",\"VideoGame\",\"Icecream\"]\n",
    "    label = \"Type\"\n",
    "    error_count = 0\n",
    "    for x in test_data_df.iterrows():\n",
    "        result = classfier(x[1].values[:-1],train_df[features],train_df[label],3)\n",
    "        print(\"[Predict] : \",result,\"\\t[Real] : \",x[1].values[-1])\n",
    "        if result != x[1].values[-1]:\n",
    "            error_count +=1\n",
    "    print(error_count/test_data_df.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-100\n",
      "(100, 4)\n",
      "(900, 4)\n",
      "[Predict] :  largeDoses \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  largeDoses \t[Real] :  smallDoses\n",
      "[Predict] :  smallDoses \t[Real] :  smallDoses\n",
      "[Predict] :  didntLike \t[Real] :  didntLike\n",
      "[Predict] :  largeDoses \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "[Predict] :  didntLike \t[Real] :  largeDoses\n",
      "0.22\n"
     ]
    }
   ],
   "source": [
    "datingClassTest(raw_data_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EX2: Hand writing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import pandas as pd\n",
    "import os.path\n",
    "lst = glob.glob(\"./Data/CH2/digits/trainingDigits/*.txt\")\n",
    "\n",
    "features = []\n",
    "labels = []\n",
    "for filepath in lst:\n",
    "    num = pd.read_csv(filepath,header=None).values\n",
    "    fpath,fname = os.path.split(filepath)\n",
    "    labels.append(int(fname.split(\"_\")[0]))\n",
    "    features.append([int(x) for x in \"\".join([x[0] for x in num])])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "hw_train_df = pd.DataFrame(features)\n",
    "hw_train_df[\"label\"] = labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lst = glob.glob(\"./Data/CH2/digits/testDigits/*.txt\")\n",
    "features = []\n",
    "labels = []\n",
    "for filepath in lst:\n",
    "    num = pd.read_csv(filepath,header=None).values\n",
    "    fpath,fname = os.path.split(filepath)\n",
    "    labels.append(int(fname.split(\"_\")[0]))\n",
    "    features.append([int(x) for x in \"\".join([x[0] for x in num])])\n",
    "hw_test_df = pd.DataFrame(features)\n",
    "hw_test_df[\"label\"] = labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
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      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
      "[Predict] :  0 \t[Real] :  0\n",
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      "[Predict] :  1 \t[Real] :  1\n",
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      "[Predict] :  1 \t[Real] :  1\n",
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    {
     "name": "stdout",
     "output_type": "stream",
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      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  7 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "[Predict] :  9 \t[Real] :  9\n",
      "10\n"
     ]
    }
   ],
   "source": [
    "# error_count = 0\n",
    "# features = [x for x in range(1024)]\n",
    "# label = \"label\"\n",
    "# for x in hw_test_df.iterrows():\n",
    "#     result = classfier(x[1].values[:-1],hw_train_df[features],hw_train_df[label],3)\n",
    "#     print(\"[Predict] : \",result,\"\\t[Real] : \",x[1].values[-1])\n",
    "#     if result != x[1].values[-1]:\n",
    "#         error_count +=1\n",
    "# print(error_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 946 entries, 0 to 945\n",
      "Columns: 1025 entries, 0 to label\n",
      "dtypes: int64(1025)\n",
      "memory usage: 7.4 MB\n"
     ]
    }
   ],
   "source": [
    "hw_test_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Sklearn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sklearn.neighbors.KNeighborsClassifier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EX1: Dating"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dataSet = pd.read_table(\"./Data/CH2/datingTestSet.txt\",names=[\"Miles\",\"VideoGame\",\"Icecream\",\"Type\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Miles</th>\n",
       "      <th>VideoGame</th>\n",
       "      <th>Icecream</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40920</td>\n",
       "      <td>8.326976</td>\n",
       "      <td>0.953952</td>\n",
       "      <td>largeDoses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14488</td>\n",
       "      <td>7.153469</td>\n",
       "      <td>1.673904</td>\n",
       "      <td>smallDoses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26052</td>\n",
       "      <td>1.441871</td>\n",
       "      <td>0.805124</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75136</td>\n",
       "      <td>13.147394</td>\n",
       "      <td>0.428964</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38344</td>\n",
       "      <td>1.669788</td>\n",
       "      <td>0.134296</td>\n",
       "      <td>didntLike</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Miles  VideoGame  Icecream        Type\n",
       "0  40920   8.326976  0.953952  largeDoses\n",
       "1  14488   7.153469  1.673904  smallDoses\n",
       "2  26052   1.441871  0.805124   didntLike\n",
       "3  75136  13.147394  0.428964   didntLike\n",
       "4  38344   1.669788  0.134296   didntLike"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataSet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 4 columns):\n",
      "Miles        1000 non-null int64\n",
      "VideoGame    1000 non-null float64\n",
      "Icecream     1000 non-null float64\n",
      "Type         1000 non-null object\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 31.3+ KB\n"
     ]
    }
   ],
   "source": [
    "dataSet.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Miles</th>\n",
       "      <th>VideoGame</th>\n",
       "      <th>Icecream</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>didntLike</th>\n",
       "      <td>342</td>\n",
       "      <td>342</td>\n",
       "      <td>342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>largeDoses</th>\n",
       "      <td>327</td>\n",
       "      <td>327</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smallDoses</th>\n",
       "      <td>331</td>\n",
       "      <td>331</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Miles  VideoGame  Icecream\n",
       "Type                                  \n",
       "didntLike     342        342       342\n",
       "largeDoses    327        327       327\n",
       "smallDoses    331        331       331"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataSet.groupby(\"Type\").count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以上:\n",
    "- 样本不是绝对均衡"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PUV1arZPfUPqdKgbB4tLF5NhzqBhWwaufv8qUK6ZQMayCS7MvxRP2pBgP9111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cyc2Weyzz5rr/IuL7JkOoAzH2qJHpl1IyRe/H7RBYRaul1+mNsu5kRCLeD+aYDHKeamLDSKbvOB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N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\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UqKhHUJO/+HjxUp9AHYD6HtR91IfP6Jd+jb/06wujrlxnXTkPUM9FxSWEOvOnQoUKFSpU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\nUgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1adb4773438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "sns.pairplot(dataSet,hue=\"Type\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import Normalizer,StandardScaler,MinMaxScaler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preprocess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = dataSet.values[:,:-1].astype(float)\n",
    "X = StandardScaler().fit_transform(X)\n",
    "y = dataSet.values[:,-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def testDatebyKNN(X,y):\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.1,random_state=124,stratify=y)\n",
    "    knn = KNeighborsClassifier(algorithm=\"ball_tree\",p=2)\n",
    "    knn.fit(X_train,y_train)\n",
    "    y_pred = knn.predict(X_test)\n",
    "    print(\"error rate : %1.2f%%\" % (100*sum(y_pred != y_test)/len(y_test)))\n",
    "    return y_pred, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error rate : 4.00%\n"
     ]
    }
   ],
   "source": [
    "y_pred, y_test = testDatebyKNN(X,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "结果说明\n",
    "- KNN是lazy learning，所以这里面训练集和测试集拆分也没什么好拆分的。\n",
    "- 算法具体实现提供三种方式:[1]\n",
    "    - ball-tree O(DlogN)\n",
    "    - kd-tree O(DlogN) -> O(DN) D < 20 有效 D > 20 退化\n",
    "    - brute froce O(DN²)\n",
    "* ball-Tree 我觉得可以认为是球坐标吧  \n",
    "* Kd-Tree是从BST(Binary search tree)发展而来，是一种高维索引树形数据结构，常用于大规模高维数据密集的查找比对的使用场景中，主要是最近邻查找(Nearest Neighbor)以及近似最近邻查找(Approximate Nearest Neighbor)。在计算机视觉(CV)中主要是图像检索和识别中的高维特征向量的查找和比对。 \n",
    "* 高效的暴力近邻搜索是非常有竞争力的。 然而，随着样本数N的增长，暴力方法很快变得不切实际了。\n",
    "\n",
    "\n",
    "错误率|描述\n",
    "-|:-|-\n",
    "20%|输入数据不做处理\n",
    "8%|StandardScaler,MinMaxScaler\n",
    "7%|stratify=y\n",
    "3%|random_state=2018,stratify=None\n",
    "2%|random_steat=124,stratify=None\n",
    "[1] kNN里面的两种优化的数据结构：kd-tree和ball-tree，在算法实现原理上有什么区别？ - kobe在流浪的回答 - 知乎\n",
    "https://www.zhihu.com/question/30957691/answer/338362344"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EX2: Hand Writing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# \"./Data/CH2/digits/testDigits/*.txt\"\n",
    "def loadImage(files):\n",
    "    lst = glob.glob(files)\n",
    "    samples = []\n",
    "    labels = []\n",
    "    for filepath in lst:\n",
    "        num = pd.read_csv(filepath,header=None).values\n",
    "        fpath,fname = os.path.split(filepath)\n",
    "        labels.append(int(fname.split(\"_\")[0]))\n",
    "        samples.append([int(x) for x in \"\".join([x[0] for x in num])])\n",
    "    return samples, labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import os.path\n",
    "\n",
    "X,y = loadImage(\"./Data/CH2/digits/trainingDigits/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test, y_train, y_test = train_test_split(X,y,test_size = 0.1,stratify=y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Tuning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='kd_tree', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=-1, n_neighbors=3, p=1,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier(algorithm=\"kd_tree\",n_neighbors=3,p=1,n_jobs=-1)\n",
    "knn.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error rate : 1.03%\n"
     ]
    }
   ],
   "source": [
    "y_pred = knn.predict(X_test)\n",
    "print(\"error rate : %1.2f%%\" % (100*sum(y_pred != y_test)/len(y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error rate : 1.37%\n"
     ]
    }
   ],
   "source": [
    "X_pred, y_label = loadImage(\"./Data/CH2/digits/testDigits/*.txt\")\n",
    "y_pred = knn.predict(X_pred)\n",
    "print(\"error rate : %1.2f%%\" % (100*sum(y_pred != y_label)/len(y_label)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以上:\n",
    "- n_neighbors调整有1个点左右的效果\n",
    "- 全量数据上fit，然后做预测。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error rate : 1.27%\n"
     ]
    }
   ],
   "source": [
    "knn.fit(X,y) \n",
    "X_pred, y_label = loadImage(\"./Data/CH2/digits/testDigits/*.txt\")\n",
    "y_pred = knn.predict(X_pred)\n",
    "print(\"error rate : %1.2f%%\" % (100*sum(y_pred != y_label)/len(y_label)))"
   ]
  }
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