Explore Diabetes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This line configures matplotlib to show figures embedded in the notebook.\n",
    "%matplotlib inline\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import r2_score\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.axes as ax\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import cross_val_score\n",
    "#import folium\n",
    "#import geopandas as gpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Source: [CDC: Chronic Disease Indicators](https://www.cdc.gov/cdi/index.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th>LocationAbbr</th>\n",
       "      <th>LocationDesc</th>\n",
       "      <th>DataSource</th>\n",
       "      <th>Topic</th>\n",
       "      <th>Question</th>\n",
       "      <th>DataValueUnit</th>\n",
       "      <th>DataValueType</th>\n",
       "      <th>DataValue</th>\n",
       "      <th>...</th>\n",
       "      <th>HighConfidenceLimit</th>\n",
       "      <th>StratificationCategory1</th>\n",
       "      <th>Stratification1</th>\n",
       "      <th>GeoLocation</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>TopicID</th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DataValueTypeID</th>\n",
       "      <th>StratificationCategoryID1</th>\n",
       "      <th>StratificationID1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>US</td>\n",
       "      <td>United States</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>Alcohol</td>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "      <td>%</td>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>16.9</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Overall</td>\n",
       "      <td>Overall</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>Alcohol</td>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "      <td>%</td>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1</td>\n",
       "      <td>Overall</td>\n",
       "      <td>Overall</td>\n",
       "      <td>(32.84057112200048, -86.63186076199969)</td>\n",
       "      <td>1</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>Alcohol</td>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "      <td>%</td>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>18.2</td>\n",
       "      <td>...</td>\n",
       "      <td>20.6</td>\n",
       "      <td>Overall</td>\n",
       "      <td>Overall</td>\n",
       "      <td>(64.84507995700051, -147.72205903599973)</td>\n",
       "      <td>2</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>Alcohol</td>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "      <td>%</td>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>15.6</td>\n",
       "      <td>...</td>\n",
       "      <td>16.9</td>\n",
       "      <td>Overall</td>\n",
       "      <td>Overall</td>\n",
       "      <td>(34.865970280000454, -111.76381127699972)</td>\n",
       "      <td>4</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>AR</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>Alcohol</td>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "      <td>%</td>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.2</td>\n",
       "      <td>Overall</td>\n",
       "      <td>Overall</td>\n",
       "      <td>(34.74865012400045, -92.27449074299966)</td>\n",
       "      <td>5</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   YearStart  YearEnd LocationAbbr   LocationDesc DataSource    Topic  \\\n",
       "0       2016     2016           US  United States      BRFSS  Alcohol   \n",
       "1       2016     2016           AL        Alabama      BRFSS  Alcohol   \n",
       "2       2016     2016           AK         Alaska      BRFSS  Alcohol   \n",
       "3       2016     2016           AZ        Arizona      BRFSS  Alcohol   \n",
       "4       2016     2016           AR       Arkansas      BRFSS  Alcohol   \n",
       "\n",
       "                                            Question DataValueUnit  \\\n",
       "0  Binge drinking prevalence among adults aged >=...             %   \n",
       "1  Binge drinking prevalence among adults aged >=...             %   \n",
       "2  Binge drinking prevalence among adults aged >=...             %   \n",
       "3  Binge drinking prevalence among adults aged >=...             %   \n",
       "4  Binge drinking prevalence among adults aged >=...             %   \n",
       "\n",
       "      DataValueType DataValue        ...         HighConfidenceLimit  \\\n",
       "0  Crude Prevalence      16.9        ...                        18.0   \n",
       "1  Crude Prevalence      13.0        ...                        14.1   \n",
       "2  Crude Prevalence      18.2        ...                        20.6   \n",
       "3  Crude Prevalence      15.6        ...                        16.9   \n",
       "4  Crude Prevalence      15.0        ...                        17.2   \n",
       "\n",
       "  StratificationCategory1 Stratification1  \\\n",
       "0                 Overall         Overall   \n",
       "1                 Overall         Overall   \n",
       "2                 Overall         Overall   \n",
       "3                 Overall         Overall   \n",
       "4                 Overall         Overall   \n",
       "\n",
       "                                 GeoLocation  LocationID TopicID QuestionID  \\\n",
       "0                                        NaN          59     ALC     ALC2_2   \n",
       "1    (32.84057112200048, -86.63186076199969)           1     ALC     ALC2_2   \n",
       "2   (64.84507995700051, -147.72205903599973)           2     ALC     ALC2_2   \n",
       "3  (34.865970280000454, -111.76381127699972)           4     ALC     ALC2_2   \n",
       "4    (34.74865012400045, -92.27449074299966)           5     ALC     ALC2_2   \n",
       "\n",
       "  DataValueTypeID  StratificationCategoryID1 StratificationID1  \n",
       "0         CrdPrev                    OVERALL               OVR  \n",
       "1         CrdPrev                    OVERALL               OVR  \n",
       "2         CrdPrev                    OVERALL               OVR  \n",
       "3         CrdPrev                    OVERALL               OVR  \n",
       "4         CrdPrev                    OVERALL               OVR  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usecols = ['YearStart', 'YearEnd', 'LocationAbbr', 'LocationDesc', 'DataSource',\n",
    "       'Topic', 'Question', 'DataValueUnit', 'DataValueType',\n",
    "       'DataValue', 'DataValueAlt', 'DataValueFootnoteSymbol',\n",
    "       'DatavalueFootnote', 'LowConfidenceLimit', 'HighConfidenceLimit',\n",
    "       'StratificationCategory1', 'Stratification1', \n",
    "       'GeoLocation', 'LocationID', 'TopicID', 'QuestionID',\n",
    "       'DataValueTypeID', 'StratificationCategoryID1', 'StratificationID1' ]\n",
    "\n",
    "df = pd.read_csv(\"U.S._Chronic_Disease_Indicators__CDI_.csv\", \n",
    "                 usecols=usecols, dtype={'DataValue': 'object'})\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LocationAbbr</th>\n",
       "      <th>LocationDesc</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LocationID</th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>32.840571</td>\n",
       "      <td>-86.631861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AK</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>64.845080</td>\n",
       "      <td>-147.722059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AZ</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>34.865970</td>\n",
       "      <td>-111.763811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AR</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>34.748650</td>\n",
       "      <td>-92.274491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CA</td>\n",
       "      <td>California</td>\n",
       "      <td>37.638640</td>\n",
       "      <td>-121.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "           LocationAbbr LocationDesc   Latitude   Longitude\n",
       "LocationID                                                 \n",
       "1                    AL      Alabama  32.840571  -86.631861\n",
       "2                    AK       Alaska  64.845080 -147.722059\n",
       "4                    AZ      Arizona  34.865970 -111.763811\n",
       "5                    AR     Arkansas  34.748650  -92.274491\n",
       "6                    CA   California  37.638640 -121.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract location-related attributes into a location table.\n",
    "dfLocs = df[['LocationID', 'GeoLocation', 'LocationAbbr', 'LocationDesc']]\\\n",
    "    .set_index('LocationID').groupby('LocationID').first()\n",
    "\n",
    "# Split GeoLocation string into Latitude and Longitude floats\n",
    "geoLocs = dfLocs['GeoLocation'].str[1:-1].str.split(',', expand=True).astype('float')\n",
    "geoLocs.columns=['Latitude', 'Longitude']\n",
    "# Combine Lat/Long into Locations table, and drop unused column.\n",
    "dfLocs = (pd.concat([dfLocs, geoLocs], axis=1)).drop('GeoLocation', axis=1)\n",
    "dfLocs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Topic</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TopicID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ALC</th>\n",
       "      <td>Alcohol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ART</th>\n",
       "      <td>Arthritis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AST</th>\n",
       "      <td>Asthma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAN</th>\n",
       "      <td>Cancer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CKD</th>\n",
       "      <td>Chronic Kidney Disease</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                          Topic\n",
       "TopicID                        \n",
       "ALC                     Alcohol\n",
       "ART                   Arthritis\n",
       "AST                      Asthma\n",
       "CAN                      Cancer\n",
       "CKD      Chronic Kidney Disease"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract topic attributes into a topic table.\n",
    "dfTopics = df[['TopicID', 'Topic']].groupby('TopicID').first()\n",
    "dfTopics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Question</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QuestionID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ALC10_0</th>\n",
       "      <td>Local authority to regulate alcohol outlet den...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALC1_1</th>\n",
       "      <td>Alcohol use among youth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALC1_2</th>\n",
       "      <td>Alcohol use before pregnancy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALC2_1</th>\n",
       "      <td>Binge drinking prevalence among youth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALC2_2</th>\n",
       "      <td>Binge drinking prevalence among adults aged &gt;=...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     Question\n",
       "QuestionID                                                   \n",
       "ALC10_0     Local authority to regulate alcohol outlet den...\n",
       "ALC1_1                                Alcohol use among youth\n",
       "ALC1_2                           Alcohol use before pregnancy\n",
       "ALC2_1                  Binge drinking prevalence among youth\n",
       "ALC2_2      Binge drinking prevalence among adults aged >=..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract question attributes into a question table.\n",
    "dfQuestions = df[['QuestionID', 'Question']].groupby('QuestionID').first()\n",
    "dfQuestions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stratification1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StratificationID1</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AIAN</th>\n",
       "      <td>American Indian or Alaska Native</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>API</th>\n",
       "      <td>Asian or Pacific Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASN</th>\n",
       "      <td>Asian, non-Hispanic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BLK</th>\n",
       "      <td>Black, non-Hispanic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GENF</th>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GENM</th>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HIS</th>\n",
       "      <td>Hispanic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRC</th>\n",
       "      <td>Multiracial, non-Hispanic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OTH</th>\n",
       "      <td>Other, non-Hispanic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OVR</th>\n",
       "      <td>Overall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHT</th>\n",
       "      <td>White, non-Hispanic</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Stratification1\n",
       "StratificationID1                                  \n",
       "AIAN               American Indian or Alaska Native\n",
       "API                       Asian or Pacific Islander\n",
       "ASN                             Asian, non-Hispanic\n",
       "BLK                             Black, non-Hispanic\n",
       "GENF                                         Female\n",
       "GENM                                           Male\n",
       "HIS                                        Hispanic\n",
       "MRC                       Multiracial, non-Hispanic\n",
       "OTH                             Other, non-Hispanic\n",
       "OVR                                         Overall\n",
       "WHT                             White, non-Hispanic"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract Stratification attributes into a Stratification table.\n",
    "dfStrats = df[['StratificationID1', 'Stratification1']].groupby('StratificationID1').first()\n",
    "dfStrats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StratificationCategory1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StratificationCategoryID1</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GENDER</th>\n",
       "      <td>Gender</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OVERALL</th>\n",
       "      <td>Overall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RACE</th>\n",
       "      <td>Race/Ethnicity</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          StratificationCategory1\n",
       "StratificationCategoryID1                        \n",
       "GENDER                                     Gender\n",
       "OVERALL                                   Overall\n",
       "RACE                               Race/Ethnicity"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract StratificationCategory attributes into a StratificationCategory table.\n",
    "dfStratCats = df[['StratificationCategoryID1', 'StratificationCategory1']] \\\n",
    "    .groupby('StratificationCategoryID1').first()\n",
    "dfStratCats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DataValueType</th>\n",
       "      <th>DataValueUnit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DataValueTypeID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AgeAdjMean</th>\n",
       "      <td>Age-adjusted Mean</td>\n",
       "      <td>Number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AgeAdjPrev</th>\n",
       "      <td>Age-adjusted Prevalence</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AgeAdjRate</th>\n",
       "      <td>Age-adjusted Rate</td>\n",
       "      <td>cases per 10,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AgeSexRaceAdjRate</th>\n",
       "      <td>Adjusted by age, sex, race and ethnicity</td>\n",
       "      <td>cases per 1,000,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AvgAnnAgeAdjRate</th>\n",
       "      <td>Average Annual Age-adjusted Rate</td>\n",
       "      <td>per 100,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AvgAnnCrdRate</th>\n",
       "      <td>Average Annual Crude Rate</td>\n",
       "      <td>per 100,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AvgAnnNmbr</th>\n",
       "      <td>Average Annual Number</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CommHstLiab</th>\n",
       "      <td>Commercial host (dram shop) liability status f...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CrdPrev</th>\n",
       "      <td>Crude Prevalence</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CrdRate</th>\n",
       "      <td>Crude Rate</td>\n",
       "      <td>cases per 10,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LclCntrlAlc</th>\n",
       "      <td>Local control of the regulation of alcohol out...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean</th>\n",
       "      <td>Mean</td>\n",
       "      <td>Number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Median</th>\n",
       "      <td>Median</td>\n",
       "      <td>Number</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nmbr</th>\n",
       "      <td>Number</td>\n",
       "      <td>cases per 1,000,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PerCapAlc</th>\n",
       "      <td>Per capita alcohol consumption</td>\n",
       "      <td>gallons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prct</th>\n",
       "      <td>Percent</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prev</th>\n",
       "      <td>Prevalence</td>\n",
       "      <td>%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USD</th>\n",
       "      <td>US Dollars</td>\n",
       "      <td>$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YesNo</th>\n",
       "      <td>Yes/No</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                       DataValueType  \\\n",
       "DataValueTypeID                                                        \n",
       "AgeAdjMean                                         Age-adjusted Mean   \n",
       "AgeAdjPrev                                   Age-adjusted Prevalence   \n",
       "AgeAdjRate                                         Age-adjusted Rate   \n",
       "AgeSexRaceAdjRate           Adjusted by age, sex, race and ethnicity   \n",
       "AvgAnnAgeAdjRate                    Average Annual Age-adjusted Rate   \n",
       "AvgAnnCrdRate                              Average Annual Crude Rate   \n",
       "AvgAnnNmbr                                     Average Annual Number   \n",
       "CommHstLiab        Commercial host (dram shop) liability status f...   \n",
       "CrdPrev                                             Crude Prevalence   \n",
       "CrdRate                                                   Crude Rate   \n",
       "LclCntrlAlc        Local control of the regulation of alcohol out...   \n",
       "Mean                                                            Mean   \n",
       "Median                                                        Median   \n",
       "Nmbr                                                          Number   \n",
       "PerCapAlc                             Per capita alcohol consumption   \n",
       "Prct                                                         Percent   \n",
       "Prev                                                      Prevalence   \n",
       "USD                                                       US Dollars   \n",
       "YesNo                                                         Yes/No   \n",
       "\n",
       "                         DataValueUnit  \n",
       "DataValueTypeID                         \n",
       "AgeAdjMean                      Number  \n",
       "AgeAdjPrev                           %  \n",
       "AgeAdjRate            cases per 10,000  \n",
       "AgeSexRaceAdjRate  cases per 1,000,000  \n",
       "AvgAnnAgeAdjRate           per 100,000  \n",
       "AvgAnnCrdRate              per 100,000  \n",
       "AvgAnnNmbr                         NaN  \n",
       "CommHstLiab                        NaN  \n",
       "CrdPrev                              %  \n",
       "CrdRate               cases per 10,000  \n",
       "LclCntrlAlc                        NaN  \n",
       "Mean                            Number  \n",
       "Median                          Number  \n",
       "Nmbr               cases per 1,000,000  \n",
       "PerCapAlc                      gallons  \n",
       "Prct                                 %  \n",
       "Prev                                 %  \n",
       "USD                                  $  \n",
       "YesNo                              NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract DataValueType attributes into a DataValueType table.\n",
    "dfDataValueTypes = df[['DataValueTypeID', 'DataValueType', 'DataValueUnit']]\\\n",
    "    .groupby('DataValueTypeID').first()\n",
    "dfDataValueTypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th>DataSource</th>\n",
       "      <th>DataValue</th>\n",
       "      <th>DataValueAlt</th>\n",
       "      <th>DataValueFootnoteSymbol</th>\n",
       "      <th>DatavalueFootnote</th>\n",
       "      <th>LowConfidenceLimit</th>\n",
       "      <th>HighConfidenceLimit</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>TopicID</th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DataValueTypeID</th>\n",
       "      <th>StratificationCategoryID1</th>\n",
       "      <th>StratificationID1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>16.9</td>\n",
       "      <td>16.9</td>\n",
       "      <td>*</td>\n",
       "      <td>50 States + DC: US Median</td>\n",
       "      <td>16.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>59</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.9</td>\n",
       "      <td>14.1</td>\n",
       "      <td>1</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>18.2</td>\n",
       "      <td>18.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>20.6</td>\n",
       "      <td>2</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>15.6</td>\n",
       "      <td>15.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>16.9</td>\n",
       "      <td>4</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>BRFSS</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>17.2</td>\n",
       "      <td>5</td>\n",
       "      <td>ALC</td>\n",
       "      <td>ALC2_2</td>\n",
       "      <td>CrdPrev</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YearStart  YearEnd DataSource DataValue  DataValueAlt  \\\n",
       "0       2016     2016      BRFSS      16.9          16.9   \n",
       "1       2016     2016      BRFSS      13.0          13.0   \n",
       "2       2016     2016      BRFSS      18.2          18.2   \n",
       "3       2016     2016      BRFSS      15.6          15.6   \n",
       "4       2016     2016      BRFSS      15.0          15.0   \n",
       "\n",
       "  DataValueFootnoteSymbol          DatavalueFootnote  LowConfidenceLimit  \\\n",
       "0                       *  50 States + DC: US Median                16.0   \n",
       "1                     NaN                        NaN                11.9   \n",
       "2                     NaN                        NaN                16.0   \n",
       "3                     NaN                        NaN                14.3   \n",
       "4                     NaN                        NaN                13.0   \n",
       "\n",
       "   HighConfidenceLimit  LocationID TopicID QuestionID DataValueTypeID  \\\n",
       "0                 18.0          59     ALC     ALC2_2         CrdPrev   \n",
       "1                 14.1           1     ALC     ALC2_2         CrdPrev   \n",
       "2                 20.6           2     ALC     ALC2_2         CrdPrev   \n",
       "3                 16.9           4     ALC     ALC2_2         CrdPrev   \n",
       "4                 17.2           5     ALC     ALC2_2         CrdPrev   \n",
       "\n",
       "  StratificationCategoryID1 StratificationID1  \n",
       "0                   OVERALL               OVR  \n",
       "1                   OVERALL               OVR  \n",
       "2                   OVERALL               OVR  \n",
       "3                   OVERALL               OVR  \n",
       "4                   OVERALL               OVR  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfData = df.drop(['GeoLocation', 'LocationAbbr', 'LocationDesc', 'Topic', 'Question', \n",
    "    'Stratification1', 'StratificationCategory1', 'DataValueType', 'DataValueUnit'], axis=1)\n",
    "dfData.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CrdPrev: 53.6%; 17152 / 32012\n",
      "AgeAdjPrev: 54.5%; 16352 / 30007\n",
      "Nmbr: 58.3%; 3396 / 5830\n",
      "AgeAdjRate: 58.3%; 3396 / 5830\n",
      "CrdRate: 58.3%; 3396 / 5830\n",
      "Prev: 100.0%; 52 / 52\n"
     ]
    }
   ],
   "source": [
    "dfDia = dfData[dfData[\"TopicID\"] == 'DIA']\n",
    "types = dfDia['DataValueTypeID'].value_counts().index\n",
    "for t in types:\n",
    "    n = dfDia[dfDia['DataValueTypeID'] == t]['DataValueAlt'].notnull()\n",
    "    print(\"%s: %0.1f%%; %d / %d\" % (t, 100 * n.sum() / n.count(), n.sum(), n.count()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DIA1_2: 36.1%; 2214 / 6135\n",
      "DIA1_1: 81.5%; 4998 / 6135\n",
      "DIA11_3: 60.1%; 3136 / 5220\n",
      "DIA12_2: 56.8%; 2965 / 5220\n",
      "DIA12_1: 59.5%; 3106 / 5220\n",
      "DIA2_1: 81.3%; 4242 / 5220\n",
      "DIA13_2: 56.2%; 2934 / 5220\n",
      "DIA13_1: 58.5%; 3052 / 5220\n",
      "DIA6_0: 38.8%; 2024 / 5216\n",
      "DIA5_0: 39.2%; 2045 / 5216\n",
      "DIA10_0: 39.3%; 2052 / 5216\n",
      "DIA7_0: 39.3%; 2050 / 5216\n",
      "DIA11_2: 65.3%; 1704 / 2610\n",
      "DIA11_1: 64.5%; 1683 / 2610\n",
      "DIA9_0: 64.1%; 1674 / 2610\n",
      "DIA8_0: 65.1%; 1699 / 2610\n",
      "DIA4_0: 49.9%; 1302 / 2610\n",
      "DIA2_2: 40.5%; 789 / 1950\n",
      "DIA3_1: 41.8%; 23 / 55\n",
      "DIA3_2: 100.0%; 52 / 52\n"
     ]
    }
   ],
   "source": [
    "qs = dfDia['QuestionID'].value_counts().index\n",
    "for q in qs:\n",
    "    n = dfDia[dfDia['QuestionID'] == q]['DataValueAlt'].notnull()\n",
    "    print(\"%s: %0.1f%%; %d / %d\" % (q, 100 * n.sum() / n.count(), n.sum(), n.count()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def notNullHeatMap(df, cmap=\"Blues\", columns='DataValueTypeID', figsize=(12,6)):\n",
    "    usable = pd.pivot_table(df, index='QuestionID', columns=columns, values='DataValueAlt', \n",
    "                   aggfunc=lambda x: sum(x.notnull()))\n",
    "    # Strip off 'DIA' prefix\n",
    "    usable.index = usable.index.str[3:]\n",
    "    fig, ax = plt.subplots(figsize=figsize)   \n",
    "    _ = sns.heatmap(usable, cmap=cmap, annot=True, fmt='g', ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fBxi9iIgUx8wGA52A2maWAdwDDAAGhMcJbQN6eGhQwXQzG0JoAFMOcKO754aP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\nljonpWZmZmaWOielZmZmZpa6/w8S6Kvs4zuEDQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a13659f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullHeatMap(dfDia, \"Greens\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No data available    32\n",
       "Name: DatavalueFootnote, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDia[dfDia['QuestionID'] == 'DIA3_1']['DatavalueFootnote'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dfDia[(dfDia['QuestionID'] == 'DIA3_2') & dfDia['DataValueAlt'].notnull()]['LocationID'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                                          4983\n",
       "Data not shown because of too few respondents or cases    1137\n",
       "Name: DatavalueFootnote, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDia[dfDia['QuestionID'] == 'DIA1_1']['DatavalueFootnote'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TgLPL2H9aibezgJpmlu7u+VUZZ7wwYPBfx2MG5x7dmV8d3WWHz1+bPJ+Ts9sG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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x102c8c5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullHeatMap(dfDia[dfDia['StratificationCategoryID1'] == 'RACE'], \"Oranges\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3HhkxkblfZQJw9s1HMPLBkxje/CFy1m8F4Lq/DOLwQR3ZnreDh658m4XfrQ4y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\nWVb8P3Fog6Rbnc6ZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x102cc59b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullHeatMap(dfDia[dfDia['StratificationCategoryID1'] == 'GENDER'], \"Purples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fXnyxfAUnDx5Al76nM7b/ICoO8Gp5eMfy14f2OJZwvXps3bhpj+OKpFp1bfmU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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0bdaa320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullHeatMap(dfDia[dfDia['StratificationCategoryID1'] == 'OVERALL'], \"Reds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th>DataSource</th>\n",
       "      <th>DataValue</th>\n",
       "      <th>DataValueAlt</th>\n",
       "      <th>DataValueFootnoteSymbol</th>\n",
       "      <th>DatavalueFootnote</th>\n",
       "      <th>LowConfidenceLimit</th>\n",
       "      <th>HighConfidenceLimit</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>TopicID</th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DataValueTypeID</th>\n",
       "      <th>StratificationCategoryID1</th>\n",
       "      <th>StratificationID1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>133199</th>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>State Inpatient Data</td>\n",
       "      <td>1.76</td>\n",
       "      <td>1.76</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.65</td>\n",
       "      <td>1.86</td>\n",
       "      <td>8</td>\n",
       "      <td>DIA</td>\n",
       "      <td>DIA4_0</td>\n",
       "      <td>AgeAdjRate</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133398</th>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>State Inpatient Data</td>\n",
       "      <td>1.87</td>\n",
       "      <td>1.87</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.76</td>\n",
       "      <td>1.99</td>\n",
       "      <td>8</td>\n",
       "      <td>DIA</td>\n",
       "      <td>DIA4_0</td>\n",
       "      <td>CrdRate</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133599</th>\n",
       "      <td>2013</td>\n",
       "      <td>2013</td>\n",
       "      <td>State Inpatient Data</td>\n",
       "      <td>988</td>\n",
       "      <td>988.00</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>DIA</td>\n",
       "      <td>DIA4_0</td>\n",
       "      <td>Nmbr</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257444</th>\n",
       "      <td>2010</td>\n",
       "      <td>2010</td>\n",
       "      <td>State Inpatient Data</td>\n",
       "      <td>1.74</td>\n",
       "      <td>1.74</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.86</td>\n",
       "      <td>8</td>\n",
       "      <td>DIA</td>\n",
       "      <td>DIA4_0</td>\n",
       "      <td>AgeAdjRate</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257685</th>\n",
       "      <td>2010</td>\n",
       "      <td>2010</td>\n",
       "      <td>State Inpatient Data</td>\n",
       "      <td>1.76</td>\n",
       "      <td>1.76</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1.64</td>\n",
       "      <td>1.87</td>\n",
       "      <td>8</td>\n",
       "      <td>DIA</td>\n",
       "      <td>DIA4_0</td>\n",
       "      <td>CrdRate</td>\n",
       "      <td>OVERALL</td>\n",
       "      <td>OVR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        YearStart  YearEnd            DataSource DataValue  DataValueAlt  \\\n",
       "133199       2013     2013  State Inpatient Data      1.76          1.76   \n",
       "133398       2013     2013  State Inpatient Data      1.87          1.87   \n",
       "133599       2013     2013  State Inpatient Data       988        988.00   \n",
       "257444       2010     2010  State Inpatient Data      1.74          1.74   \n",
       "257685       2010     2010  State Inpatient Data      1.76          1.76   \n",
       "\n",
       "       DataValueFootnoteSymbol DatavalueFootnote  LowConfidenceLimit  \\\n",
       "133199                                                          1.65   \n",
       "133398                                                          1.76   \n",
       "133599                                                           NaN   \n",
       "257444                                                          1.63   \n",
       "257685                                                          1.64   \n",
       "\n",
       "        HighConfidenceLimit  LocationID TopicID QuestionID DataValueTypeID  \\\n",
       "133199                 1.86           8     DIA     DIA4_0      AgeAdjRate   \n",
       "133398                 1.99           8     DIA     DIA4_0         CrdRate   \n",
       "133599                  NaN           8     DIA     DIA4_0            Nmbr   \n",
       "257444                 1.86           8     DIA     DIA4_0      AgeAdjRate   \n",
       "257685                 1.87           8     DIA     DIA4_0         CrdRate   \n",
       "\n",
       "       StratificationCategoryID1 StratificationID1  \n",
       "133199                   OVERALL               OVR  \n",
       "133398                   OVERALL               OVR  \n",
       "133599                   OVERALL               OVR  \n",
       "257444                   OVERALL               OVR  \n",
       "257685                   OVERALL               OVR  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDia[(dfDia['QuestionID'] == 'DIA4_0') & dfDia['DataValueAlt'].notnull() &\n",
    "      (dfDia['LocationID'] == 8) & (dfDia['StratificationCategoryID1'] == 'OVERALL')].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KzWwYcBLQwMwyCFRETzOzDkAhsJySZ95jZk2AaUBtoNDMbgEO2WOylIiIiEiV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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0bd7d358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfOneType = dfDia[(dfDia['QuestionID'] != 'DIA3_1') &\n",
    "                   dfDia['DataValueTypeID'].isin(['CrdPrev', 'CrdRate', 'Prev'])]\n",
    "notNullHeatMap(dfOneType)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def notNullBarChart(df, cmap=\"Blues\", figsize=(12, 6)):\n",
    "    fig, ax = plt.subplots(figsize=figsize)\n",
    "    plt.barh(df.columns, df.notnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def corrHeatMap(df, figsize=(20,20)):\n",
    "    corr = df.corr(method='pearson')\n",
    "    mask = np.zeros_like(corr, dtype=np.bool)\n",
    "    mask[np.triu_indices_from(mask)] = True\n",
    "    corr_cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "    fig, ax = plt.subplots(figsize=figsize)     \n",
    "    _ = sns.heatmap(corr, mask=mask, cmap=corr_cmap, annot=True, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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13Q2TrAQ2Ad9Jsr6qpjrqfgD4Jdov5ZlTkpfRfoX9y4EfAj6b5IeraqbP85AkSZKGYmBL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\nJGmI/n+Nh2pJ+PZMAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0f0d6e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sparsePivot = pd.pivot_table(dfOneType, index=['StratificationCategoryID1', 'StratificationID1',\n",
    "                                               'LocationID', 'YearStart', 'YearEnd'], \n",
    "                             columns='QuestionID', values='DataValueAlt')\n",
    "sparsePivot = sparsePivot[sparsePivot.notnull().sum(axis=1) > 0]\n",
    "notNullBarChart(sparsePivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DIA10_0</th>\n",
       "      <th>DIA11_1</th>\n",
       "      <th>DIA11_2</th>\n",
       "      <th>DIA11_3</th>\n",
       "      <th>DIA12_1</th>\n",
       "      <th>DIA12_2</th>\n",
       "      <th>DIA13_1</th>\n",
       "      <th>DIA13_2</th>\n",
       "      <th>DIA1_1</th>\n",
       "      <th>DIA1_2</th>\n",
       "      <th>DIA2_1</th>\n",
       "      <th>DIA2_2</th>\n",
       "      <th>DIA3_2</th>\n",
       "      <th>DIA4_0</th>\n",
       "      <th>DIA5_0</th>\n",
       "      <th>DIA6_0</th>\n",
       "      <th>DIA7_0</th>\n",
       "      <th>DIA8_0</th>\n",
       "      <th>DIA9_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StratificationCategoryID1</th>\n",
       "      <th>StratificationID1</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">GENDER</th>\n",
       "      <th rowspan=\"10\" valign=\"top\">GENF</th>\n",
       "      <th rowspan=\"7\" valign=\"top\">1</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <th>2011</th>\n",
       "      <td>52.7</td>\n",
       "      <td>72.9</td>\n",
       "      <td>78.1</td>\n",
       "      <td>33.8</td>\n",
       "      <td>45.9</td>\n",
       "      <td>66.6</td>\n",
       "      <td>48.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>79.3</td>\n",
       "      <td>1.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65.5</td>\n",
       "      <td>72.3</td>\n",
       "      <td>63.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <th>2012</th>\n",
       "      <td>55.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.7</td>\n",
       "      <td>50.9</td>\n",
       "      <td>66.0</td>\n",
       "      <td>44.8</td>\n",
       "      <td>78.6</td>\n",
       "      <td>76.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.3</td>\n",
       "      <td>75.5</td>\n",
       "      <td>62.0</td>\n",
       "      <td>48.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>2013</th>\n",
       "      <td>54.2</td>\n",
       "      <td>70.1</td>\n",
       "      <td>79.4</td>\n",
       "      <td>35.4</td>\n",
       "      <td>50.8</td>\n",
       "      <td>59.8</td>\n",
       "      <td>48.3</td>\n",
       "      <td>75.0</td>\n",
       "      <td>74.3</td>\n",
       "      <td>1.7</td>\n",
       "      <td>14.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.5</td>\n",
       "      <td>73.2</td>\n",
       "      <td>68.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.3</td>\n",
       "      <td>50.4</td>\n",
       "      <td>70.2</td>\n",
       "      <td>43.9</td>\n",
       "      <td>76.8</td>\n",
       "      <td>65.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <th>2015</th>\n",
       "      <td>NaN</td>\n",
       "      <td>67.9</td>\n",
       "      <td>78.6</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.0</td>\n",
       "      <td>60.4</td>\n",
       "      <td>47.5</td>\n",
       "      <td>74.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <th>2016</th>\n",
       "      <td>54.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.1</td>\n",
       "      <td>39.7</td>\n",
       "      <td>59.3</td>\n",
       "      <td>51.3</td>\n",
       "      <td>79.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.4</td>\n",
       "      <td>71.8</td>\n",
       "      <td>63.9</td>\n",
       "      <td>53.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <th>2011</th>\n",
       "      <td>64.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>77.2</td>\n",
       "      <td>43.6</td>\n",
       "      <td>43.9</td>\n",
       "      <td>56.4</td>\n",
       "      <td>63.1</td>\n",
       "      <td>73.7</td>\n",
       "      <td>41.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.1</td>\n",
       "      <td>61.8</td>\n",
       "      <td>67.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <th>2012</th>\n",
       "      <td>77.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.4</td>\n",
       "      <td>36.7</td>\n",
       "      <td>66.5</td>\n",
       "      <td>41.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>49.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71.4</td>\n",
       "      <td>74.4</td>\n",
       "      <td>67.7</td>\n",
       "      <td>61.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "QuestionID                                                                DIA10_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        52.7   \n",
       "                                                       2012      2012        55.3   \n",
       "                                                       2013      2013        54.2   \n",
       "                                                       2014      2014         NaN   \n",
       "                                                       2015      2015         NaN   \n",
       "                                                       2016      2016        54.8   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        64.5   \n",
       "                                                       2012      2012        77.9   \n",
       "\n",
       "QuestionID                                                                DIA11_1  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        72.9   \n",
       "                                                       2012      2012         NaN   \n",
       "                                                       2013      2013        70.1   \n",
       "                                                       2014      2014         NaN   \n",
       "                                                       2015      2015        67.9   \n",
       "                                                       2016      2016         NaN   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        59.0   \n",
       "                                                       2012      2012         NaN   \n",
       "\n",
       "QuestionID                                                                DIA11_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        78.1   \n",
       "                                                       2012      2012         NaN   \n",
       "                                                       2013      2013        79.4   \n",
       "                                                       2014      2014         NaN   \n",
       "                                                       2015      2015        78.6   \n",
       "                                                       2016      2016         NaN   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        77.2   \n",
       "                                                       2012      2012         NaN   \n",
       "\n",
       "QuestionID                                                                DIA11_3  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        33.8   \n",
       "                                                       2012      2012        36.7   \n",
       "                                                       2013      2013        35.4   \n",
       "                                                       2014      2014        35.3   \n",
       "                                                       2015      2015        38.5   \n",
       "                                                       2016      2016        40.1   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        43.6   \n",
       "                                                       2012      2012        34.4   \n",
       "\n",
       "QuestionID                                                                DIA12_1  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        45.9   \n",
       "                                                       2012      2012        50.9   \n",
       "                                                       2013      2013        50.8   \n",
       "                                                       2014      2014        50.4   \n",
       "                                                       2015      2015        52.0   \n",
       "                                                       2016      2016        39.7   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        43.9   \n",
       "                                                       2012      2012        36.7   \n",
       "\n",
       "QuestionID                                                                DIA12_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        66.6   \n",
       "                                                       2012      2012        66.0   \n",
       "                                                       2013      2013        59.8   \n",
       "                                                       2014      2014        70.2   \n",
       "                                                       2015      2015        60.4   \n",
       "                                                       2016      2016        59.3   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        56.4   \n",
       "                                                       2012      2012        66.5   \n",
       "\n",
       "QuestionID                                                                DIA13_1  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        48.0   \n",
       "                                                       2012      2012        44.8   \n",
       "                                                       2013      2013        48.3   \n",
       "                                                       2014      2014        43.9   \n",
       "                                                       2015      2015        47.5   \n",
       "                                                       2016      2016        51.3   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        63.1   \n",
       "                                                       2012      2012        41.6   \n",
       "\n",
       "QuestionID                                                                DIA13_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd            \n",
       "GENDER                    GENF              1          2010      2010         NaN   \n",
       "                                                       2011      2011        76.7   \n",
       "                                                       2012      2012        78.6   \n",
       "                                                       2013      2013        75.0   \n",
       "                                                       2014      2014        76.8   \n",
       "                                                       2015      2015        74.1   \n",
       "                                                       2016      2016        79.0   \n",
       "                                            2          2010      2010         NaN   \n",
       "                                                       2011      2011        73.7   \n",
       "                                                       2012      2012        86.3   \n",
       "\n",
       "QuestionID                                                                DIA1_1  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010       85.1   \n",
       "                                                       2011      2011       79.3   \n",
       "                                                       2012      2012       76.2   \n",
       "                                                       2013      2013       74.3   \n",
       "                                                       2014      2014       65.8   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016        NaN   \n",
       "                                            2          2010      2010       36.4   \n",
       "                                                       2011      2011       41.6   \n",
       "                                                       2012      2012       49.3   \n",
       "\n",
       "QuestionID                                                                DIA1_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        1.4   \n",
       "                                                       2011      2011        1.4   \n",
       "                                                       2012      2012        1.3   \n",
       "                                                       2013      2013        1.7   \n",
       "                                                       2014      2014        1.5   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016        NaN   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "\n",
       "QuestionID                                                                DIA2_1  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011       12.5   \n",
       "                                                       2012      2012       12.0   \n",
       "                                                       2013      2013       14.1   \n",
       "                                                       2014      2014       13.0   \n",
       "                                                       2015      2015       14.0   \n",
       "                                                       2016      2016       14.4   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        8.2   \n",
       "                                                       2012      2012        7.4   \n",
       "\n",
       "QuestionID                                                                DIA2_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "                                                       2013      2013        NaN   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016        NaN   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "\n",
       "QuestionID                                                                DIA3_2  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "                                                       2013      2013        NaN   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016        NaN   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "\n",
       "QuestionID                                                                DIA4_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "                                                       2013      2013        NaN   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016        NaN   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012        NaN   \n",
       "\n",
       "QuestionID                                                                DIA5_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011       65.5   \n",
       "                                                       2012      2012       66.3   \n",
       "                                                       2013      2013       69.5   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016       68.4   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011       72.1   \n",
       "                                                       2012      2012       71.4   \n",
       "\n",
       "QuestionID                                                                DIA6_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011       72.3   \n",
       "                                                       2012      2012       75.5   \n",
       "                                                       2013      2013       73.2   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016       71.8   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011       61.8   \n",
       "                                                       2012      2012       74.4   \n",
       "\n",
       "QuestionID                                                                DIA7_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011       63.5   \n",
       "                                                       2012      2012       62.0   \n",
       "                                                       2013      2013       68.9   \n",
       "                                                       2014      2014        NaN   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016       63.9   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011       67.2   \n",
       "                                                       2012      2012       67.7   \n",
       "\n",
       "QuestionID                                                                DIA8_0  \\\n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd           \n",
       "GENDER                    GENF              1          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012       48.2   \n",
       "                                                       2013      2013        NaN   \n",
       "                                                       2014      2014       49.2   \n",
       "                                                       2015      2015        NaN   \n",
       "                                                       2016      2016       53.8   \n",
       "                                            2          2010      2010        NaN   \n",
       "                                                       2011      2011        NaN   \n",
       "                                                       2012      2012       61.4   \n",
       "\n",
       "QuestionID                                                                DIA9_0  \n",
       "StratificationCategoryID1 StratificationID1 LocationID YearStart YearEnd          \n",
       "GENDER                    GENF              1          2010      2010        NaN  \n",
       "                                                       2011      2011        NaN  \n",
       "                                                       2012      2012        NaN  \n",
       "                                                       2013      2013        NaN  \n",
       "                                                       2014      2014        NaN  \n",
       "                                                       2015      2015        NaN  \n",
       "                                                       2016      2016        NaN  \n",
       "                                            2          2010      2010        NaN  \n",
       "                                                       2011      2011        NaN  \n",
       "                                                       2012      2012        NaN  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparsePivot.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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n5xn/b2nfAPqvlxK3JEmSNCoW8xSUlUn2AicD08AtwPWdA5K0gDOBB460VdVk\nkmeTbKF98+XttHfI35Dk3VV1HvADwP+ZpGiXtfx6Ve2fLYgkG4BfBv4WeKi5B/SGqvrdxZ+uJEmS\nNFwLJuBVtWKevt3A7uZw/Sz9mzsOj3piSVXdC7xyoRiasQeYpfZckiRJOp74JkxJkiRpgBZTgjJw\nST5F+7ngnd48V3nKfDauX8XEdZf1JzBJkiSpRyOZgFfVlmHHIEmSJC0HS1AkSZKkARrJHfB+2v/U\nIVrX3j3sMCRJkrQMpo7DUmN3wCVJkqQBMgGXJEmSBmjBBDzJTJK9SR5J8nCSa5Kc1PRdlOSurvF3\nJNnT1XZhkoeSTCe5oqP95Uke7Jj/ZxeI5X1Jnkzy9aWdpiRJkjQaFrMD/lxVbWreXHkxcCmwc7aB\nSVYDm4HVSc7q6HoCuBq4tesnXwL+SVVtArYA1yb53nliuRN49SJiliRJkkbSkkpQquogsB3YkeZd\n8F0up50k7wKu7PjdVFXto/1K+s75/qGqnm8OX7hQPFX1QFV9aSkxS5IkSaNkyTXgVfV487t1s3SP\nA7c1n/HFzJfkjCT7gCeBX62qp5ca0yxzbk8ykWRi5vChXqeTJEmS+uZYb8I8avc7yWnAOcD9VfUo\nMJ3k/IUmqqonq+qVzW+vaubpSVXdVFVjVTW24tRVvU4nSZIk9c2SE/AkZwMzwMGurm3AGmAyyRTQ\noqMMZSHNzvcjwGuXGpMkSZJ0vFhSAp5kLXAjcENVVVf3OLC1qlpV1QIuYIEEPMmGJCub72uA1wCf\nX0pMkiRJ0vFkMQn4yiOPCQQ+Dvw58O7OAUlawJnAA0faqmoSeDbJliQ/lOQA8JPA7zRzAfwA8Kkk\nDwP/D/DrVbV/rkCS/Fozz6lJDiT5lUWepyRJkjQSFnwVfVWtmKdvN7C7OVw/S//mjsMNs/TfC7xy\noRg6xv8S8EuLHS9JkiSNmgUT8OPdxvWrmLjusmGHIUmSJAEjmoAn+RTt54J3evN85SmSJEnS8WAk\nE/Cq2jLsGCRJkqTlMJIJeD/tf+oQrWvvHnYYkiRJWoKpE7iE+FhfxCNJkiTpGJiAS5IkSQNkAi5J\nkiQN0IIJeJKZIy/iSfJwkmuSnNT0XZTkrq7xdyTZ09V2YZKHkkwnuaKjfVOSPc3c+5JsWyCWP0ry\n+SSfTXJzkpOXdrqSJEnScC1mB/y5qtpUVecBFwOXAjtnG5hkNbAZWJ3krI6uJ4CrgVu7fnIYeEsz\n91bgA80cc/kj4PuBjcBK4GcWEb8kSZI0MpZUglJVB4HtwI4kmWXI5cCdwC7gyo7fTVXVPuAbXfM9\nWlWPNd+fBg4Ca+dZ/0+rAfx3YA6iAAASZklEQVQ1s7xdU5IkSRplS64Br6rHm9+tm6V7HLit+Ywv\nZd4krwZOAb64iLEnA28GPjZH//YkE0kmZg4fWkoYkiRJ0rI61pswj9r9TnIacA5wf1U9CkwnOX9R\nkyWnA7cAb62qbyw0HvgPwF9W1Sdn66yqm6pqrKrGVpy6ajEhSJIkSQOx5AQ8ydnADO1ykU7bgDXA\nZJIpoEVHGco8870YuBt4V1U9sIjxO2mXqVyzpMAlSZKkEbCkBDzJWuBG4IamDrvTOLC1qlpV1QIu\nYIEEPMkpwO3AB6vqw4tY/2eA1wPji9wplyRJkkbKYl5FvzLJXuBkYJp2qcj1nQOStIAzgW/uYFfV\nZJJnk2yhffPl7bR3yN+Q5N3Nk09+CrgQeGmSq5ufXl1Ve+eI5Ubg74A9zT2gf1JV71nEOUiSJEkj\nYcEEvKpWzNO3G9jdHK6fpX9zx+FRTyypqj8E/nChGDrGL+Y/GCRJkqSRdcIntBvXr2LiusuGHYYk\nSZIEjGgCnuR24Kyu5ndU1T3DiEeSJEnql5FMwKvqTcOOQZIkSVoOI5mA99P+pw7RuvbuYYchSZKk\nZTB1HJYaH+uLeCRJkiQdAxNwSZIkaYBMwCVJkqQBWjABTzKTZG+SR5I8nOSaJCc1fRcluatr/B1J\n9nS1XZjkoSTTSa7oaN+UZE8z974k2xaIZUeSLySpJC9b2qlKkiRJw7eYHfDnqmpT8+bKi4FLgZ2z\nDUyyGtgMrE7S+RjBJ4CrgVu7fnIYeEsz91bgA80cc/kr4HW034YpSZIkHXeWVIJSVQeB7cCONO+C\n73I5cCewC7iy43dTVbWP9ivpO+d7tKoea74/DRwE1s6z/meqamopMUuSJEmjZMk14FX1ePO7dbN0\njwO3NZ/xpcyb5NXAKcAXlxrTLHNtTzKRZGLm8KFep5MkSZL65lhvwjxq9zvJacA5wP1V9SgwneT8\nRU2WnA7cAry1qr6x0PiFVNVNVTVWVWMrTl3V63SSJElS3yw5AU9yNjBDu1yk0zZgDTCZZApo0VGG\nMs98LwbuBt5VVQ8sNR5JkiTpeLKkBDzJWuBG4Iaqqq7ucWBrVbWqqgVcwAIJeJJTgNuBD1bVh5cS\niyRJknQ8WkwCvvLIYwiBjwN/Dry7c0CSFnAm8M0d7KqaBJ5NsiXJDyU5APwk8DvNXAA/BVwIXN2s\nsTfJprkCSfJzzTwbgH1JfnexJypJkiSNghy9kX1ieeHp59bpV31g2GFIkiRpGUxdd9mwQwAgyYNV\nNbaYsS9Y7mCGbeP6VUyMyIWRJEmSRjIBT3I7cFZX8zuq6p5hxCNJkiT1y0gm4FX1pmHHIEmSJC2H\nkUzA+2n/U4doXXv3sMOQJElSj0al3rtXx/oiHkmSJEnHwARckiRJGqAFE/AkM0eeA57k4STXJDmp\n6bsoyV1d4+9Isqer7cIkDyWZTnJFV9/Hkny1e545Yvm9JoZ9ST6S5EWLO01JkiRpNCxmB/y5qtpU\nVecBFwOXAjtnG5hkNbAZWJ2k8ykmTwBXA7fO8rP3A29eZLw/X1U/WFWvbObcscjfSZIkSSNhSSUo\nVXUQ2A7sSJJZhlwO3AnsouM19FU1VVX7gG/MMud9wNcWuf6zAM3aK4ET+y1CkiRJOuEsuQa8qh5v\nfrdulu5x4LbmM95baLNL8p+A/wJ8P/Dv5xizPclEkomZw4eWIwxJkiTpmBzrTZhH7X4nOQ04B7i/\nqh4FppOc30tws6mqtwLfC/wNsG2OMTdV1VhVja04dVW/Q5AkSZKO2ZIT8CRnAzPAwa6ubcAaYDLJ\nFNCiowyln6pqBvhj2iUvkiRJ0nFjSQl4krXAjcANVdVdfz0ObK2qVlW1gAvoYwKetnOOfAfeAPxt\nv+aXJEmSBmExb8JcmWQvcDIwDdwCXN85IEkLOBN44EhbVU0meTbJFto3X95Oe4f8DUne3TxVhSSf\npF3P/aIkB4C3VdU9s8QR4A+SvLj5/jDwL5ZwrpIkSdLQLZiAV9WKefp2A7ubw/Wz9G/uONwwxxyv\nXSiGZtw3gNcsZqwkSZI0qnwTpiRJkjRAiylBGbgktwNndTW/Y47SlHltXL+Kiesu609gkiRJUo9G\nMgGvqjcNOwZJkiRpOViCIkmSJA3QSO6A99P+pw7RuvbuYYchSQMzZdmdJI00d8AlSZKkATIBlyRJ\nkgZowQQ8yUySvUkeSfJwkmuSnNT0XZTkrq7xdyTZ09V2YZKHkkwnuaKr72NJvto9zxyx/FGSzyf5\nbJKbk5y8uNOUJEmSRsNidsCfq6pNzZsrLwYuBXbONjDJamAzsDpJ52MEnwCuBm6d5WfvB968yHj/\niPZbMzcCK4GfWeTvJEmSpJGwpBKUqjoIbAd2JMksQy4H7gR2AVd2/G6qqvbRfiV995z3AV9b5Pp/\nWg3gr5nj7ZqSJEnSqFpyDXhVPd78bt0s3ePAbc1nvLfQ5taUnrwZ+Ngc/duTTCSZmDl8aLnCkCRJ\nkpbsWG/CPGr3O8lpwDnA/VX1KDCd5PxegpvHfwD+sqo+OVtnVd1UVWNVNbbi1FXLFIIkSZK0dEtO\nwJOcDcwAB7u6tgFrgMkkU0CLjjKUfkmyE1gLXNPvuSVJkqTltqQEPMla4EbghqYOu9M4sLWqWlXV\nAi6gzwl4kp8BXg+MV9VR9eSSJEnSqFvMmzBXJtkLnAxMA7cA13cOSNICzgQeONJWVZNJnk2yhfbN\nl7fT3iF/Q5J3N09VIcknaT/Z5EVJDgBvq6p75ojlRuDvgD3NPaB/UlXvWeS5SpIkSUO3YAJeVSvm\n6dsN7G4O18/Sv7njcNYnllTVaxeKoWPsYv6DQZIkSRpZJ3xCu3H9Kiauu2zYYUiSJEnAiCbgSW4H\nzupqfsc8pSmSJEnScWEkE/CqetOwY5AkSZKWw7E+B1ySJEnSMRjJHfB+2v/UIVrX3j3sMCRpYKa8\n70WSRpo74JIkSdIAmYBLkiRJA7RgAp5kJsneJI8keTjJNUlOavouSnJX1/g7kuzparswyUNJppNc\n0dX3sSRf7Z5njlh2JPlCkkryssWdoiRJkjQ6FrMD/lxVbWreXHkxcCmwc7aBSVYDm4HVSTofI/gE\ncDVw6yw/ez/w5kXG+1fA62i/DVOSJEk67iypBKWqDgLbgR1p3gXf5XLgTmAXcGXH76aqah/tV9J3\nz3kf8LVFrv+ZqppaSsySJEnSKFlyDXhVPd78bt0s3ePAbc1nvLfQjl2S7UkmkkzMHD40rDAkSZKk\noxzrTZhH7X4nOQ04B7i/qh4FppOc30twx6qqbqqqsaoaW3HqqmGEIEmSJM1qyQl4krOBGeBgV9c2\nYA0wmWQKaNFRhiJJkiRpiQl4krXAjcANVVVd3ePA1qpqVVULuAATcEmSJOnbLCYBX3nkMYTAx4E/\nB97dOSBJCzgTeOBIW1VNAs8m2ZLkh5IcAH4S+J1mriO//STwYeDHkhxI8vq5Aknyc808G4B9SX53\nkecpSZIkjYQFX0VfVSvm6dsN7G4O18/Sv7njcMMcc7x2oRg6xv4m8JuLHS9JkiSNmgUT8OPdxvWr\nmLjusmGHIUmSJAEjmoAnuR04q6v5HVV1zzDikSRJkvplJBPwqnrTsGOQJEmSlsNIJuD9tP+pQ7Su\nvXvYYUiSjhNTli1KWmbH+iIeSZIkScfABFySJEkaIBNwSZIkaYAWTMCTzBx5EU+Sh5Nck+Skpu+i\nJHd1jb8jyZ6utguTPJRkOskVXX1XJXms+Vy1QCwXJNmf5AtJfjNJFn+qkiRJ0vAtZgf8uaraVFXn\nARcDlwI7ZxuYZDWwGVidpPMxgk8AVwO3do1/STPXFuDVwM4ka+aJ5beB7cC5zWfrIuKXJEmSRsaS\nSlCq6iDtBHjHHLvPlwN3AruAKzt+N1VV+4BvdI1/PXBvVT1TVV8B7mWOpDrJ6cCLq2pPVRXwQeAn\nlhK/JEmSNGxLrgGvqseb362bpXscuK35jC9iuvXAkx3HB5jllfYdYw8sZmyS7UkmkkzMHD60iDAk\nSZKkwTjWmzCP2v1OchpwDnB/VT0KTCc5f6nzANXr2Kq6qarGqmpsxamrFghBkiRJGpwlJ+BJzgZm\ngINdXduANcBkkimgRUcZyhwOAGd0HG8Anp5n7IZFjpUkSZJG0pIS8CRrgRuBG5o67E7jwNaqalVV\nC7iAhRPwe4BLkqxpbr68pGk7SlV9Cfhakh9u6s/fAtyxlPglSZKkYVvMq+hXJtkLnAxMA7cA13cO\nSNICzgQeONJWVZNJnk2yhfbNl7fT3iF/Q5J3V9V5VfVMkvcCn25+9p6qemaeWP4F8PvASuDPmo8k\nSZJ03FgwAa+qFfP07QZ2N4dH3RBZVZs7Djd09zdjbgZuXiiOZuwEsFBduSRJkjSyFrMDflzbuH4V\nE9ddNuwwJEmSJGBEE/AknwJe2NX85qraP4x4JEmSpH4ZyQS8qrYMOwZJkiRpORzrc8AlSZIkHQMT\ncEmSJGmATMAlSZKkATIBlyRJkgbIBFySJEkaIBNwSZIkaYBMwCVJkqQBMgGXJEmSBsgEXJIkSRog\nE3BJkiRpgEzAJUmSpAEyAZckSZIGKFU17BiWVZKvAZ8fdhziZcDfDzsIeR1GhNdhNHgdRoPXYTR4\nHXr38qpau5iBL1juSEbA56tqbNhBfKdLMuF1GD6vw2jwOowGr8No8DqMBq/DYFmCIkmSJA2QCbgk\nSZI0QN8JCfhNww5AgNdhVHgdRoPXYTR4HUaD12E0eB0G6IS/CVOSJEkaJd8JO+CSJEnSyDhhE/Ak\nW5N8PskXklw77HhOdEluTnIwyWc72l6S5N4kjzX/XNO0J8lvNtdmX5LNw4v8xJHkjCSfSPI3SR5J\n8q+adq/DgCX5riR/neTh5lq8u2k/K8mnmmvxx0lOadpf2Bx/oelvDTP+E0mSFUk+k+Su5thrMARJ\nppLsT7I3yUTT5p9NA5ZkdZKPJPnb5n8r/gevw3CckAl4khXAbwH/DHgFMJ7kFcON6oT3+8DWrrZr\ngfuq6lzgvuYY2tfl3OazHfjtAcV4opsGfqGqfgD4YeDtzf/dex0G73ngR6vqB4FNwNYkPwz8KvAb\nzbX4CvC2ZvzbgK9U1TnAbzTj1B//CvibjmOvwfD806ra1PGoO/9sGrz/C/hYVX0/8IO0/3/D6zAE\nJ2QCDrwa+EJVPV5V/wDsAn58yDGd0KrqL4Fnupp/HPiD5vsfAD/R0f7BansAWJ3k9MFEeuKqqi9V\n1UPN96/R/oN1PV6HgWv+nX69OTy5+RTwo8BHmvbua3HkGn0E+LEkGVC4J6wkG4DLgN9tjoPXYJT4\nZ9MAJXkxcCHwewBV9Q9V9VW8DkNxoibg64EnO44PNG0arNOq6kvQTg6BdU2712eZNX99/irgU3gd\nhqIpfdgLHATuBb4IfLWqppshnf++v3ktmv5DwEsHG/EJ6QPALwHfaI5fitdgWAr48yQPJtnetPln\n02CdDXwZ+E9NWdbvJvluvA5DcaIm4LPtWvi4l9Hh9VlGSV4E/N/Av66qZ+cbOkub16FPqmqmqjYB\nG2j/rdwPzDas+afXos+S/HPgYFU92Nk8y1CvwWC8pqo20y5reHuSC+cZ67VYHi8ANgO/XVWvAv5f\nvlVuMhuvwzI6URPwA8AZHccbgKeHFMt3sv965K+rmn8ebNq9Psskycm0k+8/qqo/aZq9DkPU/BXv\nbtp1+auTvKDp6vz3/c1r0fSv4uiSLi3Na4A3JpmiXYb4o7R3xL0GQ1BVTzf/PAjcTvs/Sv2zabAO\nAAeq6lPN8UdoJ+RehyE4URPwTwPnNne7nwJcCXx0yDF9J/oocFXz/Srgjo72tzR3WP8wcOjIX3/p\n2DX1qr8H/E1VXd/R5XUYsCRrk6xuvq8EXke7Jv8TwBXNsO5rceQaXQH8RfmShp5U1TurakNVtWj/\nb8BfVNX/gtdg4JJ8d5LvOfIduAT4LP7ZNFBV9V+AJ5P846bpx4DP4XUYihP2RTxJLqW927ECuLmq\n3jfkkE5oSW4DLgJeBvxXYCfwn4EPAWcCTwA/WVXPNIniDbSfmnIYeGtVTQwj7hNJkv8R+CSwn2/V\nvP4ftOvAvQ4DlOSVtG9mWkF7o+NDVfWeJGfT3o19CfAZ4Ker6vkk3wXcQrtu/xngyqp6fDjRn3iS\nXAT8YlX9c6/B4DX/zm9vDl8A3FpV70vyUvyzaaCSbKJ9U/IpwOPAW2n+jMLrMFAnbAIuSZIkjaIT\ntQRFkiRJGkkm4JIkSdIAmYBLkiRJA2QCLkmSJA2QCbgkSZI0QCbgkiRJ0gCZgEuSJEkDZAIuSZIk\nDdD/D4D6loLHgL5oAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0f74e4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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j44RNwJNsTfKlJF9Ocu2o43k5SHJzkgNJvtDV9tok9yV5vPnnmqY9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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0bd48710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfGender = sparsePivot.loc['GENDER']\n",
    "notNullBarChart(dfGender)\n",
    "dfGender = sparsePivot.loc['GENDER'].drop(['DIA3_2', 'DIA2_2'], axis=1)\n",
    "dfGender = dfGender[~dfGender.index.isin([59],1)] #location 59 is overall U.S.\n",
    "notNullBarChart(dfGender)\n",
    "#corrHeatMap(dfGender)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DIA10_0</th>\n",
       "      <th>DIA11_1</th>\n",
       "      <th>DIA11_2</th>\n",
       "      <th>DIA11_3</th>\n",
       "      <th>DIA12_1</th>\n",
       "      <th>DIA12_2</th>\n",
       "      <th>DIA13_1</th>\n",
       "      <th>DIA13_2</th>\n",
       "      <th>DIA1_1</th>\n",
       "      <th>DIA1_2</th>\n",
       "      <th>DIA2_1</th>\n",
       "      <th>DIA4_0</th>\n",
       "      <th>DIA5_0</th>\n",
       "      <th>DIA6_0</th>\n",
       "      <th>DIA7_0</th>\n",
       "      <th>DIA8_0</th>\n",
       "      <th>DIA9_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StratificationID1</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">GENF</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">4</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.4</td>\n",
       "      <td>0.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>221.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>2013</th>\n",
       "      <td>56.9</td>\n",
       "      <td>66.6</td>\n",
       "      <td>70.5</td>\n",
       "      <td>29.8</td>\n",
       "      <td>54.5</td>\n",
       "      <td>63.5</td>\n",
       "      <td>53.9</td>\n",
       "      <td>80.3</td>\n",
       "      <td>65.1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.24</td>\n",
       "      <td>63.6</td>\n",
       "      <td>76.1</td>\n",
       "      <td>70.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>198.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>2014</th>\n",
       "      <td>57.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.2</td>\n",
       "      <td>45.2</td>\n",
       "      <td>60.8</td>\n",
       "      <td>52.8</td>\n",
       "      <td>75.7</td>\n",
       "      <td>64.8</td>\n",
       "      <td>1.1</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1.73</td>\n",
       "      <td>66.1</td>\n",
       "      <td>72.6</td>\n",
       "      <td>64.5</td>\n",
       "      <td>51.2</td>\n",
       "      <td>202.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">5</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>288.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>2013</th>\n",
       "      <td>53.1</td>\n",
       "      <td>63.5</td>\n",
       "      <td>72.3</td>\n",
       "      <td>37.2</td>\n",
       "      <td>43.4</td>\n",
       "      <td>60.8</td>\n",
       "      <td>46.3</td>\n",
       "      <td>80.9</td>\n",
       "      <td>79.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "      <td>3.04</td>\n",
       "      <td>64.4</td>\n",
       "      <td>63.4</td>\n",
       "      <td>58.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>274.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.7</td>\n",
       "      <td>46.8</td>\n",
       "      <td>62.5</td>\n",
       "      <td>46.2</td>\n",
       "      <td>77.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>12.5</td>\n",
       "      <td>2.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51.5</td>\n",
       "      <td>272.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>190.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">8</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>2013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>62.2</td>\n",
       "      <td>70.4</td>\n",
       "      <td>35.6</td>\n",
       "      <td>58.3</td>\n",
       "      <td>69.9</td>\n",
       "      <td>54.9</td>\n",
       "      <td>86.8</td>\n",
       "      <td>48.3</td>\n",
       "      <td>0.8</td>\n",
       "      <td>5.9</td>\n",
       "      <td>1.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>122.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.6</td>\n",
       "      <td>58.6</td>\n",
       "      <td>68.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>86.8</td>\n",
       "      <td>51.1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.2</td>\n",
       "      <td>128.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "QuestionID                                      DIA10_0  DIA11_1  DIA11_2  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                              \n",
       "GENF              4          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013        56.9     66.6     70.5   \n",
       "                             2014      2014        57.5      NaN      NaN   \n",
       "                  5          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013        53.1     63.5     72.3   \n",
       "                             2014      2014         NaN      NaN      NaN   \n",
       "                  6          2010      2010         NaN      NaN      NaN   \n",
       "                  8          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013         NaN     62.2     70.4   \n",
       "                             2014      2014         NaN      NaN      NaN   \n",
       "\n",
       "QuestionID                                      DIA11_3  DIA12_1  DIA12_2  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                              \n",
       "GENF              4          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013        29.8     54.5     63.5   \n",
       "                             2014      2014        33.2     45.2     60.8   \n",
       "                  5          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013        37.2     43.4     60.8   \n",
       "                             2014      2014        34.7     46.8     62.5   \n",
       "                  6          2010      2010         NaN      NaN      NaN   \n",
       "                  8          2010      2010         NaN      NaN      NaN   \n",
       "                             2013      2013        35.6     58.3     69.9   \n",
       "                             2014      2014        31.6     58.6     68.6   \n",
       "\n",
       "QuestionID                                      DIA13_1  DIA13_2  DIA1_1  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                             \n",
       "GENF              4          2010      2010         NaN      NaN    50.4   \n",
       "                             2013      2013        53.9     80.3    65.1   \n",
       "                             2014      2014        52.8     75.7    64.8   \n",
       "                  5          2010      2010         NaN      NaN    78.1   \n",
       "                             2013      2013        46.3     80.9    79.3   \n",
       "                             2014      2014        46.2     77.0    78.0   \n",
       "                  6          2010      2010         NaN      NaN    86.5   \n",
       "                  8          2010      2010         NaN      NaN    48.7   \n",
       "                             2013      2013        54.9     86.8    48.3   \n",
       "                             2014      2014        53.0     86.8    51.1   \n",
       "\n",
       "QuestionID                                      DIA1_2  DIA2_1  DIA4_0  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                           \n",
       "GENF              4          2010      2010        0.9     NaN    2.06   \n",
       "                             2013      2013        0.9    10.0    2.24   \n",
       "                             2014      2014        1.1     9.3    1.73   \n",
       "                  5          2010      2010        NaN     NaN    2.88   \n",
       "                             2013      2013        NaN    10.5    3.04   \n",
       "                             2014      2014        1.3    12.5    2.42   \n",
       "                  6          2010      2010        0.8     NaN    1.76   \n",
       "                  8          2010      2010        NaN     NaN    1.25   \n",
       "                             2013      2013        0.8     5.9    1.24   \n",
       "                             2014      2014        0.8     7.0    0.94   \n",
       "\n",
       "QuestionID                                      DIA5_0  DIA6_0  DIA7_0  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                           \n",
       "GENF              4          2010      2010        NaN     NaN     NaN   \n",
       "                             2013      2013       63.6    76.1    70.1   \n",
       "                             2014      2014       66.1    72.6    64.5   \n",
       "                  5          2010      2010        NaN     NaN     NaN   \n",
       "                             2013      2013       64.4    63.4    58.4   \n",
       "                             2014      2014        NaN     NaN     NaN   \n",
       "                  6          2010      2010        NaN     NaN     NaN   \n",
       "                  8          2010      2010        NaN     NaN     NaN   \n",
       "                             2013      2013        NaN     NaN     NaN   \n",
       "                             2014      2014        NaN     NaN     NaN   \n",
       "\n",
       "QuestionID                                      DIA8_0  DIA9_0  \n",
       "StratificationID1 LocationID YearStart YearEnd                  \n",
       "GENF              4          2010      2010        NaN  221.19  \n",
       "                             2013      2013        NaN  198.41  \n",
       "                             2014      2014       51.2  202.04  \n",
       "                  5          2010      2010        NaN  288.45  \n",
       "                             2013      2013        NaN  274.64  \n",
       "                             2014      2014       51.5  272.84  \n",
       "                  6          2010      2010        NaN  190.18  \n",
       "                  8          2010      2010        NaN  132.51  \n",
       "                             2013      2013        NaN  122.83  \n",
       "                             2014      2014       59.2  128.30  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfGender[dfGender['DIA9_0'].notnull()].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 584,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a4e4f65f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullHeatMap(dfDia[dfDia['StratificationCategoryID1'] == 'GENDER'], columns='YearStart', cmap=\"Purples\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>QuestionID</th>\n",
       "      <th>DIA10_0</th>\n",
       "      <th>DIA11_1</th>\n",
       "      <th>DIA11_2</th>\n",
       "      <th>DIA11_3</th>\n",
       "      <th>DIA12_1</th>\n",
       "      <th>DIA12_2</th>\n",
       "      <th>DIA13_1</th>\n",
       "      <th>DIA13_2</th>\n",
       "      <th>DIA1_1</th>\n",
       "      <th>DIA1_2</th>\n",
       "      <th>DIA2_1</th>\n",
       "      <th>DIA4_0</th>\n",
       "      <th>DIA5_0</th>\n",
       "      <th>DIA6_0</th>\n",
       "      <th>DIA7_0</th>\n",
       "      <th>DIA8_0</th>\n",
       "      <th>DIA9_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StratificationID1</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>YearStart</th>\n",
       "      <th>YearEnd</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"10\" valign=\"top\">GENF</th>\n",
       "      <th rowspan=\"7\" valign=\"top\">1</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>52.7</td>\n",
       "      <td>72.90</td>\n",
       "      <td>78.10</td>\n",
       "      <td>33.8</td>\n",
       "      <td>45.9</td>\n",
       "      <td>66.6</td>\n",
       "      <td>48.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>85.1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65.500000</td>\n",
       "      <td>72.300000</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>48.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <th>2011</th>\n",
       "      <td>52.7</td>\n",
       "      <td>72.90</td>\n",
       "      <td>78.10</td>\n",
       "      <td>33.8</td>\n",
       "      <td>45.9</td>\n",
       "      <td>66.6</td>\n",
       "      <td>48.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>79.3</td>\n",
       "      <td>1.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65.500000</td>\n",
       "      <td>72.300000</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>48.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <th>2012</th>\n",
       "      <td>55.3</td>\n",
       "      <td>71.50</td>\n",
       "      <td>78.75</td>\n",
       "      <td>36.7</td>\n",
       "      <td>50.9</td>\n",
       "      <td>66.0</td>\n",
       "      <td>44.8</td>\n",
       "      <td>78.6</td>\n",
       "      <td>76.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.300000</td>\n",
       "      <td>75.500000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>48.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>2013</th>\n",
       "      <td>54.2</td>\n",
       "      <td>70.10</td>\n",
       "      <td>79.40</td>\n",
       "      <td>35.4</td>\n",
       "      <td>50.8</td>\n",
       "      <td>59.8</td>\n",
       "      <td>48.3</td>\n",
       "      <td>75.0</td>\n",
       "      <td>74.3</td>\n",
       "      <td>1.7</td>\n",
       "      <td>14.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.500000</td>\n",
       "      <td>73.200000</td>\n",
       "      <td>68.900000</td>\n",
       "      <td>48.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>2014</th>\n",
       "      <td>54.4</td>\n",
       "      <td>69.00</td>\n",
       "      <td>79.00</td>\n",
       "      <td>35.3</td>\n",
       "      <td>50.4</td>\n",
       "      <td>70.2</td>\n",
       "      <td>43.9</td>\n",
       "      <td>76.8</td>\n",
       "      <td>65.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69.133333</td>\n",
       "      <td>72.733333</td>\n",
       "      <td>67.233333</td>\n",
       "      <td>49.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <th>2015</th>\n",
       "      <td>54.6</td>\n",
       "      <td>67.90</td>\n",
       "      <td>78.60</td>\n",
       "      <td>38.5</td>\n",
       "      <td>52.0</td>\n",
       "      <td>60.4</td>\n",
       "      <td>47.5</td>\n",
       "      <td>74.1</td>\n",
       "      <td>65.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.766667</td>\n",
       "      <td>72.266667</td>\n",
       "      <td>65.566667</td>\n",
       "      <td>51.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <th>2016</th>\n",
       "      <td>54.8</td>\n",
       "      <td>67.90</td>\n",
       "      <td>78.60</td>\n",
       "      <td>40.1</td>\n",
       "      <td>39.7</td>\n",
       "      <td>59.3</td>\n",
       "      <td>51.3</td>\n",
       "      <td>79.0</td>\n",
       "      <td>65.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>14.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.400000</td>\n",
       "      <td>71.800000</td>\n",
       "      <td>63.900000</td>\n",
       "      <td>53.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">2</th>\n",
       "      <th>2010</th>\n",
       "      <th>2010</th>\n",
       "      <td>64.5</td>\n",
       "      <td>59.00</td>\n",
       "      <td>77.20</td>\n",
       "      <td>43.6</td>\n",
       "      <td>43.9</td>\n",
       "      <td>56.4</td>\n",
       "      <td>63.1</td>\n",
       "      <td>73.7</td>\n",
       "      <td>36.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.100000</td>\n",
       "      <td>61.800000</td>\n",
       "      <td>67.200000</td>\n",
       "      <td>61.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <th>2011</th>\n",
       "      <td>64.5</td>\n",
       "      <td>59.00</td>\n",
       "      <td>77.20</td>\n",
       "      <td>43.6</td>\n",
       "      <td>43.9</td>\n",
       "      <td>56.4</td>\n",
       "      <td>63.1</td>\n",
       "      <td>73.7</td>\n",
       "      <td>41.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.100000</td>\n",
       "      <td>61.800000</td>\n",
       "      <td>67.200000</td>\n",
       "      <td>61.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <th>2012</th>\n",
       "      <td>77.9</td>\n",
       "      <td>61.45</td>\n",
       "      <td>72.70</td>\n",
       "      <td>34.4</td>\n",
       "      <td>36.7</td>\n",
       "      <td>66.5</td>\n",
       "      <td>41.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>49.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71.400000</td>\n",
       "      <td>74.400000</td>\n",
       "      <td>67.700000</td>\n",
       "      <td>61.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "QuestionID                                      DIA10_0  DIA11_1  DIA11_2  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                              \n",
       "GENF              1          2010      2010        52.7    72.90    78.10   \n",
       "                             2011      2011        52.7    72.90    78.10   \n",
       "                             2012      2012        55.3    71.50    78.75   \n",
       "                             2013      2013        54.2    70.10    79.40   \n",
       "                             2014      2014        54.4    69.00    79.00   \n",
       "                             2015      2015        54.6    67.90    78.60   \n",
       "                             2016      2016        54.8    67.90    78.60   \n",
       "                  2          2010      2010        64.5    59.00    77.20   \n",
       "                             2011      2011        64.5    59.00    77.20   \n",
       "                             2012      2012        77.9    61.45    72.70   \n",
       "\n",
       "QuestionID                                      DIA11_3  DIA12_1  DIA12_2  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                              \n",
       "GENF              1          2010      2010        33.8     45.9     66.6   \n",
       "                             2011      2011        33.8     45.9     66.6   \n",
       "                             2012      2012        36.7     50.9     66.0   \n",
       "                             2013      2013        35.4     50.8     59.8   \n",
       "                             2014      2014        35.3     50.4     70.2   \n",
       "                             2015      2015        38.5     52.0     60.4   \n",
       "                             2016      2016        40.1     39.7     59.3   \n",
       "                  2          2010      2010        43.6     43.9     56.4   \n",
       "                             2011      2011        43.6     43.9     56.4   \n",
       "                             2012      2012        34.4     36.7     66.5   \n",
       "\n",
       "QuestionID                                      DIA13_1  DIA13_2  DIA1_1  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                             \n",
       "GENF              1          2010      2010        48.0     76.7    85.1   \n",
       "                             2011      2011        48.0     76.7    79.3   \n",
       "                             2012      2012        44.8     78.6    76.2   \n",
       "                             2013      2013        48.3     75.0    74.3   \n",
       "                             2014      2014        43.9     76.8    65.8   \n",
       "                             2015      2015        47.5     74.1    65.8   \n",
       "                             2016      2016        51.3     79.0    65.8   \n",
       "                  2          2010      2010        63.1     73.7    36.4   \n",
       "                             2011      2011        63.1     73.7    41.6   \n",
       "                             2012      2012        41.6     86.3    49.3   \n",
       "\n",
       "QuestionID                                      DIA1_2  DIA2_1  DIA4_0  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                           \n",
       "GENF              1          2010      2010        1.4    12.5     NaN   \n",
       "                             2011      2011        1.4    12.5     NaN   \n",
       "                             2012      2012        1.3    12.0     NaN   \n",
       "                             2013      2013        1.7    14.1     NaN   \n",
       "                             2014      2014        1.5    13.0     NaN   \n",
       "                             2015      2015        1.5    14.0     NaN   \n",
       "                             2016      2016        1.5    14.4     NaN   \n",
       "                  2          2010      2010        NaN     8.2     NaN   \n",
       "                             2011      2011        NaN     8.2     NaN   \n",
       "                             2012      2012        NaN     7.4     NaN   \n",
       "\n",
       "QuestionID                                         DIA5_0     DIA6_0  \\\n",
       "StratificationID1 LocationID YearStart YearEnd                         \n",
       "GENF              1          2010      2010     65.500000  72.300000   \n",
       "                             2011      2011     65.500000  72.300000   \n",
       "                             2012      2012     66.300000  75.500000   \n",
       "                             2013      2013     69.500000  73.200000   \n",
       "                             2014      2014     69.133333  72.733333   \n",
       "                             2015      2015     68.766667  72.266667   \n",
       "                             2016      2016     68.400000  71.800000   \n",
       "                  2          2010      2010     72.100000  61.800000   \n",
       "                             2011      2011     72.100000  61.800000   \n",
       "                             2012      2012     71.400000  74.400000   \n",
       "\n",
       "QuestionID                                         DIA7_0  DIA8_0  DIA9_0  \n",
       "StratificationID1 LocationID YearStart YearEnd                             \n",
       "GENF              1          2010      2010     63.500000    48.2     NaN  \n",
       "                             2011      2011     63.500000    48.2     NaN  \n",
       "                             2012      2012     62.000000    48.2     NaN  \n",
       "                             2013      2013     68.900000    48.7     NaN  \n",
       "                             2014      2014     67.233333    49.2     NaN  \n",
       "                             2015      2015     65.566667    51.5     NaN  \n",
       "                             2016      2016     63.900000    53.8     NaN  \n",
       "                  2          2010      2010     67.200000    61.4     NaN  \n",
       "                             2011      2011     67.200000    61.4     NaN  \n",
       "                             2012      2012     67.700000    61.4     NaN  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def interpGroup(g):\n",
    "    g=g.interpolate()\n",
    "    g=g.interpolate(limit_direction='backward')\n",
    "    return g\n",
    "dfInterp = dfGender.copy()\n",
    "#interpolate across years for the same Gender and Location (maintains differences)\n",
    "dfInterp = dfInterp.groupby(level=[0,1]).apply(interpGroup)\n",
    "dfInterp.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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t57zpqtoNvNQ33+NV9UTz/VlgP7B2nvX/tBrAXwMbholfkiRJWmpD14BX1ZPN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\nXRze18XhfR3Scf8QpiRJkrS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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0ec59160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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uWkB89Ro+u6Y6DRqwI3Ebu7Kvac6vv9CsTVuvmOat2/Lb\nj9MBmDdzJuc1uRhjDMNfG8vED6Yx8YNpdL3xJm64tRfXXHcjh9PTST90CIDD6eksW7SQajVq5eu7\nKF3WpRtDx0xk6JiJNGnVhrkzfsJay8Y1qylbtly+AkeFyChCypRl45rVWGuZO+MnmrRqA2QtUvrd\np9Po9/RQSoeEOJr3qWpYuTJb96Syfe8eXO5Mfl61gvZ163vFpBzYn/P77PVrqZFdsNqXnk5GZiYA\new8d5K9tW6kZXbgio4iIiIiIyKlwcg2OnFURrbWZQF9jzGBgBlDewX5zBAUFMWjQIPr164fb7aZb\nt27Url2biRMn0rBhQzp27MjKlSsZNGgQ+/btY/bs2SQkJDBt2jQuu+wyFi5cSI8ePTDG0Lp160IX\nR4pSYFAQ9/YfwJCBj+LxuLn8mq5Uq1mL99+YTJ0GDWjZtj2dr+nKyOeepe+ttxAaGsagZ7J2Gykf\nGkb3W3rw6L13YYyhacvWNG+d9YW6xx19+E+/BwkMCiI2riKP/Of/fHdNgUHc3a8/zz4xEI/HQ6er\nr6FajZp8+OYb1Klfn+Zt2nHZNV0Y88JzPNi7J+VDQxnw1JATPufePXt4+Zmsa3C73bS/7PICd1lx\nygXNWvDXogU82fcOSpUuzZ2PDMxpe+bh+xg6ZiIAvR94mCmjXyEje5vY85s2B+D9SeNwuTJ49ekn\nAahdvyG3PfgIAIPu6s3hQ4fIzHSx9I+5PDrsBapUq+6zawsKCOSxK66h/0fv4vFYul7YhFoxsSTM\nnEHDSpVpX68B0xbOZ876tQQGBBAWUoanul4HwKbUZF76/hsCjMFjLb1bt8u3+4qIiIiIyDnLFN8F\nOc9FpsD1G4riiY15D3jPWjs9z/G7gQnW2uCTPcf+/fudSc5Pth884u8Uipwr0+3vFIpU2qHD/k6h\nyDWcN9ffKRS5yNt7+jsFERERESkaxWdutgPSvp5+Tn2nPSr82quK5evmWDnJWtsrb3Ej+/jruYsb\nxpjOTuUgIiIiIiIiIiVDcRgv85K/ExARERERERGRs5uTa3AUVrEc2iIiIiIiIiJyJorT7oglQXEY\nwXFOzkkSEREREREREd8pDgUOEREREREREZEzUhwKHJv8nYCIiIiIiIiInN0cXYPDGBMGxFhrN+Y5\nfoG19i8Aa+0NTuYgIiIiIiIi4hcBWoPDlxwbwWGMuQVYA3xqjFlpjGmeq/ktp/oVERERERERkZLH\nySkq/wWaWmsvAvoA7xpjjo7WUBlLRERERERERIqMk1NUAq21OwCstQuMMZcC3xhj4tHOKSIiIiIi\nIiJShJwscOw3xtQ+uv6GtXaHMeYS4AugsYP9ioiIiIiIiPif0eQFX3KywHE/eaaiWGv3G2OuAm5x\nsF8RERERERERKWEcK3BYa5cd57gLeN+pfkVERERERESk5HFykdHjMsYs90e/IiIiIiIiInJucmwE\nR64dU/I1ARWd6ldERERERERESh4n1+CYStZUlIJ2TAlxsF8RERERERER/zN+mTRRYjlZ4PgLGGGt\nXZG3wRhzuYP9ioiIiIiIiEgJ42Q5qT+w7zht1zvYr4iIiIiIiIiUME7uojL7BM3aDFhERERERERE\nioyTU1S8GGMaAT2AnkAa0MxXfYuIiIiIiIj4mgnQ3/Z9ydEChzGmOlkFjZ5AJlAdaGat3eRkvyIi\nIiIiIiJSsji2BocxZi7wHRAM3GStbQrsV3FDRERERERERIqak4uMJgOhQBwQk32soC1jRURERERE\nRETOiJOLjHY3xoQDNwJDjTF1gArGmBbW2gVO9SsiIiIiIiJSLBitweFLjq7BYa1NA6YAU4wxccC/\ngNHGmKrW2qpO9i0iIiIiIiIiJYeTU1S8WGt3WWvHWGvbAO181a+IiIiIiIiInPscG8FhjPmaE6+5\n0c2pvkVERERERESkZHFyisoIB59bREREREREpHgL8NmkCcHZRUZnHv3dGBOTfSz5VJ7D88vMkwed\nRQJbt/F3CkVu6969/k6hSLVOS/V3CkXuiL8TKGKhl1+CK3GHv9MocsFVKvk7BRERERGRs5qj5SRj\nzDPGmBRgDbDOGJNsjBnsZJ8iIiIiIiIiUvI4VuAwxgwgazHR5tbaKGttBNASaJvdJiIiIiIiIiJS\nJJwcwXEb0NNa+8/RA9bav4Fe2W0iIiIiIiIiIkXCyUVGg621KXkPWmuTjTHBDvYrIiIiIiIi4nfG\nGH+nUKI4OYIj4zTbREREREREREROiZMjOC40xuwr4LgBQhzsV0RERERERERKGCe3iQ106rlFRERE\nRERERHJzcgSHiIiIiIiISMkV4OSqEJKX/rVFRERERERE5KynAoeIiIiIiIiInPVU4BARERERERGR\ns57W4BARERERERFxgjH+zqBE0QgOERERERERETnrqcAhIiIiIiIiImc9FThERERERERE5KynNThE\nREREREREnBCgNTh8SSM4REREREREROSspwKHiIiIiIiIiJz1VOAQERERERERkbOeChwiIiIiIiIi\nctbTIqMiIiIiIiIiDr509W4AACAASURBVDBGYwp8Sf/aIiIiIiIiInLWU4FDRERERERERM56KnCI\niIiIiIiIyFlPa3CIiIiIiIiIOMEYf2dQomgEh4iIiIiIiIic9c75ERzz1q7h1a++wGM9dG/ektsv\nvazAuF/+WsZ/3n+Ht/r1p1F8VVyZmbzw2SesTtyKMYbHrr2OprXr+Dj7LIvmzyNhzGg8HjdXdOnG\nLb1u82p3ZWTw6nPD2LBuDaFh4Tw5ZDhxlSqRmZnJmJeeZ8O6tbjdbi676mpu6XV7znlut5v+ffsQ\nFR3DkJde9ek1WWv5eMokVi5ZRKlSpendbwDVauX/992ycT3vjh1FRkYGjS9uxs133osxhm+nvs/v\nP/9A+bAwALrdejvnNW1OatIunn3kPmIrVwGgZr0G9Lz3IZ9eW16/L/+LER+8h9t6uL59R/p0ubbA\nuJ8XLeDx8WN57+khNKpZy8dZnti8jesZ/dN03NZDtwsv5rY27b3av/1rKWN/+YmY0FAAbmrWgm4X\nNQWg7QtDqR0TC0BceDiv3Hyrb5MvwJwF83lx7FjcHjc3XtOFu2/9t1f72x9P49PvviUwMJDI8Ao8\nO+hxKlesCMAFl3eibs2aAFSKjWPsc8/7PH8REREREcnvnC5wuD0eXv7iM8befS+x4eHcPnY07Rs1\nplZcRa+4g0cOM3XuHM6rWi3n2BcL/gDgwwGD2H1gP/2nvM5bDz1CQIBvB7243W4mjHqV4SNfIzom\nlgF976RVu/ZUq1EzJ+aHb7+mfGgor3/4CTN/+Yk3J47jyaHDmfPrL7hcLsa//T6HDx/m/tt60vGy\nK4irVAmArz6ZRtXqNTh08KBPrwlg5ZJFJO/YzpCxk9m0fi0fJYzj8RdH5Yv7KGE8Pe/rR816DRj/\n3DOsWrqYxhc3A6BT1+5c3v3GfOdEx1Xiv6+OdfwaCsPt8fDSe+8w/rHHiYuMpNewZ+h40cXUqlLF\nK+5gejof/vwT59Wq7adMj8/t8fDqD9/xWs/exIaFceebk2lftz41s4sWR13WqDEDr+yS7/zSQUG8\nc/f9vkr3pNxuN8Nfe43Jr4ygYkwM/7r/Pi5t05baNWrkxDSsU5epEyZRJiSEj778klcTJvHq4GcA\nKF2qFJ9OfsNP2YuIiIiIyPGc01NUVm7dQnxUFFWioggOCuKKC5swa9XKfHGTfphO746XUio4OOfY\nP0m7aF6nLgCR5UMpHxLC6sRtPsv9qHWrV1G5SjyVKlchODiYDpddzh9zZnnFzJ8zm8uuugaAdh0v\nZdmSRVhrwRgOH07HnZlJxpEjBAUFU7ZcWQBSkpJYOO93ruzSzefXBPDXwj9o2bETxhhq1mtA+sGD\npO3Z7RWTtmc3hw8dolb9hhhjaNmxE8sWzPNLvqdrxd8biY+NJT42luCgIK5s2Yrf/lySL278559y\n+1XXUDrXe7C4WLU9kfiISKpERBIcGMTljc5j1vq1/k7rtC1fs4ZqVapQtXJlgoODubpTJ2bM/d0r\npkWTJpQJCQHgwkaN2JWc7I9URURERORsF2DOzZ9i6pwucCSnpRFXoULO49jwcJLT0rxi1iZuY1fa\nXto3bOR1vG6lysxctYJMt5vE3amsSdzGrr17fZJ3bqkpyUTHHvtLeXRMLKl5vmylpiQTExsHQGBQ\nEGXLlWdfWhrtLulESEgZel1/LXfcfB039LiV0LBwABL+N5o+9z+E8fGIlKPSdqdSITom53GFqGj2\npqZ6xexNTaVCVJRXTNruYzEzv/+G5wY8yLvjRnPowP6c46lJO3lhYD9GPf0EG1atcPAqTi557x4q\nRh67htiISJL27PGKWbN5E7v27KbDRU18nV6hJO/fR2z2VCCA2NAwkvfvyxf325rV9Jo8nv9+OpVd\n+459zjIyM+kzZRJ3vzWZmWtX+yTnE0lKSaZi7LH3Xlx0DEknKGB89t23tG/RIudxRkYGt9zXl1sf\nvJ9f5sx2NFcRERERESk8v0xRMcYMttYOc7ofW2Dnx371eDyM+uYrBt/cI1/Ytc1a8E9SErf/bzSV\nIiK4oHoNAv1QDLC2gKvIsxJvQTHGGNatXklAQADvfv41B/bv4/GH7ueiZs3ZuukfwiMiqFu/AX8t\nzT+awBcKzjlfVAFnZgW1v/Iarr6pBxjDNx++y6dvv0HvB/sTFhHJs5PeonxoGFs2rmfSS8N5avQE\nypQtW+TXUBgne/k8Hg+vfvQBQ++6x3dJnaKCXwXvF6tdnfp0bnQ+pYKC+GzJQp79+nPG/vsOAD5/\naAAxoWEk7tnNQx+8Te3YOOIjIp1P/DgKfk0KrkJ//dOPrFy3lrdGvZZz7KePphEbHc3W7du567EB\n1K1Zi2p5phyJiIiIiIjv+WsNjruBAgscxpi+QF+A0fc/yB1XXHXancSGh3uNukhKSyMmewQDwKEj\nR9i4cwf3J4wHIHX/fga+NYURd9xJo/iqPHpt95zYu8aNoWp09GnncrqiY2JJSUrKeZySnERUnjyi\nY2JJTtpFdGws7sxMDh08QGhYGL/99CNNW7YiKCiIChGRNDr/fDasWc3G9euY//tsFv0xl4yMDNIP\nHuSVZ4cw6Okhjl7LzO+/4fefpwNQvU499qYc+6v53tQUwnONdID8ozqyYrK+GIdViMg53rbzVUx4\nfigAwcHBBGdP86hWuy4xFSuRtD2R6tnTjXwtNiKCnblGnSTt2U1MrtwPHj7MxsRt3PPSCwCkpqXR\nf8xoRj/cv9gsNBobGkbSvmMjNpL27yM6ezHRo8JzFZC6X9SU8b/+nPM4JjRr9EeViEgurlaDdTt3\n+LXAERcTw86kY++9XSnJxBTw2Z63eBEJ77/HW6Neo1SpUjnHY7Njq1auTPOLLmLNhvUqcIiIiIiI\nFAOODUkwxuw7zs9+oPLxzrPWJlhrm1lrm51JcQOgUXxVtqamkLg7FVdmJj8uW0r7ho1z2suXKcNP\nzzzLl08+xZdPPsV51arnFDcOZ2SQnnEEgPnr1hIYGJhvcVJfqNegIYnbtrJz+3ZcLhezfvmZlm29\nd7Bo2bYdv0z/DoA5M3/lgoubYowhJq4iy5YsxlrL4fR01qxcSXz1Gtxx7wO88+lXvDntc5545lku\nuLip48UNgI5Xd+W/r47lv6+O5cIWrZg/cwbWWv5Zt4YyZcsRnudLb3hEJKXLlOGfdWuw1jJ/5gwu\naN4KwGu9jmXz51K5WnUA9qel4XG7AUjZuYOkHduJ9sPrdlTjmrXYumsXicnJuDIz+WH+H3TMNRUl\ntGxZZowZz7evjOTbV0Zyfu3axaq4AdCwcmW27kll+949uNyZ/LxqBe3r1veKSck1RWj2+rXUiMoq\nAuxLTycjMxOAvYcO8te2rdTMNTXJH85rUJ8tidvYtmMHLpeL72fM4NLWbbxiVq9fz9CRIxk7/Hmi\nIo4VpNL27ycjIwOAPWl7WbpiBbWr1/Bl+iIiIiJyNjEB5+ZPMeXkCI69QHNr7a68DcaYrQ72myMo\nMJBB3W/g4TcS8Hgs1zZvQe2KFZn043QaxsfTodF5xz1394EDPPxGAgHGEBMeztB/9fRFyvkEBgVx\nf//HeHpgfzweD52v6Ur1mrV4940E6tZvSKt27bmiy7WMeG4od/e8idDQMB4f8iwAXa+/kVEvDueB\n2/+NtZbO13Shpp+2us2r8cXNWblkEUMevJtSpUvT68EBOW3PP/ZQzi4oPfo+yLtjR+HKOEKjJs1y\ndlD5/J0pJG76GzBExcbS875+AGxYtYJvPnqPwMBAAgIC6Nn3QcrlGW3gS0GBgTzR6zYeHPkyHo+l\nW7sO1K4Sz4TPP6VRjZp0bHKx33IrrKCAQB674hr6f/QuHo+l64VNqBUTS8LMGTSsVJn29RowbeF8\n5qxfS2BAAGEhZXiq63UAbEpN5qXvvyHAGDzW0rt1u3y7r/j8egKD+G+/R7j3iUG43R6uv/pq6tSs\nydg3p9C4Xn0ubduWVydN4NDhdB4dmrVzytHtYP/evJlho17FmACs9XBXz1u9dl8RERERERH/MQWu\n8VAUT2zMcOAra+2CAtpestY+cbLnSPviG2eS85PkPH8lPhdsSt598qCzSOu01JMHnWWObPjb3ykU\nqdDLL/F3Co4IrlLJ3ymIiIiI+EPx3ZKjCBz8Y9E59Z32qHKtmhXL182xERzW2qdO0JZT3DDGNLbW\n5t+7VURERERERESkkIrD5Jl3/Z2AiIiIiIiIiJzd/LWLSm7FcmiLiIiIiIiIyJkwAfq660vFYQTH\nOTknSURERERERER8pzgUOEREREREREREzkhxKHBk+DsBERERERERETm7OboGhzGmIoC1dqcxJgZo\nD6zNvWuKtbaVkzmIiIiIiIiI+IXRGhy+5NgIDmPMvcA84A9jzP3AN0BX4DNjzF1O9SsiIiIiIiIi\nJY+TIzgeAhoDZYDNQJ3skRwRwK/AGw72LSIiIiIiIiIliJMFDpe19hBwyBiz0Vq7E8Bau8cYo51T\nRERERERERKTIOFng8Bhjgq21LqDL0YPGmBCKx+KmIiIiIiIiIs7RGhw+5WSh4QbAAlhrt+U6HgU8\n5mC/IiIiIiIiIlLCODaCw1q75TjHE4FEp/oVERERERERkZLHL1NFjDHL/dGviIiIiIiIiJybHBvB\nYYy54XhNQEWn+hUREREREREpDkyAlp/0JScXGZ0KvE/2Ohx5hDjYr4iIiIiIiIiUME4WOP4CRlhr\nV+RtMMZc7mC/IiIiIiIiIlLCODlepj+w7zht1zvYr4iIiIiIiIiUME7uojL7BM3aDFhERERERERE\nioyTU1S8GGMaAT2AnkAa0MxXfYuIiIiIiIj4nBYZ9SlHCxzGmOpkFTR6AplAdaCZtXaTk/2KiIiI\niIiISMniWDnJGDMX+A4IBm6y1jYF9qu4ISIiIiIiIiJFzcnxMslAKBAHxGQfK2jLWBERERERERGR\nM+LkIqPdjTHhwI3AUGNMHaCCMaaFtXaBU/2KiIiIiIiIFAtG+2v4kqNrcFhr04ApwBRjTBzwL2C0\nMaaqtbaqk32LiIiIiIiISMnhsyVdrbW7rLVjrLVtgHa+6ldEREREREREzn2OjeAwxnzNidfc6OZU\n3yIiIiIiIiJSsjg5RWWEg88tIiIiIiIiUrwFaA0OX3JykdGZR383xsRkH0s+lefwpB8p6rT8KjK0\nrL9TKHJ/70rxdwpFKjAqwt8pFLmA7efW++7QwsX+TqHIHVm7wd8pFLnYJ/r7OwURERERKWEcXYPD\nGPOMMSYFWAOsM8YkG2MGO9mniIiIiIiIiJQ8jhU4jDEDyFpMtLm1NspaGwG0BNpmt4mIiIiIiIiI\nFAkn1+C4Dehsrc2Zw2Ct/dsY0wv4ERjlYN8iIiIiIiIifmWMzzYuFZydohKcu7hxVPY6HMEO9isi\nIiIiIiIiJYyTBY6M02wTERERERERETklTk5RudAYs6+A4wYIcbBfERERERERESlhnNwmNtCp5xYR\nERERERERyc3JERwiIiIiIiIiJZcx/s6gRNGSriIiIiIiIiJy1lOBQ0RERERERETOeipwiIiIiIiI\niMhZT2twiIiIiIiIiDghQGtw+JJGcIiIiIiIiIjIWU8FDhERERERERE566nAISIiIiIiIiJnPa3B\nISIiIiIiIuIEozU4fEkjOERERERERETkrKcCh4iIiIiIiIic9VTgEBEREREREZGzntbgEBERERER\nEXGAMRpT4Ev61xYRERERERGRs54KHCIiIiIiIiJy1lOBQ0RERERERESKlDHmKmPMWmPMBmPMkwW0\n32eMWW6M+dMYM8cY0+hM+1SBQ0RERERERESKjDEmEBgHXA00AnoWUMD4wFp7vrX2IuBlYOSZ9qtF\nRkVEREREREScEGD8nYG/tAA2WGv/BjDGfAR0B1YdDbDW7ssVXw6wZ9qpChwiIiIiIiIiUpSqAFtz\nPd4GtMwbZIx5EHgUKAV0OtNOz/kCx7z16xg1/Rs8Hg/dLm7Obe07erV/s3QxY3/6npjQcABuatGK\n7k2bs27Hdl7+9ksOHjlCgAngjg6X0Pm8C/xxCV7m/f47o195CbfHQ7frrue2O+/yal+6eDGjR7zM\nxvXrGfbCS3Tq3BmAxQsX8NqIETlxmzf9w7AXX6LjpWf8Hjot1lo+fTOBlUsWU6p0aXo9+AhVa9XJ\nF7dl4wbeGzcaV0YGjS9uyo19+mKMYcrIl0janghA+qGDlClbjidHjGHNsqV89f7bZGZmEhQURPfe\nfah//oU+vbbflyzmpcmT8Xg8XN+5M3fddLNX+7Tvv2fq998SGBBAmZAQBj/wELWrVWPen0t57Z23\ncWVmEhwUxIA7+tDyAt/mfjzz1q1l5Hdf4vFYujVtwe0dL/Vq/2bJIv43/VtiwsIAuLlVG7o3y7p/\nPfL266zYuoULq9dgZO87fZ778cxbu4ZXv/oCj/XQvXlLbr/0sgLjfvlrGf95/x3e6tefRvFVcWVm\n8sJnn7A6cSvGGB679jqa1s7/3vW1UjWrU/6yjhAQwOFlKzg0f1G+mNIN6lKubSsAMpOS2ff1dAAC\nQkMJu/pyAsJCwVr2fvwlnn378p0vIiIiIgJgjOkL9M11KMFam5A7pIDT8o3QsNaOA8YZY24FngJu\nP5O8zukCh9vjYcR3XzGm953EhoXRZ/J42tdvQM3YOK+4yxtfwMAu3byOhQSXYvD1N1MtKprkffu4\nI2EcrWrXJbRMGV9eghe3282rLz7PaxMmERsXx53/vpX2HS+hZu3aOTEVK1Xk6aHP8v47b3ud27R5\nC96ZOg2AtLQ0bu7WlZatWvs0/9xWLV1M0o7tDP7fJDatX8vUyRMY+MKr+eKmTh5Pz3sfoka9+kx4\nfgir/lxM4ybNuPPRJ3JiPnv7DcqULQtAubAw7n3yacIjo9i+ZTPjhw9meMLb+Z7XKW63m+cnTWTS\n0GeJi4ri1oGPckmLltSuVi0n5pqOHbnl6qsB+G3+fEZMeYMJQ4ZSISyMMf/3NLFRUazfvJn7hwzm\n5zd9l/vxuD0eXvn6c/7X5x5iw8K5Y+L/aN+wEbXyfo7Ov5BB116X7/xe7Tpy2OXi84V/+Crlk3J7\nPLz8xWeMvfteYsPDuX3saNo3akytuIpecQePHGbq3DmcV/XY6/fFgqzr+HDAIHYf2E//Ka/z1kOP\nEBDgxyWNjCG086XsmfoZnv0HiLi9J0c2/I07dXdOSGBEBcq2as6e96ZhjxzBlD12LwvreiUH5y3A\ntWkLJjgYa894dKCIiIiInMOyixkJJwjZBlTN9Tge2H6C+I+ACWea1zm9yOiqxG3ER0ZRJTKS4KAg\nOp93AbPWri7UudWio6kWFQ1ATFgYEeXKsefQQSfTPalVK1YQX7UqVeLjCQ4O5vIrr2LWb795xVSq\nXIU69eqd8MvWrz//ROu27QjxY7Fm+cI/aNGxE8YYatZrQPrBg6Tt2e0Vk7ZnN4fTD1GzfgOMMbTo\n2InlC7y/JFtrWTpvDk3bZY3MqVqzNuGRUQBUqloNl8uFy+XyzUUBK9avp2rFSsRXrEhwcDBXte/A\nbwvme8WUzy7GAKQfOYzJrm02rFWb2Kis3OtUq0aGy0WGD3M/nlXbthIfFU2VyKisz9H5FzJr9cpC\nn9+8dl3KlirtYIanbuXWLcRHRVElKuuarriwCbNW5b+mST9Mp3fHSykVHJxz7J+kXTSvUxeAyPKh\nlA8JYXXiNp/lXpCgShXJ3JuGJ20feDwcWb2O0nVre8WEXHge6UuWYY8cAcAeSgcgMCoSAgyuTVuy\njrtckJnp2wsQEREROVcFBJybPye3EKhrjKlpjCkF9AC+yh1gjKmb62EXYP2Z/nOf0yM4kvelERsW\nnvM4Niycldu25ov7dfVKlm7eRLWoKPpf1YW48Ape7Su3bcXldhMfEel4zieSnJREbK6/MMfGxbJy\nxfJTfp6ff5hOj169izK1U7Z3dyoR2QUkgApRUaTtTiU8179x2u5UKnjFRLN3d6rX82xcvZLQ8ArE\nVqqcr48//5hLfM1aBOf6cuq0pNRUKkYfyzk2Korl69bli/vo229596svcLkymTz8uXztP8+dS4Oa\ntby+WPtL0r404sIL8TlauZw/N/1N1egYBlx9LXEVKuSLKS6S09K88osND2flli1eMWsTt7ErbS/t\nGzbi/Vm/5RyvW6kyM1etoPOFF7ErbS9rErexa+9eGuca5eFrgaHl8Ozbn/PYs38/QZW8R6MERUQA\nUOHft2ACDAfn/EHGP5sJjIzAHj5C2HVdCawQRsamLRyc+TtoFIeIiIiInCZrbaYx5iHgByAQmGKt\nXWmMGQYsstZ+BTxkjLkccAF7OMPpKeBwgcMYcyVZQ1F+sdZuynX8TmvtFCf7huMswZpnJlD7+g25\n4vwLKRUUxGcL5zPs808Yd8fdOe0p+/cx9POPGXzdTf4dgg7YAq7IFDi16fhSkpPZuH4DrVq3Kaq0\nTkvB351MnpgCrtd4xyyeM4um7Trki9uxdTNfvf8WDzw17AyyPHUFvkYm/2vUo0sXenTpwnczf2Py\ntKkM7z8gp23Dls2MfuctJg7xbe6nIu8ltW/QkCsuuCjrc7RgHkM/ncr4u+71T3KFcLK3n8fjYdQ3\nXzH45h75wq5t1oJ/kpK4/X+jqRQRwQXVaxDo53tDwVMc8wgwBEVUYO+HnxAQWp6If9/M7jfewwQY\ngqtWYfeb7+PZt5+w7tcQcn4jDv9V+FE6IiIiIiJ5WWu/A77Lc2xwrt8fKeo+Hfu/cmPM88D/AecD\nvxhj+uVqfugE5/U1xiwyxix665efziiH2LBwkval5TxO2pdGTGiYV0x42bKUCsqq83Rv2pw1OxJz\n2g4ePsyj77/DvZ06e83B95fY2DiSdu3MeZy0K4nomNhTeo5ffvqRjp06EeSHkQGzpn/LiwMf5sWB\nDxMeGcme1JSctr2pqYRHeo+QqRAVzV6vmBSvER5ut5tlC+ZxcZv2XuftSU1h8ivP0/uhAcRUrOTQ\n1RQsLiqanSnHck5KTSU28vgjf65q34Ff5x+bdrMrJYUBLzzP8P4DqFrJt7kfT2xYOLvSvD9H0fk+\nR+WOfY6atWTN9kSKs9jwcHbt3ZvzOCktjZhco70OHTnCxp07uD9hPN1fHM6KLZsZ+NYUVm3bSlBg\nII9e2533+z/GiNvvZH96OlVzjdrxB/f+A1kLhGYLCA3Fc8B7Sp1n/wGOrP8bPB48aftwp+4hMKIC\n7v0HyNyVnDW9xVoy1m8kKO7U7isiIiIiIsWBk392vBboZK3tDzQFrjbGjMpuO+6fG621CdbaZtba\nZndc1vmMEmhYuQpbU1PYvmc3rsxMflrxF+3rN/SKSdl/bKeA2WtXUyM663/sXZmZPDH1Pa65sAmX\nNT7/jPIoKg0bN2brli1sT9yGy+Xi5x+m0/6Sjic/MZefpn9P56uucijDE+twVReeHDGGJ0eM4YLm\nrVgwcwbWWv5Zt4aQsmW9ihcA4RGRhJQpwz/r1mCtZcHMGZzfvFVO+9q//iSuchWvqS6HDh5g4gtD\n6XbrbdRq0Mhn13ZU47p12bJjO9t27cTlcjF99iw6tmjhFbN5+7G1dWYtWkS17Ok1+w4c4KFnh/JI\n79to0tD3uR9PwyrxWZ+j3dmfo+XL6JDn39brc7RmFTVOsfDma43iq7I1NYXE3am4MjP5cdlS2jds\nnNNevkwZfnrmWb588im+fPIpzqtWnRF33Emj+KoczsggPSNrHYv569YSGBiYb3FSX8vcsZOgiAoE\nhIdBQAClG9bjyIaNXjFH1m8kuFo8AKZMCIGREbj3ppG5YxcmpDQme02e4OpVcaek5utDRERERE6d\nMeac/CmunJyiEmStzQSw1u41xlwLJBhjPiZrj1vHBQUGMvCabjzy7pt4rKVrk6bUio0jYcZPNKgc\nT4cGDZk2fx6z164mMCCAsDJlePq6GwH4eeVylm7eRNqhdL79cwkAT193I/UKWOvBV4KCgnjsif/Q\n/4H78Xg8dO1+HbVq1yFh/DgaNmpM+0suYdXKFTz56AD279vHnFkzeX3ieD749HMAdmxPZNfOnTRp\n2sxv13BU44ubsWrpIob160twqaxtYo96ceDDPDliDAD/uueBnG1iG17UlEZNmubELf59Vs7iokfN\nmv4tKTt3MP2TqUz/ZCoADz49jNBw36wHERQYyH/63sf9Q57B4/Fw3WWXU6dadca9/x6N69TlkpYt\n+ejbb/hj2Z8EBwURWq48z/bvD8BH333Llh07SJg2lYRpWblPGDKMKD+vZREUGMjArt15+O3X8Xg8\nXNu0ObXiKjLp5x9oWCWeDg0bM3Xe78xesyrnczT4xltyzu87eTybk5NJzzhC15ef46nrb6JV3fp+\nvKKsaxrU/QYefiMBj8dybfMW1K5YkUk/TqdhfDwdGp133HN3HzjAw28kEGAMMeHhDP1XTx9mfhzW\nsv+nX6lwy/UYY0hfvhJ3ym7KtWuFa2cSGRv+JuOfzZSqWZ3Iu3qDtRz4bTb28GEADvw6m4geN4Ax\nuHYmkb5shZ8vSERERETk1BmntgM0xnwDvGKtnZnn+HDgv9bak44e2fPhp+fUKne2exd/p1DkFm3Y\ncvKgs0gHn5TefOvw8sLtHHS2MMGB/k6hyB1Zu8HfKRS52Cf6+zsFEREROTsU3+EARSDj703n1Hfa\no0rVqlEsXzcnp6jcDCzIe9Ba+xS59sM1xjTOGyMiIiIiIiIiciocm6JirU0/QVvuFQjfBS52Kg8R\nERERERERv/D7bnslS3H41y6WQ1tERERERERE5OxRHAoc5+ScJBERERERERHxneJQ4BARERERERER\nOSPFocCR4e8EREREREREROTs5tgiowDGmIoA1tqdxpgYoD2w1lq78miMtbaVkzmIiIiIiIiI+IXR\nkpO+5NgIDmPMvcA84A9jzP3AN0BX4DNjzF1O9SsiIiIiIiIiJY+TIzgeAhoDZYDNQJ3skRwRwK/A\nGw72LSIiIiIiFNjhrgAAIABJREFUIiIliJMFDpe19hBwyBiz0Vq7E8Bau8cYo51TRERERERERKTI\nOFng8Bhjgq21LqDL0YPGmBCKx+KmIiIiIiIiIs7RGhw+5WSh4QbAAlhrt+U6HgU85mC/IiIiIiIi\nIlLCODaCw1q75TjHE4FEp/oVERERERERkZLHL1NFjDHL/dGviIiIiIiIiJybHBvBYYy54XhNQEWn\n+hUREREREREpDkyA1uDwJScXGZ0KvE/2Ohx5hDjYr4iIiIiIiIiUME4WOP4CRlhrV+RtMMZc7mC/\nIiIiIiIiIlLCOLkGR39g33HarnewXxEREREREREpYZzcRWX2CZo1EUlERERERETObcYv+3qUWE5O\nUfFijGkE9AB6AmlAM1/1LSIiIiIiIiLnNkcLHMaY6mQVNHoCmUB1oJm1dpOT/YqIiIiIiIhIyeLY\neBljzFzgOyAYuMla2xTYr+KGiIiIiIiIiBQ1JycEJQOhQBwQk32soC1jRURERERERETOiJOLjHY3\nxoQDNwJDjTF1gArGmBbW2gVO9SsiIiIiIiJSLBjtr+FLjq7BYa1NA6YAU4wxccC/gNHGmKrW2qpO\n9i0iIiIiIiIiJYfP9qyx1u6y1o6x1rYB2vmqXxERERERERE59zk2gsMY8zUnXnOjm1N9i4iIiIiI\niEjJ4uQUlREOPreIiIiIiIhI8RagNTh8yVjr/MYmxpgYAGtt8qmc9+Nf686pXVfioyP8nUKRqxoa\n4u8UitScvxP9nUKRa1qrmr9TKFLhO3f4O4UityL43PochQQH+zsFRzSuEuvvFERERM5F53QFwLVz\n1zn1nfao4IpxxfJ1c3QNDmPMM8aYFGANsM4Yk2yMGexknyIiIiIiIiJS8jhW4DDGDCBrMdHm1too\na20E0BJom90mIiIiIiIiIlIknFyD4zags7U25egBa+3fxphewI/AKAf7FhEREREREfErY3y2cang\n7BSV4NzFjaOy1+E4Nydoi4iIiIiIiIhfOFngyDjNNhERERERERGRU+LkFJULjTH7CjhugHNrywAR\nERERERER8auTFjiMMVHArUCD7EOrgQ+ttaknOs9aG3jm6YmIiIiIiIicpQKK5W6q56wTTlExxjQE\nVgBNgXXAeqA5sNwY0+BE54qIiIiIiIiI+MrJRnA8CzxirZ2W+6Ax5kbgOeBGpxITERERERERESms\nky0yen7e4gaAtfZT4DxnUhIREREREREROTUnK3AcPM02ERERERERERGfOdkUlVhjzKMFHDdAjAP5\niIiIiIiIiJwT0kNK+zsFR4T6O4HjOFmBYzLHz/31Is5FREREREREROS0nLDAYa0d6qtERERERERE\nRERO1wkLHMaYMSdqt9Y+XLTpiIiIiIiIiIicupNNUVnskyxERERERERERM7AyaaovO2rRERERERE\nRERETtfJRnAAYIypBwwEauQ+x1rbyZm0REREREREREQKr1AFDuBjYCJZO6e4nUtHREREREREROTU\nFbbAkWmtneBoJiIiIiIiIiIipymgkHFfG2MeMMZUMsZEHv1xNDMRERERERERkUIq7AiO27P/OyjX\nMQvUKtp0REREREREREROXaEKHNbamk4nIiIiIiIiIiJyugq7i0owcD/QIfvQb8Aka63LobxERERE\nRERERAqtsFNUJgDBwPjsx72zj93tRFIiIiIiIiIiIqeisAWO5tbaC3M9nmGMWeZEQiIiIiIiIiIi\np6qwBQ63Maa2tXYjgDGmFuB2Lq0zY63l0zcTWLlkMaVKl6bXg49QtVadfHFbNm7gvXGjcWVk0Pji\nptzYpy/GGKaMfImk7YkApB86SJmy5XhyxBjWLFvKV++/TWZmJkFBQXTv3Yf651+Y73mL2pIFf/DG\n2NfwuD1c3qUrN97a26vdlZHBay8MZ+O6tYSGhTHwmWHEVqxE0s4d9Lv931SuWg2Aeo0ac/+jWevE\nzv7lJz55/12MMURGRdH//wYTFl7B8WspyNy5cxkxYgQej4frrruOO+64w6v9vffe48svvyQwMJCI\niAgGDx5MpUqVAOjXrx/Lly/noosuYvTo0X7IPou1ls/enMzqpYsJLl2aWx94hKq1aueL2/r3Bj4Y\nNwZXxhEaNmnKDX3uwRjDtk1/8/HkCbgyXAQGBnDT3fdRvU49diVu44PxY9j2z0a69OhFp27X++Hq\nYP7c33ltxCt4PB66Xncdve6406v9zyWLGfPqCP7esJ5nnnuBSy/v7NV+8MABet18Ax0u6cSAJ570\nZeqFMmfxIl5KmITH4+GGK67krptv8Wqf9t23fPTtNwQGBFK2TAiDH3qY2tWq+Snbgi1buIB3Jo7F\n4/Zw6dXX0O1ft3q1uzIymPDKi/yzfh3lw8J4+L+DialYkeWLF/HhlMm4MzMJDAri3/fcS+OLLvbT\nVXhbsmA+U8a+hsfj4fJrunLDrb282l0ZGbz24nP8nX3ve2zw0Jx738N39PK69903YKA/LkFERERE\nfKiwBY5BwK/GmL8BA1QH+jiW1RlatXQxSTu2M/h/k9i0fi1TJ09g4Auv5oubOnk8Pe99iBr16jPh\n+SGs+nMxjZs0485Hn8iJ+eztNyhTtiwA5cLCuPfJpwmPjGL7ls2MHz6Y4QlvO3otbrebhNdGMuSV\nUUTFxPL4fXfTok07qtY4tu7rz999Q7nQUCa8P5XZM37mnUkTGPjMMADiKldh1Otv5XnOTF4f+xr/\ne+s9wsIr8PbE8Xz3+af0uOMuR6+lIG63m5deeolx48YRFxfHbbfdRocOHahV69gGPQ0aNOCmm24i\nJCSETz75hDFjxvDCCy8A0Lt3bw4fPsxnn33m89xzW710Mck7d/B/Yyayef06Pn59Ao8+PyJf3MeT\nJ3LLvQ9Qo259Jr0wjNV/LqFRk6Z8/d7bXHlTDxo1acqqJYv46r236TfkOcqWL8+Nfe5h+cI//HBV\nWdxuNyNfepFR4yYQExfHPbf9m7YdOlIzVwEnrmIl/jtkKB+9+06Bz/H6xPFcdHFTX6V8StxuN89P\nGE/C8OeIi4qm54D+XNKylVcB45pLLuWWa7oA8Ov8P3jl9clMHPasv1LOx+N28+a41/jPC68QFR3D\nU/3u5+JWbYivXiMn5rcfvqdc+VBGvfUec3+bwYdvJPDw/w0mNDycQcOeIyIqmq2b/uHF/z7OuA8+\n9t/FZHO73Ux+bSTPvDKKqJgYHr//Hpq3aet97/v+W8qHhjL+vY+YM+Nn3kmYyMDBQ4Gse9/IyW/6\nK30RERER8YOAwgRZa38B6gIPZ//Ut9b+6mRiZ2L5wj9o0bETxhhq1mtA+sGDpO3Z7RWTtmc3h9MP\nUbN+A4wxtOjYieULvL9EWmtZOm8OTdt1BKBqzdqER0YBUKlqNVwuFy6Xs+usrl+zmkqV46lYuQrB\nwcG063Q5C36f4xWz4Pc5XHrl1QC06XgJfy1ZjLX2uM9pLWDhcPphrLUcOnSQyKhoJy/juFauXEnV\nqlWJj48nODiYK664gpkzZ3rFNGvWjJCQEADOO+88du3aldPWokULymYXoPxp+aIFNO9wKcYYatSr\nf+L3XL2s91zzDpeyfOH8rEYDh9MPAZB+6BDhEZEAhIZXoFqdugQEFrYWWfRWr1xBlapVqZz9Gl12\nxZXMmfmbV0ylypWpU7ceJiD/LWXt6lXsTk2leavWPsr41KxYt45qlSoTX7ESwcHBXNWhA7/+Mc8r\npnyu91j64cMY4+ssT2zD2jXEVa5CXKXKBAUH0/qSTiyeN9crZtG832nf+QoAWrbvyIo/l2CtpUad\nukRkf/7jq9fAleHClZHh82vIa8Oa1VSqUoWKlStn3/suY8Fc73vfwt9nc+kVVwHQuuMlLD/JvU9E\nREREzm0n/NZkjOlkrZ1hjLkhT1NtYwzWWv/+2fw49u5OzfkfdoAKUVGk7U7N+dIIkLY7lQpeMdHs\n3Z3q9TwbV68kNLwCsZUq5+vjzz/mEl+zFsHBwQ5cwTG7U5KJjo3NeRwVE8O61au8YlJzxQQGBlG2\nfDn270sDIGnnDh69pw9lypbj33fdQ6MLLiQoKIh7BzxG/7tuIySkDJXi4+n7yKOOXsfxJCUlERcX\nl/M4NjaWFStWHDf+yy+/pE2bNr5I7ZSk7U4lItr7/VTwey4qV0zW+xLg+tvvZuJzQ/jq3TexHssj\nw1/yXfInkZyURGyu1ygmNo7VJ3iNcvN4PIwdNZKnhg1n8cIFTqV4RnalphIXc+y1i4uOZvnatfni\nPvrma9754nNcmZm8/twLvkzxpPakphAVc+w+ERkdzYY1q71jUo7FBAYGUrZcOfbv20dYeHhOzII5\ns6heuw7BpUr5JvETSE1JJir3vS86hvWrV+eJScmJCQwMyr6mY/e+x/reSZmyZbn1zqx7n4iIiIic\n2042gqNj9n+vLeCn6+l2aozpfPKo01fwH/BMnpj8QSbPn2UXz5lF03Yd8sXt2LqZr95/ix59HzyD\nLAunMHkWfMGGiMgoEj76lJGT3+TOBx5i5PChHDp4kMzMTKZ/+QWvJrzJG598QfVatfnsg3eduYDT\nkO/6sn333XesXr2a2267zccZFUKhXqf8p5ns9+XvP37P9bffxZAJU7ju9rv4aOL/nMiy6BRyBMPn\nH0+jVdt2xFWs6Gw+Z6QQrx3Qo+u1fPf6FPrf0YeEqR/5IrFCK8x9ouCYY79v2/QPH76RwN2PDCjy\n/E5Lwbe1PDEFXNPRe9+Hn/BqwhT6PNCPUc8N49DBg46kKSIiIiLFxwlHcFhrn8n+dZi19p/cbcaY\nmgWcUlhvAAWu0GeM6Qv0BXjk6WFcc9O/CvWEs6Z/y9yffwCgWp267ElNyWnbm5pKeGSkV3yFqGj2\nesWkeP213e12s2zBPAa9NMrrvD2pKUx+5Xl6PzSAmIqVCpXbmYiKiSUlKSnncWpycr7pJEdjomNi\ncbszOXTgIKFhYRhjcv4SW7t+AypWrsz2bVtzvuhUqlIFgLaXdOKzD99z/FoKEhsb6zXlJCkpiZiY\nmHxx8+fPZ8qUKSQkJFCqGPx1GWD29G+Z98tPAFSrXYc9Kd7vp7AI7/dceFQUe1NTc8WkEpb9vlw4\n81du6HMPABe1bstHk8Y6nX6hxcTGkpTrNUpO2kV0Aa9RQVYu/4tlS5fyxSfTSD+UjivTRZmyZbiv\n3yNOpXvK4qKi2ZV87LXblZJCTJ77RW5Xd+jIc+PH+SK1QouMjiE1+dh9YndKitcoNoDImKyYqJgY\n3G43hw4epHxoGJB1Xxk57BnuH/Qf4ipX8WnuxxMVE0Nq7ntfSjKR0XnvfVkxOfe+gwcpn/feV69+\nzr2vTv0GPr0GEREREfGtQq3BAXxawLFPTnSCMear4/x8DUQd7zxrbYK1tpm1tllhixsAHa7qwpMj\nxvDkiDFc0LwVC2bOwFrLP+vWEFK2rFfxAiA8IpKQMmX4Z90arLUsmDmD85u3ymlf+9efxFWu4vUl\n4dDBA0x8YSjdbr2NWg0aFTq3M1G3QQN2JG5l147tuFwu5sz4meZt2nrFNG/Tll9/+B6AuTN/4/wm\nF2OMIW3vHtzurM1udm5PZEfiNuIqVSYqOoZtmzeRtncPAMsWLyS+WnWfXE9ejRo1YuvWrSQmJuJy\nufjxxx/p0MF71MyaNWt4/vnnGTlyJJEn+OLpa+2v6sLjr4zm8VdGc36LViyc9SvWWjatW0uZsuUK\nfM+VLlOGTevWYq1l4axfOb9ZCwDCIiPZsCpr2sf6FX8RUzH/tCh/adCoMdu2bmF79mv0y48/0K7D\nJYU6d/Dw5/n02+/5+OvveKD/AK66pmuxKm4ANK5Xj83bt7Nt505cLhfTZ83ikpatvGI2Jybm/D5r\n4UKqVS4+rw9kFTB3JiaStHMHmS4X836bQdM8a540bdWG2T/9CMD82TNpfGETjDEcPHCAV57+Dz36\n3E39xuf5I/0C1WnQgB2J23Ld+36heet2XjHN27Tj1x+nAzDvuPe+7ezYlnXvExEREZFzmznRgmzG\nmAZAY+BlsnZSOSoMGGStbXyCc/cAvYADeZuAqdbauPxnefvxr3WntVqctZaP35jI6j+XEFwqa5vY\narXrAvDiwId5csQYALZsXJ+zTWzDi5py81335gzrfnfsKGrWa0C7K67Oed7pn07lp88/9vry+eDT\nwwgt5Paq8dERp3M5LP5jHm+My9oq8bKru3Bzr9v5YMrr1KnfgBZt25GRcYTRzz/LP+vXUz4sjMee\nHkLFylWYN/M3PnzzdQIDAwkIDKTHHXfSvE3WF4TpX33BN59+TFBQEDFxcfR74v+85uIXVtXQkNO6\nptzmzJnDyJEjcbvddOvWjbvuuouJEyfSsGFDOnbsyAMPPMCGDRuIzv7rbVxcHKNGZY2sufvuu9m0\naRPp6emEh4fz9NNP07r16S9mOefvxJMHFcBay6dvTGL1sqWUKlWang/0y3nPvTyoP4+/krWF7ZaN\n6/lg/Jjs99zF3Hhn1tbEf69ZxWdvvo7H4yYoOJib776PqrXqsG/vHl598jEOpx/CmABKh4Twn5Fj\nCTmFhVWb1jrz7UznzZnNmJEj8Lg9dOnWndvuupvXJ46nQcNGtOt4CatXruT/Bj3K/n37KFW6NJFR\nUbw7zbsu+t3XX7F21aoz3iY2fOeOMzq/ILMXLuTlyZNwezxc1/kK+v6rB+Pee5dGdetyactWvDhp\nIvOX/UlQYBBh5cvzn/vup071oisKrgg+88/R0gV/8O7E8Xg8bi654mquu7UXH7/9JrXq1aNp67Zk\nZGQw/uXn2bxhA+VCQ+n336f/n737Do+iavs4/j1JNiEhCekJKYReQu8IUgWsD6KPig3EBjYsKL62\nx64IAiqKYMOCXWxYsKBSBKT33jtpBEIJpOx5/0gICUkANbtL4Pe5Li+zM2d27sMMQ/bec+5DdNVY\nvv54ApM+/YSYuGMjNx4aOpwqIf/seQVQqZxqEy34azbjXx+NMy//2XfF9f345N23qVX32LPvleef\nZdP6dQQGBTP4f08SExvL7OlT+fTdd/Dy9sbLy4ur+99cIjH8TzSMizp5IxEREfm7TrPy7eVr//79\nZ2QF9KCgoNPyup0swXEp0BvoBUwqsms/8Km1dlapB+YfOxkYXtpqK8aY6dbaksUtjvNPExynq3+a\n4DidlUeC43TyTxMcp7PySHCcTlyR4PC08khwnE7KK8FxulGCQ0RExCVOyw/K5UUJDvc6WQ2Ob4Fv\njTHnWGtnn6htKcdeeIJ9J01uiIiIiIiIiIicqlOtwXGZMSbYGOMwxvxmjEkzxlxfHgEYY/5W4kRE\nRERERERE5HinmuDoaa3NJH9p2O1AXYrX5Pg3zqyx2SIiIiIiIiLidqea4Dg6ofoi4BNr7Z5yjOGM\nnJMkIiIiIiIiIu5zwhocRXxnjFkNZAF3GGMigcOuC0tERERERERE5NSd0ggOa+1DwDlAK2ttDnAI\nuLScYjgtq6+KiIiIiIiISMVxSgkOY0wAcCcwtmBTLNCqnGLoW07vIyIiIiIiIiJnqVOtwfEukA20\nL3i9HXj2n57UGLPs6M/W2uX/9H1ERERERERERODUa3DUstb2McZcA2CtzTLGnHBqiTHm8rJ2ATF/\nI0YRERERERERkRM61QRHtjHGn4IVT4wxtYAjJznmM+AjSl8lRUvDioiIiIiIiEi5OdUExxPAT0CC\nMeYjoAPQ/yTHLAVGlDYFxRjT/e8EKSIiIiIiIiJyIqeU4LDW/mqMWQi0I3+KyT3W2rSTHHYvkFnG\nvstOPUQRERERERERkRM7pQSHMaZTwY/7C/6fZIzBWju9rGOstTNO9JanGJ+IiIiIiIiIyEmd6hSV\nIUV+rgS0ARYA3U71RMaYJOBq4BpgH+W3zKyIiIiIiIiInOVOdYrKf4q+NsYkAMNPdpwxJpH8hMY1\nQC6QCLSy1m7+25GKiIiIiIiIiJTB6x8etx1odKIGxphZwI+AA7jCWtsS2K/khoiIiIiIiIiUt1Ot\nwfEqx5Z79QKaA0tOclgqEA9EA5HAOkpfMlZERERERERE5F851RocqwHvgp/TgU+stTNPdIC19lJj\nTBXgv8BTxpjaQIgxpo21du4/jlhERERERERE5DgnTHAYYxzAi0A/YDP5q59EAa8CM40xza21i8o6\n3lq7DxgPjDfGRAN9gJeNMQnW2oTy6YKIiIiIiIjI6SfH2+HpEM4qJ6vBMRIIBBKttS2stc2BBkBN\nY8xY4KtTPZG1NtlaO9pa2x449x9HLCIiIiIiIiJynJNNUbkIqGOtLaydYa3NNMbcDqQBF5Z1oDHm\nO05cc6PX3wlURERERERERKQsJ0twOIsmN46y1uYZY1KttX+d4NgR/y40EREREREREZFTc7IEx0pj\nTD9r7QdFNxpjrgdWnehAa+20Iu0jC7al/tNARURERERERCqSksMFxJVOluC4E/jKGHMTsID8KSet\nAX/gspO9uTHmCWAQ+cVJvYwxucCr1tqn/1XUIiIiIiIiIiJFnDDBYa3dAbQ1xnQDGpKfqJhsrf3t\nZG9sjLmP/GKira21mwq21QTGGmPus9a+9K+jFxERERERERHh5CM4ALDW/g78/jffux/Qw1qbVuR9\nNhZMb/kFUIJDRERERERERMrFyZaJ/TccRZMbRxXU4dBiwCIiIiIiIiJSbk5pBMc/lP0P94mIiIiI\niIhUeE5VGXUrVyY4mhpjMkvZboBKp/IGKZn7yzciDzuSm+fpEMpdgF9VT4dQrowxng6h3G1Ny/B0\nCOWqXkyUp0Mod6mbdno6hHJ1JDvX0yGUu66pO8lc6ukoylfwhT08HYKIiIhIuXJZgsNa6+2q9xYR\nERERERERKcqVNThERERERERERNzClVNURERERERERM5aVjU43EojOERERERERESkwlOCQ0RERERE\nREQqPCU4RERERERERKTCUw0OERERERERERdQDQ730ggOEREREREREanwlOAQERERERERkQpPCQ4R\nERERERERqfBUg0NERERERETEBZyqweFWGsEhIiIiIiIiIhWeEhwiIiIiIiIiUuEpwSEiIiIiIiIi\nFZ4SHCIiIiIiIiJS4anIqIiIiIiIiIgLqMaoe2kEh4iIiIiIiIhUeEpwiIiIiIiIiEiFpwSHiIiI\niIiIiFR4qsEhIiIiIiIi4gJWRTjcSiM4RERERERERKTCU4JDRERERERERCo8JThEREREREREpMJT\nDQ4RERERERERF3CiGhzupBEcIiIiIiIiIlLhKcEhIiIiIiIiIhXeGT9FxVrLz598wPpli3H4+tLr\nptuomlijRLvfv/qMZbNmkHXoIA+9/m6xfSvm/cX0b78EA9EJiVw+4C53hQ/k9+Hb999m1eIF+Pr6\n0ef2u4mvUatEu+0b1/PpuNHkZGfToFlLLr3hFowx7NyyiS/fGceRw1mERkZx3Z2DqRQQwNqli/nh\n0w/Iy83F28eHS67tT51GTdzSp3l/zWbcy6PIy3Ny4X960affDcX2Z2dn8+IzT7Fu9WqCq1ThkWee\nJaZqLDk5ObwybCjrVq/GeBluv3cwTVu0BOCPX37m0w/exxhDWEQE//fEU1QJCXFLf6y1fPXuW6xc\nOB+Hnx/X3XkvCTVLXqNtG9bz0ZhXyMk+QlKLVlx+460YY3hv1HBSdu4AIOvQQfwDKvPgiFcA2LFl\nE5+/8TqHsw5hjBf3vzASh6+vy/u0ZP5cJox9DafTSZcLLqJXn2uL7c/JzmbsiBfYvG4tgcHBDHr4\ncSJjYtifuY9Xnn2KjWtX06nH+fS/854S7z3yiUdJ2b2LYW+Md3k/SjNr1ixGjBiB0+mkd+/e9O/f\nv9j+hQsXMnLkSNavX89zzz1H9+7dC/eNHj2aP//8E4BbbrmFnj17ujP0Ylx1321Zt5bP3hiTfw4s\nF1x5DU3bnuPWvkF+/yZ98A6rlyzE4evHVQPvKvXZ99PnH7FgxlSyDh7k2fEfF27fuGoFkz4cz+6t\nW7j2rsE0adveneGXMGvVSkZ+NRGndXJpu/b07176vfPb4kU89N47vD94CEnVEgFYt3MHQz/7hANH\nDuNlDO8PfhA/h8Od4YuIiIic9s74BMf6ZYvZk7ybO58fxY6N6/lxwnhufuyZEu3qNm1B6249GfPI\n4GLb05N3MfOHb+n/8BP4Vw7kYOY+d4VeaPXiBaTu3sVDL41l6/q1fPnOOO559sUS7b4c/wZX3HIH\niXXq8fawZ1i9ZCENmrXk8zfH8J/r+lMrqRFz/5jC1O+/5oKrrqNyUDA3PfAYVcLC2LVtC28NfYrH\nX3f9B868vDzGjHiRoa+8SkRUFINu7k+7jh1JrFGzsM3P300iMCiI9774kqm//sI7r4/h0WeeY/Kk\nbwB448OP2btnD4/efy+vvvMe1ulk7Msv8dbHn1IlJIS3x7zKpIlf0PeWW13eH4CVixaQumsnj736\nBlvWreGLt8YyeOiIEu0+f2ssfQbeSfW69Xjj+adYtXghSc1b0n/wg4Vtvn7/HfwDKgP5f1YTRo+i\n76DBxFWvwcH9mXh7e7u8P868PN4b8woPP/8iYRGR/O/u22nRrj3xidUL20z9eTKVA4MY9e6HzJ76\nO5+Mf5O7H3kch68vV/a7kW1bNrF986YS7z3vz+n4+fu7vA9lycvLY9iwYYwZM4bo6Gj69etHp06d\nqFnz2P0XExPDk08+yYQJE4od++eff7J69Wo+/vhjcnJyGDBgAO3btycwMNDd3QBcd99VrZbI/cNG\n4e3tzb6MPQx/4B4atWrjlnuvqNVLFpK2excPjhzD1vVr+frdNxn09LAS7Ro0b0X7Hhcy/P7iyeeQ\niEj6DBzEtB++dVfIZcpzOhk+8XNeu/0uokNCuGHUi3Rq1JiaMVWLtTt4+DCfTZ9KoyJ/13Lz8nh8\nwvs8dX0/6sbFs/fgAXzcfC1ERETkn7FWNTjc6YyforJ28QKatO+IMYb4WnU4fOgQ+/dmlGgXX6sO\nQSGhJbb+Ja7bAAAgAElEQVQvmv4Hrbv1xL9y/geYysFVXB7z8VYsmEurjl0wxpBYpx6HDx0kM2NP\nsTaZGXs4nHWI6nXrY4yhVccurJg/B4DUXTuo2aAhAHWbNGXp3NkAxNWoSZWwMABi4quRm5NDbk6O\ny/uzZuVKYuPjqRoXh8PhoEv3HsyeMb1Ym9kzptPjwosB6Ni1G4vnz8Nay9ZNm2jeqjUAIWFhBAYG\nsXb1qoLSPZbDWVlYazl48CDhEREu78tRy+fNoXXnrhhjqF63PlkHD7LvuGu0r+Aa1aiXf41ad+7K\nsrl/FWtjrWXx7Jm0OLcTAKuXLCI2sTpx1fNHHVUOCsbLDR9sNqxZTXTVOKKqxuLjcNCuczcWzJ5V\nrM2C2TPpVPANdJuOnVmxeCHWWipV8qdeo8Y4HCVHmRzOyuLHrybS+5rrXd6HsqxYsYKEhATi4+Nx\nOBz07NmTadOmFWsTGxtLnTp18PIq/ojcuHEjLVq0wMfHB39/f+rUqcPs2bPdGX4xrrrvfP38CpMZ\nudnZYNzTn+OtXDCXFkWefVmlPPsAEuvUIzg0rMT2sMgoqlarjjGe/6duxZbNJEREEB8RgcPHhx7N\nWzBt2dIS7cb9+D19z+uOr8+x7x/mrFlN7dg46sbFAxBSORBvL8/3SUREROR0c8b/hrQ/I4PgsGO/\n+AaHhpWa4ChL+u5dpCfv4t2hTzL+ucdZv2yJK8I8oX179hASfuzDepWwcPbt2VOyTVj4sTbhx9rE\nxFdjxYK5ACz5axb70tNKnGPp3NnEVa+BjxuGPKenphAZHV34OiIyirTU1GJt0lJTiYyOAsDbx4fK\nlQPJ3LePmrXrMHvGdPJyc9m9cyfr1qwmNTkZHx8fBj3wILf1vZZre13M1k2bOP8/vVzel6P27kkn\nJDyy8HX+n396sTb79qQXu44h4RHsPa7NhlUrCKoSQlTVWCA/OWUwjH32CV588F5++/ZLF/bimD3p\naYRHRhW+DouIICO9+DXKSE8jrKCNt7c3AZUrcyAz84Tv+8UH47nov1fi51ep/IM+RSkpKUQXuf+i\noqJISUk5pWPr1q3LrFmzOHz4MHv37mXBggUkJye7KtSTctV9B7B53RqG3ncnL9x/N1fdeofbR29A\nyWdfSFh4iQRORZG6bx/RoceS6NEhoaTuKz4icM32bSTvzaBjw8bFtm9JScEYGDT2Na4f8QIf/Par\nW2IWERERqWhcmuAwxgQbY0pMmDbGuKfQA6UPCfo7X0Zap5M9ybvpN+QxLhtwF9+//xaHDx0svwBP\nJYbS+nBcJ2xpyw8VtOkzcBCzfvmRlx4ZzJGsLLx9iicxdm/byo8fv89/b7m9vEI+odIGaZnjOlRa\nf4wxnH/Jf4iIiuKum/sz9uVRJDVujLe3N7m5uXz/9VeMeW8CH0/6gRq1a/PZB++7pgOlKfWP/7g+\nldbmuH4v/HM6Lc7tWPjamedk4+qV9L37fu55ZhhL5/zFGnck2Uq9547vT9n3XGk2b1hP8s4dtO7Q\nsexGHnJ838rSrl07OnTowE033cQjjzxC44L7z2NcdN8BVK9Tj4dfGsP9L4xkytcTycnO/tfh/n0n\nvw8ritKfacd+djqdjPr6S+699PIS7fKceSzZuJFn+vbn7bsHM3XpEuauXePKcEVEREQqJJfV4DDG\nXAW8DKQYYxxAf2vtvILd7wEtyjhuADAA4MYhj9CtV8lf9k5m3u+/sGj6HwDEVq9JZpHRDpkZewgs\nZSpKWYJCw4ivWRtvHx9CI6MIj67KnuTdxJZS6K48zfzlR+b8/gsACTXrsLfIqIt9e9JLDMcOCQsv\n9q3svvR0qhS0iYqLZ8AjTwH5IwJWLV5Q2G5vehrvjXqBq++4l4jo4nPBXSUiMorUIt96p6WmlJhO\nEhkZRWpyCpFR0eTl5nLw4AGCgoMxxnDbPfcVtrt3wC3EJSSwYe1aAGLj84dwd+7Wnc8+dG2CY8ZP\nPzB7Sv41qla7DnuLjHDYl55ebOQQQEh4eLHruDc9rfAaQX5tiCVzZzNk2EvFjqmd1IjA4GAAklq0\nZPvGDdRr3NQlfToqLCKS9NRjoxr2pKUREhZRos2e1BTCIyPJy8vj0MGDBAYFl/me61etYNO6ddzT\n7xrynHlk7t3Ls0Pu47EXXyrzGFeIiooqNuoiJSWFyMjIExxR3M0338zNN98MwKOPPkpCQkK5x3gi\n7rjvioqJT8C3UiV2bdtCtVp1yrMrpZr1y2Tm/JE/QiGhZu3ise9JJ/hvPL9PJ1FVQkjOODZ6MHlv\nBhFFpjweOnKEDbt3cdtr+cWF0/dncv/bbzDyloFEh4TQvFZtQgpqvbRPasia7dtoU7eeezshIiIi\nf5tTNTjcypUjOB4BWlprmwE3AhOMMUezFWV+BWetfdNa28pa2+qfJDcAWnfryYAnhzLgyaHUa96K\npbNmYK1l+4Z1VArwL7XWRlnqNW/F5jUrATi0P5M9ybsIKTJ031U69LyIwS+8zOAXXqZhq7bMnzEV\nay1b1q2hUkDlEgmO4NAw/Cr5s2XdGqy1zJ8xlYYt2wCwf99eIP8bwilff8E5550PQNbBA7wz/Fku\nuvp6atRr4PI+HVWvQQN2bN/G7p07ycnJYeqUX2lXMPf/qHYdO/Lr5B8AmPHH7zRt2QpjDIcPH+Zw\nVhYAC+bOwdvbm8QaNYmIjGTr5k3sLfgAsXDeHBJKWS2nPHW84GIeHPEKD454hcat2zJv2h9Ya9m8\ndjWVAgKKfYgEqBIahp+/P5vXrsZay7xpf9CoddvC/WuXLiY6Nr7YkPz6TVuwc+tmso8cIS8vj/Ur\nVxAT7/oP1DXr1Wf3zh2k7N5Fbk4Of037nZbtiq+i0aJde6YXfNCeO2MaDZs2P+G3690vuZQxH3/B\nKx98whMjRlM1Lt7tyQ2ApKQktm3bxo4dO8jJyeGXX36hU6dOJz+Q/GTA3r35f5/WrVvHunXraNeu\nnSvDLcEd91168m7y8vIA2JOaQsrOHYRFRuMO7XteyH1DR3Hf0FE0bNWGhUWeff7+AaXW2qgIkqol\nsjUtlR3paeTk5vLrooV0KrJqVaC/P1OeG8akJ55m0hNP0yixOiNvGUhStUTa1U9i/a4dHM7OJjcv\nj4Ub1lMjOsaDvRERERE5PblyFRVva+0uAGvtXGNMV+B7Y0w8pc9ScInaTZqxftlixjx8Hz6+fvS6\naWDhvjeffJgBTw4FYMoXH7N8zixysrN5+YG7aN6xC50vvYJajZqwccVSxj42BOPlxXlXXktAYJC7\nwgegQfOWrF68gBfuvQ2Hnx99Bt5duG/UQ/cy+IWXAfjvTbfx6bjR5GYfoV6zltRvlr986uJZM5j5\ny2QAGrdpR+su5wEw8+cfSUvexZSvP2fK158DcOvDTxJUxbVLq3r7+HDn4Ad45L67ceY56XnJf6he\nsybvv/UGdes34JyOnbjgkl4Mf/pJ+l/5X4KCg3nk6WcB2Juxh0fvuwdjvAiPjOTBx58EIDwykutu\nuoUH7rgNHx8fomJieOCxx13aj6KSWrRi5aIFPDNoIL6+flx757FrNPyBewqXfL3q1tsLluvMJqlZ\nC5Katyxst3DmjMIij0cFBAbS5ZJLGfnQYDCGpOYtadiytcv74+3tTf87BjHs0f/D6cyjc88Lia9e\ng4kfvEuNOnVpeU4HulxwEWOHP8/gG6+nclAQgx7+X+Hx9/S7hqxDh8jNzWH+7Jk89NzwYiuweJKP\njw9Dhgxh0KBB5OXl0atXL2rVqsW4ceNo0KABnTt3ZsWKFQwZMoTMzExmzJjBm2++yeeff05ubi63\n3pq/Mk/lypV55pln8PHx3GJUrrrvNq5exZRvnsHb2wfjZbjyltsKRxG5U/1mLVm9eCHDBt+Br68f\nVw48tkrKSw8P5r6howD44eMPWDxrOjnZR3jurlto3bU7Pf97Nds2rOODl4Zx6NBBVi2ax69ffsb9\nw19xez8AfLy9efC/V3H3uDHkOS292rajVtWqjPvxexpUq0bnEyzRHRwQwLVdutFv1HAMhg5JDTm3\nYSM3Ri8iIiJSMRhXLVtjjJkF9LXWbiiyLQj4BjjXWut3svf48M8FZ9R4nioBAZ4Oodw1TnTPtBZ3\nWb3DcwUjXSUiyDNLmLpKvQj3f9B2tZmbdno6hHJ1JDvX0yGUu66pZ9Y1Agi+sIenQxAREQGPrdfm\nHpvT955Rn2mPqh4eclpeN1d+9Xg7x92s1tr9xpgLgKtceF4REREREREROcu4LMFhrS11qQdrbQ7w\n0dHXxpjZ1tpzSmsrIiIiIiIiUlE5nWfkAI7TlkuXiT1FlTwdgIiIiIiIiIhUbKdDgkMpLRERERER\nERH5V06HBIeIiIiIiIiIyL/iufUNjzktq6+KiIiIiIiI/BsuWrRUynA6jODo6+kARERERERERKRi\n80iCwxiz7OjP1trlnohBRERERERERM4cLpuiYoy5vKxdQIyrzisiIiIiIiIiZx9X1uD4DPiI0ldJ\n0dKwIiIiIiIickazKsLhVq5McCwFRpQ2BcUY092F5xURERERERGRs4wra3DcC2SWse8yF55XRERE\nRERERM4yLhvBYa2dcYLdWhpWRERERERERMqNK6eoFGOMSQKuBq4B9gGt3HVuEREREREREXdzllqS\nUlzFpQkOY0wi+QmNa4BcIBFoZa3d7MrzioiIiIiIiMjZxWU1OIwxs4AfAQdwhbW2JbBfyQ0RERER\nERERKW+uLDKaCgQB0UBkwTaNzxERERERERGRcueyBIe19lKgMbAQeMoYswkINca0cdU5RURERERE\nROTs5NIaHNbafcB4YLwxJhroA7xsjEmw1ia48twiIiIiIiIinmStJjG4kyunqBRjrU221o621rYH\nznXXeUVERERERETkzOeyERzGmO84cc2NXq46t4iIiIiIiIicXVw5RWWEC99bRERERERERKSQyxIc\n1tppR382xkQWbEt11flERERERERETieqweFeLq3BYYx5whiTBqwG1hpjUo0xj7vynCIiIiIiIiJy\n9nFZgsMYcx/5xURbW2vDrbWhQFugQ8E+EREREREREZFy4coRHP2Aa6y1m45usNZuBK4v2CciIiIi\nIiIiUi5cWWTUYa1NO36jtTbVGONw4XlFREREREREPM6pEhxu5coRHNn/cJ+IiIiIiIiIyN/iyhEc\nTY0xmaVsN0ClU3mDyQtXlm9EHjaq/+WeDqHcBcyZ6+kQypV3TLynQyh3vyxe5ekQylVqzTPvGn09\nZ6mnQyhXlf18PR1Cueteu6qnQyhXeZmZZE7+1dNhlLvgC3t4OgQRERHxIFcuE+vtqvcWERERERER\nESnKlSM4RERERERERM5a1qoIhzu5sgaHiIiIiIiIiIhbKMEhIiIiIiIiIhWeEhwiIiIiIiIiUuEp\nwSEiIiIiIiIiFZ6KjIqIiIiIiIi4gIqMupdGcIiIiIiIiIhIhacEh4iIiIiIiIhUeEpwiIiIiIiI\niEiFpxocIiIiIiIiIi7gVA0Ot9IIDhERERERERGp8JTgEBEREREREZEKTwkOEREREREREanwVIND\nRERERERExAVUg8O9NIJDRERERERERCo8JThEREREREREpMJTgkNEREREREREKjzV4BARERERERFx\nAasaHG6lERwiIiIiIiIiUuEpwSEiIiIiIiIiFZ4SHCIiIiIiIiJS4SnBISIiIiIiIiIVnoqMioiI\niIiIiLiAU0VG3UojOERERERERESkwlOCQ0REREREREQqvLNiikq/Tq1pWj2W7Nw83vh1FptT95TZ\ndvAlXYiqEsRDH30HQLWIUG7q2pZKDh9S9x/k9Z//JCs7x12hlzBn1kxGjxyB05nHxZdexvX9byy2\nf/HCBbw6aiQb16/jieeG0uW87sX2HzxwgL5X/ZeOXbpy34MPuTP0Ms1auYIREz/H6XTSu30H+ve8\noNR2UxYt4KF33uKDIQ+TlJhYuH33nj1c+exTDLjoYvp27+musIux1jJx/JusWDQfX18/+t51Lwk1\na5dot3XDeiaMeYmc7GwaNm/FFTcNwBgDwNQfv2P6T9/j5eVNo5at6N33JlYtWcSkj94jNzcXHx8f\neve9iXqNm7q5d/l6NKlLregIcvPy+G7BSpL37S+238fbi8vbNCG0sj9Oa1m3O42pK9YDEOxfiUta\nJBHg5yArO5dJ85ez//ARt8ZvreWrd99i1aIFOPz8uPaOe0ioWatEu20b1/PxmNHkZB+hQfOWXH7j\nrRhj2L55I1+8NZac7By8vb244pbbSKxdl+Qd2/n49dFs37SBi6++nm69LnNrv4rq0745jRNiyM7N\n472pc9mavrfMtnee34GIoECemvgzAL1aNaJZYizWWvYfPsK7U+ey79Bhd4VepsvaNKZBXDQ5uXl8\nMnMh2/fsK9FmQPdzCPavhLeXYWNyOhPnLMFaiA0N5sp2zfB1eJNxIIsJM+ZzJCfXA73IN3PZUkZ8\n/CF51sllHTtz48X/KbZ/4h+/8/nvU/Dy8iLAz4/HbriJmnFx5OTm8uz777Jq8yaMMQy59npa1W/g\noV4UN2vVSkZ+NRGndXJpu/b0L+MZ/NviRTz03ju8P3gISdUS2ZmezlUvPEu1yCgAGlevzsNXXePO\n0EVEROQMdMYnOJomxhITEsT9H3xL7ZgIbuzalic+n1xq21a1Ekr88nvLee34+M8FrN6RQuekWlzc\nIomJfy1xR+gl5OXl8dLwYYx67XUio6MZcMP1nNupM9Vr1ixsEx1TlUeeeJJPP5xQ6nu8PW4szVq0\ndFfIJ5XndDLs808Yc9c9RIeE0u/FoXRq3ISaVWOLtTt4+DCfTf2DRtVrlHiPkV9+QfuGDd0VcqlW\nLppP6q6dPPHqm2xet4ZP33ydIS+MKtHus7fGcM3Au6hRtz5jn3uSlYsW0LBFK9YuX8qyeX/x8MjX\ncDgc7N+X/8E0MCiYgQ89TkhYODu3bmbMs4/z3JsfuLt71IoOJ6xyAON+nUVsaDAXNKvP+9PmlWg3\nZ90WtqRl4GUM153bgprR4WxMTue8xnVYtm0Xy7buIjEilC4Na/PdghVu7cOqRQtI3b2LR0ePY8u6\ntXzx9lgGPz+iRLsv3hrHVQPvoHqderwx9GlWLV5IUvOWfPfh+5x/xdUkNW/JyoXzmfTh+wx68jkC\nAgP57423smzeX27tz/EaJcQQHRzIY59NpkZUGNd1bMnQb34rtW3z6nEcPu5Z98uS1UyavxyAbg3r\ncEmLhnz05wKXx30iDeKiiQwK5Pmvp5AYEcoV7Zry8o/TS7R7f9q8wmd3/y5taJYYx6LNO+jTvjmT\n5i9nQ3I6bWpXo1vDOkxevMrd3QAKnnUffsDr9z9IdFgY1z/9BJ2btaBmXFxhmwvancMVXbsBMG3R\nQkZ+9jFjBg/hq2lTAfj8mefZk5nJXS+N4MP/PYmXl2cHYeY5nQyf+Dmv3X4X0SEh3DDqRTo1akzN\nmKrF2h08fJjPpk+lUWL1YtvjwiP4+MGH3RixiIiI+6kEh3ud8VNUWtZMYMbqjQCs351GgJ+DkAD/\nEu38HD5c1DyJb+YtK7Y9NjSY1TtSAFi2dRdtaldzfdBlWLViOXEJ8cTGx+NwODivx/n8WfCL71FV\nY2OpVacuxpS8tGtWrSRjTzqt27ZzU8Qnt2LzZhIiooiPiMTh40PPFq2ZtnRpiXbjvp9Ev+498fUp\nnpObumQx8RERJX6hdrel8+bQpks3jDHUqFufrEMH2ZdRfKTQvow9HD6URc16DTDG0KZLN5YWfCie\n8fOP9LjsShwOBwBBVUIASKhZi5CwcACqJiSSk51DTo77RxDVrRrJsm27ANiZkUklhw+V/XyLtcnN\nc7IlLQPIL6a0e+9+gv39AIgIqszmlPw/jy1pGdStGunG6PMtmz+X1p26Yoyhet16ZB0s4xplHaJG\n3foYY2jdqSvL5s3J32ngcNYhALIOHaJKaBiQf62q1a6Dl7dn88XNqscxe91mADal7MHf10EV/0ol\n2vn5+NCjSV1+XFj8g37RhIevwxuL5/81bpQQw7yNW4H8+8bf11F4TxV1NLnhZQw+Xl6FkUcFB7Ih\nOR2AtTtTaZLouefE8o0biI+KIj4qCoePD+e3bcfUxQuLtQn0P/ZvU9aRIxjyR3dt3LmDNklJAIQF\nBxMUEMDKzZvcF3wZVmzZTEJEBPERETh8fOjRvAXTlpXy/P7xe/qe173E81tERESkvHkkwWGM6eGu\nc4UFBpC+/2Dh6z0HDhEaWDLBcWW7Zvy4cGWJERzb0vfSsmY8AG3rJBIWWNm1AZ9AWmoqUdExha8j\no6NITU05pWOdTidjXn6J2+++11Xh/SMp+zKIDg0tfB0VGkLKvoxibVZv28rujAw6Nm5SbHvWkSO8\n/+vP3HrRxW6J9UT2pqcTGh5R+DokLJy96ekl2oSEh5faJmXXDjasWsGLDw3m5ccfYsv6tSXOsfiv\nmSTUqFmYBHGnQH8/MrOOTVfYn3WEoFI+aB7l5/ChdtUINqfkX8uUfQeoH5c/FL1ebCR+Dh/8fd3b\nj3170gmNKHKNwiPYtye9RJti1yg8vLDNZTfcwqQJ7/Hk7TcxacK7XHJtX/cEfopCAvzJOJBV+Drj\nYBYhlUs+6y5t3Yhflq4lO7fkVI3erRvxwrWX0LZ2IpPmu3eETWmqBPiz9+CxPu09dJgqpSSoAQZ2\nP4dn+lzI4ZwclmzZAcCuvZk0Ssh/ZjatHlvqn4e7pO7NICbs2L0VFRpGSkZGiXaf/TaFXv/3AK98\n8RkPXnc9AHUTqjFt0UJy8/LYkZrKqs2bSd5T9lRLd0ndt6/Y8zs6JJTUfcWnEK3Zvo3kvRl0bNi4\nxPE796Rz3YsvMODVl1m0Yb3L4xUREZEzn6dGcLzjofMCJYcJJUaEEh0SxPyN20q0fXPKbHo0qcez\nV1+Ev8NBbp7TTVGWZEsZ33S0fsPJfD3xc9p16EB0TMzJG7tTKV8SH/3WEvITM6O+/IL7Lv9viXZv\n/PAd13Y7jwC/kt9Su9+pXJvS2uT/35mXx6EDB3hg6Eh6972R8aOGFbveu7Zt4dsP3+PqgXeVZ9Cn\nrOg1OWlbY+jdqhHzN2xj76H8D6e/LV9bWM+mWngomVmHcTrd/HfpVP7+nOB+nPnLZC674WaeHDue\n3jfczKfjXnVFlP9YaY+C47sTHx5CZHAgizfvKPU9vpm3nIc+/p4567fQtWHJGjLuVmqfyhjn+caU\n2Tzx+U/4eHtTJyZ/hNCnMxdxbv2aDL6kC5UcPuTleW5USmlhl9a/Pud1Z9KwEdx95VW8/d23AFza\nsRNRofnTWkZ88iFNa9fG29vzAzBLG+VTtE9Op5NRX3/JvZdeXqJdRJVgvnviaT4a8hD39b6cxya8\nx4HDWSXaiYiIiPwdLhsvaoyZVNYuILyMfRhjBgADANr0uZHa7bv+7XP3aFKXrg3rALAxOZ3woMqw\nKxXIH9FR9BtBgNpVI6kRGcbL/S/D28sQ7F+JRy/vwXNf/cqujExeKJjHHhMSRLPqcXhKZFQUKcm7\nC1+nJqcQEXFqQ/1XLF3G0sWL+GbiF2QdyiInNwd//wBuG3S3q8I9JVEhoSQX+RYzJWMvkQXTMwAO\nHTnChl07GfhKfj2L9MxMBr/xOqMG3sHyLZv5bfFCRn/zFfuzsvAyBl+Hgz6d//49809Mm/w9s37L\nL9CYWKsOGelphfv27kmnSlhYsfYh4RHFRnXktwkv3Ne07Tn50yfq1MMYw4HMTIKqVCEjPY03hz9H\n30GDiXTjVJyWNeIL7/edezMJ9q8E5H87G+Tvx/6s0ouEXtS8AXsOHmLehmMJwwOHs/lyTv7QdYe3\nN/XiojiSm+faDgAzfvqB2b/9CkC1WrXJSCtyjdLTCA4tfo2qhBcfebM3PZ3ggus4b9ofXH7jrQA0\nO6cDn77xmqvDP6kuSbXpWD+/Ls3m1Iz80WnJ+ftCK/uz77hnXa2ocBIjQnn+movxNoYgfz/uv6QL\nI7+fWqzd3PVbGXRBR7fXSQHoUK8G59StDsDWtIxioy5CAioVG0l0vFynkxXbdtGoWlXW7kolJfMA\n436dBUBkcGUaxHsuwRsVGsruIiOGUjL2EBkSWmb789u0Y+iE9wHw8fbmgWuuK9zX/7mnqRbl+WR1\nVJWQYs/v5L0ZRARXKXx96MgRNuzexW2vvQJA+v5M7n/7DUbeMpCkaon4+uSP4mqQUI348Ai2pqSQ\nVC0RERGRM0lZX86Ia7hyQmxH4HrgwHHbDdCmrIOstW8CbwJcN3rCP7obfl26ll+X5g/xb1Y9jp5N\n6jF77WZqx0SQdSSn8Fvlo35btpbfluW3jwiqzAO9uvHcV/kfioL983+hNkDv1o35bXnJqQPuUj+p\nIdu3bmPnjh1ERkXx268/8/gzz5/SsY8/+1zhz5O/m8TqVSs9ntwASEpMZFtqCjvS0ogKCeGXhfN4\ntv/NhfsD/f35bdjIwtcDXh7JvZddQVJiIm/f90Dh9jd++I4APz+3JTcAOl94CZ0vvASA5QvmMX3y\n97Ts0InN69bgHxBQWKPhqCqhYfj5+7Np7Wqq16nH3Km/0/mi/OObtG7H2uVLqduoCck7d5Cbm0tg\ncDCHDh5g3PNP0uu6G6hVP8ltfQNYsGk7CzZtB/KLjLaqmcDK7cnEhgZzJCeXg0eySxzTuUEt/Hx8\n+GHhymLb/X0dhasPta9XnaVbdrq+A0DHCy6m4wX5U5hWLJzPjJ9+oEWHjmxZtxb/gMplXqPNa9eQ\nWKcu86b/QaeC44PDwli/cjl1GjZm3fKlRMbEljifu01duZ6pK/OH9jdOqErXhrWZt2EbNaLCyMrO\nYd9xyYBpqzYwbdUGAMIDA7jrgo6FyY2o4EBSMvMf100TY9m9N9N9HSli5ppNzFyTX18iKS6ac+vX\nZNGmHSRGhJKVk0vmcYk1Xx9vKjl8yMw6gpcxNIiLZmNKfiIhsJIvBw5nY4AeTeoxa43n6lY0rFGT\nbccwgSkAACAASURBVMnJ7EhNJSo0lJ/n/MXzA28v1mZr8m6qFUxDnLF0CQlR0UD+dDwAfz8//lqx\nHG9v72LFST0lqVoiW9NS2ZGeRlSVEH5dtJBn+vYv3B/o78+U54YVvh746svcc+llJFVLJOPAfoID\nKuPt5cX2tDS2paUSV2San4iIiMg/4coEx1/AIWvttON3GGPWuPC8xSzevINm1eMYdUNvsnNyeWPK\nrMJ9z19zMY988sMJjz+nbnV6NKkHwLwNW5m2coNL4z0RHx8f7n3w/3jg7jtx5jm5qFcvatSqxTvj\nxlKvQRLndu7MqhUreOzB+9mfmcmsP6cz/o1xfPD5RI/FfDI+3t4MuaoPg8aMJs866dWuPbWqxjLu\n+0k0qJZI5yaeWRL172rYohUrFs7nqbtuxeHnx/V3HKt1MvSBQTw8In86Q59b7+DDgmVik5q3JKl5\nKwDO6daDj15/hefuuwNvHwd977oPYwzTJ39P6u5d/DTxU36a+CkAd/3vmcIipO6yITmd2jER3N6j\nPTl5Tr5feOyb/Zu7tuWdP+YQVMmPDvVrkLb/IDd3bQvA/I3bWLJlZ+HKKRbLtrS9/LxktVvjB0hq\n3pJVC+fz7N234evrxzV3DCrcN3zIvTz44ssAXHnLbXz8+mhysrNp0KwFDZrnrzp09cA7+erdt3E6\n8/BxOOgz8A4AMvdmMPKh+zmcdQhjvJj243c8POo1KgUEuLV/ywpGLjx39UVk5+by3tRjq9z87/Ie\nPFOQtC3L5W2bEF0lCGst6QcO8dEMz66gArByRzIN4qN59PIeZOfm8unMRYX7HvhPV0Z89we+Pj7c\n3K0dPl5eeHkZ1u1KY9aazQC0qBFPh3r5q0wt27qTueu3eqIbQP6z7v+u78edo4bjdFp6nduJWnHx\njP36S5Kq16Bz8xZ89tsU5qxcgY+3N8GVK/P0LQMAyNifyZ0jX8R4GaJCQnnmloEe60dRPt7ePPjf\nq7h73BjynJZebdtRq2pVxv34PQ2qVaNzoyZlHrtow3rGTf4BHy9vvLwMD115NVUqe67GlYiIiJQ/\nY8wFwCuAN/C2tfaF4/b7AR8ALYF0oI+1dvO/OufpPGTmn47gOF2N6l9yHnJFFzBnrqdDKFd/xcR7\nOoRyN2/9Fk+HUK6a1zzzrtHXc0quPFGRHb/Czpng2dqeXampvOVlemaEjqsFX+i2GuYiIlJ+Tr3Y\nWwU0b+P2M+oz7VGta8af8LoZY7yBtUAPYDswD7jGWruySJs7gCbW2tuMMVcDl1lr+/ybuDy+Zpsx\nZra19hxPxyEiIiIiIiJSnpyn8YACF2sDrLfWbgQwxnwKXAoUnct+KfBkwc8TgdeMMcb+i1EYni/D\nDqfDEhgiIiIiIiIiUj7igKLLlG4v2FZqG2ttLvkrGpS5IMmpOB0SHGdtSktERERERESkojHGDDDG\nzC/y34Djm5Ry2PGf/U+lzd/i8SkqIiIiIiIiIlJxFF39tAzbgYQir+OB45dSPNpmuzHGB6gC7Pk3\ncZ0OIzjO6KIyIiIiIiIiImeZeUAdY0wNY4wvcDUw6bg2k4AbCn6+Avj939TfgNNjBEdfTwcgIiIi\nIiIiUt5O51VLXclam2uMuQv4mfxlYsdba1cYY54G5ltrJwHvABOMMevJH7lx9b89r8sSHMaYBOBF\n8guHTAZetNbmFOz7xlrbG8Bau9xVMYiIiIiIiIiI+1lrfwR+PG7b40V+PgxcWZ7ndOUUlfHAVGAQ\nUBWYZow5WhE10YXnFREREREREZGzjCunqERaa8cV/DzIGHM9MN0Y0wutnCIiIiIiIiIi5ciVCQ6H\nMaZSwbATrLUfGmN2kz8Hp7ILzysiIiIiIiLicWdpCQ6PceUUlbeBtkU3WGunkD/HRnU3RERERERE\nRKTcuGwEh7X2pTK2LzLGPOKq84qIiIiIiIjI2cdty8QaY5LIX/blGmAf0Mpd5xYRERERERGRM5tL\nExzGmETyExrXALnkr57Sylq72ZXnFREREREREfE0p4pwuJXLanAYY2aRv+atA7jCWtsS2K/khoiI\niIiIiIiUN1cWGU0FgoBoILJgm9JXIiIiIiIiIlLuXJbgsNZeCjQGFgJPGWM2AaHGmDauOqeIiIiI\niIiInJ1cWoPDWrsPGA+MN8ZEA32Al40xCdbaBFeeW0RERERERMSTrGpwuJUrp6gUY61NttaOtta2\nB85113lFRERERERE5MznshEcxpjvOHHNjV6uOreIiIiIiIiInF1cOUVlhAvfW0RERERERESkkMsS\nHNbaaUd/NsZEFmxLddX5REREREREROTs5dIio8aYJ4BBgAG8jDG5wKvW2qddeV4RERERERERT3Oq\nyKhbuazIqDHmPvKLiba21oZba0OBtkCHgn0iIiIiIiIiIuXClauo9AOusdZuOrrBWrsRuL5gn4iI\niIiIiIhIuXBlgsNhrU07fmNBHQ6HC88rIiIiIiIiImcZV9bgyP6H+0REREREREQqPNXgcC9XJjia\nGmMyS9lugEouPK+IiIiIiIiInGVcuUys9799jyqV/csjlNPG1rQMT4dQ7uq3a+XpEMrVcyPf93QI\n5e4/rRp5OoRyVS0izNMhlLvKfr6eDqFc7cooLbddsVlnlKdDKFeO2KqeDqHcZW/dzr7vfvJ0GOWq\nyn8u8HQIIiIiFYora3CIiIiIiIiIiLiFK6eoiIiIiIiIiJy1rGpwuJVGcIiIiIiIiIhIhacEh4iI\niIiIiIhUeEpwiIiIiIiIiEiFpxocIiIiIiIiIi6gGhzupREcIiIiIiIiIlLhKcEhIiIiIiIiIhWe\nEhwiIiIiIiIiUuEpwSEiIiIiIiIiFZ6KjIqIiIiIiIi4gFM1Rt1KIzhEREREREREpMJTgkNERERE\nREREKjwlOERERERERESkwlMNDhEREREREREXsFZFONxJIzhEREREREREpMJTgkNEREREREREKjwl\nOERERERERESkwlMNDhEREREREREXUA0O99IIDhERERERERGp8JTgEBEREREREZEKTwkOERERERER\nEanwVINDRERERERExAWcqAaHO2kEh4iIiIiIiIhUeEpwiIiIiIiIiEiFpwSHiIiIiIiIiFR4Z0UN\njivbNaVhQlVycnP5YPp8tqXvLbPtbd3bExFcmWe/+hWAy1o3pnG1quQ5naRmHmTCjPlkZee4POYl\n8+cyYdwYnE4nXS64iF5XXVNsf052NuNGDmPTurUEBQdz18P/IzI6BoBJn33M1J8n4+XlRb/b76JJ\ny9YAHDxwgLdfHsH2LZsxxnDrfQ9Qp0FDtmxYz/hXXyYnJxtvb2/633kPterVd3kfj5o1axYjRozA\n6XTSu3dv+vfvX2z/hx9+yLfffou3tzehoaE8/vjjVK1alV27djFkyBCcTie5ublcddVVXHHFFW6L\n+0QGXdiRdnUSOZyTywvf/Ma6Xakl2vh4e3HPRZ1pVj0Oay1v//YX01dtoEliLHddcC61oiN4euLP\nTFu5wQM9KM5ay6xvPmPbquX4+PrS5er+RMRXK9YmNzubXz94g8y0VLy8vKiW1IS2l1wOwKxvP2fX\n+jWF7bIO7Kf/cy+7tQ8L585h/Guv4HQ66X7RJVx+7fXF9udkZ/PKC8+xce0agoKDuf/xp4iKqUrK\n7l3c3f96YhPy+1s3qSG33fcAAB+98yZTf/mZg/v38/GPv7i1P6W5rE1jGsRFk5ObxyczF7J9z74S\nbQZ0P4dg/0p4exk2Jqczcc4SrIXY0GCubNcMX4c3GQeymDBjPkdycj3Qi7Ld0Lk1zWvEcSQnj7G/\nzGRz6p4SbR6/oichAf5k5+UB8PxXU8jMOuzuUEs1a/kyRnzyMXlOJ707duLGiy4utd2U+fP4v3Gv\nM+Gxx0mqXoO9Bw7w4NgxrNy8if+078D/XdfXzZGXbebiRQx/dzxOp5PLzjuPm3pfXmz/F7/8zGc/\n/4SXlxcBlSrxv4G3USs+gR0pKVx+3z0kxsYC0KROXR4bMNATXShm9upVjPz2K5xOJ5e2bccN3XqU\n2u63JYt5eMK7vHfP/SQlVCM3L49nP/+ENTu2k+d0clHL1vQ/r/RjRURExHXO+ARHw/gYooKDePKL\nn6geGcbV7Vvw4ne/l9q2WWIsR3KL/0K/emcK385fjtNaerduzPlN6/PNvGUujdmZl8f7Y0bz0PPD\nCYuI5PF77qBl23OIS6xe2GbqL5OpHBjIqPETmD31dz4d/xaDHv4fO7Zs5q9pfzBs3Dtk7EnnhYeH\nMOLt9/Hy9mbCuNdo0qo19zz2JLk5ORw5cgSAT955k8uv60vT1m1ZPHcOn7zzJo8NH+XSPh6Vl5fH\nsGHDGDNmDNHR0fTr149OnTpRs2bNwjb169fniiuuoFKlSkycOJHRo0czdOhQIiIiGD9+PL6+vhw6\ndIg+ffrQuXNnIiMj3RJ7WdrWSSQ+LITrRn9IUnw0913cmTvenlii3fUdW7H34CH6vvohxkCwfyUA\nUvbt54VvfqNP++buDr1M21YvJzMthT4PP0PK1k3M+PIjLrvn4RLtmnbpSWzteuTl5vLDuJfYumo5\n1Ro0ov2lVxW2WT7jd9J2bHNn+OTl5fHWK6N44sWXCI+M5MHbb6V1+w4kVK9R2GbK5B8IDAri9Q8/\n5c/fp/DBm+N44PGnAIiOjWPUW++WeN9W53Tgwt6Xc1ffa93Wl7I0iIsmMiiQ57+eQmJEKFe0a8rL\nP04v0e79afMKExf9u7ShWWIcizbvoE/75kyav5wNyem0qV2Nbg3rMHnxKnd3o0zNqsdRNTSYe9/7\nhtoxEdxyXlse+3RyqW1f++lPNqakuznCE8tzOnnhowm8PvgBokPD6Pvs03Ru1oyasXHF2h08nMWn\nv02hUZFnoJ/Dwe29L2PDjh1s2LHd3aGXKc+Zx9B33mLcY48THR7OdQ//H51btaZWfEJhmwvP7ciV\nPc8HYOr8eYx8/z1ef/R/AMTHRPP5iyM9Entp8pxOhn/9Ba8NuIOoKiHc8MpIOiY1pmZMTLF2Bw8f\n5rM/p9OoWmLhtilLFpGTl8snDzzE4exs+rw4lJ7NWxAbFu7uboiIyGnGWhUZdaczfopKk8RY5qzf\nAsDm1D0E+DoKP0gW5efjTbdGdUv8Qr9qRzLOgptyU0o6IQH+Lo95w9rVRMfGEVU1Fh+Hg3adu7Lg\nr1nF2iycPYuO3XsC0KZjZ1YsXoi1lgV/zaJd5644fH2JiqlKdGwcG9au5tDBg6xZvowu518EgI/D\nQeXAQACMMWQdOgTAoUMHCQ133y9kK1asICEhgfj4eBwOBz179mTatGnF2rRq1YpKlfKvWaNGjUhO\nTgbA4XDg6+sLQHZ2Nk6n021xn0iHejX4eclqAFZuTyawkh9hgQEl2l3UvAEfzVgAgLWw71D+t8y7\n9+5nY3L6afUw3Lx8CXVatsMYQ3RiTbKzsjiUWXx0gI+vL7G16wHg7eNDRHw1Du7LKPFeGxbNo3bz\n1m6J+6j1q1dRNS6OmNhYHA4H53Y7j7mz/izWZt7MGXTteQEA53TuwrKFC056DeolNSQsPMJlcf8d\njRJimLdxKwBb0jLw93UQ7O9Xot3R5IaXMfh4eRXW9Y4KDmRDcn5SYO3OVJokVnVL3KeqVa0Epq/K\nH820fncaAb6+bnkel5cVmzaSEBVFfGQUDh8ferZpw9TFi0q0G/vN1/S74EL8fByF2/z9/Ghepy6+\nDkeJ9p60fP16EmJiiI+OweHj4Pz25zJ13rxibQIDjj37sg4fxvw/e/cdHkW1xnH8O9kEQkjvQAKh\nQ0B67yCiYr9eFRsiIiqCihVUbAgI0kRBumIFbGABadIRkF5DryG90VJ35/6xMSQkKF6zmwC/z/P4\nmJ05m3kPMzuZfeecdwzD2WFett3HjxEWEESlgED7PmrUhFW7C9/QmLJoAQ937kKZfPvIMAzSM7PI\nsVrJyM7G1WKhvHvhaw0RERFxLIeO4DDsVzItgEqACZwCNppO/Obm61GOlHPn816nnE/Ht3y5QkOW\nb21an2W79pOVY73k72pTK4LNhx1/9ywlMRH/fKMQ/AODOLSvYOIlJSkR/8BgACwWCx4e5Tl7+jQp\nSYlUr1M333sDSUlMpEyZsnj5+DB17CiOHz5MRM2aPPzk07i7l+OhJ/ox6vVBfDV9CqZp480xHzq8\nj3+Kj48nJCQk73VwcDC7du26ZPv58+fTpk2bvNexsbE899xznDhxgmeffbbER28ABHl7knD6bN7r\nhNNnCfL2JPnshePQ092emOndpRWNIipyKvk0HyxYScq5dKfHeznOp6Xi6euf97q8jy/n0lLw8PYp\nsn1m+nmO7d5B/fZdCiw/k5zE6eREKtZ03hQogKTEBAKCg/NeBwQGcWDv3ovaJOa1sVhc8ShfnjO5\nSZz42Bhe6Nubch4ePND7cSIbNHRe8JfJx6McqfmOn9TzGfh4lON0emahtk90bU3lQD/2Rsex/Vg0\nADGpp6kfHsquE7E0jKiIb/nSlTzwL+9B0pkLn6Hks+fx9/Qg9Xzhz8yT3dpgM002HjjG9xsdO+Lu\ncsWnpBDid+EzFOLnz67DBaefRR0/RlxyMh0aNuKLRb86O8R/LD45mdB8Cb6QAH92HjhQqN3sXxfy\nxS8/kZ2Tw9Q33spbHh0fz30vv4hnuXI83eN+mtSNdEbYl5SQlkaIr2/e62BfX3YfO1agzb7ok8Sl\nptA+sj5frliet/z6Bo1YtXsn3d8ZQkZWNgPvuAsfj/JOi11ERETsHDaCwzCMbsAB4C2gO3AL8DZw\nIHedUxR1s+ji/EqYvw/B3uXZfuzUJX/PTQ3rYLWZbDx0vLhDLKTo7E/BjhSZIzIutdzAarVy9OAB\nrr/ldoZNnEJZd3d+mjsbgGW//MSDfZ9iwuezebBvP6aNH/2v+/BvXOoO34IFC9i7dy89e/bMWxYa\nGsrs2bOZN28eP//8M0lJpWtY+p8u3i8WFxeCfbzYdTyGvlPmsvtkLE91a1tC0f09s8ijsuj9ZLNa\n+e2L6dRv3xnvgIIJp0Pb/qBagya4uDh58NjlhF/EZ8fAwM8/gKlff8uYqTN5tN8Axg17h/Pnzjkk\nzH/jcs51f5qy9HfenPsrrhYLNUPt+2j22q20q1ON52/thLubK1Zr6RlBBBR5uBV1XH64cDUvf/ET\nb839lTqVQmhft1rhN5aAIg/BfDvNZrMxdvbXDLy3h/OC+peKOr6KOn/3uOlmfv5wEs8++DDTvvsO\ngCA/P36dNIU5o0bzwiO9GDxhPGfPny/0Xmcq8jyXrzs2m41x83/g2dvuLNRs9/FjuBguLHhjKPNe\nfYMvVy4nOinRgdGKiIhIURw5guMDoKtpmkfzLzQMoyqwAKhb1JsMw+gL9AXo+HBfIjv+8yJdHepW\np21t+9z6Y4nJ+JX3AOxffP08yuVNBfhT1eAAwgP8GHrvzbi4GHi5u/Nc946MX2CfKtGyRhXqV67A\nB0XMZ3cE/8BAkhMuFKVMTkwoNG3EPzCI5MR4AoKCsFqtnD9/Dk8vb/vyAu9NxC8gAP/AIPwDg6iR\nO7qjRbsOeQmO1UsX8/CTTwPQsn1Hpo933pzo4ODgvCknYB/RUdQojA0bNjBz5kymTp2aNy0lv6Cg\nIKpXr87WrVvp2rWrQ2Muyp3Nr+PWpva7j1HR8QR5e16IzduTxDMFvxCnnc8gPSub1VH2O7grdh+k\ne+MiPxIlZvea5URtsE/jCAqP4GzqhYKO59JSKe/jW+T7Vn3zBd6BwVzXofB+OLR1E23/c38R73Ks\ngKAgkuLj814nJSbgHxhYZJvAoGCs1hzOnzuHp7c3hmHglnvMVa9Vm9CKFTl18gQ1nFiI91La1q5K\n61oRABxPTCkw6sLXw/0vi2vm2GzsPhFD/coV2B+TQPzps0xeYp8KF+RdnrphoZd8r7N0a1CbLtfV\nBOBQbBIBXhemO/h7epBytvDojT9HQWVk57B23xFqhASyeu9h5wT8F0L8/IhLufAZiktJJjDfaIFz\nGRkcPBVN3/ffAyApLY2BH05g3IBniMxXK6Y0CQkIIDbfl/i4pGSC8o1SudhNbdoyfNpUAMq4ueVN\nuYmsVp2wkFCOxZyiXvUajg36LwT7+BKXeqEIeXxqKkH5Rqmdz8zkUGwMT338EQBJZ07z4ifTGP3o\n4yzaupnWderiarHg7+VFw4iq7DlxgkqlZAqbiIiUHFspu2d0tXPkbVRXoKj5HNHAJScSm6Y51TTN\nZqZpNvt/khsAq/YeYsS8pYyYt5Qdx07Rsoa9EFhEkD/p2dmFLvpXRx3m1dm/MGTuQsb8vIL402fy\nkhuRlULo1qA2k5esJdt66ekrxalarTrEnoomPjaGnOxs1q9cTpNWbQq0adKqNauX2p/asHH1SiIb\nNsYwDJq0asP6lcvJzsoiPjaG2FPRVK9VB19/f/yDgjh10l7ccfe2rVTKLZDmFxDA3p3b85aHVipY\n9M6RIiMjOXHiBNHR0WRnZ7N48WI6dOhQoE1UVBTDhw9n7Nix+PtfuHiOi4sjI8O+L0+fPs327duJ\niIhwWuz5zftjJ30mz6HP5DmsiTrMjQ3tX34jw0I4l5lVYHrKn37ff4RGEfZ/66bVwjiWULheRUmq\n164zd78whLtfGEJE/UYc2Lwe0zSJO3aYMu7lipye8sfCeWRlpBcoKvqn1PhYMtPPExLh/DvqNerU\nISb6JHExp8jOzmbNb8to3rpdgTbN27Rj+WL7tIDfV67gusZNMAyDtNQUrLmf/dhTp4g5eZKQChWd\n3oeirN13hNE/LWf0T8vZdTyG5tXsT3qpEuhHenZOoekpZVwteXU5XAyDupVCiE87A1yYNmUANzSo\nzbp9R5zXkUtYvGMfg778mUFf/symQ8fpULc6ADVCAzmflV1oeoqLYeDlbu+fxcWgSdWwv3xqljNF\nRlTlRFw80QkJZOfksHjjRjo2vFBI2MvDg9/Gf8jPI0fz88jRXFeteqlObgDUq16D4zExRMfHkZ2T\nzaJ1a+jYrFmBNsdiLoyMXL1lM5Ur2Gu7JJ9Ow2qzf65OxsVyPCaGsHzTFUtCZHhlTiQmEJ2UZN9H\n27bQvl79vPWe5cqx5J3hzH/tTea/9ib1K0cw+tHHiQyvTIivH5sO7Mc0TdIzM9l17CgR+abFiYiI\niHM4cgTHTOAPwzBmA38+MiEc6AHMcOB2C9h1IpZ6YaG8fc9NZOVY+Xz1prx1g+/syoh5S//y/fe2\naYybiwsDbrJ/6T4an8TX6woXhitOFouFR54awKjXX8FmtdGx282EVYng288+oWqt2jRt1YaON3Zn\n8vsjeL73w3h6edF/0OsAhFWJoGX7TrzyRG9cLBZ69RuAi8UCwCNPDeDjUcPJyc4muEIF+g58GYDH\nnnmez6dMxGa14lamDI8987xD+5efq6srL730EgMGDMBqtXL77bdTvXp1Jk+eTN26denYsSMTJkwg\nPT2dQYMGARASEsK4ceM4cuQI48ePxzAMTNPkoYceokaNkrv796f1B47RsmYVvnzmYTKzcxg5f1ne\nuulP3kefyXMAmLLkd179T1f631SW1HPpee1qVwzm3R7d8XQvS+taVenVqQWPTvq6RPryp/C69Tm+\ndyezR7yOq1sZOvV4JG/dd2OGcvcLQzibmsLWpQvxDQ7l+3HDAKjXtjN1WtkTCQe3/kH1Rs1KpMig\nxeJKnwEDeeeVF7BZbVx/8y1UrlqVrz+ZTvVadWjRth3Xd7+FD4a/S7+HeuDp5c3zQ94CYM+O7cz+\nZAYuFgsuLi48MfBFvLy9AfhsyiRWLVtKZmYGfe79D12730qPXr2d3j+APdFx1A0L4bX/3EBWTg6z\n1144T714W2dG/7ScMq6uPNalFa4uLri4GByISWTdvqMANKkaRtva9uTTzuOn2HjQ8dPx/omtR6Np\nVLUSH/S6i8ycHCYvvlB4+b0Hb2XQlz/jZrEw+K6uWHL7t+t4DMt2Fa4JURJcLRZefuBB+o8fg9Vm\n44627aleqRIfz/uByIgIOjb666cm3frKi5xLzyDbmsOKbVuZOPCFQk9gcTZXi4VBvfvw1LCh9seq\ndu5CjfDKTJrzNZHVa9CpWXNm/7qQDTt34GpxxduzPO883R+ALXv2MGnubFxzP1evP94XH0+vEu/P\nS3fdzTPTPsZm2riteSuqh1Zgyq8LqBseTod6113yvfe0bc87c76ix+j3wDS5tXlLapbw/hEREbkW\nGY6s92kYRl3gDuxFRg3sIzp+NE1zz+W8v9+Mb6+qAT2Pdm5V0iEUuzpBRReZvFLdNmZWSYdQ7G5r\nVv/vG11BbmpcsoUIHWH60nV/3+gKEpNyuqRDKHbTm5Z88rQ4WXKTdFeTrOOl5xG6xcXntptKOgQR\nEWcovY/YKga/bIu6qr7T/umWRnVK5X5z6FNUTNPcC+z9qzaGYXxnmubdjoxDRERERERExNlsKsLh\nVE5+lEGRSkeJexERERERERG5YpWGBIdSWiIiIiIiIiLyr5SGBIeIiIiIiIiIyL/i0Bocl6lUFicR\nERERERER+Tcc+VAPKcypIzgMw2hSxOJXnBmDiIiIiIiIiFx9HDaCo4hkhgHMNwzjNuyPp90CYJrm\nYkfFICIiIiIiIiLXBkdOUdkErAcy8y0LAMZiLyzaxYHbFhEREREREZFriCMTHPcCA4D3TdNcAGAY\nxhHTNDs7cJsiIiIiIiIicg1yWILDNM1vDcP4FRhqGMajwAvokbAiIiIiIiJyjVCRUedy6FNUTNM8\nCww0DKMRMAvwcuT2REREREREROTa5JSnqJimuQ17zY3qAIZhNHfGdkVERERERETk2uDQERwXqQv0\nMAzjfiANaObEbYuIiIiIiIjIVcyhCQ7DMKoA9+f+lwNUAZqZpnnUkdsVERERERERKWk2laF0KodN\nUTEMYx2wAHAD/muaZlPgjJIbIiIiIiIiIlLcHFmDIwF7UdEQICh3mdJXIiIiIiIiIlLsHJbgzea1\n+wAAIABJREFUME3zDuA6YAvwtmEYRwA/wzBaOGqbIiIiIiIiInJtcvRjYtOAmcBMwzBCgPuA8YZh\nhJumGe7IbYuIiIiIiIiUJNPUJAZncspjYgFM04wzTXOCaZptgHbO2q6IiIiIiIiIXP0cNoLDMIyf\n+OuaG7c7atsiIiIiIiIicm1x5BSV0Q783SIiIiIiIiIieRyW4DBNc+WfPxuGEZS7LMFR2xMRERER\nEREpTVSCw7kcWoPDMIw3DcNIBKKA/YZhJBiG8YYjtykiIiIiIiIi1x6HJTgMwxiIvZhoc9M0A0zT\n9ANaAm1z14mIiIiIiIiIFAtHjuDoCdxvmuaRPxeYpnkYeCh3nYiIiIiIiIhIsXBkgsPNNM3Eixfm\n1uFwc+B2RUREREREROQa48inqGT9n+tERERERERErng2VRl1KkcmOBoahnG6iOUG4O7A7YqIiIiI\niIjINcYwS3FG6dzaDaU3uP/DzpAKJR1CsYtLPVPSIRQrwzBKOoRi1ynuZEmHUKzcKl59n6Oso8dK\nOoTi5eLQB3SViISWrUo6hGK152RsSYdQ7H7dtqekQyhWT3ZrV9IhOESD8NCSDkFESp+r7wI8n282\n7LiqvtP+6Z6WDUrlfrv6rkJFRERERERE5JrjyCkqIiIiIiIiItes0jxj4mqkERwiIiIiIiIicsVT\ngkNERERERERErnhKcIiIiIiIiIjIFU81OEREREREREQcQDU4nEsjOERERERERETkiqcEh4iIiIiI\niIhc8ZTgEBEREREREZErnmpwiIiIiIiIiDiATTU4nEojOERERERERETkiqcEh4iIiIiIiIhc8ZTg\nEBEREREREZErnhIcIiIiIiIiInLFU5FREREREREREQdQkVHn0ggOEREREREREbniKcEhIiIiIiIi\nIlc8JThERERERERE5IqnGhwiIiIiIiIiDmCqBodTaQSHiIiIiIiIiFzxlOAQERERERERkSueEhwi\nIiIiIiIicsVTDQ4RERERERERB7CpBIdTaQSHiIiIiIiIiFzxlOAQERERERERkSueEhwiIiIiIiIi\ncsW76mtwrN25g9FffYHVtHFX+448esttBdZ/u/w35v62FBcXFzzKluX1R3pTrVIlsnNyeHfWJ+w9\negTDMHjpgYdoVqeu0+I2TZMvp0xi+6aNlClblscHvkREjZqF2h05sJ/p494nKyuLhs1a8OAT/TAM\ng7NnTjPpvWEkxscSGBzK04Nep7yXF1t+X8d3X3yKi2HgYrHwYN9+1KpXH4A5M6ex7Y8NmDYb9Rs3\nzftdzujrj5/NIGr7FtzKlOXeJ/oTVrV6oXa/zv2SzatXkH7uHO/O/Cpv+eG9u/nxi5nEHj/GA/2f\np0HLNg6P+WKmaTL/sxlEbduMW5my3PfkgCL7cPLwIeZMmUB2VhZ1GjXljp6PYRgGp44d4bsZk8nK\nzMAvMJgHnh6Iu4cH1pwcvpk2keijh7FZrTRt35kud9zt9P6t27uHMT98h820cUfL1vTq2q3Idsu2\nbWXQrJnMGvgSkZUrA3DgVDQj5s7mbEYGLi4Gswa+RFk3N2eGX6S127Yy6tNPsNls3NXlenrfeVeB\n9d8sWcScRYvs5wZ3d4b0fYLqYeFEx8fzn+efo0rFigA0qFmT1x9/oiS6UMDv+6IY8+M8+z5q3pJH\nOl9fZLtlO7Yz+MvP+HTAc0SGhZOdk8OI779lb/QJDMPghdvupGn1Gk6Ovmi/R+1lzI8/YLOZ3NGi\nJY906Vpku2U7tjH481l8+sxAIsMrk2O18u43s9kXHY3VZqV70+b0usR7HW3Tht+ZOmE8NpuVbrfc\nzr0P9SywPjsrizHD3uHg/ii8vH0Y9Na7hFSoQE5ODhNGDufg/n1YrVauv+lm7n3oEbIyM3llwFNk\nZ2djtVpp26kzD/V+vET6drHLPQ8unPNF3rl82Cdfl0Ckf+2eVg2pF16B7JwcPlu1iRNJqZds+2TX\nNgR6l+fd75cAcFfz67iucgWsNhsJp8/x+epNpGdlOyv0PFs3buCTSR9is9m4/uZbuOv+Bwusz87K\n4sORwzl8YD9e3t4MfP1NgkMrcCBqL1PGjbY3Mk3u6dmLlu065L3ParUyqF9f/AODGDzsPWd2SUTk\nimWaKsLhTFf1CA6rzcbILz7jw4Ev8t277/HrhvUcjo4u0OamVq2ZO3Q4s99+l0duvoUxc+xfnL9f\nuQKAuUOH8/GLrzB2ztfYbDanxb5j00ZiT0UzatqnPDrgOWZNnFBku1mTJvDogIGMmvYpsaei2bH5\nDwB++WYOkQ0bM2raLCIbNubnb2YDENmoMe9+NIWhH03hsedeZOaEsQAc2LOb/Xt2MeyjKQyfNI3D\nB/YRtXOHU/oatX0LibExvDxmInc/9iQ/fDK1yHZ1GzdjwDsjCy33DQzivicG0KhNe0eHeklR27aQ\nGHuKV8ZO4r99nuL7mVOKbPf9zMnc/dhTvDJ2Eomxp9i3fQsA30ybRPf7H+aFkR9Qv3lLVvw8D4Ad\nG9aRk53DCyM/4NlhY1i/bBHJCfFO6xfYP0ejvvuGD/o+xdxXXmPx1s0cjo0p1O5cRgZzVq+kfpWI\nvGU5VitvfPEZg+65j7mDXmPy08/iarE4MfqiWW1WRsyczsTBr/H92HH8unYNh06eKNDm5rbt+Xb0\nWOaOGk2v2+9gzGez8taFhYQwd9Ro5o4aXSqSG1abjVHzvueD3o8z5/mXWbR9K4fjYgu1O5eZwZx1\na6gfXjlv2byN6wH4euBLfNTnCT745SennusuxWqzMeqH7/jgsb7MefEVFm27RJ8yMpizZjX1K1fJ\nW7Z0xzayc6x8/cLLfPbsC/ywfh2nkpOdGT5g/zL48bgxvP3+WD7+7GtWLVvC8aNHCrRZ9MtPeHp5\nMf3rb7nz3h58MnkiAGuWLyM7O5tJs77kg+mfsvDHecTFxOBWpgzDx3/ER598zoczP2PzhvVE7d7l\n9L4V5XLPg5FNmvPM0FFOju7y1AsLJdjbi7e++ZUv12yhR5sml2zbqEpFMnNyCiyLOhXPu98vYdgP\nS4k/fZYbG9ZxdMiFWK1WZnw4nteGj2LcjFmsXb6ME8eOFmjz28Jf8PTy4qPPvuLWu+/hi2n2fVU5\noiojJ01h9JQZvDbifaaOH4PVeqGPC374lkr5PmsiIiKlzVWd4Nh1+BBhwcGEBQfj5urKjS1bsWLb\nlgJtPMuVy/s5PTMTA/uIhcOnomkRGQmAv7c3Xh4e7LnowtSRtqz/nbZdumIYBjXqRHL+3FlSk5MK\ntElNTiLj/Hlq1I3EMAzadunKlt/X5b5/He263gBAu643sGW9fbl7uXJ5ozKyMjLyfpdhGGRnZZOT\nk2O/M5iTg4+vrzO6yp7NG2nSvhOGYVClZm3Sz5/jdErhLyNVatbG28+/0HL/oGAqVI7AMErucN69\neSNN23fO60NGEX04nZJMRno6EbXqYBgGTdt3ZtemjQAkxERTrU49AGpd14idf/xuf5NhkJWZgdVq\nJTsrE4urK+75jlmn9O34McIDAwkLDMTN1ZUbGjdl5a6dhdpNXvgLD3fpShnXCwPDNuyLokbFitSq\nFAaAb/nyWFxK/rSz6+BBwkNCCQsJwc3VjRvbtGXFH38UaOPp4ZH3c3pmJk4YzPR/233iOGEBAVQK\nCMDN1ZVuDRuzas/uQu2mLPqVhzt2pky+ETRH4uNonjs6zN/TC093d/ZGn3Ra7Jey+/hxwgIDqRRg\nP+66NWrMqiK+yE9ZtJCHO3UpcNwZGKRnZZJjtZKRnY2rxZXy7mWdGT4A+/fuoWKlMCpUrISbmxsd\nru/K+jWrCrTZsGY119/UHYB2HTuzfcsm+50ewyAjIx1rTg5ZmZm4urrhUd4DwzAol3ts5uTkYM3J\nobQcnJdzHoRLn8tLgwZVKrLh4DEAjiYk41HGDe9y7oXalXW10KV+LRZu21tg+d7oOGy5d+qOxCfh\n6+Hc8zXAwX17Ca1YiZCKFXFzc6Ntpy5sWrumQJs/1q2lY7cbAWjVoSO7tm7BNE3Kurtjsdg/S1lZ\nWXnXRABJCfFs2bCe67vf6rzOiIiI/EMOnaJiGIYPcBNQCTCBU8Ai0zQvPd6zGCWkphDqH5D3OtjP\nn12HDxVqN2fZUr5c/CvZOTlMeXkQALXCK7Ny6xZubNGKuORk9h49SlxyMvWrFR5u6wgpSYkEBAXn\nvfYPDCQlKRHffP1JSUrELyAwX5sgUpISATidmpLX1tc/gNOpF/7JN61bw7ezZnI6NZXn33oXgBp1\nI6nboCHPPnwfpmnS9dY7qOikuzRpycn45uuHr38AaSnJpfYCuCinU5IK7BufIvqQlpKMz0VtTqfY\nk1ahYZXZvXkj9Zu1ZPv6taTl7scGLVqze9NGhvbrTVZWJrc/1BsPTy8n9couITWVEF+/vNchPr7s\nOn60QJt9J08Ql5pC+3r1+WL5srzlxxLiMTAYMHkiKWfP0q1xU3peXzJTBfKLT04mNN8xFxIQwM6D\nBwq1m71oIV/88jPZOTlMHfJW3vLohHjue+VFPMt58PR9PWhSN9IZYV9SQloaIfkSksE+Puw+frxA\nm33RJ4lLS6V93Ui+XLUib3nNChVZuWcXNzRsRFxaKlHRJ4lLTaVevlEeJSHhdOrl9Sk1lfaR9fhy\n5fK85dc3aMiq3bvoPvRNMrKyGXj7Hfh4lHda7H9KSkwgMPjCeTwwKJh9FyWekhITCAoOAcDi6opH\neU9Op6XRrlMXNqxZzUN33UZmZgaP938WL28fwH6H/tnHHyUm+iS33Hk3dSLrOa9Tf+FyzoOlna9H\nOVLOnc97nXI+Hd/y5TidnlGg3a1N67Ns136ycqyX/F1takWw+bDzk4XJiYkE5Dvu/IOCOBBVMBGT\nnJRIYO41hsXiikf58pw5nYa3jy8H9u5h0uiRJMTFMWDQq3kJj08mfcRDjz9JxvnziIiIlFYOu5Vq\nGEZPYAvQCfAAygOdgc256xyuqOlORd3ouu/6rvw4cjTP3HMv03+aD8Ad7TsQ7OfPQ++8yeivv6Bh\njRpYLE6881zkXC3jb5tcTs2MZm3a8d6UmTwz5C2++/xTAOJORRNz4jjjZn3N+M9ms2fHNqJ2OWeK\nij33VZAzan8UpyL3xUX766/26b19+7NuyULGv/oCmRkZWHLvRh8/dAAXFxeGTJzBq+Mns2rBfJKK\nGKbvSEVHfaFvNpuNsfO+57k77irUzmqzsf3IIYY+9AjTnxnIip3b2bh/nwOjvTxFzYUstL+AHjfe\nzM8TJvLsAw8x7ftvAQjy8+PXiZOZM3I0L/R8hMEffsDZEr7gL3JmZ77u2Gw2xv38I8/ecnuhZrc1\na0Gwjy+PfDiecT/Np0GViFIxyubvToE2m41xP87j2dvuKNRs9/FjuLgYLBjyNvNefZ0vV60gOjdp\n6ExFzrk1Lj6PF33+2793Ny4uLnz+w0/MnPMdP8z5mphT9imWFouFj2Z+xqxv57M/ag9Hi0jcl4TL\nOg+WckX96bl4H4X5+xDsXZ7tx05d8vfc1LAOVpvJxkPHL9nGYYo8v13c5NLnwJp1Ixk3YxbvTZzM\nD19/SVZWJpvXr8PH15fqtWo7ImIREZFi48gRHK8BTS8erWEYhh+wAfisqDcZhtEX6Asw4aVB9L7j\nzv87gGA/P2LzTeuIT0kmKN+d6Ivd2KIVIz63z7N3tVh4MV9Rrl7D3qFycOj/HcvlWPrzfFb+ugCA\nqrVqk5Sv1kJyYiJ+AQEF2v85quNCm4S8u2fevn6kJtvvpqUmJ+FdxHSTOvUbMC02hjNpaWz+fS3V\n69TNm/7QoGlzDkXtpU79BsXeT4B1ixeyYbm9KFt4tRqk5uuHPd5L76fSYu3iBQX7kO9YS0tOwtuv\nYB98/ANIK9TGfmczuFIYfQe/Bdinq0Rt3QTA1nWrqN2wMRZXVzx9fImoVYeTRw4REOLYYzG/YF9f\n4lJT8l7HpaUS6OOT9/p8ZiaHYmN48iN7nZikM6d5YcYUxjz2BCE+vjSuXgNfT08A2kTWY9/JE7Qo\n4YvkkIAAYvMdc3FJSQT5XfqYu6lNW4ZPnwZAGTe3vCkekdWqExYSwrGYU9QrwcKcwT4+xOUbpRWf\nlkaQd+F99NTUSQAknTnDi5/OZHSv3kSGhfN8viTBYxMnEB54YXRLSQn28b2MPsXy1OSPgD/7NIPR\nvR5j0dYttK5dB1eLBX9PLxpGVGXPyRNUCnBuvwKDgkmMv3AeT0yIJ+Cif9vAoGAS4uMIDA7GmpPD\n+XNn8fL2ZsWSxTRt2QpXV1d8/fyJvO46DkbtpULFSnnv9fTyokGjJmzesJ4IJ40uvNg/PQ+WRh3q\nVqdt7aoAHEtMxq+8B2Dvh59HOdLOFxy9UTU4gPAAP4beezMuLgZe7u48170j4xesBKBljSrUr1yB\nDxYUnI7kLP5BQSTlO+6SExLwv+jYDwgMsh+PQcFYrTmcP3cOT2/vAm3CqkTg7u7OiSNHiNq1i02/\nr2Prxg1kZWWRfv4cE0a8yzODX3dKn0RErmQqMupcjrxNZ1D0jUUbhW8m5DFNc6ppms1M02z2b5Ib\nAPWqVuNEXBzRCQlk5+SwaMN6OjZqXKDN8Xx3w1fv2E547lDh9MxM0jMzAVi/excWi4VqlSrhSF1v\nvYOhuQVAm7Rqy9rflmKaJgej9lCufPkCQ3/BPpXDvVw5DkbtwTRN1v62lCatWgPQuGVr1iy1X3Su\nWbqEJq3sTxaJOxWd9yE7evAAOTnZeHp7ExAUTNTOHVitVnJycti3awcVHThEvU23mxk4YiwDR4yl\nXrMWbFm9AtM0OXZgH+XKeVwRQ5rbduvO8yPG8fyIcdRv1pLNq5fn9cG9iD54+/lTtlw5jh3Yh2ma\nbF69nHpNWwBwNs3+Rc5ms7H0h29p1dU+N9ovIIiDu3dimiZZGRkcO7ifoIqOPQ4vFhlemeMJCUQn\nJZKdk8OSrZvpUO+6vPWe5cqx9N33+PGNt/nxjbepXyWCMY89QWTlyrSqU5eDp06RkZVFjtXKloMH\nqOrE5Myl1Kteg+OxMUTHx5Gdk82idWvp2Kx5gTbHYi4UUl29dQuVK9jjTj6dhtVmH5Z+Mi6O4zGx\nhIWEOC/4IkSGhXMiKZHo5CSyc3JYvH0r7etemLbgWa4cS94cyvxBrzN/0OvUr1wlL7mRkZVFepb9\nXLdh/z77ua4U7KPI8HBOJCZc6NO2rbSPvKhPb7/L/FffYP6rb+T26TEiwysT4ufHpoMHMU2T9KxM\ndh07RkSQ8/dRrTp1iT55gthTp8jOzmbVsqW0bFuwGHLLtu1YlpvYXrNyOQ2aNMUwDIJCQtm+ZTOm\naZKRnk7U7t2EVYkgLTWFs2fOAJCZmcG2zX8QXqXkij7+0/NgabRq7yFGzFvKiHlL2XHsFC1r2P89\nI4L8Sc/OLjQ9ZXXUYV6d/QtD5i5kzM8riD99Ji+5EVkphG4NajN5yVqyrZeevuJINWrXISb6JHEx\nMWRnZ7N2xW80a9O2QJtmbdqycvEiANavWkn9Ro0xDIO4mJi8oqIJcbGcOnmCoNBQHuzTlymzv2XS\nl3MY+Nob1G/URMkNEREplRw5gmMYsMUwjMXAn48nqAzcAAx14HbzuFosvPJQT54eOwqbzeT2dh2o\nXimMj3/4jsiIqnRs3IQ5y5ayYc9uXC0WvMuX550+fQFIOXOap8e8j+FiEOzrx9A+zn1SQsPmLdix\naQMv9XmEsmXL0mfgi3nrhvR/gqEf2SueP/L0M0wbN5qszEwaNGtOg2b2L8y33tODie8NZdWShQQE\nBfP04CEAbFq7mjW/LcXVYsGtbFmefuV1DMOgedv27Nm+jdf6PY5hGFzXtDmNW7Z2Sl/rNGpK1LYt\njHy+H2XKlOWeJ/rnrRs3+HkGjrA/6eWXrz5j27pVZGdlMqx/H5p37kq3u3tw4tABPhs3kvPnz7F3\n6x8s+W4OL4z6wCmx5+/D3m2beW/gU5QpW5Z7nxiQt27s4IE8P2IcAP/p/QRzJuc+JrZhE+o0slfo\n37puNeuWLATguuataN7R/ojPNt1uZu7kDxnz8rOYmDTv0IWKlSOc2jdXi4WX776HZ6ZMwmozub1l\nK6pXqMDkhb9QN7wyHetfd8n3ent48ECnLvQc+769EG7dSNrlPpa4JLlaLAzq3Yenhr+LzWbjjk5d\nqBEezqS5s4msVp1OzZoze9FCNuzcgavF1X5u6Gffp1v27mXS3Nm4ulhwcXHh9cf74uPkuihF9eel\nO/7DMzOmYrOZ3Na8BdVDQ5my+FfqhoXRIfLS/+bJZ8/yzIypuBgGQT4+vH3f/U6M/NJcLRZeuvNu\nnpk2BZvNxm0tWlI9tAJTFi2kblg4Hf7iOLqnTTvemfs1PcaMBBNubd6CmrmP9XUmi6srTz33AkNe\nfA6bzcYN3W+lStVqfD5jKjVr16VVu/Z0u+U2Rg97mz73/xcvL29efsv+5/HWu+5m3Hvv0u+RBzFN\nkxu630LV6jU4cuggY4e/g81qwzRN2nXuQos27Zzet6Jc7nnw569msW3darKzMnm3fx9adOpKt//2\nKKmwC9h1IpZ6YaG8fc9NZOVY+Xz1prx1g+/syoh5S//y/fe2aYybiwsDbrI/WvVofBJfr9vq0Jgv\nZrG48tiA5xg26EVsNhudb+pOeERVZn86g+q16tC8TVu63NydD98bRv+eD+Dp5cXA194EIGrXDubN\n/gqLqysuhkGfZwbi7eOcguMiIiLFwXDkkJnc6Sg3Yi8yagAnsRcZTfnLN+Y6t3bDVTWeZ2dIhZIO\nodjFpZ4p6RCK1ZVW++NydIor+SdiFCe3ilff5yjr6LGSDqF4lYIaHsUtoWWrkg6hWO056dxaPs7w\n67Y9JR1CsXqyW+lIXBW3BuElP0JMREqdq+8CPJ9PV/5xVX2n/VOvjs1L5X5z6FNUchMZs/+qjWEY\nv5um6ZyhAiIiIiIiIiJOYlMNDqcqDbfZCj9gXkRERERERETkHygNCQ6ltERERERERETkXykNCQ4R\nERERERERkX/FoTU4LlOpLE4iIiIiIiIi8m+oBIdzlYYRHA+XdAAiIiIiIiIicmVzWILDMIze+X4O\nMwxjmWEYqYZhrDMMo9af60zT3OWoGERERERERETk2uDIERz98/08FpgL+APvAx87cLsiIiIiIiIi\nco1xVg2OWqZp3pv78w+GYbzhpO2KiIiIiIiIlAhTRTicypEJjjDDMCZgLyIaZBiGm2ma2bnr3By4\nXRERERERERG5xjgywfFSvp83AZ5AimEYocCPDtyuiIiIiIiIiFxjHJbgME1z1iWWxxqG8YOjtisi\nIiIiIiIi1x5n1eDAMIxIoAdwP5AGNHPWtkVERERERETk6ubQBIdhGFWwJzTuB3KAKkAz0zSPOnK7\nIiIiIiIiIiXNpiKjTuWwx8QahrEOWIC9oOh/TdNsCpxRckNEREREREREipvDEhxAAuAFhABBucuU\nvhIRERERERGRYuewBIdpmncA1wFbgLcNwzgC+BmG0cJR2xQRERERERGRa5NDa3CYppkGzARmGoYR\nAtwHjDcMI9w0zXBHbltERERERESkJJmqweFUjpyiUoBpmnGmaU4wTbMN0M5Z2xURERERERGRq5/D\nRnAYhvETf11z43ZHbVtEREREREREri2OnKIy2oG/W0REREREREQkj8MSHKZprvzzZ8MwgnKXJThq\neyIiIiIiIiKliU01OJzKoTU4DMN40zCMRCAK2G8YRoJhGG84cpsiIiIiIiIicu1xWILDMIyB2IuJ\nNjdNM8A0TT+gJdA2d52IiIiIiIiISLFw5AiOnsD9pmke+XOBaZqHgYdy14mIiIiIiIiIFAtHFhl1\nM00z8eKFpmkmGIbh5sDtioiIiIiIiJQ41eBwLkeO4Mj6P9eJiIiIiIiIiPwjjhzB0dAwjNNFLDcA\ndwduV0RERERERESuMY58TKzl3/6OPRUqFUcopYZ/+XIlHUKxq1UxuKRDKFbpmdklHUKxM5LjSjqE\nYuVS3qOkQyh2Hi2alXQIxSrDq3xJh1Ds/C1X18xKN1eHPkStRPS9oW1Jh1CsjsYnl3QIxa6rmcn5\nuJiSDqNYeTRrXNIhiIhIPlffFY6IiIiIiIiIXHMcOUVFRERERERE5JplqsioU2kEh4iIiIiIiIhc\n8ZTgEBEREREREZErnhIcIiIiIiIiInLFUw0OEREREREREQdQCQ7n0ggOEREREREREbniKcEhIiIi\nIiIiIlc8JThERERERERE5IqnGhwiIiIiIiIiDmBTEQ6n0ggOEREREREREbniKcEhIiIiIiIiIlc8\nJThERERERERE5IqnGhwiIiIiIiIiDmCqBodTaQSHiIiIiIiIiFzxlOAQERERERERkSueEhwiIiIi\nIiIicsVTgkNERERERERErngqMioiIiIiIiLiACoy6lwawSEiIiIiIiIiVzwlOERERERERETkiqcE\nh4iIiIiIiIhc8VSDQ0RERERERMQBbKrB4VQawSEiIiIiIiIiVzwlOERERERERETkiqcEh4iIiIiI\niIhc8a6aGhzbN23k88kTsdlsdLqpO7ffe3+B9dlZWUweM5IjB/bj5e1N/8FDCAoJBeDHOV+xYtFC\nXFxc6PlUfxo0bQ7Awh++ZcWvCzAMg7CIqvR9/mXKlCnD7m1b+Wr6ZKw5OUTUqMnjA1/CYrE4rG+b\nN6xn2oTx2GxWbrjlNu55qGehvo0dNpRD+6Pw8vbh5beGElKhAisWL+L72V/ltTt66CDjp39CaKVK\nDOrfL295YkI8nW+4kcefec5hffgrv69dy/j3R2K12bj9zrvo2fuxAuu3bt7M+NGjOHTgAO+MGEmX\nG27IWxcbE8OId94iLi4OA4OxH31EhYqVnN2FAjb+vo6Pxo3GZrPR/fY7eaBnrwLrt2/dwsRxYzh8\n6CBDhg6jY5euABzcv4/xo97j3LlzWFxceLBXbzrf0K0EelDYuj27Gf3tXGw2G3e2aUtLWHKLAAAg\nAElEQVSvbjcV2W7p1s0MmjGNz14aTGSVKnnLY5OTuefdt+nb/RYe7lo6+pTfms2bGDl1Cjabjf90\nu5HH7rm3wPq5C35h9i8/Y3Gx4FHOnTf6P0P1ypVLKNqirdm4gfc++hCr1cbdt9xCnwceLLB+1tw5\nfLfgFywWC/4+vgx9+RUqhtrPgQ2u70zNqtUAqBASzEfDRjg9/outW7eO0aPtn6M777yTXr16FVj/\nxRdfMH/+fCwWC35+frzxxhtUqFABgAEDBrBz504aNWrE+PHjSyD6ol0t5zrTNPn+k2ns3boZt7Jl\neaDfs4RXq16o3YnDB/lq4gSyszKp27gp/3n0cQzD4OTRw3wz7WOys7KxWFz4b58nqVKjFptWr2DZ\n/O8BKOvuzj19nqJSRFWH92fbHxv4dNJH2GxWutx8C3f2KPjZyc7KYuKoERw+sA8vbx+efe0NgkMr\ncDBqL1PHjbb/mwD3PNyLFu3akxgfz8RRw0lNTsbFxYXru99K9//81+H9yM80TeZ/NoOobZtxK1OW\n+54cQFjVwvvo5OFDzJkygeysLOo0asodPR/DMAxOHTvCdzMmk5WZgV9gMA88PRB3Dw+sOTl8M20i\n0UcPY7Naadq+M13uuNupfVu7fRvvfz7Lfm7o1IXet99RYP03S5cwd8liXFxc8HB35/XHHqd6WBgA\n+48f490Z0zmXno6LYfDF0GGULVPGqfGLyLVHFTic66pIcNisVmZNnMCg4aPwDwzijWf70bRlaypV\nichrs2LxQsp7ejJ25uf8vuI3Zs+cxoDBQ4g+dpT1K5czcvIMUpKTeG/wS4yePovUlGQWz/+BkVNm\nUqZsWSYMf4f1K3+j3fXdmDJmJINHvE+FsHC+/ewTVi9dRKcbuzukb1arlcnjRjN07AcEBAXzfN/H\naNmuPZXzXfQt/uUnPL28mPr1N6xatoRPJ0/ilbeH0qnbjXTqdiMARw8d4t1XX6FazVoATJg5K+/9\nz/V5lNYdOjok/r9jtVoZ895wPvh4CsEhIfR+8AHad+xE1eoXLsRCK4Qy5O2hfPnZrELvf2fI6/Tq\n04cWrVpz/vx5XAzDmeEXYrVa+WD0SN6fMJGg4BCeerQnbdp3ICL3yyNASEgorwx5i7lffV7gvWXd\n3Rn0xtuEVa5MYkICT/Z6iOatWuPp5eXsbhRgtdkYOfdrJvZ/lhBfP3q+P4IO1zWgWoWKBdqdy8hg\nzorl1C/iC8mY776hTb16zgr5H7FarQz/eBJT3x1GSEAg9w98jk4tWxVIYHTv1Jl7u98CwPIN63l/\n+jQmvzO0pEIuxGq18u4H45n2/hhCg4K478kn6NymLdUjIvLa1K1ZkzmTp1LO3Z3Z8+cxZspkxrz5\nFgBly5Tlu+kzSib4IlitVkaOHMnEiRMJCQmhZ8+edOjQgWrVLnyO6tSpw3//+1/c3d359ttvmTBh\nAiNG2BMzDz/8MBkZGXz//fcl1YVCrqZz3d6tm0mIjeG1CZM5dmA/30z/mOeHjy7U7ptpk7n3iX5E\n1KzNlBHvsHfbFiIbN+WnL2Zx4397ENm4KXu2bOLHL2Yx4K1hBASHMOCt4Xh4erJn62bmTJ1Y5O8t\nTjarlZkffsBrI0cTEBjE4P5P0qx1W8LyXT/89usCynt6MmHWV6xdvoyvpk/ludffJDyiKiMmTcFi\ncSUlKYmXn3yMpq1bY7FYePiJflSrWYv08+cZ3K8vDZo2K/A7HS1q2xYSY0/xythJHD+4n+9nTuGZ\noaMKtft+5mTufuwpqtSszYxRQ9m3fQt1GjXlm2mTuPXBR6hetz4bVyxlxc/zuOneB9ixYR052Tm8\nMPIDsjIzGf3SABq1aY9/ULBT+mW12Xjv05l8PPg1QvwDeHDIq3Rs0jQvgQFwc5u23NPVnhxcsXkT\nY7/8nImvDCbHauX1SRMZ+tTT1K5ShdQzZ3B1vSoug0VEJJ+rYorKof1RhFSsRHCFiri6udGqY2c2\nr19XoM2W39fRPvfOcYv2Hdm9bQumabJ5/TpadeyMW5kyBIdWIKRiJQ7tjwLsF6RZWZn2/2dm4Ocf\nyNnTp3F1c6NCWDgA9Zs05Y81qx3WtwN791ChUhihFSvh5uZGh+u7suGi7W1Ys5rrb7oZgLYdO7N9\nyybMi6r1rlq2hA5duxb6/adOnCAtJYV6DRs5rA9/Zc+uXYSFh1MpLAw3Nze63ngTq1asKNCmQsVK\n1KhVCxeXgofrkUOHsFpzaNGqNQAeHh64lyvnrNCLFLVnN5XCwqlYyd6fLjd0Y92qlQXahFasSPWa\nNXExCvYnvHIVwnK/VAcGBeHr509qSorTYr+U3UePEh4YTFhgEG6urnRr0pyVO3YUajf55x/p2bUb\nZS66YFyxfRthgYFUC63grJD/kV3791O5QkXCQivg5ubGTR06sHz97wXaeHp45P2cnpFBCefRCtkZ\ntZfKFSsRXrEibm5u3NylC7+tXVOgTYvGTSjn7g5Aw8hI4hISSiLUy7J7927Cw8MJyz0vdOvWjZUr\nC36OmjVrhntuf+rXr09cXFzeuhYtWuCRb5+VBlfTuW7npo0079AZwzCIqFWb9HPnSEtJLtAmLSWZ\njPTzVK1VB8MwaN6hMzv/2GBfaUBG+nkA0s+fx8fPH4Cqtevi4ekJQETN2qQlJTm8Lwf32a8fQnKv\nH9p06sIf69YWaLNp3Vo65o5aa9WhI7u2bsY0Tcq6u2Ox2M932VlZGNhPDH4BAXk3E8p5eFCpchWS\nExMd3pf8dm/eSNP29n1UpWZtMs6f4/RF++h0SjIZ6elE5O6jpu07s2vTRgASYqKpVseelK51XSN2\n/pF7TjQMsjIzsFqtZGdlYnF1deqxuOvQQcJDQgkLDsHN1ZUbW7VhxeZNBdoUOF9nZub9/PvOHdSs\nXJnauaMLfb28sLhcFZfBIiKSj0PP7IZh+BiGcZ9hGM8bhjEw92ff4t5OSmIi/kFBea/9A4NISSp4\nMZGSlIh/oP0Og8ViwcOjPGdPn7YvL/DeQPvvCwyi+9338GzP++n/wD14eHhyXdNmePn4YLXmcHj/\nPgA2rllFUqLjvigkJSYQGByS9zogKIiki76Y5G9jcXWlfPnynE5LK9Bm9W9L6Xj9DVxs5bIltOty\nPUYJfWNLiI8nOHeqEEBwSDAJCXF/8Y4Ljh8/hqeXF4NeGEjPHvfy4bixWK1WR4V6WRIT4gnOt78C\ng4NJSIj/x79n7+5d5GRnUzHfXamSEp+WQoifX97rYD9f4tMKJl6iThwnNiWF9tc1KLA8PTOTWUsW\n8Xju6IfSKC4piZCgwLzXIYGBxBfxxWr2zz/RvU9vxn0yk0F9n3RmiH8rPjGR0OALd1BDgoKI/4sv\nVN8vWED7li3zXmdlZXHvE315oN9TLHNgwvZyxcfHExJy4XMUHBxMfPylP0fz58+nTZs2zgjt/3Y1\nnevSkpPwC7zwmfENCCQtOalQG9+AgHxtAvLa3PVIH378/FPeeqo3P37+Cbc+8HChbaz/bQl1Gzdx\nUA8uSE5MICDfNUBAYBApF/1NT0660MZiccWjvCdnTtv/xh7Yu4cX+vTixb6P0ufZ5/MSHn+Kj43h\nyMED1KhT18E9Keh0ShK+/hf+/X38A4pMQvlc1OZ0in0fhYZVZvdme7Jj+/q1pOVeUzVo0ZoyZd0Z\n2q83w57pS8db7sTD03mjDOOTkwnJd1yF+PuTcFG/AOYsXsRtA5/hg6+/5OVHegFwPCYGA+j33nDu\nf20Qn/70o5OiFhERZ3JYgsMwjJ7AFqAT4AGUBzoDm3PXFZui5zUV/MJ+8YiGP5sUvdzg3JkzbFm/\njnGffMmHX84lMzOdNb8twTAM+g96nS+mTuKNZ/tRrpwHFhfH1d8oOryL+/bXbfbt2U3Zsu5UKWKO\n9OplS+nYtXDiw1nMIvaeweUlW6w5VrZv3cqAgS8w84uvOHXyJL/8OL+4Q/xHij7M/lnyKCkxkRFv\nv8HLQ94sdCe3RPxNn2w2G2O/+4aB/yk8D3vKLz/xQJfr8Sjr7sgI/6UijsEiEn49br2NBdNn8lyv\nR5k6Z7YzArtsRZ3HLpWz/GnJYnbv28ej9/XIW7ZkzlzmTpnKyNeHMPKjjzgeHe2oUP9vl0rCLliw\ngL1799KzZ7H+WSl2V9W5rsjj7aK+/MV5Y+3ihdz1yGO89fFM7nzkMWZP/rBAuwO7drB++VJue/CR\nYgv5Uoo6Zxf68PzF39iadSMZM/1Thn80hXmzvyQr68KIgYz084x9500eeao/HuXLF2PUf++y/hYV\n3XkA7u3bn3VLFjL+1RfIzMjAkjsy7/ihA7i4uDBk4gxeHT+ZVQvmkxQXW8zR/0NFnBvu63YjP42b\nwLM9HmD6vB8AsNqsbN2/j2FP92fmG2/z26Y/2LBrp7OjFZFrkM00r8r/SitHTj58DWhqmmZq/oWG\nYfgBG4DPinqTYRh9gb4Ag999j7vuf7CoZgX4BwaSnG9UQ3JiAn75Mvz2NkEkJ8YTEBSE1Wrl/Plz\neHp525cXeG8ifgEB7Nq2haCQULx97QNOmrVpz4E9e2jX5QZq1q3HG6M/AGDn5k3ERJ/8+3+N/1Ng\nUBCJ8Rfu8iUlJOCf785Z/jaBwcFYc3I4d+4cXt7eeetXLVtKhyKSGEcOHsBqtVKjdh2Hxf93goND\niM93cRQfF0/gZc7lDQ4JoVbtOlTKHeXQoXNndu0s2YuVoOBg4vPtr8T4eALz3R38O+fOnWXw88/S\n+4l+RNa/zhEh/mPBvn7E5ZsqE5+SSpDPhYFY5zMzORRziic+GAtA0unTPD9lEmOf6MeuY0dZtm0L\nE+Z9z5ncom5l3Ny4r2Nnp/fjUkICAolLuDDaIS4xkSB//0u2v7lDR4ZNmuiM0C5bSFAQsflGOMQl\nJBAUEFio3e+bNzH1i8/5dPwEyuQrrBece04Jr1iR5o0aEXXwAJUrlVyx3uDg4AJTTuLj4wkq4nO0\nYcMGZs6cydSpUwv0pzS60s91q3/9hd+XLQGgcvUapOQbIZSalIi3X8HPjE9AAKn5RkKlJiXhnfu5\n+mPlcv7z6OMANGrdltlTPsprd+rYUWZPmcgTg9+gvJc3jnbxqMikxAT8Lvrs+Afa2wQEBWO15nD+\n3Fk8L4otrEoVyrq7c+LIEarXrkNOTg5j3n6Tdl260rJ9B4f3A2Dt4gVsWG7fR+HVapCab1RNWnIS\n3vlG4kHuqI5Cbez7KLhSGH0HvwXYp6tEbbVPA9m6bhW1GzbG4uqKp48vEbXqcPLIIQLyjU5ypGB/\nf+LyHVdxyckE+fpdsv2Nrdsw/JMZue8NoGmduvjl7rt2jRoRdfQoLUvJ31oRESkejrw9bFD04Aob\nFw+vyMc0zammaTYzTbPZ5SQ3AKrVqkPsqWjiY2PIyc5m/crlNGlVcLhyk1atWb10MQAbV68ksmFj\nDMOgSas2rF+5nOysLOJjY4g9FU31WnUICArmYNReMjMyME2T3du2UCncXh8hLdX+ZS87K4ufvpnN\n9d1vu6w4/x8169Tl1MmTxJ46RXZ2NquWLaVF23YF2rRs255lvy4EYO3K5TRo0jTv7pLNZmPtit/o\ncH3h+hsrly4pMvHhTHX/x959R0dRtXEc/042FUhI3ZCEAKEmAaX3LgiCqNgr2BAr9t5BiihFEBRR\nsWABu6IiTar0DqH3EEIKCaGl7s77R0JISFDwze4m+Puc4zE7c3fnuezs3dlnbmnYkPgDBziUcJDc\n3FzmzvqDjl3Ob8LTmIYNOX7sGOlp+d1T16xaSVSRSQhdITomloT4eBIPJZCbm8ufc2bT9jwvbnNz\nc3n1uWfo0ftKupTyfrlKbM2axKckk5CaSm5eHrPXrqLTpWeGolTx8WHeyNHMGDKcGUOG06hWFGPu\nf4jYmjX56ImnC7ff2uUy7u5xRblKbgA0rF+f/YcOcfDwYXJzc/lj0SK6tG5TrMz+Ij0aFq1aRY3w\n8LNfxqUaRUdzIOEgBxMTyc3NZeaff9K1XftiZbbu3MHgMaOZMGwEQUV+6GQcP05OTg4A6RlHWbd5\nE3WcOBliaWJjY4mPjychIf9zNHv2bDp1Kv452rZtG8OHD2fMmDEE/k1Cqryo6G1dxyuu5Nm33+HZ\nt9/hklZtWLVoPqZpsm/HdnwqVS6cR+O0qgGBePn4sG/HdkzTZNWi+VzSohUAfoGB7NqyGcjvrRFS\nLf/zlJ6awpRRI7jjkcexOmmFmDoNGnA44SDJifnXD0sX/EmLtsWvH1q0bcfC2X8AsHzRQho2aYZh\nGCQnJmKz5QGQknSYxPh4QqpVwzRNJo1+i4gaNehzw00ljuko7Xv05skRY3lyxFgatWjNmsX579H+\nndvx9qlUIgnlV/Ae7d+Z/x6tWTyfhs3z36MTGfn3pux2O3N//I423fMnLA8ICmFX3CZM0yQnK4v9\nu3YQ4sTVfBrWrsOBw4dJSE4mNy+PWcuX0qV582Jl9h9OLPx78fp1RBbM/9Tu0kvZGX+AzOxs8mw2\n1mzdSm0XJnJFRMQxHNmDYxiw1jCM2UB8wbYawOVAmS4/YLFYuPPBQbz18nPYbXY69+hF9Zq1+O7z\nT4iq34DmbdrRuWdvJr09gifv6UcVX18eef5lAKrXrEXrjl147v57cLNYuOuhQbhZLNSNjqFVh068\nPOgBLBYLNevUpWuv/HkEfvvuG9avXI7dbqf7lVfTsEnTsqxO8bq5u/PA40/y2tNPYLfb6N67DzWj\navPFxx9Sr0E0rTt05PIr+zBm2BAG3nojVXz9ePb1IYXPj9uwnuAQK9VKuQBZMv9PXnvLsTPU/xN3\nd3eeeu4FHn/oQex2O32u6UvtOnWZ/N5EYmIb0rFLF7bEbeb5J5/g+LFjLFm0kI8mvcdX3/+IxWJh\n0JNPMuiBgZimSXRMLNeUMkzCmSzu7gx6+hmee2wQNruNXn2uJqp2HT6ZPIn60TG079SZbVviePW5\nZzhx/BjLlizm0w8n88nX37Bg7hw2rlvLsYwMZv32KwDPvfIades3cGmd3C0WnrnpZgZNHI/NtHN1\nm3bUCQtn0q+/EFOjJp0vbezS+P5f7hYLLz7wIA+++jI2u52+l/egbs2aTPxiKrH16tG1dRu+/nUG\nKzasx93ijl+VKgx94ilXh12Mu8WdFx99nPuffRqb3c61vXpTNyqKCVM+pmGDaLq2b8/oSZM4lZnJ\nk6+/BpxZDnbP/v0MGTMKw3DDNO3ce+vtxVZfcUl93N155plnGDRoEDabjauvvpo6deowadIkYmJi\n6Ny5M+PHjyczM5Pnn38egNDQUMaOHQvAgAED2LdvH5mZmfTu3ZtXXnmFtm3burJKF1VbF9u0OVvX\nrmboow/g6enFrQ8NKtz31jOP8+zb+Uvz3jjgAb56L38J0pgmzYhpmv9D9Jb7H+aHTz7Cbrfh7uHB\nzffnL1s+67tpnDxxnG8/+gAAi8WNp94c49C6WCzu3PPIYwx/4Zn8ZeZ79iKyVhTffDqF2vUb0KJd\ne7r26s2EN4fz6J23UcXXj8deehWAbZs38fP0r7BYLBhubtz76OP4VfVn2+aNLJ47mxpRtXn2/vyl\ngG+95z6anpU4daToJs3Zun4Nbz7xIJ5eXtx0/5n3aMwLT/DkiPzPynX33M/0SQXLxDZuRnST/HlP\n1i1dzNI5+TdOLmnZhpaduwHQrkcvvpn0LqOffQwTk5adLiO8Ri2n1cvdYuG5u+7moZHDsdvtXNO5\nK3WqR/Led98QG1WbLs1bMH32LFZs3oy7xYJf5cq88cCDAPhVrsIdva7kjldewjCgQ+OmdHTCPC8i\nIuJcRqlzUJTVi+cPR+kJRJDfa+MgMMs0zfNaGmLVnoPld3DPv1C1smtX+HCEYF/njit2tMzsXFeH\nUOb8Vq/+50IViGetGv9cqIJxc/L4fEfLusjaBYBci4erQyhTK3buc3UIZS4soKqrQyhTB1Jcv4pW\nWetuZv9zoQqmUgvH3eQS+Q8pZ+vTla23Zsy/qH7TnvbsVV3L5fvm0AXACxIZfzsbn2EYy0zTdO2t\nNREREREREZEy5sgOBVJSOViigfK8vIKIiIiIiIiIVADlIcGhlJaIiIiIiIiI/F/KQ4JDRERERERE\nROT/4tA5OM5TuZycREREREREROT/YbdrwIIzOa0Hh2EYfoZhNC9YWaWofs6KQUREREREREQuTg5L\ncBiG8YVhGMEFf/cE4oCRwHrDMG48Xc40zc2OikFERERERERE/hscOUSlsWmaqQV/vwZ0NE1zX0HS\nYx7wrQOPLSIiIiIiIiL/IY5McLgZhuFnmuYxwA4cADBNM9UwjPIw94eIiIiIiIiIw5im5uBwJkfO\nwTEYmG8Yxj3AX8C3hmH0NwzjU+APBx5XRERERERERMohwzACDcOYYxjGzoL/nz1PJ4Zh1DQMY41h\nGOsNw4gzDOOB83lthyU4TNP8BrgZaADUBzyBtsDXpmk+5ajjioiIiIiIiEi59TwwzzTNeuRPX/F8\nKWUSgXamaTYBWgPPG4YR/k8v7NChIqZp7gKeO3u7YRgtTdNc5chji4iIiIiIiEi5cw3QpeDvz4AF\nnJU3ME0zp8hDL86zc4bT5sIwDCMWuAW4FcgAWjjr2CIiIiIiIiLOZtccHKUJNU0zEcA0zUTDMKyl\nFTIMIxL4DagLPGOa5qF/emGHJjgMw6hJfkLjViAPqAm0ME1znyOPKyIiIiIiIiKOYRjGQGBgkU2T\nTdOcXGT/XKBaKU996XyPYZpmPHBpwdCUnwzD+M40zaS/e47DEhyGYSwFqgLTgBtM09xpGMZeJTdE\nREREREREKq6CZMbkv9nf/Vz7DMNIMgwjrKD3RhiQ/A/HOmQYRhzQEfju78o6chWVFMAXCAVCTsfm\nwOOJiIiIiIiISPn2C3Bnwd93Aj+fXcAwjOqGYfgU/B0AtAe2/9MLO3IVlWuAS4C1wGDDMPYCAYZh\ntHLUMUVERERERESkXHsTuNwwjJ3A5QWPMQyjhWEYHxWUiQFWGIaxAVgIjDJNc9M/vbCjV1HJAKYA\nUwzDCCV/2dh3DMOINE0z0pHHFhEREREREXElDWEoyTTNI0C3UravBgYU/D0HuPRCX9uRQ1SKMU0z\nyTTN8aZptgM6OOu4IiIiIiIiInLxc+QkozP4+4TV1Y46toiIiIiIiIj8tzhyiMooB762iIiIiIiI\niEghhyU4TNNcePpvwzBCCralOOp4IiIiIiIiIuWJaWoWDmdy6BwchmG8ZhhGKrAN2GEYRophGK86\n8pgiIiIiIiIi8t/jsASHYRhPkD+ZaEvTNINM0wwAWgPtC/aJiIiIiIiIiJQJR/bg6A/caprm3tMb\nTNPcA9xRsE9EREREREREpEw4cpJRD9M0U8/eaJpmimEYHg48roiIiIiIiIjL2TUHh1M5sgdHzr/c\nJyIiIiIiIiJyQRzZg6OxYRjHStluAN4OPK6IiIiIiIiI/Mc4cplYy//7GoFVKpdFKOXG7sMX3yq5\nB1LSXR2C/IO2F9nnyPD0dHUIZS7L9+J6j3xOZbk6hDK35HCCq0MoU39u2uHqEMqcr8/Fde+kUY0w\nV4dQ5nITE10dQpmy+PlxYsESV4dR5qp06eDqEERE/jVH9uAQERERERER+c8yNQeHUzlyDg4RERER\nEREREadQgkNEREREREREKjwlOERERERERESkwlOCQ0REREREREQqPE0yKiIiIiIiIuIAdk0y6lTq\nwSEiIiIiIiIiFZ4SHCIiIiIiIiJS4SnBISIiIiIiIiIVnubgEBEREREREXEATcHhXOrBISIiIiIi\nIiIVnhIcIiIiIiIiIlLhKcEhIiIiIiIiIhWe5uAQERERERERcQBTk3A4lXpwiIiIiIiIiEiFpwSH\niIiIiIiIiFR4SnCIiIiIiIiISIWnOThEREREREREHMCuOTicSj04RERERERERKTCU4JDRERERERE\nRCo8JThEREREREREpMJTgkNEREREREREKjxNMioiIiIiIiLiAJpk1LnUg0NEREREREREKjwlOERE\nRERERESkwlOCQ0REREREREQqvItyDo7VK5bxwbix2O12eva5mpvu6F9sf25ODqOGDWbX9u34+vnx\nwuChhIaFk5eXx7iRw9m1Yzt2Wx6X9ezNzf3uBOCnb6cza8bPmKbJFVddQ9+bbnFafUzT5PtPJhO3\ndg2eXl7c8fBjRNauW6Lcgd27+GLiO+Tm5NCwWXOuv3sghmEwZcxIkg8lAJB56iQ+lSrz/KjxnDx+\njI9Hv8n+XTtp3aUbNw14wKl1+nbKB8StXY2npxf9Bj1BjVLrtJOpE8aSk5NDw2YtuPGe+zEMg9+m\nf8lfc2dRxc8PgKtvu5NGzVtyJDmJNx57AGt4BABR9aO59f5HKmx9TktLSeaNxx/kyptuo/s11zu8\nPmf7a+NGRn01FZvdzrWdunB3n6uK7f/uz3l88+dc3Aw3Knl78/Jd91A7IoLcvDyGfjqFrfv2YhgG\nz9zWjxYxMU6PvzRLVq1k5PvvYbPbue6KXgy45dZi+z/77jt++ON3LBYLgVX9GfLU04SHhgIw5sPJ\nLFq5ArvdpG2zZjz/0MMYhuGKahRaunQpo0aNwm6307dvX+66665i+7/44gt+/vlnLBYLAQEBvPrq\nq4SFhQEwaNAgNm3aRJMmTXjnnXdcEH3pFq9Yzpvjx2Gz27n+yj7cd0e/Yvs/nT6N73/9FXeLhQB/\nf4Y+/wLh1aoV7j9x8iRX9budbh078fITTzo7fCC/bfjhkw/Zum4NHl5e3PbQY0TWrlOiXPyeXXw1\ncTy5OdnENG3OdXffh2EYHNy3h28/fJ/cnFwsFjduGPAANevWZ/XiBcz7+QcAvLy9uXHAg0TUinJ2\n9QC4pkUjoiNCyc2zMX3ZOhLSMkqUGXBZG3x9vHAzDPYmp/Hjqo2YJtzeoTlWvyoAeHt6kJWTy9jf\nFzq7CsX0bNyAetVCyLXZ+Hn1Zg4fPV6izG3tm1HF2ws3N4MDqenMXLcVE4iJCMCrwmsAACAASURB\nVKVzbB1CfCvz0Z8rSDx6zPkVOItpmsyYOoXt69fh6eXJDQMfISKqdolys775inVLFpJ58iSDP/6i\ncPvi32ewesE83CxuVPb14/qBDxMQHOLMKhSzbNtWRv/yI3a7yTWtWnPnZd1LLTdv43pemPoZnz76\nBLGRNciz2Rj67TS2JyRgs9vo3bwld53juc62dPMmRn3zNTa7Sd8OHbn7it6llpu7ZjXPTX6fqS+8\nQmytWizfEse7P35Pbl4eHu7uPHb9jbSKLh/fsSJyhqk5OJzqoktw2Gw23hszimFjxxMcYuXx++6m\nTfuO1Ig6c+E367dfqOLrx8fTvmPh3DlMmTSRFwYPY/H8eeTm5PD+Z1+SlZXFA/1uoUv3y8nMzGTW\njJ8ZO3kKHu7uvPL047Rs246IyBpOqdOWdWtITjzEq+9+wL6d25n+4fs8PWJ0iXLTP3yPW+9/hFr1\nG/D+8NfZsn4NDZu24J4nnyss88NnH+NTqRIA7h6eXHnz7STGH+DQgf1OqctpcWtXk5J4iNcnfMi+\nnduZNnkiz745tkS5aZPf49YHBhFVP5r3hr3GlnVraNisBQCX9bmm1B/7waFhvDh6gsPrUJQj6wPw\n/Scf0rBpc4fW4Vxsdjsjp37Ge888R2hgIHcMfpXOTZtROyKisMwVbdtxw2XdAFi4bi2jv/6SiU8/\nyw8L5gPwzdARpB3L4JHRo/jitcG4ubm285jNZmPYhHeZ/OZIqgWHcMugh+nath11atYsLBNTty7T\nJryHj7c302f8wpiPJjPqpVdYHxfHurg4vp80GYD+Tz7O6o0baNm4iauqg81mY+TIkUycOJHQ0FD6\n9+9Pp06dqF37zI+Y6OhobrjhBry9vfnuu+8YP348I0aMAKBfv35kZWXxww8/uKoKJdhsNoaNHcOH\nY8YSGmLl5oED6NqhA3WL/IiPqVefbz78CB9vb6b99COj33+P0YOHFO5/96MPadHEde8LwNZ1a0g5\nnMhL4yexf+cOvv3ofZ4cPqpEuW8/nMRN9z9ErXoN+GDEELauX0ts0+bM+OIzet5wC7FNm7Nl7Wp+\n+eIzBr0+jCBrKINeH06lKlXYsm4N0ydPLPV1HS063Eqwb2VG/jyPGsEBXNfqUt79Y3GJclMXryY7\nNw+A/p1acGmNcDbsP8SXS9YUlunTrCFZublOi700dasFE1SlMhNmLSEisCpXNo3l4/krSpT7bsUG\ncvJsANzYpjGx1asRd/AwKcdO8O2y9VzZLNbZoZ/T9g3rOHI4kadHv0v87p389OlkHh78ZolyMc1a\n0PbyXox+elCx7eG1onj4jZF4enmxfO4sZn49ldsGuSZhaLPbeevH75kw8AGsVf25c/xYOjZsRO3Q\nasXKnczKYvqSxTSqcaZNn7txPbl5Nr5+6lmycnK4edSb9GjSjPDAQGdXoxib3c6bX3/Je48/RWhA\nAP1GvEHnS5tQOzy8WLmTWZlM+3MujYokp/yrVOGdhwcR4h/AroSDPDJ+LH+MLHl9KCLyX3LRDVHZ\nsXUL4RHVCQuPwMPDg07dLmfZkkXFyixfvJjuBdnxDl26smHNakzTxDAMsrIyseXlkZOdjbu7B5Uq\nVyZ+/z4axDbE29sbi7s7jZo0Y+ki591h2rRqOa06X4ZhGETVjybz5Eky0tOKlclITyMr8xRRDaIx\nDINWnS9j08rlxcqYpsm6ZUto3qEzkH/Xr05MQ9w9PJxWl9M2rlpO6/Op06lT1G4Qg2EYtO58GRtW\nLnN6rOfDkfXZsGIZQaHVCIus+Y9lHWHznt1UDw2lutWKh7s7PVu3YcG6NcXKVPHxKfw7Mzu7sDfD\nnkMJtIptCECgX1V8K1Viy769zgv+HDZt306N8HAiw8Lx8PCgV+cuzF/6V7EyrZo0wcfbG4BLY2JI\nSknN32EYZOfkkJuXR05uLnl5NoICApxdhWLi4uKIjIykevXqeHh40KNHDxYuLN5GtWjRAu+C+jRq\n1IikpKTCfa1ataJSQeKzvNi0dSuREdWJDI/A08OD3t26M3/JkmJlWjdrVvgeNY5tyOGUlMJ9cdu3\ncSQ9nXYtWzk17rNtWr2Slp26YhgGteo3+Pv2u35++92yU1c2rSr4UW1AVuYpADJPnaJqQP6PsagG\nMVSqkt/zoVa9BmQcOeK8ShXRMLIaa/YeBOBAajrenh74+niVKHc6ueFmGFjOkeBsXDOc9fsSHBfs\neWgQFsKG/YcASEjLwMvDnSreniXKnU5unK6PSf7dudTjJzly4pTzAj4PW9esommHLhiGQY269ck6\neYpj6eklytWoWx+/UtqyOrGN8PTyKihTj2NprjnXAOIOHKB6cDARQcF4uLvTo0lTFsVtLlHug1kz\n6dflMjzdz9zHMzDIzMkmz2YjKzcXd4s7lb1LnqvOFrd3D5FWK9VDQvLr1KIVCzasK1Hu/Z9/on/P\nXngVuWaLrlGTEP/896xOeAQ5ubnkuDhJKCLiag5NcBiGUdUwjJsNw3jSMIwnCv72d+Qxj6SkEGy1\nFj4ODrFyJDWleJnUFEKs+V3NLe7uVKpchWMZGXTochne3j7c3rcPd95wDdffeju+flWpGVWbzRvW\ncywjg6ysLFYvX0pqchLOcjTtCAFBwYWP/YOCyDjrAiMj7Qj+xcoEc/SsMru3xuFb1R9rWPG7Aq6Q\nkXYE/yJdXP2Dgjl61gX60SNH8A8KKlamaL0XzvyVYU88zNSJ73DqxJkuxEeSDzPi6UGMfeU5dm0p\neeHjCI6qT3ZWFnN++o7eN93m4BqcW0p6OtWK3OGyBgSSXMrF8fS5c7j6macY9800nr09fyhB/Ro1\nWLh2DXk2GwkpyWzdt4+kI2klnutsyampVAs5006EhoSQ9Dc/EH/44w86tMwfMtQkNpZWTZpw2S03\ncdktN9G+RQtq13BN8um05ORkQguGzwBYrVaSk5PPWf7nn3+mXbt2zgjtX0tKTSHMetZ7lJJyzvLf\n//YrHVu3BsBut/P2xAk89eBDDo/zn2SkHSEguHjbXHr7XbRtONPGX3vnAH6Z+imvP3gPv0z9hD63\nFR+mA7D8zznENG3moBr8PT8fb46ezCx8nHEyk6o+3qWWHXBZG167oSfZuXlsPHCo2L4oayDHs7JJ\nPX7SofH+E18fb45lZhU+Pp6Zha936fW5vUMznurThezcPLYedN41wYXKSC9+flUNDORY+r9LUqxa\n+Cf1Gzctq9AuWMqxo4T6n7mMtFatSkpG8SFR2xMOknT0KB0Lkuundbu0MT6eXvR+4zWuHjaEOzp3\noWqlyk6J++8kHz1KaMCZ79jQgABSjh4tVmbbgf0kpafR6dLG53ydeWvX0CCyBp4uuGklIlKeOCzB\nYRhGf2At0AWoBFQGugJrCvY5xOm7KMViObtMKeOgDMNg+5Y43CxufPHTr3zyzQ/8MO0rEg8lUKNW\nFDfe3o+XnhjEK08/TlTdelgszhvdU/qwLeOsMqXXqag1SxbRvEOnMozs3ys93hKlSnlmfqGOPXsz\neOJHvDD6Xar6B/D9Zx8D4BcQyBsffMoLo97l+rsG8Mk7b5N5yvF30xxVn9+mf0HXPn3xLtJDwtlK\nrVuJTxXc3P1yfnl7NI/eeDMfzfgZgGs6dsYaGMgdr7/KqK++pHG9ulgsru84Vmo7cY4pNGbMncuW\nHdu5+8abADiQkMCeA/uZ+9U05n09nRXr17F640ZHhvuvnGtOkN9//52tW7fSv7/DmuGycR5t2mkz\nZs8ibvs27rk1PxH49Y8/0rFNW8KKJH1c5nzqUUrTcPoz9tfsmVx75728/v4U+t55L9MmvVus3M7N\nG1k+fy5X3X5nmYV8IUp7T8410vijP5fzxvezcbe4UTe0+BwOTWtVd3nvDSh5vZCv9Bp9uWQtY35b\niLvFjSira4c5/K3Szq9/MWfQuiWLSNizm05XXlMGQf07pV4PFamK3W5n7C8/8dhVJWOMO7AfNzeD\n318ZzE8vvsyXixaQcCTVccGep3+6brXb7Yz5djpP3HDzOV9j96EExv/wHS/eUc7bdZH/KNM0L8r/\nyitH/kp/CWhummaxNLRhGAHACuDz0p5kGMZAYCDA0LfHcEv/uy7ooMEhVlKL3LlMTUkm8KzJsIJD\nrKQkJxFstWLLy+PUyRP4+vmxYO5smrdqi7u7O/4BgcRecik7t20lLDyCnn2upmefqwH49IP3CbY6\ndoKtRX/8xtK5s4D8LqHpRb6Ejx45QtWzxozm9xgoWia1sCsz5I9n37ByGc+MLDkvhLMsnPkrf839\nA4CadetztEjPmqNHUqkaGFSs/Nm9IPLL5NfJz/9MN9r2l1/B+8MHA+Dh4YFHwd2LGnXqEVItjORD\nCdSsW69C1mffzh2sW/YXP02dQubJkxhuBu4ennTpXXyST0eyBgZyOO1Mr4vk9DRCAs7dEatn6zaM\n+PxTANwtFp6+7Y7CfXcNHUyNs8ZKu0JocAiHU860E0kpKVjPer8Alq1dw4dff8Uno0bj6ZnfTX3e\nX0u4NDqWSgVJpw4tW7Fx21ZaXHqpc4IvhdVqLTbkJDk5mZCQkm3UihUrmDJlCpMnTy6sT3kVGmIl\nMfms96hIT4jTlq1exeTPP+fTdycU1mlD3GbWbNzAtJ9+5FRmJrm5uVTy8eHJBx50SuyL//iNZfPm\nAFCjTl3SU4u3zX4BxdvvqkFBZ7UNR/AraBtWLZzPdXffB0CTtu2Z9sGZ+YUO7d/HtA8mcv8Lr1LZ\n189h9Tlbu/q1aF03v9dS/JGj+Ff2gYLmr2pln2I9IM6WZ7cTdzCJhpHV2Hk4/0luhkGjyDDGzXTN\n5KItakfSLCp/TqFD6cfwK9IDxdfHm+NZ2ed8rs1uZ/uhFOqHW9mT7PreaactmzOTVfPnAVC9dp1i\n51dGWhq+/heWkNm1eSPzf/megS8Nccmw1tOsVf1JKtK7ITkjgxC/qoWPT2Vns/vwYR6clP85OXL8\nOE9/+jGj7rqXWevW0rZBNO4WC4FVfGlcK4otB+OJCCrZrjhTqH8ASUWGrSWlpxNcpJfKyewsdiUk\nMHDMWwAcycjgiffGM/ahR4mtVYuk9DSefn8iQ+6+l8giPRNFRP6rHJngMCj9toedc90kAUzTnAxM\nBtidnH7BqaH60TEcOhjP4UOHCAoJYdG8OTz72pBiZVp36MjcP34nptElLFkwn0ubtcAwDKyhoWxY\nu5rLel5BdlYW2+I20/fG/Iz50fQ0/AMCSU46zNJFCxg96cMLDe2CdLriSjpdcSUAm9esYtEfv9K8\nfSf27dyOd6VKxZIXAFUDAvH28WHvjm3UqteAlQv/pHOvMz+Ct29cT2h4RLGhLs7WuVcfOvfqA8Dm\nNStZOPNXmnfozL6d2/GpVLnUOnkVqdOKInXKSE8rLL9hxVLCC4YIHM/IoHKVKrhZLKQeTiQ58RDB\nDvpB7Yz6PDn0rcLn/zb9S7y8vZ2a3ABoGFWb+KTDJKQkYw0IZNaK5Qx/oHjX/wOHD1OjYPWKxRvW\nE1nwb56ZnQ2Y+Hh5s3zzJixulmKTk7pKowYN2J+QwMHEREKDg5m5cAEjn3+xWJmtu3YyZNw7TBo+\notgcG2FWK9/N/J08262YpsmajRu549rrnF2FYmJjY4mPjychIQGr1crs2bMZOnRosTLbtm1j+PDh\nvPvuuwS6eFK989EoOpoDB+M5eOgQ1pAQfp83l7dffa1Yma07djB41Nt88PboYu/RW0XK/Tjzd+K2\nbXNacgOg4xVX0rGg/Y5bu5rFf/xGs/Yd2b9zx9+2Dft2bKdmvfqsWjS/sP33Cwxk15bN1Gt4CTs3\nbySkWv4Qw/TUFKaMGsEdjzxeuGqUsyzdsY+lO/YBEB1hpX39KNbvS6BGcABZObkczyyeEPB0t+Dl\n4c7xzGzcDIPocCt7k8/84K5XLZjkY8fJOHXuxIgjrd4Tz+o98YWxtKxTg7iDh4kIrEp2bh4nsnKK\nlfewWPDysHAiKwfDMKhXLZgDR0oO23Oltpf3ou3lvQDYtm4Ny+bMpHHb9sTv3ol3pUqlzrVxLof2\n7eHHKR9w97MvU6Vq1X9+ggPFRkYSn5pCQtoRrH5Vmb1+HW8USaJX8fFhzuAzbd8D70/g0T5XExtZ\ng1W7drJ61y56NWtBVm4Om/fv55aCOclcKbZWFPHJSSSkpmD1D2D26pUMu3dg4X5fn0r8OWZc4eOB\no9/i8etvIrZWLY6fOsVjE8bxyLXX0cQBN3JERCoiRyY4hgFrDcOYDcQXbKsBXA684aiDWtzdefCJ\np3n5qcew2+30uLIPNaNqM/WjydSLjqZNh070vPIqRg0dzL233ICvnx/PvZ4fTp9rb2DsiKE82P82\nTNPk8t59iCr4whj28gscy8jA3d2dh554Gl8n3i1r2KwFW9atZsiggXh45i8Te9qbTz/K86PGA3Dz\nfQ8VLhMb06Q5sUVW3Vjz16LCyUWLeu2he8k6dYq8vDw2rVrOQy8PIcwJq8M0bNaSuLWref3hAQVL\n3z5RuG/4U48UroJyy8CHmTphLLk52cQ2bVG44siPn08hYd8ewCDIauXWB/Jnfd+1ZTO/TvsCi8WC\nm5sbtw58mMq+vhW2PuWBu8XCc3f05+FRb2O327m6YyfqRFTn/R++JzYqis5NmzF93hxWxMXhbrHg\nV7kyQ+7LvzhLP3aMh0e/hWG4YQ0I4I2BzluK+O+4Wyy8+MggHnjx+fylb3teQd1atZjw2ac0rF+f\nrm3bMfrDyZzKzOSpN/LbhzCrlXeHvMHlHTuxYv16rht4H4YB7Vu0pEvbtq6tj7s7zzzzDIMGDcJm\ns3H11VdTp04dJk2aRExMDJ07d2b8+PFkZmby/PPPAxAaGsrYsfk9ugYMGMC+ffvIzMykd+/evPLK\nK7QtB3V66fEnGfj0k9jtdq7tfSV1o2rz7scf0bBBNJd16MCo9ydyKjOTJ157BYAwaygT3xzp0rjP\nFtu0OVvXrmboow/g6enFrQ+d+Wy/9czjPPt2/rK8Nw54gK/eG1/QfjcjpqD9vuX+h/nhk4+w2224\ne3hw8/35ycVZ303j5InjfPvRBwBYLG489eYYJ9cOtiUkExMeyvPXdCMnz8Y3y85MjvhE786M/X0h\nnu7u3N2lFe5uFgwDdh1OZfnOMyt3NakVUS6GpwDsPJxK3WrBPNKzA7k2G7+sjivcN7BbGybPW46n\nu4Wb2zbF3eKGYRjsS05j9Z78iVYbhFvp1TiaSl6e3Nq+KUkZx/lyyVpXVSc/pibN2L5hLaOeegQP\nTy9uGHgmQT3+xad5tGD1nZlfT2X90sXk5mQzYtBAWnbpRvfrb+b3r6eSk5XFV+PzV+fwDwqm/1PP\nu6Qu7hYLz/S9nkc//AC73c5VrVpTp1oYH8yaSUz1SDo1bHTO597YrgNDvvmaW0aPBBP6tGxFvXDX\nz0nmbrHw7C2388i4sdjsdq5p34E64RG8/8tPxNasRee/WaFr+vx5xCcn89Fvv/LRb78CMPGxJwn0\nc941qohIeWM4cvxMwXCUnkAE+b02DgKzTNM8r1sd/6YHR3m2+/C5J8irqFy93Kf8s7bHy0+36bLg\nER7m6hDKXHagQ+dedjofF92Jd6Q5h123coQj/Llph6tDKHO+55jctKJqVOPia+u6Jcb/c6EKxHKR\nJhKqdOng6hDkv+fCJwaqQJ6a+stF9Zv2tNH9ri6X75tDZ8osSGRM+7syhmEsM03TtbcKRURERERE\nRKRCKw+33y+uWy4iIiIiIiIi4nTlIcFxUXbZERERERERERHnKQ8JDhERERERERGR/4tD5+A4T+Vy\nchIRERERERGR/4cjF/WQkspDD45+rg5ARERERERERCo2hyU4DMNIMwzjI8MwuhmGcc5eGqZpbnZU\nDCIiIiIiIiLy3+DIHhwpwHpgCHDQMIxxhmG0ceDxREREREREROQ/ypFzcJw0TXMCMMEwjBrALcB7\nhmH4A9NM03zRgccWERERERERcSnNweFcjuzBUTgsxTTNA6ZpvmWaZjOgF5DtwOOKiIiIiIiIyH+M\nI3twzC9to2ma24HBDjyuiIiIiIiIiPzHOKwHh2maT55rn2EYLR11XBERERERERH573FkD45iDMOI\nJX8ejluBDKCFs44tIiIiIiIi4mx2zcHhVA5NcBiGUZP8hMatQB5QE2hhmuY+Rx5XRERERERERP5b\nHDZExTCMpcDvgAdwg2mazYHjSm6IiIiIiIiISFlz5CoqKYAvEAqEFGxT/xwRERERERERKXMOG6Ji\nmuY1hmFUBa4HBhuGURfwNwyjlWmaKx11XBEREREREZHywNQcHE7l0Dk4TNPMAKYAUwzDCAVuBt4x\nDCPSNM1IRx5bRERERERERP47HDlEpRjTNJNM0xxvmmY7oIOzjisiIiIiIiIiFz+H9eAwDGMGfz/n\nxtWOOraIiIiIiIiI/Lc4cojKKAe+toiIiIiIiEi5ZtcUHE7lyElGF57+2zCMkIJtKY46noiIiIiI\niIj8dzl0Dg7DMF4zDCMV2AbsMAwjxTCMVx15TBERERERERH573FYgsMwjCfIn0y0pWmaQaZpBgCt\ngfYF+0REREREREREyoQje3D0B241TXPv6Q2mae4B7ijYJyIiIiIiIiJSJhw5yaiHaZqpZ280TTPF\nMAwPBx5XRERERERExOXspt3VIfynOLIHR86/3CciIiIiIiIickEc2YOjsWEYx0rZbgDe5/MCAVV8\nyjYiF1u9+4CrQyhzx7OyXR1Cmbq0ZrirQyhz9ktiXB1CmcoGVscnuzqMMtUoyJFNsfNlVa5CcsZx\nV4dRpuJTj7o6hDJVL8xK/JF0V4dRpjbuT3B1CGVq4/4ELr802tVhlCnP6hGuDqHMeUReXHU6uXgZ\nGT/McHUYZarqdVe5OgQRcSJHLhNrcdRri8h/18WW3LgYXWzJjYvRxZbcuBhdbMmNi9HFltwQEbkY\nXFy3DUVERERERETKCdN0dQT/LY6cg0NERERERERExCmU4BARERERERGRCk8JDhERERERERGp8DQH\nh4iIiIiIiIgDmJqEw6nUg0NEREREREREKjwlOERERERERESkwlOCQ0REREREREQqPM3BISIiIiIi\nIuIAds3B4VTqwSEiIiIiIiIiFZ4SHCIiIiIiIiJS4SnBISIiIiIiIiIVnhIcIiIiIiIiIlLhaZJR\nEREREREREQcwNcmoU6kHh4iIiIiIiIhUeEpwiIiIiIiIiEiFpwSHiIiIiIiIiFR4moNDRERERERE\nxAE0B4dzqQeHiIiIiIiIiFR4SnCIiIiIiIiISIWnBIeIiIiIiIiIVHiag0NERERERETEAeyagsOp\n1INDRERERERERCo8JThEREREREREpMJTgkNEREREREREKjzNwSEiIiIiIiLiAKapSTic6aJPcCz7\n6y/eeXskNrudq/teS/977i22f92aNbwz6i1279zJkBEjuezyywv3HU5MZMSQ10lKSsLAYMyECYSF\nRzi7CiVcfml96oQGk2ezMWPNFpIyjhfb725x47pWlxJQ2Qe7abLzcCoL4nYB4OfjTZ9msVTy8iAz\nJ49fVm/meFa2K6pRzFXNYmkQbiXHZuO75Rs4lH6sRJm7u7TE19sbNzeDfclp/LxmM6YJ3RrVo2Wd\nGpzMzq/H7A3b2Z6Y4uwqFDJNk5lffcbOjevw8PSi770PEl4rqkS5ed9PY8Nfi8g8dZKXJn1WuH3d\nkgXMmf4lvgGBALTq1pPmnS9zWvylWbp0KaNGjcJut9O3b1/uuuuuYvvXrl3L6NGj2bVrF8OGDaN7\n9+4ArF69mjFjxhSW27dvH8OHD6dLly5OjD6faZp88/EHbF6zCk8vL+4c9CQ16tQtUW7/7p18Nn4M\nuTk5NGrekpvuvR/DMAr3z/7pe3747GNGffY1VfyqsmLhfGb/+C0AXt4+3Hb/w1SPqu20ep22fOlf\njBv1FnabnT59r6Xf3fcU279+7RrGj3qb3bt28vrwN+na/Uxb16llM2rXzf+3CK0Wxsix45wa+2lr\nV65gyoRx2O12uvfuw3W33VFsf25ODuPeHMaeHdvx9fPjqVcHY60WVrg/JSmJx+7ux0133k3fm28F\nYMa305n7+69gGNSMqs0jz72Ap6eXU+t1mmmazP/2S/bGbcDdw5Mr+t9HaI1axcrk5mQz48OJHE1N\nxs3NoPYlTenU9yYADu7cxvzvviIlIZ4+9zxE/WYtXVCLkno3jaF+tRBybTZ+WLmJxKMl2+/+HVvg\n6+OFm2GwLzWdX9fGFbbf0eFWTBNOZufww8qNLv9Ouqdra5pGVScnN48Js5awN/lIiTKDb7wC/8qV\nyMnLA+CN72dzLDOLmIhQ7u7SmpohAYz9bQHLd+53dvglnDnvNuLh6UnPfgNKPe9+/ajgvDPcqH1J\nEzoWnnfbWfB9/nl35d0Puvy8+2v9et76/BPsdjvXdu3GPdf0Lbb/2zmzmT5nFm5ublTy9uaVAfdT\np3p1AHbs38/Qjydz4lQmbm4GXw4dgZenpyuqUczi5ct5c9w72Ox2ru9zFff161ds/6fTpvH9rzNw\nt1gI8Pdn6AsvEl6tGocOH+axF1/EZreRl5fH7TfcwM19r3VRLUq3bPs2Rv/6M3a7nWtatubOLsWv\nZ35ds4rxM38lxK8qADe2bU/flq1dEaqIXCQu6gSHzWZj9JvDGff+B1hDQ7nn9tvo2LkLUXXqFJap\nFlaNVwa/wZeff1bi+UNeeZm7BgygVZu2nDp1CrciP3JcpU5oEIGVKzFpzlLCA/y4okk0ny1cVaLc\nip372Z+ajpthcHuHZtQODWJP0hG6XVKPTfGJbDqQSM3gALo0rMuMNXEuqMkZDcJCCPKtzKhfFxAZ\n5E/fFo14b87SEuW+WrKO7IKLyds7NOOSyDA2HkgE4K/te1m8bY9T4z6XnRvXk5aUyKNvvsPBPbv4\nbepH3PfKsBLl6jdpTqtuPRn//OMl9jVs1ZYr+91TYrsr2Gw2Ro4cycSJp4SaaQAAIABJREFUEwkN\nDaV///506tSJ2rXP/IivVq0ar7/+OlOnTi323BYtWvDVV18BkJGRwbXXXkubNm2cGv9pm9euJvlQ\nAkPe+4i9O7bz1QcTeP6td0qU+2rSRO548FGiGkQz4Y1XiVu7mkbN8y/o01JT2LZhHYEhIYXlg0ND\neXLoSCpX8WXzmlV88f74Ul/XkWw2G2PeHMHY9yZhDQ1lQL/b6dC5M1G1z7R1odWq8eLgIXw99fMS\nz/fy8uLTr79xZsgl2Gw2Phw3htfeHktQSAjPPngfLdu1J7JIcnDuzN+o4uvLe19MY8mfc/l88iSe\nfnVw4f5P3nuXpq3OXBgfSUnhtx+/Z9wnU/Hy8mLU4FdZ8uc8Lruit1PrdtreuI2kJx/mntffInHf\nbuZO+4zbn32tRLkW3XtRo0EMtrw8vh03kr1xG4hq2BjfwCCu6DeA1XNnuiD60tWrFkJQlcq8M3MR\n1QP9uap5QybPW1ai3PRl6wvb71vaNaVR9TA2xSeyZNte5m3eCUCbejVd/p3UNKo6Yf5+DJryPfXC\nQhjYrS0vfP1rqWXHz1zI7qTiyY/U4yeZOGsxV7do5Ixwz8veuI0cTUnintdHkrhvN/Omfc5tz75a\nolzz7r2oUT//vPtu/FvsjdtIVMNL8Q0MpGc5Oe9sdjsjPvmYSS++TGhQELe/9AKdm7coTGAA9Grf\ngRsv7wHAgtWrGT31M9574SXybDZemvguQx9+hAY1a3H0+HHc3V1/GWyz2Rg2ZjQfjn2HUKuVmwcM\noGuHDtSNOtP2xdSvxzcffYyPtzfTfvyR0e9NZPSQNwgOCuLLSZPw9PTk5KlT9O3fj64dOmANDvmb\nIzqPzW7nrV9+ZMK9A7H6VeXOiePoGBNL7dBqxcpdfkljnrnmOhdFKSIXm4t6Do4tmzdTPTKSiOrV\n8fDwoHvPK1i0YEGxMmHhEdStXx83t+L/FHt378Zmy6NVm7YAVKpUCW8fH2eFfk71w0LYFJ//o/5Q\n+jG8Pdyp7FX87kOezc7+1HQA7KbJ4aPH8fPJv2MZ7FuZfclpAOxPTad+mOu/BGOqh7JuXwIA8UeO\n4u3pga93yTuspy+O3QwDi5sb5bWz1/Z1q2ncrhOGYRBZpx5Zp05x/Gh6iXKRderh6x/ggggvTFxc\nHJGRkVQv+Bz16NGDhQsXFisTHh5OvXr1SnyOipo3bx7t2rXD29vb0SGXauPK5bTp2g3DMKjdIJrM\nkyfJSEsrViYjLY2szFPUjo7BMAzadO3GhpXLC/d/O2Uy1/W/BziT7KwTHUvlKr4ARDWIJv1Iybu9\njrY17qy2rkdPlpTW1tWrXy4StaXZtW0rYRERVAsPx8PDgw6XdWPl0iXFyqz6azFde1wBQNvOXdi0\ndk1ht88VSxYRGhZWLCEC+T8ecrKzsdnyyM7OIjAo2DkVKsXujWuJbd0ewzAIj6pL9qlTnMg4WqyM\nh6cXNRrEAGBxd8caWZPj6fntR9WgEEKq18D4m8+Zs8VEWFlf0H4fTDuKj4c7Vc6r/TaLbQfwtFhw\ndcPesk4NFmzJ7/G4MzGFSl6e+Fc+/+/+lGMn2J+ajr0cdUfevXFd8fMu8xznXf2zzruj+e1j1aAQ\nQiIii/Vkc5XNu3YRWa0a1UND8XB3p2fbdixYXfwmT5VKlQr/zszOKox72cYN1KtRgwY1awHg7+uL\npRx8ljZt3Upk9epERkTg6eFB7+7dmL9kcbEyrZs1x6fgu7Nxw4YcTsnvperp4YFnQQ+U3Nxc7OVs\nLcq4+ANUDwoiIjAID3d3ejRuwqKtrr2pJiIXP4emro38b5VWQAT5ly2HgJWmkwYipSQnYy2SJbaG\nWonbvOm8nnvgwH6q+Pry/FNPcCghgZat2/DQo49hsVgcFe55qeLjxbHMrMLHxzOz8fXx4mR2Tqnl\nvTzcqRsWzKrd8QAkZ5wgOsLKqt3xNAgPwcvDHR9PDzJzcp0Sf2mq+nhz9GRm4eOMU1n4VfIutZvy\n3V1aERnkz/ZDyWwuSPQAtK1Xk6ZRESSkZfDb2i1k5eaVeK6zHDuahl9gUOFjv4BAjqWnXVAyY+ua\nlezfsY2gatW44pb+VHXhj7Lk5GRCQ0MLH1utVjZv3nzBrzN79mxuv/32sgztghw9kkpA0JmEnn9Q\nMEfTUqkaGHimTFoqAUX+rf2Dgjl6JBWADSuX4x8Y9LfDT/6aO5tGzZo7IPq/d3ZbFxIaypbzbOsA\ncnJyuPeO27BYLNxx19106ur8IVFHUlMIsloLHwcFh7Bz69azyqQWlrFY3KlUuTLHj2Xg6enFj9O+\n4rW3x/Dz9GlnXiMkhGtuuoX7b7kBTy9PGrdoRZOWrZxToVKcOJqOb8CZtsE3IJATR9OpUtW/1PJZ\np06yZ9N6ml3Ww1khXjA/H28yinwnZWRm4efjxYlS2u/+nVpQPdCfnYkpxB08XLi9e6N6NKkVQVZu\nHlMWrHRK3OcSVKUSR46fLHycduIkQVUqFfuOOu2hnh2x2+2s2Lmf71ZscGaYF+RERjq+/mfauSr+\nAed13jXtenmp+10pOT2NakFnPkOhQUFs2rWzRLlps//gi99+Izcvj8kv5/dW2Z+YiGEYPDhiGOnH\njtGzbTvuvvoap8V+LkkpKYQVaftCQ6xs3HLuJMD3v86gY+szPSETk5J46NlnOHDwIE899HC56b0B\nkHIsg9Ai55nVz5+4+JLDtv6M28S6fXupERzME1deQ6h/6eemiMj5cFiCwzCMHsB7wE4goWBzdaCu\nYRgPmaY521HHPs0s5VaQwfndgbDl2diwbh2ffT2d0GrVeOW5Z/ntl5+5+lrXdqE73/gBDMOgb4tG\nrN4dz9FT+Rdn8zbvoGfjaC6pEU58ajrHMrOw2+2OCvd8Iy2x5Vw5sE8WrMTdzY2b2zWhTmgwuw6n\nsmLXfv6M2wkmXH5pA65sFsv3KzY6OuhzKyX0C7nz1aBJcy5p3R53Dw9WzZ/Djx+9z13PvVKGAf7/\nLvROXmpqKrt27aJt27YOiuiflXpGnVWPUk87wyAnO4uZ303jsddKDjU6bfumDSydO5unh7/9f8X5\nb5T2ebmQ9+j732YSHGIl4eBBHnvgPurUrUdEZGRZhvjPSv23P7tM6W36tE+ncNUNN+HjU6nYvhPH\nj7PyryW8/9V0KlfxZdTgV1g4ZxadL+9ZdnFfgNLOr3O9TXabjd+mvE/TrpfjH2wtvVAF8/mi1bi7\nuXFDm8bUtgYVDu+Yu3knczfvpFN0bdrUrcGfBXNGlRelvW/jZi4i7cQpvD3ceeaqy+gcU4eFW3c7\nP7jzcQHtg91m4/dPJtG0S/dyed6V2taVcg1xS48ruKXHFfz+1xI+/PF7hj70CDa7jXXbt/Hl0BF4\ne3lx/7AhxNauTetGlzgj9HO7gPdnxqxZxG3bxmcTJhZuCwsN5cfPPic5NYVBL7xAj65dCS6SuHel\n8/ne7RAdS4/GTfF0d+f7FUt5/duvef++B50Sn4iz2F3dPfE/xpE9OMYB3U3T3Fd0o2EYUcDvQExp\nTzIMYyAwEGDMuxO486xJQS+E1RpKctKZu0TJSckEh5zfF7Y1NJT6DaKJKBjX2alrVzZvOv87omWp\neVR1mtTKn9z00NFj+Pl4AxkA+Pp4cTyz9AnZejeNIe3kqcLeGwAnsnIKf/x7WCw0iLCSnWdzbAVK\n0aZeTVrWyf8BdfBIBv6VfQqH1VSt5H3OOgHk2e1sTUgiNiKUXYdTOZF1pvfKyt0HuLOT8ydAWzlv\nFmsW/glARFQdjqWdGaZwob03KhUMdwBo3rkbc7/9quwC/ResVitJSUmFj5OTkwkJubA7RHPmzKFr\n165OH++84PcZLJkzC4CadeuRfuTM5LNHj6TiX+RuOkBAUDDpBT02CssEBpFyOJEjSUm88cTDhduH\nPfUoz781lqoBgRzct5epE8cx6JUhVPHzc0LNirOGFm/rUpKSCL6Au3in28WI6tVp2rwFO7Zvc3qC\nIygkhCPJyYWPj6SmEBgcXGqZ4BArNlsep06epIqfHzu3bWHZogV8/sH7nDxxAjc3A09PT/wDAgkN\nC6NqweevdcfObIvb7NQEx7qFc9n0V/6Qrmo1oziefqZtOJ6eRuWqpbcNs7/6hABrNZpf5ppkzN9p\nVbcGLaLyz4+E9Ayq+pwZdlbVx5tj/9B+b0tIJjo8tMT8FRsOHKJfxxZOT3Bc0TiabpfUB2B3UipB\nvpUL9wVWqUzayVMlnpN2In9bVm4ei7ftoW5YSLlKcKwvct6F1owqHG4C+T2JKp+j98acrz7FPySU\nZuXwvAMIDQzicJFhgElHjhAScO7v1yvatmP4xx8WPrd5TCwBBW10hyZN2bp3r8sTHKFWK4lF2r6k\nlGSswSV7bS5btYrJn3/GpxMmFg5LKcoaHELdqCjWbNhAz65dHRrz+bL6VSWpyHCo5GNHCTnrO9K/\n8pnPW9+WbZgw83enxSciFydH/tpwBw6Wsj0B8DjXk0zTnAxMBkg7lfV/pbtiGjYk/sABDiUcJMQa\nytxZfzB4xIjzfu7xY8dIT0sjIDCQNatWEh3b8P8J519bs/cga/bm/1PWCQ2iRe1IthxMIjzAj+zc\nvFKHp3SOqYOXuzu/rd1SbHvR4SjtGtRi4/5Djq9AKZbv3F84u3yDcCtt69Vkw/5DRAb5k5WbV2J4\niqe7BS93d45nZeNmGDQIs7IvJf+Czdfbq7B8w+rVSqwq4wytuvWkVbf8C8IdG9ayct4sGrVux8E9\nu/DyqXRBCY7jR9MLy29ft5rgMNeu3BMbG0t8fDwJCQlYrVZmz57N0KFDL+g1Zs2axSOPPOKgCM+t\nS++r6NL7KgA2rV7Jgt9n0KJDZ/bu2I53pcrFhqcAVA0MxNvHhz3btxFVvwHL58+jy5VXE1Ezirc/\n+7qw3IsD7+LFUeOo4leVtJRkPhg5lLsff5rQiOq4QnRsQ+LjD3AoIYEQq5W5s2fx2rDh5/XcY8eO\n4e3tjaenJ0fT09m0YT233XmXYwMuRd3oaBITDpKUeIjA4BCW/DmPJ14qPgFny3YdmD/7Dxo0bMSy\nhQu4pGkzDMNg2LgzdzOnfToFbx8fel97PTu2xrFjSxzZWVl4enmxae0a6tRv4NR6Ne3cnaad81cV\n2rNpPesWziW6RRsS9+3Gy8en1GECS375jpzMTHreXj4mGj7byl0HWLnrAJA/L1TrujXZFJ9I9cD8\n9vvs4Sme7hY83d05UdB+1w8LYX9qfvsdWKVSYbIgOjyU1GMncbY/Nmzjjw3bAGgWVZ1eTWL4a/te\n6oWFcConp8TwFDfDoLKXJ8ezsrG4GTSvHcmmA675Lj2XJp270+T0ebd5PesXzqNB89Yk7tuN5znO\nu79mfE921il63H63s8M9bw3r1OHA4UQSkpOxBgYya9lShj/yaLEy+xMTqRmWv7rS4nVrqVGw0lK7\nSxvz6YxfyMzOxsPdnTVbt3J7ryudXoezNYqO5kD8QQ4eOvS/9u47Popq/eP458kmgdDT6b03AQFR\nlKKI9WK9CldEbNgbyrV7Uezl5xVFERUVFQXLtWFBEAtIUToRBAWkE0Lvaef3x25CAmnAlmT5vl+v\nfbGZOTvnPMzu7Owz55whKTGRryZN5pn/5D/2LV66lIefeZpXn/s/4vMkdDakplKtalXKlyvH9h07\nmLtgIVdc2jfYIRSqZe06rE5LY+2WzSRVqcrE+fMY1jf/UNW0HTtI8CU9flqcQoOk0tdzSETKlkAm\nOEYDv5rZB0BOF4I6QF/gjQDWmysyMpI7776X22+8gezsbM4973waNmrMqJdH0KJlK07p0YPfUxZx\nz+A72LljB1N/+pHXR77M2I//h8fj4ZbBg7nl+kE452jeoiXnXXhRMJpdpL82bqZx9QRuOP0kMrKy\n+XLOgXGaV/c8gTemzKRy+XJ0bd6AtJ27ubqn944Cvy1fzfy/1+XeOcXhWJ22jW99J3Wh9Me6VJrV\nSOSuc3uQkZXFR3mGl9xy5sm8+M1UoiM9DOjWEY8ngggz/tq4mZm+E+yz2jWnRmwVHLB1114+/TU0\nPW1yNGnbnmUL5jH87tuIii7HeVdfn7vulYfu5oZHngJg4vj3WDhjGhnp6Tw3+EY6dOtJz/P/yczv\nvuGPebOJ8EQQU7ES518T2q6akZGRDBkyhFtuuYWsrCz69OlDo0aNGDlyJC1atKB79+6kpKQwZMgQ\nduzYwc8//8yoUaMYP957V45169axceNGOnToENI4Wh/fiUWzf+XBG6723Sb2jtx1j95xMw88/xIA\n/7ruJt4e/jzp6ftp1aEjrTt0LHK7E8aPZffOnbz/6ssARHgiuO/Z4YELpACRkZEM/vc9DL75BrKz\nsjnnvPNo2Kgxr7/yMs1btuTk7j1YnLKI++4azM4dO5j280+88eorvPvhJ/y9YjnPPPYoFhGBy86m\n/8Cr8t19JVg8nkiuueUOHrn7TrKzsjntrHOo26AB77/5Oo2aNqdz15M57exzeOHxR7mxf18qVa7C\n4AeHFrnNpi1acWL3Htx13dVEeDw0bNyE3uf2CU5ABWjQ+jiWpyzgjf8MISq6HGdcfk3uujGPP8iA\n+4axc+sWZn7zBXHJNXjnSe+PnHbdT6Nt1x5sWLmcz0YNZ9+e3fy1cC6/TPiEgQ+WLGkfKEvXb6Jp\njUTuOLs7GZlZfPLrgeP3jad35eXvphHl8XDZyR2IjPAev5enbs7tWdi7bTMSKlfEOce2Pfv4fPbh\nz+/jT3NWrKFDg9q8dNVF7M/M4uVvD0z2+Ez/Pgx593OiPB4euKh3bjwLVq1n0sKlADRKTuDffU6l\nYvloOjasw6UntueOMZ+GKhwAGrQ6jhUpCxg99N9ERpfjjP4Hesa+8/iDXH7Q++7d3PddL9p07c6G\nv5fz+agXvXNzLJrH9An/44oHS5ZA9bdIj4d7Bl7FDU885r3taI+eNK5Th5c/HEfLBo3o0bEjH0z8\nhpkLFxIZ6aFKxUo8coO3512VSpW4/OxzuOz+ezEzTm7Xnm4h/l4C7/H7/sF3MGjwYLKzs7jgnHNp\n3LAhL77+Gq2aN+fUk0/h2REj2LN3L3c8+ADgHZYy4qmnWf73Sp556SW84/kcA/v1o2mj4B+/CxPp\n8TCkzwXcOvo1sp3jHx070Si5Oq9+9w0tatWhW8tWjPtlKj8tTsETEUHVChV46OLSk6ARkbLJAjnf\np5m1AM7DO8mo4e3R8blz7vciX+hztD04SpuR304tvlAZU9BEoGVZ23o1Q90Evzu3TeNQN8Gvflud\nWnyhMqZ13fB636WGoBdVoE0rJbeh9pfVmw+9s1NZtzjPxKXh4PS2zUPdBL8bEFeh+EJlSFSd0Paw\nDITdPx96m+eyruqF/wh1E6R4ob9NUwANGPFeWP2mzTHmpstK5X4L6IB459xiYHFRZczsY+dc6LtG\niIiIiIiIiEiZFfobgEPh91wUERERERERESmB0pDgCMsuOyIiIiIiIiISPMG9Z6OIiIiIiIjIMSI7\nW9fzg6k09OAolZOTiIiIiIiIiEjZEdQEh5klFLD47mC2QURERERERETCT8ASHGZ2lpmtMLOpZtbe\nzFKAmWa2xsxOyynnnJsYqDaIiIiIiIiIyLEhkHNwPAGcDVQDJgHnOOdmmFkL4D2gQwDrFhERERER\nEQkp5zQHRzAFMsGR7ZxbDGBme5xzMwCcc4vNrDTM/SEiIiIiIiIiYSKQCY5tZnYdUAXYamZ3AOOB\nXsCuANYrIiIiIiIiIseYQPakuALvMJSGQG/fsm+BS4BrAliviIiIiIiIiBxjAtaDwzm3Grguz6Ln\nfQ/MrFOg6hURERERERGRY08gh6jkY2Ytgb5AP2A70DFYdYuIiIiIiIgEW7bmGA2qgCY4zKwe3oRG\nPyATqAd0dM6tDGS9IiIiIiIiInJsCdgcHGb2C/AVEAVc7Jw7Htip5IaIiIiIiIiI+FsgJxndBFQG\nkoFE3zJ10BERERERERERvwvkJKPnmVlV4CLgYTNrDFQzs87OuVmBqldERERERESkNHBO1/iDKaBz\ncDjntgOjgdFmlgxcCvzXzOo45+oEsm4REREREREROXYEcohKPs65jc654c65k4CTg1WviIiIiIiI\niIS/gPXgMLMvKHrOjT6BqltEREREREREji2BHKLybAC3LSIiIiIiIlKqOd1nI6gCOcnojznPzSzR\nt2xToOoTERERERERkWNXQOfgMLP/mFkasARYamabzOyhQNYpIiIiIiIiIseegCU4zOwOvJOJdnLO\nxTvnYoETgK6+dSIiIiIiIiIifhHIOTgGAKc759JyFjjnlptZf2Ai8HwA6xYREREREREJqWynOTiC\nKZBDVKLyJjdy+ObhiApgvSIiIiIiIiJyjAlkgiP9CNeJiIiIiIiIiByWQA5ROc7MdhSw3IDyJdnA\n7W9+7N8Whdio0zqFugl+t3f2vFA3wa/W1q0Z6ib43Sdz/wh1E/yqXmJcqJvgd5/MCK/PUeqOXaFu\ngt/d3aFZqJvgV/s7twp1E/xuz/BXQ90Ev6pU0RPqJvjdy+u2hroJfjWoScNQN8HvFrZqE+om+NWY\nH2fBqPGhbobfjRp0SaibIFJqBfI2seH3zSwiIiIiIiIipVIge3CIiIiIiIiIHLOcJhkNqkDOwSEi\nIiIiIiIiEhRKcIiIiIiIiIhImacEh4iIiIiIiIiUeZqDQ0RERERERCQAsjUFR1CpB4eIiIiIiIiI\nlHlKcIiIiIiIiIhImacEh4iIiIiIiIiUeZqDQ0RERERERCQAnNMkHMGkHhwiIiIiIiIiUuYpwSEi\nIiIiIiIiZZ4SHCIiIiIiIiJS5mkODhEREREREZEA0BwcwaUeHCIiIiIiIiJS5inBISIiIiIiIiJl\nnhIcIiIiIiIiIlLmKcEhIiIiIiIiImWeJhkVERERERERCYBsTTIaVOrBISIiIiIiIiJlnhIcIiIi\nIiIiIlLmKcEhIiIiIiIiImWe5uAQERERERERCQDNwRFc6sEhIiIiIiIiImWeEhwiIiIiIiIiUuYp\nwSEiIiIiIiIiZZ7m4BAREREREREJAKc5OILqmEhw9D/leI6rV4v9GZm8Nnk6f6dtLbTs7Wd3J6lK\nJe77YAIAN/U+meqxlQGoEB3NnvR0Hhz3dVDaXZBpc2bz1GuvkZ2dzQWnn87VF/8z3/rxX3/NuK8n\n4ImIIKZ8eR668WYa1a3L9HlzeWHM22RkZhIVGckdA6/khLbHhSiK/Kb/uYznv51AdrajT/vjGXBy\nt3zrv5w3h5cmfUti5SoAXNzpBM7r0DF3/e79++j78nC6N2/JXWedG9S255g7ayajRwwnOzub084+\nhwv79c+3PiM9neFPPcbypUupXKUKgx8cSlL1GrnrN23cyO1XDeCSKwZy3iX9cpdnZWVx942DiItP\n4L7HnwpaPAdzzvHdB2P4a+F8IqOj+ceV11G9XoNDyv3wv/EsnP4z+/bsZshLo3OXb9+cxhdvjmT/\nnj1kZ2fT86K+NG7TLpgh4Jxj3OsjWTT7V6LLlWPgrXdSt1HjQ8r9/ecy3hr+f2Sk76f18Z249Jrr\nMTM+e28M82dNxyyCylWrMvC2O6kWF8/uXTsZ8+LzbNqwnqjoaAbcfAe16tUPamw58U358D1WpCwg\nKjqaMy6/huS6+duRkb6fL18fwba0VCIsgoZt2nHK+ZcAsGbZH/zw8Vg2rV3NOVfeQNMOnYIeQ0HO\naNuMxtUTyMjK4vPZKWzYtvOQMv26tqdyuXJERBir0rbx9bzFOKBFrSS6t2hEQuWKvDFlFuu37Qh+\nAHlM/fVXnhr5MllZ2Vx41llcc2nffOvf/vgjPvnmazweD3FVq/LI4LuomZwMwP+9/ho/zZxJtsvm\nxA7Hc88NN2JmoQijUL/88gvPPvss2dnZnH/++QwcODDf+nfffZfPPvsMj8dDbGwsDz30EDVq1Ch4\nYyES3bA+lXufCmbsnbeQPdNnHVKmXItmVDrlJMCRsXETOz7zni9UOrUb5Ro3BDPSV/zNzonfB7n1\nBZu2YAHPjn2HrOxsLujWgyvP/Ue+9R99P5nx308iwiKoUL48Dwy8ioa1apGRmcmjb41m8coVmBlD\n/nU5HVu0CFEUBzjn+OXTcaxevIjI6Gh69B1IQu26+cpkpqfz3ZhX2ZG2iYiICOq2bMsJ516Yu/6v\neb8xe+KXGBBXszan9b8myFHkV9xnZ86cOTz33HP8+eefPPbYY/Tq1St33fDhw5k6dSoA11xzDb17\n9w5m03M553j/tVdY+NssosuV56rb76ReoyaHlFv55zJGv/AsGfv306ZjZ/pdewNmxvg3X2P+rBlE\nRkaRWKMGV916JxUqVSJt4wYeuOlaqteqDUDDZs0ZcONtwQ4PgEtPak+bOtVJz8zirR9msWrztkLL\n3nRGVxIqV+Lhj77Nt/z0ts34Z5fjGPz2p+zanx7oJosck8I+wdG2Xk2Sq1ZhyLuf0yg5noE9Oh9y\nsMnRsWEd9mdk5ls2YuLU3Of9unZgTwgPRllZWTz+6khefXgYyfHx/OuuwfTofAKN6h74Yj+7e3cu\nOessAH6YOZNnR7/BK0MfplqVKgy//0GS4uNZ9vff3DD0ISa9+XaoQsmVlZ3Ns19/wfD+A0mqUoUr\nXx/JKc2a0yAxKV+5Xq3aFJq8eHXKZNqH4AdljqysLF4b/jwPPf1/xCcmcveNg+h04snUqX+gTZO/\nnkClSpUZ8c77TP1+Mu+8NpI7H3w4d/2br7xI+84nHLLtCZ98RK269di7e3cwQinUX4vmsyV1A9c/\n9hzrlv/JN++9ycD7HjmkXJO27enY83ReeeDOfMunTfiUFh27cHyPXmxat4bxw5+h8ZMvBKv5ACya\n/Sup69cx7JU3WLF0Ce+NfIl7n/nvIeXGvvoS/W+8lYbNmvPisIdImfMbrY/vRO8LLuK8ywYA8P2X\nnzFh3Fguu+EWvv5oHLUbNOKGex9iw5rVjH11BIOHPRnU2ABWpCwDsWxTAAAgAElEQVRg26aNXDX0\nKdav/IvJH4zhX/9+6JByx/c6i7pNW5CVmclHw59mRcoCGrRqS+W4OM64/Bp+mxS6BO7BGicnEFep\nAiMmTqNWbFXObteC0T8c+oPz45kLSM/MAuDiE9rSsnYyKWs2smnHbj6cMZ+z24f+R1lWVhaPjXiR\nUU88RfWEBPrecjM9u5xIo3r1csu0aNSYD14cQUz58oz74gv+7/XXePb+B5iXksLclEV8PPJVAAbc\neQe/LVhAp+NKR5IavPE99dRTjBgxguTkZAYMGEC3bt1o2LBhbpnmzZtz8cUXU758eT766COGDx/O\nE088EcJWH8SMymf2YtvYD8nasZO4q/qzf9lfZKVtzi3iia1GxZM6s2XMWNy+/ViFCgBE1apJVO1a\nbH7N+70aO6AfUXXrkLFqdUhCyZGVnc1T77zNy0PuJjkujv4PP0T39h1oWKtWbpkzTzyJi089DYAf\n587hufffY8Rd/+aTH6YAMP7RJ9iyYzs3P/cs7/7nYSIiQju6efWSRexIS+XSe4eRumoFP3/8Hhfc\ndu8h5Y7r0ZuajZuRlZnJhJHPs2rxIuq2aM32TRuZN/kbzrt5COUqVGTvztAmPkvy2alevTpDhw7l\nnXfeyffaqVOnsmTJEsaOHUtGRgaDBg3ipJNOolKlSsEOg4Wzf2XjurU8/uqbLP9jCe+88iIPPDv8\nkHLvvjKcATfdRqNmLfjvww+waM5vtDm+Ey3bdeCiAVfh8Xj48K3XmfDRB/xzoDfxlFi9BkNfeCXY\nIeXTuk51kqtU4oFxX9MgKY7LTjmeJz6dXGDZ9vVrse+g3xMAsRVjaFkrmc07Q3tOJxLuwn4Ojg4N\najPtj+UA/LVxMxWio6laofwh5cpFRXLmcc357LeFhW6rc6O6zFj2d8DaWpxFy5ZRp3oNalevTlRU\nFGee0o0fZs3MV6aS72QLYO/+feRc4GvRsBFJ8fEANK5bl/SMDNIzMoLW9sL8vnYNtWPjqRUbR5Qn\nktNbteGnPxaX+PVL1q1ly+5ddG546JX4YPlzyWKq16pF9Zo1iYqK4uSep/HrL1PzlZn1y1R69D4T\ngBO7d2fhnDm53dVmTv2Z5Bo18yVEADZvSmXOzOn0OvucoMRRlKXzZtOmyymYGbUaNWHfnj3s2nZo\nT6hajZpQqVrsoRswI33vXgD2791bcJkAmz9rBl16nIaZ0bBZC/bu3sX2LVvyldm+ZQt79+yhUfMW\nmBldepzGvJnTAYipUDG33P59+8D32Vq/ehUtfL2hqteuw+bUjewo4P8m0P5aMJeWJ3TFzKjZoDH7\n9+5h1/b8V5eiostRt6n3x74nMpKkOvXYuc37f1A1PpHEWnVKVa+ApjUTWbBqPQBrt26nfFQklcpH\nH1IuJ7kRYYYnIoKcnqBpO3ezedeeoLW3KAv/+IO6NWtSp0YNoqKiOKtHD6ZM/yVfmc7t2hFT3vv9\n1LZFCzambfKuMGN/egYZmZmkZ2SQmZlJfGy1YIdQpJSUFOrUqUPt2rWJioqid+/e/Pjjj/nKdOzY\nkfK++Fq3bs3GjRtD0dRCRdWsTtaWrWRt2w7Z2ez7fQnlmjbKVyamfVv2zp6H27cfALcn5/3lsEgP\neLwP80SQHeLENMCi5X9ROzmZ2klJREVGcsYJXfhh7ux8ZSrFxOQ+37t/f+4xYPm6tXRu2QqAuCpV\nqVyhAr+vXBG8xhdi5aL5NDm+C2ZGcr2GpO/dy54d2/OViYyOpmbjZoD3WJdQuy67t3uPy4tnTKVV\n1x6U8x3TY3y9Q0OlJJ+dmjVr0qRJk0OSS8uXL6dDhw5ERkYSExNDkyZNmD59ejCbn2vezOmc1LMX\nZkaj5i3Ys3s327Zszldm25bN7N2zh8bNW2JmnNSzF3NneI+Drdsfj8fjAaBRsxZs3ZwW9BiK0q5+\nLaYvWwnAitQtxERHUTWmgN8TkZGc3rYpX8059Fz2khPb8fHM+WiwgkhgBTTBYWZVzexSMxtsZnf4\nngf1rCyuYgW25DnB3bJ7D3EVKxxS7qLObfl63uLcE+WDNauRxI69+9i4/dDu0cGSunkz1RMScv9O\nio9n4+bNh5T7YMIEzrnuWp5/6y3uvva6Q9ZP+uUXmjdoSHRUVEDbWxKbdu4gqWrV3L+TqlRl085D\n/4+nLE7hspEvce+H77Nxu/dEJttl88J333BLrzOD1t6CbElLIyFPj5O4xEQ25/wwyVsmyVvG44mk\nQsWK7NyxnX179/LpB2O5ZMDAQ7Y7esSLXD7oBsxCn4fctXULVeLic/+uHBvHzsP4Ed/tHxeyaOZU\nXhxyM+OHP03vflcEoplF2rZlM3F5Pj/V4hPYuiX/CdTWLWnExh8oExufkO8E7dN33+Keqy9n1k9T\n6NPvcgBq12/IHN8J2oqlf7BlUypb04J/YrZr+1YqV4vL/btStdgCk1A59u3ZzfKF86jbrGUwmndE\nKpcvx469+3L/3rF3H5XLH3pCCfCvru0ZfE530jMzWby2dP1wBkjdnEb1xMTcv5MTEthYxPvkk2++\n5uROnQFo17IlnY87jlP7Xcqp/S6l6/EdaVi3XqGvDYXU1FSSfcNpAJKSkkhNTS20/GeffcZJJ50U\njKaVWETlymTn+f7J3rELT+XK+cp44mLxxMUSO6AfsQP/RXTD+gBkrF1P+t+rSbztehJvu4H9y1eS\ntTl/AjUUNm3dSvW4A8eFpNg4UrceelwYN+k7+gy5kxfGf8C/L/Me25rWrcuPc2aTmZXF2k2pLF65\nko2lIKY927dRKc+xrmLVarnJi4Ls37uHv1MWUKtJcwC2b9rItk0b+ezFp/n0hSdZvWRRwNtclMP9\n7OTVtGlTfvnlF/bt28e2bduYPXt2yBKHWzenEZfnGBcbn8C2g85Rt23eTGye7+HYhIQCExlTJ31L\nmzzDJNM2bmDobTfy1L13sTSl8AuRgVStQgxbd+3N/Xvr7r1UqxhzSLnzOrVm4oKlpGfm78FxXL2a\nbNu9lzVbth/yGgl/zoXno7QK2C8nMxsAzAF6ABWAikBPYLZvXcgcvD/qJsSSXLUys1esKfQ1XZrW\ny83choorIOdb0NXWvuecw4RXX+P2K67gtfHj8q37c9Xf/HfMWzx4400Ba+fhKMln45SmzfnfrXfy\n3vU306lBIx757GMAPv51Fic1bkpyngRJKJRkvxQ0uZBhjHt7NOde/E9iYvIn3X6b/gtVY2Np1LSZ\nfxt7hArcT4dxpT9l1nTantSNW555iUtu/Tefv/EyLjvbb+0ricL2wUGFitzG+f0H8uQb79C5W0+m\nfPUFAGde9E/27NrFsNtvYsqEz6nTsBERvqtQQVVQfIXso+ysLL56cyTte/SiWkJSgWVKg4KaX9Dn\nDWDstLk8/9VPeCIiqJ8UV2CZUCrw/VfI/vli8iR+X7aUK31zLK1au5blq1cx6b33mTz2A2bOn8dv\nCxcEtL3+UFh8X331FYsXL2bAgJCeCpTMQfvNIiLwxMWy9d1xbP/fBKqccwZWrhye2GpEJsSTNvxV\n0oaPJLpeXaLq1A5Row8o0XEPuLTX6Xz+zHPc+s9Lef2LzwA475TuJMXF0X/oQzw79j2Oa9IYjyf0\nCfeCjwGFH+u+f/d1Wp/Skyrx3h/fLjubHWmp/OPGOzm1/zX8NP4d9u8tHT29cpS0J12XLl3o2rUr\nV111Fffddx9t2rTJ7QURbCU5TyjJ+dKX48cS4fHQpcepAFSNi+OZN95l6Asvc+nV1zHquSfZuyf4\nvaMK/j7Kr3Z8NRKrVGLeyrX5lkd7PJzdvgWf/5YSuAaKSK5AzsFxP3C8cy5fH2kziwVmAmMKepGZ\nDQIGAZzQ9yqannzqYVd8Wuum9Gjl7Va6YuMW4iod+PEYV7ECW3fn/yJrnJxA/aQ4nrv8PDwREVSJ\nKce95/fiiU8nAd5uzx0b1uGh8aEdm54cn8CGPFf8UjdvJimu8BP5M0/pxmMjD4xZ3JiWxh1PPM6j\nt99BnVIysVtS5Sqkbj+QzU7dsZ3Eg66YVc0z7Oa8Dh0ZMXkiAAvXrGb+qr/5+LdZ7E1PJyMri5io\naG7qFdwJtuITEknbdOBqy5ZNm4jL0wsAID4xkbTUVOITk8jKymTP7t1UqlKFZYsXM/2nH3ln1Eh2\n79pFRIQRFR3NlrQ0fv1lGnNmziAjPZ09e3bzwuPDuO2+B4MW129TJjLvJ+8Y7JoNGrIjT0+GnVu3\nULlqyTtjzZ/6A31vvxuA2o2akJWRwZ5dO6lYJbDJqSlffcHUid8AUL9JU7bk+fxs25xGtTy9UgBi\n4xPzXU3aWkAZgM7devDSo/+hT7/LialQkYG3Dga8PybuHzSQhDxX4wJp3o+TWDjN25U5uV6D3OEm\nALu2baViIfvou7FvUS0xmQ6nnhGUdh6Ojg1r076+94fhuq3bqZKnC3CVmPLs8g0NKEhWdjZL12+i\nWY1EVqSG/kpzXskJiWzYdKBn18a0tNxhg3lNnzOH194fy5vPPkd0tHc4zuRfptG2eQsq+IYSnNyx\nEwsWL6Zjm7bBaXwJJCUl5btynJqaSmKeq7k5Zs6cyejRoxk1alRufKVF9s6dROT5/omoUomsXbvy\nlcnauZOMteshO5vs7dvJ3LwFT1ws0fXqkLF2Hc439DP9rxVE1apBxurCL5wEQ1JcHBvyDMVL3bqF\nxCKGN51xQheeGPMWAJEeD3f968CE2QMffZi6ydUD1taipEydwpKZ3qGfiXXqsyvPsW739m2FHut+\n+vBdqiQk0abbgUk5K1aLJaluAyI8HqrEJ1A1MZntm1JJOmhS5mAp6WenMFdffTVXX301APfffz91\n6tTxexsL8/2Ez/lpovfcuH6TpmzJc4zzfn/mP0eNjU/I18Nxa1r+79hpk79j/q+zuOvRJ3MTH1FR\n0URFeY8V9Rs3Ial6TTauXUv9Jk0DFleOHi0bc0pz74TqKzdtJbZSDPh2VWzFGLbv3puvfKOkeOol\nxPJ4v3PwmFE5phx3ntuDD6bNJb5yRR68uHfuax+46HQe/9/kfL0URcQ/ApngMApO6GZTWKodcM6N\nAkYBDBjx3hF1fpm8aCmTFy0FvF3CerVpxoxlf9MoOZ496els35P/YPJ9yjK+T1kGQELligw+p0du\ncgOgVZ3qrN+6g60HHciCrVWTJqxav441GzeQHBfPNz//xBN33pWvzN/r1lGvZk0AfvrtN+rW8D7f\nsWsXNw97mNsuH0D7FqWnS3qLWrVYvWUz67ZuJbFKZb5LWcgjF+S/M0zazp0k+E46f166hPoJ3i/+\nRy48UO7LeXNYsn5d0JMbAI2bN2f92jVsXL+OuIREpk6ZzO3355/csdOJXflh4jc0a9Wa6T/+SOv2\nHTAzHn3hpdwy494eTfmYGM4+/yIA+l/jHV60aN5cPh//QVCTGwAde/amY0/v/+efC+by25SJtOx8\nIuuW/0m5mJjDmkejSnw8Kxcvom3X7qStX0tmRgYVgjDuuefZ/6Dn2d47Biz8bRZTvvqCTqd0Z8XS\nJcRUrEjVg06+qsbFUT4mhuV/LKZB0+bM+GFy7us3rltLck3vxHzzZ83IndF9z65dRJcrR2RUFFO/\n+4Ymrdrkm68jkNp170W77t4T9+WL5jHvx8k0O/4E1q/8i+iYGCoVcNI/7YuP2b9vD70vuzIobTxc\nvy1fw2/LvT8KG1dPoFPDOqSs2UCt2Krsy8hk1778Ez1HeTyUi/Kwa186Zkbj6gmsSit8ZvtQad2s\nGX+vXcuaDetJjk/g6x9+4Kl78k+MuPjPP3lk+H8Z+djjxOf5fNVITOKjr78is28WzjlmL1xA/wsu\nPLiKkGrZsiWrV69m7dq1JCUlMXHiRB599NF8ZZYsWcLjjz/Oiy++SFwRyflQyVi3AU9cLBFVq5K9\ncyflWzZn+6cT8pXZ/8eflG/Vgn0LUrCYGCLjY8nato2salWJad8WbCaYEVW3Nnt+nV1ITcHTqkFD\nVm/cwNpNqSTFxvHtzBk8fv2N+cqs2rCButW9iYuf58+jji+JsXf/fsARU648MxYtxBPhyTc5aTC1\nOrknrU7u6W3v7wtJmTaFRu07kbpqBdHlY6hQQLL8168/JX3fXrpfcnm+5fVbH8efc3+lWeeT2Ldr\nF9s3pVLloIsSwVSSz05hsrKy2LlzJ9WqVWPZsmUsW7aMhx9+uPgX+smp5/Th1HP6ADD/15l8P+Fz\nOnfrwfI/llChQoVDLhBUi4unfEwF/lqymIbNmvPLlEmcdu55gHeS0q8/Gc/djz9DuXIHEts7t2+j\nYqXKRHg8bNqwno3r1pJQPTiJth9+/5Mffv8TgDZ1atCzVWN+/Ws1DZLi2JuewfaDkhM/Lv6LHxf/\nBUB8pQrcfOYpPPflDwDc9c7nueUe73cOj3/yne6iIhIggUxwPAbMMbOJQM404nWB04FhAaw3n/l/\nr+O4erV4pn8f0jOzeH3ygcmXhl16Volu+dqlcT2mh3By0RyRHg/3DrqeG4b+x3srsdN60bhuPUa8\n9y6tGjehxwkn8MGEL5kxfx5RkZFUrliJYbffDsAHX01g1fr1jBo/jlG+YSuvDH2E+GqhnaguMsLD\nXWedy23vvU22y+bcdh1omJTMqCmTaV6zJt2atWD8rOn8vHSJt3dN+Qo8eF7pOrH3eCK55pbbGXb3\nXWRnZ3PqWWdTt34D3n/zDRo3a0ank07mtLPPYfgTj3HT5f2oVLkydzwwNNTNPiyN2rTjz4XzeOX+\nwURFR3PuwANzu7z+8L1c8x/vnRC+/2gsKTN/ISM9nReH3Mxxp/SkW5+LOO2fl/H1mNeZNcnbm+Lc\nK68L+mSWrY/vxMLZv/LA9VcRXa48V9x6R+66YbffxIP/HQHAv66/mbeH/x/p+723iW19vHcc8P/G\nvMnGdWswM+ISk7jshlsAWL9mNW+98CwWEUGNOnUZcPPtQY0rR4NWx7EiZQGjh/6byOhynNH/6tx1\n7zz+IJffN4ydW7cw85sviEuuwbtP/gfwJknadO3Ohr+X8/moF71zcyyax/QJ/+OKBx8PSSw5/tyQ\nRuPkBG7q3ZXMrCw+n/177rprT+3Ca9/PIDrSw6UntsMTEUGEGSs2bckdbtisZiJnHtecCtHR9D2p\nHRu372TstLkhiSXS4+G+m27m+vvu9d6us/cZNK5fn5fefotWTZvS88STeO61UezZu5c7H/V+RdZI\nSuLFh4dx+imnMHP+PC687lrMjK4dO9Gjy4khiaMwkZGRDBkyhFtuuYWsrCz69OlDo0aNGDlyJC1a\ntKB79+4MHz6cvXv3cs899wCQnJzM888/H+KW5+EcO7+dTGy/iyAign3zF5KVtpmK3bqSuX4D+5f9\nRfrylUQ3rE/8oCtxLpudk3/E7d3H/iVLia5fl/hBA8HB/uUrSF+2PNQREenxcHf/Adz07DNkZ2fT\n55RuNKpVm1c++ZiWDRrQvX0Hxk3+jpkpKUR6PFSpWJFHrh0EwNYdO7jpuacxiyApNpZhg64PcTRe\ndVq0ZtXihXzwxANERkXTo++BOZ0+fm4YF935ILu2bWXupK+pllSdT55/DIBWXXvSvMvJ1G7WijV/\n/M74p4diZpzwj4soXzH4dx3JUZLPTkpKCkOGDGHHjh38/PPPjBo1ivHjx5OZmcm1114LQMWKFRk2\nbBiRkaG5QWLbjp1ZOPtX7r3uSqLLleOqWw/cTW3obTfk3gXl8htu4Y0XniUjPZ02HTrSxvcdO/bV\nEWRkZvDcQ97Eb87tYP9IWchn740hwuMhIsLD5TfeSqUQTAy7cPV6WtetwWN9zyY9M5O3fvg1d92D\nF57OsE++C3qbRKRgVtD4TL9t3Dsc5QygFt5eG2uAb51zJZqd8Eh7cJRWo07rVHyhMmbv7HmhboJf\nre3ePdRN8LvZy0N7m0J/q5dY+q78Hq0/SuGkmEcjdceu4guVMXd3KB3z4fjL/vjg38ko0PYMfzXU\nTfCrSqd2C3UT/G7k5tI118XRGtT9+FA3we/mrzt08vqybMyPh95aPByMGnRJqJvgb6XnFm4BcObj\nr4bVb9oc39x3XancbwFN8/oSGR8UVcbMpjvnStelKBEREREREREpU0I/HTYUfM8/EREREREREZES\nKg0JjrDssiMiIiIiIiIiwROamYhEREREREREwlwg57yUQ5WGHhylcnISERERERERESk7gpLgMLNY\nM6tcyOrLC1kuIiIiIiIiIlIiAUtwmFlNMxtjZtuBNCDFzFaZ2VAzi8op55xbFKg2iIiIiIiIiMix\nIZA9ON4FRjvnqgL/BD4GWuCd92NEAOsVERERERERCbls58LyUVoFMsER75z7AcA59wnQzTm32zn3\nANAtgPWKiIiIiIiIyDEmkAmOTWbW3zdU5RZgJYCZWYDrFREREREREZFjTCATDVcBfYCJwAnAzb7l\nccC9AaxXRERERERERI4xkYHasHNuFXBJAcs3m9mqQNUrIiIiIiIiUhq4UjxfRTgKWILjYGbWEugL\n9AO2Ax2DVbeIiIiIiIiIhLeAJjjMrB7ehEY/IBOoB3R0zq0MZL0iIiIiIiIicmwJ2BwcZvYL8BUQ\nBVzsnDse2KnkhoiIiIiIiIj4W0DvogJUBpKBRN8yDUASEREREREREb8L5CSj55lZVeAi4GEzawxU\nM7POzrlZgapXREREREREpDTQHKPBFdA5OJxz24HRwGgzSwYuBf5rZnWcc3UCWbeIiIiIiIiIHDsC\nOUQlH+fcRufccOfcScDJwapXRERERERERMJfwHpwmNkXFD3nRp9A1S0iIiIiIiIix5ZADlF5NoDb\nFhERERERESnVsjUJxyHMLA4YB9QHVgKXOOe2FlCuLvA6UAdv54mzi7srayAnGf0xT8MSfcs2Bao+\nERERERERESn17gEmO+eeNLN7fH/fXUC5McBjzrnvzKwSkF3chgM6B4eZ/cfM0oAlwFIz22RmDwWy\nThEREREREREptc4D3vY9fxs4/+ACZtYSiHTOfQfgnNvlnNtT3IYDluAwszvwTibayTkX75yLBU4A\nuvrWiYiIiIiIiMixJdk5tx7A929SAWWaAtvM7BMzm2tmz5iZp7gNB3IOjgHA6c65tJwFzrnlZtYf\nmAg8H8C6RURERERERELKhekcHGY2CBiUZ9Eo59yoPOsnAdULeOn9JawiEjgFaA+swjtnx0DgjeJe\nFChReZMbOZxzm8wsKoD1ioiIiIiIiEiA+JIZo4pY36uwdWa20cxqOOfWm1kNILWAYmuAuc655b7X\nfAp0oZgERyDn4Eg/wnUiIiIiIiIiEp4+B67wPb8C+KyAMr8CsTk3LAFOBX4vbsOB7MFxnJntKGC5\nAeUDWK+IiIiIiIiIlE5PAuPN7Gq8w0/+CWBmHYHrnXPXOOeyzOwuYLKZGTAbeK24DVu4jgk6HGY2\nKO94oXAQbjGFWzwQfjGFWzwQfjGFWzygmMqCcIsHwi+mcIsHwi+mcIsHwi+mcIsHwjMmCX8BvU1s\nGTKo+CJlTrjFFG7xQPjFFG7xQPjFFG7xgGIqC8ItHgi/mMItHgi/mMItHgi/mMItHgjPmCTMKcEh\nIiIiIiIiImWeEhwiIiIiIiIiUuYpweEVjmPLwi2mcIsHwi+mcIsHwi+mcIsHFFNZEG7xQPjFFG7x\nQPjFFG7xQPjFFG7xQHjGJGFOk4yKiIiIiIiISJmnHhwiIiIiIiIiUuYpwSEiIiIiIiIiZV6ZTXCY\nWZaZzTOzFDObb2aDzSzCt66HmX15UPnPzGz6Qcu6mdkcM8s0s4sPWneFmS3zPa4opi3Hm9lCM/vT\nzIabmZXCeL4xs20Hb6eQttzsi8WZWcLhxlJKY3rPzP4ws0VmNtrMosp4PG/42rDAzD4ys0qHG0+g\nYzKzdmY23bftBWZ2aTFtOer3XSmL56jfc0GIqZ6Zzc6z/euLactjZrbazHYdSSylKR4zq2BmE8xs\nia/sk0caU7DiK6LOEh87Dlew4zncz1kIYxpsZr/72jjZzOoVU2fA9pFv+0cdU551F5v3ONyxmDrv\nNe8x+w8zO8N/0fhtHw00s02+7cwzs2uKqbPE532hism3/BLfey/FzMYWU2fAYvLTPno+z/5Zambb\nQhWPH2Oqa2ZTzGyu7/hwdjF1lvbPUT3fMW6Bmf1gZrWLqTOg+0ikRJxzZfIB7MrzPAmYBDzs+7sH\n8GWe9dWA1cBioEGe5fWBtsAY4OI8y+OA5b5/Y33PY4toyyzgRMCAr4GzSlM8vnWnAf/Iu50i2tLe\nt62VQEJp3EdHENPZvv1jwPvADWU8nip5nv8fcE9p20dAU6CJ73lNYD1QLZDvu1IWz1G/54IQUzRQ\nzve8ku//vmYRbekC1MjbprIaD1AB6JnndT9zBMfuYMZXRJ0lPnaU9ngO93MWwph6AhV8z28AxoVq\nH/krJt+6ysBPwAygYxH1tQTmA+WABsBfgKc0xQMMBF4qYX2Hdd4XwpiaAHNz2gYkhSomf73n8pS5\nBRgdBvtoFL7ve9/nZGUR9ZWFz9GHwBW+56cC74RyH+mhR0keZbYHR17OuVRgEHCzWYG9Jy4CvgA+\nAPrmed1K59wCIPug8mcA3znntjjntgLfAWcWVLeZ1cD7Y3O6c87hPYE7v5TFg3NuMrCzhPXPdc6t\nPIKmF7XNUMf0lfPBm5AqMgNdgu2FOp4dAL66YwB3uDEUsE2/xuScW+qcW+Z7vg5IBRKLqN+v77tS\nEI9f33O+bfo7pnTn3H7fn+Uoplefc26Gc279UYRw8PZCFo9zbo9zbkrO64A5+GEfHVSH348ThdRT\n4mPH0QhGPIf7OTtaRxHTFOfcHt+fMyjmvROsfeSr64hi8hkGPA3sK6aa84APnHP7nXMrgD+BzkfV\n8EIcZTwlVeLzPn84ipiuBUb42pizncIELSY/7aN+eC8GFKas7CMHVPE9rwqsK6KasvA5aglM9j2f\n4mtzYYK6j0QKExYJDgDn3HK88SQVsDrnoPm+73lxauHNYmE2B9kAAAjrSURBVOZY41tWWNk1JSxb\nYn6Op1QoDTGZd5jA5cA3R7utUMdjZm8CG4DmwIv+2GagYjKzznivkv91tG08HKUhHn++58D/MZlZ\nHTNbgPeY95TvR2XQlIZ4zKwa3qvrk4sre7hCfZzwt2DGE6zjhh9iuhpv781S40hiMrP2QB3nXEmG\n0RzOedJRO4p9dJEdGMpZp4gqghoPHHFMTYGmZjbNzGaYWVE/HsvKPsK8Q7waAN8XUUVZ2UdDgf5m\ntgb4Cm/PlMKUhX00H2/yA+ACoLKZxRdSRdD3kUhBwibB4XNIRtLMkoHGwFTn3FIg08xaH+52KPwK\n+eGUPVz+iqc0CXVMLwM/Oed+9tP2QhaPc+5KvF24FwP+HKfu15h8vZzeAa50zpXoirSfhToef7/n\nwI8xOedWO+fa+l57hW87wRayeMwsEu8J3XDfyV8ghPq4528BjycEx40jisnM+gMdgWeC0MbDVeKY\nfOPynwfuPNJt479znxLXWcw++gKo7zseTALePpxtE/h4Cqy3mJgi8Q5T6YH3R+jrvgRtibZN6dtH\nOfoCHznnsg5n25TOfdQPeMs5VxvvUNV3cua9KMm2KX376C6gu5nNBboDa4HMkm6b4OwjkXzCJsFh\nZg2BLLzdWfO6FO84sBVmthLvWODiujCuAfJm+mtTeBezNeTvmlpU2RLzczylQqhjMrP/4O3qPNhP\n2wv5PvKdDIzjQHb9qPg7JjOrAkwAHnDOzfBHGw9HqOPx93vOt82AvO98PR1SgFP80tASKgXxjAKW\nOef+W9JtH47ScJzwp2DEE+zjxpHGZGa9gPuBPnmGRpUKRxBTZaA18INveRfgcyt8otHDOU86akey\nj5xzm/Psl9eA44uoIqjxwBG/79YAnznnMnxDGv7Am/AoSKnfR3n0pejhKVB29tHVwHgA59x0oDxQ\n2MTppX4fOefWOecudM61x3u8wzm3vZAqgr6PRAoSFgkOM0sERuKdTOrgTGE/4EznXH3nXH28X3DF\nnXR9C/Q2s1gziwV6+5YdwjcefaeZdfGNaRsAfHbk0QQknpALdUzmnT39DKCfP64GhjIe82qc8xxv\n1/olftiuX2Mys2jgf8AY59yHR9u+wxXqePz9nvNt098x1TazGN/zWKAr3hPmoAh1PGb2KN4x0rcf\ncRBFtyesjuXBiCfYx40jjcm8wzlexZvcKGoehKA7kpicc9udcwl5ls/AG9tvhVTzOdDXzMqZWQO8\nP7JnlZZ4fK+rkadcH7y9HQtT4vM+fziKz9KneCe4xbx3G2uKdyLHggQtpqM5NphZM7w/rgu8q08e\nZWUfrcI7qTBm1gJvgmNTIdWUhc9RQp4eKPcCo4uoJqj7SKRQrhTMdHokD7wZyHl4r9DNx9uFKsK3\nrgfwJd4M5FrADnrtHOAEoBPebONuYDOQkqfMVXgn+/kTbxfZotrSEViEd5zwSwfXV0ri+RnvAXav\nr8wZRbTlVl+ZTLyZ19dL6T46nJgyfftnnu/xUFmNB29ichqw0Pe+e488d1UpLTEB/YGMPP/n84B2\ngXzflbJ4jvo9F4SYTgcW+La7ABhUTFue9m0n2/fv0LIaD94rSw7vj56cfXTNkeyjYB4nCqmzxMfC\n0h4Ph/k5C2FMk4CNedr4eaj2kb9iOmjZDxRxFxVfmfvxHuP+wA93IArAPnoiz+unAM2LqbPE530h\njMnw3jntd7znAH1DFZO/3nN456x4soR1loV91BLvOdp837Z6l/HP0cXAMmAp8Dq+O5WFah/poUdJ\nHuachkaJiIiIiIiISNkWFkNUREREREREROTYFhnqBpQlZjYTKHfQ4sudcwtD0Z6jZWb/w3tbrrzu\nds6V2fFy4RZTuMUD4RdTuMUDYXmsK/PxmFkbvHcVyWu/c+6EULTnaIVbPBC2MZ0BPHXQ4hXOuQtC\n0Z6jFab7KKxiCrd4QJ8jkWDTEBURERERERERKfM0REVEREREREREyjwlOERERERERESkzFOCQ0RE\npBhmVtvMPjOzZWa23MxeMrOD5/U4mu2fb2Yt8/z9iJn1OsJtDTSzl3zPh5rZWjOb52v7J3nrERER\nEQknSnCIiIgUwcwM+AT41DnXBGgCxABP+7Ga84HcxINz7iHn3CQ/bft551w7X9vHAd+bWaKfti0i\nIiJSaijBISIiUrRTgX3OuTcBnHNZwB3AADO7Oae3BICZfWlmPXzPe5vZdDObY2Yfmlkl3/Inzex3\nM1tgZs+a2UlAH+AZX0+LRmb2lpld7Ct/mpnNNbOFZjY6p+eIma00s4d9219oZs2LC8Q5Nw6YCPzL\nn/9BIiIiIqWBEhwiIiJFawXMzrvAObcDWEkht1s3swTgAaCXc64D8Bsw2MzigAuAVs65tsCjzrlf\ngM+BIb6eFn/l2U554C3gUudcG199N+SpKs23/VeAu0oYzxyg2GSIiIiISFmjBIeIiEjRDCjonupW\nxGu64B1yMs3M5gFXAPWAHcA+4HUzuxDYU0zdzYAVzrmlvr/fBrrlWf+J79/ZQP1itlWSdouIiIiU\nWUpwiIiIFC0F6Jh3gZlVAZKBzeT/Li2fUwT4ztcjo51zrqVz7mrnXCbQGfgY77wb3xRTd3HJiP2+\nf7MopDdJAdoDi0tYVkRERKTMUIJDRESkaJOBCmY2AMDMPMBzwEvACqCdmUWYWR28yQuAGUBXM2vs\ne00FM2vqm4ejqnPuK+B2oJ2v/E6gcgF1LwHq52wHuBz48UgDMbOLgN7A+0e6DREREZHSSgkOERGR\nIjjnHN55My42s2V4e21kO+ceA6bhTXIsBJ7FO78FzrlNwEDgfTNbgDfh0RxvEuNL37If8U5WCvAB\nMMQ3mWijPHXvA64EPjSzhUA2MPIwQ7gj5zaxQH/gVF/7RERERMKKec/bREREpCR8dz15H7jQOTe7\nuPIiIiIiEhxKcIiIiIiIiIhImachKiIiIiIiIiJS5inBISIiIiIiIiJlnhIcIiIiIiIiIlLmKcEh\nIiIiIiIiImWeEhwiIiIiIiIiUuYpwSEiIiIiIiIiZZ4SHCIiIiIiIiJS5v0/MsKB3MBr4pMAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a0bd99d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notNullBarChart(dfInterp)\n",
    "corrHeatMap(dfInterp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 650,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def indicatorFacetGrid(df):\n",
    "    #instead of sns.pairplot, use sns.FacetGrid: better short hand analysis for distribution \n",
    "    g = sns.FacetGrid(pd.melt(df.reset_index(),\n",
    "                          id_vars=['StratificationID1'],\n",
    "                          value_vars=dfInterp.columns),\n",
    "                      hue='StratificationID1',col='QuestionID',col_wrap=6,\n",
    "                      sharex=False, sharey=False, legend_out=True)\n",
    "    _ = g.map(sns.kdeplot,'value')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 646,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a51fa5e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a645a59b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "indicatorFacetGrid(dfGender)\n",
    "indicatorFacetGrid(dfInterp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(740, 8)\n",
      "(469, 8)\n",
      "Beta_0 (y-intercept) for DIA11_3 linear regression model is 4.4121\n",
      "Beta_1 (slope) for DIA1_1 is 0.0599\n",
      "Consider dropping: DIA1_1\n",
      "Beta_2 (slope) for DIA1_2 is 0.9826\n",
      "Beta_3 (slope) for DIA8_0 is -0.2001\n",
      "Beta_4 (slope) for DIA13_1 is 0.2416\n",
      "Beta_5 (slope) for DIA13_2 is 0.1407\n",
      "Beta_6 (slope) for StratificationID1 is 11.1183\n",
      "Beta_7 (slope) for LocationID is -0.0201\n",
      "Consider dropping: LocationID\n",
      "R^2 score for DIA11_3 linear regression model is 0.7010\n"
     ]
    }
   ],
   "source": [
    "predictors = [\n",
    "    'DIA1_1',\n",
    "    'DIA1_2',\n",
    "    #'DIA2_1',\n",
    "    #'DIA4_0',\n",
    "    #'DIA5_0',\n",
    "    #'DIA6_0',\n",
    "    #'DIA7_0',\n",
    "    'DIA8_0',\n",
    "    #'DIA9_0',\n",
    "    #'DIA10_0',\n",
    "    #'DIA11_1',\n",
    "    #'DIA11_2',\n",
    "    #'DIA12_1',\n",
    "    #'DIA12_2',\n",
    "    'DIA13_1',\n",
    "    'DIA13_2', \n",
    "    'StratificationID1', \n",
    "    'LocationID',\n",
    "]\n",
    "response = 'DIA11_3'\n",
    "dfIndicators = dfInterp.reset_index()[predictors + [response]] \n",
    "print(dfIndicators.shape)\n",
    "dfIndicatorsNoNAN = dfIndicators.copy().dropna() \n",
    "print(dfIndicatorsNoNAN.shape)\n",
    "dfIndicatorsNoNAN['StratificationID1'] = dfIndicatorsNoNAN['StratificationID1'].replace(['GENM', 'GENF'], [0,1])\n",
    "X = dfIndicatorsNoNAN[predictors]\n",
    "y = dfIndicatorsNoNAN[response]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state = 42)\n",
    "linregr = LinearRegression()\n",
    "linregr.fit(X_train, y_train)\n",
    "# Print y-intercept (beta_0)\n",
    "beta_0 = linregr.intercept_\n",
    "print(\"Beta_0 (y-intercept) for %s linear regression model is %0.04f\" % (response, beta_0))\n",
    "for N in range(len(predictors)):\n",
    "    beta_N = linregr.coef_[N]\n",
    "    print(\"Beta_%d (slope) for %s is %0.04f\" %(N+1, predictors[N], beta_N))\n",
    "    if abs(beta_N) < 0.1:\n",
    "        print(\"Consider dropping: %s\" %(predictors[N]))\n",
    "\n",
    "y_pred = linregr.predict(X_test)\n",
    "\n",
    "linModel_score = r2_score(y_test, y_pred)\n",
    "print (\"R^2 score for %s linear regression model is %0.04f\" % (response, linModel_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.700233780335\n",
      "0.712965338589\n",
      "0.711495785776\n",
      "0.712079009182\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import ShuffleSplit\n",
    "for folds in range(5,21,5):\n",
    "    #how CV selects each fold is equivalent of test_train_split fold times to get several selections\n",
    "    cv = ShuffleSplit(n_splits=folds, test_size=0.3, random_state=42) \n",
    "    cv_results = cross_val_score(linregr, X, y, cv = cv, scoring='r2')\n",
    "    print(np.mean(cv_results))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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