assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "16bd11d9",
   "metadata": {},
   "source": [
    "# Crash Analysis System (CAS) data exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28a8bb5b",
   "metadata": {},
   "source": [
    "## Data inspection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "42aba66b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d3e1827f",
   "metadata": {},
   "outputs": [
    {
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       "      <th>OBJECTID</th>\n",
       "      <th>advisorySpeed</th>\n",
       "      <th>areaUnitID</th>\n",
       "      <th>bicycle</th>\n",
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       "      <th>carStationWagon</th>\n",
       "      <th>cliffBank</th>\n",
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       "      <th>truck</th>\n",
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      "text/plain": [
       "                   X             Y  OBJECTID  advisorySpeed  areaUnitID  \\\n",
       "0       2.037858e+06  5.707835e+06         1            NaN    544801.0   \n",
       "1       1.799424e+06  5.815528e+06         2            NaN    528900.0   \n",
       "2       1.756461e+06  5.936053e+06         3            NaN    507000.0   \n",
       "3       1.551129e+06  5.171320e+06         4            NaN    597513.0   \n",
       "4       1.245391e+06  4.849172e+06         5            NaN    611500.0   \n",
       "...              ...           ...       ...            ...         ...   \n",
       "821739  1.757918e+06  5.914599e+06   1318959            NaN    518600.0   \n",
       "821740  1.833766e+06  5.638669e+06   1318960            NaN    554900.0   \n",
       "821741  1.758255e+06  5.918060e+06   1318961            NaN    517400.0   \n",
       "821742  1.773738e+06  5.888266e+06   1318962            NaN         NaN   \n",
       "821743  1.754396e+06  5.875116e+06   1318963            NaN    526104.0   \n",
       "\n",
       "        bicycle  bridge  bus  carStationWagon  cliffBank  ... tree truck  \\\n",
       "0           0.0     NaN  0.0              2.0        NaN  ...  NaN   0.0   \n",
       "1           0.0     NaN  0.0              2.0        NaN  ...  NaN   0.0   \n",
       "2           0.0     NaN  0.0              0.0        NaN  ...  NaN   0.0   \n",
       "3           0.0     0.0  0.0              2.0        0.0  ...  0.0   0.0   \n",
       "4           0.0     NaN  0.0              1.0        NaN  ...  NaN   0.0   \n",
       "...         ...     ...  ...              ...        ...  ...  ...   ...   \n",
       "821739      0.0     NaN  0.0              2.0        NaN  ...  NaN   0.0   \n",
       "821740      0.0     0.0  0.0              0.0        0.0  ...  1.0   0.0   \n",
       "821741      0.0     0.0  0.0              1.0        0.0  ...  0.0   0.0   \n",
       "821742      0.0     0.0  0.0              0.0        0.0  ...  0.0   0.0   \n",
       "821743      0.0     0.0  0.0              1.0        0.0  ...  0.0   0.0   \n",
       "\n",
       "       unknownVehicleType  urban  vanOrUtility vehicle waterRiver    weatherA  \\\n",
       "0                     0.0  Urban           0.0     NaN        NaN        Fine   \n",
       "1                     0.0  Urban           0.0     NaN        NaN        Fine   \n",
       "2                     0.0  Urban           1.0     NaN        NaN        Fine   \n",
       "3                     0.0   Open           0.0     0.0        0.0        Fine   \n",
       "4                     0.0  Urban           1.0     NaN        NaN        Fine   \n",
       "...                   ...    ...           ...     ...        ...         ...   \n",
       "821739                0.0  Urban           0.0     NaN        NaN        Fine   \n",
       "821740                0.0   Open           0.0     0.0        0.0        Fine   \n",
       "821741                0.0  Urban           0.0     0.0        0.0        Fine   \n",
       "821742                0.0   Open           1.0     0.0        0.0  Light rain   \n",
       "821743                0.0  Urban           0.0     0.0        0.0        Fine   \n",
       "\n",
       "        weatherB crashCount  \n",
       "0           Null          1  \n",
       "1           Null          1  \n",
       "2           Null          1  \n",
       "3           Null          1  \n",
       "4           Null          1  \n",
       "...          ...        ...  \n",
       "821739      Null          1  \n",
       "821740      Null          1  \n",
       "821741      Null          1  \n",
       "821742      Null          1  \n",
       "821743      Null          1  \n",
       "\n",
       "[821744 rows x 73 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load table from csv file as a dataframe\n",
    "cas_df = pd.read_csv('Crash_Analysis_System_(CAS)_data.csv')\n",
    "\n",
    "# Add extra column with 1s to help with pivoting later\n",
    "cas_df['crashCount'] = pd.Series([1 for x in range(len(cas_df.index))])\n",
    "cas_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3ee7de69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['X', 'Y', 'OBJECTID', 'advisorySpeed', 'areaUnitID', 'bicycle',\n",
       "       'bridge', 'bus', 'carStationWagon', 'cliffBank',\n",
       "       'crashDirectionDescription', 'crashFinancialYear', 'crashLocation1',\n",
       "       'crashLocation2', 'crashRoadSideRoad', 'crashSeverity',\n",
       "       'crashSHDescription', 'crashYear', 'debris', 'directionRoleDescription',\n",
       "       'ditch', 'fatalCount', 'fence', 'flatHill', 'guardRail', 'holiday',\n",
       "       'houseOrBuilding', 'intersection', 'kerb', 'light', 'meshblockId',\n",
       "       'minorInjuryCount', 'moped', 'motorcycle', 'NumberOfLanes',\n",
       "       'objectThrownOrDropped', 'otherObject', 'otherVehicleType', 'overBank',\n",
       "       'parkedVehicle', 'pedestrian', 'phoneBoxEtc', 'postOrPole', 'region',\n",
       "       'roadCharacter', 'roadLane', 'roadSurface', 'roadworks', 'schoolBus',\n",
       "       'seriousInjuryCount', 'slipOrFlood', 'speedLimit', 'strayAnimal',\n",
       "       'streetLight', 'suv', 'taxi', 'temporarySpeedLimit', 'tlaId', 'tlaName',\n",
       "       'trafficControl', 'trafficIsland', 'trafficSign', 'train', 'tree',\n",
       "       'truck', 'unknownVehicleType', 'urban', 'vanOrUtility', 'vehicle',\n",
       "       'waterRiver', 'weatherA', 'weatherB', 'crashCount'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cas_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f88a8fd8",
   "metadata": {},
   "source": [
    "Some columns are hard to interpret. For instance, `strayAnimal` could refer to stray animals that were actively involved in the crash and contributed to the cause, e.g. chicken crossing the road; or these animals became stray as a result of the crash, e.g. traumatized pets. In other words, was the animal counted as a contributing factor or just a circumstancial feature? I suppose the interpretation might depend on how and why these particular features were recorded,e.g. to indicate the damage, to help attributing the cause, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e49e36fa",
   "metadata": {},
   "source": [
    "Focus on three sets of column labels, which we will call `agent_types`, `feature_types`, and `harm_types`. Labels in these three sets will correspond to columns with **counts** of different moving agent/vehicle types, different feature/object/factor types, and different types of harm for each crash."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4db26ad8",
   "metadata": {},
   "source": [
    "### Vehicle types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5839d871",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>pedestrian</th>\n",
       "      <th>bicycle</th>\n",
       "      <th>moped</th>\n",
       "      <th>motorcycle</th>\n",
       "      <th>bus</th>\n",
       "      <th>schoolBus</th>\n",
       "      <th>suv</th>\n",
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       "      <th>taxi</th>\n",
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       "      <td>821739.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>821739.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.041383</td>\n",
       "      <td>0.028963</td>\n",
       "      <td>0.007098</td>\n",
       "      <td>0.036274</td>\n",
       "      <td>0.01587</td>\n",
       "      <td>0.000753</td>\n",
       "      <td>0.105117</td>\n",
       "      <td>0.080399</td>\n",
       "      <td>0.001511</td>\n",
       "      <td>0.010698</td>\n",
       "      <td>1.311054</td>\n",
       "      <td>0.175788</td>\n",
       "      <td>0.025046</td>\n",
       "      <td>0.003057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         pedestrian        bicycle          moped     motorcycle  \\\n",
       "count  26605.000000  821739.000000  821739.000000  821739.000000   \n",
       "mean       1.041383       0.028963       0.007098       0.036274   \n",
       "min        1.000000       0.000000       0.000000       0.000000   \n",
       "max        6.000000       5.000000       4.000000       8.000000   \n",
       "\n",
       "                bus      schoolBus            suv          truck  \\\n",
       "count  821739.00000  821739.000000  821739.000000  821739.000000   \n",
       "mean        0.01587       0.000753       0.105117       0.080399   \n",
       "min         0.00000       0.000000       0.000000       0.000000   \n",
       "max         3.00000       3.000000       6.000000       5.000000   \n",
       "\n",
       "               train           taxi  carStationWagon   vanOrUtility  \\\n",
       "count  332913.000000  821739.000000    821739.000000  821739.000000   \n",
       "mean        0.001511       0.010698         1.311054       0.175788   \n",
       "min         0.000000       0.000000         0.000000       0.000000   \n",
       "max         1.000000       5.000000        11.000000       6.000000   \n",
       "\n",
       "             vehicle  unknownVehicleType  \n",
       "count  332913.000000       821739.000000  \n",
       "mean        0.025046            0.003057  \n",
       "min         0.000000            0.000000  \n",
       "max         4.000000            3.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List of column labels referring to a type of counted moving agents  \n",
    "agent_types = ['pedestrian','bicycle','moped','motorcycle','bus','schoolBus',\n",
    "               'suv','truck','train','taxi','carStationWagon','vanOrUtility', \n",
    "               'vehicle','unknownVehicleType'\n",
    "              ]\n",
    "cas_df[agent_types].describe().loc[['count','mean','min','max']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "469f4d74",
   "metadata": {},
   "source": [
    "From the number of missing counts in the above summary, it is reasonable to assume that all the missing counts for the pedestrians should be zeros. It is difficult to say why `trains` and `vehicles` have so many missing values (more than half), but for all other vehicle types the number of missing values is very small and thus can be ignored."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94900e0d",
   "metadata": {},
   "source": [
    "### Counted features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9fa9d57f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bridge</th>\n",
       "      <th>cliffBank</th>\n",
       "      <th>ditch</th>\n",
       "      <th>fence</th>\n",
       "      <th>guardRail</th>\n",
       "      <th>houseOrBuilding</th>\n",
       "      <th>kerb</th>\n",
       "      <th>objectThrownOrDropped</th>\n",
       "      <th>otherObject</th>\n",
       "      <th>parkedVehicle</th>\n",
       "      <th>phoneBoxEtc</th>\n",
       "      <th>postOrPole</th>\n",
       "      <th>trafficIsland</th>\n",
       "      <th>trafficSign</th>\n",
       "      <th>tree</th>\n",
       "      <th>waterRiver</th>\n",
       "      <th>strayAnimal</th>\n",
       "      <th>slipOrFlood</th>\n",
       "      <th>roadworks</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
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       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "      <td>332913.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.013724</td>\n",
       "      <td>0.106319</td>\n",
       "      <td>0.09443</td>\n",
       "      <td>0.210034</td>\n",
       "      <td>0.078095</td>\n",
       "      <td>0.023568</td>\n",
       "      <td>0.035361</td>\n",
       "      <td>0.002217</td>\n",
       "      <td>0.023439</td>\n",
       "      <td>0.259122</td>\n",
       "      <td>0.012427</td>\n",
       "      <td>0.122831</td>\n",
       "      <td>0.028815</td>\n",
       "      <td>0.048709</td>\n",
       "      <td>0.101555</td>\n",
       "      <td>0.009967</td>\n",
       "      <td>0.003454</td>\n",
       "      <td>0.002508</td>\n",
       "      <td>0.002932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
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      ],
      "text/plain": [
       "              bridge      cliffBank         ditch          fence  \\\n",
       "count  332913.000000  332913.000000  332913.00000  332913.000000   \n",
       "mean        0.013724       0.106319       0.09443       0.210034   \n",
       "min         0.000000       0.000000       0.00000       0.000000   \n",
       "max         4.000000       3.000000       3.00000       3.000000   \n",
       "\n",
       "           guardRail  houseOrBuilding           kerb  objectThrownOrDropped  \\\n",
       "count  332913.000000    332913.000000  332913.000000          332913.000000   \n",
       "mean        0.078095         0.023568       0.035361               0.002217   \n",
       "min         0.000000         0.000000       0.000000               0.000000   \n",
       "max         4.000000         2.000000       3.000000               4.000000   \n",
       "\n",
       "         otherObject  parkedVehicle    phoneBoxEtc     postOrPole  \\\n",
       "count  332913.000000  332913.000000  332913.000000  332913.000000   \n",
       "mean        0.023439       0.259122       0.012427       0.122831   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "max         5.000000       8.000000       3.000000       4.000000   \n",
       "\n",
       "       trafficIsland    trafficSign           tree     waterRiver  \\\n",
       "count  332913.000000  332913.000000  332913.000000  332913.000000   \n",
       "mean        0.028815       0.048709       0.101555       0.009967   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "max         4.000000       4.000000       3.000000       2.000000   \n",
       "\n",
       "         strayAnimal    slipOrFlood      roadworks  \n",
       "count  332913.000000  332913.000000  332913.000000  \n",
       "mean        0.003454       0.002508       0.002932  \n",
       "min         0.000000       0.000000       0.000000  \n",
       "max         3.000000       4.000000       3.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List of column labels referring to a type of counted features/objects/factors\n",
    "feature_types = ['bridge', 'cliffBank','ditch','fence','guardRail',\n",
    "                 'houseOrBuilding','kerb','objectThrownOrDropped',\n",
    "                 'otherObject','parkedVehicle','phoneBoxEtc','postOrPole',\n",
    "                 'trafficIsland','trafficSign','tree','waterRiver',\n",
    "                 'strayAnimal','slipOrFlood','roadworks'\n",
    "                ]\n",
    "cas_df[feature_types].describe().loc[['count','mean','min','max']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cacc9e24",
   "metadata": {},
   "source": [
    "The following check shows that `NaN` values for column `train` and columns listed in `feature_types` appear in same rows, suggesting that these particular columns came from the same source but different from that of other columns listed in `agent_types`. In other words, the missing values in the CAS dataset may be due to it being merged from multiple sources."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fb795a7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bridge                   True\n",
       "cliffBank                True\n",
       "ditch                    True\n",
       "fence                    True\n",
       "guardRail                True\n",
       "houseOrBuilding          True\n",
       "kerb                     True\n",
       "objectThrownOrDropped    True\n",
       "otherObject              True\n",
       "parkedVehicle            True\n",
       "phoneBoxEtc              True\n",
       "postOrPole               True\n",
       "trafficIsland            True\n",
       "trafficSign              True\n",
       "tree                     True\n",
       "waterRiver               True\n",
       "strayAnimal              True\n",
       "slipOrFlood              True\n",
       "roadworks                True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cas_df[(cas_df['train'].isna())][feature_types].isna().all()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "506c3014",
   "metadata": {},
   "source": [
    "### Degrees of harm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b78582ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fatalCount</th>\n",
       "      <th>minorInjuryCount</th>\n",
       "      <th>seriousInjuryCount</th>\n",
       "      <th>crashCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>821743.000000</td>\n",
       "      <td>821743.000000</td>\n",
       "      <td>821743.000000</td>\n",
       "      <td>821744.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.010433</td>\n",
       "      <td>0.318563</td>\n",
       "      <td>0.069203</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.116837</td>\n",
       "      <td>0.641788</td>\n",
       "      <td>0.301608</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>14.000000</td>\n",
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      ],
      "text/plain": [
       "          fatalCount  minorInjuryCount  seriousInjuryCount  crashCount\n",
       "count  821743.000000     821743.000000       821743.000000    821744.0\n",
       "mean        0.010433          0.318563            0.069203         1.0\n",
       "std         0.116837          0.641788            0.301608         0.0\n",
       "min         0.000000          0.000000            0.000000         1.0\n",
       "max         9.000000         34.000000           14.000000         1.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List of column labels referring to a type of counted harm, i.e. injuries/fatalities \n",
    "harm_types = ['fatalCount','minorInjuryCount','seriousInjuryCount','crashCount']\n",
    "cas_df[harm_types].describe().loc[['count','mean','std','min','max']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3474fe14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cumulative crash count: 821744\n",
      "Cumulative count of minor injuries: 261777.0\n",
      "Cumulative count of serious injuries: 56867.0\n",
      "Cumulative fatalities count: 8573.0\n"
     ]
    }
   ],
   "source": [
    "print('Cumulative crash count:',cas_df['crashCount'].sum())\n",
    "print('Cumulative count of minor injuries:',cas_df['minorInjuryCount'].sum())\n",
    "print('Cumulative count of serious injuries:',cas_df['seriousInjuryCount'].sum())\n",
    "print('Cumulative fatalities count:',cas_df['fatalCount'].sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b26fb1b",
   "metadata": {},
   "source": [
    "### Coordinates and identifiers\n",
    "Columns labeled `X` and `Y` clearly provide crash coordinates (in unspecified coordinate system), whereas `OBJECTID`, `areaUnitID`, and `tlaID` seem to be identifiers that might be useful for linking with other (GIS?) datasets. I will ignore most of these columns, but will rely on `region` for regional breakdown, `urban` for comparing fatality rates on open and urban roads, `holiday` for checking if holiday periods stand out, and `year` for temporal analysis (i.e. looking for trends over time)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59d8a947",
   "metadata": {},
   "source": [
    "## National trends\n",
    "\n",
    "It is important to get a sense for how things change over time: are they getting better, or are they improving?\n",
    "It's hard to develop this sense by just staring at the tabulated data, but we can break-down the crash counts by year and look at temporal trends. We can also adjust these trends using population data (from StatsNZ), and compare with other countries on per-capita basis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1113bd73",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "01fb9b70",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_125397/3857943919.py:8: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  nzpop_df = pd.read_csv('estimated-resident-population-of-new-zealand-at-30-june-2023.csv',\n"
     ]
    },
    {
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       "      <th>crashCount</th>\n",
       "      <th>fatalCount</th>\n",
       "      <th>minorInjuryCount</th>\n",
       "      <th>seriousInjuryCount</th>\n",
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       "      <th>2000</th>\n",
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       "      <td>1.443930</td>\n",
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       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>36125</td>\n",
       "      <td>455.0</td>\n",
       "      <td>10002.0</td>\n",
       "      <td>2473.0</td>\n",
       "      <td>3892075.0</td>\n",
       "      <td>928.168137</td>\n",
       "      <td>11.690422</td>\n",
       "      <td>34.532872</td>\n",
       "      <td>1.259516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>38045</td>\n",
       "      <td>405.0</td>\n",
       "      <td>11406.0</td>\n",
       "      <td>2649.0</td>\n",
       "      <td>3960325.0</td>\n",
       "      <td>960.653482</td>\n",
       "      <td>10.226433</td>\n",
       "      <td>36.943094</td>\n",
       "      <td>1.064529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>37950</td>\n",
       "      <td>461.0</td>\n",
       "      <td>11907.0</td>\n",
       "      <td>2618.0</td>\n",
       "      <td>4036675.0</td>\n",
       "      <td>940.130181</td>\n",
       "      <td>11.420290</td>\n",
       "      <td>38.274045</td>\n",
       "      <td>1.214756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>37051</td>\n",
       "      <td>435.0</td>\n",
       "      <td>11548.0</td>\n",
       "      <td>2552.0</td>\n",
       "      <td>4095275.0</td>\n",
       "      <td>904.725568</td>\n",
       "      <td>10.621997</td>\n",
       "      <td>38.055653</td>\n",
       "      <td>1.174057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>38364</td>\n",
       "      <td>405.0</td>\n",
       "      <td>12063.0</td>\n",
       "      <td>2585.0</td>\n",
       "      <td>4141850.0</td>\n",
       "      <td>926.252761</td>\n",
       "      <td>9.778239</td>\n",
       "      <td>38.181629</td>\n",
       "      <td>1.055677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>39778</td>\n",
       "      <td>393.0</td>\n",
       "      <td>12695.0</td>\n",
       "      <td>2688.0</td>\n",
       "      <td>4191325.0</td>\n",
       "      <td>949.055490</td>\n",
       "      <td>9.376510</td>\n",
       "      <td>38.672130</td>\n",
       "      <td>0.987983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>41661</td>\n",
       "      <td>421.0</td>\n",
       "      <td>13492.0</td>\n",
       "      <td>2712.0</td>\n",
       "      <td>4230800.0</td>\n",
       "      <td>984.707384</td>\n",
       "      <td>9.950837</td>\n",
       "      <td>38.894890</td>\n",
       "      <td>1.010537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>39535</td>\n",
       "      <td>366.0</td>\n",
       "      <td>12770.0</td>\n",
       "      <td>2587.0</td>\n",
       "      <td>4266325.0</td>\n",
       "      <td>926.675769</td>\n",
       "      <td>8.578812</td>\n",
       "      <td>38.844062</td>\n",
       "      <td>0.925762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>38247</td>\n",
       "      <td>384.0</td>\n",
       "      <td>12234.0</td>\n",
       "      <td>2464.0</td>\n",
       "      <td>4311375.0</td>\n",
       "      <td>887.118379</td>\n",
       "      <td>8.906671</td>\n",
       "      <td>38.429158</td>\n",
       "      <td>1.004000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>36870</td>\n",
       "      <td>375.0</td>\n",
       "      <td>11812.0</td>\n",
       "      <td>2315.0</td>\n",
       "      <td>4358250.0</td>\n",
       "      <td>845.981759</td>\n",
       "      <td>8.604371</td>\n",
       "      <td>38.315704</td>\n",
       "      <td>1.017087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>32450</td>\n",
       "      <td>284.0</td>\n",
       "      <td>10585.0</td>\n",
       "      <td>2088.0</td>\n",
       "      <td>4389475.0</td>\n",
       "      <td>739.268364</td>\n",
       "      <td>6.470022</td>\n",
       "      <td>39.053929</td>\n",
       "      <td>0.875193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>30443</td>\n",
       "      <td>308.0</td>\n",
       "      <td>10115.0</td>\n",
       "      <td>2101.0</td>\n",
       "      <td>4414025.0</td>\n",
       "      <td>689.687983</td>\n",
       "      <td>6.977758</td>\n",
       "      <td>40.127451</td>\n",
       "      <td>1.011727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>30109</td>\n",
       "      <td>253.0</td>\n",
       "      <td>9907.0</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>4453350.0</td>\n",
       "      <td>676.097769</td>\n",
       "      <td>5.681116</td>\n",
       "      <td>39.619383</td>\n",
       "      <td>0.840280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>29784</td>\n",
       "      <td>292.0</td>\n",
       "      <td>9223.0</td>\n",
       "      <td>2074.0</td>\n",
       "      <td>4530575.0</td>\n",
       "      <td>657.399999</td>\n",
       "      <td>6.445098</td>\n",
       "      <td>37.929761</td>\n",
       "      <td>0.980392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>32103</td>\n",
       "      <td>317.0</td>\n",
       "      <td>10177.0</td>\n",
       "      <td>2164.0</td>\n",
       "      <td>4625325.0</td>\n",
       "      <td>694.070146</td>\n",
       "      <td>6.853572</td>\n",
       "      <td>38.441890</td>\n",
       "      <td>0.987447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>37249</td>\n",
       "      <td>327.0</td>\n",
       "      <td>10232.0</td>\n",
       "      <td>2548.0</td>\n",
       "      <td>4729475.0</td>\n",
       "      <td>787.592703</td>\n",
       "      <td>6.914087</td>\n",
       "      <td>34.309646</td>\n",
       "      <td>0.877876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>39314</td>\n",
       "      <td>377.0</td>\n",
       "      <td>11176.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>4826525.0</td>\n",
       "      <td>814.540482</td>\n",
       "      <td>7.811003</td>\n",
       "      <td>35.704838</td>\n",
       "      <td>0.958946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>38469</td>\n",
       "      <td>378.0</td>\n",
       "      <td>12089.0</td>\n",
       "      <td>2601.0</td>\n",
       "      <td>4912300.0</td>\n",
       "      <td>783.115852</td>\n",
       "      <td>7.694970</td>\n",
       "      <td>38.186592</td>\n",
       "      <td>0.982609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>36919</td>\n",
       "      <td>350.0</td>\n",
       "      <td>12239.0</td>\n",
       "      <td>2506.0</td>\n",
       "      <td>4997950.0</td>\n",
       "      <td>738.682860</td>\n",
       "      <td>7.002871</td>\n",
       "      <td>39.938785</td>\n",
       "      <td>0.948021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>32808</td>\n",
       "      <td>318.0</td>\n",
       "      <td>10694.0</td>\n",
       "      <td>2173.0</td>\n",
       "      <td>5093850.0</td>\n",
       "      <td>644.070791</td>\n",
       "      <td>6.242822</td>\n",
       "      <td>39.219093</td>\n",
       "      <td>0.969276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>34080</td>\n",
       "      <td>318.0</td>\n",
       "      <td>10938.0</td>\n",
       "      <td>2317.0</td>\n",
       "      <td>5112675.0</td>\n",
       "      <td>666.578650</td>\n",
       "      <td>6.219836</td>\n",
       "      <td>38.893779</td>\n",
       "      <td>0.933099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>27982</td>\n",
       "      <td>375.0</td>\n",
       "      <td>11191.0</td>\n",
       "      <td>2473.0</td>\n",
       "      <td>5129850.0</td>\n",
       "      <td>545.474039</td>\n",
       "      <td>7.310155</td>\n",
       "      <td>48.831392</td>\n",
       "      <td>1.340147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>4412</td>\n",
       "      <td>114.0</td>\n",
       "      <td>4506.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>5210650.0</td>\n",
       "      <td>84.672738</td>\n",
       "      <td>2.187827</td>\n",
       "      <td>125.022665</td>\n",
       "      <td>2.583862</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      crashCount  fatalCount  minorInjuryCount  seriousInjuryCount  \\\n",
       "2000       31996       462.0            8776.0              2286.0   \n",
       "2001       36125       455.0           10002.0              2473.0   \n",
       "2002       38045       405.0           11406.0              2649.0   \n",
       "2003       37950       461.0           11907.0              2618.0   \n",
       "2004       37051       435.0           11548.0              2552.0   \n",
       "2005       38364       405.0           12063.0              2585.0   \n",
       "2006       39778       393.0           12695.0              2688.0   \n",
       "2007       41661       421.0           13492.0              2712.0   \n",
       "2008       39535       366.0           12770.0              2587.0   \n",
       "2009       38247       384.0           12234.0              2464.0   \n",
       "2010       36870       375.0           11812.0              2315.0   \n",
       "2011       32450       284.0           10585.0              2088.0   \n",
       "2012       30443       308.0           10115.0              2101.0   \n",
       "2013       30109       253.0            9907.0              2022.0   \n",
       "2014       29784       292.0            9223.0              2074.0   \n",
       "2015       32103       317.0           10177.0              2164.0   \n",
       "2016       37249       327.0           10232.0              2548.0   \n",
       "2017       39314       377.0           11176.0              2861.0   \n",
       "2018       38469       378.0           12089.0              2601.0   \n",
       "2019       36919       350.0           12239.0              2506.0   \n",
       "2020       32808       318.0           10694.0              2173.0   \n",
       "2021       34080       318.0           10938.0              2317.0   \n",
       "2022       27982       375.0           11191.0              2473.0   \n",
       "2023        4412       114.0            4506.0              1010.0   \n",
       "\n",
       "      estimatedPopulation  crashesPer100k  fatalitiesPer100k  \\\n",
       "2000            3862900.0      828.289627          11.959926   \n",
       "2001            3892075.0      928.168137          11.690422   \n",
       "2002            3960325.0      960.653482          10.226433   \n",
       "2003            4036675.0      940.130181          11.420290   \n",
       "2004            4095275.0      904.725568          10.621997   \n",
       "2005            4141850.0      926.252761           9.778239   \n",
       "2006            4191325.0      949.055490           9.376510   \n",
       "2007            4230800.0      984.707384           9.950837   \n",
       "2008            4266325.0      926.675769           8.578812   \n",
       "2009            4311375.0      887.118379           8.906671   \n",
       "2010            4358250.0      845.981759           8.604371   \n",
       "2011            4389475.0      739.268364           6.470022   \n",
       "2012            4414025.0      689.687983           6.977758   \n",
       "2013            4453350.0      676.097769           5.681116   \n",
       "2014            4530575.0      657.399999           6.445098   \n",
       "2015            4625325.0      694.070146           6.853572   \n",
       "2016            4729475.0      787.592703           6.914087   \n",
       "2017            4826525.0      814.540482           7.811003   \n",
       "2018            4912300.0      783.115852           7.694970   \n",
       "2019            4997950.0      738.682860           7.002871   \n",
       "2020            5093850.0      644.070791           6.242822   \n",
       "2021            5112675.0      666.578650           6.219836   \n",
       "2022            5129850.0      545.474039           7.310155   \n",
       "2023            5210650.0       84.672738           2.187827   \n",
       "\n",
       "      injuriesPer100Crashes  fatalitiesPer100Crashes  \n",
       "2000              34.573072                 1.443930  \n",
       "2001              34.532872                 1.259516  \n",
       "2002              36.943094                 1.064529  \n",
       "2003              38.274045                 1.214756  \n",
       "2004              38.055653                 1.174057  \n",
       "2005              38.181629                 1.055677  \n",
       "2006              38.672130                 0.987983  \n",
       "2007              38.894890                 1.010537  \n",
       "2008              38.844062                 0.925762  \n",
       "2009              38.429158                 1.004000  \n",
       "2010              38.315704                 1.017087  \n",
       "2011              39.053929                 0.875193  \n",
       "2012              40.127451                 1.011727  \n",
       "2013              39.619383                 0.840280  \n",
       "2014              37.929761                 0.980392  \n",
       "2015              38.441890                 0.987447  \n",
       "2016              34.309646                 0.877876  \n",
       "2017              35.704838                 0.958946  \n",
       "2018              38.186592                 0.982609  \n",
       "2019              39.938785                 0.948021  \n",
       "2020              39.219093                 0.969276  \n",
       "2021              38.893779                 0.933099  \n",
       "2022              48.831392                 1.340147  \n",
       "2023             125.022665                 2.583862  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aggregate crash, injury, and fatality counts for each year using a pivot operation\n",
    "annual_counts = pd.pivot_table(cas_df,\n",
    "                               values=['crashCount','minorInjuryCount','seriousInjuryCount','fatalCount'], \n",
    "                               index='crashYear',                     \n",
    "                               aggfunc=np.sum)\n",
    "\n",
    "# Create a commensurate dataframe for annual estimates of resident population\n",
    "nzpop_df = pd.read_csv('estimated-resident-population-of-new-zealand-at-30-june-2023.csv',\n",
    "                       parse_dates=True, index_col=0)\n",
    "nzpop_df.index = pd.to_datetime(nzpop_df.index, format=\"%b-%y\")\n",
    "nzpop_df = nzpop_df.resample('Y').mean()\n",
    "nzpop_df.index = nzpop_df.index.strftime('%Y').astype(int)\n",
    "nzpop_df.drop([1991,1992,1993,1994,1995,1996,1997,1998,1999], inplace=True)\n",
    "\n",
    "# Add the population estimates as another column to the annual_counts dataframe \n",
    "annual_counts = pd.concat([annual_counts,nzpop_df], axis=1)\n",
    "annual_counts.rename(columns={\"Estimated resident population\":\"estimatedPopulation\"}, inplace=True)\n",
    "\n",
    "# Calculate crash and fatality counts per capita\n",
    "annual_counts['crashesPer100k'] = (100000*annual_counts['crashCount'])/annual_counts['estimatedPopulation']\n",
    "annual_counts['fatalitiesPer100k'] = (100000*annual_counts['fatalCount'])/annual_counts['estimatedPopulation']\n",
    "annual_counts['injuriesPer100Crashes'] = 100*(annual_counts['minorInjuryCount']+annual_counts['seriousInjuryCount'])/annual_counts['crashCount']\n",
    "annual_counts['fatalitiesPer100Crashes'] = 100*annual_counts['fatalCount']/annual_counts['crashCount']\n",
    "annual_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7326065c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83b37f92a0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axs = annual_counts[['crashesPer100k','fatalitiesPer100k']].plot.bar(ylabel='per 100k residents',\n",
    "                                                               xlabel='year',\n",
    "                                                               subplots=True,\n",
    "                                                               title=['',''],\n",
    "                                                               legend=True,\n",
    "                                                               width=0.8\n",
    "                                                              )\n",
    "axs[0].legend(labels=['crashes'])\n",
    "axs[1].legend(labels=['fatalities'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bf5063ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83b37ea2f0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axs = annual_counts[['injuriesPer100Crashes','fatalitiesPer100Crashes']].plot.bar(ylabel='per 100 crashes',\n",
    "                                                               xlabel='year',\n",
    "                                                               subplots=True,\n",
    "                                                               title=['',''],\n",
    "                                                               legend=True,\n",
    "                                                               width=0.8\n",
    "                                                              )\n",
    "axs[0].legend(labels=['injuries'])\n",
    "axs[1].legend(labels=['fatalities'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf9507b3",
   "metadata": {},
   "source": [
    "### Holidays\n",
    "The dataset declares some crashes one of four holiday annual holiday periods: 'Christmas New Year', 'Easter','Labour Weekend', and 'Queens Birthday'. Although these periods are not defined in the dataset, they can be estimated to be about $10+5+3+3 = 21$ days, or $3$ weeks, which accounts for nearly 6% of a whole year. It might be useful to know how the combined holiday share of annual crashes and fatalities changed over the years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78d7f325",
   "metadata": {},
   "outputs": [],
   "source": [
    "hol_counts = pd.pivot_table(cas_df,\n",
    "                            values=['crashCount','fatalCount'],\n",
    "                            index='crashYear', \n",
    "                            columns='holiday', \n",
    "                            aggfunc=np.sum)\n",
    "hol_counts[('crashCount','combined')] = hol_counts[('crashCount')].sum(axis=1)\n",
    "hol_counts[('fatalCount','combined')] = hol_counts[('fatalCount')].sum(axis=1)\n",
    "#hol_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dbcb551d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7f83b6b581c0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hol_fracs = pd.DataFrame()\n",
    "hol_fracs.index = hol_counts.index\n",
    "hol_fracs['crashes'] = hol_counts[('crashCount','combined')]/annual_counts['crashCount']\n",
    "hol_fracs['fatalities'] = hol_counts[('fatalCount','combined')]/annual_counts['fatalCount']\n",
    "ax = hol_fracs.plot.bar(width=0.8,ylabel='holiday share of annual counts',xlabel='year')\n",
    "ax.axhline(y=0.06,color='black',linestyle='--',linewidth=0.6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bb4bd7d",
   "metadata": {},
   "source": [
    "### Urban vs open roads\n",
    "From regional variation one could glean crashes in cities are, on average, less lethal than crashes in the country. This observation is further supported by considering an aggregate split over the binary `urban` attribute, which presumably distinguishes between a) roads in urban areas with lower speed limits and b) roads outside urban areas, i.e. in the countryside, with higher speed limits.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f7b48286",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83b6b5b5e0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "urban_pt = pd.pivot_table(cas_df,\n",
    "                    values=['crashCount','fatalCount'],\n",
    "                    index='crashYear', \n",
    "                    columns='urban', \n",
    "                    aggfunc=np.sum)\n",
    "urban_pt[('fatalitiesPer100crashes','Urban')] = 100*urban_pt[('fatalCount','Urban')]/urban_pt[('crashCount','Urban')]\n",
    "urban_pt[('fatalitiesPer100crashes','Open')] = 100*urban_pt[('fatalCount','Open')]/urban_pt[('crashCount','Open')]\n",
    "ax = urban_pt['fatalitiesPer100crashes'].plot.bar(width=0.8, ylabel='fatalities per 100 crashes', xlabel='year',color=['red','green'])\n",
    "ax.legend(labels=['urban roads','open roads'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "badf3256",
   "metadata": {},
   "source": [
    "## Regional variation\n",
    "\n",
    "Here we split the national aggregate counts by regions as well as years."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9713336d",
   "metadata": {},
   "source": [
    "Found [this solution from stackoverflow](https://stackoverflow.com/questions/68382133/pandas-stacked-histogram-from-column-of-dataframe-by-values-of-another-column) to plot a histogram stacked by \"region\", but it caused my Python kernel to crash, presumably due to excessive memory usage when dealing with the entire table. Extracting just the three relevant columns into a separate dataframe and applying the solution to this smaller dataframe resolves the issue. However, I don't really understand the solution on StackOverflow, so I've decided to proceed by aggregating using a pivot operation first and then plotting a stacked bar chart instead of a stacked histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5889d294",
   "metadata": {},
   "outputs": [],
   "source": [
    "pt = pd.pivot_table(cas_df,\n",
    "                    values='crashCount',\n",
    "                    index='crashYear', \n",
    "                    columns='region', \n",
    "                    aggfunc=np.sum)\n",
    "for column in pt.columns: \n",
    "    pt[column] = pt[column]/annual_counts['crashCount'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f62e0739",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>region</th>\n",
       "      <th>Auckland Region</th>\n",
       "      <th>Bay of Plenty Region</th>\n",
       "      <th>Canterbury Region</th>\n",
       "      <th>Gisborne Region</th>\n",
       "      <th>Hawke's Bay Region</th>\n",
       "      <th>Manawatū-Whanganui Region</th>\n",
       "      <th>Marlborough Region</th>\n",
       "      <th>Nelson Region</th>\n",
       "      <th>Northland Region</th>\n",
       "      <th>Otago Region</th>\n",
       "      <th>Southland Region</th>\n",
       "      <th>Taranaki Region</th>\n",
       "      <th>Tasman Region</th>\n",
       "      <th>Waikato Region</th>\n",
       "      <th>Wellington Region</th>\n",
       "      <th>West Coast Region</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crashYear</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>2000</th>\n",
       "      <td>0.383954</td>\n",
       "      <td>0.041755</td>\n",
       "      <td>0.111358</td>\n",
       "      <td>0.009970</td>\n",
       "      <td>0.038630</td>\n",
       "      <td>0.062008</td>\n",
       "      <td>0.008501</td>\n",
       "      <td>0.009001</td>\n",
       "      <td>0.031723</td>\n",
       "      <td>0.048537</td>\n",
       "      <td>0.022409</td>\n",
       "      <td>0.023784</td>\n",
       "      <td>0.009251</td>\n",
       "      <td>0.085917</td>\n",
       "      <td>0.099919</td>\n",
       "      <td>0.009189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>0.378408</td>\n",
       "      <td>0.048194</td>\n",
       "      <td>0.107516</td>\n",
       "      <td>0.012042</td>\n",
       "      <td>0.036484</td>\n",
       "      <td>0.056415</td>\n",
       "      <td>0.008388</td>\n",
       "      <td>0.009080</td>\n",
       "      <td>0.031003</td>\n",
       "      <td>0.054561</td>\n",
       "      <td>0.025689</td>\n",
       "      <td>0.022256</td>\n",
       "      <td>0.008166</td>\n",
       "      <td>0.100706</td>\n",
       "      <td>0.089273</td>\n",
       "      <td>0.007779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>0.389302</td>\n",
       "      <td>0.051281</td>\n",
       "      <td>0.096465</td>\n",
       "      <td>0.011828</td>\n",
       "      <td>0.037718</td>\n",
       "      <td>0.058799</td>\n",
       "      <td>0.010172</td>\n",
       "      <td>0.010277</td>\n",
       "      <td>0.032488</td>\n",
       "      <td>0.059324</td>\n",
       "      <td>0.025470</td>\n",
       "      <td>0.022053</td>\n",
       "      <td>0.008437</td>\n",
       "      <td>0.091076</td>\n",
       "      <td>0.084584</td>\n",
       "      <td>0.007097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>0.380632</td>\n",
       "      <td>0.059736</td>\n",
       "      <td>0.093491</td>\n",
       "      <td>0.010962</td>\n",
       "      <td>0.041238</td>\n",
       "      <td>0.054466</td>\n",
       "      <td>0.009091</td>\n",
       "      <td>0.010777</td>\n",
       "      <td>0.040896</td>\n",
       "      <td>0.055389</td>\n",
       "      <td>0.025033</td>\n",
       "      <td>0.020659</td>\n",
       "      <td>0.010145</td>\n",
       "      <td>0.096232</td>\n",
       "      <td>0.080711</td>\n",
       "      <td>0.007194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>0.362365</td>\n",
       "      <td>0.057839</td>\n",
       "      <td>0.089660</td>\n",
       "      <td>0.012145</td>\n",
       "      <td>0.044344</td>\n",
       "      <td>0.053899</td>\n",
       "      <td>0.010202</td>\n",
       "      <td>0.011525</td>\n",
       "      <td>0.041564</td>\n",
       "      <td>0.059108</td>\n",
       "      <td>0.023940</td>\n",
       "      <td>0.020377</td>\n",
       "      <td>0.009419</td>\n",
       "      <td>0.099269</td>\n",
       "      <td>0.091064</td>\n",
       "      <td>0.009446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>0.354186</td>\n",
       "      <td>0.059457</td>\n",
       "      <td>0.097018</td>\n",
       "      <td>0.012512</td>\n",
       "      <td>0.045094</td>\n",
       "      <td>0.054400</td>\n",
       "      <td>0.010348</td>\n",
       "      <td>0.009175</td>\n",
       "      <td>0.037796</td>\n",
       "      <td>0.055599</td>\n",
       "      <td>0.024893</td>\n",
       "      <td>0.021114</td>\n",
       "      <td>0.007533</td>\n",
       "      <td>0.108696</td>\n",
       "      <td>0.090058</td>\n",
       "      <td>0.008107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.345995</td>\n",
       "      <td>0.057720</td>\n",
       "      <td>0.105837</td>\n",
       "      <td>0.011212</td>\n",
       "      <td>0.040500</td>\n",
       "      <td>0.051461</td>\n",
       "      <td>0.010357</td>\n",
       "      <td>0.010307</td>\n",
       "      <td>0.038790</td>\n",
       "      <td>0.053924</td>\n",
       "      <td>0.024410</td>\n",
       "      <td>0.021142</td>\n",
       "      <td>0.007793</td>\n",
       "      <td>0.108276</td>\n",
       "      <td>0.101488</td>\n",
       "      <td>0.008070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.055544</td>\n",
       "      <td>0.109023</td>\n",
       "      <td>0.010153</td>\n",
       "      <td>0.044262</td>\n",
       "      <td>0.047334</td>\n",
       "      <td>0.010057</td>\n",
       "      <td>0.009793</td>\n",
       "      <td>0.039125</td>\n",
       "      <td>0.053623</td>\n",
       "      <td>0.023475</td>\n",
       "      <td>0.023883</td>\n",
       "      <td>0.008977</td>\n",
       "      <td>0.102782</td>\n",
       "      <td>0.117160</td>\n",
       "      <td>0.008137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.342684</td>\n",
       "      <td>0.053016</td>\n",
       "      <td>0.105729</td>\n",
       "      <td>0.012723</td>\n",
       "      <td>0.039307</td>\n",
       "      <td>0.048084</td>\n",
       "      <td>0.009789</td>\n",
       "      <td>0.010548</td>\n",
       "      <td>0.039459</td>\n",
       "      <td>0.055520</td>\n",
       "      <td>0.025800</td>\n",
       "      <td>0.024409</td>\n",
       "      <td>0.008828</td>\n",
       "      <td>0.098874</td>\n",
       "      <td>0.113520</td>\n",
       "      <td>0.008094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.336392</td>\n",
       "      <td>0.057730</td>\n",
       "      <td>0.102936</td>\n",
       "      <td>0.013570</td>\n",
       "      <td>0.040840</td>\n",
       "      <td>0.047219</td>\n",
       "      <td>0.009831</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>0.040526</td>\n",
       "      <td>0.057625</td>\n",
       "      <td>0.027950</td>\n",
       "      <td>0.024133</td>\n",
       "      <td>0.008837</td>\n",
       "      <td>0.100034</td>\n",
       "      <td>0.107564</td>\n",
       "      <td>0.009857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.345891</td>\n",
       "      <td>0.056442</td>\n",
       "      <td>0.094142</td>\n",
       "      <td>0.013724</td>\n",
       "      <td>0.040738</td>\n",
       "      <td>0.054977</td>\n",
       "      <td>0.009601</td>\n",
       "      <td>0.010686</td>\n",
       "      <td>0.039083</td>\n",
       "      <td>0.055492</td>\n",
       "      <td>0.027095</td>\n",
       "      <td>0.023217</td>\n",
       "      <td>0.008055</td>\n",
       "      <td>0.102251</td>\n",
       "      <td>0.103797</td>\n",
       "      <td>0.009683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>0.346965</td>\n",
       "      <td>0.059846</td>\n",
       "      <td>0.100647</td>\n",
       "      <td>0.012142</td>\n",
       "      <td>0.038490</td>\n",
       "      <td>0.059076</td>\n",
       "      <td>0.009861</td>\n",
       "      <td>0.009153</td>\n",
       "      <td>0.037720</td>\n",
       "      <td>0.056795</td>\n",
       "      <td>0.025146</td>\n",
       "      <td>0.024807</td>\n",
       "      <td>0.009553</td>\n",
       "      <td>0.109337</td>\n",
       "      <td>0.087889</td>\n",
       "      <td>0.008351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.356864</td>\n",
       "      <td>0.053543</td>\n",
       "      <td>0.107085</td>\n",
       "      <td>0.011398</td>\n",
       "      <td>0.033801</td>\n",
       "      <td>0.056400</td>\n",
       "      <td>0.009625</td>\n",
       "      <td>0.009690</td>\n",
       "      <td>0.039944</td>\n",
       "      <td>0.055481</td>\n",
       "      <td>0.025720</td>\n",
       "      <td>0.023519</td>\n",
       "      <td>0.008639</td>\n",
       "      <td>0.105969</td>\n",
       "      <td>0.089709</td>\n",
       "      <td>0.008672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.354910</td>\n",
       "      <td>0.054236</td>\n",
       "      <td>0.109801</td>\n",
       "      <td>0.012056</td>\n",
       "      <td>0.034707</td>\n",
       "      <td>0.054602</td>\n",
       "      <td>0.008835</td>\n",
       "      <td>0.009565</td>\n",
       "      <td>0.039623</td>\n",
       "      <td>0.053439</td>\n",
       "      <td>0.025109</td>\n",
       "      <td>0.022252</td>\n",
       "      <td>0.009632</td>\n",
       "      <td>0.101000</td>\n",
       "      <td>0.098575</td>\n",
       "      <td>0.008502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.357239</td>\n",
       "      <td>0.052511</td>\n",
       "      <td>0.112476</td>\n",
       "      <td>0.009905</td>\n",
       "      <td>0.033508</td>\n",
       "      <td>0.056104</td>\n",
       "      <td>0.009468</td>\n",
       "      <td>0.009166</td>\n",
       "      <td>0.042472</td>\n",
       "      <td>0.052713</td>\n",
       "      <td>0.027431</td>\n",
       "      <td>0.020212</td>\n",
       "      <td>0.007151</td>\n",
       "      <td>0.105224</td>\n",
       "      <td>0.092164</td>\n",
       "      <td>0.008864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.356415</td>\n",
       "      <td>0.056038</td>\n",
       "      <td>0.101392</td>\n",
       "      <td>0.008847</td>\n",
       "      <td>0.031212</td>\n",
       "      <td>0.056942</td>\n",
       "      <td>0.009874</td>\n",
       "      <td>0.008753</td>\n",
       "      <td>0.042551</td>\n",
       "      <td>0.057783</td>\n",
       "      <td>0.026789</td>\n",
       "      <td>0.021026</td>\n",
       "      <td>0.008068</td>\n",
       "      <td>0.110550</td>\n",
       "      <td>0.090926</td>\n",
       "      <td>0.009688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.357271</td>\n",
       "      <td>0.060861</td>\n",
       "      <td>0.097291</td>\n",
       "      <td>0.009718</td>\n",
       "      <td>0.035974</td>\n",
       "      <td>0.051008</td>\n",
       "      <td>0.011195</td>\n",
       "      <td>0.009343</td>\n",
       "      <td>0.040296</td>\n",
       "      <td>0.054176</td>\n",
       "      <td>0.025262</td>\n",
       "      <td>0.019920</td>\n",
       "      <td>0.009638</td>\n",
       "      <td>0.107090</td>\n",
       "      <td>0.097103</td>\n",
       "      <td>0.009906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.350689</td>\n",
       "      <td>0.058402</td>\n",
       "      <td>0.093097</td>\n",
       "      <td>0.009844</td>\n",
       "      <td>0.035280</td>\n",
       "      <td>0.055654</td>\n",
       "      <td>0.010963</td>\n",
       "      <td>0.008903</td>\n",
       "      <td>0.042479</td>\n",
       "      <td>0.049016</td>\n",
       "      <td>0.020705</td>\n",
       "      <td>0.019815</td>\n",
       "      <td>0.011421</td>\n",
       "      <td>0.119245</td>\n",
       "      <td>0.100600</td>\n",
       "      <td>0.010403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.328368</td>\n",
       "      <td>0.061504</td>\n",
       "      <td>0.092282</td>\n",
       "      <td>0.012608</td>\n",
       "      <td>0.038421</td>\n",
       "      <td>0.057423</td>\n",
       "      <td>0.011490</td>\n",
       "      <td>0.009514</td>\n",
       "      <td>0.047805</td>\n",
       "      <td>0.051444</td>\n",
       "      <td>0.021342</td>\n",
       "      <td>0.021810</td>\n",
       "      <td>0.010138</td>\n",
       "      <td>0.121968</td>\n",
       "      <td>0.099691</td>\n",
       "      <td>0.009774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.319212</td>\n",
       "      <td>0.066226</td>\n",
       "      <td>0.088708</td>\n",
       "      <td>0.012622</td>\n",
       "      <td>0.039709</td>\n",
       "      <td>0.059807</td>\n",
       "      <td>0.012189</td>\n",
       "      <td>0.010266</td>\n",
       "      <td>0.045234</td>\n",
       "      <td>0.055229</td>\n",
       "      <td>0.023403</td>\n",
       "      <td>0.022861</td>\n",
       "      <td>0.010157</td>\n",
       "      <td>0.121238</td>\n",
       "      <td>0.099001</td>\n",
       "      <td>0.010293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>0.301451</td>\n",
       "      <td>0.065411</td>\n",
       "      <td>0.095800</td>\n",
       "      <td>0.015515</td>\n",
       "      <td>0.044044</td>\n",
       "      <td>0.066295</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>0.010119</td>\n",
       "      <td>0.047610</td>\n",
       "      <td>0.052518</td>\n",
       "      <td>0.023805</td>\n",
       "      <td>0.025055</td>\n",
       "      <td>0.010455</td>\n",
       "      <td>0.120276</td>\n",
       "      <td>0.098330</td>\n",
       "      <td>0.009114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>0.301086</td>\n",
       "      <td>0.066579</td>\n",
       "      <td>0.094425</td>\n",
       "      <td>0.014114</td>\n",
       "      <td>0.044542</td>\n",
       "      <td>0.070540</td>\n",
       "      <td>0.010358</td>\n",
       "      <td>0.009683</td>\n",
       "      <td>0.045951</td>\n",
       "      <td>0.049149</td>\n",
       "      <td>0.023327</td>\n",
       "      <td>0.027788</td>\n",
       "      <td>0.010769</td>\n",
       "      <td>0.119777</td>\n",
       "      <td>0.100792</td>\n",
       "      <td>0.007218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>0.304339</td>\n",
       "      <td>0.065113</td>\n",
       "      <td>0.096634</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>0.044815</td>\n",
       "      <td>0.070760</td>\n",
       "      <td>0.009113</td>\n",
       "      <td>0.008899</td>\n",
       "      <td>0.048710</td>\n",
       "      <td>0.049210</td>\n",
       "      <td>0.023158</td>\n",
       "      <td>0.025338</td>\n",
       "      <td>0.009292</td>\n",
       "      <td>0.123865</td>\n",
       "      <td>0.090022</td>\n",
       "      <td>0.008327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>0.279692</td>\n",
       "      <td>0.064370</td>\n",
       "      <td>0.110154</td>\n",
       "      <td>0.011786</td>\n",
       "      <td>0.040118</td>\n",
       "      <td>0.073663</td>\n",
       "      <td>0.010879</td>\n",
       "      <td>0.009519</td>\n",
       "      <td>0.051451</td>\n",
       "      <td>0.054397</td>\n",
       "      <td>0.021532</td>\n",
       "      <td>0.027425</td>\n",
       "      <td>0.013599</td>\n",
       "      <td>0.128286</td>\n",
       "      <td>0.088169</td>\n",
       "      <td>0.010653</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "region     Auckland Region  Bay of Plenty Region  Canterbury Region  \\\n",
       "crashYear                                                             \n",
       "2000              0.383954              0.041755           0.111358   \n",
       "2001              0.378408              0.048194           0.107516   \n",
       "2002              0.389302              0.051281           0.096465   \n",
       "2003              0.380632              0.059736           0.093491   \n",
       "2004              0.362365              0.057839           0.089660   \n",
       "2005              0.354186              0.059457           0.097018   \n",
       "2006              0.345995              0.057720           0.105837   \n",
       "2007              0.333333              0.055544           0.109023   \n",
       "2008              0.342684              0.053016           0.105729   \n",
       "2009              0.336392              0.057730           0.102936   \n",
       "2010              0.345891              0.056442           0.094142   \n",
       "2011              0.346965              0.059846           0.100647   \n",
       "2012              0.356864              0.053543           0.107085   \n",
       "2013              0.354910              0.054236           0.109801   \n",
       "2014              0.357239              0.052511           0.112476   \n",
       "2015              0.356415              0.056038           0.101392   \n",
       "2016              0.357271              0.060861           0.097291   \n",
       "2017              0.350689              0.058402           0.093097   \n",
       "2018              0.328368              0.061504           0.092282   \n",
       "2019              0.319212              0.066226           0.088708   \n",
       "2020              0.301451              0.065411           0.095800   \n",
       "2021              0.301086              0.066579           0.094425   \n",
       "2022              0.304339              0.065113           0.096634   \n",
       "2023              0.279692              0.064370           0.110154   \n",
       "\n",
       "region     Gisborne Region  Hawke's Bay Region  Manawatū-Whanganui Region  \\\n",
       "crashYear                                                                   \n",
       "2000              0.009970            0.038630                   0.062008   \n",
       "2001              0.012042            0.036484                   0.056415   \n",
       "2002              0.011828            0.037718                   0.058799   \n",
       "2003              0.010962            0.041238                   0.054466   \n",
       "2004              0.012145            0.044344                   0.053899   \n",
       "2005              0.012512            0.045094                   0.054400   \n",
       "2006              0.011212            0.040500                   0.051461   \n",
       "2007              0.010153            0.044262                   0.047334   \n",
       "2008              0.012723            0.039307                   0.048084   \n",
       "2009              0.013570            0.040840                   0.047219   \n",
       "2010              0.013724            0.040738                   0.054977   \n",
       "2011              0.012142            0.038490                   0.059076   \n",
       "2012              0.011398            0.033801                   0.056400   \n",
       "2013              0.012056            0.034707                   0.054602   \n",
       "2014              0.009905            0.033508                   0.056104   \n",
       "2015              0.008847            0.031212                   0.056942   \n",
       "2016              0.009718            0.035974                   0.051008   \n",
       "2017              0.009844            0.035280                   0.055654   \n",
       "2018              0.012608            0.038421                   0.057423   \n",
       "2019              0.012622            0.039709                   0.059807   \n",
       "2020              0.015515            0.044044                   0.066295   \n",
       "2021              0.014114            0.044542                   0.070540   \n",
       "2022              0.014724            0.044815                   0.070760   \n",
       "2023              0.011786            0.040118                   0.073663   \n",
       "\n",
       "region     Marlborough Region  Nelson Region  Northland Region  Otago Region  \\\n",
       "crashYear                                                                      \n",
       "2000                 0.008501       0.009001          0.031723      0.048537   \n",
       "2001                 0.008388       0.009080          0.031003      0.054561   \n",
       "2002                 0.010172       0.010277          0.032488      0.059324   \n",
       "2003                 0.009091       0.010777          0.040896      0.055389   \n",
       "2004                 0.010202       0.011525          0.041564      0.059108   \n",
       "2005                 0.010348       0.009175          0.037796      0.055599   \n",
       "2006                 0.010357       0.010307          0.038790      0.053924   \n",
       "2007                 0.010057       0.009793          0.039125      0.053623   \n",
       "2008                 0.009789       0.010548          0.039459      0.055520   \n",
       "2009                 0.009831       0.011034          0.040526      0.057625   \n",
       "2010                 0.009601       0.010686          0.039083      0.055492   \n",
       "2011                 0.009861       0.009153          0.037720      0.056795   \n",
       "2012                 0.009625       0.009690          0.039944      0.055481   \n",
       "2013                 0.008835       0.009565          0.039623      0.053439   \n",
       "2014                 0.009468       0.009166          0.042472      0.052713   \n",
       "2015                 0.009874       0.008753          0.042551      0.057783   \n",
       "2016                 0.011195       0.009343          0.040296      0.054176   \n",
       "2017                 0.010963       0.008903          0.042479      0.049016   \n",
       "2018                 0.011490       0.009514          0.047805      0.051444   \n",
       "2019                 0.012189       0.010266          0.045234      0.055229   \n",
       "2020                 0.011034       0.010119          0.047610      0.052518   \n",
       "2021                 0.010358       0.009683          0.045951      0.049149   \n",
       "2022                 0.009113       0.008899          0.048710      0.049210   \n",
       "2023                 0.010879       0.009519          0.051451      0.054397   \n",
       "\n",
       "region     Southland Region  Taranaki Region  Tasman Region  Waikato Region  \\\n",
       "crashYear                                                                     \n",
       "2000               0.022409         0.023784       0.009251        0.085917   \n",
       "2001               0.025689         0.022256       0.008166        0.100706   \n",
       "2002               0.025470         0.022053       0.008437        0.091076   \n",
       "2003               0.025033         0.020659       0.010145        0.096232   \n",
       "2004               0.023940         0.020377       0.009419        0.099269   \n",
       "2005               0.024893         0.021114       0.007533        0.108696   \n",
       "2006               0.024410         0.021142       0.007793        0.108276   \n",
       "2007               0.023475         0.023883       0.008977        0.102782   \n",
       "2008               0.025800         0.024409       0.008828        0.098874   \n",
       "2009               0.027950         0.024133       0.008837        0.100034   \n",
       "2010               0.027095         0.023217       0.008055        0.102251   \n",
       "2011               0.025146         0.024807       0.009553        0.109337   \n",
       "2012               0.025720         0.023519       0.008639        0.105969   \n",
       "2013               0.025109         0.022252       0.009632        0.101000   \n",
       "2014               0.027431         0.020212       0.007151        0.105224   \n",
       "2015               0.026789         0.021026       0.008068        0.110550   \n",
       "2016               0.025262         0.019920       0.009638        0.107090   \n",
       "2017               0.020705         0.019815       0.011421        0.119245   \n",
       "2018               0.021342         0.021810       0.010138        0.121968   \n",
       "2019               0.023403         0.022861       0.010157        0.121238   \n",
       "2020               0.023805         0.025055       0.010455        0.120276   \n",
       "2021               0.023327         0.027788       0.010769        0.119777   \n",
       "2022               0.023158         0.025338       0.009292        0.123865   \n",
       "2023               0.021532         0.027425       0.013599        0.128286   \n",
       "\n",
       "region     Wellington Region  West Coast Region  \n",
       "crashYear                                        \n",
       "2000                0.099919           0.009189  \n",
       "2001                0.089273           0.007779  \n",
       "2002                0.084584           0.007097  \n",
       "2003                0.080711           0.007194  \n",
       "2004                0.091064           0.009446  \n",
       "2005                0.090058           0.008107  \n",
       "2006                0.101488           0.008070  \n",
       "2007                0.117160           0.008137  \n",
       "2008                0.113520           0.008094  \n",
       "2009                0.107564           0.009857  \n",
       "2010                0.103797           0.009683  \n",
       "2011                0.087889           0.008351  \n",
       "2012                0.089709           0.008672  \n",
       "2013                0.098575           0.008502  \n",
       "2014                0.092164           0.008864  \n",
       "2015                0.090926           0.009688  \n",
       "2016                0.097103           0.009906  \n",
       "2017                0.100600           0.010403  \n",
       "2018                0.099691           0.009774  \n",
       "2019                0.099001           0.010293  \n",
       "2020                0.098330           0.009114  \n",
       "2021                0.100792           0.007218  \n",
       "2022                0.090022           0.008327  \n",
       "2023                0.088169           0.010653  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fd18cac2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83b67bace0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wHh4e1KxZk2HDhlGnTh1lqWsvLy/mz59PeHg4NWvWZOnSpaxYsULpwapbty5z5sxhxowZ1KpVizVr1hAWFqbWTnp6OoMGDVKupVq1akqPU+XKlZk4cSKjR4+mYsWKWVZRex1/f3/OnTvHDz/8QJ06ddi3bx9//vknLVq0oH79+gQHB1OpUiWl/KpVq6hYsSItW7bE29sbPz8/TE1NMTAwyLZ+IyMjdu3axe3bt2nYsCGffvopH3zwAQsXLtQoTvH2yGpvQgghhHhnDV+3taBDeC1bW9tsFxiwsbHJdr9KpWLIkCEMGTIk2/rGjx/P+PHjc2yvT58+9OnTJ1exde7cmc6dO7+yzIABAxgwYECOx4cOHcrQoUPV9nXv3l35/nXzeyZMmMCECRNeWcbNzS3be2VlZaU2b6lhw4b88ssvOdZjaWnJ9u3ble2///6bmzdv4uDgoOx7uZ3atWuzd+/eHOvMbknrF98bJN4uSX6EEEIIIYQA9u7dS3JyMrVr1yYpKYmRI0dia2tLy5YtCzo0oSWS/BRzrWIG5bGGc68vIoQQQghRBKSlpTF27FguX76MqakpTZs2Zc2aNa9935EoOiT5KULynqiAJCtCCCGEENnz8PDAw8OjoMMQ+UgWPBBCCCGEEEIUC9Lzk49kSJkQuSd/L0IIIYTIb5L8CK3S9gOsDPUTb6oo/O7kR8InSaQoLOR3UQhRGEnyI4QQQhRzReHDAiGE0AaZ8yOEEEIIIYQoFqTnRxQ7MhRDvKni+LtTHK85PxS+IcHycxFCFE+S/Px/0uUvhBD5Lz/+rS18iUXWOoV4m2JiYnB3d+fOnTuULl2ayMhIAgMDuXv3LgChoaFs3ryZEydOFGicRYHcq3ePJD9CCCGEeGd91X/vW21v0JJWuS67ZMkSgoKCuHPnDiVKPHskS05OxtzcnGbNmhETE6OUfZ7QXLx4kapVq+YpxhEjRjB48OA81ZEdlUrFpk2b8PLy0nrdL3Nzc2Pfvn0A6OvrY21tTc+ePRk9ejQqlUpr7eTXvRIFR5IfIYTG5JNxIYTIO3d3d5KTkzl69CiNGzcGYP/+/VhYWHD48GEeP36MgYEBANHR0VhbW+c58QEwMTHBxMQkz/UUND8/PyZNmkRqaip79+6lb9++lC5dmgEDBmitjXflXon/IwseCFEMtIoZlKcvIYQQ2ufk5ISlpWWWHp5OnTphZ2fHb7/9prbf3d0dgIyMDMLCwrCzs8PQ0JC6devy448/5rrd0NBQ6tWrp2z7+vri5eVFeHg4lpaWlC1blkGDBpGWlqaUSUpKwtPTE0NDQ+zs7Pjuu++wtbVl3rx5ANja2gLg7e2NSqVStgEWL15M1apV0dPTw8nJidWrV6vFo1Kp+Oabb/D29sbIyAhHR0e2bNny2uswMjLCwsICGxsbevbsSZ06ddi9e7dyPDU1lREjRlC5cmWMjY15//331e41wLJly7CyssLIyAhvb2/mzJlD6dKlc7xXGRkZTJo0iSpVqqCvr0+9evXYuXOncjwhIQGVSsXGjRtxd3fHyMiIunXrcujQoddej3g7pOdHiEJIJjMLIUTx4O7uTnR0NKNHjwae9fCMHDmS9PR0oqOjcXNz49GjRxw+fJhevXoBEBYWxv/+9z+WLFmCo6Mjv/76K19++SXly5fH1dX1jeKIjo7G0tKS6OhoLl68SJcuXahXrx5+fn4A9OjRg//++4+YmBhKlizJsGHDuHnzpnJ+XFwcFSpUYMWKFbRt2xZdXV0ANm3axJAhQ5g3bx6tW7dm69at9OzZkypVqijJHMDEiROZOXMms2bNYsGCBXTr1o2//vqLMmXKvDb2zMxMDhw4wPnz53F0dFT2+/v7c/bsWdauXUulSpXYtGkTbdu25fTp0zg6OhIbG0v//v2ZMWMGHTt2ZM+ePUyYMOGVbc2fP5/Zs2ezdOlS6tevz/Lly+nYsSN//PGHWtvjxo0jPDwcR0dHxo0bR9euXbl48aIyvFEUHPkJCJFHMgRMCCHEm3J3dycwMJCnT5/y6NEjjh8/jqurK2lpaSxZsgSAQ4cOkZqairu7O6mpqUybNo09e/bQpEkTAOzt7Tlw4ABLly594+TH3NychQsXoquri7OzM56enkRFReHn58f58+fZs2cPcXFxuLi4APDNN9+oPeyXL18egNKlS2NhYaHsDw8Px9fXl4EDBwIwbNgwfvvtN8LDw9WSH19fX7p27QrAtGnTiIiI4MiRI7Rt2zbHmBctWsQ333zDkydPSEtLw8DAgICAAAASExNZsWIFiYmJVKpUCXg2f2fnzp2sWLGCadOmsWDBAj766CNGjBgBQLVq1Th48CBbt27Nsc3w8HBGjRrF559/DsCMGTOIjo5m3rx5fPXVV0q5ESNG4OnpCTxL7GrWrMnFixdxdnZ+5c9B5D8Z9iaEEEIIUUDc3NxISUkhLi6O/fv3U61aNaUH5/m8n5iYGOzt7bG2tubixYs8fPiQNm3aKPNRTExMWLVqFZcuXXrjOGrWrKn01gBYWloqPTvx8fGUKFGCBg0aKMcdHBwwNzd/bb3nzp2jWbNmavuaNWvGuXPqH/rVqVNH+d7Y2BgzMzO1nqXsdOvWjRMnThAbG8tHH33EuHHjaNq0KQCnT58mPT2datWqqd2nffv2KfcpPj6eRo0aqdX58vaL7t+/zz///KPx9VhaWgK89nrE2yE9P0IIIYQQBcTBwYEqVaoQHR3NnTt3lJ6bSpUqYWVlxcGDB4mOjqZVq2eryCUnJwOwbds2KleurFaXvr7+G8dRsmRJtW2VSkVGRsYb1/c22i9VqhQODg4ArF+/HgcHBxo3bkzr1q1JTk5GV1eXY8eOqSV1wFtZwODF63m++tzbvJ8iZ9LzI4QQQghRgNzd3YmJiSEmJgY3Nzdlf8uWLdmxYwdHjhxRhojVqFEDfX19EhMTcXBwUPuysrLKl/icnJx4+vQpx48fV/ZdvHiRO3fuqJUrWbIk6enpavuqV69ObGys2r7Y2Fhq1Kih1RhNTEwYMmQII0aMIDMzk/r165Oens7Nmzez3Kfnw/KcnJyIi4tTq+fl7ReZmZlRqVKlt3I9Iv9Iz48QQgghRAFyd3dXVld7cc6Oq6sr/v7+PHnyREl+TE1NGTFiBEOHDiUjI4PmzZtz7949YmNjMTMzw8fHR+vxOTs707p1a/r27cvixYspWbIkw4cPx9DQUO2dOra2tkRFRdGsWTP09fUxNzcnKCiIzp07U79+fVq3bs3PP//Mxo0b2bNnj9bj7NevH5MnT2bDhg18+umndOvWjR49ejB79mzq16/Pv//+S1RUFHXq1MHT05PBgwfTsmVL5syZQ4cOHdi7dy87dux45XuCgoKCCAkJoWrVqtSrV48VK1Zw4sQJ1qxZo/XrEflDen6EEEIIIQqQu7s7jx49wsHBgYoVKyr7XV1defDggbIk9nOTJ09mwoQJhIWFUb16ddq2bcu2bduws7PLtxhXrVpFxYoVadmyJd7e3vj5+WFqaqq8hwhg9uzZ7N69GysrK+rXrw+Al5cX8+fPJzw8nJo1a7J06VJWrFih1sOlLWXKlKFHjx6EhoaSkZHBihUr6NGjB8OHD8fJyQkvLy/i4uKwtrYGns3VWbJkCXPmzKFu3brs3LmToUOHql3TywICAhg2bBjDhw+ndu3a7Ny5ky1btqgt/iAKN1VmZmZmQQfxNt2/f59SpUpx7949zMzMlP3nnKvnue7q59Unu+W1Tm3Xlx91Fvb68qPO4hhjcbzm/Kgzv+vLjzoLW335UWdxjLEoXnNO/38DPH78mCtXrmBnZ/fKB1ehPX///TdWVlbs2bOHDz74oKDD0Zrnq9vt37+/oEMRGtDk3wAZ9iaEEEIIIV5p7969JCcnU7t2bZKSkhg5ciS2tra0bNmyoEPLk/DwcNq0aYOxsTE7duxg5cqVLFq0qKDDEvlIkh8hhBBCCPFKaWlpjB07lsuXL2NqakrTpk1Zs2ZNllXaipojR44wc+ZMHjx4gL29PREREfTp06egwxL5SJIfIYQQQgjxSh4eHnh4eBR0GFq3fv36gg5BvGWy4IEQQgghhBCiWJDkRwghhBBCCFEsSPIjhBBCCCGEKBYk+RFCCCGEEEIUC5L8CCGEEEIIIYoFSX6EEEIIIYQQxYIkP0IIIYQQ75CYmBhUKhV3794FIDIyktKlSxdoTG9bQkICKpWKEydOFHQoopCR9/wIIYQQ4p11zrn6W22v+vlzuS67ZMkSgoKCuHPnDiVKPHskS05OxtzcnGbNmhETE6OUjYmJwd3dnYsXL1K1atVX1tu0aVOSkpIoVarUG11DdmxtbQkMDCQwMDBP9URGRtKzZ08AVCoVFStWpGXLlsyaNQtra2stRPqMlZUVSUlJlCtXTmt1ineD9PwIIYQQQhQAd3d3kpOTOXr0qLJv//79WFhYcPjwYR4/fqzsj46Oxtra+rWJD4Cenh4WFhaoVKp8iTuvzMzMSEpK4tq1a2zYsIH4+Hg+++wzrbahq6uLhYWFklQK8ZwkP0IIIYQQBcDJyQlLS8ssPTydOnXCzs6O3377TW2/u7s7AKtXr8bFxQVTU1MsLCz44osvuHnzplrZF4e9vezff//FxcUFb29vUlNTuXTpEp06daJixYqYmJjQsGFD9uzZo5R3c3Pjr7/+YujQoahUKrWkasOGDdSsWRN9fX1sbW2ZPXv2a69bpVJhYWGBpaUlTZs2pXfv3hw5coT79+8rZX766ScaNGiAgYEB9vb2TJw4kadPnyrHz58/T/PmzTEwMKBGjRrs2bMHlUrF5s2bgeyHve3bt49GjRqhr6+PpaUlo0ePVqvTzc2NgIAARo4cSZkyZbCwsCA0NPS11yOKFkl+hBBCCCEKiLu7O9HR0cp2dHQ0bm5uuLq6KvsfPXrE4cOHleQnLS2NyZMnc/LkSTZv3kxCQgK+vr65au/q1au0aNGCWrVq8eOPP6Kvr09ycjLt2rUjKiqK48eP07ZtWzp06EBiYiIAGzdupEqVKkyaNImkpCSSkpIAOHbsGJ07d+bzzz/n9OnThIaGMmHCBCIjI3N9/Tdv3mTTpk3o6uqiq6sLPOv96tGjB0OGDOHs2bMsXbqUyMhIpk6dCkB6ejpeXl4YGRlx+PBhvv76a8aNG/fKdq5du0a7du1o2LAhJ0+eZPHixXz77bdMmTJFrdzKlSsxNjbm8OHDzJw5k0mTJrF79+5cX48o/KQvUAghhBCigLi7uxMYGMjTp0959OgRx48fx9XVlbS0NJYsWQLAoUOHSE1NVZKfXr16Kefb29sTERFBw4YNSU5OxsTEJMe24uPjadOmDd7e3sybN0/pwalbty5169ZVyk2ePJlNmzaxZcsW/P39KVOmDLq6ukpP03Nz5szhgw8+YMKECQBUq1aNs2fPMmvWrFcmY/fu3cPExITMzEwePnwIQEBAAMbGxgBMnDiR0aNH4+Pjo1zj5MmTGTlyJCEhIezevZtLly4RExOjxDN16lTatGmTY5uLFi3CysqKhQsXolKpcHZ25p9//mHUqFEEBwejo/OsP6BOnTqEhIQA4OjoyMKFC4mKinpl3aJokeSnCOk8Ju8/rtNarvPl+oQQQgiRe25ubqSkpBAXF8edO3eoVq0a5cuXx9XVlZ49e/L48WNiYmKwt7dXFgQ4duwYoaGhnDx5kjt37pCRkQFAYmIiNWrUyLadR48e0aJFC7744gvmzZundiw5OZnQ0FC2bdtGUlKSkog97/nJyblz5+jUqZPavmbNmjFv3jzS09OVnpyXmZqa8vvvv5OWlsaOHTtYs2aN0qsDcPLkSWJjY9X2paen8/jxYx4+fEh8fDxWVlZqiVijRo1eG2uTJk3Uhuw1a9aM5ORk/v77b+Xe1qlTR+08S0tLtSGFougr8GFvX331Fba2thgYGPD+++9z5MiRV5afN28eTk5OGBoaYmVlxdChQ9UmBAohhBBCFBUODg5UqVKF6OhooqOjcXV1BaBSpUpYWVlx8OBBoqOjadWqFQApKSl4eHhgZmbGmjVriIuLY9OmTQA8efIkx3b09fVp3bo1W7du5dq1a2rHRowYwaZNm5g2bRr79+/nxIkT1K5d+5X15YWOjg4ODg5Ur16dYcOG0bhxYwYMGKAcT05OZuLEiZw4cUL5On36NBcuXMDAwCBfYnquZMmSatsqlUpJLsW7oUCTn3Xr1jFs2DBCQkL4/fffqVu3Lh4eHjlm2N999x2jR48mJCSEc+fO8e2337Ju3TrGjh37liMXQgghhNAOd3d3YmJiiImJwc3NTdnfsmVLduzYwZEjR5Qhb+fPn+fWrVtMnz6dFi1a4OzsnKueCR0dHVavXs17772Hu7s7//zzj3IsNjYWX19fvL29qV27NhYWFiQkJKidr6enR3p6utq+6tWrExsbq7YvNjaWatWq5djrk53Ro0ezbt06fv/9dwAaNGhAfHw8Dg4OWb50dHRwcnLi6tWr3LhxQ6kjLi7ulW1Ur16dQ4cOkZmZqRarqakpVapUyXWsougr0GFvc+bMwc/PT1nvfcmSJWzbto3ly5czevToLOUPHjxIs2bN+OKLL4Bna8537dqVw4cPv9W4C8rpK6/ufhZCCCFE0ePu7s6gQYNIS0tTen4AXF1d8ff358mTJ0ryY21tjZ6eHgsWLKB///6cOXOGyZMn56odXV1d1qxZQ9euXWnVqpUyZ8bR0ZGNGzfSoUMHVCoVEyZMyNLbYWtry6+//srnn3+Ovr4+5cqVY/jw4TRs2JDJkyfTpUsXDh06xMKFC1m0aJFG129lZYW3tzfBwcFs3bqV4OBg2rdvj7W1NZ9++ik6OjqcPHmSM2fOMGXKFNq0aUPVqlXx8fFh5syZPHjwgPHjxwPkuLz3wIEDmTdvHoMHD8bf35/4+HhCQkIYNmyYMt9HFA8Flvw8efKEY8eOMWbMGGWfjo4OrVu35tChQ9me07RpU/73v/9x5MgRGjVqxOXLl9m+fTvdu3fPsZ3U1FRSU1OV7ReXUXxRfsynKQokoRJCCPEu0+SlowXF3d2dR48e4ezsTMWKFZX9rq6uPHjwQFkSG6B8+fJERkYyduxYIiIiaNCgAeHh4XTs2DFXbZUoUYLvv/+eLl26KAnQnDlz6NWrF02bNqVcuXKMGjUqy/PSpEmT6NevH1WrViU1NZXMzEwaNGjA+vXrCQ4OZvLkyVhaWjJp0qRcrzz3oqFDh9KkSROOHDmCh4cHW7duZdKkScyYMYOSJUvi7OxMnz59gGdJ3ObNm+nTpw8NGzbE3t6eWbNm0aFDhxyHxVWuXJnt27cTFBRE3bp1KVOmDL1791aSJlF8FFjy899//5Genq72Rw5QsWJFzp8/n+05X3zxBf/99x/NmzcnMzOTp0+f0r9//1cOewsLC2PixIlajT23ZDEBIYQQQryOra2t2nCs52xsbLLd37VrV7p27aq278Vybm5uatu+vr5qCUmJEiXYsGGD2vl79+5V2x40aJDaduPGjTl58mSWWD755BM++eSTbK4qey/H8mL9L8bs4eGBh4dHjvU4Oztz4MABZfv58DsHBwcg+3vq6ur6yrnlL75v6bnn7w0S744itdpbTEwM06ZNY9GiRbz//vtcvHiRIUOGMHnyZGWZxZeNGTOGYcOGKdv379/HysrqbYVc7EjCJ4QQQoj8tmnTJkxMTHB0dFSeB5s1a0bVqlULOjRRyBVY8lOuXDl0dXXVJqsB3LhxQ23pwhdNmDCB7t27K92etWvXJiUlhb59+zJu3Lhsx2zq6+ujr6+v/QsQQgghhBAF4sGDB4waNYrExETKlStH69atmT17dkGHJYqAAkt+9PT0eO+994iKisLLywuAjIwMoqKi8Pf3z/achw8fZklwnq8mkl23sCbyY+6LzKcRIve03WtYFObxSU+pEEK8mR49etCjR4+CDkMUQQU67G3YsGH4+Pjg4uJCo0aNmDdvHikpKcrqbz169KBy5cqEhYUB0KFDB+bMmUP9+vWVYW8TJkygQ4cOGi2pKIqOovAAK4oPSVaEEEKIoq1Ak58uXbrw77//EhwczPXr16lXrx47d+5UFkFITExU6+kZP348KpWK8ePHc+3aNcqXL0+HDh3U3gAsCpb0dglRsCRBE0IIIXJW4Ase+Pv75zjM7eVVN0qUKEFISAghISFvIbLCx/bxd3muIyHvYQhRJBSFRLwoxCjJlBBCiHdJgSc/omDlNaFK0E4YOcqPh0N5mCucikIiIIQQQoiiTZIfIYqB4riYQH4oCglaUYhRCCGEKCiS/AhRCEnvlBBCCCGE9knyI4od+WQ87+QeFh/ysxZCFBUJCQnY2dlx/Phx6tWrV9DhiEJK4+SnV69ezJ8/H1NTU7X9KSkpDB48mOXLl2stOCGKgqIwBEweYIUoWIW9Nzc//h0rLNdce2VtLdWUO6d9ch+5SqV65fGQkBBCQ0PzGFHBi4yMVF5jolKpqFixIi1btmTWrFlYW1trrR0rKyuSkpIoV66c1uoU7x6N/2VauXIl06dPz5L8PHr0iFWrVhXZ5Cc/VlIr7IsJ5IfieM35QZIV8a4qCh8WFIcYZWhs4ZCUlKR8v27dOoKDg4mPj1f2mZiYFERY+cLMzIz4+HgyMzO5cuUKAwcO5LPPPuPw4cNaa0NXVxcLCwut1SfeTbn+1/P+/ftkZmaSmZnJgwcPMDAwUI6lp6ezfft2KlSokC9BCiHEu0g+LNAOSQREUfXig3qpUqVQqVTKvkuXLtGvXz9+++03UlJSqF69OmFhYbRu3Vo5Z9GiRcydO5erV69SqlQpWrRowY8//giAm5sbtWvXRldXl5UrV6Knp8eUKVP44osv8Pf358cff6RixYosWLCAjz76CHj2PNe3b1/27t3L9evXsba2ZuDAgQwZMkRp09fXl7t379K8eXNmz57NkydP+Pzzz5k3bx4lS5bM8VpfvDZLS0t69+5NQEAA9+/fx8zMDICffvqJiRMncvbsWSpVqoSPjw/jxo2jRIlnf+Pnz5+nT58+HD16FHt7eyIiImjTpg2bNm3Cy8sr22Fv+/btIygoiJMnT1KmTBl8fHyYMmWKUqebmxt16tTBwMCAb775Bj09Pfr37/9O9LiJ7OX6f4zSpUujUqlQqVRUq1Yty3GVSsXEiRO1GpwQ8m4jIYTIf9LbXPgkJyfTrl07pk6dir6+PqtWraJDhw7Ex8djbW3N0aNHCQgIYPXq1TRt2pTbt2+zf/9+tTpWrlzJyJEjOXLkCOvWrWPAgAFs2rQJb29vxo4dy9y5c+nevTuJiYkYGRmRkZFBlSpV+OGHHyhbtiwHDx6kb9++WFpa0rlzZ6Xe6OhoLC0tiY6O5uLFi3Tp0oV69erh5+eXq2u7efMmmzZtQldXF11dXQD2799Pjx49iIiIoEWLFly6dIm+ffsCz4b/paen4+XlhbW1NYcPH+bBgwcMHz78le1cu3aNdu3a4evry6pVqzh//jx+fn4YGBioJTcrV65k2LBhHD58mEOHDuHr60uzZs1o06ZNrq5HFC25Tn6io6PJzMykVatWbNiwgTJlyijH9PT0sLGxoVKlSvkSpHjmsUflgg5BZEMeGgonSZxFYaLtfyfk3513X926dalbt66yPXnyZDZt2sSWLVvw9/cnMTERY2Nj2rdvj6mpKTY2NtSvXz9LHePHjwdgzJgxTJ8+nXLlyilJSnBwMIsXL+bUqVM0btyYkiVLqn2QbWdnx6FDh1i/fr1a8mNubs7ChQvR1dXF2dkZT09PoqKiXpn83Lt3DxMTEzIzM3n48CEAAQEBGBsbAzBx4kRGjx6Nj48PAPb29kyePJmRI0cSEhLC7t27uXTpEjExMUoP0tSpU1+ZoCxatAgrKysWLlyISqXC2dmZf/75h1GjRhEcHIyOjg4AderUISQkBABHR0cWLlxIVFSUJD/vqFwnP66urgBcuXIFKysr5RdGFG2SUInCoigMAZMY864oPLQXhRiLArmPeZOcnExoaCjbtm0jKSmJp0+f8ujRIxITn93XNm3aYGNjg729PW3btqVt27Z4e3tjZGSk1FGnTh3le11dXcqWLUvt2v+3AETFihWBZz0xz3311VcsX76cxMREHj16xJMnT7KsnFazZk2lxwaeDWM7ffrVA0hNTU35/fffSUtLY8eOHaxZs4apU6cqx0+ePElsbKzavvT0dB4/fszDhw+Jj4/HyspKbahgo0aNXtnmuXPnaNKkidrCEs2aNSM5OZm///5bWWzhxfv0/HpevCfi3aLxQGkbGxvu3r3LkSNHuHnzJhkZGWrHe/ToobXghBBCFKzCnkyBPGSLd9OIESPYvXs34eHhODg4YGhoyKeffsqTJ0+A/0smYmJi+OWXXwgODiY0NJS4uDhKly4NkGUOjkqlUtv3PCl4/iy3du1aRowYwezZs2nSpAmmpqbMmjUry6IE2dX78vPgy3R0dHBwcACgevXqXLp0iQEDBrB69WrgWbI3ceJEPv744yznvjjPPD+8yfWIokvj5Ofnn3+mW7duJCcnY2ZmppZNq1QqSX5EoVcUHuaEEEIUb7Gxsfj6+uLt7Q08Sw4SEhLUypQoUYLWrVvTunVrQkJCKF26NHv37s02gchtm02bNmXgwIHKvkuXLr3xNbzK6NGjqVq1KkOHDqVBgwY0aNCA+Ph4JUF6mZOTE1evXuXGjRtKj1VcXNwr26hevTobNmwgMzNTeV6NjY3F1NSUKlWqaPeCRJGhcfIzfPhwevXqxbRp09S6VoUQxYfMpxFCiPzl6OjIxo0b6dChAyqVigkTJqj1RmzdupXLly/TsmVLzM3N2b59OxkZGTg5OeWpzVWrVrFr1y7s7OxYvXo1cXFx2NnZaeOS1FhZWeHt7U1wcDBbt24lODiY9u3bY21tzaeffoqOjg4nT57kzJkzTJkyhTZt2lC1alV8fHyYOXMmDx48UOYz5fS+pIEDBzJv3jwGDx6Mv78/8fHxhISEMGzYMJm+UYxpnPxcu3aNgICAdy7xkbkv4l0mvV1CiOJKk5eOFiZz5syhV69eNG3alHLlyjFq1Cju37+vHC9dujQbN24kNDSUx48f4+joyPfff0/NmjXfuM1+/fpx/PhxunTpgkqlomvXrgwcOJAdO3Zo45KyGDp0KE2aNOHIkSN4eHiwdetWJk2axIwZMyhZsiTOzs706dMHeDZnafPmzfTp04eGDRtib2/PrFmz6NChQ47D4ipXrsz27dsJCgqibt26lClTht69eytJkyieNE5+PDw8lPXVxasVx4SqOF5zfpBkRQghihdfX198fX2VbVtbW/bu3atWZtCgQcr3zZs3JyYmJsf6sjv28rA5gMzMTOV7fX19VqxYwYoVK9TKhIWFKd9HRkZmqWPevHk5xgFZr+25xo0bq7Xv4eGBh4dHjvU4Oztz4MABZTs2NhZAGSpna2urVh88W7DryJEjOdaZ3X3avHlzjuVF0adx8uPp6UlQUBBnz56ldu3aWSaJdezYUWvBCSGEEEIIAbBp0yZMTExwdHTk4sWLDBkyhGbNmlG1atWCDk0UIRonP8/XcJ80aVKWYyqVivT09LxHJYQQQgghxAsePHjAqFGjSExMpFy5crRu3ZrZs2cXdFiiiNE4+ZGl/8TbVBSG0cnk/8KpKPzuFIUYta24/r0U9qGsxfXnIoqWHj16yKrCIs80Tn6EECI/FIVEoCjEWBxpO7GQREAIId5dGic/2Q13e1FwcPAbByOEECJvJEErHgp7T5IQQhRWGic/mzZtUttOS0vjypUrlChRgqpVq0ryIwo9eTgUIvfk70W8KUnQhBCFkcbJz/Hjx7Psu3//vtpbiIUQQgghhBCisNHKnB8zMzMmTpxIhw4d6N69uzaqFEIUYtIbIIQQQoiiSGsLHty7d4979+5pqzohhBZJsiKEEEII8QbJT0REhNp2ZmYmSUlJrF69mo8++khrgQlRnEmyIt5V8rstxLshISEBOzs7jh8/Tr169bIto1Kp2LRpE15eXm81tpdFRkYSGBjI3bt3CzQOUThonPzMnTtXbVtHR4fy5cvj4+PDmDFjtBaYEEWFPMwJIYq6d/rfsdBSb7m93I+CUalUrzweEhJCaGhoHgMqOElJSZibm+d43NfXl5UrVwJQokQJqlSpwmeffcakSZMwMDDQWhxdunShXbt2WqtPFG0aJz9XrlzJjziEEEKIN6LtB/f8SATe6eRCvLGkpCTl+3Xr1hEcHEx8fLyyz8TERKP6njx5gp6entbiyysLC4vXlmnbti0rVqwgLS2NY8eO4ePjg0qlYsaMGVqLw9DQEENDQ63VJ4o2nbyc/Pfff/P3339rKxYhhBBC5MJjj8p5+hKFg4WFhfJVqlQpVCqVsp2SkkK3bt2oWLEiJiYmNGzYkD179qidb2try+TJk+nRowdmZmb07dsXgFGjRlGtWjWMjIywt7dnwoQJpKWlKeeFhoZSr149Vq9eja2tLaVKleLzzz/nwYMHSpmdO3fSvHlzSpcuTdmyZWnfvj2XLl3K8VrS09Pp1asXzs7OJCYmAs96tjZv3vzKe6Cvr4+FhQVWVlZ4eXnRunVrdu/erRzPyMggLCwMOzs7DA0NqVu3Lj/++KNaHVu2bMHR0REDAwPc3d1ZuXIlKpVKGeYWGRlJ6dKl1c5ZvHgxVatWRU9PDycnJ1avXq12XKVS8c033+Dt7Y2RkRGOjo5s2bLlldciigaNk5+MjAwmTZpEqVKlsLGxwcbGhtKlSzN58mQyMjLyI0YhhBBCFDGSoOVNcnIy7dq1IyoqiuPHj9O2bVs6dOigJBbPhYeHU7duXY4fP86ECRMAMDU1JTIykrNnzzJ//nyWLVuWZdrCpUuX2Lx5M1u3bmXr1q3s27eP6dOnK8dTUlIYNmwYR48eJSoqCh0dHby9vbN91ktNTeWzzz7jxIkT7N+/H2tr6ze65jNnznDw4EG13quwsDBWrVrFkiVL+OOPPxg6dChffvkl+/btA56NSPr000/x8vLi5MmT9OvXj3Hjxr2ynU2bNjFkyBCGDx/OmTNn6NevHz179iQ6Olqt3MSJE+ncuTOnTp2iXbt2dOvWjdu3b7/RtYnCQ+Nhb+PGjePbb79l+vTpNGvWDIADBw4QGhrK48ePmTp1qtaDFPlnTeYneawh50+BhBBCCPFm6tatS926dZXtyZMns2nTJrZs2YK/v7+yv1WrVgwfPlzt3PHjxyvf29raMmLECNauXcvIkSOV/RkZGURGRmJqagpA9+7diYqKUp7jPvlE/flg+fLllC9fnrNnz1KrVi1lf3JyMp6enqSmphIdHU2pUprNsdq6dSsmJiY8ffqU1NRUdHR0WLhwIfAsqZo2bRp79uyhSZMmANjb23PgwAGWLl2Kq6srS5cuxcnJiVmzZgHg5OTEmTNnXvk8Gh4ejq+vLwMHDgRg2LBh/Pbbb4SHh+Pu7q6U8/X1pWvXrgBMmzaNiIgIjhw5Qtu2bTW6RlG4aJz8rFy5km+++YaOHTsq++rUqUPlypUZOHCgJD/5KO+JCkiyIoQQQhR+ycnJhIaGsm3bNpKSknj69CmPHj3K0vPj4uKS5dx169YRERHBpUuXSE5O5unTp5iZmamVsbW1VRIfAEtLS27evKlsX7hwgeDgYA4fPsx///2n9PgkJiaqJT9du3alSpUq7N27943m1bi7u7N48WJSUlKYO3cuJUqUUBKvixcv8vDhQ9q0aaN2zpMnT6hfvz4A8fHxNGzYUO14o0aNXtnmuXPnlCGCzzVr1oz58+er7atTp47yvbGxMWZmZmr3SBRNGic/t2/fxtnZOct+Z2fnIt0VKImFEEIIIQqLESNGsHv3bsLDw3FwcMDQ0JBPP/2UJ0+eqJUzNjZW2z506BDdunVj4sSJeHh4UKpUKdauXcvs2bPVypUsWVJtW6VSqQ1p69ChAzY2NixbtoxKlSqRkZFBrVq1srTfrl07/ve//3Ho0CFatWql8XUaGxvj4OAAPOtdqlu3Lt9++y29e/cmOTkZgG3btlG5svpQSH19fY3b0tTr7pEomjSe81O3bl2lO/JFCxcuVOueFUIIIYQQbyY2NhZfX1+8vb2pXbs2FhYWJCQkvPa8gwcPYmNjw7hx43BxccHR0ZG//vpLo7Zv3bpFfHw848eP54MPPqB69ercuXMn27IDBgxg+vTpdOzYUZmH86Z0dHQYO3Ys48eP59GjR9SoUQN9fX0SExNxcHBQ+7KysgKeDXM7evSoWj1xcXGvbKd69erExsaq7YuNjaVGjRp5il8UDRr3/MycORNPT0+18ZeHDh3i6tWrbN++XesBCiGEEEIUN46OjmzcuJEOHTqgUqmYMGFCrnodHB0dSUxMZO3atTRs2JBt27axadMmjdo2NzenbNmyfP3111haWpKYmMjo0aNzLD948GDS09Np3749O3bsoHnz5hq196LPPvuMoKAgvvrqK0aMGMGIESMYOnQoGRkZNG/enHv37hEbG4uZmRk+Pj7069ePOXPmMGrUKHr37s2JEyeIjIwEcn6PUlBQEJ07d6Z+/fq0bt2an3/+mY0bN2ZZTU+8mzROflxdXYmPj2fRokWcP38egI8//piBAwdSqVIlrQdYlMliAkIIIUQB0+Clo4XJnDlz6NWrF02bNqVcuXKMGjWK+/fvv/a8jh07MnToUPz9/UlNTcXT05MJEyZo9LJUHR0d1q5dS0BAALVq1cLJyYmIiAjc3NxyPCcwMJCMjAzatWvHzp07adq0aa7be1GJEiXw9/dn5syZDBgwgMmTJ1O+fHnCwsK4fPkypUuXpkGDBowdOxYAOzs7fvzxR4YPH878+fNp0qQJ48aNY8CAATkOjfPy8mL+/PmEh4czZMgQ7OzsWLFixSuvT7w7VJmZmZkFHcTbdP/+fUqVKsW9e/fUJv9F7a2a57o/aKWerOS1Tm3Xlx91vlyfRfSJPNV33b2eVuvLjzqLY4zF8Zrzo878ri8/6ixs9eVHncUxxqJ4zTn9/w3w+PFjrly5gp2dHQYGBnlqVxR9U6dOZcmSJVy9erWgQxFviSb/Bmjc87NixQpMTEz47LPP1Pb/8MMPPHz4EB8fH02rFO8Q6e0SIvfk70UIIfJu0aJFNGzYkLJlyxIbG8usWbPUlgMX4kUaJz9hYWEsXbo0y/4KFSrQt29fSX6EVskqfEIIIYR4lQsXLjBlyhRu376NtbU1w4cPZ8yYMQUdliikNE5+EhMTsbOzy7LfxsYmy9rzQghRUPIjcZaeGiGEKHzmzp3L3LlzCzoMUURonPxUqFCBU6dOYWtrq7b/5MmTlC1bVltxCSGKGUkshBBCCJHfNE5+unbtSkBAAKamprRs2RKAffv2MWTIED7//HOtByiEtslDtniXafv3W/5ehBBCvEs0Tn4mT55MQkICH3zwASVKPDs9IyODHj16MG3aNK0HKIQQQgghhBDaoHHyo6enx7p165gyZQonTpzA0NCQ2rVrY2Njkx/xiRfs/7V7nuv4oJUWAhFCCCGEEKII0jj5ec7R0RFHR0dtxlKgJLEQIvdkFT7xpuR3p3CSn4sQorh44+RHvBvymvRJwpc/ZJ6FEEIIIYT2SfIjRB4VhU9MJZkS7zL5/RbizcTExODu7s6dO3coXbp0tmVCQ0PZvHkzJ06cKPBY3hZfX1/u3r3L5s2bCzQOkT8k+fn/+jz+QOt1artXJT9iFEIIkf9kFb6CYzt621ttL2G6p0bl//33X4KDg9m2bRs3btzA3NycunXrEhwcTLNmzbQWl5ubG/Xq1WPevHlaq/Nts7W15a+//gLA0NCQqlWrMmTIEPr06aPVdubPn09mZqZW6xSFhyQ/QgghxAuKQm+ueHd88sknPHnyhJUrV2Jvb8+NGzeIiori1q1bBR1aoTRp0iT8/Px4+PAhP/zwA35+flSuXJmPPvpIa22UKlVKa3WJwueNkp+7d+9y5MgRbt68SUZGhtqxHj16aCUw8XZIb5IQQoj8IL1Tr3f37l32799PTEwMrq6uANjY2NCoUSO1comJiQwePJioqCh0dHRo27YtCxYsoGLFikD2w7QCAwM5ceIEMTEx+Pr6sm/fPvbt28f8+fMBuHLlilL22LFjjBo1irNnz1KvXj1WrFiBk5NTtjHHxcUxduxYjh8/TlpaGvXq1WPu3Lk0aNBAKaNSqVi2bBnbtm1j165dVK5cmdmzZ9OxY0elzPbt2wkMDOTq1as0btwYHx+fXN0zU1NTLCwsABg1ahQzZ85k9+7dSvJz9+5dRowYwU8//URqaiouLi7MnTuXunXrKnVMmTKFiIgIHj16RJcuXShXrhw7d+5Uhva9fD9TU1MJCgpi7dq13L9/X6mzYcOGwP8N2duzZ0+u76MoOBonPz///DPdunUjOTkZMzMzVCqVckylUhXZ5GfdlRl5rmM4LdS2JbEQQgghRE5MTEwwMTFh8+bNNG7cGH19/SxlMjIy6NSpEyYmJuzbt4+nT58yaNAgunTpQkxMTK7amT9/Pn/++Se1atVi0qRJAJQvX56EhAQAxo0bx+zZsylfvjz9+/enV69exMbGZlvXgwcP8PHxYcGCBWRmZjJ79mzatWvHhQsXMDU1VcpNnDiRmTNnMmvWLBYsWEC3bt3466+/KFOmDFevXuXjjz9m0KBB9O3bl6NHjzJ8+HCN7l1GRgabNm3izp076OnpKfs/++wzDA0N2bFjB6VKlWLp0qV88MEH/Pnnn5QpU4Y1a9YwdepUFi1aRLNmzVi7di2zZ8/Gzs4ux7ZGjhzJhg0bWLlyJTY2NsycORMPDw8uXrxImTJllHKa3EdRcDROfoYPH06vXr2YNm0aRkZG+RGTyEF+JGhCCCGEKBglSpQgMjISPz8/lixZQoMGDXB1deXzzz+nTp06AERFRXH69GmuXLmClZUVAKtWraJmzZrExcUpvQ+vUqpUKfT09DAyMlJ6TV40depUpedp9OjReHp68vjxYwwMDLKUbdVKfULy119/TenSpdm3bx/t27dX9vv6+tK1a1cApk2bRkREBEeOHKFt27YsXryYqlWrMnv2bACcnJw4ffo0M2a8/jln1KhRjB8/ntTUVJ4+fUqZMmWUOT8HDhxQRiY9TyTDw8PZvHkzP/74I3379mXBggX07t2bnj17AhAcHMwvv/xCcnJytu2lpKSwePFiIiMjld6lZcuWsXv3br799luCgoLe6D6KgqNx8nPt2jUCAgIk8RHZ0vYiD/L+JSGEEO+yTz75BE9PT/bv389vv/3Gjh07mDlzJt988w2+vr6cO3cOKysrJfEBqFGjBqVLl+bcuXO5Sn5e53miBWBpaQnAzZs3sba2zlL2xo0bjB8/npiYGG7evEl6ejoPHz4kMTExxzqNjY0xMzPj5s2bAJw7d473339frXyTJk1yFWtQUBC+vr4kJSURFBTEwIEDcXBwAODkyZMkJydTtmxZtXMePXrEpUvPhlHGx8czcOBAteONGjVi79692bZ36dIl0tLS1BafKFmyJI0aNeLcuXM5XvPr7qMoOBonPx4eHhw9ehR7e/v8iOedkteemrfRS1MUYhSisChsyb0k9kK8GwwMDGjTpg1t2rRhwoQJ9OnTh5CQEHx9fXN1vo6OTpbVydLS0nLdfsmSJZXvn09neHlO93M+Pj7cunWL+fPnY2Njg76+Pk2aNOHJkyc51vm83pzq1ES5cuVwcHDAwcGBH374gdq1a+Pi4kKNGjVITk7G0tIy2+GAb2P5bE3uoyg4uUp+tmzZonzv6elJUFAQZ8+epXbt2ll+uV+czCaEELlV2BKL7OoUQoi3oUaNGspk++rVq3P16lWuXr2q9P6cPXuWu3fvUqNGDeDZ/J0zZ86o1XHixAm1ZzQ9PT3S09PzHFtsbCyLFi2iXbt2AFy9epX//vtPozqqV6+u9mwJ8Ntvv2kci5WVFV26dGHMmDH89NNPNGjQgOvXr1OiRAlsbW2zPcfJyYm4uDi1OepxcXE5tlG1alX09PSIjY3FxsYGeJZYxsXFERgYqHHMouDlKvnx8vLKsu/5hLkXqVQqrfxhCZGf5NN2IYQQhcGtW7f47LPP6NWrF3Xq1MHU1JSjR48yc+ZMOnXqBEDr1q2pXbs23bp1Y968eTx9+pSBAwfi6uqKi4sL8GwezqxZs1i1ahVNmjThf//7H2fOnKF+/fpKW7a2thw+fJiEhARMTEzUJuprwtHRkdWrV+Pi4sL9+/cJCgrC0NBQozr69+/P7NmzCQoKok+fPhw7dozIyMg3imfIkCHUqlWLo0eP0rp1a5o0aYKXlxczZ86kWrVq/PPPP2zbtg1vb29cXFwYPHgwfn5+uLi40LRpU9atW8epU6dyHNFkbGzMgAEDCAoKokyZMlhbWzNz5kwePnxI79693yhmUbBylfxIl53ILW2vcCcr5ol3WVH4/ZYPC0RRp+lLR98mExMT3n//febOnavMLbGyssLPz4+xY8cCzz5Y/umnnxg8eDAtW7ZUW+r6OQ8PDyZMmMDIkSN5/PgxvXr1okePHpw+fVopM2LECHx8fKhRowaPHj1SW+paE99++y19+/alQYMGWFlZMW3aNEaMGKFRHdbW1mzYsIGhQ4eyYMECGjVqxLRp0+jVq5fG8dSoUYMPP/yQ4OBgtm/fzvbt2xk3bhw9e/bk33//xcLCgpYtWyrLgnfr1o3Lly8zYsQIHj9+TOfOnfH19eXIkSM5tjF9+nQyMjLo3r07Dx48wMXFhV27dmFubq5xvKLgaeUlp3fv3n0rYymFECK38iOxkGRFCKFN+vr6hIWFERYW9spy1tbW/PTTT68sM3HiRCZOnJjj8WrVqnHo0CG1fba2tlnmCtWrV09tX2hoKKGhocp2/fr1swwT+/TTT9W2X64Tnj0rvqh9+/Zqq8MBygpsOXm+NPfLdu7cqXxvampKREQEEREROdYzYcIEJkyYoGy3adNGWTQByNILZWBg8Mo63dzcXnsfReGhcfIzY8YMbG1t6dKlC/BsPfUNGzZgaWnJ9u3b1V4iJYR4N+XHfJqikFgIIYQo2h4+fMiSJUvw8PBAV1eX77//nj179rB79+6CDk28JRonP0uWLGHNmjUA7N69mz179rBz507Wr19PUFAQv/zyi9aDFMWXvHxWiIKl7b8XWYhCCFGQVCoV27dvZ+rUqTx+/BgnJyc2bNhA69atCzo08ZZonPxcv35dWW1k69atdO7cmQ8//BBbW9ssa7aL4keWztaOwrbymTxsPqPt3+/8+HuR5F4IIXJmaGjInj17CjoMUYA0Tn7Mzc2V5RZ37tzJlClTgGfjO2WlN1EcySfZ2lHYEovs6hRCCCFE0aZx8vPxxx/zxRdf4OjoyK1bt/joo48AOH78uNpkMSHEu0t6F4R4t8iHOEKI4kLj5Gfu3LnY2tpy9epVZs6ciYmJCQBJSUkMHDhQ6wEKoW0yNE+I3NP230t+JM4yrFMIIURuaZz8lCxZMtv13IcOHfpGAXz11VfMmjWL69evU7duXWW995zcvXuXcePGsXHjRm7fvo2NjQ3z5s1T3jQsxNtWXJdUFoWTJPd5lx+9IDKPTwghCoc3fs/P2bNnSUxM5MmTJ2r7O3bsmOs61q1bx7Bhw1iyZAnvv/8+8+bNw8PDg/j4eCpUqJCl/JMnT2jTpg0VKlTgxx9/pHLlyvz111/yjiEhXkOSKSGEEEKIN0h+Ll++jLe3N6dPn0alUikvcFKpVAAaLXowZ84c/Pz8lJdaLVmyhG3btrF8+XJGjx6dpfzy5cu5ffs2Bw8epGTJksCzF3QJId4uWUxAiHeLfEAihCguNE5+hgwZgp2dHVFRUdjZ2XHkyBFu3brF8OHDCQ8Pz3U9T5484dixY4wZM0bZp6OjQ+vWrbO8gfi5LVu20KRJEwYNGsRPP/1E+fLl+eKLLxg1ahS6urrZnpOamkpqaqqyff/+/VzHKERBkaFL4l0l7+7SjuJ4zaL48vX15e7du2zevLmgQxHvAI2Tn0OHDrF3717KlSuHjo4OOjo6NG/enLCwMAICAjh+/Hiu6vnvv/9IT0+nYsWKavsrVqzI+fPnsz3n8uXL7N27l27durF9+3YuXrzIwIEDSUtLIyQkJNtzwsLCmDhxomYXKYQGikIviCRTQuSezOPTjsIyL8ki+oR2Ksql6+71ND7n6tWrhISEsHPnTv777z8sLS3x8vIiODiYsmXLKuVsbW0JDAwkMDBQewHnga2tLX/99Rfw7P05VatWZciQIfTp00er7cyfP18ZaSREXmmc/KSnp2NqagpAuXLl+Oeff3BycsLGxob4+HitB/iijIwMKlSowNdff42uri7vvfce165dY9asWTkmP2PGjGHYsGHK9v3795WXtAohhBCiaHyI8666fPkyTZo0oVq1anz//ffY2dnxxx9/EBQUxI4dO/jtt98oU6ZMQYeZo0mTJuHn58fDhw/54Ycf8PPzo3LlysqrULShVKlSWqtLCB1NT6hVqxYnT54E4P3332fmzJnExsYyadIk7O3tc11PuXLl0NXV5caNG2r7b9y4gYWFRbbnWFpaUq1aNbUhbtWrV+f69etZFl54Tl9fHzMzM7UvIYQQQojCYNCgQejp6fHLL7/g6uqKtbU1H330EXv27OHatWuMGzcOADc3N/766y+GDh2KSqVS5lrfunWLrl27UrlyZYyMjKhduzbff/+9WhsPHjygW7duGBsbY2lpydy5c3Fzc1PrQbpz5w49evTA3NwcIyMjPvroIy5cuPDa+E1NTbGwsMDe3p5Ro0ZRpkwZdu/erRy/e/cuffr0oXz58piZmdGqVSvlOfK5KVOmUKFCBUxNTenTpw+jR4+mXr16ynFfX1+8vLyU7dTUVAICAqhQoQIGBgY0b96cuLg45XhMTAwqlYqoqChcXFwwMjKiadOm+f4hvSgaNO75GT9+PCkpKcCzbL99+/a0aNGCsmXLsm7dulzXo6enx3vvvUdUVJTyC52RkUFUVBT+/v7ZntOsWTO+++47MjIy0NF5lrf9+eefWFpaoqenp+mlCCGEeAcUx2GdReGai+NQP03dvn2bXbt2MXXqVAwNDdWOWVhY0K1bN9atW8eiRYvYuHEjdevWpW/fvvj5+SnlHj9+zHvvvceoUaMwMzNj27ZtdO/enapVqyqvDhk2bBixsbFs2bKFihUrEhwczO+//54lwbhw4QJbtmzBzMyMUaNG0a5dO86ePassMvUqGRkZbNq0iTt37qg9k3322WcYGhqyY8cOSpUqxdKlS/nggw/4888/KVOmDGvWrGHq1KksWrSIZs2asXbtWmbPno2dnV2ObY0cOZINGzawcuVKbGxsmDlzJh4eHly8eFGtl2zcuHHMnj2b8uXL079/f3r16kVsbOxrr0W82zROfjw8PJTvHRwcOH/+PLdv38bc3Fz5FCK3hg0bho+PDy4uLjRq1Ih58+aRkpKirP7Wo0cPKleuTFhYGAADBgxg4cKFDBkyhMGDB3PhwgWmTZtGQECAppchhBBCvDVFIVkRb9+FCxfIzMykevXq2R6vXr06d+7c4d9//6VChQro6uoqPS3PVa5cWe39i4MHD2bXrl2sX7+eRo0a8eDBA1auXMl3333HBx88S0hXrFhBpUqV1OLYsmULsbGxNG3aFIA1a9ZgZWXF5s2b+eyzz3K8hlGjRjF+/HhSU1N5+vQpZcqUUeb8HDhwgCNHjnDz5k309fUBCA8PZ/Pmzfz444/07duXBQsW0Lt3b+XZLzg4mF9++YXk5ORs20tJSWHx4sVERkYqQ+uWLVvG7t27+fbbbwkKClLKTp06FVdXVwBGjx6Np6cnjx8/xsDAIMfrEe8+jZKftLQ0DA0NOXHiBLVq1VL2v+lY1C5duvDvv/8SHBzM9evXqVevHjt37lQWQUhMTFR6eACsrKzYtWsXQ4cOpU6dOlSuXJkhQ4YwatSoN2r/RQbmw15fqIDlR4xF4bqFEOJtkvkv4m3Ly2T+9PR0pk2bxvr167l27RpPnjwhNTUVIyMj4NmcorS0NLUXyJcqVQonJydl+9y5c5QoUYL3339f2Ve2bFmcnJw4d+7cK9sPCgrC19eXpKQkgoKCGDhwIA4ODgCcPHmS5ORktUUbAB49esSlS5cAiI+PZ+DAgWrHGzVqxN69e7Nt79KlS6SlpdGsWTNlX8mSJWnUqFGWWOvUqaN8b2lpCcDNmzextrZ+5TWJd5tGyU/JkiWxtrbW6F0+r+Pv75/jMLeYmJgs+5o0acJvv/2mtfbzkyQWQgghhMiJg4MDKpWKc+fO4e3tneX4uXPnMDc3p3z58jnWMWvWLObPn8+8efOoXbs2xsbGBAYG5jgXWtvKlSuHg4MDDg4O/PDDD9SuXRsXFxdq1KhBcnIylpaW2T7PvY0X1L84XO/56KSMjIx8b1cUbhoPexs3bhxjx45l9erVhXr1ESGEEEIUHBnq93ply5alTZs2LFq0iKFDh6rN+7l+/Tpr1qyhR48eyoO7np5elg+gY2Nj6dSpE19++SXw7OH+zz//pEaNGgDY29tTsmRJ4uLilB6Pe/fu8eeff9KyZUvg2fC6p0+fcvjwYWXY261bt4iPj1fqyQ0rKyu6dOnCmDFj+Omnn2jQoAHXr1+nRIkSOb6U3snJibi4OHr06KHse3HxgpdVrVoVPT09YmNjsbGxAZ6NTIqLiys0S4CLwk3j1d4WLlzIr7/+SqVKlXBycqJBgwZqX0IIIYQQIncWLlxIamoqHh4e/Prrr1y9epWdO3fSpk0bKleuzNSpU5Wytra2/Prrr1y7do3//vsPAEdHR3bv3s3Bgwc5d+4c/fr1U1tJ19TUFB8fH4KCgoiOjuaPP/6gd+/e6OjoKEmVo6MjnTp1ws/PjwMHDnDy5Em+/PJLKleuTKdOnTS6niFDhvDzzz9z9OhRWrduTZMmTfDy8uKXX34hISGBgwcPMm7cOI4ePQo8m6P07bffsnLlSi5cuMCUKVM4depUjvPIjY2NGTBgAEFBQezcuZOzZ88qS2337t1bo1hF8aRxz8+LSw0KIYQQQhRmb/LS0bfJ0dGRo0ePEhISQufOnbl9+zYWFhZ4eXkREhKiNspm0qRJ9OvXj6pVq5KamkpmZibjx4/n8uXLeHh4YGRkRN++ffHy8uLevXvKeXPmzKF///60b98eMzMzRo4cydWrV9Um/q9YsYIhQ4bQvn17njx5QsuWLdm+fXuuVnp7UY0aNfjwww8JDg5m+/btbN++nXHjxtGzZ0/+/fdfLCwsaNmypTK/u1u3bly+fJkRI0bw+PFjOnfujK+vL0eOHMmxjenTp5ORkUH37t158OABLi4u7Nq1C3Nzc41iFcWTxslPTi8TFUIIIYQQmrOxsSEyMvK15Ro3bpzlHTllypRh8+bNrzzP1NSUNWvWKNspKSlMnDiRvn37KvvMzc1ZtWqVRnEnJCRku3/nzp1qbUdERBAREZFjPRMmTGDChAnKdps2bZRFE4As98bAwOCVdbq5uWVZRKJevXp5WlhCvDs0Tn7i4uLIyMhQWxEE4PDhw+jq6uLi4qK14ISQRSOEEEKIvDl+/Djnz5+nUaNG3Lt3j0mTJgFoPKQtPzx8+JAlS5bg4eGBrq4u33//PXv27FF7UaoQ2qRx8jNo0CBGjhyZJfm5du0aM2bM4PDhw1oLThQ9kqyId5m2f7/l70UI8baEh4cTHx+vvGR+//79lCtXrqDDQqVSsX37dqZOncrjx49xcnJiw4YNtG7duqBDE+8ojZOfs2fPZruwQf369Tl79qxWghJCCCGEENpRv359jh07VtBhZMvQ0JA9e/YUdBiiGNE4+dHX1+fGjRvY29ur7U9KSqJECY2rE+Ktk0/biwf5OWuH3EchhBDvEo2zlQ8//FBZv71UqVIA3L17l7Fjx9KmTRutByiEKB7kIVsIIYQQ+U3j5Cc8PJyWLVtiY2ND/fr1AThx4gQVK1Zk9erVWg9QCCGEEEIIIbRB4+SncuXKnDp1ijVr1nDy5EkMDQ3p2bMnXbt21XgteCHeBfnRYyG9IOJNye+OEEIIkbM3mqRjbGystja8EKJwk1XKhBBCCCHeMPl5F7WKGaSFWs5poY6cFYUYhRDiVSRxFkIIUZAk+clHeU9W8j9RKQoxCiGEEG8qam/Vt9reB60uvdX23pSvry93795l8+bNOZaxtbUlMDCQwMDAAo/lbVGpVGzatAkvL6+CDkXkE52CDkAIIYQQorjy9fVFpVIxffp0tf2bN29GpVLluf6EhARUKhUnTpzIc10FJSYmBpVKpXyVL1+edu3acfr0aa23lZSUxEcffaT1ekXhIcmPEEIIIUQBMjAwYMaMGdy5c0er9T558kSr9RW0+Ph4kpKS2LVrF6mpqXh6emr9Gi0sLNDX19dqnaJwkWFv/1/nMXm/Fdr//EFdUYhRCCGEEJpp3bo1Fy9eJCwsjJkzZ+ZYbsOGDQQHB3Px4kUsLS0ZPHgww4cPV47b2trSu3dvLly4wObNm/n4449ZuXIlgPJ6EldXV2JiYpRzwsPDmT17Nk+ePOHzzz9n3rx5Oa7eO2fOHFasWMHly5cpU6YMHTp0YObMmZiYmAAQGRlJYGAg69atIzAwkKtXr9K8eXNWrFiBpaUlAOnp6QQFBbF8+XJ0dXXp3bs3mZmZubpPFSpUoHTp0lhYWBAYGEjHjh05f/48derUAeDAgQOMGTOGo0ePUq5cOby9vQkLC8PY2Bh41qvTp08f9u7di4WFBVOnTmXs2LFqQ/teHvZ2+vRphgwZwqFDhzAyMuKTTz5hzpw5yjU/H7LXvHnzXN9HUbBy9TRtbm6e667X27dv5ymgd0lek5W3kagUhRiFEOJVZBEFUdTp6uoybdo0vvjiCwICAqhSpUqWMseOHaNz586EhobSpUsXDh48yMCBAylbtiy+vr5KufDwcIKDgwkJCQFg0KBBNGrUiD179lCzZk309PSUstHR0VhaWhIdHc3Fixfp0qUL9erVw8/PL9s4dXR0iIiIwM7OjsuXLzNw4EBGjhzJokWLlDIPHz4kPDyc1atXo6Ojw5dffsmIESNYs2YNALNnzyYyMpLly5dTvXp1Zs+ezaZNm2jVqlWu79e9e/dYu3YtgHI9ly5dom3btkyZMoXly5fz77//4u/vj7+/PytWrACgR48e/Pfff8TExFCyZEmGDRvGzZs3c2wnJSUFDw8PmjRpQlxcHDdv3qRPnz74+/sTGRn5xvdRFKxcPfnOmzcvn8MQQojCT9sLhMiCI0KI57y9valXrx4hISF8++23WY7PmTOHDz74gAkTJgBQrVo1zp49y6xZs9SSn1atWqn1Bunq6gJQtmxZLCws1Oo0Nzdn4cKF6Orq4uzsjKenJ1FRUTk+tL+48IGtrS1Tpkyhf//+aslPWloaS5YsoWrVZwtN+Pv7M2nSJOX4vHnzGDNmDB9//DEAS5YsYdeuXbm5RUpSmJKSAkDHjh1xdnYGICwsjG7duikxOjo6EhERgaurK4sXLyYhIYE9e/YQFxeHi4sLAN988w2Ojo45tvfdd9/x+PFjVq1apfQeLVy4kA4dOjBjxgwqVqz4RvdRFKxcJT8+Pj75HYcQQmiVLA0vhChqZsyYQatWrRgxYkSWY+fOnaNTp05q+5o1a8a8efNIT09XkpznD/a5UbNmTeU8AEtLy1cuIrBnzx7CwsI4f/489+/f5+nTpzx+/JiHDx9iZGQEgJGRkZL4PK/zee/KvXv3SEpK4v3331eOlyhRAhcXl1wNfdu/fz9GRkb89ttvTJs2jSVLlijHTp48yalTp5QeJoDMzEwyMjK4cuUKf/75JyVKlKBBgwbKcQcHB8zNzXNs79y5c9StW1dJfODZPc/IyCA+Pl5JfjS9j6Jg5WnM0+PHj7NMNDMzM8tTQEIIIQqP4tg7VRyH0RXHay6MWrZsiYeHB2PGjFHrzdHEiw/qr/PynBSVSkVGRka2ZRMSEmjfvj0DBgxg6tSplClThgMHDtC7d2+ePHmiJD/Z1ZnbOT2vY2dnR+nSpXFycuLmzZt06dKFX3/9FYDk5GT69etHQEBAlvOsra35888/tRJDdjS5j6LgaZz8pKSkMGrUKNavX8+tW7eyHE9PT9dKYEKAfHov3m35MeeuOCYrRYEkFyK3pk+fTr169XByclLbX716dWJjY9X2xcbGUq1aNbVeh5c9nxOT1+ezY8eOkZGRwezZs9HRebZY8Pr16zWqo1SpUlhaWnL48GFatmwJwNOnTzl27Jhaj0xuDBo0iLCwMDZt2oS3tzcNGjTg7NmzODg4ZFveycmJp0+fcvz4cd577z0ALl68+MoV9qpXr05kZCQpKSlKUhkbG4uOjk6Wn48oOjT+n3fkyJFER0ezePFiunfvzldffcW1a9dYunRpljXqRfFTFB68ikKMxZH8XITIPUmm3l21a9emW7duREREqO0fPnw4DRs2ZPLkyXTp0oVDhw6xcOFCtfk22alQoQKGhobs3LmTKlWqYGBgQKlSpTSOy8HBgbS0NBYsWECHDh2IjY1VG3aWW0OGDGH69Ok4Ojri7OzMnDlzuHv3rsb1GBkZ4efnR0hICF5eXowaNYrGjRvj7+9Pnz59MDY25uzZs+zevZuFCxfi7OxM69at6du3L4sXL6ZkyZIMHz4cQ0PDHBf16tatGyEhIfj4+BAaGsq///7L4MGD6d69uzLkTRQ9Gic/P//8M6tWrcLNzY2ePXvSokULHBwcsLGxYc2aNXTr1i0/4hRCCI3kx9LwsjqiEEXPB60uFXQIGps0aRLr1q1T29egQQPWr19PcHAwkydPxtLSkkmTJr12eFyJEiWIiIhg0qRJBAcH06JFC7WlrnOrbt26zJkzhxkzZjBmzBhatmxJWFgYPXr00Kie4cOHk5SUhI+PDzo6OvTq1Qtvb2/u3buncUz+/v7MmTOHH374gc6dO7Nv3z7GjRtHixYtyMzMpGrVqnTp0kUpv2rVKnr37k3Lli2xsLAgLCyMP/74AwMDg2zrNzIyYteuXQwZMoSGDRuqLXUtii6N/ye/ffs29vb2wLP5Pc+Xtm7evDkDBgzQbnRCFFPSCyIKC0n4hMhfLy6Z/JytrS2pqalZ9n/yySd88sknOdaVkJCQ7f4+ffrQp0+f17b78uq+L9c3dOhQhg4dqrave/fuyve+vr5ZkjEvLy+1OT8lSpRg3rx5Gq0k7Obmlu28ISsrK9LS0pTthg0b8ssvv+RYj6WlJdu3b1e2//77b27evKk2VO7ldmrXrs3evXtzrDM391EULhr/r2Zvb8+VK1ewtrbG2dmZ9evX06hRI37++WdKly6dDyEKIYTIrcKerMg8PiFEQdm7dy/JycnUrl2bpKQkRo4cia2trTL/SBQPGv8v2bNnT06ePImrqyujR4+mQ4cOLFy4kLS0NOkGFFp/8JKhS9pR+N5Pk7VOIYQQIj+lpaUxduxYLl++jKmpKU2bNmXNmjVZVmsT7zaNnwJf7O5s3bo158+f59ixYzg4OFCnTh2tBidEUSCJgHYUx6RUiHeZLMogChsPDw88PDwKOgxRwPL8sbqNjQ02NjbaiEUIIYQQQggh8s0bJT9RUVFERUVx8+bNLC9xWr58uVYCE6I4k14Q8a7Kj6GsQgghRG5p/L/QxIkTmTRpEi4uLlhaWua4NroQxYU8zAkhhBBCFA0aP7UtWbKEyMhItaUNhRCFW1FYiEIIIYQQIr9p/ATz5MkTmjZtmh+xCCGEEBqT92IJIYTILR1NT+jTpw/fffddfsQihBBCCCGEEPlG456fx48f8/XXX7Nnzx7q1KmTZW10edePEEIIIQqL0NDQd7q9F9na2hIYGEhgYGCBxfC2FKdrFdqlcfJz6tQp6tWrB8CZM2fUjsniB0IIIYo6eXeXeJt8fX1ZuXIlYWFhjB49Wtm/efNmvL29yczMLMDoNJOQkICdnZ2ybW5uTu3atZkyZQotWrTQaltxcXEYGxtrtU5RPGic/ERHR+dHHEIIIcQbkaXhRVFnYGDAjBkz6NevH+bm5gUdTp7t2bOHmjVr8t9//zF16lTat2/Pn3/+ScWKFbXWRvny5bVWlyheNJ7z86K///6bv//+W1uxCCGEEKIAtIoZlOcv8eZat26NhYUFYWFhryx34MABWrRogaGhIVZWVgQEBJCSkpJt2czMTEJDQ7G2tkZfX59KlSoREBCgHL9z5w49evTA3NwcIyMjPvroIy5cuKAcj4yMpHTp0uzatYvq1atjYmJC27ZtSUpKeu31lC1bFgsLC2rVqsXYsWO5f/8+hw8fVo6fOXOGjz76CBMTEypWrEj37t3577//lOMPHjygW7duGBsbY2lpydy5c3Fzc1Mb4mZra8u8efOU7cTERDp16oSJiQlmZmZ07tyZGzduKMdDQ0OpV68eq1evxtbWllKlSvH555/z4MGD116PeLdo/HFZRkYGU6ZMYfbs2SQnJwNgamrK8OHDGTduHDo6ecqnhBBCiHeOtlekkxXu3i26urpMmzaNL774goCAAKpUqZKlzKVLl2jbti1Tpkxh+fLl/Pvvv/j7++Pv78+KFSuylN+wYQNz585l7dq11KxZk+vXr3Py5EnluK+vLxcuXGDLli2YmZkxatQo2rVrx9mzZ5X53A8fPiQ8PJzVq1ejo6PDl19+yYgRI1izZk2uruvRo0esWrUKAD09PQDu3r1Lq1at6NOnD3PnzuXRo0eMGjWKzp07s3fvXgCGDRtGbGwsW7ZsoWLFigQHB/P7778r0y5elpGRoSQ++/bt4+nTpwwaNIguXboQExOjdg83b97M1q1buXPnDp07d2b69OlMnTo1V9cj3g0aJz/jxo3j22+/Zfr06TRr1gx49klEaGgojx8/ll8gIYQQRZq8x0oUBG9vb+rVq0dISAjffvttluNhYWF069ZN6f1wdHQkIiICV1dXFi9ejIGBgVr5xMRELCwsaN26NSVLlsTa2ppGjRoBKElPbGys8vqSNWvWYGVlxebNm/nss88ASEtLY8mSJVStWhUAf39/Jk2a9Npradq0KTo6Ojx8+JDMzEzee+89PvjgAwAWLlxI/fr1mTZtmlJ++fLlWFlZ8eeff2JpacnKlSv57rvvlHNWrFhBpUqVcmwvKiqK06dPc+XKFaysrABYtWoVNWvWJC4ujoYNGwLPkqTIyEhMTU0B6N69O1FRUfLsWsxo3E2zcuVKvvnmGwYMGECdOnWoU6cOAwcOZNmyZURGRuZDiEIIIYQQ774ZM2awcuVKzp3L2jN38uRJIiMjMTExUb48PDzIyMjgypUrWcp/9tlnPHr0CHt7e/z8/Ni0aRNPnz4F4Ny5c5QoUYL3339fKV+2bFmcnJzU2jYyMlISHwBLS0tu3rz52utYt24dx48fZ8OGDTg4OBAZGan0Jp08eZLo6Gi163B2dgae9cxcvnyZtLQ0JVEDKFWqFE5OTjm2d+7cOaysrJTEB6BGjRqULl1a7XpsbW2VxEeT6xHvFo0/3rp9+7byS/oiZ2dnbt++rZWghBBCCCGKm5YtW+Lh4cGYMWPw9fVVO5acnEy/fv3U5u08Z21tnWWflZUV8fHx7Nmzh927dzNw4EBmzZrFvn37ch3Py68zUalUuVp9zsrKCkdHRxwdHXn69Cne3t6cOXMGfX19kpOT6dChAzNmzMhynqWlJRcvXsx1fJrK7noyMjLyrT1ROGmc/NStW5eFCxcSERGhtn/hwoXUrVtXa4EJIYQQ4u3Ij6F+Mi/pzUyfPp169epl6elo0KABZ8+excHBIdd1GRoa0qFDBzp06MCgQYNwdnbm9OnTVK9enadPn3L48GFl2NutW7eIj4+nRo0aWr2eTz/9lODgYBYtWsTQoUNp0KABGzZswNbWlhIlsv7e2dvbU7JkSeLi4pSk7t69e/z555+0bNky2zaqV6/O1atXuXr1qtL7c/bsWe7evav16xFFn8b/2s2cORNPT0/27NlDkyZNADh06BBXr15l+/btWg9QCCGEKOpkOW6RW7Vr16Zbt25ZPmQeNWoUjRs3xt/fnz59+mBsbMzZs2fZvXs3CxcuzFJPZGQk6enpvP/++xgZGfG///0PQ0NDbGxsKFu2LJ06dcLPz4+lS5diamrK6NGjqVy5Mp06ddLq9ahUKgICAggNDaVfv34MGjSIZcuW0bVrV0aOHEmZMmW4ePEia9eu5ZtvvsHU1BQfHx+CgoIoU6YMFSpUICQkBB0dnRzfJ9m6dWvlvs2bN4+nT58ycOBAXF1dcXFx0er1iKJP43+NXV1d+fPPP/nqq684f/48AB9//DEDBw585WQ0IYQQQmiHJFO5FxoaWtAhaGzSpEmsW7dObV+dOnXYt28f48aNo0WLFmRmZlK1alW6dOmSbR2lS5dm+vTpDBs2jPT0dGrXrs3PP/9M2bJlgWeLCAwZMoT27dvz5MkTWrZsyfbt27MMDdMGHx8fxo0bx8KFCxk5ciSxsbGMGjWKDz/8kNTUVGxsbGjbtq2yYvCcOXPo378/7du3x8zMjJEjR3L16tUsizo8p1Kp+Omnnxg8eDAtW7ZER0eHtm3bsmDBAq1fiyj63uhfz0qVKsnKGEIIIYQQeZTdYlG2trakpqZm2d+wYUN++eWXHOtKSEhQvvfy8sLLyyvHsubm5soy1Nnx9fXNMu/Iy8vrlXN+bG1tsz1uZGSkNi/c0dGRjRs35liPqamp2nLaKSkpTJw4kb59+yr7XrxWeDbv6aeffsqxztDQ0CyJcGBgoNq7g0TxkKvk59SpU9SqVQsdHR1OnTr1yrJ16tTRSmBCCCGEEKL4OX78OOfPn6dRo0bcu3dPWV5b20PyRPGUq+SnXr16XL9+nQoVKlCvXr0cV/tQqVSkp6drPUghhBBCFC0yNE/kRXh4OPHx8ejp6fHee++xf/9+ypUrV9BhiXdArv5lunLlCuXLl1e+F0IIIYQQIj/Ur1+fY8eOFXQY4h2Vq+THxsZG+f6vv/6iadOmWZYnfPr0KQcPHlQrK4QQQgghhBCFhY6mJ7i7u2f7MtN79+7h7u6ulaCEEEIIIYQQQts0Tn4yMzOzXWf91q1bGBsbayUoIYQQQgghhNC2XM9G/Pjjj4Fnixr4+vqir6+vHEtPT+fUqVPKW4JF/jh9JbFI1CmEEEIIIURhlOvkp1SpUsCznh9TU1MMDQ2VY3p6ejRu3Bg/Pz/tRyiEEEIIIYQQWpDr5GfFihXAsxdYjRgxQoa4CSGEEEIIIYoUjRfhDwkJyY84hBBCCCG07u/R+99qe1Wmt3ir7eVWZGQkgYGB3L17F4DQ0FA2b97MiRMnCjSuvCjs16BSqdi0aRNeXl4FHYp4gcYLHgD8+OOPdO7cmcaNG9OgQQO1LyGEEEIIkTu+vr6oVCr69++f5digQYOUudZCO2JiYlCpVMpX+fLladeuHadPa/+1uklJSXz00Udar1fkjcY9PxEREYwbNw5fX19++uknevbsyaVLl4iLi2PQoEH5EeNbIYsJCCGEEKIgWFlZsXbtWubOnavMqX78+DHfffcd1tbWea4/LS0tz3Vo0lbJkiXfWntvKj4+HjMzM/755x+CgoLw9PTk4sWL6Onpaa0NCwsLrdUltEfjnp9Fixbx9ddfs2DBAvT09Bg5ciS7d+8mICCAe/fu5UeMQgghhBDvrAYNGmBlZcXGjRuVfRs3bsTa2pr69eurld25cyfNmzendOnSlC1blvbt23Pp0iXleEJCAiqVinXr1uHq6oqBgQFr1qzJse2lS5diZWWFkZERnTt3VnuWy8jIYNKkSVSpUgV9fX3q1avHzp07X9vW68573vvyfAgewIkTJ1CpVCQkJCj7li1bpsTm7e3NnDlzKF26dJZrWL16Nba2tpQqVYrPP/+cBw8evPJ+A1SoUAELCwsaNGhAYGAgV69e5fz588rxAwcO0KJFCwwNDbGysiIgIICUlBTleFJSEp6enhgaGmJnZ8d3332Hra0t8+bNU8qoVCo2b96sbJ8+fZpWrVphaGhI2bJl6du3L8nJycpxX19fvLy8CA8Px9LSkrJlyzJo0KC3mrwWBxonP4mJicqS1oaGhsovWPfu3fn++++1G50ock5fSczTlxBCCFEc9erVS1lcCmD58uX07NkzS7mUlBSGDRvG0aNHiYqKQkdHB29vbzIyMtTKjR49miFDhnDu3Dk8PDyybfPixYusX7+en3/+mZ07d3L8+HEGDhyoHJ8/fz6zZ88mPDycU6dO4eHhQceOHblw4cIr28rtea8SGxtL//79GTJkCCdOnKBNmzZMnTo1S7lLly6xefNmtm7dytatW9m3bx/Tp0/PdTv37t1j7dq1AEqvz6VLl2jbti2ffPIJp06dYt26dRw4cAB/f3/lvB49evDPP/8QExPDhg0b+Prrr7l582aO7aSkpODh4YG5uTlxcXH88MMP7NmzR61OgOjoaC5dukR0dDQrV64kMjKSyMjIXF+PeD2Nh71ZWFhw+/ZtbGxssLa25rfffqNu3bpcuXKFzMzM/IhRCCFEAZEPJYR4O7788kvGjBnDX3/9BTx7+F+7di0xMTFq5T755BO17eXLl1O+fHnOnj1LrVq1lP2BgYHKOxpz8vjxY1atWkXlypUBWLBgAZ6ensyePRsLCwvCw8MZNWoUn3/+OQAzZswgOjqaefPm8dVXX+XYVm7Pe5UFCxbw0UcfMWLECACqVavGwYMH2bp1q1q5jIwMIiMjMTU1BZ59GB8VFZVtovSiKlWqACi9OR07dsTZ2RmAsLAwunXrRmBgIACOjo5ERETg6urK4sWLSUhIYM+ePcTFxeHi4gLAN998g6OjY47tfffdd8r9fr5i8sKFC+nQoQMzZsygYsWKAJibm7Nw4UJ0dXVxdnbG09OTqKgoeZ2MFmnc89OqVSu2bNkCQM+ePRk6dCht2rShS5cueHt7az1AIYQQQoh3Xfny5fH09CQyMpIVK1bg6elJuXLlspS7cOECXbt2xd7eHjMzM2xtbYFnI3Ne9Pyh/FWsra2VxAegSZMmZGRkEB8fz/379/nnn39o1qyZ2jnNmjXj3LlzObalyXmvEh8fT6NGjdT2vbwNz17B8jzxAbC0tHxlD8xz+/fv59ixY0RGRlKtWjWWLFmiHDt58iSRkZGYmJgoXx4eHmRkZHDlyhXi4+MpUaKE2kJfDg4OmJub59jeuXPnqFu3rtqrYpo1a6bc7+dq1qyJrq6uxtcjck/jnp+vv/5a6VodNGgQZcuW5eDBg3Ts2JF+/fppPUBRvMmnzkJoRv5mhCi6evXqpQyDyqmHpEOHDtjY2LBs2TIqVapERkYGtWrV4smTJ2rl3ub7GDVtS0fn2WfvL44YetN5LS8vrqBSqbIMAcyOnZ0dpUuXxsnJiZs3b9KlSxd+/fVXAJKTk+nXrx8BAQFZzrO2tubPP/98o1hz402vR+SexsmPjo6O8ksL8Pnnnyvdmm/qq6++YtasWVy/fp26deuyYMGCbLP7l61du5auXbvSqVMntQllQghRFFZwLI6JSnG8ZiFyq23btjx58gSVSpXtPJ1bt24RHx/PsmXLaNHi2fuEDhw48MbtJSYm8s8//1CpUiUAfvvtN3R0dHBycsLMzIxKlSoRGxuLq6urck5sbOwrn9Fyc1758uWBZ4sGPO8tefldPU5OTsTFxante3lbWwYNGkRYWBibNm3C29ubBg0acPbsWRwcHLIt7+TkxNOnTzl+/Djvvfce8Gz+1J07d3Jso3r16kRGRpKSkqIki7Gxscr9Fm+PxskPwN27dzly5Ag3b97Mko326NFDo7rWrVvHsGHDWLJkCe+//z7z5s3Dw8OD+Ph4KlSokON5CQkJjBgxQvnjF0IUbfJQLIQo7nR1dZWhYS8OfXrO3NycsmXL8vXXX2NpaUliYiKjR49+4/YMDAzw8fEhPDyc+/fvExAQQOfOnZUlmoOCgggJCaFq1arUq1ePFStWcOLEiVeuHpeb8xwcHLCysiI0NJSpU6fy559/Mnv2bLU6Bg8eTMuWLZkzZw4dOnRg79697NixA5VK9cbXmxMjIyP8/PwICQnBy8uLUaNG0bhxY/z9/enTpw/GxsacPXuW3bt3s3DhQpydnWndujV9+/Zl8eLFlCxZkuHDh2NoaJhjfN26dSMkJAQfHx9CQ0P5999/GTx4MN27d1fm+4i3Q+Pk5+eff6Zbt24kJydjZmam9kNWqVQaJz9z5szBz89PWdFkyZIlbNu2jeXLl+f4B52enk63bt2YOHEi+/fvV1sqUYjXkYdsIYQoPqpML1ofkpqZmeV4TEdHh7Vr1xIQEECtWrVwcnIiIiICNze3N2rLwcGBjz/+mHbt2nH79m3at2/PokWLlOPPX2MyfPhwbt68SY0aNdiyZcsrJ/bn5rySJUvy/fffM2DAAOrUqUPDhg2ZMmUKn332mVJHs2bNWLJkCRMnTmT8+PF4eHgwdOhQFi5c+EbX+jr+/v7MmTOHH374gc6dO7Nv3z7GjRtHixYtyMzMpGrVqnTp0kUpv2rVKnr37k3Lli2xsLAgLCyMP/74AwMDg2zrNzIyYteuXQwZMoSGDRtiZGTEJ598wpw5c/LlekTONE5+hg8fTq9evZg2bRpGRkZ5avzJkyccO3aMMWPGKPt0dHRo3bo1hw4dyvG8SZMmUaFCBXr37s3+/ftf2UZqaiqpqanK9v379/MUsxBCEkghhNCW1y1j/PKw/tatW3P27Fm1fS/OnbG1tc129V1fX198fX2V7dDQUEJDQwEYMGBAtm3r6OgQEhJCSEhItsdzaut158Gz5ObUqVM5XgeAn5+f2ipnfn5+akPRXryG5wIDA5VV2rLj5uaWbcxWVlZq844aNmzIL7/8kmM9lpaWbN++Xdn++++/uXnzplp8L7dTu3Zt9u7dm2Od2f0uvPjeIKEdGic/165dIyAgIM+JD8B///1Henp6lu6+ihUrqr1o6kUHDhzg22+/zTI2NCdhYWFMnDgxr6EKIYQQQoi3KDw8nDZt2mBsbMyOHTtYuXKlWs9UQdq7dy/JycnUrl2bpKQkRo4cia2tLS1btizo0MRraJz8eHh4cPToUezt7fMjnld68OAB3bt3Z9myZdku/5idMWPGMGzYMGX7/v37WFlZ5VeIQmiF9KwIIYQo7o4cOcLMmTN58OAB9vb2RERE0KdPn4IOC3i2Ot3YsWO5fPkypqamNG3alDVr1mRZrU0UPhonP56engQFBXH27Flq166d5YfcsWPHXNdVrlw5dHV1uXHjhtr+GzduKJPtXnTp0iUSEhLo0KGDsu/5ggslSpQgPj6eqlWrqp2jr6+Pvr5+rmMS4l0kyZQQQoiiZv369QUdQo48PDyyXZFPFH4aJz/Px15OmjQpyzGVSkV6enqu69LT0+O9994jKioKLy8v4FkyExUVpaxz/yJnZ2dOnz6ttm/8+PE8ePCA+fPnS4+OEEIUQ5LcCyGEyC2Nkx9tv2hp2LBh+Pj44OLiQqNGjZg3bx4pKSnK6m89evSgcuXKhIWFYWBgQK1atdTOL126NECW/e8i28ff5bmOhLyHIV4iD15CCCGEEEXDG73nR5u6dOnCv//+S3BwMNevX6devXrs3LlTWQQhMTFR7aWqQgghRH6SDzSEEOLdVeDJDzxbWz27YW4AMTExrzz3dUtE5pb0qgghhBBCCPFuKxTJjyg4eU36ErQThhBCCCGEEPlOkp98JImFEEIIIYQQhUeukp9hw4YxefJkjI2N+fXXX2natCklSkjeJIQQQojCbXaX9m+1veHrtr7V9kTuREZGEhgYyN27dws6lLcmJiYGd3d37ty5oywQVlB8fX25e/cumzdvLtA4AHK1ksCCBQtITk4GwN3dndu3b+drUEIIIYQQxYGvry8qlYr+/ftnOTZo0CBUKhW+vr5vPzAtc3NzIzAwMMv+mJgYVCqV8uXm5vbKeho3bpzlXi1ZsgSVSpVlHrivry8tWrTIY+RFV9OmTUlKSqJUqVI5lrG1tVXuvZGREbVr1+abb77Reizz58/X2jz9vMpV942trS0RERF8+OGHZGZmcujQIczNzbMt27JlS60GKIQQQoj8JSvcFSwrKyvWrl3L3LlzMTQ0BODx48d89913WFtbF3B0+ev5A/pzenp6ryzv7u7Opk2b1PZFR0djZWVFTEyMWqIYExODj4+PVuMtSvT09LCwsHhtuUmTJuHn58fDhw/54Ycf8PPzo3Llynz00Udai+VVCdjblquen1mzZvHtt9/i7u6OSqXC29sbNze3LF/u7u75Ha8QQghR5Jy+kpinr/yuTxSsBg0aYGVlxcaNG5V9GzduxNramvr166uV3blzJ82bN6d06dKULVuW9u3bc+nSJeV4QkICKpWKjRs34u7ujpGREXXr1uXQoUNKmVu3btG1a1cqV66sfNr//fffK8e3bt1K6dKllRfXnzhxApVKxejRo5Uyffr04csvv8xVfb6+vuzbt4/58+crvQwJCQlERkZSoUIFLCwslK9ff/0VlUqV471yd3cnPj6e69evK/v27dvH6NGj1VYIvnLlCn/99VeWZ9Ndu3ZRvXp1TExMaNu2rVriFRcXR5s2bShXrhylSpXC1dWV33//Xe18lUrFN998g7e3N0ZGRjg6OrJlyxa1Mlu2bMHR0REDAwPc3d1ZuXIlKpVKGXL3uvsFz3rKAgICGDlyJGXKlMHCwoLQ0FDl+POf84kTJ5R9d+/eRaVSKffhea/a64b6mZqaYmFhgb29PaNGjaJMmTLs3r1brd4+ffpQvnx5zMzMaNWqFSdPnlSrY8qUKVSoUAFTU1P69OnD6NGjqVevnnLc19cXLy8vZTs1NZWAgAAqVKiAgYEBzZs3Jy4uTjn+PPaoqChcXFwwMjKiadOmxMfHv/JaciNXyY+XlxfXr1/n/v37ZGZmEh8fz507d7J8yXA4IYQQQgjN9erVixUrVijby5cvV174/qKUlBSGDRvG0aNHiYqKQkdHB29v7ywvoR83bhwjRozgxIkTVKtWja5du/L06VPgWa/Se++9x7Zt2zhz5gx9+/ale/fuHDlyBIAWLVrw4MEDjh8/DjxLLsqVK6eWXOzbt08Zova6+ubPn0+TJk3w8/MjKSmJpKQkrKys3ug+NWvWjJIlSxIdHQ3A2bNnefToEb179+bWrVtcuXIFeNYbZGBgQJMmTZRzHz58SHh4OKtXr+bXX38lMTGRESNGKMcfPHiAj48PBw4c4LfffsPR0ZF27drx4MEDtRgmTpxI586dOXXqFO3ataNbt27KM/CVK1f49NNP8fLy4uTJk/Tr149x48apnf+6+/XcypUrMTY25vDhw8ycOZNJkyapJSXalpGRwYYNG7hz545aD9xnn33GzZs32bFjB8eOHaNBgwZ88MEHyjWvWbOGqVOnMmPGDI4dO4a1tTWLFy9+ZVsjR45kw4YNrFy5kt9//x0HBwc8PDyy5BLjxo1j9uzZHD16lBIlStCrV688X6dGqxaYmJgQHR2NnZ2dLHggsiUr3AkhhBCa+/LLLxkzZgx//fUXALGxsaxduzbL+w4/+eQTte3ly5dTvnx5zp49S61atZT9I0aMwNPTE3j2sF6zZk0uXryIs7MzlStXVnvoHzx4MLt27WL9+vU0atSIUqVKUa9ePWJiYnBxcSEmJoahQ4cyceJEkpOTuXfvHhcvXsTV1RUgV/Xp6elhZGSUq2FYr2JsbEyjRo2IiYmha9euxMTE0Lx5c/T19WnatCkxMTHY2dkRExNDkyZN0NfXV85NS0tjyZIlVK1aFXj2nslJkyYpx1u1aqXW1tdff03p0qXZt28f7dv/38IZvr6+dO3aFYBp06YRERHBkSNHaNu2LUuXLsXJyYlZs2YB4OTkxJkzZ5g6dapy/uvu13N16tQhJCQEAEdHRxYuXEhUVBRt2rTJ0z182ahRoxg/fjypqak8ffqUMmXK0KdPHwAOHDjAkSNHuHnzpnIvw8PD2bx5Mz/++CN9+/ZlwYIF9O7dW0nWg4OD+eWXX5T1Al6WkpLC4sWLiYyMVIbWLVu2jN27d/Ptt98SFBSklJ06daryezZ69Gg8PT15/PgxBgYGb3y9Gmcwrq6upKens2HDBs6dOwdAjRo16NSpE7q6um8ciBBCFDdF4cOCohCjEO+C8uXL4+npSWRkJJmZmXh6elKuXLks5S5cuEBwcDCHDx/mv//+U3p8EhMT1ZKfOnXqKN9bWloCcPPmTZydnUlPT2fatGmsX7+ea9eu8eTJE1JTUzEyMlLOcXV1JSYmhuHDh7N//37CwsJYv349Bw4c4Pbt21SqVAlHR0eAXNX3JhITE6lRo4ayPXbsWMaOHYubmxs//PAD8Gx41PMeqOcx9+zZk5iYGPz8/NTqMzIyUhKf5/fl5s2byvaNGzcYP348MTEx3Lx5k/T0dB4+fEhiovpQ0RfvrbGxMWZmZko98fHxNGzYUK38iwkN5P5+vdhOdvFqS1BQEL6+viQlJREUFMTAgQNxcHAA4OTJkyQnJ1O2bFm1cx49eqQMt4yPj2fgwIFqxxs1asTevXuzbe/SpUukpaXRrFkzZV/JkiVp1KiRkls8l9PvcV7mwmmc/Fy8eBFPT0/+/vtvnJycAAgLC8PKyopt27ap/VIJIURByetDO2R9cC8KiUBRiFEIkb1evXrh7+8PwFdffZVtmQ4dOmBjY8OyZcuoVKkSGRkZ1KpViydPnqiVK1mypPL98zk0zxOlWbNmMX/+fObNm0ft2rUxNjYmMDBQrQ43NzeWL1/OyZMnKVmyJM7Ozri5uRETE8OdO3eUT+NzW192dHR0yMzMVNuXlpamfF+pUiW1OS1lypQBns37mTp1KteuXSMmJkbpRXF1dWXp0qVcunSJq1evZunJefGePL8vL7bv4+PDrVu3mD9/PjY2Nujr69OkSZNX3tvn9bw87PBVcnu/XtWOjs6zmSsvxv/ivdNEuXLlcHBwwMHBgR9++IHatWvj4uJCjRo1SE5OxtLSMksPJPBWls9+1e/xm9I4+QkICMDe3p5Dhw4pv4S3bt3iyy+/JCAggG3btuUpICFelB8PsEIIIURh1LZtW548eYJKpcLDwyPL8Vu3bhEfH8+yZcuUJZwPHDigcTuxsbF06tRJWbAgIyODP//8U62X5fm8n7lz5yqJjpubG9OnT+fOnTsMHz5co/r09PSUBRSeK1++PA8ePCAlJQVjY2MAtWSnRIkSSg/Ei5o2bYqenh6LFi1S5s8ANGzYkH///Zfly5crw+M0vS+LFi2iXbt2AFy9epX//vtPozqcnJzYvn272r4XJ/I/b+d19+t1ypcvD0BSUpKyKMaL9+5NWVlZ0aVLF8aMGcNPP/1EgwYNuH79OiVKlMDW1jbbc5ycnIiLi6NHjx7Kvpev+UVVq1ZFT0+P2NhYbGxsgGeJW1xcXLbLoWubxsnPvn37+O2335TEB6Bs2bJMnz5drftKCCGEeJl8oCFEznR1dZVhP9lNJTA3N6ds2bJ8/fXXWFpakpiYqLYCW245Ojry448/cvDgQczNzZkzZw43btxQe/g2NzenTp06rFmzhoULFwLPXmfSuXNn0tLS1Hp+clOfra0thw8fJiEhARMTE8qUKcP777+PkZERY8eOJSAggMOHD+fqXTCGhoY0btyYBQsW0KxZM+Ve6enpqe1/ueckN/dl9erVuLi4cP/+fYKCgpSlx3OrX79+zJkzh1GjRtG7d29OnDihXNPznovc3K/XeX4Ppk+fjp2dHTdv3mT8+PEaxZqTIUOGUKtWLY4ePUrr1q1p0qQJXl5ezJw5k2rVqvHPP/+wbds2vL29cXFxYfDgwfj5+eHi4kLTpk1Zt24dp06dwt7ePtv6jY2NGTBgAEFBQZQpUwZra2tmzpzJw4cP6d27t1au4VU0Tn709fWzrHoBkJyc/Nq12YUQIicyXEsIkR+Gr9ta0CFoxMzMLMdjOjo6rF27loCAAGrVqoWTkxMRERGvfTHoy8aPH8/ly5fx8PDAyMiIvn374uXlxb1799TKubq6cuLECaX+MmXKUKNGDW7cuKFMfchtfSNGjMDHx4caNWrw6NEjrly5gq2tLf/73/8ICgpi2bJlfPDBB4SGhtK3b9/XXoO7uzu//vprlmt3dXUlOjr6jV6/8u2339K3b19l6fFp06apLUyQG3Z2dvz4448MHz5cWeVu3LhxDBgwQFkwILf3/3WWL19O7969ee+993BycmLmzJl8+OGHGtWRnRo1avDhhx8SHBzM9u3b2b59O+PGjaNnz578+++/WFhY0LJlSypWrAhAt27duHz5MiNGjODx48d07twZX1/fLKvXvWj69OlkZGTQvXt3Hjx4gIuLC7t27crxPaLapMp8ebDla/To0YPff/+db7/9VulOPHz4MH5+frz33nuF5u2tObl//z6lSpXi3r17av/A2I7O+3C9hOmeatt5rVPb9eVHnYW9vvyo8+X6CNXCi7tCX/oHL6915nN9ReHnUhxizPK7mA91Frb6squz0P295Eedhb2+/Kjzpfpy+v8bni0dfOXKFezs7PK0CpQQ+WHq1KksWbKEq1evFnQob02bNm2wsLBg9erVb6U9Tf4N0LjnJyIiAh8fH5o0aaJ0Jz59+pSOHTsy//+1d99RUV3f28CfGfoAih1UEAnSFLGACjZUEEuM2GNUxIjG3gtGo2LD3lu+FhArdo1iRbFgwQY2wIoYRTSxIoII5/eHL/d1AiiDICDPZy3W8t5zZt99hkxmNufcM4sW5SxjIlLCWRAiIqLCafny5XBwcECpUqUQGhqKOXPmSBtZfI8SExOxcuVKuLm5QU1NDZs3b8bRo0fz9DuJvobKxY+BgQH27NmDO3fuSOtSra2tM70hjYiIiIioKLl9+zamTZuG58+fw8TEBCNHjsS4cePyO608I5PJEBQUhOnTpyMpKQmWlpbYsWMHXFxc8ju1TOX4m0rTt8QjooKPM0lERETfxoIFC7BgwYL8TuOb0dHRwdGjR/M7jWzLcfFDRB9x9yoiIiKiwkGe3wkQERERERF9C5z5ISKiQo3LOomIKLs480NEREREREVCjoqfU6dOoXv37nB0dMSjR48AAOvXr8fp06dzNTkiIiIiIqLcovKytx07dqBHjx7o1q0brly5guTkZADAq1evMGPGDAQFBeV6kkRERN8KNzEhIvp+qVz8TJs2DStXroSHhwe2bNkina9fvz6mTZuWq8kRERERfY1l/Y590+sNXNn0m14vp/z9/TFs2DC8fPkyv1P5bnl6euLly5fYvXt3fqdCn1B52Vt0dDQaNWqU4Xzx4sX5AiIiIiJSgaenJ9zd3TOcDwkJgUwmK7CfrWJiYiCTyXL8eGdnZ8hkMumnXLly6NSpEx48eJCLWWbO1NRUuq5CoYCtrS1Wr16d69dZtGgR/P39cz0ufR2Vix9DQ0PcuXMnw/nTp0/DzMwsV5IiIiIiou9bnz59EBcXh8ePH2PPnj14+PAhunfv/k2uPWXKFMTFxeH69evo3r07+vTpgwMHDuTqNYoXLw4DA4NcjUlfT+Xip0+fPhg6dCjOnz8PmUyGx48fY+PGjRg1ahT69++fFzkSERERFWn//vsvunbtigoVKkizFZs3b5ba9+3bBwMDA6SmpgIAwsPDIZPJ4O3tLfXx8vLKsrh49uwZ7O3t0a5dOyQnJyMtLQ2+vr6oXLkydHR0YGdnh+3bt2eZ34MHD9CmTRuUKFECurq6qFq16hfvA1coFDA0NISRkRHq1auHQYMG4fLly1J7amoqevfuLeVgaWmJRYsWSe0nT56EhoYGnjx5ohR32LBhaNiw4Wevra+vD0NDQ5iZmWHs2LEoWbIkjhw5IrW/fPkSXl5eKFOmDIoVK4amTZsiIiJCKca0adNQtmxZ6Ovrw8vLC97e3qhRo4bU/t9ZveTkZAwZMgRly5aFtrY2GjRogAsXLkjt6bN9wcHBsLe3h0KhgJOTE6Kjoz87FlKNysWPt7c3fvnlFzRr1gwJCQlo1KgRvLy88Ntvv2Hw4MF5kSMRERFRkZaUlITatWtj//79uH79Ovr27YsePXogLCwMANCwYUO8efMGV65cAQCcOHECpUuXRkhIiBTjxIkTcHZ2zhD74cOHaNiwIapVq4bt27dDS0sLvr6+CAgIwMqVK3Hjxg0MHz4c3bt3x4kTJzLNb+DAgUhOTsbJkydx7do1zJo1C3p6etke3/Pnz7F161bUrVtXOpeWloaKFSti27ZtuHnzJiZOnIjff/8dW7duBQA0atQIZmZmWL9+vfSYlJQUbNy4Eb/++mu2rpuWloYdO3bgxYsX0NTUlM536tQJT58+xYEDB3Dp0iXUqlULzZo1w/PnzwEAGzduxPTp0zFr1ixcunQJJiYmWLFixWevNWbMGOzYsQPr1q3D5cuXYW5uDjc3NylmuvHjx2PevHm4ePEi1NXVsz0Wyh6VNjxITU1FaGgoBg4ciNGjR+POnTtISEiAjY2NSv+BExERUcHBHe7y1759+zJ8jkqfwUlXoUIFjBo1SjoePHgwDh06hK1bt6JOnTooXrw4atSogZCQENjb2yMkJATDhw+Hj48PEhIS8OrVK9y5cweNGzdWihsdHQ1XV1e0a9cOCxcuhEwmQ3JyMmbMmIGjR4/C0dERAGBmZobTp0/jzz//ROPGjWFqagohhBQnNjYWHTp0gK2trdT/S5YvX47Vq1dDCIHExERYWFjg0KFDUruGhgZ8fHyk48qVK+Ps2bPYunUrOnfuDADo3bs3/Pz8MHr0aADAX3/9haSkJKk9K2PHjsWECROQnJyMDx8+oGTJkvDy8gLw8VaOsLAwPH36FFpaWgCAuXPnYvfu3di+fTv69u2LJUuWoHfv3ujVqxcAYOLEiTh8+DASEhIyvd7bt2+xYsUK+Pv7o2XLlgCAVatW4ciRI1izZo2UPwBMnz5d+j15e3ujdevWSEpKgra29hefU/oylYofNTU1NG/eHJGRkTAwMICNjU1e5UVERPTd+NriIiaP41H+atKkSYZZg/PnzystUUtNTcWMGTOwdetWPHr0CO/fv0dycjIUCoXUp3HjxggJCcHIkSNx6tQp+Pr6YuvWrTh9+jSeP3+O8uXLo0qVKlL/d+/eoWHDhvjll1+wcOFC6fydO3eQmJgIV1dXpZzev3+PmjVrZjqGIUOGoH///jh8+DBcXFzQoUMHVK9e/bPj7tatG8aPHw8AiI+Px4wZM9C8eXNcunQJ+vr6AIBly5Zh7dq1iI2Nxbt37/D+/fsMS8smTJiAc+fOoV69evD390fnzp2hq6v72WuPHj0anp6eiIuLw+jRozFgwACYm5sDACIiIpCQkIBSpUopPebdu3e4e/cugI9F44ABA5Ta69Spg2PHMt9d8O7du0hJSUH9+vWlcxoaGqhTpw4iIyOV+n76vBkZGQEAnj59ChMTk8+OibJH5a2uq1Wrhnv37qFy5cp5kQ8RERFRkaKrqyt98E73999/Kx3PmTMHixYtwsKFC2FrawtdXV0MGzYM79+/l/o4Oztj7dq1iIiIgIaGBqysrODs7IyQkBC8ePEiw6yPlpYWXFxcsG/fPowePRoVKlQAAGn2Yv/+/dK5Tx+TGS8vL7i5uWH//v04fPgwfH19MW/evM/eElG8eHFp3Obm5lizZg2MjIwQGBgILy8vbNmyBaNGjcK8efPg6OgIfX19zJkzB+fPn5dilC1bFm3atIGfnx8qV66MAwcOKC31y0rp0qVhbm4Oc3NzbNu2Dba2trC3t4eNjQ0SEhJgZGSUaZxvsYGBhoaG9O/0HfXS0tLy/LpFhcr3/EybNg2jRo3Cvn37EBcXh9evXyv9EBEREVHuCg0NRdu2bdG9e3fY2dnBzMwMt27dUuqTft/PggULpEInvfgJCQnJcL+PXC7H+vXrUbt2bTRp0gSPHz8GANjY2EBLSwuxsbFSgZD+Y2xsnGWOxsbG6NevH3bu3ImRI0di1apVKo1RTU0NwMcZlvQxOzk5YcCAAahZsybMzc2lmZdPeXl5ITAwEP/73//www8/KM2uZIexsTG6dOmCcePGAQBq1aqFJ0+eQF1dPcP4S5cuDQCwtLRU2qwAQIbjT/3www/Q1NREaGiodC4lJQUXLlzgSqpvTOWZn1atWgEAfvrpJ6X93YUQkMlkGdaoEhEREdHXqVKlCrZv344zZ86gRIkSmD9/PuLj45U+OJcoUQLVq1fHxo0bsXTpUgAfNwXo3LkzUlJSMsz8AB8Ljo0bN6Jr165o2rQpQkJCYGhoiFGjRmH48OFIS0tDgwYN8OrVK4SGhqJYsWLo2bNnhjjDhg1Dy5YtYWFhgRcvXuD48eOwtrb+7JgSExOlndri4+MxdepUaGtro3nz5tKYAwICcOjQIVSuXBnr16/HhQsXMqw+cnNzQ7FixTBt2jRMmTJFtSf2/xk6dCiqVauGixcvwsXFBY6OjnB3d8fs2bNhYWGBx48fY//+/WjXrh3s7e0xePBg9OnTB/b29nByckJgYCCuXr2a5b1Ourq66N+/P0aPHo2SJUvCxMQEs2fPRmJiInr37p2jnClnVC5+jh8/nhd5EBEREeW6gSub5ncKuWLChAm4d+8e3NzcoFAo0LdvX7i7u+PVq1dK/Ro3bozw8HBplqdkyZKwsbFBfHw8LC0tM42trq6OzZs3o0uXLlIBNHXqVJQpUwa+vr64d+8eDAwMUKtWLfz++++ZxkhNTcXAgQPx999/o1ixYmjRogUWLFjw2TGtWrVKmh1KL9yCgoKkPH/77TdcuXIFXbp0gUwmQ9euXTFgwIAM38cjl8vh6emJGTNmwMPD44vPZWZsbGzQvHlzTJw4EUFBQQgKCsL48ePRq1cvPHv2DIaGhmjUqBHKlSsH4OP9Svfu3cOoUaOkDRY8PT2l3fcyM3PmTKSlpaFHjx548+YN7O3tcejQIZQoUSJHOVPOqFz8ZPZXAyIiIiJSnb+/f6bnnZ2dlXZTK1myJHbv3v3FeAsXLlTavAD4+J0//+Xp6QlPT0/pWF1dHTt27FDqM3ToUAwdOvSL1wSAJUuWZKtfuuzcl6OlpQU/Pz/4+fkpnff19c3Q99GjR2jVqpW0QcDnxMTEZHr+4MGD0r/19fWxePFiLF68OMs4f/zxB/744w/p2NXVVenerf/+brW1tT8b87+/cwCoUaNGhnP0dVQuftIlJiYiNjZW6UY7AF/c2YOIiIiIKDe8evUK165dw6ZNm7B3795vdt3ExESsXLkSbm5uUFNTw+bNm3H06FGlL0qlgknl4ufZs2fo1atXhinHdLznh4iIiIi+hbZt2yIsLAz9+vXLsDV3XpLJZAgKCsL06dORlJQES0tL7NixAy4uLt8sB8oZlYufYcOG4eXLlzh//jycnZ2xa9cuxMfHY9q0aZg3b15e5EhERESFDL+LiL6F7Cyfyws6Ojo4evRovlybvo7Kxc+xY8ewZ88e2NvbQy6Xo1KlSnB1dUWxYsXg6+uL1q1b50WeREREREREX0Xl7/l5+/YtypYtC+DjzhzPnj0DANja2uLy5cu5mx0REREREVEuUbn4sbS0RHR0NADAzs4Of/75Jx49eoSVK1dma4cNIiIiIiKi/KDysrehQ4ciLi4OADBp0iS0aNECGzduhKamZpbbNRIREREREeU3lYuf7t27S/+uXbs2Hjx4gKioKJiYmKB06dK5mhwREREREVFuyfH3/KRTKBSoVatWbuRCRERERESUZ1QuflJTU+Hv74/g4GA8ffoUaWlpSu3Hjh3LteSIiIiIvkaklfU3vZ51VGSexZbJZNi1axfc3d1ztW9REhMTg8qVK+PKlSuoUaNGfqdD+UDlDQ+GDh2KoUOHIjU1FdWqVYOdnZ3SDxERERFl35MnTzB06FCYm5tDW1sb5cqVQ/369bFixQokJiZK/eLi4tCyZct8zDTv+Pv7QyaTQSaTQS6Xw8jICF26dEFsbGyuXsfY2BhxcXGoVq1arsalwkPlmZ8tW7Zg69ataNWqVV7kQ0RERFRk3Lt3D/Xr14eBgQFmzJgBW1tbaGlp4dq1a/jf//6HChUq4KeffgIAGBoa5muu79+/h6amZp7FL1asGKKjoyGEwP379zFgwAB06tQJ58+fz7VrqKmp5fvzSPlL5ZkfTU1NmJub50UuREREREXKgAEDoK6ujosXL6Jz586wtraGmZkZ2rZti/3796NNmzZSX5lMht27dwP4WIgMGjQIRkZG0NbWRqVKleDr66sUO32mSEdHB2ZmZti+fbtS+7Vr19C0aVPo6OigVKlS6Nu3LxISEqR2T09PuLu7Y/r06ShfvjwsLS0RExMDmUyGnTt3okmTJlAoFLCzs8PZs2eVYp8+fRoNGzaEjo4OjI2NMWTIELx9+/azz4VMJoOhoSGMjIzg5OSE3r17IywsDK9fv5b67NmzB7Vq1YK2tjbMzMzg4+ODDx8+SO1RUVFo0KABtLW1YWNjg6NHjyo9b+n5h4eHS485ceIE6tSpAy0tLRgZGcHb21spprOzM4YMGYIxY8agZMmSMDQ0xOTJkz87Fiq4VC5+Ro4ciUWLFkEIkRf5EBERERUJ//77Lw4fPoyBAwdCV1c30z4ymSzT84sXL8bevXuxdetWREdHY+PGjTA1NVXq88cff6BDhw6IiIhAt27d8PPPPyMy8uM9SW/fvoWbmxtKlCiBCxcuYNu2bTh69CgGDRqkFCM4OBjR0dE4cuQI9u3bJ50fP348Ro0ahfDwcFhYWKBr165SwXD37l20aNECHTp0wNWrVxEYGIjTp09niP05T58+xa5du6CmpgY1NTUAwKlTp+Dh4YGhQ4fi5s2b+PPPP+Hv74/p06cD+Hhfuru7OxQKBc6fP4///e9/GD9+/Gev8+jRI7Rq1QoODg6IiIjAihUrsGbNGkybNk2p37p166Crq4vz589j9uzZmDJlCo4cOZLt8VDBka1lb+3bt1c6PnbsGA4cOICqVatCQ0NDqW3nzp25lx0RERHRd+rOnTsQQsDS0lLpfOnSpZGUlAQAGDhwIGbNmpXhsbGxsahSpQoaNGgAmUyGSpUqZejTqVMneHl5AQCmTp2KI0eOYMmSJVi+fDk2bdqEpKQkBAQESIXX0qVL0aZNG8yaNQvlypUDAOjq6mL16tXScreYmBgAwKhRo9C6dWsAgI+PD6pWrYo7d+7AysoKvr6+6NatG4YNGwYAqFKlChYvXozGjRtjxYoV0NbWzvT5ePXqFfT09CCEkO51GjJkiJSfj48PvL290bNnTwCAmZkZpk6dijFjxmDSpEk4cuQI7t69i5CQEGlp2/Tp0+Hq6prl72D58uUwNjbG0qVLIZPJYGVlhcePH2Ps2LGYOHEi5PKP8wTVq1fHpEmTpPEsXboUwcHBn41NBVO2ip/ixYsrHbdr1y5PkiEiIiIq6sLCwpCWloZu3bohOTk50z6enp5wdXWFpaUlWrRogR9//BHNmzdX6uPo6JjhOH25V2RkJOzs7JRmnOrXr4+0tDRER0dLxY+trW2m9/lUr15d+reRkRGAj7M1VlZWiIiIwNWrV7Fx40apjxACaWlpuH//PqytM9+BT19fH5cvX0ZKSgoOHDiAjRs3SrM6ABAREYHQ0FClc6mpqUhKSkJiYiKio6NhbGysdE9PnTp1Mr1WusjISDg6OirNsNWvXx8JCQn4+++/YWJikmG86WN++vTpZ2NTwZSt4sfPzy+v8yAiIiIqUszNzSGTyRAdHa103szMDACgo6OT5WNr1aqF+/fv48CBAzh69Cg6d+4MFxeXDPf1fK2sluN9uvInvXBI//qThIQE/PbbbxgyZEiGx6UXE5mRy+XSfeXW1ta4e/cu+vfvj/Xr10txfXx8MqxIApDlbFJu+e9KJ5lMluHrXqhwUPmen3fv3iltu/jgwQMsXLgQhw8fztXEiIiIiL5npUqVgqurK5YuXfrFzQAyU6xYMXTp0gWrVq1CYGAgduzYgefPn0vt586dU+p/7tw5adbF2toaERERStcNDQ2FXC7PsAxPVbVq1cLNmzdhbm6e4UeV3eK8vb0RGBiIy5cvS3Gjo6MzjZue98OHDxEfHy/FuHDhwmevYW1tjbNnzyrdyx4aGgp9fX1UrFhRxZFTYaBy8dO2bVsEBAQAAF6+fIk6depg3rx5aNu2LVasWJHrCRIRERF9r5YvX44PHz7A3t4egYGBiIyMRHR0NDZs2ICoqCjpZv//mj9/PjZv3oyoqCjcunUL27Ztg6GhIQwMDKQ+27Ztw9q1a3Hr1i1MmjQJYWFh0qYD3bp1g7a2Nnr27Inr16/j+PHjGDx4MHr06CEtecupsWPH4syZMxg0aBDCw8Nx+/Zt7NmzR6UND4CP38nTrl07TJw4EQAwceJEBAQEwMfHBzdu3EBkZCS2bNmCCRMmAABcXV3xww8/oGfPnrh69SpCQ0Oltqw2jhgwYAAePnyIwYMHIyoqCnv27MGkSZMwYsQI6X4f+r6o/D0/ly9fxoIFCwAA27dvh6GhIa5cuYIdO3Zg4sSJ6N+/f64nSURERJQT1lGR+Z3CZ/3www+4cuUKZsyYgXHjxuHvv/+GlpYWbGxsMGrUKAwYMCDTx+nr62P27Nm4ffs21NTU4ODggKCgIKUP7D4+PtiyZQsGDBgAIyMjbN68GTY2NgAAhUKBQ4cOYejQoXBwcIBCoUCHDh0wf/78rx5T9erVceLECYwfPx4NGzaEEAI//PADunTponKs4cOHw9HREWFhYXBzc8O+ffswZcoUzJo1CxoaGrCyspI2dVBTU8Pu3bvh5eUFBwcHmJmZYc6cOWjTpk2Wy+IqVKiAoKAgjB49GnZ2dihZsiR69+4tFU30/VG5+ElMTIS+vj4A4PDhw2jfvj3kcjnq1auHBw8e5HqCRERERN8zIyMjLFmyBEuWLPlsv0+XZvXp0wd9+vT5Yt+siifg42YGx44dy7Ld398/wzlTU9MMX3diYGCQ4ZyDg4NKt0R4enrC09Mzw/l69eopxXZzc4Obm1uWcaysrHD69GnpODQ0FACke4kyy79x48YICwvLMmZISEiGc+nfG0SFj8rzeebm5ti9ezcePnyIQ4cOSTuLPH36FMWKFcv1BImIiIiIsmPXrl04cuQIYmJicPToUfTt2xf169fHDz/8kN+pUQGhcvEzceJEjBo1Cqampqhbt660jeLhw4dRs2bNXE+QiIiIiCg73rx5g4EDB8LKygqenp5wcHDAnj178jstKkBUXvbWsWNHNGjQAHFxcbCzs5PON2vWjN//Q0RERET5xsPDAx4eHvmdBhVgKhc/AGBoaKj0BVLAl79EioiIiIiIKD9xDz8iIiIiIioSWPwQEREREVGRwOKHiIiIiIiKhAJR/CxbtgympqbQ1tZG3bp1P7vX+qpVq9CwYUOUKFECJUqUgIuLy2f7ExERERERAQWg+AkMDMSIESMwadIkXL58GXZ2dnBzc8PTp08z7R8SEoKuXbvi+PHjOHv2LIyNjdG8eXM8evToG2dOREREVHSZmppi4cKF+Z3GNzd58mTUqFEjv9OgHMrRbm+5af78+ejTpw969eoFAFi5ciX279+PtWvXwtvbO0P/jRs3Kh2vXr0aO3bsQHBwMLc2JCIiIiW262y/6fWu9bym8mOePHmC6dOnY//+/Xj06BHKli2LGjVqYNiwYWjWrFmu5ebp6YmXL19i9+7duRazIHF2dsaJEycAAFpaWjAxMUGvXr3g7e0NmUyWa9cZNWoUBg8enGvx6NvK1+Ln/fv3uHTpEsaNGyedk8vlcHFxwdmzZ7MVIzExESkpKShZsmSm7cnJyUhOTpaOX79+/XVJExEREeWSmJgY1K9fHwYGBpgzZw5sbW2RkpKCQ4cOYeDAgYiKisrvFDN4//49NDU18yS2EAKpqalQV8/ZR9Q+ffpgypQpSE5OxrFjx9C3b18YGBigf//+uZajnp4e9PT0ci0efVv5uuztn3/+QWpqKsqVK6d0vly5cnjy5Em2YowdOxbly5eHi4tLpu2+vr4oXry49GNsbPzVeRMRERHlhgEDBkAmkyEsLAwdOnSAhYUFqlatihEjRuDcuXNSv/nz58PW1ha6urowNjbGgAEDkJCQILX7+/vDwMAAhw4dgrW1NfT09NCiRQvExcUB+LhUa926ddizZw9kMhlkMhlCQkIAAA8fPkTnzp1hYGCAkiVLom3btoiJiZFie3p6wt3dHdOnT0f58uVhaWkptb158wZdu3aFrq4uKlSogGXLlkltMTExkMlkCA8Pl869fPlS6dohISGQyWQ4cOAAateuDS0tLWzYsAFyuRwXL15Ueq4WLlyISpUqIS0tLcvnU6FQwNDQEJUqVUKvXr1QvXp1HDlyRGpPTk7GqFGjUKFCBejq6qJu3bpSLulWrVoFY2NjKBQKtGvXDvPnz4eBgYHU/t9lb2lpaZgyZQoqVqwILS0t1KhRAwcPHszwPOzcuRNNmjSBQqGAnZ1dtv/QT7kr3+/5+RozZ87Eli1bsGvXLmhra2faZ9y4cXj16pX08/Dhw2+cJREREVFGz58/x8GDBzFw4EDo6upmaP/0A7dcLsfixYtx48YNrFu3DseOHcOYMWOU+icmJmLu3LlYv349Tp48idjYWIwaNQrAx6VanTt3lgqiuLg4ODk5ISUlBW5ubtDX18epU6cQGhoqFU7v37+XYgcHByM6OhpHjhzBvn37pPNz5syBnZ0drly5Am9vbwwdOlSp2Mgub29vzJw5E5GRkfjpp5/g4uICPz8/pT5+fn7w9PSEXP7lj69CCJw6dQpRUVFKs1SDBg3C2bNnsWXLFly9ehWdOnVCixYtcPv2bQBAaGgo+vXrh6FDhyI8PByurq6YPn36Z6+1aNEizJs3D3PnzsXVq1fh5uaGn376SYqZbvz48Rg1ahTCw8NhYWGBrl274sOHD9l9iiiX5Ouyt9KlS0NNTQ3x8fFK5+Pj42FoaPjZx86dOxczZ87E0aNHUb169Sz7aWlpQUtLK1fyJSIiIsotd+7cgRACVlZWX+w7bNgw6d+mpqaYNm0a+vXrh+XLl0vnU1JSsHLlSvzwww8APn7QnzJlCoCPS7V0dHSQnJys9Blrw4YNSEtLw+rVq6X7Yvz8/GBgYICQkBA0b94cAKCrq4vVq1dnWO5Wv3596R5tCwsLhIaGYsGCBXB1dVXpuZgyZYrSY7y8vNCvXz/Mnz8fWlpauHz5Mq5du4Y9e/Z8Ns7y5cuxevVqvH//HikpKdDW1saQIUMAALGxsfDz80NsbCzKly8P4GNRePDgQfj5+WHGjBlYsmQJWrZsKRWNFhYWOHPmjFLB919z587F2LFj8fPPPwMAZs2ahePHj2PhwoVKM2GjRo1C69atAQA+Pj6oWrUq7ty5k63fP+WefJ350dTURO3atREcHCydS0tLQ3BwMBwdHbN83OzZszF16lQcPHgQ9vb23yJVIiIiolwlhMh236NHj6JZs2aoUKEC9PX10aNHD/z7779ITEyU+igUCqnwAQAjI6Msd89NFxERgTt37kBfX1+6l6VkyZJISkrC3bt3pX62traZ3ufz389rjo6OiIyMzPa40v3385y7uzvU1NSwa9cuAB+X9TVp0gSmpqafjdOtWzeEh4cjNDQULVu2xPjx4+Hk5AQAuHbtGlJTU2FhYSGNVU9PDydOnJDGGh0djTp16ijF/O/xp16/fo3Hjx+jfv36Sufr16+f4Xn49I/1RkZGAPDF3w/lvnzf7W3EiBHo2bMn7O3tUadOHSxcuBBv376Vdn/z8PBAhQoV4OvrC+BjNT1x4kRs2rQJpqam0r1BvPmMiIiICpMqVapAJpN9cVODmJgY/Pjjj+jfvz+mT5+OkiVL4vTp0+jduzfev38PhUIBANDQ0FB6nEwm+2KBlZCQgNq1a2fYTRcAypQpI/07s2V5X5K+PO3THFJSUjLt+9/4mpqa8PDwgJ+fH9q3b49NmzZh0aJFX7xm8eLFYW5uDgDYunUrzM3NUa9ePbi4uCAhIQFqamq4dOkS1NTUlB73LT5Dfvr7SZ9l+9z9S5Q38r346dKlC549e4aJEyfiyZMn0k1i6ZsgxMbGKq3tXLFiBd6/f4+OHTsqxZk0aRImT578LVMnIiIiyrGSJUvCzc0Ny5Ytw5AhQzIUAC9fvoSBgQEuXbqEtLQ0zJs3T/pMtHXrVpWvp6mpidTUVKVztWrVQmBgIMqWLYtixYqpHPPTTRnSj62trQH8/+IpLi4ONWvWBAClzQ++xMvLC9WqVcPy5cvx4cMHtG/fXqXc9PT0MHToUIwaNQpXrlxBzZo1kZqaiqdPn6Jhw4aZPsbS0hIXLlxQOvff408VK1YM5cuXR2hoKBo3biydDw0N/eyMEeWfArHhwaBBg/DgwQMkJyfj/PnzqFu3rtQWEhICf39/6TgmJgZCiAw/LHyIiIiosFm2bBlSU1NRp04d7NixA7dv30ZkZCQWL14sLSkzNzdHSkoKlixZgnv37mH9+vVYuXKlytcyNTXF1atXER0djX/++QcpKSno1q0bSpcujbZt2+LUqVO4f/8+QkJCMGTIEPz9999fjBkaGorZs2fj1q1bWLZsGbZt24ahQ4cCAHR0dFCvXj1pI4MTJ05gwoQJ2c7X2toa9erVw9ixY9G1a1fo6OioPObffvsNt27dwo4dO2BhYYFu3brBw8MDO3fuxP379xEWFgZfX1/s378fADB48GAEBQVh/vz5uH37Nv78808cOHDgs98TNHr0aMyaNQuBgYGIjo6Gt7c3wsPDpeeBCpYCUfwQERERFUVmZma4fPkymjRpgpEjR6JatWpwdXVFcHAwVqxYAQCws7PD/PnzMWvWLFSrVg0bN26UbgdQRZ8+fWBpaQl7e3uUKVMGoaGhUCgUOHnyJExMTNC+fXtYW1ujd+/eSEpKytZM0MiRI3Hx4kXUrFkT06ZNw/z58+Hm5ia1r127Fh8+fEDt2rUxbNgwTJs2TaWc05f2/frrryqPF/g4u+bh4YHJkycjLS0Nfn5+8PDwwMiRI2FpaQl3d3dcuHABJiYmAD7eq7Ny5UrMnz8fdnZ2OHjwIIYPH57lrsIAMGTIEIwYMQIjR46Era0tDh48iL1796JKlSo5ypnyVr4veyMiIiLKK9d6XsvvFL7IyMgIS5cuxdKlS7PsM3z4cAwfPlzpXI8ePaR/e3p6wtPTU6nd3d1d6X6bMmXK4PDhwxliGxoaYt26dVle+9MVOJ/69LuAsmJtbY0zZ84onfs0J2dn58/el/To0SPY2trCwcHhi9f67/f1pPt0lkwul8PHxwc+Pj5ZxunTpw/69OmjdJx+HxHw8Xt+Pl1xJJfLMWnSJEyaNCnTeKamphnGaGBgoNKGF5R7WPwQERERUYGSkJCAmJgYLF26VOXZoq81d+5cuLq6QldXFwcOHMC6deuUthSnwo3L3oiIiIioQBk0aBBq164NZ2fnHC95y6mwsDC4urrC1tYWK1euxOLFi+Hl5fVNc6C8w5kfIiIiIipQ/P39s1xul9dyspMeFR6c+SEiIiIioiKBxQ8RERERERUJLH6IiIiIiKhIYPFDRERERERFAosfIiIiIiIqElj8EBERERFRkcDih4iIiIgytXv3bpibm0NNTQ3Dhg3LUQxPT0+4u7vnal6FkUwmw+7du/M7jSKP3/NDRERE36/Jxb/x9V6p1N3T0xPr1q2TjkuWLAkHBwfMnj0b1atXz+3sVPbbb7+hV69eGDJkCPT19TPtY2pqigcPHgAAFAoFLC0tMW7cOHTq1CnP8po8eTJ2796N8PDwr4oTEhKCJk2aSMelS5eGg4MDZs2aBVtb26/MUllcXBxKlCiRqzFJdZz5ISIiIspHLVq0QFxcHOLi4hAcHAx1dXX8+OOP+Z0WEhIS8PTpU7i5uaF8+fJZFj8AMGXKFMTFxeHKlStwcHBAly5dcObMmW+Y7deJjo5GXFwcDh06hOTkZLRu3Rrv37/P1WsYGhpCS0srV2OS6lj8EBEREeUjLS0tGBoawtDQEDVq1IC3tzcePnyIZ8+eSX3Gjh0LCwsLKBQKmJmZ4Y8//kBKSgoAICYmBnK5HBcvXlSKu3DhQlSqVAlpaWmZXvfFixfw8PBAiRIloFAo0LJlS9y+fRvAxxmR9GKnadOmkMlkCAkJyXIM+vr6MDQ0hIWFBZYtWwYdHR389ddfmfZNS0uDr68vKleuDB0dHdjZ2WH79u1Se0hICGQyGYKDg2Fvbw+FQgEnJydER0cDAPz9/eHj44OIiAjIZDLIZDL4+/vj119/zVA0pqSkoGzZslizZk2WuQNA2bJlYWhoiFq1amHYsGF4+PAhoqKipPbTp0+jYcOG0NHRgbGxMYYMGYK3b99K7XFxcWjdujV0dHRQuXJlbNq0Caampli4cKHU57/L3q5du4amTZtCR0cHpUqVQt++fZGQkCC1py8XnDt3LoyMjFCqVCkMHDhQ+r1TzrD4ISIiIiogEhISsGHDBpibm6NUqVLSeX19ffj7++PmzZtYtGgRVq1ahQULFgD4uOzMxcUFfn5+SrH8/Pzg6ekJuTzzj3uenp64ePEi9u7di7Nnz0IIgVatWiElJUWp2NixYwfi4uLg5OSUrTGoq6tDQ0Mjy5kTX19fBAQEYOXKlbhx4waGDx+O7t2748SJE0r9xo8fj3nz5uHixYtQV1fHr7/+CgDo0qULRo4ciapVq0ozZl26dIGXlxcOHjyIuLg4Kca+ffuQmJiILl26ZCv3V69eYcuWLQAATU1NAMDdu3fRokULdOjQAVevXkVgYCBOnz6NQYMGSY/z8PDA48ePERISgh07duB///sfnj59muV13r59Czc3N5QoUQIXLlzAtm3bcPToUaWYAHD8+HHcvXsXx48fx7p16+Dv7w9/f/9sjYUyx3t+iIiIiPLRvn37oKenB+Djh2IjIyPs27dPqWiZMGGC9G9TU1OMGjUKW7ZswZgxYwAAXl5e6NevH+bPnw8tLS1cvnwZ165dw549ezK95u3bt7F3716EhoZKRc3GjRthbGyM3bt3o1OnTihbtiyAj/chGRoaZmss79+/x7x58/Dq1Ss0bdo0Q3tycjJmzJiBo0ePwtHREQBgZmaG06dP488//0Tjxo2lvtOnT5eOvb290bp1ayQlJUFHRwd6enpQV1dXysvJyQmWlpZYv3699Lz4+fmhU6dO0vOblYoVKwKANJvz008/wcrKCsDHYq1bt27Shg9VqlTB4sWL0bhxY6xYsQIxMTE4evQoLly4AHt7ewDA6tWrUaVKlSyvt2nTJiQlJSEgIAC6uroAgKVLl6JNmzaYNWsWypUrBwAoUaIEli5dCjU1NVhZWaF169YIDg5Gnz59PjseyhpnfoiIiIjyUZMmTRAeHo7w8HCEhYXBzc0NLVu2lDYRAIDAwEDUr18fhoaG0NPTw4QJExAbGyu1u7u7Q01NDbt27QLwcWlYkyZNYGpqmuk1IyMjoa6ujrp160rnSpUqBUtLS0RGRqo8hrFjx0JPTw8KhQKzZs3CzJkz0bp16wz97ty5g8TERLi6ukJPT0/6CQgIwN27d5X6frrhg5GREQB8djYF+FgEps+AxcfH48CBA9KM0eecOnUKly5dgr+/PywsLLBy5UqpLSIiAv7+/kr5urm5IS0tDffv30d0dDTU1dVRq1Yt6THm5uaf3dwgMjISdnZ2UuEDAPXr10daWpo04wYAVatWhZqamtLz8KXngD6PMz9ERERE+UhXVxfm5ubS8erVq1G8eHGsWrUK06ZNw9mzZ9GtWzf4+PjAzc0NxYsXx5YtWzBv3jzpMZqamvDw8ICfnx/at2+PTZs2YdGiRd9sDKNHj4anpyf09PRQrlw5yGSyTPul39Oyf/9+VKhQQantv5sBaGhoSP9Oj5fV/UvpPDw84O3tjbNnz+LMmTOoXLkyGjZs+MX8K1euDAMDA1haWuLp06fo0qULTp48KeX822+/YciQIRkeZ2Jiglu3bn0xfk59+hwAH5+HLz0H9HksfoiIiIgKEJlMBrlcjnfv3gEAzpw5g0qVKmH8+PFSn09nhdJ5eXmhWrVqWL58OT58+ID27dtneQ1ra2t8+PAB58+fl5a9/fvvv4iOjoaNjY3KOZcuXVqpgMuKjY0NtLS0EBsbq7TETVWamppITU3NcL5UqVJwd3eHn58fzp49i169eqkce+DAgfD19cWuXbvQrl071KpVCzdv3sxyfJaWlvjw4QOuXLmC2rVrA/g4w/XixYssr2FtbQ1/f3+8fftWmv0JDQ2FXC6HpaWlyjlT9nHZGxEREVE+Sk5OxpMnT/DkyRNERkZi8ODBSEhIQJs2bQB8vMckNjYWW7Zswd27d7F48WJpedunrK2tUa9ePYwdOxZdu3aFjo5OltesUqUK2rZtiz59+uD06dOIiIhA9+7dUaFCBbRt2zbPxqqvr49Ro0Zh+PDhWLduHe7evYvLly9jyZIlSt939CWmpqa4f/8+wsPD8c8//yA5OVlq8/Lywrp16xAZGYmePXuqnKNCoUCfPn0wadIkCCEwduxYnDlzBoMGDUJ4eDhu376NPXv2SJsTWFlZwcXFBX379kVYWBiuXLmCvn37QkdHJ8sZsG7dukFbWxs9e/bE9evXcfz4cQwePBg9evSQ7vehvMHih4iIiCgfHTx4EEZGRjAyMkLdunWl3b+cnZ0BfLz5fvjw4Rg0aBBq1KiBM2fO4I8//sg0Vu/evfH+/fts3efi5+eH2rVr48cff4SjoyOEEAgKCsqw1Cq3TZ06FX/88Qd8fX1hbW2NFi1aYP/+/ahcuXK2Y3To0AEtWrRAkyZNUKZMGWzevFlqc3FxgZGRkfT9RDkxaNAgREZGYtu2bahevTpOnDiBW7duoWHDhqhZsyYmTpyoFDsgIADlypVDo0aN0K5dO/Tp0wf6+vrQ1tbONL5CocChQ4fw/PlzODg4oGPHjmjWrBmWLl2ao3wp+7jsjYiIiL5fk1/ldwafld2ti2fPno3Zs2crnUvffexTjx49gq2tLRwcHL4Ys0SJEggICMiy3cDAAEKIL8aJiYn5bPt/xyeTyTB06FAMHTo00/7Ozs4ZrlujRg2lc1paWkrfDfSpt2/f4sWLF+jdu/cXc8/sWgBgbGys9H06Dg4OOHz4cJZxjIyMEBQUJB3//fffePr0qdJSuf9ex9bWFseOHcsyZmb/XXz6vUGUMyx+iIiIiAq5hIQExMTEYOnSpZg2bVp+p5Mv0tLS8M8//2DevHkwMDDATz/99M2ufezYMSQkJMDW1hZxcXEYM2YMTE1N0ahRo2+WA2UPix8iIiKiQm7QoEHYvHkz3N3ds7Xk7XsUGxuLypUro2LFivD394e6+rf7mJuSkoLff/8d9+7dg76+PpycnLBx48Y8X0JIqmPxQ0RERFTIZXf53PfM1NQ0W8v08oKbmxvc3Nzy5dqkGm54QERERERERQKLHyIiIiIiKhJY/BARERERUZHA4oeIiIiIiIoEFj9ERERERFQksPghIiIiIqIigcUPERER0XfO1NQUCxcuzLLd2dkZw4YNy/M8Jk+ejBo1auT5dbLjS88JfZ/4PT9ERET03TL13v9Nrxczs3WOHnf27Fk0aNAALVq0wP793zbngiQmJgaVK1eWjkuUKAFbW1tMmzYNDRs2zNVrXbhwAbq6urkakwo+zvwQERER5bM1a9Zg8ODBOHnyJB4/fpzf6eS7o0ePIi4uDidPnkT58uXx448/Ij4+PlevUaZMGSgUilyNSQUfix8iIiKifJSQkIDAwED0798frVu3hr+/v1K7v78/DAwMlM7t3r0bMplM6dxff/0FBwcHaGtro3Tp0mjXrl2W11y9ejUMDAwQHBycafv69ethb28PfX19GBoa4pdffsHTp0+l9pCQEMhkMgQHB8Pe3h4KhQJOTk6Ijo5WijNz5kyUK1cO+vr66N27N5KSkrLxjAClSpWCoaEhqlWrht9//x2vX7/G+fPnpfbr16+jZcuW0NPTQ7ly5dCjRw/8888/UvubN2/QrVs36OrqwsjICAsWLMiwtO+/y95iY2PRtm1b6OnpoVixYujcubNSwZW+ZG/9+vUwNTVF8eLF8fPPP+PNmzfZGhMVDCx+iIiIiPLR1q1bYWVlBUtLS3Tv3h1r166FEEKlGPv370e7du3QqlUrXLlyBcHBwahTp06mfWfPng1vb28cPnwYzZo1y7RPSkoKpk6dioiICOzevRsxMTHw9PTM0G/8+PGYN28eLl68CHV1dfz6669K45o8eTJmzJiBixcvwsjICMuXL1dpXO/evUNAQAAAQFNTEwDw8uVLNG3aFDVr1sTFixdx8OBBxMfHo3PnztLjRowYgdDQUOzduxdHjhzBqVOncPny5Syvk5aWhrZt2+L58+c4ceIEjhw5gnv37qFLly5K/e7evYvdu3dj37592LdvH06cOIGZM2eqNCbKX7znh4iIiCgfrVmzBt27dwcAtGjRAq9evcKJEyfg7Oyc7RjTp0/Hzz//DB8fH+mcnZ1dhn5jx47F+vXrceLECVStWjXLeJ8WMWZmZli8eDEcHByQkJAAPT09pes2btwYAODt7Y3WrVsjKSkJ2traWLhwIXr37o3evXsDAKZNm4ajR49ma/bHyckJcrkciYmJEEKgdu3aUqG2dOlS1KxZEzNmzJD6r127FsbGxrh16xaMjIywbt06bNq0SXqMn58fypcvn+X1goODce3aNdy/fx/GxsYAgICAAFStWhUXLlyAg4MDgI9Fkr+/P/T19QEAPXr0QHBwMKZPn/7FMVHBwJkfIiIionwSHR2NsLAwdO3aFQCgrq6OLl26YM2aNSrFCQ8Pz3IWJ928efOwatUqnD59+rOFDwBcunQJbdq0gYmJCfT19aUCJzY2Vqlf9erVpX8bGRkBgLQ8LjIyEnXr1lXq7+jomK3xBAYG4sqVK9ixYwfMzc3h7+8PDQ0NAEBERASOHz8OPT096cfKygrAx5mZe/fuISUlRWnmq3jx4rC0tMzyepGRkTA2NpYKHwCwsbGBgYEBIiMjpXOmpqZS4ZM+5k+XA1LBx5kfIiIionyyZs0afPjwQWlWQggBLS0tLF26FMWLF4dcLs+wDC4lJUXpWEdH54vXatiwIfbv34+tW7fC29s7y35v376Fm5sb3NzcsHHjRpQpUwaxsbFwc3PD+/fvlfqmFyQApHuQ0tLSvpjLlxgbG6NKlSqoUqUKPnz4gHbt2uH69evQ0tJCQkIC2rRpg1mzZmV4nJGREe7cufPV18/Kp+MFPo45N8ZL3w5nfoiIiIjywYcPHxAQEIB58+YhPDxc+omIiED58uWxefNmAB93JXvz5g3evn0rPTY8PFwpVvXq1bPcvCBdnTp1cODAAcyYMQNz587Nsl9UVBT+/fdfzJw5Ew0bNoSVlVWOZjesra2VNikAgHPnzqkcp2PHjlBXV5fuF6pVqxZu3LgBU1NTmJubK/3o6urCzMwMGhoauHDhghTj1atXuHXr1mdzffjwIR4+fCidu3nzJl6+fAkbGxuVc6aCi8UPERERUT7Yt28fXrx4gd69e6NatWpKPx06dJCWvtWtWxcKhQK///477t69i02bNmXYEW7SpEnYvHkzJk2ahMjISFy7di3TmREnJycEBQXBx8cnyy/4NDExgaamJpYsWYJ79+5h7969mDp1qsrjGzp0KNauXQs/Pz/cunULkyZNwo0bN1SOI5PJMGTIEMycOROJiYkYOHAgnj9/jq5du+LChQu4e/cuDh06hF69eiE1NRX6+vro2bMnRo8ejePHj+PGjRvo3bs35HJ5hh3y0rm4uMDW1hbdunXD5cuXERYWBg8PDzRu3Bj29vYq50wFF4sfIiIionywZs0auLi4oHjx4hnaOnTogIsXL+Lq1asoWbIkNmzYgKCgINja2mLz5s2YPHmyUn9nZ2ds27YNe/fuRY0aNdC0aVOEhYVlet0GDRpg//79mDBhApYsWZKhvUyZMvD398e2bdtgY2ODmTNnfnamKCtdunTBH3/8gTFjxqB27dp48OAB+vfvr3IcAOjZsydSUlKwdOlSlC9fHqGhoUhNTUXz5s1ha2uLYcOGwcDAAHL5x4+28+fPh6OjI3788Ue4uLigfv36sLa2hra2dqbxZTIZ9uzZgxIlSqBRo0ZwcXGBmZkZAgMDc5QvFVy854eIiIi+WzEzW+d3Cln666+/smyrU6eO0n0+7u7ucHd3V+rTp08fpeP27dujffv2mcaLiYlROm7UqBESEhKk45CQEKX2rl27SpswpPs0H2dn5wz3IdWoUSPDud9//x2///670rnMZqTSmZqaZrrNt0KhwPPnz6XjKlWqYOfOnVnG0dfXx8aNG6Xjt2/fwsfHB3379pXO/fc5MTExwZ49e7KMOXny5AxF57Bhw5S+O4gKPhY/RERERPRduXLlCqKiolCnTh28evUKU6ZMAQC0bds2nzOj/Mbih4iIiIi+O3PnzkV0dDQ0NTVRu3ZtnDp1CqVLl87vtCifsfghIiIiou9KzZo1cenSpfxOgwogbnhARERERERFAosfIiIiIiIqElj8EBER0XchLS0tv1MgonyQ2Q6BWeE9P0RERFSoaWpqQi6X4/HjxyhTpgw0NTWz/DJLIvq+CCHw7NkzyGQyaGhofLE/ix8iIiIq1ORyOSpXroy4uDg8fvw4v9Mhom9MJpOhYsWKUFNT+2JfFj9ERERU6GlqasLExAQfPnxAampqfqdDRN+QhoZGtgofgMUPERERfSfSl71kZ+kLERVN3PCAiIiIiIiKBBY/RERERERUJLD4ISIiIiKiIoHFDxERERERFQksfoiIiIiIqEhg8UNEREREREUCix8iIiIiIioSWPwQEREREVGRwOKHiIiIiIiKhAJR/CxbtgympqbQ1tZG3bp1ERYW9tn+27Ztg5WVFbS1tWFra4ugoKBvlCkRERERERVW+V78BAYGYsSIEZg0aRIuX74MOzs7uLm54enTp5n2P3PmDLp27YrevXvjypUrcHd3h7u7O65fv/6NMyciIiIiosJEPb8TmD9/Pvr06YNevXoBAFauXIn9+/dj7dq18Pb2ztB/0aJFaNGiBUaPHg0AmDp1Ko4cOYKlS5di5cqVGfonJycjOTlZOn716hUA4PXr10r90pITv3osuR2zKOZYFMecFzELery8iFkUc/xvvLyIWdDi5UXMophjYRxz+rEQ4qviElHRJhP5+H+R9+/fQ6FQYPv27XB3d5fO9+zZEy9fvsSePXsyPMbExAQjRozAsGHDpHOTJk3C7t27ERERkaH/5MmT4ePjkxfpExER0Tf28OFDVKxYMb/TIKJCKl9nfv755x+kpqaiXLlySufLlSuHqKioTB/z5MmTTPs/efIk0/7jxo3DiBEjpOO0tDQ8f/4cpUqVgkwmy3aur1+/hrGxMR4+fIhixYpl+3GFNV5exCyKORbFMedFzIIeLy9iMseCmWNRHHNexMxJPCEE3rx5g/Lly3/19Ymo6Mr3ZW95TUtLC1paWkrnDAwMchyvWLFiufZmUhji5UXMophjURxzXsQs6PHyIiZzLBrx8iLm95hj8eLFc+3aRFQ05euGB6VLl4aamhri4+OVzsfHx8PQ0DDTxxgaGqrUn4iIiIiICMjn4kdTUxO1a9dGcHCwdC4tLQ3BwcFwdHTM9DGOjo5K/QHgyJEjWfYnIiIiIiICCsCytxEjRqBnz56wt7dHnTp1sHDhQrx9+1ba/c3DwwMVKlSAr68vAGDo0KFo3Lgx5s2bh9atW2PLli24ePEi/ve//+VpnlpaWpg0aVKGJXTfa7y8iFkUcyyKY86LmAU9Xl7EZI4FM8eiOOa8iJkXORIRZUe+7vaWbunSpZgzZw6ePHmCGjVqYPHixahbty4AwNnZGaampvD395f6b9u2DRMmTEBMTAyqVKmC2bNno1WrVvmUPRERERERFQYFovghIiIiIiLKa/l6zw8REREREdG3wuKHiIiIiIiKBBY/RERERERUJLD4ISIiIiKiIoHFDxERERERFQksfrIhOTkZycnJ+Z3GdyEkJATv3r3L7zSylJycjLt37xb433d8fDyePHnyVTFSU1MRHx+PZ8+e5VJWwKtXrxAdHY3o6Gi8evUq1+IWFkIIpKam5lo8f3//Av083r59G8HBwbhz505+p6Lkv7+DsLAwnDt37qte17GxsTh//jwuXLiAf//992tTlPD9hYjo22Lxk4UjR46gVatWKFGiBBQKBRQKBUqUKIFWrVrh6NGjuXqtyMhImJmZqfSYiIgITJs2DcuXL8c///yj1Pb69Wv8+uuvKuexevVq9OzZE35+fgCAwMBAWFtbw8zMDJMmTVI5XmaaN2+OmJiYHD326dOnSsfh4eHo2bMn6tevj44dOyIkJESleP7+/jh79iwAICkpCb1794auri4sLCygp6eHfv36qfShxNbWFlOnTsXDhw9VyuNznj9/jo4dO8LExAT9+/dHamoqvLy8YGRkhAoVKsDJyQlxcXEqxdy/fz8aNWoEXV1dlC9fHoaGhjAwMECPHj0QGxubozxXr14NGxsblCxZEjY2Nkr/XrNmTY5iZiUiIgJqamoqPSYoKAheXl4YM2YMoqKilNpevHiBpk2bqhTvw4cPmDBhAho3biy9NubMmQM9PT0oFAr07NkT79+/VylmZvr27YvHjx/n6LFhYWFKRcC+ffvQuHFjVKhQAfb29ggICFApnq+vL4KDgwF8fM5cXFxgaWkJV1dXWFpaomXLlnj58qVKMfX19dG7d2+cOXNGpcdl5cGDB7C3t4eWlhZatmyJ169fw9XVFfXq1YOTkxNsbGxw69YtlWIuX74clSpVQuXKleHk5IR69eqhbNmyaNCgAS5dupSjPAv6+wuQ++8x3+L9hYgoWwRl4O/vL9TV1cXPP/8s/Pz8RFBQkAgKChJ+fn6ia9euQkNDQwQEBOTa9cLDw4VcLs92/0OHDglNTU1RtWpVYWJiIkqVKiWOHTsmtT958kSleEIIsWDBAqGrqyvat28vjIyMxLRp00SpUqXEtGnThI+PjyhWrJj4888/sx2vZs2amf7IZDJhbW0tHatCLpeL+Ph4IYQQoaGhQkNDQzRu3FiMHj1auLq6CnV1dXHixIlsx6tcubI4d+6cEEKIUaNGCVNTU7Fz504RGRkpdu/eLSwsLMTo0aOzHU8mk4lSpUoJNTU14ebmJrZv3y5SUlJUGuN//frrr6JatWpiyZIlonHjxqJt27aievXq4vTp0+LMmTPCwcFBeHh4ZDteQECA0NfXFyNHjhTjx48XhoaGwtvbW6xYsUI0btxYlC5dWty6dUulHGfPni0UCoXw9vYWx48fFzdv3hQ3b94Ux48fF+PGjRO6urpizpw5qg49S+Hh4UImk2W7/8aNG4Wamppo3bq1aNCggdDW1hYbNmyQ2nPyepkwYYIoV66cGDFihLCxsRH9+vUTxsbGYsOGDWLdunWiQoUKYtasWdmOV6JEiUx/ZDKZKF68uHSsik9fL3v37hVyuVx4eHiIZcuWCS8vL6Guri527tyZ7XgVK1YUly9fFkII4eXlJWrWrCkuX74s3r17J8LDw0W9evVE7969VcpRJpOJqlWrCplMJqysrMTcuXPF06dPVYrxqQ4dOojGjRuLv/76S3Tu3FnUr19fODs7i7///ls8fvxYuLm5CXd392zHmzNnjihfvrxYsmSJWLVqlbC2thZTpkwRBw4cED169BAKhUJcuHBBpRwL+vuLELn/HpPb7y9ERF+DxU8mqlSpIpYuXZpl+7Jly4S5uXm24w0fPvyzP927d1fpjcTR0VH8/vvvQggh0tLSxKxZs4Senp44cOCAECJnH+asrKzExo0bhRBCXL58Wairq4vVq1dL7atXrxa1a9fOdjx1dXXRokULMXnyZOln0qRJQi6XiwEDBkjnVCGTyaQPc66uruLXX39Vah86dKho2rRptuNpaWmJBw8eCCGEsLCwkJ6/dCdOnBAmJiYq5ffo0SOxa9cu0aZNG6Guri7KlCkjRo4cKW7evJntOJ8yMjISoaGhQoiPv1eZTCYOHz4stZ8+fVpUqFAh2/GsrKzEli1bpOMLFy6IihUrirS0NCGEEF26dBHt2rVTKUcTExMRGBiYZfuWLVuEsbFxtuO1a9fusz9NmzZV6b/vGjVqiEWLFknHgYGBQldXV/rvOyevFzMzM/HXX38JIYS4ffu2kMvlSs9rYGCgqFatWrbj6enpidatWwt/f3/px8/PT6ipqYnp06dL51Tx6eulQYMGwtvbW6l9+vTpol69etmOp6WlJWJiYoQQQpiammb4Q8PFixeFkZFRjnIMDw8XgwYNEiVLlhSampqiffv2IigoSPrvMrvKlCkjrly5IoQQ4uXLl0Imk4lTp05J7ZcuXRLlypXLdjxTU1MRFBQkHUdHR4tSpUpJf9QYMmSIcHV1VSnHgv7+IkTuv8fk9vsLEdHXYPGTCS0tLREVFZVle1RUlNDW1s52PLlcLmrVqiWcnZ0z/bG3t1fpjaRYsWLizp07Suc2btwodHV1xV9//ZWjD3M6OjpSISDEx+fg+vXr0vHt27eFgYFBtuOdPn1a/PDDD2LixIkiNTVVOq+uri5u3LihUm7pPv0wZ2RkJM6ePavUfv36dVG6dOlsx6tUqZL018wKFSpk+AvuzZs3ha6ubo7yE0KIx48fixkzZogqVaoIuVwuHB0dxZo1a7IdTwghFAqF9IFTCCE0NDTEtWvXpON79+6plKOOjo64f/++0jl1dXXx6NEjIYQQ58+fV+n3LIQQ2trany3ubty4IXR0dLIdT11dXbRs2VJ4enpm+vPTTz+p9N+3rq6uuHfvntK5Y8eOCT09PbFixYocvV60tbVFbGys0nFkZKR0fO/ePaGvr5/teLdv35Zm8d68eSOdz63XS9myZcXFixeV2qOiolT6XVtYWIh9+/YJIT7OmqYX5emuXLkiihUrluMchRAiKSlJbNq0STRr1kzI5XJRsWJF8ccff2Q7nr6+vvS7Tk1NFerq6iI8PFxqv337tkq/F4VCofR6SUtLE+rq6uLx48dCiI+zKnp6etmOJ0TBf38RIvffY3L7/YWI6Guw+MlErVq1PrvcacyYMaJWrVrZjmdhYSHWr1+fZfuVK1dUeiMpU6ZMhg8yQgixefNmoVAoxIoVK1R+sytVqpTSB9iKFSsqfei+ffu2ym/yL1++FD///LOoW7eu9Eb6tR/m7ty5I169eiUqV64sLcFJd+fOHaFQKLId7/fffxeOjo7ixYsXwtvbW7Rp00b64Pn27VvRuXNn0bx582zH+3SZ0X8dP35cdO/eXaVCRQgh7OzspL8SBwUFCX19fTFv3jypfcWKFSrNMFhbW4tt27ZJx5cuXRKampriw4cPQoiPv2dVc2zYsKHw8PDIdInfhw8fhIeHh2jUqFG249na2ir9Vfi/VH29ZFYoCyFESEiI0NPTE+PHj1f59VKuXDlx9epV6djJyUn8/fff0nFkZKTKhUBKSooYM2aM+OGHH8Tp06eFEF//ejl+/LiIiIgQlSpVEmFhYUrtUVFRKr2m58yZI6ytrcXt27fFvHnzhKOjo/S6vnfvnnB2dhYdO3ZUKcfPvWbu378vJkyYoNKsYb169cSECROEEEKsXbtWlCtXTmnGa8qUKSrNMNSoUUP873//k46Dg4OFQqGQZqSioqJUKqaEKPjvL0Lk/ntMXry/EBHlFIufTBw/flzo6uoKW1tbMXz4cDFz5kwxc+ZMMXz4cFG9enWhp6en0r0lv/zyixg2bFiW7arew+Dq6prlPRSbNm0SGhoaKr/Z1a9fX2nZzn/99ddfKn3I/tTatWuFoaGh+PPPP4WGhsZXfZiTy+VCLpcLmUym9KFECCH27Nmj0nKR5ORk8dNPP4kSJUoIV1dXoa2tLRQKhahSpYrQ1dUVJiYmIjo6WqX8svogl+7Vq1fZjieEEBs2bBBqamrC3NxcaGlpiW3btony5cuLzp07i59//lloamp+dgnNfy1dulQUL15cjBkzRkycOFGUL19e6T6NDRs2qHwvVkREhDA0NBSlSpUS7dq1E/369RP9+vUT7dq1E6VKlRJGRkZKs1Vf4unpKQYMGJBl+82bN4WpqWm247Vt21ZMnDgx07b017qqr5cmTZp8dhna1q1bc7yMJzg4WJiYmIhx48blyutFJpMJmUwmFixYoNS+efNmYWNjo1LMwYMHCw0NDWFlZSW0tbWFXC4XmpqaQi6XC3t7exEXF6dyjl96zaiy9O3gwYNCW1tbaGpqCm1tbXHixAlhYWEh6tSpI+rVqyfU1NQ+u0TzvwIDA4WGhobo3Lmz8PDwEHp6ekrF1MqVK4Wjo2O24wlR8N9fhMj995i8fH8hIlKVTAgh8nvThYIoJiYGK1aswLlz56QthQ0NDeHo6Ih+/frB1NQ027GePHmC5ORkVKpUKVdy27VrF06ePIkFCxZk2r5p0yasWrUKx48fz3bM0NBQ6OrqokaNGpm2L1++HGlpaRg0aFBOUsbt27fRrVs3XLx4EdevX4eNjY3KMU6cOKF0bGRkBAsLC+l40aJFeP/+PUaPHq1S3IMHD+Kvv/7CvXv3kJaWBiMjI9SvXx+//PILdHV1sx2nV69eWLx4MfT19VW6/peEhobi3LlzcHR0hJOTE27evImZM2ciMTERbdq0Qc+ePVWKt2LFCmzYsAHJyclwc3PDH3/8AW1tbQAff0+pqamwsrJSKeabN2+wYcOGTF8vv/zyC4oVK5btWMnJyUhNTYVCoVAph6ycOHECZ86cwbhx4zJtP378OAICAqRdqLLj1q1b0NDQQOXKlTNt37RpE9TV1dG5c+cc5fzvv/+iT58+OH78OM6dOwdLS0uVYzx48EDpWE9PD6VKlZKO03d78/DwUCluZGQk9u3bl+H14uLiAplMplIsHx8fjB49Otd+18DH/3dfunQJtWvXhqmpKeLj47Fs2TIkJiaidevWaNKkiUrxDhw4oPR66dOnj9SWvuX1p89rdnMsqO8vQO6/x+T1+wsRkSpY/NA3k5aWhjdv3qBYsWIqf0giIiIiIvpa6vmdQEH24cMH3LhxQ/rLnJGREaytraGhoZEr8QwNDWFjY1Ng4jHHghmvsOSYlZSUFMTFxcHExCRX4n348AGPHz8usPHyImZhyDG3f89AwX8e8+L3QkREeSx/V90VTKmpqWL8+PHCwMBAWi+f/mNgYCAmTJigtINZYY/HHAtmvMKS45fk5HtGCnO8vIjJHL+veMuWLRPNmjUTnTp1EkePHlVqe/bsmahcuXK+xissORIR5QSLn0yMHj1alClTRqxcuVLcv39fJCYmisTERHH//n3x559/irJly4oxY8Z8N/GYY8GMV1hy/JKC8oHzW8XLi5jM8fuJt2jRIqFQKMTAgQNF9+7dhaamppgxY4bUruo20rkdr7DkSESUU7znJxOGhoZYt24d3NzcMm0/dOgQPDw8EB8f/13EY44FM15hybFWrVqfbX/37h1u3bqF1NTU7yIecyw6OebFmKtWrYrx48fjl19+AQCcOXMG7u7u6NevH6ZMmYL4+HiUL18+2zFzO15hyZGIKKd4z08m3rx5g/Lly2fZbmRkhLdv33438ZhjwYxXWHK8efMmfv755yx3PouLi8OtW7e+m3jMsejkmBdjvn//PpycnKRjJycnHDt2DC4uLkhJScGwYcPyNV5hyZGIKMfye+qpIGrVqpVo3ry5ePbsWYa2Z8+eiRYtWojWrVt/N/GYY8GMV1hyrF27tli+fHmW7ap+yWJBj8cci06OeTFmY2NjcfLkyQznb9y4IcqVKyc8PDxUipnb8QpLjkREOcWZn0ysXLkSrVq1gpGREWxtbVGuXDkAQHx8PK5duwYbGxvs27fvu4nHHAtmvMKSY/369REdHZ1lu76+Pho1avTdxGOORSfHvBhzgwYNsHPnTjRs2FDpvI2NDYKDg1X+HqLcjldYciQiyine85OFtLQ0HDp0KNMvoWvevDnkcvl3FY85Fsx4hSVHIsqeq1ev4tKlS+jVq1em7devX8eOHTswadKkfIlXWHIkIsopFj9ERERERFQkcNnbZ4SFheHs2bNKfx13cnKCg4PDdxmPORbMeIU5R0dHR9SpU+e7jMcci06ORXHMhSVHIiKV5e8tRwVTfHy8aNCggZDJZKJSpUqiTp06ok6dOqJSpUpCJpOJBg0aiPj4+O8mHnMsmPGYY8GMxxyLTo55Neb69evnao65Ga+w5EhElFMsfjLRoUMH4ejoKKKiojK0RUVFCScnJ9GxY8fvJh5zLJjxmGPBjMcci06ORXHMhSVHIqKcYvGTCT09PXH58uUs2y9evCj09PS+m3jMsWDGY44FMx5zLDo5FsUxF5YciYhyits6ZUJLSwuvX7/Osv3NmzfQ0tL6buIxx4IZjzkWzHjMsejkWBTHXFhyJCLKsfyuvgqiAQMGiEqVKomdO3eKV69eSedfvXoldu7cKUxNTcWgQYO+m3jMsWDGY44FMx5zLDo5FsUxF5YciYhyisVPJpKSkkS/fv2EpqamkMvlQltbW2hrawu5XC40NTVF//79RVJS0ncTjzkWzHjMsWDGY45FJ8eiOObCkiMRUU7xe34+4/Xr17h06ZLStpy1a9dGsWLFvst4zLFgxmOOBTMecyw6ORbFMReWHImIVMXih4iIiIiIigRueJCFd+/e4fTp07h582aGtqSkJAQEBHxX8ZhjwYzHHAtmPOZYdHIsimMuLDkSEeVI/q66K5iio6OlL1+Ty+WiUaNG4tGjR1L7kydPhFwu/27iMceCGY85Fsx4zLHo5FgUx1xYciQiyinO/GRi7NixqFatGp4+fYro6Gjo6+ujQYMGiI2N/S7jMceCGY85Fsx4zLHo5FgUx1xYciQiyrH8rr4KorJly4qrV69Kx2lpaaJfv37CxMRE3L17V+W/UhX0eMyxYMZjjgUzHnMsOjkWxTEXlhyJiHKKxU8m9PX1xc2bNzOcHzhwoKhYsaI4efKkSv+jLujxmGPBjMccC2Y85lh0ciyKYy4sORIR5RSLn0w4ODiIgICATNsGDhwoDAwMVPofdUGPxxwLZjzmWDDjMceik2NRHHNhyZGIKKdY/GRixowZomXLllm29+/fX8hksu8mHnMsmPGYY8GMxxyLTo5FccyFJUciopzi9/wQEREREVGRwN3eiIiIiIioSGDxQ0RERERERQKLHyIiIiIiKhJY/BARERERUZHA4oeIiIiIiIoEFj9ERERERFQksPghIgKQmpqKtLS0/E6DiIiI8hCLHyIqcAICAlCqVCkkJycrnXd3d0ePHj0AAHv27EGtWrWgra0NMzMz+Pj44MOHD1Lf+fPnw9bWFrq6ujA2NsaAAQOQkJAgtfv7+8PAwAB79+6FjY0NtLS0EBsb+20GSERERPmCxQ8RFTidOnVCamoq9u7dK517+vQp9u/fj19//RWnTp2Ch4cHhg4dips3b+LPP/+Ev78/pk+fLvWXy+VYvHgxbty4gXXr1uHYsWMYM2aM0nUSExMxa9YsrF69Gjdu3EDZsmW/2RiJiIjo25MJIUR+J0FE9F8DBgxATEwMgoKCAHycyVm2bBnu3LkDV1dXNGvWDOPGjZP6b9iwAWPGjMHjx48zjbd9+3b069cP//zzD4CPMz+9evVCeHg47Ozs8n5ARERElO9Y/BBRgXTlyhU4ODjgwYMHqFChAqpXr45OnTrhjz/+QJkyZZCQkAA1NTWpf2pqKpKSkvD27VsoFAocPXoUvr6+iIqKwuvXr/Hhwweldn9/f/z2229ISkqCTCbLx5ESERHRt6Ke3wkQEWWmZs2asLOzQ0BAAJo3b44bN25g//79AICEhAT4+Pigffv2GR6nra2NmJgY/Pjjj+jfvz+mT5+OkiVL4vTp0+jduzfev38PhUIBANDR0WHhQ0REVISw+CGiAsvLywsLFy7Eo0eP4OLiAmNjYwBArVq1EB0dDXNz80wfd+nSJaSlpWHevHmQyz/e2rh169ZvljcREREVTCx+iKjA+uWXXzBq1CisWrUKAQEB0vmJEyfixx9/hImJCTp27Ai5XI6IiAhcv34d06ZNg7m5OVJSUrBkyRK0adMGoaGhWLlyZT6OhIiIiAoC7vZGRAVW8eLF0aFDB+jp6cHd3V067+bmhn379uHw4cNwcHBAvXr1sGDBAlSqVAkAYGdnh/nz52PWrFmoVq0aNm7cCF9f33waBRERERUU3PCAiAq0Zs2aoWrVqli8eHF+p0JERESFHIsfIiqQXrx4gZCQEHTs2BE3b96EpaVlfqdEREREhRzv+SGiAqlmzZp48eIFZs2axcKHiIiIcgVnfoiIiIiIqEjghgdERERERFQksPghIiIiIqIigcUPEREREREVCSx+iIiIiIioSGDxQ0RERERERQKLHyIiIiIiKhJY/BARERERUZHA4oeIiIiIiIqE/wMKwMgPjRaeFQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = pt.plot.bar(stacked=True, width = 0.8, ylim=(0,1), ylabel='share of national crash count', xlabel='year')\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "ax.legend(reversed(handles), reversed(labels),loc='center left', bbox_to_anchor=(1.0, 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38849d59",
   "metadata": {},
   "source": [
    "Let's look at the correlation matrix between the regional annual tallies, but without reading too much into it, because the interpretation is actually not straightforward, especially when looking at correlation between shares. The main reason for attempting this approach is to see if there is negative correlation, which would (possibly) be indicative of some trade-offs between regions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fbffe5fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sn.heatmap(pt.corr(method='pearson'), annot=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5fd4048f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pt2 = pd.pivot_table(cas_df,\n",
    "                     values='fatalCount',\n",
    "                     index='crashYear', \n",
    "                     columns='region', \n",
    "                     aggfunc=np.sum)\n",
    "for column in pt2.columns: \n",
    "    pt2[column] = pt2[column]/annual_counts['fatalCount']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2c96ee3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f83a8b92d10>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = pt2.plot.bar(stacked=True, width = 0.8, ylim=(0,1), ylabel='share of national fatality count', xlabel='year')\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "ax.legend(reversed(handles), reversed(labels),loc='center left', bbox_to_anchor=(1.0, 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01299872",
   "metadata": {},
   "source": [
    "### Choropleth maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8cbf3c13",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "307a1e4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "map_df = gpd.read_file(\"./nz_region.geojson\")\n",
    "map_df.set_index(\"REGC2016_N\", drop=True, inplace=True)\n",
    "map_df.drop([\"REGC2016\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2ab19e5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "harm_df = pd.pivot_table(cas_df, \n",
    "                         values=['crashCount','minorInjuryCount','seriousInjuryCount','fatalCount'], \n",
    "                         index='region',\n",
    "                         aggfunc=np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bbabb85f",
   "metadata": {},
   "outputs": [],
   "source": [
    "harm_df['fatalitiesPer100crashes'] = 100*harm_df['fatalCount'] / harm_df['crashCount']\n",
    "harm_df['injuriesPer100crashes'] = 100*(harm_df['minorInjuryCount']+harm_df['seriousInjuryCount']) / harm_df['crashCount']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e93845c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AREA_SQ_KM</th>\n",
       "      <th>LAND_SQ_KM</th>\n",
       "      <th>rmapshaperid</th>\n",
       "      <th>geometry</th>\n",
       "      <th>crashCount</th>\n",
       "      <th>fatalCount</th>\n",
       "      <th>minorInjuryCount</th>\n",
       "      <th>seriousInjuryCount</th>\n",
       "      <th>fatalitiesPer100crashes</th>\n",
       "      <th>injuriesPer100crashes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Northland Region</th>\n",
       "      <td>12510.3503</td>\n",
       "      <td>12497.9209</td>\n",
       "      <td>0</td>\n",
       "      <td>MULTIPOLYGON (((174.70210 -35.95510, 174.70580...</td>\n",
       "      <td>33299</td>\n",
       "      <td>667.0</td>\n",
       "      <td>11902.0</td>\n",
       "      <td>3192.0</td>\n",
       "      <td>2.003063</td>\n",
       "      <td>45.328689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auckland Region</th>\n",
       "      <td>4940.8756</td>\n",
       "      <td>4939.8049</td>\n",
       "      <td>1</td>\n",
       "      <td>MULTIPOLYGON (((175.16600 -36.90360, 175.16900...</td>\n",
       "      <td>285346</td>\n",
       "      <td>1343.0</td>\n",
       "      <td>77518.0</td>\n",
       "      <td>12372.0</td>\n",
       "      <td>0.470657</td>\n",
       "      <td>31.502106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waikato Region</th>\n",
       "      <td>24578.1774</td>\n",
       "      <td>23899.7930</td>\n",
       "      <td>2</td>\n",
       "      <td>MULTIPOLYGON (((174.86390 -38.10250, 174.86610...</td>\n",
       "      <td>87849</td>\n",
       "      <td>1676.0</td>\n",
       "      <td>31241.0</td>\n",
       "      <td>7561.0</td>\n",
       "      <td>1.907819</td>\n",
       "      <td>44.168972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bay of Plenty Region</th>\n",
       "      <td>12280.4622</td>\n",
       "      <td>12070.5112</td>\n",
       "      <td>3</td>\n",
       "      <td>MULTIPOLYGON (((177.13920 -38.01110, 177.13480...</td>\n",
       "      <td>47177</td>\n",
       "      <td>740.0</td>\n",
       "      <td>14256.0</td>\n",
       "      <td>3636.0</td>\n",
       "      <td>1.568561</td>\n",
       "      <td>37.925260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gisborne Region</th>\n",
       "      <td>8385.8161</td>\n",
       "      <td>8385.8161</td>\n",
       "      <td>4</td>\n",
       "      <td>MULTIPOLYGON (((178.34320 -38.37900, 178.34600...</td>\n",
       "      <td>9784</td>\n",
       "      <td>121.0</td>\n",
       "      <td>3039.0</td>\n",
       "      <td>759.0</td>\n",
       "      <td>1.236713</td>\n",
       "      <td>38.818479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawke's Bay Region</th>\n",
       "      <td>14191.2980</td>\n",
       "      <td>14137.2063</td>\n",
       "      <td>5</td>\n",
       "      <td>MULTIPOLYGON (((177.03000 -39.83170, 177.02850...</td>\n",
       "      <td>32388</td>\n",
       "      <td>421.0</td>\n",
       "      <td>10487.0</td>\n",
       "      <td>2583.0</td>\n",
       "      <td>1.299864</td>\n",
       "      <td>40.354452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taranaki Region</th>\n",
       "      <td>7254.3159</td>\n",
       "      <td>7254.3159</td>\n",
       "      <td>6</td>\n",
       "      <td>POLYGON ((174.61510 -38.70660, 174.61400 -38.7...</td>\n",
       "      <td>18604</td>\n",
       "      <td>271.0</td>\n",
       "      <td>6950.0</td>\n",
       "      <td>1590.0</td>\n",
       "      <td>1.456676</td>\n",
       "      <td>45.904107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manawatū-Whanganui Region</th>\n",
       "      <td>22220.5036</td>\n",
       "      <td>22220.5036</td>\n",
       "      <td>7</td>\n",
       "      <td>POLYGON ((176.08570 -39.12940, 176.08460 -39.1...</td>\n",
       "      <td>46329</td>\n",
       "      <td>764.0</td>\n",
       "      <td>15722.0</td>\n",
       "      <td>4032.0</td>\n",
       "      <td>1.649075</td>\n",
       "      <td>42.638520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wellington Region</th>\n",
       "      <td>8119.5100</td>\n",
       "      <td>8048.6185</td>\n",
       "      <td>8</td>\n",
       "      <td>MULTIPOLYGON (((174.86530 -41.25270, 174.86780...</td>\n",
       "      <td>79725</td>\n",
       "      <td>435.0</td>\n",
       "      <td>21618.0</td>\n",
       "      <td>4329.0</td>\n",
       "      <td>0.545626</td>\n",
       "      <td>32.545626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Coast Region</th>\n",
       "      <td>23319.6480</td>\n",
       "      <td>23243.8118</td>\n",
       "      <td>9</td>\n",
       "      <td>MULTIPOLYGON (((168.88340 -43.85930, 168.88650...</td>\n",
       "      <td>7218</td>\n",
       "      <td>169.0</td>\n",
       "      <td>2741.0</td>\n",
       "      <td>843.0</td>\n",
       "      <td>2.341369</td>\n",
       "      <td>49.653644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canterbury Region</th>\n",
       "      <td>45207.2014</td>\n",
       "      <td>44508.4879</td>\n",
       "      <td>10</td>\n",
       "      <td>MULTIPOLYGON (((172.69180 -43.62300, 172.69260...</td>\n",
       "      <td>82146</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>30353.0</td>\n",
       "      <td>7237.0</td>\n",
       "      <td>1.225866</td>\n",
       "      <td>45.759988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Otago Region</th>\n",
       "      <td>31904.9841</td>\n",
       "      <td>31208.9464</td>\n",
       "      <td>11</td>\n",
       "      <td>MULTIPOLYGON (((170.63190 -45.82600, 170.63500...</td>\n",
       "      <td>44574</td>\n",
       "      <td>394.0</td>\n",
       "      <td>18313.0</td>\n",
       "      <td>4431.0</td>\n",
       "      <td>0.883923</td>\n",
       "      <td>51.025261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southland Region</th>\n",
       "      <td>31841.2008</td>\n",
       "      <td>31195.1303</td>\n",
       "      <td>12</td>\n",
       "      <td>MULTIPOLYGON (((167.39580 -47.26400, 167.39830...</td>\n",
       "      <td>20234</td>\n",
       "      <td>261.0</td>\n",
       "      <td>8708.0</td>\n",
       "      <td>2191.0</td>\n",
       "      <td>1.289908</td>\n",
       "      <td>53.864782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tasman Region</th>\n",
       "      <td>9649.7336</td>\n",
       "      <td>9616.2281</td>\n",
       "      <td>13</td>\n",
       "      <td>MULTIPOLYGON (((173.14470 -41.28670, 173.15470...</td>\n",
       "      <td>7541</td>\n",
       "      <td>118.0</td>\n",
       "      <td>2866.0</td>\n",
       "      <td>819.0</td>\n",
       "      <td>1.564779</td>\n",
       "      <td>48.866198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nelson Region</th>\n",
       "      <td>424.4161</td>\n",
       "      <td>424.4161</td>\n",
       "      <td>14</td>\n",
       "      <td>POLYGON ((173.29740 -41.39310, 173.27220 -41.3...</td>\n",
       "      <td>8076</td>\n",
       "      <td>43.0</td>\n",
       "      <td>2364.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>0.532442</td>\n",
       "      <td>35.450718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marlborough Region</th>\n",
       "      <td>10470.4614</td>\n",
       "      <td>10457.6710</td>\n",
       "      <td>15</td>\n",
       "      <td>MULTIPOLYGON (((174.10160 -41.53220, 174.10220...</td>\n",
       "      <td>8266</td>\n",
       "      <td>124.0</td>\n",
       "      <td>2688.0</td>\n",
       "      <td>622.0</td>\n",
       "      <td>1.500121</td>\n",
       "      <td>40.043552</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           AREA_SQ_KM  LAND_SQ_KM  rmapshaperid  \\\n",
       "Northland Region           12510.3503  12497.9209             0   \n",
       "Auckland Region             4940.8756   4939.8049             1   \n",
       "Waikato Region             24578.1774  23899.7930             2   \n",
       "Bay of Plenty Region       12280.4622  12070.5112             3   \n",
       "Gisborne Region             8385.8161   8385.8161             4   \n",
       "Hawke's Bay Region         14191.2980  14137.2063             5   \n",
       "Taranaki Region             7254.3159   7254.3159             6   \n",
       "Manawatū-Whanganui Region  22220.5036  22220.5036             7   \n",
       "Wellington Region           8119.5100   8048.6185             8   \n",
       "West Coast Region          23319.6480  23243.8118             9   \n",
       "Canterbury Region          45207.2014  44508.4879            10   \n",
       "Otago Region               31904.9841  31208.9464            11   \n",
       "Southland Region           31841.2008  31195.1303            12   \n",
       "Tasman Region               9649.7336   9616.2281            13   \n",
       "Nelson Region                424.4161    424.4161            14   \n",
       "Marlborough Region         10470.4614  10457.6710            15   \n",
       "\n",
       "                                                                    geometry  \\\n",
       "Northland Region           MULTIPOLYGON (((174.70210 -35.95510, 174.70580...   \n",
       "Auckland Region            MULTIPOLYGON (((175.16600 -36.90360, 175.16900...   \n",
       "Waikato Region             MULTIPOLYGON (((174.86390 -38.10250, 174.86610...   \n",
       "Bay of Plenty Region       MULTIPOLYGON (((177.13920 -38.01110, 177.13480...   \n",
       "Gisborne Region            MULTIPOLYGON (((178.34320 -38.37900, 178.34600...   \n",
       "Hawke's Bay Region         MULTIPOLYGON (((177.03000 -39.83170, 177.02850...   \n",
       "Taranaki Region            POLYGON ((174.61510 -38.70660, 174.61400 -38.7...   \n",
       "Manawatū-Whanganui Region  POLYGON ((176.08570 -39.12940, 176.08460 -39.1...   \n",
       "Wellington Region          MULTIPOLYGON (((174.86530 -41.25270, 174.86780...   \n",
       "West Coast Region          MULTIPOLYGON (((168.88340 -43.85930, 168.88650...   \n",
       "Canterbury Region          MULTIPOLYGON (((172.69180 -43.62300, 172.69260...   \n",
       "Otago Region               MULTIPOLYGON (((170.63190 -45.82600, 170.63500...   \n",
       "Southland Region           MULTIPOLYGON (((167.39580 -47.26400, 167.39830...   \n",
       "Tasman Region              MULTIPOLYGON (((173.14470 -41.28670, 173.15470...   \n",
       "Nelson Region              POLYGON ((173.29740 -41.39310, 173.27220 -41.3...   \n",
       "Marlborough Region         MULTIPOLYGON (((174.10160 -41.53220, 174.10220...   \n",
       "\n",
       "                           crashCount  fatalCount  minorInjuryCount  \\\n",
       "Northland Region                33299       667.0           11902.0   \n",
       "Auckland Region                285346      1343.0           77518.0   \n",
       "Waikato Region                  87849      1676.0           31241.0   \n",
       "Bay of Plenty Region            47177       740.0           14256.0   \n",
       "Gisborne Region                  9784       121.0            3039.0   \n",
       "Hawke's Bay Region              32388       421.0           10487.0   \n",
       "Taranaki Region                 18604       271.0            6950.0   \n",
       "Manawatū-Whanganui Region       46329       764.0           15722.0   \n",
       "Wellington Region               79725       435.0           21618.0   \n",
       "West Coast Region                7218       169.0            2741.0   \n",
       "Canterbury Region               82146      1007.0           30353.0   \n",
       "Otago Region                    44574       394.0           18313.0   \n",
       "Southland Region                20234       261.0            8708.0   \n",
       "Tasman Region                    7541       118.0            2866.0   \n",
       "Nelson Region                    8076        43.0            2364.0   \n",
       "Marlborough Region               8266       124.0            2688.0   \n",
       "\n",
       "                           seriousInjuryCount  fatalitiesPer100crashes  \\\n",
       "Northland Region                       3192.0                 2.003063   \n",
       "Auckland Region                       12372.0                 0.470657   \n",
       "Waikato Region                         7561.0                 1.907819   \n",
       "Bay of Plenty Region                   3636.0                 1.568561   \n",
       "Gisborne Region                         759.0                 1.236713   \n",
       "Hawke's Bay Region                     2583.0                 1.299864   \n",
       "Taranaki Region                        1590.0                 1.456676   \n",
       "Manawatū-Whanganui Region              4032.0                 1.649075   \n",
       "Wellington Region                      4329.0                 0.545626   \n",
       "West Coast Region                       843.0                 2.341369   \n",
       "Canterbury Region                      7237.0                 1.225866   \n",
       "Otago Region                           4431.0                 0.883923   \n",
       "Southland Region                       2191.0                 1.289908   \n",
       "Tasman Region                           819.0                 1.564779   \n",
       "Nelson Region                           499.0                 0.532442   \n",
       "Marlborough Region                      622.0                 1.500121   \n",
       "\n",
       "                           injuriesPer100crashes  \n",
       "Northland Region                       45.328689  \n",
       "Auckland Region                        31.502106  \n",
       "Waikato Region                         44.168972  \n",
       "Bay of Plenty Region                   37.925260  \n",
       "Gisborne Region                        38.818479  \n",
       "Hawke's Bay Region                     40.354452  \n",
       "Taranaki Region                        45.904107  \n",
       "Manawatū-Whanganui Region              42.638520  \n",
       "Wellington Region                      32.545626  \n",
       "West Coast Region                      49.653644  \n",
       "Canterbury Region                      45.759988  \n",
       "Otago Region                           51.025261  \n",
       "Southland Region                       53.864782  \n",
       "Tasman Region                          48.866198  \n",
       "Nelson Region                          35.450718  \n",
       "Marlborough Region                     40.043552  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapharm_df = pd.concat([map_df,harm_df], axis=1)\n",
    "mapharm_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1b99e3f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot: title={'center': 'injuriesPer100crashes'}>,\n",
       "       <AxesSubplot: title={'center': 'fatalitiesPer100crashes'}>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JkTNnzqTrvj1q1CgpV66cODo6irW1tfj7+8vo0aMlOTnZsExm2zxt+7xo5syZEhgYKNbW1mJnZyfFixeXr776Sm7cuCEiIkeOHJGWLVtKvnz5RK/Xi5ubm3z88cdy6NChDLcX0btAJ/Ia1ySJ6I1ERESgZs2a2Llzp9HcKURElB7bjBBpIK1HR65cuRSvCRHRu49XRohMKDExEQsXLsTkyZMRHx+Pq1evvtb8K0RE7zOeJYlM6Pbt2+jZsyesra3x+++/MxEhInoNvDJCRERESvFnGxERESn1nxhnJDU1FTdu3ICdnV2WjPhIREREb09E8ODBA+TOnfult63/E8nIjRs30s13QURERP8N0dHRRhNuvug/kYzY2dkBeFaZ5+emICIiondXfHw8vLy8DN/jmflPJCNpt2bs7e2ZjBAREf3HvKqJBRuwEhERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESn1n+hNQ0RE7wfvr9e91fuvfFfPRGtCWYlXRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESjEZISIiIqXeOhkZNmwYdDqd0cPf39/w+uPHj9G9e3e4uLjA1tYWTZs2RWxs7NuGJSIiomzCJIOeFS1aFJs3b/6/D83xfx/bt29frFu3DsuWLYODgwN69OiBJk2aYPfu3aYITUREJsaBxyirmSQZyZEjBzw8PNKVx8XFYfbs2Vi0aBGqV68OAJgzZw6KFCmCffv2oUKFCqYIT0RERP9hJmkzcv78eeTOnRu+vr5o1aoVoqKiAACHDx/GkydPULNmTcOy/v7+yJcvH/bu3Zvp5yUlJSE+Pt7oQURERNnTWycj5cuXR3h4ODZs2IBp06bh8uXLqFy5Mh48eICYmBhYWlrC0dHR6D3u7u6IiYnJ9DPDwsLg4OBgeHh5eb3tahIREdE76q1v09StW9fw/xIlSqB8+fLInz8/li5dCmtr63/1mYMGDUJoaKjheXx8PBMSIspybDtBlDVM3rXX0dERhQoVwoULF+Dh4YHk5GTcv3/faJnY2NgM25ik0ev1sLe3N3oQERFR9mSSBqzPS0hIwMWLF9G6dWsEBgbCwsICERERaNq0KQDg7NmziIqKQlBQkKlDExER/Wu8EqbOWycj/fv3R/369ZE/f37cuHEDQ4cOhbm5OVq2bAkHBwd07NgRoaGhcHZ2hr29PXr27ImgoCD2pCEiIiIAJkhGrl27hpYtW+Lu3btwdXVFpUqVsG/fPri6ugIAJk6cCDMzMzRt2hRJSUkICQnBzz///NYrTkRERNnDWycjixcvfunrVlZWmDp1KqZOnfq2oYiIiCgb4tw0REREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREqZfNAzItIGB2QiouyKyQgR0TuIySe9T7JFMsI/WiIiov8uthkhIiIipZiMEBERkVLZ4jbN+4q3p4iIKDvglREiIiJSiskIERERKcVkhIiIiJRiMkJERERKsQErEb0SG0sTkZZ4ZYSIiIiUYjJCRERESjEZISIiIqVMmox899130Ol06NOnj6Hs8ePH6N69O1xcXGBra4umTZsiNjbWlGGJiIjoP8xkycjBgwcxY8YMlChRwqi8b9++WLt2LZYtW4bt27fjxo0baNKkianCEhER0X+cSZKRhIQEtGrVCr/88gucnJwM5XFxcZg9ezYmTJiA6tWrIzAwEHPmzMGePXuwb98+U4QmIiKi/ziTdO3t3r076tWrh5o1a2LUqFGG8sOHD+PJkyeoWbOmoczf3x/58uXD3r17UaFChQw/LykpCUlJSYbn8fHxplhNorfGLq5ElN28C+e1t05GFi9ejCNHjuDgwYPpXouJiYGlpSUcHR2Nyt3d3RETE5PpZ4aFhWH48OFvu2pERET0H/BWt2mio6PRu3dvLFy4EFZWVqZaJwwaNAhxcXGGR3R0tMk+m4iIiN4tb5WMHD58GLdu3UKZMmWQI0cO5MiRA9u3b8ePP/6IHDlywN3dHcnJybh//77R+2JjY+Hh4ZHp5+r1etjb2xs9iIiIKHt6q9s0NWrUwIkTJ4zK2rdvD39/fwwcOBBeXl6wsLBAREQEmjZtCgA4e/YsoqKiEBQU9Dah6T32LtzfJCIi03mrZMTOzg7FihUzKrOxsYGLi4uhvGPHjggNDYWzszPs7e3Rs2dPBAUFZdp4lYiIiN4vmk+UN3HiRJiZmaFp06ZISkpCSEgIfv75Z63DEhER0X+EyZORbdu2GT23srLC1KlTMXXqVFOHIoV4q4SIiEyFc9MQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJTSfJwRIiIiern3fbgEXhkhIiIipZiMEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESnHQMyJ6p73vg0ERvQ94ZYSIiIiUYjJCRERESvE2zVviJWQiIqK389ZXRqZNm4YSJUrA3t4e9vb2CAoKwvr16w2vP378GN27d4eLiwtsbW3RtGlTxMbGvm1YIiIiyibeOhnJmzcvvvvuOxw+fBiHDh1C9erV0bBhQ5w6dQoA0LdvX6xduxbLli3D9u3bcePGDTRp0uStV5yIiIiyh7e+TVO/fn2j56NHj8a0adOwb98+5M2bF7Nnz8aiRYtQvXp1AMCcOXNQpEgR7Nu3DxUqVMjwM5OSkpCUlGR4Hh8f/7arSURERO8okzZgTUlJweLFi5GYmIigoCAcPnwYT548Qc2aNQ3L+Pv7I1++fNi7d2+mnxMWFgYHBwfDw8vLy5SrSURERO8QkyQjJ06cgK2tLfR6Pbp27YqVK1ciICAAMTExsLS0hKOjo9Hy7u7uiImJyfTzBg0ahLi4OMMjOjraFKtJRERE7yCT9KYpXLgwIiMjERcXh+XLl6Nt27bYvn37v/48vV4PvV5vilUjIiKid5xJkhFLS0sUKFAAABAYGIiDBw9i8uTJ+PTTT5GcnIz79+8bXR2JjY2Fh4eHKUITERHRf5wmg56lpqYiKSkJgYGBsLCwQEREhOG1s2fPIioqCkFBQVqEJiIiov+Yt74yMmjQINStWxf58uXDgwcPsGjRImzbtg0bN26Eg4MDOnbsiNDQUDg7O8Pe3h49e/ZEUFBQpj1piIiI6P3y1snIrVu30KZNG9y8eRMODg4oUaIENm7ciFq1agEAJk6cCDMzMzRt2hRJSUkICQnBzz///NYrTkRERNnDWycjs2fPfunrVlZWmDp1KqZOnfq2oYiIiCgb4kR5REREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUuqtk5GwsDB88MEHsLOzg5ubGxo1aoSzZ88aLfP48WN0794dLi4usLW1RdOmTREbG/u2oYmIiCgbeOtkZPv27ejevTv27duHTZs24cmTJ6hduzYSExMNy/Tt2xdr167FsmXLsH37dty4cQNNmjR529BERESUDeR42w/YsGGD0fPw8HC4ubnh8OHDqFKlCuLi4jB79mwsWrQI1atXBwDMmTMHRYoUwb59+1ChQoW3XQUiIiL6DzN5m5G4uDgAgLOzMwDg8OHDePLkCWrWrGlYxt/fH/ny5cPevXsz/IykpCTEx8cbPYiIiCh7Mmkykpqaij59+qBixYooVqwYACAmJgaWlpZwdHQ0Wtbd3R0xMTEZfk5YWBgcHBwMDy8vL1OuJhEREb1DTJqMdO/eHSdPnsTixYvf6nMGDRqEuLg4wyM6OtpEa0hERETvmrduM5KmR48e+OOPP7Bjxw7kzZvXUO7h4YHk5GTcv3/f6OpIbGwsPDw8MvwsvV4PvV5vqlUjIiKid9hbXxkREfTo0QMrV67Eli1b4OPjY/R6YGAgLCwsEBERYSg7e/YsoqKiEBQU9LbhiYiI6D/ura+MdO/eHYsWLcLq1athZ2dnaAfi4OAAa2trODg4oGPHjggNDYWzszPs7e3Rs2dPBAUFsScNERERvX0yMm3aNABA1apVjcrnzJmDdu3aAQAmTpwIMzMzNG3aFElJSQgJCcHPP//8tqGJiIgoG3jrZEREXrmMlZUVpk6diqlTp75tOCIiIspmODcNERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESjEZISIiIqWYjBAREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREq9dTKyY8cO1K9fH7lz54ZOp8OqVauMXhcRDBkyBJ6enrC2tkbNmjVx/vz5tw1LRERE2cRbJyOJiYkoWbIkpk6dmuHr33//PX788UdMnz4d+/fvh42NDUJCQvD48eO3DU1ERETZQI63/YC6deuibt26Gb4mIpg0aRIGDx6Mhg0bAgDmzZsHd3d3rFq1Ci1atHjb8ERERPQfp2mbkcuXLyMmJgY1a9Y0lDk4OKB8+fLYu3dvpu9LSkpCfHy80YOIiIiyJ02TkZiYGACAu7u7Ubm7u7vhtYyEhYXBwcHB8PDy8tJyNYmIiEihd7I3zaBBgxAXF2d4REdHq14lIiIi0oimyYiHhwcAIDY21qg8NjbW8FpG9Ho97O3tjR5ERESUPWmajPj4+MDDwwMRERGGsvj4eOzfvx9BQUFahiYiIqL/iLfuTZOQkIALFy4Ynl++fBmRkZFwdnZGvnz50KdPH4waNQoFCxaEj48Pvv32W+TOnRuNGjV629BERESUDbx1MnLo0CFUq1bN8Dw0NBQA0LZtW4SHh+Orr75CYmIiunTpgvv376NSpUrYsGEDrKys3jY0ERERZQNvnYxUrVoVIpLp6zqdDiNGjMCIESPeNhQRERFlQ+9kbxoiIiJ6fzAZISIiIqWYjBAREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJZloxMnToV3t7esLKyQvny5XHgwIGsCk1ERETvsCxJRpYsWYLQ0FAMHToUR44cQcmSJRESEoJbt25lRXgiIiJ6h+XIiiATJkxA586d0b59ewDA9OnTsW7dOvz666/4+uuv0y2flJSEpKQkw/O4uDgAQHx8fIafn5r08K3WL7PPfR2MzdiMzdiMzdiM/fLXROTlHyIaS0pKEnNzc1m5cqVReZs2baRBgwYZvmfo0KECgA8++OCDDz74yAaP6Ojol+YKml8ZuXPnDlJSUuDu7m5U7u7ujjNnzmT4nkGDBiE0NNTwPDU1Fffu3YOLiwt0Ot0bxY+Pj4eXlxeio6Nhb2//5hV4C4zN2IzN2IzN2O9zbBHBgwcPkDt37pculyW3ad6UXq+HXq83KnN0dHyrz7S3t8/yncjYjM3YjM3YjP2+x3ZwcHjlMpo3YM2VKxfMzc0RGxtrVB4bGwsPDw+twxMREdE7TvNkxNLSEoGBgYiIiDCUpaamIiIiAkFBQVqHJyIiondcltymCQ0NRdu2bVG2bFmUK1cOkyZNQmJioqF3jZb0ej2GDh2a7rZPVmBsxmZsxmZsxmbsV9OJvKq/jWlMmTIFP/zwA2JiYlCqVCn8+OOPKF++fFaEJiIiondYliUjRERERBnh3DRERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESjEZIfr/Dh48iA8//BA2NjbQ6XSIjIzMsthVq1ZF1apVDc+vXLkCnU6H8PDw13q/TqfDsGHDNFk3ynrh4eHQ6XQ4dOiQ6lUhyhJMRogAPHnyBM2aNcO9e/cwceJEzJ8/H/nz53+t9+7ZswfDhg3D/fv3NV3HP//8U0nCkfbFmPawsrJCoUKF0KNHj3TTPLytAwcOoFu3bggMDISFhcUrJ8acPXs2ihQpAisrKxQsWBA//fRThstdv34dzZs3h6OjI+zt7dGwYUNcunTJpOtORP/eOzlRHlFWu3jxIq5evYpffvkFnTp1eqP37tmzB8OHD0e7du3eekLHNPnz58ejR49gYWFhKPvzzz8xderUDBOSR48eIUcObf+cR4wYAR8fHzx+/Bi7du3CtGnT8Oeff+LkyZPImTOnSWL8+eefmDVrFkqUKAFfX1+cO3cu02VnzJiBrl27omnTpggNDcXOnTvRq1cvPHz4EAMHDjQsl5CQgGrVqiEuLg7/+9//YGFhgYkTJyI4OBiRkZFwcXExyboT0b/HZIQIwK1btwC8/ezQppJ2BeJ1vcmy/1bdunVRtmxZAECnTp3g4uKCCRMmYPXq1WjZsuVbffbDhw+RM2dOfPnllxg4cCCsra3Ro0ePTJORR48e4ZtvvkG9evWwfPlyAEDnzp2RmpqKkSNHokuXLnBycgIA/Pzzzzh//jwOHDiADz74wFCXYsWKYfz48RgzZsxbrfvTp0+RmpoKS0vLt/ocovcZb9PQe69du3YIDg4GADRr1gw6nQ5Vq1bF8ePH0a5dO/j6+sLKygoeHh7o0KED7t69a3jvsGHDMGDAAACAj4+P4VbGlStXAABz5sxB9erV4ebmBr1ej4CAAEybNu2V6/Rim5F27dph6tSpAGB0yyRNRm1Grl+/jg4dOsDd3R16vR5FixbFr7/+mi7WTz/9hKJFiyJnzpxwcnJC2bJlsWjRoleuY/Xq1QEAly9fNpQtWLAAgYGBsLa2hrOzM1q0aIHo6Gij91WtWhXFihXD4cOHUaVKFeTMmRP/+9//AADu7u6wtrZ+ZeytW7fi7t276Natm1F59+7dkZiYiHXr1hnKli9fjg8++MCQiACAv78/atSogaVLlxq9//Hjxxg2bBgKFSoEKysreHp6okmTJrh48SKA/9sv48aNw6RJk+Dn5we9Xo+///4bycnJGDJkCAIDA+Hg4AAbGxtUrlwZW7duTbf+ixcvRmBgIOzs7GBvb4/ixYtj8uTJ6ZZLSkpCaGgoXF1dYWNjg8aNG+P27dvpllu/fj0qV64MGxsb2NnZoV69ejh16pTRMjExMWjfvj3y5s0LvV4PT09PNGzY0HCsEqnEKyP03vviiy+QJ08ejBkzBr169cIHH3wAd3d3bNq0CZcuXUL79u3h4eGBU6dOYebMmTh16hT27dsHnU6HJk2a4Ny5c/jtt98wceJE5MqVCwDg6uoKAJg2bRqKFi2KBg0aIEeOHFi7di26deuG1NRUdO/e/Y3W8caNG9i0aRPmz5//yuVjY2NRoUIF6HQ69OjRA66urli/fj06duyI+Ph49OnTBwDwyy+/oFevXvjkk0/Qu3dvPH78GMePH8f+/fvx2WefvTRG2hd02m2O0aNH49tvv0Xz5s3RqVMn3L59Gz/99BOqVKmCo0ePGl11unv3LurWrYsWLVrg888/h7u7+2tvCwA4evQoABiu1KQJDAyEmZkZjh49is8//xypqak4fvw4OnTokO4zypUrh7/++gsPHjyAnZ0dUlJS8PHHHyMiIgItWrRA79698eDBA2zatAknT56En5+f4b1z5szB48eP0aVLF+j1ejg7OyM+Ph6zZs1Cy5Yt0blzZzx48ACzZ89GSEgIDhw4gFKlSgEANm3ahJYtW6JGjRoYO3YsAOD06dPYvXs3evfubbSOPXv2hJOTE4YOHYorV65g0qRJ6NGjB5YsWWJYZv78+Wjbti1CQkIwduxYPHz4ENOmTUOlSpVw9OhReHt7AwCaNm2KU6dOoWfPnvD29satW7ewadMmREVFGZYhUkaISLZu3SoAZNmyZYayhw8fplvut99+EwCyY8cOQ9kPP/wgAOTy5cvpls/oM0JCQsTX19eoLDg4WIKDgw3PL1++LABkzpw5hrLu3btLZn+yAGTo0KGG5x07dhRPT0+5c+eO0XItWrQQBwcHw3o1bNhQihYtmuFnppkzZ44AkM2bN8vt27clOjpaFi9eLC4uLmJtbS3Xrl2TK1euiLm5uYwePdrovSdOnJAcOXIYlQcHBwsAmT59+kvjvqy+3bt3F3Nz8wxfc3V1lRYtWoiIyO3btwWAjBgxIt1yU6dOFQBy5swZERH59ddfBYBMmDAh3bKpqaki8n/7xd7eXm7dumW0zNOnTyUpKcmo7J9//hF3d3fp0KGDoax3795ib28vT58+zazqhm1es2ZNQ2wRkb59+4q5ubncv39fREQePHggjo6O0rlzZ6P3x8TEiIODg6H8n3/+EQDyww8/ZBqTSCXepiHKxPO3Cx4/fow7d+6gQoUKAIAjR4688WfExcXhzp07CA4OxqVLlxAXF2faFf7/RAS///476tevDxHBnTt3DI+QkBDExcUZ1t/R0RHXrl3DwYMHX/m5NWvWhKurK7y8vNCiRQvY2tpi5cqVyJMnD1asWIHU1FQ0b97cKJ6HhwcKFiyY7laFXq9H+/bt/3UdHz16lGkbDSsrKzx69MiwXFq8jJZ7fpnff/8duXLlQs+ePdMt+2KvnqZNmxqufqUxNzc3rFNqairu3buHp0+fomzZskbHi6OjIxITE7Fp06ZX1rNLly5GsStXroyUlBRcvXoVwLOrLPfv30fLli2Ntru5uTnKly9v2O7W1tawtLTEtm3b8M8//7wyLlFW420aokzcu3cPw4cPx+LFiw0NXNO8biKxe/duDB06FHv37sXDhw/TfYaDg4PJ1jfN7du3cf/+fcycORMzZ87McJm0+gwcOBCbN29GuXLlUKBAAdSuXRufffYZKlasmO49U6dORaFChZAjRw64u7ujcOHCMDN79nvm/PnzEBEULFgww3jP9woCgDx58rxVg09ra2skJydn+Nrjx48NSWDav0lJSRku9/wyFy9eROHChV+rV5KPj0+G5XPnzsX48eNx5swZPHnyJMPlu3XrhqVLl6Ju3brIkycPateujebNm6NOnTrpPi9fvnxGz9Ma5aYlFOfPnwfwf+13XmRvbw/gWTI2duxY9OvXD+7u7qhQoQI+/vhjtGnTBh4eHq+sL5HWmIwQZaJ58+bYs2cPBgwYgFKlSsHW1hapqamoU6cOUlNTX/n+ixcvokaNGvD398eECRPg5eUFS0tL/Pnnn5g4ceJrfca/kfa5n3/+Odq2bZvhMiVKlAAAFClSBGfPnsUff/yBDRs24Pfff8fPP/+MIUOGYPjw4UbvKVeuXLo2Gs/H1Ol0WL9+PczNzdO9bmtra/T8dRqpvoynpydSUlJw69YtuLm5GcqTk5Nx9+5d5M6dGwDg7OwMvV6PmzdvpvuMtLK0Zd9ERuu/YMECtGvXDo0aNcKAAQPg5uYGc3NzhIWFGdrXAICbmxsiIyOxceNGrF+/HuvXr8ecOXPQpk0bzJ071+gzM9qWwLOrX8D/7ev58+dnmFQ8n1j16dMH9evXx6pVq7Bx40Z8++23CAsLw5YtW1C6dOk33gZEpsRkhCgD//zzDyIiIjB8+HAMGTLEUJ72S/R5mQ3MtXbtWiQlJWHNmjVGv3Az6l3xOl41AFgaV1dXQ4PMmjVrvnJ5GxsbfPrpp/j000+RnJyMJk2aYPTo0Rg0aNBrdxn28/ODiMDHxweFChV6rfe8jbTGoIcOHcJHH31kKD906BBSU1MNr5uZmaF48eIZjmS6f/9++Pr6ws7OzlCH/fv348mTJ+mu5LyO5cuXw9fXFytWrDDaV0OHDk23rKWlJerXr4/69esjNTUV3bp1w4wZM/Dtt9+iQIECrx0zrVGtm5vba+1rPz8/9OvXD/369cP58+dRqlQpjB8/HgsWLHjtmERaYJsRogyk/SJN+wWaZtKkSemWtbGxAYB0I7Bm9BlxcXGYM2fOv1qnzOK8yNzcHE2bNsXvv/+OkydPpnv9+a6hz3dTBp59SQYEBEBEjG4zvEqTJk1gbm6O4cOHp9tmIpIuztuqXr06nJ2d03WTnjZtGnLmzIl69eoZyj755BMcPHjQKCE5e/YstmzZgmbNmhnKmjZtijt37mDKlCnp4r1Yp4xktL/379+PvXv3Gi334rYwMzMzXKnK6HbSy4SEhMDe3h5jxozJcH+l7euHDx8abkul8fPzg52d3RvHJNICr4wQZcDe3h5VqlTB999/jydPniBPnjz466+/jMbUSBMYGAgA+Oabb9CiRQtYWFigfv36qF27tuEX8BdffIGEhAT88ssvcHNzy/C2waukxenVqxdCQkJgbm6OFi1aZLjsd999h61bt6J8+fLo3LkzAgICcO/ePRw5cgSbN2/GvXv3AAC1a9eGh4cHKlasCHd3d5w+fRpTpkxBvXr1DFcMXoefnx9GjRqFQYMG4cqVK2jUqBHs7Oxw+fJlrFy5El26dEH//v1f+TlXr141dF1OSx5GjRoF4NmotK1btwbw7DbJyJEj0b17dzRr1gwhISHYuXMnFixYgNGjR8PZ2dnwmd26dcMvv/yCevXqoX///rCwsMCECRPg7u6Ofv36GZZr06YN5s2bh9DQUBw4cACVK1dGYmIiNm/ejG7duqFhw4YvXfePP/4YK1asQOPGjVGvXj1cvnwZ06dPR0BAABISEgzLderUCffu3UP16tWRN29eXL16FT/99BNKlSqFIkWKvOYWf8be3h7Tpk1D69atUaZMGbRo0QKurq6IiorCunXrULFiRUyZMgXnzp1DjRo10Lx5cwQEBCBHjhxYuXIlYmNjMz2GiLKUmk48RO+WjLr2Xrt2TRo3biyOjo7i4OAgzZo1kxs3bqTrRisiMnLkSMmTJ4+YmZkZdfNds2aNlChRQqysrMTb21vGjh1r6EL6fFfg1+na+/TpU+nZs6e4urqKTqcz6vaa0TrFxsZK9+7dxcvLSywsLMTDw0Nq1KghM2fONCwzY8YMqVKliri4uIherxc/Pz8ZMGCAxMXFGZZJ62Z68ODBV27H33//XSpVqiQ2NjZiY2Mj/v7+0r17dzl79qxRXTPrTpy2HzJ6PL990sycOVMKFy4slpaW4ufnJxMnTjTqCpsmOjpaPvnkE7G3txdbW1v5+OOP5fz58+mWe/jwoXzzzTfi4+Nj2GaffPKJXLx4UUT+b79k1EU2NTVVxowZI/nz5xe9Xi+lS5eWP/74Q9q2bSv58+c3LLd8+XKpXbu2uLm5iaWlpeTLl0+++OILuXnzpmGZzLZ52vbZunVruvKQkBBxcHAQKysr8fPzk3bt2smhQ4dEROTOnTvSvXt38ff3FxsbG3FwcJDy5cvL0qVLM9wPRFlNJ/Ia1x+JiIiINMI2I0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERK/SfGGUlNTcWNGzdgZ2f32qNQEhERkVoiggcPHiB37tyGuawy8p9IRm7cuAEvLy/Vq0FERET/QnR0NPLmzZvp6/+JZCRtJMjo6GjDLJRERET0bouPj4eXl9crR3T+TyQjabdm7O3tmYwQERH9x7yqiQUbsBIREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREp9Z/oTUNEpMQwh7d8f5xp1oMom+OVESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUeqNkJCwsDB988AHs7Ozg5uaGRo0a4ezZs69837Jly+Dv7w8rKysUL14cf/75579eYSIiIspe3igZ2b59O7p37459+/Zh06ZNePLkCWrXro3ExMRM37Nnzx60bNkSHTt2xNGjR9GoUSM0atQIJ0+efOuVJyIiov8+nYjIv33z7du34ebmhu3bt6NKlSoZLvPpp58iMTERf/zxh6GsQoUKKFWqFKZPn57he5KSkpCUlGR4Hh8fDy8vL8TFxcHe3v7fri4R0ZsZ5vCW748zzXoQ/UfFx8fDwcHhld/fOd4mSFzcsz80Z2fnTJfZu3cvQkNDjcpCQkKwatWqTN8TFhaG4cOHv/6K8IRBRET0n/WvG7CmpqaiT58+qFixIooVK5bpcjExMXB3dzcqc3d3R0xMTKbvGTRoEOLi4gyP6Ojof7uaRERE9I7711dGunfvjpMnT2LXrl2mXB8AgF6vh16vN/nnEhER0bvnXyUjPXr0wB9//IEdO3Ygb968L13Ww8MDsbGxRmWxsbHw8PD4N6GJiIgom3mj2zQigh49emDlypXYsmULfHx8XvmeoKAgREREGJVt2rQJQUFBb7amRERElC290ZWR7t27Y9GiRVi9ejXs7OwM7T4cHBxgbW0NAGjTpg3y5MmDsLAwAEDv3r0RHByM8ePHo169eli8eDEOHTqEmTNnmrgqRERE9F/0RldGpk2bhri4OFStWhWenp6Gx5IlSwzLREVF4ebNm4bnH374IRYtWoSZM2eiZMmSWL58OVatWvXSRq9ERET0/nijKyOvMyTJtm3b0pU1a9YMzZo1e5NQ9DrYpZmIiLIBzk1DRERESjEZISIiIqWYjBAREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJTKoXoFiOg/YJjDW74/zjTrQUTZEq+MEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnF3jT077B3BRFlNzyvKfPGV0Z27NiB+vXrI3fu3NDpdFi1atVLl9+2bRt0Ol26R0xMzL9dZyIiIspG3jgZSUxMRMmSJTF16tQ3et/Zs2dx8+ZNw8PNze1NQxMREVE29Ma3aerWrYu6deu+cSA3Nzc4Ojq+8fuIiIgoe8uyBqylSpWCp6cnatWqhd27d7902aSkJMTHxxs9iIiIKHvSvAGrp6cnpk+fjrJlyyIpKQmzZs1C1apVsX//fpQpUybD94SFhWH48OFarxoRERG9Aw13NU9GChcujMKFCxuef/jhh7h48SImTpyI+fPnZ/ieQYMGITQ01PA8Pj4eXl5eWq8qERERKaCka2+5cuWwa9euTF/X6/XQ6/VZuEZE/wHvwK8XIiItKBn0LDIyEp6enipCExER0Tvmja+MJCQk4MKFC4bnly9fRmRkJJydnZEvXz4MGjQI169fx7x58wAAkyZNgo+PD4oWLYrHjx9j1qxZ2LJlC/766y/T1YKIiIj+s944GTl06BCqVatmeJ7WtqNt27YIDw/HzZs3ERUVZXg9OTkZ/fr1w/Xr15EzZ06UKFECmzdvNvoMIiIien+9cTJStWpViEimr4eHhxs9/+qrr/DVV1+98YoRERHR+4ET5REREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlFIyHDzRfxaHZCciMjkmI0RE9O5gwv9e4m0aIiIiUorJCBERESnFZISIiIiUYpsR+u/hPWV6H/A4p/cIr4wQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJMRoiIiEgpJiNERESk1BsnIzt27ED9+vWRO3du6HQ6rFq16pXv2bZtG8qUKQO9Xo8CBQogPDz8X6wqERERZUdvnIwkJiaiZMmSmDp16mstf/nyZdSrVw/VqlVDZGQk+vTpg06dOmHjxo1vvLJERESU/bzxrL1169ZF3bp1X3v56dOnw8fHB+PHjwcAFClSBLt27cLEiRMREhLypuGJiIgom9G8zcjevXtRs2ZNo7KQkBDs3bs30/ckJSUhPj7e6EFERETZk+bJSExMDNzd3Y3K3N3dER8fj0ePHmX4nrCwMDg4OBgeXl5eWq8mERERKfJO9qYZNGgQ4uLiDI/o6GjVq0REREQaeeM2I2/Kw8MDsbGxRmWxsbGwt7eHtbV1hu/R6/XQ6/VarxoRERG9AzS/MhIUFISIiAijsk2bNiEoKEjr0ERERPQf8MbJSEJCAiIjIxEZGQngWdfdyMhIREVFAXh2i6VNmzaG5bt27YpLly7hq6++wpkzZ/Dzzz9j6dKl6Nu3r2lqQERERP9pb5yMHDp0CKVLl0bp0qUBAKGhoShdujSGDBkCALh586YhMQEAHx8frFu3Dps2bULJkiUxfvx4zJo1i916iYiICMC/aDNStWpViEimr2c0umrVqlVx9OjRNw1FRERE74F3sjcNERERvT80701DRET/McMc3vL9caZZD3pv8MoIERERKcVkhIiIiJRiMkJERERKMRkhIiIipZiMEBERkVJMRoiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESjEZISIiIqWYjBAREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUv8qGZk6dSq8vb1hZWWF8uXL48CBA5kuGx4eDp1OZ/SwsrL61ytMRERE2UuON33DkiVLEBoaiunTp6N8+fKYNGkSQkJCcPbsWbi5uWX4Hnt7e5w9e9bwXKfT/fs1JqL3yzCHt3x/nGnWg4g088bJyIQJE9C5c2e0b98eADB9+nSsW7cOv/76K77++usM36PT6eDh4fF2a0pERJRdvedJ9xvdpklOTsbhw4dRs2bN//sAMzPUrFkTe/fuzfR9CQkJyJ8/P7y8vNCwYUOcOnXqpXGSkpIQHx9v9CAiIqLs6Y2SkTt37iAlJQXu7u5G5e7u7oiJicnwPYULF8avv/6K1atXY8GCBUhNTcWHH36Ia9euZRonLCwMDg4OhoeXl9ebrCYRERH9h2jemyYoKAht2rRBqVKlEBwcjBUrVsDV1RUzZszI9D2DBg1CXFyc4REdHa31ahIREZEib9RmJFeuXDA3N0dsbKxReWxs7Gu3CbGwsEDp0qVx4cKFTJfR6/XQ6/VvsmrqvOf3+YiIiN7WG10ZsbS0RGBgICIiIgxlqampiIiIQFBQ0Gt9RkpKCk6cOAFPT883W1MiIiLKlt64N01oaCjatm2LsmXLoly5cpg0aRISExMNvWvatGmDPHnyICwsDAAwYsQIVKhQAQUKFMD9+/fxww8/4OrVq+jUqZNpa0JERET/SW+cjHz66ae4ffs2hgwZgpiYGJQqVQobNmwwNGqNioqCmdn/XXD5559/0LlzZ8TExMDJyQmBgYHYs2cPAgICTFcLIiIi+s9642QEAHr06IEePXpk+Nq2bduMnk+cOBETJ078N2GIiIjoPcC5aYiIiEgpJiNERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESjEZISIiIqWYjBAREZFSTEaIiIhIKSYjREREpBSTESIiIlKKyQgREREpxWSEiIiIlGIyQkREREoxGSEiIiKlmIwQERGRUkxGiIiISCkmI0RERKQUkxEiIiJSiskIERERKcVkhIiIiJRiMkJERERKMRkhIiIipf5VMjJ16lR4e3vDysoK5cuXx4EDB166/LJly+Dv7w8rKysUL14cf/75579aWSIiIsp+3jgZWbJkCUJDQzF06FAcOXIEJUuWREhICG7dupXh8nv27EHLli3RsWNHHD16FI0aNUKjRo1w8uTJt155IiIi+u9742RkwoQJ6Ny5M9q3b4+AgABMnz4dOXPmxK+//prh8pMnT0adOnUwYMAAFClSBCNHjkSZMmUwZcqUt155IiIi+u/L8SYLJycn4/Dhwxg0aJChzMzMDDVr1sTevXszfM/evXsRGhpqVBYSEoJVq1ZlGicpKQlJSUmG53FxcQCA+Pj4TN4gr1mDTGT2ua+DsRmbsRmbsRmbsTN56dlrIq+IIW/g+vXrAkD27NljVD5gwAApV65chu+xsLCQRYsWGZVNnTpV3NzcMo0zdOhQAcAHH3zwwQcffGSDR3R09Evzize6MpJVBg0aZHQ1JTU1Fffu3YOLiwt0Ot0bfVZ8fDy8vLwQHR0Ne3t7U68qYzM2YzM2YzM2Y2dCRPDgwQPkzp37pcu9UTKSK1cumJubIzY21qg8NjYWHh4eGb7Hw8PjjZYHAL1eD71eb1Tm6Oj4Jquajr29fZbvRMZmbMZmbMZm7Pc9toODwyuXeaMGrJaWlggMDERERIShLDU1FREREQgKCsrwPUFBQUbLA8CmTZsyXZ6IiIjeL298myY0NBRt27ZF2bJlUa5cOUyaNAmJiYlo3749AKBNmzbIkycPwsLCAAC9e/dGcHAwxo8fj3r16mHx4sU4dOgQZs6cadqaEBER0X/SGycjn376KW7fvo0hQ4YgJiYGpUqVwoYNG+Du7g4AiIqKgpnZ/11w+fDDD7Fo0SIMHjwY//vf/1CwYEGsWrUKxYoVM10tXkKv12Po0KHpbvswNmMzNmMzNmMz9rsRWyfyqv42RERERNrh3DRERESkFJMRIiIiUorJCBERESnFZISIiIiUYjJCRERESr2Tw8HTvxMREYGIiAjcunULqampRq9lNqtydqC63snJyRnGzpcvn6Zx79+/jwMHDmQYu02bNprGBtTVOzU1FRcuXMgwdpUqVTSNrZLqeqva3ypjqz63vE+yXTKSkpKC8PDwTA+gLVu2aBY7MTER3333XaaxL126pFns4cOHY8SIEShbtiw8PT3feA6ft6Fym6us9/nz59GhQwfs2bPHqFxEoNPpkJKSolnstWvXolWrVkhISIC9vb1RvXU6nabJiMp679u3D5999hmuXr2abhZQrWOrPM5V1lvl/lYZW+W5ReV3iarjPNslI71790Z4eDjq1auHYsWKZekB1KlTJ2zfvh2tW7fO8oN3+vTpCA8PR+vWrbMsZhqV21xlvdu1a4ccOXLgjz/+yPL93a9fP3To0AFjxoxBzpw5sywuoLbeXbt2RdmyZbFu3bosj63yOFdZb5X7W2VslecWld8lyo7zl87p+x/k4uIi69atUxLbwcFBdu3apSS2s7OzXLhwQUlsldtcZb1z5swpp0+fVhb74sWLymKrrPf58+eVxFZ5nKust+r9rSq2ynOLyu8SVcd5tmvAamlpiQIFCiiJ7eTkBGdnZyWxO3XqhEWLFimJrXKbq6x3QEAA7ty5oyR2SEgIDh06pCS2ynqXL18eFy5cUBJb5XGust4q97fK2CrPLSq/S1Qd59luOPjx48fj0qVLmDJlSpZe2gKABQsWYPXq1Zg7d26WXzrv3bs35s2bhxIlSqBEiRKwsLAwen3ChAmaxVa5zVXWe8uWLRg8eDDGjBmD4sWLp4ut5VTfs2fPxogRI9C+ffsMYzdo0ECz2CrrvXLlSgwePBgDBgzIMHaJEiU0i63yOFdZb5X7W2VslecWld8lqo7zbJeMNG7cGFu3boWzszOKFi2a7gBasWKFZrFLly6NixcvQkTg7e2dLvaRI0c0i12tWrVMX9PpdJo2rlO5zVXWO21CyBf/YCULGtc9Pxnli7Iq9rtSb51OlyWxVR7nKuv9LuxvFbFVnltUfpeoOs6zXQNWR0dHNG7cWEnsRo0aKYkLAFu3blUWW+U2V1lvlbFfbOGelVTW+/Lly8piqzzOVdb7ff0bUxlb5XeJquM8210ZIeDatWsAgLx58ypek6z1vtabiLTFc4v2st2VkTS3b9/G2bNnAQCFCxeGq6trlsU+fPgwTp8+DQAoWrQoSpcurXnM1NRUjBo1CuPHj0dCQgIAwM7ODv369cM333zz0sv6pqJim6uu9/379zF79myj/d2hQwc4ODhoGhcAtm/fjnHjxhliBwQEYMCAAahcubLmsVXW++LFi5g0aZJRvXv37g0/Pz/NYwPqzi0q661yf6uKrfrcAqj5LkmT5cd5lvff0VhCQoK0b99ezM3NRafTiU6nkxw5ckiHDh0kMTFR09ixsbFSrVo10el04uTkJE5OTqLT6aR69epy69YtTWN//fXX4urqKj///LMcO3ZMjh07JlOnThVXV1f53//+p2lsldtcZb0PHjwozs7OkidPHmncuLE0btxY8ubNKy4uLnL48GFNY8+fP19y5MghzZs3l8mTJ8vkyZOlefPmYmFhIQsXLtQ0tsp6b9iwQSwtLaVcuXLSt29f6du3r5QrV070er389ddfmsZWeZyrrLfK/a0ytspzi8rvElXHebZLRrp06SK+vr7y559/SlxcnMTFxcm6devEz89Punbtqmns5s2bS9myZeXvv/82lJ06dUrKli0rLVq00DS2p6enrF69Ol35qlWrJHfu3JrGVrnNVda7UqVK0q5dO3ny5Imh7MmTJ9K2bVupXLmyprH9/f1lwoQJ6crHjx8v/v7+msZWWe9SpUrJwIED05UPHDhQSpcurWlslce5ynqr3N8qY6s8t6j8LlF1nGe7ZMTFxUW2bt2arnzLli2SK1cuTWPb29vLgQMH0pXv379fHBwcNI2t1+vl7Nmz6crPnDkjVlZWmsZWuc1V1tvKyirDAZlOnTol1tbWmsa2tLTMcBCs8+fPi16v1zS2ynrr9Xo5d+5cuvKzZ89qXm/Vx7mqeqvc36qPNVXnFpXfJaqO82w36NnDhw/h7u6ertzNzQ0PHz7UNHZqamq6blAAYGFhoXnvh5IlS2LKlCnpyqdMmYKSJUtqGlvlNldZb3t7e0RFRaUrj46Ohp2dnaaxvby8EBERka588+bN8PLy0jS2ynq7uroiMjIyXXlkZCTc3Nw0ja3yOFdZb5X7W2VslecWld8lyo5zzdIcRapXry7NmjWTR48eGcoePnwozZo1kxo1amgau0GDBlKlShW5fv26oezatWsSHBwsjRo10jT2tm3bxMbGRooUKSIdOnSQDh06SJEiRcTW1lZ27NihaWyV21xlvXv27Cl58+aVxYsXS1RUlERFRclvv/0mefPmld69e2sa++effxZLS0vp2rWrzJs3T+bNmydffPGF6PV6mT59uqaxVdZ7+PDh4ujoKN99953s2LFDduzYIWFhYeLo6CgjRozQNLbK41xlvVXub5WxVZ5bVH6XqDrOs10ycuLECcmdO7e4uLhI9erVpXr16uLi4iJ58uSRkydPaho7KipKSpUqJRYWFuLr6yu+vr5iYWEhpUuXlujoaE1ji4hcv35d/ve//0mTJk2kSZMm8s033xgdzFpRuc1F1NU7KSlJevXqJZaWlmJmZiZmZmai1+ulT58+8vjxY83jr1ixQipWrCjOzs7i7OwsFStWlFWrVmkeV2W9U1NTZcKECZInTx5D47o8efLIpEmTJDU1VdPYKo9zlfVWub9V/42pOreo/C5RdZxny3FGHj58iIULF+LMmTMAgCJFiqBVq1awtrbWPLaIYPPmzUaxa9asqXlc1VRuc9UePnyIixcvAgD8/PyyfPhmVVTX+8GDBwCg+eX6570Lx7mKegNq97fqY00Fld8lKo7zbJmMvC+OHz+OYsWKwczMDMePH3/pslrOXZHV3td6E5G2eG5RJ1skI2vWrEHdunVhYWGBNWvWvHRZU08g9uOPP6JLly6wsrLCjz/++NJle/XqZdLYZmZmiImJgZubG8zMzAxzVbxIizkcVG5zlfVu0qQJwsPDYW9vjyZNmrx0WVPP4eDs7Ixz584hV65ccHJyeukkVvfu3TNpbJX1LlOmDCIiIuDk5ITSpUu/tN6mnrND5XGust4q97fK2CrPLSq/S1Qe52myxQisjRo1MhxALxvTX4sDaOLEiWjVqhWsrKwwceLEl8Y29QF0+fJlw6h4WT13hcptrrLeDg4Ohi+FrBh98nkTJ040XJqfNGlSlsZWWe+GDRtCr9cDyPo5O1Qe5yrrrXJ/q4yt8tyi8rtE5XFu+OzscGWEiIiI/ruyxZURQqaX1nQ6HaysrFCgQAH4+Phk8Vpp732td3x8fIblOp0Oer0elpaWWbxGRNnL+3puUSXbXRnJ7F7b8wdQlSpVYG5ubvLYoaGhr4zdsGFDODs7mzx2Zvc308p0Oh0qVaqEVatWwcnJyaSxVW5zlfXO7D7+8/Vu164dqlWrZtK4wP/VOzN58+ZFu3btMHToUJNP6KWy3pm1lXkxdvv27U0eW+VxrrLeKvf3u/A3puLcovK7RNlxrlmnYUW8vb3FxsZGdDqdYfwFnU4nNjY24u7uLjqdTvz8/CQqKsrksatWrSr29vZiY2MjZcqUkTJlyoitra04ODhI+fLlxdHRUZycnOTUqVMmj71582YpX768bN68WeLj4yU+Pl42b94sQUFBsm7dOtm1a5cULVpUOnToYPLYKre5ynp//fXX4uDgIJUqVZLQ0FAJDQ2VypUri4ODg/Tu3Vtq1aolZmZmmoz9MXfuXMmbN68MHjxY1qxZI2vWrJHBgweLl5eXzJgxQ0aNGiWOjo4yevRok8dWWe8JEyaIi4uLfP755/Ljjz/Kjz/+KJ9//rnkypVLRo8eLZ06dRK9Xi8zZ840eWyVx7nKeqvc3ypjqzy3qPwuUXWcZ7tkZNGiRVK1alW5cOGCoez8+fNSvXp1Wbx4sURHR0vFihWladOmJo89ceJEadKkicTFxRnK7t+/L5988olMmjRJEhMTpWHDhlK7dm2Txy5atKjs3r07XfmuXbskICBAREQ2bdokXl5eJo+tcpurrHenTp0yHP1y5MiR0qlTJxERGTJkiAQGBpo8dvXq1WXJkiXpypcsWSLVq1cXEZF58+ZJ4cKFTR5bZb2bNGki06ZNS1c+ffp0adKkiYiI/Pjjj1KsWDGTx1Z5nKust8r9rTK2ynOLyu8SVcd5tktGfH195ejRo+nKjxw5Ij4+PiIisnv3bvHw8DB57Ny5c2eYqZ48edIwy+Phw4fFxcXF5LGtrKzkxIkT6cqPHz9umNTpypUrmkwupXKbq6y3vb19ppPV2dvbi4jI6dOnxdbW1uSxraysMpw47dy5c4a6Xrp0KdvV28bGJtPYNjY2IiJy4cIFyZkzp8ljqzzOVdZb5f5W/Tem6tyi8rtE1XGe7SbKu3nzJp4+fZqu/OnTp4iJiQEA5M6d2zCKoSnFxcXh1q1b6cpv375taHDo6OiI5ORkk8cODAzEgAEDcPv2baO4X331FT744AMAwPnz5zWZRE3lNldZbysrK+zZsydd+Z49e2BlZQXg2YRXaf83JS8vL8yePTtd+ezZsw11vXv3rsnvZQNq6+3s7Iy1a9emK1+7dq3h/nliYqImo5OqPM5V1lvl/lYZW+W5ReV3iarjPNv1pqlWrRq++OILzJo1C6VLlwYAHD16FF9++SWqV68OADhx4oQmraAbNmyIDh06YPz48YaD9eDBg+jfv7+h7/aBAwdQqFAhk8eePXs2GjZsiLx58xr+OKKjo+Hr64vVq1cDABISEjB48GCTx1a5zVXWu2fPnujatSsOHz5stL9nzZqF//3vfwCAjRs3olSpUiaPPW7cODRr1gzr1683xD506BDOnDmD5cuXG9bl008/NXlslfX+9ttv8eWXX2Lr1q0oV66cIfaff/6J6dOnAwA2bdqE4OBgk8dWeZyrrLfK/a0ytspzi8rvEmXHuUmvs7wDbt68KTVr1hSdTieWlpaGCZZq1aolMTExIiKyZcsW2bhxo8ljP3jwQDp16mQ0qZOlpaV07txZEhISRETk6NGjGV4CM4WUlBRZv369TJ48WSZPniwbNmyQlJQUTWI9T+U2F1FXbxGRBQsWSIUKFcTJyUmcnJykQoUKsnDhQsPrDx8+NJr90pQuXbokAwcOlMaNG0vjxo3l66+/lsuXL2sS60Uq671r1y5p0aKFlC5dWkqXLi0tWrTI8N6+qak+zlXVW0Tt/lYZW9W5ReV3iarjPNt17U1z5swZnDt3DgBQuHBhFC5cOMtiJyQk4NKlSwAAX19f2NraZllsAHj8+DH0ev1Lu35qQeU2B9TVm94vqo9zynqqzi0qv0uy+jjPdm1G0vj6+qJw4cL46KOPsvxkERMTg5s3b6JgwYKwtbXNcG4DU0tNTcXIkSORJ08e2NraGoYy/vbbbzNsW6AFFdtcdb3v379vuGScNh/MkSNHcP36dc1j79y5E59//jk+/PBDQ7z58+dj165dmsdWWe+LFy9i8ODB+Oyzzwz31devX49Tp05pHhtQd25RWW+V+1tVbNXnFkDNd0maLD/OTXqd5R2QmJgoHTp0EHNzczE3N5eLFy+KiEiPHj0kLCxM09h37tyR6tWri06nEzMzM0Ps9u3bS2hoqKaxhw8fLr6+vrJgwQKxtrY2xF68eLFUqFBB09gqt7nKeh87dkxcXV2lQIECkiNHDkPsb775Rlq3bq1p7OXLl4u1tbVhfIm02D/99JPUrVtX09gq671t2zaxtraWmjVriqWlpSF2WFiYJl1qn6fyOFdZb5X7W2VslecWld8lqo7zbJeM9OrVSwIDA2Xnzp1iY2Nj2JCrVq2SUqVKaRq7devWEhISItHR0WJra2uIvWHDBkO/dK34+fnJ5s2bRUSMYp8+fVocHR01ja1ym6usd40aNWTAgAHpYu/evVvy58+vaexSpUrJ3Llz08U+cuSIuLu7axpbZb0rVKgg48ePTxd7//79kidPHk1jqzzOVdZb5f5WGVvluUXld4mq4zzbJSP58uWTvXv3iojxAXT+/Hmxs7PTNLa7u7tERkami33x4kXDWABasbKykitXrqSLferUKc1jq9zmKuttb29vGBjo+dhXrlwRvV6vaWxra2tDY9UXjzWtY6ust42NjVy6dCld7MuXL2seW+VxrrLeKve3ytgqzy0qv0tUHefZrs3I7du34ebmlq48MTFR88ZHiYmJyJkzZ7rye/fuGaYC10pAQAB27tyZrnz58uWG7llaUbnNVdZbr9dnOGHduXPnDNOQa8XDwwMXLlxIV75r1y74+vpqGltlvR0dHXHz5s105UePHkWePHk0ja3yOFdZb5X7W2VslecWld8lqo7zbJeMlC1bFuvWrTM8T9t4s2bNQlBQkKaxK1eujHnz5hnFTk1Nxffff6/JRE7PGzJkCHr06IGxY8ciNTUVK1asQOfOnTF69GgMGTJE09gqt7nKejdo0AAjRozAkydPADyrd1RUFAYOHIimTZtqGrtz587o3bs39u/fD51Ohxs3bmDhwoXo378/vvzyS01jq6x3ixYtMHDgQMTExBj+vnbv3o3+/fujTZs2msZWeZyrrLfK/a0ytspzi8rvEmXHuWbXXBTZuXOn2NraSteuXcXKysowmZKNjY0cOnRI09gnTpwQNzc3qVOnjlhaWsonn3wiRYoUEXd3d6Nx/rWyY8cOqVmzpri6uoq1tbVUrFhRszEPnqdym4uoq/f9+/elZs2a4ujoKObm5uLl5SUWFhZSuXJlw1gAWklNTZVRo0YZJrTS6XRiZWUlgwcP1jSuiNp6JyUlSadOnSRHjhyi0+nEwsJCzMzM5PPPP5cnT55oGlvlca6y3ir3t8rYIurOLSq/S1Qd59lynJGLFy/iu+++w7Fjx5CQkIAyZcpg4MCBKF68uOax4+LiMGXKFKPY3bt3h6enp+axM3Po0CGULVtW0xgqt3lmsqLewLNbI8ePHzfUu2bNmprHTJOcnIwLFy4gISEBAQEBsLW1xaNHj2Btba15bJX1jo6OxokTJ5CQkIDSpUujYMGCWRJX9XGuqt6A2v2tMnZGsuLcovK7RMlxrlma8w5atmyZkriPHj2SH374QdMYDx48kIcPHxqVHT16VD7++GMxMzPTNPbLaL3N38V6Hz58WOrVq5flcR8/fizjx4/XvDdNZlTVW0Tk999/l+LFiyuJLaLu3KKy3ir3d1bEfhfPLVnxXfIyWh7n2SoZefLkiZw4cULOnj1rVL5q1SopUaKEWFpaahb71q1bsnbtWtm4caM8ffpURESSk5Nl0qRJ4u7ursnsiiIiUVFRUqFCBTEzMxMLCwvp27evJCYmSuvWrcXS0lI+/fRT2bdvnyaxRdRtc9X13rBhg/Tr108GDRpk1OWvYcOGYmZmptlYH48fP5avv/5aAgMDJSgoSFauXCkiIr/++qt4enpK3rx55bvvvtMktoi6eouITJ8+XZo2bSotW7Y07NuIiAgpVaqU5MyZU7p27apZbJXnFpX1Vrm/VcVWfW5R9V0iovY4zzbJyIkTJyR//vyGcfwbN24sMTExUqVKFXF2dpaBAwdKdHS0JrF37twpDg4OhgFqypUrJ6dOnZKCBQtKkSJFZNq0aekybFP59NNPpVSpUvLTTz9JtWrVxMzMTMqWLSvdu3fXrL5pVG5zlfWeNWuW6HQ6cXFxETMzM3F1dZX58+eLo6OjfPHFF/L3339rFvurr74SBwcHadq0qXh6ekqOHDmkc+fOUrx4cfntt98MJy8tqKx3WFiYWFhYSGBgoNjY2EjOnDll9OjR4uHhIWFhYXLv3j3NYqs8zlXWW+X+Vhlb5blF5XeJyuNcJBslIx999JHUqFFD1q5dK5999pnodDrx9/eXH374QbOdlyY4OFhatmwpJ06ckP79+4tOp5NChQplyaVbT09PQ5/w2NhY0el0MnHiRM3jiqjd5irrXbx4cfn+++9F5NlIqDqdToKCgjQ/UYmI+Pj4yOrVq0Xk2clDp9NJ+/btJTU1VfPYKutdqFAhCQ8PF5FnjQp1Op3Uq1cvSxoxqjzOVdZb5f5WGVvluUXld4nK41wkGyUjrq6uhhkM79+/LzqdTubNm5clsZ2dneXUqVMi8mwGSTMzM1m1alWWxDYzMzPMpCjybHCkM2fOZElsldtcZb1z5sxpGHAsNTVVLCwsZNeuXVkS28LCQq5du2Z4bmVlJcePH8+S2CrrbWVlJVFRUYbnlpaWWdJTS0Ttca6y3ir3t8rYKs8tKr9LVB7nItlo0LM7d+4gd+7cAAAHBwfY2NigQoUKWRL7n3/+Qa5cuQAA1tbWyJkzJ4oVK5YlsQHAzMzM6P+WlpZZElflNgfU1fvRo0eGAYl0Oh30en2W9ZZKSUkxqmeOHDmybCZPlfVOSkqClZWV4bmlpSWcnZ2zJLbK41xlvVXub5WxAXXnFpXfJarP5zmyLJLGdDodHjx4ACsrK4gIdDodHj16lG70Pnt7e03i//3334iJiQEAiAjOnj2LxMREo2VKlChh8rgigkKFChkGpknr8vf8HxMAw2yXpqRym6usN/BsAKC0JODp06cIDw83nETS9OrVy+RxRQTt2rUzjML4+PFjdO3aFTY2NkbLrVixwuSxAXX1Bp7Nlpr2BZWcnIxRo0bBwcHBaJkJEyaYPK7qc4uqegNq97fKvzGV5xZV3yWqj/NsM86ImZmZ0VC1aRvzxecpKSmaxc5oU6aVaxV77ty5r7Vc27ZtTR5b5TZXWW9vb+9XDous0+lw6dIlk8du3779ay03Z84ck8dWWe+qVau+VuwtW7aYPLbK41xlvVXub5Wx34VzqorvEpXHOZCNkpHt27e/1nLBwcEmj3316tXXWi5//vwmj62Sym1OlFV4nFNWUfldovo4zzbJCBEREf03ZZsGrERERPTfxGSEiIiIlGIyQkREREoxGcmG5NlgdqpXI0slJyfj7NmzePr0qepVISKiN5RtxhkhYN68efjhhx9w/vx5AEChQoUwYMAAtG7dWtO4c+bMwaeffmoYCyErPXz4ED179jR0xzt37hx8fX3Rs2dP5MmTB19//bVmsYODg9GxY0c0a9YM1tbWmsVJs2bNGtStWxcWFhZYs2bNS5dt0KCBSWPHx8cbxhd4cdyBF2k1DkGa+/fv48CBA7h16xZSU1ONXmvTpo1mcTt06IDJkyfDzs7OqDwxMRE9e/bEr7/+qllsb29vdOjQAe3atUO+fPk0i5OZlJQUrFq1CqdPnwYAFC1aFA0aNIC5ubnJY73q+HqelsdaSkoKwsPDERERkeGxpkV36vdZtuhN06RJk9de1tSDQZUuXfqV/eHTHDlyxKSxnzdhwgR8++236NGjBypWrAgA2LVrF6ZOnYpRo0ahb9++msV2d3fHo0eP0KxZM3Ts2BEffvihZrFe1Lt3b+zevRuTJk1CnTp1cPz4cfj6+mL16tUYNmwYjh49qlnsPn36YNGiRUhKSkLz5s3RsWNHTUcsNDMzQ0xMDNzc3NINwPQ8LcYCMDc3x82bNw2xMzrmtR6HAADWrl2LVq1aISEhAfb29kbrodPpNBuICjDeBs+7c+cOPDw8NL0qN2nSJISHh+PkyZOoVq0aOnbsiMaNGxsGv9PShQsXUK9ePVy7dg2FCxcGAJw9exZeXl5Yt24d/Pz8TBovs+MrI1oeaz169EB4eDjq1asHT0/PdOs0ceJEzWLHxsaif//+hkToxa9pLeudmJiI7777LtMkTIuxXYBskow8PxCUiGDlypVwcHBA2bJlAQCHDx/G/fv30aRJE5MPBjV8+HDD/x8/foyff/4ZAQEBCAoKAgDs27cPp06dQrdu3RAWFmbS2M/z8fHB8OHD0/0ynDt3LoYNG4bLly9rFvvp06dYu3YtwsPDsX79evj6+qJ9+/Zo27YtPDw8NIsLPOtvv2TJElSoUAF2dnY4duwYfH19ceHCBZQpU+aNfmX9G0+fPsWaNWswd+5crF+/HgUKFECHDh3QunVruLu7axo7K23fvh0VK1ZEjhw5XjkegZbjbRQqVAgfffQRxowZk2VX4uLj4yEicHJywvnz5+Hq6mp4LSUlBWvXrsXXX3+NGzduaL4uR44cQXh4OH777TekpKTgs88+Q4cOHVCmTBnNYn700UcQESxcuNAwFP3du3fx+eefw8zMDOvWrTNpvOePrytXruDrr79Gu3btDOfUvXv3Yu7cuQgLC9Nk4LE0uXLlwrx58/DRRx9pFiMzdevWRVRUFHr06JFhItSwYUPNYrds2RLbt29H69atM4zdu3dvbQJrOO+NEl999ZV06tTJaCr1p0+fSpcuXaR///6axu7YsaMMHjw4XfmQIUOkffv2msbW6/Vy/vz5dOXnzp0TvV6vaeznxcTEyLhx46R48eJiYWEh9evXl1WrVklKSoom8aytreXixYsiImJra2v4f2RkpNjb22sSMzOxsbEycuRIsbKyEgsLC2nYsKFERERoEutls5emzTiaHeXMmdOwj7NK2nTumT3Mzc1l1KhRWbpOycnJMmnSJNHr9WJmZiYlS5aU2bNnazJ7c86cOTOcjDEyMlJsbGxMHu951atXl0WLFqUrX7hwoQQHB2sa29PTU86ePatpjMzY2toaJq3Lag4ODlk2KeHzsl0ykitXrgxnWDxz5ow4OztrGtve3l7OnTuXrvzcuXOafzEWLVpURo8ena585MiRUqxYMU1jv2jfvn3SpUsX0ev14u3tLQ4ODuLt7S1bt241eazKlSvLjz/+KCLP/oAvXbokIiI9evSQkJAQk8fLzP79+6Vr167i6Ogo+fLlkyFDhkjHjh3F2tpa+vXrZ/J4RYoUkbt376Yr37Vrlzg4OJg83vO2b9/+0oeWGjduLEuWLNE0xou2bdsmW7duFZ1OJytWrJBt27YZHnv27JHr169n2bokJyfLkiVLpE6dOmJubi4VK1aUX3/9VUaMGCHu7u7SsmVLk8d0cnKS3bt3pyvftWuXODk5mTze86ytrTM8p549e1asra01jT1u3Djp1q2bJgneqxQpUkSOHDmS5XFFRLy9veXvv//O8rjZLhlxdHTMcMrlVatWiaOjo6ax3d3dZc6cOenK58yZI25ubprGXr58uZibm0tISIiMGDFCRowYISEhIZIjRw5ZsWKFprFFnl0R+eGHHyQgIECsrKykRYsWsmnTJhERSUhIkK+++kry5ctn8rg7d+4UW1tb6dq1q1hZWUnv3r2lVq1aYmNjo/lU67GxsTJu3DgpWrSoWFpaStOmTWX9+vVGJ6+dO3dq8uuxffv2EhgYKPHx8Yay7du3i729vUyYMMHk8Z6n0+nSPZ6/UqClWbNmSb58+WTo0KGyfPlyWb16tdFDS1euXFHyxSQicvjwYenRo4e4uLiIq6ur9OvXT06fPm20zIkTJ8TKysrksVu3bi1FixaVffv2SWpqqqSmpsrevXulWLFi0rZtW5PHe16hQoVkwIAB6coHDBgghQoV0jR2o0aNxMHBQXx8fOTjjz+Wxo0bGz20tHHjRqldu7ZcvnxZ0zgZmT9/vnzyySeSmJiYpXGzXTLSt29fcXFxkfHjx8vOnTtl586dMm7cOMmVK5f07dtX09hhYWFiZWUlPXv2lPnz58v8+fOlR48ekjNnTgkLC9M0tojIoUOHpFWrVlKmTBkpU6aMtGrVKkuy648//lgsLCykaNGiMnHixAx/scfGxopOp9Mk/oULF6RTp07ywQcfSJEiRaRVq1YZXlY2NQsLC/H395fvv/9ebt26leEycXFxUrVqVZPHTklJkcaNG0twcLA8fvxYtmzZIra2tjJp0iSTx3rR/fv3jR63b9+Wv/76S8qXLy+bN2/WNHZGidDzCZGW1q9fLzt37jQ8nzJlipQsWVJatmwp9+7d0zS2mZmZhISEyNKlSyU5OTnDZRISEqRdu3Ymj/3PP/9IgwYNRKfTiaWlpVhaWoqZmZk0atRI7t+/b/J4z1u3bp1YWVlJsWLFpGPHjtKxY0cpXry4WFlZybp16zSN3a5du5c+tOTo6GjYzra2tuLk5GT0MLVSpUpJ6dKlDQ87OzuxtbWVYsWKGZWXLl3a5LHTZIsGrM9LTU3FuHHjMHnyZNy8eRMA4Onpid69e6Nfv36adEV73tKlSzF58mRDF7giRYqgd+/eaN68uaZxVerYsSM6depkaGCWERFBVFRUtposcOfOnahcubKy+MnJyahXrx4ePnyI48ePIywsDD169FC2Ptu3b0doaCgOHz6sbB20VLx4cYwdOxYfffQRTpw4gbJly6Jfv37YunUr/P39NZkpGXjWSHbBggVo0KABnJycNInxOs6fP48zZ84AeHZeK1CgQJbEvXbtGn7++Wej2F27doWXl1eWxFfhVTMHm7rh7vMdMV5l6NChJo2dJtslI89L60mh9bgH74LMuh3evXsXbm5umnYFmzdvHj799NN03QyTk5OxePFiTcd+AJ4loBcuXMiwG1qVKlU0jZ2Vjh8/nq7swYMHaNmyJerVq4cvv/zSUF6iRImsXDUAwJkzZ1C2bFkkJCRkeeysYGtri5MnT8Lb2xvDhg3DyZMnsXz5chw5cgQfffQRYmJiNIttZWWF06dPw8fHR7MYRCpl62REleTk5Ay/GLUcrOj5MSied+PGDfj5+eHRo0eaxVaZCO3btw+fffYZrl69mq4vvtZjXgDA8uXLsXTpUkRFRSE5OdnoNVOPK5M2/sLz9Xz+edr/ta73i0mRiODmzZv47rvv8PTpU+zatUuz2MCzKzDjxo0zXH0MCAjAgAEDNL9K5ezsjF27diEgIACVKlVCmzZt0KVLF1y5cgUBAQF4+PChZrHLli2LsWPHokaNGprFyExoaGiG5TqdDlZWVihQoAAaNmxo6PZraqoGuQOy9u/7RVk50Ny7INuNwKpysJjz58+jQ4cO2LNnj1G5ll8QP/74I4BnJ4ZZs2bB1tbW8FpKSgp27NgBf39/k8d9Xlr9XnTt2jU4ODhoGrtr164oW7Ys1q1bl2GfeC39+OOP+Oabb9CuXTusXr0a7du3x8WLF3Hw4EF0797d5PG0HCvmTZQqVSpdUgQAFSpU0HQUUgBYsGAB2rdvjyZNmqBXr14AgN27d6NGjRoIDw/HZ599plnsSpUqITQ0FBUrVsSBAwewZMkSAM9G/c2bN69mcQFg1KhR6N+/P0aOHInAwEDY2NgYva7l1d+jR4/iyJEjSElJMQx6du7cOZibm8Pf3x8///wz+vXrZ0jUTOlVg9xpmYxk9d/38y5cuICPPvoI169fN2zzsLAwzQaae56Tk1OG59Hnk8927doZje9lCtnuyojKwWLSBoX6+uuvM4xdsmRJk8dMu2x79epV5M2b1yhrtrS0hLe3N0aMGIHy5cubPHba6LPHjh1D0aJFkSPH/+W2KSkpuHz5MurUqYOlS5eaPHYaGxsbHDt2LMvuXz/P398fQ4cORcuWLY0GXBsyZAju3buHKVOmZPk6ZYWrV68aPTczM4OrqyusrKw0j12kSBF06dIl3YjCEyZMwC+//GL4FamFqKgodOvWDdHR0ejVqxc6duwIAOjbty9SUlIMPwy08PyIu8+fV7LiStikSZOwc+dOzJkzx5D0xMXFoVOnTqhUqRI6d+6Mzz77DI8ePcLGjRtNGlvFIHdpVP59Z/VAc8+bOHEiRo8ejbp166JcuXIAgAMHDmDDhg3o27cvLl++jPnz5+Onn35C586dTRY32yUjdnZ22LlzJ0qVKpXlsW1sbHD48GHNr0RkpFq1alixYkWWNnBLa/Q0fPhw9OvXz+iqTFoi1LRpU1haWmq2DtWrV8dXX32FOnXqaBYjMzlz5sTp06eRP39+uLm5YdOmTShZsiTOnz+PChUq4O7du5qvw99//53hJWRTz03zrtDr9Th16lS65PPChQsoVqwYHj9+rGjNtKVy1Ns8efJg06ZN6a56nDp1CrVr18b169dx5MgR1K5dG3fu3DFpbBsbG5w4cQK+vr4m/dzXofLv28bGBvv27UPx4sWNyo8dO4aKFStq2i6radOmqFWrFrp27WpUPmPGDPz111/4/fff8dNPP2HmzJk4ceKEyeJmu9s0Xl5eymasDQgIMPkf4+vaunVrlsdMa1Xt7e2NTz/9NEt+Gb+oZ8+e6NevH2JiYlC8eHFYWFgYva5lQ04PDw/cu3cP+fPnR758+bBv3z6ULFkSly9f1vwYvHTpEho3bowTJ06kazcCaHs7EgAiIiIynbtCy1s1Xl5eiIiISJeMbN68OUt7Vzx+/DhdAqjlrRItk41XiYuLw61bt9IlI7dv3zZ0EnB0dEy3PUwhJCQEhw4dUpKMqPz71uv1ePDgQbryhIQETX/cAcDGjRsxduzYdOU1atRAv379ADy7cmPqSUizXTIyadIkfP3115gxYwa8vb2zNPbYsWPx1VdfYcyYMRl+MWrdq+fatWtYs2ZNhr+UJ0yYoFnctG5mKhruNm3aFMCzGVXTZFVDzurVq2PNmjUoXbo02rdvj759+2L58uU4dOjQG03e+G/07t0bPj4+iIiIgI+PDw4cOIC7d++iX79+GDdunKaxhw8fjhEjRqBs2bJZ3k6nX79+6NWrFyIjIw0TMu7evRvh4eGYPHmyprETExMxcOBALF26NMNfxVoeazt27Hjp61r2GmvYsCE6dOiA8ePH44MPPgAAHDx4EP3790ejRo0APLuMX6hQIZPHrlevHgYMGIC///47w3OqllcAVf59f/zxx+jSpQtmz55tuFWyf/9+dO3aVfOrns7Ozli7dm26W6Fr16413DJKTExMN3v1W9NsBBNFsnqwmOdlNBqlmZlZlgzItHnzZsmZM6cUK1ZMcuTIIaVKlRJHR0dxcHCQatWqaRr73LlzUqlSJSX1vnLlyksfWkpJSZEnT54Ynv/222/Ss2dP+fHHHyUpKUnT2C4uLnLs2DEReTYNQdoUCBEREVKqVClNY3t4eMi8efM0jfEyK1askIoVK4qzs7M4OztLxYoVMxx12dS6desmRYoUkeXLl4u1tbX8+uuvMnLkSMmbN68sWLBA09gqR7198OCBdOrUyXBeNTMzE0tLS+ncubMkJCSIiMjRo0c1mUtF5SB3Kv++VQ40N3PmTDE3N5f69evLyJEjZeTIkdKgQQPJkSOHzJo1S0SeDZXfvHlzk8bNdm1GsnqwmOepvK9brlw51K1bF8OHDzc0tnJzc0OrVq1Qp04dozEoTE1Fw10AePLkCfz9/fHHH3+gSJEimsR4Vzk5OeHIkSPw8fGBn58fZs2ahWrVquHixYsoXry4pt1MXVxccODAAU1b9L+L8uXLh3nz5qFq1aqwt7fHkSNHUKBAAcyfPx+//fYb/vzzT81ix8XFGT1/8uQJjh49im+//RajR4/Oki6/CQkJhunjfX19jdqIkTYuXLhgNIBmVjXU3717N6ZMmYKzZ88CAAoXLoyePXsarkZqIdslI+8rOzs7REZGws/PD05OTti1axeKFi2KY8eOoWHDhrhy5YpmsVU23M2TJw82b96sPBlJTEzEkiVL8OjRI9SuXRsFCxbUNF7lypXRr18/NGrUCJ999hn++ecfDB48GDNnzsThw4dx8uRJzWIPHDgQtra2+PbbbzWLkRlfX18cPHgQLi4uRuX3799HmTJlDF+WWrC1tcXff/+NfPnyIW/evFixYgXKlSuHy5cvo3jx4koGe8vuo96q9vjxYxw/fjzD289Z2Ug8JSUFJ06cQP78+ZWOwqulbNdm5HlZ3cgszcOHDzNst6FlY0obGxtDPE9PT1y8eBFFixYFAM0b1apsuNu9e3eMHTsWs2bNMuparKWoqCi0bt0aR44cQYUKFTB79mzUqlUL58+fBwBYW1tj/fr1mt7HHzx4MBITEwEAI0aMwMcff4zKlSvDxcXFMP6FVh4/foyZM2di8+bNKFGiRLr7+Fq2T7py5UqGbTOSkpJw/fp1zeICzxKhy5cvI1++fPD398fSpUtRrlw5rF27Fo6OjprGzoy7u7vh16uWDh06lOngXytWrNA0dmJiIrZv355h7LSxZrSwYcMGtGnTJsNzm9bt0fr06YPixYujY8eOSElJQXBwMPbs2YOcOXPijz/+QNWqVTWLHRUV9dLXtWoDmO2ujKhsZHb79m20b98e69evz/B1LWM3atQI9erVQ+fOndG/f3+sXr0a7dq1M3T33bx5s2axt2zZgsGDBytpuNu4cWNERETA1tYWxYsXTzcYlBYnyubNmyM6Oho9evTA0qVLce7cOfj5+WH27NkwMzPDl19+iXv37mHLli0mj/0y9+7dy3TAIlOqVq1apq/pdDpN6r1mzRoAz47zuXPnGg2ml5KSgoiICGzatEnTL+aJEyfC3NwcvXr1wubNm1G/fn2ICJ48eYIJEyagd+/emsVWOept2pQOISEh+Ouvv1C7dm2cO3cOsbGxaNy4sWZz8gDPBlz76KOP8PDhQyQmJsLZ2Rl37txBzpw54ebmpumVsIIFC6J27doYMmQI3N3dNYuTkbx582LVqlUoW7YsVq1ahW7dumHbtm2YP38+tmzZgt27d2sWO22k58xo9j1m0hYo7wCVjcw+++wzqVixohw8eFBsbGzkr7/+kvnz50vhwoXljz/+0DT2xYsXDQ0aExIS5IsvvpDixYtLkyZNNG/IqbLhroqZNd3d3WX//v0iInL37l3R6XSyZ88ew+uRkZHi4uKiSez31fPH2IsNGS0tLaVQoUKydu3aLF2ny5cvy++//274u9NSZnUPCgqS06dPaxq7ePHiMmXKFBERsbW1lYsXL0pqaqp07txZhgwZomns4OBg6dy5s6SkpBhiR0VFSZUqVeT333/XNLadnZ1cuHBB0xiZ0ev1Eh0dLSIinTt3lt69e4uIyKVLl8TOzk7T2JGRkUaPgwcPysyZM8Xf31/TbZ7tkhEvLy/ZunWriDw7mM6fPy8iIvPmzZO6detqGtvDw8PwJWVnZydnz54VEZHVq1dLxYoVNY2d2bTiIiK3b9/WNPa2bdte+shudDqdxMTEGJ7b2NjIxYsXDc9jYmI0T8ISEhJk8ODBEhQUJH5+fuLj42P0yK68vb01P57fRS/2EouKipJHjx5lSeycOXPK5cuXRUTE2dlZjh8/LiIif//9t3h4eGga28HBwdBTzMHBQf7++28REdm3b58ULlxY09jt27c39B7Javny5ZONGzfK06dPxcvLy/Bj9uTJk+Lo6Khknf744w8JDg7W7POzXZuRe/fuGQbIsbe3x7179wA8m1dCyx4lwLNbRGmTxTk5OeH27dsoVKgQihcvrvmkSi1atMDy5cvTXV6LjY1FjRo1NG3QqHJApjS3b982avnt6uqqabwX58jIap06dcL27dvRunXrLB/rA1DXhkD1/DyqJunLnz+/pp//Mk5OToYBuPLkyYOTJ0+iePHiuH//vqa9tgDAwsLCMBS+m5sboqKiUKRIETg4OCA6OlrT2FOmTEGzZs2wc+fODG8/a9lepX379mjevLnhb7tmzZoAno01oqKjAPDsvHrw4EHNPj/bJSMqG5kVLlwYZ8+ehbe3N0qWLGkYeG369Onw9PTUNHZUVBQ6deqE2bNnG8pu3ryJ6tWrGxqyamnnzp2YMWMGLl26hGXLliFPnjyYP38+fHx8UKlSJc3iJiYmomfPnpg3b56htbu5uTnatGmDn376SbP5LIYMGWL47OTkZIwePdrQjkHrEzQArF+/HuvWrUPFihU1j/WiV7Uh0FJm8788P4lXlSpVNJnZNKNJ+nbt2pUlk/QBz0a9nThxolFXzz59+hi+qLRSpUoVbNq0CcWLF0ezZs3Qu3dvbNmyBZs2bdK8S3Hp0qVx8OBBFCxYEMHBwRgyZAju3LmD+fPno1ixYprG/u233/DXX3/BysoK27ZtS/cDRMtkZNiwYShWrBiio6PRrFkz6PV6AM/ObaYe+fRFaaPqppH/3z5p2LBh2vYS1OyaiyITJkyQyZMni4jIpk2bxMrKSvR6vZiZmcmkSZM0jT1//nyZM2eOiIgcOnRIcuXKJWZmZmJlZSWLFy/WNPatW7fE399f+vbtKyIi169fl0KFCkmzZs0kJSVF09hp7XM6deoker3ecMvip59+0vzWWJcuXcTX11f+/PNPiYuLk7i4OFm3bp34+flJ165dNYkZHBwsVatWfeVDS97e3oZL1llNZRsCb29vsbGxEZ1OZxj0TKfTiY2Njbi7u4tOpxM/Pz+JiooyeWx/f3+ZMGFCuvLx48eLv7+/yeM9b+rUqZIjRw5p0aKFTJ48WSZPniwtW7YUCwsLw77Qyt27d+X69esi8mwgsLCwMKlfv76EhobKvXv3NI198OBB2bJli4iIxMbGSkhIiNjZ2UmZMmUkMjJS09ju7u4yevRozc+f75rM2v/ly5fPqG2cyeOKZK/eNC+6evUqDh8+jAIFCmjatTYjDx8+xJkzZ5AvXz7kypVL83jR0dGoVKkSmjZtij/++ANlypTBwoULNfmV+LzSpUujb9++aNOmjdHslkePHkXdunURExOjWexcuXJh+fLl6bq6bd26Fc2bN8ft27c1i63SggULsHr1asydOzfLZzO1sbHBqVOn4O3tDRcXF2zbtg3FixfH6dOnUb16ddy8eVOz2L/99htmzpyJWbNmGQZdu3DhAr744gt06dIFFStWRIsWLeDh4YHly5ebNLbKSfry5s2Lr7/+Gj169DAqnzp1KsaMGaN5t+b3kbOzMw4ePJhlg/u9yazPWl6VeXHwzrRZuQsUKKDt8AmapTmkxNmzZ8XNzU1atWolqampWRLT2tra0MAt7ZeyyLMePnq9XvPYGV0hOHnypOTMmVPT2CqVKlVK7OzsxNbWVooVKyalS5c2emgpT548hkaMxYsXl0WLFomIyJ49e8Te3l7T2L6+vhkOO37kyBFDw93du3dr0rDSz89Ppk+fnq582rRpUqBAAZPHe56NjY2hMf7zzp07JzY2NprGNjMzk9jY2HTld+7c0byhtkp9+vSR0aNHZ1k8b2/v13pk1wbq2aLNiMqMMjQ09LWXNfVgUJmNKfHw4UOsXbvWaJTKtIa8WvDw8MCFCxfSTUy4a9cuzWfbDAoKwtChQzFv3jzDrMGPHj3C8OHDERQUpGlsldImKFNBZRuCmzdv4unTp+nKnz59argClzt37gxnPH1bKifpa9CgAVauXIkBAwYYla9evRoff/yxprElk4vnSUlJmswgW7p06ddukK1lx4CUlBR8//332LhxY5YM7qe6cfbzLl68iEmTJhk11O7du7emV4myRTIyceLE11pOi0ZHR48eNennvYlJkyYpi/28zp07o3fv3vj111+h0+lw48YN7N27F/3799d8yPDJkycjJCQEefPmNcyBc+zYMVhZWWHjxo2axlZp6NChymJPmTLFcEvim2++gYWFBfbs2YOmTZti8ODBmsauVq0avvjiC8yaNQulS5cG8Oxv8Msvv0T16tUBACdOnICPj4/JY3/55Zfw8PDA+PHjsXTpUgDPGpEuWbIEDRs2NHm8539kBQQEYPTo0di2bZshyd63bx92795tmNZdq/g6nQ6zZs0ymosmJSUFO3bs0KRnh8pE+3knTpwwHGMv9kbMqt5rycnJuHz5Mvz8/LJshOmNGzeiQYMGKFWqlKGB/O7du1G0aFGsXbsWtWrV0iRutm8zQtoTEYwZMwZhYWGGniR6vR79+/fHyJEjNY//8OFDLFy4EGfOnAHw7AuiVatWsLa21jw2Za2YmBi0bt0aERERhl+qT58+RY0aNTB//ny4u7tj69atePLkCWrXrq14bd/O6yZUOp1Ok5FI0+JfvXoVefPmNWp7ZmlpCW9vb4wYMQLly5c3eez33cOHD9GzZ0/DxK/nzp2Dr68vevbsiTx58mjao6Z06dIICQnBd999Z1T+9ddf46+//tLsahSTERPaunVrpkNlT506Fd27dzdpvPj4eMNQ6y92x3pRVszJk5ycjAsXLiAhIQEBAQGc1VNDKSkpmDhxYqZjfWh5Wy6zY02n00Gv12ty6f5FZ86cwblz5wA861JfuHBhzWL9888/WLBgAdq2bZvu7yguLg7z5s3L8LXsolq1aoZpJVRJTk7OcLI6reZJyUh8fDy2bNkCf39/zcf66N27N3bv3o1JkyahTp06OH78OHx9fbF69WoMGzZM0yvyVlZWOHHiRLpuvOfOnUOJEiW0a6itssGKFp4+fSqzZs2Sli1bSo0aNaRatWpGDy05OjrKoUOH0pVPmjRJkyF8n29YllF3rKwakl21M2fOSPfu3aV69epSvXp16d69u+ZDZIuIrF+/Xnbu3Gl4PmXKFClZsqS0bNlS8y6P3377rXh6esq4cePEyspKRo4cKR07dhQXFxdD13atZHaspT3y5csnQ4YMyTZdIkeMGCGffPJJpq83a9ZMRo0apVn85ORk8fX1VdaVO83t27ezfPTbs2fPSqVKlZSc15o1ayY//fSTiIg8fPhQChYsKBYWFpIjRw5Zvny5prHz5csne/fuFRHjTgHnz5/XfDj4vHnzytKlS9OVL1myRLy8vDSLmy3ajDyvd+/eCA8PR7169VCsWLEsHZnyhx9+QN26dY3upY4fPx4jRozAunXrTB5vy5YtcHZ2BvDsqkxWatKkyWsvq+WInL///jtatGiBsmXLGt1LL168OBYvXoymTZtqFnvAgAEYO3YsgGf3l/v164fQ0FBs3boVoaGhmk4gtnDhQvzyyy+oV68ehg0bhpYtW8LPzw8lSpTAvn37NO36Fx4ejm+++Qbt2rVDuXLlAAAHDhzA3LlzMXjwYNy+fRvjxo2DXq/H//73P5PGTklJQXh4OCIiIjL8pazFJH2///47xo8fn+nrX3zxBfr3749vvvnG5LGBZ6OQatlt+GXu37+Pb775BkuWLME///wD4FnD+RYtWmDUqFGaDyTZvn175MiRA3/88UeWjzS8Y8cOwz5duXIlRAT379/H3LlzMWrUKE3PLbdv3zaM5v28xMREzbdB586d0aVLF1y6dMmoofbYsWPfqMPGm8p2t2ly5cqFefPm4aOPPlIS//vvv8ePP/6IXbt2YcmSJRgzZgz+/PNPJSNlaql9+/avvayWX8p+fn5o1aoVRowYYVQ+dOhQLFiwABcvXtQstq2tLU6ePAlvb28MGzYMJ0+exPLly3HkyBF89NFHmo6vYmNjg9OnTyNfvnzw9PTEunXrUKZMGVy6dAmlS5dGXFycZrFr1KiBL774As2bNzcqX7p0KWbMmIGIiAjMnz8fo0ePNrTjMZUePXoYfmxk9OX0uo3Z34SdnR1OnTqV6S2BqKgoFCtW7JW3St/GmDFjcO7cOcyaNSvLGjLeu3cPQUFBuH79Olq1aoUiRYoAAP7++28sWrQIXl5e2LNnj6a3b2xsbHD48GElQ6BbW1vj3Llz8PLyQps2bZA7d2589913iIqKQkBAABISEjSLXaVKFTRr1gw9e/aEnZ0djh8/Dh8fH/Ts2RPnz5/Hhg0bNIstIpg0aRLGjx+PGzduAHjWQ23AgAHo1auXdsmQZtdcFPH09DRMUKfKV199JS4uLuLo6Gi41JZVEhMT5fTp03Ls2DGjR3ZlbW2d6fgL1tbWmsZ2cnKSU6dOiYhIxYoVZcaMGSLybDZXrWMXKlRI9u3bZ4gdFhYmIiKLFy8WV1dXTWNbWVnJuXPn0pU/v80vXbqkyTZwcXGRdevWmfxzX8bBweGlf8d79+4VBwcHTdehUaNGYmdnJ56enlK7dm1p3Lix0UMLvXv3lmLFihlNCpnm5s2bUrx4cenTp48msdOULVvW6FZoVipYsKAsWbJEEhISxNXVVSIiIkQka2bl3rlzp9ja2krXrl3FyspKevfuLbVq1RIbG5sMmwKYypMnT2Tu3LmGfR4fHy/x8fGaxXtetrtN069fP0yePBlTpkzJkkt6GY1xkidPHuTMmRNVqlTBgQMHcODAAQDajpp3+/ZttG/fHuvXr8/w9ZSUFE3i7tu3D2vXrkVycjJq1KiBOnXqaBInM1WrVsXOnTvTjYq5a9cuzScvq1SpEkJDQ1GxYkUcOHAAS5YsAfCsoVfevHk1jd24cWNERESgfPny6NmzJz7//HPMnj0bUVFR6Nu3r6axvby8MHv27HSt7WfPng0vLy8AwN27dzX5xWxpaZluX2utdOnSWLVqFSpUqJDh6ytXrjR0AdWKo6OjprcFMrJq1SrMmDED7u7u6V7z8PDA999/j65du5r8atTzV5jGjh2Lr776CmPGjMlwsjotGw336dMHrVq1gq2tLfLnz28Y5XnHjh0oXry4ZnGBZ+eWyMhIfPfddyhevDj++usvlClTBnv37tU0do4cOdC1a1fD+CJ2dnaaxXpRtrhN82L7hbS2FEWLFk138Jq6/YLq7ndpWrVqhatXr2LSpEmoWrUqVq5cidjYWIwaNQrjx49HvXr1TB5z+fLl+PTTT2FtbQ0LCwvEx8dj7Nix6N+/v8ljPW/NmjWG/9+4cQNDhgxB8+bNDV8W+/btw7JlyzB8+HB07dpVs/WIiopCt27dEB0djV69eqFjx44AgL59+yIlJeWNBuN7W/v27cOePXtQsGBB1K9fX9NYa9asQbNmzeDv748PPvgAwLNZfM+cOYPly5fj448/xrRp03D+/HmTDww1fvx4XLp0Kct+bAD/1y5p4sSJ+PLLLw1dXFNSUvDzzz+jX79+WLRoET755JMsWZ+sotfrcfHixUwT62vXrqFAgQImb89iZmZmtG9FJN2+TivT6kdWmsOHDyMqKgq1atUy9A5ct24dHB0ds92t9zRVq1ZFnz59sny8l2yRjLwr7RdU8vT0xOrVq1GuXDnY29vj0KFDKFSoENasWYPvv/8eu3btMnnMwMBAfPDBB5g6dSrMzc0RFhaGH374QdNupQAMU4q/SlacrFR48uQJvvjiC3z77beaDO71Oi5fvowZM2YYda/94osv0o3Ca2qNGzfG1q1bs+zHRppvvvkGYWFhsLOzM4wqfOnSJSQkJGDAgAHprhJp4enTp9i2bRsuXryIzz77DHZ2drhx4wbs7e016UafJ08eLFmyJNNZt3fu3IlPP/3U0K7AVF6cG+VlgoODTRqbnrX9GjRoEPr27YvAwEDY2NgYva7VHG/ZIhmhZ5crjx8/Dm9vb+TPnx+LFi1CxYoVcfnyZRQtWlSTae1tbW0RGRlpuGyenJwMGxsbXL9+PcOW4GQ6Dg4OiIyMVJaMqPKqHx5a/tg4cOAAFi5ciAsXLkBEUKhQIXz22WeGHkVaunr1KurUqYOoqCgkJSUZBsHq3bs3kpKSMH36dJPH7NChAy5evIhNmzalGzsmKSkJISEh8PX1xa+//mry2GmioqLg5eWV4ZWR6OhozccZuXbtGtasWZPhWD6mvuoHpL8qlBGdTpfhlAimXIeMYmp9NSrbtRmpXr06VqxYka7LWXx8PBo1aqRJ1780TZs2Rbly5TBw4ECj8u+//x4HDx7EsmXLNItduHBhnD17Ft7e3ihZsiRmzJgBb29vTJ8+HZ6enprEfPjwodE9W0tLS1hZWSEhIUFpMnL//n1NuxymnTCy6lJxRho1aoRVq1Zp3j4kM/fv38eBAwcy7F7bpk0bzeKqvLJZrly5LEk8MtK7d2+ULVsWx44dM5pzqnHjxujcubMmMUeMGIGyZcuiYMGC6N69O/z9/SEiOH36NH7++WckJSVh/vz5msRO4+Pjg5s3b6Y7n9y7dw8+Pj6a/u1FRESgQYMG8PX1xZkzZ1CsWDFcuXIFIoIyZcpoEnPlypWZvrZ37178+OOP6f7eTE3VHDnZLhnZtm1bugwWAB4/foydO3dqGnvHjh0YNmxYuvK6deu+dJwCU+jdu7dh6vahQ4eiTp06WLhwISwtLREeHq5Z3BfnrHj69CnCw8ORK1cuQ5mWDXfHjh0Lb29vfPrppwCAZs2a4ffff4enpyf+/PNPw3w1pvQuTGhVsGBBjBgxArt3787wUqqW23zt2rVo1aoVEhISYG9vb/RLTqfTaZqMvK927tyJPXv2pLtC4e3tjevXr2sSM2/evNi7dy+6deuGQYMGGSbM0+l0qFWrFqZMmWJosKyVjNqLAEBCQoJhYkytDBo0CP3798fw4cNhZ2eH33//HW5ubmjVqpVmDfUzmuPo7Nmz+Prrrw1/dy8OY2Bq+fPn1/TzM5NtbtMcP34cAFCqVCmjwcCAZw3NNmzYgBkzZuDKlSuarYO1tTUiIyPTDU195swZlC5dGo8ePTJ5zMuXL2d4qf7hw4c4c+YM8uXLZ5QYmJK3t/drXVLUsuGuj48PFi5ciA8//BCbNm1C8+bNsWTJEsMw6X/99ZdmsVV62e0Zrbd5oUKF8NFHH2HMmDHImTOnZnHSlClTBhEREXBycnrljK5azuKqkpOTE3bv3o2AgADY2dnh2LFj8PX1xa5du9C0aVPExsZqGv+ff/7B+fPnAQAFChQwOr9qIW1wrcmTJ6Nz585Gx1lKSgr2798Pc3Nz7N69W7N1sLOzQ2RkJPz8/ODk5IRdu3ahaNGiOHbsGBo2bKjpdwnwrHH+0KFDMXfuXISEhCAsLAzFihXTNGYaztr7FkqVKgWdTgedTmeYvfN51tbW+OmnnzRdh+LFi2PJkiUYMmSIUfnixYsREBCgSUw/Pz/kz58f1apVQ/Xq1VG1alXkzZsXOXPm1OxSYhqt/xhfR0xMjOHX2R9//IHmzZujdu3a8Pb2zpIJvHbu3IkZM2bg4sWLWL58OfLkyYP58+fDx8cn04Z/pqDy6sz169fRq1evLElEgGe/FvV6PYB3Z0bXrFa7dm1MmjQJM2fOBPAs4UxISMDQoUOzZIBHJyenLL1FlTb3iojgxIkTRleELC0tUbJkSc177dnY2Biusnt6euLixYsoWrQoAODOnTuaxY2Li8OYMWPw008/oVSpUoiIiNB8mILnqZq1N9sMenblyhW5fPmy6HQ6OXjwoFy5csXwuHHjhjx9+lTzdVizZo3kyJFD2rRpI+Hh4RIeHi6tW7eWHDlyyMqVKzWJuXXrVhk6dKgEBweLlZWVmJmZSYECBaRLly7y22+/ZThgUXbi6ekpu3fvFpFnA4Glzalw5swZzedwWL58uVhbW0unTp1Er9cb5o/46aefpG7duprGVqlx48ayZMkS1avxXomOjpaAgAApUqSI5MiRQypUqCAuLi5SuHBhw/xU2VG7du0kLi4uS2MOHz5cEhISpGHDhjJz5kwREenXr58UKFBARo0aJWXKlJEaNWpoEnvs2LHi7OwsAQEBsmrVKk1ivEqpUqVk4MCB6coHDhwopUuX1ixutrlNAzzr8tilSxcMGTJEWS+DdevWYcyYMYiMjIS1tTVKlCiBoUOHZkkXtMePH2PPnj3Ytm0btm3bhgMHDuDJkyfw9/fHqVOnNI+vQo8ePfDHH3+gYMGCOHr0KK5cuQJbW1ssXrwY33//vaaX7UuXLo2+ffuiTZs2RpfOjx49irp162o6HDyQ9S3908yePRsjRoxA+/btMxyIqkGDBprFVkll43jgWXusJUuW4NixY0hISECZMmXQqlUrWFtbaxr3fWNubo6bN28iISEBCQkJKFGiBBITE9GvXz/DWD4TJkzQpG2FmZkZrK2tUbNmTcN4NhnRcr4vVbP2ZqtkBHg2UuHRo0ffuy6Pz0tOTsbu3buxfv16zJgxAwkJCdlyvA3gWQI6efJkREdHo127doaRMCdOnAg7Ozt06tRJs9g5c+bE33//DW9vb6Nk5NKlSwgICNB0crNXtfTX8ovxZeO8aNG7yMnJ6bUHONNyjBszMzPExMSk69lx69Yt5MmTB0+ePNEs9o4dO/Dhhx+mm5fm6dOn2LNnD6pUqaJZbJUyuuX+PC2O88z2c1Zo167dax3rWvYq8/LywoQJE9CsWTOj8qVLl6J///6IiorSJG62aTOSpmHDhkq7PKqQnJyMffv2YevWrdi2bRv2798PLy8vVKlSBVOmTMnWAwNZWFhkeO84K/a/h4cHLly4kG6gr127dhkGxtKKipb+abTuWviiSZMmZWm8F6U1jgeeTRL3/BWvtMbxefLk0XQdqlWrlmEX17i4OFSrVi3b/th4sTfckydPEBkZiZMnT6Jt27aaxc3K2YGfp2XPx9fFWXtNJG348xo1amR5l8dXDVijxQmjevXq2L9/P3x8fBAcHIzKlSsjODhYs7FF0oSGhmLkyJGwsbHJ9FebVtasWYO6devCwsLCaGj4jGh5yyAsLAwLFizAr7/+ilq1auHPP//E1atX0bdvX3z77bfo2bOnZrFVt/R/nzz/d53R6TKtcXyHDh00XYfY2Fi4uroalZ87dw5ly5bVdMbgd9GwYcOQkJCAcePGmfyzzczM4ODg8MqEROuRplURRbP2ZrtkRGWXx9WrVxs9f/LkCY4ePYq5c+di+PDhhrlLTMnCwgKenp5o1KgRqlatiuDgYKNBkbRiYWGBa9euwd3d3XCPNasuaz5/GTWrbxk8T0QwZswYhIWFGUa41ev16N+/P0aOHKlZXODZVZmtW7eiSJEiCAgIwHfffYcGDRrg2LFjqFixoqbTmwNAYmIitm/fnmF7FVMn/G/yRavFxGlXr16FiMDX1xcHDhwwSggsLS3h9v/au/eoKMvtD+DfGWDUcbiMgAnKRRQIPBJgKeqBYTCl8u5ZWQkaynKVHsQIL1moUedY2im8kZcURdQRjqIcshsKAxJCCEjcRAkCLwQpUYByEZ7fHyxmiag/RuedV4b9WYu1ZF4WewsM7Hne/Tx76NBH3t9/El1ztxISEvDSSy+pdhUBnS9ufv75Zzg6OnI6Uv5pVFZWhvHjx3NSEAiFQmzduhXGxsaP/DguV2aeFg0NDQC0MzBP54qRp9HRo0cRGxvbo1jRhKamJpw7dw5KpRIpKSm4ePEiHBwcIJPJVMXJ/a+mNMHe3l61jVYul+PkyZMPndKqq/ez29raYGBggNbWVpSVlaGxsRHOzs6QSCS4efMmJ+e7fPTRRwgNDYWfnx+mT5+OpUuXYtWqVUhISEBAQADi4+MhlUpx5swZjcfukpeXh1deeQW3b99GU1MThgwZgps3b0IsFmPo0KEaL/h7c0Q24/E0XC51HX8fHR2N+fPnd2tWFYlEsLW1xdKlSzk7S+hpFRMTg7Vr12p8Lg7Ab8/I06S2thalpaUAgGeffZaTvyP30ulihN1zYiCfysvL4eLiwvmrVaCzkk1PT1f1j+Tn58Pe3h6FhYUajXPq1Cm8/fbbqK2tVR2N/iC6+Aeiyz/+8Q8cP368x89XTU0NpkyZovGvOcBvp38Xb29vODg4YPfu3TA2NkZ+fj4MDAzg7++PlStX9pii/aSelsFp0dHRMDMzU03AXrNmDfbu3QtnZ2coFApOv+bh4eFYtWpVj9vOuu7+nyXGGKqrq3HhwgWsX78eGzdu1HhMba/0Pm0aGhqwfPlyKBQKVX+Ynp4eXnvtNURGRv6/K0aPSyeLkUOHDuGzzz5TnRjo4OCA1atXY+HChVrP5c6dO1i3bh2+/fZbVZXJpY6ODmRnZyMlJQUpKSlIT09Hc3MzZwVB15HgpaWlD33ycvHDe+fOHZw9exYzZswA0NnQ2dLSorqup6eHjz/+mNMjo1944QW4uLhg//79qseqq6vh4+ODMWPG4Pjx4xqP+TS8ajMxMUFWVhYcHR1hYmKC8+fPw8nJCVlZWXjzzTdx6dIl3nLjkqOjI3bt2gUfHx+cP38eU6ZMwdatW/H1119DX1+f0+2W/dX9gxGFQiHMzc3h4+ODadOmcRLzaXiO8em1115DXl4eduzYgYkTJwLonIuzcuVKuLq64tixY9wE5uwEE558/vnnTCwWszVr1rCEhASWkJDAVq9ezcRiMfviiy84jW1iYsKkUqnqzcTEhOnp6TFDQ0OWkJDAScz29naWlZXFNm/ezF566SVmaGjIhEIhs7KyYosWLWIHDhxgv/76KyexuyiVStbW1sZpjPvt2rWLzZgxQ/W+RCJhEyZMYN7e3szb25sNGzaM8+93bW0te/bZZ1lISAhjjLHr168zBwcH9uqrr7L29nZOYgoEAlZbW8vJ5+4tMzMzdvnyZcYYY/b29uy7775jjDFWUlLCxGIx5/HT0tKYn58fmzhxIrt27RpjjLFDhw6xc+fOcRp30KBBrLKykjHG2Jo1a9jChQsZY4wVFhYyMzMzTmP/9ttvzN/fn1lYWDA9PT0mFAq7vRGiKWKx+IHPpbS0NE6f3zq3tXfHjh3YtWtXt2Fds2bNwpgxY/Dhhx9yuuXz/i2IXVX8hAkTHtpP8aRMTEzQ1NSEYcOGQS6XIyIiAt7e3pzOELifTCZDe3s7Tpw40W2WwezZszlr7Dty5AjWrFnT7bGjR4+qttQePnwYkZGRnH6/zc3N8cMPP6iOff/666/h7u6OI0eOPLKx9kk5ODjw2unv5uaG7Oxs2NvbQyaTYcOGDbh58yZiYmI4n51x4sQJLFy4EH5+fsjNzVWthnUdof3NN99wFlsikeDWrVuwtrbGDz/8oNrmOHDgQE7mTt0rICAAVVVVWL9+PSwsLHi/9axtOTk5qt8tY8aMUZ0nRDTP1NT0gavZxsbGnP0dA6B7KyMDBgxgV65c6fH45cuX2YABA3jIqFNBQQEnn3f37t2stLSUk8/dW1euXGEODg5MLBYzNzc35ubmxsRiMXN0dGRlZWWcxBw2bBirqKhQvW9mZtbt/dLSUmZkZMRJ7PuVlpayoUOHMj8/P9bR0cFpLIFAwLZt26YaN/CwNy5lZ2ez5ORkxhhjNTU1zNfXlxkaGjJ3d3d28eJFTmO7urqy6OhoxljnaljXEfy5ubnsmWee4TT2ggULmLu7OwsMDGRisZjdvHmTMcZYQkICGzNmDKexJRIJy8vL4zTG06impobJ5XImEAhUK84CgYD5+PjwvkKoq/bs2cNefPFFVl1drXqsurqaTZs2je3evZuzuDq3MjJ69GjExcXh/fff7/Z4bGxsj+NtudbQ0ACFQoF9+/YhJyeHk76Nt956S+OfU13BwcGws7PD+fPnVdM8b926BX9/fwQHB+P06dMaj1lfX9+tR+T333/vdr2jo6PbdU152Gmgt2/fRmJiYrdt1VytTrz++uu83s9+/vnnVf8eOnSoVreVlpaWPnB3lrGxMerr6zmNHRkZibCwMFy9ehUnTpxQfa9zcnLwxhtvcBrbysrqoU3iumzFihVoaGhAUVERnJycAHQePPfmm28iODgYCoWC5wx1w/3TsK9cuQJra2tYW1sDAKqqqjBgwAD8/vvvnP3N0bliJDw8HK+99hrS0tK6TRw8e/Ys4uLitJJDWloa9u/fjxMnTsDS0hLz5s1DZGSkVmLzITU1FZmZmd3GipuamuLTTz9VfQ80bcSIESgsLISjo+MDr//8888YMWKExuPyfRpof1uevx+fp96amJhg586dPR4PDw/nNC7Q+XP33nvvYc+ePT3+77rsu+++w5kzZ1SFCNB5CzgyMpKzBtb+6KmYhs3ZmguPLly4wPz8/Ji7uztzd3dnfn5+LDc3l9OY1dXV7JNPPmGjR49mQ4cOZUFBQUxfX58VFRVxGvdpIJVKVZNz75Wens6kUiknMYODg5mzszO7c+dOj2u3b99mzs7OLDg4mJPYfBIIBLxPaeWzmXLTpk3M2dmZZWZmMkNDQ3bu3Dl2+PBhZm5uzrZv385pbMb4a541MTFhIpGICYVCJpFIujXKc/Ucexo87PZUbm4u51O5iXbp5NZebZs5cybS0tIwffp01WwQPT09GBgYID8/H87OznynyKlFixYhNzcX+/fvx/jx4wEAWVlZWLp0KcaNG8fJvIWamhq4urpCJBIhKCgIDg4OADqX8Xfu3Im7d+8iLy8PzzzzjMZjd1m0aBHkcjm8vLy02jDMt5dffhlVVVUICgp6YDPl7NmzOYvNeDz19t7m2ZiYGBQXF8POzg47d+7EN998w2nzbHR09COv6+ppoLNnz0Z9fT0UCgUsLS0BANevX4efnx+kUilOnjzJc4ZEY3guhnSCnp4eCwkJUW137NJfVkb++OMPNmvWLCYQCJhIJFK9gpszZw6rr6/nLG55eTnz9fVlQqGQCQQCJhAImFAoZL6+vqrGRi4FBgYye3t7JhAI2IgRI5ifnx/76quvevwc6Bo+minLy8u7vd/S0sKKiopYVlYWa2ho0EoOfDbP9ldVVVXM1dWVGRgYMDs7O2ZnZ8cMDAyYm5sbu3r1Kt/p6Yz7j6V41BtXdGZlpDdHRgsEAty9e1fjsTMzM7F//37ExsbCyckJCxcuxOuvvw4LC4t+sTLSpaysTLX9zsnJCaNHj9ZK3Lq6OpSVlQHobGC+t3dFG65fv460tDSkpqYiNTUVly9fhoWFBa5du6bVPLTF2dkZR44c0er2SqFQCBsbG8jlcvj4+EAul3M+Kfd+YrEYxcXFsLW1haGhIfLz82FnZ4fy8nI4OzujublZK3k0Nzf3mAfExUyepwVjDGfOnFEdpufk5IQXX3yR56x0y/+38nYvrlbhdKaB9VHLdefPn8f27ds5G33u4eEBDw8PbN26FbGxsYiKisK7776Ljo4OJCUlwcrKSiuDhvg2evRorRUg9xoyZIjq9hAfpFIpTE1NIZVKYWJiAn19fc7nOPCJj2bK5ORkKJVKKJVKKBQKtLa2ws7OTlWYyOVyTm/JAfw2zzY1NWHt2rWIi4vDrVu3elzX1ZELQOeLyKlTp2Lq1Kl8p6KzugqMu3fv4ujRo/D19eX8+dQDZ2suT4FLly6xOXPmMD09PbZo0SLOTyK9P/bq1avZsGHD2MCBA9nMmTO1Fptox7p169jEiRPZwIEDmZubG3vnnXfYqVOnWF1dHd+padz9y7h8NlPeuXOHnT17lq1fv555enqyAQMGMKFQyJydnTmNy2fz7PLly5mTkxM7fvw4GzRoEIuKimIff/wxGzFiBDt8+DCnsfmQkZHBEhMTuz0WHR3NbG1tmbm5OVu6dClrbm7mKTvdNmjQIK3+reyiM7dp7nXjxg1s3LgR0dHR8PX1xSeffML5yZAP097ejsTERERFReF///sfLzkQbnSdsBsSEoJ58+apmmh10dOwjHu/1tZW/Pjjj/j222+xZ88eNDY2crpCwHhsnrW2tsahQ4fg7e0NIyMj5ObmYvTo0YiJiYFCoeC0eZYPL7/8Mry9vbF27VoAQEFBAdzd3REQEAAnJyd89tlneOutt/Dhhx/ym6gO8vb2xjvvvKP17b46VYx0HQm9Y8cOuLq6YvPmzfD09OQ7LaKj8vPzkZqaCqVSiXPnzkEkEkEmk8Hb21s12ZZoTmtrKzIzM1UTqbOysmBlZQUvLy94eXlBJpOpDmnSpIqKCowcObJbHmVlZWhsbISzszMkEonGY95PIpGguLgY1tbWGDFiBOLj4zF+/HhUVFRg7NixWpkIrk0WFhZITExUHbD3wQcfIDU1Fenp6QCA//73v9i4cSOKi4v5TFMnxcXFYd26dQgJCcG4ceN6TIp2cXHhJrDW12I4snnzZjZkyBDm7OzMTp06xXc6pB+6ePEie/PNN5m+vr5ODi/z8vJi4eHhLC0tjbW2tmo1tlwuZ2KxmI0ZM4YtX76cKRQKduPGDa3EFggEzNbWli1evJjFxMSozhfRprFjxzKlUskYY2zKlCksNDSUMcbYtm3b2PDhw7WeD9cGDBjAqqqqVO9PnjyZ/etf/1K9X1FRwSQSCR+p6byunYn3vnXtWOTy95rOrIwIhUIMGjQIL7744iOHs9GYb82ztbXFkiVLEBAQwMkr06cVYwx5eXmqxsr09HT89ddfcHFxgUwmQ0REBN8palRAQABSU1NRWVmJQYMGYeLEiardLePHj+dsKCIAGBgYwMLCAnPmzIG3tzdkMlm3o/e51PX97VqN4aN5NiIiAnp6eggODsaZM2cwc+ZMMMbQ1taGL774AitXruQ0vrbZ2NggJiYGXl5eaG1thYmJCRITEzFlyhQAnbdtZDIZpwMh+6vKyspHXrexseEkrs4UIwEBAb06KvvAgQNayKZ/2bp1Kw4ePIjCwkLI5XIEBgZi7ty5GDBgAN+pcUoqlaKxsRHPPfec6vaMp6cnTExM+E6NU7/++iuSk5NVt6iuXr0KiUSCyZMnw8fHB6tXr9Z4zKamJpw7dw5KpRIpKSm4ePEiHBwcVF93mUymlR1Mzc3NyMjIUBUnP/30E9ra2vDss8+iqKiI8/hdKisrkZOTg9GjR3O3bM6jZcuWIT8/H5s3b8apU6cQHR2NGzduQCQSAeic2r1161ZkZ2fznCnRFJ0pRgj/cnNzcfDgQSgUCrS3t2PBggVYsmQJ3N3d+U6NE6dPn4anp6dOn/HQG+Xl5YiKisKOHTs4byLt0tDQgPT0dFX/SH5+Puzt7VFYWMh5bED7zbP9zc2bNzFv3jykp6dDIpEgOjoac+fOVV2fMmUKPDw88O9//5vHLHVbcXExqqqqepxpM2vWLE7iUTFCNK6trQ1ffvkl1q5di7a2NowdOxbBwcFYvHhxvx/0pisqKyu73b6ora2Fh4cHZDIZNmzYwHn8jo4OZGdnIyUlBSkpKUhPT0dzczNnBQFfzbPJyckICgpCZmZmj6L3zz//xKRJk7B7926dbdT/888/IZFIetwCrKurg0QiUa2UEM0pLy/H3LlzUVBQAIFAoJoW3fW7m6vnGBUjRGPa2tpw8uRJHDhwAElJSfDw8EBgYCCuXbuGyMhI+Pj44OjRo3ynqVEXLlxAXFzcA19B6Fp/0qFDh1TFx82bNzFp0iTIZDLIZDK88MILMDAw4Cx2R0cHLly4oLpN8+OPP6KpqQnDhw9X9W3I5XJO7mf7+PggKysLI0eOhEwmg6enJ2QyGSwsLDQe636zZs2CXC5HSEjIA69v374dKSkpNKOFaMzMmTOhp6eHffv2YeTIkfjpp59w69YthIaG4j//+Q93hS9nrbGk38jJyWFBQUHM1NSUmZubs9DQUFZSUtLtYwoKCtjAgQN5ypAbCoWCGRgYsBkzZjCRSMRmzJjBHBwcmLGxMQsICOA7PY0TCATMxsaG7dq1S+u7aQwNDZlQKGSWlpbMz8+P7du3j5WVlWkltr6+PrOysmIrVqxgJ06cYDdv3tRKXMYYs7a2ZsXFxQ+9XlJSwqysrLSWD9F9pqamLD8/nzHGmJGREbt06RJjjLGzZ88yV1dXzuLqzHHwhD8vvPACpk6dil27dmHOnDkPfIU8cuRIvP766zxkx51NmzYhIiIC//znP2FoaIht27Zh5MiReOutt7TyqlnbvvzySyiVSoSHh2PdunX4+9//rmoeHTduHKe34D777DPI5XJezm6pr69XNc9u3rwZb7zxhtaaZ2tqah654qSvr4/ff/+dk9ikf2pvb1eNLzEzM8ONGzfg6OgIGxsblJaWchaXbtOQJ1ZZWcnZdq+n2eDBg1FUVARbW1uYmppCqVRi7NixKCkpgY+PD6qrq/lOkTPFxcWq3TRKpRItLS2YPHky5HI5Vq1axXd6nNJm8+yoUaPw+eefP/Q0zPj4eKxatQrl5eUaj036J09PT4SGhmLOnDlYsGAB/vjjD4SFhWHv3r3IycnhrElcyMlnJf1KfyxEgM6tvQ0NDQCA4cOHq56k9fX1quPCdZWzszOWLVuG2NhY5OXlISgoCOnp6arju3XZ4MGDMWTIEAwZMgRSqRT6+vqqadWa9sorr2D9+vUPnAh8584dbNy4ETNmzOAkNumfwsLCVENlP/roI1RUVMDT0xPffPMNtm/fzllcWhkhT6y9vR0REREPbeTU1YOJFixYgOeffx7vvvsuPv74Y+zYsQOzZ89GUlIS3N3dda6BtUttba1qVUCpVOLy5cswMDCAh4cH5HI5Nm7cyHeKGsVn82xNTQ3c3d2hp6eHoKAgODo6AgAuXbqEyMhItLe3Izc3V/sTVkm/UldXB6lUyumtWCpGyBPbsGED9u3bh9DQUISFheGDDz7Ar7/+ilOnTmHDhg0IDg7mO0VO1NXVobm5GZaWlujo6MCWLVuQkZEBe3t7hIWFQSqV8p2iRi1fvhxKpRKlpaXQ19fH+PHj4e3tDblcjkmTJmHgwIF8p8gJIyMjNDU1YdiwYarCw9vbG6NGjdJK/MrKSixbtgzff/99t22Wvr6+iIyM7DY3h5C+iooR8sRGjRqF7du3Y/r06TA0NMTFixdVj2VmZurcdt7+quv4d7lcjsmTJ0MsFvOdklbs2bOHt+bZe/3xxx8oKysDYwz29vY6V+wSfi1ZsqRXHxcVFcVJfCpGyBMbPHgwSkpKYG1tDQsLC5w+fRru7u4oLy+Hm5sb/vzzT75T1Ki//vqrVx/XH05m/fTTT/H222/r/BH4hOg6oVAIGxsbuLm54VFlAVdn2tDWXvLERowYgerqalhbW2PUqFH44Ycf4O7ujuzsbJ2cT2NiYvLIe6eMMQgEgn5xPPimTZswf/58KkYI6eOWLVsGhUKBiooKLF68GP7+/hgyZIjW4tPKCHli7733HoyMjPD+++8jNjYW/v7+sLW1RVVVFUJCQvDpp5/ynaJGpaamqv7NGMMrr7yCffv2Yfjw4d0+TiaTaTs1rTM0NER+fj7s7Oz4ToUQ8oRaWloQHx+PqKgoZGRkYPr06QgMDMS0adM4H+VBxQjRuPPnz+P8+fOwt7fHzJkz+U6Hc/35D3J//r8TossqKytx8OBBHDp0CHfv3kVRUREkEgln8eg2DdG4iRMnYuLEiXynQbSguLgYlpaWfKdBCNEwoVCoGpSnjVvOdOgZeWK3bt1S/fvq1avYsGEDVq9ejXPnzvGYFdEGKyurHhNVCSF9U0tLCxQKBaZOnQoHBwcUFBRg586dqKqq4nRVBKDbNOQJFBQUYObMmbh69Srs7e1x7NgxvPTSS2hqaoJQKERTUxOOHz/+0KOsdYWhoSF+/vnnfnPeQ9crpofpD427hOia5cuX49ixY7CyssKSJUvg5+cHMzMzrcWnYoQ8tpdffhn6+vp47733EBMTg6+//hq+vr746quvAAArVqxATk4OMjMzec5Us+bNm9ft/cTERPj4+GDw4MHdHte1E1h9fHwQHx8PpVLZrRhpa2tDXl4eoqOjER4ejsDAQB6zJIQ8DqFQCGtra7i5uT3yxQZXv9eoGCGPzczMDMnJyXBxcUFjYyOMjIyQnZ2NcePGAeg8strDwwP19fX8Jqphixcv7tXHHThwgONMtEsoFOK3337D0KFDH3j96NGjiI2NRUJCgpYzI4Q8qYCAgF7tmOHq9xoVI+Sx3f/H6f6dFTU1NbC0tKRlex2hp6eH6urqhxYj5eXlqsKUEELUQQ2s5IncX0lzvRed8OdRr1vu3LmD7du39zhrhRBCeoO29pInEhAQoDpltbm5GW+//baqd6KlpYXP1IiGpaSkQCqV9pjeyRhDQ0MDxGIxDh8+zGOGhJC+im7TkMfWX3sn+ruDBw92K0aEQiHMzc0xYcIEGt5GCHksVIwQQtRSVVUFKyurB96Sq6qqgrW1NQ9ZEUL6MipGCCFqeVgj661btzB06FBqWCaEqI0aWAkhannY65fGxkYMHDhQy9kQQnQBNbASQnrl3XffBdC5Y2rDhg0Qi8Wqa+3t7cjKyoKrqytP2RFC+jIqRgghvZKXlwegc2WkoKAAIpFIdU0kEuG5557DqlWr+EqPENKHUc8IIUQtixcvxrZt22BkZMR3KoQQHUHFCCGEEEJ4RbdpCCFqu3DhAuLi4lBVVYXW1tZu13RtQCAhhHu0m4YQopZjx45h0qRJKCkpwcmTJ9HW1oaioiIkJyfD2NiY7/QIIX0QFSOEELVs2rQJERERSExMhEgkwrZt23Dp0iXMnz+fDjwjhDwWKkYIIWr55ZdfMH36dACdu2iampogEAgQEhKCvXv38pwdIaQvomKEEKIWqVSKhoYGAMDw4cNRWFgIAKivr8ft27f5TI0Q0kdRAyshRC1eXl5ISkrC2LFj8eqrr2LlypVITk5GUlISpkyZwnd6hJA+iLb2EkLUUldXh+bmZlhaWqKjowNbtmxBRkYG7O3tERYWRpN7CSFqo2KEEEIIIbyinhFCiFoWLVqEAwcO4JdffuE7FUKIjqBihBCiFpFIhE8++QT29vawsrKCv78/9u3bhytXrvCdGiGkj6LbNISQx3L9+nWkpaUhNTUVqampuHz5MiwsLHDt2jW+UyOE9DG0MkIIeSxSqRSmpqaQSqUwMTGBvr4+zM3N+U6LENIH0coIIUQt77//PpRKJfLy8uDk5ASZTAZvb294eXnRThpCyGOhYoQQohahUAhzc3OEhIRg3rx5cHBw4DslQkgfR8UIIUQt+fn5SE1NhVKpxLlz5yASiVSrI97e3lScEELURsUIIeSJ5OfnIyIiAkeOHEFHRwfa29v5TokQ0sfQcfCEELUwxpCXlwelUgmlUon09HT89ddfcHFxgUwm4zs9QkgfRCsjhBC1SKVSNDY24rnnnlPdnvH09ISJiQnfqRFC+igqRgghajl9+jQ8PT1hZGTEdyqEEB1BxQghhBBCeEU9I4QQtV24cAFxcXGoqqpCa2trt2vx8fE8ZUUI6avoBFZCiFqOHTuGSZMmoaSkBCdPnkRbWxuKioqQnJwMY2NjvtMjhPRBVIwQQtSyadMmREREIDExESKRCNu2bcOlS5cwf/58WFtb850eIaQPomKEEKKWX375BdOnTwfQOcG3qakJAoEAISEh2Lt3L8/ZEUL6IipGCCFqkUqlaGhoAAAMHz4chYWFAID6+nrcvn2bz9QIIX0UNbASQtTi5eWFpKQkjB07Fq+++ipWrlyJ5ORkJCUlYcqUKXynRwjpg2hrLyFELXV1dWhuboalpSU6OjqwZcsWZGRkwN7eHmFhYTS5lxCiNipGCCGEEMIruk1DCFFbR0cHysrKUFtbi46Ojm7XvLy8eMqKENJXUTFCCFFLZmYmFixYgMrKSty/sCoQCGhqLyFEbXSbhhCiFldXVzg4OCA8PBwWFhYQCATdrtPBZ4QQdVExQghRy+DBg5Gfn4/Ro0fznQohREfQOSOEELVMmDABZWVlfKdBCNEh1DNCCFHLihUrEBoait9++w1jx46FgYFBt+suLi48ZUYI6avoNg0hRC1CYc8FVYFAAMYYNbASQh4LrYwQQtRSUVHBdwqEEB1DKyOEEEII4RWtjBBCHktxcTGqqqrQ2tra7fFZs2bxlBEhpK+iYoQQopby8nLMnTsXBQUFql4RAKrzRqhnhBCiLtraSwhRy8qVKzFy5EjU1tZCLBajqKgIaWlpeP7556FUKvlOjxDSB1HPCCFELWZmZkhOToaLiwuMjY3x008/wdHREcnJyQgNDUVeXh7fKRJC+hhaGSGEqKW9vR2GhoYAOguTGzduAABsbGxQWlrKZ2qEkD6KekYIIWr529/+hvz8fIwcORITJkzAli1bIBKJsHfvXtjZ2fGdHiGkD6LbNIQQtXz//fdoamrCvHnzUFZWhhkzZuDy5cswNTVFbGwsfHx8+E6RENLHUDFCCHlidXV1kEqlPSb4EkJIb1AxQgghhBBeUc8IIaRXlixZ0quPi4qK4jgTQoiuoZURQkivCIVC2NjYwM3NDY/6tXHy5EktZkUI0QW0MkII6ZVly5ZBoVCgoqICixcvhr+/P4YMGcJ3WoQQHUArI4SQXmtpaUF8fDyioqKQkZGB6dOnIzAwENOmTaPmVULIY6NihBDyWCorK3Hw4EEcOnQId+/eRVFRESQSCd9pEUL6IDqBlRDyWIRCoWpQHg3HI4Q8CSpGCCG91tLSAoVCgalTp8LBwQEFBQXYuXMnqqqqaFWEEPLYqIGVENIry5cvx7Fjx2BlZYUlS5ZAoVDAzMyM77QIITqAekYIIb0iFAphbW0NNze3RzarxsfHazErQoguoJURQkivLFq0iHbMEEI4QSsjhBBCCOEVNbASQgghhFdUjBBCCCGEV1SMEEIIIYRXVIwQQgghhFdUjBBCCCGEV1SMEEIIIYRXVIwQQgghhFdUjBBCCCGEV/8HoXdyfO25CfQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mapharm_df.plot(y=[\"injuriesPer100crashes\",\"fatalitiesPer100crashes\"],kind=\"bar\",subplots=True,legend=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "94a6a017",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mapharm_df.plot(column=\"fatalitiesPer100crashes\", cmap=\"Reds\", legend=True, edgecolor=\"black\", linewidth=0.1, \n",
    "                legend_kwds={\"label\":\"fatalities per 100 crashes\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b41e61c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r56LiEn7Y+TPenl5cevEFba612WwUF5cQGRnRu8wLLueUkpAoSbXLZUHqnnvuaf13TEwMDz/8MPPnz8dsNqNWqzly5AgrVqzg4MGDJCcnAxAXF+eq7AhCr8VHhXHdyALeOmTucBXfzujc1XafI8PDuPaKyzo8v76+AUmSqKurx9vbq8f3E/qOCFKu0ydtUtXV1XzwwQdMmTIFtbrlD/Wrr74iPj6er7/+mri4OGJjY/nDH/7QZUnKaDRiMBjsNkHoK7+dMZHx3o51ojhR1WD3uVZv4K9vvNfh+T4+3kREhIsANRiILugu49Ig9dBDD+Hp6UlAQAAFBQV8+eWXrcdyc3M5ceIEq1at4r333uOdd94hIyODq666qtM0n332WXQ6XesWFRXlykcQBDuSJHHH3HF4WWp7fO32wgb0hrrWz746Hx744yIn5k4Qhp4eBamHH364y94pR48ebT3/gQceYO/evaxfvx6lUsmiRYtae0jZbDaMRiPvvfceU6dOZfr06axcuZLvv/+erKysDvOwZMkS9Hp961ZYWOjgowuCYyJDglg0Jgibxdyj6+o1/jz4/hZe/WR9r+7/6aef0dAoBgQPJH3du2/p0qVtrk1JSWk93tzczO23305AQABeXl4sWLCAsrKyTtOUZZnHH3+csLAw3N3dmTlzJsePH3f4Z+IsPapYv++++1i8eHGn58THx7f+OzAwkMDAQJKSkkhNTSUqKoodO3YwefJkwsLCUKlUJCUltZ6fmpoKQEFBQWs71Zm0Wi1arbYn2RYEp7vi/HHsyv2Wnxu634kCIFcO5Mi2ncwem0hSYnzXF5zhhx+3MSwljeKTJxk2LLHH1wuu0TKJeW/bpHp2+vDhw9mwYUPrZ5Xq19f5PffcwzfffMOqVavQ6XT83//9H1deeSU//fRTh+m98MILvPrqq7z77rvExcXx2GOPMWvWLA4fPoybm1uPH8dZehSkgoKCCApybAkDm80GtLQpAZx77rlYLBZycnJISEgA4NixY0BLRwtBGOj+NHsMd3y0lzqbigBFEzXqQADMjQZMGV9AcCKeyVOoO7AJj6TJrQsnGsvzWbdxc4+DlCzLnDxZhK9/IIcOHaagsJBpU6eiVrus/5MwgKlUKkJDQ9vs1+v1rFy5kg8//JALL7wQgLfffpvU1FR27NjBOeec0+YaWZZZvnw5jz76KPPmzQPgvffeIyQkhC+++IJrrrnGtQ/TCZe0Se3cuZPXXnuNzMxMTpw4waZNm7j22mtJSEhg8uSWLrgzZ85k7Nix3Hjjjezdu5eMjAz++Mc/ctFFF9mVrgRhoIoKC2ZBqjeSxoMASw3DlJXEKWow52diLj2OzWTEUldF48ksDPs3Ai1f1i4cm8Llc+dQUVHZafrZ2Tk0NTW3ft67N5ODBw/h5++Pzi8ApVIpAtQAIeGE6r4eFqWOHz9OeHg48fHxLFy4kIKClpWfMzIyMJvNzJw5s/XclJQUoqOj2b59e7tp5eXlUVpaaneNTqdj0qRJHV7TV1wSpDw8PPjss8+YMWMGycnJ3HTTTaSnp7Nly5bWqjqFQsFXX31FYGAg06ZNY+7cuaSmpvLRRx+5IkuC4BLXzpxIkqqKHFUE6SHuPDJvND6RCZjVXoTUZyOfyEAlW/EddwkAF7kX8tCt1xMaGkbhyZIOZ7HIzc3DU+ff+uIBiIiIYP/+fSgUCiafey4ent598oxC15zZJnVm7+VTtU+nmzRpEu+88w7r1q1jxYoV5OXlMXXqVOrq6igtLUWj0eDr62t3TUhICKWlpe3m/9T+kJCQbl/TV1zyNWzkyJFs2rSpy/PCw8NZvXq1K7IgCH1CpVJx8/QU7l9byBfHGpgyvJE/z07hJc0NeFRn499UTe6514EkkVz5EzfeeXNr/f6w5BQy9x9kzKiRbdINDw8nOyeX2Jjo1n35+fncdedd7NqxndmXzBWlqCHqzB7LTzzxBEuXLrXbN2fOnNZ/p6enM2nSJGJiYvjkk09wd3fvi2z2GTF3nyD00pjURBLdm7F6BXHvm//DYrXx1PyRjEiIolARjOr4JkaWf8+o6AB8fHxar1Or1SQMS2bPvgMcOnzELk03Ny0jhqfi5eXZum/SpInMmHEB48aM4tv/fYOnt47j2Tl99pxCJ5w4TqqwsNCuB/OSJUu6vL2vry9JSUlkZ2cTGhqKyWSitrbW7pyysrJ227CA1v1n9gDs7Jq+IoKUIDjB2KiWXn4WnzB+3Hec4YlxzJ6QwlifJi4bG8fdt97E7xctbnNdQ0MDn3z0ETHR0W2OdSQqKpKwsBD2Ze6hplbvrEcQesMZVX2/VPf5+PjYbd3pzVxfX09OTg5hYWGMGzcOtVrNxo0bW49nZWVRUFDQ2ifgTHFxcYSGhtpdYzAY2LlzZ4fX9BURpATBCeIDW6pY1AGRHK21IssyarWWmxddx9xLL+erLz9v97rSkhJSUlPJy8+nvLyi2/ebOGE88THReHt6OCX/wuBy//33s2XLFvLz89m2bRtXXHEFSqWSa6+9Fp1Ox0033cS9997L999/T0ZGBjfccAOTJ0+269mXkpLC55+3/F5KksTdd9/NsmXLWLNmDQcOHGDRokWEh4czf/78fnrKFqJSWxCcICY0iHTPI6gVCuZMGUFtrZ7Ghnqyso5QVVWNQtH+kvGvvfoy8+dfQWFhIb66no25GjdurDOyLjiBM+bu68n1RUVFXHvttVRVVREUFMR5553Hjh07WocIvfzyyygUChYsWIDRaGTWrFn885//tEsjKysLvf7XkviDDz5IQ0MDt9xyC7W1tZx33nmsW7euX8dIAUiyI4vkDCAGgwGdToder7er7xeE/lJWVs6GDRu54or5eHi409jYxI6du5gy9Xy78w7s38/Pu3Yw/fxpfPzJJ4wfP4FL587pINXu0RvqyMrOZeLYUb1KZyjoi3fDqXsELHwbhaZ3pVqbqZGqD24Q77IziOo+QXCyouJSEpNTOZ6TC4CHhzsBQcFtzlMoFPz91eU0NDSwePFizp82tcu0d+8/zNtfb6ZW3/7EyjofbxGg+oOYYNZlRJASBCdzd9MyfMQINFp3an/p2GA2tR3rEp+QwA033oSnpydhoaHdmu3864MlfFPhzd8+/JrP1m91aLVgQRhMRJASBCdLTUnieNZRYuPiyM7NJ/9EAY0NDVgsFrvztFot06adT2pqClqtpltpx/u5IdusHNYk8t6BWj7f8IMrHkHoIbF8vOuIICUITiZJEjFRERQXF5M2YiQ7d+0iPz8fhcL+z23Nl1+QmBCPzWajoKCQkpKuR/Yvmj2F38XLqJpqUQdEUm+02pWmjmbnsfKjz5z+TELnRJByHRGkBMEF/P39aG6ow2KxsHHDBnbt2tnmJTRh4iT+9tLLvPraP8jctx9ZlrusvpMkiSsumMQ0/0YsNcWsPt7Mt9v3th6PiQxjx/5jfLN1J/sOHmLtJlHSEgY30QVdEFwkLTWZA4ezWP73f/L1V19SUVFBcPCvHSgiIiKYdM5kZlxwvt3MEl2pqKjAPzgUlUmD3FxP/WkLKbq7ufG3JbdT39CALEuMGjHcqc8ktK+vu6CfTURJShBcRJIkvDzcaG5u5vJ5V9gFqFPOm3a+3VQ0er2hy1kkqmpqyatqOnUTVu/Mor6hEYCfDx1j0+6DhIWEEBEW0kkqgjOJ6j7XEUFKEFwoPi6WooITdvtOVevlZGfj5uaG+ZcOFRaLlc1btuDp8et4m6amZvbs2Wt3vY+PDxPCPVCXH0PSetLsF8ufn3mRO/++ir/+VMqan4+z5aedlHexFIggDAaiuk8QXCzAr2VAqe6XGSWqqqq4/dabUavVvP3eBzQbTRzNOk7Gnj1ERUaRsWcPZWXlaDRqZBSAfTtVeGgIz73yGqkR8ewHJHcfCnTDUXnHEdRwguV3X4NG073egoKTOGOckyhItUuUpATBxSIiwikvLWn9HBAQwBNPLuPyyy7nxx+28uclD2PQ15I0LBHZZkGr0bB79y5QqAgJDaPeYLDrUFHf0ICPjz9ltMxKoFRrUAXH4VZXzJxhOo7lF2Goq2uTD8F1RHWf64iSlCD0Aem00pAkSRw7loWbmxZ3rZbzpk7j4KHDhAQHM2pUOpGREYwdO4ZDhw7z/ebNlJWVMdswC53ul6CkUHC0qBxbQgKnzwhYsm0Nr+QOwyeshiWzUpgwSnSaEAY/EaQEoQ+4u7vR2NiIxy/tTfOvuJLrfnsVH3y0inPOPY/a2lr++8H7eOt8KSgsRKP1wGoxctutt/Lfjz7C87TZzt3d3YkaM40ilX3HCLPJiH/KFBRqDUVVdUzo0yc8u4nefa4jqvsEoQ9ER0WRdcR+YcNnn3+R/Zl7+fi/H5B97Bg7d+wgJi6e/61dx4j0dJqajGzd+gPDhiVhNJrsrl04ZRgKo32VXtCld6LUuCEplGw40r9Lfp9tRHWf64ggJQh9QK1W4eHx67Leq1d9DFYTOm9PGhoasckyTz71NCEhITz6+FIAgkPDGDF6LPHDkjl6LKd1HkCA8WmJXBRpv/zH6S86X2/7Gbnr6uvZtnOXi55OEBPMuo4IUoLQR9RqFbIss2nDd0RFRpCcnERQUBBRUVH887VXCDljme74hAQkhYKKqmqGjxxJdm6+3fEpyRFYmxvbvdfun7ayK+PXruveXl5MmTTR6c8kCK4m2qQEoY9oNWq2bNpAeHgYsixTdLKYyIhwLps7mwnjxvDEo49w8ew5zJh5Ues1P27fyceZxeCWibq5lvdOW4YjNSEW73WHacS+1GQ1m5DV7hwsNlBasYHLZ8/ss2c8W4k2KdcRQUoQ+khCfBxKhQK/oFBkWebwgUwiI8LJ2LMXGQXhERH87+uv7IJUSXUdltA0ADT1SmRZtnuZmW1t5/pTqjX4jp+DTWVi3Kgk1z+YIIKUC4kgJQh9KCYmmv2HjpKUnMLxY8fR6XRs37GLG/9wMylpwykqLLQ7X+euQW62IimUKBX2L0JJkvBT2yhv5z7WRgPF2blEzDnHxU8kCK4l2qQEoQ9JkoRa2fJnd+ToUe666y5iYmNRKBSoVCpi4+Lszi+pqgGp5fxahTdHcwvsjsf7u9Mehc1EUmqKC55AaI+EE3r3iZ4T7RIlKUHoY8MSEziem8t1v1tEYFAQMy+6uPXYmu+2cOJkCccr6qkxgVoXjOTb8vJSunnx7Z7jDIuJoK6hkfc2/Mx2vQdSOzMgmapLyT5ihJlT+uqxzmqius91RJAShD6mVquQbRaGJSXx6aqPWfnxGvblFRPgpaXU5kmdLg5FmBoA8xnX/mDQseuVLzFrPJG9gtoNUADa6BH4ete49kEEoQ+IICUI/SAowJ+l/3yPIs9hHGwKQRkVRe0vxzqrg5cUCkz+sd26x8mGjhdQ/GrDD4xOiScqMqK7WRY6IyaYdRnRJiUI/SA4OAi3wEhMQcko1a6ZsTyrQc2h7Px2j7mrFYSGtF3fSnCMmHHCdUSQEoR+ct6wICjPxctQ2PXJDlC6e7Pl0Il2j808/1zUarVL7isIziSClCD0k4smpmMt3I/e3TUlmoaSPIoPiqmQ+oIoSbmOCFKC0E+sViuq+PEo1VqXpB/YWEBAWAz19fUuSV/4lSQ5ZxPaEkFKEPqJUqkkPczT6enaLBaMORmcN2YUYSEBfL7mf06/h2CvJcj0tiTV308xMIkgJQj9aFK0r92qu85gK8tm7uh41Bo1x4/nYpI0HD6W49R7nFJUXIrBIFYBFlxHdEEXhH50wcRR/Hffd9S5h3R9cnf5hePu4UZwVBwnj+zlyjkX8Nm3m4mLCsfdvf0ZKhzl6dG79PYeOIS+wUhJWRkhISFUVNfi7eVJsK8XsZHhBPr7OSmnLuaM6jpRkmqXKEkJQj9SqVTE+Lk5PV1JqUCpVGIymymvqERfq+eTr79zeqnNz1eHj4+3w9fX6BuoUfqSdaKUEqsXmsg0jL4xHCxvJicv33kZdTHRccJ1RJAShH4W7+fcjhMqDx8qq6oASJtyEZ+s/pwRiVEc3JfJ6/9+n8KTxXbn/7BjN4eOZDk1D13JO1HA19/vZNeBLCoryhg2/jy07r8uOaILjiC31szuzP1k5+Vjs9n6NH/CwCGClCD0sykp0diandsDL6+sBqvFgn9wGJHp5/L3f77OeVPOQalU8smabyktr2g9Ny4qgqTEeKfevz2yLFNfX8+GH3ayJ6cUbWgCkkpNQEQsHl7eKFX2rQ9uQdEUKYL5uczGO2t/4vgZiz4OJP3du++5555DkiTuvvtuAPLz8zssra1atarDdBYvXtzm/NmzZzueMScQbVKC0M8SYiIJVh6kEi+npXnSJ4ncw/sYlj6OyLhhLLpnKbV1egrKj1NfXsDq7/wZmRTL6JR4IiPCnXbfzqzdvI1qqxuBITH4/BKQ2lkOqw2thwdaj2H8ePQ4kWEhTm9XcwaFQkKh6F11nezg9bt37+aNN94gPT29dV9UVBQlJSV257355pv89a9/Zc6cOZ2mN3v2bN5+++3Wz1pt70r6tbW1+Pr6Ony9KEkJwgAQoWt58Zbt/IamyuIuzu6aQqHg6MlfS0u+AUGExyYSk5RG6uSLiB85EaNXBN/tzWPrzj3k5OZhtVp7fd+O7D14GKPWn5CIGLsSk1KSqSzIxtjQeUnSarGQEOQ9IANUf6qvr2fhwoW89dZb+Pn92slEqVQSGhpqt33++edcffXVeHl1/mVIq9XaXXd6ul15/vnn+fjjj1s/X3311QQEBBAREcG+fft6/oCIICUIA0KcvzvVGesJbSpEYzM6Jc1Ct0jKT+bb7YtNHkl82mhUv0yJ5BMUTp1bCF9uyeBf73+EyWRyyr3PVFKpx8svqM3+iIQ0sNjQlxd1nkBNEVPHj3JJ3pzBmdV9BoPBbjMaO/59uP3225k7dy4zZ87sNH8ZGRlkZmZy0003dfksmzdvJjg4mOTkZG677Taqfmnf7I7XX3+dqKgoAL777ju+++471q5dy5w5c3jggQe6nc7pRHWfIPSz0ooqiotLqDm6A2VcGlobKJ2QrtJQhrdfXJfnaTRaRp4zHVmW+frHfUxKjSYizHld4rfu+BmT1o/2Zgr09NFRW1FMeOqYDq+vr6lkxoj4Ad37zZnrSZ16yZ/yxBNPsHTp0jbnf/TRR+zZs4fdu3d3mfbKlStJTU1lypTO1xebPXs2V155JXFxceTk5PDII48wZ84ctm/fjlLZ9W9laWlpa/6//vprrr76ai6++GJiY2OZNGlSl9e3x2Ulqcsvv5zo6Gjc3NwICwvj97//PcXF9tUY3377Leeccw7e3t4EBQWxYMEC8vPzXZUlQRiQnv9yF7tsUSQsfBzdlKtwC+06sHSH1TuYkhPZ3T5fkiS8w+LYlV/Dxu17qayqbnPO7p/30NjY2O00j+fkUmnzxNM3sN3jRccPdBqgALTN1YQFty2FDVWFhYXo9frWbcmSJe2ec9ddd/HBBx/g5tb5EIampiY+/PDDbpWirrnmGi6//HJGjhzJ/Pnz+frrr9m9ezebN2/uVt79/PwoLGyZMHndunWtJTxZlh2uTnZZkLrgggv45JNPyMrKYvXq1eTk5HDVVVe1Hs/Ly2PevHlceOGFZGZm8u2331JZWcmVV17pqiwJwoDkqs7VKk8d23dnYDI29+g6L99AbL5RbM0qZ+1Pe/lpz0HyTrS8eCaMH4uHh0cXKfxqb3Yx3u1U8wFYLBY0Xr6dXt9QZ+C89KQBXYoC51b3+fj42G3tdVzIyMigvLycsWPHolKpUKlUbNmyhVdffRWVSmUXED799FMaGxtZtGhRj58rPj6ewMBAsrO792Xnyiuv5LrrruOiiy6iqqqqtZPG3r17SUxM7PH9wYXVfffcc0/rv2NiYnj44YeZP38+ZrMZtVpNRkYGVquVZcuWoVC0xMr777+fefPmtZ4jCGeDpGAfCoobUWrckBTO/d7oGxSK1WIBBzpoefu1lH4agQOVDfyc/TO+7goSwgOIj43p9NrGxkY27dyPZ0hsh+dkH8ggLKXzdiaroYrwsKSeZr3P9fXy8TNmzODAgQN2+2644QZSUlJ46KGH7KrmVq5cyeWXX05QUM9Lo0VFRVRVVREWFtat819++WViY2MpLCzkhRdeaO2kUVJSwp/+9Kce3x/6qE2qurqaDz74gClTprQGn3HjxqFQKHj77bdZvHgx9fX1vP/++8ycObPTAGU0Gu0aEg0Gg8vzLwiu5OehYgT5lJdUUx3hWL19R4wqD2QnDIR19/DE3aNlMtyMghKyT2wn2M+L9BHDW79kAthsNvYdPkpOSS1eofFtxj6dTq1RdXocQKscHIN4+zpIeXt7M2LECLt9np6eBAQE2O3Pzs5m69at/O9/7U8ynJKSwrPPPssVV1xBfX09Tz75JAsWLCA0NJScnBwefPBBEhMTmTVrVrfypVaruf/++9vsP73Q0lMu7d330EMPtf7gCgoK+PLLL1uPxcXFsX79eh555BG0Wi2+vr4UFRXxySefdJrms88+i06na93ObGQUhMEmQAtleVmUWp3fvbrcK5Y13//IyTznzSjhGxTGwZxCXvvnG9z9yJOs3ryHz7bsYdWmDP67aQ/FFh90kUl2Aago7zjVVRV26Sg0nbelNFSc5KLxaU7L99no3//+N5GRkVx88cXtHs/KykKv1wMt3db379/P5ZdfTlJSEjfddBPjxo3jhx9+6NFYqffff5/zzjuP8PBwTpxoWXRz+fLldu//nuhRkHr44Ye7nHvq6NGjrec/8MAD7N27l/Xr16NUKlm0aFHr3GGlpaXcfPPNXH/99ezevZstW7ag0Wi46qqrOp1fbMmSJXaNiqca6QRhsKq3KilWh2FtasBibHJq2gqFAkPICNYfLKSxznm1DiMnX8jF1/6R0VNm4BMSjXdwNL5hMQRHxKLRtg0+dTWVVJSdpOD4YQCOH9iDT2h0p/eQJAl93eCYYb2/Z5yAlq7jy5cvt9v3zDPPUFBQYFfaPZ0syyxevBgAd3d3vv32W8rLyzGZTOTn5/Pmm28SEtL9np4rVqzg3nvvZc6cOdTW1ra2jfn6+rbJW3dJcg9mnKyoqOiyz3x8fDwajabN/qKiIqKioti2bRuTJ0/mscceY926dXbdJ0+ds337ds4555xu5clgMKDT6dDr9fj4+HT3UQRhwPjXp/8jPiaKLz/9mCxtAt7xzh8PZNJXcGWSL+GxCU5Puzt+/PZLks+ZjrW5ifqKIiQgJHl0l9d51xcxc8p4h+7ZF++GU/cY+fAalG69WxvM2tzAgecuH9TvsrS0NJ555hnmz5+Pt7c3+/btIz4+noMHDzJ9+nQqKyt7nGaP2qSCgoIcanwDWieIPNWe1NjY2Ca6n2rsE5NJCmeD737aTX6Nke++XUdNWTGNvjGEX+iaAasKrScWs3MGCTtCrVZiMZvw9g9EoVZjbux6rkJzeR5pI/onqAqOycvLY8yYtkMKtFotDQ0NDqXpkjapnTt38tprr5GZmcmJEyfYtGkT1157LQkJCUyePBmAuXPnsnv3bv7yl79w/Phx9uzZww033EBMTEy7DykIQ018RChri2zYJi/CEjEK35HTXHYvlZsHlRXlLku/Mwd2bSU0LgVvXcv0Oh7eOnQhEV1epwAC/HQuzp1zDITqvoEgLi6OzMzMNvvXrVtHamqqQ2m6JEh5eHjw2WefMWPGDJKTk7nppptIT09ny5YtrQ1wF154IR9++CFffPEFY8aMYfbs2Wi1WtatWyfm5xLOCgmxUfjTgKRQEDhpLh5Bru0EtMMcypG9Oyk4fgibzeb0taXOVGeoZffmtfhHxhEQGdvj602ShqrqGudnzAXEelIt7r33Xm6//XY+/vhjZFlm165dPP300yxZsoQHH3zQoTRd0gV95MiRbNq0qcvzrrnmGq655hpXZEEQBgVNH86eqXLzYGNFI8r8EuKycwjQ6Zgw5XyX3Ksg9xgVFaWknnuRw2n40Eh4WKgTcyW42h/+8Afc3d159NFHaWxs5LrrriM8PJxXXnnF4Xe9mLtPEPqRh6ZvB61rdIGgC6QAyK2vJvjYQWKSRnR5XU+ZmpoIj0/pVRoGc8uUPoOhZsUZ1XVDoCAFwMKFC1m4cCGNjY3U19cTHBzcq/REkBKEfmKxWGgwmh2aDcIZVF7+bM4v4DzzXnx8/QiKiHVa2qamekJ9/XuVxmB6aff1YN7BwMPDo0dTaHVELNUhCP3kP+u3U6Hp3bfM3jLqovnO4MeBI0ed0kZlbGrm6J5t+IV3PgaqOzxUikFRihJ+VVZWxu9//3vCw8NRqVQolUq7zRGiJCUI/SDzaA6bTlqQ1P3/7VmhUHBUHUf8sUPEJjtW9Wez2cjK3IGbt46IEROcUio4fYn7gU5U97VYvHgxBQUFPPbYY4SFhTnl90AEKUHoB1U1tTSpB073apWbO/pGx2akMDU3c2T/LmJHTuxyLr7ukmUZHx9vp6TVF0R1X4sff/yRH374gdGjRzstTVHdJwj9wNNN2+vqtYaKk1Qe+MlJOQKdp2PtBxo3N3QBwU4LUAD1pSe4evZ0p6Xncs4YIzX4YxRRUVFOH9oggpQg9IPSOmOvvjlrT+wiIkBH8ujxBDYW0VTUuwlkTY31eHh6OXStxWKhQV/bq/ufyU2lcLgNQ+g/y5cv5+GHH3bq4rWiuk8Q+oHs4NfmxvIC/GwGvIeNQ+X+S1Dx8kVXuxNTL/KjqS/F3Wtsj68rLzlJcUEOcaOct8SIsakRtbVnCzX2t7O5us/Pz88u7w0NDSQkJODh4dFm2aXq6rarPXdFBClB6AeNJgs9/fOr3beJ6MhwPEOikN3tSz1enp70/M+/hc1iYlZSEN463x5dd2jPDirLTjJu5ryWdGy2Dmfb7i6L2YyfqYJZF7tuiihXOJs7Tjg6u3l3iSAlCP2gpqnrIFVfcBg3Ux02lRtuGhUJaemoAiKRz3ibWRv0VJoUDtfdxxtPEJt0YbfPb2poYN/PP2JVu+E3bDTHMncQGpPMkYwfCQgModlkJGHE2NZFEnvCWJLDBRdP6fF1Qv+5/vrrXZq+CFKC0A/qjdZ299ssFiw5Ownw0+EbHolbQBg2swmr2Yjao/3ebg2FR1GEpTuUD1lfxoQxaV1WNZ3Mz0Hj5k5QaDhZhzLwHznl12sCQigvK8QvMg7PyESkmgrKi/KJSRre5f2tFgvGpgZUKjXUFHDljEntLvUz0J3N1X2n27NnD2q1mpEjRwLw5Zdf8vbbb5OWlsbSpUsd+n8rOk4IQj+orG2/u7fF1EhgVAKewybgFhAGgEKt6TBAWZobaMTxl/qUQBt+QWEdHt+z7Xt2/bydkiYzJyvK+HnbJpS+wW1eqJ4hUXhHJgJQkXukW/c2GZsJNJeT6mNFoy/kt7On4zFIB++KWdBb/PGPf+TYsWMA5Obm8tvf/hYPDw9WrVo1sCaYFQShc1lHjqL2qQCbFVmWsbh54RaehFtlNm5p3VvwE8BWehzCHJsjz7smh2HTJnZ4/HDmTqSAMPyCI3uUbsy4adRk7+vyPH1JPr+9fDoAY0f26BbCAHXs2LHWMVKrVq3i/PPP58MPP+Snn37immuucaj9SpSkBKGPVdfUUueXRKX3MCp1KVT5ptJUVoTHyT3oIuJR9KDrdXOzYwsZ2iwmpsQH4dZJu5FVlvHqYYA6RaUL4vCuHzs/x92LXRl7HUp/oBFLdbSQZbl10doNGzZwySWXAC3jpxxZlRdESUoQ+tzGXfuxefw6+aq1pphhqamoQuJ7nJY2JJbG8hwI7tkKtmENeURPmWm379DenTQjoTKb0Pn60WQy4dbjHLXwDgqnzKBn/84t+AaEEJ3YtrQXqLExcZxjS8MPNKJNqsX48eNZtmwZM2fOZMuWLaxYsQJoWbE3JCTEoTRFSUoQ+pAsy2zJs1863awvB7+uV6ptj0qSsah73o7j6aZt81JsNhrxiU2D4GiqrBK2Xk4cEJKQSkDqBA79/BMZP3zX5ri3W98uUyK43vLly9mzZw//93//x5///GcSE1vaKT/99FOmTHGs16YoSQlCHzGZTDz/3w3sq/NEOq1GTxM5AlPRUVTxo3qcpgxYbVKP/5Dr9NUcO5RJ0vDRAJzMz0btGwiAh84fdP4Q2vuZzBUKBckXXE7FwZ1kZe5GrdHiFxiMX3AoauXQ+Y58No+TOl16ejoHDhxos/+vf/2rwzOIDJ3fEkEY4F75fCvrK32QlPYhxbPqiMPz3il9gtE0lPf4OndPLwyoaGpoAODEiWzcQ3oflNq/lzdhY6bSpNBg0nhwaN/PNDU2oFENnWmPRJtU59zc3NrMPtFdIkgJggvIsty6AXz1wx6+zpfbfRHJ5iY0UWkO3cdUW0q9wpOG/IOY6vXdusZmMeHhpsUnLIaMn3/CZrOh0rq267daoyUkPhldaCThqaPIP7wXd/VQClKiCzqA1WrlxRdfZOLEiYSGhuLv72+3OUJU9wmCE1ksFj7asIvP91fQaLbiqVbiqVVwotkNWd3+LOMBXm3bh7pL4xtKhMmESu1PRXUVeHW+/IfNYiHBmEvo6MlIkkTQ8Elk7vsZhbrvlgd29w3CarERG+1Yz0Fh4HryySf517/+xX333cejjz7Kn//8Z/Lz8/niiy94/PHHHUpTBClBcIKaWj0V1bW8um4/+xp8kFSBoIIGACvQSU2HTXK8RCEpFLgHR6M//CPKqAldnq8r20PU1BmtQVGhVOId61gprjONdQbMjQYkWUataCklmGQJT/9QFEolSpsJLy/HZl0fiETvvhYffPABb731FnPnzmXp0qVce+21JCQkkJ6ezo4dO7jzzjt7nKYIUoLQS81GI0/8ZxN7DB4o3PzpSczxMeTg5tbLaYAkCX19Ex2VhUz1NVBTjM07GG+VO811tXj6BfXunmcwm4yo6iqI8HUnzMeNmIRQAgPSUCqVrS9fk8lEVk4++SVlFNqa+WbzNiYMTyIk2Ll56Q8STug44ZSc9K/S0tLWKZG8vLzQ61uqoC+99FIee+wxh9IUQUoQHGSz2Vi1aTdrD5WTYwlC4daz14xvfR7RUWFI/r2r9pIkiaioKDrqPuFbdwI3f3+UdfmMmDarV/c6k6nBgL/cyOjoAEaef26npQGNRsPI1CRGpAzjlS+2kK8KZd+67dx66VQC/P2cmi+hf0RGRlJSUkJ0dDQJCQmsX7+esWPHsnv3brRax6qURZASBAeUVVbz2Ic/cMTkh6Twd+hbdKWhidBYrw5LQD1hsdra3d9cU0ZgSCwqvzC0xY7NTtEem9WKW10xs4bHkhDTs8ltv9+2C2VAJLb6ahbNmDAkApRCklD0sijV2+sHgiuuuIKNGzcyadIk7rjjDn73u9+xcuVKCgoKuOeeexxKUwQpQeghs9nMg+9uJk8KQepF/1hFcCIWQwVab99e5cfaUEOZSd2m2UsuzSJMC0pdSxCpraro1X1OF9pczII55znUjpIQE0nm4Sqi3SEqouPJbQcTMU6qxXPPPdf679/+9rfExMSwbds2hg0bxmWXXeZQmqILuiD00IZd+8kluNfpKFQaco5n02xwdLnCX9QUow6yH+Nk1pcTovNEGzsa6ZeFCBuN5t7d5xfGOj2Thyc63NAfExlBc0kuw6MGf1vUQPHcc88hSRJ33313677p06e3GYd16623dpqOLMs8/vjjhIWF4e7uzsyZMzl+/Hi38mA2m7nxxhvJy8tr3XfOOedw7733OhygQAQpQeixn3KqndYTq9k3AWOt4yUci7GZE7k5WJobsVlM2Cwti8h76Aux+dsHrtBQx+ZOO1OgXEdEeO9KQBcOjyE1IdYp+RkI+nMw7+7du3njjTdIT29b7XrzzTdTUlLSur3wwgudpvXCCy/w6quv8vrrr7Nz5048PT2ZNWsWzc3NXeZDrVazevVqh56hMyJICUIPKRTOG4Sq1QWSl38SW1WhQ9ertG7ETb2MYGUzgbZa/EyVBDUV4Zs4CpXGvrXLKCsxG3vZLlVVxNxzer+uho9X+2PGBiuF5Jytp+rr61m4cCFvvfUWfn5t2/Y8PDwIDQ1t3Xx8fDpMS5Zlli9fzqOPPsq8efNIT0/nvffeo7i4mC+++KJb+Zk/f363z+0u0SYlCD2UGOTJ5nKL09KTokaTcyKHSEM17nE9n79PkiQ0gZ1PUGuzWpFsFmw2CzjYVUOlL2HuxCT8fTsfMNwdaSnJvU5jQJGcMM7pl8sNBvsFMbVabYc9426//Xbmzp3LzJkzWbZsWZvjH3zwAf/5z38IDQ3lsssu47HHHsPDo/0vCHl5eZSWljJz5q+z4+t0OiZNmsT27du55pprunyEYcOG8Ze//IWffvqJcePG4elpvxSMGCclCH0gMcQb275yFCrnzeLd6JdAXc0+3OOclqQdU9EhtDYLCoVjf/KyLDMixJuIkN63xQmdi4qKsvv8xBNPsHTp0jbnffTRR+zZs4fdu3e3m851111HTEwM4eHh7N+/n4ceeoisrCw+++yzds8vLS0FaLOkRkhISOuxrqxcuRJfX18yMjLIyMiwOyZJkghSgtAXJo9KZdKObHY3Bjg3YbWjqzd1zS0mnea6WipPniAsPqnH1zdUljB21lgX5GxocGbvvsLCQrtqufZKUYWFhdx111189913uLm1/3tzyy23tP575MiRhIWFMWPGDHJyckhI6Nn6Y911eqcJZxFtUoLQQ5IksfT3M0lTlDg13SJFGPW5mci29sc89Zabty8NtY71JFQqJPbtP+jkHA0dkpP+A/Dx8bHb2gtSGRkZlJeXM3bsWFQqFSqVii1btvDqq6+iUqmwWq1trpk0aRIA2dnZ7T5DaGgoAGVlZXb7y8rKWo/1BxGkBMEB3p4ePPX7GYRYHVsSuz1KDx+ymvxoLjzstDTPZPYIpOjI/h5f12y2sb2ozgU5EhwxY8YMDhw4QGZmZus2fvx4Fi5cSGZmZrtrN2VmZgIQFtZ+z8y4uDhCQ0PZuHFj6z6DwcDOnTuZPHlyt/K1YMECnn/++Tb7X3jhBX7zm990K40ziSAlCA4KCvDjxesmku5WBU3dWyajKyoPb5obXBcMrJ6BWExddyc+k19oBCpNL+cYHML6uneft7c3I0aMsNs8PT0JCAhgxIgR5OTk8NRTT5GRkUF+fj5r1qxh0aJFTJs2za6rekpKCp9//jlA6zirZcuWsWbNGg4cOMCiRYsIDw9n/vz53crX1q1bueSSS9rsnzNnDlu3bu3+A55GtEkJQi/ERITx99suo7Siim92HiW32kiJvomCRhVmjbdDaXp4um52cFV5FrHjJjl0rUntRUFxCdG9HCM1FA20WdA1Gg0bNmxg+fLlNDQ0EBUVxYIFC3j00UftzsvKymqdBBbgwQcfpKGhgVtuuYXa2lrOO+881q1b12G715nq6+vRtPNlRq1Wt+m12F2SfGpVtkHKYDCg0+nQ6/WdjgEQhL50LK+I1zccYE+1ClsH60h1ZIRbJcqwnndu6A5LfTVe9cXEjep6WY/2+NQVcfUFE9t9EQ00ffFuOHWPOa98j9q9d18uzE31rL3rgkH9Lps4cSKXXnppm7Wjli5dyldffdWmx193iJKUILhAUlwkL90cyeafD/H894U0KLtfqtJXlOLvoiAlK1QoerFse61nOK+v24W5sY7fnJdOdGTn47POFmLuvhaPPfYYV155JTk5OVx44YUAbNy4kf/+97+sWrXKoTRFkBIEF5o+fjglNXX8M9OIpOz6zy20Zh8+ST0f0Ntdag8fLLWOdxNWKBTgF0a8t1IEqNOIWdBbXHbZZXzxxRc888wzfPrpp7i7u5Oens6GDRs4//zzHUpTBClBcLFrZk5i/4n/8aNe12m7g8XUjLu7Gyovf5flxWJsxk3Vuz97laGU+ZdMcVKOhKFm7ty5zJ0712npid59guBikiTx5KKLuCLKhNrS0O451sY6kqWTeCc71qmh23lprCY4Zliv0gj1cRsSS50706nqvt5uQlsiSAlCH9BoNNx79YU8dH44Aeby1tnKAUwVeQz3rsMjYWzrshqu4mmtx9Ond3PvBXg6Y5nGoaU/Z0Ef6vokSBmNRkaPHo0kSa0Dyk7Zv38/U6dOxc3NjaioqC6nkheEweziSSP47MH5vDwnnKn+9chmI8HGIpSBMSjaGYDpbJKtd2tKWS0WDKd1WRZaiJKU6/RJm9SDDz5IeHg4+/bts9tvMBi4+OKLmTlzJq+//joHDhzgxhtvxNfX127eKUEYSiRJYsLIZCaMTGbfkWOEBY2isdnIjqxCdpRasHq4pk3K3NyIey+/lyoNpcwR7VFCH3J5kFq7di3r169n9erVrF271u7YBx98gMlk4t///jcajYbhw4eTmZnJSy+9JIKUcFYYlfprV/PYyHAmFRbzjx/yMLo7P1DZDOUERjs+zbrVYiE5wL2lh59gR/Tucx2X/raVlZVx88038/7777e7hsn27duZNm2a3cDAWbNmkZWVRU1NjSuzJggDUlxUONdPCMezyfHVejtitclYzI6vg2WuLmHmpDFOzNHQITlpG8wOHz7Mn/70J8aMGUNYWBhhYWGMGTOGP/3pTxw+7Ph8lC4rScmyzOLFi7n11lsZP348+fn5bc4pLS0lLs7+m92ptUxKS0vbXWnSaDRiPG11UUen2hCEgWrksDj+5OXJ8k1ZmD0CnZauB2aaDDUo1Sq8dW3/troS5+cmSlFCu9auXcv8+fMZO3Ys8+bNa32Pl5WV8d133zF27Fi+/PJLZs2a1eO0exykHn744XZnuT3dkSNHWL9+PXV1dSxZsqTHmerMs88+y5NPPunUNAVhoIkOC2Z+aiUfHWtEqXXSUuuhSZRWFGI1lOLRlEna5Au6famxqZER8WLBw44MtLn7+trDDz/MQw89xF/+8pc2x5YuXcrSpUt54IEHHApSPf5adN9993HkyJFOt/j4eDZt2sT27dvRarWoVCoSExMBGD9+PNdffz3Qsn5Je2uXnDrWniVLlqDX61u3wsLCnj6CIAwK08amMcGn5zOWd8YtKArPsFhs4SM4uH0LpubupS/bbBiNpq5PPEv19SzoA82xY8dYuHBhh8evvfZajh8/7lDaPS5JBQUFERQU1OV5r776KsuWLWv9XFxczKxZs/j4449bF9+aPHkyf/7znzGbzajVLUtxf/fddyQnJ7db1Qctq1S2twiYIAxF184Yz+FV22j2dO6ic0o3L5rc/KmvrsQ/PLLL86WGaoYnT3VqHoShIzY2lm+++Ybk5OR2j3/zzTfExMQ4lLbL2qSio6PtPnt5tcwQnJCQQGRkyx/Fddddx5NPPslNN93EQw89xMGDB3nllVd4+eWXXZUtQRhU3LRaxoZ5ss0FTa/u4YmUFB1EoVLjGxzS4XkWs4mUAO2gro5ytbO9uu8vf/kL1113HZs3b2bmzJl2bVIbN25k3bp1fPjhhw6l3a9z9+l0OtavX8/tt9/OuHHjCAwM5PHHHxfdzwXhNGlhOn6sMaHoxgS1PSWr3ToNUAAafTGzL3NsctCzySCOMb32m9/8hoiICF599VX+9re/UVpaCrQ020yePJnNmzd3e3XfM/VZkIqNjaW9pavS09P54Ycf+iobgjDopCbGYdvxIwo/5y82aJK01FaU4hvUtjrRbKgm0Utm0nmjBvW3fKFvTJkyhSlTnD/QW8yCLggDnEajQaeB9qem7R334Cjy929i9Az7WavNJiPnhCiZNMZ1y4YMJWd7dd/p9Hq9XUlKp+vdXJFi0IMgDAK+7mqXpe0f2nZdKJu+nImj0112z6HmbO/dB/Cvf/2LtLQ0/P39SUtLIzU1tfXfK1eudDhdUZIShEHAU6MCxyeL6JDVYqaqtIjo4aPt9us0iiHzzb4vnO0lqb/+9a8sXbqUO++8k1mzZtl1nFi/fj133XUXNTU13H///T1OWwQpQRgEbO205zqDUqVG0gVReTIfXWAY6l+Gd8QFernkfsLQ9Nprr/H2229z9dVX2+1PTU1l+vTpjBo1igceeEAEKUEYqgxGi8v+WhVR6ZRVFlBYcgiNZMFUW8YVf7zGNTcbopwx997gLUdBeXk5I0eO7PD4yJEjqaysdCht0SYlCIOAvql360B1RREYjVtUKorIkSjiJmC1uKBucQg7NQt6b7fBasKECTz33HNY2vm9sVqtPP/880yYMMGhtEVJShiyNvyUQWZeNVH+WsorqwgPCSQtPpKUxNhBVf/f1NREnUWJputTe8VqNhGv1BMWpCQ8tPOxU4Jwutdee41Zs2YRGhrKtGnT7Nqktm7dikajYf369Q6lLYKUMOTIsswrH23g1c0VmCUVr10Vxc1Xz6GsoorDOUV8s2ErwQF+LLr68v7OarfsP5aH2te1k7varFbO96vntxdNc+l9hipnrKw7iL43tZGens6xY8f4z3/+w44dO8jNzQVauqAvW7aM6667Dh8fH4fSFkFKGFJkWeZv//qIXXsP4WkOZMboOObNbBnpHhMVQUxUBHOmT8Jms/VzTruvoLYJSXLSTOgdcDcU8ZsrL3bpPYays713H4C3tze33XYbt912m1PTFUFKGDJOnCzlweUfkb1/O9XB52H2jmJcYvslkMG0LlJuZSMoXBekVPpiHrx84qD6mQiDi9lspqSkpM2crt0hfiuFIeFIbiHX/G0TP+rDKYu7GotPNGFSJT5So8vvLcsy1TW1Lkm7qbmZvBrnLddhs9nQH/sZi6ll2Q2b1cqlKf4EBzp/ufqzyanqvt5uQ9Xhw4fbLHDbXaIkJQx65VW13LvyJ4qMnihOm5ih0uJJeaNrxhedbs++/YSFOX9ePYA1G7Yiewa02W+z2VCe2IM1ZmxrCUhVkY3WqEfvGYHK79e5+FoCko10cw5hgf6M+t0c8k/ks/PgIbx8dFw46RKX5P1s4ozeeYO5d58riSAlDGr7j+Xzpze2caLZs80xi8qDnRn7uHnBTJfce8/+gwQH+LFjzz5uvX6ES+6REBmOYf9B9ihSUWk0NJfmkeJppLS8kvv/8Dt2//wzP2YVUd1gZMG0dIanXcyKDz6lgpYgZSw6ygitnjGjRhEWNpWAwJbl6Ef7+eHppmHCmJGDvi1E6H9jx47t9HhTU5PDaYsgJQxKFouFZ9/+ik/2NVAre3d43obqCL7aksFl549r3WcymajR1xES1LaE0l0/bN/B199vJy87iwkTJlJQWERcrGOLunUkJzePiOg4PL11hOTmYbFaiZgUTVJKKiaTCY1Gw7lTpjD5HBs11dUEBAZiMplorKtlmPt+NGo1o89NIjkltU3aRqMRH093EaCc5Gzv3Xf48GGuueaaDqv0SkpKOHbsmENpiyAlDDqyLHPn31axN7uEWk1Cp+dale7c+WEWR/OLufd3l7Btz2He/PQ7FF5BvPvY7x3OQ1aZAW1wFMnBkcwYl+S0AFVTU9O6KrW+vgn/UDdCw8IJDQu3O0+j+XXUlEKhaC0haTQaHvq/W7u8T3HRCcaObBu8BMf0d+++5557jiVLlnDXXXexfPlyqqureeKJJ1i/fj0FBQUEBQUxf/58nnrqqU5nJV+8eDHvvvuu3b5Zs2axbt26Tu8/YsQIJk2a1GHPvszMTN56662ePxgiSAmD0D8+3siqIxLxShuybEOSOu//Y1F58spOC1/v/5Aao0StOZx4m4WM/YcZl57W4/sfOHKMvdt/IHLChbg3VDBmdDp6vb7XSxLo9XrWrt/AVVfMIyc3n+Cwrpd1d5TSZSmfnRT0vheao9fv3r2bN954g/T0X2etLy4upri4mBdffJG0tDROnDjBrbfeSnFxMZ9++mmn6c2ePZu333679bP2l/kcO3PuueeSlZXV4XFvb2+mTXNsDJ4IUsKgknOimPe2lSIpNJysbiIiuJBiVdelGElSkNv8y2BCFeQ0wvMfb+cTB4JUdU0NwWkT0TTWcN7IYeSdOEF8bCyHjmZhbG5i7OjRPU4TYG/mfqZPPY+8E4W4efvj6dm2nc0ZDHo9fr5iAtmhoL6+noULF/LWW2+xbNmy1v0jRoxg9erVrZ8TEhJ4+umn+d3vfofFYkGl6vjVr9VqCQ1tuwhmZ1555ZVOjyckJPD999/3KM1TRBd0YVD58UAe+fUtVV0mv2QaDHq8mk6CpefdtG2SY9/RoiMjsBkqmDYinjqTlVdW/odX33obk9HI6HTH12Cafv5UwsPDMJmt+P5S5edssixTVJCLby9LfYK9U9V9vd166vbbb2fu3LnMnNl15yC9Xo+Pj0+nAQpg8+bNBAcHk5yczG233UZVVVWP8+VMoiQlDCoeGvtf2XL3ZGymZqI1NVTQs27gJn2pQ3nQqBSobGZOFJ0kp7SGsSPTSIiJ4qPVXzAsIZ6yigoSHBwTAmC2Wh2+tis5xw4zadzoLl9UQs9ITli08FSMMhgMdvu1Wm27VW4fffQRe/bsYffu3V2mXVlZyVNPPcUtt9zS6XmzZ8/myiuvJC4ujpycHB555BHmzJnD9u3bUSr7p5JY/KYKg0p8qA+yzYKkaPnVlY31RHs0UKHs2Uj2GLc6brv0/B7ff+/+Q3z948+cLClF7ReMjwa83N3Y+ONOIiIi2LIjg+0/7yE+IpgbfncdmfsPMGZU90tXBw4dITzSub0ET6mrqyPQTycC1AAXFRVl9/mJJ55g6dKldvsKCwu56667+O6773Bzc+s0PYPBwNy5c0lLS2uTzpmuuebXJVpGjhxJeno6CQkJbN68mRkzZvToOZxF/LYKg4q7mwZsttaKalmpwtzcQLD5KDabjEajoVjbeY8/gNqaamadP7Hb962rq2PfoSNsOlxIfl4u45OiiQjyoKHOyseffsa8yy4jq9xAdU4xXpGJxMcF8tZ/PmHi6I7X2DldY2Mj+w8dJSwytlsN1Y6oKCt2qKOI0DVnLP9+6vrCwkK7yVjb+33IyMigvLzcbnyS1Wpl69atvPbaaxiNRpRKJXV1dcyePRtvb28+//xz1Gp1m7Q6Ex8fT2BgINnZ2SJICUJ3FJXrkVSndb9WuWEwWGnyGQYKCGo+gSQ1IGs673QQExZIXUMjOu+uOxBs25nBf9d8w28un4uPVkVgeDQGk0zewVzqi3OZPfNCNFo3IkYNR6lSU19Vzr6SGvy8dYwemUZDQ0OnnSCyc3Jwc3PDbJXxdnCm6K7IsoxSHjyT6g42zuyC7uPj0+WM4TNmzODAgQN2+2644QZSUlJ46KGHUCqVGAwGZs2ahVarZc2aNV2WuNpTVFREVVVVt2ZUkWWZwsJCgoODHbpXR0THCWFQaTa1XVStyWdY67/LVBH4N2Yj2UydprOvQsHR4/ld3m/Xnv1UN4FPdBIb9h3He9gYSgty0cSmY2mqJyEpBbWPP3uO52MxNiFJEid2bqCqvAy5oZZvN37Ps6+9hdzJ8u8atZr1GzaxZdMGKisqusyTI0pKiomP6/nknsLA5O3tzYgRI+w2T09PAgICGDFiBAaDgYsvvpiGhgZWrlyJwWCgtLSU0tJSrKe1eaakpPD5558DLT0FH3jgAXbs2EF+fj4bN25k3rx5JCYmMmvWrC7zJMsyiYmJFBYWOvVZRUlKGFS8PDpf+k+hUFGsTSGmKZcStwQkZfvVG6FSFVWVZUDb6YxkWebt9z5Aq1ETkZhOaVkhMSMnovylLWfUBXM5/uNavJQytpCJ5FZWEjgsHWQwG5sJCI8iMcib4EB/dv68tzV4daS0sobLr/ytyxqm6+rqsDQa8PERQcpVnFnd5wx79uxh586dACQmJtody8vLIzY2FoCsrCz0ej0ASqWS/fv38+6771JbW0t4eDgXX3wxTz31VLeqoBUKBcOGDaOqqophw4Z1eX53iSAlDCoWS/cmjM2zRRHbnI3VO4JKW9uqkzJVJM/+9ycumHou7u6/Vk3U1dfz874s0iZcgEKhoKq6ksr6eoJO62yg9fQmdcYVlGduxVJbjlxdTNHxvRglNag00NzAsOCJ/G/rTmQ3L8aPG95hPjP27iMmPsmlPaeqyooZk+6auQWFFgNhWqTNmze3/nv69Omdlt5POf0cd3d3vv32217l4bnnnuOBBx5gxYoVjBjhnN85EaSEQaW2wYgsy13X/ysUVDdY8OqkaSrfYxRfbdnD1bOntO7Lys4jODYFgOPHDnNC30jQyMl217l5+VBdUgDN9RTl1VF2spDaspNMPmcSEjJuvsGs27iFwKAgrpw6himTJrW5t8FgYP+BQwSGRbV09jhZSL2+loTkNKcGLIPBgK+PawYFC8KZFi1aRGNjI6NGjUKj0eDu7m53vLq6usdpiiAlDCrFeUdQ1FUj+0R1el6k5TiVAanU0HFvJluzgX+8/jnf/biLuxfNo6y0GEOzzLAgqKmuIreiGl2s/fx2VouF/f/7EI1SQWDMMLSSCl8vD4wRYRiV7vgnjaHsyB7UvoHU19cxeWL7PQiz8wpITBuFVqvl2NHDJMVF0uihJuf4MZLamRDWETnHjhCg8yIuLtYp6QkdE0t1tFi+fLnT0xRBShhUCps8kLtRMvDw9O6wPeoUhZsPxb4TUJVWsXP7NsaeP5eQX7ro7j+wF13imDbXKFUq0i66CmNtJVpvHVovHQwfR1O9AXcvH07u3kThsQPEpo7mL0vu7LDEZzIaW+v5tVo33v/Ph0ydNo2EYcldPlt3lJWWEh8djr+/WMywL/Tn3H0DyfXXX+/0NIfCz0U4ixQauvdtU1Z3rwtss2ckWeoR7ClsbB3keuTQfqzeHS/joXX3wCcsuiVA/cLdywdDRSm+SjMTJk7iwT9c12m385HDUzh6MJMjhw5QVlJEUlISkkrrlKq+pqYm6msqRIDqQ2Jl3l/l5OTw6KOPcu2111JeXg7A2rVrOXTokEPpiZKUMGicOFnG3sJ6oP2xTXKTHsldh4+pmEb37s99JymUfF7oi+mNfzE2LR6Tuy+e4bE9zp+/1cD1t97crXM9PT2ZPHEcxl9KVGazmcyDRwGora6muqoMjUqNrFQRFd29vMiyTG52Fh4aJePHje5x/gWht7Zs2cKcOXM499xz2bp1K08//TTBwcHs27ePlStXdjkDe3tESUoYFOobGrnllW/R29oPUDZTIyFSGdFutUie/lTj26P0FSoN31TGUGVTOxSgGqrLuGJ62w4SXTlV5adWq/F013Jw3x4kaxPjRo1g5PBkhsWEcyL7CIZfugl3pK6ujuOH9jEqLYm01JQe50PoHQVSa7uUwxuDvyj18MMPs2zZMr777ju7Nc8uvPBCduzY4VCaoiQlDAr3//Mb9lZ2XoVndg9GL4U4/Fs90buI4PhLHbpWaTXh49PxCsHdkZaShNVqtavyc3d3J31EGnsPHMWng5nLDXo9+qoyJk0c1+5xwfUGQhf0geDAgQN8+OGHbfYHBwdTWVnpUJqiJCUMePuO5PLN4cYOj3sZy4nzbqZBG9yr+2Tp3dCXnHDoWoVXAO9/8lmv7g+02yZVW1uLj2/b9iWTycSxwweory0nfYRYZVfof76+vpSUlLTZv3fvXiIiIhxKU5SkhAHvlS/3YpTcOzwe5itRQJjDlSW+Tblce1EaEI27ruMOE53RuHuwdsP3NNRW88ebb+r1PG6nM5pMyDb7efdsNht5x49wzoSxHVwl9KWBNuNEf7nmmmt46KGHWLVqFZIkYbPZ+Omnn7j//vtZtGiRQ2mKICUMaLsPZrP+aAMoOq7qs1isDv8m22w2JifqCEnofUnknN/8AaPVxO79h5g4ynkzPISFhlKy/zBBISHU19dTUVwAssz4MY4vsCg4V8t6Ur2dYNZJmelHzzzzDLfffjtRUVFYrVbS0tKwWq1cd911PProow6lKYKUMGA1NTXz+PvbMXUQoGwWCwFyGU3ugQ6lrzVXMzG0mVFTpvcil7/y1LX0KCw1lDslvdP5+XiSd/wI7loNY7u5/Icg9DWNRsNbb73FY489xsGDB6mvr2fMmDG9mstPBClhQCqvquGu19aRUdHxxJYxci617lE04tjyFjOGaZl4vvPXyPHUOP/PKi42BsfX+hVcTXScsBcdHd26eGNvq75FxwlhwMk4lMNlS9ew8UT7A1slo56AukM011ViUvs6dA+bqZmoUMeu7Upts9kl6QoD16k2qd5uQ8HKlSsZMWIEbm5uuLm5MWLECP71r385nJ4oSQn9ymKxoFAoWPXVeqIjIziYX8mrGwopM3bcUSJcVU2lby86DDTVcNVIFaFJHc9O3hvlVjc+27yTQHc10yaJjg3C2ePxxx/npZde4o477mDy5JaJmbdv384999xDQUEBf/nLX3qcpghSQr+xWCxMWPwCsmcQ1eXFNPkmAxKS1HEnCR9TMQavzieX7YzNZuHyOAPp5853OI2uaLx0lDZIxHj1bKluYfCSfvmvt2kMditWrOCtt97i2muvbd13+eWXk56ezh133CGClDC4qFQqmjUBVJl14Kfr1p9oveyBp7kBlI4tPzHGp5rh55zv0LU9EWwzMG74lK5PFIYE0QW9hdlsZvz48W32jxs3Doul7ara3dEnbVJGo5HRo0cjSRKZmZmt+zdv3sy8efMICwvD09OT0aNH88EHH/RFloQBwq2HnQxsWl+kbizm1h6pqYaZ09Jx13V/Xj9HNFWWcP4o58xmLgwOok2qxe9//3tWrFjRZv+bb77JwoULHUqzT0pSDz74IOHh4ezbt89u/7Zt20hPT+ehhx4iJCSEr7/+mkWLFqHT6bj0UsempxEGj9KKKvTNtm5/VbLZbIQ3H6LW17Eu2NMiGvAOCnPo2u4yNtZxTrSOoEDHBgULwmC3cuVK1q9fzznnnAPAzp07KSgoYNGiRdx7772t57300kvdSs/lQWrt2rWsX7+e1atXs3btWrtjjzzyiN3nu+66i/Xr1/PZZ5+JIHUWePD1ddQr2p+Prn02ZK9QZGXH3dI702Dp/TIYdRUlFOdlE508goaaCuoMdTTV6wmPT0Kp1pDmIzN+xIRe30cYXCRJ6nVXa2fOUtJfDh48yNixLZ2FcnJyAAgMDCQwMJCDBw+2nteTZ3VpkCorK+Pmm2/miy++wMPDo1vX6PV6UlPFPGRDnSzLHDrZBJ2snHsmr6aTNPo6VhKKkEq5YGrbRQx7wma1Uph9jD217uTuPEiFZyzgDgRjziznHCmPOx65s1f3EAYn0SbV4vvvv3d6mi4LUrIss3jxYm699VbGjx9Pfn5+l9d88skn7N69mzfeeKPDc4xGI0ajsfWzwWBwRnaFPpZ34iQnG5U9+g1s9IwhwnSCCoUHkqJnpaLzU3V4Bjpe1WcoL+b44QMckBJR+GioOOP45FAVL9x0p1MWLRQE4Vc97jjx8MMPtxZtO9qOHj3K3//+d+rq6liyZEm30v3++++54YYbeOuttxg+vOPxK88++yw6na51OzWqWRhc3vx6FzZVz3voFdercbP27IvJ9IAiYoaP6vG9TtGfzGPr/hMcUqehUGnaHA+XannkN1NFgDqLiZV5XafHJan77ruPxYsXd3pOfHw8mzZtYvv27a2Lup0yfvx4Fi5cyLvvvtu6b8uWLVx22WW8/PLLXc6Uu2TJErvGN4PBIALVIFNaUcW6Q7V0tMJuZ2SVF+4YMXZ9KrIsI1vNpKUlofVwrMt6WfYhdhyvRu8T2+5xm9XCH6ZGEeDXk7Y1Yag5tXBhb9MQ2upxkAoKCiIoKKjL81599VWWLVvW+rm4uJhZs2bx8ccfM2nSryuYbt68mUsvvZTnn3+eW265pct0tVptm8AnDC6rNu6l2NjzAAWAuw8KSzG+NTsw+KZh03Q8b1+c7ThmSxMaz4sdulV9ZSnrDlUgBSZ0eE6QXMuFE6c5lL4gCF1zWZtUdHS03Wcvr5aXUkJCApGRkUBLFd+ll17KXXfdxYIFCygtLQVaZtL192+7yJswNOSUN/Xq+hLCwTucgJoDBIVHUo87FVb7kozG2oCkC0Jya/m9a9DXtM5S3l3Gxjpk35hOBxmbrNDU3IyHe8fTOAlDn+g44Tr9OsHsu+++S2NjI88++yxhYWGt25VXXtmf2RJcrKi6d0HqlCqfkRyt98PTWt/mmNZiQA6MQ+Mbxpc/HWHHTzvQlxX1KH19VQWWpo7bv5TmRq4cGYC7W+fL2gtnAWe0Rw2BIPXuu+/yzTfftH5+8MEH8fX1ZcqUKZw44eCq187KXFdiY2ORZZnRo0e37nvnnXda2g3O2DZv3txX2RL6QbneOUHqFKvVZPc5VConMECDQtVSUSCFJJGnjMTWzV/3jPWfs/W7DWyr8EDj3X6JXrZZuTTaxo1zzxsS41sEwRmeeeYZ3H+pVdi+fTv/+Mc/eOGFFwgMDOSee+5xKE0xd5/Qp+rqGyjRm2gZX+SkNPV6ZJ0FtWwkyFaGJjQCyT/C7hyVhw/H9mcy6aLwDtOxmE1s/WYN+R6pqDw6buuSjA1cFi1zz28da+sShh4FEopeFoV6e/1AUFhYSGJiIgBffPEFCxYs4JZbbuHcc89l+vTpDqUp1pMS+tTHGzLQ49yecCXqYQSZTuBjOIYuPgnlGQEKQKFQoHVzpzhrf7tpNOmr2btjB0VBk1B5dr6I4u9HeHD/dbNECUpoJbqgt/Dy8qKqqgqA9evXc9FFFwHg5uZGU5NjNSiiJCX0GYvFwtubsnGk63lnFCoVJ4kkNaAYo7bj2dQziUc6lM1VQRV4+v/aQ1WWZXZ8+yXHpWjcOi5oATDG08Clk89xXuaFIUF0nGhx0UUX8Yc//IExY8Zw7NgxLrnkEgAOHTpEbGysQ2mKkpTQZ1797waO1XVveqye8LJWMcq/Bu/QiE5LNwqFAikkiRPHj1JfVd66X5IkUkaPQxOa2PmNGmt5+IoJhAS4dhZ1QRis/vGPfzB58mQqKipYvXo1AQEtEy1nZGTYrTHVEyJICX1ClmU+2VWCJDn3V87fVk5qUhCmiBHUeXZRDPrFruZIasuKWz/XV5Swp7ARhaLjvMUra5gZCd9s+qnXeRaGnlODeXu7Oeq5555DkiTuvvvu1n3Nzc3cfvvtBAQE4OXlxYIFCygrK+s0HVmWefzxxwkLC8Pd3Z2ZM2dy/PjxbufD19eX1157jS+//JLZs2e37n/yySf585//3OPnAhGkhD6yduvP5NQ5dyxRsnspCUnh1Hv0bE4+i7GRopJyaksLObx9Cz8fzKXKrW07FrT80U7wquHl66fx2PVzufHqy52RdWGI6c82qVPznaanp9vtv+eee/jqq69YtWoVW7Zsobi4uMvhPS+88AKvvvoqr7/+Ojt37sTT05NZs2bR3Nzc7fz88MMP/O53v2PKlCmcPHkSgPfff58ff/yx5w+HCFJCH/kpqxKpk5JKT8W7VeAWnUS9e0iPr9V4+nDMLZWfdh9klyWWAk10h+dGyFU8u3gWvrqWzhSis4QwkNTX17Nw4ULeeust/Px+rYbW6/WsXLmSl156iQsvvJBx48bx9ttvs23bNnbs2NFuWrIss3z5ch599FHmzZtHeno67733HsXFxXzxxRfdys/q1auZNWsW7u7u7Nmzp3UycL1ezzPPPOPQM4ogJbhcaUUVX/zceTVDT9gsJgKCfTFpvHuVTpX/iE6r+ADOifNDre7+ciLC2UmBE6r7funyYzAY7LbTV3040+23387cuXOZOXOm3f6MjAzMZrPd/pSUFKKjo9m+fXu7aeXl5VFaWmp3jU6nY9KkSR1ec6Zly5bx+uuv89Zbb9n93Zx77rns2bOnW2mcSQQpweWe/s9WKizO6TChMNYyJtJMnU+MU9LrjGyzobZ1v5pDOHs5s7ovKirKbqWHZ599tt17fvTRR+zZs6fd46WlpWg0Gnx9fe32h4SEtE4/1941p87p7jVnysrKYtq0tnNZ6nQ6amtru5XGmUQXdMGlfsg4wup9daDo/dRBNpuFWHUJpqCZfTLsMdhWza1XXtYHdxKEXxUWFuLj8+tYvfYm1C4sLOSuu+7iu+++w20ATcsVGhpKdnZ2m+7mP/74I/Hx8Q6lKUpSgsscyy1kyfu7sfQyQHkYSxgbVMuoGAm3kRc6KXddm5Ua2GV1oCBAy4vUGRuAj4+P3dZekMrIyKC8vJyxY8eiUqlQqVRs2bKFV199FZVKRUhICCaTqU3ppaysjNDQ0Haf4dT+M3sAdnbNmW6++Wbuuusudu7ciSRJFBcX88EHH3D//fdz2223dSuNM4mSlOASWXlFXP3XjZQYe1fNZ7NYSEoMosm3pXqvr7otaIx6Lj9nUtcnCgK0Lvja2zS6a8aMGRw4cMBu3w033EBKSgoPPfQQUVFRqNVqNm7cyIIFC4CWqriCggImT57cbppxcXGEhoaycePG1jlWDQYDO3fu7HaAefjhh7HZbMyYMYPGxkamTZuGVqvl/vvv54477uj2851OBCnB6QqKy7n+5U29DlAA6f41NPuk9/msZudGaQkJDOjjuwpC93h7ezNixAi7fZ6engQEBLTuv+mmm7j33nvx9/fHx8eHO+64g8mTJ3POOb/OmJKSksKzzz7LFVdc0TrOatmyZQwbNoy4uDgee+wxwsPDmT9/frfyJUkSf/7zn3nggQfIzs6mvr6etLS01qWaHCGClOBUsizz6NubyK3vXRWfzWYjUlGMIijeqV3Xu0MyN3L5WMfqz4WzkzNW2nD2F7GXX34ZhULBggULMBqNzJo1i3/+859252RlZaHX61s/P/jggzQ0NHDLLbdQW1vLeeedx7p163rc7qXRaEhLS3PKc0iyLMtOSamfGAwGdDoder3errFR6B/fbN3D4pVHkZSOf/+xmZoZEaRHDooHd1/nZa6b0jRVrLhdDNod7Pri3XDqHm9uPoy7V++GRDTV13HL9LRB9y678soreeedd/Dx8elysPBnn33W4/RFSUpwmkM5Bfzl00NIyrYNvT0RpKzCFjAMqR8ClI9Vz0PzRVuU0HNn6zBvnU7X2p6m0zl3hQMQQUpwksKScv70zy3k1fcsQNksFhQqFTZLM6DA01JFiJ8V2bN/JnGN87QQG9HzWSwE4Wz19ttvAy1V/U8++SRBQUGtCx86gwhSQq/t2JfFLa9vo9To2aPrQmyFREQFIMvNmFVakJRIqkgsGud/G+sOd3MdN1+a3vWJgnAGZ6wHNdhn3JJlmcTERA4dOsSwYcOclq4IUoLDGpuaeGLlej7KqMUodS9AKUx60vwNWGQJ96Aomrzbn9i1r2lNem4/N5yRw2L7OyvCINTXXdAHIoVCwbBhw6iqqhJBSuhfsizz3U+Z/O2rQ+yt0IDUvaK9m7matEQdTbo0JGBATDhkbuZ3KSoumTSBiJCgrs8XBKFDzz33HA888AArVqxo00XeUSJICd22fvsBXv/fQXLL6zlp9ERSaHp0fZhWT5NupIty13NyQw3zkty5+fLz+zsrwiB3+owRvUljsFu0aBGNjY2MGjUKjUbTpm2qurq6x2mKICV0y3c/ZnDbOweps7kDOnqydqG2sYhYXxu6qATqXJbD7tM0VTEz3pObLpqCj7dzl7IXzk6iuq/F8uXLnZ6mCFJCp97/Zhubf84i/0gGBs0EpB7+xgzTFOAZHUGzdyR1/TwPnofFwO/Tdcw5Zzp+usEzDkUQBovrr7/e6WmKICV06H8bfuCF1fspIwg8pvV4HIhbwwm0iSkY3f37fQxJmpueO2eNIDW+4wUOBcFRA3HGif5QUFDQ6fHo6J7//YkgJbTLYrHw7n9X4e89krIe1tHZbBZAQUqkO81ufv3+xycZG/i/y4eLACW4jKjuaxEbG9vpc1it1h6nKYKU0EaN3sCdT71BpXsiR+p6NmbJZqxndGgj5sYGmkInohgAf3gTQ2B4gusXSRSEs93evXvtPpvNZvbu3ctLL73E008/7VCaIkgJdpqamrnr7//j2+qev9RtNhvpAQbMkROAgdNbaWpiYH9nQRjiRO++FqNGjWqzb/z48YSHh/PXv/61y7n92iOClNCqobGReY/+l/21PZwos76YEHcr4SGeNPmn9Xv13ukUTTWclz5wur0LQ5Oo7utccnIyu3fvduhaEaQE4JclNt5c2+MApbNVEhvrTnPgMJrV2gEVoACCtDbRk09wOdFxooXBYLD7LMsyJSUlLF261OFZKESQOss1NjaScfA4b60/wtpserR2k81iISpEwhQ2YsBWVViaBsLILEE4O/j6+rYpEcqyTFRUFB999JFDaYogdRb79+dbWPrZUZqUOiSFonsDdI0NxLqVYrNa0WoVWMJ63jW9L9WcyOrvLAhnATHBbIvvv//e7rNCoSAoKIjExERUKsfCjQhSZ6nvtu/nsS9PYFZ3v4u4ZKpjTKSFptBpyDYrss064OvRFTFjMJvNqNXq/s6KMIQpkFD08utab68fCM4/3/lTjIkgdRaqqqnliY/3YVZ0Y0noJgOJnmXUNUvExEdQ55cCgKRQIimULs5p75nd/Mk8msOEkSn9nRVBGJLWrFnDnDlzUKvVrFmzptNzvby8SElJITw8vNvpiyB1FvrbR1vJNnS9OGGyezFSTDSSTyp+skzdAC81tUc2N7F1+y4RpASXOpur++bPn09paSnBwcHMnz+/y/OVSiUvvPAC99xzT7fSH6jt3YKTmc1mavQGLnlgJf/a2XlnApvFxEjvUtTRKUg+LavUDvRqvY64STZ2ndCz7ed9/Z0VYQiTnPTfYGSz2QgODm79d2dbc3Mzb731Fi+88EK30xclqSFMlmWqqmspLqvgL+//QEmjmuN13l1+NRkdrMcUMhJJ1bOlOAYajbmONM9GlCp3Pl3/Iz9lHiE5OoTZ089FoxnczyYIg5FGo2HBggXs37+/29eIIDVEHTx+grte/568KjN1Ni2Sqnvjn2w2GxpPH8yDPEABKEoOUYWeQo8k0Prjf7KOXTkH+Pf3Rxgb5c2cKWOYMNo5C7MJZ7ezubrvTMePH+f777+nvLwcm81md+zxxx/H29ubl156qdvpiSA1xJSUV/HWVzv59OcKSo0eoKDbaz/JTTVMjFdT750wSCse7DVFjKdAUiApFMg2K1VSMO7mYzQHJLOpooy9q7Zyj9nGtAnp/Z1VYZCTnNC7b7BW953urbfe4rbbbiMwMJDQ0FC7ZgJJknj88cd7nKYIUkOELMv8+8sfeHltNuVmL6B7S7qfLpgy6v3OR1IOjV+L05/jVE/E5oBkAGSfEKoJ4Y0vv2fq+JGDts1NEAaSZcuW8fTTT/PQQw85LU3RcWKIePT1r3j4i6JfAlTPuTeewD911JAJUB1xaygloHBr6+cTtgAKT5b0Y46EoeBUdV9vt8GupqaG3/zmN05NUwSpQU6WZf72n2/51446JIVjASZUKiclzg+F99CfLdxUX0tKxK/POT7ah6iIsH7MkTAUiCDV4je/+Q3r1693appD+2vzEGc2m7nnlc/5+KAVSenYjAppXhW4hUTQ5BHs5Nz1LblJj7/KTKCnhlAfDeE6d3TuKtzUSlZt3cdJdQQKNy8SIkNoclNBHUhlRxk1MVJU9Qm95owu5EOhTSoxMZHHHnuMHTt2MHLkyDYzvdx55509TlOSZVl2VgY7YjQamTRpEvv27WPv3r2MHj26zTnZ2dmMGTMGpVJJbW1tt9M2GAzodDr0ej0+PmfHbNd1dXV8//NR/rXhGNuLVQ69ZG02G6leFWiihmHR9HBpjgHCw6xnapQ742L9GJUQSWhw+yXBxsZGlr/9Cf/7+RjqiDTOCbRwpKCMu6+ZzfSJbde/EYaGvng3nLrH57ty8fTq3d9RQ30dV0yMH9Tvsri4uA6PSZJEbm5uj9Psk5LUgw8+SHh4OPv2tT+g0mw2c+211zJ16lS2bdvWF1katCwWC7e8+AUbCtRIktrhKoI4ZQFEj8ei7nrmiYHEZjKS5t3MtGEBzBxzDiGB/l1e4+HhwSO3L+ZBi4WSsgqaTGaS4sRS8oLzKKSWrbdpDHZ5eXlOT9PlQWrt2rWsX7+e1atXs3bt2nbPefTRR0lJSWHGjBkiSJ0mv7AEk9lMUnzLC9VoNPHoG1+xoUDjUOkp2JSHEsBmRJc2EvNgClDmZsb7m1kwIZYpoxyb4kilUon2J8ElRHWf67g0SJWVlXHzzTfzxRdf4OHh0e45mzZtYtWqVWRmZvLZZ591mabRaMRoNLZ+PnORrcFsz8HjaNUSVbUN/HC4mH99f4JL0gNIisolu8TA5sMVlJq9HG5DsclKcpr8SA+ow+w5ONqgZJuNYRo9i89PYOrY1P7OjiAMCCtWrGDFihXk5+cDMHz4cB5//HHmzJlDfn5+h9Vun3zySYe97xYvXsy7775rt2/WrFmsW7eu07zce++9PPXUU3h6enLvvfd2em5PBvGe4rIgJcsyixcv5tZbb2X8+PGtP8zTVVVVsXjxYv7zn/90uw722Wef5cknn3RybvvfvqO5XP+PbZQ2KEGpbglEKn9WHZbhcPkvZ3k7VL1nNTcRJZdQaW4ZO1VfW0U35j/vd4G2Wq4dE8SV0y9B0YPFGAWhr/X1jBORkZE899xzDBs2DFmWeffdd5k3bx579+4lJSWFkhL7YRVvvvkmf/3rX5kzZ06n6c6ePZu333679bNW23Vty969ezGbza3/7oijX657HKQefvhhnn/++U7POXLkCOvXr6euro4lS5Z0eN7NN9/Mddddx7Rp07p9/yVLlthFa4PBQFRUVLevH6j+umoXZUZ3JAe+NthsNpQNpcjeLdPfhzcfo9zmjcUjjHBLPg0mOGoKRJIkgjWNeEXEOzn3zuVh1nNJoifXXzwdHy/P/s6OIHSpZfn43lb3dd9ll11m9/npp59mxYoV7Nixg+HDhxMaGmp3/PPPP+fqq6/Gy6vzcZRarbbNtV05faHDMxc9dIYevxLvu+8+Fi9e3Ok58fHxbNq0ie3bt7eJxOPHj2fhwoW8++67bNq0iTVr1vDiiy8CLaUvm82GSqXizTff5MYbb2yTtlar7VZ0H0z++v63fJ9jBEUPZ4loriWEKixWmSZJS6BcCLJMvsmPSLc65KYsCoz+NOGGJIEs2wh1M+AWOdY1D9JLKlM9F8Wquf7CSYQFBfR3dgShX5zZhNHVO89qtbJq1SoaGhqYPHlym+MZGRlkZmbyj3/8o8t7b968meDgYPz8/LjwwgtZtmwZAQH9+7fosi7oBQUFdj/s4uJiZs2axaeffsqkSZOIjIzkyJEjWK3W1nO+/PJLnn/+ebZt20ZERAR+fn5d3mewd0HffySbq1/6gWprz0sMwfp9ZNtikbo5OV+0qpjgSdMHXNWZLMukamu4e84oUuNFrzvBOfqyC/r/MvLw9OrdPRrqDVwyrm1b0hNPPMHSpUvb7D9w4ACTJ0+mubkZLy8vPvzwQy655JI25/3pT39i8+bNHD58uNP7f/TRR3h4eBAXF0dOTg6PPPIIXl5ebN++HaWy/xY4dVmbVHS0/cvmVDEzISGByMhIAFJT7RvCf/75ZxQKBSNGDP2ZqWVZ5p2vfuDZr/KpdSBAKWpPUKUKRZK7F3D8VQ0EJSUNuAClMtdz5TAtf7xsDiqVGFsuDE7O7N1XWFhoF1Q7KkUlJyeTmZmJXq/n008/5frrr2fLli2kpaW1ntPU1MSHH37IY4891uX9r7nmmtZ/jxw5kvT0dBISEti8eTMzZsxw9LF6TbwV+oEsy7z47v94YbMBqTtLuJ/GZrMRYTxOuaylxuze7cbWYFUNkt8YB3LrOtEKPfdclszY1IT+zoogDBg+Pj7dKvlpNBoSExMBGDduHLt37+aVV17hjTfeaD3n008/pbGxkUWLFvU4H/Hx8QQGBpKdnX12BKnY2Fi6qllcvHhxl+1dg53RaGT2df/HUVU6alMdYZIBswzF3mkoVF0HLP/6I2RZIpAUyh59bztSH8TIoqN4RKd1fXIfGK6tZtl15+PvO/iqaAXhTANhPSmbzWY3PAdg5cqVXH755QQFBfU4vaKiIqqqqggL69+xhQOr7ucsoNVqWf/RP/EpzcSQf4LDefUcyzPgcWxDt6738dG1LjvRE2pbEyq/nvXacZVRHrW8dNPFIkAJQ4bkpK27lixZwtatW8nPz+fAgQMsWbKEzZs3s3DhwtZzsrOz2bp1K3/4wx/aTSMlJYXPP/8cgPr6eh544AF27NhBfn4+GzduZN68eSQmJjJr1qwe5Mz5RHVfHyosPMl1dzyHt28QJ/Ta1g4PkqSgGS/cyzNpCh7daRpms7XT4x1RKyVkm2PXOlO0spa/XDsNtyHWQ1M4uymQUPSyKNSTRRPLy8tZtGgRJSUl6HQ60tPT+fbbb7noootaz/n3v/9NZGQkF198cbtpZGVlodfrAVAqlezfv593332X2tpawsPDufjii3nqqaf6vTe1CFJ95HjuCd5ftY7s/CJqJblNj7w6owL3yhNYvaJQeth3+bSam5BsFiJsJznWFORQ+TfQ3YZW1/MivzPJpiYWnuOHr8/gnNBWEAaKlStXdnnOM888wzPPPNPh8dObX9zd3fn222+dkjdnE0GqD2TnFfCbO/5OVnEzM0en8eOBSppt9lPYqyUzlpDkNgEqxJRPXbMNL6n5l7Yox2povQbAFBOSxp16U3/nQhCcr6fVdR2lIbQlgpSLybLMH5a8TlZxMwA5xY2MiPfj5+x6u/PcVDImj1AkwGpsIkIqQQLyGnwwS1rK6F3Dqs1iwZy9G0VAJEq//mkIlcyNxEd0PJW/IAxaIkq5jAhSLvbaylXsOFqDJLV0dsgtbSQ2xL5Y4+8B/t5KlOpalLY6zJKN442/VM056Rc3qzEIGmG8VAz9FKQuipIYm5bYL/cWBGFwEkHKxarrTa0BCgCFiv15ek41LAV6S6j8AslWRkJ9+2k4k6mhsV8ml9Wa9Nw0c1I/3FkQXE8s1eE6Iki5iNVq5bvvf6KgpMZuvyRJVDX8+svo763mmDKyz/KlcXfHWlWEZDGiCOm7QbSTI7WEivn4hKHKCeOkRIxqnwhSLlBcWs5z//yEf391gJQgMwmBHmRX2Nr06JNlGw19/L+guMaGZ30RPl4aCOm7+6aFijFRgiD0nAhSTrbvwBEWL/kXR08aATWHKtRMSHBjoq+C3dmNdueG+VgoVCf06YjqYqMPGCFeakRXfAxJqULVoMeiC0YVEOGy+2rVYty4MHSJfhOuI4KUEy17+V3e+nwX3h723ct3ZTcRrKkG7Ku7vL08UCj6539Bbp0HyhoDGpWSJtyZYKsAFwapumaLy9IWhH4nopTLiCDlJAePHOd4bgFlBiivs38hS5JEhbmd9hhN/47ktqq8aPrl34ZGCzoX3qvO2P+zXQiCMPiIOpheslqt5OadYNEDK1i1NZ9Yr+puX1tdWorN3OzC3HVfoV5BU8VJl6XfbBJBShi6JCf9J7QlglQvlJaWcc3tz5A272m01hpsqClu7P6UP4GBASjUA2AqCKARD9zqyl2WvtHqkrU1BWFAODULem83oS1R3eegI8dyuXfZv/l+fw1qpQKNmweSQsLczXdxYqiKUmlgdcm2WWy4av1NGRGkhKFLNEm5jihJOeCf73zBRTe+SKC3EkmSkCUorWrq+sLTyCoVevXAWDrjlEOlEvKJ/Q5fbzWbaaouxWaztTnm5ya+DwmC0HPizdFDn3z2NU/8cy31ZjWVtU2oZCMWtBTU9exHqRwAy2acqVnyIK+gnKjgOtTu3thsNmy5GZibLWh9vFFEj7A731JbirngOA1WN6w2CdlqotCgIFaXi5+PBpQSVndP0IUyLKTvBiwLQp8TRSmXEUGqBw4ePsYjf19Hvbmli3llbROJoSqOlvU8LX29mQBlMVWqcCfnsncqCUZ3+AAatYbqBjOlJm8khYqU5mJ8on89z1xXQ8Ph7RyzptonoIW85pYNAGszyZ6ZnP9w+2vaCMJQIKZFch0RpLrp4OHjzLzpZfTNv7baFFY04+duRpY9kXrY6llmgAT3KgxWN8xaf2dnt1dyGn/Nz6lJMjy9PVv3WUpzqS4oI9+S3GVjr6zQcMu8c1Cr1Z2fKAiC0A7RJtUNjY1N/PGRf9gFKAC9WUu+wavHAeqUnDIL0XIJUZVbsRkbnJFVl1EoW4KMsbYC/clyThj92kzzdCZZlrl6lBu3XX1hX2RREPqN6N3nOqIk1Q23P/ZP9pxwzYwJOSUmogO8UWg9uz65HxVWmgm17aSiykKxpeteibLNwk2TdSy/d4HDQVwQBgvRJOU6Ikh14eU3P+ajjdkguaZztizLaN00LknbmUrNOkp70PZ2fqzEaw/+VgQoQRB6RQSpTvxz5Uc89eb3ILmuPSUuwEiWcuSQqndN8rOy9PqpIkAJZw9RlHIZEaQ68OrK1Xz3/U5MNtf+5jQYleA9dH47ZZuVB+YlMXlMatcnC8IQIXr3uc5Q+gLvNIezcnjxva14+/hic/FECeX1ChIbMl17kz40IczCwsvO7+9sCIIwRIgg1Q4PdzeC/dzYur+Mc9MCkWWZSD8F4Z7O74EnSUpqG2VszYY2x2w2C4nN+4g3Hur4epMeyaR3er4cNX9KoqjmE846onef64jqvjNs3LKTJS9+yOL557L7QB7eWhsNhmpQa6ksq0KWPZz+Eq5vsqLytXBqMiGbzUZwczaK+hqO16tJiWq/Y4XWVEWosQh3T3eOunShje4JdWvm93PG93c2BKHPiSYp1xFB6jRV1TX839MfkV9h5fnXPyciLIi0uCCyy23UmZrw1nghYQMnT8NqkrXEmgpRU4pNlqmra6LMAJJCgySB0WhEkvXIml8Dkc1mIdJykpxKG35NDcT6Z5OvSnRqvnpqRJQ3wYEDa2CyIPQJEaVcRlT3nebr73aQX2EGoNISwL5CGzv2HCY+WEmEn4I6k9plXdHzK20cLzaSU2KivF6JpPj1PvkVMiF1uQQ157bui7XlkV3aMnarpgGqy/W4NRS4JG/d9WN2A3/556p+zYMgCEOLCFK/kGWZtz/7sfWzhgZCNFVICgWZhZAY1I+ZA0oNoJRagpLNZkPZ3GhX7WgwKgg0VfRX9gAYGa7mxvlT+zUPgtAfxKKHriOq+37x444MdmVVgdTyIzHhSZnJE0wANiqra5Bl7y6nAnIlY3UtIdJWtF5e5JbZ7EpbCaFqDCqffssbwPmpQUSGD6zlRwShLzij44PoONE+EaR+sWbtZmTJ/sfhrjSBpREfjZnDlV3PVedqNc1qQA1N2AUoAJW7OxVEt39hH5BtVjQq8VcmCIJziSAFZB3PYcVXx4CWXnRB7s14qEwo1W7kVOloNMn9HqA6o5SsVBoVoO2/PCwa78ajN1/WfxkQhH4k+k24zsB98/ahI9mFKLAyJdmTqYkywT4SVquV5kYDKsk0oAMUQHSQliptXL/dP9bbyIt3XSnGRwlnL8lJWzetWLGC9PR0fHx88PHxYfLkyaxdu7b1+PTp05EkyW679dZbO01TlmUef/xxwsLCcHd3Z+bMmRw/frz7mXKRgf32dbHaWgOvvPUxGQdyefIPUzE02fghW+JQmZbCBl8MJg3W/iyedIMs22hW9t8Etf7mQmaNDMDH26vf8iAIZ5vIyEiee+45MjIy+Pnnn7nwwguZN28ehw79OvD/5ptvpqSkpHV74YUXOk3zhRde4NVXX+X1119n586deHp6MmvWLJqbmzu9ztXO2uq+PfsPc80f/0JhcyAA5yZ7kHuyhlGRWlQKqKqpp7hxYC+fARDtZ+OEJqHfvm0sGKvj5fuu7qe7C8LA0Ndz9112mX3V+tNPP82KFSvYsWMHw4cPB8DDw4PQ0O51ZJJlmeXLl/Poo48yb948AN577z1CQkL44osvuOaaa7qdN2c7K0tSZrOZp5Z/iJvShCy3TM5nk9QkhXuyv9BKRoFEfp03JouLJ+7rJYVsoUIVhELRP9814n3M3HztPFHNJ5z1nDktksFgsNuMRmOn97ZarXz00Uc0NDQwefLk1v0ffPABgYGBjBgxgiVLltDY2NhhGnl5eZSWljJz5szWfTqdjkmTJrF9+/be/XB66awsST327Ap+M3catovHcc9fv8BkkbGaNASHhPC3BcMpq9KzY88RSgqyOVYX0t/Z7VBkgIIC79h+uXdqgJUbp/gzMiW+X+4vCENVVFSU3ecnnniCpUuXtjnvwIEDTJ48mebmZry8vPj8889JS0sD4LrrriMmJobw8HD279/PQw89RFZWFp999lm79ywtLQUgJMT+fRcSEtJ6rL+clUHqvj8tJCgwgPr6Bo4VlJMUF8XwYTEcO1FKWUUNR44cYcv+CmRF8IAeuyD1UwkKoKyimqf/c4DcGpkb5oxjZGr/TskkCP3Jmb37CgsL8fH5dcyjVtt+u3hycjKZmZno9Xo+/fRTrr/+erZs2UJaWhq33HJL63kjR44kLCyMGTNmkJOTQ0JCQi9z2rfOyiDl7eXJS298zKGsPPy8taz8fAf7jn1Bk1XTUv0n25CUbgO+S6jJbENrrsGo9uvze1crgggN8cZmbOSuZ/7NG0/czLDE/uthKAj9yolR6lSPva5oNBoSE1u+HI4bN47du3fzyiuv8MYbb7Q5d9KkSQBkZ2e3G6ROtV2VlZURFhbWur+srIzRo0f39Emc6qwLUrIsc+nix/gpqwlsFmRJ+UubSksPOUmSXDY/n7PVNVmR3BqwKXUoFH3bvOghGTk/uIKM/Y00mSFITCwrnMUGwqKHNputw/arzMxMALsAdLq4uDhCQ0PZuHFja1AyGAzs3LmT2267rVf56i2Xv9mMRiOjR49GkqTWH9Qpsizz4osvkpSUhFarJSIigqefftql+ZFlmWNFv6zdpFAhSRKeGhs+UrVL7+sSkkSgsYyohr19ettYbRXnRzWzvjiQ6lo9/iERnCwt79M8CMLZbMmSJWzdupX8/HwOHDjAkiVL2Lx5MwsXLiQnJ4ennnqKjIwM8vPzWbNmDYsWLWLatGmkp6e3ppGSksLnn38OtHw5v/vuu1m2bBlr1qzhwIEDLFq0iPDwcObPn99PT9nC5SWpBx98kPDwcPbt29fm2F133cX69et58cUXGTlyJNXV1VRXuzZYNDc3o1L+GptlWWZcrIqtR33sQ7ZsaZ3Hb6CqNyqoN0JceN+Mk5KtZpJ8TUxJjsDf14f5F/igVafz20um9cn9BWHAcsaihT24vry8nEWLFlFSUoJOpyM9PZ1vv/2Wiy66iMLCQjZs2MDy5ctpaGggKiqKBQsW8Oijj9qlkZWVhV7/64KpDz74IA0NDdxyyy3U1tZy3nnnsW7dOtzc3Hr5YL0jyaf6YLvA2rVruffee1m9ejXDhw9n7969rUXJI0eOkJ6ezsGDB0lOTnb4HgaDAZ1Oh16v71Y9LsDCu/7GZ1vzABgV68nUMTEcPVFNVflJ9hYpGRYsUauvo8I4OAaoJoZKZLuPdln66UEWbpmVwrikYEYNTxFdzoVBwZF3g6P32Jtdird37+5RV2dgTGKoS/M7GLmsqFBWVsbNN9/MF198gYeHR5vjX331FfHx8Xz99dfMnj0bWZaZOXMmL7zwAv7+HbdvGI1Gu3pXg6Htsutd8VBbSQpVsWjeOQT7e/OPj34gp7CKQE8L88aHkltmGjQBSrZZKco/jhwbg+Tu/A4Uk8KtfPP87/H0bPv/UBAEwdVcEqRkWWbx4sXceuutjB8/nvz8/Dbn5ObmcuLECVatWsV7772H1Wrlnnvu4aqrrmLTpk0dpv3ss8/y5JNP9ip/Tz1wA6EhQciyzJU3Pcq+vHrCPUzEB7vzxW7DoCopSAol4dFJ5KsUrcvPO0uQm5F/PzhfBChB6IqYYdZletRx4uGHH24zaeGZ29GjR/n73/9OXV0dS5Ys6TCtUz1R3nvvPaZOncr06dNZuXIl33//PVlZWR1et2TJEvR6fetWWFjYk0cAIDSkZQXDA4ePU11VyUUj3YnzN5FbNDgb/3PLFUTVH3Z6ujdPDSY+Otzp6QrCUCMWPXSdHpWk7rvvPhYvXtzpOfHx8WzatInt27e3GYQ2fvx4Fi5cyLvvvktYWBgqlYqkpKTW46mpqQAUFBR02E6l1Wo7HNzWUzofL1b/+1k8Pdz508MvseNk4aAqRZ3OZLE6NT1ZtpEYLRYwFAShf/UoSAUFBREU1PU66q+++irLli1r/VxcXMysWbP4+OOPWweVnXvuuVgsFrsR0MeOHQMgJiamJ9lyWExUOFu3/cw9z33MoYJGJAd68yWHu6FUKsgtrqPZ2o/jq6yN2Gw2p42XClbVcdn5o52SliAMdWJlXtdxSZtUdLT9CrFeXi2dEBISEoiMjARg5syZjB07lhtvvJHly5djs9m4/fbbueiii+xKV66WGBdJXX2jQyWo9DhvVr16J9GRYeTlF/LP/3zLf9buo7ax7yemrWn2wq32KCb/tF6nFevZyNv3XdL6/00QhM6JJinX6beBQAqFgq+++oo77riDadOm4enpyZw5c/jb3/7Wp/kIDwvl7WdvYu+hPPYdOYFaoyY82I+svFIOZpegr2+muLb9lXmvvWQ80ZEtI7jjYqP466N/4PdXHOf3D77FseKOZxx2hWbZnSRvONaLNDSYuOX8YJb+4VrRWUIQhAHBpeOk+oKrx0LIssx3m7ezacdhKmubqG9o4vyJKegNDfz20vOIi41qc01ufhHX3beCfbn6dlJ0naQoN46pUh26Vm1rYsUfRrPw0vOcnCtB6B99OU5qf16ZU8ZJpceFiHFSZxjYUyoMAJIkcfEFU7j4gindviY8NJBJw8P6PEhZLBaH/o8m+jTx7v2zGTtCzGQuCI4YCHP3DVUiSLlAdl4Rh7KL7XdajYS7VeETGIWfny9H8quodWKNoEZpoc7Ss+mR/DUm7rs0nusvmUSAv6/zMiMIZxkJJ3SccEpOhp6zcmVeVxuRmsizDywkNULLgmkxTErU8v7T13LuuecyPlHHpg+eZOfHf+b89GCn3TPCV6Zc27OlMv66MI17fzdLBChBEAYsUZJykQljhrN99TNoNBoMhjp0Oh+uuuzC1uPRkWGsfO6PTLnmacoNNrxURuotjo//yqtSMywih2xGdut8WZYxWZw9R4UgnJ1E7z7XESUpF9JqtRzJOt7h8YiwEBZeMhYvUz6L5yTTmz4saoUFk+Te5Xmt95Ct5J844fD9BEH41alxUr3dhLZEkHKxtJQkdLqOe+r84eoLSR4Wy82LFhDmbXb4PjZZwtqsx2bruHTkJjcSbztKsmk3b/wuhkf/73cO308QBKEviOq+fvb+Zxto0Fdw4fXPU9mgdvjblFVWUlRhI44MTnhPaPccI2o0vpE8eNVorrtsuuOZFgThDKLCz1VEkGpHY2Mjtfo6wsNCXH6vGeeO5tsf9rF80UV8tn4XsqSktkli18ETXHV+HCp3f46dKMdktnEot5IGc8eFX19NI3XYL3OisdZx28wo6hrNWJr0vLH0bhc/kSCcfcS0SK4jglQ7PDw8qK/vmxkjzjtnLEvvMvHq6+8wJj2Fo3kVhPu6c82MZGZPH8tlc2a2nnvwSDa/uXsF+eXGNukEeRipaPTCq6YGm6YOdzcto0PgynFh3HnTgj55FkEQBGcTQaoDwcGBfXaviy84h5BAX1KS4jAajR2ONh+RmkhanD/F5XkYrQokZcu4KH9PBQneBppM3lx67jBmTkvlZHUDD/7hyj57BkE4m4nKPtcRQcqFMjIPEBURxt79R7n4wnM7ncR21MgUgC6XIfnnX27By9ODnLwivt++H3+dO8GB/lw0/Rz0egO+vrpBu9yIIAxWorrPdUSQcpFHnn6Nlz85gK+nkpoGGynhn/LMfb/hkpnndut6q9WKUtl26Y+Q4JalUtJHJJM+wn7NLT8/317nWxAEYSARXdCdSJZl7ntiOQVFJfyQeRIUav6/vXsPavLq8wD+TSABlJvciij3UC6vgogub2gXKSiE913kFbdva3Hxglrbjnbs1O3grGuLWqk6Mh2nizqNrLO1nS0UrNZBR9SILsgqxdGllArlYoRAhebCrQg5+4dDaiSEQhJ4wN9nJjNwnifnnF8Okx/nyclzlH188PjWqFMM4j9Olz65v54RHR2/4ET+V9jy3j7cb2icpJ4TQkxBO/NaDiUpM+LxeHC0d0DHoy5Y8UbulFv6fRv+q+C80Trc3d3g4e6KvyUvg8982rqdkGmBZ6YHGYGSlJnt2ZmJJYv+hFXLF4Mx/S/W8vjW2Jl7Af+afRTAk5lX2fX/0T+Hx8Pf/ikRKZK4MT+fIoRwA+Uoy6EkZSHbNv0dvq76L68Q/bAT8iE9V4O/vP4OAMDHe/5UdI8QQqYFWjhhIXw+H+EhPmgpb9GVpb7kg8G+LvCsHWHNe4yblbeg6u6Dn5/vFPaUEGIqWt1nOTSTsoDT/12IGze/x817cl3ZfKdB1NxvxqM+W8T9459hP9sO35w5D8nyZVPYU0KIOdDCCcuhmZQF1De1Y9PHlwC+QFfWruyHnGcPdHTjQds5RAS9AEVXN5pbHsLXZ94U9pYQQriLZlJm1tn5K5ZEhMBOoF/+mGev+7lJaYtvb6nwv/U9uHLtxiT3kBBidrRywmJoJmVGivZfEP8v+9Ch/A08K2tg5Cp0HaYdQrjbrwgW+U1a/wghlkG3RbIcSlJmtDM7D42/DGG0l5Vph8DHENz5cmgHe/HX5Slg9KdJCCGjoiRlorIbFYh9WYzOzi5otU/uJsEYA9gQePzfX95IP1v8JTYMYaJ5SIgV48EDOebN84K9/eyp6johxExodZ/l0GdSJvqHJZEAgIbmVjT9MgD+oAZLfIG/RjkjKdIVIg8rbJAEoOQ//x3/tmMj0lKS4OTkiAULwjBnjjMEAsEYLRBCuM8cK/v+eJbKy8tDeHg4HB0d4ejoCLFYjJKSEgBAV1cXtm3bhuDgYNjZ2cHHxwfbt2+HSqUyWuf69evB4/H0HhKJxJQXxSxoJjVB/1dTiy6lGj/db4K8Q4m8ou8xMKBFqKMCwfMWYeO6v+Ol6MVgjNFdyQkhZjV//nzk5OQgKCgIjDGcOnUKqampqK6uBmMMra2tOHz4MMLCwtDc3IytW7eitbUVhYWFRuuVSCTIz8/X/c6Fu95QkpqgBX8KxeVr5Whp/xUXbtRC1W8NP9tWPIYN/nmVBC9FLwYASlCEPAcm+3JfSkqK3u/79+9HXl4ebt68iczMTHzzzTe6Y4GBgdi/fz/Wrl2LwcFBWFuP/rZvY2MDT0/PcffdkihJmSA+Voz4WDEiwy6hpqEN8eJw/HlpBPh8uopKCJkYtVqt97uNjY3RGc3Q0BAKCgrQ09MDsVhs8ByVSgVHR0ejCQoAZDIZPDw8MGfOHMTHx2Pfvn1wdXUdfxBmREnKBMOzpFUpiVg1xX0hhEwdc86kvL299cr37NmDDz/8cMT59+7dg1gsRn9/P+zt7VFcXIywsLAR5z169Ah79+7Fli1bjLYvkUiQlpYGf39/NDQ0YNeuXUhOTkZFRYXBve0mC48xxqasdTNQq9VwcnLS/adACCHA5Lw3DLfRrOgyuQ21Wg1fTxc8ePBAr67RZlIDAwNoaWmBSqVCYWEhPv/8c1y7dk0vUanVaqxYsQIuLi44e/bsuBZq/fzzzwgMDERpaSkSEhJMis0UdF2KEEJMZM579w2v2Bt+jHapTygUQiQSISoqCgcOHEBERAQ+/fRT3XGNRgOJRAIHBwcUFxePeyVxQEAA3NzcUF9fP/EXxgzoch8hhJiIC9+T0mq1+O233wA8mUElJSXBxsYGZ8+eha2t7bjrk8vl6OzsxNy5c03rmIloJkUIIdNMVlYWysrK0NTUhHv37iErKwsymQzp6elQq9VITExET08PpFIp1Go1FAoFFAoFhoZ+v1dbSEgIiouLAQDd3d3YuXMnbt68iaamJly+fBmpqakQiURISkqaqjAB0EyKEEJMNtn37uvo6EBGRgba2trg5OSE8PBwXLx4EStWrIBMJkNlZSUAQCQS6T2vsbERfn5+AIC6ujrdF3ytrKxw9+5dnDp1CkqlEl5eXkhMTMTevXun/LtSlKQIIcRUk5ylpFLpqMfi4uLwR9bDPX2OnZ0dLl68+Mc7MInoch8hhBDOopkUIYSYyBw769LOvIZRkiKEEBNxYXXfTEWX+wghhHAWzaQIIcREtDOv5VCSIoQQU1GWshhKUoQQYiJaOGE59JkUIYQQzpr2M6nhL6Q9uwcLIeT5NvyeMBkbPWg0apNX52k09B5myLRPUhqNBsDIPVgIIQR48h7h5ORkkbqFQiE8PT0R5G+e9x9PT08IhUKz1DVTTPv9pLRaLVpbW+Hg4DBlW7Wr1Wp4e3uP2AdmOpkJMQAzIw6KwTwYY9BoNPDy8rLobtn9/f0YGBgwS11CoXBCdyyfyab9TIrP52P+/PlT3Q0Av+8DM53NhBiAmREHxWA6S82gnmZra0uJxYJo4QQhhBDOoiRFCCGEsyhJmYGNjQ327Nkz5fuumGImxADMjDgoBkJ+N+0XThBCCJm5aCZFCCGEsyhJEUII4SxKUoQQQjiLkhQhhBDOeu6TVFlZGVJSUuDl5QUej4czZ86MOKe2thYrV66Ek5MTZs+ejaVLl6KlpQUA0NTUBB6PZ/BRUFAwarvr168fcb5EIrFIDKP179ChQ7pzurq6kJ6eDkdHRzg7OyMzMxPd3d1G2+3v78c777wDV1dX2NvbY/Xq1Whvb5+SGJqampCZmQl/f3/Y2dkhMDAQe/bsGfNOAHFxcSPq3Lp164RiMEccAODn5zfieE5OjtF2uTQWMpls1HNu3bo1arvmHgsyMzz3SaqnpwcRERH47LPPDB5vaGjAyy+/jJCQEMhkMty9exe7d+/WfcPc29sbbW1teo+PPvoI9vb2SE5ONtq2RCLRe95XX31lkRie7d/JkyfB4/GwevVq3Tnp6emoqanBpUuX8N1336GsrAxbtmwx2u6OHTtw7tw5FBQU4Nq1a2htbUVaWtqUxPDjjz9Cq9Xi+PHjqKmpQW5uLo4dO4Zdu3aN2fbmzZv16j548OCEYjBHHMOys7P1ztu2bZvRdrk0FjExMSPO2bRpE/z9/bFkyRKjbZtzLMgMwYgOAFZcXKxX9tprr7G1a9eOq55FixaxjRs3Gj1n3bp1LDU1dZw9HJuhGJ6VmprK4uPjdb//8MMPDAC7deuWrqykpITxeDz28OFDg3UolUomEAhYQUGBrqy2tpYBYBUVFZMegyEHDx5k/v7+Rs9ZtmwZe/fdd8fZwz9monH4+vqy3NzcP9wO18diYGCAubu7s+zsbKP1WHIsyPT13M+kjNFqtTh//jxefPFFJCUlwcPDA9HR0QYvCQ6rqqrCnTt3kJmZOWb9MpkMHh4eCA4OxltvvYXOzk4z9t6w9vZ2nD9/Xq9/FRUVcHZ21vsvd/ny5eDz+aisrDRYT1VVFR4/fozly5frykJCQuDj44OKigrLBQDDMRiiUqng4uIyZn2nT5+Gm5sbFixYgKysLPT29pqrq0YZiyMnJweurq6IjIzEoUOHMDg4OGo9XB+Ls2fPorOzExs2bBizvqkaC8Jd0/4Gs5bU0dGB7u5u5OTkYN++ffjkk09w4cIFpKWl4erVq1i2bNmI50ilUoSGhiImJsZo3RKJBGlpafD390dDQwN27dqF5ORkVFRUwMrKylIh4dSpU3BwcNC7FKRQKODh4aF3nrW1NVxcXKBQKAzWo1AoIBQK4ezsrFf+wgsvjPocczEUw7Pq6+tx9OhRHD582Ghdb7zxBnx9feHl5YW7d+/igw8+QF1dHYqKiszd7RFGi2P79u1YvHgxXFxcUF5ejqysLLS1teHIkSMG6+H6WEilUiQlJY15I+ipHAvCXZSkjNBqtQCA1NRU7NixAwCwaNEilJeX49ixYyOSVF9fH7788kvs3r17zLpff/113c8LFy5EeHg4AgMDIZPJkJCQYMYo9J08eRLp6enT+q7NY8Xw8OFDSCQSvPrqq9i8ebPRup7+3G3hwoWYO3cuEhIS0NDQgMDAQLP2+1mjxfHee+/pfg4PD4dQKMSbb76JAwcOcO42Q2ONhVwux8WLF/H111+PWddUjgXhLrrcZ4Sbmxusra0RFhamVx4aGqpb3fe0wsJC9Pb2IiMjY9xtBQQEwM3NDfX19RPu71iuX7+Ouro6bNq0Sa/c09MTHR0demWDg4Po6uqCp6enwbo8PT0xMDAApVKpV97e3j7qc8xhtBiGtba24pVXXkFMTAxOnDgx7vqjo6MBwKLjAIwdx7N9GhwcRFNTk8HjXB0LAMjPz4erqytWrlw57vonaywIt1GSMkIoFGLp0qWoq6vTK//pp5/g6+s74nypVIqVK1fC3d193G3J5XJ0dnZi7ty5E+7vWKRSKaKiohAREaFXLhaLoVQqUVVVpSu7cuUKtFqt7o3iWVFRURAIBLh8+bKurK6uDi0tLRCLxZYJAKPHADyZQcXFxSEqKgr5+fkT2ujuzp07AGDRcQCMx2GoT3w+f8Ql2WFcHAvgyaaD+fn5yMjIgEAgGHf9kzUWhOOmeuXGVNNoNKy6uppVV1czAOzIkSOsurqaNTc3M8YYKyoqYgKBgJ04cYLdv3+fHT16lFlZWbHr16/r1XP//n3G4/FYSUmJwXaCg4NZUVGRrs3333+fVVRUsMbGRlZaWsoWL17MgoKCWH9/v9ljYIwxlUrFZs2axfLy8gzWIZFIWGRkJKusrGQ3btxgQUFBbM2aNbrjcrmcBQcHs8rKSl3Z1q1bmY+PD7ty5Qq7ffs2E4vFTCwWj7v/5ohBLpczkUjEEhISmFwuZ21tbbrHaDHU19ez7Oxsdvv2bdbY2Mi+/fZbFhAQwGJjYycUgzniKC8vZ7m5uezOnTusoaGBffHFF8zd3Z1lZGSMGgdj3BqLYaWlpQwAq62tHXFsMsaCzAzPfZK6evUqAzDisW7dOt05UqmUiUQiZmtryyIiItiZM2dG1JOVlcW8vb3Z0NCQwXYAsPz8fMYYY729vSwxMZG5u7szgUDAfH192ebNm5lCobBYDMePH2d2dnZMqVQarKOzs5OtWbOG2dvbM0dHR7Zhwwam0Wh0xxsbGxkAdvXqVV1ZX18fe/vtt9mcOXPYrFmz2KpVq/SSwmTGkJ+fb/D5T/8f9mwMLS0tLDY2lrm4uDAbGxsmEonYzp07mUqlmlAM5oijqqqKRUdHMycnJ2Zra8tCQ0PZxx9/rPfPC9fHYtiaNWtYTEyMwWOTMRZkZqCtOgghhHAWfSZFCCGEsyhJEUII4SxKUoQQQjiLkhQhhBDOoiRFCCGEsyhJEUII4SxKUoQQQjiLkhQhhBDOoiRFCCGEsyhJEUII4SxKUoQQQjiLkhQhhBDO+n8ZW0CdxkR2HgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mapharm_df.plot(column=\"injuriesPer100crashes\", cmap=\"Blues\", legend=True, edgecolor=\"black\", linewidth=0.1, \n",
    "                legend_kwds={\"label\":\"injuries per 100 crashes\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ca30da3",
   "metadata": {},
   "source": [
    "Is it possible to explain why West Coast has the highest fatality rate? Could it be just due to relatively low numbers in both crash and fatality counts, or is it actually due to mostly open roads with specific features? Note that the higher harm rate down South could be due to under-reporting of harmless crashes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f0eb5553",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "urban\n",
       "Open     4776\n",
       "Urban    2442\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cas_df[(cas_df['region'] == 'West Coast Region')]['urban'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3f586468",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "urban\n",
       "Open     18157\n",
       "Urban    15142\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cas_df[(cas_df['region'] == 'Northland Region')]['urban'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9b66fcb",
   "metadata": {},
   "source": [
    "## Elements of high fatality\n",
    "Explore a simple question: which vehicle types or roadside features may be associated with higher fatality rates (i.e. number of fatalities per crash)? This exploratory analysis will be more ad-hoc and rely on some custom functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ea2fa713",
   "metadata": {},
   "outputs": [],
   "source": [
    "from cas_functions import fatal_agg1, fatal_agg2, format_vertical_headers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c32ea0d3",
   "metadata": {},
   "source": [
    "### Particular agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "39c7f1a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crashes</th>\n",
       "      <th>fatalCrashes</th>\n",
       "      <th>fatalities</th>\n",
       "      <th>fatal_fraction</th>\n",
       "      <th>fatality_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pedestrian</th>\n",
       "      <td>26605</td>\n",
       "      <td>877</td>\n",
       "      <td>891</td>\n",
       "      <td>0.032964</td>\n",
       "      <td>0.033490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bicycle</th>\n",
       "      <td>23400</td>\n",
       "      <td>238</td>\n",
       "      <td>242</td>\n",
       "      <td>0.010171</td>\n",
       "      <td>0.010342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>moped</th>\n",
       "      <td>5805</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>0.003962</td>\n",
       "      <td>0.003962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>motorcycle</th>\n",
       "      <td>29004</td>\n",
       "      <td>1000</td>\n",
       "      <td>1036</td>\n",
       "      <td>0.034478</td>\n",
       "      <td>0.035719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bus</th>\n",
       "      <td>12900</td>\n",
       "      <td>144</td>\n",
       "      <td>164</td>\n",
       "      <td>0.011163</td>\n",
       "      <td>0.012713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>schoolBus</th>\n",
       "      <td>612</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.027778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>suv</th>\n",
       "      <td>81445</td>\n",
       "      <td>884</td>\n",
       "      <td>1015</td>\n",
       "      <td>0.010854</td>\n",
       "      <td>0.012462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>truck</th>\n",
       "      <td>63476</td>\n",
       "      <td>1415</td>\n",
       "      <td>1634</td>\n",
       "      <td>0.022292</td>\n",
       "      <td>0.025742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>503</td>\n",
       "      <td>61</td>\n",
       "      <td>70</td>\n",
       "      <td>0.121272</td>\n",
       "      <td>0.139165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxi</th>\n",
       "      <td>8536</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>0.002929</td>\n",
       "      <td>0.003046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carStationWagon</th>\n",
       "      <td>711257</td>\n",
       "      <td>5190</td>\n",
       "      <td>5981</td>\n",
       "      <td>0.007297</td>\n",
       "      <td>0.008409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vanOrUtility</th>\n",
       "      <td>135279</td>\n",
       "      <td>1479</td>\n",
       "      <td>1714</td>\n",
       "      <td>0.010933</td>\n",
       "      <td>0.012670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vehicle</th>\n",
       "      <td>8251</td>\n",
       "      <td>37</td>\n",
       "      <td>43</td>\n",
       "      <td>0.004484</td>\n",
       "      <td>0.005211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unknownVehicleType</th>\n",
       "      <td>2432</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>0.002467</td>\n",
       "      <td>0.003289</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    crashes  fatalCrashes  fatalities  fatal_fraction  \\\n",
       "pedestrian            26605           877         891        0.032964   \n",
       "bicycle               23400           238         242        0.010171   \n",
       "moped                  5805            23          23        0.003962   \n",
       "motorcycle            29004          1000        1036        0.034478   \n",
       "bus                   12900           144         164        0.011163   \n",
       "schoolBus               612            17          17        0.027778   \n",
       "suv                   81445           884        1015        0.010854   \n",
       "truck                 63476          1415        1634        0.022292   \n",
       "train                   503            61          70        0.121272   \n",
       "taxi                   8536            25          26        0.002929   \n",
       "carStationWagon      711257          5190        5981        0.007297   \n",
       "vanOrUtility         135279          1479        1714        0.010933   \n",
       "vehicle                8251            37          43        0.004484   \n",
       "unknownVehicleType     2432             6           8        0.002467   \n",
       "\n",
       "                    fatality_rate  \n",
       "pedestrian               0.033490  \n",
       "bicycle                  0.010342  \n",
       "moped                    0.003962  \n",
       "motorcycle               0.035719  \n",
       "bus                      0.012713  \n",
       "schoolBus                0.027778  \n",
       "suv                      0.012462  \n",
       "truck                    0.025742  \n",
       "train                    0.139165  \n",
       "taxi                     0.003046  \n",
       "carStationWagon          0.008409  \n",
       "vanOrUtility             0.012670  \n",
       "vehicle                  0.005211  \n",
       "unknownVehicleType       0.003289  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agfat_df = fatal_agg1(agent_types, cas_df)\n",
    "agfat_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7df1a91",
   "metadata": {},
   "source": [
    "According to this [article](https://www.nzta.govt.nz/resources/nz-pedestrian-profile/6.html) on the Waka Kotahi website, pedestrian fatalities constitute 11% of total fatalities in New Zealand. Indeed, we find that $877/8573 \\times 100 = 10.4\\%$, which seems close enough. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "af15678e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.10393094599323457"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agfat_df['fatalities']['pedestrian']/cas_df['fatalCount'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "07d43b4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agfat_df[['fatality_rate','fatal_fraction']].plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f0ac64d",
   "metadata": {},
   "source": [
    "The plot clearly shows that crashes involving a `train` have the highest fatality **rate**, followed by `motorcycle` and then `pedestrian`. To be clear, even though crashes involving a train are relatively rare, when they do happen they are more likely to produce fatalities than crashes that involve a bus instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "315fff80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot: title={'center': 'Aggregates for different agents involved'}>,\n",
       "       <AxesSubplot: >, <AxesSubplot: >], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UavzRlF82otLC6cyISsm+fftw584dbNiwARs2bMjz+Lp169CxY8dSz/F8LxoAqUAcN24cvLy88n1OSadbS0lJQZs2baBWqzFr1izUqFEDxsbGOHnyJCZOnFisojQnJwfu7u6YP39+vo87OjoCeHY8Bw8exP79+7Fjxw6Eh4dj48aNaN++Pfbs2QMDA4MSZS+pF8+nNsjJyYFCocCuXbvyPf7ne0aB/I+huOc/V0HnWbxwQWBxZWdn491338W9e/cwceJE1K5dG2ZmZrh9+zYGDRr0Un/Y5OTkwNbWtsALSp//JgR4tWNSKBT45Zdf8M8//2Dbtm3YvXs3Bg8ejHnz5uGff/7J829QHMXJ07x5c1SrVg2bNm3Chx9+iG3btuHx48caRemr6tevH5YuXYpdu3ahe/fu2LRpE2rXro369etLbUr6+iGSCwtfolKybt062Nra4vvvv8/z2JYtW/Dbb78hNDQUJiYmcHJywv79+/Ho0SONXt/nr+AGACcnp3zXF7QuP9WrVwcAlCtXDp6enoW2dXJyKta+IiMjcffuXWzZsgWtW7eW1sfExOR57vNf+z+vRo0aOHPmDDp06FBgm1xKpRIdOnRAhw4dMH/+fMyZMwdTpkzB/v37izymFzk5OeHPP//EgwcPNHp9c4dn5J7zksp93pUrV6RzDgDJycmv1Cuanxo1akAIAWdnZ6mH7WW2UdzzX1wl2U50dDT+/fdfrF69GgMHDpTW7927V6NdSd4DNWrUwJ9//omWLVu+tj9Yijqm5s2bo3nz5vjqq6+wfv16DBgwABs2bMDQoUNfy/7z06dPH4SEhCAtLQ0bN25EtWrV0Lx5c+nx3HN2+fJljddiZmYmYmJiinzPtG7dGpUqVcLGjRvRqlUr7Nu3D1OmTNFoU9zXj5OTE3JycnDt2jWNXt7Lly+X6JiJXhaHOhCVgsePH2PLli3o0qULPvjggzzLqFGj8ODBA+nrSS8vL2RlZWH58uXSNnJycvIUzQ4ODnBzc8OaNWs0xvQdOHAA0dHRxcpma2uLtm3bYunSpbhz506ex5OTk6X/9/LyQlRUFE6fPi2tu3fvXp4etNyeqed7ojIzM7FkyZI82zczM8t36EOfPn1w+/ZtjXOQ6/Hjx3j48KG0/xfljkF+ma+VO3fujOzsbCxevFhj/YIFC6BQKPDee++VeJvAszGw5cqVw6JFizTOS2ncta5nz54wMDDAzJkz8/ROCiFw9+7dIrdR3PNfEmZmZgBQrDu35fcaEkIgJCREo11J3gN9+vRBdnY2vvzyyzz7e/r06UvdUa6gY7p//36ec/8qr8uS6Nu3LzIyMrB69WqEh4ejT58+Go97enrCyMgICxcu1Mi4cuVKpKamwtvbu9DtK5VKfPDBB9i2bRvWrl2Lp0+f5ulRLu7rJ/f9tHDhQo02ct3NkfQPe3yJSsEff/yBBw8e4P3338/38ebNm0s3s+jbty+6d++Opk2bYuzYsbh69Spq166NP/74Qyrynu9BmTNnDrp164aWLVvC19cX9+/fx+LFi+Hm5qZRCBTm+++/R6tWreDu7o5hw4ahevXqSExMRFRUFG7duoUzZ84AACZMmICffvoJ7777Lvz9/WFmZoYVK1agatWquHfvnpSrRYsWsLS0hI+PD0aPHg2FQoG1a9fm+xVx48aNsXHjRgQGBuLtt99G+fLl0bVrV3z88cfYtGkTRowYgf3796Nly5bIzs7GpUuXsGnTJuzevRtNmjTBrFmzcPDgQXh7e8PJyQlJSUlYsmQJqlSpIl3MUxJdu3ZFu3btMGXKFNy4cQP169fHnj178PvvvyMgICDPWMTisrGxwbhx4xAUFIQuXbqgc+fOOHXqFHbt2gVra+uX2mZBatSogdmzZ2Py5Mm4ceMGunfvjgoVKiAmJga//fYbhg8frjHfan6Ke/5LonHjxgCAKVOmoF+/fihXrhy6du0qFY/Pq127NmrUqIFx48bh9u3bUKvV+PXXX/PtHS/ue6BNmzb45JNPEBQUhNOnT6Njx44oV64crly5gs2bNyMkJAQffPBBiY6pQYMGMDAwwDfffIPU1FSoVCq0b98e69evx5IlS9CjRw/UqFEDDx48wPLly6FWq9G5c+cS7aOkGjVqhJo1a2LKlCnIyMjIU5Ta2Nhg8uTJmDlzJjp16oT3338fly9fxpIlS/D2229LY/EL07dvXyxatAjTp0+Hu7u7NAY+V3FfPw0aNED//v2xZMkSpKamokWLFoiIiCj2N1ZEr6zM55Eg0gNdu3YVxsbG4uHDhwW2GTRokChXrpw072lycrL48MMPRYUKFYS5ubkYNGiQOHTokAAgNmzYoPHcDRs2iNq1awuVSiXc3NzEH3/8IXr16iVq164ttcmdzmzu3Ln57v/atWti4MCBwt7eXpQrV05UrlxZdOnSRfzyyy8a7U6dOiXNHVulShURFBQkFi5cKACIhIQEqd2hQ4dE8+bNhYmJiXBwcBATJkyQpkJ6fuqn9PR08eGHHwoLC4s8009lZmaKb775RtStW1eoVCphaWkpGjduLGbOnClSU1OFEEJERESIbt26CQcHB2FkZCQcHBxE//79xb///lv4P4rIfzozIYR48OCBGDNmjHBwcBDlypUTLi4uYu7cuRrTkAnxbBqv5+dGLUp2draYOXOmqFSpkjAxMRFt27YV586dE05OTq91OrNcv/76q2jVqpUwMzMTZmZmonbt2sLPz09cvny5yHMgRPHOf2Hn4cXjEkKIL7/8UlSuXFkolcoipza7cOGC8PT0FOXLlxfW1tZi2LBh0jRpz0/pJ0Tx3gO5li1bJho3bixMTExEhQoVhLu7u5gwYYKIj4/XyO7t7Z3nuS9ONSaEEMuXLxfVq1cXBgYG0r/byZMnRf/+/UXVqlWFSqUStra2okuXLuL48eMFHm9B+8h9PWzevFmjXe57+sVzIYQQU6ZMEQBEzZo1C9zP4sWLRe3atUW5cuWEnZ2dGDlypMYcz0Lknc4sV05OjnB0dMx36r9cxX39PH78WIwePVpYWVkJMzMz0bVrVxEXF8fpzKhMKIR4ySsRiKjUbd26FT169MDff/+Nli1bFtq2QYMGsLGxyTMmsjQEBARg6dKlSE9PL/WLyYiKqyzfA0SkmzjGl0hLvHhb1uzsbCxatAhqtRqNGjWS1mdlZeHp06cabSMjI3HmzBmN256WVq67d+9i7dq1aNWqFYtekkVZvweI6M3BMb5EWsLf3x+PHz+Gh4cHMjIysGXLFhw+fBhz5szRuCL99u3b8PT0xEcffQQHBwdcunQJoaGhsLe3x4gRI157Lg8PD7Rt2xZ16tRBYmIiVq5cibS0NEydOvW174uoOMr6PUBEbw4WvkRaon379pg3bx62b9+OJ0+eoGbNmli0aBFGjRql0c7S0hKNGzfGihUrkJycDDMzM3h7e+Prr7+GlZXVa8/VuXNn/PLLL1i2bBkUCgUaNWqElStXakxbRlSWyvo9QERvDo7xJSIiIiK9wDG+RERERKQXWPgSERERkV7gGN9C5OTkID4+HhUqVHhtt/AkIiIiotdHCIEHDx7AwcEBSmXhfbosfAsRHx8PR0dHuWMQERERURHi4uJQpUqVQtuw8C1EhQoVADw7kWq1WuY0RERERPSitLQ0ODo6SnVbYVj4FiJ3eINarWbhS0RERKTFijMslRe3EREREZFeYOFLRERERHqBhS8RERER6QWO8SUiIqJiqzZpR6ls98bX3qWy3ZeVnZ2NrKwsuWPQ/zMyMipyqrLiYOFLRERE9P+EEEhISEBKSorcUeg5SqUSzs7OMDIyeqXtsPAlIiIi+n+5Ra+trS1MTU15AystkHtDsTt37qBq1aqv9G/CwpeIiIgIz4Y35Ba9VlZWcseh59jY2CA+Ph5Pnz5FuXLlXno7vLiNiIiICJDG9JqamsqchF6UO8QhOzv7lbbDwpeIiIjoORzeoH1e178JC18iIiIi0gssfImIiIioRAYNGoTu3bvLHaPEeHEbERERUSFKa+7igmjbnMZvEvb4EhEREekRfb4xBwtfIiIiIh2Xk5ODb7/9FjVr1oRKpULVqlXx1Vdf4caNG1AoFNi4cSPatGkDY2NjrFu3Dnfv3kX//v1RuXJlmJqawt3dHT///LPGNn/55Re4u7vDxMQEVlZW8PT0xMOHDzXafPfdd6hUqRKsrKzg5+enUVRnZGRg3LhxqFy5MszMzNCsWTNERkZKj9+8eRNdu3aFpaUlzMzMULduXezcubNUzxOHOhARERHpuMmTJ2P58uVYsGABWrVqhTt37uDSpUvS45MmTcK8efPQsGFDGBsb48mTJ2jcuDEmTpwItVqNHTt24OOPP0aNGjXQtGlT3LlzB/3798e3336LHj164MGDB/jrr78ghJC2uX//flSqVAn79+/H1atX0bdvXzRo0ADDhg0DAIwaNQoXLlzAhg0b4ODggN9++w2dOnVCdHQ0XFxc4Ofnh8zMTBw8eBBmZma4cOECypcvX6rniYUvERERkQ578OABQkJCsHjxYvj4+AAAatSogVatWuHGjRsAgICAAPTs2VPjeePGjZP+39/fH7t378amTZukwvfp06fo2bMnnJycAADu7u4az7e0tMTixYthYGCA2rVrw9vbGxERERg2bBhiY2MRFhaG2NhYODg4SPsLDw9HWFgY5syZg9jYWPTq1UvabvXq1Uvl/DyPhS8RERGRDrt48SIyMjLQoUOHAts0adJE4+fs7GzMmTMHmzZtwu3bt5GZmYmMjAzp5h3169dHhw4d4O7uDi8vL3Ts2BEffPABLC0tpW3UrVsXBgYG0s+VKlVCdHQ0ACA6OhrZ2dl46623NPabkZEh3RVv9OjRGDlyJPbs2QNPT0/06tUL9erVe7WTUQSO8SUiIiLSYSYmJkW2MTMz0/h57ty5CAkJwcSJE7F//36cPn0aXl5eyMzMBAAYGBhg79692LVrF1xdXbFo0SLUqlULMTEx0jZevHWwQqFATk4OACA9PR0GBgY4ceIETp8+LS0XL15ESEgIAGDo0KG4fv06Pv74Y0RHR6NJkyZYtGjRK52LorDwJSIiItJhLi4uMDExQURERLGfc+jQIXTr1g0fffQR6tevj+rVq+Pff//VaKNQKNCyZUvMnDkTp06dgpGREX777bdibb9hw4bIzs5GUlISatasqbHY29tL7RwdHTFixAhs2bIFY8eOxfLly4t9DC+DQx2IiIiIdJixsTEmTpyICRMmwMjICC1btkRycjLOnz9f4PAHFxcX/PLLLzh8+DAsLS0xf/58JCYmwtXVFQBw5MgRREREoGPHjrC1tcWRI0eQnJyMOnXqFCvTW2+9hQEDBmDgwIHSRXXJycmIiIhAvXr14O3tjYCAALz33nt46623cP/+fezfv7/Y239ZJS58b9++jYkTJ2LXrl149OgRatasibCwMGnsiBAC06dPx/Lly5GSkoKWLVvihx9+gIuLi7SNe/fuwd/fH9u2bYNSqUSvXr0QEhKicSXf2bNn4efnh2PHjsHGxgb+/v6YMGGCRpbNmzdj6tSpuHHjBlxcXPDNN9+gc+fO0uPFyUJERERUGF24ocTUqVNhaGiIadOmIT4+HpUqVcKIESMKbP/FF1/g+vXr8PLygqmpKYYPH47u3bsjNTUVAKBWq3Hw4EEEBwcjLS0NTk5OmDdvHt57771iZwoLC8Ps2bMxduxY3L59G9bW1mjevDm6dOkC4Nk4Yz8/P9y6dQtqtRqdOnXCggULXu1EFEEhnp+Xogj3799Hw4YN0a5dO4wcORI2Nja4cuUKatSogRo1agAAvvnmGwQFBWH16tVwdnbG1KlTER0djQsXLsDY2BgA8N577+HOnTtYunQpsrKy4Ovri7fffhvr168HAKSlpeGtt96Cp6cnJk+ejOjoaAwePBjBwcEYPnw4AODw4cNo3bo1goKC0KVLF6xfvx7ffPMNTp48CTc3t2JnKUxaWhrMzc2RmpoKtVpdsjNLRET0Biqtu5hpQ3H55MkTxMTEwNnZuVh1ApWdwv5tSlKvlajwnTRpEg4dOoS//vor38eFEHBwcMDYsWOlKTJSU1NhZ2eHVatWoV+/frh48SJcXV1x7NgxqZc4PDwcnTt3xq1bt+Dg4IAffvgBU6ZMQUJCAoyMjKR9b926VZqTrm/fvnj48CG2b98u7b958+Zo0KABQkNDi5XlRRkZGcjIyNA4kY6Ojix8iYiI/h8LX5LD6yp8S3Rx2x9//IEmTZqgd+/esLW1RcOGDTUGIcfExCAhIQGenp7SOnNzczRr1gxRUVEAgKioKFhYWGhMq+Hp6QmlUokjR45IbVq3bi0VvQDg5eWFy5cv4/79+1Kb5/eT2yZ3P8XJ8qKgoCCYm5tLi6OjY0lODxERERFpsRIVvtevX5fGyO7evRsjR47E6NGjsXr1agBAQkICAMDOzk7jeXZ2dtJjCQkJsLW11Xjc0NAQFStW1GiT3zae30dBbZ5/vKgsL5o8eTJSU1OlJS4urqhTQkREREQ6okQXt+Xk5KBJkyaYM2cOgGdTVZw7dw6hoaHSnUJ0mUqlgkqlkjsGEREREZWCEvX4VqpUSZrmIledOnUQGxsLANK8bImJiRptEhMTpcfs7e2RlJSk8fjTp09x7949jTb5beP5fRTU5vnHi8pCRERE9KISXP5EZeR1/ZuUqPBt2bIlLl++rLHu33//le7h7OzsDHt7e40JlNPS0nDkyBF4eHgAADw8PJCSkoITJ05Ibfbt24ecnBw0a9ZManPw4EFkZWVJbfbu3YtatWpJt8rz8PDIM1Hz3r17pf0UJwsRERFRrtw7kT169EjmJPSi5+8o9ypKNNRhzJgxaNGiBebMmYM+ffrg6NGjWLZsGZYtWwbg2R0+AgICMHv2bLi4uEhTiDk4OKB79+4AnvUQd+rUCcOGDUNoaCiysrIwatQo9OvXDw4ODgCADz/8EDNnzsSQIUMwceJEnDt3DiEhIRpzu3322Wdo06YN5s2bB29vb2zYsAHHjx8vURYiIiKiXAYGBrCwsJC+mTY1NYVCoZA5FeXk5CA5ORmmpqYwNHy1e6+V6Nlvv/02fvvtN0yePBmzZs2Cs7MzgoODMWDAAKnNhAkT8PDhQwwfPhwpKSlo1aoVwsPDNaaeWLduHUaNGoUOHTpIN7BYuHCh9Li5uTn27NkDPz8/NG7cGNbW1pg2bZo0hy8AtGjRAuvXr8cXX3yBzz//HC4uLti6das0h29xsxARERHlyh0O+eKwTJKXUqlE1apVX/kPkRLN46tveAMLIiIiTW/yPL7Py87O1hhySfIyMjKCUpn/CN2S1Guv1l9MRERE9AYyMDB45fGkpH1KdHEbEREREZGuYuFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF16p8P3666+hUCgQEBAgrXvy5An8/PxgZWWF8uXLo1evXkhMTNR4XmxsLLy9vWFqagpbW1uMHz8eT58+1WgTGRmJRo0aQaVSoWbNmli1alWe/X///feoVq0ajI2N0axZMxw9elTj8eJkISIiIiL98NKF77Fjx7B06VLUq1dPY/2YMWOwbds2bN68GQcOHEB8fDx69uwpPZ6dnQ1vb29kZmbi8OHDWL16NVatWoVp06ZJbWJiYuDt7Y127drh9OnTCAgIwNChQ7F7926pzcaNGxEYGIjp06fj5MmTqF+/Pry8vJCUlFTsLERERESkPxRCCFHSJ6Wnp6NRo0ZYsmQJZs+ejQYNGiA4OBipqamwsbHB+vXr8cEHHwAALl26hDp16iAqKgrNmzfHrl270KVLF8THx8POzg4AEBoaiokTJyI5ORlGRkaYOHEiduzYgXPnzkn77NevH1JSUhAeHg4AaNasGd5++20sXrwYAJCTkwNHR0f4+/tj0qRJxcpSlLS0NJibmyM1NRVqtbqkp4mIiOiNU23SjlLZ7o2vvUtlu/TmK0m99lI9vn5+fvD29oanp6fG+hMnTiArK0tjfe3atVG1alVERUUBAKKiouDu7i4VvQDg5eWFtLQ0nD9/Xmrz4ra9vLykbWRmZuLEiRMabZRKJTw9PaU2xcnyooyMDKSlpWksRERERPRmMCzpEzZs2ICTJ0/i2LFjeR5LSEiAkZERLCwsNNbb2dkhISFBavN80Zv7eO5jhbVJS0vD48ePcf/+fWRnZ+fb5tKlS8XO8qKgoCDMnDmzkKMnIiIiIl1Voh7fuLg4fPbZZ1i3bh2MjY1LK5NsJk+ejNTUVGmJi4uTOxIRERERvSYlKnxPnDiBpKQkNGrUCIaGhjA0NMSBAwewcOFCGBoaws7ODpmZmUhJSdF4XmJiIuzt7QEA9vb2eWZWyP25qDZqtRomJiawtraGgYFBvm2e30ZRWV6kUqmgVqs1FiIiIiJ6M5So8O3QoQOio6Nx+vRpaWnSpAkGDBgg/X+5cuUQEREhPefy5cuIjY2Fh4cHAMDDwwPR0dEasy/s3bsXarUarq6uUpvnt5HbJncbRkZGaNy4sUabnJwcRERESG0aN25cZBYiIiIi0h8lGuNboUIFuLm5aawzMzODlZWVtH7IkCEIDAxExYoVoVar4e/vDw8PD2kWhY4dO8LV1RUff/wxvv32WyQkJOCLL76An58fVCoVAGDEiBFYvHgxJkyYgMGDB2Pfvn3YtGkTduz435WkgYGB8PHxQZMmTdC0aVMEBwfj4cOH8PX1BQCYm5sXmYWIiIiI9EeJL24ryoIFC6BUKtGrVy9kZGTAy8sLS5YskR43MDDA9u3bMXLkSHh4eMDMzAw+Pj6YNWuW1MbZ2Rk7duzAmDFjEBISgipVqmDFihXw8vKS2vTt2xfJycmYNm0aEhIS0KBBA4SHh2tc8FZUFiIiIiLSHy81j6++4Dy+REREmjiPL2mbUp/Hl4iIiIhI17DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL7DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL7DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL7DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL7DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL7DwJSIiIiK9wMKXiIiIiPQCC18iIiIi0gssfImIiIhIL5So8A0KCsLbb7+NChUqwNbWFt27d8fly5c12jx58gR+fn6wsrJC+fLl0atXLyQmJmq0iY2Nhbe3N0xNTWFra4vx48fj6dOnGm0iIyPRqFEjqFQq1KxZE6tWrcqT5/vvv0e1atVgbGyMZs2a4ejRoyXOQkRERET6oUSF74EDB+Dn54d//vkHe/fuRVZWFjp27IiHDx9KbcaMGYNt27Zh8+bNOHDgAOLj49GzZ0/p8ezsbHh7eyMzMxOHDx/G6tWrsWrVKkybNk1qExMTA29vb7Rr1w6nT59GQEAAhg4dit27d0ttNm7ciMDAQEyfPh0nT55E/fr14eXlhaSkpGJnISIiIiL9oRBCiJd9cnJyMmxtbXHgwAG0bt0aqampsLGxwfr16/HBBx8AAC5duoQ6deogKioKzZs3x65du9ClSxfEx8fDzs4OABAaGoqJEyciOTkZRkZGmDhxInbs2IFz585J++rXrx9SUlIQHh4OAGjWrBnefvttLF68GACQk5MDR0dH+Pv7Y9KkScXKUpS0tDSYm5sjNTUVarX6ZU8TERHRG6PapB2lst0bX3uXynbpzVeSeu2VxvimpqYCACpWrAgAOHHiBLKysuDp6Sm1qV27NqpWrYqoqCgAQFRUFNzd3aWiFwC8vLyQlpaG8+fPS22e30Zum9xtZGZm4sSJExptlEolPD09pTbFyfKijIwMpKWlaSxERERE9GZ46cI3JycHAQEBaNmyJdzc3AAACQkJMDIygoWFhUZbOzs7JCQkSG2eL3pzH899rLA2aWlpePz4Mf777z9kZ2fn2+b5bRSV5UVBQUEwNzeXFkdHx2KeDSIiIiLSdi9d+Pr5+eHcuXPYsGHD68wjq8mTJyM1NVVa4uLi5I5ERERERK+J4cs8adSoUdi+fTsOHjyIKlWqSOvt7e2RmZmJlJQUjZ7WxMRE2NvbS21enH0hd6aF59u8OPtCYmIi1Go1TExMYGBgAAMDg3zbPL+NorK8SKVSQaVSleBMEBEREZGuKFGPrxACo0aNwm+//YZ9+/bB2dlZ4/HGjRujXLlyiIiIkNZdvnwZsbGx8PDwAAB4eHggOjpaY/aFvXv3Qq1Ww9XVVWrz/DZy2+Ruw8jICI0bN9Zok5OTg4iICKlNcbIQERERkf4oUY+vn58f1q9fj99//x0VKlSQxsqam5vDxMQE5ubmGDJkCAIDA1GxYkWo1Wr4+/vDw8NDmkWhY8eOcHV1xccff4xvv/0WCQkJ+OKLL+Dn5yf1to4YMQKLFy/GhAkTMHjwYOzbtw+bNm3Cjh3/u5I0MDAQPj4+aNKkCZo2bYrg4GA8fPgQvr6+UqaishARERGR/ihR4fvDDz8AANq2bauxPiwsDIMGDQIALFiwAEqlEr169UJGRga8vLywZMkSqa2BgQG2b9+OkSNHwsPDA2ZmZvDx8cGsWbOkNs7OztixYwfGjBmDkJAQVKlSBStWrICXl5fUpm/fvkhOTsa0adOQkJCABg0aIDw8XOOCt6KyEBEREZH+eKV5fN90nMeXiIhIE+fxJW1TZvP4EhERERHpCha+RERERKQXWPgSERERkV5g4UtEREREeoGFLxERERHphZe6cxsRERGRruBMFJSLPb5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBd45zYiojLEO0gREcmHPb5EREREpBdY+BIRERGRXuBQByIiKlBpDc0AODyDiMoee3yJiIiISC+w8CUiIiIivcDCl4iIiIj0AgtfIiIiItILLHyJiIiISC9wVgeiUsSbFRAREWkPFr6vkS5O+8PCjIiIiPSFXgx1+P7771GtWjUYGxujWbNmOHr0qNyRiIiIiKiMvfE9vhs3bkRgYCBCQ0PRrFkzBAcHw8vLC5cvX4atra3c8Yi0Dr8FICKiN9UbX/jOnz8fw4YNg6+vLwAgNDQUO3bswI8//ohJkybJnI6IiPQd/9ikF/E1UXre6MI3MzMTJ06cwOTJk6V1SqUSnp6eiIqKytM+IyMDGRkZ0s+pqakAgLS0tGLtLyfj0SsmLlhxM5RUaWUurbxu03eXynbPzfQqle3q2vkFdDOzLtG186uLn2u6hq+JZ/i59j+6llfu3825xyWEKLqxeIPdvn1bABCHDx/WWD9+/HjRtGnTPO2nT58uAHDhwoULFy5cuHDRsSUuLq7I2vCN7vEtqcmTJyMwMFD6OScnB/fu3YOVlRUUCsVr209aWhocHR0RFxcHtVr92rZbmnQtM/OWPl3LzLylS9fyArqXmXlLn65lZt5nhBB48OABHBwcimz7Rhe+1tbWMDAwQGJiosb6xMRE2Nvb52mvUqmgUqk01llYWJRaPrVarRMv1OfpWmbmLX26lpl5S5eu5QV0LzPzlj5dy8y8gLm5ebHavdHTmRkZGaFx48aIiIiQ1uXk5CAiIgIeHh4yJiMiIiKisvZG9/gCQGBgIHx8fNCkSRM0bdoUwcHBePjwoTTLAxERERHphze+8O3bty+Sk5Mxbdo0JCQkoEGDBggPD4ednZ1smVQqFaZPn55nWIU207XMzFv6dC0z85YuXcsL6F5m5i19upaZeUtOIURx5n4gIiIiItJtb/QYXyIiIiKiXCx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr1gKHcAbZaTk4P4+HhUqFABCoVC7jhERERE9AIhBB48eAAHBwcolYX36bLwLUR8fDwcHR3ljkFERERERYiLi0OVKlUKbcPCtxAVKlQA8OxEqtVqmdMQERER0YvS0tLg6Ogo1W2Fka3wvX37NiZOnIhdu3bh0aNHqFmzJsLCwtCkSRMAz7qtp0+fjuXLlyMlJQUtW7bEDz/8ABcXF2kb9+7dg7+/P7Zt2walUolevXohJCQE5cuXl9qcPXsWfn5+OHbsGGxsbODv748JEyYUK2Pu8Aa1Ws3Cl4iIiEiLFWdYqiwXt92/fx8tW7ZEuXLlsGvXLly4cAHz5s2DpaWl1Obbb7/FwoULERoaiiNHjsDMzAxeXl548uSJ1GbAgAE4f/489u7di+3bt+PgwYMYPny49HhaWho6duwIJycnnDhxAnPnzsWMGTOwbNmyMj1eIiIiIpKfQgghynqnkyZNwqFDh/DXX3/l+7gQAg4ODhg7dizGjRsHAEhNTYWdnR1WrVqFfv364eLFi3B1dcWxY8ekXuLw8HB07twZt27dgoODA3744QdMmTIFCQkJMDIykva9detWXLp0qcicaWlpMDc3R2pqKnt8iYiIiLRQSeo1WXp8//jjDzRp0gS9e/eGra0tGjZsiOXLl0uPx8TEICEhAZ6entI6c3NzNGvWDFFRUQCAqKgoWFhYSEUvAHh6ekKpVOLIkSNSm9atW0tFLwB4eXnh8uXLuH//fp5cGRkZSEtL01iIiIiI6M0gyxjf69ev44cffkBgYCA+//xzHDt2DKNHj4aRkRF8fHyQkJAAALCzs9N4np2dnfRYQkICbG1tNR43NDRExYoVNdo4Ozvn2UbuY88PrQCAoKAgzJw58/UdKBER0ZtmhnkpbTe1dLZbiOzsbGRlZZX5fqnkjIyMipyqrDhkKXxzcnLQpEkTzJkzBwDQsGFDnDt3DqGhofDx8ZEjEgBg8uTJCAwMlH7OvUqQiIiI3hxCCCQkJCAlJUXuKFRMSqUSzs7OGt/ivwxZCt9KlSrB1dVVY12dOnXw66+/AgDs7e0BAImJiahUqZLUJjExEQ0aNJDaJCUlaWzj6dOnuHfvnvR8e3t7JCYmarTJ/Tm3zfNUKhVUKtUrHBkRERFpu9yi19bWFqamprxJlZbLvaHYnTt3ULVq1Vf695Kl8G3ZsiUuX76sse7ff/+Fk5MTAMDZ2Rn29vaIiIiQCt20tDQcOXIEI0eOBAB4eHggJSUFJ06cQOPGjQEA+/btQ05ODpo1aya1mTJlCrKyslCuXDkAwN69e1GrVq08wxyIiIjozZednS0VvVZWVnLHoWKysbFBfHw8nj59KtV0L0OWi9vGjBmDf/75B3PmzMHVq1exfv16LFu2DH5+fgCezcMWEBCA2bNn448//kB0dDQGDhwIBwcHdO/eHcCzHuJOnTph2LBhOHr0KA4dOoRRo0ahX79+cHBwAAB8+OGHMDIywpAhQ3D+/Hls3LgRISEhGsMZiIiISH/kjuk1NTWVOQmVRO4Qh+zs7Ffajiw9vm+//TZ+++03TJ48GbNmzYKzszOCg4MxYMAAqc2ECRPw8OFDDB8+HCkpKWjVqhXCw8NhbGwstVm3bh1GjRqFDh06SDewWLhwofS4ubk59uzZAz8/PzRu3BjW1taYNm2axly/REREpH84vEG3vK5/L1nm8dUVnMeXiIjoBTo+q8OTJ08QExMDZ2dnjc400m6F/btp/Ty+RERERFQyQggMHz4cFStWhEKhwOnTp0ttXwqFAlu3bgUA3Lhxo1j7a9u2LQICAkot0+sgy1AHIiIiIq1SWj3ZBe6v5D3c4eHhWLVqFSIjI1G9enVYW1sX2v7GjRtwdnbGqVOnpMkCXoajoyPu3Lkj7S8yMhLt2rXD/fv3YWFhIbXbsmXLK114VhZY+BIRERHpgGvXrqFSpUpo0aJFme7XwMAg32lgX1SxYsUySPNqONSBiIiISMsNGjQI/v7+iI2NhUKhQLVq1RAeHo5WrVrBwsICVlZW6NKlC65duyY9J/futQ0bNoRCoUDbtm0BAMeOHcO7774La2trmJubo02bNjh58mSB+35+qMONGzfQrl07AIClpSUUCgUGDRoEIO9Qh4yMDIwbNw6VK1eGmZkZmjVrhsjISOnxmzdvomvXrrC0tISZmRnq1q2LnTt3vp4TVgAWvkRERERaLiQkBLNmzUKVKlVw584dHDt2DA8fPkRgYCCOHz+OiIgIKJVK9OjRAzk5OQCAo0ePAgD+/PNP3LlzB1u2bAEAPHjwAD4+Pvj777/xzz//wMXFBZ07d8aDBw+KzOHo6CjdcOzy5cu4c+cOQkJC8m07atQoREVFYcOGDTh79ix69+6NTp064cqVKwAAPz8/ZGRk4ODBg4iOjsY333yD8uXLv/K5KgyHOhARERFpOXNzc1SoUEFj2EGvXr002vz444+wsbHBhQsX4ObmBhsbGwCAlZWVxlCF9u3bazxv2bJlsLCwwIEDB9ClS5dCcxgYGEhDGmxtbTXG+D4vNjYWYWFhiI2Nle6vMG7cOISHhyMsLAxz5sxBbGwsevXqBXd3dwBA9erVi3k2Xh57fImIiIh00JUrV9C/f39Ur14darUa1apVA/Cs6CxMYmIihg0bBhcXF5ibm0OtViM9Pb3I55VEdHQ0srOz8dZbb6F8+fLScuDAAWk4xujRozF79my0bNkS06dPx9mzZ1/b/gvCHl8iIiIiHdS1a1c4OTlh+fLlcHBwQE5ODtzc3JCZmVno83x8fHD37l2EhITAyckJKpUKHh4eRT6vJNLT02FgYIATJ07AwMBA47Hc4QxDhw6Fl5cXduzYgT179iAoKAjz5s2Dv7//a8vxIha+RERERDrm7t27uHz5MpYvX4533nkHAPD3339rtCnoNr+HDh3CkiVL0LlzZwBAXFwc/vvvv2Lvuzi3D27YsCGys7ORlJQk5cuPo6MjRowYgREjRmDy5MlYvnx5qRa+HOpAREREpGMsLS1hZWWFZcuW4erVq9i3bx8CAwM12tja2sLExATh4eFITExEauqzuYNdXFywdu1aXLx4EUeOHMGAAQNgYmJS7H07OTlBoVBg+/btSE5ORnp6ep42b731FgYMGICBAwdiy5YtiImJwdGjRxEUFIQdO3YAAAICArB7927ExMTg5MmT2L9/P+rUqfMKZ6Vo7PElIiIiKqNbJr8uSqUSGzZswOjRo+Hm5oZatWph4cKF0pRlAGBoaIiFCxdi1qxZmDZtGt555x1ERkZi5cqVGD58OBo1agRHR0fMmTMH48aNK/a+K1eujJkzZ2LSpEnw9fXFwIEDsWrVqjztwsLCMHv2bIwdOxa3b9+GtbU1mjdvLl1Al52dDT8/P9y6dQtqtRqdOnXCggULXvXUFEohhBClugcdVpJ7PxMREemF0rrDWRkVnk+ePEFMTAycnZ1hbGxcJvukV1fYv1tJ6jUOdSAiIiIivcDCl4iIiIj0AgtfIiIiItILLHyJiIiISC+w8CUiIiK9w2v7dcvr+vdi4UtERER6o1y5cgCAR48eyZyESiL3rnIv3gWupDiPLxEREekNAwMDWFhYICkpCQBgamoKhUIhcyoqTE5ODpKTk2FqagpDw1crXVn4EhERkV6xt7cHAKn4Je2nVCpRtWrVV/4jhYUvERER6RWFQoFKlSrB1tYWWVlZcsehYjAyMoJS+eojdFn4EhERkV4yMDB45TGjpFt4cRsRERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF2QvfL/++msoFAoEBARI6548eQI/Pz9YWVmhfPny6NWrFxITEzWeFxsbC29vb5iamsLW1hbjx4/H06dPNdpERkaiUaNGUKlUqFmzJlatWlUGR0RERERE2kjWwvfYsWNYunQp6tWrp7F+zJgx2LZtGzZv3owDBw4gPj4ePXv2lB7Pzs6Gt7c3MjMzcfjwYaxevRqrVq3CtGnTpDYxMTHw9vZGu3btcPr0aQQEBGDo0KHYvXt3mR0fEREREWkPhRBCyLHj9PR0NGrUCEuWLMHs2bPRoEEDBAcHIzU1FTY2Nli/fj0++OADAMClS5dQp04dREVFoXnz5ti1axe6dOmC+Ph42NnZAQBCQ0MxceJEJCcnw8jICBMnTsSOHTtw7tw5aZ/9+vVDSkoKwsPDi5UxLS0N5ubmSE1NhVqtfv0ngYiISNfMMC+l7aaWznbpjVeSek22Hl8/Pz94e3vD09NTY/2JEyeQlZWlsb527dqoWrUqoqKiAABRUVFwd3eXil4A8PLyQlpaGs6fPy+1eXHbXl5e0jbyk5GRgbS0NI2FiIiIiN4MhnLsdMOGDTh58iSOHTuW57GEhAQYGRnBwsJCY72dnR0SEhKkNs8XvbmP5z5WWJu0tDQ8fvwYJiYmefYdFBSEmTNnvvRxEREREZH2KvMe37i4OHz22WdYt24djI2Ny3r3hZo8eTJSU1OlJS4uTu5IRERERPSalHnhe+LECSQlJaFRo0YwNDSEoaEhDhw4gIULF8LQ0BB2dnbIzMxESkqKxvMSExNhb28PALC3t88zy0Puz0W1UavV+fb2AoBKpYJardZYiIiIiOjNUOaFb4cOHRAdHY3Tp09LS5MmTTBgwADp/8uVK4eIiAjpOZcvX0ZsbCw8PDwAAB4eHoiOjkZSUpLUZu/evVCr1XB1dZXaPL+N3Da52yAiIiIi/VLmY3wrVKgANzc3jXVmZmawsrKS1g8ZMgSBgYGoWLEi1Go1/P394eHhgebNmwMAOnbsCFdXV3z88cf49ttvkZCQgC+++AJ+fn5QqVQAgBEjRmDx4sWYMGECBg8ejH379mHTpk3YsWNH2R4wEREREWkFWS5uK8qCBQugVCrRq1cvZGRkwMvLC0uWLJEeNzAwwPbt2zFy5Eh4eHjAzMwMPj4+mDVrltTG2dkZO3bswJgxYxASEoIqVapgxYoV8PLykuOQiIiIiEhmss3jqws4jy8REdELOI8vaRmdmMeXiIiIiKgssfAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvyFL4BgUF4e2330aFChVga2uL7t274/Llyxptnjx5Aj8/P1hZWaF8+fLo1asXEhMTNdrExsbC29sbpqamsLW1xfjx4/H06VONNpGRkWjUqBFUKhVq1qyJVatWlfbhEREREZEWkqXwPXDgAPz8/PDPP/9g7969yMrKQseOHfHw4UOpzZgxY7Bt2zZs3rwZBw4cQHx8PHr27Ck9np2dDW9vb2RmZuLw4cNYvXo1Vq1ahWnTpkltYmJi4O3tjXbt2uH06dMICAjA0KFDsXv37jI9XiIiIiKSn0IIIeQOkZycDFtbWxw4cACtW7dGamoqbGxssH79enzwwQcAgEuXLqFOnTqIiopC8+bNsWvXLnTp0gXx8fGws7MDAISGhmLixIlITk6GkZERJk6ciB07duDcuXPSvvr164eUlBSEh4fnyZGRkYGMjAzp57S0NDg6OiI1NRVqtbqUzwIREZEOmGFeSttNLZ3t0hsvLS0N5ubmxarXtGKMb2rqsxd7xYoVAQAnTpxAVlYWPD09pTa1a9dG1apVERUVBQCIioqCu7u7VPQCgJeXF9LS0nD+/HmpzfPbyG2Tu40XBQUFwdzcXFocHR1f30ESERERkaxkL3xzcnIQEBCAli1bws3NDQCQkJAAIyMjWFhYaLS1s7NDQkKC1Ob5ojf38dzHCmuTlpaGx48f58kyefJkpKamSktcXNxrOUYiIiIikp+h3AH8/Pxw7tw5/P3333JHgUqlgkqlkjsGEREREZUCWXt8R40ahe3bt2P//v2oUqWKtN7e3h6ZmZlISUnRaJ+YmAh7e3upzYuzPOT+XFQbtVoNExOT1304RERERKTFZCl8hRAYNWoUfvvtN+zbtw/Ozs4ajzdu3BjlypVDRESEtO7y5cuIjY2Fh4cHAMDDwwPR0dFISkqS2uzduxdqtRqurq5Sm+e3kdsmdxtEREREpD9kGerg5+eH9evX4/fff0eFChWkMbnm5uYwMTGBubk5hgwZgsDAQFSsWBFqtRr+/v7w8PBA8+bNAQAdO3aEq6srPv74Y3z77bdISEjAF198AT8/P2m4wogRI7B48WJMmDABgwcPxr59+7Bp0ybs2LFDjsMmIiIiIhnJMp2ZQqHId31YWBgGDRoE4NkNLMaOHYuff/4ZGRkZ8PLywpIlS6RhDABw8+ZNjBw5EpGRkTAzM4OPjw++/vprGBr+r56PjIzEmDFjcOHCBVSpUgVTp06V9lGUkkyPQUREpBc4nRlpmZLUa1oxj6+2YuFLRET0Al0sfHUxMxVbSeo12Wd1ICIiLVZaBQPAooGIypzs8/gSEREREZUFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6wVDuAERvtBnmpbTd1NLZLhER0RuMhS8RUVniH0NERLLhUAciIiIi0gvs8X2dSqsnB2BvDhEREdErYo8vEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFQ7kDkMxmmJfSdlNLZ7tEREREL4k9vkRERESkF/Six/f777/H3LlzkZCQgPr162PRokVo2rSp3LGItBO/BSAiojfUG9/ju3HjRgQGBmL69Ok4efIk6tevDy8vLyQlJckdjYiIiIjK0Bvf4zt//nwMGzYMvr6+AIDQ0FDs2LEDP/74IyZNmiRzOiIieu34rQURFeCNLnwzMzNx4sQJTJ48WVqnVCrh6emJqKioPO0zMjKQkZEh/Zya+uxDLi0trXg7zBCvFrgwxc1QUqWVubTyBlUpne1OvlU629W18wvoXma+Jp7Rtc8IQPcy8zX8jK6dX0D3Muvaa0JmuXWaEMX4dxZvsNu3bwsA4vDhwxrrx48fL5o2bZqn/fTp0wUALly4cOHChQsXLjq2xMXFFVkbvtE9viU1efJkBAYGSj/n5OTg3r17sLKygkKheG37SUtLg6OjI+Li4qBWq1/bdkuTrmVm3tKna5mZt3TpWl5A9zIzb+nTtczM+4wQAg8ePICDg0ORbd/owtfa2hoGBgZITEzUWJ+YmAh7e/s87VUqFVQqlcY6CwuLUsunVqt14oX6PF3LzLylT9cyM2/p0rW8gO5lZt7Sp2uZmRcwNzcvVrs3elYHIyMjNG7cGBEREdK6nJwcREREwMPDQ8ZkRERERFTW3ugeXwAIDAyEj48PmjRpgqZNmyI4OBgPHz6UZnkgIiIiIv3wxhe+ffv2RXJyMqZNm4aEhAQ0aNAA4eHhsLOzky2TSqXC9OnT8wyr0Ga6lpl5S5+uZWbe0qVreQHdy8y8pU/XMjNvySmEKM7cD0REREREuu2NHuNLRERERJSLhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkF1j4EhEREZFeYOFLRERERHqBhS8RERER6QUWvkRERESkFwzlDqDNcnJyEB8fjwoVKkChUMgdh4iIiIheIITAgwcP4ODgAKWy8D5dFr6FiI+Ph6Ojo9wxiIiIiKgIcXFxqFKlSqFtWPgWokKFCgCenUi1Wi1zGiIiIiJ6UVpaGhwdHaW6rTAsfAuRO7xBrVaz8CUiIiLSYsUZlsqL24iIiIhIL7DwJSIiIiK9wMKXiIiIiPQCx/gSEdEbxX21e6lsN9onulS2SwXLzs5GVlaW3DFICxgZGRU5VVlxsPAlIiIirSKEQEJCAlJSUuSOQlpCqVTC2dkZRkZGr7QdFr5ERESkVXKLXltbW5iamvImUnou94Zid+7cQdWqVV/p9cDCl4iIiLRGdna2VPRaWVnJHYe0hI2NDeLj4/H06VOUK1fupbfDi9uIiIhIa+SO6TU1NZU5CWmT3CEO2dnZr7QdFr5ERESkdTi8gZ73ul4PLHyJiIiISC+w8CUiIiJ6DYQQGD58OCpWrAiFQoHTp0+X2r4UCgW2bt0KALhx40ap7+9NwYvbiIiISOuV1vzMBXmZeZvDw8OxatUqREZGonr16rC2ti60/Y0bN+Ds7IxTp06hQYMGL5kUcHR0xJ07d6T9RUZGol27drh//z4sLCxeeruvw+s6xteFhS8RERHRa3Dt2jVUqlQJLVq0KNP9GhgYwN7evkz3mZmZ+cpz6sqBQx2IiIiIXtGgQYPg7++P2NhYKBQKVKtWDeHh4WjVqhUsLCxgZWWFLl264Nq1a9JznJ2dAQANGzaEQqFA27ZtAQDHjh3Du+++C2tra5ibm6NNmzY4efJkgft+fqjDjRs30K5dOwCApaUlFAoFBg0ahDVr1sDKygoZGRkaz+3evTs+/vjjIo9vxowZaNCgAVasWAFnZ2cYGxsDwEsfIwCsWLECderUgbGxMWrXro0lS5YUmeNVsfAlIiIiekUhISGYNWsWqlSpgjt37uDYsWN4+PAhAgMDcfz4cURERECpVKJHjx7IyckBABw9ehQA8Oeff+LOnTvYsmULAODBgwfw8fHB33//jX/++QcuLi7o3LkzHjx4UGQOR0dH/PrrrwCAy5cv486dOwgJCUHv3r2RnZ2NP/74Q2qblJSEHTt2YPDgwcU6xqtXr+LXX3/Fli1bpPHEL3uM69atw7Rp0/DVV1/h4sWLmDNnDqZOnYrVq1cXK8vL4lAHIiIioldkbm6OChUqaAw76NWrl0abH3/8ETY2Nrhw4QLc3NxgY2MDALCystIYqtC+fXuN5y1btgwWFhY4cOAAunTpUmgOAwMDVKxYEQBga2urMcb3ww8/RFhYGHr37g0A+Omnn1C1alWNXtjCZGZmYs2aNVLuVznG6dOnY968eejZsyeAZz3DFy5cwNKlS+Hj41OsPC+DPb5EREREpeDKlSvo378/qlevDrVajWrVqgEAYmNjC31eYmIihg0bBhcXF5ibm0OtViM9Pb3I5xVl2LBh2LNnD27fvg0AWLVqFQYNGlTsOXKdnJw0il7g5Y7x4cOHuHbtGoYMGYLy5ctLy+zZszWGSZQG9vgSERERlYKuXbvCyckJy5cvh4ODA3JycuDm5obMzMxCn+fj44O7d+8iJCQETk5OUKlU8PDwKPJ5RWnYsCHq16+PNWvWoGPHjjh//jx27NhR7OebmZnlWfcyx5ieng4AWL58OZo1a6bxmIGBQbHzvAwWvkRERESv2d27d3H58mUsX74c77zzDgDg77//1mhT0G14Dx06hCVLlqBz584AgLi4OPz333/F3ndht/cdOnQogoODcfv2bXh6esLR0bH4B/WClz1GOzs7ODg44Pr16xgwYMBL7/9lsPAlIiIies0sLS1hZWWFZcuWoVKlSoiNjcWkSZM02tja2sLExATh4eGoUqUKjI2NYW5uDhcXF6xduxZNmjRBWloaxo8fDxMTk2Lv28nJCQqFAtu3b0fnzp1hYmKC8uXLA3g2znfcuHFYvnw51qxZI9sxzpw5E6NHj4a5uTk6deqEjIwMHD9+HPfv30dgYOAr5SoMC18iIiLSei9zQwk5KZVKbNiwAaNHj4abmxtq1aqFhQsXalxIZmhoiIULF2LWrFmYNm0a3nnnHURGRmLlypUYPnw4GjVqBEdHR8yZMwfjxo0r9r4rV66MmTNnYtKkSfD19cXAgQOxatUqAM8uwuvVqxd27NiB7t27y3aMQ4cOhampKebOnYvx48fDzMwM7u7uCAgIeKVMRVEIIUSp7kGHpaWlwdzcHKmpqVCr1XLHISKiYiitO3zpWuGlq548eYKYmBiNuWLp9erQoQPq1q2LhQsXyh2l2Ap7XZSkXmOPLxEREZEeuH//PiIjIxEZGVkmN4vQRix8iYiIiPRAw4YNcf/+fXzzzTeoVauWxmN169bFzZs3833e0qVLy/witNLCwpeIiIhID9y4caPAx3bu3ImsrKx8H7OzsyulRGWPhS8RERGRnnNycpI7QpngnduIiIhI6/Dae3re63o9sPAlIiIirVGuXDkAwKNHj2ROQtok905wr3pnNw51ICIiIq1hYGAACwsLJCUlAQBMTU2hUChkTkVyysnJQXJyMkxNTWFo+GqlKwtfIiIi0ir29vYAIBW/REqlElWrVn3lP4JY+BIREZFWUSgUqFSpEmxtbQucaYD0i5GREZTKVx+hy8KXiIiItJKBgcErj+kkeh4vbiMiIiIivcDCl4iIiIj0AgtfIiIiItILLHyJiIiISC9oVeH7/fffo1q1ajA2NkazZs1w9OjRAtueP38evXr1QrVq1aBQKBAcHPzK2yQiIiKiN5fWFL4bN25EYGAgpk+fjpMnT6J+/frw8vIqcA6/R48eoXr16vj666+l+f5edZtERERE9ObSmsJ3/vz5GDZsGHx9feHq6orQ0FCYmprixx9/zLf922+/jblz56Jfv35QqVSvZZtERERE9ObSisI3MzMTJ06cgKenp7ROqVTC09MTUVFRZbbNjIwMpKWlaSxERERE9GbQisL3v//+Q3Z2Nuzs7DTW29nZISEhocy2GRQUBHNzc2lxdHR8qX0TERERkfbRisJXW0yePBmpqanSEhcXJ3ckIiIiInpNtOKWxdbW1jAwMEBiYqLG+sTExAIvXCuNbapUqgLHCxMRERGRbtOKHl8jIyM0btwYERER0rqcnBxERETAw8NDa7ZJRERERLpLK3p8ASAwMBA+Pj5o0qQJmjZtiuDgYDx8+BC+vr4AgIEDB6Jy5coICgoC8OzitQsXLkj/f/v2bZw+fRrly5dHzZo1i7VNIiIiItIfWlP49u3bF8nJyZg2bRoSEhLQoEEDhIeHSxenxcbGQqn8Xwd1fHw8GjZsKP383Xff4bvvvkObNm0QGRlZrG0SERERkf5QCCGE3CG0VVpaGszNzZGamgq1Wi13HCIiKgb31e6lst1on+hS2S4RvZqS1GtaMcaXiIiIiKi0sfAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AILXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9IJWFb7ff/89qlWrBmNjYzRr1gxHjx4ttP3mzZtRu3ZtGBsbw93dHTt37tR4fNCgQVAoFBpLp06dSvMQiIiIiEhLaU3hu3HjRgQGBmL69Ok4efIk6tevDy8vLyQlJeXb/vDhw+jfvz+GDBmCU6dOoXv37ujevTvOnTun0a5Tp064c+eOtPz8889lcThEREREpGW0pvCdP38+hg0bBl9fX7i6uiI0NBSmpqb48ccf820fEhKCTp06Yfz48ahTpw6+/PJLNGrUCIsXL9Zop1KpYG9vLy2WlpZlcThEREREpGW0ovDNzMzEiRMn4OnpKa1TKpXw9PREVFRUvs+JiorSaA8AXl5eedpHRkbC1tYWtWrVwsiRI3H37t0Cc2RkZCAtLU1jISIiIqI3g1YUvv/99x+ys7NhZ2ensd7Ozg4JCQn5PichIaHI9p06dcKaNWsQERGBb775BgcOHMB7772H7OzsfLcZFBQEc3NzaXF0dHzFIyMiIiIibWEod4DS1K9fP+n/3d3dUa9ePdSoUQORkZHo0KFDnvaTJ09GYGCg9HNaWhqLXyIiIqI3hFb0+FpbW8PAwACJiYka6xMTE2Fvb5/vc+zt7UvUHgCqV68Oa2trXL16Nd/HVSoV1Gq1xkJEREREbwatKHyNjIzQuHFjRERESOtycnIQEREBDw+PfJ/j4eGh0R4A9u7dW2B7ALh16xbu3r2LSpUqvZ7gRERERKQztKLwBYDAwEAsX74cq1evxsWLFzFy5Eg8fPgQvr6+AICBAwdi8uTJUvvPPvsM4eHhmDdvHi5duoQZM2bg+PHjGDVqFAAgPT0d48ePxz///IMbN24gIiIC3bp1Q82aNeHl5SXLMRIRERGRfLRmjG/fvn2RnJyMadOmISEhAQ0aNEB4eLh0AVtsbCyUyv/V6S1atMD69evxxRdf4PPPP4eLiwu2bt0KNzc3AICBgQHOnj2L1atXIyUlBQ4ODujYsSO+/PJLqFQqWY6RiIiIiOSjEEIIuUNoq7S0NJibmyM1NZXjfYmIdIT7avdS2W60T3SpbJeIXk1J6jWtGepARERERFSaWPgSERERkV5g4UtEREREeoGFLxERERHpBRa+RERERKQXWPgSERERkV5g4UtEREREekFrbmBB9CbifKJERETagz2+RERERKQX2OP7GpVW7x7AHj4iIiKiV8UeXyIiIiLSCyx8iYiIiEgvsPAlIiIiIr3AwpeIiIiI9AIvbiMincYp44iIqLjY40tEREREeoE9vkREVCBO00hEbxL2+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFFr5EREREpBdY+BIRERGRXmDhS0RERER6gYUvEREREekFQ7kDEJF2cV/tXirbjfaJLpXt6hqeX6Kyx/cd5WKPLxERERHpBfb46jn+FUxERET6gj2+RERERKQX2ONLRERExcZvCkmXsceXiIiIiPQCC18iIiIi0gsc6kBERESkRTicpPRoVeH7/fffY+7cuUhISED9+vWxaNEiNG3atMD2mzdvxtSpU3Hjxg24uLjgm2++QefOnaXHhRCYPn06li9fjpSUFLRs2RI//PADXFxcyuJwqBTww4CIiIheltYUvhs3bkRgYCBCQ0PRrFkzBAcHw8vLC5cvX4atrW2e9ocPH0b//v0RFBSELl26YP369ejevTtOnjwJNzc3AMC3336LhQsXYvXq1XB2dsbUqVPh5eWFCxcuwNjYuKwPkYiIKA/+QU+6Tpdew1ozxnf+/PkYNmwYfH194erqitDQUJiamuLHH3/Mt31ISAg6deqE8ePHo06dOvjyyy/RqFEjLF68GMCz3t7g4GB88cUX6NatG+rVq4c1a9YgPj4eW7duLcMjIyIiIiJtoBU9vpmZmThx4gQmT54srVMqlfD09ERUVFS+z4mKikJgYKDGOi8vL6mojYmJQUJCAjw9PaXHzc3N0axZM0RFRaFfv355tpmRkYGMjAzp59TUVABAWlpasY4j+3F2sdq9jOJmKKnSysy8z+haXkD3MjPvM7qWF9C9zMz7jK7lBXQvM/M+U9y8ue2EEEU3Flrg9u3bAoA4fPiwxvrx48eLpk2b5vuccuXKifXr12us+/7774Wtra0QQohDhw4JACI+Pl6jTe/evUWfPn3y3eb06dMFAC5cuHDhwoULFy46tsTFxRVZc2pFj6+2mDx5skYvck5ODu7duwcrKysoFIrXtp+0tDQ4OjoiLi4OarX6tW23NOlaZuYtfbqWmXlLl67lBXQvM/OWPl3LzLzPCCHw4MEDODg4FNlWKwpfa2trGBgYIDExUWN9YmIi7O3t832Ovb19oe1z/5uYmIhKlSpptGnQoEG+21SpVFCpVBrrLCwsSnIoJaJWq3Xihfo8XcvMvKVP1zIzb+nStbyA7mVm3tKna5mZ99lw1uLQiovbjIyM0LhxY0REREjrcnJyEBERAQ8Pj3yf4+HhodEeAPbu3Su1d3Z2hr29vUabtLQ0HDlypMBtEhEREdGbSyt6fAEgMDAQPj4+aNKkCZo2bYrg4GA8fPgQvr6+AICBAweicuXKCAoKAgB89tlnaNOmDebNmwdvb29s2LABx48fx7JlywAACoUCAQEBmD17NlxcXKTpzBwcHNC9e3e5DpOIiIiIZKI1hW/fvn2RnJyMadOmISEhAQ0aNEB4eDjs7OwAALGxsVAq/9dB3aJFC6xfvx5ffPEFPv/8c7i4uGDr1q3SHL4AMGHCBDx8+BDDhw9HSkoKWrVqhfDwcNnn8FWpVJg+fXqeYRXaTNcyM2/p07XMzFu6dC0voHuZmbf06Vpm5i05hRDFmfuBiIiIiEi3acUYXyIiIiKi0sbCl4iIiIj0AgtfIiIiItILLHyJiIiISC+w8CUiIiIivcDCl4j0RnZ2Nk6fPo379+/LHSVfs2fPRkxMjNwxiu3WrVsFPvbPP/+UYRKil+Pj44ODBw/KHaNErl27hi+++AL9+/dHUlISAGDXrl04f/68zMl0A6czK2M5OTm4evUqkpKSkJOTo/FY69atZUpFcrp27RrCwsJw7do1hISEwNbWFrt27ULVqlVRt25dueMVKSUlpVRv7f0qAgIC4O7ujiFDhiA7Oxtt2rTB4cOHYWpqiu3bt6Nt27ZyR9RQv359nDt3Ds2aNcNHH32EPn36wNraWu5YBXJ1dcXff/+NihUraqw/dOgQvL29kZKSIk+wQqSkpODo0aP5fgYPHDhQplT/U7FiRfz777+wtraGpaUlFApFgW3v3btXhsmKJzExEePGjUNERASSkpLwYomRnZ0tU7L8de/eHTt37oSTkxN8fX3h4+ODypUryx2rQAcOHMB7772Hli1b4uDBg7h48SKqV6+Or7/+GsePH8cvv/wid0Stx8K3DP3zzz/48MMPcfPmzTwfBgqFQus+EABg7dq1CA0NRUxMDKKiouDk5ITg4GA4OzujW7ducscr8hfD87Txl4SufYh98803qFatGvr27QsA6NOnD3799VfY29tj586dqF+/vswJNVWpUgVbt25FkyZNsHXrVvj5+WH//v1Yu3Yt9u3bh0OHDskdMY/z589j3bp12LBhA27duoV3330XAwYMQPfu3WFqaip3PA2DBw/G2bNnsX//flSoUAEAcPDgQXTt2hUzZszAmDFjZE6oadu2bRgwYADS09OhVqs1PjsUCoVWfEasXr0a/fr1g0qlwqpVqwr9fPPx8SnDZMXz3nvvITY2FqNGjUKlSpXy5NeG3xsvSk5Oxtq1a7F69WpcuHABnp6eGDJkCLp164Zy5crJHU+Dh4cHevfujcDAQFSoUAFnzpxB9erVcfToUfTs2bPQb2Hk9Ndff2Hp0qW4du0afvnlF1SuXBlr166Fs7MzWrVqVbZhBJWZ+vXri969e4sLFy6I+/fvi5SUFI1F2yxZskRYW1uL2bNnCxMTE3Ht2jUhhBBhYWGibdu2Mqd7ZtWqVdIyb948YWlpKfr16ydCQkJESEiI6Nevn7C0tBTz58+XO2q+mjdvLubNmyeEEKJ8+fLSOT5y5IioXLmynNHyVa1aNXHo0CEhhBB79uwRFhYWYvfu3WLIkCHi3XfflTldXiqVSsTFxQkhhBg2bJj47LPPhBBCXL9+XVSoUEHGZMXz999/i08//VTY2NhoZd7s7GzRo0cP0aZNG/HkyROxb98+Ub58eREcHCx3tHy5uLiIzz77TDx8+FDuKG+s8uXLi1OnTskd46WdOHFCjBo1ShgbGwtra2sREBAg/v33X7ljSczMzMT169eFEJq/M2JiYoRKpZIzWoF++eUXYWJiIoYOHSpUKpWUedGiReK9994r8zwsfMuQqampuHLlitwxiq1OnTrit99+E0JovsGio6OFlZWVjMny17NnT7Fo0aI86xctWiS6detW9oGKQdc+xIyNjUVsbKwQQojRo0eL4cOHCyGEuHz5srCwsJAzWr6qVq0qdu/eLZ4+fSocHR3F9u3bhRBCnDt3TivzvujUqVNi7NixonLlysLY2FjuOPnKyMgQnp6eokWLFqJ8+fL5vge1hampqfQe0wVhYWH5rs/KyhKTJk0q2zDFVKdOHXHy5Em5Y7yU+Ph48fXXX4tatWoJMzMzMXDgQNGhQwdhaGioNZ0nlStXljofnv+dsWXLFlG9enU5oxWoQYMGYvXq1UIIzcwnT54UdnZ2ZZ6HF7eVoWbNmuHq1atyxyi2mJgYNGzYMM96lUqFhw8fypCocLt370anTp3yrO/UqRP+/PNPGRIVzcLCAnfu3Mmz/tSpU1o5zszS0hJxcXEAgPDwcHh6egIAhBBaOVTH19cXffr0gZubGxQKhZT3yJEjqF27tszp8hcTE4OvvvoKdevWRZMmTXDq1CnMnDkTCQkJckcDAJw9e1ZjuXTpEmbMmIG4uDh89NFHaN26tfSYtvHy8sLx48fljlFso0ePRu/evTUuxrx8+TKaNWuGn3/+WcZkBQsODsakSZNw48YNuaMUS1ZWFn799Vd06dIFTk5O2Lx5MwICAhAfH4/Vq1fjzz//xKZNmzBr1iy5owIA+vXrh4kTJyIhIQEKhQI5OTk4dOgQxo0bpxVj1PNz+fLlfK9hMjc3l+U6AMMy36Me8/f3x9ixY5GQkAB3d/c8Y4fq1asnU7L8OTs74/Tp03ByctJYHx4ejjp16siUqmBWVlb4/fffMXbsWI31v//+O6ysrGRKVbjcD7HNmzfrxIdYz5498eGHH8LFxQV3797Fe++9B+BZoV6zZk2Z0+U1Y8YMuLm5IS4uDr1794ZKpQIAGBgYYNKkSTKny6t58+Y4duwY6tWrB19fX/Tv31/r/gBq0KABFAqFxnUKuT8vXboUy5YtgxBCK69b8Pb2xvjx43HhwoV8P4Pff/99mZLl79SpU/joo4/g7u6OsLAw/Pvvv5gwYQK6d++OJUuWyB0vX3379sWjR49Qo0YNmJqa5jnH2jCO+nmVKlVCTk4O+vfvj6NHj6JBgwZ52rRr105rLuCdM2cO/Pz84OjoiOzsbLi6uiI7OxsffvghvvjiC7nj5cve3h5Xr15FtWrVNNb//fffqF69epnn4cVtZUipzNvBnvsLQxt/SaxYsQIzZszAvHnzMGTIEKxYsQLXrl1DUFAQVqxYgX79+skdUcOqVaswdOhQvPfee2jWrBmAZz174eHhWL58OQYNGiRvwHxkZmbCz88Pq1atQnZ2NgwNDaUPsVWrVsHAwEDuiBqysrIQEhKCuLg4DBo0SPpGYMGCBahQoQKGDh0qc0LdNmXKFAwYMACurq5yRynQzZs3i932xT+a5ZbfZ3AubfwMBp7NBBQQEIDvv/8eBgYGWL16Nfr37y93rAKtXr260Me17YK8tWvXonfv3jA2NpY7SonExsbi3LlzSE9PR8OGDeHi4iJ3pAIFBQXhp59+wo8//oh3330XO3fuxM2bNzFmzBhMnToV/v7+ZZqHhW8ZKuoXhrb9kgCAdevWYcaMGbh27RoAwMHBATNnzsSQIUNkTpa/I0eOYOHChbh48SIAoE6dOhg9erRUCGsrXfoQ0yVFfT05bdq0MkpC9HK2bduGIUOG4K233sK///6LevXqYc2aNXBwcJA72hth8ODBCAkJkWYlyfXw4UP4+/vjxx9/lCnZm0MIgTlz5iAoKAiPHj0C8GzI5Lhx4/Dll1+WeR4WvlQsjx49Qnp6OmxtbeWOQjJas2ZNoY9r2/CMF8eoZ2VlISYmBoaGhqhRowZOnjwpU7L8DR48uNDHte2XcFBQEOzs7PLk/vHHH5GcnIyJEyfKlOzN8Mknn2D16tX46quvEBgYiMTERAwePBhHjhzBDz/8gD59+sgdMV/Z2dnYunWr1AFRt25dvP/++1r3DRbwbNjTnTt38vxu+++//2Bvb4+nT5/KlOx/AgMDi912/vz5pZjk1WRmZuLq1atIT0+Hq6srypcvL0sOFr4yuHDhAmJjY5GZmamxXtvGl+mi3JtBXL9+HcHBwVp5Mwhd/hCztLTU+DkrKwuPHj2CkZERTE1NtW78Xn7S0tIwaNAg9OjRAx9//LHccTT06NFD4+esrCycO3cOKSkpaN++PbZs2SJTsvxVq1YN69evR4sWLTTWHzlyBP369dOKu9AtXLgQw4cPh7GxMRYuXFho29GjR5dRquJxc3PDunXr8syP/f3332PixIlIT0+XKVnBrl69is6dO+P27duoVasWgGcXNzk6OmLHjh2oUaOGzAmfSUtLgxAClpaWuHLlCmxsbKTHsrOzsW3bNkyaNAnx8fEypnymXbt2xWqnUCiwb9++Uk7zanIvjnZ0dJQtAwvfMnT9+nX06NED0dHRGheH5E7wrQ3jyxo2bFjsG0JoW2+ZrtwM4k36EAOAK1euYOTIkRg/fjy8vLzkjlMs0dHR6Nq1q05ceZ6Tk4ORI0eiRo0amDBhgtxxNBgbG+PixYtwdnbWWH/9+nW4urriyZMnMiX7H2dnZxw/fhxWVlZ5cj5PoVDg+vXrZZisaBkZGdIFmS+6fPmyVFhqk86dO0MIgXXr1kl39Lt79y4++ugjKJVK7NixQ+aEzyiVykJ/1ykUCsycORNTpkwpw1RvpqdPn2LmzJlYuHCh9Mda+fLl4e/vj+nTp5f5TUI4q0MZ+uyzz+Ds7IyIiAg4Ozvj6NGjuHv3LsaOHYvvvvtO7ngAnt2+UVdNmjQJs2fPlu5ok6t9+/ZYvHixjMk07d+/X+4Ir5WLiwu+/vprfPTRR7h06ZLccYolNTUVqampcscoFqVSicDAQLRt21brCl9HR0ccOnQoT0F56NAhrRmD+nyvszb0QJdEQUUvAK0seoFnHRD//POPxm2srays8PXXX6Nly5YyJtO0f/9+CCHQvn17/Prrrxp5jYyM4OTkpDWv4eelpqYiOzs7z23C7927B0NDQ6jVapmSFczf3x9btmzBt99+Cw8PDwBAVFQUZsyYgbt37+KHH34o0zwsfMtQVFQU9u3bB2trayiVSiiVSrRq1QpBQUEYPXo0Tp06JXdETJ8+Xe4ILy06Ohrr16/Ps97W1hb//fefDImKposfYvkxNDTUiq8EX/TiV9tCCNy5cwdr166VpmLTBdeuXdOKsYYvGjZsGAICApCVlYX27dsDACIiIjBhwoQ80wrSy/nll1+wadOmfIfHadu3bsCzYv3Bgwd51qenp8PIyEiGRPlr06YNgGd/DFWtWrXY33TKrV+/fujatSs+/fRTjfWbNm3CH3/8gZ07d8qUrGDr16/Hhg0bND5z69WrB0dHR/Tv35+F75ssOztb6om0trZGfHw8atWqBScnJ1y+fFnmdHkdO3YMOTk5eWZEOHLkCAwMDNCkSROZkuUv92YQL/Y+aevNIADd+xD7448/NH7OLSQXL16sVb05uRYsWKDxs1KphI2NDXx8fDB58mSZUhXsxfHfued3x44dWjcNFACMHz8ed+/exaeffioVZcbGxpg4caJWnl8AuHXrFv744498C0ltG1O/cOFCTJkyBYMGDcLvv/8OX19fXLt2DceOHYOfn5/c8fLVpUsXDB8+HCtXrkTTpk0BPPudMWLECK25juXs2bNwc3ODUqlEamoqoqOjC2yrbfPrHzlyJN/Xadu2bbV2WIZKpcozhy/wbBiSLH8MleFd4vReq1atpFsA9+/fX3Tq1En8/fffYuDAgaJu3bryhsvH22+/LTZv3pxn/a+//iqaNm0qQ6LCjR07VrRq1UrcuXNHVKhQQVy5ckX8/fffonr16mLGjBlyx8uXpaWluHDhQp71Fy9eFBUrVpQhUeEUCoXGolQqhZ2dnejfv7+Ij4+XO57Oa9u2rcbSvn170bdvX7F06VKRlZUld7wCPXjwQBw9elRER0eLJ0+eyB2nQH/++acwNTUVbm5uwtDQUDRo0EBYWFgIc3Nz0a5dO7nj5VGrVi2xfv16IYTmrV6nTp0q/Pz85IxWoPv374v3339fKBQKYWRkJIyMjIRSqRTdu3cXKSkpcscTQjz7HEtMTJT+X6lU5vlsy12vbUxNTcXZs2fzrD979qwwMTGRIVHRZs6cKfr376/x2fDkyRMxYMAAWX438+K2MrR79248fPgQPXv2xNWrV9GlSxf8+++/sLKywsaNG6WvCrVF+fLlcfbs2Tx3VomJiUG9evXy/TpLTrp2MwgAMDMzwz///AN3d3eN9dHR0WjWrJk056E2ysnJAVD4TQGoZB49egQhBMzMzAAAN27cwNatW1GnTh2duXBQmzVt2hTvvfceZs6ciQoVKuDMmTOwtbXFgAED0KlTJ4wcOVLuiBpMTU1x8eJFODk5wdbWFnv37kX9+vVx5coVNG/eHHfv3pU7YoGuXLkijfmvU6eOVt3Z8ebNm9LwBl2bX79du3Zwc3PDokWLNNb7+fnh7Nmz+Ouvv2RKVrAePXogIiICKpVKmqHkzJkzyMzMRIcOHTTalsXMNRzqUIae/8VVs2ZNXLp0Cffu3YOlpaVWji9SqVRITEzMU/jeuXMHhoba99IxMjLC8uXLMXXqVJ25GUTTpk2xbNmyPB9ioaGhaNy4sUypCrdy5UosWLAAV65cAfDs4raAgACtu2vb/v37cfLkSTRv3hwtW7bE0qVL8dVXX+Hx48fo3r07Fi5cCBMTE7ljaujevTt69uyJESNGICUlBc2bN0e5cuXw33//Yf78+VpXmLVr167Qzy5tm5Xk4sWL+PnnnwE8G5f++PFjlC9fHrNmzUK3bt207vza29vj3r17cHJyQtWqVfHPP/+gfv36iImJgbb3Wbm4uGjtZ+/zxay2FbZFmT17Njw9PXHmzBmpaIyIiMCxY8ewZ88emdPlz8LCAr169dJYJ+d0ZtpXveiZFy9q0iYdO3bE5MmT8fvvv8Pc3BwAkJKSgs8//xzvvvuuzOkKVrVqVelNpY1/UDxP1z7Epk2bhvnz58Pf31/j6twxY8YgNja2yDullZXly5dj5MiRcHZ2xpQpUzB9+nR89dVX+Pjjj6FUKvHTTz9JV5prk5MnT0rjkn/55RfY2dnh1KlT+PXXXzFt2jStK8waNGig8XNWVhZOnz6Nc+fOaeWYZDMzM2lcb6VKlXDt2jVpfm9tvAC2ffv2+OOPP9CwYUP4+vpizJgx+OWXX3D8+HH07NlT7nj5KmiecoVCAWNjY9SsWRPdunWT9Xffi9cqFEZbxiXnatmyJaKiojB37lxs2rQJJiYmqFevHlauXKm1f2iEhYXJHUFTmQ+u0DM9evQQqamp0v8XtmibW7duierVqwtzc3NpzKGFhYWoVauWiI2NlTtevlasWCHq1q0rjS2rW7euWL58udyxCnXq1Cnx4YcfCldXV9G4cWPh6+sr/v33X7lj5cva2loac/i89evXCysrKxkS5a9u3bpi4cKFQgghdu3aJQwNDcWqVaukxzdt2iRq1KghV7wCmZiYiJs3bwohhOjdu7c0/i02NlZrx+/lZ/r06WLs2LFyx8ijW7duYtmyZUKIZ9cE1KxZU8yePVs0atRIdOjQQeZ0eV2/fl1kZGRIP//888/C399fLFy4UGs/I9q2bSvUarUwMzMTjRo1Eo0aNRLly5cX5ubmolmzZsLCwkJYWlqK8+fPy5Yxv/G8ujLGVxdNmzZN3LhxQ+4YEo7xLWW+vr5YuHAhKlSoAF9f30Lbat1fRXh2v/J169bhzJkz0l+W/fv3L/MJp4ujoN7IxYsXY8yYMVrTG6nLLCwscOzYsTw9C//++y+aNm2KlJQUeYK94PmxkcCzYTBnzpxBnTp1AACxsbFwcXFBRkaGnDHzqFevHoYOHYoePXrAzc0N4eHh8PDwwIkTJ+Dt7Y2EhAS5IxbL1atX0bRpU627k9/169eRnp6OevXq4eHDhxg7diwOHz4MFxcXzJ8/X+u+9i7odrp3796Fra2tVtz06EXBwcH466+/EBYWJk3HmJqaiqFDh6JVq1YYNmwYPvzwQzx+/Bi7d++WOa1uSEtLk85lWlpaoW21cQrMBg0a4Ny5c2jTpg2GDBmCXr16FTpHdamTu/LWFzk5OeLmzZvi0aNHckcptvT0dLkjlIiu9EY+r3Xr1mL16tU687oYNWqUGDNmTJ71Y8eOFZ9++qkMifL3/FXbQmheES+EEAkJCVrZm7N582ZRrlw5oVQqxbvvviutnzNnjujUqZOMyUpmzZo1olKlSnLH0PD06VNx4MABcf/+fbmjFNuLr+NcN27cEKampjIkKpqDg0O+vbnnzp0TDg4OQgghTpw4obWfydpIqVTmmYXixUXbe6hPnjwp/P39hbW1tbCwsBAjRowQR48elSULx/iWESEEatasifPnz2vtOJwX2dnZoU+fPhg8eDBatWold5wiZWVl5Tu3cOPGjbVy8n/g2S2ix40bB39/f/Tp0wdDhgxB8+bN5Y6l4fkxewqFAitWrMCePXuknEeOHEFsbCwGDhwoV8Q8FAoFHjx4AGNjYwghoFAokJ6eLvWWFNVrIpcPPvgArVq1wp07d6SrnwGgQ4cO6NGjh4zJ8vfiOFPx//MOHz9+HFOnTpUpVf4MDAzQsWNHXLx4ERYWFnLHKVTue06hUGDatGkwNTWVHsvOzsaRI0fyjK/WFqmpqUhKSoKrq6vG+uTkZOl9Z2FhkWcO5bK0cOFCDB8+HMbGxnlucvOi0aNHl1Gqgu3bt08aE62rd/5s2LAhGjZsiHnz5mHbtm0ICwtDy5YtUbt2bQwZMgSDBg2SriUqbRzqUIbq1q2LlStXal1hU5CtW7di1apV2LlzJ6pVq4bBgwdj4MCBWnkbR+DZbRHLlSuXZ3LvcePG4fHjx/j+++9lSla4p0+f4o8//sDq1auxa9cu1KxZE4MHD8bHH38MOzs7ueOhXbt2xWqnUCi05ip+pVKpcWFjbvH74s/a+FWxLnlx+FbuDULat2+Pjh07ypSqYE2aNME333yTZwolbZP7njtw4AA8PDw0Jvk3MjJCtWrVMG7cOK3sRBkwYACioqIwb948vP322wCe3Qxp3LhxaNGiBdauXYsNGzbgu+++w/Hjx2XJ6OzsjOPHj8PKyirPDY+ep1AocP369TJM9ubLzMzEb7/9hh9//BH79u1DixYtEB8fj8TERCxfvhx9+/Yt9QwsfMvQtm3b8O233+KHH36Am5ub3HGKLTk5GWvXrsWqVatw8eJFeHl5YfDgwXj//fe1alozf39/rFmzBo6Ojvn2Rj4/Llnb7tCUKykpCcuWLcNXX32F7OxsdO7cGaNHj9a6OZ613YEDB4rVLve2pVRy2dnZOHToENzd3WFpaSl3nGIJDw/H5MmT8eWXX6Jx48bSfMm5tG18pK+vL0JCQrQuV2HS09MxZswYrFmzRvqmzdDQED4+PliwYAHMzMxw+vRpAHlnBaHiSUlJwdGjR5GUlCTNp55Lm755e96JEycQFhaGn3/+GSqVCgMHDsTQoUOl+Z0XLVqE2bNnIzExsdSzsPAtQ5aWlnj06BGePn0KIyOjPHOIatuFIPlZtGgRxo8fj8zMTFhbW2PEiBGYNGmSxldxctHFnsnnHT16FGFhYdiwYQPUajUGDRqE27dvY/369fj000/x3XffyR2RSIOxsTEuXrxYaK+ZNnn+Ziv8BqB0paenS72l1atXR/ny5WVOlL9Zs2Zh3LhxeX6HPX78GHPnzsW0adNkSpa/bdu2YcCAAUhPT4dardZ4HSsUCq2qI3IvzuzQoQMuXbqEjh07YtiwYejatWueG0r9999/sLW1zVPIlwYWvmVo1apVhc4rq43zXgJAYmIiVq9ejVWrVuHmzZvo0aMHhgwZglu3buGbb76Bg4ODVs45qwuSkpKwdu1ahIWF4cqVK+jatSuGDh0KLy8v6bXy999/o1OnTkhPT5c5rW4oyfhdXepJ00a6MnQg1+rVq+Ho6Jjnl25OTg5iY2O19jOYSo+uzZzx1ltvoXPnzpgzZ45WdDgVRqlUIiEhAUuXLsXgwYNRuXJluSMBYOFLhdiyZQvCwsKwe/duuLq6YujQofjoo480Lgy5du0a6tSpI+uFCvm5desWAKBKlSoyJymckZERatSogcGDB2PQoEGwsbHJ0yYtLQ3dunXT2YsaytqL43vzwx6+10PXhg7oWpGjq44fP45NmzYhNjY2z++GsrglbUkolUokJibm+ezdt28f+vbti+TkZJmS5c/MzAzR0dF57qiqjXIL3xffb3LTngGaekDXPnR9fX3Rr18/HDp0SLpI4UUODg6YMmVKGSfLX05ODmbPno158+ZJvaMVKlTA2LFjMWXKFI2vObVFREQE3nnnnULbqNVqFr0lwHNVdjp37gzg2d2tdGHowIsXOeZKT0+HsbGxDInePBs2bMDAgQPh5eWFPXv2oGPHjvj333+RmJioVTOTWFpaQqFQQKFQ4K233tJ4XWRnZyM9PR0jRoyQMWH+vLy8cPz4cZ0ofAFgxYoVRQ5zKeuZM9jjW4YK+usnPj4eNWrUwOPHj2VKlr9Hjx5p/Vcpz5s8eTJWrlyJmTNnomXLlgCeDROYMWMGhg0bhq+++krmhHnFxMTg6dOnea7OvnLlCsqVK4dq1arJE4yoGHRl6EDu9GAhISEYNmxYvtODGRgY4NChQ3JFfGPUq1cPn3zyCfz8/FChQgWcOXMGzs7O+OSTT1CpUiXMnDlT7ogAnr12hRAYPHgwgoODNabSyp05I/dGSHJ7/hbLycnJmDVrFnx9feHu7p7nZlLadItlpVKJKlWq5Pl8eJ4cM2ew8C0DufMEjhkzBl9++aXGXz/Z2dk4ePAgbty4gVOnTskVMV87d+6EgYEBvLy8NNbv3r0bOTk5eO+992RKlj8HBweEhobmeeP//vvv+PTTT3H79m2ZkhWsTZs2GDx4cJ4C4aeffsKKFSsQGRkpT7A3SEpKClauXImLFy8CeDat4ODBg8tszsg3ma58i6XL04PpGjMzM5w/fx7VqlWDlZUVIiMj4e7ujosXL6J9+/a4c+eO3BE1HDhwAC1bttSqGYpeVNxvK7XtWxYOddBjCxYsAPDsa7bQ0FCNv35yP3RDQ0PlilegSZMm4euvv86zXgiBSZMmaV3he+/ePdSuXTvP+tq1a2vVla7PO3XqlNQ7/bzmzZtj1KhRMiR6sxw/fhxeXl4wMTFB06ZNATybyu6rr77Cnj170KhRI5kT6jZdGTqQO/xFF6cH0zWWlpZ48OABAKBy5co4d+4c3N3dkZKSgkePHsmc7n/Onj0L4FneCxcuSOvNzc1RtWrVIq8TKEtlMdNBadCmc/g8Fr5lICYmBsCzXoctW7bozJyXV65cyXP3HeBZIXn16lUZEhWufv36WLx4cZ478SxevFjjLljaJPcOYy9KTU3Vqr/cddWYMWPw/vvvY/ny5VKPztOnTzF06FAEBATg4MGDMifUTc/fWWzq1Kk6c2exsLAwuSO88Vq3bo29e/fC3d0dvXv3xmeffYZ9+/Zh7969WjX7R4MGDaBQKPDil94KhQLGxsYICAjArFmzCv2aXm5PnjzRqj8wX6StAwpY+JahFy+6yc7ORnR0NJycnLSyGDY3N8f169fzjDO9evVqnqu3tcG3334Lb29v/Pnnn9LYrKioKMTGxmLXrl0yp8tf69atERQUhJ9//ln6gM3OzkZQUJBO3CZa2x0/flyj6AWeTaY/YcKEfG9vTcWTOyxLCIHo6Og8Qwfq16+PcePGyRWPZLR48WI8efIEADBlyhSUK1cOhw8fRq9evfDFF1/InO5/cjukXpSSkoITJ05g6tSpsLS01LrXcXZ2NubMmYPQ0FAkJibi33//RfXq1TF16lRUq1YNQ4YMkTuiZPr06do5f7OgMvPZZ5+JFStWCCGEePr0qWjRooVQKBTCzMxM7N+/X95w+Rg+fLhwd3cXV69eldZduXJF1KtXTwwZMkTGZAW7deuWmDJliujZs6fo2bOnmDJlirh9+7bcsQp07tw5YWVlJWrUqCEGDRokBg0aJGrUqCFsbGxEdHS03PF0nq2trdi9e3ee9eHh4cLW1laGRG+WQYMGidTUVLljkBYYOHCgWL16tbh586bcUV6LzZs3Czc3N7lj5DFz5kxRvXp18dNPPwkTExNx7do1IYQQGzZsEM2bN5c5XcEOHjwoBgwYIJo3by5u3bolhBBizZo14q+//irzLNo3v9MbbPPmzdJX7tu2bcONGzdw6dIljBkzRmumBHvet99+CzMzM9SuXRvOzs5wdnZGnTp1YGVlpbV3EbOyssL7778PX19f+Pj4oGnTpjh+/LjGVbHapG7dujh79iz69OmDpKQkPHjwAAMHDsSlS5d06rbW2qpv374YMmQINm7ciLi4OMTFxWHDhg0YOnQo+vfvL3c8nRcWFsbxsgQAuHnzJj755BM4OzujRo0aGDp0KNatW6d1F7MVV+PGjQvsFZbTmjVrsGzZMgwYMEBjGEb9+vVx6dIlGZMV7Ndff5WutTh16hQyMjIAPBvSN2fOnDLPw1kdypCxsTGuXr2KKlWqYPjw4TA1NUVwcDBiYmJQv379Et1xqqwIIbB3716cOXMGJiYmqFevHlq3bi13rHyFh4dj4MCBuHv3br7jtrRtzGxWVhY6deqE0NBQXk1eSjIzMzF+/HiEhobi6dOnAIBy5cph5MiR+Prrr6FSqWROSPTmyMjIwOHDhxEZGYnIyEgcOXIEWVlZcHFxQbt27dC+fXv07t1b7pjFEhUVhQ8//FDril8TExNcunQJTk5O0nRx1atXx4ULF9C0aVOtvMNnw4YNMWbMGAwcOFAj86lTp/Dee+8hISGhTPNwjG8ZsrOzw4ULF1CpUiWEh4fjhx9+APBsvlxtHUCvUCjQsWNHdOzYUe4oRfL390fv3r0xbdo02NnZyR2nSOXKlZOuLKbSYWRkhJCQEAQFBeHatWsAgBo1aujU/NREukKlUqFdu3bS9HFPnjzB4cOHsWvXLixbtgzLli3TicI3OTkZU6dOlY5Dm7i6uuKvv/6Ck5OTxvpffvkFDRs2lClV4S5fvpxvh5m5uTlSUlLKPA8L3zLk6+uLPn36oFKlSlAoFPD09AQAHDlyJN9puOSwcOFCDB8+HMbGxnlmR3hRWd9tpSiJiYkIDAzUiaI310cffYSVK1fmO20cvT6mpqbSBaQseolKV2ZmJqKiohAZGYn9+/fjyJEjcHBwQK9eveSOJmnYsGG+022lpqbi1q1bqFWrFn766ScZkhVu2rRp8PHxwe3bt5GTk4MtW7bg8uXLWLNmDbZv3y53vHzZ29vj6tWreS6U//vvv2W5Ax2HOpSxX375BXFxcejduzeqVKkC4NkdZCwsLNCtWzeZ0wHOzs44fvw4rKys4OzsXGA7Oe62UpTBgwejZcuWWnVVa1H8/f2xZs0auLi4oHHjxnlmy5g/f75Myd4MungbayJddPDgQY1Ct2rVqmjTpg3atGmD1q1bS7/vtEVBd5BTq9WoVasWvLy8tPab2L/++guzZs3CmTNnkJ6ejkaNGmHatGla+81sUFAQfvrpJ/z444949913sXPnTty8eRNjxozB1KlT4e/vX6Z5WPjKRNvn33tR7stEWyekBp4NGenduzdsbGzyvZWjtvVQAyj0qzSFQoF9+/aVYZo3jy7exppIFymVSlStWhUTJ05Ez549deKbt+zsbBw6dAj16tWDhYWF3HGKZejQofjoo4/Qtm1buaMUmxACc+bMQVBQkHQTE5VKhXHjxuHLL78s8zwsfMuQLs2/l2vlypVYsGABrly5AgBwcXFBQEAAhg4dKnOyvFauXIkRI0bA2NgYVlZWGkW6NvZQU+nTxdtYE+miSZMmITIyEqdOnUKtWrXQpk0btG3bFm3atIG1tbXc8QpkbGyMixcvFvoNpzbp1q0bdu/eDRsbG/Tv3x8DBgzQ2hs0vSgzMxNXr/5fe/ceVXO6/wH8vTe5VioKNUJyr4zLYDipWAeVa05ukfs5dGQOyf2aYRyXELPcisJoXIaJMUNTQ8hIJpQpl9wqyqUURUrt3x/W7GXPzjnOr72/z96792ut1qrn21reay+sz3725/k86SgsLES7du3EzfiVfIBaFaZv8/cWL16sqFu3rmLevHmKqKgoRVRUlGLevHkKY2NjxeLFi0XHU9OwYUPFypUrFWVlZaKj/L9kZmYqMjMzRccwKDVr1lTcvHlTbf3GjRuKWrVqCUhEZNhevnyp+PHHHxVz5sxRdO3aVWFkZKRo3769ws/PT3Ho0CHR8dR07txZERMTIzrG/yQvL0+xfft2hYuLi0IulyvatWunWLlypeLevXuio+kF7vhKyN7eHtu3b0efPn1URnrcuHEDn3/+OZ4/fy46ogpLS0uEhISozTuNjIyEv78/nj17JihZxSwsLJCYmIgWLVqIjvLR2IOqXd26dUO3bt3UDmr6+/sjMTERFy9eFJSMqGrIy8tDcHAwNm/ejMLCQp0bK3ny5EnMnz8fK1asqPCcha7Pqc7KykJkZCR27dqF27dvK8c2iubl5fXRv3vkyBEtJlHHqQ4SevjwIezt7dXWy8vLUVpaKiDRf1ZaWlrhta6dO3fWmX9c7xs3bhwOHDiABQsWiI7y0RYuXKic6vDnHtTi4mL2oFbSh66xzszMxI8//ig4HZHhKS8vR2JionKWb3x8PAoLC2Fra/s/FUNS8fDwAAAMGjRIpT1OoVDo5Pz395WWluLy5ctISEjA/fv3daqvul69eqIjfBALXwnp2/y9sWPHYuvWrWqTBf64NUbXlJWVYc2aNTh16hScnJzUDrfp4oSEiIgIhIaGqvSgOjk5wcbGBn5+fix8K8nFxQW3bt3C119/rbzVyMvLC35+frC2thacjshwrFmzRlnovnz5EjY2NnB1dcXGjRvh5uamsz20p0+fFh3hf3b69Gns378f3333HcrLy+Hl5YUffvgBvXv3Fh1Naffu3aIjfBALXwnpw/y9WbNmKb+XyWQIDQ1FdHQ0unfvDuDdzOGMjAz4+vqKivhBKSkpyjcQ169fV3mmq9Mo8vLyKpzh3KZNG+Tl5QlIZHisra35BoJIyzZu3AhXV1esW7cObm5uFX66qYtcXFxER/if2NjYIC8vD/3798eOHTswcOBAnb+B8t69e3j79q3aDaW3b9+GkZGR2nxfbWOPr8R0ff7ex95Uw1FbmsEeVO3Lz8/HpUuX8OTJE5SXl6s808U3cEQkncTERERGRuLWrVsAgNatW2PUqFEVtvnpgp07d8Lb21tvxq8B795cTJw4EePGjVNZ37dvH0JDQ3HmzBlJ87DwJRIoLi4Onp6esLW1rbAH1dnZWXBC/Xb8+HH4+PigsLAQpqamaiPuuKtOpHn68mZzzpw5WLduHYyNjZU3iN25cwevXr3C7Nmz8e9//1twQsNgamqKpKQktU8B0tPT0aVLF8mvLWbhSyTYo0ePVHpQ27Ztyx5UDWnVqhU8PDywatUqXlVMJAF9ebMZERGBqVOnYu3atfjHP/6hPBNSWlqKrVu3Yu7cudi+fbtOFer6ql69ejhz5ozaWabffvsNrq6uePnypaR5WPhqmbm5+Uf3l+rKfwgknYyMDDRp0qTCvyMZGRmwtbUVkMpw1K1bFykpKULugyeqivTlzWbXrl0xatQozJw5s8LnwcHB+Pbbb3Hp0iWJkxmegQMHonbt2oiMjFReA11WVoYRI0agqKgIP/30k6R5WPhqWUREhPL73NxcfPnll+jXr5/Kx9qnTp3C4sWLP/gPkAxXtWrVkJ2dDSsrK5X13NxcWFlZ6fQoHX3g5eWFkSNHYvjw4aKjEFUJ+vJm87/lvHv3LhwdHVFUVCRxMsOTmpqKXr16wczMTNm+d+7cObx48QK//PILHBwcJM3DqQ5a9n4z97BhwxAUFITp06cr12bMmIEtW7YgJiaGhW8V9MesyD8rLCxErVq1BCTSf8eOHVN+7+npicDAQKSmpsLR0VFtxN2frzImosrp168fLl++rPOFb7Vq1VBSUvLB56WlpcrdSaqcdu3aITk5GVu2bMG1a9dQu3Zt+Pr6Yvr06bCwsJA8D3d8JWRsbIyrV69W2OD96aefKm/uIsP3x9i4TZs2YcqUKSofCZaVlSEhIQHVqlVDfHy8qIh662Nvu9P14fRE+igsLAxBQUGYMGGCTr/ZdHV1hbOzM1asWFHh80WLFuH8+fOSTxwg7eOOr4Tq16+PqKgoBAQEqKxHRUWhfv36glKRCFeuXAHwbsc3JSUFNWrUUD6rUaMGOnTogNmzZ4uKp9f+fIqciKQzZcoUAEBQUJDaM116szl79mwMGTIEb968QUBAgPLWs5ycHKxfvx4bN27E0aNHBafUX8nJyXBwcIBcLkdycvJ//F0nJyeJUr3DHV8JhYeHY/LkyXB3d0e3bt0AvLsQ4uTJk9i5cyfGjx8vNiBJbsKECdi0aZPO3wdPRGRoNm/ejNmzZ+Pt27fKK3YLCgpQvXp1rFmzBl988YXghPpLLpcjJycHVlZWkMvlkMlkqKjcFPFmiIWvxBISEhASEoK0tDQA70ZXzZgxQ1kIU9WVlZUFAPjkk08EJzEcM2bMgL29PWbMmKGyvmXLFqSnp2Pjxo1ighGRTsjKysKhQ4dw+/ZtAO+mUgwbNgxNmjQRnEy/PXjwALa2tpDJZHjw4MF//N2mTZtKlOodFr5EApWXl+PLL7/E+vXrlT3eJiYmCAgIwMKFCz+6X5UqZmNjg2PHjqFz584q60lJSRg0aJDyzQYRaU5cXBzWrVun3OBp164dAgMDeSEP6QT2+Erszp072L17N+7evYuNGzfCysoKP/30E2xtbdG+fXvR8UhiCxcuRFhYGFavXo2ePXsCAM6fP49ly5ahuLgYK1euFJxQv+Xm5io/wnyfqakpnj17JiARkWHbt28fJkyYAC8vL+UnLfHx8ejTpw/Cw8MxevRowQnV3b59G6dPn67wprklS5YISmVYdOk15o6vhOLi4uDu7o6ePXvi7NmzSEtLg52dHVavXo3Lly/j8OHDoiOSxKytrbFt2za1k85RUVHw8/PDw4cPBSUzDA4ODpg6darKCEHgXW/f1q1bkZqaKigZkWFq27Yt/v73v6uN5wwODsbOnTuVu8C6YufOnZg2bRoaNGiARo0aqd00l5SUJDCdYdC115iFr4Q+//xzeHt7Y9asWTAxMcG1a9dgZ2eHS5cuwcvLix+7VkG1atVCcnIyWrVqpbJ+8+ZNfPrpp3j9+rWgZIZh165dmD59OgIDA9G7d28AQGxsLNatW6ccJUdEmlOzZk38/vvvFY7tdHBwQHFxsaBkFWvatCn8/Pwwd+5c0VEMlq69xmwglFBKSgqGDh2qtm5lZcWPXauoDh06YMuWLWrrW7ZsQYcOHQQkMiwTJ07E+vXrERYWBjc3N7i5ueGbb77Btm3bWPQSaUGTJk0QGxurth4TE6OTB8aeP38Ob29v0TEMmq69xuzxlZCZmRmys7PRvHlzlfUrV67AxsZGUCoSac2aNfD09ERMTIzKNdYZGRmS319uiF6/fo1x48Zh2rRpePr0KR4/foyff/5ZObOTiDQrICAAM2bMwNWrV9GjRw8A73p8w8PDsWnTJsHp1Hl7eyM6OhpTp04VHcVg6dprzFYHCc2ePRsJCQk4dOgQWrVqhaSkJDx+/Bi+vr7w9fXF0qVLRUckAR4+fIitW7eqjLjz8/ODtbW14GT6r2/fvvDy8sLUqVORn5+PNm3awMjICM+ePUNwcDCmTZsmOiKRwTl69CjWr1+v8n9aYGAgBg8eLDiZuq+++grBwcHw9PSs8Ka5P49CpI8TEhKi/L6oqEinXmMWvhIqKSnBP//5T4SHh6OsrAzVq1fH27dv4ePjg/DwcN4LXkUVFxcjOTm5wtOuunK9p75q0KAB4uLi0L59e4SGhmLz5s24cuUKvvvuOyxZskTnDtoQkbT+/Ans+2QyGe7evSthGsPxn17X94l4jVn4CpCZmYmUlBQUFRWhY8eOaocAqOo4efIkfH19kZubq3arjS5d76mv6tSpgxs3bsDW1hbDhw9H+/btsXTpUmRmZqJ169Z49eqV6IhERCQhHm6TWFhYGNzd3TF06FCMGTMGQ4YMQWhoqOhYJIi/vz+8vb3x6NEjlJeXq3yx6K08e3t7fP/998jMzMSpU6fQt29fAMCTJ094TTSRhlhYWCgPaJubm8PCwuKDX1R1lZSU4ObNm3j79q3QHDzcJqElS5YgODgY/v7+KgeZZs6ciYyMDAQFBQlOSFJ7/PgxZs2axcNWWrJkyRKMHj0aM2fORJ8+fZT/7qKjo9GxY0fB6YgMw4YNG2BiYqL8/v05rfogKysLx44dQ0ZGBkpKSlSeBQcHC0plOF69egV/f39EREQAAG7dugU7Ozv4+/vDxsYG8+bNkzQPWx0kZGlpiZCQEIwaNUplPTIyEv7+/hxpVgVNnDgRPXv2xKRJk0RHMVg5OTnIzs5Ghw4dlFdAX7p0CaampmjTpo3gdEQkUmxsLAYNGgQ7OzvcuHEDDg4OuH//PhQKBTp16oRffvlFdES998UXXyA+Ph4bN25E//79kZycDDs7O0RFRWHZsmW4cuWKpHlY+ErIzMwMiYmJaNmypcr6rVu30LVrV+Tn54sJRsK8evUK3t7esLS01InTrkRElVGtWjVkZ2fDyspKZT03NxdWVlY618LVtWtXuLu7Y/ny5cqLpaysrODj44P+/ftz8osGNG3aFAcOHED37t1VLu9KT09Hp06d8OLFC0nzsNVBQmPHjsXWrVvVPjrZsWMHfHx8BKUikSIjIxEdHY1atWrhzJkzalc5svAlIn3yob20N2/eoEaNGhKn+e/S0tIQGRkJAKhevTpev34NY2NjBAUFYfDgwSx8NeDp06dqb4SAd2PORLTFsPCVWFhYGKKjo9G9e3cAQEJCAjIyMuDr64tZs2Ypf499RVXDwoULsXz5csybN0/5MTwRkb75Y26rTCZDaGgojI2Nlc/Kyspw9uxZnWwtqlu3rrKvt3Hjxrhz5w7at28PAGw/1JAuXbrgxIkT8Pf3BwBlsRsaGqo8dyElFr4Sun79Ojp16gQAuHPnDoB3c0YbNGiA69evK39P3w4G0P9fSUkJRowYwaKXiPTahg0bALzb8d22bZvKXPoaNWqgWbNm2LZtm6h4H9S9e3ecP38ebdu2hYeHBwICApCSkoIjR44oN6ioclatWgV3d3ekpqbi7du32LRpE1JTU3HhwgXExcVJnoc9vkQCzZw5E5aWlliwYIHoKERElebm5oYjR47A3NxcdJSPcvfuXRQWFsLJyQlFRUUICAjAhQsX0LJlSwQHB6Np06aiI+qt69evw8HBAcC7zb7Vq1fj2rVrKCwsRKdOnTB37lw4OjpKnouFL5FAM2bMwJ49e9ChQwc4OTmpHW5jywsRkfZMnjwZY8aMgaurq+goBkcul+Ozzz7D5MmTMXLkSOXIO9FY+BIJ5Obm9sFnMpmMo3SISO/o01zcwYMH49SpU7C0tMTIkSMxZswYdOjQQXQsg3Du3Dns3r0bhw8fRnl5Of72t79h0qRJcHZ2FpqLhS8RERFphD7OxX3+/DkOHTqE/fv349y5c2jTpg18fHwwevRoNGvWTHQ8vVdUVISDBw8iPDwc586dg729PSZNmoRx48ahUaNGkudh4UtEREQaoe9zcbOyshAZGYldu3bh9u3bwq/XNTTp6enYvXs39u7di5ycHPTv3x/Hjh2TNAMLXyIiItIIExMTXL16FS1atIC5uTnOnz+P9u3b49q1axg8eDDu378vOuIHlZaW4sSJE9i3bx9OnDgBCwsLPHz4UHQsg1NUVIRvvvkG8+fPR35+vuSXmnCGEhEREWlERXNx/6Crc3FPnz6NKVOmoGHDhhg/fjxMTU3xww8/ICsrS3Q0g3L27FmMHz8ejRo1QmBgILy8vBAfHy95Ds7xJSIiIo3Qt7m4NjY2yMvLQ//+/bFjxw4MHDgQNWvWFB3LYDx69Ajh4eEIDw9Heno6evTogZCQEAwfPhx169YVkomtDkRERKQR+jYXd+fOnfD29oaZmZnoKAbH3d0dMTExaNCgAXx9fTFx4kS0bt1adCwWvkRERESkWYMGDcKkSZMwYMAAlZv8RGPhS0RERBphZ2eHxMRE1K9fX2U9Pz8fnTp1wt27dwUlI3qHPb5ERESkEffv36/wlP6bN284IaGKKioqwurVqxEbG4snT56gvLxc5bnUb4ZY+BIREVGlvD+L9dSpU6hXr57y57KyMsTGxvIyiCpq8uTJiIuLw9ixY9G4cWPIZDKhedjqQERERJUil7+bjiqTyfDnssLIyAjNmjXD+vXrMWDAABHxSCAzMzOcOHECPXv2FB0FAHd8iYiIqJL++Pi6efPmSExMRIMGDQQnIl1hbm4OCwsL0TGUuONLRERERFqxb98+REVFISIiAnXq1BEdh4UvERERVc6vv/6K3NxclVaGPXv2YOnSpSgqKsKQIUOwefNmXg5RBXXs2BF37tyBQqFAs2bNYGRkpPI8KSlJ0jxsdSAiIqJKCQoKgqurq7LwTUlJwaRJkzB+/Hi0bdsWa9euhbW1NZYtWyY2KEluyJAhoiOo4I4vERERVUrjxo1x/PhxdOnSBQCwcOFCxMXF4fz58wCAQ4cOYenSpUhNTRUZkwhy0QGIiIhIvz1//hwNGzZU/hwXFwd3d3flz5999hkyMzNFRCPBlixZgtOnT6O4uFh0FAAsfImIiKiSGjZsiHv37gEASkpKkJSUhO7duyufv3z5Uq23k6qGX3/9FQMHDoSZmRmcnZ2xaNEixMTE4PXr10LysPAlIiKiSvHw8MC8efNw7tw5zJ8/H3Xq1IGzs7PyeXJyMlq0aCEwIYny888/Iz8/H7GxsfDw8MDly5fh5eUFMzMz/OUvf5E8Dw+3ERERUaWsWLECXl5ecHFxgbGxMSIiIlCjRg3l8127dqFv374CE5JI1atXR8+ePWFpaQkLCwuYmJjg+++/x40bNyTPwsNtREREpBEFBQUwNjZGtWrVVNbz8vJgbGysUgxT1bBjxw6cOXMGcXFxePPmDZydneHq6gpXV1c4OTlJfoUxC18iIiKqtNLSUtSuXRtXr16Fg4OD6DikI+RyOSwtLREQEAA/Pz8YGxuLzSP0TyciIiKDYGRkBFtbW5SVlYmOQjrkyJEj8PHxwbfffgtLS0v06NEDCxYsQHR0NF69eiV5Hu74EhERkUaEhYXhyJEj2Lt3LywsLETHIR1TUFCAc+fO4dChQ4iMjIRcLpd8zBkPtxEREZFGbNmyBenp6bC2tkbTpk1Rt25dledSX09LuiE3NxdxcXE4c+YMzpw5g99//x3m5uYqkz+kwsKXiIiINELXrqcl8RwdHZGWlgZzc3P06tULU6ZMgYuLC5ycnITkYasDEREREWnF119/DRcXF5058MjCl4iIiIi07o+SU+oRZu/jVAciIiLSiLKyMqxbtw5du3ZFo0aNYGFhofJFVdOePXvg6OiI2rVro3bt2nBycsLevXuFZGHhS0RERBqxfPlyBAcHY8SIESgoKMCsWbPg5eUFuVyOZcuWiY5HAgQHB2PatGnw8PDAwYMHcfDgQfTv3x9Tp07Fhg0bJM/DVgciIiLSiBYtWiAkJASenp4wMTHB1atXlWsXL17E/v37RUckiTVv3hzLly+Hr6+vynpERASWLVuGe/fuSZqHO75ERESkETk5OXB0dAQAGBsbo6CgAAAwYMAAnDhxQmQ0EiQ7Oxs9evRQW+/Roweys7Mlz8PCl4iIiDTik08+URYzLVq0QHR0NAAgMTERNWvWFBmNBLG3t8fBgwfV1g8cOICWLVtKnodzfImIiEgjhg4ditjYWHTr1g3+/v4YM2YMwsLCkJGRgZkzZ4qORwIsX74cI0aMwNmzZ9GzZ08AQHx8PGJjYyssiLWNPb5ERESkFRcvXsSFCxfQsmVLDBw4UHQcEuS3337Dhg0bkJaWBgBo27YtAgIC0LFjR8mzsPAlIiIijfjqq6/QsGFDTJw4UWV9165dePr0KebOnSsoGdE7LHyJiIhII5o1a4b9+/erHWZKSEjAyJEjJT/BT7qhvLwc6enpePLkCcrLy1We9erVS9Is7PElIiIijcjJyUHjxo3V1i0tLYWc4CfxLl68iNGjR+PBgwf4816rTCZDWVmZpHk41YGIiIg0okmTJoiPj1dbj4+Ph7W1tYBEJNrUqVPRpUsXXL9+HXl5eXj+/LnyKy8vT/I83PElIiIijZgyZQr+9a9/obS0FL179wYAxMbGYs6cOQgICBCcjkS4ffs2Dh8+DHt7e9FRALDwJSIiIg0JDAxEbm4u/Pz8UFJSAgCoVasW5s6di/nz5wtORyJ069YN6enpOlP48nAbERERaVRhYSHS0tJQu3ZttGzZkpdXVGFHjx7FokWLEBgYCEdHRxgZGak8d3JykjQPC18iIiIi0gq5XP04mUwmg0KhEHK4ja0ORERERKQVujbCjoUvEREREWmFubk5TE1NK3yWnp4ucRqOMyMiIiIiLfH09ERxcbHa+s2bN+Hq6ip5Hha+RERERKQVxsbG8PLywtu3b5VraWlpcHV1xbBhwyTPw8KXiIiIiLTiyJEjKCgogI+PDxQKBa5fvw5XV1eMGjUKmzZtkjwPpzoQERERkdbk5+fD1dUVLVu2xNmzZ+Hr64u1a9cKycLCl4iIiIg05sWLF2pr2dnZ+Otf/4oBAwZg9erVyvUPHXzTFha+RERERKQxcrkcMplMbf2PkpNzfImIiIjIIJw+fVp0hA/iji8RERERVQnc8SUiIiIircnPz8elS5fw5MkTlJeXqzzz9fWVNAt3fImIiIhIK44fPw4fHx8UFhbC1NRUpfdXJpMhLy9P0jwsfImIiIhIK1q1agUPDw+sWrUKderUER2HhS8RERERaUfdunWRkpICOzs70VEA8OY2IiIiItKSfv364fLly6JjKPFwGxERERFphaenJwIDA5GamgpHR0cYGRmpPB80aJCkedjqQERERERaIZd/uLlAxAUWLHyJiIiIqEpgqwMRERERaUVQUNAHn8lkMixevFjCNNzxJSIiIiIt6dixo8rPpaWluHfvHqpXr44WLVogKSlJ0jzc8SUiIiIirbhy5Yra2osXLzB+/HgMHTpU8jzc8SUiIiIiSaWkpGDgwIG4f/++pH8u5/gSERERkaQKCgpQUFAg+Z/LVgciIiIi0oqQkBCVnxUKBbKzs7F37164u7tLnoetDkRERESkFc2bN1f5WS6Xw9LSEr1798b8+fNhYmIiaR4WvkRERERUJbDHl4iIiIiqBBa+RERERFQlsPAlIiIioiqBhS8RERERVQksfImIiIioSmDhS0RERERVAgtfIiIiIqoS/g/YNstibGg9wwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agfat_df[['crashes','fatalities','fatality_rate']].plot.bar(subplots=True,title=['Aggregates for different agents involved','',''], figsize=(8,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56fefa7f",
   "metadata": {},
   "source": [
    "### Specific features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "be84e94d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crashes</th>\n",
       "      <th>fatalCrashes</th>\n",
       "      <th>fatalities</th>\n",
       "      <th>fatal_fraction</th>\n",
       "      <th>fatality_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bridge</th>\n",
       "      <td>4525</td>\n",
       "      <td>177</td>\n",
       "      <td>205</td>\n",
       "      <td>0.039116</td>\n",
       "      <td>0.045304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cliffBank</th>\n",
       "      <td>35260</td>\n",
       "      <td>577</td>\n",
       "      <td>635</td>\n",
       "      <td>0.016364</td>\n",
       "      <td>0.018009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ditch</th>\n",
       "      <td>31201</td>\n",
       "      <td>655</td>\n",
       "      <td>713</td>\n",
       "      <td>0.020993</td>\n",
       "      <td>0.022852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fence</th>\n",
       "      <td>69193</td>\n",
       "      <td>1068</td>\n",
       "      <td>1178</td>\n",
       "      <td>0.015435</td>\n",
       "      <td>0.017025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>guardRail</th>\n",
       "      <td>25448</td>\n",
       "      <td>365</td>\n",
       "      <td>413</td>\n",
       "      <td>0.014343</td>\n",
       "      <td>0.016229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>houseOrBuilding</th>\n",
       "      <td>7788</td>\n",
       "      <td>72</td>\n",
       "      <td>79</td>\n",
       "      <td>0.009245</td>\n",
       "      <td>0.010144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kerb</th>\n",
       "      <td>11722</td>\n",
       "      <td>139</td>\n",
       "      <td>155</td>\n",
       "      <td>0.011858</td>\n",
       "      <td>0.013223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>objectThrownOrDropped</th>\n",
       "      <td>681</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.002937</td>\n",
       "      <td>0.002937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>otherObject</th>\n",
       "      <td>7724</td>\n",
       "      <td>108</td>\n",
       "      <td>121</td>\n",
       "      <td>0.013982</td>\n",
       "      <td>0.015665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>parkedVehicle</th>\n",
       "      <td>81561</td>\n",
       "      <td>154</td>\n",
       "      <td>172</td>\n",
       "      <td>0.001888</td>\n",
       "      <td>0.002109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>phoneBoxEtc</th>\n",
       "      <td>4116</td>\n",
       "      <td>40</td>\n",
       "      <td>41</td>\n",
       "      <td>0.009718</td>\n",
       "      <td>0.009961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>postOrPole</th>\n",
       "      <td>40661</td>\n",
       "      <td>587</td>\n",
       "      <td>654</td>\n",
       "      <td>0.014436</td>\n",
       "      <td>0.016084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trafficIsland</th>\n",
       "      <td>9510</td>\n",
       "      <td>100</td>\n",
       "      <td>113</td>\n",
       "      <td>0.010515</td>\n",
       "      <td>0.011882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trafficSign</th>\n",
       "      <td>16103</td>\n",
       "      <td>200</td>\n",
       "      <td>222</td>\n",
       "      <td>0.012420</td>\n",
       "      <td>0.013786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tree</th>\n",
       "      <td>33447</td>\n",
       "      <td>943</td>\n",
       "      <td>1078</td>\n",
       "      <td>0.028194</td>\n",
       "      <td>0.032230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>waterRiver</th>\n",
       "      <td>3306</td>\n",
       "      <td>271</td>\n",
       "      <td>319</td>\n",
       "      <td>0.081972</td>\n",
       "      <td>0.096491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strayAnimal</th>\n",
       "      <td>1070</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0.003738</td>\n",
       "      <td>0.003738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>slipOrFlood</th>\n",
       "      <td>815</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>0.009816</td>\n",
       "      <td>0.011043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>roadworks</th>\n",
       "      <td>935</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>0.008556</td>\n",
       "      <td>0.009626</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       crashes  fatalCrashes  fatalities  fatal_fraction  \\\n",
       "bridge                    4525           177         205        0.039116   \n",
       "cliffBank                35260           577         635        0.016364   \n",
       "ditch                    31201           655         713        0.020993   \n",
       "fence                    69193          1068        1178        0.015435   \n",
       "guardRail                25448           365         413        0.014343   \n",
       "houseOrBuilding           7788            72          79        0.009245   \n",
       "kerb                     11722           139         155        0.011858   \n",
       "objectThrownOrDropped      681             2           2        0.002937   \n",
       "otherObject               7724           108         121        0.013982   \n",
       "parkedVehicle            81561           154         172        0.001888   \n",
       "phoneBoxEtc               4116            40          41        0.009718   \n",
       "postOrPole               40661           587         654        0.014436   \n",
       "trafficIsland             9510           100         113        0.010515   \n",
       "trafficSign              16103           200         222        0.012420   \n",
       "tree                     33447           943        1078        0.028194   \n",
       "waterRiver                3306           271         319        0.081972   \n",
       "strayAnimal               1070             4           4        0.003738   \n",
       "slipOrFlood                815             8           9        0.009816   \n",
       "roadworks                  935             8           9        0.008556   \n",
       "\n",
       "                       fatality_rate  \n",
       "bridge                      0.045304  \n",
       "cliffBank                   0.018009  \n",
       "ditch                       0.022852  \n",
       "fence                       0.017025  \n",
       "guardRail                   0.016229  \n",
       "houseOrBuilding             0.010144  \n",
       "kerb                        0.013223  \n",
       "objectThrownOrDropped       0.002937  \n",
       "otherObject                 0.015665  \n",
       "parkedVehicle               0.002109  \n",
       "phoneBoxEtc                 0.009961  \n",
       "postOrPole                  0.016084  \n",
       "trafficIsland               0.011882  \n",
       "trafficSign                 0.013786  \n",
       "tree                        0.032230  \n",
       "waterRiver                  0.096491  \n",
       "strayAnimal                 0.003738  \n",
       "slipOrFlood                 0.011043  \n",
       "roadworks                   0.009626  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fefat_df = fatal_agg1(feature_types, cas_df)\n",
    "fefat_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "949b8a8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fefat_df[['fatality_rate','fatal_fraction']].plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "02ffc178",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot: title={'center': 'Aggregates for different features involved'}>,\n",
       "       <AxesSubplot: >, <AxesSubplot: >], dtype=object)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fefat_df[['crashes','fatalities','fatality_rate']].plot.bar(subplots=True,title=['Aggregates for different features involved','',''], figsize=(8,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc763305",
   "metadata": {},
   "source": [
    "### Pair combinations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3ff2525",
   "metadata": {},
   "source": [
    "Here we look at what might be the most fatal pairings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "1ebb29cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "result = fatal_agg2(agent_types+feature_types, agent_types, cas_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "a02cdf18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_81702 th {\n",
       "  width: 40px;\n",
       "}\n",
       "#T_81702 th.col_heading {\n",
       "  writing-mode: vertical-rl;\n",
       "  transform: rotateZ(180deg);\n",
       "  height: 150px;\n",
       "  vertical-align: top;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_81702\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_81702_level0_col0\" class=\"col_heading level0 col0\" >pedestrian</th>\n",
       "      <th id=\"T_81702_level0_col1\" class=\"col_heading level0 col1\" >bicycle</th>\n",
       "      <th id=\"T_81702_level0_col2\" class=\"col_heading level0 col2\" >moped</th>\n",
       "      <th id=\"T_81702_level0_col3\" class=\"col_heading level0 col3\" >motorcycle</th>\n",
       "      <th id=\"T_81702_level0_col4\" class=\"col_heading level0 col4\" >bus</th>\n",
       "      <th id=\"T_81702_level0_col5\" class=\"col_heading level0 col5\" >schoolBus</th>\n",
       "      <th id=\"T_81702_level0_col6\" class=\"col_heading level0 col6\" >suv</th>\n",
       "      <th id=\"T_81702_level0_col7\" class=\"col_heading level0 col7\" >truck</th>\n",
       "      <th id=\"T_81702_level0_col8\" class=\"col_heading level0 col8\" >train</th>\n",
       "      <th id=\"T_81702_level0_col9\" class=\"col_heading level0 col9\" >taxi</th>\n",
       "      <th id=\"T_81702_level0_col10\" class=\"col_heading level0 col10\" >carStationWagon</th>\n",
       "      <th id=\"T_81702_level0_col11\" class=\"col_heading level0 col11\" >vanOrUtility</th>\n",
       "      <th id=\"T_81702_level0_col12\" class=\"col_heading level0 col12\" >vehicle</th>\n",
       "      <th id=\"T_81702_level0_col13\" class=\"col_heading level0 col13\" >unknownVehicleType</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row0\" class=\"row_heading level0 row0\" >pedestrian</th>\n",
       "      <td id=\"T_81702_row0_col0\" class=\"data row0 col0\" >0.037879</td>\n",
       "      <td id=\"T_81702_row0_col1\" class=\"data row0 col1\" >0.005272</td>\n",
       "      <td id=\"T_81702_row0_col2\" class=\"data row0 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row0_col3\" class=\"data row0 col3\" >0.038348</td>\n",
       "      <td id=\"T_81702_row0_col4\" class=\"data row0 col4\" >0.044213</td>\n",
       "      <td id=\"T_81702_row0_col5\" class=\"data row0 col5\" >0.041667</td>\n",
       "      <td id=\"T_81702_row0_col6\" class=\"data row0 col6\" >0.037058</td>\n",
       "      <td id=\"T_81702_row0_col7\" class=\"data row0 col7\" >0.137931</td>\n",
       "      <td id=\"T_81702_row0_col8\" class=\"data row0 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row0_col9\" class=\"data row0 col9\" >0.017341</td>\n",
       "      <td id=\"T_81702_row0_col10\" class=\"data row0 col10\" >0.026104</td>\n",
       "      <td id=\"T_81702_row0_col11\" class=\"data row0 col11\" >0.050263</td>\n",
       "      <td id=\"T_81702_row0_col12\" class=\"data row0 col12\" >0.071429</td>\n",
       "      <td id=\"T_81702_row0_col13\" class=\"data row0 col13\" >0.007194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row1\" class=\"row_heading level0 row1\" >bicycle</th>\n",
       "      <td id=\"T_81702_row1_col0\" class=\"data row1 col0\" >0.005272</td>\n",
       "      <td id=\"T_81702_row1_col1\" class=\"data row1 col1\" >0.031884</td>\n",
       "      <td id=\"T_81702_row1_col2\" class=\"data row1 col2\" >0.021277</td>\n",
       "      <td id=\"T_81702_row1_col3\" class=\"data row1 col3\" >0.039683</td>\n",
       "      <td id=\"T_81702_row1_col4\" class=\"data row1 col4\" >0.020356</td>\n",
       "      <td id=\"T_81702_row1_col5\" class=\"data row1 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row1_col6\" class=\"data row1 col6\" >0.013393</td>\n",
       "      <td id=\"T_81702_row1_col7\" class=\"data row1 col7\" >0.072792</td>\n",
       "      <td id=\"T_81702_row1_col8\" class=\"data row1 col8\" >0.200000</td>\n",
       "      <td id=\"T_81702_row1_col9\" class=\"data row1 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row1_col10\" class=\"data row1 col10\" >0.005186</td>\n",
       "      <td id=\"T_81702_row1_col11\" class=\"data row1 col11\" >0.018722</td>\n",
       "      <td id=\"T_81702_row1_col12\" class=\"data row1 col12\" >0.004237</td>\n",
       "      <td id=\"T_81702_row1_col13\" class=\"data row1 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row2\" class=\"row_heading level0 row2\" >moped</th>\n",
       "      <td id=\"T_81702_row2_col0\" class=\"data row2 col0\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col1\" class=\"data row2 col1\" >0.021277</td>\n",
       "      <td id=\"T_81702_row2_col2\" class=\"data row2 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col3\" class=\"data row2 col3\" >0.027778</td>\n",
       "      <td id=\"T_81702_row2_col4\" class=\"data row2 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col5\" class=\"data row2 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col6\" class=\"data row2 col6\" >0.008174</td>\n",
       "      <td id=\"T_81702_row2_col7\" class=\"data row2 col7\" >0.058333</td>\n",
       "      <td id=\"T_81702_row2_col8\" class=\"data row2 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col9\" class=\"data row2 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col10\" class=\"data row2 col10\" >0.001333</td>\n",
       "      <td id=\"T_81702_row2_col11\" class=\"data row2 col11\" >0.004454</td>\n",
       "      <td id=\"T_81702_row2_col12\" class=\"data row2 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row2_col13\" class=\"data row2 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row3\" class=\"row_heading level0 row3\" >motorcycle</th>\n",
       "      <td id=\"T_81702_row3_col0\" class=\"data row3 col0\" >0.038348</td>\n",
       "      <td id=\"T_81702_row3_col1\" class=\"data row3 col1\" >0.039683</td>\n",
       "      <td id=\"T_81702_row3_col2\" class=\"data row3 col2\" >0.027778</td>\n",
       "      <td id=\"T_81702_row3_col3\" class=\"data row3 col3\" >0.096210</td>\n",
       "      <td id=\"T_81702_row3_col4\" class=\"data row3 col4\" >0.078431</td>\n",
       "      <td id=\"T_81702_row3_col5\" class=\"data row3 col5\" >0.333333</td>\n",
       "      <td id=\"T_81702_row3_col6\" class=\"data row3 col6\" >0.047104</td>\n",
       "      <td id=\"T_81702_row3_col7\" class=\"data row3 col7\" >0.137356</td>\n",
       "      <td id=\"T_81702_row3_col8\" class=\"data row3 col8\" >0.428571</td>\n",
       "      <td id=\"T_81702_row3_col9\" class=\"data row3 col9\" >0.012903</td>\n",
       "      <td id=\"T_81702_row3_col10\" class=\"data row3 col10\" >0.021000</td>\n",
       "      <td id=\"T_81702_row3_col11\" class=\"data row3 col11\" >0.050612</td>\n",
       "      <td id=\"T_81702_row3_col12\" class=\"data row3 col12\" >0.019355</td>\n",
       "      <td id=\"T_81702_row3_col13\" class=\"data row3 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row4\" class=\"row_heading level0 row4\" >bus</th>\n",
       "      <td id=\"T_81702_row4_col0\" class=\"data row4 col0\" >0.044213</td>\n",
       "      <td id=\"T_81702_row4_col1\" class=\"data row4 col1\" >0.020356</td>\n",
       "      <td id=\"T_81702_row4_col2\" class=\"data row4 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row4_col3\" class=\"data row4 col3\" >0.078431</td>\n",
       "      <td id=\"T_81702_row4_col4\" class=\"data row4 col4\" >0.007407</td>\n",
       "      <td id=\"T_81702_row4_col5\" class=\"data row4 col5\" >0.028381</td>\n",
       "      <td id=\"T_81702_row4_col6\" class=\"data row4 col6\" >0.010471</td>\n",
       "      <td id=\"T_81702_row4_col7\" class=\"data row4 col7\" >0.012069</td>\n",
       "      <td id=\"T_81702_row4_col8\" class=\"data row4 col8\" >0.500000</td>\n",
       "      <td id=\"T_81702_row4_col9\" class=\"data row4 col9\" >0.008368</td>\n",
       "      <td id=\"T_81702_row4_col10\" class=\"data row4 col10\" >0.006960</td>\n",
       "      <td id=\"T_81702_row4_col11\" class=\"data row4 col11\" >0.010448</td>\n",
       "      <td id=\"T_81702_row4_col12\" class=\"data row4 col12\" >0.005226</td>\n",
       "      <td id=\"T_81702_row4_col13\" class=\"data row4 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row5\" class=\"row_heading level0 row5\" >schoolBus</th>\n",
       "      <td id=\"T_81702_row5_col0\" class=\"data row5 col0\" >0.041667</td>\n",
       "      <td id=\"T_81702_row5_col1\" class=\"data row5 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row5_col2\" class=\"data row5 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row5_col3\" class=\"data row5 col3\" >0.333333</td>\n",
       "      <td id=\"T_81702_row5_col4\" class=\"data row5 col4\" >0.028381</td>\n",
       "      <td id=\"T_81702_row5_col5\" class=\"data row5 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row5_col6\" class=\"data row5 col6\" >0.051282</td>\n",
       "      <td id=\"T_81702_row5_col7\" class=\"data row5 col7\" >0.042553</td>\n",
       "      <td id=\"T_81702_row5_col8\" class=\"data row5 col8\" ></td>\n",
       "      <td id=\"T_81702_row5_col9\" class=\"data row5 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row5_col10\" class=\"data row5 col10\" >0.027190</td>\n",
       "      <td id=\"T_81702_row5_col11\" class=\"data row5 col11\" >0.010753</td>\n",
       "      <td id=\"T_81702_row5_col12\" class=\"data row5 col12\" >0.037037</td>\n",
       "      <td id=\"T_81702_row5_col13\" class=\"data row5 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row6\" class=\"row_heading level0 row6\" >suv</th>\n",
       "      <td id=\"T_81702_row6_col0\" class=\"data row6 col0\" >0.037058</td>\n",
       "      <td id=\"T_81702_row6_col1\" class=\"data row6 col1\" >0.013393</td>\n",
       "      <td id=\"T_81702_row6_col2\" class=\"data row6 col2\" >0.008174</td>\n",
       "      <td id=\"T_81702_row6_col3\" class=\"data row6 col3\" >0.047104</td>\n",
       "      <td id=\"T_81702_row6_col4\" class=\"data row6 col4\" >0.010471</td>\n",
       "      <td id=\"T_81702_row6_col5\" class=\"data row6 col5\" >0.051282</td>\n",
       "      <td id=\"T_81702_row6_col6\" class=\"data row6 col6\" >0.010283</td>\n",
       "      <td id=\"T_81702_row6_col7\" class=\"data row6 col7\" >0.024363</td>\n",
       "      <td id=\"T_81702_row6_col8\" class=\"data row6 col8\" >0.104167</td>\n",
       "      <td id=\"T_81702_row6_col9\" class=\"data row6 col9\" >0.004963</td>\n",
       "      <td id=\"T_81702_row6_col10\" class=\"data row6 col10\" >0.007058</td>\n",
       "      <td id=\"T_81702_row6_col11\" class=\"data row6 col11\" >0.010673</td>\n",
       "      <td id=\"T_81702_row6_col12\" class=\"data row6 col12\" >0.006553</td>\n",
       "      <td id=\"T_81702_row6_col13\" class=\"data row6 col13\" >0.004292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row7\" class=\"row_heading level0 row7\" >truck</th>\n",
       "      <td id=\"T_81702_row7_col0\" class=\"data row7 col0\" >0.137931</td>\n",
       "      <td id=\"T_81702_row7_col1\" class=\"data row7 col1\" >0.072792</td>\n",
       "      <td id=\"T_81702_row7_col2\" class=\"data row7 col2\" >0.058333</td>\n",
       "      <td id=\"T_81702_row7_col3\" class=\"data row7 col3\" >0.137356</td>\n",
       "      <td id=\"T_81702_row7_col4\" class=\"data row7 col4\" >0.012069</td>\n",
       "      <td id=\"T_81702_row7_col5\" class=\"data row7 col5\" >0.042553</td>\n",
       "      <td id=\"T_81702_row7_col6\" class=\"data row7 col6\" >0.024363</td>\n",
       "      <td id=\"T_81702_row7_col7\" class=\"data row7 col7\" >0.033546</td>\n",
       "      <td id=\"T_81702_row7_col8\" class=\"data row7 col8\" >0.142857</td>\n",
       "      <td id=\"T_81702_row7_col9\" class=\"data row7 col9\" >0.003030</td>\n",
       "      <td id=\"T_81702_row7_col10\" class=\"data row7 col10\" >0.018885</td>\n",
       "      <td id=\"T_81702_row7_col11\" class=\"data row7 col11\" >0.024631</td>\n",
       "      <td id=\"T_81702_row7_col12\" class=\"data row7 col12\" >0.015472</td>\n",
       "      <td id=\"T_81702_row7_col13\" class=\"data row7 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row8\" class=\"row_heading level0 row8\" >train</th>\n",
       "      <td id=\"T_81702_row8_col0\" class=\"data row8 col0\" >0.000000</td>\n",
       "      <td id=\"T_81702_row8_col1\" class=\"data row8 col1\" >0.200000</td>\n",
       "      <td id=\"T_81702_row8_col2\" class=\"data row8 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row8_col3\" class=\"data row8 col3\" >0.428571</td>\n",
       "      <td id=\"T_81702_row8_col4\" class=\"data row8 col4\" >0.500000</td>\n",
       "      <td id=\"T_81702_row8_col5\" class=\"data row8 col5\" ></td>\n",
       "      <td id=\"T_81702_row8_col6\" class=\"data row8 col6\" >0.104167</td>\n",
       "      <td id=\"T_81702_row8_col7\" class=\"data row8 col7\" >0.142857</td>\n",
       "      <td id=\"T_81702_row8_col8\" class=\"data row8 col8\" ></td>\n",
       "      <td id=\"T_81702_row8_col9\" class=\"data row8 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row8_col10\" class=\"data row8 col10\" >0.118467</td>\n",
       "      <td id=\"T_81702_row8_col11\" class=\"data row8 col11\" >0.090909</td>\n",
       "      <td id=\"T_81702_row8_col12\" class=\"data row8 col12\" ></td>\n",
       "      <td id=\"T_81702_row8_col13\" class=\"data row8 col13\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row9\" class=\"row_heading level0 row9\" >taxi</th>\n",
       "      <td id=\"T_81702_row9_col0\" class=\"data row9 col0\" >0.017341</td>\n",
       "      <td id=\"T_81702_row9_col1\" class=\"data row9 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row9_col2\" class=\"data row9 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row9_col3\" class=\"data row9 col3\" >0.012903</td>\n",
       "      <td id=\"T_81702_row9_col4\" class=\"data row9 col4\" >0.008368</td>\n",
       "      <td id=\"T_81702_row9_col5\" class=\"data row9 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row9_col6\" class=\"data row9 col6\" >0.004963</td>\n",
       "      <td id=\"T_81702_row9_col7\" class=\"data row9 col7\" >0.003030</td>\n",
       "      <td id=\"T_81702_row9_col8\" class=\"data row9 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row9_col9\" class=\"data row9 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row9_col10\" class=\"data row9 col10\" >0.002943</td>\n",
       "      <td id=\"T_81702_row9_col11\" class=\"data row9 col11\" >0.002639</td>\n",
       "      <td id=\"T_81702_row9_col12\" class=\"data row9 col12\" >0.002445</td>\n",
       "      <td id=\"T_81702_row9_col13\" class=\"data row9 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row10\" class=\"row_heading level0 row10\" >carStationWagon</th>\n",
       "      <td id=\"T_81702_row10_col0\" class=\"data row10 col0\" >0.026104</td>\n",
       "      <td id=\"T_81702_row10_col1\" class=\"data row10 col1\" >0.005186</td>\n",
       "      <td id=\"T_81702_row10_col2\" class=\"data row10 col2\" >0.001333</td>\n",
       "      <td id=\"T_81702_row10_col3\" class=\"data row10 col3\" >0.021000</td>\n",
       "      <td id=\"T_81702_row10_col4\" class=\"data row10 col4\" >0.006960</td>\n",
       "      <td id=\"T_81702_row10_col5\" class=\"data row10 col5\" >0.027190</td>\n",
       "      <td id=\"T_81702_row10_col6\" class=\"data row10 col6\" >0.007058</td>\n",
       "      <td id=\"T_81702_row10_col7\" class=\"data row10 col7\" >0.018885</td>\n",
       "      <td id=\"T_81702_row10_col8\" class=\"data row10 col8\" >0.118467</td>\n",
       "      <td id=\"T_81702_row10_col9\" class=\"data row10 col9\" >0.002943</td>\n",
       "      <td id=\"T_81702_row10_col10\" class=\"data row10 col10\" >0.003529</td>\n",
       "      <td id=\"T_81702_row10_col11\" class=\"data row10 col11\" >0.006934</td>\n",
       "      <td id=\"T_81702_row10_col12\" class=\"data row10 col12\" >0.003606</td>\n",
       "      <td id=\"T_81702_row10_col13\" class=\"data row10 col13\" >0.001883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row11\" class=\"row_heading level0 row11\" >vanOrUtility</th>\n",
       "      <td id=\"T_81702_row11_col0\" class=\"data row11 col0\" >0.050263</td>\n",
       "      <td id=\"T_81702_row11_col1\" class=\"data row11 col1\" >0.018722</td>\n",
       "      <td id=\"T_81702_row11_col2\" class=\"data row11 col2\" >0.004454</td>\n",
       "      <td id=\"T_81702_row11_col3\" class=\"data row11 col3\" >0.050612</td>\n",
       "      <td id=\"T_81702_row11_col4\" class=\"data row11 col4\" >0.010448</td>\n",
       "      <td id=\"T_81702_row11_col5\" class=\"data row11 col5\" >0.010753</td>\n",
       "      <td id=\"T_81702_row11_col6\" class=\"data row11 col6\" >0.010673</td>\n",
       "      <td id=\"T_81702_row11_col7\" class=\"data row11 col7\" >0.024631</td>\n",
       "      <td id=\"T_81702_row11_col8\" class=\"data row11 col8\" >0.090909</td>\n",
       "      <td id=\"T_81702_row11_col9\" class=\"data row11 col9\" >0.002639</td>\n",
       "      <td id=\"T_81702_row11_col10\" class=\"data row11 col10\" >0.006934</td>\n",
       "      <td id=\"T_81702_row11_col11\" class=\"data row11 col11\" >0.009517</td>\n",
       "      <td id=\"T_81702_row11_col12\" class=\"data row11 col12\" >0.005016</td>\n",
       "      <td id=\"T_81702_row11_col13\" class=\"data row11 col13\" >0.011070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row12\" class=\"row_heading level0 row12\" >vehicle</th>\n",
       "      <td id=\"T_81702_row12_col0\" class=\"data row12 col0\" >0.071429</td>\n",
       "      <td id=\"T_81702_row12_col1\" class=\"data row12 col1\" >0.004237</td>\n",
       "      <td id=\"T_81702_row12_col2\" class=\"data row12 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row12_col3\" class=\"data row12 col3\" >0.019355</td>\n",
       "      <td id=\"T_81702_row12_col4\" class=\"data row12 col4\" >0.005226</td>\n",
       "      <td id=\"T_81702_row12_col5\" class=\"data row12 col5\" >0.037037</td>\n",
       "      <td id=\"T_81702_row12_col6\" class=\"data row12 col6\" >0.006553</td>\n",
       "      <td id=\"T_81702_row12_col7\" class=\"data row12 col7\" >0.015472</td>\n",
       "      <td id=\"T_81702_row12_col8\" class=\"data row12 col8\" ></td>\n",
       "      <td id=\"T_81702_row12_col9\" class=\"data row12 col9\" >0.002445</td>\n",
       "      <td id=\"T_81702_row12_col10\" class=\"data row12 col10\" >0.003606</td>\n",
       "      <td id=\"T_81702_row12_col11\" class=\"data row12 col11\" >0.005016</td>\n",
       "      <td id=\"T_81702_row12_col12\" class=\"data row12 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row12_col13\" class=\"data row12 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row13\" class=\"row_heading level0 row13\" >unknownVehicleType</th>\n",
       "      <td id=\"T_81702_row13_col0\" class=\"data row13 col0\" >0.007194</td>\n",
       "      <td id=\"T_81702_row13_col1\" class=\"data row13 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col2\" class=\"data row13 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col3\" class=\"data row13 col3\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col4\" class=\"data row13 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col5\" class=\"data row13 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col6\" class=\"data row13 col6\" >0.004292</td>\n",
       "      <td id=\"T_81702_row13_col7\" class=\"data row13 col7\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col8\" class=\"data row13 col8\" ></td>\n",
       "      <td id=\"T_81702_row13_col9\" class=\"data row13 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col10\" class=\"data row13 col10\" >0.001883</td>\n",
       "      <td id=\"T_81702_row13_col11\" class=\"data row13 col11\" >0.011070</td>\n",
       "      <td id=\"T_81702_row13_col12\" class=\"data row13 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row13_col13\" class=\"data row13 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row14\" class=\"row_heading level0 row14\" >bridge</th>\n",
       "      <td id=\"T_81702_row14_col0\" class=\"data row14 col0\" >0.142857</td>\n",
       "      <td id=\"T_81702_row14_col1\" class=\"data row14 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row14_col2\" class=\"data row14 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row14_col3\" class=\"data row14 col3\" >0.208955</td>\n",
       "      <td id=\"T_81702_row14_col4\" class=\"data row14 col4\" >0.125000</td>\n",
       "      <td id=\"T_81702_row14_col5\" class=\"data row14 col5\" >0.250000</td>\n",
       "      <td id=\"T_81702_row14_col6\" class=\"data row14 col6\" >0.031348</td>\n",
       "      <td id=\"T_81702_row14_col7\" class=\"data row14 col7\" >0.026820</td>\n",
       "      <td id=\"T_81702_row14_col8\" class=\"data row14 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row14_col9\" class=\"data row14 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row14_col10\" class=\"data row14 col10\" >0.038870</td>\n",
       "      <td id=\"T_81702_row14_col11\" class=\"data row14 col11\" >0.053599</td>\n",
       "      <td id=\"T_81702_row14_col12\" class=\"data row14 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row14_col13\" class=\"data row14 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row15\" class=\"row_heading level0 row15\" >cliffBank</th>\n",
       "      <td id=\"T_81702_row15_col0\" class=\"data row15 col0\" >0.075269</td>\n",
       "      <td id=\"T_81702_row15_col1\" class=\"data row15 col1\" >0.107143</td>\n",
       "      <td id=\"T_81702_row15_col2\" class=\"data row15 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row15_col3\" class=\"data row15 col3\" >0.058741</td>\n",
       "      <td id=\"T_81702_row15_col4\" class=\"data row15 col4\" >0.040462</td>\n",
       "      <td id=\"T_81702_row15_col5\" class=\"data row15 col5\" >0.062500</td>\n",
       "      <td id=\"T_81702_row15_col6\" class=\"data row15 col6\" >0.016936</td>\n",
       "      <td id=\"T_81702_row15_col7\" class=\"data row15 col7\" >0.037590</td>\n",
       "      <td id=\"T_81702_row15_col8\" class=\"data row15 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row15_col9\" class=\"data row15 col9\" >0.031250</td>\n",
       "      <td id=\"T_81702_row15_col10\" class=\"data row15 col10\" >0.014747</td>\n",
       "      <td id=\"T_81702_row15_col11\" class=\"data row15 col11\" >0.022411</td>\n",
       "      <td id=\"T_81702_row15_col12\" class=\"data row15 col12\" >0.050000</td>\n",
       "      <td id=\"T_81702_row15_col13\" class=\"data row15 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row16\" class=\"row_heading level0 row16\" >ditch</th>\n",
       "      <td id=\"T_81702_row16_col0\" class=\"data row16 col0\" >0.153846</td>\n",
       "      <td id=\"T_81702_row16_col1\" class=\"data row16 col1\" >0.081633</td>\n",
       "      <td id=\"T_81702_row16_col2\" class=\"data row16 col2\" >0.058824</td>\n",
       "      <td id=\"T_81702_row16_col3\" class=\"data row16 col3\" >0.084337</td>\n",
       "      <td id=\"T_81702_row16_col4\" class=\"data row16 col4\" >0.026667</td>\n",
       "      <td id=\"T_81702_row16_col5\" class=\"data row16 col5\" >0.105263</td>\n",
       "      <td id=\"T_81702_row16_col6\" class=\"data row16 col6\" >0.026724</td>\n",
       "      <td id=\"T_81702_row16_col7\" class=\"data row16 col7\" >0.041983</td>\n",
       "      <td id=\"T_81702_row16_col8\" class=\"data row16 col8\" >0.153846</td>\n",
       "      <td id=\"T_81702_row16_col9\" class=\"data row16 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row16_col10\" class=\"data row16 col10\" >0.019060</td>\n",
       "      <td id=\"T_81702_row16_col11\" class=\"data row16 col11\" >0.023239</td>\n",
       "      <td id=\"T_81702_row16_col12\" class=\"data row16 col12\" >0.031250</td>\n",
       "      <td id=\"T_81702_row16_col13\" class=\"data row16 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row17\" class=\"row_heading level0 row17\" >fence</th>\n",
       "      <td id=\"T_81702_row17_col0\" class=\"data row17 col0\" >0.054201</td>\n",
       "      <td id=\"T_81702_row17_col1\" class=\"data row17 col1\" >0.101695</td>\n",
       "      <td id=\"T_81702_row17_col2\" class=\"data row17 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row17_col3\" class=\"data row17 col3\" >0.106877</td>\n",
       "      <td id=\"T_81702_row17_col4\" class=\"data row17 col4\" >0.014388</td>\n",
       "      <td id=\"T_81702_row17_col5\" class=\"data row17 col5\" >0.030303</td>\n",
       "      <td id=\"T_81702_row17_col6\" class=\"data row17 col6\" >0.026064</td>\n",
       "      <td id=\"T_81702_row17_col7\" class=\"data row17 col7\" >0.040067</td>\n",
       "      <td id=\"T_81702_row17_col8\" class=\"data row17 col8\" >0.192308</td>\n",
       "      <td id=\"T_81702_row17_col9\" class=\"data row17 col9\" >0.007874</td>\n",
       "      <td id=\"T_81702_row17_col10\" class=\"data row17 col10\" >0.012191</td>\n",
       "      <td id=\"T_81702_row17_col11\" class=\"data row17 col11\" >0.023472</td>\n",
       "      <td id=\"T_81702_row17_col12\" class=\"data row17 col12\" >0.009346</td>\n",
       "      <td id=\"T_81702_row17_col13\" class=\"data row17 col13\" >0.013986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row18\" class=\"row_heading level0 row18\" >guardRail</th>\n",
       "      <td id=\"T_81702_row18_col0\" class=\"data row18 col0\" >0.085106</td>\n",
       "      <td id=\"T_81702_row18_col1\" class=\"data row18 col1\" >0.035714</td>\n",
       "      <td id=\"T_81702_row18_col2\" class=\"data row18 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row18_col3\" class=\"data row18 col3\" >0.095238</td>\n",
       "      <td id=\"T_81702_row18_col4\" class=\"data row18 col4\" >0.068182</td>\n",
       "      <td id=\"T_81702_row18_col5\" class=\"data row18 col5\" >0.181818</td>\n",
       "      <td id=\"T_81702_row18_col6\" class=\"data row18 col6\" >0.025210</td>\n",
       "      <td id=\"T_81702_row18_col7\" class=\"data row18 col7\" >0.029567</td>\n",
       "      <td id=\"T_81702_row18_col8\" class=\"data row18 col8\" >0.166667</td>\n",
       "      <td id=\"T_81702_row18_col9\" class=\"data row18 col9\" >0.011364</td>\n",
       "      <td id=\"T_81702_row18_col10\" class=\"data row18 col10\" >0.010342</td>\n",
       "      <td id=\"T_81702_row18_col11\" class=\"data row18 col11\" >0.024498</td>\n",
       "      <td id=\"T_81702_row18_col12\" class=\"data row18 col12\" >0.039474</td>\n",
       "      <td id=\"T_81702_row18_col13\" class=\"data row18 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row19\" class=\"row_heading level0 row19\" >houseOrBuilding</th>\n",
       "      <td id=\"T_81702_row19_col0\" class=\"data row19 col0\" >0.037037</td>\n",
       "      <td id=\"T_81702_row19_col1\" class=\"data row19 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row19_col2\" class=\"data row19 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row19_col3\" class=\"data row19 col3\" >0.058824</td>\n",
       "      <td id=\"T_81702_row19_col4\" class=\"data row19 col4\" >0.012987</td>\n",
       "      <td id=\"T_81702_row19_col5\" class=\"data row19 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row19_col6\" class=\"data row19 col6\" >0.008264</td>\n",
       "      <td id=\"T_81702_row19_col7\" class=\"data row19 col7\" >0.010526</td>\n",
       "      <td id=\"T_81702_row19_col8\" class=\"data row19 col8\" ></td>\n",
       "      <td id=\"T_81702_row19_col9\" class=\"data row19 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row19_col10\" class=\"data row19 col10\" >0.008677</td>\n",
       "      <td id=\"T_81702_row19_col11\" class=\"data row19 col11\" >0.014252</td>\n",
       "      <td id=\"T_81702_row19_col12\" class=\"data row19 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row19_col13\" class=\"data row19 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row20\" class=\"row_heading level0 row20\" >kerb</th>\n",
       "      <td id=\"T_81702_row20_col0\" class=\"data row20 col0\" >0.073620</td>\n",
       "      <td id=\"T_81702_row20_col1\" class=\"data row20 col1\" >0.029126</td>\n",
       "      <td id=\"T_81702_row20_col2\" class=\"data row20 col2\" >0.009524</td>\n",
       "      <td id=\"T_81702_row20_col3\" class=\"data row20 col3\" >0.044534</td>\n",
       "      <td id=\"T_81702_row20_col4\" class=\"data row20 col4\" >0.031746</td>\n",
       "      <td id=\"T_81702_row20_col5\" class=\"data row20 col5\" >0.333333</td>\n",
       "      <td id=\"T_81702_row20_col6\" class=\"data row20 col6\" >0.014493</td>\n",
       "      <td id=\"T_81702_row20_col7\" class=\"data row20 col7\" >0.023599</td>\n",
       "      <td id=\"T_81702_row20_col8\" class=\"data row20 col8\" ></td>\n",
       "      <td id=\"T_81702_row20_col9\" class=\"data row20 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row20_col10\" class=\"data row20 col10\" >0.009339</td>\n",
       "      <td id=\"T_81702_row20_col11\" class=\"data row20 col11\" >0.015640</td>\n",
       "      <td id=\"T_81702_row20_col12\" class=\"data row20 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row20_col13\" class=\"data row20 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row21\" class=\"row_heading level0 row21\" >objectThrownOrDropped</th>\n",
       "      <td id=\"T_81702_row21_col0\" class=\"data row21 col0\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col1\" class=\"data row21 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col2\" class=\"data row21 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col3\" class=\"data row21 col3\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col4\" class=\"data row21 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col5\" class=\"data row21 col5\" ></td>\n",
       "      <td id=\"T_81702_row21_col6\" class=\"data row21 col6\" >0.014706</td>\n",
       "      <td id=\"T_81702_row21_col7\" class=\"data row21 col7\" >0.006211</td>\n",
       "      <td id=\"T_81702_row21_col8\" class=\"data row21 col8\" ></td>\n",
       "      <td id=\"T_81702_row21_col9\" class=\"data row21 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col10\" class=\"data row21 col10\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col11\" class=\"data row21 col11\" >0.000000</td>\n",
       "      <td id=\"T_81702_row21_col12\" class=\"data row21 col12\" ></td>\n",
       "      <td id=\"T_81702_row21_col13\" class=\"data row21 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row22\" class=\"row_heading level0 row22\" >otherObject</th>\n",
       "      <td id=\"T_81702_row22_col0\" class=\"data row22 col0\" >0.051852</td>\n",
       "      <td id=\"T_81702_row22_col1\" class=\"data row22 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col2\" class=\"data row22 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col3\" class=\"data row22 col3\" >0.050584</td>\n",
       "      <td id=\"T_81702_row22_col4\" class=\"data row22 col4\" >0.057692</td>\n",
       "      <td id=\"T_81702_row22_col5\" class=\"data row22 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col6\" class=\"data row22 col6\" >0.015177</td>\n",
       "      <td id=\"T_81702_row22_col7\" class=\"data row22 col7\" >0.008432</td>\n",
       "      <td id=\"T_81702_row22_col8\" class=\"data row22 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col9\" class=\"data row22 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col10\" class=\"data row22 col10\" >0.010702</td>\n",
       "      <td id=\"T_81702_row22_col11\" class=\"data row22 col11\" >0.024155</td>\n",
       "      <td id=\"T_81702_row22_col12\" class=\"data row22 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row22_col13\" class=\"data row22 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row23\" class=\"row_heading level0 row23\" >parkedVehicle</th>\n",
       "      <td id=\"T_81702_row23_col0\" class=\"data row23 col0\" >0.029455</td>\n",
       "      <td id=\"T_81702_row23_col1\" class=\"data row23 col1\" >0.007918</td>\n",
       "      <td id=\"T_81702_row23_col2\" class=\"data row23 col2\" >0.005602</td>\n",
       "      <td id=\"T_81702_row23_col3\" class=\"data row23 col3\" >0.021640</td>\n",
       "      <td id=\"T_81702_row23_col4\" class=\"data row23 col4\" >0.001687</td>\n",
       "      <td id=\"T_81702_row23_col5\" class=\"data row23 col5\" >0.024390</td>\n",
       "      <td id=\"T_81702_row23_col6\" class=\"data row23 col6\" >0.002247</td>\n",
       "      <td id=\"T_81702_row23_col7\" class=\"data row23 col7\" >0.006410</td>\n",
       "      <td id=\"T_81702_row23_col8\" class=\"data row23 col8\" >0.666667</td>\n",
       "      <td id=\"T_81702_row23_col9\" class=\"data row23 col9\" >0.001326</td>\n",
       "      <td id=\"T_81702_row23_col10\" class=\"data row23 col10\" >0.001726</td>\n",
       "      <td id=\"T_81702_row23_col11\" class=\"data row23 col11\" >0.002453</td>\n",
       "      <td id=\"T_81702_row23_col12\" class=\"data row23 col12\" >0.018293</td>\n",
       "      <td id=\"T_81702_row23_col13\" class=\"data row23 col13\" >0.001650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row24\" class=\"row_heading level0 row24\" >phoneBoxEtc</th>\n",
       "      <td id=\"T_81702_row24_col0\" class=\"data row24 col0\" >0.057971</td>\n",
       "      <td id=\"T_81702_row24_col1\" class=\"data row24 col1\" >0.083333</td>\n",
       "      <td id=\"T_81702_row24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col3\" class=\"data row24 col3\" >0.113636</td>\n",
       "      <td id=\"T_81702_row24_col4\" class=\"data row24 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col5\" class=\"data row24 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col6\" class=\"data row24 col6\" >0.020492</td>\n",
       "      <td id=\"T_81702_row24_col7\" class=\"data row24 col7\" >0.032258</td>\n",
       "      <td id=\"T_81702_row24_col8\" class=\"data row24 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col9\" class=\"data row24 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col10\" class=\"data row24 col10\" >0.008523</td>\n",
       "      <td id=\"T_81702_row24_col11\" class=\"data row24 col11\" >0.012346</td>\n",
       "      <td id=\"T_81702_row24_col12\" class=\"data row24 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row24_col13\" class=\"data row24 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row25\" class=\"row_heading level0 row25\" >postOrPole</th>\n",
       "      <td id=\"T_81702_row25_col0\" class=\"data row25 col0\" >0.030488</td>\n",
       "      <td id=\"T_81702_row25_col1\" class=\"data row25 col1\" >0.062500</td>\n",
       "      <td id=\"T_81702_row25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row25_col3\" class=\"data row25 col3\" >0.195195</td>\n",
       "      <td id=\"T_81702_row25_col4\" class=\"data row25 col4\" >0.015504</td>\n",
       "      <td id=\"T_81702_row25_col5\" class=\"data row25 col5\" >0.071429</td>\n",
       "      <td id=\"T_81702_row25_col6\" class=\"data row25 col6\" >0.019551</td>\n",
       "      <td id=\"T_81702_row25_col7\" class=\"data row25 col7\" >0.016129</td>\n",
       "      <td id=\"T_81702_row25_col8\" class=\"data row25 col8\" >0.315789</td>\n",
       "      <td id=\"T_81702_row25_col9\" class=\"data row25 col9\" >0.008264</td>\n",
       "      <td id=\"T_81702_row25_col10\" class=\"data row25 col10\" >0.013245</td>\n",
       "      <td id=\"T_81702_row25_col11\" class=\"data row25 col11\" >0.013751</td>\n",
       "      <td id=\"T_81702_row25_col12\" class=\"data row25 col12\" >0.048387</td>\n",
       "      <td id=\"T_81702_row25_col13\" class=\"data row25 col13\" >0.018182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row26\" class=\"row_heading level0 row26\" >trafficIsland</th>\n",
       "      <td id=\"T_81702_row26_col0\" class=\"data row26 col0\" >0.078431</td>\n",
       "      <td id=\"T_81702_row26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row26_col2\" class=\"data row26 col2\" >0.017544</td>\n",
       "      <td id=\"T_81702_row26_col3\" class=\"data row26 col3\" >0.057751</td>\n",
       "      <td id=\"T_81702_row26_col4\" class=\"data row26 col4\" >0.013158</td>\n",
       "      <td id=\"T_81702_row26_col5\" class=\"data row26 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row26_col6\" class=\"data row26 col6\" >0.014842</td>\n",
       "      <td id=\"T_81702_row26_col7\" class=\"data row26 col7\" >0.025840</td>\n",
       "      <td id=\"T_81702_row26_col8\" class=\"data row26 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row26_col9\" class=\"data row26 col9\" >0.022727</td>\n",
       "      <td id=\"T_81702_row26_col10\" class=\"data row26 col10\" >0.008977</td>\n",
       "      <td id=\"T_81702_row26_col11\" class=\"data row26 col11\" >0.016234</td>\n",
       "      <td id=\"T_81702_row26_col12\" class=\"data row26 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row26_col13\" class=\"data row26 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row27\" class=\"row_heading level0 row27\" >trafficSign</th>\n",
       "      <td id=\"T_81702_row27_col0\" class=\"data row27 col0\" >0.049383</td>\n",
       "      <td id=\"T_81702_row27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row27_col3\" class=\"data row27 col3\" >0.118750</td>\n",
       "      <td id=\"T_81702_row27_col4\" class=\"data row27 col4\" >0.007874</td>\n",
       "      <td id=\"T_81702_row27_col5\" class=\"data row27 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row27_col6\" class=\"data row27 col6\" >0.013310</td>\n",
       "      <td id=\"T_81702_row27_col7\" class=\"data row27 col7\" >0.023939</td>\n",
       "      <td id=\"T_81702_row27_col8\" class=\"data row27 col8\" >0.200000</td>\n",
       "      <td id=\"T_81702_row27_col9\" class=\"data row27 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row27_col10\" class=\"data row27 col10\" >0.009715</td>\n",
       "      <td id=\"T_81702_row27_col11\" class=\"data row27 col11\" >0.021918</td>\n",
       "      <td id=\"T_81702_row27_col12\" class=\"data row27 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row27_col13\" class=\"data row27 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row28\" class=\"row_heading level0 row28\" >tree</th>\n",
       "      <td id=\"T_81702_row28_col0\" class=\"data row28 col0\" >0.109375</td>\n",
       "      <td id=\"T_81702_row28_col1\" class=\"data row28 col1\" >0.076923</td>\n",
       "      <td id=\"T_81702_row28_col2\" class=\"data row28 col2\" >0.093750</td>\n",
       "      <td id=\"T_81702_row28_col3\" class=\"data row28 col3\" >0.144522</td>\n",
       "      <td id=\"T_81702_row28_col4\" class=\"data row28 col4\" >0.045161</td>\n",
       "      <td id=\"T_81702_row28_col5\" class=\"data row28 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row28_col6\" class=\"data row28 col6\" >0.042791</td>\n",
       "      <td id=\"T_81702_row28_col7\" class=\"data row28 col7\" >0.058292</td>\n",
       "      <td id=\"T_81702_row28_col8\" class=\"data row28 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row28_col9\" class=\"data row28 col9\" >0.045455</td>\n",
       "      <td id=\"T_81702_row28_col10\" class=\"data row28 col10\" >0.024776</td>\n",
       "      <td id=\"T_81702_row28_col11\" class=\"data row28 col11\" >0.028539</td>\n",
       "      <td id=\"T_81702_row28_col12\" class=\"data row28 col12\" >0.057143</td>\n",
       "      <td id=\"T_81702_row28_col13\" class=\"data row28 col13\" >0.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row29\" class=\"row_heading level0 row29\" >waterRiver</th>\n",
       "      <td id=\"T_81702_row29_col0\" class=\"data row29 col0\" >0.250000</td>\n",
       "      <td id=\"T_81702_row29_col1\" class=\"data row29 col1\" >0.200000</td>\n",
       "      <td id=\"T_81702_row29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row29_col3\" class=\"data row29 col3\" >0.173077</td>\n",
       "      <td id=\"T_81702_row29_col4\" class=\"data row29 col4\" >0.250000</td>\n",
       "      <td id=\"T_81702_row29_col5\" class=\"data row29 col5\" >1.000000</td>\n",
       "      <td id=\"T_81702_row29_col6\" class=\"data row29 col6\" >0.095057</td>\n",
       "      <td id=\"T_81702_row29_col7\" class=\"data row29 col7\" >0.153409</td>\n",
       "      <td id=\"T_81702_row29_col8\" class=\"data row29 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row29_col9\" class=\"data row29 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row29_col10\" class=\"data row29 col10\" >0.072551</td>\n",
       "      <td id=\"T_81702_row29_col11\" class=\"data row29 col11\" >0.106436</td>\n",
       "      <td id=\"T_81702_row29_col12\" class=\"data row29 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row29_col13\" class=\"data row29 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row30\" class=\"row_heading level0 row30\" >strayAnimal</th>\n",
       "      <td id=\"T_81702_row30_col0\" class=\"data row30 col0\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col1\" class=\"data row30 col1\" ></td>\n",
       "      <td id=\"T_81702_row30_col2\" class=\"data row30 col2\" ></td>\n",
       "      <td id=\"T_81702_row30_col3\" class=\"data row30 col3\" >0.076923</td>\n",
       "      <td id=\"T_81702_row30_col4\" class=\"data row30 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col5\" class=\"data row30 col5\" ></td>\n",
       "      <td id=\"T_81702_row30_col6\" class=\"data row30 col6\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col7\" class=\"data row30 col7\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col8\" class=\"data row30 col8\" ></td>\n",
       "      <td id=\"T_81702_row30_col9\" class=\"data row30 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col10\" class=\"data row30 col10\" >0.003617</td>\n",
       "      <td id=\"T_81702_row30_col11\" class=\"data row30 col11\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col12\" class=\"data row30 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row30_col13\" class=\"data row30 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row31\" class=\"row_heading level0 row31\" >slipOrFlood</th>\n",
       "      <td id=\"T_81702_row31_col0\" class=\"data row31 col0\" ></td>\n",
       "      <td id=\"T_81702_row31_col1\" class=\"data row31 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col2\" class=\"data row31 col2\" ></td>\n",
       "      <td id=\"T_81702_row31_col3\" class=\"data row31 col3\" >0.037037</td>\n",
       "      <td id=\"T_81702_row31_col4\" class=\"data row31 col4\" ></td>\n",
       "      <td id=\"T_81702_row31_col5\" class=\"data row31 col5\" ></td>\n",
       "      <td id=\"T_81702_row31_col6\" class=\"data row31 col6\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col7\" class=\"data row31 col7\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col8\" class=\"data row31 col8\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col9\" class=\"data row31 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col10\" class=\"data row31 col10\" >0.011570</td>\n",
       "      <td id=\"T_81702_row31_col11\" class=\"data row31 col11\" >0.016393</td>\n",
       "      <td id=\"T_81702_row31_col12\" class=\"data row31 col12\" >0.000000</td>\n",
       "      <td id=\"T_81702_row31_col13\" class=\"data row31 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_81702_level0_row32\" class=\"row_heading level0 row32\" >roadworks</th>\n",
       "      <td id=\"T_81702_row32_col0\" class=\"data row32 col0\" >0.052632</td>\n",
       "      <td id=\"T_81702_row32_col1\" class=\"data row32 col1\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col2\" class=\"data row32 col2\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col3\" class=\"data row32 col3\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col4\" class=\"data row32 col4\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col5\" class=\"data row32 col5\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col6\" class=\"data row32 col6\" >0.015873</td>\n",
       "      <td id=\"T_81702_row32_col7\" class=\"data row32 col7\" >0.012500</td>\n",
       "      <td id=\"T_81702_row32_col8\" class=\"data row32 col8\" ></td>\n",
       "      <td id=\"T_81702_row32_col9\" class=\"data row32 col9\" >0.000000</td>\n",
       "      <td id=\"T_81702_row32_col10\" class=\"data row32 col10\" >0.009358</td>\n",
       "      <td id=\"T_81702_row32_col11\" class=\"data row32 col11\" >0.009615</td>\n",
       "      <td id=\"T_81702_row32_col12\" class=\"data row32 col12\" >0.062500</td>\n",
       "      <td id=\"T_81702_row32_col13\" class=\"data row32 col13\" >0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f83a42cfbe0>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format_vertical_headers(result['fatalfracmat_df'])"
   ]
  },
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   "id": "18356a55",
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    "So far this century, there have been 322170 crashes involving a pair `carStationWagon`'s, leading to 1137 deaths, which is more than any other pair combination on both counts. Second-most fatal combination is a `truck` and a `carStationWagon`, featuring in 38284 crashes causing 723 deaths."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4324a993",
   "metadata": {},
   "source": [
    "## Potential future work\n",
    "\n",
    "Given that we have coordinates, we can look at spatial clustering and even create a heat map for each year.\n",
    "Is there a correlation between crash hot-zones and kill-zones? \n",
    "\n",
    "What might be a useful similarity measure for crash incidents, apart from location?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "728ac672",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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