AirBNB Machine Learning Clustering.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "39ba2bdd",
   "metadata": {},
   "source": [
    "# Machine Learning Clustering\n",
    "\n",
    "Contents\n",
    "\n",
    "1) Import libraries and data set\n",
    "\n",
    "2) Data Cleaning \n",
    "\n",
    "3) Elbow Technique\n",
    "\n",
    "4) Decide the number of clusters for K-means algorithms\n",
    "\n",
    "5) Run K-means algorithm\n",
    "\n",
    "6) Attach a new column\n",
    "\n",
    "7) Visualizations\n",
    "\n",
    "8) Observations based on the clusters\n",
    "\n",
    "9) Calculate descriptive statistics for clusters\n",
    "\n",
    "10) Findings"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e21bf87",
   "metadata": {},
   "source": [
    "# 1. Importing libraries and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "338960d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import sklearn\n",
    "from sklearn.cluster import KMeans\n",
    "import pylab as pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0b3327c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This option ensures that the graphs you create are displayed within the notebook without the need to \"call\" them specifically.\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "739c704a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Turn project folder path into a string\n",
    "\n",
    "path = r'/Users/giorjeanmutuc/AirBNB NYC'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "efedf3fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import data\n",
    "\n",
    "df_clean = pd.read_csv(os.path.join(path, '01 Data', 'Prepared Data', 'AB_NYC_clean.csv'), index_col = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd2807fe",
   "metadata": {},
   "source": [
    "# 2. Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ed0e1116",
   "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>id</th>\n",
       "      <th>host_id</th>\n",
       "      <th>neighbourhood_group</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>room_type</th>\n",
       "      <th>price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>last_review</th>\n",
       "      <th>reviews_per_month</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>2787</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Kensington</td>\n",
       "      <td>40.64749</td>\n",
       "      <td>-73.97237</td>\n",
       "      <td>Private room</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>2845</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown</td>\n",
       "      <td>40.75362</td>\n",
       "      <td>-73.98377</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>2019-05-21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2</td>\n",
       "      <td>355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3647</td>\n",
       "      <td>4632</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.80902</td>\n",
       "      <td>-73.94190</td>\n",
       "      <td>Private room</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3831</td>\n",
       "      <td>4869</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Clinton Hill</td>\n",
       "      <td>40.68514</td>\n",
       "      <td>-73.95976</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5022</td>\n",
       "      <td>7192</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79851</td>\n",
       "      <td>-73.94399</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-11-19</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  host_id neighbourhood_group neighbourhood  latitude  longitude  \\\n",
       "0  2539     2787            Brooklyn    Kensington  40.64749  -73.97237   \n",
       "1  2595     2845           Manhattan       Midtown  40.75362  -73.98377   \n",
       "2  3647     4632           Manhattan        Harlem  40.80902  -73.94190   \n",
       "3  3831     4869            Brooklyn  Clinton Hill  40.68514  -73.95976   \n",
       "4  5022     7192           Manhattan   East Harlem  40.79851  -73.94399   \n",
       "\n",
       "         room_type  price  minimum_nights  number_of_reviews last_review  \\\n",
       "0     Private room    149               1                  9  2018-10-19   \n",
       "1  Entire home/apt    225               1                 45  2019-05-21   \n",
       "2     Private room    150               3                  0         NaN   \n",
       "3  Entire home/apt     89               1                270  2019-07-05   \n",
       "4  Entire home/apt     80              10                  9  2018-11-19   \n",
       "\n",
       "   reviews_per_month  calculated_host_listings_count  availability_365  \n",
       "0               0.21                               6               365  \n",
       "1               0.38                               2               355  \n",
       "2               0.00                               1               365  \n",
       "3               4.64                               1               194  \n",
       "4               0.10                               1                 0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "83c1cd88",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename columns \n",
    "\n",
    "df_clean.rename(columns = {'minimum_nights' : 'min_nights', 'number_of_reviews' : 'total_reviews','reviews_per_month' : 'reviews_per_mon','calculated_host_listings_count' : 'host_listings_count'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cb34c83d",
   "metadata": {
    "scrolled": false
   },
   "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>id</th>\n",
       "      <th>host_id</th>\n",
       "      <th>neighbourhood_group</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>room_type</th>\n",
       "      <th>price</th>\n",
       "      <th>min_nights</th>\n",
       "      <th>total_reviews</th>\n",
       "      <th>last_review</th>\n",
       "      <th>reviews_per_mon</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>2787</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Kensington</td>\n",
       "      <td>40.64749</td>\n",
       "      <td>-73.97237</td>\n",
       "      <td>Private room</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>2845</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown</td>\n",
       "      <td>40.75362</td>\n",
       "      <td>-73.98377</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>2019-05-21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2</td>\n",
       "      <td>355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3647</td>\n",
       "      <td>4632</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.80902</td>\n",
       "      <td>-73.94190</td>\n",
       "      <td>Private room</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3831</td>\n",
       "      <td>4869</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Clinton Hill</td>\n",
       "      <td>40.68514</td>\n",
       "      <td>-73.95976</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5022</td>\n",
       "      <td>7192</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79851</td>\n",
       "      <td>-73.94399</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-11-19</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  host_id neighbourhood_group neighbourhood  latitude  longitude  \\\n",
       "0  2539     2787            Brooklyn    Kensington  40.64749  -73.97237   \n",
       "1  2595     2845           Manhattan       Midtown  40.75362  -73.98377   \n",
       "2  3647     4632           Manhattan        Harlem  40.80902  -73.94190   \n",
       "3  3831     4869            Brooklyn  Clinton Hill  40.68514  -73.95976   \n",
       "4  5022     7192           Manhattan   East Harlem  40.79851  -73.94399   \n",
       "\n",
       "         room_type  price  min_nights  total_reviews last_review  \\\n",
       "0     Private room    149           1              9  2018-10-19   \n",
       "1  Entire home/apt    225           1             45  2019-05-21   \n",
       "2     Private room    150           3              0         NaN   \n",
       "3  Entire home/apt     89           1            270  2019-07-05   \n",
       "4  Entire home/apt     80          10              9  2018-11-19   \n",
       "\n",
       "   reviews_per_mon  host_listings_count  availability_365  \n",
       "0             0.21                    6               365  \n",
       "1             0.38                    2               355  \n",
       "2             0.00                    1               365  \n",
       "3             4.64                    1               194  \n",
       "4             0.10                    1                 0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "30ac0fb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop categorical columns\n",
    "\n",
    "df_clean_2 = df_clean.drop(columns = ['host_id','neighbourhood_group','neighbourhood','latitude','longitude','room_type','last_review'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "744d4494",
   "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>id</th>\n",
       "      <th>price</th>\n",
       "      <th>min_nights</th>\n",
       "      <th>total_reviews</th>\n",
       "      <th>reviews_per_mon</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2</td>\n",
       "      <td>355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3647</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3831</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5022</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  price  min_nights  total_reviews  reviews_per_mon  \\\n",
       "0  2539    149           1              9             0.21   \n",
       "1  2595    225           1             45             0.38   \n",
       "2  3647    150           3              0             0.00   \n",
       "3  3831     89           1            270             4.64   \n",
       "4  5022     80          10              9             0.10   \n",
       "\n",
       "   host_listings_count  availability_365  \n",
       "0                    6               365  \n",
       "1                    2               355  \n",
       "2                    1               365  \n",
       "3                    1               194  \n",
       "4                    1                 0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean_2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bee6c502",
   "metadata": {},
   "source": [
    "# 3. Elbow technique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ea90ba9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_cl = range(1, 10) # Defines the range of potential clusters in the data.\n",
    "kmeans = [KMeans(n_clusters=i) for i in num_cl] # Defines k-means clusters in the range assigned above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "538fa470",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-5.898018185530817e+18,\n",
       " -1.4582702072987423e+18,\n",
       " -5.977357253714834e+17,\n",
       " -3.403317815906399e+17,\n",
       " -2.289241694494747e+17,\n",
       " -1.4278400035651378e+17,\n",
       " -1.0741270237656346e+17,\n",
       " -8.363416003446456e+16,\n",
       " -6.286983052757134e+16]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score = [kmeans[i].fit(df_clean_2).score(df_clean_2) for i in range(len(kmeans))] # Creates a score that represents \n",
    "# a rate of variation for the given cluster option.\n",
    "\n",
    "score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ff5021ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the elbow curve using PyLab.\n",
    "\n",
    "pl.plot(num_cl,score)\n",
    "pl.xlabel('Number of Clusters')\n",
    "pl.ylabel('Score')\n",
    "pl.title('Elbow Curve')\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d177eb07",
   "metadata": {},
   "source": [
    "# 4. Decide the number of clusters for K-means algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19370f1a",
   "metadata": {},
   "source": [
    "#### The line curves at 2 to 3 then gradually evens out into a consistent line. This means 3 is the optimal count for the clusters."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5429d3f5",
   "metadata": {},
   "source": [
    "# 5. Run K-means algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1e08365b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the k-means object.\n",
    "\n",
    "kmeans = KMeans(n_clusters = 3, n_init = 1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cdb44919",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=3, n_init=1)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the k-means object to the data.\n",
    "\n",
    "kmeans.fit(df_clean_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de2583f2",
   "metadata": {},
   "source": [
    "# 6. Attach a new column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "20976523",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clean_2['clusters'] = kmeans.fit_predict(df_clean_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "857becf7",
   "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>id</th>\n",
       "      <th>price</th>\n",
       "      <th>min_nights</th>\n",
       "      <th>total_reviews</th>\n",
       "      <th>reviews_per_mon</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "      <th>clusters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2</td>\n",
       "      <td>355</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3647</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>365</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3831</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5022</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  price  min_nights  total_reviews  reviews_per_mon  \\\n",
       "0  2539    149           1              9             0.21   \n",
       "1  2595    225           1             45             0.38   \n",
       "2  3647    150           3              0             0.00   \n",
       "3  3831     89           1            270             4.64   \n",
       "4  5022     80          10              9             0.10   \n",
       "\n",
       "   host_listings_count  availability_365  clusters  \n",
       "0                    6               365         2  \n",
       "1                    2               355         2  \n",
       "2                    1               365         2  \n",
       "3                    1               194         2  \n",
       "4                    1                 0         2  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a8d8598d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    16847\n",
       "1    16827\n",
       "2    15221\n",
       "Name: clusters, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean_2['clusters'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20c4e609",
   "metadata": {},
   "source": [
    "# 7. Visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f190cbff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the clusters for the \"price\" and \"total_reviews\" variables.\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "ax = sns.scatterplot(x=df_clean_2['total_reviews'], y=df_clean_2['price'], hue=kmeans.labels_, s=100) \n",
    "# Here, you're subsetting `X` for the x and y arguments to avoid using their labels. \n",
    "# `hue` takes the value of the attribute `kmeans.labels_`, which is the result of running the k-means algorithm.\n",
    "# `s` represents the size of the points you want to see in the plot.\n",
    "\n",
    "ax.grid(False) # This removes the grid from the background.\n",
    "plt.xlabel('Total Reviews') # Label x-axis.\n",
    "plt.ylabel('Price') # Label y-axis.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9cd6392b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuAAAAHgCAYAAADkNtiUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzddXxcx7k//s8cWF4xmJkhdhInDjM10KRJA8W0SZsmtwy3dNt7f/22veVbpjRtqOE0bZI2DA06YIfMINuyJEuyLFw8OL8/VpataEG2tSDp8369/LJ0ZvZoZEtnnzNn5nmElBJERERERFQYSrEHQEREREQ0njAAJyIiIiIqIAbgREREREQFxACciIiIiKiAGIATERERERUQA3AiIiIiogLSij2AQqupqZEzZswo9jCIiIiIaIxbs2bNXill7buPj7sAfMaMGVi9enWxh0FEREREY5wQojHdcS5BISIiIiIqIAbgREREREQFxACciIiIiKiAxt0acCKisc6yLDQ3NyOZTBZ7KBn5fD5MmTIFuq4XeyhERAXHAJyIaIxpbm5GOBzGjBkzIIQo9nCGkFKis7MTzc3NmDlzZrGHQ0RUcFyCQkQ0xiSTSVRXV5dk8A0AQghUV1eX9Aw9EVE+MQAnIhqDSjX43qfUx0dElE8MwImIaMQ99thjmD9/PubMmYMf/vCHxR4OEVFJYQBOREQjynEcfPrTn8ajjz6KDRs24K677sKGDRuKPSwiopLBTZhEROOc0d2JRFsLXMuEonvgnzAZ3srqQz7fa6+9hjlz5mDWrFkAgKuuugoPPvggFi1aNFJDJiIa1TgDTkQ0jhndnYg1N8K1TACAa5mINTfC6O485HO2tLRg6tSpA59PmTIFLS0thz1WIqKxggE4EdE4lmhrAaQ7+KB0U8cPkZRyyDFuuiQi2o9LUAogEYtBEQJSSviCwWIPh0qUZRiQbioQUjQNGguUUAHsm/ke7vHhmDJlCpqamgY+b25uxqRJkw75fEREh8J1XZixJCAB1aNB93mKPaQBDMDzyDIMmH29cHo74ZiptZV2RRW8ZRXQvd5iD49KhGkYEK6DxJ42uPEoIAAlWIZA3QRAURmIU14puidtsK3oh/5Gdcwxx2Dr1q3YsWMHJk+ejLvvvht33nnn4QyTiOigGJEEmt7Yih0vrYOVNFE1vR4L33MM/BVheALFj8HyFoALIf4C4EIAe6SUS/qPVQG4B8AMADsBXCGl7O5v+waAawE4AD4npXy8//jRAG4B4AfwCIDPSymlEMIL4DYARwPoBHCllHJnvr6fg2UbBuJN2+HEYwPHHNuCk4jB7u1GaOpMaAzCxz3LMGHHokg27xh03DX3oq+nC8EZcyEUBaqqFmmENNb5J0xGrLlx8DIUocA/YfIhn1PTNPzmN7/BueeeC8dxcM0112Dx4sUjMFoiotzi3RE889P7EO/sGzgW3dODXa9vxvLLT8WMExbB4y9uDJbPNeC3ADjvXce+DuBpKeVcAE/3fw4hxCIAVwFY3P+a3wkh9kUcvwdwHYC5/X/2nfNaAN1SyjkAfg7gR3n7Tg6SZdlIdHYMCr4P5MajiO/dA8u0CjwyKjUCEsmWnekbpYt4UwOkbRd0TDS+eCurEZwyfWDGW9E9CE6ZflhZUADg/PPPx5YtW9DQ0ID/+q//GomhEhHlZMQSePXmxwcF3wd6677nkOxNH58VUt4CcCnl8wC63nX4YgC39n98K4BLDjh+t5TSkFLuALANwLFCiIkAyqSUq2RqV89t73rNvnPdD+BMUSK7fKRjw+7NnkHA6e0EXKdAI6JSlezaC6TZsLaPtG2YGW7kiEaKt7IaFQuPQNURK1Cx8IjDDr6JiIrFNix0bGnO2mfT46thGYe+z2UkFDoLSr2UshUA+v+u6z8+GUDTAf2a+49N7v/43ccHvUZKaQPoBVAS7xpCANLKPrstbRsoidsFKhbbsgDLyN2PATgREdGwxDp6c/bpaeqAYxb36XKppCFMF4rKLMezvWboyYW4TgixWgixuqOj4xCHOHwCIhWF5+zFCHw8E4oCqeT+FRQq90oTERENhz6Mtd2azwMxjPfffCr0V2/vX1aC/r/39B9vBjD1gH5TAOzuPz4lzfFBrxFCaADKMXTJCwBASnmjlHKFlHJFbW3tCH0rmVmOAy1ckbWPFi6DZXMJynimqio8lTU5egn4K6sKMh4iIqLRLlAZgjccyNpnzqlHwBv0FWhE6RU6AH8IwNX9H18N4MEDjl8lhPAKIWYitdnytf5lKhEhxHH967s/+q7X7DvX+wE8I9NVfygCfyAA/4RJEEqGzBVKKsOAP5j9B4TGPqFqUIJlGdu1yho4rpuxnYiIiPbT/V4sf//JGdvDEypRv3BaAUeUXt4CcCHEXQBWAZgvhGgWQlwL4IcAzhZCbAVwdv/nkFKuB3AvgA0AHgPwaSnlvunhGwDchNTGzAYAj/Yf/zOAaiHENgBfQn9GlVLhCgXBWfOhBUKDjmuBIEIz58MVpbL6h4rJ4/MhNGU69Kpa4IDHYULVoNdOhL9uArx+fxFHSERENHoomoqJS2dh5bXvgb9if/FDIQQmLZuF0774fnhDxX9fFSUyaVwwK1askKtXry7Y10vG41BVBa5pQfXosB0XvgBnvmkwI2lAVQDHNAEhoGo6pFCge1iEhw7exo0bsXDhwqKO4ZprrsE///lP1NXVYd26dWn7lMI4iWhsch0XZjwJI5KAbVgIVIWh6lrBi/AIIdZIKVe8+zinYfPMFwhA9/rgDYeheX0Mviktr88LzeOFNxSGNxiC5vUy+KZR7WMf+xgee+yxYg+DiMYpRVXgCwdQPqka1TMnwF8eLIkKmPswvQIR0TjX+OomrH3wJcS7IghUhbH04hMxfeWCwzrnKaecgp07d47MAImIxhgG4ERE41jjq5uw+o6nBnLixrsiWH3HUwBw2EE4ERGlxyUoRETj2NoHXxpSkMIxbax98KUijYiIaOxjAE5ENI7FuyIHdZyIiA4fA3AionEsUBU+qONERHT4GIATEY1jSy8+Eapn8HYg1aNh6cUnHtZ5P/CBD+D444/H5s2bMWXKFPz5z38+rPMREY0l3IRJRDSO7dtoOdJZUO66666RGB4R0ZjEAJyIaJybvnIBM54QERUQl6AQERERERUQA3AiIiIiogJiAE5EREREVEAMwImIiIiICogBOBERERFRATEAJyKiEdXU1ITTTz8dCxcuxOLFi/HLX/6y2EMiIiopTENIREQjStM0/OxnP8NRRx2FSCSCo48+GmeffTYWLVpU7KEREZUEzoATEY1z//rHkzj3hCuwbMZpOPeEK/Cvfzx5WOebOHEijjrqKABAOBzGwoUL0dLSMhJDJSIaEzgDTkQ0jv3rH0/iO1//CZIJAwDQ2tKO73z9JwCACy45+7DPv3PnTrz55ptYuXLlYZ+LiGis4Aw4EdE49qsf/2kg+N4nmTDwqx//6bDPHY1Gcdlll+EXv/gFysrKDvt8RERjBQNwIqJxrG33noM6PlyWZeGyyy7Dhz70IVx66aWHdS4iorGGATgR0Tg2YVLdQR0fDiklrr32WixcuBBf+tKXDvk8RERjFQNwIqJx7HNf/SR8fu+gYz6/F5/76icP+ZwvvfQSbr/9djzzzDNYvnw5li9fjkceeeRwh0pENGZwEyYR0Ti2b6Plr378J7Tt3oMJk+rwua9+8rA2YJ500kmQUo7UEImIxhwG4ERE49wFl5w9IhlPiIhoeLgEhYiIiIiogBiAExEREREVEANwIqIxqNTXYJf6+IiI8okBOBHRGOPz+dDZ2VmyQa6UEp2dnfD5fMUeChFRUXATJhHRGDNlyhQ0Nzejo6Oj2EPJyOfzYcqUKcUeBhFRUTAAJyIaY3Rdx8yZM4s9DCIiyoBLUIiIiIiICogBOBERERFRATEAJyIiIiIqIAbgREREREQFxACciIiIiKiAGIATERERERUQA3AiIiIiogJiAE5EREREVEAMwImIiIiICogBOBERERFRATEAJyIiIiIqIAbgREREREQFxACciIiIiKiAGIATERERERUQA3AiIiIiogJiAE5EREREVEAMwImIiIiICogBOBERERFRATEAJyIiIiIqIK3YAyAiIqL8cW0LrmXB6O4EpIReVg7NH4BQNQghij08onGJATgREdEY5doWojsbYMejA8eMzj1QdB3hWfOheLwMwomKgEtQiIiIxiDXthHbtWNQ8D3QZlnoa9gM6dhFGBkRMQAnIiIag6TjwIr2ZW63LVjRSAFHRET7MAAnIiIag6xY7uDa7OmC6zgFGA0RHYgBOBERERFRATEAJyIiGoP0UDhnH29FFRRVLcBoiOhADMCJiIjGIKGo0MPlmds1HdowgnQiGnkMwImIiMYgRdMQnDoDWnBokK3oHpTNXgChMhsxUTHwN4+IiGiMUjQdoemzIW0LRk8XpCvhKSuH6vOxEA9RETEAJyIiGsMUTQM0DYEJk4s9FCLqxyUoREREREQFxACciIiIiKiAGIATERERERUQA3AiIiIiogJiAE5EREREVEAMwImIiIiICogBOBERERFRATEAJyIiIiIqIBbiISIiIqIxR0qJ3u4+uNKF3++DP+Av9pAGMAAnIiIiojGlu6sHzz/zCv5218OIReNYunwhPvapD6CmrgqhULDYwyvOEhQhxBeFEOuFEOuEEHcJIXxCiCohxJNCiK39f1ce0P8bQohtQojNQohzDzh+tBBibX/br4QQohjfDxERERGVho72vfjwJf+Bb3/5B3hr9Tps3bQdD9z9L7z39A/jkQefRjQSK/YQCx+ACyEmA/gcgBVSyiUAVABXAfg6gKellHMBPN3/OYQQi/rbFwM4D8DvhBBq/+l+D+A6AHP7/5xXwG+FiIiIiEpIb08f/utLP0BTY0va9u9982fo3NtV4FENVaxNmBoAvxBCAxAAsBvAxQBu7W+/FcAl/R9fDOBuKaUhpdwBYBuAY4UQEwGUSSlXSSklgNsOeA0RERERjTOJeBKvvLg6a5+b/3g3EolkgUaUXsEDcCllC4CfAtgFoBVAr5TyCQD1UsrW/j6tAOr6XzIZQNMBp2juPza5/+N3HyciIiKicahp1+6cfda/vQmJeKIAo8msGEtQKpGa1Z4JYBKAoBDiw9lekuaYzHI83de8TgixWgixuqOj42CHTERERESjQCDgy9knGAxAUYqbibsYX/0sADuklB1SSgvAAwBOANDev6wE/X/v6e/fDGDqAa+fgtSSleb+j999fAgp5Y1SyhVSyhW1tbUj+s0QERERUWmYOHkCKirLs/a57IMXobyirEAjSq8YAfguAMcJIQL9WUvOBLARwEMAru7vczWAB/s/fgjAVUIIrxBiJlKbLV/rX6YSEUIc13+ejx7wGiIiIiIaZ8JlQXzpm9dnbJ8+cwpOOm0lip04r+B5wKWUrwoh7gfwBgAbwJsAbgQQAnCvEOJapIL0y/v7rxdC3AtgQ3//T0spnf7T3QDgFgB+AI/2/yEiIiKicUjXdZx53smAEPjFD/6Ars4eAIAQAieccgz+30++hsqq7DPkhSBSCUTGjxUrVsjVq7PvjiUiIiKi0cuyLET6Ymjb3Y54PIGp0ybD5/ehvCJc0HEIIdZIKVe8+zgrYRIRERHRmKLrOqqqK1BVXVHsoaTFAJyIaJhc29qfa0kAiqYXdTxERDQ6MQAnIsrBdWw48Tjibc1wEnEAgOoPIDBhCtRAAIrKSykREQ1fcZMgEhGVONdxYPZ0IbJjy0DwDQBOIo7Iji0wu7vgOk6WMxAREQ3GAJyIKBvXRbylKWNzfHcT4LoFHBAREY12DMCJiLIwe7uRochuP9nfh4iIaHgYgBMRZeEYyWH0SRRgJERENFYwACciykL1+obRx1+AkRAR0VjBAJyIKAtPeSWQrWSxEKk+REREw8TcWURE2SgKApOmIt6yK21zYNJUQBn9cxlGLAHppNa6C0XAG+KsPhGNTo7twEoYgJSAENC8OjRPadVtYABORJSFoqrwVFRB9fgQb2uBk4gBAFR/EIEJk/vzgKtFHuWhsxIG+lq78M7fX0TH1hYAQNXMCVj63hNQOb0enoC3yCMkIhq+ZCSBhuffxrZ/vw0jkoDm1THzxMVYcO4x8JUFILI90SwgIWW23f1jz4oVK+Tq1auLPQwiGoXGWiVM27Cw++0GvPKXx9K2L7/iVMw8YTF0n6fAIyMiOnhGNIHnfvEAepo7hrT5K0I46+tXwV8RKuiYhBBrpJQr3n189D83JSIqEEXToej9f0Z58A0Atmnh9dufytj+9n3Pw06aBRwREdGhcR0XO15enzb4BoBETxRr//ESrBK5pjEAJyIap9o37oJj2RnbpZRofG1TAUdERHRozHgSW595K2ufXau3wDEzX/MKiQE4EdE4FWntyt2nrQsuK30S0SiQ6IlmbXdtB67jFGg02TEAJyIap4J1FTn7hGoroIyBLC9ENPb5ygJZ2xVVKZlN87yqEhGNUxMXz4CiZXkzEsD04xYWbkBERIfI4/dizmnLsvaZfNRcqHppJABkAE5ENE5pXh1HXXV6xval7z0BGjOgENEooGgqZp28FOEJ6QujecN+LLv0JOj+0rimlcZtABERFZzm1THl6LkIVpfhnb+/iO5dewAA5ZOqseS9x6N23hR4/MwDTkSjgy8cwOlfuhybnliNHS+ug5U0oWgqph27AEsuOg6+8mCxhziAecCJiAhGNAHXSW22FIoCX5iVMIlodHJMG5ZhQrouhKJA82jQvMWZ+c6UB5wz4ERExNLzRDRmqB4Nqqe0Q1yuASciIiIiKiAG4EREREREBcQAnIiIiIiogBiAExEREREVEANwIiIiIqICYgBORERERFRADMCJiIiIiAqIATgRERERUQExACciIiIiKiAG4EREREREBcQAnIiIiIiogBiAExEREREVEANwIiIiIqICYgBORERERFRADMCJiIiIiAqIATgRERERUQFpxR4AEREREdFIkK6EEUvAiCQQ29sLX3kQgaowPAEvFFUt9vAGMAAnIiIiolHPsR1E2rqw6k+PINLePXDcXxHEMR89B9WzJkL3eYo4wv24BIWIiIiIRr1kTxRP//ieQcE3ACR6Ynjh1/9AX2tnkUY2FANwIiIiIhrVbMPE+n++Ase007ZLKfHWvc/DiCYKPLL0GIATERER0ahmmzaa1mzJ2qdzRytcxy3QiLJjAE5EREREo55jOzn7SJcBOBERERHRYRMQqJxal7WPNxyAopVGJhQG4EREREQ0qnnDfiy6YGXWPvPOWA6P31ugEWXHAJyIiIiIRr3aOZMx94zladsmLp2JWScvLZkZcOYBJyIiIqJRzxP0YfEFx2HWiUuw6YnViO7pha88gPlnH41wfSW8IX+xhziAATgRERERjQmeoA+eoA9HffAMuJYDRVNLpvjOgRiAExEREdGYons9QGks906LAXgeJRNJxOMJvL7qLTRub8LUGZOx8oSjEAj64fP7ij08GieshAHbsLD7ne0woklUz5qA8sk18AS8UNTSWAtHREQ0ksz4vve+BlhxA9WzJ6F8YhX0oA+KUvwtkAzA8yQajeHFZ1/F//znj5BIJAeO+3xe/PcPvoLTzj4RoXCwiCOk8cCMJbHh0dew9ek3IaUcOO4rC+Dkz16C8onVJbMhhYiIaCSYsSTeefAlbH9hLbD/rQ/+yhBO+ez7EK6vKPoEVPFvAcao7Vt24muf/X+Dgm8ASCYNfPOL38fmjduKNDIaLxzLRsPz72DLU28MCr4BINkXx7M/vQ9GLJnh1URERKOPbVjY9MRqbH9+cPANAInuKJ756b0wY0ZxBncABuB50NPdh5//8I9Dgp4D/eKHf0RPd28BR1X6XNuCYxiwYhE4RhKubWX9N6TsrKSJTU+sydhuGxYann9nWJXDiIiIRgPbtLD1mbcytltxA42vbix6SXoG4HngOA7WvPp21j5vr1nPwKefdF04yQQiO7aid/NaRBo2o3fzOvQ1bIaTiMF1+e90KBI9MViJ7Hf5zW9szdmHiIhotIju6YFj2Vn77Fq9pejvfQzA82GYs7ac3U1xbRt92zbBScQHHzeS6GvYDNdggHgopMx9dy9dOeQRHRER0Wgl3dxvatJ1hxuq5Q0D8DxQVBULl8zL2mfugllQmYECruMgsWc3ZKZZbikRb22Ca2e/m6WhApVhqHr2fdb1C6dB8+kFGhEREVF+pTZYZg9vJy6ZUfTc4AzA86Cyqhyf+cq1Wfv8xxevQWV1RWEGVMqkC7O7K2sXOxoZ9lMF2k/z6Jh18pKM7YqqYP7ZR0PzMAAnIqKxQdV1TF+5IEu7itmnLIOqMwvKmLTs6MX4/NeugxBi0HEhBD795WtxzPHLizOwUjSMpRJcJ3HwNK+OReevxKRls4e0qbqKkz5zMbzh0inLS0REdLh0vwdHXHoy6hdNH9KmeXWc8vlL4QkVvxaLGG/rkFesWCFXr15dkK8VjcQQi8bxj/seHSjE874rzkcwFEC4LFSQMZQ617IQ2b4ZjpE5HZ5QNZTPXwxF40ztoTCiCRiROBpeWAszZqBm9kRMXj4Hmt8DLccSFSIiotHIiCaQ6I1h+wtrYSVM1M6bjElHzILu90DVCvfeJ4RYI6VcMeQ4A/D8k1LCsmzoujZkRny8k1LC7OlCrGlHxj6++knw106AKIHKVaOZdCVc14XKwjtERDROuK4L6cqivfdlCsAZ0RSAEAIej87gOw0hBPRwOTwVVWnbtWAYvuo6Bt8jQCiCwTcREY0riqKU5Hsfnz9T0SmahsCkafBW1SLZ0QbHNKBoOny19dACISgFfFRERERElG+MbKgkKJoGJRSG6vOnMp4IwcCbiIiIxiRGOFRSGHQTERHRWMeFtUREREREBcQAnIiIiIiogBiAExEREREVEANwIiIiIqIC4o63AnAdZ39mD7X0clESERERjSbRSAyO48Af8MPjGX2VshmA55Fr23AtE8mONriWCUX3wFdbD0X3MtsHERER0UHq7urBO29swL13PIh4LIHlRy/BlR+5GGXlZQgE/cUe3rAVpRS9EKICwE0AlgCQAK4BsBnAPQBmANgJ4AopZXd//28AuBaAA+BzUsrH+48fDeAWAH4AjwD4vMzxDRWqFL1r24i3NsPs3jukzVNZjcDEqQzCiYiIiIaps6ML133oy9i6efug46qq4ke//m+cdNrKkgvCS60U/S8BPCalXABgGYCNAL4O4Gkp5VwAT/d/DiHEIgBXAVgM4DwAvxNC7FvH8XsA1wGY2//nvEJ+E5lIKWFFetMG3wBgdnfC7O1GMW5+iIiIiEabvt4IvvP1nwwJvgHAcRx87bP/D93dvUUY2aEpeAAuhCgDcAqAPwOAlNKUUvYAuBjArf3dbgVwSf/HFwO4W0ppSCl3ANgG4FghxEQAZVLKVf2z3rcd8Jqiko6NxJ7WrH2SHW2Qjl2gERERERGNXolEEs89vSpju+M4+OtN9yGZNAo4qkNXjBnwWQA6ANwshHhTCHGTECIIoF5K2QoA/X/X9fefDKDpgNc39x+b3P/xu48XnwRcI5m1i2saqY2ZRERERJRV4/amnCsH3nj9bSTiiQKN6PAUIwDXABwF4PdSyiMBxNC/3CQDkeaYzHJ86AmEuE4IsVoIsbqjo+Ngx3vw0o3s8DoSERERjVtenzdnH4/XAyFGR2xVjAC8GUCzlPLV/s/vRyogb+9fVoL+v/cc0H/qAa+fAmB3//EpaY4PIaW8UUq5Qkq5ora2dsS+kYyEgB4uz9pFC5UBo+SHhIiIiKiYpk6fjHBZKGuf911xPsrKwwUa0eEpeAAupWwD0CSEmN9/6EwAGwA8BODq/mNXA3iw/+OHAFwlhPAKIWYitdnytf5lKhEhxHEidbvz0QNeU1SKqsE/cUqWAFsgMHEKs6AQERERDUMw6MenPn91xvYJk+pw2tknQVFGR43JYkWAnwVwhxDCA2A7gI8jdTNwrxDiWgC7AFwOAFLK9UKIe5EK0m0An5ZSOv3nuQH70xA+2v+nJCgeD8Kz5iG2aztcyxo4LnQdoakzoXhyP0ohIiIiotQSlEsufw8c28EffnnroLXeS5cvxE9/9x1UVVcUb4AHqSh5wIupUHnAgVQ6QunYcE0TjmlA9XigeLwQqgohRscdGhEREVGpSCSSSMST2LxhG2LRGOYumI2y8jAqq7Iv/S2WTHnAuQYij4QQEJoORdOhBYLFHg4RERHRqOb3++D3+3D8yUNi2lGF07BERERERAXEAJyIiIiIqIAYgBMRERERFRADcCIiIiKiAmIATkRERERUQAzAiYiIiIgKiAE4EREREVEBMQAnIiIiIiogBuBERERERAXEAJyIiIiIqIAYgBMRERERFRADcCIiIiKiAmIATkRERERUQAzAiYiIiIgKiAE4EREREVEBMQAnIiIiIiogBuBERERERAXEAJyIiIiIqIC0Yg9grEsmkojHE3BsB6qqwh/0w+/3FXtYRERERFQkDMDzaG9HF2781W148P7HkIgn4Pf7cOGl5+D6L3wMNbVVEEIUe4hEREREVGAMwPOks6MLH77kBuxubhs4lkgkcd8dD+GFZ1/BHQ/+AbV11UUcIREREREVA9eA50EyaeAvf7hrUPB9oLbde/CnX9+OZCJZ4JERERERUbExAM+DeCyOB+7+Z9Y+D97/GOKxRIFGRERERESlggF4HriuRCwaz9onEU/Acd0CjYiIiIiISsWwAnAhxDwhxNNCiHX9nx8hhPhWfoc2eimKQLgslLVPMBSAqvD+h4iIiEY/K2Ei2RdHvCuCZF8MZtwo9pBK2nA3Yf4JwH8C+CMASCnfEULcCeB7+RrYaBYKBXH5h96Lv/z+zox9Lr3qQgRCgQKOioiIiGhkSSmR7I3h7b+9gOY3tsJ1XAghMGHpDBx1xWnwV4agqGqxh1lyhjsFG5BSvvauY/ZID2as8Hg9+OgnrsCMWVPTtk+dPhnXXP8B+HzeAo+MiIiIaOQk++J46kd3Y9frm+E6qaW1Ukq0vrMDT/7vnUj0xIo8wtI03AB8rxBiNgAJAEKI9wNozduoxoCqmkrcct+v8cnPfARl5WEEQgGEy0K45oYP4vYHfovq2qpiD5GIiIjokDmmjc1PrkGiO5q23YwbeOfvL8JKcjnKuwkpZe5OQswCcCOAEwB0A9gB4MNSyp15HV0erFixQq5evbpgX88xTUAA0nEhVAWQgOrxFOzrE1H+WUkTjmXDTppQdQ2KpsIb8hd7WEREeZWMxPHot2+BlTQz9lFUBRf+4BPwleV/2a1pmIhGY4jHElAUBbpHh6qoiMViCIaC8Ad8Ba9GLoRYI6Vc8e7jw1oDLqXcDuAsIUQQgCKljIz0AMca13UhLRPxll2won0Dx7VQGYKTp0HoOhSFa6KIRrtkXwxv3d+/9tF2AACV0+tx9AfOQNnEKmhevcgjJCLKE4mswTcAuI4L13HyPpTenj7cecsDuOMv96OvNxWmTpoyAR+//gMIhgL43jf/Dxdddg7+44vXoLK6Iu/jyWW4WVD+VwhRIaWMSSkjQohKIQQ3YGYhbQt92zYOCr4BwI72oW/bRkibS+iJRjsjksCzP7sfu17bNBB8A0B3Yzue/vE96GvtLOLoiIjyTAD+iuxZ3zSvDkgXbh7jnt6ePnzvWz/H739+80DwDQC7m9vw/W/9HLub23DlRy/BPbc/iE9//Gvo6erN21iGa7hrwN8jpezZ94mUshvA+XkZ0Rjg2BYS7bshM9zxScdBoq0lrz+MRJRfruui6Y0tiLR3p22XrovVdzwNI0dNACKi0coT9GHeWUdm7TPj+EVwYz2wE/nbjNmxpxOPP/xMxvY//fp2XHDJ2dA0Feve3oS31qzL21iGa7gBuCqEGEjZIYTwA2AKjwyElDB7urL2MXu7AclCPESjlRlLYtu/387ap6epA46Z/0evRETFoCgKZhy3CFUzJ6RtD0+oxIJzjoLV1wVjbztcZ+QnHm3Lxt23PpC1j2GYePuN9Vi6fBEA4I6b70dvT3FXUw83D/hfATwthLgZqUwo1wC4NW+jGgtybW6Vsj+nDBGNSjIVhOdiG9nXRxIRjWbekB8n3XARmtZswdZn3kKssw++8iDmnLIUM1YugNHRBOk4qaf+w0j8cbAsy0JXZ0/Ofj3dvQj211/p7uqFU4B16dkMdxPmj4UQawGcCUAA+K6U8vG8jmyUE5oOaVuZ21Ut9S9JRKOSUAXC9ZVI9mVeYiKEgCdY2B33RESFpntVTJgZxsTPXAhF0yEdG26iD4mWbQNBt+r1A2LkK4B7vB7MXzQHTz36fNZ+M2ZNxWMPpZapzJozHV5vcTPSDftfQkr5qJTyK1LKLzP4zkFR4a2uzdrFW10DMAsK0ajlDfqx8D3HZu0z8YiZULThPmgkIhqdhKrCNQ2Y7Y1ItmyD0bYTVm/XoBlvX92EvFTEVFUV77vifChK5pC2pq4KtfU12Lp5OwDg2v/40MBseLFkDcCFEC/2/x0RQvQd8CcihOjL9trxTFFV+KpqoQWCadtVfxC+6nqWZiUa5Sqn12PGcQvTtgWqwjj6A2fAE+B2GSIa2xRNR2j6bIgMcY2vbiIULX8pWYOhIL7z469CiKFLC3w+L77702/gT7+5HQBwzQ0fxMTJ9Xkby3ANqxDPWFLIQjyuZcHs64HRuQeuaULRdXir6+CpqMzrDyIRFY4RS6Jzeys2Pvoa+lq74Al6MevkpZh5wmL4wsWdYSEiKhQpJaRtIbl3D4yeTsBxoQYC8NdPgurzQ1Hz+zQwGo2hpakNf/j5zXj9lbeg6RrOOOdkXPHh9+K+Ox5C444mfOrzH8P8hbNRVh7O61gOlKkQT84AXAihAHhHSrkkX4MrpEJXwnRdN5XzW/Qv+Va1rI9JiGh0MqIJSDd1PfUEfVBU/p4T0fgjXXd/GmYhCr4ML9IXhdm/+d3n98IwLEjpQtM0lFeUFXQswGFUwpRSukKIt4UQ06SUu/IzvLFLURSApeeJxjyWniciAoSiQBRxojFcNrgwUDB7naCiGe5tyUQA64UQrwEYyKQupXxvXkZFRERERDRGDTcA/05eR0FERERENE5kDcCFED4A1wOYA2AtgD9LKVk/nYiIiIjoEOVapHMrgBVIBd/vAfCzvI+IiIiIiGgMy7UEZZGUcikACCH+DOC1/A+JiIiIiGjsyjUDPlBLnUtPiIiIiIgOX64Z8GUHVLwUAPz9nwsAUkpZ+ISKRERERESjWNYAXErJWulERERERCOosOWJiIiIiIjyLB6JA46Ltk27YCUMVM+aCH9ZEMHKwpWhz4YBOBERERGNGfG+GDY/tQYNz7wN13YGjpdNrMIJ11+IYE05VLW4izyKVyuUiIiIiGgEJeNJNDz3DrY+8cag4BsA+lq78O+f3Q8zmijS6PZjAE5EREREY4Jr2dj69JsZ25N9cex4bRNsu7jJ/RiAExEREdGY0NfeDTtpZu2z+41tSPTFCzSi9BiAExEREdGY4FpO7j62A8gCDCYLBuBERERENCaUT6qGUETWPtWzJ8ET8BRoROkxACciIiKisUERmLR8dsZmoSiYd+aR8Pp9BRzUUAzAiYiIiGhMCJaHcOSVp6NqxoQhbYqq4LhPvgea31uEkQ3GPOBERERENGYEyoM44YYL0bu7EztfWg/bsFAxvQ6zTlwCxaPBH/QXe4gMwImIiIhobAmUhxAoD6Fyej1c24HH74Wml07YWzojISIiIiIaQb5Acdd6Z8IAnGiUsQ0LtmFh9zvb0b2rHYGqMkxfuQCa1wNPoPjr2oiIiPYxYkmY0QR2vrIRZjyJ+gXTUDNnEvSAt+jl4IuJATjRKGIlTbRvaMQrf3lsUIndtQ++hAXnrMCCc1bAEyzNu30iIhpfjGgCr9/2JHa/s33gWMNz78AT9OHUz1+K8knVULSRD8KllJDO/kqXQlEhlNLKO1JaoyGirOKdfVj1p0cGBd8AAAlsenw1mt7YCtd1izM4IiKiflbCwDv/eGlQ8L2PGUvi2Z/dByOWHPGv69o2knv3oG/rRvRseBu9m9cjsacVrmWN+Nc6HAzAiUYJK2Fg3cOrIGXm8l0bHnkVZh4uaDS+OLYD6Ra5TBwRjWqOZaNx1YaM7bZhYecrG4ZOKB0G17YR2bkVidYmuFaqHL10bCT3tKKvYePAsVLAJShEo4RjOWjfuCtrn0R3dFhleInezTYt2EkLzW9uRef2VniCPsw+eSm8ZQF4SyBlFxGNLr27u+A62Z/ItrzVgFknLoE3dPjXGCkljO5OOPFY2nbXNBFv343AxKlQSmDtOQNworEmewVeoiFsw0LHtha89PuHB81GbX3mLUw+cg5WfPgseLm3gIgOxjDei8QIvmFJx4axtz1rH7O7C4H6yUAJBOBcgkI0Sii6igmLZ2TtE6gug5qHDS00tiUjcbz424fSPgpueXMbNj76GmyztNZPElFpK59YlXOD5ZSj5kAfwaqUOZeYSBfIsoyzkBiAF4Bt2YjH4rAtO3dnGreklEgkkkgmjbTtHr8XSy46HkLJPGOw+IKV0DlTSe/iOg5cJ/3SJNu0sPmJ1ZBZNu9uf2EtbIMBOBENn+rRMfOExRnbdb8X01cugKKOXCgq1GEs7BCl8ZiYS1DyqK8vir6ePtx92z/Q1NiCyVMn4gNXvw/lFWUoKw8Xe3hUIhzHQW9PBC8//xqefeJFKIqCiy47F0uXL0RlVcWgvv6qEE68/iKsuukROOYBKZaEwMLzj8Xk5bOhlFiqJSoe17Zgx6Iwe7ogAXjKK6CHyiBUDaL/TchOWjn3FtiGhWRPDL5woACjJqKxQPd5sOS9x8OMJdC0ZuugNm84gFO/cOmIThgJRYW3uhbJPa2Zx1RWAWSZxCokkS2jQl6/sBAqgNUAWqSUFwohqgDcA2AGgJ0ArpBSdvf3/QaAawE4AD4npXy8//jRAG4B4AfwCIDPyxzf0IoVK+Tq1avz8S0N0tcbwS1/vBs3/favQ9quvu5KfPIzH2EQTnAcB407mvGx938WPd29g9omT52Im+/9FSZMqht03DZThXjaN+xCd9MeBKrCmHrUXKheHZ4RfJRHo5tjGog0bB7ySFZoGspmL4Di8UIIgWRfHM/+7D5E2ruznu+cb38YFZNr8jlkIhqDzFgSZtzArtc3wUoYqJs/DZXT6+AJ+EZ09hsAXMtCX8MmuObQJ8lCVVE2dxFUT2HfJ4UQa6SUK959vJhTZZ8HsPGAz78O4Gkp5VwAT/d/DiHEIgBXAVgM4DwAv+sP3gHg9wCuAzC3/895hRl6bq+vejNt8A0At954D1567rWs6eRofOjtieDjlw8NvgGgpakVn/7Y19Dd1TPouObR4QsHMH3lAix//ymYd8aR8FeEGHzTANe2ENm+Je16SGnb6GvYPFCkQvd7MHn57Kzn8wS88JVx9puIDp4n6EOothyLzl+JZZedgolLZsAXDox48A0Aiq6jbPYCeKpqALHv/AJ6WQXK5i6Cousj/jUPVVECcCHEFAAXALjpgMMXA7i1/+NbAVxywPG7pZSGlHIHgG0AjhVCTARQJqVc1T/rfdsBrymq7q4e/O7nN2ft84df3orurqFBF40vq195K+vPwdbN29He2lHAEdFY4BhG2hmgfaRtwe5P1aXqGuaevhyaN/Mb04Jzj4Hu4w0eEZU+RdcRmDgVFQuWomLBEahYeASCU2dA9XghROks0SzWSH4B4KsADtz1Uy+lbAWA/r/3PXefDKDpgH7N/ccm93/87uNF5zgutm4aWvnpQDu2NWbcFEXjg2la+PeTL+Xs98qL+V8yRWOLFcl9c2/19Qw8hfOG/Dj9y5cPmeUWisD8c47GrJOWQNWZXYeIRgdFVaHoOhSPJ/X3cDZnFljBRySEuBDAHinlGiHEacN5SZpjMsvxdF/zOqSWqmDatGnDG+hhEEJACJFziYkokZ24VByKIqDpuX8FdU/pPDKj0WFY15YDZoKEAALlHpz1tcvR29qNrsZ2eEN+TFw8A7ANaF4G30REI6kYM+AnAnivEGIngLsBnCGE+CuA9v5lJej/e09//2YAUw94/RQAu/uPT0lzfAgp5Y1SyhVSyhW1tbUj+b2kpWkqjj3hqKx9jl65bFjBF41dmqbhfVe8J2e/0846sQCjobHEU1GVs4+3snogUHctE7HGbUi2NCDgTWLa4lrUTw3AaN0OY08T4m0tkHxiR0Q0YgoegEspvyGlnCKlnIHU5spnpJQfBvAQgKv7u10N4MH+jx8CcJUQwiuEmInUZsvX+pepRIQQx4nUu8hHD3hNUZVXlOFL37w+Yzo4IQS+9I3rUV5RVuCRUamZMXs65i6YlbH99LNPQigcLOCIaCwQqgYtlDnLkuoPQPF4AADScZDoaBtocxJxWH09sKJ9qaIVAMzuzqx5womI6OCUzmp04IcAzhZCbAVwdv/nkFKuB3AvgA0AHgPwaSnlvqmYG5DayLkNQAOARws96Eymz5yCX970fYTLQoOOh8tC+Pkfv4tZc2cUZ2BUUiqryvHHv/4MR65YOqTtrPeciu/8+Ku8UaODpmgaQtNmQQ+XD2nTgmGEZ8yFoqWWNknXhR2LZD+hlHBtFuIhIhopRcsDXiyFygMOAKZpIhFPYk/7XiQTBnx+L+rqa+Dz++D1egoyBhoderp60dvbh9dXvQVNU7HypKMRCAZQzlzxdBhc24Z0HViRPgCAHgpDqBoUbf/yN9ey0Ld9M1wjmfVc5fMWQ/X58zpeIqKRZsSSkK4LzatDK8Keqkx5wLkIOY8SsSR2bN+FW/54N1pb2lA/oRYfv/6DmDlnGgNwGqSiqhwVVeWYPnNq7s5Ew5QKtDWo1Zn3vghVhbeiCon2tFtoUn00bXglnomISoQRTaBtYyO2v7AOdtJE1cwJmH/WUfCGAtD9xY/BOAOeJ709ffjfb/8Cjz709JC2s88/Ff/9g69waQERFZ10HLi2hb5tmwaK87xbYOJUeCqqSqqIBRFRJoneGP79f/cPrfArgGM+cjamHDm3YEF4KVbCHLNc18VTjz2fNvgGgCcfeQ6PPvQMHGYVIKIik66LeNtuhGfMgeL1DW5UFPjrJ0NoGteAE9GoYMSSeP3WJ4YG3wAggddvfxJGJF74gb0LA/A86Onuw59/e0fWPjf/4U70dvcVaERERBkIwE3GEdvdhMDEqQjPmofApKkITp2JstkLIB0bsaYdrFtARKOCY1po29iYuYMENj25BrZZ3EkFLurLA9d10bwr83pKAGhtaYfDtF5EVGRCUeGpqkGitRnRnVshdB2q7oV0HTjJRKqPrkNofLsgotIX7ejNUJZxv64dbbANqyibMvfhFTUPFEVAVdWsS0wURcmYJ5yIxj4zYcAxbfQ0dQCQqJhaB82jQfd7CzoOoSjwVlQj2dEGaduQlgXbGjwzFJgwBUJlNUwiKj4jloR0XAhFwBsamplJ8+QObTWvXvSnegzA80DXdZx21gl4+vEXMvY56bSV0LmhiWhcMqIJvPP3F7Fz1caBAjdCEZi6Yj6OvOLUtG8q+SQ0DWVzFiLa2AAnsX9tpFBVBCZOhR4uhxCcMCCi4jGiCXTv2oNNj7+O2N4++MqCmHfWkaibP3XQNTNQXQZP0Aczljm16syTlsAT9GVsLwRmQcmTxu1NuOy8a2Aa5pA23aPjvkdvwqw5M/I+DiIqLUYsidW3P4WWt7albZ+wZAZWfuzcggfhAODaFqTjwDGSEKoG1euFUFQIPq0joiIyYkmsueNpNL+xdUhb9eyJOOmG9w5cMx3bxs5VG7HmjvSJMII15Tjra1fBGy7MNZZZUApswqQ63Hr/bzBj1uC8ztNmTMYt9/0Kk6ZMLNLIiKiYrHgyY/ANAG3rdsKIJgo4ov0UTYfq9cFTVgE9GIKi6WM6+JZSQkruxSEqZVJKtK7dkTb4BoDOhlZseeoNOFYqjaqqaZh69Fwc/aEz4QkMXtJXN38KzvjK5QULvrPhEpQ88fq8WLR0Hm65/zfo7upBe2sH6ibUoKq6EhWVZVz/TZSFY9mwkiYibd0wY0mEJ1TCG/TBGw4Ue2iHbdfrm3P22blqA45430kFGM345NoWHCMJs7sTUkp4yiuhBYIQqlb0daFENJgRTWDjY69l7bPt+Xcw94wjoeqpsNYT8GHGcYsweflsxDp6YRkmwvWV0Lw6vMHiB98AA/C8EkKgqroCVdUVmD13RrGHQzQqmPEkWt5qwFv3Pw8rbgwcr5hSixM+dQEC1aP7BtZKDl2W9m52kjm388W1LER2bBnI8AIAZncnhKajbPZ8KB4vg3CiEhNpS5PT+wBW3IDrDH6apeoqVD0AX4lO3IzedzEiGnNc10Xb+ka8ftuTg4JvAOhp7sDTP74HZpGWZ4yU+gXTcvdZlLsPHTzXthDZuW1Q8L2PtC30NWzOWA2UiIpH8+ZIWiEARR1dN84MwImoZJixJN5+IHP2ICOSwPYX18G1R28V2cqpdfCVBzO2e0N+VM/iHpF8kLYNJxHL0m7BjkULOCIiykXz6ph+3MKsfeoXTBt1qVIZgBNRybASBhLd2QOgxlc3wXzX7Phooge9OPULlw7ZHAQAut+LU794Wdo2OnxmNHf1YbO3eyA1JBEVn+bRseg9x2a8LiqaiuWXnwpvkdMKHiyuASeikuGYuWe2HdNGzjJnJUxRFITrKnDe/3c1mtZsQfMbWyElMPnI2Zh+zHzoQR+UUTaTM1oM7wH16HqMTTQeeMN+nPWND+C1W5/A3m37K41XTKnFMR89G8Ha8iKO7tAwACeikuErD0DR1KxLTKpmThjY6T5aKaoKX1kAs089AtOOXQAA0P2eUb25dDTQw+UAmrL28VRWjenUi0SjkaKqCNVW4MTrL4Jj2Uj2xeEN+qB6PfCVQErBQzG638WIaExRdQ3TVy7AjpfWZ+yz6PxjC16uPV8URRl1j01HM6Fq0ENlsDIsRVE8Xmj+0syYQEQYKLYTqAwXeSSHj7f5RFQydJ8HSy85EVUzJqRtP/LK0xCoLivwqGisUDQNwWkzoYWGvnmrPj/Cs+dD0XJkWyAiGgGcASeikuILB3DyZy5GT9MebHnmLVgJAxVTajHvzKPgCfngGSOz31QciqYjNG0WpOPA7OsBXAm9rAyK7mHwTUQFwwCciEqON+RH/cLpqJoxAa7jQvPqo37dN5UORdMBTYe/Nv2TFiKifOM7GhGVrLGy1puIiOhADMCJiIiIaEyQrgvpOnAMI5XaVlGRKpUp4A36IZTSSDXKAJyIiIiIRj3XdeAk4kju7YT0hrD+4VfR/GYDpOsiVFeBBeeuwOTlc0oi+xQDcCIiIiIa9aRlId7aAkcrx7PfvxuOZQ+0Rff0YPXtT6F94y4cddXpAykNi4VpCImIiIhoVHMdB/G2Fqjharx265ODgu8DNa3egkh7d4FHNxQDcCIiIiIa3aQLOxaBY0v0tXZl7brxsddhJowCDSw9BuBERERENOoJRUWiJ5qzX7wrAtd2CjCizLgGnIiIiIhGPdXjg08P5uznrwxBUdUCjCgzzoATERER0aimaDq8tXXQvSrC9ZVZ+y4452h4AsWtM8EZ8Dwz4km4lgPpuhCKAkVTSyL9jeu4MONJuLYDoQgoqlr0HcE0fK7jANIFXAkIAQgBReOvM1EuruvCjCZTn4hU1VUhsucFdm0HZsKAdPZdxxV4AiN/HU/lL3ZTv89Fnp2j/DKiCbhO6v9b0VR4/F4o2sj8n0snFXNApt4fhKJAjJOfJy0QhGv24JiPnol///zvaZeZTDxiFson1RRhdIPxHTtPpJRI9saw/p+voPG1TXBMG6quYeox87HkouPgKwtCUYvzAMKIJdH46kZsfmI1Ej0xAEDF1Fose/8pqJxWBw+rD5Y017KQaN8No7szFYQD0MPlCEyaBkXXIRQ+2CJKx4gksPPVDdj277eR7IsjVJvKCzxh8XR4g+knIIxYEjteWoctT72BZF8cEMCEhdOx7PJTEKwug+bRD3tcruNAOjaSnR1w4lEIRYW3uhZaIMQb6zHGSprobdmLt+57Hl072wAAvrIA5p55JGadtCTjz+FwSCkhbQvxthaYPV0DAbinrAL+iVNT7w85bjZHO0XV4CmvQNhn4qxvfADv/P1FtK9vhJQS/ooQ5p6+HDOOX1QSE45CSlnsMRTUihUr5OrVq/P+dRI9UTz943sQ74oMafNXhnDmV69CoDKU93G8mxFL4q37/o3GVzalbT/uE+dj0rJZ0HRe9EuRa1voa9gE10ize1tRUD53EVRv8Z+wEJWaZF8Mz/7s/rTpxyYsmo6V1543JPgxogm8evNjaFvfOOQ1iqbijK9cjsrp9YcV1LiOAyvSi9iu7UPaVJ8f4ZnzoOiHH+RT8bm2g/aNu/DC7x4E0oRek5fPxoqPnHXIQbhrWejbtgGuZQ1pE6qGsnmLoOqeQzr3aOLYNjq3t+GNu5/F7JOXomb2JACAlTCw/aX1SEbjOO7j58EXDhRkPEKINVLKFe8+zqmyPLASBjY+9nra4BsAEt1RbHjkFZjxZIFHBiR7YxmDbwBYc+fTsJNmAUdEwyVdF0bX3vTBNwC4LuItu+Da6XOfEo1XlmFi3UOrMub+bdvQiN1vb8e7J6S6d+1JG3wDqWDq1Vse37+c5RBJx04bfAOAk0wg1rITrsPf6bHATBh4/fYn0wbfANDyVgOiHb2HdG7XdZDY05o2+AZSP2eJthZIp7iZPwrBjBl4/bYn0be7E2/e8288+b934sn/vRP//vnfsOu1TdizYRe6d+0p9jAZgOeDbdrY+crGrH0aX90ExyrsL4Jj2djy9JtZ+1hxAz1NHQUaER0M6TgwOrP/31jRvtRjR6JD4DoOXNuCYxpwLROunf7NfLRxTBuNr2aeeACATU+shhFNDHxuxpLY/OSarK+JtHXDOIyJFNd1kOxoz9rH6utNreelUS/a0ZtaxpTF5ifXwDqUSTDXhdG9N2sXs6cLUo79nyUzmkBsb/YbmS1Pv4lEX6xAI0qP6wzyQcqcs8iOaUO6hQ2UXNtBoncY+TG708/cU5EJDCsgGg8XWBp5rm0h0dYCo7trYG+B6g8iOHkaFK9vVG8KdC0nY1W8faLtPYNf47jDyids9MaAHBkXMg8sVTgkZzcjOS6WDox1yd7cAV+yNwbXOYRruASQ60ZNynExQZOMZL/JAVL/zsW+seUMeD4I5Exvo/s8EEphN0Mouoay+qqc/XKl76HiUTw5Nsj273gnOhiubSOyfQuMrr0DwTcAOIkY+rZtgpNMDFmeMZoomgrkuNx6w/5BSwMUTUWwuiznuf0Vh7eXZzi/r0KM7t9p27SQjMQR7ehFvCuCZGR0/zwdqmBNec4+4fpKqPoh3OwKQOTYsCsUNZU1a4wLVIZz9gnVlo9Y1plDNbp/q0uU5vNg5olLsvaZfsIiaN7CbqxRNRVzTl+WtY+vPMgAvEQJVYOvtj5rH09Z5ah/s6bCklLCivTASSYy9UC8eSfkKF6HrKgK6hdMy9pn1slLoR8wceIJeLHg3CH7pgapmFIL3X/oM9NC1eCpzJ4OTSgqFO/ozUxlRBNY+4+X8Mi3bsYj374Z//zmn/HsT+9F2/pGWEUuBV5o/opgziB83llHHVJmHaGo8FXXZe3jqapJBeFjnObTUTGlNmufBeeugC9UmE2YmfCdOg90rwfzzjoqYyAbqqvAwnOPge4r/CNFT8CHJe89Pm2boqk44boLBr0JUekQ/emktGD6GTdF9yAwacq4yfdKI0M6NpJ7s29IcozkqN685Qn6cOSVp0P1pJ8hDFSGMefUZVDfNSNWNqkaU1fMS/sazatj5cfPhfcwMikIIeApr4CSZXmJr37iqA2ajGgCL/3xYWx95i3Yxv7lc5H2brzwm3+gbUNj0cuBF5In6MMJ110ANUOWsflnHw1/We4qjukIRYG3uhaqP/3Po+L1wV87YVw8IfWXh7DymvOgZYixZp64CMGa3E+38o1pCPMo2RvD1mffRMML62DGkvAEvJh50lLMO/NI+MsP7ZdsJJhxA92N7Vj3z1Xo3N4KRVUxeflsLHnv8QhUhKCOQF5bGnmubcPo2gs9FIIVjaQyopgGhKrBW1UDX009hKaN+TyvNLJSqcs2wrWy71spm7MQWqB4163D5dgOYnt78cZdz2DP5mYAqaBlypGzsfzyU+ErD6b93TFiSex+uwEbH3sd0T09UDQVU46ai6XvPR6+itCQoP1gSSnhWiaijdvhJA5YI6wo8NdNgreqZtTmAm/ftAvP/eKBjO3esB/n/fdHDusmZrRxLHugRkjTmi1wbAdV0+ux6ILjUDN74mEXeHJtC0Z3J4y97XAtC0LT4auuhbe6Foo2ft7bTcOEFUti4yOvYdfrm2GbFiom12LBeStQv2AqvAWc/c6UhpABeJ4loglI2xlYfig1BYEiP/bYx4juX4en6ip0H2e+S5Vr24jv3pUqrgABvbwC3spqKJoO6bpwHRueUBlnv+mguY6NaON22NG+rP3KFx4xJjYCGrEEXNuFa9lQPXrq2pej+Jh0JYxYIrVGXACqro34E0zXtiAdB04yAaEoqZlMoYzaza9mwsCrf3kMrWt3ZO135levRPWsiQUaVemwkubAxmAhxIgWhpHShbSdgX0PQlHHxcx3OkY8AWm7AASkdOEvL3z9lUwB+Oi8rR4FbMtGS1Mr/vs/f4Q3V68dOH7EUYvx3Z98DVOmTYJe5JnmUqgERcMjHbs/+AYACau3G1bvgTmNBfSFSxmA00FTVA3+uomIZAnAtVB4zOwtOJQiJ0IReS/aoWg6oOljppCWdNxh5Ug/MPXjeKL7PHlbhiqEAqGPjd/Xw+UNlG6cw/+hPNnTvhef+shXsOzoxbjjwT/g7n/eiDsf+iNWrFyGG67+KtrbsufrJNpHSolkjvzfgIQZObQCDkSqzw9PZXXaNqFpCE6ZMWqXQVBxqB4NZZNyZ90K1VXkfzBEJYgBeB7EonE8cPc/8Ysbv4d4LIFPfvCLuOrC63DtVV9Ab08Ev/zT9/G3ux5GNFLcJPA0SkgJOZz83znyHBNlomgaAhOnIjR9NlR/EBBKau1o7USUz12cdZMgUTqaR8f8s4/O2qd8cs0hl10nGu04pZEHpmni7PNPwxeu+xZamloHjifiCfztrofx8vOv4Zc3/S9Mc2xUmaP8EooCNRAEBpagpKcGSmNvAY1OiqbBU14JLRgGIAEJCHX8rh2lw+crC2DxRcdj/cOrhrTpAS+O/+T5qfzrROMQr6x5ICXwt7v/OSj4PlBrSzvuvf0fo64QgXRduLYFKxaFGelNlau2OetaCN7yqqwFFISqQcuQforoYCiaBkXToeg6g286LJ6AD3NPX4Yz/vMK1C+cBk/AC39FEPPPWYHz/uejCNXmLkxDNFYxC0oedOzpxMVnfCTrEhN/wI9/PXcHaurSr7ssNa5tw+jpRLJtN6S7P2+rFgojNHUmH1Hnmes4sKJ9iDU2DG0UAmWz5kP1BxgwEVFJMuNJuHaqyqru92TMhU10sKSUcEwLtmkj3tkH27QRqi2H6tHhDRZ/UzOzoBSQAHKu707ER08pXum6MLr3ItHaPKTNjkbQ17AZZXMWcpNWHimqCj1UhvJ5S5DYsxtWNAKIVOVLX209FI2zlURUug43vzVROq5tw4zFsfudRqx98OX9WXUEUL9wOo69+uyipB4cDkZMeaCoCsJlIUT6ohn7BEMBqKMkZZx0HSTb0y+nAQDXNGBFe+GtGB2z+aOVoqqAqiI4eTqk6/YfHL15gqn02JYNO2HCtR0ITYGiKtwkR0QlybVtJPbuQduWvVhz5zODGyXQvqERz/7sfpz51StLMu0yA/A8CIaCeP8HL8LNf7gLAFA/oRaV1RXo7upBe2sqndwlV5xfMgV5cnGM5KBlJ+kYnXuhh8o5C14AQlWZ75tGnBFJYOPjr2P7i+tgJ1NVMWvnTcGRV56GUG05NFbIJaISIaWE2dsNoQew9sGXM/aL7ulB2/pGTDt2fslViWa0lAderwdXf/JK9Hb34aqPXIyqyhCkZUHoOnp6Y7jztn/gE//xIfhGSeVJ6bi5+7guUmXiKJ+MRAKqosCMGzDjBmJ7++ANBxCqLYfH74VymGWxxyPXsQHXhZ2IA0BqM6uiQFGHf3l0bQvSduAYSQhNher1FaT6nBGJw4wbiLR3Qw94Ea6vhO47+PW1RjSB53/zD3Q3tg863rGlGU/94C6c8ZUrUDWjftjnsxImHMtCT1MHpJSomFIL1aPDExgd1zwiKm3SsWF0d8JCCGYse8GnhhfeQf2iqfAG/SW1VJMBeJ6Ew0F889s3IN68A25XZOB4ne7BN791PeAZPevhVF/usWqBIITC4C+fbNOA3dOFhK3hlb88jr7W/WkJfWUBHP2hM1E3byp0PzfEDpdr24i3NsHs7jzgqICnsgqBiVNzPtGRUsI1DUQbG+Ak91f0E6qKwKSp0MsqDiqQH/a4XRfxzghW/elf6N61Z+C4J+DFsstPweRlc4Yd7LqOg7b1O4cE3wPttoPXb38Sp33hUniHUQ3SiCaw7uFV2PHiOrj9N+9CCEw5ag6O+sAZJfkomIhGH2lbsJ3c6ZztpAUrEoECG1ogVDLLNkvnVmCMkY6F6M4tcC1z0HHXMhHduRWwzQyvLD1CUftzA2fmq60vqTvLscZKJhFrbgS0AJ752d8GBd8AkOyL46U/PIzuXemDKBrKtW3Emna8K/gGAAmzuxOxpp0502xK20bftk2Dgm8AkI6DWNNO2NFIXjZbm9Eknv7xPYOCbwAw4wZev/VJtG3YCdfN/eTKtW0kOrux9d9vZ+3X27IXtpH7jc6MJfHWfc+h4bl3BoJvIHWj0rRmK16+8V/jtvQ4EY0gCUjpIlRbkbNr1Yw6wDEQ3bEVrlE61x9GTHlgJJJItrekEoKnIyUS7S0wEtkfm5QKRdMQmjYTiif9jFpw6kyIPMzy0X6uZULRvdj01BsD63OHkMBb9z3PAGeYpGPDivRmbLciPZBO5gBcui6SXXuy9om3NmVtPxSu7WDHS+tgROIZ+7zztxdzPpYFUhuspesi2Zf5XPsY8dznswwTja9uytjesaUZiZ7Mm9OJiIZDqCo85VWAnUTdgqlZ+849YznsSA8AIL67qWTqlzAAzwNVEbAjfVn7ONEIVKW0NgRko+gelM1ZgODUmdCCYaj+ILzVdShfsLT/MXtpPNIZixzHgdXTBcUXQtPqrVn79jR3wLWzb5ilFGPIzHe6Ppmrj0rHgZmlHQBc0xzWHoqDYcYN7HxlY9Y+8e4IrISR+1y93ZCOjVBN7oIovnAwZ5+WN9PkqX+X7S+ug3S5X4SIDp1QFPhrJ8CJ9eCYD5+ZsajTUR84DYprQNqpJ3h2PJZ5crTAOG1ZVKXxQzBciqbDW1kNPVwOQBZkkxmlHt9DuhBCGdYygOEsPaBUAJ2zT47sP3I4/9ZypP8/JBwz9wyOYw7j+3McuPE+zD/7SOzZ3JSxX+28KVA9uW+ybSP30jrbsCClhMDomYAgotIjNA2h6bOR3NuG0790KVo37MKOlzfATlqomlGP+WcdCeEkYXW1DXqd4zgQmlb0rCgMwPPAlS4UjxeumXkGStE9pXITdtCYarCwNE0DvAG4ZhJVMyZg77aWjH31gJcV5oZJD5fB6NyTvU8oy94HRUALBGD1ZV7GAiEgRvj3RdU1VM2cgHh3JGMfRVPhK8u9YVIPhZHc04qyibWYevRcNK0Z+oTFG/LjmI+ePax84LXzpuTsU79wGhSVN+5EdHiEEFA9HvjrJgFSYvox8zBp6Uy4lg1pxmF2twzMfA+8RtPQunsPQuVlqKquKM7A+/EqmAeq7oFWWZu1j1ZZA0VnXl0aHl9lJdxEHxadd3TWfrNPOQK6j1lQhkMLBLPuXRCaBi2QedmFomrw10/K+jU8ldWAGNnLrO73YtH5x2btM+2Y+VA9uQN/1eeHousw25uw7H3H4diPnY3yyTWASN3MzT1jOc751ocQqMq+CXufsvrKrH11vxf1C6cN61xERMOhaBoUXYfq8UKRFpIt22B07B4SfAOAVlGNW2+6D08+8m84w3gKmk8MwPNAVVV4KyqhhivSt4fL4a2sHjWVMKn4JBR46yYiXBvCgnPTB+H1C6dh/llHcQZ8mEzLQWjm3LTpM4WqIjxrfs7NxYrHC//E9LO+aiCIwITJedkfEagqw5FXnJq2rXJ6PY649ORh3YgJVUN45jxACCR370B1nY4TP3kOLvz+x3DON6/EkguPha8sAGWYS808QT9O/fylaVMNal4dp37hUuh+5gInovxQ/UF4q9JPgOrhcviqarC7uQ0P/+1x9PUWd0O4yEeKrFK2YsUKuXr16oJ8LTOZhLRMGJ0dqbSDmg5PVR0UjweeYeTWJjqQZVoQ0oUZicFK2tj89FuItHXDW+bHvDOPQvmkauZYHqa+3gjuv+thbFy3BV/9r/+AYsSgO6klY2qoHL6qaiiaBjGM2WvXsSFtG8mONjjJBISqwVtTB80fzOtyLTNhwIwmsOWpN9Dd1AFPwIs5py9H1fT6g/o5kFJCOjbMnm6YvV2ABPTyCngrqlNVVw9yn4frujBjSbS8sQ27Vm+GlBKTjpiF6SsXwhv0sVgUEeWF6ziINTfCEy6D4vHA6NoL1zQgNB3eqhoAQLKjHZtaI/jp//4Bf7j9pwVZhiKEWCOlXDHkOAPw/DMNA67jQFFUeEZJ9UsqXbZtw7EswAWkK6FqGovvHATbtvHgfY/hO1//CQBA9+g45/zTcPyJRwEA1ry+Fp/+8jWom5B9Gdm7ua4DuBIQyEvxnUxsy4ZjWBCqAs9hzC6nAvHUI1mhKsO6+cjGdV1YidSmTN3n4bpvojHGtW1I6cLq64V0nVSRG02DFYtCKAr0YLi/qnBhbrpd20LPxncAKaHoHngqq6FoemqCobd7oF6DUzsVf7nxXnz+a9cVpCI5A/B+xQjAiah0dHX24PLzrkHHnsxpCK++7kp85iufgNfLGxsiondzbRuJthYYXR2DjiseL0LTZiLe1gI7FkNw8jTo5fmpCDx0TBZ6NmQvKgYATs0UWC4wacqEvI8JyByAc0qCiMaVaCSaNfgGgCcfeQ7RCAvGjAeu48C1LBhde5Fo3w2ztxuubQ0vxSTROOQ6DhIdrUOCbwBwTQORHdsQmDgVkBKx5p1w4rkLfY0ULRDK2i50Hb6AHxVVuWsf5Bt3axHRuOIMo1CRZebOt06jn+vYMLo6kWhrHlScQygqgtNnpR6pc7M80WCuC2Nv5hSu+6oMe8orYPZ2I97WjLB/LhQtv5nfFE2Hr34iojsyF6zz1tRD9ftL4ukmZ8CJaFwpryxDIEdO62OOXw4v92uMaVJKWJE+JFqbhlTGk66D6I5tkFbuwkJE441jJHJWk7T6eqEFUylJnUS8YNUntUAQ/vrJads8FVXwVdaURPANMAAfN6SUqUetOSr7EY11gYAfV3z44oztQghc99mrEQrlLr1Oo5d0bCTaMxe1AiTibS1wndxVR4nGlWEE07JIlb4VVYO3uhblC5bCW1MPPVwOb1UNyuYtRmDStJIqJFg6I6G8kK4L6Tgw+3pgRXohFAWeympo/kDeHwcRlSKf34drbvggdjbswr+fenlQm6qq+P7/fRP1Ew8uAwqNQlLCNTJXKwYAK9JbsJk7otFC9eVOc6oHw3CSqbXfiscLFKjse3dXD7Zva8RrL72JxUfMw5JlC+Dz+6ANY8yFxgB8DJOuCyeZQN/2zcABG4rMni6oXh/Cs+azGieNSxWV5fjuT7+B9rYO3HXrA+jp7sXCJfNxyRXvQSgUzLlEhUa/YcXVjL2JhhIKPOWVMHu7M7QLeCqq0NewCQDgr5uYs6jZ4ZJSYndzGz75wS+hedfuQW1Hr1yGn/3+O6iqrszrGA4W0xCOYa5loWfz2kHB94G0QAihGbM5E07jmmlasG0bXq+H1WnHEde20Ld1A1wr84ZbPVSG4LRZJfXYmqgUuLaF6M4G2PF3ZYtSFISmzYLZ2w2zuxO+mnr46ibm/Xeou7MHV1zwCbS3Ds3MAgAnnHIMfvir/0ZFZVlex5FOpjSEvKoUiG1Z0Ao42yylTN2dZkmlZcejqcIbDMDzwnEcBnSjgMejw+MZv78DUkqIAj0eLiVCVeGrm4h4y66MffwTJjP4JkpD0XSEZsyBaxpIdnYArgMtFIYeKofZ1w2h6iifvxRCVQvyO/TmmnUAgPddeT6CwQDqJ9TgjHNORGVVBXSvB117e6CVWBVeXlnyKNEXg3RcNL66CdE93QjWVmDGyoUQmgJ/WZ43eLluav1iDnYsCtXry+9YxpF4PIF4LIEn/vksNm3YhomT63HJ5e9BKBxAuCxc7OERAejfG+I6MPt6YcciUPpLNQtVGzcBpxAKPOVVcJJJGJ1DU6oFJk2D69hwkgkITR83/y4jzXVcmPEkuhrb0b5xFzw+D6atXABP0Acvl3qNaoqWul4E962v7r+R91bXQgilYDf2yaSBKZPrcecDv4ZPWgjU1sOM9AKKD2bUxLYn3oSVMFEzdxLURTOg6Cq8geLHPQVfgiKEmArgNgATALgAbpRS/lIIUQXgHgAzAOwEcIWUsrv/Nd8AcC0AB8DnpJSP9x8/GsAtAPwAHgHweZnjGyrUEpRkJI7GVzbinQdexIFDEkJgycXHY+YJi+HLYxDuOg5iTTtg9fVk7RecNgveiqq8jWM8iUZjePaJF/E///kj2O/KNX31dVfik5/+MMoqCv/4i+hAruvAicUQ2bkNkIOfkHkqqkouU0C+ubYN6TowOjvgWiZUrw96WQXMni4kO9oAAHq4AsGpM8bVv8tIcB0HkbZu/PsXD8CIDC7GMmnZbBzzkbPgDTEIp8PjWBaiu7bDiUdRPm8xorub4K2ehNduexJt63YO6qv7PDjpMxcjPLEKvgLdAJZSJUwbwJellAsBHAfg00KIRQC+DuBpKeVcAE/3f47+tqsALAZwHoDfCSH2PUf4PYDrAMzt/3NeIb+RbLob2/H2317Au+8HpJRY+4+X0bmjLa9fX1FVeCurc/bTg9mrRtHwNe1swbe+9IMhwTcA3HrjPXjikefgOEwDScUlbRuRnVuHBN8ABoLO8ZSuVNE0qB4vvDX1EJqe2ri+bdNA8A0AVqQHibaW1JI9GjYzlsQzP7tvSPANALvfbsDbf3sBZiJ7JhqibKTjINHeAicWgbe6DmZfD7RwFdb+4+UhwTcAWEkTz//y73DN4qcXLXgALqVslVK+0f9xBMBGAJMBXAzg1v5utwK4pP/jiwHcLaU0pJQ7AGwDcKwQYiKAMinlqv5Z79sOeE1RJXqjWPfwK1n7rH/4FSR681vqWguGUul/MvBUVgOCqeBHQl9vBL/56Z+H3HAd6E+/uR29PX0FHBXRYK7jILmnLWsKkGTnnqx7R8Yi6bow9rbD2Nue2juT5ubE6N7L8vQHwXVdNL6+GVY8c4Dd+OomOCUQCFHq2mBbdtb3sFIkXRdmdycAwFtVA2NvBxTNi8bXNmV8jWPZ2PbcOzASyUINM62iPk8TQswAcCSAVwHUSylbgVSQLoSo6+82GcCB0Wxz/zGr/+N3Hy8+mZoBz6anuSPvKa4UTUd49nxEd25LVaI6gKeyGoGJU/lIdYTYtoNXXlqTtU9rSztLnFNxuS6saI6bQNeFa1njKjuSdJzce2akhGMaTN06TFbCRMub27L2ka6L3uYO+MtZ9KpYjGgC0b292P78O7ANG3ULpmLy8tnQ/R6oJRofGLEkpONCKAKqKgcmFBRVheLR0dfaBTfNk+gDtW9oxOxTlsLrL95a8KL96wohQgD+BuALUsq+LIv10zXILMfTfa3rkFqqgmnTph38YEcxVfcgPHMupG3DikUhFAEtVAahKFDynJdzvFHGYSYJGqP4s5wW/1VG3iibcB1TkpEEXvrDQ+hsaB041rRmC96+/3mc8rn3oXJaHVS9dOIEI5pAd2M7Nj2xGrG9ffCVBTH3zOWomTkb5p5dqdl7oQ5vbUcJXOOKsv5ACKEjFXzfIaV8oP9we/+yEvT/vW9bejOAqQe8fAqA3f3Hp6Q5PoSU8kYp5Qop5Yra2vxXuJMAamZPytqnasaEgtV4UDQdqs8PX3UtvJU1UHUPg+8Rpns0nHT6cVn7TJsxGbrHU6AREQ0lVBV6WUXOPuPtyZhQVXjKcxTpEAoUb+YlfTSY7vdg8vI5WfsIRUHFVFadLQYznsQbdz49KPjexzYsPPeLB2DGirtE40BGLIk1dz6D53/9D+zZ3IxYZx86d7TilZsexaqbnoC3fjocIwnN70PZhCqoevaUg5OOmAktUNzf54IH4CI11f1nABullP93QNNDAK7u//hqAA8ecPwqIYRXCDETqc2Wr/UvV4kIIY7rP+dHD3hNUWleDQvPPzZrn4XvORbqOM49PNaEwyF85ivXZs37/Zkvf2JEiwBYloVoJAYjyU1MNDxCUeCrqc+698NXWw+hlFa+3HwTigJvVQ2gZPl3qanjnpmDoCgKph87H7o/c5AzfeUCaJ7xdbNXKhzTRstbDRnbyyZWoXf3XpjxJNwi732QUqJ17Q40v7E1bXvnjlZsfW4dzEgU3up6SNvErJOXZjyf7vdi1olL4PWNswAcwIkAPgLgDCHEW/1/zgfwQwBnCyG2Aji7/3NIKdcDuBfABgCPAfi0lHLf4p4bANyE1MbMBgCPFvQ7ySCeMFBWX4mjrjp9yF2YoqlYfvmpKJ9cjXgyUaQRUj5MnFyPX970/SFlzDVNxRe/cT1OOPUYKFne4IcrEolid3Mbfv2Tm/DVz34H3//2L7B5wzb0dJfmBk/XtmAnE0h0tCHR0QbHSMK1uRa+WBRNQ9nseWlLQ3ur6+CtqoMYgZ/T0UaoGspmL4BIM/vvqayBr3YCFBbWOiieoA+nf+VyeMND071NPGImll12ctYAnfKnp2Vv2g2XwZpynP7l92PBuSuw/aX1ePUvj2HLU28i0RuDXaQ9TEY0gY2PvZa1T8MLa6F4AjD7euANB7HwvGMwfeXCIf18ZQGc9qXLoHiLf+PHUvR50Lm3G7f87k5ce+2VAICOLc2Id0Xgrwyhbv5UABK33fYAPviJy1FTyxzcY4mRNBCLxfH6qrewdVMDJkyqx2lnnwi/34dgKHDY54/0RfH3ex7BT7/32yFt51x4Or79/S+hvIRyjbuWhUjjNjjx2KDjWjCM0PRZ42qjXynZV4jHjsfgGAaE7oXQPBBCAYSA7vNAKMVfI1loUrqQjgM7EYcdi0KoGjzlFRDK+FuWMxIcy0akvRuu46Jvdye6GtuhejRMXjYbVtxA5cx6+Ebgulhs0pWwTSu1x2qUPNlu37QLz/3igUHH/BUhnPTpi/H6bU+gp2lwSXdFU3Hypy9G9eyJBf8ek5E4HvrPGwGkAuhpx8yHrzwIM5ZE05qtiO1NbaC+8AfXQtgxKLoXWiAIM2HBsWw0rd4CK2GgZs4kVE6rh+LVCjr7zVL0BaSqCoSqoicRg3CBmrmTYSdNaH4P+hJxOJCwXZYpH4u8Pi+8Pi/OvfB0nHvh6SN+/oatO9MG3wDwxD+fxfwFs/Gx66+C/q5MDftuDABAQKCyumLEx/Zurm0hsmMLnDRPeuxYBNHGBoSmz2YQXgRCUSAUBVLxIh5NYsszq2BGEwjXV2LmiYvhWDZCtRXwBLzjatZXCAVCU+AJl8MTLi/2cEY9M5bE0z+6B45lo3rWRJRNqIQZT+LlP/4Tyb44Ji+fjWM+ejY8JVCV8FA4tgMrbqDpja3Ys2kXFE3FrJOWoGJKbckXGCqfVANFUwdlC1n4nmOx7qGXhwTfAODaDl747YM4/7sfK8pNhh7wYunFJ6JiSg12rtqA9o274CsLYMWHzoQZT+L1vz4FRVXgq5ww8Bp//56rhecdU/DxDgcD8DyoqCzH5R95L6664JMoKw/jQx+7DJMm1aOtbQ/uuOUBdHf14K6Hb0RlFS/wNHy9PRH87v9uztrnr3+5D5d98EJUVac2lDmOg6693bj1T/fgofsfRzQSxdwFs/HJz3wYxxx/ZF5nyx3TSBt872PHopC2DTAALwojmsCrtzyBtnU7Bo61b9yFbf9+G4svOg6Rtm5UzahHuL4Kijr+lqTQ4XFtB9tfWg/HSuX57tzeis7tgzf8tbzdgCON00ZlAO7YNrob9+D5X/0dtrF/aUbT6i0on1yDUz//vrxWuz5cmlfDnFOPwJan3+z/XEf1zAl44+5nMr7GtR00PL8Wiy5YCVUr3I255tVx8mcuRvOarXjjrsHja3x1E6YcNRenfeEyiAyTBWY8Cem60Lw61BJKI8qrah7EY3H85Xd34rs/+ip+97vvYrYIARvaMdMN4Ne/+g5+8NNv4qbf3I5YdGh1sIPl2jZc24JrWXBZpW1Mcxwbb77+TtY+3V29MJLmwOetLXvw/vOuwW1/uhc93b2wbQcb123Bl67/b/z0u7/NW2EgKeVAcYRszN7uvHx9ys6xbGx+6o1BwfeB1j/8CrzhANbc+SzMeOlkQqDRw0qaaNuwM3snCfS27C3IeEaaGTfw3C8fGBR879Pbshev/OUxGNHS3eeleT1YeP6xmHXyUgghEKguQ+/uvTnrk+zZ1AT7gPeYQtA8OsyYMXCz8G7Nb2xFx9YW6L7BWcaMaBy732nAqzc/jpf/+C+sf/gVxLr6YJVI9VXOgOdBMmngwveeCWNTG15/6F+D2ppWb8HkFXNx2RUXwEgah7wu2HVsOMkkEu27U2sVFQG9vBL+uolQNH1cbqIa8yTg8XpgGNkvfvtmK3u6e/HtL/8vurvSFxh58P7HcMkV5+PolctGfKgAhpXgd7ztQSkVVtJEw3PZb+a2PfsWpq6Yi73bdmPKkdnTyRENIcSwli+Nxvcq13WxK0cVzz2bmmAbZkkvRfEG/TjifSdh8QUrsXf77mHNDiu6WvAc2kYkgQ3/ejVrny1PrcH0YxfAV5aKqZK9MTz3q78PusHr2NqCzU++gZXXnIcJS2bAU+QNwKPvJ38UUFUV3piN5tc2p21vWb0Vak/ykNeAu44No2svIg2bYEf7gP6NQ2bXXvRuXg8nmWBgMwb5/D6c9Z5TsvaZOWf6wPrvZNLAmteyB1k3/fav6OuNjNgY9xEidUOYiydHTmrKD8e0cs4CdW5vRfnEarSu21H0NGQ0+nj8Xkw/dkHWPoqmomLK6MsDbicttK7fmbNf187sFbFLgSfghb8ihKlHzUPVjPqchXemr1xY8MBVQqJrZ1vWPome2MB1yoglsPqOp9M+XZFS4tW/PAazBJ5OMADPA9UFml7cAAAom1SNpRefgBUfPgtLLzkR5ZNrAAC7XlgP9RBjZOk4SLQ2Z2h0EW1sgHQy35nT6BQI+vGpz10NrzdzMZ8vffOGgb0Fe/fkXgLSuKMZlpWfnxXNH4CiZx6r6vVBYWGiohjOrKOia3AdF6pHR5ZKxURpCUVg0rJZAzOS6cw5bRm0EkgHd9AEhrUGWingOumRoHl0zD/rqIzt/ooQJh0xsygZkobzb7nvOuVaDlrX7gAEMGHRdBx5xalY8eEzMf+co+ENByClxOan3oCV42lyvjEAzwNFUZDsjeHE6y/CEZeciM6d7dj23Nvo3N6KJRcdj5P+470wY8lDKl0uXRfJvXuy9nEtE65ZGmucaGRV11bh5vt+jfoJg2eNgqEAvvuzb+CoY5cOXITKysPDOF/liOQmT0eoGsKz56cNwhWPF6GZ85gBpUgUTUWoriJrnynLZ6N90y7MPGExA3A6JN6gH2f855UI1w9+GiaEwOyTl2Lhe46BlmVCoVR5/F7MOG5R1j6KqqBq5oSsfUqN5tUx76yjMP+cFUM2XpdPrsEZ/3lFUZbUqJqKyctnZ+1TNaN+YMyR9i6UTazCWV//ACYtm4XmtxrQ8PxaWHEDJ91wEZZcfAI6t7fCSbN+v5BG4a3n6HDC9Reh4fl3BlVu6mnqwO53tmPy8tk48YaLDmkdlZQu3GEU8HGSSWiB0EGfn0qb1+vBgsVzcc8jN6GpsQXbtzaitr4ai5bOQyAYgO+A3KahcAiz5k7H9q2NGc/34Wsuz1s2HiEEFN2DsrkLYcdjMHu6AQF4K6qg+gMMvovIG/Rj2WUn46XfP5y2XfPqmHXyUqx96CUEKnkdoUMjFIFgTRlO/8rliHdF0Lm9FZpXx4RF06F6dHiKXAr8cNQtmIpAdRninek3ss86eemorPLpCfqw6D3HYv5ZR6Jj227YSRNVMybAF/bDGy5Oznbd78XS956AlrcaBqVNHCCAZe8/ZeDmQPf7sPKa87DqT48g0r5/o3/3rj3Y/tI6LL/8VMw5bRlQ5HkFFuLJAyOWxK5XN+LNe5/L2OeIS0/GjBMXwRc8uLtJ13UQb26E2dOVtV945lzozGM7rkkpsfbNDfjY5Z+FneaitfiIBfj9bT9GRWVhfk5k//q80bjpaiwyEwZ2v92AN+95btB68GBNOY756NnYu303Zp24BL4ivekSlbp4VwQv/v6hQXmzhSIw68QlWHLJifAGR196xVJlWzZ6mzrw8p/+hUR3dOC4J+jDMR85G3Xzp0L3p56mJHpjeP3WJ9C2IcPkkwDO+daHUTahMClWMxXiYQCeB4neGJ75yb2I7e2F6tEwcclM+MJ+GNEkWtftgG1YCFSFcebXroK//ODzhNrxGPq2bczYLhQV5QuW5HWG0TYt2EkLEIAn4CuJPMGubacybwgx5qrW7f/ecFD/r8lEEjsaduEH//NLvLV6HYDUcpX3XXkBPvmZD6OyqiJPI6bRwLFsWEkTPU0dSPbFEaqrgDfog+bzQNVUeLIEENJxUjdVAoBQALnvBksddJN1YD+haqNiOctoHPNIGKlrqJU0UxlCRCpAytcyt1JgRBJIRuLo7M8iUjd/ClSvXvQMG4XmOg6wb5JFVfMy0eI6Lsx4EtGOXkT39MBfGUL5pGrofi9UTYXrurBiSTiWg3/+15+zplScdfJSLHv/ydALsASKlTALLN7Zh8UXHofJy2ej5a0GxLsiCE+oxILzjkHruh1Y/9CqYaVpS0fxeKGXVcDq60nbHpg8FULJz+YPyzBh9CWw+ak12LO5CYqqYtqx8zHz+EXwBP1FCcRd24KTTCLZ0QrHNKBoOnw19dCCoVG/zMG1bThGAsk9bXDMJBRVh6+mDlooPKzvzef3YeGSefjVTf8L27Jh2Ta8Hg8CocHLVWh8sg0LezY3YffaHVAUBbGuXkxZNidr8O3aNlzLRGJPK5xkHELR4K2shhYMId7WAtXrg6+mDkJR4FrW4H7VtfCUlZfs76Xr2HBNE8k9rbCTcQhFhbeqFp7yipId80hwbRt2PIpkRztc24Sie+GvnQDVH4ALoK83imgkCttyUFFVjkDAB59/6M+HlTCQ6I1h02Ovo3NHG1SPhpknLMbUFfPgDfnH5I2MN+yHN+xH+aTqYg+lKFzHgbRtJDvaYMUiEELAU1EFb2UNhDayN6+Rvii2bG7AQ/c/DtMwoGk6znrPKVhx3HLoQkH3rnaEayvQ196TM59514422IZZkAA8E86A50GyL4bda3cg2RvD+odfGZQSUAiBhecfi1BtOeoXTYf/ECtlubYNo3MPknvbIfsL8CheHwITp0ALhvNSPto2LLRtbMSqG/8F6Q7+ufEEfTjzq1ciVFdR0Iusa9uI796VdkmOFgghNGP0ljp3bRvx1maY3UNTKan+IMIz54za742KLxmJ4/lf/T1t2ek5py3DkouOHxKE77vuJNp3D3mN4vUiNG02oju3wVc3EdI2kWhvHdrP40VZhs25xeTaNozuvWkzTCkeD8pmLyi5MY8E17YRbWyAHRuajlQvq4QdqsSVF34Kba2pzf/+gB+XXXUBrvvcRwctX7MSBprWbMHqvz495Dz+ihDO+OoVCFblr/IuFZ7rOLCjfYg2NgxpE6qGsjkLoHi8IxIT9Pb04Qf/80s88o+nBh2fPnMKbv7rz7Hz+bWYcuQcvHn3v7Hs/afgxd8+mPV8NbMn4YTrL4AvnP9qpZlmwMfuc6EiEpoKT8CHdQ+tGpKPW0qJDf96FYqqHlYpV0XT4KudgPJ5S1C+YCnKFx6BstnzoYfL8xJ8A6kL7KobHxkSfAOAGUvihd8+WNDKX1JKWJHejOvhUzM6ewbWHo82diySNvgGACcRQ6K9Fa7L6qd08GzDwrqHVqUNvgFg27/fTpt317WMtME3ALhGqs1fPwmqx5s2+AYA1zQQa25MLXcoIa5tZUzv6pomok07S27Mh0u6LozOPWmDbwCw+rrhxPqwYPH+QkyJeAJ//cv9+Prnv4ee7v0bEI1YEqvvGBp8A0CiJ4pX/vRoSVeGpEPgOog2bk/bJB0bkR1bRyQlspQSLz332pDgGwD+8xs3YN19L2DOKUfg5T/+C5H2bvjC/qzL5wBgxgmL4TnIPXgjjQF4Hri2g42PvZ61z6bHV8NJt5v3IAhFgaLrUD1eqLonVQFTCFgJE8m+GJJ9MTjWyARorutix6oNWYPZ6J6eQZsj8k06qcde2RhdewaeEIwmrm0hsSfH99a9d2DNHdHBsE0Lja9k3kcCABsefW1QwOQ6dsageh+rrwdaMIRkZ/ZUqVakd2DNeCmQjoPknuzfmx3tG7U385lI18mZ1lZLRnHN9VcNOf7yc6+hpSn1b+ZYNrY89UbWx/6dO1pLpgQ4HT4pXRhdncj2n+6aBlzz8HNtd3f14k+/vn3IcX/AjyOWLYTm09G+qQl2MvW1tr+4DgvPOybj+YI15aidMwlmPHnYYzscDMDzQQLdjdkrYPU0dxzyGvBMrKSB3t2dWH3nU3jyB3fhmZ/ciw2PvIJEbyy1QeIwOKaNzu3Z36CAVJqfQnJypGSUjjPi/86F4iTj2Tu47mH/v9L4ZBsWnBwFmHqa9w5+2uXK3D+TSM1W5fq9BADXKm4O3gNJ6cJJ5P7eXGuMBZBS5pyhdI3kkLoD+9x16wMwDBO2YaG7Mfe1v6+tO2cfGiVcCTuee8LNzvB75boubNOC6wznplaiYevOIUenzZiMRFcU5ROrB8Un219aB284gGWXnTwk1WXd/Ck44boLsO6hVamNwkXETZhjhJU00fzmNrx+25ODbkg3Pvo6tj33Ds7sL4ZwqBWshKoMpPjJpuB5XRUl9yzwaNz4I1PZJHK9ORpJE/GkNayiO0T7DGf5m+4b+vs+nM3dAqksCDn7lVhmjOGNeXRVNsxtGNdGIWBnWHrT290H27KhKyq0Ybw/DOc9hEYHKYb3O/PuJbFmwoCdMNHwwlpE2rsRqAphzqnL4An64AlkWjYi4Pf7kEgMnrEOhgLQfTpcxxlcKVMCr936OGaftBSnfP5SJHqisA0LVdPrYUQTWHXTI/CVBYseG5TWFXCMkFKiZvYkAKmcoHXzp2DqinmoWzB14E2nasaEXJt0D4qVMIYE3wNtcQMv/v4hmLFDX3+n6RrmnLY8ax9FU1EzZ/Ihf42DJhR4K6qydtGC4aL/kh0KoarwVGbfVa8GgnhzzTo070q/JpcoE0VTUDF16Kym5tWheVMbe2ccvwj6ATfUQtPgrUo/EzpwXt0DV7rwlGf/vVR0D0QJpQoVau7vTWg6FH2MbXoWAloo+8ZIJVSOJx99Pm3bwqXz4PV54Al4MefUI7KeRw94h1TEpNFLUVR4q+uydxIi9R7cz4wb2P7CWvzzm3/GxkdfQ/MbW7HlqTfxyLdvwbqHVsGMpV8S4vd7ceGl5ww53rKrFf7KELqbOoZWypRAwwtr8dQP7sKb9z6HDY+8Ctd1IR0XJ3zqAsw8eTGClcWduCqdK+AYInWBpZecgOY3tmHmiYvRsa0F8a4IamZPwvL3n4KdqzZg4tKZgDYy9z+u7aDh+bVZ199F9/Qg3h0dqGTl2g7MuAHXcVIVC1UVnpAv627lcF0FauZOwt6t6QO+he85BmoBK38pqgpf3SSYvd3p13kLgcCkqaMyJ7hQFPhr62F2d2acBbcDFfjjb36NmtpqfPenX0eoALu5aWzwhgI46qrT8exP7wOEwMwTF2PmCYvh2g6klND9HvgrQoNmylPpxSqR7GiDa6Vf1+mfMBnJ9lb46yfB6PJkXP8ZmDQVQi2d30shBPSyciheL1wj/TKTwKT8pXctFkXTEJg0FX1bN6RfqqcocPxluPOWv6dpUnDZVRdC67++1syehPLJNehtSb9x/Ij3nTTkqYoZN/o3tgroAe9hJSbIxTYtuJYDRVeheYZ3I9XXG4Fl2QAkgqEgU7e+i+r1QguEMi5F8dVNTD2l7te9qx3vPPBi2r7b/v02KqbWYsbxi4bkjfcH/Ljusx/FYw8/g0jf/q/V3taBeDKJ6cfOhzfkz/jzF+/sw/SVC7BncxPevPvfWHDuCsw9Y/khfMcjq3SugGOJFPBWhVExtRZP/+ieQWstVV3FkVeehkBdBdw02UQOhW3Zw1p73bt7Lyqn1cGIJbH9hbXY8vQbMCKpWfGyiVVYdtkpqJ41MeMyEm/IjxM/dRHe/tsL2PXapoG1W56AFwvPX4mZxy9K+9g6nxRdQ9mchYg27YATj+0/7vUhNHUGFO/ovWAKTUdgxlwYrU2DLnCK1ws3XIM7//ow3l6zHjNmTYVhmAzA6aCUT67BqV+8FNIFOht244Xf/GNgBkr3ezH3jOWYe8ZyeA/IFKBoOsrmLECsaSes6P4MGIrugb9+ElzbghXphRYIIjxrAeItO2FFDuynIzBpGrRQuORyQiuajrJZ8xFrbkxtEu0nNB2BSVOhh8tKbtnMSFA9XpTNXoBY0w44xv4ZSNUfgH/SdHznW7/AnvbBQY0QAv/vp19D+IA0ut6QH6d+/lK8cfezaHlr28D+AW84gCPedyImL58NVU+FHGbcQGxvL9b/6xV07WyH5tEwfeVCzD5lKTwh/4gW7jFjScS7I9j81BuId0UQrC7D/LOOgr8ilDFTRqQvih0Nu/D7n9+Md97cAK/Pg/MuOhMfu+5KVFZXQB9rT0IOkaLpCM2YjfjuZpi9XQM3cUJV4aubCG9lzcASFCOawLqHVmU938ZHX8OkI2alrb5bXVOJOx78A/7ri9/H2rf2byC/986Hcc0170dn4x6svOY8vHXfc9izqWmgXSgCM45biJknLsHzv/4HgFQSjKlHz4O/PHS4/wSHhXnA82RvQwue+cl9GdtP++JlqJs/dUS+lm1aWP3Xp7Drtc1Z+5306feiZs5krLnjafS1dmH2KUtRPrkG0nGxZ3MTtr+4DkdcejKmHjUHapYZglSVMwuxzggUTYW/Igjd54WqF292yLUtSNeFa1lQNC1ViWsMVLBr3rUbDZsasPiI+XAMA6quo629E7/5v5vx8vOpTDtLly/Eb27+ESqrClNS/lCYCQNuf0YeVVehH0SVOCtuDGQMOtjX0gFVHQFAEVAOmHk24wY2PPoqtjz5RtrXzjhuIZZdfuqQktqubUNKF65pQqgqFFVN3ZC7DhSPBxBK6lh/P9nfT2hayf9euo6d2uBsmoCq7r+eiLEXfB/ItS1Ix4Fr21B0PVVICQLdnT2485YH8NjDz8AyLRx17BH41OeuxoRJdQiGhgZKZsKAY9qId0WgejT4ywLQ/d6BNbpmwsDOl9fjrfuGLmvxhvwD9SRGghlL4u0HXsCOl9YPaZt9yhFYevEJQ4LwSF8U99/1MH7+v38Y8ppQOIjb//47zJw9bUxX9zxY0nHgOg4c0wCE6M/Kpg26YU1G4njoP2/Mea4Lf/gJBCoyB8Y93b2IxxLo2NOJyqpyKIqCpp1NWLJwNjRNh+MA0pVo27ATiqqieuYEtG/chfX/enUgSwoATF0xH0d94PQh17Z8YCXMAkpG4njn7y9l7fPOP17CSf/x3rR3egdL8+iYe9ryrAG46tFQNWMC4p19qJs3BdNXLsTWZ97E2397AYqmYvKy2Tj5M5eg4fl3MGHx9KwBuO7zQPd5UpsYSsS+gjSqZ2wFZ4FgAD/4zm/Qtbcb5ZVliEXjiEZig/pc+dFLUFFZmgUurKSJeGcf1j28Cu0bdwFCYOKSGVh84fEIVIYG1htnf+0raN/YmHrt4ulYfNHxCFSGs76W+ivUWRYS7S0w+2d09VDZQJ5uoapwTAtbn3oz4zl2vrIRiy5YOeRNat+yLvWAwjRKmv+OgeVfo6iAjaJqgIoxWXQnG0XTAU2HesAlVAFQW1+DG77wMXz42vcDEvD6vQiFMl/7PX4v4PfCX56+jxFJpA2+gdQs6ct/+hdO/fyl8IYOL0ezdCVa3m5IG3wDQMPz76Bm9iRMO3b+oBvC7u7etME3AEQjMXzxum/hlvt/g6rqisMa31ix72nBH355C3ZtbwYUgRUrl+GTn/0Iamqr4T2g0qRQRNo6IgfKdW9eUVmOispyTJoyAQDQtbcbX7z+f3D6OSfhE9d/ALV1VYjvjWDXq5shpYu37v132nTMfa2dsA2rIAF4JryFywPpSuzdln1jXNeOthHNKRuqq8g6o7704hOhaipie3thRBN48bcPon3jLjimDStuYOeqDXjmJ/diytFzEevohRFLwIgkkIzEh5kmaHhc2x6YrT7kc7gukpF4anx9cbiHmU+9lJVXhPFf3/sikkkD7a0dQ4LvWXOn4+TTjyvJGUXbsNC2bice/95f0fJWA2zDgp000bR6Cx7/f7ejY1sL7AxpoGzDQvuGRjzxvTvQ8ta2/a9dszX12q3NsHOk0RurHMtBsi+OZCT1J91TTOm6sONR9G5ZD7O3O5UpyHVh9fWgb+sGmJFeuI6D5re2pX39gba/mD6AofHD4/WguqYK1bVVQ4JvwzDR3dWD3p6+DK/ezzYtbH5yTdY+PU0dGTfjHQwjlsDGR1/L2mfDo68OynVvGCbu+PP9WV+zc3sT9u7pPKQx9XT3oquzG117uxE/jKQIpSIaieHhvz2OD19yA1589lXsamzBrh3NeODuf+GSMz6KrRsbYPe/PwtFwYQlM7Ker3Ja3cCSlX2xwr4nM++WTCTRubcbEsCNd/wf2nbvwfvOvQbf/e9fweP3onNHK7p2tmesheIN+Yqen4Ez4GOEN+TH8Z88H+v/+Qp2vLR+YN25vyKIJRefgMnLUjuEgzXleOkP/0x7Dsey8fptT+LUL1yGN+9+Fk2rt8JXHsSc05dh1glL4A0f+oyEa1uwon0wOvdCui60QBC+2noIVTuoyp1GNIGmNVux5ak1iO3tg688gDmnLsPMk5aMyNOEUqOqKo48Zin+cPtP8YP//gUad6Qq9WmairPecyq++j+fRWVVRXEHmYFtmHj1lsfTbg6WrotVN/4L53/v49DSbNy1DQuv/OWxDMGlxKo/PZJ6rT5+LmFSShiROLY++xa2v7gOZjSJ8IRKLDhnBSYeMWvQTI50nf7y0OmD61jTDlQsXAajN3fuayMSh+u6fOROg8RjcfR09+Gvf7kfb69ZB5/fh0uvuhAnnLIi4zXJMe2MmzQPFGnvPqiMKa5t799EKlJZbaQrEe3ozfq6SFv3oAmmZMLAti07cn69ndt3Yd7C2Tn77dPXF8GmdVvxu/+7Ge+8uR66x4NzLjgN13/h6iGzxKNJpC+KH/5/v0rbZhgmvnDdt/D3p25FwOeBE+nE0ouOQ9u6nRlnwY9430nQ/R5YsSgSbS2wY1FACHjKK+CvnwRF98BxXHTu7caff/dX/PPvTyIRT2LB4rm4+rorcfUnr8R3vvYT+MqD8FcEkeiJpf06ADDr5CMO+ynL4Ro/716FJIDK6fXobmxH+eQaTD92AbxhP4xoArte34yepg5UTMme8upQeEN+HPG+k7DogpUwIgkomgLd74Un4IOiKrBNCztzVL9LdEeR7I3BiBmQUiLRE8Xav7+Exlc24rQvvh++soMPcl3LRF/DZrjm/uwCTiIGo3MPglNnQi+rGFYQbkQTePH3D6GzYX/C/URPDGsffBk7Vm3AGV+5vKSWxYyUUCiI4046Grf97beIxeJIJJKoqq6A1+st6Y2XzW9uy/p0wjYsdGxpxtSj5w1pa3m7Iedr92xqwrRj5o/IWEeDRE8UT//oHiR69m/I7Wvtwmu3PoGJS2fi2I+dM7Bh0opGsufHlxJWrA9VMyfk/LpVMycw+KZB4rEEnn/mFXz9c9+Fe8DP2eur3sTU6ZNx832/Ql19zZDXCVUZVq2IzPmgB3MdB65pIN7aDLt/U7Di9cFfNxFC9aXSnGd5wCOEQCKegKMA4bIQdI82rOV8B7P8pK83ijtveQC/+7+/DByz7QQevO9RPP7wM7jl/l9j/qI5UA9iIqoU2JaNe//6YNY+EybXw6MAfVvWQ7oOtIpanHTDRXj15sdhxvfHA5pXx1EfOB2V0+tgdO1FonX/JkpICbOnC2ZvN8Kz5qGrL4FLz/n4oGwo69/ZhK9+5ju48qPvw013/xy2dHHkFafh5Rv/lXZcldPqUDdv8sCm4GLhVTUPNK+ORReuxIk3XIQlFx2Pjm0t2PL0m+jY0oxF7zkWJ3/mYiw492jsfHkDoh09I/ooXfPq8IUDKJ9UjXBdJXzhABQ19d8sHRd9bV05zxFp7x4S/PS1dmHT468f9Fhd20a0aeeg4PtAsaYdOYvNAKllJ7te2zQo+D5QdE8P1v/zFdhm6VTXG0mKoqCyugJTpk3C3PmzUF1TVdLBt+u6w8rM093UMeSYlDJnJdnUawtbdbWYzISBN+95blDwfaDWtTuwZ1PzwOfDqepoR1IBeLaASNXVgadnRPv0dPcOCb73aWpswTc+/z30dA+dffb4vZh7+vKs5/YEfQjVV+Qcg3RdOIkY+rZuGAi+gVTlzljTDrhmMmeig/pF0/DcM6vQ3dUDAAgE/PjwtZdnfU1ZeRiz5s7MOb59erp7BgXfB0omDXzp+v9GX09k2OcrFYZhYtvm7E8Lvvz165Dc3QjppuIJu6cDwZCLc771AZx0w4VYdtlJOOFTF+D8730cU46aC1UTg4PvA0mJaGMDHMsaFHwf6J7b/g7DsODVdfgrQjjp0+8d9CRF0VTMOH4RTvqP98KIFrcMPcAAPC/spIXyCVVofHUjXvrDw2hduwO9LXvRum4nXr7xX2h4YS2qZkzE+n++gse+czt6mztGdJ11JoqmDuQBz0b3eWAlhgbM219aDzuRPq9vJtJ1Bl0c00l2tMN1s6/jNmNJbH4682YxILVhzDbGZgA+2iiKgsAwihyk6yOEQKDq0F47VrmWg93vNGTts+nx1wfSig5nA6GieaD7vTjp0xenzWAkFAUnfOpCaL7U7krXdVJrMq3UHymHf81y7NS69X37SnJtxKL9XMfZvxa2BLKWGYaJO27+W9rge58NazfDtmx07e1G595uRPoiSPTFkOyLo2JqLY756NkIVqefaT7yilOHVTFTug6iu7ZnbLe62rDsspMzVn8WioLpZyzDbbfcj7/++X4YRuq9bebsaTjhlGMynvcb/+/zabO/pGMaJv6aY015d1cvIpEoujpT/1Zdnd0wizSRtO/nLPUn+8SYrmuors28TKiishxTpk6Akxy81t2O9CDZvA3BgIlJc8pRNcEPbyCVRc3oHDohcyBp21Clg7nzZ2Xsc+ctf4MRS+LpH9+Dzh1tOOnTF+P8734c5377w7jgex/HtGPm498//xvWPfwyrIOMZ0YaA/A8UFSB1vU70fzGtrTtu9/ejqY1WzD5yLlwbQerbnwEZjz/d2OqrmH+GUdm7aP5PAjXV6Kneegvgp00BzZPSinhOnb6AjgHcI3c35cdj+YuJ49UMv1sHNMe0xsyR5sZxy/K2i4UMbR62b7XHpfjtUJgypFzDnlso42VNHIGrdGO3oEAzVNekfOcnqpqqJqKiml1OO87V2PO6csQqArDXxnCjOMX4cyvXgEzbsCMJuGYBhKtLejZtBY9G99G37YNSO7tyPkmLaVEsi+ODf96FY9/93Y8+NU/4pmf3IsdL68ftPmNhnIdG04ygfjuXehr2IzIjm0wuvbCtYs7yZCIJfD2mnUZ2+cvmoNb7vs1/nrz/bj8/E+gYUMDmt/Yhud/8QAe+uqN+Oc3/oy2DY048YaLMPPExQOvC1aX4YTrLsDEpbOgDqN4mmMkIbP8/DnJBLw+4KTPXAzfuzKy+CuCOOqas3H/A49i+9ZG7GhohJFMTTpVVJbjh7/6Nj5+/QcGPWWcMWsqfv3nH+CUM48f9prtZNLAjv+fvbeMj+s80/+/Zxg0I2ZmlixblkFmjB07tsOcNCklhTTFlLfb3fKWm223W24aBidxzMwgW5YsZmYchjPzf3GksccayS64/X32n+vdnJk5c+bA89zPfV/3dbV0zPp+akYyf3jtZ7zz+l7uXP84qxdsZ9uaR/n1z/7I6Mj4Tf3GPwIetxvn5DimtibGay8zXnsZS3c7ot2GZ5Y5XqVW8eAH7pp1n+ERobNWvkGq0rlME7jMk5JUqcfrp0M/G+QeN5HRs7tE2212LFOxQseZOrorGnFa7b6qbPPRy5iHxjEPTuBy/GsD8Pc54LcAHtFD4xzSXgAtR6tY+Nh6ui40YB0zYRmZ/Kc0EWrDgkiYn0n3xaaA7xfesYS2k1cC8uZkcpmkDety4RgfxW2aAEFAHRaBQh/kkwK87ks3PCZJKzRwlkJ0i7isDrxeDyq9Zs7ueEEm/FUNne/j1kKpVZG5toSmWSoXebcvCtiACdJCMGvdfBoPBNanzr19EfL/H8kQKm5iwtcYdb6spCCTo42OwzYQWI1JHR6FMPWsKJQKRLWSkIRIorOTQICxjgFOPP829kkrSp2atZ+9B6/lKq/c43Jh6+vCNTFGUErGrG6z9gkLB7/7MtaxqyV28+A4F/58gK4LjSz+4KZ/eSPU/4vwiG6cY6NYezv9tlt7LNgH+zBm5PzLZBJlchnaWTjaIaHBfPMHz/Hpj36Nro4efvT8NxBbh6k+U+/7jEf00HWhkd7LLaz+7L3kbioDLyg0SlR6zU33G8wV3E3DbRpHExVO9kMrkTnc2MYt6EINuBXws1/8iUP7JFfGyKgIlNdI74aEBvP0sx/gsQ/fj9ViRalUoFSpCA0L/qsUp1QqJRGRgYNFfZCO7/z0q3zxmf+gpandt31ifJJf/fSP7HnnEL9/7eeER9x8M+psGB0Zx+vxIAgCCqUCY/DV6qFHdGMfHsA+6E/vdE2OM2GawJCaiaALCmhCFR0Tycata9j7zqEZ75kmzQQFG3FMzp3VlimUIAiSI/dNGBx5BPmsFBSAyKhwlDo1SQuzydlYimlwXFI78YJcpSStvIDM1fNoOlyJ+A9Uovtb8H4AfivgBcvw3N3X1jGTX6OJeXCc8JQbN0T9vVDrtSx4aC3BCRE0HbzkC2gN0aEUbF2Cw2Kj+WhVwO8mzM9EELyM11fDNeVnl2kCmUqFIT3HTxcYJKtaQSb3ccACHlNYpC8YuBYOk43mo5U0H6kisTSLlMW5NM5BQ4krSv+XmgG9D3+odBryNy8iKDKE+j3nfB3punAj+VsWEV+cPqupjkqnJm9zGUGRwdTtPu/jPuvCDORvWUx8cbqkN/z/E8jkMiIy4uaUN01ZkkdfVSuJC7JQ6TWoI6KQKVXYBnp91vGCQok2KhZVSJifIc9o2wAX/nQg4H5dVgcXXjhE2cMrEO3dfu+5rWZck+OoQsNnBCYuu5PK14/5Bd/XYqC+k97qNlIW5/4/KaP5r4TX7Z4RfE/D43Ji7mwjKDl91oXPrYQx2MBdD2zl7MmZi+Md923mlT/vpKujh4SkONIS4jn/TuBGONElcuY3u1nzuXv/puST7CY8H2QqFQqNhg8+8hmCQwyEhAYzOjJOd6f/c/Twk/eg1fovKtQaNWqN+u/S+9ZoNTz85D3semv/jPe23LmBXW/u8wu+r0VHWze//e+/8MnPfRC15m8b6yYnTJw7dZH//tHvaWpoRRAElq1axKe++BESEmPR6rR43e4ZwbcPXi/mzlaCs/IDBuDBIUa+8s1nycpO48+/fZWxUSnuSUlL5FNf/ChqnQ6XUonHNXvVRhMR7RuLNOFRc9NQZDIEtZaaqtk9T5avXoI6WEfObaV4XCJdFxroqWzF6/EQFBlMxqpiIjMTKLpzOSj+tSSQ9wPwWwFBuKHg/PUTjnYO56e/B5MTZtwul09GLDjUiFqvIWdDKenLCxFdbgRBhlwhwysT2P/NFwLuR6XXULi9HFtvm1/wPQ2P04m5vRlDaiYyhRKHzYZcLsdtd6GJz8DrEfE4bIiWMb8GMZlKLVk8X3c+7CYbR3/8uk+yquNMHas/ew/dl5qxjs6c0JVaNfPuXh4woLOYrTgcTrxeL4Ig3FQWQ3SJuOwOHzdfxIvb4yEkdOax/jWQXPa8gFe6T65zBbya8fciyATkKgXKqeynNIh58XpBFD2IDjdepHtJJpf9QzKJ046V0+dKFXTzGalAUOk1pC8vJHFBpuSEKUi9CDeT6VLpNKQtLyRh/tXvyhVylH9Fluz/CpxekfkPrOHgd17ySYxeC2NsGDF5yRz87kvE5CVL51euQBUajtIYPDUWeRFkshmujvZJK/X75nYHHm7pBYVacsm4jodsH+pHaQxGuK4CJjrd9MxCw5tGw/4KYgtS/inVP6/Hi8Nik6p7gkTJU2pufRbZ4/HgtNjxeqRnSqaQz9n46hFFbEP9c+7TbTFNJTX+NVP4ovL5JKcm+GRRp7F+8yqevP9TAGy/+zb6zjeBADF5KaQvL0QXZsDr9TLY0EXLsSrMg+PSwlwQEPCi1CgRZPKAwd71kKs1CAqFHw1FkMtRGMOQ64x4vQJylRJBruAb3/8CX/zkN1myrJR1G5ehVCmpqW7khd+/QW5hls/U5VYgPjGWtZtWcHD3MaJjo/ji1z9BWVkxcoUCURRZuKiYb339p/T1zGw8f/PlXTz59IOzBuAOk02inU2Pq9fMf2aThborjcQnxfEfP/wiNpsdrwfCw4IJNhoQ7S5sbg84r8kmCzKUxlBkumDpGng9iNZJRLsdWVDg7LROq+aRx+7ioUd2IHo8CAoZMkGG4PHidrjRxqdh65WEGBR6AzJdiLR4EqTFJCo1dpsdjVaDoFCiCgnDOR5YLEIXl8TAuH+DuUaj5rY71rL1zg2EhocQGhaMUqHAZp3k+E/f8hsvzUMTVL56jIT5GRTdufxfroLyfgB+S+AlriiNnsrZm6ZiClIYbu4BpCDFGBv2Dz0Cm81OT2cfP/r2Lzl59Bwej4eEpDieePoh1m9aQXCIEfl1k57X62Xdc/dz+Y0TdFc04hE9CDKBuKI05t2zErnMjWMOjpZos+IRRdxOJ6LNSX9zH3V7LjDZJz1MkVkJFG1fgio0CNfYIAq9gaCk1BnUFY9bpO3UFT+9WJfdyfk/HaD8qTto2F9B98UmPG4RQRCILUpl3j0r0YT6L2KcThdDA8P8/L9+w75dR3A5XaSkJ/Ghjz3MirVLCA4J3ARkN1lpOlRJy7EqnBY7cqWC+PkZpKwu4sTlOopK8mb97mzwejx4XE6sfd24JsdBEFBodajCIlAZQ5EpFNhNNpqPVNJ85PLU78pJKsshf8sS1DoF1r5uvKIbVUQijYcraT1e7ftcQmk2hVuXoDZqb4o/eT1Et4ht3EzVmyfoudSC1+NBG6Ina918Upbk+eTt/hbI5LK/OcCSyf727/6z4DDbJOqHVzrev0cv/3qYzRYG+4awWSwkJSew5vP3UvXGCQbqO6dKqgqSFmaTsWoeZ37zHh7RQ9vpWgq2LgGkxdn1gfE0PKIH+6QFy8ikjzM55/80WZHJ5TN4t6LTGZCyJrrcN2wutwyN3/B3/xFwWOz0Xm6hbs95zIPjyBRyEkuzKNi6BE2wHrni1lTOHBY7necbaNh3AeuoSRpPC9MounMZ2jBDYB17rwfROrt+8TQ8Dse/zPk3NCyE3778E7707Lc4e/KqsY5CIcdmlbj9MdGROHqtLP/YNqyjJqrfPsVk7wiCTEb8vDQWP7mZ1uNVTPaN4PV4mewfISQuDJVWhiY45IZ0BEEmJygxDVNbIwByrQ5lWBz1+y/RfroWt8OFQqMibVkBS9Yv4Pilt7AODoDdBB4v6evmc+c9G5Gr1Gh0t44GFRJq5N++8zk2b1tH+dIFtByt4uC3X8JhtqHSa0hbXsCb7/2Wf/vKf7HnOiqH2WRBDPAMOS12hpp6qNl1hvGuId99VbijHF2YAZco0tczwB9+/TInj5zD6/Xy5FMP8vBD22nYc4HzU2O8MS6c3I2lRKal4hztRx2ZQOvJWpqP7cNhsqHUqUlbVkDWmgiuvxqiyy3JFO88Re/lFgq2lRNbmIIgymg7W09XRSNuh4vQ5GjyNpWhjdYw2jFA7csHGescRBAEYgpSSFlTTGNbB0UL8nG5RURRgT4kAsE8gXeq30Gu1qCNTUChDyJSredPbz7Pd//tp4yOjPNf//0NDu45xpee/RZf++azaEUBbYySi385FDBZAdB9sZnUpfmEpkb/Q67x3wrh/4Wu6n8mSktLvRcuzJ3t+XthN1lwWhzs/88XArowyRRyVj17F+f/uB/T4BhLP7KF2IIUX+Dk9XqvTnICIAh+5eIbQRRFqi7V8vEnnmPzlrWsXb8MpVJBc3M7L/zxTfKLsvnC1z9BSGhwwO+7bM6pyVNEJpcjU8pRqhSYu9qk4HEWKIKMaKNicUyaaT7ZGJAuIggCSz+6hajseOQKRcASqt1kZd9/vIB9YuYkpA3Rk768iLjiNJRaNXKlYtaMUlN9Kw9vfwqbbeai4fYd63nu658k+DrNV4fJxpFrMu/TUGrVZKyWDH9sVjtBBh0KteqmM2hum5XJ5noEmYAiOBK51oBpYAxBLmCICkOmkHP8+bcZbZuZ+VIbtKz93D24R3vRxKVy7GdvMR5Avk8dpGXtc/cTFBH4us6Fid4RDn73pYAqMtF5ySx+4rZbxtX1uEWcNge2MTMumwN9RDBKrQqP6PHbptAo/66FwD8aTquD0fZ+qt866ZNcDEmMpHB7OeGpsTeldzwXbFY7I4PDaBUCCtsEcrWGnsYxFCoV4emxeKcm5u6LTbSeuOJrakxbVsCCB9fOqv4wDcvwBPu//SJFO5bRdqqGkdZZytBT2PyNR3AOts/IgMtUaozpOTMCJvuEhbef+/WcOsy6cCPrvnD/3+QvcLNwWOxcfPEQXRcaZ7ynUCtZ+4X7CY6bvanrb/5ds40LLxyk59LMKoBcKWfN5+4jJDHSVwHzej143VL1ydLVKpmQzAFjRi4K3c1LkTrMNt+CSJAJqPXaG94jN4Jp0ozodON2OCXDFK2aLasfYnxskmc//2E2rV1O59l62k/XzviuXCmn/Ok7UKhVnPnf98jZWIptwkJ0dgJarRt9bOINg/BpHXDbQC9yQwSHfvhGwGb9oMhgVj17J47eVh8dUhlkBI0RuUaHXKm4KYWwvwf2SSuHf/gqpv6xmccXFcKqT9/F3Vs/7EeP0WjU7Dn5MmHX8MCdVjt1e87TsG+mo6hMLmPFM3diiA3lP772E3a/cxC3y82i8gV8+bmnqfj17oAxSfrKQvI2L+LYT95konemy6c+wsiaz92HNlgvVZLMNkS3G5fFwXjPEOogLabBcSLS4zjxi53YJ2fKoBbukNy4K1895rddkAnMe3Qdr76zlzsf3MqnPvRlFi1bwGMfvAejQQ+CgMlkISImEpfTjSiKKJVKXC4XgiDwySe/yNDACJ957qMsnFfA5MAohqhQDn3v5TmvR2xhKqUPr0UbfGvYB37/URAqvF5v6fXb38+A3wLIFApG2ztZ9vQ2Lr582O+BM0SHUnLvKtpO1aDUqlj96XsISYj0Bd8etxuXaQL7YJ+vI1hpMKKNSUCmUt9Uk+H46ASv/nknr7z1K/ormuk/WIPodBGXHM2Pf/hVquub6OronTUAV2pVM2SgPKJ4Q+qFNjIGa183gj5yVq621+vl/B/2cds3HkOpmf32CxR8g2S8c+Wd01x55zRbvv3krBP36Mg4z33ymwGDb4Bdb+7nvke2M29BgW+blD2smRF8G2JCWfzkZtpP1bD/3/+My+70ZdAKty1FE6yfkxLhcbuwdLUhyGVoYlKoevssnecafIoycpWCjFXzKNxWzolf7JyxaneYbFx+4yQL7l9Bx9n6gME3SBNs5atHKX1o3V8V0DjMNs79fu+sEo4DtR2MtPYRVzS79NPfCpfNQX9tB5dePuIbtOfdswKlTkP1myf8BvKIjDgWfeA2dGGGfxpneFoB4PrnzmV30nG2jksvH/HbPt41xPGfvcW8e1eSujT/76I4eEQ3OpkIo0OISM3KuhA9p/93z5zfC0+LvWFg5bTaqXjpMM6pDG3q0jxGWvsITYoibVkB+vBg3E4XvVWtdF1owBgbDl73jOAbQB0RhRBgIS0o5ETnJDFQF5jLDJC5qhiV/uZMV/5WTPQMBwy+QTJ0Ovu7Paz85J3/0MoFSIvaQME3TPGff7ub1Z+5B41Bh8ftxjE2jH1oAIVGiyo4bM4AXJArbqphDaSEykTfCJdfP+bzUQiKCiFvcxlxhWl/8/l3Wh24xizU7DrDWPsAcpWS5MU5vLHrt3zpc9/m3JlKtm5eEzD4BukcXPzLIVY8cyfWUROXXjrCui8+wNnf72X5U5uxDw+gjY6bk44ik8uRaXVoYhKpfuvUrEpZ5qEJmg5dJq0sCbd5AnV0EoONvTQdPoR1zIwuzED2uvlE5ybdkkSD6HTReLAiYPANUg9Y4/6LfOkbn+TpDzzn2771ro1or0s6OEy2gME3SHPYmd/sZt3n7+bTn3qQR564iyceeJaPP/M4Na8cn9WW3St6aT1WHTD4BrAMT1K39zz5mxfRW9VK3e5zPpfRiPQ4CrcvJTw1losvHQ4YfANUv3lS4vsH6/3md6/HS82rx7nviW385tcvsf3ezTz/o9/x5svv+X3/1y/+iD/9+hWOHToNwKee+zALSov4/o+/im3URGh4KCqdGtuo6aZMjayjpn+5HOr7AfgtgMfl5tJLhwlJiqLkvlWo9BrsExa0IUEotWo8oofM1fNQB2n9uN8etxvbQC+OEX+DEZdpEpepDkPa7N3I12Ji3MTTTz3Ched3+Ul99VW30VfdRuamhUyOTGCxWJEJAjarHbfbjUKhQK1R+zRORZfo0wOXyWWoI6JwTgQeQASFQuKhabQ0H59dogqkgXu8a4iYvORZP6M26HCYZjcTkSnkyOYoG1vMFlavL+cHP/0aCrkcBDhy8BR//sMbPq7db59/gf/88ZcxGIKmjstO0+FKv/3IlXIWP7GJs7/d7aPSgJS17ThTR/+VdtZ96QH0YbNTUryiKElixSRz9o8HGaz3NxoQnW4a9l3AZbVTuL2cylePzthHb1UrJfetouVY4AbZafRVt/3VWsFuh+uGpjkN+ysIT4/9h2agPR4Pg43dnP711YE2fl46Kr2Gc7/fN+Pzw829HPr+y6z/8kO3nJbiMNsY6xigcypwSyrNIjQ52jc5ux2uGZmca3H5teMkLsj6mwJwj9sFXtCoVTgmri4G3RYz4WkZKLXqgDr9IPGaYwtvbBLicXvor2kHYLChi/w7FrPimR24rA6aj1Yx2TsiKQmUZrP2uQcQBPCYZy785Bot6pCwgAsitV7D/PtXs/9bfwm4uDNEh5K8ONdnFHYr4LTaqd87d8VzvGsIl935Dw3AXVYHDTfg1Zv6x3Ba7Ki0Kixd7bhM49J3zS60MfHI1JpZZVy10bG+4MGX2fZ6JafJa3okRJebgYZOTv3qXb9KhHlwnHO/30fm6nnkb1n8VwfhTquD1hPVVL1xwm977btnaTlaxdf//VnOnq2k6VDlnPsxD01gGzP5grLO8w1EpMXiMDuQOcfRREb7zXfTz4bEeb66ABGd4qyB/jRaT9aQuaoQRVAIFS8fIzQxitKH1/ne77ncQtfFRhY8sBaZXIZCJedqr45/3wRITpAelxuZUhGYSnQNXHYnrTeYF9tO1rD+aw/7XkdGhfPRZx7zaw4VXW4aD82tsGafsGAenkSFiWidml/89lsYNNo5hSGSynI4/evAzbLTCE2M4so7p2m5TqRhuKWXE798hzWfuTdgBfdatJ64QsriPOr3nvfb7rTYcY1baGvt5JEP3sPzP/odoWHB3PfQNjZvWYNcLkelVvHRTzzK4vL5rLttOSFGI1U7T3H67BGf/LBSqyb3toU3RenVht44lrrVeD8AvwWQNLJFUpbkIZPLaT9di8vmRKlRkVCSgXXMTMULB9n8zcf9v+d2zQi+r3kXc2cbwVl5N7xpdCoVVX8+NKvObtPu86z4/D047A4O7z/J+VOXOHvqIpMTJm7buobPfOkptEoVzYcr6Thbj9vpIjQpivwti9HGJOHo7+L6urJMrpjSBJZjvoECDMytEqPSqslYVUTNO2dm/UzC/Mw5GyiC9UEsjE7i0n+/h9vhQiaXkVacxm//+F988xs/4dSx8/R09+NyuGBKkUkAbGP+WafE0mx6Klv8gu9r4TDbuPzacUofWTerKofH7UKmUuOwuGYE39ei7WQN67/8IAq1ckbAMt3AFagB9frPzcZ7mw03o8dsHTP5KA//KDgtdipf8V9sZKwq5sKfA6txgFQB6ThTR+aaklsWuFlGJjnyw9f8eNHtp2vRRxhZ9em70YcZ6b7U7KtgBILX46H7YtMNXf+uhUd0I1qtWPu7kSmUKIIMMzLO7vEhyj+ymWM/f3uG5r0gk7H0o1tQ3ETQ73a4/B5hp8nGQH0XzUcu+7Y5zDZq3ztL++la1nzuXjweHVitSM2cclRhEWijYgLLj05BF25k/Zcf4tIrR6SA3ystEpIX5VBwx5JbvpDyuD1YRm48HtkmzARF/vXUrdkgiuINn1WQgiWtQeULvqdh6WojKCkNW38PLtPV4xcUCrRRcQgyAbfDyUjHIJdfP+FzjtWHG8ndVEZCSQYqvUbqnfnj/llpQE2HK8n4G6oQDpN1RvB99T0bta8cZ+Vj66n880x5uuthHpxAY9Bhn7Aw0TtCZEYc1lETBoPgSyZ43G5c5knJtM3lRK5SoYmMkZr6FAq8Xu8NTdhcNgfI5PTVdZC/ZQmNBy5y8Hsv43GLUh/NgizyNi+m53ILbqeLmJwEZC4Lom0SdWQM6pBwZAoFTosd24SFxoOXsIxMoA8zkrVuPtpg/azn0evFz3o94PHZnQiAWq1i8/Z1fOwzTxIe6R9Iii63L/M85zkdmiQiVonbMklychIDjXPTyxRqpc/EKxA0wXqCIoM5/4eZiREArVHP+E04E0/0jhCeGhvwPfuY2ZcMy8pN58e/+AbdJ+uoeH4XotONTC4jYX4m27dvQCZ4Of2bPQw1+M+nLpuDqjdPkFiahSE6FNNA4IQhQNaakr+bgvX34v0A/BZAEASWfmQrg41d2MZMpC4tkLITMoG+K+04zDbKn9qKXCnHaZMMNhQqBbZZg28JXrcL0W5H0M3dJa5WKBnvGiI8LZaMVcUEx4X7ArP207V0nK2j+3Q9yeV5pCoMZK5fy+c+9xEmzGZ+/5uXsY2ZOfbLXX6a2wN1nQzUdVJwxxKSS9Nw9F9rLiCALggUKmDypjjI+gCfcdmnuOdukbRlhXSeawj4AGmMOop2lM+aXbSbrJz46ZuYB8d92zyih56LzQw1dPOVrz3Dhz7wWaKiI1Beo0PtRVoVXxuEJy3MliawOdBT2cL8+1fDLAk0mUKJQm+g/ljdnPvxer3013YQkR5Hf62/eYMgkyYjXZhhzgFYkAl/dWf3zZRcdaEGhH9wwOuyOf2CXLlSgUKlxDI8d0Ng68krJC/KvSW8YbvJxtGfvBGwKdEyPMnRH7/B2s/dO+fAPo2b+cw0PKKIc3wUa49E15CHhPukA6+F2zyBNjicjV99kIb9l+i70obXCzH5KeTdthBNsD5gNs7r8UjcV4+U0VOoJfUdr9dLcHwECIJf8H0trGMmLrxwkEUf2IguOo7pFKQgv7FahVwhxxAVwuInbsPjFvGIHmRyOQq1EsU/QcddJpehDQnylf6VGhXa0CBEp9vvGv+j7yW5XI4uzDBrSd/3u8F67MMz1S9Ehx1zezOayBi0MfF4RbeUjJXJsI8O4RG9jA+NcuY3u/2+ZxmZ5MKfDzDWNUj+1sWMtg/gukHg13S4kuK7V9x0I6rL4aRhf2AKxDTGOgfRaNRoQm7MUdeE6H1zjUqnxu1wSWopzlE8Hi+C2425vVkybJuC2+3C3NGCIshIUFKapG8dIHFxLZRaNYJcTlhyDMd//pZPFhWkam/HmToGG7pY/rHtuOwO9n/7ZVZ+cjsqtRZbbxei1YIyLDZgFrjtVA3pK4oo3LY0YBAuCJK3gds+u/GLXKVArpCz99QraLQadAGqjXKl4iYdhoPwuqX/p3RYCImaW0vc4xZR6tSz3iuJCzLpODNz/gpLjSFzVTGhSVE45vDomIZKp8Y9i8unKliH1WpDJhP40c+/QdXvD/jNdR7RQ+f5BuQqBTkbS8lcXUxyWTZdFxp9TekgiVo4rXZK7l3Fif+emagAiC1IQaFW/sOTSn8t3g/AbwHkKgUe0UNSaTYN+yuofe8cHreITC4jviSD3E1lqHRqBhq6aTsp8bMjsxJIXZqHItiDe2L2QVu0W/G4HCgNIbNqwFqGxsndtJCI9Hhqd51lpE1a/aoNWtKWFbLyU3dRs+ssE+2DNE8ZBtXvOkdMQQrPfeUTnPj5zlkNb668fZqEkkx06blMDA5iMBqwub2cO3+FlWuj8dhtpK8omEHluBYqvYaQxEjfa6/Hg91k5crOU3Seb0B0iQTHR1D+1FZaT1yh7cQVXHanTxWkYOsSNMbAA7vHLfrkrQLBabHTfrCShx+/m4zcdAzGq4OZSqcha00Jl18/7nestom5m6G8Hs+sbmEgSWMJirkH32m47S5kAQKouOI0FGoF6SuLufza7NSH2MK0gDzduaBQKwlNjvZl0QIhe0PpP7wBUrxuIJYr5TfMYsFU9nauzr6/A6aB0VnvHZBK95MDY0Smx9E8xz0O/HXKRh4P1t6r2Ryv24VCG/h8uyZGECwTZK/MIm9TKTKlciqgDbwg9bhd2Ib6cY4M+xrQ1DFJROcn03+lndSl+bQcr57z8Ppr26Ux7G/kx6pmMW651VDpNWSvX4BtzEzupoUYY8Mx9Y+i0KjQhgTReuIKw809s+rR/61Q6tTkbCyl70r7rJ8xxoah0qlxTAYeaz0up6QFLgjok9KwD/X71FG0iZlc+HFgyViQjN6Sy/MZG5h7AQASF9bjFm8YgHu9XjwuJ47xSca7h+f8LIBpaJz0FYWz8uBBWtjLlQqfVnzSwmyaDleSVp6D06JDFD24x0f9gu9r4TZP4hgfQWkII2VJ3qyLSIC0ZfkIQNOhSr/g+1rYxsy0HL1M9oYFeNwiZ3+/j9XP7kA0T+IRRfqutM8IvqfRcqyK8LRYkstyZmRWFWoVqUvz5qTkpCzORa5WEjbL3AZSAJ61tkQyy5sFKr0GY0wo9h7p2nuddpRB4ehCDbNq8nddaCRtWeGstCm1XsvIdVrhORtLicpKpGbXGUZa+1j7hftRB2nnrKgmleXQdrJmxnalVo0+OoSU1ATMkxZsff0zEk1KnZrFT25CdLm58OeDknmhUUfqknzyty7hzK/fk/xV9BpM/WMMNnSx8lN3UrfnPAM1HXi9XrQhQaSvKCQyK4GqN0+w9CNbZj3WfwbeD8BvAdwOF0GRRo7+5E2/ZoNpB7Chxm5WPHMnl65pWBhq6qF+z3mWfHgzhpAI3BOBBziZUoW1vwfnxDj6hBQmzVZfZ3uQXotCIcMQGYJX9HDiFzv9+MAOk4263ecY7x2m5J4VCDIZ67/0IAgCtjET7WfqsE9YAtrQX4uG/RdI3TCfF/6yh9yCTL777z/nlXd+hWOwF11MHC6HizWfvxeFSolH9OD1euk8W0/bqRpEp5uyxzf6mjw9bjcOs51D33/FLyM10TPMwe+9TPqKIm77t0dBQNIrV0mZO4fFNrWokSNXyVFO6aQ6rfZZB8hp9FW1se65e2dwPmVyGSlL8mg/U+drxHSYbOjCjLM290x/by4+ukyhRBMWTkRGLJ3nZzcQ0Bh1xJdkkFiaSd7mMmQKOcPNPXSeq6d4Rzkuk4Wk0iw6z9UH5GyrDVrm3b38rzbnUAdpKXt8Awe/E1gFJSY/mfDUf7xOrsaoR5DJfFQOl82J2qhDJpfNKV8XmhR1ywxI5goWptFb2ULu7YvmPM7pxfbNwjk57rdwcllMaGMTAupug2TU4rGZUAaH47ZLHH6lTkNQZLCkDjR1P3rcLkxtzYg2/4DDPTHM/PtWcqCtH124YVaK1dUfBNuk5R/uVzCtzT2dpZrWiBddbkSHRKWSKeV/l+lSeGoMSz9yOxV/OeyTfgUpUMnbvIicjaUBq0BOqx2P2yONMwq5pMl/TdVNdLlx2Z2SHKpMNkOL3xgXTkJJBt2zqKAs+sBtUtZRpUK0z0ED83qRKRQ+Prhcp2esa+SGC/rOU7VkrptP896KgPSCmPwUMlYWYYgOxWV1ILrcKLUqJifNuJxuPF4PKpUSo1GSS/S4XEw21aEIjgiY5Y3OSyZjZRG6MCN4vaj0GtxOF/Hz0gNK8goygZL7VvncbiMz49GGBLHwsfVSD0RIFKLNhUwdhCoyXpLUVGl918NjNeE2jeIYGkAdHEbe5jL6qtsCVq+CokLIXF0szUUXZh+DATrO1ZO7uQyQKEIeBNTxGcjkCkJUNjLXlNBy9HLAZ79u9zli8pNnUKsUaiU5GxfSU9kSkJqkDQkib/Min+fDXNAE60ldmk/bqZmBLAIsfHgtXnHaf8MrzSODw+TdvYyK3+wNSJ1zWh0U3bmQ7ouNASuQbqcLfWSI73VccTphydEc//lbvhij5VgV+VuXcPHFQ8gUcpLLckgtz5cqsoKA02pHY9TNpLEIkLNtMW+8upunP/0EGoWS46+95v8RQaD8I1toOlzpdy9ZRyYZbesnPDWWpR/dwpEfvY7TbEMbOrW4bumVKhN3LAUkikrryRpq3ztHdG7SX52s+kfj/QD8FkAQBJoOVc6q5GGftNJ44CJpywqofe/c1JekAP30/7zHpm88gts06rN99u1XoUCmUOJx2PE47DgtZn70rV/icrr57Jc+gn1gFNE8gSY+k8pXjwZsxlNqVGSvnU93ZQtNhyp9jY7GuHDyb180iyG8PyZ6R1ErVUTGhLN31xG27liP0mnBNTmGXGfEOuHk0qvHfBlVpU5NWnk+az5/H3glSSO5QuKM28fGaD7REHDQdFkd1O85j2VonNKH16HUqrFNWKh99wztZ+t8vLD4kgyKdixDpZXjFcVZu7Cn4fV4CNLr0IfObJxUB2lZ+am7aDp8iZajVXScqyNtaT5X3jk96/5uxEcHkCmVJJRkcvn1E4jOmRztkIRIyj6wkcYDF+k83yAFJALE5CZT+uh61EFaXKZxhltHWfb0HTQfraL1eDUOsw25Uk7iwhzyb1/EQEMXiX9F4DeNoMgQNnz1YarfOkn3xeYpHfAgstfPJ3lR7i1RBpCr5CQuyPQtSrxeL33VbcSXZNI1xySZt3nR3y3xNxtuRmVIkMuQyeXMf2DNrHz1kvtWoVDdPMVCvL7ZzuvFOTaCLjbBLzM+DbkuCHlwDCeef5vR9quVC5VeQ8m9K4ktlComzsmJGcG3TKVCn5CM02Ri3XP3YRkxodZr5lxkAqj+Rje+2eC0Sgo4V94+5as6ZG9YQOqSfBoOVNBb1YrX4yUqJ5H82xejCzP8TU2tXtHL8Z/vnBH4OC12Kl89ilylIKEkw3ePi24R25iJiy9f5a3LFHKSSrMo3LEMbbAeh9lG/b4LtB6rxjUVCIelxlB853KCokNRqpU+1+GonCTq913AOjI55auQTtGOcrRhBuQKBZrIWFyTs9PK5GoNXlHEK4oojSHo4pIYOl0/6+enYR0zM945yMpn7uTcH/b5qSeV3L8KlU5D1ZsnfIsvjVFHxpp5KOJDeez+T2IxWwmPDOOxD93L/Y9sxz3ch1d047WbyFhR4GviBZh370o0Bh3VOyWtb5Aa6XM2llJy7yrCkqNpPlrlc7SNyk4gd9Mi+q60MVDXQdqyAvK3LGaosRsIo2bXWfqqpesvyGQklKSTt2UxFb/by3BTr29b4faliBP9U8evZ9kzOySfiPONuO1TfVeLssletwCX04pSpQ84/l4Lt8OF6HQTHB/Bso/dQffFZpqPVGIdNaMLCyJj1Tw2ffNxTvx85wyKkWlgbFZlDY1Rx9ov3E/Nu2foOFOH6HL7V3WDb05SUq3XUHzXcsJSY6jbc9733Eakx1G0Yym68GCuvHOarqlqskwhJ35eOjlbFrHys3dTu/MUgw2SgZI2JIiMNfMwZMRw/MR5Vn/2Xup2n6PjTJ3UO6WQk7Qwm8w1JYgOl6/ql7W2hHO/2+sXY7SfriUsJZqFj28gKCKYwfouTv3qXd98bIwNo2DbUhY+tp7zf5BoneGpsaSum8eAaZJHP3IfzfUt5Odlz8iixxSkSKpCs3irjLT10XmunpTFuTQfuYzL6sAYG8Zk3yiXXjkSsGCavqLoFtVRbx7v64DfAtgmLOz+2u/nLKfLlXJWf+5e2k/VkjxlxSzIZNgnLNhNVqJzEsDjQbSM45qUgnF9UhquiTE8oohcHwoKFU6nC7VWg2gewTU+gkyuQFRHcPB7rwT83SUf2kxXRSPdszjULXx0PaNt/XOWpGMKUlj8xG30D47wk+/+io89+zihrgnk2iAsFjknnn8nYPAflZPIkg9uvjrR2W3YTTb2f+eVWSkvIPEeb//2E8hkMg5+9+WADZwqvYZ1X7gXQfBy+EdvzdkAJVPIJQnDWRrAPB4PnW1dhAQZUCnlyBQKjv98Z8CsszZEz9ovPIAu9MaZQdHlZqStn2M/fdOPlyZXKlj73P2c/O93Av43hVrJui/ej0rpRVAHYR2bRKFSSkowchmCXMZYxwD1+ysoe2R9QH79tFKCxy0iV0lc60AcXJfNgfgPdMK8EeyTVo7+5A1fxUFj1LH8Ezs49/u9M+QgAQq2LSVjZdEtoTTYrHZsQxMc+PaLc35u/ZcfIjQxEqdNUvOp3nnSJ+8WnhZLwbalhMSHo1QrQRAQ3R4pgzpHlcQ+Ooy1u33Gdl1sIjK1Gvtgv68ML9cHoY5IZN9/vjDrYnPJhzYTk5uAtadDcqAzhiHXB+NxicjVKjxOG+LkMAgy1FEJ9FS1zWpFD5JiyerP3I3GqJ9Soph6vq9xc3U7pcbOQPeVw2LDK3oQXaKvitV9qZmKFw76PpMwP4OUxXmc+p9dMxtMBYFFT24irjBlBtVm+nen93stvB4vrSeqqfjL7M2AaoOONZ+7B5Veg1qvxTw0zr7//EvADLM+3MjaL9zHqf/ZxXBz74z3BZnA0g9vQalVEZocjVKjwu104bI5ff/j+oy+6HThmBhHtJlxm8bxXktnE2QYM7IRFCopOSIIyBQKBuo6OfqTN2b9T4AUNLncDNR1UP7RrRz6wau47U4yVhVjiA6dIaE5jbiSDFyJRp556qu+bUcr3sTb1+a77trETE7+ajej7f2kLy8kOCGCiy8eDri/xNJsMlcXSzxjrRr5VP+B2+HC65FoAQhQ885p0pcXcfQnbwScDzRGHSs+uYOjP37DF6BpjDrWfv5etCF6ZAol1ZdqObj7GFu2rUOlUuJwuHj7zb28+epuVm8o5wtf+hj7v/nCrCpCIPGUV3xyB5pgPSeefzug7GtIYiTLnr6DPf/+J9y2a+4TAe747ofn7Clw2Z2IThdejwdBJpuqrPz1i1uPx4PTbJfojx4Rj8uBQqvjwHdfCTj/aYw61n/5QWw2B2q15LMwODDM0aNnmF9aQHpmMmq1CgEZolv0LX4UagUKtcqnKNRxtp6Fj6zn2M/eDHhcq569i5YTV+iapdpb+vA6IrPikSsVeLxePHLQatS4bQ7wCpLLs8vNcFMPTYcrmewbpfyprVS9eWJWGUeQEn0rPr6dg997mbTlBeRsKEV0uhGn6FXDLX00Hb7EZN8oCfMzyVwzj6DI4Pd1wP/P4SY6suUqJVqjHrlKwfGfvunrkDbEhJK/ZTHWMQvHf/YW6csLyFxdjEIp4DJN4JWrsZqcXP7zHt/qW6lVk7a8gKxVhbjG+jGPB+bL6cONqPSaWYNvgMpXjrL6M/fQcqJ6Vppt1poSVDoNMXGRbN62nuBgA96BURTGcC78zxtXg29BcgacLtUN1ncx3j1EdE6SxPseGUTQBs8ZfMMUR9zmoPtM/azqKU6LneqdpynesYjMVcVcnqVDHyB5Uc6cGevxsUm+/Jnv8JPnv45noBuZSsWyj95O6+lamo9U4zBZUaiVpCzJI/e2hbPy0a+HXKkgLDWGzd98nJajVfTVtCOTy8jbvIieypZZ/5vb4eLyGydZ+PBa2k5W03jwki/w0ocbyd6wgOD4CEruWUnj4UryNy/ylYjdDheTfSNUvHjYV5GQqxSkLskjb8viGYsQpVaN8p/odaMx6lj17F0MNnTTfFTKXHScq2fFJ7Yz3NJL89EqXFYHwQmR5GxYgDZEf0uC75HhUX76vV+zfftGwlKi/bLK1yIsJdq32FJp1URlJbDsqTukJkevF4/Dhjg5gnPUg1sXTPuUbrtKryFj1Tx0oUEBqwkqQzDWAHQTa18Xcp0eTVgkQclpgIDHKzXOzVXpufz6cSK+cB+CIKCOTaH2PWninFbICUuNoeTelQRFGPB6IDo70Zcxuh6CIDD//pUoVDKcpklsfV0+yoQyOBRlSDQj7QN0nKsHr5f4kgyic5JQ6TV4PR4sQ5NUvHhoKrspLYAT5meQvb6UkMRIX4CTs3HhjMXpNLxeL+d+t4fbv/2kLwB3mG2MtPXTcaYOr9dDfHEG0XlJqHQan0KOw2IPXKq/Bg6TFdu4hcZDlWStKaHy1SOz0ju0oUEMNfYEDL5BCvgrXztG6UNrMQ+O43a6aD4i0RXiitKk5q+pxm+nxY7dZKX5yGVs42YM0aGklefjdVpwjQ6gCg6R5AiVqhnNrsEJEg1krrEzeVEOx376Jm67k84LjRRuW8qlV4+QWl7A4R8ETtAA9F5qZsOWhzlT+S5ytZJvfOWHuJxOFFP3pioynvHuYUofXkfToYukrSjkyH+9Nuv+ui40kLVmHtXvnGakuddX2cvfshiX04VHKWOsZwhdiIGG/RWz/if7pJXmo1WkLs2nfoqr7LTYqd9/kaId5cgUkJAUx9tv7uW3v5q5iN756h6CjUbWlRfQeGB2Kb/U8gJcDhc9R6tm9VwY7xqi5Vg1RduWcvGlI77t0TlJN1RnUmpu3sBtLshkMjRGnc9l2T7hoH5vxazJJ/uklStvn2bePSupqWnk0Ts/xhe+9jG2bVuNwjKGq6sZF5LDqCo0HHVYBF6v15c4UOk0ZK9bQGRmPA5LYMqULkzqqZot+AaofPUoqz97LzXvnmXBg2uQKaTEY+Xrx+mtbJUoMgJE5yaz8NEN1O05jy7UMGfwDVLFXKaQE52TSO7GhVy+xtUZQbo2Cx/dgMNsJSQhEsvI5JzU0X8G3g/AbwUE4YaDY9njG7nwl4P0VbX5bTf1j3Hmf3dT+uh6lnxoM9qQIGyTNrTBelDqGO8d4vSv/TvfXTYHDfsqGOscoOzhNeiVgSePhPmZdJydu3TpskvKFCEJkQEHn/C0WEISpAZKlUrF/LJC1Ao5To0Wu8mObdwscQtXFaMNCcLjciNXKei60EjzsSoaDlwkNCkahVriFMqU7hnKI9dDrlKgVCjmbDwB6L7UQvFdy0gqzaCzoilgU6EuzEDBHUv8BkDTpBmn04XFbEWn0+B0uthx32a0SgWe8HjwenCN9ZNUEE1KWRaCTNKHFa2TyAQnXo8Gj8stbZ/KUM0GhVKBItRA3u2LyVxbAl5JJ3yuDB1AfHEaV94+TesJ/3NgGZnk4ouHKbhjyRT16RK5G6WFttfrZaxrkCM/fM2vLCo63TQfrWK4tY+Vz9x5yxwubxbqIC2JCzKJyknE6/EgV0pc2/h5aUTlJOBxe6caNgVEpxu724rL5kCpU6NQKX3KOaLT7ZPg84ieqUYoL3i8eEQPcrUSlVY9Y9AdGx3nifs+RVtzB+dPV/Kr332PxjdP+bLa04hIj2PpR26fcb7UQVqf0yleL8qwaEa7TZz741t+573tZA2xhamUPbZh5jmXydDHJ2MJkAWXKZR4BBV2k4NpjtiNNI+toyZJ+jQygWM/fWtGNWG0rZ9D33+V1Z+5G9PAGA37K1j0xCbq916g51KTb9EcHBdOyf2r0WokIy5ze5NvkSDXaBG0oRz43iu+MnhwnMRJd5hseN0iTpuTA99+0U8a0+MW6TzXwEhrH2s+ey92kxWlTs1Ez8icY6ZH9NB5roHU8nxcVgdHfvS636K1+2IzKr2GNZ+9l6DokKnKzY2TISDxvfuqWklfVkD/lQ6MsWFkrComIiMe79S91FvdhsagvWHDqmV4AkEuo27fBSIz4nwmQD2XmlHp1Kz+zD1oQ4OoevMEXRcbcdvdPl5u/d4LFN25jLRlBXhED3azE6/HgUKjRKlR+RIHKq2aJR/azLGfvhWQ05t720JcNgcrP3WXbwxW6TTEFaUx3j10w3PSdPASwfHhOCx2vvKVTyBTynA5g0FQMNA0RMVfDqHSayi4Ywm2cYuPhjMbWo5Xs+CBNZLqhCAw0trLQH0n9kkrmavnMVjRQu6mMmp3n5tzP53n6ln5qbvQRwZLwa5CBghTdAkZBmMQ3/np1/j4B77AqrVLWbV6CUqlktq6Zjo7urnznk3ExkbRV90eUKXIGBtG0sJsVHo1p29wnVuOVbHhqw8TkZnAWMcAgkxGdE4iDovd5yJ9q02mAExTdvVqlZ62U/7jglwpJ3lxHilL8pAr5AiCgMvu5NCe42zdsZ7bNi5FaTchC45EE2/A45KUigRBwOnwoNQpcVlMoJC496LLTWhqDI6pJtbIrASpohIVgtfjRalRUbfvfKDD9MHtcDHePYRleEJyUbWLHPzeK/6UXa9kADfa2seKT92JF26ocoMgmQgufGwDB7/7so/u5NtfXScjrX2s/uw9VL1+guJ7ls8pJfvPwPsB+C2AIBNIW1YwqwGEIToUhUoxI/i+FpdfO8aaz97L3m/+yWc8sOHLD/mttq/HYH03pqFJjNHBATUwlTo1E3037op3mG3Mu2clFS8c9O1DrlKQsiiX1GUFOCw2X4ktNCwEt9OJEBbBWI+Jwu3lBEUGU/XGcV82bfq7K5+5kytvn55y1VQiV2sQrRNkriqm6s2Tsx5PQmkWDqdzTp1SmJJaEz04h7tY9pFNdJxrpOnIZWzjFpQ6NenLC8laO9937F6vl4H+Ib779Z9y5MApRFFEq9Xwy99/j5UL53PptVNYhiZQG3VkrioiNCEEx2AXXvfVQUChUmIZHfFp9Sp0QegSkpGr1HNKtMmVcuRK6TjsJqt/NlOQ9is63Xi9XtQGLcFxEXNSBGp3nWXdFx+gZtdZxKkMosNs48KfDszKSRzvGmKgrpOkhdlzntd/FtRTk5VHFHFbzThtLroqmqnff8nXq6CPDCF9RQGGqFCGWnqJy0/h8uvHffSga7OrZ3+7G7VBR8HWxbSdqqW/pp3cTWUkl+X4JkaPx8Pedw/T1izJPnZ39vLhxz/LV7/xLIs2L2SkqRe5TEZKaTYaoy7gYsXjdkmBs9eLTKlC9Ko4+4d9AStIfdVt1O89T/7WJX4ccZlcjjI4BIMqG1t/N26rBRDQxKUw2NRPza+v6pIv//g2X4PiXBDdIkPVbQGpPCA9LxUvHKRg+1Im+0Y5/rM3yVw9j9xNC3FZHSg0KqyjkxiiQnCZBiVnxmsy9IrQaI794h1f8D1NNbjyzmkq/nKQ0ofX+WXdr4dleFKqcNidZK8tuaGJB0jydjG5SZz5ze6AFSOnxc7hH77Kxq89gsagQ65SEJYSM2eTqSAIBEUEY5+04vV4iZuXTs76BdS8e4aLLx32ccATSjJIvGMJjTcwlwEpqz7eOUT22vl+2102JxUvH2bJk5vJ37KYzDUlyFUKvB4v7adrqd9zHo1RT+/lVq68e8Z3bpU6NZmr55G+osi3L0N0KBu+/CDVb5+SDLg8XsJSYshaV0J4aix1ey/QcabWx3k2xoYx/4E1AfttrofdZEVnM1D33jka9lWw7Ok7CE2Mx+PxcPmH7/nOdVdFE3E3YfxkN1npvdzClbev9tKsfe5+Tvx8J2nLCrBPWhEEIWD141q4HS50oUGYh8Y59T/vMt415OsDyt+yGLVRR9G8XA6ffp3WM7UMXG5FdImUp6fzgcfvpu9KG0dfOcHiD26m60IDbSdrcJhtqA1aUssLSFyQxZnfvMfKZ+68YWXWabHjmLRy5Z1TFG4v5/LrJzj3h72++To6J4kFD6xBF264qd6SvxaiKDLQN8R/fOWHVF2sZc+Rv0i8cpUC0elGqVWz7Ok7GKjr4OTzb/toO8bYMLasX0ZkehwKtw2noEev1dN8pIrmI5W4bE5iC1IIToggtiAVXUgQlS8coLuyBblCjkf0surZO5l370qCIoKpefeMb/wt3FGOfWLuHiwAx6RVuu/x0rD/4qz9ci67k7rd58lYVUzSwuwZCahrEZ2ThNvhou3wZf/g+xq4HS6uvH2a6NwkRtv6ichKuOGx3kq8H4DfAnhFD0kLs+m70h5w8ktfUTjnjQRSOWWiZ5jg2HAmekfQhwdjGZm8YRDadKSaeTsWsugDGzj8w9f9Gk5s42YMkSHcaJpTG7ToQoOY/8BqVDqNxKFSKuiuaOToT94gtiCVBQ+u8WWRZTIBpS4IY7wap83p52wIUsa15Xg1493DzH9wDQqVAkEmQx0eyUTDFZIXZtJ9qYXR9plHFhQZTNzSXPp7Bm6cKVfKEWQCHpcTW08L8bnhJM6/E0EuZabVei3ya/ijI8NjPLztKQYHhlm4pIQnP3Q/hUU5iFPcRGNMOMNNPUz0jjBY30VERjxLnliPrbfV1yArU6nxTI779ulxObGPjKIwhCA6pcFQkMt9weVsCIoKxuP2kLW2hKisBBwWOyqdmsm+UUxD43M2JYKUHRxs6CYqOxH5VAbeZXPeUIu66VDlX22/PK3XLpPJbkmGR7TbcIxP0nCsnpajVejCDBTfvYKY3CQcFjtKrRqZXIZKp+bIj97wy2JMZ1fHOgdZ/MQmDnznJY7+5E1WfHIHE70jXHr5CNYxEzkbFqBQyvAiMDkxiUKpwD0VKPZ09fPRJ75AdEwkuQWZAHx1cTbBs5wjr9eLaJMmHYUhlCt7L86pkjjeM4zL6sBpseO2u1DpNciVcul/BRmQp2RKNDanm6YjVdRc1wA80TNCaHLUrJJiIAWMSo2K1mNzZ/EmekckKpxSjn3SSvXOU1TvPCVJqU7xQHNvW0j+1sWYmq/qAMvUamwTdl9ZODg+gszVxRz9yRu+MScsJWbORSNAx5k6yp/eStel5pu6lzRGHTKlfE59bYfJxmBjN0kLslCqVeRsLJ2zYhBbmMpQY7dPXSNnQylHf/KGHw3F4xbpPN9AeHocQVEhvkbD2aALN/o1koUmR5O1toSwlBjfeZ2W4Ww+cpnBhi4K7ljK+q8+JAXfO0/57c9ldVC76ywTPcMkLcym7XQtBVuX0HjoEvPuWUne5kUIgsBk/yiG6FDO/O9un/zsNCb7Rrn44iHm3bNyzmMHMESFYJsKijxukZP//Ta3f+tJxjoG/bKQ9gkLQVEhN95f5NX9gUQ3Gmntw2G2odSqMUSH+jjic/GzNUYdDrONs7/d49s2rS7We7mFlc/ejS40iIPfeckvqJvoGabtxBVKH1pHbEEqh3/wCkkLs1ny4dtRG7QoNSrGxiewOOwUP7Zuyk9BPqt1O0DiwixUQVrm3bMKx6SF4juX0VURRfORKlw2BwN1nez/zots+NKDiG4PSq0KuVKO1yudU5fVgVKnQqZQ+M0PbqcLt8OF02KXnmO1EqV+Zi/O8NAo92/5MC6Xiz+8+jNkgsCaz9+H6HT5HLfrdp+b0bg42TdK5R8PUvb4BgzRoWhDgqh48RA9lS3kblxIYmmWT02m/0o7KUvzyNu8iII7liK63Kh0GrxeLyFeL0f+61W/sc4yLC3Y57b9kai2nRUN4GVG1v569FW3suDBNRiiyui+1BxwYSRTyMnbvEjScz87t99G/5V2CrctpfK1Y4TdAnWvvwbvB+C3ADKlnIGGLsoe20DP5RbaTtZgGzejCdaTVp5PwvzMOfVhp+EwWX36tEqt6qYcCx1mK163iFJwsPHLD1K75zxdF5oQ3W5M/aPMf2DNnBrd2pAgVDo1l984QXhqDNVvnkSQy/wyE+bBMb/XgiDDMTqC3BA+qzsaSJ3KtjEToVMa4IJcjjYmHsdAJ+Ufvo3emi5ajlcx3jmE2qAjfUUhUSVpPP3BL5Kdm85dK1fSvGf2BtqksmxE21RQ4vXimhiDCSlAMGbk+gXfToeTP//mVQYHhvn4s0+wdvliWvZcYPerkvumQq0kuSyHlZ+6i5O/fAfrqInh5h6ajl4hdUECrvFhBLlcyuJPBV9yrR5FaAxVb56ie5p7hlSmW/DgGvQRwQEb8dx4ydu6GGNkKFfeOU3lK1cVbMJSoil7bAO1u+cu64FURo8rSkM+xTGdvl8EmTDVDOaekWFymK03XYZzWuxYR03U7TuPqX8MdZCWzDUlhKfG3HQA73G7pSyqgK95z/99F7beLmTB0bQcrSI0KYrSR9ZTu+sMVW8c92XzVzxzJ5dfOzbrsZv6xxio7ySuOI2eS81Uv3WS7LUlnPndHhr2V5CxogBLexuCIOOebasoX17Ghx7+DHabHffUORroH2KgX6JhPftFM5FR4YH/1LVNcwoNQ03ds/7/zNXziClI4fgvdvooXoJMIL44nZL7VqENCfJRmESLg9pdM91gW09eofThdfRUtqDQqNAYtSQuyCauOA2ZTIbT6sA0MIbodN/UmOG0OFCoVYguGwqN1Ox3LaXAPmmZkgW8OvHJNTp6qq+qs2SunseVt0/5LfhvlM0E6f5T67XU7jrLms/e45OllCnkAb+fsiSP/pqOAHvyR19VK/HF6cgVcrTBQSx4cE1AmpcxNoz8rUs48fxO6XhMVur3V8zKAW8+UsmCB9bSe11QI1NI5kIum5OQxEjcDhcRaTGMdvSTVJZD+vICqt44yUjbVOA4xYMu3F6OPtzI/PtXc+L5t1n/5Qepe+/srP+rp7KFzDUlTPaOcPznO1n5zA46z0m9MW2naglPjyVjRdGM4Hsak32jKLUqNEbdnD0EyYtyOPLjq02eoktksL5rBgXANDCGSqeRqJLXZh0FqZ/E45JoC8mLcjn28zcJT48la00JHrfIxZeOEJoSjVytJHv9AlpPVJO6NI/Gg7PzszNWFdM0ixW76BI5+9s9lD2+IWBG1evxcuGFA6z74oO0HKui9cQVXyJs+bN38tRHv0R7axcxcVHs3PN7EkuzZ124LXhwLXKVgiP/9aqvouCr9H7qTk48/zb2CQsuq4Pqt09hjA5jpK2PgjuWcvn1Yz4VEpDmh9KH1qILN+K2O6l97xxtp65Iz4LoQaXXULhjGbH5KT71J5vVRt3lBl547RcY9DrM/WMc/q/XsE9akCnkaEP0LHhg7ayqIQCXXj7K2ufux2Gy0nOphZL7VuFxi+z/1ou+cTU6N4nYghSqd57yM7uJSI+j6K5lJMzPpLuiybfPropGVj5z55zXUGPUEZIYSfryQgSBORdcIHHS3TYnY90DLP/EdmreOcNwc4/vXgxJjKT4ruW0n64lfWXRjXvKvBIl0WGyzVod/mfh/QD8FsDjEklakEXVmydILS8gdWm+T5hfppAjutwYY8MYqOuccz9BUaG+Qc0+YSHoGh3O2WCMCUNpCMY2bkLu8VC4rZyiHcvwerwMNfUw1jFA4fZyqt+aSfmQK+UsfGQ99Xsv0F/bSd7mRVS9cQLvdROhxqj3azQR5HI0kdGM94zcUAKw+chlQpKi0ARpJGUAZRCaeCNer5ewlGgi0jei0msR5DJOnzzPh2/7AGaThfbWLj74kQcJresKyO3WhxvJ37wIj8OCJiFjyjVOkCrmgoDbLYDThclsRXS7cYsir7/4LqvXl7N6SSkV/7vbbyXvdrhoOV7NWNcQi5/cxKHvS01LLceryViRj2tiBH1CCvahqay9TIYyPI5D339tRmZyqLGb/d/6C+u/9BDGmFApw2F3YjdZEQQZMpWC6MwEDnznRayj/hn+0fYBat87R0hiJJ1z0yMxxoYRmRHve60NCWL+A2uIyIjDZXOgDdbjsjnpudxC/d4LeNwiQdGhuOcwEZqG02qnbu95GvZVIAgCcfPSydtUhmrqOjrMNlQ6NQqNKqD8nsctBXD2wT5Ehx1BoUATHoXSEOzHmfd6PMjUajrONkj346PrOfHf7/hJ5MkUclQ69azUiml0nK0n7/ZFhKfEEFuQgiCXseHLD2EaGGOktZ/wpGgEhRaZWk1aMBw88QpWi5XJSQt/+sNrvPXqbtxuEZlMhjF4dvc5QX7tMOqVKi4BEJERR2xBKsd/sdNv4eD1eOm+1MxY5yBrn7sfjUGHRxSxjEyy5IObcTtd9FS2+GT5rGNmgqJC2PTvj/sagmUKOW0na2g+UolyylBKqVURFBUytyW6AJpgHQmlWaQuzsXtlBZISq2ajrN1tByrJjguYmZjmdfrx6UPS42ZIck4rY8/VyAeFBUqUY7sTkbb+1n9mbt9joFKjYr+uk6aDldiHZkkZUmez01zLmiC9STMz5QWjOMmlBoVsUVpbMpOpH7fBca7h1FqlCSWZhOaGMmZ37znq6ypg7QMzBHgm/rHcNrspC0vpPV4tRRQrp1PUETwFDVPj1ypQHS5yVo3n6ZDleRsLOXoj9/wp+J4ob+2g7GuIVY+s4P6vRdY/MFN9Nd0zJl1BYkHHT8vnaZDlbQer0YVpCVjdQmDjd0kzMug/QZ9PnW7z7Pkw7dz9MdvBLw2hdvLUeo0hCZG+gWKluEJwtPjZu5v73lKH1nHqV++g0KtInPNPOKK0yWagVqJSqtCoVGx4hM7mOwbYbJ/lOicJJZ/bBtyjRJBkIIyfbiRhPmZDNR1BqxwhCZFkTA/k/3/+ZdZ/5tleALR5fYtCBQaFTK5DJfVgdfrxevx0nm+fgadof34FZ7+1ON4BYHy8lKajl4mf+ti+q60zag6p68owiOKVPz+oN/26UrvRN8oZY9v4NhPJJWQ7ovNrP3CfcQWpnLkx6/PcJscauxm/7dfZMOXH8Lj9ZC+opDMNfOwjpp8z13LsWpkMoHIrAS8omRcN784D6fZhnlwnK6KRhY+uh6ZXIbodKOPCplRObseLpsD89A4o639hKXEoAszcPK/3/G9rzboKLpzOUd//PqMoHa8Z5juiiaK71pO3qYyRJdI98UmOs7VYxmZZNnHttF+WqL9XbtokynkLP7gZpoOXvLRqXThgX024opSyd+yBFWQFofZSnhqHIJcRsl9K/G4PSg1KkSXm4meYSkob+klviQDfUTwrIIGcFWlyRAdekMn31uN9wPwWwFBoO3kFXI3lXHhTwcYbrnaMR+eGsu8e1eSujR/TlcsfYQRmULmW13bJ624Ha5ZlQqmkbGqmJG2AU796l28Xi+aYD0FWxYRk59M7e5zmPpH2fzvj2OMCaPx0CVGWnqRKeTEFaeTtWYeLceqrmbnZ5GozF4/X5okHS6QCZL1tVzuU3KZCw6zjdG2PgwxYYx1DRGdlUDte2d9Jj0gDca5m8pYVFbCa2//mqNHz/D6y7v41Me+zk//+5vY2oem3MzMqPQa0pYXkLlqHh5R5PLbFUz2j7L4iU10TnH8nBa7lJ1Ykkfisnw+/+n/4PNf+ziiKPLRjz9KwysnZ6UMjLb3YxoYIzIznqGmnqmBXMCYlo1jfBTnxJjUdBsSQeupmllpAaLTTfXbp1hw/2pJP/h4tU9nNSgyhNRl+cy/fw2nfvXujACjp7KZvM2LqH7r1KwZX6VOTVBkCO9+8TeUPrqehHnp4PUy2NiFLjQImUJO3e7zuOwOwlJi2Pi1h2k6VElwZiyzsYkdFjselxu7yYpCpSQyIx6HyUbm6nlM9A5z8eXDkkJJXARpywsZbunFbrKTVp7np67icbuxDfTgGLmmqdfpwGJtQ67RYkjNQqaUBkWvKIJMhm3CQsKCLLovNc8YnBUqxQ2zJiDda6FJUXRVNFK98+q5C02OZv4Dq0EllbNb9lzEYbETHBtOwvwMLM0DbF++nE1b1vDUE8+xdMVCVHMZZAgCSmMIrslxvE4rCfPSA2aAMteUULPrNDKFDNE58zpaRibpOFNHank+k30j1O25wGTvCEqdmuSyHPI2L+LCnw+w4ME1tJ+qofHARd8zp9SoSF9RxPJP7ODEL3ZKkl0DY+RsKGWwfqaO+DSic5IQ5DI0QVqO/ewt30Sr1KhIW17Iik/uICgyWKpUCDLwSsfttpqJK0ql+q1TkodBgECut6qVhPkZdJ6bnT6VvrwQryCQsiSPoKhQLr923Je9lTSz0yj/6FZG2vqIzU/BPDxBTF4ygfwOFRoVunADix6/jbo95zn1q12+ax4UGcy8+1dRsG0p1jEzbruTut3nqN55UpKAFQRfZuxG0rxnf7uH2/7tMRIXZiEgcPm1Y34SpVHZiSx4aC0Oi42Y/BQaDl5CoVFK1JPr9u0wWWk9cQWNUYdcqfSXIJwFDrMNY6xUjek4W8/yT2zn/B/3Uf7RrTitjjnNvkC6LrmbF7H+yw9Sv/s8PZdb8LhFIjLiyFxTgsNk5eD3XmH501s5/6cDvoWux+NFG6KfQQXsv9KOdkrjWqZQULf7HAe+/aLvntCFGSjcsQyZTNLPV2rVXHr1KGnlBYQlR9Nf04FaryGxNJu6Pecpe3wjvVWttJ2SKse6MANp5QUkLsym6o0Ts/YUTMM6MklqeT4xecl4PR5Et4jGoKPnsuR9Md4lKXH5XwcbK+4qRwQme0ZRKBW0na5j+ce3U7f7nG/xK8gEMlfP4+D3Xp7194ebe3DbXZKQQfcQHreIQqWkZtfZWa3e3XYn1W+dJCQxkro950lZnEvasgLO/WEfDpOVkvvXYIgK5tSv3vVT4AlLjWHxB27DlZfMud/t9c0/hTvKb0hXBbCPW/C43aSvLKJhv2SIpFBLBnpp5fk0H6mcEXwbY8NY9MQmOs7Usv8/XsBpdUgV48V5rHvufgbqOhms6yQ0OYr8LYvprW6lfs95YgtTyVxTwmBDFwnzM+mtbiVlcR4Zq4qpusZ9GiD39kWkLMrh8usnGG7u8R1DaHI0xXctp+1UDf01HeRtLsMYG8ZY5wAKtRLTwBjZ6+Zz8aXDqA06khZmow3W47Ta6aqQTIaSFmbTfbFJ0gF/34jn/x6khp1MDn7npRnd4SNtfRz98eus//KD5G9ZTM27M0vMCrWShY+sv2rSM4W6PedY8NBaTvx8Z8Cu8+wNCxhp7cdptZO5toTGAxfxuEXskzYEmZwlT27i0A9exTQ0TsvxKpLLsinaXo7H42GwvouTv3zHZ9Gr1Kl9zXzXIm/LYoKiQmk7VUNfdRuRWYnEF6ciOsWA+tPXwxATxnjXEOd+v4/b/u1Rzv9p/4ySsn3SyqWXj+CyOkhYkMnmjatYv3IJLq8HtV5L/Op4UpbkTZWPvHjsZmzjJg5PSWGt+dx9nPvDPr8Mqeh003K0ip7KFr7/w6+gUKt49c1folWrqZ4rQwi0n6kjYX4mQ02Si56gkGPt78HrdqGKSEBQqbGb7MQVpBGWFEPDgYs+yTW/c3dbKRV/OUhPZQvG2DCy1y8gJDEK+4RZyvrLBEofXc+53+31+57oEmk7XcPCR9dxLkBzn0wuo+zRDTTsq8Dr9XLp5cPE5CZx9KdvsvgDG6Xy4TXVlu6LzVzZeYpFT9yGPEyP/LrsptfrxTpm4sKfDviVHSOzEyl7dD3Hf/6W3yJwsm+UropGcjeVoQuTGrdyN5f5gnC3zeIffF/73+w2rAM9kt61XI5MocTrchGaHIXGqOfya8dmfMdlc6I26HxB02wwxoQy3NzrVyIFMPWP4hU9XHr5CL2XW33bey41U7fnHPPvX4PdZMHTMca/feuzlK9ehFKQYRocQ3SJqPUavEhVKaVWhVKrRhefjMlmxW0aI3N1Ea0nrvgyPzK5jNTyAsLTYim+a4Uk7aVU0H66ltYTV/yC15bj1URkxHHo+69ePeARqWHWEB3K8k9sp/HAxRmW2y67UzJ7GTcx796VXPjTAdpO1ZC1bj5JZTl0npuZFdUYdcx/YDVdFU0zxiGX3UnD/gpsE2aK71wuqbQkpmDplM6X1+1GLvMQk59Mf02HlO2+zhm0+WgVyz++nZHW/oAZqZiCFILjw5nsHiZtWQFHfvS637nwerz0VLYw2jHAms/dS+f5BqKmAqfYolT6qtrQGHVkrikhrjAVh8UuZT7HTLgdTr/FqnloghM/28miD22mur2NteuXUXzncpwWO16PF02wju6LTSDcmPurDZGaAOUK+YxjBhhs6OLwD15lzefvRa6QY4gOIa08H22wnu6LzTQdrvRbQHacrWfZ03fQcaaWtOWFs/7uNIwxYb7KqMvuRKaQM941xKEfvMq6L94/FZDM9Cy4FjK5gFf0+O4pmUzGeM8wNe+e8VGjLr50mNxNZZz5X6mnJyo7AdEtsvDR9Zx8/h2/QLjtVC1pywo5/6cDMyqU1lETZ3+zm4WPbUBj0FL73lkWPbGJ6jdPUPGXg77xZf2XH6JlymAsYX4mCx5ciypIg2PSSsfZ+puiCwiCQERGPAN1HX4mMNOGMis+uYOWY1UzgnhjTCheuwWlLoj2kzXk3raQQ99/hY7TNWSsLCZ/y2IUaiVejxfT4PgNEwAdZ+uIn5fOePcQaoMWmUIu3V9zoKeymZyNpVS/dZLmI5fpq25j6Ue3cvZ3e9CHGTj0/Vdn/G5IfAR9Ne0zNN1toyaCIm9mPg7FbrISHB9BRHos8+9fhcvmQCaXow0JYve//cHv8wq1kkVPbOLsb3f7zQFuh4uWo5fpq2ql/Ok7qH7rpCR7+NYp8rYsZv2XH6LzbD2nfvUutjGz5G3x3P1Uv3WC1PJCIjLiGW7uIWlhNlnr50tBs9kuVQNWF6PUqGg7WUPrySsc/9mbrPzUXYx1DHDp5SPkb13M+q88jMNkZai5l5i8JBZ/aDO6UAMdp2sZqO9EY9RT+tA6RLeINtRA5/kGNEbt+06Y/xfhcYvU7j7nC5IVGhUqnRqn1YHH5UapU1O/r4K0pfmEJkXRdLiSkda+KQWHTLLWllDz7lkGG7pQqJWSpKHVwUhLH40HLrLuiw/QeOgS3RVNkixQcjSZq4oRXW7O/WE/MoWMtZ+/j56qNso/vJmWY9Xs+srviMlPZvVn7ma0Y4CIjDgu/PngrP8hfXkhw809vsHDK3qYd89KDNGh7Pn6H3DZnSx4aC144dD3X8E2bmHJh28nNClqzsE/bVkB536/F41Rh3loYk4+Z+3ucyTMz2Tff7zgm0yD4yMoe2wDhtgwHHYHrtFBlBojZ3+/C9ElkrIkj57LLbPSE+wTFlr2XyIsOYrmI5cpunP5Da+n02zzNZxGpMdhMlkwhEYgOuH8C4cY6xxEpZeoGLowAyX3rqIvtZ2GfRd8VJiIjHgEuZyeyhaichIp2rGMy68fZ+iP+32/Y4wNo/ThdWSumTejOtKwr4Lb//MJyaXz4CUGG7oQZDJiC1PIXFNCx5k6uiokubPkslyaDl0iearMGojq5BE9nPnNbjZ+/VEMRn8jAofJKjUxXUcniitIofK1Y7NWYOp2n2PFJ3fQuP8i2esX4PV6cdodOIYHEeQKvGLgzJVzbARddDzI5SATQJAyn6b+MRwB+Hxer5ehhi5iClLoq55dSShr7fyAC9z0FUV0VTQxUNuJLsyA2+70ZZJlcjl1e8+x+MlNtP1mN6s/fQ+WkQkuvHECuUJByb0rOffH/QzUdfgCh6CoEBY8uIbQ5ExE0xhu+wRrn7uP5kOXcZhtpK8qZriph33f/LMvk6PSqclev4CVn7qTk8+/g9MqbXda7L5xQyaXET8vg/iSDJRaFYIgBRjNRwPlfyV0nmsgc02JTwb1/J/2s+gDG4nJTaL5aBUTvcOodGpSluSTtDALgJq3Zy9Vd55rIH/LYjSCpFUuz8jF2t8DHg9eu4mFD6+l4qUj9F1pJ74kg+6LTSi1akSXG/uEhfN/2Ef5R7fQfbGZ9rN1OCatBEWFkL6iiOC4ME7+8l1KH1pL9VsnZ6Wq2MbMtJ2sIWNVMRPdw6D2UPrgWkbKBwgKN1K35wI175z2Bf+G6FAK7lhCRGrsDAfbmjdPsvLZO2k/XUfD3vM4rQ4EQZBoKwsyUagVJC3MmVM7PGNlMaLTRd175wIes0wuo/ThtXRdaPTTtZ6WhFvxzA5O/Hynj5/vsjmQqxQ4LHbkaiWaYP2sqhCCIJCwIMun4x0UFeL7rNvuRHS6yVg1b0652bDUGARBoPVUDc2HKuEq6wClRoUuzIAgk2Ebt6APM6DSqdGFGzFEhuBxu2irbmP1Z++h5ehlei63gtdLxpoS7CZrQHrgNC6/dowVn9hO2WMbOPOb92bqOnu9kpKVR6LZXL9oHO8JpfiuFXMGsrmby+ivaafyVf+Fu8ct0n66FvPgOAsf28CZ3/hL+WauLkZl0OC02HBa7D5FFsvwJJensrPpywsJSYxizg7rKTinVIQA0pYV4vFIJmjqIC2p5fkklGRIHG+vl57KZlpP1CA6XQgywUfBsoxM0nqsiqIdy2g8eDFg0J+2vJBjAQyZOi80svwT22cs1K+FNjQIhVpJ0sIc5EopCXP61+9hGZnE4xZZ/+UHZ7iGJpXl0HW+YdY5wDpmounQJZ/Lt9frpead02hD9Iy09/sqJ26Hi6q3ThKVlcDJX77D0o9sQRDAPDSOUqOm5p0zdJyt8y2EVXoN2evms/TDWzj1P7uo3XWW7PULqHzlKHW7zxNfnM6xn7yJQq0kPCWGyd4RzlwjBqFQK+m70kZ0XhJF25cRlhKN6BLRhN68W/GtwPsB+C1C98UmwtNiyd6wAF2IAUEu+BrVzEMTktV3qAGPx8OCB9ciCPiyLwgCSq2SpR/Zgi7UgMNqQ63TYJuw0FvVBl6pwWXxk5uQKeRM9o9St+e8L/AVnR4sw5Os/OR2JvtGSF6cS2xBCg37Kzjyo9dJLc8nc00JA3WdDDX2zDj2kMRIstcvwCN6iM5JQnS5fYPydPCdWp6PRxS5dI0sYv2e88x/YA3Hf/5WwEaI7PULMA2MYR01kbVu/g21jD1ukZHWPsJSo32azBM9wxz83sus/9KDaIK1yEKi8IjSOTT1jxKdl8zhH7w65367LzaRs2EB6mA9IQkRfu9JpWDFVOOZ9PAHRUtcfEEmkLdlEXK5HC9KLrywl7TlhRiiQ7FNWjBEhaBQKpnsHyW+KI208gLJ7UwuQ6lRUbvrLEqdmnl3r/Bzc5vGZN8oh//rNVY9eycjrX1+ZjBypQKZQoYxJpR5966UuNJTtB+PKBJXlDa1oGknfl465/64nxUf38aB77wU8BwkLsgiY1UxLoud4ZZedGFGFCoFcrWS5qNVM4JvQSYjOi+Zqjdnb7IFSRs3tTyfropGUqb0mgVdBMiNaAxaRKsZcXIYj+tqBUcdHgUCiA4HHrcLXXwSI+0DKHVqjLFhM/S4ARoPXWLpR7Yy0T0ckPaTsiQPmUIecDGYsiSPsc5B1nzuXqyjJlR6STLS7XChDtJiHTUhILDik3dOceeDKLxjKfpw49XfumYONg+Oc/Qnb7DqU3cRnBCJZ8KM0+wga918EAS6LjT4LQTiitPIXF0yRUVxs/a5+xjvHqK/rhO5XI51zExwXDhlj2+kv7aD2l1ncFrspJbnM949DF6mgug8wtNiQRAYax+g7ZQkqdZzsZnYghQ6ztZj6htFrlAQFB3KwkfX+3iTCo1qinvedMMybNvJGop2LAM5eFCgDI/HOjKJV/SikMkpfXgdXtGD1yvRZGzjZpQaFS6Hk+bDlzn43ZfIv2Mpqz9zDzKZILnseb0oVErKn9qKOkjrqy7NhtYTV4jKSvC5P8pVctZ/6SFO/8+ugHbgp//3PRY/sYn4eel+jWipywpoO1ZN/d4LaEP0FG8qIzovGfuEBYVGhcvuouCOJYy09yM6XNJC4ppnITIrgYSSDJxWO4MNgak9eZsXMdTUQ8P+Cr/tokuk9Xg1luEJSh9Z5+PbGqbGl5D4CMbaByh/aitH/us1n6Rc4oIsDFEhiC4RY2wo3RebfNWV9OWFvsVCWEo0lpFJ1Hot5U9t9bkrT/QO03KsGo8okrepjNiCVCyjkyTMyyC5NJuW49VYRibJXjefoOgQ5AoF9kmrNO5HGFn9mXtQ6tR48SDXqElckMXpX79H+ooi1m9ZIvXaeDyIDjelD6+j+ejlgB4SkvGQDY8oBjRVEV1u1EHaWRuHTf1jCDKBhAWZUlVpaYHUlCgIjHcO0ny8mrTyAvZ8448Bvw8w3NKLddQk6ZFPIf+OJciUSswjFtQGLVlrS3A7XVcbVQVILssheXEuKr3Wp14zF4yxYVhHJwlLjSGtPB/ruIWksmxyNi6k+XAlh3/4mk8lK2lhNuueux+3Q+qlWfnJHdhNVhr2V9Bxrp7czWWc+tW7M35jur8jEPXTabEz3NQza5VdrlSw9MNbUKiVKFRy7CYbUTmJhKfFog83MtjQjdNqn8HPTlqYzen/2TXnf++60MDqz97rV8FvPHCRojuX+yVM+qrbyN+yhMpXj0n9FGmxkiLLXw4xWO+fNJKM9k6Rs7GU3E0LqX3vLAseWsvyT2zHZXNgm7Cy6d8fQ5DJGOscpHaX1MicMD+DjJXFyBRy3A4XmmA91lET1pEJei+3UHznMvgX2mC8H4DfCni9xM/LIH1FIV0VTWSsKkIml3H59eN0X2z2ZXNVeg25ty3EEBPGmf/dhdvhRqXXsOgDG8neUIpleBKPx4Pb7kKpVqFQK8laP5+Bhi7q95ynfs/syhhOq4Pzf9znC7CNceGU3LOSzvP1tB6rJmVxHsV3LmekrZ/WE1ewjprQhuhJXZpPwvwMei63UP3WKZ/+cvy8dCIzE3DZnWhDgshcPY/jP9/p95tjnYPUvHOaVc/eRfvpWroqmnA7XYQmRZG5ah4uu5MLf5IyvgqVEvPQ7I0S03A7XSSVZvsFYR63SOWrR8lYWczJX70DXih7bAOCXOqWnk0D9NrvKzUqBms7EbxSRsgYE0ba8kLcdiduh4ugqBDGuwapefcs6csLadh3gaUf2UL/lXYSluTSfbmFoh3LqHz1GObhcZZ/bBsNe6UBczorptSoyFgzj+icJBxKGU6LnZTFebSeuDLrJOP1eKh+6xQZq4o59/t9vu1JZdlS41ZdBxEZ8Vx59wwjLX3YRk14vV6CokIovms5wXFhUlOeTMA2bg6YoSu+ewUqvYYzv9mNbdyMTC5DGxZEeFo8RduWBpSDVOnV2MbNNywDj3cNkVyWg0ylYKy9n4svHcE8OA5I2bvYolRK7lmBe7QH5EpU4bFM9o/RXVuFxqAlMjMerBN0X2omaUEWORtK/RqDpmEZnqTihYOs/NSddF1sou3EFZw2h2SgsqKIiPQ4Dv2X/0IsKCqEzLUlKDVKrOMmLr54yBfI6MONFN21nJHWPmrePUNoUhQLH11P9Vsn6a/p8AWphphQinYsIzQx0l/n3yuV7Ofds5JjP71q0RyZlUDxXcvpr+lguKWXvNsXEZIYyYU/7ffTY55WyjEPTWCIDiEqO5GKPx9gsKF7yrJawO1wIzrdpCzJI3P1PNpO1dB85DJeIDgmjOWf2E77qRqcVrvPLVIbGsRoRz+nfrULuVLOsqe3YRocJyI9lv66ThzXBJeCTEAbakAArGNm3zjlMNmkhZ5bpPHQJZoPV/rOm1wpJ2VpPvm3L6Lq9ZN0nr9KFQiKDKZw+zKJmhRuoO3kFG99anGuUCtJW15I5up5c95TIE3A6in9frlKQWJpFoP1XbPLEXqh6q2TlD263heAy5VyYgtS2P+tv2CICWXxk5tpPV5N66/fQ3S6cNmdBMeHU/rQOlZ8fDsTfSPI5DIUKiXdlc0ERQYTW5jGaHsfxpjAijhSP00aB74904lxGgN1nWRvWOBrFktfWUTbqRrm378akAL1Tf/+uJSJlQt0nqtnqKkHhUZJREYc6SsKSSrNwu10odSoqN55Cl2YgcVPbkJ0S4ZJ3Zea6L7UjNfjJWttCauevROZXE7FS4e5+OJh3/2sNugouGMJeZvLMA9P0nWhkcaDl1ColCz50GZ6K1tpO12DfcKCLsxIxsoiIrMSWP25exAQaD9dS/ORSh91MSo7geK7VtBX3RqwD8Lr8cxa9ew4U+fnchkIpoExSu5bRefZes79Ya8voxqZlcDCR9Yx3jN8Q5OhlmNVpK8sovN8A7m3LcRptfPeV3+H1yM1FieX5ZBzWynpK4qo2XWGskc34HI4Of3rXdjGLSz/+LYb9mKlLs1ntHOArHULGGrqJjo3kaLtyzh8jWoKSNTItpM19Nd2sOzpbZz+n/dwmG0Ex0cw756VtJ+RklSBxnFJdceBPiIYr+jBOm7ySwxUvXmCBQ+uZdnHttF4oILhlj7kCjlx89LJXD2P7kvNpJXn03O5lStvn/Jxxqd7L+KKUslYUeSXdFFqbqzGJrrEGepWk32jkpngNfB6vL4xJn1FEZWvHiHv9sUM1ncSHB9B+opCguMjJAGJxm5aT1yh8eAl1j13P81Hq3A7XJx4/m3UBi0LHlyLw2TDNm6mbkoxbN49K1Hp1Jz7437fIkKQyUgoyWDevStwO1x43ldB+b8HQSYje/18Kl87StGO5TjNdi6/fmyGvbXTYufy68cp3F7Ohq88TF9NOx1n6tFHBGMfN3P5tWN+VApjbBjz7l1JdE5iQKOda2GMCfVTo5jsHeH4L3ay6tm70EcE03byCk2HKonJlyyBNcF6HGYb1lET3RebfWW3aQTHRyDIBdY9d7+UyZi0suxj2xhp7aN+73mf0kJ/bQcjrX0kL85l8ZObUOk1DDX1ULNL4hbqwgzIlQpskxbiilJRqBU4LQ4GG7oCDjL6cCNqg87X0DKNgfpOiu9aDl4poykJ7J+i/Ok75izhwlV1hsw18yS96Ccl9YFTv3znarZLgJi8FFZ/5m5kCjkLH9tAX007rSdryFhbQnRmIkd++CpOq4Pyj26dwbOGKROB987hsjpIWphNSGIkoUnRnP713BmE4ZZe5j+45uq1jAsn97Yy6TrEhmMdnqRgyxI8bhFBJtBxpo7Ggxc59at3Wfaxbb4FhBDAEjlhfiZqvYZzf9iHUqemYNtS4gpTpSBZJuCyO5j/wBr2ffMF3I6rWWrRJd6UfbI+MgRNiB6X1cGxn73lNyF4vV56L7cy2TvC6s/cjXXUxNFvveiXYZQr5RTcsZTsdaWY+kcJSYgkeXEuHWdmars6rXY8Hg+JZdkklGbhMtsQZDKphOt0ow8zYhuTGnXLHt+IUqui+2IzF2uPYIwJZ/Vn76XrQiP1e89jGZnk9K93sfTDW4gpTKVo29IZ6isgZeFO/fJdln50C1HZiX5Z0Mm+UVR6yQZdpdcQmhwNwPk/HWDR4xtoPlZFREY8x376xowq9lBjN0d++Bprv3A/LocT+/AkebcvYsEDa7BONRs7rXbJ2NMl0lvVStqyAszDE+CVgt3e6jai81IQZALNU1KjqUvzfXSEwu3L6K5sIa08n1O/ehd1kCT1KVcqyFo3n8QFmdL+PNKCrreqlYb9FzHGheO02qnfKzUPXwvRJdJytArrqInkRbl+GrzmoQlO/+8uln1sGxM9QzO0rd0OF40HLpK+ouiGvGtjTBgyuZzSR9YRmhiFIBOoeGFu91jryKTUID1F/wtPj5OoW3IZy57ehtfrJX1FETkbS7GNm5ErFagNWtpP10rUlalrpDFKahDRuUlYhscxRIai1Kh8VIFrEZ4Wy1BTzw2VWrouNBJXJD13oYlRyBUKJnpH6L7UTNuJK2Stm09YcjTnfr/Xb1/dF5sJSYxk4aMbuPTyETLXzmfj1x9BoVbScbaesKQoTjz/Nm6HC31EMEs+upnBhi6cVgdnf7tnRtDoMFmpeOEg8x9YjVqvpeadMyjUUmWi8pWjfgIC01KscfPSWPDAWi6+eJieyma//Q02dDPU1MvSj9yOaXB8BkXMEBVK82hVwHPSca6eVZ++m6GmnoAyipFZCcQXp0u/e8n/d4cau7n44iFSywvmPO8gUX7CU2OJyU/m/B/2+Sm9eNwibadqMI9MsPjJTSjUSuwmq5+87uTAGIueuI2jP3o9YPZ53j0rUBu0RGbEY+ofxT5uoflwFS6rfVYTJNuYmZajl0ktz6d+7wUmeoY58Yu3WPXs3YCALszgp2akMepIX15IVHYiCo1KktsMCaL9TJ20KPd4JNnFPx+gYPtSSu5bLQWcbjcD9V2ceP5tX3Xo+rl+uvfCMiypmfTXdfgaud0O1w1dvuXKmzMdUmrVeD1eqcpvthGeJrnGlty/iqCIYBoPVXL5tePI5DLiitMof2orrcerGe8ZZvWzd2GbMLP0I1uQyWW+vprg+AhG2vtIKstGoVFKPVN+/81DV0Ujk/2jrHxmB573nTD/D0KA+n0XKNi6lMYDF0lckDkj+FYbdKiDpBu59r2zxBakMFDXyZIPbcZlk4KX6/lXk32jnPjF26z57D3k3raQml1nkSlk2MbMyFUK1EFanBY7Co3UGBZbmEZ0bjJOi42ey614RJHBxm6SF+XisjlJXZqPQqNCdLmY6BlBY9QTUhRJ06GLBEUGYxmexOv1SpnLghRG2vr9lBIQICY/hfKn7vBrynDZnTQfucxIWz85G0u5+NIh0pcXUfrwOqlxTa8hKNzIQEMX2mA9oYlRFO0op6uikbo9530Tny7ciEKjonrnSdJXFlHxwjWcdS++iSl7/QKsU9JHABkri/wc165HfEkGPVWt1O0+T86G+Qw1SYO3H7zQX9POkR+9zopPbMc2ZiYoMoT5D63Bi5RFcVod6COMKDTKOSUlW45Vkba8kKSF2ZJts21u22aQzJyMceGkLc0nbl46gw1dfhUJkLJN8+5dhS7MwPKPb+f4L3ZSv+cCBduXkLlmHiqdxhd8TCNjVTHnfrcXdZCWZR/fRuuxKg585yXf4keuVJC+sojVn73bR+VRB2lx2Z14RM+sklHJi3PJmJLnUgdppez9LMkF89AEPZWtDDX3zKC6iC6Ry68fR65SMtTYTd+VNpY+tYWUxbm0nqxhqKkbpUZF6pI8YovSaT5SKfE+azsIjY+kft8Fhpt70UUYJYUNr5dFH9iIy+7E1D9GbH4KCo2SpsOVHPjWXyiZUsa4svMUeOHK26coe2wjPZUtAf8nSAuJKztPUbBtKePdQyg1KuwmK6LTjUf0sPiDm9EYdQzWd+HFS86GUkAgb1OZlB2f5bzYJ620n6lDppARkhCBUqtmtGMATbAelVZN8+FK8m5fjHV0EofZxsHvvuQLWmUKOSmLc4nOSUIXFsRAfRehydFEZsZT/fYpQhIiiM5LZqStj4H6TsxDE5iHJih5YDUrn7mTropGDn73ZV9z2nQmcMUzO1ColLjtTlpPzG7q01fdRs7GUrQhel82VDpZcOmlI5Q+tHbW7zottjk1l4Gp+1lN57kGLvzpAIueuM3Hm78WKp0apVaNw2zD7XDhsjkIigyRKAXBetxON6s/cw+91a1EZydy5Z3T9FW1+TLC2rAgSu5eycavP4rHKVnE99W0U/3WSdwOFyNtfXScqSN/62LSyvNnZHnlKsWsShfXwmVzkFqeP+Us6MEjinScq0MfakSlU5O0MJuD3305oOrReNcQwy29LP7gZoabeui93EpwXDhJpVnUvncOt8OFUqem/KmtVL1x3CcrOVfG9srbp1nxyR0AJC/KpbuiyS/4noZMLiNrzXwm+0ZmBN/T8HqkBueyxzf6BeChSVHI1Urm37ea0fZ+aY5ovRpoi043la8eZcGDaxjvHaLxwCVsExbCU2NIWphDaGIktgnzjOB7GpbhSfRhs8uFTiM4PoLui00Ex0s0L7vJilwuxzJqwj5pwWGySVKIPcMklmb7UVoEQSAqK5Ha986y6tN30366lu7KFjwuN2GpMWSsKsbUP8Zk7yhupzTmXHn7NGs/fx9Hr6mMBULn+QZWPXuXr7ImukTq9p4n7/ZFpK8sonrKLVofbmTpR7ZQt+ccF1867Ks4KTUqstbNZ+lHbvdTAIrOTqT1RDUpS/KpfOWob3GTujSfoz+eyR+fxnj3EJahMcoe28BAXSctx6roqWohtTyfhn0Vs34vYUEWPZf99ceD48JnUAXTlhXQeaFBemZsDhQqBaFJSdjGzH7VddElNSp3VTRR/tGtuBxOKl8/zkCtVEkJigym5L7VdF9sImlhDjK5nIyVxQFpO9OY6BlmoKFbUgv7F+L9APwWwOvxog3Wo9SqCI4Lp/NCo++9qOxEcjaWSpOB3YlcrcRptuFyuMi9rQxBJlC7+9yM4Pvqvj2Mdg4SX5yOQqvCK3oITYrC6/Ey0TuCSqeeUiPxMtLah8vhJG1pASlL83HZnIhOl59LmtqgJW1ZIbEFKZx4/m1UOjULH9tA+spivG6R9jN1uJ1uhpt7Z6yU8UoSVJbhCRY9vpED333JL7gISYhAFxrEog/chm3czLGfvEHm2hJ0IQaOXeOYB9LAnr9lMQsfWc/5P+5HqVGx6PEN1Lx7hsHGbsoe20jupoU07JeUXVQ6NV7RQ+qyAjyih6q3TjLRM4xcqfApJgSacDRGHYXbyxnvGmTho+swRIfOWS42D44z2NhNVHYCY11DGCNDUKmVdE45U8YWpNJV0YRKryE6Jwm5SoF5cNxv8vJ6vAzUdRKZFY9CrSA0OQpDdCihiVF4PR6GW3p9MlcglRZVQRqK71yGJljPQG2npBZwHQYbujnxvLQgc1ocbPjyQ5JLpdNFUEQIMoWcrPULfJlHpVaNIAhYx0ws/fDt1Lx9mv5a/3Kw6HLTeOAiLruD9V96EJfdOcWT1qBQKSh9eK1P33YaJfevQiaXc+K/38HtcLLqU3f5aCezofXEFbLXz6frmmfjWtTvu8Cyp7YSPz8DrUHP5MAYqUvyKL5rGR6X5CQ42TdKfHE6iF5icpNx2aRKQ3JZjq/SEpYSzZnf7PGj1WhD9BRuLyckIZKLLx1m9afv8S0sprPYN5Jym+gdITgugqUf2YLTYkcfbsQ8NE5QpJHqN0/4cZprOENERjyLPrBxziAIoP10Das/cw8TvSNYhicwxobRfbGZ8+f3U3DHUrxeDy3Hq2dUBDxukdYTV7BPWim4YwmlD68lOCGS4eYe1n3hfszDE5iHxinasYyB+k7fwkwmE2g+dYX269zopjOBdpOVgq1L6Ktpv2HvWffFJmLyU2g76d/AaBmeQK5SBMwYg9SknrmmhJHWvoBVvbiiNIKiQjANjPkqDtZRE8bYMN/nY/JTyFpbglypwGG2oQsz4LI5MMaGU7BtKfZJK4boUEntpKKJyKwETv/6Pd/3ZQo5GauKSS7LwTZhwTFhQRsSRNfFJqxjZsqf2krz0cukryii40wdQ409lD22QfJWuKbPwDI8QfpNKJmEpcSgCQnCbXPidYloQ4LIWV8qBc96De2na2eVHC2+azkymcC+/3jB73yqDVoWPLSWqJxEQhMisY2bSV9eRHB8+AyN9uvhtNixjZvRhxtJXpTDieffDvi53E1liE7XDZ2craMmPG7Rp8etNuhY8NBaTj7/NuPdQ4SnxpJ3+yKGW3po2FdB1tr5JJVlYx4cxzQ4RlRmIhHpccjkcsyD43hED3KlAue00k0AmqFt3Ozz2Jj1ORMkOVCn2UbNu2c487+7pSSTTCC2MJWCrUsY7Ryk9OG1kviAx8P6Lz5A+9laGvdfJCgyBPukhbDkaBAEMlYVk7F6Hm67k5HWPi69dATTwBhx89IouXcVY51DrP3C/WiDdax85k66LzbRdqomYAbZ7XChNurIXr+AxoOXpMVfdRsFW5cQnZ3IYG4yA3UdLHxsAxf+fGBGf4vL7qTm3TPkbFxIzsZS6nafo3B7OUNNPTQdqqT7YjPLPraN4z+TmhWto6YZjZ2G6FCC4yPwiB5EhwttmBGnxY4uzEDpI+tRB2nweqSK1FjHAB3nGvz2oQ3Rk7V2Psd/5j9HZG9YQMvRKoLjwklfUURoSjTakCDsJgsRabFEpMcREh+BQqPCNDA2o3cDpDHp/B/3sfYL99F24spU74FXUjh6/m1WfHIH5sExyp/aikwuwz5pRW3QoTHqcFrtM1y0W49XE5Eed1OLtluF9wPwWwBBkDhNQ409yJUK3yCZujSPjDUlyGQy+mvbsY6aCIoMIX5eOiAw0TOELjSI3imHO324EUN0KDK5DPPQBJN9wyz50BbGOgd9zZDTiM5LpmjHMs7+djeiy03pI+vJ3rAAlU6DdXRSkr6LCeXEL972a7pymGzU7T7HWOcgiz6wkeM/38nRH73Oqk/fjUqvQWPUkVCSyd5v/nnW/2vqH2Osa0gqyV+jOZy2vBBtsJ6Rtn6q3jhBcFw4EelxUiPVdZO5R/RQPSWNt+ChtYSnxlCz66yvPOgwWfG4RZZ/bBsnnt9JzqYyLCOT5GwsZf9/vODj/YkuN+1naiU1jgOXaDtdg8vqQK5UkLQwi9zNiyTZphcPownWs+jxjTfUS207VYNMJkMTrPNlJPVhRsatQyi1aiIy4n1cOrddqizMu3clte+d9cnciU4Xar0Wj1tkyQc303ayhu5LzcjkArEFqeRvWcylV44y1NhN8uJcmg9fZrxnmNKH11ITwA1xGtaRSTrPN2AaHCe+OJ3JvhHGuoaISI9FqVFNyTVC3XtnkCvluOxOdKEGVEHaGcG3338+WUPubWU0Ha70BXuG2FBKH1rHxq8+zInnd2IZMUnKEUol56e4/eog7U1l+K/lKc/2vxRqFf1X2jn7mz14PZIj3IpPbKf5aNWULJkHtUGLPtxIdG4ycUWp1O+9gMvuxGVzsOrZuzn8g1dmXF/buIVzv9/Hkg9tJn1lMd2XmkhbVnANRcIbMLt6PWwTZk78Yqfv3ovMjMcQHRqwqXGso/+GJlUgSSya+sc4/rO3gKsc60Uf2CipE7jEgHScafRWtZJ3+yJCk6Nx252Y+kapeuOEr8IhyGQ+Obazf9iHQqOaEXxfi77qNsnmPMB7iinFDtHpxjZuxmVz+kwurofb7iRv00IQBGzjFjrPN/iqOaLTzbnf752igrXTfqYOh8lKUFQoacsL0IcbOfU/u1j/xQdY8cwOzvzvbtpP11Jy7yp6KlvIWjefyMx4Lr54yK+vJCw1hvn3raLx4CX6a9oBKfu56MnbGG7q9Qu+lz19B0ON3Rz+4Wu+8Xpaui5jVTGnf72LJR+6HQQBjVFHypI8Bhq7WPqRLfRWt9J+qhb7pBWNQYcxNhxdqGFWTwCZXEZ8cTqmvlEqXznqt+gITY5m4SPraJulGhCZlYA+Ijhgds9lleTjJvtGqfjTAd/8UPrw2pt6Jt12J3KVwhfoBjzueemSo/H47BS/adgnLYQmRZG+opC4ojQqXz3qoxGOtPVx4hc7WfzBTaz+3H30VjZz6PuvSN4IchnlT21luLWPpoOXrnK6BUhZnMfKT93F+T/u82XPtaFBUvOmyUbNrrMs/uBmjvzwtZn/QYBFT2zCK3o4+pM3/N73erySHrlBR97mRbisdqx9o3Scq2eouZeMlUVs+OojNB+9jCEqhLZTNT7lHZlcRty8dHI3LkQTrMc0MEZIvOT27LI5OPqTN3DbpWcjeVEuq569i/N/3O8LoKfneplCjmPSikwhp/yjW3yeEDKlAplSTtlj6xnrHMRpsc+pNNZ06CIbvvoIsYUpjHUMUPnKMUmJTa+hv7ad3M2L6L3cgtvlJjg+ApVejTbUQPqyAlw2aSGhjwgmrjiN6rdO0X6qBkNMKIs+cBv9tR10nm9EdLgIS41h1bN30XmhgeYjl0leJFVBK1485BvrBJmMwu1L0Rj1JMzPQBdqoOHgJS6/cRxVkJYVH9vGZP8YFX855LseQZHB5N5WRmxhqrRwvGY4tU9aMQ9NkLW2hOK7ltN9sZmG/RckKtyxKorvXk7DvgriitNZ/vHtKLUqnGY7Cq0KQRBoPHjRF9i7rA6fQeK/Cu8H4LcAXq/k+DjNt3XZHFKweFsZfdWtVL3pL7l1+bVjFNyxlMiseASZjNKH1xGREYfXi2/lpgsNQhsSxFBzL1fePjXjNwdqOzgzOknZ4xs5+J2XOP7TN1n57F2c+/1enFYHKz6xnaM/foPIrHgyVs0jKDJYonB4vXScq6ftZI2v6WFiSg82ZUkeUTlJTPaN3FD3dJrTOB2AF+5YhkKlRJDJfF3YWevmS6WrOTJpdXvOs/DR9Rz6wau+iVCl1yC6RRr2XyQ0OZpN33gch9mGeXgCx6SVjV9/hM7zjVS/eQJNsJ6UxXkc+M5LJJRkSG5rSsWU3FMLh37wCmWPbiAsJQaH2XZTgZZ7avI6/rOdLP/kDjxukUUf2MjB771MwvxMGvZXzJDMUuk1LP7gJhQqJZ3nG4jIiMftdOG02Dn+s7f8GoUGG7rRGHWUP30HzUcuS1bNLhG7VZLEmovPjiCd+4xVxZx4fiernr2bsJQY6vecx2VzMtzSR/a6+aSW5zFY34kxJoyY/OQbatLilUqiuRtLsQxPkFCSSVR2AuNdQzh1GlZ/9l5El4hMIePwNZrVTqsDTfCNNbqD48KxjARowhXw3R8uu4PR9n5CEiKwjplZ8NAaat49Q9+VdsJSosndVIZKp8Y6avZNJDkbS3HZnISnxmAZnsDjnp3jd+Xt05R/dCumwTFCEiIxD45LmW9BIDguYlaVC5AmFqVW7Xcdh5p6OPazt1jxyR0c/M5LflrDoktErlLc0BkyJCES89C477VMoUAfbkSl0yCTy+m60XVDsoPOXr+AS7vPzagweD0eOs5KAe6SD26etZzvt78LjSSWZsHUAsUQE0rB1iUYokOnrM3VKHVqnFa7JHt2zTUEQJD0/9vP1uE024lIj2PFMzsYbu6l8pUjCIKAQq2k4oWDGGLDKNy2FKVWavptO13LUGM3oUlR2CcseFwiG778EK2nrmCICWXefSsxRodx/OdvzWgQHm3r59hP32TVp+9mtL0fp8XORM8wY20Dflz1gjuW0FvVOkOybVq6zjpmYt49K7nw5wMse/oOIjLi/j/2zjpMrvO6/587PLM7s8zMTNKCVtoVM1mW2Y5jhxxw0qRJ00C5v3KTNG2ThsFN7JjZli1mWkmr1TIzMw3Pvb8/7uxYowU5raFJ5vM8eWLNDtx5573ve855z/keQpIjmRud5s2/+CWR2fGkbS5ErddinTbTcuwaZR/fydnvL+7XICgE1nxqN6Iocu6/RgDEcAAAg05JREFUXl2UKz7ZPcyJbz/P5q/eQ8/lZq+UM4CCgxVceXJp+dis3aWMtvR6GqosMDcyTWBc2G21wY0RQVgmZbWnpe7fwPhwxjuHsE6b8QsxLVms7fX8mDA0fnpMkUG8/be/XqS9LUkS1587xfo/OiinHi58j12ljDT3eanIROUlycpcDhcTXUMU3bcRlUYFgoB5fBbz1Kys1CUIoBDY9JV76LncRN/1NkSHi+CkKFI35OMXaqL25XOLjHO/0ADKP7VbTjv8znOYJ+QGQEnrcjxyd/Z5C5nbizny9096OdOiS5RTdlr7qfzCnVz86Rsklmdz8jsveOnfO20OudFdfRfrPrOPy/99mLQNBQTGhTE9MC73FDDoWDi9ztxRTOf5ekS7k8v/fZiCgxUExIZS8/wtJ9FuBIVATGEKKevzUagUGIJNGIKMROenyCpTdhcOiw272cqq+zfJHYX3r0VQKwiMCcNps6Px1+MfHoTTZmeovovY1alk7ylFEAROffdFL2dxrH2A1uPVrPnkbrb/WQ7TAxOo9RoSSjMJTozEL9REbFEqlqk57GYbEZnxdF5oYKy1D5fDReFdldS9fnHRGmSenGO8c5CMbavZ8ZcPy3vhjJm2U7I2+mTPCMNNvYy19pGyPp+Kxw9w9vuvkFyZy8WfHMI/IhBDsD/WaTMuhwvbnAVBKaDx05G+dRXGiCCa3r5CQEwIwodrf/sM8PeLBeWCS794i3Wf3Y8pOoTZ4clF+qQg38A3XjrLmk/uZqCui7iiNGZHprj2m+PMj72Th2oIMlL0wKYldaJBjkRP948Rlh7LaEsfDW9eJrkiTy4yG5shpVI2sBcKIkFuuJO0NocNX7qLtlM1xBWny/lRTT3kH6zEOjWPw7pyVbmgkKNC/uFBJK3NIaE8C0OQUdbxLkzFPzQAncmPiKwET6R0OWYGxlEoFF5Hq6kb8hlt6aXwPrk44+R3X/BKcdAH+rH6oa1s/OO75OO2E9exTs/TdrKG3qst6Ex+aP31cnMOl0j9GxdJ3ZjP1SeP4x8WuNhguIXAuHDmRqdkTdNXL1D28Z2Mdw5SdN9Gus7XL9nkxD5v5fwPX2fzV+9lomcEtV4DEpz53itLVulbZ8xc/fVR1n/xIJO9I1Q9cZSovEQS12Qteq4+0I/UDQVE5SUhukRUGjWiy0VAdCjXnztF1i45J1qOeNsYbe0jbXMRhmAjsyMTBMVHLFnkdCtOq53Bui7KHt3BjZfOUfvyOQwhRpBkvdeEskxy9qzxMjIkUWSsbYCo/CSvJje3kra5iOvuJjvBSZGkbSqUjz6dLhRKuQOs1mggZ185Tqud4MRIEGCwrovI3ESyd5dx9cljWGfmqXz8DpoOV9F7pcVjhAkKBfGlcqT3zH++tGSx1OzwJC6Hk/M/eh21Xkv+neuILUplpLmXlA35KxrgMUUpS2qQW6fn6b3SQnxJOp23RJYHbnQQX5xOlzuCbQg2otZpsEzP4xdiIm1TIWEZsdjnrWz/84cYqu8iPCuBthPXqX35PHHF6egD/Rd95q04LDaQWDa9B+Ri6aIHNmF/Fx1FZaUFI4Zgo1ysuSpNTpEZn8EUFcxwU49c77F9Navu3yTXoWhkpZnui03Y5i0MNXQTGBNGZE4Cc6PTmMdnic5LJCr3UZAk0reuwmVzykZe+wDXnj7hZeSkbJDVGEaa+9AF+LH2sT20nqgmsTyHK78+uqw6j91so+NMLYnl2bQcvYbWaEBj1HkCCkq1isjsBI78w9LtzfVB/thmzKj1WhwWO9bpeYru3YjoEml4/ZKcJlDX9U73YDfW6Xm2fuMBui830Xu1BcklEpYWS/L6PCSXyLXfnFi2UNNhsdF6oobkdTlehmn27jK0JgNB8eEEJ0Yy1TfKRKdsBCtUSmIKUpZMp+u62MC6z+xblBp0M6GpMcxPzOKw2hlt7SciJ4GhW76TUq3CaXPQfbmJVfdt8vQdWAr/8EDUBi3j19pwmK3Ldq+0TM1jnpjBEGzEOj1PQGwo8SUZnPvha6gNWhxmG2mbCwnPiPPq9AhyLnTpx3bgF2ai+dhVj2OQubOYnktNuJwucvasQaFUMDM4QeMhuZFd7y2NuVRaNWsf20PVr454ySfOj01T98p5+q61UvG5/Yy1yRKGW75+P9P9Y9S9eoHp/nFMUcEoVErmx6ZpO1FN/sFK2k7ULNsO3Tw+Q+f5OtZ//gCXf/m2V3qQUq0idVMBEZnx6EwGVHotLcer5WLFEBPmyTlMUcGLCiGVGhUVj9/B7NAk1c+eIjQ5ivjSTLT+OlRaNS67iNPhoObFMxTdt4mR5l6CEyPR+MtF47JhLavAXPr528yPTRNXnE7uvnK5oc4r55dMD5NEiYs/fZNdf/MofqEmJCAoMYLowmQ6z9bz5l/+EtGxUF+kJLkyn4rH7+Dab46j9dcvMr5VWjUVj9/BaEsfx286vTRGBJG1s4To/GQEhYDDYsPlcNFyrBqXw0XR/RtlJZjJGUoe2YZ1ap4rTx5bZCcU3L2BuJIMRlr6SN+yyteK/vcRQZALWa48eYzc/bJOalhaDBd++uaKr2s+fMX9fDj3g9cWRcrMk7Oc/+HrbPjSQUaa+5ZsNtN7tZWktTkERAUjukTC0mPpOFOLSqvCL9Tkke1bwGG20X9dbkWcvrmQ8c4ht4rLarRGPXOjUwTELC25tfC8+JJ05kamcNkdpG9dhVKtpOmtK0RlJ2AMDyTZXa39bqLNtxKWFkPsqnTMkzMYI4I5/P8WR1IsU/Oc+69X2fjlu0lZn0fXxUbCM+NI37IKvxATKq2aabc8lTEiCOuMGb9QEy6Hk4nuYSIy41csokyuzOXiT+XGDeOdgwhKBZ0XGin/5C6u/eaEPBaCQEBMKEq1ivnxaawzZvdm1cz6LxzANmtmomt4yRxYXYAfOXvWEJwYIXfQFAS2fv0+JEnCabF7RaMC48IoeXgbTYevUv/6Rc8mviBj13ayBmN4EAV3ryciM47pgXEEQfBsElefPE7JI9sQRdeKRW+CIBCZm4je5IfT7iB7Txm5+8uZ6B72vN/AjQ5uvHKegrsqufLro7LBvLeMsNQYInMSme4fX3ITkqMQgcwMjpO6sYCYghRqXz3vMSaUahUJZZkExYcTFB/O7PAkQ/VdWGfmUes05B9YJx8xm22Uf2o3dUvkskuiSPfFRhwWO4X3buTyL99edB0gy1wudHG0TpuJyE7EYLai9deTsiGf9lOLFRvkzaCUs99/ecn37KlqpuDuSo+hrdZryd5TRkRmHCqtBl2gP9H5ydjdJzAB0XLuY9PbVZ6qfTn9IZ3oghQmuoeRRBGn1U5oShQrZ6dDWFrs8vJ8bgKiQ3DZHISmxtzm3WQHSaFQsvmr99J+upZDf/UETpuDuNXppG0uJCgunICYMNQGHbY5C01vXaH/ehvBiREU3r0Bv1AToigy2TWMUqMmMDbUvQQJNL11mc7zcr6zWqchYU0WSWtz2PZnD2KenKPlWDWCIAcfpvrGyNpVStzqNFxOF2mbi0DCM2+Wo+dKixy5TolGa9QjCBAQG8bM4AShqdEMN/UuMuBjClNI37IKl92JdWYepUZF+Sd34bQ76L7YSHxZ1opObP/1dsbaB9n+5w9ijAiS9bj7Rjn7/VfZ8MU7l+yU63XNl5vY+dcfxWG1037qBoFxYSSty8E6bUapViG6RNI3FxIUH0FfdRu2eQtj7YNLGvXWGTOjrf0U3FW5uI4H2REs+ehWXDZZh7vtVA0lD29jtLnPa62dH50mMDaUuZEp7GbrsupESrWSkoe3MTUwRuqGPGyzFnb+zSPuRjOy9v1QQxcdZ+qwTM1hm7WQuaNYVg0ZmWSqb4x1n9kHgMvpwmmzc+Jbzy/KiZ8fn+HUd19ky9fup+zRHYy1D2I3W9H46cncWeJxmLovN9F7pZnVD27BabMv2lcTyrLoqWpeUrsc5KLXtpM1sjP3s0MYgoysfmgLpY/uQOOnY2ZwnPnRGQLj5NOr4ISIRd2Mb6XrfANJa3MW7Tsuh1PuaCxKxBenE1+cjiAIOO1ObLPzjDbLaa3rv3CA6cEJap4/jX3eStnHdtJT1cRY6wBrPrGL3qstXPjJG9hmLWgMWpIqckmpzKP8sT1Yp+eZGZqg5oUznmCQIdhI7v61gMT8+DRxq9NJrsjlxLefo/LzB1bcHyVRouXYNQRBoPNCA1u+ei9nv//qovF0OVy0Hq9GdLkouncT3UsErlY/tIX2UzcWOXezw5NcfuIwBXdVEluU6iXI0HG2lt07PkbdaxdI3yr3Lznz/VcW1dFZpua59LNDVP7RAYof2oJar13xhPSDwGeAvw9IosRAXSelj2yn7rULXPjRG+z9x08s2VDkZiZ7RjBGBHH9+TOITheBcWEklGaiNeqxzVnpqWpmsnuYxkOXSd2Qz9WnFstwOW3yJh2cGI7olItLCu5Zj19oABd+8qbH+Nb46cg7sI7wjDgsU3PMjUxiN9uIzE5g81fvYeBGB4f+4pe4HE5KH93uaRW7gKBQsPbTe5joGvJSTwB5wy7/5G6aj1zlwk/eJDAuDJ3JgG3WQlha7Iqbj394IE6bndw71hKVm4SExOn/eJGt33iA2pfPeX2OoJDVIrQmA4JCoOtiAxFZ8ah0GgoOVmKdNdN3rZWmw1e8bsbowhRW3b+JdZ/bT93L5yj92E4u/Pj1JXXJ8++sYG5kylP04xcagCSKRGbHy4VGLhcZ21eTUJrJVN8YTreWsH3eRsObl5gfn5E3nPpuZkfkCIIgCHITFocLQ5CRdZ/dR+eFBvpr2mRDcNbCzOAEcavSyNoj58IN3OhAqVFR+sh2zv3gtUVyVqMtfZz67ous/+KdaAxaJrqGufHiGY9hoVApSVqXQ/FHtshHi0Vp1L50bslovMZPR8Xn9jM3MkX9qxcouHs9LceueUWYFSolieXZpFTkolSriMiMo/DejdS9ep5rT58gMCaMtZ/ey3BDN92Xm+SCuOgQsneVoNRocDlc7P7bj2GZmuXkv70ISMSXZpBckeeROzSPz+IfHoBlatYTUU5cm0PXhQbsZhv6QH90Jr8Vc9kHatrJ2lEs30O35IIr1UrUOg1+YYGUfWwnzUeucugvf4nodKFUq1j3mb1yitHbV5gZmkBj0JFcmUtIUhSXfvHWknmwC91Jg+LC2fKn98k5w0YDA7WdHPn731B0/0YCY8O4+NM3sUzOeTlWqx/cgnliluHGHnf6QyPjHUOs+cQujv3z0yg1KowRQWiNBk9qgl+IicTybPxCTDjtDoYbewlNjkK50EF3iTzYxDVZZO4oYapvlOCEiHcajiyBSqchOCGC5iNXCYgNpfGQ3Fwjd385fqEBVD97kqydpWiNerrdDl3WzmIytq/myq+OcOI7z7HhS3dhCDYSnBiJKIq47E4cFhtdFxs8xXzBSZEUP7SFrgsNnPquLO/mF2IifesqYlfJpxLbvvEAjW9Vea032//8oUXXrNSoCIgORVAIzA5N4LTKHWqrnznJZM8IhhATpY9sp7eq2atGZ4GsXSXyb+TWyV/AFBXMmo/vIqogeckCSYVKSdzqdJLW5chzWBAQHS4aD132LgoU5CJMQSEwOzy5bEGebdaCf3gg2775ICq9mgs/eZOJriEEhUDO3jWYokIYae0jIDYMY0QAww09nuvU+OnkfFl3BPDGy2fJv7OCLV+7n7ZTNUx0DaHSqIkvySAqN4np/jGCEyPZ8vX76bvaymBdFxu/cjdd5xtwOpwYwwIwhgeiD/Qn78511Lx4huKHthKSFEXbyevMDE4gKBTEFKWQt38toijS8OYlhpt65G7Aboc+Z+8a6l49j9ZoYN1n99F68jphGbG0HL3G9edOexnH4RmxFD+8jZrnTy9bkCo6XdS/fpHw9Fjaz9xgzSd2032xgc5z9VhnzOiD/Elel8v2v3iYuZFJT6+Nm8d8paLTBTrP1bP203vpOFOLeXKWcz94lQ1fOshocy8hqTHMDk5w7J+fJjQ1hrD02EWpR0v9viuduradrCFj6yoG6joJSYzk/I/f8Irm1iI7iZVfOMCV/z6Cf1gAvVUtbPqTe7n0i7eYuckBt5ttNB++Sn91G5VfuJPx9oFFJ+jmiVku//Jtiu7byK6/fgSVVs2hv3oCQ4iJ6YGlu0rfzET3MIlrsvEPC2BmeHJZZwag40wdGVtXYZvznveGIKNc+LzCyUrdaxeIW53O1m88SOOhS+6+KpLcOM/uIDovifo3Li0vYiFJ1L96kfLHdjNY20lMYeptv9v7ic8Afz9QKIgrSvMq9LidLqznpSoVY219VHxuP6JLpPNcHfMTsxgC/cnYthqNXsvFXxxatoV6aFIUlhkzGr0WjZ9WzvMyaHFYbGTtKmWgtpOguDCS1uYwPzHLye8877XJyNXqsgb1wiY33jFI6aPbOfVvL3gMvwUN7QXR+5uZ6BzixHeep+Jz+5mfmKHgrvV0nKnFYbWTub14RQM8Z08ZpqgQrDNmJnuGCU6MZONX7kGpUXvylgWFgswdxcSXZDAzOI7T7iQgOgSFSonWX++p0lfrNHScqyNrRwmROQkotWqUKiW2WQv91W0YI4Ko/MIBOi80UPmFA4y29tN5th6HzU5QfDgZW1fhtDkwT86x468/iuR0YZ6cY7S1n+CECAxBRjb9yT0MN/Rw7F+e8brpA2PDKH9sD7Y5uXg0aV0OCqWC7N2lSKJceKbWa+ScYJdI0toclGolE13DsnpOTCjjHYO0n7rB6oe2EpXXhjE8SK5IDzEtqSfrcjipf+0iJR/dRu8V7zip6JT1ml12J2mbC5kbmaTy8wc4/R8veusvC7Dus/toPHSZwbou1n5mL7Uvn1sUARGdclc/h8VO2uZCSh/dycWfH/L8tlN9oxz7p98QXZhC5o5ijJFB6Ex+2OesTA+Oo9aqCYgJZaihG0EhsPaxvcwOT8qGrbta3S/ERPaeMiKzExlp7ccUFUJQfDgDdZ2o9VrCM+MWyV0txcCNDsLT4xYt7PElGfRXt1P26A4u/vQdRQxdgB/ReUnua1NQcM96bDNmlFo1/iEBvPnXTyDe0g1PUAhE5iSRs7eM0dY+jv3z0x6jVmcykLqpkC1fvw8kuZit7OM7Ues0zI1O03q8mtHWfs5872W2feMBTv37ix5ncHZ4ksH6LmKK0hAEOc+8/JO7OPejN8g/sBZjRBDtZ+rkFvAGLckVeTgdTqYHx6n4/H6O//OznmtMWZ9PckWuJyIaEBOK3Wyl4nP7OfXdFxcZDUq1HPVtevsKg/VdbPry3SDISk6mqBCuP3+Kis/u59rTJ72c84Y3LxMYG8aaT+6m62IDSrWSK78+Kqf0SG5DtTiD9C1FjHcMYTdbWf3gFs58/xUvpYL58RmqnzlJ79VWyj+1m7Pff8Urj1lQCIiihEqvwWmxo9Zrydm7hvCMWMY7BpFEieDECMyTc0wPjDPZK7/WPD7DzMA42bvL6KuWTwwXCEmRFRluLVYHWQb2+LefY/Of3COvq346lBoV/qEBsorTvnKGm3q49PNDWKbmEQSBiJwEVj+0hf6adhxmG5k7ilGqVZ5OwsGJkcwOTVD32kUv2cuAmFDmxqa5/uwpCu9eT3SRWy5NgNJHd8jFY4Igd2cdm0GlURGeHsvWr9/P/PgM1ul5/EIDUOu1NB2+wmBtJzdePEvBXZXErU4jd385TqsDy9Qc5qlZ+QTm8BWyd5WSuCZLbgBnc5C5o5i50Snmx2ZQamUVG41eS+Xjd9Bd1cR03zh5d6zDEGxEkiQUCgUSEsf/5VmvuiFJkjwdClc/uIWT332e/uttbP3mA7Qeq14ypdI2a0FyuWQjfgUGazvkk7f0WI8cbuyqVFLW57ujnC5Ep5yih0IgqSKX5puaaC1XdOp1LXMWrwJj0SXS+PYVonITZVUuo4G8O9fRf70d+5xF7gS7ghGu0mlW1KAWnS5GW/sJT5f7TSzl7Pdfb0epVlH88FZaj19/p038Mqdfc6PTtBy7tmLjq9qXzxHp7qIr64a7UGpu365dqVYhOl1EZifSd23luhJJFLHOmgmICmbgpvU7pihlyXTOm3HZnQw1dtNzuZmM7atRqlV0X2qSAwWJUSg1KvqrV66TkU+uBHRB/j4d8N9PJFpPXPfc1AHRIVim5wlOilzxuDQwLgxJdLH20/toPV7tJcMzMzDOUEM3kbmJVHx2P2q9hlX3b2LgRoenHfnM0ARxJRmc+vcXcZhtBCVEUPbxHSjcx36CUkFSeTahKdE4HU4u/ORNHLekhdhmzVz40RtUfv4AQwk9hCRGyBHYmnY2feUeRJcoH/MZdBz+O1kZRaFSEhQfjkKlZG50CsvkHObxGSa6h1n1wCZEu4vwjDjmRibRBchyVNd+c8I7qiFA1o4SAuPCee0bP/XkjS2My9rH9hJflknX+UbWfWYvY+2DHP3Hp7yMx8DYMMo+sRPL1DypGwsYrO+m4rP7aD56jYZDlxGdLoyRQaRvLiIqLwm72YZ5ao7U9flIoog+0J/0rasQFPIC6HI4megaYqp/DI1By5VfHfXKQdQYtBTetxGlRrXI457qH2W0tQ9jRBA1L5whLD2W4IQIal44LUeLBIHyx/ZgnpwjPC2GGy+dRUCOvgmCwMzgBIYgI+EZsdjNFgZru2gdvY7WX09ieTaFd6+n4dBlhht7vCJ4I829KJQKQlOjGW8fROOvB0nydC/ruthAxtZV1L16gZiiFHb85cO0n77BcFMvgiCQtqmI+fEZBuu6MLiL/5QaFcUf2YpKq2Z+bFpuVOE2EHuvNJN3RzkulxOFSkHRvRtQatWYx2eY7B1FrdMyNzqNf2gAp//9RVlLPMjokTfMu6NcrqSval5UBDc/PkPVfx8hc0cJKp2athPXSa7MI251Ojv+8iPYZi1M9AyjUCpWdHBdDifGyCCv3ykoIYLUjYW0naphqLGH2eFJ1DoNJY9swy8skKG6LllqMCoYAbkyf7ChG41ey8Yv3ikXoCoVdJ5vQHS5SNtUKKccXWqk9fh1FColpqhgQN74equaSSzLouaFM/Rfb/Ncb2BcGHl3rCMoPpyWY9W0n6ll/RcPcvxbz2F1O8bdFxvJu2Mtta+cJ6Esk+mBMXb+1UfoOFu/6BRsrG2AgOgQyj6xC62/npKHt1H76nmyd5chuVyc/M7zOKyysRoQE4o+0I/8g5Vs/tP76KlqZqi+C0mSiMiMJ6Esk5Zj1R7HxTZvQWPQkbapkLpXL1B070auPX2CsbbFetFTfaNc+MkbrP+jg7z110943R+i00X3xQbG2/vl7rIN3TS9VbVIJuyd79TPwI0OQlKjUWrUBESHEJGdQKA7NW733z7KeOcQhiB/mo9ckyOmNxnPEdnxlDy8jZ1/9VHG2voZrO+m41wdyRV5FN23EY2fztPoJG1jIfWvX1q2gNhptdN6ooaENZls+NJB7PM2pvvHiMxJoOaFM151AZIkMVTXxUhTL5u+cje6AD/qX79E98UGr5SX8Iw41n1mHxd+8k6UM3VDAR1n61CqVbQcryYsI5bij2yh4c3L+IWamB+d9lL6yN1XjikqmCtPHvMyJhfqY/SB/nSdryciK55j//w0G750Fxd+8iYRWfGEp8ei0mlIrsxjdmwatVbDSHMvOqOB6mdOenU+1Af6sfrBLbSfqSMyO57I7ERuvHiWkMQIUjYU4LDaaDl02cv4DogJJXdfOVqjnpmhCSa6htjy1fuYGZ5ApVItuu/jSzNI21zkbqSkuK38pSRKqDRq2k7VMDM4weqHtiAoBK78+qinhkqlVXsKKtM2FjDc0O2J0spNXFZuBKVUqxZF4Yfru8nbv5aOc3WkbS5EdDhJWpeD1mggaQmN+JuRtdaXj/TqAvwwhBixzcwT4C5mXTLl9EoL+XdWYJ6aI3tXCed+uLz2NchrSdbOkmX/7rQ5sM9aGHU71LK0auCyEqILxK1KY6C2k+DECFwOBwjgHxaIUqWU5Q7dr1XpNJR9bAcuu5P4kgwa336n74dap2V+fGnloJuxm20ExoVy6Rdvs/FLBxnvHERj0BFTkIwkSrhuSTHyCw0gKjcRpVrF7Mgkg7VdsvMbF86HXYXpM8DfDyTZMIkrziB9axHzYzOYJ6bJ279WluBbhoxtq3FYHUz1ji7SwFxgqK6L0OQoYgpT6KtuJW1zEabIYCZ6hglNktt6i+7ItehwIjpFqp484tXwQFAIJK3LpeKz+zjzvZcXpSFIkkTDoctkbFuNf0QAChSMtvZz5B+fwjZrcRsNaxFdoqeT4njHIC6Hi+DECARBoP7QZbovNBCSFMmpf3vBq8Nkzp417P7bR+i92srs8CS6AD9ii1JRatWc+c+XvIxvkHPwTnz7ObZ+4wGSyrNR6bQkhJpIXJcty/BdbmaiZ5ii+zcy3T9O79Vm/EICiC/JoP10LYYgE0nl2fRdb2fWLXkUX5pJ3h3l2K0O7GYbp//jpSXzlfMOrCN7Zylv/79fLVqg7WYbl3/xNmsf27OoK2L27jLs81ZOfOs5oguSCYoP5+wPXkGtk08lktbmMDs8SVBCOFW/PkpAdAipmwpQKBRMdA0zNzqF1mhwFyJZCc+MY+CGXNQ42tpPSFIUZR/fidNqZ6xjkLpXz3s2XuusmdJHtuO0ObBMy5E4rb+erouNtLsNzqydsmQWgCE0gNSNwSBJGEKMXH/2FABJ5VnoA/wIT4+j42wdDouNgJgQVj+4hfnxaa4+JTtRPZebCUoIZ/UDm6l+7jT6QD9SKvOJyEpgZnAcXYAfaoOWtZ/ei2V6ntmhCbRGAwHRIbSfrkUX4L9swRJA85Er7PrbR4kpTKH58FWP42UIMclttr98N+d+8JqXoWAINhKdn4xKqyZ2VSrWWQtbv3Y/00MTKN0nJYP1XWTtKuXs918hLC2Gko9uwzI9z3j7AH4hJiKzE+g4V8fRf3mG7d98ENushWP/8gz2eSu6AD/SNhWSvrUIpUbN/NgUGj95jPPvrCAyN1HeMCWJgJhQVFrNouLhhbl99r9eofLxA8QUpaHWqnGYbWz903vpu95Oy7FqbLNyEaDNbMUUHUJgXBgOq53O80sX1U0PjNP45mXyD1Yw1NjDpq/cw3jHAFVPnCC2OI2MbatRazWMtvYjSRKi0wkCxBalkFieBQjMjU55SaXJt668WfmFvKMNvJTxvcDs0CTTfaMYw4O8utguMDc6Td+1NhLXZi/qknkzC5HmjM1FDDV0Y4oOwS/UhGVKrgkYuNEBgoB/qImo3ETG2ge8osnDDT2c+8Fr5B+soL+mg8K71zM/Po3W6MdgbQeGYBOVj9/B8W8/R2Bs6G3VPXqvtpCzp4zT33uZmYFxghIi0Af6LVmUC7LDMTs8JctnLpEzPdLcS9UTh6l4/A5cVlmJQqFWEZYeg8Nsw+V0ofXTMz0wRv7BChxuzWlTVDBjbQOyhnJcGGd/8OoiY9UyNc/5H73Opi/fTVRuIh1n63A55JO8DX98Fz2XGmk+eg3R5SIsNYaM7avlVMjwQM58/5Vl32/Ln97HSGsf8aVZrP30HkSHi8meEYKTIhFdLio+tx99oD8KtRKlSsVQQxf+4YEYI4JRaVTMjkxhnpzDEGT0MoKyd5dhjAzijLvh24YvHly2+dcCxoggBKWCrguNpG7I9zT0uRmnzUHrcTlVJmtXKWs+sYvhhh5aT1QzWNdJ7Kp0L2WcW4krTqf/lqLyBSdtZnCCwRudnvz6Wr9zbPnafQzc6FgyrdEvVF63jv3z04v+ZooKJnf/WvRB/kz3jyEoFKy6fyN2txJX67Frns62C9dgmZ5z1zppbhvJd9ocK6pTgRyw8HSzlKDbHbRZUDO7Gf+wADK2FROVl0hIchQup4uovERy9qxhbmwal82BKSqY6cEJmg5VseqBTbSfraPvags5e9eQf2eFp8uoZWoOY3jgitcGEBQbhqEgmeSKfCxTs5Q/theX08nc2DT+YQEExYUz2TOCf3ggRfduQFAqGKiRA5VhqTHk7V8rq4ddbSVhTeZtP+/9xGeAvx9IEmmbiwiMC/csJADFH9lK0f2buP7sKS9vWlAI5OwrR3S4EARodbeRXo7207VE5SYy0tzHSHMf4Zlx5O5fy9t//ySJZVluWZ6XKX54Gxd+/Mai6mVJlDwtpSu/cICrTx7z5CjqA/0xRYcQlZsoSyG6RGyzZuKKM1CoFHRXtYAkYTfbqPjcfgbrOjn6j7/xikAGRIfIDUqsdiZ7RrzzSyWof/0iTYer2PTlexEUAhPdI1x56jj5B9Z5qb7cjGVqjt6rLcStSuPMf72K6HASnZ9MUkUueXesBZA7iuYlk72rDI2/DofFjsZPz9zYFHqTHxWf3cf0wBjVz5yk53ITieXZ+IcGcPWpY8sagLUvnyM8Mw6Nn15O1XEfwUfnJaNUq5gbnaTtZA2pmwrlqJHJQHBiJIlrsjyKBPkHKpjsGWbbNx7EOmtG66dHbdDKUkjRIVim5ij7+E6m+0ap+tVRr0iDQqkgc2cJccXpRGYnePKdxzsHaTl2DaVayfz4DOu/cIDTbnlDQRDovdbKzOCEZ8NX67Wkbiyg4vE7GGsboONcHf3X24kvyyL/wFr6qttpO3Gd4o9sYW50CkOQkfgSOTfy5vkzOzxJ37U2MncUs/rBzVz59VFcDifdl5pxWKzk7l+L3Wzl7H95pxOotGpy9pWj1mk8hasqrZr8gxUgSfKJxS2qCwuYIoNx2Rwc//ZzXl0GzeMzXH/2FBHZCZR/ajcn/+0F1AYtxQ9tQWs00FvVzNzYNMNNfUTlJNB5vh7LzDwFd61ndkg+hZgbmSIwNoz0ras48/1XmB1657uq9Vpy9q1h4xcP0nT4queeicxNJG//WlqOV7uLgl0kV+QSlhHH9j97iIY3L1H79+c993js6nRCEiOWbU4kiRI1L56h4O5KTnxLThkRBIGo/CTWfXovrSeuY4wKZvufPURPVTMuu4OQxCjWf+EATruTq08eZbL7HUNZqVYhKBUoVEoisuPkfPKLjWz5xgNoDFquP3fa6+gXICIrntUPbfFocusC/Mg/WMFE1zC1L59DrdfKubNmK6JLJCIzftnf62YGbnQQkhK1pAEO8olM0trsZU8wFrTfmw5f5fITb1P26E7G2gdQqlQ0H7kqp6XdZE+EpcfK0eRbajome0Zw2Z3Mj01z4jvPe1I1QpKjEBQKRAm2fu1+BOXtVRFcdoenQzDIqUy3Kt7cjEonN2S7/MTyhXly18EpJrqGMUWHEBQXxo2XznqUhAKiQyj92E5sM2a6LjTIaWvrcim8ZwP2OQt1r11cNlIsOl00H71G8rocT7TZPyyA8z98zSs3fXZoks7z9Wz7s4fkIrfl3s8l0nDoMgllWbQeryalMo/B+i4GatoJz4wjvjiDlmPVKJQKVj24GZfDyWT3iFeOt1+IidwD67BOm8nYtprGQ5cJSoggNCValpR0G4kd5+pIXS8r4CxH6qYCJFHEYbWRtC6Xk995ftnnDjf2kL2njInuIURJpPRjOzEE+sunFfVdXk78AlqjnrTNRYuay/iHB7qbvXj3PrDPW6l5/gwbv3w3Lceq6TxbJ586uYuMkytyQZIWRZQXCuyvPHmMye53OmcLCoHENdkkrc0mKjcRv9AAGt645Pm7eWKO1A35iC7RrdazvLKRUq1Euk06rEKlJKYw1ZNK0nriOmsf20v2njJajl7zBOyS1maTsqGAxrequPb0cSRRwj88UA7chQdS9cThd3okpMey9rN7mRmc8ET+69+4SNE9G1j/hTtpOVHNYH0XlZ8/QPPR5aWKdSYDSo2K8z9+g7WP7cEvLBClWumWajaiUCko/sgWBKXcREmpUqLUqElal4t9zoLWZGCwoZuQpEg0Bi1OmxOt34rD8b7iM8DfBwSFgsjsBE79+4uoNGoS1mShM+qZ7B0hICaUPf/wcfqutTI7NIk+yJ/ovCTGOgdRaFSo9boVo4GAO2f7najBSFMvQyldxBamygusJLHqgS3MDk8sKR0EsnExcKNDFrS/ZwNOqx1dgB8qjRqXw4ltxsypf3uB2eFJAmJCydxeTHxJJlH5KWj0cqv74YbuJXP3pgfGOflvz7Phi3cRkhS5uD01sibptadPUHjPejrO1lHx+B0o1Up2/7+PMdreT8PrlxaNQ+/VFvzDAkhem8O1p08wMzhB+5latn7tfiZ7RgjPjOfGi2fI2LYau9lGzQunvW7k1hPXSVqXw9rP7OPs91+l40wtBQcrV6zwBmg7cZ2ktdn0VbdR8sh2pnpG6b3agsNqJygujLwD69AF+lP+2B50RrlZz2BdF+u/eBDrrBmFSkHXxUZPQRLIi23RvRuZG50ic0cxTqudzguNpG0qRBIlxtr6GWsfkDe7Ny6hD/QnZ3+5V8Fh18VGdv71R+Wq9sEJVj2wmcG6Dia6h+mtaiF9S5HHAHdYbDQeuozdnE/qxkKmeoZJKM3CYbXRdbGRhNJMIjJiUWrVaP3lDafmxbPLzp+WY9Vs/fr9bPuzB1Eo5YJSSZLQmvSc+M5zOG+RrnTaHNQ8f5qSh7d5upyptGoGajrI3FmMITRgWTnI9K2ruPb0iWVbfA83dBNfnEFkdjzZe9bQdPiKlwRi39VW6l45z+qHNnv0pgvv3cDpf3+J4ke2kb27lGP/+uyi93dYbFx/9hRrPrEL+7y8MZuigsnZt4bWE9XojHoS12QzUNtBSHIUwQnhVD97cpH8YmxhCg3u4sWbCU2NJnVDAcaIIAB3N9U4WZVDkhio6WCqb4zNf3IvY+0D1L9ynpJHdzDdP0bDocvY5y0YI4JYdd8m5samqfrvI6RtKiBlQz4uuwu72UpoSgwKhUDZx3Yw1TdG3SvnPU1pvMawsYeLPzvE6gc2s/Yze3HM25AkibC0GHL3r0V0uei73uYpqAuIC71tbwCQnQuFcvm/22bNshSY+7cPiAklblUaar0Gy9Q8gfFhNL5VRf/1dmKKUuV1ymig8a3LS54Sjrb0UfXfh1n90FZOffcFr7/1X28nPCOOnqpm5kam0Jn8GGmRFVDCM+KYHhyXpdmWKl69iaB4+ZQv7461aI1yl72uZU4jAIITIhjvGiJrZwkxBSmyEojDSU9Vs9xp2G2I9VQ1ozMZuPDjN2SpxU/vxWl1MDc2TenHdnLlV94nEp3n69GZDGz5+v23jdr3X28nc/tqQD4d0ui17hMq746RkighiZLXielSDNzoIGtXKed/9LpbH7sEvxATw409BCdEkH9nBWPt/Yy29BOcGIEpKtjjsICcXnbpZ4co+eg2ktZm0/R2FakbC2g4dNkrQttf3UZKZR6xq1KXzC1OKMvEGBaEwyLX7cwMTdy2ALLtRA3GiEAa3nTfkwJs/up9bPrKPdS+cs7TlVhQCETnJ5O1q5Trz51aVKgspwnVkr5l1aL7OyI7nqm+MRRKBZV/dCdaPx2iKNJ5to6T33meuJIMSj+2k8u/eMvjfBZ/ZCvnf/zGon1PEiU6z9cjKAT8wwMJTY4mKCGCudEpFEolgbGhqA1aXA4nieVZS+7JC8SVZq5YN+MXYsLlcOEfGoAxIojZ4UkkUeL8j98gfUsRm/7kXmaH5G7Bar2WE9961utkeG5kiqtPHiO+JIOSR7Zz4cdvAPJ9ee6/XmXtZ/a9s85LUP3sKUxRwaRU5pG5vVhOY7xnI9XPnlx0bQqVkpKPbmOgpoOKz92BUqWg8e0rmCdmMEWGuB2HFLouNtFxtpbc/WvR+uupf/2CJ7CnUCqIKUojMjOe8Kz4254GvN/4DPD3AUmSaHz7CnkH1hGVk8j00AQBkcGeokZBAmN4INH5KShVcsQlLDla7takEBAUimWrvkHeAG8+tlMoFXScrWPNJ3bRdUFWFtizq5Tqm47h/EJMmKJDCE2NJjw9FhDkoyaNCkOgPxqjnqnuYc/16AL8WPOJXbJEm0rJjVfOYZ01E54Rx2BtJ067Uy76+cYDXHv6xKLcdsvUPIN18vNy71hH1ROHMUbIne1UGjXjnUN0X2xEZzSw4Uuy9rVCoZSPKcODWP9Hd+KyOah7/SLjHXJea0JZFlp/A6bIEPTBRuxzFkJTolHp1BhCTACs/fRerDPzVH3He/NdoPNcPabIYGJXpeKw2r2anizHVO8oUXnJlBWleYp8FpjsHma0rZ/Kxw/QcuSalzSZWq9ly9fu49i/PLuoocZU7yin/v1FNn75LvQB/rgcTqJyExhp7kOhUJBcmUvBPeu5+uQxpnpHaT58hQ1fusvrPZxWO7YZMye+9Syxq2XN1uDEcGxzVoITI9CaDHK+6E2nCh2na8nYtpruy3KxjtaoJ6EsC0GhQKXXgSiy4UsHUaiU1Dy/WLMe3Fqtn9tPX3UbbSeuezS2tUYDmdtXs+bjuzj/4zeWbDjT+NZlih/eRlxxBoYgf0Zb+5noHEYf6E/ZozupefGMV+MhQaEgKD6cqv9eWT++42wtJR/dRseZuiX1xyVR5Oqvj7HpT+6h83wDTquD8sd2Yx6fpfNCw7LGPcinIGs+uZu+a20U3b8JtVaDf1igp2392k/vlTvxzVmX/GyV7pajYQFW3b8JndFA0+GrHuMpKD6cjO2riSvO4MqTcgc4yeXCYbFS/ZsTrP+jOxe1oJ4ZnKD/ejtpW4rY8rX70Oi1cqrRmVqs0/OyMkVhCjl7y/ALMS1pfC8w0TmE0+6g+mcnGGsf9Lw278A6VFpZ+i44IZKZwXH0gf6EpkTT8PqlZd8PIDwzbsUTPf+wQESXSOKabOKK09EaDSiVCllBRHSh1sla0IO1naSsz+PGi+cofmjzivNhqncUl92BKTrEqyDN5XShC/Bj/R/dSeOhxQZ8SHIUaz+9l+SKXJpuKtK7ldSNBYguF1p/Pd2XGkndVOhWi1i6+C0wLoyIzHia3qrixLefx+VwojFoSSzPZtNX7vEUALscLgS3t2KdnufcD15j/RcOyP0jnj25ZCMd64z5tmkHIM9/BAFBIVB493quv3CGzO2rGazr9DqZCYwLQ6G8fV7sgoG68ct3Y52e5/DfP0lgbBiFd1dy9gevep0kLaQ8Vn7+Ds5872Uvg63mhTNs//OHMEYEERgb5lXMC3K0/dwPXqPkke0krc2VT7Gm5CY56ZuLsJttnPvRa2TvLiOmKHXFsQjPjCNtYyH+4YEISgWRuUl0XWjAOjXHzOC4W12sQD6NdrrQmQxMdo9w4cdvLCp6jy/NxBQd7CkiX/3AZqyzZncnUSVOq4Nj//Q0kiTR9PYVNH46Nv7xXfRVt2E322g/dQNBENjytfvlUy2HU5YzXCH41nm+gW3ffIDB+k7KP7kL8+Qckiii0qoRnS7Ofu8Vyj6+k4GajiWL9GW527JlT65UOg0lj2yn/vWL2OYsrPnkbq795ri7oFmk+chVWo5Xk7WzhKR1OZz67ovL5s33VDWTuDYHU2QwM0Pyfjk3Os1Yaz+R2Yle69DM4ATV7rRHBNj7j58kMC6MhjcvMdbWj0KpJLogmazdZVim5kjbugrJ6aTt1A2SyrMZae5jtK2f9C1F1L50lsG6LuJLMtDotYvkZ0WXSO+VZmYGx+WAmcmw7Hh/EPgM8PeJ5IpcZgYnmOwdwWG2ceH1iySUZRGVl8Rk3yhqvQalWslYxwDDTT2krMtjuLEHvxATMUUp9LmbBagW5MTMNk+kJDI3kfGOQdK3FJFQliU3L3FX5ccUpdJf3cZoaz9xq9OJyIgjJDkKu9mGUqVkZmiC8z9+g+CECJIr87DPWVFqVEgOF5PdIySuzaHp7SpPZEZu4Z5B4V3r6alq4ug/POXlNfqHB7LmE7u48eIZT9v4BfprOsjYWkRAbBh7/vETIEkMXO/ANm8lcU0WOfvKUahViA4ngTFhdF5o4PyPXvc4Kgtto7UGHaNtA3Seq8NpdRCSHMmmP74bhfs4TaFU0Hu1ma7zjRTcXemVI7cUrSeus+YTu5ifmEFt0N72t1TpNZiigqh9+TwzgxMExIQSnZ+EKSoEpVqJKTqYhkOXFukCJ67Jov30DS/jOyAmlOi8JDl9ZWyagevtJKzJ5sS3n/PaPHqvtuAXamLtY3u5/MRhTwFOxrbV9FW3Mj82Q2haNFp/HRFZ8fRWNTNU18XGL9/N1SePUf7J3Zin5lh1/2YUSgV1r19gvH0QfaA/Uz2jBCdFMtkz4vmfZWqOpIpcal86y3jnECUPb1s2OlB47wY6z9cvGmfbrJmaF86QvqWI3P3l3HjxLEq1ktDUGHcB5wxTfaMYgo3UvXrBa7O98dJZIrLiqXz8Di7+/C3C0mIwBPkjie+uLbx5YgaVVk3H2dplnyNJEu1naln76T3Mj08TGBdOcEIkx7/17LKvATlapzFo5Uj4nIUz//GSV8rEQtfb3H3lKNWqRTr15olZTJFBHscic1sxLruT8+7o0AKTPSNc/Okh8u5YS/auMhrevETWzlKajlwjZX0ebSdrlu1m2HqsmujcJASFgqm+UbfxLZBQlklyRS4KtWrFxjwL9F5pwRQVwli7vOn2XWtlqL6LDV86SP0bFzGPz5K0Nof40kyQJALjwpaVHDMEG+Wc6hUKz1PW5zPS0kvBXRWy1vGMmZaTNVhnzRgjgkipzCMiK57Sj+9E66dHH2Bg6DYnVuCOdqfHehngkdkJRGTGcfU3Jxal4ICs9rQQpZvsGVnyZCylMg99oB+jrf1c+81xtv/5Q6j0GtK3FC2ZA64P8idxTRYnvvWsVwTVbrbRcqya4cYe1nxiF8f/9RlCkqO86khss2am+8cwRYcw2tq/6L0XcFjs6IP8ly1iBbnoWK3XsOMvH2a0td/z/VPW51Pz/GmSK3NJ3VDAzNAkCIKnKHU5AuPC0BoNWKfnufizQwgKgVX3b+T0f768qHPvQsqjUq0iZ385zYevedZE+7yV+bEZQpIj5RbSS+C0O+m62EhoahRJa7MxRYXQeb6e9rO15O1f525KloxSrVw2Vzz/YAV+oQHUvXbBs5YuaP1n7Szh4s8OMT82I+dxv3CGgOgQ8u5cR0BMCOWP7aHl2DXME7MEJ0SQtC4XQSHgtNkpfngLlsl57GarXKB+ro6ktTl0XmjwWj/t81auPXOSzX9yL/WvX/QUnfdebSbvzkoiMuOpfvrEsuMNIEkikiQXKx7/13fmU2R2PHElGSjUKkZb+1n/pYOMNPdy48WzOMw2jzxm3h1r5d82yJ9t33xQNnDbBzxNnJIrcml487JHyerCT94gd/9aij+y1fNZhhATTqsN+7x12ZS6BdpP32Dd4/tpO37d44T3XmsltjBl6UCAACFJUQiCwET3MOlbisi/U655kGV2X6Dko9s8MrExhSmc+M7zOMw2/EIDEB0uj3ORurGA8z9aviB1un+M8Y5BonITV/wO7zc+A/x9QKFUoFAosM2aUaqVtJ2oYd1n99FyoprpAblzluQSaXrrCpG5iaRtKOTYvz6L0yJr35Y/tgfbrJm0TUXoA/2xTM+hN/lhnTXTevw6WTtLUGnUzI1McvI7zyMoFcSuSsMYHkDa5iJiC1MQnS5sM/MMN/Yw2TNC2uZCxjuGqH7mJGs/vZfZkUmu/eaEx+MOTY2m4GAlfddavarSXQ4nnefrGWroouLxA7Qev+61kcyNTHH2+3IL9Lf/36+9Ivei04XWaMBhttJ+upbOc/WeRckvxETZx3ficjjpOFOH02YnKD6CLV+7j/bTtQw1dMkyUloNl375NvpAfyJzExHtTmZHprjy1DEyt63GaXdgnpwluTKf0ORoghMiUGk1aAxaz1HirbjsTgyB/vTXtLubcxgWRahvJnldLjqjn6zLvbMEu9lG96VGpnpHCUqIwBQVQuKabFI3FHD1yWMeIymmMEXWXkfOrV8ojOy50oLTaiM4MZKkdTm0n65dMnIzPzbD5V++Tf7BSs5872WPmkn5p2TP3WV3MjM8Rc6+coru38RIUy+1r54jcU0WPVdacFhstBy9JjtJn9yFy+YAhULuOBcVTMXj+5kfnab7chPR+Ukc+fsncdmdqHQauXPnEmj99QTEhHLlV0eX/DtA6/HrbPuzB0EQiMySmxw5LDY56h1sRHS6GO9YXLw33NTDZN8oFZ/bT/upGsY6BtEZDSQEL+4Geit+YYHY5ixeBcX6QD8ytq4mNE1uNjPS3EdPVRNafz2jbQPMDk8SlZtE0X0bqX721LKbd1BCBAgCISlRvPXX/71kvnLftVY5Paoyj9bj3uoHnefrydy+Wj7dUCmJL83w6ljoHxZA4tocWcvb5qC/pp38OysIz4rHP8RIaGq0u8253BDm5rSFm2k4dJnkdTnErkojKDGSgKhgzBOzXH/+NKaIILTvItojOl2LusM5bQ6qnzlF+pYiLv7sEDUvnKHtZA0bv3I3pW4Jx1tTGQzBRjZ86SAqrQa/ZWQzI7ITCEuPobuqGdElUfP8aa80g8HaTlqOXiPvznUklGZin7ciKJVLnqws+h4uFxkbi2WJQUFgsnuIkKRI7PPWJY3vBSa6h5kdniB7TxkplXl0XmjAOmPGPyyQ5HU5WKbnEEWJoPhw1jy2B8vUPKNXWojKS/IEP24mdX0+jW9VLauzPj0wTr/bCY/IjOPGi+80ytEa5WJM68w8/mEBSxb0AXScrSNtUyENb17GEOSPy+FaFEnN3l1Kw5uXmR2eJLkil61fv5+xzkGi85KIyklAqVEz1TeG1k8HokTR/Zs4t0RR5wJZu0qZH52i3n0CEp2fzHBjzyLj2+s6z9xg5988SmBsGGqdlo4ztXReqMc2ZyHvjgpEUSShLBMQMEUGyWoWEsSuSmW4Ue62Ot0/TnJFLknlOcyNTtF1qYGQlCjUOhXz47P4RwTiHx7oZRwmlmej8dN50iEWsM1ZaHjjEtMD42RuL+bcD18D5Pu9+KEtdJyrwxgZAoJA1s5S1DoNtjkLda9eYLxzEKVaNmxTNuTTcbaexjflsSi4a/2iLrpqg5aguDDmx6cxxYSwacM9aP3l3HGn3U7/9dbbzuuU9fmeLrE3E5WbRGBsmCc4M1TfRUhKNDv+4iM4bQ5cdicDNzoYbu7FMj1HQkkGLcevE7s6jdRNhWgNOsyTsx5jdgGVRo0pMkgu9G+XI9FqnQbz5OyynU1vxjwxy2hzn6cYsvrZU7jsDhSqxTlpieXZpG2W0y+dVjuCQpD313gBhVrFcFMvSrUKndGAeWJG7oj9by94rjc6P5ket/TugrjAcvfcAl0XGgjPiL3t93g/8Rng7wMup4v6Ny6y9tN7OfJ3T7Lus/vov9FOxpZV9Ne0M9Y2IN+8xWkYI4IZa+snpSIXp9VO0roclFoVRfds5PJ/H/aKLgVEh1D88DZUejU1z51huLGHgrsqCU2JoqeqmbH2QcyT86RsyEOtlTWwx9oGcFrtZGxfzY0Xz7Dqwc30XWtdpKAw1jbA8X99ltJHt5NQlrkoummZmqf1eDXJFXk0vOl97GydMTPc1MPaz+xlomOQmKJUBEFApVXjtDsYqOnwNNwA+QZZ+5l9i3IaB+u6aDp8hbWf2UvO3jKPRmfJR7cx3T9O14V6OQKeGk327lKm+sZwOZzEFaUx0txLq7v9r85kILE8m6xdpVz86ZuejSs0JZrMHcWo9Rqm+seIzE5AEARy95d7dda6Gf/wQCJzEhlq6CQ4KYrLTxz2iugN1nXReKiKko9uxTw5R/FHtnoi1kqtGru7q2LF5/Zz7ekTXrmVg3VdNLx5meKHt5K5o4Smtxdrqk8PjCMoBUKSo3DYZN1eSZK48NM3vRo7+YcHsur+TWRsK0bnr+f8j14n0y03JSgEVBo1TosdyeVkum8UBAF9oD8afx2rHtjE+R++7pGKc1rlbnFLqQ9E5iZ6TmeWQ5IkRlv60Og1HPmHp7ycIJ3JQMXn9hO7Km1RRLbwbrmg7NBf/dJr44/Iir+thGfS2hyvhT13fznxpZnYZsxulQyIykn0pB7dWFAseOkcoanRrPvMPs798DWv7xtTmELmzhJmhyfpqWpGrdew5U/vY7C206sL6QLtp2vZ+Md3LTLAJ7uHUaiUJKzJwjZnkRvtuE9uVj+4BX2wPx1naum+1IjGoCOhNBO1QYtSraLaXTApiRJqg5ak8mw2ffluzv/49UUFy1N9o+gC/Dj13RfZ+TePIDpdqPVaMretxhgZhG3WQvPhqyv+diEp0XTedK8uMNE1hDEiyCPXNj8+w9WnjpNQmknJR7fhcrjoqWpGEuUCTb8QE9efO03imiw57edcPR1n67DNmvF3d8eNLUrDaXeQvqmQ9tO1y+oH1750jpCkKPk7zJkJTY5e8TsAhGfG03q8Gr9QExFZCYQkR8lqNROzt83x7r7URGhKFO2na4lbnS7no0/Pc+XJo8StTifcvcEHxYbhsjuJzElkomuYwrvXE5mdQPORq8yNTLnzTVOXVI+4mc7zdWz6yj3ceOkskiihNRoovLsS//AgRpp75c6B929CQKDmxTNecnShqTHEF6cTGBdG3Op0RIcLm9mKUqWUo8SnbpCxfTU6owG9SVZq0Qf6Y5kxMzMwQURGPLWvnGfwRocnOKI1Gsg7sJYNXzwoq3bdYoSnbS7EFBWM6HB50qfC0mJvq8nvcrgYbx+g/o2L2OetZO8pY8/ejyMg4LQ7cNkd5N9ZQefFBkZb+lFq1SSVZ+O0yX0dFupRui82EpwYQdnHd6IL8GO0pY/2zmGMEbLKytrH9nDiW895csFTN+Rz+j9fXva6+qvbSKnIkw330SmKH9rCZO8IKZV51L1yjvHOITJ3yKdWt6blNb19hY4ztVQ8fgcjjT3vnIIuSOvptRTcVUFgXDhDDd2MNPcRGBcmny6rlJz41rNs+OO7CIoLR3S4lm0qpjMZyNi6ismeEco+tgOnXW4opNKoCYgO5spTxxm6KbVksK6LhjcuseYTuxhq6KbjTC1F924gqTwb+7wNU0Qwthkz+gB/5idm5HX5s/upf/0iY+0DhCRFsfqhzZz/0etezvV4/gCrH9qKdWZ5R2sBQ5A/tlkzta+cp/yxPYSlx8qdVG/ZU7J2lhAQF4YgCLSfuUHHuTqvOWcIMbHm4zvR+Ovoq24jpiCV3mutXs5CVF4i7afl08+0zYW3rQMAuQu4rxX97yECUHBXJbNDE/iHB6JQKQmOj1jUMbL/ejvGiCDKP7WbqPxkei43UfXro5Q8vI2T33l+kTzg9MA4J7/zHFu//gDzY9OUfWwHk70jHP0nbzmj1uPVpKzPJ2ldDlE5iVQ/dwrL1DxKjRr/0ACq3O2ub0WSJKqfPcX6LxxYMo2j90ozm7963yIDHGCyd4SYghQGb3Rw4tvP4bI7UaiUxK5KJWPbakZb+zwpKlk7iml44+KSx+mi08X5H7zG7v/3KJbpeVQaNZefOOz13KGGbhpev0TpI9sIjAun6ldHvY60bHMWal44Q2BcGOWf2sPJ775ARFY8aRsLuPrUca8FxRBkpOLzd1D88FbqXjnvJZcYmZNI3h3rOPOfL5O5s5iGNy4taQRKokjVfx9hy5/eR/UzJ8m/cx1nvvcK5vEZTFEhxJdk0Hz06pKFTZIocuVXR9j8p/fReb5uUbdGkJ2jrF0ldJy5QcFdlZz8txcWGRBzI1Oc+d7LbPzju+XmEy5Z1xzkxh2SS6TmhTNe49jwxiXCM2Ip+9jORdGC1pM15O0v59ItLZXVOo2nIHElLNPzzI/PLjqBsM6YOflvL7D5q/cyVNflWSiNkUGYooM5/e8vLXqvlqPXKLxnA6f/86UlO5yFpERhDA/EYbGjNcrOV0JZFhd++qbX79Xw+iVCUqJY84ldpG0u8hjKY20DXHvqOKvu2+jpiJe0NpvYVemc/d4rXsoIgkJB+pYiyh/bw/kfve71/RwWGy67c0ld+Es/f4vyT+1GF+BP1wXZ+S3+yFamB8ao+pV3PrPTaic4MYKT333RK9LtcKctyM14dnPsX57x+ny1VoPL7iRn3xrmx6a5+tRxL4diy9fuXzGSqjMZZGm79qWlBR1WOyqdFpdDnitD9V3kH1gnKxu9dhG/EBOCSknLsWqPYTZY2ynnVa/PIzQ1GpVGjWVqjv7aTgJjwzj1by+w9x8/sUgL+lYaD12WC3jz5YY0pqjgRVH3BTR+OiKz4gmOD6f+jYvUvnzekyubUJ7Nhi/dtaiW42bkLsThrLp/E22nbrgj0IGs+fguJEnCPm/1kmj0Cw0gfXMhs8OTROYk4B8WgMag8xi0t2vCZpmaR3SJ9F1rQ2vUU/n5O6h77YKXQQVgig6h7NEdnjqA/IMVGCOCqH/jkkc1wy/EROqmQgKiQ/ALDWD3330Mu9nKlV8fo+j+jUQXJNNw6DJDdV1s+fr9XPjpm4sat9hmzVz51VFWPbCZHX/+EZqPXsMyNefpuioIAjUvniVvX7nnNYJCQHS9i5MJp8t9Omyh+umTsiTi2DRtp24QmhpD9p5SHGabxxDtr24jIDqENZ/czbkfvOpJi5noGqbm+TNE5SV5RYRVWjXrPref7X/+EK0na5jsHWF+fPa2efJdlxqIW53GRPeI7Aw4nBz+uycBeT4Fx4cv2mcXsJttVP3qCAV3refs91/BPDFLQHQI5olZKr9wgNZj1Vz5tXeAxy80gA1fvJOA2DCcdgeT3cNE5iQu2cUxe08Z0XlJNB6qQhRFMncU03ulRVYksTsIToggY+sqIrMTqHnuHQ180eni4s8OyXnml5uIzEmk/dQNmt6+4jUnA+PkrsUtJ64TV5xO7v5yDMFGjn/rOc/6odZpKP34TgKjQ+i6UE9UbtKi+qJbSVmfz3W3w9L0VhWZO0swhgfitDsZcZ/MGyODiMpPRmvU037qhlegbgHz+Axn/+tVtn79fllv/EaH114auzoNpUpJQFQI0/1jhKXGLBllvxVTtHdh8IfBh2v+/56iUCvRGHRYpuaILkiRj79+8uaSxzazw5Nce/oE1ul5brx4lvjV6TQfvrpki3CQowi1r5wnZ98aRJe4bESr/fQNJjqH6LveTtF9G3GYrcStTltR6xTkXLW50WkCYkKX/OylUOs0ZGxbzYnvPCfrzLoXENHpoudyM6f/4yUK7lqPPsgfpVpFaFrsksVqC+gC/LCb7Ux0D1P32oUlDXVJFLn8xBFZxrBz6Yr9qd5ROs/Vkba5iKwdJZz53iuLNl3z5CxH/u5JAuPCqPzCAbZ980HWfXYf2//sIaLzkjj3w9eYGRzHFBlM7wqRX0mU6DxXL8uaKRX4hZroOFtH6sZConIT6b1ym9eerSOpPGfJv6s0avxCAxCUKjrP1S+7mUiiRM0LZxBFkbC0GJQqBQExoWj99Vz46ZtLjuNIcx8Xf/4Whfes93q8v7oN64yZ0ke3y1q9N43XUnPjVoyRwZgnl16cnTYHXRcaSCzP9jyWUplH24mljbDJnhHaTtWw8ct3E12YIncBRE6HydxRTNG9G7nwkzfpPFtLxrZVpLnz/5ZylsbbB7nwkzdJ31J0s5CQfKSsUeMXYkJr1JO6sZDzP3ptkSzZQjHS7NAkiWsWp8Zo/HSolkjfEQQBjZ+eia4h/MMDMUWHoPHX03zk2qLnpm0p4sZLZ5dtfDHZM8Joaz/R+clej8eVpDM3MkVwfARnvvfyotOL6mdOsOZTuz2O2c1o/fWs/fReal86t+RnguyseimfSCC5RIYauhlq6Kb9TC3tp24sUuS4/twpOX1EoeDYvzzD+R+/QURGHG0nr7t1yF1Lyr/dzFhbP4JCICAmlInuIco+ttNTeH0zGoOWdZ/dh91i5/i3n3O3qpaNDafNQfvJGi7+7E3KPrbzHa3jWwhzN8Zy2OwkVeQQnhGHQqWgr6adqb5Rzv7Xq1730vzYNNXPnsJpc9Dw+iVOffdFjvzDUxz9x9/IDZtuYwzoA/08Db7yD1TQ8MalRcY3yM3Yzv/4dVY9uJnkyjzUei3nfvCal2Td/PgMNc+fpvdKCxq9lr7qViRRTl3T+evl36qui/CMWKb7RpftmghQ9+p5RJcoF2qXZpJcmcf5H7/BZO8I9lkLLocT/7AAAI/hsyICBMSGMXdTekzjm5dJdHciHWvr58x/vkxIYiQxhSme50wPjHPjpbNk7y7zeruB2g53yuE7nRqdNgenvvsC1jkzfiEm8vaV47QvvZfejHVa1tqPyklArdNQ/cxJz98SSjPpWkK//WZmhyZRqlXoA/1oP31D3nN2l9J5tnbJ1urzY9Nce/oEeQfWotFrqX/9Ek2Hr7L2sT0oNe/ERTO3F2MI8ufYPz/DZO8IqRsLOPmd52l44xKzw5NYJufov94uF0TaneTduc7rc0Sni96qZrL3lskpN29eXuQQLvTZSFqTzbWnjlP7ynmGGro964dKq6byCwfou9rCG3/+C2pfPs+Nl85RdN8mFMvIdsYUphIQE+opxp3sGSEoPpzeqy1cf/YkmTuK2fL1+yn/5G7UOg2SU6T91I1lx9c+b6XnSguCQoFtxuIpVgZI21hI1X8fJnZVKqkbCmg6fIWZwXFCU1c+KUtZn48kfbidMH/nDXBBEHYKgtAsCEKbIAhf/7CvB2RDte71iwQlRBIYG0rf1dYVc6bG2gaQREmWIctOoP/6yq1cB2s7CUmKouXY4s37ZlpPXCcsNQbr9DymKHnDN08tX6izgGVqDo2fbtHjSrVqycK8hDVZdF1oWNYbts1aaDp8lZT1+RiCjcwOTawo/5NSmUfzkSuEpsSsaKhLokjbqRoS1mQv+5yuS00klGbQeuL6sk6NJElyNMbuYKC2g+pnTnLsn5/m2m9OYB6fQRfoz9zY9IrKNABj7bJai9wkI4Thph5MUUFYpuff3Wvdnf1uJaYwheYjV4nOS/TkuS3HRNcQSBLJlXmYp+aJK05ndmhi2WgfyBJR+kB/T+7cAjUvnGHgRielH9vB5q/ey6av3EPO3nJiClNXNCrUBq08Du3LS5kN1HZ6LZAB0aHLRl5BLg689PO3KLp3Izv+8mGPo2Q32zjx7eewTM3RdbGR8Mw45idmli1WBFntwzozT1xxhtfjI009ZO9dQ+6+ctrP1K7YGa/l2DWS1uV6PaYzGRBdLjZ84U5y95UTmhJNSEoUeQfWsf0vPsLsyATBCRFEZieSXJFL+6mlHY6QpKhFBc230nm+nviSd65fazSQUJaFX3ggN14+t2Tu7kTXMNXPnGTjl++i5JHtxBSmEF2QzKoHNrH1mw9Q//rFRbmrCwQnRcpRZI33oanaT3fbOWmemMU+Z5WLQsuzKH10B9aZ+XdSThS3j0IplEokSaLzQj0B0aHoTAY2feVuj6xldH4yhfdsYOOX78Y2Z+HGi2eWVbaZHZqk/3r7ot8fZEckODHSU9hV+9I5al8+R9uJGuKLMzzNVpbCL8RET5X3yeFgXScxhakrfrfkyjy6LzWhMWgJiAnxNNxaivmxGWaHJkjfumrFa+k8X48xMoiOs3XoTH4o3K3rF7Tso/OT6alauSjXPm/FPDlL37VWLj9xmLG2frJ3l2KZnCMwNhQJ2VkEWfUiviRjWadG/swUxtr7vSK8DosN8/gM/u4GLJIon8Kmu993geGGbgLjwlDpbnJuJTntyi80wPuDJLjx4jlUGjWXfvE2OuPtax+MkUGEJEdhig6l81y9dwpEsHFZhZubmR2eRB9kZKixG42/3iOJtxxD9d0o1SrMk3M4rXZ6LjfRfbmJLV+7n4K71xO3Op3E8myuPnUcSZLI3l3G1SePLXlKCrJaU1hqDFqj3uvxsfYB4oszqHpieeUgy+QcY619ROYmEpYa41VQnLmjmO7LTV6n4kP1XQzVdbLhSweJzE7wBDMMQUbyDqwjbXMhtlkz+QffcQgkl0jjoSomuoa58JM3OfXdF1Fq1Yw09TA9OH7bvPLBG504bXZGWnqJKZCDDzqTAZfDydzoDF0XGojOT2awtoumt69QdO9G9IFLi3zn7Ct32wO+CPj/GEEQlMD3gV1ANvCAIAjLW2MfEIIge/NqvQaVVu1p67oSk93DGMODEAThtkeWkiSBwLLqAwvMDk+iMxnoOFuHQqVEoVTgF7w4anQrhhDTkkWJ8SUZSzoHccXpS+aN3kz/9TaichI9ua8rEZ4Vz2TvqKxBehudzvH2QQKig5f9u6zkol4yCuH1Ph2DGIJNtJ28gXli1sv4klwuFMrbH2kpVEpEUUSpUsnNDtxNh7RLODNLv3bxd43OT8ZpdzA7LEdYbm74sByiS2RudIqJziH8QwOW7ap6M8ONPYQkRS56vO9aKye/87ysPa8QOPbPT9Nd1UT5p3Z7ItG3fo91n9lH0+HlZdxAXoxvPv57N/NibmQKJInj//osR/7hKY7/67N0nKn1bOiSKDHdPy43Z7kNfdfbCUvzjti5HE4EQSAkKWrZroYLWGfMIAhejkj61lW0Hq/m6D89zczwBLkH1lLykW3El2Zy+Rdvc/kXhznxneeZ6BoiPD12yeY0SrXyXelrW6bnPU5yaEo0m//kHm68eBa/YOOSLasXGG8f5OR3X8AUGUTqxkJiClMZrO3EvEILaJVWTcFdldjmrV7yp/7hgQjwruakw2qn9cR1cveuYeBGu6f7HchRugUt9OWIKUpFUCgwRQQz1TfKZN8YVU8coetSIwHRoQTFhzPS3MuRf3gK/9CAJSPIN9N5oZ644nSvxxak4gSVkswdxcz0j3tSpIKTI5nsHloyBWoBSZIWOW3tp2+QuX31snJnAdEhJJZnk7I+j6L7NjK+Qp3DAoN1XTit9hVbg4Ocyx6RGc/M4DgZ2+Uc5oVUM6Va/e7yZC2yEhbA9edOMzM4QVxJBmmbC1GpVfgFm0iuzPN0mlzzyd2e599McGIEOXvX0HhocZ2Lw2r3eo1lag6nzYkh2Oj1vOn+MfxuOfUQFIol94jRFjnXen58BqVaueh1t5JQlkX/9XZMkUFM3XL/OG2OJQNStyI3dnGABE1vXWaqd/S2gZfO8/VehmfP5WaO/sNTjHcOkrAmi+7Lje66AD1ao/62e37nhQYSSr27OypUShxWO7MjS/d0WKC/pp2IzDgEheBJbVMoFUTnJ8tOyS20nbrB1d+cILogmd1/+yg7/uphSh7ZxlTfGKf//UWaj1wjKjcJkAvNBaXCS3XMabWjUCjorW69bXMgQN5bNWomuoYxBBsxRgah1ms9J8Itx6rluSBJzAxOcO2ZE1R+/gA5e9dgjAySe67kJ1P5hQMklGWi9dcvOVc/SH6nDXCgFGiTJKlDkiQ78DRwx4d8TSCBf2gAU70jGIJN7yofacF4s86a8QtdebHwRCrfpfNmm7XgcjiIyEpwt5peHq3RgCHQf0lVg/Stq+g4630jKjUqDEFGjxb0cixUeJvHZ/ALC/Q6NrwVQRBw2Rwo3+24uVYw0t2S6e+maltwK9fcimVqHn2AH2r9ypKFMQUpjDT3EpWbiC7Qn4rH7yDvjnUoVMrbyh3GFKUy0uQdfYwpTCF7bxmCQsF4xyDzY9MExoat+D4qrRqlWoV/aICsmTs9d9tNAOQcTqVm6cUoMjsBv5AAJjoGkUSJyMx4RJeLTX9yL/FlmehMBvSBfiStzWHzV+/FL9R0WwMoPCOWyd53otRyVCNlhVfILZxFl7hilE10OJdUvln8RGmR6kBYeixNh69gdhe63g5JlJ0IQaEgY/tqjOFBdF1s9KRe9V1pdSuPSJ7Nz2m1c+nnbyGJknc0z43LIRdO3u7e9gsxoTMZ2PqNB0iuzMU2b2Oia3jFqP0CTousjKD113HlV0cZrOui6ldHKHl4G3kH1nlSVBRKBXGr09n45btpO3UDpVr1jiSkAKvu38hEzwiBcSvPScEtfTbcKDeiurXYsvVkzaKj85tRqpVk7yplZnCcvupW6l+/iNNiwzI1x2hLHw1vXqL+9Yse1SNJlG77+1mn5zFFBhNXnEHsqlRKH9nOxi/dBUoFJ/7lGS785E0me0cIjJXTrTQGHZYVFD4WxutWp9QyOUf1sydZ/0d3klyR67nHNH46MratovTRHZz+95c4/8PXmR+fXdKpvRVJlN6V8WyZnkdj0MkNw+LDvQI7c2NTBN3mdwMwRQZ5NVFrO1nDkb97ktmhSVQ6Ded//AZB8eFs+dP7UGpUzI1Os/0vPkLRvRuIKUoloSyTdZ/dR96BdZz7watLqqSYIoOxTHo7gJbpxaewCpXSay1TqOQmNHPLNAtboPGtKkof3b6ssZW5o5jJ7mFajl1Dcoloblmr+6+3LzJqb0Wt02CMCGJmUI6US6L0rhxT6/QcplucT9El0ne1len+MSa65PQifaC/l7b6cswMjC86EYgvTr9tihfI4hGCQsFk7whh6bI6iF9YADODE8sqtMwMjHPtNye4/MvDjDT1cuq7L9J7pRnRJTLj7jYMkLa5iJ4rzWz68t0U3ruB2FWpxJdkoFAqmOgclhs13aYgMiIrDqVKhX94IFd+fZQ1n9iNLtAfv7B3vu9oS59H9Wq8fZCj//Q0c6PT5OwtZ9X9mwhLi6Hp8FVcdgezQ5O43kV60vvJ77oBHgPcbLX0uR/7UJEkCf+wAJw2J20na0hau3JQXqFUEJwUyXT/GJ3n6klZn7/i89M2F+Gyywb1SoQkRzEzNIExIgiFSkX1MyfQGQ2kb1215PMFhYKyj+1gZmjCswipdBrSNhdS8fgdOKw2Sh/ZRmJ5NrGr08g/WMGWP70P+7z1toL2So2cviJJEj1VTaRvWfoaQD6y1vjpMAQblzRSbiZudTojzcvrAkdmJ2KdMRMUF77i+2j8dIhOlyen8Va6LjYsOha9Ga3RQHRBMpIkF+UEJ0YgukSO/fPTdJytI2Pb8t9Xa9STuCaLlA15rHpgMwV3r2frNx4gKjeR2aFJ2k5cB0mWG0vdsPLcSCzPRlAI9FQ1Y5+30ne1jejbGLYgF5xm7ighrjjDE4k2BMvHidl7ynBYrIy1DbD5q/dgnTGj1mpRqpRk7Shh6zceYM0nd6MLMHD2+6/QcbaO5MrcZT9LUCjI3FlKcFIUccXpxJdkEBQfQcaO4hUds6ydpYy29q1oqHddbrqtIQ8QXZDsdaTqHx6IWq9ldnACtV5NeEbciq9X67Xo3GoR2775AGqtbIzcbPybooMZbuxmfnRmUd51y7Fq4kuW3tRHW/qIzE5c8fOTK3JpOnyVk995nmtPn0SpUmCft6BUK28b1QmMC0Nt0NJ+utZj0AREh9B7tYXQ1GjKH9vDtm8+yOY/vY/AuDDO//gNtH46WbVGAmNEEJWfP4DW38BwQw8ZK9wXAFH5SYy09CEIwpKqdm3HrxOcEMHqh7Ys+v11AX5s+NJd9FxtpvnINXL2rgHkQsFbI6QLCArhtqcpC9KIfsFGktbl4rDZqXn5LKNNvR7jtut8A8kVeYB84nG7KOpIcy9ReUmLHh9rG+DUv7+Ixk/Ptm8+yL5/+iRbvnYfCrWKE995nrnRaUJSo4kuSCY4cfEp1K1EZMa9q9iLX4gJ66yZoLgwzv3wNSZ7hj2GVdeFRlmicQVCU6OZGZpcdCIjSbIDoFTJkeWrTx7j7A9e8xSothy9ykTPCEFx4eTsK6fu1fOc+u6LS+qKhyRFMT8+syiA43fLKaxSrSIgOsSrM2/SuhwGbnQseWIclBDBrFuKcLixh47zDez4y4+QsCYLlVaNQqkgNDWG8sf2YIoK4fpzp4nOS0apUS0al6m+UdQ6DaEr5LjnH6yQhQDcE3x2eJLgxIjbOtJBcRHYzVaC4hfvTy670xP0cdmdixyDpVAvROHdGIKMROUnoTP53fZaQpOjmR4YZ7C2k4jMODQGrXzPvqtghLSooFHrp8Nhs5O6IR+/EBP1r1zgyN8/xXBjD+lbVhGSHIXoLo4ebuwhbnXasu+vVCtJWZ9P79UmSh/ZztzoNBd/+iapG/LR6LUEu09v20/f8NprRaeL7kuNXPzpm5z7wWvUvHCG+NVpmCfm5BReXxHm/4qlRm/RbBEE4TFBEK4IgnBldHTlI5z3Ao2/nrjiDAJjQ+k4cwNDsMmT47YUKRvymegaQnS66L/eTkhSJNEFyUs+NyI7gbC0GCZ7Rsm7Y+3yERNBlveRHYAcRlv70QX48/bf/ZrYolTWfHK3p5hOEASichPZ+McHGWnpY6J7mIrH72DbNx9kwx/dSfqWIq786ijH/+VZal44g8agxT80gPGOQY78w29oPXGd1E2FK45JQlkWCqWSpHU5WKbmiC/LIHNH8aLTgYDoEExRwaRvWUX35SbSNy//vvpAP+JWpzG2TK6xUq0ie3cprSeqb3t9yZV5qDSqZR2DtpM3CIoPJ2tnyaJrNkYGUfG5/fTXdJC+uYgLP32DoNgw6l+7AMiLQkB0KDl71yx+bUQQFZ+7gyu/OspoSx8qrYrBug4a3rxEQEwYQfHhnuYCo639aPx0XsWLNxOcGEn2rlJElwvrrIXo/GQicxMJTohAH7S48G6BhaYa1546RkBMCJv/9D62ffNBih/eylTfKAM3OjBFyY0pVDoNl37xNqf/8yWO/+uznPj2cxz++ydlOchV6cQUpGCenCVlfQExRYtzXxUqJWs+uUuOqAgQnZeEPtCfthPXqX35HBWf27/IsFJp1ax6YBNKrYobL5yRf6tlHLPxtgGMEUHLOlILY67117+jHBFqYt1n9zHdN8rWbz7IePsgWTuLV4xGpm0uZKS1n8G6Lo7+09PUvXZhUXQuKjcJjUFH85Erizb13qstxBQkL/m7tByvJnd/OVp//aK/AW45rzC6LzXitDlIqcxlqL6b4MQI7GYbCUsUh95M5o5ixjsGaT/tLnoSZKe+/0YHgkLg+L884ykirH35HIExoWTtLCF2VRo7/+YRSh7ZTmBsGNOD46RuKsButZO7v3zJzzJGBJGzt5yWI9eILUpdUg88oSwTy+QcugADu/7mEdZ9dh+rHtjMpq/czZav3cdU3xjmiTny7lhLaEo0JR/dRv/19mUNyMHaziXn3s2krM+Xv78gIDpdXH/2FLl719B+5p1GTubJWab6RsndX85k9zCmqJAVT7LaTtVQcFflkidltlkLvVebUeu19NW0I4oiKZV57Pyrh9n5Vw+TUJLBcH03Gj8doSnLF49pjXKOutLdoG0lEsoysc1ZmOobxTI5R9vJGrJ3l3lO+kZa+ii4q3LJ1xqCjKx+cDONb11e9Lf40kz0Af7Mjk6RvbfM/f3MtJ+6QeOhy7SfrqX7YiN1r57HabWTurFwyZ1aH+jPqgc2LWrj7h8eiCRKXpH31I359F1r9Rh6yRW5xBen0/jW4pQWgNx9a+i60OD5d/eFBpoPXyVz+2rW/9GdbPrKPSSVZ9N8+AqXf/m27AA+uBnz1DyBsWGEJEV5vd+lX75N4T3rSa7M83JwDcFGSh/dTlReErGr09j1t4+w6U/ukRs0adUrBj9UOg3RBclcf+40qx/asihfeaC2g3h3mtTs8CSGENNtT1ITSjM9aaKBcWFs/MrdWKbkGqTInMRlXyf3J8ik53ITkihR+8p5T41NQHTIbU9mwjPjmLipGBggdVMhSq0aU3SIHJxwB+BGmntR67XudDs7yetyaXyrivStqzwOotc4adVUPH4HHadrichMQJQktn3jAfzDA7n4kze5+tRxSj66Da3RwGTPCObJOYru27ikwknqxgL8wwI5+1+vEJWbuGy/iw8K4d14N/9XEQShHPhrSZJ2uP/9DQBJkv5xudcUFxdLV66snJ/6v8VmsSI5RKb6Rhmq72K4qZfSR3dw7anjXt0SBYWC1A35ZO0qxW62curfX8QyOYfGoKXsE7twWu10nK3DPDGLPtCfpHU56EwGLv70EFqTgXWf3cfM4ARVv3zbK4Kg1mkouHu93JjE7pCLY1QqRJeLq08dZ7S1j/CMOFLX58vqGgoBjb+e7ouNNL5V5cktNAQZyd5bRmBcGJJL5OS/vbBkDmRyRS65+8s5/Z8vL5mjJksuHUSSRGxzFvSB/jS+VUX2rjJcDicjzb04bQ4CY8Nw2R3UvXaB7F2ljHUMEZ4ew1jbAC3Hq72OwQJiQin56DY6L9STVJ5D3WsXGK7v9njrISlR5B+ooP3MDXouN7Pus/sYqu/yaIXeTGR2AqWPbsc6Z0Hnb+D8j99Y1BIZwD8iiA1fvBOFQsGoW189IDoElU4NCgUjjT0M1HSQf7ACFAJOi42eqhYcVhuhqdFE5ycjIDDS3It11kJATAiSS6T1xHUicxKJLUqVPXJJYrCui85zdeiDjKRvLsRutmGZnMMQYiQoPoK50Sma3r7C3MgUWqOBtE0FhKbGIAhQ/dxpcveuYbS1D7VBiz7QH5VGzZnvv7KoW54xMoi1n9pD3esXyNmzhsG6LnqqmnGYbQTEhpKxbRX2eRuXn3gbp9VBdH4yBXevp/Gty/RWNeNyuPALDSBz+2piV6chiRLmiVkmekYIiApGpdXQeb4e+7yFwNhwInMSsEzOMjsyRVBcOFp/HRd//pZn3oRnxpG1sxSXw4l5fAatyUBgbBhOmx2dyY/ui43MT84QvzqDy0+87VX4q9JpyNm7Bv+wAExRIZz+jxcXFQb7hwWw4UsH6bzQgHl8Vo46xkcwWN/FeMcgfddaSa7MI3VjAVO9o1z82aFFx6/xZZlk7ShhrL2fq08eXzRPAEoe2UZkVgKjLf1MdA+RsqGAy0+87VWYGpIUxaoHNlHzwhmv4kdDsJHij2zFLzSA5sNX6L7cJDePCjKSsj6P8Mx4+Th/xkzsqjSK7t2A0+ZAqVHhtDpQadXuiOfiQtS0zYVEZMZ75BYFhYLVD27CaXMQkRmPoFIwcL2Dqf5RWZO8LAuFUoE2wMBQXRf9NzpYde8GlCoVCIL7npa17i1TczQdvsJ0/xhqvZb4kgzCUmO4/Mu3mR+fYftffIRrT5/wpCdpDFpSNhSQtC4HlUaFZXqeutcuYp81ozUZME/Okbwuh6i8JMwTc9S+fJaxtgG2fuMBdEa54LX6udMM3lK0qA/0p+Lx/Zz9/qty7cIthCRFUfaJnTitdvqutdJ0+Cr5BysIS4tlbnSKiz895HGmBEGg4J71BCdEMNEzgt5k4OLPDi2Z5pS9p4yo3CS0/jquP3eawdpOJElCqVYSW5xO3v519F1r4fpzsjSbWqdh/ZcOMt0/xtzIFJapeSZ7Ryj72E6qnji8qEZAZzKw4Ut3MTcyiVKrBgnOfO+VJVPMsnaW4BcaQEhyFHMjk/iFBmA32zAE+TM3NsPVXx9lfmKG/DsrCEmOouNMLRPdw6g0ahLLs4nKTcQ2Z8EyOUfnhQaPDGHG9mL0AX5IoohCrZIdiyvNNL3tvacKgkD+wQpMkcFM9Y8RlhZD+5laJruHUapVxJVkEJkVz9WnjntJyinVKtZ9bh9Nb11hpLkXhUpJ2uZCUtcX0HO1WW5LnpeESqeh42ytrLF+808hQM6eNYQkRyMo4PyP3/Aqxo0pTCHvjnWMdw0x3NiDSqMiviwT/5AAqp87hc5oILkiF7VeS8Ohy/RcbvLc/8bIIEoe3oZfiAn7vBWX0yUr65y6Qe+1FtQ6LQqlkoJ7KjFFBjNY20F0fgrVz5xcVGCuNmjZ8MWDqHUaOSXC4SB7VylDDT10X2rE5XASnBhJzr41XPzJIcY7B0muzCMgKvidtu23EJwYSdnHdzBY20lgXLicHhpsouGNCwgKJelbijj/w9cXzSuFSknF5/Yx0txL09vvqKpF5iZScLASl9NFy9Gr9FxeuthapVWz+av3eskshyRFUf7Ybg7/3ZOLVLvkFJQ0qp85yUhTL5u+cjfnfvAaLoeT4o9sRalW0XetFYfNTnBCJHHuFJr2kzWIkkh8aSaB0SFyyowg56svpK+0Hq+m92oLJQ9vQxfgR8/lJuZGp9EF+BFfnM5E9wjXnzuFIAjs+ttHvBS+3k8EQbgqSVLxosd/xw1wFdACbAH6gSrgQUmSFlcMuPkgDHCA+clZFIKcgNx85CrDjT1k7SrFEOTPZPcwKq2GiOwE5NVD3sgUKiV919rovtiAy+4kriSD+JIMbHMWJjqH6LnczHjXIFG5Sax+cDMd5+rR+uuJzk9mZmCcmcFxtEYDATGhDDd2E5wYiTEyGEEBkkvOebWbrTitDnquNLs33TiC4sJpfLsKfYAf8aVZcj6wWiV7+oJ8pIso4bQ5qH/9In3VbYhOFwHRIaRvW01UTgIup4hCKdB1oZHW49VYZ8xoDFqSK/NIrsxjtKUPQ4gJY3ggCNB9sYn+mnbWfWYfU32j9F5tZbixG8vUHBGZ8WTuLEahVCIIApapOQKiQ5joGUFyiQQlRCCJEn3XWgCB5Mo8OZdLchdqqFVMdg/TfOQqkz0jGIKMZO0qISQlGtusmY6zdfJN6W5uYIwMlgvwFAIuh8st39VGy7FrzI9OozXqSVmf7yk2khBxWByoNGrUejVKlRLrjBmlRu0+Zpc8ucFKtQrbrJmhxh50Jj2hydFuTWINdrMNyX29DqsdrTsNRqFSMtjQTefZOjl/My6MrN2lsoxd5yC9V1uJzkskNDUW0SXn7Qnu/NOpvlH83XUHgkJB75UWJrqGSFmfj19YAJM9I/RXtyEIgiyRadBy9TfHmRkYJyAmlHWf24eA3BV6tLmX5qPXPPUAWqOBovs2uqUWBVw2uWhRFOW8SUGpcC+GgmwUSHKL+PGuYZAklColQfER2OYsmKJDsEzP0XellcTybGaGJug4U4vDYiMgJpTM7auZH5+h9pULTPWMICgVxJdmUHBXJS67E9HpQpLkgq250Sl0Jj9MkUH0VbfRf72dlPV5RGQlMNU3St9VeZ7ElaTjF2Kit6oZQ1gg4akxOKw2rv3mBLZ5K6bIYFIq83A5ne7rNKP109NzpZmp3jG0/jqSK/JQadU47Hame8dQG7Q0H7nqyd8Pz4gld/9a9IFyznNoajQ6k4HJ3lG0/np6q5ppP1PrluUTSKnMJ31rES6ni9nhSTQGHTqTAaVaRfuZWgxBRkJTotH4ycfBC/eK2qAluSLXPcfkFtyG0ADUOo3cflqpYKxjgLYTNdjmLBgjgsjcUSyfNpyqwTI5T0B0CDGFKTisdjR+OiZ7hjEEGvGPCJSLYhUKBKWA5JKYGZ5AH+CPQqlEoVHiMNuwz1nwDw1EEsA6M4/OaGBudBrz5CxOi43+mg6G6rowBBtZ88nd6AP95N/NbbwqNSocZhsao96jkqLSqpnsGcE+b8UQZERQCDS+VcVwYw/+4YEU3r1e1k622BBUCjQGHT1uTWTz+AyCQkFsUQr5d1WiUChoPlpN57k6HBYb+kB/0rcWkVCaxVBDFyNNvfiHBxGdn0RPVQtNb1dR/qndskF6to6J7mHUWg3J6/PwDwtgpKmXwPgIBOQI4VBdF5IkEZIcRfbuUgJjw+i/0cFM/zipG/NRG7Tu+1kFSChUChwWuZlW98VGRJdIeEYcoSlRiC6RyZ4RXA4nYSnRqPQa5kanPc8LS4shMC6Mye5hIrISGG7sxi80AK3RQN2r52VjX5QITowkY9sqjBFBaPz1uBxOrvzqKGNt/Sg1alx2J1m7iklam4tleg6H2Y5fqAm1XuP5XebHZ2g9Xo3L7iS2OJ2IzHgkl9z+G4WAQlDgsDlQKOUCSEmUkFwut1M7gzEimIQ1mYhOUT7hl0Cp04Ak4TBbUWjUKBQC452DNLxxmen+Mblp0apUcveWIygEuWusWkl4eiw9Vc10nm/AFBFEWHoMsavSMI/PoA8xIblEui82Mjc6hX9YINEFKQzVdVL36gXZ6bljLeMdgww1dKPSqElal4M+wA+FWi6UF10uJHDXJ0iEpkSj1msQRUlWjpHk9CNZ51zEPDWHWqdBH2hApdHQX91G16UmRIeTkJRo0rcU4XAXyBqCTYCE0+rAYbXTW9WM0+EkMiuekORoJnqHCY6PkNd/sw3R5UIfZMQ6Y0ahFFBpNVimZtH6G6h77Ty9VS1yQyYBGt647JGuVKiUxJdkyN1Q37iE3WJDEKDsE7tQKpVIooTdYkWpUSOJIjODE3Seq8dldxCaGiN3HxUUCIKsojXU0I1SpSShLAudyeAeKxcXf/E2I43e6Z5qvZa1j+2h83w9PVXNKDUqEsuzydlTRteFBhrfuuJJYTKEmMjbX054Zhy2WQtKtYqGNy8xOzLF6ge3yMbzlWZ0Af5E5SYSGBdGRGY8ToeDjjN1SO7fxOV0ERgTiikyhL6aNvxDTUTnp6BQK7FOmzFPzKDSaPALNdF7rQX7nAX7vI3+mnbs81ZUOg2Vn7+DgJhQNLep63qv+L00wAEEQdgNfBdQAj+XJOnvV3r+B2WA22127LMWhhq6iCmQj0MnuoYQRdGjXSooFJ4iAEEpoBCUCEoBu9kOyAYLCgWIInOj07gcTlkpRalAoVSg1KgQXaK8kEgiCoVcpCK5RCQJ1H5aRIcTpVp+nqAQkJwiEnhyJCVRZLSlj9mRKfxCTISlxSAole6Od86bVFkEFGoFLptbccJdbexyuFBpVciWOigUCq+cPK9cTEFCdIjyQi/IURIEAaVGidPmBOmdlCyFUi5KRZIQlAqPYSoIcmW+SqtBUMqOgsvpQkCuVpckSVYhkWSHQXYmlAhKJZI7kiEI8k28YKQ67bJSioCEJAhYpmYxBPh7PGtJWjAqpXdSxhQKeWw1KkSniNPuQKPXehwpQVCAAKLDhSjJC4cgKBBF+XdQKAScNif2eQu2OSsqjQpdkL9cDS5KON0NXRaO/iRJwmmxozUZPEaX6HDhcjpRKJQIKiXuvQ5EERQCguzbeQrzBEFAoVaiUAiIooTkEhnvGsIxbyMgJsTT+lpAQKEEh82Jfc7C7MgUOqPBc1oiCAKiJHnGU6GUP3/BKFIo5N9LdLoLJgXkC0FCdIqodBoklwuX0yXn/AoCCqWA0+qUI2tKBQr3piQIAi6HE5Veg+gUMY9Pozbo0AX6ITlciKKIfd7KZM8oUdny8SSS3DXSZXN47hUEeX46LXZEUUStUcvFTtfbUKqUKFQqHBYbGn894emx8usUcoc+tVYjS12Nz9B/vR21Vk1CaSaSIGu0LzQXkdxfU76vnSjc8xNBcKsjSCjUSiSXJBdwKt4p2hMdLqxzFlQaFWq9FrVBg+gSEd2/nSRJKJQKVFq127kRsFvsWCZmMM/MExAZhM7kh+h6Z4467S55ToO8lrjvHdlZkhVcXDYnSBISgvt1AnazBbVOI6sn2OSmJFp/vXwf2uXfSKXX4Ji3ucdXXndEhwuFSnbCJrqHsc6YMUUFy/NGAERQauXxUKqVOOZtuJwuOTIb6OdZoxaMAdm4E7HOWFBp1ai0KlRaDQ6LHYVK4YlMqrQanHaHZ5qJooTSbRwuRMhEUZTzaP10SJLs9EriOwXa8meo5M/RqN3rgsMTWVtw8AWlgFKrxmW9qXhLEFDrNbicLlw2B26RKs8aJ7l/X0EpO+WSKOJyK2u4HC7P85QaFS6HC6VKAQgeRSVRdCFI4FpQDnLf6C67AxSCu1hdQEAu4BNUSrfsIHKBuiQ7ww6rHaVGhX3eilqvlfcQtQqFSoHLZkWp1cmNpLRqnFY7kiTn3oqiCCJIoguXQ0StU+Nyr/Fqdz610+ZAoVUhSII8T1wiIHkyT1xO0bNeKpRKnHYHQ/VdBESFojXp5ftHkvcLp92OWic79C67UzZOnS60AQYQBEabe5kfn0GhUmIIMhKeHguCgKCQ5/fcyJRciB4eiFKlQKEUkCTBvVbIJ4mCAFqTwXP/Igho/LQ4bE6U7mJPuaBX9Kytlqk5j+EakZ1IeFoMCrUS25wVkFBpNSjUSpQqFS6n0/19NfLvbXe41zoQXaBUKTy/r8vpBARmh8Zx2hxyLwJ/PZIEosuFQiEgISA5XZgnZ9H461GpVXKbeYecJ95f007joSqUGhVpmwqIW50uF1oHGHDZnDitcl8NpUZFaEq0Z58QXRKiw+mei3LzPNHpcq9T75xuKdTy/mmdtdB5rg6n1U54RhwRWfFIgoDoDoqo9BrZMUMCUUISZanJBXtFkuSIueSS7RAk+fNx2wICchBN4d53F+7hmws0JVF2Zu1mK2qtBsk9D10u+TcTHU5aT9Qw2TNM1s5iNH56ui834TDbCE+PJSInAaVGjeY29WXvJb+3BvhvywdlgAOIDgd2mxPJJRto8hGVgCi6QJINT9EhyouZe6Jp/XXIm6DVfbQoICIhKUCn1SE6ZaPYU5zhcrkjkaDUyhFYl92J0+5AoVKg0qjljV+1dGGWKIrupVteoEWXbBQpFLKR5TTPIbhcCFo9Kq32pg3JicuzAaoQlEr3PaRwOwHyxiIbp073AqdDoVDIi5NbuUShENxFU7dXPFm4IUHebt6NYsA731PexFAoFuWGLYzBUu93O3k8l9Mlh4sRcdmtCKJs8Kj0BgSF0mvhcNqduOxy5Eit19409hKi2+gW3JuxiIRKpZSdJUHhXoTkTeSdTmciSCKCoFixeHE5FozA9wuH1e4+WVAsK8W4YGQhirIholQt251MdDqRRBf2yXFEhx2lwQ9NQBBIwqLc+uVwOpzMzZkRJRGjQQeS/LvIFyPXb8hz0ntcFpxKcUGS0u1svqtxcDiZnzPLhgwQHBLo/d7ux2XnVZ5PsnF++/e/+bXvBkmS549odyA6bIgOB0qNFqXeAMjOjtPmwGmTpeEEhYA+YPn6gRWv7V1IS76XyE01hCXnz+2uZanXulyyY4UkIUkiTvM8ztkZEEAbHIagVHnW1ZnpWZwOJxqtBn/jYu1h0eVCcrlwWuZxWS2oDH6o9H5u51M2ehYaxiiUynd9P4sulzx/3QEHhUqJRq9d9n5YmF/y+uxe8xTySeNS4+ZyuTx/k1xORJeIyyE/ptKql91XlsPldHkioh7nyP0ZCpXSq+5BdMrfC4WAQvnO54iiiGPehoSsJKT6LaXkJEmSHRVhwfZ5d/vPwmslSXrX99vNOO0OJFGSnRAvg9K9pgtyxP3d3DM3r92iy+WVgrqwz74bFtaPhcCEJImy8+M+BpUdbO/xleU2nXJwwO0AKlRywE7+LWWnXFAsXKfsVC8E0W6+NpfT5f6+8h64sA/b561IkuzU3Np7YAH5O4vuAJf8eXIAQn6PhXRZjUErp8u5Vave7W/9XuIzwN18kAb4zSx4db+LLHihPm6Pb6w+GN7rcf5D/N08zuwf2Pf+3/BezJM/xLnm43cH3/x871nOAP9wVcj/gPhdNb7Bt0H/NvjG6oPhvR7nP8Tf7Q/xO/9veS/GzDfuPv4v45ufHxy/u1ahDx8+fPjw4cOHDx+/g/gMcB8+fPjw4cOHDx8+PkB8BrgPHz58+PDhw4cPHx8gPgPchw8fPnz48OHDh48PEJ8B7sOHDx8+fPjw4cPHB4jPAPfhw4cPHz58+PDh4wPEZ4D78OHDhw8fPnz48PEB4jPAffjw4cOHDx8+fPj4APEZ4D58+PDhw4cPHz58fID4DHAfPnz48OHDhw8fPj5AfAa4Dx8+fPjw4cOHDx8fID4D3IcPHz58+PDhw4ePDxCfAe7Dhw8fPnz48OHDxweIIEnSh30NHyiCIIwC3R/Sx4cCYx/SZ/++4RvL9w7fWL63+MbzvcM3lu8dvrF8b/GN53vH7/tYJkiSFHbrg39wBviHiSAIVyRJKv6wr+P3Ad9Yvnf4xvK9xTee7x2+sXzv8I3le4tvPN87/lDH0peC4sOHDx8+fPjw4cPHB4jPAPfhw4cPHz58+PDh4wPEZ4B/sPz4w76A3yN8Y/ne4RvL9xbfeL53+MbyvcM3lu8tvvF87/iDHEtfDrgPHz58+PDhw4cPHx8gvgi4Dx8+fPjw4cOHDx8fID4D/ANAEISdgiA0C4LQJgjC1z/s6/ldQxCELkEQagVBuC4IwhX3Y8GCIBwRBKHV/f9BH/Z1/l9FEISfC4IwIghC3U2PLTt+giB8wz1XmwVB2PHhXPX/TZYZy78WBKHfPT+vC4Kw+6a/+cZyGQRBiBME4YQgCI2CINQLgvBF9+O+ufk/YIXx9M3P3xJBEHSCIFwWBKHGPZZ/437cNzd/S1YYyz/4eelLQXmfEQRBCbQA24A+oAp4QJKkhg/1wn6HEAShCyiWJGnspsf+BZiQJOmf3E5NkCRJX/uwrvH/MoIgrAfmgP+WJCnX/diS4ycIQjbwG6AUiAaOAumSJLk+pMv/P8UyY/nXwJwkSd+65bm+sVwBQRCigChJkq4JgmAErgIHgEfxzc3fmhXG81588/O3QhAEAfCTJGlOEAQ1cBb4InAQ39z8rVhhLHfyBz4vfRHw959SoE2SpA5JkuzA08AdH/I1/T5wB/CE+7+fQN5ofCyBJEmngYlbHl5u/O4AnpYkySZJUifQhjyHfbDsWC6HbyxXQJKkQUmSrrn/exZoBGLwzc3/ESuM53L4xnMZJJk59z/V7v9J+Obmb80KY7kcfzBj6TPA339igN6b/t3Hyouij8VIwGFBEK4KgvCY+7EISZIGQd54gPAP7ep+N1lu/Hzz9X/G5wVBuOFOUVk4lvaN5btEEIREoAi4hG9u/q+5ZTzBNz9/awRBUAqCcB0YAY5IkuSbm/9DlhlL+AOflz4D/P1HWOIxX97Pb8c6SZJWAbuAx91pAD7eH3zz9bfnB0AKUAgMAt92P+4by3eBIAj+wAvAlyRJmlnpqUs85hvPW1hiPH3z83+AJEkuSZIKgVigVBCE3BWe7hvLFVhmLP/g56XPAH//6QPibvp3LDDwIV3L7ySSJA24/38EeAn5OGrYnfO4kPs48uFd4e8ky42fb77+lkiSNOzeYETgJ7xzXOoby9vgzgl9AXhSkqQX3Q/75ub/kKXG0zc//3dIkjQFnETOWfbNzf8FN4+lb176DPAPgiogTRCEJEEQNMD9wKsf8jX9ziAIgp+7oAhBEPyA7UAd8hg+4n7aI8ArH84V/s6y3Pi9CtwvCIJWEIQkIA24/CFc3+8MCxuymzuR5yf4xnJF3MVZPwMaJUn6zk1/8s3N/wHLjadvfv72CIIQJghCoPu/9cBWoAnf3PytWW4sffMSVB/2Bfy+I0mSUxCEzwNvA0rg55Ik1X/Il/W7RATwkry3oAKekiTpLUEQqoBnBUH4BNAD3PMhXuP/aQRB+A2wEQgVBKEP+Cvgn1hi/CRJqhcE4VmgAXACj/8+Vp//T1lmLDcKglCIfEzaBXwafGP5LlgHPAzUuvNDAb6Jb27+T1luPB/wzc/fmijgCbeKmQJ4VpKk1wVBuIBvbv62LDeWv/pDn5c+GUIfPnz48OHDhw8fPj5AfCkoPnz48OHDhw8fPnx8gPgMcB8+fPjw4cOHDx8+PkB8BrgPHz58+PDh4/+3d38hUlZhHMe/P2rTArObKKQLTVBJ0fyzgUa5gpGFkYWZItVS1E1QG3VnBRWV24WBgkGK7UWhoklQIuGFlq6Y/7d1aauLCCop6J9ZmpRPF+cMvs1us6POvFH8PjDs7HnP+5xnZmF59uHMHjMrkQtwMzMzM7MSuQA3MzMzMyuRC3AzswaTtFPSrVVjHZJWl7B2h6TL6pjXJum9Juaxp8HxJkr6LP8v4crYVkmLG7mOmVkZXICbmTXeetKhW0WL83izdQBDFuDNFhGzGhyvD9gCLAOQtABoiYgN5xtTks/CMLN/hQtwM7PG2wzMlzQMQNJoYBSwW9Jrkg5I6pP0XOUGSa2S9kjqkbRP0ghJoyXtknQoP2bluW25y75ZUr+kt5Q8ltfZIWlHdVKS5uX5u4G7C+M35LUP56/j8/iufFhGZV63pMmSZks6kh+HK6fVVq11olaug8x/WNL+/Prf/ocu/vPAPTmn5cCjkqZL+kDSQUnv6+xR4YPGk9QlaUV+fzpr/RDNzJrFBbiZWYNFxPek45Pn5aHFwMZIJ58ti4gZwGRgdi5oLwE2Ao9HxBTScc0nge+AWyJiGnAvsLKwzFRSt/s64FrgxohYCXwDzImIOcWcJA0H1gB3ADcBVxcu9wM3R8RU4FngpTy+FmjP948DhkXEx8BTpBPqrs+xTg7xlgzIdZA5WyKiNb/+T4CHqidExG957Q+BDaQT9FYBCyNiOrAOeLGOeOOAuRHx5BB5m5k1hQtwM7PmKG5DKW4/WSTpEHAYmEgqSscDxyJiP0BEHI+IP4AWYI2kXmBTnluxLyK+iogzwBFg9BD5TAC+iIjP8x8CbxaujQQ2SToKvJrzIq85X1IL8CDQlce7gRW5435FzrWWenKdlDvuvcDSQg5/ExHvAj8Bq0nv2yRgez5+/Wngmjribfq/Hm9tZv8N3v9mZtYc75CK1GnApRFxSNIYUge3NSJ+lNQFDAcExCAxngC+BaaQGianCtd+Lzz/k/p+nw+2BsALwI6IuCtvl9kJqeMsaTtwJ7AImJHHl0vaCtwO7JU0NyL6a6xbT65dwIKI6JHUDrTViHcmPwT0RcTMc4z3a43YZmZN5w64mVkTRMQJUiG7jrPd78tJxd/Pkq4Cbsvj/cAoSa0Aef/3xaTO9LHcOb4PuKiOpX8BBuzJzmuMkTQ2f7+kcG0k8HV+3l5131rS1pf9EfFDzm9sRPRGRCdwgNRdv1AjgGO52760zns+Ba6UNDPn1SKp0uk+n3hmZqVwAW5m1jzrSd3rDQAR0UPaetJHKsy78/hp0h7vVZJ6gO2kzvhq4AFJe0n7luvp3L4ObKv+EGZEnAIeAbbmD2F+Wbj8CvCypG6qivyIOAgcB94oDHdIOppzPQlsqyOvoTwDfER67bW66cXcTgMLgc6cyxGg8t9XzjmemVlZlLYCmpmZDSRpFKmTPyF34s3M7AK5A25mZoOSdD+pi7zMxbeZWeO4A25mZmZmViJ3wM3MzMzMSuQC3MzMzMysRC7AzczMzMxK5ALczMzMzKxELsDNzMzMzErkAtzMzMzMrER/Aci2VzVqFulQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the clusters for the \"price\" and \"availability_365\" variables.\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "ax = sns.scatterplot(x=df_clean_2['availability_365'], y=df_clean_2['price'], hue=kmeans.labels_, s=100)\n",
    "\n",
    "ax.grid(False) \n",
    "plt.xlabel('Vacant days in a Year') \n",
    "plt.ylabel('Price') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "88e5dc10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the clusters for the \"price\" and \"min_nights\" variables.\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "ax = sns.scatterplot(x=df_clean_2['min_nights'], y=df_clean_2['price'], hue=kmeans.labels_, s=100)\n",
    "\n",
    "ax.grid(False) \n",
    "plt.xlabel('Minimum Nights') \n",
    "plt.ylabel('Price') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ac2013e",
   "metadata": {},
   "source": [
    "# 8. Observations based on the clusters\n",
    "\n",
    "#### For total_reviews and price, all three clusters behave similarly in that both variables are positively related. Cluster 3 (coded 2) is the most popular cluster and it covers a wide range of prices and number of reviews.\n",
    "\n",
    "#### For availability_365 and price, the second cluster (coded 1) is the most populated where most of the properties are about $2000 and below but are available randomly. \n",
    "\n",
    "#### For minimum_nights and price, the second cluster (coded 1) is again the most populated. Interesting to see a property that requires a minimum of 1400 nights for a price very close to zero. \n",
    "\n",
    "#### All three charts are not very conclusive. Further analysis is needed to establish the relationships of the variables. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58609457",
   "metadata": {},
   "source": [
    "# 9. Calculate descriptive statistics for clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "38d4c973",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_clean_2.loc[df_clean_2['clusters'] == 2, 'cluster'] = 'dark purple'\n",
    "df_clean_2.loc[df_clean_2['clusters'] == 1, 'cluster'] = 'purple'\n",
    "df_clean_2.loc[df_clean_2['clusters'] == 0, 'cluster'] = 'pink'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "67b51020",
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">total_reviews</th>\n",
       "      <th colspan=\"2\" halign=\"left\">availability_365</th>\n",
       "      <th colspan=\"2\" halign=\"left\">min_nights</th>\n",
       "      <th colspan=\"2\" halign=\"left\">price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster</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>dark purple</th>\n",
       "      <td>39.062020</td>\n",
       "      <td>9.0</td>\n",
       "      <td>107.485185</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.492609</td>\n",
       "      <td>3.0</td>\n",
       "      <td>155.532225</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pink</th>\n",
       "      <td>24.318573</td>\n",
       "      <td>7.0</td>\n",
       "      <td>91.541996</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.530183</td>\n",
       "      <td>3.0</td>\n",
       "      <td>141.917552</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purple</th>\n",
       "      <td>7.948357</td>\n",
       "      <td>2.0</td>\n",
       "      <td>138.836572</td>\n",
       "      <td>89.0</td>\n",
       "      <td>7.111844</td>\n",
       "      <td>2.0</td>\n",
       "      <td>160.993463</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            total_reviews        availability_365        min_nights         \\\n",
       "                     mean median             mean median       mean median   \n",
       "cluster                                                                      \n",
       "dark purple     39.062020    9.0       107.485185   10.0   7.492609    3.0   \n",
       "pink            24.318573    7.0        91.541996   11.0   6.530183    3.0   \n",
       "purple           7.948357    2.0       138.836572   89.0   7.111844    2.0   \n",
       "\n",
       "                  price         \n",
       "                   mean median  \n",
       "cluster                         \n",
       "dark purple  155.532225  117.0  \n",
       "pink         141.917552  100.0  \n",
       "purple       160.993463  109.0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean_2.groupby('cluster').agg({'total_reviews':['mean', 'median'], \n",
    "                         'availability_365':['mean', 'median'], \n",
    "                         'min_nights':['mean', 'median'],\n",
    "                          'price':['mean', 'median']})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5614a6e1",
   "metadata": {},
   "source": [
    "# 10. Findings\n",
    "\n",
    "#### Total Reviews - Dark purple cluster have the highest average number of reviews even if the average price is a bit high.\n",
    "\n",
    "#### Availability_365 - Pink cluster is the least available, therefore has very high demand. No surprises there as this cluster has the lowest average price.\n",
    "\n",
    "#### Minimum nights - All three clusters get rented 7 times on average even if they have very similar pricing.\n",
    "\n",
    "#### Price - The rental prices are generally very similar but upon inspection, the most expensive got the least number reviews as maybe fewer people can afford this place."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e84ada7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}