MAT240E: Homework03

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Muhammad Hafiz Wan Rosli\n",
      "# Media Arts & Technology\n",
      "# Music Information Retrieval\n",
      "# MAT240E: Homework03 - Audio Feature Extraction I\n",
      "\n",
      "#import numpy\n",
      "import essentia\n",
      "import essentia.standard\n",
      "import essentia.streaming\n",
      "import os\n",
      "%pylab inline\n",
      "\n",
      "import matplotlib as mpl\n",
      "mpl.rcParams['figure.figsize'] = (16,4)\n",
      "\n",
      "ratm = []\n",
      "evilEmpire = []\n",
      "battleOfLA = []\n",
      "renegades = []\n",
      "\n",
      "ratm_path = './Music/iTunes/iTunes Media/Music/Rage Against The Machine/Rage Against the Machine'\n",
      "evilEmpire_path = './Music/iTunes/iTunes Media/Music/Rage Against The Machine/Evil Empire'\n",
      "renegades_path = './Music/iTunes/iTunes Media/Music/Rage Against The Machine/Renegades'\n",
      "battleOfLA_path = './Music/iTunes/iTunes Media/Music/Rage Against The Machine/The Battle of Los Angeles'\n",
      "\n",
      "for root, dirs, files in os.walk(ratm_path):\n",
      "    tempMono = []\n",
      "    for name in files:\n",
      "        loader = essentia.standard.AudioLoader(filename = os.path.join(root, name))\n",
      "        ratm.append(loader())\n",
      "ratmInd = arange(len(ratm))\n",
      "ratmRMS = []\n",
      "for everyFile in ratm:\n",
      "    tempMono.append(sum(everyFile[0]/2, axis=1))\n",
      "    for everyFileMono in tempMono:\n",
      "        N = float(len(everyFileMono))\n",
      "        ms = sum(everyFileMono**2)/N\n",
      "        rms = sqrt(ms)\n",
      "    ratmRMS.append(rms)\n",
      "\n",
      "#-----\n",
      "for root, dirs, files in os.walk(evilEmpire_path):\n",
      "    tempMono = []\n",
      "    for name in files:\n",
      "        loader = essentia.standard.AudioLoader(filename = os.path.join(root, name))\n",
      "        evilEmpire.append(loader())\n",
      "evilEmpireInd = arange(len(evilEmpire))\n",
      "evilEmpireRMS = []\n",
      "for everyFile in evilEmpire:\n",
      "    tempMono.append(sum(everyFile[0]/2, axis=1))\n",
      "    for everyFileMono in tempMono:\n",
      "        N = float(len(everyFileMono))\n",
      "        ms = sum(everyFileMono**2)/N\n",
      "        rms = sqrt(ms)\n",
      "    evilEmpireRMS.append(rms)\n",
      "\n",
      "#-----\n",
      "for root, dirs, files in os.walk(battleOfLA_path):\n",
      "    tempMono = []\n",
      "    for name in files:\n",
      "        loader = essentia.standard.AudioLoader(filename = os.path.join(root, name))\n",
      "        battleOfLA.append(loader())\n",
      "battleOfLAInd = arange(len(battleOfLA))\n",
      "battleOfLARMS = []\n",
      "for everyFile in battleOfLA:\n",
      "    tempMono.append(sum(everyFile[0]/2, axis=1))\n",
      "    for everyFileMono in tempMono:\n",
      "        N = float(len(everyFileMono))\n",
      "        ms = sum(everyFileMono**2)/N\n",
      "        rms = sqrt(ms)\n",
      "    battleOfLARMS.append(rms)  \n",
      "    \n",
      "#-----\n",
      "for root, dirs, files in os.walk(renegades_path):\n",
      "    tempMono = []\n",
      "    for name in files:\n",
      "        loader = essentia.standard.AudioLoader(filename = os.path.join(root, name))\n",
      "        renegades.append(loader())\n",
      "renegadesInd = arange(len(renegades))\n",
      "renegadesRMS = []\n",
      "for everyFile in renegades:\n",
      "    tempMono.append(sum(everyFile[0]/2, axis=1))\n",
      "    for everyFileMono in tempMono:\n",
      "        N = float(len(everyFileMono))\n",
      "        ms = sum(everyFileMono**2)/N\n",
      "        rms = sqrt(ms)\n",
      "    renegadesRMS.append(rms)\n",
      "\n",
      "\n",
      "ax = plt.subplot(111)\n",
      "width = 0.2\n",
      "w = 0.2\n",
      "figure_title = \"RMS comparison of Rage Against the Machine albums\"\n",
      "plt.text(0.3, 1.2, figure_title,\n",
      "         horizontalalignment='center',\n",
      "         fontsize=20,\n",
      "         transform = ax.transAxes)\n",
      "xlabel('Tracks')\n",
      "ylabel('RMS')\n",
      "grid()\n",
      "ax.bar(ratmInd, sorted(ratmRMS),width,color = 'k')\n",
      "ax.bar(evilEmpireInd-w, sorted(evilEmpireRMS),width, color = 'r')\n",
      "ax.bar(battleOfLAInd-(2*w), sorted(battleOfLARMS),width,color = 'g')\n",
      "ax.bar(renegadesInd-(3*w), sorted(renegadesRMS),width, color = 'b')\n",
      "xticks(renegadesInd+width-(2*w), renegadesInd );\n",
      "ax.legend (('Rage Against the Machine', 'Evil Empire', 'Battle of Los Angeles', 'Renegades of Funk'),bbox_to_anchor=(0., 1.02, 1., .102), loc=3,\n",
      "       ncol=4, mode=\"expand\", borderaxespad=0.)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "<matplotlib.legend.Legend at 0x113673f90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAA7EAAAFCCAYAAAAnulrHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XdUFNfbB/DvLL2zFBERBEVRsIsFUAGNXbEgVlCwt/ws\n0Rg7GjWWFLsRNALR2BWwd+yK2EtUFAHFhvQi/b5/+O7IsLsUBXHJ8zmHozv3ztz7TL8zd2Y4xhgD\nIYQQQgghhBCiAESVXQFCCCGEEEIIIaS0qBFLCCGEEEIIIURhUCOWEEIIIYQQQojCoEYsIYQQQggh\nhBCFQY1YQgghhBBCCCEKgxqxhBBCCCGEEEIUBjViiUIICAiASCRCYGBgZVflqzlx4gQcHR2hr68P\nkUiEvn37VnaVSDGq0jrq7e0NkUiE2NjYyq7KN+lzlnVVmKdhYWEQiURYuHChYLiLiwtEIjqdIIQQ\n8vUo3FFHJBIJ/pSVlWFoaAhXV1e5JxTR0dF8fh0dHaSnp8vMxxhDnTp1+Lznzp2TynPy5En07dsX\nNWrUgJqaGgwMDGBjYwMPDw+sXbu2XGMln3Acx//9F0RHR6N3796IiYnBqFGj4Ovri8GDBxc7juQE\ns/CfqqoqzMzM4O7ujgsXLnyl2n89S5Ys4WN98uRJpdalMtbRz208+Pr6QiQS4fz583LzVOa2Jlmm\nSkpKiIqKkpvP1dWVz1sZFw/KMo+q0v5LVhxVJTZCCCGKQbmyK/A5OI7DggULAAC5ubmIjIzEgQMH\ncO7cOVy/fh3r1q2TOZ6ysjIyMjKwY8cOjB49Wir99OnTeP78OZSVlZGfny91UF66dCnmzp0LFRUV\ndO3aFTY2NlBSUsLTp09x/vx57N+/HxMnTqQr0hWgb9++cHBwQPXq1Su7Kl/FqVOnkJ2djd9++w2D\nBg0q07iWlpbw9vYGAGRmZiIiIgIHDhxAcHAwdu7cCQ8Pjwqo8dfHGMPmzZv53/7+/li5cmWl1aey\n1tGKajwwxipkuqWlrKyMvLw8bNmyBUuWLJFKj4yMxLlz5/h833oj6pdffsGsWbNQo0aNyq4KIYQQ\novAUshELAPPnzxf8vnz5Mtq3b4+NGzfihx9+gJWVldQ4LVq0QExMDPz9/WU2Yv39/aGmpoYOHTrg\n6NGjgrSYmBjMnz8fenp6uHjxIuzs7ATpjDGcOnWKGrAVRFdXF7q6upVdja/m1atXAABTU9Myj2tp\naSm1fSxfvhyzZs3Cjz/+WGUasSdOnEBMTAyGDRuGo0ePIjAwEEuXLoWKikql1EcR19HKbqgWx8TE\nBKampti6dSsWLVoEJSUlQbrkAkavXr1w4MCByqhimVSvXv0/cxGOEEIIqWhVpsXl6OgIGxsbMMZw\n8+ZNmXmUlZXh4+ODiIgI3L17V5D2/v17BAcHo3///jAwMJAa99q1aygoKICrq6tUAxb4eDekU6dO\nZapzYmIi5syZg4YNG0JLSwv6+vpo2rQpZs2ahczMTEHeyMhIDBs2DGZmZlBTU4OZmRmGDx+Op0+f\nSk1X0lXw3Llz2LFjB+zt7aGlpYUaNWrghx9+QE5ODoCPd/ucnZ2hq6sLsVgMLy8vJCYmSk3P0tIS\nVlZWSE1NxaRJk2BmZgYNDQ3Y2dnJ7UIdEBAAd3d31K5dG5qamtDT00Pbtm2xfft2mfkl3SJzc3Ox\naNEi2NjYQF1dHT4+Pvz0ZHUZvHv3LgYPHgxLS0uoq6ujWrVqaNGiBaZOnYq8vDxB3pSUFMyaNQs2\nNjbQ0NCAgYEBunbtitOnT0vVp/CzX7dv30aPHj2gr68PLS0tuLi44MqVKzLjKM7u3bvRvn176Onp\nQVNTE40bN8ayZcv45VG4XF9fXwDC7pLFdf0syciRIwEAsbGxSEhIEKQFBwfD09MT9erVg7a2NrS1\ntWFvb4+1a9fKbeQ8efIE7u7uEIvF0NbWhpOTE44cOVLss4IvX77EpEmTULt2bairq8PIyAi9e/dG\nRETEZ8Xk7+8PABgzZgyGDh2K9+/fF9uYef36NXx8fFCtWjVoamqiWbNmCAoKkvuc340bNzB58mQ0\nadIEhoaG0NDQQL169TB9+nQkJydLTV9e7JLtJzMzEzNmzICFhQXU1dVRt25drFixQmZdQ0ND0bFj\nR5iamkJdXR1mZmZwcXHBxo0bAXx6ROL8+fNgjAm6kLu6uhY73ywtLbFo0SIAwvVL1gU4xhg2bdqE\nRo0aQUNDA9WrV8fYsWORmpoqc9rluYw5jsPo0aPx5s0bHDp0SJCWm5uLgIAAODk5wdbWVub4ZV1+\nErt27ULHjh1hYGAADQ0NWFlZYciQIbhx44ZUXsYYzp49CxcXF+jq6kJPTw89e/bEo0ePpPLKeiZW\nshx9fHwQHR2NQYMGwcjICBoaGmjZsiUOHz4st547duyAq6sr9PX1oaGhAVtbWyxZskSwPynJkydP\n8NNPP8He3h7GxsZQV1eHpaUlxo4di7i4uFJPRyInJwdz586FlZUV1NXVYW1tjUWLFiE3N1eQr3Dc\nssjqJl94O42IiEDXrl2hr68PsVgMd3d3vHjxAgDw7NkzDBw4EMbGxtDU1ISrq6vU8R4A3r59i+nT\np8PGxgba2toQi8WoX78+fHx88Pz58zLHTggh5OtS2DuxxVFTU5M5nOM4jBo1CsuWLYO/v7+gARYY\nGIjc3FyMHj0afn5+UuMaGRkB+HiALCgo+OI7rs+fP4erqytiY2Nhb2+PCRMmoKCgAI8fP8aqVasw\nfvx4WFhYAACuX7+O7777Dunp6ejduzdsbW3x77//Ytu2bQgJCcGpU6dgb28vVcbatWtx9OhR9O3b\nF66urjh+/Dj++OMPxMfHw83NDZ6enujZsyfGjRuHS5cuYfv27UhISMCRI0ek5ltOTg46duyI1NRU\nDBkyBNnZ2di3bx8mT56Mx48fS3XhnjBhAho2bAgXFxeYmpri/fv3OHLkCLy8vPD48WP+JLqofv36\nISIiAt27d0e/fv1QrVo1qbpI3L17F61bt4aSkhLc3Nz4hnZkZCQ2btyIJUuWQFn54yqenJwMJycn\n/Pvvv2jVqhXc3d0RHx+P3bt3o3Pnzti4cSPGjBkjVZ+IiAisWLECjo6OGDNmDGJiYrBv3z507NgR\nt2/fRr169UqxtIHZs2dj2bJlMDY2hqenJ7S1tXHkyBHMnj0bx48fx4kTJ6CiogIrKyssWLAAYWFh\nOHfuHLy9vWFpaQkAqFWrVqnKkqVwY7To9jFr1iwoKSnBwcEBZmZmSElJwenTpzF58mRcv34dQUFB\ngvyPHj2Co6MjkpOT0bNnTzRu3BjPnj1D37590b17dwDSXVxv3ryJzp07IykpCV27dkX//v0RHx+P\n4OBgtG3bFgcOHEC3bt1KHc/bt28RGhqKevXqwdHRETo6Oli1ahX8/PwwYMAAqfzv3r2Dg4MDYmNj\n4ezsDEdHR7x+/RoTJkzgLz4VrbO/vz+Cg4Ph4uKCzp07o6CgABEREfj9999x9OhRXLt2Ddra2lJl\nFZ0Ox3HIzc1F586d8fr1a/To0QPKyso4cOAAfvrpJ2RlZQnunPv5+WHcuHEwNTVF7969YWRkhHfv\n3uHOnTsICAjA+PHjIRaLsWDBAgQEBCAmJoa/6AGAX1/kmTp1KoKDg6XWL1lmzJiBEydOwM3NDV27\ndsWZM2fg7++Pp0+fSl38Ke9lDACDBw/GtGnTsHnzZvTu3ZsfHhoaivj4eKxcuVLus9BlXX6MMfj4\n+CAoKAjGxsbo378/jI2N8eLFC4SFhaF+/fpo0aKFoIxDhw4hJCQE3bt3x/jx4/HgwQMcOXIE169f\nx8OHD2FoaCjIL6/Lc0xMDFq3bo06depg+PDhSEhIwK5du9C7d2+cOnUKLi4ugvwjRoxAQEAAzM3N\n4eHhAX19fVy5cgXz5s3D6dOncfLkSak717Ls378fmzZtQocOHdC2bVuoqqri/v372Lx5Mw4ePIiI\niIhSd39mjMHDwwMRERHw8PCAiooKgoOD4evri4iICISGhkqNU1wXcHlp169fx/Lly+Hi4oIxY8bg\n7t27OHDgAO7du4cDBw6gffv2sLOzg7e3N6Kjo7F//3506tQJUVFR0NLSAvDxMQsnJydERUWhc+fO\n6N27NxhjiI6ORmhoKDw8PGT25iKEEPINYQqG4zgmEomkhp87d46JRCKmqanJ3r17J0h7/vw54ziO\ntWvXjjHG2HfffcfEYjH78OEDn6d+/frMxsaGMcbY0KFDGcdx7Ny5c3x6RkYGs7S0ZBzHsfbt27O/\n/vqLPXjwgOXl5X1WHA4ODozjOLZs2TKptISEBJaVlcUYY6ygoIDVr1+fiUQi9s8//wjy7dq1i3Ec\nx+rXr88KCgr44QsWLGAcxzF9fX326NEjfnh2djazs7NjIpGIicVidv78eT6toKCAderUiXEcx27f\nvi0op1atWvz8y8nJ4YcnJiayOnXqMI7jBNNijLGoqCipuHJycljHjh2ZiooKi4uLE6Q5OzszjuNY\nkyZNWEJCgtS4W7duZRzHscDAQH7YtGnTGMdxLDQ0VCp/cnKyYJ6MGTOGcRzHxo0bJ8gXGRnJ9PT0\nmJqaGouOjuaHnz17lnEcJ1UmY4xt2rSJcRzHJkyYIFWuLJcvX2Ycx7FatWqxt2/f8sPz8vJYr169\nGMdxbOnSpYJxJMuw8DpYEkmdXV1dpdJ+/vlnxnEca9GihVSarGVVUFDAhg8fzjiOY9euXROkdejQ\ngXEcx/7880/B8KNHj8qcZ7m5uaxOnTpMQ0NDaj159eoVMzMzY6ampiw7O7vUsf7yyy+M4zj2yy+/\n8MOaN2/ORCIRe/r0qVT+ESNGMI7j2E8//SQYfufOHaampsY4jmMLFy4UpMXExAjWIYktW7YwjuPY\n8uXLBcNlraOMfdp+evTowW/XjDH27t07pq+vz/T19Vlubq4gDnV1dRYfHy9VdtFtw9nZWeb+sCQl\nrV+SZV+rVi324sULfnheXh5r37494ziOhYeH88PLexlzHMfMzc0ZY4yNGjWKKSsrs5cvX/LpXbp0\nYfr6+uzDhw9szpw5Mud7WZefZLtu3bo1S01NFaTl5+ez169f878ly1pFRYWdOXNGkHfWrFmM4zi2\nYsUKwXDJPI2JieGHSY5NHMexRYsWCfIfP36ccRzHunfvLhguKdvd3V2wPjHGmK+vL+M4jq1evVoq\nblni4uIE+3SJEydOMCUlJTZ+/HjBcMk+pui2Itl/29jYsOTkZH54VlYWf6z7+++/peL28fGRWS9Z\n63XhfXLRY+HIkSMZx3FMT09Pal8q2fcVniehoaGM4zg2bdo0qbJzc3NZWlqazHoRQgj5dihkI5bj\nOObr68sWLFjAZs+ezQYMGMBUVFSYqqoqCwgIkBqnaCNW0vgLCgpijDF2/vx5xnEcW7lyJWNMdiOW\nMcbu3r3LmjVrxteB4zimoaHBnJ2d2YYNG0p9ghYREcE4jmPNmzcvMe/FixcZx3HMyclJZnq7du2k\nGpGSE9T58+dL5V+0aBHjOI4NHz5cKi0wMFAwXyQkJ+EXL16UGicgIKDYk5Gi9u3bJ7MMyUmQrAYp\nY8U3Yk+cOFFsmdnZ2UxTU5Pp6uqypKQkqfR58+ZJnURKTpgk60xhubm5TFlZmbVs2bLYciVGjRrF\nOI5j/v7+UmlPnjxhSkpKrHbt2oLhX9KItbS0ZAsWLGALFixgM2bMYK6urozjOGZiYsJu3bpV6und\nuHGDcRzHfv75Z35YbGws4ziO1atXT+Y4kgshhZdTcHAw4ziO/fjjjzLHWbVqFeM4jh05cqRU9Soo\nKGB16tRhysrKgosha9euZRzHsZkzZwryZ2dnMw0NDSYWi1l6errU9EaPHi3zxLy48nV1dVnHjh0F\nw4trxIpEIvbs2TOpaQ0bNoxxHMcePHjAD2vevDnT0tKSua4WVdGN2C1btkilSeJcv349P6y8l3Hh\nRuy1a9cE22d0dDQTiURs4sSJjDEmtxErj7zl17BhQyYSiaQu4skimQdeXl5SaZLjjYeHh2B4cY1Y\nKysrmQ1uCwsLZmxsLBjWtGlTpqqqylJSUqTy5+XlMSMjI9aqVasSYyhJo0aNpPZLJTVit23bJjWd\nsLAwqYtrX9KIbd++vVR+yTG8du3aUvMxJiaGcRzHRowYwQ+TNGJnz54tJ3pCCCHfOoXtTlz0+TWR\nSIRt27aV6k2uffr0gZGREfz9/eHl5QU/Pz+oqqryb3SVp1GjRrh58yZu3LiBs2fP4tatW7hy5QrO\nnz+P8+fPw8/PD2fPnoW+vn6x07l69SoAoEuXLiXWVfJ8b4cOHWSmu7q64uLFi7h9+zbatWsnSJPV\nxVjyoqCi3eIA8N3GXr58KZWmoqICR0dHqeGSbm63b98WDI+NjcXy5ctx+vRpvHjxAh8+fBCkS15c\nVBjHcWjVqpXUcHkGDRqENWvWoE+fPujfvz86duwIJycn1KlTR5Dv8ePH+PDhA9q2bStz2XTo0AGL\nFy+WigGQPQ+VlZVhYmKCpKSkUtXz5s2b4DhO5jKsW7cuzMzMEB0djbS0NOjo6JRqmsWJiYmR6q5t\nZGSEs2fPokGDBlL5ExISsHLlShw5cgRRUVFSz2MXfjZOMo8cHBxklu3k5IRTp04JhkmeH46OjhZ0\ne5WIjIwEAPz777+l6m565swZREVFoWvXroKujkOGDMH06dMREBCAxYsX813JHz9+jKysLLRq1Yrv\nTli0zoXfciyRm5uLTZs2YefOnXj48CFSU1NRUFDAp5flmUE9PT3Url1bari5uTkACNYlT09P/PDD\nD7C1tcWgQYPQvn17ODk5wdjYuNTllRdZ63/NmjUBCOtc3su4sFatWqFRo0b466+/MHfuXGzevBmM\nMZkv5yusLMsvIyMDDx48QPXq1dGkSZNS162086ckTZs2ldl91tzcHNeuXeN/Z2Zm4s6dOzA2Nsbv\nv/8uc1qqqqr4999/S132tm3bEBAQgDt37iA5ORn5+fl8mrxHc+RxdnaWGubk5ASRSCRz//o5ijuu\nyZqPso5rLi4uMDMzw7Jly3Dz5k1069YNbdu2RdOmTenljIQQoiAUshHLcRx/oP3w4QMuX76MkSNH\nwtvbG9WrV5d6fqgoVVVVDBs2DL///juuXr2KvXv3ws3NjX/utSQtWrQQNAKvX7+O4cOH486dO1i4\ncCH++OOPYseXvFTEzMysxLJSUlIAyH9LrWS4rBeV6OnpSQ2TnNgXl1b0JRzAx0aQrJMsExMTQT0B\nICoqCq1atUJycjLat2+Prl27Qk9PD0pKSnj+/DkCAwORnZ0tMx7J9EqjZcuWuHDhApYsWYK9e/fi\n77//BgDY2NhgwYIF/AWNkuah5I2hsuahvAsSks8wlUZpluHLly+RnJxcLo1YFxcXnDlzBsDHmPbu\n3YtJkyahS5cuiIiIEDxnnJycjJYtWyI6OhqtW7eGt7c3DAwMoKysjKSkJKxevVqwrCSxyFtOsoZL\nXiS1Z88euXXmOA4ZGRmlik/yzPrw4cMFww0MDNCzZ0/s378fISEhcHd3/+w6A8DAgQMRHByMOnXq\noG/fvqhevTrU1NTAGMOqVavkrsOyFLceARCsS1OnToWRkRE2bNiANWvWYNWqVeA4Ds7Ozli5cqXM\nC1AVRVa9ZdW5vJdxUaNHj8b//vc/HD16FFu3boW9vX2Jjc2yLL+y7JMLK+38+ZzpSKZVuOEtaRjH\nx8fLfa8AUPrPLk2dOhWrV69GjRo10K1bN/6lfQCwdetWwUuoSsJxnMxtSVlZGUZGRnj//n2pp1Wc\n8jiu6ejo4OrVq1iwYAFCQ0Nx/PhxAB+PcxMmTMDcuXP58QghhHybFH4vraGhgY4dO+LgwYNo3rw5\nhg8fjkePHvEHYnlGjx6N33//HR4eHsjOzpb5Up/SatmyJdatW4fvvvsOZ8+eLTG/5IRF1h3PoiQH\n5Tdv3shMf/36tSBfRXn//j0YY1InR5J6FS7/999/R2JiIgICAjBs2DBB/h07dsh8c+3natOmDQ4e\nPIjc3FxERETg2LFjWLt2LYYMGQJjY2N07Nix0uehZLqvX7+WeTeuIsvX19fHqFGjkJOTg0mTJmHC\nhAnYu3cvn75582b+7lnRz/JcuXIFq1evFgyTfELm7du3MsuTNVwSV2hoKHr27PlF8UheFAR8fOnP\n4MGDZebz8/PjG7GfU+eIiAgEBwejU6dOOHr0qODuDGMMy5cv/6I4SuLl5QUvLy+kpKTg8uXLOHDg\nAP766y906dIFjx49KvUFt6+lPJexLF5eXpg5cybGjh2LV69eybzbW1hZl59kn/w5b+T9miTzuXnz\n5p/9Vm+Jd+/eYc2aNWjUqBEuX74s1UtB3pvk5WGM4e3bt/ydaIm8vDy8f/9e8PkpyfIo+gZ5ieLe\nHl1ezMzM+B4YDx8+xJkzZ7B+/XosWrQIBQUFxV4kIIQQUvmqTL+ZRo0aYfTo0Xjx4kWJd0KBj3fr\n2rVrh7i4OFhZWeG77777ovIlb7lkpfjuoqQr5vHjx0vM37x5cwCQ2ziWDJfkqyi5ubm4dOmS1PCw\nsDAAQLNmzfhhT58+BcdxfCOisHPnzlVI/VRUVODg4ICFCxdizZo1AICQkBAA4D+pc+fOHcEdY4mK\nnofNmzcHY4yfV4U9ffoUL1++hJWVVYV+Y3TcuHGws7PD/v37cfnyZUH5AEq9rCTL+cqVKzLX3YsX\nL0oNk6zvX/KJIAnJW8Tt7e0xatQomX/GxsY4deoUoqOjAQD169eHuro67t69i/T09FLVWTJf3Nzc\npLoXXrt2DVlZWV8cS2no6emhW7du8PPzg7e3NxITEwXzUfIG2tLsdwqTjFeWu4XFKc9lLIuenh76\n9++PuLg4aGtry714IVHW5aelpYWGDRvizZs35dbttSJoa2vDzs4O9+/fL1N3ZVmioqLAGEPnzp2l\nGrAvX75EVFRUmacpax938eJFFBQUCI4RYrEYAPjP4hSWmpoq943TFcXW1haTJk3CyZMnAXw6dhBC\nCPl2VZlGLADMnTsXampq+PXXX0t1JdfPzw/BwcHYv39/iXnDw8MREBAg8+Q1NzeXv7Lfvn37EqfV\nvHlzODo64vbt2zLv6CQkJPBd3ZycnGBjY4OLFy9i3759gnx79+7FxYsXYWNjg7Zt25ZY7peaNWuW\n4BuEiYmJWLx4MTiOE3zvz8rKiv9+YmHHjx+X+ezh57p8+bLM5SG54yo5MVNVVYWnpydSU1Mxb948\nQd5nz55hzZo1UFVVhZeXV7nVrbARI0YAABYvXizoUpefn4/p06eDMcZ/x7WiFP4O6pw5c/jhks9I\nFF1Wt27dwi+//CI1HXNzc7i4uCAyMhKbNm0SpB07dkzmN3d79+6NOnXqYP369Th69KjM+l25ckXq\nuWlZ/P39wXEcNmzYAD8/P5l/Y8eOBWOMX9dUVVUxaNAgJCcnY/HixYLp3blzR+oTQoD8+fLu3TtM\nnDixxHp+CXkXrCR3jAs3OAwNDcEYQ0xMTJnKkHz6pazjyVOey1iexYsXIzg4GMePH5f5bHNhn7P8\n/ve//wGAzO/gFhQUyO3J8bVNmzYNOTk5GDFihMyLcklJSbh161aJ05HMowsXLgi6LKenp2P06NGf\ndYHj559/Fhx7s7KyMGvWLAAQHCN0dHRQv359XLx4UfD8bn5+PqZNm1bhF4kePnwosweGZBlrampW\naPmEEEK+nMJ3Jy6sRo0aGDduHFavXo0VK1Zg6dKlxea3sbGBjY1Nqab96tUrjBgxAt9//z3atm2L\nBg0aQF1dHa9fv8axY8fw9u1b1K1bV6pLpjzbtm2Di4sLZs+ejX379sHZ2RmMMURGRuLkyZN4/Pgx\n/53YwMBAdOrUCQMHDkTv3r1hY2ODx48fIzg4GLq6ujJPwsubqakpsrOz0bBhQ7i5uSEnJwd79+7F\nmzdvMHHiREEjesKECdi6dSs8PDzQv39/mJqa4v79+zh+/DgGDBiAXbt2ySyjrHeTVqxYgbNnz6Jd\nu3awtLSEtrY2Hjx4gGPHjsHAwEDQRXzZsmW4cOEC1q1bh+vXr8PFxQXv37/H7t27kZGRgXXr1n3R\nd1iL4+DggB9//BErVqxAw4YN0b9/f2hqauLo0aN48OAB2rVrhxkzZlRI2YX169cPTZs2xblz53Di\nxAl07twZw4YNw8qVKzFlyhScPXsW1tbWiIyMxOHDh+Hu7o6dO3dKTWf9+vVwcnLChAkTcOTIETRq\n1AhRUVHYv38/evfujZCQEMHdL2VlZezfvx9dunRBjx494OjoiCZNmkBTUxMvXrzA9evX8fz5c7x5\n86bYxwDCwsIQGRmJxo0by3y5i8TIkSOxePFibN26FQsXLoSSkhKWLVuGM2fOYMWKFbh27RocHBzw\n+vVr7NmzBz169EBwcLCgzi1btoSTkxP2798PJycnODk54e3btzh27Bjq16+PGjVqlHl9La2+fftC\nR0cHbdq0Qa1atcAYw4ULFxAREQF7e3tBr5HvvvsOe/fuRb9+/dCtWzdoaGjA0tISnp6exZbRoUMH\niEQizJo1C/fu3ePvjM2dO/ez6lxey7g45ubm/IuwSvI5y2/UqFG4cOEC/v77b9StWxdubm4wNjbG\nq1evcPbsWYwcObLU+/fyVLSePj4+uHHjBjZs2IA6deqgS5cuMDc3R2JiIp4/f44LFy5gxIgR2LBh\nQ7HTNTExwaBBg7Bz5040bdoUnTp1QkpKCk6ePAlNTU00bdq0zHelbW1tYWdnh/79+0NZWRkhISGI\niopCz549pdbJGTNmYOTIkXByckL//v2hrq6Os2fPIj8/H02aNMGdO3fKVHZZnDhxAjNmzICjoyPq\n1q2LatWq4eXLlwgJCYGSktJX2R8TQgj5Ql/xTcjlQt53YiXevn3LtLS0mLa2Nv+92KKf2CmJp6cn\nE4lEgs9PpKWlsR07djAfHx/WuHFjZmRkxJSVlZmhoSFzcnJiy5cvZxkZGWWKJSEhgc2cOZPZ2Ngw\ndXV1JhaLWbNmzdjcuXNZZmamIO/jx4+Zl5cXMzU1ZSoqKqxGjRrMy8uLPXnyRGq6vr6+UvWXCAgI\nYCKRSOb+puQsAAAgAElEQVTnKOR9PqFWrVrMysqKpaamsokTJzIzMzOmpqbGbG1t2dq1a2XGdvny\nZdahQwcmFouZjo4Oa9euHQsJCeE/t1C0DBcXl2KXq6x6nzhxgvn4+DBbW1ump6fHtLS0WP369dnk\nyZNZbGys1DSSk5PZzJkzWd26dZmamhoTi8Wsc+fO7OTJk6WeFxKWlpbMyspKbn1l2blzJ2vbti3T\n0dFh6urqrGHDhmzp0qUyP81U3DKUR9anLIo6ePAg4zhO8AmOhw8fMjc3N1atWjWmpaXF7O3t2ZYt\nW1h0dLTcz2A8evSI9evXj+nr6zMtLS3m6OjIjhw5wlauXMk4jmMhISFS47x794799NNPrGHDhkxT\nU5Npa2uzevXqMQ8PD7Z9+/YSv7k8dOhQJhKJ5K5zhXXu3JmJRCIWHBzMD4uLi2PDhw9nxsbGTEND\ngzVr1owFBQWxvXv3yvy2ZmJiIpswYQKztLRk6urqzNrams2ZM4dlZmbKXP7ytq3i1hVZy/nPP/9k\nffv2ZbVr12aamprMwMCANW/enK1cuVLqE0H5+fls9uzZrHbt2kxFRaXE5V/Ytm3bWNOmTZmGhobU\nftXb25uJRCLB52Akits2vnQZSxT+xE5J5s6dK3O+l3X5SWzfvp05OzszPT09pq6uzmrXrs08PT0F\nn6cqbj8qqX/R5SBrnpb0qZni9ouHDh1iPXv2ZNWqVWOqqqrM1NSUtW7dms2bN489fvxY5jhFZWZm\nsjlz5jBra2umrq7OLCws2KRJk1hCQoLMsuUte0nenJwcNnfuXGZlZcXU1NRYnTp12KJFi2R+i5ax\nj9/stbOzY2pqaszU1JSNGzeuzGUzVvJ8LLo8/v33XzZt2jRmb2/PjI2NmZqaGrOysmIeHh7sypUr\npZp3hBBCKhfHWAXdTiBVhqWlJUQi0Wc9I0X+W4YOHYodO3bg8ePHqFu3bmVXp1TmzJmDX375BceP\nH0enTp0quzqEEEIIIaQEVeqZWEJIxWOMyXw+8PTp09i1axfs7Oy+yQasrG8T37t3D2vWrIGhoaHM\nb1wSQgghhJBvT5V6JpYQUvGys7Nhbm6ODh06wMbGBsrKynjw4AFOnjwJdXV1rF+/vrKrKJO9vT3q\n1q0LOzs7aGlp8c/+Ah9fGKWqqlrJNSSEEEIIIaVB3YlJiaysrMBxHHUnJgA+vql1ypQpOHPmDF6+\nfInMzEwYGxujffv2+Omnn9CkSZPKrqJMixYtQnBwMKKjo5GWlgaxWIw2bdpg+vTppXqrOCGEEEII\n+TZQI5YQQgghhBBCiMKgZ2IJIYQQQgghhCgMasQSQgghhBBCCFEY1IglhBBCCCGEEKIwqBFLCCGE\nEEIIIURhUCOWEEIIIYQQQojCoEYsIYQQQgghhBCFQY1YQgghhBBCCCEKgxqxhBBCCCGEEEIUBjVi\nCSGEEEIIIYQoDGrEEkIIIYQQQghRGNSIJYQQQgghhBCiMKgRSwghhBBCCCFEYShXdgXKysDAAElJ\nSZVdDUIIIYQQQgghFUAsFiMxMVFuOscYY1+xPl+M4zgoWJUJIYQQQgghhJRSSW0+6k5MCCGEEEII\nIURhUCOWEEIIIYQQQojCoEYsIYQQQgghhBCFQY1YUmaxsbHQ0dGplGeTAwIC0K5du69e7ucICwuD\nubm53PTx48dj8eLFX7FGhHxy4cIF1K9fn/9taWmJ06dPV2KNPurevTv+/vvvyq4GIXJ5e3tj3rx5\n5T7dt2/fon379tDV1cWMGTPKffrfsm9l/0NIZamM89sDBw7A3NwcOjo6uHPnzlcpszz3n1WiEaur\nqwuO4yrsT1dXt9R1sbS0hKamJnR0dFC9enV4eXkhNTW1AqMvXkBAAEQiEXbv3l1u07SwsEBaWho4\njvui6bi4uGDLli1y06OjoyESiVBQUPBF5cjj6+sLkUiENWvWCIavXr0aIpEICxcurJByJTZu3Ii5\nc+dWaBmkYhhU8D7H4DP3OZK///3vfyWO165dOzx69Ij/LSlbFm9vb6ipqQnKaNasWanrWBZHjhyB\nl5dXhUybVAxd/Qo+But/3vZgYGCAnj174uXLl6UaV9YxR9aJZXHbypfw8/NDtWrVkJqaipUrV0ql\nV1TjWVY5KioqePPmTYWXJVFR85RUHF1dgwo+9zYodV2+tXNvRTF9+nRs2LABaWlpaNKkiVS6SCSC\ntrY2f9w3MCj9MpGnPLd1hfvEjixpaWnfzPQ5jsOhQ4fQoUMHvH37Fl26dMHixYuxYsWKCqyhfIGB\ngWjUqBGCgoIwYMCASqmDPKVdiSvqji/HcahXrx6CgoIEJ/2BgYGwsbGhAyqRKyktDRXZD4H7zH1O\nhdWH4zBz5kwsWrSowsoojfz8fCgpKVVqHYi0tJQ0wLcCp+/7edtDdnY2JkyYgO+//x4HDhwo9TRK\nc8ypiONSTEwMGjRoIDf9azT0MjIysG/fPtja2mLbtm2YPn16hZZHFFdaWhJQgUfCtLTSr+vf2rm3\nImCMITY2Fra2tsXmu3v3LmrXrl3uZZeHKnEn9ltlYmKCzp0748GDB/ywZcuWwdraGrq6urCzs0Nw\ncDCfVlBQgB9++AHGxsaoXbs21q1bJ7gqnJKSgpEjR6JGjRqoWbMm5s2bV+xdypiYGFy6dAlbt27F\nyZMn8fbtW0H6ihUr+Glt3rwZIpEIUVFRAIDDhw+jWbNm0NPTg4WFheCuZNGr1S4uLpg/fz7atm0L\nXV1ddOnSBQkJCQCArKwseHp6wsjICGKxGK1atcK7d+8wZ84cXLhwAZMmTZJ756h9+/YAAH19fejq\n6uLq1av8AXzGjBkwMDBA7dq1cezYMX6css6jli1bIjMzEw8fPgQAPHjwANnZ2bC3t+c3sqSkJPTs\n2RPVqlWDgYEBevXqhbi4OH4aiYmJ8PHxgZmZGQwMDNC3b19BGb///jtMTExQo0YNBAQE8MMLX1UP\nCwtDzZo15ebNzs7G9OnTUatWLVSvXh3jx49HVlaW3LgIyc7Ohr6+vmD/Ex8fD01NTbx//77E7u6l\nJdkfBAQEwMLCAoaGhvjzzz9x/fp1NG7cGGKxGN9//z2fPyAgAE5OTvj++++hr6+PBg0a4MyZM3x6\n4R4akrzTpk2DkZERFi5ciJycHNoWSKmoqanB3d2d378DxR/bZB1zxo0bhytXrgjuQhQ9ATt06BCa\nNm0KsVgMJycn3Lt3T26dLl++jJYtW0JfXx+tWrXClStXAHw8HgQFBWHFihXQ0dERbBOFyTv58/f3\nR926dWFoaIjevXvj9evXfNrUqVNhYmICPT09NG7cWLBPKGrfvn2wsrLCjz/+iMDAQEGar68vBgwY\ngOHDh0NXVxcNGzbEjRs3+PSbN2+iWbNm0NXVxYABAzBw4EDBnePSzifGGH+uZGRkhIEDByIpKQmA\n/HMKQiRknXtfvXoVjo6OEIvFaNq0Kc6dO8enFXcOW9K4z58/5x8B6NSpEyZOnCjoSeTh4QFTU1Po\n6+vD2dlZsC9KSEiAm5sb9PT00Lp1azx79kwQx6NHj9CpUycYGhqifv362LNnD5925MgR2NnZQVdX\nFzVr1sRvv/0mc14wxrB48WJYWlrCxMQEw4cPR2pqKrKzs6Gjo4P8/Hw0adIEdevWLdM8LtxeAMp2\nPltYWloaXF1dMWXKlDKVz9fjs8YixZIcZF6+fIljx46hdevWfJq1tTUuXryI1NRULFiwAJ6ennzj\n0s/PD8eOHcOdO3dw8+ZNBAcHC666ent7Q1VVFc+ePcOtW7dw4sQJbN68WW49goKC4OzsjObNm8Pe\n3h7bt2/n044dO4Y//vgDp0+fRmRkJMLCwgTjamtrY9u2bUhJScHhw4exceNGhISEyC1rx44dCAgI\nwLt375CTk4Nff/0VwMe7mqmpqXj58iUSExOxadMmaGhoYMmSJWjXrh3Wr1+PtLQ0qS69wMdn9oCP\nDdPU1FS0adMGjDFcu3YN9evXR0JCAn788UeMHDnys+cRAHh5eSEoKIivb9GujIwxjBw5ErGxsYiN\njYWGhgYmTZokGD8rKwsPHz7Eu3fvMG3aND7tzZs3SE1NxatXr7BlyxZMnDgRKSkpAKSvqr99+1Zu\n3p9++glPnz7FnTt38PTpU8TFxVX6XTHy7ZB1Yis5gd+xYwc/bPfu3XBxcYGRkVG5lFFYeHg4nj59\nip07d2Ly5MlYunQpzpw5gwcPHmD37t04f/68IK+1tTUSEhKwcOFC9OvXD8nJyQCkt4vw8HDUqVMH\n7969w+zZszFz5kzaFkixJOtqZmYmdu3aBQcHBz6tuGObrGPOpk2b4ODggLS0NCQmJgIQ9iK6desW\nRo4cCX9/fyQmJmLs2LFwc3NDTk6OVL0SExPRo0cPTJkyBYmJiZg2bRp69OiBpKQkBAQEYOjQoZg5\ncybS0tLK1LPizJkzmD17Nvbs2YPXr1+jVq1aGDRoEADg+PHjuHDhAiIjI5GSkoI9e/bA0NBQ7rQC\nAwMxcOBAuLm54enTp7h586Yg/eDBgxg8eDBSUlLg5ubGHwtzcnLQt29fjBgxAklJSRg8eLDgHEbe\nfMrNzZWqw5o1axAaGorz58/j9evXEIvFmDhxIl8/WecUhMg7946Li0PPnj0xf/58JCUl4ddff4W7\nu7ugoSrvHLakcYcMGYI2bdogMTERvr6+2LZtm2D/0KNHDzx9+hTx8fFo3rw5hg4dyqdNnDgRmpqa\nePPmDf766y9s3bqVHzcjIwOdOnWCp6cn4uPjsXPnTkyYMIF/BGjkyJHw8/NDamoqHjx4IHd/sXXr\nVgQGBiIsLAxRUVFIT0/HpEmToKamhvT0dAAf77RGRkaWOF+LU5bzWUn+hIQEdOzYEe3atcOqVatK\nLENe5RSKrCrjY3+GCv0rrVq1ajFtbW2mo6PDOI5jffr0Yfn5+XLzN23alIWGhjLGGHN1dWV+fn58\n2qlTpxjHcSw/P5+9efOGqampsQ8fPvDp//zzD3N1dZU7bWtra7Zp0ybGGGN//PEHa9KkCZ/m4+PD\nZs+ezf9++vQp4ziOPXv2TOa0Jk+ezKZOncoYY+z58+d8vRhjzMXFhS1ZsoTPu2HDBta1a1fGGGN/\n/fUXc3R0ZHfv3pWapouLC9u8ebPc+hcthzHGtm7dyqytrfnfGRkZjOM49vbt2zLPowULFjBPT08W\nGxvLLCwsWG5uLrOwsGAvXrxgnp6ezNfXV+Z4t27dYmKxmDHG2KtXr5hIJGLJyclS+c6ePcs0NDQE\n9a9WrRq7du0aY4wxb29vNnfu3BLzFhQUMC0tLcGyuXz5MrOyspI770jFAsBYBf59zj5HX1+f/5Ns\nV6dOnWJ16tTh8zo6OrK///6bMfZxnatZsyafZmlpyU6fPi2zjOHDhzN1dXVBGd7e3oyxT9vpq1ev\n+PyGhoZs9+7d/G93d3e2atUqxtjHbbhGjRqC6bdq1Yqvl4uLC9uyZQuf18LCgs9H28K3CQCDbwX+\nfeb2oKKiwszMzNi9e/fk5i/u2MbYx3Wwbdu2gnG8vb3ZvHnzGGOMjRs3jv+/hI2NDTt37pxUWUFB\nQax169aCYQ4ODiwgIICfruSYIIu89BEjRrCZM2fyv9PT05mKigqLiYlhZ86cYfXq1WNXr14t9lyE\nMcZiYmKYSCRijx8/Zowx1rt3bzZ58mQ+fcGCBaxTp0787wcPHjANDQ3GGGPnzp1jZmZmgum1bdu2\nxPl0/vx5xphw/9OgQQPBvujVq1dMRUWF5eXlFXtOQb6uj+fHFXkoLJ9z72XLljEvLy9B/i5durDA\nwEDGWPHnsMWNGxMTw5SVlQXnnJ6enszT01NmHZOSkhjHcSw1NZXl5eUxFRUVfltjjLHZs2fz+5qd\nO3eydu3aCcYfM2YMW7hwIWOMMQsLC7Zp0yaWkpJS7Hzp0KED27hxI//78ePHTEVFhZ83xZ33S9J1\ndXX5475kf1B0vNKez0ryjhgxgjVs2JD9+uuvxda/pHWA7sSWM47jEBISgtTUVISFheHMmTOIiIjg\n04OCgtCsWTOIxWKIxWLcv38f79+/BwC8fv1a0L2vZs2a/P9jYmKQm5sLU1NTftxx48YhPj5eZj0u\nXbqE6Oho9OvXDwDQv39/3Lt3D3fv3i2xLAC4du0aXF1dUa1aNejr62PTpk2Cq1ZFVa9enf+/hoYG\nf4XHy8sLXbp0waBBg2BmZoaZM2ciLy9PML/KqnBZmpqaAID09PQyzyNJ+ebm5rC2tsasWbNQr149\nqXmRmZmJsWPHwtLSEnp6enB2dkZKSgoYY3jx4gUMDAygp6cnc/qGhoYQiT5tZpqamvy8KW3e+Ph4\nZGZmokWLFnxc3bp149cb8t8m2eckJSXxf5LeCS4uLsjMzER4eDiio6Nx584dqe7upS1jxowZgjK2\nbt0qyGNiYsL/X0NDQ+p3RkYG/9vMzEwwbq1atQTdHwsrvJ+ibYGUpPD2kJ2djbVr18LZ2Znv8VTW\nY1tJYmJi8Ntvv/Hro1gsxsuXL2Wuz69evYKFhYVgWK1atfDq1avPLh8Af/dVQktLC4aGhoiLi4Or\nqysmTZqEiRMnwsTEBGPHjpX7no+///4bDRs2RL169QB87Ar5zz//ID8/n89TeLvW1NREVlYWCgoK\n8OrVK6ntuvC2K28+yYo9Ojoaffv25fPZ2tpCWVkZ7969K/Gcgvw3FXfuHRMTgz179gjWvUuXLgle\nXCbvHLa4cV+9egUDAwOoq6vz4xZe5/Pz8/HTTz/B2toaenp6sLKyAsdxeP/+PeLj45GXlyfIX3jf\nEBMTg2vXrgnK/eeff/j92L59+3DkyBFYWlrCxcUFV69elTlfiu4bLCwskJeXJ/V4YXFu3brFH/dL\ne8e0uHNfxhgOHz6MrKwsjB07ttT1kIUasRWoffv2+P777zFz5kwAH1fKMWPGYP369UhMTERSUhIa\nNmzI36o3NTXFixcv+PEL/9/c3BxqampISEjgV6aUlBS5z5QEBgaCMYZGjRrB1NQULVu2BAC+X3px\nZQEfu0j06dMHL1++RHJyMsaNG/dZbwlWVlbG/Pnz8eDBA1y+fBmHDh3iu+6W1IAtawO3rPMI+NRN\nYtiwYfj9998xbNgwqfJ/++03PHnyBOHh4UhJScG5c+fAGANjDObm5khMTBR0kyiL0sRoZGQEDQ0N\nPHz4kI8rOTmZ3rxHSqSkpIQBAwZgx44d2LFjB3r16gUtLa3KrpbgmXLg476xRo0aMvMW3kZoWyBl\nwXEc+vbtCyUlJVy6dAlA8cc2WfvjkvbRFhYWmDNnjuACT3p6OgYOHCiV18zMDDExMYJhMTExUo2/\nkmIqqkaNGoiOjuZ/Z2RkICEhgZ/u999/j4iICDx8+BBPnjyR+eZj4ONF9sjISJiamsLU1BRTpkzB\n+/fvcfjw4RLrZWpqKrVdx8bG8v8vy3yysLDAsWPHBHkzMzNhampa7DkFIYD0ubeFhQW8vLwE61Na\nWhp+/PHHEqdV3LimpqZITEzEhw8f+PyxsbH8NvrPP/8gNDQUp0+fRkpKCp4/f86fOxobG0NZWVmw\njRTdXpydnaXKXb9+PQDA3t4ewcHBiI+PR58+feS+uLXoviE2NhbKysqCi1GfQ1NTE5mZmfzv169f\nl/qcneM4jB49Gl26dEH37t0F0ykrasRWsClTpiA8PBzXrl1DRkYGOI6DkZERCgoKsHXrVty/f5/P\nO2DAAKxevRqvXr1CcnIyli9fzq8Upqam6Ny5M6ZNm4a0tDQUFBTg2bNngufMJLKysrB79274+/vj\nzp07/N/atWv5q6oDBgzA1q1b8ejRI2RmZuLnn38WTCM9PR1isRiqqqoIDw/HP//8U+wKKmkMFnX2\n7Fncu3cP+fn50NHRgYqKCv92URMTE6kH2QszNjaGSCQqNk9hZZlHRQ0cOBAnT56Eh4cHH48kpvT0\ndGhoaEBPTw+JiYmCF4GYmpqiW7dumDBhApKTk5Gbm1uq8oqWURyRSITRo0djypQp/F3luLg4nDhx\nolTlkKqvuPVoyJAh2LlzJ/755x8MGTLks6dfmnW1pGlIvHv3DmvWrEFubi727NmDR48eoXv37iVO\ng7YFUhqSdY0xxt+Vlbz1t7hjm6xjTvXq1fHy5UvBs5uFt4fRo0fjzz//RHh4OBhjyMjIwOHDh2X2\nuOnevTuePHmCHTt2IC8vD7t27cKjR4/Qs2dPQb2LiysvLw9ZWVn8X05ODgYPHoytW7fizp07yM7O\nxuzZs9GmTRtYWFggIiIC165dQ25uLjQ1NaGuri7zDd9XrlxBVFQUrl+/zp8z3L9/H0OGDClVI9HB\nwQFKSkpYt24d8vLyEBISguvXr/PpZZlP48aNw+zZs/mT+vj4eISGhgL4+NIYeecUhEgUPvf29PTE\nwYMHceLECeTn5yMrKwthYWGCiy7ytr3ixq1Vqxbs7e3h6+uL3NxcXLlyBYcOHeLHTU9Ph5qaGgwM\nDJCRkYHZs2fzaUpKSujXrx98fX3x4cMHPHz4EIGBgfy+qEePHnjy5Am2bduG3Nxc5Obm4vr163j0\n6BFyc3Oxfft2pKSkQElJCTo6OnK3gcGDB+OPP/5AdHQ00tPTMXv2bAwaNEhwl/RzNG3aFNu3b0d+\nfj6OHTtW6vNe4NO8XrduHWxsbNCrV6/PfjljlWjE6ujofLPTNzIywvDhw7F8+XLY2trihx9+gIOD\nA6pXr4779++jbdu2fN7Ro0ejc+fOaNy4MVq0aIEePXpASUmJX9mCgoKQk5MDW1tbGBgYwMPDQ+Z3\n3IKDg6GlpYVhw4ahWrVq/J+Pjw/y8vJw/PhxdO3aFf/73//g6uqKevXq8S++UFNTAwBs2LAB8+fP\nh66uLn7++Wepq6VFG7SFfxd+wPvt27fw8PCAnp4ebG1t4eLiwr84afLkydi7dy8MDAxkvplMU1MT\nc+bMgZOTEwwMDHDt2jWZnxgo/Lu086hoPdXV1dGhQwe+W0jhtClTpuDDhw8wMjKCo6MjunXrJijz\n77//hoqKCurXrw8TExPBS6qKa/gXjaW4vMuXL4e1tTXatGkDPT09dOrUCU+ePJGbn1QssY4OOKDC\n/sRl3Of06tVL8A1Xd3d3Pq1Vq1bQ1tbG69ev0a1bN8F4ZblyKnlrquSvWrVqZZpO4TytW7dGZGQk\njI2NMW/ePOzbtw9isVjmOEWnTdvCt0dHT+fjJ3Yq6E9H7/O2Bz09PcybNw9BQUF8I7a4Y1vhY45Y\nLEZ4eDg6dOgAOzs7VK9enV/nC6+XLVq0gL+/PyZNmgQDAwPUrVtXbqPPwMAAhw4dwm+//QYjIyP8\n+uuvOHToEP/W45I+ocNxHJYtWwZNTU3+77vvvkPHjh3x888/w93dHTVq1MDz58+xc+dOAEBqairG\njBkDAwMDWFpawsjICDNmzJCadlBQEPr06QM7Ozv+nMHExASTJ0/G4cOHkZSUVOzxV1VVFfv378eW\nLVsgFouxfft29OzZE6qqqsXOJ1nxTp48GW5ubujcuTN0dXXh4OCA8PBwAB9flijvnIJ8XTo6YlTc\nUZD7/+l/nsLn3jVr1kRISAiWLl2KatWqwcLCAr/99pug4SrvHFbeuJLeG9u3b8eVK1dgaGiIefPm\nYeDAgfw6P2zYMNSqVQtmZmZo2LAhHBwcBOWsW7cO6enpqF69OkaMGIERI0YUmrc6OHHiBHbu3Akz\nMzOYmppi1qxZ/Avjtm3bBisrK+jp6cHPz0/w4tbCRowYAS8vL7Rv3x61a9eGpqYm1q5dKzNuWeSl\nr169GgcPHuS7ORd9TKm0575+fn6oWbMm+vTpg+zs7GLrInNa7Esvr39lHMdV2HdDvzVHjx7F+PHj\nBV0BKsq///6LRo0aIScn54uv0BBCiDwBAQHYsmUL/yZYQkjV1Lp1a0yYMAHDhw+v7KoQ8lUMHDgQ\ntra2WLBgQWVXpUooqc1HrZVvSFZWFo4cOYK8vDzExcXxn56oKAcOHEB2djaSkpIwc+ZMuLm5UQOW\nEEIIIWV2/vx5vHnzBnl5eQgMDMT9+/fRtWvXyq4WIRUmIiICz549Q0FBAY4ePYrQ0FD06dOnsqv1\nn0Etlm8IYwy+vr4wMDBA8+bNYWdnV6HfP/Tz84OJiQmsra2hoqKCjRs3VlhZhBAClNxlkhCimB4/\nfoymTZtCLBbjjz/+wN69e7/4BTKEfMvevHkDV1dX6OjoYOrUqfjzzz/RpEmTyq7WfwZ1JyaEEEII\nIYQQ8s2g7sSEEEIIIYQQQqoMasQSQgghhBBCCFEY1IglhBBCCCGEEKIwlCu7AmUlFovppSCEEEII\nIYQQUkXJ+n58YRXyYqdjx45hypQpyM/Px6hRozBz5kyZ+a5fvw4HBwfs2rUL7u7uZRqXEEIIIYQQ\nQsh/T7k3YvPz82FjY4NTp07BzMwMLVu2xI4dO9CgQQOpfJ06dYKmpiZ8fHzg7u5e6nEJIYQQQggh\nhPw3lfszseHh4bC2toalpSVUVFQwaNAghISESOVbu3Yt+vfvD2Nj4zKPSwghhBBCCCHkv6ncG7Fx\ncXEwNzfnf9esWRNxcXFSeUJCQjB+/HgA4J9xLc24hBBCCCGEEEL+u8r9xU6leenSlClTsGzZMv4j\ntpIezaUZl17qRAghhBBCCCFVW3FPvZb7nVgzMzO8ePGC//3ixQvUrFlTkOfGjRsYNGgQrKyssG/f\nPkyYMAGhoaGlGhcA3/Clv2/jb8GCBZVeB4qN4qP4qt5fVY6vKsdG8Sn+H8WnuH9VOTaK77/1V5Jy\nvxNrb2+PyMhIREdHo0aNGti1axd27NghyBMVFcX/38fHB7169YKbmxvy8vJKHJd8e6Kjoyu7ChWm\nKscGUHyKjuJTXFU5NoDiU3QUn+KqyrEBFB/5pNwbscrKyli3bh26dOmC/Px8jBw5Eg0aNMCmTZsA\nAGPHji3zuIQQQgghhBBCCFBB34mtSJLnaMm3IywsDC4uLpVdjQpRlWMDKD5FR/EprqocG0DxKTqK\nT3Wa8H0AACAASURBVHFV5dgAiu+/pKQ2HzViCSGEEEIIIYR8M0pq85X7i53If09YWFhlV6HCVOXY\nAIpP0VF8iqsqxwZQfIqO4lNcVTk2gOIjn1AjlhBCCCGEEEKIwqDuxIQQQgghhBBCvhnUnZgQQggh\nhBBCSJVBjVjyxapy//2qHBtA8Sk6ik9xVeXYAIpP0VF8iqsqxwZQfOQTasQSQgghhBBCCFEY9Ews\nIYQQQgghhJBvBj0TSwghhBBCCCGkyqBGLPliVbn/flWODaD4FB3Fp7iqcmwAxafoKD7FVZVjAyg+\n8gk1YgkhhBBCCCGEKAx6JpYQQgghhBBCyDeDnoklhBBCCCGEEFJlUCOWfLGq3H+/KscGUHyKjuJT\nXFU5NoDiU3QUn+KqyrEBFB/5hBqxhBBCCCGEEEIUBj0TSwghhBBCCCHkm0HPxBJCCCGEEEIIqTKo\nEUu+WFXuv1+VYwMoPkVH8SmuqhwbQPEpOopPcVXl2ACKj3xCjVhCCCGEEEIIIQqjQp6JPXbsGKZM\nmYL8/HyMGjUKM2fOFKSHhIRg/vz5EIlEEIlEWLlyJTp06AAAsLS0hK6uLpSUlKCiooLw8HBhhemZ\nWEIIIYQQQgipskpq85V7IzY/Px82NjY4deoUzMzM0LJlS+zYsQMNGjTg82RkZEBLSwsAcO/ePfTt\n2xdPnz4FAFhZWeHGjRswMDCQXWFqxBJCCCGEEEJIlfXVX+wUHh4Oa2trWFpaQkVFBYMGDUJISIgg\nj6QBCwDp6ekwMjISpFMjVbFU5f77VTk2gOJTdBSf4qrKsQEUn6Kj+BRXVY4NoPjIJ+XeiI2Li4O5\nuTn/u2bNmoiLi5PKFxwcjAYNGqBbt25Ys2YNP5zjOHz33Xewt7eHv79/eVePEEIIIYQQQj6brq4B\nOI4r1Z+uruzepeTLKJf3BDmOK1W+Pn36oE+fPrhw4QK8vLzw+PFjAMClS5dgamqK+Ph4dOrUCfXr\n10e7du0E43p7e8PS0hIAoK+vj6ZNm8LFxQXApysY9Pvr/pb4VupTXr8lw76V+lB8FB/F9+3U70t+\nu7i4fFP1ofgoPoqPftPv0v9OS0sCcBbAx99A2P//K/07LY2r9Poqwu/bt28jOTkZABAdHY2SlPsz\nsVevXoWvry+OHTsGAPjll18gEomkXu5UWJ06dRAeHg5DQ0PB8IULF0JbWxs//PDDpwrTM7GEEEII\nIYSQSvLxpl1p2yPUdvkcX/2ZWHt7e0RGRiI6Oho5OTnYtWsX3NzcBHmePXvGV+rmzZsAAENDQ2Rm\nZiItLQ3Ax5c/nThxAo0aNSrvKpJyJrmaUhVV5dgAik/RUXyKqyrHBlB8io7iU1xVOTaA4iOflHt3\nYmVlZaxbtw5dunRBfn4+Ro4ciQYNGmDTpk0AgLFjx2Lfvn0ICgqCiooKtLW1sXPnTgDAmzdv0K9f\nPwBAXl4ehg4dis6dO5d3FQkhhBBCCCGEKKgK+U5sRaLuxIQQQgghhJDKQt2JK95X705MCCGEEEII\nIYRUFGrEki9WlfvvV+XYAIpP0VF8iqsqxwZQfIqO4lNcVTk2gOIjn1AjlhBCCCGEEFJu6DuqpKLR\nM7GEEEIIIYSQclPVnxmt6vF9C+iZWEIIIYQQQgghVQY1YskXq8r996tybADFp+goPsVVlWMDKD5F\nR/EprqocG0DxkU+oEUsIIYQQQgghRGHQM7GEEEIIIeSboqtrgLS0pFLl1dERIzU1sYJrVL6qenxV\n/ZnRqh7ft6CkNh81YgkhhBBCyDelqjcSKD5BboqPSKEXO5EKV5X771fl2ACKT9FRfIqrKscGUHxf\nS0V9xuRbia+iVOX4qnJsAMVHPlGu7AoQQgghhJCy+9gdtXR3eNLSuIqtDCGEfEXUnZgQQgghVdL/\ntXf/0VGVdx7HP5MfXZRfAUoDZLCjJkogIQkGs9RySis/DK7pQrVF7ULWQLNU1mNXu+juuifa027R\nw24x6e6mlPrjYAG7WQ3d4pTSlpWjS6INAfagNrTOEgKoq8QEghszvfsHyYSZJMwM3Mmd++T9OieH\neZLn3vl+MmFyv7n3mWHdYdhsVx0/mZxNIl/EbPJhANbEAgCAEcn0A02T85mcTSJfxGzyYQDWxCLh\nTL5+3+RsEvncjnzuZXI2iXxuRz73MjmbRD70o4kFAAAAALgGlxMDADBCsWY0bLbrji9MzmdyNol8\nEbPJhwGi9Xy8OjEAACMUr24LAHAjLifGZTP5+n2Ts0nkczvyJR7vw3lpyOdu5HMvk7NJ5EM/zsQC\nADAEzlQCAJB8ErIm1u/36/7771cwGNTq1au1fv36sK/X19fr7//+75WSkqKUlBQ98cQT+sIXvhDT\ntqyJBQAMF9PXPZEvbDb5kojJ2STyRcwmHwYY9veJDQaDuv7667Vnzx5lZWVp7ty52rZtm3Jzc0Nz\nzp49q9GjR0uSDh8+rGXLluno0aMxbUsTC8BtTH7xHJOzSeYfqJAvbDb5kojJ2STyRcwmHwYY9veJ\nbWxsVHZ2tnw+n9LT07VixQrV19eHzelrYCXpzJkz+uQnPxnztkg+Jl+/b3I2iXzDpf+S1OgfsTaE\nUnLkS1Q2KTnyJYrJ2STyuR353MvkbBL50M/2NbFtbW2aPn16aOz1etXQ0DBg3osvvqiHH35YJ0+e\n1O7du+Patry8XD6fT5KUkZGhwsJCLViwQFL/g894+MbNzc1JVY+d4+bm5qSqh3zuzNevb7wgylgx\n7d99+c5vY+7jF1++ZBmTj3zJOO7PMFSe8LHT9SZLvtCeyUc+l42bm5vV3t4uSQoEAorG9suJ6+rq\n5Pf7tXnzZknS1q1b1dDQoOrq6kHn79u3T6tXr9abb76puro6/fznP7/otlxODMBtTL7syORsEvki\nZpMvyZicz+RsEvkiZpMPAwz75cRZWVlqbW0NjVtbW+X1eoecP3/+fPX09OiDDz6Q1+uNa1sAAAAA\nwMhiexNbXFyslpYWBQIBdXd3a8eOHSorKwub87vf/S7UWTc1NUmSJk2aFNO2SD4DL2kyh8nZpOTJ\nx3txXhryuZfJ2STyuR353MvkbBL50M/2NbFpaWmqqanRkiVLFAwGVVFRodzcXNXW1kqSKisrVVdX\np2effVbp6ekaM2aMtm/fftFtAZiN9+IEAABArBLyPrGJxJpYwDymry0xOZ/J2STyRcwmX5IxOZ/J\n2STyRcwmHwYY9jWxAAAAAAAkCk0sLpvJ1++bnE0in9uRz71MziaRz+3I514mZ5PIh340sQAAAAAA\n12BNLADHmb62xOR8JmeTyBcxm3xJxuR8JmeTyBcxm3wYgDWxAAAAAABj0MTispl8/b7J2STyuR35\n3MvkbBL53I587mVyNol86EcTCwAAAABwDdbEAi4wbtxEdXaejmnu2LET1NHxQYIrspfpa0tMzmdy\nNol8EbPJl2RMzmdyNol8EbPJhwGi9Xxpw1gLgEt0voGN7Qmws9OT2GIAAAAAB3E5MS6bydfvm5xN\nIp/bkc+9TM4mkc/tyOdeJmeTyId+NLEAAAAAANdgTSyMwJrRsNmu+z9CvrDZrspncjaJfBGzyZdk\nTM5ncjaJfBGzyYcBWBOLEYE1owAAAMDIwOXEuGwmX79vcjaJfG5HPvcyOZtEPrcjn3uZnE0iH/rR\nxAIAAAAAXIM1sTCC6WsTyBc2m3xJxORsEvkiZpMvyZicz+RsEvkiZpMPA0Tr+TgTCwAAAABwDZpY\nXDaTr983OZtEPrcjn3uZnE0in9uRz71MziaRD/1oYgEAAAAArpGQNbF+v1/333+/gsGgVq9erfXr\n14d9/bnnntPjjz8uy7I0duxY/cu//Itmz54tSfL5fBo3bpxSU1OVnp6uxsbG8IJZE4tBmL42gXxh\ns8mXREzOJpEvYjb5kozJ+UzOJpEvYjb5MMCwv09sMBjUunXrtGfPHmVlZWnu3LkqKytTbm5uaM41\n11yjl19+WePHj5ff79fXvvY17d+/P1Tw3r17NXHiRLtLAwAAAFznfNMU3djxY9XR3pHgagDn2X45\ncWNjo7Kzs+Xz+ZSenq4VK1aovr4+bM68efM0fvx4SVJJSYmOHz8e9nX+WuEuJl+/b3I2iXxuRz73\nMjmbRL5k5fF4Yvq4csyVTpcat1izuTWfqmL76Pywc5gLG15u/b8XK9Pz2cn2M7FtbW2aPn16aOz1\netXQ0DDk/C1btmjp0qWhscfj0cKFC5WamqrKykqtWbNmwDbl5eXy+XySpIyMDBUWFmrBggWS+h98\nxsM3bm5udryefn3jBVHGimn/zc3NjuQhX2SeyLFi2j/5hmd8QcVD5FnQP2Pv3pj3b3q+ZBmTb+Tk\nU7kkX+/tQO+/g4zPVZ1zPF9/hqHyRIzLh84TOXZlvovkCRv3be2yfPH+vJPPvHFzc7Pa29slSYFA\nQNHYvia2rq5Ofr9fmzdvliRt3bpVDQ0Nqq6uHjD317/+te6991698sormjBhgiTp5MmTmjp1qt57\n7z0tWrRI1dXVmj9/fn/BrInFIExfm0C+sNnkSyImZ5PIFzE75v0myyWN5Aubff5sXSyqnL8qLmHZ\nJLPzVTmfTeK5M2K26/Ilg2FfE5uVlaXW1tbQuLW1VV6vd8C8Q4cOac2aNfL7/aEGVpKmTp0qSZo8\nebKWLVumxsbGsCYWAAA4pCq2aZ1VLr2ksSq2aa7NBwCGSLF7h8XFxWppaVEgEFB3d7d27NihsrKy\nsDnHjh3T8uXLtXXrVmVnZ4c+39XVpc7O878Yzp49q927dys/P9/uEmGzgZc0mcPkbBL53I58ycfo\nNXkA4DA3/l6Ih+n57GT7mdi0tDTV1NRoyZIlCgaDqqioUG5urmprayVJlZWVeuyxx3T69GmtXbtW\nkkJvpXPq1CktX75cktTT06O7775bixcvtrtEAIBDYn2FTUm6YvQV6jrTlcBqEqAqtmnnqs4ltAwA\nAEyWkPeJTSTWxGIwpq9NIF/YbOPzxSoZ1uWxbi1stvHr1sjXq4p8icZzS9hsVz12Er/XI2a7Ll8y\nGPY1sQCAy1QV2zTW5QEAgJHI9jWxGHlMvn7f5GwS+QAAgHuY/nvd9Hx24kwsANeJdV2lK9dUAgAA\n4KJoYnHZwt/42SwmZ5NcnK8qtmm8eA4AAOZw7XFLjEzPZycuJwYAAAAAuAZNLC6bydfvuzUb71UJ\nAABM49bjsliZns9OXE4MmKgqtmlcbgsAAAC34UwsLpvJ1++bnA0AAMBNTD8uMz2fnWhiAQAAAACu\nQROLy2by9fsmZwMAAHAT04/LTM9nJ5pYAAAAAIBr0MTispl8/b7J2QAAANzE9OMy0/PZiSYWAAAA\nAOAaMTex3d3dOnDggN59991E1gMXMvn6fZOzAQAAuInpx2Wm57PTkE1sZWWl/vu//1uS9OGHH6qg\noEArV65UYWGhfvzjHw9bgQAAAAAA9Bmyid23b5/y8vIkSU899ZSuv/56HT58WE1NTXr88ceHrUAk\nP5Ov3zc5GwAAgJuYflxmej47DdnE/tEf/VHo9u7du/XFL35RkjRlypTEVwUAAAAAwCCGbGLHjx+v\nn/70p2pqatKrr76qW265RZL08ccf66OPPhq2ApH8TL5+3+RsAACMVB6PJ6aPiePGOV0qLmD6cZnp\n+eyUNtQXamtrdd999+nUqVP63ve+p6lTp0qSfvnLX+rWW28dtgIBAACQnMaNG6fOzs6Y5o4dO1Yd\nHR0Jrig2VozzPDFmAzC8hjwTe/311+vnP/+5Dh48qPLy8tDnb7nlFm3cuPGiO/X7/ZoxY4ZycnK0\nYcOGAV9/7rnnVFBQoNmzZ+umm27SoUOHYt4Wycfk6/dNzgYAwFBiPVN5Lo4mL9ZmFxiK6cdlpuez\n05BnYv/yL/9SHo9HljXwb1Uej0dPPvnkoNsFg0GtW7dOe/bsUVZWlubOnauysjLl5uaG5lxzzTV6\n+eWXNX78ePn9fn3ta1/T/v37Y9oWsIPH44lp3tjxY9XRnhx/NQYAYLjEfKYyoVUAwOCGbGL/9V//\nVXl5efryl7+sadOmSVKoob1YA9DY2Kjs7Gz5fD5J0ooVK1RfXx/WiM6bNy90u6SkRMePH495WySf\nvXv3uu8vR1WxTeus4q/GAAAAycCVx5xxMD2fnYZsYk+ePKmf/OQnev7555WamqqvfOUruuOOO5SR\nkXHRHba1tWn69OmhsdfrVUNDw5Dzt2zZoqVLl8a1bXl5eajRzcjIUGFhYegB71sQzXj4xs3NzY7X\n069vvCDKuFeg91/fEGOFP6GQLzHjC6oZIk/keIg8kWORbzjGF1QzRJ4F/VMCF8kTOZbZ+ZLh+Ttc\nZJ7Isch3wTjWK3omjB2rDzo6XJcv2t4i7z1e0fL130u0CnrHgd6hTzGNo+xtQD67H7/+e4lWwYJB\n6x9ynKB6E50v3p938pk3bm5uVnt7uyQpEAgoGo812PXCEY4fP67t27frH//xH7Vhwwb92Z/92ZBz\n6+rq5Pf7tXnzZknS1q1b1dDQoOrq6gFzf/3rX+vee+/VK6+8ogkTJsS07VCXOGNkO38wEcfFT1Ux\nTq1SUvy8kS9sNvn6VDmfL2HZJLPzVTmfTSJfxOz48sW+14R9L5IlXzxi/V4k/Lkl9j0n5PHj/17Y\n7KSoOR6m50sG0Xq+Ic/E9vnNb36j7du36xe/+IVKS0t1ww03XHR+VlaWWltbQ+PW1lZ5vd4B8w4d\nOqQ1a9bI7/drwoQJcW0LAAAAABiZUob6wiOPPKIbbrhB//RP/6TPfe5zeu2117RlyxbNnDnzojss\nLi5WS0uLAoGAuru7tWPHDpWVlYXNOXbsmJYvX66tW7cqOzs7rm2RfAZe0gQAGOl4H85+sX4vxo2A\n7wVwOUw/5jQ9n52GPBP77W9/W1dffbUOHjyogwcP6uGHHw59zePxhL0tTtgO09JUU1OjJUuWKBgM\nqqKiQrm5uaqtrZUkVVZW6rHHHtPp06e1du1aSVJ6eroaGxuH3BbDa1zGOHV+GPsLGl0x+gp1nelK\nYEUAALeJ5304Y11fKiXXe43ajbegAYDYDNnE/v73vx9yo2i/bEpLS1VaWhr2ucrKytDtH/7wh/rh\nD38Y87YYXp0fdsa1tuRc1bmE1QIApoqncet7cSDQ6AEjWfgLK5nH9Hx2GrKJ7Xv130iWZen555/X\npz/96UTVBACA8eJ5mQ8PjRsAACFDrok9c+aMNm7cqK9//ev653/+Z/3hD3/QCy+8oFmzZum5554b\nzhoBACMU6yoBAH1MXzNqej47DXkmduXKlRo3bpzmzZun3bt36+mnn9aoUaP04x//WIWFhcNZIwBg\nhIpnXSUAABgZhmxijx49GnrxptWrV2vq1Kn6n//5H11xxRXDVhwA4OJiXVfJmkoAgNuZvmbU9Hx2\nGvJy4tTU1LDbWVlZNLAAXMf0y1GtGD9Oc6bS9XibFgAAzhuyiT106JDGjh0b+jh8+HDoNr8gAbgF\nTR5GGl69F4CpTF8zano+Ow15OXEwGBzOOgA4hMtRAQAA4CZDNrEAzjP9vRx54RwAAOAGpq8ZNT2f\nnWhiYQuTz+bxXo4AAABA8hhyTSwQD9YdAgAAIJFMXzNqej470cQCAIzAq/cCADAy0MQCAEYUXr0X\nANzJ9DWjpuezE00sAAAAAMA1aGIBoJfpl6Oang8AYDbT14yans9ONLEAECfTL0c1PR8AAHA3mlgA\nAAAASc/0NaOm57MTTSyAmMV6OSqXpAIAACBRaGIBJASXpAIAADuZvmbU9Hx2ookFAAAAALhGQppY\nv9+vGTNmKCcnRxs2bBjw9TfffFPz5s3TqFGjtHHjxrCv+Xw+zZ49W0VFRbrxxhsTUR4AAAAAlzF9\nzajp+eyUZvcOg8Gg1q1bpz179igrK0tz585VWVmZcnNzQ3MmTZqk6upqvfjiiwO293g82rt3ryZO\nnGh3aQAAAAAAl7P9TGxjY6Oys7Pl8/mUnp6uFStWqL6+PmzO5MmTVVxcrPT09EH3YVmW3WUBAAAA\ncDHT14yans9Otp+JbWtr0/Tp00Njr9erhoaGmLf3eDxauHChUlNTVVlZqTVr1gyYU15eLp/PJ0nK\nyMhQYWFh6PR734PP+PLGIYHef31Rxr36tl4wxLjvPhJWb9QKIub31e8bYty7RbS99Y37ajI5XzzI\ntzdyiygVRMwP9P7rG2Ist+XT+Qy+C27rImOZnS/a3gbZe1zcku9SkS/yHqJVJFfl67+XaBX0jgO9\nQ59iGkfZ24B8dh9v9d9LtAoWDFp/1OMxh48n+zMMkSdiHO/PO/nMGzc3N6u9vV2SFAgEFI3Hsvm0\nZ11dnfx+vzZv3ixJ2rp1qxoaGlRdXT1g7qOPPqoxY8bogQceCH3u5MmTmjp1qt577z0tWrRI1dXV\nmj9/fn/BHg9nahPM4/FIVXFsUCXF+oh4lJgz7R6PR3FVURXj1KrY99q7Z2PzeWKcd6FYvxduzBfP\n42xyvoRlk8zOVxX/c0s83JSP55ZwPLf07jeJnltc93s9CY6T482XDDXHw/R8ySBaz5di9x1mZWWp\ntbU1NG5tbZXX6415+6lTp0o6f8nxsmXL1NjYaHeJAAAAAACXsr2JLS4uVktLiwKBgLq7u7Vjxw6V\nlZUNOjeyu+7q6gq9t+TZs2e1e/du5efn210iAAAAAJcZeBm9WUzPZyfb18SmpaWppqZGS5YsUTAY\nVEVFhXJzc1VbWytJqqys1KlTpzR37lx1dHQoJSVFmzZt0pEjR/Tuu+9q+fLlkqSenh7dfffdWrx4\nsd0lAgAAAABcyvYmVpJKS0tVWloa9rnKysrQ7SlTpoRdctxnzJgxam5uTkRJAAAAAFws/IWVzGN6\nPjvZfjkxMNJ5PJ6YPsaNG+d0qQAAAIDr0MQCDulb/w0AAIDoTF8zano+O9HEYthxphIAAADApaKJ\nRdLiTCUAAAD6mL5m1PR8dqKJBQAAAAC4Bk0sAAAAgKRn+ppR0/PZiSYWAAAAAOAaNLEAAAAAkp7p\na0ZNz2cnmlgAAAAAgGvQxAIAAABIeqavGTU9n51oYgEAAAAArkETCwAAACDpmb5m1PR8dqKJHSHG\njZsoj8cT04eU5nS5AAAAADAomtgRorPztCQrxo8eh6oEAAAABmf6mlHT89mJJhYAAAAA4Bo0sQAA\nAACSnulrRk3PZyeaWAAAAACAa9DEAgAAAEh6pq8ZNT2fnWhiAQAAAACukZAm1u/3a8aMGcrJydGG\nDRsGfP3NN9/UvHnzNGrUKG3cuDGubQEAAACMPKavGTU9n51sb2KDwaDWrVsnv9+vI0eOaNu2bXrj\njTfC5kyaNEnV1dV68MEH494WAAAAADBy2d7ENjY2Kjs7Wz6fT+np6VqxYoXq6+vD5kyePFnFxcVK\nT0+Pe1sAAAAAI4/pa0ZNz2enNLt32NbWpunTp4fGXq9XDQ0Ntm5bXl4un88nScrIyFBhYWHo9Hvf\ng884fNyvb7wgyrhXoPdfX5RxjHuPl+P5ereItre+cbzItzdyiygVRMwP9P7rG2Is8l04jpf9+XQ+\ng++C27rIWGbni7a3QfYeF7fku1Tki7yHaBXJVfn67yVaBb3jQO/Qp5jGUfY2IJ/dx2f99xKtggWD\n1h/1eMzh48/+DEPkiRjH+/NOPvPGzc3Nam9vlyQFAgFF47Esy4o6Kw51dXXy+/3avHmzJGnr1q1q\naGhQdXX1gLmPPvqoxowZowceeCDmbT0ej2wueUTweDySYv2+eaSqOHZeFdee4xLrY52wfFWx77V3\nz3FxU754s0lm54vnecjkfDy3RFRRFePUKp5bLthr3EzOx3NL736T6LklEcedCX3skuA4Od58yVBz\nPEzPlwyi9Xwpdt9hVlaWWltbQ+PW1lZ5vd6EbwsAAAAAMJ/tTWxxcbFaWloUCATU3d2tHTt2qKys\nbNC5kd11PNsCAAAAGDkGXkZvFtPz2cn2NbFpaWmqqanRkiVLFAwGVVFRodzcXNXW1kqSKisrderU\nKc2dO1cdHR1KSUnRpk2bdOTIEY0ZM2bQbQEAAAAAkBLQxEpSaWmpSktLwz5XWVkZuj1lypSwy4aj\nbQsAAABgZAt/YSXzmJ7PTrZfTgwAAAAAQKLQxAIAAABIeqavGTU9n51oYgEAAAAArkETCwAAACDp\nmb5m1PR8dqKJBQAAAAC4Bk0sAAAAgKRn+ppR0/PZiSYWAAAAAOAaNLEAAAAAkp7pa0ZNz2cnmlgA\nAAAAgGvQxAIAAABIeqavGTU9n51oYgEAAAAArkETCwAAACDpmb5m1PR8dqKJBQAAAAC4Bk0sAAAA\ngKRn+ppR0/PZiSYWAAAAAOAaNLEAAAAAkp7pa0ZNz2cnmlgAAAAAgGvQxAIAAABIeqavGTU9n51o\nYgEAAAAArpGQJtbv92vGjBnKycnRhg0bBp1z3333KScnRwUFBTpw4EDo8z6fT7Nnz1ZRUZFuvPHG\nRJQHAAAAwGVMXzNqej47pdm9w2AwqHXr1mnPnj3KysrS3LlzVVZWptzc3NCcXbt26ejRo2ppaVFD\nQ4PWrl2r/fv3S5I8Ho/27t2riRMn2l0aAAAAAMDlbD8T29jYqOzsbPl8PqWnp2vFihWqr68Pm7Nz\n506tWrVKklRSUqL29na98847oa9blmV3WQAAAABczPQ1o6bns5PtZ2Lb2to0ffr00Njr9aqhoSHq\nnLa2NmVmZsrj8WjhwoVKTU1VZWWl1qxZM+A+ysvL5fP5JEkZGRkqLCwMnX7ve/AZh4/79Y0XRBn3\nCvT+64syjnHv8XI8X+8W0fbWN44X+fZGbhGlgoj5gd5/fUOMRb4Lx/GyP5/OZ/BdcFsXGcvsfNH2\nNsje4+KWfJeKfJH3EK0iuSpf/71Eq6B3HOgd+hTTOMreBuSz+/is/16iVbBg0PqjHo85fPzZn2GI\nPBHjeH/eyWfeuLm5We3t7ZKkQCCgaDyWzac96+rq5Pf7tXnzZknS1q1b1dDQoOrq6tCc2267DPus\n4AAAD0JJREFUTQ899JBuuukmSdLChQv1+OOPa86cOTpx4oSmTZum9957T4sWLVJ1dbXmz5/fX7DH\nw5naS+DxeCTF+n3zSFVx7Lwqrj3HJdbHOmH5qmLfa++e4+KmfPFmk8zOF8/zkMn5eG6JqKIqxqlV\nPLdcsNe4mZyP55be/SbRc0sijjsT+tglwXFyvPmSoeZ4mJ4vGUTr+VLsvsOsrCy1traGxq2trfJ6\nvRedc/z4cWVlZUmSpk2bJkmaPHmyli1bpsbGRrtLBAAAAAC4lO1NbHFxsVpaWhQIBNTd3a0dO3ao\nrKwsbE5ZWZmeffZZSdL+/fuVkZGhzMxMdXV1qbOzU5J09uxZ7d69W/n5+XaXCAAAAMBlBl5GbxbT\n89nJ9jWxaWlpqqmp0ZIlSxQMBlVRUaHc3FzV1tZKkiorK7V06VLt2rVL2dnZGj16tJ566ilJ0qlT\np7R8+XJJUk9Pj+6++24tXrzY7hIBAAAAAC5lexMrSaWlpSotLQ37XGVlZdi4pqZmwHbXXHONmpub\nE1ESAAAAABcLf2El85iez062X04MAAAAAECi0MQCAAAASHqmrxk1PZ+daGIBAAAAAK5BEwsAAAAg\n6Zm+ZtT0fHaiiQUAAAAAuAZNLAAAAICkZ/qaUdPz2YkmFgAAAADgGjSxAAAAAJKe6WtGTc9nJ5pY\nAAAAAIBr0MQCAAAASHqmrxk1PZ+daGIBAAAAAK5BEwsAAAAg6Zm+ZtT0fHaiiQUAAAAAuAZNLAAA\nAICkZ/qaUdPz2YkmFgAAAADgGjSxAAAAAJKe6WtGTc9nJ5pYAAAAAIBr0MQCAAAASHqmrxk1PZ+d\naGIBAAAAJL3m5manS0go0/PZKSFNrN/v14wZM5STk6MNGzYMOue+++5TTk6OCgoKdODAgbi2BQAA\nADCytLe3O11CQpmez062N7HBYFDr1q2T3+/XkSNHtG3bNr3xxhthc3bt2qWjR4+qpaVFP/jBD7R2\n7dqYtwUAAAAAjFy2N7GNjY3Kzs6Wz+dTenq6VqxYofr6+rA5O3fu1KpVqyRJJSUlam9v16lTp2La\nFgAAAMDIEwgEnC4hoUzPZ6c0u3fY1tam6dOnh8Zer1cNDQ1R57S1tenEiRNRt5Ukj8djd9kjRBzf\nt6qE7Tm+/cb1WCcmXyJ/2sgXNjv2qVUJ2Wtc4n8eMjkfzy0hVQnZa9zIFzY79qlVCdlrXHhuucQq\nquKsI565CTvuTNBjlzTHybHXEU/NzzzzzKUUkwCm50tutjexsT5IlmVd0v4vdTsAAAAAgPvZ3sRm\nZWWptbU1NG5tbZXX673onOPHj8vr9erjjz+Oui0AAAAAYOSyfU1scXGxWlpaFAgE1N3drR07dqis\nrCxsTllZmZ599llJ0v79+5WRkaHMzMyYtgUAAAAAjFy2n4lNS0tTTU2NlixZomAwqIqKCuXm5qq2\ntlaSVFlZqaVLl2rXrl3Kzs7W6NGj9dRTT110WwAAAAAApAS9T2xpaaneeustHT16VA8//LCk881r\nZWVlaE5NTY2OHj2qgwcPas6cORfdFsnL5Pf1veeee5SZman8/HynS7Fda2urPv/5z2vWrFnKy8vT\nk08+6XRJtvroo49UUlKiwsJCzZw509jnkmAwqKKiIt12221Ol2I7n8+n2bNnq6ioSDfeeKPT5diq\nvb1dt99+u3JzczVz5kzt37/f6ZJs89Zbb6moqCj0MX78eOOeX/7hH/5Bs2bNUn5+vu666y793//9\nn9Ml2WrTpk3Kz89XXl6eNm3a5HQ5l22w3+UffPCBFi1apOuuu06LFy929XtzDpbvJz/5iWbNmqXU\n1FQ1NTU5WN3lGSzbN7/5TeXm5qqgoEDLly/Xhx9+6GCFl2ewfI888ogKCgpUWFiom2++OWyZJSJY\nwCXq6emxrr32Wuvtt9+2uru7rYKCAuvIkSNOl2Wbl19+2WpqarLy8vKcLsV2J0+etA4cOGBZlmV1\ndnZa1113nVGPnWVZ1tmzZy3LsqyPP/7YKikpsfbt2+dwRfbbuHGjddddd1m33Xab06XYzufzWe+/\n/77TZSTEypUrrS1btliWdf7ns7293eGKEiMYDFpTpkyxjh075nQptnn77betq6++2vroo48sy7Ks\nL3/5y9bTTz/tcFX2OXz4sJWXl2edO3fO6unpsRYuXGgdPXrU6bIuy2C/y7/5zW9aGzZssCzLsr77\n3e9a69evd6q8yzZYvjfeeMN66623rAULFli/+c1vHKzu8gyWbffu3VYwGLQsy7LWr19v3GPX0dER\nuv3kk09aFRUVTpTmCgk5E4uRwfT39Z0/f74mTJjgdBkJMWXKFBUWFkqSxowZo9zcXJ04ccLhqux1\n5ZVXSpK6u7sVDAY1ceJEhyuy1/Hjx7Vr1y6tXr3a2FdtNzHXhx9+qH379umee+6RdH4Zzfjx4x2u\nKjH27Nmja6+9Nuyt89xu3LhxSk9PV1dXl3p6etTV1aWsrCyny7LNm2++qZKSEo0aNUqpqan63Oc+\np3//9393uqzLMtjv8p07d2rVqlWSpFWrVunFF190ojRbDJZvxowZuu666xyqyD6DZVu0aJFSUs63\nLyUlJTp+/LgTpdlisHxjx44N3T5z5ow++clPDndZrkETi0s21Pv9wl0CgYAOHDigkpISp0ux1R/+\n8AcVFhYqMzNTn//85zVz5kynS7LVN77xDT3xxBOhX+am8Xg8WrhwoYqLi7V582any7HN22+/rcmT\nJ+vP//zPNWfOHK1Zs0ZdXV1Ol5UQ27dv11133eV0GbaaOHGiHnjgAV111VWaNm2aMjIytHDhQqfL\nsk1eXp727dunDz74QF1dXfrZz37m6iZhKO+8844yMzMlSZmZmXrnnXccrgiX4kc/+pGWLl3qdBm2\n+9u//VtdddVVeuaZZ/TQQw85XU7SMvPoB8Mied5MG5fqzJkzuv3227Vp0yaNGTPG6XJslZKSoubm\nZh0/flwvv/yy9u7d63RJtvmP//gPfepTn1JRUZGRZysl6ZVXXtGBAwf00ksv6fvf/7727dvndEm2\n6OnpUVNTk77+9a+rqalJo0eP1ne/+12ny7Jdd3e3fvrTn+qOO+5wuhRb/e53v9P3vvc9BQIBnThx\nQmfOnNFzzz3ndFm2mTFjhtavX6/FixertLRURUVFxv6hrI/H4+F4xoW+/e1v6xOf+IRxfyiTzmc7\nduyYysvL9Y1vfMPpcpKW2c9MSKhY3hMYyevjjz/Wl770JX31q1/Vn/7pnzpdTsKMHz9et956q15/\n/XWnS7HNq6++qp07d+rqq6/WnXfeqV/96ldauXKl02XZaurUqZKkyZMna9myZWpsbHS4Int4vV55\nvV7NnTtXknT77be7+oVXhvLSSy/phhtu0OTJk50uxVavv/66PvOZz2jSpElKS0vT8uXL9eqrrzpd\nlq3uuecevf766/rP//xPZWRk6Prrr3e6JNtlZmbq1KlTkqSTJ0/qU5/6lMMVIR5PP/20du3aZdQf\nkAZz11136bXXXnO6jKRFE4tLxvv6updlWaqoqNDMmTN1//33O12O7f73f/839GqT586d0y9+8QsV\nFRU5XJV9vvOd76i1tVVvv/22tm/fri984Quh9942QVdXlzo7OyVJZ8+e1e7du415lfApU6Zo+vTp\n+u1vfyvp/LrRWbNmOVyV/bZt26Y777zT6TJsN2PGDO3fv1/nzp2TZVnas2ePcUsV3n33XUnSsWPH\n9MILLxh5pqusrEzPPPOMJOmZZ54x+g+5pl2t4/f79cQTT6i+vl6jRo1yuhzbtbS0hG7X19cbdexi\nOydfVQrut2vXLuu6666zrr32Wus73/mO0+XYasWKFdbUqVOtT3ziE5bX67V+9KMfOV2Sbfbt22d5\nPB6roKDAKiwstAoLC62XXnrJ6bJsc+jQIauoqMgqKCiw8vPzrccff9zpkhJm7969xr068e9//3ur\noKDAKigosGbNmmXcc0tzc7NVXFxszZ4921q2bJlxr0585swZa9KkSWGvsmmSDRs2WDNnzrTy8vKs\nlStXWt3d3U6XZKv58+dbM2fOtAoKCqxf/epXTpdz2fp+l6enp4d+l7///vvWzTffbOXk5FiLFi2y\nTp8+7XSZlywy35YtW6wXXnjB8nq91qhRo6zMzEzrlltucbrMSzJYtuzsbOuqq64KHbusXbvW6TIv\n2WD5vvSlL1l5eXlWQUGBtXz5cuudd95xusyk5bEsw/5EAwAAAAAwFpcTAwAAAABcgyYWAAAAAOAa\nNLEAAAAAANegiQUAAAAAuEaa0wUAADASvP/++1q4cKEk6dSpU0pNTdXkyZPl8XjU2NiotLT4fyX7\nfD41NTVp4sSJdpcLAEDSookFAGAYTJo0SQcOHJAkPfrooxo7dqz+6q/+KvT1YDCo1NTUuPbp8Xhs\nrREAADfgcmIAABxgWZbKy8v1F3/xF/rjP/5jrV+/Xq+99po+85nPaM6cObrpppv029/+VtL5BvfB\nBx9Ufn6+CgoK9P3vfz9sX+fOnVNpaam2bNmirq4u3XrrrSosLFR+fr6ef/55J+IBAJAwnIkFAMAh\nHo9HJ06c0H/913/J4/Gos7NT+/btU2pqqvbs2aO/+Zu/0b/927/pBz/4gY4dO6aDBw8qJSVFp0+f\nDu2js7NTX/nKV7Rq1Sp99atfVV1dnbKysvSzn/1MktTR0eFUPAAAEoImFgAAB91xxx2hy4Lb29u1\ncuVKHT16VB6PRz09PZKkX/7yl1q7dq1SUs5fQDVhwgRJ58/mfvGLX9T69et15513SpJmz56tBx98\nUA899JD+5E/+RJ/97GcdSAUAQOJwOTEAAA668sorQ7cfeeQR3XzzzTp8+LB27typc+fOhb5mWdaA\nbT0ejz772c/qpZdeCn0uJydHBw4cUH5+vv7u7/5O3/rWtxIbAACAYUYTCwBAkujo6NC0adMkSU8/\n/XTo84sWLVJtba2CwaAkhV1O/Nhjj2nChAm69957JUknT57UqFGjdPfdd+vBBx9UU1PT8AUAAGAY\n0MQCAOCgC19h+K//+q/18MMPa86cOQoGg6GvrV69WldddZVmz56twsJCbdu2LWwfmzZt0rlz57R+\n/XodPnxYJSUlKioq0re+9S098sgjw5oHAIBE81iDXZ8EAAAAAEAS4kwsAAAAAMA1aGIBAAAAAK5B\nEwsAAAAAcA2aWAAAAACAa9DEAgAAAABcgyYWAAAAAOAa/w+Usvuq8XGnggAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x110b11410>"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}