{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing with the `ggpy`\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# standard\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# I've got style,\n",
    "# miles and miles\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "sns.set_context('notebook', font_scale=1.0)\n",
    "cp = sns.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from ggplot import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br/>\n",
    "\n",
    "### Thing 1: Line Chart (with many lines)\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dt</th>\n",
       "      <th>kind</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000-01-01</td>\n",
       "      <td>A</td>\n",
       "      <td>1.442521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000-01-02</td>\n",
       "      <td>A</td>\n",
       "      <td>1.981290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>A</td>\n",
       "      <td>1.586494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>A</td>\n",
       "      <td>1.378969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>A</td>\n",
       "      <td>-0.277937</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          dt kind     value\n",
       "0 2000-01-01    A  1.442521\n",
       "1 2000-01-02    A  1.981290\n",
       "2 2000-01-03    A  1.586494\n",
       "3 2000-01-04    A  1.378969\n",
       "4 2000-01-05    A -0.277937"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = pd.read_csv('data/ts.csv')\n",
    "\n",
    "# casting to datetime is important for\n",
    "# ensuring plots \"just work\"\n",
    "ts = ts.assign(dt = pd.to_datetime(ts.dt))\n",
    "ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>kind</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dt</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-01</th>\n",
       "      <td>1.442521</td>\n",
       "      <td>1.808741</td>\n",
       "      <td>0.437415</td>\n",
       "      <td>0.096980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>1.981290</td>\n",
       "      <td>2.277020</td>\n",
       "      <td>0.706127</td>\n",
       "      <td>-1.523108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-03</th>\n",
       "      <td>1.586494</td>\n",
       "      <td>3.474392</td>\n",
       "      <td>1.358063</td>\n",
       "      <td>-3.100735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>1.378969</td>\n",
       "      <td>2.906132</td>\n",
       "      <td>0.262223</td>\n",
       "      <td>-2.660599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>-0.277937</td>\n",
       "      <td>3.489553</td>\n",
       "      <td>0.796743</td>\n",
       "      <td>-3.417402</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "kind               A         B         C         D\n",
       "dt                                                \n",
       "2000-01-01  1.442521  1.808741  0.437415  0.096980\n",
       "2000-01-02  1.981290  2.277020  0.706127 -1.523108\n",
       "2000-01-03  1.586494  3.474392  1.358063 -3.100735\n",
       "2000-01-04  1.378969  2.906132  0.262223 -2.660599\n",
       "2000-01-05 -0.277937  3.489553  0.796743 -3.417402"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# in matplotlib-land, the notion of a \"tidy\"\n",
    "# dataframe matters not\n",
    "dfp = ts.pivot(index='dt', columns='kind', values='value')\n",
    "dfp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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N0jVAi4mAoMPmmT4oNom2zOsKko7T3pcZgDcuNMo9ui8N47QPB2GzLPHtmacUtT86tbCE\ng4iIiGqWOYFQsus5vZ+nkh1Az3tfEN5eByKWpLIoA3OuCKf+l5walKCYvP3Mj5lmv5oPoO+66y44\nHA4AgM/nw5o1a/Dkk09CFEUsWrQIl156aXUPkIiIiMrGWIUQEB3FZYOtKxMCgK1h+ttLzvR1sgNw\nqi01HUArivFTy4033pg6784778SHP/xh+Hw+PPjgg+jv70d3d3e1DpGIiIjKyJqBLobdEkALkl5Q\nAC5bgmyBAXRNq+kAenBwEIqi4Be/+AU0TcOll14KVVXR0tICAFi8eDEOHDiQCqADgQCCwWDGNqLR\nKBobG8t2jJIkwWar/O88sixn/K20ehx3tcYM1N+4+fzmuCup0uOu9niBU+t1HVWNkgrJKRR3zJar\n6qoAu9027bgdTenTdqeEUtxFs+Hxplw1/WjYbDZccMEFOPvsszEyMoIHH3wQTqczdbndboff70/9\nv3nzZjz33HMZ21i7di0uu+yyih1zpfl8vmofQlVw3PWh3sZr4rjrQ72N11TsuLXBBIAY3F472tu9\nRd22sSeCiT4NkgNob2+f9vqJbgUnYCzS0tLhRUt76cKsen28Z6uaDqBbW1vR0tICQRDQ1tYGh8OB\niKX6Px6PZwTUa9aswbJlyzK2EY1GMTQ0VLZjdDgciMVi01+xxGRZhs/ng9/vRyIxfTP4UqvHcVdr\nzED9jZvPb467kio97mqPFzi1XtfHt9oByEggiqGhiaL22fN2Acefs6PldAVDQ+Fpx21ku424QnH7\nUYrwYbpxFxLYU+nVdAC9ZcsWDA4OYt26dQgEAlAUBTabDaOjo/D5fNi3b1/GJEKv1wuvN/PbaV9f\nX6qWuhxkWS7r9qeTSCSqsv96HHe1xwzU37j5/K4sjruyqjVe4NR5Xes6ML7PBQAQnWrxx+wA5rzT\nyCgryvTjtncAvlUC3N0JqHoCagnvomo+3pSrpgPo1atXY8OGDbj33nshCALe//73QxAEPPLII9B1\nHYsWLUJvb2+1D5OIiIjKQFcAwJhE2HJG+TPmggh0nBct+36o+mo6gJZlGR/84Adzzv/0pz9dhaMh\nIiKiSkpEjeBZ9mgQ7VU+GKopXImQiIiIapIaNcIc2alNc02i4jCAJiIiopqkJjPQ1gVOiEqBATQR\nERHVpFQA7WIATaXFAJqIiIhqUiqALnIZb6LpMIAmIiKimqTGjQC6kGW4iYrBAJqIiIhqkq4kA2iZ\nATSVFgNoIiIiqkmaGUDbGEBTaTGAJiIiopqkJRfuE23VPQ6qPQygiYiIqCYxA03lwgCaiIiIahID\naCoXBtBERERUk7QEA2gqDwbQREREVJNYA03lwgCaiIiIapIWZwaayoMBNBEREdUcTUmvRMgAmkqN\nATQRERHVnPHddgACHK0qBLnaR0O1hgE0ERER1ZyYXwIANC2NQxCqfDBUcxhAExERUc1RJowQx+7V\nqnwkVIsYQBMREVHNUQJGiGNjAE1lwACaiIiIaoqmAEpIAAQdNg8DaCo9Qdd1Tk2dwvDwMCRJKtv2\nRVGEplX+xS0IAux2O+LxOKrxFKjHcVdrzED9jZvPb467kio97mqPF5j9r+vAYQEHHrPB2aZh+UcT\nJTuG2Thun89X0eMhA+elTiMej5d1+y6XC5FIpKz7yMdms6G5uRmhUAiKolR8//U47mqNGai/cfP5\nzXFXUqXHXe3xArP/dX3gsSYAgKMlUdLjnI3jZgBdHSzhICIiopqhWxLETcvLmwSj+sUAmoiIiGqG\nnqzYEGQdrg61ugdDNYsBNBEREdUMTU2uPihxiheVDwNoIiIiqhl6MukslG/+PxEDaCIiIqodejID\nLcjMQFP5MIAmIiKimsEMNFUCA2giIiKqGWYNtMAaaCojBtBERERUM8wMtMgMNJURA2giIiKqGXqC\nGWgqPwbQREREVDNYA02VwACaiIiIakaqBlqu8oFQTWMATURERDUjXQPNEg4qHwbQREREVDNYwkGV\nwACaiIiIagYnEVIlMIAmIiKimqExA00VwACaiIiIaoaZgWYNNJUT56gSERHRKU/XgeNPuxE6YgMA\nyB6tykdEtYwZaCIiIjrlKRNCKngGAIePATSVDwNoIiIiOuVFhzN/VLc3q1U6EqoHDKCJiIjolBfu\nS88abOhVIDmqeDBU8+qiBjoYDOJnP/sZrr/+eoiiiA0bNkAQBHR0dODKK6+EKPJ7BBER0akqPi4i\nsNcOAGg7NwrfGbEqHxHVupqPHFVVxeOPPw5ZNr4r/OEPf8Dll1+OT3ziE9B1Hbt3767yERIREdHJ\nGN9rg64KcLSqaHlLDCJb2FGZ1XwG+qmnnsI555yD559/HgDQ39+PBQsWAACWLFmC/fv3Y8WKFQCA\nQCCAYDCYcftoNIrGxsayHZ8kSbDZbNNfscTMLxTm30qrx3FXa8xA/Y2bz2+Ou5IqPe5qjxeYfa9r\nQTMiZt9SFXZ7+Y5rto2bqqemH40tW7bA7XZj8eLFqQBa13UIgtEj0m63IxqNpq6/efNmPPfccxnb\nWLt2LS677LLKHXSF+Xy+ah9CVXDc9aHexmviuOtDvY3X5PP5oMZ1jB1R0bJIgiAI8NtjABJobPKg\nvb06iYpyq9fHe7aq+QBaEAQcOHAAAwMD+O1vf4tQKJS6PB6Pw+l0pv5fs2YNli1blrGNaDSKoaGh\nsh2jw+FALFb5Wi1ZluHz+eD3+5FIJCq+/3ocd7XGDNTfuPn85rgrqdLjrvZ4geq/ro+9IGB4iw2t\nqxR0X6QgHLQDkBGKTGBoqHzdN6o97nyPd3t7e0WPhww1HUB/4hOfSJ3++c9/jnXr1uHpp5/GwYMH\nsXDhQuzduxcLFy5MXcfr9cLr9WZso6+vD4qilO0YZVku6/ank0gkqrL/ehx3tccM1N+4+fyuLI67\nsqo1XqA6Y9Z14MAf41AkHaPbjSzzyDYb2s4LQ00Y4YymqzX7mV3Nx5ty1XQAnc873/lObNy4Ec88\n8wza2tqwcuXKah8SERERTSM2KuDwCwoAB1xdCUQGjBBG1wE9mXQWOHmQKqRuAugbb7wx72kiIiKa\n/WJj6cZhWlxIn44J0DXjf0HUK35cVJ9qvo0dERERnfpi/nTQHA+kwxc1KkBPrtqdnYHeEZjA1vHx\nShwe1Zm6yUATERHRqcsaNOuJdDCdiArQVTMDnb6+puv42vYdAIBfvfVcOCTmDKl0+GwiIiKiWS8R\nEfKen5mBNko4dF3HmGXC3XCcKxNSaTEDTURERLNeIpL/fDUq5Ewi/NK2N3EgFE5d50QshjkuV5mP\nkOoJM9BEREQ066lZGWjPAiPDrEbFjEmEiqZlBM8AMBSLV+YgqW4wgCYiIqJZTY0BSjAzZHG2GWnn\n7Ax0XNNybn+iSotYUe1iAE1ERESzzsgbdvT9yQU1Bgy+mFl+0dCrQHYbgXJGDbQIRNXcANof5wIk\nVFqsgSYiIqJZRZkQMPyKETS7u1SEjhnhSmO3iJ53BqHLCkJHjfNUaxcOSUdUM9LRnQ4HzvX58PjA\nAMYUlnBQaTEDTURERLNKIpIOT8IDErSYCLlBw5pPOWFzA4IASE6j40ZGCYeYLuFwSRLWtrcCQEZH\njnIZVxTsDEyUfT80OzCAJiIiollFjaUnDIb7jEyzs1WHIKTPNwPo6LAMNWqEM4Kkp0o4HKKIZpsN\ngFHCoeo6Ennqo0vlq9u24+btO/DmeAC6ruOJ/gHsnmBAXasYQBMREdGsokbTgbKazEY7WzKDX8mZ\nGwwLEhBLlnA4JBFNyQB6XFHwj29sw6dfex2qXp7lvgeSExW3jgewNxjC3YcO45dHj5VlX1R9DKCJ\niIhoVtFiuYumOJIB9K5AALfu3I0TajTnOoIIxLR0BtomivDZbNAAHI1EMKYoGC9DOUfAsk1BAA6H\njTZ6LTZ7yfdFswMnERIREdGsouYJoM0M9Ne3bUdEVRHZr+Jv0JlxncORcKqEwykaq6r0uJzwWwLc\ncmSgd08EU6eHY3FEVCML3uvm4i21ihloIiIimlWsJRwmR7MR+JrB6ZFI7tKE/75nbzoDLRkhTo/T\nmXGdfG3uTtafh0dSpwdjUewPhgAAvS7nZDehUxwDaCIiIpo1Qn0SxnY6AAAdFxhBsr1JhWjLvF4w\nkci57XAshmgywHaIRojTmRVA51to5WQdjaRXPtwemMCO5OTBFjtLOGoVSziIiIhmqbim4XgkgoUN\nDdU+lIo59oQnddrRrGLRXwUgSDoA2+Q3StKRroF2SkYJh0vKzBWafaJLaXiSpcJ9tumPmU5NzEAT\nERHNUv/85nZ8Yeub2GOpsa01ug4Mb3bg6O/dCA9IGZfJDTpklw4pmciNq5nBb1TMnBBoDaDNDLRD\nzNxmrMQlHBFVRUhV8wZUTQygaxYDaCIiolnocCiMAyGjNGBfsHYD6PAxGSNbnAgft2Hg+cxJd7Ir\nM9g9mNVX+e4Fr6ZOxwUVOpAq4XAmM89OMTPUiZW4hMPMPnc6HTmX2USGWbWKjywREdEs9LLfnzod\nL1Pv4tlg4lA6S6uMZ2aLxawS4u2jxn0iJxdUOe6awC9734AiqHhg7hvQdd2SgTa2ZZeyA+jSlnC8\n7B8FAHQ7OWGwnrAGmoiIaBbaY8k6ByqwFHW1RLLKNqby0uAgAGB1cxNe8Y8BALY2DeJN7wlogvEl\nI6AYkwvNEo7sDHSpu3A8N2R04LiyqwuvjY2nzv/gnJ6S7odmFwbQ07Db7ZCkwl/cxRJFES5X5ftE\nCoKAcDgMm80GWa7806Aex12tMQP1N24+vznuSirXuIOWQC+iI7WPao8XSI85pqp46NBhXNLRgdMa\nPdPf0ELXgf4XJcTHJQiyDlHObF+3/K/jcFru14iq4vn+AYgAruztTQXQAFLBMwAMKUZJhdflhMvl\ngjee+eVDk6QZP17Zj3VQUXA0EoFNEPDWrk5cH4vhsWPH8aNz16CjRBnp2fB4Uy4+EtOIx/PPrC0V\nl8uFSJ5eluVms9nQ3NyMUCgEpQqZjXocd7XGDNTfuPn85rgrqVzjDlg+f/zRaGof1R4vkB7zI8eP\n41dHjuFXh4/gt+efh10TE5jrcqFhmkBPU4F993uha0bA7GxTERnIvI1mj8B6tx6Px6HqOnpdLnRO\nkdgaSN5ISKjGfZZ1HwVjMfx4xy4MxKL452VLIQq5PaenG7dpx7iRcV7Y4IYai+EDXZ24prMDgq6X\n7Dkx3ePt8/lKsh8qDgNoIiKiWcja53giT8/j2eBYOL2c9j9t2449wSCWN3rwnTNOn/J2kT45FTwD\nuQG0IOkQsmZpDcdiAIA2hwONtsnDl4ia1YUjqwb6oaPHUqcHozF0n8RiJ6PJ7HaHI70NoYiAnE5d\nnERIRERUJSeiMbximSxo0nQ9I4Aem6U10LKYDhbNmu1dE0EcDoUnuwkAIDaWDj8kl4aWt8TQeeHk\nGdvfHu/Do8f6AABtDjs8soy/njcXfz2vd9LbmF04HFN0wjiZntD+eBzf37cfAOCzs11dvWEATURE\nVCXf2LETt+/ag7+MjGacH1FVWKe69UWj6ItEMdtE1fwB6Oe3bkN4kqy5GhUw9JJRR9z+tggW/9UE\nZLeO5hXpkhVdTQfmfZEofnHkKLaMGTXPbQ6jXdy1c3pw7Zw5kx6b2YXDOUW5R6GZ/YeOHsMX3tiG\niOX6vx84kTrdzH7PdYcBNBER0UkKJhKpEoNC6bqOweRtnhseztkeALQ70n3cPvf6Gyd5lKU3Ep88\nM/7p117Pm133b0+PydObP4CV3ZYJlFlBelfW5LwLWlsAAO6sQNnMQNunyEAXGkD/+thxHAyH8eyJ\ndNCs6OljzN431T4G0ERERCfp05u34NOvvZ5RdjGdgOW6/dHM7LJZstGYNRlvNmWhdV3H8eREuS8s\nWQxbVu1vWFVx+649ObcLHTPG1PP2EOzNmS3lpOTCKZ4F6cDcGqgCwJqWzElz/2vRafjS0sX4lxXL\nM843SzekKWqSJ5TiasvHLV8YBqPpL0xTBelUm/iIExERzcBwLIaj4QgUTUM0uXjHUBFZ6OOWLg2H\nwxH89MBBfH/vPoQSCXz1zR0AgN6sdmubx8YwWwzGYggkEvDKMi5qbcF955w97W10HYiNGdlaV3du\n+cfcK0NSagLiAAAgAElEQVRoPSuK9vPSXxTCifT13LIMnz1zdRWXJOHC1lac1uDOON9a+/yJBfPx\n3q7OnP0V8oUnblm5cDTZGUXT9dRj3eFw4MLW1mm3Q7WFATQREdEMfO71rfj7N7bizj17U+fFi1gm\n+lhWNvnJwRN4bngE39q5K3Vej9OJ756xEg3JEoHX/FMH0EfDEfzswCGMV2DS4f5gCACwtNEDQRDg\nKaBHcSIkQFcESE4NsjN3dUWHT0PbOTGIlooIawnHVEtjy6KIe9esxhynE2d4GyFbrntVdxc+sWB+\n6v/eZOeNQko4rIvY9IWNLz13HzyEfSFj/P+yYnlOpw+qfXzEiYiIiqTreipYfqKvP3V+eJJJdfkc\nS2ags+tn9yYDUwA4t8WHZY2N+N4qoy3cQHTyEo6oquLrO3bg94OD+OmBgwUfx0z1JY9lbhGLksST\n2efs0o2pWO/T6UolWux2/Oist+DbK1fkXCYKAlY3NaHX5cS7Oo1sdCgx/eM1binzOBYOQ9d1PDmY\nroX2yKx/rkcMoImIiIoUmyTTHC4gIDOZJRz/e9Fp6Mmzat35LS04raEBgFGmACBVKmKl6ToiqoqP\nv7I5FeztmgjmXK/UzGDeOqnv84sX4ZK2ycsZYv5kazlf4fdTuMAMtEkQhEl7MX9j5XJ8/8y3wJfs\nmlHIFx5rC8HBaBRHshZImW7RGKpNfNSJiIiKNFntbKiIDHQgGey22O3odjpTGV3TcsvS2KkAOmv7\niqbhH9/YBr+iIK6nSyImC/BLqT85ia7b6Uidt7a9DWvb23BNTw/+ceu21DGage9JZ6BLUCohCULq\n/szu8DHd/nUA9x48nLM9qj/MQBMRERUpmMw0t2ZNaCumhMNcxMMpiWjJsxCHtX+xOSEuqmnQkoGy\nruv4wtZtOB6N5uy3EgG0OaGuJes+AIAFDW548gSpyoQRbNq9hR+f9fZv7cidCDgT7mTZxXA8Bl3P\nrcW2yq5r3xYIlOQY6NTGAJqIiKhIZga6w+HIOH97IICEpuGxvv4p65UBIJZcctopSjjD602df3l7\nGy5rb8PatrbUeaIgwGkG0cmAcs9EMGciokmdJiicicPhMJ4bGsbRsLHKoBmkuybpgexOljZYg3st\nYQTQor3w4zPrlOe73fjsGSuLP/A8zGM+Folig6WGPZ9iJoZS/WAJBxERUZF+uN9YwtkhivjKyhX4\nz527kNB1vOofw//Ztx8vjoziueFh/MdbVuXcNqqq+OnBQxhKZnAdkoiL2loxnkhgZWMjFnka8u7T\nKUmIahqiqoYDgQDuPnBgymPUdX3SWuCZ+N7uval+1Q9fdEEqkJ9sqWx3ngy0ngyg7z5yEN4I8LF5\nvdNODIyoxpeVj86fB5csoxTV3daJm784chTXzOmZ9LpmAO0QxZzMvpP9n+sWA2giIqIiqLqOoZgR\n/B6NRHB5VydENYHv7jba2b2YXJb7QCic9/ZPDAzi2aH0yoNOUYQoCLiqu2vK/ZrBWkRTcd/2ndgV\nmJjy+lFNmzQ7XKyEpmUs9jIQjaaCycmWym5IlkkELF0stOTJraFxjCTCWNXkxRpf85T7NjPYpVzt\nL3tbE0oCjbb8IZEZQM93u7An2SFljsuJD/f2YpnHk/c2VPv41YmIiKgII8nMMQB8pHcOAOAcny8n\nG9mWpzYYQEaPZgGFr2JnnUj4Qv/UZQdAYYuEFGo0a8nuwWgUOgBZECadRGfWh1vvL00xrhsXjaB4\nIjF9v+pUAF3CdnHZQf9U/aDNLwrdlm4j7XYHLm5rRYfTMdnNqMYxgCYiIiqQqut4OtkDeHFDA97R\n2QHA6MTwzuRpU3bLtVAigX/ZsRObRkdT5zlEseAyCzPoiyTUgm5TSI/jQp3IWmFxIFl7PVUJQ74A\n2izhUJIBdCFt/9IZ6NL9aJ4d9Ec1NTU5M1s8TwA9x5XbdpDqCwNoIiKiAv1+YBC/Od4HIDeIanNk\nZpzHFQXf3rELv+sfAAA8NXgCW8cDqfIPAEWtYOdMXvdYxFg+fDohtXQZ6OF4ZgDdn+yFPFn5BpDO\nwA8nx6vr6RIOMwNdSNu/SKL0GWgA6LRMAH3NP4aPvfwqnhgYyLmeGUB7belOKdbTVJ8YQBMRERVo\n00g6ezzf7c64rM2e+XN+WFWxZXwc9xw6jMPhMMQ8WWO7UPjHsFnC8foUy3m/rcWHhcnjKmUJh7lA\nizkCM4Ce6gtAa/ILxUgshrGddsRGREAXoEKDJhjZ3kKy5OWogQaAH5y5CkuTEzYfPHoMMU3D3Vk9\nnoF0AG0ttSlm9UWqTQygiYiICtRjyTqf0eTNuCw7A221MzCRN6BNFNFurj2Z0X1heDjv5QvdbvzT\nsqWpwL6UJRyBZN22mXU/kVxExSlOlYE2vlA07WvB4P9z4dhTRrBqZp+B6bPkqq4jqmkQMHW2eyYc\nkoQ2R24Nc3Z23xpAf2/1mfjo3F6c1+Ir6bHQqYddOIiIiGbAXGbb1G6ffELZ3mAwbwa6mAC6M89y\n31bm5j3J/stTTYwrViC5rXaHA8ciUYyZLfimqIE2v1CcOd4NAFDDydUILQH0dAvPmK3yXJKU9/47\nWfm+APRFopjfkP51IZYKoAWc6fNh6TSPA9WHmg6gNU3DY489hpGREQDAunXrIMsyNmzYAEEQ0NHR\ngSuvvBIi+zgSEVEBzKzul5YszpmI5p2kDRoA+BUFcp4AcKrbZOvK6vjwlqYmbB0fz7meGbgOZU38\nOxkTSjqABtKB71QlHB5dxscPr0ZnLLPVm2LNQE8T5JulIw0lrn825fsCMBDLDKCtfaCJTDUdQO/e\nvRsA8MlPfhIHDx7EH//4R+i6jssvvxwLFy7Exo0bsXv3bqxYsQIAEAgEEAxmtmiPRqNobGws2zFK\nkgRbFSYjyMkMhfm30upx3NUaM1B/4+bzm+Mul0gymGp0OFJjnWrcp3u92B4IJJfgzr38U4tOK/g+\nW+TNLBn55pmr8LmXX031ZxYFETabDV3JEo4XR0dx5ZwezG/IvzBLIQ6FQvjXN3dgMBmMd2XV/pr7\nzGd8u4wVwdyylriootVux0g8jrCmTTn+E8le13Nc7rI8zlE9Xa7hkiREVBVDSiJ1TKOxOLaOG0t3\nu+z2unw/o/xq+tFYsWIFli5dCgAYHx+H0+nEgQMHsGDBAgDAkiVLsH///lQAvXnzZjz33HMZ21i7\ndi0uu+yyih53Jfl89VnHxXHXh3obr4njLp94Movc296G9paWnMt/tvYSfOe1LTg4YQR+53Z3YXsg\ngBjS5QimH198Ic7t6MjZxmTaAXwqMIF7du4CAMxpb8cvrng7rtj4OwBAp6cB7e3tWCJJwM5d8McV\nfGP7DvzuyvfMaEXCcCKB//XnFzLOW9zeDhxKT7S7ZslitLe35739hBwHYNROh6Q4GlQjmI4LKpb4\nmjEyeAJ7J4LYMDSM986fh00Dg7j6tIWpzP7/HDuG/5fMsC9uaUk9vqV8nKPJxW8A4DOnr8T3t27D\nCU1LjelP+/anLu9saYU360tMJdXr63q2qukAGjAyA7/97W+xc+dOXHfdddi/f3/qjcRutyNqWVlp\nzZo1WLZsWcbto9EohoaGynZ8DocDsRL+zFYoWZbh8/ng9/uRKGGdXKHqcdzVGjNQf+Pm85vjLpfx\n5GdGfGICQ2YZg2XcPQB+tPpM/OboMWwfH8f53kb8F4BANJaqSfbZbQgoCTTE4kV/vry3tQVvtrVi\ndWdnary3v+UM/OboMXxy3lwMDQ3Bbum7PBKNYdfx43kny03nLkvwCBi9k71Z9+/pdtukY4hEZQBG\n0NznnMCSUKtxvpRAjyWLe8/OXXho716EEiomgkG8t6cbJ6JRfO3lV1PXaRUAv99f8sfZbpkweFqy\nTOQPR47ir3q64ZFlDFlKZBpiUQQCgVn3fjbZFxgqr5oPoAHgmmuuwTve8Q7cc889GU++eDwOp2Uy\ngNfrzfl22dfXB0WZfqWkmZJluazbn04ikajK/utx3NUeM1B/4+bzu7LqYdxmza5d11P7yjfud8nd\nuEzuhQSj3dtoPA4NgF0QcOdZZyGQUNAsiTM63ltWrkB7ezuGhoagKApWNDTg68uN5I+iKPAIAj4+\nfx7uP3wEAHAgEEBT89TLZefzut+f8f/ZzU1oFNOZbIcoAqoKZZKJgIl4umZ4zBZJnQ5LCrxZHTXM\n2vIdY2N4Z3sb/JbkFgCc0+RNfX6X8nH+67lzEE4ouLqnB3MdDiz1eLAnGMROvx9nNTdjOHkcN86f\nB5uuQ1XVuns/o/xquiL+jTfewPPPPw8AsNlsEAQBPT09OHjwIABg7969mD9/fjUPkYiITiHWrhBT\nObyhEf1/ckOcMDKtZp6zyWaDQxJTk/HK5eqebrw7uTLikXBkmmvnZ63Z9sgyPrNwYcbKg55pJvap\n0fR1g3I6Kx6RFDROUs8bTAbSEUtQflZT04wy6IVoczhw8/JlWOk15jotSfaF/t3AIADjiw+QXlWR\nyFTTAfSKFSvQ39+P++67Dw888ADe/e5348orr8Szzz6Le+65B6qqYuXKldU+TCIiOkWYbeesHTUS\nEWDgBSeiI8ZHqmb9lV0RM4LOpgpOQDOXnh6MzqzkQLW02PvkgvloddjhsHxxmG5pbTWavo+2eQdT\np3VBR4Ms4eqe7pzbHImEkdA03LJ9Z+q8f1yyaEbHPxPLk00DXvWPYTgWw2jcyPj6GEBTlpou4bDb\n7bjuuutyzr/xxhurcDRERHQq03Q9bwB96EkZwWMiIgMyFn4wiPh4OmDWNaMFWzRu5KArGUB3Jtve\n/X5wEMejEbgkCUs8Dbiio6Ogpag1pANocxVAa+u+6dq6mQH0wKp+9GkTqfMbZRlnNbnxVp8PV3Z1\n4uY3d2AkHocOYCgWxyuWlRYvbm2t6LLZ57e2AMl5hQdCYewPhSAicwEdIqDGM9BERESlYg2erV0t\ngseSC4SMSVCCAqJD6SytpggZmdoWewUDaEc66Ns6HsBLo348cOQYfrT/QEG3t5Zw5FtGWxan7uyR\nCBn3i96emQG/oK0FDkmCIAhodzhw19ln4YFz1+C0ZO/l3RPpdrJT9ZkuB0kQsCo5F+rFkRGouo6z\nfc1orlILUpq9GEATEREVIJHs2GCbInA88aILgX3pn/v1BNBkswbQ+UsBElEB4YHSLhaSvfCK6VVL\nhncqmqWEI1/Nt882eVmDrgNK2LifHMl1VCKiUQ7h7c5cKlsSBLhlGT1Oo8f07mA6W60WsVJjqZi1\n3QdCYQBILY1OZMUAmoiIqABKMpizCZYSjaz4LnhURnwsfbmmCBlB82QB9JFHPTj6uAfh/tIF0U5J\nwlXdXTO+fczS4s36neGq7i4s8njwt6ctyLlN8IiME39xIhEWAE2A5NTgthv3x/9Z/CIemv86vPPz\nd+0wA9ejlkmP1mOolIbkBMejEeM4Oso84ZNOTTVdA000G4UHJIxsdqLz4gjs3sp/OBDR9HRdh19R\n4Et2cAIAJU8GWs/qKuZsVzNLOBICfO70z/++SUo4lAkjyAz3y3B35w8wZ+IcXzM29g8UfTtd1zMW\nfrF2DfnEgvlwuVyIRHK7exx/KrnqYfIukht0LEiWZgRsMexyDEMQFubdpxm4hiz7jVcjgM6aHMkA\nmvJhBpqowvr/5Ea4X8bRJ2a+vC4RldfzwyP45OYt+MBfXsbBUAiAtQY6/dGpKpnlHImgCOjp8zQl\nc+JgW54MtGU1aYhyaUsWJst4TyemaanWe3euPhOeIpeRjp4wvkTILg1NNht8yftgqoxyvjrr06uw\n8p8zq+6aATTlwwCaqNKSn4+JIF9+RLPVXcn1AgDgzgPGaSU5q846eU5LBtBCMvBNhDNf13pCSNUP\n21UJtk1tCB7ODEYT4fT21HjxS25PxTfJ5LcxRcF3d+3Bv+7cBT1PnXE4mQVussnochbfgcK8H0S7\nse1vrlyOZpsN1+RpXWdqyOorfXVPN97b1Vn0vk/WUCye8X+7gy3sKBc/wYkqTPakMzBVmB9DRAVo\nktOBpzmRLZFMFVtroIdfMYJLmyd/ZjU+LuLS9jZc2t6Gb7hXI3TIjuNPZ/76pFi+TKuR0n4sN8gy\nPrdoITqzsqjbxgN4ye/Ha2PjqWDZylzIJF9WOB81lvl+Zn4pEJN34zy3G/euWY2/mT9v0m1k95W+\ndk4PbNO0yiuHc3yZqzZW4xho9uOzgqjCdNVSP5mY4opEVDVOS+A4z2XU8MZDAq7uW4HWaLorQ/Cw\nESEqE2IqC201ccAOOS7jHxYvQm9DOpMbD1iyzhHroiylzUADwDs6OvDt01fg3Z0dWJjsKPHS6Gjq\n8oCSwFhcwX8dOoKt4+PQdB1R1fhCMN2KiwAQPCxj34NenPhLenzm+5yZgQYAUZh6bA1Z+8r+v1Le\n1uKbdKVEIhMDaKIKU2PpD5G99zchMlSdDwkimpxfSf+MryfrrvRXmvE2/1y8d9cZxv+WpLOuCpAc\n+X9SMrtyaJYvz/Hx9OveuuR16IgNRx5vgDqzxQMn1eFw4DOnLcSH584BALw06k9dNp5Q8JMDB/Bo\nfz/+Zccu/PLoMfxh0Fg50ClO//50/OkGQBMwtj23VtgaQE/HnpXpFaYJuMtFEAR8JtlhZE1z89RX\nprrFr1hEFabFMj8U/FvtGI4bH749l+fOaieiytgXDEISBPhsdowr6Z+HUp0gxoxss1uxA4hAy6pX\nlpw6EsZ8Q/hOj8GfDCjNFfmsvzglQpYMdDRzO5EBGWM7HGhdXeIoGsBSj9GUOWGptwgoCey0LF7y\nyPG+1OnxRFabkSJJtsIDaK+lX/aPz3rLSe33ZF3Q0oLvnrGSPaBpUgygiSpI19KTjkwTBy2LLlwW\nQZWSLkR1TdE0fHnbdgDA32X1NzY7R+hCqjsbgMwJf75VMcT9ImIwMraNpynQNWBspyM1oc762jdX\n6QMyf5UqN5/djrkuV6rHMQCMK0reiYQAcDwSnXabol3P+TJhvaxQ89xu/OPiRZjjcmGOy1Xw7cpB\nEAQsa2ys6jHQ7MYSDqIKmuxDxqSXrv0rERVhXElnWu86cAgAcEFrC4B0Btos5TCZga9o19H+1igk\nZ/pyR6sKyZWcfJisa9YS6de/Ygmg89U9FxN4FuvcrElyY4qCyfaWPfkwrykOVSwiAw0Al7S3YZGH\nLT5p9mMATVRB02WasrPTRFQZY0puqcK6LmMVv7glA2119HdGoOdq1SEImTXOogzIbuN2aioDnb5t\nRuu6PO8L5ezQ89YWX8b/fzwxlHfBkrf6fPinZUum3JauAxonQ1MdYgkHUQVZM9ANvQo63hbFwd+k\nfybUEkDML2L4VSfazonC4eNKhUSV4M8KoL2ynFpQI66Z0Ww6qh153QE9mVEO9ScD5Mz2wZCzM9CW\nL8jW9wLztLM9geiQ8bGsl/HL9BKPB0s9DVB1IKqpOWUanQ4H/r/VZ0IqoJ5M15D7zcLC0cL3MKpN\nDKCJKsjMNLl7Euh9dzjncl0RcPzpBigTIuJjIhZ+KJhzHSIqLV3X8W+792ac55DEVFeImKZhJBZH\nMG6HWfww/Gq6ZVvrGUbtVctbYggft8F3hjH5L7uEQ7eUcFgnE5st39rWxHDsSeNjuZy/RomCgO+t\nMjqJ/GloCD/cdyDj8m+fvqKg4BnIH+h3XhiBZ74CNSbA3sQAmmoTSziIKsicdDRZfaOmCFAmklmv\nAF+eRJUQSCQyulIARvs2M4COaxruO3wYLjX/qn49FxgBdMMcFYs+FkD7eUZGN7eEw1K2YTltdueQ\nGzR0nB9JXvdkR1WY7KWyG2UZLZOsXphPvvINm1eF7Nb5CxrVNH5CE1VIbBwYesnIWk3WL5Y10ESV\nNxTLbRfntGSgR+JxvDTkh0PL/dHW1ZWAZJlnJ7v1VCcdawZa1zOD4owSjmQGWpD01KQ764TDcuqw\nTBIUAdyzZjXkIlbeM7PqNq+KpuUxODsScHVwNjTVPpZwEFXI/kdtqd6vk2egM/+PDElwtqoQ+FWX\nqGyGYvGc86wZaACp7HNQiqN1UQKxPUZ/YDPLnI8oAaJDgxYToUaFjKBYTwjQNUAQ0913RDndtaIa\nX6Y15C5mMp2xXUYbTkECui6avuUdUa3gxzJRmWkJIDokIT6e/kCcLANtTiACAOgCjjzqwdgOe97r\nElFpmBno+e5072FrBhoA3MkAWnbomLM6XbcgN0zdLkNOtrZTI0JOUGyWdJlZXCMDbVxWqRKOk+V/\n08hgx/1cUZXqCzPQ07Db7ZCk8r0xiKIIVxUaxguCgHA4DJvNBlmu/NOgnsZ96PcSxvZlPodcjTJc\nLuPDWXLoqcmFo1tze66GjznQc+7JPQer+XhX47Hm85vjLsSEouCp/gEcTQbQi71eHA4bNcgNdjs8\nllXozAy07AIafOkJhI1dEkQRk45bdgqIjwM20ZkKlEWbDk0REDnkRvMSLZWBdntcgNneLiFNus1S\nP842UYCS7DRS6OMniiIctszrlvuxr/bzG6jP9zPKj4/ENOLx3J/2SsnlciESqfzyzTabDc3NzQiF\nQlDy9D8tt3oa99i+ptwzG6KIRIxPzd4rYzj828lXvIoH9ZO+r6r5eFfjsebzm+OeztFwBH//xtaM\n85Y3uPGMuU0983VnZqBhUxFTFADJX4ZcUWiaffJxS24AIiLBODTF+MiV3Rri4xL6XpDR/xcdumYE\nzdF4BJosALAhNoFJtzmT8Qb22yCIOhoX5s76O73Ri9fHx7HA7S748XO5XAgMxpC6HzD58ZZKtZ/f\nwOx8P/P5fHluReXGEg6iKnA0p+smna0aui7JbWlnio+L0Dgnh6ikfn3seM55Z1g6Ujizfnl0aUYA\nLTqMSYJNy+JwdyfgbJv6xWmWZKgxwWhXJ+iwNaZf/9byDUFIloSIOtSwCC2R7LN8kiKDEvr/5Ebf\nMw0I9+X+mvW/F5+Gq7q7pl00JZu1U9DcK9lyk+oLM9BEVWBd8hcA7JZ2T86OBERZR7gv+cmrCxh4\n1gXZo6PjPE7SISoFv5L562Kb3Y42ezqb6siaTNeQSNdAA0DXxYVlIc0Jw+bKg6KMjADaJMjG9QQR\nsHk0KAEJkQEZ/c+54JmvnNQEvcC+dFu60DEb3D2ZQX+L3Y5PLJhf9HYTyfZ8TctjOdskqnXMQBNV\n2Jx3hXLOczSnP3wku46et4fRdk4Uri7j59aJg3b4tzlSXTyIKNdwLDbpstTZsq/zD4sXQRZF3HTa\nQvS6nFjjM5ZMMV9xTYpR92zzFLfGttlVQ42Iqf+zv0ADRscOk81rHNvxp91QIyLGd+XOjShGdCS9\n8eARuSRZbSD9pUB2l3HdcaJZigE0URklorkBr6s9N1MjWtYtUGMCJAfQelYM7u7MesUYZ7oT4aXR\nUQxEczOy/33oMH60/wBu27V72m3445m1pD678SJ8Z2cHfnTWmVjeaMxLMFfka1GMiWOOPNnjqZgB\ntBlsCrZ0r2crQUqfZ0/uw1yh8GToeub7RnxMyshIz5QaN7oLAVO38iOqVQygicrIvzW3BZ2Q58PT\nKhFJvyw987IDaL5kqb7tDEzgu7v34qYtb2A0HkdUTX8hfc3vBwBsHQ9MuQ1N1+HPmozVPMnqe+Yr\nzhc3AugGb3FBrZh8CzDLHUQZaF4Rh2e+ArvllyfBUlCZU+Ih6NBnmORVJoSc5bbN1nMzpQQF7Pxv\nG8LHzc4kzEBT/eGnMVGJWT/o8mWMJ1sUxbPA+EBvXJj+YHdkTVCKDjMDTfWtz5J5/uTmLfi3PXtT\n/xcaZE4kElB1PeMD0D1Ju9LzWloAAC0JI4B252mqM5XsDLRoM3o9z7kijKal6Tps0ZKBzgmgdSG1\n3HexYqPGuNw96fcVu6/4euWBP7tw+LEG6KqxeIo5HoAlHFSfOImQqIT82+0Yec2BuVeF4GjWUlkn\nK2GSBFb3JWEET7PBM0/JuK6zI4HoCeOlav4lqlfZge6WsXHoycg5VkDtMwCMJtuT9rpc+MCcHrgl\nCcIkL8zPnLYAKxu8cGyXIYj6pIsgTSYdQJsZ6PTtrSuSCpZh2Ztzx6HGhbylH9MJHzfeM5xtGpqW\nhdH/J3fGMuKFiPlFjO8xUumxMRGhI5nZemsmnaheMANNVEInNrmgxkSMvmH8RGrN0kxHtAPe0xSI\nWTFy7zvD8K0yFnpQJsRTZoUyonLIN0FwTFGg6zpilnIOdYp09Giy/rnFbsfa9jac2zJ5H90GWcbb\nvZ0AAMmlT/oFeDLmhEEzaJU96eO3zn1o6E2nmPMF0Fqs+HpoTUkvte1ZoMCW3Lda5LaObPSkTqsR\nMeN9rXllLGMcRPWCATRRGQiSDl0zlu8FdHRcEIEo63k7cExHchrt6ySn8eGXvRwwUT2J5mmKfjQc\nxoSiwBp2WoPpbCPJDHSLPXeOQj7mvATJVfxkOUdWdtZhaVkpWLLRLWfG0ucLRreexkVxOFqM26tF\nZo0BQAmKgC7A5lXh6lBTwbyaZ3LzpNsICRkZ60RYSAXgCz80gY63sbUm1Sf+HkxUItaEl2gzZ6gL\nkJwafCvj6F4tIRqbYSEjjJ+C1agZQLPmkOpTVE0HoJ0OBwZjMfjjCkayunJENQ3mQty6rmM8kUhN\nFDRLOFrthaVOjS/CM5ssJ2e1vTMDYgDwzE3AtyoGzzwlZ26EZ24CnrkJHPuDG7FRaUYZ6ImDxvhs\nDcYxmOUnarTw3Fn0RGbJTDxgBOWirMPexO4bVL+YgSYqEfNDFgD82xypnz3dPUbQPNnkwUKZP5Nq\nM4/BiU55ZteND83pwepmY0ZfQFGwZXgk43oRSwb6oaPHcOOrr+HNZHeO0aIz0MZrW5pBAC0IQOPC\nOCDo8C6Jw9Vp6bwhAh3nReHunjxbbtY9F/vLk6YAI68ZvavNX69Ehw4IOrS4UPD7iBLKfOOKJydG\nSyfXyIPolMcMNNEM6Krx06bdm/xwSwAHHm7Me92mpaUpWjZ/7mUJB9WzaLIG2iEZv/AARgB9cHg4\n4zsOE1YAACAASURBVHqHQmG8POrHFZ0d+L/H+wAAzwwN4Ywmb0YNdCGUoBFEzrTfcfflEXSpkZz5\nDYWY6RfnhOULvVmCIghGNloJCkiExIIyyGbm29akQhmXEBtLlrPkWQyGqJ4wgCYqUrhfwtHfGdnl\nueuCcHepiPTLky564GgtzQx1MxOV3dOVqJ6YGWiXKKaW255IJHAinrk0908OHERYVfF4/0DqPDOX\nmq6BLqyEI5Zcyc/RMrMAWhAy+zwXI5WBLrIGWoulM8etq9PlLbJHgxIUoQQF2AtoyWfu19GsQRmX\noIwzA00EsISDqGhm8AwAI1uSnyJTfLaVapEBM3vFEg6qZ9YMdKNsvCgCioLhiBEkdjiM12Q4GWiP\nWhZMGYwZE/WKLeEwA2hnib4MFyMVQCeKC6DNiX6urgQa5qSP2+zEkQgV9vFvTl7MblXHAJrqHQNo\nopMQPm5DfFyEFs+9THJoM+q6MRnzgzQ2KiE2ypcu1Sezu4ZTElMB9J+HhnE8ZLzWup2TR3YnojEo\nmoZAIgERQNMkqw9a6Xq6HWXOAicVMNMaaDOAlrM6h5gBdLivsJS4lgqgM7fD1Qep3vFTmOgkHfld\nA8Z252ayFn4oCM/c0qWLzQ/SkS1OHFrfyH7QVJdCZgAtSvBZSjB0ADZBQJfTOelt/YqCY5EIAKDd\n4YBUQFNnXQEAAYKsn/RE4JkwSz/82xwIDxS+EqnZqi67Vtm7xHjjCOy3QZ/m+0A8ICB4OLlcd0Pm\nlZ0+BtBU3xhAE50kNSwifDz5IePW0Lo6ip63h0o+ySa7xjrfKodEtUzXdRwMhQEAc10uLHC7My5v\nsdvhmyKrnNB1vD42DgBY4mkoaJ9qMvNrXTWwkqyrDx593DPFNTOZGWgxa+VEe5NmdOXQhSn7QYf7\nJRz8tTf1v2TXM5YAdzQzgKb6xk9gohJqXhFH25oYGheWvlA55s98uRazGAJRLRiIxjCR7Ofc7rBD\nEARcO6cndfnKJi98eeqaXZKI7mRm+rWxMQDAIk9hwahZOjGTZbRLYab7NQPofEuPF7KgSmQgs8RD\ntAELrgmm/ncwA02zyPr163HHHXek/v/zn/+Mhx9+uKDb7t+/H9dff33R+2QXDqIiTLE6MIDyZqma\nliqIDqVfskc2euDsSGDeulBVflomms7xSAQ/3LcfH53bi7Oam096e0NxYxJgr8sJIVl+4ZXTr4kr\nujoRzOrG8fXly9DucOBnBw+iPxrFm4EJAMYiLIUwa4ClUy2Ajk4fQCciAia7F6yTlWWPBtmjQRCB\n+VdPIBES4fTZkKyGIZp1LrnkkrLvgwE0URH0aRLLehkn6Tctj0O06eh/Nv2zdfSEDDUqQHYzG0Sz\nz10HDmJPMIRv7dyN355/3klvL5wwXmBuKf3R5bWUbPS4XBi2vBRkQcDq5iYIggCfLTMz7SuwhZ05\n10AsrGFHyYmFHWYGXQPUyOT9ms0FYYwVCfO/aZmZ9/bzIvCdEYdZLu5s04A2DcAMDoyozEZHR/HZ\nz34W1157LQ4fPoyPfOQj+OIXv4iuri4cPXoUq1atwre+9S2cOHECX/rSl6DrOtrb22e0r5oOoFVV\nxaOPPoqxsTEkEglccsklaG9vx4YNGyAIAjo6OnDllVdCFJm+o8JYZ8LLHg2J5AILnvkKlKAI7+Ly\nzewTBMC7WEHMH8XoG+mJUkZ7KwbQlEnVddy5/yDObG7CxW2tFd33wVAIt+7cndFCrhTM1nRuKT2Z\nzmF5/26x2xG37NMlSalMdXbHjXwt7OLjIiDqsDemX0+zrYRjul/BNBU4+H8bU+9N+TLQcnJlQuvq\nqdlSJSBOHQXMtSSqupGREdx00024+eabsX///tT5hw4dwr333guXy4V3vOMdGBoawl133YV169bh\nuuuuwxNPPIGHHnqo6P3VdAC9detWuFwufOADH0A4HMZdd92Frq4uXH755Vi4cCE2btyI3bt3Y8WK\nFQCAQCCAYDCYsY1oNIrGxvwrzJWCJEmwFdBKqdTk5M+eslydp8CpOm5NT7Z08mroeKuCY/9j/ADa\ndV4CzlYdU72kSjVmhzfzC58EGbZpPtyr+XhX47Hm81vGjlE/nhkawjNDQ7i8u6si+zfHvXFgMCd4\nLsX9EUv+9dhtqe01WUox7DYbmixdONyyZLleZsDc4XbDZgm+jcDT+HXn9L8Lp4JGQTWCddkhTDqG\nsj7eWaXakmCb8vkdCwmp4BkAHA0SbLbM9wx7gzE4XZnivSNhjNvukpBvaPX4ugbqd9yngueffx7t\n7e3QtMyOMfPmzYMnOeehvb0dsVgMhw4dwnXXXQcAOPvssxlAZ1u5ciVWrlyZ+l8URfT392PBggUA\ngCVLlmD//v2pAHrz5s147rnnMraxdu1aXHbZZRU75krz+XzVPoSqmOm4JxQVQBR2twxfqwvHkh/p\nPYtaIdkqk6ZpfpuO/ufDqf+9Hh+a2gtrb1Vvj3e9jdfk8/nQFEvXAmsNHnS6XRXbf3f/AHBiKOO8\nmf5MaiUMjwAA2hobU9t7e1sb9isK3tLaaozbkqJtcjhT1+sOTACHj6Qu6+nszNh2cFADYBT1eh2t\ncDYZQWfsoAIgjgavE+3tBSzdV2JaQsdupF/vLd422D3Ge02+5/dYxHiPMnX0tsLuznxvircrOIE4\nbLoL7e35a9OPahEAGlo7m9Bc4PtLpdTz65omd/XVV+P9738/Pv/5z+NjH/tY6nwhz08oixYtwpYt\nW7B8+XJs27ZtRvur6QDakcxMxGIx/PrXv8bll1+Op556KnVn2u12RKPpN5o1a9Zg2bJlGduIRqMY\nGsr8ICj1McZisemvWGKyLMPn88Hv9yORqPzSdqfquIODIgAnNFGBfyQCJKfgjI4NT3vbUo556V8L\nOLDeiURYwOjQGOKOqRu6FjPuUJ8Ie7MGm3vKqxWsEo91JD6GP27/Dlb2vg8L2y/k89vvx6B/NHX+\nd195BV9dsRximX+LN8c9mvVLHoCSvI8OBQLGiXg8Y3vX9XTnfbx1TU1dT7C8139p+dKc4xk/IMF8\nPfcf8MPTa7ymRo/bANgQ1yMYGgrkPa7/n70vj5OrLLM+d62tq3pPdzrpJJ19I0ACCSAIURZBFFEB\nZYQBGUX8RJFxdEYZFb9xVIYZdPwcxwVGQB0gg47IIiCyhrAFsm+dTqfT6X2pveru9/vj7rdudVdX\nVy8J9/x++aXrru/dz/u85znP1F9v62EcGhhBWKSK3t/JXus4ACCRHgbhqueUl7VlMnGu6DFx2SAA\nEqlcHOJQYZR6Ju7xmX6ugdl53JXonJ4sWLZsGT784Q/je9/7Hm644Yaiy91yyy34u7/7Ozz55JOY\nP39+Wfs6qQk0ACSTSTz00EM488wzsW7dOjz77LPmPEEQELQN98ViMcRiMcf6vb29ECus47ODpukp\n3f54kCRpRvZ/oh43n9GG7qiAjGALByZGI7pILGlblTxmIggE6mlIOQYiL0MUS/uYFDvuTDeNTBeN\n2GIR3U+GQQUULL0uXZG2Tse1fuPwf6E3vgO98R244bzHzenv5vs7bYtAvzo8gieO9+ADzU1jrDV5\n0DSNJ4734E99/QXzBEHwjARNBH8ZGASg0UOv8+u+3oRqLRe27fu0aLRg/dyQJXPI9AGBJhGqCiQO\na9+I0HweouidcDed11vIS2Al3UXD4/7mMy6/eFkszBNkFAABiDnv8wgAMq8dt0qKEEUPHfUM3uMz\n9VwD797jnu346Ec/av5988034+abbzZ/P/LII55/33vvvZPa50mdPZfJZPDggw/ioosuwvr16wEA\nc+fORWdnJwCgvb0dCxcunMkm+jjBYCTdUCEVFAssvjqDxo3TH2kEAJLWS/xKk48q9jwdQfJAAP0v\na8P8Mn9ivRpS+d6ZbsKsAyc7WdMbo/Ep3+cIz+OnRzo95+XkyVnU7EulkDDIMFWapMBeadC+Tshj\n/fywNS2+h9VKeGcIyHkSVFBBsGEKLXYmAH507GM33lHhFgkLr/TuBJs2djYfaG6YxJGHo8h00+CG\nSUhZEgStmo4dPnz4cOKkjkC//PLLyOfzePHFF01t86WXXoqnnnoKzz33HBoaGhwaaR8+iiHVwaDv\neWsYtdJVBsuBUeJ3PGu9saCqQPKglRAjpmeX1rFU8FJlouUnE/KuRJqkNPWRq21DTilTPctgRND2\nm5YkRCaRBHUwbclCxqlAbcJOoAOU1Sl0S1lUFeCGrHtf5kiokkVWA3XyrHGi6HshDCbAo9iovVGh\ntGqRiGC995miDRs73epuYGsQif2a7KPn6QgaN+pa8CUiyJOaJfjwUT5O6kfj0ksvxaWXXlow/cYb\nb5yB1vg4EaGqmn2cnTwDs4NAVyICndjPYvBV7+QyRQbIWcync/wIOFEryxzPekc9383IuyK+PXkO\nnCwjWGL01o19qRT+o6MT66qr8dnFizyXOZ7LOX7fuXoV/q39MI5kc0hLEibjBdKTtzTM62tKS+aj\nbI/GglAIFzQ2oMUm2zOgSoDCkyAoFVRAhZQjIfME+IRGMAN1pVL26UHPSyyWFLHVFrPaQTNVxdtM\nBlSAUKEIBGQBJnk2IKTIcbfhw8e7HSc1gfbhYzIQswS6fl+F2jVCwTw6NPMfFiMCLWXKJ9CZo8Vf\nAbnjNKoWzkyiTinY8saNUKEgEnCG4kSZmxELudkGt4SDVxTsTqZwZl15mfzPDw2jh+PQw3H4m7aF\nngmJfbZEPQCI0jSietQ5XaJOvxh6OC0q+p3VKx3FU7ywvqYabyeSuKCxwZxGEAS+tHSJ5/KKrB0L\nQasaucxpPshaoRGAmuHnfeFH0uj6X8tOdSz/ZsPCjo4UbzNBaEEAOU8UlOwGrMj7bAgU+PAxW3Fi\nCR19+JhGjO4IQOZIDG8vjFjNhsp/RgR6dFcQQro8Ei1mir8Cep6NlLXN6UCa64eqD+RneaebghGV\nfrfDHYEGNBlFOXig6xj+bLOlExRvctab00julS1z8elFCxBjGJNAZybpmhDXpSD17PgluL+6fBl+\nsHYNzm9oGHdZwKogSlIAxeojOwJhlfGeoSqEBoINCupO48ZdTlUBMVta9Nggxz3PFD7nFoGe+UCB\nDx+zFT6B9uGjCGSuOCllq2f+wyJlrce38+EYht8en1icLOiN7yiYVhteBADgRV8PDVgEuoZhUKNH\nbN1R6VKQlST8vrfPMY2TC+//3ckkunM5kAA+Nq8FH5o7FwBQZUSgJ0GgVVVFXNBGgkopwR2gKCyP\nVpXs+qFKtgi0TqBlgYCiDz4Z02YS7k677OGMIecJqCIBglHHLT1Oj5EcaJwPryqGPnz40OATaB8+\nPCBxBNKdxb9As2Fo0z2sPPJ2EMoE88RUuZBgLPyIRUDVme8nFGAkcxjbDv+kYDrLaJWmRDlXMO/d\niIykkeUvLV2MzbqUwZ1YWAqyUiHp5pTCaTuTmp/wexsbHMmCUVojvJMh0DlZhqCqCJKkp4PGZGFE\noAnKIo0KT0AWZg+RNEacDAjZwjalOrRzHW6Wxk16LCW6PBvecz58TBS/+MUvcO655065X7evgfbh\nwwNjaYOJccpmTxfqT+OR66HBDVttFTMkArWlkySDINgRbLDW7/1LGPMunF2E9I/v3OY5naW0RE9R\nzk9nc6YFiqril51deGpgACujVfjO6lWOMtReMCzfahjWJJ1eso7x0M8XSgfcEehRQcCjPZqV4FqX\nl36U0fadliT8ovMo2jMZfHfN6nHb79y+diy17NRoKUwNNKVroKFpoA0Jx2yIQLOu51rIqPZ6KZBy\nhCk3q15emLfhhoMcEyqgFr4LfALtY6JQM2mIDz8A5fAhoJLFbmga5NLlYK65HkRVdMxFH3vsMVx2\n2WV44oknHP7QlYYfgfbhwwNEkSdj/iVZtH18dkgESAZoOs9JFqVc6VpoVQFU0bk86eocZI7OrmQ8\nRS1OABmTQM8uwl8J7Eml8NTAAADgQDqDfanx70GLQDMI6hZuE5Vw5GUZ39p3oGC6OwJt935ucJFc\nQz4yKgh4sn8A7ZksjuUm1slJiLp8Y4qSQx0aaINAcwRkfvYQ6FCjjLkX5MyRJ9EVgU4cZKFKBCKt\nIqoWjU9cmKhFyIONhfcFE5N9D2gfE4b48ANQDuyrLHkGAEmCcmAfxIcfGHOx119/HQsWLMAnPvEJ\n/OY3v6lsG1zwCbQPHx5QPCKzABBplcBEZs9Hxa1jNHxdS4H9GAP1MuZuzpmdg1IiWDOBHD/i+L1m\n3pUAAAIkGEqz4xOlk49AD7qGIrOyhGGex45EwnN5SVGQliSQAKIMjRBpRKAnJuHYkfBOyHRHoO2E\nuCHgJNB1OqG2+ziLE9QGGXKU6CR8pMeCqYGmVDC6e4WUI21JhLPjmY8tFRFdpHWMssPWOZR5YMSI\nPq8USvKsrllpPeOqRGDOWXlE5lsasNhScdZ4X/s4caB0Ta2l6Hjb37JlC6666iosXrwYLMti586d\nU9YWn0D78OEBL2lDy/uzM9CSseEeYp1IBFrWv5V0lYJFV2YQWyKC1jsH9si2Mou4dIYfdPw+beG1\nWNXyYXzwtH8FQ2sRaMEWgVZVFdJsOoAy4dYhJ0QRN7+9A3fuP+gZjT6m+zFXMwwogihbwnEwbW2b\nJghsqKkBoEWyVVVFP8dBUVUwNqbV4HLJMAh03FaC2K2H7uc4fHb7O/j3wx1Q1UKyajh4TKYQy1iw\na6CNZ0DKkOZ7oJwI9Paj9+OJHV+BPNHEhHFgRIvTvRaBtjsFheaUdo1JWzBfTJOoXSug6VzruQ/U\nzo7Kiz5OLJAL22Zs+8lkEi+99BIeeOAB3HTTTchkMvj1r389dW2Zsi378HECwx2BrlooIto2+zyR\n3VKTbA/tmfgnC8DeRzmkOq0ErLGiawShDeECgJibPa+JLOck0AwVwqYln0VDdJmnhOPF/Xfj11s/\nWmB1d6LBIJDGXTnCC2Y1vo5spmD5e3VJhVE0xfh/ohKOrG35pkDALIfNKQruPdqFW97ZiWcGBjGg\nR8j/bcPpjop/AFDHFOqW3ZZ2B9IZDAkCnh8axsGMdjyKjUi/rUfaq+ipqexjEmja8k/mkySgEJoz\nRxm8fXf3FgylD6AvUdkImFFSPDNgPeh2qdVY7hpuVK/QOpexZdr/dqcPJjYLM4h9zHow11wPcuVq\noNKdXZoGuXI1mGuuL7rIY489ho997GO47777cO+99+KRRx7B1q1bMTo6Wtm2GE2akq368HGCw02g\nZ4MGshhaL88gsZ9FuoNFrofB8PYAGs90DvlnjlEY3CsDewNovVxEuFmGMo6+kw6pEFNA/4shLLxi\ndkTf7RHoZc0XO+YZSYS7u7egIboYjY3XoL3/zwCAjsEXsK71qulraIVhEM75oRC683n8zmYrR3mM\nsxuR5vMb6gEAIZ3U5j3cM8aCXarBkKSppc5KEp7o1zTZP+s8CgBoZFmsrq5GPu/UNwcoElGadkSd\n3QTaPu94Po9tI6N4sn8A1y9sxcJwGK+NxgFYlniVhpFESFKqSaBlveM42UQ6tcJWNkb7hIzVLmMX\niz46sfyMOWdrso3IfL2DRgKhuRKkLDGhZGQfPgwQVVGwN/2fGdn3li1bcNddd5m/Q6EQLr74Yjzy\nyCP43Oc+V/H9+QTahw8PuCUcbgup2YRws4zQnDzSHVqkL9dLQ0iKDq9q2aZiiO8OINycg2QQhCIR\nq0CDjPwADUWcPULIjB6BXjv/o1i/6K8d8wwJBwA8v+8HOGPVh21zZ+/1KwWGhMMg0HZsjyfQkcni\nc4vbYMQhU3rVv3NNAq1FbnMelnRjwZ4s+IUli/Hi8DAAoJ8rtIeix3DVWBAOYa9NapIWne2wVyns\nzXN4rK8fAPB0/yDWVVtluyNTHYGmtKIpJKOa9305xUTsya4qKktESVbTassCAUXUkx05EgStFjh1\njLstGgUja62XZQG1eCK1Dx+zFY899ljBtG9/+9tTtj//EfHhwwNu2Sw5u8woCkCQwLyLtCgxN0Sj\nc0sU3Ij1eBtuAoBVIEZIa/PZqDepqlunkSQvPfhMwYhAN1efApJwkikjidDAQOKQ9ePE5s/IyhrJ\nObu+sAz324kk/jI0jOdslQLTut7YSLqr13XIQwLvqTEuBkPycefqlVhSFUFQT0Y0ymrbsSgcLphW\nbJ47Am3/vVv3kwY0KZFx7ABATxGrsycRAs4y2HQZEWhRytv+rmxSK0FYUgspT0DSy3ozEaUiSX8E\n4ZNnHz5Kgf+Y+PDhgqpqSTV2zGYJhwH3UHNir5XMZZekGIRYTOklf4toHc2SxvzsIdCGljkSmFMw\nzz3tgeduNP+udBSwFKiqClVVsSeZwg1vbcdb8XjZ2zJcKBoDAdyxcoXnMoZtnaQoyMoySFhJd1Ga\nRpiikJcVpCZgL2VIOAzibGiQj+cLCfSnFy0oup33z2lEjKaxNKKVjbaT4jdG46ZFHwAczlpyoYwk\nO6LdYhmFYEqBYotAA5N/3gU5Y/u78vInQ+cs5QjIOoH2Led8+Jhe+BIOHz5c4EdIiGkKVEhBzSoB\nqcOMw/JptsL90ZcdpNmabpBpPq4T6CrvDy9BAyBUqDIBVbbIxUzCKNMdYmoK5kVDzWOsOf3k4lv7\nDkBWVRxIp6EAuKe9A7/ZeEZZ2zI0zSGKwspoFMurqnAo40weNJLuknrJ6whNm/pogiDQHAzgSDaH\nfo5DdYl+yoZm2tBQGxrkId66oWI0jS8sWYyGQPFS8m2RCO4/cwPeGI3jewcPISvJ6Mnn8c29+zEq\nFnepSIii2TFgCALvbWgoqd0ThVGR05BqiRmrAy2VkUQrSFnPvysFIwIt5gjIftltHz5mBH4E2ocP\nF/hRjSmGWyQ0rOex+OrMCVGRy10ERbEFGu0RaClPoPvJCPhhGiSjIjTHOyJJEFYUejbIOFRVNaN5\ndr2zgQBdVXRdWZleB5WcJGF3KoV9OnkGgMAEKu+5IeiRV1bfhpdcQnIRaLdncpNOcAf50juDZgRa\n11C7Ncgfm9eC+8/cgDPrCqUlXgjb7PTuO9pVQJ7njEHCf7nhdESZqbexA4BYm9Wuxo2FlRjHw1QT\naCaqE+gUASlv5DL4SX8+fEwnfALtw4cNqgIMbNW0tOwJZuPkjkDbqwzaI9BQCOR6NSISnieBHKM6\nsrHNYoVlpguKKqO9/2moqgyKZEEVEaVXBZo8p0uyRYIkRcDz+/4Zhweem5K2AlrVPTfqJ1GG2pAu\nsLo49ZOt8wuWMZwsMjopdVu+1eh2cskxIr5uGBpoS8LhJLATLWxiEPCcLGPYg8gbriFuEJg6D2jA\nyhEworgNZ3JoPj+HZTckTYeKiUCQplbCEajR2snFSVOKNdEIdI4fQZYfrnjbfPh4t8An0D5mDJlj\nNI7+vgrHnw5PqADIVCLTRZvDufZStycC3JxSEQt1z27Q4bGP0SDXM02g9/c8hlcP/z8AVsluL3zo\n9B9hefMlBdNF2dLsHhl8Hl0jr+KVQ/dUvqE6Rj3IYQ1bfiaqoEeXGZIwt/UPK5Y7ljGIsSA7o9UG\nqvXobakEWlVVcIoRgdYlHJSTxE7UVs5wA0mKIo65dNR3rFzhcNxw78fLrq9SMCp4Go4bJA1ULxPL\n8n8GnPdbe/8zyAveFSPLRaBGa2fiAI34Hi1qTwVVdI+8gUff/Ax2dW8Zc31VVbHljRux5Y0bKl7o\nxYePdwtKItAcx+HgwYPaC5Wb+HCWDx9eSB5iwY9QyHYzSB+ZHTYXdrcKe1GBEwFufuGQcBRJBBzv\nGI2oljzDEvC+5C7zb5aOFF0uwFQhxNYVTLcTmrxQfjJfqRgVCm3eJKX8+0lSCklxzCVnSOpWcIKu\nW2YIN4HWnrGObGFEtCOTxY8PHzH1xoAmCZFVFTRBgNH365ZwRKiJCeMNCUfcReJvWdyGDbU1WBWL\nmtMuDc7D+kQLoE5dCW8DUoUT8WSXjc8L+79Xke0aCNQVdnxT1AHs7fk90lwf3j56v8NKzw1J4czE\n2nh2aksv+/AxHXj99ddx9tln47rrrsOnPvUpXH311di3b9+U7nPct9KOHTvwhS98ATRN46GHHsIV\nV1yBn/70p1i/fv2UNszHyQtVBY6/RCFz1Pr4CsmZGQyReS26amgKDTsrQNNAn8gwItCqAvAJPaoe\nU8whX6BQN+2GMX+mI9AhxtLYEuP0+5tiawqm2asTOv/OF9jfVQJxDwkHN8EiJnYYGmjGRqCbg0HH\nMu4INFMQgdYI9DuJJA6k01gZtcjqV3bvMffzt8uXArC8pMM2kuyOOE80Ah0uQriDelspgsBXly/D\n3lQK5z2nXccMJUCqqqwVnBuGtWM5lnVecJePH0jtrch2DTBhgI0SENJWe18Yvg0gLGLdPfI6Fjac\n47m+XZc9mDqAhuhyz+V8+JgostwoHn/jWzg68GZBR3IyoEgWi5rOxOUb70QkWBgkAYCzzjoL99yj\njSy+8sor+NGPfoSf/exnFWuDG+O+/e666y786le/wle+8hU0Nzfjrrvuwne/+108+uijU9ao2QSW\nZUFNMMoyEZAkiVCo8h/w8UAQBHK5HBiGAT3F0R03cgMEhnc6z2n2GAthCYnYQnVKPUjdx733vxmI\nWQJrbhLAhIGkqu286QwZ4Uhlr8t0XOvl14jgEwS6nqahSgRCoRBygwRUmUCwFmg5V8GRP1onmGEY\nhELF7282rBMbNYBQqLxRgkoct6RaEeQ01z/m9hYHz8JHQvdgf+8TONijVSJUVMFcJydYfsnP7bsT\nl2/4ARgq6LmtchEXCofFRRVlnQdZUaAAIAmgypY8GHQR6LQkgWEYZHQf5SBDO/ZXZ1v3ueERnD6n\n0ApwWLTOU0Y/hjmhoDktqKqI0JRZ2KUuEnbso9xr3VodM9d73/x5eB/mYYcuUZ/HRRFnpTG3W+77\nTBa0kRuZ0yPstQHQZdwK7uMmycIIcSWffYIgEJ6jQtBr0+xceIODPAPA8/v/Gbdc7K3zz9tKXYQw\nCwAAIABJREFUtPNyvKy2zcS3aya/WwbercddKh5/41vo6Nta8e3KioCOvq14/I1v4Zr3/njc5VOp\nFOrqvIl2pTDuleA4DkuXLjV/n3/++SbDfzdA8IgkVRKhUKig9O10gGEY1NTUIJvNQpxAUlElkM9Q\nAJxkTMwS6HycwdzNOcSWlN8eIUVCleFZhlZVATnFYv6yamSzWeRGJYhZTeSb6hMQbpHB54IAaCik\ngHy+std+Oq41EQUCVQBQDUUkkMvlkR5gADCIzqUQnp9D3ToZo7sCAKEi2JpDPl886qZSQQAUuIxY\n9vmoxHFnOSvZSVHFcbfXGF0Nuk01CTQvZpHP5zGcbseRwZfN5foTe/DmoQdx+qJPIZnrQffo61jR\n/AFPl4+JYIQvlHDkJGncdquqiqO5HOaHQmYE2SA7LEGOuX5OlpHhOED/wJKK6li+ySa/SPGC57YU\n2zo9aY2I19GMczuBAI7oxUFoWXbMm+i1Pre+DiuiUbSxrMd62rNJqSTqXW1wY6z3mcQRyPXQiLaJ\njs65IgCd/xMFwajaCAuhQlDyEMu4Vd3HzfFOmUxtZFFFn32GYVAzP4xEh3asHHvcc7li+0xnR82/\ns1y8rLbNxLdrJr9bBmbjcdfWluaCMx3oGd41/kJTtP3XXnsN1113HQRBwIEDB/CTn/xkStsybqyP\npmkkk0kQusDyyJEjU9ogHyc3VMUaLjUQabVeCH0vhJDpKr+H3flIFEcfjRbsAwBShxl0bAnh4JOC\n/ttyRTDkDoZW+EQonFIMBAEQtCFJsc43G9H+b9zIYflNSSy/IWUWZCiGmXThUFUVgpQDJ6YcuuXW\n+rNKWn9Zy/k4e9ktACwN9OM7bi9YLpE7BgB4++j9eKvzPjy791uTbbqZRHj7sqW4smUuAKCP49Cd\nG/vD+9LwCG7ftQf3tB9GXpbxZH8/evSPtVuSAQDfXLUCH57bjBpdnpEURZvcw3nNahgG/6gXYenK\neUsi7GsYLhkNAad7iN1qrqqM0blTq2Pm3+fU1+PyuYX+3aqt/0srJNZURwuWKRU9T4fR93wYo7ud\nx5HuZCDlSIhJ7RjokFqRSn6AJeFYMmczAEBVK5+QHKq1GquQzg6bIXNyJwgOJPdiMHXA4RLCS04/\ncR8+JoN5DetmbPtnnXUWHnzwQTz88MP4/e9/j9tvv31K8/bGJdC33HILPvWpT6G/vx+33347PvnJ\nT+KWW26Zsgb5OHkxsjOA9vtjyPVZBDlQL6PlfTnUnqJ/AFQCPc8WTxIbC/Zv1OFfx5DtdX7c47u1\nD3//Dk3bmeqwouASRyC+j0XykPaRne2lu8eDqV0WCUg6gWbC1geXIEorjGL4QMf3s5gCDjAm/rz3\n2/jttqvxyOt/jTTXDwA4b8Xf4tzlt5W0PkEQWDznPAAage6N74BXQZWsoEW3j8ffAgAMpvZPqNy1\nF4wkwvmhID42r8Wc/sWdu9CeKU5Y/qyX4942Gsc39+7HLzq7cH+XRvBZspDdnV5TgxsXLUSd7vCx\nI56AoEesvQj3Wp28DvC8J4m2E8hBPYre4LLfs2uvg2UQ6H9ctdL8O1RkfXuH7bRgLc6fRAEVbkh7\n32SPOR/q/JBz35X0epcV7dwFaO18S3LhiMRkUbeEBggVifCbjum1kTYwtCYxsCfPyoqIp3Z9DU/u\n/IrTp1ovTuTDRyVw+cY7sWTue0CN5Y9aBiiSxZK578HlG+8safmGKSq6ZMe4ob7Nmzdj8eLF2Lp1\nKxRFwec//3mHpMOHj1Ix/Kb24U3s14hsqElC83vzIBmgbi1vElxAc5CYqIWU7HKaGN0VQKTFIgl2\nVwpV0eQe5rocgeE3LV3biV7Vi2RUyHmNiJgR6PDEw2tmBJonkepgUL1s+oZNe+LbtX2r2j5pMoDF\njReYo2GlwLC848QEntlzhzl9Yf056Bp5FQAwnG5HTog7ooRZfghVwUKNcKkwkghrGbaggMpXd+/F\nQxvPQMCDPNqPzChpvSelERy3q4YdDaxWZfDf2w/jwvnzii5vd/G4bedu/P7sTY75aUlCTpIQpmkc\nSGtEf3HE2aG9aM4cJEURF82ZA7KMkK3djs5ttWdAzFjLtCACkqhAEqGrqbKrwmAlC5EYkd8Ao0XO\nJaXyUTA2QqDmI6/htT13oKl6LZY3X4KOgb/g7GVfwJ92/T0EKQtRziPIaCSeE5Pmuolct/k3L/kE\n2kflEAnWlaRRngoYEg6SJJHNZvH3f//3BbkilcS4FCWRSKC6uhqXXXaZY1pNTWEpXR8+JoKqNhFs\ntfbRolx2alKWNOeVCrdVm5R1fiDtvshihgAUouiyJ7KEA9A6ACK0ToWRIMVEyiDQto4EN0RNG4FW\nPCoHhtjaCZFnAKCpIDTm5Lyem1d/HcPpQ3i1/ScYzXbgxQM/gKJa+0zkuooS6NHMETB0GNGgd+lw\nWVWREiUQAKKMt3/xIC+gNexMRBoVBPRyxSUetEcE2kBrOIQ34prM5dX+AQCFEo5S0JPn8Fdvbse3\nVq1EZzYLEsDyqLPCY0soiC8uXTLhbdvxucWL0J7OYmXUu3rk8act0l5OKW0vKCKBdCeNqoUSCNKy\nrjMwJRFoZuoi0AAgUhmopACWrsKSOZtNyYjhLGN3nOHElPn3ru6Hzb8FX8Lh4yTApk2bsG3btmnd\n57gE+qyzzir4aDU2NuKll16askb5eHfAHuV1cwwxS4D1rqlQFEaxELZahpCkIMQpjLwTQM0qLRoo\n2z6YXU86SwbnB53RwEBt+ZZjswEGGZA5KwLNhAhM1JjPflnKLSpRDgS5MOLo5e88HgiCAEMFHUPZ\nBhqiy3Hm4pvw9O6vYyC5xzGvWOELXkzjsXe+CAC44bzHPZfJ6hUBIxRVtPjHsMCbBFpRVRzL5fHl\nXbvHPJbefPEoZrNNl5zT918sunvF3Ln4Q18fAC1B0UtGcef+AwCAepYpKrOYDC5pasIl3kUjtWTf\nvNV2IU4he5wuqyKgXXbEj1DofS4COqIg0iqa0g4D4+UDTASGBjpoSDgUHqqqTrgDOO5+JEMf74yy\nmQRasiU2ikXuaZ9A+/BRFsbt2h84cAD79+/H/v37sWvXLtx999244oorpqNtPmYQUp4AH6+cn5xH\nQLHggzXnbOtlL2W0ffNxEkK6tI+OIeGgo4pZUWx4exDD2wPIHqdhp4PGsZEBbTl+2PqYzrsoe8Jr\noD0JdBkRaHs1RnfEbiohSh4Emilv1Iu2+TwTBIVLTvmu+XtuzTqct+JvEWSq0Vq3CcubP6Dt34PA\nA0CGtyzwilVwMyze7KWnW122V0O2SoX3He0alzwDgHs8JssPozf+DgDggsYGMC5yRhcha3+1wCoD\nnhjHySBMTb9lluxxnx3/U3l5EV73rJQlkTwQKJheWQmHdn1pKqBrQVUzKl1JGB1Dt5e5IV0S5TwU\nRdKKoNkkHACwZM77QZEByIrg2cH04cPH2JgQQ2IYBh/84AexdWvlPf58zC4ceVhzsxCzlSFNg9sK\nfTMNkmugZrWA2jXaR0bKklAk4OijUXQ+HEMp1WYNCQcVUB3SAyFFFi3UEmp0Rppr1/CoWnhiF1AB\nLAIt2Ql0Gc5sgTrFTPBMtbMlXYdKQJALq+WVE4EGnOTivOW3Y27NqY75S+ZsxjWbHsT7Vt+BIKMN\newgeBB5wRvFywojnMlnZKEBi3XN3rFqBs+tqcbbuSzpks7l7QpdcTBSP77gdz+z5R/QldoImSXx9\npbMYRrEINEOSWFGlSSe8/KrtcFcenA7wCa3dwTmTfw4n4h5TtaByz72kk2WKDIAmNbI+FTIOg/jS\nBQRa+9059BJ+s+0a/Gn3PxQQ6FPmfwxhVrM/ywuj8OHDx8QwLoFOJBLmv3g8jpdffhmpVGq81Xyc\n4DAq8gmjlfmAJg8WZuS6E/UIQquUB2gSjlyPFf1KdxYPCfe/HELv8yGTKFIu/bKYJiGmtVs91OQk\nzEEXgTb2f6LDikCTZmSeCZXXGapZZX34x7oOlYQRgTYILQDEQnPL2padQEcC9Z7LEAQJgiDA0kbk\nrpBAizKHt48+aP4+OvQKntz5VaTyfVBUGc/s+Sb+vPdOpEUt+pjO7MPRoVcAaNZvX12xHGv1UtUZ\nXWZhlOguhi2bzjTJrhsG6eka1nR/LUEXiSpCoAGgRnftiIuF3t6GJR4ARKYpAm03PTFGn+yjH+VC\nkca+5xs2cJhzdh5N5+U8vePLhRGBpkhW1+FbpLqSKBaBNgj1kcHnISs8BpJ7kOGcHbWq4ByzU5rj\nfQLtw8dEUbIG2rB1qq+vxze+8Y0pb5iPmUO227otKmFdViyKTXloDumItsP8AO0YZuWGKVQvL4yW\nqbJFzrlhjQxTAdWRMyamSZNQVi+VkR+wOgWs66Pp1aYTEZQuTTGcTUhWBUmVR6DZmIpIq4hsN1P0\nOlQahga6OtwKLqlFzqLB8gg0S1sENBwY29rIGPr2ioDv6PotRjLt5u/tR38FANja/iOc2voJ9Mbf\nBgDEA28DiIIBhxcOfB83NFpaaVaPSvM6cU5JY0c9aZLE6lgUB8ewvsvygwA0v+YgSYIr4gNth+Hl\nfPehw2g7zSmPWBAOIZHUrvF0RKCFBImux6pQfxqHunWCmdDLRFQ0vzeH/pfCBaNVpUId51atO42v\nmPezgUT2mGkTR5MsaF2fXEwWNBlYBNqpgTY6gqpN+NOX2Gn+3RhdAZoKmrKoP+3+B1x/7h9AluJt\n6cOHDwAlEOgDBw5MRzt8zCI4MuAroHs1or8AEJorIa/7QHslpTFV2gtfiDtf5O7fgBa1slvRGQUR\nSLcFnUqAG9R2Fl0go9+mQDL8kg1E5s1MdatKwx1Jn2yCVO0aAdluBnyFRiTGg6gTkAhrEd5wkejx\neKgKWG4aYXbsbZjaUalQE5rKe1d7E8QM+hI7zN/D+SEYBNqNIKmdP05WEBcE3Hu0C4CmkV5XHfOU\nc1wzX9Msn9vg3fYMpxFokiCwIBLGId1+bizbuxabtdMde/cVzNullwMPT0ECIaCV0B55O4jYUgHx\nfQEoAoGhN0Iagc7puQxhBVWLROAlQJHLew/ZnXcMLPpYGlKOAB2pXOEUA13Dr+L5/f9s/qbIACKB\nBiTz3chwg6iNLKro/oz71C3hsI/cGDAKBm1YdANWz9PymNK2qHQ824X6qsUVbZ8PHyczihLo//qv\n/xpzxRtvvLHijfEx83DXjzAs0CYDIymoaqGI6pUCevqK99uYKhUEpUJ1fTDdCY2Zbho9T3snFo3l\n4cxEVSw4h8GxV3Wf1hoZzefnkB+g0HQOhzE4xwmFYL1TmjJZBw1WdyUREuOfIFkRQRIUiEmcTCMC\nzNIRnL7wU0jme1AXaStrWzRljWRQ42SHGpG7nDCCodRBNMZWmPOyvKZ5ZqiQI+mKdrl8JPQyzl4E\nOqBHoLeNjmLbqDVsHmNoXD1/HuKiiFdHRgvWuX7hAsc0ewJjmuuHqiogCBKrYjGLQI8RgW60uXbE\nXYmE820Jj/ZEyEpidGcA8T3av+qVTmmDYVtHRxTzvlVF7d00UcJrSDiooGK+y9hqBYEpqny8q3uL\n+XeQqUE02IRYqAW9iXeQ4norvj+jQqfh9WygWMItARKr5n3YfA5WtXwQW9v/HQDQn9ztE2gfJzTa\n29vxL//yL8jn88jlcjj//PNx6623Vtz9xkDRt+OhQ4emZIc+ZjfcJbArEYGWdEsqKqQgMk9CZL6I\nWGsRWUdQReNGriDpUOZISBwBRQBGdwSROV78w04FtG30/rmQYJMUsORCFsElKXBJGUxURXVUnNYC\nIdMBjTOqMJxH3JH2iYIOax0bmSMhCwBVpMiUrIj4/VufQzQ0F5ec8k9l789I4mPoME5d8ImytwNY\nUeXSltXumcHUPjyx82+xrvUarF90HQAgp1csvHLDf+KRN/7aXIeXMg5965Ae9QyqhbKLYBFdcoym\nEWMY/N3yZfja7r04NIZkA3C6lEgKhzTXj1ioBetra/GHHo2ojWU/t6wqAhKFzh4AMM9OoKcoAm33\nXbf3aVQVtgi0CoLUytKrEgFVAogJSvCNfgYVVCHr/Zmp7CTbvcTbGt8LkqQRDWmVKNP5vorvz+jU\nuUdngqx3D6E20gbaViFuSdP70Z/cjY7B55HKeY+w+PAxEYxyPL7z1nZsHxqCME6Ox0TAkiQ2NDbi\nm2dsQF2w0EUnlUrh9ttvx49//GMsWrQIsizjS1/6Eh566CF88pOfrFg77CjKQr73ve9NyQ59zG5w\nw84Pppel1ESRPabdZnRI+yDO/0AOoVAI+SLOSTWrBUhZAqO7nLo+IU4isZ9F+sjYJULJgIpws4yl\nn0pBVYCO38YKlmGrVBCBE9vreTy0fTyD7HEamWMMGtZN7lgJQkvqEhIUxBQJqsH7xZjK9yDDDyDD\nD0BR5bI1laIegZ4I+S2GVS2X48jgC1jefMm4yxoRaAO7uh/GvNrTUR9dDk5MggCJIOuM7uWEEUg6\nO1MB9KoLAQJoVDu1aTb/3wDpfT7qbOWyi9nP2SHIGQSEuQjzSxGPvowcP4JYqAWn19bg82tXYyiZ\nwppY4X1vIMYw+MWG03HT9ncK5s0PWc/dWNuYDOwyK3vOhcwRpge0kY9AMipkiYAiEhPuCBoSjlCz\nBJkjEKifumdeUgRkbTaHTdVrAFgSooyuVa8kcrzWqXNLk7wkHFqbVjt+kwSFBfXnoGPwebOkvQ8f\nk8F33tqObQPlOQuNBUFRsG1gAN95azt+eO45BfOfe+45bNq0CYsWLQIAUBSFH/zgB2CYqUt8H3d8\n7p133sHPf/5z5HI5qKoKRVFw/PhxvPDCC1PWKB8zB7cswl7QoBwICRLZ49oNXGp5bIIAGjfyBQSa\nH6WQOTb+w2Dsx0gcZGtlTw31yQ62RgFbI6B2rVCRlwgb0wg0P0ohWIRA26uacUKibN2yEYFmqfL8\nf+0IsbX4+MZ7S1rWi3j0xncgrGuxw4H6gk6BJOdNCYeIIHgiCkoVEIP2EZEU3kzyClLez9Pmxkbz\n71IqCApSDus7HwEA7G29FbKeLUcSBP56xQoMDQ1BHMfj2U7a7WgIBHDDwgWI0FRBFcJKgaRtNpMJ\nyvY3CYm3ZBeArSy9aFWUTHUwSB5g0fL+3JgVBC0Jh4oln0xP0Li1dCiqjFcP/bt5/y+sPwetdRsB\nAEG9nHelK/7Jsoi8mAABEiFXxDnEeks4aj1kUBE9sTbHe9sy+vAxEewZnVpHl2LbHxwcRGtrq2Na\nJDL578dYGPd1cscdd+D0009HJpPBhz70IVRVVeHiiy+e0kb5mHkw1VqkRuImF4HO2fTOk3W4yA9S\npr2egeb35lC1SESgzoosuYl6oEafR5wcDhszhUirNjydOlycjNsr+JUb0Ypnj6JHd7RwR4SnGkGm\nGiThjCvIqmTKN4olIRoeuxw0shRE2izbYyREAlYSoYFz6+vx3TWrsKTKetHfuGghojSNWxYX13wL\n9m0KC0zbtErhipa5uHCOdynzSsAruQ8Acv00VJEASNWUdhj/p49Y913f82Hk+mgMv104lGuH4cJB\nMgBBAbIqQFErH4XuHHgFR4ZeAACc0XYjNq/+uqkzDujVCDkxXbCeJPN45dAPcWzkdfBiaQRbVkQc\nHXoVRwY0+8IQW1vQqQsx3hIOe0KtAcOZJsv7EWgfk8fauvL8+ie7/ZaWFvT39zumdXd3480335yy\ntoxLoAmCwGc/+1ls3LgRixcvxo9+9CO89dZbU9YgHzMHewJhy2YtAjhZCQc3pDtjMCqibZPTGac7\nCiNmgXoZ8y7MmUluQKELx5yzOUQXC1jwoUJrMh+lI7pYAEGpyPXSRa0J82Lc/Pvtow+YPsgAMJw+\njGf2fBOJ7LEx9/OHt79gWrMx9NRGENwgCLKgYMue4/+DFw/cDcDSmlaH5juWMZK5mKBGeoOwyJCd\n7AZsEeibFi3EbcuWYLVLJrEwHMb9Z6zHxU3FCaw9mqmQ+YoQ6I/Pa8F316wef8EKoBiBNuQcVLDQ\nISPdVThgao9ee+5H73CnhC788Z0v4ddbP4qnd329jBaPjb6EVUmypXa9Yx5rRqALCfS+3sdweODP\n+Mu+/4tH3rgeI5nDY+6HF9N4cOuVeHb3ndjy8m0AgKpgYU10e+KsvUMYDTYXLBtiqkEQFHgphSd2\nfAVqJbxLfbxr8c0zNuDspqaihZzKBUuSOLupCd88Y4Pn/M2bN+Pll1/GsWPa90UURXz/+9+f0ny+\ncSUcRgh8wYIFaG9vx4YNGyDLJ7d29N0KIzBDUCoCdQoAFTJHQFUmnnijqkBiH4vkIY30tn4wMyXJ\nO8bwrd0qzy0zpcMqWt5nCK5PEpuNGQAVAKoWiEh3skgdZlF/amFhCHsEui+xE32JnVi14CIAwNO7\n/wGinMer8v/DZafe5bkP98ebrYAGeqII0FGTwBswItCGrd6Fa76N9oFncbDvKfBSyiTQdHAJkAEC\negIhI9WCywiA3g+wJxEurYqAKqJ3Hi9rnOcthw8VStGy4uPhe2tX48m+AXy6baGjgEolYXTM7YdU\nrEKgYTdpH0Vq3JjH8aeqAKVwnfEqpRr72TfwKEaqOwAAA6m9Jbd9oqgJLyhwiwnoPuS8mHbo4QEt\nZ8CArAjYcewhvH/1HUW3b4zM2OFFiu1g6Yg5QuIlqSIIEgE6Ck5MYCh9AJyYLJCE+PBRKuqCAU+N\n8lSjqqoK3//+93HHHXdAVVVks1ls3rwZ11577ZTtc1wCfcopp+C2227Dl770Jdx88804evQoqCnK\nzPYxszA+NiSrJftpmeskZI4AHZ6Y/CF7nDadNJiojED9xKMaVW0iMp0MwvNF5I57f9yNDy1brYAb\nrEz1Mh/FEVumEej0EcaTQHuVtzaio4ZOmBOTELPaPeXmie4S2uw0R6ABIMAU1/0aBCQaasb6Rdeh\nJ/4W+EzKLFhRFV0PZFI4reVcLBzkMPfgV5E6LqHprzSLRHt1wMlU+RNzCownglKCE45Aq6qK7Uf/\nC7WRNty+fHPZ7VBVQEyRYGKKp8Xc6C4WQ2+EwMRktH3c6kSPx/dpm66ZqVL1dQp3YFjeFYNRhVOi\nkmMuN1nkeK0Dta716oJ5FMmApkKQ5DwEOWsSakCzILRjMLm3gGTbkeYKnTzGKzDEUGEsajgXLF01\nro0joLnK+ATax4mItWvX4oEHHpi2/RV9+3z+85/Htm3b8I1vfAM33HAD2tra8PWvfx2KouDuu++e\ntgb6qCwSuW50j76Jlw/8EEPJI455JoFmnEl4bmu7UmD3C2ai3h/X8TD3/BzmX5pB09lOP122xhoB\nMaR/jWdyqFvHo/Wyyibq+HAi1KzpoIUEWeAZDlhFPezghJRDd9oUvwJH/juGdEfhx1yQndevEi4c\nE8WmJZ9DdWg+Fs8pJJYN0eWO3+4CFllFuyGbI7WIxc8GAQoqHzCfIdL2IISKJBSWAnudF1KdOIEe\nzXZiz/Hf4eWD/2pWmS0H/S+F0LklisR+74TEoTe08yOmKEe02IsME5TVDipsdYRJVifQHoeojl3I\n0TzvootAT+aYvWD5MXsn7wVoXcbh0jm7nxdeSheQajuMYih2REPeEWgjYbC5ei3OWnqLacfoBfvI\njxGt9uHDx9goGgI544wz8J3vfAcAcO2112Lp0qW44IILcMEFF0xX23xMAf53+y3m372Jd3DNWfeb\nv2XRikADVnTXiOJMCLbvU6nuG26QNBCZJzuiVYF62crgJ60IJh3WvJ99TC0oVisTLvMkZL2amx0Z\nvtC+iBNTIPSLOG/kOjQMa56cw28HEFvqDEXa9cKAswz3dKEm3Iorz/hPAMCRwefN6Y3RFWiKrXEs\ny7gIdFLSzkcdy4IRLS21lLNGca5tnY+EKKIhMHYC3Fiw5yaQSgiSjV3mhRQeevUGtDW+tyhpkmyF\nX/LCaFluKYoEpNo14swPjz8qqXXQi0eTmZhiuuWwtkqaRofesQ6hAioBqAQSBxk0rvXep0Gg3RFo\nRZVATdRUegzkdAJdzP0iEmhAlh9EMt9jEl5Flc0Rm6s2/gqvd/wnjo28ht74O4iFvKPKBlG3o1h1\nwwvXfAsdg3/BirmXjdt+FVYHlxdT4y7vw4ePMSLQn/70p/HUU0/hzjvvxM6dO3HRRRfh29/+Ntrb\n26ezfRXB8ePHzcqKIyMjuPfee3Hffffh8ccfh1JBo+/ZDkl2Drmncs5Ih/ENNopklEOg0100ep8L\nOdYhx7ZtHheOUUdCRdN78gi3iFj0ET/aPBMwyoQLaefrQ1FlZLmhguU5MQlOTICWo1gw/FlzupdF\ntNvqy01QpxubltwMimRx6bof4JJT/rlgaN3tfpAQNSJSy7KgeItMibbCIVfNn4fPtC0qaf/cMOkp\nd5BFW7RWDTgi0Ae7n0Oa68Ou7oeLbtd+nkezR0tqixv2YiiKRyTYHeS16569CLTdSccuxSIoAIQK\nVSGgGHkatltv4OXioxRG9UGRSjinV9i1hBM0gl7Mf7lRH7kYSh+wrZOAqsoI0DFEAg1YUH82AODY\n6GvF9+MRHXYntBqIBBqwrvVqh2SkGM5su2nMffjw4aMQ444hbty4EXfffTeeeuoptLW14Wtf+xqu\nv/766WhbRfDKK6/gsccegyRpb/inn34a73vf+/DpT38aqqri4MGDM9zC6cN4L0a3hMNws1AmQKB7\nn40g3clidKfNw7mC9nGqTCBQp6D1spye6OhjusFUaeddyjhfH5yYNLXAjulCCnkhgRC/yDHdkIHY\nh9PdEeipKsFaKlbOvRyfOudRNFWvcTgbGOhPWu4LJMEgoXsv1wVYkILlrtH7bMRT8jIWUkcYdP1v\nFP0vOTsRighUH7zK2q8SciQRMoxFKO1D87Ii4tk938KTO7+KeK7LnB7Pdk6sYTrEjHVtvGRebre4\nsQg0QakINtoItC0CTRA2GYe+XilGEaqsL08okMksltgkOVIFCbSqquB1hw1DquFGY3TRyAv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o25rptAn9J6NarDhUVQakKtY27H0HFPBQI+gfYxSay6IoC6pZSZ9FwpkBRQt1TTQJeCTCaDLVu2\n4AMf+EBlG2KDbyp4kkFWROzr1T66a+d/1CwtG9r6AuT8IFAN1D35BBLVcXQ1AemARWSMb4o9Am2A\noFXA0BTqBNpeSEPMkAXrBRtOPvI4FgwCTUKLQA8LAh7v68dV88f+sJ5ocBe1MCDJWlTZiEADcESg\nCVkjLxRDgCYK5RSk1ALgYEExlYlAtGmLxUKVCBSe0IjtJPHS0Ag6sln89Egn7lz+FTx9OIMmlsKV\n81rAj+q5BAEVZy7+DDqTWvKeyMkYfstpBO1VstoOI3p9tO81xJIZ8AkSFACx4TBiS5rAxTXCQ0oR\nKIoEgAEvauSnKtCIQdf23NFLo8AHAHBiaUOdRnU/4zzaJT2qqkm8uCEKab2TQNIqArWF74IFH54Y\nSbNXJ2y5MItDSho8Y1VTZcIECKjIuw7a0N6zdFVRCYeqKkhz/YiFCq0W7fAqpX3qgk+W1P4AHQVN\nhcwy6vbOix3llFWvFIw27e7eglUtHxpnaR8+CsFGCJx6rYfh/TTgtddew3XXXQeSJCHLMm699VYs\nXrx4yvbnE+iTDIbOGdBM+xfUa0O726Wt6KrWtJisTCEmaCQnHrCG0g1pHuURgaZYFbKRlKUTaH7U\nIiuqSJj60+qVPLghGi3vPzklDMXQm9fO5Rm1tXhD110NC5UtGTwbUEwDzcs8VMBRsS/oINAMVGiE\nKigVDqv1y5vRQQZxGvds2W0TUlbYQ8yrjqIdACDlK0OgRVsiQFV4EYA9COjZt0ZVPiqoYs28KxCK\nt0PsB4QUwLo0vHZS6JWEK5EagablKJ7a9TWs5/8FFAAqpj1bRlEbWokiL44gEAghxxsFOgrJoLtq\nHUtHcO3Zj+C3266GIGXxesfPsGnJzWMeu3V8Wtvtkp4jf6DBJaogpq3rQFCF8ouWC7MIzZlgQaaA\ndd2qFkoQDmfBMdY7hgkTaDhNQGY0B3nEuu8oRSPQDBUEo1ercUdYD/Q+gdeP/AzvWX4bljVdWLQN\nbgLN0hHMrVlXUvsJgkA02IS4XjqdLVJiu75qqef0Zc0XQxAzWDPvypL2Vw5CrDaSkRNG0T3yOlrr\nN42zhg8fswObNm3Ctm3bxl+wgvAlHCcZRNkixCPpdqiqAkWR8HrY8tcNyBRaMtoweVcsAUWvbmRE\nFL0S/+yyDmM5bsQ5RmMQgLpTBCy6MgOmqnIlvE8EGGR5WZUVWXpmYBDZk8yRwxyyt7lw7O97Dj/s\nm4tt5LVmEiHgjEBD1u4zggYYwUqE64jow/ByK46SZ6A3/AlHee+JgB+xdepkTUZg1+ZKucroigTF\nIoQp3VaK0ROSZd4i0ADQ3KAliUXyywu2Y5e/1qzhAdJ53EYEmlK05zUzrD3fdLW2T4NU0nIUWV6T\nKuR4TdYxXjTVAGsrgbhfd3oYC/YOAgAQxv3AE0h3kw7yDAB0WAHtehfYyXCpsK/Tn9yJRK4bPO2M\nQDNhILfhYcd6WqVGgCBIRFjtvsvaKjECwOtHfgYA2Hroh2O2ISeMOn4XI8HFYCfHLFXomQ8Ac2vW\nOdxRLj/tHlx79sN4z7IvYvPqrzuuV6WxtOn9psync+ilKduPDx8nA3wCfZLBGB4EgP19f8RvXr0a\n2w7/h2MZVqbQnK1CSKSRDPK4b+129IUzUCTtduAxikSu27GOk0Br/xvD5QTl/Bh6DUW/GzCiE+gN\ntc6qi/d3je2/e6LBnTSWyvfh2cO/QRYRDJFLQBAWgTYICwCoEmWuLyzVHAVemvMSdsU0ElQrhsAo\nJKSB92DP8MQ1mHychJiiQAYUUCGtjRJPOKQmXl7l5YC3EeiESaAJZI/TpkOFSW710UxinAG/YL2C\n+o/vQOC8NwEA7KqjpstEQNT0s0G9mmOoRn/2SEAhORCgwOdzGM0cRY7XSF6pBNoN2T204J6vE2ja\nlHBo/4sZ73PLVitgIgrsSYrljAJULxcQmishvL4TT+/+BgZSe5APWMWhmJBWDbVz2En8uht+aUpV\nwoFCAu0+3q2HfuTowPXG30H3qHZN8i6ZS2CCBLo2ssj8uyaysOhyCxrONv9uiC4rKveoNBgqhPet\n/kcAwLDLZcSHDx9O+AT6JINoI9CClIWkcGgfeMaxDKtQUOsbcerijwAAUnQOD688DIAAQat45M3r\n8Njbt4ITrSpzbI1FGAziZEQg3ck9xpDuiYwsP4Te+I7xF9SRkyTkZK2M86JwGBfNsRK4jmRPLimL\nkcOkSgRURRsOl2xWbhnC6kBEQ7pUQyUBhQSgIqNIeLNRwFNLbsdr9YcwwmrnpzVfjSt7V+PqnrXI\nvDxxJw5eHxEJz5VB6wRa5pwuHHK+MhFou0VhQtR2QBMEEgeswkOmxKFItFVkRwoi7Y/v/CJeGLwd\nzVe3g1ixD5nQHgBANH8KCJUGJWuR6JoaSwKjMNoz/077Fjz6hiW/sPsLGzCs1MbCg1uvxFDqYNH5\n7gi0EUUfedtb98jWyCAoJ2nWCPXEQLLAgg9mkW95y5wm0lZVFTEPJPM9iGeP4vCCbyI0T8DiT6Zw\n6Xn/gAvXfAuA5UxybGQbRjNHAMD0xzbQPvAsHn79OqiqCkWV8cyef8Rze++EKHMFEg6anJjWc0nj\nZjTF1uA9y28bk3wvqNuE+qol+P/svXeAXGd9NXyeW6fvbO9FWnXJsiT3XjC4xCUGbDDggmMChFBS\nvpQv4U17k8CXhEDiBAhuVBsbA8bYGNsQXHFV73Wl7X2nz+3fH8/tc2eLtOuVrDl/Tb1z29x7nvOc\n3/lt7Lx9TsufD1RHO8EQDulCPySzZXgFFVRQigqBfpfBTaDLQV97Dgq33oGmNqfTFaeZCodGK8t1\nQ0W2OGy/X7epCLGOEgVdIVALxC4m9N8MF7BI/B2BYeh47I2P49mdf12ixJfDhKlC1go8CCHodtk4\nivOdKL/IIMQ1ba8CgAGFOEkUecYhafEQbd9tZUAzPPDd3mN4aoLHC6FrMMF0YFyg52yjFMOmFFVN\naybmTqBVkxxzEd328esy8Vk45ueS5z6m1gwDTxjPTI3V/MNvV+itvR8D1T/EztY/xLdfvgF7B54G\nABwZfclZvjECWc1C4SZR4I+BNUIIS53gdEq6IjEX+eLN1tkFbzSgu2CQIRyWN70PZ7R9MHB7/FaE\np7b9CV4/9E3PINpCaRFh+QEzG9Htwbf7usCUNjidNdzEkyEcsuJ+AEB1F2MTPqOhHx3XFsBHDcRD\nTRB5OvCwCDQA/GzL52AYOqbypTNERWUKmeKAhzBni8MlBDrlI98zISRU4dozvzytzxqgedA3bPwa\nzuz40JyWPx9gGR6NVesAGDhWJkqvggoqqBDodx1mQ6AL77kORjyBiFhtv8bqlPAZcBIQ3DdPVgTa\nrqZKoZplcOj7CbupAecqECKsAXKKn1Uj6d3240xxCLquIlMcntaXmzFVyARHldiQK8Pn3dhQxR1d\npmhFyHAI9IjqqHJWdBdnKqeMaGBbykvKUnwRMikdZMzgJCiBpS5zYcMmaJrsTQvJ9XHQZtfIaloE\nHVOOIfasTNc1CkJ1JnFkAEN0ZiEy4V042nAvikIfAOC1Q/+NidwRvLDXyRXWdMVOI+HNsRiv1YIz\nvdCeOgWe7ihrHwO0uI24/oit1WfhouWfs4vo/LjmjH8qeW3PwJM4MuLYITQZmNojQMl6iwgtu4wf\nTZfmsfSWjK1Q122iBL9q5fwV1tbElmJ3++exf8mfoWYZC8WM4uPL+IutIjkLW489jInckcDPjqT3\nekSEbHEIBdMDzRB6ANx+/3cT2qqpuDI2Q3fFCio4nXGKa4UV+GFFiXFEhGpMzxSCCLS7MUHBpz6V\nU5r4qDHjZ04lWMVYAKCoebxy4D9waOTXWN1yQ9mEgqxGCXSUo8Q5xLo64r1Ls6A10MKx4uFaIP8+\nwORvbstKiE/gfWf+DdSxKhSOUDVW9HX/1ImBh9u244KJdqzIOQphz49jqFolo2a9PKuGPKo5oGPD\nuofguy0c8hSLvl9G0XpVHoxggDnOK6DbA22BZxibQLM+XkXiGUCipE7iB0q+e2zMq/RJatYm0CRE\nCWdIpnGIjOAdpDKCaSHRqGp/5ZlfQG34DM/yOP8K+VATW4quukvQM/aS5/WimXUMAIO/jiDX5zB3\nS4EuF1fJRQwP0U8sVyAksxBrTuz/4I6gi4mNGGcPYpz9LXRdhWx1Wy1DoP0dLrcde9h+3JzcgMGp\nrWisWofh1E5M5A57BiH9k5uRlyfAsWHcuPFreOPQ/+DMztlF2J1qsIp/ZyPIVFDB6YpTXCuswA8r\nxi4hzTxHGgk5aoxFoFXWIdCv7P8qxjKOAkHvPV6CTFjD4208XkJyMsEdBSipGRwa+TUA4MBQ+Xg1\nK2kjZiaauBXonKZBCSBcpwIs1V3TFeRdAwuLoI68HoK8dQ2uHHqv/V6Pz/Pd3XgpasXVAACd1+y4\nPzf2JEbxcNt2z2tKhsXYm2FM7Z7dfL9d3BY2wLqi9vx51cURDod+kED/s8dfmFUMItCEQDO5nZ+v\nsnFnMOvOLrYwMLXZ81xSM3bUGiPSc2t9zd30uS9m0uDpj3J6AgDB+avuQNJs0GFl+a5r+8CM29SQ\nWFXymjvuzU2eAYdAlyPE/vUkBAg3aCd8jXAT6Lr4ctuqkpMmbAtHOaV9OqxsugZ3XvwzrGm5CQAw\nmesx259T7B18CgDQWXsBEuEWXLXubz1tuN9N4Fk6o1Qh0BVUUB4VAv0ugxVjVyUFK07W1CMARATH\nI2kRaJnzFo24FRqqAnrJCMMb3iKpRew+yB/YC2Hn7Av/ysHdyMNdYKQbWlkbR1alJCLKmlFtvv3Q\nVzj1bkTbjz2KR177KCZzPXjt0Nfx6Bt3Yji1G5O5ozaBzvfT86lOdshoKiC2Tzej3Ub1IvzUU2QY\nXF5XhwKn4nBkosTOIU3MrqWVFaPIhg2n2YtMbGLtJ3T5Ae64OxNKAbMKAhhIY/T4+33P4RVjmIq8\niV3tn4URYFdxD1QBQFayNnm1rBJG1pvuYcHgzExoLYFbz7/f8965S38ft53/CGpj3TNu0+qWG7Gp\n6w7vekzT1MZdRNj63hyar8yj7Qrn2Aflyc8H3G24V7fcgLBAZ9JGUwfx8r6vAShv4ZgOIp8AIYzd\nHXBwapvn+mehepr0jHcLLAKtzrI7ZQUVnI6oEOh3GawYu7hRWuFdF+rCteu/ZD9nXFKQ5Z8s+Ah0\nUIGNG4xggAs5lKiknfc7BcNA/OePI/bcU0h891tgpmbXVS0IbgX60Mj/2o91Q0FBmSr5/IujY7i/\nh8ZpxUwLh5+Y9eRPvRvR5qPfgaSm8dzO/4MDQzTJ5Rfb/wxPbP4MJKN0P1iQdb1EcbcKTqcIVWIv\nrnW6rUVZFp9f3o0vr1uLJ1buwBuX7/R8V59FjLYu0xg7EANiUrOtA0qWQDUJdMcNWYTqvAuzyPVc\noBkGlADm3dnvpF74FehIDYs97X+MdCR4gKcb3vXafPQ7ODz6Al1WmK6jbMZG+gcCoSgli5wWR1XE\n2/WSEAKRn13UGiHEVl8tWJaIoGPgb2ySWKog3u7qrLhABNpSoNe03gSW4W0C/fKub9mfsQhgENa3\nBxfmWU1/EqFm8Gz52Qm/j/rdCK6iQFdQwYyoEOh3GSzFKFlwpr0vP9aFK/q6cf3Gr6I+4Z1y/J2N\nX8aZ7R+GoNLYNZkbxerxOpxVcyMAIFMctn3VQWB4INykIdpGC5lq1s9DhdZxgBSdCz03NoKq7993\n3Mtyq27+jmXZYun0+78fdPJSo6aFY3UijtawU0w3Jp0aHQn7Jzfj1QP3QlKzIGBgANilLMEkvJnC\nWa00naRV24m46f3O+RRaq7nImEHPpWWulBJrn62Ix/CNszbgrqVehc9QCfKD7LRFhYVRFjAIQnUa\nGMFRP8d38NAluk5ClY5Yl5cJypNzvwTKZew4yw465NWfMuHP8W1Jbgx8PQi8SaAVs8uiX9mtrW4H\nAHRXXzPjsmaC3yvdO/4aRtP7SmwwjRfnA4uFxSogsVxGtF0pW1x4ItjZ92O8deEa2jcAACAASURB\nVOQBuq5mAV8iTPd7/7hjATJK5jkcbOz8GG4590HcdcnPPV39LN8vw3C4dv0/l/1+mK8u+967BY6F\no/y1v4IKTndUCPQpCsMw8OqBe7H1qHeK0SJ/4byOS/o6cHFfBzaNNGPFursArtR82FK9ARu7Poa4\nQfvFS/wwagsRbIpciWSkA4CBqXxf2fUgDC1oarsmjxV3p1B/7uJccJmcl+gSWQY7Ukp2ZwNZ86rF\n9fGV6Ky7CABN5ZgOlgdaYBj855nr8YkuSgZPlZberx74T+wfegbP7fgiDBiYQBu2s9fhRe73PJ8b\nE14t+W6zWI8YT6Vff/dFi8SOowiOECyJOlPsVuGlBZYQ9EedAtbsUR69T8UwvsVL7gojLFL76e9Z\nTTysyDR/N02r8I6L+JTx41CgrW0TXD4dYgA6Q5fNRXUwPteJOyYuGenAZav+DOvbP4TrN3wVxHUZ\n9ivAAMCHvZdpf660pQSz2tyaeswWL+3/iodAd96cQXJV+dFM82UFtF2dn1Xh51xhkWfAaUvubk5i\nISh+zwIhBFGRCgY0ro1C5JwUk5rY0rIttS3F+92Mige6ggpmRoVAn6IoKFPYP/QMth77PnTDUftk\njRLokMpiU2411i37GArnXghp3YZplxdSqYoj8cOokkSQYhHJCCV/U3mn21fbtT6i6iIKixlfR3Kl\nXs3Yzx4DjiMBQ/H5Plurz7LzjIMUaDdaQo7qTAhBrUilyPFTRIG2OrTR+CpvvrMOgkGyAq8wt2NA\n2Fzy3bCu2B7wnOrd70qOsqkUL+GsZNL+HADPYwu/Wb4fGc47mzGx3du04tjPYhh6MQJpgoFm5jtz\nYTM6ztcdk5gtsv3+YU2eO8tLmZGFLeEw/ma12aZbE8DoDAhvYOmHS5tPuBtuvGft/4HIx7Gp63Yk\nws02mQOAuvgKnL3k4+huuBJnL7kb3Q3vQXV1o2dZfgXa2iZL5Z9PcGoVosPn2y3QxRoNodrFKYj1\nt99mTZm/Pl7aIr0utnxWy2xMrAUAEDA2IbfgbkN/63nfsR9HTgMLR4VAV1DBzHgXZCacnnC37C7I\nE/ZN2FKgBY2FnqxG8ZwLZ7U8XqGeVJkbRkKOg0gFVNd0oGfMS6AjTV5ixMdPjnQJvwINAGwmDSY1\nBb2mNuAb5SH7Cmc66y7CSHoPAGppcUMzDDAAdAD/uHYNVsW9KmCdQFXT8VNEgRa5GCTVIYCGqyr0\nKNmE7ex1AIAtvIbzfd+tYWNIm2pyTvMq0KqpEE/xBVwcj0FwRdlF2NIiQSai4aGOLfjsYe+vHHs6\nQtVN12BNKxK7iQobmd42EGlWEWpQURyhlz79OAh0WqXqaxXPYUOSdl2MK/Q48zE9UHklhGBj58cg\nqznERC8h7m680i5Wi4p1WNpwmed9v0ruV6CZBSTQ3UN/iZrcRRh+if7vFzOm8pntf+l5bhHo6mgX\nuhuvwKFhWq9w8Yo/wtL6y0q+HwSRj+Hms75ZQp4B2lDJQphP4rzuT0FWc3ZTlncz7CJCrQDDMEAW\nYjqhggpOcVQI9CkKN8nbN/gMNnXRlq9WI4GQxkGvSgZ+NwiMSqfUFTaF6mIDdJcCPZlzCDTxT00n\nThICnfeqxmpNHbiJMbBTE3Mm0DlpFABw7fovQ+QTSEbakZdphFvWR6AzqgodQJzjsCZRemOtFUwF\n+hQg0LqhecgzAKhwzLwWeQaAEbYOfixPno1RnTaacCvQhmHYFospvogQWwXRlZPtt3AAQITloJBS\nP31hgEeqj0GsziFyvU/HYMUrWi28q5ZrMDIcFBQwsZtF9Wq6/xkB6Lwxh/EtIsbeDh0X6Uy5muYY\nBvC32QswaZ4WfouIG2d2fDjw9VXNv+Mi0PUl7zOiQT0ihjlIKKNA6/NEoK8+45+w7djD6Ky7CMw+\nal2SU/QYLSaBzhQHPc9Zl9F8Vcu1NoFe1vieOS3XX3hp/17B+T1CGKxuuX5Oyz2VwTAcGMJDNxSM\nZvaiNrYscJBRQQWnMyoWjlMU7qSI7b0/tB9bFg5R46DNhUDr9GZ0XehmhDQOjOQQ6P7Jt/Hawa97\nrCIWkmsWp2jQDyJR77VBCIrrN0Ft6wCAOadx5KQxZKVh8GwY9YlVSEZogVaIp/vSypm1kJIdNTII\nCZ4DRwgyqoriSd5QpaikS19kq0pfA1BgSl9PslHETDtGxvQJa4aBz76+GXKOwICBFFeEwDAeBToa\n4M2PciwUJpiMDvU4irYDKwPa9ECzwMrrRDSeo6D7tgxqN3rPU3fM3Vzw1OAQvmYWjSZ4DlqBIHQ0\njuYiHTxxMyjgQQgLSVy55os4v/vTiIUaSt4nBN6s9QW2cDQn1+Oa9f+M1S3XlxTjLRaBltSAGSYX\ngW5OrsdVG/4Y12/8l3n7zc46OnvXWTu7Wbx3GwQzS/vpbf8PdvQ+tshrU0EFJx8qCvQMEAQBbMAU\n83yBYRiEw+Ujl8qBZLxT5OHXfwOOEaDYBJoFqW8ou2xCCPL5PHieB8twMDR6822vXgVgLzhVQUPN\nErAMD01XsHfwKSxrvhTtdWfby+h4r4pY8jjWfXIc3I4twKZzAG5+VA3eJKfKVdfBOOcCcK+/DAAQ\ncxkwrn3g3m4ugLgNZ2i6RGPVaoRCETx6rBdn19SgKUYVV1nLevapXKTELCmIZfd1nShiqFjEpKKg\n+TiO9Xxgpu0GgLw6WPKaIDQBsxTPq/gIWvkoMAKMKArGdAOKrmN8SgEDgoIgQ2MMxEMhJCNOEeHK\nZLJk31WFQlAYpxCMixh4sHYbbu/dAOZAHGpDcLZdtEZAKDzz9hZilIATjZv1/29SlnFfjzMbUxeJ\ngDO83w3FWYTD4Tn/r1e2XT7t+3wUsFxb4TiPcNjZJiNEPd6GRsASfsbjPBcYXBFEdY4VFyLTbtfx\nXs9mwpG+X5e8Fg7F7N8ihGBd+/shy3LZrPa54sJVn0BzzRosabgYHDt9M5+F2u5ymM3/+UQh8nG7\nGPPo+Ku4YJW3kPid3mbgndnumXC6bncFpagciRkgL/DUezgcRuE4mmxk815l9dC+n2A0koPcmAcM\n6oFOh6PQyiyb53kkk0nkcjlIeQWAAMIZkFkWIgA9l4NUlMExYWhmfthkdhCq+iZqL1iDYl8MYlse\nx9MfJPnA18FIRciShOLZfift8YHJ58ABkAmBXChAEETwALR02rN/3dutKKVJAukcLVQSuSR+fqwX\n3z58BN8+fASPnrseAFBUMp7lTZjWkTBDyh7HGp7HULGIkUIByXm6uc8V5bY7L40jVehDU9V6pLLU\nukIIC8OcbSAsVd7b9B3oY84oXbD7NxQdjRF6SflpXz9+2tcPBkCnQlML0oKZ0KKq0Fz/q6WiWLLv\nRMPwNFQhooYjEeecH3il9NJFOAO6UEChMPNx1ggHgINc0Gf9/zuc9ir0SYYgNyUBcA0CRRmFgnzc\n/+tyCNWHUByjPmsVEgoF72wGI1I1vJhVUFNXfrvnCoYVANdYZap4FA2FUpuJhfnebgBIFwbxwu6v\nAACqwu1IFeggV1Nh/9ZMx/t40Za8AIqsQcH027QQ2z0dFmp73XAXvvJs6fa909sMzNN2qyqga4Aw\nfXv7cjgZt7u6+t2fDHMyomLhOEWh+KLWnl1yCFsaaUKEoLMgILYHWtI0vDQ2jkIZC4EVUcVwBgwz\nRYIUKdlZ2Xyt/blX9n8Vz2z/C+zl/wNtV+dLorpmC8a0W7CjwzN8cvYgMlWCDZFeFPUwVc2YQvlO\nakGwcp9FLo5+10WSY0JgCAdNl6Bqjh3A6kAYm0YVsHzQo8WTw+7ixsv7v4pf7vgr7Or/sV2AWlN1\nHta134YNHR9BMkEHDmtrZu5kJ+ocWkJeZUYHkFToOTXG0f0pMgxYQvD+lmbc3NJsJ5W4Eec4qC4L\nh8HryHPT3zDFGm3WSTBztXAYhoEDWe+5tCaegJr3/qBQtTA1AbEuc9uJASGgcHchkjgMA4DiTT6R\npt7ZYrK+ibfw47c+YT9f2exkXUeFudU2VDBXOIP9QHvXKYrk/fei5r/+lRLpCio4AVQI9CkKRS0/\nAmZ1Al0QYZgk8rmRUXzlwEH86fadgZ+3uowRDjBEk0CbJHdD50dQH/c2X+mb2oOh4vHlPZOMcyG2\nyO58wCbQAl1/I0IbVJB8HkxqatZk3fJainwMbq2YEGLnxLqbq2TNi/B0BDpu+qOzJ9kF2zB0DExt\nAQDsHXwaipZHCo14IPse/FY9Hxs6PwJJp4Spu2btjMsjGkFzqPSYVpskbJSlgz7L/3x7Zwfu6OwI\nXFZjSIROnCOgmzF0/7bslbK/L5oZ0BOyjN9/8y08tHdf2c9ahXizjbH76cAgHjrqdOVcHouiISSW\ntBnnEwvjc4+2aui4MYslt2TBRUtnMawBwfHkWpeDrgDQvcubSnjzvydyRzCePTxvv+nH87v+1vPc\nqkUAYObUV7BQ0F0pJAW5fOfRUwq6bhec+wvPK6hgrqgQ6FMUVrFgEK7uWQatth5WntaBLCV8A8Vi\nSYMLAJjYTkkPVaBNT6HZ2Y8hLM7uvNPz+ef1G/DpLdvQm5/jNJZhIP7Eo/ZTcccWxB/7HkgmDVnN\noWf05cBCReu70ad/isjzTwe+TSSLQFM101Gg84g//n1Ufe8+sGMjM66ilULhbnxhry8fhwHgR/2D\n2G1O51v7MzqNT96KacupKt6enMKh7MJcuLdOpfDs8MzbaMEdyadpMhQ1j70Mjf/69egY0oqCX49S\nW0c4YPsead2BcT6PfTFqe9EkAo5hEDcHEzFFQETlkZTpOTVlWjjcBYTl0Ch6lU/VvJmPijnsvDSY\nGAvV9NzZOpXCQKGIr+/ajbcmJgI/y8wxueJng07+9+eXdeMf1qzG1B4Bkzu8AwY+tnAWnXCDVjb1\nxhoQTNetcTqkDvDID3qPsVagx4mP62j/WA92tX0BvZFH7PclNYufbf4sntzyOeiz6bc+D3C3JWeY\nigNxIeGO8VO0HFT95E8SmgmWMASgokBXcMKoEOhTFOUC7q/qWYqlqWpodY5P0a18Tvn8U2oeSO2l\nJEArEOgmcWFcF5r6X73s+c64QZf9ehlyUg7M5AQ4lxJMdB1831GI+3fjV7v+Hr/Z+yUcGHo2+MuK\nDHHfLoR2bAFknxVC1x0Cba6/pb4z+RzYFFVPYk88BqjTMwwrZcPdlcyCwMXQS9bjJ8M5/NUumgs9\nGwuHRaAHCgX837378Kc7ds5boZMbf7dnL75++Aj6ZunPSxf67ccFZRJ5eQpjpMt+7bCrOU1HJIxr\nG2l+8Zn6LwEAW5OD+JcVL+NYmO5fyw7xT+vW4NqaJvz1/svxJwcvQotBZwMmedPCwc582ak3bR09\nYep7now6lqVJvoimy/KoPkPCklsySK6RIFRpqFpBb/DuyMAn+gYClz9XBbra7LB4eX0dLqurBStz\nGH7Fsauwoo7my4PbW78TIKYN299yezZQsgRDL0TQ+5R30Gip2WxIR1hMIhPbCllP20Tq6JgzG1BU\n53+K3/8fuWTFH6MluQnnLP0Ert/w7/P+exV44SbQAJA34z1PZZCCcx0h/vtIBRXMERUCfRJgNL0P\nB4aeQ7oQfLP3ozDKIrrzJghKAza2fMjznqBTsqbVOXFYo64ueFaGrYV0j6M6aTIBBAEGISCKYnfx\nS/aNI48qPMt+DoeJk8KRmeMInjEvXoZPzSxMHMVwehcAYN/gLwK/S1zEn510iDvX34vkN74CNkWJ\nlqVAg2Wh+/y4bHoKbO9RTAfLniFwceiuG7huGIiK9UiRJs9r1uAkKIrNQsTMOT7mIqT+43CikHXn\nZvfj/gFMzqL41Z/5fCQ7AZU4iuqYed6cV1ONjkgEt3e24yvr1+EDHWs83yuwZmSdqea2hcO4vYa2\nho9qAjoUGnk3xc9egeYZBmsTcdzX9Ta+074Fz9Ue8qyX3JFF7bkFCFU6Gi8sYsktWbDmqo9Izo2x\nXP424QAQA4ZKYMzCtmwt5/aOdhBCoOYcoipUaVh2ewaJZQtTzDUbMNzxK9Bu0l0cc46N3ZwmZARa\nmFL5PvuzCzHF759l6268EoQQrG29CXXx2XUarOD40Zxc73n+47c+iV19P1mktZkfMC5xoUKgKzhR\nVAj0ImMyexRPbfsTvHLga/jJW5+a1Xd6n4xCHFuDZUP/Lxrf2IWGXNR+T9BKCfSY60KR8inQ+SEX\nmTUIQIit4sZ/8gigKOAMBgeYC1EgVdjBOkWFw/m5KRLWBUttboPW1gEtTlvlFlLOjdjf6c/+rmu9\nuaEBCLu3A7IE/shBMC7CZLim/pWu0sI3rqe8X1PXVaQKdF1EPoZXxx2iXtQ0iEILBsgq+7UxScbe\nLCWhdUL5mKuImY3c77K8HM3ny318zphSFJvsAsD/jo7hb3bvnfY7BXkSfRNvel7bn/cyyWPmzcZq\nTx5mWSyJRnFG+wdtRRYACiw9Nu4CNnnKubToeacLIUCLCGeDv1uzGh/pasXuxCi25h2C9vrkJH5/\n81b8sLc/8HtuAj1VjkATl294BhVa0nSkVRUcIUia263mnG2wIiAXE1Y+8/Eo0Lrq6jb5U2fmxVKg\nreY0omlrsmZpiopzTNyP5wtFFylf3vi+eV9+BdPjrK47cfaSu+1+AADw5pH7F3GNThweBVqqEOgK\nTgwVAr3ImMj22I/9TQvKwTALe0JyG/iiDF53DqP12LJwKLqOguYs10+gCyOlp4BVgMf39qDm3v8P\nABBTSj93YOrIrNbXgkWg9XAE8h2/j/RH7gYASGlHeVe0HFSttECRKA4Riv76GcR++SQiLzxX2sLb\npQQrHV32Y8uawh49hHIYTG1DThpFVKzHUaUWk659VdB0HNbaUCROA5HH+vsxKsloCYWwOqALoQXL\nwpF3paD0z2CzmFIUPNbXX2K58WPL1BQ+/tZm3HvIOzDoLRSmtYk8ueXzODL6oue1ATXheX4kR282\ntQGDgy+tW4sVMUqoLAKtlyHQAKCwGiSWbv9sFGgAYAlBY0BRor0Ng6W51QAwJTv7LK2qUPQZfMMz\n+KAtQl4rCGDMugLFRaBjSxZPebZgEWjNXJW5OIQM3+pbdmbLA82G6P6zWlhP5nqQl8ZRUJyc7uIC\nKNAFk5QnIx24cPkfzvvyK5gePBfBurb3ozY2cwLPqQKmYuGoYB5RIdCLDM1198qjCoU52CIYPQRO\nZ2zVGQCMrjUonnmWXQyY80XXuQm0YRiQU6XkwW99AIANY6Wd57KYW4yU41OmpMgi6jnep4rLpd0D\nSQCRFPfvAXFVUhfXnel5361GyytWw2A5sCPDOHhgv8fyYP+uRNt1N1Wtx4Gcl8T/+c5deC0b8bz2\n/AhV4G9obgJLypOwSEAB3tgMFot7Dx7GD3r78G/7D2JckvE/h3swGJB88oipwu7JZEre+0FvX8lr\nFvKyywbD0ONRIN5jbHmgawQBUBRahGkys4aQiFvbaAvkvKVAu5Rcf5yaJjrn9WwJNEDbZZdDq6uZ\ngW4YeH54BGOS5BmoAKWDRgtWI7uZouwGzILalrDrfDIHCHxMR/3Zx5dIM5+w6ul0hUDOG9j37TBG\nXgtN/yU433FDSdNtU/OmhcNUoHmWnv8v7vsXPPrGnR7SXFgABdqyisRCjSCLZS6vAGFh9h1tT3bw\nPY6AQha4x0MF735UrkqLDMs7mEcVnuM+hz/ZvmPW32UMEZzOgNddPuYLr0L+SicrNa96ycThnDMC\nVwqOmk1YA40Xm+8F8ImQVippySSKm3/7Ol4bn10xoTXiz4oK9g08Zydu5H0EuiAHLC+ABBksBzZN\nVbDCuRchf8U13vddBFqPxSGtOQNPNrTgo9t34eGjx8BMTQC6jq1TKTwxMIiCTAuhQnyiZL+NyzJ6\ni5R0t5Mez3sr4qWJHW5YHmj/8qbD9hTdrp3pNL68fz9+MTyMrx44WPK5JF+eYP6ofyAw+1vzGWVr\nYtSvrIIyyiURSqgtItrAc6j6zjdR9d1vgRtwSLmVzGF5oN1Krt/WEI46z6cbbPiR8LVID7nIt+EK\nGnx7cgr/dfgIPrF5q+1Lbza7HU6WIdCzzU4eKFCCbFlZdBVI7af7qvGSPMjCNSqdNWwLhwqM7VWh\nFggmd84uJtJt4QAAOUP3sTRJN0ww4wGzRW/Ci9tutRAWDqtQ2iLuFSwO3NGBpzQMA/wR5xpaUaAr\nOFFUCPQiwyLQo6QLADAozX5UzBohcIZXgeZZr3qc0yiZsIjW9lQKqqm+yhl60xWSGpbfmUZyFSUa\nakt7yW9J03RN+fL+A7NaX0uBfoL8GL/e+SXsGXgSmUsux7b6Ic/nCkEKtFq6X5hCHuwEjVCT1m/y\n2DcA2E1hAJrKIS9fjX9dSgvgHuvtQ/LBryP8m2fxd3v24qGjx3CoQPeVyCcwJAWrioKRQ5V+zPNa\nkMXBjURAgeHYDMeZdxFFq4FHb4DtYyYyOhrg88tJXiJUE6VTtBaBfk9Dk+f9lkzaHqhY+xsAOPO3\nLQVadWUQG76JlGiU4M9WLMdfr/Jmis8EvwJd52q64h4cuPdN0Ty/l1dRRb1cZjkbpp9zFwQGwVL+\nLQVaKxAYKgEb1hFtXZjc57mCuDzQDOdsz0zpcnKawdhbXqVaSTEwDECapOegWEO3kfFdAxRXkV+m\nMARJ8dmpThBW1r3/mlbBO4ua6JLFXoV5ASnkQVzXjIoHuoITRYVALzIssqiX66ouS+CO9XhMjYRx\nHnM6YydvAADnJ9CmktoRCaNOEFDUdTuVQ8pQAsFFdE/8VuGCS5G/8DLIy5yCueI0OccA8PVDRzyp\nFUGwRvwpUIW5f+Jt7GkrIico4DQGzQnaKjqIQLNj0xcsWrnPbngU6HAE2ZjjU14u0ZvzxN7d9mtj\nMt1XIS6OCVMhbg9792cdesHrzvpxhAQSZDeqBQGdEbqcC2poy9WZFOigQruaAKI+U2Sd384AAFuO\nft/zfGnD5Vjb+rt22+71VY4XOsKyiLsGL27LzLJYFFfU1+G27maAGNAlBlaMtx5QWHdBbQ3Oqp6b\nmhX3KdBR1nmec80S+BNhwiyLJaYvva9QZjBkKqtyavpz21p2lTkItawqbGhx2rIHgTHHGbkBBprk\nrJeSmf4S3/dMpOQzcpqhkZYSA0YwwEXo8i5e8Udll3N0/FU8/tY9yJk2qPmA1W21okAvLpqS6z33\nFf8M1qkCJuONWqwo0BWcKCoEepGRLVJiaKl/ADxFT7FfPIHE499H6E2nAxhxcQpOZ9CQd1I4ONY7\nbWsp0FGWRZOpyFqK2vBOSkBKOpuxLIrnXQyl1VGiCz5C16Fv9Tx/dmQE21PTZ8EaUgG/6HLUas1Q\nsKufxiJdeWwJGiMrANBMWXawH8y4SZplCZFXX5h22X71GXAKBwHACIexxWV7jpgXz70xhyz2SCFM\nohkin7DJWb1L8bysrhbnM68iBEdpqxUEkFlYEr64ahU+sawbn+leCgKqDJcrbgO8CrSFGt5LoLdM\nTQWq0oBjdfBbODRdRu/46wCAluRGXLj8s6iPr8Q5S++BZNDvNLqUe5FhPEoN40oPYQjB55Z143da\nmmyfrKVC+/vhHG+Lab/C7rbLuAcHE74BCQHQFacEulzBptV2W05Nfxm0zgWLvFueacsCcjLAirFT\n0gwO/9rZF5afuRyUtDN4sJRmJcPYpFpIaFY/psBisqUNV9iPZTWL/935Lzgw/Dxk9cRTZhwLR0WB\nXkwwhMUHz3HSN/zxl6cKmKx3vSsEuoITRYVALyIMQ8foBFVAeaHLft1ufDIxglfl57CrdgSRV34D\nro9aB6ybJUAJ9JIpquoRMGB8hkz75s9xtofTmtIe30d/J14mRUBPOOTSr0BHjFKV2Op4WA4TxV7s\nqXMsAOOZg5jM9yCsClg1UYewRgmiVBhD1SMPIfmd/wEA8P290y43c/OHg99wKbaGIGJSc1TKoskK\nRgSHLO5W2vAidw+m9JhNztwNUr6wfBmSYghhwxkoNMyyHXmtKOADHe2IchwaRBE6gKFi6QVc3PIm\nxB1bwDOlhJPzvbYr7dwQzqupxvJYFDWmSrrcTMjwK9DDqT1QdQnVkS6874x/wIqmqwFQMq4aBlhC\nwLtI68Zk0nOjIYXgLopW1Nnwy2HIaQaG6autXieBCxuoP+f4C+3cJPq29jZ8oLUFAKAahl0M6lf0\n85pme6An5ODzW6ii+2ZGAm0NQk0vu0WgLd/xyQAu6gzGVNdpZWU5u2EYwOALYUzs9A7IxFqTQKdZ\nyGmnC+F0qHZFnAFA7/ibeGX/V7HVN8txPLAVaK6iQC82QnwCVeE2AICkzH/TnHcCTJautx6l10b7\nuqbrc4utqaACE5VeqIuIrDQKySggKvPQELaPRlZVUSNLOPKLv8fmDhrVtXa8AeKubRhNL4Oad274\njM4jrDG4a8cGZD7+mZLfcLeatqaghyQJhu7caKNtwUZJtY3eHCXC4Pm6Zs97IkoVpj3pDMYyB9E/\n+TbOaP+gl8wbBvKZfriDO1SdkqqOfC04g0H1a28B3YCUGwNAiW3VQ9+gbcmD1q+pBZkbPgAjlgh8\nH4SgJxxFmuPQEY6gkHEldph+zhGhlACnUY28Rve7v8NgWKhBFE5833Qxa+XQFg5jWJLQXyigPeKo\na4Ys4d/6BvCruqbA70mal8xYxW2fXNKFa5oazc9oKOg6vnuUDjoK/mLIDK1Cr0849pwf9Q/YiR1h\nhgEhBF9ctRKvjI/j7q4OMNvetj/L5MsRaB0SWOR6eRwbYW3iFV+qoPMKgkLh+L3CYYZB1hwIhFkW\nH+tox3PDI0irKvKqhjw07M+UDt4S5gAqG5BsoxuG3RZbTjMwdJTtIuhXoLWTUIEO1eqoP7eA0Te8\naq1aKN0oaYJB+oAA+EoXLEuKmie2As37WoevbrkBewaetJ9XR70E2sLR8VdxztJ7ZjU7Uw4VBfrk\ngsgngAJt4X4qgpgzUVqyGkwuCyLJYEeGEH/8BzDEEFJ3/H7gTGYFFZRDl7SL2QAAIABJREFURYFe\nRISZOLonq3HBQDtyukPEXj3yCNjxUfRUOZXtWaYV+8euxsirvhtkshtK51JEl5yDeNhLcgEngaCK\n51FnqqVjkmx3LGMEoyxxMEJhFM88C08uXVXynhBAoLekUnhk699jy9Hv4sDQc573mHQKeRJMvton\n6DaFVXrxkvKOSs1OjkM4WNoUJH/xlUjf9vHy5NnEnWdegM+uPQepcBRFlxo7KRp4onsvRgIU5Jcn\nCtAMAzwhWB335jtXR7vAuPK6ozN4w4PQahajDe/cBuLKsT46MVGWPANAUfeSUMuKszTqWHhElkWS\n513Z06rdehkAJnNH7e2w8HBvabLGpuokPrusG1GOA3EVVJIyDWAsnywAaBKD4hg9loQ9cZIZDkgx\nsdTgnKbihbExKIaBc6qTuLnF+Q8kBDpg9BPolKLg7rc346H+o1S51QlS+8unmVhRkLYCbdpRrEYs\nJwuCOiFqZhSdJtOmSYZRvtlKqE4DYQ0YGsH4ZnqOCj4CffaSu1EXX2E/j4oNCEJOGvVE203le/G9\nV2/BQy9dj4HJrYHf8UNRLQ90hUCfDHAa6ZyiCrR5HdPjtLiYyBKE/XvAFAtgU5MlFo8KKpgJFQK9\niBDyEt57ZC3+s+kGHBHq7NcPT+5CaPtmO6YrLC3BjujnkS2UKrGa2IDM+29D7tqbAn/DagJRL4p2\nWsS4LEFOmyraDCQge8XV+NXS0uSEC7tuwyXqAyWvZwhdx8mct8kKk8siywcXznWlqQUlolIS4ybQ\nbhgApu76NKbu/CSKZ58PgPrF35yYDPQTD7qKx7KqiqJLwS0yLA5VT2IgVFqY98YktadEOBYX1dbg\nM0uX4N4NtK1tTZRGvl0S2o32cBg3tZQOWmaClV/8kBABnn/afn3r5PRRYIdzeQ8ZtI5tU4AKbhHh\n3cMv4nuvvB/fefED2HLocUzmegA4U++KrsN9BoQCBgRuC0c5BTrSGjyLwcyDoNNpWjHcF6u4qRSl\nFRVvmcfr0ro6fKitFdc0NuBLZ56BuHm+Z1TVbiozXCzixbFxpBQVTw4OQUhScjz8cgTZoxyyvZxn\nNtcwDORdszgAoCknJ4EOWh9Lge5/Noren8eQPcoFEuimS/OIL1FKCiMtW4cFluGxqvl37OdhPom6\nGG2r3VF7Pj580YOoCtPaCXcc5Zae70I1FeVnd/71rLanEmN3ckHkqVhxqnqgLSHAsiZyYyMIu2uL\nyiQvVVBBOVQI9CJCT1ThmQsux36firqZuQnk0H6oDCV8a3r/vewyZH76ZiZWjFn9eAKJQaqm1owk\ncOhHlMTNRAJeHBvHbleTDkHXITIMNjSux7Xd16Nep5aAGoP6syXQm52/UptIRaSFUs9vPNSMhEwJ\nYMhUoItcMBnL3HI79Ooa6DV1sCqbnhgYxD/t24+vHXQC8g9lc9iZSuMPtm6zXyvomqegTgUPBQKO\nhhNgDAObQqUtxCMsB0IIrmpssElvPEQV4mXGVvzHhvWoniHCLghtroYcP1J0GJk0BgtFDJeJW3Pj\nK2YWtKTpyGsaOEJsMmlBNzQUCj0AgLH8EIqI4WnjdnxqK4PdZge9ZLQDADDg+82SJBVVRWiL0/Kb\nFPLUM+hDfImCeHfpAIlwJ04yP7VkCc6rqcY/rltjv5Yw7Ui9hQL6zYHSqngMIsvik0uXYF1VFUIs\nC5FhoBoGJF3HsXwen9qyDQ/0HLWXE1vvKOr9z0XR/8so8n3O/izqOnTQokzOLMy0FOiZBp/vNNyD\nFTvj2vRAF4bom5lDfEnjGD6uoWqFAsKUJotYSSVutNee57zPx3DVur/DGW0fxHndn0J1tAMRkV6T\nntzyeTvrHcdh5bCImlDxQJ8UEDl6/7BauZ9qsIqhLQW63PsVVDBbVAj0YoJhMN5RmrGpEhFPNLZA\ntlofaw5JNoj3hiazwRcDC6OSTKXbl+qQe6kKosbi4v6l9vuHpKytZAZhs08V/fnezXjw7E1I8jwE\nLobz9UdwtfoV1NoEmk7zabqXTEmFcRyopopUVHSUdIGLwDBvrqLGmdsU7Jc1AjokvmI2cXnF1czl\nT3fsxBd37/F87sGeox4LhE54/Jb9KDTCYrUi4UJhK1boL3m+E2ZL/x6WGmYVOB0P2l2RewcicTz/\n8yfwB1u34ZnizBngW6ZoHnPKZc3x+0x7x99A7+izAAAVIvYxlyBL6AzHK+QDCPPVCPH0vPHnUfs9\n3+KubZ7nBCaJ9oEwQMsVBacZj/X6PDQZqRUF/MXKFVjlstNY+dBfP3zEtikFNZWxtiejqngzQOEf\nTmRQu9E7iCiOOSv90hiNZXMPUpSs2eI6fHIRaDesZB0toMuin0AzrjEgKzrXl3CTGjiDIHIx3LTp\nXty06V4whEWIT+CsJXchKtJzjHMt0FKhQ9z0Vis/VE0yZ0sIkpGOOX13PsGODIEdDm4Zf7rBauV+\nIgp0ThpF7/jr9ozQOwlbgY4Hn4sVBbqCuaJCoBcZE2XIa44LJpKjy+/zPFdIAr1PRzH4m1JyWdQ0\nZFQVcd0hFm1sFEXGlZ9LZDwxUP4G4W67/AdH90NMT6Hpe98CMzUJkUuAgY4QchANOrUvEerHVXXX\nduk6Rt98BCqro1VvxS3nPmi/xRAO6Q/dCWnlGmR/7wt0m1jd02XOXky4dBtbXWpuQdPKRsPtTGdw\nKOu1H0wSWlW+XC4iJ41BMLzvF7TSZfEcXQdrevl4EOc5fLZnHwBgWAzhv7tWTPv5i2prSl6bmoY0\nZotD4EFvBjLC0OD9TNJV+OX3VX+8y0tWhIN0PfVYHFqCkm4mgEDby16loOZM50bEzIMHOghRny86\nwXG2QuyGlSOdVVVPuoiF54ZHPP5tABh7O4TxrXRW5IVRaie6usnx+spWg5Hqk6OJShCsVBRDIZ5I\nwcwRwW7RbcGdJuIeFDRfXv44V0e7PD56N9xt4mWV/qesgmGgvG/ajYncYeiGiupIJwQuOuPnFwSG\ngarv34+qHzwAVCLP7EHQzr7H0T+5+biW8dK+f8evdv8D9g0+PfOH5xk2gY4En0/TXdcqqCAIFQK9\niDAMA1smnTi4hGtUPhydQDFMb/4q44z4U6pjVQCAkZGlyA9wSB8UkB/wkgrLvtHOONm5y7gEZMYV\n58aqnuI6P9wEOmLGebET40g++N9oyjpKqgiTQINenNw3Uf7wAfTGqXLawXizZBmGh9bcitx1NwOx\nBHhC1SuZ0ZC/+ApIK51p+yAF2t1ye0KWbWU2CGNlmpdUyxlM5nqwxNiGG5rq7Li/9zaUes55xiLQ\nJ3axvXacWkYGArbJjT9evgyf6V7qeS2vqphU6LYEEeiikkLIjNorkjgYeI/v6pYbnc+ag4SLa2tw\n36aNWOkrmmSm6HFMf/Cj0E0CTcr4oC24o88Wqs21vzCwqkxL87ipVL8xMRnY1vxANhdoYxp7K4SM\nomK/Gc34vgaacpI6wNuNV4LsDScLLAKtq8DIa95Og+NbvM/dBJqPOdt0vAp7W8059mOLQLuTG2aT\nzJEuDABwrEaLAlfsJTfYv3jrcZKguXqj/XjbsYcde84cMJTaDgDY3vvDeVuv2YKYsaGGGIIRUOsR\n/dUvgIDEngoqKIfTjkDruo4nn3wS9913Hx588EGMj89f56y5YkyWPYVuS3QV7TqdMu9J5KGYqo3E\n01bXvbX3I2sc8y3FuRn1Ph1Dfsi5MIyY0/MtxBlxd7JRyC4FusAqduvjILgJdNRHQBoe/zFYM3tP\nNJuLWAr0ePYwvntkJ5458jxILouUSLelhqUe4qpIKwCgtXqTZ5kWQZVZDcWzL0BxE/VbaokqIOCi\nl3Zd8CZlBSml/AVQLTNtqDB9MKCjMb4Udy/pxtfOPAPfOfss3GzmDbuRfPpJEINaVCZzR7Gr/6co\nzrUq3TAQ0TWImgZ5mhbpAHBJXS3CLItPLumyX/v50LC9nYEEWk0jDDroKiABAu/xra1y9rk1eIpz\nPGpFn59bVcFk0jAIgZ5I2soNk88Digx2qD8wP9Wt6JZLeDlR1Pm85+W6YFabSRyP9PXj+ZHSbpaT\nilI2ju7x/n6ohoEVsaitZBcGHU/DfBRIzjfqNipgOKD+LDqQ1BUCaWr6c8ydKx/vcv4/M5yaZbG+\n/Vb7saxmYRg6+iYcH73Vons65CSq/LvtXu803J5YfqBvmk+eHoiHGtFZdxEAYCS9B9978TZ7gDQb\nGIYrq1x/ZxR9dmgArDn4sRRoIxRC+sN3BX6eSafekfWq4N2B045A7927F6qq4p577sFVV12FZ599\ndtHWpYYT8Fe587EuRdWtK4pZhEzio4GDbiqHrE5J5VjiORSFPvTVfBtTkdcDl+kugLIU6EbDUTmX\ncF6FcVd8pCRf2A138w4hgGjfvY2mU1gWjqLpgT6As/DjoRy+ORTH7sxvkOfoDT0q0/W78ex/xQXL\nPoO1rTd7f4+nJK2YjAOEQGtqwdSdn0Tmgx8LXL+0S3H+xpEjOJSb+YJ+nvYIbsw8aj8vstQba2Xa\ncgxT0kLagnjoAASNMosX9/0L3jx8H17Y86UZf9MDVQHRNCRdLbJrXVPEy0x7wkrZGVxd09SIOzpo\nusFwsehYOIQgBTptn0dFkkBdbJnn/TFJtq0uloUjyO/NpFMghkGVZ5aFYRJoks8h/rMfoerhh8Af\n2l/yvXfCG3xTSzOub2rC73V1okEUcWOZNBR3kWfQDERWVfES24/qdUUklnvff3KAzhJc3+wsWzf5\nZfMVJ+d0b9P5Ci758wjEagMAjaSzouwSK4JnYAzD+Y+H6jU0X5lH+3XHn/XLMjyW1l8OgCrPB4af\n97wva7kZPbA5iQ52FpVAu84XZqq0cdTpiLO7Pm4/zknjGErtmPV3i4pDTmU154nXXBAYBqoefhBV\njzwEKAoYqQiDEBiCCEMMBX6FqKdmm/IKFgcnoYaysDh27BiWLaOEor29HQMDA/Z76XQaWV83vWKx\niLhvWnu+oGUI4j1hfDy2HOmR53GpXEBvfTXkaBIXT3wIkw3bYEBHSKFeXY2hyk1v/X1I5DYhmXeq\n4fm4DiXDQJc48DwlR2lNQ0e+CmcccQoVG5kY+g26nDeTfTgUm8B6owp8mSnwlEvhDaLZccVM0DAt\nHDlSi9+wn0CKOHnGx1KbUQjT5YRj9eB5HjGxGes6bixZnsBHgSKQuelG1Fvr1EgJjF8Q0w3Do0D3\nF4r4+uEjmAnVRh8665djo3YYh+UQojiAKQCJrAFBKsKITX+8BY2FxGl2JNxY9kDZ/ecGy7LgeR4k\nQ28komtAsiKXxt17D0P+3VsRURQ88ebruFWTPMvtNNtYZzQNYdO6UhsKlfy2rKbBQIdoZCGRGN7K\nJz3v78hm8ec7d+Gm1hbbaR4VhJLlsGbXQSORpOtt7pfw5tfBZKjqLh49DKxe5/ke10gbewgJHTzP\n29s9n0jyPD61gv6Pb+5oL3mfM4v+qqZJSUnyPKYUBd/s6cFfrA5ho9KAtKu5SEjjkOcUtEajzvrr\nZoMRkcV0m7QQ2zwbcBwHhiXgeQ4MD+iKU/QYbQDSpeMdEBDPutauBKi2Mnd9xdrukEj9sqOZPdg3\n+IznM4ahgWENcGz5Y5Mp0rqMqmjzrPajdby5eWyEwbjqA7j01LTr8U4f74XY3tkgwTR6nhfViVlv\n92RhwvNcUicQjpb+d6fDnLbbNYMgmlY0IxIBL4qA7szKGoJoR3XyugZmhu1ZjP/2Yh3vCqbHaXc0\nJElCKOSMPgkh0DQNLMvi7bffxgsvvOD5/GWXXYYrrrhiQdalwOs4iAIYQ8SVpie2IZbEp0fPBQAM\nsHeiOnuB/XmLQAOAyjq+6EQbg44LROx8TAKriaivp15VY2AQHxhY6/lNqT+Ethy9cb1ae8xcLoP6\n+lKl57WhYTw/PGI/r+5aAkyOgv/oxwGOhz7QB+25p3H3jo24/4wtIIYOgzAe8gwAo+GcHU3X+L4P\ngAvFUA6RcBWQASLJaOA6uXEolYY0jf2kHEQUEK9txbX6OHb1PoOUeTpU7zyI2Gv/jdA//GvZ7xYB\nCLqXyuuGCjZUwOGh32Jj9/vBMqUXV0PXoXz/AYRr68EsWwEFwKjozAwohMGKfAbiqtUwUpNY+th3\nQBqaILr2QQfDANiDPICdZrRgR21tyX5SNDoIrBcN9AWIPPebg4xHe/twq+mvrkskSpajHT0MBYBQ\nV49YfT3UhkaogE2eASDS0opEwHGq/wNKzU+kE918gPM1ygmxLO5ZvQqb6uvwt2++bSv5BY5DQ0M1\njsD5j0U0HnlOwdKmRtSbzWr6SQGAjuq6KtTUL5DBex5QXV0NTsxDVqgKDQB1bXEMghKF6iUMJo/Q\n/47AO9eMefv9IUq0jo2/Zr92+5UP4PFX/gR5aRLxqhBi4brA745MHcTg1DYABMvaNyEZm70KXV1d\nfULr7YaWnoSlR7Lp1IzXo8XAfG7v8SCvDs56v4wVvYk+rFg87n06m+02JsdhUeiqXAYqADaRRH19\nPQxNs99jl3QDhEDfuwtVoRBYc52MbAaIxspew7Q9O6E8/BC4y64C955rjms75orFPt4VeHHaEWhR\nFCG5RqaGYYA1vbVnnXUWVq70Ng0pFosYHS31Ts4HNAkAIlDkYJtEIr8RYcUpotGJM6WvMY5S3npN\nFrkxBkAIuSkZo6OUXE1ks6gn3gtUqtfdTIQqLFlJKtlGzTDw+VeckPn2SBidF56HzCVXAFbhW2ML\nwof2I3n4IJJaHAKbgwSvessZRRR4Sp4FLorJTAHIFEqOg7OR9JQcHR9ElJl+v79ozh5cUl+Hc2pq\n8JV9AfIagOWxGA74Zhbakuejd4y2qLZmsGOyABQLGB0YQDl5MQ7YFg4Lmq7gG0//LgAgk8lgXftN\ngKKAHeyH1t4JEAIyMYbY9i0AgBxoo/KCy19+Rz8ltWOZDEgujxgALZ/zHBc9T8ndrglnOpkNOD+z\nRaq2fGHlRvzpjoOB22Hh0UOH6TYUCiXLEQb7IQIo8jxSo6PgdAP+ksdcOg15hv9H2WO9gOA4DtXV\n1Wjy+ea7o1FcU1MNaBrqeR5WRUEhn0c2OQ7AKYwNazxgAGo6g1GzA2MxLwJgkclNQRstP3hbjG0G\nnO2enJwEWA6WisyGDOiJScQ7BYTqDNRvUjD5LbqtUtG5ZpworO3WZPq7BZnaozrrLkAIrQhxSeSl\nSRwd2IOGRGmHUwA4NEQTHtprz4ZSEDBamPn6695udZ4KwdjhYedsyGYw2t8PlJnReKeP90Js72yx\nsesj2NLzAwDAnmPPYWP7x8Gxpc2c/BgY8faOHx7rRZyb2711LtvNDA/C0pnzhw5AAKCIIaTN65V1\np5JlCYYYAg8gPToKdXQU7JGDiDz2PchnngXp6hs8yxVFEeqBvYg88m0AgPrMk5hcf9actmOumGm7\nT8bB3emA045Ad3R0YN++fVi3bh16e3vR2OhMSSUSCSQS3ozIgYEBKNMkO5wIKHEzoCsMDBAQGBBd\nfuSY5Is3I45vUOEcEqVDAXhKoNU8sdc3qygosOXXXQgRQKeFZP5tfG3cO912a2srVAP0puz6rPq+\nG8Bk0uAPfBEhlBJoDTwM0FJHkUvYv8NxXOB+ZQm9EL9+8Fs4Ovo6EuEWJCPtePXAf+LKNX/taSPc\na8bSdUciuKSmGs8mEtiZpuroH3YvxSO9fbi7qxMX1NZgfyaLv9y5C2fotMV4c3IDBid2e347ptCb\noz7YD625tXSHmb7NmFx+6nk0vR+KoiDxvW+BGx1B5uYPQ+nqBudqRhP6X+q7v91Q8F3C44+OHcSZ\nGUo0FFW1q7eIJHn2UVBeR4whns/ougpZzYKAQb3ga0Nu9NnRfX4IQMnx4M2CGiUchaIoMASxZB2M\nYmHG/0e5Y/1O4PyaatzS2orH+mkhUYxj7XX5SHsr3jZTcNKSBFVVoFZJ4FL0HOzO1WBJMYnD98fQ\ncVMWoVodumlZ0qBAUaapHVjEbQYAVVVBXFF/bEiHqitoeS9dJ81lQSZC6f//eGFtN896Z5mqI0uh\nKAqSkQ5M5I5gNHUQ1eHuwGXkJbMTqFA/5/VSVXXetsWfd66Pj0KrC47gW6zjPZ/bO1uc2f4RnNn+\nEfz4rU8gXRjERKbXrh+ZDun8kOd5rjhx3Os+m+3mXK25he10UKaFIyXfMxQFWjQOHoBeyENRFIhv\nUPFI2PY2sld61WWO40AO7PWuTyYdmBI131iM411BeZx2RYSrVq0Cx3G477778Mtf/hJXX331oq0L\nIU4TAw3URyAa5TNPOc05XDpTxMEln8bS2yhh5ML0Zq4WCKQJBkcej+Hc7csRU+kP+JtFhOp0PHDN\nZQAQaIM4VvBWygsBGbsAYIQj0BqakEQNRMNRea9Wv0LfJyx0070cC82c/xrmqV83XRjA/qFn8NaR\nB/D8rr9DXp7AW0cesj/35OAQnhqitpd6Mz2CdxU8XlZXi2+dtREXmBnKK+IxPHLuRnTpr4EhHDhG\n9OTLVhVF1BWo3hR9/unAbnvWwGH9WGPpeyYYwoFJTYEbpdYXbqAPwq5tSPzw2yWfvTUexb0b1uN3\n6FQE1AbT+iIIMFgWRJE9+bNRji35w9b6FLGianqT+TjiPA/BNf14abK8yigEFRGaNyAjSslQUA73\nyZ6PyxCCm1udIsCoS5FeGo3irk46w5Mz00ieX7sbWZb6Xi6a6MB1gyth6ASTuyhxtooIT8YEDj88\n+c6h0qK9tmtyiLSoqD93/htIhHnvVLOlUFZHaT2GVT8QBCvVRuQWpvZktiC+c5tJlTbiOZ1hNVbR\nZpmokTULQ63GOAvd0ZAEdHZ1Z0Cnb7kdWnUNipvOgyHQ89MqHCUzNXrhfPUiYwszS13ByY3TjkAz\nDIMbbrgB99xzD+65555Fn/qwZr5UQsmJwAQonwDqlLcR9ymfy6LN4M2OY4QHCEv9jlN7BciTLJqm\nqpBU6HKjbd5pn7oNCkKmQhWUAz3ou/iIZQi0hUua70KVq4I5hBx4s1hRA13v2VTUr227GS3JjYHv\nRc0WwYque9ox15kXvynZ+f2gphqqRhXrkBAHIcQTq3RpXyeIGQnIjY0g9HZpyol1Q63Plx/kMITz\nRCERSfK0wvagpg6t4TByV98Iae16ZG+8xfwSgVZD/aGR377oWjbBGtcMyZ2dHQj7LAqSST5CfBUI\nIZ5oujvP/zw+v2J54KqwKPX5MZN0FkKrMosQ+VLlnZTJ1j6Z4D53/fvLItQ5syhzzJDwQCe19sRV\nZ1raatttqHQ/zUeL8oWGm0BbA2w3om0q2q/L2deQ+URE8Db/4RgqEFjXgIJcPtXCIlYhfm7dC+cL\n7MgQ2LGRknM79tRPAmMbT1dwDP1/qNrsCLTVlbLGHERZg/2FAlMsjUu0xAAAUNs6kLrr01C6V9jW\nHHvQZMxUW+M9D5jc8afWVHDq4rQj0CcbrAxalYShIgS+eF3JZ5bdkcKS+P/aiRcAcMPBFVgXv9x+\nTojTPEGacEhCSOcAGBCSXpLMCgZCJnmQdb0kVmrIR6DZGYrBjCWrsDK+3vMaB3oDUk0CPZv2rVGx\nDleu/WLgezxLiWvG5wGrM0lik1kcWlUmgs7KLA2Zykln3QUQSRiX9XZi+VSt57P8sdI0D+viGlad\n5XOsV5VlFAWJH33PeZ5Nl41M0qopydBr65B73w2eFrO6WbQW2vwG4BrgfKzDsWBsSpYWfllRUaJJ\nPqpdpLc2HMKKeGkB503NzdiQrAIMA8KubVRN0TSwk+MwAGi1ZlFNQAX4qUCgGde5y/jO46i5TTmz\naUZWVTEUKr0Z5gc5KFkC3STQzClAoOejKcrxIiwEK9DWrI+s5jCc2oX9voQOwGkVLS4CgeaOHkbV\n9+9H/LHvgZizcKp5/hNNBdff+46v08kKjqXXtdlmOlvXpqoITd5YcAXatOC4m6aU60LoV6ChT/9/\nIb4ZWlIh0KclKgR6kcGZnDi/chMmOCcO7KVlBwDGQKhBBSsAmd/9sK1AKxBxiF8J1Re3xpoqU2HI\nS3SIYIARqEJtf1akKi1HaJuN50dG8aM+6hPVDANH817/34xpF4Sgu92JJIooPKIq/c5KnA2GcDij\n/YMz7A0Kjgn2GFvtgN0Euobn7WYid3d14L0N9fi/a9cEft/qhiaa3uBEuBUfvuhRbJDPKN0cqXT6\nzyLQxKXWJkLe/GF94LDnOZPNUCtGAIxwJPB1AJDWbnB+1+XFXBZzCLC/mUhenrSLtkI8Jddu9TXE\nsuiMRvGHvs6Gd3V1gCEE4s6tiD37c8Qf/Q7YyQkQXYdeVW0XVBqnqALtBgM/gfYq0BlVgU4M6Lx3\nwCmNszj2ZOyUsnDwVS4CHWDhWEgInHegZqmVNoHW8vjF9j/HqwfvxXjWW+gq2RaOd55A80fpwJkp\nFsCmqEpePOs8yN209iLy62cqKrSJuRNoelyrwlQE6Bl7CenC4MKsHAB2nNoqlC7Ha28JE34Y1rVU\nkRB6/WXw/f6GZV74235XFOjTExUCvciwLByF5Rswsup6AMBPm/ZgX80Ilt6SQdvVZhZvLI5oPU0I\n2c28B//cvQH3573kpdx1nREMEAKEm1XPawAgmt7X/z58BN/v7UN/oYAjuRwKmo4mVwRYU2jmKutL\n6+rw0fY2/Ne+rfjUtrNRJ9FlL+XPxUcvfAzJyNwyP/1QNDrqz5hd+FrDIXz1zPW2qlgniviD7qVo\nC/LqolSBBswYw2pnujn7PnoMSEBFPVMonRLs7JEgGg6xlH0tvrmhAXDDpTeJ9K130GmDMlBWrIaW\nSJq/6yyTJQT/tn4d/nHtakRcivBwahceff12vLTv38xtpATar7gCwHsa6nF5fWmEmLhzK/2OVAQx\npz91F2EP6gTp94me7GB8uyPK0n2YVVUYhmGfW0LApIGaYwCd0GLeU+DKKSwigSaEoCbqEBeLbPEs\nHTQqrg52eZedY3PPdzEwRdNqwsL8RuvNBsTVvpudoF1qjUgU2WvyEzKiAAAgAElEQVRuhMFx4MZH\nK2qjCZ61LBwze+hVTYKqFcAQDo1Va8EQ+r97/dA3Fmz9uBFatCgvX22/ZkSCI1QN28IhI/LqC4Gf\nAWhzKebIQVvUkFbRmNgKgT49cQrcBt7dsCwcmspC16jSNykUIOs6+LgBdzpQNNwEA0APQyNznpzy\nth2VJ4Nzaa3fiHc5HmGrh0Gt4CXGx/IFvDxGvWpnVCXwzY0b8I9rV6O1DCl1gyEEH2xrxSqTpYRM\n60GRFwKzkadDrat73trW9wMAxjMHkcr32wp0SyhUtmNgEGRTgQ750inc1gmryt6vQDMTY55uZFf1\nLEVdIYpz+5twx/Z1aKs5BwBwONyPLB+syhbv/CTS778NqY/+HtTWmQcTehUlEMQ3G7A0GvV4oQFg\nz8CTAADDbHcTMtU7P2G0EFQU6vFum6q5R3UOIONMLntKKXL+AYXV6rsnn8eErEA2DPCEgJuGcDLc\ntGOfkwahOlcjkAAP9ELj4pVfcH7fp0AXFKcgz12LsL33h/bjZGTmZIf5BnElHLATtJ24HokCgmjX\nJbhz0E9nWLac2SjQln0jxCcQFqpx/cZ/BwCMZw8tyLqxo8NgJydgcDyUJc69RI8Ez/o5Fo7ptyV5\n/70QH34IfB9VqNUWqqZXCPT/z957h8lxXme+71ehq/PkPIM0yJEASJCgGMAgMYpiEEWRkhW4kkWt\nVvKu7XXY62ut7OfaXtvyeu91VLCtRAWSoMQgkhIpZoIJIAEQBIicB2EwoWN1xftH5e7qnu6Z6enu\nme/3PHgwXfnrUHXq1HveMzehAXSNsQJkLefoK2VGtV0B3IRivRBdNnEMvLriYtX0nBkDxRe5Lg5m\ngJCviT2RzeKlYePCcX1nJzqDQkGwNhGaKS2Jmdmcv5E1PDF0BloFgdZ1q76OTYt+G/dt/ikG2ozG\nMqncWTy6/Us4lTAKCGNcZUG5ddEOCd7OfEqPcRLUhKCt9yU50Q4MuZPH0fy9f0XkBaft+9rhLnxm\nz1pElABisoCL5t1rzzvcNIr01R+2L7gWencvlPmLoHZ6G80UQwsaJ/v41gcnDFKb8rL7Vgb6lm5j\nX9d0egs47+jtgcAwuKuv157mlppY0gw/2QZgBBVaKAwmm/EE3vVOS56/d7Pr9dd27gIAxPK03gvu\n8mo1G6GAEDBqIvpvTqF5RQ6RgZn1CgYAwSXjsDLQATMDbd3MAobm+czYbhw8+5w9LcBFKr7pnhZ8\nWjlbulnrvMakpqDdlSQwiXEE9uxE9PGHgRn2cJ5OrMJQtYwiQttZxTwvtYTng2UCEOUxSEqm1KqT\nIrB/LwAgt2ot9GAQuZVrIQ0uLSqbs85zfk8Zi6HG4lA6DQmfn+SPMvtpACXf7MbOQOcINNkIoCVG\nxZgsQ9N1T8aso309AseftD81DYCoabazQPMKCcNvB+3tWDDmPpiAEQzoKsCY2s+1zc2eboPbLoxg\nVJbRyvNYEi3uNlEKLW6cJBdk0ni5FRjVge8ePYa2QMC2lZuIcKAFK/uMVt886zxPH0UP9o+eBdBS\nEOhMREo0bO+aI16nE2n5KqQ0FfL8hQDHQec4EEUxLqZ8AMLOtz3Lq80tYMe8LgLNIVfDG5ZBbv0l\nCBw5aGexAPhKIEqhJoext/U8BsdawSTGoTU1Fyyj6SrOJ/ZBUb0nfqsAa11zE/5l/Tr0RL03St3B\nIH5wyUbwViZaUTzZN0vCgYB/EKPzPNTWdgSOHAR35jQk17EF3t8FLRKFMn+R77q14I+XLcW2kRF8\npMtrpej+fWXMm9YmnkeoS4V4nkN8qQShRbMdbgDHkaMRiPSqiPQW3ozPBAGXDZ2VgebYEAgY+0kJ\nAOw7/SQupLxNNm696H/PzEHmQXwCWt0KoM0nVZPOQOs64g//0HD4ML9rwvu7AEIQ2L8XyY9+vGij\nlnqkkgx0SjTkFJGAUaxNCINYsAdjmWNIZE+jPba41OoVY1kOKt1GgiCd1wwlH92UK1by2cqLltjr\n+Un+KLMfmoGuMVYGWk4x0M1zN8cbhXwJ18lc13WQplZsPLXas37atQxhAMIXPqp1X/CFFg3BdmeZ\nazo78PUVy/G7Swy94lFTLrCuuWnSbZhzq40CuJ6cN6jLd88oF44x5CMaGLzE3o+9OaPCv5jbRjGs\nALop0uudQQikVeugR40LpOWaYfmIsmPepjJKd6HVIK/oWNN+CwAgG2IAQpC99EMVHV8+z/cdxFOL\nDuKZBQftgph89p1+Ak/t+kPsOfVzz3QrAw0AXcGgr4sK75Jx5GfVAmajgGIZaJ3j7YDerQllkglE\nn3kc8a0/LjW0GWdTawt+Z/GgZ8zF6A4G0X6xiHm3pdB9pfEddlvCMQ0UQNcSK2gGYGteCCHgOa8c\nLD94BoB4qLdg2kxA8ptsMIx94zvVDDQ3dArc2SE7eLa2FXn2l+CPH0HgcOH7UM9UUkR4IW1INVqj\nji7e6guQkYZ91yn7OE4eR/zH/w72/Fl7GpMwAmgtXph08MPOQGfSBfMC772LyNOPFXjei+svKVv6\nQZmd0Ax0jbEC6OQhJ1AJBxhAA0YlCc08j5eHh/F3Bw5hS3s7ws1eu7VMntQjP/sMlL7gE0JwUXMT\nTme9j6CunYI/ttrdi7HPfgnLuACwZ69zHJPcnnXBlRA27hJMWopkR/3YcfQHODFieDs3R3qBEkk5\nTQiCSafA5ESokSjYUW8ALS1bCaWnD0p3L6JPbgWbGAcRRbuYUDLfb6V/Pka+9kfgTh6DHomh0tzS\nIfYwoAEHWkfw0V/8DNKS5UjddLsnk/3+6cd81w1WWIDF5128+RNHARQPoMHz0MzHoUzWuegQ9wVI\n1xtCLHzfQD8ePHHSft0TFMBwQKjT+ZIQ15myFsqCRsR9A241SAIMdw1JKQxUZhxdR/iFX0GLxCBu\nutyYlneTn7jvfvtvS8qR78BQLsxIYaDovjHWK0wI1Bo7gC6jiHA0ZbibtEadp1KWnEdWy5dN+BH9\nxc/ASDlEn9iK8c9/GSSdAj9kOEpZT0MnQheKF8lHf/0kAFejKxMtHAXMG3Iq4ZibNNYvdhZiSTjc\nRIMskAFGJBktARl/d8C4e39heBjo9GY/LfstC/7ScaRfjWOUF9EpRYruI592wRsozS9SbFEuWms7\nWgF8/+KN+N6x43ju/HlIE1nhFYFnXQG0i5ZiwZ0P7uKkpkgv0oni7VDdj+XYC+cLslJaKAx5kdGQ\nRA+GgMQ4iJhBwAygc5xrnCw7aSkDywRs6z7AyAoLA+8gt+5ie1qxi1ckUOiyUYrAwX2+0/Uij5R1\njrP1hO4ix9CrLzgLqUpBx6565O7+Prw7No73zXbrlp+4G4alGejJ8PFL/g2Smra71gHAos4t2Hm8\ntk8oAnt3I/q0c/MpXrIZIATEpYHWWQ5qh9N11Pm+Ty7498tcBw5+YP9NlNpIbSYLX4GEIy0Zjiax\noPN+Wh765QTgpWDM7C87NoLQK8/bQS3gPDWYiKKJAheWq4eNeW7UGcZ4qqAoQIWyQkpjQyUcNcYv\nQRcPGhnG87mcp7uem/mKUeSVVr0ZE7kvg6+v+A3eaT5tT2PLqMAPMAzirh9/mKtMr1uMGM/ZXrsT\nekkXgWdDWD//U1jQc6dnerkZaEXzumJMaI9lPZaTJfBHCqvE3Y1R9KBxEWBEEYJuHE+OnZ4LIesy\nG97WcwK/GTiC8G+eBnfsMBLZIfz0jc/Y1e35uAOWcijm51xSwmFloE29NDM+hsAxxwe7kXSBi116\n/5XxwvfOm4GmAXS5RIOdduc5iwHTsaYYH1n959U8JEDXPcEz4MiQ3Bro5B2f9Cwz5Qz0RNIPnwLG\nesaS6JRXRGi5cDjnXqu2ZaoZaJ11fpyht14DZz49Ey+62BNMl6SMwFfYu9s7gRCAEEfyR2Uccw4a\nQNeYaF/+xVhHZ9gIWh45dRqvXRgpWOf6TBLzWg0pRyYvayFqKjSiIxZzPlquzC5klic0MHHnwUqw\nLNMmm4EGgHXz7kVby2bPNEbx1wW7GRrbhR++6g28J9J2W0Ejf/QQwq8+Xzjf9bhPM+39SDaLgGqc\nhA8IR+2q86nAuhrKbOs7iXe7zuBI0xiiTz6KV/b/b7s1bj6T0Y9aWfbEnffZTSMAo1jQjbTY8CLP\nrd0APezNQJO8wKKRLii39fSgmedxRVubr2Wju/NgIxUR1iNux5j87+qmRV9Eb8v6qu6fGb1QME3Y\nuxvxH33HLvodu/8rUAa8NnrVyEC7yX/SVe+Uo4FWNAnHhl+zz1WCK4C2MtBTDqDz5Bf8aUOOJc9b\nMOltZi+7EmqsPPcpWwdNZRxzDhpA1xiGB+Z/zCnCIhzQaTYtGZYkPHTqVME6nctWIGxe5FN5Geis\nqYlWQy7LujIDaBbV0asK0xBAA0BC9o711zu/gqR4tsjSBi/s/auK96ObcpbgO28VmV+YgSZiFoLm\nZO0/GPplxfvNh/XpyHikaRTnhDGMZ/xbCi/vuQU3r/ubivdlPbrWWtuQueIaZwbjfRKRuvkOjH32\nAciLlhRooPMzc42UgW4TAvjuxvX4vaX+bgBy2jlVujt6UirHkmQBQFd8ddF5VUHXEdz9TsHk8CvP\ngzvnnEv82tZ7MtCT8D5n0rM0gC6SgU5kh/CTbffi+b1/4azjOqfxFWioS6EXyTJrRZqmFEPud5yU\nlM5uz3m+5P6pE8echQp26gC3xILhdHT5dP3jCIFinrRXx+PYPmZUGSfl/ADa2JYWcnXUCpYXuHLF\num5MEScDPfnAI60oeHzI6Og3T3sHK7TnQQDsObkVmq5g7cA9dlW3RU5OIqd4M8GbBr8w4b50foKu\ni66LqxVAR174FaLtDLDAmJ4Uz+DlD76J3pYNGOy8xmcjE+MXQO/sPIudnWeBIoYmy3tv9TwmLRvz\n4q3zPHRX5qWguIZloZlPP7R4M3RCjAYzilzQ8KWRMtCAf9dGCyXlXKSl8emRN81l7tj4L8hII2gK\nD2A8ewLnEkaxMSHVfW/Dzz+D4M7tEy6n+2n3eR46a1pcynLFlnNMykiUaEIQjCtbqbMsiKp69NeN\nwEQ2dqPpIyWz05PJQPO7dkDt6wfanHM9Y7olacGQLScDHPvBckne9SmE3ngFzNgI5AWDEHbtAIYN\ni1elrQOcq+AzffX1zn4sGV82U6o2nTILoQF0HeAu8mM4YMDnEfK1HR1QdB2dQgAr4jEcTBtZv/G8\nAFq0XDlcQXO5Eg6OVOeBxFQlHKqu49NvORe9AX03gjDGv2/IqJAeSR/BrRf9HTRdBXQdDMPh5Ehh\nBnnd/Lsn3J9f4ZwO+ObntaArmzasgh9gILMaDp59FgBw6NzzFQfQJy68CULIpBpJ2Bk8VUVg3x7I\n8xdCdxfS5GfOJAlMKuF0HjQDh7HPPgD+2GG7WNJ/Z4YXNHfhPKKPP4zA0cOe2bM1IxMf9NeLU8qn\nKdyPprDRwOjmdX+D/3j5VgAAqdJTMItygmcA/ppYQqAHgyDpFEhOLFpg64uqgmTS0AnB+Ge/hOCO\nNxF6exsAQzJG1Kx9E9so8HkZ6HRuGBnpAjpipsxrAhkbX2ERIZMYR/DpxyADwB/8T2NiLgeiyNBZ\nFpmrrkP0V0/Yy2sVBtBgGGQ3X+Ws70kkBDH2mS+BHRsBt2otcqJzzFrEyHTTFu9zDyrhqAPcBUpg\ndEQ4DoMR748/xnP46uJFuGfAuOg0mSf4RF7WwpJwBAQgvlhCbFDybr8E06l7djPVANrtdR1EGu36\nsYJlLiQPAgCe2vmHeOjNz0PTFGRlo9lJ2DTvv3jh58van28AXaSaW3cF0AQEV59YULBMJZ22JCWN\n597/Mzy75xuT0lFbdmHBHW8i+qvHEX/kR/Y8bWQYkX/6WwS3v25Pi//se2j+3r+CaBp0QhzP29Y2\n5NZfMqENndVVMT94BhovA12KpuXGWJqWSYgubNzucfVKW9S4UetuXlvjIzEywsWaHmnmY307g1ym\nlINJp0BgZEX1SBTZK6+156ntZvfTRstAM94M9KPbv4wn3/09jKWNNtc5s9vkQOulaIksxKWDD+St\nX1kRoafGQjOuc/wpY19qZ7en4FlnWYCfmgOQ28FDFwRobe2QB5cWnBOtADry/K/Q9N1/AEmnjILq\nvbsnJfWhNA40A10HuH+PlvHCN1Yuxz8fPoJXzSLCSN4JPW6eHKwM9OF0Gj85cdLWGwdZFj1bKivO\naBcCOJSefn9W65gm68LhXq/Y+SjARXEhdRjnk4YdW0IcsgPXpd03YGnPTQjyZRaF5D2+FddthNbU\njPBLzxUum/e0IKgU/qROjb6NhR1XFUz3Yzi53/47kfXq3wkYNIkBjAWLZ2yEY0ehtneCP2L4OrMj\nTsGU+soLYNJphF96DuLGywAA3HmnCyV4vmLfZrWlsLOkFo6AyaRnVQa663IRzcslCG1aI1hbNxw3\nr/tryGpmcvKjcikzmCnVfMPdZEnY/Q5Cr72IzJaPABdtLLlfq4DQHZQlPvEZcCeOQo9EwZ883rAa\naFXLQVZFuxvqhfQhNEfm2fK5jvgyXDfwfxes72SgsxjLnMCJC29gZd/Hij55cxfpkUwGYFiEtr0E\nwCwYdCU+fCU4FeLJQAeLa/Otz5QoMtjEOIS9uxF6/WUQWUYKgLRizZSPhVKf0AC6zrAssiIch+s7\nO+wAOt9WzurC914iAUnT8NcfHMBZV8ASnYQf5RcWzIekabi9t2eyh+/LVDPQoqtZjF5EZpJTEnj8\nna/Zr48Nv2J7P/NsCOFAS9n7y6+mzlx7I6DIYM8OQVqywjNPyzuxhnwC6G0H/7HsAPrM+O6i85rC\n/fjc7kU4zZ/Hwys+gGa2rmQ0Ao0xvjexnxtj9q0gd2VomPGxgtbgk7no+AUb0tIVCL779qzKQBMG\nng6elOmFZXiwTBWDZwChl3/jeS0NLoXOsBAO7PVML9V8QzfrU4T33rVtzQIf7IFaIoCOPPO4vayV\nrQQApW8ASt8AAh/sMSc0ZgCtqDmMpA7a0y3HjZxsZKAFzj9xYQXQaWkET7zzX6FoOejQsHbgE77L\nM1knIUQyaURef9n2ZlbjzbYbhrHxqQfQlusKgJIFhe7PFAB0hrVvhrjTJ2kAPYuhEo46w+0xG3EF\nwYvyJB1xV7Dz4vlhnMvL9lXa5hoA2gUBf7piOdY2Te+FbKoBtFUYCQBr41E0h+dh8+L/UnKdd445\n0gWu0sp+v0CS45G++Q7IS5Z7JqtdPcitWme/DimF6xKUVxil64522g+WCUAPhtGfiuOzK76D/tZL\n0CT0YsUFo2lKRHL2zSYL5R/EVRAYfeKRghuFcpoJ5JMfhKevv9nO3MymAJrS+IRc0iUASF97A7KX\nX124YInzlBVIcUOup0OlakdyOY9/sCfIs6aZ55vGy0BbEg4RiazTdyCRNYq9rQy0wPm7YbRE5iPI\nNyGRPWnLQM6O7ym6P7eEg2TSEPY5y+qhkEd6Nx0ZaHfWuVSnQj0vgLbqSYyZVMIxm6EZ6DqBDWtQ\nMwwi/Y6+stvS2wFYnBdAt7qaiIxIEqIch6RLKxyrow5wU85Aa04G+qtL1yHO/xPSucK2uMWo1BpL\nXLsB7LkhMJkMMq5qa18YBumP3Aphz04AQFwqzFSUq/HLSBeQKeLtDJgBdDgMjI+CFbO4buWfgjl7\nGqHXv4NgoAmrzvl3H4w89QtIt94J3RUwc+fOIPboTzzL5Xs+l4Pa6rSWF9dtRG7NeqN6HbO3iJAy\nO9ADQcDVhCN528cRefYpZC+7svg65jmZHXN+p6VuFPnTXrtJ3/oKvkEDaNMlSNUkz/l4/5mnoUND\nRjJqUIo1deLYIAZaN+HA2V/b0ySleCFefgDtRg+GvRroaWiLrrnkeflPGj3L5QXQjPvYaAA9q6EB\n9AQEAgGwRQpKpgOGYRAKhbD0bgXJ4wzaVrIgjPFjDYWAf7tsE8Ich7DPifcLixfhOwcPQyIE8QDv\nCaA7ohGEfNw8LAghyGQy4HkeXJXbj8bM45Kh28dkjbscdFOXfWlbG7riRnaT451gkRAGul48OI+E\nm+x9lTXuUAjaXfdBA1BuTla++npwr70E7dP/CYG970FSjGMmYKDpMgICP+GYL2SMi5DAxZBTfNr+\nckEQU28nqAr4cBiMqkJQOVyhXg5ChgGMFqwn7HsPuPRyKMmk7XGgtXd6s2gwMtTlfiY2oRC0llYw\noyNgBuYjFAqBNY+RUxWEQqGKPuvpYia/337UYswAHXcl4w7F4wAhkLd8GHowBG71Rcitvgg8gGK3\nkmykMJvKyhK0IuNmRe/NMxsKFyxHTMkIK0tlv3e1/pwB47PmGAGKlkNG9ja1OnDmV+ZfBN2tSxES\n/MfVEusHXFb+55MfQGMyiAhtBcvyrhsMfsTbDCfQ3Azd5ftMApM4l+WjO7I/PhYDU+zalSev5F2f\nOcdOz++hHj5vSiH0k5gAqUiL4+kiFAohm80CPBAZBMS8ZEYLIYCqGsvkwZu+yolcDorqDSCFIuvY\n6/I8mpubkU6nIVc58xEwuyUmJNk+JnvcZZAwl+MBex1d19EcnoecnMSynpvw7vEHi66vKYy9XtXG\nveFSYN3FAMuiKTRgFzNybAiymkYyNYrmeIfvmMczJ7HrxE8RFboAAF1Nq3H8wjafnbBQAgGwAJTx\nMeSyWQgjFyAAUIQgWJYrqskSvvctkO5eWPkQ3SdrJnd0lf2ZuBE/+XnwRw5CGlwGZLPgCUEAgJbJ\nIJvNVvRZTxcz+f32oxZjBui4S407CK8VZdayIlu/yZww8XELAaEguNZFEZqm+Y47OD7muQlXCClY\njiEMggD0TLrs967WnzNgfNasGUCPpo77LtMRWwaiFf9OCGxhEfKDL38Gn7r8oYKOsUwmbQcs3Gsv\neuZlQaBrGqxQVWOYqX8PddjbyxECucS1yx0i62NOEkPN5abl9zDR593SUn6ND2X6oAF0AxM2M+MZ\nVfVkn4H6knBYeuxhScKYLKO5QqmApYEOulqNE0Lw0fX/B7quAiCIBbvxyv6/h47CTDTPhgumVQXz\n81g//9N479RWLOm6Hm8d/jfIahqyWtzK7tk930BSHLJft0UX+wbQLBOAFjK7oZlV/VZbYrW5BXog\n4DH7z0c/4+gU2cS4/XfiznuhdnR5imYqQQ8GIa1wOsrZTgVUA02pF6ScJ3hOfvSuyW1m5Rrwxw4j\ncMQpmivVwpnJlxr41Bno+dZ4DQTHCsgpwHieY5BFV9OqkutbSQM3iibiQuoQ2mPerqClzid6MOS1\nHlSnoeC3SIfDCVcbdcl7xJm/maTMHLSIsIEJmSeMhCwj43KqmB8OQWDr56MVXCe2r7yzs+L1LReO\nYF5baZbhwbFBcKyAwa5rPcWCN651Wnhbhv8zRW/LRfjI6j/Dwo6r7H27ddCymsWp0e3QdBUZacQT\nPAOGZvDyJV8FAKzqu8OezhDWLtATdr8Dkk4htP0NAIDa3onMh66B3Ntf0bEqHV1Q5i8yunZNkz+b\npfOkGmhKvRB98lH77+THPgF58fISSxdHF4JI3XqnZ1qpwC6/O6dfnYEuCNAJAZEkQG2sXnZB03e+\nmHa5PVqiEROAcKAwAw0YXQzzKXlDnieznG5PbT1Q+hqitjqSQveNECM23k0RpXxoBrqBiZjaq/0p\nI8vRExTwV6tX2ZnpesQd6I9KEnQAJ7NZrI7Hi7ZSFrXCDLQfjKsavrvJyYiSKnVYLAfep13tu8d+\njD2nthZdJ8BGsKjzasxr24wgH8eeU8bFP50bRm7lGoRfehZMOoWQ6zGm2t4JCALSN34Mzf/2j2Uf\nXynLrsliZ9RoBpoyU+RE6CWKlANHD9l/q20dU9sXx0NcfRHYZALcscNGa2934KvrCOzfC+7EUQSO\nHfKs6tu9kBDoQhBEzBodDivtoFdDlvXciNcOGJ7zPBsqKJjucp2H/QgG/M8/loOHm2I35OP3FjbI\nIsr0NDtK3Xw7uKFTUAbml1wucc9nwIyOIP6z74O4voc0Az27oQF0A2NloC13i4WRiN1gpZ75o917\nsKy5CU+fHrKP/YFFC3BDV+HjPMCVgZ7wxsAbgK/ovQ1JcQix4PT6WleCX7vaD8z248UImLZP+Y1f\nUuIZICBA6e4Ff+oEgu+9CwBQm1uhNRsaOHejhtTNdyD41qt2sxTuzk9iPBJD5AfftpdR2/ydO6aC\nZjebyNIqdErVIekUot/+fyGvWA3cOrE0YzJuM/lkPnwLAKD5n//O+J5ns3YWlD98ANFfPuq7XjGr\nSMYMtKJPP4bknfdO+fhmCneGORbswUja6Uh6zYr/gVCgeFMawOlGmI8ojxdM89jDmahNLVC7ews3\nME0ZaGnZKkjLSstQAENCovb0QQ+FPS29Cc1Az2rq5zk/pWLyuxPmW93VE+6s+AepFB47ecpja/f8\nueK2dKKpZwtNoElb0XsrAGBJ14cBAJcO/jauX/X1gmKUmYSzM9AZ8/8sFM17IVjafQPaoo7eL8B5\nP0erFTlnarm1vCYpydtdjQdc77Pa1AS1xalm5zZfCa2nz7Ou2u5/0zIleB46xxlZoAaz5qI0HoHD\nB0B0Hdr7xZsQuZmOANrC+n0xZ536AiZd3Ipton3zxw6XnF9vhAXnBjwe6kNPk9GK/c6Lv4X57ZdP\nuL773MypDD58dBEAQJSLZ6D5z33Jnpb90Bb/7dbovKPlXYNpEmF2QwPoBsbdaIUBcENXZ+0OZgL+\ncvXKkvNLnWIsH2hhggz02nn34Ka1/wuXLf7PlR5e1ciXcBhduryjvXjhf0Is2G2/zg+gP7L6z9Hb\nsgFXLft9ADC0ki60Jm8Fdvr6myGu3QC1q9eQdhRB6eiCtHRF0fmThhBo5mPo/CIqCmXacT+uLyfz\nOI0F1kqvcUMaePJRx5u4hHyAFNE4ZzY7nUrZ4eKFwPWGwDlPvJrC/bh+9TfwiU3fQzzkkxWegKgc\nsBtR+WagzfMes3gpkv/96xj7wlchLfO/rug1kjFqEef90JOX0SgAACAASURBVDkOBKWLTCmNDQ2g\nG5iQ6yTRIQgI17E/5LxwGOua/Fu6AoBeIoR2JBwTaaBZdDWtAsvUj4wlbPqZpnPGRVGUvf7O/a2X\nIMCFEQs5MpNAXueu5sg8fGT1n9lV6eLGy7w7ycvM59asR+a6mwBCIG68FJnNVyF9v3NTkbztbojr\nL0HivvunrXAwH50G0JQZgk2M2X8Ty11GURD76fcQeum5wsfo0/idV3qMol2SSiL2yIOArpcsYHNL\nrNyIl15h/930g28h+PbrvsvVG+4MckdsGViGt8955cIyRpe/wbEWhGUrgE54A09NA1Fk4yoREIyb\n9Fjh9SRx96ehtrYhfcudBfNmAndTFc30paY66NlL/UZclIrQGuAxUYtfAY1JtkT1uSXhyHfhaASi\nQUMikRKNbgE589FkkG9Cd9MaXLzwfgBAR8xxBcjPQOej9M+DGov7tusugOMhXnYleNejY3lwKeTB\npRWNo1I00xKPZGkATfHCjI0axauTtAkr2J6rqQYzPgbEmsCfOAr+9Enwp08WtPCeTpQeJ9PKDZ9D\n69//BaQFiwqWG/+t3wYzegFqZ3fBPAAFQX1g326IF1/mv2ydceOav8Ro5ij6WjZOav2b1/01jp95\nCVdsP4kMZ9x8jCUPI/Sv/wvSnZ+H0j/PeeoWEEpK8pT++Rj/7AOTOo7pQOnpA8zaFD0YBBI0gJ7N\n0Az0LEErKYKoD1pK6P/G5OKPPbOmhCNUR9Z85WJJM5LiGQCwOwz2tmzAlhV/hGjQkFh0xh0phdUi\ntxRK7wAAQI2XLtKpFZYWkEnTAJriwO/fi+Z//yeEXv7N9GxQ1z0dNYUXnwVUtahjg7hm/fTs19p9\nNA41z8kmcLRQx6y2d0BeUto6Tx5YYP/NZIr7xtcb3c1rsKL3o5OuNWmLDmJjy61gdQYxWUC/1AUF\nMo7GxxB+xfieWNloXRCm7birgbRqHTIf2oLEJz5jJxH4E/5NZiiNT+NFJBQPVnFed3BmvY4ng18D\nlUtajAAwrShQi2TRc2YGWmjEDLTZKCCVM5wwLG2fWzsIGI4bN679K9y87m/L2m5my4chbtiE5J2f\nnMajnT50s+ELyTZOIECpLvzBfYg9adg3hna8MS3bZEZHPL677LkzEN7f5VvIN/b5LyNz/c3Tsl83\nifvu952umPUHcl7hbjFSt9yBxD2fBQBDT90ATxWnC9bVva991AjE0wEJY8o5iPK4ncWdbLOnGYMQ\niJs+BKVvALnVFwEAuDP+TWYojQ+VcDQ431i5HD87eQqfn1/ap7Ie8Augu4NBRDkOKUVBSlHQ5LOM\nVUQ4kQa6HrHkGLJiXACsDHS+RR3g9a6eCD0cQebqD0/DEVYHdxHh3AkDKKWI/OaZad8mk04WTGNH\nhgsamACAFpt+z3PACOrEz38ZwX//Z890ccMm6MGg/bSonO0ooTA0QQCTy4E7dRxKf/2f16cDdtSR\n4YTNQsJz4TRebHsJ4R3v4b7u/wkA0EMhv9XrEnnpCoy3fKGo7p3S+DReRELxsDgaxf9Yvgw9ofrP\nQLNM4SM+gWEQN4sfh4p4Zto2dnXcIKYYnNmJUNGMR8o5s4hQ4IoXVM4G9LCpgaZFhBQT99MIneOm\nJcNKsmZm0i0fUFUEPtjjWU7p6CzoVjetBAsDO50PQB5cVnHWlDHlJ/GHfjgth9YIuNtfhxTjerC3\n1bA2zUgjYKzPOVjnGeg81I6u+s+aUyYNDaApM8b8cOGJJMiyUMwL6R+/977velm7lXfjfV0tPbOq\n5aDrmquIcHYH0E4Gmko4KDCCZVfATBQFwTdfnfJmGTMoV5Y7zS64E8dAXPtSunqQ/Pinp7yvUvhm\nRuvYFanecGegQ6YTh6cvllmM3EgZaMrsp/EiEkrD0h8K4S9WrcQ31zpSBQbAOVfBj5LXjlfXdbuV\n90Q+0PUIIYxt06SoOYhmi1qBn92P9aiNHcWDqnqCWgAIv/Yioo8/DO740Ulv1tLGak0t4O7+FACA\nGzEyl1o0BrmnD6lb74LukyGeVnyK2ybbsCVldjmcS7CuDLQl4XATeOlpAA2ggabMKWgATZlRVsRj\nWOTq1pRQFFze1mq/Pp/XJOTnp4cAGFIPtoYdBacCZwXQWs7OQAuzPQMdohIOioPVhlkLeAPNwMEP\nEH/kR+COH5nUdq0MtB4KgYS99o/ZjZch+cnPGZZ51YYUXkr1STZskVatcyQpJew9ZwskJxq1EmbG\nPiIXvm851nBpohloSj1BA2hKTfiT1auwKBLGrd3d+NLCBfb0s6KTjdZ0Hc+cNdwrNrbUp11bOXCs\nETTIqujSQM/yDLRgaL8ZMQvW9EWlzF2s1srFbMjijzwI9uxQ5dvNOu4M+QF0qS6c1UC86GLvhMm2\nDCfEzrTOBRcbq/Oi1Ra9ORe0G6pYiJwRQGut7aBQ6gUaQFNqwhWdHfjm2jVoEwKI8zyu7TBOjG45\nxy9OD+Gs+fr+BnAZKQbHmIWEquiScMzuDLRb/xl47OEaHgilHrAbYfDFPc75o4cq2qawaweEfe8B\nAPRYHMjLNCvdPX6rVY3MNTdg5Cu/b7/WS4x1IjRTcsLMgSYc3JnTAAytOgAQEAxI3oYzWU6BFgpD\nXTA448dHoRSDBtCUuiBqBlxpxWmosj/leLm2CZO/GNUaKwM9mjoGXVfBMcGymqXMKvK07ZQ5hmIE\n0DrPI13Eizn82otgLgyXvUl3EaI6MB9MewfklWsAAHLvgNHyeaYJCEjedjfSV38YWtPkn5rZGeg5\nUITLnjUDaJdfdoxt8Szz8LL3Mf5bX5y27pUUynRAv42UuiBiBtAZl+ZvOGdcdP985QrfdRoFKwO9\n48iDAICOWHXbaNcjlgaWMjchkinh4APIrVmP3LJVvstV1HabNW+6r/kIYDZZEm+5E+P3fh6pj909\ntQOeAvLgUuQ2bJrSNrQ5VITLJA1Zm9bUgtQNt0FtbUNgsLAt+AX9nO/6mq5iJHUY+hxqPEOpD2gA\nTakLrI6KacUJoC05R28DeFyXwspADycPAgBW9t1ey8OpCUSiAfRcxrqBspwp1M5u/+V8GqMU3aZk\nnB+kxa4W2YRA7e6tvutGldGjUQD+jWJmG9ZNghaOQFq5BuOffQB8rKNguXOJvb7r7zn5KB5752v4\nYOipqh4nhZLPrA+g9+7di4cfdjSYJ06cwLe//W1897vfxQsvvFC7A6N4iHBGAJ1RFVzISXjw+Ekk\nFAU8Ib4dDBsJy4XDoiWyoDYHUkOIS9tez5BsBlDkWh/GrCP69C88r8UNm5B2ddKU++cBAIisoCx0\n3S6wm43WZlrEKDJmUrM/gCaWx7OrT0A44DgzbRS2ADAaqvix/eh/AABeP/RP1TlACqUIszqAfuqp\np/Dss896Hu088cQTuOuuu3D//ffj5MmTGBqqvPKbMv1YGeiMquLP9u7DQ6dOAQCWx2JgGtS+zoJj\nnWwYywiICHOvktzKFtYz7NkhNH/nHxD7+c9qfSizCnb4nP0EQms2ta0Mg9yGTbatnbR0JQCAlHnz\nQsQsiK5DE4TqdhisEZqZgSauOpBGhj96CMTvZkBRwORy0BnG89SgM74Kq/ruwJXLfg/8gPHdyMqj\nBatrulry9Z5Tv8CeUz+fhhFQKIXM6lZJAwMDWL58Od5++20AgCiKUFUVra3G3e3ixYtx+PBh9PQY\n1b+JRAKpvBOWKIqIxapnOcayLPgaZFg5U3PM1ahbVv6446a9VUbVcDzrVJ5f2t42re9PLcbd0bQY\nh849BwBoDvcjUIPiplp/3pymgszg97zi8WYziD70AxBFBn/iKITEGLS2wsfI5UJ/1w78qRMAAJ1h\noFx+tWd+5nMPGLIN8zdBFKWs940ZNs/ToQh4nq/LcU8Fpsm40WAzKd/t1nq8QPljZg8fQPjRn0AL\nR5D+L//dM8/9FIEPeAurL1/2AADg6PnXAAA5ebxg3MmsNyudU0cRDxnX87HMSbx1+NsAgJX9NyPA\neW0OJ0stftv18HlTCpkVn8aOHTuwbds2z7Tbb78dq1evxpEjjkF/LpeD4PIhDQQCGB117mq3b9+O\nF1980bOdq6++Gtdcc02Vjrz2tLS0TLzQDDBgnpByecnmpV2d6OiYfCBTjJkc9/rQzXj9wL8CANqb\nF1RlPOUyk+MWXX83CQLYGoy73PFqRw5Bkp3sZ9PwOXDLV/ove/4sSEAAmYLLQrWpl981AMiKDBUA\nf+NH0b5goXem+Z3QLgxDAsBpWtHfh3pgH5iuHpB4E+QXfw0VANfT61m+nsY9FTRVhgSAl3KIlvjd\nNMJ45TdehgpD65z/2WqSCAkAG28q+rlLzCJgNyBpCXu81v/Zc8e9C/NJdHSsBQC89da/2pO5YA4d\nLQumZTy1pBE+77nErAigN2zYgA0bNky4nCAIyLm0mJIkIRh0CtQ2btyIZcuWedYRRRHnz5+fvoOd\n4JhmCo7j0NLSgtHRUShKmbrDaSR/3LmsEW6dSXttm7hpfv9rM27nOyaKmap+n4pRi3Gz93wW4Z9+\nDwCQHD4PeQbHXXS8kgQmOV6QXeZOn4K77Cx7cD9EH6cIkkoi+k/fhB4MIvW1Pyq6/zn/u9Y0sKdP\nQO3uRfDcGfAAkoSFUuQ7QFJJRAGoOf/fO3v4AMIP/whacwvSv/07CJ0+CQ5AevkqjJ8/Xz/jniZI\nJmu8H+mU7/tR6/ECZYxZzAJCEEIyCSu3nD8W9swZhAHILItEke+GJBpK0/H0WYyOjnrGffLMfs+y\nx4f2Is4thaRksPOIo7t/5u1v4qaL/p8Jx3QhdRi7j29FRGjFxYs+D+IjH6zFb3uiz7uWSZm5zKwI\noMslGAyCZVmMjIygpaUFBw8exJYtW+z58Xgc8bi3wcXp06chy9UrKuI4rqrbnwhFUWqy//xxN7MM\nWngeo3nHEiOkKsc30+O+bPDLePPwt7Cm/+4583nLvf1g1l+C4DtvQcukazLu/PHGf/If4M6cx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tzXFg33ueWVZxpdvmT4tEMN3kVq8Dd+o4civXTrzwHEBtdrLwpbp5Mq4Amj13Blrz9N/clMQM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\nALIM/sQxe5l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R7eYBAGyggL6OkpISud3ujD2/y+VSaWlpxp5/MIZhqKurS16vVx5P9neD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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117eca390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (293521997)>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(7.5, 5))\n",
    "\n",
    "g = ggplot(ts, aes(x='dt', y='value', color='kind')) + \\\n",
    "        geom_line(size=2.0) + \\\n",
    "        xlab('Date') + \\\n",
    "        ylab('Value') + \\\n",
    "        ggtitle('Random Timeseries')\n",
    "g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br/>\n",
    "\n",
    "### Thing 2: Scatter\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>petalLength</th>\n",
       "      <th>petalWidth</th>\n",
       "      <th>sepalLength</th>\n",
       "      <th>sepalWidth</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   petalLength  petalWidth  sepalLength  sepalWidth species\n",
       "0          1.4         0.2          5.1         3.5  setosa\n",
       "1          1.4         0.2          4.9         3.0  setosa\n",
       "2          1.3         0.2          4.7         3.2  setosa\n",
       "3          1.5         0.2          4.6         3.1  setosa\n",
       "4          1.4         0.2          5.0         3.6  setosa"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/iris.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RTjm0xkBfoxp9s4L0zGx5wD5lgB+rJb5Gn64h+nTCOdoZyRFG9Ah+a2mUKQP9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\nAAAAwGII6QAAAIDF/H+mjayEB/NAKgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1188b8a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (293583489)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='petalLength',\n",
    "                   y='petalWidth',\n",
    "                   color='species')) + \\\n",
    "        geom_point(size=40.0) + \\\n",
    "        ggtitle('Petal Width v. Length -- by Species')\n",
    "g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br/>\n",
    "\n",
    "### Thing 3: Trellising the Above\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OF/t/QNx/ekWzx/kuGU2BqZR69EwdB6VCg2E95SuGjux9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\nKu/8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118bcb6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (294393961)>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 2, figsize=(10, 10))\n",
    "\n",
    "g = ggplot(ts, aes(x='dt', y='value', color='kind')) + \\\n",
    "        geom_line(size=2.0) + \\\n",
    "        facet_wrap(x='kind', ncol=2) + \\\n",
    "        ggtitle('Random Timeseries')\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Hv4iItEF+08+asi0ccR+nX3wO/eJzWrpLIi3meIWFj3c48fkhweWnrMpGp2Q/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\nIlQDAAAAJhGqAQAAAJMI1QAAAIBJ/x/tuZIBvmbsnwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a07b6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (293152633)>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='petalLength',\n",
    "                   y='petalWidth',\n",
    "                   color='species')) + \\\n",
    "        facet_grid(y='species') + \\\n",
    "        geom_point(size=40.0)\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>petalLength</th>\n",
       "      <th>petalWidth</th>\n",
       "      <th>sepalLength</th>\n",
       "      <th>sepalWidth</th>\n",
       "      <th>species</th>\n",
       "      <th>random_factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>setosa</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>setosa</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>setosa</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>setosa</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   petalLength  petalWidth  sepalLength  sepalWidth species random_factor\n",
       "0          1.4         0.2          5.1         3.5  setosa             B\n",
       "1          1.4         0.2          4.9         3.0  setosa             B\n",
       "2          1.3         0.2          4.7         3.2  setosa             A\n",
       "3          1.5         0.2          4.6         3.1  setosa             A\n",
       "4          1.4         0.2          5.0         3.6  setosa             A"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp_n = df.shape[0] - df.shape[0]/2\n",
    "\n",
    "df['random_factor'] = np.random.permutation(['A'] * tmp_n + ['B'] * (df.shape[0] - tmp_n))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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APffcg9frxTRNfvWrXzV7TEqqRURamb7ebuSn5LHXVxxTPj5rKCmmO0m9EhFp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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117992cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (295716085)>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='petalLength',\n",
    "                   y='petalWidth',\n",
    "                   color='species')) + \\\n",
    "        facet_grid(x='random_factor', y='species') + \\\n",
    "        geom_point(size=40.0)\n",
    "g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br/>\n",
    "\n",
    "### Thing 4: Visualizing Distributions (Boxplot and Histogram)\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pAAAAgGEo6QAAAIBhKOkAAACAYSjpAAAAgGEo6QAAAIBhKOkAAACAYSjpAAAAgGEo6QAA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119fa9b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (297585805)>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='species',\n",
    "                   y='petalWidth',\n",
    "                   fill='species')) + \\\n",
    "        geom_boxplot() + \\\n",
    "        ggtitle('Distribution of Petal Width by Species')\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AYQjpAAAAgGEI6QAAAIBhCOkAAACAYQjpAAAAgGEI6QAAAIBh7OEuwHR79+713bbZbKpb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\nJEmSFDCGdEmSJClgDOmSJElSwPwBK/jVumGcxhsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c136fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (297886001)>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='petalWidth',\n",
    "                   fill='species')) + \\\n",
    "        geom_histogram() + \\\n",
    "        ylab('Frequency') + \\\n",
    "        ggtitle('Distribution of Petal Width by Species')\n",
    "g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br/>\n",
    "\n",
    "### Thing 5: Bar Chart\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who adult_male deck  embark_town alive  alone  \n",
       "0    man       True  NaN  Southampton    no  False  \n",
       "1  woman      False    C    Cherbourg   yes  False  \n",
       "2  woman      False  NaN  Southampton   yes   True  \n",
       "3  woman      False    C  Southampton   yes  False  \n",
       "4    man       True  NaN  Southampton    no   True  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/titanic.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>fare</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th>1</th>\n",
       "      <td>64.684008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.412328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13.669364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>1</th>\n",
       "      <td>95.608029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22.055700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13.694887</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      fare\n",
       "survived pclass           \n",
       "0        1       64.684008\n",
       "         2       19.412328\n",
       "         3       13.669364\n",
       "1        1       95.608029\n",
       "         2       22.055700\n",
       "         3       13.694887"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfg = df.groupby(['survived', 'pclass']).agg({'fare': 'mean'})\n",
    "dfg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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ciNdSqVRy+PDhtLe3p1Y77mVNAXajediP5mI3aDXTdT3PpN047lfiL3zhC/n617+eP/uz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c1a4410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (296106953)>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='class', y='fare')) + \\\n",
    "        geom_bar()\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AAIxDBAMAAMA4RDAAAACMQwQDAADAOEQwAAAAjEMEAwAAwDhEMAAAAIxDBAMA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\n6KTU7z4oVa8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c71e350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (298384553)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df, aes(x='class', weight='fare')) + \\\n",
    "        geom_bar()\n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class</th>\n",
       "      <th>survived</th>\n",
       "      <th>fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>First</td>\n",
       "      <td>0</td>\n",
       "      <td>64.684008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>First</td>\n",
       "      <td>1</td>\n",
       "      <td>95.608029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Second</td>\n",
       "      <td>0</td>\n",
       "      <td>19.412328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Second</td>\n",
       "      <td>1</td>\n",
       "      <td>22.055700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Third</td>\n",
       "      <td>0</td>\n",
       "      <td>13.669364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Third</td>\n",
       "      <td>1</td>\n",
       "      <td>13.694887</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    class  survived       fare\n",
       "0   First         0  64.684008\n",
       "1   First         1  95.608029\n",
       "2  Second         0  19.412328\n",
       "3  Second         1  22.055700\n",
       "4   Third         0  13.669364\n",
       "5   Third         1  13.694887"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['class', 'survived']).\\\n",
    "               agg({'fare': 'mean'}).\\\n",
    "               reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/dsaber/anaconda/lib/python2.7/site-packages/ggplot/ggplot.py:602: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  fill_levels = self.data[[fillcol_raw, fillcol]].sort(fillcol_raw)[fillcol].unique()\n"
     ]
    },
    {
     "data": {
      "image/png": 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YwIXiaUIAAACAoYgBAAAAwFDnFANff/21li1bpoqKCm3bts3fMwEAAAAIgHpj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\nuYhcTr/xoAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11cac0ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (297661029)>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df.groupby(['class', 'survived']).\\\n",
    "               agg({'fare': 'mean'}).\\\n",
    "               reset_index(), aes(x='class',\n",
    "                                  fill='factor(survived)',\n",
    "                                  weight='fare',\n",
    "                                  y='fare')) + \\\n",
    "        geom_bar() + \\\n",
    "        ylab('Avg. Fare') + \\\n",
    "        xlab('Class') + \\\n",
    "        ggtitle('Fare by survival and class') \n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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22SYvvPBCSqVSkuRXv/pVtt5663ZfGAAAW47mOa92yvGXL1/e5hfX5XI5jZs7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\nRhuriwNnKQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c905390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (298427109)>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = ggplot(df.groupby(['class', 'survived']).\\\n",
    "               agg({'fare': 'mean'}).\\\n",
    "               reset_index(), aes(x='class',\n",
    "                                  fill='factor(survived)',\n",
    "                                  y='fare')) + \\\n",
    "        geom_bar() + \\\n",
    "        ylab('Avg. Fare') + \\\n",
    "        xlab('Class') + \\\n",
    "        ggtitle('Fare by survival and class') \n",
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# # in R, I believe you'd do something like this:\n",
    "\n",
    "ggplot(df, aes(x=factor(survived), y=fare)) +\n",
    "    stat_summary_bin(aes(fill=factor(survived)),\n",
    "                     fun.y=\"mean\",\n",
    "                     geom=\"bar\") +\n",
    "    facet_wrap(~class)\n",
    "    \n",
    "# # damn ggplot2 is awesome..."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}