loan_uci

loan_uci.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.style.use('ggplot')\n",
    "import seaborn as sns\n",
    "sns.set_style(\"darkgrid\")\n",
    "plt.rcParams['figure.figsize'] = (20, 10)\n",
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('/Users/kramaswamy/Downloads/DefaultOfCreditCardClients.csv',header=None)"
   ]
  },
  {
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>90000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14331</td>\n",
       "      <td>14948</td>\n",
       "      <td>15549</td>\n",
       "      <td>1518</td>\n",
       "      <td>1500</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>5000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28314</td>\n",
       "      <td>28959</td>\n",
       "      <td>29547</td>\n",
       "      <td>2000</td>\n",
       "      <td>2019</td>\n",
       "      <td>1200</td>\n",
       "      <td>1100</td>\n",
       "      <td>1069</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50000</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>20940</td>\n",
       "      <td>19146</td>\n",
       "      <td>19131</td>\n",
       "      <td>2000</td>\n",
       "      <td>36681</td>\n",
       "      <td>10000</td>\n",
       "      <td>9000</td>\n",
       "      <td>689</td>\n",
       "      <td>679</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19394</td>\n",
       "      <td>19619</td>\n",
       "      <td>20024</td>\n",
       "      <td>2500</td>\n",
       "      <td>1815</td>\n",
       "      <td>657</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>800</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>500000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>542653</td>\n",
       "      <td>483003</td>\n",
       "      <td>473944</td>\n",
       "      <td>55000</td>\n",
       "      <td>40000</td>\n",
       "      <td>38000</td>\n",
       "      <td>20239</td>\n",
       "      <td>13750</td>\n",
       "      <td>13770</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       0   1   2   3   4   5   6   7   8   9  ...      14      15      16  \\\n",
       "0   90000   2   2   2  34   0   0   0   0   0 ...   14331   14948   15549   \n",
       "1   50000   2   2   1  37   0   0   0   0   0 ...   28314   28959   29547   \n",
       "2   50000   1   2   1  57  -1   0  -1   0   0 ...   20940   19146   19131   \n",
       "3   50000   1   1   2  37   0   0   0   0   0 ...   19394   19619   20024   \n",
       "4  500000   1   1   2  29   0   0   0   0   0 ...  542653  483003  473944   \n",
       "\n",
       "      17     18     19     20     21     22  23  \n",
       "0   1518   1500   1000   1000   1000   5000   0  \n",
       "1   2000   2019   1200   1100   1069   1000   0  \n",
       "2   2000  36681  10000   9000    689    679   0  \n",
       "3   2500   1815    657   1000   1000    800   0  \n",
       "4  55000  40000  38000  20239  13750  13770   0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    14030\n",
       "1    10585\n",
       "3     4917\n",
       "5      280\n",
       "4      123\n",
       "6       51\n",
       "0       14\n",
       "Name: 2, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[2].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10c4d4c90>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAATQAAAEyCAYAAAB02CyCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBJoQwjD+P/Y/D+pYm4YdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c4d4710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(5,5), dpi=200)\n",
    "ax = plt.subplot(111)\n",
    "data[1].value_counts(normalize=True).plot(kind='pie', ax=ax, autopct='%1.1f%%', startangle=270, fontsize=17, title='random')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x118448150>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJgAAAJZCAYAAADlMI+bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAACAQf7Wg9hbGAEAsAgmAAAAAJYAhsEhFXe3WGEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1175991d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(data[0])\n",
    "plt.title('asass')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1175a2d90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABLAAAAJZCAYAAAC5usy/AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAPA0CiwAAAAAAAB42r8AxfSn654uoGYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1170ce990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[0].plot(kind='hist',title='asasa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "###data.columns = # add column names herelike this :['abc','def','ghi']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#train.columns = ['loan_id','gender','married','dependents','education','self_employed','income','co_income','amount','amount_term','credit_history','property_area','loan_status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    18112\n",
       "1    11888\n",
       "Name: 1, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[1].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1207e9e50>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3YAAAN8CAYAAAAUNjjrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12718fcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp=pd.DataFrame(data.groupby([23,5]).size(), columns=['count'])\n",
    "tmp.reset_index(inplace=True)\n",
    "tmp=tmp.pivot(index=23,columns=5,values='count')\n",
    "fig, axes = plt.subplots(1,1,figsize=(15,15))\n",
    "tmp.plot(ax=axes,kind='bar', stacked=True,title='asassa')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "acc_data = pd.DataFrame()\n",
    "acc_data['error_rates'] = [0.1,0.12,0.13]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11982e8d0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIUAAAJNCAYAAACvJ8VOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSBQCAAAASOj/AQjlN9nv8ebJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a80eb50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "acc_data.error_rates.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_data_fold_one = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_data_fold_two = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_data_fold_three = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sample_data_fold_one['first fold'] =[0.1,0.11,0.12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sample_data_fold_three['second fold'] =[0.11,0.134,0.72]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_data_fold_two['third fold'] =[0.6,0.15,0.82]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = ['svnm','asa','asasas']\n",
    "sample_data_fold_one['class'] = x\n",
    "sample_data_fold_two['class'] = x\n",
    "sample_data_fold_three['class'] = x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>first fold</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>svnm</th>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asa</th>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asasas</th>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        first fold\n",
       "class             \n",
       "svnm          0.10\n",
       "asa           0.11\n",
       "asasas        0.12"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_data_fold_one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_data_fold_one.set_index(['class'],inplace=True)\n",
    "sample_data_fold_two.set_index(['class'],inplace=True)\n",
    "\n",
    "sample_data_fold_three.set_index(['class'],inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11cb4d190>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJ4AAAJoCAYAAAAnCCvUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xdgk+XexvEro+mgRVZBQYZsZCk4kCF7KUNExMHeCoKC\nIHhQyyhlKXuPskVFBJWjMgqKIKLIKlNkI0LLECjpSHK/f/Qlh6mgDWnh+/nnNM2TO1fS8hy5uJ9f\nLMYYIwAAAAAAACCNWf0dAAAAAAAAAHcmiicAAAAAAAD4BMUTAAAAAAAAfILiCQAAAAAAAD5B8QQA\nAAAAAACfoHgCAAAAAACAT1A8AQCQAbhcLlWuXFkdO3b0d5RbUrx4cTVq1EhNmjRRkyZN1LBhQ02d\nOlWStHHjRjVs2NDPCW9Ov379FB0dLSn1NZ09e/Yvjz9z5oyKFy+ephkmTJigmJgYSdLYsWO1dOnS\nNF0/vfrkk0/04Ycf+jsGAAD4h+z+DgAAAP7eihUrVLx4ce3YsUP79+9XwYIF/R3pplgsFs2dO1f3\n3HOPJOnChQt65plnVKxYMQUHB/s53T9jsVj+9hhjzE0ddys2bNigIkWKSJK6d++epmunZ7/88ouK\nFi3q7xgAAOAfongCACADWLBggRo0aKACBQpo9uzZGjBggHr16qWSJUuqXbt2kqSFCxdq48aN+uCD\nDxQTE6PJkyfL5XIpKChIb731lsqWLavx48dr8+bNiouLU/HixfXWW2/p3Xff1alTpxQfH6/cuXNr\n9OjRypYtm7Zt26YBAwbI5XIpb968+v3339WvXz89+uij16zfp08fPfTQQ9fkNsbIGOO9HRoaqlKl\nSmn//v0qWbKkEhIS1LNnT+3fv1/JyckaNGiQypcvrwsXLmjAgAHavXu3LBaLqlSpol69eslqtapM\nmTLq1KmT1q1bp7i4OLVs2VKtW7eWJC1atEgLFiyQJGXJkkX9+/e/bkm3aNEizZo1SzabTVmzZtWw\nYcOUM2dORUZGavv27UpISJAxRoMHD9bDDz98zWu6nuXLl2v06NEKDg5WqVKlvN//7LPP9M0332jy\n5MnX3O7Xr5/Onj2ro0ePqlq1amratKkGDhyoixcv6uTJkypRooRGjRqlTz75RLGxsRo+fLisVqtW\nrVqlokWLqm3btvr55581YsQIJSYmKiAgQD169FCVKlX02WefacWKFbJarTp06JACAgI0fPhwFS5c\n+Ircn332mb788ksZY3TixAnde++9Gjp0qMLDw3XhwgVFRkZq7969crlceuKJJ9SnTx9ZrVaVLl1a\nNWvW1J49ezRy5EiVLFnSu+bFixc1aNAg/fLLLwoICFDNmjX1xhtvqF+/ft7ckq64vWDBAn300Udy\nOBwKDAzUgAEDdODAAcXExGj9+vUKDAzU888/r6ioKG3YsEE2m01ly5ZVv379FBISoho1aqhhw4Za\ns2aN/vzzT3Xr1k2//PKLduzYoYCAAE2aNEnh4eE6ceKEBg0apOPHj8vlcunpp59Wp06ddOzYMb38\n8ssqVKiQjh07pnnz5ilHjhw3+BMJAABumgEAAOnar7/+asqUKWPOnTtntm3bZh566CFz9uxZs2HD\nBtOgQQPvcc2aNTM//PCDOXjwoGnQoIE5e/as9/GVKlUyTqfTjBs3ztSvX994PB5jjDGzZ88206ZN\n867RsWNHEx0dbVwul6latapZu3atMcaYDRs2mBIlSpiNGzf+5fpXK1asmDlz5oz39m+//WYqVapk\ntm/fbn788UdTsmRJs23bNmOMMdHR0aZNmzbGGGP69OljIiMjjTHGJCcnm3bt2pmpU6d615w/f74x\nxpjY2FhTunRpk5SUZH788Ufz8ssvm8TERGOMMd9//7156qmnrsm0a9cuU6FCBfPHH39434P33nvP\nbN682fTo0cN73JQpU0yXLl2MMcb07dvXzJw587qvyRhj4uPjzSOPPGJ+++0372OLFy9ujDFm8eLF\npnPnzt5jL7/dt29f07ZtW+99w4YNM59//rkxxpiUlBTTsGFDs3z5cmOMMS1atPB+fSnPmTNnTMWK\nFb3v4a+//moef/xxc/ToUbN48WLz6KOPmhMnThhjjBk0aJDp27fvNe/H4sWLzcMPP2wOHTpkjDFm\n5MiRpnv37sYYY/r162fmzZtnjDHG7Xab3r17m+nTp3vfh0tZrxYVFWV69uxpjEn9+bVo0cJs3Ljx\nivfx8tfhdrtNqVKlTFxcnDHGmKVLl5qPP/74mvd+zJgx5rXXXjNut9ub77333jPGGFO9enUzdOhQ\nY4wxy5YtMyVKlDB79uwxxhjTtWtXM2XKFGOMMa1atTKrV682xhiTlJRkWrVqZb766itz9OhRU6xY\nMbNp06brviYAAPDPsOMJAIB0buHChapatarCwsJUunRp5cmTRx999JE6deqk5ORk7dixQ0FBQTpz\n5owqVKigBQsWKD4+Xm3atPHuzrHb7Tp06JAkqWzZst7LwFq1aqWff/5Zs2bN0sGDB7Vv3z6VLVtW\ne/fulcViUeXKlSVJjz/+uPcyr3Xr1t1w/WLFil2Tv1WrVrLZbHK5XMqUKZPeeustlSpVShs3blTe\nvHlVunRpSVKJEiW0ePFiSdLatWu1cOFCSVJAQIBefPFFzZ492zvjqmbNmpKkkiVLKiUlRU6nU99+\n+60OHz6sF154wZvr3LlzOnfunDJnzuzNs2HDBlWpUkW5cuXy5rukR48e+vDDD3X48GFt3LhRoaGh\nN/Uz2rRpk4oVK+bdXdW8eXONGjXqph5brlw579e9e/fWunXrNH36dB08eFBxcXFKSEjw3m+u2m21\ndetW5c+f3/seFi5cWOXLl9fGjRu970/OnDklSQ8++KBWrFhx3QyVK1dWvnz5JEnPP/+8nnnmGUnS\nmjVrtH37dn3yySeSpKSkJFmt/xsRWr58+euut379evXr109S6s9v7ty5kuT9+V7NarWqfv36at68\nuapVq6ZKlSpdd/7X2rVr1bNnT2+Gli1bqmvXrt7769SpI0nKly+fwsPDvZfo5c2bV2fPnpXT6dRP\nP/2kc+fOafTo0ZIkp9OpXbt2qXTp0rLb7dfduQcAAP45iicAANIxp9OpJUuWKCgoSDVr1pQxRgkJ\nCZo/f77at2+v5557Tp999pkcDoeee+45SZLH49ETTzyhDz74wLvOH3/8oZw5c2rFihXKlCmT9/sj\nRoxQbGysmjZtqgoVKsjlcskYI5vNJo/Hc0WWS3/Zv9H6l4qcq10+4+lqdvv//lPEYrF4i5Wrn9vj\n8cjlcnlvBwYGXnG/MUYej0eNGzdWr169vN8/ceLEFaWTJNlstivmLyUlJenYsWM6cuSIIiMj1a5d\nO9WqVUsFCxbUF198cd3cV7s8+6XnuPy+y6WkpFxx+/KfxxtvvCGPx6P69eurevXqOn78+F8+r7nq\nUkZJcrvdcrlcstvtV7xPV2e83OV53W6397bb7daYMWO8hdr58+eveD0hISHXXc9ut19x3B9//KGg\noCBv5kuSk5O9Xw8fPlz79u3T+vXrNW3aNC1atEgTJ068Yt2rfy8uvdZLHA7HFRmu5na7Jcl7SZ+U\nOgg+KChIp0+flsPhuKJYAwAA/x7/zwoAQDr2+eefK1u2bPr++++1atUqxcTEaOXKlUpISNBXX32l\nJk2aKCYmRt98842effZZSVKFChW0bt067d+/X5L07bffqnHjxlf8Jf+SdevWqXXr1mrUqJGyZs2q\n9evXy+PxqFChQgoMDNT3338vSdq2bZt3F9SN1k9KSrrua7hR2fFXKleurPnz50tKLSc++ugjVapU\n6S/Xr1SpkpYtW6a4uDhJ0vz589WmTZtrjn/88ce1fv16xcfHS5I+/PBDjRw5UuvXr1eNGjX0wgsv\nqFSpUlq1atU1RceNlC9fXvv27dOePXskXbmzJ2vWrNq7d6+Sk5Plcrm8n0x3PevXr1fXrl1Vv359\nGWO0detWb1lit9uvKFmk1N1rBw8e1Pbt2yVJv/76qzZt2qTHHnvspnJf8sMPP+jkyZOSUkuZGjVq\nSEr9OcyaNUtS6s/hlVde8f5c/soTTzyhJUuWyBij5ORkde/eXT///LOyZcum2NhYSdLp06e1adMm\nSanlT7Vq1ZQlSxa1atVKr7/+uve9tNls3rKucuXK+vDDD+VyueTxeLRgwYIb/l5cT2hoqMqWLasZ\nM2ZISt0R9+KLL2rVqlWS/tnvKgAA+GvseAIAIB1buHChdxDzJWFhYWrZsqVmz56tBg0aqGTJkvJ4\nPAoPD5eUernVwIED1bNnT0mpf3GfNGmSd8fJ5bp27aphw4ZpwoQJstvtKl++vA4dOiSbzaaxY8fq\nvffe0wcffKACBQooPDxcQUFBt7T+P/1kt/79+2vQoEFq2LChUlJSVKVKFXXp0uW6a166XblyZXXo\n0EHt2rWT1WpVaGioxo8ff83aRYsWVZ8+fdS+fXtZLBaFh4dryJAhOn/+vN588001btxYNptNjzzy\niJYvX35TrylbtmwaOXKk3nzzTQUEBFxR/FSuXFmPPfaY6tWrp5w5c+rxxx/3lipXe+ONN9S1a1dl\nyZJFwcHBeuyxx3T48GFJUvXq1TVs2LArCsSsWbNqzJgxGjRokJxOp2w2m6KiopQ/f3798ssvf/c2\ne917773q06ePTp48qcKFC2vQoEGSUn8OQ4YMUcOGDeVyuVSpUiV16NDhhu/DJd26dVNkZKQaNWok\nY4yeeuop1apVS6VKldKbb76p+vXrK0+ePHr88ce9r+PVV19V69atFRgYqICAAEVGRkqSnnzySW+e\nrl27aujQoXrmmWfkdrtVpkwZvfPOO3+b53IjR470/m65XC41bNhQDRo00LFjx9L8kwgBAIBkMfzT\nDgAAuI7hw4erQ4cOypYtm/744w81btxYq1atuum5R8gYrv7UPQAAgLTk0x1PxhhFRERoz549cjgc\nioyMVN68eb33L1myRDNnzlTmzJn1zDPPeGdTAAAA/8uTJ49at27tnZUTGRlJ6QQAAIBb4tMdTytW\nrFBMTIyioqK0detWTZkyxTsk8syZM2ratKmWLl2q0NBQtWnTRlFRUcqdO7ev4gAAAAAAAOA28ulw\n8U2bNqlKlSqSUodfXhomKUlHjhxRiRIlFBYWJovFotKlS2vLli2+jAMAAAAAAIDbyKfF04ULFxQW\nFua9bbfbvZ8OU6BAAe3bt0+nT5+W0+nUDz/8IKfT6cs4AAAAAAAAuI18OuMpNDRUCQkJ3tsej0dW\na2rXlTlzZvXt21evvfaasmTJopIlSypr1qx/uZ4xhk8bAQAAAAAAyCB8WjyVK1dOq1evVr169bRl\nyxYVLVrUe5/b7daOHTs0f/58JScnq3379t6PZb4Ri8WiuLjzvowM4C4UHh7GuQVAmuPcAsAXOLcA\n8IXw8LC/P+gf8mnxVLt2ba1bt04vvPCCJCkqKkpffvmlnE6nmjVrJklq0qSJAgMD1a5dO2XJksWX\ncQAAAAAAAHAb+fRT7XyBdh9AWuNfDgH4AucWAL7AuQWAL/hyx5NPh4sDAAAAAADg7kXxBAAAAAAA\nAJ+geAIAAAAAAIBPUDwBAAAAAADAJyieAAAAAAAA4BMUTwAAAAAAAJdxu93q3r2LXnmlvT7++EOt\nW7f2ph63f/8+bd26+ZrvT5w4Vm3avKQtW3657uOGDBmgjRs3XPG95ORkNWvW6NbDpzN2fwcAAAAA\nAABIT+Li4nTx4kVNnz7nlh63Zk2MsmXLrrJlH77q+6s0e/ZCBQcH3/RaxhhJllt6/vSI4gkAAAAA\nAKRbmSL6K/CLJWm6ZlLDZ5QQMfiG97//fpSOHj2skSOjlC1bdmXLll358xfQpEnj5HA41KhREx08\neECbN/8st9ujatVqqE6d+vrqqy8VEBCg4sVLqHjxByVJs2ZNV3x8vHr37qH33x+nqVMnavv2rbJY\nLKpdu66ee+4F7/M6nU4NHNhf58+fV54896fpa/YXLrUDAAAAAAC4TK9efVWgQEG9+WY/SZLFkrrz\nKCUlWePHT1WdOvW1YsU3eu+9IZowYZpCQ8OUI0e46tdvoObNX/aWTpLUpk0HZc+eQ6NHT9SmTT/p\nxInjmjp1liZMmKYVK77R/v37vMcuWfKpChYsrPHjp6px42dv74v2EXY8AQAAAACAdCshYvBf7k66\nnfLly+/9+t13B2rSpLE6c+a0KlSo+LePNcbo4MEDKlMm9TI8u92uBx8spQMHDniPOXLkkCpWrCJJ\nevDBUrLbbWn8Cm4/djwBAAAAAADcBIsltUZJSUnR6tUrNWDAEI0dO1n//e8XOnHiD1mtVnk8nus8\n0kiSChR4QNu2bZEkuVwuxcZuVb58+bxHPfBAIcXGbpMk7d27Wy6X27cv6DZgxxMAAAAAAMAtCAgI\nUObM96hTpzYKCgrS448/oVy57lWxYsU1ceJYFSjwgB5+uPxlj0i9VK9ixcravHmTunRpJ5fLpRo1\naqtIkWLeoxo3flaDB7+nrl07Kl++/HI4Am7zK0t7FpM6Jj3DiIs77+8IAO4w4eFhnFsApDnOLQB8\ngXMLAF8IDw/z2dpcagcAAAAAAACfoHgCAAAAAACAT1A8AQAAAAAAwCcongAAAAAAAOATFE8AAAAA\nAADwCYonAAAAAAAA+ATFEwAAAAAAwGWSk5P15ZdLJEkzZ07V0qWLrzmmf/8+f7tGs2aNrvn+p59+\npBYtnldMzMrrPu5Gz9e4cd2biZ7uUDwBAAAAAABc5tSpeH3xxdK/PGbw4OF/eb8xRpLlmu9/990a\nDRwYpRo1at1iqmvXygjs/g4AAAAAAABwIxERgfrii7StLxo2dCkiIumG98+ZE61Dhw5o1qzpkqS1\na9coJmalzp//Ux06vKKKFSurceO6Wrr0G732WmdlzZpN58+f0+DBwzR48Hs6f/688uS5/5p1P//8\nM+3Zs1tDhw7SwIFRWr16lWJilstut6ts2XLq0qWb91iPx6PhwyN18OAB5c6dRykpKWn6Htwu7HgC\nAAAAAAC4TOvW7VSgQEG1adNBkhQenktjxkzUa6/11JIli/7/qP/tQKpTp55GjZqgzz9fooIFC2v8\n+Klq3PjZa9Zt1KiJihYtpnfeGaiLFxO0Zs0qTZkyS5MmzdTRo4e1fv333mO/+261UlKSNXnyTHXu\n3FWJiYk+fc2+wo4nAAAAAACQbkVEJP3l7qTboVix4pKk7NmzX7cAyps3vyTpyJFDqlixiiTpwQdL\nyW63XXOsMUbGGB06dFAlS5aS1Zq6J6hMmYd04MBvslgs/7/WYZUoUVKSlCvXvcqZM1fav7DbgB1P\nAAAAAAAAl7FYLPJ4PFfcvpa55v4CBQoqNnabJGnv3t1yudw3fI78+Qto584d8ng8MsZoy5bNypcv\n///PhpIeeKCgtm9PXSs+Pk5xcSf+7cvyC3Y8AQAAAAAAXCZr1mxyuVI0efJ4BQYG3uCo1LLp8lLq\nmWeaavDg99S1a0fly5dfDkfAtY/6/+MLFiysGjVqqUuXdjLGqGzZh1WlSjX9+uteSVLlylW1ceMG\nde7cVrly3ausWbOl7Yu8TSzmUpWWQcTFnfd3BAB3mPDwMM4tANIc5xYAvsC5BYAvhIeH+WxtLrUD\nAAAAAACAT1A8AQAAAAAAwCcongAAAAAAAOATFE8AAAAAAADwCYonAAAAAAAA+ATFEwAAAAAAAHyC\n4gkAAAAAACAdOHz4oF57rfM13584cazatHlJW7b8ct3HDRkyQBs3brjie8nJyWrWrJFPct4Ku78D\nAAAAAAAAIJXFYrnme2vWrNLs2QsVHBx80+sYYyRdu9btRvEEAAAAAADSrYj1/fXFb0vSdM2GhZ5R\nRMXBN7z/yJHDGjJkgOx2u4wxeu+9wQoPz6kpUyZo27Yt8njcat78ZVWrVlM7dsRq3LgPZIxReHi4\n3n13sA4e3K/Ro0fKZrPJ4QjUW2/9Rx6PRxER/1GuXLl09OhRlShRUm++2VenTsVr4MB3JElZs2a7\nJsusWdMVHx+v3r176P33x2nq1Inavn2rLBaLateuq+eee8F7rNPp1MCB/XX+/HnlyXN/mr5n/xTF\nEwAAAAAAwGV++ulHPfhgKb36andt3bpZFy5c0G+/7dPx479rwoRpSk5OVufObfTII49r5MghGjAg\nSvny5deyZZ/r4MH9Gj58iPr1e1eFChXW999/q7FjP1C3bq/r6NHDGj16ohwOh5o3f0ZnzpzWnDkz\nVbt2XTVo8IxWrVqhpUs/vSJLmzYdtGzZFxo9eqI2btygEyeOa+rUWXK5XOrataPKlXvEe+ySJZ+q\nYMHC6tjxFe3cGatfftl0u9+6a1A8AQAAAACAdCui4uC/3J3kCw0aNNb8+bPVs+drCgsLVadOr2r/\n/n3avXuXunfvImOM3G63jh//XadPn1a+fPklSU8/nTpT6dSpeBUqVFiSVLZsOU2ePEGSlCdPXgUF\nBUmSsmfPoaSkZB05cliNGj0rSSpTpuw1xdMlxhgdPHhAZco8LEmy2+168MFSOnDggPeYI0cOqWLF\nKpKkBx8sJbvdltZvzS1juDgAAAAAAMBl1q79VmXLPqwxYyaqWrWamj9/jvLnf0Dlyz+isWMna+zY\nyapRo7by5LlfOXKE69ixo5Kk+fNn67vv1ihHjhz67bd9kqTNmzcpb9581zxH6gwm6YEHCmr79q2S\npJ07d9wgUeqxBQo8oG3btkiSXC6XYmO3Kl++/639wAOFFBu7TZK0d+9uuVzuf/9m/EvseAIAAAAA\nALhM8eIlFBkZoYCAAHk8HnXv3lNFihTTL7/8rK5dO8rpdOrJJ6spJCREvXv305AhA2S1WpU9ew41\nb/6y7rvvPo0aNVzGGNntdvXtmzrD6fLB4Ze+btWqnQYMeEcxMSt03325b5Ao9diKFStr8+ZN6tKl\nnVwul2rUqK0iRYp5j2rc+FkNHvyeunbtqHz58svhCPDNG3QLLOZSxZZBxMWd93cEAHeY8PAwzi0A\n0hznFgC+wLkFgC+Eh4f5bG0utQMAAAAAAIBPUDwBAAAAAADAJyieAAAAAAAA4BMUTwAAAAAAAPAJ\niicAAAAAAAD4BMUTAAAAAAAAfILiCQAAAAAAAD5B8QQAAAAAAACfoHgCAAAAAACAT1A8AQAAAAAA\n3KUSEny7PsUTAAAAAADAXWjfPotq1szk0+egeAIAAAAAALjLfPutTfXrZ9L+/b6thiieAAAAAAAA\n7iKzZgXohReC5XRK48Y5ffpcdp+uDgAAAAAAgHTB5ZLefTdQ06c7lD27R9HRiapQwe3T56R4AgAA\nAAAAuMOdOyd17Bis1avtKl7crblzncqf3/j8ebnUDgAAAAAA4A524IBFTz0VotWr7apVy6Vlyy7e\nltJJongCAAAAAAC4Y61fb1O9epm0d69NnTsna+5cp8LCbt/zc6kdAAAAAADAHWjBArt69w6SMdL7\n7yeqZcuU256B4gkAAAAAAOAO4nZLgwYFauJEh7JmNZo506lKlXw7RPxGKJ4AAAAAAADuEBcuSF26\nBGv5crsKF3Zr3jynCha8PfOcrsenxZMxRhEREdqzZ48cDociIyOVN29e7/2ff/65Zs2aJZvNpmef\nfVYvvviiL+MAAAAAAADcsY4csahFi2Dt2mVT1aouTZ/u1D33+DeTT4eLr1y5UsnJyVq4cKF69eql\nqKioK+4fPny4Zs+erQULFig6Olrnz5/3ZRwAAAAAAIA70saNVtWtG6Jdu2xq1y5ZH37o/9JJ8vGO\np02bNqlKlSqSpLJlyyo2NvaK+4sXL64///xTFotFkrz/CwAAAAAAgJvz8cd29ewZJLdbiopKVPv2\nt3+I+I34tHi6cOGCwi77jD673S6PxyOrNXWjVZEiRdS0aVOFhISodu3aCg0N9WUcAAAAAACAO4bH\nI0VFOTRmTKAyZzaaNs2p6tX9M0T8Rnx6qV1oaKgSEhK8ty8vnfbs2aM1a9YoJiZGMTExOnXqlL75\n5htfxgEAAAAAALgjJCRI7dsHacyYQBUo4NFXX11Md6WT5OMdT+XKldPq1atVr149bdmyRUWLFvXe\nFxYWpuDgYDkcDlksFmXLlk3nzp372zXDw8P+9hgAuFWcWwD4AucWAL7AuQXA0aPSs89KmzdL1apJ\nixZZlT17Jn/Hui6LMcZnn6l3+afaSVJUVJR27Nghp9OpZs2aaeHChfr000/lcDiUL18+DRo0SHb7\nX3dhcXEMIAeQtsLDwzi3AEhznFsA+ALnFgCbN1vVsmWwTp60qkWLZA0dmiSH49+t6ctC26fFky9w\nkgWQ1vgPOAC+wLkFgC9wbgHubkuX2vXaa0FKTpYiIpLUuXOK0uJz2nxZPPn0UjsAAAAAAAD8O8ZI\nI0c6NGJEoEJDjWbMcKp27fQ3z+l6KJ4AAAAAAADSKadT6tEjSEuWBChfPo/mznWqRAmPv2PdNIon\nAAAAAACAdOjECYtatQrW5s02PfaYS9HRiQoPz1ATk2T1dwAAAAAAAABcaft2q+rWDdHmzTY9/3yK\nPv3UmeFKJ4niCQAAAAAAIF1Ztsyuhg1DdPy4Rf37J2ncuEQFBvo71T/DpXYAAAAAAADpgDHSuHEO\nDR4cqJAQo+joRD31lMvfsf4ViicAAAAAAAA/S0qSevYM0iefBCh37tQh4qVLZ5wh4jdC8QQAAAAA\nAOBHcXEWtWkTrJ9+sqlcObdmz3YqV66MN8/pepjxBAAAAAAA4Cc7d1pVr16IfvrJpiZNUvTZZxfv\nmNJJongCAAAAAADwi+XLbXr66RAdOWJVnz5Jmjw5UcHB/k6VtrjUDgAAAAAA4DYyRpo8OUAREYEK\nDJSmTXOqceOMPUT8RiieAAAAAAAAbpPkZKlv30DNm+dQrlwezZnj1MMPZ/wh4jdC8QQAAAAAAHAb\nnD4ttWsXrPXr7Spd2q25c53KnfvOmed0Pcx4AgAAAAAA8LFff7WqXr1MWr/erqefTtHnn1+840sn\nieIJAAAAAADAp1avtql+/RAdPGjVG28kacaMRGXK5O9UtweX2gEAAAAAAPjIjBkB6t8/UHa7NHGi\nU889d2eCX0esAAAgAElEQVQOEb8RiicAAAAAAIA0lpIi9e8fqOhoh3Lk8Gj2bKceffTOHSJ+IxRP\nAAAAAAAAaejsWalDh2B9951dJUq4NW+eU3nz3vnznK6HGU8AAAAAAABpZP9+i556KkTffWdX3bou\nLVt28a4tnSSKJwAAAAAAgDTx/fc21auXSfv22dS1a7JmzXIqNNTfqfyLS+0AAAAAAAD+pblzA/TW\nW4GyWKTRo5166aW7a4j4jVA8AQAAAAAA/ENutxQREagpUxzKls2j6OhEPfGE29+x0g2KJwAAAAAA\ngH/g/HmpU6dgrVplV9GiqUPECxS4e+c5XQ/FEwAAAAAAwC06dMiili2DtXu3TdWruzRtmlOZM/s7\nVfrDcHEAAAAAAIBbsGGDTfXqhWj3bps6dUrW/PmUTjfCjicAAAAAAICbtHChXb16BcnjkUaMSFTr\n1in+jpSuUTwBAAAAAAD8DY9Hiox0aNy4QN1zj9GMGU49+SRDxP8OxRMAAAAAAMBfuHBBevXVIH39\ndYAKFvRo/vyLKlSIIeI3g+IJAAAAAADgBo4eTR0ivmOHTVWquDRjhlNZsvg7VcbBcHEAAAAAAIDr\n+Plnq+rWDdGOHTa1apWshQspnW4VO54AAAAAAACusnixXT16BCklRRoyJFHt26fIYvF3qoyH4gkA\nAAAAAOD/eTzS8OEOffBBoMLCjGbPdqpGDYaI/1MUTwAAAAAAAJIuXpReey1IX3wRoPz5PZo3z6li\nxTz+jpWhUTwBAAAAAIC73vHjFrVqFaytW22qUMGl6OhEZc/OJ9f9WwwXBwAAAAAAd7WtW1OHiG/d\natOLL6Zo0SInpVMaoXgCAAAAAAB3rS++sKtRoxCdOGHRe+8lavToRDkc/k515+BSOwAAAAAAcNcx\nRho1yqGhQwOVKZPRnDlO1a3LEPG0RvEEAAAAAADuKomJ0uuvB2nx4gDdf79Hc+c6VbIkQ8R9geIJ\nAAAAAADcNU6csKhNm2Bt2mTTI4+4NWuWUzlzMs/JV5jxBAAAAAAA7gqxsVbVqxeiTZtsato0RYsX\nX6R08jGKJwAAAAAAcMf7+mubGjQI0bFjVr39dpImTkxUUJC/U935uNQOAAAAAADcsYyRxo93aPBg\nh4KCpBkznGrY0OXvWHcNiicAAAAAAHBHSkqSevcO0sKFAbrvvtQh4mXKMET8dqJ4AgAAAAAAd5z4\neIvatQvShg12PfSQW3PmOHXvvcxzut2Y8QQAAAAAAO4ou3enDhHfsMGuRo1StGTJRUonP6F4AgAA\nAAAAd4xVq2x6+ukQHT5s1ZtvJmnq1ESFhPg71d2LS+0AAAAAAECGZ4w0bVqA3n03UAEB0pQpTjVp\nwhBxf6N4AgAAAAAAGVpKitS3b6DmznUoPNyjOXOcKl+eIeLpAcUTAAAAAADIsM6ckTp0CNbatXaV\nLOnWvHlO5cnDPKf0ghlPAAAAAAAgQ9q3z6L69TNp7Vq76tdP0RdfXKR0SmcongAAAAAAQIbz7bc2\n1a+fSfv3W9W9e5KioxMVGurvVLgaxRMAAAAAAMhQZs0K0AsvBMvplMaNc6p//2RZaTj+kW1xW3y6\nPj8WAAAAAACQIbhc0ttvB6pPnyBlyWK0aJFTzZvzyXX/hMd4NH7zGNX7tIZPn4fh4gAAAAAAIN07\nd07q2DFYq1fbVby4W3PnOpU/P/Oc/omTF0/qtVWdtfrIKuUMyeXT52LHEwAAAAAASNcOHLDoqadC\ntHq1XbVqubRs2UVKp39ozZEYVf+oolYfWaWa+Wpr9fPrffp87HgCAAAAAADp1vr1NrVtG6wzZyzq\n3DlZERFJstn8nSrjSXGnaNjGSI3bPEp2q10DKg5R57Kvymrx7Z4kiicAAAAAAJAuLVhgV+/eQTJG\nev/9RLVsmeLvSBnSoXMH1WVFe2068ZMKZH5AU+tE66Gc5W7Lc1M8AQAAAACAdMXtlgYNCtTEiQ5l\nzWo0c6ZTlSq5/R0rQ/p832fquaa7ziX/qWeLNNOIqqMU5sh8256f4gkAAAAAAKQbFy5IXboEa/ly\nuwoXdmvePKcKFmSe0626mHJR76zrp7k7oxViD9HYGpPUvNhLslgstzUHxRMAAAAAAEgXjhyxqEWL\nYO3aZVPVqi5Nn+7UPff4O1XGs+vUTnVe0Va7T+9SyeylNbVOtIpkLeqXLHyqHQAAAAAA8LuNG62q\nWzdEu3bZ1K5dsj78kNLpVhljNHvHTNVdVE27T+9S+9Kd9FXTVX4rnSR2PAEAAAAAAD/7+GO7evYM\nktstRUUlqn17hojfqj+Tzqrnmu764rclyhKYRVPqRKv+A0/7O5ZviydjjCIiIrRnzx45HA5FRkYq\nb968kqT4+Hi98cYbslgsMsZo9+7devPNN9W8eXNfRgIAAAAAAOmExyNFRTk0ZkygMmc2mjbNqerV\nGSJ+q37640d1WdFeR84fVoX7KmpSrenKE3a/v2NJ8nHxtHLlSiUnJ2vhwoXaunWroqKiNHHiRElS\njhw5NHfuXEnSli1bNHr0aD3//PO+jAMAAAAAANKJhASpW7cgLVsWoAIFPJo/36kiRTz+jpWheIxH\n434ZpaEbB8tjPOr1yFvq9chbslvTzwVuPk2yadMmValSRZJUtmxZxcbGXve4QYMG6YMPPrjtk9UB\nAAAAAMDt9/vvFrVsGazt222qVMmlGTOcypbN36kylhMXT6jryk767uhq3ZvpPk2qNV2V8lTxd6xr\n+LR4unDhgsLCwv73ZHa7PB6PrNb/zTSPiYlR0aJFlT9/fl9GAQAAAAAA6cDmzVa1bBmskyetatEi\nWUOHJsnh8HeqjCXm8Ap1W9VZ8c541clfT2NqTFL24Oz+jnVdPi2eQkNDlZCQ4L19dekkSZ9//rla\nt25902uGh4f9/UEAcIs4twDwBc4tAHyBcwsyso8/llq3lpKTpQ8+kF5/3SGLhdbpZiW7k/WfVf/R\nyB9GymFzaHTd0er+ePd0fQWZT4uncuXKafXq1apXr562bNmiokWv/fi+2NhYPfzwwze9Zlzc+bSM\nCAAKDw/j3AIgzXFuAeALnFuQURkjjRzp0IgRgQoNNZoxw6natd2Kj/d3sozj4J8H1HlFW20++YsK\n3lNIU+tEq0z4Q4qPv/Cv1/Zloe3T4ql27dpat26dXnjhBUlSVFSUvvzySzmdTjVr1kynT5++4lI8\nAAAAAABwZ3E6pR49grRkSYDy5fNo7lynSpRgiPit+OzXReq1pocupJxXs6IvaNiT7yvUkTH6FIsx\nxvg7xK2g3QeQ1viXQwC+wLkFgC9wbkFGc+KERa1aBWvzZpsee8yl6OhEhYdnqBrCrxJSEvSftX20\nYPdchdgzadiT76t58ZfS/Hky7I4nAAAAAABwd9q+PXWI+O+/W/X88yl6//1EBQb6O1XGsSM+Vp2W\nt9GvZ/eqdI6ymlpnpgplKeLvWLfM+veHAAAAAAAA3Lxly+xq2DBEx49b1L9/ksaNo3S6WcYYzYyd\npnqfVtevZ/eqc5lX9d+mKzNk6SSx4wkAAAAAAKQRY6Rx4xwaPDhQISFG0dGJeuopl79jZRhnEk/r\njdWv6b8HvlC2oGyaUXeO6hSo7+9Y/wrFEwAAAAAA+NeSkqSePYP0yScByp07dYh46dIMEb9ZPx7f\noC4r2unYhaOqmLuyJtWarvtCc/s71r9G8QQAAAAAAP6VuDiL2rQJ1k8/2VSunFuzZzuVKxdDxG+G\n2+PWmF/e14ifomRk1OfRt/VG+d6yWW3+jpYmKJ4AAAAAAMA/tnNn6hDxI0esatIkRaNHJyo42N+p\nMoY/Eo7r1ZUd9f2x75Q7Ux5Nrj1DFXJX9HesNEXxBAAAAAAA/pHly23q3DlYCQkW9emTpF69kmWx\n+DtVxrDi4NfqHvOKTiWeUr0Hntbo6uOVLSi7v2OlOYonAAAAAABwS4yRJk8OUEREoAIDpWnTnGrc\nmCHiNyPZnazBGyI0eet4OawORVUZqXalOspyhzZ2FE8AAAAAAOCmJSdLffsGat48h3Ll8mjOHKce\nfpgh4jdj/5+/qfPydtoat1mFsxTRlDrRKp2jjL9j+RTFEwAAAAAAuCmnT0vt2gVr/Xq7Spd2a+5c\np3LnZoj4zVi09yP1/vYNJaRc0IvFW2hIlRHKFJDJ37F8juIJAAAAAAD8rV9/terll4N18KBVTz+d\novHjE5Xpzu9N/rULKRfU77s39dGeBQoNCNOkWtPVtOjz/o5121A8AQAAAACAv7R6tU0dOwbr3DmL\n3ngjSW+9lSyr1d+p0r/t8dvUaXkb/XZ2n8qGP6wpdWaq4D2F/B3rtuLXBAAAAAAA3NCMGQF66aVg\nJSZKEyY41a8fpdPfMcZo+rbJqr+ohn47u0+vlH1Ny55dcdeVThI7ngAAAAAAwHWkpEj9+wcqOtqh\nHDk8mj3bqUcfZYj43zmdeEqvx3TV1wf/q+xB2TWu5mTVyl/X37H8huIJAAAAAABc4exZqUOHYH33\nnV0lSrg1b55TefMyRPzv/PD7Or2yooN+TzimKnmqakKtqbo3033+juVXFE8AAAAAAMBr/36LWrQI\n1r59NtWp49LkyU6Fhvo7Vfrm9rj1wabhev/nYbLIon6PvaPu5XrKZrX5O5rfUTwBAAAAAABJ0vff\n29SuXbDOnrWoa9dk9e+fJBvdyV/6/cIxvbqyo9b//r3uD82rSbVn6PH7Kvg7VrpB8QQAAAAAADR3\nboDeeitQFos0erRTL73k8nekdO+bg1+p+6ouOpN0Rk8XbKRR1cYpS1BWf8dKVyieAAAAAAC4i7nd\nUkREoKZMcShbNo+ioxP1xBNuf8dK15LcSRq4/h1N2z5ZgbZADXvyA7Up2V4Wi8Xf0dIdiicAAAAA\nAO5S589LnToFa9Uqu4oWTR0iXqAAQ8T/ym9nf1Wn5e20PX6rimYtpim1o1UyRyl/x0q3KJ4AAAAA\nALgLHTpkUcuWwdq926bq1V2aNs2pzJn9nSp9+2j3Ar31XS9ddCWoRYnWGlR5qDIFZPJ3rHSN4gkA\nAAAAgLvMhg02tW0bpFOnrOrUKVkREUmy0xDc0IXk8+rzXU8t2vuRwhyZNbV2tJ4p0tTfsTIEfq0A\nAAAAALiLLFxoV69eQfJ4pBEjEtW6dYq/I6VrW09uVqcVbXXgz/0ql7O8JteeqQL3PODvWBkGxRMA\nAAAAAHcBj0eKjHRo3LhA3XOP0YwZTj35JEPEb8QYo6nbJmrgD+8qxZOibg+/rr6P9ZfD5vB3tAyF\n4gkAAAAAgDvchQvSq68G6euvA1SwoEfz519UoUIMEb+ReGe8esS8ohWHvlGO4HCNrzlFNfLV8nes\nDIniCQAAAACAO9jRo6lDxHfssKlKFZdmzHAqSxZ/p0q/1h1bq1dWdtAfCcf15P3VNaHWVOUKyeXv\nWBmW1d8BAAAAAACAb/z8s1V164Zoxw6bWrVK1sKFlE434vK4NHTjYD27tIHiLp5U/woD9HHDzyid\n/iV2PAEAAAAAcAdavNiuHj2ClJIiDRmSqPbtU2Sx+DtV+nT0/BG9srKDfjz+g/KF5dfk2jP0yL2P\n+TvWHYHiCQAAAACAO4jHIw0f7tAHHwQqLMxo9mynatRgiPiN/Hf/l3p99as6m3RWjQo10fvVxuie\nQLaFpRWKJwAAAAAA7hAXL0rduwfp888DlD+/R/PmOVWsmMffsdKlRFeiItb/RzNjpynIFqSRVceo\n5YNtZGFbWJqieAIAAAAA4A5w/LhFrVoFa+tWmypUcCk6OlHZs/PJddez9/QedVrRVjtPxap4thKa\nWmeWimcr4e9YdySGiwMAAAAAkMFt3Zo6RHzrVptefDFFixY5KZ2uwxijD3fNU51FVbXzVKxaPdhO\nXzddTenkQ+x4AgAAAAAgA/viC7u6dQtSYqL03nuJevVVhohfz/nkc+r97eta/OsiZXbcoxl156hh\noWf8HeuOR/EEAAAAAEAGZIw0apRDQ4cGKlMmozlznKpblyHi17P5xCZ1WtFWh84d1CO5HtPk2jOU\nL3N+f8e6K1A8AQAAAACQwSQmSq+/HqTFiwN0//0ezZ3rVMmSDBG/msd4NGnLeEX+GCG3x60e5Xqp\nz6NvK8AW4O9odw2KJwAAAAAAMpCTJy1q3TpYmzbZ9Mgjbs2a5VTOnMxzulrcxTi9FtNZMYdXKmdI\nLk2oOVVV81b3d6y7DsUTAAAAAAAZRGysVS1bBuvYMauaNk3RqFGJCgryd6r057uja/Tqyo46efGE\nquetqfE1pyo8JNzfse5KFE8AAAAAAGQAX39tU5cuwbp40aK3305Sjx7JDBG/Soo7RSN+itKYX96X\nzWrTe08M1isPdZPVYvV3tLsWxRMAAAAAAOmYMdKECQEaNChQQUHSjBlONWzo8nesdOfwuUPqsqK9\nfj6xUfkzF9CU2jNVLtcj/o5116N4AgAAAAAgnUpKknr3DtLChQG6777UIeJlyjBE/Gpf/LZUb6zu\npnPJf6pJ4aYaUXW0Mgfe4+9YEMUTAAAAAADp0qlTFrVtG6QNG+x66CG35sxx6t57GSJ+OafLqXe+\n76c5O2cq2B6s0dUn6MXiLWThGsR0g+IJAAAAAIB0Zs8eq15+OViHD1vVqFGKxo5NVEiIv1OlL7tP\n71Ln5W216/ROPZi9lKbWjlbRbMX8HQtXYboWAAAAAADpyKpVNj31VIgOH7bqzTeTNHUqpdPljDGa\nu3OW6i6qpl2nd6ptqQ76qukqSqd0ih1PAAAAAACkA8ZI06YF6N13AxUQIE2Z4lSTJgwRv9y5pD/V\na00PLf1tse4JzKKJtabr6YIN/R0Lf4HiCQAAAAAAP0tJkfr1C9ScOQ6Fh3s0Z45T5cszRPxyP/+x\nUV1WtNfh84f02L0VNLn2DN0fltffsfA3KJ4AAAAAAPCjM2ekDh2CtXatXSVLujVvnlN58jBE/BKP\n8Wj85jEaunGQ3B63epbvrTcf7Se7lUojI+CnBAAAAACAn+zbZ1GLFiHav9+q+vVTNGFCokJD/Z0q\n/Th58aS6ruyob4+uVq6QezWp9nRVzvOkv2PhFlA8AQAAAADgB99+a1OHDsH680+LundP0ttvJ8vK\nR4B5rT68St1WdVac86Rq5aujsTUnK0dwDn/Hwi2ieAIAAAAA4DabNStA/foFymaTxo1zqnlzhohf\nkuJO0dCNgzVu8ygFWAM0sNIQdS7TVRaLxd/R8A9QPAEAAAAAcJu4XNK77wZq+nSHsmf3KDo6URUq\nuP0dK904dO6guqxop00nftYD9xTU1NrRKpvzYX/Hwr9A8QQAAAAAwG1w7pzUsWOwVq+2q3hxt+bO\ndSp/foaIX7J032L1XNNd55PPqWmR5zWi6iiFOsL8HQv/EsUTAAAAAAA+duCARS1bBmvvXptq1XJp\nyhSnwuhUJEkXUy7qnXV9NXfnLIXYM2lsjUlqXuwlLq27Q1A8AQAAAADgQ+vX29S2bbDOnLGoc+dk\nRUQkyWbzd6r0YeepHeq8vK32nNmtUjnKaGrtaBXOWsTfsZCGKJ4AAAAAAPCRBQvs6t07SMZI77+f\nqJYtU/wdKV0wxmj2jpl6d10/JboT1bF0F73zxEAF2YP8HQ1pjOIJAAAAAIA05nZLgwYFauJEh7Jm\nNZo506lKlRgiLklnE8+o55ru+nL/UmUNzKqpdWap3gNP+TsWfITiCQAAAACANHThgtSlS7CWL7er\ncGG35s1zqmBBhohL0sbjP6rLinY6euGInshdSZNqTVfu0Dz+jgUfongCAAAAACCNHDliUYsWwdq1\ny6aqVV2aPt2pe+7xdyr/c3vcGrd5lIZtjJSRUe9H+6ln+T6yWRl2daejeAIAAAAAIA1s3GhVmzbB\nio+3ql27ZA0enCQ7f+vWiYQ/9OqqTlp7dI3uy5Rbk2pNV8U8lf0dC7fJX/4ROH36tObPn6+YmBgd\nOnRIVqtV+fLlU82aNfXiiy8qW7ZstysnAAAAAADp1scf29WzZ5DcbikqKlHt2zNEXJJWHVqu12K6\nKN4Zr7oF6mtMjYnKFpTd37FwG92weJo/f76WL1+uOnXqaOjQocqTJ4/sdruOHj2qH3/8Ud26dVO9\nevXUqlWr25kXAAAAAIB0w+ORoqIcGjMmUJkzG02b5lT16gwRT3YnK3LDAE3aOk4Oq0ORlYepQ+ku\nslgs/o6G2+yGxVOuXLk0e/bsa75fuHBhFS5cWC+//LK++eYbn4YDAAAAACC9SkiQunUL0rJlASpQ\nwKP5850qUsTj71h+d+DP/eq8vK22xG1WoSyFNbV2tEqHl/V3LPiJ9UZ31KpVy/t1cnKyJOnQoUNa\ns2aNPJ7UP0h169b1cTwAAAAAANKf33+3qFGjEC1bFqBKlVz6+usESidJi3/9RDU/rqItcZvVvNhL\nWtHsO0qnu9zfjjkbP368Dh8+rNdff10vv/yyChcurJUrV2rw4MF/u7gxRhEREdqzZ48cDociIyOV\nN29e7/3btm3TsGHDJEk5cuTQiBEj5HA4/sXLAQAAAADAtzZvtqply2CdPGlVixbJGjo0SXf7X2UT\nUhL09tre+nD3PGUKCNWEmlPVrNgL/o6FdOCGO54uiYmJ0eDBg/Xll1+qUaNGmjVrlnbu3HlTi69c\nuVLJyclauHChevXqpaioqCvuf/fddzV06FDNnz9fVapU0e+///7PXgUAAAAAALfB0qV2NW4covh4\niwYOTNT771M6xcZvV51PqurD3fNUJvwhrWr2HaUTvP62ePJ4PHI4HFq9erWqVq0qj8cjp9N5U4tv\n2rRJVapUkSSVLVtWsbGx3vsOHDigLFmyKDo6Wi1bttSff/6pAgUK/LNXAQAAAACADxkjjRjhUMeO\nwbLbpblznerSJUV386xsY4xmbJ+q+p/W0K9n96pzmVe17NkVKpilsL+jIR352+LpiSeeUIMGDZSS\nkqJHH31ULVq0UI0aNW5q8QsXLigsLMx72263e+dDnTlzRlu2bFHLli0VHR39f+zde5iN9f7/8ec6\nz6yZRHIoVBSlHUnlGJEGE5VRJl8lI6UQ1aTID1MTQ2VK5dCwUVRfg0gZpxzaI/Zg24kUu53kWOTY\nzKxZ598ffbdde2Mo99xrzXo9rmuuK2tm7nnN3ryve73vz+f9Yd26daxfv/6M17vjDli71nZWP1tE\nRERERETkfPB44NFH43jlFReXXRYiL6+YpKTYPrnuaMkR0pbez3NrBpPgSOC9O+bw4i1jcdlcZkeT\nCFPqjKchQ4bQs2dPqlevjtVqZcSIEdSvX/+sLp6YmEhRUdHJP4dCIazWX3pdFStW5LLLLqN27doA\ntGrVii+//JKmTZue9npLlsCSJW66dIGXX4a6dc8qhohIqapUuaD0LxIROUeqLSJiBNWWsnXgANx7\nL2zcCC1bwvz5VqpWTTA7lqk+2/0ZPT7owZ4Te2hzRRveTXmXGhVqmB1LIlSpjafjx48zadIkdu/e\nzeuvv87MmTMZOnQoF154YakXb9y4MatXr6Zjx45s3ryZevXqnfxcrVq1KC4uZs+ePdSqVYtNmzZx\n7733nvF6GzfCwIEBPvzQzqJFYfr08ZOe7qVSpbP4TUVETqNKlQs4dOhns2OISDmj2iIiRlBtKVtb\nt/4yRHz/fiupqX6ys0uwWODQIbOTmSMYCjL+7+N4ZeMv85uHNhnOE42fxua16e9llDOyoV3qVrsR\nI0bQoEEDjh07RkJCAlWrVuWZZ545q4snJSXhdDrp3r07Y8eO5bnnnmPRokXMnTsXh8PB6NGjSU9P\np1u3blxyySXceuutZ7zeTTfBwoUepk/3ULNmmJwcJ02bJjJligOf7+x+YREREREREZHS5OXZufNO\nNwcOWBg+3Mubb5bgiuFdZAcK93PvR3fx0obRXJJwKR92WUL6Tc9is2ocjpyZJRwOh8/0BV27dmX+\n/Pl06dKFDz/8EIC77rqLjz76qEwC/qd/dVG9Xpg+3UF2tosTJyzUrh0iI8NLcnIgpoe7ici505ND\nETGCaouIGEG1xXjhMLz5ppNRo1y43WEmTSrhjjsCZscy1fJdSxi0qh9HSo6QXLsz49tOoFLcRWbH\nkvPI1BVPNpuNn3/+Gcv/dXN27dp1ck6TmVwu6NfPz/r1RTz8sI/duy2kpcWTkhLPli3m5xMRERER\nEZHo4vXC44/HMWqUi0svDfHxx8Ux3XTyBr2M+GwoDyy+jyJ/EWNajePtju+p6STnpNQVT/n5+bz6\n6qscOHCAG2+8kc2bN5OVlUWbNm3KKOJvna67/803VjIzXSxbZsdiCZOaGmDYMC+XXHLGX09ERE8O\nRcQQqi0iYgTVFuMcOvTLYoaNG200bhzknXc8VKsWu+8ndx77J30/eYgthzZzVcW6TGn/Ntdd3MDs\nWGIQI1c8ldp4Ajhy5AhbtmwhGAxy/fXXU6FCBZxOp2GhzqS0IpufbyMjw8W2bTbc7jD9+/sYMMBH\nQmwfOiAiZ6AbOBExgmqLiBhBtcUYX331yxDxPXuspKT4GT++hPh4s1OZZ+6O2Tybn06Rv5Ae1/Rk\ndKuXSXDoTXV5ZupWu/vuu4+LLrqINm3a0K5dOy666CLuuecewwL9Ua1bB1mxopjx4z0kJoYZN85F\n8+YJzJ5tJxQyO52IiIiIiIhEkuXLbXTq5GbPHivPPuvlrbdit+lU6C/k8ZWPMmBlXyxYeCtpGuNv\nm6imk/whp208Pfjgg1xzzTV88cUXXHPNNdSvX5/69evTsGFDateuXZYZz5nNBj16BCgoKCI93cvx\n4xYGDYonKcnN2rWauC8iIiIiIhLrwmGYPNlBz57xBIMwdaqHwYN9MXtY1dZDX3D7nFbM2fG/NKpy\nAytT19C1bjezY0k5UOpWu1GjRjF8+PCyylOq37OsdN8+C1lZLubOdQCQnOwnI8NLnTqxu19XRP5N\nS9ZFxAiqLSJiBNWW88Png6FDXbz7rpNq1ULMnOnhhhtic4tMOBxm6pbJZP51JL6Qj/6NBjGs6Uic\nNr0oBaUAACAASURBVHPG64g5TJ3xtGDBgpMn2v1aly5dDAt1Jn+kyG7ebGXkSBcFBXbs9jB9+vhJ\nT/dSqdJ5DCgiUUc3cCJiBNUWETGCassfd+QIPPRQPOvW2WnQIMisWR4uvTQ2FyUc9hzmydX9WbZr\nCRfHX8ybt71Fu8vbmx1LTGBk48le2hds2LDh5H/7/X42bdrETTfdZFrj6Y9o1CjEwoUe8vLsZGa6\nyMlxkpvrYPBgL2lpfkyaly4iIiIiIiJl4JtvrNx/fzy7dlnp1MnPhAklMXsQ1bp9n9FvxcMcKNpP\nq5ptmNRuCtUSqpsdS8qhszrV7teOHTvGU089xYwZM4zKdEbnq7vv9cL06Q6ys12cOGGhdu0QGRle\nkpMDMbunVyRW6cmhiBhBtUVEjKDa8vutXm3jkUfiOXHCwlNPeRkyxIe11OO2yp9AKMCrf3uZVze9\njAULQ5sM5/EbnsRm1TzkWGbqqXb/ye12s2/fPiOylCmXC/r187N+fREPP+xj924LaWnxpKTEs2VL\nDFYfERERERGRcmraNAc9esRTUgITJ3p47rnYbDrt+3kvXRd2ZtzfxlIjsSYLuyzliRufVtNJDFXq\nVruePXuenPEUDofZu3cvrVu3NjxYWalcOUxWlpfevf1kZrpYtsxOUpKN1NQAw4Z5ueSS2NzrKyIi\nIiIiEu38fhg+3MWMGU4uvjjEO+94uPnm2BwivvS7xTyxqh9HvUfpXOduXm3zBhXjNPBYjFfqVrtf\nz3iyWCxUqlSJq666yvBgp2P0stL8fBsZGS62bbPhdofp39/HgAG+mN33KxILtGRdRIyg2iIiRlBt\nOXvHjsHDD8eTn2+nfv0g777roVat2FtYUBIoIfOvI/jz1hzibHG8eMtYHry29ykPEZPYZepWuyZN\nmlCpUiWs/7cO8ejRo2zcuNGwQGZr3TrIihXFjB/vITExzLhxLpo3T2D2bDuh2GyMi4iIiIiIRJWd\nOy3ccYeb/Hw77dsHyMsrjsmm0z+PfkPyB+3489Ycrq50Dcvu/ZRef3pITScpU6WueMrMzGTVqlXU\nqlXr399ksTBz5kzDw51KWXb3CwthwgQnkyc78XgsNGgQJDPTS8uWwTLLICLG05NDETGCaouIGEG1\npXSffWbjoYfiOXbMwoABPoYP92KLsRFG4XCY3B3vMzR/MMWBInpem8aLLcfidrjNjiYRysgVT6U2\nntq3b89HH31EXFycYSHOhRlFdt8+C1lZLubOdQCQnOwnI8NLnTqx1zEXKY90AyciRlBtEREjqLac\n2axZDoYMcWGxwCuvlNCjR8DsSGWu0Pczz/zlKT74Zg4XOCvwaps3uPuqrmbHkghn6la7WrVqUUpv\nqtyrUSPMxIklLF9eRLNmAZYscXDLLQmMGOHi6FGz04mIiIiIiMS2YBBGjHDx9NNxVKgQZt48T0w2\nnTYf/Du3zbmFD76Zw43VbmJV6mdqOonpSj3V7sILL6RTp07ccMMNOJ3Ok6+PGTPG0GCRqFGjEAsX\nesjLs5OZ6SInx0luroPBg72kpfn51f88IiIiIiIiUgZ+/hn69o1n5Uo79eoFmTXLQ+3asbV4IhQO\nkfPFJEYVZOAP+Rl4w1MMbTIch81hdjSR0rfaLViw4JSvp6SkGBKoNJGyrNTrhenTHWRnuzhxwkLt\n2iEyMrwkJwfQnDaR6KIl6yJiBNUWETGCastvff+9hZ4949m+3UbbtgGmTvVQoYLZqcrWT56fGLTy\nMVbsXs7F8VWY2G4KbS9rZ3YsiTKmzHg6dOgQVapUYf/+/af8xksvvdSwUGcSaUX28GEL2dlOZsxw\nEAxaaNEiQGaml4YNdQSeSLTQDZyIGEG1RUSMoNrybwUFNnr3juPwYSuPPOLjhRe82Evd01O+rNn7\nF/qveIQfi3+gTa3bmNBuClXdVc2OJVHIlMbTo48+Sk5ODrfddhsWi+U3c54sFgsrV640LNSZRGqR\n/eYbK5mZLpYts2OxhElNDTBsmJdLLomtJZ4i0Ug3cCJiBNUWETGCassvZs+28/TTcYRCMGbML6NP\nYkkgFGDcxjG8tmkcNquN55qOZECjQVgtpY5xFjklU0+1izSRXmTz821kZLjYts2G2x2mf38fAwb4\nSEgwO5mInI5u4ETECKotImKEWK8toRCMHu3kzTddXHhhmGnTPLRuHTQ7Vpna+/MeHvukDxt+KOCy\nCy4np/10bqx2s9mxJMqZ2njauXMnc+bM4fjx47953azh4tFQZINByM21k5Xl4uBBK9Wrhxg2zEtq\nagCrGtAiESfWb+BExBiqLSJihFiuLYWF0L9/HEuXOqhTJ8R77xVz5ZVRtY7iD8vb+TFPrh7Ace8x\n7r6yK9ltXqeC60KzY0k5YGTjqdQ2yOOPP05iYiJNmjT5zYecns0GPXoEKCgoIj3dy/HjFgYNiicp\nyc3atTaz44mIiIiIiESVvXst3Hmnm6VLHbRqFWDp0qKYajp5Ah6G5KfTe+n9+IJeXm3zJlPaz1DT\nSaJCqaPXKlSowOOPP14WWcqdxEQYOtRHz55+srJczJ3rICXFTXKyn4wML3XqxE6hFBERERER+T3+\n9jcrvXrFc+iQlQcf9DFmjBeHw+xUZecfR3bwyPI0vj6yjfoXXcuU9m9z9UXXmB1L5KyVutUuNzeX\n/fv306xZM+y/OiLg5pvN2UMazctKN2+2MnKki4ICO3Z7mD59/KSne6lUyexkIrEtlpesi4hxVFtE\nxAixVlvmz7fzxBNx+P0wapSXPn38WCxmpyob4XCY97+exf/77FmKA8X0+lMfMltmEW+PNzualENG\nbrUrdcXThg0b2Lp1K3//+99PvmaxWJg5c6ZhocqrRo1CLFzoIS/PTmami5wcJ7m5DgYP/uUUBqfT\n7IQiIiIiIiLmC4Xg5ZedvPqqiwsuCPPOOx5uuy12hoif8B7nmb88yYJ/fsCFropMa5fDnVfebXYs\nkd+l1BVPHTp0YNmyZWWVp1Tlpbvv9cL06Q6ys12cOGGhdu0QGRlekpMDMdPBF4kUsfbkUETKhmqL\niBghFmpLcTEMGhTHRx85uPzyEO++6+Hqq0Nmxyozf//xb/T95CF2n9jFzdWb8lbSNGpdcJnZsaSc\nM3W4eL169di+fbthAWKVywX9+vlZv76Ihx/2sXu3hbS0eFJS4tmyRUffiYiIiIhI7DlwwMLdd7v5\n6CMHzZoFWLq0OGaaTqFwiAmfv07nBe3Zc+J7nrpxMAu7LFHTSaJeqSueunTpwo4dO6hSpQoOh4Nw\nOIzFYmHlypVllfE3ymt3/5tvrGRmuli2zI7FEiY1NcCwYV4uuUQDyEWMFgtPDkWk7Km2iIgRynNt\n+eILKz17xvPDD1b+53/8vPJKScyMIzlYfJCBKx9l9Z6VVHVXY9LtU2lds43ZsSSGGLniqdTG0759\n+075eo0aNQwJVJryWmT/JT/fRkaGi23bbLjdYfr39zFggI+EBLOTiZRf5fkGTkTMo9oiIkYor7Xl\n44/tPP54HCUlMHKkl/79Y2eI+F/2rKb/ikc45DlIu8uSeOO2t6jirmJ2LIkxpjaeIk15LLL/KRiE\n3Fw7WVkuDh60Ur16iGHDvKSmBrBqF57IeVdeb+BExFyqLSJihPJWW8JheO01J2PHukhICPPWWx46\ndIiNIeL+oJ+XNozmzc9fw2618/+aPc9j1w/AatGbPil7ps54krJns0GPHgEKCopIT/dy/LiFQYPi\nSUpys3atzex4IiIiIiIif1hJCfTrF8fYsS5q1gyxaFFxzDSddp/4nrs+7Mgbn7/KZRUuZ1HKcvo3\nGqimk5RL+lsdwRITYehQH+vWFdGtm5+tW22kpLjp1SuOnTtjZN2piIiIiIiUOwcPWkhJcTN/voOb\nbgqydGkxf/pTbAwR/+ifC7htzi1s+nEjXet2Y1XqZ9xQ7UazY4kYptStdoFAgM8++4xjx4795vUu\nXboYGux0ytOy0nO1ebOVkSNdFBTYsdvD9OnjJz3dS6VKZicTiW7lbcm6iEQG1RYRMUJ5qC1ffvnL\nEPF9+6zcc4+f114rIS7O7FTG8wQ8jPjsOWZ+NR233c3Y1tncd3UPLLEyzEoimqkznp544gn279/P\nlVde+Zt/EGPGjDEs1JlEe5H9o8JhyMuzk5npYtcuKxUrhhk82Etamj9mTnwQOd/Kww2ciEQe1RYR\nMUK015alS2089lg8xcUWhg3z8sQTvpgYIr79yNf0XZ7G9iNfc23l65ja/m3qVqpndiyRk0xtPHXs\n2JGlS5caFuBcRXORPZ+8Xpg+3UF2tosTJyzUrh0iI8NLcnIgJgq3yPkU7TdwIhKZVFtExAjRWlvC\nYZg40cGLL7qIi4MJE0q4886A2bEMFw6HmfXV2wz/bAglwRL6NOhLRvNRxNljYImXRBVTh4tfeeWV\nHDx40LAA8vu4XNCvn5/164t4+GEfu3dbSEuLJyUlni1bNLpLREREREQig9cLTzwRR2ZmHNWrh/n4\n4+KYaDod9x7jkeVpDP7LE8TZ43i74/uMaTVOTSeJOfbSvqCkpISOHTtSr149nL/ayzVz5kxDg8nZ\nqVw5TFaWl969/WRmuli2zE5Sko3U1ADDhnm55JIzLmgTERERERExzOHDFnr3jqOgwE6jRkFmzvRQ\nvXr5f4/ytx828OgnD7Hn5900vaQ5b90+jRoX1DQ7logpSt1qt2HDhlO+3qRJE0MClSYal5WWpfx8\nGxkZLrZts+F2h+nf38eAAT4SEsxOJhK5onXJuohENtUWETFCNNWWHTus3H9/PLt3W7nrLj9vvFGC\n2212KmOFwiEmfD6eMetfJBQOkX7Tszx90xDs1lLXfIiYypStdtu2bQPAYrGc8kMiU+vWQVasKGb8\neA+JiWHGjXPRvHkCs2fbCcXG6aQiIiIiImKylStt3HGHm927rQwe7GXKlPLfdPqx+EdSP05hVMHz\nVHFXZf7dixjS5P+p6SQx77QrnoYPH86oUaPo2bPnf3+TxWLaVrto6e5HgsJCmDDByeTJTjweCw0a\nBMnM9NKyZdDsaCIRJZqeHIpI9FBtEREjRHptCYdh6lQHI0e6cDjgjTdKSEkp//OcVu1eweMrH+Un\nzyHaX96R12+bTOX4ymbHEjlrpp5qF2kiuchGqn37LGRluZg71wFAcrKfjAwvdepE1f/1IoaJ9Bs4\nEYlOqi0iYoRIri1+Pzz3nIuZM51UqRJi5kwPN95Yvrdd+II+xqx/kYmbX8dhdZDR/EUeadhPu4Qk\n6piy1W7QoEGsXbv2tN/46aefMnDgQENCyflVo0aYiRNLWL68iGbNAixZ4uCWWxIYMcLF0aNmpxMR\nERERkWh39Ch07x7PzJlO/vSnIMuXF5f7ptOu499x14IOTNz8OnUuvJIl96yk7/X91XQS+Q+nXfFU\nVFTEhAkT+PTTT7nmmmuoXr06NpuNffv28eWXX3L77bczYMAAEhMTyzRwpHb3o0U4DHl5djIzXeza\nZaVixTCDB3tJS/Pzq0MLRWJKJD85FJHopdoiIkaIxNry7bcW7r/fzc6dVpKT/UycWEIZv00scx9+\n8wFP/+UJfvadoFu97rzUOptEp3ErRkSMZupWu8LCQgoKCvj++++xWq3UqlWLFi1a4DZpMlykFdlo\n5fXC9OkOsrNdnDhhoXbtEBkZXpKTA6hBL7EmEm/gRCT6qbaIiBEirbbk59vo0yee48ctDBrkZdgw\nH9bT7quJfkX+IoZ/NoT3vp6J257AS62zue+aHmbHEvnDNOPpVyKpyJYHhw9byM52MmOGg2DQQosW\nATIzvTRsWL6XxYr8WqTdwIlI+aDaIiJGiKTa8vbbDp57zoXNBtnZJdx3X/keIv7V4W30XZ7GP47u\noMHF1zOl/XSurFjX7Fgi54UpM54kNlSuHCYry0t+fjEdOgRYt85OUpKbgQPjOHBAS59EREREROS3\nAgEYNszFs8/GUbFimHnzPOW66RQOh5nx5Z/pMK8N/zi6g74N+7H4nhVqOomcJTWeBIC6dUPMmuVh\n3rxirr02RG6ug+bNE3j5ZSdFRWanExERERGRSHDiBNx/fzx//rOTa64JsnRpMc2aBc2OZZhjJUfp\nvfQBhuSnk+BIYNYduYy65SVcNpfZ0USixlk1ngoLCzlw4AD79+8/+SHlU+vWQVasKGb8eA+JiWHG\njXPRvHkCs2fbCWn3nYiIiIhIzPruOwt33OFm9Wo7t98eIC+vmMsvj6rJLedk/YECbptzC4u/+5jm\nl7ZkVepaOlyRbHYskahT6oynt956iylTplCxYsV/f5PFwsqVKw0PdyqRsp85FhQWwoQJTiZPduLx\nWGjQIEhmppeWLcvvEw2JTZE0K0FEyg/VFhExglm15a9/tdG7dxxHjlh59FEfzz/vxWYr8xhlIhgK\n8sbfX+XljVmECTP4pqE8deMz2Kzl9BcWweTh4rfffjtz5szhoosuMizEudANXNnbt89CVpaLuXMd\nACQn+8nI8FKnTvl9uiGxRW8ORcQIqi0iYgQzasv779t55pk4wmF46SUvPXv6y/Tnl6Ufig7Qf8Uj\nfLYvn0sTajA56c80v7Sl2bFEDGfqcPFLLrmECy+80LAAEvlq1AgzcWIJy5cX0axZgCVLHNxySwIj\nRrg4etTsdCIiIiIiYoRgEJ5/3sWTT8aTmAhz53rKddNpxffLaJvbgs/25dPxijtYdd9najqJnAf2\n0r7giiuuoEePHjRt2hSn03ny9ccff9zQYBJ5GjUKsXChh7w8O5mZLnJynOTmOhg82Etamp9f/fUQ\nEREREZEoVlgIjz0Wz/Lldq66Ksi773rK7Y4HX9DHqILneeuLCTitTsa0eoWHruuLxaJTvkXOh1JX\nPFWrVo1WrVr9pukksctigc6dA6xZU8QLL5QQCsHw4XG0apXA4sV2zrxxU0REREREIt2ePRY6dXKz\nfLmdW28NsGRJcbltOu08/i2d5ifx1hcTuKpiXZbcu4o+DR5V00nkPCp1xhPAkSNH+OKLLwgGgzRq\n1IiLL764LLKdkmYlRJbDhy1kZzuZMcNBMGihRYsAmZleGjbUEXgSPTSHRUSMoNoiIkYwurZs2GAl\nLS2en36y8tBDPkaN8mIvdZ9MdJr3j1ye+ctTFPkL6X7N/WS1eoVER6LZsURMYeqMpzVr1nD33Xcz\nf/58FixYwF133cXq1asNCyTRpXLlMFlZXvLzi+nQIcC6dXaSktwMHBjHgQN6SiAiIiIiEi3mzrXT\ntaubo0ctjBlTwtix5bPpVOgvZNCqfvRf8QgAk26fyhu3TVbTScQgpa546tq1K6+//jq1atUCYM+e\nPTz++OMsXLiwTAL+Jz05jGz5+TYyMlxs22bD7Q7Tv7+PAQN8JCSYnUzk9LQqQUSMoNoiIkYworaE\nQjB2rJPx411UqBBm6lQPbdsGz+vPiBRbf9rCo8t7889j33B9lRvIaT+dOhdeaXYsEdOZuuIpEAic\nbDoB1KpVi1BI26jk1Fq3DrJiRTHjx3tITAwzbpyL5s0TmD3bjv7aiIiIiIhElqIi6NMnjvHjXVxx\nRYglS4rLZdMpHA4zbWsOyfNu45/HvuGx6x8nr+snajqJlIFSG0+XXnopb7/9NoWFhRQWFvL2229T\no0aNssgmUcpmgx49AhQUFJGe7uX4cQuDBsWTlORm7Vqb2fFERERERATYv9/CXXe5yctz0LJlgKVL\ni6hbt/w9LT5ScpheS3vw3JpnuMB5Ae93mktmyyycNh2gJVIWSm08jR49ms2bN3P77bfTrl07Pv/8\nczIzM8sim0S5xEQYOtTHunVFdOvmZ+tWGykpbnr1imPnTs1/EhERERExy+efW+nQwc3WrTYeeMBH\nbq6Hiy4yO9X599f9a7kt9xaWfpfHLTVas/q+ddx+eQezY4nElLM61S6SaFZC9Nq82crIkS4KCuzY\n7WH69PGTnu6lUiWzk0ms0xwWETGCaouIGOF81JaFC+0MHBiHzwfPP+/l0Uf9WMrZc+FgKMirm14m\n+28vYcHCszcPY1DjdGxW7cAQORUjZzydtvH06KOPkpOTw2233YblFFVo5cqVhoU6E93ARbdwGPLy\n7GRmuti1y0rFimEGD/aSlubHqZWuYhK9ORQRI6i2iIgR/khtCYdh3Dgnr7ziIjExTE6Oh6Sk8jfP\naX/hPvqveIR1+z+jZmItJidNo+klzcyOJRLRTGk8HTx4kKpVq7Jv375TfuPZzHkKh8M8//zz7Nix\nA6fTyejRo38zqPztt99m3rx5XPR/azozMzO54oorznhN3cCVD14vTJ/uIDvbxYkTFmrXDpGR4SU5\nOVDunrZI5NObQxExgmqLiBjh99YWjweefDKOBQscXHZZiFmzPNSvX/7mOS3ftYRBq/pxpOQId9S+\nk/FtJ1AxTlssREpjyql2VatWBWDs2LHUqFHjNx/Dhg07q4uvWLECn8/H7NmzefrppxkzZsxvPr9t\n2zZefvllZs6cycyZM0ttOkn54XJBv35+1q8v4uGHfezebSEtLZ6UlHi2bCl19JiIiIiIiJylH3+0\n0KWLmwULHDRpEmDJkuJy13TyBr0M/2wIDyy+jyJ/ES+1fpUZHd9V00kkAthP94kBAwawfft2Dh48\nSLt27U6+HgwGqV69+lldfNOmTbRq1QqA66+/ni+//PI3n9+2bRs5OTkcOnSINm3a0Ldv39/zO0gU\nq1w5TFaWl969/WRmuli2zE5Sko3U1ADDhnm55JKoGkEmIiIiIhJRtm610rNnPPv3W0lN9ZOdXYLL\nZXaq8+vbY9/Qd/lDbP3pC+pVupqcpBn86eLrzI4lIv/ntI2nl156iWPHjjF69GiGDx/+72+w26lc\nufJZXbywsJALLvj3ci273U4oFMJq/WVFS6dOnbj//vtJTExkwIAB/OUvf+HWW2/9vb+LRLG6dX9Z\n7pufbyMjw0VuroOPP7bTv7+PAQN8JCSYnVBEREREJLrk5dkZMCAOjweGD/cycKCv3I21yN3+PkPy\nn6Y4UMT99R9k1C0vkeDQmweRSHJWp9p99dVXFBcXEw6HCQaD7N27l3vvvbfUi48dO5ZGjRrRsWNH\nANq0acOnn3568vOFhYUkJiYC8P7773P8+HH69ev3O38VKS+CQXjnHfh//w9++AEuvRRGj4YHHwSr\nduGJiIiIiJxROAwvvQTPPQduN7z3HnTpYnaq8+tn788MWDyAWVtmcYHzAqbcOYXu13U3O5aInMJp\nVzz9y5AhQ/j88885fvw4derUYfv27TRu3PisGk+NGzdm9erVdOzYkc2bN1OvXr2TnyssLKRz584s\nWbKEuLg4CgoKzuqaGtIZG+68E9q2hQkTnEye7KR3bwuvvhokM9NLy5bl7+QNMZcGAIuIEVRbRMQI\npdUWrxfS0+OYO9fBpZf+squgQYMQhw6VYUiDbTm0mb7Le7Pz+Lc0rnojbyVN54oLa6vmivwBpgwX\n/5eNGzeSl5dHhw4dePHFF5kzZw4+n++sLp6UlITT6aR79+6MHTuW5557jkWLFjF37lwSExNJT0+n\nZ8+ePPDAA9SrV4/WrVv/4V9Iyo/ERBg61Me6dUV06+Zn61YbKSluevWKY+fOcrZGWERERETkDzp0\nyELXrm7mznXQuHGQZcuKadCg/AwRD4fDTPliEskftGPn8W8Z0OgJPkpZxhUX1jY7moicQalb7bp3\n787s2bN55513uPjii+nUqRNdu3Zl/vz5ZZXxN9TFjl2bN1sZOdJFQYEduz1Mnz5+0tO9VNJBFfIH\naVWCiBhBtUVEjHC62vLVV78MEd+zx0pKip/x40uIjzchoEEOew7zxKp+LP9+KRfHV2FCuxxuu+x2\ns2OJlBumrniqVq0aOTk53HDDDcyePZu8vDyKi4sNCyRyOo0ahVi40MP06R5q1gyTk+OkadNEpkxx\ncJaL8EREREREyp3ly2106uRmzx4rzz7r5a23ylfTae2+NbSd04Ll3y+ldc22rL5vnZpOIlGk1MbT\n6NGjqVmzJg0bNqR9+/YsWrSI559/vgyiifw3iwU6dw6wZk0RL7xQQigEw4fH0apVAosX2yl9VL6I\niIiISPkQDsPkyQ569ownGISpUz0MHlx+Tq4LhAKM3TCKrgs7c6j4IMObPc+cOxdQzV3N7Ggicg5K\n3Wr30EMPMX369LLKUyotWZdfO3zYQna2kxkzHASDFlq0CJCZ6aVhw/Kzl12Mp+0wImIE1RYRMcK/\naovPB0OHunj3XSfVqoWYOdPDDTeUn3vgfT/v5bEVfVh/4K/UuuAy3kqaxs3Vm5odS6TcMnWrXUlJ\nCQcOHDAsgMgfUblymKwsL/n5xXToEGDdOjtJSW4GDozjwIFy8qhHRERERORXjhyB1NR43n3XSYMG\nvwwRL09NpyXf5dF2TgvWH/grd12ZwqrUz9R0Eolipa546tixI99//z2VK1fG5XIRDoexWCysXLmy\nrDL+hp4cypnk59vIyHCxbZsNtztM//4+BgzwkZBgdjKJZFqVICJGUG0RESMcPnwByckhdu2y0qmT\nnwkTSsrNvW5JoIQX/jqcaVunEGeLY9QtL9Hz2jQs5WXvoEgEM3LFU6mNp3379p3y9Ro1ahgSqDS6\ngZPSBIOQm2snK8vFwYNWqlcPMWyYl9TUANZS1/hJLNKbQxExgmqLiJxvq1fb6NvXzfHj8NRTXoYM\n8ZWb+9tvjv6Dvst7s+3wVq65qD45STOoX/las2OJxAxTG08ffvjhKV/v0qWLIYFKoxs4OVuFhTBh\ngpPJk514PBYaNAiSmemlZcug2dEkwujNoYgYQbVFRM6nadMcDB/uwmaz8NprHrp1C5gd6bwIh8PM\n3v4ez60ZTHGgmAevfYjMllm4HW6zo4nEFCMbT/bSvmD9+vUn/9vv97Np0yZuuukm0xpPImcrMRGG\nDvXRs6efrCwXc+c6SElxk5zsJyPDS506OgJPRERERCKb3w/Dh7uYMcPJxReH+OgjC1ddVT6a4/dY\nlAAAIABJREFUTj/7TvDMX55i/jdzqeC8kD+3f4e7rkoxO5aInGelrnj6T8eOHeOpp55ixowZRmU6\nIz05lN9r82YrI0e6KCiwY7eH6dPHT3q6l0qVzE4mZtOqBBExgmqLiPxRx47Bww/Hk59vp379IO++\n66Fx48RyUVs2H/w7fZf3ZteJ77ix2s3kJE3nsgqXmx1LJGaZeqrdf3K73aed+yQSyRo1CrFwoYfp\n0z3UrBkmJ8dJ06aJTJniwOczO52IiIiIyL/t3Gnhjjvc5Ofbad8+QF5eMbVqRf+K/VA4xKTNb9Jp\nfhLfn9jFE42f5qMuS9V0EinHSt1q17Nnz5OnCITDYfbu3cutt95qeDARI1gs0LlzgKSkANOnO8jO\ndjF8eBzTpjnJyPCSnBxAh2aIiIiIiJk++8zGQw/Fc+yYhQEDfAwf7sVmMzvVH3eo+BCDVj3Gyt2f\nUCW+KpNun8qttdqaHUtEDFbqVrsNGzb8+4stFipVqsRVV11leLDTKQ/LSiVyHD5sITvbyYwZDoJB\nCy1aBMjM9NKwYcjsaFKGtB1GRIyg2iIiv8esWQ6GDHFhscArr5TQo8dv5zlFa23J3/sp/Vc8wsHi\nH2lbqx1vtsuhqruq2bFE5P+YutWuYsWKHDlyhOLiYqpXr25q00nkfKtcOUxWlpf8/GI6dAiwbp2d\npCQ3AwfGceCAlj6JiIiISNkIBmHECBdPPx1HhQph5s3z/FfTKRoFQgGyCjLp9tHdHCk5TEbzUfxv\n5w/UdBKJIadd8XT48GEGDRrEN998w+WXX47FYuG7776jUaNGZGdnU6FChbLOCmjFkxgrP99GRoaL\nbdtsuN1h+vf3MWCAj4QEs5OJkaL1yaGIRDbVFhE5Wz//DH37xrNypZ169YLMmuWhdu1Tb0yJptqy\n5+fdPPZJHzb+sJ7LK1xBTtJ0Gle7yexYInIKRq54Om3j6cknn+Syyy5j4MCBOBwOAHw+H2+++SaH\nDh1i7NixhoU6k2gpshK9gkHIzbWTleXi4EEr1auHGDbMS2pqAOs5j+OXaBBNN3AiEj1UW0TkbHz/\nvYWePePZvt1G27YBpk71cKZn/NFSWz7+diHpnw7kuPcYXa7qyrhbX6eC60KzY4nIaZiy1W7Hjh2k\np6efbDoBOJ1O0tPT+eqrrwwLJGI2mw169AhQUFBEerqX48ctDBoUT1KSm7Vry8FURxERERGJCAUF\nNjp2dLN9u41HHvHx3ntnbjpFA0/AwzN/eYo+y3riC3p5rc0EcpJmqOkkEsNO23hyuVynfN1isWDV\nsg+JAYmJMHSoj3XriujWzc/WrTZSUtz06hXHzp2a/yQiIiIiv9/s2XbuueeXk+tefrmE0aO92Es9\nczyy7TiynY7z2vLOtmnUv+hPfHJvPvdf++DJU9JFJDadtoN0puKgwiGxpEaNMBMnlrB8eRHNmgVY\nssTBLbckMGKEi6NHzU4nIiIiItEkFIIXX3QyaFA8bjfk5npIS/ObHesPCYfDvPvVO7SfdytfH/mK\n3tc9zNJ7V1HvoqvNjiYiEeC0M56uu+46qlWr9l+vh8NhDh06xNatWw0PdyrRsJ9Zyq9wGPLy7GRm\nuti1y0rFimEGD/aSlubH6TQ7nfxe0TIrQUSii2qLiPynwkLo3z+OpUsd1KkT4r33irnyylMPET+d\nSKstJ7zHefrTJ1j47XwudFVkfNuJdKpzp9mxROQcmTJcfN++fWf8xho1ahgSqDSRVGQldnm9MH26\ng+xsFydOWKhdO0RGhpfk5ABaEBh9Iu0GTkTKB9UWEfm1vXt/GSK+bZuNVq0C/PnPHipVOvfrRFJt\n2fTjRh79pA+7T+yiSfVmTE76M7UuuMzsWCLyO5jSeIpUkVJkRQAOH7aQne1kxgwHwaCFFi0CZGZ6\nadgwZHY0OQeRdAMnIuWHaouI/Mvf/malV694Dh2y8uCDPsaM8fKrM5zOSSTUllA4xMTNbzBmfSbB\nUJCnbhzM4Jufw26N8iFVIjHMlFPtRKR0lSuHycrykp9fTIcOAdats5OU5GbgwDgOHNDSJxEREZFY\nN3++nZQUN4cPWxg9uoRXXvn9TadIcLD4IN0XdeXFv46kctzFzLvrI4Y2HaGmk4iclhpPIudB3boh\nZs3yMG9eMddeGyI310Hz5gm8/LKToiKz04mIiIhIWQuFYOxYJ489Fo/TCe+/7+GRR/xRPZbh0z2r\naJvbgk/3rOL2y9qz+r51tKp5q9mxRCTCnXar3caNG8/4jTfffLMhgUpj9rJSkdIEg5Cbaycry8XB\ng1aqVw8xbJiX1NQAVrV6I1IkLFkXkfJHtUUkdhUXw6BBcXz0kYPLLw/x7rserr76/IxiMKO2+IN+\nxm4YxZufv4bD6mBE8xfo27A/VotubkXKC1NmPPXs2fP032SxMHPmTMNCnYlu4CRaFBbChAlOJk92\n4vFYaNAgSGaml5Ytg2ZHk/+gN4ciYgTVFpHYdOCAhQcfjOeLL2w0axZgxowSKlc+f2N1y7q2fH9i\nF4998hCbfvwbV1SozZT2M2hUtXGZ/XwRKRsaLv4ruoGTaLNvn4WsLBdz5/6ymT852U9Ghpc6daLq\nn165pjeHImIE1RaR2PPFF1Z69oznhx+s/M//+HnllRKczvP7M8qytiz853zSPx3Ez74TdK3bjVdu\nfY0LnBXK5GeLSNkybcWT5QwbkLXiSeTcbN5sZeRIFwUFduz2MH36+ElP9/6uY3Tl/NKbQxExgmqL\nSGz5+GM7jz8eR0kJjBzppX9/Y+Y5lUVtKfYXM2LtUGZ99TZuu5uxrbO57+oeZ3x/KCLRzZTG04YN\nG874jU2aNDEkUGl0AyfRLByGvDw7mZkudu2yUrFimMGDvaSl+c/70zA5e3pzKCJGUG0RiQ3hMLz2\nmpOxY10kJIR56y0PHToYN1rB6Nry9eGv6Ls8jR1Ht/Onyg2Y2v5trqpU17CfJyKRwcjG02mnwTVp\n0uTkR2JiIlarFYvFQigUYvfu3YYFEinPLBbo3DnAmjVFvPBCCaEQDB8eR6tWCSxebCe6Nr6KiIiI\nxLaSEujXL46xY13UrBli0aJiQ5tORgqHw7yzbTod5rVhx9HtPNzgUZbcs1JNJxH5w0qd8TRkyBA+\n//xzjh8/Tp06ddi+fTuNGzdm2rRpZZXxN/TkUMqTw4ctZGc7mTHDQTBooUWLAJmZXho2PD+nnsjZ\n0aoEETGCaotI+XbwoIVeveLZtMnGTTcFefttD1WrGv8U0YjacqzkKOmfDmLRzoVUclVi/G2TSK7d\n6bz+DBGJbKasePqXjRs3kpeXR4cOHXjxxReZM2cOPp/PsEAisaRy5TBZWV7y84vp0CHAunV2kpLc\nDBwYx4ED2kMvIiIiEom+/NJKhw5uNm2ycc89fubPLy6TppMRNv6wnnZzW7Fo50KaXdKCValr1XQS\nkfOq1MZT1apVcTgcXHnllezYsYO6detSVFRUFtlEYkbduiFmzfIwb14x114bIjfXQfPmCbz8shP9\ncxMRERGJHEuX2ujc2c2+fVaGDfMyaVIJcXFmpzp3wVCQ8ZvGcdeCjuwr3Mvgm4Yy/+5F1LigptnR\nRKScKbXxVK1aNXJycrjhhhuYPXs2eXl5FBcXl0U2kZjTunWQFSuKGT/eQ2JimHHjXDRvnsDs2XZC\n2n0nIiIiYppwGCZMcNCrVzzhMEyb5uHJJ32GnFxntB+LfiB1UQpZ6zOp6q7G/LsW8WyTYditdrOj\niUg5VGrjafTo0dSsWZOGDRvSvn17Fi1axPPPP18G0URik80GPXoEKCgoIj3dy/HjFgYNiicpyc3a\ntTaz44mIiIjEHK8XnngijszMOKpXD/Pxx8XceWfA7Fi/y6rdn9B2TgvW7P2U9pd3ZFXqWlrUuMXs\nWCJSjp1xuHgwGMTn8xEfHw/At99+y2WXXYbD4SizgP9JQzol1uzbZyEry8Xcub/8u0tO9pOR4aVO\nneicIxCJNABYRIyg2iJSPhw+bKF37zgKCuw0ahRk5kwP1aubdx/2e2uLL+gja30mkza/gdPqJKPF\nizzc4DEs0bhkS0TOO1OGi+/Zs4fk5GTWrFlz8rUZM2bQuXNn9u7da1ggEfmtGjXCTJxYwvLlRTRr\nFmDJEge33JLAiBEujh41O52IiIhI+bVjxy9DxAsK7Nx1l58PPyw2ten0e313fCd3LmjPpM1vUOfC\nK1lyz0oeadhPTScRKROnXfH02GOP0alTJ+68887fvP7BBx+wcuVKJk2aVCYB/5OeHEosC4chL89O\nZqaLXbusVKwYZvBgL2lpfpxOs9NFL61KEBEjqLaIRLeVK2307RvPzz9bGDzYy+DBPqylDiox3rnW\nlvnfzGXwp09S6P+Z1Kv/h7GtxpHoNG5lg4hEJ1NWPP3www//1XQCuOeee9izZ49hgUTk9CwW6Nw5\nwJo1RbzwQgmhEAwfHkerVgksXmzn9BtnRURERORshMMwZYqD+++Px+eDnBwPzz4bGU2nc1HkL+LJ\nVQN47JM+hMIhJrTLYUK7HDWdRKTMnbZ8BgLROSxPJBa4XNCvn5/164t4+GEfu3dbSEuLJyUlni1b\nouyuSERERCRC+P3wzDMuhg+Po3LlMB9+WExKSvS9L9r205e0n3sr72+fRcMqjViVuobUq//H7Fgi\nEqNO+w61fv36zJ07979e/+CDD6hVq5ahoUTk7FSuHCYry0t+fjEdOgRYt85OUpKbgQPjOHBAe/ZF\nREREztbRo9C9ezwzZzr505+CLF9ezI03hsyOdU7C4TDTv5xKxw/a8s2xf/Bow/7kdf2EOhWvMjua\niMSw0854OnToEA888ADVqlXj+uuvJxwOs3XrVvbv38+MGTOoWbNmWWf9v1yalSByOvn5NjIyXGzb\nZsPtDtO/v48BA3wkJJidLLJpDouIGEG1RSR6fPuthfvvd7Nzp5XkZD8TJ5aQmGh2qlM7XW05WnKE\np1YPZPF3H3NR3EW8cdtk2l+RbEJCEYlGRs54Om3jCcDj8ZCXl8fXX3+NxWLhuuuuIzk5GZfLZVig\n0ugGTuTMgkHIzbWTleXi4EEr1auHGDbMS2pqIOpmE5QVvTkUESOotohEh/x8G336xHP8uIVBg7wM\nGxbZ85xOVVsKDvyVfp/0YV/hXlpe2opJt0/lksRLTUooItHItMZTJNINnMjZKSyECROcTJ7sxOOx\n0KBBkMxMLy1bBs2OFnH05lBEjKDaIhL53n7bwXPPubDZIDu7hPvui/x5Tr+uLcFQkNf/ns3LG7MA\neObm53iy8WBsVpuZEUUkCplyqp2IRLfERBg61Me6dUV06+Zn61YbKSluevWKY+dOzX8SERGR2BUI\nwLBhLp59No6KFcPMm+eJiqbTr/1QdIB7P7qLsRtGUd19CR/evZinbxqippOIRBw1nkTKuRo1wkyc\nWMLy5UU0axZgyRIHt9ySwIgRLo4eNTudiIiISNk6cQLuvz+eP//ZyTXXBFm6tJhmzaJrRfgnu5bS\nNrcFa/evIbl2Z1bft5Zml7YwO5aIyCmdVeNp7969fPrppwSDQfbs2WN0JhExQKNGIRYu9DB9uoea\nNcPk5Dhp2jSRKVMc+HxmpxMREREx3nffWbjjDjerV9u5/fYAeXnFXH559Ewe8Qa9pC9L5/7FqRT6\nCxnTahxvd3yPSnEXmR1NROS0Sm08LV68mH79+jFq1CiOHTtG9+7dWbhwYVlkE5HzzGKBzp0DrFlT\nxAsvlBAKwfDhcbRqlcDixXaia+KbiIiIyNn7619tJCe7+cc/bDz6qI9ZszxcYNxIk/Nu57F/0ml+\nEq8VvMZVFeuy5J5V9GnQF4tFIxREJLKV2niaOnUq//u//0tiYiKVK1dmwYIFTJkypSyyiYhBXC7o\n18/P+vVFPPywj927LaSlxZOSEs+WLdqBKyIiIuXL++/buffeeE6csJCdXcKLL3qxRdEopLk7ZtNu\nbmu2HNrMQ40e4pNu+Vx3cQOzY4mInJVS32FarVYSExNP/rlq1apYI/l8URE5a5Urh8nK8pKfX0yH\nDgHWrbOTlORm4MA4DhzQ0zMRERGJbsEgPP+8iyefjCcxEebO9dCzp9/sWGet0F/IwJWPMWBlXyxY\neCtpGtPunkaCI8HsaCIiZ63UDlLdunV59913CQQCfP3114wYMYJrrrmmLLKJSBmpWzfErFke5s0r\n5tprQ+TmOmjePIGXX3ZSVGR2OhEREZFzV1gIvXrFM2mSk6uuCrJkSREtW0bPEPGth74gaW5rcne8\nT6MqN7AydQ1d63YzO5aIyDkrtfE0cuRIfvzxR1wuF8OGDSMxMZGMjIyyyCYiZax16yArVhQzfryH\nxMQw48a5aN48gdmz7YRCZqcTEREROTt79ljo1MnN8uV2br01wJIlxdSpEx3DLMPhMFO3TCb5g3Z8\ne+yf9Lt+IIu6fkLtC+uYHU1E5HexhMPRNU740KGfzY4gEhMKC2HCBCeTJzvxeCw0aBAkM9MbVU8K\nz1aVKheotojIeafaImKODRuspKXF89NPVh56yMeoUV7sdrNTnZ0jJYd5YlV/lu1awsXxF/PmbW/R\n7vL2v/ka1RYRMUKVKsadtlDqiqf58+fTtGlT6tevT/369bnmmmuoX7++YYFEJDIkJsLQoT7WrSui\nWzc/W7faSElx06tXHDt3av6TiIiIRJ65c+107erm6FELY8aUMHZs9DSd1u37jLa5LVm2awmtarZh\ndeq6/2o6iYhEo1JXPLVr147JkydTr169ssp0Rurui5hj82YrI0e6KCiwY7eH6dPHT3q6l0qVzE72\nx+nJoYgYQbVFpOyEQjB2rJPx411UqBBm6lQPbdtGxyrtYChI9t9e4tVNL2PBwtAmw3n8hiexWU99\n7J5qi4gYwdQVT9WqVYuYppOImKdRoxALF3qYPt1DzZphcnKcNG2ayJQpDnw+s9OJiIhIrCoqgj59\n4hg/3sUVV4RYsqQ4appO+wv30fWjzoz721guTajBwi5LeeLGp0/bdBIRiUalrngaPXo0P/74Iy1b\ntsTlcp18vUuXLoaHOxV190XM5/XC9OkOsrNdnDhhoXbtEBkZXpKTA1iicBeenhyKiBFUW0SMt3+/\nhZ4949m61UbLlgGmTfNw0UVmpzo7S79bzBOr+nHUe5TOde7m1TZvUDGu9KXkqi0iYgRTVzwVFhaS\nkJDA5s2bWb9+/ckPEYldLhf06+dn/foiHn7Yx+7dFtLS4klJiWfLllLLioiIiMgf9vnnVjp0cLN1\nq40HHvCRmxsdTaeSQAnD1jzDg0u64wl4eLn1a0zrMPOsmk4iItHorE618/v9fPfddwSDQerWrYvd\nxAl96u6LRJ5vvrGSmeli2TI7FkuY1NQAw4Z5ueSS6Dg0U08ORcQIqi0ixlm40M7AgXH4fPD8814e\nfdQfFauu/3n0G/p+0psvf9pCvUpXM6X921xb+U/ndA3VFhExgpErnkptPH355ZcMGjSIihUrEgqF\n+Omnn5g4cSLXX3+9YaHOREVWJHLl59vIyHCxbZsNtztM//4+BgzwkZBgdrIz0w2ciBhBtUXk/AuH\nYdw4J6+84iIxMUxOjoekpMif5xQOh8nd8T5D8wdTHCii57VpvNhyLG6H+5yvpdoiIkYwtfHUvXt3\nnnvuuZONps2bNzNq1CjmzZtnWKgzUZEViWzBIOTm2snKcnHwoJXq1UMMG+YlNTWANUJ34ekGTkSM\noNoicn55PPDkk3EsWODgsstCzJrloX79kNmxSlXo+5ln89OZ949cLnBW4NU2b3D3VV1/9/VUW0TE\nCKbOeCouLv7N6qZGjRrh9XoNCyQi0c1mgx49AhQUFJGe7uX4cQuDBsWTlORm7Vqd0CIiIiLn7scf\nLXTp4mbBAgdNmgRYsqQ4KppOXxz8nHZzWzHvH7ncWO0mVqV+9oeaTiIi0ajUxtOFF17IihUrTv55\nxYoVVKxY8awuHg6HycjIoHv37jz44IPs2bPnlF83cuRIXn311bOMLCLRIDERhg71sW5dEd26+dm6\n1UZKipteveLYuTMKhjCIiIhIRNi69Zch4p9/biM11c8HH3ioUiWy50iGw2He+mICd8y/ne+O72Tg\nDU/xUZdlXF7hCrOjiYiUuVIbTy+++CI5OTk0bdqUJk2a8NZbb/HCCy+c1cVXrFiBz+dj9uzZPP30\n04wZM+a/vmb27Nn84x//OPfkIhIVatQIM3FiCcuXF9GsWYAlSxzccksCI0a4OHrU7HQiIiISyRYv\ntnPnnW4OHLAwfLiXN98sweUyO9WZ/eT5ifvzujFy7TAudFUkt/MCRjR/AYfNYXY0ERFTlHo83RVX\nXMHcuXMpLi4mFAqRmJh41hfftGkTrVq1AuD666/nyy+//M3nP//8c7Zu3Ur37t3ZuXPnOUYXkWjS\nqFGIhQs95OXZeeEFFzk5TnJzHQwe7CUtzY/TaXZCERERiRThMLz5ppNRo1y43WFmzCjhjjsCZscq\n1Wf78un3ycP8WPwDt9Zsy4Tbp1DNXc3sWCIipiq18bRlyxamT5/O0aNH+fUc8pkzZ5Z68cLCQi64\n4N8Dqux2O6FQCKvVyqFDh5gwYQKTJk1i8eLFvzO+iEQTiwU6dw6QlBRg+nQH2dkuhg+PY9o0JxkZ\nXpKTA1FxFLKIiIgYx+uFp5+OY84cB5de+ssQ8QYNInueUyAUYNzGMby2aRw2q40RzTMZ0GgQVkuE\nnqwiIlKGSm08DRkyhAceeICrrroKyzm+I0xMTKSoqOjkn//VdAJYunQpx44d45FHHuHQoUN4vV7q\n1KlDly5dzvFXEJFo43JBv35+UlMDZGc7mTHDQVpaPC1aBMjM9NKwYWTfXIqIiIgxDh2y0Lt3HBs2\n2GncOMg773ioVi2y5znt/XkPj33Shw0/FHDZBZeT0346N1a72exYIiIRwxL+9TKmU0hJSWHBggW/\n6+LLly9n9erVjBkzhs2bNzNp0iSmTJnyX1+3YMECvvvuO9LT03/XzxGR6LZ9Ozz7LHz88S+roh58\nEEaPhho1zE4mIiIiZWXrVrjzTvj+e+jeHaZPh/h4s1Od2YL/z969x0VZ5+8ffw0zwxwYKzOzYjuv\nVnaytk1IoDQJPDspWHSQTS3NlS3sYC5m2qYtabGVlW7qFq6BkkomKKIUAYttbSXZcaOyg2uu4Wlm\nmGGY+/dH+93fHmorZZgBrudf8QDvz+XjYZ+5ueae9+fdtUx4YQJNzU1knpvJ4uGLOcb+ww5iEhHp\nKr6zePryyy8BePzxx+nTpw9XXnklZvP/Pwr9pJNO+t6LG4bBfffdx/vvvw/A/Pnz2bFjBz6fj4yM\njH/+3I8pnvbsOfi9PyMiHVN1tZnZs23s2GHG6TS49dYAU6cGiIsL77o9e3bT3iIibU57i8gPt3mz\nmZtvduDxmLjrLj/Tpwei+uP3zcFmZtfNZPnbT+OwOHggKZ/rzrnxR39C5HBobxGRcOjZs9v3/9Bh\n+s7iadCgQd/9h0wmtmzZErZQ/4s2WZHOrbUViostzJtn46uvYjjhhBAzZ/rJzAwSE6YxCbqBE5Fw\n0N4i8v0MA556ysp999mw2eCxx5oZNSq6h4h/8PX73Lz5F7yz923OObYvS676A2cde3a7ra+9RUTC\nISLFU7TSJivSNRw6BI8/HsuTT8bi85k4//xW5s71M2BAa5uvpRs4EQkH7S0i/1sgADNm2FixIpZe\nvUI8+6yPiy6K3jmPhmHw3HsrmPnKnXiDXsafO4G5A+bhsLTv5wG1t4hIOISzePrO5wd2797NtGnT\nGDFiBLNnz+bAgQNhCyEi8p9cLpgxI0BdnYeMjBYaGsy43U7Gj7fT2BjFz96LiIjI9/r6a8jMdLBi\nRSznn9/Kpk3eqC6dDvj3M3nzTdxWNRWrOZalaYU8dPkj7V46iYh0RN9ZPM2cOZPTTz+dO++8k0Ag\nwPz589szl4gIAPHxBosWNVNR4SEhIUh5uZWkpDhmzbLR1BTpdCIiIvJjffhhDOnpcdTVWRg2rIUX\nXvBy0knR+yGMN3a/zpWrk1n71+e5pNelbM2sYcSZoyIdS0Skw/ifTzzl5uaSkpLC3Llz2b59e3vm\nEhH5N/36hSgt9bFsmY/4eIPFi2Pp39/FkiVWAoFIpxMREZEfoqrKzJAhTj75JIbbb/ezdGlz2A8R\nOVwhI8SiNx5l2NpUdh74lNsuvoPS0eWc3O2USEcTEelQvrN4slqt//bf//q1iEgkmEwwfHiQmhoP\nc+Y0EwpBXp6d5OQ4ysosdKyJdSIiIl3L0qVWsrIcNDfDokU+7rknELaDQ47UHu8ern1xDHP+lMex\n9h6sHlnKzIR7sZr1O5GIyI/1g7f69jgaVETkh7DZYMqUFrZt8zBxYoCdO01kZztwux1s3x6ld7Ai\nIiJdVDAId99t45577HTvbrB2rZeMjOg9ue7lz6oYuOoyqj7bwqBTBlOVWUfKT66IdCwRkQ7rO0+1\nO++88+jVq9c/v969eze9evXCMAxMJhNbtmxpt5D/Sic4iMh/+vDDGObOtbFpkwWTySAzM8jMmX5O\nPPGHPQKl02FEJBy0t4jAvn0wcaKD6moL55zTyooVPk4+OTofUW5pbSH/z/N49C8PY44xk5cwh8kX\nTiXGFF1vamlvEZFwCOepdt9ZPH3xxRf/8w/Gx8eHJdD30SYrIt+lutrM7Nk2duww43Qa3HprgKlT\nA987O0I3cCISDtpbpKtrbDRx/fUO/vpXM1ddFeSpp3y4XJFO9e12HviUWzbfxOu7/8ypR53GktTl\nXNTrZ5GO9a20t4hIOESkeIpW2mRF5H9pbYXiYgvz5tn46qsYTjghxMyZfjIzg985R0I3cCISDtpb\npCurqTFz000O9u0zMXVqgLw8P2ZzpFN9u/UfreP2qmkcCOzn6t5jeejyArrFHhXpWN9Je4uIhEM4\ni6foem5UROQImc2QlRWkvt5Dbq6f/ftN5OQ4SE11UlsbpXe8IiIinUhhoZXMTAceDxTFkh5eAAAg\nAElEQVQU+Jg9OzpLJ1/Qxx0v3caETTcSDLXwu4FP8OTgpVFdOomIdEQqnkSkU3K5YMaMAHV1HjIy\nWmhoMON2Oxk/3k5jow5LEBERaWutrTBrlo3p0+0cdZRBSYmPrKzoHCL+3tfvklZyBc++s4y+Pc6j\nYuzLXHvO9TpQSUQkDFQ8iUinFh9vsGhRMxUVHhISgpSXW0lKimPWLBtNTZFOJyIi0jkcPAg33OBg\n8eJY+vRppbzcS2Jia6Rj/RfDMCh85w+klVzBe1+/y03nTWLjmK30OfasSEcTEem0VDyJSJfQr1+I\n0lIfy5b5iI83WLw4lv79XSxZYiUQiHQ6ERGRjuvTT00MG+akstLCwIFBysq8nH569I2R3e/fx6SK\nbKa/lIPNbGN5+h95MGUhdos90tFERDo1FU8i0mWYTDB8eJCaGg9z5jQTCkFenp1zz4WyMgsd66gF\nERGRyKuvN5Oe7uS998xMmhTgj3/0cVQUjkh67W+vcuWqZF74aC39T0xka2Ytw84YEelYIiJdgoon\nEelybDaYMqWFbds8TJwY4OOPITvbgdvtYPt2bYsiIiI/RFGRhTFjvjm5Lj+/mQce8GOxRDrVvwsZ\nIR79yyOMXJfOZwd3knvJXawdtYGfdDs50tFERLoMk2F0rPf4dXSoiLS1vXu7cdttQTZtsmAyGWRm\nBpk508+JJ3ao7VFEooyOPJfOKhSCBx6I5bHHbBx9tMHSpT5SUqJvntNu725+WXkzL39exQlxJ/LE\n4N+TFJ8S6VhHTHuLiIRDz57dwnZtvbUvIl3e2WdDYaGPkhIvffuGKC62kpgYR35+LB5PpNOJiIhE\nj0OHIDvbzmOP2TjjjBAbN3qisnSq2rmFgcWX8fLnVaSemsbWzNpOUTqJiHREKp5ERP4hJaWVykov\nBQU+XC6DBQtsJCbGUVRkIRSKdDoREZHI+vxzEyNGONm40UpycpDycg9nnhldTwe3tLYw90/3Mu5F\nN/v9+7h/wHxWDF3FcY7jIh1NRKTLUvEkIvIvzGbIygpSX+8hN9fP/v0mcnIcpKY6qa01RzqeiIhI\nRLz2WgxpaU527DBz440Biop8dO8e6VT/7pP9HzNi7VU8/kYBpx99BmVXV3LLhVMxmUyRjiYi0qWp\neBIR+RYuF8yYEaCuzkNGRgsNDWbcbifjx9tpbNQNrIiIdB1r1lhwu53s3WvigQeaeeghP1ZrpFP9\nu3UfPs+Vq5P5y1evM7bPOLZkvMKFx18U6VgiIoKKJxGR/yk+3mDRomYqKjwkJAQpL7eSlBTHrFk2\nmpoinU5ERCR8QiF48MFYJk92EBsLK1f6mDSphWh6gMjb4iW3aho3b/4FraFWHhv0FE8M/j2u2PAN\nyRURkR9HxZOIyA/Qr1+I0lIfy5b5iI83WLw4lv79XSxZYiUQiHQ6ERGRtuX1ws0323n4YRunnhqi\nrMzLoEHRNUT8nb07uKrkcla8+wznHXcBWzKrGXd2VqRjiYjIf1DxJCLyA5lMMHx4kJoaD3PmNBMK\nQV6eneTkOMrKLBjRNV9VRETksOzaZWLUKCcvvGAlISHIxo1ezjorek7ZMAyD5W8/TXrJQD5oep9J\n50+mfMwWzjymd6SjiYjIt1DxJCLyI9lsMGVKC9u2eZg4McDOnSaysx243Q62b9e2KiIiHddbb30z\nRPytt8xce20Lq1f76NEjet5Z2dfcxE2bbuDu6lwcFgfPDinigeR8bGZbpKOJiMh30G9IIiKHqUcP\ng3nz/FRXe0lLC1JXZyE11cm0aXZ27YqiARgiIiI/wPr1FkaOdLJ7t4nZs5spKGjGFkV9zrZd9Qxa\nlcSGxhdIPGkAVePqSD99aKRjiYjI91DxJCJyhHr3DlFY6KOkxEvfviGKi60kJsaRnx+LxxPpdCIi\nIv+bYcDDD8cyYYIDkwmeecbH1KnRM0S8NdRKwesLGL1uCF96vuDOn9/DmpEvcpIrPtLRRETkB1Dx\nJCLSRlJSWqms9FJQ4MPlMliwwEZiYhxFRRZC0TMaQ0RE5J+am2HKFDsPPmjjJz8JsWGDl/T06Bki\n/jfPLjLXj2betrkc7+zF2lEbuPPn92COMUc6moiI/EAqnkRE2pDZDFlZQerrPeTm+tm/30ROjoPU\nVCe1tbpJFhGR6PHVVybcbidr1li55JJWNm70cu650fNOyZZPKxhYfBmvfPEy6acNpWpcLYknDYh0\nLBER+ZFUPImIhIHLBTNmBKir85CR0UJDgxm328n48XYaG6PkswsiItJlvf32N0PEX3/dzJgxLaxZ\n4+X446NjiHigNcC9tTO5dsNYDgYOMi8pn2eGPMex9h6RjiYiIodBxZOISBjFxxssWtRMRYWHhIQg\n5eVWkpLimDXLRlNTpNOJiEhXtHGjmeHDnXzxRQz33OPniSeasdsjneobjfs/YviaVJ5663HOPOan\nlI/dysQLJmOKloFTIiLyo6l4EhFpB/36hSgt9bFsmY/4eIPFi2Pp39/FkiVWAoFIpxMRka7AMODx\nx62MH+/AMGDpUh+33x6ImiHiz3+wisGrUnhzzxtcc/Z1bM6o5vzjLoh0LBEROUIqnkRE2onJBMOH\nB6mp8TBnTjOhEOTl2UlOjqOszIIRHZ9wEBGRTsjvh1/9ys7cuXZOOMFg/XovI0YEIx0LAE+Lh19t\nvZUplRMxMHhi8O95dNCTuKyuSEcTEZE2oOJJRKSd2WwwZUoL27Z5mDgxwM6dJrKzHbjdDrZv17Ys\nIiJta+9eExkZDoqKrPTr18qmTV4uuCA6hog3/H07qatTeO69FVzY8yK2ZFQzts+4SMcSEZE2pN9w\nREQipEcPg3nz/FRXe0lLC1JXZyE11cm0aXZ27YqSzz2IiEiH9v773wwRr6+3MHJkC+vWeTnhhMg/\nYmsYBksbFjP0+Sv5674PmXzhL9lw9WbOOOankY4mIiJtTMWTiEiE9e4dorDQR0mJl759QxQXW0lM\njCM/PxaPJ9LpRESko9qyxczQoU527ozhjjv8LFnSjNMZ6VTQ1Pw14zdmcc8rd+Kyulg5bDVzB8wj\n1hwb6WgiIhIGKp5ERKJESkorlZVeCgp8uFwGCxbYSEyMo6jIQig6PhEhIiIdgGHAkiVWrrvOQSAA\nixf7uOuuADFRcOdf/2UdA4sHsPHjDSTFp1A1ro7Bp6ZFOpaIiIRRFLz8iIjI/zGbISsrSH29h9xc\nP/v3m8jJcZCa6qS21hzpeCIiEuVaWuDOO23k5dnp0cNg3Tovbnfkh4i3hlpZ8OcHGV06lN3ev3HP\npbNYPaKUE+JOjHQ0EREJMxVPIiJRyOWCGTMC1NV5yMhooaHBjNvtZPx4O42Nmv8kIiL/rakJrrnG\nwbPPxnLuua1UVHj52c8i/8jsrkNfMuaFEeT/eR4nxp3EutHl3H7JnZhj9IaKiEhXoOJJRCSKxccb\nLFrUTEWFh4SEIOXlVpKS4pg1y0ZTU6TTiYhItPjoIxNDhsTxyisWhgxpYf16L/HxkR8iXvFJOQNX\nXUbdlzUMPX0EWzNr6H9iQqRjiYhIO1LxJCLSAfTrF6K01MeyZT7i4w0WL46lf38XS5ZYCQQinU5E\nRCKputpMenocjY0x5OT4Wb68GZcrspn8rX7yau7m+rJxeFo8/DblYZanr6C7/djIBhMRkXan4klE\npIMwmWD48CA1NR7mzGkmFIK8PDvJyXGUlVkwIv/GtoiItLM//MHKuHEOfD547DEfeXmRHyL+0b4P\nGfr8YJZsf5I+3c9i45gqfnHeREwmfVRcRKQrUvEkItLB2GwwZUoL27Z5mDgxwM6dJrKzHbjdDrZv\n17YuItIVBIMwc6aNu+6yc8wxBiUlPsaNi/wQ8VXvP8eVq1Jo+PtbXHfOjWwa+xLnHndepGOJiEgE\n6TcUEZEOqkcPg3nz/FRXe0lLC1JXZyE11cm0aXZ27dK7yiIindWBA3DddQ6efjqWs89uZeNGLwkJ\nrRHNdChwkKmVN/PLLbcQY4phceoyHhn4OHHWuIjmEhGRyFPxJCLSwfXuHaKw0EdJiZe+fUMUF1tJ\nTIwjPz8WjyfS6UREpC19/LGJoUOdVFVZGDw4yIYNXk49NbKftd6+500Gr05h9QdFXHT8xWzNrMHd\ne2xEM4mISPRQ8SQi0kmkpLRSWemloMCHy2WwYIGNxMQ4iooshCJ/mraIiByhP/3JzJAhTj74wMwt\ntwQoLPTRrVvk8hiGwZK3nmDo84Np3P8RU/v9ivXuCk47+vTIhRIRkaij4klEpBMxmyErK0h9vYfc\nXD/795vIyXGQmuqkttYc6XgiInKYVq60MHasgwMHTCxc2Mz99/sxR3Bb3+vbyw1l48irncFRtqMo\nGr6G2ZfdT6w5NnKhREQkKql4EhHphFwumDEjQF2dh4yMFhoazLjdTsaPt9PYqPlPIiIdRWsr3Hef\njdtuc+BywerVPm64oSWimWq/eIWBqy6j4tONpPxkIFWZdQw6ZXBEM4mISPRS8SQi0onFxxssWtRM\nRYWHhIQg5eVWkpLimDXLRlNTpNOJiMj/cugQjB/v4IknYvnpT1spL/cwYEDkhogHQ0F+++oDXF06\nnD3er8hLuI9VI9bSK+6EiGUSEZHop+JJRKQL6NcvRGmpj2XLfMTHGyxeHEv//i6WLLESCEQ6nYiI\n/KfPPjMxbJiTigoLl18epLzcyxlnRG6I+BcHP+fq0uEsfO23/KTbybzg3kjOxbnEmPTrhIiI/G96\npRAR6SJMJhg+PEhNjYc5c5oJhSAvz05ychxlZRaMyB6KJCIi//DqqzGkpTl5910zN90U4LnnfBx9\ndOTylH+8gYGrLqN+Vx0jzhzN1swafn5C/8gFEhGRDkXFk4hIF2OzwZQpLWzb5mHixAA7d5rIznbg\ndjvYvl0vCyIikbR6tYWrr3bS1GRi/vxmHnzQj8USmSzNwWbueeUOxpdfS3OwmQWX/46nr3qGo23H\nRCaQiIh0SPoNQ0Ski+rRw2DePD/V1V7S0oLU1VlITXUybZqdXbs0gFxEpD2FQjBvXixTpzqw22Hl\nSh8TJkRuiPiHTR8w5PkrWdqwhLOPPYdNY1/ixnN/gcmk1wcREflxVDyJiHRxvXuHKCz0UVLipW/f\nEMXFVhIT48jPj8XjiXQ6EZHOz+OBCRPsFBTYOO20EOXlXgYOjMwQccMweO7dFaSuTmHH3gZu6PsL\nNo6p4pwefSOSR0REOj4VTyIiAkBKSiuVlV4KCny4XAYLFthITIyjqMhCKBTpdCIindOXX5oYOdLJ\nhg1WBgwIsnGjh969I7PpHgwcYErlRH5VdSuWGCtPX/UMC6/4HU6rMyJ5RESkc1DxJCIi/2Q2Q1ZW\nkPp6D7m5fvbvN5GT4yA11UltrTnS8UREOpU33vhmiHhDg5nrrw9QXOzj2GMjk+XNr/7ClauSWfPh\nan7W6xK2ZL7CyJ+6IxNGREQ6FRVPIiLyX1wumDEjQF2dh4yMFhoazLjdTsaPt9PYqPkeIiJHqrTU\nwqhRTvbsMTF3bjMLF/qJjW3/HCEjxJNvPs6wNal8euATci7K5YXRmzj1qNPaP4yIiHRKKp5EROQ7\nxccbLFrUTEWFh4SEIOXlVpKS4pg1y0ZTU6TTiYh0PIYBDz0Uy6RJDiwWKCz0MXlyC5GY2f1339+5\nbkMGs+tmcoytO8Uj1pKXeB9Ws7X9w4iISKel4klERL5Xv34hSkt9LFvmIz7eYPHiWPr3d7FkiZVA\nINLpREQ6Bp8PJk+289BDNk45JcSGDV5SUyMzRPyVz19mYPFlbNm5mStOHkTVuDquOHlQRLKIiEjn\npuJJRER+EJMJhg8PUlPjYc6cZkIhyMuzk5wcR1mZBcOIdEIRkei1e7eJ0aOdrF1r5dJLg5SXeznn\nnPYfIh4MBZm/bS5jXxjJ3ua/c2/i/RQNX8PxzuPbPYuIiHQNKp5ERORHsdlgypQWtm3zMHFigJ07\nTWRnO3C7HWzfrpcVEZH/1NDwzRDxN94wk5nZwvPP++jZs/3b+s8O7mTUuiE88voCTj7qVNa7N/HL\ni35FjEl7t4iIhI9eZURE5LD06GEwb56f6movaWlB6uospKY6mTbNzq5dGkAuIgJQVmZhxAgnu3aZ\nyMvz89hjzdhs7Z/jxY9eYNCqJP78t22M/unVbM14hZ/1+nn7BxERkS5HxZOIiByR3r1DFBb6KCnx\n0rdviOJiK4mJceTnx+LxRDqdiEhkGAY8+mgs2dkOAJYvbyYnJ9DuQ8R9QR93vXw7N226nkCrn0eu\neJzFqcs5ynZ0+wYREZEuK6zFk2EYzJ49m2uuuYYbb7yRzz777N++v2nTJsaOHUtmZibPPvtsOKOI\niEiYpaS0UlnppaDAh8tlsGCBjcTEOIqKLITaf4yJiEjE+P0wbZqd3/zGxkknhVi/3svQocF2z/HB\n1++TXjKIP+xYyjnHnkvF2Je5ru+NmCJxhJ6IiHRZYS2eKisrCQQCFBUVMX36dObPn//P74VCIR5+\n+GGeeeYZioqKWLlyJfv27QtnHBERCTOzGbKygtTXe8jN9bN/v4mcHAepqU5qa82RjiciEnZ79pgY\nM8bBqlVWLr64lU2bvJx/fvu274ZhsOKdZ0gtSeHdr3eQfe4ENo7dylnHnt2uOURERCDMxdPrr79O\ncnIyABdeeCFvv/32/184Joby8nLi4uJoamrCMAysVms444iISDtxuWDGjAB1dR4yMlpoaDDjdjsZ\nP95OY6PeaReRzumdd2JIT3fy6qsW3O4W1q710qtX+w4RP+Dfzy2bf0HuS9OINdtYlraC/MsfwWFx\ntGsOERGR/xPW4unQoUN069btn19bLBZC//J5i5iYGDZv3syoUaO49NJLcTqd4YwjIiLtLD7eYNGi\nZioqPCQkBCkvt5KUFMesWTaamiKdTkSk7WzebGbYMCeffRbDXXf5eeqpZhzt3PX8ZfdrDFqdzLq/\nruHnJ/Rna2YNw88c2b4hRERE/oPJMIywvQ3z4IMP0q9fP9LT0wG44ooreOmll771Z++++24SEhJw\nu93hiiMiIhFkGLB2Ldx5JzQ2QvfuMHs2TJkCsbGRTicicngMAx55BO64A2w2eOYZyMxs3wwhI8TC\nuoXM3DqT1lArM5Nnct8V92GJsbRvEBERkW8R1lejiy++mKqqKtLT03nzzTfp06fPP7936NAhpkyZ\nwtKlS4mNjcXhcPygQYd79hwMZ2QR6YJ69uymvaWdJCfDyy/DsmVWFi60cdttJn73uxCzZ/sZMiTY\n7qc9iYST9pbOLxCAGTNsrFgRS69eIZ591sdFF4XYs6f9Mnzl/YppW26h6rMt9HKewBODf0/yTy6n\naa+v/UJIu9LeIiLh0LNnt+//ocMU1ieeDMPgvvvu4/333wdg/vz57NixA5/PR0ZGBqtXr2b16tVY\nrVbOOussZs2a9b3lkzZZEWlruoGLjL17TSxcGMvy5VZaW01cdlmQuXP9XHCBjsCTzkF7S+f29ddw\n000O6uosnH9+K4WFPk46qX3nOb302VamVt7MHt9XXHlKKo9duZjjHMe1awZpf9pbRCQcOmzxFA7a\nZEWkrekGLrI+/DCGuXNtbNpkwWQyyMwMMnOmnxNP7FAvTyL/RXtL5/XhhzFcd52DTz6JYdiwFh5/\nvJm4uPZbv6W1hd+++gCPvfEIlhgLeQlzuOXCW4kxhXV8q0QJ7S0iEg7hLJ706iQiIhHVu3eIwkIf\nJSVe+vYNUVxsJTExjvz8WDyeSKcTEfl3VVVmhgxx8sknMdx+u5+lS9u3dPr0wCeMXJfOo288zKlH\nncaGqzczpd8vVTqJiEjU0iuUiIhEhZSUViorvRQU+HC5DBYssJGYGEdRkYWQPn0nIlFg6VIrWVkO\nmpth0SIf99wTIKYd76Zf+OtarlyVzOu7/8zVvTPYkvkK/Y6/uP0CiIiIHAYVTyIiEjXMZsjKClJf\n7yE318/+/SZychykpjqprTVHOp6IdFHBINx9t4177rHTvbvB2rVeMjKC7ba+t8XL9Jd+xcSK8QRD\nLTw66EmeHPw03WKParcMIiIih0vFk4iIRB2XC2bMCFBX5yEjo4WGBjNut5Px4+00NuroOxFpP/v2\nwTXXOFi+PJZzzmll0yYvP/95+z2G+e7ed0h/fiCF7yzn3B7nszmjmmvOvu4HnQYtIiISDVQ8iYhI\n1IqPN1i0qJmKCg8JCUHKy60kJcUxa5aNpqZIpxORzq6x0cTQoU6qqy1cdVWQDRu8nHxy+xx8YBgG\nz+xYRlrJFbz39btMPP8WysdsoXf3Pu2yvoiISFtR8SQiIlGvX78QpaU+li3zER9vsHhxLP37u1iy\nxEogEOl0ItIZ1dSYSU+P469/NTN1aoBnnvHhcrXP2vv9+5hYMZ47X74Nh8XBM0OeY17yQ9gt9vYJ\nICIi0oZUPImISIdgMsHw4UFqajzMmdNMKAR5eXaSk+MoK7NgtM9DCCLSBRQWWsnMdODxQEGBj9mz\n/Zjbaczcn/+2jUGrklj/0ToSTryMrZm1DDl9WPssLiIiEgYqnkREpEOx2WDKlBa2bfMwcWKAnTtN\nZGc7cLsdbN+ulzUROXytrTBrlo3p0+0cdZRBSYmPrKz2GSIeMkL87vWFjFybzheHPmf6JXezZtSL\nxHf7SbusLyIiEi4mw+hY7xHv2XMw0hFEpJPp2bOb9pYO7MMPY5g718amTRZMJoPMzCAzZ/o58cQO\n9fImnZD2lo7l4EG45RYHlZUW+vRppbDQx+mnt88+stu7m6mVN1P9eRUnxJ3Ik4OfZkB8crusLR2P\n9hYRCYeePbuF7dp6a1hERDq03r1DFBb6KCnx0rdviOJiK4mJceTnx+LxRDqdiHQEn35qYtgwJ5WV\nFgYODFJW5m230mnrzs0MLE6k+vMqrjo1narMOpVOIiLSqah4EhGRTiElpZXKSi8FBT5cLoMFC2wk\nJsZRVGQh1H4nn4tIB1NfbyY93cl775mZNCnAH//o46ijwr9uoDXAfXV5XPPiGA74D/BA0m8pHFpM\nD0eP8C8uIiLSjlQ8iYhIp2E2Q1ZWkPp6D7m5fvbvN5GT4yA11UltbTtNBhaRDqOoyMLYsQ727TOR\nn9/MAw/4sVjCv+4n+z9mxNqreOLNRznj6DMpG1PJpAumYDKZwr+4iIhIO1PxJCIinY7LBTNmBKir\n85CR0UJDgxm328n48XYaG/WLnUhXFwrB/ffHkpPjwOGA4mIf2dkt7bL22g9LGLQqiTe++guZZ11L\nZUY1F/Ts1y5ri4iIRIKKJxER6bTi4w0WLWqmosJDQkKQ8nIrSUlxzJplo6kp0ulEJBIOHYLsbDuP\nPWbjjDNCbNzoISWlNezrelo83LZ1KrdsvomQEeLxKxfz+JWLccWGb5iriIhINFDxJCIinV6/fiFK\nS30sW+YjPt5g8eJY+vd3sWSJlUAg0ulEpL18/rmJESOcbNxoJTk5SHm5hzPPDP8Q8R1/f5urVl/O\nyvcKOf+4C9mSWU3mWdeGfV0REZFooOJJRES6BJMJhg8PUlPjYc6cZkIhyMuzk5wcR1mZBaN9DrAS\nkQh57bUY0tKc7Nhh5sYbAxQV+ejePbxrGobBsrd/T/rzA/lw3wfccsGtlI2p5Mxjeod3YRERkSii\n4klERLoUmw2mTGlh2zYPEycG2LnTRHa2A7fbwfbtelkU6YzWrLHgdjvZu9fEAw8089BDfqzW8K7Z\n1Pw1v9h4PTOqpxNnjWPF0GLuT3oQm9kW3oVFRESijO6wRUSkS+rRw2DePD/V1V7S0oLU1VlITXUy\nbZqdXbs0gFykMwiF4Le/jWXyZAexsbBypY9Jk1oI9+Fx9bv+xKBVSZR9vJ7LTkqiKrOOq04bEt5F\nRUREopSKJxER6dJ69w5RWOijpMRL374hioutJCbGkZ8fi8cT6XQicri8Xrj5ZjsLF9o49dQQZWVe\nBg0K7xDx1lArD7+Wz+h1Q9jl+ZK7L/01z49cz4muk8K6roiISDRT8SQiIgKkpLRSWemloMCHy2Ww\nYIGNxMQ4iooshEKRTiciP8bf/mZi9GgnL7xgJSEhyMaNXs46K7z/I//Ns4uM9aN48NXfcILzRNaN\nKmP6JXdjjjGHdV0REZFop+JJRETkH8xmyMoKUl/vITfXz/79JnJyHKSmOqmt1S+PIh3BW2/FcNVV\nTt5808y117awerWPHj3Ce3rA5k82MrD4Mmq+qCb99GFUjasl4aTLwrqmiIhIR6HiSURE5D+4XDBj\nRoC6Og8ZGS00NJhxu52MH2+nsVHzn0Si1fr1FkaOdLJ7t4nZs5spKGjGFsZZ3v5WP7Nq7+G6skwO\ntRxifvICnklfSXf7seFbVEREpINR8SQiIvId4uMNFi1qpqLCQ0JCkPJyK0lJccyaZaOpKdLpROT/\nGAY88kgsEyY4MJngmWd8TJ0a3iHijfs/Yviaq1j81iJ+ekxvysdsZcL5N2MK9+RyERGRDkbFk4iI\nyPfo1y9EaamPZct8xMcbLF4cS//+LpYssRIIRDqdSNfW3Ay33mpn/nwbP/lJiA0bvKSnh3eI+Or3\ni7hyVTJv7XmDa8++ns0Z1Zx33PlhXVNERKSjUvEkIiLyA5hMMHx4kJoaD3PmNBMKQV6eneTkOMrK\nLBjhHSEjIt/iq69MuN1Onn/eyiWXtLJxo5dzzw3fEPFDLYeYtmUyU7fcjAkTTw5+mt8NeoI4a1zY\n1hQREenoVDyJiIj8CDYbTJnSwrZtHiZODLBzp4nsbAdut4Pt2/WyKtJeduyIIS3NyeuvmxkzpoU1\na7wcf3z4GuCGv28ndXUKxe+vpF/Pi9iS+Qpj+mSGbT0REZHOQnfIIiIih6FHD4N58/xUV3tJSwtS\nV2chNdXJtGl2du3SjBeRcNq40cywYU6++CKGe+7x88QTzdjt4VnLMAye3v4UQ0oG8dG+vzLlwmm8\nePVmTj/6jPAsKCIi0smoeBIRETkCvXuHKCz0UVLipW/fEMXFVhIT48jPj8XjibbtyP8AACAASURB\nVHQ6kc7FMODxx62MH+/AMGDpUh+33x4I2xDxr5v3Mr78WmbW3MVRtqN4blgJcwY8QKw5NjwLioiI\ndEIqnkRERNpASkorlZVeCgp8uFwGCxbYSEyMo6jIQih8I2dEuoxAAG67zc7cuXZ69TJYv97LiBHB\nsK33py9rGVg8gI2flJEcfzlVmXVceepVYVtPRESks1LxJCIi0kbMZsjKClJf7yE318/+/SZychyk\npjqprTVHOp5Ih7V3r4mxYx0895yVfv1aqajwcsEF4Wl0W0OtPPTn+bhLh/GVdzcz+9/LqhHr6BV3\nQljWExER6exUPImIiLQxlwtmzAhQV+chI6OFhgYzbreT8ePtNDZq/pPIj/H++98MEa+vtzByZAvr\n1nk54YTwDBH/8tAXjHlhBA/9eT4nxcVTOnojt/3sDswxKo5FREQOl4onERGRMImPN1i0qJmKCg8J\nCUHKy60kJcUxa5aNpqZIpxOJflu2mBk61MnOnTFMn+5nyZJmnM7wrLXpk3IGFl9G3Zc1DD9jFFsz\na7j0xP7hWUxERKQLUfEkIiISZv36hSgt9bFsmY/4eIPFi2Pp39/FkiVWAoFIpxOJPoYBS5ZYue46\nB4EAPPWUj7vvDhAThjtXf6ufX79yFzeUjcMb9JKf8ghL057lGHv3tl9MRESkC1LxJCIi0g5MJhg+\nPEhNjYc5c5oJhSAvz05ychxlZRaM8HxySKTDaWmBO++0kZdnp0cPg3XrvFx9dXiGiH+070OGPj+Y\n3zc8RZ/uZ7Fp7EtknzcBU7iOyRMREemCVDyJiIi0I5sNpkxpYds2DxMnBti500R2tgO328H27XpZ\nlq6tqQmuucbBs8/Gcu653wwR/9nPwjNEvPi9lVy5KoWGv7/FDX2zqRj7Mn17nBuWtURERLoy3eGK\niIhEQI8eBvPm+amu9pKWFqSuzkJqqpNp0+zs2qWnLaTr+egjE0OGxPHKKxaGDGlh/Xov8fFt/yjg\nocBBbq2cxLStkzHHmFmSupyFVzyK0xqm4VEiIiJdnIonERGRCOrdO0RhoY+SEi99+4YoLraSmBhH\nfn4sHk+k04m0j+pqM+npcTQ2xpCT42f58mZcrrZf562v3uDK1cmUfFDMxcf/jC0ZrzC695i2X0hE\nRET+ScWTiIhIFEhJaaWy0ktBgQ+Xy2DBAhuJiXEUFVkIheeTRiJR4Q9/sDJunAOfDx57zEdeXtsP\nETcMg8VvLWLomsF8vL+RX150G+vdFZx29Oltu5CIiIj8FxVPIiIiUcJshqysIPX1HnJz/ezfbyIn\nx0FqqpPaWnOk44m0qWAQZs60cddddo45xqCkxMe4cW0/RPzvvr9zfVkms2rv4WjbMRQNX8O9iXOx\nmq1tvpaIiIj8NxVPIiIiUcblghkzAtTVecjIaKGhwYzb7WT8eDuNjZr/JB3fgQNw3XUOnn46lrPP\nbmXjRi8JCa1tvk7tF68waNUANn+6ict/MpCqcXUMOmVwm68jIiIi303Fk4iISJSKjzdYtKiZigoP\nCQlBysutJCXFMWuWjaamSKcTOTwff2xi6FAnVVUWBg8OsmGDl1NPbdsh4sFQkAdf/Q1Xlw7n7749\n5CXMoXjEWno5e7XpOiIiIvL9VDyJiIhEuX79QpSW+li2zEd8vMHixbH07+9iyRIrgUCk04n8cH/6\nk5khQ5x88IGZW24JUFjoo1u3tl3j84Of4S4dxsOv5XNyt1N4YfRGci6+nRiTbntFREQiQa/AIiIi\nHYDJBMOHB6mp8TBnTjOhEOTl2UlOjqOszILR9qfOi7SplSstjB3r4MABEwsXNnP//X7MbTy6rKzx\nRQatGsC2XX9i5JlutmS+wiUnXNq2i4iIiMiPouJJRESkA7HZYMqUFrZt8zBxYoCdO01kZztwux1s\n366XdYk+ra1w3302brvNgcsFq1f7uOGGljZdoznYzIzq6WRvzKI52MzCKx7l91f9gaNtx7TpOiIi\nIvLj6Q5VRESkA+rRw2DePD/V1V7S0oLU1VlITXUybZqdXbs0gFyiw6FDMH68gyeeiOWnP22lvNzD\ngAFtO0T8g6/fJ/35QSx7+/ecfew5VGS8zA19szGZ9P+BiIhINFDxJCIi0oH17h2isNBHSYmXvn1D\nFBdbSUyMIz8/Fo8n0umkK/vsMxPDhjmpqLBw+eVBysu9nHFG230m1DAMnnt3BVeVXM47e99m/LkT\n2DT2Jc4+9pw2W0NERESOnIonERGRTiAlpZXKSi8FBT5cLoMFC2wkJsZRVGQhFIp0OulqXn01hrQ0\nJ+++a+ammwI895yPo49uu+sfDBxgSuUEflV1K5YYK0vTnuWhyx/BYXG03SIiIiLSJlQ8iYiIdBJm\nM2RlBamv95Cb62f/fhM5OQ5SU53U1rbxFGeR77B6tYWrr3bS1GRi/vxmHnzQj8XSdtd/Y/frDFqV\nxJoPS7ik16VszaxhxJmj224BERERaVMqnkRERDoZlwtmzAhQV+chI6OFhgYzbreT8ePtNDZq7o2E\nRygE8+bFMnWqA7sdVq70MWFC2w0RDxkhFr3xKMPWprLzwKf86uLplI4u55SjTm2zNURERKTtmQyj\nYx3AvGfPwUhHEJFOpmfPbtpbpFN7880Y7r3XRn29BYvFYMKEFnJz/XTvHulknVtX2ls8HvjlL+1s\n2GDltNNC/PGPPnr3brvPeO7x7mHa1lvYurOS4529WHTlEi4/eWCbXV+kI+lKe4uItJ+ePbuF7dp6\n4klERKST69cvRGmpj2XLfMTHGyxeHEv//i6WLLESCEQ6nXR0X35pYuRIJxs2WBkwIMjGjZ42LZ2q\nP3+JgasuY+vOSgadMpiqzDqVTiIiIh2IiicREZEuwGSC4cOD1NR4mDOnmVAI8vLsJCfHUVZmoWM9\n/yzR4o03vhki3tBg5vrrAxQX+zj22La5dktrC/Pq55Lxwii+bt7L7MTfsHJYCT2dPdtmAREREWkX\nKp5ERES6EJsNpkxpYds2DxMnBti500R2tgO328H27botkB+utNTCqFFO9uwxMXduMwsX+omNbZtr\n7zzwKaPWDaHgLws45ahTedFdwdSLcogx6d+oiIhIR6NXbxERkS6oRw+DefP8VFd7SUsLUldnITXV\nybRpdnbt0gBy+W6GAQ89FMukSQ4sFigs9DF5cgumNvpns/6jUgatSuK13a/i/ukYtmbWcHGvS9rm\n4iIiItLuVDyJiIh0Yb17hygs9FFS4qVv3xDFxVYSE+PIz4/F44l0Ook2Ph9MnmznoYdsnHJKiA0b\nvKSmtrbNtYM+7njpNiZsuoFgqIWCgYt4KnUZ3WKPapPri4iISGSoeBIRERFSUlqprPRSUODD5TJY\nsMBGYmIcRUUWQm03J1o6sN27TYwe7WTtWiuXXhqkvNzLOee0zT+O975+l/SSgTz7zjL69jiPirEv\nk3XODZja6jEqERERiRgVTyIiIgKA2QxZWUHq6z3k5vrZv99ETo6D1FQntbXmSMeTCGpo+GaI+Btv\nmMnMbOH553307HnkE+kNw6DwnT+QVnIF7379DjedN4mNY7bS59iz2iC1iIiIRAMVTyIiIvJvXC6Y\nMSNAXZ2HjIwWGhrMuN1Oxo+309ioJ1C6mrIyCyNGONm1y0Renp/HHmvGZjvy6x7w7+fmil8w/aUc\nbGYby9P/yIMpC7Fb7Ed+cREREYkaKp5ERETkW8XHGyxa1ExFhYeEhCDl5VaSkuKYNctGU1Ok00m4\nGQY8+mgs2dkOAJYvbyYnJ9AmQ8Rf+9urDFqVROlHa7j0hAS2ZtYy7IwRR35hERERiToqnkREROR/\n6tcvRGmpj2XLfMTHGyxeHEv//i6WLLESCEQ6nYSD3w/Tptn5zW9snHRSiPXrvQwdGjzi64aMEI/+\n5RFGrkvns4M7yb3kLtaNLuMn3U5ug9QiIiISjVQ8iYiIyPcymWD48CA1NR7mzGkmFIK8PDvJyXGU\nlVkwjnzcj0SJPXtMjBnjYNUqKxdf3MqmTV7OP//Ih4jv9u5m3Ho3v6mfzXGOnjw/aj0zLs3DEmNp\ng9QiIiISrVQ8iYiIyA9ms8GUKS1s2+Zh4sQAO3eayM524HY72L5dtxUd3TvvxJCe7uTVVy243S2s\nXeulV68jbxWrdm5hYPFlvPx5FYNPuYqtmbUkxae0QWIRERGJdmG9QzQMg9mzZ3PNNddw44038tln\nn/3b91988UUyMzPJysrivvvuC2cUERERaUM9ehjMm+enutpLWlqQujoLqalOpk2zs2uXBpB3RJs3\nmxk2zMlnn8Vw111+nnqqGYfjyK7Z0trC3D/dy7gX3ez372PugHn8cdhqjnMc1zahRUREJOqFtXiq\nrKwkEAhQVFTE9OnTmT9//j+/5/f7efTRR1mxYgUrV67k4MGDVFVVhTOOiIiItLHevUMUFvooKfHS\nt2+I4mIriYlx5OfH4vFEOp38EIYBTz5p5frrHbS2wu9/7+OOO458iPinBz5h5Lo0Hn+jgNOPPoOy\nqyuZfOEvMbXFdHIRERHpMMJaPL3++uskJycDcOGFF/L222//83uxsbEUFRURGxsLQDAYxNYWZ/OK\niIhIu0tJaaWy0ktBgQ+Xy2DBAhuJiXEUFVkIHfl4IAmTQACmT7cxe7ad4483KC31MmrUkQ8RX/fh\n8wxalcTru19jbJ9xbMl4hQuPv6gNEouIiEhHE9bi6dChQ3Tr1u2fX1ssFkL/uPs0mUwce+yxABQW\nFuLz+bjsssvCGUdERETCyGyGrKwg9fUecnP97N9vIifHQWqqk9pac6TjyX/4+mvIzHSwYkUs55//\nzRDxiy46spbQ2+Ilt2oaN2/+Ba2hVh4b9BRPDP49rthu3/+HRUREpFMK6zEiLpcLz788Zx8KhYiJ\n+f9dl2EY5Ofn8+mnn/L444//oGv27KkbFxFpe9pbRNpOz56wcCHcdhv8+tdQWGjG7XYyejTk50Pv\n3pFO2H6idW957z0YPhw++giuvhqefdZMXJzriK7ZsLuBa9Zdwzt73qHfCf0oGlPEWced1UaJReRf\nReveIiLybcJaPF188cVUVVWRnp7Om2++SZ8+ff7t+7NmzcJut/PEE0/84Gvu2XOwrWOKSBfXs2c3\n7S0iYWC3f1NA3XBDDPfea2PdOgsvvmgwYUILubl+unePdMLwita9parKzKRJDg4cMHH77X7uvjuA\n1wte7+FdzzAMntmxjHtr76G5tZlJ50/m3svux2bYovLvL9LRReveIiIdWzgLbZNhGEd+Ru53MAyD\n++67j/fffx+A+fPns2PHDnw+H+eeey5jx47lZz/72TdBTCZuvPFGBg8e/D+vqU1WRNqabuBEws8w\nYMMGC3Pm2Pj00xiOOcbgjjv8ZGe38I9xj51ONO4tS5daycuzYTbDI480k5FxZPOc9jU3kftSDi82\nltLd1p3fDXqS9NOHtlFaEfk20bi3iEjH12GLp3DQJisibU03cCLtx++HZcusLFxo48ABE6efHmL2\nbD9DhgSP+BS1aBNNe0swCL/+tY3ly2M57rgQzzzj4+c/P7J5Tq/u2sbkzTfx+aHPSDxpAE8OfpqT\nXPFtlFhEvks07S0i0nmEs3gK63BxERERkX9ls8GUKS1s2+Zh4sQAO3eayM524HY72L5dtyXhsG8f\nXHONg+XLYznnnG+GiB9J6dQaaqXg9QWMWpfOl54vuPPn97Bm5IsqnURERORb6Q5PRERE2l2PHgbz\n5vmprvaSlhakrs5CaqqTadPs7NrVyR59iqDGRhNDhzqprrZw1VVBNmzwcvLJh/+w+27P38hcP5p5\n2+ZyvLMXa0dt4M6f34M5RqcWioiIyLdT8SQiIiIR07t3iMJCHyUlXvr2DVFcbCUxMY78/Fj+5WBc\nOQw1NWbS0+P461/NTJ0a4JlnfLiO4OC6LZ9WMHDVZbzyxcuknTaEqnG1JJ40oO0Ci4iISKek4klE\nREQiLiWllcpKLwUFPlwugwULbCQmxlFUZCF0ZKOIuqTCQiuZmQ48Higo8DF7th/zYT6UFGgNMLv2\n11y7YSwH/AeYl5TPs0OKONbeo21Di4iISKek4klERESigtkMWVlB6us95Ob62b/fRE6Og9RUJ7W1\n+ijXD9HaCrNm2Zg+3c5RRxmUlPjIyjr8k+s+3t/I8DWpPPnWY5x5zE8pH7OFiRdMxtTZJsGLiIhI\n2Kh4EhERkajicsGMGQHq6jxkZLTQ0GDG7XYyfrydxkYVHt/l4EG44QYHixfH0qdPK+XlXhITWw/7\nems+XM2Vq5J5c88bjDsri80Z1Zzf88I2TCwiIiJdgYonERERiUrx8QaLFjVTUeEhISFIebmVpKQ4\nZs2y0dQU6XTR5dNPTQwb5qSy0sLAgUHKyrycfvrhDRH3tHj41dZbmbx5AgYGi65cwmNXPoXLegQD\nokRERKTLUvEkIiIiUa1fvxClpT6WLfMRH2+weHEs/fu7WLLESiAQ6XSRV19vJj3dyXvvmZk0KcAf\n/+jjqKMO71pv/72Bq1ZfznPvreCCnv3YklFNxlnXtG1gERER6VJUPImIiEjUM5lg+PAgNTUe5sxp\nJhSCvDw7yclxlJVZMA7v4Z4Or6jIwtixDvbtM5Gf38wDD/ixWH78dQzDYGnDEoY8P4gP933ALRdO\nZcPVmznjmJ+2fWgRERHpUlQ8iYiISIdhs8GUKS1s2+Zh4sQAO3eayM524HY72L6969zWhEJw//2x\n5OQ4cDiguNhHdnbLYV2rqflrsjdexz2v3IHL6uKPQ1dx/4D52My2Nk4tIiIiXVHXuUMTERGRTqNH\nD4N58/xUV3tJSwtSV2chNdXJtGl2du3q3APIDx2C7Gw7jz1m44wzQmzc6CEl5fCGiNfv+hODViVR\n/vGLJMWnUDWujtTT0ts4sYiIiHRlKp5ERESkw+rdO0RhoY+SEi99+4YoLraSmBhHfn4sHk+k07W9\nzz83MWKEk40brSQnBykv93DmmT/+c4atoVYWvvZbRq8bwi7Pl8y4NI/VI0o5Ie7EMKQWERGRrkzF\nk4iIiHR4KSmtVFZ6KSjw4XIZLFhgIzExjqIiC6FQpNO1jddeiyEtzcmOHWZuvDFAUZGP7t1//HV2\nHfqSsS+M5LevPsCJcSexbnQ5uZfchTnG3PahRUREpMtT8SQiIiKdgtkMWVlB6us95Ob62b/fRE6O\ng9RUJ7W1HbtUWbPGgtvtZO9eEw880MxDD/mxWn/8dSo+KWfgqsuo/fIVhp4+gq2ZNSScmNj2gUVE\nRET+QcWTiIiIdCouF8yYEaCuzkNGRgsNDWbcbifjx9tpbOxY859CIfjtb2OZPNlBbCysXOlj0qQW\nTD/yr+Fv9TOrZgbXl43D0+LhwZSFLE9fQXf7seEJLiIiIvIPKp5ERESkU4qPN1i0qJmKCg8JCUHK\ny60kJcUxa5aNpqZIp/t+Xi/cfLOdhQttnHpqiLIyL4MG/fgh4o37/sqwNaks3v4EvY/pQ/mYrdx0\n3iRMP7a9EhERETkMKp5ERESkU+vXL0RpqY9ly3zExxssXhxL//4uliyxEghEOt3/a+/Og6sqDz6O\n/+6elUUM2ArFDbQqZXXpWCiIkQExBQMUYcAlLgVBBWSAogasghVbsSyWKNrYYQStDIos5kUpFBgR\nUFCxLy9aKLJIwiKScJfce877R25ubhbghuTkZvl+Zhjvcs65z8GZzMmX5zm3at9/b9OgQUl6/32X\nbr45qLVrz+jqq6t/s6p39ixV33d66YuCnRpxzSjlDd2g6y/uZMGIAQAAqkZ4AgAAjZ7NJg0cGNSm\nTUWaOdMnw5CefDJBPXsma/Vqp8zqfzGcZXbtsuv225O0c6dDd99drHfe8apVq+oNsLC4UOM+eliP\nfPSQbLLpr+mLNffWBUp2JVs0agAAgKoRngAAQJPh8UhjxhRr69YiPfBAQAcO2HTvvYkaPDhRX3wR\n/8uilSudyshI0tGjNmVn+zR3rk8eT/WO8WXBLt32dk+9vectdW3dTR8N+5fu6jDUmgEDAACcR/yv\nsAAAAOpYq1amZs3ya+PGM+rXL6gtW5xKT0/S+PEJOnKk7u99ZJrSSy+5lZWVKJtNys316pFHqncT\ncdM0lbNrofq/21f/OfWtxnZ5VCsH5+ny5ldYN3AAAIDzsJlmfZpcfn4FBafjPQQAjUxaWio/W4Am\nbuNGh7KzPdq926GkJFNjxwb0yCMBJddgZVqsP1t8PmnChAS9+65Lbdsa+vvfvbruuurdz+m497ge\nXz9WH+5fo4sTL9b8vot068/SL3ToAOoxrlsAWCEtLdWyYzPjCQAANHm9eoW0bt0ZzZ3rVUqKqRdf\n9OiXv0zW0qVOGdW/p3fM8vNtGjw4Se++61KPHiGtXXum2tFpy6FNuvXtW/Th/jXq2ba31g/bQnQC\nAAD1BuEJAABAksMhjRgR1CefFGniRL9OnbLp0UcTlZ6epM2bHbX+ebt329WvX5J27HAoM7NYy5ef\nUevWsU9EDxpBvfDpLN31/kDlnzmq6Tdl6507V6hN8iW1PlYAAIALRXgCAACIkpIiTZ0a0JYtRRo6\ntFhffunQ4MFJuueeBP3nP7Vz/6e1ax26444kHTpk17Rpfi1c6FNCQuz7Hzp9UHe9N1Avbn9el6a0\n1XuD1uqx7pNkt3FpBwAA6heuTgAAAKpw6aWmFizwKS+vSDffHNSaNS796lfJeuopj06evLBjmqY0\nf75L99yTKNOUFi/2asKEQLVuIr5232rd+vYt+uTIFg284jf6eNgm3fiTmy5sQAAAABYjPAEAAJxD\nly6G3nvPq9df9+rSS00tWuTWTTelKCfHpUAg9uMEAtLjjyfomWcS1KaNqZUrz+jOO4Mx7+8L+vT7\nf03W6DXD5Q16NefXc7W435tq7mlxAWcFAABQNwhPAAAA52GzSQMHBrVpU5FmzvTJMKQnn0xQz57J\nWr3aqfN9R/Dx4zYNGZKot95yqUuXkPLyzugXv4j9JuLfnNyr/u/21WtfLtLVLa/Rh0P+qXuuu1+2\n6kyVAgAAiAPCEwAAQIw8HmnMmGJt3VqkBx4I6MABm+69N1GDByfqiy+qvqzas6fkJuKffOJURkax\nVqw4o0suie0m4qZpaun/LtFt7/TS7uNfatS19+nDIf/Uz1tdW5unBQAAYBnCEwAAQDW1amVq1iy/\nNm48o379gtqyxan09CSNH5+gI0fKZiF9/LFDAwYk6cABuyZN8isnx6ekpNg+ozBwWmPXPahHPx4j\nh92h127P1Z96v6wkV4wHAAAAqAdspnm+yeH1S0HB6XgPAUAjk5aWys8WADWycaND2dke7d7tUFKS\nqbFjA/rJTzyaPNmUyyW9/LJPd90V+/2cduZ/pofy7tP+H/epe5se+mv662rf7DLrTgBAg8F1CwAr\npKWlWnZswhOAJo8LOAC1IRSSli1zatYsj/LzSyaVp6UZevNNr7p3j+1+ToZpaNGuhXr2k2wVG8V6\ntOtETblxulwOl5VDB9CAcN0CwApWhienZUcGAABoQhwOacSIoDIyglqwwK1vvvFoxowzuvTS2P6N\n75j3mB796HdadyBPaYmtteC2HPVud6vFowYAALAW4QkAAKAWpaRIU6YElJbmUUFBbNHpXwc3aOy6\nB3X0zPfq3e5Wze+bo9ZJrS0eKQAAgPUITwAAAHESNIKas22W5u74kxx2h5765TN6pMujstv4/hcA\nANA4EJ4AAADi4ODp7/S7/8nSp99/op+lttei219X9zY3xHtYAAAAtYrwBAAAUMc++PZ9TfjnOJ3y\n/6BBV92lF3/9spp5msd7WAAAALWO8AQAAFBHvEGvsjf/Xn/bvViJzkS91Hu+Rvx8lGw2W7yHBgAA\nYAnCEwAAQB34vxN79GDevfr3id36+UXXKuf2v+nqi66J97AAAAAsxZ0rAQAALGSappZ8/abS/9FL\n/z6xW/del6W1Q9YTnQAAQJPAjCcAAACL/Og/pSc2PKYV3yxXc08Lze+bozuv/E28hwUAAFBnCE8A\nAAAW+PTQpxr6zm914Mf9uuGSm/TX9MVql/qzeA8LAACgThGeAABAk2GapoJGUP6QT76QX4GQX76Q\nT/5g6WO//CFfyeNg6eNAyTalj4M++UNn394f8ssf8uvz/B0KGSFN6P6EJt/wezntXHYBAICmhysg\nAABQJ0zTDEcZn/yhQMl/g/6o1/xlf4LRz8PbB33l941sW3H/6O1LwlIg/J4v6JMp0/JzddgcuqzF\nZXqh51z1bPtryz8PAACgviI8AQDQBISMUOXAU0Ww8QWjZgFFz+oJVn/mT9n2/kj4qQtuu1seZ4I8\nDrc8jgSluFLkSWglj8MjjzNBbodHCQ6PPI4EuR1uJTgS5HGWPPc4PJHtPJHjhF9zJCjB6ZE7/DzB\nkVD22FlyrNJjOO1OpaWlqqDgdJ2cMwAAQH1FeAIAwEI1XdpVNiOo4kyhKmb+nG2mUMinoBG0/Fxt\nsoUDTFmYaeFpEXOwSXCUblN5e48zQW67WwnhEOSOvO6pFJLsNr60FwAAoL4gPAEAGi2rl3b5wpEo\neqZQPJd2lQab0gDTzN3sLMEmPPPH7im3ffmQU8X2UYHH4/TIYy95vTQYuewu2Ww2y88VAAAADQfh\nCQBgiYpLu3zBqEhTRbCp7aVd/qBPASNQJ+d6vqVdJcuv3BWWctX+0i4AAACgvuEqFQAamQtZ2lVu\npk8TWNpVbiZP+L3KM39Y2gUAAADUFOEJAGqRFUu7zjdTKF5Lu5x2Z6WlWrWxtCsyO6jiTCGWdgEA\nAAANDuEJQKMRMkKVAkwsS7vciTYdO3Uq5qVd55r5U/dLu0pm8ZQs7bq46mBTi0u7SkMSS7sAAAAA\nxILfGgDU2LmWdp1/qVbjWtpVbiZP6WOWdgEAAACojwxDCoUs/QjCE9DA1WRpV9lSrbJg1JiXdp1t\n5k/ri1rKVxhiaRcAAADQ0JSGk1BICgZlM8KPQyWv20LByPsl7xlSMBj1goXlhwAADB1JREFUvHTf\nCs+NkGzBYOQ4MkKyhT+jZN+ozw0FS96L3jYYjDqWUbZv+DPKti/dN/pzyx5Htg1WeG6EX4t+Hgp/\nbtTYbOHxRf4+Ss8xGP7cUqZ1v88RnoAauNClXWf71q4LmfnTkJd2JZxt5k8VM4WsXNqVlpaqgoLT\nlhwbAAAAOCfCSe2EkybEdDgkp1NyOGTaHZLDITnsksNZ8l7pH5dLRng72R1l7zkrPLc75LZwvIQn\nNEimaarYKC4XcPyGv9aXdvnCYccfrCIkGf64Le1q6WkZc7C50KVd0SGJpV0AAAA4K8IJ4aSarAgn\nclZ47nDIdJY9lqP0fafksFfYN/y5dnvZtk5n1L72qH3D75duG9k3atty+4bP0VnheeTvwB71d+CQ\nGfkMe9S+ZZ8ruzW/l6VZctQShCdUWyxLu84ZbBrh0q6zfgvX2Wb+8K1dAAAA9UdDCiduu5ILvYST\nOCOc1L9wgvqL8NTAXOjSrpIZQYHKN2VupEu7EsKRKDrg1KelXQAAALWqIYUTZpzUWFItHINwQjgB\n6gq/VcfIyqVdlWb+1JOlXdFLr2pzaVfZrJ+oWUAs7QIAoGkjnDSpcFIbmmo4aXlxM5380Uc4AdBg\nNKjw9KP/R+WfKYiEnEozfyxY2hW5EXSclnZ5HJ7I0q7KwaZ2lnZFZgGFt3PanSztAgCguiqEE7kN\n2U7+QDghnJxVUw0nzDipobRUBflSFAANSIMKT82fb27p8ata2tWqwtKucsu2nOHlXCztAgA0Bsw4\nqfVwcnEd/y+sa4QTwgkAAOfToCrH4GsGyyi2nXVpV0kcqjjzh6VdANBklAsY0aEkKhSUCyVGFZGl\n5PXoyFIWSio8j+xb1edWHVki4SQSMaLCSaXIEpKtNO5UEVkqhhIFKzwPhcqFmEqRJXq7oPVLueuj\nsgDiLB9O7OFgER1OSgNDdCipGFnsZcHCk+iRP2hGhZIK4eSskcVZPpyUCyX2qH1Lg8/ZI0v5AFIa\nSuxVxKLwWOwVx+ksH06iQhPhBAAAxKJBhaflv12uAqaVAmjMCCeEk2qyMpyUiyGEk2pLS0vVj1y3\nAACAJq5BhScADUBDDCduh1IKvYSTOCGc1N9wAgAAANSUpeHJNE3NmDFDe/bskdvt1nPPPad27dqV\n28br9er+++/XrFmzdPnll1s5HCA2FQNGJJRUcU+P6HBSLrKEw4kRHTuigkU4YlQKEpU+t+rIUj6c\nlMQTZpzUTGIN9iWcEE4AAAAAVM3S8LRu3ToFAgEtXbpUu3bt0uzZs7Vw4cLI+1999ZWys7N19OhR\nK4fR9DSCcBKJGNHhpHR2SnQ4CY+vfCgxwjeEjR7bOSKLUWHcpvXfXljfNPVw0vLiZjpxykc4AQAA\nAIBaZml42rFjh3r27ClJ6ty5s7766qty7xcXF2vhwoWaPHlybAc8cUK2oycIJ4STSpp6OGHGSQ2l\npSrEfVgAAAAAoNZZGp4KCwuVmppa9mFOpwzDkD38i27Xrl0llSzJi0mrVo32a4nNSpEgKpxER4LS\ncBKOGOXCSXRksUfFjaiIQTgBAAAAAAB1xdLwlJKSoqKiosjz6Oh0QRrxTB7bWR4DqBtpaann3wgA\nqomfLQCswM8WAA2JpVNFunXrpg0bNkiSdu7cqY4dO1r5cQAAAAAAAKhHLJ3xlJ6ers2bN2v48OGS\npNmzZ+uDDz6Q1+vV0KFDI9vZbMzxAQAAAAAAaGxsZsw3WAIAAAAAAABix12ZAQAAAAAAYAnCEwAA\nAAAAACxBeAIAAAAAAIAlCE8AAAAAAACwBOEJAAAAAAAAlnDGewD79+/XtGnT5HQ6ZRiG2rdvrxtv\nvFGDBg3SsWPH9NBDD2nq1Kl69dVX5XK5dPDgQd1xxx16+OGHI/sdPnxYgUBAAwYM0Pr163XkyBEt\nXLhQ7dq1i/fpAQCARqqwsFBPPvmkTp8+rfz8fI0YMUKmaWrFihWy2+3q1KmTpk+frr179+r555+X\nYRg6efKkZsyYoS5dusR7+AAAoBGp6XXJtGnT9N1338nn82n06NHKyMjQhx9+qCVLligUCslms2n+\n/PkyDEMTJkyQaZoKBAKaMWOGrrnmmnOOLe7hafPmzercubMmT56s7du3q2XLlnruuec0aNAgvffe\ne8rMzJQkHTlyRCtXrpTP51PPnj318MMPS5Latm2rP/zhD8rOztahQ4eUk5OjefPmaf369Ro9enQ8\nTw0AADRiBw4c0MCBA3XbbbcpPz9fo0aNUrNmzZSdna3rr79eS5culWEY2rt3r6ZOnaoOHTrogw8+\n0PLlywlPAACgVtXkuqRDhw7asWOHli1bJknasmWLJOm///2vXn31VXk8Hj399NPatGmTUlNT1bJl\nS73wwgvau3evvF7veccW9/A0dOhQ5eTkKCsrS82aNdPjjz8uwzB0+PBhrV69Wrm5ufr666/VsWNH\n2Ww2JSYmKiEhIbL/tddeK0lq1qyZrrzyyshjv98fl/MBAABNQ6tWrZSbm6u8vDwlJycrGAxq9uzZ\nWrx4sQ4ePKiuXbvKNE21adNGCxYsUGJiogoLC5WSkhLvoQMAgEamJtclycnJmjZtmp566ikVFRUp\nIyNDktSyZUtNmTJFiYmJ2rdvn7p166ZevXpp//79GjNmjFwul8aMGXPescU9PK1bt049evTQuHHj\ntGrVKr322mvKzMzUnDlz1KFDh8jFmc1mq3L/s70OAABgpTfeeENdu3bV8OHDtXXrVm3YsEFvv/22\nZs6cKbfbraysLH322WeaPXu2XnzxRV1xxRWaN2+eDh8+HO+hAwCARqYm1yUFBQXavXu35s+fr0Ag\noN69eys9PV3z5s3Thg0bZJqm7rvvPpmmqa1btyotLU2LFy/Wzp079ec//1m5ubnnHFvcw1OnTp00\nZcoUvfLKKzIMQ9OnT9dll12mWbNm6ZVXXon5OAQoAABQl/r06aNnn31Wq1atUmpqqpxOp6666iqN\nGDFCycnJuuSSS9S5c2dlZGToscceU/PmzdWmTRv98MMP8R46AABoZGpyXZKWlqaCggINHz5cTqdT\nWVlZSklJUffu3TVs2DA5HA61aNFC+fn56tOnjyZOnKi33npLhmFo3Lhx5x2bzTRNsw7+DgAAAAAA\nANDE2OM9AAAAAAAAADROhCcAAAAAAABYgvAEAAAAAAAASxCeAAAAAAAAYAnCEwAAAAAAACxBeAIA\nAAAAAIAlCE8AAAAXaNSoUdq2bVu8hwEAAFBvEZ4AAAAAAABgCWe8BwAAANBQzJkzR+vWrZPL5dKw\nYcMir4dCIc2YMUN79+7V8ePHdfnll2v+/PkKBAKaNGmSjh07JkkaN26c+vTpozfeeEMrVqyQw+FQ\np06dNHPmzHidEgAAgKUITwAAADFYu3atdu7cqVWrVqm4uFh33323AoGAJOnzzz+X2+3W0qVLZZqm\nRo8erQ0bNqioqEht27bVokWL9O2332r58uXq1auXcnJytGnTJtntdj3zzDPKz89X69at43yGAAAA\ntY/wBAAAEINt27apf//+cjqdcjqdWrFihUaNGiVJ6tGjh1q0aKElS5Zo3759OnDggIqKitS1a1e9\n9NJL+v7779W7d2+NHTtWDodD3bp1U2Zmpvr27auRI0cSnQAAQKPFPZ4AAABi4HSW//e6gwcPyuv1\nSpI+/vhjPfHEE0pOTlZmZqZ69OghSWrfvr3WrFmjjIwMbd++XUOGDJEkLViwILK8LisrS9u3b6/D\nMwEAAKg7hCcAAIAY3HDDDcrLy1MwGJTX69WDDz6o/Px8SdKWLVs0YMAADRo0SBdddJG2bdumUCik\nJUuW6C9/+Yv69eunp59+WidOnNDJkyfVv39/dezYUePHj9ctt9yiPXv2xPnsAAAArGEzTdOM9yAA\nAAAagrlz5+qjjz6SJI0cOVKrV6/W+PHj1bx5c02aNEkul0tut1utW7fWlVdeqQceeEATJ07U4cOH\n5XK5lJmZqZEjRyo3N1fLli1TYmKifvrTn+qPf/yjkpKS4nx2AAAAtY/wBAAAAAAAAEuw1A4AAAAA\nAACWIDwBAAAAAADAEoQnAAAAAAAAWILwBAAAAAAAAEsQngAAAAAAAGAJwhMAAAAAAAAsQXgCAAAA\nAACAJQhPAAAAAAAAsMT/Aw2cfwN4R5FFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11cb7c150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sample_data_fold_one.plot(kind='line',title='Average Phone call duration per customer',color='red')\n",
    "sample_data_fold_two.plot(kind='line',title='Average Phone call duration per customer',color='blue',ax=ax)\n",
    "sample_data_fold_three.plot(kind='line',title='Average Phone call duration per customer',color='green',ax=ax)\n",
    "ax.set_ylabel('Phone Call Duration (in minutes)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [python2]",
   "language": "python",
   "name": "Python [python2]"
  },
  "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
}