12 - ML - K Means Clustering Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K Means Clustering Project \n",
    "\n",
    "For this project we will attempt to use KMeans Clustering to cluster Universities into to two groups, Private and Public.\n",
    "\n",
    "___\n",
    "It is **very important to note, we actually have the labels for this data set, but we will NOT use them for the KMeans clustering algorithm, since that is an unsupervised learning algorithm.** \n",
    "\n",
    "When using the Kmeans algorithm under normal circumstances, it is because you don't have labels. In this case we will use the labels to try to get an idea of how well the algorithm performed, but you won't usually do this for Kmeans, so the classification report and confusion matrix at the end of this project, don't truly make sense in a real world setting!.\n",
    "___\n",
    "\n",
    "## The Data\n",
    "\n",
    "We will use a data frame with 777 observations on the following 18 variables.\n",
    "* Private A factor with levels No and Yes indicating private or public university\n",
    "* Apps Number of applications received\n",
    "* Accept Number of applications accepted\n",
    "* Enroll Number of new students enrolled\n",
    "* Top10perc Pct. new students from top 10% of H.S. class\n",
    "* Top25perc Pct. new students from top 25% of H.S. class\n",
    "* F.Undergrad Number of fulltime undergraduates\n",
    "* P.Undergrad Number of parttime undergraduates\n",
    "* Outstate Out-of-state tuition\n",
    "* Room.Board Room and board costs\n",
    "* Books Estimated book costs\n",
    "* Personal Estimated personal spending\n",
    "* PhD Pct. of faculty with Ph.D.’s\n",
    "* Terminal Pct. of faculty with terminal degree\n",
    "* S.F.Ratio Student/faculty ratio\n",
    "* perc.alumni Pct. alumni who donate\n",
    "* Expend Instructional expenditure per student\n",
    "* Grad.Rate Graduation rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Libraries\n",
    "\n",
    "**Import the libraries you usually use for data analysis.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(style='darkgrid')\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get the Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Read in the College_Data file using read_csv. Figure out how to set the first column as the index.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "college = pd.read_csv('College_Data', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Check the head of the data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Private</th>\n",
       "      <th>Apps</th>\n",
       "      <th>Accept</th>\n",
       "      <th>Enroll</th>\n",
       "      <th>Top10perc</th>\n",
       "      <th>Top25perc</th>\n",
       "      <th>F.Undergrad</th>\n",
       "      <th>P.Undergrad</th>\n",
       "      <th>Outstate</th>\n",
       "      <th>Room.Board</th>\n",
       "      <th>Books</th>\n",
       "      <th>Personal</th>\n",
       "      <th>PhD</th>\n",
       "      <th>Terminal</th>\n",
       "      <th>S.F.Ratio</th>\n",
       "      <th>perc.alumni</th>\n",
       "      <th>Expend</th>\n",
       "      <th>Grad.Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Abilene Christian University</th>\n",
       "      <td>Yes</td>\n",
       "      <td>1660</td>\n",
       "      <td>1232</td>\n",
       "      <td>721</td>\n",
       "      <td>23</td>\n",
       "      <td>52</td>\n",
       "      <td>2885</td>\n",
       "      <td>537</td>\n",
       "      <td>7440</td>\n",
       "      <td>3300</td>\n",
       "      <td>450</td>\n",
       "      <td>2200</td>\n",
       "      <td>70</td>\n",
       "      <td>78</td>\n",
       "      <td>18.1</td>\n",
       "      <td>12</td>\n",
       "      <td>7041</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adelphi University</th>\n",
       "      <td>Yes</td>\n",
       "      <td>2186</td>\n",
       "      <td>1924</td>\n",
       "      <td>512</td>\n",
       "      <td>16</td>\n",
       "      <td>29</td>\n",
       "      <td>2683</td>\n",
       "      <td>1227</td>\n",
       "      <td>12280</td>\n",
       "      <td>6450</td>\n",
       "      <td>750</td>\n",
       "      <td>1500</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>12.2</td>\n",
       "      <td>16</td>\n",
       "      <td>10527</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrian College</th>\n",
       "      <td>Yes</td>\n",
       "      <td>1428</td>\n",
       "      <td>1097</td>\n",
       "      <td>336</td>\n",
       "      <td>22</td>\n",
       "      <td>50</td>\n",
       "      <td>1036</td>\n",
       "      <td>99</td>\n",
       "      <td>11250</td>\n",
       "      <td>3750</td>\n",
       "      <td>400</td>\n",
       "      <td>1165</td>\n",
       "      <td>53</td>\n",
       "      <td>66</td>\n",
       "      <td>12.9</td>\n",
       "      <td>30</td>\n",
       "      <td>8735</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnes Scott College</th>\n",
       "      <td>Yes</td>\n",
       "      <td>417</td>\n",
       "      <td>349</td>\n",
       "      <td>137</td>\n",
       "      <td>60</td>\n",
       "      <td>89</td>\n",
       "      <td>510</td>\n",
       "      <td>63</td>\n",
       "      <td>12960</td>\n",
       "      <td>5450</td>\n",
       "      <td>450</td>\n",
       "      <td>875</td>\n",
       "      <td>92</td>\n",
       "      <td>97</td>\n",
       "      <td>7.7</td>\n",
       "      <td>37</td>\n",
       "      <td>19016</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska Pacific University</th>\n",
       "      <td>Yes</td>\n",
       "      <td>193</td>\n",
       "      <td>146</td>\n",
       "      <td>55</td>\n",
       "      <td>16</td>\n",
       "      <td>44</td>\n",
       "      <td>249</td>\n",
       "      <td>869</td>\n",
       "      <td>7560</td>\n",
       "      <td>4120</td>\n",
       "      <td>800</td>\n",
       "      <td>1500</td>\n",
       "      <td>76</td>\n",
       "      <td>72</td>\n",
       "      <td>11.9</td>\n",
       "      <td>2</td>\n",
       "      <td>10922</td>\n",
       "      <td>15</td>\n",
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      ],
      "text/plain": [
       "                             Private  Apps  Accept  Enroll  Top10perc  \\\n",
       "Abilene Christian University     Yes  1660    1232     721         23   \n",
       "Adelphi University               Yes  2186    1924     512         16   \n",
       "Adrian College                   Yes  1428    1097     336         22   \n",
       "Agnes Scott College              Yes   417     349     137         60   \n",
       "Alaska Pacific University        Yes   193     146      55         16   \n",
       "\n",
       "                              Top25perc  F.Undergrad  P.Undergrad  Outstate  \\\n",
       "Abilene Christian University         52         2885          537      7440   \n",
       "Adelphi University                   29         2683         1227     12280   \n",
       "Adrian College                       50         1036           99     11250   \n",
       "Agnes Scott College                  89          510           63     12960   \n",
       "Alaska Pacific University            44          249          869      7560   \n",
       "\n",
       "                              Room.Board  Books  Personal  PhD  Terminal  \\\n",
       "Abilene Christian University        3300    450      2200   70        78   \n",
       "Adelphi University                  6450    750      1500   29        30   \n",
       "Adrian College                      3750    400      1165   53        66   \n",
       "Agnes Scott College                 5450    450       875   92        97   \n",
       "Alaska Pacific University           4120    800      1500   76        72   \n",
       "\n",
       "                              S.F.Ratio  perc.alumni  Expend  Grad.Rate  \n",
       "Abilene Christian University       18.1           12    7041         60  \n",
       "Adelphi University                 12.2           16   10527         56  \n",
       "Adrian College                     12.9           30    8735         54  \n",
       "Agnes Scott College                 7.7           37   19016         59  \n",
       "Alaska Pacific University          11.9            2   10922         15  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "college.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Private</th>\n",
       "      <th>Apps</th>\n",
       "      <th>Accept</th>\n",
       "      <th>Enroll</th>\n",
       "      <th>Top10perc</th>\n",
       "      <th>Top25perc</th>\n",
       "      <th>F.Undergrad</th>\n",
       "      <th>P.Undergrad</th>\n",
       "      <th>Outstate</th>\n",
       "      <th>Room.Board</th>\n",
       "      <th>Books</th>\n",
       "      <th>Personal</th>\n",
       "      <th>PhD</th>\n",
       "      <th>Terminal</th>\n",
       "      <th>S.F.Ratio</th>\n",
       "      <th>perc.alumni</th>\n",
       "      <th>Expend</th>\n",
       "      <th>Grad.Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Texas A&amp;M Univ. at College Station</th>\n",
       "      <td>No</td>\n",
       "      <td>14474</td>\n",
       "      <td>10519</td>\n",
       "      <td>6392</td>\n",
       "      <td>49</td>\n",
       "      <td>85</td>\n",
       "      <td>31643</td>\n",
       "      <td>2798</td>\n",
       "      <td>5130</td>\n",
       "      <td>3412</td>\n",
       "      <td>600</td>\n",
       "      <td>2144</td>\n",
       "      <td>89</td>\n",
       "      <td>91</td>\n",
       "      <td>23.1</td>\n",
       "      <td>29</td>\n",
       "      <td>8471</td>\n",
       "      <td>69</td>\n",
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       "                                   Private   Apps  Accept  Enroll  Top10perc  \\\n",
       "Texas A&M Univ. at College Station      No  14474   10519    6392         49   \n",
       "\n",
       "                                    Top25perc  F.Undergrad  P.Undergrad  \\\n",
       "Texas A&M Univ. at College Station         85        31643         2798   \n",
       "\n",
       "                                    Outstate  Room.Board  Books  Personal  \\\n",
       "Texas A&M Univ. at College Station      5130        3412    600      2144   \n",
       "\n",
       "                                    PhD  Terminal  S.F.Ratio  perc.alumni  \\\n",
       "Texas A&M Univ. at College Station   89        91       23.1           29   \n",
       "\n",
       "                                    Expend  Grad.Rate  \n",
       "Texas A&M Univ. at College Station    8471         69  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "college.loc[['Texas A&M Univ. at College Station']] # Just wanted to see some info about my college :D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Check the info() and describe() methods on the data.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 777 entries, Abilene Christian University to York College of Pennsylvania\n",
      "Data columns (total 18 columns):\n",
      "Private        777 non-null object\n",
      "Apps           777 non-null int64\n",
      "Accept         777 non-null int64\n",
      "Enroll         777 non-null int64\n",
      "Top10perc      777 non-null int64\n",
      "Top25perc      777 non-null int64\n",
      "F.Undergrad    777 non-null int64\n",
      "P.Undergrad    777 non-null int64\n",
      "Outstate       777 non-null int64\n",
      "Room.Board     777 non-null int64\n",
      "Books          777 non-null int64\n",
      "Personal       777 non-null int64\n",
      "PhD            777 non-null int64\n",
      "Terminal       777 non-null int64\n",
      "S.F.Ratio      777 non-null float64\n",
      "perc.alumni    777 non-null int64\n",
      "Expend         777 non-null int64\n",
      "Grad.Rate      777 non-null int64\n",
      "dtypes: float64(1), int64(16), object(1)\n",
      "memory usage: 135.3+ KB\n"
     ]
    }
   ],
   "source": [
    "college.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Apps</th>\n",
       "      <th>Accept</th>\n",
       "      <th>Enroll</th>\n",
       "      <th>Top10perc</th>\n",
       "      <th>Top25perc</th>\n",
       "      <th>F.Undergrad</th>\n",
       "      <th>P.Undergrad</th>\n",
       "      <th>Outstate</th>\n",
       "      <th>Room.Board</th>\n",
       "      <th>Books</th>\n",
       "      <th>Personal</th>\n",
       "      <th>PhD</th>\n",
       "      <th>Terminal</th>\n",
       "      <th>S.F.Ratio</th>\n",
       "      <th>perc.alumni</th>\n",
       "      <th>Expend</th>\n",
       "      <th>Grad.Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.000000</td>\n",
       "      <td>777.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3001.638353</td>\n",
       "      <td>2018.804376</td>\n",
       "      <td>779.972973</td>\n",
       "      <td>27.558559</td>\n",
       "      <td>55.796654</td>\n",
       "      <td>3699.907336</td>\n",
       "      <td>855.298584</td>\n",
       "      <td>10440.669241</td>\n",
       "      <td>4357.526384</td>\n",
       "      <td>549.380952</td>\n",
       "      <td>1340.642214</td>\n",
       "      <td>72.660232</td>\n",
       "      <td>79.702703</td>\n",
       "      <td>14.089704</td>\n",
       "      <td>22.743887</td>\n",
       "      <td>9660.171171</td>\n",
       "      <td>65.46332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3870.201484</td>\n",
       "      <td>2451.113971</td>\n",
       "      <td>929.176190</td>\n",
       "      <td>17.640364</td>\n",
       "      <td>19.804778</td>\n",
       "      <td>4850.420531</td>\n",
       "      <td>1522.431887</td>\n",
       "      <td>4023.016484</td>\n",
       "      <td>1096.696416</td>\n",
       "      <td>165.105360</td>\n",
       "      <td>677.071454</td>\n",
       "      <td>16.328155</td>\n",
       "      <td>14.722359</td>\n",
       "      <td>3.958349</td>\n",
       "      <td>12.391801</td>\n",
       "      <td>5221.768440</td>\n",
       "      <td>17.17771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>81.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2340.000000</td>\n",
       "      <td>1780.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>250.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3186.000000</td>\n",
       "      <td>10.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>776.000000</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>242.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>992.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>7320.000000</td>\n",
       "      <td>3597.000000</td>\n",
       "      <td>470.000000</td>\n",
       "      <td>850.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>11.500000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>6751.000000</td>\n",
       "      <td>53.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1558.000000</td>\n",
       "      <td>1110.000000</td>\n",
       "      <td>434.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>1707.000000</td>\n",
       "      <td>353.000000</td>\n",
       "      <td>9990.000000</td>\n",
       "      <td>4200.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>13.600000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>8377.000000</td>\n",
       "      <td>65.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3624.000000</td>\n",
       "      <td>2424.000000</td>\n",
       "      <td>902.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>4005.000000</td>\n",
       "      <td>967.000000</td>\n",
       "      <td>12925.000000</td>\n",
       "      <td>5050.000000</td>\n",
       "      <td>600.000000</td>\n",
       "      <td>1700.000000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>16.500000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>10830.000000</td>\n",
       "      <td>78.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>48094.000000</td>\n",
       "      <td>26330.000000</td>\n",
       "      <td>6392.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>31643.000000</td>\n",
       "      <td>21836.000000</td>\n",
       "      <td>21700.000000</td>\n",
       "      <td>8124.000000</td>\n",
       "      <td>2340.000000</td>\n",
       "      <td>6800.000000</td>\n",
       "      <td>103.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>39.800000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>56233.000000</td>\n",
       "      <td>118.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Apps        Accept       Enroll   Top10perc   Top25perc  \\\n",
       "count    777.000000    777.000000   777.000000  777.000000  777.000000   \n",
       "mean    3001.638353   2018.804376   779.972973   27.558559   55.796654   \n",
       "std     3870.201484   2451.113971   929.176190   17.640364   19.804778   \n",
       "min       81.000000     72.000000    35.000000    1.000000    9.000000   \n",
       "25%      776.000000    604.000000   242.000000   15.000000   41.000000   \n",
       "50%     1558.000000   1110.000000   434.000000   23.000000   54.000000   \n",
       "75%     3624.000000   2424.000000   902.000000   35.000000   69.000000   \n",
       "max    48094.000000  26330.000000  6392.000000   96.000000  100.000000   \n",
       "\n",
       "        F.Undergrad   P.Undergrad      Outstate   Room.Board        Books  \\\n",
       "count    777.000000    777.000000    777.000000   777.000000   777.000000   \n",
       "mean    3699.907336    855.298584  10440.669241  4357.526384   549.380952   \n",
       "std     4850.420531   1522.431887   4023.016484  1096.696416   165.105360   \n",
       "min      139.000000      1.000000   2340.000000  1780.000000    96.000000   \n",
       "25%      992.000000     95.000000   7320.000000  3597.000000   470.000000   \n",
       "50%     1707.000000    353.000000   9990.000000  4200.000000   500.000000   \n",
       "75%     4005.000000    967.000000  12925.000000  5050.000000   600.000000   \n",
       "max    31643.000000  21836.000000  21700.000000  8124.000000  2340.000000   \n",
       "\n",
       "          Personal         PhD    Terminal   S.F.Ratio  perc.alumni  \\\n",
       "count   777.000000  777.000000  777.000000  777.000000   777.000000   \n",
       "mean   1340.642214   72.660232   79.702703   14.089704    22.743887   \n",
       "std     677.071454   16.328155   14.722359    3.958349    12.391801   \n",
       "min     250.000000    8.000000   24.000000    2.500000     0.000000   \n",
       "25%     850.000000   62.000000   71.000000   11.500000    13.000000   \n",
       "50%    1200.000000   75.000000   82.000000   13.600000    21.000000   \n",
       "75%    1700.000000   85.000000   92.000000   16.500000    31.000000   \n",
       "max    6800.000000  103.000000  100.000000   39.800000    64.000000   \n",
       "\n",
       "             Expend  Grad.Rate  \n",
       "count    777.000000  777.00000  \n",
       "mean    9660.171171   65.46332  \n",
       "std     5221.768440   17.17771  \n",
       "min     3186.000000   10.00000  \n",
       "25%     6751.000000   53.00000  \n",
       "50%     8377.000000   65.00000  \n",
       "75%    10830.000000   78.00000  \n",
       "max    56233.000000  118.00000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "college.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA\n",
    "\n",
    "It's time to create some data visualizations!\n",
    "\n",
    "**Create a scatterplot of Grad.Rate versus Room.Board where the points are colored by the Private column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a247baa90>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.scatterplot(x='Room.Board', y='Grad.Rate', hue='Private', data=college, edgecolor='black', alpha=0.6)\n",
    "plt.legend(loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a scatterplot of F.Undergrad versus Outstate where the points are colored by the Private column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a251c2e50>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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St28/li79joqKciwWC9988xV9+vRzyX2bkkzkaETe3t488etHWbtuHT/t3kxseAjTHplJVFSUu0MTotWw2+0s+eZLDmxeSWKoLzklFdiD2jH1ngfx9vZ2d3hCiEbilTqJitVzanfxmrzwSp3kkvtVd/P+5jcPM3jwlRQVFTFjxnSsVgv9+w9k0qTJLrlvUzLY7fa6j2pdEoAjeXnF5zTfulpERAA5OUVNes/mRurAQerh8utg164d7PrmfW4Y0L2mBX3X0XTSPNsxacpdjRyl68lnQeqgWmuvh6ysNKKjO1z0GJPJiMVyZuKjq2fvNkdZWWmkpPSo+SwYjQbCwvwBEoGjDbm2tPQJIVqUTauWMbZHx1pDJrp3iGX18h3Y7XYZSiFEK+LVeXCrT/KakiR9QogGyc3N5dsvPuZURhqYPLli8NUMHTbSZcmXpaoCL1PtRVQNBoMMUBZCiDrI70khxGUrKSnh/df/zuDQKu4b3p27B3Yif8dSliz6wmX37NFvCJsOHK9Vlp5ziuDoDtLKJ4QQFyFJnxDism1av5qB7QOJDQ8BwNPkwTW9k9m3ebXL1qbsP3AIWZ6RfLFxD3uOprPip4Ms3JfDhMnTXXI/IUTjaYPzCC6Jq+tHuneFEJctO/0YA8KCapUZDAZCfT0pKiokNLTxl1bw8PBg+sxHOHLkMGmHDxAdHsmoHj0xmeTXmRDNmcnkRUlJIX5+gdIqfx52u52SkkJMJtet6yu/JYUQl61dYmeO7l1BVMiZxM9ms5FbaiEwMOgiZzaMwWCgY8dOdOzYyWX3EEI0rpCQCPLzcyguLrjgMUajsU1vW2oyeRESEuG667vsykKIVq9v6iDeXL2UwLR0usTHUlxWzrfbD5I64jppeRNC1OLhYSI8POaix7T2ZWvcTX4rC9HE8vLyWLr4Uw7t209sQhJXjhhNcHCIu8O6LGazmRm/fIrl3y9izdqdmH39GTRuOj1Serk7NCGEED8jSZ8QTSgzM4N5b7zE9VfE079nFEeyDvPOK39l+sO/JyzMNVsLuZq/vz/X3zQZaPmr1QshRGsms3eFaELffvExk/p2pFO7KLw8Tai4GK7rFsOyxQvcHZoQQohWTpI+IZpQcV4WEcGBtcriI8M4eeywmyISQgjRVri0e1cp9SfgVufLRVrrJ5RS7wBDgRJn+XNa6wVKqVHAy4APME9r/bTzGr2BWUAgsAq4X2ttUUrFA3OBSEADt2uti135PEI0lIe3L2UVlZh9PGvKTpeU4RsQ7MaohBBCtAUua+lzJnGjgSuA3kBfpdRNQD/gKq11b+fXAqWUDzAbuAHoCqQqpcY6LzUXeFhrnQwYgJnO8teB17XWXYDNwDOuehYhGsvgUeNZuFlTZbECUFFVxddb93PlmAlujqzxFRUVsnzpt3w1/0P27Nkti7IKIYSbubKlLxN4TGtdCaCU2gvEO79mK6XaAQuA54D+wAGt9RHnsXOBW5RSewAfrfV65zXnAM8ppWYBVwE3nlW+EnjShc8jRIP1vqIfVZWVvL16MVUlxdhMPowYP53k5C7uDq1RHTlymC/nvMaghFBi/X3Y891ONq6OYfrMRzAaZVSJEEK4g8uSPq317urvlVKdcXTzXgkMBx4ETgNfAzOAYhxJYrVMoD0Qe4HycKBQa235WXm9hYX5X8rhjSYiIsAt921OWlsd2O120tPTKS8vJyEhoc716a4bP4brxo/Bbre3ylXp7XY7s16Zy70je+DvawZAJcTw3ZZ9HD+m6Zfav+bY1vZZuFxSD1IH1aQepA6quaIeXL5ki1KqO7AIeFxrrYGbznrvNWA68Blwdt+PAbDh6H6uTznO8nrLyyvGZmva7iZZdLL11cGpU3l8NOtVQgzl+Hp5cDi/nNGTptMjpfdFz4uICCA3t3UOQS0uLoKSQkyGeMrLzuy/2y02gjUrVtIhoSvQ+j4Ll0vqQeqgmtSD1EG1s+vBaDQ0WkOVqydyDAHmA7/SWn+slEoBkrXW852HGIAq4ARw9jLd0UDGRcqzgSCllIfW2uo8JsOVzyLEz9ntdj56+z+MV6E125BVVll497M5tI/7U4tdcLmhPD29KK8692+w4rJyfPxC3RCREEIIcO1EjjjgC2Cq1vpjZ7EB+LdSKkQp5Qnch2Nc3wbHKSpJKeUBTAUWa63TgHJn8ggwzVleBazmzGqw04HFrnoWIc4nOzubQFtJrX1nvTxN9E8IY9vmDW6MzL28vb0JjU9m77EzIzOqLFZW6AwGDB3pxsiEEKJtc2VL328BM/CyUqq67A3gb8CPgCcwX2v9EYBS6i4crYJm4BscXb4AtwNvKaUCga3Aq87yB4F3lVJPA8eAKS58FiHOUVVViZfp3L+bzF4mCirK3RBR47HZbBQU5OPj44uPj88lnz9xyl18+v5bbFz1E0E+nmQWWxhx/R3ExMS6IFohhBD14cqJHI8Cj17g7dfPc/wy4JwNO7XWO3DM7v15eRqOSSFCuEVsbDsyiq2UVVTi4+0FOLp8Nx/J4dq7p7k5usv3085tLP3iQ8LNBgrLLUR07M5Nk6fj6elZ98lOZrOZaTMfoaiokJKSEiIiIvHw8HBh1EIIIeoie+8KcZmMRiPjp97Lu3PfoF9cEL5enmw7nke7XkNp1+6SJpM3GxkZ6az+fA4zrkzBy9Px62HrwWMsnP8RE2+bfsnXCwgIJCAgsO4DhRBCuJwkfUI0QOfOinsf/ws7tm2moLyUcaOvIDo6pu4Tm6n1q5cxslv7moQP4IpOcfxv+TYslql1LkcjhBCi+ZLf4EI0kL+/P0OuHO7uMBpFSWEBQbG+tcoMBgM+nh5UVlZK0ieEEC2YLI0vhKihevblp6OZtcqKy8qp8PDB19f3AmcJIYRoCSTpE0LU6NN3AEetAfyw8wBZeQXsSUvng3Wa8ZPvcndoQgghGkj6aoQQNUwmEzMe+i07tm9l094dBIYmcOf1w9rsQtNCCNGaSNInhKjFw8ODPn1T6dM31d2hCCGEaETSvSuEEEII0QZI0ieEEEII0QZI964QTaCgIJ9tm9dTVlpC15Q+hIf3dHdIQggh2hhJ+oRwsb17dvH9vFkMTAwjwtuLHz9Zz8G9Axg19mYMBoO7wxNCCNFGSNInhAvZbDa+/XQOd1/ZHbOXY+/apHZRfLVlC2nd+pGQkOjmCIUQQrQVMqZPCBfKzMwg1t9Uk/BVu6JDBHt2bnFTVEIIIdoiSfqEcCGz2YfSSus55SXllfj4+rshIiFar9LSUo4cOczp0wXuDkWIZkm6d4VwobCwMCp9QjmenUdcZBgA5ZVVrD+ax5RxA90cnRCtg91uZ8k3X7J/8yrigs1kF1UQEKe45fZ7ZL9oIc4iPw1CuNiUex7ko9mv43VgNz5eHmQWW5n6i4cICgp2d2hCtArbt23h9J4fuXd4Ss3kqA36KN9/8yVjJ0xyc3RCNB+S9AnhYoGBQfziV0+Rl5dHRUU50dExREUFkZNT5O7QhGgVNq1awsSenWrNhk/tHM//Vq2XpE+Is0jSJ0QTCQsLc3cIQrRKVZUV50yWMhqNGOw2N0UkRPMkEzmEaALl5eVkZKRTVlbm7lCEaHW69h7A1oPHapWlncwlPC7JTREJ0TxJS58QLmS321n67UL2blhOVKBjgHlCSn/uvu9ed4cmRKsxdPgoZr++g/xt++kYEUjm6RL2nLJw98PycybE2STpE8KFtmzewOk9a5g5omfNeKOlO3byw/dL6HnFYDdHJ0Tr4OXlxX2/fJK9e/dw4uhBwpJjeKhXHzw9Pes+WYg2RJI+IVxo06ol3NYzqdYA82HdOzFvhSR9QjQmo9FI9+496N69h7tDEaLZkjF9QriQ5TwDzE0eRqxVlW6KSAghRFslSZ8QLpTQpSd7j2XUKjualUNccjc3RSSEEKKtkqRPCBcaOXo8P6aXs3r3YY5n57F272G+O5jPDbdMcXdoQggh2hgZ0yeEC/n5+XH/Y39k+/bN7D12hMiU/jzQtz/BwcGyOLMQQogmJUmfEC7m6elJauogSB3k7lCEEEK0YZL0CdHC2Gw2liz6gr1b1+Jht+IXHsv4W6YRFRXt7tCEEEI0YzKmT4gW5otP5+KZvp37h3fnvpG9GB3vzYdv/JOSkhJ3hyaEEKIZk6RPiBaktLSUjH3bGdKtY83afxHBgQxoH8Cm9T+6OTohhBDNmUu7d5VSfwJudb5cpLV+Qik1CngZ8AHmaa2fdh7bG5gFBAKrgPu11halVDwwF4gENHC71rpYKRUMfAB0BHKAW7XWWa58HiHcraioiFA/r3PKo0MC2Z6T6YaIhBBCtBQua+lzJnejgSuA3kBfpdQUYDZwA9AVSFVKjXWeMhd4WGudDBiAmc7y14HXtdZdgM3AM87yvwKrtdZdgbeAV1z1LEI0F2FhYZwsrsRms9UqP5B1ivikLm6KSgghREvgyu7dTOAxrXWl1roK2AskAwe01ke01hYcid4tSqkOgI/Wer3z3DnOck/gKuCzs8ud34/D0dIH8BEw1nm8EK2WyWRi4DUT+OTHnzhVWEyVxcomfZSDpZ707t3X3eEJIYRoxlzWvau13l39vVKqM45u3tdwJIPVMoH2QOwFysOBQmeCeHY5Z5/j7AYuBCKA2tsfXEBYmP8lPlHjiIgIcMt9m5OG1EFpaSmrfljGwT07CY2MZuS144iObpmzVi+3HibceD17kjux8ruvKT6WQ0q/4Tw1ajTe3t6NHKHrNfefB6vVyvbt20g7oIlqF0fqgIF4eZ3bvd5Qzb0emoLUgYPUg9RBNVfUg8uXbFFKdQcWAY8DFhytfdUMgA1Hi6O9HuU4y6uPOZvhrPfqlJdXjM3280u7VkREQJtfkLchdVBaWspb/36e1CgvRrWPJrvgKP/98+8ZN/1hOnXq3MiRulZDPwsREXHcfMcDNa8LCyuB+u3na7c7PvfVE0Hcpbn/PFRUVPD2f/5BvFcpnSKDOXFwM9/M/4S7HnqC4OCQRrtPc6+HpiB14CD1IHVQ7ex6MBoNjdZQddGkTyk19WLva60/rOP8IcB84Fda64+VUsOAmLMOicbRMnfiAuXZQJBSykNrbXUeU92Sl+487oRSygQEAHkXi0e0bGtX/cDAGDO9OsUBkOgTydTgQObN/4CHnnjWvcG1AAUF+Xzx8buczkrDbofoTl2ZcPMd+Pr6uju0ZmnVD0voHWylT2fH36mJMZG0P5nH1/M/5I4ZD7k5OiGEuHR1jemb5vx6DMdkiduByTgmV8y8yHkopeKAL4CpWuuPncUbHG+pJKWUBzAVWKy1TgPKnUli9X0XO8cCrnbeE2A6sNj5/TfO1zjfX+08XrRSh/ftRMXV7sr19zFjKzt9zsQGUZvVamXO6/9gaISNX4zsxf1X96KrRx4fzPqPu0NrtvTOTfTqGFerLD4qjLwTh90UkRBCNMxFW/q01mMBlFJfA7dprQ84XycAb9Rx7d8CZuBlpVR12RvAXTha/8w4ErfqSRq3A28ppQKBrcCrzvIHgXeVUk8Dx4DqneqfAeYopXYDBc7zRSsWHBZJ3ulC2kWE1pTZbDYsdqPbuyqbu717d5MUAO3PqjsVF8NP6XvIzMwgJibWjdE1T17eZsoqK/H3MdeU2Ww27AYPN0YlhBCXr75j+uKrEz4ArfVRpVT7i52gtX4UePQCb/c6z/E7gP7nKU8Dhp+n/BQw4eJhi9ZkyMhr+XLWP5g62B+ztxc2m41lOw/Sa/DVjZ70FRUVsuHHVeSeTCe+k6Jv6qAWOVGiWv6pXCL8zOeUR/h5cerUKUn6zqP/sDEsW/oxE/p3q/l8rdt3lG79htRxphBCNE/1TfqylVLP4FgyxQDcB6S5Kighzqddu/aMuGUm7335MSZLKeVW6DlwOCOuGVv3yZfg5MksPvy/fzAkMQQVEsihPct5c/VS7n309y12/FtCYhIr1y+mV9KZMrvdzqG8EgbHx7svsGasV+8+5J5MZ9aKFcQGmTlZVE5kpxQmXnu9u0MTQojLUt+k707g/4CncMymXQzc7aqghLiQrt160KXrX7BYLJhMJpd06y76bC439+lARHAg4NjmzOfQcVYvX8KYcTc2+Po7tm/lpw0/kH+qgI7dejHiml4eSR0AACAASURBVHEuTybj4uIxRHTi++2agcnxWKw2Vu45QkLvIQQEBLr03i2VwWBg1LUTGDp8NDk52YSEhODvL0tJCCFarnolfVrrdKQrVTQTBoMBT0/XrcNdnJtJREpKrbKUxHa8s2Frg5O+FUu/JXPL99w4qBtGWyh70jRvv7qT+x/7o0ufCWDKnfexZcsGFm5Yg9Fkot/YaXTv3tOl97xUxcVFbN28gdKiQlSP3iQkJLp9vKbZbCYuTlpDhRAtX72SPqVUf+BJwB9H964H0FFrnejC2IRwC5vRA6vVhofHmcntp0vK8AkIatB1Kysr2fHjEu4bnoKPjxflZVX0SGxPfukhtm3dSP8Brh0rZjQaSU0dRGrqIJfe53IdOnSAhe+9Tv/4YNr5eLP203Vsiu3CLbff4/bETwghWoP6bsM2G8eM2jAcs20rgC9dFZQQ7tRr4AiW7zpYs4ix1Wrj2+0HGXL1uAZdNz//FJF+XuckMB0jQ0g/eqhB127p7HY7Cz96m+lDutCncwc6t49m0sDu2DI1Bw7sd3d4QgjRKtR7Rw6t9fNKqRBgF/A+sNllUQnhRsNHXcvishL+t3wtwT4mTpVZGTJmIkp1adB1g4KCyS05d9eM9FOFRKjeDbp2S5eXl0eYlw1fc+0Z0n0SotizfRPJyeoCZwohhKiv+iZ9hc5/DwIpWuu1Simri2ISwq0MBgPXTbiZqrE3UFJSTGBgEEZjfRvFL8xsNpOQ0p9lO3YyJtWRQB7PzmNLVin339E8u1ybire3F2WV5/5KKauswBzk54aIhBCi9alv0rdFKfUh8BywUCnVEZCkT7Rqnp6eF9xj1WKxsHPHNtIO7iU0MoZ+/Qfj51d3cjL+psmsWh7K2z+uprykjPD2HbnzoSfx8fFp7PBblICAQDyCYzh6MoeEqAgAqixW1hzM5tYHL7r5jxBCiHqqb9L3GNBfa62VUo8Do5AdMEQbVVlZyazXXiLRXEZKdBjZh4/yv1XfMvX+x4mKir7ouQaDgWEjR3Pz5EmyqfjPTL7rF3w0+3XWHdxNgNmTY6crGHXTdCIiItwdmhBCtAr1TfrWa637AGitv0QmcYg2bO3qFXQPrGKA6gw4tjaLjyxi4Sfvcu8jT7o5upbL3z+Amb98kry8PEpLS7gxJhaTqd7DjoUQQtShvgOVypVSMS6NRIgWQu/cSO+OtXchDA8KoCQvq2bGr7h8YWFhxMXFS8InhBCNrL6/Vc1AmlLqKFBcXVjd+idEW+LjF0BRaTneQWcWU7bb7VgxyHpyQgghmq36Jn2PuzQKIVqQgcOv5ftP32DykJSaWb0b9FHUFW17Bq4QQojmrb5JX9nPXtuBUqWUn9a6pJFjEqJZS05WnBp+I29+/yXR/l6cKq0kunNPbhw/0d2hCSGEEBdU36TvdaAHsA+wAV2BbMBbKXWX1vprF8UnRLM0cMgw+g0YQl5eLgEBgfj6+ro7JCGEEOKi6juR4yAwRmvdQ2vdExgGrAT6AH92VXBCNGcmk4moqGhJ+IQQQrQI9U36krTWy6pfaK3XAkprfcw1YQkhhBBCiMZU36TPopS6uvqFUmokUKWUCgM8L3yaEEIIIYRoDuo7pu8hYL5SqgIw4JjIcTPwO+AtF8UmRI3S0lK03ovBYKBLl26YzWZ3h9TsZGVl8sPiL8jNOkF0XCLDR08gMjKyzvOqqqr4cdVy9mxbh7fZhwHDx9CjR68miFgIIURTqm/SFw4kAL0BC7Bba10FbHNRXELU+GnnNpbNf5eU6ABs2Fm+4H2unTyDrt16uDu0ZmP//n288uxviPGx4+vtxYnMA8zetYW7f/0nwsMjMBqN511D0GazMfu//6KLbynT+nSgrKKSZd+8z8kTx7j62uvd8CRCCCFcpb5J30ta60XAZlcGI8TPlZaWsmz+u8wYloKnyQOA1M5VzJ73Nh1//3e8vb0BSEs7yvdfzqPsdC4GTzODrxlPn74DzrnegQOaFd98TnlRAX6hkYwafzPx8R2a9Jlc4ZXnf8+0PtGkxEcBcCKvkHd+PMDzv3uYzglxWGzQodsVXD9xCp6eZ0Zk7Nmzm2jDaQZ0UQB4mny4cUB3Zi3/gcHDRuHj4+OW5xFCCNH46pv07VRKPQmspvaOHDtdEpUQTnv37qFnTEBNwgdg9vKka6QvBw7sp0ePFE6ezOKrd/7NzamdCQmIoryyioXff4LVYiV1wOCa8/S+vSyf9yY39U8myC+GvNNFzH/7ZSbd9zjt2rU/3+1bhPT0E0Qay0iJVzVlof4+VBSfZkyvCK4e0Qu73c72w0f57IPZTLnrFzXHnThygKTI4FrXMxgMtA/24eTJLBISEpvsOYQQQrhWfSdyDAUeBuYBi5xfsjafcDmDAWzn2c/Wbqemu3LV94u4tkccIQF+gCMpvCG1K2uXLqx1zvJFn3HzwC4E+TmWWAkLCuCGPh1ZvniBi5/CtfLz84kK9qPKYq0p2370JFd1jiDQ39FSZzAYuKJTPAXHNcXFRTXHhUZFk1lw7vrq2cUVhISEuD54IYQQTaZeSZ/WOu48X/GuDk6Irl2781NmMRVVVTVl5RWV7MspIznZ0bKVk3WCduG1ExQvTxNGS0WtsqrSQvx9ak8AiQoJIj8ny0XRN424uDhOewRxJDsfi9UGwKmiEqw2O3EJSbWODfX1orCwsOZ17979+Cm3kvScU4BjD+FN+9MIbJ9MUFDtFkAhhBAtW726d5VSfsDzOHbiuA34K/C41rrUhbEJgY+PD2Mmz+DtT96me6Q/NuzszS6j59DRvPt/L1NWVEBWTg4b/asY2O1MglNWUYnB7F/rWl7+QRSVlhHge2acWlZeASERMZcU0549u1i/fDFlxUUk9ejDVSPHNMrYN7vdTlraUQ7pPQQEB9Ord7+aMYsXExQUTI8rr2XL5iWcrjyFwWZlZ0YhYUH+jI+KrjnOZrORUVRJRMSZGb1eXl7c+dDjfP3ZXPJ37cSGkeTeA7hl3E0Nfh4hhBDNS33H9L0C5AHtgEogEvgfcIeL4hKiRrfuKXT6/Yvs378Pg8FIrLWKDV++xw2pyQT5RZGWFcK/532Dp4eRPsmJnCosZuHWQ1x9y721rjNy/C189uHr3NQvmeAAP3IKClm4/SiTfvF4vWNZu3o5B9YsZFzvJPzNYew6+hNvv7qNX/zm6VoTJC6V3W5n3vuzsGbtp1t0MPlHK3h98QKm3P8Y0dF1J6XXTbiZpT7+fPr+G9gqS/EPjuSExciqnw7SJ6k9xWUVLNt1lEHX3HhOnKGhYUy/79HLjl0IIUTLUN+kr6/W+gql1GitdYlS6jbgJ1cGJsTZvL29SUlxrB3335f+xNRB3fDx9gKgQ3QkD0y8hnlb0tiaayUgJJwx0x8hMbFTrWt07qww3vEIi775nNLC4wSGRzPxvt8SG9uuXjFYLBY2LFvIL4b3wGh0jIzo1SmOwvJDbNu6kf4Dhlz28+3atQPvvEOMHdi9pqxr+xIWfPAWDzz2xzrPLy4uYvfa7/nj1DEE+flit9vZqI+yLrOSE/YifPwDGDH1YTp27FTntYQQQrRO9U36rD97bQBsjRyLEPViKy+uSfiqdW4fS8yJCh5+8uJbQXfqlESnR564rPvm5+cT5e9Vk/BVS4oOZetB3bCkb8t6hnSMrVUWEuCHsewwJSUl+Pn5XfT8TevWMCghpGaSisFgYECXRHZl7eS2ex6S/YGFEELUe/buGqXUC4CPczu2z4AVLotKiIswePtRXlFZq+xEziki27l2blFAQAB5xRXnlGeeKiQsumFLvnh5edearFLNYrNjMtX9t1lBXjYRgf7nlAf7eFFScu7sXCGEEG1PfZO+J4AqoAT4F6CB+g+EEqIRDb9uIp9t2ENRaRkAOQWFfPPTMYZd49odJMxmMx1S+rPipwPYbI6G7qxTp9lwoojUgZffygfQb8gIVu47UXNdgMOZOQTGJNZrMkeiSmFvek6tMovVSnaphdDQ0AbFJoQQonWoV/eu1roS+JPz65IopQKBtcB4rfVRpdQ7ONb9q25+eE5rvUApNQp4GfAB5mmtn3ae3xuYBQQCq4D7tdYWpVQ8MBfHpBIN3K61Lka0ej1SeuPhMZPPv1tAZUkRAeHR3PKLJ4iKinL5vcffNJkVS4P436oVWKvKsXr6MnbitDq7X+vSoUMC3YZN4K1lX5EY6ktBWRUVPmFMnXFPvc7v2as3G1d9z5rdh+iVGEtRaTlLd6dx1bjb8PDwqPsCQohWyW63s3HTRlauWQ/A0EGpDBww8JxhKqJtuGjSp5T6Hjh3ZVwnrfXoOs4fALwFJJ9V3A+4SmudedZxPsBsYBhwHFiklBqrtV6MI7G7V2u9Xin1NjAT+D/gdeB1rfXHSqlngGeAJy8Wj2g9unbrTtdu3es+sBGUl5dTUJBPcHAIZrOZEdeMpbKinMPbVtMpzMSOxR+w7ofF3DHzl/UeO2e329m0cS0bV3yHtbKc8HYJXH3dRDCa2LZhFWHtYhg39oZ6J5MeHh7c89BjbN64joU7NuIfEMy1d/76sraYKy0tJT39BIGBQU2SSAshXGfuhx+h00vpoK4CDCxes4W9ej8z7rrL3aEJN6irpW+W898JQCiOxMyCY6mWU/W4/kzgIeB9AKWULxAPzFZKtQMWAM8B/YEDWusjzuPmArcopfYAPlrr9c7rzQGeU0rNAq4CbjyrfCWS9IlGZLfb+e7rBezfspqoQDPZRRV07jOUdgmdKNi3lruH9azZFUQfz+LLT96vtcXZxSz9djGHV37F7X2SMXt5ciw7l2cfvZNr+qcwvlN7Coqz+PC1vzD2jgdJSkqu+4KAp6cng4ZcxaAhV132M69Y9i0/rf6OxDBfTpVWUekXztR7HpaJIEK0QDk5Oew6mEG3AeNrypJShrBn4zdkZWXWazko0bpcNOnTWs8DUEr9ChiqtbY6X3+Fo8v2orTW9zqPry6KBn4AHgRO49jKbQaO/Xwzzzo1E2gPxF6gPBwo1FpbflZeb2Fh5w56bwoREQFuuW9z0lLqYPXKFViPbeGR6/piMBiw2+0s3ryFxVvXMWNIZ3x8z8wg7pUcx9ql2wkP969JBC/EarWybukifjGiZ00XS5A3jFMhmL0NdIgNpwPhJMVH88FXHzLwhX/WeU2APbt3sfjzeVQUncYnMIRxt06t2bWkPvbt20fm9h942Pm8APp4JksXzWPGg7+s93UuRUv5LLia1IPUQbXGrIe0NE1wZDxmc+21OUOiEygszCElpX5/UDY1+Sw4uKIe6rtkSwTgBZQ5X/vhaPm7JFrrw0DNUv9KqdeA6ThmA5/djVy9JIyxnuVwiUvI5OUVY7NdsOfaJSIiAsjJKar7wFasJdXBsq+/4o6+CVSUW2rKhqgEFq39Cmv/jpSX1Z5tW1VhITu7sM6xMkVFhQR5G6mssFK9GlJ21km6xIbx4/Hcmut6YMRYXszRo5n4+9f+4c/OzmbDmh8oKTpNco8+mM0+rJ7/FpMGdMXfJ5LTJaV89MqLjL3zURITO9breZcsXMigTu1qPW+H8HC++2EHmZn59ZpFfCla0mfBlaQepA6qNX49eFOUn015ee3fVcWnsvHwSGmWdS6fBYez68FoNDRaQ1V9R3J+DKxTSj2jlPojjla+ty/1ZkqpFKXUpLOKDDhmBZ8Azm5njgYyLlKeDQQppapHqMc4y4VoNNaqCrx+luh4mUyEhkWwfn9arfL0nFMERsfXa3C0n58/pyvttWbqenp5cygrn+iIsFrHllXZ8PauvV/w7t07+eT1F0isSGNISAWZaxfw2t/+wI39kmv2Fg7y8+XGfp1ZvnhBvZ+3qrICb89zEzsPo6OVUwjRssTHdyDI20LWiUM1P8M5mWn4Govp2DGpjrNFa1SvpM85k/YvOJKraOAprfXfL+N+BuDfSqkQpZQncB+OcX0bAKWUSnImclOBxVrrNKBcKVW9HsY0Z3kVsBqY7CyfDiy+jHiEuKD2nbpxMONkrbKDGSfpNfAqioMS+WTtLnYcPMbSHftZuC+XG2+7q17XNRqNXDX2Rj5fv5vS8grsdjsldk/mbz9BSqczEy+2HTpGbHLPWtum2e12lnw+l2lXdiepXRQRwYFc3SuZLoF20rLyat0nNNCfkoLaZRfTo+9gNh04Uassp6AQr+DIBm0xdymKigrJzc2VJFOIRmAwGHjkgfuI9s5n79rP2P3jp4QYsnj0oQfqNWREtD6X0l+zHtiPI3FDKdVTa73zUm6mtd6plPob8CPgCczXWn/kvN5dwHzADHyDo8sX4HbgLefSL1uBV53lDwLvKqWeBo4BUy4lFnGurKxMdm3fgsnLi959UgkODnF3SG41evxNzHrlb+QUlhIfHsyx3AJ25lqY8csHCQgI5PjxYxw9cpCE0HDGdu1+SUujDL96FFa7F58uW0RleSmxicnM+N3f+OT7Lwk22SmqsBCd1IMbb7691nn5+acI8zLg/bMkrHuHKH46eJieSWcWqM46dZrgiOh6x9T7ir7s3bmFz9fvoUt0ELnFZezOreSOB1y/JGdxcTFvz3mPjNxiPDy9MVqKueuOySR1ktYIIRrC19eXO6fd4e4wRDNhqM9f1EqpPwFPATk4xtIZALvW2rVbILhGAnBExvTVtvTbrziy6Qf6dYig0mpj49E8hk2cTs9efRr1Ps21DiwWCyuXfceerY75Sd37DuGqkaOx2Wxs27KRzONHiYyNIygkDJPJRMeOnRrU+nWherDb7Zw+XYCPj+95F2UuKytj9j/+wIzhPWuVb9pzgM/X7+Y3E0cSERxIVl4BX247wi33P1HvvYWr75+WdpQjBzWBwWH07NXbZa18Z9fBy6+8hj1IER7t+JVSWVHG/k0L+eOTvyIgINAl928umuvPRFOSOnCQepA6qHaBMX2JwNGGXLe+LX13AUla6xN1HShanuzsbA5tWs70q3rVNPl36xDLW5+/T9duKU3WtedOH8x+nQ72XO4e6Jj0sHn/ej6YfZA77/slAwYNJS22PZ/P+S+JQSZMHgYW5ZUz7raZqC5dGzUOg8Fw0RZWHx8fQjt0YeeRdHomOpK5sopKtmeVcM9jf2bFuhUU7D5ASGQstz7wJDExsRe81oXun5CQSEJCYoOe41KcOpVH9ulKuqozf0N6efsQHNuDDRs3Merqq5ssFiGEaM3qm/Qdl4Sv9dq7eye924fUGuPhafIgKcyXtLSjJCV1dmN0rpeefgJjwXEGDjyz2PPArh05tm4XGRnpREZG8fmc/zBtYFLNRImhlVXM/vBN4p/6Gz4+PnXe4/TpApYvWcSJw5rg0AhumjoVP7+wOs87n0lT7mLBvHfZsHwnfl4eFNk8ue72B+jcWZGS0rPuC5zFbrdTVVWFp6en28b4lJWVYfI6tw69fPwoLJK/+IUQorHUN+lbqpR6AfiSM8u2cKlj+kTz5G02U15lPae8rMqKl5fXec5oXTIzM4gPMp9T3iHYh8zMDIqKiugU4lWT8AGYvTzpHRvA7t276NcvtdZ5xcVFHDx4ALPZh+RkRXFxEbNfeZ5RncMYMzCRnIIiPn7tBQZPuJuu3Xo4zymmpKSE8PDwOscGenl5MXnaTCoqKqisrMDfP+CSEza73c6aFUvZvPI7zB52KgyejBh3C72u6HtJ12kM0dExVJXkYrVY8DhrtvSpjP1MGja2yeMRQojWqr5J30znv9POKrPj2F1DtHA9e/XhzW/n0zOxEh9vR5KXe7qIk5WexMW55j+xzWZj8+b17Nr4Ix6envQbejXdu6e45F51iYqKZnVhxTnlJ05XcFVkFEVFRZiM5yZVHkYDNpulVtmalcvYtnwh3aICKKm0sPhTO5HxnRjRMYTO7RyTKiJDApkypAdvfzWPTknJfPrB2xSeOEiwjydZxVUMv34yV/TtX2fc3t7e5x33Vx8b1q4mc/MSfjG8G0ajkYqqKj75+n38AgKbvGXXw8ODKTdPYO6nXxKR0Bsvbx9yju8juX0QiYmdmjQWIYRozeqV9Gmt41wdiHAfX19frp/2AHM+eIt2AR5UWmwU2M1MufeXLunys9vtfPjO/xFcms71neOoslhZuehdThwdyphxN9Z9gUbWvn0cZb6RbD1wjN6dHBu7bD90gnK/SOLi4qmsrOTbeSUMqaqqmTVrtdrYmV7I3VN71FwnKyuTPau+ZsbwMzttnCos5rm5nzPhvkm17ulr9oLyYhbMe4/OxlP0HOZIeC1WK3MXfUhkdCzt2l3SJjOXZOPKb7l7YJeaOL09PRl3RRLffb+QpKTfuOy+F9K7V2/axbZj7fr1FJfkcN2kkSQnK1lWQrQapaWlHD58CB8fM4mJneq1pqcQje2iSZ9SaurPiqxAHrBea13ssqhEk0tKSubRZ14kPf0Enp6eREVFX9b/cPPy8sjIOEFEROQF93VMSzuKMe8oo84aQ3fjgO7MXrmSIcOuPmf3CVczGAxMv+9Rli7+irfWbAIguWcq08dOABzdqaNvuZt3Pn2HK2IDMRoNbDtRwKDrJteKddvGtQzsGElFZQXZWRlUVZQTGBJGXIgve9My6NnpTKtplcVKpcGDk4d2c8PIXjXlJg8PRnRtz4bVy5h4252ue2ZrJZ6m2t3IIQF+FJ/Octk96xIREcEN119/WeeWlZWh9V4MBgNKdcVsPre7Xgh3Wbt2LQu+WYZvaDxWSwWG8k955P57iYyMdHdooo2pq6Vv2s9eG4EoIFYpNVZrvcU1YQl3MBqNl92da7fbmf/RHPKP7CIh1JdthRVYA2O4fcZD54wLTDtykOTI2stwGAwGEkP9OHHiBF0aeUZsfXh6ejJ2wiTGTph03vd79OhFYuLz7N61E6vVwt239TpnKRE7dkpKijmUfYTYYF+8fEwU5B6nvLSUJbuO0SE6nCA/XyqrLCzddpB+V17DvrVLzrlXoK8PpZmFLnnOaj7BEZwqLCY08MzWPvtPZBGf1M2l93WF3bt3smTebHrE+GO3ww+fl3Dt5Bk14yWFcKecnBzmf7OCHoMnYjQ6/tAqKSrgjbff4ZnfPSGt2aJJXTTp01qfdxS1UmoU8BIgaykIADasW4M57wDTrjwzLm/7oeN8u3A+EybVXjc7ODSMjD3l51wjt6SCviHNd0FoPz8/+g8YdMH3e/UdyKtP/o+nrutd04pW7m2lpKwUu8Gbf369gfBAf3wCghhz062orn3YtXktRaVlBPiemb26/UgGasDltXjV17U3TeXTWS8zUkXRLiyEgxnZ/Hi8iBmPPujS+za28vJylsybzT3Dutd0vQ9QVbw9bxYdf//iZY95FKKxbNy8mYj4lJqED8AvIJgTNjM5OTnS2iea1GUNKtBaL8XR4icEANvWLWdo19pru/Xq2J7Du7eec2z37j3RBTYycvNryvYey2RfZgEfvfkyrzz3GO+9+Qp5efXfQqw5CA4OwcMvhPfW7mfDwQyW7j7GG99vY0zXdkRZ85g6MBkfL0/G3nInQ68aBsD4yXfzwbr97Dh8nOPZeSzZpskwhNKnT2odd2uY9u3juOORpzni1YEvDhRxOqoXM3/9RwIDg1x638a2b98eesT419qhxNvTk+6Rfuzfv8+NkQnhYLVaMZxn/J7BYMRmO3fVBCFc6VK2Yfu5qkaLQrR4NqsNj/MNTD7Pji8mk4k7H3ycL+bNoWjnDmx2yCkqZUjHcEb07IzRaCQzL5/3/vt37n/8z/VaB6858Pb2JiqmHbf278ThjGwoLWFKRAB2DBR7G+jaoR0J0RG898m7DBrkWBqlQ4cEZvz2OTatW0NGfh5JI69mfPeeFxzkXVxcjNFoxNfXt8HxhoWFndMK29JcuGusabvMsrIyWfHdV+SdzCA2IYlho64jNPTy1mEUrUv/fn1Z9fr7RLXrWPN5LS8rxsNaTFRU/bdJFKIxXFbSp5QaCJQ0ciyiBeuROoSNehVDup1ZYmP/iSziks8/riokJJS77/8NNpuNsrIy5vzrGa7urWrejwkLoW9MAVs2rWPoVSNdHn9jMJlMxHfrg04/yACVyKH9ewgyevP51jRuuGYEAD7eXgR4VHH69GnA0d0TEBDIyNHXXfTaJ09mMf/9/2EqP43VDt6hsdwyfWar36KsLkp15YfPS+iffGZmdXllFbuzSxie3KVR7mG1Wjl5MgsfHx9CQkLPef/IkcMsnPMK43p2IDYhgcMZGbz76gvc+cvfS+IniI6OYfSVV7Bk9RcERnTCWlVOef5RHpp5p4znE02urtm7C3Csx3e2cKALcP4R76JNGnLlCObu38OCDXvoGOZHRmE5GRYf7n7w1oueZzQaKSoqJMzv3LFXMSGB7DmZ4aqQL8piseDh4XHJv5Svn3gbX83/kLeWb6cgOx1LaSETrx5KVMiZbtOSCgtms5mqqvo1lldVVfHhG/9ict8OhAY6Jtocz8nj/Tdf4YHHnm7T/+Mwm81cO3kGb8+bRfdIP8DA7uwSxk2Z2Sjj+Xb9tJ3v579PbIAnxRUWCIzmtrsfwM/Pr+aY77/8mFsHKIL9Ha2vndpFMdZoZPl3C5k05a4GxyBavtHXXENqv77s27cPs9mb7t1vq9fC9wUF+axYtZr0zJOopI4MGTy4xfR8iOaprpa+r3/22gbk8v/ZO8/AKK5zYT+zXXWllVa9t1Wnit5tMM1gjG1sXLCNcXfsJE5ubm5yk3u/m3aTG5fEdtwN7jYGDJjejJDoVQKxkpCEeq+r7dr5fggEsoRBIFHn+YP2cOacd87OzrzznrfALqPR2NRLf4lbFIVCwaInf0Jp6WkqyktJ0QdyV3zCJSkkOp0f1W02RFHs1v9UTRPhoyYMpNg9KCsrZe1XH+Fqb8LugpjUDGbddR8KxaUZxRUKBXcveASH4wHKykr5bunrRAWfc9TOKa5AH92ZUqSt7dKUvtzcY6ToNd0ibcP1fvgW1VBeXjZg5VvqNgAAIABJREFUCbRvFJKSU4n59V+6fPgmJST2i8JXV1fHjm8+YvH4VFTKzu+/uKqWr5a9zWPPnMtlaGtrxMeze43jyCB/NmcXXrEMEjcPvr46Ro8ec8n9q6oqeeXN99CFD0HrP4jdeSXszHqFX/7shaue1kri5uFi0bvvXy1BJG58BEEgMjKKyMioPh2nUqkYMuEOvtm9iWmD4nDXqDhWVM4ps5LbBw0ZGGF7oa2tlW/ef5X7R8Th4xmBKIrsz89n1Vcfc8/Cx/o0llKpJCYmltvue4IPVnyMnwpMNic+4QnMX9i3/Humtha0GmWPdh93JSaTlC4TOv0p09IGXbxjHzi4dxfj4wO6FD6A6OAAdhbkYDK1dT14BaUbVrsDjercd1Tf0oZWp+9XeSRuLT7/egWRabfj6d3pUhARl05VqYZNW7Zy911XP4m9xM3BZacENxgMv+lPQSRubSZOuYPBsxexprCNpftLMYcOY/EL/3bJFrb+YF92JmOifLu26QRBYIQhiprCHCwWy0WO7p3klDRe+s1fmPXEv/Hoy//Dwsee7rMVKj4hiRM13fP2iaJIYZ25zwq2xKVjaTfh3st35a6SY7WeK9s3duqdrN5/EtuZ7Xqz1cbaI0VMnD73qskqcfNRU9/cpfCdJTAsjpwTxmskkcTNwJU8UaWU9xL9SmpqOqmp6dds/ub6GmK0nj3afdxUmEymy/alEQQBP7/Ld+gPCgpGGzOIVXuPMTIuBIfTRaaxnEETZ/RLFK9E7ySmD+Pwdx8RHnDuu7PY7DTYZd2+zyHDRuByuVi6eTWCw4rc3Zvb7ntKUsglrgilQqCjw4lcfu4xbWlvxUd7awdvSVwZl630GY1GydIncVMRnZjGyT2rCPY7lyDa2dFBrdmJTtczavNqMu++hzh5Mo/tOzZSVVFFRFwyCUlpFz9Q4rJJTEziyL44Vu09Tnq4njaLjd0lDcx++NkevqrDMkYxLGPUNZJU4mbktvFj2bIvm/j08QiCQIfTSVFuJk89JFmQJS6fi0XvvmM0Gp8887e/0WisvzpiSUhcfdIHDeG9zC1k5xWRHhVCa7uFLcdPM3H2A8jl8osPMIAIgkBrUz3W2tPMNOiRCXWsfvd/MYydzsQpd1zWmD8MnLkREEWRfbt3cTBrK067jQhDGlNnzO0WTdtfCILA/Y8soaiokJM5h/HQa1l8z+hbPk2OxNVh0qSJmK0WdmYvR1C6IXRYWXDnHcTHJ1xr0SRuYC5m6Rt+3t+bgKEDKIvEdUZjYwM5Rw8jkwmkDx6GVutzrUUaUBQKBYufe5l9e3ax+ugBPLy1TF/0UyIiIq+1aJjNZvZsXMGSyecSNyeEB/PBjvUMGjoCH59LL1+XdyKXLau/AFs7HTIVI6fMYPTYSQMkef+yfs032E/t58GhcagUCoxlJbz/+p945uXfoVT2DHa5UgRBIDY2ntjY+H4fW0LixxAEgVkzZjB92jQsFgseHh433EuaxPXHxZQ+4QJ/S9zk7Mn6noNbVjI8QofLJbJ022rGz3mQIcNGXGvRBhSlUsnY8ZMZO37ytRalG6dOFZAU4NmtUocgCKQFe5Ofb2TEiEvbWiwpKWbH1+/y0JgU3NQqnB0drM1ei1ymYMTocQMlfr9gsVg4dTibJyaldT38EiNCqG09xdGjBxk+XNpelbj5kMvleHr29DWWkLgc+uLT17OelsRNSVtbK/s3r2TxpHNWpbSYMN5b/RlJKeloNLdODE99fT0H9+7CZrWQOiSD6OjYa/K2rdG4YXb0rNNpcbjw6cP3kblpDbOHxOKm7kwMq5DLmTk0kY+2r7vulb7GxgaCtZoe6x/h701haQlcZ0pfcfEpdm5aQ2tTPWExiUyeNqtPFlkJCQmJ/uZiSp/MYDD40mnlk5/3NwBGo7FxIIWTuDbk5eWRHuzdzaqkkMtJCvCkoCCftLRrF2F7NTl29BA7Vy5jbKweN5WK3V8f4khUOncvePiqyxIbG8faNpGmtnZ8vTr911rbLZyoszIlKeWSx2lurMXfENutTaVUIDjt/SrvQODrq6O6xdqjvayhlcDh134L/nyOHz9G5vIPmD00Fr/EWE5VVvDh639k8Uu/wdtbe/EBrgC73c76jRs5eCQXQRAYnTGE22+77aqmP5KQkLg+udhdII3OChxnFb2G8/5P5GzxUImbCqVSQXOHq0e72e7g++1b+PzDN/D2cCdxUAa3T7/zpswO73Q62bLyE5ZMSEOp6LzMo4L1fJl9hNLSCVfdz08mk7HwyZf4+sM30MpsyGUCtTYZ9yz+SZ982cJjkyisLCM+tLPQu81u5UTeSXKP5/HPP/+WjAnTGDF63HXpO+Tu7k5k2gg2HznKpNQ4FHIZhZU1nGhy8ezg4Rcf4Cqybc1XPDwmGc0Zi2pcaCAOp5PM7ZuYNffeAZtXFEX+8ea/sKhCiB42F1F0sTfvGKfLlvLUE4sHbF4JCYkbg4tV5Ljs5M0SNy7Jyam8sepThsfZcNd0Jqc9VVHDlxu2MyUhiGnBvpysraNqfwPvnszhmZd/d9Nt+VZUlBOpVXcpfGcZHO6P8fjRaxLcERgYxHP/9t/U1tYgiiKBgUF9Vs4mT5vFB6/9gY4OFxEBOnZl7SKnvIGfzZ9KkJ+WLXvW0t7WwpQ7Zg/QWVwZs+ctICszgKXZ2+lw2AmPT2bxT54bkCCOy0UURbC1dyl8Z4kNCWTfsYFNrFtcXESDRYEhMfVMi4yoxKGc2LeO2tpaAgICfvR4CQmJmxvJ3i/RA7VazbxHn2Ppsn8R4a3AJYpszD7IY2MSGJsYjiDA8FiRFQdO4SM3c2BfNuMmTLnWYvcrbm7utNt7+tCZrDbcPK6dU7UgCAQGBl328VqtD4tf+g2Z2zexfN0mtB12Hp4zgwDfzjQkM4cl8vb2bYyfcsd1pUidRRAExk2Ycl1fb4Ig0CHrDJJRnJfqp7KhCf+gsAGdu7KqEjfvnoqdm1cANTVVktInIXGLI1nyJHolOjqWF3/7F4betYTkOx5iSEoiwTovzhqWBEFgZGwA7a0tVJbcfIXlAwICMKu0lNWd82gwW23sO93M4KE3dgSzt7eWWXPvJW3IcO6fOq5L4YPO71XnpsRkaruGEt74jJwyg7UH8rpKszW3tbPpeAXjb5s5oPOGBAdjaa3t0W5tqyUg4PJfFiQkJG4OJEufxAWRyWRER8dgMrUhVyiwOW2IIl2Kn8sl0tJuJS406prKOVAsXPw8X3z4FnJjLmqFnHq7wJxFz9006ROCI2MpKdyF3uec0ieKIo0Wh5SA+AoZPXYScrmSZdvXgcOGxsefuY+/NOCWtujoWHRuTsqKjhMalQSIlBUeIyLIi8DAwAGdW0JC4vpHUvokLoqnpxcy70AcijrK65sJ8dMiE2Bzbhmt7qFkjBp7rUUcELy9tTz54q9obm7Cbneg1+uvywCHyyVj5FjeztqKr0cNsSEBWGx2Nh7OZ8iEO27aSM+2tlYO7M2iuaGOmMRU0tIGd4tS709GjBrLiKv82xAEgReeeYp1GzZw6MC3yGQCI4cPYtrtAxc8IiEhceMgiOItl34vCihuaDDhcl3dc9frvairuzG3zZqbm/j4X6+gbK1AbG8kr6oFv9h0nn/5t92Kz1+M630N2tvbMRpP4nDYiYtL6NO59YXrZR1aW1vYsv5bygvzUGncGTl5OkOGZlyVuc9fA1EU2ZO9k8PZ23F1dJA4eCQTb+tfv8LS0tOs+OA1Rkf54uflwcnKeipFLY8/+/NrquReL9fCtURag06kdZDW4Cznr4NMJuDn5wkQDZRcybg35+u8RL/j4+PL8//2X5SUFGMymXg4OuaG2eZsa2tl64Y1lBWeQO3mwegpM0lLH9ytT3NzE8vefo1ThzPxUgrIVRp8AiNIHjuNO2bd1af5TCYTB/fvprWpgdjENJKSkq9bC6G3t5a7Fzwy4PNUVVVy/OghlGo1Q4aN6JGrbuWXH6OszePBoTEoZHIOFR7gw7eOs+SFX/bb2q396iMeGBmH1sMdgDC9jp25hRzYt5tRY8b3yxwSV8bhI4dZt2kbFqudsGA9d8+dIwWfSEj0IwOq9BkMBm8gG5htNBpLDAbD7cDfATfgS6PR+Jsz/QYD7wHewE7gaaPR6DQYDBHAJ0AAYAQeNBqNJoPB4AN8CsQAdcB9RqOxeiDPRaJz6yg6Ouayj6+urmLn1tXU1zWRMmQkCQmGAVeGLBYL77/+JyZHeXPHmDjarTY2rPuY1uZGxp6JALVYLLzzyh9IVzby4OwhaFRKKpvaWJtbTdXRnRQnpxMQEEhp6Wm0Wi0hIaEXnK+srJTl77/KyHAt8Z7u5G08wr7MYB5Z8kKPbUSbzYbRmIfL5cJgSMLNzW1A1+JasfG7VZQf3snQCD9sTicfbl/L7QsWM2lS59Znc3MTtQVHeHTiuaTfGYYoag+epKAgn4QEwxXLYLfbwdyC1qN7qp1B0SGsP7pfUvquA/bs3cOKDdnED56CSu1Gc2MNf3v9X/z65RekSiYSEv3EgEXvGgyGkcAuIOHMZzfgA2AukARkGAyGGWe6fwI8bzQaE+hMBL3kTPubwJtGozEROAD89kz7/wCZRqMxCXgXeG2gzkOifziwbzcr3/kLwS0FpCnqObz6A1Z8sWzA592/N4thgWoM4cEIgoCnm4a7R6Wwd9taHA4HXy3/hhd/8WvMlYXU1Faz6UgBmXmleLupCfdWEuKl4qul7/DB335DybZP2f7Ja7z96h8xmUy9zrf6iw9YODKOofGRRAXrmTEsEX97DYcPHejW7/iJPH7z//7MN1uOsWL7cf7zD3/lyNEjA74eV5vq6irKDu9k4fg0kqJCGRwXyaMTU9n49VKcTueZPtVE6tx7HBul86Sy/HS/yKFQKLB3iPzQncVktuIhBa1cc0RRZM2GrSQOm4ZK3fny46MLxD96OJu3bb/G0klI3DwMZMqWJcBzQOWZzyOAAqPRWGw0Gp10Knr3GgyGSMDNaDTuOdPvozPtSmACsPz89jN/z6LT0gfwOTDjTH+JAUAUez4s+4LdbmfXuq95eHwa8eFBhAf4cdfIZNpP51BWVtqPkvak8vQpogO7++XJZDL83BSsXLWS42XthBpG0djSTl2zCXWHjbq6Gl5dk43DYae2oZGm03k8MSmdyWnxzB+VzIRgBSs//7DHXGazGbmttWv78CxDo0PIO7K367PD4eCfby/DMGIuMckjiE3KIGnU3Xzy9WrMZnOv59HR0XFF38G14kTOEYaE67pZdNVKJdE+Kk6f7lTo9PoAqnopr1bRYkYfGNIvcshkMiKShnD4VFlXm7Ojg60nShk5YWq/zCFx+XR0dOBwyZD/wLdSpw+hpLTiGkklIXHzMWDbu0aj8QkAg6FrayYEqDqvSxUQ9iPt/kDrGQXx/PZuY53ZBm4F9JxTMCX6AbPZzOrln1B9Kg9BAF1oDHMXPNLn2qHl5WVE+ai7JaoFSA/VYTx+jPDwiP4UuxsBweFUVBzEX3uuVJwoijRZnBw/mkfSmHspytuPj8zK7UnBhGrdEQSR5CATf96UR2x0FHeOG95NaYkODmDLyaPY7XZUqnNVF5RKJQ5nT8XMZLHh5q7r+lxQkI9KG45Sda6KiVyhwNM/juPHc8nIOJcHsKammm8//wBbSx1OF0QmDeHO+Q9cl4mTe0Ol0WBxOHu0W50ianVntRc/Pz9UQTHsPVlMRkIkgiCQX15NmU3F7KTkS57L5XJht9tRq9W9ug3cOf8Bvvn8Q47sOIaPu4oak4MJs++/JtVVJLojl8tRyVx0OJ3dFL/G2gpiIgY2obWExK3E1QzkkNFZr/csAuDqQztn2s/2OR/hvP+7JM5Ewlx19Pobo06tKIq88sf/I8NPJHF2Z13Tkqp6vvzwdX7133/uU5oLpzOQ/YDGrVNROfuvVewgNDxoQNdk1txZ/P33mYQGtBEWoMPucLL5cAGjp81k7bYDuLuraasyMjHSH19Pd5wuFwIiAV5uBHipQRdCQlRwl8xncdco8fPz6FF+Ljp9CKdqakiJ6rRQOTs6yCqqYsELj3Wd59lrT6PpPqZKJUen8+jqZzab+ebDV7lveBT+2khEUeRoYTnrVn7ME8+9OCDr1d/cPnUyr2SuY3gSaFSd51vT2EK7ypPQ0NAu5eyFn/+c775dycf7doHLRXTyIH6x5AE8PDwuOocoiqxdtYLDu7biLhewyVTMvv8RBg0e0qPvCz//Oe3t7bS1taHX65HLr4/y4TfKfWEgeWThXJYt30r84Mlo3DxorKvEVHOM+5/+Bb6+t876SNeCtAZnGYh1uJpKXzkQfN7nIDotcxdqrwW0BoNBbjQaO870OWvJqzjTr9xgMCgAL6CBPiClbOmO1Wpl68Y1nMo9hCCTExKbjNBcTVRiClZLZ1WBIB8tgUINWVkHSExMuuSxFQpPmvHCWFKFISoYq8VBm9lC9qlGnr4necDX5N7FP2fDt1/SeOgIgkLF8AlTGTF6Irv251FfW0u72YLGXwNqL0wWE3JBxN3TEz9fHQnDxpGZc5KZwxO7xqtrbqVD40tbm4O2Nke3uabOWsBXy94ha+MhtG5KKtvsjJ95L+7uuq7z1OlCsLeU09ba1mXtczodNFYaCQ6+s6vfrp3bSPPX4KnSdH0HiWFB7Nl5jKKiihsmgfKUux/nrS/fJ9xbidXRQQtu3L/4JwiC0O27HzNhOmMmTO/6bDa7MJsvfm1s2/QdZmMWj45ORBAErHYHn7//Tzoe+9kFrchyuQeNjb1vpV9truf7wtVCr/ciIT6VBXe6WLdxGyazhcjQYF548gmcTsUtsz7StSCtwVkukLLlirmaSt9ewGAwGOKAYmAh8IHRaDxtMBisBoNhrNFozAIeBtYbjUaHwWDIBBYAnwGPAOvPjLXuzOc/nvn/TKPR6EDisnC5XHzwxt8Y5icyZVwCzg4X6/fupri0AkaldOurd1fR2FBHZyxOp5Vl5/ZNHMnejtDhwMMviFn3PERQUHC34xYufp6vlr7DnpJjiB0iLS4l8x9/EXf3ng78F0MURerr6wHw9/e/aASwv78/Dy1+rkf7wvvm88ob76HSBrHh+AHiA7QolUr8dDoKqpuwKdwZO3Y8+7M6+DI7l6RAb5rMdk40Onjo6Zd7nUutVvPwkhdobW2hra2NwMCgHjnglEolP3n6Ef731fdw00WBINBeX8LDC+Z2W4+WxnpivXpauvw81LS0tNwwSp8hMYn43/4v5eVlqFQqAgOD+jVq+2j2dp6adC4tjkal5I7USLK2ref+RU/12zwSA09aajppqekX73gdY7FY2H9gP3X1jSQmxJGUlDxgCcAlJPrKVVP6jEaj1WAwPAp8A2joVNzOBmk8CLx7JsXLIeD1M+3PAksNBsNvgFLggTPtvwU+MhgMx4HmM8dLXCYnT+YRIm9nUEyn/6VSIeeOjFQO5pyg2WTGx/OcIpJfb2JqdGzX583rV2PN38PisfEo5HLqW9r44l9/5fGf/a6b75+XlzeLn38ZjQYqKxvw9dVd1oO/urqK5R+9iVawIQJtghv3LHqGwMC+1xUNDg7ht//2Ejt37eKz/O95Z9dJBkcF0prfQLMdQpOHExUVQ3R0LBUV5RTmnyTQV8dtqekXTebr7a39Ud/HpKRE/uc//x2jMQ9RFElIuK/HVnFkXBIntxwmKljf1eZyuahosV3W+V5LZDLZgPjOiaKIgo4eD1U/rSctp2v6fT4JiR+jpqaav7/xDp76RNy8fDj8XTZ+W3fwwrNP37RVbiRuLAb8KjQajVHn/b0VGNRLn6N0Rvf+sP00MKmX9kZgTn/KeStTU1lGhK676VitUpMQFcbXmYe5d/wQFHIZu42nUQUndOWpczqdnNj3PU9NTutS4Py1XoyP8WN35vZekxp7eXmh0/VoviScTiefv/MKDwyLxOeMBayx1cRn77zKi//xx8t6m/by8mbWjJlMnjiJb7/+hIKcg6jcFMQMH8rsux/oOq/Q0DBCQ/vXoVylUpGW1uPn0EVycgp7dvixM6eQoXFhtFttbM0tIXnkFGpqqgkKCr6pHyRWqxVRFH80f6EgCMg9fWgzW/ByP9cvr7SK2KShV0NMCYkuln76JRGpt+Pp3XmT0wdFUHRiH3v27mHc2HHXWDoJCakihwQQGBJOwfGdJEd1b+/w8Gfw+DtZn3sIV4eT9NFzGDZsZNf/WyxmvDXyHha7YJ0WY03/B1IbjSeJ91V0KXwAOm9PYrUy8vONffIz/CHu7u48sOjJ/hCz35DJZDz69Evs35vN6sN7kSlVNOGOePh7mvOyqGhzMGn2AoYM6/G+dEPT2trC8k/fx1pXjiCA3FvP3Q8uwd/fv9f+M+Y/xOcf/YMpicEE+npjLK/lYK2DJQumXGXJJW5lOjo6qGtqIzC5+1ttSHQK+w5KSp/E9YGk9EmQmJjE9nUacoorSI0KocPlIjuvGJ/IZMZPmMT4CZN6Pc7Dw5MWe2eE6vnpWAqr6ghPmNAvslmtVnZu20j+sQM0NjUTqrIiivHdFE1PlRyr1dIv811vKBQKRo+dwOixE1j2zuvcEeNNXGggAA5nBx+v+ZSQsIgbbrv3QoiiyMdvv8K0GC/CUzp9u2qaWvjk7f/jhV/9T6/RttHRsTzw/H+we+cWDhRXEZUwmicfHH/TVjiRuD6RyWQguhBFsdv9yW6z4O6u+ZEjJSSuHpJ3qQQymYzHn/sF1d5xvJNp5MM9RagM47hn4WMXPW789Lv5MiuXprZ2XC4XucXlHK5zkjFy7BXL5XK5eP+f/4tX9VEeGxnNk+MTaKguZ8u+o936HK9uIy4u/ormamtrpbCwgEOHDpCbm9NZtqsXefZkZ/L2K3/g3df+xIEDe69awmSz2YyppqRL4YNO38uJhhD2Ze24KjJcDU6fLsFfZiVcfy6hdqCvljhvgby84xc8Tq/XM2f+Azz6zM+YdNs0SeGTuOoIgsCglAQqS/K62lwuF6Un93D7pP55CZaQuFIkS58EAG5ubtw5bwHMW9Cn44aPGI23j44NW7/D3FpDdNIgnrhneo+ghMshN/coUWobQ84odD7eXsyfMpp/rNxGkN4PtVLBnqJaBk+ajafn5eUzcjqdLP/sAwqO7Kax4jSx/p546fzZJPNh1gNLMJy3ZfzZR//Cz1zBgtRIOlwimZkrKCsqYN59D13RebpcLg4d2s+xfZnI5QqGjZ1CSkpad2uB3YZG0dPK5a5RYW3vvSTcjUhbWyu+bj1vSzo3JW2trddAIgmJS2fBPfP5cNnHHN/zLWo3LTZTLbOnTrril1IJif5CUvokrpiEBAMJCYaLd+wj5SWniAnojIAVRZHc4nJyjKeQqzRsLrMxOD2JOUse7ZEepi9sWrcK//ZSyiyN/HbOMFQKBSW1TXgEBbDy83eI+vWfUavVVFSU46otYvKY1K5jpw9LYtnOwzQ2zkCn8/uRWX6cLz9+D4+mYmYZwnG5RL5fv4zSolHMnHNPVx+t1oc2UYXJYsXT7ZxCfbi4hqRpt1/23NcbUVHR7FzRzvgfbJHl1ZiYfaf04JS4vlEqlTy5+HFaW1toaWkhMDCoW9UeCYlrjaT0SVy36INDqThwjOjgANbu2o+rvZFp8cHEeAlUK8zY7bYfVfhyc4+SuWEVTks7blo/ps5dQGRkVLc++Uf2Mibci9Rgb9TKzp9DqJ83p+urSQnwID//JGlpgyg9XUK8f8/kmDF+7lRUlF+20ldRUY6jOp9po88pk3NHpPDhjixaJ03tSvsiCAJzHljMJ0v/wYhwH3w83Mgpr8fpF0NKSuqFhr/h8PLyxjByMl9lf894QxgymYy9hRX4GYYRGBh48QEkJK4DLpaySULiWiEpfRJXRElJMd9v/JbWxjr0IRFMmTGPgICAfhl78ODhvLFpNZ4FJTTW1fDg6Hiqm0wEBAUzKs7Ax5mHaGiYjp9fT4Ur59hh9q1exoIRibhr1DS1tbP8w1eY/+Qvu1LOAAhiZ/U+2XkByAqZDLvdTl1DK/u+XEZZ8WgCQiIpN9l6zFPTZiPR9zJz0ADFRYUYflBqRxAE4vSelJaWkpqa1tUeHR3DEy//Nwf376GkrYXh8+YRExPXr4mOrwdunz6HU/FJHNz9PR0dHaTPXERSH2rwSkhISEj0jhTIIXHZFBbms+6jV7ktRM6SsfEM92znszf+RG1tbb+Mr1Qqeez5f2N7hQOlTCSvugW89UTHJQCQ4O9BSUlRr8d+v34l80cm4a5RA+Dr5cHsQVHs2Li6Wz9dSCQebmpyKluxOzsAqGxoprWlBWNJOY+PjCK4JZ+daz8nv6mDoqrOcxNFkbzSKtrVfoSFhV/2Ofr4+lHX3lOZrDPZ8PX17dHu6enFxMlTmTnnHmJj4286he8ssbHx3PvQE9y/6CmSk1Nu2vOUkJCQuJpIlj6Jy2bL6q+4d1RiV1LcML2OWWki2zd+y4KHl/TLHFqtD/c9+ChHV79P2pDEbv9Xb7YT5uPT63GizYxG3d2XJkjnQ4PxVLe2WfMfZOkbf8UvMJjXNx0lzt+DmtZ2TA6BebdPwE/rhZ/WC293DTvrBPY2yfgseyft7Sa8dQHcMXcBDocDpVJ5WeeXnJzCltWQWNdImL7TYlhQUYNJ5dvvyaAlJCT6htPppLa2Bk9PT2m7VuKmQFL6JC4bR3szXu7dFZPwAD82ZBVe+BiHg63btrH34BHc3TRMnTzhoj5pMTFxrLerOV1TT2RgZ4Le0zX1VDs0xMTE9XqM3N2rR9BDaW0DgWFR3frpdH48+8v/4uiRA/iWnqbFbKY0exu/XzgJpVJOSVEBrU31IIps3JzD0PR0TDWnSQ70JC5IwHRkI//K3MTjL/wKD4+edXIvhkwm49Fnf8GqL5bSmnMUlwiB0Yk8/OTDfR5LQkKi/9i7by8r1mxE6eGPw2oiMsSXxYseQa3PN3AmAAAgAElEQVRWd+tXVVXJ4aNH0ajUDB8+TFIOJa5rJKVP4rKRqT2w2Oy4nWdRq25swVd/LlGwy+WisLAAq9VCdHQMb7z9FvVWLWGJt2O3W1n6zRZur6xi2tSpF5xHEAQWPftzVn7+ERuPd+bo8wmJ5pFnftZj28/pdHL8+DF0wdG8v3UXD41Pw0/rRXldI+tzK3jw+UU9xler1UTHJHAgcytqeyvutmbe/3YTw6IDiNEqCAvRseN4MSODNYiNp3lsdDxxwb6U1Tej8XdH7y2yZf23zL1n4WWto4+PL48+/RIulwtBEBAEAZerZ5LXK6W2tpZThfl4eWtJTEy6qUu4SUhcCWVlpXy9dgfJo+5GLu/8nVSV5fPpF1/w+KJz95DVa9ey60AeviGJdDjMrNv6Go8tvPumCq6SuLmQ7voSl83EGfNY8e1S5p0Jlmg2mVl7pIh5S34BdCoZn737ClEe4KGW8+2HFVQLQYyY1nnTVChVJGfcwebvlzNh/Pgfze3n5eXNI0/+BJfrTODFeXV2rVYrVqsFm83OZ+/8nSSdgmg3FfUqGa+s309EWBj6kAgWPvfv6PX6HmO7XC4+fefv3JMegr82gsbkIIy5R9i6/yjD7hpPh8vFxiOn+OmsEXy68xihPp1yhui8ya+pJCV9GJm7cq54PWUyGQ0NDaz6/APM9ZV0iBAcl8zcex++oryHoiiyZsUX1J08QFKgJ6ctDrZ8K/LQUz+/YGkzCYnrnbOJ0fvb3/P4ieP87dV/IvNLpbKyipDgEOQKOcHhCRzPWt7lzlFdXUXm/hOkjLqzS4bgiHiWfbGCP/wuUXqpkrguka5KicsmNW0wCAJfbliF02JC461j1qIXCQ0NQxRFvv7oDe4bFIrOuzPVSYibnI+yCmhpqkPr26l8CYKAm3cgtbU1REREXnTO85U9u93Oii8+or74JB5qObsPHePFOeOIjegMrBgUF8nqfSdInfkgyckpFxwzP99IjCf4azujaHU6fwLDItHklfC39Yfw8vDAy0tLgI8XSrkcm8OJmxvIBBmiqwObw4lCpb7g+JeKw+Fg2Zt/ZV5aMEHpgwDIK63isw/e4PFnf37Z4548mYe56CAPjj8XCZze3Mo3n7zDUy/9+orllpC4mrS0NLP6q2U0VhTjAsLi07hz/sJ+SQi/fccO1n9/GJdbIL4BMdS1OqhvyGVQelrnvUeu7FL6jh47hi40sZvSqVCqUHkFUlZWSnR0zBXLIyHR30hKn8QVkZo6iNTUQT3aGxoa8BTNXQofgIenGxkRvhw5dRTt8HMJha3mJnwuEJDxY3zz+UfEUcddk9Ox2OyYyguw1JVhDdSjUXc+AEbEhbJn/64fVfra2014a7r/FMLDIwnS+xGXmMaIpFjW7tpPflUj4XpfdhfVMmOwF02mdjy1OrYfK2T4+Dl9lv+H5Bw7SoqfkiDdOZ+gpIhgjmbnUltbe9mpcHL2ZzEqrrvvpd7HG9F0GrPZjLu7+xXJLSFxtejo6OCjN/7KzAQd4YZBXVH0n773TxY///IVje1wOFi/NZOk0fPxLDrOqdMFhCWMoLXJ2Xk/c9fg7Sbr+r1oNBo6nG09xnE57T38/iQkrheklC23GHV1dZSUFONwOAZ0HlEUkdF920Xvr0d0tNNuau7qU1p4DENkYJ+dny0WC42nT5IW3ZlzTxAEEASCtW7UVld29evo6OjyybkQcXHxnKhu61ZHV6FQUmxRcrqhjXarjXGDk/l8fzGtLiX1HRr+sHofn+wrZsOpNtziR5Ixckyf5O+NlqZ6/D17Wiv0HmpaWpove1yZXIarlxrBrn72GbwZqamp5uDB/Zw+XXLV6ixLXJgTJ3KJ8+oMGIPO331yZAjK9hpqaqqvaOyGhnpU7jpkMhnhMSkonC2U5u3CZmmj4MRBig6vZ9HCc2Uqhw0dSnPFCRz2cymXWpvr0QgWgoNDrkgWCYmBQrL03SKYTG189v4bqCz1aDUqVjZbmTD7PoYNH3XJY9TU1LBx1Re01FaAQsmIidMZMXpcr4qDv78/zWKnn5+PZ+ebsUyQ0abSoneTk5v1NTIgY0gKd83pe+1aq9WCh+rc5atRKdG4e1HTYkaj7UwhI4oiO0+WMXr+9DPKX8/atdCZFiZh1O38c9WXJPl2vgedbHYxad4i/AKCWbVrKw6HjdlP/BIPT2/qqysY7B9ESGgoen0Abm5ufZa/N6JiE9h7ZBvJUeeSR4uiSFGjmUnnJZTuK0NHTyTzize5b6xP13dVXteI2jek32S/2XC5XHy4bBn5pY24+QRjN+1F597B808/1S/biBKXR2N9HQFevbwYeapobGwkMDCol6MuDW9vLXZLC9DpRjJ+2j1Ul5/i+OFdDDUEsWTxz/D0PLdz4enpxeMP3cPSz5ej9AjA5bTjJrfy7JOLr9uXKZfLRUNDAx4eHpKF/xZFUvpuEb7++F0mhMiJCuyMKnN2dPDxui8IDgknMDDoggrRWVpamvnsrb8wb3AkQUnJ2B1ONu1eg8XSzqTbpvfoLwgC9yx6hs/feQWDnwoPpYzj1W2MnH4Xw0ZOvuLz8fHxpdkpw2p3oFF15si7a/Jo/vLxSmKjBEothRwuqabRZMO2/D02OEVi0kYwc+69vTpY11SWE+SnxeRyAhDop6S2upLbp9/JkKHDr1jeSyEqKppdPhFsPZrPiPhwbA4nO46XkDxyymWlgzlLTEwcJcNv44Pvt5Cg96TJ7KCuQ8NDT73Uj9LfXGRl7+J0AySPmNnVVlWaz4pVq1h4//3XULJbm6iYOLL2byLtPHc5URQpbjAzLuzK8lq6u7uTnhRD4cmDRCYMQSaT4e6pJUzvwVNLnuxVSUpOSuaPv/sPysvLUKvVBAYGXbcK3+Ejh/lq5Vpkai0OWzsJUcE88uBCqTbwLYak9N0CmEwmbA0VRKWcc+QXRRcRinb+/O/PEh8dg0dgOPPufxTfC5QU2525nYmxfl3+ZiqlgpnDEnn7+81MmDytW4DFWYKDQ3jhP/5EXt4JLBYzCxMMxMdHUFfX0w+mrwiCQLghnd+99wETYv3x0WppEt1JHD2NqXfeQ2VlBarKz/j3eRm4a9SIosi+fCNrV37JXfc+2G2s6uoqHNWF3D+hu3L3RVYuNTXVV2Q96A1RFDl16hT5+SWEhYV31Q8WBIEHH3+Wgwf3smZ/FiqlmmFzF/dLCbIp02aRMXo8JSXFxHl6ERUVfd0+nK4HMrMPEJF4W7e2oPB4ju3+hstLzCPRH0RERLJTF8H2YwWMTIjA0dHBjtxiogaPxcvL+4rHX7jgPtauW8fuvSvocImEBfnzs+ef/lGrmFwu71HT+3qjurqKT5avJ2XUPORnXnorS/L47IsvefQRKSforYSk9N0COJ0O1IpzSpmISEFeLkEakTGxQdw1aRCV9U0sffNvvPCr/9er1a+2spTBYd3LgslkMryUMsxmM/nGPA5nbwdg8OhJDB2WgSAIKBQK0tLS+/2c9mbvxFZ0iBfvm8mxwhKKGpo51dbOT3/3KwIDA8k9sp+pKWFdZdgEQWBEQiTvbj+A4677ulXQKC8vI1rXc5szWudGeXlZn5U+p9OJ0XgSu91GfLyh25aQxWJh6b9eIVhpxlclsGGzBVVwPPc/sgSZTIZMJiMjYzQZGaMvc2V6l6e1tQUvL2/S0noG3Uj0xCW6cDocVNfUYrXZ8PXxQXcFNZYl+oezL0b792bzzb5M5EoVw+9YSFra4H4ZXyaTMWf2bObMnt0v410vbPt+JyHxGV0KH0BIVFK3FDQStwaS0neT0mlNKuTovl0gk1HZaqPNbMHL3Q2zuR2ly8bxWhNJqZ0KWYi/L3HedeTlHSc1taeSFhYVT0nFAQZ7RnS1OTs6aHPChtXLUdTkMScpCoCsXSsoLjjBPQ88OmDntnvrdzwxLgmFXE6If+fD+FRlDSu+XEp8QjJ5x46QPiiw23GCIOCpVmC1Wrrd5Pz99Zwy9QxsqTLZGeXXtzx2ZWWlLP/gdRJ0KtwUcj78to0R0+5m5JgJAKxb9SUj/WFIYhJWi4MRwPZjBezJzmTMuIl9XImLk7VzG/u2f4efRkGT1UHi8AlMmzn3R618oiiyf282BzI347TbiDCkcfv0Od2U15udxPgoPlv3DRHJE1AoPSipaCD36F4mD4q+1qLd8shkMkaOHsfI0eMuqb/VaqW6ugofHx98fHrWs74VaG01odFG9GiXKdTY7XZJ6buFkKJ3b1LWrV7OnuX/YpC6iTR5PeqOdv5v1ffsN5ZwvKiczbmldGi8SQgP7jpG76Gmuamx1/FGjp3I7vJ2CiqqEUWRlnYzy7NzSR05iZbiHKYPS8LL3Q0vdzemD02kpSiH2traATk3URRRuBwozrNIulwuTLXlFO3bhr4hB017FWu37sB+XmSdzeGgtUOOp6dXt/EiI6Nolms5cboSURQRRZHjpytpkfv0adtGFEW+WfomD46I5bZBCYxJiWXxpHQObl5BQ0MDAGX5uSRGBHc7bnRiFEf3fn8ZK/Hj5OYcpSj7O56amMJ9o5N4clIa1oK9ZO3c/qPHbVy7kors1SwcEsqScQlEWUv44PU/D3jE9/WEsaAEH08NNaf201RTRGPlSerL8wgN6d+tfomBZfOWLfz2f/7K+19t4U+vvstb7753S13HZxk6OJWaMmO3NqulHY3CJQV03GJISt9NSF1dHRXHspk/OpUwvY6IQD+emzmOAH9/bJEjaA4chNkzmHmTRnWz+JysbSMmNr7XMT08PFj84q8plIfxXnYhawraGDFvMTr/AOL8e9404vzdKSs7PSDnJ5PJ6FBosNrP3byrqytoaWpkbHoChvBgFk0bS4Olg5VbM2lpN1NSXcenu44zbd6DPaxcgiCw6OmfUqIK4+0dx3l7x3FOq8JY9PRPEQQBu91O9q4dLHvnNVZ9/Qk1NTW9ylVRUU6wG3h7nNsqlslkZET5cezw/gFZix9j97Z1TB8c1+VvKQgCU9LjOJS15YLHWK1WCg7tYvqwRDQqJYIgkBgRQpKvjCNHDlwt0a8pDoeDFrODidMXMHrsJCKDvBk6dBiz7n2KnBPGiw8gcV2Ql3eCzVk5pIy9h7j08SSPmkOjU8fyFSuutWhXnWFDh6NTmSjMyaK5oYaCEwdZ+/mrNDQ28Pqb/6K0dGDu1RLXH9L27k1IYaGRlGDvbsqNIAikhvgQGBxK2rSZqFRqvt2XzYSkSORyOXvzy1CHGAj5kdQg3t5axk+ZTsuwkQQHh+Lu7k5RUSHF7eeUL5fLhd1hp8ZkJ9z38rdSmpoa2bh6ObVlp5Cr1GSMn0bGqLFd53TbnPv4auVH3DksHh9Pd3JOFpBfY2LRnM4tH6VCzov3z+G/vtwCpTa8fAK5+6mHuoImfohGo+HuBY90fRZFkRMncjmwaxv7s7czJCqQmSPSaWqr5Ku3/si0+5/GkJjU5/OKMKSRV1rB0MRz1Uey84oZPKpnBPSVYjWb8HTrbplSKuTgvLClo7GxgUAvdQ/FONJfy8nSYuhHX8PrFblcDi4Hoiii1QWg1XUmxW6qr8bb2+siR0tcL2zdkUlU8uhu13JoVBKHsr7i/vturRyVcrmcnzz3LMdyjrJtRyYFR3KYPPtR/AJCMbU28drbH/PS048QHt5zC1ji5kJS+m5CPD29KLM6e7S3Wp3EeXT6Zd0xex55sQa2Z23F2WEjffzdP5qaxGaz8fmHb+FqLEfvpWZdg5mUMbczeepMNogenKqsxU200VBdTl2LiU051fgkjSE6OrbPN9f29nY++sefmZkUQOSEJGwOB5uzV9NuamXy1M4UGqlpg9G4PceGTWswtVRSXOnk2TsmdrOyKeQywkLDWPTUT/s0P8D6Nd/QatxDmk5N2mB/iupb2XEwh3mTRhHs58Oybz4m4dd/6P5ACQ2jygKt7ZYuOVwuF/uK67l/dgYAM+bex7K3X6V0Tx6+KhlFjWY0IQlMP88/SRRFamtrUCiU+Pn59Vn2s0QlpnOytJCkyHOKfGV9E7qQCERRpKAgn+KCPLS+/gweOhyNRoOvr46aNluPscobWwgadOk5HW8kOjo6yMk5RlHJaUJDghk6ZChDUhM5VZRLeGzamT5OyvP38pMnpHQtNwoWqw2fH5RHFAQBkVtD2aurqyMnNwe1SsXgwUPw8PBg8KAhbN6WyeS5T+Lm0fkC4+ntS3T6ZL5du57nn3nqGkstMdBISt9NSFJSCltWOkhvaeuqJ1vV0ES1Q9VVD1IQBJKTU3otT1ZcXMSODaswNTfgHxzOlBnz2LnlO1Ld20lN7szzJ4oi3+zexsnwaB556qe89cofqczNJkynxd/Pjz8vuZfME9ns1foyauyEPsm/f88uRoZ6EBnYGUShViqZNTyJt7dvYfzkaV159uLi4omL+xkAhw8d4PC2rwj19+1SxA4UlBI/aMQlz9vQ0MCxw/sxmUwUHdzOk7cPp8CYS1iAL4ZQPZ/tLqCmqYVAXy1u2LFYLN38YQRBYP6iZ/n0bCCHUs7x6jZGTJvfpby5ubnx5Iu/wmSqJz+/hJlh4d2ig4uLT/Htp++iV4s4OkQsKi8WPPosOl3flb/JU2fy3mt/otVaQkygjoqGZnaXtvLgM79k2bv/wL2tgsRgXxorLLy1aRULn3mZwMAgYgaPZtPhg0xKjUOpkHOqspZj9U6eHZrRZxmuJeXlZSxftYa6hhY83dXcOXMqqeelLYLO7ez/e+0f2BT+ePuFcqykkO82bOXF555izXfrOJ69AqXGC6eliQVzZ15SfWiJ64NRGYPZsj+XmKRz121LUx2hQf43vZVv/caNbM06jG9QAh1OOyvXbePJR+8nIT6BphYTAR7dLdZeWj8K83v355a4uZCUvpsQhULBg0+/zDcfv43CWoJLBJl3AA899dOL3uzy80+y5bO3mDssDr+UeCrqGvnszT/RbrYye/bIrn6CIDA5JYqtmZtJevJFPN01/HbxA7ipVQiCgLOjAz93JV+8/zp2h51hGaMvOcFwdXkJY/Xdt4YFQUDnpsRkaus1Am/wkGFUl5/m/R27iPB1p6bNiltwLPfPmndJc+7bncn+Td8wIsqP6vIa3FrLqKsLQ6XSYLO3o1YqSAryoqSqjgAfb8yOjl6TmoaHR/DCf/y5K2XLYz9I2XL2XGJiYvDy0ndrN5vNrPzonywak4hCIcNstWOx2fn8vdd59he/7/ODytPTi6d//p8c2JfN7pJC9OEZLLl3PCdP5uJvq+a2jHPb0/EhJlZ99gFP/fTXzJxzD9m7/FiWtZ0Oh42wuGQW/+SZGyqJa01NNa++9RHRg24jIU6HzWrmo6828OA8J0MGD+nqt3HzZvCOJTa6MxeiPiiC+mo9q9asZfGjizCbzZhMJvz8/C6awPxWRRRFiouLaG1tITIy6oK5Pq82o0eN4eCRHPKP7sBHH4W5tRFb0yl+9sIz11q0AaWmppptWUdIHX0uSt8RlcgHH3/BH3//G3y8PbC0t3VZ+gDaWhoI8O/fyOaKinJ27d6L0+lk9IjhxMTE9uv4EpeHpPTdpAQEBPDMz3+LydSGIMguWeHauuYr7hudhKdbZ6mjUL2Omaku/rFqB4LQfXtPrVLisLUC4LBauhQ+m8PB0jVbiPNVMi3KHfmpLN75fgMPPvNL9PqL+0QFR8Rw+lQ2ep9zyVZFUaTB4ugReXsWQRCYMWc+pil3UFNTxThf3SVbx0wmE3s3fsPiSenIZDK83d042FZHbVkxEQmplObn4q5RU2eyER3ixu6TJcSmj+y1sgd0Kt0pKamXNPf55Bw7xOAgD7bsP0J1dTXeGiUNZgeiuw+VlRWEhoZRV1fH7p1baG6oJSYxjYyRY3+0uLtGo2HchCkwYUpX2/GDu7kjtnv1Ap23J862U9jtdlQqFWPHT2Hs+Ck/HO6G4bsNmwhLGoend6cCota4kzhsGqvXbeym9B0+dpzIIXO6HesfFMHJ3fuAzioNUnTjhWlra+W1N97GiicKjZb2xk2MGpLI3Xf9eFqgq4FCoeDF557l5Mk88k8VEZAczdAh83/093ItMJvNVFdXotP54XC08cGyr6msqiVA78fcWdMJCwsHOl1Fjp/IpaKiiojwMBITk3pNin/4yFF0YUnd1l+p0qDwCKCsrJS7587irQ+/Im7wbbh7amlva6b42HZeevqRHmNdLtt37OC7bfsIihmMTCbn7U9WM2pQDPPmzu23OSQuD0npu8m5kJJ0IZzmVjzdujvzRgT4IQLVjS1dFTkA9heUkTp8BgBhcUmcKClBaWtlT46RKA8Bg58XFo2OuPhIwvxbWLv8Y1JSfn9RGTJGjuWdrK34eNQQGxKA1e5g4+F8hk6444KK1rnz9cTTs/cI5AtRUGAkJdCr6wYaEeDHJpuAyWzBbrcRFpvEriNH2HCimkRZAHGDRjFz7r19muNSsJjN5BYUkeqvYvaERAAcHR28sv4wRUVFWK0W1i17g8mJwfiHeXEybwfv7d3JEz/59z49yNQad6w2C3h2V2acLnp9iNyIlFVUETmk+3a0UqXGbO0exKJRq3E67KjU5+q5ulwdyOU39/Zff7Hs0y/wCBlKeECn36goDmHfwS0kGU706jpytREEgaSk5H6patPfiKLI2nXr2LnnCG7aQFrqKykryWfcrMeIGT6G1uZ6XnlrKc8/sZDAwCD+/vob2BU63LWBZB3bjft3G/jpC8/1qAWtUirpcLb3nM/lRKlUEhkZxXOP38fKtRuoaG7DX6flJ08+1G9BHO3t7Xy3ZRcpY+7uup/o9CFk71nNuDFj0Ov1FxlBYiCR//73v7/WMlxtfICXLBY7onh1J/bwUGM226/upH3kwN4skvQenVGeZ8g/Xcb+omqyDuewJycPu6OD3MpGmt2CmXHnfGQyGYEhYfzxb38jzF2kuKaRCXGBVDWbkGs80AcE4emmITu3kCmz5lx0DZRKJUmDhnOgsIIdR42cbLAz6La7GDWmb76Bl0pDQwMNxTlEB3ZaBgVBwBAVxqeZOeTWmClqsmHXJ7Dk5//J5BnzSEpJv2LlqLdrQa1xY+UXH3JnejhV9Y20tJlRKBTIZTLqRDeO7c9iYUYMQTotGpWSML0vjvYmyttFoqIvfevE3duXbds2kxoe0GUNOHG6ErsuivQhV89vbyB/D6dPn6bB5MLd85y12G6zYGsuYeL4sV1tKqWcPXv34RcU1bkWIpw4nIlW7UCjVqPX67tt64pi/0d93gj3hd5wOp2sWLOJyKTubh9unr6UFhwmY9jQSx7rRl2DK+HI0cOsz8whecQsdIGRNFnkuFS+2NrqCAqLQa1xx8svlGMHv6eyooI2eQgR8YPx0urQBUbQYnbSWldMosHQbVydzpeNG9biF5qATNZ57ZpaG7E3FjJrxnQEQcDXV8eYkSOYMnE8o0Zk4OPj02/nlZ9vpKDSjC4gvKtNEASsNgdeKms3v9iammpqa6vx8PDs+p3ditdCb5y/DoIg4O6uAngNaL6ScSVLn0Q3Js6Yx4pvlzJvRCLuGjVllVV8uGYbz867g9iQQEorK1ielcvoeYuZctvUrgdgSXEx8yaMQKOA+pNVtLkUDEqIobi2BavNikqpwiVcXFGqra1l89rlNFaVovbwZuq8h0gaYItBYmISm7+xkWG2dG1ri6KIf6SBZ3/1B+Ry+UUtjP2Bv78elwsqq6rx81AhukTyS5rR+YdT2dqCzG7Cw627RS8lIpjVJ44ycfLUHuM5HA7kcnkPBTUmJpaqCXfyztY1RPq60Wi2o/ALY8Gim6cG58w7pvG/r72FQjERH79AzKYWCo9u5/H7u5fXyhieQVVNLbuyv0HjpScv9yAAPmNmsjbzJCvWrOel556itOQUWZtWI+uwISo1TJ59L2npQ3qb+pait/dmQZDhcl3lN+obkK07sog+L6WM2WwlNG4oJ7O/ZvAZPdrdU0tZYyuNTS3EZ9yNw+FAJpMhl8sJiUzk0MFvuWtOd/cErdaHRxbM4dOvVqDWhuLqsKNwtvDck4uvypa7h4cHTru5R7vTbsbrjH9zW1srb737AU1mUKg9sbVWMv/OOxg5YmSP4yT6F0npk+hGatpgEAS+3PgtTrOJ/MICFs2cQnxYZ367qLBwlsz249vcA9x2+7Su4xrrqgn388IQEYKf1puDhw+QEBqAm0qG3Wbj4KlKkof/eNmkhoYGPnvzz8xJDyckLpE2s4XVK97DbnuIQUOG9et5ni1Tl3fsIO4eXoydcQ/P/u5lnKbOyhkKLz/++//euar+P5WVFVgsZnSebug8OoMmPNw0rMoxknj3dI5lbephaWpoNaH17e67WFVVydJPv6Ch1QouJ2lJcdx/7z3dAjHGTpjC8JFjqaqqxNvb+7Kig69n9Ho9L7/wFKvWfkfh/mx8tF48vWg+8XHdt/4FQWDu7NlMnTKF77/fjtVmIzXj3HXd1hLNX//+CqlaG4+PSUGpkGO1O/j626Wo/z977x3YxnWlff/QG9FIEGDvJNjFIlG9WJblKlu25V7iFpe4ZZ28STbJ7pfd791kU23HJY5777Jk9V6pSoqkSLGAvfcKAgRAgMD7B2RSNCWZsmXZSfT8x+HMvTMXM/eee85zniNXkJSUfKEf7XsDsVhMRIiegd4O9IYJ/cvW2mJuvWbed3hn/xhwulwESiZCszK5FI97FN8p37fTYUMToKCru5vCoiK8AjF4vWjUSuKio864GZ2ROYPUlFSamhqRSqVERkZ9Y4PP4/HgcrlQKpVnbSsmJhaZz8pQf/e4xqV9eJDRoWZSU28H4NU330FiyCD5JC1gbMzDx+vXEx0VNS3e90V8fXwnRp/ZbN4NGIEvCDYPAfHArwEJ8IzFYnnh5LnLgL8ACuAji8Xy65PHs4BXAQ2wD3jYYrFMFae7iHNGevoM0tNnAPDc//yC9PjJXA+tSonLNlnBPVu3+qoAACAASURBVCoukbKKfMxRYZijQhmwmnl5XwV2hxNNh5io1JmsvHLyjvTL2LdzE8uTQwg7mUWmVipYNTeVtzavPq9Gn8/n46N3XoOuarKigrF2unj2T6uJVom4bZH/ubeWt/L7X/8bb3y65YIR0g/l72VBYgjry9pYmGjEECCnqmOIkqZu5hmCSc6dT35FKQtSY/3hklE3Oytauf7B28fbsNvtPPPia0RnXkao2h+yaWus5I233+GhB+6f1J9MJiMm5p+3lqzJZOKh+++b1rlKpZKGlg5ikydL/Ki1QdTVN/PTe+aPUx7kUgkrcpPYuHXdt2L0+Xw+TpSXsS//MGNeLwvmzCI7O+c7T4w4He6583aeef7v9LUHIpZrGBloISs5iozT1O++iMmYMzObA+VlxCT5PcYxkREUHisg4KSWqtNhp6Z4J7deu5Q/P/cSUvqJSPTTLxx2K3t3rOGHN196xvYlEgkajZb8gwfZs+8AOVkZpKWln/N75PF4+OjTTyk5UYNIIkcq9HDnrTeSlJh02vMFAgGPP/xDXnnjbdpq3AgFQpSSMZ585AEkEr8CQ2efjdTECf1QkUhMSGw2+QcPk5Fx+nYv4vzgght9ZrNZACQB0V8YaWazORz4EMgFXMDBk4ZhA/A6sBhoATaazeYrLRbLZuBd4AGLxXLYbDa/BvwQ+NuFfp7vO3w+HwVHD1Gwdytjo05CYhJZfs2N0y48rjWE0j1gxaif4Eb1DQ2jOrmD+wKJiUnskxrIL69jVlIUqbGRtFmdiCMzWXH9zdPKgOxsaeCynMkVQWQSCQK387xyqWpqqqHLwsrZ/rBxR2c7d+aEUdY+RGKIX+cvMUTPrz87yoED+1iwYPG02/b5fOTv3UXxwZ3gcRMYFs0VK2/FYDB85bW9vT1ohbA8PYrytl4qu2zEhxqIDzPico1yxTU3sHm9j7/vPoRKImQEKZetup/Q0LDxNgoKCwgwmVGpJzg6YTEpVBz+HKt1CI1Ge7quLwL/IulwT+USjXlcKOWTPb5alYKR4dZv5T5Wr1nDsaoOIhNzkQiFrN5eSFlFFT+4845vpb9zgcvl4ljRMXp6+0iMjyMlJZX/+Pf/Q01NNUNDg8TEXILRaPzqhi6CxYsWcbzsb1Qf34vWEInd2otR3EGAKYCqw5+hVsq579ZraO/oJC3vStpbm6gt3IBcY8Qx1MmYvZPsrBlnbP946XHe+WQDxphsZHI9H2w8SNThozx4/33nNJd++MmnNPQJSZu/yl+W0uXk5bc+4hc/fuSM85peH8jPnvoxw8NWxsbGJq03brcboUgy5RqJVIbT9Y3oahcxDXwXnr4vWKfbzGZzEPAKMAzsslgs/QBms/lTYBWwF6ixWCwNJ4+/C9xkNpsrAIXFYjl8sq03gf/iotE3Bbu3b6KvdC935CQik4hp6urljed+x0M/+c20DLFLr7mRD174LddlxxFpMtDZP8S64npW3v/UpPMEAgH3PPxjDh3Yy/uFB5HKZMy68i4yMrOmPcGYImJo6e4kNnRi0XC53XjF8vPq5agqO0ZW9EQfnR0dROiUNPXZOGRpRa+SoVXJyYsJYt++vZOMvs7ODjav+QBbXycCsYy5y64md6Zfyqa5uYnXX/4bwa52Vi3MJlCnp713gHde/F8e/Ml/nVU2x+VyUV7dgKepl6z4SBakJuB2jdDncNM+4iU+3l9D9+rrbmLsmhtwOp2nDbP09g2gVE816CVyNcPDwxeNvrNg6aJ5vPTuOjR5V42Pa09HE8bAALoHhhjz+tCoFOgClDR392GKijvv9zAw0M+RkmrSTtFYS5qxmIojG+nq6pwk5H2h0dvby1+efwmZLg6lJpCCygME7djN4z96GLP5XzfM/XUhkUh46snHqaqqpL6hEdOMFJYte5DBQeek805UWlAE6Ji9OJ0RuxXbUD9q7Vxaq48yMjKCVjs1CcPr9fL+p5+TMvt6xGK/gaULMmEp2U11tWXav9fo6CilFXWkzb9x/JhUJscUO5O9+/O58fqVZ71erdZMOabT6ZEJR3E6bMgVExqmnY0nuPKmqdzkizi/+C6MPj2wE3gcfyh3D/AR0HHKOR1AHhB2muMRZzk+bQQFBXz1Sd8CLiRfwe12Yynax8NLM8cXkOTYMGyjo1RXFnHZFVee9frKygo2fPgKaoWYFzbsQSyRM3vxpTz0y/8mIuL0w33DqpXcsOrsE8GZxuDGW2/hxd/+Gr1WRUiQDtuIkw3F1Vx36z3nddxMocG4m1uQK/yToSE4iK6qZhzuMdLDdagVUnqHnVR3DTHv6szxvvv6+ljzxtPckBODaeYMnKNuNuSvRakQMWhzsn7bUYbaWrh6YSp1ja24Qh3ExUSz2OGgurKI5VdedcZx2LW7kIi0BTSO2PnoWDMaqQD3mJd+q42cS68hLW162bnz52ZR+dFu5NETBonX60U4ZiUtLQGJZOoO+7vE+fxdfT4fe/buY9O2vbhG3WSkJnLLqpVoNFMXntPfSw59Az2s3/I5cm0YbqcVk07CdTes5Kevvk1MZCxin5MAn5VAUwhP/MfjGAzn5/6/GIeWlhr0oTEoFJOFsPWhsQwOdpGefm5yROcTr7z+KjGZl47ztIhLpK6ygBPlRVy27MxhxuniX5XLZTTOZtGiiQSG4ODJ3+jiBbm89N52IqJjkcuDCAwKYszjRuy1kpoaf1peX3t7OwF6EwFfkmUKi0mhrqGWBQuml6VvtVpRBgQgl0++J73BgNNR87V/s58++QC/f+ZlJNoY2rv6aW8oRy1x0TcwA6/Xi0QyxpGjBYyNecmblTutSMk/I76Nb+KCG30Wi+UQcOiLv0+GZv8C/N9TThMAXkDI5ASxrzo+bfT12S54hllwsJqenuFpn9/e3kZxwUG8Y2PMmDn3nEtA9ff3ESAE15fq8BrVag6XV5CVe+bEiv7+Pt5/7s/ctSAVhSwOFudQ2dxBucuHTKY9p+c4FaeOgdfrRSAQnOKtknHDfT9h27qPGTxWilShZv4VdxITn/a1+zsdEpNzeG/rRqKCA5FJJOh0gezrsuIc9aCSSfB6fYy43FR327g/JWu873WrV7MgJhCtQonT4aejXjEjkRc/eI8uDMTNWIa8vxaZXIVUpqSppZFAfRBBASqOVlrInrnwtOMAcLjgBNqgRLKufAjLwbUM2zrxCgQMynRcufLOaT+/yRSNWuygoiif0OhUXK4RWixHWXn5wpMeBOdXtnGhcK7fw1fh8/XrOVrRTlzqpYjEEmraG/n5r3/Hr372k2kn5OTNnEd6ahatrS1otVrsdht/e3sty+/8NV0drTjtNvps/ZiMUnw+GT09w7jdbvIPHKCwpAy1SsllSxcTH58w7fs+dRzGxsTYh/pxfklP0D7UD6Sedbys1iGEQtGUCjDnAz6fj+r6DtIXLJh0b8FhyWzbuZescyh3eDqc73fhHxWnGwejMQqDcoyyo7sxRSXjco7QWXeM21YuZ2DAcdp2RkbGsA0NTXmPhgYGEAUqp/Th8/nweDyIxeJJ0QOfDzxOG8NWG5JT6hi31Fdy5bykr/2bBQQY+PEjD/LTf/81SkMiS6+8GW2gkS0HCigq+h0N7UPow9IQAB99/meuXb6QRQsXfmW7/0w49V0QCgXnzVH1XXD6FgAyi8Wy8+QhAdAIhJ5yWgjQDrSe4/F/GuTv3UXFvnXMSwhFKBCw452jROUuYdkVZ0+GOBUajdZf0eFLfLjmngFCEuaf5UooOLSfhQnBKGQTHoeUqFAO7y3DbrdPu8IH+LNJN6/5AHtfJwp1ABFJWTRWlWHtbsUrFJGau4CrrrsJsViMyRTCXT98Ytptfx0EBgZx6c338/rqtwlRimjp7KLbKkLkFvLSXgsAtjEhqy5fSm9vD9HRMQB0tzWxMGVyiSmxSIR7ZAhlRA4KZQC9Ix6/Z00oRCxXY7UO0dhrJzz1zNwbgPBQEyVNvYRHm8m94l7GxjyAgMrDnxEUNP1drlAo5LGHH6KgsICjxwpRq1Q8du+qf+qEDfDX0D1wtJTUeTeMv+vG8FhGbAMcKzrGvLnTzyZVKpUkJflZKK+8/iaR5tkolUpi4ycI5ifyP8br9eLz+Xj6uRdwiIyExS7E6bDxt7fXcP3l85k/79wzWKOjYwgQOejtaMIQ6t/k9fe0I3b3kXgG4nxHRzuvvvku9lEhPp8Xk17B/ffcddqw3zeDd8pc4h51olDIz3LNRZwNXq+XLdu2se9gAWM+AbGRBlZes4KwsAlus0Ag4JEHf0hp2XG279xLXX09AWo1ldU1xMbGnDbzXqvVEWHU0N3eiDEsBvDrVA62nWDuHRPzq8/nY8u2bezOPwICMQqpgFtuuHZcWFsgEHD7TSt5/YO1hMTNRBmgpau1BpWvn5m5M7/Rs5eWnSAucylRCRNJPzHmWXz8+m+5/u6nkMv9a0xYTDLrtn5G1ozMi/SU84DvIryrA/7bbDbPwx/e/QFwJ/Cu2WwOBuzAjcCDQClgNpvNCfiTOm4HXrdYLE1ms9lpNpvnWyyWA8BdwObv4Fm+FdhsNop3rxsvCwYQGxrMG3t2kTt7wbRrW4rFYrIWLmfd0Z0sz0pELpVQ395NYaeDh+44u9Fntw6iVU3l/KllYhwOx7SNvv7+Pj566Y/cmBtLcHoaHp+bP736VwwBcq5Ki8Lt8VBWsJ4PrUPcee/D02rzfCA1LYPklN/T3d1Ff38fxRve5hJzCHX1dQgEAuLj4thZ1UFIyMTeIiwmgYZOC6nRExPyqNuDRyTH53EhEokJTJrP5mMHWZIRh9fjpr6jj5IhMQ/PmnvW+1k4fz57DzyLVh9MgCYQgUBIQ+VR5uRknHNIViwWM3fOXObOOXuf/0wYHBxAqtRN4Thqg0JpbG5l3tccihGHA5lWjtNhp6nuBA67nZCIGHwI8Xq9lJYex+bVEp/qFyKWyuSkzb6adZtXMzsv75z1HQUCAY8/8hDvfvgRJ/KP4gNiwo38+NGHTisIPjo6yrN/e5XozMuJCvAviAO9HTz/0qv88mc/OW9cWIFAQG5mKnUNFUTE+Q0Cn89HY8Uh7r358vPSx78i1ny+juP1g5jn+EXuPaM2nvnba/zqp09MMtqFQiEKuZLO/hHSFtyMWhtEZ2czf3j6RX7+1KOnXRPuv+du3nznXcoPFSMSyxD7nDx0722TDKdt27dz4HgLKXNXIRQKGXU5ee39z3nqES3h4X4KT2pqGv/nMQO79+2nf6CFy+ekMmvmrd9Yu7StoxONPnTSsSHrEEpdGKNOx7jRJxQKCTAmUFlVyey8Oadr6iLOAd9FeHeD2WyeDRQDIuAFi8VywGw2/wrYDUiBVy0Wy1EAs9l8D7AakAObgE9PNnUH8IrZbNYARcBfL+iDfItoaKgj2RQwaZIXCARkhGmorq5i9uzpexAWL72cIq2eD/dswe1yEB6XzL2PP4RCoTjrdUkZ2ZTt+HBcPgX8SRW9LggKmr6m24E927k02TReR7e7vY2V6Ua2VXYSE6xFIBAQolPw513rueGWu1Eqldjtdqqrq5BIpJjNyd8aD00oFBISEkpISChvv9SHsLeOS9NiANiZf4ATTh13hk9wFxdespxX/3IYhVRCTEgwQ3YHG4qqWXHrvazduIPhoT5i0+bQHqDn7YLt2LpruemOe7jh2nls+vxjOprrMYVHs/DSq6ZwNdRqDf/26AO8//Fqmk4MIhbCormzuHz5ci40vF4vVusQCoXye1en9EzQ6fS47ANTPFFDfR3k5cV87XbzcrP4cMM+2jo6CYxIRSo3UVxUBNZahEIhlZZaAkMmty8UChEr9fT19X6txIuAgAAefuB+vF7veHtnQmlZKXJ9HMqAiYVcbwilu1lOW1vreN3W84Ebr1/J62+9TcXhdUiVOpzWLpYvmfu9LHH2jwC3282RojJS560af2cDNHr0kVnszz/ANVdfPen8T9auxzzzCmRy/2Y8ODQafD62bt/JrTdPLQupVCr50UMPYrfbcbmc6PWBUzYBu/IPkzxn1fg7JpXJiUyex9adu7nv7gmxdpPJxK03rTrnZ/T5fLhcLmQy2ZS+E+JiqDtUiy7INH5MKBDgtPWgCpjspfaNuZF+z/jI/6j4TnT6LBbLfwD/8aVj7wPvn+bcncCU2JjFYjmOP9njnw4KhRKba2zKcdvoGBHKc4vrCwQCcmfOJnfmVKVzl8tFc3MTKpWK0NCwSR9lamoGhQf2sK3YQmaUCavDwd7qTpZefw822zABAeppeRF62luYnzRhOPZ0dRIWIEcpFeMe8yIVi9AoFWhFY3R1ddDb3cXBTR+RHqLGNeZj+6cubrj3sfEQ69eFz+fD4XAgkUimGJF9fX1EB6lRqzS8V9hIn9WODxgaGWTD56tZfuUKpFIparWGHzz+73z6/pt8UHCU8PBIltz0EGZzClHRcbzyxtu0jnjxAZGxsTzwX/+JQCDg3Rd+x3KzieW5kbT09PDBC7/loX//DXL55IktJCSUp5547Bs95zdF6fEidn7+AYEyAVanh7CkGVx30x0XpCLJuaK4pJh1m7Yz4nSjUkiIDg+k+vg+4tPmIhJL6G5vYMzayMzcc1+svsCsmbP407MvYki5ApXGiMczSmBILEqjhrITpZiMBhos/ZPEiQE8zuFzrnv9ZUyn1N/w8DBi2VSPvEQegM1mm3SstOw4m7buwu5wEh8dwbXXXHVOotwSiYSHHrifwcEBBgcHCQkJnVL39SKmj5EROyKpaso8qtEZaO+0TDl/2O4iUj75tzaERlNdsv6s/ahUqtNGZnw+H17f1Io9am0gPdXF032MM2L/gXw2bd2NTyRD4HVx9eVLWTBvIsKUm5PL9l37aG2oJCzazKhrhLaaI4QGKRh1OVCI/d/PqMuBo6+e1NSbv/E9XcTFihzfS8TFxbPBLqBn0DruIRsctlPVO8pl33BX7fV6aWpqpKykkLrigyQEqxhyuBkWa7jzh0+Mp9gLhULu/uHjnDhxnILSYyhUYWijdOxZ8zaFcjFWj5Bl193mr+BxFoTHJlLfcYL0WL/HTCKT028dwunxIhH5J5sxr5dumwuXy83hzR/xwJIZiE7+L8/h5J23X+TJX/3v16p36/P52LRhLevefwWRx4VCG0je4su54dYfjBt/jY31pIZomJ0ShyZASbWlisvSIxhxjFJt2curtZU8+OQvGBoa4oNXnyVYPEpYtJ7avh7sNisej4eW5iZmZSShMwSTkJA0rkv14Vt/Z0VGBBHB/vBLTEgwNyrkrPv4PW6++9Fzfp5vE21trRz4/G0eWJAxLkR8xNLAxrUfc92q27/i6guLE+VlvLdmB8m5lyORyhh1ObEc20JeegyW8q24Rt2kJMVx7Y8fm1SJ5Fzg8/lob28lNiGNyKR4BoeGkMtUBBtisA33U1BUyq2rbmD7nqexB4ejUuvw+Xy01pWRmhh1TrzXr4uU5GS27H0f4ibmBa/Xy0h/C9HRt4wfO3jwIGu3HyY8MRfPUD+1PTb+8PQL/OpnPz6trMbp4HK52Lh5M0Wl5QgEQvKyM7ji8stpaWmiqrqGQL2e7Kzsfxjv8HcNtVoDHjtjYx5EoomluLejkaW5U7P1pRIhHo97XIIFYKi/m/AQ05RzpwOBQIBWJcXpsCNXTLyrna21ZKV+MwmeouIiNuw6RvKcGxAKRYyNeVi3fTsBKiVZM/xi1BKJhJ88+Rjbd+6kuHg9ASold12/lMTEe/ifP7yIT6oDgZCxkR4evv/Oi+/VeYLoN7/5zXd9DxcaOuDHDscovgtcHnK6haQFAgHxKZms2ZVPVVMr5S09lHQ7ueWBJ85IZG1ra2Xvjk1UlR9HrlSfVny5oaGet577HX0Vh2gs3IHXYWN+hpm5ydEYJG425heQkzexExMIBJhMoaRl5lBtKSfIWs91s5LJjDKSEaZjw9ZthCVmnFUSIyQsnDVbtqGX+NCrVXgEQl7acIBIYyAJIXr6bU4+K6xnRGkiLDKWaPoIDZrwgEklYrp6+1CFJUxbUPpUfPLBm9RsfYcnlpi5IiOCAEY5dvw43UN2MrL8RGS73U5TxTFijXo+35XPD+abUcmlDI24SExMxGEbwipU8+7LzzLP4CE1TE9qbCQ5MSbWbNrC3r27UQ/WYfL201h5nIKyCjJzZiMSidi96TMuSZksb6OUyzhqaSJ3/jeXuTif2L5hNXNDpOjVEwtAeJCWHUdLyFt02Xnjh32Bb1JY/bW33iMi9RLEYgkDvR0IhUICQ2Lp66jlFz/5N5YuXkhmevrXXiiam5t45oWXyC8sp+xEBVJNKHExMWi1WoRCIcODvQSrIScri4zUJAoObKOxuoSe5hPMSArl5htvnPYm5ZuMQ0CAmr7uNk6UlSKWKrEPD1Jfto9rli0gMcGfQezz+fjba2/jEes4XnwUq8PPtW1vb0Eu8pCelv6V/fh8Pp55/gU6HRqiUxeiD0vGUtfCW689T23HCENjWiz1nWzftoHMtJRzNni/yRj8o0IgEKAJULBn13ZU2mBEYgkdzRbGhuq5ZdWqKd51lUJKfv5+9MYohCIRDvswDWW7uPu2G6dtuH8ZYaEmtm5ag0imQSyR0tZURU99AUsXzycoyPC1NtoAr7/zPpFpSxBL/BsuoVCILjiC0qO7WTh/gmArkUhINptZsmgB8+bMxmQyERoaTN7MPBKjTWSnxXPDdSv+6cpETgenfhMCgQClUgrwLPCNFKwvevq+pwgODuZHP/1P+vv78PkgMHAqH+ML7N+9nar8jcxPDEMoFLDn/ecIy1rM8quuGz/H7Xaz9q0XuGtuIr2drWhDzQhFIt7enc8jN60gMjiIscqy8dDtqfB6vdSUHOLhSyb0/mQSCZelRXFozzZW3XHmUlcBAWrufeKX7Nq6nrWbjjDqduINMdPicvL6oToQiHBIg/jhoz+nraX5PIzcBIaHrZTv38L9s+PRqvxhqDmJYfTaXVSVHGHkprtQKpUkJCSyxSmmvKGVEI0MoVCAzeHC7hUSo9EQbxrl6ed+T6zMQWJ6KiODHVS0t5CUlkWMzMGgx8WSDH8GmjkqjCNVDRzYt5slly5HqdYxaBtBd4pe1ojThUR15jC90+mk4MgBWustGEIimLNgydee1M8F1sF+tLGTw0cCgQCpyP/+XKid9nSqrwwMDdNZWkhDbTlaQxQelw2ZVECI5psbpk6nk+dfeYu47KtQKAMYtHuxWm2UV1aRnZnJmNdDZ30Rdz56D+APy//sqSdPI0F0YXDLTavIqanmcMExpAoxtzx42yQun9PpZHBomNZBG6aEBQjFEnzeMSTqUNZu3MItN99CTU01m7btZMg6TEaqmeXLlk0y3BobG+h3SDAnT3gUlfow+l1KcmMy0OqDAbBZY3jz3Q/42VNPXrgB+AdG3qw8ggID2bJjNx0NVhYvzCU3+4nTfmuz82YjEAjZtG0TztEx9Bolj95/26RM33NFQnwCP3v8QXbs2k1F8SEaGpuINufy0aYjuD/+nIfuvYPY2HMXIR9xuJDKJvPGpTIFtpHpSUYJBIJzlii7iOnhotH3PcdX7XBstmFK9m3igSUzxhebaJOBt/buoW/2gvGki6qqClKC5QQo5PR4x/wZUXIpycEB1LR0khITjkQkxOOZWr7Y4/EgE05dzPRqFdbu/q98Bq1Wh8vpJDFYRV5SIr0DNraXNqCPSyfRnEJu3lw0Gi0GQzDv7F1PekzEeHjX5nDSYvdyw9eYADo6OghXi5FLJ3P44oPVlFYNsfbjd+luqgafF11oDId7B2ho6CY5RItYEUBSSgYCBFTW1BOrlxKmkBKgkBGgkKGSu2iur2HMOUKgbnJ4JSchircLDzJ3wWK8IilPv/sZK7JjMBhDMIZGsq6gimV3nT5T2W638+qzvyMrWMyikCA6ukt59c97uP2Rn533agwOh4PGxgaUSiVRUdGYM3MpO7GT+akToaXhEQc+meaCGHz5Bw+wefse3B5QysXctPJq0k7jhdq9Zw9FJcX4FBHEZV8FvjH0eh2DXY10dhz4xvdRcrwYlSEBxUn+7OxFV3Jw9waqq5sQjbQg8Y5w68qrJmV2w/Q4eN8GBAIBSUnmcZmZL+BwOKiqqsDn81FTXUVI1k3IVRORglGXg2HHGPvz8/l8+yHi0hcSGauhqrWW4r88yy//z1PjnL3Ork7k6uBJ7Xf19BEYlsjwUN+40RegCaRp0I7b7f7eCYF/XxEfn8CjJ3Udv0qvMG/WLPJmTU9Y+Wxoa2uluPgYpRU1uEY9REWEMGx3csn1jyOV+X9z2/AAv/nt77n68uUkmxNIT8uY9jseHRnKQG/HJK5rf08bcdFf30C9iPODi0bfPzgaGuoxB08mAwsEAtJD1dTUVBEU5A/Xut1upCc/WL3BRE9jFQEKGVKxgFHPGEP2EUYE8tNqe0mlUnxyNTaHk4BTNLlONLaTmPbVdWmrqy0Ie2q5Li8VuUJCqE5HYriJNw7WsHjpk+MTiU6nZ86Vt/Dqpo9JDwnANeajtH2YSHMGb7zwR4JCIlhwyeWT1NmHh60czt9LX3c7UfFmcmfNHTdQgoIMDCNnwO5EdUrt1PZBBw3tnazwdXH9kjQEAgH1Hd3sGvSSd/VtDDtamZMSi0AgoHdomC3FNfzXvdfz7qad2JyjBMilqOQynL19HGvu477syZPwqNuDRCrlnVf+SqbKSfbyReQfK2WwvIVO5zEeeOo/kcoVFBcfIyEhcZIXb+/OzcwPl49zIIO0akx6DRtXv8d9P/rJV471dHHk4D4Ob1tDosGfNLTeI+Xmex9l9dEDeMpqSY4Ips9qY39dL9f+4PHz1u+ZcPjIYdbvKsI88zpEIjHuUSdvfLieR+9TEBs7YYR2dXWxcedhohJzGBhVIBAKEUsU9HR3IRcL0eiMOJ3Ob5RgYLXakMgnPLESqZzFy1dRdGADy+aYueyyRv9NywAAIABJREFUK76XiS2norz8BG+8/xkqQ5z/Pe7rRWsbQBMUhlAoxj3qYMw1jNs9xrrNO0idt2qcVxYWlUTzqJMDBw9y6dKlAISGhOK0FgEZ432IhELsA+1odJN5vb6Tm8qL+P7B5XLxwt9fwVLfTmu3lZC4HIzBQVS0tNE+KCQd/zpisw6wd9tqBPJYTrT5KGssZOuO3fz4sUenZczfcO0K/vTXv+EcyUIfHEZ/TxuDLSXc/ePvF4/5XxEXOX0XEN8Gb8VmG6alsojE0MkCvpaOXgyJOZhMfi+UWq1h6/YtZEUZUSjkWEccdPb0sqOilaBgI7tqell172Nn5AwGh0Xx6fpNqCV+GYmiulYqbRKuXXUHIpHorPd4YM9W0rU+dAFKxBIRHo8XsUhEc1cfIYmZkyoIhEdEkpG3kBFFMMNiHYf27STc3UG8yovOa2Xzjh2Exaeg1ero7Ozgned+S5LUSqpeTG9DBZt37yUjZw4SiQSlUklNQxMdTXVoJCAVi7C09fHKvkpSosO5Ki9tfALTq1X09nZjnnclvR4RWw4do7ihkyaXDIU2CM9wL85RD2uPViEVChiwO1ld1Ig+aSZ6qY/wkzxEn8/HtpJqgpNn4W6r5JLMBIx6LTPTkliQnYHV5WFLQQ1VrXYqGvvZvn0bAp+b+Dh/CGXLmg+4PD1qkhGvkss4VF7H7CXnRw+ts7ODPZ+8yn2LM4kLMWAONxCmErJ+32F++MTPGRKpONHaz1hQLFff/ANCQ8POS79fxqnfwytvvkvcjMvGSeoikRiVzkR12WHyZk2IwO7dv59hDNisQ2iN8XhGR3DY+hkbtZGRkoRruIuFc3KQSr++Z1Iul7Fv/36Cw/0lz2w2GyWlZVhK9+N0izh27CipyeZp1a6eDs73vOB0Onn6xVdJmbOSIFMkekMYLQ0WbMPDyJVqnPYBBD436gAVQy3FaPQmHD4l/f0DSCUSZDIZYomM/o5qZuX69Qe1Wh0njhfSM2BDrTPg9Xrpaqmku7mCrDnLx9/XrtY6ogwScnOyL/gYuFwumpoacLvd30pVkguBb5vb+Olna+gZ1dHS0kpi3ko0gSFYh+34Ru24fGIkUjl6vZ5DezZgiJuLUmMgLNREeLSZ3gEbXkcvcXFfHe5VKpXk5WZh62uit7WKpEgtP7jjlmnxsv8V+Z2nw0VO30WcFnFxCWwYEdI1MIRJf1KcddhOVZ97PNPXZhum8MhBfEo9//PpTq7JTkQgkLG/Q0jknGsIypnFj2bknNU7Ehsbz11P/geH83dT0dtNXNblPDhz9rR2fQplAMUlTaw9bMHt85ETHczCjARGRt2nVfNXqVSEhUXw5z//meszE4kJNTLY1cRIXzVJEimvP/97/r/fv8DGT99lVW4sBq2fgxis06CoayF/z/ZxPuPt9z7Cps8NvLNvK4N9jfQMWkmMiyFO5aGpsgSpWo/BGEp7ayMjHe2sfv91Hn7y51x93U34fD6s1iH+8t8/p3eomyUJYUQpI9hT00lgkJFZ19zFDTffwYdvv4xlfxkmjZzmgRFis+ZjDAlF3jLV8HAPdqMIvpTETH85K58vh2371pOabCY8PAKVRovV7iBAIcPtcSOXyRnzevGKpn6qg4MDHD5yFPuIg+wZ6cTGxk+LT3bsSD4LEkMneWNCArVIKlqw2YaZNWsuqamZ1NfX0tPTg0aj/UaeG5fLRUFhAc2t7cTFRJGbkzvlvXG5x8ZJ319ApdbTWDMw6ZhAAAJ8RMUmUWGpITplAa5RF11t9dRUWxBbu1GdhS85HYSHR5BljuB44TaCI1IpPn6cEWsXc5asICBAy0BvB3965q/89r9/g0Ag8Jcoq7bQ3dNNdFT0eeMiNTY2sGHzNnr6BoiJCmf2zFx27NlLe1c/YpGASxfOY8mSxVN+8+rqKpSBMZPGMyE1h4rycqztJzCEm3HbBmmuriQuNgJLdQ0Z4QtBAOWWeiJCDIi8I6SEGsevFwgEPPrwg2zbvoOjResRCGB5Xg7LZ8exfc+nKHShuEeshATJuePOM3N8v4zOzg62bt9J/9AAkWHhLF926dequrD/QD7rtuxGoQ3F7bShV8KPHrz/G8vm/LPheLmFpNk3UHzs8Pj7odYasLqGcA7WMDDoD8dah62EqAMZ6GpAq/F72sPj0jhatJ1ll04vAU2j0XLdihXfzoNcxNfGRU/fBcS3sYMRCAQkpmaxdnc+FfUtlLf2UNo7yi33P4FGo6GtrZV3nv8dsYI+ZoQEIBYK2NcwQHTeZVxzyz3MW7CE8IjIaYWrFAolieZUMrJnYQoJpbraQk9PNzqd7qzeviPHillzsI749CUERaRS3mZjz5FDBMWambvgktNe88lna+hsbuWyzFgGWquI0UkJD9IRKIVD5dWg1NNRe4KFyVGTrgvWqtlRVEne/CUIBAJEIhHJqRksvfJ6hoZt3JQTzZJMM8WWei5Ni6Srq5uerjbiDRqqu4bIjgtj+65dxKZmExAQwDuvvUCW2kmkQc+IYwSjRond4aB+NIDHn/oldXW1WBrb6RsVExibyvW330d6Zg5CoZDCg/tIjzLiw0dHZyflFVVsLWnEqU8j2GhEKDxZ51Isx97XTGpKMjKVhvfeeR3pSDe7jhSxaf9hNh4+jjEhk5mz540v8BWVFTz70lsM+oIYdivIP3iYjtZ6MjPSv9LwqzxRglFgQxcwOcOysq2XxOz5FBQW8ve3PqK200VJeS17dm0jIzX5a0mQDA0N8r9//itN/QI8UiMV1U3s37OVWbnZ6HQB499DcUkJAoUBiXRiE9DT0URciIKM9Alen06rY9u2LcSlzaW7xUJDbTnDdgdDPY3Y+5vQB4XQ1d5I1ozMKfcyXbS2tlBTW4dtqJe2mkJGRuzkzrmE8pLD9FodODxiamoq8Yz0k5SYxB/+8ixF1V20DcDBIwVUVx4nJzvrG2XvVtdU8+IbH6GPySMkLofuQTcvvPA0kSmLiU2bjy4kkaKS4zisXSQlJk66tru7i4r6TvTBE1njQcFh1JQdJCzUiEICUp+dMIMcn1hNaEw6PZ0t6I3RKAL0NNdX4B20cM8dt07aCIpEIpISE7lk0QIWL5xPe0cHu/Ydwu324nP2s3DODNyeMXbvy8c6NEh4WNhZN4UNDfU88/e3kBjSMMVl09hhZfvmNczKmXFO4fnW1hbe+ngTaXNXEmSKxhCWgMsr53jhHhLj46irq8Pn8/1DeP++bS/Xjt37CI5Mpa6yGF1IIgKhEB8w5raj18hprz6MTK6ivroMmVJHUkIsqpPzhHPEhmi0lzl5p+cUOp1OiouLqKmtOaM24HRw0dPnx7fl6bto9F1AfPEjejwetm9ex8aP3uDI3q00NTcRHZf4tcnySqWSWXMXE5+Zhzl3AYuWXTU+wb33yrPclBVBTIgBrUpJYrgRPE5UEckkJJq/ouXJcLlc7Niyng9fe473X36agbrjSAab2bx1CzpTBMHBxinX2O12PlyzmdS519Ha2YNj1INLqKR10MkNK1ecMXS4buNWvAIpwWM9RKhArVQgEAhwupy0j0DfwCAen4Dc6GCEQr+R0z/QR0nxMfYfr6K6spQxxERGx4x7Y3Z+/h7LZ8Qjl0po77dS19KBxDuKSS2jonOYXreYK+bkEKqWcbCigZqmVras+YS5yXGMIaHXamODZZBucQTtdgnrN23kyHELIUkLUBkSqK5vpqnmBLk5OQQEqCmvraO3vQmf005r5wA1/W6OdowSlb2ClsZ6ggL1iMViRmxD6GRuUlNSOLBnOwJbF+sPHicrTMOsGAPxwWpkIiHlTR2kZWbj9Xr5y/N/JynvWnRBJlRqHYaweCoqyoiPNHxlmT6ZIoCD+3eTFmkcNxCH7CMc63CQnJHNmx9tIG3eSgKNEQSaopGqTezftY7FC85euu90+OCjj/FqkwiPSUahUqMzhOHwCOnvqGHWzKzxSS0izMSWjWsQK3TIZEq62xvobyrk3rtuRy6fyAJUqVSo5SL27dqIOjCU5voqbD01pKdnMCN3EQFaA3V11WSmxNHd3cnLr7zK+k2bqKgoZ/uuvezau5+eni6io6JOq993rKiIV99di8SQgj4shZ7+Yfp7uxga6MOYuIDgcDNqfQgqfQStjRbqqksRBaYRlZiFWCzBi4j2rj4UolFiTgqKu91uKisraGlpRqPRTAk9Dw318dpb77Nu41YslipCQ4x88MkaItOXoTpZaaN/aBifIgR7fysR0Yl+iRpjFIWHdnLJovm0tDTzxjvvsWHrThoam2hprCQ0JnOcp+f1jsFIO3ffdDUmvZxL5ucQGx1Jp01GYtos3CP91J/YT19bJba+Ru5eddVZK23sP5DP5n2lJGRdTmhsBvZRAZ98tgZDXB6GqExqmrrYv2szc/JmnnFD+fLrbxKWshSNzoBUKkGu1OITKuluqSIyIpz29lakUtlX6ixu2LwFNPGo1BMeQoVKzbYNH1FW1UhtxwgHDh2lsvw4OVkzJm1Q+/v7+PSzz/ls3UaOl5bi9bgQiUTTFp8/3zgXg8fj8VBbW0Nvby86nW5am4zOjjba++zoA4OpqzyGOigC+3A/OqWIsaEGfvnUIwRrBAh9DmRKLeFRfi+fz+ejpmQ3K5YvpLaulq07d9HZ0YHJGIxcLqexsYE/PPM3Gvugtd/Nrt07cdgGCA0xIRaLzylScNHo8+Oi0Xf+8J0bfR+/+yra/mquzYlnVqwJqaOP1Vt2MXPuom8URpPL5ZPKq7ndbgp3rWNe0uRSTHqVgoNVjWTPmn45N5/Px+sv/plwVwsJEiu3zIzD6xqh2+rktkXZfLJxK9lzl0yZ4Ftbmylv6CU8OhljaDjaYCM6QyhafRAKgX2Kl+ILNDTUYxcFU35sD3NigpBJxHjGPOw40UhmejqjPghNmUVLfRUxxkCGbcO0VJdzorWfGy5dwLK0GIoKDjGMlMioGACO7N3KzFh/BmxiZBg2r5A3tx2ledBJTEIyV8zNQSQUolEp2HCklLreMURAVmQQoy4Xa4saERlziIhNRaCJAFUU/b1dxCWmogzQEGiMpL62hvjIYPR6Pekzcmkf8fGn1z+kqMNBl0uM3e1DY4xHrg7EYRtCr9PRcGI/q65dTkCAmi2fvMmc+DBC5XBJRhwhQYEEalQoZFIsLV0kzpjN4OAAx8qbCI740tgJJTgGWklNSTnrb6nX62kfGOZAwTFwO6np6GOnpYeb7nuMgmNFOCWhqLWB49IpUpmC9uY6stOTzpnH9snaDUQlTy58G6AJxFJ6kKuvvHR8UtPpdGRlpNDRcILOxlISwzVn5ABFRkYyf85MHAMtDI8KWbbiB9RWHqepsYG+QTvNTbUc3LuN1ZvzsctiaWrtpqSyAaEugdScS2jvsbFv5wbmzp5cG9fr9fLcS6+SPPs6VGotEqmMQGMktbU1WAd7iU71G72jLidDva1ExSRQeHg32QtWUJC/mYryUmxOAQMD/Rzav53rVlxNR0c7v3/6eapa7VQ29vHeu69z4kQpUokYk9FEd3cXf3j2FWTGTELjZzLiVbBl41qGhqxEmSc8Ku0dncg1IXQ3Hic6IQ2v14vT4aCk8AD5+btZvXEnUWmXogyKpuBYEdUWC2VHt+J22nE5rHTWHeG+O28ma0YW5qQkQkJCGRoa4kR1E4HGSAymCBJTs0lKzUbsc3LJ/Nyzbh5efuNdEnIuRyQW4/P5OLR3I/G51+L1uDGZTGj1RoZHRvGdhQO2fssuwuL9SSBisZ/rK1ep2fDZW5RamjhR183OXbuwDvaRkmw+oxFWWFSMWxKIXDHhyau3lNDVZ2fepTdiCInCEJ5I94CNvvba8e9jcHCA//3L8/i0SSj1Uew/cIA9h8soq6rj8KF8khPjLohU0qmYrsFTV1/LH599kfKGAcqqW9i2dRPRkaFfWSIzIT6ew/u34Bz1gG8MS+FGHL3VJIapuP/uW4mJiSUqMoo5ebNpqimhsqwQa38nHXWFLJmdzt78w9R3+5AGxtHSbWPblnWkmuN55Y13icm+iuDQaLT6YIbtTlav/piKmib27NvHiN2KzWZl49bt1DfUExwUdEZP4EWjz4+LnL5/EgwODmBttrBy0UQWXFyoEXOvlbLS42Tn5J63vkQiEe6xqbpnNocT1TlOZvX1tejdA8QFGxl0diGTiJhvDuf9Q9XYHE4yQgOoqqogKytn0nWBgUG47H5elkAgQKFQ4nS6sVt7Mc04s3Fy1eXL+eNf/47TmMXzuw8TqlUwbLczNzudWSkJFO85wa3X3sD2zSJe3n2QwfZ6RGNuLpmdQ2KE37C7MjeZ1/dsZe7JUK8pJpnati4Swk0IBAJykuL4LDCQ265aRERoGIVV9ZRW12J3uKizy0letByJTMPOwt3MSQjDKw8iKMhIS0cPHlUQEoUOQ1QmjXXlpGX5DQJ1cDTVNTXExsYhFApJz8xGIBBxZUYUUcF6Wrp7WL3zGeSJy5CIhDg6irls0SwiIiL9GdYi6OkfJCpIhUzi/zwlYjHukVEidCp6enoICgrC456qdzXqchCgmp5RdtW1q+ies4hqSwVBqgAeTc9EKpVytPAYPR3tFB/dh3vMi1DgwxQSRk9bLfn5+Sz7kn7bV0EiFjHm8SA6xbhyj7qQSqeG/YxGI3fdcdu02lWpVMyalcexqk5KCnYj1ccQGuqXvZBpTFiObSUubQEhUUl0tVhIXXgn1p4GmppbSEpMpNExTEFhAQvmLxhvc2BgAJFMN+leFQo5cUnpHNz+EQ77MM01JXQ0VSCRSqkrc2DvraemvIBhl5DEXH+t1LGxMTqq5Xz2+eccL6ukzyGht7GEzrYGTHE5WPoCcO6tYOuOPWg1AUSnL0Gm9Bu3Wn0wpviZbPzwedAfQ68PJCI8DK1GTU1DE7YRJ0XHK3C7RxkaHGDE5WZEEIohaTYlpeU0WgqITFtKZsKlDLRX0d5hYX5WDDc99ospkYSUlFTGPluHzTpAgMbf/1B/N1KfdVLG9Ong9vjGvYge9yg+gQSFSoO9v2Xi9wyPo7yq8IwcMNlpKkwcO7AVeVASaXP8nFyfz0fh8b1EFBxldt7UUpIAs2fm8M7aPegCJ6STLBVFhMfOQCKVgs8vOdPZP8q+rWupb2zmlhuv4+ixIoKicwkMDmPzZ28Sn3stYokce38L4eZ4nvv76/z///Hv37tMbbfbzctvvE/CzBXjWnijLievvPUBq1Zczq59BxlxuDAnxLLi6ismKTIolUp+8dOnqK+vpbe3l/DwyZqOXV1dbNq6jaaWdqIjw3jo7lVIpVKMRhM7d+9CoI0nJi4NALU2CG2gkVfeeBuvRDNe1aOjpQ6LpYr0JfeiU0JUZCSvv/sXQqOSSMueT+OgjSN/fYV7b7vutJJMF/Ht4mJe/QVGf38fIZqpfJUwnYrerrbz2pdQKCQqJZuS+omJ2DM2xs7yJmYvuuyc2upob0PscfDu5j2sO1rJi5uPsON4PRF6Jd0DVoQwXiD+VOh0euIjgmiuLcV30rXa39OOb7iVGTPOXMLNZDLx1KP3k5YQTr9XRmyYkSduv44F2ZmsPVJOzuIrkEgkXHXtKn70q98jC4ln6ZyZDNrsVDa24fV6kYhFCMcmdozX3nQn+9pHWVdQyZHKet7LLyMqaxF7a3v5YNs+BjsauD49hAWxeqJUPhrrLMi0YXQIQvjwSDU9NjfVnQMoA9TgGWXM40IskeJxT/ThtA9gOGW3fWDPdq40B5IZG06gRs2MhDgeXbEY0UAleUkB/PqnP2L5Zf7fQiKRIFTpUSrkNPXZx9vos9rRBQbTOuggODgYvT4Qg0ZCf/fE++IeddHXXMqc2dMvR200GlmwcAk5OTPHQ2hGQyClx48SmXkVSXnXozRmUl5Zg8unprTFxX//719ob5/+e7pk/hwaKo+M/+3z+agvP8hllyw863Verxe3233WcyIiIgmQuGiuryYwxG+kuJwOnPYhwpMX0d9Vj8sxjEylRyyWIJYp6R/wb0D0wRHUNTRNak+pVOJ22ab0ExyoJTHaSFd9Ab2d9aTOv4m0hbcTkbYUTUgy29e/Q2jcRLaqbbCH1BmzOXS0mLKqWsS6OCRqE4lzbiE4dhY+kRJlYBTKkEyOFBahDZygRQz0dnL0wC70Eel0tVQzaPdQUlqOVCygPP8T1EFR6IxReAQyhnqbcbud2IetBBojaWutIzh+DjpjDDKZEqlCizI0h1ff+YQ/PvMc5eUnJj2XWCzmyUceZKjxIJVHNlBxeB2urmIef/iHU7xqNpuNpqZG7Hb/e6kJkONyjgAgEkvwelyM2KzotRObyeHBPkzGyaoCp+KKZYupKdnD2Elt0FGXk+oTR5g1b9n4OQKBgLiUOezad2b9xZSUVFKidFQWbKG9uZpGSxFDXQ2YzX5PeGt7G5b6NsYkOsRKA/LQmTz3yjscLyvHEBJNV1s9ysAopHIVQpEIz5gPhVKNRB1OTU31Gfv9rlBdbUGmi5wkfiyVyemzenjz020Yki4hftZKOpw6/vjMC4yMjEy6XiAQEB+fyOzZc4mIiGRsbIySkmL+/sor/Ow//y993hBic69jUBDO3954H7FYjEwmo/h4BWFRkylBKrWO/qERvGMT+q5V5ceITJnv51QLRbQ3V6MJS0esiUKjM2AMiyFl9gre//Tz8TXhIi4cvl9bmH8BGI0htAw6pnjfGnqHScw+++7662DFjbex+oM3KN5bil4hpdPuZsEVNxN9km80XcgVSg6VlPFvV2ThtA4gEQkpae5jd3kHj6Tnsq+uhweTT88Buu8Hd7N23XoKD69GKhUTZjRw7xOPIJFIaG1tYfuuPQwNDZOVmcq8ufPGDZCwsHB+/MRj2O77Abu2bmB1xQmk8hHmXH4HM07xKDqdDrraW2lxeTGHBdJQ08mBkhNcu2gOMs2EAaZSqXjkqV/T0FBPV1cnsQ4ner2Ovt5e9r7/V2ZkRdLjEpCUnk18uohHX9uFQh1E2oz5+LyzWb/1c0xyvwFa3TGASCygobKARUv9UipDAz14rM1kZvq9VT6fj+NH9rMsMpjW+nKCw2KRKwJQS4Uo3P3cd8/9U7xm19x8D5+++jT9rQPoFWJCdUqGPBJ6u4YxxGeM79offuDe/8feWwdWlp1Xvr/LzChdMVOVSlKpGJvB3W6w2xjbsR1wxoHJeCaJZyaT5E2eJ8kktgOOHWPHbjdTdReDikFSSSVmuldwmRnfH+pUu9zGTJ4zk+n159U5+95ztM8+3/6+tdbHV7/xbaaWbyGSyCmkgnzqI0/8REuEQqGA1+tBpVL9WIXkwPAY2/c9TDC4Rq4AeYRUtR8iON+HvbKRvL2a7zzzPJ//j7/706YMAIcOHSQQCnHjykvIVEayiSAHd3fTu/1Hk8ELhQKvHXmDGzdHKQnF6FRSPvLUE7e7AgQCAW4M9FPIF+jp7uI3P/Nr9P/KZwl5lgABKoWU6qoKltaCFPI5pHIVmWSYUqlEIZ+nUEoRjwYJBzbo6LiTT6pQKKgqM3Lj0kkM9josZjNyqYSg6xZ/8of/lQ9+4tPU7vgghVyGSMyPTqvDcdeHOfndPyTiX0Mq15DPJjHq1dgsVmaTScRKC0ZbDUuT19GWdRByz5OI+AiblHRs7SKdyZGIhRFJNufByOBFHC0HEJbSmLVSJkevE49G8E5F6Nm+A7lGwdLN1/EHIzRsPUAi7CYbW2Nx6ibpZByZ2kIqnUIogFw+j85Ujkxjw1C7l28/f5RPflBIW9vmc5pIJIhEwvzKL38MuVyGQCD4kd14nn/xRYYnF5GpTGTifnq3tfD+xx/hH/7xJara9qHVWzDodTgn+mh7ZHPup1Nx3Av9fPy3f7QJOcCe3XsoFIucOPM6QpEIiUhIQ101mh9q6yiWSMhkfvwGQCAQ8LGPfgSXy8nk1BQ6nYXe5k8xMLOAQt7B6PgUOlsj0ZAbidLI9PwKjsou3NN9hAJu8rkcIslmFrRULCIUAgIQimVkMj9bB4lfJIrFAgLBncK5QiHP+sYa9zzyidvBoLW8hqBvlS/99V/T2tpKb0/3HVk9gGw2yxf/5u+Il3QszM+jKtvJ0qoPtc6C3mQnYm3mq1//Jp//vf+EXqchlYyi1hp/4LcUUSpkqKUFomE/Wr2ZTCqJRKog7nNhqWllbHAMY1kjufTbGyqxREpJpCIUCv5f2WLtXxPvBn2/YKjVamo6d3Pi5iCHttQjEYu4tbDKelHFIy0/mYv1z4FEIuGDH/tV4vE4iUQck8n8M5cr4vE4l8+fZnlmnNX1NXbUl3F12sncmg+1BHyxFIvuBK8OL3LP+z7xI/lexWKRiYlRSAU5uL2Nhx59mFJJRqlU4u/+/u85cvoatvpe1Bota1dmudZ/k8/9zm/dofpTqzU8+uSPL/sdf/0FPnFoKxm/C4NSgqnaDIsb/NXrF/j3f/RXdxwrEAjIpFNcO/4iW8rUBICTtxY52FZPR9edpelHtlg4MnKKtNGMRiakSZej4B1kRZbFF8tj0Iip1BdwTV5gNpWi2mHjdz+7GcyWSiW+9fTTTK942VfZgtakxO1aQKOSY7aY2da97UeWSSsrq/j05/6YKxfOceHSWYq+NGarkc5dh3ng4F133JPP/c5vEQwGSKfT2O1lP5EPOnxrmOdefgOx0kQ+m6TCouHTv/zxOzigAKFwlMaew2SzWYZHRslRopArEIrEOPXm81RW1SDKpclkMj+T8EggEPC+Jx7n4QcfIBIJYzAYf+J5L778CjMbOdr2vn9TuJOK85VvPsPn/8O/Y35hkedeO4m5cgtCkYhL//B9Du3awuH9OylqytGZrAiFQlKpFMM3+pCr9QhFEkzWKuaHjxP1u3BU1tF32knCN8svvefP7vjukdERFl0+krEMqytz5LJp9IoiX/jj/0pNTS0WswV7WRXFYgGF2YRAKCKZTCKTKxGk1nFpEJkeAAAgAElEQVRUdpGKpVAqhHjWFrCbtMy7Fhg8+302VsaJhAI4mvciVZuZHLlGOrJBJpPmhW//JZbyOrp33kUsGkFuStDSWINer6eipplSqUT/yW9gcTRQ19JNJ3Bz6BYqUxXZVIyEL4VvYwCRRE0mGUSmUBP0rqAz2CgWcpQKGZRqHY1d93Dk2Ena2to4fvIk5y4PotCVkU2GKTPJ+bVPvdNqpe/8eaZWU7Tvfvz2Z7dGL1Fm8/K7n/k4x06eYW20n/v2tIEABm8eoYgQnVrOb3zqw1gslneM+YPYv3cf+/fuw2xW4/fH+eZ3nsa/sYK57G3bm9WlSXq7f7oau7KyisrKTTV/Pp9nfuEfuHDi+8RTMrLpOJmYj47d76FYgkDEi9FoZGP2Ko6WfUSHb2CtaCMaclNTUU6xWCTuX6Sh4b0/5Vt/schms9waneDahaN4ogIMei31dbWk03GEAiEG49sB2eLMCNPT01jLa5AEZFz7xnMc3NnBww8+ePuYCxcvkpGU0dC0jenpKUz2Wgr5HKO3BgmszyJVW0lG4/yX/+fP2L+zk4uDV2jb8SAi0SaXc2lqgP27t7Nrxw7+9qvfwCPSICxlWZ68Qvf23SgUcuQKFeGIH6P+zo1mIZe6Q6T1Ln4xeFfI8QvEPxEzG5vbSEg1nBkcY8gZRN/Uy2NP/dL/r22LpFIparX6ZxaKxONxvvHlP6VFEuZwczlz05MU0gniqRSPbaumpdxEd52D9ViGXY99kl27971jjGKxyNNf+zLZhQG2mcVI425ee/MoGksl1/r7+d7LJ9l2z6cxWKuQKvTEEikEQjEaaY7KH9qR/iScee1Z7u+sB6GIpZUVsukkSqmYa0t+Hn7iI3cEo5lMhu9/9S/41MF26uwWqqxGqoxqLg7cpLej5Y77s+CP8YFP/gbLU/3sqpByqKOOWquKqbkJGhpqqCw34VxeJOeeYbtDgbSUZt3ro6W9k/n5Ofr6Z6lo24dzbpgttVXojVay6RjurJhtdz+KrezOa0yn05w5e5Yjx06SyRV44v0f4okPfZyd+++murbuRxLZFQolGo2WVCrFxsY6YrHkHWpHj8fNV59+kdadj2FxNGCpaCacLDJ56wq9PXdySJ0rywTiJbQ6I6urq+QESqQKDcVMjNadj7LunCcVcnLXwf2MjY3g9XowGk0/dSMhkUhQqzV3HPfDhG2/38/3XniNlp77SCdjrK3Mks2kUWhtRLyLnOq7Qtvux9EZLKi1RiyOJvqvXeBDTzzCtUsniERjpFIpfK4JzIokqaiXdecCyaiX9bl+mnvuw2yvoayihm29B7l09g0OHdiHUCikUCjwpb//Oq27Hqe+pYuWjh5at+ygWMixtbkak8nM6OgIwbQIk62KXL5AMBQhFg6Qia4Q9LgYv3WDrEDJ0sI01868wPLqOnJDHQpjFflsFkfbYbKpGGqdhbKaNm70vUz7jodo69pPOidkoO9lYoEVyh2VmMyW2xypZDyCrBgmGgliKm9CIBAgkYjZWF8nsDpOsQSNXfezOHKG0NoMEoUWhc5GvpBjZeQkXT07sTtqEUukrC+OUW4z8drpftp2vgejrQqLo5FwPM/yzBDbOjvv+L89/czz1HQcuuO50OhtvPnKd5mdXyIcidLe1sQjDz9M55at3HP4AD2d7TjsVrQa7c8shLi9NtbXcf70EULhKNlsDvfKBIqCnw9/4Kmfi1snFArZ0budi+dPszQ3RjadQiiWkooG0JsduFemuXt3O4+9534mbl0h7F1jafoGDocDuVjA8sQlHn/oMA1vtUf7X0EmkyEQ8CMWi3/sNQQCAfoH+vF53SiVmh+rWP7K176ON6ujumErC1MDJLMl5mdGyIXmkYqK1LT0IhAIyGbSXLt4koq2wzjK7JQ5qrA4mhi4doGera2318TnX3oVS20v45OTTI/dIJUpUBRImL11lpad70VnqUGj1dHetZ/BGxd48PAOBq+cxu9x4lm+RU9rJY++52Gy2Qzbu7voaKqiq70Rj2uGklC6afLtX2Pg7AvksilW5scRCgWk4mEqzRJ2vmX/kk6nuXL1ChcvXyOTjqHT/fQ15d863lXv/svhXz3oEwgElJdXsH33AXbsO0xdQ9P/dhO87/QxmsVhttRWIBIKyeQLDIxP8UR3NXa7HaVKhVQmQ6lUMrkRoXfvoXeMMToyTG5pkPu6mtEoFZh1GjprLDx39Aw3p50UZRZMjk2OiFAoBKGYUiFLMemlp+vH8/3+CWOjw7zyva8zdvMaVYoiId8G22rLsRr1aNVKVsMpZpeW6d1z6HbAND09hcw/Q0PZ2xkIg0bFqcEJlFIxjrc4SDMuN3NJKQ89+iQSuZIzZ88QcK+y4vYjNZYRzgpZCwux5z08tbcLRSFJZ6URUSbGuMuHc91HQVmJzVFLICvkys2brAYiXJhcprbnIE99+EN3BDzZbJY//+KX2UiqsNf1khFoOHP6FHq1BIfjzn6VhUKB5eUlYrEYGo2Wl159lWdeeoPR2XXO9vURCnhpa229fc3HT50ir6hCo3s7C6DWGpibHGLvzreNkiORMF6vmzPHX0EkVRGOZ0ml0rjnr9GwZT8yhRqBRMHG9GWmFlZxhoRMLro5feooDbWVGAzvLC0XCgXeeOM1vvP3X+Ty2aOEw2EcVTXIZDJUKhlTU7O89Oor/PVXvsrFG6MsrwcYHTzP0uIMOZEen8/L4vQg+VQYmb4ak/3tDJBAICCTLWBUFfjohz6IXlFEK81y74Fe3v/k+3j4/ntoqNAjLsQoKh00t3ajkZfIJAKIhELSuTyu+TGWVpzEoiEWVqNYHA0Ui0USiSSUQCxVkA6v0d7WSkd7Ky9+/xtkiyLiySzJqBfn2HFaO7rIlSTUdt5Hmd1KPCvAVNtLYGORpp3vIxZcR642obfXQ6lELpvE715BrjaTTOcIJ/LkMknymRhqo4NUQYpraYagz4XVXsn8rXMc3tvFwMAAVy6dY27qFoVsgnzUBSkPsUQKa0U97Z072VhfweeawL8yytrUecz2WqwVzVgtFpLxCJJCANfqGrrKbmQ/kGVR60xcPf8mE5NTvHnyHFeuXUerUjAxPYtUY+PGxWNMjPSzMH2LtbU1vF43u+7/JeLpEtduDHLm1Bsc2LeX1468yUtvnmN+PcXVgZuM3hqkq3PrT13f/mltlMlk7NuzG4OihEIQZ+/2Nh579JGfe0OcSqUIhUKcPneOosKBoWobtrrtIJIxdeN1MsEFfv9zv4PVamPPzh089ujD3Hd4H7JSjDKDhA888QgtzS2USiVGx0Z4+dUj3BweRimXYrFYyGQyzM/PkUwm0Wp1LCzM89xLr9J34RKZdIqKigqEQiHHTpzgW8+8yM3xZc6cO0c0EnyHEvlcXx/ffvY1vCkV86shjh07QoXd/A4LLI/Hw6lLQ9R37EFnMFPb0IqEDJnIOh9/6mHqa6oYGh5GZyrH73ERiKaQSaU01tcjFAnfsrzKoZakbhuIDwwNc+H6GNMj15CqTaSTcTzLt0Akp7qph1hgjYa6TXsjfyCCKBfks5/5dXb3bOHBe+9CqZDzmd/+XZ597QyvHT/H1auXePiBe3n4gfsR5sJsLI0yOz3O7vs+ikRlRayyMjt+HY3Az+989rOIxeJNFfVf/jWrUSklZRmT86v0nT5Kb/e2/6XOOv+n41317rv4hWJlbpKdHW+r4bqaavn+GyeJJ1Ik0xmKJVgNxqlraGJ43P8jx5gdH6K3ynbHZwqZFK0wT0mgJJ+9k2AslcrZWFlFkUzyZ3/5RcrsNu6/5y50Oj3Xrl9nbmEJR7mdA/v2MjM1wcSZF/jA9hYq6WTZtYJVKSKXNyGViDg/tcqebR0shlJ4vR5stk1Fr0Ag4IdjfYFAwP6eToYTSm71jQHgaOzg8EO7+MJf/E/Whs7yiYNbqa+rQalQMj47z5f7ZjHZa9heYyMUiSGQ6hmfnKWmykH/8HVadt1HNrxJeq9t20lVcw/pZJzYaB8PPPL4O7J2AwMDFOUV1NRtqtm0ejNtOx/i1TdfZXvPdoRCIaVSiampSZ5+7mWkajvFYh738jgGRytb9jx5e6yxsStYL17k0MHNvsjxeAKZ/J2E+lyuyKuvv45KpUIpl3HqYj+6sjbqu+5hcvgCizNjyLU2hFIVk4MnsFe1otdpKYjVtO954nb2J5Pu4OtPf5///oefvyMjlEwm+b3f/z2UsTXu7WpBJiiwPn6Gv+q/jKN9F4tLC2z44oTiWcqaNxWeerGfQklMcHUMW2UrQpGYDYmG0fE3UOmDlEQyctksyUQMa1kluWwKhVyBRCKhp2c7kUiYsfExrl67zq2JGeaWPQR8buTGWpaPPofaYKe8qoVF5wTOmRuEtm2nsaOSK0NXWFt1YqzaxvziMkKJklIxT8y3SP3BJrxeL06nkz/495/hTN9FTp47TkkowupoZm3dj0BhJhKNEQomEEk1aPQ21KZKcpkYIrGMwlvCH6VaSzEnplAoUMzn0Fmq0FmqGL/4LPb6HVj0SiorHThda7hmBynFvsUHnnyCF14/Revu99EqEHDzxnlGhq5h1or53G//JmcvXMVaX8Pw2BTWhj045Br8rjF8K2MI5QaSWVhanCHuHuc3P/0RXjlyDNUPBVHhgIflVR9dhz5MmUpDLpvhuTfOoKDAqSPP0Nj7KGUaI9lMhltXj6BTqek7/gISTTnm+n14V2f59d/+j1gdDXTvf7sk6nbO8eLLr/7MqmzYFJh0/zNdDAqFAs++8CKjU4sIpUpGJmYpa3sASiUi3kXEUhkaYxl7W5rRaLQUi0UGBge4NjCEXCrh8IF9NDe34PV6uXzlEpcuX8WXFFMSyohFw5y7+CUqbRoEUh1qUzX5bJLgxhxipYnmrrvQWxW80XeBYyeOU19bw9mBBWra9mIqs2MwGBgev4rpB57NYDDA0bPX2LJ3c02QyyVYyhv5zrMv8//+t+Y7guVgMIBc/Tb/TSpTUNvUiUQqI55Ict+996LVajjddwqP14swI6az417EkrfHyOfSqH6w8pGMMzV4koZd70dtqCAd8xP2LBIPupifuIHFbGJsYopUOkOpkMHv9jCz9Bd88iPvo76+gd/83O9T0/sBGi0VlEoQ9q/xH/7gj3j26a9z+NAhwpEIaXkN9op6akqQSCZpbazBOXr8diD/yutvYKjZgdm2Wfmwl1ewLFLy5rETfPCp9/+z5sG7+PF4N+h7Fz8SBrMdbyhElc1EKp1ibnKE9goT4+shwtkiYrma9m09+KIp7DU/ugSi0uqJxHzYjXdyOVKFIhqlhIJEj3tpFFvNFgQCAYGNJRZGz1P32CcxVzfhD/n4whe/CoUkxqoeTLYWRpxeLv75l9EXfHz2nk4kYhGHu7fw7decTK9uMOZJkBfKqKqspLupltXBmTtUoE1NzZx8IcXuTBa5bLOEksnlmA1k+Mzn//h2J4D5hXn+5uvfI5HMc9+WNkpSPaPjU2ztaEUqhAqNhHW/h1K5DdlbprByjYlEBtbXVvnlXTvo+6uvYLZXI5HKEInEpOIRKuy6O0QUoVCQsZEhTpw+i7Hh0B33SSQSg0RNOBzi4uUrnDp7gZnFFao7DpNzrZHJpFldXKVJ33mHMKimdQfnLx+9/WLp3raF779xBY3uMELRZlC2tLTA+NgthAoDxYKP0aGrHH7Pp6is2lx4lWorqxs+Og9+CK2pjGQ8inP8DKVYiYaOPXcEdzK5EqHCjMvlvEMg9Pobb5II+PjYPbtIJBJkCkKUMg2y1TlOXJBRVJYTDwYQCEQYrJtcrGDAg1xrQW2qweuaRSAWsTJ9BYtjB6VSnnOn3sRc0UpVwxam55YILl7jc5/+FgCXr17htWN9CORmJiZGMVVuxdTQjLwsxsyNI1R33o+hrIl0Ko7S1o4hkWZyfJi2ngN07n2U6a//d/qvX6a2Yz9CoZBcNoVr8iIvvjLJ9ZEFlIZKcukIgkwOk0GHtfU+TOWNTAyeQ6qxIpSpyKQTCCRCEIjJZVJk0hm01jqWbx1DY60lm8sgkYgRCiUEViepad9HqVhAIBQhkqqQSITYrFZsVivtzfWEly7ytW8+jbRsOwsuH1MDxzFVbqX14KcIbszxhb/9Pi0VKtbOP8dGSoPKXE8yvEEhE6eiaScbczcILV+jrbGOP/nDP8DhqGD3jm6OXR6jon4LM2MDuDecbLgW0dubmJxZQCwSUVlRRlPXPfS98iUM9lYK+TypZIxoyI9aayW4PkZtRwf22k2unVUoJiSV4g+u3zGHbZUNjF99adPL7/p1zl28QjabY2t7Mw/ef/8/u2vDj8ORN99kwVekfc8TDF8/g9xQjdZSvVnCz2dJRdy0tW3BbMpQKpX4h298k7WIEEfddvL5LN949hgKwQtkSgrEmjLGpgJ4XdNUte4mX5QRTstZGlqke/8TVFe0oNFouBCGQswNwNmjzyFVW/H7oe/q67TvehShwszc8jr2eBydqYIv/t3XOH3+KjqNknKbEUN5yx2bQLFEikxbzsrKEvX1b3txlpeXk4xsvOOak8E1amu2IhAI2L1rN7t37aZUKvFHf/o/yGYSyN5a01LJOOngEu3tHwA2hWbjk9Oo9HY0xgoyyQgiqYLyln3MXHmGkkhONFVAIBCgMdcxP/gqDz3yFHqDiW9//yV2dbchNdTd7vwiEIDB4sCrq+Hq1cscPnw3ztUN9OXboQRLy8t4/CHyRQETQ9O8/8O/xEc/9BSzCyu07rnTdcDmqGNi8LV/0bnxLjbxbnn3F4j/k0wnTVY7R44fpdluwLkwTaVWxlokzZgnQUeVHRFFFgIJrm9kePKjv/IOQQCAwWTl6InjtDtMiN9ywZ9e9RBVlHPf/Q8wMjpGPpvEOTvA2vwQrolzHH7PJ6hv7kQoEqFUaYmkBCzMzdDetQ+5QoXeZEOqtuAcPMoDvZt+UUKhgOaaCiT5JDPBLJ98/EEqLTqmpiZ55fIwK6urODe8SMRirFYbprJqnjt6gkg4xK2ZBV66Mc09T37itkIU4E++8GfEpbUkowHqlVnEQgEKpYZ4NIBGrWZ4cQOPwErUu4Q/6CcUiyMrZZGqjVyaXeOjH/8kFXYz50+/TtC3hsc5iU4c59O//HGkUikqlYzzZ89x4pm/p7LoQ5P1c3PgCgK1Ga1hMztaKpXwLo8wOTnGS8cukCypiCUyeFYXMFTvoLplN0HfKlJtBRQzmN4icQsEQnyuSe4+dICJiXGee/kIkxOjTE1NkkpnycQDnD3yHdLZLBtuH4vzk4jVNkoSFY4yOyKRiKnZeTTGcqKBFcQyDWKxFIQSfAvXad6yC73xztJT0L1Ib2czOt3bAe33nn0BDRnKVGJEEgViqZwCYgqpCBPeNPaOB0AgJhYNYrJVIZXJSSbiKJQq8tkEhaSfqHeJlp3vRSJTkAosY2s5jEShp5BJoNUZKHc40MkL6HU6vvb0C3TseYLlxSnMNdsRyvQEfGtojJUEN2ZRGSooFvIUiwXSMT+m8npScT8B9zINLduIhPxsuOZIRTaI+JyE1yaorW/CE87QtfdhTJZyLOW1INMzcOUk1VvuoVAUUESCd2UEraWOqH+ZdDxANp/FtzKKXGVEod4UfaxOnCUZ3iAZ8+FZGEAgFKK1NYBQhN85jlgqp6OthUI+z+raOgGfh5tXT6My12Gr3U7Q56Io0qCx1qNUaykVslQ2djN0/SwPHNrBlcvnASGFXIp8Pk8JyGaSxMN+HDY9Wq2O0fEJGupqcS6M88ZrLyHS16GzNRFL5kklwujNFagMZWxsbCARCVicusnBB96PUi5h7MZJ1hZHyebzBDzLqPU2TGW1AKTiQaRiESHfKs3t3beDGIFAgNc1QTIepW9wgcq2g5gq23G6I1zqO8q+3bsQCoU/09r4T5ZQP6lTxtPPvEjDtrspFgrcvNZHoSTEWt2JRARmswWZTE4x6cVhlHCmr48L10ewV7eg1hlRafQUEHLj5gj77v8QRYGEQKKEvWEXzukbNHQ/RDYVRW1pQGOwEvR7Meh1RJMFYiE3S7O3qNpyHxpLDUK5CaXOTsi7iMlehVpnZXlujIXpIcw12+necz8ilZ2LF84SDgdYWZhmamyAoG8Nrc5MLLTB9i1Nd6jx5XI5oYCHickptAYbpVKJ5dkhrOoc99177x33RSAQsKWtlSt9b7LmnCfkXiLhneYzn/oYxh8Qezzz/EukBSosVdtIJ8JoTBWIxFJy6Tie+WtI5BqSsRBe5yhKrY1QLEUun0csErOxNMFGBEpCOblMGqlMjlAoIhbyUWEU0dHRQTDoY2k1SDpXYt0fRSTXkSsKScW8WGp6mJ2fZ2VxmsYte253ShGLRaSSSTJhJwf2/uwNBP6t4d3y7rv4hcJuL+OhX/osz774XWZvjmDXKrCb9LxnRzsjC8sEowkmA2n23/OeH8vXMZvN3PPUp/nOK9/FKCkRz+SpaN3C9r17OHriDBTSpMM+Gsut7N9zD/1DFdS23Ekk9/mDRL0uogPPsBjPIi1ro7n3AQKJHNlcHulbpQuVUkVBoSeSizA6t8TKwgyrkQx6vYlABOavz3Oufw6vcxy9wYhAJOH1a7PUt/ZS03aY54+c5Xr/IFqDCbvFyNj0AjsfeYyYxsTI3KvcpRASCK8jFZUwW20sevxkyaIyZWjVqUmkPJwZcpM1ZjBVbVpitLW186f/rZWRkWFm5+YxmcwU3vKzisVi3Dj5Ep88uBWRSEhblR2ddJRXB45grWhEJJayPDNIVZmBo3032Xb3rxKPBclP30Qs14JISjKZxGCpoFjIsLbuoVTaNG4lF2NLYy0ej5tvP/c6Lb2P0LhTimd9ifGbF0muBUkmEzTsfAqRSEwi7CGVShAMhQmGgthsdopFEFCiraUFiVLNisuFUChAIBSzPHWVitoWhAIRgWAAt3sd/9I4ev1HicWi3OgfIBKNkclmCAVjiMTVCEUiioUipVKJaA7C8QTWXBqBUETUu4xvYwVV41YUcjm5ZIRC3MOeQ/dx4ewbJBMJwn4P/lCE1mYDMqmUXNxNT1cX6XSCgaHrCAClqY5QKITP60EnqyKdy4FQRjqToVgoIBAIEYllFIt58tk0EpkSkUiKUKYjEvKRSsZp27aX1o5tm3YvMgWvP/d3JHIyLl86j0ShQywUUFVZTh4Jbtccfs8K2WSUbCLCxLl/QGOuQWkoY236MkKxhFQyxOrZr1IqlbDV70ShNhL1LSCVKanvfhD33HVymQQR7zIanZmlhSnC0SRmRxNLk7eIZQWYhLAyP0osGkBra0UolhKLholHQwjFMiTaCp577QTJRARp3E8iGkRjqqRYLNHQ+xTuxX76xwdY8DzPtu6dDE25KMQ36N3/MAqtlVg8jrmshpKgkcG+72Mub6RUyONe0mAxagn51phfmKcg1tFx6CEymQwqYyWejVmKxVMYbDVoVQosFQ4Wbp2+I/jwu53UVNi4MjBK+54nb/+trKqRxXiQkZFbdHZuI5PJ3D7H43Hz0mtvsO7xo5RL2bOjm6GRcdz+CJSKdG9p5n1PPHEHz29tbZUjx04wMjGFyDKPyaBBpjaiNOtYn7mCtXoLQqGATCrK4sAJRPk95GUWitomLl26QDF9hJr6JiQSGbbabhKJBCKRiFJJgFShRSLTkM+mKRYLyNQ6MukUGrWadDpNsZClUCiQzRfJZpIIioJNhbdKjUBYj9c1S3XLDnzrC1Q27cBs2OwcolCqqWzq4czRF9j14K9iV+tJRjycPvocjeXaH2mr9f4nn6Bu6CbnLlwkXyhwqLeb/fv2/chA2Gw2859/73P4/f631Mzz/OOzL1IoFNi1fRuHDx3Gajbiml4nHnYjFEmgBPl8hmTEQ2XLbgTFLMvzN+m869Mo1AbiASd5gZqZyfPIS1HCgSwV7XeTy2VYdS5Q5qghtDbOnt2bdJMD+/Zz+fqX2EiqMVd343GvE3CNUtXUjdXRzMLga1jK6hi5foqefQ/fbpm5MH6ZJ+8/8BPfUe/in4d3M32/QPxrZPqKxSJLS4uEw2F0Ot3P1U/SaDTRtWMvZ46/zoM9W6hw1BD3r9Hl0NFgN6Az2djfbOfVs5fZvvvA7bHj8RjHjrzCN/7mzxm8dAaTzUHX4fdw32Mfpraxnr/426exNu6jqnkHZdUd+D0uHrh7P36/nzQqZPJNzkkg4Ce0Oo82u877d7Wyvb6cpG+FpUCCYilPJBKkxqJDJpGw6gty2RXnw//uP/Pq2fO0VNhQaozEte3UN3YiEYpwJ8RkJWYyRQkeb4DqLYdZdy4S9K2xurqKL6vBUtnB0PgCC7Pj2Go6kMnVTA+dIhPeoEwtIhAO8czlMXoO3E+TYJ06q56SUIxaraWxro6ZkICKynJ6urYhkUh45bXXOHnpFhlpOXOuAM987zt43WskExG0ESfj80ucuTbI0PQ8QqmMSNDN8fMXmL51GbtOhEQiIyWrQWcqQySWsDx1g7KGHWSSEeQKNWZ7FbMDbxKLhhEr9UQCblamrqFVSbje348nrSeeyiIRizHozVTWttJ36lWKEiPpeBjECkoCIRtz19Fa69Cq5JjNFtbXXficY2zrPczU7DwCuYFsJoXZbKKQyzAxeI6JyUkWF2bwOSewV7Vw8sRRzvRdIFw0MbmwxvjoTdz+ECIKlBk0CAUlVtecnJzx4U0W8SyNUEKMUCJjZeIiUEJYylGKLZONbaDSGhkZvIDCWIvVUc/6yhRKcyPRSAClFMrLy0jEwshKUfoH+hlb8OKNFnGvu4iEvIgkKkrFAvl0nHQiuGnfUtGGSCJDLFWwOnkRmUpHNh7EuTCOz71KOORHprWhlMs4d/x54nkFanM1kZCHWGADnaOddbePjfkBwp4lisUC1rodCIWg0Nspq2lHb7QhkKgAId6FfizV29Baa8kkAoQ2ZiAVQKlUkEpnEMm0JCJegsxta8gAACAASURBVOsz5FJBgpEk+WKRheFTGPQ6THV7WZodIeRzAUJEYilShYaY34VKb0NnKsezPIxYpqWy7SCFQhGVqYZkxEPVlvsIrI+TCK7RtPuD6GzNxGNhcukEi0tLbN1xDza7HX8giECsIBT0UchlaOx9LypTNatzAzx4aDve9UWGR8Zo3PFeSsUCybCHnGeEitI6LUIX8oybRCKCWCpDLYgSjfhJpjL41mYpRpd45MH7mVzyYrLX3l5bSsUS0VicC6df5dL1Yc6cv8b1GzewmHR85ZvfRVPRS1ldF+mShu8+8z1UxhoqmrqxVW9lzRthdqKfnu5NQ+zFpQW+/LXvoa3oIRqNUJCZ8fv8hL1L1HXeTSLqJ7w6TMw7T8K/iE6jYftdH2RuaRWxwkQ2HSccWCeeyuKcG0ZjLKO+oQm1Ws384gJSpZ7gxiwmRzMhzyKuyQskoz6SsQCVVdXEowHGb5xAINWSzeZwzdwgm4pS39qDb32BeNCFRKJgceIy5dUttLW23M5qDVw5hb1uBwLyZHNZBAKgJGBrg4Xe7e/kNW6KAMvZu3sX+/fupram5qc6MiiVSv7xe8/wxsUxSqpaVKZalte9jA1f5aMffIoXX36FTDxEMualmM/iWbiORKbEZK9HIhYQ9DqpbNlPPp9GJCigUmsYu/IKe+7/CCVEOGdvolCbyBcKTF97mf09jbz30UeBTdeI7V1bef2lp/GtLxPyrlDTsgNL+SYlKLg+xZaeA6R941y/eJzRm5dwTl3j3v293H34rn+V/sf/u+Bd9e6/HP6vCfqWlhZ4+m/+B5mVW6xPD3Hq7GnKaxrR6/U//eS34HI5OXrmMo12E1Jy6EVp9Bo1rw/Osre3h9oyK0ura5hq2tBqtcTjMb7y53/EUv8pHm8x8lCLmVJ4jVNnzzGysMbNW2NYGw/cbvskkcrQmioY6T/H448+zMnjbyJRmYnHE9wa6qcYmKVZk8GsN5JKJqgtt3L6Yh8f+tgnaN2+n1P9I/TPrxOWWXjsI79KZWUlkwOXed/udl68Nk1V826SqRRFRHjCMSz1vazPXqdQgqJASnXHXeSFCsQKHamon4qaJnRGKxmBmvmhEwgzEZ5ot1BmMTGxtIJQrmJbTTkXb47wuQ8/Qi6TRKbUodKZySbjXLxxhXVPiFePneb0uTOsuOPoKraxvOplI5CgILMwNHCFNW+Ea1fO82CzmQe2VNJdaWJo1knfhpS7n/wsuw6/l7xQxeW+42itdUhVBor5LOtLI3idE6RiQYqFJLGAC5XBTmBlGLkoS01VNXvufoK+M8dZ9UTQlm8hEo0xePkoC7PjjI70s+GaRyxT07Tnw6hNFSh1dtSmGuZuPE/Yv45nbZGUd4JUPMqs00sWJcl4mI25flBYKUkNzE8OUBLJCGwsUhRKEYikLK2sEUtkcDqXiRcU6Cu6iMTjDI0OMzw3z7XxaS7MrJDWtlLMZWjc9RQiiRKFxoLOVs/C0FGqTUI+/7u/wUc+8D4Mijz9g0OojA6KQjWZVIxCNk2hWCCTTmAyGXBNXUVUiDOxHGRlfpJCUUAmESabCpOK+QmuThDxL2Ou6iSXSRBYnSAZ9hBcHcfvmiAVj7CxMkGuKKJn992YzBYWZ8cZGbyIpW4XArECkUSOqXIrmVScdDKKZ3EIgUiMpbYXpd7O2swlEmEPTTseo1jIolKqyOeyFBGRz2Wo3/4YKr0drbmGkHuG+vpGDI4OXDM3SMeDqI3lZFMRHC0Hkat0ZJMxbFUteDeWkWnMiGUabFXtCAQCVsbPIBLLkKt0qHRW/K4xQmvT6CyVRAPrpOJ+guvT6Gz1yNUGgs5RHK2HUGhMCEQijBYHsZAXYSkHYgX2MgfpVIq5+Rny+TyuyQt4VyYQSWSodBYSgRU++OQjHD95BrWpkkwiQiqwzHaNn/u3NaIsRumqK0eWcrMR8rNr3wHc606E2QAPHOzlwx/8AEqlkjN9fVgr20glU4yNj3NrbIKZyWFca2sE4wUE2joCSSGvPv8tWrY/hEiqYmxiCrc/TDyZZWLoIukczE0NA0Vi0Sg7e7Ygk8n5+re/S3nrYdRaA0aznanBMwikanLpKP71BeyOGg7d8zAms5Wkd5qK5p34gjH8kSTr84NIVSZ09kZUBgcSpZnFkZN0dO1HpVaTzaQ3NwOeRdKJMGKZCrOjBb29AQRi5m+dJuAaZ+uexyjJjOhsDZjLm/AsD6M3VxD3zZGN+fB5nAiFUEiHKHNUoVRtWtlM3OqnrKqRrm1b0SilVNjN1Nc3s7E0wsH9e3+u9X50bIRvf/dZTpw5z9z8HNWVFahUKm4ODfKVp1+huvM9yFRGIvEkqUyedCrOzm2teN1r+AIB0rEQsYCT8rptlFe3EtyYIRN2UVbXy8rkeWLBdSSCAr7lm5RKJdq6DtC+pQupVMrKTD+FhAe7VsCX//Iv7vhdcrkcmVRKQWZGpq/CaKsBIOJfRSEuEA97iMXibD/8flq7DmApq2JxZpSdvd3vqnffDfr+RfCvEvTlcjkunD3Oq898i/7L50ikMlRW1/7Mvnk/L7LZLP/4t1/gE3uaaKu00VRuptWm4fk3T9C7766f+Xtv9A8QFdkYWXAxOTlCIhrgzJiTaF5AKAO+SBxKRQy1HZjNZk4fP0JhbZxdFRo6a6wU8nlkFFBKJVyecTO6sIGhvAWNSsnK4gTrzjkkUhlB9zL3HN7PYN/rTF4/yeLYFVZm+rm/2cCOljriYS+ZTJKNtRVmfRH2Hb6X1tY2du2/i50H7mHLtu3kclnOnjvP4MB17NIs/bPrSHRVZDIZBCIZG+EkSn0ZvuURCoUCjra7KBSLJONhLFUdRAMu8pEVoovXyXmmyMS8pAMr7KpUUMjEqattoqO1A6PBwrEr/bQ7DGxtb0MhE7HhmkOYCTMdFnL/479OfV0bw9OLhNJSskUpJakenaUKpcaEb22e5o5uXMuLPNCk5ej4Oi+O+Dm7EEVfu5dkNo/b40WuUCEQy1icGiCRLjJ8/nkkSgMylY54aI1ioYBIpsI1M4DGYAORismRq8yM9ZNBQSIRx7s6R8jnpFAsIdNVYKzuJp/LUMpnifmdhDdmCa5NIlWooQTRgAupXMPSwgzhWIpY2EvEPU94Yw59RQcaUzWpVJp0MkHIu4xCV45QLCcWi2Kp28nSxGWMNTuwVHUgEEmRKLRo7I2E4gkk9m3oqncSC7pQGysRiqUo1CZUejtqrYlcJsXi7Bir65uK2y0dW5hZCTA3M8XK9HWifid+1xh+5yghrxPn9DUef/AAL77Zh7ZyB2KlBd/yENa67RgdrYhEEtRGB+75G+jtjWjNVYilCjLJMOaqreQzceyNu6hsv3uTa5fJo1XL6ezZw8TwZeqaO1HprQR8a5RKJWRKHSujJynmczTuegqtqQqtqQpz1VZcE+cob+wln02jlkEynUMsVRNcmyQZdpMIb+Cev05DcwfrKzOsO2exNe7B0XaYQi6NWKIgHt5ApS/HUrMNgVBMYGMBpUJO0LOCUCRBayonFfEQWr1F2LNMzO9CKRMTC60hN1Shszeht9Yi11gIrE2h0poRS2VIFBokMhUUCqhVcoQiIYWkj3TIRVl1K/OLy8TSRZJhL0ZHKzKVAffcdRo6DzF09QThVAmXy4lQqkGhtZDdGOb+1nIyiRB2k5qtbS001zh45ew1ZFX7qGzeQ0lmpP/6JVoba7FYLIT8XoZHRllYDRCK5xBLlXhWJqjb/gRStQWPcxJ9RSfzk4PIdeUEw3H0tlq8q3Ob5uNNu9FZ66hq7CYQ8BLzO+ne2sLRE6d47dgZchILsWiIDecM0UgI/+oUqfAqj927k0LCg291mgqDkEcevI/hsRk80RJylYmQex5DeStKnR2xVIFab6NUyHPzwgvIZDLEhRihlX5MejXrq8tYqtrR6fTIxUVqqitQyKSU8imMFR2AgHjEj0wmRypVMHP9eeKhdWo676Wtcye79t5LNCticqiPhpZO0sk4IzdO0rN7s5+1XC5HpVLgc69i1ZTo+iHPxJ+8Tt/guSPnqWg7hLV6K7GshFPHXqa3eytf+puvIDa2YrJvvm+kciW5fJF8JkG5UcLj732U5aUlqpq6qKioJuyeJbo6xMGeBhQSIUtzo5Q5KmlqbKCqqoquHXcxPXKJ+tZuxsbHGB+6TEkgJV+EWHCdQ/t239HvF6C6uoqb1/tYW1slFksQDbiIuadoaOpgYvAsh977a2j1ZqRSGUaLjWRWRMS3SGtzy8/z2vs3hXeDvn85/MKDvlKpxHe++iVsyRXub6tiW4WBtYUJro5M0dnzs/dK/XkwMTGGwj9Lo+Ntwr1UIiYSDVPSO36qUz7A+Ngtjr/wLRLOMfxuJ6sFI7GsgKJMR0rTjMjYiL+g5cT1Ie69957NoO/Ii0hTIXqr9UhFIkLhCAqVlkgyg7+gQGCoweuPMDpwBk8wSSCSZvzWNbyuaQpRN092WPnI4S4qpEkqLSbk2SCOihqMFju3nH7OLydR1e3HFy9x8sQRGmsrMRiMLC4t8Fd/901CRQNL7givn72AopQmkpcgkqpY9IQoSjVE/CvIJGIyuRw6WwNSmYpcOo5EriHsHGabfIMP7dtKT42VCkkMly+AXafEatm8Z8ViEY8/wI3VJLML81gUYDEbyUUDDCz5wd6N2VbBuj9IMuwlJ9Wj0egQSZUUSwLEEikR7yKFTJQyWyVvXrrKmmwLWV0T0UwJc00XgWAAkcyALxQjEAjgc44Q9q5gre1Fa6kluD6F1mCluv0w6VSCiqbd+NfnkCoNtOz5ANGwj3Q6hdbWgKG8GZ2tEaXRwepEH2H3DPHgKnK1ierOBzFXbUFrqcGz0E8+m8Zasw23aw6xQsfWu38dg6MVS3UnurJm/M4REEmQa624xk5T0XaIqo57EIqlZDNJPIsDKDVW1OZKJEo9hVyWQi6DUmtjY/YKMoUGBELSUR8KrRmZSo/eVotQICCfz1EqZMllM0iMjUzMu3jmO19hZnYOta15c2Nha0IoFiNV6DazeN5VbLZyhOZOiiIVyXgYraUGpc5GPptEotBsKmMFAjKJILbaXgqFLEKhmFwmTtS3hKVyKzKVAZFERi6TZHV+hJB/g2gkSNfOu/B43OQLArSWKrLpGMH1KWz1O1EZykAAYokMoVBE2D2LXCzAYivHUWYlEE0T9ixgLKujpuMQenMFWks1RiWszPQjVtmoaL+bYj5LIrROLLiKvX4HaoMDmUKDSmdGqjLjmrqMRCwiFvXic00glyvp2bGPfDZBfct2du7Zz3D/eSra70OptSBXaCgWskR8K2QSYUqFLFLFZmcSAQWMRgPBjXmE6XX+02/9GtcvHKPv7DFy6SQqkwNbbQ9aSw3x0CqBjTnUehtNnQdRKlXMT/YjUWgRJNx0mIXkM1EEpQJisQiPx8uoL0/r3scRCoUoVVrUBgeXzx1hYmqahWUXtwYu4FldIBnzISjl0Ts6UGptiCQy4gEnprJG4mE3qXQGlc6GgDwT19/Y3JiFN1BoTKg0OrSGMmaHT+L1uLk+sog/4Eemq2Lm1iUEyjL+v/buMzyO6z78/Xe2d+xiF8Aueh80kiAJ9k6KVKGqJau6F7kqTpzY/9iWc+M4N7k3Tnwdx7acuMSOq+Ii2+pUsSSSYhF7ATEEQfS2KFuwvd4Xu6TYVChRoiicz/PwIXd2Znbmx5kzZ05tbN9IUdVc9Do9hRYVf/s3n2fD2lXMnzcPt9vDL3/xE7QF1cRiEYLTYxTXzCebSaFSa1CpJIwWK1J8GpcpzWc/djcf+/CHaGuqxeuL0dw2n5IiB/V1dbhcLhKJJPv3bKOqbQO2whK0RisTowMkYgF02TAFrgrWbbyJkpIS9Ho9LmchkxPjjCnP4TSluWbdSjo7D2MvqkCt0RCPznDy4LN86O73YjKZGB4eIh5PvGov52w2ywM/+imNHZvR5kvGjCYLGZWByeHj9I9MMhNNUuh+eZQFtUbLUPdurt+wnOrqGpYtXog6HcSgSXL9xlV8/i/uY/WqVWzcsA5VNkk8o6OqoR2jyUpv124ayu3s2LEDr3eMyrZNlNS0ozVYMTs8HN67lbWrVpzV1luj0bB86RLqK51M9h8mPNWHp7iQujIriYyKioYFZ6yrRqe30Ne1h1Urll3MY+9dRWT6Lp23PdM3ODjA2IE/c01HE5l0FpVKRUWRgyPHu3HXzzlvvstLYWhokNSoQkVR4dnLJ32YK5pOj1v3SoaHh9jyi+9y74b5WFMB5NIinGYDTx86gTeuI5LMEIrE0Fg91LWvoevQTlavXM6J48eQZrwYSFJg1JBIplGptXhn4hzwpqmdv5bnn/w1jooOimvmU1Bcg62omlg0QmpoD+9Z3QHA2LiXstIqnj/SjT8YJJ6GLYofyd2OPGch7rIaCj31PLflD6xdvZJvP/ADPM1r2bfjz0Sx42xaz1goy7HD2xn3B4iiZ3LwCIGRTorKZKYmhjBaXaSTUVRkiIZ9SINbuWtVrmNFYGqE9pYGKooK+NPOI2xYtgSNWs3E5BS7eiegej0jviAD/jh7Dx/mYP84XT5oWrCRZCqFd9pHrdvFwc6DWB2l6IzWXKeJ0BThiV50GonB/m68URWVc67C6vAwNtyNvrAGtUaHRqPF4nAzE8hV11ldVRgshdgcbszOilzV1dARfCPHmRrpRmsuJDg9TDwWQq3WMj3aTX3HLWSRiIYm8Y8oVC/YjNFWQiYVx1HahM5gIZ1KkM2mMTvKGO1+kcKKOajUWgxWFwXFNag0WiL+cTKZFMHJAUITA4R9I2h0Jopr2hk49CSSJGG0ugh4TzIzNUjINwKZNCZHKalYmOBEL2qNntqOW7A6KzAW5DKBJkcZapWKrCSh1mgZ79mNrbieUGACS7HM2PAJslkI+0awuqqADOWtGygorqawvI2At5doZCZXijvQTTqdQq01YC+pI5NOYnVWoFJrCE70MjnUyUTffhLRIIlYkLBvBL3JQTQ4ARIk4yH8o92Ut67H5KxlcrQX76QfjUZHVqUjm8kyNXQESZLQ6M2YrEVk0inUGh3ZbIaZyT7i0yeJBUdJJ3Ntw9LJMJlkHJPNhaTWEhw/gS5ykprGuXin/LgqWgj5xigsa2ao63kq52wCCVKJGGoVBKdHCI73IEmg1plxNyxH0hrpVfZhIIS7QM0J5SiRlBaHR0aj1qA3mDCYbKSScaZ7dxKYGEJnLiCdSpBJJZkY7sbXu52vf/VvaW1tQ6PK8tJxP01LbkGlMeViEQsS8o0x2PkcNkcxzpJy4qFpyprX4p/oJ+SfwCbNUFdRQywWRaO3sevQUYZ11VQ3vfzwTqUzbHns9zR2bKa0biGBhIFpbz+NC6+htLYdv28KvbmQTDpJNOjFWughND3E+Mk9TIz2MHh8HwWeZtwNy3Mltif3olFrCASmGT25nxO9g1S2bcJd1cLwib1ojIU4yprQa9WEA+O0z1/I6Eg/zXXl2PLz+UqSRMDv5+jhA0yPDzA5coKiqvno9GZSqThGo4nAWDeqVAiPx81tt9yIJEmYzRae3/oCVXIHJpPpdE3J4X1bmfFPUtrQQTYrEQyGsbnKGTr2AguWrCaS0hJNpPG4S4hGIvj8fsgkuX5dB++/+25kWcZZoOfAzmcY7TuCVR3gfbffit/v55vf/U/2Hxti+6597Nu7i7aWptNDSp0pnU7z1PM7KKlqPWu53mBirP8IyVSKVFZDOBLDbMuN1zkxdJzMdBcf/+hHkCQJvV5PQ30DC+e3U1VVdVaGbU5bK4VmiZ5ju0mFRrh27WJWr1rJlmeeJhTLYna4iYV92O2FmG2FpBJRSgv1lJaePai8JEmUlLhZvWoVN2y+jqvWraF97ly2btuO3dN4OqYajZop7xhOU5L57a+/tPPdRvTevYKNjo5QaT9/SJNKh4GxsVHcbs8l/01ZbuLHf/oFi+UM6vzYbKl0ms7xEKvqG19z+xf//CSb2qow6nVUVpRyWOnnWM8AzvI5lMirMem1TI0odHXu4eqmOYyMxUkmk6y6ajP/+72DjCoj2I0aVJkMAxM+nlXGOBmyEzzaSSadJR4NQCZNNhWj0F6AqXU5ga0vkkwl0Wq0lLqLGfb62LBkMb854uP5A+PEjVWUOasYnYwwMHyYqvJSsroCentPEk2p6e8+itHVgNVaShYVntarsLplYr6TWAtLSTuLme7dha/vRaSUGoMmTbHbjSRJjA4cI5PwERg9DnoJt8XM9Gg/pYUuDE4P33p4G5pkCG8wTkDtxFY2SDSther1dHZtIzt1CLfdTCgSY2p6gkg4iNtagVmnYfzYM+gcVWSAcHCKRDSI35tEpbNiKmokmlYTnBgnlU4y1PU8noblRKNhAlPDjPe8hL20DZ3eiNFWzGDXduLxCBqtjmR0BntpCyqtgcm+A0RD06RTCZKxGdKJKNHQNFqDhamBw1TNvRqNwUI8PI1Klav2jPhH0RptqDV6EpEAyViIiZN7SMSCODzNxCJB1BoNWUlCqzehNxaQ0ujwjR6ntHEFw8e2Uta0GkthOb0HHqWqbRMqrY542E8yHqbvwKOU1Cxkov8AFS3rCE0PkYyFMNmKqWhdz8Dhp8jULyMeniIVD2FxVhOYOEkyEsRsL0WrN6M3O4kFJ4iHp6mady3pRBSN3oTOaKeseQ0n9j1Ms7sDS7Gd0PQQI11b8+OeqTg1CnfYN4bZ7iY+M4XFWYEkqXDXL0VSqRg4/BRqtY6+Y4/RvOIespkUsUiQjnV30vXS44z4h8iiJp0Ik0zG0ZmLGep8DqurGq3eRCw0TTI2g2+kixKnlbr6JmKxGKnwOG1LNjNw8hg9ex7CZivAps/wla/dz/d/+hsqK6rwjSgYbB5UKjUWRxmTQ4ex2kuRVBK+sTHIJEnEQxhsRcjL7iSZiGIqKMFeVMX0yW1ktVbU6UFsZj1FhTZSGUgkwmg0agyqBHNbm7BXr6Cr8wCxqV4imTSRoJfl7TU05+f5ttvtRIPe3FAbE71MDh0lnU6SjM7gqpiD2lTE9id/wdwFKzDoddS1LKFq/dXsePx/CChjeDQBesJaXhhMUdBSw8DAACqVioKCAnr7TmJzuLHZcxkNs7WA2jlX0du5g0Ub7sFgNDMzNYhGqyManGB6uIvQZB8uTy2xFBRVtqM1WJDIYDDb8DQspefQ49TPXYvdVYrZ0w5aK5CioLCIaDxLwDuAPm2jrbUFi8WC3lzExISXsrLy02nbujWr6Oz10jBvPb/68TcYO76NkrrFSIBvuJ9oYISqylosppcfj0ajkZWL57Hz4PPUtSxFrdExNniC6aEjbNh8N/tfehSdo4qs2sRYzy5IhqhpbOfE8V8TS1TQ3d2Ncuwggalx/N5eBo7aqa2tQW5sYsH8BSzIz/tdVGTlxIlB/v0//4eWpTej0ebGEvVNjvGfP/oJX/z8X56XVqvVarSqDOlUCvWZgzl7h6mtKqe5sY6dR0eJRGOc2P373MDgsUn+9R//7nU185EkiQULFp41YHZfXy9FJeUYi+x4KmpRqdRIEkTCQdJqPaFw+DX3e8rGtSvZsmMr9XNXoVZriMciDCnb+fynPvS69yG8fiLT9zYoKXGzMxA9b/mgP07Ta5S4vVEWi5Vl193Ojx9/kI6KQrJk2TvgZ82Nd19wTL1zzQR82ItyQwuo1RqmgmEy9gZKTOVYTUZ0Wh2l1XMZTQQ5fvglTKoEarWaiopKrnv/Z3nolz/km3/uZHpqgohkQVu2mPnX3gbZNDNJPfEZL+pMiMKiagASMS0TURXjUz7KS4rxeDxEYzEee3Y/ppIOOruPUduxghJPNUiQzbroH+rDGA9jMpnIpuKMjPVSMWcz0/4A6fyYXiabk9BENyXlDRTb9Uxa43zkrhv42e+3EM+kGDr6VK69lt5IJJmiymGgqrQErUZDNguP7FNoXbCYx7Yext1yI069EycSA0efRa23ozYXodYXMBgxEI1PcOzRn1NUvYB4Kk3X8ceoMMexl5ZhdDroGQvgi4Ux2ooorpyLqaCYnoNPk1bpSaQhqzJiL65luPM5NDodEhLpdAqbswK1Rove7KRq/nUcfPK72IprKW1eg7WwAkmtQcrC9HAnRbUL0RksDB19Fv94D1q9mVQyjkqtJRENotYYyGTSpBIRNAYrKrWG2Mwk8YgfZ0UbFS3rCHj78I92EQ6MozeYsThKiUcCRAJjlNQuwuaqYfDo01gLKzDaXMxMD2IwO7CV1JLN5GaaMFgK8Y0qnNz7MImIH4OtGL3RSlyjIwuo1LpcyVPfPiBLSd0ijLYSwr5hmld/iL6DTxDyjVLRso5T/fd0JhtksySiM6dL2Qrc9WiMhZjNhZjtHjLpFEee+S9q2q8jFvIxomxFrdWTTsXQGq0YrS50RhuRwCgGi5OCompGT+wim0lDNkkiEqCiRibgm8TTtJLjO3+LKh3DU1JCWFsLKh3BqUGObf0JdncD2VSS+MwYBg3c9MEvYyvIdVCSNBr27XiaxgVXYfc00Xf0BaRkil//7iG0xJg7fwnPP/V7wv4xbEXVkM3gPbEL49xr0JssFJfV0t+1k2Q0iMNdRzoZzQ0jYywAvQnJ4EJvKyMx4aWuoYGBI09TUtuBWm1gvL8Tb+8e3O0LiWd0VDQtJxrNzX4jZdMc636WgYF+qqqqaWlpg+g43fseA0mFR16JzlhAJpXAN9qFTm9Co1uA0nUY08gY5fXz0WhceOZtZtw3ysmxoyztuJH55X62PPo71HobBYXFDI320LXnMdZsuP50mlJVUY6SGCAaGOHw1geJp7L4p7wkItMUl9aSiU1iMuopb1zMeO9+7K4yNDoDvolBUvEQTmcx2WyWsPcYpeU1xHU2TDYXgYl+PFVzGeg5hNFspbnp5fEio8ExPJ71Z6VtVVXVLJ/fwOPPPojb7aGvt4fewBg2RzH2wmKMWzgzwwAAIABJREFUOhW6bIybr7/1rO1uvP56iot28ewLz5weYLr2tlvo9am5+qZ72LntGWYiYaob5jGhjqM3mJjTvpitz/yRrqwWa1ENruqFVLetJhHy8n++8jV+/+Avzst47dq9G2fl3NMZPsgNlt91MsPU1BROp/Os9SVJ4sZrr+J3jz9J/bx16A0m/FPjTPXv5d7b7qOgwE42+yjbd+2jusyJQZPlzts+Rt2bmFe4vLwCozrD2OQAktTBqU62sZAPdXScluZbX30HZ1izJjc0y5bn/kgyncVdZOXeD7z3vJLCd5poNMofH36EQ53HkSRYOK+VGzZvvugpA99uonr3bVBQYGfnvgNIER9Oq5lsNsvu4/349MWsWrvxLfvdsvIK5PaljKV04Kpm0813UV1T97q2DUWjeHuOUu5yMDg8TN9UlAmVG9QGEulMrn1WNgOZFCHvcdqaali6ZAkARUXFrFp/Ddfeeg8bbrid323ZRmnrBhLRGbKJIEa9DowupoeOUVwhk81mGeh8AavNyHQ0Tiw8gz8YYv9IiNrFG1i6qJ0DR08w3HeM6YkhMukENoebaDhI1HuEe+68g+Ghfo5191JQUk8mkyWZShHyj2NzFDM9rJCVtMQTKZSDL+AsLMCgyaIyuFiwdCPRtJaZcJyMr5t4Mk2BJovVqKd73M9LgwG84TRNy29lYnKKcHCaTDpJcdVcfKNdTA13E4mEqJq7kXBShUpnQm8vR2cqxF1cRjY8znX1ZmLhCbr7jtO66GqS8Rka568nmUqTyUpMDh4mFZ/B5m5Ea7BgtnsobVyKrbiewHgP4337ScbCaPQmVGoD8bCPVCJCcVU72WyWTCaFt3cvZc1rUas1qDV6tHoL3r69ZNIpstl0bsDVeBit3oS5sJyRrq25EiZnBVPDnQQn+qhuvw690Ybe7GBq8DATvXsJB8ZIxSJM9O3F5alH0mgwWJzMTPaTTsYoqmpnZrIfvakAndGWa98X8WN1VZJKRJnq24vO7MDqLM9lCDMpJJUaJBVavZmKtg34Ro/jH+kkk07irl/K5MBhQlODJGMz2D2NGCxOfKNdONyN6IxWkvEwId8wiWgQs81JOpUilYiQSsbJpBPEw34ymRTjPS9Rt/hW7O46ims70OiM+Ea7cJXPQWe0kogGCHp7iYV9JCJ+zIWlqHVG/NMTWArLUUsSOq2a2rlX0Xt0GxqDDb3ZTvXcTXgaVzA9fBSVBOnoNA1ti2htzw0kG49FOHJgD/KSmzBpsqQyEvKCjURCfqpbljE23Es2PIzdWULPsX1kJRUVdW25UuCIn+BkPyFvNzq9DrXehkqlxuyqQqXWIUkSarUG32gXmayK6ppGJgcPMnfxRo4depHJkZMkwtOUVVbTc/wYamsZeosLq8OD0VJIPB5lpGcPcl0VjY25KrXy0hIe+cOvsZe1kUrE0JtsqDUa7K4qho/vwNO4HG/vPqRsCm/vfkwGDT3HdmM1qll33d1Y7S727XwWs6ua4HgXEd8Q0cAImVQCV5GbIndulhej0YiUiXNs3zMYLS4KXOV4PB5mpofRqxKUlZYTCk7Q0LoYo1ZCY7BiMFqwFThIx3zoVEn8o8e55e7PoNVpGRzoRW9xkcmksVhtjPUfJh6apH3+YrLZDH1de6kq0rFm1aqz0rZkMslTz/6ZWMaAqaAUs1GNOulDSwQp4WNOYyUfvuc2WlvbztpOkiQqystZvWI561avpKW5marKCp5+8o+o9HbKq5vwB8NMD3cxt30xBYVFGExmBjqfJ5nVUd26EmdRruTTVljK+EgfDRXOs+bWNpv17Nq9H39cj9l6dmeIae8AC9rqsVpt56XX5WXllDjNHHrpOcb6juA0JfjI++/G6XQhSRJyYyMb1q5izYrFXLVuDcXnzOt7sVQqFe4SJ3te2kn/iaNkUeMb7yM2eYzr1y+hY+Hrn0ZPkiSqq6vZsHY1G9et4qYbNmI0XPomT5dSNpvlm9/+Dr5sEdUtK3GWNdMzOM6RfdtZsqjjkvyGaNN36bztmT5JkpgzfxF9/jCPbN/P/sFpHI2LuOm997xlvXdPMRiMVFXVUFlVc8H2IK/E7SnjiRdeJBKYJDITJJiU2H5inLLyWuxGLT7/FIl4lPGTL1GsmuZD936awsLz30CNRhMHjhyjdf4Kil2FNNTX4HS66Dt5nCFlB1qNmpHunZg0SW67cRPv/8gniRicxKwelm+6hfYFi3jgB/9NytpI3byryGpMTI8PMtD5PLHAEDddvYa2tjZampvpUQ6zb+9OCpweIoFxErEI/vEe0qkk1U0dhCYHqG9sIa11YFJFaakr5unH/pf+k13UVFXj1KVY0dbEjp4xnj96EltxOes65rHt2BAl8nJiSRU2u4uZwDQ6g5WRru0YbC7K5aUYLYXoTIUUehrwjXVTO+8q4mkIxpJ09vWhLXBx7Q23oDKX0q0cRWUpBUmTm+M1nSQw2oXWYM715NTpkbIS6VSCqcHD6PRGKto2EpoaJBGeJDjZh8FkoahyLolYGL3RxtTgEZzlrURDk1gKyzDbPRQUVdO9839JxiMk4yFsRbVYXVVkUgkC4z1MDx9lsv8AkcA4JfWLMBe4SScTjHW/iM5gwVHaiFqtIhYcpbJpKTqDFYejkIDPy8xkPwDZbIZMOkUiFsZR0kA0OEYmncJodTLRuw+jLoulqD4/76mJeNgP2QxTg4dw1y/FZHWBpCIbnaKmZRmDx3ejM9monn890ZkJrM4KTAXFmB3lDBx6HJBIxsMkozOMHd9G3cJrSSWiGMwFGKwuQtMjBLw9WJwVOMtb0BksaPRmdIZch53ozBRqrQ6zozzX1rR3DwaLk9BUP+l4mFjITzQ4QWB6hKC3h4Y5q0glY2QlCUljpKp1HTqDCUlSY3aUEQtPoSfCnLkLcXlyM7qMD/cyE5cwWp2EZ/wUVzSi1epIpdLoiFMld2BWRfjEh+5k184X0RltaLRG0pKG4so5lFbW4yopZ177YsYnJhnr3Y+1KNfWU6vTEZzsIzjaRWXLcrKRce64YR1bn30UfzCC2aSnqXUei1ddx/joAJPTPtzVuanSMpk0I8e3Y7EVUeexMG9eOwB1tXUc7ezEXtpEMBjC5vRgttjIZLIEvT0YrYVEp05w6/s+S0V1I9XODCatRN3ctZgsBaRSSToP7cVV2sj6DZuRWxfQ2LKAYk81Lz33e6ob5qHTG4hFQxza/gdqmxay8YZ7aGiUqamTmbdwDdqUl4/cdRM1laX4w2nKa5ro3Psshe4atFo9qmyUbGgAi8VCbdNCrAWFDJ/YTyIRJxELo0qFMEkhlreVMjl8nNBED6sXtfCem286b6y3LU89Re+kGnneKjxlVdQ0tlPgLGX1wkb+4atfYd2a1a+roxuAXq+nY/5cRnqPMHRiP9GpHnQasLvK8Y0PMn5yF/VVZYRUJZTVzkGjebkUKBycptZjorHx5eY2ZrOeTBpe2LqNorKXp2BLJuJMDeznpus3v+LYdSUlblYuX8b6NavoWDD/vM4fkiSh0Wgu2dh3JSUlrFu9HLM2SWz6JK01Dj75obtYumTpG95nrv3kO3/mqp6eE+w6MkC13IEkSUiSRIGjmN4TXbTJVZeknb5o03eF0+l03HL7naxct/lyH8rrotfrufcvv8Tel3by7BMP0+PTUFhiY9Q7yqK2ObhsFvp7D7O0XKLA0/aqVQVlJU7i0ZnTbXu0Wi2NlU6qjHOIxsZolN1cfdU6OhbmbqD29pcbg7+0ZzfGogYKIlqMJitVtXbcnkp69j1CpcfBurVrgVx87//yl3lyyxYef/oFqhzFBJliaLybrLqAceU56hvn0NCa+42jOxXef/edHO/pY6FnEUaThb1P9KHTablu1Qqmx/tYNH8OT+0/zoLlq+kd7yebMWB3FTETnCYZDZCMB6hsXoHZZGJ6cgy1RoPGWEAmnSadSmEpcKKlkcqOxUS8CsuWLOFr//ZD7CV1+EYVSuuXotZoCU1p0Rv0JH0nqVuwGUdRGRPeUcKhGYwWO8XV80hFp6mbtx7lxV9j1IJOoyIWHEfSGIlHgqTTCWYm+7EUlqPS6CCbRaXSUFBUTSQ4Sc3865noP8B4zy6M1iKKazoYjPhRSRIFJXXEQ9NkMxkSET9qrZ6S2kWEpwdpaF7A1NQEk717qG1eRGV5KWMndrHp2psJzQQ5tG8bGY2dcMCLRBaj1YXFVcFk/wFU2RjtyzZy5MhhKlrWEwl6Gel6nvK29VS0bUCjNRKdmUJrMJNMJZg7p5UBZTeFZa0kowGsheVM9O2jonU9Nmc5xoU3MXTsOeJhHyq1BpvdyeTAUVyeGtAYiYSmCIx353qDTg+cLrXU6oxEAmPoTDZS8RD9h57E27uXVCKKxVHGeM8uClxVVLauJpWGTDbL1OARYiEvyUQMT3EhU6NGtEjEwgH0ZhsGvZ6IP4ZJp6G1YwFS0kcsGsJgtKDTG0jFw8TDPjT5eZcBUvEwOkMhFlshPcf9lJS4qW+QKW9bz7Eje/EOjlFWsRGNVp/rWVzkQq4uJjqc5uTu36A15kt+MgmWXP1hwoFJ1KER1qz5HFt37mXZ5s2oVOrT9868RWv47c8fQNmVwGgtJB6awlPdRiLiw3HOC9qGNas4PJQinSomGAthMJqJhKZQa7T4hg6y9prbKHAUoTcYiY9O8Dd/dR8P/OC/Ge0BVGpC00Osuea9aLQvP1L0eh2rly8kNrqH4c4ZbFYjbY1VqF1zz/ptrV6P2e6hrKyCpqYWOr/1baZTSdoXLGP/7oeZ8Xlpa6rlzps2s23HbgZPHqWsupkVG25ix9P/iz4dZm7jPDZ94MM0Nsqvmbbt2nuAyvbrz1rmqWzg4K7fccd7X3Pz89jtDt53952nP4+Pj9N5rBOL2czcubdy8mQPW7/272QzK5HyL/mJeIxkyEtjw03n7a+qqpp2uYwDLz2Bs1QmkYjiHzrCR9/33re8kOBi2e0O7rj9Tu643AfyNhsfH8dgPf/FQG9xMTHhfUva6V8qV3SmT5blu4H7AS3wLUVRvnuZD+ldRavVsnT5KjoWL+M/vvd9JkJqek928/AffohFk6G5yoW1poG7Pva5V317vPv22/i373wfS3ETrhIPowM9GNKTfOmrf4de/+qDbw4MjWB1uCmpdHKkU0GtM4NKTTYLqztaKSkpOWv9qzdtYsP69fh8PqxWK3969DEGQzZcJeVnraczWAkGgxTaC5gKBzCaLDStuIXfPv0T5hZPootP0h/vRF/azD23v49v/H/fJuhNoTFYMBkNHNr+ELbCUlLxKGqzAa2UIBKJodIaSaeSkI5jLbDiVU5QsvB2eicUqqtriPiHUBUYycZiHH3hZ6g0WgxaKHVoWbywnSdffI5Mw2KmvCOEpoeZs3QzI/0K8YifkH+MVDzMTXd+ku7Ofex8/r+xFtWg0hoJTvQR9o3SvOoDZNMpEhEfw11b8dQv5MTuP+Ht3YOrsh1nWTOJ6AwzUwMkw5OU1szDN66gs5QwenwbZLPYPTLBiV7Kyquw2Z1IEgweCTDduw2XVE2d24i7tJrC4jIWrbyGI/u2se3xnzDeuQWVyYXBaMVisVBZXsH8ZZs4emAH8cAAtqJGzIWl6Ex2Ir4x1Do9eqOVZHgKsyZNxD9GUbEnN0REJEBlbQsBsx7lxV9h98ioJDBZ7Dg8dfTte4T111yF0nUMb3iUeDLLtLePWCREZet6fGPdhP2j2IqriQbGSadiGPUaMhEvBqMdq6OEaHCShL8Pvc5ASe0CiitayWQzzAR92ItrOPLMA9RWFON0FXF4+++olDsIpmZIJ9TEE3Eme3fTVF/N1esWU1dXw/d++FN0tgpQafD27KKuroGZaJpUMkEqGSM81Y9nzTp8k6NUluba8rbPaebktJf2RevJZrKMntyHw9OIvcDKSP9xbJoQv/nVr/jC/f+ApbiOvp5j6E1ORpQXmRlX+PED/45KpcJmtRCLhDBZXp772OF0U2i30tK+FL8/gLGiAb1eg0o7Q0tz81n3w1UbNrD/W/+B0+whEvLSd/AAY70HsdkdtM5ZSG1jrlRwyjvM3KoK7HYHX/rC55mcnCSZTPCw20IgNA35XrLZbJZBZTeffP+N1NW9XGL1yKOPcmQ4dN59nk5EMBqNGAwGvvhXn2PX7l10dnXzvls2sHb1KhyO3CgEHQs72PLUU+zd/ye0Wi2feP97WLZ06UWVXqlUKrLnVPNks1lUl7AE7Mx0qbm5hbn1JZw89CyuilaymTShqX6aqwpoaDi/U50kSdx1x+2sGOhn/8FDmE0FLL7nc9hsBeetK1weZWVlRJ/bD5zdBCA6M47bffXlOajX6Yqt3pVluQz4BbAU+C7wve985zsv3HfffROvsemsmZHjUlGpVCxZ1IG70EiJ08bm667mvXfcwdqrb2Tj5puxWCyvur3ZbGbFkkWok34MUoBFbXXcesvN6HS6V90OIBYJc7Czh5KyWko9JZj0aqwmLdrEGJ/82Icv2Gg2N4G7OTfsQDbNS/sP4SypOv19JpPGe3IfN1x3De7iIp584lGcnjoMRjPuhoUc6h8FWyHv+eCnWb5qLRqNhiWLFmJghu1P/S/hqX5qa6qI+gZJRHzU1jcxp6WZQkcBxw9tIxULYnc4GT3+Iq3zOkglojSU2Zg3Zw77Dh6lvnUJBh24Szy0zV1A+6LVaFN+vvj5v2TPrm2YrAUY9DqKqxdgstjxD+xl5dpriAR9hCZO4LAYsGoTrF+9FLu7geaWOblx/Ya7yWbSTI90koz4sDkrUElgUIUZ6dlPIhJArdES9J6A6Dgf/dw/oVOlWNRUgtkgIUkZpoePYzAYaWttJRGPEo0EySSjmKUA3/nG19l87dWsWrGMQ3uep/vYXiaHFdwFKv71//knPnffZzGoEkwHgixauYn2xeuZnhiB6Cg6VYaof5jg9BhTwwqF5U1odUZmxk8QGtrNj773bTLRCfbv3UG9PA+NWpWb1steQjQwin/4EDq9nkTUT8zbyTf+8e+496Mf5bb33EKpy4xOFWd+awNul4WerkNYnFWEfEOEpofQqCUMqhROrZ8v//VnKLYbGOlTKCsro76hnpMnOqmesxG9yXa6qiYa8pGOTFLssjPSvYc7bt6EXorSp+xltPcQweGDVJRYuWbtEq7etAm73c7aVStwO/TIVU7uuv1WlMM78HkH6Nz/AtHpAdZseg/RcJARZRsfef9dmM1maqqr2bfrGYaGRyksKic41s1w1/O4zGnaaov44D13Y7Xa8BS76DxyiMr6dqxmI4aMjy9/4XPU1uSqlB0FVp559hlcpfWn5y8d7N5PncdMOplAbmnHXeIiGRyhyqVh41VXnZVR0mq1rFi6BJM6hk0bZ+mcKha01YPKRNuiDWg0Wqa8w/gH9vKBu+84PVOCyWTCarXS3NTEvh1PM9DXTWDay8iJ3Wxa3UFHx6Kz7k2Xy8mTTzxMobvudAno+FAPlS4Vi/LrajQaqqqq6Fi4gOamprM6nmk0GuTGRtauXsnqFcupqKi46OrKTDrJwSNdOIpefhEc7DnMguZymuTXLil8I1avXEEm6mVQ2Y0qPsrKBfV84qMfOS8NPPMZUVBgp0mWqa2tRa9//U1zrnRXwnOyoMDOsSP7GPX6sDqKyGTS9HXtoc5jYuXy5ZfkN96q6l3p3DeeK4Usyx8EViuK8tH8568CkqIo//Aam1YDvVNTITKZt/fci4qsTEzMvK2/+U5zsTFIpVL8879+E42jCU9lA6lkgt7OnSxsKuE9N9/8mttnMhm+/b0HmI5bKK1uIR6PMNi1i/dcs5Ll+Zvz8JFDPPi7h0lLBtLJKAvmyLz31vecnh/zXJOTk0SjEcrKynn8ySd57sW9GAvcxMN+PIUGJqcm6B+epLx2HlImhsuq4tP3fgyDwcCvHnyQ/qCZmoZmYrEkkHvgzKsyccP1mxkcHOCBH/0PWV0hSvdJ4tEgK9ffiLXAQe+Rrdy0aTlyo0xxcTEHDx3goWcOUtuylJGREQ4c3MdYfxd2TxPusupcG7XxfXzu43fjchXxpX/4BgaLi6r6Vmoa5yFJEoO9nSyX7axevZqenhMEAn5+/YcttC67GY1GRzKVJDA1hmrmOH9132fOikMikcj3fD67tHbf/n1seeZ5wtEYDbVV3HDdNfz293+gdzyGubCczkN7OLr3GZyOAlavXM5ffObTp0ty9uzdy6//+DSVzctJpWGkvwtTxsuX/ubzdHV1IkkSc+e2v2o1V39/Hz//5S840XMSi9WCw+5ElhvZsHbN6WqXmZkgw8PDOByF/PyXP2PLS6NUtm1AUqlIJ2OkotNEBrdz963Xs3zZstPjWsZiMWZmZpAkCZvN9povLsFggOHhIZ7ftoMx7yRVFWVsvuZqiotfbkjvdJp5/vmdDAwNUVbqYU7b3AueXygUorPzKGq1mpaW1vN64W/dvo1HnvgzGkMBydgMi9qbufWWm1GULp59YTuJeIKlixewZPGS111NeOjwQR578lnC0Rh1VeXceP1157XdPdP4+BjBYJCysnJMJtMF1+nq6uLnD/6OjNpMKhmlpryIL37+U8zMJF/XMb1ZmUyGn/zsZyh9ExhtbuKhCSqKzXz8Ixd+iXw7iWfElRODVCrFs39+lh0vHUCtUrFy2SJWr1p1yargz4yDSiXhdFoAaoC+N7PfKznT9yXArCjK/fnPHwMWK4py72tsWg30vsWHJ1xCkUiEh/74KHsPHM21udu4mlWrVr7uN/xUKsWLO3ayfedebFYL125aR21t7VnrZLNZZmZmMBqNF53wh8NhRkZGKCwsPD2cwuTkJIODg7hcLioqKs46l6//8zeJUIDRVkzYN4LTlOTLX/zL0xmITCbDiRMnCAaDdHZ1c+TYCYpcDm654Rrq619uO5lOp7n/7/+ZjKWWsuomFKWLHc88RHRmErPZQm1VCV/7yt/Q3NxENpvlr//27ylpWo85XwWYTiU58uIf+MbXv3DWfMwHDx7iv37yIGqjg2QiSqnTxF9+9l6s1jfeODmbzdLV1cVL+w7iKChg9arlp4fVONfJkyf54yNbmPYFWLxwLhuvWndRnZAuVjKZ5AMf/QyTqSIsjlIMOjW61AQ3rJvDbe957ReLd5JUKoXf78dqtb5m04nLKZvNMj09nZ967JVnm3greb1eRkZGKCkpweN557bBEoQzzOpM31cAg6IoX81//jiwUFGUT77GptWIkr7LRsQgl6nzegc4crSHyopyGhoa33CPumg0yhNPbeHAoWPodFpWLFlIQ309TqfrvIzS2Ngo3/3PH5M1FqFW64j6B7jjlutZuGDBefvNZDKMj49hNBqx2x1v6NheyzvpWgiFQjz2xJMcPnYcg17HVWtXsnjR4kvW0/HVvJPicLmIGOSIOIgYnPJWlfRdyR05hoAzB2ByAyOX6VgE4XVTqVTMmTMHt7v6Te/LaDRyy403ccuN5/cCPJfb7eFrX/0Svb09JBJJamvvesXSIJVKhcdT+qaP70phsVi4/bZbuf1yH4ggCMJb6ErO9D0N/L0sy0VAGLgVeK2qXUGY1VQq1Vm9KQVBEITZ45016M9FUBRlGPgK8GfgAPBLRVF2X96jEgRBEARBeGe6kkv6UBTll8AvL/dxCIIgCIIgvNNdsSV9giAIgiAIwusnMn2CIAiCIAizgMj0CYIgCIIgzAIi0ycIgiAIgjALXNEdOd4gNeQGO7wcLtfvvpOIGOSIOIgYnCLiIGJwioiDiMEpp+JwRjwuPDfoRbhiZ+R4E1YCWy/3QQiCIAiCIFyEVcC2N7OD2Zjp0wOLgFEgfZmPRRAEQRAE4dWoAQ/wEhB/MzuajZk+QRAEQRCEWUd05BAEQRAEQZgFRKZPEARBEARhFhCZPkEQBEEQhFlAZPoEQRAEQRBmAZHpEwRBEARBmAVEpk8QBEEQBGEWEJk+QRAEQRCEWUBk+gRBEARBEGaB2Tj37iUly/L/Bdye//iooihflGX5v8lN9xbOL/+aoigPybJ8FfBNwAg8qCjK/fl9tAM/BGzAC8AnFUVJvZ3n8WbJsvxnoBhI5hd9AqgD7ge0wLcURfluft13XRxkWf4Y8NkzFtUAPwPMzIJrQZZlG/AicL2iKH0Xe36yLFcCPyd3DSnAPYqihGRZtgO/AGqBCeB2RVHG3ubTe90uEId7gb8AssAe4BOKoiTy6cZHAF9+0x8oivLdi43P23pyr9MFYnBJ0sMrKQZwdhyAFuCfzvi6DNilKMr179Zr4RWejbMuXXiFOFy2dEGU9L0J+Qt4EzAfaAcWyrJ8C9ABrFYUpT3/5yFZlo3Aj4GbgGZgkSzL1+Z39XPgs4qiNAIS8PG3+1zeDFmWJaARmHfqnIEh4P8ml9i3A/fKstzybo2Doig/POPc7wG8wN8zC64FWZaXkJsPsjH/+Y2c3/eA7ymK0kQuEfxqfvk/AlsVRWkGfgD8+1t/Rm/MBeLQCHwBWA7MJZfefia/egdw5xnXxXfzyy82Pu8o58Yg71LdA1dEDOD8OCiK8tgZ6cM1QBD4q/zq77pr4RWejXcxy9KFV4jD/+Eypgsi0/fmjAJ/rShKQlGUJHAMqMz/+bEsy4dkWf6aLMsqYDHQrShKb77k5ufAe2VZrgKMiqLszO/zJ8B73/YzeXPk/N9bZFk+KMvyZ4GrgGcVRZlWFCUM/Ba4jXd3HE55APgyEGF2XAsfJ5dojeQ/X9T5ybKsBVaTu0ZOL8//ezO5N3qAXwHX5td/Jzo3DnHg04qiBBVFyQKHyV0PkEvcv5y/Lr4jy7LhDcbnneasGMiybOIS3ANXWAzg/GvhTN8Avq8oSnf+87vxWrjQs7GR2ZcuXCgOBi5juiCqd98ERVGOnvq3LMsN5IpwVwFrgU8DAeAR4KNAiNwFcMooUA6UvsLyK4kDeAa4j1xV7nPAg5x/Xot55fMpTB4YAAAGfElEQVR9N8Th1JudUVGU38iyXAs8y7v8WlAU5WMAsnwq73/R/8cuIHhGNfaZ5316m3x1RhAo4sIP08vq3DgoitIP9OeXFZGr/v+QLMsWYD+5t/0T5BLrr5K7Pi42Pu8oF7gW3Fyae+CKiQFcMA7kPzeQez6c+v5deS28wrPxP5hl6cIrxGHFqQz/5UgXRKbvEpBluRV4FPiCoigKcMsZ3/0H8AFyufHsGZtJQIZcaeuFll8xFEXZAew49VmW5R+Ra7fxj2es9lrne8XHIe8T5M4dRVFOMsuuhbyL/T8+dzm8fN7SOcuvuJjIslwGPA78SFGU5/KLrzvj+38jV+31GBcfn3e0S3gPXLExOMe95Krj4gD59lfv2mvhzGcjkOLsav9Zky6ck0c4leG7LOmCqN59k2RZXkGulOtvFUX5qSzLc2RZvvWMVSRynRuGAM8Zy93k3kpeafkVQ5bllbIsbzhjkQT0cXHn+26Igw5YA/wp/3nWXQt5F3t+XqBAlmV1frmHl897OL8esixrACsw9ZYd+SUmy3ITucb8P1UU5ev5ZZWyLH/kjNVe67p4tfi8o13Ce+CKjcE5bgZ+ferDu/laOPfZyCxNFy4Qh8uaLohM35sgy3IF8AfgbkVRTt3IEvAtWZYd+Tr3e4GHgF25TeT6/H/S3cDj+SqgWP7CAHg/udz/lcQOfCPf/sAKfBB4H7BBluWifLueW4EneHfHYS5wPN+GEWbntQAXeX75ti5bgTvyyz/Ay+f9WP4z+e+35td/x8vfC1uA+xVF+bczvooC/yLLco2c6wT1GeChNxifd7pLcg9c4TEAQJZlF7mmH71nLH5XXguv8GycdenCheJwudMFUb375vwNuUaZ3zyj7cb3gX8GtpNr3/Y7RVF+BSDL8oeA3+W3eYyXG2DeA/xAznXx3wd8+206/ktCUZRH5Fxvtf2AGviuoijbZVn+CvBnQAf8UFGU3fDujQO54QOGTn1QFOWQLMuz6loAUBQl9gbO79PAT2VZvh8YAO7KL/8q8BNZlo8C/vz2V4qPASXAX8uy/Nf5ZX9SFOXvZFn+BPAwuXtjG3Aq8b/Y+LyjXeJ74IqMwRnOSh8AFEWZeJdeC6/0bPwQsytduFAcHuQypgtSNntulbAgCIIgCILwbiOqdwVBEARBEGYBkekTBEEQBEGYBUSmTxAEQRAEYRYQmT5BEARBEIRZQGT6BEEQBEEQZgExZIsgCLOWLMufBD5FbjiRLLnhEL6iKMrAa2z3A3Lzp+59lXU2A0sURfm719jX61pPEAThzRIlfYIgzEqyLP8ruUHDr1cUpQWYAzwF7JBl+bXmsNzI+VNBnWsRUPg6DuX1ricIgvCmiHH6BEGYdfKZui6gQlEU3znf/Tu5WpDNwG2KouzJL+8DbiM3l+wXgF5yo+CXAfeTm/cynf8uDvyR3GDl/wX8E/AA0AA4gRlyMxLYz1xPUZSvyLL8UXKDrqrITS31WUVRut6CMAiCMMuIkj5BEGajJcCxczN8eU8DK19pQ0VRvkJujst7FEXZBXwD+LSiKB3kZgpYm1/+feDB/PrXAn5FUZYpitIIvEQuM3fWerIsryE3jeEqRVHmA/9CbtoyQRCEN0206RMEYbbSvsJyPbn2fa/Xr4GHZFl+lFz18L+cu4KiKL+VZfmkLMv3AfXAWmDHBfa1Of/9i2dM2+SQZblQUZTpizgmQRCE84iSPkEQZqOdQIMsy+4LfLcOeJFcxu/Mdnu6C+0oX5K3EthDbm7RF85dR5blTwE/AiLAL4FfceE2gWrgZ4qitCuK0g4sADqAC5VICoIgXBSR6RMEYdZRFGWY3KTlv5JluezUclmWP0yuc8f/C0yQy3Ahy/JawHPGLlKAVpZlTb6tn0lRlO+Ta4s3V5Zl/al18utfDfxEUZQfAQpwA7kMHues9yRwlyzLp37rk8Azl+asBUGY7URHDkEQZq18p4lPAQZy1bq7gfsVRemVZXkduc4XMWAvMA/4pKIoe2RZ/hdymcNPASbg60CSXGeObyqK8ktZlpeTK9V7GHiQXIeOFLkSvh3AHEVRlp25nqIo98my/Jn8fjNAEPiEoihH34ZwCILwLicyfYIgCIIgCLOAqN4VBEEQBEGYBUSmTxAEQRAEYRYQmT5BEARBEIRZQGT6BEEQBEEQZgGR6RMEQRAEQZgFRKZPEARBEARhFhCZPkEQBEEQhFng/wfEfCsMG8rqPQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.scatterplot(x='Outstate', y='F.Undergrad', hue='Private', data=college, edgecolor='black', alpha=0.6)\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a stacked histogram showing Out of State Tuition based on the Private column. Try doing this using [sns.FacetGrid](https://stanford.edu/~mwaskom/software/seaborn/generated/seaborn.FacetGrid.html). If that is too tricky, see if you can do it just by using two instances of pandas.plot(kind='hist').**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a251c9810>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgrid = sns.FacetGrid(college, hue='Private', palette='viridis', height=5, aspect=3)\n",
    "fgrid.map(plt.hist, 'Outstate', bins=30, alpha=0.7)\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a similar histogram for the Grad.Rate column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a255e5690>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgrid = sns.FacetGrid(college, hue='Private', palette='viridis', height=5, aspect=3)\n",
    "fgrid.map(plt.hist, 'Grad.Rate', bins=30, alpha=0.7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Notice how there seems to be a private school with a graduation rate of higher than 100%.What is the name of that school?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Private</th>\n",
       "      <th>Apps</th>\n",
       "      <th>Accept</th>\n",
       "      <th>Enroll</th>\n",
       "      <th>Top10perc</th>\n",
       "      <th>Top25perc</th>\n",
       "      <th>F.Undergrad</th>\n",
       "      <th>P.Undergrad</th>\n",
       "      <th>Outstate</th>\n",
       "      <th>Room.Board</th>\n",
       "      <th>Books</th>\n",
       "      <th>Personal</th>\n",
       "      <th>PhD</th>\n",
       "      <th>Terminal</th>\n",
       "      <th>S.F.Ratio</th>\n",
       "      <th>perc.alumni</th>\n",
       "      <th>Expend</th>\n",
       "      <th>Grad.Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cazenovia College</th>\n",
       "      <td>Yes</td>\n",
       "      <td>3847</td>\n",
       "      <td>3433</td>\n",
       "      <td>527</td>\n",
       "      <td>9</td>\n",
       "      <td>35</td>\n",
       "      <td>1010</td>\n",
       "      <td>12</td>\n",
       "      <td>9384</td>\n",
       "      <td>4840</td>\n",
       "      <td>600</td>\n",
       "      <td>500</td>\n",
       "      <td>22</td>\n",
       "      <td>47</td>\n",
       "      <td>14.3</td>\n",
       "      <td>20</td>\n",
       "      <td>7697</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Private  Apps  Accept  Enroll  Top10perc  Top25perc  \\\n",
       "Cazenovia College     Yes  3847    3433     527          9         35   \n",
       "\n",
       "                   F.Undergrad  P.Undergrad  Outstate  Room.Board  Books  \\\n",
       "Cazenovia College         1010           12      9384        4840    600   \n",
       "\n",
       "                   Personal  PhD  Terminal  S.F.Ratio  perc.alumni  Expend  \\\n",
       "Cazenovia College       500   22        47       14.3           20    7697   \n",
       "\n",
       "                   Grad.Rate  \n",
       "Cazenovia College        118  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "college[college['Grad.Rate']>100]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Set that school's graduation rate to 100 so it makes sense. You may get a warning not an error) when doing this operation, so use dataframe operations or just re-do the histogram visualization to make sure it actually went through.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "college.loc['Cazenovia College', 'Grad.Rate'] = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a259da790>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgrid = sns.FacetGrid(college, hue='Private', palette='viridis', height=5, aspect=3)\n",
    "fgrid.map(plt.hist, 'Grad.Rate', bins=30, alpha=0.7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K Means Cluster Creation\n",
    "\n",
    "Now it is time to create the Cluster labels!\n",
    "\n",
    "**Import KMeans from SciKit Learn.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create an instance of a K Means model with 2 clusters.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(n_clusters=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Fit the model to all the data except for the Private label.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "       n_clusters=2, n_init=10, n_jobs=None, precompute_distances='auto',\n",
       "       random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.fit(college.drop(['Private'], axis=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**What are the cluster center vectors?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.81323468e+03, 1.28716592e+03, 4.91044843e+02, 2.53094170e+01,\n",
       "        5.34708520e+01, 2.18854858e+03, 5.95458894e+02, 1.03957085e+04,\n",
       "        4.31136472e+03, 5.41982063e+02, 1.28033632e+03, 7.04424514e+01,\n",
       "        7.78251121e+01, 1.40997010e+01, 2.31748879e+01, 8.93204634e+03,\n",
       "        6.50926756e+01],\n",
       "       [1.03631389e+04, 6.55089815e+03, 2.56972222e+03, 4.14907407e+01,\n",
       "        7.02037037e+01, 1.30619352e+04, 2.46486111e+03, 1.07191759e+04,\n",
       "        4.64347222e+03, 5.95212963e+02, 1.71420370e+03, 8.63981481e+01,\n",
       "        9.13333333e+01, 1.40277778e+01, 2.00740741e+01, 1.41705000e+04,\n",
       "        6.75925926e+01]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.cluster_centers_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation\n",
    "\n",
    "There is no perfect way to evaluate clustering if you don't have the labels, however since this is just an exercise, we do have the labels, so we take advantage of this to evaluate our clusters, keep in mind, you usually won't have this luxury in the real world.\n",
    "\n",
    "**Create a new column for df called 'Cluster', which is a 1 for a Private school, and a 0 for a public school.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "Cluster = pd.get_dummies(college['Private'], drop_first=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a confusion matrix and classification report to see how well the Kmeans clustering worked without being given any labels.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cluster 1</th>\n",
       "      <th>Cluster 2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prediction</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Cluster 1</th>\n",
       "      <td>138</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cluster 2</th>\n",
       "      <td>531</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Cluster 1  Cluster 2\n",
       "Prediction                      \n",
       "Cluster 1         138         74\n",
       "Cluster 2         531         34"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm = pd.DataFrame(confusion_matrix(Cluster, kmeans.labels_), columns = ('Cluster 1', 'Cluster 2'),\n",
    "                                                       index=('Cluster 1', 'Cluster 2'))\n",
    "\n",
    "cm.index.names = ['Prediction']\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.21      0.65      0.31       212\n",
      "           1       0.31      0.06      0.10       565\n",
      "\n",
      "    accuracy                           0.22       777\n",
      "   macro avg       0.26      0.36      0.21       777\n",
      "weighted avg       0.29      0.22      0.16       777\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(Cluster, kmeans.labels_))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not so bad considering the algorithm is purely using the features to cluster the universities into 2 distinct groups! Hopefully you can begin to see how K Means is useful for clustering un-labeled data!"
   ]
  }
 ],
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