AIproject - Learning Model (2).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CROSS VALIDATION, INCREASE DATA INPUTS, CHECK FOR RANDOM GRAPHS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing necessary modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy as sp\n",
    "import pandas as pd\n",
    "from sklearn import metrics\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from math import sqrt\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading in data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   |V|    |E|  max_deg  avg_deg  min_deg  chrom_num\n",
      "0  450   8169       94    36.31        1         15\n",
      "1  450  16680      139    74.13       18         15\n",
      "2  450  16750      138    74.44       18         15\n",
      "3  450   8260      128    36.71        2         25\n",
      "4  450   8263      111    36.72        2         25\n",
      "5  450  17343      179    77.08        7         25\n",
      "6  450  17425      157    77.44       11         25\n",
      "7  450   5714       42    25.40       13          5\n",
      "8  450   5734       42    25.48       12          5\n",
      "9  450   9803       66    43.57       27          5\n"
     ]
    }
   ],
   "source": [
    "# data = sp.genfromtxt(\"graphs.csv\", delimiter=',')\n",
    "data = pd.read_csv(\"graphs2 wodwm.csv\", header=None)\n",
    "data.columns = ['|V|', '|E|', 'max_deg', 'avg_deg', 'min_deg', 'chrom_num']\n",
    "print(data[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['|V|', '|E|', 'max_deg', 'avg_deg', 'min_deg', 'chrom_num'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = data[['|V|', '|E|', 'max_deg', 'avg_deg', 'min_deg']]\n",
    "y = data[['chrom_num']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    |V|    |E|  max_deg  avg_deg  min_deg\n",
      "0   450   8169       94    36.31        1\n",
      "1   450  16680      139    74.13       18\n",
      "2   450  16750      138    74.44       18\n",
      "3   450   8260      128    36.71        2\n",
      "4   450   8263      111    36.72        2\n",
      "5   450  17343      179    77.08        7\n",
      "6   450  17425      157    77.44       11\n",
      "7   450   5714       42    25.40       13\n",
      "8   450   5734       42    25.48       12\n",
      "9   450   9803       66    43.57       27\n",
      "10  450   9757       68    43.36       29\n",
      "11    4      6        3     3.00        3\n",
      "12    5     10        4     4.00        4\n",
      "13    4      4        3     2.00        1\n",
      "14    5      7        4     2.80        2\n"
     ]
    }
   ],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1c720e92a90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABDsAAAQwCAYAAADrdFXhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3X2wXOd9H/bvs3tfyHtBRwREeRiRMkSL7sRWZMACJLGxO45UW7SdRk4cTok0EWOrZtpKA3bSqpbr6dhN4kSqkthEx3EiRoqotAFjxUmkieUyil/qZkpbgAuElu3JCEZgkxbHJAHKJnHF+7L79I+7IO8F7gXuy+7d3bOfz8yZvfvss2efc87vefbs756XUmsNAAAAQFO0ht0AAAAAgH6S7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGmbhkx7333luTmEz9mPaEmDX1cdoz4tbUp2nPiFlTn6Y9I2ZNfZz2hJg19XHakolLdjz//PPDbgJsi5hlHIlbxo2YZdyIWcaNmGWvTVyyAwAAAGg2yQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDmBPdDrdvPjycrq15sWXl9PpdHc0n5WV9fNZWdl8Pt1uzUsvr6RbVx8XllbS7W75blUjZaP116912nT9Wk/dbs3C0sq6mNpNPHW7NS8t9ua1eON5bbf+jd6z0/6xk3b08/1cq58x/vLSypbn1aQxNtm4j3c63b72+710dV+7+vuzn98Z/erXG83n6rJOpzuwMWQcvle3sq4nZZzdzj7huJqEZUwGt5xTfZkLjKiDH/q5bb/nwoe/ZwAtmWydTjcXLy/locfO5tSFSzl6cH8evv9QDszPpN3ees51ZaWbSwvXzmf/3EymptbPp9utuXh5McdPvlr3o/e9JbfMTuWWm6bTapV+L+bAbLT+HnnvW7Ow1Nn1Om26fsVet7v65fvi4ko++OknX5nXiWOHcmB+dtvxtBqfSzl+8syaeR3OgfmZDee13fo3ek+SHfWPnbSjn+/nWv2M8YWllS2PK00aY5ON+/jxd74p7/1PD+alPvX7vXR1X/vfjx3KW79u/0C+M/rVrzeazz/4S9+SpU53XZw9fP+hPPaF38uJXzzX1zGkX31pkLayridlnN3OPuG4moRlTAa7nM1ZS8DIWlhe3Xl+4vzFrHRrnjh/MQ89djYLy51tzeerKxvP56sr185nYbmT4yfX1/3gp5/MCwvL2/7cYdto/a10a1/WadP1K/YWljt5YWE5H/z0k+vmdfzkztb5anyeuWpeZzad13br3+g9O+0fO2lHP9/PtfoZ49sZV5o0xiYb9/F3v/n2fKWP/X4vXd3X7vn61w7sO6Nf/Xqj+bywsHxNnD302Nm8+823930M6VdfGqStrOtJGWe3s084riZhGZPBLqcjO4CBm5+dyqkLl9aVnbpwKfOz2xuCtjOfuZn2hnXv3D+XMmb/2Nhoub/m5um+rNOm61fszc20c+f+uQ3nNTfT3na7NovPzea13fpbec9O+sdO2tHP93OtfsZ4svH2afoYm2zcx9/0un1JNu4rox6zV2+fQX5n9KtfbzSfzcbdK9tmp5+1kX71pUHayrqelHF2HLbXbk3CMiaDXU5HdgADd3lxJUcP7l9XdvTg/lxeXBnYfBaWOhvWferSQhaWxisjvtFy/9FXl/uyTpuuX7G3sNTJU5cWNpzXTuJps/jcbF7brX+j9+y0f+ykHf18P9fqZ4xvZ1xp0hibbNzHzz37Ul/7/V66evsM8jujX/16o/lstv7PPfvSrj5rI/3qS4O0lXU9KePsOGyv3ZqEZUwGu5ySHcDAzU238/D9h3LPXQcy1Sq5564Defj+Q5mb3t5/GW6e2ng+N09dO5+56XZOHFtf96P3vSW3zk1v+3OHbaP1N9UqfVmnTdev2JubbufWuel89L63rJvXiWM7W+er8Xn4qnkd3nRe261/o/fstH/spB39fD/X6meMb2dcadIYm2zcxx//4jN5TR/7/V66uq898TvPD+w7o1/9eqP53Do3fU2cPXz/oTz+xWf6Pob0qy8N0lbW9aSMs9vZJxxXk7CMyWCXs9TazKvzbubIkSP19OnTw24Ge2TAFyjdkwN1mxKznU43C8udzM9O5fLiSuam2zu64NfKSjdfXXl1PjdPtTe9eNHqBfc6mZttZ2Gxk1YruWmqPZYX6Npo/SXZ7jrdswUfpbjtV+x1uzUvr3TS7eaVmJqb2Xk8dbs1C8ur81hY6mRu+vrz2m79G71np/1jJ+3YxfsnMma3q58xvrTSyXK3bmleTRpjk437+M3TrSx2utvp9yMTs1f3tZvarXXfnzuNk6181nbHhevNJ8m6spunWvnqSnfXn7WRfvWlQdrKut7B9hjLfdrt7BOOq0lYxmRHy7mlmG3WCT/AyGq3W7mlt8Nwy03TO57P1FQrt0xtbT6tVsm+m1aHuSuP42qz9dePddp0/Yq9VqtkbubVONptTLVaJft656Pu28J5qdutf6P37LR/7KQd/Xw/1+pnjN80M5Wbes8naYxNNu/jc2t+7I7Tcm7U17b6/dmPz+rnfK4u29fbJv0eQ/rVlwZpK+t6UsbZ7ewTjqtJWMZkcMvZvLQQAAAAMNEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaZSSTHaWUdinlTCnlX/eev7GU8mullC+VUv5ZKWWmVz7be36u9/rBYbYbAAAAGL6RTHYkeSjJb695/pEkP1FrvTvJC0ne1yt/X5IXaq1vSvITvXoAAADABBu5ZEcp5Y4k35PkH/WelyTvTPLPe1UeTfK9vb/f03ue3uvv6tUHAAAAJtTIJTuS/GSS/ylJt/f8QJKv1FpXes+fTvL63t+vT/JUkvRe/8Ne/XVKKQ+WUk6XUk4/99xzg2w79IWYZRyJW8aNmGXciFnGjZhlmEYq2VFK+TNJnq21/vra4g2q1i289mpBrR+rtR6ptR657bbb+tBSGCwxyzgSt4wbMcu4EbOMGzHLME0NuwFX+VNJ/mwp5buT3JTka7J6pMdrSilTvaM37kjy5V79p5PcmeTpUspUkj+W5NLeNxsAAAAYFSN1ZEet9YdrrXfUWg8muT/JL9Za/6skv5TkL/SqPZDkM72/P9t7nt7rv1hrvebIDgAAAGByjFSy4zp+KMlfK6Wcy+o1OT7eK/94kgO98r+W5ENDah8AAAAwIkbtNJZX1Fp/Ockv9/4+n+RtG9R5Ocl9e9owAAAAYKSNy5EdAAAAAFsi2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKNIdgAAAACNItkBAAAANIpkBwAAANAokh0AAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKOMVLKjlHJTKeULpZR/X0r5zVLK/9orf2Mp5ddKKV8qpfyzUspMr3y29/xc7/WDw2w/AAAAMHwjlexIspjknbXWb05yKMm9pZR3JPlIkp+otd6d5IUk7+vVf1+SF2qtb0ryE716AAAAwAQbqWRHXfVS7+l0b6pJ3pnkn/fKH03yvb2/39N7nt7r7yqllD1qLgAAADCCRirZkSSllHYp5WySZ5N8PsnvJPlKrXWlV+XpJK/v/f36JE8lSe/1P0xyYG9bDAAAAIySkUt21Fo7tdZDSe5I8rYkf2Kjar3HjY7iqFcXlFIeLKWcLqWcfu655/rXWBgQMcs4EreMGzHLuBGzjBsxyzCNXLLjilrrV5L8cpJ3JHlNKWWq99IdSb7c+/vpJHcmSe/1P5bk0gbz+lit9Uit9chtt9026KbDrolZxpG4ZdyIWcaNmGXciFmGaaSSHaWU20opr+n9fXOS/zzJbyf5pSR/oVftgSSf6f392d7z9F7/xVrrNUd2AAAAAJNj6sZV9tTtSR4tpbSzmoj5mVrrvy6l/FaSx0opfzPJmSQf79X/eJJ/Uko5l9UjOu4fRqMBAACA0TFSyY5a65NJDm9Qfj6r1++4uvzlJPftQdMAAACAMTFSp7EAAAAA7JZkBwAAANAokh0AAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKNIdgAAAACNItkBAAAANIpkBwAAANAoU4OYaSnlvVuserbW+uQg2gAAAABMpoEkO5K8cYv1Lgzo8wEAAIAJNahkx9+qtS4PaN4AAAAAmxrUNTt+v5TySCnlnaWUMqDPAAAAALjGoJIdfyLJ6ST/S5KnSik/WUp5+4A+CwAAAOAVA0l21Fov1lr/Ya31Tyd5W5L/mOQnSym/U0r58UF8JgAAAECyB7eerbV+OcnHk/x0kheT/NeD/kwAAABgcg0s2VFKuamUcl8p5V8k+Z0k70ryw0n++HXec2cp5ZdKKb9dSvnNUspDvfL9pZTPl1K+1Hu8tVdeSiknSinnSilPllK+ZVDLAwAAAIyHgSQ7Sin/NMnvJfkvk/zTJF9Xa32g1vrztdbOdd66kuR/qLX+iSTvSPL+Uso3JvlQkl+otd6d5Bd6z5Pku5Lc3ZsezOrRIwAAAMAEG9StZx9P8reS/FHv+es2uSnLV2qtV+qk1vpMkmd6f79YSvntJK9P8p4k396r9miSX07yQ73yT9Vaa5JfLaW8ppRye28+AAAAwAQaVLLjryR5oPf3ZreerUk+meRTG71YSjmY5HCSX0vytVcSGLXWZ0opr+tVe32Sp9a87elemWQHAAAATKiBJDt6d2HZsVLKviQ/m+S/r7X+0SZHhSQbJ1LqBvN7MKunueQNb3jDbpoGe0LMMo7ELeNGzDJuxCzjRswyTAO/G8t2lVKms5ro+D9rrf+iV/wHpZTbe6/fnuTZXvnTSe5c8/Y7knz56nnWWj9Waz1Saz1y2223Da7x0CdilnEkbhk3YpZxI2YZN2KWYRqpZEdZPYTj40l+u9b699a89Nm8elrMA0k+s6b8vb27srwjyR+6XgcAAABMtkFds2On/lSSv5zkN0opZ3tl/3OSDyf5mVLK+7J6l5f7eq99Lsl3JzmXZCHJ9+9tcwEAAIBRM1LJjlrrv8vmFzR91wb1a5L3D7RRAAAAwFgZqdNYAAAAAHZLsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaJSpYTdgVB380M9t+z0XPvw9A2gJAAAAsB2O7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGiUkUp2lFI+UUp5tpTyxTVl+0spny+lfKn3eGuvvJRSTpRSzpVSniylfMvwWg4AAACMipFKdiT5ZJJ7ryr7UJJfqLXeneQXes+T5LuS3N2bHkzy03vURgAAAGCEjVSyo9b6K0kuXVX8niSP9v5+NMn3rin/VF31q0leU0q5fW9aCgAAAIyqkUp2bOJra63PJEnv8XW98tcneWpNvad7ZQAAAMAEG4dkx2bKBmV1w4qlPFhKOV1KOf3cc88NuFmwe2KWcSRuGTdilnEjZhk3YpZhGodkxx9cOT2l9/hsr/zpJHeuqXdHki9vNINa68dqrUdqrUduu+22gTYW+kHMMo7ELeNGzDJuxCzjRswyTOOQ7Phskgd6fz+Q5DNryt/buyvLO5L84ZXTXQAAAIDJNTXsBqxVSjmZ5NuTvLaU8nSSH03y4SQ/U0p5X5LfS3Jfr/rnknx3knNJFpJ8/543GAAAABg5I5XsqLUe2+Sld21QtyZ5/2BbBAAAAIybcTiNBQAAAGDLJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4Yc51ONy++vJxurXnx5eV0Ot1hNwluSNwyjrrdmpcWV16N22539Xm3DrtpcENr43ezuN1KHRiU7cafeOVGpobdgH4opdyb5OEk7ST/qNb64SE3CfZEp9PNxYWlPHTybE5duJSjB/fn4WOHcmBuJu22XCajaWWlm0tfvSpu7z+UA/PiltG10Xj7ke97S/7Vmadz7O1flwPzM2m1yrCbCa/odmsWljuZm2nn5eVOLi+u5Pia+D1x7HD2z03nqyvd69YR2+yFbrfm4uXFq+LvUA7MzybJK7G8sNTJ3HQ7SXLx8lKOnzwjXtnU2O9VllLaSX4qyXcl+cYkx0op3zjcVsHeWFju5KGTZ/PE+YtZ6dY8cf5iHjp5NgvLnWE3DTbU6XQ3jtvHxC2jq9utubx0bdz+0M8+mXe/+fYcP3lG/DJSVn84LuUHHz2db/iRn8+zf7T6I3Jt/B4/eSaXlzo3rCO22QsLS50N4u9sFpZW1sXyDz56OhcvL/XqnxGvXNfYJzuSvC3JuVrr+VrrUpLHkrxnyG2CPTE/O5VTFy6tKzt14VLmZxtx0BYNtLDcEbeMnevF7Ztety+nLlzK3Ex7SK2Day0sr/8heOf+uU3H3RvVEdvshbnZ9sbxNzu1YVJj0/rilTWakOx4fZKn1jx/ulcGjbew2MnRg/vXlR09uD8Li7LajKb52amce/alDeP28uLKkFoF1zc30940bq+ULywZdxkdczPrfwheL35vVEdssxeut0+7UVJj0/rilTWakOzY6KSsdVenKaU8WEo5XUo5/dxzz+1Rs2DnthqzrZJ89L635J67DmSqVXLPXQfy0fveEqcqMgxbidvLiyt5/IvP5CPftz5uHz526JVzcGGvbHWsXVjqbBi3P3n/oTz+xWdy4thh8cue2E7Mrv0h+FO/dO6a/YWHj63G7/XqiG12a8v7tK3N92k3Smq0WsmJY4fFK9dVah3vq9aWUu5J8mO11nf3nv9wktRa//ZG9Y8cOVJPnz59w/ke/NDPbbstFz78Pdt+D4M14O24JymF68Vsp9PNi4sr+crCcu7cP5enLi3kNXPTuWV2yoUe2ciepcE2i9tOp5uLl5fy2Bd+L+9+8+150+v25fLiSuam25maErNcY+gxm7x64byTv3ZV3M608/Ly6sUdXRCPnhGK2fUXb/wHf+lb0m61Mje7epHHm6daubSwfN06c9Nie0IMfZ+22129y9ULa/Zpb52bzr7ZqWvi9MqFSJNrL1wqXifGljZ0E06QPpXk7lLKG5P8fpL7k/zF4TYJ9ka73VpNbLRKSkkO7JvJ3HRbooOR1W63cmB+Jt//rW/M/OxULi+uZH5GzDLaWq2SA/Oz+YFvvWv1R+BiJ1PtklYp2XdTE3alaJrVmJ3JIw8c2fCH4L7eNZK2Ugf2QqtVcstN02m3Wyklee0ts6/E41biVLyykbGPilrrSinlA0kez+qtZz9Ra/3NITcL9ky73cotvR+Kt9w0PeTWwI2JWcZRq/VqYkOCg3HQapUb/hDcSh3YK5vFozhlpxoRLbXWzyX53LDbAQAAAAyf44YBAACARpHsAAAAABpFsgMAAABolLG/9ex2lVKeS/K7N6j22iTP70Fzhsky7t7ztdZ7Bzj/JFuO2WQytuluTfo62pOYTW4Yt5O+HW7E+nnVKMTsuGwP7ey/nbR12DE7Tut3rXFs9zi2Odm43aO2TzvqxnXbb9coL+eWYnbikh1bUUo5XWs9Mux2DJJlbJ5JW96dsI5Gg+1wfdbPaBmX7aGd/TdObb1iHNucjGe7x7HNyfi2e5RMyjpswnI6jQUAAABoFMkOAAAAoFEkOzb2sWE3YA9YxuaZtOXdCetoNNgO12f9jJZx2R7a2X/j1NYrxrHNyXi2exzbnIxvu0fJpKzDsV9O1+wAAAAAGsWRHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKNIdgAAAACNItkBAAAANIpkBwAAANAokh0AAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADTKxCU77r333prEZOrHtCfErKmP054Rt6Y+TXtGzJr6NO0ZMWvq47QnxKypj9OWTFyy4/nnnx92E2BbxCzjSNwybsQs40bMMm7ELHtt4pIdAAAAQLNJdgAAAACNItkBAAAANIpkBwAAANAokh0AAABAo0h2QE+3W/PS4kq6tffY3fJdjQAmhrGSSSPm9451DZNpUH1/qi9zgTHX7dZcvLyY4yfP5tSFSzl6cH9OHDuUA/OzabXKsJsHMBJWx8qlHD95Zs1YeTgH5me2PFZ2uzULy53MzbSzsNTJ3HTbOMvI6nS6ubiwlIfW7R9sL+YnQT/6dT/GF2D8DPJ3mCM7IMnCUifHT57NE+cvZqVb88T5izl+8mwWljrDbhrAyFhY7uT4yTNXjZVnsrC8tbHyyo+ZH3z0dL7hR34+P/jo6Vy8vOS/t4ykbrfm8lInD12zf7D1mJ8E/erXux1fgPE0yN9hkh2QZG62nVMXLq0rO3XhUuZm20NqEcDomZvZZKyc2dpY6ccM42RhuZP52aldxfwk6Fe/3u34AoynQf4Ok+yAJAuLnRw9uH9d2dGD+7OwaAcc4IqFpU3Gyi3+98WPGcbJ3Ew75559aVcxPwn61a93O74A42mQv8MkOyBJq5V89L635J67DmSqVXLPXQfy0fvekpYeAjTUTi4GNjfdzoljh9eNlSeOHc7c9BaP7PBjhhG3tl9cXlzJ4198Jh/5vvX7Bw8fO7TlmJ8E/erXux1f+sEFUhk1kxCTg/wd5gKlkGS23cq+2an87T//J3Pn/rk8dWkh+2anMtuW7QCaZ6MLAT587FAOzM2kfZ1xr9UqOTA/k0ceOLKjCxFe+TFz9QUI/XBkFFx9MdLj73xT7n/bG/LYF34vP/Znvylvet2+XF5cyfyMi+qu1a9+vdvxZbdcrJ5RMykxedNUO7dc9Tvsltmp3DS1+30DyQ5I8tXlbj71/17Iu998e5JkcWX1+Q98613ZJ+EBNMzac+yT5InzF/PQybP5h3/5rdk3W667E9VqleybXd19uPK4VcP+MQObufpipEny9/7tl5Ik3/+tb8z87FQWljrZNzslXq/Sz369m/Flt9ZeJDHJKxdJfOS9R7LvJj+Z2HuTEpOtVsktN02n3W6llOS1t8z2bd+gOWsJdmFutp0Tv3julR2bJJlqlXzgXXcPsVUAg7HZOfbzs1NZWO4M9EfGMH/MwGY2uxjpiV88lw+86+60ShGv19GEfu1i9YyaSYrJQY0h/mUNcYFSYLJsdo79uWdfcrFQJpKLkWJfkFEjJndPsgPiAqXAZJmbbufhY4fWjXkf+b635PEvPuOHHRNpYanjYqQTzr4go0ZM7t54HmcGfTbIC+MAjJpWq+TA3Ez+4V9+a+Znp3Lu2Zfyr848nWNv/zo/7JhIc9PtHHv71+Xkr/2ui5FOKPuCjBoxuXuSHZDBXhgHYBS1263smy1ZWO7k7q/dl9ffepdxj4l15SKbP/Btd71ykU0XI50s9gUZNWJy9yQ7oKcJF9cC2A7jHrxKf0AMMGrE5O444wcAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGmWgyY5SyidKKc+WUr64puzHSim/X0o525u+e81rP1xKOVdK+Q+llHevKb+3V3aulPKhNeVvLKX8WinlS6WUf1ZKmRnk8gAAAACjb9BHdnwyyb0blP9ErfVQb/pckpRSvjHJ/Um+qfeev19KaZdS2kl+Ksl3JfnGJMd6dZPkI7153Z3khSTvG+jSAAAAACNvoMmOWuuvJLm0xervSfJYrXWx1vofk5xL8rbedK7Wer7WupTksSTvKaWUJO9M8s977380yff2dQEAAACAsTOsa3Z8oJTyZO80l1t7Za9P8tSaOk/3yjYrP5DkK7XWlavKAQAAgAk2jGTHTyf5+iSHkjyT5O/2yssGdesOyq9RSnmwlHK6lHL6ueee236LYY+JWcaRuGXciFnGjZhl3IhZhmnPkx211j+otXZqrd0kj2T1NJVk9ciMO9dUvSPJl69T/nyS15RSpq4q3+gzP1ZrPVJrPXLbbbf1b2FgQMQs40jcMm7ELONGzDJuxCzDtOfJjlLK7Wue/rkkV+7U8tkk95dSZkspb0xyd5IvJDmV5O7enVdmsnoR08/WWmuSX0ryF3rvfyDJZ/ZiGQAAAIDRNXXjKjtXSjmZ5NuTvLaU8nSSH03y7aWUQ1k95eRCkr+aJLXW3yyl/EyS30qykuT9tdZObz4fSPJ4knaST9Raf7P3ET+U5LFSyt9McibJxwe5PAAAAMDoG2iyo9Z6bIPiTRMStdYfT/LjG5R/LsnnNig/n1dPgwEAAAAY2t1YAAAAAAZCsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGmWgyY5SyidKKc+WUr64pmx/KeXzpZQv9R5v7ZWXUsqJUsq5UsqTpZRvWfOeB3r1v1RKeWBN+VtLKb/Re8+JUkoZ5PIAAAAAo2/QR3Z8Msm9V5V9KMkv1FrvTvILvedJ8l1J7u5NDyb56WQ1OZLkR5O8PcnbkvzolQRJr86Da9539WcBAAAAE2agyY5a668kuXRV8XuSPNr7+9Ek37um/FN11a8meU0p5fYk707y+VrrpVrrC0k+n+QVU/KsAAAgAElEQVTe3mtfU2t9otZak3xqzbwAAACACTWMa3Z8ba31mSTpPb6uV/76JE+tqfd0r+x65U9vUA470ul08+LLy+nWmhdfXk6n0x12k4AR0u3WLCyt5KWXV9KtdfWxW4fdLBiabreu6w8LS/oEDFq3W/PSYq/fLW7c57ZSpwnsu3MjU8NuwBobXW+j7qD82hmX8mBWT3fJG97whp22jwbrdLq5eHkpDz12NqcuXMrRg/vz8P2HcmB+Ju323ucExSzjqMlx2+2u7ki9uLiSD376yVfGiRPHDuXA/GxaLZeMGkdNjtlB63ZrLl5ezPGTr35vfvS+t+SW2ancctO0PjEgYnayrfa7pRw/eWbN99DhHJifeaXPbaXOXhpUzI7avjujaRiR8Ae9U1DSe3y2V/50kjvX1LsjyZdvUH7HBuXXqLV+rNZ6pNZ65LbbbuvLQtAsC8udPPTY2Txx/mJWujVPnL+Yhx47m4XlzlDaI2YZR02O24XlTl5YWM4HP/3kunHi+MnhjRPsXpNjdtAWljs5fnL99+YHP/1kXlhY1icGSMxOttV+d+aq76Ez6/rcVurspUHF7KjtuzOahpHs+GySK3dUeSDJZ9aUv7d3V5Z3JPnD3mkujyf5zlLKrb0Lk35nksd7r71YSnlH7y4s710zL9iW+dmpnLqw/vIypy5cyvzsKB38BAzL3Ew7d+6f23CcmJtpD6lVMDxzM+0N+8Od++f0CRiQzfrd2j63lTpNYN+drRj0rWdPJnkiyX9SSnm6lPK+JB9O8h2llC8l+Y7e8yT5XJLzSc4leSTJf5cktdZLSf5GklO96a/3ypLkv03yj3rv+Z0kPz/I5aG5Li+u5OjB/evKjh7cn8uLK0NqETBKFpY6eerSwobjxMKS/yIxeRaWOhv2h6cuLegTMCCb9bu1fW4rdZrAvjtbMei7sRyrtd5ea52utd5Ra/14rfVirfVdtda7e4+XenVrrfX9tdavr7X+yVrr6TXz+USt9U296R+vKT9da31z7z0f6N2VBbZtbrqdh+8/lHvuOpCpVsk9dx3Iw/cfytx0s7LgwM7MTbdz69x0PnrfW9aNEyeOGSeYTHPT7Zw4tv5786P3vSW3zk3rEzAgq/3u8FXfQ4fX9bmt1GkC++5sheN8IEm73cqB+Zl87L1vzfzsVC4vrmRuuu0CR0CSpNUqueWm6UxPtfLIe49kbradhcVO5mbaLsTIRGq1Sg7Mz67rD61WctOUPgGDstrvZvLIA0cyN9POwlInc9Pr+9xW6jSBfXe2QrIDetrtVm7pDZC33DQ95NYAo6bVKpmbefVrc99NvkKZbK1WeaUf6A+wN1qtkn2961Ls2+T6FFup0wT23bkRqS8AAACgUW6Y6iul/FKSrVwL45O11k/tvkkAAAAAO7eV45r+yhbn9ZVdtAMAAACgL26Y7Ki1/u5mr5VSpmqt7u9DI3Q63Swsd1zkCBhJ3W7NwnJnWxec28l7mGy+C5vLtgVG1aDGpxvOoZTy79b8/U+uevkLu24BjIBOp5uLl5fy4Kd+Pd/wIz+fBz/167l4eSmdTnfYTQMaqtuteWlxJd3ae+xufsZot1tz8fJSfvDR0/mGH/n5/OCjp3Px8lLf38NkW1nxXdgka8eYl5dWbFsYQ9vZVxhXg/wdtpV0yfyav7/pqtf8e4hGWFju5KHHzuaJ8xez0q154vzFPPTY2Swsd4bdNKCBtpuIWFju5PjJM+vGqOMnz1x3jNrJe5hc3W7NV1d8FzbF1WPMyytd2xbGzKT802KQv8O2kuy43tps1ppmYs3PTuXUhUvryk5duJT5Bt+uCxie7SYi5mbaG45RczPtTT9jJ+9hcl05fNh3YTNcPcZ8zc3Tti2MmUn5p8Ugv3u2kux4TSnlz5VSvq/395/vTd+X5I/tugUwAi4vruTowf3ryo4e3J/Liy5JA/TfdhMRC0udDceohaXrHNmxg/cwueZm2vmjry77LmyIq8cY2xbGz6T802KQv8O2kuz4v5P82SR/pvf3f9Gb/kySX9l1C2AETLdKHr7/UO6560CmWiX33HUgD99/KNMu5AcMwHYTEXPT7Zw4dnjdGHXi2OHMTV/nyI4dvIfJtbDUyRO/8/yG34ViZvxcPcb8qzO/b9vCmJmUf1rMTbcHNj6VWq9/Jkop5Q1bnNdXaq1/tOsWDdiRI0fq6dOnh90MRky3W7OwtPLKoZ5/9NXlTLVK5mamrnfngj3JhIhZ+mjPsnfi9vqunId7/OSZnLpwKUcP7s+JY4dzYH5m0zFnQu/GImb3yJWYPH3hYu75+tfma26ezuXFldw81c7UlDt2bMNIxOxGY8wj731rauJuLGzEPu0I2sm+wrjawd1YtrQCtnIizKO5/rU5Su/1Tyb51FY+FEZNq5fYuHIO3FS7NY4/CoAx0WqVHJifySMPHNlyIqLVKtnXO3913xbPY93Je5hMV2Ly277hda/E5Pz1E/6MsBuNMbfcND3kFgI3spN9hXHVbrdySy+50c/x6YZ7PrXWP923T4MR5kcBsJeMOYwaMdkstieMP/14dxy7BgAAADSKZAcAAADQKJIdAAAAQKNIdgAAAACNItkBAAAANIpkBwAAANAokh0AAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHZAT6fTzYsvL6dba158eTmdTnfYTQL6QN+m6cQ4Tdbt1ry0uJJuXX3sdLrrnne7ddhNZEiMfdzI1LAbAKOg0+nm4uWlPPTY2Zy6cClHD+7Pw/cfyoH5mbTbcoIwrvRtmk6M02Tdbs3Fy0s5fvLMuvh+7Au/lxO/eC5HD+7PiWOHc2B+Jq1WGXZz2UPGPrZCJECSheVOHnrsbJ44fzEr3Zonzl/MQ4+dzcJyZ9hNA3ZB36bpxDhNtrDcyfGTZ66J73e/+fZXnh8/eUa8TyBjH1vhyA5IMj87lVMXLq0rO3XhUuZnx6eLHPzQz237PRc+/D0DaAm7td1taTturgl9G65HjNNkczPtDeP7Ta/bt+753Ex7r5vGkBn72ApHdkCSy4srOXpw/7qyowf35/LiypBaBPSDvk3TiXGabGGps2F8n3v2pXXPF5b8N3/SGPvYiqElO0opF0opv1FKOVtKOd0r219K+Xwp5Uu9x1t75aWUcqKUcq6U8mQp5VvWzOeBXv0vlVIeGNbyMN7mptt5+P5DueeuA5lqldxz14E8fP+hzE37TwGMM32bphPjNNncdDsnjh2+Jr4f/+Izrzw/ceyweJ9Axj62YtjH+fzpWuvza55/KMkv1Fo/XEr5UO/5DyX5riR396a3J/npJG8vpexP8qNJjiSpSX69lPLZWusLe7kQjL92u5UD8zP52HvfmvnZqVxeXMncdNsFjmDM6ds0nRinyVqtkgPzM3nkgSOZm2lnYamTm6da+YFvuysfeNfdWVjqZG667eKkE8jYx1aMWjS8J8mjvb8fTfK9a8o/VVf9apLXlFJuT/LuJJ+vtV7qJTg+n+TevW40zdBut3LLTdNplZJbbpo2WEJD6Ns0nRinyVqtkn2zU2mV1cd2u7XuuUTH5DL2cSPDjIia5N+UUn69lPJgr+xra63PJEnv8XW98tcneWrNe5/ulW1Wvk4p5cFSyulSyunnnnuuz4sB/SdmGUfilnEjZhk3YpZxI2YZpmEmO/5UrfVbsnqKyvtLKf/ZdepulLKt1ylfX1Drx2qtR2qtR2677badtRb2kJhlHIlbxo2YZdyIWcaNmGWYhpbsqLV+uff4bJJ/meRtSf6gd3pKeo/P9qo/neTONW+/I8mXr1MOAAAATKihJDtKKfOllFuu/J3kO5N8Mclnk1y5o8oDST7T+/uzSd7buyvLO5L8Ye80l8eTfGcp5dbenVu+s1cGAAAATKhh3Y3la5P8y1LKlTb801rr/1VKOZXkZ0op70vye0nu69X/XJLvTnIuyUKS70+SWuulUsrfSHKqV++v11ov7d1iAAAAAKNmKMmOWuv5JN+8QfnFJO/aoLwmef8m8/pEkk/0u40AAADAeHJ/HgAAAKBRJDsAAACARpHsAAAAABplWBcoBdjUwQ/93Lbfc+HD3zOAlgAAAOPIkR0AAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKNIdgAAAACNItkBAAAANIpkBwAAANAoU8NuANBsBz/0cyP5ORc+/D0DagkAADBsjuwAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGaUSyo5RybynlP5RSzpVSPrSbea2sdPPiy8vp1poXX17Oykq3X80EIEmn083C4kpeennllbG20zHWMtq63Xpt3Ha7eWlxJd1uHXbz4Brdbl2Nz7r62Ol01z3vduuW6sBe6XTW/w67sm9wdZxeicvNyuGKqWE3YLdKKe0kP5XkO5I8neRUKeWztdbf2u68Vla6ubSwlIceO5tTFy7l6MH9efj+Q9k/N5OpqUbkhQCGqtPp5sXFlby0uJIPfvrJV8faY4dyYG4m7baxltHT7a7ueL94Vdz+nfu+OT/760/l2Nu/LgfmZ9JqlWE3FZKsxuzFy0s5fvJMTl24lOPvfFPuf9sb1u3jnjh2KDPtVv6b/+P/u06dw2KbPdHpdHPx8sa/w1746vIrsXwlLvfPTefSwrXl4pW1mrBX+bYk52qt52utS0keS/KenczoqyudPPTY2Txx/mJWujVPnL+Yhx47m6+udPraYIBJtbDcyVcWlvPBTz+5fqw9eTYLy8ZaRtPCcicvbBC3/+On/33e/ebbc/zkGfHLSFlY7uT4yTOvxOu733z7Nfu4x0+ezQsLyzeoI7bZGwvLm/8OWxvLa+Nys3K4ognJjtcneWrN86d7Za8opTxYSjldSjn93HPPbTqj+dmpnLpwaV3ZqQuXMj879gfAMGa2GrMwSrYSt/OzU7lz/5yxlpGw1bF2bqa9ady+6XX7curCpczNtAfdXNhWzK6N1ytxutapC5dy5/65G9YR2+xGP36HbadcvLJWE5IdGx2ntO6ErVrrx2qtR2qtR2677bZNZ3R5cSVHD+5fV3b04P5cXlzpS0Nhq7YaszBKthK3lxdX8tSlBWMtI2GrY+3CUmfTuD337Es5enB/Fpb8N5HB207Mro3XK3G61tGD+/PUpYUb1hHb7EY/fodtp1y8slYTkh1PJ7lzzfM7knx5JzO6eaqdh+8/lHvuOpCpVsk9dx3Iw/cfys1TMoQA/TA33c5r5qbz0fvesn6sPXYoc9PGWkbT3HQ7t24Qt3/nvm/O4198JieOHRa/jJS56XZOHDv8Srw+/sVnrtnHPXHsUG6dm75BHbHN3pib3vx32NpYXhuXm5XDFU04ZvhUkrtLKW9M8vtJ7k/yF3cyo6mpVvbPzeRj731r5mencnlxJTdPtV2cFKBP2u1Wbpmdyky7lUfeeyRzs+1cXlzJ3HTbxUkZWa1WyS03TWf66ridaecHvu2uzE23XRCPkdJqlRyYn8kjDxzJ3Ew7C0ud3DzVWvf8yo/CG9UR2+yFdruVA/Prf4dd2Te4OpavxOVm5XDF2Cc7aq0rpZQPJHk8STvJJ2qtv7nT+U1NtXJLL7lxy03T/WkkAK9ot1uZW5PYMNYyDlqtkrk115W5Erf7ZiXpGE2tVsm+Xsy+8tgbe/etieWt1IG90G63ckv72t9hG8Xy9crhikZERa31c0k+N+x2AAAAAMPn3xEAAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0Cil1jrsNuypUspzSX73BtVem+T5PWjOMFnG3Xu+1nrvAOefZMsxm0zGNt2tSV9HexKzyQ3jdtK3w41YP68ahZgdl+2hnf23k7YOO2bHaf2uNY7tHsc2Jxu3e9T2aUfduG777Rrl5dxSzE5csmMrSimna61Hht2OQbKMzTNpy7sT1tFosB2uz/oZLeOyPbSz/8aprVeMY5uT8Wz3OLY5Gd92j5JJWYdNWE6nsQAAAACNItkBAAAANIpkx8Y+NuwG7AHL2DyTtrw7YR2NBtvh+qyf0TIu20M7+2+c2nrFOLY5Gc92j2Obk/Ft9yiZlHU49svpmh0AAABAoziyAwAAAGgUyQ4AAACgUSQ7AAAAgEaR7AAAAAAaRbIDAAAAaBTJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkOAAAAoFEkOwAAAIBGkewAAAAAGkWyAwAAAGgUyQ4AAACgUSQ7AAAAgEaZuGTHvffeW5OYTP2Y9oSYNfVx2jPi1tSnac+IWVOfpj0jZk19nPaEmDX1cdqSiUt2PP/888NuAmyLmGUciVvGjZhl3IhZxo2YZa9NXLIDAAAAaDbJDgAAAKBRJDsAAACARpHsAAAAABpFsgMAAABoFMkO6Ol2a15aXEm39h67W76rEQyFmAUYLOPs1lhPwG4MagyZ6stcYMx1uzUXLy/l+MkzOXXhUo4e3J8Txw7nwPxMWq0y7ObBNcQswGAZZ7fGegJ2Y5BjiCM7IMnCcifHT57JE+cvZqVb88T5izl+8kwWljvDbhpsSMwCDJZxdmusJ2A3BjmGSHZAkrmZdk5duLSu7NSFS5mbaQ+pRXB9YhZgsIyzW2M9AbsxyDFEsgOSLCx1cvTg/nVlRw/uz8KS/0owmsQswGAZZ7fGegJ2Y5BjiGQHJJmbbufEscO5564DmWqV3HPXgZw4djhz0/4rwWgSswCDZZzdGusJ2I1BjiEuUApJWq2SA/MzeeSBI5mbaWdhqZO56bYLazGyxCzAYBlnt8Z6AnZjkGOIZAf0tFol+2ZXu8SVRxhlYhZgsIyzW2M9AbsxqDHEaSwAAABAo0h2AAAAAI0i2QEAAAA0imQHAAAA0CiSHQAAAECjSHYAAAAAjSLZAQAAADSKZAcAAADQKJIdAAAAQKNIdkBPt1vz0uJKurX32K3DbhJcl5gFGDxj7d6xrmEyDarvT/VlLjDmut2ai5eXcvzkmZy6cClHD+7PiWOHc2B+Jq1WGXbz4BpiFmDwjLV7x7qGyTTIvu/IDkiysNzJ8ZNn8sT5i1np1jxx/mKOnzyTheXOsJsGGxKzAINnrN071jVMpkH2fckOSDI3086pC5fWlZ26cClzM+0htQiuT8wCDJ6xdu9Y1zCZBtn3RyrZUUr5RCnl2VLKF9eU/Vgp5fdLKWd703evee2HSynnSin/oZTy7uG0miZYWOrk6MH968qOHtyfhSX/TWA0iVmAwTPW7h3rGibTIPv+SCU7knwyyb0blP9ErfVQb/pckpRSvjHJ/Um+qfeev19KkfplR+am2zlx7HDuuetAplol99x1ICeOHc7ctJBiNIlZgMEz1u4d6xom0yD7/khdoLTW+iullINbrP6eJI/VWheT/MdSyrkkb0vyxICaR4O1WiUH5mfyyANHMjfTzsJSJ3PTbRfEYmSJWYDBM9buHesaJtMg+/6oHdmxmQ+UUp7sneZya6/s9UmeWlPn6V4Z7EirVbJvdiqt0nv05cqIE7MAg2es3TvWNUymQfX9cUh2/HSSr09yKMkzSf5ur3yjNbDhDXlLKQ+WUk6XUk4/99xzg2kl9JGYZRyJW8aNmGXciFnGjZhlmEY+2VFr/YNaa6fW2k3ySFZPVUlWj+S4c03VO5J8eZN5fKzWeqTWeuS2224bbIOhD8Qs40jcMm7ELONGzDJuxCzDNPLJjlLK7Wue/rkkV+7U8tkk95dSZkspb0xyd5Iv7HX7AAAAgNEyUhcoLaWcTPLtSV5bSnk6yY8m+fZSyqGsnqJyIclfTZJa62+WUn4myW8lWUny/lqre1MBAADAhBupZEet9dgGxR+/Tv0fT/Ljg2sRAAAAMG5G/jQW2Cvdbs1Liyvp1t5jd8Pr3cJQiE+AwTLOIgYYNWJydyQ7IKsDyYsvL+f5FxdTa/L8i4t58eVlAwojQXwCDFa3W3Px8lI+8f+cz5f+4KXcPN3OS4sr6XS6w24ae8R3LaNGTO7eSJ3GAsPy8konLy6u5If/xW/k1IVLOXpwfz5631syPdXK3IxuwnCJT4DBWlju5OSv/W6+9/Ad+aGfffKVsfbhY4fy2vnZtFpl2E1kwHzXMmrE5O45sgOSdLvJBz/9ZJ44fzEr3Zonzl/MBz/9ZLr+ocMIEJ8AgzU3086733x7fuhn14+1D508m4Vl17+fBL5rGTVicvckOyDJ3Gw7py5cWld26sKlzM22h9QieJX4BBishaVO3vS6fRuPtTPG2kngu5ZRIyZ3T7IDkiwsdnL04P51ZUcP7s/Cov/mMHziE2Cw5qbbuby4svFYu2SsnQS+axk1YnL3JDsgq4evnjh2KPfcdSBTrZJ77jqQE8cO+W8OI0F8AgxWq1UyP9POw9eMtYczN22snQS+axk1YnL3XNkEsrqTc2B+No88cCRzM+0sLHUyN912QTJGgvgEGLx2u5XXGmsnlu9aRo2Y3D3JDuhptUr2za52iSuPMCrEJ8DgGWsnm+3PqBGTu+M0FujpdmteWlxJt/Ye3cN6JNlOAINjjG0u2xYYVYMan6SHIKsd7OLlpRw/eeaV+1ifOHY4B+ZnHCo2QmwngMExxjaXbQuMqkGOT47sgCQLy50cP3lm3X2sj588k4VlVzseJbYTwOAYY5vLtgVG1SDHJ8kOyOrVjje8j7WrHY8U2wlgcIyxzWXbAqNqkOOTZAckWVja5D7WS/7jMUpsJ4DBMcY2l20LjKpBjk+SHZBkbrqdE8cOX3Uf68OZm/Yfj1FiOwEMjjG2uWxbYFQNcnxygVLIlftYz7iP9YiznQAGxxjbXLYtMKoGOT5JdkCP+1iPB9sJYHCMsc1l2wKjalDjk9NYAAAAgEaR7AAAAAAaRbIDAAAAaJSBnbBXSjmxQfEfJjlda/3MoD4XAAAAmGyDPLLjpiSHknypN70lyf4k7yul/OQAPxcAAACYYIO8FPObkryz1rqSJKWUn07yb5J8R5LfGODnwo50uzULyx23ZBtxthPA4Bhjm8u2BUbVoManQSY7Xp9kPqunrqT39x+vtXZKKYsD/FzYtm635uLlpRw/eSanLlzK0YP7c+LY4RyYn7EjMEJsJ4DBMcY2l20LjKpBjk+DPI3lf0tytpTyj0spn0xyJsnfKaXMJ/m3A/xc2LaF5U6OnzyTJ85fzEq35onzF3P85JksLHeG3TTWsJ0ABscY21y2LTCqBjk+DezIjlrrx0spn0vytvz/7N1/dCR3eef7z1PV3Rq3NFksIXO8/oGY2CQxMEhYMp44ZAEvN2b5GWDuHd2A5wavnZzFq2FD2Hgh54Sbm1zMMQsZ3eWyOxMTJrusBgwEvMHES4xZLtmJ0YAG2+CAZyfCdjzrkSVjz6g9aqn7uX+opVHPtEYtqaurq/r9OqdPq0rV3U/X96lvVT/9rWrJJH3I3Z+s/PuDUb0usBH5XKjxyZmqeeOTM8rnwpgiQi20EwBEhz42vWhbAK0qyv4pspEdZmaSrpf0Snf/iqSMmV0T1esBm1EoljTU1101b6ivW4Ui33i0EtoJAKJDH5tetC2AVhVl/xTlaSz/r6QdkoYr0yclfSrC1wM2LJ8NNTo8oB3bepQJTDu29Wh0eED5LN94tBLaCQCiQx+bXrQtgFYVZf8U5QVKX+3urzKzCUly92fMLBfh6wEbFgSmns6c9u8e5CrlLYx2AoDo0MemF20LoFVF2T9FObJj3sxCSS5JZtYrqXy+B5jZZ8zshJk9vGJet5l9w8werdxfWJlvZjZqZkfN7EEze1WE7wVtIAhMXR0ZBVa55wCgJdFOABAd+tj0om0BtKqo+qcoix2jkv5C0kVm9seSviPp/17jMZ+VdMNZ826TdJ+7Xynpvsq0JL1R0pWV2y2SPt2YsAEAAAAAQJJF+WssnzOz72nxIqUm6e3u/sgaj/m2mfWdNfttkl5b+fuApG9J+r3K/D93d5f0t2b2AjO72N2PN+xNAAAAAACAxGl4scPMVl5K9YSksZX/c/eZcx91Xi9aKmC4+3Ezu6gy/xJJj69Y7onKPIodAAAAAAC0sShGdnxPi9fpMEmXS3qm8vcLJD0m6SUNep1aJ/J4zQXNbtHiqS66/PLLG/TyQHTIWSQReYukIWeRNOQskoacRZwafs0Od3+Ju2+TdK+kt7j7C929R9KbJX15A0/5lJldLEmV+xOV+U9IumzFcpdKenKVmPa5+6C7D/b29m4gBLSDctl1am5BZa/cl2vWzpqCnF1dK7UTqpG3SBpythr9a+tbT87SnmgF9LObw3a8OVFeoHTI3e9ZmnD3r0v6Jxt4nrsl7a78vVvSV1fMv7HyqyzXSnqW63Vgo8pl1/RsUTcfOKyXfvjruvnAYU3PFulQWgztBADRoH9NF9oTSD62482LstjxtJn9vpn1mdmLzezDkqbP9wAzG5N0SNIvmNkTZnaTpNslvcHMHpX0hsq0JN0j6Ziko5L2S/oXUb0RpF9hvqSRsQkdOjathbLr0LFpjYxNqDBfijs0rEA7AUA06F/ThfYEko/tePMi+zUWScOS/kCLPz/rkr5dmbcqd1/t/9fXWNYlvW+TMQKSpHwu1Phk9bVzxydnlM+FMUWEWmgnAIgG/Wu60J5A8rEdb15kIzvcfcbd97j7gLu/yt3fv/KXWMzs/4nqtYH1KhRLGurrrpo31NetQpHKaSuhnQAgGvSv6UJ7AsnHdrx5UZ7GspbrYnxtoEo+G2p0eEA7tvUoE5h2bOvR6PCA8lkqp62EdgKAaNC/pgvtCSQf2/HmRXkaC5AYQWDq6cxp/+5B5XOhCsWS8tlQQVDrF44RF9oJAKJB/5outCeQfGzHm0exA6gIAlNXx+ImsXSP1mXeQeIAACAASURBVEM7AUA06F/ThfYEko/teHPiPI2FkhQAAAAAAGi4yIodZralxrwXrpjcG9VrAwAAAACA9hXlyI5xM7t2acLM3inpvy9Nu/tnI3xtAAAAAADQpqI88ed/l/QZM/uWpH8sqUfS6yN8PQAAAAAAgOiKHe7+kJn9saT/KOmkpF919yeiej0AAAAAAAApwmKHmd0p6eclbZf0Ukn/xcz+nbt/KqrXBAAAAAAAiPKaHQ9Lep27/7273yvpWkmvivD1AAAAAAAAIj2N5ZNnTT8r6aaoXg8AAAAAAECK9jSWKyV9VNJVkpZ/htbdt0X1mgAAAAAAAFGexvJnkj4taUHS6yT9uRYvVgoAAAAAABCZKIsdF7j7fZLM3X/q7h8RPz0LAAAAAAAiFtlpLJJOm1kg6VEzu1XSP0i6KMLXAwAAAAAAiHRkx/sl5SWNSLpa0rsl3Rjh6wGbUi67Ts0tqOyV+7LHHRI2iTYFgOjQxwKtqV22zXZ5n9i4KEd2uBav0fFiSdnKvP2Stkf4msCGlMuu6dmiRsYmND45o6G+bo0OD6inM6cgsLjDwwbQpgAQHfpYoDW1y7bZLu8TmxPlyI7PafEipe+U9ObK7S0Rvh6wYYX5kkbGJnTo2LQWyq5Dx6Y1Mjahwnwp7tCwQau2aZE2BYDNoo8F4rHWaIZ2OaZtl/eJzYlyZMeUu98d4fMDDZPPhRqfnKmaNz45o3wujCkibNaqbdoRqlx2qv4AsAn0sUDz1TOaoV2OadvlfWJzohzZ8Qdm9qdmNmxm71i6Rfh6wIbNzi1oqK+7at5QX7dm5xZiigibVSiWarbpY9MFqv4AsEn0sUDz1TOaYbVtM22jrjh2Rz2iLHb8pqR+STdo8fSVt2jxVBag5eRzoT72zu3asa1HmcC0Y1uPPvbO7VSHEyyfDTU63H9Om/7JX/+EdgWATaKPBZqvntEMi9vmQNW2OTo8oHw2Xdslx+6oR5SnsbzS3V8R4fMDDfP8fFlfmXhCH3nry3TFRV06euKUvjLxhN77mm3q6oiyJoioBIGpsyOjj77jFbqsO6+jJ07p4//1x5o6OadCsaSujii7PwBIN/pYoPmWRm0cOja9PG9p1MbSNhcEpp7OnPbvHlQ+F6pQLCmfDVN3ahnH7qhHlHuivzWzq9z9RxG+BtAQ+Wyo4Ve/+JxzINNWBW83WzKhOjsyevefPkC7AkCD0ccCzbU0amOt49UgsOXiR1oLjxy7ox5RZv+vSNptZn8vaU6SSXJ356dn0XLapQrebmhXAIgOfSzQXGxzZ7AuUI8oix03RPjcQMO1QxW8HdGuravvtq+t+zGTt78pgkgAbBR9LNBcbHNnsC6wlsiywt1/GtVzAwAAAAAArIartwAAAAAAgFSh2AEAAAAAAFIlMSc3mdmkpJOSSpIW3H3QzLolfV5Sn6RJSf+ruz8TV4wAAAAAACB+SRvZ8Tp373f3wcr0bZLuc/crJd1XmQYAAAAAAG0sacWOs71N0oHK3wckvT3GWAAAAAAAQAtIUrHDJf1XM/uemd1Smfcidz8uSZX7i2KLDgAAAAAAtITEXLND0nXu/qSZXSTpG2b2d/U+sFIcuUWSLr/88qjiAxqGnEUSkbdIGnIWSUPOImnIWcQpMSM73P3Jyv0JSX8h6RpJT5nZxZJUuT+xymP3ufuguw/29vY2K2Rgw8hZJBF5i6QhZ5E05CyShpxFnBJR7DCzTjPbuvS3pP9F0sOS7pa0u7LYbklfjSdCAAAAAADQKhJR7JD0IknfMbMfSPqupK+5+19Jul3SG8zsUUlvqEwDG1IqlXXy9LzK7jp5el6lUjnukFKF9QsA0aB/RZqVy65Tcwsq++J9qVSumi6XPe4QERP6PqwlEdfscPdjkl5ZY/60pOubHxHSplQqa3q2qD0Hj2h8ckZDfd3au6tfPZ05hWFSaoKti/ULANGgf0Walcuu6dmiRsYmqvL74Hcf0+g3j2qor1ujwwPq6cwpCCzucNFE9H2oRyKKHUDUCvMl7Tl4RIeOTUuSDh2b1p6DR7Tvxqu1lQ5z01i/QDz6bvvauh8zefubIogEUaF/RZoV5ksaGZs4J78/8taX6RN//agOHZvWyNiE9u8eVFcHH2vaCX0f6kEmAJI6OzIan5ypmjc+OaNOdpwNwfoFgGjQvyLN8rmwZn5fcVFX1XQ+FzY7NMSMvg/1oNgBSJqdW9BQX3fVvKG+bs3OLcQUUbqwfgEgGvSvSLNCsVQzv4+eOFU1XSiWmh0aYkbfh3pQ7AAk5bOh9u7q145tPcoEph3berR3V7/yWb4paATWLwBEg/4VaZbPhhodHjgnv+99+Pjy9OjwAPnehuj7UA/G+QCSwjBQT2dO+268Wp0dGc3OLSifDbnAUYOwfgEgGvSvSLMgMPV05rR/96DyuVCFYkkXZAK99zXbdOv1V6pQLCmfDbk4aRui70M9KHYAFWEYLF/QaOuWbMzRpA/rFwCiQf+KNAsCW7746PJ9Jd+5KGl7o+/DWih9AQAAAACAVKHYAQAAAAAAUoViBwAAAAAASBWKHQAAAAAAIFUodgAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVMnEHAABAlPpu+1rkrzF5+5sifw0AAADUj5EdAAAAAAAgVSh2AAAAAACAVKHYAQAAAAAAUoViBwAAAAAASBWKHQAAAAAAIFUodgAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVKHYAAAAAAIBUodgBAAAAAABShWIHAAAAAABIlUzcAbSahYWynl8oqbMjo9m5BV2QCZXJUBNC6yJngWTqu+1rcYdQU7Pimrz9TU15nUYpl12n50squ5TvCDU7t6B8LtTz82Xls6GCwOIOEahSLrsK8yXlc6EKxZIuyAR6fqG8PJ3PhpK05jLkNpqlVCqrMH/mmDafDRWGwTm5vJSXq80HllDsWGFhoayZQlF7Dh7R+OSMhvq6tXdXv7rzOT48oiWRswAQvXLZdfL0vE7OLeiDdz243N9+fOcr9aXvPa7hV79YPZ05DrLRMspl1/RsUSNjExqfnNHI66/QrmsurzpeGB3uVy4M9Nv/6fvnWWaA3EZTlEplTc/WPqZ95vn55VxeysvufFYzhXPnk69YKRWfhszsBjP7sZkdNbPbNvo8zy+UtOfgER06Nq2FsuvQsWntOXhEzy+UGhku0DDkLABErzBf0jOFeX3wrger+tvfvesH+rWXX6yRsQkV5ul30ToK8yWNjE0s5+uvvfzic44XRsaO6JnC/BrLkNtojsL86se0K3N5ZV6uNh9Ykvhih5mFkj4l6Y2SrpI0bGZXbeS5OjsyGp+cqZo3Pjmjzg4GwKA1kbMAEL18LtRl3fma/e0VF3VpfHJG+VwYU3TAufK5sCpfl/J0pfHJGV3WnV9zGXIbzXC+Y9r1zCdfsVLiix2SrpF01N2PuXtR0kFJb9vIE83OLWior7tq3lBft2bnFjYfJRABchYAolcolvT4TKFmf3v0xCkN9XWrUOTbRLSOQrFUla9LebrSUF+3Hp8prLkMuY1mON8x7Xrmk69YKQ3FjkskPb5i+onKvHW7IBNq765+7djWo0xg2rGtR3t39euCDBVCtCZyFgCil8+GujCf1R07t1f1tx/f+Urd+/BxjQ4PLF/sEWgF+Wyo0eGB5Xy99+Hj5xwvjA7368J8do1lyG00Rz67+jHtylxemZerzQeWpGGse60r0HjVAma3SLpFki6//PJVnyiTCdSdz2nfjVfzyxaIFTmLJKo3b4FWUW/OBoFp65assmGg/TcOVv0ay3tfs41fAEDTrCdnezpz2r97sOqXVlZOL30oXGsZchubUW/OhmGgns7qY9qlX2M5O5eX8nK1+cCSNHwiekLSZSumL5X05MoF3H2fuw+6+2Bvb+95nyyTCbR1S1aBLR7Y8KERcSBnkUTryVugFawnZ4PAlO/IqGtLZrm/DYNAXR0ZDq7RNOvN2a6OxXzt6sgoDIOq6SCwupYBNmM9ORuG1ce0Ybh4THt2ni7l5WrzgSVp+FQ0LulKM3uJmeUk7ZJ0d8wxAQAAAACAmCT+NBZ3XzCzWyXdKymU9Bl3/2HMYQEAAAAAgJgkvtghSe5+j6R74o4DAAAAAADELw2nsQAAAAAAACyj2AEAAAAAAFLF3H3tpVLEzKYk/XSNxV4o6ekmhBMn3uPmPe3uN0T4/JLqzlmpPdp0s9p9HTUlZ6U187bd22EtrJ8zWiFnk9IexNl4G4k17pxN0vpdKYlxJzFmqXbcrXZM2+qS2vbr1crvs66cbbtiRz3M7LC7D8YdR5R4j+nTbu93I1hHrYF2OD/WT2tJSnsQZ+MlKdYlSYxZSmbcSYxZSm7craRd1mEa3iensQAAAAAAgFSh2AEAAAAAAFKFYkdt++IOoAl4j+nTbu93I1hHrYF2OD/WT2tJSnsQZ+MlKdYlSYxZSmbcSYxZSm7craRd1mHi3yfX7AAAAAAAAKnCyA4AAAAAAJAqFDsAAAAAAECqUOwAAAAAAACpQrEDAAAAAACkCsUOAAAAAACQKhQ7AAAAAABAqlDsAAAAAAAAqUKxAwAAAAAApArFDgAAAAAAkCoUOwAAAAAAQKpQ7AAAAAAAAKlCsQMAAAAAAKQKxQ4AAAAAAJAqFDsAAAAAAECqUOwAAAAAAACp0nbFjhtuuMElcePWiFtTkLPcGnhrGvKWW4NuTUPOcmvQrWnIWW4NvDUFOcutgbe6tF2x4+mnn447BGBdyFkkEXmLpCFnkTTkLJKGnEWzJabYYWb/ysx+aGYPm9mYmW0xs5eY2QNm9qiZfd7McnHHCQAAAAAA4pWIYoeZXSJpRNKgu79cUihpl6SPSfqku18p6RlJN8UXJQAAAAAAaAWJKHZUZCRdYGYZSXlJxyW9XtIXK/8/IOntMcUGAAAAAABaRCKKHe7+D5I+LukxLRY5npX0PUk/c/eFymJPSLqk1uPN7BYzO2xmh6emppoRMrAp5CySiLxF0pCzSBpyFklDziJOiSh2mNmFkt4m6SWS/rGkTklvrLFozSuzuvs+dx9098He3t7oAgUahJxFEpG3SBpyFklDziJpyFnEKRHFDkn/VNLfu/uUu89L+rKkX5b0gsppLZJ0qaQn4woQyVcuu07NLajslfty3b9qBMSCnEUcyDsAUaF/AdpTVNt+Uoodj0m61szyZmaSrpf0I0n3S3pXZZndkr4aU3xIuHLZNT07p5sPHNZLP/x13XzgsKZn59jJomWRs4jDYt4Vz8q74rryjg8zQPo0YrtuRP8CIHmiPKZNRLHD3R/Q4oVIvy/pIS3GvU/S70n6HTM7KqlH0p2xBYlEKxRLGhk7okPHprVQdh06Nq2RsSMqFEtxhwbURM4iDoX5kkbGJs7KuwkV5uvLOz7MAOnTqO16s/0LgGSK8pg2EcUOSXL3P3D3X3T3l7v7e9x9zt2Pufs17n6Fu+9097m440Qy5TtCjU/OVM0bn5xRviOMKSLg/MhZxCGfWyXvcvXlHR9mgPRp1Ha92f4FQDJFeUybmGIHEKXCXElDfd1V84b6ulWY4wAcrYmcRRwKxVXyrs5vX/gwA6RPo7brzfYvAJIpymNaih2ApCCQ7ti5XTu29SgTmHZs69EdO7crYAtBizj7fOjAyFlszkbOsc9nQ40OD1Tl3ejwgPLZOkd28GEGSJ1Gbdeb7V8agWsKodW0Q05G+Tkss/YiQPp1hIG6OjL66Dteocu683p8pqCujow6Qj45In5LF24aGTui8ckZDfV169+/+1XaelbObu3IaEuGb8ixtqVz7EfGJpZzau9wv3ryOYXn6feCwNTTmdP+3YPK50IViiXls6GCwOp63aUPMytft9kfZgA0VqO26832L5tVa187Otyvns6OpsUArNQuObklE0Z2TMsnOUDS8/Nl/fl/n9TcQlmSNLewOP38fDnmyIDaF2767f/0fWXDQC/c2iEz6YVbO7R1SzZVOz9Ep9Y59nvGjmi2WFrzW6MgMHV1ZBRY5X4dObfyw8xP/viN2r97UD2dOfIWSLBGbteb6V82iwt/o9W0S04GgWnrlmwkx7SM7AC0eGGc0W8e1Sf++tHleZnAdOv1V8YYFbBotQs3bcmFCmxxR9DVQXeO+q12jn1nR0aF+VKk+bT0YUYib4G0SMN2zYW/0WraKSej6kMY2QGIiz2itZGfaLTVzrE/euIUFwsF0JbY16LVkJObR7EDEBcoRWsjP9Fo+WyovcP9VTn1sXdu170PH0/d8FgAqAf7WrQacnLzkjnODGiwKC+MA2wW+YlGCwJTTz6n//Ceq9XZkdHRE6f0lYknNPzqF3OxUABtiX0tWg05uXkUOwCduTBOGAbLF8Zp5hXAgfMhPxGFMAzU1WEqzJd05Yu6dMmF28grAG2LfS1aDTm5eRQ7gIo0XFwL6UV+IgrkFQCcQZ+IVkNObg5n/AAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVKHYAAAAAAIBUodgBAAAAAABShWIHAAAAAABIFYodAAAAAAAgVSh2AAAAAACAVKHYAQAAAAAAUoViBwAAAAAASBWKHQAAAAAAIFUodgAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVElPsMLMXmNkXzezvzOwRM9thZt1m9g0ze7Ryf2HccQIAAAAAgHglptghaa+kv3L3X5T0SkmPSLpN0n3ufqWk+yrTAAAAAACgjSWi2GFmPyfpVyXdKUnuXnT3n0l6m6QDlcUOSHp7PBECAAAAAIBWkYhih6RtkqYk/ZmZTZjZn5pZp6QXuftxSarcXxRnkAAAAAAAIH5JKXZkJL1K0qfdfUDSrNZxyoqZ3WJmh83s8NTUVFQxAg1DziKJyFskDTmLpCFnkTTkLOKUlGLHE5KecPcHKtNf1GLx4ykzu1iSKvcnaj3Y3fe5+6C7D/b29jYlYGAzyFkkEXmLpCFnkTTkLJKGnEWcElHscPf/KelxM/uFyqzrJf1I0t2Sdlfm7Zb01RjCAwAAAAAALSQTdwDr8C8lfc7McpKOSfpNLRZrvmBmN0l6TNLOGOMDAAAAAAAtIDHFDnc/Immwxr+ub3YsAAAAAACgdSXiNBYAAAAAAIB6UewAAAAAAACpQrEDAAAAAACkCsUOAAAAAACQKhQ7AAAAAABAqlDsAAAAAAAAqUKxAwAAAAAApArFDgAAAAAAkCoUOwAAAAAAQKpQ7AAAAAAAAKlCsQMAAAAAAKQKxQ4AAAAAAJAqmWa/oJm9o8bsZyU95O4nmh0PAAAAAABIl6YXOyTdJGmHpPsr06+V9LeSXmpmf+ju/zGGmAAAAAAAQErEUewoS/old39KkszsRZI+LenVkr4tiWIHAAAAAADYsDiu2dG3VOioOCHppe4+I2k+hngAAAAAAECKxDGy4/8zs7+UdFdl+l2Svm1mnZJ+FkM8AAAAAAAgReIodrxP0jsk/Yokk3RA0pfc3SW9LoZ4AAAAAABAijS92OHubmaHJT3r7n9tZnlJXZJONjsWAAAAAACQPk2/ZoeZ3Szpi5L+Q2XWJZK+0uw4AAAAAABAOsVxgdL3SbpO0nOS5O6PSroohjgAAAAAAEAKxVHsmHP34tKEmWUkeQxxAFVKpbJOnp5X2V0nT8+rVCrHHRI2qVx2nTq9oLIv3heKCyqX6W6wMeWyq1BcqMop8gkA0EzlsuvUXGU/NFd7P1TPMmnAsTvWEscFSv+bmX1I0gVm9gZJ/0LSf4khDmBZqVTW9GxRew4e0fjkjIb6urV3V796OnMKwzhqgtisctk1PTunkbEzbXrHzu3a2pHR1i1ZBYHFHSISpFxePJA6ObegD9714HJOjQ73q6ezg3wCAERu8dimqJGxiRX7oQH1dOaW90P1LJMGHLujHnFkwm2SpiQ9JOm3JN0j6fdjiANYVpgvac/BIzp0bFoLZdehY9Pac/CICvOluEPDBhXmSxoZq27TD971oJ4pzNOuWLfCfEnPFOb1wbserMqpkTH6CQBAcywe20yctR+aqNoP1bNMGnDsjnrE8WssZUn7KzegJXR2ZDQ+OVM1b3xyRp0dcQx+QiPkc2HNNr2sOy9LzxcbaJJ8LtRl3fmaOZXPhTFFBQBoJ6sd26zcD9WzTBpw7I56NG1kh5k9ZGYPrnZrVhxALbNzCxrq666aN9TXrdm5hZgiwmYViqWabfr4TEGFIlV/rE+hWNLjM4WaOUU+AQCaYbVjm5X7oXqWSQOO3VGPZp7G8mZJb5H0V5Xbb1Ru92jxp2jXZGahmU2Y2V9Wpl9iZg+Y2aNm9nkzy0UUO1Iunw21d1e/dmzrUSYw7djWo727+pXPpqsK3k7y2VCjw9VtesfO7bown6VdsW75bKgL81ndsXN7VU6NDtNPAACaY/HYZuCs/dBA1X6onmXSgGN31KNp43zc/aeSZGbXuft1K/51m5n9jaQ/rONp9kh6RNLPVaY/JumT7n7QzP69pJskfbqBYaNNhGGgns6c9t14tTo7MpqdW1A+G3KBowQLAlNPZ4f23ziofEeowlxJQSBtyYSpukAXmiMITFu3ZJXNBFU5lc+RTwCA5lg8tslp/+5B5XOhCsWS8tnq/VA9y6QBx+6oRxzZ0Glmv7I0YWa/LKlzrQeZ2aWS3iTpTyvTJun1OjMq5ICktzc8WrSNMAwWf6XDFj/U0FkmXxCYurZkFNjifT6XSd3OHs0TBKZ8LlOVU+QTAKCZgsDU1VHZD3XU3g/Vs0wacOyOtcRxBZebJH3GzP6RJJf0rKT31vG4P5H0ryVtrUz3SPqZuy+dmPWEpEsaHCsAAAAAAEiYppe/3P177v5KSdsl9bt7v7t/f+n/Zrb77MeY2ZslnXD3762cXevpa72mmd1iZofN7PDU1NQm3wEQPXIWSUTeImnIWSQNOYukIWcRp9jG+rj7c+7+bI1/7akx7zpJbzWzSUkHtXj6yp9IeoGZLY1OuVTSk6u81j53H3T3wd7e3s0HD0SMnEUSkbdIGnIWSUPOImnIWcSpFU9sOmfEhrv/G3e/1N37JO2S9E13/w1J90t6V2Wx3ZK+2rQoAQAAAABAS2rFYkfNU1FW8XuSfsfMjmrxGh53RhMS2kGpVNbJ0/Mqu+vk6XmVSuW4Q0INtBPaVbnsOjW3oLJX7str7y438hgA6cT+E0Criqp/iuMCpWs57+WC3f1bkr5V+fuYpGuiDwlpVyqVNT1b1J6DRzQ+OaOhvm7t3dWvns4cV3ZuIbQT0qRcdhXmS3X9NGC57JqeLWpkbGI590eHB9TTmWvoYwCkx8o+pjhf0nOnF9h/AgmznmOFpIry+L4Ve7e/iTsAtJ/CfEl7Dh7RoWPTWii7Dh2b1p6DR1SYL8UdGlagnZAWS4WImw8c1ks//HXdfOCwpmeLq468KMyXNDI2UZX7I2MT5839jTwGQDqc3cecXiiz/wQSZr3HCkkV5fF900d2mNnv1Jj9rKTvufsRd7+12TEBnR0ZjU/OVM0bn5xRZ0crDn5qX7QT0mJlIULSciFi/+5BddXI53wurJn7+Vy46mts5DEA0uHsPubnLsiy/wQSZr3HCkkV5fF9HCM7BiX9tqRLKrdbJL1W0n4z+9cxxANodm5BQ33dVfOG+ro1O7cQU0SohXZCWqy3EFEolmrmfqF4npEdG3gMgHQ4u4957vl59p9AwrTLlxZRHt/HUezokfQqd/+Au39Ai8WPXkm/Kun/iCEeQNnAtHdXv3Zs61EmMO3Y1qO9u/qVTdk5cUlHOyEt1luIyGdDjQ4PVOX+6PCA8tnzjOzYwGMApMPZfcxXJv6h5v6T/gBoXe3ypUU+G0bWP8Ux/uVyScUV0/OSXuzuz5vZXAzxAMplQuVzrk+/+1X6uQuyeu75eWUCUy7DQUAroZ2QFkuFiLMvHrrajj0ITD2dOe3fPVj3Rco28hgA6XB2H3PvD5/Su66+VPtuvFqdHRnNzi0onw25OCnQwtZ7rJBUYRiopzMXSf8UR7HjP0v6WzP7amX6LZLGzKxT0o9iiAdQEJjyuczyhXAyYcCHghZEOyEtNlq8WDpHt95zdTfyGADJt1Yfs3VLNuYIAaylnb60CMNAWyvFjUb2T00/8nH3/8vM7pH0K1r8mdnfdvfDlX//RrPjAZbwoSAZaCekBbkMIEr0MUDysR1vThy/xrJX0ufdfW+zXxsAAAAAAKRfHCfqfV/S75vZUTO7w8wGY4gBAAAAAACkVNOLHe5+wN3/maRrJP1E0sfM7NFmxwEAAAAAANIpzkswXyHpFyX1Sfq7GOMAAAAAAAAp0vRih5ktjeT4Q0kPS7ra3d/S7DgAAAAAAEA6xXFJ17+X9MuStknqkLTdzOTu344hFgAAAAAAkDJxFDtKkr4p6VJJRyRdK+mQpNfHEAsAAAAAAEiZOK7ZMSJpSNJP3f11kgYkTcUQBwAAAAAASKE4ih2n3f20JJlZh7v/naRfiCEOAAAAAACQQnGcxvKEmb1A0lckfcPMnpH0ZAxxAAAAAACAFGp6scPdf73y50fM7H5J/0jSXzU7DgAAAAAAkE5xnMayzN3/m7vf7e7FOOMAJKlUKuvk6XmV3XXy9LxKpXLcIaUK6xdxIfcAILnKZdepuQWVffG+VCpXTZfLHneIiAn7d6wljtNYgJZTKpU1PVvUnoNHND45o6G+bu3d1a+ezpzCMNaaYCqwfhEXcg+N1nfb19a1/OTtb4ooEmzGettRoi3jUC67pmeLGhmbqOrDD373MY1+86iG+ro1Ojygns6cgsDiDhdNxP4d9SATAEmF+ZL2HDyiQ8emtVB2HTo2rT0Hj6gwX4o7tFRg/SIu5B4AJFdhvqSRsYlz+vBfe/nFy9MjYxP06W2I/TvqQbEDkNTZkdH45EzVvPHJGXV2MPipEVi/c5sUkwAAIABJREFUiAu5BwDJlc+FNfvwKy7qqprO58Jmh4aYsX9HPSh2AJJm5xY01NddNW+or1uzcwsxRZQurF/EhdwDgOQqFEs1+/CjJ05VTReKfJvfbti/ox4UOwBJ+Wyovbv6tWNbjzKBace2Hu3d1a98lm8KGoH1i7iQewCQXPlsqNHhgXP68HsfPr48PTo8QJ/ehti/ox6M8wEkhWGgns6c9t14tTo7MpqdW1A+G3KBowZh/SIu5B4AJFcQmHo6c9q/e1D5XKhCsaQLMoHe+5ptuvX6K1UolpTPhlyctA2xf0c9KHYAFWEYaGulg9y6JRtzNOnD+kVcyD0ASK4gMHVVrsOwfF/p07u4PkNbY/+OtVD6AgAAAAAAqZKIYoeZXWZm95vZI2b2QzPbU5nfbWbfMLNHK/cXxh0rAAAAAACIVyKKHZIWJH3A3X9J0rWS3mdmV0m6TdJ97n6lpPsq0wAAAAAAoI0lotjh7sfd/fuVv09KekTSJZLeJulAZbEDkt4eT4QAAAAAAKBVJKLYsZKZ9UkakPSApBe5+3FpsSAi6aJVHnOLmR02s8NTU1PNChXYMHIWSUTeImnIWSQNOYukIWcRp0QVO8ysS9KXJL3f3Z+r93Huvs/dB919sLe3N7oAgQYhZ5FE5C2ShpxF0pCzSBpyFnFKzO81mVlWi4WOz7n7lyuznzKzi939uJldLOlEfBECAAAkQ99tX1v3YyZvf1MEkQAAEI1EjOwwM5N0p6RH3P0TK/51t6Tdlb93S/pqs2MDAAAAAACtJSkjO66T9B5JD5nZkcq8D0m6XdIXzOwmSY9J2hlTfAAAAAAAoEUkotjh7t+RZKv8+/pmxgIAAAAAAFpbIk5jAQAAAAAAqBfFDgAAAAAAkCoUOwAAAAAAQKpQ7AAAAAAAAKlCsQMAAAAAAKQKxQ4AAAAAAJAqFDsAAAAAAECqUOwAAAAAAACpQrEDAAAAAACkCsUOAAAAAACQKpm4AwAAAMDm9N32tZZ8jcnb3xRBJAAArI2RHQAAAAAAIFUodgAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVKHYAAAAAAIBUodgBAAAAAABShWIHAAAAAABIFYodAAAAAAAgVSh2nKVcdp2aW1DZK/dljzsk4LzIWSQReQsArYe+GUlCvmItmbgDaCXlsmt6dk4jY0c0Pjmjob5ujQ73q6ezQ0FgcYcHnIOcRRKVSmVNF4raU5W3A+rpzJG3ANBE5bKrMF9SPhfq9HxJs3MLZx1T0DcjfivztFAsKZ8NJUnTs0WNjE2Qr1gVIztWKBRLGnvgMX3krS/Tj//ojfrIW1+msQceU6FYijs0oCZyFklTLrtmiyUdPCdvf6rCPHkLAFE5+1vwUqms6dmibj5wWC/98Nd14rnFL08OHZvWQtl16Ni0RsYm6JvRNLVGaix+sXcmT28+cFjTs0UViiWNjE2QrzgvRnascEEu0Duvvky/e9cPliuEH9/5Sl2QoyaE1kTOImkK84vfyPxv11yu9x888+3hx965XRdkyVsAaJS1Rm3sHe7XwQce06Fj05Kky7rzGp+cqXqO8ckZ5XNhHOGjzaw2WrmzI7Nc1JC0XNT43M2vJl+xJo4sVygUS/rdu35QVSH83bt+wLfkaFnkLJLmgmyg2fmS3n+w+tvD3/vSg+QtADTI2d+G1xq1sWfsiH7t5RcvP+boiVMa6uuuep6hvm76ZjTF4kiNs0cWHVG57DWLGoW5EvmKNVHsWKGzI1NzY+rsYAAMWhM5i6QpFEvqIm8BIFKF+eoh/quN2rjioq7l6U/df1R37NyuHdt6lAlMO7b1aHR4YPn6CECU8h1h7ZEaHZmaRY0gkEaHB8hXnFcqih1mdoOZ/djMjprZbRt9nlUrhHNUCNGayFkkTWdHhm8PASBi+Vz1B8fV+t3ZuYXlD4tTJ+e0tSOj/TcO6id//Ebt3z3IxR7RNOc7pq1V1NiSCdXTmdP+3eQrVpf4YoeZhZI+JemNkq6SNGxmV23kuYJA51S079i5XUHi1xLSipxF0hSKJd378HF97J3Vebt3uJ9vYwCgQQrF6g+Oq43a6MyFVR8Wt27JqmtLRoGZujoyfHBE05zvmHa1okYQVPKUfMUq0jBm+BpJR939mCSZ2UFJb5P0o/U+0ZZMqK0dGX30Ha/QZd15PT5T0NaOjLZkOABHayJnkTT5bKjhV79YYw/8VB9568t0xUVdmp1bUGcu5CAFABoknw01Ojyw/LOcK0dt5DvO/HxnEJi6wsVvSLo4lRAxOt8x7VJRQyJPsT5pyJZLJD2+YvoJSa/eyBMFgWnrlqzCMJCZ9MKtHcs7AqAVkbNImiAw9XTm9N7XbFM+Fy5fw4OcBYDGWepr9+8eXO5rVx4f8IERrYZjWkQhDYPda20BXrWA2S1mdtjMDk9NTZ33yRgOhVZAziKJ6s1bchatYj19LdAKOD5A0pCziFMaih1PSLpsxfSlkp5cuYC773P3QXcf7O3tbWpwwEaQs0gi8hZJQ84iachZJA05izilodgxLulKM3uJmeUk7ZJ0d8wxAQAAAACAmCT+hD13XzCzWyXdKymU9Bl3/2HMYQEAAAAAgJgkvtghSe5+j6R74o4DAAAAAADELw2nsQAAAAAAACwzd197qRQxsylJP11jsRdKeroJ4cSJ97h5T7v7DRE+v6S6c1ZqjzbdrHZfR03JWWnNvG33dlgL6+eMVsjZpLQHcTbeRmKNO2eTtH5XSmLcSYxZqh13qx3Ttrqktv16tfL7rCtn267YUQ8zO+zug3HHESXeY/q02/vdCNZRa6Adzo/101qS0h7E2XhJinVJEmOWkhl3EmOWkht3K2mXdZiG98lpLAAAAAAAIFUodgAAAAAAgFSh2FHbvrgDaALeY/q02/vdCNZRa6Adzo/101qS0h7E2XhJinVJEmOWkhl3EmOWkht3K2mXdZj498k1OwAAAAAAQKowsgMAAAAAAKQKxQ4AAAAAAJAqFDsAAAAAAECqUOwAAAAAAACpQrEDAAAAAACkCsUOAAAAAACQKhQ7AAAAAABAqlDsAAAAAAAAqUKxAwAAAAAApArFDgAAAAAAkCoUOwAAAAAAQKpQ7AAAAAAAAKlCsQMAAAAAAKQKxQ4AAAAAAJAqFDsAAAAAAECqtF2x44YbbnBJ3Lg14tYU5Cy3Bt6ahrzl1qBb05Cz3Bp0axpyllsDb01BznJr4K0uiSh2mNkWM/uumf3AzH5oZv9nZf5LzOwBM3vUzD5vZrm1nuvpp5+OPmCggchZJBF5i6QhZ5E05CyShpxFsyWi2CFpTtLr3f2Vkvol3WBm10r6mKRPuvuVkp6RdFOMMQIAAAAAgBaQiGKHLzpVmcxWbi7p9ZK+WJl/QNLbYwgPAAAAAAC0kEQUOyTJzEIzOyLphKRvSPofkn7m7guVRZ6QdElc8QEAAAAAgNaQmGKHu5fcvV/SpZKukfRLtRar9Vgzu8XMDpvZ4ampqSjDBBqCnEUSkbdIGnIWSUPOImnIWcQpMcWOJe7+M0nfknStpBeYWabyr0slPbnKY/a5+6C7D/b29jYnUGATyFkkEXmLpCFnkTTkLJKGnEWcElHsMLNeM3tB5e8LJP1TSY9Iul/SuyqL7Zb01XgiRBqUy65Tcwsqe+W+XPevGqFF0aZoNHIKOIPtAUCc6IOwlszai7SEiyUdMLNQiwWaL7j7X5rZjyQdNLM/kjQh6c44g0Rylcuu6dmiRsYmND45o6G+bo0OD6inM6cgsLjDwwbQpmg0cgo4g+0BQJzog1CPRIzscPcH3X3A3be7+8vd/Q8r84+5+zXufoW773T3ubhjRTIV5ksaGZvQoWPTWii7Dh2b1sjYhArzpbhDwwbRpmg0cgo4g+0BQJzog1CPRBQ7gKjlc6HGJ2eq5o1PziifC2OKCJtFm6LRyCngDLYHAHGiD0I9KHYAkgrFkob6uqvmDfV1q1CkOpxUtCkajZwCzmB7ABAn+iDUg2IHICmfDTU6PKAd23qUCUw7tvVodHhA+SzV4aSiTdFo5BRwBtsDgDjRB6EeSblAKRCpIDD1dOa0f/eg8rlQhWJJ+WzIBY4SjDZFo5FTwBlsDwDiRB+EelDsACqCwNTVsbhJLN0j2WhTNBo5BZzB9gAgTvRBWAunsQAAAAAAgFSh2AFUlMuuU3MLKnvlvuxxh4QGoF3RKOQScC62CwBxof/BWhjvA2ixs5yeLWpkbELjkzMa6uvW6PCAejpznPuXYLQrGoVcAs7FdgEgLvQ/qAcjOwBJhfmSRsYmdOjYtBbKrkPHpjUyNqHCPD9flWS0KxqFXALOxXYBIC70P6gHxQ5AUj4Xanxypmre+OSM8jl+virJaFc0CrkEnIvtAkBc6H9QD4odgKRCsaShvu6qeUN93SoUqQ4nGe2KRiGXgHOxXQCIC/0P6kGxA5CUz4YaHR7Qjm09ygSmHdt6NDo8oHyW6nCS0a5oFHIJOBfbBYC40P+gHlygFNDi73T3dOa0f/eg8rlQhWJJ+WzIBY4SjnZFo5BLwLnYLgDEhf4H9aDYAVQEgamrY3GTWLpH8tGuaBRyCTgX2wWAuND/YC2cxgIAAAAAAFIlEcUOM7vMzO43s0fM7Idmtqcy/yNm9g9mdqRy+2dxxwoAAAAAAOKVlPE+C5I+4O7fN7Otkr5nZt+o/O+T7v7xGGMDAAAAAAAtJBHFDnc/Lul45e+TZvaIpEvijQoAAAAAALSiRJzGspKZ9UkakPRAZdatZvagmX3GzC6MLTAAAAAAANASElXsMLMuSV+S9H53f07SpyX9vKR+LY78+LerPO4WMztsZoenpqaaFi+wUeQskoi8RdKQs0gachZJQ84iTokpdphZVouFjs+5+5clyd2fcveSu5cl7Zd0Ta3Huvs+dx9098He3t7mBQ1sEDmLJCJvkTTkLJKGnEXSkLOIUyKKHWZmku6U9Ii7f2LF/ItXLPbrkh5udmwAAAAAAKC1JOICpZKuk/QeSQ+Z2ZHKvA9JGjazfkkuaVLSb8UTHgAAAAAAaBWJKHa4+3ckWY1/3dPsWAAAAAAAQGtLxGksAAAAAAAA9aLYAQAAAAAAUoViBwAAAAAASBWKHQAAAAAAIFUodgAAAAAAgFSh2AEAAAAAAFKFYgcAAAAAAEgVih0AAAAAACBVKHYAAAAAAIBUodgBAAAAAABShWIHAAAAAABIFYodAAAAAAAgVSh2AAAAAACAVKHYAQAAAAAAUoViBwAAAAAASJVEFDvM7DIzu9/MHjGzH5rZnsr8bjP7hpk9Wrm/MO5YAQAAAABAvBJR7JC0IOkD7v5Lkq6V9D4zu0rSbZLuc/crJd1XmQYAAAAAAG0sEcUOdz/u7t+v/H1S0iOSLpH0NkkHKosdkPT2eCIEAAAAAACtIhHFjpXMrE/SgKQHJL3I3Y9LiwURSRfFFxkAAAAAAGgFiSp2mFmXpC9Jer+7P7eOx91iZofN7PDU1FR0AQINQs4iichbJA05i6QhZ5E05CzilJhih5lltVjo+Jy7f7ky+ykzu7jy/4slnaj1WHff5+6D7j7Y29vbnICBTSBnkUTkLZKGnEXSkLNIGnIWcUpEscPMTNKdkh5x90+s+NfdknZX/t4t6avNjg0AAAAAALSWTNwB1Ok6Se+R9JCZHanM+5Ck2yV9wcxukvSYpJ0xxQcAAAAAAFpEIood7v4dSbbKv69vZiwAAAAAAKC1Nb3YYWYPSfKzZj8r6bCkP3L36WbHBAAAAAAA0iOOkR1fl1SS9J8r07sq989J+qykt8QQE6BSqazCfEmdHRnNzi0onw0Vhom4rA3aAPmJRiuXXYViSfmOUIW5koJA2pIJFQSrDaQE0q1cdp1eKKlc1vJ2kc+xTQCID8d/mxNHseM6d79uxfRDZvY37n6dmb07hngAlUplTc8WtefgEY1Pzmior1t7d/WrpzNHh4LYkZ9otHLZNT07p5GxMzl1x87t2tqR0dYtWT7coe2Uy66Tp+d1cm5BH7zrweXtYnS4Xz2dHWwTAJqO47/Ni2MtdZnZq5cmzOwaSV2VyYUY4gFUmC9pz8EjOnRsWgtl16Fj09pz8IgK86W4QwPITzRcYb6kkbHqnPrgXQ/qmcI8eYW2VJgv6ZnCvD5414NV28XIGH0tgHhw/Ld5cYzs+OeSPmNmSwWOk5L+uZl1SvpoDPEA6uzIaHxypmre+OSMOjsScQ1fpBz5iUbL58KaOXVZd17GF9hoQ/lcqMu68zW3i3wujCkqAO2M47/Na/rIDncfd/dXSOqXNODu2939u+4+6+5faHY8gCTNzi1oqK+7at5QX7dm5xhshPiRn2i0QrFUM6cenymoUOQbI7SfQrGkx2cKNbcLtgkAceD4b/OaXuwwsxeZ2Z2SDrr7z8zsKjO7qdlxACvls6H27urXjm09ygSmHdt6tHdXv/JZvs1B/MhPNFo+G2p0uDqn7ti5XRfms+QV2lI+G+rCfFZ37NxetV2MDtPXAogHx3+bF8cYmM9K+jNJH65M/0TS5yXdGUMsgCQpDAP1dOa078arudoxWg75iUYLAlNPZ4f23zjIr7EAWtwmtm7JKpsJqrYLfo0FQFw4/tu8ONbUCyunq5Qlyd0XtPhTtECswjBY/BUCWzzgoSNBKyE/0WhBYOraklFgi/f5XIYPdWhrQWDK5zJV2wXbBIA4cfy3OXGsrVkz65HkkmRm10p6NoY4AAAAAABACsVxGsvvSLpb0s+b2d9I6pX0rhjiAAAAAAAAKdT0Yoe7f9/M/omkX5Bkkn7s7vPNjgMAAAAAAKRT04odZvaOVf71UjOTu3+5WbEAAAAAAID0aubIjrdU7i+S9MuSvlmZfp2kb0mi2AEAAAAAADatacUOd/9NSTKzv5R0lbsfr0xfLOlTzYoDAAAAAACkWxwXKO1bKnRUPCXppWs9yMw+I+nNkk64+8sr8z4i6WZJU5XFPuTu9zQ2XAAAACCZ+m772rqWn7z9TRFFAgDNFUex41tmdq+kMS3+/OwuSffX8bjPSvp3kv78rPmfdPePNzRCAAAAAACQWHH8GsutZvbrkn61Mmufu/9FHY/7tpn1RRkbAAAAAABIviCOF3X3v3D3f1W5VRU6zOzQOp/uVjN70Mw+Y2YX1lrAzG4xs8NmdnhqaqrWIkBLIWeRROQtkoacRdKQs0gachZxiqXYsYYt61j205J+XlK/pOOS/m2thdx9n7sPuvtgb29vA0IEokXOIonIWyQNOYukIWeRNOQs4tSKxQ6ve0H3p9y95O5lSfslXRNdWAAAAAAAIAlasdhRt8rP1i75dUkPxxULAAAAAABoDXH8GstarOZMszFJr5X0QjN7QtIfSHqtmfVrcTTIpKTfalKMAAAAAACgRbViseM9tWa6+3CN2XdGHAsAAAAAAEiY/7+9+4+Ts67vvf/+zOxuktlEZNfggyqcNIWqKJjIBsmNxxuxKkqLypGe5LS3kXJLex7YxNpybqz3qfT0eKRS9STa2oIi2NrEgwXliHeR4g9O2yiJJIYgVTAGoXJIyKKEDOzuzHzuP+baZHYzszu7OzPf63tdr+fjMY+duebX5/p+P/Odaz9zXd+r54exmNklZvaQmf3czJ42s8Nm9vTk/e7OoSgAAAAAAGDeQszZ8RFJF7v7Ce7+PHdf5u7PCxAHMEWt5npmrKKaJ39rbc+VizbQvgiF3EPWkeMA8oixD7MJcRjLE+7+YID3BVqq1VyHjoxr49Zd2rF/VGtWDGnL+tUaHhxQodB0GhnMAe2LUMg9ZB05DiCPGPvQjhB7duw0sy+Y2frkkJZLzOySAHEAR5Unqtq4dZe27zukSs21fd8hbdy6S+WJaujQMoH2RSjkHrKOHAeQR4x9aEeIPTueJ6ks6Y0Ny1zSrQFiASRJpYGiduwfnbJsx/5RlQaKgSLKFtoXoZB7yDpyHEAeMfahHT3fs8PdL2ty+a1exwE0Ko9XtWbF0JRla1YMqTxOdbgTaF+EQu4h68hxAHnE2Id29GzPDjP7T+7+ETP7hOp7ckzh7ht7FQswXam/qL/8zVfpqfKEThkq6dHRsk4s9avUT3W4E2hfhELuIevIcQB5xNiHdvTyMJbJSUl3qkmxAwhtvFrT+2+9v2GSo1WhQ8oU2hehkHvIOnIcQB4x9mE2PTuMxd3/Z3L1+5LeLun3JF2VXP6gV3EAzdQnOdo9bZKj3Uxy1CG0L0Ih95B15DiAPGLsQztCTFD6N6oXOO6XVAvw/sBxmOSou2hfhELuIevIcQB5xNiHdoQ49exBd7/d3X/s7o9MXgLEARzFJEfdRft2R63memasoponf2scITgdudd55F26kOPdR84D6cPYly3dGmdDFDs+aGafNrP1ZnbJ5CVAHMBRS/oK2rxuldauHFZfwbR25bA2r1ulJX0hPiLZU+ovasv61VPad8v61UwitQC1muvQkXG9++ad+uUP/H969807dejIOBvh05B7nUXepQ853l3kPJBOjH3Z0c1xNsRhLJdJeqmkfh07jMUl3RogFkCS9Gylpm33/kTXXPxynXbSUj184Bltu/cn+q1/u1JLixQ8FqpQMA0PDuiGDSMqDRRVHq+q1F9UoWChQ4tW/VjVXdq+75AkJceq7tING0a0dFGIoT2dyL3OIu/ShxzvLnIeSCfGvuzo5jgbYpR+pbufGeB9gZZKA0Vt+frD+tg/PHR0WV/B9J7Xnx4wqmwpFOzogMUG4sJxrGr7yL3OIe/SiRzvHnIeSC/Gvmzo5jgb4ifrb5vZGQHeF2iJ4/4QG3IWIZB3yBtyHgC6q5vjbIhix2sk7TazH5jZHjO738z2zPYkM7vRzA6Y2d6GZUNmdpeZPZT8PbGrkSOzOO4PsSFnEQJ5h7wh5wGgu7o5zobY3+fCeT7vJkmflPS5hmVXS7rb3a81s6uT2//PwsJDHnHcH2JDziIE8g55Q84DQHd1c5ztebFjvqeZdfd7zGzFtMVvlXR+cv1mSd8UxQ7ME8f9ITbkLEIg75A35DwAdFe3xtnYTzPxQnd/XJKSvyc1e5CZXWFmO81s58GDB3saIDAf5CxiRN4iNuQsYkPOIjbkLEKKvdjRFne/3t1H3H1k+fLlocMBZkXOIkbkLWJDziI25CxiQ84ipNiLHU+Y2cmSlPw9EDgeAAAAAAAQWOzFjtslbUiub5D05YCxAAAAAACAFIim2GFmWyVtl/QSM3vMzC6XdK2kN5jZQ5LekNwGAAAAAAA5Fs2U0u6+vsVdr+9pIAAAAAAAINWi2bMDAAAAAACgHRQ7AAAAAABAplDsAAAAAAAAmUKxAwAAAAAAZArFDgAAAAAAkCkUOwAAAAAAQKZQ7AAStZrrmbGKap78rXnokIAZkbOIEXmLmJCvANB93Rpr+zryKkDkajXXoSPj2rh1l3bsH9WaFUPasn61hgcHVChY6PCA45CziBF5i5iQrwDQfd0ca9mzA5BUnqhq49Zd2r7vkCo11/Z9h7Rx6y6VJ6qhQwOaImcRI/IWMSFfAaD7ujnWUuwAJJUGitqxf3TKsh37R1UaKAaKCJgZOYsYkbeICfkKAN3XzbGWYgcgqTxe1ZoVQ1OWrVkxpPI4v94gnchZxIi8RUzIVwDovm6OtRQ7AEml/qK2rF+ttSuH1VcwrV05rC3rV6vUz683SCdyFjEibxET8hUAuq+bYy0TlAKSCgXT8OCAbtgwotJAUeXxqkr9RSYgQ2qRs4gReYuYkK8A0H3dHGspdgCJQsG0dFH9IzH5F0gzchYxIm8RE/IVALqvW2NtJkZtM9sv6bCkqqSKu4+EjQgAAAAAAISSiWJH4nXu/mToIAAAAAAAQFhMUAoAAAAAADIlK8UOl/Q1M/uumV0ROhgAAAAAABBOVood57n7qyS9WdKVZvbaxjvN7Aoz22lmOw8ePBgmQmAOyFnEiLxFbMhZxIacRWzIWYSUiWKHu/80+XtA0m2Szpl2//XuPuLuI8uXLw8RIjAn5CxiRN4iNuQsYkPOIjbkLEKKvthhZoNmtmzyuqQ3Sto739er1VzPjFVU8+RvzTsVKtAV5CxiRN4iZuQvAITHWIzZZOFsLC+UdJuZSfX1+Vt3//v5vFCt5jp0ZFwbt+7Sjv2jWrNiSFvWr9bw4IAKBetkzEBHkLOIEXmLmJG/QGesuPqOOT9n/7UXdSGSqYgrDozFaEf0e3a4+z53f2Vyebm7f2i+r1WeqGrj1l3avu+QKjXX9n2HtHHrLpUnqp0MGegYchYxIm8RM/IXAMJjLEY7oi92dFJpoKgd+0enLNuxf1SlgWKgiICZkbOIEXmLmJG/ABAeYzHaQbGjQXm8qjUrhqYsW7NiSOVxKoRIJ3IWMSJvETPyFwDCYyxGOyh2NCj1F7Vl/SqtXTmsvoJp7cphbVm/SqV+KoRIJ3IWMVrSV9Dm4/J2NXmL1KvVXAVTk3GX/AWAbmk2EWl9G3g1YzFmlIUJSjtqoFjQhy85U6cMlfToaFkDRepBSDdyFjGp1Vyj5Qlt+85PdM3FL9dpJy3VkbGKBgeKTCiGVGucDO+Fz1ukD19ypk4dLqk8VlWJ/AWArphpItLhwQHdsGFEpYGiyuNVlfoZizEVxY4G5Ymqfudv7tP2fYeOLlu7clg3bBjR0kU0FdKHnEVsGicU+9g/PCSpIWcp1CHFGnNXkr60+6dHc5eNawDojulj7+REpJPbupPbu2z3ohm2LBsw0Q1iQ84iNuQsYkXuAkDvMfZiISiBNSiPV7XxgtP0plecrNNOWqqHDzyjO/c+rvJ4lWphDlSrNZUnqhpc1KcjYxWV+osqpvyX5jzmbIz9hGMmJxRbvmyRrnzdaTrtpKV6dLSs5yaqKg1kM2c7pVZzlSeqc9pddz7PQXN5GW8ZYwGE0uw7qzxR325o3It5ciLSLI29edet7x4ypMGSvoLWnXOqNm3bffSYsM2nikPiAAAgAElEQVTrVmlJH1/yWVet1nToyPhxfT88OJDqjby85Wys/YRjSv1F/eVvvkqHxyq66pY9DcffrtLiPv4Rb2WmY5Zbtdl8noPW8jDeMsYCCKXVd9ZQqV9b1q8+bjkTkWZHN797+OZq8Gylpk3bdmv7vkOq1Fzb9x3Spm279WylFjo0dFl5otq078sT6T59Vd5yNtZ+wjGFgqlYKOiqW/ZM6ceNW+nHmTQes3yszXbN2GbzeQ5ay8N4yxgLIJRW31nPVmpHJyL94YferBs2jFC0z5hufvewZ0cDjgnLr8FFfU37fjDlu8flLWdj7SdMVVqUr7zthPl81vM2PnRbHtqTMRZAKDONsQUzJiLNsG5+97BnR4PJY8kbTR4Thmw7MlZp2vdHxiqBImpP3nI21n7CVHnL206YT5vRzp2Vh/ZkjAUQSh7GWDTXze8eSmMNSv1FbVm/Shu37p5yHDnHhGVfqb+ozetWHXesWNr7Pm85G2s/YaolfQVtXr9Km6bkbf6Ov53L5KH1z/rcjlmez3PQWh7ydkkfYyykFVffETqEluYa2/5rL+pSJOi0vG3TtisPE413c/ueYsc0A8WCPnzJmTplqKRHR8saYEKuXDAzlQaK+tRvvkrPW9Kvp5+dUF/BZJb+wSRPORtzP6GuVnONlie07Ts/0TUXv1ynnbRUR8YqGhzI3pf3TOY6eWihYEePWW53g2c+z0FzecjbWs311LMT+u4jo0fH2CNjFS3p42wsAHojT9u07cjLROPFYkHDgwO6/p1nczaWbipPVPU7f3PflFMbrV05rBs2jHB8WMaVJ6p69+e+G13f5y1nY+0nHNM4AdnH/uEhSQ19mKONmsZ2kHR0IraZcrlQmPsxy/N5Do6Xh7ydnpNSwzpm6IwzANIpb9u07ZjPtkKsisWCliXfp8sW93fsdfn2apCHycfQXKx9H2vc85W39c0i+rCOdohLHvorD+sIIL0Yg45HmyxcJoodZnahmf3AzB42s6vn+zpMjJNfsfZ9rHHPV97WN4vowzraIS556K88rCOA9GIMOh5tsnDRFzvMrCjpzyW9WdIZktab2Rnzea3JydzWrhxWX8G0duVw5iYfQ3Ox9n2scc9X3tY3i+jDOtohLnnorzysI4D0Ygw6Hm2ycFk42OccSQ+7+z5JMrNtkt4q6ftzfSEmc8uvWPs+1rjnK2/rm0X0YR3tEJc89Fce1hFAejEGHY82WbgsFDteJOnRhtuPSXr1fF+MydzyK9a+jzXu+crb+mYRfVhHO8QlD/2Vh3UEkF6MQcejTRYm+sNYJDUrbfmUB5hdYWY7zWznwYMHexQWMH/kLGJE3iI25CxiQ84iNuQsQspCseMxSac03H6xpJ82PsDdr3f3EXcfWb58eU+DA+aDnEWMyFvEhpxFbMhZxIacRUhZKHbskHS6mf2imQ1IWifp9sAxAQAAAACAQKI/8MfdK2b2Hkl3SipKutHdHwgcFgAAAAAACCT6YockuftXJX01dBwAAAAAACA8c/fZH5UhZnZQ0iOzPOwFkp7sQTghsY4L96S7X9jF15fUds5K+ejThcp7G/UkZ6VZ8zbv/TAb2ueYNORsLP1BnJ03n1hD52xM7dsoxrhjjFlqHnfatmnTLta+n6s0r2dbOZu7Ykc7zGynu4+EjqObWMfsydv6zgdtlA70w8xon3SJpT+Is/NiinVSjDFLccYdY8xSvHGnSV7aMAvrmYUJSgEAAAAAAI6i2AEAAAAAADKFYkdz14cOoAdYx+zJ2/rOB22UDvTDzGifdImlP4iz82KKdVKMMUtxxh1jzFK8cadJXtow+vVkzg4AAAAAAJAp7NkBAAAAAAAyhWIHAAAAAADIFIodAAAAAAAgUyh2AAAAAACATKHYAQAAAAAAMoViBwAAAAAAyBSKHQAAAAAAIFModgAAAAAAgEyh2AEAAAAAADKFYgcAAAAAAMgUih0AAAAAACBTKHYAAAAAAIBModgBAAAAAAAyhWIHAAAAAADIFIodAAAAAAAgU3JX7LjwwgtdEhcunbj0BDnLpYOXniFvuXTo0jPkLJcOXXqGnOXSwUtPkLNcOnhpS+6KHU8++WToEIA5IWcRI/IWsSFnERtyFrEhZ9FruSt2AAAAAACAbKPYAQAAAAAAMoViBwAAAAAAyBSKHQAAAAAAIFOiKHaY2Slm9g0ze9DMHjCzTcnya8zsX81sd3J5S+hYAQAAAABAWFEUOyRVJP2+u79M0rmSrjSzM5L7Pu7uq5LLV8OFiNhVKjUdfm5CNXcdfm5ClUotdEhoolqd2k/Van77ibbIl1rN9cxYRTVP/tZmP/PafJ7T7dfsRkzoHMaVqWo1V3m8omeeS3L2uXhztpt926nPNeMDgE7qCx1AO9z9cUmPJ9cPm9mDkl4UNipkSaVS02h5XJu27daO/aNas2JIm9et0lBpQH19sdQEs69arenQkeP7aXhwQMVivvqJtsiXWs116Mi4Nm7ddbS/t6xfreHBARUK1rHndCOObseEzmFcmapWqxcFDo9VdNUtexpydpWGBxdFlbPd7NtOfa4ZHwB0WnTfXGa2QtJqSd9JFr3HzPaY2Y1mdmKwwBC1ZytVbdq2W9v3HVKl5tq+75A2bdutZyvV0KGhQXmieT+VJ/LXT7RFvpQnqtq4ddeU/t64ddeM/T2f53Qjjm7HhM5hXJmqPFHVU+UJXXXLnmk5G1+bdLNvO/W5ZnwA0GlRFTvMbKmkv5P0Xnd/WtKnJP2SpFWq7/nx0RbPu8LMdprZzoMHD/YsXsRjcFGfduwfnbJsx/5RDS4Ks/MTOdtc2voppDS2BXnbPaWBYtP+Lg0UO/qcbsTR7ZgWgpydKo3jSkilgaJOGSplIme72bed+lynbXxAZzDOIqRoih1m1q96oePz7n6rJLn7E+5edfeapBskndPsue5+vbuPuPvI8uXLexc0onFkrKI1K4amLFuzYkhHxipB4iFnm0tbP4WUxrYgb7unPF5t2t/l8Rn27JjHc7oRR7djWghydqo0jishlcerenS0nImc7WbfdupznbbxAZ3BOIuQoih2mJlJ+oykB939Yw3LT2542Nsl7e11bMiGJX1FbV63SmtXDquvYFq7clib163Skj5+TUiTUn/zfir156+faIt8KfUXtWX96in9vWX96hn7ez7P6UYc3Y4JncO4MlWpv6gTS/267tKzpuVsfG3Szb7t1Oea8QFAp5l7+mc5NrPXSPpfku6XNDl19B9KWq/6ISwuab+k304mM21pZGTEd+7c2b1gEa1KpaZnK1UNLurTkbGKlvQVZ5uctCezZZGzU1WrNZUnjvVTqb+Yy4nzpHm1Rc9meCNvO69Wc5UnqioNFFUer6rUX5x10r75PKcbcSzg+eRsjzHGTlWruZ6rVFWrSaVFRZXH6rkbY852s287NdZ0Y8xCW9imRWzaytkoDsJ0939U8xXiVLPomL6+gpYlxY1li/sDR4NWisWClhXpJ4m2yJtCwbQ0Ob5+aZvH2c/nOd1+zW7EhM5hXJmqUDCVBo7l6dLF8eZsN/u2U59rxgcAnZTfUj0AAAAAAMgkih0AAAAAACBTKHYAAAAAAIBModgBAAAAAAAyhWIHAAAAAADIFIodAAAAAAAgUyh2AAAAAACATKHYAQAAAAAAMoViBwAAAAAAyBSKHQAAAAAAIFModgAAAAAAgEyh2AEAAAAAADKFYgcAAAAAAMgUih0AAAAAACBTKHYAAAAAAIBModgBAAAAAAAyhWIHAAAAAADIFIodAAAAAAAgUyh2AAAAAACATKHYAQAAAAAAMoViBwAAAAAAyJQoih1mdoqZfcPMHjSzB8xsU7J8yMzuMrOHkr8nho4VAAAAAACEFUWxQ1JF0u+7+8sknSvpSjM7Q9LVku5299Ml3Z3cBgAAAAAAORZFscPdH3f3+5LrhyU9KOlFkt4q6ebkYTdLeluYCAEAAAAAQFpEUexoZGYrJK2W9B1JL3T3x6V6QUTSSeEiAwAAAAAAaRBVscPMlkr6O0nvdfen5/C8K8xsp5ntPHjwYPcCBDqEnEWMyFvEhpxFbMhZxIacRUjRFDvMrF/1Qsfn3f3WZPETZnZycv/Jkg40e667X+/uI+4+snz58t4EDCwAOYsYkbeIDTmL2JCziA05i5CiKHaYmUn6jKQH3f1jDXfdLmlDcn2DpC/3OjYAAAAAAJAufaEDaNN5kv4vSfeb2e5k2R9KulbS/zCzyyX9RNKlgeIDAAAAAAApEUWxw93/UZK1uPv1vYwFAAAAAACkWxSHsQAAAAAAALSLYgcAAAAAAMiUKA5jAQAAAABk34qr75jzc/Zfe1EXIkHs2LMDAAAAAABkSpA9O8zsREmnNL6/u98XIhYAAAAAAJAtPS92mNmfSHqXpB9J8mSxS7qg17EAAAAAAIDsCbFnx69L+iV3Hw/w3gAAAAAAIONCzNmxV9LzA7wvAAAAAADIgRB7dnxY0i4z2ytpbHKhu18cIBYAAAAAAJAxIYodN0v6U0n3S6oFeH8AAAAAAJBhIYodT7r7lgDvCwAAAAAAciBEseO7ZvZhSbdr6mEsnHoWAAAAAAAsWIhix+rk77kNyzj1LAAAAAAA6IieFzvc/XW9fk8AAAAAAJAfPS92mNkfNVvu7v+l17EAAAAAAIDsCXEYy5GG64sl/aqkBwPEAQAAAAAAMijEYSwfbbxtZn+m+mSlAAAAAAAAC1YIHYCkkqSVoYMAAAAAAADZEGLOjvtVP/uKJBUlLZfEfB0AAAAAAKAjQszZ8asN1yuSnnD3SoA4AAAAAABABvX8MBZ3f0TSY5ImVN+z4xfM7NRexwEAAAAAALIpxGEsvyvpg5KekFRLFruks3odCwAAAAAAyJ4QE5RukvQSd3+5u5+ZXGYtdJjZjWZ2wMz2Niy7xsz+1cx2J5e3dDVyZFqlUtPh5yZUc9fh5yZUqdRmfxJ6rlZzPTNWUc2TvzWf/UkZUK1Ozc9qlfyMXehcrtVczzyXvP9zFZXH8/N5QnOhczK0Ws1VHq9M+VzE3AZ578/54LsWyJYQc3Y8Kunn83jeTZI+Kelz05Z/3N3/bKFBId8qlZpGy+PatG23duwf1ZoVQ9q8bpWGSgPq60vDSYsg1TfcDh0Z18atu47205b1qzU8OKBCwUKH1zXVak2Hjhyfn8ODAyoWyc8Yhc7l+vuPaePWYzl13aVnadmiPi1b3J/pzxOaC52TodVq9X9uD49VdNUtexraYJWGBxdF1wZ578/54LsWyJ4Qn9x9kr5pZu83s/dNXmZ7krvfI2m0++Ehj56tVLVp225t33dIlZpr+75D2rRtt56tVEOHhgbliao2bt01pZ82bt2l8kS2+6k80Tw/s77eWRY6l+vvPzWnrrplj54qT5BXORU6J0MrT1T1VHlCV92yZ1obxDnW5r0/54PvWiB7QhQ7fiLpLkkDkpY1XObrPWa2JznM5cRmDzCzK8xsp5ntPHjw4ALeClk1uKhPO/ZPraXt2D+qwUUhdn4iZ1spDRSb9lNpoBgoot5IW362Qt62L3Qut3r/U4ZKmf88NSJnjwmdk6GVBoo6ZaiU+jZoN2fz3p/zEct3bWwYZxFSiLOx/HGzy+T9ZvaJObzcpyT9kqRVkh6X9NEW73m9u4+4+8jy5csXFD+y6chYRWtWDE1ZtmbFkI6MhTkrMjnbXHm82rSfyuPZ/tUlbfnZCnnbvtC53Or9Hx0tZ/7z1IicPSZ0ToZWHq/q0dFy6tug3ZzNe3/ORyzftbFhnEVIaTwA7bx2H+juT7h71d1rkm6QdE73wkKWLekravO6VVq7clh9BdPalcPavG6VlvTxC0ialPqL2rJ+9ZR+2rJ+tUr92e6nUn/z/Mz6emdZ6Fyuv//UnLru0rN0YqmfvMqp0DkZWqm/qBNL/bru0rOmtUGcY23e+3M++K4Fsifq/bLM7GR3fzy5+XZJe2d6PNBKX19BQ6UBXf/OszW4qE9Hxipa0ldkctKUKRRMw4MDumHDiEoDRZXHqyr1FzM/2VqxWNDw4NT8LPUXmTAtYqFzuf7+i3TDO0dUWlRUeayqQkFa3Jf9zxOaC52ToRUKpmWL+9XfV5jyuSgNxNkGee/P+eC7FsieaIodZrZV0vmSXmBmj0n6oKTzzWyVJJe0X9JvBwsQ0evrK2hZUtxYtrg/cDRopVAwLU2On12ao+Noi8WClhXJzywJncuFgmnp4uT9F+fns4TWQudkaIWCqTRwbL1j/1zkvT/ng+9aIFvSOPI1LTm7+/omiz/T5VgAAAAAAEBk0rhf1ubQAQAAAAAAgHj1fM8OMxuR9AFJ/yZ5f5Pk7n6W6ldu6nVMAAAAAAAgO0IcxvJ5SVdJul9SLcD7AwAAAACADAtR7Djo7rcHeF8AAAAAAJADIYodHzSzT0u6W9LY5EJ3vzVALAAAAAAAIGNCFDsuk/RSSf06dhiLS6LYAQAAAAAAFixEseOV7n5mgPcFAAAAAAA5EOLUs982szMCvC8AAAAAAMiBEHt2vEbSBjP7sepzdkw59SwAAAAAAMBChCh2XBjgPQEAAAAAQE70/DAWd39E0vMl/VpyeX6yDAAAAAAAYMF6Xuwws02SPi/ppOTyN2b2u72OAwAAAAAAZFOIw1gul/Rqdz8iSWb2p5K2S/pEgFgAAAAAAEDGhDgbi0mqNtyuJssAAAAAAAAWLMSeHZ+V9B0zuy25/TZJnwkQBwAAAAAAyKCeFzvc/WNm9k3VT0Frki5z9129jgMAAAAAAGRTT4sdZlaQtMfdXyHpvl6+NwAAAAAAyIeeztnh7jVJ3zOzU3v5vgAAAAAAID9CzNlxsqQHzOxeSUcmF7r7xQFiAQAAAAAAGROi2PHHAd4TAAAAAADkRIgJSr/V6/cEAAAAAAD50dM5OyTJzC4xs4fM7Odm9rSZHTazp9t43o1mdsDM9jYsGzKzu5LXu8vMTuxu9AAAAAAAIO16XuyQ9BFJF7v7Ce7+PHdf5u7Pa+N5N0m6cNqyqyXd7e6nS7o7uQ0AAAAAAHIsRLHjCXd/cK5Pcvd7JI1OW/xWSTcn12+W9LYFxgYAAAAAACLXszk7zOyS5OpOM/uCpC9JGpu8391vncfLvtDdH0+e/7iZnbTwSAEAAAAAwHytuPqOOT9n/7UXdTSGXk5Q+mvJX5dUlvTGhvtc0nyKHW0xsyskXSFJp556arfeBugYchYxIm8RG3IWsSFnERtyFiH17DAWd7/M3S+TVJT0ew2337eAl33CzE6WpOTvgRbvfb27j7j7yPLlyxfwdkBvkLOIEXmL2JCziA05i9iQswgpxJwdZ7n7zyZvuPtTklbP87Vul7Qhub5B0pcXGBsAAAAAAIhciGJHofEUsWY2pDYOpzGzrZK2S3qJmT1mZpdLulbSG8zsIUlvSG4DAAAAAIAc6+WcHZM+KumfzeyLqs/V8euSPjTbk9x9fYu7Xt/B2AAAAAAAQOR6Xuxw98+Z2U5JF0gySZe4+/d7HQcAAAAAAMimEHt2KCluUOAAAAAAAAAdF2LODgAAAAAAgK6h2AEAAAAAADKFYgcAAAAAAMgUih0AAAAAACBTKHYAAAAAAIBMCXI2FgAAAAAAMNWKq++Y0+P3X3tRlyKJH3t2AAAAAACATKHYAQAAAAAAMoViBwAAAAAAyBSKHQAAAAAAIFModgAAAAAAgEyh2AEAAAAAADKFYgcAAAAAAMgUih0AAAAAACBTKHYAAAAAAIBModgBAAAAAAAyhWIHAAAAAADIFIodAAAAAAAgUyh2AAAAAACATOkLHUAnmNl+SYclVSVV3H0kbEQAAAAAACCULO3Z8Tp3X7XQQket5npmrKKaJ39r3qn4kHKVSk2Hn5tQzV2Hn5tQpVILHVJbYsnZanVq+1ar3W/fWs31zHNJ2zxXUXk8ve2TN73M207lXq3mKo9XpuQU+ZRPaRt3Q4yvEmNsFqUtt5vFVK3WUhdjL7XTR2nsRyCETOzZ0Sm1muvQkXFt3LpLO/aPas2KIW1Zv1rDgwMqFCx0eOiiSqWm0fK4Nm3bfbTvN69bpaHSgPr60lsTjCVnq9WaDh05vn2HBwdULHanfettM6aNW4+953WXnqVli/q0bHF/qtonb3qZt53KvVqt/k/k4bGKrrplT0PcqzQ8uIh8ypG0jbshxleJMTaL0pbbrWLavG6Vtt37E235+sOpiLGX2umjNPYjEEp6/4ubG5f0NTP7rpldMd8XKU9UtXHrLm3fd0iVmmv7vkPauHWXyhPVDoaKNHq2UtWmbbun9P2mbbv1bCXdfR9LzpYnmrdvN+Ost83U97zqlj16qjyRuvbJm17mbadyrzxR1VPlCV11y55pcXc3j5E+aRt3Q4yvk+/LGJstacvtVjFt2rZbb3rFyamJsZfa6aM09iMQSlaKHee5+6skvVnSlWb22sY7zewKM9tpZjsPHjzY8kVKA0Xt2D86ZdmO/aMqDRS7ETNSZHBRX9O+H1wUZuenrOVsiPZt1TanDJVS1z5Zkca87VTulQaKOmWoFMXnDe1rN2cbpW3cDfX9xRgbxnxytl1py22pdUynnbR0yu285Fw7fZS2fuxmzgKzyUSxw91/mvw9IOk2SedMu/96dx9x95Hly5e3fJ3yeFVrVgxNWbZmxZDK41RCs+7IWKVp3x8ZqwSJJ2s5G6J9W7XNo6Pl1LVPVqQxbzuVe+Xxqh4dLUfxeUP72s3ZRmkbd0N9fzHGhjGfnG1X2nJbah3TwweemXI7LznXTh+lrR+7mbPAbKIvdpjZoJktm7wu6Y2S9s7ntUr9RW1Zv1prVw6rr2Bau3JYW9avVqk/H9XiPFvSV9Tmdaum9P3mdau0pC/dfR9Lzpb6m7dvN+Ost83U97zu0rN0Yqk/de2TN73M207lXqm/qBNL/bru0rOmxd3dPEb6pG3cDTG+Tr4vY2y2pC23W8W0ed0q3bn38dTE2Evt9FEa+xEIxdzjnp3XzFaqvjeHVJ9w9W/d/UOtHj8yMuI7d+5s+XrVak3liaoGF/XpyFhFpf5iVyf4QnpUKjU9WznW90v6irNNTtqTWZ6ykrMh4qyfPaOq0qKiymNVFQrS4r5inifo6tmKz5S3tZrruUpVtZqO9k1poHv90qnc63XckJSSnJ1Uq7nKE1Ut6S+oPF7PqfJ4VaX+sHkQ6nuAMbapVOXsbCZzujRQVHm8qiV9BT1bqR29HTq3Y4mxl6a3R7P1b+cx06Rim3bSiqvvmPNr77/2ovmElEpzXf+0rnuX+7GtnI3+bCzuvk/SKzvxWrWaa7Q8wezFOdXXV9CypLixbHF/4GjaE1POFosFLSv2tn0LBdPSxfVhbvIvwmo1S3w3jyXuVO4VCqbSwLE8IqfyJc1nOAgxvkqMsbGbMafNtDTQvGXTFQrHYjn6N8n3tMTYS83aYz6PAfIgfT//BsTsxYgNOYvYkLOIFbmLrCGnAWQdxY4GaZu9GJgNOYvYkLOIFbmLrCGnAWQdxY4GaZu9GJgNOYvYkLOIFbmLrCGnAWQdxY4GzF6M2JCziA05i1iRu8gachpA1jFjTYNCwXTikn5d/86zp5yRI/TEY0Ar5CxiUyiYhkr9+syGEdV88qwmldBhAW0ZHCjqhneOqLSoePSsJ4y3SKt2zmIyPDigGzaM5PbMJgCyjWJHg2q1ptHyuDZt2310VurN61ZpeHAglafyBMhZxKZWcz0zVtHhsYquumVPwxkAVml4cBEb2UilWs11+LkJ8hbRmH6mlY0XnKZ155w6ZXth8swrnLUDQFbx31CD8kRVm7btnjIr9aZtu5mVGqlFziI25YmqnipP6Kpb9kw7AwB5i/QibxGb6WdaedMrTj5ue4EzrwDIOoodDQYX9TWdlXqQSjdSipxFbEoDRZ0yVOIMAIgKeYvYTD/TymknLSV/AeQOxY4GR8YqTWelPsLx5EgpchaxKY9X9ehomTMAICrkLWIz/UwrDx94hvwFkDsUOxqU+ovavG7VlFmpN69bxazUSC1yFrEp9Rd1Yqlf11161rQzAJC3SC/yFrGZfqaVO/c+ftz2AmdeAZB17OveoFgsaHhwYMqZLUr9RSZ6RGqRs4hNoWBatrhf/X2Fo2e1KI/VzxbAJI9IK/IWsSkU7LgzrSzpK3DmFQC5QrFjmmKxoGXJP4rLFvcHjgaYHTmL2BQKptLAsa+fpYv5KkL6kbeITaFgx51pZWmyvcCZVwDkAT//AgAAAACATKHYAQAAAAAAMoViBwAAAAAAyBSKHQAAAAAAIFModgAAAAAAgEwxdw8dQ0+Z2UFJj8zysBdIerIH4YTEOi7ck+5+YRdfX1LbOSvlo08XKu9t1JOclWbN27z3w2xon2PSkLOx9Adxdt58Yg2dszG1b6MY444xZql53Gnbpk27WPt+rtK8nm3lbO6KHe0ws53uPhI6jm5iHbMnb+s7H7RROtAPM6N90iWW/iDOzosp1kkxxizFGXeMMUvxxp0meWnDLKwnh7EAAAAAAIBModgBAAAAAAAyhWJHc9eHDqAHWMfsydv6zgdtlA70w8xon3SJpT+Is/NiinVSjDFLccYdY8xSvHGnSV7aMPr1ZM4OAAAAAACQKezZAQAAAAAAMoViRwMzu9DMfmBmD5vZ1aHjmS8zO8XMvmFmD5rZA2a2KVk+ZGZ3mdlDyd8Tk+VmZluS9d5jZq8KuwbtM7Oime0ys68kt3/RzL6TrOMXzGwgWb4ouf1wcv+KkHF3WlZyt11mdqOZHTCzvQ3L5pzfZrYhefxDZrahYfnZZnZ/8pwtZma9XcPsyluuNtOp/EX3pTVfZ/iev8bM/tXMdieXt6Qg1v3JeLrbzHYmy5rme8AYX9LQZrvN7Gkze28a23Mmac3XRnMZ/9JkrtvWaWBmi83sXjP7XhLzHyfLm24ro7lYc3auYszxdlDsSJhZUdKfS3qzpDMkrTezM8JGNfkiT20AAA3eSURBVG8VSb/v7i+TdK6kK5N1uVrS3e5+uqS7k9tSfZ1PTy5XSPpU70Oet02SHmy4/aeSPp6s41OSLk+WXy7pKXc/TdLHk8dlQsZyt103SZp+bu055beZDUn6oKRXSzpH0gcbBvBPJY+dfF7Xzz2fBznN1WZu0gLzF92X8nxt9T0v1b8DVyWXr4YLcYrXJfFMnsKwVb4H4e4/mGwzSWdLKku6Lbk7je15nJTna6Ob1P74lyZz3bZOgzFJF7j7KyWtknShmZ2r1tvKaO4mxZmzcxVjjs+KYscx50h62N33ufu4pG2S3ho4pnlx98fd/b7k+mHViwEvUn19bk4edrOktyXX3yrpc173bUnPN7OTexz2nJnZiyVdJOnTyW2TdIGkLyYPmb6Ok+v+RUmvz9Cv9ZnJ3Xa5+z2SRqctnmt+v0nSXe4+6u5PSbpL9Q2BkyU9z923e31So881vBYWJne52kyH8hfdl9p8neF7Phat8j0NXi/pR+7+SOhA5ii1+dpojuNfasxj2zq45HvjmeRmf3Jxtd5WRhOx5uxcxZjj7aDYccyLJD3acPsxxbXh0JTVD9dYLek7kl7o7o9L9YSWdFLysFjX/b9L+k+SasntYUk/c/dKcrtxPY6uY3L/z5PHZ0Gs/ddpc83vmZY/1mQ5Fo5cbS1r43MWRNH2077nJek9ySFPN6Zkd2OX9DUz+66ZXZEsa5XvabBO0taG22lrz1aiyNcW0pwPx2lz2zoVrH64925JB1T/UedHar2tjPalut8XKqYcnw3FjmOa/cof9alqzGyppL+T9F53f3qmhzZZlup1N7NflXTA3b/buLjJQ72N+2KX5XXrhFbtM9flWDjadu5os3BS3/ZNvuc/JemXVN9l/XFJHw0Y3qTz3P1Vqh9ecaWZvTZ0QK0kcxdcLOmWZFEa27OV1OdrFsxh2zoV3L2aHJ71YtX3/nlZs4f1NiqkWWw5PhuKHcc8JumUhtsvlvTTQLEsmJn1q56on3f3W5PFT0zu/pz8PZAsj3Hdz5N0sZntV31XzQtU39Pj+WbWlzymcT2OrmNy/wk6fpe0WMXYf90w1/yeafmLmyzHwpGrrWVpfM6KVLd9s+95d38i+eemJukG1f+5Ccrdf5r8PaD6PBjnqHW+h/ZmSfe5+xNSOttzBqnO11mkNR+mmOO2daq4+88kfVP1uRhabSujfVH0+1zFnOOtUOw4Zoek05MZigdU343x9sAxzUsyF8VnJD3o7h9ruOt2SZNnnNgg6csNy99pdedK+vnk7kpp5e7vd/cXu/sK1fvq6+7+G5K+IekdycOmr+Pkur8jeXxWKtmZyd0Fmmt+3ynpjWZ2YrJr8hsl3Zncd9jMzk0+S+9seC0sDLnaWmbG5wxJbb62+p6fNp/L2yXtnf7cXjKzQTNbNnld9XF2r1rne2jr1XAIS9racxapzdc2pDUfjprHtnVwZrbczJ6fXF8i6VdUn4eh1bYy2pfafp+vGHO8Le7OJblIeoukH6p+PNsHQsezgPV4jeq7pO2RtDu5vEX1OSrulvRQ8ncoebypPoP3jyTdL2kk9DrMcX3Pl/SV5PpKSfdKelj13VAXJcsXJ7cfTu5fGTruDrdBJnJ3Duu7VfVdiidU/zXr8vnkt6TfSnLiYUmXNSwfUX2j9keSPinJQq9zVi55y9UWbdCR/OXSk75KZb7O8D3/10me7FF9A/XkwHGulPS95PLAZBu2yvfAsZYkHZJ0QsOyVLVnG+uQynydFmPb41+aLjN85lIbu6SzJO1KYt4r6Y+S5U23lbm0bMcoc3Ye6xldjrdzsWTlAAAAAAAAMoHDWAAAAAAAQKZQ7AAAAAAAAJlCsQMAAAAAAGQKxQ4AAAAAAJApFDsAAAAAAECmUOwAAAAAAACZQrEj58zsm2b2LjPbOm35C8zsoJktMrNrzOxdgUIEpkhydoWZ3WRmPzaz3cnln5P7V5jZNwOHCSyYme03sxeEjgOYTTLu7g0dB/LBzC42s6s78Do3mdk7OhET8oXciUdf6ACQCvdJ+jMzK7l7OVn2Dkm3u/uYmQUMDZjRVe7+xdBBAACA3nD32yXdHjoOYCZmVnT3aug48o49OyBJT0u6R9KvNSxbJ2lr84cDQH4kv1r/i5l92sz2mtnnzexXzOyfzOwhMzsnufyzme1K/r4kee77zOzG5PqZyfNLLd5n2My+lrzGX0myhvt+08zuTfZi+iszKybLLzezHyZ7PN1gZp/sQZMgImb2JTP7rpk9YGZXmNl/NLOPNNz/LjP7RHL9Pye5fpeZbTWzP5jhdc82s++Z2XZJVzYsL5rZdWa2w8z2mNlvJ8sLZvYXSRxfMbOv8ssopmtzvH3X5FiX/MK+JRl3982UU1b3STP7vpndIemkhvvONrNvJZ+VO83s5GT5miSPtyd5zR5MOWRm70zy4Htm9tfJ4tdOzzszO9/MvmFmfyvp/mTZ+5Jc3mtm702WzZrnM8RyjZndmHzv7zOzjQ2vubfhcX9gZtck179pZh83s3vM7MEkr29N3uu/dqXRUoJiByZtVb3AITP7BUm/LOkbQSMCZnedHTuM5fOhg0GmnSZps6SzJL1U0n+Q9BpJfyDpDyX9i6TXuvtqSX8k6b8lz/vvkk4zs7dL+qyk327Yg266D0r6x+Q1bpd0qiSZ2csk/XtJ57n7KklVSb+RjNX/WdK5kt6QxAVM91vufrakEUkbJd0q6ZKG+/+9pC+Y2YikfydpdXL/yCyv+1lJG9197bTll0v6ubuvkbRG0rvN7BeT11wh6UxJ/7ek6c8DJs023k53cnL/r0q6dobXfbukl6ieg++W9H9Ikpn1S/qEpHckn5UbJX0oec5nJf1Okuf8Sp9DZvZySR+QdIG7v1LSpuSuVnl3jqQPuPsZZna2pMskvVr17+p3m9nq5HFzzfNGL5X0puS9Ppjk8GzG3f21kv5S0pdVL1K/QtK7zGy4jedHicNYMOkrkv7CzJ4n6dclfZFdrxABDmNBr/zY3Sd/pXlA0t3u7mZ2v+r/wJ0g6WYzO12SS+qXJHevWX3Ooz2S/srd/2mG93itkn9C3f0OM3sqWf56SWdL2mH1wwqXSDqg+kbOt9x9NInrFtUL1UCjjUmxTZJOkfSLkvaZ2bmSHlL9n79/Un0D/svu/qwkmdn/bPWCZnaCpOe7+7eSRX8t6c3J9TdKOqvhF/YTJJ2u+kb8Le5ek/S/zYwfVNDKbOPtdF9K8ur7ZvbCGV73tZK2Jtu3PzWzryfLX6L6P313JWNsUdLjZvZ8Scvc/Z+Tx/2t6v/YIl8uUP3/oiclyd1HkzxplXf3uvuPk+uvkXSbux+RJDO7VdK/Vf0HjbnmeaM73H1M0piZHZA0U95Pmjz0635JD7j748l771P9u+FQG68RHYodkCS5+7Nm9veqV73XSfq9wCEBQJqMNVyvNdyuqf5d+ieSvuHubzezFZK+2fD40yU9I+kX2ngfb7LMJN3s7u+fsvDYP7BAU2Z2vqRfkbTW3ctWn7x5saQvqP7Dxr+oviHuZnOaoMvUPFcn7/tdd79zWiwXzTF85Nds4+1Mj58tj1uNsQ9M30vJzE6c5bWQD63Gu1Z5d6TF8pme306et3puNXl8RVOP2ljc4jmN79Xu+0WLw1jQaKuk96leHfx24FgAICYnSPrX5Pq7Jhcmv4BvVv0XxeFZ5ii4R9JvJM97s6TJDe27Jb3DzE5K7hsys38j6V5J/6eZnWhmfaofggA0OkHSU0mh46Wq70Yt1Q9leZuk9aoXPiTpHyX9mpktNrOlkloWJ9z9Z5J+bmavSRb9RsPdd0r6j5O7VZvZL5vZYPL6/87qc3e8UNL5HVlDoH33SFpn9XllTpb0umT5DyQtN7O1Uv2wFjN7ubs/JelwsheUlBzujdy5W9KvTx7qYWZDc3juPZLeZmalZBx8u6T/1YUYJekJSSdZff6vRWIvJEkZruJgXr4m6WZJn3H3Vr/YAGlynZn9vw23W07oBHTZR1Q/jOV9kr7esPzjkv7C3X9oZpdL+oaZ3ePuB5q8xh9L2mpm90n6lqSfSJK7fz/J86+ZWUHShKQr3f3bZvbfJH1H0k8lfV/Sz7u1gojS30v6HTPbo/o/dN+WJHd/ysy+L+kMd783WbbDzG6X9D1Jj0jaqZnz6TJJN5pZWfUCx6RPq74L9n3J3iIHVS+s/J3qh2TtlfRD1fOWfEUv3ab6IQn3q56D35Ikdx9PCtFbkgJ1n+rzLT2g+hw0N5jZEdX32CNnc8bdHzCzD0n6lplVJe2aw3PvM7ObVP9xQpI+7e67kj1AOx3nhJn9F9XH1h+rvude7hn/0+Zbskvru9x9/wyPuUbSfne/qTdRAa3NlrPJF8hN7n5+z4ICAjGzpe7+TLJnx22SbnT320LHhTg15FNJ9V8kr3D3+7rw+sOqb/yf5+7/u1OvD3TaZM4m16+WdLK7b5rlaQBSgj07AACI1zVm9iuqH5v7NUlfChwP4na9mZ2hej7d3MlCR+IryaSPA5L+hEIHInCRmb1f9f+ZHlHDYYoA0o89O3IuOUvAl5Ljb1s95nxJP3P33b2KC2hltpxNNqTfxp5ISCszu0zHTl036Z/c/coQ8QAzMbM/l3TetMWb3f2zIeIBZmNmZ6p+hqBGY+7+6hDxAPPBtkJnUOwAAAAAAACZwtlYAAAAAABAplDsAAAAAAAAmUKxAwAAAAAAZArFDgAAAAAAkCkUOwAAAAAAQKb8/7TDpbZ6NdDXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Programming\\Anaconda\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c721fd9f98>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(data['chrom_num'], hist_kws={'range':(0,30)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function error definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### calcs error !"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def error(f, x, y, z):\n",
    "#     return sp.sum((f(x,y)-z)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c7228508d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(np.array(x), np.array(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lm = LinearRegression()\n",
    "lm.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "cdf = pd.DataFrame(lm.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = np.rint(lm.predict(x_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[21.]\n",
      " [18.]\n",
      " [28.]\n",
      " [ 5.]]\n",
      "[[25]\n",
      " [15]\n",
      " [25]\n",
      " [ 5]]\n"
     ]
    }
   ],
   "source": [
    "print(predictions)\n",
    "print(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1c722c6ab00>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def root_mean_squared_error(y_true, pred):\n",
    "    print(sqrt(metrics.mean_squared_error(y_true, pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.9154759474226504\n"
     ]
    }
   ],
   "source": [
    "root_mean_squared_error(y_test, predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.25"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.accuracy_score(y_test, predictions)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}